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0.779500 2 0.181052 0.882005 2 0.513039 0.078496 3 0.059265 0.847502 2 0.229107 0.796278 2 0.252028 0.015057 3 0.272083 0.109695 3 0.113048 0.225295 2 0.002748 0.054859 2 0.966657 0.623956 1 0.481529 0.714891 2 0.533624 0.184655 3 0.340450 0.678241 2 0.678868 0.933981 2 0.224212 0.575659 2 0.365764 0.838320 2 0.046409 0.952145 2 0.885603 0.050040 3 0.204321 0.178640 3 0.214929 0.111583 3 0.866825 0.041936 3 0.141517 0.241508 2 0.343087 0.071504 3 0.197780 0.579119 2 0.531928 0.335066 3 0.508347 0.237184 3 0.297650 0.143133 3 0.158764 0.839194 2 0.900954 0.894171 1 0.340880 0.423021 2 0.994320 0.730051 1 0.246198 0.841788 2 0.159181 0.085072 3 0.833487 0.140857 3 0.084832 0.945870 2 0.266456 0.533448 2 0.661671 0.304256 3 0.029532 0.123370 2 0.957822 0.006465 3 0.716311 0.159242 3 0.070107 0.872042 2 0.930525 0.468580 1 0.567654 0.480870 1 0.031192 0.570962 2 0.887131 0.580477 1 0.932709 0.456686 1 0.878830 0.336310 1 0.381040 0.930767 2 0.356826 0.089090 3 0.065847 0.942649 2 0.166622 0.365546 2 0.295664 0.270744 3 0.970529 0.347028 1 0.412285 0.019873 3 0.763192 0.085669 3 0.507926 0.471411 3 0.493883 0.486650 3 0.643953 0.143492 3 0.093343 0.479718 2 0.665789 0.355967 1 0.514073 0.181543 3 0.830763 0.926176 2 0.005180 0.015960 2 0.983205 0.762129 1 0.995417 0.291004 1 0.545963 0.375055 3 0.468343 0.224408 3 0.475020 0.649704 2 MSVMpack1.2/Makefile.osx0000644000175000017500000002251011761337256014205 0ustar lauerlauer# Version VERSION=1.2 # Detect SSE instruction set (SSE2, SSE3 or SSE4.1...) #SSE=`TESTSSE42=\`sysctl -a hw | grep sse4_2 | wc -l;\`; if [ $$TESTSSE42 -eq 0 ]; then (TESTSSE41=\`sysctl -a hw | grep sse4_1 | wc -l;\`; if [ $$TESTSSE41 -eq 0 ]; then (TESTSSE3=\`sysctl -a hw | grep sse3 | wc -l;\` ; if [ $$TESTSSE3 -eq 0 ]; then echo -msse2; else echo -msse3; fi); else echo -msse4.1; fi); else echo -msse4.2; fi` # MSVMpack cannot use SSE instructions on Mac OSX yet SSE=-msse2 # Default flags for GCC: use level 3 optimization DEBUG=-O3 CFLAGS=$(DEBUG) $(SSE) -mfpmath=sse -DVERSION=$(VERSION) # Flags required by lp_solve LPSOLVELINK= -ldl # Default directories for MSVMpack include and lib INCLUDE= -Iinclude/ -Ilp_solve_5.5/ LIB= -Llib/ CURRENT_DIR= `pwd` # Directories for web server WEBDIR=webpages/ WEBSRC=src/web/ DIR=\"`pwd`\" MONGOOSEDIR=mongoose/ # Default rule: use 'make' to build all welcome: @echo @echo "... Building MSVMpack $(VERSION) ..." @echo "(parallel implementation for Mac OSX)" @echo # @echo "Using SSE flag '$(SSE)' for vectorized kernels... " # @echo "(use e.g. 'make SSE=-msse2' to change that)" # @echo @make -f Makefile.osx all @echo @echo "**************************************" @echo "MSVMpack build completed successfully." @echo "Static library 'libmsvm.a' stored in $(CURRENT_DIR)/lib/." @echo "You can now use 'trainmsvm' and 'predmsvm' command-line tools." @echo "**************************************" @echo @echo "... Now building MSVMpack Server ..." @echo @make -f Makefile.osx server all: lib/libmsvm.a trainmsvm predmsvm # Debugging rules: use 'make debug' to build for debugging purposes debug: make -f Makefile.osx DEBUG="-g -O0" SSE="-msse2" # or 'make profile' for performance analysis profile: make -f Makefile.osx DEBUG="-g -pg -O3" # Use 'make clean' to remove all compiled objects, library and executables clean: rm -f lib/*.a src/*.o trainmsvm predmsvm # Use 'make install' for a system-wide install of the command-line tools install: trainmsvm predmsvm cp trainmsvm /usr/local/bin/ cp predmsvm /usr/local/bin/ cp tools/plotlog /usr/local/bin/ cp tools/plotlog_msvm2 /usr/local/bin/ # Use 'make uninstall' to remove the system-wide install # (does not remove the MSVMpack directory) uninstall: rm -f /usr/local/bin/trainmsvm /usr/local/bin/predmsvm /usr/local/bin/plotlog # Use 'make package' to generate a clean archive MSVMpack.tar.gz # (this requires 'lp_solve_5.5.0.15_source.tar.gz' in the parent directory) # Note that this will REMOVE ALL MODEL FILES from the MSVMpack directory package: clean rm -f *.model *.tmp *.outputs *.log .*.log .*.gnuplot *.ps *.out *~ doc/*~ doc/*.outputs doc/*.model doc/*.src/*~ include/*~ Save_alpha/* -rm -rf lp_solve_5.5 -rm -f doc/example -rm -rf package tar -zxvf ../lp_solve_5.5.0.15_source.tar.gz cd .. ; tar -zcvf MSVMpack$(VERSION).tar.gz MSVMpack$(VERSION) --exclude-vcs mkdir package mv ../MSVMpack$(VERSION).tar.gz package/ #### Rules for internal use ### # Make the MSVMpack static library 'libmsvm.a' lib/libmsvm.a: src/libMSVM.o src/kernel.o src/libtrainMSVM.o src/libevalMSVM.o src/libtrainMSVM_WW.o src/libevalMSVM_WW.o src/libtrainMSVM_CS.o src/libevalMSVM_CS.o src/libtrainMSVM_LLW.o src/libevalMSVM_LLW.o src/libtrainMSVM_2.o src/libtrainMSVM_2fw.o src/libevalMSVM_2.o src/biblio.o src/algebra.o lib/liblpsolve55.a @cd lib ; ar x liblpsolve55.a @ar rcs lib/libmsvm.a src/libMSVM.o src/kernel.o src/libtrainMSVM.o src/libtrainMSVM_WW.o src/libevalMSVM.o src/libevalMSVM_WW.o src/libtrainMSVM_CS.o src/libevalMSVM_CS.o src/libtrainMSVM_LLW.o src/libevalMSVM_LLW.o src/libtrainMSVM_2.o src/libtrainMSVM_2fw.o src/libevalMSVM_2.o src/biblio.o src/algebra.o lib/*.o @rm lib/*.o @echo libmsvm.a... # Get either osx32/liblpsolve55.a or osx64/liblpsolve55.a lib/liblpsolve55.a: lp_solve_5.5/lpsolve55/bin/liblpsolve55.a -@cp lp_solve_5.5/lpsolve55/bin/liblpsolve55.a lib/ # This builds the lp_solve API lp_solve_5.5/lpsolve55/bin/liblpsolve55.a: @echo "Building lp_solve library (this may take some time)..." @cd lp_solve_5.5/lpsolve55 ; sh ccc.osx -@cp lp_solve_5.5/lpsolve55/bin/osx32/liblpsolve55.a lp_solve_5.5/lpsolve55/bin/ 2>/dev/null -@cp lp_solve_5.5/lpsolve55/bin/osx64/liblpsolve55.a lp_solve_5.5/lpsolve55/bin/ 2>/dev/null # Make object files src/libMSVM.o: src/libMSVM.c src/custom_kernels.c @gcc -o src/libMSVM.o -c src/libMSVM.c $(CFLAGS) $(INCLUDE) @echo libMSVM.o... src/kernel.o: src/kernel.c src/custom_kernels.c @gcc -o src/kernel.o -c src/kernel.c $(CFLAGS) $(INCLUDE) @echo kernel.o... src/libtrainMSVM.o: src/libtrainMSVM.c @gcc -o src/libtrainMSVM.o -c src/libtrainMSVM.c $(CFLAGS) $(INCLUDE) @echo libtrainMSVM.o... src/libevalMSVM.o: src/libevalMSVM.c @gcc -c src/libevalMSVM.c -o src/libevalMSVM.o $(CFLAGS) $(INCLUDE) @echo libevalMSVM.o... src/libtrainMSVM_2.o: src/libtrainMSVM_2.c @gcc -o src/libtrainMSVM_2.o -c src/libtrainMSVM_2.c $(CFLAGS) $(INCLUDE) @echo libtrainMSVM_2.o... src/libtrainMSVM_2fw.o: src/libtrainMSVM_2fw.c @gcc -o src/libtrainMSVM_2fw.o -c src/libtrainMSVM_2fw.c $(CFLAGS) $(INCLUDE) @echo libtrainMSVM_2fw.o... src/libevalMSVM_2.o: src/libevalMSVM_2.c @gcc -c src/libevalMSVM_2.c -o src/libevalMSVM_2.o $(CFLAGS) $(INCLUDE) @echo libevalMSVM_2.o... src/libtrainMSVM_WW.o: src/libtrainMSVM_WW.c @gcc -o src/libtrainMSVM_WW.o -c src/libtrainMSVM_WW.c $(CFLAGS) $(INCLUDE) @echo libtrainMSVM_WW.o... src/libevalMSVM_WW.o: src/libevalMSVM_WW.c @gcc -c src/libevalMSVM_WW.c -o src/libevalMSVM_WW.o $(CFLAGS) $(INCLUDE) @echo libevalMSVM_WW.o... src/libtrainMSVM_CS.o: src/libtrainMSVM_CS.c @gcc -o src/libtrainMSVM_CS.o -c src/libtrainMSVM_CS.c $(CFLAGS) $(INCLUDE) @echo libtrainMSVM_CS.o... src/libevalMSVM_CS.o: src/libevalMSVM_CS.c @gcc -c src/libevalMSVM_CS.c -o src/libevalMSVM_CS.o $(CFLAGS) $(INCLUDE) @echo libevalMSVM_CS.o... src/libtrainMSVM_LLW.o: src/libtrainMSVM_LLW.c @gcc -o src/libtrainMSVM_LLW.o -c src/libtrainMSVM_LLW.c $(CFLAGS) $(INCLUDE) @echo libtrainMSVM_LLW.o... src/libevalMSVM_LLW.o: src/libevalMSVM_LLW.c @gcc -c src/libevalMSVM_LLW.c -o src/libevalMSVM_LLW.o $(CFLAGS) $(INCLUDE) @echo libevalMSVM_LLW.o... src/algebra.o: src/algebra.c @gcc -c src/algebra.c -o src/algebra.o $(CFLAGS) $(INCLUDE) @echo algebra.o... src/biblio.o: src/biblio.c @gcc -c src/biblio.c -o src/biblio.o $(CFLAGS) $(INCLUDE) @echo biblio.o... # Make command-line tools # # use '-Llib/ -lmsvm' to link with the MSVMpack library # trainmsvm: src/trainMSVM.c lib/libmsvm.a @gcc -o trainmsvm src/trainMSVM.c $(CFLAGS) $(INCLUDE) $(LIB) -lmsvm -lm $(LPSOLVELINK) @echo trainmsvm... predmsvm: src/predMSVM.c lib/libmsvm.a @gcc -o predmsvm src/predMSVM.c $(CFLAGS) $(INCLUDE) $(LIB) -lmsvm -lm @echo predmsvm... # Make MSVMpack web server # server: $(WEBDIR)trainmsvm $(WEBDIR)predmsvm $(WEBDIR)home.cgi $(WEBDIR)Server.cgi $(WEBDIR)upload.cgi $(WEBDIR)upload_libsvm.cgi $(WEBDIR)upload_raw.cgi $(WEBDIR)admin/admin.cgi $(WEBDIR)admin/delete.cgi $(WEBDIR)convert datadir msvmserver @echo @echo "**************************************" @echo MSVMpack Server build completed. @echo @echo "Use 'msvmserver start' in " @echo $(DIR) @echo to start the server. @echo "**************************************" @echo # Copy MSVMpack binaries to server $(WEBDIR)trainmsvm: trainmsvm @echo "trainmsvm..." @cp trainmsvm $(WEBDIR) $(WEBDIR)predmsvm: predmsvm @echo "predmsvm..." @cp predmsvm $(WEBDIR) # Web CGI pages $(WEBDIR)home.cgi: $(WEBSRC)home.c @echo home.cgi... @gcc -O3 -o $(WEBDIR)home.cgi $(WEBSRC)home.c -DVERSION=$(VERSION) $(WEBDIR)Server.cgi: $(WEBSRC)Server.c @echo Server.cgi... @gcc -O3 -o $(WEBDIR)Server.cgi $(WEBSRC)Server.c -DVERSION=$(VERSION) $(WEBDIR)upload.cgi: $(WEBSRC)upload.c @echo upload.cgi... @gcc -O3 -o $(WEBDIR)upload.cgi $(WEBSRC)upload.c $(WEBDIR)upload_libsvm.cgi: $(WEBSRC)upload_libsvm.c @echo upload_libsvm.cgi... @gcc -O3 -o $(WEBDIR)upload_libsvm.cgi $(WEBSRC)upload_libsvm.c $(WEBDIR)upload_raw.cgi: $(WEBSRC)upload_raw.c @echo upload_raw.cgi... @gcc -O3 -o $(WEBDIR)upload_raw.cgi $(WEBSRC)upload_raw.c $(WEBDIR)admin/admin.cgi: $(WEBSRC)admin.c @echo admin.cgi... @gcc -O3 -o $(WEBDIR)admin/admin.cgi $(WEBSRC)admin.c -DVERSION=$(VERSION) $(WEBDIR)admin/delete.cgi: $(WEBSRC)delete.c @echo delete.cgi... @gcc -o $(WEBDIR)admin/delete.cgi $(WEBSRC)delete.c $(WEBDIR)convert: $(WEBSRC)convert.c @echo convert... @gcc -o $(WEBDIR)convert $(WEBSRC)convert.c datadir: @echo "Data/..." @cp Data/* $(WEBDIR)Data/ # Server executable $(MONGOOSEDIR)mongoose: @echo "Building mongoose http server..." @cd $(MONGOOSEDIR); make CFLAGS=" -W -std=c99 -pedantic -O2" mac msvmserver: $(WEBSRC)msvmserver.c $(MONGOOSEDIR)mongoose @echo msvmserver... @gcc -O3 -o msvmserver $(WEBSRC)msvmserver.c -DDIR=$(DIR) # Clean web server server-clean: -./msvmserver stop rm -f $(WEBDIR)home.cgi $(WEBDIR)Server.cgi $(WEBDIR)upload.cgi $(WEBDIR)upload_libsvm.cgi $(WEBDIR)upload_raw.cgi $(WEBDIR)admin/admin.cgi $(WEBDIR)admin/delete.cgi $(WEBDIR)trainmsvm $(WEBDIR)predmsvm $(WEBDIR)convert msvmserver # Package web server server-package: server-clean -rm -f $(WEBDIR)training.out -rm -f $(WEBDIR)Data/* -rm -f $(WEBDIR)Models/* -rm -f $(WEBDIR)admin/server.conf -rm -f $(WEBDIR)*~ -rm -f $(WEBDIR)admin/*~ # reset admin passwd mongoose -A $(WEBDIR)admin/.htpasswd "mydomain.com" "admin" "admin" -rm -rf mongoose tar -zxvf ../mongoose-3.0.tgz MSVMpack1.2/lp_solve_5.5/0000775000175000017500000000000010763107543014144 5ustar lauerlauerMSVMpack1.2/lp_solve_5.5/lp_rlp.y0000664000175000017500000005204111141374251015621 0ustar lauerlauer/* ========================================================================= */ /* NAME : lp_rlp.y */ /* ========================================================================= */ /* made reentrant with help of http://www.usualcoding.eu/post/2007/09/03/Building-a-reentrant-parser-in-C-with-Flex/Bison */ /* Note that a minimum version of bison is needed to be able to compile this. Older version don't know the reentrant code. Version 1.35 is not enough. v1.875 could be ok. Tested with v2.3 */ %pure-parser %parse-param {parse_parm *parm} %parse-param {void *scanner} %lex-param {yyscan_t *scanner} %token VAR CONS INTCONS VARIABLECOLON INF SEC_INT SEC_BIN SEC_SEC SEC_SOS SOSDESCR SEC_FREE TOK_SIGN AR_M_OP RE_OPEQ RE_OPLE RE_OPGE END_C COMMA COLON MINIMISE MAXIMISE UNDEFINED %{ #include #include #include #define scanner yyscanner #define PARM yyget_extra(yyscanner) #define YYSTYPE int #define YY_EXTRA_TYPE parse_parm * #define YY_FATAL_ERROR(msg) lex_fatal_error(PARM, yyscanner, msg) #undef YY_INPUT #define YY_INPUT(buf,result,max_size) result = lp_input((void *) PARM, buf, max_size); #define yyerror read_error #include "lpkit.h" #include "yacc_read.h" typedef struct parse_vars_s { read_modeldata_func *lp_input; void *userhandle; char HadVar, HadVar0, HadVar1, HadVar2, HasAR_M_OP, HadConstraint, Had_lineair_sum, Had_lineair_sum0, do_add_row, HadSign, OP, Sign, isign, isign0, make_neg; char state, state0; char Within_int_decl; /* TRUE when we are within an char declaration */ char Within_bin_decl; /* TRUE when we are within an bin declaration */ char Within_sec_decl; /* TRUE when we are within a sec declaration */ char Within_sos_decl; /* TRUE when we are within a sos declaration */ char Within_sos_decl1; char Within_free_decl; /* TRUE when we are within a free declaration */ short SOStype, SOStype0; /* SOS type */ int SOSNr; int SOSweight; /* SOS weight */ char *Last_var, *Last_var0; REAL f, f0, f1; } parse_vars; #ifdef FORTIFY # include "lp_fortify.h" #endif /* let's please C++ users */ #ifdef __cplusplus extern "C" { #endif #if defined MSDOS || defined __MSDOS__ || defined WINDOWS || defined _WINDOWS || defined WIN32 || defined _WIN32 #define YY_NO_UNISTD_H static int isatty(int f) { return(FALSE); } #if !defined _STDLIB_H # define _STDLIB_H #endif #endif static int __WINAPI lp_input_yyin(void *fpin, char *buf, int max_size) { int result; result = fread( (char*)buf, sizeof(char), max_size, (FILE *)fpin); return(result); } static int __WINAPI lp_input(void *vpp, char *buf, int max_size) { parse_parm *pp = (parse_parm *) vpp; parse_vars *pv = (parse_vars *) pp->parse_vars; int result; result = pv->lp_input(pv->userhandle, buf, max_size); if (result < 0) lex_fatal_error(pp, pp->scanner, "read() in flex scanner failed"); return(result); } #ifdef __cplusplus }; #endif #include "lp_rlp.h" #undef yylval %} %start inputfile %% EMPTY: /* EMPTY */ ; inputfile : { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->isign = 0; pv->make_neg = 0; pv->Sign = 0; pv->HadConstraint = FALSE; pv->HadVar = pv->HadVar0 = FALSE; } objective_function constraints int_bin_sec_sos_free_declarations ; /* start objective_function */ /* objective_function: MAXIMISE real_of | MINIMISE real_of | real_of; real_of: lineair_sum END_C; lineair_sum: EMPTY | x_lineair_sum; */ objective_function: MAXIMISE real_of { set_obj_dir(PARM, TRUE); } | MINIMISE real_of { set_obj_dir(PARM, FALSE); } | real_of ; real_of: lineair_sum END_C { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; add_row(pp); pv->HadConstraint = FALSE; pv->HadVar = pv->HadVar0 = FALSE; pv->isign = 0; pv->make_neg = 0; } ; lineair_sum: EMPTY | x_lineair_sum ; /* end objective_function */ /* start constraints */ /* constraints: EMPTY | x_constraints; x_constraints: constraint | x_constraints constraint; constraint: real_constraint | VARIABLECOLON real_constraint; real_constraint: x_lineair_sum2 RE_OP x_lineair_sum3 optionalrange END_C; optionalrange: EMPTY | RE_OP cons_term RHS_STORE; RE_OP: RE_OPEQ | RE_OPLE | RE_OPGE; cons_term: x_SIGN REALCONS | INF; x_lineair_sum2: EMPTY | x_lineair_sum3; x_lineair_sum3: x_lineair_sum | INF RHS_STORE; x_lineair_sum: x_lineair_sum1; x_lineair_sum1: x_lineair_term | x_lineair_sum1 x_lineair_term; x_lineair_term: x_SIGN x_lineair_term1; x_lineair_term1: REALCONS | optional_AR_M_OP VAR; x_SIGN: EMPTY | TOK_SIGN; REALCONS: INTCONS | CONS; optional_AR_M_OP: EMPTY | AR_M_OP; */ constraints: EMPTY | x_constraints ; x_constraints : constraint | x_constraints constraint ; constraint : real_constraint | VARIABLECOLON { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if(!add_constraint_name(pp, pv->Last_var)) YYABORT; pv->HadConstraint = TRUE; } real_constraint ; real_constraint : x_lineair_sum2 { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->HadVar1 = pv->HadVar0; pv->HadVar0 = FALSE; } RE_OP { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if(!store_re_op(pp, pv->OP, (int) pv->HadConstraint, (int) pv->HadVar, (int) pv->Had_lineair_sum)) YYABORT; pv->make_neg = 1; pv->f1 = 0; } x_lineair_sum3 { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->Had_lineair_sum0 = pv->Had_lineair_sum; pv->Had_lineair_sum = TRUE; pv->HadVar2 = pv->HadVar0; pv->HadVar0 = FALSE; pv->do_add_row = FALSE; if(pv->HadConstraint && !pv->HadVar ) { /* it is a range */ /* already handled */ } else if(!pv->HadConstraint && pv->HadVar) { /* it is a bound */ if(!store_bounds(pp, TRUE)) YYABORT; } else { /* it is a row restriction */ if(pv->HadConstraint && pv->HadVar) store_re_op(pp, '\0', (int) pv->HadConstraint, (int) pv->HadVar, (int) pv->Had_lineair_sum); /* makes sure that data stored in temporary buffers is treated correctly */ pv->do_add_row = TRUE; } } optionalrange END_C { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if((!pv->HadVar) && (!pv->HadConstraint)) { yyerror(pp, pp->scanner, "parse error"); YYABORT; } if(pv->do_add_row) add_row(pp); pv->HadConstraint = FALSE; pv->HadVar = pv->HadVar0 = FALSE; pv->isign = 0; pv->make_neg = 0; null_tmp_store(pp, TRUE); } ; optionalrange: EMPTY { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if((!pv->HadVar1) && (pv->Had_lineair_sum0)) if(!negate_constraint(pp)) YYABORT; } | RE_OP { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->make_neg = 0; pv->isign = 0; if(pv->HadConstraint) pv->HadVar = pv->Had_lineair_sum = FALSE; pv->HadVar0 = FALSE; if(!store_re_op(pp, (char) ((pv->OP == '<') ? '>' : (pv->OP == '>') ? '<' : pv->OP), (int) pv->HadConstraint, (int) pv->HadVar, (int) pv->Had_lineair_sum)) YYABORT; } cons_term { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->f -= pv->f1; } RHS_STORE { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if((pv->HadVar1) || (!pv->HadVar2) || (pv->HadVar0)) { yyerror(pp, pp->scanner, "parse error"); YYABORT; } if(pv->HadConstraint && !pv->HadVar ) { /* it is a range */ /* already handled */ if(!negate_constraint(pp)) YYABORT; } else if(!pv->HadConstraint && pv->HadVar) { /* it is a bound */ if(!store_bounds(pp, TRUE)) YYABORT; } } ; x_lineair_sum2: EMPTY { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; /* to allow a range */ /* constraint: < max */ if(!pv->HadConstraint) { yyerror(pp, pp->scanner, "parse error"); YYABORT; } pv->Had_lineair_sum = FALSE; } | x_lineair_sum3 { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->Had_lineair_sum = TRUE; } ; x_lineair_sum3 : x_lineair_sum | INF { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->isign = pv->Sign; } RHS_STORE ; x_lineair_sum: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->state = pv->state0 = 0; } x_lineair_sum1 { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if (pv->state == 1) { /* RHS_STORE */ if ( (pv->isign0 || !pv->make_neg) && !(pv->isign0 && !pv->make_neg)) /* but not both! */ pv->f0 = -pv->f0; if(pv->make_neg) pv->f1 += pv->f0; if(!rhs_store(pp, pv->f0, (int) pv->HadConstraint, (int) pv->HadVar, (int) pv->Had_lineair_sum)) YYABORT; } } ; x_lineair_sum1 : x_lineair_term | x_lineair_sum1 x_lineair_term ; x_lineair_term : x_SIGN x_lineair_term1 { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if ((pv->HadSign || pv->state == 1) && (pv->state0 == 1)) { /* RHS_STORE */ if ( (pv->isign0 || !pv->make_neg) && !(pv->isign0 && !pv->make_neg)) /* but not both! */ pv->f0 = -pv->f0; if(pv->make_neg) pv->f1 += pv->f0; if(!rhs_store(pp, pv->f0, (int) pv->HadConstraint, (int) pv->HadVar, (int) pv->Had_lineair_sum)) YYABORT; } if (pv->state == 1) { pv->f0 = pv->f; pv->isign0 = pv->isign; } if (pv->state == 2) { if((pv->HadSign) || (pv->state0 != 1)) { pv->isign0 = pv->isign; pv->f0 = 1.0; } if ( (pv->isign0 || pv->make_neg) && !(pv->isign0 && pv->make_neg)) /* but not both! */ pv->f0 = -pv->f0; if(!var_store(pp, pv->Last_var, pv->f0, (int) pv->HadConstraint, (int) pv->HadVar, (int) pv->Had_lineair_sum)) { yyerror(pp, pp->scanner, "var_store failed"); YYABORT; } pv->HadConstraint |= pv->HadVar; pv->HadVar = pv->HadVar0 = TRUE; } pv->state0 = pv->state; } ; x_lineair_term1 : REALCONS { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->state = 1; } | optional_AR_M_OP { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if ((pv->HasAR_M_OP) && (pv->state != 1)) { yyerror(pp, pp->scanner, "parse error"); YYABORT; } } VAR { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->state = 2; } ; RE_OP: RE_OPEQ | RE_OPLE | RE_OPGE ; cons_term: x_SIGN REALCONS | INF { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->isign = pv->Sign; } ; /* end constraints */ /* start common for objective & constraints */ REALCONS: INTCONS | CONS ; x_SIGN: EMPTY { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->isign = 0; pv->HadSign = FALSE; } | TOK_SIGN { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->isign = pv->Sign; pv->HadSign = TRUE; } ; optional_AR_M_OP: EMPTY { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->HasAR_M_OP = FALSE; } | AR_M_OP { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->HasAR_M_OP = TRUE; } ; RHS_STORE: EMPTY { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if ( (pv->isign || !pv->make_neg) && !(pv->isign && !pv->make_neg)) /* but not both! */ pv->f = -pv->f; if(!rhs_store(pp, pv->f, (int) pv->HadConstraint, (int) pv->HadVar, (int) pv->Had_lineair_sum)) YYABORT; pv->isign = 0; } ; /* end common for objective & constraints */ /* start int_bin_sec_sos_free_declarations */ int_bin_sec_sos_free_declarations: EMPTY | real_int_bin_sec_sos_free_decls ; real_int_bin_sec_sos_free_decls: int_bin_sec_sos_free_declaration | real_int_bin_sec_sos_free_decls int_bin_sec_sos_free_declaration ; SEC_INT_BIN_SEC_SOS_FREE: SEC_INT | SEC_BIN | SEC_SEC | SEC_SOS | SEC_FREE ; int_bin_sec_sos_free_declaration: SEC_INT_BIN_SEC_SOS_FREE { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->Within_sos_decl1 = pv->Within_sos_decl; } x_int_bin_sec_sos_free_declaration ; xx_int_bin_sec_sos_free_declaration: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if((!pv->Within_int_decl) && (!pv->Within_sec_decl) && (!pv->Within_sos_decl1) && (!pv->Within_free_decl)) { yyerror(pp, pp->scanner, "parse error"); YYABORT; } pv->SOStype = pv->SOStype0; check_int_sec_sos_free_decl(pp, (int) pv->Within_int_decl, (int) pv->Within_sec_decl, (int) (pv->Within_sos_decl1 = (pv->Within_sos_decl1 ? 1 : 0)), (int) pv->Within_free_decl); } optionalsos vars optionalsostype END_C { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if((pv->Within_sos_decl1) && (pv->SOStype == 0)) { yyerror(pp, pp->scanner, "Unsupported SOS type (0)"); YYABORT; } } ; x_int_bin_sec_sos_free_declaration: xx_int_bin_sec_sos_free_declaration | x_int_bin_sec_sos_free_declaration xx_int_bin_sec_sos_free_declaration ; optionalsos: EMPTY | SOSDESCR { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; FREE(pv->Last_var0); pv->Last_var0 = strdup(pv->Last_var); } sosdescr ; optionalsostype: EMPTY { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if(pv->Within_sos_decl1) { set_sos_type(pp, pv->SOStype); set_sos_weight(pp, (double) pv->SOSweight, 1); } } | RE_OPLE INTCONS { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if((pv->Within_sos_decl1) && (!pv->SOStype)) { set_sos_type(pp, pv->SOStype = (short) (pv->f + .1)); } else { yyerror(pp, pp->scanner, "SOS type not expected"); YYABORT; } } optionalSOSweight ; optionalSOSweight:EMPTY { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; set_sos_weight(pp, (double) pv->SOSweight, 1); } | COLON INTCONS { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; set_sos_weight(pp, pv->f, 1); } ; vars: EMPTY | x_vars ; x_vars : onevarwithoptionalweight | x_vars optionalcomma onevarwithoptionalweight ; optionalcomma: EMPTY | COMMA ; variable: EMPTY { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if(pv->Within_sos_decl1 == 1) { char buf[16]; pv->SOSweight++; sprintf(buf, "SOS%d", pv->SOSweight); storevarandweight(pp, buf); check_int_sec_sos_free_decl(pp, (int) pv->Within_int_decl, (int) pv->Within_sec_decl, 2, (int) pv->Within_free_decl); pv->Within_sos_decl1 = 2; pv->SOSNr = 0; } storevarandweight(pp, pv->Last_var); if(pv->Within_sos_decl1 == 2) { pv->SOSNr++; set_sos_weight(pp, (double) pv->SOSNr, 2); } } ; variablecolon: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if(!pv->Within_sos_decl1) { yyerror(pp, pp->scanner, "parse error"); YYABORT; } if(pv->Within_sos_decl1 == 1) { FREE(pv->Last_var0); pv->Last_var0 = strdup(pv->Last_var); } if(pv->Within_sos_decl1 == 2) { storevarandweight(pp, pv->Last_var); pv->SOSNr++; set_sos_weight(pp, (double) pv->SOSNr, 2); } } ; sosweight: EMPTY { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if(pv->Within_sos_decl1 == 1) { char buf[16]; pv->SOSweight++; sprintf(buf, "SOS%d", pv->SOSweight); storevarandweight(pp, buf); check_int_sec_sos_free_decl(pp, (int) pv->Within_int_decl, (int) pv->Within_sec_decl, 2, (int) pv->Within_free_decl); pv->Within_sos_decl1 = 2; pv->SOSNr = 0; storevarandweight(pp, pv->Last_var0); pv->SOSNr++; } set_sos_weight(pp, pv->f, 2); } ; sosdescr: EMPTY { /* SOS name */ parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if(pv->Within_sos_decl1 == 1) { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; storevarandweight(pp, pv->Last_var0); set_sos_type(pp, pv->SOStype); check_int_sec_sos_free_decl(pp, (int) pv->Within_int_decl, (int) pv->Within_sec_decl, 2, (int) pv->Within_free_decl); pv->Within_sos_decl1 = 2; pv->SOSNr = 0; pv->SOSweight++; } } ; onevarwithoptionalweight: VAR variable | VARIABLECOLON variablecolon INTCONSorVARIABLE ; INTCONSorVARIABLE:REALCONS /* INTCONS */ sosweight | sosdescr x_onevarwithoptionalweight ; x_onevarwithoptionalweight: VAR variable | VARIABLECOLON variablecolon REALCONS /* INTCONS */ sosweight ; /* end int_bin_sec_sos_free_declarations */ %% static void yy_delete_allocated_memory(parse_parm *pp) { parse_vars *pv = (parse_vars *) pp->parse_vars; /* free memory allocated by flex. Otherwise some memory is not freed. This is a bit tricky. There is not much documentation about this, but a lot of reports of memory that keeps allocated */ /* If you get errors on this function call, just comment it. This will only result in some memory that is not being freed. */ # if defined YY_CURRENT_BUFFER /* flex defines the macro YY_CURRENT_BUFFER, so you should only get here if lp_rlp.h is generated by flex */ /* lex doesn't define this macro and thus should not come here, but lex doesn't has this memory leak also ...*/ # if 0 /* older versions of flex */ yy_delete_buffer(YY_CURRENT_BUFFER); /* comment this line if you have problems with it */ yy_init = 1; /* make sure that the next time memory is allocated again */ yy_start = 0; # else /* As of version 2.5.9 Flex */ yylex_destroy(pp->scanner); /* comment this line if you have problems with it */ # endif # endif FREE(pv->Last_var); FREE(pv->Last_var0); } static int parse(parse_parm *pp) { return(yyparse(pp, pp->scanner)); } lprec *read_lp1(lprec *lp, void *userhandle, read_modeldata_func read_modeldata, int verbose, char *lp_name) { parse_vars *pv; lprec *lp1 = NULL; CALLOC(pv, 1, parse_vars); if (pv != NULL) { parse_parm pp; memset(&pp, 0, sizeof(pp)); pp.parse_vars = (void *) pv; yylex_init(&pp.scanner); yyset_extra(&pp, pp.scanner); yyset_in((FILE *) userhandle, pp.scanner); yyset_out(NULL, pp.scanner); pv->lp_input = read_modeldata; pv->userhandle = userhandle; lp1 = yacc_read(lp, verbose, lp_name, parse, &pp, yy_delete_allocated_memory); FREE(pv); } return(lp1); } lprec * __WINAPI read_lp(FILE *filename, int verbose, char *lp_name) { return(read_lp1(NULL, filename, lp_input_yyin, verbose, lp_name)); } lprec * __WINAPI read_lpex(void *userhandle, read_modeldata_func read_modeldata, int verbose, char *lp_name) { return(read_lp1(NULL, userhandle, read_modeldata, verbose, lp_name)); } lprec *read_LP1(lprec *lp, char *filename, int verbose, char *lp_name) { FILE *fpin; if((fpin = fopen(filename, "r")) != NULL) { lp = read_lp1(lp, fpin, lp_input_yyin, verbose, lp_name); fclose(fpin); } else lp = NULL; return(lp); } lprec * __WINAPI read_LP(char *filename, int verbose, char *lp_name) { return(read_LP1(NULL, filename, verbose, lp_name)); } MYBOOL __WINAPI LP_readhandle(lprec **lp, FILE *filename, int verbose, char *lp_name) { if(lp != NULL) *lp = read_lp1(*lp, filename, lp_input_yyin, verbose, lp_name); return((lp != NULL) && (*lp != NULL)); } MSVMpack1.2/lp_solve_5.5/lp_wlp.h0000664000175000017500000000044611141374256015614 0ustar lauerlauer#ifndef HEADER_lp_lp #define HEADER_lp_lp #include "lp_types.h" #ifdef __cplusplus extern "C" { #endif /* Put function headers here */ MYBOOL LP_writefile(lprec *lp, char *filename); MYBOOL LP_writehandle(lprec *lp, FILE *output); #ifdef __cplusplus } #endif #endif /* HEADER_lp_lp */ MSVMpack1.2/lp_solve_5.5/lp_wlp.c0000664000175000017500000003020711254506611015602 0ustar lauerlauer #include #include #include #include "commonlib.h" #include "lp_lib.h" #include "lp_scale.h" #include "lp_utils.h" #include "lp_report.h" #include "lp_wlp.h" #ifdef FORTIFY # include "lp_fortify.h" #endif /* Define buffer-size controled function mapping */ # if defined _MSC_VER # define vsnprintf _vsnprintf # endif /* ------------------------------------------------------------------------- */ /* Input and output of lp format model files for lp_solve */ /* ------------------------------------------------------------------------- */ static int write_data(void *userhandle, write_modeldata_func write_modeldata, char *format, ...) { char buff[DEF_STRBUFSIZE+1]; va_list ap; int n; va_start(ap, format); vsnprintf(buff, DEF_STRBUFSIZE, format, ap); va_end(ap); n = write_modeldata(userhandle, buff); return(n); } STATIC void write_lpcomment(void *userhandle, write_modeldata_func write_modeldata, char *string, MYBOOL newlinebefore) { write_data(userhandle, write_modeldata, "%s/* %s */\n", (newlinebefore) ? "\n" : "", string); } STATIC int write_lprow(lprec *lp, int rowno, void *userhandle, write_modeldata_func write_modeldata, int maxlen, int *idx, REAL *val) { int i, j, nchars, elements; REAL a; MYBOOL first = TRUE; char buf[50]; elements = get_rowex(lp, rowno, val, idx); if(write_modeldata != NULL) { nchars = 0; for(i = 0; i < elements; i++) { j = idx[i]; if(is_splitvar(lp, j)) continue; a = val[i]; if(!first) nchars += write_data(userhandle, write_modeldata, " "); else first = FALSE; sprintf(buf, "%+.12g", (double)a); if(strcmp(buf, "-1") == 0) nchars += write_data(userhandle, write_modeldata, "-"); else if(strcmp(buf, "+1") == 0) nchars += write_data(userhandle, write_modeldata, "+"); else nchars += write_data(userhandle, write_modeldata, "%s ", buf); nchars += write_data(userhandle, write_modeldata, "%s", get_col_name(lp, j)); /* Check if we should add a linefeed */ if((maxlen > 0) && (nchars >= maxlen) && (i < elements-1)) { write_data(userhandle, write_modeldata, "%s", "\n"); nchars = 0; } } } return(elements); } #if !defined LP_MAXLINELEN # define LP_MAXLINELEN 100 #endif MYBOOL __WINAPI write_lpex(lprec *lp, void *userhandle, write_modeldata_func write_modeldata) { int i, j, b, nrows = lp->rows, ncols = lp->columns, nchars, maxlen = LP_MAXLINELEN, *idx; MYBOOL ok; REAL a, *val; char *ptr; if(!mat_validate(lp->matA)) { report(lp, IMPORTANT, "LP_writefile: Could not validate the data matrix.\n"); return(FALSE); } /* Write name of model */ ptr = get_lp_name(lp); if(ptr != NULL) { if(*ptr) write_lpcomment(userhandle, write_modeldata, ptr, FALSE); else ptr = NULL; } /* Write the objective function */ write_lpcomment(userhandle, write_modeldata, "Objective function", (MYBOOL) (ptr != NULL)); if(is_maxim(lp)) write_data(userhandle, write_modeldata, "max: "); else write_data(userhandle, write_modeldata, "min: "); allocREAL(lp, &val, 1 + lp->columns, TRUE); allocINT(lp, &idx, 1 + lp->columns, TRUE); write_lprow(lp, 0, userhandle, write_modeldata, maxlen, idx, val); a = get_rh(lp, 0); if(a != 0) write_data(userhandle, write_modeldata, " %+.12g", a); write_data(userhandle, write_modeldata, ";\n"); /* Write constraints */ if(nrows > 0) write_lpcomment(userhandle, write_modeldata, "Constraints", TRUE); for(j = 1; j <= nrows; j++) { if(((lp->names_used) && (lp->row_name[j] != NULL)) || (write_lprow(lp, j, userhandle, NULL, maxlen, idx, val) == 1)) ptr = get_row_name(lp, j); else ptr = NULL; if((ptr != NULL) && (*ptr)) write_data(userhandle, write_modeldata, "%s: ", ptr); #ifndef SingleBoundedRowInLP /* Write the ranged part of the constraint, if specified */ if ((lp->orig_upbo[j]) && (lp->orig_upbo[j] < lp->infinite)) { if(my_chsign(is_chsign(lp, j), lp->orig_rhs[j]) == -lp->infinite) write_data(userhandle, write_modeldata, "-Inf %s ", (is_chsign(lp, j)) ? ">=" : "<="); else if(my_chsign(is_chsign(lp, j), lp->orig_rhs[j]) == lp->infinite) write_data(userhandle, write_modeldata, "+Inf %s ", (is_chsign(lp, j)) ? ">=" : "<="); else write_data(userhandle, write_modeldata, "%+.12g %s ", (lp->orig_upbo[j]-lp->orig_rhs[j]) * (is_chsign(lp, j) ? 1.0 : -1.0) / (lp->scaling_used ? lp->scalars[j] : 1.0), (is_chsign(lp, j)) ? ">=" : "<="); } #endif if((!write_lprow(lp, j, userhandle, write_modeldata, maxlen, idx, val)) && (ncols >= 1)) write_data(userhandle, write_modeldata, "0 %s", get_col_name(lp, 1)); if(lp->orig_upbo[j] == 0) write_data(userhandle, write_modeldata, " ="); else if(is_chsign(lp, j)) write_data(userhandle, write_modeldata, " >="); else write_data(userhandle, write_modeldata, " <="); if(fabs(get_rh(lp, j) + lp->infinite) < 1) write_data(userhandle, write_modeldata, " -Inf;\n"); else if(fabs(get_rh(lp, j) - lp->infinite) < 1) write_data(userhandle, write_modeldata, " +Inf;\n"); else write_data(userhandle, write_modeldata, " %.12g;\n", get_rh(lp, j)); #ifdef SingleBoundedRowInLP /* Write the ranged part of the constraint, if specified */ if ((lp->orig_upbo[j]) && (lp->orig_upbo[j] < lp->infinite)) { if(((lp->names_used) && (lp->row_name[j] != NULL)) || (write_lprow(lp, j, userhandle, NULL, maxlen, idx, val) == 1)) ptr = get_row_name(lp, j); else ptr = NULL; if((ptr != NULL) && (*ptr)) write_data(userhandle, write_modeldata, "%s: ", ptr); if((!write_lprow(lp, j, userhandle, write_modeldata, maxlen, idx, val)) && (get_Ncolumns(lp) >= 1)) write_data(userhandle, write_modeldata, "0 %s", get_col_name(lp, 1)); write_data(userhandle, write_modeldata, " %s %g;\n", (is_chsign(lp, j)) ? "<=" : ">=", (lp->orig_upbo[j]-lp->orig_rhs[j]) * (is_chsign(lp, j) ? 1.0 : -1.0) / (lp->scaling_used ? lp->scalars[j] : 1.0)); } #endif } /* Write bounds on variables */ ok = FALSE; for(i = nrows + 1; i <= lp->sum; i++) if(!is_splitvar(lp, i - nrows)) { if(lp->orig_lowbo[i] == lp->orig_upbo[i]) { if(!ok) { write_lpcomment(userhandle, write_modeldata, "Variable bounds", TRUE); ok = TRUE; } write_data(userhandle, write_modeldata, "%s = %.12g;\n", get_col_name(lp, i - nrows), get_upbo(lp, i - nrows)); } else { #ifndef SingleBoundedRowInLP if((lp->orig_lowbo[i] != 0) && (lp->orig_upbo[i] < lp->infinite)) { if(!ok) { write_lpcomment(userhandle, write_modeldata, "Variable bounds", TRUE); ok = TRUE; } if(lp->orig_lowbo[i] == -lp->infinite) write_data(userhandle, write_modeldata, "-Inf"); else write_data(userhandle, write_modeldata, "%.12g", get_lowbo(lp, i - nrows)); write_data(userhandle, write_modeldata, " <= %s <= ", get_col_name(lp, i - nrows)); if(lp->orig_lowbo[i] == lp->infinite) write_data(userhandle, write_modeldata, "+Inf"); else write_data(userhandle, write_modeldata, "%.12g", get_upbo(lp, i - nrows)); write_data(userhandle, write_modeldata, ";\n"); } else #endif { if(lp->orig_lowbo[i] != 0) { if(!ok) { write_lpcomment(userhandle, write_modeldata, "Variable bounds", TRUE); ok = TRUE; } if(lp->orig_lowbo[i] == -lp->infinite) write_data(userhandle, write_modeldata, "%s >= -Inf;\n", get_col_name(lp, i - nrows)); else if(lp->orig_lowbo[i] == lp->infinite) write_data(userhandle, write_modeldata, "%s >= +Inf;\n", get_col_name(lp, i - nrows)); else write_data(userhandle, write_modeldata, "%s >= %.12g;\n", get_col_name(lp, i - nrows), get_lowbo(lp, i - nrows)); } if(lp->orig_upbo[i] != lp->infinite) { if(!ok) { write_lpcomment(userhandle, write_modeldata, "Variable bounds", TRUE); ok = TRUE; } write_data(userhandle, write_modeldata, "%s <= %.12g;\n", get_col_name(lp, i - nrows), get_upbo(lp, i - nrows)); } } } } /* Write optional integer section */ if(lp->int_vars > 0) { write_lpcomment(userhandle, write_modeldata, "Integer definitions", TRUE); i = 1; while((i <= ncols) && !is_int(lp, i)) i++; if(i <= ncols) { nchars = write_data(userhandle, write_modeldata, "int %s", get_col_name(lp, i)); i++; for(; i <= ncols; i++) if((!is_splitvar(lp, i)) && (is_int(lp, i))) { if((maxlen!= 0) && (nchars > maxlen)) { write_data(userhandle, write_modeldata, "%s", "\n"); nchars = 0; } write_data(userhandle, write_modeldata, ",%s", get_col_name(lp, i)); } write_data(userhandle, write_modeldata, ";\n"); } } /* Write optional SEC section */ if(lp->sc_vars > 0) { write_lpcomment(userhandle, write_modeldata, "Semi-continuous variables", TRUE); i = 1; while((i <= ncols) && !is_semicont(lp, i)) i++; if(i <= ncols) { nchars = write_data(userhandle, write_modeldata, "sec %s", get_col_name(lp, i)); i++; for(; i <= ncols; i++) if((!is_splitvar(lp, i)) && (is_semicont(lp, i))) { if((maxlen != 0) && (nchars > maxlen)) { write_data(userhandle, write_modeldata, "%s", "\n"); nchars = 0; } nchars += write_data(userhandle, write_modeldata, ",%s", get_col_name(lp, i)); } write_data(userhandle, write_modeldata, ";\n"); } } /* Write optional SOS section */ if(SOS_count(lp) > 0) { SOSgroup *SOS = lp->SOS; write_lpcomment(userhandle, write_modeldata, "SOS definitions", TRUE); write_data(userhandle, write_modeldata, "SOS\n"); for(b = 0, i = 0; i < SOS->sos_count; b = SOS->sos_list[i]->priority, i++) { nchars = write_data(userhandle, write_modeldata, "%s: ", (SOS->sos_list[i]->name == NULL) || (*SOS->sos_list[i]->name==0) ? "SOS" : SOS->sos_list[i]->name); /* formatnumber12((double) lp->sos_list[i]->priority) */ for(a = 0.0, j = 1; j <= SOS->sos_list[i]->size; a = SOS->sos_list[i]->weights[j], j++) { if((maxlen != 0) && (nchars > maxlen)) { write_data(userhandle, write_modeldata, "%s", "\n"); nchars = 0; } if(SOS->sos_list[i]->weights[j] == ++a) nchars += write_data(userhandle, write_modeldata, "%s%s", (j > 1) ? "," : "", get_col_name(lp, SOS->sos_list[i]->members[j])); else nchars += write_data(userhandle, write_modeldata, "%s%s:%.12g", (j > 1) ? "," : "", get_col_name(lp, SOS->sos_list[i]->members[j]), SOS->sos_list[i]->weights[j]); } if(SOS->sos_list[i]->priority == ++b) nchars += write_data(userhandle, write_modeldata, " <= %d;\n", SOS->sos_list[i]->type); else nchars += write_data(userhandle, write_modeldata, " <= %d:%d;\n", SOS->sos_list[i]->type, SOS->sos_list[i]->priority); } } FREE(val); FREE(idx); ok = TRUE; return(ok); } static int __WINAPI write_lpdata(void *userhandle, char *buf) { return(fprintf((FILE *) userhandle, "%s", buf)); } MYBOOL LP_writefile(lprec *lp, char *filename) { FILE *output = stdout; MYBOOL ok; if (filename != NULL) { ok = (MYBOOL) ((output = fopen(filename, "w")) != NULL); if(!ok) return(ok); } else output = lp->outstream; ok = write_lpex(lp, (void *) output, write_lpdata); if (filename != NULL) fclose(output); return(ok); } MYBOOL LP_writehandle(lprec *lp, FILE *output) { MYBOOL ok; if (output != NULL) set_outputstream(lp, output); output = lp->outstream; ok = write_lpex(lp, (void *) output, write_lpdata); return(ok); } MSVMpack1.2/lp_solve_5.5/fortify.h0000664000175000017500000003027511141374241015776 0ustar lauerlauer#ifndef __FORTIFY_H__ #define __FORTIFY_H__ /* * FILE: * fortify.h * * DESCRIPTION: * Header file for fortify.c - A fortified shell for malloc, realloc, * calloc, strdup, getcwd, tempnam & free * * WRITTEN: * spb 29/4/94 * * VERSION: * 1.0 29/4/94 */ #include #include "declare.h" #if defined HP9000 || defined AViiON || defined ALPHA || defined SIGNED_UNKNOWN # define signed #endif #ifdef __cplusplus extern "C" { #endif #ifdef FORTIFY typedef void (*OutputFuncPtr) __OF((char *)); extern char *_Fortify_file; extern int _Fortify_line; #define Fortify_FILE(file) _Fortify_file=file #define Fortify_LINE(line) _Fortify_line=line #define _Fortify_FILE (_Fortify_file==(char *) 0 ? __FILE__ : _Fortify_file) #define _Fortify_LINE (_Fortify_line==0 ? __LINE__ : _Fortify_line) void _Fortify_Init __OF((char *file, unsigned long line)); void *_Fortify_malloc __OF((size_t size, char *file, unsigned long line)); void *_Fortify_realloc __OF((void *ptr, size_t new_size, char *file, unsigned long line)); void *_Fortify_calloc __OF((size_t nitems, size_t size, char *file, unsigned long line)); char *_Fortify_strdup __OF((char *str, char *file, unsigned long line)); void *_Fortify_memcpy __OF((void *to, void *from, size_t size, char *file, unsigned long line)); void *_Fortify_memmove __OF((void *to, void *from, size_t size, char *file, unsigned long line)); void *_Fortify_memccpy __OF((void *to, void *from, int c, size_t size, char *file, unsigned long line)); void *_Fortify_memset __OF((void *buffer, int c, size_t size, char *file, unsigned long line)); void *_Fortify_memchr __OF((void *buffer, int c, size_t size, char *file, unsigned long line)); int _Fortify_memcmp __OF((void *buffer1, void *buffer2, size_t size, char *file, unsigned long line)); int _Fortify_memicmp __OF((void *buffer1, void *buffer2, size_t size, char *file, unsigned long line)); char *_Fortify_strchr __OF((char *buffer, int c, char *file, unsigned long line)); char *_Fortify_strrchr __OF((char *buffer, int c, char *file, unsigned long line)); char *_Fortify_strlwr __OF((char *buffer, char *file, unsigned long line)); char *_Fortify_strupr __OF((char *buffer, char *file, unsigned long line)); char *_Fortify_strrev __OF((char *buffer, char *file, unsigned long line)); char *_Fortify_strset __OF((char *buffer, int c, char *file, unsigned long line)); char *_Fortify_strnset __OF((char *buffer, int c, size_t size, char *file, unsigned long line)); char *_Fortify_strstr __OF((char *to, char *from, char *file, unsigned long line)); char *_Fortify_strcpy __OF((char *to, char *from, char *file, unsigned long line)); char *_Fortify_strncpy __OF((char *to, char *from, size_t size, char *file, unsigned long line)); int _Fortify_strcmp __OF((char *buffer1, char *buffer2, char *file, unsigned long line)); double _Fortify_strtod __OF((char *buffer1, char **buffer2, char *file, unsigned long line)); long _Fortify_strtol __OF((char *buffer1, char **buffer2, int n, char *file, unsigned long line)); int _Fortify_atoi __OF((char *buffer1, char *file, unsigned long line)); long _Fortify_atol __OF((char *buffer1, char *file, unsigned long line)); double _Fortify_atof __OF((char *buffer1, char *file, unsigned long line)); unsigned long _Fortify_strtoul __OF((char *buffer1, char **buffer2, int n, char *file, unsigned long line)); size_t _Fortify_strcspn __OF((char *buffer1, char *buffer2, char *file, unsigned long line)); int _Fortify_strcoll __OF((char *buffer1, char *buffer2, char *file, unsigned long line)); int _Fortify_strcmpi __OF((char *buffer1, char *buffer2, char *file, unsigned long line)); int _Fortify_strncmp __OF((char *buffer1, char *buffer2, size_t size, char *file, unsigned long line)); int _Fortify_strnicmp __OF((char *buffer1, char *buffer2, size_t size, char *file, unsigned long line)); char *_Fortify_strcat __OF((char *buffer1, char *buffer2, char *file, unsigned long line)); char *_Fortify_strpbrk __OF((char *buffer1, char *buffer2, char *file, unsigned long line)); size_t _Fortify_strlen __OF((char *buffer, char *file, unsigned long line)); char *_Fortify_getcwd __OF((char *buf, int size, char *file, unsigned long line)); char *_Fortify_tempnam __OF((char *dir, char *pfx, char *file, unsigned long line)); void _Fortify_free __OF((void *uptr, char *file, unsigned long line)); int _Fortify_OutputAllMemory __OF((char *file, unsigned long line)); int _Fortify_CheckAllMemory __OF((char *file, unsigned long line)); int _Fortify_CheckPointer __OF((void *uptr, char *file, unsigned long line)); int _Fortify_Disable __OF((char *file, unsigned long line, int how)); int _Fortify_SetMallocFailRate __OF((int Percent)); int _Fortify_EnterScope __OF((char *file, unsigned long line)); int _Fortify_LeaveScope __OF((char *file, unsigned long line)); int _Fortify_DumpAllMemory __OF((int scope, char *file, unsigned long line)); typedef void (*Fortify_OutputFuncPtr) __OF((/* const */ char *)); Fortify_OutputFuncPtr _Fortify_SetOutputFunc __OF((Fortify_OutputFuncPtr Output)); #endif /* FORTIFY */ #ifdef __cplusplus } #endif #ifndef __FORTIFY_C__ /* Only define the macros if we're NOT in fortify.c */ #ifdef FORTIFY /* Add file and line information to the fortify calls */ #if defined malloc # undef malloc #endif #if defined realloc # undef realloc #endif #if defined calloc # undef calloc #endif #if defined strdup # undef strdup #endif #if defined memcpy # undef memcpy #endif #if defined memmove # undef memmove #endif #if defined memccpy # undef memccpy #endif #if defined memset # undef memset #endif #if defined memchr # undef memchr #endif #if defined memcmp # undef memcmp #endif #if defined memicmp # undef memicmp #endif #if defined strcoll # undef strcoll #endif #if defined strcspn # undef strcspn #endif #if defined strcmp # undef strcmp #endif #if defined strcmpi # undef strcmpi #endif #if defined stricmp # undef stricmp #endif #if defined strncmp # undef strncmp #endif #if defined strnicmp # undef strnicmp #endif #if defined strlwr # undef strlwr #endif #if defined strupr # undef strupr #endif #if defined strrev # undef strrev #endif #if defined strchr # undef strchr #endif #if defined strrchr # undef strrchr #endif #if defined strcat # undef strcat #endif #if defined strpbrk # undef strpbrk #endif #if defined strcpy # undef strcpy #endif #if defined atoi # undef atoi #endif #if defined atol # undef atol #endif #if defined atof # undef atof #endif #if defined strtol # undef strtol #endif #if defined strtoul # undef strtoul #endif #if defined strtod # undef strtod #endif #if defined strstr # undef strstr #endif #if defined strncpy # undef strncpy #endif #if defined strset # undef strset #endif #if defined strnset # undef strnset #endif #if defined strlen # undef strlen #endif #if defined getcwd # undef getcwd #endif #if defined tempnam # undef tempnam #endif #if defined free # undef free #endif #define malloc(size) _Fortify_malloc(size, _Fortify_FILE, _Fortify_LINE) #define realloc(ptr,new_size) _Fortify_realloc(ptr, new_size, _Fortify_FILE, _Fortify_LINE) #define calloc(num,size) _Fortify_calloc(num, size, _Fortify_FILE, _Fortify_LINE) #define strdup(str) _Fortify_strdup(str, _Fortify_FILE, _Fortify_LINE) #define memcpy(to,from,size) _Fortify_memcpy((void *)(to),(void *)(from),size, _Fortify_FILE, _Fortify_LINE) #define memmove(to,from,size) _Fortify_memmove((void *)(to),(void *)(from),size, _Fortify_FILE, _Fortify_LINE) #define memccpy(to,from,c,size) _Fortify_memccpy((void *)(to),(void *)(from),c,size, _Fortify_FILE, _Fortify_LINE) #define memset(buffer,c,size) _Fortify_memset(buffer,c,size, _Fortify_FILE, _Fortify_LINE) #define memchr(buffer,c,size) _Fortify_memchr(buffer,c,size, _Fortify_FILE, _Fortify_LINE) #define memcmp(buffer1,buffer2,size) _Fortify_memcmp((void *)buffer1,(void *)buffer2,size, _Fortify_FILE, _Fortify_LINE) #define memicmp(buffer1,buffer2,size) _Fortify_memicmp((void *)buffer1,(void *)buffer2,size, _Fortify_FILE, _Fortify_LINE) #define strlwr(buffer) _Fortify_strlwr(buffer, _Fortify_FILE, _Fortify_LINE) #define strupr(buffer) _Fortify_strupr(buffer, _Fortify_FILE, _Fortify_LINE) #define strrev(buffer) _Fortify_strrev(buffer, _Fortify_FILE, _Fortify_LINE) #define strchr(buffer,c) _Fortify_strchr(buffer,c, _Fortify_FILE, _Fortify_LINE) #define strrchr(buffer,c) _Fortify_strrchr(buffer,c, _Fortify_FILE, _Fortify_LINE) #define strset(buffer,c) _Fortify_strset(buffer,c, _Fortify_FILE, _Fortify_LINE) #define strnset(buffer,c) _Fortify_strnset(buffer,c, _Fortify_FILE, _Fortify_LINE) #define strstr(buffer1,buffer2) _Fortify_strstr(buffer1,buffer2, _Fortify_FILE, _Fortify_LINE) #define atoi(buffer) _Fortify_atoi(buffer, _Fortify_FILE, _Fortify_LINE) #define atol(buffer) _Fortify_atol(buffer, _Fortify_FILE, _Fortify_LINE) #define atof(buffer) _Fortify_atof(buffer, _Fortify_FILE, _Fortify_LINE) #define strtol(buffer1,buffer2,n) _Fortify_strtol(buffer1,buffer2,n, _Fortify_FILE, _Fortify_LINE) #define strtoul(buffer1,buffer2,n) _Fortify_strtoul(buffer1,buffer2,n, _Fortify_FILE, _Fortify_LINE) #define strtod(buffer1,buffer2) _Fortify_strtod(buffer1,buffer2, _Fortify_FILE, _Fortify_LINE) #define strcpy(to,from) _Fortify_strcpy((char *)(to),(char *)(from), _Fortify_FILE, _Fortify_LINE) #define strncpy(to,from,size) _Fortify_strncpy((char *)(to),(char *)(from),size, _Fortify_FILE, _Fortify_LINE) #define strcoll(buffer1,buffer2) _Fortify_strcoll((char *)(buffer1),(char *)(buffer2), _Fortify_FILE, _Fortify_LINE) #define strcspn(buffer1,buffer2) _Fortify_strcspn((char*)(buffer1),(char *)(buffer2), _Fortify_FILE, _Fortify_LINE) #define strcmp(buffer1,buffer2) _Fortify_strcmp((char *)(buffer1),(char *)(buffer2), _Fortify_FILE, _Fortify_LINE) #define strcmpi(buffer1,buffer2) _Fortify_strcmpi((char *)(buffer1),(char *)(buffer2), _Fortify_FILE, _Fortify_LINE) #define stricmp(buffer1,buffer2) _Fortify_strcmpi((char *)(buffer1),(char *)(buffer2), _Fortify_FILE, _Fortify_LINE) #define strncmp(buffer1,buffer2,size) _Fortify_strncmp((char *)(buffer1),(char *)(buffer2),size, _Fortify_FILE, _Fortify_LINE) #define strnicmp(buffer1,buffer2,size) _Fortify_strnicmp((char *)(buffer1),(char *)(buffer2),size, _Fortify_FILE, _Fortify_LINE) #define strcat(buffer1,buffer2) _Fortify_strcat((char *)(buffer1),(char *)(buffer2), _Fortify_FILE, _Fortify_LINE) #define strpbrk(buffer1,buffer2) _Fortify_strpbrk((char *)(buffer1),(char *)(buffer2), _Fortify_FILE, _Fortify_LINE) #define strlen(buffer) _Fortify_strlen((char*)(buffer), _Fortify_FILE, _Fortify_LINE) #define getcwd(buf,size) _Fortify_getcwd(buf, size, _Fortify_FILE, _Fortify_LINE) #define tempnam(dir,pfx) _Fortify_tempnam(dir, pfx, _Fortify_FILE, _Fortify_LINE) #define free(ptr) _Fortify_free(ptr, _Fortify_FILE, _Fortify_LINE) #define Fortify_Init() _Fortify_Init(_Fortify_FILE, _Fortify_LINE) #define Fortify_OutputAllMemory() _Fortify_OutputAllMemory(_Fortify_FILE, _Fortify_LINE) #define Fortify_CheckAllMemory() _Fortify_CheckAllMemory(_Fortify_FILE, _Fortify_LINE) #define Fortify_CheckPointer(ptr) _Fortify_CheckPointer(ptr, _Fortify_FILE, _Fortify_LINE) #define Fortify_Disable(how) _Fortify_Disable(_Fortify_FILE, _Fortify_LINE,how) #define Fortify_EnterScope() _Fortify_EnterScope(_Fortify_FILE, _Fortify_LINE) #define Fortify_LeaveScope() _Fortify_LeaveScope(_Fortify_FILE, _Fortify_LINE) #define Fortify_DumpAllMemory(s) _Fortify_DumpAllMemory(s,_Fortify_FILE, _Fortify_LINE) #else /* FORTIFY Define the special fortify functions away to nothing */ #define Fortify_FILE(file) #define Fortify_LINE(line) #define Fortify_Init() #define Fortify_OutputAllMemory() 0 #define Fortify_CheckAllMemory() 0 #define Fortify_CheckPointer(ptr) 1 #define Fortify_Disable(how) 1 #define Fortify_SetOutputFunc() 0 #define Fortify_SetMallocFailRate(p) 0 #define Fortify_EnterScope() 0 #define Fortify_LeaveScope() 0 #define Fortify_DumpAllMemory(s) 0 #endif /* FORTIFY */ #endif /* __FORTIFY_C__ */ #endif /* __FORTIFY_H__ */ MSVMpack1.2/lp_solve_5.5/lp_params.c0000664000175000017500000005572111250514763016276 0ustar lauerlauer#include #include #include #include #include "commonlib.h" #include "lp_lib.h" #include "lp_report.h" #include "ini.h" typedef int (__WINAPI fn_int_get_function)(lprec *lp); typedef long (__WINAPI fn_long_get_function)(lprec *lp); typedef MYBOOL (__WINAPI fn_MYBOOL_get_function)(lprec *lp); typedef REAL (__WINAPI fn_REAL_get_function)(lprec *lp); typedef void (__WINAPI fn_int_set_function)(lprec *lp, int value); typedef void (__WINAPI fn_long_set_function)(lprec *lp, long value); typedef void (__WINAPI fn_MYBOOL_set_function)(lprec *lp, MYBOOL value); typedef void (__WINAPI fn_REAL_set_function)(lprec *lp, REAL value); #define intfunction 1 #define longfunction 2 #define MYBOOLfunction 3 #define REALfunction 4 #define setvalues(values, basemask) values, sizeof(values) / sizeof(*values), basemask #define setNULLvalues NULL, 0, 0 #define setvalue(value) value, #value #define setintfunction(get_function, set_function) { get_function }, { set_function }, intfunction #define setlongfunction(get_function, set_function) { (fn_int_get_function *) get_function }, {(fn_int_set_function *) set_function }, longfunction #define setMYBOOLfunction(get_function, set_function) { (fn_int_get_function *) get_function }, { (fn_int_set_function *) set_function }, MYBOOLfunction #define setREALfunction(get_function, set_function) {(fn_int_get_function *) get_function }, { (fn_int_set_function *) set_function }, REALfunction #define WRITE_COMMENTED 0 #define WRITE_ACTIVE 1 struct _values { int value; char *svalue; }; struct _functions { char *par; /* name of parameter in ini file */ union { fn_int_get_function *int_get_function; /* set via setintfunction */ fn_long_get_function *long_get_function; /* set via setlongfunction */ fn_MYBOOL_get_function *MYBOOL_get_function; /* set via setMYBOOLfunction */ fn_REAL_get_function *REAL_get_function; /* set via setREALfunction */ } get_function; union { fn_int_set_function *int_set_function; /* set via setintfunction */ fn_long_set_function *long_set_function; /* set via setlongfunction */ fn_MYBOOL_set_function *MYBOOL_set_function; /* set via setMYBOOLfunction */ fn_REAL_set_function *REAL_set_function; /* set via setREALfunction */ } set_function; int type; /* set via set*function */ struct _values *values; /* set via setvalues to a structure of _values */ int elements; /* or via setNULLvalues if the value is shown as is */ unsigned int basemask; int mask; /* WRITE_ACTIVE or WRITE_COMMENTED */ }; static struct _values anti_degen[] = { { setvalue(ANTIDEGEN_NONE) }, { setvalue(ANTIDEGEN_FIXEDVARS) }, { setvalue(ANTIDEGEN_COLUMNCHECK) }, { setvalue(ANTIDEGEN_STALLING) }, { setvalue(ANTIDEGEN_NUMFAILURE) }, { setvalue(ANTIDEGEN_LOSTFEAS) }, { setvalue(ANTIDEGEN_INFEASIBLE) }, { setvalue(ANTIDEGEN_DYNAMIC) }, { setvalue(ANTIDEGEN_DURINGBB) }, { setvalue(ANTIDEGEN_RHSPERTURB) }, { setvalue(ANTIDEGEN_BOUNDFLIP) }, }; static struct _values basiscrash[] = { { setvalue(CRASH_NONE) }, /* { setvalue(CRASH_NONBASICBOUNDS) }, */ /* not yet implemented */ { setvalue(CRASH_MOSTFEASIBLE) }, { setvalue(CRASH_LEASTDEGENERATE) }, }; static struct _values bb_floorfirst[] = { { setvalue(BRANCH_CEILING) }, { setvalue(BRANCH_FLOOR) }, { setvalue(BRANCH_AUTOMATIC) }, }; static struct _values bb_rule[] = { { setvalue(NODE_FIRSTSELECT) }, { setvalue(NODE_GAPSELECT) }, { setvalue(NODE_RANGESELECT) }, { setvalue(NODE_FRACTIONSELECT) }, { setvalue(NODE_PSEUDOCOSTSELECT) }, { setvalue(NODE_PSEUDONONINTSELECT) }, { setvalue(NODE_PSEUDORATIOSELECT) }, { setvalue(NODE_USERSELECT) }, { setvalue(NODE_WEIGHTREVERSEMODE) }, { setvalue(NODE_BRANCHREVERSEMODE) }, { setvalue(NODE_GREEDYMODE) }, { setvalue(NODE_PSEUDOCOSTMODE) }, { setvalue(NODE_DEPTHFIRSTMODE) }, { setvalue(NODE_RANDOMIZEMODE) }, { setvalue(NODE_GUBMODE) }, { setvalue(NODE_DYNAMICMODE) }, { setvalue(NODE_RESTARTMODE) }, { setvalue(NODE_BREADTHFIRSTMODE) }, { setvalue(NODE_AUTOORDER) }, { setvalue(NODE_RCOSTFIXING) }, { setvalue(NODE_STRONGINIT) }, }; static struct _values improve[] = { { setvalue(IMPROVE_NONE) }, { setvalue(IMPROVE_SOLUTION) }, { setvalue(IMPROVE_DUALFEAS) }, { setvalue(IMPROVE_THETAGAP) }, { setvalue(IMPROVE_BBSIMPLEX) }, }; static REAL __WINAPI get_mip_gap_abs(lprec *lp) { return(get_mip_gap(lp, TRUE)); } static REAL __WINAPI get_mip_gap_rel(lprec *lp) { return(get_mip_gap(lp, FALSE)); } static void __WINAPI set_mip_gap_abs(lprec *lp, REAL mip_gap) { set_mip_gap(lp, TRUE, mip_gap); } static void __WINAPI set_mip_gap_rel(lprec *lp, REAL mip_gap) { set_mip_gap(lp, FALSE, mip_gap); } static struct _values pivoting[] = { { setvalue(PRICER_FIRSTINDEX) }, { setvalue(PRICER_DANTZIG) }, { setvalue(PRICER_DEVEX) }, { setvalue(PRICER_STEEPESTEDGE) }, { setvalue(PRICE_PRIMALFALLBACK) }, { setvalue(PRICE_MULTIPLE) }, { setvalue(PRICE_PARTIAL) }, { setvalue(PRICE_ADAPTIVE) }, { setvalue(PRICE_RANDOMIZE) }, { setvalue(PRICE_AUTOPARTIAL) }, { setvalue(PRICE_LOOPLEFT) }, { setvalue(PRICE_LOOPALTERNATE) }, { setvalue(PRICE_HARRISTWOPASS) }, { setvalue(PRICE_TRUENORMINIT) }, }; static struct _values presolving[] = { { setvalue(PRESOLVE_NONE) }, { setvalue(PRESOLVE_ROWS) }, { setvalue(PRESOLVE_COLS) }, { setvalue(PRESOLVE_LINDEP) }, { setvalue(PRESOLVE_AGGREGATE) }, { setvalue(PRESOLVE_SPARSER) }, { setvalue(PRESOLVE_SOS) }, { setvalue(PRESOLVE_REDUCEMIP) }, { setvalue(PRESOLVE_KNAPSACK) }, { setvalue(PRESOLVE_ELIMEQ2) }, { setvalue(PRESOLVE_IMPLIEDFREE) }, { setvalue(PRESOLVE_REDUCEGCD) }, { setvalue(PRESOLVE_PROBEFIX) }, { setvalue(PRESOLVE_PROBEREDUCE) }, { setvalue(PRESOLVE_ROWDOMINATE) }, { setvalue(PRESOLVE_COLDOMINATE) }, { setvalue(PRESOLVE_MERGEROWS) }, { setvalue(PRESOLVE_IMPLIEDSLK) }, { setvalue(PRESOLVE_COLFIXDUAL) }, { setvalue(PRESOLVE_BOUNDS) }, { setvalue(PRESOLVE_DUALS) }, { setvalue(PRESOLVE_SENSDUALS) }, }; static char *STRLWR(char *str) { char *ptr; for(ptr = str; *ptr; ptr++) *ptr = (char) tolower((unsigned char) *ptr); return(str); } static char *STRUPR(char *str) { char *ptr; for(ptr = str; *ptr; ptr++) *ptr = (char) toupper((unsigned char) *ptr); return(str); } static void __WINAPI set_presolve1(lprec *lp, int do_presolve) { set_presolve(lp, do_presolve, get_presolveloops(lp)); } static void __WINAPI set_presolve2(lprec *lp, int maxloops) { set_presolve(lp, get_presolve(lp), maxloops); } static struct _values print_sol[] = { { FALSE, "0" }, { TRUE, "1" }, { setvalue(AUTOMATIC) }, }; static struct _values scaling[] = { { setvalue(SCALE_NONE) }, { setvalue(SCALE_EXTREME) }, { setvalue(SCALE_RANGE) }, { setvalue(SCALE_MEAN) }, { setvalue(SCALE_GEOMETRIC) }, { setvalue(SCALE_CURTISREID) }, { setvalue(SCALE_QUADRATIC) }, { setvalue(SCALE_LOGARITHMIC) }, { setvalue(SCALE_USERWEIGHT) }, { setvalue(SCALE_POWER2) }, { setvalue(SCALE_EQUILIBRATE) }, { setvalue(SCALE_INTEGERS) }, { setvalue(SCALE_DYNUPDATE) }, { setvalue(SCALE_ROWSONLY) }, { setvalue(SCALE_COLSONLY) }, }; static struct _values simplextype[] = { { setvalue(SIMPLEX_PRIMAL_PRIMAL) }, { setvalue(SIMPLEX_DUAL_PRIMAL) }, { setvalue(SIMPLEX_PRIMAL_DUAL) }, { setvalue(SIMPLEX_DUAL_DUAL) }, }; static struct _values verbose[] = { { setvalue(NEUTRAL) }, { setvalue(CRITICAL) }, { setvalue(SEVERE) }, { setvalue(IMPORTANT) }, { setvalue(NORMAL) }, { setvalue(DETAILED) }, { setvalue(FULL) }, }; static struct _functions functions[] = { /* solve options */ { "ANTI_DEGEN", setintfunction(get_anti_degen, set_anti_degen), setvalues(anti_degen, ~0), WRITE_ACTIVE }, { "BASISCRASH", setintfunction(get_basiscrash, set_basiscrash), setvalues(basiscrash, ~0), WRITE_ACTIVE }, { "IMPROVE", setintfunction(get_improve, set_improve), setvalues(improve, ~0), WRITE_ACTIVE }, { "MAXPIVOT", setintfunction(get_maxpivot, set_maxpivot), setNULLvalues, WRITE_ACTIVE }, { "NEGRANGE", setREALfunction(get_negrange, set_negrange), setNULLvalues, WRITE_ACTIVE }, { "PIVOTING", setintfunction(get_pivoting, set_pivoting), setvalues(pivoting, PRICER_LASTOPTION), WRITE_ACTIVE }, { "PRESOLVE", setintfunction(get_presolve, set_presolve1), setvalues(presolving, ~0), WRITE_ACTIVE }, { "PRESOLVELOOPS", setintfunction(get_presolveloops, set_presolve2), setNULLvalues, WRITE_ACTIVE }, { "SCALELIMIT", setREALfunction(get_scalelimit, set_scalelimit), setNULLvalues, WRITE_ACTIVE }, { "SCALING", setintfunction(get_scaling, set_scaling), setvalues(scaling, SCALE_CURTISREID), WRITE_ACTIVE }, { "SIMPLEXTYPE", setintfunction(get_simplextype, set_simplextype), setvalues(simplextype, ~0), WRITE_ACTIVE }, { "OBJ_IN_BASIS", setMYBOOLfunction(is_obj_in_basis, set_obj_in_basis), setNULLvalues, WRITE_COMMENTED }, /* B&B options */ { "BB_DEPTHLIMIT", setintfunction(get_bb_depthlimit, set_bb_depthlimit), setNULLvalues, WRITE_ACTIVE }, { "BB_FLOORFIRST", setintfunction(get_bb_floorfirst, set_bb_floorfirst), setvalues(bb_floorfirst, ~0), WRITE_ACTIVE }, { "BB_RULE", setintfunction(get_bb_rule, set_bb_rule), setvalues(bb_rule, NODE_STRATEGYMASK), WRITE_ACTIVE }, { "BREAK_AT_FIRST", setMYBOOLfunction(is_break_at_first, set_break_at_first), setNULLvalues, WRITE_COMMENTED }, { "BREAK_AT_VALUE", setREALfunction(get_break_at_value, set_break_at_value), setNULLvalues, WRITE_COMMENTED }, { "MIP_GAP_ABS", setREALfunction(get_mip_gap_abs, set_mip_gap_abs), setNULLvalues, WRITE_ACTIVE }, { "MIP_GAP_REL", setREALfunction(get_mip_gap_rel, set_mip_gap_rel), setNULLvalues, WRITE_ACTIVE }, { "EPSINT", setREALfunction(get_epsint, set_epsint), setNULLvalues, WRITE_ACTIVE }, /* tolerances, values */ { "EPSB", setREALfunction(get_epsb, set_epsb), setNULLvalues, WRITE_ACTIVE }, { "EPSD", setREALfunction(get_epsd, set_epsd), setNULLvalues, WRITE_ACTIVE }, { "EPSEL", setREALfunction(get_epsel, set_epsel), setNULLvalues, WRITE_ACTIVE }, { "EPSPERTURB", setREALfunction(get_epsperturb, set_epsperturb), setNULLvalues, WRITE_ACTIVE }, { "EPSPIVOT", setREALfunction(get_epspivot, set_epspivot), setNULLvalues, WRITE_ACTIVE }, { "INFINITE", setREALfunction(get_infinite, set_infinite), setNULLvalues, WRITE_ACTIVE }, /* read-only options */ { "DEBUG", setMYBOOLfunction(is_debug, set_debug), setNULLvalues, WRITE_COMMENTED }, { "OBJ_BOUND", setREALfunction(get_obj_bound, set_obj_bound), setNULLvalues, WRITE_COMMENTED }, { "PRINT_SOL", setintfunction(get_print_sol, set_print_sol), setvalues(print_sol, ~0), WRITE_COMMENTED }, { "TIMEOUT", setlongfunction(get_timeout, set_timeout), setNULLvalues, WRITE_COMMENTED }, { "TRACE", setMYBOOLfunction(is_trace, set_trace), setNULLvalues, WRITE_COMMENTED }, { "VERBOSE", setintfunction(get_verbose, set_verbose), setvalues(verbose, ~0), WRITE_COMMENTED }, }; static void write_params1(lprec *lp, FILE *fp, char *header, int newline) { int ret = 0, ret2, i, j, k, value, value2, elements, majorversion, minorversion, release, build; unsigned int basemask; REAL a = 0; char buf[4096], par[20]; ini_writeheader(fp, header, newline); lp_solve_version(&majorversion, &minorversion, &release, &build); sprintf(buf, "lp_solve version %d.%d settings\n", majorversion, minorversion); ini_writecomment(fp, buf); for(i = 0; i < sizeof(functions) / sizeof(*functions); i++) { switch(functions[i].type) { case intfunction: if(functions[i].get_function.int_get_function == NULL) continue; ret = functions[i].get_function.int_get_function(lp); break; case longfunction: if(functions[i].get_function.long_get_function == NULL) continue; ret = functions[i].get_function.long_get_function(lp); break; case MYBOOLfunction: if(functions[i].get_function.MYBOOL_get_function == NULL) continue; ret = (int) functions[i].get_function.MYBOOL_get_function(lp); break; case REALfunction: if(functions[i].get_function.REAL_get_function == NULL) continue; a = functions[i].get_function.REAL_get_function(lp); break; } buf[0] = 0; if(functions[i].values == NULL) { switch(functions[i].type) { case intfunction: case longfunction: case MYBOOLfunction: sprintf(buf, "%d", ret); break; case REALfunction: sprintf(buf, "%g", a); break; } } else { elements = functions[i].elements; basemask = functions[i].basemask; for(j = 0; j < elements; j++) { value = functions[i].values[j].value; ret2 = ret; if(((unsigned int) value) < basemask) ret2 &= basemask; if(value == 0) { if(ret2 == 0) { if(*buf) strcat(buf, " + "); strcat(buf, functions[i].values[j].svalue); } } else if((ret2 & value) == value) { for(k = 0; k < elements; k++) { value2 = functions[i].values[k].value; if((k != j) && (value2 > value) && ((value2 & value) == value) && ((ret2 & value2) == value2)) break; } if(k == elements) { if(*buf) strcat(buf, " + "); strcat(buf, functions[i].values[j].svalue); } } } } if(functions[i].mask & WRITE_ACTIVE) par[0] = 0; else strcpy(par, ";"); strcat(par, functions[i].par); ini_writedata(fp, STRLWR(par), buf); } } static void readoptions(char *options, char **header) { char *ptr1, *ptr2; if(options != NULL) { ptr1 = options; while(*ptr1) { ptr2 = strchr(ptr1, '-'); if(ptr2 == NULL) break; ptr2++; if(tolower((unsigned char) *ptr2) == 'h') { for(++ptr2; (*ptr2) && (isspace(*ptr2)); ptr2++); for(ptr1 = ptr2; (*ptr1) && (!isspace(*ptr1)); ptr1++); *header = (char *) calloc(1 + (int) (ptr1 - ptr2), 1); memcpy(*header, ptr2, (int) (ptr1 - ptr2)); } } } if(*header == NULL) *header = strdup("Default"); } MYBOOL __WINAPI write_params(lprec *lp, char *filename, char *options) { int k, ret, params_written; FILE *fp, *fp0; int state = 0, looping, newline; char buf[4096], *filename0, *ptr1, *ptr2, *header = NULL; readoptions(options, &header); k = (int) strlen(filename); filename0 = (char *) malloc(k + 1 + 1); strcpy(filename0, filename); ptr1 = strrchr(filename0, '.'); ptr2 = strrchr(filename0, '\\'); if((ptr1 == NULL) || ((ptr2 != NULL) && (ptr1 < ptr2))) ptr1 = filename0 + k; memmove(ptr1 + 1, ptr1, k + 1 - (int) (ptr1 - filename0)); ptr1[0] = '_'; if(rename(filename, filename0)) { switch(errno) { case ENOENT: /* File or path specified by oldname not found */ FREE(filename0); filename0 = NULL; break; case EACCES: /* File or directory specified by newname already exists or could not be created (invalid path); or oldname is a directory and newname specifies a different path. */ FREE(filename0); FREE(header); return(FALSE); break; } } if((fp = ini_create(filename)) == NULL) ret = FALSE; else { params_written = FALSE; newline = TRUE; if(filename0 != NULL) { fp0 = ini_open(filename0); if(fp0 == NULL) { rename(filename0, filename); FREE(filename0); FREE(header); return(FALSE); } looping = TRUE; while(looping) { switch(ini_readdata(fp0, buf, sizeof(buf), TRUE)) { case 0: /* End of file */ looping = FALSE; break; case 1: /* header */ ptr1 = strdup(buf); STRUPR(buf); ptr2 = strdup(header); STRUPR(ptr2); if(strcmp(buf, ptr2) == 0) { write_params1(lp, fp, ptr1, newline); params_written = TRUE; newline = TRUE; state = 1; } else { state = 0; ini_writeheader(fp, ptr1, newline); newline = TRUE; } FREE(ptr2); FREE(ptr1); break; case 2: /* data */ if(state == 0) { ini_writedata(fp, NULL, buf); newline = (*buf != 0); } break; } } ini_close(fp0); } if(!params_written) write_params1(lp, fp, header, newline); ini_close(fp); ret = TRUE; } if(filename0 != NULL) { remove(filename0); FREE(filename0); } FREE(header); return( (MYBOOL) ret ); } MYBOOL __WINAPI read_params(lprec *lp, char *filename, char *options) { int ret, looping, line; FILE *fp; hashtable *hashfunctions, *hashparameters; hashelem *hp; int i, j, elements, n, intvalue, state = 0; REAL REALvalue; char buf[4096], *header = NULL, *ptr, *ptr1, *ptr2; if((fp = ini_open(filename)) == NULL) ret = FALSE; else { /* create hashtable of all callable commands to find them quickly */ hashfunctions = create_hash_table(sizeof(functions) / sizeof(*functions), 0); for (n = 0, i = 0; i < (int) (sizeof(functions)/sizeof(*functions)); i++) { puthash(functions[i].par, i, NULL, hashfunctions); if(functions[i].values != NULL) n += functions[i].elements; } /* create hashtable of all arguments to find them quickly */ hashparameters = create_hash_table(n, 0); for (n = 0, i = 0; i < (int) (sizeof(functions)/sizeof(*functions)); i++) { if(functions[i].values != NULL) { elements = functions[i].elements; for(j = 0; j < elements; j++) if((strcmp(functions[i].values[j].svalue, "0") != 0) && (strcmp(functions[i].values[j].svalue, "1") != 0)) puthash(functions[i].values[j].svalue, j, NULL, hashparameters); } } readoptions(options, &header); STRUPR(header); ret = looping = TRUE; line = 0; while((ret) && (looping)) { line++; switch(ini_readdata(fp, buf, sizeof(buf), FALSE)) { case 0: /* End of file */ looping = FALSE; break; case 1: /* header */ switch(state) { case 0: STRUPR(buf); if(strcmp(buf, header) == 0) state = 1; break; case 1: looping = FALSE; break; } break; case 2: /* data */ if(state == 1) { for(ptr = buf; (*ptr) && (isspace(*ptr)); ptr++); } else ptr = NULL; if((ptr != NULL) && (*ptr)) { STRUPR(buf); ptr = strchr(buf, '='); if(ptr == NULL) { report(lp, IMPORTANT, "read_params: No equal sign on line %d\n", line); ret = FALSE; } else { *ptr = 0; for(ptr1 = buf; isspace(*ptr1); ptr1++); for(ptr2 = ptr - 1; (ptr2 >= ptr1) && (isspace(*ptr2)); ptr2--); if(ptr2 <= ptr1) { report(lp, IMPORTANT, "read_params: No parameter name before equal sign on line %d\n", line); ret = FALSE; } else { ptr2[1] = 0; hp = findhash(ptr1, hashfunctions); if(hp == NULL) { report(lp, IMPORTANT, "read_params: Unknown parameter name (%s) before equal sign on line %d\n", ptr1, line); ret = FALSE; } else { i = hp->index; ptr1 = ++ptr; intvalue = 0; REALvalue = 0; if(functions[i].values == NULL) { switch(functions[i].type) { case intfunction: case longfunction: case MYBOOLfunction: intvalue = strtol(ptr1, &ptr2, 10); while((*ptr2) && (isspace(*ptr2))) ptr2++; if(*ptr2) { report(lp, IMPORTANT, "read_params: Invalid integer value on line %d\n", line); ret = FALSE; } break; case REALfunction: REALvalue = strtod(ptr1, &ptr2); while((*ptr2) && (isspace(*ptr2))) ptr2++; if(*ptr2) { report(lp, IMPORTANT, "read_params: Invalid real value on line %d\n", line); ret = FALSE; } break; } } else { while(ret) { ptr = strchr(ptr1, '+'); if(ptr == NULL) ptr = ptr1 + strlen(ptr1); for(; isspace(*ptr1); ptr1++); for(ptr2 = ptr - 1; (ptr2 >= ptr1) && (isspace(*ptr2)); ptr2--); if(ptr2 <= ptr1) break; else { ptr2[1] = 0; hp = findhash(ptr1, hashparameters); if (hp == NULL) { report(lp, IMPORTANT, "read_params: Invalid parameter name (%s) on line %d\n", ptr1, line); ret = FALSE; } else { j = hp->index; if((j >= functions[i].elements) || (strcmp(functions[i].values[j].svalue, ptr1))) { report(lp, IMPORTANT, "read_params: Inappropriate parameter name (%s) on line %d\n", ptr1, line); ret = FALSE; } else { intvalue += functions[i].values[j].value; } } ptr1 = ptr + 1; } } } if(ret) { switch(functions[i].type) { case intfunction: functions[i].set_function.int_set_function(lp, intvalue); break; case longfunction: functions[i].set_function.long_set_function(lp, intvalue); break; case MYBOOLfunction: functions[i].set_function.MYBOOL_set_function(lp, (MYBOOL) intvalue); break; case REALfunction: functions[i].set_function.REAL_set_function(lp, REALvalue); break; } } } } } } break; } } FREE(header); free_hash_table(hashfunctions); free_hash_table(hashparameters); ini_close(fp); } return( (MYBOOL) ret ); } MSVMpack1.2/lp_solve_5.5/lp_rlp.bat0000775000175000017500000000047011041164230016112 0ustar lauerlauerrem flex -L -l lp_rlp.l flex -L lp_rlp.l rem sed -e "s/^#line.*//g" lex.yy.c >lp_rlp.h sed -e "s/yy/lp_yy/g" lex.yy.c | sed -e "s/^#line.*//g" >lp_rlp.h rem copy lex.yy.c lp_rlp.h del lex.yy.c bison --no-lines -y lp_rlp.y sed -e "s/yy/lp_yy/g" y.tab.c >lp_rlp.c rem copy y.tab.c lp_rlp.c del y.tab.c MSVMpack1.2/lp_solve_5.5/lp_simplex.c0000664000175000017500000022520011245563711016464 0ustar lauerlauer /* Core optimization drivers for lp_solve v5.0+ ---------------------------------------------------------------------------------- Author: Michel Berkelaar (to lp_solve v3.2), Kjell Eikland (v4.0 and forward) Contact: License terms: LGPL. Requires: lp_lib.h, lp_simplex.h, lp_presolve.h, lp_pricerPSE.h Release notes: v5.0.0 1 January 2004 New unit applying stacked basis and bounds storage. v5.0.1 31 January 2004 Moved B&B routines to separate file and implemented a new runsolver() general purpose call method. v5.0.2 1 May 2004 Changed routine names to be more intuitive. v5.1.0 10 January 2005 Created modular stalling/cycling functions. Rewrote dualloop() to optimize long dual and also streamlined primloop() correspondingly. v5.2.0 20 March 2005 Reimplemented primal phase 1 logic. Made multiple pricing finally work (primal simplex). ---------------------------------------------------------------------------------- */ #include #include "commonlib.h" #include "lp_lib.h" #include "lp_BFP.h" #include "lp_simplex.h" #include "lp_crash.h" #include "lp_presolve.h" #include "lp_price.h" #include "lp_pricePSE.h" #include "lp_report.h" #ifdef FORTIFY # include "lp_fortify.h" #endif STATIC void stallMonitor_update(lprec *lp, REAL newOF) { int newpos; OBJmonrec *monitor = lp->monitor; if(monitor->countstep < OBJ_STEPS) monitor->countstep++; else monitor->startstep = mod(monitor->startstep + 1, OBJ_STEPS); newpos = mod(monitor->startstep + monitor->countstep - 1, OBJ_STEPS); monitor->objstep[newpos] = newOF; monitor->idxstep[newpos] = monitor->Icount; monitor->currentstep = newpos; } STATIC MYBOOL stallMonitor_creepingObj(lprec *lp) { OBJmonrec *monitor = lp->monitor; if(monitor->countstep > 1) { REAL deltaOF = (monitor->objstep[monitor->currentstep] - monitor->objstep[monitor->startstep]) / monitor->countstep; deltaOF /= MAX(1, (monitor->idxstep[monitor->currentstep] - monitor->idxstep[monitor->startstep])); deltaOF = my_chsign(monitor->isdual, deltaOF); return( (MYBOOL) (deltaOF < monitor->epsvalue) ); } else return( FALSE ); } STATIC MYBOOL stallMonitor_shortSteps(lprec *lp) { OBJmonrec *monitor = lp->monitor; if(monitor->countstep == OBJ_STEPS) { REAL deltaOF = MAX(1, (monitor->idxstep[monitor->currentstep] - monitor->idxstep[monitor->startstep])) / monitor->countstep; deltaOF = pow(deltaOF*OBJ_STEPS, 0.66); return( (MYBOOL) (deltaOF > monitor->limitstall[TRUE]) ); } else return( FALSE ); } STATIC void stallMonitor_reset(lprec *lp) { OBJmonrec *monitor = lp->monitor; monitor->ruleswitches = 0; monitor->Ncycle = 0; monitor->Mcycle = 0; monitor->Icount = 0; monitor->startstep = 0; monitor->objstep[monitor->startstep] = lp->infinite; monitor->idxstep[monitor->startstep] = monitor->Icount; monitor->prevobj = 0; monitor->countstep = 1; } STATIC MYBOOL stallMonitor_create(lprec *lp, MYBOOL isdual, char *funcname) { OBJmonrec *monitor = NULL; if(lp->monitor != NULL) return( FALSE ); monitor = (OBJmonrec *) calloc(sizeof(*monitor), 1); if(monitor == NULL) return( FALSE ); monitor->lp = lp; strcpy(monitor->spxfunc, funcname); monitor->isdual = isdual; monitor->pivdynamic = is_piv_mode(lp, PRICE_ADAPTIVE); monitor->oldpivstrategy = lp->piv_strategy; monitor->oldpivrule = get_piv_rule(lp); if(MAX_STALLCOUNT <= 1) monitor->limitstall[FALSE] = 0; else monitor->limitstall[FALSE] = MAX(MAX_STALLCOUNT, (int) pow((REAL) (lp->rows+lp->columns)/2, 0.667)); #if 1 monitor->limitstall[FALSE] *= 2+2; /* Expand degeneracy/stalling tolerance range */ #endif monitor->limitstall[TRUE] = monitor->limitstall[FALSE]; if(monitor->oldpivrule == PRICER_DEVEX) /* Increase tolerance since primal Steepest Edge is expensive */ monitor->limitstall[TRUE] *= 2; if(MAX_RULESWITCH <= 0) monitor->limitruleswitches = MAXINT32; else monitor->limitruleswitches = MAX(MAX_RULESWITCH, lp->rows/MAX_RULESWITCH); monitor->epsvalue = lp->epsprimal; /* lp->epsvalue; */ lp->monitor = monitor; stallMonitor_reset(lp); lp->suminfeas = lp->infinite; return( TRUE ); } STATIC MYBOOL stallMonitor_check(lprec *lp, int rownr, int colnr, int lastnr, MYBOOL minit, MYBOOL approved, MYBOOL *forceoutEQ) { OBJmonrec *monitor = lp->monitor; MYBOOL isStalled, isCreeping, acceptance = TRUE; int altrule, #ifdef Paranoia msglevel = NORMAL; #else msglevel = DETAILED; #endif REAL deltaobj = lp->suminfeas; /* Accept unconditionally if this is the first or second call */ monitor->active = FALSE; if(monitor->Icount <= 1) { if(monitor->Icount == 1) { monitor->prevobj = lp->rhs[0]; monitor->previnfeas = deltaobj; } monitor->Icount++; return( acceptance ); } /* Define progress as primal objective less sum of (primal/dual) infeasibilities */ monitor->thisobj = lp->rhs[0]; monitor->thisinfeas = deltaobj; if(lp->spx_trace && (lastnr > 0)) report(lp, NORMAL, "%s: Objective at iter %10.0f is " RESULTVALUEMASK " (%4d: %4d %s- %4d)\n", monitor->spxfunc, (double) get_total_iter(lp), monitor->thisobj, rownr, lastnr, my_if(minit == ITERATE_MAJORMAJOR, "<","|"), colnr); monitor->pivrule = get_piv_rule(lp); /* Check if we have a stationary solution at selected tolerance level; allow some difference in case we just refactorized the basis. */ deltaobj = my_reldiff(monitor->thisobj, monitor->prevobj); deltaobj = fabs(deltaobj); /* Pre v5.2 version */ isStalled = (MYBOOL) (deltaobj < monitor->epsvalue); /* Also require that we have a measure of infeasibility-stalling */ if(isStalled) { REAL testvalue, refvalue = monitor->epsvalue; #if 1 if(monitor->isdual) refvalue *= 1000*log10(9.0+lp->rows); else refvalue *= 1000*log10(9.0+lp->columns); #else refvalue *= 1000*log10(9.0+lp->sum); #endif testvalue = my_reldiff(monitor->thisinfeas, monitor->previnfeas); isStalled &= (fabs(testvalue) < refvalue); /* Check if we should force "major" pivoting, i.e. no bound flips; this is activated when we see the feasibility deteriorate */ /* if(!isStalled && (testvalue > 0) && (TRUE || is_action(lp->anti_degen, ANTIDEGEN_BOUNDFLIP))) */ #if !defined _PRICE_NOBOUNDFLIP if(!isStalled && (testvalue > 0) && is_action(lp->anti_degen, ANTIDEGEN_BOUNDFLIP)) acceptance = AUTOMATIC; } #else if(!isStalled && (testvalue > 0) && !ISMASKSET(lp->piv_strategy, PRICE_NOBOUNDFLIP)) { SETMASK(lp->piv_strategy, PRICE_NOBOUNDFLIP); acceptance = AUTOMATIC; } } else CLEARMASK(lp->piv_strategy, PRICE_NOBOUNDFLIP); #endif #if 1 isCreeping = FALSE; #else isCreeping |= stallMonitor_creepingObj(lp); /* isCreeping |= stallMonitor_shortSteps(lp); */ #endif if(isStalled || isCreeping) { /* Update counters along with specific tolerance for bound flips */ #if 1 if(minit != ITERATE_MAJORMAJOR) { if(++monitor->Mcycle > 2) { monitor->Mcycle = 0; monitor->Ncycle++; } } else #endif monitor->Ncycle++; /* Start to monitor for variable cycling if this is the initial stationarity */ if(monitor->Ncycle <= 1) { monitor->Ccycle = colnr; monitor->Rcycle = rownr; } /* Check if we should change pivoting strategy */ else if(isCreeping || /* We have OF creep */ (monitor->Ncycle > monitor->limitstall[monitor->isdual]) || /* KE empirical value */ ((monitor->Ccycle == rownr) && (monitor->Rcycle == colnr))) { /* Obvious cycling */ monitor->active = TRUE; /* Try to force out equality slacks to combat degeneracy */ if((lp->fixedvars > 0) && (*forceoutEQ != TRUE)) { *forceoutEQ = TRUE; goto Proceed; } /* Our options are now to select an alternative rule or to do bound perturbation; check if these options are available to us or if we must signal failure and break out. */ approved &= monitor->pivdynamic && (monitor->ruleswitches < monitor->limitruleswitches); if(!approved && !is_anti_degen(lp, ANTIDEGEN_STALLING)) { lp->spx_status = DEGENERATE; report(lp, msglevel, "%s: Stalling at iter %10.0f; no alternative strategy left.\n", monitor->spxfunc, (double) get_total_iter(lp)); acceptance = FALSE; return( acceptance ); } /* See if we can do the appropriate alternative rule. */ switch (monitor->oldpivrule) { case PRICER_FIRSTINDEX: altrule = PRICER_DEVEX; break; case PRICER_DANTZIG: altrule = PRICER_DEVEX; break; case PRICER_DEVEX: altrule = PRICER_STEEPESTEDGE; break; case PRICER_STEEPESTEDGE: altrule = PRICER_DEVEX; break; default: altrule = PRICER_FIRSTINDEX; } if(approved && (monitor->pivrule != altrule) && (monitor->pivrule == monitor->oldpivrule)) { /* Switch rule to combat degeneracy. */ monitor->ruleswitches++; lp->piv_strategy = altrule; monitor->Ccycle = 0; monitor->Rcycle = 0; monitor->Ncycle = 0; monitor->Mcycle = 0; report(lp, msglevel, "%s: Stalling at iter %10.0f; changed to '%s' rule.\n", monitor->spxfunc, (double) get_total_iter(lp), get_str_piv_rule(get_piv_rule(lp))); if((altrule == PRICER_DEVEX) || (altrule == PRICER_STEEPESTEDGE)) restartPricer(lp, AUTOMATIC); } /* If not, code for bound relaxation/perturbation */ else { report(lp, msglevel, "%s: Stalling at iter %10.0f; proceed to bound relaxation.\n", monitor->spxfunc, (double) get_total_iter(lp)); acceptance = FALSE; lp->spx_status = DEGENERATE; return( acceptance ); } } } /* Otherwise change back to original selection strategy as soon as possible */ else { if(monitor->pivrule != monitor->oldpivrule) { lp->piv_strategy = monitor->oldpivstrategy; altrule = monitor->oldpivrule; if((altrule == PRICER_DEVEX) || (altrule == PRICER_STEEPESTEDGE)) restartPricer(lp, AUTOMATIC); report(lp, msglevel, "...returned to original pivot selection rule at iter %.0f.\n", (double) get_total_iter(lp)); } stallMonitor_update(lp, monitor->thisobj); monitor->Ccycle = 0; monitor->Rcycle = 0; monitor->Ncycle = 0; monitor->Mcycle = 0; } /* Update objective progress tracker */ Proceed: monitor->Icount++; if(deltaobj >= monitor->epsvalue) monitor->prevobj = monitor->thisobj; monitor->previnfeas = monitor->thisinfeas; return( acceptance ); } STATIC void stallMonitor_finish(lprec *lp) { OBJmonrec *monitor = lp->monitor; if(monitor == NULL) return; if(lp->piv_strategy != monitor->oldpivstrategy) lp->piv_strategy = monitor->oldpivstrategy; FREE(monitor); lp->monitor = NULL; } STATIC MYBOOL add_artificial(lprec *lp, int forrownr, REAL *nzarray, int *idxarray) /* This routine is called for each constraint at the start of primloop and the primal problem is infeasible. Its purpose is to add artificial variables and associated objective function values to populate primal phase 1. */ { MYBOOL add; /* Make sure we don't add unnecessary artificials, i.e. avoid cases where the slack variable is enough */ add = !isBasisVarFeasible(lp, lp->epspivot, forrownr); if(add) { int *rownr = NULL, i, bvar, ii; REAL *avalue = NULL, rhscoef, acoef; MATrec *mat = lp->matA; /* Check the simple case where a slack is basic */ for(i = 1; i <= lp->rows; i++) { if(lp->var_basic[i] == forrownr) break; } acoef = 1; /* If not, look for any basic user variable that has a non-zero coefficient in the current constraint row */ if(i > lp->rows) { for(i = 1; i <= lp->rows; i++) { ii = lp->var_basic[i] - lp->rows; if((ii <= 0) || (ii > (lp->columns-lp->P1extraDim))) continue; ii = mat_findelm(mat, forrownr, ii); if(ii >= 0) { acoef = COL_MAT_VALUE(ii); break; } } } /* If no candidate was found above, gamble on using the densest column available */ #if 0 if(i > lp->rows) { int len = 0; bvar = 0; for(i = 1; i <= lp->rows; i++) { ii = lp->var_basic[i] - lp->rows; if((ii <= 0) || (ii > (lp->columns-lp->P1extraDim))) continue; if(mat_collength(mat, ii) > len) { len = mat_collength(mat, ii); bvar = i; } } i = bvar; acoef = 1; } #endif bvar = i; add = (MYBOOL) (bvar <= lp->rows); if(add) { rhscoef = lp->rhs[forrownr]; /* Create temporary sparse array storage */ if(nzarray == NULL) allocREAL(lp, &avalue, 2, FALSE); else avalue = nzarray; if(idxarray == NULL) allocINT(lp, &rownr, 2, FALSE); else rownr = idxarray; /* Set the objective coefficient */ rownr[0] = 0; avalue[0] = my_chsign(is_chsign(lp, 0), 1); /* Set the constraint row coefficient */ rownr[1] = forrownr; avalue[1] = my_chsign(is_chsign(lp, forrownr), my_sign(rhscoef/acoef)); /* Add the column of artificial variable data to the user data matrix */ add_columnex(lp, 2, avalue, rownr); /* Free the temporary sparse array storage */ if(idxarray == NULL) FREE(rownr); if(nzarray == NULL) FREE(avalue); /* Now set the artificial variable to be basic */ set_basisvar(lp, bvar, lp->sum); lp->P1extraDim++; } else { report(lp, CRITICAL, "add_artificial: Could not find replacement basis variable for row %d\n", forrownr); lp->basis_valid = FALSE; } } return(add); } STATIC int get_artificialRow(lprec *lp, int colnr) { MATrec *mat = lp->matA; #ifdef Paranoia if((colnr <= lp->columns-abs(lp->P1extraDim)) || (colnr > lp->columns)) report(lp, SEVERE, "get_artificialRow: Invalid column index %d\n", colnr); if(mat->col_end[colnr] - mat->col_end[colnr-1] != 1) report(lp, SEVERE, "get_artificialRow: Invalid column non-zero count\n"); #endif /* Return the row index of the singleton */ colnr = mat->col_end[colnr-1]; colnr = COL_MAT_ROWNR(colnr); return( colnr ); } STATIC int findAnti_artificial(lprec *lp, int colnr) /* Primal simplex: Find a basic artificial variable to swap against the non-basic slack variable, if possible */ { int i, k, rownr = 0, P1extraDim = abs(lp->P1extraDim); if((P1extraDim == 0) || (colnr > lp->rows) || !lp->is_basic[colnr]) return( rownr ); for(i = 1; i <= lp->rows; i++) { k = lp->var_basic[i]; if((k > lp->sum-P1extraDim) && (lp->rhs[i] == 0)) { rownr = get_artificialRow(lp, k-lp->rows); /* Should we find the artificial's slack direct "antibody"? */ if(rownr == colnr) break; rownr = 0; } } return( rownr ); } STATIC int findBasicArtificial(lprec *lp, int before) { int i = 0, P1extraDim = abs(lp->P1extraDim); if(P1extraDim > 0) { if(before > lp->rows || before <= 1) i = lp->rows; else i = before; while((i > 0) && (lp->var_basic[i] <= lp->sum-P1extraDim)) i--; } return(i); } STATIC void eliminate_artificials(lprec *lp, REAL *prow) { int i, j, colnr, rownr, P1extraDim = abs(lp->P1extraDim); for(i = 1; (i <= lp->rows) && (P1extraDim > 0); i++) { j = lp->var_basic[i]; if(j <= lp->sum-P1extraDim) continue; j -= lp->rows; rownr = get_artificialRow(lp, j); colnr = find_rowReplacement(lp, rownr, prow, NULL); #if 0 performiteration(lp, rownr, colnr, 0.0, TRUE, FALSE, prow, NULL, NULL, NULL, NULL); #else set_basisvar(lp, rownr, colnr); #endif del_column(lp, j); P1extraDim--; } lp->P1extraDim = 0; } STATIC void clear_artificials(lprec *lp) { int i, j, n, P1extraDim; /* Substitute any basic artificial variable for its slack counterpart */ n = 0; P1extraDim = abs(lp->P1extraDim); for(i = 1; (i <= lp->rows) && (n < P1extraDim); i++) { j = lp->var_basic[i]; if(j <= lp->sum-P1extraDim) continue; j = get_artificialRow(lp, j-lp->rows); set_basisvar(lp, i, j); n++; } #ifdef Paranoia if(n != lp->P1extraDim) report(lp, SEVERE, "clear_artificials: Unable to clear all basic artificial variables\n"); #endif /* Delete any remaining non-basic artificial variables */ while(P1extraDim > 0) { i = lp->sum-lp->rows; del_column(lp, i); P1extraDim--; } lp->P1extraDim = 0; if(n > 0) { set_action(&lp->spx_action, ACTION_REINVERT); lp->basis_valid = TRUE; } } STATIC int primloop(lprec *lp, MYBOOL primalfeasible, REAL primaloffset) { MYBOOL primal = TRUE, bfpfinal = FALSE, changedphase = FALSE, forceoutEQ = AUTOMATIC, primalphase1, pricerCanChange, minit, stallaccept, pendingunbounded; int i, j, k, colnr = 0, rownr = 0, lastnr = 0, candidatecount = 0, minitcount = 0, ok = TRUE; LREAL theta = 0.0; REAL epsvalue, xviolated, cviolated = 0.0, *prow = NULL, *pcol = NULL, *drow = lp->drow; int *workINT = NULL, *nzdrow = lp->nzdrow; if(lp->spx_trace) report(lp, DETAILED, "Entered primal simplex algorithm with feasibility %s\n", my_boolstr(primalfeasible)); /* Add sufficent number of artificial variables to make the problem feasible through the first phase; delete when primal feasibility has been achieved */ lp->P1extraDim = 0; if(!primalfeasible) { lp->simplex_mode = SIMPLEX_Phase1_PRIMAL; #ifdef Paranoia if(!verify_basis(lp)) report(lp, SEVERE, "primloop: No valid basis for artificial variables\n"); #endif #if 0 /* First check if we can get away with a single artificial variable */ if(lp->equalities == 0) { i = (int) feasibilityOffset(lp, !primal); add_artificial(lp, i, prow, (int *) pcol); } else #endif /* Otherwise add as many artificial variables as is necessary to force primal feasibility. */ for(i = 1; i <= lp->rows; i++) { add_artificial(lp, i, NULL, NULL); } /* Make sure we update the working objective */ if(lp->P1extraDim > 0) { #if 1 /* v5.1 code: Not really necessary since we do not price the artificial variables (stored at the end of the column list, they are initially basic and are never allowed to enter the basis, once they exit) */ ok = allocREAL(lp, &(lp->drow), lp->sum+1, AUTOMATIC) && allocINT(lp, &(lp->nzdrow), lp->sum+1, AUTOMATIC); if(!ok) goto Finish; lp->nzdrow[0] = 0; drow = lp->drow; nzdrow = lp->nzdrow; #endif mat_validate(lp->matA); set_OF_p1extra(lp, 0.0); } if(lp->spx_trace) report(lp, DETAILED, "P1extraDim count = %d\n", lp->P1extraDim); simplexPricer(lp, (MYBOOL)!primal); invert(lp, INITSOL_USEZERO, TRUE); } else { lp->simplex_mode = SIMPLEX_Phase2_PRIMAL; restartPricer(lp, (MYBOOL)!primal); } /* Create work arrays and optionally the multiple pricing structure */ ok = allocREAL(lp, &(lp->bsolveVal), lp->rows + 1, FALSE) && allocREAL(lp, &prow, lp->sum + 1, TRUE) && allocREAL(lp, &pcol, lp->rows + 1, TRUE); if(is_piv_mode(lp, PRICE_MULTIPLE) && (lp->multiblockdiv > 1)) { lp->multivars = multi_create(lp, FALSE); ok &= (lp->multivars != NULL) && multi_resize(lp->multivars, lp->sum / lp->multiblockdiv, 2, FALSE, TRUE); } if(!ok) goto Finish; /* Initialize regular primal simplex algorithm variables */ lp->spx_status = RUNNING; minit = ITERATE_MAJORMAJOR; epsvalue = lp->epspivot; pendingunbounded = FALSE; ok = stallMonitor_create(lp, FALSE, "primloop"); if(!ok) goto Finish; lp->rejectpivot[0] = 0; /* Iterate while we are successful; exit when the model is infeasible/unbounded, or we must terminate due to numeric instability or user-determined reasons */ while((lp->spx_status == RUNNING) && !userabort(lp, -1)) { primalphase1 = (MYBOOL) (lp->P1extraDim > 0); clear_action(&lp->spx_action, ACTION_REINVERT | ACTION_ITERATE); /* Check if we have stalling (from numerics or degenerate cycling) */ pricerCanChange = !primalphase1; stallaccept = stallMonitor_check(lp, rownr, colnr, lastnr, minit, pricerCanChange, &forceoutEQ); if(!stallaccept) break; /* Find best column to enter the basis */ RetryCol: #if 0 if(verify_solution(lp, FALSE, "spx_loop") > 0) i = 1; /* This is just a debug trap */ #endif if(!changedphase) { i = 0; do { i++; colnr = colprim(lp, drow, nzdrow, (MYBOOL) (minit == ITERATE_MINORRETRY), i, &candidatecount, TRUE, &xviolated); } while ((colnr == 0) && (i < partial_countBlocks(lp, (MYBOOL) !primal)) && partial_blockStep(lp, (MYBOOL) !primal)); /* Handle direct outcomes */ if(colnr == 0) lp->spx_status = OPTIMAL; if(lp->rejectpivot[0] > 0) minit = ITERATE_MAJORMAJOR; /* See if accuracy check during compute_reducedcosts flagged refactorization */ if(is_action(lp->spx_action, ACTION_REINVERT)) bfpfinal = TRUE; } /* Make sure that we do not erroneously conclude that an unbounded model is optimal */ #ifdef primal_UseRejectionList if((colnr == 0) && (lp->rejectpivot[0] > 0)) { lp->spx_status = UNBOUNDED; if((lp->spx_trace && (lp->bb_totalnodes == 0)) || (lp->bb_trace && (lp->bb_totalnodes > 0))) report(lp, DETAILED, "The model is primal unbounded.\n"); colnr = lp->rejectpivot[1]; rownr = 0; lp->rejectpivot[0] = 0; ok = FALSE; break; } #endif /* Check if we found an entering variable (indicating that we are still dual infeasible) */ if(colnr > 0) { changedphase = FALSE; fsolve(lp, colnr, pcol, NULL, lp->epsmachine, 1.0, TRUE); /* Solve entering column for Pi */ /* Do special anti-degeneracy column selection, if specified */ if(is_anti_degen(lp, ANTIDEGEN_COLUMNCHECK) && !check_degeneracy(lp, pcol, NULL)) { if(lp->rejectpivot[0] < DEF_MAXPIVOTRETRY/3) { i = ++lp->rejectpivot[0]; lp->rejectpivot[i] = colnr; report(lp, DETAILED, "Entering column %d found to be non-improving due to degeneracy.\n", colnr); minit = ITERATE_MINORRETRY; goto RetryCol; } else { lp->rejectpivot[0] = 0; report(lp, DETAILED, "Gave up trying to find a strictly improving entering column.\n"); } } /* Find the leaving variable that gives the most stringent bound on the entering variable */ theta = drow[colnr]; rownr = rowprim(lp, colnr, &theta, pcol, workINT, forceoutEQ, &cviolated); #ifdef AcceptMarginalAccuracy /* Check for marginal accuracy */ if((rownr > 0) && (xviolated+cviolated < lp->epspivot)) { if(lp->bb_trace || (lp->bb_totalnodes == 0)) report(lp, DETAILED, "primloop: Assuming convergence with reduced accuracy %g.\n", MAX(xviolated, cviolated)); rownr = 0; colnr = 0; goto Optimality; } else #endif /* See if we can do a straight artificial<->slack replacement (when "colnr" is a slack) */ if((lp->P1extraDim != 0) && (rownr == 0) && (colnr <= lp->rows)) rownr = findAnti_artificial(lp, colnr); if(rownr > 0) { pendingunbounded = FALSE; lp->rejectpivot[0] = 0; set_action(&lp->spx_action, ACTION_ITERATE); if(!lp->obj_in_basis) /* We must manually copy the reduced cost for RHS update */ pcol[0] = my_chsign(!lp->is_lower[colnr], drow[colnr]); lp->bfp_prepareupdate(lp, rownr, colnr, pcol); } /* We may be unbounded... */ else { /* First make sure that we are not suffering from precision loss */ #ifdef primal_UseRejectionList if(lp->rejectpivot[0] < DEF_MAXPIVOTRETRY) { lp->spx_status = RUNNING; lp->rejectpivot[0]++; lp->rejectpivot[lp->rejectpivot[0]] = colnr; report(lp, DETAILED, "...trying to recover via another pivot column.\n"); minit = ITERATE_MINORRETRY; goto RetryCol; } else #endif /* Check that we are not having numerical problems */ if(!refactRecent(lp) && !pendingunbounded) { bfpfinal = TRUE; pendingunbounded = TRUE; set_action(&lp->spx_action, ACTION_REINVERT); } /* Conclude that the model is unbounded */ else { lp->spx_status = UNBOUNDED; report(lp, DETAILED, "The model is primal unbounded.\n"); break; } } } /* We handle optimality and phase 1 infeasibility ... */ else { Optimality: /* Handle possible transition from phase 1 to phase 2 */ if(!primalfeasible || isP1extra(lp)) { if(feasiblePhase1(lp, epsvalue)) { lp->spx_status = RUNNING; if(lp->bb_totalnodes == 0) { report(lp, NORMAL, "Found feasibility by primal simplex after %10.0f iter.\n", (double) get_total_iter(lp)); if((lp->usermessage != NULL) && (lp->msgmask & MSG_LPFEASIBLE)) lp->usermessage(lp, lp->msghandle, MSG_LPFEASIBLE); } changedphase = FALSE; primalfeasible = TRUE; lp->simplex_mode = SIMPLEX_Phase2_PRIMAL; set_OF_p1extra(lp, 0.0); /* We can do two things now; 1) delete the rows belonging to those variables, since they are redundant, OR 2) drive out the existing artificial variables via pivoting. */ if(lp->P1extraDim > 0) { #ifdef Phase1EliminateRedundant /* If it is not a MIP model we can try to delete redundant rows */ if((lp->bb_totalnodes == 0) && (MIP_count(lp) == 0)) { while(lp->P1extraDim > 0) { i = lp->rows; while((i > 0) && (lp->var_basic[i] <= lp->sum-lp->P1extraDim)) i--; #ifdef Paranoia if(i <= 0) { report(lp, SEVERE, "primloop: Could not find redundant artificial.\n"); break; } #endif /* Obtain column and row indeces */ j = lp->var_basic[i]-lp->rows; k = get_artificialRow(lp, j); /* Delete row before column due to basis "compensation logic" */ if(lp->is_basic[k]) { lp->is_basic[lp->rows+j] = FALSE; del_constraint(lp, k); } else set_basisvar(lp, i, k); del_column(lp, j); lp->P1extraDim--; } lp->basis_valid = TRUE; } /* Otherwise we drive out the artificials by elimination pivoting */ else eliminate_artificials(lp, prow); #else /* Indicate phase 2 with artificial variables by negating P1extraDim */ lp->P1extraDim = my_flipsign(lp->P1extraDim); #endif } /* We must refactorize since the OF changes from phase 1 to phase 2 */ set_action(&lp->spx_action, ACTION_REINVERT); bfpfinal = TRUE; } /* We are infeasible in phase 1 */ else { lp->spx_status = INFEASIBLE; minit = ITERATE_MAJORMAJOR; if(lp->spx_trace) report(lp, NORMAL, "Model infeasible by primal simplex at iter %10.0f.\n", (double) get_total_iter(lp)); } } /* Handle phase 1 optimality */ else { /* (Do nothing special) */ } /* Check if we are still primal feasible; the default assumes that this check is not necessary after the relaxed problem has been solved satisfactorily. */ if((lp->bb_level <= 1) || (lp->improve & IMPROVE_BBSIMPLEX) /* || (lp->bb_rule & NODE_RCOSTFIXING) */) { /* NODE_RCOSTFIXING fix */ set_action(&lp->piv_strategy, PRICE_FORCEFULL); i = rowdual(lp, lp->rhs, FALSE, FALSE, NULL); clear_action(&lp->piv_strategy, PRICE_FORCEFULL); if(i > 0) { lp->spx_status = LOSTFEAS; if(lp->total_iter == 0) report(lp, DETAILED, "primloop: Lost primal feasibility at iter %10.0f: will try to recover.\n", (double) get_total_iter(lp)); } } } /* Pivot row/col and update the inverse */ if(is_action(lp->spx_action, ACTION_ITERATE)) { lastnr = lp->var_basic[rownr]; if(refactRecent(lp) == AUTOMATIC) minitcount = 0; else if(minitcount > MAX_MINITUPDATES) { recompute_solution(lp, INITSOL_USEZERO); minitcount = 0; } minit = performiteration(lp, rownr, colnr, theta, primal, (MYBOOL) (/*(candidatecount > 1) && */ (stallaccept != AUTOMATIC)), NULL, NULL, pcol, NULL, NULL); if(minit != ITERATE_MAJORMAJOR) minitcount++; if((lp->spx_status == USERABORT) || (lp->spx_status == TIMEOUT)) break; else if(minit == ITERATE_MINORMAJOR) continue; #ifdef UsePrimalReducedCostUpdate /* Do a fast update of the reduced costs in preparation for the next iteration */ if(minit == ITERATE_MAJORMAJOR) update_reducedcosts(lp, primal, lastnr, colnr, pcol, drow); #endif /* Detect if an auxiliary variable has left the basis and delete it; if the non-basic variable only changed bound (a "minor iteration"), the basic artificial variable did not leave and there is nothing to do */ if((minit == ITERATE_MAJORMAJOR) && (lastnr > lp->sum - abs(lp->P1extraDim))) { #ifdef Paranoia if(lp->is_basic[lastnr] || !lp->is_basic[colnr]) report(lp, SEVERE, "primloop: Invalid basis indicator for variable %d at iter %10.0f.\n", lastnr, (double) get_total_iter(lp)); #endif del_column(lp, lastnr-lp->rows); if(lp->P1extraDim > 0) lp->P1extraDim--; else lp->P1extraDim++; if(lp->P1extraDim == 0) { colnr = 0; changedphase = TRUE; stallMonitor_reset(lp); } } } if(lp->spx_status == SWITCH_TO_DUAL) ; else if(!changedphase && lp->bfp_mustrefactorize(lp)) { #ifdef ResetMinitOnReinvert minit = ITERATE_MAJORMAJOR; #endif if(!invert(lp, INITSOL_USEZERO, bfpfinal)) lp->spx_status = SINGULAR_BASIS; bfpfinal = FALSE; } } /* Remove any remaining artificial variables (feasible or infeasible model) */ lp->P1extraDim = abs(lp->P1extraDim); /* if((lp->P1extraDim > 0) && (lp->spx_status != DEGENERATE)) { */ if(lp->P1extraDim > 0) { clear_artificials(lp); if(lp->spx_status != OPTIMAL) restore_basis(lp); i = invert(lp, INITSOL_USEZERO, TRUE); } #ifdef Paranoia if(!verify_basis(lp)) report(lp, SEVERE, "primloop: Invalid basis detected due to internal error\n"); #endif /* Switch to dual phase 1 simplex for MIP models during B&B phases, since this is typically far more efficient */ #ifdef ForceDualSimplexInBB if((lp->bb_totalnodes == 0) && (MIP_count(lp) > 0) && ((lp->simplex_strategy & SIMPLEX_Phase1_DUAL) == 0)) { lp->simplex_strategy &= ~SIMPLEX_Phase1_PRIMAL; lp->simplex_strategy += SIMPLEX_Phase1_DUAL; } #endif Finish: stallMonitor_finish(lp); multi_free(&(lp->multivars)); FREE(prow); FREE(pcol); FREE(lp->bsolveVal); return(ok); } /* primloop */ STATIC int dualloop(lprec *lp, MYBOOL dualfeasible, int dualinfeasibles[], REAL dualoffset) { MYBOOL primal = FALSE, inP1extra, dualphase1 = FALSE, changedphase = TRUE, pricerCanChange, minit, stallaccept, longsteps, forceoutEQ = FALSE, bfpfinal = FALSE; int i, colnr = 0, rownr = 0, lastnr = 0, candidatecount = 0, minitcount = 0, #ifdef FixInaccurateDualMinit minitcolnr = 0, #endif ok = TRUE; int *boundswaps = NULL; LREAL theta = 0.0; REAL epsvalue, xviolated, cviolated, *prow = NULL, *pcol = NULL, *drow = lp->drow; int *nzprow = NULL, *workINT = NULL, *nzdrow = lp->nzdrow; if(lp->spx_trace) report(lp, DETAILED, "Entered dual simplex algorithm with feasibility %s.\n", my_boolstr(dualfeasible)); /* Allocate work arrays */ ok = allocREAL(lp, &prow, lp->sum + 1, TRUE) && allocINT (lp, &nzprow, lp->sum + 1, FALSE) && allocREAL(lp, &pcol, lp->rows + 1, TRUE); if(!ok) goto Finish; /* Set non-zero P1extraVal value to force dual feasibility when the dual simplex is used as a phase 1 algorithm for the primal simplex. The value will be reset when primal feasibility has been achieved, or a dual non-feasibility has been encountered (no candidate for a first leaving variable) */ inP1extra = (MYBOOL) (dualoffset != 0); if(inP1extra) { set_OF_p1extra(lp, dualoffset); simplexPricer(lp, (MYBOOL)!primal); invert(lp, INITSOL_USEZERO, TRUE); } else restartPricer(lp, (MYBOOL)!primal); /* Prepare dual long-step structures */ #if 0 longsteps = TRUE; #elif 0 longsteps = (MYBOOL) ((MIP_count(lp) > 0) && (lp->bb_level > 1)); #elif 0 longsteps = (MYBOOL) ((MIP_count(lp) > 0) && (lp->solutioncount >= 1)); #else longsteps = FALSE; #endif #ifdef UseLongStepDualPhase1 longsteps = !dualfeasible && (MYBOOL) (dualinfeasibles != NULL); #endif if(longsteps) { lp->longsteps = multi_create(lp, TRUE); ok = (lp->longsteps != NULL) && multi_resize(lp->longsteps, MIN(lp->boundedvars+2, 11), 1, TRUE, TRUE); if(!ok) goto Finish; #ifdef UseLongStepPruning lp->longsteps->objcheck = TRUE; #endif boundswaps = multi_indexSet(lp->longsteps, FALSE); } /* Do regular dual simplex variable initializations */ lp->spx_status = RUNNING; minit = ITERATE_MAJORMAJOR; epsvalue = lp->epspivot; ok = stallMonitor_create(lp, TRUE, "dualloop"); if(!ok) goto Finish; lp->rejectpivot[0] = 0; if(dualfeasible) lp->simplex_mode = SIMPLEX_Phase2_DUAL; else lp->simplex_mode = SIMPLEX_Phase1_DUAL; /* Check if we have equality slacks in the basis and we should try to drive them out in order to reduce chance of degeneracy in Phase 1. forceoutEQ = FALSE : Only eliminate assured "good" violated equality constraint slacks AUTOMATIC: Seek more elimination of equality constraint slacks (but not as aggressive as the rule used in lp_solve v4.0 and earlier) TRUE: Force remaining equality slacks out of the basis */ if(dualphase1 || inP1extra || ((lp->fixedvars > 0) && is_anti_degen(lp, ANTIDEGEN_FIXEDVARS))) { forceoutEQ = AUTOMATIC; } #if 1 if(is_anti_degen(lp, ANTIDEGEN_DYNAMIC) && (bin_count(lp, TRUE)*2 > lp->columns)) { switch (forceoutEQ) { case FALSE: forceoutEQ = AUTOMATIC; break; /* case AUTOMATIC: forceoutEQ = TRUE; break; default: forceoutEQ = TRUE; */ } } #endif while((lp->spx_status == RUNNING) && !userabort(lp, -1)) { /* Check if we have stalling (from numerics or degenerate cycling) */ pricerCanChange = !dualphase1 && !inP1extra; stallaccept = stallMonitor_check(lp, rownr, colnr, lastnr, minit, pricerCanChange, &forceoutEQ); if(!stallaccept) break; /* Store current LP index for reference at next iteration */ changedphase = FALSE; /* Compute (pure) dual phase1 offsets / reduced costs if appropriate */ dualphase1 &= (MYBOOL) (lp->simplex_mode == SIMPLEX_Phase1_DUAL); if(longsteps && dualphase1 && !inP1extra) { obtain_column(lp, dualinfeasibles[1], pcol, NULL, NULL); i = 2; for(i = 2; i <= dualinfeasibles[0]; i++) mat_multadd(lp->matA, pcol, dualinfeasibles[i], 1.0); /* Solve (note that solved pcol will be used instead of lp->rhs) */ ftran(lp, pcol, NULL, lp->epsmachine); } /* Do minor iterations (non-basic variable bound flips) for as long as possible since this is a cheap way of iterating */ #if (defined dual_Phase1PriceEqualities) || (defined dual_UseRejectionList) RetryRow: #endif if(minit != ITERATE_MINORRETRY) { i = 0; do { i++; rownr = rowdual(lp, my_if(dualphase1, pcol, NULL), forceoutEQ, TRUE, &xviolated); } while ((rownr == 0) && (i < partial_countBlocks(lp, (MYBOOL) !primal)) && partial_blockStep(lp, (MYBOOL) !primal)); } /* Make sure that we do not erroneously conclude that an infeasible model is optimal */ #ifdef dual_UseRejectionList if((rownr == 0) && (lp->rejectpivot[0] > 0)) { lp->spx_status = INFEASIBLE; if((lp->spx_trace && (lp->bb_totalnodes == 0)) || (lp->bb_trace && (lp->bb_totalnodes > 0))) report(lp, DETAILED, "The model is primal infeasible.\n"); rownr = lp->rejectpivot[1]; colnr = 0; lp->rejectpivot[0] = 0; ok = FALSE; break; } #endif /* If we found a leaving variable, find a matching entering one */ clear_action(&lp->spx_action, ACTION_ITERATE); if(rownr > 0) { colnr = coldual(lp, rownr, prow, nzprow, drow, nzdrow, (MYBOOL) (dualphase1 && !inP1extra), (MYBOOL) (minit == ITERATE_MINORRETRY), &candidatecount, &cviolated); if(colnr < 0) { minit = ITERATE_MAJORMAJOR; continue; } #ifdef AcceptMarginalAccuracy else if(xviolated+cviolated < lp->epspivot) { if(lp->bb_trace || (lp->bb_totalnodes == 0)) report(lp, DETAILED, "dualloop: Assuming convergence with reduced accuracy %g.\n", MAX(xviolated, cviolated)); rownr = 0; colnr = 0; } #endif /* Check if the long-dual found reason to prune the B&B tree */ if(lp->spx_status == FATHOMED) break; } else colnr = 0; /* Process primal-infeasible row */ if(rownr > 0) { if(colnr > 0) { #ifdef Paranoia if((rownr > lp->rows) || (colnr > lp->sum)) { report(lp, SEVERE, "dualloop: Invalid row %d(%d) and column %d(%d) pair selected at iteration %.0f\n", rownr, lp->rows, colnr-lp->columns, lp->columns, (double) get_total_iter(lp)); lp->spx_status = UNKNOWNERROR; break; } #endif fsolve(lp, colnr, pcol, workINT, lp->epsmachine, 1.0, TRUE); #ifdef FixInaccurateDualMinit /* Prevent bound flip-flops during minor iterations; used to detect infeasibility after triggering of minor iteration accuracy management */ if(colnr != minitcolnr) minitcolnr = 0; #endif /* Getting division by zero here; catch it and try to recover */ if(pcol[rownr] == 0) { if(lp->spx_trace) report(lp, DETAILED, "dualloop: Attempt to divide by zero (pcol[%d])\n", rownr); if(!refactRecent(lp)) { report(lp, DETAILED, "...trying to recover by refactorizing basis.\n"); set_action(&lp->spx_action, ACTION_REINVERT); bfpfinal = FALSE; } else { if(lp->bb_totalnodes == 0) report(lp, DETAILED, "...cannot recover by refactorizing basis.\n"); lp->spx_status = NUMFAILURE; ok = FALSE; } } else { set_action(&lp->spx_action, ACTION_ITERATE); lp->rejectpivot[0] = 0; if(!lp->obj_in_basis) /* We must manually copy the reduced cost for RHS update */ pcol[0] = my_chsign(!lp->is_lower[colnr], drow[colnr]); theta = lp->bfp_prepareupdate(lp, rownr, colnr, pcol); /* Verify numeric accuracy of the basis factorization and change to the "theoretically" correct version of the theta */ if((lp->improve & IMPROVE_THETAGAP) && !refactRecent(lp) && (my_reldiff(fabs(theta), fabs(prow[colnr])) > lp->epspivot*10.0*log(2.0+50.0*lp->rows))) { /* This is my kludge - KE */ set_action(&lp->spx_action, ACTION_REINVERT); bfpfinal = TRUE; #ifdef IncreasePivotOnReducedAccuracy lp->epspivot = MIN(1.0e-4, lp->epspivot*2.0); #endif report(lp, DETAILED, "dualloop: Refactorizing at iter %.0f due to loss of accuracy.\n", (double) get_total_iter(lp)); } theta = prow[colnr]; compute_theta(lp, rownr, &theta, !lp->is_lower[colnr], 0, primal); } } #ifdef FixInaccurateDualMinit /* Force reinvertion and try another row if we did not find a bound-violated leaving column */ else if(!refactRecent(lp) && (minit != ITERATE_MAJORMAJOR) && (colnr != minitcolnr)) { minitcolnr = colnr; i = invert(lp, INITSOL_USEZERO, TRUE); if((lp->spx_status == USERABORT) || (lp->spx_status == TIMEOUT)) break; else if(!i) { lp->spx_status = SINGULAR_BASIS; break; } minit = ITERATE_MAJORMAJOR; continue; } #endif /* We may be infeasible, have lost dual feasibility, or simply have no valid entering variable for the selected row. The strategy is to refactorize if we suspect numerical problems and loss of dual feasibility; this is done if it has been a while since refactorization. If not, first try to select a different row/leaving variable to see if a valid entering variable can be found. Otherwise, determine this model as infeasible. */ else { /* As a first option, try to recover from any numerical trouble by refactorizing */ if(!refactRecent(lp)) { set_action(&lp->spx_action, ACTION_REINVERT); bfpfinal = TRUE; } #ifdef dual_UseRejectionList /* Check for pivot size issues */ else if(lp->rejectpivot[0] < DEF_MAXPIVOTRETRY) { lp->spx_status = RUNNING; lp->rejectpivot[0]++; lp->rejectpivot[lp->rejectpivot[0]] = rownr; if(lp->bb_totalnodes == 0) report(lp, DETAILED, "...trying to find another pivot row!\n"); goto RetryRow; } #endif /* Check if we may have lost dual feasibility if we also did phase 1 here */ else if(dualphase1 && (dualoffset != 0)) { lp->spx_status = LOSTFEAS; if((lp->spx_trace && (lp->bb_totalnodes == 0)) || (lp->bb_trace && (lp->bb_totalnodes > 0))) report(lp, DETAILED, "dualloop: Model lost dual feasibility.\n"); ok = FALSE; break; } /* Otherwise just determine that we are infeasible */ else { if(lp->spx_status == RUNNING) { #if 1 if(xviolated < lp->epspivot) { if(lp->bb_trace || (lp->bb_totalnodes == 0)) report(lp, NORMAL, "The model is primal optimal, but marginally infeasible.\n"); lp->spx_status = OPTIMAL; break; } #endif lp->spx_status = INFEASIBLE; if((lp->spx_trace && (lp->bb_totalnodes == 0)) || (lp->bb_trace && (lp->bb_totalnodes > 0))) report(lp, DETAILED, "The model is primal infeasible.\n"); } ok = FALSE; break; } } } /* Make sure that we enter the primal simplex with a high quality solution */ else if(inP1extra && !refactRecent(lp) && is_action(lp->improve, IMPROVE_INVERSE)) { set_action(&lp->spx_action, ACTION_REINVERT); bfpfinal = TRUE; } /* High quality solution with no leaving candidates available ... */ else { bfpfinal = TRUE; #ifdef dual_RemoveBasicFixedVars /* See if we should try to eliminate basic fixed variables; can be time-consuming for some models */ if(inP1extra && (colnr == 0) && (lp->fixedvars > 0) && is_anti_degen(lp, ANTIDEGEN_FIXEDVARS)) { report(lp, DETAILED, "dualloop: Trying to pivot out %d fixed basic variables at iter %.0f\n", lp->fixedvars, (double) get_total_iter(lp)); rownr = 0; while(lp->fixedvars > 0) { rownr = findBasicFixedvar(lp, rownr, TRUE); if(rownr == 0) { colnr = 0; break; } colnr = find_rowReplacement(lp, rownr, prow, nzprow); if(colnr > 0) { theta = 0; performiteration(lp, rownr, colnr, theta, TRUE, FALSE, prow, NULL, NULL, NULL, NULL); lp->fixedvars--; } } } #endif /* Check if we are INFEASIBLE for the case that the dual is used as phase 1 before the primal simplex phase 2 */ if(inP1extra && (colnr < 0) && !isPrimalFeasible(lp, lp->epsprimal, NULL, NULL)) { if(lp->bb_totalnodes == 0) { if(dualfeasible) report(lp, DETAILED, "The model is primal infeasible and dual feasible.\n"); else report(lp, DETAILED, "The model is primal infeasible and dual unbounded.\n"); } set_OF_p1extra(lp, 0); inP1extra = FALSE; set_action(&lp->spx_action, ACTION_REINVERT); lp->spx_status = INFEASIBLE; lp->simplex_mode = SIMPLEX_UNDEFINED; ok = FALSE; } /* Check if we are FEASIBLE (and possibly also optimal) for the case that the dual is used as phase 1 before the primal simplex phase 2 */ else if(inP1extra) { /* Set default action; force an update of the rhs vector, adjusted for the new P1extraVal=0 (set here so that usermessage() behaves properly) */ if(lp->bb_totalnodes == 0) { report(lp, NORMAL, "Found feasibility by dual simplex after %10.0f iter.\n", (double) get_total_iter(lp)); if((lp->usermessage != NULL) && (lp->msgmask & MSG_LPFEASIBLE)) lp->usermessage(lp, lp->msghandle, MSG_LPFEASIBLE); } set_OF_p1extra(lp, 0); inP1extra = FALSE; set_action(&lp->spx_action, ACTION_REINVERT); #if 1 /* Optionally try another dual loop, if so selected by the user */ if((lp->simplex_strategy & SIMPLEX_DUAL_PRIMAL) && (lp->fixedvars == 0)) lp->spx_status = SWITCH_TO_PRIMAL; #endif changedphase = TRUE; } /* We are primal feasible and also optimal if we were in phase 2 */ else { lp->simplex_mode = SIMPLEX_Phase2_DUAL; /* Check if we still have equality slacks stuck in the basis; drive them out? */ if((lp->fixedvars > 0) && (lp->bb_totalnodes == 0)) { #ifdef dual_Phase1PriceEqualities if(forceoutEQ != TRUE) { forceoutEQ = TRUE; goto RetryRow; } #endif #ifdef Paranoia report(lp, NORMAL, #else report(lp, DETAILED, #endif "Found dual solution with %d fixed slack variables left basic.\n", lp->fixedvars); } /* Check if we are still dual feasible; the default assumes that this check is not necessary after the relaxed problem has been solved satisfactorily. */ colnr = 0; if((dualoffset != 0) || (lp->bb_level <= 1) || (lp->improve & IMPROVE_BBSIMPLEX) || (lp->bb_rule & NODE_RCOSTFIXING)) { /* NODE_RCOSTFIXING fix */ set_action(&lp->piv_strategy, PRICE_FORCEFULL); colnr = colprim(lp, drow, nzdrow, FALSE, 1, &candidatecount, FALSE, NULL); clear_action(&lp->piv_strategy, PRICE_FORCEFULL); if((dualoffset == 0) && (colnr > 0)) { lp->spx_status = LOSTFEAS; if(lp->total_iter == 0) report(lp, DETAILED, "Recovering lost dual feasibility at iter %10.0f.\n", (double) get_total_iter(lp)); break; } } if(colnr == 0) lp->spx_status = OPTIMAL; else { lp->spx_status = SWITCH_TO_PRIMAL; if(lp->total_iter == 0) report(lp, DETAILED, "Use primal simplex for finalization at iter %10.0f.\n", (double) get_total_iter(lp)); } if((lp->total_iter == 0) && (lp->spx_status == OPTIMAL)) report(lp, DETAILED, "Optimal solution with dual simplex at iter %10.0f.\n", (double) get_total_iter(lp)); } /* Determine if we are ready to break out of the loop */ if(!changedphase) break; } /* Check if we are allowed to iterate on the chosen column and row */ if(is_action(lp->spx_action, ACTION_ITERATE)) { lastnr = lp->var_basic[rownr]; if(refactRecent(lp) == AUTOMATIC) minitcount = 0; else if(minitcount > MAX_MINITUPDATES) { recompute_solution(lp, INITSOL_USEZERO); minitcount = 0; } minit = performiteration(lp, rownr, colnr, theta, primal, (MYBOOL) (/*(candidatecount > 1) && */ (stallaccept != AUTOMATIC)), prow, nzprow, pcol, NULL, boundswaps); /* Check if we should abandon iterations on finding that there is no hope that this branch can improve on the incumbent B&B solution */ if(!lp->is_strongbranch && (lp->solutioncount >= 1) && !lp->spx_perturbed && !inP1extra && bb_better(lp, OF_WORKING, OF_TEST_WE)) { lp->spx_status = FATHOMED; ok = FALSE; break; } if(minit != ITERATE_MAJORMAJOR) minitcount++; /* Update reduced costs for (pure) dual long-step phase 1 */ if(longsteps && dualphase1 && !inP1extra) { dualfeasible = isDualFeasible(lp, lp->epsprimal, NULL, dualinfeasibles, NULL); if(dualfeasible) { dualphase1 = FALSE; changedphase = TRUE; lp->simplex_mode = SIMPLEX_Phase2_DUAL; } } #ifdef UseDualReducedCostUpdate /* Do a fast update of reduced costs in preparation for the next iteration */ else if(minit == ITERATE_MAJORMAJOR) update_reducedcosts(lp, primal, lastnr, colnr, prow, drow); #endif if((minit == ITERATE_MAJORMAJOR) && (lastnr <= lp->rows) && is_fixedvar(lp, lastnr)) lp->fixedvars--; } /* Refactorize if required to */ if(lp->bfp_mustrefactorize(lp)) { if(invert(lp, INITSOL_USEZERO, bfpfinal)) { #if 0 /* Verify dual feasibility in case we are attempting the extra dual loop */ if(changedphase && (dualoffset != 0) && !inP1extra && (lp->spx_status != SWITCH_TO_PRIMAL)) { #if 1 if(!isDualFeasible(lp, lp->epsdual, &colnr, NULL, NULL)) { #else set_action(&lp->piv_strategy, PRICE_FORCEFULL); colnr = colprim(lp, drow, nzdrow, FALSE, 1, &candidatecount, FALSE, NULL); clear_action(&lp->piv_strategy, PRICE_FORCEFULL); if(colnr > 0) { #endif lp->spx_status = SWITCH_TO_PRIMAL; colnr = 0; } } #endif bfpfinal = FALSE; #ifdef ResetMinitOnReinvert minit = ITERATE_MAJORMAJOR; #endif } else lp->spx_status = SINGULAR_BASIS; } } Finish: stallMonitor_finish(lp); multi_free(&(lp->longsteps)); FREE(prow); FREE(nzprow); FREE(pcol); return(ok); } STATIC int spx_run(lprec *lp, MYBOOL validInvB) { int i, j, singular_count, lost_feas_count, *infeasibles = NULL, *boundflip_count; MYBOOL primalfeasible, dualfeasible, lost_feas_state, isbb; REAL primaloffset = 0, dualoffset = 0; lp->current_iter = 0; lp->current_bswap = 0; lp->spx_status = RUNNING; lp->bb_status = lp->spx_status; lp->P1extraDim = 0; set_OF_p1extra(lp, 0); singular_count = 0; lost_feas_count = 0; lost_feas_state = FALSE; lp->simplex_mode = SIMPLEX_DYNAMIC; /* Compute the number of fixed basic and bounded variables (used in long duals) */ lp->fixedvars = 0; lp->boundedvars = 0; for(i = 1; i <= lp->rows; i++) { j = lp->var_basic[i]; if((j <= lp->rows) && is_fixedvar(lp, j)) lp->fixedvars++; if((lp->upbo[i] < lp->infinite) && (lp->upbo[i] > lp->epsprimal)) lp->boundedvars++; } for(; i <= lp->sum; i++){ if((lp->upbo[i] < lp->infinite) && (lp->upbo[i] > lp->epsprimal)) lp->boundedvars++; } #ifdef UseLongStepDualPhase1 allocINT(lp, &infeasibles, lp->columns + 1, FALSE); infeasibles[0] = 0; #endif /* Reinvert for initialization, if necessary */ isbb = (MYBOOL) ((MIP_count(lp) > 0) && (lp->bb_level > 1)); if(is_action(lp->spx_action, ACTION_REINVERT)) { if(isbb && (lp->bb_bounds->nodessolved == 0)) /* if(isbb && (lp->bb_basis->pivots == 0)) */ recompute_solution(lp, INITSOL_SHIFTZERO); else { i = my_if(is_action(lp->spx_action, ACTION_REBASE), INITSOL_SHIFTZERO, INITSOL_USEZERO); invert(lp, (MYBOOL) i, TRUE); } } else if(is_action(lp->spx_action, ACTION_REBASE)) recompute_solution(lp, INITSOL_SHIFTZERO); /* Optionally try to do bound flips to obtain dual feasibility */ if(is_action(lp->improve, IMPROVE_DUALFEAS) || (lp->rows == 0)) boundflip_count = &i; else boundflip_count = NULL; /* Loop for as long as is needed */ while(lp->spx_status == RUNNING) { /* Check for dual and primal feasibility */ dualfeasible = isbb || isDualFeasible(lp, lp->epsprimal, boundflip_count, infeasibles, &dualoffset); /* Recompute if the dual feasibility check included bound flips */ if(is_action(lp->spx_action, ACTION_RECOMPUTE)) recompute_solution(lp, INITSOL_USEZERO); primalfeasible = isPrimalFeasible(lp, lp->epsprimal, NULL, &primaloffset); if(userabort(lp, -1)) break; if(lp->spx_trace) { if(primalfeasible) report(lp, NORMAL, "Start at primal feasible basis\n"); else if(dualfeasible) report(lp, NORMAL, "Start at dual feasible basis\n"); else if(lost_feas_count > 0) report(lp, NORMAL, "Continuing at infeasible basis\n"); else report(lp, NORMAL, "Start at infeasible basis\n"); } /* Now do the simplex magic */ if(((lp->simplex_strategy & SIMPLEX_Phase1_DUAL) == 0) || ((MIP_count(lp) > 0) && (lp->total_iter == 0) && is_presolve(lp, PRESOLVE_REDUCEMIP))) { if(!lost_feas_state && primalfeasible && ((lp->simplex_strategy & SIMPLEX_Phase2_DUAL) > 0)) lp->spx_status = SWITCH_TO_DUAL; else primloop(lp, primalfeasible, 0.0); if(lp->spx_status == SWITCH_TO_DUAL) dualloop(lp, TRUE, NULL, 0.0); } else { if(!lost_feas_state && primalfeasible && ((lp->simplex_strategy & SIMPLEX_Phase2_PRIMAL) > 0)) lp->spx_status = SWITCH_TO_PRIMAL; else dualloop(lp, dualfeasible, infeasibles, dualoffset); if(lp->spx_status == SWITCH_TO_PRIMAL) primloop(lp, TRUE, 0.0); } /* Check for simplex outcomes that always involve breaking out of the loop; this includes optimality, unboundedness, pure infeasibility (i.e. not loss of feasibility), numerical failure and perturbation-based degeneracy handling */ i = lp->spx_status; primalfeasible = (MYBOOL) (i == OPTIMAL); if(primalfeasible || (i == UNBOUNDED)) break; else if(((i == INFEASIBLE) && is_anti_degen(lp, ANTIDEGEN_INFEASIBLE)) || ((i == LOSTFEAS) && is_anti_degen(lp, ANTIDEGEN_LOSTFEAS)) || ((i == NUMFAILURE) && is_anti_degen(lp, ANTIDEGEN_NUMFAILURE)) || ((i == DEGENERATE) && is_anti_degen(lp, ANTIDEGEN_STALLING))) { /* Check if we should not loop here, but do perturbations */ if((lp->bb_level <= 1) || is_anti_degen(lp, ANTIDEGEN_DURINGBB)) break; /* Assume that accuracy during B&B is high and that infeasibility is "real" */ #ifdef AssumeHighAccuracyInBB if((lp->bb_level > 1) && (i == INFEASIBLE)) break; #endif } /* Check for outcomes that may involve trying another simplex loop */ if(lp->spx_status == SINGULAR_BASIS) { lost_feas_state = FALSE; singular_count++; if(singular_count >= DEF_MAXSINGULARITIES) { report(lp, IMPORTANT, "spx_run: Failure due to too many singular bases.\n"); lp->spx_status = NUMFAILURE; break; } if(lp->spx_trace || (lp->verbose > DETAILED)) report(lp, NORMAL, "spx_run: Singular basis; attempting to recover.\n"); lp->spx_status = RUNNING; /* Singular pivots are simply skipped by the inversion, leaving a row's slack variable in the basis instead of the singular user variable. */ } else { lost_feas_state = (MYBOOL) (lp->spx_status == LOSTFEAS); #if 0 /* Optionally handle loss of numerical accuracy as loss of feasibility, but only attempt a single loop to try to recover from this. */ lost_feas_state |= (MYBOOL) ((lp->spx_status == NUMFAILURE) && (lost_feas_count < 1)); #endif if(lost_feas_state) { lost_feas_count++; if(lost_feas_count < DEF_MAXSINGULARITIES) { report(lp, DETAILED, "spx_run: Recover lost feasibility at iter %10.0f.\n", (double) get_total_iter(lp)); lp->spx_status = RUNNING; } else { report(lp, IMPORTANT, "spx_run: Lost feasibility %d times - iter %10.0f and %9.0f nodes.\n", lost_feas_count, (double) get_total_iter(lp), (double) lp->bb_totalnodes); lp->spx_status = NUMFAILURE; } } } } /* Update iteration tallies before returning */ lp->total_iter += lp->current_iter; lp->current_iter = 0; lp->total_bswap += lp->current_bswap; lp->current_bswap = 0; FREE(infeasibles); return(lp->spx_status); } /* spx_run */ lprec *make_lag(lprec *lpserver) { int i; lprec *hlp; MYBOOL ret; REAL *duals; /* Create a Lagrangean solver instance */ hlp = make_lp(0, lpserver->columns); if(hlp != NULL) { /* First create and core variable data */ set_sense(hlp, is_maxim(lpserver)); hlp->lag_bound = lpserver->bb_limitOF; for(i = 1; i <= lpserver->columns; i++) { set_mat(hlp, 0, i, get_mat(lpserver, 0, i)); if(is_binary(lpserver, i)) set_binary(hlp, i, TRUE); else { set_int(hlp, i, is_int(lpserver, i)); set_bounds(hlp, i, get_lowbo(lpserver, i), get_upbo(lpserver, i)); } } /* Then fill data for the Lagrangean constraints */ hlp->matL = lpserver->matA; inc_lag_space(hlp, lpserver->rows, TRUE); ret = get_ptr_sensitivity_rhs(hlp, &duals, NULL, NULL); for(i = 1; i <= lpserver->rows; i++) { hlp->lag_con_type[i] = get_constr_type(lpserver, i); hlp->lag_rhs[i] = lpserver->orig_rhs[i]; hlp->lambda[i] = (ret) ? duals[i - 1] : 0.0; } } return(hlp); } STATIC int heuristics(lprec *lp, int mode) /* Initialize / bound a MIP problem */ { lprec *hlp; int status = PROCFAIL; if(lp->bb_level > 1) return( status ); status = RUNNING; lp->bb_limitOF = my_chsign(is_maxim(lp), -lp->infinite); if(FALSE && (lp->int_vars > 0)) { /* 1. Copy the problem into a new relaxed instance, extracting Lagrangean constraints */ hlp = make_lag(lp); /* 2. Run the Lagrangean relaxation */ status = solve(hlp); /* 3. Copy the key results (bound) into the original problem */ lp->bb_heuristicOF = hlp->best_solution[0]; /* 4. Delete the helper heuristic */ hlp->matL = NULL; delete_lp(hlp); } lp->timeheuristic = timeNow(); return( status ); } STATIC int lag_solve(lprec *lp, REAL start_bound, int num_iter) { int i, j, citer, nochange, oldpresolve; MYBOOL LagFeas, AnyFeas, Converged, same_basis; REAL *OrigObj, *ModObj, *SubGrad, *BestFeasSol; REAL Zub, Zlb, Znow, Zprev, Zbest, rhsmod, hold; REAL Phi, StepSize = 0.0, SqrsumSubGrad; /* Make sure we have something to work with */ if(lp->spx_status != OPTIMAL) { lp->lag_status = NOTRUN; return( lp->lag_status ); } /* Allocate iteration arrays */ if(!allocREAL(lp, &OrigObj, lp->columns + 1, FALSE) || !allocREAL(lp, &ModObj, lp->columns + 1, TRUE) || !allocREAL(lp, &SubGrad, get_Lrows(lp) + 1, TRUE) || !allocREAL(lp, &BestFeasSol, lp->sum + 1, TRUE)) { lp->lag_status = NOMEMORY; return( lp->lag_status ); } lp->lag_status = RUNNING; /* Prepare for Lagrangean iterations using results from relaxed problem */ oldpresolve = lp->do_presolve; lp->do_presolve = PRESOLVE_NONE; push_basis(lp, NULL, NULL, NULL); /* Initialize variables (assume minimization problem in overall structure) */ Zlb = lp->best_solution[0]; Zub = start_bound; Zbest = Zub; Znow = Zlb; Zprev = lp->infinite; rhsmod = 0; Phi = DEF_LAGCONTRACT; /* In the range 0-2.0 to guarantee convergence */ /* Phi = 0.15; */ LagFeas = FALSE; Converged= FALSE; AnyFeas = FALSE; citer = 0; nochange = 0; /* Initialize reference and solution vectors; don't bother about the original OF offset since we are maintaining an offset locally. */ /* #define DirectOverrideOF */ get_row(lp, 0, OrigObj); #ifdef DirectOverrideOF set_OF_override(lp, ModObj); #endif OrigObj[0] = get_rh(lp, 0); for(i = 1 ; i <= get_Lrows(lp); i++) lp->lambda[i] = 0; /* Iterate to convergence, failure or user-specified termination */ while((lp->lag_status == RUNNING) && (citer < num_iter)) { citer++; /* Compute constraint feasibility gaps and associated sum of squares, and determine feasibility over the Lagrangean constraints; SubGrad is the subgradient, which here is identical to the slack. */ LagFeas = TRUE; Converged = TRUE; SqrsumSubGrad = 0; for(i = 1; i <= get_Lrows(lp); i++) { hold = lp->lag_rhs[i]; for(j = 1; j <= lp->columns; j++) hold -= mat_getitem(lp->matL, i, j) * lp->best_solution[lp->rows + j]; if(LagFeas) { if(lp->lag_con_type[i] == EQ) { if(fabs(hold) > lp->epsprimal) LagFeas = FALSE; } else if(hold < -lp->epsprimal) LagFeas = FALSE; } /* Test for convergence and update */ if(Converged && (fabs(my_reldiff(hold , SubGrad[i])) > lp->lag_accept)) Converged = FALSE; SubGrad[i] = hold; SqrsumSubGrad += hold * hold; } SqrsumSubGrad = sqrt(SqrsumSubGrad); #if 1 Converged &= LagFeas; #endif if(Converged) break; /* Modify step parameters and initialize ahead of next iteration */ Znow = lp->best_solution[0] - rhsmod; if(Znow > Zub) { /* Handle exceptional case where we overshoot */ Phi *= DEF_LAGCONTRACT; StepSize *= (Zub-Zlb) / (Znow-Zlb); } else #define LagBasisContract #ifdef LagBasisContract /* StepSize = Phi * (Zub - Znow) / SqrsumSubGrad; */ StepSize = Phi * (2-DEF_LAGCONTRACT) * (Zub - Znow) / SqrsumSubGrad; #else StepSize = Phi * (Zub - Znow) / SqrsumSubGrad; #endif /* Compute the new dual price vector (Lagrangean multipliers, lambda) */ for(i = 1; i <= get_Lrows(lp); i++) { lp->lambda[i] += StepSize * SubGrad[i]; if((lp->lag_con_type[i] != EQ) && (lp->lambda[i] > 0)) { /* Handle case where we overshoot and need to correct (see above) */ if(Znow < Zub) lp->lambda[i] = 0; } } /* normalizeVector(lp->lambda, get_Lrows(lp)); */ /* Save the current vector if it is better */ if(LagFeas && (Znow < Zbest)) { /* Recompute the objective function value in terms of the original values */ MEMCOPY(BestFeasSol, lp->best_solution, lp->sum+1); hold = OrigObj[0]; for(i = 1; i <= lp->columns; i++) hold += lp->best_solution[lp->rows + i] * OrigObj[i]; BestFeasSol[0] = hold; if(lp->lag_trace) report(lp, NORMAL, "lag_solve: Improved feasible solution at iteration %d of %g\n", citer, hold); /* Reset variables */ Zbest = Znow; AnyFeas = TRUE; nochange = 0; } else if(Znow == Zprev) { nochange++; if(nochange > LAG_SINGULARLIMIT) { Phi *= 0.5; nochange = 0; } } Zprev = Znow; /* Recompute the objective function values for the next iteration */ for(j = 1; j <= lp->columns; j++) { hold = 0; for(i = 1; i <= get_Lrows(lp); i++) hold += lp->lambda[i] * mat_getitem(lp->matL, i, j); ModObj[j] = OrigObj[j] - my_chsign(is_maxim(lp), hold); #ifndef DirectOverrideOF set_mat(lp, 0, j, ModObj[j]); #endif } /* Recompute the fixed part of the new objective function */ rhsmod = my_chsign(is_maxim(lp), get_rh(lp, 0)); for(i = 1; i <= get_Lrows(lp); i++) rhsmod += lp->lambda[i] * lp->lag_rhs[i]; /* Print trace/debugging information, if specified */ if(lp->lag_trace) { report(lp, IMPORTANT, "Zub: %10g Zlb: %10g Stepsize: %10g Phi: %10g Feas %d\n", (double) Zub, (double) Zlb, (double) StepSize, (double) Phi, LagFeas); for(i = 1; i <= get_Lrows(lp); i++) report(lp, IMPORTANT, "%3d SubGrad %10g lambda %10g\n", i, (double) SubGrad[i], (double) lp->lambda[i]); if(lp->sum < 20) print_lp(lp); } /* Solve the Lagrangean relaxation, handle failures and compute the Lagrangean objective value, if successful */ i = spx_solve(lp); if(lp->spx_status == UNBOUNDED) { if(lp->lag_trace) { report(lp, NORMAL, "lag_solve: Unbounded solution encountered with this OF:\n"); for(i = 1; i <= lp->columns; i++) report(lp, NORMAL, RESULTVALUEMASK " ", (double) ModObj[i]); } goto Leave; } else if((lp->spx_status == NUMFAILURE) || (lp->spx_status == PROCFAIL) || (lp->spx_status == USERABORT) || (lp->spx_status == TIMEOUT) || (lp->spx_status == INFEASIBLE)) { lp->lag_status = lp->spx_status; } /* Compare optimal bases and contract if we have basis stationarity */ #ifdef LagBasisContract same_basis = compare_basis(lp); if(LagFeas && !same_basis) { pop_basis(lp, FALSE); push_basis(lp, NULL, NULL, NULL); Phi *= DEF_LAGCONTRACT; } if(lp->lag_trace) { report(lp, DETAILED, "lag_solve: Simplex status code %d, same basis %s\n", lp->spx_status, my_boolstr(same_basis)); print_solution(lp, 1); } #endif } /* Transfer solution values */ if(AnyFeas) { lp->lag_bound = my_chsign(is_maxim(lp), Zbest); for(i = 0; i <= lp->sum; i++) lp->solution[i] = BestFeasSol[i]; transfer_solution(lp, TRUE); if(!is_maxim(lp)) for(i = 1; i <= get_Lrows(lp); i++) lp->lambda[i] = my_flipsign(lp->lambda[i]); } /* Do standard postprocessing */ Leave: /* Set status variables and report */ if(citer >= num_iter) { if(AnyFeas) lp->lag_status = FEASFOUND; else lp->lag_status = NOFEASFOUND; } else lp->lag_status = lp->spx_status; if(lp->lag_status == OPTIMAL) { report(lp, NORMAL, "\nLagrangean convergence achieved in %d iterations\n", citer); i = check_solution(lp, lp->columns, lp->best_solution, lp->orig_upbo, lp->orig_lowbo, lp->epssolution); } else { report(lp, NORMAL, "\nUnsatisfactory convergence achieved over %d Lagrangean iterations.\n", citer); if(AnyFeas) report(lp, NORMAL, "The best feasible Lagrangean objective function value was %g\n", lp->best_solution[0]); } /* Restore the original objective function */ #ifdef DirectOverrideOF set_OF_override(lp, NULL); #else for(i = 1; i <= lp->columns; i++) set_mat(lp, 0, i, OrigObj[i]); #endif /* ... and then free memory */ FREE(BestFeasSol); FREE(SubGrad); FREE(OrigObj); FREE(ModObj); pop_basis(lp, FALSE); lp->do_presolve = oldpresolve; return( lp->lag_status ); } STATIC int spx_solve(lprec *lp) { int status; MYBOOL iprocessed; lp->total_iter = 0; lp->total_bswap = 0; lp->perturb_count = 0; lp->bb_maxlevel = 1; lp->bb_totalnodes = 0; lp->bb_improvements = 0; lp->bb_strongbranches= 0; lp->is_strongbranch = FALSE; lp->bb_level = 0; lp->bb_solutionlevel = 0; lp->best_solution[0] = my_chsign(is_maxim(lp), lp->infinite); if(lp->invB != NULL) lp->bfp_restart(lp); lp->spx_status = presolve(lp); if(lp->spx_status == PRESOLVED) { status = lp->spx_status; goto Reconstruct; } else if(lp->spx_status != RUNNING) goto Leave; iprocessed = !lp->wasPreprocessed; if(!preprocess(lp) || userabort(lp, -1)) goto Leave; if(mat_validate(lp->matA)) { /* Do standard initializations */ lp->solutioncount = 0; lp->real_solution = lp->infinite; set_action(&lp->spx_action, ACTION_REBASE | ACTION_REINVERT); lp->bb_break = FALSE; /* Do the call to the real underlying solver (note that run_BB is replaceable with any compatible MIP solver) */ status = run_BB(lp); /* Restore modified problem */ if(iprocessed) postprocess(lp); /* Restore data related to presolve (mainly a placeholder as of v5.1) */ Reconstruct: if(!postsolve(lp, status)) report(lp, SEVERE, "spx_solve: Failure during postsolve.\n"); goto Leave; } /* If we get here, mat_validate(lp) failed. */ if(lp->bb_trace || lp->spx_trace) report(lp, CRITICAL, "spx_solve: The current LP seems to be invalid\n"); lp->spx_status = NUMFAILURE; Leave: lp->timeend = timeNow(); if((lp->lag_status != RUNNING) && (lp->invB != NULL)) { int itemp; REAL test; itemp = lp->bfp_nonzeros(lp, TRUE); test = 100; if(lp->total_iter > 0) test *= (REAL) lp->total_bswap/lp->total_iter; report(lp, NORMAL, "\n "); report(lp, NORMAL, "MEMO: lp_solve version %d.%d.%d.%d for %d bit OS, with %d bit REAL variables.\n", MAJORVERSION, MINORVERSION, RELEASE, BUILD, 8*sizeof(void *), 8*sizeof(REAL)); report(lp, NORMAL, " In the total iteration count %.0f, %.0f (%.1f%%) were bound flips.\n", (double) lp->total_iter, (double) lp->total_bswap, test); report(lp, NORMAL, " There were %d refactorizations, %d triggered by time and %d by density.\n", lp->bfp_refactcount(lp, BFP_STAT_REFACT_TOTAL), lp->bfp_refactcount(lp, BFP_STAT_REFACT_TIMED), lp->bfp_refactcount(lp, BFP_STAT_REFACT_DENSE)); report(lp, NORMAL, " ... on average %.1f major pivots per refactorization.\n", get_refactfrequency(lp, TRUE)); report(lp, NORMAL, " The largest [%s] fact(B) had %d NZ entries, %.1fx largest basis.\n", lp->bfp_name(), itemp, lp->bfp_efficiency(lp)); if(lp->perturb_count > 0) report(lp, NORMAL, " The bounds were relaxed via perturbations %d times.\n", lp->perturb_count); if(MIP_count(lp) > 0) { if(lp->bb_solutionlevel > 0) report(lp, NORMAL, " The maximum B&B level was %d, %.1fx MIP order, %d at the optimal solution.\n", lp->bb_maxlevel, (double) lp->bb_maxlevel / (MIP_count(lp)+lp->int_vars), lp->bb_solutionlevel); else report(lp, NORMAL, " The maximum B&B level was %d, %.1fx MIP order, with %.0f nodes explored.\n", lp->bb_maxlevel, (double) lp->bb_maxlevel / (MIP_count(lp)+lp->int_vars), (double) get_total_nodes(lp)); if(GUB_count(lp) > 0) report(lp, NORMAL, " %d general upper-bounded (GUB) structures were employed during B&B.\n", GUB_count(lp)); } report(lp, NORMAL, " The constraint matrix inf-norm is %g, with a dynamic range of %g.\n", lp->matA->infnorm, lp->matA->dynrange); report(lp, NORMAL, " Time to load data was %.3f seconds, presolve used %.3f seconds,\n", lp->timestart-lp->timecreate, lp->timepresolved-lp->timestart); report(lp, NORMAL, " ... %.3f seconds in simplex solver, in total %.3f seconds.\n", lp->timeend-lp->timepresolved, lp->timeend-lp->timecreate); } return( lp->spx_status ); } /* spx_solve */ int lin_solve(lprec *lp) { int status = NOTRUN; /* Don't do anything in case of an empty model */ lp->lag_status = NOTRUN; /* if(get_nonzeros(lp) == 0) { */ if(lp->columns == 0) { default_basis(lp); lp->spx_status = NOTRUN; return( /* OPTIMAL */ lp->spx_status); } /* Otherwise reset selected arrays before solving */ unset_OF_p1extra(lp); free_duals(lp); FREE(lp->drow); FREE(lp->nzdrow); if(lp->bb_cuttype != NULL) freecuts_BB(lp); /* Reset/initialize timers */ lp->timestart = timeNow(); lp->timeheuristic = 0; lp->timepresolved = 0; lp->timeend = 0; /* Do heuristics ahead of solving the model */ if(heuristics(lp, AUTOMATIC) != RUNNING) return( INFEASIBLE ); /* Solve the full, prepared model */ status = spx_solve(lp); if((get_Lrows(lp) > 0) && (lp->lag_status == NOTRUN)) { if(status == OPTIMAL) status = lag_solve(lp, lp->bb_heuristicOF, DEF_LAGMAXITERATIONS); else report(lp, IMPORTANT, "\nCannot do Lagrangean optimization since root model was not solved.\n"); } /* Reset heuristic in preparation for next run (if any) */ lp->bb_heuristicOF = my_chsign(is_maxim(lp), lp->infinite); /* Check that correct status code is returned */ /* peno 26.12.07 status was not set to SUBOPTIMAL, only lp->spx_status Bug occured by a change in 5.5.0.10 when && (lp->bb_totalnodes > 0) was added added status = See UnitTest3 */ /* peno 12.01.08 If an integer solution is found with the same objective value as the relaxed solution then searching is stopped. This by setting lp->bb_break. However this resulted in a report of SUBOPTIMAL solution. For this, && !bb_better(lp, OF_DUALLIMIT, OF_TEST_BE) is added in the test. See UnitTest20 */ if((lp->spx_status == OPTIMAL) && (lp->bb_totalnodes > 0)) { if((lp->bb_break && !bb_better(lp, OF_DUALLIMIT, OF_TEST_BE)) /* || ISMASKSET(lp->trace, TRACE_NOBBLIMIT) */) status = lp->spx_status = SUBOPTIMAL; } return( status ); } MSVMpack1.2/lp_solve_5.5/lpsolve.h0000664000175000017500000000141211141374242015770 0ustar lauerlauer// stdafx.h : include file for standard system include files, // or project specific include files that are used frequently, but // are changed infrequently // #if !defined(AFX_STDAFX_H__22BF6D92_917F_4BDF_B806_0954721EBA95__INCLUDED_) #define AFX_STDAFX_H__22BF6D92_917F_4BDF_B806_0954721EBA95__INCLUDED_ #if _MSC_VER > 1000 #pragma once #endif // _MSC_VER > 1000 // Insert your headers here #define WIN32_LEAN_AND_MEAN // Exclude rarely-used stuff from Windows headers #include // TODO: reference additional headers your program requires here //{{AFX_INSERT_LOCATION}} // Microsoft Visual C++ will insert additional declarations immediately before the previous line. #endif // !defined(AFX_STDAFX_H__22BF6D92_917F_4BDF_B806_0954721EBA95__INCLUDED_) MSVMpack1.2/lp_solve_5.5/README.txt0000664000175000017500000006470411254506753015657 0ustar lauerlauerIntroduction ------------ What is lp_solve and what is it not? The simple answer is, lp_solve is a Mixed Integer Linear Programming (MILP) solver. It is a free (see LGPL for the GNU lesser general public license) linear (integer) programming solver based on the revised simplex method and the Branch-and-bound method for the integers. It contains full source, examples and manuals. lp_solve solves pure linear, (mixed) integer/binary, semi-continuous and special ordered sets (SOS) models. See the reference guide for more information. lp_solve 5.5 ------------ Why a jump from version numbers 5.1 to 5.5 ? This is done to indicate that this is more than just another update. The solver engine was revised and optimised in such a way that performance has improved considerably. Numerical stability is also better resulting in more models that can be solved. The LUSOL bfp is now also the default. In the past, the etaPFI bfp package was the default, but for larger models this leads faster to numerical instabilities and performance problems. Overall, the v5.5 code is faster and more robust than v5.1. This robustness is for example proven by the fact that many more models can now be solved even without scaling. The API hasn't changed very much. There are a couple of new routines and one routine has an extra argument. Some constants got new values. * Fundamental internal change to the solver engine resulting in better performance and numerical stability. Both the LP solver and the B&B solvers are enhanced. * Optimised MILP branch truncation, with reduced cost fixing. * LUSOL bfp is now the default. * Presolve is improved in functionality and performance. * Better handling of degeneracy, with more options. * Store and read options from a file make it easier to set options. * Partial pricing for the primal simplex now works. * Full support for xli_ZIMPL v2.0.3. * The objective function is no longer stored as part of the constraint matrix. * Dual-long step code is in place, but not fully activated yet. * General code cleanup. * Added OBJSENSE and OBJNAME headers in the free MPS format (See MPS file format). * The MathProg xli driver has now the ability to generate a model. * New API routines Start by taking a look at 'Changes compared to version 4', 'Changes from version 5.1 to version 5.5' and 'lp_solve usage' This gives a good starting point. BFP's ----- BFP stands for Basis Factorization Package, which is a unique lp_solve feature. Considerable effort has been put in this new feature and we have big expectations for this. BFP is a generic interface model and users can develop their own implementations based on the provided templates. We are very interested in providing as many different BFPs as possible to the community. lp_solve 5.5 has the LUSOL BFP built in as default engine. In addition two other BFPs are included for both Windows and Linux: bfp_etaPFI.dll, bfp_GLPK.dll for Windows and libbfp_etaPFI.so, libbfp_GLPK.so for Linux. The bfp_etaPFI includes advanced column ordering using the COLAMD library, as well as better pivot management for stability. For complex models, however, the LU factorization approach is much better, and lp_solve now includes LUSOL as one of the most stable engines available anywhere. LUSOL was originally developed by Prof. Saunders at Stanford, and it has now been ported to C and enhanced by Kjell. If you compile BFPs yourself, make sure that under Windows, you use __stdcall convention and use 8 byte alignments. This is needed for the BFPs to work correctly with the general distribution of lp_solve and also to make sharing BFPs as uncomplicated as possible. See the reference guide for more information. XLI's ----- XLI stands for eXternal Language Interface, also a unique lp_solve feature. XLI's are stand-alone libraries used as add-on to lp_solve to make it possible to read and write lp models in a format not natively supported by lp_solve. Examples are CPLEX lp format, LINDO lp format, MathProg format, XML format... See the reference guide for more information. lpsolve API ----------- Don't forget that the API has changed compared to previous versions of lpsolve and that you just can't use the version 5 lpsolve library with your version 4 or older code. That is also the reason why the library is now called lpsolve55.dll/lpsolve55.a. lpsolve55.dll or lpsolve55.a are only needed when you call the lpsolve library via the API interface from your program. The lp_solve program is still a stand-alone executable program. There are examples interfaces for different language like C, VB, C#, VB.NET, Java, Delphi, and there is now also even a COM object to access the lpsolve library. This means that the door is wide-open for using lp_solve in many different situations. Thus everything that is available in version 4 is now also available in version 5 and already much more! See the reference guide for more information. Conversion between lp modeling formats -------------------------------------- Note that lp2mps and mps2lp don't exist anymore. However this functionality is now implemented in lp_solve: lp2mps can be simulated as following: lp_solve -parse_only -lp infile -wmps outfile mps2lp can be simulated as following: lp_solve -parse_only -mps infile -wlp outfile via the -rxli option, a model can be read via an XLI library and via the -wxli option, a model can be written via an XLI library. How to build the executables yourself. --------------------------------------- At this time, there are no Makefiles yet. However for the time being, there are batch files/scripts to build. For the Microsoft compiler under Windows, use cvc6.bat, for the gnu compiler under Windows, use cgcc.bat and for Unix/Linux, use the ccc shell script (sh ccc). See the reference guide for more information. IDE --- Under Windows, there is now also a very user friendly lpsolve IDE. Check out LPSolveIDE See the reference guide for more information. Documentation (reference guide) ------------------------------- See lp_solve55.chm for a Windows HTML help documentation file. The html files are also in lp_solve_5.5_doc.tar.gz. Start with index.htm Also see http://lpsolve.sourceforge.net/ for a on-line documentation Change history: --------------- 17/05/05 version 5.5.0.0 - Beta release of version 5.5 ??/??/05 version 5.5.0.1 - ? 26/06/05 version 5.5.0.2 - ? 29/06/05 version 5.5.0.3 - ? 16/08/05 version 5.5.0.4 - There are no API changes - The LUSOL message routine could generate a crash under some cicumstances. Fixed - A crash could occur when building the model in add_row_mode. Fixed. - write_params didn't write the PRESOLVE and PRESOLVELOOPS correctly. Fixed. - write_params didn't write constants with value 0. Fixed. - The library did not compile under msdev 2002 (VC 7.0 _MSC_VER 1300). Fixed. - There were some problems with printing long long variables which could generate a crash. Fixed. - An overflow error could occur because memory was sometimes overwritten. Fixed. - Presolve routines are revised. They are again improved and made faster. Also some problems with it are fixed (possible crashes). - Solver revised. Again made faster and more stable. - get_row/get_column returned FALSE if the row/column is empty. Fixed. - get_rowex/get_columnex now returns -1 if and error is detected. This instead of 0. This to know the distinction between an empty row/column and an error. - set_bounds had a possible problem when min and max are equal. Fixed. - A crash/damage error could occur when rows/columns are added after a solve. Fixed. - The my_chsign macro in lp_types.h gave warnings with some compilers. Fixed. - The lp_solve program now returns 255 if an unexpected error occurs. Before this was 1 But this interferes with the lpsolve library return codes. - With the lp_solve program, debug and print modes were not written correctly in a specified parameter file. Fixed. - With the lp_solve program, presolveloops was not set correctly. Fixed. 17/09/05 version 5.5.0.5 - In some cases, SOS restrictions were not optimized till optimality. Fixed. - Presolve sometimes generated 'Column -xxx out of range during presolve' with a possible crash. - Presolve sometimes removed integer and/or semi-cont variables that should not be deleted. Fixed. - B&B sometimes didn't find the most optimal solution. Fixed. - Internal constant COMP_EQUAL renamed to COMP_PREFERNONE because this could interfere with a define in the standard header files. - The lp parser had problems with variables starting with INF and there is a + or - sign just before it. Fixed. - Added options -presolvem, -presolvefd, -presolvebnd, -presolved, -presolveslk - Updated documentation. put_bb_branchfunc, put_bb_nodefunc, set_epslevel, dualize_lp, set_basisvar 16/11/05 version 5.5.0.6 - set_add_rowmode should not be called after a solve. There is now a test in this routine when this is done and it then returns FALSE. - When an empty string ("") as filename is provided to set_outputfile, then output is completely ignored. - In some cases, SOS models did not solve to their most optimal solution. - There was as problem with get_sensitivity_objex. Calling it (sometimes only after multiple times) resulted in protection errors/core dumps. - When a model has no constraints, it did not solve most of the times. - column_in_lp didn't work anymore. - Large upper bounds could make the model unstable. A change was made to fix this. - set_improve could let crash the model. - lp_params.c used the non-ANSI function unlink(). Changed to ANSI function remove(). - Presolve is again revised considerably. - SOS handling is improved when there are a lot of SOS constraints. - Limited constraint-to-SOS1 presolve to constraints with at least 4 variables. - Limited bound tightening presolve loops. 12/02/06 version 5.5.0.7 - When SOS restrictions are added after a previous solve, a crash could occur. - Optimized renaming a variable when the new name is equal to the old name. - A possible crash could occur when presolve was enabled - The constant ANTIDEGEN_DEFAULT is changed. ANTIDEGEN_INFEASIBLE is removed from it. This constant should not be used unless you have some very tight and hard to solve models where the optimal solution numerically straddles infeasibility. - There was a possible problem with set_row(ex). It sometimes wrongfully changed the row. - When integer variables were scaled, it could happen that because of rounding errors, a loop was created. - Sometimes integer models kept on looping in the B&B algorithm. - A memory overrun could occur when an initial basis is set. This when variable names are in Rnnn format and constraint names in Cnnn format. - Some fixes are made in presolve. - On 64-bit systems, compiler warnings were given and some code worked wrong resulting in wrong results. - lp_solve.c didn't compile with some compilers because if a very deep nested if statement. - The distributed files now have the version number include in the filename. For example lp_solve_5.5.0.7_exe.zip This for a possible move to SourceForge in the (near?) future. - When illegal bounds are specified in the MPS format (lower bound larger than upper bound) then a warning was given but the illegal bound was just ignored and the model was solved. This resulted in a solution that did not comply to the original model. Now the message is seen as an error and solving is aborted. 06/09/06 version 5.5.0.8 - When presolve is active and columns are removed and there are SOS constraints, then presolve had an error which could result in hanging while solve or maybe wrong solutions. - set_row(ex) set wrong values when used after a previous solve and scaling is active. - disabled PRESOLVE_REDUCEMIP since it is very rare that this is effective, and also that it adds code complications and delayed presolve effects that are not captured properly. - made routine guess_basis available for all languages (now exported by the dll). The routine is now also documented. - some bug corrections in guess_basis. - Corrected a problem with add_column(ex) when add_rowmode is enabled. - write_lp now wraps long lines over multiple lines to make it more readable. - A compilation warning/error sometimes occured on is_fixedvar in lp_lusol.c with some compilers. - Added options -wxlisol and -wxlisolopt to lp_solve program to write a solution file for those XLIs that support it. - Updated CPLEX XLI to support constants in objective. - Added documentation on infeasible models, guess_basis, DIMACS models, CPLEX format, Zimpl, GNU Mathprog. Corrected/updated documentation on get_col_name, get_row_name, get_nameindex, write_xli, External Language Interfaces. - The mps reader was improved for the rarely cases where the same elements are provided multiple times. These are now added. - Revised the java unittest example because it gave some errors that it shouldn't give. 07/10/06 version 5.5.0.9 - set_row(ex) could sometimes set wrong values in the model. - Sometimes models with semi-cont variables which are also integer and scaling is active, a solution was returned that is not most optimal or it returns infeasible. - write_mps didn't write semi-cont variables with an infinite upper bound. - When presolve can solve the model on its own and objective direction is maximize then a wrong sign was shown in the reported price on screen. - write_lp writes constraint and bounds in the same way if a constraint is not named. If a constraint only has one variable then it looks like a bound. This can give problems because when a constraint is interpreted as bound and it is negative then the problem definition changes. Therefore a constraint which is not named and having only one variable in it is getting a name to make sure it is interpreted as a constraint. - The lp_solve program didn't interprete the PRESOLVED solve return code very well. Fixed. - bfp_GLPK and xli_MathProg are now compiled against GLPK 4.11 - When an integer model is aborted before the most optimal solution is found (timeout or break at first, ...) solve returned OPTIMAL (0) instead of SUBOPTIMAL (1). This is now corrected. 14/01/07 version 5.5.0.10 - If a model has integer variables, but the model is already integer optimal in the simplex fase, then it was reported as suboptimal feasible. - get_objective, get_variables, get_ptr_variables, get_constraints, get_ptr_constraints, get_primal_solution reported 'not a valid basis' when presolve is active and the model is entirely solved by presolve. - presolve on a model with SOS variables sometimes went wrong. - presolve on a model with SOS variables where infeasibility is detected crashed. - read_bas could fail when not all constraints had names or had names like default variable names. - A crash could occur with set_row(ex) in rowmode. - The lp format has been extended with a free section to define free variables. - bfp_GLPK and xli_MathProg are now compiled against GLPK 4.13 - fixed bug in the pseudocost logic that can blow up subsequent pseudocost values in that branch and make them almost random. - In some rare cases a memory overrun could occur when constraints are added after a previous solve. - Made the copy_lp routine work. Note that information about the optimisation of the original model is not copied (at this time). Only the model is. - Fixed a bug in the hashing routines that had only influence in some rare cases in the MATLAB, O-Matrix, Scilab, Octave, Python drivers. - coldual sometimes worked on a uninitialised variable value with unpredictable results. 27/12/07 version 5.5.0.11 - Fixed a problem in presolve. Sometimes an array-index-out-of-bounds error occured. - Added a makefile for Linux. - When adding constraints, in some rare cases a memory overrun could occur resulting in a crash. - add_constraintex with count=0 and row=colno=NULL gave a protection error. several XLIs didn't work anymore because of this. - set_constr_type sometimes set wrong signs for the coefficient matrix when add_rowmode is on. - presolve did an unnecessary extra loop. Also a test is added to stop presolve when very few changes are done. - for very large models, a request of much more memory than is reasonable could occur. Fixed. - Modified LINDO XLI to read keywords also not at column 1 and to accept an empty objective function. Previously this wat not possible. - In some rare cases, numbers very close to their integer values (for example 11276.999999999998) were truncated to their ceiling value (for example 11276) instead of rounded (for example 11277). - Solved a problem with presolve with an all-int constraint. - Solved a problem with presolve coldominate - Added stronger checking of the MPS format. Fields that must be blank are now also tested accordingly so that if data is there that it is not ignored as before. - FREE MPS format was not read ok if row/column name were all numbers or a FR, MI, PL, BV bound was defined. Fixed. - The lp-format now also supports a bin(ary) section to define binary variables. - When an integer model is aborted before the most optimal solution is found via break at first or break at value, solve returned OPTIMAL (0) instead of SUBOPTIMAL (1). This is now corrected. Problem occured in version 5.5.0.10 - Fixed a problem with del_constraint. Constraints names were not shifted and reported variable result was incorrect. - read_XLI failed with MathProg if datamodel was provided with "" when there is no datamodel. NULL was expected in the past. "" is now also accepted. - Added an XLI to read Xpress lp files. - Added routines MPS_writefileex, write_lpex. - Added options -o0, -o1 to lp_solve command driven program to specify if objective is in basis or not. - Added new information in the reference guide: - Linear programming basics - Presolve - Xpress lp files 04/01/08 version 5.5.0.11 - There was an error in the lp-parser resulting is misreading the model in many cases. This was fixed in the existing release and an update of following files is posted: lp_solve_5.5.0.11_exe.tar.gz lp_solve_5.5.0.11_dev.tar.gz lp_solve_5.5.0.11_source.tar.gz lp_solve_5.5.0.11_exe.zip lp_solve_5.5.0.11_dev.zip 13/03/08 version 5.5.0.12 - When NODE_RCOSTFIXING (bound tightening during B&B) (enabled by default) was enabled some models were not solved to optimality. - In following situation a (sub-optimal) solution was returned while no integer solution isn't found yet at this time. - The model contains integers - A break at first is set - A timeout is set - The timeout occurs before a first integer solution is found - When the timeout occurs, the simplex algorithm is in phase 2 and has a feasible (but non-integer) solution, but not optimal yet. - If an integer solution is found with the same objective value as the relaxed solution then B&B is stopped. However this resulted in a report of a SUBOPTIMAL solution while this is not true. The found solution is then optimal. - On 64-bit Linux systems crashes occured when information is printed via variable argument routines. - There was a warning about redefinition of MAXINT32, MAXUINT32, MAXINT64, MAXUINT64 when compiled with MS Visual C 2008. - The reference guide now also contains the Java documentation. 03/08/08 version 5.5.0.13 - The code should now completely be reentrant and thread safe. Especially the lp-parser, but also the solver code itself used static variables which made it not reentrant. The lp parser code has changed considerably for this. Also the lex and yacc code had to be made reentrant. This is only tested with GNU flex and bison. Not with lex and yacc. This should be no problem since the corresponding c files are included with the source so people don't have to build these themselves. - commonlib.c/h were also under BFP/BFP_LUSOL/LUSOL while a more advanced version is also under the shared directory. The one from LUSOL is removed. - If objective coefficients are all integer and the columns are integer or objective coefficients are zero, then B&B can stop when the objective function equals ceil/floor(real objective) which results in a faster solving process. This did not work anymore and is now fixed. - The lpsolve IDE is now also on sourceforge (previously it was a link to another site). Also the sources are included. 02/02/09 version 5.5.0.14 - The lp format now allows spaces between the row label and the colon. - Added better error handling in the copy_lp API - Timeout in a MIP model sometimes resulted in an endless loop - Revised isnan call for gnu compilers - Removed some extra static variables for better reentrance support. - REPORT_Objective now reports large objective values (>1e-5) with better precision - On Windows the binaries are again compiled with compiler optimization /O2 for better performance. - Compiled and tested on Windows and Linux 64-bit. 64-bit binaries are now provided. Changed project files and compile scripts for 64-bit compilation. Binaries are now located in a subdirectory bin\platform - Added PHP driver so that lpsolve can be called from PHP - When an MPS file is created, upper bounds were written before lower bounds. Now it is the other way around. First lower bounds and then upper bounds. - The MPS reader could not handle negative lower bounds where the lower bound was specified after the upper bound. - The MPS write now writes the implicit lower bound of zero if the variable has no lower bound and it is integer. This to make sure that other solvers (like CPLEX) interprete the variable as integer and not binary. - The LINDO XLI parser interpreted negative lower and upper bounds as positive - Added the option -stat to the lp_solve driver program. It prints statistics of the model like number of rows/columns used and smalled and largest value in objective, RHS and coefficient matrix. - Added the option -plp to the lp_solve driver program. It prints the model via the print_lp API function. 09/09/09 version 5.5.0.15 - Improved guess_basis - set_row(ex) corrections. Actually completely revised the routine. Sometimes the matrix was corrupted after the call. - When in set_add_row mode, all API calls can now be used. For example printing or writing the model, retrieving data from the model and so on are now all possible in that mode. Will help greatly when debugging your models. - Sometimes an integer model is reported infeasible while it isn't because the integer solution is much different from the relaxed (real) model. Then API call set_bb_depthlimit can be used to increase the default B&B depth. However its new value was not used for the depth limit of an individual variabled which could result in still infeasible results. - modified the demo program not to use the str_ versions of API calls, because they are not performant and not intended to be used in real programs. - Added an lpsolve driver to Sysquake. - Added an lpsolve driver to FreeMat. - Added an lpsolve driver to Euler. - Added an Access example. - Added documentation to use lpsolve from Sage via the existing Python driver. - Changed the second parameter to read_mps, read_MPS, read_freemps and read_freeMPS from verbose to options. These routines now supports via this options parameter the native IBM interpretation of integer variables and allows to negate the objective constant. This is also supported by the lp_solve command line program via the -mps_ibm and -mps_negobjconst options. This is also supported by the IDE in the options tab. - Removed read_LPhandle and read_MPShandle from the lprec structure. On their place there is now read_LP and read_MPS. The handle functions are not usable anyway under windows as dll because the FILE structure is searched in the dll space and therefore not working. read_LP and read_MPS work on the file name and always work. Since these handle routines were not documented anyway and the lp structure should not be accessed by applications (except XLI and BFP drivers) this change should not give any (compatibility) problem at all. - write_lp/write_LP write just a + or - if the factor to a variable is +1 or -1 However when the number was not exactly one, for example 1.0000000000001, then the test on equal to one gave false, but the writing was a 1 because only 12 significant digits are written. The result was that the 1 was written in that case. Not an error, but when lp files are compared, this is enoying. Now this is solved. When a +1 or -1 would be written then alyways only + and - is written and +1 or -1 will never occur again. - When a message function is set via put_msgfunc, in message MSG_LPOPTIMAL it was not possible to get the solution. Now it is. Also when messages MSG_MILPFEASIBLE, MSG_MILPBETTER, MSG_MILPEQUAL were catched the returned solution was the one from the previous MIP solution. This is now also fixed. With this fix, the IDE now also shows the relaxed solution (column LP Optimal). - Extended the MATLAB, O-Matrix, Scilab, Octave, Python, PHP and of course the new Sysquake, FreeMat and Euler drivers to support string constants. See the reference guide. - Compiled and tested lpsolve on MAC OSX 10.4.8 (Intel). Compilation scripts for this platform were added and revised and binaries are provided to download. - Revised the c# and vb.net lpsolve code to pass arrays back and forth to the dll to make it also work on 64 bit systems. - IDE enhancements: - Can talk to the lpsolve55.dll large address aware version so access to 3.4G 32 bit memory. - Can write and read lp_solve parameter files ( type .lpi) via Options, Solver params, so it is easy to save a readable file of parameters for a particular problem class when it is found. The file can then be collected by the -rpar exe param or the read_params() API. - Added Options, Reset to solver defaults to go back to all lp_solve defaults. - Added in Help a link to the online help files. - Resized the help, main and statistics windows for Vista. - Added the Xpress XLI to the setup. - Use the latest dlls, especially lpsolve55.dll, in the setup. - Added the two new MPS options for IBM integer variables and negate objective constant. - Added the option to ignore integer restrictions. 17/09/09 version 5.5.0.15b - objfrom values where not correct if scaling is active. Routine to calculate these values and the objective from-till values is revised and made a bit more performant. - write_lp did not write all column data. For objective function and constraints. We are thrilled to hear from you and your experiences with this new version. The good and the bad. Also we would be pleased to hear about your experiences with the different BFPs on your models. Please send reactions to: Peter Notebaert: lpsolve@peno.be Kjell Eikland: kjell.eikland@broadpark.no MSVMpack1.2/lp_solve_5.5/configure.ac0000664000175000017500000000206711127454706016440 0ustar lauerlauerAC_PREREQ(2.52) AC_INIT([lpsolve],5.5.0.14,[], []) AC_CONFIG_SRCDIR(lp_simplex.c) AC_CANONICAL_HOST SHARED_LIB=liblpsolve55.so SO=.so case $host_os in hp*|HP*) DEF=-ldld case `uname -m` in ia64) SO=.so;; *) SO=.sl;; esac if test "$GCC" = yes; then CCSHARED="-fPIC"; else CCSHARED="+z"; fi;; CYGWIN*) SO=.dll;; linux) CCSHARED="-fPIC";; apple-darwin) DEF=-ldl -idirafter /usr/include/sys -DINTEGERTIME -Wno-long-double ;; OpenUNIX*|UnixWare*) DEF='-dy -DNOLONGLONG' if test "$GCC" = "yes" then CCSHARED="-fPIC" else CCSHARED="-K PIC" fi;; SCO_SV*) DEF='-dy -DNOLONGLONG' if test "$GCC" = "yes" then CCSHARED="-fPIC" else CCSHARED="-Kpic -belf" fi;; *) esac AC_SUBST(SO) AC_SUBST(CCSHARED) AC_SUBST(DEF) AC_SUBST(SHARED_LIB) AC_PROG_CC if test "x$GCC" != "xyes" then echo "*** non GNU CC compiler detected." echo "*** This package has not been tested very well with non GNU compilers" fi AC_PROG_INSTALL AC_CONFIG_FILES([ \ Makefile \ ]) AC_OUTPUT MSVMpack1.2/lp_solve_5.5/lp_MDO.h0000664000175000017500000000037411141374245015427 0ustar lauerlauer#ifndef HEADER_MDO #define HEADER_MDO #include "lp_types.h" #ifdef __cplusplus extern "C" { #endif int __WINAPI getMDO(lprec *lp, MYBOOL *usedpos, int *colorder, int *size, MYBOOL symmetric); #ifdef __cplusplus } #endif #endif /* HEADER_MDO */ MSVMpack1.2/lp_solve_5.5/lp_types.h0000664000175000017500000002307711141374255016162 0ustar lauerlauer#ifndef HEADER_lp_types #define HEADER_lp_types #ifdef WIN32 #include #endif /* Define data types */ /* ------------------------------------------------------------------------- */ #ifndef LLONG #if defined __BORLANDC__ #define LLONG __int64 #elif !defined _MSC_VER || _MSC_VER >= 1310 #define LLONG long long #else #define LLONG __int64 #endif #endif #ifndef COUNTER #define COUNTER LLONG #endif #ifndef REAL #define REAL double #endif #ifndef REALXP #if 1 #define REALXP long double /* Set local accumulation variable as long double */ #else #define REALXP REAL /* Set local accumulation as default precision */ #endif #endif #ifndef LREAL #if 0 #define LREAL long double /* Set global solution update variable as long double */ #else #define LREAL REAL /* Set global solution update variable as default precision */ #endif #endif #define RESULTVALUEMASK "%18.12g" /* Set fixed-format real-valued output precision; suggested width: ABS(exponent of DEF_EPSVALUE)+6. */ #define INDEXVALUEMASK "%8d" /* Set fixed-format integer-valued output width */ #ifndef DEF_STRBUFSIZE #define DEF_STRBUFSIZE 512 #endif #ifndef MAXINT32 #define MAXINT32 2147483647 #endif #ifndef MAXUINT32 #define MAXUINT32 4294967295 #endif #ifndef MAXINT64 #if defined _LONGLONG || defined __LONG_LONG_MAX__ || defined LLONG_MAX #define MAXINT64 9223372036854775807ll #else #define MAXINT64 9223372036854775807l #endif #endif #ifndef MAXUINT64 #if defined _LONGLONG || defined __LONG_LONG_MAX__ || defined LLONG_MAX #define MAXUINT64 18446744073709551615ll #else #define MAXUINT64 18446744073709551615l #endif #endif #ifndef CHAR_BIT #define CHAR_BIT 8 #endif #ifndef MYBOOL #define MYBOOL unsigned char /* Conserve memory, could be unsigned int */ #endif /* Constants */ /* ------------------------------------------------------------------------- */ #ifndef NULL #define NULL 0 #endif /* Byte-sized Booleans and extended options */ #define FALSE 0 #define TRUE 1 #define AUTOMATIC 2 #define DYNAMIC 4 /* Sorting and comparison constants */ #define COMP_PREFERCANDIDATE 1 #define COMP_PREFERNONE 0 #define COMP_PREFERINCUMBENT -1 /* Library load status values */ #define LIB_LOADED 0 #define LIB_NOTFOUND 1 #define LIB_NOINFO 2 #define LIB_NOFUNCTION 3 #define LIB_VERINVALID 4 #define LIB_STR_LOADED "Successfully loaded" #define LIB_STR_NOTFOUND "File not found" #define LIB_STR_NOINFO "No version data" #define LIB_STR_NOFUNCTION "Missing function header" #define LIB_STR_VERINVALID "Incompatible version" #define LIB_STR_MAXLEN 23 /* Compiler/target settings */ /* ------------------------------------------------------------------------- */ #if (defined _WIN32) || (defined WIN32) || (defined _WIN64) || (defined WIN64) # define __WINAPI WINAPI #else # define __WINAPI #endif #if (defined _WIN32) || (defined WIN32) || (defined _WIN64) || (defined WIN64) # define __VACALL __cdecl #else # define __VACALL #endif #ifndef __BORLANDC__ #ifdef _USRDLL #if 1 #define __EXPORT_TYPE __declspec(dllexport) #else /* Set up for the Microsoft compiler */ #ifdef LP_SOLVE_EXPORTS #define __EXPORT_TYPE __declspec(dllexport) #else #define __EXPORT_TYPE __declspec(dllimport) #endif #endif #else #define __EXPORT_TYPE #endif #ifdef __cplusplus #define __EXTERN_C extern "C" #else #define __EXTERN_C #endif #else /* Otherwise set up for the Borland compiler */ #ifdef __DLL__ #define _USRDLL #define __EXTERN_C extern "C" #ifdef __READING_THE_DLL #define __EXPORT_TYPE __import #else #define __EXPORT_TYPE __export #endif #else #define __EXPORT_TYPE #define __EXTERN_C extern "C" #endif #endif #if 0 #define STATIC static #else #define STATIC #endif #if !defined INLINE #if defined __cplusplus #define INLINE inline #elif (defined _WIN32) || (defined WIN32) || (defined _WIN64) || (defined WIN64) #define INLINE __inline #else #define INLINE static #endif #endif /* Function macros */ /* ------------------------------------------------------------------------- */ #define my_limitrange(x, lo, hi) ((x) < (lo) ? (lo) : ((x) > (hi) ? (hi) : (x))) #ifndef my_mod #define my_mod(n, m) ((n) % (m)) #endif #define my_if(t, x, y) ((t) ? (x) : (y)) #define my_sign(x) ((x) < 0 ? -1 : 1) #if 0 #define my_chsign(t, x) ( ((t) && ((x) != 0)) ? -(x) : (x)) #else #define my_chsign(t, x) ( (2*((t) == 0) - 1) * (x) ) /* "Pipelined" */ #endif #define my_flipsign(x) ( fabs((REAL) (x)) == 0 ? 0 : -(x) ) #define my_roundzero(val, eps) if (fabs((REAL) (val)) < eps) val = 0 #define my_avoidtiny(val, eps) (fabs((REAL) (val)) < eps ? 0 : val) #if 1 #define my_infinite(lp, val) ( (MYBOOL) (fabs(val) >= lp->infinite) ) #else #define my_infinite(lp, val) is_infinite(lp, val) #endif #define my_inflimit(lp, val) ( my_infinite(lp, val) ? lp->infinite * my_sign(val) : (val) ) #if 0 #define my_precision(val, eps) ((fabs((REAL) (val))) < (eps) ? 0 : (val)) #else #define my_precision(val, eps) restoreINT(val, eps) #endif #define my_reldiff(x, y) (((x) - (y)) / (1.0 + fabs((REAL) (y)))) #define my_boundstr(x) (fabs(x) < lp->infinite ? sprintf("%g",x) : ((x) < 0 ? "-Inf" : "Inf") ) #ifndef my_boolstr #define my_boolstr(x) (!(x) ? "FALSE" : "TRUE") #endif #define my_basisstr(isbasic) ((isbasic) ? "BASIC" : "NON-BASIC") #define my_simplexstr(isdual) ((isdual) ? "DUAL" : "PRIMAL") #define my_plural_std(count) (count == 1 ? "" : "s") #define my_plural_y(count) (count == 1 ? "y" : "ies") #define my_lowbound(x) ((FULLYBOUNDEDSIMPLEX) ? (x) : 0) /* Bound macros usable for both the standard and fully bounded simplex */ /* ------------------------------------------------------------------------- */ /* #define my_lowbo(lp, varnr) ( lp->isfullybounded ? lp->lowbo[varnr] : 0.0 ) #define my_upbo(lp, varnr) ( lp->isfullybounded ? lp->upbo[varnr] : lp->lowbo[varnr] + lp->upbo[varnr] ) #define my_rangebo(lp, varnr) ( lp->isfullybounded ? lp->upbo[varnr] - lp->lowbo[varnr] : lp->upbo[varnr] ) */ #define my_lowbo(lp, varnr) ( 0.0 ) #define my_upbo(lp, varnr) ( lp->lowbo[varnr] + lp->upbo[varnr] ) #define my_rangebo(lp, varnr) ( lp->upbo[varnr] ) #define my_unbounded(lp, varnr) ((lp->upbo[varnr] >= lp->infinite) && (lp->lowbo[varnr] <= -lp->infinite)) #define my_bounded(lp, varnr) ((lp->upbo[varnr] < lp->infinite) && (lp->lowbo[varnr] > -lp->infinite)) /* Forward declarations */ /* ------------------------------------------------------------------------- */ typedef struct _lprec lprec; typedef struct _INVrec INVrec; union QSORTrec; #ifndef UNIONTYPE #ifdef __cplusplus #define UNIONTYPE #else #define UNIONTYPE union #endif #endif /* B4 factorization optimization data */ typedef struct _B4rec { int *B4_var; /* Position of basic columns in the B4 basis */ int *var_B4; /* Variable in the B4 basis */ int *B4_row; /* B4 position of the i'th row */ int *row_B4; /* Original position of the i'th row */ REAL *wcol; int *nzwcol; } B4rec; #define OBJ_STEPS 5 typedef struct _OBJmonrec { lprec *lp; int oldpivstrategy, oldpivrule, pivrule, ruleswitches, limitstall[2], limitruleswitches, idxstep[OBJ_STEPS], countstep, startstep, currentstep, Rcycle, Ccycle, Ncycle, Mcycle, Icount; REAL thisobj, prevobj, objstep[OBJ_STEPS], thisinfeas, previnfeas, epsvalue; char spxfunc[10]; MYBOOL pivdynamic; MYBOOL isdual; MYBOOL active; } OBJmonrec; typedef struct _edgerec { REAL *edgeVector; } edgerec; typedef struct _pricerec { REAL theta; REAL pivot; REAL epspivot; int varno; lprec *lp; MYBOOL isdual; } pricerec; typedef struct _multirec { lprec *lp; int size; /* The maximum number of multiply priced rows/columns */ int used; /* The current / active number of multiply priced rows/columns */ int limit; /* The active/used count at which a full update is triggered */ pricerec *items; /* Array of best multiply priced rows/columns */ int *freeList; /* The indeces of available positions in "items" */ UNIONTYPE QSORTrec *sortedList; /* List of pointers to "pricerec" items in sorted order */ REAL *stepList; /* Working array (values in sortedList order) */ REAL *valueList; /* Working array (values in sortedList order) */ int *indexSet; /* The final exported index list of pivot variables */ int active; /* Index of currently active multiply priced row/column */ int retries; REAL step_base; REAL step_last; REAL obj_base; REAL obj_last; REAL epszero; REAL maxpivot; REAL maxbound; MYBOOL sorted; MYBOOL truncinf; MYBOOL objcheck; MYBOOL dirty; } multirec; #endif /* HEADER_lp_types */ MSVMpack1.2/lp_solve_5.5/lpsolve55/0000775000175000017500000000000011254510565016000 5ustar lauerlauerMSVMpack1.2/lp_solve_5.5/lpsolve55/ccc.aix0000664000175000017500000000404411153276677017250 0ustar lauerlauer: src='../lp_MDO.c ../shared/commonlib.c ../shared/mmio.c ../shared/myblas.c ../ini.c ../fortify.c ../colamd/colamd.c ../lp_rlp.c ../lp_crash.c ../bfp/bfp_LUSOL/lp_LUSOL.c ../bfp/bfp_LUSOL/LUSOL/lusol.c ../lp_Hash.c ../lp_lib.c ../lp_wlp.c ../lp_matrix.c ../lp_mipbb.c ../lp_MPS.c ../lp_params.c ../lp_presolve.c ../lp_price.c ../lp_pricePSE.c ../lp_report.c ../lp_scale.c ../lp_simplex.c ../lp_SOS.c ../lp_utils.c ../yacc_read.c' type xlc >/dev/null 2>&1 if [ $? = 0 ] then c=xlc else c=cc fi #determine platform (32/64 bit) >/tmp/platform.c echo '#include '>>/tmp/platform.c echo '#include '>>/tmp/platform.c echo 'main(){printf("ux%d", (int) (sizeof(void *)*8));}'>>/tmp/platform.c $c /tmp/platform.c -o /tmp/platform PLATFORM=`/tmp/platform` rm /tmp/platform /tmp/platform.c >/dev/null 2>&1 mkdir bin bin/$PLATFORM >/dev/null 2>&1 #check if this system has the isnan function >/tmp/isnan.c echo '#include '>>/tmp/isnan.c echo '#include '>>/tmp/isnan.c echo '#include '>>/tmp/isnan.c echo 'main(){isnan(0);}'>>/tmp/isnan.c $c /tmp/isnan.c -o /tmp/isnan $math >/dev/null 2>&1 if [ $? = 0 ] then NOISNAN= else NOISNAN=-DNOISNAN fi rm /tmp/isnan.c /tmp/isnan >/dev/null 2>&1 def= dl=-ldl so=y opts='-O2' $c -s -c -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd $opts $def $NOISNAN -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine $src ar rv bin/$PLATFORM/liblpsolve55.a `echo $src|sed s/[.]c/.o/g|sed 's/[^ ]*\///g'` ranlib bin/$PLATFORM/liblpsolve55.a if [ "$so" != "" ] then $c -s -c -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd -I. $opts $NOISNAN -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine $src tr -d '\r' <../lp_solve.def | sed -e "s/^EXPORTS$//g" >liblpsolve55.exp rm liblpsolve55.so 2>/dev/null $c -bM:SRE -bE:liblpsolve55.exp -bnoentry -o bin/$PLATFORM/liblpsolve55.so `echo $src|sed s/[.]c/.o/g|sed 's/[^ ]*\///g'` -lc -lm -ldl fi rm *.o 2>/dev/null MSVMpack1.2/lp_solve_5.5/lpsolve55/ccc.hp-ux0000664000175000017500000000352311153276715017522 0ustar lauerlauer: src='../lp_MDO.c ../shared/commonlib.c ../shared/mmio.c ../shared/myblas.c ../ini.c ../fortify.c ../colamd/colamd.c ../lp_rlp.c ../lp_crash.c ../bfp/bfp_LUSOL/lp_LUSOL.c ../bfp/bfp_LUSOL/LUSOL/lusol.c ../lp_Hash.c ../lp_lib.c ../lp_wlp.c ../lp_matrix.c ../lp_mipbb.c ../lp_MPS.c ../lp_params.c ../lp_presolve.c ../lp_price.c ../lp_pricePSE.c ../lp_report.c ../lp_scale.c ../lp_simplex.c ../lp_SOS.c ../lp_utils.c ../yacc_read.c' c=cc #determine platform (32/64 bit) >/tmp/platform.c echo '#include '>>/tmp/platform.c echo '#include '>>/tmp/platform.c echo 'main(){printf("ux%d", (int) (sizeof(void *)*8));}'>>/tmp/platform.c $c /tmp/platform.c -o /tmp/platform PLATFORM=`/tmp/platform` rm /tmp/platform /tmp/platform.c >/dev/null 2>&1 mkdir bin bin/$PLATFORM >/dev/null 2>&1 #check if this system has the isnan function >/tmp/isnan.c echo '#include '>>/tmp/isnan.c echo '#include '>>/tmp/isnan.c echo '#include '>>/tmp/isnan.c echo 'main(){isnan(0);}'>>/tmp/isnan.c $c /tmp/isnan.c -o /tmp/isnan $math >/dev/null 2>&1 if [ $? = 0 ] then NOISNAN= else NOISNAN=-DNOISNAN fi rm /tmp/isnan.c /tmp/isnan >/dev/null 2>&1 def= dl=-ldld so=y opts='-O3' $c -s -c -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd $opts $def $NOISNAN -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine $src ar rv bin/$PLATFORM/liblpsolve55.a `echo $src|sed s/[.]c/.o/g|sed 's/[^ ]*\///g'` ranlib bin/$PLATFORM/liblpsolve55.a if [ "$so" != "" ] then $c -O +Z -c -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd -I. $opts $NOISNAN -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine $src ld -b -o bin/$PLATFORM/liblpsolve55.sl *.o fi rm *.o 2>/dev/null MSVMpack1.2/lp_solve_5.5/lpsolve55/cvc8msvcrt.bat0000775000175000017500000000620611136446046020602 0ustar lauerlauer@echo off REM This batch file compiles the lpsolve libraries with the Microsoft Visual C/C++ compiler under Windows REM Microsoft Visual C++ 2005 or 2008 Redistributable Package must be installed at the client for this to work: REM 32-bit: REM http://www.microsoft.com/downloads/details.aspx?FamilyId=32BC1BEE-A3F9-4C13-9C99-220B62A191EE&displaylang=en REM http://www.microsoft.com/downloads/details.aspx?familyid=9B2DA534-3E03-4391-8A4D-074B9F2BC1BF&displaylang=en REM http://www.microsoft.com/downloads/details.aspx?familyid=A5C84275-3B97-4AB7-A40D-3802B2AF5FC2&displaylang=en REM 64-bit: REM http://www.microsoft.com/downloads/details.aspx?familyid=BA9257CA-337F-4B40-8C14-157CFDFFEE4E&displaylang=en REM See also REM http://channel9.msdn.com/ShowPost.aspx?PostID=23261 REM http://msdn2.microsoft.com/en-us/library/ms235291.aspx (How to: Deploy using XCopy) REM http://msdn2.microsoft.com/en-us/library/ms235299.aspx (Redistributing Visual C++ Files) set c=cl REM determine platform (win32/win64) echo main(){printf("SET PLATFORM=win%%d\n", (int) (sizeof(void *)*8));}>platform.c %c% /nologo platform.c /Feplatform.exe del platform.c platform.exe >platform.bat del platform.exe call platform.bat del platform.bat if not exist bin\%PLATFORM%\*.* md bin\%PLATFORM% set src=../lp_MDO.c ../shared/commonlib.c ../shared/mmio.c ../shared/myblas.c ../ini.c ../colamd/colamd.c ../lp_rlp.c ../lp_crash.c ../bfp/bfp_LUSOL/lp_LUSOL.c ../bfp/bfp_LUSOL/LUSOL/lusol.c ../lp_Hash.c ../lp_lib.c ../lp_wlp.c ../lp_matrix.c ../lp_mipbb.c ../lp_MPS.c ../lp_params.c ../lp_presolve.c ../lp_price.c ../lp_pricePSE.c ../lp_report.c ../lp_scale.c ../lp_simplex.c ../lp_SOS.c ../lp_utils.c ../yacc_read.c if not exist bin\%PLATFORM%\*.* md bin\%PLATFORM% rc lpsolve.rc %c% -W1 -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd /LD /MD /O2 /Zp8 /Gz -D_WINDLL -D_USRDLL -DWIN32 -D_CRT_SECURE_NO_DEPRECATE -D_CRT_NONSTDC_NO_DEPRECATE -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine %src% lpsolve.res /Febin\%PLATFORM%\lpsolve55.dll editbin /LARGEADDRESSAWARE bin\%PLATFORM%\lpsolve55.dll rem http://msdn2.microsoft.com/en-us/library/ms235229.aspx rem for vs2005 need to embed manifest in dll with manifest tool - #2 on the next line does this. mt /outputresource:"bin\%PLATFORM%\lpsolve55.dll;#2" /manifest "bin\%PLATFORM%\lpsolve55.dll.manifest" rem pause if exist *.obj del *.obj %c% -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd /MT /O2 /Zp8 /Gd /c -DWIN32 -D_CRT_SECURE_NO_DEPRECATE -D_CRT_NONSTDC_NO_DEPRECATE -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine %src% lib *.obj /OUT:bin\%PLATFORM%\liblpsolve55.lib if exist *.obj del *.obj %c% -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd /MTd /Od /Zp8 /Gd /RTC1 /c -DWIN32 -D_CRT_SECURE_NO_DEPRECATE -D_CRT_NONSTDC_NO_DEPRECATE -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine %src% lib *.obj /OUT:bin\%PLATFORM%\liblpsolve55d.lib if exist *.obj del *.obj set PLATFORM= MSVMpack1.2/lp_solve_5.5/lpsolve55/cg++.bat0000775000175000017500000000300011136442426017202 0ustar lauerlauer@echo off REM This batch file compiles the lpsolve libraries with the GNU gcc compiler under Windows set c=g++ set PLATFORM=win32 set src=../lp_MDO.c ../shared/commonlib.c ../shared/mmio.c ../shared/myblas.c ../ini.c ../colamd/colamd.c ../lp_rlp.c ../lp_crash.c ../bfp/bfp_LUSOL/lp_LUSOL.c ../bfp/bfp_LUSOL/LUSOL/lusol.c ../lp_Hash.c ../lp_lib.c ../lp_wlp.c ../lp_matrix.c ../lp_mipbb.c ../lp_MPS.c ../lp_params.c ../lp_presolve.c ../lp_price.c ../lp_pricePSE.c ../lp_report.c ../lp_scale.c ../lp_simplex.c ../lp_SOS.c ../lp_utils.c ../yacc_read.c if not exist bin\%PLATFORM%\*.* md bin\%PLATFORM% rem rc lpsolve.rc %c% -DINLINE=static -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd -s -O3 -shared -mno-cygwin -enable-stdcall-fixup -D_USRDLL -DWIN32 -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine %src% ..\lp_solve.def -o bin\%PLATFORM%\lpsolve55.dll %c% -DINLINE=static -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd -s -O3 -shared -D_USRDLL -DWIN32 -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine %src% -o bin\%PLATFORM%\liblpsolve55.so if exist *.o del *.o %c% -DINLINE=static -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd -s -O3 -c -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine %src% ar rv bin\%PLATFORM%\liblpsolve55.a *.o if exist *.o del *.o set PLATFORM= MSVMpack1.2/lp_solve_5.5/lpsolve55/ccc.osx0000664000175000017500000000374511237566363017304 0ustar lauerlauer: src='../lp_MDO.c ../shared/commonlib.c ../shared/mmio.c ../shared/myblas.c ../ini.c ../fortify.c ../colamd/colamd.c ../lp_rlp.c ../lp_crash.c ../bfp/bfp_LUSOL/lp_LUSOL.c ../bfp/bfp_LUSOL/LUSOL/lusol.c ../lp_Hash.c ../lp_lib.c ../lp_wlp.c ../lp_matrix.c ../lp_mipbb.c ../lp_MPS.c ../lp_params.c ../lp_presolve.c ../lp_price.c ../lp_pricePSE.c ../lp_report.c ../lp_scale.c ../lp_simplex.c ../lp_SOS.c ../lp_utils.c ../yacc_read.c' c=cc #determine platform (32/64 bit) >/tmp/platform.c echo '#include '>>/tmp/platform.c echo '#include '>>/tmp/platform.c echo 'main(){printf("osx%d", (int) (sizeof(void *)*8));}'>>/tmp/platform.c $c /tmp/platform.c -o /tmp/platform PLATFORM=`/tmp/platform` rm /tmp/platform /tmp/platform.c >/dev/null 2>&1 mkdir bin bin/$PLATFORM >/dev/null 2>&1 #check if this system has the isnan function >/tmp/isnan.c echo '#include '>>/tmp/isnan.c echo '#include '>>/tmp/isnan.c echo '#include '>>/tmp/isnan.c echo 'main(){isnan(0);}'>>/tmp/isnan.c $c /tmp/isnan.c -o /tmp/isnan $math >/dev/null 2>&1 if [ $? = 0 ] then NOISNAN= else NOISNAN=-DNOISNAN fi rm /tmp/isnan.c /tmp/isnan >/dev/null 2>&1 def= dl=-ldl so=y opts='-idirafter /usr/include/sys -O3 -DINTEGERTIME -Wno-long-double' $c -s -c -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd $opts $def $NOISNAN -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine $src libtool -static -o bin/$PLATFORM/liblpsolve55.a `echo $src|sed s/[.]c/.o/g|sed 's/[^ ]*\///g'` if [ "$so" != "" ] then $c -fPIC -fno-common -s -c -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd -I. $opts $NOISNAN -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine $src $c -dynamiclib bin/$PLATFORM/liblpsolve55.a -compatibility_version 5.5.0 -current_version 5.5.0 -o bin/$PLATFORM/liblpsolve55.dylib `echo $src|sed s/[.]c/.o/g|sed 's/[^ ]*\///g'` -lc fi rm *.o 2>/dev/null MSVMpack1.2/lp_solve_5.5/lpsolve55/readme.txt0000664000175000017500000000061411141374643017777 0ustar lauerlauerThis directory contains the files to build the Windows lpsolve55.dll dll / /linux/Unix lpsolve55.a library To build the program under Windows with the Visual C/C++ compiler, use cvc6.bat (also works for VS.NET) To build the program under DOS/Windows with the gcc compiler, use cgcc.bat To build the program under Linux/Unix, use sh ccc To build the program under Mac OS X 10.3.5, use sh ccc.osx MSVMpack1.2/lp_solve_5.5/lpsolve55/ccc.solaris0000664000175000017500000000360511153276671020137 0ustar lauerlauer: src='../lp_MDO.c ../shared/commonlib.c ../shared/mmio.c ../shared/myblas.c ../ini.c ../fortify.c ../colamd/colamd.c ../lp_rlp.c ../lp_crash.c ../bfp/bfp_LUSOL/lp_LUSOL.c ../bfp/bfp_LUSOL/LUSOL/lusol.c ../lp_Hash.c ../lp_lib.c ../lp_wlp.c ../lp_matrix.c ../lp_mipbb.c ../lp_MPS.c ../lp_params.c ../lp_presolve.c ../lp_price.c ../lp_pricePSE.c ../lp_report.c ../lp_scale.c ../lp_simplex.c ../lp_SOS.c ../lp_utils.c ../yacc_read.c' c=cc #determine platform (32/64 bit) >/tmp/platform.c echo '#include '>>/tmp/platform.c echo '#include '>>/tmp/platform.c echo 'main(){printf("ux%d", (int) (sizeof(void *)*8));}'>>/tmp/platform.c $c /tmp/platform.c -o /tmp/platform PLATFORM=`/tmp/platform` rm /tmp/platform /tmp/platform.c >/dev/null 2>&1 mkdir bin bin/$PLATFORM >/dev/null 2>&1 #check if this system has the isnan function >/tmp/isnan.c echo '#include '>>/tmp/isnan.c echo '#include '>>/tmp/isnan.c echo '#include '>>/tmp/isnan.c echo 'main(){isnan(0);}'>>/tmp/isnan.c $c /tmp/isnan.c -o /tmp/isnan $math >/dev/null 2>&1 if [ $? = 0 ] then NOISNAN= else NOISNAN=-DNOISNAN fi rm /tmp/isnan.c /tmp/isnan >/dev/null 2>&1 def= dl=-ldl so=y opts='-O3' $c -s -c -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd $opts $def $NOISNAN -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine $src ar rv bin/$PLATFORM/liblpsolve55.a `echo $src|sed s/[.]c/.o/g|sed 's/[^ ]*\///g'` ranlib bin/$PLATFORM/liblpsolve55.a if [ "$so" != "" ] then $c -fpic -s -c -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd -I. $opts $NOISNAN -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine $src $c -G -R,-Bsymbolic -Wl,-h,liblpsolve55.so -o bin/$PLATFORM/liblpsolve55.so `echo $src|sed s/[.]c/.o/g|sed 's/[^ ]*\///g'` -lc -lm -ldl fi rm *.o 2>/dev/null MSVMpack1.2/lp_solve_5.5/lpsolve55/resource.h0000664000175000017500000000061411141374243017775 0ustar lauerlauer//{{NO_DEPENDENCIES}} // Microsoft Developer Studio generated include file. // Used by lpsolve.rc // // Next default values for new objects // #ifdef APSTUDIO_INVOKED #ifndef APSTUDIO_READONLY_SYMBOLS #define _APS_NEXT_RESOURCE_VALUE 101 #define _APS_NEXT_COMMAND_VALUE 40001 #define _APS_NEXT_CONTROL_VALUE 1000 #define _APS_NEXT_SYMED_VALUE 101 #endif #endif MSVMpack1.2/lp_solve_5.5/lpsolve55/dll.sln0000664000175000017500000000321411141362066017265 0ustar lauerlauerMicrosoft Visual Studio Solution File, Format Version 10.00 # Visual Studio 2008 Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "lpsolve55", "dll.vcproj", "{C97E3E84-BCC5-4CCB-9675-5833C056E702}" EndProject Global GlobalSection(SolutionConfigurationPlatforms) = preSolution Debug fortify|Win32 = Debug fortify|Win32 Debug fortify|x64 = Debug fortify|x64 Debug|Win32 = Debug|Win32 Debug|x64 = Debug|x64 Release|Win32 = Release|Win32 Release|x64 = Release|x64 EndGlobalSection GlobalSection(ProjectConfigurationPlatforms) = postSolution {C97E3E84-BCC5-4CCB-9675-5833C056E702}.Debug fortify|Win32.ActiveCfg = Debug fortify|Win32 {C97E3E84-BCC5-4CCB-9675-5833C056E702}.Debug fortify|Win32.Build.0 = Debug fortify|Win32 {C97E3E84-BCC5-4CCB-9675-5833C056E702}.Debug fortify|x64.ActiveCfg = Debug fortify|x64 {C97E3E84-BCC5-4CCB-9675-5833C056E702}.Debug fortify|x64.Build.0 = Debug fortify|x64 {C97E3E84-BCC5-4CCB-9675-5833C056E702}.Debug|Win32.ActiveCfg = Debug|Win32 {C97E3E84-BCC5-4CCB-9675-5833C056E702}.Debug|Win32.Build.0 = Debug|Win32 {C97E3E84-BCC5-4CCB-9675-5833C056E702}.Debug|x64.ActiveCfg = Debug|x64 {C97E3E84-BCC5-4CCB-9675-5833C056E702}.Debug|x64.Build.0 = Debug|x64 {C97E3E84-BCC5-4CCB-9675-5833C056E702}.Release|Win32.ActiveCfg = Release|Win32 {C97E3E84-BCC5-4CCB-9675-5833C056E702}.Release|Win32.Build.0 = Release|Win32 {C97E3E84-BCC5-4CCB-9675-5833C056E702}.Release|x64.ActiveCfg = Release|x64 {C97E3E84-BCC5-4CCB-9675-5833C056E702}.Release|x64.Build.0 = Release|x64 EndGlobalSection GlobalSection(SolutionProperties) = preSolution HideSolutionNode = FALSE EndGlobalSection EndGlobal MSVMpack1.2/lp_solve_5.5/lpsolve55/cgcc.bat0000775000175000017500000000335111137106025017364 0ustar lauerlauer@echo off REM This batch file compiles the lpsolve libraries with the GNU gcc compiler under Windows set c=gcc REM determine platform (win32/win64) echo main(){printf("SET PLATFORM=win%%d\n", (int) (sizeof(void *)*8));}>platform.c %c% platform.c -o platform.exe del platform.c platform.exe >platform.bat del platform.exe call platform.bat del platform.bat if not exist bin\%PLATFORM%\*.* md bin\%PLATFORM% set src=../lp_MDO.c ../shared/commonlib.c ../shared/mmio.c ../shared/myblas.c ../ini.c ../colamd/colamd.c ../lp_rlp.c ../lp_crash.c ../bfp/bfp_LUSOL/lp_LUSOL.c ../bfp/bfp_LUSOL/LUSOL/lusol.c ../lp_Hash.c ../lp_lib.c ../lp_wlp.c ../lp_matrix.c ../lp_mipbb.c ../lp_MPS.c ../lp_params.c ../lp_presolve.c ../lp_price.c ../lp_pricePSE.c ../lp_report.c ../lp_scale.c ../lp_simplex.c ../lp_SOS.c ../lp_utils.c ../yacc_read.c rem rc lpsolve.rc %c% -DINLINE=static -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd -s -O3 -shared -mno-cygwin -enable-stdcall-fixup -D_USRDLL -DWIN32 -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine %src% ..\lp_solve.def -o bin\%PLATFORM%\lpsolve55.dll %c% -DINLINE=static -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd -s -O3 -shared -D_USRDLL -DWIN32 -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine %src% -o bin\%PLATFORM%\liblpsolve55.so if exist *.o del *.o %c% -DINLINE=static -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd -s -O3 -c -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine %src% ar rv bin\%PLATFORM%\liblpsolve55.a *.o if exist *.o del *.o set PLATFORM= MSVMpack1.2/lp_solve_5.5/lpsolve55/cvc6.bat0000775000175000017500000000427611136446033017342 0ustar lauerlauer@echo off REM This batch file compiles the lpsolve libraries with the Microsoft Visual C/C++ compiler under Windows set c=cl REM determine platform (win32/win64) echo main(){printf("SET PLATFORM=win%%d\n", (int) (sizeof(void *)*8));}>platform.c %c% /nologo platform.c /Feplatform.exe del platform.c platform.exe >platform.bat del platform.exe call platform.bat del platform.bat if "%PLATFORM%" == "win32" goto ok1 echo. echo This batch file is intended for 32 bit compilation with MS Visual C 6 echo For newer versions use cvc8*.bat goto done :ok1 if not exist bin\%PLATFORM%\*.* md bin\%PLATFORM% set src=../lp_MDO.c ../shared/commonlib.c ../shared/mmio.c ../shared/myblas.c ../ini.c ../colamd/colamd.c ../lp_rlp.c ../lp_crash.c ../bfp/bfp_LUSOL/lp_LUSOL.c ../bfp/bfp_LUSOL/LUSOL/lusol.c ../lp_Hash.c ../lp_lib.c ../lp_wlp.c ../lp_matrix.c ../lp_mipbb.c ../lp_MPS.c ../lp_params.c ../lp_presolve.c ../lp_price.c ../lp_pricePSE.c ../lp_report.c ../lp_scale.c ../lp_simplex.c ../lp_SOS.c ../lp_utils.c ../yacc_read.c rc lpsolve.rc %c% -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd /LD /MD /O2 /Zp8 /Gz -D"LP_MAXLINELEN=0" -D_WINDLL -D_USRDLL -DWIN32 -D_CRT_SECURE_NO_DEPRECATE -D_CRT_NONSTDC_NO_DEPRECATE -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine %src% lpsolve.res ..\lp_solve.def -o bin\%PLATFORM%\lpsolve55.dll rem /link /LINK50COMPAT if exist *.obj del *.obj %c% -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd /MT /O2 /Zp8 /Gd /c -D"LP_MAXLINELEN=0" -DWIN32 -D_CRT_SECURE_NO_DEPRECATE -D_CRT_NONSTDC_NO_DEPRECATE -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine %src% lib *.obj /OUT:bin\%PLATFORM%\liblpsolve55.lib if exist *.obj del *.obj %c% -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd /MTd /O2 /Zp8 /Gd /c -D"LP_MAXLINELEN=0" -DWIN32 -D_CRT_SECURE_NO_DEPRECATE -D_CRT_NONSTDC_NO_DEPRECATE -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine %src% lib *.obj /OUT:bin\%PLATFORM%\liblpsolve55d.lib if exist *.obj del *.obj :done set PLATFORM= MSVMpack1.2/lp_solve_5.5/lpsolve55/cccLUSOL.osx0000664000175000017500000000377711137130772020116 0ustar lauerlauersrc='../lp_MDO.c ../shared/commonlib.c ../shared/mmio.c ../shared/myblas.c ../ini.c ../fortify.c ../colamd/colamd.c ../lp_rlp.c ../lp_crash.c ../bfp/bfp_LUSOL/lp_LUSOL.c ../bfp/bfp_LUSOL/LUSOL/lusol.c ../lp_Hash.c ../lp_lib.c ../lp_wlp.c ../lp_matrix.c ../lp_mipbb.c ../lp_MPS.c ../lp_params.c ../lp_presolve.c ../lp_price.c ../lp_pricePSE.c ../lp_report.c ../lp_scale.c ../lp_simplex.c ../lp_SOS.c ../lp_utils.c ../yacc_read.c ../bfp/bfp_LUSOL/lusol.c' c=cc #determine platform (32/64 bit) >/tmp/platform.c echo '#include '>>/tmp/platform.c echo '#include '>>/tmp/platform.c echo 'main(){printf("ux%d", (int) (sizeof(void *)*8));}'>>/tmp/platform.c $c /tmp/platform.c -o /tmp/platform PLATFORM=`/tmp/platform` rm /tmp/platform /tmp/platform.c >/dev/null 2>&1 mkdir bin bin/$PLATFORM >/dev/null 2>&1 #check if this system has the isnan function >/tmp/isnan.c echo '#include '>>/tmp/isnan.c echo '#include '>>/tmp/isnan.c echo '#include '>>/tmp/isnan.c echo 'main(){isnan(0);}'>>/tmp/isnan.c $c /tmp/isnan.c -o /tmp/isnan $math >/dev/null 2>&1 if [ $? = 0 ] then NOISNAN= else NOISNAN=-DNOISNAN fi rm /tmp/isnan.c /tmp/isnan >/dev/null 2>&1 def= so= dl=-ldl so=y opts='-idirafter /usr/include/sys -O3 -DINTEGERTIME -Wno-long-double' $c -s -c -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd $opts $def $NOISNAN -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine $src libtool -static -o bin/$PLATFORM/liblpsolve55.a `echo $src|sed s/[.]c/.o/g|sed 's/[^ ]*\///g'` if [ "$so" != "" ] then $c -fPIC -fno-common -s -c -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd -I. $opts $NOISNAN -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine $src $c -dynamiclib bin/$PLATFORM/liblpsolve55.a -compatibility_version 5.5.0 -current_version 5.5.0 -o bin/$PLATFORM/liblpsolve55.dylib `echo $src|sed s/[.]c/.o/g|sed 's/[^ ]*\///g'` -lc fi rm *.o 2>/dev/null MSVMpack1.2/lp_solve_5.5/lpsolve55/lpsolve.rc0000664000175000017500000000461311236132412020005 0ustar lauerlauer// Microsoft Visual C++ generated resource script. // #include "resource.h" #define APSTUDIO_READONLY_SYMBOLS ///////////////////////////////////////////////////////////////////////////// // // Generated from the TEXTINCLUDE 2 resource. // #include "afxres.h" ///////////////////////////////////////////////////////////////////////////// #undef APSTUDIO_READONLY_SYMBOLS ///////////////////////////////////////////////////////////////////////////// // Dutch (Belgium) resources #if !defined(AFX_RESOURCE_DLL) || defined(AFX_TARG_NLB) #ifdef _WIN32 LANGUAGE LANG_DUTCH, SUBLANG_DUTCH_BELGIAN #pragma code_page(1252) #endif //_WIN32 ///////////////////////////////////////////////////////////////////////////// // // Version // VS_VERSION_INFO VERSIONINFO FILEVERSION 5,5,0,15 PRODUCTVERSION 5,5,0,15 FILEFLAGSMASK 0x3fL #ifdef _DEBUG FILEFLAGS 0x1L #else FILEFLAGS 0x0L #endif FILEOS 0x40004L FILETYPE 0x2L FILESUBTYPE 0x0L BEGIN BLOCK "StringFileInfo" BEGIN BLOCK "040904b0" BEGIN VALUE "Comments", "Mixed Integer Lineair Program Solver" VALUE "CompanyName", "Free Software Foundation, Inc." VALUE "FileDescription", "lpsolve" VALUE "FileVersion", "5, 5, 0, 15" VALUE "InternalName", "lpsolve" VALUE "LegalCopyright", "Copyright © 1991, 2009 Free Software Foundation, Inc." VALUE "OriginalFilename", "lpsolve55.dll" VALUE "ProductName", "lpsolve" VALUE "ProductVersion", "5, 5, 0, 15" END END BLOCK "VarFileInfo" BEGIN VALUE "Translation", 0x409, 1200 END END #ifdef APSTUDIO_INVOKED ///////////////////////////////////////////////////////////////////////////// // // TEXTINCLUDE // 1 TEXTINCLUDE BEGIN "resource.h\0" END 2 TEXTINCLUDE BEGIN "#include ""afxres.h""\r\n" "\0" END 3 TEXTINCLUDE BEGIN "\r\n" "\0" END #endif // APSTUDIO_INVOKED #endif // Dutch (Belgium) resources ///////////////////////////////////////////////////////////////////////////// #ifndef APSTUDIO_INVOKED ///////////////////////////////////////////////////////////////////////////// // // Generated from the TEXTINCLUDE 3 resource. // ///////////////////////////////////////////////////////////////////////////// #endif // not APSTUDIO_INVOKED MSVMpack1.2/lp_solve_5.5/lpsolve55/lib.vcproj0000664000175000017500000003612411141362160017770 0ustar lauerlauer MSVMpack1.2/lp_solve_5.5/lpsolve55/dll.vcproj0000664000175000017500000004610311141362066020000 0ustar lauerlauer MSVMpack1.2/lp_solve_5.5/lpsolve55/lib.sln0000664000175000017500000000321711141362160017256 0ustar lauerlauerMicrosoft Visual Studio Solution File, Format Version 10.00 # Visual Studio 2008 Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "liblpsolve55", "lib.vcproj", "{AEDD8A5B-DFA6-4995-9E9E-EB381C34CEAF}" EndProject Global GlobalSection(SolutionConfigurationPlatforms) = preSolution Debug fortify|Win32 = Debug fortify|Win32 Debug fortify|x64 = Debug fortify|x64 Debug|Win32 = Debug|Win32 Debug|x64 = Debug|x64 Release|Win32 = Release|Win32 Release|x64 = Release|x64 EndGlobalSection GlobalSection(ProjectConfigurationPlatforms) = postSolution {AEDD8A5B-DFA6-4995-9E9E-EB381C34CEAF}.Debug fortify|Win32.ActiveCfg = Debug fortify|Win32 {AEDD8A5B-DFA6-4995-9E9E-EB381C34CEAF}.Debug fortify|Win32.Build.0 = Debug fortify|Win32 {AEDD8A5B-DFA6-4995-9E9E-EB381C34CEAF}.Debug fortify|x64.ActiveCfg = Debug fortify|x64 {AEDD8A5B-DFA6-4995-9E9E-EB381C34CEAF}.Debug fortify|x64.Build.0 = Debug fortify|x64 {AEDD8A5B-DFA6-4995-9E9E-EB381C34CEAF}.Debug|Win32.ActiveCfg = Debug|Win32 {AEDD8A5B-DFA6-4995-9E9E-EB381C34CEAF}.Debug|Win32.Build.0 = Debug|Win32 {AEDD8A5B-DFA6-4995-9E9E-EB381C34CEAF}.Debug|x64.ActiveCfg = Debug|x64 {AEDD8A5B-DFA6-4995-9E9E-EB381C34CEAF}.Debug|x64.Build.0 = Debug|x64 {AEDD8A5B-DFA6-4995-9E9E-EB381C34CEAF}.Release|Win32.ActiveCfg = Release|Win32 {AEDD8A5B-DFA6-4995-9E9E-EB381C34CEAF}.Release|Win32.Build.0 = Release|Win32 {AEDD8A5B-DFA6-4995-9E9E-EB381C34CEAF}.Release|x64.ActiveCfg = Release|x64 {AEDD8A5B-DFA6-4995-9E9E-EB381C34CEAF}.Release|x64.Build.0 = Release|x64 EndGlobalSection GlobalSection(SolutionProperties) = preSolution HideSolutionNode = FALSE EndGlobalSection EndGlobal MSVMpack1.2/lp_solve_5.5/lpsolve55/ccc0000664000175000017500000000376011162275146016462 0ustar lauerlauer: src='../lp_MDO.c ../shared/commonlib.c ../shared/mmio.c ../shared/myblas.c ../ini.c ../fortify.c ../colamd/colamd.c ../lp_rlp.c ../lp_crash.c ../bfp/bfp_LUSOL/lp_LUSOL.c ../bfp/bfp_LUSOL/LUSOL/lusol.c ../lp_Hash.c ../lp_lib.c ../lp_wlp.c ../lp_matrix.c ../lp_mipbb.c ../lp_MPS.c ../lp_params.c ../lp_presolve.c ../lp_price.c ../lp_pricePSE.c ../lp_report.c ../lp_scale.c ../lp_simplex.c ../lp_SOS.c ../lp_utils.c ../yacc_read.c' c=cc #determine platform (32/64 bit) >/tmp/platform.c echo '#include '>>/tmp/platform.c echo '#include '>>/tmp/platform.c echo 'main(){printf("ux%d", (int) (sizeof(void *)*8));}'>>/tmp/platform.c $c /tmp/platform.c -o /tmp/platform PLATFORM=`/tmp/platform` rm /tmp/platform /tmp/platform.c >/dev/null 2>&1 mkdir bin bin/$PLATFORM >/dev/null 2>&1 #check if this system has the isnan function >/tmp/isnan.c echo '#include '>>/tmp/isnan.c echo '#include '>>/tmp/isnan.c echo '#include '>>/tmp/isnan.c echo 'main(){isnan(0);}'>>/tmp/isnan.c $c /tmp/isnan.c -o /tmp/isnan $math >/dev/null 2>&1 if [ $? = 0 ] then NOISNAN= else NOISNAN=-DNOISNAN fi rm /tmp/isnan.c /tmp/isnan >/dev/null 2>&1 def= so= if [ "$PLATFORM" = "SCO_UNIX" ] then def='-dy -K PIC -DNOLONGLONG' dl=-lc else dl=-ldl so=y fi opts='-O3' $c -s -c -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd $opts $def $NOISNAN -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine $src ar rv bin/$PLATFORM/liblpsolve55.a `echo $src|sed s/[.]c/.o/g|sed 's/[^ ]*\///g'` ranlib bin/$PLATFORM/liblpsolve55.a if [ "$so" != "" ] then $c -fpic -s -c -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd -I. $opts $NOISNAN -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine $src $c -shared -Wl,-Bsymbolic -Wl,-soname,liblpsolve55.so -o bin/$PLATFORM/liblpsolve55.so `echo $src|sed s/[.]c/.o/g|sed 's/[^ ]*\///g'` -lc -lm -ldl fi rm *.o 2>/dev/null MSVMpack1.2/lp_solve_5.5/lpsolve55/cvc8NOmsvcrt.bat0000775000175000017500000000453511136446054021041 0ustar lauerlauer@echo off REM This batch file compiles the lpsolve libraries with the Microsoft Visual C/C++ compiler under Windows set c=cl REM determine platform (win32/win64) echo main(){printf("SET PLATFORM=win%%d\n", (int) (sizeof(void *)*8));}>platform.c %c% /nologo platform.c /Feplatform.exe del platform.c platform.exe >platform.bat del platform.exe call platform.bat del platform.bat if not exist bin\%PLATFORM%\*.* md bin\%PLATFORM% set src=../lp_MDO.c ../shared/commonlib.c ../shared/mmio.c ../shared/myblas.c ../ini.c ../colamd/colamd.c ../lp_rlp.c ../lp_crash.c ../bfp/bfp_LUSOL/lp_LUSOL.c ../bfp/bfp_LUSOL/LUSOL/lusol.c ../lp_Hash.c ../lp_lib.c ../lp_wlp.c ../lp_matrix.c ../lp_mipbb.c ../lp_MPS.c ../lp_params.c ../lp_presolve.c ../lp_price.c ../lp_pricePSE.c ../lp_report.c ../lp_scale.c ../lp_simplex.c ../lp_SOS.c ../lp_utils.c ../yacc_read.c rc lpsolve.rc rem use /MT to remove dependence on msvcrt*.dll calls kernel libs directly about 200K larger dll. %c% -W1 -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd /LD /MT /O2 /Zp8 /Gz -D_WINDLL -D_USRDLL -DWIN32 -D_CRT_SECURE_NO_DEPRECATE -D_CRT_NONSTDC_NO_DEPRECATE -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine %src% lpsolve.res /Febin\%PLATFORM%\lpsolve55.dll editbin /LARGEADDRESSAWARE bin\%PLATFORM%\lpsolve55.dll rem http://msdn2.microsoft.com/en-us/library/ms235229.aspx rem for vs2005 need to embed manifest in dll with manifest tool - #2 on the next line does this. rem mt /outputresource:"bin\%PLATFORM%\lpsolve55.dll;#2" /manifest "bin\%PLATFORM%\lpsolve55.dll.manifest" rem pause if exist *.obj del *.obj %c% -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd /MT /O2 /Zp8 /Gd /c -DWIN32 -D_CRT_SECURE_NO_DEPRECATE -D_CRT_NONSTDC_NO_DEPRECATE -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine %src% lib *.obj /OUT:bin\%PLATFORM%\liblpsolve55.lib if exist *.obj del *.obj %c% -I.. -I../shared -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd /MTd /Od /Zp8 /Gd /RTC1 /c -DWIN32 -D_CRT_SECURE_NO_DEPRECATE -D_CRT_NONSTDC_NO_DEPRECATE -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine %src% lib *.obj /OUT:bin\%PLATFORM%\liblpsolve55d.lib if exist *.obj del *.obj set PLATFORM= MSVMpack1.2/lp_solve_5.5/lp_solveDLL.c0000664000175000017500000000037411141374254016467 0ustar lauerlauer /* lp_solve.cpp : Defines the entry point for the DLL. */ #include "lp_solveDLL.h" BOOL APIENTRY DllMain( HANDLE hModule, DWORD ul_reason_for_call, LPVOID lpReserved ) { return TRUE; } MSVMpack1.2/lp_solve_5.5/lp_mipbb.h0000664000175000017500000000412011141374246016073 0ustar lauerlauer#ifndef HEADER_lp_mipbb #define HEADER_lp_mipbb #include "lp_types.h" #include "lp_utils.h" /* Bounds storage for B&B routines */ typedef struct _BBrec { struct _BBrec *parent; struct _BBrec *child; lprec *lp; int varno; int vartype; int lastvarcus; /* Count of non-int variables of the previous branch */ int lastrcf; int nodesleft; int nodessolved; int nodestatus; REAL noderesult; REAL lastsolution; /* Optimal solution of the previous branch */ REAL sc_bound; REAL *upbo, *lowbo; REAL UPbound, LObound; int UBtrack, LBtrack; /* Signals that incoming bounds were changed */ MYBOOL contentmode; /* Flag indicating if we "own" the bound vectors */ MYBOOL sc_canset; MYBOOL isSOS; MYBOOL isGUB; int *varmanaged; /* Extended list of variables managed by this B&B level */ MYBOOL isfloor; /* State variable indicating the active B&B bound */ MYBOOL UBzerobased; /* State variable indicating if bounds have been rebased */ } BBrec; #ifdef __cplusplus extern "C" { #endif STATIC BBrec *create_BB(lprec *lp, BBrec *parentBB, MYBOOL dofullcopy); STATIC BBrec *push_BB(lprec *lp, BBrec *parentBB, int varno, int vartype, int varcus); STATIC MYBOOL initbranches_BB(BBrec *BB); STATIC MYBOOL fillbranches_BB(BBrec *BB); STATIC MYBOOL nextbranch_BB(BBrec *BB); STATIC MYBOOL strongbranch_BB(lprec *lp, BBrec *BB, int varno, int vartype, int varcus); STATIC MYBOOL initcuts_BB(lprec *lp); STATIC int updatecuts_BB(lprec *lp); STATIC MYBOOL freecuts_BB(lprec *lp); STATIC BBrec *findself_BB(BBrec *BB); STATIC int solve_LP(lprec *lp, BBrec *BB); STATIC int rcfbound_BB(BBrec *BB, int varno, MYBOOL isINT, REAL *newbound, MYBOOL *isfeasible); STATIC MYBOOL findnode_BB(BBrec *BB, int *varno, int *vartype, int *varcus); STATIC int solve_BB(BBrec *BB); STATIC MYBOOL free_BB(BBrec **BB); STATIC BBrec *pop_BB(BBrec *BB); STATIC int run_BB(lprec *lp); #ifdef __cplusplus } #endif #endif /* HEADER_lp_mipbb */ MSVMpack1.2/lp_solve_5.5/lp_pricePSE.h0000664000175000017500000000130211141374250016446 0ustar lauerlauer#ifndef HEADER_lp_pricePSE #define HEADER_lp_pricePSE #include "lp_types.h" #define ApplySteepestEdgeMinimum #ifdef __cplusplus extern "C" { #endif /* Price norm management routines */ STATIC MYBOOL initPricer(lprec *lp); INLINE MYBOOL applyPricer(lprec *lp); STATIC void simplexPricer(lprec *lp, MYBOOL isdual); STATIC void freePricer(lprec *lp); STATIC MYBOOL resizePricer(lprec *lp); STATIC REAL getPricer(lprec *lp, int item, MYBOOL isdual); STATIC MYBOOL restartPricer(lprec *lp, MYBOOL isdual); STATIC MYBOOL updatePricer(lprec *lp, int rownr, int colnr, REAL *pcol, REAL *prow, int *nzprow); STATIC MYBOOL verifyPricer(lprec *lp); #ifdef __cplusplus } #endif #endif /* HEADER_lp_pricePSE */ MSVMpack1.2/lp_solve_5.5/lp_lib.c0000664000175000017500000107541111252265156015561 0ustar lauerlauer /* ---------------------------------------------------------------------------------- Main library of routines for lp_solve v5.0+ ---------------------------------------------------------------------------------- Author: Michel Berkelaar (to v3.2) Kjell Eikland (v4.0 and forward) Contact: kjell.eikland@broadpark.no License terms: LGPL. Requires: (see below) Release notes: v5.0.0 1 January 2004 First integrated and repackaged version. v5.0.1 8 May 2004 Cumulative update since initial release; overall functionality scope maintained. v5.1.0 20 July 2004 Reworked lp_solve throughout to fit new flexible matrix storage model. ---------------------------------------------------------------------------------- */ /* ---------------------------------------------------------------------------------- */ /* Main library of routines for lp_solve */ /*----------------------------------------------------------------------------------- */ #include #include #include #include #if LoadInverseLib == TRUE #ifdef WIN32 #include #else #include #endif #endif /* ---------------------------------------------------------------------------------- */ /* Include core and support modules via headers */ /* ---------------------------------------------------------------------------------- */ #include "lp_lib.h" #include "commonlib.h" #include "lp_utils.h" #include "lp_matrix.h" #include "lp_SOS.h" #include "lp_Hash.h" #include "lp_MPS.h" #include "lp_wlp.h" #include "lp_presolve.h" #include "lp_scale.h" #include "lp_simplex.h" #include "lp_mipbb.h" #include "lp_report.h" #include "lp_MDO.h" #include "lp_bit.h" #if INVERSE_ACTIVE==INVERSE_LUMOD #include "lp_LUMOD.h" #elif INVERSE_ACTIVE==INVERSE_LUSOL #include "lp_LUSOL.h" #elif INVERSE_ACTIVE==INVERSE_GLPKLU #include "lp_glpkLU.h" #elif INVERSE_ACTIVE==INVERSE_ETAPFI #include "lp_etaPFI.h" #elif INVERSE_ACTIVE==INVERSE_LEGACY #include "lp_etaPFI.h" #endif #if libBLAS > 0 #include "myblas.h" #endif #ifdef __BORLANDC__ #pragma hdrstop #pragma package(smart_init) #endif /* ---------------------------------------------------------------------------------- */ /* Include selected basis inverse routines and price norm scalars */ /* ---------------------------------------------------------------------------------- */ #include "lp_price.h" #include "lp_pricePSE.h" #ifdef FORTIFY # include "lp_fortify.h" #endif /* Return lp_solve version information */ void __WINAPI lp_solve_version(int *majorversion, int *minorversion, int *release, int *build) { if(majorversion != NULL) (*majorversion) = MAJORVERSION; if(minorversion != NULL) (*minorversion) = MINORVERSION; if(release != NULL) (*release) = RELEASE; if(build != NULL) (*build) = BUILD; } /* ---------------------------------------------------------------------------------- */ /* Various interaction elements */ /* ---------------------------------------------------------------------------------- */ MYBOOL __WINAPI userabort(lprec *lp, int message) { MYBOOL abort; int spx_save; spx_save = lp->spx_status; lp->spx_status = RUNNING; if(yieldformessages(lp) != 0) { lp->spx_status = USERABORT; if(lp->bb_level > 0) lp->bb_break = TRUE; } if((message > 0) && (lp->usermessage != NULL) && (lp->msgmask & message)) lp->usermessage(lp, lp->msghandle, message); abort = (MYBOOL) (lp->spx_status != RUNNING); if(!abort) lp->spx_status = spx_save; return( abort ); } STATIC int yieldformessages(lprec *lp) { if((lp->sectimeout > 0) && ((timeNow()-lp->timestart)-(REAL)lp->sectimeout>0)) lp->spx_status = TIMEOUT; if(lp->ctrlc != NULL) { int retcode = lp->ctrlc(lp, lp->ctrlchandle); /* Check for command to restart the B&B */ if((retcode == ACTION_RESTART) && (lp->bb_level > 1)) { lp->bb_break = AUTOMATIC; retcode = 0; } return(retcode); } else return(0); } void __WINAPI set_outputstream(lprec *lp, FILE *stream) { if((lp->outstream != NULL) && (lp->outstream != stdout)) { if(lp->streamowned) fclose(lp->outstream); else fflush(lp->outstream); } if(stream == NULL) lp->outstream = stdout; else lp->outstream = stream; lp->streamowned = FALSE; } MYBOOL __WINAPI set_outputfile(lprec *lp, char *filename) { MYBOOL ok; FILE *output = stdout; ok = (MYBOOL) ((filename == NULL) || (*filename == 0) || ((output = fopen(filename,"w")) != NULL)); if(ok) { set_outputstream(lp, output); lp->streamowned = (MYBOOL) ((filename != NULL) && (*filename != 0)); #if 1 if((filename != NULL) && (*filename == 0)) lp->outstream = NULL; #endif } return(ok); } REAL __WINAPI time_elapsed(lprec *lp) { if(lp->timeend > 0) return(lp->timeend - lp->timestart); else return(timeNow() - lp->timestart); } void __WINAPI put_bb_nodefunc(lprec *lp, lphandleint_intfunc newnode, void *bbnodehandle) { lp->bb_usenode = newnode; lp->bb_nodehandle = bbnodehandle; /* User-specified "owner process ID" */ } void __WINAPI put_bb_branchfunc(lprec *lp, lphandleint_intfunc newbranch, void *bbbranchhandle) { lp->bb_usebranch = newbranch; lp->bb_branchhandle = bbbranchhandle; /* User-specified "owner process ID" */ } void __WINAPI put_abortfunc(lprec *lp, lphandle_intfunc newctrlc, void *ctrlchandle) { lp->ctrlc = newctrlc; lp->ctrlchandle = ctrlchandle; /* User-specified "owner process ID" */ } void __WINAPI put_logfunc(lprec *lp, lphandlestr_func newlog, void *loghandle) { lp->writelog = newlog; lp->loghandle = loghandle; /* User-specified "owner process ID" */ } void __WINAPI put_msgfunc(lprec *lp, lphandleint_func newmsg, void *msghandle, int mask) { lp->usermessage = newmsg; lp->msghandle = msghandle; /* User-specified "owner process ID" */ lp->msgmask = mask; } /* ---------------------------------------------------------------------------------- */ /* DLL exported function */ /* ---------------------------------------------------------------------------------- */ lprec * __WINAPI read_MPS(char *filename, int options) { lprec *lp = NULL; int typeMPS; typeMPS = (options & ~0x07) >> 2; if ((typeMPS & (MPSFIXED|MPSFREE)) == 0) typeMPS |= MPSFIXED; if(MPS_readfile(&lp, filename, typeMPS, options & 0x07)) return( lp ); else return( NULL ); } lprec * __WINAPI read_mps(FILE *filename, int options) { lprec *lp = NULL; int typeMPS; typeMPS = (options & ~0x07) >> 2; if ((typeMPS & (MPSFIXED|MPSFREE)) == 0) typeMPS |= MPSFIXED; if(MPS_readhandle(&lp, filename, typeMPS, options & 0x07)) return( lp ); else return( NULL ); } /* #if defined develop */ lprec * __WINAPI read_mpsex(void *userhandle, read_modeldata_func read_modeldata, int options) { lprec *lp = NULL; int typeMPS; typeMPS = (options & ~0x07) >> 2; if ((typeMPS & (MPSFIXED|MPSFREE)) == 0) typeMPS |= MPSFIXED; if(MPS_readex(&lp, userhandle, read_modeldata, typeMPS, options & 0x07)) return( lp ); else return( NULL ); } /* #endif */ lprec * __WINAPI read_freeMPS(char *filename, int options) { lprec *lp = NULL; int typeMPS; typeMPS = (options & ~0x07) >> 2; typeMPS &= ~MPSFIXED; typeMPS |= MPSFREE; if(MPS_readfile(&lp, filename, typeMPS, options & 0x07)) return( lp ); else return( NULL ); } lprec * __WINAPI read_freemps(FILE *filename, int options) { lprec *lp = NULL; int typeMPS; typeMPS = (options & ~0x07) >> 2; typeMPS &= ~MPSFIXED; typeMPS |= MPSFREE; if(MPS_readhandle(&lp, filename, typeMPS, options & 0x07)) return( lp ); else return( NULL ); } /* #if defined develop */ lprec * __WINAPI read_freempsex(void *userhandle, read_modeldata_func read_modeldata, int options) { lprec *lp = NULL; int typeMPS; typeMPS = (options & ~0x07) >> 2; typeMPS &= ~MPSFIXED; typeMPS |= MPSFREE; if(MPS_readex(&lp, userhandle, read_modeldata, typeMPS, options & 0x07)) return( lp ); else return( NULL ); } /* #endif */ MYBOOL __WINAPI write_mps(lprec *lp, char *filename) { return(MPS_writefile(lp, MPSFIXED, filename)); } MYBOOL __WINAPI write_MPS(lprec *lp, FILE *output) { return(MPS_writehandle(lp, MPSFIXED, output)); } MYBOOL __WINAPI write_freemps(lprec *lp, char *filename) { return(MPS_writefile(lp, MPSFREE, filename)); } MYBOOL __WINAPI write_freeMPS(lprec *lp, FILE *output) { return(MPS_writehandle(lp, MPSFREE, output)); } MYBOOL __WINAPI write_lp(lprec *lp, char *filename) { return(LP_writefile(lp, filename)); } MYBOOL __WINAPI write_LP(lprec *lp, FILE *output) { return(LP_writehandle(lp, output)); } #ifndef PARSER_LP MYBOOL __WINAPI LP_readhandle(lprec **lp, FILE *filename, int verbose, char *lp_name) { return(FALSE); } lprec * __WINAPI read_lp(FILE *filename, int verbose, char *lp_name) { return(NULL); } lprec * __WINAPI read_LP(char *filename, int verbose, char *lp_name) { return(NULL); } #endif MYBOOL __WINAPI write_basis(lprec *lp, char *filename) { int typeMPS = MPSFIXED; return( MPS_writeBAS(lp, typeMPS, filename) ); } MYBOOL __WINAPI read_basis(lprec *lp, char *filename, char *info) { int typeMPS = MPSFIXED; typeMPS = MPS_readBAS(lp, typeMPS, filename, info); /* Code basis */ if(typeMPS) { set_action(&lp->spx_action, ACTION_REBASE | ACTION_REINVERT | ACTION_RECOMPUTE); lp->basis_valid = TRUE; /* Do not re-initialize basis on entering Solve */ lp->var_basic[0] = FALSE; /* Set to signal that this is a non-default basis */ } return( (MYBOOL) typeMPS ); } /* Write and read lp_solve parameters (placeholders) - see lp_params.c */ void __WINAPI reset_params(lprec *lp) { int mode; lp->epsmachine = DEF_EPSMACHINE; lp->epsperturb = DEF_PERTURB; lp->lag_accept = DEF_LAGACCEPT; set_epslevel(lp, EPS_DEFAULT); lp->tighten_on_set = FALSE; lp->negrange = DEF_NEGRANGE; #if 0 lp->do_presolve = PRESOLVE_ROWS | PRESOLVE_COLS | PRESOLVE_MERGEROWS | PRESOLVE_REDUCEGCD | PRESOLVE_ROWDOMINATE; #else lp->do_presolve = PRESOLVE_NONE; #endif lp->presolveloops = DEF_MAXPRESOLVELOOPS; lp->scalelimit = DEF_SCALINGLIMIT; lp->scalemode = SCALE_INTEGERS | #if 0 SCALE_POWER2 | SCALE_LOGARITHMIC | SCALE_MEAN; #else SCALE_LINEAR | SCALE_GEOMETRIC | SCALE_EQUILIBRATE; #endif lp->crashmode = CRASH_NONE; lp->max_pivots = 0; lp->simplex_strategy = SIMPLEX_DUAL_PRIMAL; #define PricerDefaultOpt 1 #if PricerDefaultOpt == 1 mode = PRICER_DEVEX; #elif PricerDefaultOpt == 2 mode = PRICER_STEEPESTEDGE; mode |= PRICE_TRUENORMINIT; #else mode = PRICER_STEEPESTEDGE | PRICE_PRIMALFALLBACK; #endif mode |= PRICE_ADAPTIVE; #ifdef EnableRandomizedPricing mode |= PRICE_RANDOMIZE; #endif set_pivoting(lp, mode); lp->improve = IMPROVE_DEFAULT; lp->anti_degen = ANTIDEGEN_DEFAULT; lp->bb_floorfirst = BRANCH_AUTOMATIC; lp->bb_rule = NODE_DYNAMICMODE | NODE_GREEDYMODE | NODE_GAPSELECT | #if 1 NODE_PSEUDOCOSTSELECT | #else NODE_PSEUDOFEASSELECT | #endif NODE_RCOSTFIXING; lp->bb_limitlevel = DEF_BB_LIMITLEVEL; lp->bb_PseudoUpdates = DEF_PSEUDOCOSTUPDATES; lp->bb_heuristicOF = my_chsign(is_maxim(lp), MAX(DEF_INFINITE, lp->infinite)); lp->bb_breakOF = -lp->bb_heuristicOF; lp->sectimeout = 0; lp->solutionlimit = 1; set_outputstream(lp, NULL); /* Set to default output stream */ lp->verbose = NORMAL; lp->print_sol = FALSE; /* Can be FALSE, TRUE, AUTOMATIC (only non-zeros printed) */ lp->spx_trace = FALSE; lp->lag_trace = FALSE; lp->bb_trace = FALSE; } void __WINAPI unscale(lprec *lp) { undoscale(lp); } int __WINAPI solve(lprec *lp) { #if defined FPUexception catchFPU(_EM_INVALID | _EM_ZERODIVIDE | _EM_OVERFLOW | _EM_UNDERFLOW); #endif if(has_BFP(lp)) { lp->solvecount++; if(is_add_rowmode(lp)) set_add_rowmode(lp, FALSE); return(lin_solve(lp)); } else return( NOBFP ); } void __WINAPI print_lp(lprec *lp) { REPORT_lp(lp); } void __WINAPI print_tableau(lprec *lp) { REPORT_tableau(lp); } void __WINAPI print_objective(lprec *lp) { REPORT_objective(lp); } void __WINAPI print_solution(lprec *lp, int columns) { REPORT_solution(lp, columns); } void __WINAPI print_constraints(lprec *lp, int columns) { REPORT_constraints(lp, columns); } void __WINAPI print_duals(lprec *lp) { REPORT_duals(lp); } void __WINAPI print_scales(lprec *lp) { REPORT_scales(lp); } MYBOOL __WINAPI print_debugdump(lprec *lp, char *filename) { return(REPORT_debugdump(lp, filename, (MYBOOL) (get_total_iter(lp) > 0))); } void __WINAPI print_str(lprec *lp, char *str) { report(lp, lp->verbose, "%s", str); } /* ---------------------------------------------------------------------------------- */ /* Parameter setting and retrieval functions */ /* ---------------------------------------------------------------------------------- */ void __WINAPI set_timeout(lprec *lp, long sectimeout) { lp->sectimeout = sectimeout; } long __WINAPI get_timeout(lprec *lp) { return(lp->sectimeout); } void __WINAPI set_verbose(lprec *lp, int verbose) { lp->verbose = verbose; } int __WINAPI get_verbose(lprec *lp) { return(lp->verbose); } void __WINAPI set_print_sol(lprec *lp, int print_sol) { lp->print_sol = print_sol; } int __WINAPI get_print_sol(lprec *lp) { return(lp->print_sol); } void __WINAPI set_debug(lprec *lp, MYBOOL debug) { lp->bb_trace = debug; } MYBOOL __WINAPI is_debug(lprec *lp) { return(lp->bb_trace); } void __WINAPI set_trace(lprec *lp, MYBOOL trace) { lp->spx_trace = trace; } MYBOOL __WINAPI is_trace(lprec *lp) { return(lp->spx_trace); } void __WINAPI set_anti_degen(lprec *lp, int anti_degen) { lp->anti_degen = anti_degen; } int __WINAPI get_anti_degen(lprec *lp) { return(lp->anti_degen); } MYBOOL __WINAPI is_anti_degen(lprec *lp, int testmask) { return((MYBOOL) ((lp->anti_degen == testmask) || ((lp->anti_degen & testmask) != 0))); } void __WINAPI set_presolve(lprec *lp, int presolvemode, int maxloops) { presolvemode &= ~PRESOLVE_REDUCEMIP; /* disable PRESOLVE_REDUCEMIP since it is very rare that this is effective, and also that it adds code complications and delayed presolve effects that are not captured properly. */ lp->do_presolve = presolvemode; lp->presolveloops = maxloops; } int __WINAPI get_presolve(lprec *lp) { return(lp->do_presolve); } int __WINAPI get_presolveloops(lprec *lp) { if(lp->presolveloops < 0) return(DEF_MAXPRESOLVELOOPS); else if(lp->presolveloops == 0) return(MAXINT32); else return(lp->presolveloops); } MYBOOL __WINAPI is_presolve(lprec *lp, int testmask) { return((MYBOOL) ((lp->do_presolve == testmask) || ((lp->do_presolve & testmask) != 0))); } void __WINAPI set_maxpivot(lprec *lp, int maxpivot) { lp->max_pivots = maxpivot; } int __WINAPI get_maxpivot(lprec *lp) { return( lp->bfp_pivotmax(lp) ); } void __WINAPI set_bb_rule(lprec *lp, int bb_rule) { lp->bb_rule = bb_rule; } int __WINAPI get_bb_rule(lprec *lp) { return(lp->bb_rule); } /* INLINE */ MYBOOL is_bb_rule(lprec *lp, int bb_rule) { return( (MYBOOL) ((lp->bb_rule & NODE_STRATEGYMASK) == bb_rule) ); } /* INLINE */ MYBOOL is_bb_mode(lprec *lp, int bb_mask) { return( (MYBOOL) ((lp->bb_rule & bb_mask) > 0) ); } void __WINAPI set_action(int *actionvar, int actionmask) { *actionvar |= actionmask; } void __WINAPI clear_action(int *actionvar, int actionmask) { *actionvar &= ~actionmask; } MYBOOL __WINAPI is_action(int actionvar, int testmask) { return( (MYBOOL) ((actionvar & testmask) != 0) ); } void __WINAPI set_bb_depthlimit(lprec *lp, int bb_maxlevel) { lp->bb_limitlevel = bb_maxlevel; } int __WINAPI get_bb_depthlimit(lprec *lp) { return(lp->bb_limitlevel); } void __WINAPI set_obj_bound(lprec *lp, REAL bb_heuristicOF) { lp->bb_heuristicOF = bb_heuristicOF; } REAL __WINAPI get_obj_bound(lprec *lp) { return(lp->bb_heuristicOF); } void __WINAPI set_mip_gap(lprec *lp, MYBOOL absolute, REAL mip_gap) { if(absolute) lp->mip_absgap = mip_gap; else lp->mip_relgap = mip_gap; } REAL __WINAPI get_mip_gap(lprec *lp, MYBOOL absolute) { if(absolute) return(lp->mip_absgap); else return(lp->mip_relgap); } MYBOOL __WINAPI set_var_branch(lprec *lp, int colnr, int branch_mode) { if(colnr > lp->columns || colnr < 1) { report(lp, IMPORTANT, "set_var_branch: Column %d out of range\n", colnr); return( FALSE ); } if(lp->bb_varbranch == NULL) { int i; if(branch_mode == BRANCH_DEFAULT) return( TRUE ); allocMYBOOL(lp, &lp->bb_varbranch, lp->columns_alloc, FALSE); for(i = 0; i < lp->columns; i++) lp->bb_varbranch[i] = BRANCH_DEFAULT; } lp->bb_varbranch[colnr - 1] = (MYBOOL) branch_mode; return( TRUE ); } int __WINAPI get_var_branch(lprec *lp, int colnr) { if(colnr > lp->columns || colnr < 1) { report(lp, IMPORTANT, "get_var_branch: Column %d out of range\n", colnr); return(lp->bb_floorfirst); } if(lp->bb_varbranch == NULL) return(lp->bb_floorfirst); if(lp->bb_varbranch[colnr - 1] == BRANCH_DEFAULT) return(lp->bb_floorfirst); else return(lp->bb_varbranch[colnr - 1]); } static void set_infiniteex(lprec *lp, REAL infinite, MYBOOL init) { int i; infinite = fabs(infinite); if((init) || is_infinite(lp, lp->bb_heuristicOF)) lp->bb_heuristicOF = my_chsign(is_maxim(lp), infinite); if((init) || is_infinite(lp, lp->bb_breakOF)) lp->bb_breakOF = my_chsign(is_maxim(lp), -infinite); for(i = 0; i <= lp->sum; i++) { if((!init) && is_infinite(lp, lp->orig_lowbo[i])) lp->orig_lowbo[i] = -infinite; if((init) || is_infinite(lp, lp->orig_upbo[i])) lp->orig_upbo[i] = infinite; } lp->infinite = infinite; } MYBOOL __WINAPI is_infinite(lprec *lp, REAL value) { #if 1 return( (MYBOOL) (fabs(value) >= lp->infinite) ); #else if(fabs(value) >= lp->infinite) return( TRUE ); else return( FALSE ); #endif } void __WINAPI set_infinite(lprec *lp, REAL infinite) { set_infiniteex(lp, infinite, FALSE); } REAL __WINAPI get_infinite(lprec *lp) { return(lp->infinite); } void __WINAPI set_epsperturb(lprec *lp, REAL epsperturb) { lp->epsperturb = epsperturb; } REAL __WINAPI get_epsperturb(lprec *lp) { return(lp->epsperturb); } void __WINAPI set_epspivot(lprec *lp, REAL epspivot) { lp->epspivot = epspivot; } REAL __WINAPI get_epspivot(lprec *lp) { return(lp->epspivot); } void __WINAPI set_epsint(lprec *lp, REAL epsint) { lp->epsint = epsint; } REAL __WINAPI get_epsint(lprec *lp) { return(lp->epsint); } void __WINAPI set_epsb(lprec *lp, REAL epsb) { lp->epsprimal = MAX(epsb, lp->epsmachine); } REAL __WINAPI get_epsb(lprec *lp) { return(lp->epsprimal); } void __WINAPI set_epsd(lprec *lp, REAL epsd) { lp->epsdual = MAX(epsd, lp->epsmachine); /* Mainly used as tolerance for reduced cost */ } REAL __WINAPI get_epsd(lprec *lp) { return(lp->epsdual); } void __WINAPI set_epsel(lprec *lp, REAL epsel) { lp->epsvalue = MAX(epsel, lp->epsmachine); } REAL __WINAPI get_epsel(lprec *lp) { return(lp->epsvalue); } MYBOOL __WINAPI set_epslevel(lprec *lp, int epslevel) { REAL SPX_RELAX, MIP_RELAX; switch(epslevel) { case EPS_TIGHT: SPX_RELAX = 1; MIP_RELAX = 1; break; case EPS_MEDIUM: SPX_RELAX = 10; MIP_RELAX = 1; break; case EPS_LOOSE: SPX_RELAX = 100; MIP_RELAX = 10; break; case EPS_BAGGY: SPX_RELAX = 1000; MIP_RELAX = 100; break; default: return( FALSE ); } lp->epsvalue = SPX_RELAX*DEF_EPSVALUE; lp->epsprimal = SPX_RELAX*DEF_EPSPRIMAL; lp->epsdual = SPX_RELAX*DEF_EPSDUAL; lp->epspivot = SPX_RELAX*DEF_EPSPIVOT; lp->epssolution= MIP_RELAX*DEF_EPSSOLUTION; lp->epsint = MIP_RELAX*DEF_EPSINT; lp->mip_absgap = MIP_RELAX*DEF_MIP_GAP; lp->mip_relgap = MIP_RELAX*DEF_MIP_GAP; return( TRUE ); } void __WINAPI set_scaling(lprec *lp, int scalemode) { lp->scalemode = scalemode; } int __WINAPI get_scaling(lprec *lp) { return(lp->scalemode); } MYBOOL __WINAPI is_scalemode(lprec *lp, int testmask) { return((MYBOOL) ((lp->scalemode & testmask) != 0)); } MYBOOL __WINAPI is_scaletype(lprec *lp, int scaletype) { int testtype; testtype = lp->scalemode & SCALE_MAXTYPE; return((MYBOOL) (scaletype == testtype)); } void __WINAPI set_scalelimit(lprec *lp, REAL scalelimit) /* Set the relative scaling convergence criterion for the active scaling mode; the integer part specifies the maximum number of iterations (default = 5). */ { lp->scalelimit = fabs(scalelimit); } REAL __WINAPI get_scalelimit(lprec *lp) { return(lp->scalelimit); } MYBOOL __WINAPI is_integerscaling(lprec *lp) { return(is_scalemode(lp, SCALE_INTEGERS)); } void __WINAPI set_improve(lprec *lp, int improve) { lp->improve = improve; } int __WINAPI get_improve(lprec *lp) { return(lp->improve); } void __WINAPI set_lag_trace(lprec *lp, MYBOOL lag_trace) { lp->lag_trace = lag_trace; } MYBOOL __WINAPI is_lag_trace(lprec *lp) { return(lp->lag_trace); } void __WINAPI set_pivoting(lprec *lp, int pivoting) { /* Set new pivoting strategy */ lp->piv_strategy = pivoting; report(lp, DETAILED, "set_pivoting: Pricing strategy set to '%s'\n", get_str_piv_rule(get_piv_rule(lp))); } int __WINAPI get_pivoting(lprec *lp) { return( lp->piv_strategy ); } /* INLINE */ int get_piv_rule(lprec *lp) { return( (lp->piv_strategy | PRICE_STRATEGYMASK) ^ PRICE_STRATEGYMASK ); } STATIC char *get_str_piv_rule(int rule) { static char *pivotText[PRICER_LASTOPTION+1] = {"Bland first index", "Dantzig", "Devex", "Steepest Edge"}; return( pivotText[rule] ); } MYBOOL __WINAPI is_piv_rule(lprec *lp, int rule) { return( (MYBOOL) (get_piv_rule(lp) == rule) ); } MYBOOL __WINAPI is_piv_mode(lprec *lp, int testmask) { return((MYBOOL) (((testmask & PRICE_STRATEGYMASK) != 0) && ((lp->piv_strategy & testmask) != 0))); } void __WINAPI set_break_at_first(lprec *lp, MYBOOL break_at_first) { lp->bb_breakfirst = break_at_first; } MYBOOL __WINAPI is_break_at_first(lprec *lp) { return(lp->bb_breakfirst); } void __WINAPI set_bb_floorfirst(lprec *lp, int bb_floorfirst) { lp->bb_floorfirst = (MYBOOL) bb_floorfirst; } int __WINAPI get_bb_floorfirst(lprec *lp) { return(lp->bb_floorfirst); } void __WINAPI set_break_at_value(lprec *lp, REAL break_at_value) { lp->bb_breakOF = break_at_value; } REAL __WINAPI get_break_at_value(lprec *lp) { return(lp->bb_breakOF); } void __WINAPI set_negrange(lprec *lp, REAL negrange) { if(negrange <= 0) lp->negrange = negrange; else lp->negrange = 0.0; } REAL __WINAPI get_negrange(lprec *lp) { return(lp->negrange); } int __WINAPI get_max_level(lprec *lp) { return(lp->bb_maxlevel); } COUNTER __WINAPI get_total_nodes(lprec *lp) { return(lp->bb_totalnodes); } COUNTER __WINAPI get_total_iter(lprec *lp) { return(lp->total_iter + lp->current_iter); } REAL __WINAPI get_objective(lprec *lp) { if(lp->spx_status == OPTIMAL) ; else if(!lp->basis_valid) { report(lp, CRITICAL, "get_objective: Not a valid basis\n"); return(0.0); } return( lp->best_solution[0] ); } int __WINAPI get_nonzeros(lprec *lp) { return( mat_nonzeros(lp->matA) ); } MYBOOL __WINAPI set_mat(lprec *lp, int rownr, int colnr, REAL value) { if((rownr < 0) || (rownr > lp->rows)) { report(lp, IMPORTANT, "set_mat: Row %d out of range\n", rownr); return( FALSE ); } if((colnr < 1) || (colnr > lp->columns)) { report(lp, IMPORTANT, "set_mat: Column %d out of range\n", colnr); return( FALSE ); } #ifdef DoMatrixRounding if(rownr == 0) value = roundToPrecision(value, lp->matA->epsvalue); #endif value = scaled_mat(lp, value, rownr, colnr); if(rownr == 0) { lp->orig_obj[colnr] = my_chsign(is_chsign(lp, rownr), value); return( TRUE ); } else return( mat_setvalue(lp->matA, rownr, colnr, value, FALSE) ); } REAL __WINAPI get_working_objective(lprec *lp) { REAL value = 0.0; if(!lp->basis_valid) report(lp, CRITICAL, "get_working_objective: Not a valid basis\n"); else if((lp->spx_status == RUNNING) && (lp->solutioncount == 0)) value = my_chsign(!is_maxim(lp), lp->rhs[0]); else value = lp->solution[0]; return(value); } REAL __WINAPI get_var_primalresult(lprec *lp, int index) { if((index < 0) || (index > lp->presolve_undo->orig_sum)) { report(lp, IMPORTANT, "get_var_primalresult: Index %d out of range\n", index); return( 0.0 ); } if((lp->do_presolve & PRESOLVE_LASTMASKMODE) != PRESOLVE_NONE) return( lp->full_solution[index] ); else return( lp->best_solution[index] ); } REAL __WINAPI get_var_dualresult(lprec *lp, int index) { REAL *duals; if((index < 0) || (index > lp->presolve_undo->orig_sum)) { report(lp, IMPORTANT, "get_var_dualresult: Index %d out of range\n", index); return( 0.0 ); } if(index == 0) return( lp->best_solution[0] ); /* Make sure we actually have dual information available */ if(!get_ptr_sensitivity_rhs(lp, &duals, NULL, NULL)) return( 0.0 ); else duals = ((lp->full_duals == NULL) ? lp->duals : lp->full_duals); return( duals[index] ); } MYBOOL __WINAPI get_variables(lprec *lp, REAL *var) { if(lp->spx_status == OPTIMAL) ; else if(!lp->basis_valid) { report(lp, CRITICAL, "get_variables: Not a valid basis\n"); return(FALSE); } MEMCOPY(var, lp->best_solution + (1 + lp->rows), lp->columns); return(TRUE); } MYBOOL __WINAPI get_ptr_variables(lprec *lp, REAL **var) { if(lp->spx_status == OPTIMAL) ; else if(!lp->basis_valid) { report(lp, CRITICAL, "get_ptr_variables: Not a valid basis\n"); return(FALSE); } if(var != NULL) *var = lp->best_solution + (1 + lp->rows); return(TRUE); } MYBOOL __WINAPI get_constraints(lprec *lp, REAL *constr) { if(lp->spx_status == OPTIMAL) ; else if(!lp->basis_valid) { report(lp, CRITICAL, "get_constraints: Not a valid basis\n"); return(FALSE); } MEMCOPY(constr, lp->best_solution + 1, lp->rows); return(TRUE); } MYBOOL __WINAPI get_ptr_constraints(lprec *lp, REAL **constr) { if(lp->spx_status == OPTIMAL) ; else if(!lp->basis_valid) { report(lp, CRITICAL, "get_ptr_constraints: Not a valid basis\n"); return(FALSE); } if(constr != NULL) *constr = lp->best_solution + 1; return(TRUE); } MYBOOL __WINAPI get_sensitivity_rhs(lprec *lp, REAL *duals, REAL *dualsfrom, REAL *dualstill) { REAL *duals0, *dualsfrom0, *dualstill0; if(!lp->basis_valid) { report(lp, CRITICAL, "get_sensitivity_rhs: Not a valid basis\n"); return(FALSE); } if(!get_ptr_sensitivity_rhs(lp, (duals != NULL) ? &duals0 : NULL, (dualsfrom != NULL) ? &dualsfrom0 : NULL, (dualstill != NULL) ? &dualstill0 : NULL)) return(FALSE); if(duals != NULL) MEMCOPY(duals, duals0, lp->sum); if(dualsfrom != NULL) MEMCOPY(dualsfrom, dualsfrom0, lp->sum); if(dualstill != NULL) MEMCOPY(dualstill, dualstill0, lp->sum); return(TRUE); } MYBOOL __WINAPI get_ptr_sensitivity_rhs(lprec *lp, REAL **duals, REAL **dualsfrom, REAL **dualstill) { if(!lp->basis_valid) { report(lp, CRITICAL, "get_ptr_sensitivity_rhs: Not a valid basis\n"); return(FALSE); } if(duals != NULL) { if(lp->duals == NULL) { if((MIP_count(lp) > 0) && (lp->bb_totalnodes > 0)) { report(lp, CRITICAL, "get_ptr_sensitivity_rhs: Sensitivity unknown\n"); return(FALSE); } if(!construct_duals(lp)) return(FALSE); } *duals = lp->duals + 1; } if((dualsfrom != NULL) || (dualstill != NULL)) { if((lp->dualsfrom == NULL) || (lp->dualstill == NULL)) { if((MIP_count(lp) > 0) && (lp->bb_totalnodes > 0)) { report(lp, CRITICAL, "get_ptr_sensitivity_rhs: Sensitivity unknown\n"); return(FALSE); } construct_sensitivity_duals(lp); if((lp->dualsfrom == NULL) || (lp->dualstill == NULL)) return(FALSE); } if(dualsfrom != NULL) *dualsfrom = lp->dualsfrom + 1; if(dualstill != NULL) *dualstill = lp->dualstill + 1; } return(TRUE); } MYBOOL __WINAPI get_sensitivity_objex(lprec *lp, REAL *objfrom, REAL *objtill, REAL *objfromvalue, REAL *objtillvalue) { REAL *objfrom0, *objtill0, *objfromvalue0, *objtillvalue0; if(!lp->basis_valid) { report(lp, CRITICAL, "get_sensitivity_objex: Not a valid basis\n"); return(FALSE); } if(!get_ptr_sensitivity_objex(lp, (objfrom != NULL) ? &objfrom0 : NULL, (objtill != NULL) ? &objtill0 : NULL, (objfromvalue != NULL) ? &objfromvalue0 : NULL, (objtillvalue != NULL) ? &objtillvalue0 : NULL)) return(FALSE); if((objfrom != NULL) && (objfrom0 != NULL)) MEMCOPY(objfrom, objfrom0, lp->columns); if((objtill != NULL) && (objtill0 != NULL)) MEMCOPY(objtill, objtill0, lp->columns); if((objfromvalue != NULL) && (objfromvalue0 != NULL)) MEMCOPY(objfromvalue, objfromvalue0, lp->columns); if((objtillvalue != NULL) && (objtillvalue0 != NULL)) MEMCOPY(objtillvalue, objtillvalue0, lp->columns); return(TRUE); } MYBOOL __WINAPI get_sensitivity_obj(lprec *lp, REAL *objfrom, REAL *objtill) { return(get_sensitivity_objex(lp, objfrom, objtill, NULL, NULL)); } MYBOOL __WINAPI get_ptr_sensitivity_objex(lprec *lp, REAL **objfrom, REAL **objtill, REAL **objfromvalue, REAL **objtillvalue) { if(!lp->basis_valid) { report(lp, CRITICAL, "get_ptr_sensitivity_objex: Not a valid basis\n"); return(FALSE); } if((objfrom != NULL) || (objtill != NULL)) { if((lp->objfrom == NULL) || (lp->objtill == NULL)) { if((MIP_count(lp) > 0) && (lp->bb_totalnodes > 0)) { report(lp, CRITICAL, "get_ptr_sensitivity_objex: Sensitivity unknown\n"); return(FALSE); } construct_sensitivity_obj(lp); if((lp->objfrom == NULL) || (lp->objtill == NULL)) return(FALSE); } if(objfrom != NULL) *objfrom = lp->objfrom + 1; if(objtill != NULL) *objtill = lp->objtill + 1; } if((objfromvalue != NULL) /* || (objtillvalue != NULL) */) { if((lp->objfromvalue == NULL) /* || (lp->objtillvalue == NULL) */) { if((MIP_count(lp) > 0) && (lp->bb_totalnodes > 0)) { report(lp, CRITICAL, "get_ptr_sensitivity_objex: Sensitivity unknown\n"); return(FALSE); } construct_sensitivity_duals(lp); if((lp->objfromvalue == NULL) /* || (lp->objtillvalue == NULL) */) return(FALSE); } } if(objfromvalue != NULL) *objfromvalue = lp->objfromvalue + 1; if(objtillvalue != NULL) *objtillvalue = NULL /* lp->objtillvalue + 1 */; return(TRUE); } MYBOOL __WINAPI get_ptr_sensitivity_obj(lprec *lp, REAL **objfrom, REAL **objtill) { return(get_ptr_sensitivity_objex(lp, objfrom, objtill, NULL, NULL)); } void __WINAPI set_solutionlimit(lprec *lp, int limit) { lp->solutionlimit = limit; } int __WINAPI get_solutionlimit(lprec *lp) { return(lp->solutionlimit); } int __WINAPI get_solutioncount(lprec *lp) { return(lp->solutioncount); } int __WINAPI get_Nrows(lprec *lp) { return(lp->rows); } int __WINAPI get_Norig_rows(lprec *lp) { if(lp->varmap_locked) return(lp->presolve_undo->orig_rows); else return(lp->rows); } int __WINAPI get_Lrows(lprec *lp) { if(lp->matL == NULL) return( 0 ); else return( lp->matL->rows ); } int __WINAPI get_Ncolumns(lprec *lp) { return(lp->columns); } int __WINAPI get_Norig_columns(lprec *lp) { if(lp->varmap_locked) return(lp->presolve_undo->orig_columns); else return(lp->columns); } /* ---------------------------------------------------------------------------------- */ /* Core routines for lp_solve */ /* ---------------------------------------------------------------------------------- */ int __WINAPI get_status(lprec *lp) { return(lp->spx_status); } char * __WINAPI get_statustext(lprec *lp, int statuscode) { if (statuscode == NOBFP) return("No basis factorization package"); else if (statuscode == DATAIGNORED) return("Invalid input data provided"); else if (statuscode == NOMEMORY) return("Not enough memory available"); else if (statuscode == NOTRUN) return("Model has not been optimized"); else if (statuscode == OPTIMAL) return("OPTIMAL solution"); else if (statuscode == SUBOPTIMAL) return("SUB-OPTIMAL solution"); else if (statuscode == INFEASIBLE) return("Model is primal INFEASIBLE"); else if (statuscode == UNBOUNDED) return("Model is primal UNBOUNDED"); else if (statuscode == RUNNING) return("lp_solve is currently running"); else if (statuscode == NUMFAILURE) return("NUMERIC FAILURE encountered"); else if (statuscode == DEGENERATE) return("DEGENERATE situation"); else if (statuscode == USERABORT) return("User-requested termination"); else if (statuscode == TIMEOUT) return("Termination due to timeout"); else if (statuscode == PRESOLVED) return("Model solved by presolve"); else if (statuscode == PROCFAIL) return("B&B routine failed"); else if (statuscode == PROCBREAK) return("B&B routine terminated"); else if (statuscode == FEASFOUND) return("Feasible B&B solution found"); else if (statuscode == NOFEASFOUND) return("No feasible B&B solution found"); else if (statuscode == FATHOMED) return("Fathomed/pruned branch"); else return("Undefined internal error"); } MYBOOL __WINAPI is_obj_in_basis(lprec *lp) { return( lp->obj_in_basis ); } void __WINAPI set_obj_in_basis(lprec *lp, MYBOOL obj_in_basis) { lp->obj_in_basis = (MYBOOL) (obj_in_basis == TRUE); } lprec * __WINAPI make_lp(int rows, int columns) { lprec *lp; # if defined FORTIFY /* Fortify_EnterScope(); */ # endif if(rows < 0 || columns < 0) return(NULL); lp = (lprec*) calloc(1, sizeof(*lp)); if(!lp) return(NULL); set_lp_name(lp, NULL); lp->names_used = FALSE; lp->use_row_names = TRUE; lp->use_col_names = TRUE; lp->rowcol_name = NULL; /* Do standard initializations ------------------------------------------------------------ */ #if 1 lp->obj_in_basis = DEF_OBJINBASIS; #else lp->obj_in_basis = FALSE; #endif lp->verbose = NORMAL; set_callbacks(lp); set_BFP(lp, NULL); set_XLI(lp, NULL); #if libBLAS > 0 init_BLAS(); #if libBLAS > 1 if(is_nativeBLAS() && !load_BLAS(libnameBLAS)) /*report(lp, "make_lp: Could not load external BLAS library '%s'.\n", libnameBLAS)*/; #endif #endif /* Define the defaults for key user-settable values --------------------------------------- */ reset_params(lp); /* Do other initializations --------------------------------------------------------------- */ lp->source_is_file = FALSE; lp->model_is_pure = TRUE; lp->model_is_valid = FALSE; lp->spx_status = NOTRUN; lp->lag_status = NOTRUN; lp->workarrays = mempool_create(lp); lp->wasPreprocessed = FALSE; lp->wasPresolved = FALSE; presolve_createUndo(lp); lp->bb_varactive = NULL; lp->bb_varbranch = NULL; lp->var_priority = NULL; lp->rhsmax = 0.0; lp->bigM = 0.0; lp->bb_deltaOF = 0.0; lp->equalities = 0; lp->fixedvars = 0; lp->int_vars = 0; lp->sc_vars = 0; lp->sos_ints = 0; lp->sos_vars = 0; lp->sos_priority = NULL; lp->rows_alloc = 0; lp->columns_alloc = 0; lp->sum_alloc = 0; lp->rows = rows; lp->columns = columns; lp->sum = rows + columns; varmap_clear(lp); lp->matA = mat_create(lp, rows, columns, lp->epsvalue); lp->matL = NULL; lp->invB = NULL; lp->duals = NULL; lp->dualsfrom = NULL; lp->dualstill = NULL; lp->objfromvalue = NULL; lp->objfrom = NULL; lp->objtill = NULL; inc_col_space(lp, columns + 1); inc_row_space(lp, rows + 1); /* Avoid bound-checker uninitialized variable error */ lp->orig_lowbo[0] = 0; lp->rootbounds = NULL; lp->bb_bounds = NULL; lp->bb_basis = NULL; lp->basis_valid = FALSE; lp->simplex_mode = SIMPLEX_DYNAMIC; lp->scaling_used = FALSE; lp->columns_scaled = FALSE; lp->P1extraDim = 0; lp->P1extraVal = 0.0; lp->bb_strongbranches = 0; lp->current_iter = 0; lp->total_iter = 0; lp->current_bswap = 0; lp->total_bswap = 0; lp->solutioncount = 0; lp->solvecount = 0; allocINT(lp, &lp->rejectpivot, DEF_MAXPIVOTRETRY + 1, TRUE); set_minim(lp); set_infiniteex(lp, DEF_INFINITE, TRUE); initPricer(lp); /* Call-back routines by KE */ lp->ctrlc = NULL; lp->ctrlchandle = NULL; lp->writelog = NULL; lp->loghandle = NULL; lp->debuginfo = NULL; lp->usermessage = NULL; lp->msgmask = MSG_NONE; lp->msghandle = NULL; lp->timecreate = timeNow(); return(lp); } MYBOOL __WINAPI resize_lp(lprec *lp, int rows, int columns) { MYBOOL status = TRUE; if(columns > lp->columns) status = inc_col_space(lp, columns - lp->columns); else while(status && (lp->columns > columns)) { status = del_column(lp, lp->columns); } if(status && (rows > lp->rows)) status = inc_row_space(lp, rows - lp->rows); else while(status && (lp->rows > rows)) { status = del_constraint(lp, lp->rows); } return( status ); } void __WINAPI free_lp(lprec **plp) { if(plp != NULL) { lprec *lp = *plp; if(lp != NULL) delete_lp(lp); *plp = NULL; } } void __WINAPI delete_lp(lprec *lp) { if(lp == NULL) return; FREE(lp->rowcol_name); FREE(lp->lp_name); FREE(lp->ex_status); if(lp->names_used) { FREE(lp->row_name); FREE(lp->col_name); free_hash_table(lp->rowname_hashtab); free_hash_table(lp->colname_hashtab); } mat_free(&lp->matA); lp->bfp_free(lp); #if LoadInverseLib == TRUE if(lp->hBFP != NULL) set_BFP(lp, NULL); #endif #if LoadLanguageLib == TRUE if(lp->hXLI != NULL) set_XLI(lp, NULL); #endif unset_OF_p1extra(lp); FREE(lp->orig_obj); FREE(lp->orig_rhs); FREE(lp->rhs); FREE(lp->var_type); set_var_weights(lp, NULL); FREE(lp->bb_varbranch); FREE(lp->sc_lobound); FREE(lp->var_is_free); FREE(lp->orig_upbo); FREE(lp->orig_lowbo); FREE(lp->upbo); FREE(lp->lowbo); FREE(lp->var_basic); FREE(lp->is_basic); FREE(lp->is_lower); if(lp->bb_PseudoCost != NULL) { /* report(lp, SEVERE, "delete_lp: The B&B pseudo-cost array was not cleared on delete\n"); */ free_pseudocost(lp); } if(lp->bb_bounds != NULL) { report(lp, SEVERE, "delete_lp: The stack of B&B levels was not empty (failed at %.0f nodes)\n", (double) lp->bb_totalnodes); unload_BB(lp); } if(lp->bb_basis != NULL) { /* report(lp, SEVERE, "delete_lp: The stack of saved bases was not empty on delete\n"); */ unload_basis(lp, FALSE); } FREE(lp->rejectpivot); partial_freeBlocks(&(lp->rowblocks)); partial_freeBlocks(&(lp->colblocks)); multi_free(&(lp->multivars)); multi_free(&(lp->longsteps)); FREE(lp->solution); FREE(lp->best_solution); FREE(lp->full_solution); presolve_freeUndo(lp); mempool_free(&(lp->workarrays)); freePricer(lp); FREE(lp->drow); FREE(lp->nzdrow); FREE(lp->duals); FREE(lp->full_duals); FREE(lp->dualsfrom); FREE(lp->dualstill); FREE(lp->objfromvalue); FREE(lp->objfrom); FREE(lp->objtill); FREE(lp->row_type); if(lp->sos_vars > 0) FREE(lp->sos_priority); free_SOSgroup(&(lp->SOS)); free_SOSgroup(&(lp->GUB)); freecuts_BB(lp); if(lp->scaling_used) FREE(lp->scalars); if(lp->matL != NULL) { FREE(lp->lag_rhs); FREE(lp->lambda); FREE(lp->lag_con_type); mat_free(&lp->matL); } if(lp->streamowned) set_outputstream(lp, NULL); #if libBLAS > 0 if(!is_nativeBLAS()) unload_BLAS(); #endif FREE(lp); # if defined FORTIFY /* Fortify_LeaveScope(); */ # endif } static MYBOOL get_SOS(lprec *lp, int index, char *name, int *sostype, int *priority, int *count, int *sosvars, REAL *weights) { SOSrec *SOS; if((index < 1) || (index > SOS_count(lp))) return( FALSE ); SOS = lp->SOS->sos_list[index-1]; if(name != NULL) strcpy(name, SOS->name); if(sostype != NULL) *sostype = SOS->type; if(priority != NULL) *priority = SOS->priority; if(count != NULL) { *count = SOS->size; if(sosvars != NULL) { int i; for(i = 1; i <= *count; i++) { sosvars[i-1] = SOS->members[i]; if(weights != NULL) weights[i-1] = SOS->weights[i]; } } } return( TRUE ); } /* Make a copy of the existing model using (mostly) high-level construction routines to simplify future maintainance. */ lprec* __WINAPI copy_lp(lprec *lp) { int i, n, *idx = NULL; REAL hold, *val = NULL, infinite; lprec *newlp = NULL; char buf[256], ok = FALSE; int sostype, priority, count, *sosvars, rows, columns; REAL *weights; #if 0 if(lp->wasPresolved) return( newlp ); #endif rows = get_Nrows(lp); columns = get_Ncolumns(lp); if(!allocINT(lp, &idx, rows+1, FALSE) || !allocREAL(lp, &val, rows+1, FALSE)) goto Finish; /* Create the new object */ newlp = make_lp(rows, 0); if(newlp == NULL) goto Finish; if(!resize_lp(newlp, rows, columns)) goto Finish; set_sense(newlp, is_maxim(lp)); set_use_names(newlp, FALSE, is_use_names(lp, FALSE)); set_use_names(newlp, TRUE, is_use_names(lp, TRUE)); if(!set_lp_name(newlp, get_lp_name(lp))) goto Finish; /* set_algopt(newlp, get_algopt(lp)); */ /* v6 */ set_verbose(newlp, get_verbose(lp)); /* Transfer standard simplex parameters */ set_epspivot(newlp, get_epspivot(lp)); set_epsel(newlp, get_epsel(lp)); set_epsb(newlp, get_epsb(lp)); set_epsd(newlp, get_epsd(lp)); set_pivoting(newlp, get_pivoting(lp)); set_negrange(newlp, lp->negrange); set_infinite(newlp, get_infinite(lp)); set_presolve(newlp, get_presolve(lp), get_presolveloops(lp)); set_scaling(newlp, get_scaling(lp)); set_scalelimit(newlp, get_scalelimit(lp)); set_simplextype(newlp, get_simplextype(lp)); set_epsperturb(newlp, get_epsperturb(lp)); set_anti_degen(newlp, get_anti_degen(lp)); set_improve(newlp, get_improve(lp)); set_basiscrash(newlp, get_basiscrash(lp)); set_maxpivot(newlp, get_maxpivot(lp)); set_timeout(newlp, get_timeout(lp)); /* Transfer MILP parameters */ set_epsint(newlp, get_epsint(lp)); set_bb_rule(newlp, get_bb_rule(lp)); set_bb_depthlimit(newlp, get_bb_depthlimit(lp)); set_bb_floorfirst(newlp, get_bb_floorfirst(lp)); set_mip_gap(newlp, TRUE, get_mip_gap(lp, TRUE)); set_mip_gap(newlp, FALSE, get_mip_gap(lp, FALSE)); set_break_at_first(newlp, is_break_at_first(lp)); set_break_at_value(newlp, get_break_at_value(lp)); /* Set RHS and range */ infinite = get_infinite(lp); for(i = 0; i <= rows; i++) { if(i > 0) if(!set_constr_type(newlp, i, get_constr_type(lp, i))) goto Finish; if(!set_rh(newlp, i, get_rh(lp, i))) goto Finish; if((i > 0) && ((hold = get_rh_range(lp, i)) < infinite)) if(!set_rh_range(newlp, i, hold)) goto Finish; if(lp->names_used && lp->use_row_names && (lp->row_name[i] != NULL) && (lp->row_name[i]->name != NULL)) if(!set_row_name(newlp, i, get_row_name(lp, i))) goto Finish; } /* Load the constraint matrix and variable definitions */ for(i = 1; i <= columns; i++) { n = get_columnex(lp, i, val, idx); if ((n < 0) || (!add_columnex(newlp, n, val, idx))) goto Finish; if(is_binary(lp, i)) { if (!set_binary(newlp, i, TRUE)) goto Finish; } else { if(is_int(lp, i)) if(!set_int(newlp, i, TRUE)) goto Finish; if((hold = get_lowbo(lp, i)) != 0) if(!set_lowbo(newlp, i, hold)) goto Finish; if((hold = get_upbo(lp, i)) < infinite) if(!set_upbo(newlp, i, hold)) goto Finish; } if(is_semicont(lp, i)) if(!set_semicont(newlp, i, TRUE)) goto Finish; if(lp->names_used && lp->use_col_names && (lp->col_name[i] != NULL) && (lp->col_name[i]->name != NULL)) if(!set_col_name(newlp, i, get_col_name(lp, i))) goto Finish; } /* copy SOS data */ for(i = 1; get_SOS(lp, i, buf, &sostype, &priority, &count, NULL, NULL); i++) if (count) { if(!allocINT(lp, &sosvars, count, FALSE) || !allocREAL(lp, &weights, count, FALSE)) n = 0; else { get_SOS(lp, i, buf, &sostype, &priority, &count, sosvars, weights); n = add_SOS(newlp, buf, sostype, priority, count, sosvars, weights); } FREE(weights); FREE(sosvars); if(n == 0) goto Finish; } #if 0 /* Other parameters set if the source model was previously solved */ if(lp->solvecount > 0) { MEMCOPY(newlp->scalars, lp->scalars, lp->sum+1); MEMCOPY(newlp->var_basic, lp->var_basic, rows+1); MEMCOPY(newlp->is_basic, lp->is_basic, lp->sum+1); MEMCOPY(newlp->is_lower, lp->is_lower, lp->sum+1); MEMCOPY(newlp->solution, lp->solution, lp->sum+1); if(lp->duals != NULL) { allocREAL(newlp, &newlp->duals, newlp->sum_alloc+1, FALSE); MEMCOPY(newlp->duals, lp->duals, lp->sum+1); } newlp->solutioncount = lp->solutioncount; newlp->solvecount = lp->solvecount; } #endif ok = TRUE; /* Clean up before returning */ Finish: if(!ok) free_lp(&newlp); FREE(val); FREE(idx); return( newlp ); } MYBOOL __WINAPI dualize_lp(lprec *lp) { int i, n; MATrec *mat = lp->matA; REAL *item; /* Are we allowed to perform the operation? */ if((MIP_count(lp) > 0) || (lp->solvecount > 0)) return( FALSE ); /* Modify sense */ set_sense(lp, (MYBOOL) !is_maxim(lp)); /* Transpose matrix and reverse signs */ n = mat_nonzeros(mat); mat_transpose(mat); item = &COL_MAT_VALUE(0); for(i = 0; i < n; i++, item += matValueStep) *item *= -1; /* Row-column swap other vectors */ swapINT(&lp->rows, &lp->columns); swapINT(&lp->rows_alloc, &lp->columns_alloc); swapREAL(lp->orig_rhs, lp->orig_obj); if ((lp->rhs != NULL) && (lp->obj != NULL)) swapREAL(lp->rhs, lp->obj); /* Reallocate storage */ /* var_type sc_bound solution best_solution full_solution duals */ /* Shift variable bounds */ /* is_basic orig_upbo orig_lowbo scalars */ return( TRUE ); } /* Optimize memory usage */ STATIC MYBOOL memopt_lp(lprec *lp, int rowextra, int colextra, int nzextra) { MYBOOL status = FALSE; if(lp == NULL) return( status ); status = mat_memopt(lp->matA, rowextra, colextra, nzextra) && (++rowextra > 0) && (++colextra > 0) && (++nzextra > 0); #if 0 /* inc_ routines not well-tested for reduction in size allocation */ if(status) { int colalloc = lp->columns_alloc - MIN(lp->columns_alloc, lp->columns + colextra), rowalloc = lp->rows_alloc - MIN(lp->rows_alloc, lp->rows + rowextra); status = inc_lag_space(lp, rowalloc, FALSE) && inc_row_space(lp, rowalloc) && inc_col_space(lp, colalloc); } #endif return( status ); } /* Utility routine group for constraint and column deletion/insertion mapping in relation to the original set of constraints and columns */ STATIC void varmap_lock(lprec *lp) { presolve_fillUndo(lp, lp->rows, lp->columns, TRUE); lp->varmap_locked = TRUE; } STATIC void varmap_clear(lprec *lp) { presolve_setOrig(lp, 0, 0); lp->varmap_locked = FALSE; } STATIC MYBOOL varmap_canunlock(lprec *lp) { /* Don't do anything if variables aren't locked yet */ if(lp->varmap_locked) { int i; presolveundorec *psundo = lp->presolve_undo; /* Check for the obvious */ if(/*lp->names_used || (psundo->orig_columns != lp->columns) || (psundo->orig_rows != lp->rows)) */ (psundo->orig_columns > lp->columns) || (psundo->orig_rows > lp->rows)) return( FALSE ); /* Check for deletions */ for(i = psundo->orig_rows + psundo->orig_columns; i > 0; i--) if(psundo->orig_to_var[i] == 0) return( FALSE ); /* Check for insertions */ for(i = lp->sum; i > 0; i--) if(psundo->var_to_orig[i] == 0) return( FALSE ); } return( TRUE ); } STATIC void varmap_add(lprec *lp, int base, int delta) { int i, ii; presolveundorec *psundo = lp->presolve_undo; /* Don't do anything if variables aren't locked yet */ if(!lp->varmap_locked) return; /* Set new constraints/columns to have an "undefined" mapping to original constraints/columns (assumes that counters have NOT yet been updated) */ for(i = lp->sum; i >= base; i--) { ii = i + delta; psundo->var_to_orig[ii] = psundo->var_to_orig[i]; } /* Initialize map of added rows/columns */ for(i = 0; i < delta; i++) { ii = base + i; psundo->var_to_orig[ii] = 0; } } STATIC void varmap_delete(lprec *lp, int base, int delta, LLrec *varmap) { int i, ii, j; MYBOOL preparecompact = (MYBOOL) (varmap != NULL); presolveundorec *psundo = lp->presolve_undo; /* Set the model "dirty" if we are deleting row of constraint */ lp->model_is_pure &= (MYBOOL) ((lp->solutioncount == 0) && !preparecompact); /* Don't do anything if 1) variables aren't locked yet, or 2) the constraint was added after the variables were locked */ if(!lp->varmap_locked) { #if 0 if(lp->names_used) varmap_lock(lp); else return; #else if(!lp->model_is_pure && lp->names_used) varmap_lock(lp); #endif } /* Do mass deletion via a linked list */ preparecompact = (MYBOOL) (varmap != NULL); if(preparecompact) { preparecompact = (MYBOOL) (base > lp->rows); /* Set TRUE for columns */ for(j = firstInactiveLink(varmap); j != 0; j = nextInactiveLink(varmap, j)) { i = j; if(preparecompact) { #ifdef Paranoia if(SOS_is_member(lp->SOS, 0, j)) report(lp, SEVERE, "varmap_delete: Deleting variable %d, which is in a SOS!\n", j); #endif i += lp->rows; } ii = psundo->var_to_orig[i]; if(ii > 0) /* It was an original variable; reverse sign of index to flag deletion */ psundo->var_to_orig[i] = -ii; else /* It was a non-original variable; add special code for deletion */ psundo->var_to_orig[i] = -(psundo->orig_rows+psundo->orig_columns+i); } return; } /* Do legacy simplified version if we are doing batch delete operations */ preparecompact = (MYBOOL) (base < 0); if(preparecompact) { base = -base; if(base > lp->rows) base += (psundo->orig_rows - lp->rows); for(i = base; i < base-delta; i++) { ii = psundo->var_to_orig[i]; if(ii > 0) /* It was an original variable; reverse sign of index to flag deletion */ psundo->var_to_orig[i] = -ii; else /* It was a non-original variable; add special code for deletion */ psundo->var_to_orig[i] = -(psundo->orig_rows+psundo->orig_columns+i); } return; } /* We are deleting an original constraint/column; 1) clear mapping of original to deleted 2) shift the deleted variable to original mappings left 3) decrement all subsequent original-to-current pointers */ if(varmap_canunlock(lp)) lp->varmap_locked = FALSE; for(i = base; i < base-delta; i++) { ii = psundo->var_to_orig[i]; if(ii > 0) psundo->orig_to_var[ii] = 0; } for(i = base; i <= lp->sum+delta; i++) { ii = i - delta; psundo->var_to_orig[i] = psundo->var_to_orig[ii]; } i = 1; j = psundo->orig_rows; if(base > lp->rows) { i += j; j += psundo->orig_columns; } ii = base-delta; for(; i <= j; i++) { if(psundo->orig_to_var[i] >= ii) psundo->orig_to_var[i] += delta; } } STATIC MYBOOL varmap_validate(lprec *lp, int varno) { MYBOOL success = TRUE; int i, ii, ix, ie, n_rows = lp->rows, orig_sum = lp->presolve_undo->orig_sum, orig_rows = lp->presolve_undo->orig_rows; if(varno <= 0) { varno = 1; ie = orig_sum; } else ie = varno; for(i = varno; success && (i <= ie); i++) { ix = lp->presolve_undo->orig_to_var[i]; if((ix > 0) && (i > orig_rows)) ix += n_rows; /* Check for index out of range due to presolve */ success = (MYBOOL) (ix <= orig_sum); if(!success) report(lp, SEVERE, "varmap_validate: Invalid new mapping found for variable %d\n", i); else if(ix != 0) { ii = lp->presolve_undo->var_to_orig[ix]; if(ix > n_rows) ii += orig_rows; success = (MYBOOL) (ii == i); if(!success) report(lp, SEVERE, "varmap_validate: Invalid old mapping found for variable %d (%d)\n", i, ii); } } return( success ); } STATIC void varmap_compact(lprec *lp, int prev_rows, int prev_cols) { presolveundorec *psundo = lp->presolve_undo; int i, ii, n_sum, n_rows, orig_rows = psundo->orig_rows, prev_sum = prev_rows + prev_cols; /* Nothing to do if the model is not "dirty" or the variable map is not locked */ if(lp->model_is_pure || !lp->varmap_locked) return; /* We are deleting an original constraint/column; 1) clear mapping of original to deleted 2) shift the deleted variable to original mappings left 3) decrement all subsequent original-to-current pointers */ n_sum = 0; n_rows = 0; for(i = 1; i <= prev_sum; i++) { ii = psundo->var_to_orig[i]; /* Process variable if it was deleted in the previous round */ if(ii < 0) { ii = -ii; /* Update map back if we have an original variable, otherwise just skip */ if(i <= prev_rows) psundo->orig_to_var[ii] = 0; else psundo->orig_to_var[orig_rows+ii] = 0; } /* Otherwise shift and update map back */ else { n_sum++; /* Shift only if necessary */ if(n_sum < i) psundo->var_to_orig[n_sum] = ii; /* Update map back if we have an original variable */ if(ii > 0) { if(i <= prev_rows) { psundo->orig_to_var[ii] = n_sum; n_rows = n_sum; } else psundo->orig_to_var[orig_rows+ii] = n_sum-n_rows; } } } #ifdef xxParanoia if(!varmap_validate(lp, 0)) report(lp, SEVERE, "varmap_compact: Internal presolve mapping error at exit\n"); #endif } /* Utility group for shifting row and column data */ STATIC MYBOOL shift_rowcoldata(lprec *lp, int base, int delta, LLrec *usedmap, MYBOOL isrow) /* Note: Assumes that "lp->sum" and "lp->rows" HAVE NOT been updated to the new counts */ { int i, ii; REAL lodefault; /* Shift data right/down (insert), and set default values in positive delta-gap */ if(delta > 0) { /* Determine if we can take the easy way out */ MYBOOL easyout = (MYBOOL) ((lp->solvecount == 0) && (base > lp->rows)); /* Shift the row/column data */ MEMMOVE(lp->orig_upbo + base + delta, lp->orig_upbo + base, lp->sum - base + 1); MEMMOVE(lp->orig_lowbo + base + delta, lp->orig_lowbo + base, lp->sum - base + 1); if(!easyout) { MEMMOVE(lp->upbo + base + delta, lp->upbo + base, lp->sum - base + 1); MEMMOVE(lp->lowbo + base + delta, lp->lowbo + base, lp->sum - base + 1); if(lp->model_is_valid) { MEMMOVE(lp->solution + base + delta, lp->solution + base, lp->sum - base + 1); MEMMOVE(lp->best_solution + base + delta, lp->best_solution + base, lp->sum - base + 1); } MEMMOVE(lp->is_lower + base + delta, lp->is_lower + base, lp->sum - base + 1); } /* Deal with scalars; the vector can be NULL */ if(lp->scalars != NULL) { if(!easyout) for(ii = lp->sum; ii >= base; ii--) { i = ii + delta; lp->scalars[i] = lp->scalars[ii]; } for(ii = base; ii < base + delta; ii++) lp->scalars[ii] = 1; } /* Set defaults */ #ifdef SlackInitMinusInf if(isrow) lodefault = -lp->infinite; else #endif lodefault = 0; for(i = 0; i < delta; i++) { ii = base + i; lp->orig_upbo[ii] = lp->infinite; lp->orig_lowbo[ii] = lodefault; if(!easyout) { lp->upbo[ii] = lp->orig_upbo[ii]; lp->lowbo[ii] = lp->orig_lowbo[ii]; lp->is_lower[ii] = TRUE; } } } /* Shift data left/up (delete) */ else if(usedmap != NULL) { int k, offset = 0; if(!isrow) offset += lp->rows; i = offset + 1; for(k = firstActiveLink(usedmap); k != 0; i++, k = nextActiveLink(usedmap, k)) { ii = k + offset; if(ii == i) continue; lp->upbo[i] = lp->upbo[ii]; lp->orig_upbo[i] = lp->orig_upbo[ii]; lp->lowbo[i] = lp->lowbo[ii]; lp->orig_lowbo[i] = lp->orig_lowbo[ii]; lp->solution[i] = lp->solution[ii]; lp->best_solution[i] = lp->best_solution[ii]; lp->is_lower[i] = lp->is_lower[ii]; if(lp->scalars != NULL) lp->scalars[i] = lp->scalars[ii]; } if(isrow) { base = lp->rows + 1; MEMMOVE(lp->upbo + i, lp->upbo + base, lp->columns); MEMMOVE(lp->orig_upbo + i, lp->orig_upbo + base, lp->columns); MEMMOVE(lp->lowbo + i, lp->lowbo + base, lp->columns); MEMMOVE(lp->orig_lowbo + i, lp->orig_lowbo + base, lp->columns); if(lp->model_is_valid) { MEMMOVE(lp->solution + i, lp->solution + base, lp->columns); MEMMOVE(lp->best_solution + i, lp->best_solution + base, lp->columns); } MEMMOVE(lp->is_lower + i, lp->is_lower + base, lp->columns); if(lp->scalars != NULL) MEMMOVE(lp->scalars + i, lp->scalars + base, lp->columns); } } else if(delta < 0) { /* First make sure we don't cross the sum count border */ if(base-delta-1 > lp->sum) delta = base - lp->sum - 1; /* Shift the data*/ for(i = base; i <= lp->sum + delta; i++) { ii = i - delta; lp->upbo[i] = lp->upbo[ii]; lp->orig_upbo[i] = lp->orig_upbo[ii]; lp->lowbo[i] = lp->lowbo[ii]; lp->orig_lowbo[i] = lp->orig_lowbo[ii]; lp->solution[i] = lp->solution[ii]; lp->best_solution[i] = lp->best_solution[ii]; lp->is_lower[i] = lp->is_lower[ii]; if(lp->scalars != NULL) lp->scalars[i] = lp->scalars[ii]; } } lp->sum += delta; lp->matA->row_end_valid = FALSE; return(TRUE); } STATIC MYBOOL shift_basis(lprec *lp, int base, int delta, LLrec *usedmap, MYBOOL isrow) /* Note: Assumes that "lp->sum" and "lp->rows" HAVE NOT been updated to the new counts */ { int i, ii; MYBOOL Ok = TRUE; /* Don't bother to shift the basis if it is not yet ready */ if(!is_BasisReady(lp)) return( Ok ); /* Basis adjustments due to insertions (after actual row/column insertions) */ if(delta > 0) { /* Determine if the basis becomes invalidated */ if(isrow) set_action(&lp->spx_action, ACTION_REBASE | ACTION_REINVERT); /* Shift and fix invalid basis references (increment higher order basic variable index) */ if(base <= lp->sum) MEMMOVE(lp->is_basic + base + delta, lp->is_basic + base, lp->sum - base + 1); /* Prevent CPU-expensive basis updating if this is the initial model creation */ if(!lp->model_is_pure || (lp->solvecount > 0)) for(i = 1; i <= lp->rows; i++) { ii = lp->var_basic[i]; if(ii >= base) lp->var_basic[i] += delta; } /* Update the basis (shift and extend) */ for(i = 0; i < delta; i++) { ii = base + i; lp->is_basic[ii] = isrow; if(isrow) lp->var_basic[lp->rows+1+i] = ii; } } /* Basis adjustments due to deletions (after actual row/column deletions) */ else { int j,k; /* Fix invalid basis references (decrement high basic slack variable indexes), but reset the entire basis if a deleted variable is found in the basis */ k = 0; for(i = 1; i <= lp->rows; i++) { ii = lp->var_basic[i]; lp->is_basic[ii] = FALSE; if(ii >= base) { /* Skip to next basis variable if this one is to be deleted */ if(ii < base-delta) { set_action(&lp->spx_action, ACTION_REBASE); continue; } /* Otherwise, update the index of the basic variable for deleted variables */ ii += delta; } k++; lp->var_basic[k] = ii; } /* Set the new basis indicators */ i = k; if(isrow) i = MIN(k, lp->rows+delta); for(; i > 0; i--) { j = lp->var_basic[i]; lp->is_basic[j] = TRUE; } /* If a column was deleted from the basis then simply add back a non-basic slack variable; do two scans, if necessary to avoid adding equality slacks */ if(!isrow && (k < lp->rows)) { for(j = 0; j <= 1; j++) for(i = 1; (i <= lp->rows) && (k < lp->rows); i++) if(!lp->is_basic[i]) { if(!is_constr_type(lp, i, EQ) || (j == 1)) { k++; lp->var_basic[k] = i; lp->is_basic[i] = TRUE; } } k = 0; } /* We are left with "k" indexes; if no basis variable was deleted, k=rows and the inverse is still valid, if k+delta < 0 we do not have a valid basis and must create one (in most usage modes this should not happen, unless there is a bug) */ if(k+delta < 0) Ok = FALSE; if(isrow || (k != lp->rows)) set_action(&lp->spx_action, ACTION_REINVERT); } return(Ok); } STATIC MYBOOL shift_rowdata(lprec *lp, int base, int delta, LLrec *usedmap) /* Note: Assumes that "lp->rows" HAS NOT been updated to the new count */ { int i, ii; /* Shift sparse matrix row data */ if(lp->matA->is_roworder) mat_shiftcols(lp->matA, &base, delta, usedmap); else mat_shiftrows(lp->matA, &base, delta, usedmap); /* Shift data down (insert row), and set default values in positive delta-gap */ if(delta > 0) { /* Shift row data */ for(ii = lp->rows; ii >= base; ii--) { i = ii + delta; lp->orig_rhs[i] = lp->orig_rhs[ii]; lp->rhs[i] = lp->rhs[ii]; lp->row_type[i] = lp->row_type[ii]; } /* Set defaults (actual basis set in separate procedure) */ for(i = 0; i < delta; i++) { ii = base + i; lp->orig_rhs[ii] = 0; lp->rhs[ii] = 0; lp->row_type[ii] = ROWTYPE_EMPTY; } } /* Shift data up (delete row) */ else if(usedmap != NULL) { for(i = 1, ii = firstActiveLink(usedmap); ii != 0; i++, ii = nextActiveLink(usedmap, ii)) { if(i == ii) continue; lp->orig_rhs[i] = lp->orig_rhs[ii]; lp->rhs[i] = lp->rhs[ii]; lp->row_type[i] = lp->row_type[ii]; } delta = i - lp->rows - 1; } else if(delta < 0) { /* First make sure we don't cross the row count border */ if(base-delta-1 > lp->rows) delta = base - lp->rows - 1; /* Shift row data (don't shift basis indexes here; done in next step) */ for(i = base; i <= lp->rows + delta; i++) { ii = i - delta; lp->orig_rhs[i] = lp->orig_rhs[ii]; lp->rhs[i] = lp->rhs[ii]; lp->row_type[i] = lp->row_type[ii]; } } shift_basis(lp, base, delta, usedmap, TRUE); shift_rowcoldata(lp, base, delta, usedmap, TRUE); inc_rows(lp, delta); return(TRUE); } STATIC MYBOOL shift_coldata(lprec *lp, int base, int delta, LLrec *usedmap) /* Note: Assumes that "lp->columns" has NOT been updated to the new count */ { int i, ii; free_duals(lp); /* Shift A matrix data */ if(lp->matA->is_roworder) mat_shiftrows(lp->matA, &base, delta, usedmap); else mat_shiftcols(lp->matA, &base, delta, usedmap); /* Shift data right (insert), and set default values in positive delta-gap */ if(delta > 0) { /* Fix variable priority data */ if((lp->var_priority != NULL) && (base <= lp->columns)) { for(i = 0; i < lp->columns; i++) if(lp->var_priority[i] >= base) lp->var_priority[i] += delta; } if((lp->sos_priority != NULL) && (base <= lp->columns)) { for(i = 0; i < lp->sos_vars; i++) if(lp->sos_priority[i] >= base) lp->sos_priority[i] += delta; } /* Fix invalid split variable data */ if((lp->var_is_free != NULL) && (base <= lp->columns)) { for(i = 1; i <= lp->columns; i++) if(abs(lp->var_is_free[i]) >= base) lp->var_is_free[i] += my_chsign(lp->var_is_free[i] < 0, delta); } /* Shift column data right */ for(ii = lp->columns; ii >= base; ii--) { i = ii + delta; lp->var_type[i] = lp->var_type[ii]; lp->sc_lobound[i] = lp->sc_lobound[ii]; lp->orig_obj[i] = lp->orig_obj[ii]; if(lp->obj != NULL) lp->obj[i] = lp->obj[ii]; /* if(lp->objfromvalue != NULL) lp->objfromvalue[i] = lp->objfromvalue[ii]; if(lp->objfrom != NULL) lp->objfrom[i] = lp->objfrom[ii]; if(lp->objtill != NULL) lp->objtill[i] = lp->objtill[ii]; */ if(lp->var_priority != NULL) lp->var_priority[i-1] = lp->var_priority[ii-1]; if(lp->bb_varbranch != NULL) lp->bb_varbranch[i-1] = lp->bb_varbranch[ii-1]; if(lp->var_is_free != NULL) lp->var_is_free[i] = lp->var_is_free[ii]; if(lp->best_solution != NULL) lp->best_solution[lp->rows + i] = lp->best_solution[lp->rows + ii]; } /* Set defaults */ for(i = 0; i < delta; i++) { ii = base + i; lp->var_type[ii] = ISREAL; lp->sc_lobound[ii] = 0; lp->orig_obj[ii] = 0; if(lp->obj != NULL) lp->obj[ii] = 0; /* if(lp->objfromvalue != NULL) lp->objfromvalue[ii] = 0; if(lp->objfrom != NULL) lp->objfrom[ii] = 0; if(lp->objtill != NULL) lp->objtill[ii] = 0; */ if(lp->var_priority != NULL) lp->var_priority[ii-1] = ii; if(lp->bb_varbranch != NULL) lp->bb_varbranch[ii-1] = BRANCH_DEFAULT; if(lp->var_is_free != NULL) lp->var_is_free[ii] = 0; if(lp->best_solution != NULL) lp->best_solution[lp->rows + ii] = 0; } } /* Shift data left (delete) */ else if(usedmap != NULL) { /* Assume there is no need to handle split columns, since we are doing this only from presolve, which comes before splitting of columns. */ /* First update counts */ if(lp->int_vars + lp->sc_vars > 0) for(ii = firstInactiveLink(usedmap); ii != 0; ii = nextInactiveLink(usedmap, ii)) { if(is_int(lp, ii)) { lp->int_vars--; if(SOS_is_member(lp->SOS, 0, ii)) lp->sos_ints--; } if(is_semicont(lp, ii)) lp->sc_vars--; } /* Shift array members */ for(i = 1, ii = firstActiveLink(usedmap); ii != 0; i++, ii = nextActiveLink(usedmap, ii)) { if(i == ii) continue; lp->var_type[i] = lp->var_type[ii]; lp->sc_lobound[i] = lp->sc_lobound[ii]; lp->orig_obj[i] = lp->orig_obj[ii]; if(lp->obj != NULL) lp->obj[i] = lp->obj[ii]; /* if(lp->objfromvalue != NULL) lp->objfromvalue[i] = lp->objfromvalue[ii]; if(lp->objfrom != NULL) lp->objfrom[i] = lp->objfrom[ii]; if(lp->objtill != NULL) lp->objtill[i] = lp->objtill[ii]; */ if(lp->bb_varbranch != NULL) lp->bb_varbranch[i-1] = lp->bb_varbranch[ii-1]; if(lp->var_is_free != NULL) lp->var_is_free[i] = lp->var_is_free[ii]; if(lp->best_solution != NULL) lp->best_solution[lp->rows + i] = lp->best_solution[lp->rows + ii]; } /* Shift variable priority data */ if((lp->var_priority != NULL) || (lp->sos_priority != NULL)) { int *colmap = NULL, k; allocINT(lp, &colmap, lp->columns + 1, TRUE); for(i = 1, ii = 0; i <= lp->columns; i++) { if(isActiveLink(usedmap, i)) { ii++; colmap[i] = ii; } } if(lp->var_priority != NULL) { for(i = 0, ii = 0; i < lp->columns; i++) { k = colmap[lp->var_priority[i]]; if(k > 0) { lp->var_priority[ii] = k; ii++; } } } if(lp->sos_priority != NULL) { for(i = 0, ii = 0; i < lp->sos_vars; i++) { k = colmap[lp->sos_priority[i]]; if(k > 0) { lp->sos_priority[ii] = k; ii++; } } lp->sos_vars = ii; } FREE(colmap); } delta = i - lp->columns - 1; } else if(delta < 0) { /* Fix invalid split variable data */ if(lp->var_is_free != NULL) { for(i = 1; i <= lp->columns; i++) if(abs(lp->var_is_free[i]) >= base) lp->var_is_free[i] -= my_chsign(lp->var_is_free[i] < 0, delta); } /* Shift column data (excluding the basis) */ for(i = base; i < base-delta; i++) { if(is_int(lp, i)) { lp->int_vars--; if(SOS_is_member(lp->SOS, 0, i)) lp->sos_ints--; } if(is_semicont(lp, i)) lp->sc_vars--; } for(i = base; i <= lp->columns + delta; i++) { ii = i - delta; lp->var_type[i] = lp->var_type[ii]; lp->sc_lobound[i] = lp->sc_lobound[ii]; lp->orig_obj[i] = lp->orig_obj[ii]; if(lp->obj != NULL) lp->obj[i] = lp->obj[ii]; /* if(lp->objfromvalue != NULL) lp->objfromvalue[i] = lp->objfromvalue[ii]; if(lp->objfrom != NULL) lp->objfrom[i] = lp->objfrom[ii]; if(lp->objtill != NULL) lp->objtill[i] = lp->objtill[ii]; */ if(lp->var_priority != NULL) lp->var_priority[i-1] = lp->var_priority[ii-1]; if(lp->bb_varbranch != NULL) lp->bb_varbranch[i-1] = lp->bb_varbranch[ii-1]; if(lp->var_is_free != NULL) lp->var_is_free[i] = lp->var_is_free[ii]; if(lp->best_solution != NULL) lp->best_solution[lp->rows + i] = lp->best_solution[lp->rows + ii]; } /* Fix invalid variable priority data */ if(lp->var_priority != NULL) { for(i = 0, ii = 0; i < lp->columns; i++) if(lp->var_priority[i] > base - delta) lp->var_priority[ii++] = lp->var_priority[i] + delta; else if(lp->var_priority[i] < base) lp->var_priority[ii++] = lp->var_priority[i]; } if(lp->sos_priority != NULL) { for(i = 0, ii = 0; i < lp->sos_vars; i++) { if(lp->sos_priority[i] > base - delta) lp->sos_priority[ii++] = lp->sos_priority[i] + delta; else if(lp->sos_priority[i] < base) lp->sos_priority[ii++] = lp->sos_priority[i]; } lp->sos_vars = ii; } } shift_basis(lp, lp->rows+base, delta, usedmap, FALSE); if(SOS_count(lp) > 0) SOS_shift_col(lp->SOS, 0, base, delta, usedmap, FALSE); shift_rowcoldata(lp, lp->rows+base, delta, usedmap, FALSE); inc_columns(lp, delta); return( TRUE ); } /* Utility group for incrementing row and column vector storage space */ STATIC void inc_rows(lprec *lp, int delta) { int i; if(lp->names_used && (lp->row_name != NULL)) for(i = lp->rows + delta; i > lp->rows; i--) lp->row_name[i] = NULL; lp->rows += delta; if(lp->matA->is_roworder) lp->matA->columns += delta; else lp->matA->rows += delta; } STATIC void inc_columns(lprec *lp, int delta) { int i; if(lp->names_used && (lp->col_name != NULL)) for(i = lp->columns + delta; i > lp->columns; i--) lp->col_name[i] = NULL; lp->columns += delta; if(lp->matA->is_roworder) lp->matA->rows += delta; else lp->matA->columns += delta; if(get_Lrows(lp) > 0) lp->matL->columns += delta; } STATIC MYBOOL inc_rowcol_space(lprec *lp, int delta, MYBOOL isrows) { int i, oldrowcolalloc, rowcolsum; /* Get rid of dual arrays */ if(lp->solvecount > 0) free_duals(lp); /* Set constants */ oldrowcolalloc = lp->sum_alloc; lp->sum_alloc += delta; rowcolsum = lp->sum_alloc + 1; /* Reallocate lp memory */ if(!allocREAL(lp, &lp->upbo, rowcolsum, AUTOMATIC) || !allocREAL(lp, &lp->orig_upbo, rowcolsum, AUTOMATIC) || !allocREAL(lp, &lp->lowbo, rowcolsum, AUTOMATIC) || !allocREAL(lp, &lp->orig_lowbo, rowcolsum, AUTOMATIC) || !allocREAL(lp, &lp->solution, rowcolsum, AUTOMATIC) || !allocREAL(lp, &lp->best_solution, rowcolsum, AUTOMATIC) || !allocMYBOOL(lp, &lp->is_basic, rowcolsum, AUTOMATIC) || !allocMYBOOL(lp, &lp->is_lower, rowcolsum, AUTOMATIC) || ((lp->scalars != NULL) && !allocREAL(lp, &lp->scalars, rowcolsum, AUTOMATIC))) return( FALSE ); /* Fill in default values, where appropriate */ for(i = oldrowcolalloc+1; i < rowcolsum; i++) { lp->upbo[i] = lp->infinite; lp->orig_upbo[i] = lp->upbo[i]; lp->lowbo[i] = 0; lp->orig_lowbo[i] = lp->lowbo[i]; lp->is_basic[i] = FALSE; lp->is_lower[i] = TRUE; } /* Deal with scalars; the vector can be NULL and also contains Lagrangean information */ if(lp->scalars != NULL) { for(i = oldrowcolalloc+1; i < rowcolsum; i++) lp->scalars[i] = 1; if(oldrowcolalloc == 0) lp->scalars[0] = 1; } return( inc_presolve_space(lp, delta, isrows) && resizePricer(lp) ); } STATIC MYBOOL inc_lag_space(lprec *lp, int deltarows, MYBOOL ignoreMAT) { int newsize; if(deltarows > 0) { newsize = get_Lrows(lp) + deltarows; /* Reallocate arrays */ if(!allocREAL(lp, &lp->lag_rhs, newsize+1, AUTOMATIC) || !allocREAL(lp, &lp->lambda, newsize+1, AUTOMATIC) || !allocINT(lp, &lp->lag_con_type, newsize+1, AUTOMATIC)) return( FALSE ); /* Reallocate the matrix (note that the row scalars are stored at index 0) */ if(!ignoreMAT) { if(lp->matL == NULL) lp->matL = mat_create(lp, newsize, lp->columns, lp->epsvalue); else inc_matrow_space(lp->matL, deltarows); } lp->matL->rows += deltarows; } /* Handle column count expansion as special case */ else if(!ignoreMAT) { inc_matcol_space(lp->matL, lp->columns_alloc-lp->matL->columns_alloc+1); } return( TRUE ); } STATIC MYBOOL inc_row_space(lprec *lp, int deltarows) { int i, rowsum, oldrowsalloc; MYBOOL ok = TRUE; /* Adjust lp row structures */ i = lp->rows_alloc+deltarows; if(lp->matA->is_roworder) { i -= lp->matA->columns_alloc; SETMIN(i, deltarows); if(i > 0) inc_matcol_space(lp->matA, i); rowsum = lp->matA->columns_alloc; } else { #if 0 if((lp->rows_alloc > 0) && (lp->rows + deltarows > lp->rows_alloc)) i = deltarows; /* peno 25/12/06 */ else #endif i -= lp->matA->rows_alloc; SETMIN(i, deltarows); if(i > 0) inc_matrow_space(lp->matA, i); rowsum = lp->matA->rows_alloc; } if(lp->rows+deltarows > lp->rows_alloc) { rowsum++; oldrowsalloc = lp->rows_alloc; lp->rows_alloc = rowsum; deltarows = rowsum - oldrowsalloc; rowsum++; if(!allocREAL(lp, &lp->orig_rhs, rowsum, AUTOMATIC) || !allocLREAL(lp, &lp->rhs, rowsum, AUTOMATIC) || !allocINT(lp, &lp->row_type, rowsum, AUTOMATIC) || !allocINT(lp, &lp->var_basic, rowsum, AUTOMATIC)) return( FALSE ); if(oldrowsalloc == 0) { lp->var_basic[0] = AUTOMATIC; /*TRUE;*/ /* Indicates default basis */ lp->orig_rhs[0] = 0; lp->row_type[0] = ROWTYPE_OFMIN; } for(i = oldrowsalloc+1; i < rowsum; i++) { lp->orig_rhs[i] = 0; lp->rhs[i] = 0; lp->row_type[i] = ROWTYPE_EMPTY; lp->var_basic[i] = i; } /* Adjust hash name structures */ if(lp->names_used && (lp->row_name != NULL)) { /* First check the hash table */ if(lp->rowname_hashtab->size < lp->rows_alloc) { hashtable *ht; ht = copy_hash_table(lp->rowname_hashtab, lp->row_name, lp->rows_alloc + 1); if(ht == NULL) { lp->spx_status = NOMEMORY; return( FALSE ); } free_hash_table(lp->rowname_hashtab); lp->rowname_hashtab = ht; } /* Then the string storage (i.e. pointer to the item's hash structure) */ lp->row_name = (hashelem **) realloc(lp->row_name, (rowsum) * sizeof(*lp->row_name)); if(lp->row_name == NULL) { lp->spx_status = NOMEMORY; return( FALSE ); } for(i = oldrowsalloc + 1; i < rowsum; i++) lp->row_name[i] = NULL; } ok = inc_rowcol_space(lp, deltarows, TRUE); } return(ok); } STATIC MYBOOL inc_col_space(lprec *lp, int deltacols) { int i,colsum, oldcolsalloc; i = lp->columns_alloc+deltacols; if(lp->matA->is_roworder) { i -= lp->matA->rows_alloc; SETMIN(i, deltacols); if(i > 0) inc_matrow_space(lp->matA, i); colsum = lp->matA->rows_alloc; } else { i -= lp->matA->columns_alloc; SETMIN(i, deltacols); if(i > 0) inc_matcol_space(lp->matA, i); colsum = lp->matA->columns_alloc; } if(lp->columns+deltacols >= lp->columns_alloc) { colsum++; oldcolsalloc = lp->columns_alloc; lp->columns_alloc = colsum; deltacols = colsum - oldcolsalloc; colsum++; /* Adjust hash name structures */ if(lp->names_used && (lp->col_name != NULL)) { /* First check the hash table */ if(lp->colname_hashtab->size < lp->columns_alloc) { hashtable *ht; ht = copy_hash_table(lp->colname_hashtab, lp->col_name, lp->columns_alloc + 1); if(ht != NULL) { free_hash_table(lp->colname_hashtab); lp->colname_hashtab = ht; } } /* Then the string storage (i.e. pointer to the item's hash structure) */ lp->col_name = (hashelem **) realloc(lp->col_name, (colsum) * sizeof(*lp->col_name)); for(i = oldcolsalloc+1; i < colsum; i++) lp->col_name[i] = NULL; } if(!allocREAL(lp, &lp->orig_obj, colsum, AUTOMATIC) || !allocMYBOOL(lp, &lp->var_type, colsum, AUTOMATIC) || !allocREAL(lp, &lp->sc_lobound, colsum, AUTOMATIC) || ((lp->obj != NULL) && !allocREAL(lp, &lp->obj, colsum, AUTOMATIC)) || ((lp->var_priority != NULL) && !allocINT(lp, &lp->var_priority, colsum-1, AUTOMATIC)) || ((lp->var_is_free != NULL) && !allocINT(lp, &lp->var_is_free, colsum, AUTOMATIC)) || ((lp->bb_varbranch != NULL) && !allocMYBOOL(lp, &lp->bb_varbranch, colsum-1, AUTOMATIC))) return( FALSE ); /* Make sure that Lagrangean constraints have the same number of columns */ if(get_Lrows(lp) > 0) inc_lag_space(lp, 0, FALSE); /* Update column pointers */ for(i = MIN(oldcolsalloc, lp->columns) + 1; i < colsum; i++) { lp->orig_obj[i] = 0; if(lp->obj != NULL) lp->obj[i] = 0; lp->var_type[i] = ISREAL; lp->sc_lobound[i] = 0; if(lp->var_priority != NULL) lp->var_priority[i-1] = i; } if(lp->var_is_free != NULL) { for(i = oldcolsalloc+1; i < colsum; i++) lp->var_is_free[i] = 0; } if(lp->bb_varbranch != NULL) { for(i = oldcolsalloc; i < colsum-1; i++) lp->bb_varbranch[i] = BRANCH_DEFAULT; } inc_rowcol_space(lp, deltacols, FALSE); } return(TRUE); } /* Problem manipulation routines */ MYBOOL __WINAPI set_obj(lprec *lp, int colnr, REAL value) { if(colnr <= 0) colnr = set_rh(lp, 0, value); else colnr = set_mat(lp, 0, colnr, value); return((MYBOOL) colnr); } MYBOOL __WINAPI set_obj_fnex(lprec *lp, int count, REAL *row, int *colno) { MYBOOL chsgn = is_maxim(lp); int i, ix; REAL value; if(row == NULL) return( FALSE ); else if(colno == NULL) { if(count <= 0) count = lp->columns; for(i = 1; i <= count; i++) { value = row[i]; #ifdef DoMatrixRounding value = roundToPrecision(value, lp->matA->epsvalue); #endif lp->orig_obj[i] = my_chsign(chsgn, scaled_mat(lp, value, 0, i)); } } else { MEMCLEAR(lp->orig_obj, lp->columns+1); for(i = 0; i < count; i++) { ix = colno[i]; value = row[i]; #ifdef DoMatrixRounding value = roundToPrecision(value, lp->matA->epsvalue); #endif lp->orig_obj[ix] = my_chsign(chsgn, scaled_mat(lp, value, 0, ix)); } } return(TRUE); } MYBOOL __WINAPI set_obj_fn(lprec *lp, REAL *row) { return( set_obj_fnex(lp, 0, row, NULL) ); } MYBOOL __WINAPI str_set_obj_fn(lprec *lp, char *row_string) { int i; MYBOOL ret = TRUE; REAL *arow; char *p, *newp; allocREAL(lp, &arow, lp->columns + 1, FALSE); p = row_string; for(i = 1; i <= lp->columns; i++) { arow[i] = (REAL) strtod(p, &newp); if(p == newp) { report(lp, IMPORTANT, "str_set_obj_fn: Bad string %s\n", p); lp->spx_status = DATAIGNORED; ret = FALSE; break; } else p = newp; } if(lp->spx_status != DATAIGNORED) ret = set_obj_fn(lp, arow); FREE(arow); return( ret ); } STATIC MYBOOL append_columns(lprec *lp, int deltacolumns) { if(!inc_col_space(lp, deltacolumns)) return( FALSE ); varmap_add(lp, lp->sum+1, deltacolumns); shift_coldata(lp, lp->columns+1, deltacolumns, NULL); return( TRUE ); } STATIC MYBOOL append_rows(lprec *lp, int deltarows) { if(!inc_row_space(lp, deltarows)) return( FALSE ); varmap_add(lp, lp->rows+1, deltarows); shift_rowdata(lp, lp->rows+1, deltarows, NULL); return( TRUE ); } MYBOOL __WINAPI set_add_rowmode(lprec *lp, MYBOOL turnon) { if((lp->solvecount == 0) && (turnon ^ lp->matA->is_roworder)) return( mat_transpose(lp->matA) ); else return( FALSE ); } MYBOOL __WINAPI is_add_rowmode(lprec *lp) { return(lp->matA->is_roworder); } MYBOOL __WINAPI set_row(lprec *lp, int rownr, REAL *row) { if((rownr < 0) || (rownr > lp->rows)) { report(lp, IMPORTANT, "set_row: Row %d out of range\n", rownr); return( FALSE ); } if(rownr == 0) return( set_obj_fn(lp, row) ); else return( mat_setrow(lp->matA, rownr, lp->columns, row, NULL, TRUE, TRUE) ); } MYBOOL __WINAPI set_rowex(lprec *lp, int rownr, int count, REAL *row, int *colno) { if((rownr < 0) || (rownr > lp->rows)) { report(lp, IMPORTANT, "set_rowex: Row %d out of range\n", rownr); return( FALSE ); } if(rownr == 0) return( set_obj_fnex(lp, count, row, colno) ); else return( mat_setrow(lp->matA, rownr, count, row, colno, TRUE, TRUE) ); } MYBOOL __WINAPI add_constraintex(lprec *lp, int count, REAL *row, int *colno, int constr_type, REAL rh) { int n; MYBOOL status = FALSE; if(!(constr_type == LE || constr_type == GE || constr_type == EQ)) { report(lp, IMPORTANT, "add_constraintex: Invalid %d constraint type\n", constr_type); return( status ); } /* Prepare for a new row */ if(!append_rows(lp, 1)) return( status ); /* Set constraint parameters, fix the slack */ if((constr_type & ROWTYPE_CONSTRAINT) == EQ) { lp->equalities++; lp->orig_upbo[lp->rows] = 0; lp->upbo[lp->rows] = 0; } lp->row_type[lp->rows] = constr_type; if(is_chsign(lp, lp->rows) && (rh != 0)) lp->orig_rhs[lp->rows] = -rh; else lp->orig_rhs[lp->rows] = rh; /* Insert the non-zero constraint values */ if(colno == NULL && row != NULL) n = lp->columns; else n = count; mat_appendrow(lp->matA, n, row, colno, my_chsign(is_chsign(lp, lp->rows), 1.0), TRUE); if(!lp->varmap_locked) presolve_setOrig(lp, lp->rows, lp->columns); #ifdef Paranoia if(lp->matA->is_roworder) n = lp->matA->columns; else n = lp->matA->rows; if(lp->rows != n) { report(lp, SEVERE, "add_constraintex: Row count mismatch %d vs %d\n", lp->rows, n); } else if(is_BasisReady(lp) && !verify_basis(lp)) report(lp, SEVERE, "add_constraintex: Invalid basis detected for row %d\n", lp->rows); else #endif status = TRUE; return( status ); } MYBOOL __WINAPI add_constraint(lprec *lp, REAL *row, int constr_type, REAL rh) { return( add_constraintex(lp, 0, row, NULL, constr_type, rh) ); } MYBOOL __WINAPI str_add_constraint(lprec *lp, char *row_string, int constr_type, REAL rh) { int i; char *p, *newp; REAL *aRow; MYBOOL status = FALSE; allocREAL(lp, &aRow, lp->columns + 1, FALSE); p = row_string; for(i = 1; i <= lp->columns; i++) { aRow[i] = (REAL) strtod(p, &newp); if(p == newp) { report(lp, IMPORTANT, "str_add_constraint: Bad string '%s'\n", p); lp->spx_status = DATAIGNORED; break; } else p = newp; } if(lp->spx_status != DATAIGNORED) status = add_constraint(lp, aRow, constr_type, rh); FREE(aRow); return(status); } STATIC MYBOOL del_constraintex(lprec *lp, LLrec *rowmap) { int i; if(lp->equalities > 0) for(i = firstInactiveLink(rowmap); i != 0; i = nextInactiveLink(rowmap, i)) { if(is_constr_type(lp, i, EQ)) { #ifdef Paranoia if(lp->equalities == 0) report(lp, SEVERE, "del_constraintex: Invalid count of equality constraints\n"); #endif lp->equalities--; } } varmap_delete(lp, 1, -1, rowmap); shift_rowdata(lp, 1, -1, rowmap); if(!lp->varmap_locked) { presolve_setOrig(lp, lp->rows, lp->columns); if(lp->names_used) del_varnameex(lp, lp->row_name, lp->rows, lp->rowname_hashtab, 0, rowmap); } #ifdef Paranoia if(is_BasisReady(lp) && !verify_basis(lp)) report(lp, SEVERE, "del_constraintex: Invalid basis detected\n"); #endif return(TRUE); } MYBOOL __WINAPI del_constraint(lprec *lp, int rownr) { MYBOOL preparecompact = (MYBOOL) (rownr < 0); if(preparecompact) rownr = -rownr; if((rownr < 1) || (rownr > lp->rows)) { report(lp, IMPORTANT, "del_constraint: Attempt to delete non-existing constraint %d\n", rownr); return(FALSE); } /* if(lp->matA->is_roworder) { report(lp, IMPORTANT, "del_constraint: Cannot delete constraint while in row entry mode.\n"); return(FALSE); } */ if(is_constr_type(lp, rownr, EQ) && (lp->equalities > 0)) lp->equalities--; varmap_delete(lp, my_chsign(preparecompact, rownr), -1, NULL); shift_rowdata(lp, my_chsign(preparecompact, rownr), -1, NULL); /* peno 04.10.07 Fixes a problem with del_constraint. Constraints names were not shifted and reported variable result was incorrect. See UnitTest1, UnitTest2 min: -2 x3; c1: +x2 -x1 <= 10; c: 0 x3 <= 0; c2: +x3 +x2 +x1 <= 20; 2 <= x3 <= 3; x1 <= 30; // del_constraint(lp, 2); // See write_LP and print_solution result // To fix, commented if(!lp->varmap_locked) */ if(!lp->varmap_locked) { presolve_setOrig(lp, lp->rows, lp->columns); if(lp->names_used) del_varnameex(lp, lp->row_name, lp->rows, lp->rowname_hashtab, rownr, NULL); } #ifdef Paranoia if(is_BasisReady(lp) && !verify_basis(lp)) report(lp, SEVERE, "del_constraint: Invalid basis detected at row %d\n", rownr); #endif return(TRUE); } MYBOOL __WINAPI add_lag_con(lprec *lp, REAL *row, int con_type, REAL rhs) { int k; REAL sign; if(con_type == LE || con_type == EQ) sign = 1; else if(con_type == GE) sign = -1; else { report(lp, IMPORTANT, "add_lag_con: Constraint type %d not implemented\n", con_type); return(FALSE); } inc_lag_space(lp, 1, FALSE); k = get_Lrows(lp); lp->lag_rhs[k] = rhs * sign; mat_appendrow(lp->matL, lp->columns, row, NULL, sign, TRUE); lp->lambda[k] = 0; lp->lag_con_type[k] = con_type; return(TRUE); } MYBOOL __WINAPI str_add_lag_con(lprec *lp, char *row_string, int con_type, REAL rhs) { int i; MYBOOL ret = TRUE; REAL *a_row; char *p, *new_p; allocREAL(lp, &a_row, lp->columns + 1, FALSE); p = row_string; for(i = 1; i <= lp->columns; i++) { a_row[i] = (REAL) strtod(p, &new_p); if(p == new_p) { report(lp, IMPORTANT, "str_add_lag_con: Bad string '%s'\n", p); lp->spx_status = DATAIGNORED; ret = FALSE; break; } else p = new_p; } if(lp->spx_status != DATAIGNORED) ret = add_lag_con(lp, a_row, con_type, rhs); FREE(a_row); return( ret ); } /* INLINE */ MYBOOL is_splitvar(lprec *lp, int colnr) /* Two cases handled by var_is_free: 1) LB:-Inf / UB:var_is_free != NULL) && (lp->var_is_free[colnr] < 0) && (-lp->var_is_free[colnr] != colnr))); } void del_splitvars(lprec *lp) { int j, jj, i; if(lp->var_is_free != NULL) { for(j = lp->columns; j >= 1; j--) if(is_splitvar(lp, j)) { /* Check if we need to modify the basis */ jj = lp->rows+abs(lp->var_is_free[j]); i = lp->rows+j; if(lp->is_basic[i] && !lp->is_basic[jj]) { i = findBasisPos(lp, i, NULL); set_basisvar(lp, i, jj); } /* Delete the helper column */ del_column(lp, j); } FREE(lp->var_is_free); } } MYBOOL __WINAPI set_column(lprec *lp, int colnr, REAL *column) { return( mat_setcol(lp->matA, colnr, lp->rows, column, NULL, TRUE, TRUE) ); } MYBOOL __WINAPI set_columnex(lprec *lp, int colnr, int count, REAL *column, int *rowno) { return( mat_setcol(lp->matA, colnr, count, column, rowno, TRUE, TRUE) ); } MYBOOL __WINAPI add_columnex(lprec *lp, int count, REAL *column, int *rowno) /* This function adds a data column to the current model; three cases handled: 1: Prepare for column data by setting column = NULL 2: Dense vector indicated by (rowno == NULL) over 0..count+get_Lrows() elements 3: Sparse vector set over row vectors rowno, over 0..count-1 elements. NB! If the column has only one entry, this should be handled as a bound, but this currently is not the case */ { MYBOOL status = FALSE; /* Prepare and shift column vectors */ if(!append_columns(lp, 1)) return( status ); /* Append sparse regular constraint values */ if(mat_appendcol(lp->matA, count, column, rowno, 1.0, TRUE) < 0) report(lp, SEVERE, "add_columnex: Data column %d supplied in non-ascending row index order.\n", lp->columns); else #ifdef Paranoia if(lp->columns != (lp->matA->is_roworder ? lp->matA->rows : lp->matA->columns)) { report(lp, SEVERE, "add_columnex: Column count mismatch %d vs %d\n", lp->columns, (lp->matA->is_roworder ? lp->matA->rows : lp->matA->columns)); } else if(is_BasisReady(lp) && (lp->P1extraDim == 0) && !verify_basis(lp)) report(lp, SEVERE, "add_columnex: Invalid basis detected for column %d\n", lp->columns); else #endif status = TRUE; if(!lp->varmap_locked) presolve_setOrig(lp, lp->rows, lp->columns); return( status ); } MYBOOL __WINAPI add_column(lprec *lp, REAL *column) { del_splitvars(lp); return(add_columnex(lp, lp->rows, column, NULL)); } MYBOOL __WINAPI str_add_column(lprec *lp, char *col_string) { int i; MYBOOL ret = TRUE; REAL *aCol; char *p, *newp; allocREAL(lp, &aCol, lp->rows + 1, FALSE); p = col_string; for(i = 0; i <= lp->rows; i++) { aCol[i] = (REAL) strtod(p, &newp); if(p == newp) { report(lp, IMPORTANT, "str_add_column: Bad string '%s'\n", p); lp->spx_status = DATAIGNORED; ret = FALSE; break; } else p = newp; } if(lp->spx_status != DATAIGNORED) ret = add_column(lp, aCol); FREE(aCol); return( ret ); } STATIC MYBOOL del_varnameex(lprec *lp, hashelem **namelist, int items, hashtable *ht, int varnr, LLrec *varmap) { int i, n; /* First drop hash table entries of the deleted variables */ if(varmap != NULL) i = firstInactiveLink(varmap); else i = varnr; while(i > 0) { if(namelist[i] != NULL) { if(namelist[i]->name != NULL) drophash(namelist[i]->name, namelist, ht); } if(varmap != NULL) i = nextInactiveLink(varmap, i); else i = 0; } /* Then compress the name list */ if(varmap != NULL) { i = firstInactiveLink(varmap); n = nextActiveLink(varmap, i); varnr = i; } else { i = varnr; n = i + 1; } while(n != 0) { namelist[i] = namelist[n]; if((namelist[i] != NULL) && (namelist[i]->index > varnr)) namelist[i]->index -= n - i; i++; if(varmap != NULL) n = nextActiveLink(varmap, i); else if(n <= items) /* items has been updated for the new count */ n++; else n = 0; } return( TRUE ); } STATIC MYBOOL del_columnex(lprec *lp, LLrec *colmap) { varmap_delete(lp, lp->rows+1, -1, colmap); shift_coldata(lp, 1, -1, colmap); if(!lp->varmap_locked) { presolve_setOrig(lp, lp->rows, lp->columns); if(lp->names_used) del_varnameex(lp, lp->col_name, lp->columns, lp->colname_hashtab, 0, colmap); } #ifdef Paranoia if(is_BasisReady(lp) && (lp->P1extraDim == 0) && !verify_basis(lp)) report(lp, SEVERE, "del_columnex: Invalid basis detected\n"); #endif return(TRUE); } MYBOOL __WINAPI del_column(lprec *lp, int colnr) { MYBOOL preparecompact = (MYBOOL) (colnr < 0); if(preparecompact) colnr = -colnr; if((colnr > lp->columns) || (colnr < 1)) { report(lp, IMPORTANT, "del_column: Column %d out of range\n", colnr); return(FALSE); } /* if(lp->matA->is_roworder) { report(lp, IMPORTANT, "del_column: Cannot delete column while in row entry mode.\n"); return(FALSE); } */ if((lp->var_is_free != NULL) && (lp->var_is_free[colnr] > 0)) del_column(lp, lp->var_is_free[colnr]); /* delete corresponding split column (is always after this column) */ varmap_delete(lp, my_chsign(preparecompact, lp->rows+colnr), -1, NULL); shift_coldata(lp, my_chsign(preparecompact, colnr), -1, NULL); if(!lp->varmap_locked) { presolve_setOrig(lp, lp->rows, lp->columns); if(lp->names_used) del_varnameex(lp, lp->col_name, lp->columns, lp->colname_hashtab, colnr, NULL); } #ifdef Paranoia if(is_BasisReady(lp) && (lp->P1extraDim == 0) && !verify_basis(lp)) report(lp, SEVERE, "del_column: Invalid basis detected at column %d (%d)\n", colnr, lp->columns); #endif return(TRUE); } void __WINAPI set_simplextype(lprec *lp, int simplextype) { lp->simplex_strategy = simplextype; } int __WINAPI get_simplextype(lprec *lp) { return(lp->simplex_strategy); } void __WINAPI set_preferdual(lprec *lp, MYBOOL dodual) { if(dodual & TRUE) lp->simplex_strategy = SIMPLEX_DUAL_DUAL; else lp->simplex_strategy = SIMPLEX_PRIMAL_PRIMAL; } void __WINAPI set_bounds_tighter(lprec *lp, MYBOOL tighten) { lp->tighten_on_set = tighten; } MYBOOL __WINAPI get_bounds_tighter(lprec *lp) { return(lp->tighten_on_set); } MYBOOL __WINAPI set_upbo(lprec *lp, int colnr, REAL value) { if((colnr > lp->columns) || (colnr < 1)) { report(lp, IMPORTANT, "set_upbo: Column %d out of range\n", colnr); return(FALSE); } #ifdef DoBorderRounding if(fabs(value) < lp->infinite) value = my_avoidtiny(value, lp->matA->epsvalue); #endif value = scaled_value(lp, value, lp->rows + colnr); if(lp->tighten_on_set) { if(value < lp->orig_lowbo[lp->rows + colnr]) { report(lp, IMPORTANT, "set_upbo: Upperbound must be >= lowerbound\n"); return(FALSE); } if(value < lp->orig_upbo[lp->rows + colnr]) { set_action(&lp->spx_action, ACTION_REBASE); lp->orig_upbo[lp->rows + colnr] = value; } } else { set_action(&lp->spx_action, ACTION_REBASE); if(value > lp->infinite) value = lp->infinite; lp->orig_upbo[lp->rows + colnr] = value; } return(TRUE); } REAL __WINAPI get_upbo(lprec *lp, int colnr) { REAL value; if((colnr > lp->columns) || (colnr < 1)) { report(lp, IMPORTANT, "get_upbo: Column %d out of range\n", colnr); return(0); } value = lp->orig_upbo[lp->rows + colnr]; value = unscaled_value(lp, value, lp->rows + colnr); return(value); } MYBOOL __WINAPI set_lowbo(lprec *lp, int colnr, REAL value) { if((colnr > lp->columns) || (colnr < 1)) { report(lp, IMPORTANT, "set_lowbo: Column %d out of range\n", colnr); return(FALSE); } #ifdef DoBorderRounding if(fabs(value) < lp->infinite) value = my_avoidtiny(value, lp->matA->epsvalue); #endif value = scaled_value(lp, value, lp->rows + colnr); if(lp->tighten_on_set) { if(value > lp->orig_upbo[lp->rows + colnr]) { report(lp, IMPORTANT, "set_lowbo: Upper bound must be >= lower bound\n"); return(FALSE); } if((value < 0) || (value > lp->orig_lowbo[lp->rows + colnr])) { set_action(&lp->spx_action, ACTION_REBASE); lp->orig_lowbo[lp->rows + colnr] = value; } } else { set_action(&lp->spx_action, ACTION_REBASE); if(value < -lp->infinite) value = -lp->infinite; lp->orig_lowbo[lp->rows + colnr] = value; } return(TRUE); } REAL __WINAPI get_lowbo(lprec *lp, int colnr) { REAL value; if((colnr > lp->columns) || (colnr < 1)) { report(lp, IMPORTANT, "get_lowbo: Column %d out of range\n", colnr); return(0); } value = lp->orig_lowbo[lp->rows + colnr]; value = unscaled_value(lp, value, lp->rows + colnr); return(value); } MYBOOL __WINAPI set_bounds(lprec *lp, int colnr, REAL lower, REAL upper) { if((colnr > lp->columns) || (colnr < 1)) { report(lp, IMPORTANT, "set_bounds: Column %d out of range\n", colnr); return(FALSE); } if(fabs(upper - lower) < lp->epsvalue) { if(lower < 0) lower = upper; else upper = lower; } else if(lower > upper) { report(lp, IMPORTANT, "set_bounds: Column %d upper bound must be >= lower bound\n", colnr); return( FALSE ); } colnr += lp->rows; if(lower < -lp->infinite) lower = -lp->infinite; else if(lp->scaling_used) { lower = scaled_value(lp, lower, colnr); #ifdef DoBorderRounding lower = my_avoidtiny(lower, lp->matA->epsvalue); #endif } if(upper > lp->infinite) upper = lp->infinite; else if(lp->scaling_used) { upper = scaled_value(lp, upper, colnr); #ifdef DoBorderRounding upper = my_avoidtiny(upper, lp->matA->epsvalue); #endif } lp->orig_lowbo[colnr] = lower; lp->orig_upbo[colnr] = upper; set_action(&lp->spx_action, ACTION_REBASE); return(TRUE); } MYBOOL get_bounds(lprec *lp, int column, REAL *lower, REAL *upper) { if((column > lp->columns) || (column < 1)) { report(lp, IMPORTANT, "get_bounds: Column %d out of range", column); return(FALSE); } if(lower != NULL) *lower = get_lowbo(lp, column); if(upper != NULL) *upper = get_upbo(lp, column); return(TRUE); } MYBOOL __WINAPI set_int(lprec *lp, int colnr, MYBOOL var_type) { if((colnr > lp->columns) || (colnr < 1)) { report(lp, IMPORTANT, "set_int: Column %d out of range\n", colnr); return(FALSE); } if((lp->var_type[colnr] & ISINTEGER) != 0) { lp->int_vars--; lp->var_type[colnr] &= ~ISINTEGER; } if(var_type) { lp->var_type[colnr] |= ISINTEGER; lp->int_vars++; if(lp->columns_scaled && !is_integerscaling(lp)) unscale_columns(lp); } return(TRUE); } MYBOOL __WINAPI is_int(lprec *lp, int colnr) { if((colnr > lp->columns) || (colnr < 1)) { report(lp, IMPORTANT, "is_int: Column %d out of range\n", colnr); return(FALSE); } return((lp->var_type[colnr] & ISINTEGER) != 0); } MYBOOL __WINAPI is_SOS_var(lprec *lp, int colnr) { if((colnr > lp->columns) || (colnr < 1)) { report(lp, IMPORTANT, "is_SOS_var: Column %d out of range\n", colnr); return(FALSE); } return((lp->var_type[colnr] & ISSOS) != 0); } int __WINAPI add_SOS(lprec *lp, char *name, int sostype, int priority, int count, int *sosvars, REAL *weights) { SOSrec *SOS; int k; if((sostype < 1) || (count < 0)) { report(lp, IMPORTANT, "add_SOS: Invalid SOS type definition %d\n", sostype); return( 0 ); } /* Make sure SOSes of order 3 and higher are properly defined */ if(sostype > 2) { int j; for(k = 1; k <= count; k++) { j = sosvars[k]; if(!is_int(lp, j) || !is_semicont(lp, j)) { report(lp, IMPORTANT, "add_SOS: SOS3+ members all have to be integer or semi-continuous.\n"); return( 0 ); } } } /* Make size in the list to handle another SOS record */ if(lp->SOS == NULL) lp->SOS = create_SOSgroup(lp); /* Create and append SOS to list */ SOS = create_SOSrec(lp->SOS, name, sostype, priority, count, sosvars, weights); k = append_SOSgroup(lp->SOS, SOS); return(k); } STATIC int add_GUB(lprec *lp, char *name, int priority, int count, int *gubvars) { SOSrec *GUB; int k; #ifdef Paranoia if(count < 0) { report(lp, IMPORTANT, "add_GUB: Invalid GUB member count %d\n", count); return(FALSE); } #endif /* Make size in the list to handle another GUB record */ if(lp->GUB == NULL) lp->GUB = create_SOSgroup(lp); /* Create and append GUB to list */ GUB = create_SOSrec(lp->GUB, name, 1, priority, count, gubvars, NULL); GUB->isGUB = TRUE; k = append_SOSgroup(lp->GUB, GUB); return(k); } MYBOOL __WINAPI set_binary(lprec *lp, int colnr, MYBOOL must_be_bin) { MYBOOL status = FALSE; if((colnr > lp->columns) || (colnr < 1)) { report(lp, IMPORTANT, "set_binary: Column %d out of range\n", colnr); return( status ); } status = set_int(lp, colnr, must_be_bin); if(status && must_be_bin) status = set_bounds(lp, colnr, 0, 1); return( status ); } MYBOOL __WINAPI is_binary(lprec *lp, int colnr) { if((colnr > lp->columns) || (colnr < 1)) { report(lp, IMPORTANT, "is_binary: Column %d out of range\n", colnr); return(FALSE); } return((MYBOOL) (((lp->var_type[colnr] & ISINTEGER) != 0) && (get_lowbo(lp, colnr) == 0) && (fabs(get_upbo(lp, colnr) - 1) < lp->epsprimal))); } MYBOOL __WINAPI set_unbounded(lprec *lp, int colnr) { if((colnr > lp->columns) || (colnr < 1)) { report(lp, IMPORTANT, "set_unbounded: Column %d out of range\n", colnr); return( FALSE ); } return( set_bounds(lp, colnr, -lp->infinite, lp->infinite) ); } MYBOOL __WINAPI is_unbounded(lprec *lp, int colnr) { MYBOOL test; if((colnr > lp->columns) || (colnr < 1)) { report(lp, IMPORTANT, "is_unbounded: Column %d out of range\n", colnr); return(FALSE); } test = is_splitvar(lp, colnr); if(!test) { colnr += lp->rows; test = (MYBOOL) ((lp->orig_lowbo[colnr] <= -lp->infinite) && (lp->orig_upbo[colnr] >= lp->infinite)); } return( test ); } MYBOOL __WINAPI is_negative(lprec *lp, int colnr) { if((colnr > lp->columns) || (colnr < 1)) { report(lp, IMPORTANT, "is_negative: Column %d out of range\n", colnr); return( FALSE ); } colnr += lp->rows; return( (MYBOOL) ((lp->orig_upbo[colnr] <= 0) && (lp->orig_lowbo[colnr] < 0)) ); } MYBOOL __WINAPI set_var_weights(lprec *lp, REAL *weights) { if(lp->var_priority != NULL) { FREE(lp->var_priority); } if(weights != NULL) { int n; allocINT(lp, &lp->var_priority, lp->columns_alloc, FALSE); for(n = 0; n < lp->columns; n++) { lp->var_priority[n] = n+1; } n = sortByREAL(lp->var_priority, weights, lp->columns, 0, FALSE); } return(TRUE); } MYBOOL __WINAPI set_var_priority(lprec *lp) /* Experimental automatic variable ordering/priority setting */ { MYBOOL status = FALSE; if(is_bb_mode(lp, NODE_AUTOORDER) && (lp->var_priority == NULL) && (SOS_count(lp) == 0)) { REAL *rcost = NULL; int i, j, *colorder = NULL; allocINT(lp, &colorder, lp->columns+1, FALSE); /* Create an "optimal" B&B variable ordering; this MDO-based routine returns column indeces in an increasing order of co-dependency. It can be argued that arranging the columns in right-to-left MDO order should tend to minimize the consequences of choosing the wrong variable by reducing the average B&B depth. */ colorder[0] = lp->columns; for(j = 1; j <= lp->columns; j++) colorder[j] = lp->rows+j; i = getMDO(lp, NULL, colorder, NULL, FALSE); /* Map to variable weight */ allocREAL(lp, &rcost, lp->columns+1, FALSE); for(j = lp->columns; j > 0; j--) { i = colorder[j]-lp->rows; rcost[i] = -j; } /* Establish the MIP variable priorities */ set_var_weights(lp, rcost+1); FREE(rcost); FREE(colorder); status = TRUE; } return( status ); } int __WINAPI get_var_priority(lprec *lp, int colnr) { if((colnr > lp->columns) || (colnr < 1)) { report(lp, IMPORTANT, "get_var_priority: Column %d out of range\n", colnr); return(FALSE); } if(lp->var_priority == NULL) return(colnr); else return(lp->var_priority[colnr - 1]); } MYBOOL __WINAPI set_semicont(lprec *lp, int colnr, MYBOOL must_be_sc) { if((colnr > lp->columns) || (colnr < 1)) { report(lp, IMPORTANT, "set_semicont: Column %d out of range\n", colnr); return(FALSE); } if(lp->sc_lobound[colnr] != 0) { lp->sc_vars--; lp->var_type[colnr] &= ~ISSEMI; } lp->sc_lobound[colnr] = must_be_sc; if(must_be_sc) { lp->var_type[colnr] |= ISSEMI; lp->sc_vars++; } return(TRUE); } MYBOOL __WINAPI is_semicont(lprec *lp, int colnr) { if((colnr > lp->columns) || (colnr < 1)) { report(lp, IMPORTANT, "is_semicont: Column %d out of range\n", colnr); return(FALSE); } return((lp->var_type[colnr] & ISSEMI) != 0); } MYBOOL __WINAPI set_rh(lprec *lp, int rownr, REAL value) { if((rownr > lp->rows) || (rownr < 0)) { report(lp, IMPORTANT, "set_rh: Row %d out of range\n", rownr); return(FALSE); } if(((rownr == 0) && (!is_maxim(lp))) || ((rownr > 0) && is_chsign(lp, rownr))) /* setting of RHS of OF IS meaningful */ value = my_flipsign(value); if(fabs(value) > lp->infinite) { if(value < 0) value = -lp->infinite; else value = lp->infinite; } #ifdef DoBorderRounding else value = my_avoidtiny(value, lp->matA->epsvalue); #endif value = scaled_value(lp, value, rownr); lp->orig_rhs[rownr] = value; set_action(&lp->spx_action, ACTION_RECOMPUTE); return(TRUE); } REAL __WINAPI get_rh(lprec *lp, int rownr) { REAL value; if((rownr > lp->rows) || (rownr < 0)) { report(lp, IMPORTANT, "get_rh: Row %d out of range", rownr); return( 0.0 ); } value = lp->orig_rhs[rownr]; if (((rownr == 0) && !is_maxim(lp)) || ((rownr > 0) && is_chsign(lp, rownr))) /* setting of RHS of OF IS meaningful */ value = my_flipsign(value); value = unscaled_value(lp, value, rownr); return(value); } REAL get_rh_upper(lprec *lp, int rownr) { REAL value, valueR; value = lp->orig_rhs[rownr]; if(is_chsign(lp, rownr)) { valueR = lp->orig_upbo[rownr]; if(is_infinite(lp, valueR)) return(lp->infinite); value = my_flipsign(value); value += valueR; } value = unscaled_value(lp, value, rownr); return(value); } REAL get_rh_lower(lprec *lp, int rownr) { REAL value, valueR; value = lp->orig_rhs[rownr]; if(is_chsign(lp, rownr)) value = my_flipsign(value); else { valueR = lp->orig_upbo[rownr]; if(is_infinite(lp, valueR)) return(-lp->infinite); value -= valueR; } value = unscaled_value(lp, value, rownr); return(value); } MYBOOL set_rh_upper(lprec *lp, int rownr, REAL value) { if(rownr > lp->rows || rownr < 1) { report(lp, IMPORTANT, "set_rh_upper: Row %d out of range", rownr); return(FALSE); } /* First scale the value */ value = scaled_value(lp, value, rownr); /* orig_rhs stores the upper bound assuming a < constraint; If we have a > constraint, we must adjust the range instead */ if(is_chsign(lp, rownr)) { if(is_infinite(lp, value)) lp->orig_upbo[rownr] = lp->infinite; else { #ifdef Paranoia if(value + lp->orig_rhs[rownr] < 0) { report(lp, SEVERE, "set_rh_upper: Invalid negative range in row %d\n", rownr); return(FALSE); } #endif #ifdef DoBorderRounding lp->orig_upbo[rownr] = my_avoidtiny(value + lp->orig_rhs[rownr], lp->epsvalue); #else lp->orig_upbo[rownr] = value + lp->orig_rhs[rownr]; #endif } } else { /* If there is a constraint range, then this has to be adjusted also */ if(!is_infinite(lp, lp->orig_upbo[rownr])) { lp->orig_upbo[rownr] -= lp->orig_rhs[rownr] - value; my_roundzero(lp->orig_upbo[rownr], lp->epsvalue); if(lp->orig_upbo[rownr] < 0) { report(lp, IMPORTANT, "set_rh_upper: Negative bound set for constraint %d made 0\n", rownr); lp->orig_upbo[rownr] = 0; } } lp->orig_rhs[rownr] = value; } return(TRUE); } MYBOOL set_rh_lower(lprec *lp, int rownr, REAL value) { if(rownr > lp->rows || rownr < 1) { report(lp, IMPORTANT, "set_rh_lower: Row %d out of range", rownr); return(FALSE); } /* First scale the value */ value = scaled_value(lp, value, rownr); /* orig_rhs stores the upper bound assuming a < constraint; If we have a < constraint, we must adjust the range instead */ if(!is_chsign(lp, rownr)) { if(is_infinite(lp, value)) lp->orig_upbo[rownr] = lp->infinite; else { #ifdef Paranoia if(lp->orig_rhs[rownr] - value < 0) { report(lp, SEVERE, "set_rh_lower: Invalid negative range in row %d\n", rownr); return(FALSE); } #endif #ifdef DoBorderRounding lp->orig_upbo[rownr] = my_avoidtiny(lp->orig_rhs[rownr] - value, lp->epsvalue); #else lp->orig_upbo[rownr] = lp->orig_rhs[rownr] - value; #endif } } else { value = my_flipsign(value); /* If there is a constraint range, then this has to be adjusted also */ if(!is_infinite(lp, lp->orig_upbo[rownr])) { lp->orig_upbo[rownr] -= lp->orig_rhs[rownr] - value; my_roundzero(lp->orig_upbo[rownr], lp->epsvalue); if(lp->orig_upbo[rownr] < 0) { report(lp, IMPORTANT, "set_rh_lower: Negative bound set for constraint %d made 0\n", rownr); lp->orig_upbo[rownr] = 0; } } lp->orig_rhs[rownr] = value; } return(TRUE); } MYBOOL __WINAPI set_rh_range(lprec *lp, int rownr, REAL deltavalue) { if((rownr > lp->rows) || (rownr < 1)) { report(lp, IMPORTANT, "set_rh_range: Row %d out of range", rownr); return(FALSE); } deltavalue = scaled_value(lp, deltavalue, rownr); if(deltavalue > lp->infinite) deltavalue = lp->infinite; else if(deltavalue < -lp->infinite) deltavalue = -lp->infinite; #ifdef DoBorderRounding else deltavalue = my_avoidtiny(deltavalue, lp->matA->epsvalue); #endif if(fabs(deltavalue) < lp->epsprimal) { /* Conversion to EQ */ set_constr_type(lp, rownr, EQ); } else if(is_constr_type(lp, rownr, EQ)) { /* EQ with a non-zero range */ if(deltavalue > 0) set_constr_type(lp, rownr, GE); else set_constr_type(lp, rownr, LE); lp->orig_upbo[rownr] = fabs(deltavalue); } else { /* Modify GE/LE ranges */ lp->orig_upbo[rownr] = fabs(deltavalue); } return(TRUE); } REAL __WINAPI get_rh_range(lprec *lp, int rownr) { if((rownr > lp->rows) || (rownr < 0)) { report(lp, IMPORTANT, "get_rh_range: row %d out of range\n", rownr); return(FALSE); } if(lp->orig_upbo[rownr] >= lp->infinite) return(lp->orig_upbo[rownr]); else return(unscaled_value(lp, lp->orig_upbo[rownr], rownr)); } void __WINAPI set_rh_vec(lprec *lp, REAL *rh) { int i; REAL rhi; for(i = 1; i <= lp->rows; i++) { rhi = rh[i]; #ifdef DoBorderRounding rhi = my_avoidtiny(rhi, lp->matA->epsvalue); #endif lp->orig_rhs[i] = my_chsign(is_chsign(lp, i), scaled_value(lp, rhi, i)); } set_action(&lp->spx_action, ACTION_RECOMPUTE); } MYBOOL __WINAPI str_set_rh_vec(lprec *lp, char *rh_string) { int i; MYBOOL ret = TRUE; REAL *newrh; char *p, *newp; allocREAL(lp, &newrh, lp->rows + 1, TRUE); p = rh_string; for(i = 1; i <= lp->rows; i++) { newrh[i] = (REAL) strtod(p, &newp); if(p == newp) { report(lp, IMPORTANT, "str_set_rh_vec: Bad string %s\n", p); lp->spx_status = DATAIGNORED; ret = FALSE; break; } else p = newp; } if(!(lp->spx_status == DATAIGNORED)) set_rh_vec(lp, newrh); FREE(newrh); return( ret ); } void __WINAPI set_sense(lprec *lp, MYBOOL maximize) { maximize = (MYBOOL) (maximize != FALSE); if(is_maxim(lp) != maximize) { int i; if(is_infinite(lp, lp->bb_heuristicOF)) lp->bb_heuristicOF = my_chsign(maximize, lp->infinite); if(is_infinite(lp, lp->bb_breakOF)) lp->bb_breakOF = my_chsign(maximize, -lp->infinite); lp->orig_rhs[0] = my_flipsign(lp->orig_rhs[0]); for(i = 1; i <= lp->columns; i++) lp->orig_obj[i] = my_flipsign(lp->orig_obj[i]); set_action(&lp->spx_action, ACTION_REINVERT | ACTION_RECOMPUTE); } if(maximize) lp->row_type[0] = ROWTYPE_OFMAX; else lp->row_type[0] = ROWTYPE_OFMIN; } void __WINAPI set_maxim(lprec *lp) { set_sense(lp, TRUE); } void __WINAPI set_minim(lprec *lp) { set_sense(lp, FALSE); } MYBOOL __WINAPI is_maxim(lprec *lp) { return( (MYBOOL) ((lp->row_type != NULL) && ((lp->row_type[0] & ROWTYPE_CHSIGN) == ROWTYPE_GE)) ); } MYBOOL __WINAPI set_constr_type(lprec *lp, int rownr, int con_type) { MYBOOL oldchsign; if(rownr > lp->rows+1 || rownr < 1) { report(lp, IMPORTANT, "set_constr_type: Row %d out of range\n", rownr); return( FALSE ); } /* Prepare for a new row */ if((rownr > lp->rows) && !append_rows(lp, rownr-lp->rows)) return( FALSE ); /* Update the constraint type data */ if(is_constr_type(lp, rownr, EQ)) lp->equalities--; if((con_type & ROWTYPE_CONSTRAINT) == EQ) { lp->equalities++; lp->orig_upbo[rownr] = 0; } else if(((con_type & LE) > 0) || ((con_type & GE) > 0) || (con_type == FR)) lp->orig_upbo[rownr] = lp->infinite; else { report(lp, IMPORTANT, "set_constr_type: Constraint type %d not implemented (row %d)\n", con_type, rownr); return( FALSE ); } /* Change the signs of the row, if necessary */ oldchsign = is_chsign(lp, rownr); if(con_type == FR) lp->row_type[rownr] = LE; else lp->row_type[rownr] = con_type; if(oldchsign != is_chsign(lp, rownr)) { MATrec *mat = lp->matA; if(mat->is_roworder) mat_multcol(mat, rownr, -1, FALSE); else mat_multrow(mat, rownr, -1); if(lp->orig_rhs[rownr] != 0) lp->orig_rhs[rownr] *= -1; set_action(&lp->spx_action, ACTION_RECOMPUTE); } if(con_type == FR) lp->orig_rhs[rownr] = lp->infinite; set_action(&lp->spx_action, ACTION_REINVERT); lp->basis_valid = FALSE; return( TRUE ); } /* INLINE */ MYBOOL is_chsign(lprec *lp, int rownr) { return( (MYBOOL) ((lp->row_type[rownr] & ROWTYPE_CONSTRAINT) == ROWTYPE_CHSIGN) ); } MYBOOL __WINAPI is_constr_type(lprec *lp, int rownr, int mask) { if((rownr < 0) || (rownr > lp->rows)) { report(lp, IMPORTANT, "is_constr_type: Row %d out of range\n", rownr); return( FALSE ); } return( (MYBOOL) ((lp->row_type[rownr] & ROWTYPE_CONSTRAINT) == mask)); } int __WINAPI get_constr_type(lprec *lp, int rownr) { if((rownr < 0) || (rownr > lp->rows)) { report(lp, IMPORTANT, "get_constr_type: Row %d out of range\n", rownr); return(-1); } return( lp->row_type[rownr] ); } REAL __WINAPI get_constr_value(lprec *lp, int rownr, int count, REAL *primsolution, int *nzindex) { int i; REAL value = 0.0; MATrec *mat = lp->matA; if((rownr < 0) || (rownr > get_Nrows(lp))) return( value ); /* First do validation and initialization of applicable primal solution */ if(!mat_validate(mat) || ((primsolution == NULL) && (lp->solvecount == 0))) return( value ); i = get_Ncolumns(lp); if((primsolution != NULL) && (nzindex == NULL) && ((count <= 0) || (count > i))) count = i; if(primsolution == NULL) { get_ptr_variables(lp, &primsolution); primsolution--; nzindex = NULL; count = i; } /* Do objective or constraint, as specified */ if(rownr == 0) { value += get_rh(lp, 0); if(nzindex != NULL) for(i = 0; i < count; i++) value += get_mat(lp, 0, nzindex[i]) * primsolution[i]; else for(i = 1; i <= count; i++) value += get_mat(lp, 0, i) * primsolution[i]; } else { if(nzindex != NULL) { for(i = 0; i < count; i++) value += get_mat(lp, rownr, nzindex[i]) * primsolution[i]; } else { int j; for(i = mat->row_end[rownr-1]; i < mat->row_end[rownr]; i++) { j = ROW_MAT_COLNR(i); value += unscaled_mat(lp, ROW_MAT_VALUE(i), rownr, j) * primsolution[j]; } value = my_chsign(is_chsign(lp, rownr), value); } } return( value ); } STATIC char *get_str_constr_class(lprec *lp, int con_class) { switch(con_class) { case ROWCLASS_Unknown: return("Unknown"); case ROWCLASS_Objective: return("Objective"); case ROWCLASS_GeneralREAL: return("General REAL"); case ROWCLASS_GeneralMIP: return("General MIP"); case ROWCLASS_GeneralINT: return("General INT"); case ROWCLASS_GeneralBIN: return("General BIN"); case ROWCLASS_KnapsackINT: return("Knapsack INT"); case ROWCLASS_KnapsackBIN: return("Knapsack BIN"); case ROWCLASS_SetPacking: return("Set packing"); case ROWCLASS_SetCover: return("Set cover"); case ROWCLASS_GUB: return("GUB"); default: return("Error"); } } STATIC char *get_str_constr_type(lprec *lp, int con_type) { switch(con_type) { case FR: return("FR"); case LE: return("LE"); case GE: return("GE"); case EQ: return("EQ"); default: return("Error"); } } STATIC int get_constr_class(lprec *lp, int rownr) { int aBIN = 0, aINT = 0, aREAL = 0, xBIN = 0, xINT = 0, xREAL = 0; int j, elmnr, elmend, nelm; MYBOOL chsign; REAL a; MATrec *mat = lp->matA; if((rownr < 1) || (rownr > lp->rows)) { report(lp, IMPORTANT, "get_constr_class: Row %d out of range\n", rownr); return( ROWCLASS_Unknown ); } mat_validate(mat); /* Tally counts of constraint variable types and coefficients */ if(rownr == 0) { elmnr = 1; elmend = lp->columns; nelm = 0; } else { elmnr = mat->row_end[rownr - 1]; elmend = mat->row_end[rownr]; nelm = elmend - elmnr; } chsign = is_chsign(lp, rownr); for(; elmnr < elmend; elmnr++) { if(rownr == 0) { a = lp->orig_obj[elmnr]; if(a == 0) continue; j = elmnr; } else { j = ROW_MAT_COLNR(elmnr); a = ROW_MAT_VALUE(elmnr); } a = unscaled_mat(lp, my_chsign(chsign, a), rownr, j); if(is_binary(lp, j)) xBIN++; else if((get_lowbo(lp, j) >= 0) && is_int(lp, j)) xINT++; else xREAL++; /* Includes integer variables with negative lower bound */ if(fabs(a-1.0) < lp->epsvalue) aBIN++; else if((a > 0) && (fabs(floor(a+lp->epsvalue)-a) < lp->epsvalue)) aINT++; else aREAL++; /* Includes negative integer-valued coefficients */ } /* Get the constraint type and the RHS */ if(rownr == 0) return( ROWCLASS_Objective ); j = get_constr_type(lp, rownr); a = get_rh(lp, rownr); /* Determine the constraint class */ if((aBIN == nelm) && (xBIN == nelm) && (a >= 1)) { if(a > 1) j = ROWCLASS_KnapsackBIN; else if(j == EQ) j = ROWCLASS_GUB; else if(j == LE) j = ROWCLASS_SetCover; else j = ROWCLASS_SetPacking; } else if((aINT == nelm) && (xINT == nelm) && (a >= 1)) j = ROWCLASS_KnapsackINT; else if(xBIN == nelm) j = ROWCLASS_GeneralBIN; else if(xINT == nelm) j = ROWCLASS_GeneralINT; else if((xREAL > 0) && (xINT+xBIN > 0)) j = ROWCLASS_GeneralMIP; else j = ROWCLASS_GeneralREAL; return( j ); } REAL __WINAPI get_mat(lprec *lp, int rownr, int colnr) { REAL value; int elmnr; int colnr1 = colnr, rownr1 = rownr; if((rownr < 0) || (rownr > lp->rows)) { report(lp, IMPORTANT, "get_mat: Row %d out of range", rownr); return(0); } if((colnr < 1) || (colnr > lp->columns)) { report(lp, IMPORTANT, "get_mat: Column %d out of range", colnr); return(0); } if(rownr == 0) { value = lp->orig_obj[colnr]; value = my_chsign(is_chsign(lp, rownr), value); value = unscaled_mat(lp, value, rownr, colnr); } else { if(lp->matA->is_roworder) swapINT(&colnr1, &rownr1); elmnr = mat_findelm(lp->matA, rownr1, colnr1); if(elmnr >= 0) { MATrec *mat = lp->matA; value = my_chsign(is_chsign(lp, rownr), COL_MAT_VALUE(elmnr)); value = unscaled_mat(lp, value, rownr, colnr); } else value = 0; } return(value); } REAL __WINAPI get_mat_byindex(lprec *lp, int matindex, MYBOOL isrow, MYBOOL adjustsign) /* Note that this function does not adjust for sign-changed GT constraints! */ { int *rownr, *colnr; REAL *value, result; mat_get_data(lp, matindex, isrow, &rownr, &colnr, &value); if(adjustsign) result = (*value) * (is_chsign(lp, *rownr) ? -1 : 1); else result = *value; if(lp->scaling_used) return( unscaled_mat(lp, result, *rownr, *colnr) ); else return( result ); } static int mat_getrow(lprec *lp, int rownr, REAL *row, int *colno) { MYBOOL isnz; int j, countnz = 0; REAL a; if((rownr == 0) || !mat_validate(lp->matA)) { for(j = 1; j <= lp->columns; j++) { a = get_mat(lp,rownr,j); isnz = (a != 0); if(colno == NULL) row[j] = a; else if(isnz) { row[countnz] = a; colno[countnz] = j; } if(isnz) countnz++; } } else { MYBOOL chsign = FALSE; int ie, i; MATrec *mat = lp->matA; if(colno == NULL) MEMCLEAR(row, lp->columns+1); if(mat->is_roworder) { /* Add the objective function */ a = get_mat(lp, 0, rownr); if(colno == NULL) { row[countnz] = a; if(a != 0) countnz++; } else if(a != 0) { row[countnz] = a; colno[countnz] = 0; countnz++; } } i = mat->row_end[rownr-1]; ie = mat->row_end[rownr]; if(!lp->matA->is_roworder) chsign = is_chsign(lp, rownr); for(; i < ie; i++) { j = ROW_MAT_COLNR(i); a = get_mat_byindex(lp, i, TRUE, FALSE); if(lp->matA->is_roworder) chsign = is_chsign(lp, j); a = my_chsign(chsign, a); if(colno == NULL) row[j] = a; else { row[countnz] = a; colno[countnz] = j; } countnz++; } } return( countnz ); } static int mat_getcolumn(lprec *lp, int colnr, REAL *column, int *nzrow) { int n = 0, i, ii, ie, *rownr; REAL hold, *value; MATrec *mat = lp->matA; if(nzrow == NULL) MEMCLEAR(column, lp->rows + 1); if(!mat->is_roworder) { /* Add the objective function */ hold = get_mat(lp, 0, colnr); if(nzrow == NULL) { column[n] = hold; if(hold != 0) n++; } else if(hold != 0) { column[n] = hold; nzrow[n] = 0; n++; } } i = lp->matA->col_end[colnr - 1]; ie = lp->matA->col_end[colnr]; if(nzrow == NULL) n += ie - i; rownr = &COL_MAT_ROWNR(i); value = &COL_MAT_VALUE(i); for(; i < ie; i++, rownr += matRowColStep, value += matValueStep) { ii = *rownr; hold = my_chsign(is_chsign(lp, (mat->is_roworder) ? colnr : ii), *value); hold = unscaled_mat(lp, hold, ii, colnr); if(nzrow == NULL) column[ii] = hold; else if(hold != 0) { column[n] = hold; nzrow[n] = ii; n++; } } return( n ); } int __WINAPI get_columnex(lprec *lp, int colnr, REAL *column, int *nzrow) { if((colnr > lp->columns) || (colnr < 1)) { report(lp, IMPORTANT, "get_columnex: Column %d out of range\n", colnr); return( -1 ); } if(lp->matA->is_roworder) return(mat_getrow(lp, colnr, column, nzrow)); else return(mat_getcolumn(lp, colnr, column, nzrow)); } MYBOOL __WINAPI get_column(lprec *lp, int colnr, REAL *column) { return( (MYBOOL) (get_columnex(lp, colnr, column, NULL) >= 0) ); } int __WINAPI get_rowex(lprec *lp, int rownr, REAL *row, int *colno) { if((rownr < 0) || (rownr > lp->rows)) { report(lp, IMPORTANT, "get_rowex: Row %d out of range\n", rownr); return( -1 ); } if(rownr != 0 && lp->matA->is_roworder) return(mat_getcolumn(lp, rownr, row, colno)); else return(mat_getrow(lp, rownr, row, colno)); } MYBOOL __WINAPI get_row(lprec *lp, int rownr, REAL *row) { return((MYBOOL) (get_rowex(lp, rownr, row, NULL) >= 0) ); } STATIC void set_OF_override(lprec *lp, REAL *ofVector) /* The purpose of this function is to set, or clear if NULL, the ofVector[0..columns] as the active objective function instead of the one stored in the A-matrix. See also lag_solve().*/ { lp->obj = ofVector; } MYBOOL modifyOF1(lprec *lp, int index, REAL *ofValue, REAL mult) /* Adjust objective function values for primal/dual phase 1, if appropriate */ { MYBOOL accept = TRUE; /* Primal simplex: Set user variables to zero or BigM-scaled */ if(((lp->simplex_mode & SIMPLEX_Phase1_PRIMAL) != 0) && (abs(lp->P1extraDim) > 0)) { #ifndef Phase1EliminateRedundant if(lp->P1extraDim < 0) { if(index > lp->sum + lp->P1extraDim) accept = FALSE; } else #endif if((index <= lp->sum - lp->P1extraDim) || (mult == 0)) { if((mult == 0) || (lp->bigM == 0)) accept = FALSE; else (*ofValue) /= lp->bigM; } } /* Dual simplex: Subtract P1extraVal from objective function values */ else if(((lp->simplex_mode & SIMPLEX_Phase1_DUAL) != 0) && (index > lp->rows)) { #if 1 /* This may help increase sparsity of the (extended) basis matrix; Can it introduce degeneracy in some cases? */ if((lp->P1extraVal != 0) && (lp->orig_obj[index - lp->rows] > 0)) *ofValue = 0; else #endif { *ofValue -= lp->P1extraVal; #if 0 if(is_action(lp->anti_degen, ANTIDEGEN_RHSPERTURB)) *ofValue -= rand_uniform(lp, lp->epsperturb); #endif } } /* Do scaling and test for zero */ if(accept) { (*ofValue) *= mult; if(fabs(*ofValue) < lp->epsmachine) { (*ofValue) = 0; accept = FALSE; } } else (*ofValue) = 0; return( accept ); } STATIC void set_OF_p1extra(lprec *lp, REAL p1extra) { int i; REAL *value; if(lp->spx_trace) report(lp, DETAILED, "set_OF_p1extra: Set dual objective offset to %g at iter %.0f.\n", p1extra, (double) get_total_iter(lp)); lp->P1extraVal = p1extra; if(lp->obj == NULL) allocREAL(lp, &lp->obj, lp->columns_alloc+1, TRUE); for(i = 1, value = lp->obj+1; i <= lp->columns; i++, value++) { *value = lp->orig_obj[i]; modifyOF1(lp, lp->rows + i, value, 1.0); } } STATIC void unset_OF_p1extra(lprec *lp) { lp->P1extraVal = 0; FREE(lp->obj); } REAL __WINAPI get_OF_active(lprec *lp, int varnr, REAL mult) { int colnr = varnr - lp->rows; REAL holdOF = 0; #ifdef Paranoia if((colnr <= 0) || (colnr > lp->columns)) { report(lp, SEVERE, "get_OF_active: Invalid column index %d supplied\n", colnr); } else #endif if(lp->obj == NULL) { if(colnr > 0) holdOF = lp->orig_obj[colnr]; modifyOF1(lp, varnr, &holdOF, mult); } else if(colnr > 0) holdOF = lp->obj[colnr] * mult; return( holdOF ); } STATIC MYBOOL is_OF_nz(lprec *lp, int colnr) { return( (MYBOOL) (lp->orig_obj[colnr] != 0) ); } STATIC int singleton_column(lprec *lp, int row_nr, REAL *column, int *nzlist, REAL value, int *maxabs) { int nz = 1; if(nzlist == NULL) { MEMCLEAR(column, lp->rows + 1); column[row_nr] = value; } else { column[nz] = value; nzlist[nz] = row_nr; } if(maxabs != NULL) *maxabs = row_nr; return( nz ); } STATIC int expand_column(lprec *lp, int col_nr, REAL *column, int *nzlist, REAL mult, int *maxabs) { int i, ie, j, maxidx, nzcount; REAL value, maxval; MATrec *mat = lp->matA; REAL *matValue; int *matRownr; /* Retrieve a column from the user data matrix A */ maxval = 0; maxidx = -1; if(nzlist == NULL) { MEMCLEAR(column, lp->rows + 1); i = mat->col_end[col_nr - 1]; ie = mat->col_end[col_nr]; matRownr = &COL_MAT_ROWNR(i); matValue = &COL_MAT_VALUE(i); nzcount = i; for(; i < ie; i++, matRownr += matRowColStep, matValue += matValueStep) { j = *matRownr; value = *matValue; if(j > 0) { value *= mult; if(fabs(value) > maxval) { maxval = fabs(value); maxidx = j; } } column[j] = value; } nzcount = i - nzcount; /* Get the objective as row 0, optionally adjusting the objective for phase 1 */ if(lp->obj_in_basis) { column[0] = get_OF_active(lp, lp->rows+col_nr, mult); if(column[0] != 0) nzcount++; } } else { nzcount = 0; /* Get the objective as row 0, optionally adjusting the objective for phase 1 */ if(lp->obj_in_basis) { value = get_OF_active(lp, lp->rows+col_nr, mult); if(value != 0) { nzcount++; nzlist[nzcount] = 0; column[nzcount] = value; } } /* Loop over the non-zero column entries */ i = mat->col_end[col_nr - 1]; ie = mat->col_end[col_nr]; matRownr = &COL_MAT_ROWNR(i); matValue = &COL_MAT_VALUE(i); for(; i < ie; i++, matRownr += matRowColStep, matValue += matValueStep) { j = *matRownr; value = (*matValue) * mult; nzcount++; nzlist[nzcount] = j; column[nzcount] = value; if(fabs(value) > maxval) { maxval = fabs(value); maxidx = nzcount; } } } if(maxabs != NULL) *maxabs = maxidx; return( nzcount ); } /* Retrieve a column vector from the data matrix [1..rows, rows+1..rows+columns]; needs __WINAPI call model since it may be called from BFPs */ int __WINAPI obtain_column(lprec *lp, int varin, REAL *pcol, int *nzlist, int *maxabs) { REAL value = my_chsign(lp->is_lower[varin], -1); if(varin > lp->rows) { varin -= lp->rows; varin = expand_column(lp, varin, pcol, nzlist, value, maxabs); } else if(lp->obj_in_basis || (varin > 0)) varin = singleton_column(lp, varin, pcol, nzlist, value, maxabs); else varin = get_basisOF(lp, NULL, pcol, nzlist); return(varin); } /* GENERAL INVARIANT CALLBACK FUNCTIONS */ MYBOOL set_callbacks(lprec *lp) { /* Assign API functions to lp structure (mainly for XLIs) */ lp->add_column = add_column; lp->add_columnex = add_columnex; lp->add_constraint = add_constraint; lp->add_constraintex = add_constraintex; lp->add_lag_con = add_lag_con; lp->add_SOS = add_SOS; lp->column_in_lp = column_in_lp; lp->copy_lp = copy_lp; lp->default_basis = default_basis; lp->del_column = del_column; lp->del_constraint = del_constraint; lp->delete_lp = delete_lp; lp->dualize_lp = dualize_lp; lp->free_lp = free_lp; lp->get_anti_degen = get_anti_degen; lp->get_basis = get_basis; lp->get_basiscrash = get_basiscrash; lp->get_bb_depthlimit = get_bb_depthlimit; lp->get_bb_floorfirst = get_bb_floorfirst; lp->get_bb_rule = get_bb_rule; lp->get_bounds_tighter = get_bounds_tighter; lp->get_break_at_value = get_break_at_value; lp->get_col_name = get_col_name; lp->get_columnex = get_columnex; lp->get_constr_type = get_constr_type; lp->get_constr_value = get_constr_value; lp->get_constraints = get_constraints; lp->get_dual_solution = get_dual_solution; lp->get_epsb = get_epsb; lp->get_epsd = get_epsd; lp->get_epsel = get_epsel; lp->get_epsint = get_epsint; lp->get_epsperturb = get_epsperturb; lp->get_epspivot = get_epspivot; lp->get_improve = get_improve; lp->get_infinite = get_infinite; lp->get_lambda = get_lambda; lp->get_lowbo = get_lowbo; lp->get_lp_index = get_lp_index; lp->get_lp_name = get_lp_name; lp->get_Lrows = get_Lrows; lp->get_mat = get_mat; lp->get_mat_byindex = get_mat_byindex; lp->get_max_level = get_max_level; lp->get_maxpivot = get_maxpivot; lp->get_mip_gap = get_mip_gap; lp->get_multiprice = get_multiprice; lp->get_nameindex = get_nameindex; lp->get_Ncolumns = get_Ncolumns; lp->get_negrange = get_negrange; lp->get_nonzeros = get_nonzeros; lp->get_Norig_columns = get_Norig_columns; lp->get_Norig_rows = get_Norig_rows; lp->get_Nrows = get_Nrows; lp->get_obj_bound = get_obj_bound; lp->get_objective = get_objective; lp->get_orig_index = get_orig_index; lp->get_origcol_name = get_origcol_name; lp->get_origrow_name = get_origrow_name; lp->get_partialprice = get_partialprice; lp->get_pivoting = get_pivoting; lp->get_presolve = get_presolve; lp->get_presolveloops = get_presolveloops; lp->get_primal_solution = get_primal_solution; lp->get_print_sol = get_print_sol; lp->get_pseudocosts = get_pseudocosts; lp->get_ptr_constraints = get_ptr_constraints; lp->get_ptr_dual_solution = get_ptr_dual_solution; lp->get_ptr_lambda = get_ptr_lambda; lp->get_ptr_primal_solution = get_ptr_primal_solution; lp->get_ptr_sensitivity_obj = get_ptr_sensitivity_obj; lp->get_ptr_sensitivity_objex = get_ptr_sensitivity_objex; lp->get_ptr_sensitivity_rhs = get_ptr_sensitivity_rhs; lp->get_ptr_variables = get_ptr_variables; lp->get_rh = get_rh; lp->get_rh_range = get_rh_range; lp->get_row = get_row; lp->get_rowex = get_rowex; lp->get_row_name = get_row_name; lp->get_scalelimit = get_scalelimit; lp->get_scaling = get_scaling; lp->get_sensitivity_obj = get_sensitivity_obj; lp->get_sensitivity_objex = get_sensitivity_objex; lp->get_sensitivity_rhs = get_sensitivity_rhs; lp->get_simplextype = get_simplextype; lp->get_solutioncount = get_solutioncount; lp->get_solutionlimit = get_solutionlimit; lp->get_status = get_status; lp->get_statustext = get_statustext; lp->get_timeout = get_timeout; lp->get_total_iter = get_total_iter; lp->get_total_nodes = get_total_nodes; lp->get_upbo = get_upbo; lp->get_var_branch = get_var_branch; lp->get_var_dualresult = get_var_dualresult; lp->get_var_primalresult = get_var_primalresult; lp->get_var_priority = get_var_priority; lp->get_variables = get_variables; lp->get_verbose = get_verbose; lp->get_working_objective = get_working_objective; lp->has_BFP = has_BFP; lp->has_XLI = has_XLI; lp->is_add_rowmode = is_add_rowmode; lp->is_anti_degen = is_anti_degen; lp->is_binary = is_binary; lp->is_break_at_first = is_break_at_first; lp->is_constr_type = is_constr_type; lp->is_debug = is_debug; lp->is_feasible = is_feasible; lp->is_unbounded = is_unbounded; lp->is_infinite = is_infinite; lp->is_int = is_int; lp->is_integerscaling = is_integerscaling; lp->is_lag_trace = is_lag_trace; lp->is_maxim = is_maxim; lp->is_nativeBFP = is_nativeBFP; lp->is_nativeXLI = is_nativeXLI; lp->is_negative = is_negative; lp->is_obj_in_basis = is_obj_in_basis; lp->is_piv_mode = is_piv_mode; lp->is_piv_rule = is_piv_rule; lp->is_presolve = is_presolve; lp->is_scalemode = is_scalemode; lp->is_scaletype = is_scaletype; lp->is_semicont = is_semicont; lp->is_SOS_var = is_SOS_var; lp->is_trace = is_trace; lp->lp_solve_version = lp_solve_version; lp->make_lp = make_lp; lp->print_constraints = print_constraints; lp->print_debugdump = print_debugdump; lp->print_duals = print_duals; lp->print_lp = print_lp; lp->print_objective = print_objective; lp->print_scales = print_scales; lp->print_solution = print_solution; lp->print_str = print_str; lp->print_tableau = print_tableau; lp->put_abortfunc = put_abortfunc; lp->put_bb_nodefunc = put_bb_nodefunc; lp->put_bb_branchfunc = put_bb_branchfunc; lp->put_logfunc = put_logfunc; lp->put_msgfunc = put_msgfunc; lp->read_LP = read_LP; lp->read_MPS = read_MPS; lp->read_XLI = read_XLI; lp->read_basis = read_basis; lp->reset_basis = reset_basis; lp->read_params = read_params; lp->reset_params = reset_params; lp->resize_lp = resize_lp; lp->set_action = set_action; lp->set_add_rowmode = set_add_rowmode; lp->set_anti_degen = set_anti_degen; lp->set_basisvar = set_basisvar; lp->set_basis = set_basis; lp->set_basiscrash = set_basiscrash; lp->set_bb_depthlimit = set_bb_depthlimit; lp->set_bb_floorfirst = set_bb_floorfirst; lp->set_bb_rule = set_bb_rule; lp->set_BFP = set_BFP; lp->set_binary = set_binary; lp->set_bounds = set_bounds; lp->set_bounds_tighter = set_bounds_tighter; lp->set_break_at_first = set_break_at_first; lp->set_break_at_value = set_break_at_value; lp->set_col_name = set_col_name; lp->set_constr_type = set_constr_type; lp->set_debug = set_debug; lp->set_epsb = set_epsb; lp->set_epsd = set_epsd; lp->set_epsel = set_epsel; lp->set_epsint = set_epsint; lp->set_epslevel = set_epslevel; lp->set_epsperturb = set_epsperturb; lp->set_epspivot = set_epspivot; lp->set_unbounded = set_unbounded; lp->set_improve = set_improve; lp->set_infinite = set_infinite; lp->set_int = set_int; lp->set_lag_trace = set_lag_trace; lp->set_lowbo = set_lowbo; lp->set_lp_name = set_lp_name; lp->set_mat = set_mat; lp->set_maxim = set_maxim; lp->set_maxpivot = set_maxpivot; lp->set_minim = set_minim; lp->set_mip_gap = set_mip_gap; lp->set_multiprice = set_multiprice; lp->set_negrange = set_negrange; lp->set_obj = set_obj; lp->set_obj_bound = set_obj_bound; lp->set_obj_fn = set_obj_fn; lp->set_obj_fnex = set_obj_fnex; lp->set_obj_in_basis = set_obj_in_basis; lp->set_outputfile = set_outputfile; lp->set_outputstream = set_outputstream; lp->set_partialprice = set_partialprice; lp->set_pivoting = set_pivoting; lp->set_preferdual = set_preferdual; lp->set_presolve = set_presolve; lp->set_print_sol = set_print_sol; lp->set_pseudocosts = set_pseudocosts; lp->set_rh = set_rh; lp->set_rh_range = set_rh_range; lp->set_rh_vec = set_rh_vec; lp->set_row = set_row; lp->set_rowex = set_rowex; lp->set_row_name = set_row_name; lp->set_scalelimit = set_scalelimit; lp->set_scaling = set_scaling; lp->set_semicont = set_semicont; lp->set_sense = set_sense; lp->set_simplextype = set_simplextype; lp->set_solutionlimit = set_solutionlimit; lp->set_timeout = set_timeout; lp->set_trace = set_trace; lp->set_upbo = set_upbo; lp->set_var_branch = set_var_branch; lp->set_var_weights = set_var_weights; lp->set_verbose = set_verbose; lp->set_XLI = set_XLI; lp->solve = solve; lp->str_add_column = str_add_column; lp->str_add_constraint = str_add_constraint; lp->str_add_lag_con = str_add_lag_con; lp->str_set_obj_fn = str_set_obj_fn; lp->str_set_rh_vec = str_set_rh_vec; lp->time_elapsed = time_elapsed; lp->unscale = unscale; lp->write_lp = write_lp; lp->write_LP = write_LP; lp->write_mps = write_mps; lp->write_freemps = write_freemps; lp->write_MPS = write_MPS; lp->write_freeMPS = write_freeMPS; lp->write_XLI = write_XLI; lp->write_basis = write_basis; lp->write_params = write_params; /* Utility functions (mainly for BFPs) */ lp->userabort = userabort; lp->report = report; lp->explain = explain; lp->set_basisvar = set_basisvar; lp->get_lpcolumn = obtain_column; lp->get_basiscolumn = get_basiscolumn; lp->get_OF_active = get_OF_active; lp->getMDO = getMDO; lp->invert = invert; lp->set_action = set_action; lp->clear_action = clear_action; lp->is_action = is_action; return( TRUE ); } /* SUPPORT FUNCTION FOR BASIS FACTORIZATION PACKAGES */ MYBOOL __WINAPI has_BFP(lprec *lp) { return( is_nativeBFP(lp) #if LoadInverseLib == TRUE || (MYBOOL) (lp->hBFP != NULL) #endif ); } MYBOOL __WINAPI is_nativeBFP(lprec *lp) { #ifdef ExcludeNativeInverse return( FALSE ); #elif LoadInverseLib == TRUE return( (MYBOOL) (lp->hBFP == NULL) ); #else return( TRUE ); #endif } MYBOOL __WINAPI set_BFP(lprec *lp, char *filename) /* (Re)mapping of basis factorization variant methods is done here */ { int result = LIB_LOADED; /* Release the BFP and basis if we are active */ if(lp->invB != NULL) bfp_free(lp); #if LoadInverseLib == TRUE if(lp->hBFP != NULL) { #ifdef WIN32 FreeLibrary(lp->hBFP); #else dlclose(lp->hBFP); #endif lp->hBFP = NULL; } #endif if(filename == NULL) { if(!is_nativeBFP(lp)) return( FALSE ); #ifndef ExcludeNativeInverse lp->bfp_name = bfp_name; lp->bfp_compatible = bfp_compatible; lp->bfp_free = bfp_free; lp->bfp_resize = bfp_resize; lp->bfp_nonzeros = bfp_nonzeros; lp->bfp_memallocated = bfp_memallocated; lp->bfp_restart = bfp_restart; lp->bfp_mustrefactorize = bfp_mustrefactorize; lp->bfp_preparefactorization = bfp_preparefactorization; lp->bfp_factorize = bfp_factorize; lp->bfp_finishupdate = bfp_finishupdate; lp->bfp_ftran_normal = bfp_ftran_normal; lp->bfp_ftran_prepare = bfp_ftran_prepare; lp->bfp_btran_normal = bfp_btran_normal; lp->bfp_status = bfp_status; lp->bfp_implicitslack = bfp_implicitslack; lp->bfp_indexbase = bfp_indexbase; lp->bfp_rowoffset = bfp_rowoffset; lp->bfp_pivotmax = bfp_pivotmax; lp->bfp_init = bfp_init; lp->bfp_pivotalloc = bfp_pivotalloc; lp->bfp_colcount = bfp_colcount; lp->bfp_canresetbasis = bfp_canresetbasis; lp->bfp_finishfactorization = bfp_finishfactorization; lp->bfp_updaterefactstats = bfp_updaterefactstats; lp->bfp_prepareupdate = bfp_prepareupdate; lp->bfp_pivotRHS = bfp_pivotRHS; lp->bfp_btran_double = bfp_btran_double; lp->bfp_efficiency = bfp_efficiency; lp->bfp_pivotvector = bfp_pivotvector; lp->bfp_pivotcount = bfp_pivotcount; lp->bfp_refactcount = bfp_refactcount; lp->bfp_isSetI = bfp_isSetI; lp->bfp_findredundant = bfp_findredundant; #endif } else { #if LoadInverseLib == TRUE #ifdef WIN32 /* Get a handle to the Windows DLL module. */ lp->hBFP = LoadLibrary(filename); /* If the handle is valid, try to get the function addresses. */ if(lp->hBFP != NULL) { lp->bfp_compatible = (BFPbool_lpintintint *) GetProcAddress(lp->hBFP, "bfp_compatible"); if(lp->bfp_compatible == NULL) result = LIB_NOINFO; else if(lp->bfp_compatible(lp, BFPVERSION, MAJORVERSION, sizeof(REAL))) { lp->bfp_name = (BFPchar *) GetProcAddress(lp->hBFP, "bfp_name"); lp->bfp_free = (BFP_lp *) GetProcAddress(lp->hBFP, "bfp_free"); lp->bfp_resize = (BFPbool_lpint *) GetProcAddress(lp->hBFP, "bfp_resize"); lp->bfp_nonzeros = (BFPint_lpbool *) GetProcAddress(lp->hBFP, "bfp_nonzeros"); lp->bfp_memallocated = (BFPint_lp *) GetProcAddress(lp->hBFP, "bfp_memallocated"); lp->bfp_restart = (BFPbool_lp *) GetProcAddress(lp->hBFP, "bfp_restart"); lp->bfp_mustrefactorize = (BFPbool_lp *) GetProcAddress(lp->hBFP, "bfp_mustrefactorize"); lp->bfp_preparefactorization = (BFPint_lp *) GetProcAddress(lp->hBFP, "bfp_preparefactorization"); lp->bfp_factorize = (BFPint_lpintintboolbool *) GetProcAddress(lp->hBFP, "bfp_factorize"); lp->bfp_finishupdate = (BFPbool_lpbool *) GetProcAddress(lp->hBFP, "bfp_finishupdate"); lp->bfp_ftran_normal = (BFP_lprealint *) GetProcAddress(lp->hBFP, "bfp_ftran_normal"); lp->bfp_ftran_prepare = (BFP_lprealint *) GetProcAddress(lp->hBFP, "bfp_ftran_prepare"); lp->bfp_btran_normal = (BFP_lprealint *) GetProcAddress(lp->hBFP, "bfp_btran_normal"); lp->bfp_status = (BFPint_lp *) GetProcAddress(lp->hBFP, "bfp_status"); lp->bfp_implicitslack = (BFPbool_lp *) GetProcAddress(lp->hBFP, "bfp_implicitslack"); lp->bfp_indexbase = (BFPint_lp *) GetProcAddress(lp->hBFP, "bfp_indexbase"); lp->bfp_rowoffset = (BFPint_lp *) GetProcAddress(lp->hBFP, "bfp_rowoffset"); lp->bfp_pivotmax = (BFPint_lp *) GetProcAddress(lp->hBFP, "bfp_pivotmax"); lp->bfp_init = (BFPbool_lpintintchar *) GetProcAddress(lp->hBFP, "bfp_init"); lp->bfp_pivotalloc = (BFPbool_lpint *) GetProcAddress(lp->hBFP, "bfp_pivotalloc"); lp->bfp_colcount = (BFPint_lp *) GetProcAddress(lp->hBFP, "bfp_colcount"); lp->bfp_canresetbasis = (BFPbool_lp *) GetProcAddress(lp->hBFP, "bfp_canresetbasis"); lp->bfp_finishfactorization = (BFP_lp *) GetProcAddress(lp->hBFP, "bfp_finishfactorization"); lp->bfp_updaterefactstats = (BFP_lp *) GetProcAddress(lp->hBFP, "bfp_updaterefactstats"); lp->bfp_prepareupdate = (BFPlreal_lpintintreal *) GetProcAddress(lp->hBFP, "bfp_prepareupdate"); lp->bfp_pivotRHS = (BFPreal_lplrealreal *) GetProcAddress(lp->hBFP, "bfp_pivotRHS"); lp->bfp_btran_double = (BFP_lprealintrealint *) GetProcAddress(lp->hBFP, "bfp_btran_double"); lp->bfp_efficiency = (BFPreal_lp *) GetProcAddress(lp->hBFP, "bfp_efficiency"); lp->bfp_pivotvector = (BFPrealp_lp *) GetProcAddress(lp->hBFP, "bfp_pivotvector"); lp->bfp_pivotcount = (BFPint_lp *) GetProcAddress(lp->hBFP, "bfp_pivotcount"); lp->bfp_refactcount = (BFPint_lpint *) GetProcAddress(lp->hBFP, "bfp_refactcount"); lp->bfp_isSetI = (BFPbool_lp *) GetProcAddress(lp->hBFP, "bfp_isSetI"); lp->bfp_findredundant = (BFPint_lpintrealcbintint *) GetProcAddress(lp->hBFP, "bfp_findredundant"); } else result = LIB_VERINVALID; } #else /* First standardize UNIX .SO library name format. */ char bfpname[260], *ptr; strcpy(bfpname, filename); if((ptr = strrchr(filename, '/')) == NULL) ptr = filename; else ptr++; bfpname[(int) (ptr - filename)] = 0; if(strncmp(ptr, "lib", 3)) strcat(bfpname, "lib"); strcat(bfpname, ptr); if(strcmp(bfpname + strlen(bfpname) - 3, ".so")) strcat(bfpname, ".so"); /* Get a handle to the module. */ lp->hBFP = dlopen(bfpname, RTLD_LAZY); /* If the handle is valid, try to get the function addresses. */ if(lp->hBFP != NULL) { lp->bfp_compatible = (BFPbool_lpintintint *) dlsym(lp->hBFP, "bfp_compatible"); if(lp->bfp_compatible == NULL) result = LIB_NOINFO; else if(lp->bfp_compatible(lp, BFPVERSION, MAJORVERSION, sizeof(REAL))) { lp->bfp_name = (BFPchar *) dlsym(lp->hBFP, "bfp_name"); lp->bfp_free = (BFP_lp *) dlsym(lp->hBFP, "bfp_free"); lp->bfp_resize = (BFPbool_lpint *) dlsym(lp->hBFP, "bfp_resize"); lp->bfp_nonzeros = (BFPint_lpbool *) dlsym(lp->hBFP, "bfp_nonzeros"); lp->bfp_memallocated = (BFPint_lp *) dlsym(lp->hBFP, "bfp_memallocated"); lp->bfp_restart = (BFPbool_lp *) dlsym(lp->hBFP, "bfp_restart"); lp->bfp_mustrefactorize = (BFPbool_lp *) dlsym(lp->hBFP, "bfp_mustrefactorize"); lp->bfp_preparefactorization = (BFPint_lp *) dlsym(lp->hBFP, "bfp_preparefactorization"); lp->bfp_factorize = (BFPint_lpintintboolbool *) dlsym(lp->hBFP, "bfp_factorize"); lp->bfp_finishupdate = (BFPbool_lpbool *) dlsym(lp->hBFP, "bfp_finishupdate"); lp->bfp_ftran_normal = (BFP_lprealint *) dlsym(lp->hBFP, "bfp_ftran_normal"); lp->bfp_ftran_prepare = (BFP_lprealint *) dlsym(lp->hBFP, "bfp_ftran_prepare"); lp->bfp_btran_normal = (BFP_lprealint *) dlsym(lp->hBFP, "bfp_btran_normal"); lp->bfp_status = (BFPint_lp *) dlsym(lp->hBFP, "bfp_status"); lp->bfp_implicitslack = (BFPbool_lp *) dlsym(lp->hBFP, "bfp_implicitslack"); lp->bfp_indexbase = (BFPint_lp *) dlsym(lp->hBFP, "bfp_indexbase"); lp->bfp_rowoffset = (BFPint_lp *) dlsym(lp->hBFP, "bfp_rowoffset"); lp->bfp_pivotmax = (BFPint_lp *) dlsym(lp->hBFP, "bfp_pivotmax"); lp->bfp_init = (BFPbool_lpintintchar *) dlsym(lp->hBFP, "bfp_init"); lp->bfp_pivotalloc = (BFPbool_lpint *) dlsym(lp->hBFP, "bfp_pivotalloc"); lp->bfp_colcount = (BFPint_lp *) dlsym(lp->hBFP, "bfp_colcount"); lp->bfp_canresetbasis = (BFPbool_lp *) dlsym(lp->hBFP, "bfp_canresetbasis"); lp->bfp_finishfactorization = (BFP_lp *) dlsym(lp->hBFP, "bfp_finishfactorization"); lp->bfp_updaterefactstats = (BFP_lp *) dlsym(lp->hBFP, "bfp_updaterefactstats"); lp->bfp_prepareupdate = (BFPlreal_lpintintreal *) dlsym(lp->hBFP, "bfp_prepareupdate"); lp->bfp_pivotRHS = (BFPreal_lplrealreal *) dlsym(lp->hBFP, "bfp_pivotRHS"); lp->bfp_btran_double = (BFP_lprealintrealint *) dlsym(lp->hBFP, "bfp_btran_double"); lp->bfp_efficiency = (BFPreal_lp *) dlsym(lp->hBFP, "bfp_efficiency"); lp->bfp_pivotvector = (BFPrealp_lp *) dlsym(lp->hBFP, "bfp_pivotvector"); lp->bfp_pivotcount = (BFPint_lp *) dlsym(lp->hBFP, "bfp_pivotcount"); lp->bfp_refactcount = (BFPint_lpint *) dlsym(lp->hBFP, "bfp_refactcount"); lp->bfp_isSetI = (BFPbool_lp *) dlsym(lp->hBFP, "bfp_isSetI"); lp->bfp_findredundant = (BFPint_lpintrealcbintint *) dlsym(lp->hBFP, "bfp_findredundant"); } else result = LIB_VERINVALID; } #endif else result = LIB_NOTFOUND; #endif /* Do validation */ if((result != LIB_LOADED) || ((lp->bfp_name == NULL) || (lp->bfp_compatible == NULL) || (lp->bfp_free == NULL) || (lp->bfp_resize == NULL) || (lp->bfp_nonzeros == NULL) || (lp->bfp_memallocated == NULL) || (lp->bfp_restart == NULL) || (lp->bfp_mustrefactorize == NULL) || (lp->bfp_preparefactorization == NULL) || (lp->bfp_factorize == NULL) || (lp->bfp_finishupdate == NULL) || (lp->bfp_ftran_normal == NULL) || (lp->bfp_ftran_prepare == NULL) || (lp->bfp_btran_normal == NULL) || (lp->bfp_status == NULL) || (lp->bfp_implicitslack == NULL) || (lp->bfp_indexbase == NULL) || (lp->bfp_rowoffset == NULL) || (lp->bfp_pivotmax == NULL) || (lp->bfp_init == NULL) || (lp->bfp_pivotalloc == NULL) || (lp->bfp_colcount == NULL) || (lp->bfp_canresetbasis == NULL) || (lp->bfp_finishfactorization == NULL) || (lp->bfp_updaterefactstats == NULL) || (lp->bfp_prepareupdate == NULL) || (lp->bfp_pivotRHS == NULL) || (lp->bfp_btran_double == NULL) || (lp->bfp_efficiency == NULL) || (lp->bfp_pivotvector == NULL) || (lp->bfp_pivotcount == NULL) || (lp->bfp_refactcount == NULL) || (lp->bfp_isSetI == NULL) || (lp->bfp_findredundant == NULL) )) { set_BFP(lp, NULL); if(result == LIB_LOADED) result = LIB_NOFUNCTION; } } if(filename != NULL) { char info[LIB_STR_MAXLEN+1]; switch(result) { case LIB_NOTFOUND: strcpy(info, LIB_STR_NOTFOUND); break; case LIB_NOINFO: strcpy(info, LIB_STR_NOINFO); break; case LIB_NOFUNCTION: strcpy(info, LIB_STR_NOFUNCTION); break; case LIB_VERINVALID: strcpy(info, LIB_STR_VERINVALID); break; default: strcpy(info, LIB_STR_LOADED); } report(lp, IMPORTANT, "set_BFP: %s '%s'\n", info, filename); } return( (MYBOOL) (result == LIB_LOADED)); } /* External language interface routines */ /* DON'T MODIFY */ lprec * __WINAPI read_XLI(char *xliname, char *modelname, char *dataname, char *options, int verbose) { lprec *lp; lp = make_lp(0, 0); if(lp != NULL) { lp->source_is_file = TRUE; lp->verbose = verbose; if(!set_XLI(lp, xliname)) { free_lp(&lp); printf("read_XLI: No valid XLI package selected or available.\n"); } else { if(!lp->xli_readmodel(lp, modelname, (dataname != NULL) && (*dataname != 0) ? dataname : NULL, options, verbose)) free_lp(&lp); } } return( lp ); } MYBOOL __WINAPI write_XLI(lprec *lp, char *filename, char *options, MYBOOL results) { return( has_XLI(lp) && mat_validate(lp->matA) && lp->xli_writemodel(lp, filename, options, results) ); } MYBOOL __WINAPI has_XLI(lprec *lp) { return( is_nativeXLI(lp) #if LoadLanguageLib == TRUE || (MYBOOL) (lp->hXLI != NULL) #endif ); } MYBOOL __WINAPI is_nativeXLI(lprec *lp) { #ifdef ExcludeNativeLanguage return( FALSE ); #elif LoadLanguageLib == TRUE return( (MYBOOL) (lp->hXLI == NULL) ); #else return( TRUE ); #endif } MYBOOL __WINAPI set_XLI(lprec *lp, char *filename) /* (Re)mapping of external language interface variant methods is done here */ { int result = LIB_LOADED; #if LoadLanguageLib == TRUE if(lp->hXLI != NULL) { #ifdef WIN32 FreeLibrary(lp->hXLI); #else dlclose(lp->hXLI); #endif lp->hXLI = NULL; } #endif if(filename == NULL) { if(!is_nativeXLI(lp)) return( FALSE ); #ifndef ExcludeNativeLanguage lp->xli_name = xli_name; lp->xli_compatible = xli_compatible; lp->xli_readmodel = xli_readmodel; lp->xli_writemodel = xli_writemodel; #endif } else { #if LoadLanguageLib == TRUE #ifdef WIN32 /* Get a handle to the Windows DLL module. */ lp->hXLI = LoadLibrary(filename); /* If the handle is valid, try to get the function addresses. */ if(lp->hXLI != NULL) { lp->xli_compatible = (XLIbool_lpintintint *) GetProcAddress(lp->hXLI, "xli_compatible"); if(lp->xli_compatible == NULL) result = LIB_NOINFO; else if(lp->xli_compatible(lp, XLIVERSION, MAJORVERSION, sizeof(REAL))) { lp->xli_name = (XLIchar *) GetProcAddress(lp->hXLI, "xli_name"); lp->xli_readmodel = (XLIbool_lpcharcharcharint *) GetProcAddress(lp->hXLI, "xli_readmodel"); lp->xli_writemodel = (XLIbool_lpcharcharbool *) GetProcAddress(lp->hXLI, "xli_writemodel"); } else result = LIB_VERINVALID; } #else /* First standardize UNIX .SO library name format. */ char xliname[260], *ptr; strcpy(xliname, filename); if((ptr = strrchr(filename, '/')) == NULL) ptr = filename; else ptr++; xliname[(int) (ptr - filename)] = 0; if(strncmp(ptr, "lib", 3)) strcat(xliname, "lib"); strcat(xliname, ptr); if(strcmp(xliname + strlen(xliname) - 3, ".so")) strcat(xliname, ".so"); /* Get a handle to the module. */ lp->hXLI = dlopen(xliname, RTLD_LAZY); /* If the handle is valid, try to get the function addresses. */ if(lp->hXLI != NULL) { lp->xli_compatible = (XLIbool_lpintintint *) dlsym(lp->hXLI, "xli_compatible"); if(lp->xli_compatible == NULL) result = LIB_NOINFO; else if(lp->xli_compatible(lp, XLIVERSION, MAJORVERSION, sizeof(REAL))) { lp->xli_name = (XLIchar *) dlsym(lp->hXLI, "xli_name"); lp->xli_readmodel = (XLIbool_lpcharcharcharint *) dlsym(lp->hXLI, "xli_readmodel"); lp->xli_writemodel = (XLIbool_lpcharcharbool *) dlsym(lp->hXLI, "xli_writemodel"); } else result = LIB_VERINVALID; } #endif else result = LIB_NOTFOUND; #endif /* Do validation */ if((result != LIB_LOADED) || ((lp->xli_name == NULL) || (lp->xli_compatible == NULL) || (lp->xli_readmodel == NULL) || (lp->xli_writemodel == NULL) )) { set_XLI(lp, NULL); if(result == LIB_LOADED) result = LIB_NOFUNCTION; } } if(filename != NULL) { char info[LIB_STR_MAXLEN+1]; switch(result) { case LIB_NOTFOUND: strcpy(info, LIB_STR_NOTFOUND); break; case LIB_NOINFO: strcpy(info, LIB_STR_NOINFO); break; case LIB_NOFUNCTION: strcpy(info, LIB_STR_NOFUNCTION); break; case LIB_VERINVALID: strcpy(info, LIB_STR_VERINVALID); break; default: strcpy(info, LIB_STR_LOADED); } report(lp, IMPORTANT, "set_XLI: %s '%s'\n", info, filename); } return( (MYBOOL) (result == LIB_LOADED)); } STATIC int get_basisOF(lprec *lp, int coltarget[], REAL crow[], int colno[]) /* Fill vector of basic OF values or subtract incoming values from these. This function is called twice during reduced cost updates when the basis does not contain the basic OF vector as the top row. The colno[] array is filled with the count of non-zero values and the index to those. */ { int i, n = lp->rows, nz = 0; REAL *obj = lp->obj; register REAL epsvalue = lp->epsvalue; /* Compute offset over the specified objective indeces (step 2) */ if(coltarget != NULL) { register int ix, m = coltarget[0]; register REAL value; for(i = 1, coltarget++; i <= m; i++, coltarget++) { ix = *coltarget; /* Finalize the computation of the reduced costs, based on the format that duals are computed as negatives, ref description for step 1 above */ value = crow[ix]; if(ix > n) value += obj[ix - n]; /* if(value != 0) { */ if(fabs(value) > epsvalue) { nz++; if(colno != NULL) colno[nz] = ix; } else value = 0.0; crow[ix] = value; } } /* Get the basic objective function values (step 1) */ else { register int *basvar = lp->var_basic; for(i = 1, crow++, basvar++; i <= n; i++, crow++, basvar++) { /* Load the objective value of the active basic variable; note that we change the sign of the value to maintain computational compatibility with the calculation of duals using in-basis storage of the basic OF values */ if(*basvar <= n) *crow = 0; else *crow = -obj[(*basvar) - n]; if((*crow) != 0) { /* if(fabs(*crow) > epsvalue) { */ nz++; if(colno != NULL) colno[nz] = i; } } } if(colno != NULL) colno[0] = nz; return( nz ); } int __WINAPI get_basiscolumn(lprec *lp, int j, int rn[], double bj[]) /* This routine returns sparse vectors for all basis columns, including the OF dummy (index 0) and slack columns. NOTE that the index usage is nonstandard for lp_solve, since the array offset is 1, not 0. */ { int k = lp->bfp_rowoffset(lp), matbase = lp->bfp_indexbase(lp); /* Do target index adjustment (etaPFI with matbase==0 is special case) */ if(matbase > 0) matbase += k - 1; /* Convert index of slack and user columns */ j -= k; if((j > 0) && !lp->bfp_isSetI(lp)) j = lp->var_basic[j]; /* Process OF dummy and slack columns (always at lower bound) */ if(j <= lp->rows) { rn[1] = j + matbase; bj[1] = 1.0; k = 1; } /* Process user columns (negated if at lower bound) */ else { k = obtain_column(lp, j, bj, rn, NULL); if(matbase != 0) for(j = 1; j <= k; j++) rn[j] += matbase; } return( k ); } MYBOOL __WINAPI get_primal_solution(lprec *lp, REAL *pv) { if(lp->spx_status == OPTIMAL) ; else if(!lp->basis_valid) { report(lp, CRITICAL, "get_primal_solution: Not a valid basis"); return(FALSE); } MEMCOPY(pv, lp->best_solution, lp->sum + 1); return(TRUE); } MYBOOL __WINAPI get_ptr_primal_solution(lprec *lp, REAL **pv) { *pv = lp->best_solution; return(TRUE); } MYBOOL __WINAPI get_dual_solution(lprec *lp, REAL *rc) { REAL *duals; MYBOOL ret; if(!lp->basis_valid) { report(lp, CRITICAL, "get_dual_solution: Not a valid basis"); return(FALSE); } ret = get_ptr_sensitivity_rhs(lp, &duals, NULL, NULL); if(ret) MEMCOPY(rc, duals - 1, lp->sum + 1); return(ret); } MYBOOL __WINAPI get_ptr_dual_solution(lprec *lp, REAL **rc) { MYBOOL ret = lp->basis_valid; /* Just return availability of dual information if rc is NULL */ if(rc == NULL) return( ret && ((MIP_count(lp) == 0) || (lp->bb_totalnodes > 0)) ); if(!ret) { report(lp, CRITICAL, "get_ptr_dual_solution: Not a valid basis"); return(ret); } /* Otherwise, get the pointer to the dual information (and optionally produce it) */ ret = get_ptr_sensitivity_rhs(lp, rc, NULL, NULL); if(ret) (*rc)--; return(ret); } MYBOOL __WINAPI get_lambda(lprec *lp, REAL *lambda) { if(!lp->basis_valid || (get_Lrows(lp) == 0)) { report(lp, CRITICAL, "get_lambda: Not a valid basis"); return(FALSE); } MEMCOPY(lambda, lp->lambda+1, get_Lrows(lp)); return(TRUE); } MYBOOL __WINAPI get_ptr_lambda(lprec *lp, REAL **lambda) { *lambda = lp->lambda; return(TRUE); } int __WINAPI get_orig_index(lprec *lp, int lp_index) { if(lp->varmap_locked) return(lp->presolve_undo->var_to_orig[lp_index]); else if(lp_index <= lp->presolve_undo->orig_rows) return(lp_index); else return(lp_index-lp->presolve_undo->orig_rows); } int __WINAPI get_lp_index(lprec *lp, int orig_index) { if(lp->varmap_locked) return(lp->presolve_undo->orig_to_var[orig_index]); else if(orig_index <= lp->presolve_undo->orig_rows) return(orig_index); else return(orig_index-lp->presolve_undo->orig_rows); } MYBOOL __WINAPI is_feasible(lprec *lp, REAL *values, REAL threshold) /* Recommend to use threshold = lp->epspivot */ { int i, j, elmnr, ie; REAL *this_rhs, dist; REAL *value; int *rownr; MATrec *mat = lp->matA; for(i = lp->rows + 1; i <= lp->sum; i++) { if(values[i - lp->rows] < unscaled_value(lp, lp->orig_lowbo[i], i) || values[i - lp->rows] > unscaled_value(lp, lp->orig_upbo[i], i)) { if(!((lp->sc_lobound[i - lp->rows]>0) && (values[i - lp->rows]==0))) return(FALSE); } } this_rhs = (REAL *) mempool_obtainVector(lp->workarrays, lp->rows+1, sizeof(*this_rhs)); /* allocREAL(lp, &this_rhs, lp->rows + 1, TRUE); */ for(j = 1; j <= lp->columns; j++) { elmnr = mat->col_end[j - 1]; ie = mat->col_end[j]; rownr = &COL_MAT_ROWNR(elmnr); value = &COL_MAT_VALUE(elmnr); for(; elmnr < ie; elmnr++, rownr += matRowColStep, value += matValueStep) { this_rhs[*rownr] += unscaled_mat(lp, *value, *rownr, j); } } for(i = 1; i <= lp->rows; i++) { dist = lp->orig_rhs[i] - this_rhs[i]; my_roundzero(dist, threshold); if((lp->orig_upbo[i] == 0 && dist != 0) ||( dist < 0)) { FREE(this_rhs); return(FALSE); } } mempool_releaseVector(lp->workarrays, (char *) this_rhs, FALSE); /* FREE(this_rhs); */ return(TRUE); } int __WINAPI column_in_lp(lprec *lp, REAL *testcolumn) { int i, j, je, colnr = 0; int nz, ident = 1; MATrec *mat = lp->matA; int *matRownr; REAL value, *matValue; for(nz = 0, i = 1; i <= lp->rows; i++) if(fabs(testcolumn[i]) > lp->epsvalue) nz++; for(i = 1; (i <= lp->columns) && (ident); i++) { ident = nz; value = fabs(get_mat(lp, 0, i)-testcolumn[0]); if(value > lp->epsvalue) continue; j = mat->col_end[i - 1]; je = mat->col_end[i]; matRownr = &COL_MAT_ROWNR(j); matValue = &COL_MAT_VALUE(j); for(; (j < je) && (ident >= 0); j++, ident--, matRownr += matRowColStep, matValue += matValueStep) { value = *matValue; if(is_chsign(lp, *matRownr)) value = my_flipsign(value); value = unscaled_mat(lp, value, *matRownr, i); value -= testcolumn[*matRownr]; if(fabs(value) > lp->epsvalue) break; } if(ident == 0) colnr = i; } return( colnr ); } MYBOOL __WINAPI set_lp_name(lprec *lp, char *name) { if (name == NULL) { FREE(lp->lp_name); lp->lp_name = NULL; } else { allocCHAR(lp, &lp->lp_name, (int) (strlen(name) + 1), AUTOMATIC); strcpy(lp->lp_name, name); } return(TRUE); } char * __WINAPI get_lp_name(lprec *lp) { return((lp->lp_name != NULL) ? lp->lp_name : (char *) ""); } STATIC MYBOOL init_rowcol_names(lprec *lp) { if(!lp->names_used) { lp->row_name = (hashelem **) calloc(lp->rows_alloc + 1, sizeof(*lp->row_name)); lp->col_name = (hashelem **) calloc(lp->columns_alloc + 1, sizeof(*lp->col_name)); lp->rowname_hashtab = create_hash_table(lp->rows_alloc + 1, 0); lp->colname_hashtab = create_hash_table(lp->columns_alloc + 1, 1); lp->names_used = TRUE; } return(TRUE); } MYBOOL rename_var(lprec *lp, int varindex, char *new_name, hashelem **list, hashtable **ht) { hashelem *hp; MYBOOL newitem; hp = list[varindex]; newitem = (MYBOOL) (hp == NULL); if(newitem) hp = puthash(new_name, varindex, list, *ht); else if((strlen(hp->name) != strlen(new_name)) || (strcmp(hp->name, new_name) != 0)) { hashtable *newht, *oldht; allocCHAR(lp, &hp->name, (int) (strlen(new_name) + 1), AUTOMATIC); strcpy(hp->name, new_name); oldht = *ht; newht = copy_hash_table(oldht, list, oldht->size); *ht = newht; free_hash_table(oldht); } return(newitem); } MYBOOL __WINAPI is_use_names(lprec *lp, MYBOOL isrow) { if(isrow) return( lp->use_row_names ); else return( lp->use_col_names ); } void __WINAPI set_use_names(lprec *lp, MYBOOL isrow, MYBOOL use_names) { if(isrow) lp->use_row_names = use_names; else lp->use_col_names = use_names; } int __WINAPI get_nameindex(lprec *lp, char *varname, MYBOOL isrow) { if(isrow) return( find_row(lp, varname, FALSE) ); else return( find_var(lp, varname, FALSE) ); } MYBOOL __WINAPI set_row_name(lprec *lp, int rownr, char *new_name) { if((rownr < 0) || (rownr > lp->rows+1)) { report(lp, IMPORTANT, "set_row_name: Row %d out of range", rownr); return(FALSE); } /* Prepare for a new row */ if((rownr > lp->rows) && !append_rows(lp, rownr-lp->rows)) return( FALSE ); if(!lp->names_used) { if(!init_rowcol_names(lp)) return(FALSE); } rename_var(lp, rownr, new_name, lp->row_name, &lp->rowname_hashtab); return(TRUE); } char * __WINAPI get_row_name(lprec *lp, int rownr) { if((rownr < 0) || (rownr > lp->rows+1)) { report(lp, IMPORTANT, "get_row_name: Row %d out of range", rownr); return(NULL); } if((lp->presolve_undo->var_to_orig != NULL) && lp->wasPresolved) { if(lp->presolve_undo->var_to_orig[rownr] == 0) rownr = -rownr; else rownr = lp->presolve_undo->var_to_orig[rownr]; } return( get_origrow_name(lp, rownr) ); } char * __WINAPI get_origrow_name(lprec *lp, int rownr) { MYBOOL newrow; char *ptr; newrow = (MYBOOL) (rownr < 0); rownr = abs(rownr); #ifdef Paranoia if(((lp->presolve_undo->var_to_orig == NULL) && newrow) || (rownr > MAX(lp->rows, lp->presolve_undo->orig_rows))) { report(lp, IMPORTANT, "get_origrow_name: Row %d out of range", rownr); return(NULL); } #endif if(lp->names_used && lp->use_row_names && (lp->row_name[rownr] != NULL) && (lp->row_name[rownr]->name != NULL)) { #ifdef Paranoia if(lp->row_name[rownr]->index != rownr) report(lp, SEVERE, "get_origrow_name: Inconsistent row ordinal %d vs %d\n", rownr, lp->row_name[rownr]->index); #endif ptr = lp->row_name[rownr]->name; } else { if(lp->rowcol_name == NULL) if (!allocCHAR(lp, &lp->rowcol_name, 20, FALSE)) return(NULL); ptr = lp->rowcol_name; if(newrow) sprintf(ptr, ROWNAMEMASK2, rownr); else sprintf(ptr, ROWNAMEMASK, rownr); } return(ptr); } MYBOOL __WINAPI set_col_name(lprec *lp, int colnr, char *new_name) { if((colnr > lp->columns+1) || (colnr < 1)) { report(lp, IMPORTANT, "set_col_name: Column %d out of range", colnr); } if((colnr > lp->columns) && !append_columns(lp, colnr-lp->columns)) return(FALSE); if(!lp->names_used) init_rowcol_names(lp); rename_var(lp, colnr, new_name, lp->col_name, &lp->colname_hashtab); return(TRUE); } char * __WINAPI get_col_name(lprec *lp, int colnr) { if((colnr > lp->columns+1) || (colnr < 1)) { report(lp, IMPORTANT, "get_col_name: Column %d out of range", colnr); return(NULL); } if((lp->presolve_undo->var_to_orig != NULL) && lp->wasPresolved) { if(lp->presolve_undo->var_to_orig[lp->rows + colnr] == 0) colnr = -colnr; else colnr = lp->presolve_undo->var_to_orig[lp->rows + colnr]; } return( get_origcol_name(lp, colnr) ); } char * __WINAPI get_origcol_name(lprec *lp, int colnr) { MYBOOL newcol; char *ptr; newcol = (MYBOOL) (colnr < 0); colnr = abs(colnr); #ifdef Paranoia if(((lp->presolve_undo->var_to_orig == NULL) && newcol) || (colnr > MAX(lp->columns, lp->presolve_undo->orig_columns))) { report(lp, IMPORTANT, "get_origcol_name: Column %d out of range", colnr); return(NULL); } #endif if(lp->names_used && lp->use_col_names && (lp->col_name[colnr] != NULL) && (lp->col_name[colnr]->name != NULL)) { #ifdef Paranoia if(lp->col_name[colnr]->index != colnr) report(lp, SEVERE, "get_origcol_name: Inconsistent column ordinal %d vs %d\n", colnr, lp->col_name[colnr]->index); #endif ptr = lp->col_name[colnr]->name; } else { if(lp->rowcol_name == NULL) if (!allocCHAR(lp, &lp->rowcol_name, 20, FALSE)) return(NULL); ptr = lp->rowcol_name; if(newcol) sprintf(ptr, COLNAMEMASK2, colnr); else sprintf(ptr, COLNAMEMASK, colnr); } return(ptr); } STATIC int MIP_count(lprec *lp) { return( lp->int_vars+lp->sc_vars+SOS_count(lp) ); } STATIC int bin_count(lprec *lp, MYBOOL working) { int i, n = 0; if(working) { for(i = lp->rows+1; i <= lp->sum; i++) if(fabs(unscaled_value(lp, lp->upbo[i], i) - 1) < lp->epsvalue) n++; } else { for(i = 1; i <= lp->columns; i++) if((fabs(get_upbo(lp, i) - 1) < lp->epsvalue) && (fabs(get_lowbo(lp, i) - 0) < lp->epsvalue)) n++; } return( n ); } STATIC int SOS_count(lprec *lp) { if(lp->SOS == NULL) return( 0 ); else return( lp->SOS->sos_count ); } STATIC int GUB_count(lprec *lp) { if(lp->GUB == NULL) return( 0 ); else return( lp->GUB->sos_count ); } STATIC REAL compute_violation(lprec *lp, int row_nr) /* Returns the bound violation of a given basic variable; the return value is negative if it is below is lower bound, it is positive if it is greater than the upper bound, and zero otherwise. */ { REAL value, test; value = lp->rhs[row_nr]; row_nr = lp->var_basic[row_nr]; test = value - my_lowbound(lp->lowbo[row_nr]); my_roundzero(test, lp->epsprimal); if(test > 0) { test = value - lp->upbo[row_nr]; my_roundzero(test, lp->epsprimal); if(test < 0) test = 0; } return( test ); } STATIC REAL feasibilityOffset(lprec *lp, MYBOOL isdual) { int i, j; REAL f, Extra; Extra = 0; if(isdual) { /* This section computes a OF offset to ensure that the dual phase 1 is feasible. It is used to compute a primal feasible base that can be passed to the primal simplex in phase 2. */ #if 0 /* This is the legacy (v3.2-) P1extraVal logic that sets Extra to be the smallest negative reduced cost. Note that the reduced costs are the values of the dual slacks, which are [0..Inf> for feasibility. If we have negative reduced costs for bounded non-basic variables, we can simply switch the bound to obtain feasibility and possibly avoid having to set Extra. */ if(!isDualFeasible(lp, lp->epsprimal, NULL, NULL, &f) Extra = f; #else /* Find the most negative of the objective coefficients. We will subtract this value from every element of the objective row, making it non-negative and the problem therefore dual feasible. */ for(i = 1; i <= lp->columns; i++) { f = lp->orig_obj[i]; if(f < Extra) Extra = f; } #endif } else { /* Set Extra to be the index of the most negative of the net RHS coefficients; this approach can be used in the primal phase 1 followed by the dual phase 2 and when there are no ranged constraints. When there are ranged constraints, additional artificial variables must be introduced. */ Extra = 0; j = 0; Extra = lp->infinite; for(i = 1; i <= lp->rows; i++) { f = lp->rhs[i]; if(f < Extra) { Extra = f; j = i; } } Extra = j; } return(Extra); } STATIC REAL compute_dualslacks(lprec *lp, int target, REAL **dvalues, int **nzdvalues, MYBOOL dosum) /* Note that this function is similar to the compute_reducedcosts function in lp_price.c */ { int i, varnr, *coltarget, **nzduals, *nzvtemp = NULL; REAL d, g = 0, **duals, *vtemp = NULL; MYBOOL localREAL = (MYBOOL) (dvalues == NULL), localINT = (MYBOOL) (nzdvalues == NULL); if(is_action(lp->spx_action, ACTION_REBASE) || is_action(lp->spx_action, ACTION_REINVERT) || !lp->basis_valid) return( g ); /* Initialize */ if(!localREAL) { duals = dvalues; nzduals = nzdvalues; } else { duals = &vtemp; nzduals = &nzvtemp; } if(localINT || (*nzduals == NULL)) allocINT(lp, nzduals, lp->columns + 1, AUTOMATIC); if(localREAL || (*duals == NULL)) allocREAL(lp, duals, lp->sum + 1, AUTOMATIC); if(target == 0) target = SCAN_ALLVARS+ USE_NONBASICVARS; /* Define variable target list and compute the reduced costs */ coltarget = (int *) mempool_obtainVector(lp->workarrays, lp->columns+1, sizeof(*coltarget)); if(!get_colIndexA(lp, target, coltarget, FALSE)) { mempool_releaseVector(lp->workarrays, (char *) coltarget, FALSE); return(FALSE); } bsolve(lp, 0, *duals, NULL, lp->epsmachine*DOUBLEROUND, 1.0); prod_xA(lp, coltarget, *duals, NULL, lp->epsmachine, 1.0, *duals, *nzduals, MAT_ROUNDDEFAULT | MAT_ROUNDRC); mempool_releaseVector(lp->workarrays, (char *) coltarget, FALSE); /* Compute sum or maximum infeasibility as specified */ for(i = 1; i <= (*nzduals)[0]; i++) { varnr = (*nzduals)[i]; d = my_chsign(!lp->is_lower[varnr], (*duals)[varnr]); if(d < 0) { if(dosum) g += -d; /* Compute sum as a positive number */ else { SETMIN(g, d); /* Compute gap as a negative number */ } } } /* Clean up */ if(localREAL) FREE(*duals); if(localINT) FREE(*nzduals); return( g ); } STATIC REAL compute_feasibilitygap(lprec *lp, MYBOOL isdual, MYBOOL dosum) { REAL f = 0; /* This computes the primal feasibility gap (for use with the dual simplex phase 1) */ if(isdual) { int i; REAL g; for(i = 1; i <= lp->rows; i++) { if(lp->rhs[i] < 0) g = lp->rhs[i]; else if(lp->rhs[i] > lp->upbo[lp->var_basic[i]]) g = lp->rhs[i] - lp->upbo[lp->var_basic[i]]; else g = 0; if(dosum) f += g; else { SETMAX(f, g); } } } /* This computes the dual feasibility gap (for use with the primal simplex phase 1) */ else f = compute_dualslacks(lp, SCAN_USERVARS+USE_ALLVARS, NULL, NULL, dosum); return( f ); } /* Find the smallest fractional value in a given row of the OF/constraint matrix */ STATIC int row_decimals(lprec *lp, int rownr, MYBOOL intsonly, REAL *intscalar) { int basi, i, j, ncols = lp->columns; REAL f, /* g, */ epsvalue = lp->epsprimal; basi = 0; for(j = 1; j <= ncols; j++) { if(intsonly && !is_int(lp, j)) { if(intsonly == TRUE) break; else continue; } f = fabs(get_mat(lp, rownr, j)); /* f = fmod(f, 1); */ f -= floor (f + epsvalue); /* if(f <= epsvalue) continue; g = f; */ for(i = 0; (i <= MAX_FRACSCALE) && (/* g */ f > epsvalue); i++) { f *= 10; /* g = fmod(f, 1); */ f -= floor (f + epsvalue); } if(i > MAX_FRACSCALE) /* i = MAX_FRACSCALE */ break; SETMAX(basi, i); } if(j > ncols) *intscalar = pow(10.0, basi); else { basi = -1; *intscalar = 1; } return( basi ); } STATIC int row_intstats(lprec *lp, int rownr, int pivcolnr, int *maxndec, int *plucount, int *intcount, int *intval, REAL *valGCD, REAL *pivcolval) { int jb, je, jj, nn = 0, multA, multB, intGCD = 0; REAL rowval, inthold, intfrac; MATrec *mat = lp->matA; /* Do we have a valid matrix? */ if(mat_validate(mat)) { /* Get smallest fractional row value */ *maxndec = row_decimals(lp, rownr, AUTOMATIC, &intfrac); /* Get OF row starting and ending positions, as well as the first column index */ if(rownr == 0) { jb = 1; je = lp->columns+1; } else { jb = mat->row_end[rownr-1]; je = mat->row_end[rownr]; } nn = je - jb; *pivcolval = 1.0; *plucount = 0; *intcount = 0; *intval = 0; for(; jb < je; jb++) { if(rownr == 0) { if(lp->orig_obj[jb] == 0) { nn--; continue; } jj = jb; } else jj = ROW_MAT_COLNR(jb); /* Pick up the value of the pivot column and continue */ if(jj == pivcolnr) { if(rownr == 0) *pivcolval = unscaled_mat(lp, lp->orig_obj[jb], 0, jb); else *pivcolval = get_mat_byindex(lp, jb, TRUE, FALSE); continue; } if(!is_int(lp, jj)) continue; /* Update the count of integer columns */ (*intcount)++; /* Update the count of positive parameter values */ if(rownr == 0) rowval = unscaled_mat(lp, lp->orig_obj[jb], 0, jb); else rowval = get_mat_byindex(lp, jb, TRUE, FALSE); if(rowval > 0) (*plucount)++; /* Check if the parameter value is integer and update the row's GCD */ rowval = fabs(rowval) * intfrac; rowval += rowval*lp->epsmachine; rowval = modf(rowval, &inthold); if(rowval < lp->epsprimal) { (*intval)++; if(*intval == 1) intGCD = (int) inthold; else intGCD = gcd(intGCD, (LLONG) inthold, &multA, &multB); } } *valGCD = intGCD; *valGCD /= intfrac; } return(nn); } REAL MIP_stepOF(lprec *lp) /* This function tries to find a non-zero minimum improvement if the OF contains all integer variables (logic only applies if we are looking for a single solution, not possibly several equal-valued ones). */ { MYBOOL OFgcd; int colnr, rownr, n, ib, ie, maxndec, pluscount, intcount, intval; REAL value, valOF, divOF, valGCD; MATrec *mat = lp->matA; value = 0; if((lp->int_vars > 0) && (lp->solutionlimit == 1) && mat_validate(mat)) { /* Get statistics for integer OF variables and compute base stepsize */ n = row_intstats(lp, 0, -1, &maxndec, &pluscount, &intcount, &intval, &valGCD, &divOF); if((n == 0) || (maxndec < 0)) return( value ); OFgcd = (MYBOOL) (intval > 0); if(OFgcd) value = valGCD; /* Check non-ints in the OF to see if we can get more info */ if(n - intcount > 0) { int nrv = 0; /* See if we have equality constraints */ ie = lp->rows; for(ib = 1; ib <= ie; ib++) { if(is_constr_type(lp, ib, EQ)) break; } /* If so, there may be a chance to find an improved stepsize */ if(ib < ie) for(colnr = 1; colnr <= lp->columns; colnr++) { /* Go directly to the next variable if this is an integer or there is no row candidate to explore for hidden bounds for real-valued variables (limit scan to one row!) */ if(is_int(lp, colnr)) continue; nrv++; /* Scan equality constraints */ ib = mat->col_end[colnr-1]; ie = mat->col_end[colnr]; while(ib < ie) { if(is_constr_type(lp, (rownr = COL_MAT_ROWNR(ib)), EQ)) { /* Get "child" row statistics, but break out if we don't find enough information, i.e. no integers with coefficients of proper type */ n = row_intstats(lp, rownr, colnr, &maxndec, &pluscount, &intcount, &intval, &valGCD, &divOF); if((intval < n - 1) || (maxndec < 0)) { value = 0; break; } /* We can update */ valOF = unscaled_mat(lp, lp->orig_obj[colnr], 0, colnr); valOF = fabs( valOF * (valGCD / divOF) ); if(OFgcd) { SETMIN(value, valOF); } else { OFgcd = TRUE; value = valOF; } } ib++; } /* No point in continuing scan if we failed in current column */ if(value == 0) break; } /* Check if we found information for any real-valued variable; if not, then we must set the iprovement delta to 0 */ if(nrv == 0) value = 0; } } return( value ); } STATIC MYBOOL isPrimalSimplex(lprec *lp) { return((MYBOOL) (((lp->simplex_mode & SIMPLEX_Phase1_PRIMAL) != 0) || ((lp->simplex_mode & SIMPLEX_Phase2_PRIMAL) != 0))); } STATIC MYBOOL isPhase1(lprec *lp) { return((MYBOOL) (((lp->simplex_mode & SIMPLEX_Phase1_PRIMAL) != 0) || ((lp->simplex_mode & SIMPLEX_Phase1_DUAL) != 0))); } STATIC MYBOOL isP1extra(lprec *lp) { return((MYBOOL) ((lp->P1extraDim > 0) || (lp->P1extraVal != 0))); } STATIC MYBOOL feasiblePhase1(lprec *lp, REAL epsvalue) { REAL gap; MYBOOL test; gap = fabs(lp->rhs[0] - lp->orig_rhs[0]); test = (MYBOOL) (gap < epsvalue); return( test) ; } STATIC MYBOOL isDegenerateBasis(lprec *lp, int basisvar) { int varindex; varindex = lp->var_basic[basisvar]; if((fabs(lp->rhs[basisvar]) < lp->epsprimal) || (fabs(lp->upbo[varindex]-lp->rhs[basisvar]) < lp->epsprimal)) return( TRUE ); else return( FALSE ); } STATIC int findBasicFixedvar(lprec *lp, int afternr, MYBOOL slacksonly) { int varnr, delta = 1; if(afternr < 0) { delta = -1; afternr = -afternr; } afternr += delta; if((afternr < 1) || (afternr > lp->rows)) return( 0 ); for(; (afternr > 0) && (afternr <= lp->rows); afternr += delta) { varnr = lp->var_basic[afternr]; if(((varnr <= lp->rows) && is_constr_type(lp, varnr, EQ)) || (!slacksonly && (varnr > lp->rows) && is_fixedvar(lp, varnr))) break; } if(afternr > lp->rows) afternr = 0; return( afternr ); } STATIC MYBOOL isBasisVarFeasible(lprec *lp, REAL tol, int basis_row) { int col; REAL x; MYBOOL Ok = TRUE; MYBOOL doSC = FALSE; col = lp->var_basic[basis_row]; x = lp->rhs[basis_row]; /* The current solution of basic variables stored here! */ if((x < -tol) || (x > lp->upbo[col]+tol)) Ok = FALSE; else if(doSC && (col > lp->rows) && (fabs(lp->sc_lobound[col - lp->rows]) > 0)) { if((x > tol) && (x < fabs(lp->sc_lobound[col - lp->rows])-tol)) Ok = FALSE; } return( Ok ); } STATIC MYBOOL isPrimalFeasible(lprec *lp, REAL tol, int infeasibles[], REAL *feasibilitygap) { int i; MYBOOL feasible = TRUE; /* This is a short-hand call to rowdual() to check for primal infeasibility */ #if 0 /* Traditional indexing style */ for(i = 1; i <= lp->rows; i++) { feasible = isBasisVarFeasible(lp, tol, i); #else /* Fast array pointer style */ LREAL *rhsptr; int *idxptr; if(infeasibles != NULL) infeasibles[0] = 0; for(i = 1, rhsptr = lp->rhs+1, idxptr = lp->var_basic+1; (i <= lp->rows); i++, rhsptr++, idxptr++) { feasible = TRUE; /* if(((*rhsptr) < lp->lowbo[*idxptr]-tol) || ((*rhsptr) > lp->upbo[*idxptr]+tol)) */ if(((*rhsptr) < -tol) || ((*rhsptr) > lp->upbo[*idxptr]+tol)) feasible = FALSE; #endif if(!feasible) { if(infeasibles == NULL) break; infeasibles[0]++; infeasibles[infeasibles[0]] = i; } } /* Compute feasibility gap (could actually do this calculation above) */ if(feasibilitygap != NULL) { if(feasible) *feasibilitygap = 0.0; else *feasibilitygap = feasibilityOffset(lp, FALSE); } return(feasible); } STATIC MYBOOL isDualFeasible(lprec *lp, REAL tol, int *boundflipcount, int infeasibles[], REAL *feasibilitygap) { int i, varnr, n = 0, /* Number of infeasible duals corrected with bound-swaps */ m = 0, target = SCAN_ALLVARS+USE_NONBASICVARS; REAL f = 0; MYBOOL feasible, islower; /* The reduced costs are the values of the dual slacks, which are [0..Inf> for feasibility. If we have negative reduced costs for bounded non-basic variables, we can simply switch the bound of bounded variables to obtain dual feasibility and possibly avoid having to use dual simplex phase 1. */ if((infeasibles != NULL) || (boundflipcount != NULL)) { int *nzdcol = NULL; REAL d, *dcol = NULL; f = compute_dualslacks(lp, target, &dcol, &nzdcol, FALSE); if(nzdcol != NULL) for(i = 1; i <= nzdcol[0]; i++) { varnr = nzdcol[i]; islower = lp->is_lower[varnr]; d = my_chsign(!islower, dcol[varnr]); /* Don't bother with uninteresting non-basic variables */ if((d > -tol) || /* Positive reduced costs with a tolerance */ my_unbounded(lp, varnr) || /* Free variables cannot change bound */ is_fixedvar(lp, varnr)) /* Equality slack or a fixed variable ("type 3") */ continue; /* Check if we have non-flippable bounds, i.e. an unbounded variable (types 2+4), or bounded variables (type 3), and if the counter is NULL. */ if( (boundflipcount == NULL) || ((lp->bb_level <= 1) && (my_rangebo(lp, varnr) > fabs(lp->negrange))) || (islower && my_infinite(lp, lp->upbo[varnr])) || (!islower && my_infinite(lp, my_lowbo(lp, varnr))) ) { m++; if(infeasibles != NULL) infeasibles[m] = varnr; } /* Only do bound flips if the user-provided counter is non-NULL */ else { lp->is_lower[varnr] = !islower; n++; } } if(infeasibles != NULL) infeasibles[0] = m; FREE(dcol); FREE(nzdcol); if(n > 0) { set_action(&lp->spx_action, ACTION_RECOMPUTE); if(m == 0) f = 0; } } else f = compute_dualslacks(lp, target, NULL, NULL, FALSE); /* f = feasibilityOffset(lp, TRUE); */ /* Safe legacy mode */ /* Do an extra scan to see if there are bounded variables in the OF not present in any constraint; Most typically, presolve fixes such cases, so this is rarely encountered. */ varnr = lp->rows + 1; for(i = 1; i <= lp->columns; i++, varnr++) { islower = lp->is_lower[varnr]; if((my_chsign(islower, lp->orig_obj[i]) > 0) && (mat_collength(lp->matA, i) == 0) && !SOS_is_member(lp->SOS, 0, i)) { lp->is_lower[varnr] = !islower; if((islower && my_infinite(lp, lp->upbo[varnr])) || (!islower && my_infinite(lp, my_lowbo(lp, varnr)))) { lp->spx_status = UNBOUNDED; break; } n++; } } /* Return status */ if(boundflipcount != NULL) *boundflipcount = n; if(feasibilitygap != NULL) { my_roundzero(f, tol); *feasibilitygap = f; } feasible = (MYBOOL) ((f == 0) && (m == 0)); return(feasible); } void __WINAPI default_basis(lprec *lp) { int i; /* Set the slack variables to be basic; note that the is_basic[] array is a helper array filled in presolve() to match var_basic[]. */ for(i = 1; i <= lp->rows; i++) { lp->var_basic[i] = i; lp->is_basic[i] = TRUE; lp->is_lower[i] = TRUE; } lp->var_basic[0] = TRUE; /* Set to signal that this is the default basis */ /* Set user variables at their lower bound, including the dummy slack for the objective "constraint" */ for(; i <= lp->sum; i++) { lp->is_basic[i] = FALSE; lp->is_lower[i] = TRUE; } lp->is_lower[0] = TRUE; set_action(&lp->spx_action, ACTION_REBASE | ACTION_REINVERT | ACTION_RECOMPUTE); lp->basis_valid = TRUE; /* Do not re-initialize basis on entering Solve */ } int __WINAPI get_basiscrash(lprec *lp) { return(lp->crashmode); } void __WINAPI set_basiscrash(lprec *lp, int mode) { lp->crashmode = mode; } MYBOOL __WINAPI set_basis(lprec *lp, int *bascolumn, MYBOOL nonbasic) /* Added by KE */ { int i,s,k,n; /* Make sure we are consistent */ if(lp->wasPresolved && ((lp->rows != lp->presolve_undo->orig_rows) || (lp->columns != lp->presolve_undo->orig_columns))) return( FALSE ); /* Initialize (lp->is_basic is set in preprocess); Note that as of v5 and before it is an lp_solve convention that basic variables are at their lower bounds! This routine provides for the a possible future case that basic variables can be upper-bounded. */ lp->is_lower[0] = TRUE; for(i = 1; i <= lp->sum; i++) { lp->is_lower[i] = TRUE; lp->is_basic[i] = FALSE; } for(i = 1; i <= lp->rows; i++) lp->var_basic[i] = FALSE; /* Set basic and optionally non-basic variables; negative index means at lower bound, positive at upper bound */ if(nonbasic) n = lp->sum; else n = lp->rows; for(i = 1; i <= n; i++) { s = bascolumn[i]; k = abs(s); if(k <= 0 || k > lp->sum) return( FALSE ); if(i <= lp->rows) { lp->var_basic[i] = k; lp->is_basic[k] = TRUE; } else /* Remove this test if basic variables can be upper-bounded */ if(s > 0) lp->is_lower[k] = FALSE; } if(!verify_basis(lp)) return( FALSE ); /* Invalidate basis */ set_action(&lp->spx_action, ACTION_REBASE | ACTION_REINVERT | ACTION_RECOMPUTE); lp->basis_valid = TRUE; /* Do not re-initialize basis on entering Solve */ lp->var_basic[0] = FALSE; /* Set to signal that this is a non-default basis */ return( TRUE ); } void __WINAPI reset_basis(lprec *lp) { lp->basis_valid = FALSE; /* Causes reinversion at next opportunity */ } MYBOOL __WINAPI get_basis(lprec *lp, int *bascolumn, MYBOOL nonbasic) { int k, i; if(!lp->basis_valid || (lp->rows != lp->presolve_undo->orig_rows) || (lp->columns != lp->presolve_undo->orig_columns)) return( FALSE ); *bascolumn = 0; /* First save basic variable indexes */ for(i = 1; i <= lp->rows; i++) { k = lp->var_basic[i]; bascolumn[i] = my_chsign(lp->is_lower[k], k); } /* Then optionally save non-basic variable indeces */ if(nonbasic) { for(k = 1; (k <= lp->sum) && (i <= lp->sum); k++) { if(lp->is_basic[k]) continue; bascolumn[i] = my_chsign(lp->is_lower[k], k); i++; } } return( TRUE ); } STATIC MYBOOL is_BasisReady(lprec *lp) { return( (MYBOOL) (lp->var_basic[0] != AUTOMATIC) ); } STATIC MYBOOL is_slackbasis(lprec *lp) { int n = 0, err = 0; if(lp->basis_valid) { int i, k; MYBOOL *used = NULL; allocMYBOOL(lp, &used, lp->rows+1, TRUE); for(i = 1; i <= lp->rows; i++) { k = lp->var_basic[i]; if(k <= lp->rows) { if(used[k]) err++; else used[k] = TRUE; n++; } } FREE(used); if(err > 0) report(lp, SEVERE, "is_slackbasis: %d inconsistencies found in slack basis\n", err); } return( (MYBOOL) (n == lp->rows) ); } STATIC MYBOOL verify_basis(lprec *lp) { int i, ii, k = 0; MYBOOL result = FALSE; for(i = 1; i <= lp->rows; i++) { ii = lp->var_basic[i]; if((ii < 1) || (ii > lp->sum) || !lp->is_basic[ii]) { k = i; ii = 0; goto Done; } } ii = lp->rows; for(i = 1; i <= lp->sum; i++) { if(lp->is_basic[i]) ii--; } result = (MYBOOL) (ii == 0); Done: #if 0 /* For testing */ if(!result) ii = 0; #endif return(result); } int __WINAPI set_basisvar(lprec *lp, int basisPos, int enteringCol) { int leavingCol; leavingCol = lp->var_basic[basisPos]; #ifdef Paranoia if((basisPos < 1) || (basisPos > lp->rows)) report(lp, SEVERE, "set_basisvar: Invalid leaving basis position %d specified at iter %.0f\n", basisPos, (double) get_total_iter(lp)); if((leavingCol < 1) || (leavingCol > lp->sum)) report(lp, SEVERE, "set_basisvar: Invalid leaving column %d referenced at iter %.0f\n", leavingCol, (double) get_total_iter(lp)); if((enteringCol < 1) || (enteringCol > lp->sum)) report(lp, SEVERE, "set_basisvar: Invalid entering column %d specified at iter %.0f\n", enteringCol, (double) get_total_iter(lp)); #endif #ifdef ParanoiaXY if(!lp->is_basic[leavingCol]) report(lp, IMPORTANT, "set_basisvar: Leaving variable %d is not basic at iter %.0f\n", leavingCol, (double) get_total_iter(lp)); if(enteringCol > lp->rows && lp->is_basic[enteringCol]) report(lp, IMPORTANT, "set_basisvar: Entering variable %d is already basic at iter %.0f\n", enteringCol, (double) get_total_iter(lp)); #endif lp->var_basic[0] = FALSE; /* Set to signal that this is a non-default basis */ lp->var_basic[basisPos] = enteringCol; lp->is_basic[leavingCol] = FALSE; lp->is_basic[enteringCol] = TRUE; if(lp->bb_basis != NULL) lp->bb_basis->pivots++; return(leavingCol); } /* Bounds updating and unloading routines; requires that the current values for upbo and lowbo are in the original base. */ STATIC int perturb_bounds(lprec *lp, BBrec *perturbed, MYBOOL doRows, MYBOOL doCols, MYBOOL includeFIXED) { int i, ii, n = 0; REAL new_lb, new_ub, *upbo, *lowbo; if(perturbed == NULL) return( n ); /* Map reference bounds to previous state, i.e. cumulate perturbations in case of persistent problems */ upbo = perturbed->upbo; lowbo = perturbed->lowbo; /* Set appropriate target variable range */ i = 1; ii = lp->rows; if(!doRows) i += ii; if(!doCols) ii = lp->sum; /* Perturb (expand) finite variable bounds randomly */ for(; i <= ii; i++) { /* Don't perturb regular slack variables */ if((i <= lp->rows) && (lowbo[i] == 0) && (upbo[i] >= lp->infinite)) continue; new_lb = lowbo[i]; new_ub = upbo[i]; /* Don't perturb fixed variables if not specified */ if(!includeFIXED && (new_ub == new_lb)) continue; /* Lower bound for variables (consider implementing RHS here w/contentmode== AUTOMATIC) */ if((i > lp->rows) && (new_lb < lp->infinite)) { new_lb = rand_uniform(lp, RANDSCALE) + 1; new_lb *= lp->epsperturb; lowbo[i] -= new_lb; n++; } /* Upper bound */ if(new_ub < lp->infinite) { new_ub = rand_uniform(lp, RANDSCALE) + 1; new_ub *= lp->epsperturb; upbo[i] += new_ub; n++; } } /* Make sure we start from scratch */ set_action(&lp->spx_action, ACTION_REBASE); return( n ); } STATIC MYBOOL impose_bounds(lprec *lp, REAL *upbo, REAL *lowbo) /* Explicitly set working bounds to given vectors without pushing or popping */ { MYBOOL ok; ok = (MYBOOL) ((upbo != NULL) || (lowbo != NULL)); if(ok) { if((upbo != NULL) && (upbo != lp->upbo)) MEMCOPY(lp->upbo, upbo, lp->sum + 1); if((lowbo != NULL) && (lowbo != lp->lowbo)) MEMCOPY(lp->lowbo, lowbo, lp->sum + 1); if(lp->bb_bounds != NULL) lp->bb_bounds->UBzerobased = FALSE; set_action(&lp->spx_action, ACTION_REBASE); } set_action(&lp->spx_action, ACTION_RECOMPUTE); return( ok ); } STATIC MYBOOL validate_bounds(lprec *lp, REAL *upbo, REAL *lowbo) /* Check if all bounds are Explicitly set working bounds to given vectors without pushing or popping */ { MYBOOL ok; int i; ok = (MYBOOL) ((upbo != NULL) || (lowbo != NULL)); if(ok) { for(i = 1; i <= lp->sum; i++) if((lowbo[i] > upbo[i]) || (lowbo[i] < lp->orig_lowbo[i]) || (upbo[i] > lp->orig_upbo[i])) break; ok = (MYBOOL) (i > lp->sum); } return( ok ); } STATIC int unload_BB(lprec *lp) { int levelsunloaded = 0; if(lp->bb_bounds != NULL) while(pop_BB(lp->bb_bounds)) levelsunloaded++; return( levelsunloaded ); } #define LowerStorageModel 1 #define BasisStorageModel 1 STATIC basisrec *push_basis(lprec *lp, int *basisvar, MYBOOL *isbasic, MYBOOL *islower) /* Save the ingoing basis and push it onto the stack */ { int sum = lp->sum + 1; basisrec *newbasis = NULL; newbasis = (basisrec *) calloc(sizeof(*newbasis), 1); if((newbasis != NULL) && #if LowerStorageModel == 0 allocMYBOOL(lp, &newbasis->is_lower, sum, FALSE) && #else allocMYBOOL(lp, &newbasis->is_lower, (sum + 8) / 8, TRUE) && #endif #if BasisStorageModel == 0 allocMYBOOL(lp, &newbasis->is_basic, sum, FALSE) && #endif allocINT(lp, &newbasis->var_basic, lp->rows + 1, FALSE)) { if(islower == NULL) islower = lp->is_lower; if(isbasic == NULL) isbasic = lp->is_basic; if(basisvar == NULL) basisvar = lp->var_basic; #if LowerStorageModel == 0 MEMCOPY(newbasis->is_lower, islower, sum); #else for(sum = 1; sum <= lp->sum; sum++) if(islower[sum]) set_biton(newbasis->is_lower, sum); #endif #if BasisStorageModel == 0 MEMCOPY(newbasis->is_basic, isbasic, lp->sum + 1); #endif MEMCOPY(newbasis->var_basic, basisvar, lp->rows + 1); newbasis->previous = lp->bb_basis; if(lp->bb_basis == NULL) newbasis->level = 0; else newbasis->level = lp->bb_basis->level + 1; newbasis->pivots = 0; lp->bb_basis = newbasis; } return( newbasis ); } STATIC MYBOOL compare_basis(lprec *lp) /* Compares the last pushed basis with the currently active basis */ { int i, j; MYBOOL same_basis = TRUE; if(lp->bb_basis == NULL) return( FALSE ); /* Loop over basis variables until a mismatch (order can be different) */ i = 1; while(same_basis && (i <= lp->rows)) { j = 1; while(same_basis && (j <= lp->rows)) { same_basis = (MYBOOL) (lp->bb_basis->var_basic[i] != lp->var_basic[j]); j++; } same_basis = !same_basis; i++; } /* Loop over bound status indicators until a mismatch */ i = 1; while(same_basis && (i <= lp->sum)) { same_basis = (lp->bb_basis->is_lower[i] && lp->is_lower[i]); i++; } return( same_basis ); } STATIC MYBOOL restore_basis(lprec *lp) /* Restore values from the previously pushed / saved basis without popping it */ { MYBOOL ok; int i; ok = (MYBOOL) (lp->bb_basis != NULL); if(ok) { MEMCOPY(lp->var_basic, lp->bb_basis->var_basic, lp->rows + 1); #if BasisStorageModel == 0 MEMCOPY(lp->is_basic, lp->bb_basis->is_basic, lp->sum + 1); #else MEMCLEAR(lp->is_basic, lp->sum + 1); for(i = 1; i <= lp->rows; i++) lp->is_basic[lp->var_basic[i]] = TRUE; #endif #if LowerStorageModel == 0 MEMCOPY(lp->is_lower, lp->bb_basis->is_lower, lp->sum + 1); #else for(i = 1; i <= lp->sum; i++) lp->is_lower[i] = is_biton(lp->bb_basis->is_lower, i); #endif set_action(&lp->spx_action, ACTION_REBASE | ACTION_REINVERT); } return( ok ); } STATIC MYBOOL pop_basis(lprec *lp, MYBOOL restore) /* Pop / free, and optionally restore the previously "pushed" / saved basis */ { MYBOOL ok; basisrec *oldbasis; ok = (MYBOOL) (lp->bb_basis != NULL); if(ok) { oldbasis = lp->bb_basis; if(oldbasis != NULL) { lp->bb_basis = oldbasis->previous; FREE(oldbasis->var_basic); #if BasisStorageModel == 0 FREE(oldbasis->is_basic); #endif FREE(oldbasis->is_lower); FREE(oldbasis); } if(restore && (lp->bb_basis != NULL)) restore_basis(lp); } return( ok ); } STATIC int unload_basis(lprec *lp, MYBOOL restorelast) { int levelsunloaded = 0; if(lp->bb_basis != NULL) while(pop_basis(lp, restorelast)) levelsunloaded++; return( levelsunloaded ); } STATIC REAL scaled_floor(lprec *lp, int colnr, REAL value, REAL epsscale) { value = floor(value); if(value != 0) if(lp->columns_scaled && is_integerscaling(lp)) { value = scaled_value(lp, value, colnr); if(epsscale != 0) value += epsscale*lp->epsmachine; /* value += epsscale*lp->epsprimal; */ /* value = restoreINT(value, lp->epsint); */ } return(value); } STATIC REAL scaled_ceil(lprec *lp, int colnr, REAL value, REAL epsscale) { value = ceil(value); if(value != 0) if(lp->columns_scaled && is_integerscaling(lp)) { value = scaled_value(lp, value, colnr); if(epsscale != 0) value -= epsscale*lp->epsmachine; /* value -= epsscale*lp->epsprimal; */ /* value = restoreINT(value, lp->epsint); */ } return(value); } /* Branch and bound variable selection functions */ STATIC MYBOOL is_sc_violated(lprec *lp, int column) { int varno; REAL tmpreal; varno = lp->rows+column; tmpreal = unscaled_value(lp, lp->sc_lobound[column], varno); return( (MYBOOL) ((tmpreal > 0) && /* it is an (inactive) SC variable... */ (lp->solution[varno] < tmpreal) && /* ...and the NZ lower bound is violated */ (lp->solution[varno] > 0)) ); /* ...and the Z lowerbound is violated */ } STATIC int find_sc_bbvar(lprec *lp, int *count) { int i, ii, n, bestvar; int firstsc, lastsc; REAL hold, holdINT, bestval, OFval, randval, scval; MYBOOL reversemode, greedymode, randomizemode, pseudocostmode, pseudocostsel; bestvar = 0; if((lp->sc_vars == 0) || (*count > 0)) return(bestvar); reversemode = is_bb_mode(lp, NODE_WEIGHTREVERSEMODE); greedymode = is_bb_mode(lp, NODE_GREEDYMODE); randomizemode = is_bb_mode(lp, NODE_RANDOMIZEMODE); pseudocostmode = is_bb_mode(lp, NODE_PSEUDOCOSTMODE); pseudocostsel = is_bb_rule(lp, NODE_PSEUDOCOSTSELECT) || is_bb_rule(lp, NODE_PSEUDONONINTSELECT) || is_bb_rule(lp, NODE_PSEUDORATIOSELECT); bestvar = 0; bestval = -lp->infinite; hold = 0; randval = 1; firstsc = 0; lastsc = lp->columns; for(n = 1; n <= lp->columns; n++) { ii = get_var_priority(lp, n); i = lp->rows + ii; if(!lp->bb_varactive[ii] && is_sc_violated(lp, ii) && !SOS_is_marked(lp->SOS, 0, ii)) { /* Do tallies */ (*count)++; lastsc = i; if(firstsc <= 0) firstsc = i; scval = get_pseudorange(lp->bb_PseudoCost, ii, BB_SC); /* Select default pricing/weighting mode */ if(pseudocostmode) OFval = get_pseudonodecost(lp->bb_PseudoCost, ii, BB_SC, lp->solution[i]); else OFval = my_chsign(is_maxim(lp), get_mat(lp, 0, ii)); if(randomizemode) randval = exp(rand_uniform(lp, 1.0)); /* Find the maximum pseudo-cost of a variable (don't apply pseudocostmode here) */ if(pseudocostsel) { if(pseudocostmode) hold = OFval; else hold = get_pseudonodecost(lp->bb_PseudoCost, ii, BB_SC, lp->solution[i]); hold *= randval; if(greedymode) { if(pseudocostmode) /* Override! */ OFval = my_chsign(is_maxim(lp), get_mat(lp, 0, ii)); hold *= OFval; } hold = my_chsign(reversemode, hold); } else /* Find the variable with the largest sc gap (closest to the sc mean) */ if(is_bb_rule(lp, NODE_FRACTIONSELECT)) { hold = modf(lp->solution[i]/scval, &holdINT); holdINT = hold-1; if(fabs(holdINT) > hold) hold = holdINT; if(greedymode) hold *= OFval; hold = my_chsign(reversemode, hold)*scval*randval; } else /* Do first or last violated sc index selection (default) */ /* if(is_bb_rule(lp, NODE_FIRSTSELECT)) */ { if(reversemode) continue; else { bestvar = i; break; } } /* Select better, check for ties, and split by proximity to 0.5*sc_lobound */ if(hold > bestval) { if( (bestvar == 0) || (hold > bestval+lp->epsprimal) || (fabs(modf(lp->solution[i]/scval, &holdINT) - 0.5) < fabs(modf(lp->solution[bestvar]/ get_pseudorange(lp->bb_PseudoCost, bestvar-lp->rows, BB_SC), &holdINT) - 0.5)) ) { bestval = hold; bestvar = i; } } } } if(is_bb_rule(lp, NODE_FIRSTSELECT) && reversemode) bestvar = lastsc; return(bestvar); } STATIC int find_sos_bbvar(lprec *lp, int *count, MYBOOL intsos) { int k, i, j, var; var = 0; if((lp->SOS == NULL) || (*count > 0)) return(var); /* Check if the SOS'es happen to already be satisified */ i = SOS_is_satisfied(lp->SOS, 0, lp->solution); if((i == SOS_COMPLETE) || (i == SOS_INCOMPLETE)) return(-1); /* Otherwise identify a SOS variable to enter B&B */ for(k = 0; k < lp->sos_vars; k++) { i = lp->sos_priority[k]; #ifdef Paranoia if((i < 1) || (i > lp->columns)) report(lp, SEVERE, "find_sos_bbvar: Invalid SOS variable map %d at %d\n", i, k); #endif j = lp->rows + i; if(!SOS_is_marked(lp->SOS, 0, i) && !SOS_is_full(lp->SOS, 0, i, FALSE)) { /* if(!SOS_is_marked(lp->SOS, 0, i) && !SOS_is_full(lp->SOS, 0, i, TRUE)) { */ if(!intsos || is_int(lp, i)) { (*count)++; if(var == 0) { var = j; break; } } } } #ifdef Paranoia if((var > 0) && !SOS_is_member(lp->SOS, 0, var-lp->rows)) report(lp, SEVERE, "find_sos_bbvar: Found variable %d, which is not a SOS!\n", var); #endif return(var); } STATIC int find_int_bbvar(lprec *lp, int *count, BBrec *BB, MYBOOL *isfeasible) { int i, ii, n, k, bestvar, depthmax, *nonint = NULL; REAL hold, holdINT, bestval, OFval, randval, *lowbo = BB->lowbo, *upbo = BB->upbo; MYBOOL reversemode, greedymode, depthfirstmode, breadthfirstmode, randomizemode, rcostmode, pseudocostmode, pseudocostsel, pseudostrong, isINT, valINT; if((lp->int_vars == 0) || (*count > 0)) return( 0 ); if(lp->bb_usenode != NULL) { i = lp->bb_usenode(lp, lp->bb_nodehandle, BB_INT); if(i >= 0) { if(i > 0) (*count)++; return( i ); } } reversemode = is_bb_mode(lp, NODE_WEIGHTREVERSEMODE); greedymode = is_bb_mode(lp, NODE_GREEDYMODE); randomizemode = is_bb_mode(lp, NODE_RANDOMIZEMODE); depthfirstmode = is_bb_mode(lp, NODE_DEPTHFIRSTMODE); breadthfirstmode = is_bb_mode(lp, NODE_BREADTHFIRSTMODE) && (MYBOOL) (lp->bb_level <= lp->int_vars); rcostmode = (MYBOOL) /* FALSE */ (BB->lp->solutioncount > 0) && is_bb_mode(lp, NODE_RCOSTFIXING) ; /* 5/2/08 peno disabled NODE_RCOSTFIXING because it results in non-optimal solutions with some models */ /* 15/2/8 peno enabled NODE_RCOSTFIXING again because a fix is found. See lp_simplex.c NODE__RCOSTFIXING fix */ pseudocostmode = is_bb_mode(lp, NODE_PSEUDOCOSTMODE); pseudocostsel = is_bb_rule(lp, NODE_PSEUDOCOSTSELECT) || is_bb_rule(lp, NODE_PSEUDONONINTSELECT) || is_bb_rule(lp, NODE_PSEUDORATIOSELECT); pseudostrong = FALSE && pseudocostsel && !rcostmode && is_bb_mode(lp, NODE_STRONGINIT); /* Fill list of non-ints */ allocINT(lp, &nonint, lp->columns + 1, FALSE); n = 0; depthmax = -1; if(isfeasible != NULL) *isfeasible = TRUE; BB->lastrcf = 0; for(k = 1; (k <= lp->columns); k++) { ii = get_var_priority(lp, k); isINT = is_int(lp,ii); i = lp->rows + ii; /* Tally reduced cost fixing opportunities for ranged non-basic nonINTs */ if(!isINT) { #ifdef UseMilpExpandedRCF if(rcostmode) { bestvar = rcfbound_BB(BB, i, isINT, NULL, isfeasible); if(bestvar != FR) BB->lastrcf++; } #endif } else { valINT = solution_is_int(lp, i, FALSE); /* Skip already fixed variables */ if(lowbo[i] == upbo[i]) { /* Check for validity */ #ifdef Paranoia if(!valINT) { report(lp, IMPORTANT, "find_int_bbvar: INT var %d was fixed at %d, but computed as %g at node %.0f\n", ii, (int) lowbo[i], lp->solution[i], (double) lp->bb_totalnodes); lp->bb_break = TRUE; lp->spx_status = UNKNOWNERROR; bestvar = 0; goto Done; } #endif } /* The variable has not yet been fixed */ else { /* Tally reduced cost fixing opportunities (also when the variables are integer-valued at the current relaxation) */ if(rcostmode) { bestvar = rcfbound_BB(BB, i, isINT, NULL, isfeasible); if(bestvar != FR) BB->lastrcf++; } else bestvar = FR; /* Only qualify variable as branching node if it is non-integer and it will not be subsequently fixed via reduced cost fixing logic */ if(!valINT && (bestvar >= FR)) { n++; nonint[n] = ii; SETMAX(depthmax, lp->bb_varactive[ii]); } } } } #ifdef UseMilpSlacksRCF /* Optionally also tally slacks */ if(rcostmode) { for(i = 1; (i <= lp->rows) && (BB->lastrcf == 0); i++) { /* Skip already fixed slacks (equalities) */ if(lowbo[i] < upbo[i]) { bestvar = rcfbound_BB(BB, i, FALSE, NULL, isfeasible); if(bestvar != FR) BB->lastrcf++; } } } #endif nonint[0] = n; *count = n; bestvar = 0; if(n == 0) /* No non-integers found */ goto Done; bestval = -lp->infinite; hold = 0; randval = 1; /* Sort non-ints by depth in case we have breadthfirst or depthfirst modes */ if((lp->bb_level > 1) && (depthmax > 0) && (depthfirstmode || breadthfirstmode)) { int *depths = NULL; /* Fill attribute array and make sure ordinal order breaks ties during sort */ allocINT(lp, &depths, n + 1, FALSE); for(i = 1; i <= n; i++) depths[i] = (depthfirstmode ? n+1-i : i) + (n+1)*lp->bb_varactive[nonint[i]]; hpsortex(depths, n, 1, sizeof(*nonint), depthfirstmode, compareINT, nonint); FREE(depths); } /* Do simple firstselect handling */ if(is_bb_rule(lp, NODE_FIRSTSELECT)) { if(reversemode) bestvar = lp->rows + nonint[nonint[0]]; else bestvar = lp->rows + nonint[1]; } else for(n = 1; n <= nonint[0]; n++) { ii = nonint[n]; i = lp->rows + ii; /* Do the naive detection */ if(n == 1) bestvar = i; /* Should we do a "strong" pseudo-cost initialization or an incremental update? */ if(pseudostrong && (MAX(lp->bb_PseudoCost->LOcost[ii].rownr, lp->bb_PseudoCost->UPcost[ii].rownr) < lp->bb_PseudoCost->updatelimit) && (MAX(lp->bb_PseudoCost->LOcost[ii].colnr, lp->bb_PseudoCost->UPcost[ii].colnr) < 5*lp->bb_PseudoCost->updatelimit)) { strongbranch_BB(lp, BB, ii, BB_INT, nonint[0]); } /* Select default pricing/weighting mode */ if(pseudocostmode) OFval = get_pseudonodecost(lp->bb_PseudoCost, ii, BB_INT, lp->solution[i]); else OFval = my_chsign(is_maxim(lp), get_mat(lp, 0, ii)); if(randomizemode) randval = exp(rand_uniform(lp, 1.0)); /* Find the maximum pseudo-cost of a variable (don't apply pseudocostmode here) */ if(pseudocostsel) { if(pseudocostmode) hold = OFval; else hold = get_pseudonodecost(lp->bb_PseudoCost, ii, BB_INT, lp->solution[i]); hold *= randval; if(greedymode) { if(pseudocostmode) /* Override! */ OFval = my_chsign(is_maxim(lp), get_mat(lp, 0, ii)); hold *= OFval; } hold = my_chsign(reversemode, hold); } else /* Find the variable with the largest gap to its bounds (distance from being fixed) */ if(is_bb_rule(lp, NODE_GAPSELECT)) { hold = lp->solution[i]; holdINT = hold-unscaled_value(lp, upbo[i], i); hold -= unscaled_value(lp, lowbo[i], i); if(fabs(holdINT) > hold) hold = holdINT; if(greedymode) hold *= OFval; hold = my_chsign(reversemode, hold)*randval; } else /* Find the variable with the largest integer gap (closest to 0.5) */ if(is_bb_rule(lp, NODE_FRACTIONSELECT)) { hold = modf(lp->solution[i], &holdINT); holdINT = hold-1; if(fabs(holdINT) > hold) hold = holdINT; if(greedymode) hold *= OFval; hold = my_chsign(reversemode, hold)*randval; } else /* Find the "range", most flexible variable */ if(is_bb_rule(lp, NODE_RANGESELECT)) { hold = unscaled_value(lp, upbo[i]-lowbo[i], i); if(greedymode) hold *= OFval; hold = my_chsign(reversemode, hold)*randval; } /* Select better, check for ties, and split by proximity to 0.5 */ if(hold > bestval) { if( (hold > bestval+lp->epsprimal) || (fabs(modf(lp->solution[i], &holdINT) - 0.5) < fabs(modf(lp->solution[bestvar], &holdINT) - 0.5)) ) { bestval = hold; bestvar = i; } } } Done: FREE(nonint); return(bestvar); } STATIC BBPSrec *init_pseudocost(lprec *lp, int pseudotype) { int i; REAL PSinitUP, PSinitLO; BBPSrec *newitem; MYBOOL isPSCount; /* Allocate memory */ newitem = (BBPSrec*) malloc(sizeof(*newitem)); newitem->lp = lp; newitem->LOcost = (MATitem*) malloc((lp->columns+1) * sizeof(*newitem->LOcost)); newitem->UPcost = (MATitem*) malloc((lp->columns+1) * sizeof(*newitem->UPcost)); newitem->secondary = NULL; /* Initialize with OF values */ newitem->pseodotype = (pseudotype & NODE_STRATEGYMASK); isPSCount = ((pseudotype & NODE_PSEUDONONINTSELECT) != 0); for(i = 1; i <= lp->columns; i++) { newitem->LOcost[i].rownr = 1; /* Actual updates */ newitem->LOcost[i].colnr = 1; /* Attempted updates */ newitem->UPcost[i].rownr = 1; newitem->UPcost[i].colnr = 1; /* Initialize with the plain OF value as conventional usage suggests, or override in case of pseudo-nonint count strategy */ PSinitUP = my_chsign(is_maxim(lp), get_mat(lp, 0, i)); PSinitLO = -PSinitUP; if(isPSCount) { /* Set default assumed reduction in the number of non-ints by choosing this variable; KE changed from 0 on 30 June 2004 and made two-sided selectable. Note that the typical value range is <0..1>, with a positive bias for an "a priori" assumed fast-converging (low "MIP-complexity") model. Very hard models may require negative initialized values for one or both. */ PSinitUP = 0.1*0; #if 0 PSinitUP = my_chsign(PSinitUP < 0, PSinitUP); PSinitLO = -PSinitUP; #else PSinitLO = PSinitUP; #endif } newitem->UPcost[i].value = PSinitUP; newitem->LOcost[i].value = PSinitLO; } newitem->updatelimit = lp->bb_PseudoUpdates; newitem->updatesfinished = 0; newitem->restartlimit = DEF_PSEUDOCOSTRESTART; /* Let the user get an opportunity to initialize pseudocosts */ if(userabort(lp, MSG_INITPSEUDOCOST)) lp->spx_status = USERABORT; return( newitem ); } STATIC MYBOOL free_pseudoclass(BBPSrec **PseudoClass) { BBPSrec *target = *PseudoClass; FREE(target->LOcost); FREE(target->UPcost); target = target->secondary; FREE(*PseudoClass); *PseudoClass = target; return( (MYBOOL) (target != NULL) ); } STATIC void free_pseudocost(lprec *lp) { if((lp != NULL) && (lp->bb_PseudoCost != NULL)) { while(free_pseudoclass(&(lp->bb_PseudoCost)) ); } } MYBOOL __WINAPI set_pseudocosts(lprec *lp, REAL *clower, REAL *cupper, int *updatelimit) { int i; if((lp->bb_PseudoCost == NULL) || ((clower == NULL) && (cupper == NULL))) return(FALSE); for(i = 1; i <= lp->columns; i++) { if(clower != NULL) lp->bb_PseudoCost->LOcost[i].value = clower[i]; if(cupper != NULL) lp->bb_PseudoCost->UPcost[i].value = cupper[i]; } if(updatelimit != NULL) lp->bb_PseudoCost->updatelimit = *updatelimit; return(TRUE); } MYBOOL __WINAPI get_pseudocosts(lprec *lp, REAL *clower, REAL *cupper, int *updatelimit) { int i; if((lp->bb_PseudoCost == NULL) || ((clower == NULL) && (cupper == NULL))) return(FALSE); for(i = 1; i <= lp->columns; i++) { if(clower != NULL) clower[i] = lp->bb_PseudoCost->LOcost[i].value; if(cupper != NULL) cupper[i] = lp->bb_PseudoCost->UPcost[i].value; } if(updatelimit != NULL) *updatelimit = lp->bb_PseudoCost->updatelimit; return(TRUE); } STATIC REAL get_pseudorange(BBPSrec *pc, int mipvar, int varcode) { if(varcode == BB_SC) return( unscaled_value(pc->lp, pc->lp->sc_lobound[mipvar], pc->lp->rows+mipvar) ); else return( 1.0 ); } STATIC void update_pseudocost(BBPSrec *pc, int mipvar, int varcode, MYBOOL capupper, REAL varsol) { REAL OFsol, uplim; MATitem *PS; MYBOOL nonIntSelect = is_bb_rule(pc->lp, NODE_PSEUDONONINTSELECT); /* Establish input values; Note: The pseudocosts are normalized to the 0-1 range! */ uplim = get_pseudorange(pc, mipvar, varcode); varsol = modf(varsol/uplim, &OFsol); /* Set reference value according to pseudocost mode */ if(nonIntSelect) OFsol = pc->lp->bb_bounds->lastvarcus; /* The count of MIP infeasibilities */ else OFsol = pc->lp->solution[0]; /* The problem's objective function value */ if(isnan(varsol)) { pc->lp->bb_parentOF = OFsol; return; } /* Point to the applicable (lower or upper) bound and increment attempted update count */ if(capupper) { PS = &pc->LOcost[mipvar]; } else { PS = &pc->UPcost[mipvar]; varsol = 1-varsol; } PS->colnr++; /* Make adjustment to divisor if we are using the ratio pseudo-cost approach */ if(is_bb_rule(pc->lp, NODE_PSEUDORATIOSELECT)) varsol *= capupper; /* Compute the update (consider weighting in favor of most recent) */ mipvar = pc->updatelimit; if(((mipvar <= 0) || (PS->rownr < mipvar)) && (fabs(varsol) > pc->lp->epspivot)) { /* We are interested in the change in the MIP measure (contribution to increase or decrease, as the case may be) and not its last value alone. */ PS->value = PS->value*PS->rownr + (pc->lp->bb_parentOF-OFsol) / (varsol*uplim); PS->rownr++; PS->value /= PS->rownr; /* Check if we have enough information to restart */ if(PS->rownr == mipvar) { pc->updatesfinished++; if(is_bb_mode(pc->lp, NODE_RESTARTMODE) && (pc->updatesfinished/(2.0*pc->lp->int_vars) > pc->restartlimit)) { pc->lp->bb_break = AUTOMATIC; pc->restartlimit *= 2.681; /* KE: Who can figure this one out? */ if(pc->restartlimit > 1) pc->lp->bb_rule -= NODE_RESTARTMODE; report(pc->lp, NORMAL, "update_pseudocost: Restarting with updated pseudocosts\n"); } } } pc->lp->bb_parentOF = OFsol; } STATIC REAL get_pseudobranchcost(BBPSrec *pc, int mipvar, MYBOOL dofloor) { if(dofloor) return( pc->LOcost[mipvar].value ); else return( pc->UPcost[mipvar].value ); } STATIC REAL get_pseudonodecost(BBPSrec *pc, int mipvar, int vartype, REAL varsol) { REAL hold, uplim; uplim = get_pseudorange(pc, mipvar, vartype); varsol = modf(varsol/uplim, &hold); if(isnan(varsol)) varsol = 0; hold = pc->LOcost[mipvar].value*varsol + pc->UPcost[mipvar].value*(1-varsol); return( hold*uplim ); } STATIC int compute_theta(lprec *lp, int rownr, LREAL *theta, int isupbound, REAL HarrisScalar, MYBOOL primal) /* The purpose of this routine is to compute the non-basic bound state / value of the leaving variable. Note that the incoming theta is "d" in Chvatal-terminology */ { int colnr = lp->var_basic[rownr]; register LREAL x = lp->rhs[rownr]; REAL lb = 0, /* Put lower bound here when the fully bounded version is implemented */ ub = lp->upbo[colnr], eps = lp->epsprimal; /* Primal feasibility tolerance */ /* Compute theta for the primal simplex */ HarrisScalar *= eps; if(primal) { if(*theta > 0) x -= lb - HarrisScalar; /* A positive number */ else if(ub < lp->infinite) x -= ub + HarrisScalar; /* A negative number */ else { *theta = -lp->infinite; return( colnr ); } } /* Compute theta for the dual simplex */ else { if(isupbound) *theta = -(*theta); /* Current value is below or equal to its lower bound */ if(x < lb+eps) x -= lb - HarrisScalar; /* Current value is above or equal to its upper bound */ else if(x > ub-eps) { if(ub >= lp->infinite) { *theta = lp->infinite * my_sign(*theta); return( colnr ); } else x -= ub + HarrisScalar; } } my_roundzero(x, lp->epsmachine); *theta = x / *theta; #ifdef EnforcePositiveTheta /* Check if we have negative theta due to rounding or an internal error */ if(*theta < 0) { if(primal && (ub == lb)) lp->rhs[rownr] = lb; else #ifdef Paranoia if(*theta < -eps) { report(lp, DETAILED, "compute_theta: Negative theta (%g) not allowed in base-0 version of lp_solve\n", *theta); } #endif *theta = 0; } #endif return( colnr ); } STATIC MYBOOL check_degeneracy(lprec *lp, REAL *pcol, int *degencount) /* Check if the entering column Pi=Inv(B)*a is likely to produce improvement; (cfr. Istvan Maros: CTOTSM p. 233) */ { int i, ndegen; REAL *rhs, sdegen, epsmargin = lp->epsprimal; sdegen = 0; ndegen = 0; rhs = lp->rhs; for(i = 1; i <= lp->rows; i++) { rhs++; pcol++; if(fabs(*rhs) < epsmargin) { sdegen += *pcol; ndegen++; } else if(fabs((*rhs)-lp->upbo[lp->var_basic[i]]) < epsmargin) { sdegen -= *pcol; ndegen++; } } if(degencount != NULL) *degencount = ndegen; /* sdegen += epsmargin*ndegen; */ return( (MYBOOL) (sdegen <= 0) ); } STATIC MYBOOL performiteration(lprec *lp, int rownr, int varin, LREAL theta, MYBOOL primal, MYBOOL allowminit, REAL *prow, int *nzprow, REAL *pcol, int *nzpcol, int *boundswaps) { int varout; REAL pivot, epsmargin, leavingValue, leavingUB, enteringUB; MYBOOL leavingToUB = FALSE, enteringFromUB, enteringIsFixed, leavingIsFixed; MYBOOL *islower = &(lp->is_lower[varin]); MYBOOL minitNow = FALSE, minitStatus = ITERATE_MAJORMAJOR; LREAL deltatheta = theta; if(userabort(lp, MSG_ITERATION)) return( minitNow ); #ifdef Paranoia if(rownr > lp->rows) { if (lp->spx_trace) report(lp, IMPORTANT, "performiteration: Numeric instability encountered!\n"); lp->spx_status = NUMFAILURE; return( FALSE ); } #endif varout = lp->var_basic[rownr]; #ifdef Paranoia if(!lp->is_lower[varout]) report(lp, SEVERE, "performiteration: Leaving variable %d was at its upper bound at iter %.0f\n", varout, (double) get_total_iter(lp)); #endif /* Theta is the largest change possible (strictest constraint) for the entering variable (Theta is Chvatal's "t", ref. Linear Programming, pages 124 and 156) */ lp->current_iter++; /* Test if it is possible to do a cheap "minor iteration"; i.e. set entering variable to its opposite bound, without entering the basis - which is obviously not possible for fixed variables! */ epsmargin = lp->epsprimal; enteringFromUB = !(*islower); enteringUB = lp->upbo[varin]; leavingUB = lp->upbo[varout]; enteringIsFixed = (MYBOOL) (fabs(enteringUB) < epsmargin); leavingIsFixed = (MYBOOL) (fabs(leavingUB) < epsmargin); #if defined _PRICE_NOBOUNDFLIP allowminit &= !ISMASKSET(lp->piv_strategy, PRICE_NOBOUNDFLIP); #endif #ifdef Paranoia if(enteringUB < 0) report(lp, SEVERE, "performiteration: Negative range for entering variable %d at iter %.0f\n", varin, (double) get_total_iter(lp)); if(leavingUB < 0) report(lp, SEVERE, "performiteration: Negative range for leaving variable %d at iter %.0f\n", varout, (double) get_total_iter(lp)); #endif /* Handle batch bound swaps with the dual long-step algorithm; Loop over specified bound swaps; update RHS and Theta for bound swaps */ if((boundswaps != NULL) && (boundswaps[0] > 0)) { int i, boundvar; REAL *hold; /* Allocate and initialize accumulation array */ allocREAL(lp, &hold, lp->rows + 1, TRUE); /* Accumulate effective bound swaps and update flag */ for(i = 1; i <= boundswaps[0]; i++) { boundvar = boundswaps[i]; deltatheta = my_chsign(!lp->is_lower[boundvar], lp->upbo[boundvar]); mat_multadd(lp->matA, hold, boundvar, deltatheta); lp->is_lower[boundvar] = !lp->is_lower[boundvar]; } lp->current_bswap += boundswaps[0]; lp->current_iter += boundswaps[0]; /* Solve for bound flip update vector (note that this does not overwrite the stored update vector for the entering variable) */ ftran(lp, hold, NULL, lp->epsmachine); if(!lp->obj_in_basis) hold[0] = 0; /* The correct reduced cost goes here (adjusted for bound state) ****** */ /* Update the RHS / basic variable values and set revised thetas */ pivot = lp->bfp_pivotRHS(lp, 1, hold); deltatheta = multi_enteringtheta(lp->longsteps); theta = deltatheta; FREE(hold); } /* Otherwise to traditional check for single bound swap */ else if(allowminit && !enteringIsFixed) { /* pivot = epsmargin; */ pivot = lp->epsdual; /* #define v51mode */ /* Enable this for v5.1 operation mode */ #ifdef v51mode if(((lp->simplex_mode & SIMPLEX_Phase1_DUAL) == 0) || !is_constr_type(lp, rownr, EQ)) /* *** DEBUG CODE KE */ #endif if(enteringUB - theta < -pivot) { #ifndef v51mode if(fabs(enteringUB - theta) < pivot) minitStatus = ITERATE_MINORMAJOR; else #endif minitStatus = ITERATE_MINORRETRY; minitNow = (MYBOOL) (minitStatus != ITERATE_MAJORMAJOR); } } /* Process for traditional style single minor iteration */ if(minitNow) { /* Set the new values (note that theta is set to always be positive) */ theta = MIN(fabs(theta), enteringUB); /* Update the RHS / variable values and do bound-swap */ pivot = lp->bfp_pivotRHS(lp, theta, NULL); *islower = !(*islower); lp->current_bswap++; } /* Process for major iteration */ else { /* Update the active pricer for the current pivot */ updatePricer(lp, rownr, varin, lp->bfp_pivotvector(lp), prow, nzprow); /* Update the current basic variable values */ pivot = lp->bfp_pivotRHS(lp, theta, NULL); /* See if the leaving variable goes directly to its upper bound. */ leavingValue = lp->rhs[rownr]; leavingToUB = (MYBOOL) (leavingValue > 0.5*leavingUB); lp->is_lower[varout] = leavingIsFixed || !leavingToUB; /* Set the value of the entering varible (theta always set to be positive) */ if(enteringFromUB) { lp->rhs[rownr] = enteringUB - deltatheta; *islower = TRUE; } else lp->rhs[rownr] = deltatheta; my_roundzero(lp->rhs[rownr], epsmargin); /* Update basis indeces */ varout = set_basisvar(lp, rownr, varin); /* Finalize the update in preparation for next major iteration */ lp->bfp_finishupdate(lp, enteringFromUB); } /* Show pivot tracking information, if specified */ if((lp->verbose > NORMAL) && (MIP_count(lp) == 0) && ((lp->current_iter % MAX(2, lp->rows / 10)) == 0)) report(lp, NORMAL, "Objective value " RESULTVALUEMASK " at iter %10.0f.\n", lp->rhs[0], (double) get_total_iter(lp)); #if 0 if(verify_solution(lp, FALSE, my_if(minitNow, "MINOR", "MAJOR")) >= 0) { if(minitNow) pivot = get_obj_active(lp, varin); else pivot = get_obj_active(lp, varout); } #endif #if 0 if((lp->longsteps != NULL) && (boundswaps[0] > 0) && lp->longsteps->objcheck && ((pivot = fabs(my_reldiff(lp->rhs[0], lp->longsteps->obj_last))) > lp->epssolution)) { report(lp, IMPORTANT, "performiteration: Objective value gap %8.6f found at iter %6.0f (%d bound flips, %d)\n", pivot, (double) get_total_iter(lp), boundswaps[0], enteringFromUB); } #endif if(lp->spx_trace) { if(minitNow) report(lp, NORMAL, "I:%5.0f - minor - %5d ignored, %5d flips from %s with THETA=%g and OBJ=%g\n", (double) get_total_iter(lp), varout, varin, (enteringFromUB ? "UPPER" : "LOWER"), theta, lp->rhs[0]); else report(lp, NORMAL, "I:%5.0f - MAJOR - %5d leaves to %s, %5d enters from %s with THETA=%g and OBJ=%g\n", (double) get_total_iter(lp), varout, (leavingToUB ? "UPPER" : "LOWER"), varin, (enteringFromUB ? "UPPER" : "LOWER"), theta, lp->rhs[0]); if(minitNow) { if(!lp->is_lower[varin]) report(lp, DETAILED, "performiteration: Variable %d changed to its lower bound at iter %.0f (from %g)\n", varin, (double) get_total_iter(lp), enteringUB); else report(lp, DETAILED, "performiteration: Variable %d changed to its upper bound at iter %.0f (to %g)\n", varin, (double) get_total_iter(lp), enteringUB); } else report(lp, NORMAL, "performiteration: Variable %d entered basis at iter %.0f at " RESULTVALUEMASK "\n", varin, (double) get_total_iter(lp), lp->rhs[rownr]); if(!primal) { pivot = compute_feasibilitygap(lp, (MYBOOL)!primal, TRUE); report(lp, NORMAL, "performiteration: Feasibility gap at iter %.0f is " RESULTVALUEMASK "\n", (double) get_total_iter(lp), pivot); } else report(lp, NORMAL, "performiteration: Current objective function value at iter %.0f is " RESULTVALUEMASK "\n", (double) get_total_iter(lp), lp->rhs[0]); } return( minitStatus ); } /* performiteration */ STATIC REAL get_refactfrequency(lprec *lp, MYBOOL final) { COUNTER iters; int refacts; /* Get numerator and divisor information */ iters = (lp->total_iter+lp->current_iter) - (lp->total_bswap+lp->current_bswap); refacts = lp->bfp_refactcount(lp, BFP_STAT_REFACT_TOTAL); /* Return frequency for different cases: 1) Actual frequency in case final statistic is desired 2) Dummy if we are in a B&B process 3) Frequency with added initialization offsets which are diluted in course of the solution process */ if(final) return( (REAL) (iters) / MAX(1,refacts) ); else if(lp->bb_totalnodes > 0) return( (REAL) lp->bfp_pivotmax(lp) ); else return( (REAL) (lp->bfp_pivotmax(lp)+iters) / (1+refacts) ); } #if 0 /* INLINE */ MYBOOL is_fixedvar(lprec *lp, int variable) { if((lp->bb_bounds != NULL && lp->bb_bounds->UBzerobased) || (variable <= lp->rows)) return( (MYBOOL) (lp->upbo[variable] < lp->epsprimal) ); else return( (MYBOOL) (lp->upbo[variable]-lp->lowbo[variable] < lp->epsprimal) ); } /* is_fixedvar */ #else MYBOOL is_fixedvar(lprec *lp, int varnr) { if(lp->bb_bounds == NULL) { if(varnr <= lp->rows) return( (MYBOOL) (lp->orig_upbo[varnr] < lp->epsmachine) ); else return( (MYBOOL) (lp->orig_upbo[varnr]-lp->orig_lowbo[varnr] < lp->epsmachine) ); } else if((varnr <= lp->rows) || (lp->bb_bounds->UBzerobased == TRUE)) return( (MYBOOL) (lp->upbo[varnr] < lp->epsvalue) ); else return( (MYBOOL) (lp->upbo[varnr]-lp->lowbo[varnr] < lp->epsvalue) ); } #endif STATIC MYBOOL solution_is_int(lprec *lp, int index, MYBOOL checkfixed) { #if 1 return( (MYBOOL) (isINT(lp, lp->solution[index]) && (!checkfixed || is_fixedvar(lp, index))) ); #else if(isINT(lp, lp->solution[index])) { if(checkfixed) return(is_fixedvar(lp, index)); else return(TRUE); } return(FALSE); #endif } /* solution_is_int */ MYBOOL __WINAPI set_multiprice(lprec *lp, int multiblockdiv) { /* See if we are resetting multiply priced column structures */ if(multiblockdiv != lp->multiblockdiv) { if(multiblockdiv < 1) multiblockdiv = 1; lp->multiblockdiv = multiblockdiv; multi_free(&(lp->multivars)); } return( TRUE ); } int __WINAPI get_multiprice(lprec *lp, MYBOOL getabssize) { if((lp->multivars == NULL) || (lp->multivars->used == 0)) return( 0 ); if(getabssize) return( lp->multivars->size ); else return( lp->multiblockdiv ); } MYBOOL __WINAPI set_partialprice(lprec *lp, int blockcount, int *blockstart, MYBOOL isrow) { int ne, i, items; partialrec **blockdata; /* Determine partial target (rows or columns) */ if(isrow) blockdata = &(lp->rowblocks); else blockdata = &(lp->colblocks); /* See if we are resetting partial blocks */ ne = 0; items = IF(isrow, lp->rows, lp->columns); if(blockcount == 1) partial_freeBlocks(blockdata); /* Set a default block count if this was not specified */ else if(blockcount <= 0) { blockstart = NULL; if(items < DEF_PARTIALBLOCKS*DEF_PARTIALBLOCKS) blockcount = items / DEF_PARTIALBLOCKS + 1; else blockcount = DEF_PARTIALBLOCKS; ne = items / blockcount; if(ne * blockcount < items) ne++; } /* Fill partial block arrays; Note: These will be modified during preprocess to reflect presolved columns and the handling of slack variables. */ if(blockcount > 1) { MYBOOL isNew = (MYBOOL) (*blockdata == NULL); /* Provide for extra block with slack variables in the column mode */ i = 0; if(!isrow) i++; /* (Re)-allocate memory */ if(isNew) *blockdata = partial_createBlocks(lp, isrow); allocINT(lp, &((*blockdata)->blockend), blockcount+i+1, AUTOMATIC); allocINT(lp, &((*blockdata)->blockpos), blockcount+i+1, AUTOMATIC); /* Copy the user-provided block start positions */ if(blockstart != NULL) { MEMCOPY((*blockdata)->blockend+i, blockstart, blockcount+i+1); if(!isrow) { blockcount++; (*blockdata)->blockend[0] = 1; for(i = 1; i < blockcount; i++) (*blockdata)->blockend[i] += lp->rows; } } /* Fill the block ending positions if they were not specified */ else { (*blockdata)->blockend[0] = 1; (*blockdata)->blockpos[0] = 1; if(ne == 0) { ne = items / blockcount; /* Increase the block size if we have a fractional value */ while(ne * blockcount < items) ne++; } i = 1; if(!isrow) { (*blockdata)->blockend[i] = (*blockdata)->blockend[i-1]+lp->rows; blockcount++; i++; items += lp->rows; } for(; i < blockcount; i++) (*blockdata)->blockend[i] = (*blockdata)->blockend[i-1]+ne; /* Let the last block handle the "residual" */ (*blockdata)->blockend[blockcount] = items+1; } /* Fill starting positions (used in multiple partial pricing) */ for(i = 1; i <= blockcount; i++) (*blockdata)->blockpos[i] = (*blockdata)->blockend[i-1]; } /* Update block count */ (*blockdata)->blockcount = blockcount; return( TRUE ); } /* set_partialprice */ void __WINAPI get_partialprice(lprec *lp, int *blockcount, int *blockstart, MYBOOL isrow) { partialrec *blockdata; /* Determine partial target (rows or columns) */ if(isrow) blockdata = lp->rowblocks; else blockdata = lp->colblocks; *blockcount = partial_countBlocks(lp, isrow); if((blockdata != NULL) && (blockstart != NULL)) { int i = 0, k = *blockcount; if(!isrow) i++; MEMCOPY(blockstart, blockdata->blockend + i, k - i); if(!isrow) { k -= i; for(i = 0; i < k; i++) blockstart[i] -= lp->rows; } } } /* Solution-related functions */ STATIC MYBOOL bb_better(lprec *lp, int target, int mode) /* Must handle four modes (logic assumes Min!): -----|--.--|-----> 1 ++++++----------- LHS exclusive test point is better 2 +++++++++-------- LHS inclusive 3 ++++++-----++++++ LHS+RHS exclusive 4 --------+++++++++ RHS inclusive 5 -----------++++++ RHS exclusive */ { REAL epsvalue, offset = lp->epsprimal, refvalue = lp->infinite, testvalue = lp->solution[0]; MYBOOL ismax = is_maxim(lp), relgap = is_action(mode, OF_TEST_RELGAP), fcast = is_action(target, OF_PROJECTED), delta = is_action(target, OF_DELTA); if(relgap) { epsvalue = lp->mip_relgap; clear_action(&mode, OF_TEST_RELGAP); } else epsvalue = lp->mip_absgap; if(delta) clear_action(&target, OF_DELTA); if(fcast) clear_action(&target, OF_PROJECTED); #ifdef Paranoia if((mode < OF_TEST_BT) || (mode > OF_TEST_WT)) report(lp, SEVERE, "bb_better: Passed invalid mode '%d'\n", mode); #endif switch(target) { case OF_RELAXED: refvalue = lp->real_solution; break; case OF_INCUMBENT: refvalue = lp->best_solution[0]; break; case OF_WORKING: refvalue = my_chsign(!ismax, lp->bb_workOF /* unscaled_value(lp, lp->bb_workOF, 0) */ ); if(fcast) testvalue = my_chsign(!ismax, lp->longsteps->obj_last) - epsvalue; else testvalue = my_chsign(!ismax, lp->rhs[0] /* unscaled_value(lp, lp->rhs[0], 0) */); break; case OF_USERBREAK: refvalue = lp->bb_breakOF; break; case OF_HEURISTIC: refvalue = lp->bb_heuristicOF; break; case OF_DUALLIMIT: refvalue = lp->bb_limitOF; break; default : report(lp, SEVERE, "bb_better: Passed invalid test target '%d'\n", target); return( FALSE ); } /* Adjust the test value for the desired acceptability window */ if(delta) { SETMAX(epsvalue, lp->bb_deltaOF - epsvalue); } else epsvalue = my_chsign(target >= OF_USERBREAK, epsvalue); /* *** This seems Ok, but should be verified */ testvalue += my_chsign(ismax, epsvalue); /* Compute the raw test value */ if(relgap) testvalue = my_reldiff(testvalue, refvalue); else testvalue -= refvalue; /* Make test value adjustment based on the selected option */ if(mode == OF_TEST_NE) relgap = (MYBOOL) (fabs(testvalue) >= offset); else { testvalue = my_chsign(mode > OF_TEST_NE, testvalue); testvalue = my_chsign(ismax, testvalue); relgap = (MYBOOL) (testvalue < offset); } return( relgap ); } STATIC void construct_solution(lprec *lp, REAL *target) { int i, j, basi; REAL f, epsvalue = lp->epsprimal; REAL *solution; REAL *value; int *rownr; MATrec *mat = lp->matA; if(target == NULL) solution = lp->solution; else solution = target; /* Initialize OF and slack variables. */ for(i = 0; i <= lp->rows; i++) { #ifdef LegacySlackDefinition if(i == 0) f = unscaled_value(lp, -lp->orig_rhs[i], i); else { j = lp->presolve_undo->var_to_orig[i]; if(j > 0) { f = lp->presolve_undo->fixed_rhs[j]; f = unscaled_value(lp, f, i); } else f = 0; } #else f = lp->orig_rhs[i]; if((i > 0) && !lp->is_basic[i] && !lp->is_lower[i]) #ifdef SlackInitMinusInf f -= my_chsign(is_chsign(lp, i), fabs(lp->upbo[i])); #else f -= my_chsign(is_chsign(lp, i), fabs(lp->lowbo[i] + lp->upbo[i])); #endif f = unscaled_value(lp, -f, i); #endif solution[i] = f; } /* Initialize user variables to their lower bounds. */ for(i = lp->rows+1; i <= lp->sum; i++) solution[i] = lp->lowbo[i]; /* Add values of user basic variables. */ for(i = 1; i <= lp->rows; i++) { basi = lp->var_basic[i]; if(basi > lp->rows) { solution[basi] += lp->rhs[i]; } } /* 1. Adjust non-basic variables at their upper bounds, 2. Unscale all user variables, 3. Optionally do precision management. */ for(i = lp->rows + 1; i <= lp->sum; i++) { if(!lp->is_basic[i] && !lp->is_lower[i]) solution[i] += lp->upbo[i]; solution[i] = unscaled_value(lp, solution[i], i); #ifdef xImproveSolutionPrecision if(is_int(lp, i-lp->rows)) solution[i] = restoreINT(solution[i], lp->epsint); else solution[i] = restoreINT(solution[i], lp->epsprimal); #endif } /* Compute the OF and slack values "in extentio" */ for(j = 1; j <= lp->columns; j++) { f = solution[lp->rows + j]; if(f != 0) { solution[0] += f * unscaled_mat(lp, lp->orig_obj[j], 0, j); i = mat->col_end[j-1]; basi = mat->col_end[j]; rownr = &COL_MAT_ROWNR(i); value = &COL_MAT_VALUE(i); for(; i < basi; i++, rownr += matRowColStep, value += matValueStep) solution[*rownr] += f * unscaled_mat(lp, *value, *rownr, j); } } /* Do slack precision management and sign reversal if necessary */ for(i = 0; i <= lp->rows; i++) { #ifdef ImproveSolutionPrecision my_roundzero(solution[i], epsvalue); #endif if(is_chsign(lp, i)) solution[i] = my_flipsign(solution[i]); } /* Record the best real-valued solution and compute a simple MIP solution limit */ if(target == NULL) { if(is_infinite(lp, lp->real_solution)) { lp->bb_workOF = lp->rhs[0]; lp->real_solution = solution[0]; if(is_infinite(lp, lp->bb_limitOF)) lp->bb_limitOF = lp->real_solution; else { if(is_maxim(lp)) { SETMIN(lp->bb_limitOF, lp->real_solution); } else { SETMAX(lp->bb_limitOF, lp->real_solution); } } /* Do MIP-related tests and computations */ if((lp->int_vars > 0) && mat_validate(lp->matA) /* && !lp->wasPresolved */) { /* && !lp->wasPresolved uncommented by findings of William H. Patton. The code was never executed when the test was there. The code has effect in an integer model with all integer objective coeff. to cut-off optimization and thus make it faster */ REAL fixedOF = unscaled_value(lp, lp->orig_rhs[0], 0); /* Check if we have an all-integer OF */ basi = lp->columns; for(j = 1; j <= basi; j++) { f = fabs(get_mat(lp, 0, j)) + lp->epsint / 2; if(f > lp->epsint) { /* If coefficient is 0 then it doesn't influence OF, even it variable is not integer */ if(!is_int(lp, j) || (fmod(f, 1) > lp->epsint)) break; } } /* If so, we can round up the fractional OF */ if(j > basi) { f = my_chsign(is_maxim(lp), lp->real_solution) + fixedOF; f = floor(f+(1-epsvalue)); f = my_chsign(is_maxim(lp), f - fixedOF); if(is_infinite(lp, lp->bb_limitOF)) lp->bb_limitOF = f; else if(is_maxim(lp)) { SETMIN(lp->bb_limitOF, f); } else { SETMAX(lp->bb_limitOF, f); } } } /* Check that a user limit on the OF is feasible */ if((lp->int_vars > 0) && (my_chsign(is_maxim(lp), my_reldiff(lp->best_solution[0],lp->bb_limitOF)) < -epsvalue)) { lp->spx_status = INFEASIBLE; lp->bb_break = TRUE; } } } } /* construct_solution */ STATIC int check_solution(lprec *lp, int lastcolumn, REAL *solution, REAL *upbo, REAL *lowbo, REAL tolerance) { /*#define UseMaxValueInCheck*/ MYBOOL isSC; REAL test, value, hold, diff, maxdiff = 0.0, maxerr = 0.0, *matValue, #ifdef UseMaxValueInCheck *maxvalue = NULL, #else *plusum = NULL, *negsum = NULL; #endif int i,j,n, errlevel = IMPORTANT, errlimit = 10, *matRownr, *matColnr; MATrec *mat = lp->matA; report(lp, NORMAL, " \n"); if(MIP_count(lp) > 0) report(lp, NORMAL, "%s solution " RESULTVALUEMASK " after %10.0f iter, %9.0f nodes (gap %.1f%%).\n", my_if(lp->bb_break && !bb_better(lp, OF_DUALLIMIT, OF_TEST_BE) && bb_better(lp, OF_RELAXED, OF_TEST_NE), "Subopt.", "Optimal"), solution[0], (double) lp->total_iter, (double) lp->bb_totalnodes, 100.0*fabs(my_reldiff(lp->solution[0], lp->bb_limitOF))); else report(lp, NORMAL, "Optimal solution " RESULTVALUEMASK " after %10.0f iter.\n", solution[0], (double) lp->total_iter); /* Find the signed sums and the largest absolute product in the matrix (exclude the OF for speed) */ #ifdef UseMaxValueInCheck allocREAL(lp, &maxvalue, lp->rows + 1, FALSE); for(i = 0; i <= lp->rows; i++) maxvalue[i] = fabs(get_rh(lp, i)); #else allocREAL(lp, &plusum, lp->rows + 1, TRUE); allocREAL(lp, &negsum, lp->rows + 1, TRUE); #endif n = get_nonzeros(lp); matRownr = &COL_MAT_ROWNR(0); matColnr = &COL_MAT_COLNR(0); matValue = &COL_MAT_VALUE(0); for(i = 0; i < n; i++, matRownr += matRowColStep, matColnr += matRowColStep, matValue += matValueStep) { test = unscaled_mat(lp, *matValue, *matRownr, *matColnr); test *= solution[lp->rows + (*matColnr)]; #ifdef UseMaxValueInCheck test = fabs(test); if(test > maxvalue[*matRownr]) maxvalue[*matRownr] = test; #else if(test > 0) plusum[*matRownr] += test; else negsum[*matRownr] += test; #endif } /* Check if solution values are within the bounds; allowing a margin for numeric errors */ n = 0; for(i = lp->rows + 1; i <= lp->rows+lastcolumn; i++) { value = solution[i]; /* Check for case where we are testing an intermediate solution (variables shifted to the origin) */ if(lowbo == NULL) test = 0; else test = unscaled_value(lp, lowbo[i], i); isSC = is_semicont(lp, i - lp->rows); diff = my_reldiff(value, test); if(diff < 0) { if(isSC && (value < test/2)) test = 0; SETMAX(maxerr, fabs(value-test)); SETMAX(maxdiff, fabs(diff)); } if((diff < -tolerance) && !isSC) { if(n < errlimit) report(lp, errlevel, "check_solution: Variable %s = " RESULTVALUEMASK " is below its lower bound " RESULTVALUEMASK "\n", get_col_name(lp, i-lp->rows), value, test); n++; } test = unscaled_value(lp, upbo[i], i); diff = my_reldiff(value, test); if(diff > 0) { SETMAX(maxerr, fabs(value-test)); SETMAX(maxdiff, fabs(diff)); } if(diff > tolerance) { if(n < errlimit) report(lp, errlevel, "check_solution: Variable %s = " RESULTVALUEMASK " is above its upper bound " RESULTVALUEMASK "\n", get_col_name(lp, i-lp->rows), value, test); n++; } } /* Check if constraint values are within the bounds; allowing a margin for numeric errors */ for(i = 1; i <= lp->rows; i++) { test = lp->orig_rhs[i]; if(is_infinite(lp, test)) continue; #ifdef LegacySlackDefinition j = lp->presolve_undo->var_to_orig[i]; if(j != 0) { if(is_infinite(lp, lp->presolve_undo->fixed_rhs[j])) continue; test += lp->presolve_undo->fixed_rhs[j]; } #endif if(is_chsign(lp, i)) { test = my_flipsign(test); test += fabs(upbo[i]); } value = solution[i]; test = unscaled_value(lp, test, i); #ifndef LegacySlackDefinition value += test; #endif /* diff = my_reldiff(value, test); */ #ifdef UseMaxValueInCheck hold = maxvalue[i]; #else hold = plusum[i] - negsum[i]; #endif if(hold < lp->epsvalue) hold = 1; diff = my_reldiff((value+1)/hold, (test+1)/hold); if(diff > 0) { SETMAX(maxerr, fabs(value-test)); SETMAX(maxdiff, fabs(diff)); } if(diff > tolerance) { if(n < errlimit) report(lp, errlevel, "check_solution: Constraint %s = " RESULTVALUEMASK " is above its %s " RESULTVALUEMASK "\n", get_row_name(lp, i), value, (is_constr_type(lp, i, EQ) ? "equality of" : "upper bound"), test); n++; } test = lp->orig_rhs[i]; #ifdef LegacySlackDefinition j = lp->presolve_undo->var_to_orig[i]; if(j != 0) { if(is_infinite(lp, lp->presolve_undo->fixed_rhs[j])) continue; test += lp->presolve_undo->fixed_rhs[j]; } #endif value = solution[i]; if(is_chsign(lp, i)) test = my_flipsign(test); else { if(is_infinite(lp, upbo[i])) continue; test -= fabs(upbo[i]); #ifndef LegacySlackDefinition value = fabs(upbo[i]) - value; #endif } test = unscaled_value(lp, test, i); #ifndef LegacySlackDefinition value += test; #endif /* diff = my_reldiff(value, test); */ #ifdef UseMaxValueInCheck hold = maxvalue[i]; #else hold = plusum[i] - negsum[i]; #endif if(hold < lp->epsvalue) hold = 1; diff = my_reldiff((value+1)/hold, (test+1)/hold); if(diff < 0) { SETMAX(maxerr, fabs(value-test)); SETMAX(maxdiff, fabs(diff)); } if(diff < -tolerance) { if(n < errlimit) report(lp, errlevel, "check_solution: Constraint %s = " RESULTVALUEMASK " is below its %s " RESULTVALUEMASK "\n", get_row_name(lp, i), value, (is_constr_type(lp, i, EQ) ? "equality of" : "lower bound"), test); n++; } } #ifdef UseMaxValueInCheck FREE(maxvalue); #else FREE(plusum); FREE(negsum); #endif if(n > 0) { report(lp, IMPORTANT, "\nSeriously low accuracy found ||*|| = %g (rel. error %g)\n", maxerr, maxdiff); return(NUMFAILURE); } else { if(maxerr > 1.0e-7) report(lp, NORMAL, "\nMarginal numeric accuracy ||*|| = %g (rel. error %g)\n", maxerr, maxdiff); else if(maxerr > 1.0e-9) report(lp, NORMAL, "\nReasonable numeric accuracy ||*|| = %g (rel. error %g)\n", maxerr, maxdiff); else if(maxerr > 1.0e11) report(lp, NORMAL, "\nVery good numeric accuracy ||*|| = %g\n", maxerr); else report(lp, NORMAL, "\nExcellent numeric accuracy ||*|| = %g\n", maxerr); return(OPTIMAL); } } /* check_solution */ STATIC void transfer_solution_var(lprec *lp, int uservar) { if(lp->varmap_locked && (MYBOOL) ((lp->do_presolve & PRESOLVE_LASTMASKMODE) != PRESOLVE_NONE)) { uservar += lp->rows; lp->full_solution[lp->presolve_undo->orig_rows + lp->presolve_undo->var_to_orig[uservar]] = lp->best_solution[uservar]; } } STATIC void transfer_solution(lprec *lp, MYBOOL dofinal) { int i, ii; MEMCOPY(lp->best_solution, lp->solution, lp->sum + 1); /* Round integer solution values to actual integers */ if(is_integerscaling(lp) && (lp->int_vars > 0)) for(i = 1; i <= lp->columns; i++) { if(is_int(lp, i)) { ii = lp->rows + i; lp->best_solution[ii] = floor(lp->best_solution[ii] + 0.5); } } /* Transfer to full solution vector in the case of presolved eliminations */ if(dofinal && lp->varmap_locked && (MYBOOL) ((lp->do_presolve & PRESOLVE_LASTMASKMODE) != PRESOLVE_NONE)) { presolveundorec *psundo = lp->presolve_undo; lp->full_solution[0] = lp->best_solution[0]; for(i = 1; i <= lp->rows; i++) { ii = psundo->var_to_orig[i]; #ifdef Paranoia if((ii < 0) || (ii > lp->presolve_undo->orig_rows)) report(lp, SEVERE, "transfer_solution: Invalid mapping of row index %d to original index '%d'\n", i, ii); #endif lp->full_solution[ii] = lp->best_solution[i]; } for(i = 1; i <= lp->columns; i++) { ii = psundo->var_to_orig[lp->rows+i]; #ifdef Paranoia if((ii < 0) || (ii > lp->presolve_undo->orig_columns)) report(lp, SEVERE, "transfer_solution: Invalid mapping of column index %d to original index '%d'\n", i, ii); #endif lp->full_solution[psundo->orig_rows+ii] = lp->best_solution[lp->rows+i]; } } } STATIC MYBOOL construct_duals(lprec *lp) { int i, n, *coltarget; REAL scale0, value, dualOF; if(lp->duals != NULL) free_duals(lp); if(is_action(lp->spx_action, ACTION_REBASE) || is_action(lp->spx_action, ACTION_REINVERT) || (!lp->basis_valid) || !allocREAL(lp, &(lp->duals), lp->sum + 1, AUTOMATIC)) return(FALSE); /* Initialize */ coltarget = (int *) mempool_obtainVector(lp->workarrays, lp->columns+1, sizeof(*coltarget)); if(!get_colIndexA(lp, SCAN_USERVARS+USE_NONBASICVARS, coltarget, FALSE)) { mempool_releaseVector(lp->workarrays, (char *) coltarget, FALSE); return(FALSE); } bsolve(lp, 0, lp->duals, NULL, lp->epsmachine*DOUBLEROUND, 1.0); prod_xA(lp, coltarget, lp->duals, NULL, lp->epsmachine, 1.0, lp->duals, NULL, MAT_ROUNDDEFAULT | MAT_ROUNDRC); mempool_releaseVector(lp->workarrays, (char *) coltarget, FALSE); /* The (Lagrangean) dual values are the reduced costs of the primal slacks; when the slack is at its upper bound, change the sign. */ n = lp->rows; for(i = 1; i <= n; i++) { if(lp->is_basic[i]) lp->duals[i] = 0; /* Added a test if variable is different from 0 because sometime you get -0 and this is different from 0 on for example INTEL processors (ie 0 != -0 on INTEL !) PN */ else if((is_chsign(lp, 0) == is_chsign(lp, i)) && lp->duals[i]) lp->duals[i] = my_flipsign(lp->duals[i]); } if(is_maxim(lp)) { n = lp->sum; for(i = lp->rows + 1; i <= n; i++) lp->duals[i] = my_flipsign(lp->duals[i]); } /* If we presolved, then reconstruct the duals */ n = lp->presolve_undo->orig_sum; if(((lp->do_presolve & PRESOLVE_LASTMASKMODE) != PRESOLVE_NONE) && allocREAL(lp, &(lp->full_duals), n + 1, TRUE)) { int ix, ii = lp->presolve_undo->orig_rows; n = lp->sum; for(ix = 1; ix <= n; ix++) { i = lp->presolve_undo->var_to_orig[ix]; if(ix > lp->rows) i += ii; #ifdef Paranoia /* Check for index out of range due to presolve */ if(i > lp->presolve_undo->orig_sum) report(lp, SEVERE, "construct_duals: Invalid presolve variable mapping found\n"); #endif lp->full_duals[i] = lp->duals[ix]; } presolve_rebuildUndo(lp, FALSE); } /* Calculate the dual OF and do scaling adjustments to the duals */ if(lp->scaling_used) scale0 = lp->scalars[0]; else scale0 = 1; dualOF = my_chsign(is_maxim(lp), lp->orig_rhs[0]) / scale0; for(i = 1; i <= lp->sum; i++) { value = scaled_value(lp, lp->duals[i] / scale0, i); my_roundzero(value, lp->epsprimal); lp->duals[i] = value; if(i <= lp->rows) dualOF += value * lp->solution[i]; } #if 0 /* See if we can make use of the dual OF; note that we do not currently adjust properly for presolve */ if(lp->rows == lp->presolve_undo->orig_rows) if(MIP_count(lp) > 0) { if(is_maxim(lp)) { SETMIN(lp->bb_limitOF, dualOF); } else { SETMAX(lp->bb_limitOF, dualOF); } } else if(fabs(my_reldiff(dualOF, lp->solution[0])) > lp->epssolution) report(lp, IMPORTANT, "calculate_duals: Check for possible suboptimal solution!\n"); #endif return(TRUE); } /* construct_duals */ /* Calculate sensitivity duals */ STATIC MYBOOL construct_sensitivity_duals(lprec *lp) { int k,varnr, ok = TRUE; int *workINT = NULL; REAL *pcol,a,infinite,epsvalue,from,till,objfromvalue; /* one column of the matrix */ FREE(lp->objfromvalue); FREE(lp->dualsfrom); FREE(lp->dualstill); if(!allocREAL(lp, &pcol, lp->rows + 1, TRUE) || !allocREAL(lp, &lp->objfromvalue, lp->columns + 1, AUTOMATIC) || !allocREAL(lp, &lp->dualsfrom, lp->sum + 1, AUTOMATIC) || !allocREAL(lp, &lp->dualstill, lp->sum + 1, AUTOMATIC)) { FREE(pcol); FREE(lp->objfromvalue); FREE(lp->dualsfrom); FREE(lp->dualstill); ok = FALSE; } else { infinite=lp->infinite; epsvalue=lp->epsmachine; for(varnr=1; varnr<=lp->sum; varnr++) { from=infinite; till=infinite; objfromvalue=infinite; if (!lp->is_basic[varnr]) { if (!fsolve(lp, varnr, pcol, workINT, epsvalue, 1.0, FALSE)) { /* construct one column of the tableau */ ok = FALSE; break; } /* Search for the rows(s) which first result in further iterations */ for (k=1; k<=lp->rows; k++) { if (fabs(pcol[k])>epsvalue) { a = lp->rhs[k]/pcol[k]; if((varnr > lp->rows) && (fabs(lp->solution[varnr]) <= epsvalue) && (a < objfromvalue) && (a >= lp->lowbo[varnr])) objfromvalue = a; if ((a<=0.0) && (pcol[k]<0.0) && (-a=0.0) && (pcol[k]>0.0) && ( aupbo[lp->var_basic[k]] < infinite) { a = (REAL) ((lp->rhs[k]-lp->upbo[lp->var_basic[k]])/pcol[k]); if((varnr > lp->rows) && (fabs(lp->solution[varnr]) <= epsvalue) && (a < objfromvalue) && (a >= lp->lowbo[varnr])) objfromvalue = a; if ((a<=0.0) && (pcol[k]>0.0) && (-a=0.0) && (pcol[k]<0.0) && ( ais_lower[varnr]) { a=from; from=till; till=a; } if ((varnr<=lp->rows) && (!is_chsign(lp, varnr))) { a=from; from=till; till=a; } } if (from!=infinite) lp->dualsfrom[varnr]=lp->solution[varnr]-unscaled_value(lp, from, varnr); else lp->dualsfrom[varnr]=-infinite; if (till!=infinite) lp->dualstill[varnr]=lp->solution[varnr]+unscaled_value(lp, till, varnr); else lp->dualstill[varnr]=infinite; if (varnr > lp->rows) { if (objfromvalue != infinite) { if (!lp->is_lower[varnr]) objfromvalue = lp->upbo[varnr] - objfromvalue; if ((lp->upbo[varnr] < infinite) && (objfromvalue > lp->upbo[varnr])) objfromvalue = lp->upbo[varnr]; objfromvalue += lp->lowbo[varnr]; objfromvalue = unscaled_value(lp, objfromvalue, varnr); } else objfromvalue = -infinite; lp->objfromvalue[varnr - lp->rows] = objfromvalue; } } FREE(pcol); } return((MYBOOL) ok); } /* construct_sensitivity_duals */ /* Calculate sensitivity objective function */ STATIC MYBOOL construct_sensitivity_obj(lprec *lp) { int i, l, varnr, row_nr, ok = TRUE; REAL *OrigObj = NULL, *drow = NULL, *prow = NULL, sign, a, min1, min2, infinite, epsvalue, from, till; /* objective function */ FREE(lp->objfrom); FREE(lp->objtill); if(!allocREAL(lp, &drow, lp->sum + 1, TRUE) || !allocREAL(lp, &OrigObj, lp->columns + 1, FALSE) || !allocREAL(lp, &prow, lp->sum + 1, TRUE) || !allocREAL(lp, &lp->objfrom, lp->columns + 1, AUTOMATIC) || !allocREAL(lp, &lp->objtill, lp->columns + 1, AUTOMATIC)) { Abandon: FREE(drow); FREE(OrigObj); FREE(prow); FREE(lp->objfrom); FREE(lp->objtill); ok = FALSE; } else { int *coltarget; infinite=lp->infinite; epsvalue=lp->epsmachine; coltarget = (int *) mempool_obtainVector(lp->workarrays, lp->columns+1, sizeof(*coltarget)); if(!get_colIndexA(lp, SCAN_USERVARS+USE_NONBASICVARS, coltarget, FALSE)) { mempool_releaseVector(lp->workarrays, (char *) coltarget, FALSE); goto Abandon; } bsolve(lp, 0, drow, NULL, epsvalue*DOUBLEROUND, 1.0); prod_xA(lp, coltarget, drow, NULL, epsvalue, 1.0, drow, NULL, MAT_ROUNDDEFAULT | MAT_ROUNDRC); /* original (unscaled) objective function */ get_row(lp, 0, OrigObj); for(i = 1; i <= lp->columns; i++) { from=-infinite; till= infinite; varnr = lp->rows + i; if(!lp->is_basic[varnr]) { /* only the coeff of the objective function of column i changes. */ a = unscaled_mat(lp, drow[varnr], 0, i); if(is_maxim(lp)) a = -a; if (lp->upbo[varnr] == 0.0) /* ignore, because this case doesn't results in further iterations */ ; else if((lp->is_lower[varnr] != 0) == (is_maxim(lp) == FALSE)) from = OrigObj[i] - a; /* less than this value gives further iterations */ else till = OrigObj[i] - a; /* bigger than this value gives further iterations */ } else { /* all the coeff of the objective function change. Search the minimal change needed for further iterations */ for(row_nr=1; (row_nr<=lp->rows) && (lp->var_basic[row_nr]!=varnr); row_nr++) /* Search on which row the variable exists in the basis */ ; if(row_nr<=lp->rows) { /* safety test; should always be found ... */ /* Construct one row of the tableau */ bsolve(lp, row_nr, prow, NULL, epsvalue*DOUBLEROUND, 1.0); prod_xA(lp, coltarget, prow, NULL, epsvalue, 1.0, prow, NULL, MAT_ROUNDDEFAULT); /* sign = my_chsign(is_chsign(lp, row_nr), -1); */ sign = my_chsign(lp->is_lower[row_nr], -1); min1=infinite; min2=infinite; for(l=1; l<=lp->sum; l++) /* search for the column(s) which first results in further iterations */ if ((!lp->is_basic[l]) && (lp->upbo[l]>0.0) && (fabs(prow[l])>epsvalue) && (drow[l]*(lp->is_lower[l] ? -1 : 1)is_lower[l] ? 1 : -1) < 0.0) { if(a < min1) min1 = a; } else { if(a < min2) min2 = a; } } if ((lp->is_lower[varnr] == 0) == (is_maxim(lp) == FALSE)) { a = min1; min1 = min2; min2 = a; } if (min1solution[varnr]; if (is_maxim(lp)) { if (a - lp->lowbo[varnr] < epsvalue) from = -infinite; /* if variable is at lower bound then decrementing objective coefficient will not result in extra iterations because it would only extra decrease the value, but since it is at its lower bound ... */ else if (lp->lowbo[varnr] + lp->upbo[varnr] - a < epsvalue) till = infinite; /* if variable is at upper bound then incrementing objective coefficient will not result in extra iterations because it would only extra increase the value, but since it is at its upper bound ... */ } else { if (a - lp->lowbo[varnr] < epsvalue) till = infinite; /* if variable is at lower bound then incrementing objective coefficient will not result in extra iterations because it would only extra decrease the value, but since it is at its lower bound ... */ else if (lp->lowbo[varnr] + lp->upbo[varnr] - a < epsvalue) from = -infinite; /* if variable is at upper bound then decrementing objective coefficient will not result in extra iterations because it would only extra increase the value, but since it is at its upper bound ... */ } } } lp->objfrom[i]=from; lp->objtill[i]=till; } mempool_releaseVector(lp->workarrays, (char *) coltarget, FALSE); } FREE(prow); FREE(OrigObj); FREE(drow); return((MYBOOL) ok); } /* construct_sensitivity_obj */ STATIC MYBOOL refactRecent(lprec *lp) { int pivcount = lp->bfp_pivotcount(lp); if(pivcount == 0) return( AUTOMATIC ); else if (pivcount < 2*DEF_MAXPIVOTRETRY) return( TRUE ); else return( FALSE ); } STATIC MYBOOL check_if_less(lprec *lp, REAL x, REAL y, int variable) { if(y < x-scaled_value(lp, lp->epsint, variable)) { if(lp->bb_trace) report(lp, NORMAL, "check_if_less: Invalid new bound %g should be < %g for %s\n", x, y, get_col_name(lp, variable)); return(FALSE); } else return(TRUE); } /* Various basis utility routines */ STATIC int findNonBasicSlack(lprec *lp, MYBOOL *is_basic) { int i; for(i = lp->rows; i > 0; i--) if(!is_basic[i]) break; return( i ); } STATIC int findBasisPos(lprec *lp, int notint, int *var_basic) { int i; if(var_basic == NULL) var_basic = lp->var_basic; for(i = lp->rows; i > 0; i--) if(var_basic[i] == notint) break; return( i ); } STATIC void replaceBasisVar(lprec *lp, int rownr, int var, int *var_basic, MYBOOL *is_basic) { int out; out = var_basic[rownr]; var_basic[rownr] = var; is_basic[out] = FALSE; is_basic[var] = TRUE; } STATIC void free_duals(lprec *lp) { FREE(lp->duals); FREE(lp->full_duals); FREE(lp->dualsfrom); FREE(lp->dualstill); FREE(lp->objfromvalue); FREE(lp->objfrom); FREE(lp->objtill); } /* Transform RHS by adjusting for the bound state of variables; optionally rebase upper bound, and account for this in later calls */ STATIC void initialize_solution(lprec *lp, MYBOOL shiftbounds) { int i, k1, k2, *matRownr, colnr; LREAL theta; REAL value, *matValue, loB, upB; MATrec *mat = lp->matA; /* Set bounding status indicators */ if(lp->bb_bounds != NULL) { if(shiftbounds == INITSOL_SHIFTZERO) { if(lp->bb_bounds->UBzerobased) report(lp, SEVERE, "initialize_solution: The upper bounds are already zero-based at refactorization %d\n", lp->bfp_refactcount(lp, BFP_STAT_REFACT_TOTAL)); lp->bb_bounds->UBzerobased = TRUE; } else if(!lp->bb_bounds->UBzerobased) report(lp, SEVERE, "initialize_solution: The upper bounds are not zero-based at refactorization %d\n", lp->bfp_refactcount(lp, BFP_STAT_REFACT_TOTAL)); } /* Initialize the working RHS/basic variable solution vector */ i = is_action(lp->anti_degen, ANTIDEGEN_RHSPERTURB) && (lp->monitor != NULL) && lp->monitor->active; if(sizeof(*lp->rhs) == sizeof(*lp->orig_rhs) && !i) { MEMCOPY(lp->rhs, lp->orig_rhs, lp->rows+1); } else if(i) { lp->rhs[0] = lp->orig_rhs[0]; for(i = 1; i <= lp->rows; i++) { if(is_constr_type(lp, i, EQ)) theta = rand_uniform(lp, lp->epsvalue); else { theta = rand_uniform(lp, lp->epsperturb); /* if(lp->orig_upbo[i] < lp->infinite) lp->orig_upbo[i] += theta; */ } lp->rhs[i] = lp->orig_rhs[i] + theta; } } else for(i = 0; i <= lp->rows; i++) lp->rhs[i] = lp->orig_rhs[i]; /* Adjust active RHS for variables at their active upper/lower bounds */ for(i = 1; i <= lp->sum; i++) { upB = lp->upbo[i]; loB = lp->lowbo[i]; /* Shift to "ranged" upper bound, tantamount to defining zero-based variables */ if(shiftbounds == INITSOL_SHIFTZERO) { if((loB > -lp->infinite) && (upB < lp->infinite)) lp->upbo[i] -= loB; if(lp->upbo[i] < 0) report(lp, SEVERE, "initialize_solution: Invalid rebounding; variable %d at refact %d, iter %.0f\n", i, lp->bfp_refactcount(lp, BFP_STAT_REFACT_TOTAL), (double) get_total_iter(lp)); } /* Use "ranged" upper bounds */ else if(shiftbounds == INITSOL_USEZERO) { if((loB > -lp->infinite) && (upB < lp->infinite)) upB += loB; } /* Shift upper bound back to original value */ else if(shiftbounds == INITSOL_ORIGINAL) { if((loB > -lp->infinite) && (upB < lp->infinite)) { lp->upbo[i] += loB; upB += loB; } continue; } else report(lp, SEVERE, "initialize_solution: Invalid option value '%d'\n", shiftbounds); /* Set the applicable adjustment */ if(lp->is_lower[i]) theta = loB; else theta = upB; /* Check if we need to pass through the matrix; remember that basis variables are always lower-bounded */ if(theta == 0) continue; /* Do user and artificial variables */ if(i > lp->rows) { /* Get starting and ending indeces in the NZ vector */ colnr = i - lp->rows; k1 = mat->col_end[colnr - 1]; k2 = mat->col_end[colnr]; matRownr = &COL_MAT_ROWNR(k1); matValue = &COL_MAT_VALUE(k1); /* Get the objective as row 0, optionally adjusting the objective for phase 1 */ value = get_OF_active(lp, i, theta); lp->rhs[0] -= value; /* Do the normal case */ for(; k1 < k2; k1++, matRownr += matRowColStep, matValue += matValueStep) { lp->rhs[*matRownr] -= theta * (*matValue); } } /* Do slack variables (constraint "bounds")*/ else { lp->rhs[i] -= theta; } } /* Do final pass to get the maximum value */ i = idamax(lp->rows /* +1 */, lp->rhs, 1); lp->rhsmax = fabs(lp->rhs[i]); if(shiftbounds == INITSOL_SHIFTZERO) clear_action(&lp->spx_action, ACTION_REBASE); } /* This routine recomputes the basic variables using the full inverse */ STATIC void recompute_solution(lprec *lp, MYBOOL shiftbounds) { /* Compute RHS = b - A(n)*x(n) */ initialize_solution(lp, shiftbounds); /* Compute x(b) = Inv(B)*RHS (Ref. lp_solve inverse logic and Chvatal p. 121) */ lp->bfp_ftran_normal(lp, lp->rhs, NULL); if(!lp->obj_in_basis) { int i, ib, n = lp->rows; for(i = 1; i <= n; i++) { ib = lp->var_basic[i]; if(ib > n) lp->rhs[0] -= get_OF_active(lp, ib, lp->rhs[i]); } } /* Round the values (should not be greater than the factor used in bfp_pivotRHS) */ roundVector(lp->rhs, lp->rows, lp->epsvalue); clear_action(&lp->spx_action, ACTION_RECOMPUTE); } /* This routine compares an existing basic solution to a recomputed one; Note that the routine must provide for the possibility that the order of the basis variables can be changed by the inversion engine. */ STATIC int verify_solution(lprec *lp, MYBOOL reinvert, char *info) { int i, ii, n, *oldmap, *newmap, *refmap = NULL; REAL *oldrhs, err, errmax; allocINT(lp, &oldmap, lp->rows+1, FALSE); allocINT(lp, &newmap, lp->rows+1, FALSE); allocREAL(lp, &oldrhs, lp->rows+1, FALSE); /* Get sorted mapping of the old basis */ for(i = 0; i <= lp->rows; i++) oldmap[i] = i; if(reinvert) { allocINT(lp, &refmap, lp->rows+1, FALSE); MEMCOPY(refmap, lp->var_basic, lp->rows+1); sortByINT(oldmap, refmap, lp->rows, 1, TRUE); } /* Save old and calculate the new RHS vector */ MEMCOPY(oldrhs, lp->rhs, lp->rows+1); if(reinvert) invert(lp, INITSOL_USEZERO, FALSE); else recompute_solution(lp, INITSOL_USEZERO); /* Get sorted mapping of the new basis */ for(i = 0; i <= lp->rows; i++) newmap[i] = i; if(reinvert) { MEMCOPY(refmap, lp->var_basic, lp->rows+1); sortByINT(newmap, refmap, lp->rows, 1, TRUE); } /* Identify any gap */ errmax = 0; ii = -1; n = 0; for(i = lp->rows; i > 0; i--) { err = fabs(my_reldiff(oldrhs[oldmap[i]], lp->rhs[newmap[i]])); if(err > lp->epsprimal) { n++; if(err > errmax) { ii = i; errmax = err; } } } err = fabs(my_reldiff(oldrhs[i], lp->rhs[i])); if(err < lp->epspivot) { i--; err = 0; } else { n++; if(ii < 0) { ii = 0; errmax = err; } } if(n > 0) { report(lp, IMPORTANT, "verify_solution: Iter %.0f %s - %d errors; OF %g, Max @row %d %g\n", (double) get_total_iter(lp), my_if(info == NULL, "", info), n, err, newmap[ii], errmax); } /* Copy old results back (not possible for inversion) */ if(!reinvert) MEMCOPY(lp->rhs, oldrhs, lp->rows+1); FREE(oldmap); FREE(newmap); FREE(oldrhs); if(reinvert) FREE(refmap); return( ii ); } /* Preprocessing and postprocessing functions */ STATIC int identify_GUB(lprec *lp, MYBOOL mark) { int i, j, jb, je, k, knint, srh; REAL rh, mv, tv, bv; MATrec *mat = lp->matA; if((lp->equalities == 0) || !mat_validate(mat)) return( 0 ); k = 0; for(i = 1; i <= lp->rows; i++) { /* Check if it is an equality constraint */ if(!is_constr_type(lp, i, EQ)) continue; rh = get_rh(lp, i); srh = my_sign(rh); knint = 0; je = mat->row_end[i]; for(jb = mat->row_end[i-1]; jb < je; jb++) { j = ROW_MAT_COLNR(jb); /* Check for validity of the equation elements */ if(!is_int(lp, j)) knint++; if(knint > 1) break; mv = get_mat_byindex(lp, jb, TRUE, FALSE); if(fabs(my_reldiff(mv, rh)) > lp->epsprimal) break; tv = mv*get_upbo(lp, j); bv = get_lowbo(lp, j); #if 0 /* Requires 1 as upper bound */ if((fabs(my_reldiff(tv, rh)) > lp->epsprimal) || (bv != 0)) #else /* Can handle any upper bound >= 1 */ if((srh*(tv-rh) < -lp->epsprimal) || (bv != 0)) #endif break; } /* Update GUB count and optionally mark the GUB */ if(jb == je) { k++; if(mark == TRUE) lp->row_type[i] |= ROWTYPE_GUB; else if(mark == AUTOMATIC) break; } } return( k ); } STATIC int prepare_GUB(lprec *lp) { int i, j, jb, je, k, *members = NULL; REAL rh; char GUBname[16]; MATrec *mat = lp->matA; if((lp->equalities == 0) || !allocINT(lp, &members, lp->columns+1, TRUE) || !mat_validate(mat)) return( 0 ); for(i = 1; i <= lp->rows; i++) { /* Check if it has been marked as a GUB */ if(!(lp->row_type[i] & ROWTYPE_GUB)) continue; /* Pick up the GUB column indeces */ k = 0; je = mat->row_end[i]; for(jb = mat->row_end[i-1], k = 0; jb < je; jb++) { members[k] = ROW_MAT_COLNR(jb); k++; } /* Add the GUB */ j = GUB_count(lp) + 1; sprintf(GUBname, "GUB_%d", i); add_GUB(lp, GUBname, j, k, members); /* Unmark the GUBs */ clear_action(&(lp->row_type[i]), ROWTYPE_GUB); /* Standardize coefficients to 1 if necessary */ rh = get_rh(lp, i); if(fabs(my_reldiff(rh, 1)) > lp->epsprimal) { set_rh(lp, i, 1); for(jb = mat->row_end[i-1]; jb < je; jb++) { j = ROW_MAT_COLNR(jb); set_mat(lp, i,j, 1); } } } FREE(members); return(GUB_count(lp)); } /* Pre- and post processing functions, i.a. splitting free variables */ STATIC MYBOOL pre_MIPOBJ(lprec *lp) { #ifdef MIPboundWithOF if(MIP_count(lp) > 0) { int i = 1; while((i <= lp->rows) && !mat_equalRows(lp->matA, 0, i) && !is_constr_type(lp, i, EQ)) i++; if(i <= lp->rows) lp->constraintOF = i; } #endif lp->bb_deltaOF = MIP_stepOF(lp); return( TRUE ); } STATIC MYBOOL post_MIPOBJ(lprec *lp) { #ifdef MIPboundWithOF /* if(lp->constraintOF) { del_constraint(lp, lp->rows); if(is_BasisReady(lp) && !verify_basis(lp)) return( FALSE ); } */ #endif return( TRUE ); } int preprocess(lprec *lp) { int i, j, k, ok = TRUE, *new_index = NULL; REAL hold, *new_column = NULL; MYBOOL scaled, primal1, primal2; /* do not process if already preprocessed */ if(lp->wasPreprocessed) return( ok ); /* Write model statistics and optionally initialize partial pricing structures */ if(lp->lag_status != RUNNING) { MYBOOL doPP; /* Extract the user-specified simplex strategy choices */ primal1 = (MYBOOL) (lp->simplex_strategy & SIMPLEX_Phase1_PRIMAL); primal2 = (MYBOOL) (lp->simplex_strategy & SIMPLEX_Phase2_PRIMAL); /* Initialize partial pricing structures */ doPP = is_piv_mode(lp, PRICE_PARTIAL | PRICE_AUTOPARTIAL); /* doPP &= (MYBOOL) (lp->columns / 2 > lp->rows); */ if(doPP) { i = partial_findBlocks(lp, FALSE, FALSE); if(i < 4) i = (int) (5 * log((REAL) lp->columns / lp->rows)); report(lp, NORMAL, "The model is %s to have %d column blocks/stages.\n", (i > 1 ? "estimated" : "set"), i); set_partialprice(lp, i, NULL, FALSE); } /* doPP &= (MYBOOL) (lp->rows / 4 > lp->columns); */ if(doPP) { i = partial_findBlocks(lp, FALSE, TRUE); if(i < 4) i = (int) (5 * log((REAL) lp->rows / lp->columns)); report(lp, NORMAL, "The model is %s to have %d row blocks/stages.\n", (i > 1 ? "estimated" : "set"), i); set_partialprice(lp, i, NULL, TRUE); } /* Check for presence of valid pricing blocks if partial pricing is defined, but not autopartial is not set */ if(!doPP && is_piv_mode(lp, PRICE_PARTIAL)) { if((lp->rowblocks == NULL) || (lp->colblocks == NULL)) { report(lp, IMPORTANT, "Ignoring partial pricing, since block structures are not defined.\n"); clear_action(&lp->piv_strategy, PRICE_PARTIAL); } } /* Initialize multiple pricing block divisor */ #if 0 if(primal1 || primal2) lp->piv_strategy |= PRICE_MULTIPLE | PRICE_AUTOMULTIPLE; #endif if(is_piv_mode(lp, PRICE_MULTIPLE) && (primal1 || primal2)) { doPP = is_piv_mode(lp, PRICE_AUTOMULTIPLE); if(doPP) { i = (int) (2.5*log((REAL) lp->sum)); SETMAX( i, 1); set_multiprice(lp, i); } if(lp->multiblockdiv > 1) report(lp, NORMAL, "Using %d-candidate primal simplex multiple pricing block.\n", lp->columns / lp->multiblockdiv); } else set_multiprice(lp, 1); report(lp, NORMAL, "Using %s simplex for phase 1 and %s simplex for phase 2.\n", my_if(primal1, "PRIMAL", "DUAL"), my_if(primal2, "PRIMAL", "DUAL")); i = get_piv_rule(lp); if((i == PRICER_STEEPESTEDGE) && is_piv_mode(lp, PRICE_PRIMALFALLBACK)) report(lp, NORMAL, "The pricing strategy is set to '%s' for the dual and '%s' for the primal.\n", get_str_piv_rule(i), get_str_piv_rule(i-1)); else report(lp, NORMAL, "The primal and dual simplex pricing strategy set to '%s'.\n", get_str_piv_rule(i)); report(lp, NORMAL, " \n"); } /* Compute a minimum step improvement step requirement */ pre_MIPOBJ(lp); /* First create extra columns for FR variables or flip MI variables */ for (j = 1; j <= lp->columns; j++) { #ifdef Paranoia if((lp->rows != lp->matA->rows) || (lp->columns != lp->matA->columns)) report(lp, SEVERE, "preprocess: Inconsistent variable counts found\n"); #endif /* First handle sign-flipping of variables: 1) ... with a finite upper bound and a negative Inf-bound (since basis variables are lower-bounded) 2) ... with bound assymetry within negrange limits (for stability reasons) */ i = lp->rows + j; hold = lp->orig_upbo[i]; /* if((hold <= 0) || (!is_infinite(lp, lp->negrange) && (hold < -lp->negrange) && (lp->orig_lowbo[i] <= lp->negrange)) ) { */ #define fullybounded FALSE if( ((hold < lp->infinite) && my_infinite(lp, lp->orig_lowbo[i])) || (!fullybounded && !my_infinite(lp, lp->negrange) && (hold < -lp->negrange) && (lp->orig_lowbo[i] <= lp->negrange)) ) { /* Delete split sibling variable if one existed from before */ if((lp->var_is_free != NULL) && (lp->var_is_free[j] > 0)) del_column(lp, lp->var_is_free[j]); /* Negate the column / flip to the positive range */ mat_multcol(lp->matA, j, -1, TRUE); if(lp->var_is_free == NULL) { if(!allocINT(lp, &lp->var_is_free, MAX(lp->columns, lp->columns_alloc) + 1, TRUE)) return(FALSE); } lp->var_is_free[j] = -j; /* Indicator UB and LB are switched, with no helper variable added */ lp->orig_upbo[i] = my_flipsign(lp->orig_lowbo[i]); lp->orig_lowbo[i] = my_flipsign(hold); /* Check for presence of negative ranged SC variable */ if(lp->sc_lobound[j] > 0) { lp->sc_lobound[j] = lp->orig_lowbo[i]; lp->orig_lowbo[i] = 0; } } /* Then deal with -+, full-range/FREE variables by creating a helper variable */ else if((lp->orig_lowbo[i] <= lp->negrange) && (hold >= -lp->negrange)) { if(lp->var_is_free == NULL) { if(!allocINT(lp, &lp->var_is_free, MAX(lp->columns,lp->columns_alloc) + 1, TRUE)) return(FALSE); } if(lp->var_is_free[j] <= 0) { /* If this variable wasn't split yet ... */ if(SOS_is_member(lp->SOS, 0, i - lp->rows)) { /* Added */ report(lp, IMPORTANT, "preprocess: Converted negative bound for SOS variable %d to zero", i - lp->rows); lp->orig_lowbo[i] = 0; continue; } if(new_column == NULL) { if(!allocREAL(lp, &new_column, lp->rows + 1, FALSE) || !allocINT(lp, &new_index, lp->rows + 1, FALSE)) { ok = FALSE; break; } } /* Avoid precision loss by turning off unscaling and rescaling */ /* in get_column and add_column operations; also make sure that */ /* full scaling information is preserved */ scaled = lp->scaling_used; lp->scaling_used = FALSE; k = get_columnex(lp, j, new_column, new_index); if(!add_columnex(lp, k, new_column, new_index)) { ok = FALSE; break; } mat_multcol(lp->matA, lp->columns, -1, TRUE); if(scaled) lp->scalars[lp->rows+lp->columns] = lp->scalars[i]; lp->scaling_used = (MYBOOL) scaled; /* Only create name if we are not clearing a pre-used item, since this variable could have been deleted by presolve but the name is required for solution reconstruction. */ if(lp->names_used && (lp->col_name[j] == NULL)) { char fieldn[50]; sprintf(fieldn, "__AntiBodyOf(%d)__", j); if(!set_col_name(lp, lp->columns, fieldn)) { /* if (!set_col_name(lp, lp->columns, get_col_name(lp, j))) { */ ok = FALSE; break; } } /* Set (positive) index to the original column's split / helper and back */ lp->var_is_free[j] = lp->columns; } lp->orig_upbo[lp->rows + lp->var_is_free[j]] = my_flipsign(lp->orig_lowbo[i]); lp->orig_lowbo[i] = 0; /* Negative index indicates x is split var and -var_is_free[x] is index of orig var */ lp->var_is_free[lp->var_is_free[j]] = -j; lp->var_type[lp->var_is_free[j]] = lp->var_type[j]; } /* Check for positive ranged SC variables */ else if(lp->sc_lobound[j] > 0) { lp->sc_lobound[j] = lp->orig_lowbo[i]; lp->orig_lowbo[i] = 0; } /* Tally integer variables in SOS'es */ if(SOS_is_member(lp->SOS, 0, j) && is_int(lp, j)) lp->sos_ints++; } FREE(new_column); FREE(new_index); /* Fill lists of GUB constraints, if appropriate */ if((MIP_count(lp) > 0) && is_bb_mode(lp, NODE_GUBMODE) && (identify_GUB(lp, AUTOMATIC) > 0)) prepare_GUB(lp); /* (Re)allocate reduced cost arrays */ ok = allocREAL(lp, &(lp->drow), lp->sum+1, AUTOMATIC) && allocINT(lp, &(lp->nzdrow), lp->sum+1, AUTOMATIC); if(ok) lp->nzdrow[0] = 0; /* Minimize memory usage */ memopt_lp(lp, 0, 0, 0); lp->wasPreprocessed = TRUE; return(ok); } void postprocess(lprec *lp) { int i,ii,j; REAL hold; /* Check if the problem actually was preprocessed */ if(!lp->wasPreprocessed) return; /* Must compute duals here in case we have free variables; note that in this case sensitivity analysis is not possible unless done here */ if((MIP_count(lp) == 0) && (is_presolve(lp, PRESOLVE_DUALS) || (lp->var_is_free != NULL))) construct_duals(lp); if(is_presolve(lp, PRESOLVE_SENSDUALS)) { if(!construct_sensitivity_duals(lp) || !construct_sensitivity_obj(lp)) report(lp, IMPORTANT, "postprocess: Unable to allocate working memory for duals.\n"); } /* Loop over all columns */ for (j = 1; j <= lp->columns; j++) { i = lp->rows + j; /* Reconstruct strictly negative values */ if((lp->var_is_free != NULL) && (lp->var_is_free[j] < 0)) { /* Check if we have the simple case where the UP and LB are negated and switched */ if(-lp->var_is_free[j] == j) { mat_multcol(lp->matA, j, -1, TRUE); hold = lp->orig_upbo[i]; lp->orig_upbo[i] = my_flipsign(lp->orig_lowbo[i]); lp->orig_lowbo[i] = my_flipsign(hold); lp->best_solution[i] = my_flipsign(lp->best_solution[i]); transfer_solution_var(lp, j); /* hold = lp->objfrom[j]; lp->objfrom[j] = my_flipsign(lp->objtill[j]); lp->objtill[j] = my_flipsign(hold); */ /* under investigation */ /* lp->duals[i] = my_flipsign(lp->duals[i]); hold = lp->dualsfrom[i]; lp->dualsfrom[i] = my_flipsign(lp->dualstill[i]); lp->dualstill[i] = my_flipsign(hold); */ /* under investigation */ /* Bound switch undone, so clear the status */ lp->var_is_free[j] = 0; /* Adjust negative ranged SC */ if(lp->sc_lobound[j] > 0) lp->orig_lowbo[lp->rows + j] = -lp->sc_lobound[j]; } /* Ignore the split / helper columns (will be deleted later) */ } /* Condense values of extra columns of quasi-free variables split in two */ else if((lp->var_is_free != NULL) && (lp->var_is_free[j] > 0)) { ii = lp->var_is_free[j]; /* Index of the split helper var */ /* if(lp->objfrom[j] == -lp->infinite) lp->objfrom[j] = -lp->objtill[ii]; lp->objtill[ii] = lp->infinite; if(lp->objtill[j] == lp->infinite) lp->objtill[j] = my_flipsign(lp->objfrom[ii]); lp->objfrom[ii] = -lp->infinite; */ /* under investigation */ ii += lp->rows; lp->best_solution[i] -= lp->best_solution[ii]; /* join the solution again */ transfer_solution_var(lp, j); lp->best_solution[ii] = 0; /* if(lp->duals[i] == 0) lp->duals[i] = my_flipsign(lp->duals[ii]); lp->duals[ii] = 0; if(lp->dualsfrom[i] == -lp->infinite) lp->dualsfrom[i] = my_flipsign(lp->dualstill[ii]); lp->dualstill[ii] = lp->infinite; if(lp->dualstill[i] == lp->infinite) lp->dualstill[i] = my_flipsign(lp->dualsfrom[ii]); lp->dualsfrom[ii] = -lp->infinite; */ /* under investigation */ /* Reset to original bound */ lp->orig_lowbo[i] = my_flipsign(lp->orig_upbo[ii]); } /* Adjust for semi-continuous variables */ else if(lp->sc_lobound[j] > 0) { lp->orig_lowbo[i] = lp->sc_lobound[j]; } } /* Remove any split column helper variables */ del_splitvars(lp); post_MIPOBJ(lp); /* Do extended reporting, if specified */ if(lp->verbose > NORMAL) { REPORT_extended(lp); } lp->wasPreprocessed = FALSE; } MSVMpack1.2/lp_solve_5.5/lp_Hash.c0000664000175000017500000001267411141374244015673 0ustar lauerlauer #include #include #include "lp_lib.h" #include "lp_utils.h" #include "lp_report.h" #include "lp_Hash.h" #ifdef FORTIFY # include "lp_fortify.h" #endif #define HASH_START_SIZE 5000 /* Hash table size for row and column name storage */ #define NUMHASHPRIMES 45 STATIC hashtable *create_hash_table(int size, int base) { int i; int HashPrimes[ ] = { 29, 229, 883, 1671, 2791, 4801, 8629, 10007, 15289, 25303, 34843, 65269, 99709, 129403, 147673, 166669, 201403, 222163, 242729, 261431, 303491, 320237, 402761, 501131, 602309, 701507, 800999, 900551, 1000619, 1100837, 1200359, 1300021, 1400017, 1500007, 1750009, 2000003, 2500009, 3000017, 4000037, 5000011, 6000011, 7000003, 8000009, 9000011, 9999991}; hashtable *ht; /* Find a good size for the hash table */ if(size < HASH_START_SIZE) size = HASH_START_SIZE; for(i = 0; i < NUMHASHPRIMES-1; i++) if(HashPrimes[i] > size) break; size = HashPrimes[i]; /* Then allocate and initialize memory */ ht = (hashtable *) calloc(1 , sizeof(*ht)); ht->table = (hashelem **) calloc(size, sizeof(*(ht->table))); ht->size = size; ht->base = base; ht->count = base-1; return(ht); } STATIC void free_hash_item(hashelem **hp) { free((*hp)->name); free(*hp); *hp = NULL; } STATIC void free_hash_table(hashtable *ht) { hashelem *hp, *thp; hp = ht->first; while(hp != NULL) { thp = hp; hp = hp->nextelem; free_hash_item(&thp); } free(ht->table); free(ht); } /* make a good hash function for any int size */ /* inspired by Aho, Sethi and Ullman, Compilers ..., p436 */ #define HASH_1 sizeof(unsigned int) #define HASH_2 (sizeof(unsigned int) * 6) #define HASH_3 (((unsigned int)0xF0) << ((sizeof(unsigned int) - 1) * CHAR_BIT)) STATIC int hashval(const char *string, int size) { unsigned int result = 0, tmp; for(; *string; string++) { result = (result << HASH_1) + *string; if((tmp = result & HASH_3) != 0) { /* if any of the most significant bits is on */ result ^= tmp >> HASH_2; /* xor them in in a less significant part */ result ^= tmp; /* and reset the most significant bits to 0 */ } } return(result % size); } /* hashval */ STATIC hashelem *findhash(const char *name, hashtable *ht) { hashelem *h_tab_p; for(h_tab_p = ht->table[hashval(name, ht->size)]; h_tab_p != NULL; h_tab_p = h_tab_p->next) if(strcmp(name, h_tab_p->name) == 0) /* got it! */ break; return(h_tab_p); } /* findhash */ STATIC hashelem *puthash(const char *name, int index, hashelem **list, hashtable *ht) { hashelem *hp = NULL; int hashindex; if(list != NULL) { hp = list[index]; if(hp != NULL) list[index] = NULL; } if((hp = findhash(name, ht)) == NULL) { hashindex = hashval(name, ht->size); hp = (hashelem *) calloc(1, sizeof(*hp)); allocCHAR(NULL, &hp->name, (int) (strlen(name) + 1), FALSE); strcpy(hp->name, name); hp->index = index; ht->count++; if(list != NULL) list[index] = hp; hp->next = ht->table[hashindex]; ht->table[hashindex] = hp; if(ht->first == NULL) ht->first = hp; if(ht->last != NULL) ht->last->nextelem = hp; ht->last = hp; } return(hp); } STATIC void drophash(const char *name, hashelem **list, hashtable *ht) { hashelem *hp, *hp1, *hp2; int hashindex; if((hp = findhash(name, ht)) != NULL) { hashindex = hashval(name, ht->size); if((hp1 = ht->table[hashindex]) != NULL) { hp2 = NULL; while((hp1 != NULL) && (hp1 != hp)) { hp2 = hp1; hp1 = hp1->next; } if(hp1 == hp) { if(hp2 != NULL) hp2->next = hp->next; else ht->table[hashindex] = hp->next; } hp1 = ht->first; hp2 = NULL; while((hp1 != NULL) && (hp1 != hp)) { hp2 = hp1; hp1 = hp1->nextelem; } if(hp1 == hp) { if(hp2 != NULL) hp2->nextelem = hp->nextelem; else { ht->first = hp->nextelem; if (ht->first == NULL) ht->last = NULL; } } if(list != NULL) list[hp->index] = NULL; free_hash_item(&hp); ht->count--; } } } STATIC hashtable *copy_hash_table(hashtable *ht, hashelem **list, int newsize) { hashtable *copy; hashelem *elem, *new_elem; if(newsize < ht->size) newsize = ht->size; copy = create_hash_table(newsize, ht->base); if (copy != NULL) { elem = ht->first; while (elem != NULL) { if((new_elem = puthash(elem->name, elem->index, list, copy)) == NULL) { free_hash_table(copy); return(NULL); } elem = elem ->nextelem; } } return(copy); } STATIC int find_row(lprec *lp, char *name, MYBOOL Unconstrained_rows_found) { hashelem *hp; if (lp->rowname_hashtab != NULL) hp = findhash(name, lp->rowname_hashtab); else hp = NULL; if (hp == NULL) { if(Unconstrained_rows_found) { /* just ignore them in this case */ return(-1); } else { return(-1); } } return(hp->index); } STATIC int find_var(lprec *lp, char *name, MYBOOL verbose) { hashelem *hp; if (lp->colname_hashtab != NULL) hp = findhash(name, lp->colname_hashtab); else hp = NULL; if (hp == NULL) { if(verbose) report(lp, SEVERE, "find_var: Unknown variable name '%s'\n", name); return(-1); } return(hp->index); } MSVMpack1.2/lp_solve_5.5/demo/0000775000175000017500000000000011170643432015063 5ustar lauerlauerMSVMpack1.2/lp_solve_5.5/demo/demolib.sln0000664000175000017500000000231111141360155017205 0ustar lauerlauerMicrosoft Visual Studio Solution File, Format Version 10.00 # Visual Studio 2008 Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "demo", "demolib.vcproj", "{CED6B89F-02F2-4DB1-8610-4F12A6D02F54}" EndProject Global GlobalSection(SolutionConfigurationPlatforms) = preSolution Debug|Win32 = Debug|Win32 Debug|x64 = Debug|x64 Release|Win32 = Release|Win32 Release|x64 = Release|x64 EndGlobalSection GlobalSection(ProjectConfigurationPlatforms) = postSolution {CED6B89F-02F2-4DB1-8610-4F12A6D02F54}.Debug|Win32.ActiveCfg = Debug|Win32 {CED6B89F-02F2-4DB1-8610-4F12A6D02F54}.Debug|Win32.Build.0 = Debug|Win32 {CED6B89F-02F2-4DB1-8610-4F12A6D02F54}.Debug|x64.ActiveCfg = Debug|x64 {CED6B89F-02F2-4DB1-8610-4F12A6D02F54}.Debug|x64.Build.0 = Debug|x64 {CED6B89F-02F2-4DB1-8610-4F12A6D02F54}.Release|Win32.ActiveCfg = Release|Win32 {CED6B89F-02F2-4DB1-8610-4F12A6D02F54}.Release|Win32.Build.0 = Release|Win32 {CED6B89F-02F2-4DB1-8610-4F12A6D02F54}.Release|x64.ActiveCfg = Release|x64 {CED6B89F-02F2-4DB1-8610-4F12A6D02F54}.Release|x64.Build.0 = Release|x64 EndGlobalSection GlobalSection(SolutionProperties) = preSolution HideSolutionNode = FALSE EndGlobalSection EndGlobal MSVMpack1.2/lp_solve_5.5/demo/demo.c0000664000175000017500000001570111170642062016155 0ustar lauerlauer/* This program is originally made by by Jeroen J. Dirks (jeroend@tor.numetrix.com) Adapted by Peter Notebaert (lpsolve@peno.be) */ #include #include "lp_lib.h" #if defined FORTIFY #include "lp_fortify.h" int EndOfPgr(int i) { exit(i); } #endif void press_ret(void) { #if !defined NORETURN printf("[return]"); getchar(); #endif } int main(void) { # if defined ERROR # undef ERROR # endif # define ERROR() { fprintf(stderr, "Error\n"); exit(1); } lprec *lp; int majorversion, minorversion, release, build; #if defined FORTIFY Fortify_EnterScope(); #endif lp_solve_version(&majorversion, &minorversion, &release, &build); printf("lp_solve %d.%d.%d.%d demo\n\n", majorversion, minorversion, release, build); printf("This demo will show most of the features of lp_solve %d.%d.%d.%d\n", majorversion, minorversion, release, build); press_ret(); printf("\nWe start by creating a new problem with 4 variables and 0 constraints\n"); printf("We use: lp=make_lp(0,4);\n"); if ((lp = make_lp(0,4)) == NULL) ERROR(); press_ret(); printf("We can show the current problem with print_lp(lp)\n"); print_lp(lp); press_ret(); printf("Now we add some constraints\n"); printf("add_constraint(lp, {0, 3, 2, 2, 1}, LE, 4)\n"); { double row[] = {0, 3, 2, 2, 1}; if (!add_constraint(lp, row, LE, 4)) ERROR(); } print_lp(lp); press_ret(); printf("add_constraintex is now used to add a row. Only the npn-zero values must be specfied with this call.\n"); printf("add_constraintex(lp, 3, {4, 3, 1}, {2, 3, 4}, GE, 3)\n"); { int colno[] = {2, 3, 4}; double row[] = {4, 3, 1}; if (!add_constraintex(lp, sizeof(colno) / sizeof(*colno), row, colno, GE, 3)) ERROR(); } print_lp(lp); press_ret(); printf("Set the objective function\n"); printf("set_obj_fn(lp, {0, 2, 3, -2, 3})\n"); { double row[] = {0, 2, 3, -2, 3}; if (!set_obj_fn(lp, row)) ERROR(); } print_lp(lp); press_ret(); printf("Now solve the problem with printf(solve(lp));\n"); printf("%d",solve(lp)); press_ret(); printf("The value is 0, this means we found an optimal solution\n"); printf("We can display this solution with print_objective(lp) and print_solution(lp)\n"); print_objective(lp); print_solution(lp, 1); print_constraints(lp, 1); press_ret(); printf("The dual variables of the solution are printed with\n"); printf("print_duals(lp);\n"); print_duals(lp); press_ret(); printf("We can change a single element in the matrix with\n"); printf("set_mat(lp,2,1,0.5)\n"); if (!set_mat(lp,2,1,0.5)) ERROR(); print_lp(lp); press_ret(); printf("If we want to maximize the objective function use set_maxim(lp);\n"); set_maxim(lp); print_lp(lp); press_ret(); printf("after solving this gives us:\n"); solve(lp); print_objective(lp); print_solution(lp, 1); print_constraints(lp, 1); print_duals(lp); press_ret(); printf("Change the value of a rhs element with set_rh(lp,1,7.45)\n"); set_rh(lp,1,7.45); print_lp(lp); solve(lp); print_objective(lp); print_solution(lp, 1); print_constraints(lp, 1); press_ret(); printf("We change %s to the integer type with\n", get_col_name(lp, 4)); printf("set_int(lp, 4, TRUE)\n"); set_int(lp, 4, TRUE); print_lp(lp); printf("We set branch & bound debugging on with set_debug(lp, TRUE)\n"); set_debug(lp, TRUE); printf("and solve...\n"); press_ret(); solve(lp); print_objective(lp); print_solution(lp, 1); print_constraints(lp, 1); press_ret(); printf("We can set bounds on the variables with\n"); printf("set_lowbo(lp,2,2); & set_upbo(lp,4,5.3)\n"); set_lowbo(lp,2,2); set_upbo(lp,4,5.3); print_lp(lp); press_ret(); solve(lp); print_objective(lp); print_solution(lp, 1); print_constraints(lp, 1); press_ret(); printf("Now remove a constraint with del_constraint(lp, 1)\n"); del_constraint(lp,1); print_lp(lp); printf("Add an equality constraint\n"); { double row[] = {0, 1, 2, 1, 4}; if (!add_constraint(lp, row, EQ, 8)) ERROR(); } print_lp(lp); press_ret(); printf("A column can be added with:\n"); printf("add_column(lp,{3, 2, 2});\n"); { double col[] = {3, 2, 2}; if (!add_column(lp, col)) ERROR(); } print_lp(lp); press_ret(); printf("A column can be removed with:\n"); printf("del_column(lp,3);\n"); del_column(lp,3); print_lp(lp); press_ret(); printf("We can use automatic scaling with:\n"); printf("set_scaling(lp, SCALE_MEAN);\n"); set_scaling(lp, SCALE_MEAN); print_lp(lp); press_ret(); printf("The function get_mat(lprec *lp, int row, int column) returns a single\n"); printf("matrix element\n"); printf("%s get_mat(lp,2,3), get_mat(lp,1,1); gives\n","printf(\"%f %f\\n\","); printf("%f %f\n", (double)get_mat(lp,2,3), (double)get_mat(lp,1,1)); printf("Notice that get_mat returns the value of the original unscaled problem\n"); press_ret(); printf("If there are any integer type variables, then only the rows are scaled\n"); printf("set_scaling(lp, SCALE_MEAN);\n"); set_scaling(lp, SCALE_MEAN); printf("set_int(lp,3,FALSE);\n"); set_int(lp,3,FALSE); print_lp(lp); press_ret(); solve(lp); printf("print_objective, print_solution gives the solution to the original problem\n"); print_objective(lp); print_solution(lp, 1); print_constraints(lp, 1); press_ret(); printf("Scaling is turned off with unscale(lp);\n"); unscale(lp); print_lp(lp); press_ret(); printf("Now turn B&B debugging off and simplex tracing on with\n"); printf("set_debug(lp, FALSE), set_trace(lp, TRUE) and solve(lp)\n"); set_debug(lp, FALSE); set_trace(lp, TRUE); press_ret(); solve(lp); printf("Where possible, lp_solve will start at the last found basis\n"); printf("We can reset the problem to the initial basis with\n"); printf("default_basis(lp). Now solve it again...\n"); press_ret(); default_basis(lp); solve(lp); printf("It is possible to give variables and constraints names\n"); printf("set_row_name(lp,1,\"speed\"); & set_col_name(lp,2,\"money\")\n"); if (!set_row_name(lp,1,"speed")) ERROR(); if (!set_col_name(lp,2,"money")) ERROR(); print_lp(lp); printf("As you can see, all column and rows are assigned default names\n"); printf("If a column or constraint is deleted, the names shift place also:\n"); press_ret(); printf("del_column(lp,1);\n"); del_column(lp,1); print_lp(lp); press_ret(); write_lp(lp, "lp.lp"); delete_lp(lp); printf("An lp structure can be created and read from a .lp file\n"); printf("lp = read_lp(\"lp.lp\", TRUE);\n"); printf("The verbose option is used\n"); if ((lp = read_LP("lp.lp", TRUE, "test")) == NULL) ERROR(); press_ret(); printf("lp is now:\n"); print_lp(lp); press_ret(); printf("solution:\n"); set_debug(lp, TRUE); solve(lp); set_debug(lp, FALSE); print_objective(lp); print_solution(lp, 1); print_constraints(lp, 1); press_ret(); delete_lp(lp); #if defined FORTIFY Fortify_LeaveScope(); #endif return(0); } MSVMpack1.2/lp_solve_5.5/demo/cvc8.bat0000775000175000017500000000235311136663775016442 0ustar lauerlauer@echo off REM This batch file compiles the demo program with the Microsoft Visual C/C++ compiler under Windows set src=../shared/commonlib.c ../shared/mmio.c ../shared/myblas.c ../ini.c ../lp_rlp.c ../lp_crash.c ../bfp/bfp_LUSOL/lp_LUSOL.c ../bfp/bfp_LUSOL/LUSOL/lusol.c ../lp_Hash.c ../lp_lib.c ../lp_wlp.c ../lp_matrix.c ../lp_mipbb.c ../lp_MPS.c ../lp_params.c ../lp_presolve.c ../lp_price.c ../lp_pricePSE.c ../lp_report.c ../lp_scale.c ../lp_simplex.c ../lp_SOS.c ../lp_utils.c ../yacc_read.c ../lp_MDO.c ../colamd/colamd.c set c=cl REM determine platform (win32/win64) echo main(){printf("SET PLATFORM=win%%d\n", (int) (sizeof(void *)*8));}>platform.c %c% /nologo platform.c /Feplatform.exe del platform.c platform.exe >platform.bat del platform.exe call platform.bat del platform.bat if not exist bin\%PLATFORM%\*.* md bin\%PLATFORM% %c% -I.. -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd -I../shared /O2 /Zp8 /Gd -DWIN32 -D_CRT_SECURE_NO_DEPRECATE -D_CRT_NONSTDC_NO_DEPRECATE -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine -D_CRT_SECURE_NO_DEPRECATE -D_CRT_NONSTDC_NO_DEPRECATE demo.c %src% /Febin\%PLATFORM%\demo.exe if exist *.obj del *.obj set PLATFORM= MSVMpack1.2/lp_solve_5.5/demo/ccc.osx0000664000175000017500000000130010252644500016335 0ustar lauerlauersrc='../bfp/lp_MDO.c ../commonlib.c ../myblas.c ../colamd/colamd.c ../ini.c ../fortify.c ../lp_rlp.c ../lp_crash.c ../bfp/bfp_etaPFI/lp_etaPFI.c ../lp_Hash.c ../lp_lib.c ../lp_wlp.c ../lp_matrix.c ../lp_mipbb.c ../lp_MPS.c ../lp_params.c ../lp_presolve.c ../lp_price.c ../lp_pricePSE.c ../lp_report.c ../lp_scale.c ../lp_simplex.c demo.c ../lp_SOS.c ../lp_utils.c ../yacc_read.c' c=cc math=-lm def= if [ "$PLATFORM" = "SCO_UNIX" ] then def='-DLoadInverseLib=0 -DLoadLanguageLib=0 -D__HYPER=long' else dl=-ldl fi opts='-idirafter /usr/include/sys -O3 -DINTEGERTIME -Wno-long-double' $c -I.. -I../bfp -I../bfp/bfp_etaPFI -I../colamd $opts $def -DYY_NEVER_INTERACTIVE -DPARSER_LP $src -o demo $math $dl MSVMpack1.2/lp_solve_5.5/demo/demolib.vcproj0000664000175000017500000002416111141360236017723 0ustar lauerlauer MSVMpack1.2/lp_solve_5.5/demo/readme.txt0000664000175000017500000000053311141374614017063 0ustar lauerlauerThis directory contains the files to build a demo program To build the program under Windows with the Visual C/C++ compiler, use cvc6.bat (also works for VS.NET) To build the program under DOS/Windows with the gcc compiler, use cgcc.bat To build the program under Linux/Unix, use sh ccc To build the program under Mac OS X 10.3.5, use sh ccc.osx MSVMpack1.2/lp_solve_5.5/demo/demo.vcproj0000664000175000017500000002721611141356367017252 0ustar lauerlauer MSVMpack1.2/lp_solve_5.5/demo/cgcc.bat0000775000175000017500000000255111137106102016447 0ustar lauerlauer@echo off REM This batch file compiles the demo program with the gnu gcc compiler under DOS/Windows REM There are two ways to do that: use the lpsolve code directly or use that static library. set c=gcc REM determine platform (win32/win64) echo main(){printf("SET PLATFORM=win%%d\n", (int) (sizeof(void *)*8));}>platform.c %c% platform.c -o platform.exe del platform.c platform.exe >platform.bat del platform.exe call platform.bat del platform.bat if not exist bin\%PLATFORM%\*.* md bin\%PLATFORM% rem link lpsolve code with application set src=../lp_MDO.c ../shared/commonlib.c ../colamd/colamd.c ../shared/mmio.c ../shared/myblas.c ../ini.c ../lp_rlp.c ../lp_crash.c ../bfp/bfp_LUSOL/lp_LUSOL.c ../bfp/bfp_LUSOL/LUSOL/lusol.c ../lp_Hash.c ../lp_lib.c ../lp_wlp.c ../lp_matrix.c ../lp_mipbb.c ../lp_MPS.c ../lp_params.c ../lp_presolve.c ../lp_price.c ../lp_pricePSE.c ../lp_report.c ../lp_scale.c ../lp_simplex.c ../lp_SOS.c ../lp_utils.c ../yacc_read.c rem statically link lpsolve library rem set src=../lpsolve55/bin/%PLATFORM%/liblpsolve55.a %c% -DINLINE=static -I.. -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd -I../shared -O3 -DBFP_CALLMODEL=__stdcall -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine demo.c %src% -o bin\%PLATFORM%\demo.exe if exist *.o del *.o set PLATFORM= MSVMpack1.2/lp_solve_5.5/demo/cvc6.bat0000775000175000017500000000255511136663167016437 0ustar lauerlauer@echo off REM This batch file compiles the demo program with the Microsoft Visual C/C++ compiler under Windows set src=../shared/commonlib.c ../shared/mmio.c ../shared/myblas.c ../ini.c ../lp_rlp.c ../lp_crash.c ../bfp/bfp_LUSOL/lp_LUSOL.c ../bfp/bfp_LUSOL/LUSOL/lusol.c ../lp_Hash.c ../lp_lib.c ../lp_wlp.c ../lp_matrix.c ../lp_mipbb.c ../lp_MPS.c ../lp_params.c ../lp_presolve.c ../lp_price.c ../lp_pricePSE.c ../lp_report.c ../lp_scale.c ../lp_simplex.c ../lp_SOS.c ../lp_utils.c ../yacc_read.c ../lp_MDO.c ../colamd/colamd.c set c=cl REM determine platform (win32/win64) echo main(){printf("SET PLATFORM=win%%d\n", (int) (sizeof(void *)*8));}>platform.c %c% /nologo platform.c /Feplatform.exe del platform.c platform.exe >platform.bat del platform.exe call platform.bat del platform.bat if "%PLATFORM%" == "win32" goto ok1 echo. echo This batch file is entended for 32 bit compilation with MS Visual C 6 echo For newer versions use cvc8*.bat goto done :ok1 if not exist bin\%PLATFORM%\*.* md bin\%PLATFORM% %c% -I.. -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd -I../shared /O2 /Zp8 /Gd -DWIN32 -D_CRT_SECURE_NO_DEPRECATE -D_CRT_NONSTDC_NO_DEPRECATE -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine demo.c %src% -o bin\%PLATFORM%\demo.exe if exist *.obj del *.obj :done set PLATFORM= MSVMpack1.2/lp_solve_5.5/demo/cbcc32.bat0000775000175000017500000000161611137721060016616 0ustar lauerlauer@echo off REM This batch file compiles the demo program with the Borland C++ 5.5 compiler for Windows set src=../shared/commonlib.c ../shared/mmio.c ../shared/myblas.c ../ini.c ../lp_rlp.c ../lp_crash.c ../bfp/bfp_LUSOL/lp_LUSOL.c ../bfp/bfp_LUSOL/LUSOL/lusol.c ../lp_Hash.c ../lp_lib.c ../lp_wlp.c ../lp_matrix.c ../lp_mipbb.c ../lp_MPS.c ../lp_params.c ../lp_presolve.c ../lp_price.c ../lp_pricePSE.c ../lp_report.c ../lp_scale.c ../lp_simplex.c ../lp_SOS.c ../lp_utils.c ../yacc_read.c ../lp_MDO.c ../colamd/colamd.c set c=bcc32 -w-8004 -w-8057 set PLATFORM=win32 if not exist bin\%PLATFORM%\*.* md bin\%PLATFORM% %c% -I.. -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd -I../shared -a8 -DWIN32 -DYY_NEVER_INTERACTIVE=1 -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine demo.c -ebin\%PLATFORM%\demo.exe %src% if exist *.obj del *.obj set PLATFORM= MSVMpack1.2/lp_solve_5.5/demo/demo.sln0000664000175000017500000000230611130765423016527 0ustar lauerlauerMicrosoft Visual Studio Solution File, Format Version 10.00 # Visual Studio 2008 Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "demo", "demo.vcproj", "{CED6B89F-02F2-4DB1-8610-4F12A6D02F54}" EndProject Global GlobalSection(SolutionConfigurationPlatforms) = preSolution Debug|Win32 = Debug|Win32 Debug|x64 = Debug|x64 Release|Win32 = Release|Win32 Release|x64 = Release|x64 EndGlobalSection GlobalSection(ProjectConfigurationPlatforms) = postSolution {CED6B89F-02F2-4DB1-8610-4F12A6D02F54}.Debug|Win32.ActiveCfg = Debug|Win32 {CED6B89F-02F2-4DB1-8610-4F12A6D02F54}.Debug|Win32.Build.0 = Debug|Win32 {CED6B89F-02F2-4DB1-8610-4F12A6D02F54}.Debug|x64.ActiveCfg = Debug|x64 {CED6B89F-02F2-4DB1-8610-4F12A6D02F54}.Debug|x64.Build.0 = Debug|x64 {CED6B89F-02F2-4DB1-8610-4F12A6D02F54}.Release|Win32.ActiveCfg = Release|Win32 {CED6B89F-02F2-4DB1-8610-4F12A6D02F54}.Release|Win32.Build.0 = Release|Win32 {CED6B89F-02F2-4DB1-8610-4F12A6D02F54}.Release|x64.ActiveCfg = Release|x64 {CED6B89F-02F2-4DB1-8610-4F12A6D02F54}.Release|x64.Build.0 = Release|x64 EndGlobalSection GlobalSection(SolutionProperties) = preSolution HideSolutionNode = FALSE EndGlobalSection EndGlobal MSVMpack1.2/lp_solve_5.5/demo/ccc0000664000175000017500000000137310256611344015543 0ustar lauerlauersrc='../lp_MDO.c ../shared/commonlib.c ../colamd/colamd.c ../shared/mmio.c ../shared/myblas.c ../ini.c ../lp_rlp.c ../lp_crash.c ../bfp/bfp_LUSOL/lp_LUSOL.c ../bfp/bfp_LUSOL/LUSOL/lusol.c ../lp_Hash.c ../lp_lib.c ../lp_wlp.c ../lp_matrix.c ../lp_mipbb.c ../lp_MPS.c ../lp_params.c ../lp_presolve.c ../lp_price.c ../lp_pricePSE.c ../lp_report.c ../lp_scale.c ../lp_simplex.c ../lp_SOS.c ../lp_utils.c ../yacc_read.c' c=cc math=-lm def= if [ "$PLATFORM" = "SCO_UNIX" ] then def='-dy -K PIC -DNOLONGLONG' dl=-lc else dl=-ldl fi opts='-O3' $c -I.. -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd -I../shared $opts $def -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine demo.c $src -o demo $math $dl MSVMpack1.2/lp_solve_5.5/lp_report.h0000664000175000017500000000263411141374250016320 0ustar lauerlauer#ifndef HEADER_lp_report #define HEADER_lp_report #ifdef __cplusplus extern "C" { #endif /* General information functions */ char * __VACALL explain(lprec *lp, char *format, ...); void __VACALL report(lprec *lp, int level, char *format, ...); /* Prototypes for debugging and general data dumps */ void debug_print(lprec *lp, char *format, ...); void debug_print_solution(lprec *lp); void debug_print_bounds(lprec *lp, REAL *upbo, REAL *lowbo); void blockWriteLREAL(FILE *output, char *label, LREAL *vector, int first, int last); void blockWriteAMAT(FILE *output, const char *label, lprec* lp, int first, int last); void blockWriteBMAT(FILE *output, const char *label, lprec* lp, int first, int last); /* Model reporting headers */ void REPORT_objective(lprec *lp); void REPORT_solution(lprec *lp, int columns); void REPORT_constraints(lprec *lp, int columns); void REPORT_duals(lprec *lp); void REPORT_extended(lprec *lp); /* Other rarely used, but sometimes extremely useful reports */ void REPORT_constraintinfo(lprec *lp, char *datainfo); void REPORT_modelinfo(lprec *lp, MYBOOL doName, char *datainfo); void REPORT_lp(lprec *lp); MYBOOL REPORT_tableau(lprec *lp); void REPORT_scales(lprec *lp); MYBOOL REPORT_debugdump(lprec *lp, char *filename, MYBOOL livedata); MYBOOL REPORT_mat_mmsave(lprec *lp, char *filename, int *colndx, MYBOOL includeOF, char *infotext); #ifdef __cplusplus } #endif #endif /* HEADER_lp_report */ MSVMpack1.2/lp_solve_5.5/lp_price.c0000664000175000017500000020547711245564376016133 0ustar lauerlauer #include #include "commonlib.h" #include "lp_lib.h" #include "lp_report.h" #include "lp_pricePSE.h" #include "lp_price.h" #if libBLAS > 0 #include "myblas.h" #endif #ifdef FORTIFY # include "lp_fortify.h" #endif /* Simplex pricing utility module - w/interface for lp_solve v5.0+ ------------------------------------------------------------------------- Author: Kjell Eikland Contact: kjell.eikland@broadpark.no License terms: LGPL. Requires: lp_lib.h, commonlib.h Release notes: v1.0.0 1 July 2004 Routines extracted from lp_lib. v1.0.1 10 July 2004 Added comparison operators for determination of entering and leaving variables. Added routines for multiple and partial pricing and made corresponding changes to colprim and rowdual. v1.0.2 20 August 2004 Implemented relative pivot size control in rowprim and rowdual. v1.1.0 15 October 2004 Added dual long step logic. v1.1.1 22 October 2004 Added bound sort order to variable selections. v1.2.0 24 March 2005 Completed multiple pricing logic. ------------------------------------------------------------------------- */ /* Comparison operators for entering and leaving variables for both the primal and dual simplexes. The functions compare a candidate variable with an incumbent. */ int CMP_CALLMODEL compareImprovementVar(const pricerec *current, const pricerec *candidate) { register int result = COMP_PREFERNONE; register lprec *lp = current->lp; register REAL testvalue, margin = PREC_IMPROVEGAP; int currentcolno, currentvarno = current->varno, candidatecolno, candidatevarno = candidate->varno; MYBOOL isdual = candidate->isdual; if(isdual) { candidatevarno = lp->var_basic[candidatevarno]; currentvarno = lp->var_basic[currentvarno]; } candidatecolno = candidatevarno - lp->rows; currentcolno = currentvarno - lp->rows; /* Do pivot-based selection unless Bland's (first index) rule is active */ if(lp->_piv_rule_ != PRICER_FIRSTINDEX) { MYBOOL candbetter; /* Find the largest value - normalize in case of the dual, since constraint violation is expressed as a negative number. */ /* Use absolute test for "small numbers", relative otherwise */ testvalue = candidate->pivot; if(fabs(testvalue) < LIMIT_ABS_REL) testvalue -= current->pivot; else testvalue = my_reldiff(testvalue, current->pivot); if(isdual) testvalue = -testvalue; candbetter = (MYBOOL) (testvalue > 0); if(candbetter) { if(testvalue > margin) result = COMP_PREFERCANDIDATE; } #if 0 /* Give more opportunity to optimize on non-primary criteria */ else if (testvalue < -margin) #else /* Give reduced opportunity to optimize on non-primary criteria */ else if (testvalue < -lp->epsvalue) #endif result = COMP_PREFERINCUMBENT; #ifdef UseSortOnBound /* Extra selection criterion based on the variable's range; variable with - DUAL: small bound out; PRIMAL: large bound in */ if(result == COMP_PREFERNONE) { testvalue = lp->upbo[candidatevarno] - lp->upbo[currentvarno]; if(testvalue < -margin) result = COMP_PREFERINCUMBENT; else if(testvalue > margin) result = COMP_PREFERCANDIDATE; result = my_chsign(isdual, result); } #endif #ifdef UseSortOnColumnLength /* Prevent long columns from entering the basis */ if(result == COMP_PREFERNONE) { if(candidatecolno > 0) testvalue = mat_collength(lp->matA, candidatecolno) + (is_obj_in_basis(lp) && (lp->obj[candidatecolno] != 0) ? 1 : 0); else testvalue = 1; if(currentcolno > 0) testvalue -= mat_collength(lp->matA, currentcolno) + (is_obj_in_basis(lp) && (lp->obj[currentcolno] != 0) ? 1 : 0); else testvalue -= 1; if(testvalue > 0) result = COMP_PREFERINCUMBENT; else if(testvalue < 0) result = COMP_PREFERCANDIDATE; result = my_chsign(isdual, result); } #endif /* Select absolute best if the non-primary criteria failed to separate */ if((result == COMP_PREFERNONE) && candbetter) { result = COMP_PREFERCANDIDATE; goto Finish; } } /* Final tie-breakers */ if(result == COMP_PREFERNONE) { /* Add randomization tie-braker */ if(lp->piv_strategy & PRICE_RANDOMIZE) { result = my_sign(PRICER_RANDFACT - rand_uniform(lp, 1.0)); if(candidatevarno < currentvarno) result = -result; } /* Resolve ties via index ordinal */ if(result == COMP_PREFERNONE) { if(candidatevarno < currentvarno) result = COMP_PREFERCANDIDATE; else /* if(candidatevarno > currentvarno) */ result = COMP_PREFERINCUMBENT; if(lp->_piv_left_) result = -result; } } Finish: return( result ); } int CMP_CALLMODEL compareSubstitutionVar(const pricerec *current, const pricerec *candidate) { register int result = COMP_PREFERNONE; register lprec *lp = current->lp; register REAL testvalue = candidate->theta, margin = current->theta; MYBOOL isdual = candidate->isdual, candbetter; int currentcolno, currentvarno = current->varno, candidatecolno, candidatevarno = candidate->varno; if(!isdual) { candidatevarno = lp->var_basic[candidatevarno]; currentvarno = lp->var_basic[currentvarno]; } candidatecolno = candidatevarno - lp->rows; currentcolno = currentvarno - lp->rows; /* Compute the ranking test metric. */ if(isdual) { testvalue = fabs(testvalue); margin = fabs(margin); } /* Use absolute test for "small numbers", relative otherwise */ if(fabs(testvalue) < LIMIT_ABS_REL) testvalue -= margin; else testvalue = my_reldiff(testvalue, margin); /* Find if the new Theta is smaller or near equal (i.e. testvalue <= eps) compared to the previous best; ties will be broken by pivot size or index NB! The margin below is essential in maintaining primal/dual feasibility during the primal/dual simplex, respectively. Sometimes a small value prevents the selection of a suitable pivot, thereby weakening the numerical stability of some models */ margin = PREC_SUBSTFEASGAP; candbetter = (MYBOOL) (testvalue < 0); if(candbetter) { if(testvalue < -margin) result = COMP_PREFERCANDIDATE; } else if(testvalue > margin) result = COMP_PREFERINCUMBENT; /* Resolve a tie */ if(result == COMP_PREFERNONE) { REAL currentpivot = fabs(current->pivot), candidatepivot = fabs(candidate->pivot); /* Handle first index / Bland's rule specially */ if(lp->_piv_rule_ == PRICER_FIRSTINDEX) { #if 1 /* Special secondary selection by pivot size (limited stability protection) */ margin = candidate->epspivot; if((candidatepivot >= margin) && (currentpivot < margin)) result = COMP_PREFERCANDIDATE; #endif } else { /* General secondary selection based on pivot size */ #if 0 if(candidatepivot > MIN_STABLEPIVOT) testvalue = my_reldiff(testvalue, currentpivot); else #endif testvalue = candidatepivot - currentpivot; if(testvalue > margin) result = COMP_PREFERCANDIDATE; else if(testvalue < -margin) result = COMP_PREFERINCUMBENT; #ifdef UseSortOnBound /* Extra selection criterion based on the variable's range; variable with - PRIMAL: small bound out; DUAL: large bound in */ if(result == COMP_PREFERNONE) { testvalue = lp->upbo[candidatevarno] - lp->upbo[currentvarno]; if(testvalue < -margin) result = COMP_PREFERCANDIDATE; else if(testvalue > margin) result = COMP_PREFERINCUMBENT; result = my_chsign(isdual, result); } #endif #ifdef UseSortOnColumnLength /* Prevent long columns from entering the basis */ if(result == COMP_PREFERNONE) { if(candidatecolno > 0) testvalue = mat_collength(lp->matA, candidatecolno) + (is_obj_in_basis(lp) && (lp->obj[candidatecolno] != 0) ? 1 : 0); else testvalue = 1; if(currentcolno > 0) testvalue -= mat_collength(lp->matA, currentcolno) + (is_obj_in_basis(lp) && (lp->obj[currentcolno] != 0) ? 1 : 0); else testvalue -= 1; if(testvalue > 0) result = COMP_PREFERCANDIDATE; else if(testvalue < 0) result = COMP_PREFERINCUMBENT; result = my_chsign(isdual, result); } #endif } } /* Select absolute best if the non-primary criteria failed to separate */ if((result == COMP_PREFERNONE) && candbetter) { result = COMP_PREFERCANDIDATE; goto Finish; } /* Final tie-breakers */ if(result == COMP_PREFERNONE) { /* Add randomization tie-braker */ if(lp->piv_strategy & PRICE_RANDOMIZE) { result = my_sign(PRICER_RANDFACT - rand_uniform(lp, 1.0)); if(candidatevarno < currentvarno) result = -result; } /* Resolve ties via index ordinal (also prefers slacks over user variables) */ if(result == COMP_PREFERNONE) { if(candidatevarno < currentvarno) result = COMP_PREFERCANDIDATE; else /* if(candidatevarno > currentvarno) */ result = COMP_PREFERINCUMBENT; if(lp->_piv_left_) result = -result; } } Finish: return( result ); } int CMP_CALLMODEL compareBoundFlipVar(const pricerec *current, const pricerec *candidate) { register REAL testvalue, margin; register int result = COMP_PREFERNONE; register lprec *lp = current->lp; MYBOOL candbetter; int currentvarno = current->varno, candidatevarno = candidate->varno; if(!current->isdual) { candidatevarno = lp->var_basic[candidatevarno]; currentvarno = lp->var_basic[currentvarno]; } /* Compute the ranking test metric. */ testvalue = candidate->theta; margin = current->theta; if(candidate->isdual) { testvalue = fabs(testvalue); margin = fabs(margin); } if(fabs(margin) < LIMIT_ABS_REL) testvalue -= margin; else testvalue = my_reldiff(testvalue, margin); /* Find if the new Theta is smaller or near equal (i.e. testvalue <= eps) compared to the previous best; ties will be broken by pivot size or index */ margin = PREC_SUBSTFEASGAP; candbetter = (MYBOOL) (testvalue < 0); if(candbetter) { if(testvalue < -margin) result = COMP_PREFERCANDIDATE; } else if(testvalue > margin) result = COMP_PREFERINCUMBENT; /* Resolve a tie */ if(result == COMP_PREFERNONE) { /* Tertiary selection based on priority for large pivot sizes */ if(result == COMP_PREFERNONE) { REAL currentpivot = fabs(current->pivot), candidatepivot = fabs(candidate->pivot); if(candidatepivot > currentpivot+margin) result = COMP_PREFERCANDIDATE; else if(candidatepivot < currentpivot-margin) result = COMP_PREFERINCUMBENT; } /* Secondary selection based on priority for narrow-bounded variables */ if(result == COMP_PREFERNONE) result = compareREAL(&(lp->upbo[currentvarno]), &(lp->upbo[candidatevarno])); } /* Select absolute best if the non-primary criteria failed to separate */ if((result == COMP_PREFERNONE) && candbetter) { result = COMP_PREFERCANDIDATE; goto Finish; } /* Quaternary selection by index value */ if(result == COMP_PREFERNONE) { if(candidatevarno < currentvarno) result = COMP_PREFERCANDIDATE; else result = COMP_PREFERINCUMBENT; if(lp->_piv_left_) result = -result; } Finish: return( result ); } /* Validity operators for entering and leaving columns for both the primal and dual simplex. All candidates must satisfy these tests to qualify to be allowed to be a subject for the comparison functions/operators. */ STATIC MYBOOL validImprovementVar(pricerec *candidate) { register REAL candidatepivot = fabs(candidate->pivot); #ifdef Paranoia return( (MYBOOL) ((candidate->varno > 0) && (candidatepivot > candidate->lp->epsvalue)) ); #else return( (MYBOOL) (candidatepivot > candidate->lp->epsvalue) ); #endif } STATIC MYBOOL validSubstitutionVar(pricerec *candidate) { register lprec *lp = candidate->lp; register REAL theta = (candidate->isdual ? fabs(candidate->theta) : candidate->theta); #ifdef Paranoia if(candidate->varno <= 0) return( FALSE ); else #endif if(fabs(candidate->pivot) >= lp->infinite) return( (MYBOOL) (theta < lp->infinite) ); else return( (MYBOOL) ((theta < lp->infinite) && (fabs(candidate->pivot) >= candidate->epspivot)) ); } int CMP_CALLMODEL compareImprovementQS(const UNIONTYPE QSORTrec *current, const UNIONTYPE QSORTrec *candidate) { return( compareImprovementVar((pricerec *) current->pvoidint2.ptr, (pricerec *) candidate->pvoidint2.ptr) ); } int CMP_CALLMODEL compareSubstitutionQS(const UNIONTYPE QSORTrec *current, const UNIONTYPE QSORTrec *candidate) { return( compareBoundFlipVar((pricerec *) current->pvoidint2.ptr, (pricerec *) candidate->pvoidint2.ptr) ); /* return( compareSubstitutionVar((pricerec *) current->self, (pricerec *) candidate->self) ); */ } /* Function to add a valid pivot candidate into the specified list */ STATIC int addCandidateVar(pricerec *candidate, multirec *multi, findCompare_func findCompare, MYBOOL allowSortedExpand) { int insertpos, delta = 1; pricerec *targetrec; /* Find the insertion point (if any) */ if((multi->freeList[0] == 0) || (multi->sorted && allowSortedExpand) || (candidate->isdual && (multi->used == 1) && ((multi->step_last >= multi->epszero) || multi_truncatingvar(multi, ((pricerec *) (multi->sortedList[0].pvoidreal.ptr))->varno))) ) { UNIONTYPE QSORTrec searchTarget; /* Make sure that the list is sorted before the search for an insertion point */ if((multi->freeList[0] == 0) && !multi->sorted) { multi->sorted = QS_execute(multi->sortedList, multi->used, findCompare, &insertpos); multi->dirty = (MYBOOL) (insertpos > 0); } /* Perform the search */ searchTarget.pvoidint2.ptr = (void *) candidate; insertpos = sizeof(searchTarget); insertpos = findIndexEx(&searchTarget, multi->sortedList-delta, multi->used, delta, insertpos, findCompare, TRUE); if(insertpos > 0) return( -1 ); insertpos = -insertpos - delta; /* Check if the candidate is worse than the worst of the list */ if(((insertpos >= multi->size) && (multi->freeList[0] == 0)) || ((insertpos == multi->used) && (!allowSortedExpand || (multi->step_last >= multi->epszero)))) return( -1 ); #ifdef Paranoia /* Do validation */ if((insertpos < 0) || (insertpos > multi->used)) return( -1 ); #endif /* Define the target for storing the candidate; Case 1: List is full and we must discard the previously worst candidate Case 2: List is not full and we simply use the next free position */ if(multi->freeList[0] == 0) targetrec = (pricerec *) multi->sortedList[multi->used-1].pvoidreal.ptr; else { delta = multi->freeList[0]--; delta = multi->freeList[delta]; targetrec = &(multi->items[delta]); } } else { delta = multi->freeList[0]--; delta = multi->freeList[delta]; targetrec = &(multi->items[delta]); insertpos = multi->used; } /* Insert the new candidate record in the data store */ MEMCOPY(targetrec, candidate, 1); /* Store the pointer data and handle tree cases: Case 1: The list is unsorted and not full; simply append pointer to list, Case 2: The list is sorted and full; insert the pointer by discarding previous last, Case 3: The list is sorted and not full; shift the inferior items down, and increment count */ if((multi->used < multi->size) && (insertpos >= multi->used)) { QS_append(multi->sortedList, insertpos, targetrec); multi->used++; } else { if(multi->used == multi->size) QS_insert(multi->sortedList, insertpos, targetrec, multi->size-1); /* Discard previous last */ else { QS_insert(multi->sortedList, insertpos, targetrec, multi->used); /* Keep previous last */ multi->used++; } } multi->active = insertpos; #ifdef Paranoia if((insertpos >= multi->size) || (insertpos >= multi->used)) report(multi->lp, SEVERE, "addCandidateVar: Insertion point beyond limit!\n"); #endif return( insertpos ); } STATIC MYBOOL findImprovementVar(pricerec *current, pricerec *candidate, MYBOOL collectMP, int *candidatecount) /* PRIMAL: Find a variable to enter the basis DUAL: Find a variable to leave the basis Allowed variable set: Any pivot PRIMAL:larger or DUAL:smaller than threshold value of 0 */ { MYBOOL Action = FALSE, #ifdef ExtractedValidityTest Accept = TRUE; #else /* Check for validity and compare result with previous best */ Accept = validImprovementVar(candidate); #endif if(Accept) { if(candidatecount != NULL) (*candidatecount)++; if(collectMP) { if(addCandidateVar(candidate, current->lp->multivars, (findCompare_func *) compareImprovementQS, FALSE) < 0) return(Action); } if(current->varno > 0) Accept = (MYBOOL) (compareImprovementVar(current, candidate) > 0); } /* Apply candidate if accepted */ if(Accept) { (*current) = *candidate; /* Force immediate acceptance for Bland's rule using the primal simplex */ if(!candidate->isdual) Action = (MYBOOL) (candidate->lp->_piv_rule_ == PRICER_FIRSTINDEX); } return(Action); } /* Bound flip variable accumulation routine */ STATIC MYBOOL collectMinorVar(pricerec *candidate, multirec *longsteps, MYBOOL isphase2, MYBOOL isbatch) { int inspos; /* 1. Check for ratio and pivot validity (to have the extra flexibility that all bound-flip candidates are also possible as basis-entering variables */ if(!validSubstitutionVar(candidate)) return( FALSE ); /* 2. If the free-list is empty we need to see if we have a better candidate, and for this the candidate list has to be sorted by merit */ if(!isbatch && !longsteps->sorted && (longsteps->used > 1) && ((longsteps->freeList[0] == 0) || multi_truncatingvar(longsteps, candidate->varno) || (longsteps->step_last >= longsteps->epszero) )) { longsteps->sorted = QS_execute(longsteps->sortedList, longsteps->used, (findCompare_func *) compareSubstitutionQS, &inspos); longsteps->dirty = (MYBOOL) (inspos > 0); if(longsteps->dirty) multi_recompute(longsteps, 0, isphase2, TRUE); } /* 3. Now handle three cases... - Add to the list when the list is not full and there is opportunity for improvement, - Check if we should replace an incumbent when the list is full, - Check if we should replace an incumbent when the list is not full, there is no room for improvement, but the current candidate is better than an incumbent. */ inspos = addCandidateVar(candidate, longsteps, (findCompare_func *) compareSubstitutionQS, TRUE); /* 4. Recompute steps and objective, and (if relevant) determine if we may be suboptimal in relation to an incumbent MILP solution. */ return( (MYBOOL) (inspos >= 0) && ((isbatch == TRUE) || multi_recompute(longsteps, inspos, isphase2, TRUE)) ); } STATIC MYBOOL findSubstitutionVar(pricerec *current, pricerec *candidate, int *candidatecount) /* PRIMAL: Find a variable to leave the basis DUAL: Find a variable to enter the basis Allowed variable set: "Equal-valued" smallest thetas! */ { MYBOOL Action = FALSE, #ifdef ExtractedValidityTest Accept = TRUE; #else /* Check for validity and comparison result with previous best */ Accept = validSubstitutionVar(candidate); #endif if(Accept) { if(candidatecount != NULL) (*candidatecount)++; if(current->varno != 0) Accept = (MYBOOL) (compareSubstitutionVar(current, candidate) > 0); } /* Apply candidate if accepted */ if(Accept) { (*current) = *candidate; /* Force immediate acceptance for Bland's rule using the dual simplex */ #ifdef ForceEarlyBlandRule if(candidate->isdual) Action = (MYBOOL) (candidate->lp->_piv_rule_ == PRICER_FIRSTINDEX); #endif } return(Action); } /* Partial pricing management routines */ STATIC partialrec *partial_createBlocks(lprec *lp, MYBOOL isrow) { partialrec *blockdata; blockdata = (partialrec *) calloc(1, sizeof(*blockdata)); blockdata->lp = lp; blockdata->blockcount = 1; blockdata->blocknow = 1; blockdata->isrow = isrow; return(blockdata); } STATIC int partial_countBlocks(lprec *lp, MYBOOL isrow) { partialrec *blockdata = IF(isrow, lp->rowblocks, lp->colblocks); if(blockdata == NULL) return( 1 ); else return( blockdata->blockcount ); } STATIC int partial_activeBlocks(lprec *lp, MYBOOL isrow) { partialrec *blockdata = IF(isrow, lp->rowblocks, lp->colblocks); if(blockdata == NULL) return( 1 ); else return( blockdata->blocknow ); } STATIC void partial_freeBlocks(partialrec **blockdata) { if((blockdata == NULL) || (*blockdata == NULL)) return; FREE((*blockdata)->blockend); FREE((*blockdata)->blockpos); FREE(*blockdata); } /* Function to provide for left-right or right-left scanning of entering/leaving variables; note that *end must have been initialized by the calling routine! */ STATIC void makePriceLoop(lprec *lp, int *start, int *end, int *delta) { int offset = is_piv_mode(lp, PRICE_LOOPLEFT); if((offset) || (((lp->total_iter+offset) % 2 == 0) && is_piv_mode(lp, PRICE_LOOPALTERNATE))) { *delta = -1; /* Step backwards - "left" */ swapINT(start, end); lp->_piv_left_ = TRUE; } else { *delta = 1; /* Step forwards - "right" */ lp->_piv_left_ = FALSE; } } /* Routine to verify accuracy of the current basis factorization */ STATIC MYBOOL serious_facterror(lprec *lp, REAL *bvector, int maxcols, REAL tolerance) { int i, j, ib, ie, nz, nc; REAL sum, tsum = 0, err = 0; MATrec *mat = lp->matA; if(bvector == 0) bvector = lp->bsolveVal; nc =0; nz = 0; for(i = 1; (i <= lp->rows) && (nc <= maxcols); i++) { /* Do we have a non-slack variable? (we choose to skip slacks, since they have "natural" good accuracy properties) */ j = lp->var_basic[i] - lp->rows; if(j <= 0) continue; nc++; /* Compute cross product for basic, non-slack column */ ib = mat->col_end[j-1]; ie = mat->col_end[j]; nz += ie - ib; sum = get_OF_active(lp, j+lp->rows, bvector[0]); for(; ib < ie; ib++) sum += COL_MAT_VALUE(ib)*bvector[COL_MAT_ROWNR(ib)]; /* Catch high precision early, so we don't to uneccessary work */ tsum += sum; SETMAX(err, fabs(sum)); if((tsum / nc > tolerance / 100) && (err < tolerance / 100)) break; } err /= mat->infnorm; return( (MYBOOL) (err >= tolerance) ); } /* Computation of reduced costs */ STATIC void update_reducedcosts(lprec *lp, MYBOOL isdual, int leave_nr, int enter_nr, REAL *prow, REAL *drow) { /* "Fast" update of the dual reduced cost vector; note that it must be called after the pivot operation and only applies to a major "true" iteration */ int i; REAL hold; if(isdual) { hold = -drow[enter_nr]/prow[enter_nr]; for(i=1; i <= lp->sum; i++) if(!lp->is_basic[i]) { if(i == leave_nr) drow[i] = hold; else { drow[i] += hold*prow[i]; my_roundzero(drow[i], lp->epsmachine); } } } else report(lp, SEVERE, "update_reducedcosts: Cannot update primal reduced costs!\n"); } STATIC void compute_reducedcosts(lprec *lp, MYBOOL isdual, int row_nr, int *coltarget, MYBOOL dosolve, REAL *prow, int *nzprow, REAL *drow, int *nzdrow, int roundmode) { REAL epsvalue = lp->epsvalue; /* Any larger value can produce a suboptimal result */ roundmode |= MAT_ROUNDRC; if(isdual) { bsolve_xA2(lp, coltarget, row_nr, prow, epsvalue, nzprow, /* Calculate net sensitivity given a leaving variable */ 0, drow, epsvalue, nzdrow, /* Calculate the net objective function values */ roundmode); } else { REAL *bVector; #if 1 /* Legacy mode, that is possibly a little faster */ if((lp->multivars == NULL) && (lp->P1extraDim == 0)) bVector = drow; else #endif bVector = lp->bsolveVal; if(dosolve) { bsolve(lp, 0, bVector, lp->bsolveIdx, epsvalue*DOUBLEROUND, 1.0); if(!isdual && (row_nr == 0) && (lp->improve & IMPROVE_SOLUTION) && !refactRecent(lp) && serious_facterror(lp, bVector, lp->rows, lp->epsvalue)) set_action(&lp->spx_action, ACTION_REINVERT); } prod_xA(lp, coltarget, bVector, lp->bsolveIdx, epsvalue, 1.0, drow, nzdrow, roundmode); } } /* Primal: Prevent acceptance of an entering variable when the magnitude of other candidates is also very small. Dual: Prevent acceptance of a leaving variable when the magnitude of other candidates is also very small. Both of these cases are associated with numerical stalling, which we could argue should be detected and handled by the stalling monitor routine. */ STATIC MYBOOL verify_stability(lprec *lp, MYBOOL isprimal, REAL xfeas, REAL sfeas, int nfeas) { MYBOOL testOK = TRUE; return( testOK ); #if 1 /* Try to make dual feasibility as tight as possible */ if(!isprimal) /* if(lp->P1extraVal == 0) */ { xfeas /= (1+lp->rhsmax); sfeas /= (1+lp->rhsmax); } #endif xfeas = fabs(xfeas); /* Maximum (positive) infeasibility */ /* if(xfeas < lp->epspivot) { */ if(xfeas < lp->epssolution) { REAL f; sfeas = fabs(sfeas); /* Make sum of infeasibilities positive */ xfeas = (sfeas-xfeas)/nfeas; /* Average "residual" feasibility */ f = 1 + log10((REAL) nfeas); /* Some numerical complexity scalar */ /* Numerical errors can interact to cause non-convergence, and the idea is to relax the tolerance to account for this and only marginally weakening the (user-specified) tolerance. */ if((sfeas-xfeas) < f*lp->epsprimal) testOK = FALSE; } return( testOK ); } /* Find an entering column for the case that the specified basic variable is fixed or zero - typically used for artificial variable elimination */ STATIC int find_rowReplacement(lprec *lp, int rownr, REAL *prow, int *nzprow) /* The logic in this section generally follows Chvatal: Linear Programming, p. 130 Basically, the function is a specialized coldual(). */ { int i, bestindex; REAL bestvalue; /* Solve for "local reduced cost" */ set_action(&lp->piv_strategy, PRICE_FORCEFULL); compute_reducedcosts(lp, TRUE, rownr, NULL, TRUE, prow, nzprow, NULL, NULL, MAT_ROUNDDEFAULT); clear_action(&lp->piv_strategy, PRICE_FORCEFULL); /* Find a suitably non-singular variable to enter ("most orthogonal") */ bestindex = 0; bestvalue = 0; for(i = 1; i <= lp->sum-abs(lp->P1extraDim); i++) { if(!lp->is_basic[i] && !is_fixedvar(lp, i) && (fabs(prow[i]) > bestvalue)) { bestindex = i; bestvalue = fabs(prow[i]); } } /* Prepare to update inverse and pivot/iterate (compute Bw=a) */ if(i > lp->sum-abs(lp->P1extraDim)) bestindex = 0; else fsolve(lp, bestindex, prow, nzprow, lp->epsmachine, 1.0, TRUE); return( bestindex ); } /* Find the primal simplex entering non-basic column variable */ STATIC int colprim(lprec *lp, REAL *drow, int *nzdrow, MYBOOL skipupdate, int partialloop, int *candidatecount, MYBOOL updateinfeas, REAL *xviol) { int i, ix, iy, iz, ninfeas, nloop = 0; REAL f, sinfeas, xinfeas, epsvalue = lp->epsdual; pricerec current, candidate; MYBOOL collectMP = FALSE; int *coltarget = NULL; /* Identify pivot column according to pricing strategy; set entering variable initial threshold reduced cost value to "0" */ current.pivot = lp->epsprimal; /* Minimum acceptable improvement */ current.varno = 0; current.lp = lp; current.isdual = FALSE; candidate.lp = lp; candidate.isdual = FALSE; *candidatecount = 0; /* Update local value of pivot setting and determine active multiple pricing set */ lp->_piv_rule_ = get_piv_rule(lp); doLoop: nloop++; if((lp->multivars != NULL) && ((lp->simplex_mode & SIMPLEX_PRIMAL_PRIMAL) != 0)) { collectMP = multi_mustupdate(lp->multivars); if(collectMP) { multi_restart(lp->multivars); coltarget = NULL; } else coltarget = multi_indexSet(lp->multivars, FALSE); } /* Compute reduced costs c - c*Inv(B), if necessary (i.e. the previous iteration was not a "minor" iteration/bound flip) */ if(!skipupdate) { #ifdef UsePrimalReducedCostUpdate /* Recompute from scratch only at the beginning, otherwise update */ if((lp->current_iter > 0) && (refactRecent(lp) == AUTOMATIC)) #endif compute_reducedcosts(lp, FALSE, 0, coltarget, (MYBOOL) ((nloop <= 1) || (partialloop > 1)), NULL, NULL, drow, nzdrow, MAT_ROUNDDEFAULT); } /* Loop over active partial column set; we presume that reduced costs have only been updated for columns in the active partial range. */ ix = 1; iy = nzdrow[0]; ninfeas = 0; xinfeas = 0; sinfeas = 0; makePriceLoop(lp, &ix, &iy, &iz); iy *= iz; for(; ix*iz <= iy; ix += iz) { i = nzdrow[ix]; #if 0 /* Not necessary since we masked them out in compute_reducedcosts() */ if(i > lp->sum-abs(lp->P1extraDim)) continue; #endif /* Check if the pivot candidate is on the block-list */ if(lp->rejectpivot[0] > 0) { int kk; for(kk = 1; (kk <= lp->rejectpivot[0]) && (i != lp->rejectpivot[kk]); kk++); if(kk <= lp->rejectpivot[0]) continue; } /* Retrieve the applicable reduced cost - threshold should not be smaller than 0 */ f = my_chsign(lp->is_lower[i], drow[i]); if(f <= epsvalue) continue; /* Find entering variable according to strategy (largest positive f) */ ninfeas++; SETMAX(xinfeas, f); sinfeas += f; candidate.pivot = normalizeEdge(lp, i, f, FALSE); candidate.varno = i; if(findImprovementVar(¤t, &candidate, collectMP, candidatecount)) break; } /* Check if we should loop again after a multiple pricing update */ if(lp->multivars != NULL) { if(collectMP) { if(!lp->multivars->sorted) lp->multivars->sorted = QS_execute(lp->multivars->sortedList, lp->multivars->used, (findCompare_func *) compareImprovementQS, NULL); coltarget = multi_indexSet(lp->multivars, TRUE); } else if((current.varno == 0) && (lp->multivars->retries == 0)) { ix = partial_blockStart(lp, FALSE); iy = partial_blockEnd(lp, FALSE); lp->multivars->used = 0; lp->multivars->retries++; goto doLoop; } /* Shrink the candidate list */ lp->multivars->retries = 0; if(current.varno != 0) multi_removevar(lp->multivars, current.varno); } /* Check for optimality */ if(xviol != NULL) *xviol = xinfeas; if(updateinfeas) lp->suminfeas = fabs(sinfeas); if((lp->multivars == NULL) && (current.varno > 0) && !verify_stability(lp, TRUE, xinfeas, sinfeas, ninfeas)) current.varno = 0; /* Produce statistics */ if(lp->spx_trace) { if(current.varno > 0) report(lp, DETAILED, "colprim: Column %d reduced cost = " RESULTVALUEMASK "\n", current.varno, current.pivot); else report(lp, DETAILED, "colprim: No positive reduced costs found, optimality!\n"); } return( current.varno ); } /* colprim */ /* Find the primal simplex leaving basic column variable */ STATIC int rowprim(lprec *lp, int colnr, LREAL *theta, REAL *pcol, int *nzpcol, MYBOOL forceoutEQ, REAL *xviol) { int i, ii, iy, iz, Hpass, k, *nzlist; LREAL f, savef; REAL Heps, Htheta, Hlimit, epsvalue, epspivot, p = 0.0; pricerec current, candidate; MYBOOL isupper = !lp->is_lower[colnr], HarrisTwoPass = FALSE; /* Update local value of pivot setting */ lp->_piv_rule_ = get_piv_rule(lp); if(nzpcol == NULL) nzlist = (int *) mempool_obtainVector(lp->workarrays, lp->rows+1, sizeof(*nzlist)); else nzlist = nzpcol; /* Find unconditional non-zeros and optionally compute relative size of epspivot */ epspivot = lp->epspivot; epsvalue = lp->epsvalue; Hlimit = 0; Htheta = 0; k = 0; for(i = 1; i <= lp->rows; i++) { p = fabs(pcol[i]); if(p > Hlimit) Hlimit = p; if(p > epsvalue) { k++; nzlist[k] = i; SETMAX(Htheta, p); } #ifdef Paranoia else { if(lp->spx_trace) report(lp, FULL, "rowprim: Row %d with pivot " RESULTVALUEMASK " rejected as too small\n", i, p); } #endif } if(xviol != NULL) *xviol = Htheta; Htheta = 0; /* Update non-zero list based on the new pivot threshold */ #ifdef UseRelativePivot_Primal /* epspivot *= sqrt(lp->matA->dynrange) / lp->matA->infnorm; */ epspivot /= MAX(1, sqrt(lp->matA->colmax[colnr])); iy = k; k = 0; p = 0; for(ii = 1; ii <= iy; ii++) { i = nzlist[ii]; p = fabs(pcol[i]); /* Compress the list of valid alternatives, if appropriate */ if(p > epspivot) { k++; nzlist[k] = i; } #ifdef Paranoia else { if(lp->spx_trace) report(lp, FULL, "rowprim: Row %d with pivot " RESULTVALUEMASK " rejected as too small\n", i, p); } #endif } #endif /* Initialize counters */ nzlist[0] = k; k = 0; Retry: k++; HarrisTwoPass = is_piv_mode(lp, PRICE_HARRISTWOPASS); if(HarrisTwoPass) Hpass = 1; else Hpass = 2; current.theta = lp->infinite; current.pivot = 0; current.varno = 0; current.isdual = FALSE; current.epspivot = epspivot; current.lp = lp; candidate.epspivot = epspivot; candidate.isdual = FALSE; candidate.lp = lp; savef = 0; for(; Hpass <= 2; Hpass++) { Htheta = lp->infinite; if(Hpass == 1) { Hlimit = lp->infinite; /* Don't apply any limit in the first pass */ Heps = epspivot/lp->epsprimal; /* Scaled to lp->epsprimal used in compute_theta() */ } else { Hlimit = current.theta; /* This is the smallest Theta of the first pass */ Heps = 0.0; } current.theta = lp->infinite; current.pivot = 0; current.varno = 0; savef = 0; ii = 1; iy = nzlist[0]; makePriceLoop(lp, &ii, &iy, &iz); iy *= iz; for(; ii*iz <= iy; ii += iz) { i = nzlist[ii]; f = pcol[i]; candidate.theta = f; candidate.pivot = f; candidate.varno = i; /*i =*/ compute_theta(lp, i, &candidate.theta, isupper, my_if(lp->upbo[lp->var_basic[i]] < lp->epsprimal, Heps/10, Heps), TRUE); if(fabs(candidate.theta) >= lp->infinite) { savef = f; candidate.theta = 2*lp->infinite; continue; } /* Find the candidate leaving variable according to strategy (smallest theta) */ if((Hpass == 2) && (candidate.theta > Hlimit)) continue; /* Give a slight preference to fixed variables (mainly equality slacks) */ if(forceoutEQ) { p = candidate.pivot; if(lp->upbo[lp->var_basic[i]] < lp->epsprimal) { /* Give an extra early boost to equality slack elimination, if specified */ if(forceoutEQ == AUTOMATIC) candidate.pivot *= 1.0+lp->epspivot; else candidate.pivot *= 10.0; } } if(HarrisTwoPass) { f = candidate.theta; if(Hpass == 2) candidate.theta = 1; if(findSubstitutionVar(¤t, &candidate, NULL)) break; if((Hpass == 2) && (current.varno == candidate.varno)) Htheta = f; } else if(findSubstitutionVar(¤t, &candidate, NULL)) break; /* Restore temporarily modified pivot */ if(forceoutEQ && (current.varno == candidate.varno)) current.pivot = p; } } if(HarrisTwoPass) current.theta = Htheta; /* Handle case of no available leaving variable */ if(current.varno == 0) { if(lp->upbo[colnr] >= lp->infinite) { /* Optionally try again with reduced pivot threshold level */ if(k < 2) { epspivot = epspivot / 10; goto Retry; } } else { #if 1 i = 1; while((pcol[i] >= 0) && (i <= lp->rows)) i++; if(i > lp->rows) { /* Empty column with upper bound! */ lp->is_lower[colnr] = !lp->is_lower[colnr]; /* lp->is_lower[colnr] = FALSE; */ lp->rhs[0] += lp->upbo[colnr]*pcol[0]; } else /* if(pcol[i]<0) */ { current.varno = i; } #endif } } else if(current.theta >= lp->infinite) { report(lp, IMPORTANT, "rowprim: Numeric instability pcol[%d] = %g, rhs[%d] = %g, upbo = %g\n", current.varno, savef, current.varno, lp->rhs[current.varno], lp->upbo[lp->var_basic[current.varno]]); } /* Return working array to pool */ if(nzpcol == NULL) mempool_releaseVector(lp->workarrays, (char *) nzlist, FALSE); if(lp->spx_trace) report(lp, DETAILED, "row_prim: %d, pivot size = " RESULTVALUEMASK "\n", current.varno, current.pivot); /* *theta = current.theta; */ *theta = fabs(current.theta); return(current.varno); } /* rowprim */ /* Find the dual simplex leaving basic variable */ STATIC int rowdual(lprec *lp, REAL *rhvec, MYBOOL forceoutEQ, MYBOOL updateinfeas, REAL *xviol) { int k, i, iy, iz, ii, ninfeas; register REAL rh; REAL up, lo = 0, epsvalue, sinfeas, xinfeas; pricerec current, candidate; MYBOOL collectMP = FALSE; /* Initialize */ if(rhvec == NULL) rhvec = lp->rhs; epsvalue = lp->epsdual; current.pivot = -epsvalue; /* Initialize leaving variable threshold; "less than 0" */ current.theta = 0; current.varno = 0; current.isdual = TRUE; current.lp = lp; candidate.isdual = TRUE; candidate.lp = lp; /* Loop over active partial row set */ if(is_action(lp->piv_strategy, PRICE_FORCEFULL)) { k = 1; iy = lp->rows; } else { k = partial_blockStart(lp, TRUE); iy = partial_blockEnd(lp, TRUE); } ninfeas = 0; xinfeas = 0; sinfeas = 0; makePriceLoop(lp, &k, &iy, &iz); iy *= iz; for(; k*iz <= iy; k += iz) { /* Map loop variable to target */ i = k; /* Check if the pivot candidate is on the block-list */ if(lp->rejectpivot[0] > 0) { int kk; for(kk = 1; (kk <= lp->rejectpivot[0]) && (i != lp->rejectpivot[kk]); kk++); if(kk <= lp->rejectpivot[0]) continue; } /* Set local variables - express violation as a negative number */ ii = lp->var_basic[i]; up = lp->upbo[ii]; lo = 0; rh = rhvec[i]; if(rh > up) rh = up - rh; else rh -= lo; up -= lo; /* Analyze relevant constraints ... KE version skips uninteresting alternatives and gives a noticeable speedup */ /* if((rh < -epsvalue*sqrt(lp->matA->rowmax[i])) || */ if((rh < -epsvalue) || ((forceoutEQ == TRUE) && (up < epsvalue))) { /* It causes instability to remove the "TRUE" test */ /* Accumulate stats */ ninfeas++; SETMIN(xinfeas, rh); sinfeas += rh; /* Give a slight preference to fixed variables (mainly equality slacks) */ if(up < epsvalue) { /* Break out immediately if we are directed to force slacks out of the basis */ if(forceoutEQ == TRUE) { current.varno = i; current.pivot = -1; break; } /* Give an extra early boost to equality slack elimination, if specified */ if(forceoutEQ == AUTOMATIC) rh *= 10.0; else /* .. or just the normal. marginal boost */ rh *= 1.0+lp->epspivot; } /* Select leaving variable according to strategy (the most negative/largest violation) */ candidate.pivot = normalizeEdge(lp, i, rh, TRUE); candidate.varno = i; if(findImprovementVar(¤t, &candidate, collectMP, NULL)) break; } } /* Verify infeasibility */ if(updateinfeas) lp->suminfeas = fabs(sinfeas); if((ninfeas > 1) && !verify_stability(lp, FALSE, xinfeas, sinfeas, ninfeas)) { report(lp, IMPORTANT, "rowdual: Check for reduced accuracy and tolerance settings.\n"); current.varno = 0; } /* Produce statistics */ if(lp->spx_trace) { report(lp, NORMAL, "rowdual: Infeasibility sum " RESULTVALUEMASK " in %7d constraints.\n", sinfeas, ninfeas); if(current.varno > 0) { report(lp, DETAILED, "rowdual: rhs[%d] = " RESULTVALUEMASK "\n", current.varno, lp->rhs[current.varno]); } else report(lp, FULL, "rowdual: Optimality - No primal infeasibilities found\n"); } if(xviol != NULL) *xviol = fabs(xinfeas); return(current.varno); } /* rowdual */ STATIC void longdual_testset(lprec *lp, int which, int rownr, REAL *prow, int *nzprow, REAL *drow, int *nzdrow) { int i,j; REAL F = lp->infinite; if(which == 0) { /* Maros Example-1 - raw data */ j = 1; i = lp->rows+j; lp->upbo[i] = 0; lp->is_lower[i] = TRUE; nzprow[j] = i; prow[i] = 2; drow[i] = -1; j = 2; i = lp->rows+j; lp->upbo[i] = 1; lp->is_lower[i] = TRUE; nzprow[j] = i; prow[i] = -2; drow[i] = 2; j = 3; i = lp->rows+j; lp->upbo[i] = 1; lp->is_lower[i] = TRUE; nzprow[j] = i; prow[i] = 1; drow[i] = 5; j = 4; i = lp->rows+j; lp->upbo[i] = 1; lp->is_lower[i] = FALSE; nzprow[j] = i; prow[i] = 3; drow[i] = -6; j = 5; i = lp->rows+j; lp->upbo[i] = 1; lp->is_lower[i] = FALSE; nzprow[j] = i; prow[i] = -4; drow[i] = -2; j = 6; i = lp->rows+j; lp->upbo[i] = 1; lp->is_lower[i] = TRUE; nzprow[j] = i; prow[i] = -1; drow[i] = 0; j = 7; i = lp->rows+j; lp->upbo[i] = 2; lp->is_lower[i] = FALSE; nzprow[j] = i; prow[i] = 1; drow[i] = 0; j = 8; i = lp->rows+j; lp->upbo[i] = 1; lp->is_lower[i] = FALSE; nzprow[j] = i; prow[i] = -2; drow[i] = 0; j = 9; i = lp->rows+j; lp->upbo[i] = 5; lp->is_lower[i] = TRUE; nzprow[j] = i; prow[i] = -1; drow[i] = 4; j = 10; i = lp->rows+j; lp->upbo[i] = F; lp->is_lower[i] = TRUE; nzprow[j] = i; prow[i] = -2; drow[i] = 10; nzprow[0] = i-lp->rows; lp->rhs[rownr] = -11; lp->upbo[lp->var_basic[rownr]] = F; lp->rhs[0] = 1; } else if(which == 1) { /* Maros Example-1 - presorted in correct order */ j = 1; i = lp->rows+j; lp->upbo[i] = 0; lp->is_lower[i] = TRUE; nzprow[j] = i; prow[i] = 2; drow[i] = -1; j = 2; i = lp->rows+j; lp->upbo[i] = 1; lp->is_lower[i] = TRUE; nzprow[j] = i; prow[i] = 1; drow[i] = 5; j = 3; i = lp->rows+j; lp->upbo[i] = 1; lp->is_lower[i] = FALSE; nzprow[j] = i; prow[i] = -4; drow[i] = -2; j = 4; i = lp->rows+j; lp->upbo[i] = 1; lp->is_lower[i] = FALSE; nzprow[j] = i; prow[i] = -2; drow[i] = 0; j = 5; i = lp->rows+j; lp->upbo[i] = 1; lp->is_lower[i] = TRUE; nzprow[j] = i; prow[i] = -1; drow[i] = 0; j = 6; i = lp->rows+j; lp->upbo[i] = 2; lp->is_lower[i] = FALSE; nzprow[j] = i; prow[i] = 1; drow[i] = 0; j = 7; i = lp->rows+j; lp->upbo[i] = 1; lp->is_lower[i] = TRUE; nzprow[j] = i; prow[i] = -2; drow[i] = 2; j = 8; i = lp->rows+j; lp->upbo[i] = 1; lp->is_lower[i] = FALSE; nzprow[j] = i; prow[i] = 3; drow[i] = -6; j = 9; i = lp->rows+j; lp->upbo[i] = 5; lp->is_lower[i] = TRUE; nzprow[j] = i; prow[i] = -1; drow[i] = 4; j = 10; i = lp->rows+j; lp->upbo[i] = F; lp->is_lower[i] = TRUE; nzprow[j] = i; prow[i] = -2; drow[i] = 10; nzprow[0] = i-lp->rows; lp->rhs[rownr] = -11; lp->upbo[lp->var_basic[rownr]] = F; lp->rhs[0] = 1; } else if(which == 10) { /* Maros Example-2 - raw data */ j = 1; i = lp->rows+j; lp->upbo[i] = 5; lp->is_lower[i] = TRUE; nzprow[j] = i; prow[i] = -2; drow[i] = 2; j = 2; i = lp->rows+j; lp->upbo[i] = 1; lp->is_lower[i] = TRUE; nzprow[j] = i; prow[i] = 3; drow[i] = 3; j = 3; i = lp->rows+j; lp->upbo[i] = 1; lp->is_lower[i] = FALSE; nzprow[j] = i; prow[i] = -2; drow[i] = 0; j = 4; i = lp->rows+j; lp->upbo[i] = 2; lp->is_lower[i] = FALSE; nzprow[j] = i; prow[i] = -1; drow[i] = -2; j = 5; i = lp->rows+j; lp->upbo[i] = 2; lp->is_lower[i] = TRUE; nzprow[j] = i; prow[i] = 1; drow[i] = 0; j = 6; i = lp->rows+j; lp->upbo[i] = F; lp->is_lower[i] = TRUE; nzprow[j] = i; prow[i] = 3; drow[i] = 9; nzprow[0] = i-lp->rows; lp->rhs[rownr] = 14; lp->upbo[lp->var_basic[rownr]] = 2; lp->rhs[0] = 6; } } /* Find the dual simplex entering non-basic variable */ STATIC int coldual(lprec *lp, int row_nr, REAL *prow, int *nzprow, REAL *drow, int *nzdrow, MYBOOL dualphase1, MYBOOL skipupdate, int *candidatecount, REAL *xviol) { int i, iy, iz, ix, k, nbound; LREAL w, g, quot; REAL viol, p, epspivot = lp->epspivot; #ifdef MachinePrecRoundRHS REAL epsvalue = lp->epsmachine; #else REAL epsvalue = lp->epsvalue; #endif pricerec current, candidate; MYBOOL isbatch = FALSE, /* Requires that lp->longsteps->size > lp->sum */ dolongsteps = (MYBOOL) (lp->longsteps != NULL); /* Initialize */ if(xviol != NULL) *xviol = lp->infinite; if(dolongsteps && !dualphase1) dolongsteps = AUTOMATIC; /* Sets Phase1 = TRUE, Phase2 = AUTOMATIC */ current.theta = lp->infinite; current.pivot = 0; current.varno = 0; current.epspivot = epspivot; current.isdual = TRUE; current.lp = lp; candidate.epspivot = epspivot; candidate.isdual = TRUE; candidate.lp = lp; *candidatecount = 0; /* Compute reduced costs */ if(!skipupdate) { #ifdef UseDualReducedCostUpdate /* Recompute from scratch only at the beginning, otherwise update */ if((lp->current_iter > 0) && (refactRecent(lp) < AUTOMATIC)) compute_reducedcosts(lp, TRUE, row_nr, NULL, TRUE, prow, nzprow, NULL, NULL, MAT_ROUNDDEFAULT); else #endif compute_reducedcosts(lp, TRUE, row_nr, NULL, TRUE, prow, nzprow, drow, nzdrow, MAT_ROUNDDEFAULT); } #if 0 /* Override all above to do in-line testing with fixed test set */ if(lp->rows > 1 && lp->columns > 10) longdual_testset(lp, 10, row_nr, prow, nzprow, drow, nzdrow); #endif /* Compute the current violation of the bounds of the outgoing variable, negative for violation of lower bound, positive for upper bound violation. (Basic variables are always lower-bounded, by lp_solve convention) */ g = 1; viol = lp->rhs[row_nr]; if(viol > 0) { /* Check if the leaving variable is >= its upper bound */ p = lp->upbo[lp->var_basic[row_nr]]; if(p < lp->infinite) { viol -= p; my_roundzero(viol, epsvalue); if(viol > 0) g = -1; } /* Do validation of numerics */ if(g == 1) { if(viol >= lp->infinite) { report(lp, IMPORTANT, "coldual: Large basic solution value %g at iter %.0f indicates numerical instability\n", lp->rhs[row_nr], (double) get_total_iter(lp)); lp->spx_status = NUMFAILURE; return( 0 ); } if(skipupdate) report(lp, DETAILED, "coldual: Inaccurate bound-flip accuracy at iter %.0f\n", (double) get_total_iter(lp)); else report(lp, SEVERE, "coldual: Leaving variable %d does not violate bounds at iter %.0f\n", row_nr, (double) get_total_iter(lp)); return( -1 ); } } /* Update local value of pivot setting */ lp->_piv_rule_ = get_piv_rule(lp); /* Condense list of relevant targets */ p = 0; k = 0; nbound = 0; ix = 1; iy = nzprow[0]; for(ix = 1; ix <= iy; ix++) { i = nzprow[ix]; w = prow[i] * g; /* Change sign if upper bound of the leaving variable is violated */ w *= 2*lp->is_lower[i] - 1; /* Change sign if the non-basic variable is currently upper-bounded */ /* Check if the candidate is worth using for anything */ if(w < -epsvalue) { /* Tally bounded variables */ if(lp->upbo[i] < lp->infinite) nbound++; /* Update the nz-index */ k++; nzprow[k] = i; SETMAX(p, -w); } #ifdef Paranoia else { if(lp->spx_trace) { report(lp, FULL, "coldual: Candidate variable prow[%d] rejected with %g too small\n", i, w); } } #endif } nzprow[0] = k; if(xviol != NULL) *xviol = p; #ifdef UseRelativePivot_Dual /* epspivot *= sqrt(lp->matA->dynrange) / lp->matA->infnorm; */ epspivot /= MAX(1, sqrt(lp->matA->rowmax[row_nr])); #endif current.epspivot = epspivot; candidate.epspivot = epspivot; /* Initialize the long-step structures if indicated */ if(dolongsteps) { if((nzprow[0] <= 1) || (nbound == 0)) { /* Don't bother */ dolongsteps = FALSE; lp->longsteps->indexSet[0] = 0; } else { multi_restart(lp->longsteps); multi_valueInit(lp->longsteps, g*viol, lp->rhs[0]); } } /* Loop over all entering column candidates */ ix = 1; iy = nzprow[0]; makePriceLoop(lp, &ix, &iy, &iz); iy *= iz; for(; ix*iz <= iy; ix += iz) { i = nzprow[ix]; /* Compute the dual ratio (prow = w and drow = cbar in Chvatal's "nomenclatura") */ w = prow[i] * g; /* Change sign if upper bound of the leaving variable is violated */ quot = -drow[i] / w; /* Remember this sign-reversal in multi_recompute! */ /* Apply the selected pivot strategy (smallest theta) */ candidate.theta = quot; /* Note that abs() is applied in findSubstitutionVar */ candidate.pivot = w; candidate.varno = i; /* Collect candidates for minor iterations/bound flips */ if(dolongsteps) { if(isbatch && (ix == iy)) isbatch = AUTOMATIC; if(collectMinorVar(&candidate, lp->longsteps, (MYBOOL) (dolongsteps == AUTOMATIC), isbatch) && lp->spx_trace) report(lp, DETAILED, "coldual: Long-dual break point with %d bound-flip variables\n", lp->longsteps->used); if(lp->spx_status == FATHOMED) return( 0 ); } /* We have a candidate for entering the basis; check if it is better than the incumbent */ else if(findSubstitutionVar(¤t, &candidate, candidatecount)) break; } /* Set entering variable and long-step bound swap variables */ if(dolongsteps) { *candidatecount = lp->longsteps->used; i = multi_enteringvar(lp->longsteps, NULL, 3); } else i = current.varno; if(lp->spx_trace) report(lp, NORMAL, "coldual: Entering column %d, reduced cost %g, pivot value %g, bound swaps %d\n", i, drow[i], prow[i], multi_used(lp->longsteps)); return( i ); } /* coldual */ INLINE REAL normalizeEdge(lprec *lp, int item, REAL edge, MYBOOL isdual) { #if 1 /* Don't use the pricer "close to home", since this can possibly worsen the final feasibility picture (mainly a Devex issue?) */ if(fabs(edge) > lp->epssolution) #endif edge /= getPricer(lp, item, isdual); if((lp->piv_strategy & PRICE_RANDOMIZE) != 0) edge *= (1.0-PRICER_RANDFACT) + PRICER_RANDFACT*rand_uniform(lp, 1.0); return( edge ); } /* Support routines for block detection and partial pricing */ STATIC int partial_findBlocks(lprec *lp, MYBOOL autodefine, MYBOOL isrow) { int i, jj, n, nb, ne, items; REAL hold, biggest, *sum = NULL; MATrec *mat = lp->matA; partialrec *blockdata; if(!mat_validate(mat)) return( 1 ); blockdata = IF(isrow, lp->rowblocks, lp->colblocks); items = IF(isrow, lp->rows, lp->columns); allocREAL(lp, &sum, items+1, FALSE); /* Loop over items and compute the average column index for each */ sum[0] = 0; for(i = 1; i <= items; i++) { n = 0; if(isrow) { nb = mat->row_end[i-1]; ne = mat->row_end[i]; } else { nb = mat->col_end[i-1]; ne = mat->col_end[i]; } n = ne-nb; sum[i] = 0; if(n > 0) { if(isrow) for(jj = nb; jj < ne; jj++) sum[i] += ROW_MAT_COLNR(jj); else for(jj = nb; jj < ne; jj++) sum[i] += COL_MAT_ROWNR(jj); sum[i] /= n; } else sum[i] = sum[i-1]; } /* Loop over items again, find largest difference and make monotone */ hold = 0; biggest = 0; for(i = 2; i <= items; i++) { hold = sum[i] - sum[i-1]; if(hold > 0) { if(hold > biggest) biggest = hold; } else hold = 0; sum[i-1] = hold; } /* Loop over items again and find differences exceeding threshold; the discriminatory power of this routine depends strongly on the magnitude of the scaling factor - from empirical evidence > 0.9 */ biggest = MAX(1, 0.9*biggest); n = 0; nb = 0; ne = 0; for(i = 1; i < items; i++) if(sum[i] > biggest) { ne += i-nb; /* Compute sum of index gaps between maxima */ nb = i; n++; /* Increment count */ } /* Clean up */ FREE(sum); /* Require that the maxima are spread "nicely" across the columns, otherwise return that there is only one monolithic block. (This is probably an area for improvement in the logic!) */ if(n > 0) { ne /= n; /* Average index gap between maxima */ i = IF(isrow, lp->columns, lp->rows); nb = i / ne; /* Another estimated block count */ if(abs(nb - n) > 2) /* Probably Ok to require equality (nb==n)*/ n = 1; else if(autodefine) /* Generate row/column break-indeces for partial pricing */ set_partialprice(lp, nb, NULL, isrow); } else n = 1; return( n ); } STATIC int partial_blockStart(lprec *lp, MYBOOL isrow) { partialrec *blockdata; blockdata = IF(isrow, lp->rowblocks, lp->colblocks); if(blockdata == NULL) return( 1 ); else { if((blockdata->blocknow < 1) || (blockdata->blocknow > blockdata->blockcount)) blockdata->blocknow = 1; return( blockdata->blockend[blockdata->blocknow-1] ); } } STATIC int partial_blockEnd(lprec *lp, MYBOOL isrow) { partialrec *blockdata; blockdata = IF(isrow, lp->rowblocks, lp->colblocks); if(blockdata == NULL) return( IF(isrow, lp->rows, lp->sum) ); else { if((blockdata->blocknow < 1) || (blockdata->blocknow > blockdata->blockcount)) blockdata->blocknow = 1; return( blockdata->blockend[blockdata->blocknow]-1 ); } } STATIC int partial_blockNextPos(lprec *lp, int block, MYBOOL isrow) { partialrec *blockdata; blockdata = IF(isrow, lp->rowblocks, lp->colblocks); #ifdef Paranoia if((blockdata == NULL) || (block <= 1) || (block > blockdata->blockcount)) { report(lp, SEVERE, "partial_blockNextPos: Invalid block %d specified.\n", block); return( -1 ); } #endif block--; if(blockdata->blockpos[block] == blockdata->blockend[block+1]) blockdata->blockpos[block] = blockdata->blockend[block]; else blockdata->blockpos[block]++; return( blockdata->blockpos[block] ); } STATIC MYBOOL partial_blockStep(lprec *lp, MYBOOL isrow) { partialrec *blockdata; blockdata = IF(isrow, lp->rowblocks, lp->colblocks); if(blockdata == NULL) return( FALSE ); else if(blockdata->blocknow < blockdata->blockcount) { blockdata->blocknow++; return( TRUE); } else { blockdata->blocknow = 1; return( TRUE ); } } STATIC MYBOOL partial_isVarActive(lprec *lp, int varno, MYBOOL isrow) { partialrec *blockdata; blockdata = IF(isrow, lp->rowblocks, lp->colblocks); if(blockdata == NULL) return( TRUE ); else { return( (MYBOOL) ((varno >= blockdata->blockend[blockdata->blocknow-1]) && (varno < blockdata->blockend[blockdata->blocknow])) ); } } /* Multiple pricing routines */ STATIC multirec *multi_create(lprec *lp, MYBOOL truncinf) { multirec *multi; multi = (multirec *) calloc(1, sizeof(*multi)); if(multi != NULL) { multi->active = 1; multi->lp = lp; multi->epszero = lp->epsprimal; multi->truncinf = truncinf; } return(multi); } STATIC void multi_free(multirec **multi) { if((multi == NULL) || (*multi == NULL)) return; FREE((*multi)->items); FREE((*multi)->valueList); FREE((*multi)->indexSet); FREE((*multi)->freeList); FREE((*multi)->sortedList); FREE(*multi); } STATIC MYBOOL multi_mustupdate(multirec *multi) { return( (MYBOOL) ((multi != NULL) && (multi->used < multi->limit)) ); } STATIC MYBOOL multi_resize(multirec *multi, int blocksize, int blockdiv, MYBOOL doVlist, MYBOOL doIset) { MYBOOL ok = TRUE; if((blocksize > 1) && (blockdiv > 0)) { int oldsize = multi->size; multi->size = blocksize; if(blockdiv > 1) multi->limit += (multi->size-oldsize) / blockdiv; multi->items = (pricerec *) realloc(multi->items, (multi->size+1)*sizeof(*(multi->items))); multi->sortedList = (UNIONTYPE QSORTrec *) realloc(multi->sortedList, (multi->size+1)*sizeof(*(multi->sortedList))); ok = (multi->items != NULL) && (multi->sortedList != NULL) && allocINT(multi->lp, &(multi->freeList), multi->size+1, AUTOMATIC); if(ok) { int i, n; if(oldsize == 0) i = 0; else i = multi->freeList[0]; multi->freeList[0] = i + (multi->size-oldsize); for(n = multi->size - 1, i++; i <= multi->freeList[0]; i++, n--) multi->freeList[i] = n; } if(doVlist) ok &= allocREAL(multi->lp, &(multi->valueList), multi->size+1, AUTOMATIC); if(doIset) { ok &= allocINT(multi->lp, &(multi->indexSet), multi->size+1, AUTOMATIC); if(ok && (oldsize == 0)) multi->indexSet[0] = 0; } if(!ok) goto Undo; } else { Undo: multi->size = 0; FREE(multi->items); FREE(multi->valueList); FREE(multi->indexSet); FREE(multi->freeList); FREE(multi->sortedList); } multi->active = 1; return( ok ); } STATIC int multi_size(multirec *multi) { if(multi == NULL) return( 0 ); else return( multi->size ); } STATIC int multi_used(multirec *multi) { if(multi == NULL) return( 0 ); else return( multi->used ); } STATIC int multi_restart(multirec *multi) { int i, n = multi->used; multi->used = 0; multi->sorted = FALSE; multi->dirty = FALSE; if(multi->freeList != NULL) { for(i = 1; i <= multi->size; i++) multi->freeList[i] = multi->size - i; multi->freeList[0] = multi->size; } #if 0 if(multi->indexSet != NULL) multi->indexSet[0] = 0; #endif return( n ); } STATIC void multi_valueInit(multirec *multi, REAL step_base, REAL obj_base) { multi->step_base = multi->step_last = step_base; multi->obj_base = multi->obj_last = obj_base; #ifdef Paranoia if(step_base > 0) report(multi->lp, SEVERE, "multi_valueInit: Positive constraint violation %g provided at iteration %6.0f\n", step_base, (double) get_total_iter(multi->lp)); #endif } STATIC REAL *multi_valueList(multirec *multi) { return(multi->valueList); } STATIC int *multi_indexSet(multirec *multi, MYBOOL regenerate) { if(regenerate) multi_populateSet(multi, NULL, -1); return(multi->indexSet); } STATIC int multi_getvar(multirec *multi, int item) { #ifdef Paranoia if((item < 1) || (item >= multi->size)) return(-1); #endif return( ((pricerec *) &(multi->sortedList[item].pvoidreal.ptr))->varno ); } STATIC MYBOOL multi_recompute(multirec *multi, int index, MYBOOL isphase2, MYBOOL fullupdate) { int i, n; REAL lB, uB, Alpha, this_theta, prev_theta; lprec *lp = multi->lp; pricerec *thisprice; /* Define target update window */ if(multi->dirty) { index = 0; n = multi->used - 1; } else if(fullupdate) n = multi->used - 1; else n = index; /* Initialize accumulators from the specified update index */ if(index == 0) { multi->maxpivot = 0; multi->maxbound = 0; multi->step_last = multi->step_base; multi->obj_last = multi->obj_base; thisprice = NULL; this_theta = 0; } else { multi->obj_last = multi->valueList[index-1]; multi->step_last = multi->sortedList[index-1].pvoidreal.realval; thisprice = (pricerec *) (multi->sortedList[index-1].pvoidreal.ptr); this_theta = thisprice->theta; } /* Update step lengths and objective values */ while((index <= n) && (multi->step_last < multi->epszero)) { /* Update parameters for this loop */ prev_theta = this_theta; thisprice = (pricerec *) (multi->sortedList[index].pvoidreal.ptr); this_theta = thisprice->theta; Alpha = fabs(thisprice->pivot); uB = lp->upbo[thisprice->varno]; lB = 0; SETMAX(multi->maxpivot, Alpha); SETMAX(multi->maxbound, uB); /* Do the value updates */ if(isphase2) { multi->obj_last += (this_theta - prev_theta) * multi->step_last; /* Sign-readjusted from coldual()/Maros */ if(uB >= lp->infinite) multi->step_last = lp->infinite; else multi->step_last += Alpha*(uB-lB); } else { multi->obj_last += (this_theta - prev_theta) * multi->step_last; /* Sign-readjusted from coldual()/Maros */ multi->step_last += Alpha; } /* Store updated values at the indexed locations */ multi->sortedList[index].pvoidreal.realval = multi->step_last; multi->valueList[index] = multi->obj_last; #ifdef Paranoia if(lp->spx_trace && (multi->step_last > lp->infinite)) report(lp, SEVERE, "multi_recompute: A very large step-size %g was generated at iteration %6.0f\n", multi->step_last, (double) get_total_iter(lp)); #endif index++; } /* Discard candidates entered earlier that now make the OF worsen, and make sure that the released positions are added to the free list. */ n = index; while(n < multi->used) { i = ++multi->freeList[0]; multi->freeList[i] = (int) (((pricerec *) multi->sortedList[n].pvoidreal.ptr) - multi->items); n++; } multi->used = index; if(multi->sorted && (index == 1)) multi->sorted = FALSE; multi->dirty = FALSE; /* Return TRUE if the step is now positive */ return( (MYBOOL) (multi->step_last >= multi->epszero) ); } STATIC MYBOOL multi_truncatingvar(multirec *multi, int varnr) { return( multi->truncinf && is_infinite(multi->lp, multi->lp->upbo[varnr]) ); } STATIC MYBOOL multi_removevar(multirec *multi, int varnr) { int i = 1; int *coltarget = multi->indexSet; if(coltarget == NULL) return( FALSE ); while((i <= multi->used) && (coltarget[i] != varnr)) i++; if(i > multi->used) return( FALSE ); for(; i < multi->used; i++) coltarget[i] = coltarget[i+1]; coltarget[0]--; multi->used--; multi->dirty = TRUE; return( TRUE ); } STATIC int multi_enteringvar(multirec *multi, pricerec *current, int priority) { lprec *lp = multi->lp; int i = 0, bestindex, colnr; REAL bound, score, bestscore = -lp->infinite; REAL b1, b2, b3; pricerec *candidate, *bestcand; /* Check that we have a candidate */ multi->active = bestindex = 0; if((multi == NULL) || (multi->used == 0)) return( bestindex ); /* Check for pruning possibility of the B&B tree */ if(multi->objcheck && (lp->solutioncount > 0) && bb_better(lp, OF_WORKING | OF_PROJECTED, OF_TEST_WE)) { lp->spx_status = FATHOMED; return( bestindex ); } /* Check the trivial case */ if(multi->used == 1) { bestcand = (pricerec *) (multi->sortedList[bestindex].pvoidreal.ptr); goto Finish; } /* Set priority weights */ Redo: switch(priority) { case 0: b1 = 0.0, b2 = 0.0, b3 = 1.0; /* Only OF */ bestindex = multi->used - 2; break; case 1: b1 = 0.2, b2 = 0.3, b3 = 0.5; break; /* Emphasize OF */ case 2: b1 = 0.3, b2 = 0.5, b3 = 0.2; break; /* Emphasize bound */ case 3: b1 = 0.6, b2 = 0.2, b3 = 0.2; break; /* Emphasize pivot */ case 4: b1 = 1.0, b2 = 0.0, b3 = 0.0; break; /* Only pivot */ default: b1 = 0.4, b2 = 0.2, b3 = 0.4; /* Balanced default */ } bestcand = (pricerec *) (multi->sortedList[bestindex].pvoidreal.ptr); /* Loop over all candidates to get the best entering candidate; start at the end to try to maximize the chain length */ for(i = multi->used - 1; i >= 0; i--) { candidate = (pricerec *) (multi->sortedList[i].pvoidreal.ptr); colnr = candidate->varno; bound = lp->upbo[colnr]; score = fabs(candidate->pivot) / multi->maxpivot; score = pow(1.0 + score , b1) * pow(1.0 + log(bound / multi->maxbound + 1), b2) * pow(1.0 + (REAL) i / multi->used , b3); if(score > bestscore) { bestscore = score; bestindex = i; bestcand = candidate; } } /* Do pivot protection */ if((priority < 4) && (fabs(bestcand->pivot) < lp->epssolution)) { bestindex = 0; priority++; goto Redo; } Finish: /* Make sure we shrink the list and update */ multi->active = colnr = bestcand->varno; if(bestindex < multi->used - 1) { #if 0 /* if(lp->upbo[colnr] >= lp->infinite) */ QS_swap(multi->sortedList, bestindex, multi->used-1); multi_recompute(multi, bestindex, (bestcand->isdual == AUTOMATIC), TRUE); #else multi->used = i + 1; #endif } multi_populateSet(multi, NULL, multi->active); /* Compute the entering theta and update parameters */ score = (multi->used == 1 ? multi->step_base : multi->sortedList[multi->used-2].pvoidreal.realval); score /= bestcand->pivot; score = my_chsign(!lp->is_lower[multi->active], score); if(lp->spx_trace && (fabs(score) > 1/lp->epsprimal)) report(lp, IMPORTANT, "multi_enteringvar: A very large Theta %g was generated (pivot %g)\n", score, bestcand->pivot); multi->step_base = score; if(current != NULL) *current = *bestcand; return( multi->active ); } STATIC REAL multi_enteringtheta(multirec *multi) { return( multi->step_base ); } STATIC int multi_populateSet(multirec *multi, int **list, int excludenr) { int n = 0; if(list == NULL) list = &(multi->indexSet); if((multi->used > 0) && ((*list != NULL) || allocINT(multi->lp, list, multi->size+1, FALSE))) { int i, colnr; for(i = 0; i < multi->used; i++) { colnr = ((pricerec *) (multi->sortedList[i].pvoidreal.ptr))->varno; if((colnr != excludenr) && /* Prevent an unbounded variable from "bound-flip"; this could actually indicate that we should let the entering variable be bound-swapped (in the case that it is bounded), but we disregard this possibility here, since it brings with it issues of pivot size, etc. */ ((excludenr > 0) && (multi->lp->upbo[colnr] < multi->lp->infinite))) { n++; (*list)[n] = colnr; } } (*list)[0] = n; } return( n ); } MSVMpack1.2/lp_solve_5.5/configure0000664000175000017500000030353611236132302016045 0ustar lauerlauer#! /bin/sh # Guess values for system-dependent variables and create Makefiles. # Generated by GNU Autoconf 2.59 for lpsolve 5.5.0.15. # # Copyright (C) 2003 Free Software Foundation, Inc. # This configure script is free software; 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then echo $ECHO_N "(cached) $ECHO_C" >&6 else if test -n "$ac_ct_CC"; then ac_cv_prog_ac_ct_CC="$ac_ct_CC" # Let the user override the test. else as_save_IFS=$IFS; IFS=$PATH_SEPARATOR for as_dir in $PATH do IFS=$as_save_IFS test -z "$as_dir" && as_dir=. for ac_exec_ext in '' $ac_executable_extensions; do if $as_executable_p "$as_dir/$ac_word$ac_exec_ext"; then ac_cv_prog_ac_ct_CC="cc" echo "$as_me:$LINENO: found $as_dir/$ac_word$ac_exec_ext" >&5 break 2 fi done done fi fi ac_ct_CC=$ac_cv_prog_ac_ct_CC if test -n "$ac_ct_CC"; then echo "$as_me:$LINENO: result: $ac_ct_CC" >&5 echo "${ECHO_T}$ac_ct_CC" >&6 else echo "$as_me:$LINENO: result: no" >&5 echo "${ECHO_T}no" >&6 fi CC=$ac_ct_CC else CC="$ac_cv_prog_CC" fi fi if test -z "$CC"; then # Extract the first word of "cc", so it can be a program name with args. set dummy cc; ac_word=$2 echo "$as_me:$LINENO: checking for $ac_word" >&5 echo $ECHO_N "checking for $ac_word... $ECHO_C" >&6 if test "${ac_cv_prog_CC+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else if test -n "$CC"; then ac_cv_prog_CC="$CC" # Let the user override the test. else ac_prog_rejected=no as_save_IFS=$IFS; IFS=$PATH_SEPARATOR for as_dir in $PATH do IFS=$as_save_IFS test -z "$as_dir" && as_dir=. for ac_exec_ext in '' $ac_executable_extensions; do if $as_executable_p "$as_dir/$ac_word$ac_exec_ext"; then if test "$as_dir/$ac_word$ac_exec_ext" = "/usr/ucb/cc"; then ac_prog_rejected=yes continue fi ac_cv_prog_CC="cc" echo "$as_me:$LINENO: found $as_dir/$ac_word$ac_exec_ext" >&5 break 2 fi done done if test $ac_prog_rejected = yes; then # We found a bogon in the path, so make sure we never use it. set dummy $ac_cv_prog_CC shift if test $# != 0; then # We chose a different compiler from the bogus one. # However, it has the same basename, so the bogon will be chosen # first if we set CC to just the basename; use the full file name. shift ac_cv_prog_CC="$as_dir/$ac_word${1+' '}$@" fi fi fi fi CC=$ac_cv_prog_CC if test -n "$CC"; then echo "$as_me:$LINENO: result: $CC" >&5 echo "${ECHO_T}$CC" >&6 else echo "$as_me:$LINENO: result: no" >&5 echo "${ECHO_T}no" >&6 fi fi if test -z "$CC"; then if test -n "$ac_tool_prefix"; then for ac_prog in cl do # Extract the first word of "$ac_tool_prefix$ac_prog", so it can be a program name with args. set dummy $ac_tool_prefix$ac_prog; ac_word=$2 echo "$as_me:$LINENO: checking for $ac_word" >&5 echo $ECHO_N "checking for $ac_word... $ECHO_C" >&6 if test "${ac_cv_prog_CC+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else if test -n "$CC"; then ac_cv_prog_CC="$CC" # Let the user override the test. else as_save_IFS=$IFS; IFS=$PATH_SEPARATOR for as_dir in $PATH do IFS=$as_save_IFS test -z "$as_dir" && as_dir=. for ac_exec_ext in '' $ac_executable_extensions; do if $as_executable_p "$as_dir/$ac_word$ac_exec_ext"; then ac_cv_prog_CC="$ac_tool_prefix$ac_prog" echo "$as_me:$LINENO: found $as_dir/$ac_word$ac_exec_ext" >&5 break 2 fi done done fi fi CC=$ac_cv_prog_CC if test -n "$CC"; then echo "$as_me:$LINENO: result: $CC" >&5 echo "${ECHO_T}$CC" >&6 else echo "$as_me:$LINENO: result: no" >&5 echo "${ECHO_T}no" >&6 fi test -n "$CC" && break done fi if test -z "$CC"; then ac_ct_CC=$CC for ac_prog in cl do # Extract the first word of "$ac_prog", so it can be a program name with args. set dummy $ac_prog; ac_word=$2 echo "$as_me:$LINENO: checking for $ac_word" >&5 echo $ECHO_N "checking for $ac_word... $ECHO_C" >&6 if test "${ac_cv_prog_ac_ct_CC+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else if test -n "$ac_ct_CC"; then ac_cv_prog_ac_ct_CC="$ac_ct_CC" # Let the user override the test. else as_save_IFS=$IFS; IFS=$PATH_SEPARATOR for as_dir in $PATH do IFS=$as_save_IFS test -z "$as_dir" && as_dir=. for ac_exec_ext in '' $ac_executable_extensions; do if $as_executable_p "$as_dir/$ac_word$ac_exec_ext"; then ac_cv_prog_ac_ct_CC="$ac_prog" echo "$as_me:$LINENO: found $as_dir/$ac_word$ac_exec_ext" >&5 break 2 fi done done fi fi ac_ct_CC=$ac_cv_prog_ac_ct_CC if test -n "$ac_ct_CC"; then echo "$as_me:$LINENO: result: $ac_ct_CC" >&5 echo "${ECHO_T}$ac_ct_CC" >&6 else echo "$as_me:$LINENO: result: no" >&5 echo "${ECHO_T}no" >&6 fi test -n "$ac_ct_CC" && break done CC=$ac_ct_CC fi fi test -z "$CC" && { { echo "$as_me:$LINENO: error: no acceptable C compiler found in \$PATH See \`config.log' for more details." >&5 echo "$as_me: error: no acceptable C compiler found in \$PATH See \`config.log' for more details." >&2;} { (exit 1); exit 1; }; } # Provide some information about the compiler. echo "$as_me:$LINENO:" \ "checking for C compiler version" >&5 ac_compiler=`set X $ac_compile; echo $2` { (eval echo "$as_me:$LINENO: \"$ac_compiler --version &5\"") >&5 (eval $ac_compiler --version &5) 2>&5 ac_status=$? echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); } { (eval echo "$as_me:$LINENO: \"$ac_compiler -v &5\"") >&5 (eval $ac_compiler -v &5) 2>&5 ac_status=$? echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); } { (eval echo "$as_me:$LINENO: \"$ac_compiler -V &5\"") >&5 (eval $ac_compiler -V &5) 2>&5 ac_status=$? echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); } cat >conftest.$ac_ext <<_ACEOF /* confdefs.h. */ _ACEOF cat confdefs.h >>conftest.$ac_ext cat >>conftest.$ac_ext <<_ACEOF /* end confdefs.h. */ int main () { ; return 0; } _ACEOF ac_clean_files_save=$ac_clean_files ac_clean_files="$ac_clean_files a.out a.exe b.out" # Try to create an executable without -o first, disregard a.out. # It will help us diagnose broken compilers, and finding out an intuition # of exeext. echo "$as_me:$LINENO: checking for C compiler default output file name" >&5 echo $ECHO_N "checking for C compiler default output file name... $ECHO_C" >&6 ac_link_default=`echo "$ac_link" | sed 's/ -o *conftest[^ ]*//'` if { (eval echo "$as_me:$LINENO: \"$ac_link_default\"") >&5 (eval $ac_link_default) 2>&5 ac_status=$? echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); }; then # Find the output, starting from the most likely. This scheme is # not robust to junk in `.', hence go to wildcards (a.*) only as a last # resort. # Be careful to initialize this variable, since it used to be cached. # Otherwise an old cache value of `no' led to `EXEEXT = no' in a Makefile. ac_cv_exeext= # b.out is created by i960 compilers. for ac_file in a_out.exe a.exe conftest.exe a.out conftest a.* conftest.* b.out do test -f "$ac_file" || continue case $ac_file in *.$ac_ext | *.xcoff | *.tds | *.d | *.pdb | *.xSYM | *.bb | *.bbg | *.o | *.obj ) ;; conftest.$ac_ext ) # This is the source file. ;; [ab].out ) # We found the default executable, but exeext='' is most # certainly right. break;; *.* ) ac_cv_exeext=`expr "$ac_file" : '[^.]*\(\..*\)'` # FIXME: I believe we export ac_cv_exeext for Libtool, # but it would be cool to find out if it's true. Does anybody # maintain Libtool? --akim. export ac_cv_exeext break;; * ) break;; esac done else echo "$as_me: failed program was:" >&5 sed 's/^/| /' conftest.$ac_ext >&5 { { echo "$as_me:$LINENO: error: C compiler cannot create executables See \`config.log' for more details." >&5 echo "$as_me: error: C compiler cannot create executables See \`config.log' for more details." >&2;} { (exit 77); exit 77; }; } fi ac_exeext=$ac_cv_exeext echo "$as_me:$LINENO: result: $ac_file" >&5 echo "${ECHO_T}$ac_file" >&6 # Check the compiler produces executables we can run. If not, either # the compiler is broken, or we cross compile. echo "$as_me:$LINENO: checking whether the C compiler works" >&5 echo $ECHO_N "checking whether the C compiler works... $ECHO_C" >&6 # FIXME: These cross compiler hacks should be removed for Autoconf 3.0 # If not cross compiling, check that we can run a simple program. if test "$cross_compiling" != yes; then if { ac_try='./$ac_file' { (eval echo "$as_me:$LINENO: \"$ac_try\"") >&5 (eval $ac_try) 2>&5 ac_status=$? echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); }; }; then cross_compiling=no else if test "$cross_compiling" = maybe; then cross_compiling=yes else { { echo "$as_me:$LINENO: error: cannot run C compiled programs. If you meant to cross compile, use \`--host'. See \`config.log' for more details." >&5 echo "$as_me: error: cannot run C compiled programs. If you meant to cross compile, use \`--host'. See \`config.log' for more details." >&2;} { (exit 1); exit 1; }; } fi fi fi echo "$as_me:$LINENO: result: yes" >&5 echo "${ECHO_T}yes" >&6 rm -f a.out a.exe conftest$ac_cv_exeext b.out ac_clean_files=$ac_clean_files_save # Check the compiler produces executables we can run. If not, either # the compiler is broken, or we cross compile. echo "$as_me:$LINENO: checking whether we are cross compiling" >&5 echo $ECHO_N "checking whether we are cross compiling... $ECHO_C" >&6 echo "$as_me:$LINENO: result: $cross_compiling" >&5 echo "${ECHO_T}$cross_compiling" >&6 echo "$as_me:$LINENO: checking for suffix of executables" >&5 echo $ECHO_N "checking for suffix of executables... $ECHO_C" >&6 if { (eval echo "$as_me:$LINENO: \"$ac_link\"") >&5 (eval $ac_link) 2>&5 ac_status=$? echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); }; then # If both `conftest.exe' and `conftest' are `present' (well, observable) # catch `conftest.exe'. For instance with Cygwin, `ls conftest' will # work properly (i.e., refer to `conftest.exe'), while it won't with # `rm'. for ac_file in conftest.exe conftest conftest.*; do test -f "$ac_file" || continue case $ac_file in *.$ac_ext | *.xcoff | *.tds | *.d | *.pdb | *.xSYM | *.bb | *.bbg | *.o | *.obj ) ;; *.* ) ac_cv_exeext=`expr "$ac_file" : '[^.]*\(\..*\)'` export ac_cv_exeext break;; * ) break;; esac done else { { echo "$as_me:$LINENO: error: cannot compute suffix of executables: cannot compile and link See \`config.log' for more details." >&5 echo "$as_me: error: cannot compute suffix of executables: cannot compile and link See \`config.log' for more details." >&2;} { (exit 1); exit 1; }; } fi rm -f conftest$ac_cv_exeext echo "$as_me:$LINENO: result: $ac_cv_exeext" >&5 echo "${ECHO_T}$ac_cv_exeext" >&6 rm -f conftest.$ac_ext EXEEXT=$ac_cv_exeext ac_exeext=$EXEEXT echo "$as_me:$LINENO: checking for suffix of object files" >&5 echo $ECHO_N "checking for suffix of object files... $ECHO_C" >&6 if test "${ac_cv_objext+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else cat >conftest.$ac_ext <<_ACEOF /* confdefs.h. */ _ACEOF cat confdefs.h >>conftest.$ac_ext cat >>conftest.$ac_ext <<_ACEOF /* end confdefs.h. */ int main () { ; return 0; } _ACEOF rm -f conftest.o conftest.obj if { (eval echo "$as_me:$LINENO: \"$ac_compile\"") >&5 (eval $ac_compile) 2>&5 ac_status=$? echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); }; then for ac_file in `(ls conftest.o conftest.obj; ls conftest.*) 2>/dev/null`; do case $ac_file in *.$ac_ext | *.xcoff | *.tds | *.d | *.pdb | *.xSYM | *.bb | *.bbg ) ;; *) ac_cv_objext=`expr "$ac_file" : '.*\.\(.*\)'` break;; esac done else echo "$as_me: failed program was:" >&5 sed 's/^/| /' conftest.$ac_ext >&5 { { echo "$as_me:$LINENO: error: cannot compute suffix of object files: cannot compile See \`config.log' for more details." >&5 echo "$as_me: error: cannot compute suffix of object files: cannot compile See \`config.log' for more details." >&2;} { (exit 1); exit 1; }; } fi rm -f conftest.$ac_cv_objext conftest.$ac_ext fi echo "$as_me:$LINENO: result: $ac_cv_objext" >&5 echo "${ECHO_T}$ac_cv_objext" >&6 OBJEXT=$ac_cv_objext ac_objext=$OBJEXT echo "$as_me:$LINENO: checking whether we are using the GNU C compiler" >&5 echo $ECHO_N "checking whether we are using the GNU C compiler... $ECHO_C" >&6 if test "${ac_cv_c_compiler_gnu+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else cat >conftest.$ac_ext <<_ACEOF /* confdefs.h. */ _ACEOF cat confdefs.h >>conftest.$ac_ext cat >>conftest.$ac_ext <<_ACEOF /* end confdefs.h. */ int main () { #ifndef __GNUC__ choke me #endif ; return 0; } _ACEOF rm -f conftest.$ac_objext if { (eval echo "$as_me:$LINENO: \"$ac_compile\"") >&5 (eval $ac_compile) 2>conftest.er1 ac_status=$? grep -v '^ *+' conftest.er1 >conftest.err rm -f conftest.er1 cat conftest.err >&5 echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); } && { ac_try='test -z "$ac_c_werror_flag" || test ! -s conftest.err' { (eval echo "$as_me:$LINENO: \"$ac_try\"") >&5 (eval $ac_try) 2>&5 ac_status=$? echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); }; } && { ac_try='test -s conftest.$ac_objext' { (eval echo "$as_me:$LINENO: \"$ac_try\"") >&5 (eval $ac_try) 2>&5 ac_status=$? echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); }; }; then ac_compiler_gnu=yes else echo "$as_me: failed program was:" >&5 sed 's/^/| /' conftest.$ac_ext >&5 ac_compiler_gnu=no fi rm -f conftest.err conftest.$ac_objext conftest.$ac_ext ac_cv_c_compiler_gnu=$ac_compiler_gnu fi echo "$as_me:$LINENO: result: $ac_cv_c_compiler_gnu" >&5 echo "${ECHO_T}$ac_cv_c_compiler_gnu" >&6 GCC=`test $ac_compiler_gnu = yes && echo yes` ac_test_CFLAGS=${CFLAGS+set} ac_save_CFLAGS=$CFLAGS CFLAGS="-g" echo "$as_me:$LINENO: checking whether $CC accepts -g" >&5 echo $ECHO_N "checking whether $CC accepts -g... $ECHO_C" >&6 if test "${ac_cv_prog_cc_g+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else cat >conftest.$ac_ext <<_ACEOF /* confdefs.h. */ _ACEOF cat confdefs.h >>conftest.$ac_ext cat >>conftest.$ac_ext <<_ACEOF /* end confdefs.h. */ int main () { ; return 0; } _ACEOF rm -f conftest.$ac_objext if { (eval echo "$as_me:$LINENO: \"$ac_compile\"") >&5 (eval $ac_compile) 2>conftest.er1 ac_status=$? grep -v '^ *+' conftest.er1 >conftest.err rm -f conftest.er1 cat conftest.err >&5 echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); } && { ac_try='test -z "$ac_c_werror_flag" || test ! -s conftest.err' { (eval echo "$as_me:$LINENO: \"$ac_try\"") >&5 (eval $ac_try) 2>&5 ac_status=$? echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); }; } && { ac_try='test -s conftest.$ac_objext' { (eval echo "$as_me:$LINENO: \"$ac_try\"") >&5 (eval $ac_try) 2>&5 ac_status=$? echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); }; }; then ac_cv_prog_cc_g=yes else echo "$as_me: failed program was:" >&5 sed 's/^/| /' conftest.$ac_ext >&5 ac_cv_prog_cc_g=no fi rm -f conftest.err conftest.$ac_objext conftest.$ac_ext fi echo "$as_me:$LINENO: result: $ac_cv_prog_cc_g" >&5 echo "${ECHO_T}$ac_cv_prog_cc_g" >&6 if test "$ac_test_CFLAGS" = set; then CFLAGS=$ac_save_CFLAGS elif test $ac_cv_prog_cc_g = yes; then if test "$GCC" = yes; then CFLAGS="-g -O2" else CFLAGS="-g" fi else if test "$GCC" = yes; then CFLAGS="-O2" else CFLAGS= fi fi echo "$as_me:$LINENO: checking for $CC option to accept ANSI C" >&5 echo $ECHO_N "checking for $CC option to accept ANSI C... $ECHO_C" >&6 if test "${ac_cv_prog_cc_stdc+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else ac_cv_prog_cc_stdc=no ac_save_CC=$CC cat >conftest.$ac_ext <<_ACEOF /* confdefs.h. */ _ACEOF cat confdefs.h >>conftest.$ac_ext cat >>conftest.$ac_ext <<_ACEOF /* end confdefs.h. */ #include #include #include #include /* Most of the following tests are stolen from RCS 5.7's src/conf.sh. */ struct buf { int x; }; FILE * (*rcsopen) (struct buf *, struct stat *, int); static char *e (p, i) char **p; int i; { return p[i]; } static char *f (char * (*g) (char **, int), char **p, ...) { char *s; va_list v; va_start (v,p); s = g (p, va_arg (v,int)); va_end (v); return s; } /* OSF 4.0 Compaq cc is some sort of almost-ANSI by default. It has function prototypes and stuff, but not '\xHH' hex character constants. These don't provoke an error unfortunately, instead are silently treated as 'x'. The following induces an error, until -std1 is added to get proper ANSI mode. Curiously '\x00'!='x' always comes out true, for an array size at least. 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So we exec the FD to /dev/null, # effectively closing config.log, so it can be properly (re)opened and # appended to by config.status. When coming back to configure, we # need to make the FD available again. if test "$no_create" != yes; then ac_cs_success=: ac_config_status_args= test "$silent" = yes && ac_config_status_args="$ac_config_status_args --quiet" exec 5>/dev/null $SHELL $CONFIG_STATUS $ac_config_status_args || ac_cs_success=false exec 5>>config.log # Use ||, not &&, to avoid exiting from the if with $? = 1, which # would make configure fail if this is the last instruction. $ac_cs_success || { (exit 1); exit 1; } fi MSVMpack1.2/lp_solve_5.5/lp_solve/0000775000175000017500000000000011254510404015755 5ustar lauerlauerMSVMpack1.2/lp_solve_5.5/lp_solve/lp_solve.vcproj0000664000175000017500000006104411252255123021034 0ustar lauerlauer MSVMpack1.2/lp_solve_5.5/lp_solve/cvc8.bat0000775000175000017500000000244311136446025017324 0ustar lauerlauer@echo off REM This batch file compiles the lp_solve driver program with the Microsoft Visual C/C++ compiler under Windows set c=cl REM determine platform (win32/win64) echo main(){printf("SET PLATFORM=win%%d\n", (int) (sizeof(void *)*8));}>platform.c %c% /nologo platform.c /Feplatform.exe del platform.c platform.exe >platform.bat del platform.exe call platform.bat del platform.bat if not exist bin\%PLATFORM%\*.* md bin\%PLATFORM% set src=../shared/commonlib.c ../shared/mmio.c ../shared/myblas.c ../ini.c ../lp_rlp.c ../lp_crash.c ../bfp/bfp_LUSOL/lp_LUSOL.c ../bfp/bfp_LUSOL/LUSOL/lusol.c ../lp_Hash.c ../lp_lib.c ../lp_wlp.c ../lp_matrix.c ../lp_mipbb.c ../lp_MPS.c ../lp_params.c ../lp_presolve.c ../lp_price.c ../lp_pricePSE.c ../lp_report.c ../lp_scale.c ../lp_simplex.c lp_solve.c ../lp_SOS.c ../lp_utils.c ../yacc_read.c ../lp_MDO.c ../colamd/colamd.c %1 %c% -I.. -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd -I../shared /O1 /Zp8 /Gd -D"LP_MAXLINELEN=0" -DNoParanoia -DWIN32 -D_CRT_SECURE_NO_DEPRECATE -D_CRT_NONSTDC_NO_DEPRECATE -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine -Febin\%PLATFORM%\lp_solve.exe %src% editbin /LARGEADDRESSAWARE bin\%PLATFORM%\lp_solve.exe if exist *.obj del *.obj set PLATFORM= MSVMpack1.2/lp_solve_5.5/lp_solve/ccc.osx0000664000175000017500000000275011137130715017247 0ustar lauerlauer: src='../lp_MDO.c ../shared/commonlib.c ../colamd/colamd.c ../shared/mmio.c ../shared/myblas.c ../ini.c ../fortify.c ../lp_rlp.c ../lp_crash.c ../bfp/bfp_LUSOL/lp_LUSOL.c ../bfp/bfp_LUSOL/LUSOL/lusol.c ../lp_Hash.c ../lp_lib.c ../lp_wlp.c ../lp_matrix.c ../lp_mipbb.c ../lp_MPS.c ../lp_params.c ../lp_presolve.c ../lp_price.c ../lp_pricePSE.c ../lp_report.c ../lp_scale.c ../lp_simplex.c lp_solve.c ../lp_SOS.c ../lp_utils.c ../yacc_read.c' c=cc #determine platform (32/64 bit) >/tmp/platform.c echo '#include '>>/tmp/platform.c echo '#include '>>/tmp/platform.c echo 'main(){printf("osx%d", (int) (sizeof(void *)*8));}'>>/tmp/platform.c $c /tmp/platform.c -o /tmp/platform PLATFORM=`/tmp/platform` rm /tmp/platform /tmp/platform.c >/dev/null 2>&1 mkdir bin bin/$PLATFORM >/dev/null 2>&1 math=-lm #check if this system has the isnan function >/tmp/isnan.c echo '#include '>>/tmp/isnan.c echo '#include '>>/tmp/isnan.c echo '#include '>>/tmp/isnan.c echo 'main(){isnan(0);}'>>/tmp/isnan.c $c /tmp/isnan.c -o /tmp/isnan $math >/dev/null 2>&1 if [ $? = 0 ] then NOISNAN= else NOISNAN=-DNOISNAN fi rm /tmp/isnan.c /tmp/isnan >/dev/null 2>&1 def= dl=-ldl opts='-idirafter /usr/include/sys -O3 -DINTEGERTIME -Wno-long-double' $c -I.. -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd -I../shared $opts $def $NOISNAN -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine $src -o bin/$PLATFORM/lp_solve $math $dl MSVMpack1.2/lp_solve_5.5/lp_solve/lp_solve.sln0000664000175000017500000000453111126023502020315 0ustar lauerlauer Microsoft Visual Studio Solution File, Format Version 10.00 # Visual Studio 2008 Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "lp_solve", "lp_solve.vcproj", "{2098FB68-99FD-40D4-ABD6-87E2FD11D1B5}" EndProject Global GlobalSection(SolutionConfigurationPlatforms) = preSolution Debug Fortify|Win32 = Debug Fortify|Win32 Debug Fortify|x64 = Debug Fortify|x64 Debug|Win32 = Debug|Win32 Debug|x64 = Debug|x64 Debug2|Win32 = Debug2|Win32 Debug2|x64 = Debug2|x64 oops|Win32 = oops|Win32 oops|x64 = oops|x64 Release|Win32 = Release|Win32 Release|x64 = Release|x64 EndGlobalSection GlobalSection(ProjectConfigurationPlatforms) = postSolution {2098FB68-99FD-40D4-ABD6-87E2FD11D1B5}.Debug Fortify|Win32.ActiveCfg = Debug Fortify|Win32 {2098FB68-99FD-40D4-ABD6-87E2FD11D1B5}.Debug Fortify|Win32.Build.0 = Debug Fortify|Win32 {2098FB68-99FD-40D4-ABD6-87E2FD11D1B5}.Debug Fortify|x64.ActiveCfg = Debug Fortify|x64 {2098FB68-99FD-40D4-ABD6-87E2FD11D1B5}.Debug Fortify|x64.Build.0 = Debug Fortify|x64 {2098FB68-99FD-40D4-ABD6-87E2FD11D1B5}.Debug|Win32.ActiveCfg = Debug|Win32 {2098FB68-99FD-40D4-ABD6-87E2FD11D1B5}.Debug|Win32.Build.0 = Debug|Win32 {2098FB68-99FD-40D4-ABD6-87E2FD11D1B5}.Debug|x64.ActiveCfg = Debug|x64 {2098FB68-99FD-40D4-ABD6-87E2FD11D1B5}.Debug|x64.Build.0 = Debug|x64 {2098FB68-99FD-40D4-ABD6-87E2FD11D1B5}.Debug2|Win32.ActiveCfg = Debug2|Win32 {2098FB68-99FD-40D4-ABD6-87E2FD11D1B5}.Debug2|Win32.Build.0 = Debug2|Win32 {2098FB68-99FD-40D4-ABD6-87E2FD11D1B5}.Debug2|x64.ActiveCfg = Debug2|x64 {2098FB68-99FD-40D4-ABD6-87E2FD11D1B5}.Debug2|x64.Build.0 = Debug2|x64 {2098FB68-99FD-40D4-ABD6-87E2FD11D1B5}.oops|Win32.ActiveCfg = oops|Win32 {2098FB68-99FD-40D4-ABD6-87E2FD11D1B5}.oops|Win32.Build.0 = oops|Win32 {2098FB68-99FD-40D4-ABD6-87E2FD11D1B5}.oops|x64.ActiveCfg = oops|x64 {2098FB68-99FD-40D4-ABD6-87E2FD11D1B5}.oops|x64.Build.0 = oops|x64 {2098FB68-99FD-40D4-ABD6-87E2FD11D1B5}.Release|Win32.ActiveCfg = Release|Win32 {2098FB68-99FD-40D4-ABD6-87E2FD11D1B5}.Release|Win32.Build.0 = Release|Win32 {2098FB68-99FD-40D4-ABD6-87E2FD11D1B5}.Release|x64.ActiveCfg = Release|x64 {2098FB68-99FD-40D4-ABD6-87E2FD11D1B5}.Release|x64.Build.0 = Release|x64 EndGlobalSection GlobalSection(SolutionProperties) = preSolution HideSolutionNode = FALSE EndGlobalSection EndGlobal MSVMpack1.2/lp_solve_5.5/lp_solve/readme.txt0000664000175000017500000000054111141374643017763 0ustar lauerlauerThis directory contains the files to build the lp_solve program To build the program under Windows with the Visual C/C++ compiler, use cvc6.bat (also works for VS.NET) To build the program under DOS/Windows with the gcc compiler, use cgcc.bat To build the program under Linux/Unix, use sh ccc To build the program under Mac OS X 10.3.5, use sh ccc.osx MSVMpack1.2/lp_solve_5.5/lp_solve/Makefile.msc0000664000175000017500000000501010560210650020171 0ustar lauerlauer# Makefile for Microsoft visual C++ (tested on version 5, 6 & 7 (.NET)) # to be called with GMAKE # gmake -f Makefile.msc CC= cl CFLAGS= /ML /O1 /Zp8 /Gd /W2 /DWIN32 /D_WINDOWS /D_CRT_SECURE_NO_DEPRECATE /D_CRT_NONSTDC_NO_DEPRECATE /DYY_NEVER_INTERACTIVE /DPARSER_LP /I.. /I../bfp /I../bfp/bfp_etaPFI /I../colamd /I../shared /I../BFP/BFP_LUSOL/LUSOL # You can add a -DREAL= to the CFLAGS, to change the default float # type used in lp_solve (double) to float or 'long double'. However, type float # might be fast on your computer, but it is not accurate enough to solve even # moderately sized problems without running into numerical problems. # The use of long doubles does increase the numerical stability of lp_solve, # if your compiler actually implements them with more bits than a double. But # it slows down things quite a bit. # Choose your favorite or available version of lex and yacc YACC= bison --no-lines -y LEX= flex -L -l LEXLIB= #ANSI math lib MATHLIB= TESTFILES1= lp_examples/*.lp TESTFILES2= lp_examples/*.mps TARGET=lp_solve CSOURCES=../shared/commonlib.c ../shared/mmio.c ../shared/myblas.c ../ini.c ../lp_rlp.c ../lp_crash.c ../bfp/bfp_LUSOL/lp_LUSOL.c ../bfp/bfp_LUSOL/LUSOL/lusol.c ../lp_Hash.c ../lp_lib.c ../lp_wlp.c ../lp_matrix.c ../lp_mipbb.c ../lp_MPS.c ../lp_params.c ../lp_presolve.c ../lp_price.c ../lp_pricePSE.c ../lp_report.c ../lp_scale.c ../lp_simplex.c lp_solve.c ../lp_SOS.c ../lp_utils.c ../yacc_read.c ../lp_MDO.c ../colamd/colamd.c CSOURCES1=$(notdir $(CSOURCES)) COBJ=$(CSOURCES1:.c=.obj) HEADERS=../colamd/colamd.h ../shared/commonlib.h ../declare.h ../fortify.h ../bfp/lp_BFP.h ../lp_crash.h ../bfp/bfp_etaPFI/lp_etaPFI.h ../lp_fortify.h ../lp_Hash.h ../lp_lib.h ../lp_matrix.h ../lp_MDO.h ../lp_mipbb.h ../lp_MPS.h ../lp_presolve.h ../lp_price.h ../lp_pricePSE.h ../lp_report.h ../lp_rlp.h ../lp_scale.h ../lp_simplex.h ../lp_SOS.h ../lp_types.h ../lp_utils.h ../lp_wlp.h ../lpkit.h ../shared/myblas.h ../ufortify.h ../yacc_read.h ../BFP/BFP_LUSOL/LUSOL/lusol.h all: $(TARGET).exe $(TARGET).exe: lp_solve.c $(HEADERS) $(COBJ) $(CC) -o $(TARGET).exe $(CFLAGS) lp_solve.c $(COBJ) $(LEXLIB) $(MATHLIB) $(COBJ): $(HEADERS) $(CSOURCES) $(CC) -c $(CFLAGS) $(CSOURCES) ../lp_rlp.h: ../lp_rlp.l $(LEX) ../lp_rlp.l sed -e "s/yy/lp_yy/g" lex.yy.c >../lp_rlp.h rm lex.yy.c ../lp_rlp.c: ../lp_rlp.y $(YACC) ../lp_rlp.y sed -e "s/yy/lp_yy/g" y.tab.c >../lp_rlp.c rm y.tab.c clean: rm -f pe.cfg *.obj $(TARGET).exe TAGS: etags *.[chyl] MSVMpack1.2/lp_solve_5.5/lp_solve/cvc6d.bat0000775000175000017500000000003110413041622017444 0ustar lauerlauercall cvc6 -DParanoia %1 MSVMpack1.2/lp_solve_5.5/lp_solve/lp_solve.c0000664000175000017500000014313611252255034017757 0ustar lauerlauer#include #include #include #include #include #include "lp_lib.h" #ifdef FORTIFY # include "lp_fortify.h" #endif #define filetypeLP 1 #define filetypeMPS 2 #define filetypeFREEMPS 3 #define filetypeCPLEX 4 #define filetypeXLI 5 #define FORCED_EXIT 255 int EndOfPgr(int i) { # if defined FORTIFY Fortify_LeaveScope(); # endif exit(i); return(0); } void SIGABRT_func(int sig) { EndOfPgr(FORCED_EXIT); } void print_help(char *argv[]) { printf("Usage of %s version %d.%d.%d.%d:\n", argv[0], MAJORVERSION, MINORVERSION, RELEASE, BUILD); printf("%s [options] [[<]input_file]\n", argv[0]); printf("List of options:\n"); printf("-h\t\tprints this message\n"); #if defined PARSER_LP printf("-lp\t\tread from LP file (default)\n"); #endif printf("-mps\t\tread from MPS file, default in fixed format\n"); printf("-mps_free\t\tuse free format\n"); printf("-mps_ibm\t\tinterprete integers accoring to ibm format\n"); printf("-mps_negobjconst\tnegate objective constant\n"); printf("-fmps\t\tread from MPS file in free format\n"); printf("-rpar filename\tread parameters from filename.\n"); printf("-rparopt options\n\t\toptions for parameter file:\n"); printf("\t\t -H headername: header name for parameters. By default 'Default'\n"); printf("-rxli xliname filename\n\t\tread file with xli library\n"); printf("-rxlidata datafilename\n\t\tdata file name for xli library.\n"); printf("-rxliopt options\n\t\toptions for xli library.\n"); printf("-rbas filename\tread basis from filename.\n"); printf("-gbas filename\tguess basis with variables from filename.\n"); printf("-plp\t\tprint model.\n"); printf("-wlp filename\twrite to LP file\n"); printf("-wmps filename\twrite to MPS file in fixed format\n"); printf("-wfmps filename\twrite to MPS file in free format\n"); printf("-wxli xliname filename\n\t\twrite file with xli library\n"); printf("-wxliopt options\n\t\toptions for xli library.\n"); printf("-wxlisol xliname filename\n\t\twrite solution file with xli library\n"); printf("-wxlisolopt options\n\t\toptions for xli library.\n"); printf("-wbas filename\twrite basis to filename.\n"); printf("-wpar filename\twrite parameters to filename.\n"); printf("-wparopt options\n\t\toptions for parameter file:\n"); printf("\t\t -H headername: header name for parameters. By default 'Default'\n"); printf("-wafter\t\tWrite model after solve (useful if presolve used).\n"); printf("-parse_only\tparse input file but do not solve\n"); printf("-nonames\tIgnore variables and constraint names\n"); printf("-norownames\tIgnore constraint names\n"); printf("-nocolnames\tIgnore variable names\n"); printf("\n"); printf("-min\t\tMinimize the lp problem (overrules setting in file)\n"); printf("-max\t\tMaximize the lp problem (overrules setting in file)\n"); printf("-r \tspecify max nbr of pivots between a re-inversion of the matrix\n"); printf("-piv \tspecify simplex pivot rule\n"); printf("\t -piv0: Select first\n"); printf("\t -piv1: Select according to Dantzig\n"); printf("\t -piv2: Select Devex pricing from Paula Harris (default)\n"); printf("\t -piv3: Select steepest edge\n"); printf("These pivot rules can be combined with any of the following:\n"); printf("-pivf\t\tIn case of Steepest Edge, fall back to DEVEX in primal.\n"); printf("-pivm\t\tMultiple pricing.\n"); printf("-piva\t\tTemporarily use First Index if cycling is detected.\n"); printf("-pivr\t\tAdds a small randomization effect to the selected pricer.\n"); #if defined EnablePartialOptimization printf("-pivp\t\tEnable partial pricing.\n"); printf("-pivpc\t\tEnable partial pricing on columns.\n"); printf("-pivpr\t\tEnable partial pricing on rows.\n"); #endif printf("-pivll\t\tScan entering/leaving columns left rather than right.\n"); printf("-pivla\t\tScan entering/leaving columns alternatingly left/right.\n"); printf("-pivh\t\tUse Harris' primal pivot logic rather than the default.\n"); printf("-pivt\t\tUse true norms for Devex and Steepest Edge initializations.\n"); printf("-o0\t\tDon't put objective in basis%s.\n", DEF_OBJINBASIS ? "" : " (default)"); printf("-o1\t\tPut objective in basis%s.\n", DEF_OBJINBASIS ? " (default)" : ""); printf("-s \tuse automatic problem scaling.\n"); printf("\t -s0: No scaling\n"); printf("\t -s1: Geometric scaling (default)\n"); printf("\t -s2: Curtis-reid scaling\n"); printf("\t -s3: Scale to convergence using largest absolute value\n"); printf("\t -s:\n"); printf("\t -s4: Numerical range-based scaling\n"); printf("\t -s5: Scale to convergence using logarithmic mean of all values\n"); printf("\t -s6: Scale based on the simple numerical range\n"); printf("\t -s7: Scale quadratic\n"); printf("These scaling rules can be combined with any of the following:\n"); printf("-sp\t\talso do power scaling.\n"); printf("-si\t\talso do Integer scaling (default).\n"); printf("-se\t\talso do equilibration to scale to the -1..1 range (default).\n"); printf("-presolve\tpresolve problem before start optimizing (rows+columns)\n"); printf("-presolverow\tpresolve problem before start optimizing (rows only)\n"); printf("-presolvecol\tpresolve problem before start optimizing (columns only)\n"); printf("-presolvel\talso eliminate linearly dependent rows\n"); printf("-presolves\talso convert constraints to SOSes (only SOS1 handled)\n"); printf("-presolver\tIf the phase 1 solution process finds that a constraint is\n\t\tredundant then this constraint is deleted\n"); printf("-presolvek\tSimplification of knapsack-type constraints through\n\t\taddition of an extra variable, which also helps bound the OF\n"); printf("-presolveq\tDirect substitution of one variable in 2-element equality\n\t\tconstraints; this requires changes to the constraint matrix\n"); printf("-presolvem\tMerge rows\n"); printf("-presolvefd\tCOLFIXDUAL\n"); printf("-presolvebnd\tPresolve bounds\n"); printf("-presolved\tPresolve duals\n"); printf("-presolvef\tIdentify implied free variables (releasing their expl. bounds)\n"); printf("-presolveslk\tIMPLIEDSLK\n"); printf("-presolveg\tReduce (tighten) coef. in integer models based on GCD argument\n"); printf("-presolveb\tAttempt to fix binary variables at one of their bounds\n"); printf("-presolvec\tAttempt to reduce coefficients in binary models\n"); printf("-presolverowd\tIdenfify and delete qualifying constraints that\n\t\tare dominated by others, also fixes variables at a bound\n"); printf("-presolvecold\tDeletes variables (mainly binary), that are dominated\n\t\tby others (only one can be non-zero)\n"); printf("-C \tbasis crash mode\n"); printf("\t -C0: No crash basis\n"); printf("\t -C2: Most feasible basis\n"); printf("\t -C3: Least degenerate basis\n"); printf("-prim\t\tPrefer the primal simplex for both phases.\n"); printf("-dual\t\tPrefer the dual simplex for both phases.\n"); printf("-simplexpp\tSet Phase1 Primal, Phase2 Primal.\n"); printf("-simplexdp\tSet Phase1 Dual, Phase2 Primal.\n"); printf("-simplexpd\tSet Phase1 Primal, Phase2 Dual.\n"); printf("-simplexdd\tSet Phase1 Dual, Phase2 Dual.\n"); printf("-degen\t\tuse perturbations to reduce degeneracy,\n\t\tcan increase numerical instability\n"); printf("-degenc\t\tuse column check to reduce degeneracy\n"); printf("-degend\t\tdynamic check to reduce degeneracy\n"); printf("-degenf\t\tanti-degen fixedvars\n"); printf("-degens\t\tanti-degen stalling\n"); printf("-degenn\t\tanti-degen numfailure\n"); printf("-degenl\t\tanti-degen lostfeas\n"); printf("-degeni\t\tanti-degen infeasible\n"); printf("-degenb\t\tanti-degen B&B\n"); printf("-degenr\t\tanti-degen Perturbation of the working RHS at refactorization\n"); printf("-degenp\t\tanti-degen Limit bound flips\n"); printf("-trej \tset minimum pivot value\n"); printf("-epsd \tset minimum tolerance for reduced costs\n"); printf("-epsb \tset minimum tolerance for the RHS\n"); printf("-epsel \tset tolerance for rounding values to zero\n"); printf("-epsp \tset the value that is used as perturbation scalar for\n\t\tdegenerative problems\n"); printf("-improve \titerative improvement level\n"); printf("\t -improve0: none\n"); printf("\t -improve1: Running accuracy measurement of solved equations on Bx=r\n"); printf("\t -improve2: Improve initial dual feasibility by bound flips (default)\n"); printf("\t -improve4: Low-cost accuracy monitoring in the dual\n"); printf("\t -improve8: check for primal/dual feasibility at the node level\n"); printf("-timeout \tTimeout after sec seconds when not solution found.\n"); /* printf("-timeoutok\tIf timeout, take the best yet found solution.\n"); */ printf("-bfp \tSet basis factorization package.\n"); printf("\n"); printf("-noint\t\tIgnore integer restrictions\n"); printf("-e \tspecifies the tolerance which is used to determine whether a\n\t\tfloating point number is in fact an integer.\n\t\tShould be < 0.5\n"); printf("-g \n"); printf("-ga \tspecifies the absolute MIP gap for branch-and-bound.\n\t\tThis specifies the absolute allowed tolerance\n\t\ton the object function. Can result in faster solving times.\n"); printf("-gr \tspecifies the relative MIP gap for branch-and-bound.\n\t\tThis specifies the relative allowed tolerance\n\t\ton the object function. Can result in faster solving times.\n"); printf("-f\t\tspecifies that branch-and-bound algorithm stops at first found\n"); printf("\t\tsolution\n"); printf("-b \tspecify a lower bound for the objective function\n\t\tto the program. If close enough, may speed up the\n\t\tcalculations.\n"); printf("-o \tspecifies that branch-and-bound algorithm stops when objective\n"); printf("\t\tvalue is better than value\n"); printf("-c\n"); printf("-cc\t\tduring branch-and-bound, take the ceiling branch first\n"); printf("-cf\t\tduring branch-and-bound, take the floor branch first\n"); printf("-ca\t\tduring branch-and-bound, the algorithm chooses branch\n"); printf("-depth \tset branch-and-bound depth limit\n"); printf("-n \tspecify which solution number to return\n"); printf("-B \tspecify branch-and-bound rule\n"); printf("\t -B0: Select Lowest indexed non-integer column (default)\n"); printf("\t -B1: Selection based on distance from the current bounds\n"); printf("\t -B2: Selection based on the largest current bound\n"); printf("\t -B3: Selection based on largest fractional value\n"); printf("\t -B4: Simple, unweighted pseudo-cost of a variable\n"); printf("\t -B5: This is an extended pseudo-costing strategy based on minimizing\n\t the number of integer infeasibilities\n"); printf("\t -B6: This is an extended pseudo-costing strategy based on maximizing\n\t the normal pseudo-cost divided by the number of infeasibilities.\n\t Similar to (the reciprocal of) a cost/benefit ratio\n"); printf("These branch-and-bound rules can be combined with any of the following:\n"); printf("-Bw\t\tWeightReverse branch-and-bound\n"); printf("-Bb\t\tBranchReverse branch-and-bound\n"); printf("-Bg\t\tGreedy branch-and-bound\n"); printf("-Bp\t\tPseudoCost branch-and-bound\n"); printf("-Bf\t\tDepthFirst branch-and-bound\n"); printf("-Br\t\tRandomize branch-and-bound\n"); printf("-BG\t\tGubMode branch-and-bound\n"); printf("-Bd\t\tDynamic branch-and-bound\n"); printf("-Bs\t\tRestartMode branch-and-bound\n"); printf("-BB\t\tBreadthFirst branch-and-bound\n"); printf("-Bo\t\tOrder variables to improve branch-and-bound performance\n"); printf("-Bc\t\tDo bound tightening during B&B based of reduced cost info\n"); printf("-Bi\t\tInitialize pseudo-costs by strong branching\n"); printf("\n"); printf("-time\t\tPrint CPU time to parse input and to calculate result.\n"); printf("-v \tverbose mode, gives flow through the program.\n"); printf("\t\t if level not provided (-v) then -v4 (NORMAL) is taken.\n"); printf("\t -v0: NEUTRAL\n"); printf("\t -v1: CRITICAL\n"); printf("\t -v2: SEVERE\n"); printf("\t -v3: IMPORTANT (default)\n"); printf("\t -v4: NORMAL\n"); printf("\t -v5: DETAILED\n"); printf("\t -v6: FULL\n"); printf("-t\t\ttrace pivot selection\n"); printf("-d\t\tdebug mode, all intermediate results are printed,\n\t\tand the branch-and-bound decisions\n"); printf("-R\t\treport information while solving the model\n"); printf("-Db \tDo a generic readable data dump of key lp_solve model variables\n\t\tbefore solve.\n\t\tPrincipally for run difference and debugging purposes\n"); printf("-Da \tDo a generic readable data dump of key lp_solve model variables\n\t\tafter solve.\n\t\tPrincipally for run difference and debugging purposes\n"); printf("-i\t\tprint all intermediate valid solutions.\n\t\tCan give you useful solutions even if the total run time\n\t\tis too long\n"); printf("-ia\t\tprint all intermediate (only non-zero values) valid solutions.\n\t\tCan give you useful solutions even if the total run time\n\t\tis too long\n"); printf("-stat\t\tPrint model statistics\n"); printf("-S \tPrint solution. If detail omitted, then -S2 is used.\n"); printf("\t -S0: Print nothing\n"); printf("\t -S1: Only objective value\n"); printf("\t -S2: Obj value+variables (default)\n"); printf("\t -S3: Obj value+variables+constraints\n"); printf("\t -S4: Obj value+variables+constraints+duals\n"); printf("\t -S5: Obj value+variables+constraints+duals+lp model\n"); printf("\t -S6: Obj value+variables+constraints+duals+lp model+scales\n"); printf("\t -S7: Obj value+variables+constraints+duals+lp model+scales+lp tableau\n"); } void print_cpu_times(const char *info) { static clock_t last_time = 0; clock_t new_time; new_time = clock(); fprintf(stderr, "CPU Time for %s: %gs (%gs total since program start)\n", info, (new_time - last_time) / (double) CLOCKS_PER_SEC, new_time / (double) CLOCKS_PER_SEC); last_time = new_time; } #if 0 int myabortfunc(lprec *lp, void *aborthandle) { /* printf("%f\n",lp->rhs[0]*(lp->maximise ? 1 : -1)); */ return(0); } #endif static MYBOOL isNum(char *val) { int ord; char *pointer; ord = strtol(val, &pointer, 10); return(*pointer == 0); } static void DoReport(lprec *lp, char *str) { fprintf(stderr, "%s %6.1fsec %8g\n", str, time_elapsed(lp), get_working_objective(lp)); } static void __WINAPI LPMessageCB(lprec *lp, void *USERHANDLE, int msg) { if(msg==MSG_LPFEASIBLE) DoReport(lp, "Feasible solution "); else if(msg==MSG_LPOPTIMAL) DoReport(lp, "Real solution "); else if(msg==MSG_MILPFEASIBLE) DoReport(lp, "First MILP "); else if(msg==MSG_MILPBETTER) DoReport(lp, "Improved MILP "); } void write_model(lprec *lp, char plp, char *wlp, char *wmps, char *wfmps, char *wxli, char *wxlisol, char *wxliname, char *wxlioptions) { if(plp) print_lp(lp); if(wlp != NULL) write_lp(lp, wlp); if(wmps != NULL) write_mps(lp, wmps); if(wfmps != NULL) write_freemps(lp, wfmps); if((wxliname != NULL) && (wxli != NULL)) { if(!set_XLI(lp, wxliname)) { fprintf(stderr, "Unable to set XLI library (%s).\n", wxliname); EndOfPgr(FORCED_EXIT); } write_XLI(lp, wxli, wxlioptions, FALSE); set_XLI(lp, NULL); } if((wxliname != NULL) && (wxlisol != NULL)) { if(!set_XLI(lp, wxliname)) { fprintf(stderr, "Unable to set XLI library (%s).\n", wxliname); EndOfPgr(FORCED_EXIT); } write_XLI(lp, wxlisol, wxlioptions, TRUE); set_XLI(lp, NULL); } } static void or_value(int *value, int orvalue) { if(*value == -1) *value = 0; *value |= orvalue; } static void set_value(int *value, int orvalue) { *value = orvalue; } #define nstats 5 static void minmax1(REAL value0, REAL factor, REAL *minmax, int *nminmax, int row, int *rowminmax, int col, int *colminmax) { int i, n; REAL value; if (value0 == 0) return; value = fabs(value0) * factor; for (i = 0; (i < *nminmax) && (value <= fabs(minmax[i]) * factor); i++) if (value == fabs(minmax[i]) * factor) return; if (i >= nstats) return; n = *nminmax; if (n == nstats) n--; memmove(minmax + i + 1, minmax + i, (n - i) * sizeof(*minmax)); minmax[i] = value0; if (rowminmax != NULL) { memmove(rowminmax + i + 1, rowminmax + i, (n - i) * sizeof(*rowminmax)); rowminmax[i] = row; } if (colminmax != NULL) { memmove(colminmax + i + 1, colminmax + i, (n - i) * sizeof(*colminmax)); colminmax[i] = col; } if (*nminmax < nstats) (*nminmax)++; } static void minmax(REAL value, REAL *minima, REAL *maxima, int *nminima, int *nmaxima, int row, int *rowmin, int *rowmax, int col, int *colmin, int *colmax) { minmax1(value, -1.0, minima, nminima, row, rowmin, col, colmin); minmax1(value, +1.0, maxima, nmaxima, row, rowmax, col, colmax); } /* static void printminmax1(lprec *lp, char *s, REAL *minmax, int nminmax, int *rowminmax, int *colminmax) { int i; for (i = 0; i < nminmax; i++) { printf(" %s(", s); if (rowminmax != NULL) printf("%s", get_row_name(lp, rowminmax[i])); if ((rowminmax != NULL) && (colminmax != NULL)) printf(", "); if (colminmax != NULL) printf("%s", get_col_name(lp, colminmax[i])); printf(") = %.8f\n", minmax[i]); } } static void printminmax(lprec *lp, char *s, REAL *minima, REAL *maxima, int nminima, int nmaxima, int *rowmin, int *rowmax, int *colmin, int *colmax) { printf("Minima:\n"); printminmax1(lp, s, minima, nminima, rowmin, colmin); printf("Maxima:\n"); printminmax1(lp, s, maxima, nmaxima, rowmax, colmax); } */ static void printminmax(lprec *lp, char *s, REAL *minima, REAL *maxima, int nminima, int nmaxima, int *rowmin, int *rowmax, int *colmin, int *colmax) { int i, nminmax, n; nminmax = nminima; if (nmaxima > nminmax) nminmax = nmaxima; for (i = 0; i < nminmax; i++) { n = 0; if (i < nminima) { n += printf("%s(", s); if (rowmin != NULL) n+= printf("%s", get_row_name(lp, rowmin[i])); if ((rowmin != NULL) && (colmin != NULL)) n += printf(", "); if (colmin != NULL) n += printf("%s", get_col_name(lp, colmin[i])); n += printf(") = %.8f", minima[i]); } if (n < 40) n = 40 - n; else n = 1; printf("%*.*s", n, n, ""); if (i < nmaxima) { n += printf("%s(", s); if (rowmax != NULL) n+= printf("%s", get_row_name(lp, rowmax[i])); if ((rowmax != NULL) && (colmax != NULL)) n += printf(", "); if (colmax != NULL) n += printf("%s", get_col_name(lp, colmax[i])); n += printf(") = %.8f", maxima[i]); } printf("\n"); } } static void print_statistics(lprec *lp) { REAL *col, *RHSmin, *RHSmax, *OBJmin, *OBJmax, *MATmin, *MATmax; int *nz, ret, m, n, i, j, k, l, nRHSmin = 0, nRHSmax = 0, nOBJmin = 0, nOBJmax = 0, nMATmin = 0, nMATmax = 0, *rowRHSmin, *rowRHSmax, *colOBJmin, *colOBJmax, *rowMATmin, *rowMATmax, *colMATmin, *colMATmax; m = get_Nrows(lp); n = get_Ncolumns(lp); col = (REAL *) malloc((1 + m) * sizeof(*col)); nz = (int *) malloc((1 + m) * sizeof(*RHSmin)); RHSmin = (REAL *) malloc(nstats * sizeof(*RHSmin)); RHSmax = (REAL *) malloc(nstats * sizeof(*RHSmax)); rowRHSmin = (int *) malloc(nstats * sizeof(*RHSmin)); rowRHSmax = (int *) malloc(nstats * sizeof(*RHSmax)); OBJmin = (REAL *) malloc(nstats * sizeof(*OBJmin)); OBJmax = (REAL *) malloc(nstats * sizeof(*OBJmax)); colOBJmin = (int *) malloc(nstats * sizeof(*colOBJmin)); colOBJmax = (int *) malloc(nstats * sizeof(*colOBJmax)); MATmin = (REAL *) malloc(nstats * sizeof(*MATmin)); MATmax = (REAL *) malloc(nstats * sizeof(*MATmax)); rowMATmin = (int *) malloc(nstats * sizeof(*rowMATmin)); rowMATmax = (int *) malloc(nstats * sizeof(*rowMATmax)); colMATmin = (int *) malloc(nstats * sizeof(*colMATmin)); colMATmax = (int *) malloc(nstats * sizeof(*colMATmax)); /* minmax(2.0, MATmin, MATmax, &nMATmin, &nMATmax, 1, rowMATmin, rowMATmax, 8, colMATmin, colMATmax); minmax(1.0, MATmin, MATmax, &nMATmin, &nMATmax, 2, rowMATmin, rowMATmax, 7, colMATmin, colMATmax); minmax(1.5, MATmin, MATmax, &nMATmin, &nMATmax, 3, rowMATmin, rowMATmax, 6, colMATmin, colMATmax); minmax(3.0, MATmin, MATmax, &nMATmin, &nMATmax, 4, rowMATmin, rowMATmax, 5, colMATmin, colMATmax); minmax(4.0, MATmin, MATmax, &nMATmin, &nMATmax, 5, rowMATmin, rowMATmax, 4, colMATmin, colMATmax); minmax(0.1, MATmin, MATmax, &nMATmin, &nMATmax, 6, rowMATmin, rowMATmax, 3, colMATmin, colMATmax); minmax(5.0, MATmin, MATmax, &nMATmin, &nMATmax, 7, rowMATmin, rowMATmax, 2, colMATmin, colMATmax); minmax(1.4, MATmin, MATmax, &nMATmin, &nMATmax, 8, rowMATmin, rowMATmax, 1, colMATmin, colMATmax); printminmax(MATmin, MATmax, nMATmin, nMATmax, rowMATmin, rowMATmax, colMATmin, colMATmax); */ for (i = 1; i <= m; i++) minmax(get_rh(lp, i), RHSmin, RHSmax, &nRHSmin, &nRHSmax, i, rowRHSmin, rowRHSmax, 0, NULL, NULL); for (j = 1; j <= n; j++) { ret = get_columnex(lp, j, col, nz); for (i = 0; i < ret; i++) if (nz[i] == 0) minmax(col[i], OBJmin, OBJmax, &nOBJmin, &nOBJmax, 0, NULL, NULL, j, colOBJmin, colOBJmax); else minmax(col[i], MATmin, MATmax, &nMATmin, &nMATmax, nz[i], rowMATmin, rowMATmax, j, colMATmin, colMATmax); } printf("Constraints: %d\n", get_Nrows(lp)); printf("Variables : %d\n", get_Ncolumns(lp)); for (j = k = l = 0, i = n; i >= 1; i--) { if (is_int(lp, i)) j++; if (is_semicont(lp, i)) k++; if (is_SOS_var(lp, i)) l++; } printf("Integers : %d\n", j); printf("Semi-cont : %d\n", k); printf("SOS : %d\n", l); k = get_nonzeros(lp); printf("Non-zeros : %d\tdensity=%f%%\n", k, ((double) k) / (((double) m) * ((double) n)) * 100.0); printf("\nAbsolute Ranges:\n\n Minima Maxima\n"); printf("\nMatrix Coeficients:\n"); printminmax(lp, "A", MATmin, MATmax, nMATmin, nMATmax, rowMATmin, rowMATmax, colMATmin, colMATmax); printf("\nObj. Vector:\n"); printminmax(lp, "c", OBJmin, OBJmax, nOBJmin, nOBJmax, NULL, NULL, colOBJmin, colOBJmax); printf("\nRHS Vector:\n"); printminmax(lp, "b", RHSmin, RHSmax, nRHSmin, nRHSmax, rowRHSmin, rowRHSmax, NULL, NULL); free(col); free(nz); free(RHSmin); free(RHSmax); free(rowRHSmin); free(rowRHSmax); free(OBJmin); free(OBJmax); free(colOBJmin); free(colOBJmax); free(MATmin); free(MATmax); free(rowMATmin); free(rowMATmax); free(colMATmin); free(colMATmax); } int main(int argc, char *argv[]) { lprec *lp = NULL; char *filen, *wlp = NULL, *wmps = NULL, *wfmps = NULL, plp = FALSE; int i; int verbose = IMPORTANT /* CRITICAL */; int debug = -1; MYBOOL report = FALSE; MYBOOL nonames = FALSE, norownames = FALSE, nocolnames = FALSE; MYBOOL write_model_after = FALSE; MYBOOL noint = FALSE; int print_sol = -1; MYBOOL print_stats = FALSE; int floor_first = -1; MYBOOL do_set_bb_depthlimit = FALSE; int bb_depthlimit = 0; MYBOOL do_set_solutionlimit = FALSE; int solutionlimit = 0; MYBOOL break_at_first = FALSE; int scaling = 0; double scaleloop = 0; MYBOOL tracing = FALSE; short filetype = filetypeLP; int anti_degen1 = -1; int anti_degen2 = -1; short print_timing = FALSE; short parse_only = FALSE; int do_presolve = -1; short objective = 0; short PRINT_SOLUTION = 2; int improve = -1; int pivoting1 = -1; int pivoting2 = -1; int bb_rule1 = -1; int bb_rule2 = -1; int max_num_inv = -1; int scalemode1 = -1; int scalemode2 = -1; int crashmode = -1; char *guessbasis = NULL; /* short timeoutok = FALSE; */ long sectimeout = -1; int result; MYBOOL preferdual = AUTOMATIC; int simplextype = -1; MYBOOL do_set_obj_bound = FALSE; REAL obj_bound = 0; REAL mip_absgap = -1; REAL mip_relgap = -1; REAL epsperturb = -1; REAL epsint = -1; REAL epspivot = -1; REAL epsd = -1; REAL epsb = -1; REAL epsel = -1; MYBOOL do_set_break_at_value = FALSE; REAL break_at_value = 0; FILE *fpin = stdin; char *bfp = NULL; char *rxliname = NULL, *rxli = NULL, *rxlidata = NULL, *rxlioptions = NULL, *wxliname = NULL, *wxlisol = NULL, *wxli = NULL, *wxlioptions = NULL, *wxlisoloptions = NULL; char *rbasname = NULL, *wbasname = NULL; char *debugdump_before = NULL; char *debugdump_after = NULL; char *rparname = NULL; char *rparoptions = NULL; char *wparname = NULL; char *wparoptions = NULL; char obj_in_basis = -1; char mps_ibm = FALSE; char mps_negobjconst = FALSE; char mps_free = FALSE; MYBOOL ok; # define SCALINGTHRESHOLD 0.03 /* read command line arguments */ # if defined FORTIFY Fortify_EnterScope(); # endif for(i = 1; i < argc; i++) { ok = FALSE; if(strncmp(argv[i], "-v", 2) == 0) { if (argv[i][2]) verbose = atoi(argv[i] + 2); else verbose = NORMAL; } else if(strcmp(argv[i], "-d") == 0) debug = TRUE; else if(strcmp(argv[i], "-R") == 0) report = TRUE; else if(strcmp(argv[i], "-i") == 0) print_sol = TRUE; else if(strcmp(argv[i], "-ia") == 0) print_sol = AUTOMATIC; else if(strcmp(argv[i], "-stat") == 0) print_stats = TRUE; else if(strcmp(argv[i], "-nonames") == 0) nonames = TRUE; else if(strcmp(argv[i], "-norownames") == 0) norownames = TRUE; else if(strcmp(argv[i], "-nocolnames") == 0) nocolnames = TRUE; else if((strcmp(argv[i], "-c") == 0) || (strcmp(argv[i], "-cc") == 0)) floor_first = BRANCH_CEILING; else if(strcmp(argv[i], "-cf") == 0) floor_first = BRANCH_FLOOR; else if(strcmp(argv[i], "-ca") == 0) floor_first = BRANCH_AUTOMATIC; else if((strcmp(argv[i], "-depth") == 0) && (i + 1 < argc)) { do_set_bb_depthlimit = TRUE; bb_depthlimit = atoi(argv[++i]); } else if(strcmp(argv[i], "-Bw") == 0) or_value(&bb_rule2, NODE_WEIGHTREVERSEMODE); else if(strcmp(argv[i], "-Bb") == 0) or_value(&bb_rule2, NODE_BRANCHREVERSEMODE); else if(strcmp(argv[i], "-Bg") == 0) or_value(&bb_rule2, NODE_GREEDYMODE); else if(strcmp(argv[i], "-Bp") == 0) or_value(&bb_rule2, NODE_PSEUDOCOSTMODE); else if(strcmp(argv[i], "-Bf") == 0) or_value(&bb_rule2, NODE_DEPTHFIRSTMODE); else if(strcmp(argv[i], "-Br") == 0) or_value(&bb_rule2, NODE_RANDOMIZEMODE); else if(strcmp(argv[i], "-BG") == 0) or_value(&bb_rule2, 0 /* NODE_GUBMODE */); /* doesn't work yet */ else if(strcmp(argv[i], "-Bd") == 0) or_value(&bb_rule2, NODE_DYNAMICMODE); else if(strcmp(argv[i], "-Bs") == 0) or_value(&bb_rule2, NODE_RESTARTMODE); else if(strcmp(argv[i], "-BB") == 0) or_value(&bb_rule2, NODE_BREADTHFIRSTMODE); else if(strcmp(argv[i], "-Bo") == 0) or_value(&bb_rule2, NODE_AUTOORDER); else if(strcmp(argv[i], "-Bc") == 0) or_value(&bb_rule2, NODE_RCOSTFIXING); else if(strcmp(argv[i], "-Bi") == 0) or_value(&bb_rule2, NODE_STRONGINIT); else if(strncmp(argv[i], "-B", 2) == 0) { if (argv[i][2]) set_value(&bb_rule1, atoi(argv[i] + 2)); else set_value(&bb_rule1, NODE_FIRSTSELECT); } else if((strcmp(argv[i], "-n") == 0) && (i + 1 < argc)) { do_set_solutionlimit = TRUE; solutionlimit = atoi(argv[++i]); } else if((strcmp(argv[i], "-b") == 0) && (i + 1 < argc)) { obj_bound = atof(argv[++i]); do_set_obj_bound = TRUE; } else if(((strcmp(argv[i], "-g") == 0) || (strcmp(argv[i], "-ga") == 0)) && (i + 1 < argc)) mip_absgap = atof(argv[++i]); else if((strcmp(argv[i], "-gr") == 0) && (i + 1 < argc)) mip_relgap = atof(argv[++i]); else if((strcmp(argv[i], "-e") == 0) && (i + 1 < argc)) { epsint = atof(argv[++i]); if((epsint <= 0.0) || (epsint >= 0.5)) { fprintf(stderr, "Invalid tolerance %g; 0 < epsilon < 0.5\n", (double)epsint); EndOfPgr(FORCED_EXIT); } } else if((strcmp(argv[i], "-r") == 0) && (i + 1 < argc)) max_num_inv = atoi(argv[++i]); else if((strcmp(argv[i], "-o") == 0) && (i + 1 < argc)) { break_at_value = atof(argv[++i]); do_set_break_at_value = TRUE; } else if(strcmp(argv[i], "-f") == 0) break_at_first = TRUE; else if(strcmp(argv[i], "-timeoutok") == 0) /* timeoutok = TRUE */; /* option no longer needed, but still accepted */ else if(strcmp(argv[i], "-h") == 0) { print_help(argv); EndOfPgr(EXIT_SUCCESS); } else if(strcmp(argv[i], "-prim") == 0) preferdual = FALSE; else if(strcmp(argv[i], "-dual") == 0) preferdual = TRUE; else if(strcmp(argv[i], "-simplexpp") == 0) simplextype = SIMPLEX_PRIMAL_PRIMAL; else if(strcmp(argv[i], "-simplexdp") == 0) simplextype = SIMPLEX_DUAL_PRIMAL; else if(strcmp(argv[i], "-simplexpd") == 0) simplextype = SIMPLEX_PRIMAL_DUAL; else if(strcmp(argv[i], "-simplexdd") == 0) simplextype = SIMPLEX_DUAL_DUAL; else if(strcmp(argv[i], "-sp") == 0) or_value(&scalemode2, SCALE_POWER2); else if(strcmp(argv[i], "-si") == 0) or_value(&scalemode2, SCALE_INTEGERS); else if(strcmp(argv[i], "-se") == 0) or_value(&scalemode2, SCALE_EQUILIBRATE); else if(strncmp(argv[i], "-s", 2) == 0) { set_value(&scalemode1, SCALE_NONE); scaling = SCALE_MEAN; if (argv[i][2]) { switch (atoi(argv[i] + 2)) { case 0: scaling = SCALE_NONE; break; case 1: set_value(&scalemode1, SCALE_GEOMETRIC); break; case 2: set_value(&scalemode1, SCALE_CURTISREID); break; case 3: set_value(&scalemode1, SCALE_EXTREME); break; case 4: set_value(&scalemode1, SCALE_MEAN); break; case 5: set_value(&scalemode1, SCALE_MEAN | SCALE_LOGARITHMIC); break; case 6: set_value(&scalemode1, SCALE_RANGE); break; case 7: set_value(&scalemode1, SCALE_MEAN | SCALE_QUADRATIC); break; } } else set_value(&scalemode1, SCALE_MEAN); if((i + 1 < argc) && (isNum(argv[i + 1]))) scaleloop = atoi(argv[++i]); } else if(strncmp(argv[i], "-C", 2) == 0) crashmode = atoi(argv[i] + 2); else if((strcmp(argv[i],"-gbas") == 0) && (i + 1 < argc)) guessbasis = argv[++i]; else if(strcmp(argv[i], "-t") == 0) tracing = TRUE; else if(strncmp(argv[i], "-S", 2) == 0) { if (argv[i][2]) PRINT_SOLUTION = (short) atoi(argv[i] + 2); else PRINT_SOLUTION = 2; } else if(strncmp(argv[i], "-improve", 8) == 0) { if (argv[i][8]) or_value(&improve, atoi(argv[i] + 8)); } else if(strcmp(argv[i], "-pivll") == 0) or_value(&pivoting2, PRICE_LOOPLEFT); else if(strcmp(argv[i], "-pivla") == 0) or_value(&pivoting2, PRICE_LOOPALTERNATE); #if defined EnablePartialOptimization else if(strcmp(argv[i], "-pivpc") == 0) or_value(&pivoting2, PRICE_AUTOPARTIALCOLS); else if(strcmp(argv[i], "-pivpr") == 0) or_value(&pivoting2, PRICE_AUTOPARTIALROWS); else if(strcmp(argv[i], "-pivp") == 0) or_value(&pivoting2, PRICE_AUTOPARTIAL); #endif else if(strcmp(argv[i], "-pivf") == 0) or_value(&pivoting2, PRICE_PRIMALFALLBACK); else if(strcmp(argv[i], "-pivm") == 0) or_value(&pivoting2, PRICE_MULTIPLE); else if(strcmp(argv[i], "-piva") == 0) or_value(&pivoting2, PRICE_ADAPTIVE); else if(strcmp(argv[i], "-pivr") == 0) or_value(&pivoting2, PRICE_RANDOMIZE); else if(strcmp(argv[i], "-pivh") == 0) or_value(&pivoting2, PRICE_HARRISTWOPASS); else if(strcmp(argv[i], "-pivt") == 0) or_value(&pivoting2, PRICE_TRUENORMINIT); else if(strncmp(argv[i], "-piv", 4) == 0) { if (argv[i][4]) set_value(&pivoting1, atoi(argv[i] + 4)); else set_value(&pivoting1, PRICER_DEVEX | PRICE_ADAPTIVE); } #if defined PARSER_LP else if(strcmp(argv[i],"-lp") == 0) filetype = filetypeLP; #endif else if((strcmp(argv[i],"-wlp") == 0) && (i + 1 < argc)) wlp = argv[++i]; else if(strcmp(argv[i],"-plp") == 0) plp = TRUE; else if(strcmp(argv[i],"-mps") == 0) filetype = filetypeMPS; else if(strcmp(argv[i],"-mps_ibm") == 0) mps_ibm = TRUE; else if(strcmp(argv[i],"-mps_negobjconst") == 0) mps_negobjconst = TRUE; else if(strcmp(argv[i],"-mps_free") == 0) mps_free = TRUE; else if(strcmp(argv[i],"-fmps") == 0) filetype = filetypeFREEMPS; else if((strcmp(argv[i],"-wmps") == 0) && (i + 1 < argc)) wmps = argv[++i]; else if((strcmp(argv[i],"-wfmps") == 0) && (i + 1 < argc)) wfmps = argv[++i]; else if(strcmp(argv[i],"-wafter") == 0) write_model_after = TRUE; else if(strcmp(argv[i],"-degen") == 0) set_value(&anti_degen1, ANTIDEGEN_DEFAULT); else if(strcmp(argv[i],"-degenf") == 0) or_value(&anti_degen2, ANTIDEGEN_FIXEDVARS); else if(strcmp(argv[i],"-degenc") == 0) or_value(&anti_degen2, ANTIDEGEN_COLUMNCHECK); else if(strcmp(argv[i],"-degens") == 0) or_value(&anti_degen2, ANTIDEGEN_STALLING); else if(strcmp(argv[i],"-degenn") == 0) or_value(&anti_degen2, ANTIDEGEN_NUMFAILURE); else if(strcmp(argv[i],"-degenl") == 0) or_value(&anti_degen2, ANTIDEGEN_LOSTFEAS); else if(strcmp(argv[i],"-degeni") == 0) or_value(&anti_degen2, ANTIDEGEN_INFEASIBLE); else if(strcmp(argv[i],"-degend") == 0) or_value(&anti_degen2, ANTIDEGEN_DYNAMIC); else if(strcmp(argv[i],"-degenb") == 0) or_value(&anti_degen2, ANTIDEGEN_DURINGBB); else if(strcmp(argv[i],"-degenr") == 0) or_value(&anti_degen2, ANTIDEGEN_RHSPERTURB); else if(strcmp(argv[i],"-degenp") == 0) or_value(&anti_degen2, ANTIDEGEN_BOUNDFLIP); else if(strcmp(argv[i],"-time") == 0) { if(clock() == -1) fprintf(stderr, "CPU times not available on this machine\n"); else print_timing = TRUE; } else if((strcmp(argv[i],"-bfp") == 0) && (i + 1 < argc)) bfp = argv[++i]; else if((strcmp(argv[i],"-rxli") == 0) && (i + 2 < argc)) { rxliname = argv[++i]; rxli = argv[++i]; fpin = NULL; filetype = filetypeXLI; } else if((strcmp(argv[i],"-rxlidata") == 0) && (i + 1 < argc)) rxlidata = argv[++i]; else if((strcmp(argv[i],"-rxliopt") == 0) && (i + 1 < argc)) rxlioptions = argv[++i]; else if((strcmp(argv[i],"-wxli") == 0) && (i + 2 < argc)) { wxliname = argv[++i]; wxli = argv[++i]; } else if((strcmp(argv[i],"-wxliopt") == 0) && (i + 1 < argc)) wxlioptions = argv[++i]; else if((strcmp(argv[i],"-wxlisol") == 0) && (i + 2 < argc)) { wxliname = argv[++i]; wxlisol = argv[++i]; } else if((strcmp(argv[i],"-wxlisolopt") == 0) && (i + 1 < argc)) wxlisoloptions = argv[++i]; else if((strcmp(argv[i],"-rbas") == 0) && (i + 1 < argc)) rbasname = argv[++i]; else if((strcmp(argv[i],"-wbas") == 0) && (i + 1 < argc)) wbasname = argv[++i]; else if((strcmp(argv[i],"-Db") == 0) && (i + 1 < argc)) debugdump_before = argv[++i]; else if((strcmp(argv[i],"-Da") == 0) && (i + 1 < argc)) debugdump_after = argv[++i]; else if((strcmp(argv[i],"-timeout") == 0) && (i + 1 < argc)) sectimeout = atol(argv[++i]); else if((strcmp(argv[i],"-trej") == 0) && (i + 1 < argc)) epspivot = atof(argv[++i]); else if((strcmp(argv[i],"-epsp") == 0) && (i + 1 < argc)) epsperturb = atof(argv[++i]); else if((strcmp(argv[i],"-epsd") == 0) && (i + 1 < argc)) epsd = atof(argv[++i]); else if((strcmp(argv[i],"-epsb") == 0) && (i + 1 < argc)) epsb = atof(argv[++i]); else if((strcmp(argv[i],"-epsel") == 0) && (i + 1 < argc)) epsel = atof(argv[++i]); else if(strcmp(argv[i],"-parse_only") == 0) parse_only = TRUE; else ok = TRUE; if(!ok) ; else if(strcmp(argv[i],"-presolverow") == 0) or_value(&do_presolve, PRESOLVE_ROWS); else if(strcmp(argv[i],"-presolvecol") == 0) or_value(&do_presolve, PRESOLVE_COLS); else if(strcmp(argv[i],"-presolve") == 0) or_value(&do_presolve, PRESOLVE_ROWS | PRESOLVE_COLS); else if(strcmp(argv[i],"-presolvel") == 0) or_value(&do_presolve, PRESOLVE_LINDEP); else if(strcmp(argv[i],"-presolves") == 0) or_value(&do_presolve, PRESOLVE_SOS); else if(strcmp(argv[i],"-presolver") == 0) or_value(&do_presolve, PRESOLVE_REDUCEMIP); else if(strcmp(argv[i],"-presolvek") == 0) or_value(&do_presolve, PRESOLVE_KNAPSACK); else if(strcmp(argv[i],"-presolveq") == 0) or_value(&do_presolve, PRESOLVE_ELIMEQ2); else if(strcmp(argv[i],"-presolvem") == 0) or_value(&do_presolve, PRESOLVE_MERGEROWS); else if(strcmp(argv[i],"-presolvefd") == 0) or_value(&do_presolve, PRESOLVE_COLFIXDUAL); else if(strcmp(argv[i],"-presolvebnd") == 0) or_value(&do_presolve, PRESOLVE_BOUNDS); else if(strcmp(argv[i],"-presolved") == 0) or_value(&do_presolve, PRESOLVE_DUALS); else if(strcmp(argv[i],"-presolvef") == 0) or_value(&do_presolve, PRESOLVE_IMPLIEDFREE); else if(strcmp(argv[i],"-presolveslk") == 0) or_value(&do_presolve, PRESOLVE_IMPLIEDSLK); else if(strcmp(argv[i],"-presolveg") == 0) or_value(&do_presolve, PRESOLVE_REDUCEGCD); else if(strcmp(argv[i],"-presolveb") == 0) or_value(&do_presolve, PRESOLVE_PROBEFIX); else if(strcmp(argv[i],"-presolvec") == 0) or_value(&do_presolve, PRESOLVE_PROBEREDUCE); else if(strcmp(argv[i],"-presolverowd") == 0) or_value(&do_presolve, PRESOLVE_ROWDOMINATE); else if(strcmp(argv[i],"-presolvecold") == 0) or_value(&do_presolve, PRESOLVE_COLDOMINATE); else if(strcmp(argv[i],"-min") == 0) objective = -1; else if(strcmp(argv[i],"-max") == 0) objective = 1; else if(strcmp(argv[i],"-noint") == 0) noint = TRUE; else if((strcmp(argv[i],"-rpar") == 0) && (i + 1 < argc)) i++; else if((strcmp(argv[i],"-rparopt") == 0) && (i + 1 < argc)) i++; else if((strcmp(argv[i],"-wpar") == 0) && (i + 1 < argc)) i++; else if((strcmp(argv[i],"-wparopt") == 0) && (i + 1 < argc)) i++; else if(strcmp(argv[i],"-o0") == 0) obj_in_basis = FALSE; else if(strcmp(argv[i],"-o1") == 0) obj_in_basis = TRUE; else if(fpin == stdin) { filen = argv[i]; if(*filen == '<') filen++; if((fpin = fopen(filen, "r")) == NULL) { print_help(argv); fprintf(stderr,"\nError, Unable to open input file '%s'\n", argv[i]); EndOfPgr(FORCED_EXIT); } } else { filen = argv[i]; if(*filen != '>') { print_help(argv); fprintf(stderr, "\nError, Unrecognized command line argument '%s'\n", argv[i]); EndOfPgr(FORCED_EXIT); } } } signal(SIGABRT,/* (void (*) OF((int))) */ SIGABRT_func); if ((filetype != filetypeXLI) && (fpin == NULL)) { lp = NULL; fprintf(stderr, "Cannot combine -rxli option with -lp, -mps, -fmps.\n"); } else { switch(filetype) { #if defined PARSER_LP case filetypeLP: lp = read_lp(fpin, verbose, NULL); break; #endif case filetypeMPS: lp = read_mps(fpin, verbose | (mps_free ? MPS_FREE : 0) | (mps_ibm ? MPS_IBM : 0) | (mps_negobjconst ? MPS_NEGOBJCONST : 0)); break; case filetypeFREEMPS: lp = read_freemps(fpin, verbose | (mps_ibm ? MPS_IBM : 0) | (mps_negobjconst ? MPS_NEGOBJCONST : 0)); break; case filetypeXLI: lp = read_XLI(rxliname, rxli, rxlidata, rxlioptions, verbose); break; } } if((fpin != NULL) && (fpin != stdin)) fclose(fpin); if(print_timing) print_cpu_times("Parsing input"); if(lp == NULL) { fprintf(stderr, "Unable to read model.\n"); EndOfPgr(FORCED_EXIT); } for(i = 1; i < argc; i++) { if((strcmp(argv[i],"-rpar") == 0) && (i + 1 < argc)) { if(rparname != NULL) { if(!read_params(lp, rparname, rparoptions)) { fprintf(stderr, "Unable to read parameter file (%s)\n", rparname); delete_lp(lp); EndOfPgr(FORCED_EXIT); } } rparname = argv[++i]; } else if((strcmp(argv[i],"-rparopt") == 0) && (i + 1 < argc)) rparoptions = argv[++i]; else if((strcmp(argv[i],"-wpar") == 0) && (i + 1 < argc)) wparname = argv[++i]; else if((strcmp(argv[i],"-wparopt") == 0) && (i + 1 < argc)) wparoptions = argv[++i]; } if(rparname != NULL) if(!read_params(lp, rparname, rparoptions)) { fprintf(stderr, "Unable to read parameter file (%s)\n", rparname); delete_lp(lp); EndOfPgr(FORCED_EXIT); } if((nonames) || (nocolnames)) set_use_names(lp, FALSE, FALSE); if((nonames) || (norownames)) set_use_names(lp, TRUE, FALSE); if(objective != 0) { if(objective == 1) set_maxim(lp); else set_minim(lp); } if (obj_in_basis != -1) set_obj_in_basis(lp, obj_in_basis); if(noint) { /* remove integer conditions */ for(i = get_Ncolumns(lp); i >= 1; i--) { if(is_SOS_var(lp, i)) { fprintf(stderr, "Unable to remove integer conditions because there is at least one SOS constraint\n"); delete_lp(lp); EndOfPgr(FORCED_EXIT); } set_semicont(lp, i, FALSE); set_int(lp, i, FALSE); } } if(!write_model_after) write_model(lp, plp, wlp, wmps, wfmps, wxli, NULL, wxliname, wxlioptions); if(print_stats) print_statistics(lp); if(parse_only) { if(!write_model_after) { delete_lp(lp); EndOfPgr(0); } /* else if(!sectimeout) */ sectimeout = 1; } if(PRINT_SOLUTION >= 5) print_lp(lp); #if 0 put_abortfunc(lp,(abortfunc *) myabortfunc, NULL); #endif if(sectimeout > 0) set_timeout(lp, sectimeout); if(print_sol >= 0) set_print_sol(lp, print_sol); if(epsint >= 0) set_epsint(lp, epsint); if(epspivot >= 0) set_epspivot(lp, epspivot); if(epsperturb >= 0) set_epsperturb(lp, epsperturb); if(epsd >= 0) set_epsd(lp, epsd); if(epsb >= 0) set_epsb(lp, epsb); if(epsel >= 0) set_epsel(lp, epsel); if(debug >= 0) set_debug(lp, (MYBOOL) debug); if(floor_first != -1) set_bb_floorfirst(lp, floor_first); if(do_set_bb_depthlimit) set_bb_depthlimit(lp, bb_depthlimit); if(do_set_solutionlimit) set_solutionlimit(lp, solutionlimit); if(tracing) set_trace(lp, tracing); if(do_set_obj_bound) set_obj_bound(lp, obj_bound); if(do_set_break_at_value) set_break_at_value(lp, break_at_value); if(break_at_first) set_break_at_first(lp, break_at_first); if(mip_absgap >= 0) set_mip_gap(lp, TRUE, mip_absgap); if(mip_relgap >= 0) set_mip_gap(lp, FALSE, mip_relgap); if((anti_degen1 != -1) || (anti_degen2 != -1)) { if((anti_degen1 == -1) || (anti_degen2 != -1)) anti_degen1 = 0; if(anti_degen2 == -1) anti_degen2 = 0; set_anti_degen(lp, anti_degen1 | anti_degen2); } set_presolve(lp, ((do_presolve == -1) ? get_presolve(lp): do_presolve) | ((PRINT_SOLUTION >= 4) ? PRESOLVE_SENSDUALS : 0), get_presolveloops(lp)); if(improve != -1) set_improve(lp, improve); if(max_num_inv >= 0) set_maxpivot(lp, max_num_inv); if(preferdual != AUTOMATIC) set_preferdual(lp, preferdual); if((pivoting1 != -1) || (pivoting2 != -1)) { if(pivoting1 == -1) pivoting1 = get_pivoting(lp) & PRICER_LASTOPTION; if(pivoting2 == -1) pivoting2 = 0; set_pivoting(lp, pivoting1 | pivoting2); } if((scalemode1 != -1) || (scalemode2 != -1)) { if(scalemode1 == -1) scalemode1 = get_scaling(lp) & SCALE_CURTISREID; if(scalemode2 == -1) scalemode2 = 0; set_scaling(lp, scalemode1 | scalemode2); } if(crashmode != -1) set_basiscrash(lp, crashmode); if((bb_rule1 != -1) || (bb_rule2 != -1)) { if(bb_rule1 == -1) bb_rule1 = get_bb_rule(lp) & NODE_USERSELECT; if(bb_rule2 == -1) bb_rule2 = 0; set_bb_rule(lp, bb_rule1 | bb_rule2); } if(simplextype != -1) set_simplextype(lp, simplextype); if(bfp != NULL) if(!set_BFP(lp, bfp)) { fprintf(stderr, "Unable to set BFP package.\n"); delete_lp(lp); EndOfPgr(FORCED_EXIT); } if(debugdump_before != NULL) print_debugdump(lp, debugdump_before); if(report) put_msgfunc(lp, LPMessageCB, NULL, MSG_LPFEASIBLE | MSG_LPOPTIMAL | MSG_MILPFEASIBLE | MSG_MILPBETTER | MSG_PERFORMANCE); if(scaling) { if(scaleloop <= 0) scaleloop = 5; if(scaleloop - (int) scaleloop < SCALINGTHRESHOLD) scaleloop = (int) scaleloop + SCALINGTHRESHOLD; set_scalelimit(lp, scaleloop); } if(guessbasis != NULL) { REAL *guessvector, a; int *basisvector; int Nrows = get_Nrows(lp); int Ncolumns = get_Ncolumns(lp); int col; char buf[50], *ptr; FILE *fp; if ((fp = fopen(guessbasis, "r")) != NULL) { guessvector = (REAL *) calloc(1+Ncolumns, sizeof(*guessvector)); basisvector = (int *) malloc((1+Nrows+Ncolumns)*sizeof(*basisvector)); if ((guessvector != NULL) && (basisvector != NULL)) { while ((!feof(fp)) && (fgets(buf, sizeof(buf), fp) != NULL)) { ptr = strrchr(buf, ':'); if (ptr == NULL) { printf("Mallformed line: %s\n", buf); } else { a = atof(ptr + 1); while ((ptr > buf) && (isspace(ptr[-1]))) ptr--; *ptr = 0; col = get_nameindex(lp, buf, FALSE); if (col < 1) printf("guess_basis: Unknown variable name %s\n", buf); else guessvector[col] = a; } } if (guess_basis(lp, guessvector, basisvector)) { if (!set_basis(lp, basisvector, TRUE)) printf("Unable to set guessed basis.\n"); } else printf("Unable to guess basis from provided variables.\n"); } else printf("guess_basis: Out of memory.\n"); if (basisvector != NULL) free(basisvector); if (guessvector != NULL) free(guessvector); fclose(fp); } else printf("Unable to open file %s\n", guessbasis); } if(rbasname != NULL) if(!read_basis(lp, rbasname, NULL)) { fprintf(stderr, "Unable to read basis file.\n"); delete_lp(lp); EndOfPgr(FORCED_EXIT); } result = solve(lp); if(wbasname != NULL) if(!write_basis(lp, wbasname)) fprintf(stderr, "Unable to write basis file.\n"); if(write_model_after) write_model(lp, plp, wlp, wmps, wfmps, wxli, NULL, wxliname, wxlioptions); write_model(lp, FALSE, NULL, NULL, NULL, NULL, wxlisol, wxliname, wxlisoloptions); if(PRINT_SOLUTION >= 6) print_scales(lp); if((print_timing) && (!parse_only)) print_cpu_times("solving"); if(debugdump_after != NULL) print_debugdump(lp, debugdump_after); if(wparname != NULL) if(!write_params(lp, wparname, wparoptions)) { fprintf(stderr, "Unable to write parameter file (%s)\n", wparname); delete_lp(lp); EndOfPgr(FORCED_EXIT); } if(parse_only) { delete_lp(lp); EndOfPgr(0); } /* if((timeoutok) && (result == TIMEOUT) && (get_solutioncount(lp) > 0)) result = OPTIMAL; */ switch(result) { case SUBOPTIMAL: case PRESOLVED: case OPTIMAL: case PROCBREAK: case FEASFOUND: if ((result == SUBOPTIMAL) && (PRINT_SOLUTION >= 1)) printf("Suboptimal solution\n"); if (result == PRESOLVED) printf("Presolved solution\n"); if (PRINT_SOLUTION >= 1) print_objective(lp); if (PRINT_SOLUTION >= 2) print_solution(lp, 1); if (PRINT_SOLUTION >= 3) print_constraints(lp, 1); if (PRINT_SOLUTION >= 4) print_duals(lp); if(tracing) fprintf(stderr, "Branch & Bound depth: %d\nNodes processed: %.0f\nSimplex pivots: %.0f\nNumber of equal solutions: %d\n", get_max_level(lp), (REAL) get_total_nodes(lp), (REAL) get_total_iter(lp), get_solutioncount(lp)); break; case NOMEMORY: if (PRINT_SOLUTION >= 1) printf("Out of memory\n"); break; case INFEASIBLE: if (PRINT_SOLUTION >= 1) printf("This problem is infeasible\n"); break; case UNBOUNDED: if (PRINT_SOLUTION >= 1) printf("This problem is unbounded\n"); break; case PROCFAIL: if (PRINT_SOLUTION >= 1) printf("The B&B routine failed\n"); break; case TIMEOUT: if (PRINT_SOLUTION >= 1) printf("Timeout\n"); break; case USERABORT: if (PRINT_SOLUTION >= 1) printf("User aborted\n"); break; default: if (PRINT_SOLUTION >= 1) printf("lp_solve failed\n"); break; } if (PRINT_SOLUTION >= 7) print_tableau(lp); delete_lp(lp); EndOfPgr(result); return(result); } MSVMpack1.2/lp_solve_5.5/lp_solve/cgcc.bat0000775000175000017500000000217711245571700017364 0ustar lauerlauer@echo off REM This batch file compiles the lp_solve driver program with the GNU gcc compiler under Windows set c=gcc REM determine platform (win32/win64) echo main(){printf("SET PLATFORM=win%%d\n", (int) (sizeof(void *)*8));}>platform.c %c% platform.c -o platform.exe del platform.c platform.exe >platform.bat del platform.exe call platform.bat del platform.bat if not exist bin\%PLATFORM%\*.* md bin\%PLATFORM% set src=../lp_MDO.c ../shared/commonlib.c ../colamd/colamd.c ../shared/mmio.c ../shared/myblas.c ../lp_rlp.c ../lp_crash.c ../bfp/bfp_LUSOL/lp_LUSOL.c ../bfp/bfp_LUSOL/LUSOL/lusol.c ../lp_Hash.c ../lp_lib.c ../lp_wlp.c ../lp_matrix.c ../lp_mipbb.c ../lp_MPS.c ../lp_presolve.c ../lp_price.c ../lp_pricePSE.c ../lp_report.c ../lp_scale.c ../lp_simplex.c lp_solve.c ../lp_SOS.c ../lp_utils.c ../yacc_read.c ..\ini.c ..\lp_params.c %c% -DINLINE=static -Wall -I.. -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd -I../shared -O3 -DBFP_CALLMODEL=__stdcall -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine %src% -o bin\%PLATFORM%\lp_solve.exe set PLATFORM= MSVMpack1.2/lp_solve_5.5/lp_solve/cvc6.bat0000775000175000017500000000264411136446016017325 0ustar lauerlauer@echo off REM This batch file compiles the lp_solve driver program with the Microsoft Visual C/C++ compiler under Windows set src=../shared/commonlib.c ../shared/mmio.c ../shared/myblas.c ../ini.c ../lp_rlp.c ../lp_crash.c ../bfp/bfp_LUSOL/lp_LUSOL.c ../bfp/bfp_LUSOL/LUSOL/lusol.c ../lp_Hash.c ../lp_lib.c ../lp_wlp.c ../lp_matrix.c ../lp_mipbb.c ../lp_MPS.c ../lp_params.c ../lp_presolve.c ../lp_price.c ../lp_pricePSE.c ../lp_report.c ../lp_scale.c ../lp_simplex.c lp_solve.c ../lp_SOS.c ../lp_utils.c ../yacc_read.c ../lp_MDO.c ../colamd/colamd.c %1 set c=cl REM determine platform (win32/win64) echo main(){printf("SET PLATFORM=win%%d\n", (int) (sizeof(void *)*8));}>platform.c %c% /nologo platform.c /Feplatform.exe del platform.c platform.exe >platform.bat del platform.exe call platform.bat del platform.bat if "%PLATFORM%" == "win32" goto ok1 echo. echo This batch file is entended for 32 bit compilation with MS Visual C 6 echo For newer versions use cvc8*.bat goto done :ok1 if not exist bin\%PLATFORM%\*.* md bin\%PLATFORM% %c% -I.. -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd -I../shared /O2 /Zp8 /Gd -D"LP_MAXLINELEN=0" -DNoParanoia -DWIN32 -D_CRT_SECURE_NO_DEPRECATE -D_CRT_NONSTDC_NO_DEPRECATE -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine -Febin\%PLATFORM%\lp_solve.exe %src% if exist *.obj del *.obj :done set PLATFORM= MSVMpack1.2/lp_solve_5.5/lp_solve/cbcc32.bat0000775000175000017500000000166511137720110017514 0ustar lauerlauer@echo off REM This batch file compiles the lp_solve driver program with the Borland C++ 5.5 compiler for Windows set src=../shared/commonlib.c ../shared/mmio.c ../shared/myblas.c ../ini.c ../lp_rlp.c ../lp_crash.c ../bfp/bfp_LUSOL/lp_LUSOL.c ../bfp/bfp_LUSOL/LUSOL/lusol.c ../lp_Hash.c ../lp_lib.c ../lp_wlp.c ../lp_matrix.c ../lp_mipbb.c ../lp_MPS.c ../lp_params.c ../lp_presolve.c ../lp_price.c ../lp_pricePSE.c ../lp_report.c ../lp_scale.c ../lp_simplex.c lp_solve.c ../lp_SOS.c ../lp_utils.c ../yacc_read.c ../lp_MDO.c ../colamd/colamd.c set c=bcc32 -w-8004 -w-8057 rem -DLLONG=__int64 set PLATFORM=win32 if not exist bin\%PLATFORM%\*.* md bin\%PLATFORM% %c% -I.. -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd -I../shared -a8 -DWIN32 -DYY_NEVER_INTERACTIVE=1 -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine -ebin\%PLATFORM%\lp_solve.exe %src% if exist *.obj del *.obj set PLATFORM= MSVMpack1.2/lp_solve_5.5/lp_solve/ccc0000664000175000017500000000302411137130707016433 0ustar lauerlauer: src='../lp_MDO.c ../shared/commonlib.c ../colamd/colamd.c ../shared/mmio.c ../shared/myblas.c ../ini.c ../fortify.c ../lp_rlp.c ../lp_crash.c ../bfp/bfp_LUSOL/lp_LUSOL.c ../bfp/bfp_LUSOL/LUSOL/lusol.c ../lp_Hash.c ../lp_lib.c ../lp_wlp.c ../lp_matrix.c ../lp_mipbb.c ../lp_MPS.c ../lp_params.c ../lp_presolve.c ../lp_price.c ../lp_pricePSE.c ../lp_report.c ../lp_scale.c ../lp_simplex.c lp_solve.c ../lp_SOS.c ../lp_utils.c ../yacc_read.c' c=cc #determine platform (32/64 bit) >/tmp/platform.c echo '#include '>>/tmp/platform.c echo '#include '>>/tmp/platform.c echo 'main(){printf("ux%d", (int) (sizeof(void *)*8));}'>>/tmp/platform.c $c /tmp/platform.c -o /tmp/platform PLATFORM=`/tmp/platform` rm /tmp/platform /tmp/platform.c >/dev/null 2>&1 mkdir bin bin/$PLATFORM >/dev/null 2>&1 math=-lm #check if this system has the isnan function >/tmp/isnan.c echo '#include '>>/tmp/isnan.c echo '#include '>>/tmp/isnan.c echo '#include '>>/tmp/isnan.c echo 'main(){isnan(0);}'>>/tmp/isnan.c $c /tmp/isnan.c -o /tmp/isnan $math >/dev/null 2>&1 if [ $? = 0 ] then NOISNAN= else NOISNAN=-DNOISNAN fi rm /tmp/isnan.c /tmp/isnan >/dev/null 2>&1 opts='-O3' def= if [ "$PLATFORM" = "SCO_UNIX" ] then opts='-O0' def='-dy -K PIC -DLLONG=long' dl=-ldl else dl=-ldl fi $c -I.. -I../bfp -I../bfp/bfp_LUSOL -I../bfp/bfp_LUSOL/LUSOL -I../colamd -I../shared $opts $def $NOISNAN -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine $src -o bin/$PLATFORM/lp_solve $math $dl MSVMpack1.2/lp_solve_5.5/yacc_read.c0000664000175000017500000010455211250516333016222 0ustar lauerlauer/* ============================================================================ NAME : yacc_read.c PURPOSE : translation of lp-problem and storage in sparse matrix SHORT : Subroutines for yacc program to store the input in an intermediate data-structure. The yacc and lex programs translate the input. First the problemsize is determined and the date is read into an intermediate structure, then readinput fills the sparse matrix. USAGE : call yyparse(); to start reading the input. call readinput(); to fill the sparse matrix. ============================================================================ Rows : contains the amount of rows + 1. Rows-1 is the amount of constraints (no bounds) Rows also contains the rownr 0 which is the objective function Columns : contains the amount of columns (different variable names found in the constraints) Nonnuls : contains the amount of nonnuls = sum of different entries of all columns in the constraints and in the objectfunction Hash_tab : contains all columnnames on the first level of the structure the row information is kept under each column structure in a linked list (also the objective funtion is in this structure) Bound information is also stored under under the column name First_rside : points to a linked list containing all relational operators and the righthandside values of the constraints the linked list is in reversed order with respect to the rownumbers ============================================================================ */ #include #include #include #include "lpkit.h" #include "yacc_read.h" #ifdef FORTIFY # include "lp_fortify.h" #endif #define tol 1.0e-10 #define coldatastep 100 #define HASHSIZE 10007 /* A prime number! */ struct structSOSvars { char *name; int col; REAL weight; struct structSOSvars *next; }; struct structSOS { char *name; short type; int Nvars; int weight; struct structSOSvars *SOSvars, *LastSOSvars; struct structSOS *next; }; struct SOSrow { int col; REAL value; struct SOSrow *next; }; struct SOSrowdata { short type; char *name; struct SOSrow *SOSrow; }; struct rside /* contains relational operator and rhs value */ { int row; REAL value; REAL range_value; struct rside *next; short relat; short range_relat; char negate; short SOStype; }; struct column { int row; REAL value; struct column *next; struct column *prev; }; struct structcoldata { int must_be_int; int must_be_sec; int must_be_free; REAL upbo; REAL lowbo; struct column *firstcol; struct column *col; }; static void error(parse_parm *pp, int verbose, char *string) { if(pp == NULL) report(NULL, CRITICAL, string); else if(pp->Verbose >= verbose) report(NULL, verbose, "%s on line %d\n", string, pp->lineno); } /* * error handling routine for yyparse() */ void read_error(parse_parm *pp, void *scanner, char *string) { error(pp, CRITICAL, string); } /* called when lex gets a fatal error */ void lex_fatal_error(parse_parm *pp, void *scanner, char *msg) { read_error(pp, scanner, msg); longjmp(pp->jump_buf, 1); } void add_row(parse_parm *pp) { pp->Rows++; pp->rs = NULL; pp->Lin_term_count = 0; } void add_sos_row(parse_parm *pp, short SOStype) { if (pp->rs != NULL) pp->rs->SOStype = SOStype; pp->Rows++; pp->rs = NULL; pp->Lin_term_count = 0; } void check_int_sec_sos_free_decl(parse_parm *pp, int within_int_decl, int within_sec_decl, int sos_decl0, int within_free_decl) { pp->Ignore_int_decl = TRUE; pp->Ignore_sec_decl = TRUE; pp->Ignore_free_decl = TRUE; pp->sos_decl = 0; if(within_int_decl) { pp->Ignore_int_decl = FALSE; pp->int_decl = (char) within_int_decl; if(within_sec_decl) pp->Ignore_sec_decl = FALSE; } else if(within_sec_decl) { pp->Ignore_sec_decl = FALSE; } else if(sos_decl0) { pp->sos_decl = (char) sos_decl0; } else if(within_free_decl) { pp->Ignore_free_decl = FALSE; } } static void add_int_var(parse_parm *pp, char *name, short int_decl) { hashelem *hp; if((hp = findhash(name, pp->Hash_tab)) == NULL) { char buf[256]; sprintf(buf, "Unknown variable %s declared integer, ignored", name); error(pp, NORMAL, buf); } else if(pp->coldata[hp->index].must_be_int) { char buf[256]; sprintf(buf, "Variable %s declared integer more than once, ignored", name); error(pp, NORMAL, buf); } else { pp->coldata[hp->index].must_be_int = TRUE; if(int_decl == 2) { if(pp->coldata[hp->index].lowbo != -DEF_INFINITE * (REAL) 10.0) { char buf[256]; sprintf(buf, "Variable %s: lower bound on variable redefined", name); error(pp, NORMAL, buf); } pp->coldata[hp->index].lowbo = 0; if(pp->coldata[hp->index].upbo < DEF_INFINITE) { char buf[256]; sprintf(buf, "Variable %s: upper bound on variable redefined", name); error(pp, NORMAL, buf); } pp->coldata[hp->index].upbo = 1; } else if(int_decl == 3) { if(pp->coldata[hp->index].upbo == DEF_INFINITE * (REAL) 10.0) pp->coldata[hp->index].upbo = 1.0; } } } static void add_sec_var(parse_parm *pp, char *name) { hashelem *hp; if((hp = findhash(name, pp->Hash_tab)) == NULL) { char buf[256]; sprintf(buf, "Unknown variable %s declared semi-continuous, ignored", name); error(pp, NORMAL, buf); } else if(pp->coldata[hp->index].must_be_sec) { char buf[256]; sprintf(buf, "Variable %s declared semi-continuous more than once, ignored", name); error(pp, NORMAL, buf); } else pp->coldata[hp->index].must_be_sec = TRUE; } int set_sec_threshold(parse_parm *pp, char *name, REAL threshold) { hashelem *hp; if((hp = findhash(name, pp->Hash_tab)) == NULL) { char buf[256]; sprintf(buf, "Unknown variable %s declared semi-continuous, ignored", name); error(pp, NORMAL, buf); return(FALSE); } if ((pp->coldata[hp->index].lowbo > 0.0) && (threshold > 0.0)) { char buf[256]; pp->coldata[hp->index].must_be_sec = FALSE; sprintf(buf, "Variable %s declared semi-continuous, but it has a non-negative lower bound (%f), ignored", name, pp->coldata[hp->index].lowbo); error(pp, NORMAL, buf); } if (threshold > pp->coldata[hp->index].lowbo) pp->coldata[hp->index].lowbo = threshold; return(pp->coldata[hp->index].must_be_sec); } static void add_free_var(parse_parm *pp, char *name) { hashelem *hp; if((hp = findhash(name, pp->Hash_tab)) == NULL) { char buf[256]; sprintf(buf, "Unknown variable %s declared free, ignored", name); error(pp, NORMAL, buf); } else if(pp->coldata[hp->index].must_be_free) { char buf[256]; sprintf(buf, "Variable %s declared free more than once, ignored", name); error(pp, NORMAL, buf); } else pp->coldata[hp->index].must_be_free = TRUE; } static int add_sos_name(parse_parm *pp, char *name) { struct structSOS *SOS; if(CALLOC(SOS, 1, struct structSOS) == NULL) return(FALSE); if(MALLOC(SOS->name, strlen(name) + 1, char) == NULL) { FREE(SOS); return(FALSE); } strcpy(SOS->name, name); SOS->type = 0; if(pp->FirstSOS == NULL) pp->FirstSOS = SOS; else pp->LastSOS->next = SOS; pp->LastSOS = SOS; return(TRUE); } static int add_sos_var(parse_parm *pp, char *name) { struct structSOSvars *SOSvar; if(name != NULL) { if(CALLOC(SOSvar, 1, struct structSOSvars) == NULL) return(FALSE); if(MALLOC(SOSvar->name, strlen(name) + 1, char) == NULL) { FREE(SOSvar); return(FALSE); } strcpy(SOSvar->name, name); if(pp->LastSOS->SOSvars == NULL) pp->LastSOS->SOSvars = SOSvar; else pp->LastSOS->LastSOSvars->next = SOSvar; pp->LastSOS->LastSOSvars = SOSvar; pp->LastSOS->Nvars = pp->LastSOS->Nvars + 1; } pp->LastSOS->LastSOSvars->weight = 0; return(TRUE); } void storevarandweight(parse_parm *pp, char *name) { if(!pp->Ignore_int_decl) { add_int_var(pp, name, pp->int_decl); if(!pp->Ignore_sec_decl) add_sec_var(pp, name); } else if(!pp->Ignore_sec_decl) add_sec_var(pp, name); else if(pp->sos_decl==1) add_sos_name(pp, name); else if(pp->sos_decl==2) add_sos_var(pp, name); else if(!pp->Ignore_free_decl) add_free_var(pp, name); } int set_sos_type(parse_parm *pp, int SOStype) { if(pp->LastSOS != NULL) pp->LastSOS->type = (short) SOStype; return(TRUE); } int set_sos_weight(parse_parm *pp, double weight, int sos_decl) { if(pp->LastSOS != NULL) { if(sos_decl==1) pp->LastSOS->weight = (int) (weight+.1); else pp->LastSOS->LastSOSvars->weight = weight; } return(TRUE); } static int inccoldata(parse_parm *pp) { long Columns = pp->Columns; if(Columns == 0) CALLOC(pp->coldata, coldatastep, struct structcoldata); else if((Columns%coldatastep) == 0) REALLOC(pp->coldata, Columns + coldatastep, struct structcoldata); if(pp->coldata != NULL) { pp->coldata[Columns].upbo = (REAL) DEF_INFINITE * (REAL) 10.0; pp->coldata[Columns].lowbo = (REAL) -DEF_INFINITE * (REAL) 10.0; /* temporary. If still this value then 0 will be taken */ pp->coldata[Columns].col = NULL; pp->coldata[Columns].firstcol = NULL; pp->coldata[Columns].must_be_int = FALSE; pp->coldata[Columns].must_be_sec = FALSE; pp->coldata[Columns].must_be_free = FALSE; } return(pp->coldata != NULL); } /* * initialisation of hashstruct and globals. */ static int init_read(parse_parm *pp, int verbose) { int ok = FALSE; pp->Verbose = verbose; set_obj_dir(pp, TRUE); pp->Rows = 0; pp->Non_zeros = 0; pp->Columns = 0; pp->FirstSOS = pp->LastSOS = NULL; pp->Lin_term_count = 0; if (CALLOC(pp->First_rside, 1, struct rside) != NULL) { pp->rs = pp->First_rside; pp->rs->value = pp->rs->range_value = 0; /* first row (nr 0) is always the objective function */ pp->rs->relat = OF; pp->rs->range_relat = -1; pp->rs->SOStype = 0; pp->Hash_tab = NULL; pp->Hash_constraints = NULL; if (((pp->Hash_tab = create_hash_table(HASHSIZE, 0)) == NULL) || ((pp->Hash_constraints = create_hash_table(HASHSIZE, 0)) == NULL)){ FREE(pp->First_rside); FREE(pp->Hash_tab); FREE(pp->Hash_constraints); } else ok = TRUE; } return(ok); } /* init */ /* * clears the tmp_store variable after all information has been copied */ void null_tmp_store(parse_parm *pp, int init_Lin_term_count) { pp->tmp_store.value = 0; pp->tmp_store.rhs_value = 0; FREE(pp->tmp_store.name); if(init_Lin_term_count) pp->Lin_term_count = 0; } /* * variable : pointer to text array with name of variable * row : the rownumber of the constraint * value : value of matrixelement * A(row, variable). * Sign : (global) determines the sign of value. * store() : stores value in matrix * A(row, variable). If A(row, variable) already contains data, * value is added to the existing value. */ static int store(parse_parm *pp, char *variable, int row, REAL value) { hashelem *h_tab_p; struct column *col_p; if(value == 0) { char buf[256]; sprintf(buf, "(store) Warning, variable %s has an effective coefficient of 0, Ignored", variable); error(pp, NORMAL, buf); /* return(TRUE); */ } if((h_tab_p = findhash(variable, pp->Hash_tab)) == NULL) { if (((h_tab_p = puthash(variable, pp->Columns, NULL, pp->Hash_tab)) == NULL) ) return(FALSE); inccoldata(pp); pp->Columns++; /* counter for calloc of final array */ if(value) { if (CALLOC(col_p, 1, struct column) == NULL) return(FALSE); pp->Non_zeros++; /* for calloc of final arrays */ col_p->row = row; col_p->value = value; pp->coldata[h_tab_p->index].firstcol = pp->coldata[h_tab_p->index].col = col_p; } } else if((pp->coldata[h_tab_p->index].col == NULL) || (pp->coldata[h_tab_p->index].col->row != row)) { if(value) { if (CALLOC(col_p, 1, struct column) == NULL) return(FALSE); pp->Non_zeros++; /* for calloc of final arrays */ if(pp->coldata[h_tab_p->index].col != NULL) pp->coldata[h_tab_p->index].col->prev = col_p; else pp->coldata[h_tab_p->index].firstcol = col_p; col_p->value = value; col_p->row = row; col_p->next = pp->coldata[h_tab_p->index].col; pp->coldata[h_tab_p->index].col = col_p; } } else if(value) { pp->coldata[h_tab_p->index].col->value += value; if(fabs(pp->coldata[h_tab_p->index].col->value) < tol) /* eliminitate rounding errors */ pp->coldata[h_tab_p->index].col->value = 0; } return(TRUE); } /* store */ static int storefirst(parse_parm *pp) { struct rside *rp; if ((pp->rs != NULL) && (pp->rs->row == pp->tmp_store.row)) return(TRUE); /* make space for the rhs information */ if (CALLOC(rp, 1, struct rside) == NULL) return(FALSE); rp->next = pp->First_rside; pp->First_rside = pp->rs = rp; pp->rs->row = /* row */ pp->tmp_store.row; pp->rs->value = pp->tmp_store.rhs_value; pp->rs->relat = pp->tmp_store.relat; pp->rs->range_relat = -1; pp->rs->SOStype = 0; if(pp->tmp_store.name != NULL) { if(pp->tmp_store.value != 0) { if (!store(pp, pp->tmp_store.name, pp->tmp_store.row, pp->tmp_store.value)) return(FALSE); } else { char buf[256]; sprintf(buf, "Warning, variable %s has an effective coefficient of 0, ignored", pp->tmp_store.name); error(pp, NORMAL, buf); } } null_tmp_store(pp, FALSE); return(TRUE); } /* * store relational operator given in yylex[0] in the rightside list. * Also checks if it constraint was a bound and if so stores it in the * boundslist */ int store_re_op(parse_parm *pp, char OP, int HadConstraint, int HadVar, int Had_lineair_sum) { short tmp_relat; switch(OP) { case '=': tmp_relat = EQ; break; case '>': tmp_relat = GE; break; case '<': tmp_relat = LE; break; case 0: if(pp->rs != NULL) tmp_relat = pp->rs->relat; else tmp_relat = pp->tmp_store.relat; break; default: { char buf[256]; sprintf(buf, "Error: unknown relational operator %c", OP); error(pp, CRITICAL, buf); } return(FALSE); break; } if(/* pp->Lin_term_count > 1 */ HadConstraint && HadVar) {/* it is not a bound */ if(pp->Lin_term_count <= 1) if(!storefirst(pp)) return(FALSE); pp->rs->relat = tmp_relat; } else if(/* pp->Lin_term_count == 0 */ HadConstraint && !Had_lineair_sum /* HadVar */ /* && (pp->rs != NULL) */) { /* it is a range */ if(pp->Lin_term_count == 1) if(!storefirst(pp)) return(FALSE); if(pp->rs == NULL) { /* range before row, already reported */ error(pp, CRITICAL, "Error: range for undefined row"); return(FALSE); } if(pp->rs->negate) switch (tmp_relat) { case LE: tmp_relat = GE; break; case GE: tmp_relat = LE; break; } if(pp->rs->range_relat != -1) { error(pp, CRITICAL, "Error: There was already a range for this row"); return(FALSE); } else if(tmp_relat == pp->rs->relat) { error(pp, CRITICAL, "Error: relational operator for range is the same as relation operator for equation"); return(FALSE); } else pp->rs->range_relat = tmp_relat; } else /* could be a bound */ pp->tmp_store.relat = tmp_relat; return(TRUE); } /* store_re_op */ int negate_constraint(parse_parm *pp) { if(pp->rs != NULL) pp->rs->negate = TRUE; return(TRUE); } /* * store RHS value in the rightside structure * if type = true then */ int rhs_store(parse_parm *pp, REAL value, int HadConstraint, int HadVar, int Had_lineair_sum) { if(/* pp->Lin_term_count > 1 */ (HadConstraint && HadVar) || (pp->Rows == 0)){ /* not a bound */ if (pp->Rows == 0) value = -value; /* if(pp->Lin_term_count < 2) */ if(pp->rs == NULL) pp->tmp_store.rhs_value += value; else if(pp->rs == NULL) { error(pp, CRITICAL, "Error: No variable specified"); return(FALSE); } else pp->rs->value += value; } else if(/* pp->Lin_term_count == 0 */ HadConstraint && !HadVar) { /* a range */ if(pp->rs == NULL) /* if range before row, already reported */ pp->tmp_store.rhs_value += value; else if(pp->rs->range_relat < 0) /* was a bad range; ignore */; else { if(pp->rs->negate) value = -value; if(((pp->rs->relat == LE) && (pp->rs->range_relat == GE) && (pp->rs->value < value)) || ((pp->rs->relat == GE) && (pp->rs->range_relat == LE) && (pp->rs->value > value)) || ((pp->rs->relat == EQ) || (pp->rs->range_relat == EQ))) { pp->rs->range_relat = -2; error(pp, CRITICAL, "Error: range restriction conflicts"); return(FALSE); } else pp->rs->range_value += value; } } else /* a bound */ pp->tmp_store.rhs_value += value; return(TRUE); } /* RHS_store */ /* * store all data in the right place * count the amount of lineair terms in a constraint * only store in data-structure if the constraint is not a bound */ int var_store(parse_parm *pp, char *var, REAL value, int HadConstraint, int HadVar, int Had_lineair_sum) { int row; row = pp->Rows; /* also in a bound the same var name can occur more than once. Check for this. Don't increment Lin_term_count */ if(pp->Lin_term_count != 1 || pp->tmp_store.name == NULL || strcmp(pp->tmp_store.name, var) != 0) pp->Lin_term_count++; /* always store objective function with rownr == 0. */ if(row == 0) return(store(pp, var, row, value)); if(pp->Lin_term_count == 1) { /* don't store yet. could be a bound */ if(MALLOC(pp->tmp_store.name, strlen(var) + 1, char) != NULL) strcpy(pp->tmp_store.name, var); pp->tmp_store.row = row; pp->tmp_store.value += value; return(TRUE); } if(pp->Lin_term_count == 2) { /* now you can also store the first variable */ if(!storefirst(pp)) return(FALSE); /* null_tmp_store(pp, FALSE); */ } return(store(pp, var, row, value)); } /* var_store */ /* * store the information in tmp_store because it is a bound */ int store_bounds(parse_parm *pp, int warn) { if(pp->tmp_store.value != 0) { hashelem *h_tab_p; REAL boundvalue; if((h_tab_p = findhash(pp->tmp_store.name, pp->Hash_tab)) == NULL) { /* a new columnname is found, create an entry in the hashlist */ if ((h_tab_p = puthash(pp->tmp_store.name, pp->Columns, NULL, pp->Hash_tab)) == NULL) { error(pp, CRITICAL, "Not enough memory"); return(FALSE); } inccoldata(pp); pp->Columns++; /* counter for calloc of final array */ } if(pp->tmp_store.value < 0) { /* divide by negative number, */ /* relational operator may change */ if(pp->tmp_store.relat == GE) pp->tmp_store.relat = LE; else if(pp->tmp_store.relat == LE) pp->tmp_store.relat = GE; } boundvalue = pp->tmp_store.rhs_value / pp->tmp_store.value; #if FALSE /* Check sanity of bound; all variables should be positive */ if( ((pp->tmp_store.relat == EQ) && (boundvalue < 0)) || ((pp->tmp_store.relat == LE) && (boundvalue < 0))) { /* Error */ error(pp, CRITICAL, "Error: variables must always be non-negative"); return(FALSE); } #endif #if FALSE if((pp->tmp_store.relat == GE) && (boundvalue <= 0)) /* Warning */ error(pp, NORMAL, "Warning: useless bound; variables are always >= 0"); #endif /* bound seems to be sane, add it */ if((pp->tmp_store.relat == GE) || (pp->tmp_store.relat == EQ)) { if(boundvalue > pp->coldata[h_tab_p->index].lowbo - tol) pp->coldata[h_tab_p->index].lowbo = boundvalue; else if(warn) error(pp, NORMAL, "Ineffective lower bound, ignored"); } if((pp->tmp_store.relat == LE) || (pp->tmp_store.relat == EQ)) { if(boundvalue < pp->coldata[h_tab_p->index].upbo + tol) pp->coldata[h_tab_p->index].upbo = boundvalue; else if (warn) error(pp, NORMAL, "Ineffective upper bound, ignored"); } /* check for empty range */ if((warn) && (pp->coldata[h_tab_p->index].upbo + tol < pp->coldata[h_tab_p->index].lowbo)) { error(pp, CRITICAL, "Error: bound contradicts earlier bounds"); return(FALSE); } } else /* pp->tmp_store.value = 0 ! */ { char buf[256]; if((pp->tmp_store.rhs_value == 0) || ((pp->tmp_store.rhs_value > 0) && (pp->tmp_store.relat == LE)) || ((pp->tmp_store.rhs_value < 0) && (pp->tmp_store.relat == GE))) { sprintf(buf, "Variable %s has an effective coefficient of 0 in bound, ignored", pp->tmp_store.name); if(warn) error(pp, NORMAL, buf); } else { sprintf(buf, "Error, variable %s has an effective coefficient of 0 in bound", pp->tmp_store.name); error(pp, CRITICAL, buf); return(FALSE); } } /* null_tmp_store(pp, FALSE); */ pp->tmp_store.rhs_value = 0; return(TRUE); } /* store_bounds */ int set_title(parse_parm *pp, char *name) { pp->title = strdup(name); return(TRUE); } int add_constraint_name(parse_parm *pp, char *name) { int row; hashelem *hp; if((hp = findhash(name, pp->Hash_constraints)) != NULL) { row = hp->index; pp->rs = pp->First_rside; while ((pp->rs != NULL) && (pp->rs->row != row)) pp->rs = pp->rs->next; } else { row = pp->Rows; if (((hp = puthash(name, row, NULL, pp->Hash_constraints)) == NULL) ) return(FALSE); if(row) pp->rs = NULL; } return(TRUE); } /* * transport the data from the intermediate structure to the sparse matrix * and free the intermediate structure */ static int readinput(parse_parm *pp, lprec *lp) { int i, i1, count, index, col; struct column *cp, *tcp; hashelem *hp; struct rside *rp; signed char *negateAndSOS = NULL; REAL *row = NULL, a; int *rowno = NULL; MYBOOL SOSinMatrix = FALSE; struct SOSrowdata *SOSrowdata = NULL; struct SOSrow *SOSrow, *SOSrow1; if(lp != NULL) { if (CALLOC(negateAndSOS, 1 + pp->Rows, signed char) == NULL) return(FALSE); rp = pp->First_rside; for(i = pp->Rows; (i >= 0) && (rp != NULL); i--) { if(rp->SOStype == 0) negateAndSOS[i] = (rp->negate ? -1 : 0); else negateAndSOS[i] = (signed char) rp->SOStype; rp = rp->next; } /* fill names with the rownames */ hp = pp->Hash_constraints->first; while(hp != NULL) { if (/* (negateAndSOS[hp->index] <= 0) && */ (!set_row_name(lp, hp->index, hp->name))) return(FALSE); hp = hp->nextelem; } } for(i = pp->Rows; i >= 0; i--) { rp = pp->First_rside; if((lp != NULL) && (rp != NULL)) { if(rp->SOStype == 0) { if (rp->negate) { switch (rp->relat) { case LE: rp->relat = GE; break; case GE: rp->relat = LE; break; } switch (rp->range_relat) { case LE: rp->range_relat = GE; break; case GE: rp->range_relat = LE; break; } rp->range_value = -rp->range_value; rp->value = -rp->value; } if((rp->range_relat >= 0) && (rp->value == lp->infinite)) { rp->value = rp->range_value; rp->relat = rp->range_relat; rp->range_relat = -1; } else if((rp->range_relat >= 0) && (rp->value == -lp->infinite)) { rp->value = rp->range_value; rp->relat = rp->range_relat; rp->range_relat = -1; } if ((rp->range_relat >= 0) && (rp->range_value == rp->value)) { rp->relat = EQ; rp->range_relat = EQ; } if(i) { set_constr_type(lp, i, rp->relat); pp->relat[i] = rp->relat; } set_rh(lp, i, rp->value); if (rp->range_relat >= 0) set_rh_range(lp, i, rp->range_value - rp->value); } else { SOSinMatrix = TRUE; if(i) pp->relat[i] = rp->relat; } } if(rp != NULL) { pp->First_rside = rp->next; free(rp); /* free memory when data has been read */ } else pp->First_rside = NULL; } while(pp->First_rside != NULL) { rp = pp->First_rside; pp->First_rside = rp->next; free(rp); /* free memory when data has been read */ } /* start reading the Hash_list structure */ index = 0; if((SOSinMatrix) && (CALLOC(SOSrowdata, 1 + pp->Rows, struct SOSrowdata) == NULL)) { FREE(negateAndSOS); FREE(row); FREE(rowno); return(FALSE); } if((lp != NULL) && ((MALLOC(row, 1 + pp->Rows, REAL) == NULL) || (MALLOC(rowno, 1 + pp->Rows, int) == NULL))) { FREE(SOSrowdata); FREE(negateAndSOS); FREE(row); FREE(rowno); return(FALSE); } /* for(i = 0; i < pp->Hash_tab->size; i++) { hp = pp->Hash_tab->table[i]; */ hp = pp->Hash_tab->first; while(hp != NULL) { count = 0; index++; cp = pp->coldata[hp->index].firstcol; col = hp->index + 1; while(cp != NULL) { if(lp != NULL) { if (negateAndSOS[cp->row] <= 0) { rowno[count] = cp->row; a = cp->value; if (negateAndSOS[cp->row]) a = -a; row[count++] = a; } else { if (MALLOC(SOSrow, 1, struct SOSrow) == NULL) { FREE(SOSrowdata); FREE(negateAndSOS); FREE(row); FREE(rowno); return(FALSE); } if(SOSrowdata[cp->row].SOSrow == NULL) SOSrowdata[cp->row].name = strdup(get_row_name(lp, cp->row)); SOSrow->next = SOSrowdata[cp->row].SOSrow; SOSrowdata[cp->row].SOSrow = SOSrow; SOSrowdata[cp->row].type = negateAndSOS[cp->row]; SOSrow->col = col; SOSrow->value = cp->value; } } tcp = cp; /* cp = cp->next; */ cp = cp->prev; free(tcp); /* free memory when data has been read */ } if(lp != NULL) { add_columnex(lp, count, row, rowno); /* check for bound */ if(pp->coldata[hp->index].lowbo == -DEF_INFINITE * 10.0) /* lp->orig_lowbo[pp->Rows+index] = 0.0; */ set_lowbo(lp, index, 0); else /* lp->orig_lowbo[pp->Rows+index] = pp->coldata[hp->index].lowbo; */ set_lowbo(lp, index, pp->coldata[hp->index].lowbo); /* lp->orig_upbo[pp->Rows+index] = pp->coldata[hp->index].upbo; */ if(pp->coldata[hp->index].upbo >= DEF_INFINITE) set_upbo(lp, index, DEF_INFINITE); else set_upbo(lp, index, pp->coldata[hp->index].upbo); /* check if it must be an integer variable */ if(pp->coldata[hp->index].must_be_int) { /* lp->must_be_int[pp->Rows + index]=TRUE; */ set_int(lp, index, TRUE); } if(pp->coldata[hp->index].must_be_sec) { set_semicont(lp, index, TRUE); } if(pp->coldata[hp->index].must_be_free) { set_unbounded(lp, index); } /* copy name of column variable */ if (!set_col_name(lp, index, hp->name)) { FREE(SOSrowdata); FREE(negateAndSOS); FREE(row); FREE(rowno); return(FALSE); } /* put matrix values in intermediate row */ /* cp = hp->col; */ /* cp = hp->firstcol; */ } /* thp = hp; */ /* hp = hp->next; */ /* free(thp->name); */ /* free(thp); */ /* free memory when data has been read */ hp = hp->nextelem; } /* pp->Hash_tab->table[i] = NULL; */ FREE(pp->coldata); if(SOSrowdata != NULL) { struct structSOS *structSOS; struct structSOSvars *SOSvars, *SOSvars1; int SOSweight = 0; for(i = 1; i <= pp->Rows; i++) { SOSrow = SOSrowdata[i].SOSrow; if(SOSrow != NULL) { if(MALLOC(structSOS, 1, struct structSOS) == NULL) { FREE(SOSrowdata); FREE(negateAndSOS); FREE(row); FREE(rowno); return(FALSE); } structSOS->Nvars = 0; structSOS->type = SOSrowdata[i].type; structSOS->weight = ++SOSweight; structSOS->name = strdup(SOSrowdata[i].name); structSOS->LastSOSvars = NULL; structSOS->next = pp->FirstSOS; pp->FirstSOS = structSOS; SOSvars = NULL; while(SOSrow != NULL) { SOSvars1 = SOSvars; MALLOC(SOSvars, 1, struct structSOSvars); SOSvars->next = SOSvars1; SOSvars->col = SOSrow->col; SOSvars->weight = SOSrow->value; SOSvars->name = NULL; structSOS->Nvars++; SOSrow1 = SOSrow->next; FREE(SOSrow); SOSrow = SOSrow1; } structSOS->SOSvars = SOSvars; } } FREE(SOSrowdata); } while(pp->FirstSOS != NULL) { struct structSOSvars *SOSvars, *SOSvars1; int *sosvars, n, col; REAL *weights; hashelem *hp; pp->LastSOS = pp->FirstSOS; pp->FirstSOS = pp->FirstSOS->next; SOSvars = pp->LastSOS->SOSvars; if(lp != NULL) { MALLOC(sosvars, pp->LastSOS->Nvars, int); MALLOC(weights, pp->LastSOS->Nvars, double); } else { sosvars = NULL; weights = NULL; } n = 0; while(SOSvars != NULL) { SOSvars1 = SOSvars; SOSvars = SOSvars->next; if(lp != NULL) { col = SOSvars1->col; if(col == 0) if((hp = findhash(SOSvars1->name, lp->colname_hashtab)) != NULL) col = hp->index; if (col) { sosvars[n] = col; weights[n++] = SOSvars1->weight; } } FREE(SOSvars1->name); FREE(SOSvars1); } if(lp != NULL) { add_SOS(lp, pp->LastSOS->name, pp->LastSOS->type, pp->LastSOS->weight, n, sosvars, weights); FREE(weights); FREE(sosvars); } FREE(pp->LastSOS->name); FREE(pp->LastSOS); } if(negateAndSOS != NULL) { for(i1 = 0, i = 1; i <= pp->Rows; i++) if(negateAndSOS[i] <= 0) pp->relat[++i1] = pp->relat[i]; #if 01 for(i = pp->Rows; i > 0; i--) if(negateAndSOS[i] > 0) { del_constraint(lp, i); pp->Rows--; } #endif } /* the following should be replaced by a call to the MPS print routine MB */ #if 0 if(pp->Verbose) { int j; printf("\n"); printf("**********Data read**********\n"); printf("Rows : %d\n", pp->Rows); printf("Columns : %d\n", pp->Columns); printf("Nonnuls : %d\n", pp->Non_zeros); printf("NAME LPPROB\n"); printf("ROWS\n"); for(i = 0; i <= pp->Rows; i++) { if(pp->relat[i] == LE) printf(" L "); else if(pp->relat[i] == EQ) printf(" E "); else if(pp->relat[i] == GE) printf(" G "); else if(pp->relat[i] == OF) printf(" N "); printf("%s\n", get_row_name(lp, i)); } printf("COLUMNS\n"); j = 0; for(i = 0; i < pp->Non_zeros; i++) { if(i == lp->col_end[j]) j++; printf(" %-8s %-8s %g\n", get_col_name(lp, j), get_row_name(lp, lp->mat[i].row_nr), (double)lp->mat[i].value); } printf("RHS\n"); for(i = 0; i <= pp->Rows; i++) { printf(" RHS %-8s %g\n", get_row_name(lp, i), (double)lp->orig_rhs[i]); } printf("RANGES\n"); for(i = 1; i <= pp->Rows; i++) if((lp->orig_upbo[i] != lp->infinite) && (lp->orig_upbo[i] != 0)) { printf(" RGS %-8s %g\n", get_row_name(lp, i), (double)lp->orig_upbo[i]); } else if((lp->orig_lowbo[i] != 0)) { printf(" RGS %-8s %g\n", get_row_name(lp, i), (double)-lp->orig_lowbo[i]); } printf("BOUNDS\n"); for(i = pp->Rows + 1; i <= pp->Rows + pp->Columns; i++) { if((lp->orig_lowbo[i] != 0) && (lp->orig_upbo[i] < lp->infinite) && (lp->orig_lowbo[i] == lp->orig_upbo[i])) { printf(" FX BND %-8s %g\n", get_col_name(lp, i - pp->Rows), (double)lp->orig_upbo[i]); } else { if(lp->orig_upbo[i] < lp->infinite) printf(" UP BND %-8s %g\n", get_col_name(lp, i - pp->Rows), (double)lp->orig_upbo[i]); if(lp->orig_lowbo[i] > 0) printf(" LO BND %-8s %g\n", get_col_name(lp, i - pp->Rows), (double)lp->orig_lowbo[i]); } } printf("ENDATA\n"); } #endif FREE(row); FREE(rowno); FREE(negateAndSOS); return(TRUE); } /* readinput */ lprec *yacc_read(lprec *lp, int verbose, char *lp_name, int (*parse) (parse_parm *pp), parse_parm *pp, void (*delete_allocated_memory) (parse_parm *pp)) { REAL *orig_upbo; int stat = -1; lprec *lp0 = lp; pp->title = lp_name; if(!init_read(pp, verbose)) error(pp, CRITICAL, "init_read failed"); else if (setjmp(pp->jump_buf) == 0) stat = parse(pp); delete_allocated_memory(pp); pp->Rows--; pp->relat = NULL; if((stat != 0) || (CALLOC(pp->relat, pp->Rows + 1, short) != NULL)) { if(stat == 0) { if(lp == NULL) { lp = make_lp(pp->Rows, 0); } else { int NRows; for(NRows = get_Nrows(lp); NRows < pp->Rows; NRows++) add_constraintex(lp, 0, NULL, NULL, LE, 0); } } else lp = NULL; if ((stat != 0) || (lp != NULL)) { if(lp != NULL) { set_verbose(lp, pp->Verbose); } if (!readinput(pp, lp)) { if((lp != NULL) && (lp0 == NULL)) delete_lp(lp); lp = NULL; } if(lp != NULL) { set_lp_name(lp, pp->title); if(pp->Maximise) set_maxim(lp); if(pp->Rows) { int row; MALLOCCPY(orig_upbo, lp->orig_upbo, 1 + pp->Rows, REAL); for(row = 1; row <= pp->Rows; row++) set_constr_type(lp, row, pp->relat[row]); memcpy(lp->orig_upbo, orig_upbo, (1 + pp->Rows) * sizeof(*orig_upbo)); /* restore upper bounds (range) */ FREE(orig_upbo); } } if((pp->title != NULL) && (pp->title != lp_name)) free(pp->title); free_hash_table(pp->Hash_tab); free_hash_table(pp->Hash_constraints); } FREE(pp->relat); } null_tmp_store(pp, FALSE); return(lp); } MSVMpack1.2/lp_solve_5.5/lp_SOS.h0000664000175000017500000001102311141374255015446 0ustar lauerlauer#ifndef HEADER_lp_SOS #define HEADER_lp_SOS /* Specially Ordered Sets (SOS) prototypes and settings */ /* ------------------------------------------------------------------------- */ #include "lp_types.h" #include "lp_utils.h" #include "lp_matrix.h" /* SOS constraint defines */ /* ------------------------------------------------------------------------- */ #define SOS1 1 #define SOS2 2 #define SOS3 -1 #define SOSn MAXINT32 #define SOS_START_SIZE 10 /* Start size of SOS_list array; realloced if needed */ /* Define SOS_is_feasible() return values */ /* ------------------------------------------------------------------------- */ #define SOS3_INCOMPLETE -2 #define SOS_INCOMPLETE -1 #define SOS_COMPLETE 0 #define SOS_INFEASIBLE 1 #define SOS_INTERNALERROR 2 typedef struct _SOSgroup SOSgroup; typedef struct _SOSrec { SOSgroup *parent; int tagorder; char *name; int type; MYBOOL isGUB; int size; int priority; int *members; REAL *weights; int *membersSorted; int *membersMapped; } SOSrec; /* typedef */ struct _SOSgroup { lprec *lp; /* Pointer to owner */ SOSrec **sos_list; /* Array of pointers to SOS lists */ int sos_alloc; /* Size allocated to specially ordered sets (SOS1, SOS2...) */ int sos_count; /* Number of specially ordered sets (SOS1, SOS2...) */ int maxorder; /* The highest-order SOS in the group */ int sos1_count; /* Number of the lowest order SOS in the group */ int *membership; /* Array of variable-sorted indeces to SOSes that the variable is member of */ int *memberpos; /* Starting positions of the each column's membership list */ } /* SOSgroup */; #ifdef __cplusplus extern "C" { #endif /* SOS storage structure */ STATIC SOSgroup *create_SOSgroup(lprec *lp); STATIC void resize_SOSgroup(SOSgroup *group); STATIC int append_SOSgroup(SOSgroup *group, SOSrec *SOS); STATIC int clean_SOSgroup(SOSgroup *group, MYBOOL forceupdatemap); STATIC void free_SOSgroup(SOSgroup **group); STATIC SOSrec *create_SOSrec(SOSgroup *group, char *name, int type, int priority, int size, int *variables, REAL *weights); STATIC MYBOOL delete_SOSrec(SOSgroup *group, int sosindex); STATIC int append_SOSrec(SOSrec *SOS, int size, int *variables, REAL *weights); STATIC void free_SOSrec(SOSrec *SOS); /* SOS utilities */ STATIC int make_SOSchain(lprec *lp, MYBOOL forceresort); STATIC int SOS_member_updatemap(SOSgroup *group); STATIC MYBOOL SOS_member_sortlist(SOSgroup *group, int sosindex); STATIC MYBOOL SOS_shift_col(SOSgroup *group, int sosindex, int column, int delta, LLrec *usedmap, MYBOOL forceresort); int SOS_member_delete(SOSgroup *group, int sosindex, int member); int SOS_get_type(SOSgroup *group, int sosindex); int SOS_infeasible(SOSgroup *group, int sosindex); int SOS_member_index(SOSgroup *group, int sosindex, int member); int SOS_member_count(SOSgroup *group, int sosindex); int SOS_memberships(SOSgroup *group, int column); int *SOS_get_candidates(SOSgroup *group, int sosindex, int column, MYBOOL excludetarget, REAL *upbound, REAL *lobound); int SOS_is_member(SOSgroup *group, int sosindex, int column); MYBOOL SOS_is_member_of_type(SOSgroup *group, int column, int sostype); MYBOOL SOS_set_GUB(SOSgroup *group, int sosindex, MYBOOL state); MYBOOL SOS_is_GUB(SOSgroup *group, int sosindex); MYBOOL SOS_is_marked(SOSgroup *group, int sosindex, int column); MYBOOL SOS_is_active(SOSgroup *group, int sosindex, int column); MYBOOL SOS_is_full(SOSgroup *group, int sosindex, int column, MYBOOL activeonly); MYBOOL SOS_can_activate(SOSgroup *group, int sosindex, int column); MYBOOL SOS_set_marked(SOSgroup *group, int sosindex, int column, MYBOOL asactive); MYBOOL SOS_unmark(SOSgroup *group, int sosindex, int column); int SOS_fix_unmarked(SOSgroup *group, int sosindex, int variable, REAL *bound, REAL value, MYBOOL isupper, int *diffcount, DeltaVrec *changelog); int SOS_fix_list(SOSgroup *group, int sosindex, int variable, REAL *bound, int *varlist, MYBOOL isleft, DeltaVrec *changelog); int SOS_is_satisfied(SOSgroup *group, int sosindex, REAL *solution); MYBOOL SOS_is_feasible(SOSgroup *group, int sosindex, REAL *solution); #ifdef __cplusplus } #endif #endif /* HEADER_lp_SOS */ MSVMpack1.2/lp_solve_5.5/lp_crash.h0000664000175000017500000000063011141374243016101 0ustar lauerlauer #ifndef HEADER_lp_crash #define HEADER_lp_crash #include "lp_types.h" #define CRASH_SIMPLESCALE /* Specify if we should use a simple absolute scaling threshold */ #define CRASH_THRESHOLD 0.167 #define CRASH_SPACER 10 #define CRASH_WEIGHT 0.500 #ifdef __cplusplus __EXTERN_C { #endif STATIC MYBOOL crash_basis(lprec *lp); #ifdef __cplusplus } #endif #endif /* HEADER_lp_crash */ MSVMpack1.2/lp_solve_5.5/lp_MDO.c0000664000175000017500000001551211141374245015422 0ustar lauerlauer/* Minimum matrix inverse fill-in modules - interface for lp_solve v5.0+ ---------------------------------------------------------------------------------- Author: Kjell Eikland Contact: kjell.eikland@broadpark.no License terms: LGPL. Requires: string.h, colamd.h, lp_lib.h Release notes: v1.0 1 September 2003 Preprocessing routines for minimum fill-in column ordering for inverse factorization using the open source COLAMD library. Suitable for the dense parts of both the product form and LU factorization inverse methods. v1.1 1 July 2004 Renamed from lp_colamdMDO to lp_MDO. ---------------------------------------------------------------------------------- */ #include #include "commonlib.h" #include "lp_lib.h" #include "colamd.h" #include "lp_MDO.h" #ifdef FORTIFY # include "lp_fortify.h" #endif STATIC MYBOOL includeMDO(MYBOOL *usedpos, int item) { /* Legend: TRUE => A basic slack variable already in the basis FALSE => A column free for being pivoted in AUTOMATIC+TRUE => A row-singleton user column pivoted into the basis AUTOMATIC+FALSE => A column-singleton user column pivoted into the basis */ /* Handle case where we are processing all columns */ if(usedpos == NULL) return( TRUE ); else { /* Otherwise do the selective case */ MYBOOL test = usedpos[item]; #if 1 return( test != TRUE ); #else test = test & TRUE; return( test == FALSE ); #endif } } STATIC int prepareMDO(lprec *lp, MYBOOL *usedpos, int *colorder, int *data, int *rowmap) /* This routine prepares data structures for colamd(). It is called twice, the first time to count applicable non-zero elements by column, and the second time to fill in the row indexes of the non-zero values from the first call. Note that the colamd() row index base is 0 (which suits lp_solve fine). */ { int i, ii, j, k, kk; int nrows = lp->rows+1, ncols = colorder[0]; int offset = 0, Bnz = 0, Tnz; MYBOOL dotally = (MYBOOL) (rowmap == NULL); MATrec *mat = lp->matA; REAL hold; REAL *value; int *rownr; if(dotally) data[0] = 0; Tnz = nrows - ncols; for(j = 1; j <= ncols; j++) { kk = colorder[j]; /* Process slacks */ if(kk <= lp->rows) { if(includeMDO(usedpos, kk)) { if(!dotally) data[Bnz] = rowmap[kk]+offset; Bnz++; } Tnz++; } /* Process user columns */ else { k = kk - lp->rows; i = mat->col_end[k-1]; ii= mat->col_end[k]; Tnz += ii-i; #ifdef Paranoia if(i >= ii) lp->report(lp, SEVERE, "prepareMDO: Encountered empty basic column %d\n", k); #endif /* Detect if we need to do phase 1 adjustments of zero-valued OF variable */ rownr = &COL_MAT_ROWNR(i); value = &COL_MAT_VALUE(i); hold = 0; if((*rownr > 0) && includeMDO(usedpos, 0) && modifyOF1(lp, kk, &hold, 1.0)) { if(!dotally) data[Bnz] = offset; Bnz++; } /* Loop over all NZ-variables */ for(; i < ii; i++, value += matValueStep, rownr += matRowColStep) { if(!includeMDO(usedpos, *rownr)) continue; /* See if we need to change phase 1 OF value */ if(*rownr == 0) { hold = *value; if(!modifyOF1(lp, kk, &hold, 1.0)) continue; } /* Tally uneliminated constraint row values */ if(!dotally) data[Bnz] = rowmap[*rownr]+offset; Bnz++; } } if(dotally) data[j] = Bnz; } return( Tnz ); } STATIC MYBOOL verifyMDO(lprec *lp, int *col_end, int *row_nr, int rowmax, int colmax) { int i, j, n, err = 0; for(i = 1; i <= colmax; i++) { n = 0; for(j = col_end[i-1]; (j < col_end[i]) && (err == 0); j++, n++) { if(row_nr[j] < 0 || row_nr[j] > rowmax) err = 1; if(n > 0 && row_nr[j] <= row_nr[j-1]) err = 2; n++; } } if(err != 0) lp->report(lp, SEVERE, "verifyMDO: Invalid MDO input structure generated (error %d)\n", err); return( (MYBOOL) (err == 0) ); } void *mdo_calloc(size_t size, size_t count) { return ( calloc(size, count) ); } void mdo_free(void *mem) { free( mem ); } int __WINAPI getMDO(lprec *lp, MYBOOL *usedpos, int *colorder, int *size, MYBOOL symmetric) { int error = FALSE; int nrows = lp->rows+1, ncols = colorder[0]; int i, j, kk, n; int *col_end, *row_map = NULL; int Bnz, Blen, *Brows = NULL; int stats[COLAMD_STATS]; double knobs[COLAMD_KNOBS]; /* Tally the non-zero counts of the unused columns/rows of the basis matrix and store corresponding "net" starting positions */ allocINT(lp, &col_end, ncols+1, FALSE); n = prepareMDO(lp, usedpos, colorder, col_end, NULL); Bnz = col_end[ncols]; /* Check that we have unused basic columns, otherwise skip analysis */ if(ncols == 0 || Bnz == 0) goto Transfer; /* Get net number of rows and fill mapper */ allocINT(lp, &row_map, nrows, FALSE); nrows = 0; for(i = 0; i <= lp->rows; i++) { row_map[i] = i-nrows; /* Increment eliminated row counter if necessary */ if(!includeMDO(usedpos, i)) nrows++; } nrows = lp->rows+1 - nrows; /* Store row indeces of non-zero values in the basic columns */ Blen = colamd_recommended(Bnz, nrows, ncols); allocINT(lp, &Brows, Blen, FALSE); prepareMDO(lp, usedpos, colorder, Brows, row_map); #ifdef Paranoia verifyMDO(lp, col_end, Brows, nrows, ncols); #endif /* Compute the MDO */ #if 1 colamd_set_defaults(knobs); knobs [COLAMD_DENSE_ROW] = 0.2+0.2 ; /* default changed for UMFPACK */ knobs [COLAMD_DENSE_COL] = knobs [COLAMD_DENSE_ROW]; if(symmetric && (nrows == ncols)) { MEMCOPY(colorder, Brows, ncols + 1); error = !symamd(nrows, colorder, col_end, Brows, knobs, stats, mdo_calloc, mdo_free); } else error = !colamd(nrows, ncols, Blen, Brows, col_end, knobs, stats); #else if(symmetric && (nrows == ncols)) { MEMCOPY(colorder, Brows, ncols + 1); error = !symamd(nrows, colorder, col_end, Brows, knobs, stats, mdo_calloc, mdo_free); } else error = !colamd(nrows, ncols, Blen, Brows, col_end, (double *) NULL, stats); #endif /* Transfer the estimated optimal ordering, adjusting for index offsets */ Transfer: if(error) error = stats[COLAMD_STATUS]; else { MEMCOPY(Brows, colorder, ncols + 1); for(j = 0; j < ncols; j++) { kk = col_end[j]; n = Brows[kk+1]; colorder[j+1] = n; } } /* Free temporary vectors */ FREE(col_end); if(row_map != NULL) FREE(row_map); if(Brows != NULL) FREE(Brows); if(size != NULL) *size = ncols; return( error ); } MSVMpack1.2/lp_solve_5.5/lp_matrix.h0000664000175000017500000002764611141374245016327 0ustar lauerlauer#ifndef HEADER_lp_matrix #define HEADER_lp_matrix #include "lp_types.h" #include "lp_utils.h" /* Sparse matrix element (ordered columnwise) */ typedef struct _MATitem { int rownr; int colnr; REAL value; } MATitem; /* Constants for matrix product rounding options */ #define MAT_ROUNDNONE 0 #define MAT_ROUNDABS 1 #define MAT_ROUNDREL 2 #define MAT_ROUNDABSREL (MAT_ROUNDABS + MAT_ROUNDREL) #define MAT_ROUNDRC 4 #define MAT_ROUNDRCMIN 1.0 /* lp->epspivot */ #if 1 #define MAT_ROUNDDEFAULT MAT_ROUNDREL /* Typically increases performance */ #else #define MAT_ROUNDDEFAULT MAT_ROUNDABS /* Probably gives more precision */ #endif /* Compiler option development features */ /*#define DebugInv*/ /* Report array values at factorization/inversion */ #define NoLoopUnroll /* Do not do loop unrolling */ #define DirectArrayOF /* Reference lp->obj[] array instead of function call */ /* Matrix column access macros to be able to easily change storage model */ #define CAM_Record 0 #define CAM_Vector 1 #if 0 #define MatrixColAccess CAM_Record #else #define MatrixColAccess CAM_Vector #endif #if MatrixColAccess==CAM_Record #define SET_MAT_ijA(item,i,j,A) mat->col_mat[item].rownr = i; \ mat->col_mat[item].colnr = j; \ mat->col_mat[item].value = A #define COL_MAT_COLNR(item) (mat->col_mat[item].colnr) #define COL_MAT_ROWNR(item) (mat->col_mat[item].rownr) #define COL_MAT_VALUE(item) (mat->col_mat[item].value) #define COL_MAT_COPY(left,right) mat->col_mat[left] = mat->col_mat[right] #define COL_MAT_MOVE(to,from,rec) MEMMOVE(&(mat->col_mat[to]),&(mat->col_mat[from]),rec) #define COL_MAT2_COLNR(item) (mat2->col_mat[item].colnr) #define COL_MAT2_ROWNR(item) (mat2->col_mat[item].rownr) #define COL_MAT2_VALUE(item) (mat2->col_mat[item].value) #define matRowColStep (sizeof(MATitem)/sizeof(int)) #define matValueStep (sizeof(MATitem)/sizeof(REAL)) #else /* if MatrixColAccess==CAM_Vector */ #define SET_MAT_ijA(item,i,j,A) mat->col_mat_rownr[item] = i; \ mat->col_mat_colnr[item] = j; \ mat->col_mat_value[item] = A #define COL_MAT_COLNR(item) (mat->col_mat_colnr[item]) #define COL_MAT_ROWNR(item) (mat->col_mat_rownr[item]) #define COL_MAT_VALUE(item) (mat->col_mat_value[item]) #define COL_MAT_COPY(left,right) COL_MAT_COLNR(left) = COL_MAT_COLNR(right); \ COL_MAT_ROWNR(left) = COL_MAT_ROWNR(right); \ COL_MAT_VALUE(left) = COL_MAT_VALUE(right) #define COL_MAT_MOVE(to,from,rec) MEMMOVE(&COL_MAT_COLNR(to),&COL_MAT_COLNR(from),rec); \ MEMMOVE(&COL_MAT_ROWNR(to),&COL_MAT_ROWNR(from),rec); \ MEMMOVE(&COL_MAT_VALUE(to),&COL_MAT_VALUE(from),rec) #define COL_MAT2_COLNR(item) (mat2->col_mat_colnr[item]) #define COL_MAT2_ROWNR(item) (mat2->col_mat_rownr[item]) #define COL_MAT2_VALUE(item) (mat2->col_mat_value[item]) #define matRowColStep 1 #define matValueStep 1 #endif /* Matrix row access macros to be able to easily change storage model */ #define RAM_Index 0 #define RAM_FullCopy 1 #define MatrixRowAccess RAM_Index #if MatrixRowAccess==RAM_Index #define ROW_MAT_COLNR(item) COL_MAT_COLNR(mat->row_mat[item]) #define ROW_MAT_ROWNR(item) COL_MAT_ROWNR(mat->row_mat[item]) #define ROW_MAT_VALUE(item) COL_MAT_VALUE(mat->row_mat[item]) #elif MatrixColAccess==CAM_Record #define ROW_MAT_COLNR(item) (mat->row_mat[item].colnr) #define ROW_MAT_ROWNR(item) (mat->row_mat[item].rownr) #define ROW_MAT_VALUE(item) (mat->row_mat[item].value) #else /* if MatrixColAccess==CAM_Vector */ #define ROW_MAT_COLNR(item) (mat->row_mat_colnr[item]) #define ROW_MAT_ROWNR(item) (mat->row_mat_rownr[item]) #define ROW_MAT_VALUE(item) (mat->row_mat_value[item]) #endif typedef struct _MATrec { /* Owner reference */ lprec *lp; /* Active dimensions */ int rows; int columns; /* Allocated memory */ int rows_alloc; int columns_alloc; int mat_alloc; /* The allocated size for matrix sized structures */ /* Sparse problem matrix storage */ #if MatrixColAccess==CAM_Record MATitem *col_mat; /* mat_alloc : The sparse data storage */ #else /*MatrixColAccess==CAM_Vector*/ int *col_mat_colnr; int *col_mat_rownr; REAL *col_mat_value; #endif int *col_end; /* columns_alloc+1 : col_end[i] is the index of the first element after column i; column[i] is stored in elements col_end[i-1] to col_end[i]-1 */ int *col_tag; /* user-definable tag associated with each column */ #if MatrixRowAccess==RAM_Index int *row_mat; /* mat_alloc : From index 0, row_mat contains the row-ordered index of the elements of col_mat */ #elif MatrixColAccess==CAM_Record MATitem *row_mat; /* mat_alloc : From index 0, row_mat contains the row-ordered copy of the elements in col_mat */ #else /*if MatrixColAccess==CAM_Vector*/ int *row_mat_colnr; int *row_mat_rownr; REAL *row_mat_value; #endif int *row_end; /* rows_alloc+1 : row_end[i] is the index of the first element in row_mat after row i */ int *row_tag; /* user-definable tag associated with each row */ REAL *colmax; /* Array of maximum values of each column */ REAL *rowmax; /* Array of maximum values of each row */ REAL epsvalue; /* Zero element rejection threshold */ REAL infnorm; /* The largest absolute value in the matrix */ REAL dynrange; MYBOOL row_end_valid; /* TRUE if row_end & row_mat are valid */ MYBOOL is_roworder; /* TRUE if the current (temporary) matrix order is row-wise */ } MATrec; typedef struct _DeltaVrec { lprec *lp; int activelevel; MATrec *tracker; } DeltaVrec; #ifdef __cplusplus __EXTERN_C { #endif /* Sparse matrix routines */ STATIC MATrec *mat_create(lprec *lp, int rows, int columns, REAL epsvalue); STATIC MYBOOL mat_memopt(MATrec *mat, int rowextra, int colextra, int nzextra); STATIC void mat_free(MATrec **matrix); STATIC MYBOOL inc_matrow_space(MATrec *mat, int deltarows); STATIC int mat_mapreplace(MATrec *mat, LLrec *rowmap, LLrec *colmap, MATrec *insmat); STATIC int mat_matinsert(MATrec *mat, MATrec *insmat); STATIC int mat_zerocompact(MATrec *mat); STATIC int mat_rowcompact(MATrec *mat, MYBOOL dozeros); STATIC int mat_colcompact(MATrec *mat, int prev_rows, int prev_cols); STATIC MYBOOL inc_matcol_space(MATrec *mat, int deltacols); STATIC MYBOOL inc_mat_space(MATrec *mat, int mindelta); STATIC int mat_shiftrows(MATrec *mat, int *bbase, int delta, LLrec *varmap); STATIC int mat_shiftcols(MATrec *mat, int *bbase, int delta, LLrec *varmap); STATIC MATrec *mat_extractmat(MATrec *mat, LLrec *rowmap, LLrec *colmap, MYBOOL negated); STATIC int mat_appendrow(MATrec *mat, int count, REAL *row, int *colno, REAL mult, MYBOOL checkrowmode); STATIC int mat_appendcol(MATrec *mat, int count, REAL *column, int *rowno, REAL mult, MYBOOL checkrowmode); MYBOOL mat_get_data(lprec *lp, int matindex, MYBOOL isrow, int **rownr, int **colnr, REAL **value); MYBOOL mat_set_rowmap(MATrec *mat, int row_mat_index, int rownr, int colnr, int col_mat_index); STATIC MYBOOL mat_indexrange(MATrec *mat, int index, MYBOOL isrow, int *startpos, int *endpos); STATIC MYBOOL mat_validate(MATrec *mat); STATIC MYBOOL mat_equalRows(MATrec *mat, int baserow, int comprow); STATIC int mat_findelm(MATrec *mat, int row, int column); STATIC int mat_findins(MATrec *mat, int row, int column, int *insertpos, MYBOOL validate); STATIC void mat_multcol(MATrec *mat, int col_nr, REAL mult, MYBOOL DoObj); STATIC REAL mat_getitem(MATrec *mat, int row, int column); STATIC MYBOOL mat_setitem(MATrec *mat, int row, int column, REAL value); STATIC MYBOOL mat_additem(MATrec *mat, int row, int column, REAL delta); STATIC MYBOOL mat_setvalue(MATrec *mat, int Row, int Column, REAL Value, MYBOOL doscale); STATIC int mat_nonzeros(MATrec *mat); STATIC int mat_collength(MATrec *mat, int colnr); STATIC int mat_rowlength(MATrec *mat, int rownr); STATIC void mat_multrow(MATrec *mat, int row_nr, REAL mult); STATIC void mat_multadd(MATrec *mat, REAL *lhsvector, int varnr, REAL mult); STATIC MYBOOL mat_setrow(MATrec *mat, int rowno, int count, REAL *row, int *colno, MYBOOL doscale, MYBOOL checkrowmode); STATIC MYBOOL mat_setcol(MATrec *mat, int colno, int count, REAL *column, int *rowno, MYBOOL doscale, MYBOOL checkrowmode); STATIC MYBOOL mat_mergemat(MATrec *target, MATrec *source, MYBOOL usecolmap); STATIC int mat_checkcounts(MATrec *mat, int *rownum, int *colnum, MYBOOL freeonexit); STATIC int mat_expandcolumn(MATrec *mat, int colnr, REAL *column, int *nzlist, MYBOOL signedA); STATIC MYBOOL mat_computemax(MATrec *mat); STATIC MYBOOL mat_transpose(MATrec *mat); /* Refactorization and recomputation routine */ MYBOOL __WINAPI invert(lprec *lp, MYBOOL shiftbounds, MYBOOL final); /* Vector compression and expansion routines */ STATIC MYBOOL vec_compress(REAL *densevector, int startpos, int endpos, REAL epsilon, REAL *nzvector, int *nzindex); STATIC MYBOOL vec_expand(REAL *nzvector, int *nzindex, REAL *densevector, int startpos, int endpos); /* Sparse matrix products */ STATIC MYBOOL get_colIndexA(lprec *lp, int varset, int *colindex, MYBOOL append); STATIC int prod_Ax(lprec *lp, int *coltarget, REAL *input, int *nzinput, REAL roundzero, REAL ofscalar, REAL *output, int *nzoutput, int roundmode); STATIC int prod_xA(lprec *lp, int *coltarget, REAL *input, int *nzinput, REAL roundzero, REAL ofscalar, REAL *output, int *nzoutput, int roundmode); STATIC MYBOOL prod_xA2(lprec *lp, int *coltarget, REAL *prow, REAL proundzero, int *pnzprow, REAL *drow, REAL droundzero, int *dnzdrow, REAL ofscalar, int roundmode); /* Equation solution */ STATIC MYBOOL fimprove(lprec *lp, REAL *pcol, int *nzidx, REAL roundzero); STATIC void ftran(lprec *lp, REAL *rhsvector, int *nzidx, REAL roundzero); STATIC MYBOOL bimprove(lprec *lp, REAL *rhsvector, int *nzidx, REAL roundzero); STATIC void btran(lprec *lp, REAL *rhsvector, int *nzidx, REAL roundzero); /* Combined equation solution and matrix product for simplex operations */ STATIC MYBOOL fsolve(lprec *lp, int varin, REAL *pcol, int *nzidx, REAL roundzero, REAL ofscalar, MYBOOL prepareupdate); STATIC MYBOOL bsolve(lprec *lp, int row_nr, REAL *rhsvector, int *nzidx, REAL roundzero, REAL ofscalar); STATIC void bsolve_xA2(lprec *lp, int* coltarget, int row_nr1, REAL *vector1, REAL roundzero1, int *nzvector1, int row_nr2, REAL *vector2, REAL roundzero2, int *nzvector2, int roundmode); /* Change-tracking routines (primarily for B&B and presolve) */ STATIC DeltaVrec *createUndoLadder(lprec *lp, int levelitems, int maxlevels); STATIC int incrementUndoLadder(DeltaVrec *DV); STATIC MYBOOL modifyUndoLadder(DeltaVrec *DV, int itemno, REAL target[], REAL newvalue); STATIC int countsUndoLadder(DeltaVrec *DV); STATIC int restoreUndoLadder(DeltaVrec *DV, REAL target[]); STATIC int decrementUndoLadder(DeltaVrec *DV); STATIC MYBOOL freeUndoLadder(DeltaVrec **DV); /* Specialized presolve undo functions */ STATIC MYBOOL appendUndoPresolve(lprec *lp, MYBOOL isprimal, REAL beta, int colnrDep); STATIC MYBOOL addUndoPresolve(lprec *lp, MYBOOL isprimal, int colnrElim, REAL alpha, REAL beta, int colnrDep); #ifdef __cplusplus } #endif #endif /* HEADER_lp_matrix */ MSVMpack1.2/lp_solve_5.5/lp_rlp.c0000664000175000017500000021042311250515167015577 0ustar lauerlauer/* A Bison parser, made by GNU Bison 2.3. */ /* Skeleton implementation for Bison's Yacc-like parsers in C Copyright (C) 1984, 1989, 1990, 2000, 2001, 2002, 2003, 2004, 2005, 2006 Free Software Foundation, Inc. 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 2, 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, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. */ /* As a special exception, you may create a larger work that contains part or all of the Bison parser skeleton and distribute that work under terms of your choice, so long as that work isn't itself a parser generator using the skeleton or a modified version thereof as a parser skeleton. Alternatively, if you modify or redistribute the parser skeleton itself, you may (at your option) remove this special exception, which will cause the skeleton and the resulting Bison output files to be licensed under the GNU General Public License without this special exception. This special exception was added by the Free Software Foundation in version 2.2 of Bison. */ /* C LALR(1) parser skeleton written by Richard Stallman, by simplifying the original so-called "semantic" parser. */ /* All symbols defined below should begin with lp_yy or YY, to avoid infringing on user name space. This should be done even for local variables, as they might otherwise be expanded by user macros. There are some unavoidable exceptions within include files to define necessary library symbols; they are noted "INFRINGES ON USER NAME SPACE" below. */ /* Identify Bison output. */ #define YYBISON 1 /* Bison version. */ #define YYBISON_VERSION "2.3" /* Skeleton name. */ #define YYSKELETON_NAME "yacc.c" /* Pure parsers. */ #define YYPURE 1 /* Using locations. */ #define YYLSP_NEEDED 0 /* Tokens. */ #ifndef YYTOKENTYPE # define YYTOKENTYPE /* Put the tokens into the symbol table, so that GDB and other debuggers know about them. */ enum lp_yytokentype { VAR = 258, CONS = 259, INTCONS = 260, VARIABLECOLON = 261, INF = 262, SEC_INT = 263, SEC_BIN = 264, SEC_SEC = 265, SEC_SOS = 266, SOSDESCR = 267, SEC_FREE = 268, TOK_SIGN = 269, AR_M_OP = 270, RE_OPEQ = 271, RE_OPLE = 272, RE_OPGE = 273, END_C = 274, COMMA = 275, COLON = 276, MINIMISE = 277, MAXIMISE = 278, UNDEFINED = 279 }; #endif /* Tokens. */ #define VAR 258 #define CONS 259 #define INTCONS 260 #define VARIABLECOLON 261 #define INF 262 #define SEC_INT 263 #define SEC_BIN 264 #define SEC_SEC 265 #define SEC_SOS 266 #define SOSDESCR 267 #define SEC_FREE 268 #define TOK_SIGN 269 #define AR_M_OP 270 #define RE_OPEQ 271 #define RE_OPLE 272 #define RE_OPGE 273 #define END_C 274 #define COMMA 275 #define COLON 276 #define MINIMISE 277 #define MAXIMISE 278 #define UNDEFINED 279 /* Copy the first part of user declarations. */ #include #include #include #define scanner lp_yyscanner #define PARM lp_yyget_extra(lp_yyscanner) #define YYSTYPE int #define YY_EXTRA_TYPE parse_parm * #define YY_FATAL_ERROR(msg) lex_fatal_error(PARM, lp_yyscanner, msg) #undef YY_INPUT #define YY_INPUT(buf,result,max_size) result = lp_input((void *) PARM, buf, max_size); #define lp_yyerror read_error #include "lpkit.h" #include "yacc_read.h" typedef struct parse_vars_s { read_modeldata_func *lp_input; void *userhandle; char HadVar, HadVar0, HadVar1, HadVar2, HasAR_M_OP, HadConstraint, Had_lineair_sum, Had_lineair_sum0, do_add_row, HadSign, OP, Sign, isign, isign0, make_neg; char state, state0; char Within_int_decl; /* TRUE when we are within an char declaration */ char Within_bin_decl; /* TRUE when we are within an bin declaration */ char Within_sec_decl; /* TRUE when we are within a sec declaration */ char Within_sos_decl; /* TRUE when we are within a sos declaration */ char Within_sos_decl1; char Within_free_decl; /* TRUE when we are within a free declaration */ short SOStype, SOStype0; /* SOS type */ int SOSNr; int SOSweight; /* SOS weight */ char *Last_var, *Last_var0; REAL f, f0, f1; } parse_vars; #ifdef FORTIFY # include "lp_fortify.h" #endif /* let's please C++ users */ #ifdef __cplusplus extern "C" { #endif #if defined MSDOS || defined __MSDOS__ || defined WINDOWS || defined _WINDOWS || defined WIN32 || defined _WIN32 #define YY_NO_UNISTD_H static int isatty(int f) { return(FALSE); } #if !defined _STDLIB_H # define _STDLIB_H #endif #endif static int __WINAPI lp_input_lp_yyin(void *fpin, char *buf, int max_size) { int result; result = fread( (char*)buf, sizeof(char), max_size, (FILE *)fpin); return(result); } static int __WINAPI lp_input(void *vpp, char *buf, int max_size) { parse_parm *pp = (parse_parm *) vpp; parse_vars *pv = (parse_vars *) pp->parse_vars; int result; result = pv->lp_input(pv->userhandle, buf, max_size); if (result < 0) lex_fatal_error(pp, pp->scanner, "read() in flex scanner failed"); return(result); } #ifdef __cplusplus }; #endif #include "lp_rlp.h" #undef lp_yylval /* Enabling traces. */ #ifndef YYDEBUG # define YYDEBUG 0 #endif /* Enabling verbose error messages. */ #ifdef YYERROR_VERBOSE # undef YYERROR_VERBOSE # define YYERROR_VERBOSE 1 #else # define YYERROR_VERBOSE 0 #endif /* Enabling the token table. */ #ifndef YYTOKEN_TABLE # define YYTOKEN_TABLE 0 #endif #if ! defined YYSTYPE && ! defined YYSTYPE_IS_DECLARED typedef int YYSTYPE; # define lp_yystype YYSTYPE /* obsolescent; will be withdrawn */ # define YYSTYPE_IS_DECLARED 1 # define YYSTYPE_IS_TRIVIAL 1 #endif /* Copy the second part of user declarations. */ /* Line 216 of yacc.c. */ #ifdef short # undef short #endif #ifdef YYTYPE_UINT8 typedef YYTYPE_UINT8 lp_yytype_uint8; #else typedef unsigned char lp_yytype_uint8; #endif #ifdef YYTYPE_INT8 typedef YYTYPE_INT8 lp_yytype_int8; #elif (defined __STDC__ || defined __C99__FUNC__ \ || defined __cplusplus || defined _MSC_VER) typedef signed char lp_yytype_int8; #else typedef short int lp_yytype_int8; #endif #ifdef YYTYPE_UINT16 typedef YYTYPE_UINT16 lp_yytype_uint16; #else typedef unsigned short int lp_yytype_uint16; #endif #ifdef YYTYPE_INT16 typedef YYTYPE_INT16 lp_yytype_int16; #else typedef short int lp_yytype_int16; #endif #ifndef YYSIZE_T # ifdef __SIZE_TYPE__ # define YYSIZE_T __SIZE_TYPE__ # elif defined size_t # define YYSIZE_T size_t # elif ! defined YYSIZE_T && (defined __STDC__ || defined __C99__FUNC__ \ || defined __cplusplus || defined _MSC_VER) # include /* INFRINGES ON USER NAME SPACE */ # define YYSIZE_T size_t # else # define YYSIZE_T unsigned int # endif #endif #define YYSIZE_MAXIMUM ((YYSIZE_T) -1) #ifndef YY_ # if YYENABLE_NLS # if ENABLE_NLS # include /* INFRINGES ON USER NAME SPACE */ # define YY_(msgid) dgettext ("bison-runtime", msgid) # endif # endif # ifndef YY_ # define YY_(msgid) msgid # endif #endif /* Suppress unused-variable warnings by "using" E. */ #if ! defined lint || defined __GNUC__ # define YYUSE(e) ((void) (e)) #else # define YYUSE(e) /* empty */ #endif /* Identity function, used to suppress warnings about constant conditions. */ #ifndef lint # define YYID(n) (n) #else #if (defined __STDC__ || defined __C99__FUNC__ \ || defined __cplusplus || defined _MSC_VER) static int YYID (int i) #else static int YYID (i) int i; #endif { return i; } #endif #if ! defined lp_yyoverflow || YYERROR_VERBOSE /* The parser invokes alloca or malloc; define the necessary symbols. */ # ifdef YYSTACK_USE_ALLOCA # if YYSTACK_USE_ALLOCA # ifdef __GNUC__ # define YYSTACK_ALLOC __builtin_alloca # elif defined __BUILTIN_VA_ARG_INCR # include /* INFRINGES ON USER NAME SPACE */ # elif defined _AIX # define YYSTACK_ALLOC __alloca # elif defined _MSC_VER # include /* INFRINGES ON USER NAME SPACE */ # define alloca _alloca # else # define YYSTACK_ALLOC alloca # if ! defined _ALLOCA_H && ! defined _STDLIB_H && (defined __STDC__ || defined __C99__FUNC__ \ || defined __cplusplus || defined _MSC_VER) # include /* INFRINGES ON USER NAME SPACE */ # ifndef _STDLIB_H # define _STDLIB_H 1 # endif # endif # endif # endif # endif # ifdef YYSTACK_ALLOC /* Pacify GCC's `empty if-body' warning. */ # define YYSTACK_FREE(Ptr) do { /* empty */; } while (YYID (0)) # ifndef YYSTACK_ALLOC_MAXIMUM /* The OS might guarantee only one guard page at the bottom of the stack, and a page size can be as small as 4096 bytes. So we cannot safely invoke alloca (N) if N exceeds 4096. Use a slightly smaller number to allow for a few compiler-allocated temporary stack slots. */ # define YYSTACK_ALLOC_MAXIMUM 4032 /* reasonable circa 2006 */ # endif # else # define YYSTACK_ALLOC YYMALLOC # define YYSTACK_FREE YYFREE # ifndef YYSTACK_ALLOC_MAXIMUM # define YYSTACK_ALLOC_MAXIMUM YYSIZE_MAXIMUM # endif # if (defined __cplusplus && ! defined _STDLIB_H \ && ! ((defined YYMALLOC || defined malloc) \ && (defined YYFREE || defined free))) # include /* INFRINGES ON USER NAME SPACE */ # ifndef _STDLIB_H # define _STDLIB_H 1 # endif # endif # ifndef YYMALLOC # define YYMALLOC malloc # if ! defined malloc && ! defined _STDLIB_H && (defined __STDC__ || defined __C99__FUNC__ \ || defined __cplusplus || defined _MSC_VER) void *malloc (YYSIZE_T); /* INFRINGES ON USER NAME SPACE */ # endif # endif # ifndef YYFREE # define YYFREE free # if ! defined free && ! defined _STDLIB_H && (defined __STDC__ || defined __C99__FUNC__ \ || defined __cplusplus || defined _MSC_VER) void free (void *); /* INFRINGES ON USER NAME SPACE */ # endif # endif # endif #endif /* ! defined lp_yyoverflow || YYERROR_VERBOSE */ #if (! defined lp_yyoverflow \ && (! defined __cplusplus \ || (defined YYSTYPE_IS_TRIVIAL && YYSTYPE_IS_TRIVIAL))) /* A type that is properly aligned for any stack member. */ union lp_yyalloc { lp_yytype_int16 lp_yyss; YYSTYPE lp_yyvs; }; /* The size of the maximum gap between one aligned stack and the next. */ # define YYSTACK_GAP_MAXIMUM (sizeof (union lp_yyalloc) - 1) /* The size of an array large to enough to hold all stacks, each with N elements. */ # define YYSTACK_BYTES(N) \ ((N) * (sizeof (lp_yytype_int16) + sizeof (YYSTYPE)) \ + YYSTACK_GAP_MAXIMUM) /* Copy COUNT objects from FROM to TO. The source and destination do not overlap. */ # ifndef YYCOPY # if defined __GNUC__ && 1 < __GNUC__ # define YYCOPY(To, From, Count) \ __builtin_memcpy (To, From, (Count) * sizeof (*(From))) # else # define YYCOPY(To, From, Count) \ do \ { \ YYSIZE_T lp_yyi; \ for (lp_yyi = 0; lp_yyi < (Count); lp_yyi++) \ (To)[lp_yyi] = (From)[lp_yyi]; \ } \ while (YYID (0)) # endif # endif /* Relocate STACK from its old location to the new one. The local variables YYSIZE and YYSTACKSIZE give the old and new number of elements in the stack, and YYPTR gives the new location of the stack. Advance YYPTR to a properly aligned location for the next stack. */ # define YYSTACK_RELOCATE(Stack) \ do \ { \ YYSIZE_T lp_yynewbytes; \ YYCOPY (&lp_yyptr->Stack, Stack, lp_yysize); \ Stack = &lp_yyptr->Stack; \ lp_yynewbytes = lp_yystacksize * sizeof (*Stack) + YYSTACK_GAP_MAXIMUM; \ lp_yyptr += lp_yynewbytes / sizeof (*lp_yyptr); \ } \ while (YYID (0)) #endif /* YYFINAL -- State number of the termination state. */ #define YYFINAL 3 /* YYLAST -- Last index in YYTABLE. */ #define YYLAST 115 /* YYNTOKENS -- Number of terminals. */ #define YYNTOKENS 25 /* YYNNTS -- Number of nonterminals. */ #define YYNNTS 56 /* YYNRULES -- Number of rules. */ #define YYNRULES 89 /* YYNRULES -- Number of states. */ #define YYNSTATES 123 /* YYTRANSLATE(YYLEX) -- Bison symbol number corresponding to YYLEX. */ #define YYUNDEFTOK 2 #define YYMAXUTOK 279 #define YYTRANSLATE(YYX) \ ((unsigned int) (YYX) <= YYMAXUTOK ? lp_yytranslate[YYX] : YYUNDEFTOK) /* YYTRANSLATE[YYLEX] -- Bison symbol number corresponding to YYLEX. */ static const lp_yytype_uint8 lp_yytranslate[] = { 0, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24 }; #if YYDEBUG /* YYPRHS[YYN] -- Index of the first RHS symbol of rule number YYN in YYRHS. */ static const lp_yytype_uint8 lp_yyprhs[] = { 0, 0, 3, 4, 5, 10, 13, 16, 18, 21, 23, 25, 27, 29, 31, 34, 36, 37, 41, 42, 43, 44, 53, 55, 56, 57, 63, 65, 67, 69, 70, 74, 75, 78, 80, 83, 86, 88, 89, 93, 95, 97, 99, 102, 104, 106, 108, 110, 112, 114, 116, 118, 120, 122, 124, 127, 129, 131, 133, 135, 137, 138, 142, 143, 149, 151, 154, 156, 157, 161, 163, 164, 169, 171, 174, 176, 178, 180, 184, 186, 188, 190, 191, 193, 195, 198, 202, 205, 208, 211 }; /* YYRHS -- A `-1'-separated list of the rules' RHS. */ static const lp_yytype_int8 lp_yyrhs[] = { 27, 0, -1, -1, -1, 28, 29, 32, 58, -1, 23, 30, -1, 22, 30, -1, 30, -1, 31, 19, -1, 26, -1, 46, -1, 26, -1, 33, -1, 34, -1, 33, 34, -1, 36, -1, -1, 6, 35, 36, -1, -1, -1, -1, 43, 37, 52, 38, 44, 39, 40, 19, -1, 26, -1, -1, -1, 52, 41, 53, 42, 57, -1, 26, -1, 44, -1, 46, -1, -1, 7, 45, 57, -1, -1, 47, 48, -1, 49, -1, 48, 49, -1, 55, 50, -1, 54, -1, -1, 56, 51, 3, -1, 16, -1, 17, -1, 18, -1, 55, 54, -1, 7, -1, 5, -1, 4, -1, 26, -1, 14, -1, 26, -1, 15, -1, 26, -1, 26, -1, 59, -1, 61, -1, 59, 61, -1, 8, -1, 9, -1, 10, -1, 11, -1, 13, -1, -1, 60, 62, 65, -1, -1, 64, 66, 71, 68, 19, -1, 63, -1, 65, 63, -1, 26, -1, -1, 12, 67, 77, -1, 26, -1, -1, 17, 5, 69, 70, -1, 26, -1, 21, 5, -1, 26, -1, 72, -1, 78, -1, 72, 73, 78, -1, 26, -1, 20, -1, 26, -1, -1, 26, -1, 26, -1, 3, 74, -1, 6, 75, 79, -1, 54, 76, -1, 77, 80, -1, 3, 74, -1, 6, 75, 54, 76, -1 }; /* YYRLINE[YYN] -- source line where rule number YYN was defined. */ static const lp_yytype_uint16 lp_yyrline[] = { 0, 116, 116, 120, 120, 145, 149, 153, 156, 170, 171, 201, 202, 205, 206, 210, 212, 211, 224, 232, 242, 223, 288, 298, 311, 297, 342, 355, 364, 366, 365, 376, 376, 400, 401, 405, 444, 452, 451, 470, 470, 470, 473, 475, 489, 489, 492, 500, 510, 517, 526, 547, 548, 551, 552, 555, 555, 555, 555, 555, 560, 559, 570, 570, 598, 599, 602, 604, 603, 614, 626, 624, 643, 650, 660, 661, 664, 665, 670, 671, 674, 703, 724, 749, 770, 772, 777, 779, 784, 786 }; #endif #if YYDEBUG || YYERROR_VERBOSE || YYTOKEN_TABLE /* YYTNAME[SYMBOL-NUM] -- String name of the symbol SYMBOL-NUM. First, the terminals, then, starting at YYNTOKENS, nonterminals. */ static const char *const lp_yytname[] = { "$end", "error", "$undefined", "VAR", "CONS", "INTCONS", "VARIABLECOLON", "INF", "SEC_INT", "SEC_BIN", "SEC_SEC", "SEC_SOS", "SOSDESCR", "SEC_FREE", "TOK_SIGN", "AR_M_OP", "RE_OPEQ", "RE_OPLE", "RE_OPGE", "END_C", "COMMA", "COLON", "MINIMISE", "MAXIMISE", "UNDEFINED", "$accept", "EMPTY", "inputfile", "@1", "objective_function", "real_of", "lineair_sum", "constraints", "x_constraints", "constraint", "@2", "real_constraint", "@3", "@4", "@5", "optionalrange", "@6", "@7", "x_lineair_sum2", "x_lineair_sum3", "@8", "x_lineair_sum", "@9", "x_lineair_sum1", "x_lineair_term", "x_lineair_term1", "@10", "RE_OP", "cons_term", "REALCONS", "x_SIGN", "optional_AR_M_OP", "RHS_STORE", "int_bin_sec_sos_free_declarations", "real_int_bin_sec_sos_free_decls", "SEC_INT_BIN_SEC_SOS_FREE", "int_bin_sec_sos_free_declaration", "@11", "xx_int_bin_sec_sos_free_declaration", "@12", "x_int_bin_sec_sos_free_declaration", "optionalsos", "@13", "optionalsostype", "@14", "optionalSOSweight", "vars", "x_vars", "optionalcomma", "variable", "variablecolon", "sosweight", "sosdescr", "onevarwithoptionalweight", "INTCONSorVARIABLE", "x_onevarwithoptionalweight", 0 }; #endif # ifdef YYPRINT /* YYTOKNUM[YYLEX-NUM] -- Internal token number corresponding to token YYLEX-NUM. */ static const lp_yytype_uint16 lp_yytoknum[] = { 0, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279 }; # endif /* YYR1[YYN] -- Symbol number of symbol that rule YYN derives. */ static const lp_yytype_uint8 lp_yyr1[] = { 0, 25, 26, 28, 27, 29, 29, 29, 30, 31, 31, 32, 32, 33, 33, 34, 35, 34, 37, 38, 39, 36, 40, 41, 42, 40, 43, 43, 44, 45, 44, 47, 46, 48, 48, 49, 50, 51, 50, 52, 52, 52, 53, 53, 54, 54, 55, 55, 56, 56, 57, 58, 58, 59, 59, 60, 60, 60, 60, 60, 62, 61, 64, 63, 65, 65, 66, 67, 66, 68, 69, 68, 70, 70, 71, 71, 72, 72, 73, 73, 74, 75, 76, 77, 78, 78, 79, 79, 80, 80 }; /* YYR2[YYN] -- Number of symbols composing right hand side of rule YYN. */ static const lp_yytype_uint8 lp_yyr2[] = { 0, 2, 0, 0, 4, 2, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 0, 3, 0, 0, 0, 8, 1, 0, 0, 5, 1, 1, 1, 0, 3, 0, 2, 1, 2, 2, 1, 0, 3, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 0, 3, 0, 5, 1, 2, 1, 0, 3, 1, 0, 4, 1, 2, 1, 1, 1, 3, 1, 1, 1, 0, 1, 1, 2, 3, 2, 2, 2, 4 }; /* YYDEFACT[STATE-NAME] -- Default rule to reduce with in state STATE-NUM when YYTABLE doesn't specify something else to do. Zero means the default is an error. */ static const lp_yytype_uint8 lp_yydefact[] = { 3, 0, 31, 1, 31, 31, 9, 2, 7, 0, 10, 2, 6, 5, 16, 29, 11, 2, 12, 13, 15, 18, 27, 28, 8, 47, 46, 2, 33, 2, 31, 2, 55, 56, 57, 58, 59, 51, 4, 52, 60, 53, 26, 14, 0, 34, 45, 44, 49, 48, 35, 36, 37, 17, 50, 30, 54, 62, 39, 40, 41, 19, 0, 64, 2, 61, 31, 38, 67, 66, 2, 65, 20, 2, 2, 81, 74, 2, 2, 76, 2, 83, 68, 80, 84, 2, 0, 69, 0, 79, 78, 0, 22, 0, 23, 2, 0, 85, 70, 63, 77, 21, 2, 82, 86, 2, 81, 87, 2, 43, 24, 0, 88, 0, 0, 72, 71, 2, 42, 2, 73, 25, 89 }; /* YYDEFGOTO[NTERM-NUM]. */ static const lp_yytype_int8 lp_yydefgoto[] = { -1, 6, 1, 2, 7, 8, 9, 17, 18, 19, 30, 20, 44, 66, 80, 93, 102, 117, 21, 22, 31, 23, 11, 27, 28, 50, 62, 61, 110, 51, 29, 52, 55, 38, 39, 40, 41, 57, 63, 64, 65, 70, 73, 88, 108, 116, 77, 78, 91, 84, 85, 104, 82, 79, 97, 107 }; /* YYPACT[STATE-NUM] -- Index in YYTABLE of the portion describing STATE-NUM. */ #define YYPACT_NINF -85 static const lp_yytype_int8 lp_yypact[] = { -85, 13, 46, -85, 2, 2, -85, 32, -85, 7, -85, 26, -85, -85, -85, -85, 64, 40, 27, -85, -85, -85, -85, -85, -85, -85, -85, 42, -85, 3, -2, -85, -85, -85, -85, -85, -85, -85, -85, 40, -85, -85, -85, -85, 67, -85, -85, -85, -85, -85, -85, -85, -85, -85, -85, -85, -85, -85, -85, -85, -85, -85, 59, -85, 52, 0, 84, -85, -85, -85, 22, -85, -85, -85, -85, -85, -85, 60, 35, -85, 67, -85, -85, -85, -85, 82, 87, -85, 74, -85, -85, 22, -85, 75, -85, -85, 73, -85, -85, -85, -85, -85, -5, -85, -85, -85, -85, -85, 76, -85, -85, 82, -85, 82, 91, -85, -85, -85, -85, -85, -85, -85, -85 }; /* YYPGOTO[NTERM-NUM]. */ static const lp_yytype_int8 lp_yypgoto[] = { -85, -7, -85, -85, -85, 85, -85, -85, -85, 81, -85, 72, -85, -85, -85, -85, -85, -85, -85, 34, -85, 70, -85, -85, 77, -85, -85, 23, -85, -84, 4, -85, -12, -85, -85, -85, 68, -85, 43, -85, -85, -85, -85, -85, -85, -85, -85, -85, -85, 6, 8, -10, 28, 24, -85, -85 }; /* YYTABLE[YYPACT[STATE-NUM]]. What to do in state STATE-NUM. If positive, shift that token. If negative, reduce the rule which number is the opposite. If zero, do what YYDEFACT says. If YYTABLE_NINF, syntax error. */ #define YYTABLE_NINF -76 static const lp_yytype_int8 lp_yytable[] = { 16, 95, 109, -62, 26, 15, -62, 46, 47, 25, 37, 42, -62, 3, -2, -2, -2, -62, 48, -62, 26, -2, 49, 42, 54, 74, 24, 118, 75, 119, -31, -31, -31, 14, 15, -31, -31, -31, 14, 15, 25, -31, -31, -2, -2, -2, -31, -31, 32, 33, 34, 35, -75, 36, -75, 89, 25, 69, -32, -32, -32, -32, 67, 76, 68, -2, 81, 83, 4, 5, 87, 90, 10, 92, 10, 10, 105, 86, 81, 106, -26, -26, -26, 58, 59, 60, 46, 47, 103, 12, 13, 15, 98, 99, 101, 26, 120, 114, 83, 43, 72, 115, 53, 94, 45, 121, 111, 56, 71, 122, 54, 112, 103, 96, 113, 100 }; static const lp_yytype_uint8 lp_yycheck[] = { 7, 85, 7, 3, 11, 7, 6, 4, 5, 14, 17, 18, 12, 0, 16, 17, 18, 17, 15, 19, 27, 19, 29, 30, 31, 3, 19, 111, 6, 113, 3, 4, 5, 6, 7, 3, 4, 5, 6, 7, 14, 14, 15, 16, 17, 18, 14, 15, 8, 9, 10, 11, 17, 13, 19, 20, 14, 64, 16, 17, 18, 19, 3, 70, 12, 19, 73, 74, 22, 23, 77, 78, 2, 80, 4, 5, 3, 17, 85, 6, 16, 17, 18, 16, 17, 18, 4, 5, 95, 4, 5, 7, 5, 19, 19, 102, 5, 21, 105, 18, 66, 108, 30, 80, 27, 117, 102, 39, 65, 119, 117, 105, 119, 85, 106, 91 }; /* YYSTOS[STATE-NUM] -- The (internal number of the) accessing symbol of state STATE-NUM. */ static const lp_yytype_uint8 lp_yystos[] = { 0, 27, 28, 0, 22, 23, 26, 29, 30, 31, 46, 47, 30, 30, 6, 7, 26, 32, 33, 34, 36, 43, 44, 46, 19, 14, 26, 48, 49, 55, 35, 45, 8, 9, 10, 11, 13, 26, 58, 59, 60, 61, 26, 34, 37, 49, 4, 5, 15, 26, 50, 54, 56, 36, 26, 57, 61, 62, 16, 17, 18, 52, 51, 63, 64, 65, 38, 3, 12, 26, 66, 63, 44, 67, 3, 6, 26, 71, 72, 78, 39, 26, 77, 26, 74, 75, 17, 26, 68, 20, 26, 73, 26, 40, 52, 54, 77, 79, 5, 19, 78, 19, 41, 26, 76, 3, 6, 80, 69, 7, 53, 55, 74, 75, 21, 26, 70, 42, 54, 54, 5, 57, 76 }; #define lp_yyerrok (lp_yyerrstatus = 0) #define lp_yyclearin (lp_yychar = YYEMPTY) #define YYEMPTY (-2) #define YYEOF 0 #define YYACCEPT goto lp_yyacceptlab #define YYABORT goto lp_yyabortlab #define YYERROR goto lp_yyerrorlab /* Like YYERROR except do call lp_yyerror. This remains here temporarily to ease the transition to the new meaning of YYERROR, for GCC. Once GCC version 2 has supplanted version 1, this can go. */ #define YYFAIL goto lp_yyerrlab #define YYRECOVERING() (!!lp_yyerrstatus) #define YYBACKUP(Token, Value) \ do \ if (lp_yychar == YYEMPTY && lp_yylen == 1) \ { \ lp_yychar = (Token); \ lp_yylval = (Value); \ lp_yytoken = YYTRANSLATE (lp_yychar); \ YYPOPSTACK (1); \ goto lp_yybackup; \ } \ else \ { \ lp_yyerror (parm, scanner, YY_("syntax error: cannot back up")); \ YYERROR; \ } \ while (YYID (0)) #define YYTERROR 1 #define YYERRCODE 256 /* YYLLOC_DEFAULT -- Set CURRENT to span from RHS[1] to RHS[N]. If N is 0, then set CURRENT to the empty location which ends the previous symbol: RHS[0] (always defined). */ #define YYRHSLOC(Rhs, K) ((Rhs)[K]) #ifndef YYLLOC_DEFAULT # define YYLLOC_DEFAULT(Current, Rhs, N) \ do \ if (YYID (N)) \ { \ (Current).first_line = YYRHSLOC (Rhs, 1).first_line; \ (Current).first_column = YYRHSLOC (Rhs, 1).first_column; \ (Current).last_line = YYRHSLOC (Rhs, N).last_line; \ (Current).last_column = YYRHSLOC (Rhs, N).last_column; \ } \ else \ { \ (Current).first_line = (Current).last_line = \ YYRHSLOC (Rhs, 0).last_line; \ (Current).first_column = (Current).last_column = \ YYRHSLOC (Rhs, 0).last_column; \ } \ while (YYID (0)) #endif /* YY_LOCATION_PRINT -- Print the location on the stream. This macro was not mandated originally: define only if we know we won't break user code: when these are the locations we know. */ #ifndef YY_LOCATION_PRINT # if YYLTYPE_IS_TRIVIAL # define YY_LOCATION_PRINT(File, Loc) \ fprintf (File, "%d.%d-%d.%d", \ (Loc).first_line, (Loc).first_column, \ (Loc).last_line, (Loc).last_column) # else # define YY_LOCATION_PRINT(File, Loc) ((void) 0) # endif #endif /* YYLEX -- calling `lp_yylex' with the right arguments. */ #ifdef YYLEX_PARAM # define YYLEX lp_yylex (&lp_yylval, YYLEX_PARAM) #else # define YYLEX lp_yylex (&lp_yylval, scanner) #endif /* Enable debugging if requested. */ #if YYDEBUG # ifndef YYFPRINTF # include /* INFRINGES ON USER NAME SPACE */ # define YYFPRINTF fprintf # endif # define YYDPRINTF(Args) \ do { \ if (lp_yydebug) \ YYFPRINTF Args; \ } while (YYID (0)) # define YY_SYMBOL_PRINT(Title, Type, Value, Location) \ do { \ if (lp_yydebug) \ { \ YYFPRINTF (stderr, "%s ", Title); \ lp_yy_symbol_print (stderr, \ Type, Value, parm, scanner); \ YYFPRINTF (stderr, "\n"); \ } \ } while (YYID (0)) /*--------------------------------. | Print this symbol on YYOUTPUT. | `--------------------------------*/ /*ARGSUSED*/ #if (defined __STDC__ || defined __C99__FUNC__ \ || defined __cplusplus || defined _MSC_VER) static void lp_yy_symbol_value_print (FILE *lp_yyoutput, int lp_yytype, YYSTYPE const * const lp_yyvaluep, parse_parm *parm, void *scanner) #else static void lp_yy_symbol_value_print (lp_yyoutput, lp_yytype, lp_yyvaluep, parm, scanner) FILE *lp_yyoutput; int lp_yytype; YYSTYPE const * const lp_yyvaluep; parse_parm *parm; void *scanner; #endif { if (!lp_yyvaluep) return; YYUSE (parm); YYUSE (scanner); # ifdef YYPRINT if (lp_yytype < YYNTOKENS) YYPRINT (lp_yyoutput, lp_yytoknum[lp_yytype], *lp_yyvaluep); # else YYUSE (lp_yyoutput); # endif switch (lp_yytype) { default: break; } } /*--------------------------------. | Print this symbol on YYOUTPUT. | `--------------------------------*/ #if (defined __STDC__ || defined __C99__FUNC__ \ || defined __cplusplus || defined _MSC_VER) static void lp_yy_symbol_print (FILE *lp_yyoutput, int lp_yytype, YYSTYPE const * const lp_yyvaluep, parse_parm *parm, void *scanner) #else static void lp_yy_symbol_print (lp_yyoutput, lp_yytype, lp_yyvaluep, parm, scanner) FILE *lp_yyoutput; int lp_yytype; YYSTYPE const * const lp_yyvaluep; parse_parm *parm; void *scanner; #endif { if (lp_yytype < YYNTOKENS) YYFPRINTF (lp_yyoutput, "token %s (", lp_yytname[lp_yytype]); else YYFPRINTF (lp_yyoutput, "nterm %s (", lp_yytname[lp_yytype]); lp_yy_symbol_value_print (lp_yyoutput, lp_yytype, lp_yyvaluep, parm, scanner); YYFPRINTF (lp_yyoutput, ")"); } /*------------------------------------------------------------------. | lp_yy_stack_print -- Print the state stack from its BOTTOM up to its | | TOP (included). | `------------------------------------------------------------------*/ #if (defined __STDC__ || defined __C99__FUNC__ \ || defined __cplusplus || defined _MSC_VER) static void lp_yy_stack_print (lp_yytype_int16 *bottom, lp_yytype_int16 *top) #else static void lp_yy_stack_print (bottom, top) lp_yytype_int16 *bottom; lp_yytype_int16 *top; #endif { YYFPRINTF (stderr, "Stack now"); for (; bottom <= top; ++bottom) YYFPRINTF (stderr, " %d", *bottom); YYFPRINTF (stderr, "\n"); } # define YY_STACK_PRINT(Bottom, Top) \ do { \ if (lp_yydebug) \ lp_yy_stack_print ((Bottom), (Top)); \ } while (YYID (0)) /*------------------------------------------------. | Report that the YYRULE is going to be reduced. | `------------------------------------------------*/ #if (defined __STDC__ || defined __C99__FUNC__ \ || defined __cplusplus || defined _MSC_VER) static void lp_yy_reduce_print (YYSTYPE *lp_yyvsp, int lp_yyrule, parse_parm *parm, void *scanner) #else static void lp_yy_reduce_print (lp_yyvsp, lp_yyrule, parm, scanner) YYSTYPE *lp_yyvsp; int lp_yyrule; parse_parm *parm; void *scanner; #endif { int lp_yynrhs = lp_yyr2[lp_yyrule]; int lp_yyi; unsigned long int lp_yylno = lp_yyrline[lp_yyrule]; YYFPRINTF (stderr, "Reducing stack by rule %d (line %lu):\n", lp_yyrule - 1, lp_yylno); /* The symbols being reduced. */ for (lp_yyi = 0; lp_yyi < lp_yynrhs; lp_yyi++) { fprintf (stderr, " $%d = ", lp_yyi + 1); lp_yy_symbol_print (stderr, lp_yyrhs[lp_yyprhs[lp_yyrule] + lp_yyi], &(lp_yyvsp[(lp_yyi + 1) - (lp_yynrhs)]) , parm, scanner); fprintf (stderr, "\n"); } } # define YY_REDUCE_PRINT(Rule) \ do { \ if (lp_yydebug) \ lp_yy_reduce_print (lp_yyvsp, Rule, parm, scanner); \ } while (YYID (0)) /* Nonzero means print parse trace. It is left uninitialized so that multiple parsers can coexist. */ int lp_yydebug; #else /* !YYDEBUG */ # define YYDPRINTF(Args) # define YY_SYMBOL_PRINT(Title, Type, Value, Location) # define YY_STACK_PRINT(Bottom, Top) # define YY_REDUCE_PRINT(Rule) #endif /* !YYDEBUG */ /* YYINITDEPTH -- initial size of the parser's stacks. */ #ifndef YYINITDEPTH # define YYINITDEPTH 200 #endif /* YYMAXDEPTH -- maximum size the stacks can grow to (effective only if the built-in stack extension method is used). Do not make this value too large; the results are undefined if YYSTACK_ALLOC_MAXIMUM < YYSTACK_BYTES (YYMAXDEPTH) evaluated with infinite-precision integer arithmetic. */ #ifndef YYMAXDEPTH # define YYMAXDEPTH 10000 #endif #if YYERROR_VERBOSE # ifndef lp_yystrlen # if defined __GLIBC__ && defined _STRING_H # define lp_yystrlen strlen # else /* Return the length of YYSTR. */ #if (defined __STDC__ || defined __C99__FUNC__ \ || defined __cplusplus || defined _MSC_VER) static YYSIZE_T lp_yystrlen (const char *lp_yystr) #else static YYSIZE_T lp_yystrlen (lp_yystr) const char *lp_yystr; #endif { YYSIZE_T lp_yylen; for (lp_yylen = 0; lp_yystr[lp_yylen]; lp_yylen++) continue; return lp_yylen; } # endif # endif # ifndef lp_yystpcpy # if defined __GLIBC__ && defined _STRING_H && defined _GNU_SOURCE # define lp_yystpcpy stpcpy # else /* Copy YYSRC to YYDEST, returning the address of the terminating '\0' in YYDEST. */ #if (defined __STDC__ || defined __C99__FUNC__ \ || defined __cplusplus || defined _MSC_VER) static char * lp_yystpcpy (char *lp_yydest, const char *lp_yysrc) #else static char * lp_yystpcpy (lp_yydest, lp_yysrc) char *lp_yydest; const char *lp_yysrc; #endif { char *lp_yyd = lp_yydest; const char *lp_yys = lp_yysrc; while ((*lp_yyd++ = *lp_yys++) != '\0') continue; return lp_yyd - 1; } # endif # endif # ifndef lp_yytnamerr /* Copy to YYRES the contents of YYSTR after stripping away unnecessary quotes and backslashes, so that it's suitable for lp_yyerror. The heuristic is that double-quoting is unnecessary unless the string contains an apostrophe, a comma, or backslash (other than backslash-backslash). YYSTR is taken from lp_yytname. If YYRES is null, do not copy; instead, return the length of what the result would have been. */ static YYSIZE_T lp_yytnamerr (char *lp_yyres, const char *lp_yystr) { if (*lp_yystr == '"') { YYSIZE_T lp_yyn = 0; char const *lp_yyp = lp_yystr; for (;;) switch (*++lp_yyp) { case '\'': case ',': goto do_not_strip_quotes; case '\\': if (*++lp_yyp != '\\') goto do_not_strip_quotes; /* Fall through. */ default: if (lp_yyres) lp_yyres[lp_yyn] = *lp_yyp; lp_yyn++; break; case '"': if (lp_yyres) lp_yyres[lp_yyn] = '\0'; return lp_yyn; } do_not_strip_quotes: ; } if (! lp_yyres) return lp_yystrlen (lp_yystr); return lp_yystpcpy (lp_yyres, lp_yystr) - lp_yyres; } # endif /* Copy into YYRESULT an error message about the unexpected token YYCHAR while in state YYSTATE. Return the number of bytes copied, including the terminating null byte. If YYRESULT is null, do not copy anything; just return the number of bytes that would be copied. As a special case, return 0 if an ordinary "syntax error" message will do. Return YYSIZE_MAXIMUM if overflow occurs during size calculation. */ static YYSIZE_T lp_yysyntax_error (char *lp_yyresult, int lp_yystate, int lp_yychar) { int lp_yyn = lp_yypact[lp_yystate]; if (! (YYPACT_NINF < lp_yyn && lp_yyn <= YYLAST)) return 0; else { int lp_yytype = YYTRANSLATE (lp_yychar); YYSIZE_T lp_yysize0 = lp_yytnamerr (0, lp_yytname[lp_yytype]); YYSIZE_T lp_yysize = lp_yysize0; YYSIZE_T lp_yysize1; int lp_yysize_overflow = 0; enum { YYERROR_VERBOSE_ARGS_MAXIMUM = 5 }; char const *lp_yyarg[YYERROR_VERBOSE_ARGS_MAXIMUM]; int lp_yyx; # if 0 /* This is so xgettext sees the translatable formats that are constructed on the fly. */ YY_("syntax error, unexpected %s"); YY_("syntax error, unexpected %s, expecting %s"); YY_("syntax error, unexpected %s, expecting %s or %s"); YY_("syntax error, unexpected %s, expecting %s or %s or %s"); YY_("syntax error, unexpected %s, expecting %s or %s or %s or %s"); # endif char *lp_yyfmt; char const *lp_yyf; static char const lp_yyunexpected[] = "syntax error, unexpected %s"; static char const lp_yyexpecting[] = ", expecting %s"; static char const lp_yyor[] = " or %s"; char lp_yyformat[sizeof lp_yyunexpected + sizeof lp_yyexpecting - 1 + ((YYERROR_VERBOSE_ARGS_MAXIMUM - 2) * (sizeof lp_yyor - 1))]; char const *lp_yyprefix = lp_yyexpecting; /* Start YYX at -YYN if negative to avoid negative indexes in YYCHECK. */ int lp_yyxbegin = lp_yyn < 0 ? -lp_yyn : 0; /* Stay within bounds of both lp_yycheck and lp_yytname. */ int lp_yychecklim = YYLAST - lp_yyn + 1; int lp_yyxend = lp_yychecklim < YYNTOKENS ? lp_yychecklim : YYNTOKENS; int lp_yycount = 1; lp_yyarg[0] = lp_yytname[lp_yytype]; lp_yyfmt = lp_yystpcpy (lp_yyformat, lp_yyunexpected); for (lp_yyx = lp_yyxbegin; lp_yyx < lp_yyxend; ++lp_yyx) if (lp_yycheck[lp_yyx + lp_yyn] == lp_yyx && lp_yyx != YYTERROR) { if (lp_yycount == YYERROR_VERBOSE_ARGS_MAXIMUM) { lp_yycount = 1; lp_yysize = lp_yysize0; lp_yyformat[sizeof lp_yyunexpected - 1] = '\0'; break; } lp_yyarg[lp_yycount++] = lp_yytname[lp_yyx]; lp_yysize1 = lp_yysize + lp_yytnamerr (0, lp_yytname[lp_yyx]); lp_yysize_overflow |= (lp_yysize1 < lp_yysize); lp_yysize = lp_yysize1; lp_yyfmt = lp_yystpcpy (lp_yyfmt, lp_yyprefix); lp_yyprefix = lp_yyor; } lp_yyf = YY_(lp_yyformat); lp_yysize1 = lp_yysize + lp_yystrlen (lp_yyf); lp_yysize_overflow |= (lp_yysize1 < lp_yysize); lp_yysize = lp_yysize1; if (lp_yysize_overflow) return YYSIZE_MAXIMUM; if (lp_yyresult) { /* Avoid sprintf, as that infringes on the user's name space. Don't have undefined behavior even if the translation produced a string with the wrong number of "%s"s. */ char *lp_yyp = lp_yyresult; int lp_yyi = 0; while ((*lp_yyp = *lp_yyf) != '\0') { if (*lp_yyp == '%' && lp_yyf[1] == 's' && lp_yyi < lp_yycount) { lp_yyp += lp_yytnamerr (lp_yyp, lp_yyarg[lp_yyi++]); lp_yyf += 2; } else { lp_yyp++; lp_yyf++; } } } return lp_yysize; } } #endif /* YYERROR_VERBOSE */ /*-----------------------------------------------. | Release the memory associated to this symbol. | `-----------------------------------------------*/ /*ARGSUSED*/ #if (defined __STDC__ || defined __C99__FUNC__ \ || defined __cplusplus || defined _MSC_VER) static void lp_yydestruct (const char *lp_yymsg, int lp_yytype, YYSTYPE *lp_yyvaluep, parse_parm *parm, void *scanner) #else static void lp_yydestruct (lp_yymsg, lp_yytype, lp_yyvaluep, parm, scanner) const char *lp_yymsg; int lp_yytype; YYSTYPE *lp_yyvaluep; parse_parm *parm; void *scanner; #endif { YYUSE (lp_yyvaluep); YYUSE (parm); YYUSE (scanner); if (!lp_yymsg) lp_yymsg = "Deleting"; YY_SYMBOL_PRINT (lp_yymsg, lp_yytype, lp_yyvaluep, lp_yylocationp); switch (lp_yytype) { default: break; } } /* Prevent warnings from -Wmissing-prototypes. */ #ifdef YYPARSE_PARAM #if defined __STDC__ || defined __cplusplus int lp_yyparse (void *YYPARSE_PARAM); #else int lp_yyparse (); #endif #else /* ! YYPARSE_PARAM */ #if defined __STDC__ || defined __cplusplus int lp_yyparse (parse_parm *parm, void *scanner); #else int lp_yyparse (); #endif #endif /* ! YYPARSE_PARAM */ /*----------. | lp_yyparse. | `----------*/ #ifdef YYPARSE_PARAM #if (defined __STDC__ || defined __C99__FUNC__ \ || defined __cplusplus || defined _MSC_VER) int lp_yyparse (void *YYPARSE_PARAM) #else int lp_yyparse (YYPARSE_PARAM) void *YYPARSE_PARAM; #endif #else /* ! YYPARSE_PARAM */ #if (defined __STDC__ || defined __C99__FUNC__ \ || defined __cplusplus || defined _MSC_VER) int lp_yyparse (parse_parm *parm, void *scanner) #else int lp_yyparse (parm, scanner) parse_parm *parm; void *scanner; #endif #endif { /* The look-ahead symbol. */ int lp_yychar; /* The semantic value of the look-ahead symbol. */ YYSTYPE lp_yylval; /* Number of syntax errors so far. */ int lp_yynerrs; int lp_yystate; int lp_yyn; int lp_yyresult; /* Number of tokens to shift before error messages enabled. */ int lp_yyerrstatus; /* Look-ahead token as an internal (translated) token number. */ int lp_yytoken = 0; #if YYERROR_VERBOSE /* Buffer for error messages, and its allocated size. */ char lp_yymsgbuf[128]; char *lp_yymsg = lp_yymsgbuf; YYSIZE_T lp_yymsg_alloc = sizeof lp_yymsgbuf; #endif /* Three stacks and their tools: `lp_yyss': related to states, `lp_yyvs': related to semantic values, `lp_yyls': related to locations. Refer to the stacks thru separate pointers, to allow lp_yyoverflow to reallocate them elsewhere. */ /* The state stack. */ lp_yytype_int16 lp_yyssa[YYINITDEPTH]; lp_yytype_int16 *lp_yyss = lp_yyssa; lp_yytype_int16 *lp_yyssp; /* The semantic value stack. */ YYSTYPE lp_yyvsa[YYINITDEPTH]; YYSTYPE *lp_yyvs = lp_yyvsa; YYSTYPE *lp_yyvsp; #define YYPOPSTACK(N) (lp_yyvsp -= (N), lp_yyssp -= (N)) YYSIZE_T lp_yystacksize = YYINITDEPTH; /* The variables used to return semantic value and location from the action routines. */ YYSTYPE lp_yyval; /* The number of symbols on the RHS of the reduced rule. Keep to zero when no symbol should be popped. */ int lp_yylen = 0; YYDPRINTF ((stderr, "Starting parse\n")); lp_yystate = 0; lp_yyerrstatus = 0; lp_yynerrs = 0; lp_yychar = YYEMPTY; /* Cause a token to be read. */ /* Initialize stack pointers. Waste one element of value and location stack so that they stay on the same level as the state stack. The wasted elements are never initialized. */ lp_yyssp = lp_yyss; lp_yyvsp = lp_yyvs; goto lp_yysetstate; /*------------------------------------------------------------. | lp_yynewstate -- Push a new state, which is found in lp_yystate. | `------------------------------------------------------------*/ lp_yynewstate: /* In all cases, when you get here, the value and location stacks have just been pushed. So pushing a state here evens the stacks. */ lp_yyssp++; lp_yysetstate: *lp_yyssp = lp_yystate; if (lp_yyss + lp_yystacksize - 1 <= lp_yyssp) { /* Get the current used size of the three stacks, in elements. */ YYSIZE_T lp_yysize = lp_yyssp - lp_yyss + 1; #ifdef lp_yyoverflow { /* Give user a chance to reallocate the stack. Use copies of these so that the &'s don't force the real ones into memory. */ YYSTYPE *lp_yyvs1 = lp_yyvs; lp_yytype_int16 *lp_yyss1 = lp_yyss; /* Each stack pointer address is followed by the size of the data in use in that stack, in bytes. This used to be a conditional around just the two extra args, but that might be undefined if lp_yyoverflow is a macro. */ lp_yyoverflow (YY_("memory exhausted"), &lp_yyss1, lp_yysize * sizeof (*lp_yyssp), &lp_yyvs1, lp_yysize * sizeof (*lp_yyvsp), &lp_yystacksize); lp_yyss = lp_yyss1; lp_yyvs = lp_yyvs1; } #else /* no lp_yyoverflow */ # ifndef YYSTACK_RELOCATE goto lp_yyexhaustedlab; # else /* Extend the stack our own way. */ if (YYMAXDEPTH <= lp_yystacksize) goto lp_yyexhaustedlab; lp_yystacksize *= 2; if (YYMAXDEPTH < lp_yystacksize) lp_yystacksize = YYMAXDEPTH; { lp_yytype_int16 *lp_yyss1 = lp_yyss; union lp_yyalloc *lp_yyptr = (union lp_yyalloc *) YYSTACK_ALLOC (YYSTACK_BYTES (lp_yystacksize)); if (! lp_yyptr) goto lp_yyexhaustedlab; YYSTACK_RELOCATE (lp_yyss); YYSTACK_RELOCATE (lp_yyvs); # undef YYSTACK_RELOCATE if (lp_yyss1 != lp_yyssa) YYSTACK_FREE (lp_yyss1); } # endif #endif /* no lp_yyoverflow */ lp_yyssp = lp_yyss + lp_yysize - 1; lp_yyvsp = lp_yyvs + lp_yysize - 1; YYDPRINTF ((stderr, "Stack size increased to %lu\n", (unsigned long int) lp_yystacksize)); if (lp_yyss + lp_yystacksize - 1 <= lp_yyssp) YYABORT; } YYDPRINTF ((stderr, "Entering state %d\n", lp_yystate)); goto lp_yybackup; /*-----------. | lp_yybackup. | `-----------*/ lp_yybackup: /* Do appropriate processing given the current state. Read a look-ahead token if we need one and don't already have one. */ /* First try to decide what to do without reference to look-ahead token. */ lp_yyn = lp_yypact[lp_yystate]; if (lp_yyn == YYPACT_NINF) goto lp_yydefault; /* Not known => get a look-ahead token if don't already have one. */ /* YYCHAR is either YYEMPTY or YYEOF or a valid look-ahead symbol. */ if (lp_yychar == YYEMPTY) { YYDPRINTF ((stderr, "Reading a token: ")); lp_yychar = YYLEX; } if (lp_yychar <= YYEOF) { lp_yychar = lp_yytoken = YYEOF; YYDPRINTF ((stderr, "Now at end of input.\n")); } else { lp_yytoken = YYTRANSLATE (lp_yychar); YY_SYMBOL_PRINT ("Next token is", lp_yytoken, &lp_yylval, &lp_yylloc); } /* If the proper action on seeing token YYTOKEN is to reduce or to detect an error, take that action. */ lp_yyn += lp_yytoken; if (lp_yyn < 0 || YYLAST < lp_yyn || lp_yycheck[lp_yyn] != lp_yytoken) goto lp_yydefault; lp_yyn = lp_yytable[lp_yyn]; if (lp_yyn <= 0) { if (lp_yyn == 0 || lp_yyn == YYTABLE_NINF) goto lp_yyerrlab; lp_yyn = -lp_yyn; goto lp_yyreduce; } if (lp_yyn == YYFINAL) YYACCEPT; /* Count tokens shifted since error; after three, turn off error status. */ if (lp_yyerrstatus) lp_yyerrstatus--; /* Shift the look-ahead token. */ YY_SYMBOL_PRINT ("Shifting", lp_yytoken, &lp_yylval, &lp_yylloc); /* Discard the shifted token unless it is eof. */ if (lp_yychar != YYEOF) lp_yychar = YYEMPTY; lp_yystate = lp_yyn; *++lp_yyvsp = lp_yylval; goto lp_yynewstate; /*-----------------------------------------------------------. | lp_yydefault -- do the default action for the current state. | `-----------------------------------------------------------*/ lp_yydefault: lp_yyn = lp_yydefact[lp_yystate]; if (lp_yyn == 0) goto lp_yyerrlab; goto lp_yyreduce; /*-----------------------------. | lp_yyreduce -- Do a reduction. | `-----------------------------*/ lp_yyreduce: /* lp_yyn is the number of a rule to reduce with. */ lp_yylen = lp_yyr2[lp_yyn]; /* If YYLEN is nonzero, implement the default value of the action: `$$ = $1'. Otherwise, the following line sets YYVAL to garbage. This behavior is undocumented and Bison users should not rely upon it. Assigning to YYVAL unconditionally makes the parser a bit smaller, and it avoids a GCC warning that YYVAL may be used uninitialized. */ lp_yyval = lp_yyvsp[1-lp_yylen]; YY_REDUCE_PRINT (lp_yyn); switch (lp_yyn) { case 3: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->isign = 0; pv->make_neg = 0; pv->Sign = 0; pv->HadConstraint = FALSE; pv->HadVar = pv->HadVar0 = FALSE; } break; case 5: { set_obj_dir(PARM, TRUE); } break; case 6: { set_obj_dir(PARM, FALSE); } break; case 8: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; add_row(pp); pv->HadConstraint = FALSE; pv->HadVar = pv->HadVar0 = FALSE; pv->isign = 0; pv->make_neg = 0; } break; case 16: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if(!add_constraint_name(pp, pv->Last_var)) YYABORT; pv->HadConstraint = TRUE; } break; case 18: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->HadVar1 = pv->HadVar0; pv->HadVar0 = FALSE; } break; case 19: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if(!store_re_op(pp, pv->OP, (int) pv->HadConstraint, (int) pv->HadVar, (int) pv->Had_lineair_sum)) YYABORT; pv->make_neg = 1; pv->f1 = 0; } break; case 20: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->Had_lineair_sum0 = pv->Had_lineair_sum; pv->Had_lineair_sum = TRUE; pv->HadVar2 = pv->HadVar0; pv->HadVar0 = FALSE; pv->do_add_row = FALSE; if(pv->HadConstraint && !pv->HadVar ) { /* it is a range */ /* already handled */ } else if(!pv->HadConstraint && pv->HadVar) { /* it is a bound */ if(!store_bounds(pp, TRUE)) YYABORT; } else { /* it is a row restriction */ if(pv->HadConstraint && pv->HadVar) store_re_op(pp, '\0', (int) pv->HadConstraint, (int) pv->HadVar, (int) pv->Had_lineair_sum); /* makes sure that data stored in temporary buffers is treated correctly */ pv->do_add_row = TRUE; } } break; case 21: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if((!pv->HadVar) && (!pv->HadConstraint)) { lp_yyerror(pp, pp->scanner, "parse error"); YYABORT; } if(pv->do_add_row) add_row(pp); pv->HadConstraint = FALSE; pv->HadVar = pv->HadVar0 = FALSE; pv->isign = 0; pv->make_neg = 0; null_tmp_store(pp, TRUE); } break; case 22: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if((!pv->HadVar1) && (pv->Had_lineair_sum0)) if(!negate_constraint(pp)) YYABORT; } break; case 23: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->make_neg = 0; pv->isign = 0; if(pv->HadConstraint) pv->HadVar = pv->Had_lineair_sum = FALSE; pv->HadVar0 = FALSE; if(!store_re_op(pp, (char) ((pv->OP == '<') ? '>' : (pv->OP == '>') ? '<' : pv->OP), (int) pv->HadConstraint, (int) pv->HadVar, (int) pv->Had_lineair_sum)) YYABORT; } break; case 24: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->f -= pv->f1; } break; case 25: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if((pv->HadVar1) || (!pv->HadVar2) || (pv->HadVar0)) { lp_yyerror(pp, pp->scanner, "parse error"); YYABORT; } if(pv->HadConstraint && !pv->HadVar ) { /* it is a range */ /* already handled */ if(!negate_constraint(pp)) YYABORT; } else if(!pv->HadConstraint && pv->HadVar) { /* it is a bound */ if(!store_bounds(pp, TRUE)) YYABORT; } } break; case 26: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; /* to allow a range */ /* constraint: < max */ if(!pv->HadConstraint) { lp_yyerror(pp, pp->scanner, "parse error"); YYABORT; } pv->Had_lineair_sum = FALSE; } break; case 27: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->Had_lineair_sum = TRUE; } break; case 29: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->isign = pv->Sign; } break; case 31: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->state = pv->state0 = 0; } break; case 32: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if (pv->state == 1) { /* RHS_STORE */ if ( (pv->isign0 || !pv->make_neg) && !(pv->isign0 && !pv->make_neg)) /* but not both! */ pv->f0 = -pv->f0; if(pv->make_neg) pv->f1 += pv->f0; if(!rhs_store(pp, pv->f0, (int) pv->HadConstraint, (int) pv->HadVar, (int) pv->Had_lineair_sum)) YYABORT; } } break; case 35: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if ((pv->HadSign || pv->state == 1) && (pv->state0 == 1)) { /* RHS_STORE */ if ( (pv->isign0 || !pv->make_neg) && !(pv->isign0 && !pv->make_neg)) /* but not both! */ pv->f0 = -pv->f0; if(pv->make_neg) pv->f1 += pv->f0; if(!rhs_store(pp, pv->f0, (int) pv->HadConstraint, (int) pv->HadVar, (int) pv->Had_lineair_sum)) YYABORT; } if (pv->state == 1) { pv->f0 = pv->f; pv->isign0 = pv->isign; } if (pv->state == 2) { if((pv->HadSign) || (pv->state0 != 1)) { pv->isign0 = pv->isign; pv->f0 = 1.0; } if ( (pv->isign0 || pv->make_neg) && !(pv->isign0 && pv->make_neg)) /* but not both! */ pv->f0 = -pv->f0; if(!var_store(pp, pv->Last_var, pv->f0, (int) pv->HadConstraint, (int) pv->HadVar, (int) pv->Had_lineair_sum)) { lp_yyerror(pp, pp->scanner, "var_store failed"); YYABORT; } pv->HadConstraint |= pv->HadVar; pv->HadVar = pv->HadVar0 = TRUE; } pv->state0 = pv->state; } break; case 36: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->state = 1; } break; case 37: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if ((pv->HasAR_M_OP) && (pv->state != 1)) { lp_yyerror(pp, pp->scanner, "parse error"); YYABORT; } } break; case 38: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->state = 2; } break; case 43: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->isign = pv->Sign; } break; case 46: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->isign = 0; pv->HadSign = FALSE; } break; case 47: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->isign = pv->Sign; pv->HadSign = TRUE; } break; case 48: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->HasAR_M_OP = FALSE; } break; case 49: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->HasAR_M_OP = TRUE; } break; case 50: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if ( (pv->isign || !pv->make_neg) && !(pv->isign && !pv->make_neg)) /* but not both! */ pv->f = -pv->f; if(!rhs_store(pp, pv->f, (int) pv->HadConstraint, (int) pv->HadVar, (int) pv->Had_lineair_sum)) YYABORT; pv->isign = 0; } break; case 60: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pv->Within_sos_decl1 = pv->Within_sos_decl; } break; case 62: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if((!pv->Within_int_decl) && (!pv->Within_sec_decl) && (!pv->Within_sos_decl1) && (!pv->Within_free_decl)) { lp_yyerror(pp, pp->scanner, "parse error"); YYABORT; } pv->SOStype = pv->SOStype0; check_int_sec_sos_free_decl(pp, (int) pv->Within_int_decl, (int) pv->Within_sec_decl, (int) (pv->Within_sos_decl1 = (pv->Within_sos_decl1 ? 1 : 0)), (int) pv->Within_free_decl); } break; case 63: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if((pv->Within_sos_decl1) && (pv->SOStype == 0)) { lp_yyerror(pp, pp->scanner, "Unsupported SOS type (0)"); YYABORT; } } break; case 67: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; FREE(pv->Last_var0); pv->Last_var0 = strdup(pv->Last_var); } break; case 69: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if(pv->Within_sos_decl1) { set_sos_type(pp, pv->SOStype); set_sos_weight(pp, (double) pv->SOSweight, 1); } } break; case 70: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if((pv->Within_sos_decl1) && (!pv->SOStype)) { set_sos_type(pp, pv->SOStype = (short) (pv->f + .1)); } else { lp_yyerror(pp, pp->scanner, "SOS type not expected"); YYABORT; } } break; case 72: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; set_sos_weight(pp, (double) pv->SOSweight, 1); } break; case 73: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; set_sos_weight(pp, pv->f, 1); } break; case 80: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if(pv->Within_sos_decl1 == 1) { char buf[16]; pv->SOSweight++; sprintf(buf, "SOS%d", pv->SOSweight); storevarandweight(pp, buf); check_int_sec_sos_free_decl(pp, (int) pv->Within_int_decl, (int) pv->Within_sec_decl, 2, (int) pv->Within_free_decl); pv->Within_sos_decl1 = 2; pv->SOSNr = 0; } storevarandweight(pp, pv->Last_var); if(pv->Within_sos_decl1 == 2) { pv->SOSNr++; set_sos_weight(pp, (double) pv->SOSNr, 2); } } break; case 81: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if(!pv->Within_sos_decl1) { lp_yyerror(pp, pp->scanner, "parse error"); YYABORT; } if(pv->Within_sos_decl1 == 1) { FREE(pv->Last_var0); pv->Last_var0 = strdup(pv->Last_var); } if(pv->Within_sos_decl1 == 2) { storevarandweight(pp, pv->Last_var); pv->SOSNr++; set_sos_weight(pp, (double) pv->SOSNr, 2); } } break; case 82: { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if(pv->Within_sos_decl1 == 1) { char buf[16]; pv->SOSweight++; sprintf(buf, "SOS%d", pv->SOSweight); storevarandweight(pp, buf); check_int_sec_sos_free_decl(pp, (int) pv->Within_int_decl, (int) pv->Within_sec_decl, 2, (int) pv->Within_free_decl); pv->Within_sos_decl1 = 2; pv->SOSNr = 0; storevarandweight(pp, pv->Last_var0); pv->SOSNr++; } set_sos_weight(pp, pv->f, 2); } break; case 83: { /* SOS name */ parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; if(pv->Within_sos_decl1 == 1) { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; storevarandweight(pp, pv->Last_var0); set_sos_type(pp, pv->SOStype); check_int_sec_sos_free_decl(pp, (int) pv->Within_int_decl, (int) pv->Within_sec_decl, 2, (int) pv->Within_free_decl); pv->Within_sos_decl1 = 2; pv->SOSNr = 0; pv->SOSweight++; } } break; /* Line 1267 of yacc.c. */ default: break; } YY_SYMBOL_PRINT ("-> $$ =", lp_yyr1[lp_yyn], &lp_yyval, &lp_yyloc); YYPOPSTACK (lp_yylen); lp_yylen = 0; YY_STACK_PRINT (lp_yyss, lp_yyssp); *++lp_yyvsp = lp_yyval; /* Now `shift' the result of the reduction. Determine what state that goes to, based on the state we popped back to and the rule number reduced by. */ lp_yyn = lp_yyr1[lp_yyn]; lp_yystate = lp_yypgoto[lp_yyn - YYNTOKENS] + *lp_yyssp; if (0 <= lp_yystate && lp_yystate <= YYLAST && lp_yycheck[lp_yystate] == *lp_yyssp) lp_yystate = lp_yytable[lp_yystate]; else lp_yystate = lp_yydefgoto[lp_yyn - YYNTOKENS]; goto lp_yynewstate; /*------------------------------------. | lp_yyerrlab -- here on detecting error | `------------------------------------*/ lp_yyerrlab: /* If not already recovering from an error, report this error. */ if (!lp_yyerrstatus) { ++lp_yynerrs; #if ! YYERROR_VERBOSE lp_yyerror (parm, scanner, YY_("syntax error")); #else { YYSIZE_T lp_yysize = lp_yysyntax_error (0, lp_yystate, lp_yychar); if (lp_yymsg_alloc < lp_yysize && lp_yymsg_alloc < YYSTACK_ALLOC_MAXIMUM) { YYSIZE_T lp_yyalloc = 2 * lp_yysize; if (! (lp_yysize <= lp_yyalloc && lp_yyalloc <= YYSTACK_ALLOC_MAXIMUM)) lp_yyalloc = YYSTACK_ALLOC_MAXIMUM; if (lp_yymsg != lp_yymsgbuf) YYSTACK_FREE (lp_yymsg); lp_yymsg = (char *) YYSTACK_ALLOC (lp_yyalloc); if (lp_yymsg) lp_yymsg_alloc = lp_yyalloc; else { lp_yymsg = lp_yymsgbuf; lp_yymsg_alloc = sizeof lp_yymsgbuf; } } if (0 < lp_yysize && lp_yysize <= lp_yymsg_alloc) { (void) lp_yysyntax_error (lp_yymsg, lp_yystate, lp_yychar); lp_yyerror (parm, scanner, lp_yymsg); } else { lp_yyerror (parm, scanner, YY_("syntax error")); if (lp_yysize != 0) goto lp_yyexhaustedlab; } } #endif } if (lp_yyerrstatus == 3) { /* If just tried and failed to reuse look-ahead token after an error, discard it. */ if (lp_yychar <= YYEOF) { /* Return failure if at end of input. */ if (lp_yychar == YYEOF) YYABORT; } else { lp_yydestruct ("Error: discarding", lp_yytoken, &lp_yylval, parm, scanner); lp_yychar = YYEMPTY; } } /* Else will try to reuse look-ahead token after shifting the error token. */ goto lp_yyerrlab1; /*---------------------------------------------------. | lp_yyerrorlab -- error raised explicitly by YYERROR. | `---------------------------------------------------*/ lp_yyerrorlab: /* Pacify compilers like GCC when the user code never invokes YYERROR and the label lp_yyerrorlab therefore never appears in user code. */ if (/*CONSTCOND*/ 0) goto lp_yyerrorlab; /* Do not reclaim the symbols of the rule which action triggered this YYERROR. */ YYPOPSTACK (lp_yylen); lp_yylen = 0; YY_STACK_PRINT (lp_yyss, lp_yyssp); lp_yystate = *lp_yyssp; goto lp_yyerrlab1; /*-------------------------------------------------------------. | lp_yyerrlab1 -- common code for both syntax error and YYERROR. | `-------------------------------------------------------------*/ lp_yyerrlab1: lp_yyerrstatus = 3; /* Each real token shifted decrements this. */ for (;;) { lp_yyn = lp_yypact[lp_yystate]; if (lp_yyn != YYPACT_NINF) { lp_yyn += YYTERROR; if (0 <= lp_yyn && lp_yyn <= YYLAST && lp_yycheck[lp_yyn] == YYTERROR) { lp_yyn = lp_yytable[lp_yyn]; if (0 < lp_yyn) break; } } /* Pop the current state because it cannot handle the error token. */ if (lp_yyssp == lp_yyss) YYABORT; lp_yydestruct ("Error: popping", lp_yystos[lp_yystate], lp_yyvsp, parm, scanner); YYPOPSTACK (1); lp_yystate = *lp_yyssp; YY_STACK_PRINT (lp_yyss, lp_yyssp); } if (lp_yyn == YYFINAL) YYACCEPT; *++lp_yyvsp = lp_yylval; /* Shift the error token. */ YY_SYMBOL_PRINT ("Shifting", lp_yystos[lp_yyn], lp_yyvsp, lp_yylsp); lp_yystate = lp_yyn; goto lp_yynewstate; /*-------------------------------------. | lp_yyacceptlab -- YYACCEPT comes here. | `-------------------------------------*/ lp_yyacceptlab: lp_yyresult = 0; goto lp_yyreturn; /*-----------------------------------. | lp_yyabortlab -- YYABORT comes here. | `-----------------------------------*/ lp_yyabortlab: lp_yyresult = 1; goto lp_yyreturn; #ifndef lp_yyoverflow /*-------------------------------------------------. | lp_yyexhaustedlab -- memory exhaustion comes here. | `-------------------------------------------------*/ lp_yyexhaustedlab: lp_yyerror (parm, scanner, YY_("memory exhausted")); lp_yyresult = 2; /* Fall through. */ #endif lp_yyreturn: if (lp_yychar != YYEOF && lp_yychar != YYEMPTY) lp_yydestruct ("Cleanup: discarding lookahead", lp_yytoken, &lp_yylval, parm, scanner); /* Do not reclaim the symbols of the rule which action triggered this YYABORT or YYACCEPT. */ YYPOPSTACK (lp_yylen); YY_STACK_PRINT (lp_yyss, lp_yyssp); while (lp_yyssp != lp_yyss) { lp_yydestruct ("Cleanup: popping", lp_yystos[*lp_yyssp], lp_yyvsp, parm, scanner); YYPOPSTACK (1); } #ifndef lp_yyoverflow if (lp_yyss != lp_yyssa) YYSTACK_FREE (lp_yyss); #endif #if YYERROR_VERBOSE if (lp_yymsg != lp_yymsgbuf) YYSTACK_FREE (lp_yymsg); #endif /* Make sure YYID is used. */ return YYID (lp_yyresult); } static void lp_yy_delete_allocated_memory(parse_parm *pp) { parse_vars *pv = (parse_vars *) pp->parse_vars; /* free memory allocated by flex. Otherwise some memory is not freed. This is a bit tricky. There is not much documentation about this, but a lot of reports of memory that keeps allocated */ /* If you get errors on this function call, just comment it. This will only result in some memory that is not being freed. */ # if defined YY_CURRENT_BUFFER /* flex defines the macro YY_CURRENT_BUFFER, so you should only get here if lp_rlp.h is generated by flex */ /* lex doesn't define this macro and thus should not come here, but lex doesn't has this memory leak also ...*/ # if 0 /* older versions of flex */ lp_yy_delete_buffer(YY_CURRENT_BUFFER); /* comment this line if you have problems with it */ lp_yy_init = 1; /* make sure that the next time memory is allocated again */ lp_yy_start = 0; # else /* As of version 2.5.9 Flex */ lp_yylex_destroy(pp->scanner); /* comment this line if you have problems with it */ # endif # endif FREE(pv->Last_var); FREE(pv->Last_var0); } static int parse(parse_parm *pp) { return(lp_yyparse(pp, pp->scanner)); } lprec *read_lp1(lprec *lp, void *userhandle, read_modeldata_func read_modeldata, int verbose, char *lp_name) { parse_vars *pv; lprec *lp1 = NULL; CALLOC(pv, 1, parse_vars); if (pv != NULL) { parse_parm pp; memset(&pp, 0, sizeof(pp)); pp.parse_vars = (void *) pv; lp_yylex_init(&pp.scanner); lp_yyset_extra(&pp, pp.scanner); lp_yyset_in((FILE *) userhandle, pp.scanner); lp_yyset_out(NULL, pp.scanner); pv->lp_input = read_modeldata; pv->userhandle = userhandle; lp1 = yacc_read(lp, verbose, lp_name, parse, &pp, lp_yy_delete_allocated_memory); FREE(pv); } return(lp1); } lprec * __WINAPI read_lp(FILE *filename, int verbose, char *lp_name) { return(read_lp1(NULL, filename, lp_input_lp_yyin, verbose, lp_name)); } lprec * __WINAPI read_lpex(void *userhandle, read_modeldata_func read_modeldata, int verbose, char *lp_name) { return(read_lp1(NULL, userhandle, read_modeldata, verbose, lp_name)); } lprec *read_LP1(lprec *lp, char *filename, int verbose, char *lp_name) { FILE *fpin; if((fpin = fopen(filename, "r")) != NULL) { lp = read_lp1(lp, fpin, lp_input_lp_yyin, verbose, lp_name); fclose(fpin); } else lp = NULL; return(lp); } lprec * __WINAPI read_LP(char *filename, int verbose, char *lp_name) { return(read_LP1(NULL, filename, verbose, lp_name)); } MYBOOL __WINAPI LP_readhandle(lprec **lp, FILE *filename, int verbose, char *lp_name) { if(lp != NULL) *lp = read_lp1(*lp, filename, lp_input_lp_yyin, verbose, lp_name); return((lp != NULL) && (*lp != NULL)); } MSVMpack1.2/lp_solve_5.5/ufortify.h0000664000175000017500000000343611141374260016163 0ustar lauerlauer/* * FILE: * ufortify.h * * DESCRIPTION: * User options for fortify. Changes to this file require fortify.c to be * recompiled, but nothing else. */ #ifndef __UFORTIFY_H__ #define __UFORTIFY_H__ #define FORTIFY_STORAGE #if defined MSDOS || defined __BORLANDC__ || defined __HIGHC__ # define KNOWS_POINTER_TYPE #endif #define FORTIFY_WAIT_FOR_KEY /* Pause after message */ #if !defined FORTIFY_BEFORE_SIZE # define FORTIFY_BEFORE_SIZE 16 /* Bytes to allocate before block */ #endif #if !defined FORTIFY_BEFORE_VALUE # define FORTIFY_BEFORE_VALUE 0xA3 /* Fill value before block */ #endif #if !defined FORTIFY_AFTER_SIZE # define FORTIFY_AFTER_SIZE 16 /* Bytes to allocate after block */ #endif #if !defined FORTIFY_AFTER_VALUE # define FORTIFY_AFTER_VALUE 0xA5 /* Fill value after block */ #endif #define FILL_ON_MALLOC /* Nuke out malloc'd memory */ #if !defined FILL_ON_MALLOC_VALUE # define FILL_ON_MALLOC_VALUE 0xA7 /* Value to initialize with */ #endif #define FILL_ON_FREE /* free'd memory is cleared */ #if !defined FILL_ON_FREE_VALUE # define FILL_ON_FREE_VALUE 0xA9 /* Value to de-initialize with */ #endif #define FORTIFY_CheckInterval 1 /* seconds */ /* #define CHECK_ALL_MEMORY_ON_MALLOC */ #define CHECK_ALL_MEMORY_ON_FREE #define PARANOID_FREE #define WARN_ON_MALLOC_FAIL /* A debug is issued on a failed malloc */ #define WARN_ON_ZERO_MALLOC /* A debug is issued on a malloc(0) */ #define WARN_ON_FALSE_FAIL /* See Fortify_SetMallocFailRate */ #define WARN_ON_SIZE_T_OVERFLOW/* Watch for breaking the 64K limit in */ /* some braindead architectures... */ #define FORTIFY_LOCK() #define FORTIFY_UNLOCK() #endif MSVMpack1.2/lp_solve_5.5/lp_report.c0000664000175000017500000006047011224160040016305 0ustar lauerlauer /* Mixed integer programming optimization drivers for lp_solve v5.0+ ---------------------------------------------------------------------------------- Author: Michel Berkelaar (to lp_solve v3.2), Kjell Eikland Contact: License terms: LGPL. Requires: stdarg.h, lp_lib.h Release notes: v5.0.0 3 1 January 2004 New unit isolating reporting routines. v5.2.0.0 1 December 2005 Addition of Matrix Market writing function. ---------------------------------------------------------------------------------- */ #include #include #include #include "lp_lib.h" #include "lp_scale.h" #include "commonlib.h" #include "lp_report.h" #include "mmio.h" #ifdef FORTIFY # include "lp_fortify.h" #endif /* Define buffer-size controled function mapping */ # if defined _MSC_VER # define vsnprintf _vsnprintf # endif /* Various reporting functions for lp_solve */ /* ------------------------------------------------------------------------- */ /* First define general utilties for reporting and output */ char * __VACALL explain(lprec *lp, char *format, ...) { char buff[DEF_STRBUFSIZE+1]; va_list ap; va_start(ap, format); vsnprintf(buff, DEF_STRBUFSIZE, format, ap); va_end(ap); allocCHAR(lp, &(lp->ex_status), (int) strlen(buff), AUTOMATIC); strcpy(lp->ex_status, buff); return( lp->ex_status ); } void __VACALL report(lprec *lp, int level, char *format, ...) { char buff[DEF_STRBUFSIZE+1]; va_list ap; if(lp == NULL) { va_start(ap, format); vfprintf(stderr, format, ap); va_end(ap); } else if(level <= lp->verbose) { if(lp->writelog != NULL) { va_start(ap, format); vsnprintf(buff, DEF_STRBUFSIZE, format, ap); va_end(ap); lp->writelog(lp, lp->loghandle, buff); } if(lp->outstream != NULL) { va_start(ap, format); vfprintf(lp->outstream, format, ap); va_end(ap); if(lp->outstream != stdout) fflush(lp->outstream); } } #ifdef xParanoia if(level == CRITICAL) raise(SIGSEGV); #endif } STATIC void print_indent(lprec *lp) { int i; report(lp, NEUTRAL, "%2d", lp->bb_level); if(lp->bb_level < 50) /* useless otherwise */ for(i = lp->bb_level; i > 0; i--) report(lp, NEUTRAL, "--"); else report(lp, NEUTRAL, " *** too deep ***"); report(lp, NEUTRAL, "> "); } /* print_indent */ STATIC void debug_print(lprec *lp, char *format, ...) { va_list ap; if(lp->bb_trace) { print_indent(lp); if (lp == NULL) { va_start(ap, format); vfprintf(stderr, format, ap); va_end(ap); fputc('\n', stderr); } else if(lp->debuginfo != NULL) { char buff[DEF_STRBUFSIZE+1]; va_start(ap, format); vsnprintf(buff, DEF_STRBUFSIZE, format, ap); va_end(ap); lp->debuginfo(lp, lp->loghandle, buff); } } } /* debug_print */ STATIC void debug_print_solution(lprec *lp) { int i; if(lp->bb_trace) for (i = lp->rows + 1; i <= lp->sum; i++) { print_indent(lp); report(lp, NEUTRAL, "%s " RESULTVALUEMASK "\n", get_col_name(lp, i - lp->rows), (double)lp->solution[i]); } } /* debug_print_solution */ STATIC void debug_print_bounds(lprec *lp, REAL *upbo, REAL *lowbo) { int i; if(lp->bb_trace) for(i = lp->rows + 1; i <= lp->sum; i++) { if(lowbo[i] == upbo[i]) { print_indent(lp); report(lp, NEUTRAL, "%s = " RESULTVALUEMASK "\n", get_col_name(lp, i - lp->rows), (double)lowbo[i]); } else { if(lowbo[i] != 0) { print_indent(lp); report(lp, NEUTRAL, "%s > " RESULTVALUEMASK "\n", get_col_name(lp, i - lp->rows), (double)lowbo[i]); } if(upbo[i] != lp->infinite) { print_indent(lp); report(lp, NEUTRAL, "%s < " RESULTVALUEMASK "\n", get_col_name(lp, i - lp->rows), (double)upbo[i]); } } } } /* debug_print_bounds */ /* List a vector of LREAL values for the given index range */ void blockWriteLREAL(FILE *output, char *label, LREAL *vector, int first, int last) { int i, k = 0; fprintf(output, "%s", label); fprintf(output, "\n"); for(i = first; i <= last; i++) { fprintf(output, " %18g", vector[i]); k++; if(my_mod(k, 4) == 0) { fprintf(output, "\n"); k = 0; } } if(my_mod(k, 4) != 0) fprintf(output, "\n"); } /* List the current user data matrix columns over the selected row range */ void blockWriteAMAT(FILE *output, const char *label, lprec* lp, int first, int last) { int i, j, k = 0; int nzb, nze, jb; double hold; MATrec *mat = lp->matA; if(!mat_validate(mat)) return; if(first < 0) first = 0; if(last < 0) last = lp->rows; fprintf(output, "%s", label); fprintf(output, "\n"); if(first == 0) { for(j = 1; j <= lp->columns; j++) { hold = get_mat(lp, 0, j); fprintf(output, " %18g", hold); k++; if(my_mod(k, 4) == 0) { fprintf(output, "\n"); k = 0; } } if(my_mod(k, 4) != 0) { fprintf(output, "\n"); k = 0; } first++; } nze = mat->row_end[first-1]; for(i = first; i <= last; i++) { nzb = nze; nze = mat->row_end[i]; if(nzb >= nze) jb = lp->columns+1; else jb = ROW_MAT_COLNR(nzb); for(j = 1; j <= lp->columns; j++) { if(j < jb) hold = 0; else { hold = get_mat(lp, i, j); nzb++; if(nzb < nze) jb = ROW_MAT_COLNR(nzb); else jb = lp->columns+1; } fprintf(output, " %18g", hold); k++; if(my_mod(k, 4) == 0) { fprintf(output, "\n"); k = 0; } } if(my_mod(k, 4) != 0) { fprintf(output, "\n"); k = 0; } } if(my_mod(k, 4) != 0) fprintf(output, "\n"); } /* List the current basis matrix columns over the selected row range */ void blockWriteBMAT(FILE *output, const char *label, lprec* lp, int first, int last) { int i, j, jb, k = 0; double hold; if(first < 0) first = 0; if(last < 0) last = lp->rows; fprintf(output, "%s", label); fprintf(output, "\n"); for(i = first; i <= last; i++) { for(j = 1; j <= lp->rows; j++) { jb = lp->var_basic[j]; if(jb <= lp->rows) { if(jb == i) hold = 1; else hold = 0; } else hold = get_mat(lp, i, j); if(i == 0) modifyOF1(lp, jb, &hold, 1); hold = unscaled_mat(lp, hold, i, jb); fprintf(output, " %18g", hold); k++; if(my_mod(k, 4) == 0) { fprintf(output, "\n"); k = 0; } } if(my_mod(k, 4) != 0) { fprintf(output, "\n"); k = 0; } } if(my_mod(k, 4) != 0) fprintf(output, "\n"); } /* Do a generic readable data dump of key lp_solve model variables; principally for run difference and debugging purposes */ MYBOOL REPORT_debugdump(lprec *lp, char *filename, MYBOOL livedata) { FILE *output = stdout; MYBOOL ok; ok = (MYBOOL) ((filename == NULL) || ((output = fopen(filename,"w")) != NULL)); if(!ok) return(ok); if((filename == NULL) && (lp->outstream != NULL)) output = lp->outstream; fprintf(output, "\nGENERAL INFORMATION\n-------------------\n\n"); fprintf(output, "Model size: %d rows (%d equalities, %d Lagrangean), %d columns (%d integers, %d SC, %d SOS, %d GUB)\n", lp->rows, lp->equalities, get_Lrows(lp), lp->columns, lp->int_vars, lp->sc_vars, SOS_count(lp), GUB_count(lp)); fprintf(output, "Data size: %d model non-zeros, %d invB non-zeros (engine is %s)\n", get_nonzeros(lp), my_if(lp->invB == NULL, 0, lp->bfp_nonzeros(lp, FALSE)), lp->bfp_name()); fprintf(output, "Internal sizes: %d rows allocated, %d columns allocated, %d columns used, %d eta length\n", lp->rows_alloc, lp->columns_alloc, lp->columns, my_if(lp->invB == NULL, 0, lp->bfp_colcount(lp))); fprintf(output, "Memory use: %d sparse matrix, %d eta\n", lp->matA->mat_alloc, my_if(lp->invB == NULL, 0, lp->bfp_memallocated(lp))); fprintf(output, "Parameters: Maximize=%d, Names used=%d, Scalingmode=%d, Presolve=%d, SimplexPivot=%d\n", is_maxim(lp), lp->names_used, lp->scalemode, lp->do_presolve, lp->piv_strategy); fprintf(output, "Precision: EpsValue=%g, EpsPrimal=%g, EpsDual=%g, EpsPivot=%g, EpsPerturb=%g\n", lp->epsvalue, lp->epsprimal, lp->epsdual, lp->epspivot, lp->epsperturb); fprintf(output, "Stability: AntiDegen=%d, Improvement=%d, Split variables at=%g\n", lp->improve, lp->anti_degen, lp->negrange); fprintf(output, "B&B settings: BB pivot rule=%d, BB branching=%s, BB strategy=%d, Integer precision=%g, MIP gaps=%g,%g\n", lp->bb_rule, my_boolstr(lp->bb_varbranch), lp->bb_floorfirst, lp->epsint, lp->mip_absgap, lp->mip_relgap); fprintf(output, "\nCORE DATA\n---------\n\n"); blockWriteINT(output, "Column starts", lp->matA->col_end, 0, lp->columns); blockWriteINT(output, "row_type", lp->row_type, 0, lp->rows); blockWriteREAL(output, "orig_rhs", lp->orig_rhs, 0, lp->rows); blockWriteREAL(output, "orig_lowbo", lp->orig_lowbo, 0, lp->sum); blockWriteREAL(output, "orig_upbo", lp->orig_upbo, 0, lp->sum); blockWriteINT(output, "row_type", lp->row_type, 0, lp->rows); blockWriteBOOL(output, "var_type", lp->var_type, 0, lp->columns, TRUE); blockWriteAMAT(output, "A", lp, 0, lp->rows); if(livedata) { fprintf(output, "\nPROCESS DATA\n------------\n\n"); blockWriteREAL(output, "Active rhs", lp->rhs, 0, lp->rows); blockWriteINT(output, "Basic variables", lp->var_basic, 0, lp->rows); blockWriteBOOL(output, "is_basic", lp->is_basic, 0, lp->sum, TRUE); blockWriteREAL(output, "lowbo", lp->lowbo, 0, lp->sum); blockWriteREAL(output, "upbo", lp->upbo, 0, lp->sum); if(lp->scalars != NULL) blockWriteREAL(output, "scalars", lp->scalars, 0, lp->sum); } if(filename != NULL) fclose(output); return(ok); } /* High level reports for model results */ void REPORT_objective(lprec *lp) { if(lp->outstream == NULL) return; if(fabs(lp->best_solution[0]) < 1e-5) fprintf(lp->outstream, "\nValue of objective function: %g\n", (double)lp->best_solution[0]); else fprintf(lp->outstream, "\nValue of objective function: %.8f\n", (double)lp->best_solution[0]); fflush(lp->outstream); } void REPORT_solution(lprec *lp, int columns) { int i, j, n; REAL value; presolveundorec *psundo = lp->presolve_undo; MYBOOL NZonly = (MYBOOL) ((lp->print_sol & AUTOMATIC) > 0); if(lp->outstream == NULL) return; fprintf(lp->outstream, "\nActual values of the variables:\n"); if(columns <= 0) columns = 2; n = 0; for(i = 1; i <= psundo->orig_columns; i++) { j = psundo->orig_rows + i; value = get_var_primalresult(lp, j); if(NZonly && (fabs(value) < lp->epsprimal)) continue; n = (n+1) % columns; fprintf(lp->outstream, "%-20s %12g", get_origcol_name(lp, i), (double) value); if(n == 0) fprintf(lp->outstream, "\n"); else fprintf(lp->outstream, " "); } fflush(lp->outstream); } /* REPORT_solution */ void REPORT_constraints(lprec *lp, int columns) { int i, n; REAL value; MYBOOL NZonly = (MYBOOL) ((lp->print_sol & AUTOMATIC) > 0); if(lp->outstream == NULL) return; if(columns <= 0) columns = 2; fprintf(lp->outstream, "\nActual values of the constraints:\n"); n = 0; for(i = 1; i <= lp->rows; i++) { value = (double)lp->best_solution[i]; if(NZonly && (fabs(value) < lp->epsprimal)) continue; n = (n+1) % columns; fprintf(lp->outstream, "%-20s %12g", get_row_name(lp, i), value); if(n == 0) fprintf(lp->outstream, "\n"); else fprintf(lp->outstream, " "); } fflush(lp->outstream); } void REPORT_duals(lprec *lp) { int i; REAL *duals, *dualsfrom, *dualstill, *objfrom, *objtill, *objfromvalue; MYBOOL ret; if(lp->outstream == NULL) return; ret = get_ptr_sensitivity_objex(lp, &objfrom, &objtill, &objfromvalue, NULL); if(ret) { fprintf(lp->outstream, "\nObjective function limits:\n"); fprintf(lp->outstream, " From Till FromValue\n"); for(i = 1; i <= lp->columns; i++) if(!is_splitvar(lp, i)) fprintf(lp->outstream, "%-20s %15.7g %15.7g %15.7g\n", get_col_name(lp, i), (double)objfrom[i - 1], (double)objtill[i - 1], (double)objfromvalue[i - 1]); } ret = get_ptr_sensitivity_rhs(lp, &duals, &dualsfrom, &dualstill); if(ret) { fprintf(lp->outstream, "\nDual values with from - till limits:\n"); fprintf(lp->outstream, " Dual value From Till\n"); for(i = 1; i <= lp->sum; i++) fprintf(lp->outstream, "%-20s %15.7g %15.7g %15.7g\n", (i <= lp->rows) ? get_row_name(lp, i) : get_col_name(lp, i - lp->rows), (double)duals[i - 1], (double)dualsfrom[i - 1], (double)dualstill[i - 1]); fflush(lp->outstream); } } /* Printing of sensitivity analysis reports */ void REPORT_extended(lprec *lp) { int i, j; REAL hold; REAL *duals, *dualsfrom, *dualstill, *objfrom, *objtill; MYBOOL ret; ret = get_ptr_sensitivity_obj(lp, &objfrom, &objtill); report(lp, NORMAL, " \n"); report(lp, NORMAL, "Primal objective:\n"); report(lp, NORMAL, " \n"); report(lp, NORMAL, " Column name Value Objective Min Max\n"); report(lp, NORMAL, " --------------------------------------------------------------------------\n"); for(j = 1; j <= lp->columns; j++) { hold = get_mat(lp,0,j); report(lp, NORMAL, " %-25s " MPSVALUEMASK MPSVALUEMASK MPSVALUEMASK MPSVALUEMASK "\n", get_col_name(lp,j), my_precision(hold,lp->epsprimal), my_precision(hold*lp->best_solution[lp->rows+j],lp->epsprimal), my_precision((ret) ? objfrom[j - 1] : 0.0,lp->epsprimal), my_precision((ret) ? objtill[j - 1] : 0.0,lp->epsprimal)); } report(lp, NORMAL, " \n"); ret = get_ptr_sensitivity_rhs(lp, &duals, &dualsfrom, &dualstill); report(lp, NORMAL, "Primal variables:\n"); report(lp, NORMAL, " \n"); report(lp, NORMAL, " Column name Value Slack Min Max\n"); report(lp, NORMAL, " --------------------------------------------------------------------------\n"); for(j = 1; j <= lp->columns; j++) report(lp, NORMAL, " %-25s " MPSVALUEMASK MPSVALUEMASK MPSVALUEMASK MPSVALUEMASK "\n", get_col_name(lp,j), my_precision(lp->best_solution[lp->rows+j],lp->epsprimal), my_precision(my_inflimit(lp, (ret) ? duals[lp->rows+j-1] : 0.0),lp->epsprimal), my_precision((ret) ? dualsfrom[lp->rows+j-1] : 0.0,lp->epsprimal), my_precision((ret) ? dualstill[lp->rows+j-1] : 0.0,lp->epsprimal)); report(lp, NORMAL, " \n"); report(lp, NORMAL, "Dual variables:\n"); report(lp, NORMAL, " \n"); report(lp, NORMAL, " Row name Value Slack Min Max\n"); report(lp, NORMAL, " --------------------------------------------------------------------------\n"); for(i = 1; i <= lp->rows; i++) report(lp, NORMAL, " %-25s " MPSVALUEMASK MPSVALUEMASK MPSVALUEMASK MPSVALUEMASK "\n", get_row_name(lp,i), my_precision((ret) ? duals[i - 1] : 0.0, lp->epsprimal), my_precision(lp->best_solution[i], lp->epsprimal), my_precision((ret) ? dualsfrom[i - 1] : 0.0,lp->epsprimal), my_precision((ret) ? dualstill[i - 1] : 0.0,lp->epsprimal)); report(lp, NORMAL, " \n"); } /* A more readable lp-format report of the model; antiquated and not updated */ void REPORT_lp(lprec *lp) { int i, j; if(lp->outstream == NULL) return; fprintf(lp->outstream, "Model name: %s\n", get_lp_name(lp)); fprintf(lp->outstream, " "); for(j = 1; j <= lp->columns; j++) fprintf(lp->outstream, "%8s ", get_col_name(lp,j)); fprintf(lp->outstream, "\n%simize ", (is_maxim(lp) ? "Max" : "Min")); for(j = 1; j <= lp->columns; j++) fprintf(lp->outstream, "%8g ", get_mat(lp, 0, j)); fprintf(lp->outstream, "\n"); for(i = 1; i <= lp->rows; i++) { fprintf(lp->outstream, "%-9s ", get_row_name(lp, i)); for(j = 1; j <= lp->columns; j++) fprintf(lp->outstream, "%8g ", get_mat(lp, i, j)); if(is_constr_type(lp, i, GE)) fprintf(lp->outstream, ">= "); else if(is_constr_type(lp, i, LE)) fprintf(lp->outstream, "<= "); else fprintf(lp->outstream, " = "); fprintf(lp->outstream, "%8g", get_rh(lp, i)); if(is_constr_type(lp, i, GE)) { if(get_rh_upper(lp, i) < lp->infinite) fprintf(lp->outstream, " %s = %8g", "upbo", get_rh_upper(lp, i)); } else if(is_constr_type(lp, i, LE)) { if(get_rh_lower(lp, i) > -lp->infinite) fprintf(lp->outstream, " %s = %8g", "lowbo", get_rh_lower(lp, i)); } fprintf(lp->outstream, "\n"); } fprintf(lp->outstream, "Type "); for(i = 1; i <= lp->columns; i++) { if(is_int(lp,i)) fprintf(lp->outstream, " Int "); else fprintf(lp->outstream, " Real "); } fprintf(lp->outstream, "\nupbo "); for(i = 1; i <= lp->columns; i++) if(get_upbo(lp, i) >= lp->infinite) fprintf(lp->outstream, " Inf "); else fprintf(lp->outstream, "%8g ", get_upbo(lp, i)); fprintf(lp->outstream, "\nlowbo "); for(i = 1; i <= lp->columns; i++) if(get_lowbo(lp, i) <= -lp->infinite) fprintf(lp->outstream, " -Inf "); else fprintf(lp->outstream, "%8g ", get_lowbo(lp, i)); fprintf(lp->outstream, "\n"); fflush(lp->outstream); } /* Report the scaling factors used; extremely rarely used */ void REPORT_scales(lprec *lp) { int i, colMax; colMax = lp->columns; if(lp->outstream == NULL) return; if(lp->scaling_used) { fprintf(lp->outstream, "\nScale factors:\n"); for(i = 0; i <= lp->rows + colMax; i++) fprintf(lp->outstream, "%-20s scaled at %g\n", (i <= lp->rows) ? get_row_name(lp, i) : get_col_name(lp, i - lp->rows), (double)lp->scalars[i]); } fflush(lp->outstream); } /* Report the traditional tableau corresponding to the current basis */ MYBOOL REPORT_tableau(lprec *lp) { int j, row_nr, *coltarget; REAL *prow = NULL; FILE *stream = lp->outstream; if(lp->outstream == NULL) return(FALSE); if(!lp->model_is_valid || !has_BFP(lp) || (get_total_iter(lp) == 0) || (lp->spx_status == NOTRUN)) { lp->spx_status = NOTRUN; return(FALSE); } if(!allocREAL(lp, &prow,lp->sum + 1, TRUE)) { lp->spx_status = NOMEMORY; return(FALSE); } fprintf(stream, "\n"); fprintf(stream, "Tableau at iter %.0f:\n", (double) get_total_iter(lp)); for(j = 1; j <= lp->sum; j++) if (!lp->is_basic[j]) fprintf(stream, "%15d", (j <= lp->rows ? (j + lp->columns) * ((lp->orig_upbo[j] == 0) || (is_chsign(lp, j)) ? 1 : -1) : j - lp->rows) * (lp->is_lower[j] ? 1 : -1)); fprintf(stream, "\n"); coltarget = (int *) mempool_obtainVector(lp->workarrays, lp->columns+1, sizeof(*coltarget)); if(!get_colIndexA(lp, SCAN_USERVARS+USE_NONBASICVARS, coltarget, FALSE)) { mempool_releaseVector(lp->workarrays, (char *) coltarget, FALSE); return(FALSE); } for(row_nr = 1; (row_nr <= lp->rows + 1); row_nr++) { if (row_nr <= lp->rows) fprintf(stream, "%3d", (lp->var_basic[row_nr] <= lp->rows ? (lp->var_basic[row_nr] + lp->columns) * ((lp->orig_upbo[lp->var_basic [row_nr]] == 0) || (is_chsign(lp, lp->var_basic[row_nr])) ? 1 : -1) : lp->var_basic[row_nr] - lp->rows) * (lp->is_lower[lp->var_basic [row_nr]] ? 1 : -1)); else fprintf(stream, " "); bsolve(lp, row_nr <= lp->rows ? row_nr : 0, prow, NULL, lp->epsmachine*DOUBLEROUND, 1.0); prod_xA(lp, coltarget, prow, NULL, lp->epsmachine, 1.0, prow, NULL, MAT_ROUNDDEFAULT); for(j = 1; j <= lp->rows + lp->columns; j++) if (!lp->is_basic[j]) fprintf(stream, "%15.7f", prow[j] * (lp->is_lower[j] ? 1 : -1) * (row_nr <= lp->rows ? 1 : -1)); fprintf(stream, "%15.7f", lp->rhs[row_nr <= lp->rows ? row_nr : 0] * (double) ((row_nr <= lp->rows) || (is_maxim(lp)) ? 1 : -1)); fprintf(stream, "\n"); } fflush(stream); mempool_releaseVector(lp->workarrays, (char *) coltarget, FALSE); FREE(prow); return(TRUE); } void REPORT_constraintinfo(lprec *lp, char *datainfo) { int i, tally[ROWCLASS_MAX+1]; MEMCLEAR(tally, ROWCLASS_MAX+1); for(i = 1; i <= lp->rows; i++) tally[get_constr_class(lp, i)]++; if(datainfo != NULL) report(lp, NORMAL, "%s\n", datainfo); for(i = 0; i <= ROWCLASS_MAX; i++) if(tally[i] > 0) report(lp, NORMAL, "%-15s %4d\n", get_str_constr_class(lp, i), tally[i]); } void REPORT_modelinfo(lprec *lp, MYBOOL doName, char *datainfo) { if(doName) { report(lp, NORMAL, "\nModel name: '%s' - run #%-5d\n", get_lp_name(lp), lp->solvecount); report(lp, NORMAL, "Objective: %simize(%s)\n", my_if(is_maxim(lp), "Max", "Min"), get_row_name(lp, 0)); report(lp, NORMAL, " \n"); } if(datainfo != NULL) report(lp, NORMAL, "%s\n", datainfo); report(lp, NORMAL, "Model size: %7d constraints, %7d variables, %12d non-zeros.\n", lp->rows, lp->columns, get_nonzeros(lp)); if(GUB_count(lp)+SOS_count(lp) > 0) report(lp, NORMAL, "Var-types: %7d integer, %7d semi-cont., %7d SOS.\n", lp->int_vars, lp->sc_vars, lp->sos_vars); report(lp, NORMAL, "Sets: %7d GUB, %7d SOS.\n", GUB_count(lp), SOS_count(lp)); } /* Save a matrix column subset to a MatrixMarket formatted file, say to export the basis matrix for further numerical analysis. If colndx is NULL, then the full constraint matrix is assumed. */ MYBOOL REPORT_mat_mmsave(lprec *lp, char *filename, int *colndx, MYBOOL includeOF, char *infotext) { int n, m, nz, i, j, k, kk; MATrec *mat = lp->matA; MM_typecode matcode; FILE *output = stdout; MYBOOL ok; REAL *acol = NULL; int *nzlist = NULL; /* Open file */ ok = (MYBOOL) ((filename == NULL) || ((output = fopen(filename,"w")) != NULL)); if(!ok) return(ok); if((filename == NULL) && (lp->outstream != NULL)) output = lp->outstream; /* Compute column and non-zero counts */ if(colndx == lp->var_basic) { if(!lp->basis_valid) return( FALSE ); m = lp->rows; } else if(colndx != NULL) m = colndx[0]; else m = lp->columns; n = lp->rows; nz = 0; for(j = 1; j <= m; j++) { k = (colndx == NULL ? n + j : colndx[j]); if(k > n) { k -= lp->rows; nz += mat_collength(mat, k); if(includeOF && is_OF_nz(lp, k)) nz++; } else nz++; } kk = 0; if(includeOF) { n++; /* Row count */ kk++; /* Row index offset */ } /* Initialize */ mm_initialize_typecode(&matcode); mm_set_matrix(&matcode); mm_set_coordinate(&matcode); mm_set_real(&matcode); mm_write_banner(output, matcode); mm_write_mtx_crd_size(output, n+kk, m, nz+(colndx == lp->var_basic ? 1 : 0)); /* Allocate working arrays for sparse column storage */ allocREAL(lp, &acol, n+2, FALSE); allocINT(lp, &nzlist, n+2, FALSE); /* Write the matrix non-zero values column-by-column. NOTE: matrixMarket files use 1-based indeces, i.e. first row of a vector has index 1, not 0. */ if(infotext != NULL) { fprintf(output, "%%\n"); fprintf(output, "%% %s\n", infotext); fprintf(output, "%%\n"); } if(includeOF && (colndx == lp->var_basic)) fprintf(output, "%d %d %g\n", 1, 1, 1.0); for(j = 1; j <= m; j++) { k = (colndx == NULL ? lp->rows + j : colndx[j]); if(k == 0) continue; nz = obtain_column(lp, k, acol, nzlist, NULL); for(i = 1; i <= nz; i++) { if(!includeOF && (nzlist[i] == 0)) continue; fprintf(output, "%d %d %g\n", nzlist[i]+kk, j+kk, acol[i]); } } fprintf(output, "%% End of MatrixMarket file\n"); /* Finish */ FREE(acol); FREE(nzlist); fclose(output); return(ok); } MSVMpack1.2/lp_solve_5.5/lp_utils.h0000664000175000017500000001312011245561655016151 0ustar lauerlauer#ifndef HEADER_lp_utils #define HEADER_lp_utils #ifdef FORTIFY #include "lp_fortify.h" #define allocCHAR allocCHAR_FORTIFY #define allocMYBOOL allocMYBOOL_FORTIFY #define allocINT allocINT_FORTIFY #define allocREAL allocREAL_FORTIFY #define allocLREAL allocLREAL_FORTIFY #endif #include "lp_types.h" /* Temporary data storage arrays */ typedef struct _workarraysrec { lprec *lp; int size; int count; char **vectorarray; int *vectorsize; } workarraysrec; typedef struct _LLrec { int size; /* The allocated list size */ int count; /* The current entry count */ int firstitem; int lastitem; int *map; /* The list of forward and backward-mapped entries */ } LLrec; typedef struct _PVrec { int count; /* The allocated list item count */ int *startpos; /* Starting index of the current value */ REAL *value; /* The list of forward and backward-mapped entries */ struct _PVrec *parent; /* The parent record in a pushed chain */ } PVrec; #ifdef __cplusplus extern "C" { #endif /* Put function headers here */ STATIC MYBOOL allocCHAR(lprec *lp, char **ptr, int size, MYBOOL clear); STATIC MYBOOL allocMYBOOL(lprec *lp, MYBOOL **ptr, int size, MYBOOL clear); STATIC MYBOOL allocINT(lprec *lp, int **ptr, int size, MYBOOL clear); STATIC MYBOOL allocREAL(lprec *lp, REAL **ptr, int size, MYBOOL clear); STATIC MYBOOL allocLREAL(lprec *lp, LREAL **ptr, int size, MYBOOL clear); STATIC MYBOOL allocFREE(lprec *lp, void **ptr); REAL *cloneREAL(lprec *lp, REAL *origlist, int size); MYBOOL *cloneMYBOOL(lprec *lp, MYBOOL *origlist, int size); int *cloneINT(lprec *lp, int *origlist, int size); int comp_bits(MYBOOL *bitarray1, MYBOOL *bitarray2, int items); STATIC workarraysrec *mempool_create(lprec *lp); STATIC char *mempool_obtainVector(workarraysrec *mempool, int count, int unitsize); STATIC MYBOOL mempool_releaseVector(workarraysrec *mempool, char *memvector, MYBOOL forcefree); STATIC MYBOOL mempool_free(workarraysrec **mempool); STATIC void roundVector(LREAL *myvector, int endpos, LREAL roundzero); STATIC REAL normalizeVector(REAL *myvector, int endpos); STATIC void swapINT(int *item1, int *item2); STATIC void swapREAL(REAL *item1, REAL *item2); STATIC void swapPTR(void **item1, void **item2); STATIC REAL restoreINT(REAL valREAL, REAL epsilon); STATIC REAL roundToPrecision(REAL value, REAL precision); STATIC int searchFor(int target, int *attributes, int size, int offset, MYBOOL absolute); STATIC MYBOOL isINT(lprec *lp, REAL value); STATIC MYBOOL isOrigFixed(lprec *lp, int varno); STATIC void chsign_bounds(REAL *lobound, REAL *upbound); STATIC REAL rand_uniform(lprec *lp, REAL range); /* Doubly linked list routines */ STATIC int createLink(int size, LLrec **linkmap, MYBOOL *usedpos); STATIC MYBOOL freeLink(LLrec **linkmap); STATIC int sizeLink(LLrec *linkmap); STATIC MYBOOL isActiveLink(LLrec *linkmap, int itemnr); STATIC int countActiveLink(LLrec *linkmap); STATIC int countInactiveLink(LLrec *linkmap); STATIC int firstActiveLink(LLrec *linkmap); STATIC int lastActiveLink(LLrec *linkmap); STATIC MYBOOL appendLink(LLrec *linkmap, int newitem); STATIC MYBOOL insertLink(LLrec *linkmap, int afteritem, int newitem); STATIC MYBOOL setLink(LLrec *linkmap, int newitem); STATIC MYBOOL fillLink(LLrec *linkmap); STATIC int nextActiveLink(LLrec *linkmap, int backitemnr); STATIC int prevActiveLink(LLrec *linkmap, int forwitemnr); STATIC int firstInactiveLink(LLrec *linkmap); STATIC int lastInactiveLink(LLrec *linkmap); STATIC int nextInactiveLink(LLrec *linkmap, int backitemnr); STATIC int prevInactiveLink(LLrec *linkmap, int forwitemnr); STATIC int removeLink(LLrec *linkmap, int itemnr); STATIC LLrec *cloneLink(LLrec *sourcemap, int newsize, MYBOOL freesource); STATIC int compareLink(LLrec *linkmap1, LLrec *linkmap2); STATIC MYBOOL verifyLink(LLrec *linkmap, int itemnr, MYBOOL doappend); /* Packed vector routines */ STATIC PVrec *createPackedVector(int size, REAL *values, int *workvector); STATIC void pushPackedVector(PVrec *PV, PVrec *parent); STATIC MYBOOL unpackPackedVector(PVrec *PV, REAL **target); STATIC REAL getvaluePackedVector(PVrec *PV, int index); STATIC PVrec *popPackedVector(PVrec *PV); STATIC MYBOOL freePackedVector(PVrec **PV); #ifdef __cplusplus } #endif #endif /* HEADER_lp_utils */ #ifdef FORTIFY #if defined CODE_lp_utils && !defined CODE_lp_utils_ int _Fortify_ret; #else extern int _Fortify_ret; #endif #ifdef CODE_lp_utils #define CODE_lp_utils_ #else # undef allocCHAR # undef allocMYBOOL # undef allocINT # undef allocREAL # undef allocLREAL # define allocCHAR(lp, ptr, size, clear) (Fortify_LINE(__LINE__), Fortify_FILE(__FILE__), _Fortify_ret = allocCHAR_FORTIFY(lp, ptr, size, clear), Fortify_LINE(0), Fortify_FILE(NULL), _Fortify_ret) # define allocMYBOOL(lp, ptr, size, clear) (Fortify_LINE(__LINE__), Fortify_FILE(__FILE__), _Fortify_ret = allocMYBOOL_FORTIFY(lp, ptr, size, clear), Fortify_LINE(0), Fortify_FILE(NULL), _Fortify_ret) # define allocINT(lp, ptr, size, clear) (Fortify_LINE(__LINE__), Fortify_FILE(__FILE__), _Fortify_ret = allocINT_FORTIFY(lp, ptr, size, clear), Fortify_LINE(0), Fortify_FILE(NULL), _Fortify_ret) # define allocREAL(lp, ptr, size, clear) (Fortify_LINE(__LINE__), Fortify_FILE(__FILE__), _Fortify_ret = allocREAL_FORTIFY(lp, ptr, size, clear), Fortify_LINE(0), Fortify_FILE(NULL), _Fortify_ret) # define allocLREAL(lp, ptr, size, clear) (Fortify_LINE(__LINE__), Fortify_FILE(__FILE__), _Fortify_ret = allocLREAL_FORTIFY(lp, ptr, size, clear), Fortify_LINE(0), Fortify_FILE(NULL), _Fortify_ret) #endif #endif MSVMpack1.2/lp_solve_5.5/lp_lib.h0000664000175000017500000035114011245551461015560 0ustar lauerlauer #ifndef HEADER_lp_lib #define HEADER_lp_lib /* -------------------------------------------------------------------------- This is the main library header file for the lp_solve v5.0 release Starting at version 3.0, LP_Solve is released under the LGPL license. For full information, see the enclosed file LGPL.txt. Original developer: Michel Berkelaar - michel@ics.ele.tue.nl Most changes 1.5-2.0: Jeroen Dirks - jeroend@tor.numetrix.com Changes 3.2-4.0: Kjell Eikland - kjell.eikland@broadpark.no (Simplex code, SOS, SC, code optimization) Peter Notebaert - lpsolve@peno.be (Sensitivity analysis, documentation) Changes 5.0+: Kjell Eikland - kjell.eikland@broadpark.no (BFP, XLI, simplex, B&B, code modularization) Peter Notebaert - lpsolve@peno.be (Sensitivity analysis, New lp parser, LINDO (XLI) parser, VB/.NET interface, documentation) Release notes: Version 4.0 enhances version 3.2 in terms of internal program/simplex architecture, call level interfaces, data layout, features and contains several bug fixes. There is now complete support for semi-continuous variables and SOS constructions. In the process, a complete API was added. The MPS parser has been amended to support this. Sensitivity analysis and variouse bug fixes was provided by Peter Notebaert in 4.0 sub-releases. Peter also wrote a complete documentation of the API and contributed a VB interface, both of which significantly enhanced the accessibility of lp_solve. Version 5.0 is a major rewrite and code cleanup. The main additions that drove forward this cleanup were the modular inversion logic with optimal column ordering, addition of primal phase 1 and dual phase 2 logic for full flexibility in the selection of primal and dual simplex modes, DEVEX and steepest edge pivot selection, along with dynamic cycling detection and prevention. This cleanup made it possible to harmonize the internal rounding principles, contributing to increased numerical stability. Version 5.1 rearranges the matrix storage model by enabling both legacy element record-based storage and split vector storage. In addition the lprec structure is optimized and additional routines are added, mainly for sparse vector additions and enhanced XLI functionality. Support for XML- based models was added on the basis of the LPFML schema via xli_LPFML. Version 5.2 removes the objective function from the constraint matrix, adds a number of presolve options and speed them up. Degeneracy handling is significantly improved. Support for XLI_ZIMPL was added. Multiple and partial pricing has been enhanced and activated. -------------------------------------------------------------------------- */ /* Define user program feature option switches */ /* ------------------------------------------------------------------------- */ # if defined _WIN32 && !defined __GNUC__ # define isnan _isnan # endif #if defined NOISNAN # define isnan(x) FALSE #endif #define SETMASK(variable, mask) variable |= mask #define CLEARMASK(variable, mask) variable &= ~(mask) #define TOGGLEMASK(variable, mask) variable ^= mask #define ISMASKSET(variable, mask) (MYBOOL) (((variable) & (mask)) != 0) /* Utility/system settings */ /* ------------------------------------------------------------------------- */ /*#define INTEGERTIME */ /* Set use of lower-resolution timer */ /* New v5.0+ simplex/optimization features and settings */ /* ------------------------------------------------------------------------- */ /*#define NoRowScaleOF */ /* Optionally skip row-scaling of the OF */ #define DoMatrixRounding /* Round A matrix elements to precision */ #define DoBorderRounding /* Round RHS, bounds and ranges to precision */ #define Phase1EliminateRedundant /* Remove rows of redundant artificials */ #define FixViolatedOptimal #define ImproveSolutionPrecision /* Round optimal solution values */ /*#define IncreasePivotOnReducedAccuracy */ /* Increase epspivot on instability */ /*#define FixInaccurateDualMinit */ /* Reinvert on inaccuracy in dual minits */ /*#define EnforcePositiveTheta */ /* Ensure that the theta range is valid */ #define ResetMinitOnReinvert /*#define UsePrimalReducedCostUpdate */ /* Not tested */ /*#define UseDualReducedCostUpdate */ /* Seems Ok, but slower than expected */ /*#ifdef UseLegacyExtrad */ /* Use v3.2- style Extrad method */ #define UseMilpExpandedRCF /* Non-ints in reduced cost bound tightening */ /*#define UseMilpSlacksRCF */ /* Slacks in reduced cost bound tightening (degen prone); requires !SlackInitMinusInf */ #define LegacySlackDefinition /* Slack as the "value of the constraint" */ /* Development features (change at own risk) */ /* ------------------------------------------------------------------------- */ /*#define MIPboundWithOF */ /* Enable to detect OF constraint for use during B&B */ /*#define SlackInitMinusInf */ /* Slacks have 0 LB if this is not defined */ #define FULLYBOUNDEDSIMPLEX FALSE /* WARNING: Activate at your own risk! */ /* Specify use of the basic linear algebra subroutine library */ /* ------------------------------------------------------------------------- */ #define libBLAS 2 /* 0: No, 1: Internal, 2: External */ #define libnameBLAS "myBLAS" /* Active inverse logic (default is optimized original etaPFI) */ /* ------------------------------------------------------------------------- */ #if !defined LoadInverseLib # define LoadInverseLib TRUE /* Enable alternate inverse libraries */ #endif /*#define ExcludeNativeInverse */ /* Disable INVERSE_ACTIVE inverse engine */ #define DEF_OBJINBASIS TRUE /* Additional rows inserted at the top (1 => OF) */ #define INVERSE_NONE -1 #define INVERSE_LEGACY 0 #define INVERSE_ETAPFI 1 #define INVERSE_LUMOD 2 #define INVERSE_LUSOL 3 #define INVERSE_GLPKLU 4 #ifndef RoleIsExternalInvEngine /* Defined in inverse DLL drivers */ #ifdef ExcludeNativeInverse #define INVERSE_ACTIVE INVERSE_NONE /* Disable native engine */ #else #define INVERSE_ACTIVE INVERSE_LEGACY /* User or DLL-selected */ #endif #endif /* Active external language interface logic (default is none) */ /* ------------------------------------------------------------------------- */ #if !defined LoadLanguageLib # define LoadLanguageLib TRUE /* Enable alternate language libraries */ #endif #define ExcludeNativeLanguage /* Disable LANGUAGE_ACTIVE XLI */ #define LANGUAGE_NONE -1 #define LANGUAGE_LEGACYLP 0 #define LANGUAGE_CPLEXLP 1 #define LANGUAGE_MPSX 2 #define LANGUAGE_LPFML 3 #define LANGUAGE_MATHPROG 4 #define LANGUAGE_AMPL 5 #define LANGUAGE_GAMS 6 #define LANGUAGE_ZIMPL 7 #define LANGUAGE_S 8 #define LANGUAGE_R 9 #define LANGUAGE_MATLAB 10 #define LANGUAGE_OMATRIX 11 #define LANGUAGE_SCILAB 12 #define LANGUAGE_OCTAVE 13 #define LANGUAGE_EMPS 14 #ifndef RoleIsExternalLanguageEngine /* Defined in XLI driver libraries */ #ifdef ExcludeNativeLanguage #define LANGUAGE_ACTIVE LANGUAGE_NONE /* Disable native engine */ #else #define LANGUAGE_ACTIVE LANGUAGE_CPLEXLP /* User or DLL-selected */ #endif #endif /* Default parameters and tolerances */ /* ------------------------------------------------------------------------- */ #define OriginalPARAM 0 #define ProductionPARAM 1 #define ChvatalPARAM 2 #define LoosePARAM 3 #if 1 #define ActivePARAM ProductionPARAM #else #define ActivePARAM LoosePARAM #endif /* Miscellaneous settings */ /* ------------------------------------------------------------------------- */ #ifndef Paranoia #ifdef _DEBUG #define Paranoia #endif #endif /* Program version data */ /* ------------------------------------------------------------------------- */ #define MAJORVERSION 5 #define MINORVERSION 5 #define RELEASE 0 #define BUILD 15 #define BFPVERSION 12 /* Checked against bfp_compatible() */ #define XLIVERSION 12 /* Checked against xli_compatible() */ /* Note that both BFPVERSION and XLIVERSION typically have to be incremented in the case that the lprec structure changes. */ /* Include/header files */ /* ------------------------------------------------------------------------- */ #include #include #include #include #include #include "lp_types.h" #include "lp_utils.h" #if (LoadInverseLib == TRUE) || (LoadLanguageLib == TRUE) #ifdef WIN32 #include #else #include #endif #endif #ifndef BFP_CALLMODEL #ifdef WIN32 #define BFP_CALLMODEL __stdcall /* "Standard" call model */ #else #define BFP_CALLMODEL #endif #endif #ifndef XLI_CALLMODEL #define XLI_CALLMODEL BFP_CALLMODEL #endif #define REGISTER register /* Speed up certain operations */ /* Definition of program constrants */ /* ------------------------------------------------------------------------- */ #define SIMPLEX_UNDEFINED 0 #define SIMPLEX_Phase1_PRIMAL 1 #define SIMPLEX_Phase1_DUAL 2 #define SIMPLEX_Phase2_PRIMAL 4 #define SIMPLEX_Phase2_DUAL 8 #define SIMPLEX_DYNAMIC 16 #define SIMPLEX_AUTODUALIZE 32 #define SIMPLEX_PRIMAL_PRIMAL (SIMPLEX_Phase1_PRIMAL + SIMPLEX_Phase2_PRIMAL) #define SIMPLEX_DUAL_PRIMAL (SIMPLEX_Phase1_DUAL + SIMPLEX_Phase2_PRIMAL) #define SIMPLEX_PRIMAL_DUAL (SIMPLEX_Phase1_PRIMAL + SIMPLEX_Phase2_DUAL) #define SIMPLEX_DUAL_DUAL (SIMPLEX_Phase1_DUAL + SIMPLEX_Phase2_DUAL) #define SIMPLEX_DEFAULT (SIMPLEX_DUAL_PRIMAL) /* Variable codes (internal) */ #define ISREAL 0 #define ISINTEGER 1 #define ISSEMI 2 #define ISSOS 4 #define ISSOSTEMPINT 8 #define ISGUB 16 /* Presolve defines */ #define PRESOLVE_NONE 0 #define PRESOLVE_ROWS 1 #define PRESOLVE_COLS 2 #define PRESOLVE_LINDEP 4 #define PRESOLVE_AGGREGATE 8 /* Not implemented */ #define PRESOLVE_SPARSER 16 /* Not implemented */ #define PRESOLVE_SOS 32 #define PRESOLVE_REDUCEMIP 64 #define PRESOLVE_KNAPSACK 128 /* Implementation not tested completely */ #define PRESOLVE_ELIMEQ2 256 #define PRESOLVE_IMPLIEDFREE 512 #define PRESOLVE_REDUCEGCD 1024 #define PRESOLVE_PROBEFIX 2048 #define PRESOLVE_PROBEREDUCE 4096 #define PRESOLVE_ROWDOMINATE 8192 #define PRESOLVE_COLDOMINATE 16384 /* Reduced functionality, should be expanded */ #define PRESOLVE_MERGEROWS 32768 #define PRESOLVE_IMPLIEDSLK 65536 #define PRESOLVE_COLFIXDUAL 131072 #define PRESOLVE_BOUNDS 262144 #define PRESOLVE_LASTMASKMODE (PRESOLVE_DUALS - 1) #define PRESOLVE_DUALS 524288 #define PRESOLVE_SENSDUALS 1048576 /* Basis crash options */ #define CRASH_NONE 0 #define CRASH_NONBASICBOUNDS 1 #define CRASH_MOSTFEASIBLE 2 #define CRASH_LEASTDEGENERATE 3 /* Solution recomputation options (internal) */ #define INITSOL_SHIFTZERO 0 #define INITSOL_USEZERO 1 #define INITSOL_ORIGINAL 2 /* Strategy codes to avoid or recover from degenerate pivots, infeasibility or numeric errors via randomized bound relaxation */ #define ANTIDEGEN_NONE 0 #define ANTIDEGEN_FIXEDVARS 1 #define ANTIDEGEN_COLUMNCHECK 2 #define ANTIDEGEN_STALLING 4 #define ANTIDEGEN_NUMFAILURE 8 #define ANTIDEGEN_LOSTFEAS 16 #define ANTIDEGEN_INFEASIBLE 32 #define ANTIDEGEN_DYNAMIC 64 #define ANTIDEGEN_DURINGBB 128 #define ANTIDEGEN_RHSPERTURB 256 #define ANTIDEGEN_BOUNDFLIP 512 #define ANTIDEGEN_DEFAULT (ANTIDEGEN_FIXEDVARS | ANTIDEGEN_STALLING /* | ANTIDEGEN_INFEASIBLE */) /* REPORT defines */ #define NEUTRAL 0 #define CRITICAL 1 #define SEVERE 2 #define IMPORTANT 3 #define NORMAL 4 #define DETAILED 5 #define FULL 6 /* MESSAGE defines */ #define MSG_NONE 0 #define MSG_PRESOLVE 1 #define MSG_ITERATION 2 #define MSG_INVERT 4 #define MSG_LPFEASIBLE 8 #define MSG_LPOPTIMAL 16 #define MSG_LPEQUAL 32 #define MSG_LPBETTER 64 #define MSG_MILPFEASIBLE 128 #define MSG_MILPEQUAL 256 #define MSG_MILPBETTER 512 #define MSG_MILPSTRATEGY 1024 #define MSG_MILPOPTIMAL 2048 #define MSG_PERFORMANCE 4096 #define MSG_INITPSEUDOCOST 8192 /* MPS file types */ #define MPSFIXED 1 #define MPSFREE 2 #define MPSIBM 4 #define MPSNEGOBJCONST 8 #define MPS_FREE (MPSFREE<<2) #define MPS_IBM (MPSIBM<<2) #define MPS_NEGOBJCONST (MPSNEGOBJCONST<<2) /* MPS defines (internal) */ #define MPSUNDEF -4 #define MPSNAME -3 #define MPSOBJSENSE -2 #define MPSOBJNAME -1 #define MPSROWS 0 #define MPSCOLUMNS 1 #define MPSRHS 2 #define MPSBOUNDS 3 #define MPSRANGES 4 #define MPSSOS 5 #define MPSVARMASK "%-8s" #define MPSVALUEMASK "%12g" /* Constraint type codes (internal) */ #define ROWTYPE_EMPTY 0 #define ROWTYPE_LE 1 #define ROWTYPE_GE 2 #define ROWTYPE_EQ 3 #define ROWTYPE_CONSTRAINT ROWTYPE_EQ /* This is the mask for modes */ #define ROWTYPE_OF 4 #define ROWTYPE_INACTIVE 8 #define ROWTYPE_RELAX 16 #define ROWTYPE_GUB 32 #define ROWTYPE_OFMAX (ROWTYPE_OF + ROWTYPE_GE) #define ROWTYPE_OFMIN (ROWTYPE_OF + ROWTYPE_LE) #define ROWTYPE_CHSIGN ROWTYPE_GE /* Public constraint codes */ #define FR ROWTYPE_EMPTY #define LE ROWTYPE_LE #define GE ROWTYPE_GE #define EQ ROWTYPE_EQ #define OF ROWTYPE_OF /* MIP constraint classes */ #define ROWCLASS_Unknown 0 /* Undefined/unknown */ #define ROWCLASS_Objective 1 /* The objective function */ #define ROWCLASS_GeneralREAL 2 /* General real-values constraint */ #define ROWCLASS_GeneralMIP 3 /* General mixed integer/binary and real valued constraint */ #define ROWCLASS_GeneralINT 4 /* General integer-only constraint */ #define ROWCLASS_GeneralBIN 5 /* General binary-only constraint */ #define ROWCLASS_KnapsackINT 6 /* Sum of positive integer times integer variables <= positive integer */ #define ROWCLASS_KnapsackBIN 7 /* Sum of positive integer times binary variables <= positive integer */ #define ROWCLASS_SetPacking 8 /* Sum of binary variables >= 1 */ #define ROWCLASS_SetCover 9 /* Sum of binary variables <= 1 */ #define ROWCLASS_GUB 10 /* Sum of binary variables = 1 */ #define ROWCLASS_MAX ROWCLASS_GUB /* Column subsets (internal) */ #define SCAN_USERVARS 1 #define SCAN_SLACKVARS 2 #define SCAN_ARTIFICIALVARS 4 #define SCAN_PARTIALBLOCK 8 #define USE_BASICVARS 16 #define USE_NONBASICVARS 32 #define SCAN_NORMALVARS (SCAN_USERVARS + SCAN_ARTIFICIALVARS) #define SCAN_ALLVARS (SCAN_SLACKVARS + SCAN_USERVARS + SCAN_ARTIFICIALVARS) #define USE_ALLVARS (USE_BASICVARS + USE_NONBASICVARS) #define OMIT_FIXED 64 #define OMIT_NONFIXED 128 /* Improvement defines */ #define IMPROVE_NONE 0 #define IMPROVE_SOLUTION 1 #define IMPROVE_DUALFEAS 2 #define IMPROVE_THETAGAP 4 #define IMPROVE_BBSIMPLEX 8 #define IMPROVE_DEFAULT (IMPROVE_DUALFEAS + IMPROVE_THETAGAP) #define IMPROVE_INVERSE (IMPROVE_SOLUTION + IMPROVE_THETAGAP) /* Scaling types */ #define SCALE_NONE 0 #define SCALE_EXTREME 1 #define SCALE_RANGE 2 #define SCALE_MEAN 3 #define SCALE_GEOMETRIC 4 #define SCALE_FUTURE1 5 #define SCALE_FUTURE2 6 #define SCALE_CURTISREID 7 /* Override to Curtis-Reid "optimal" scaling */ /* Alternative scaling weights */ #define SCALE_LINEAR 0 #define SCALE_QUADRATIC 8 #define SCALE_LOGARITHMIC 16 #define SCALE_USERWEIGHT 31 #define SCALE_MAXTYPE (SCALE_QUADRATIC-1) /* Scaling modes */ #define SCALE_POWER2 32 /* As is or rounded to power of 2 */ #define SCALE_EQUILIBRATE 64 /* Make sure that no scaled number is above 1 */ #define SCALE_INTEGERS 128 /* Apply to integer columns/variables */ #define SCALE_DYNUPDATE 256 /* Apply incrementally every solve() */ #define SCALE_ROWSONLY 512 /* Override any scaling to only scale the rows */ #define SCALE_COLSONLY 1024 /* Override any scaling to only scale the rows */ /* Standard defines for typical scaling models (no Lagrangeans) */ #define SCALEMODEL_EQUILIBRATED (SCALE_LINEAR+SCALE_EXTREME+SCALE_INTEGERS) #define SCALEMODEL_GEOMETRIC (SCALE_LINEAR+SCALE_GEOMETRIC+SCALE_INTEGERS) #define SCALEMODEL_ARITHMETIC (SCALE_LINEAR+SCALE_MEAN+SCALE_INTEGERS) #define SCALEMODEL_DYNAMIC (SCALEMODEL_GEOMETRIC+SCALE_EQUILIBRATE) #define SCALEMODEL_CURTISREID (SCALE_CURTISREID+SCALE_INTEGERS+SCALE_POWER2) /* Iteration status and strategies (internal) */ #define ITERATE_MAJORMAJOR 0 #define ITERATE_MINORMAJOR 1 #define ITERATE_MINORRETRY 2 /* Pricing methods */ #define PRICER_FIRSTINDEX 0 #define PRICER_DANTZIG 1 #define PRICER_DEVEX 2 #define PRICER_STEEPESTEDGE 3 #define PRICER_LASTOPTION PRICER_STEEPESTEDGE /* Additional settings for pricers (internal) */ #define PRICER_RANDFACT 0.1 #define DEVEX_RESTARTLIMIT 1.0e+09 /* Reset the norms if any value exceeds this limit */ #define DEVEX_MINVALUE 0.000 /* Minimum weight [0..1] for entering variable, consider 0.01 */ /* Pricing strategies */ #define PRICE_PRIMALFALLBACK 4 /* In case of Steepest Edge, fall back to DEVEX in primal */ #define PRICE_MULTIPLE 8 /* Enable multiple pricing (primal simplex) */ #define PRICE_PARTIAL 16 /* Enable partial pricing */ #define PRICE_ADAPTIVE 32 /* Temporarily use alternative strategy if cycling is detected */ #define PRICE_HYBRID 64 /* NOT IMPLEMENTED */ #define PRICE_RANDOMIZE 128 /* Adds a small randomization effect to the selected pricer */ #define PRICE_AUTOPARTIAL 256 /* Detect and use data on the block structure of the model (primal) */ #define PRICE_AUTOMULTIPLE 512 /* Automatically select multiple pricing (primal simplex) */ #define PRICE_LOOPLEFT 1024 /* Scan entering/leaving columns left rather than right */ #define PRICE_LOOPALTERNATE 2048 /* Scan entering/leaving columns alternatingly left/right */ #define PRICE_HARRISTWOPASS 4096 /* Use Harris' primal pivot logic rather than the default */ #define PRICE_FORCEFULL 8192 /* Non-user option to force full pricing */ #define PRICE_TRUENORMINIT 16384 /* Use true norms for Devex and Steepest Edge initializations */ /*#define _PRICE_NOBOUNDFLIP*/ #if defined _PRICE_NOBOUNDFLIP #define PRICE_NOBOUNDFLIP 65536 /* Disallow automatic bound-flip during pivot */ #endif #define PRICE_STRATEGYMASK (PRICE_PRIMALFALLBACK + \ PRICE_MULTIPLE + PRICE_PARTIAL + \ PRICE_ADAPTIVE + PRICE_HYBRID + \ PRICE_RANDOMIZE + PRICE_AUTOPARTIAL + PRICE_AUTOMULTIPLE + \ PRICE_LOOPLEFT + PRICE_LOOPALTERNATE + \ PRICE_HARRISTWOPASS + \ PRICE_FORCEFULL + PRICE_TRUENORMINIT) /* B&B active variable codes (internal) */ #define BB_REAL 0 #define BB_INT 1 #define BB_SC 2 #define BB_SOS 3 #define BB_GUB 4 /* B&B strategies */ #define NODE_FIRSTSELECT 0 #define NODE_GAPSELECT 1 #define NODE_RANGESELECT 2 #define NODE_FRACTIONSELECT 3 #define NODE_PSEUDOCOSTSELECT 4 #define NODE_PSEUDONONINTSELECT 5 /* Kjell Eikland #1 - Minimize B&B depth */ #define NODE_PSEUDOFEASSELECT (NODE_PSEUDONONINTSELECT+NODE_WEIGHTREVERSEMODE) #define NODE_PSEUDORATIOSELECT 6 /* Kjell Eikland #2 - Minimize a "cost/benefit" ratio */ #define NODE_USERSELECT 7 #define NODE_STRATEGYMASK (NODE_WEIGHTREVERSEMODE-1) /* Mask for B&B strategies */ #define NODE_WEIGHTREVERSEMODE 8 #define NODE_BRANCHREVERSEMODE 16 #define NODE_GREEDYMODE 32 #define NODE_PSEUDOCOSTMODE 64 #define NODE_DEPTHFIRSTMODE 128 #define NODE_RANDOMIZEMODE 256 #define NODE_GUBMODE 512 #define NODE_DYNAMICMODE 1024 #define NODE_RESTARTMODE 2048 #define NODE_BREADTHFIRSTMODE 4096 #define NODE_AUTOORDER 8192 #define NODE_RCOSTFIXING 16384 #define NODE_STRONGINIT 32768 #define BRANCH_CEILING 0 #define BRANCH_FLOOR 1 #define BRANCH_AUTOMATIC 2 #define BRANCH_DEFAULT 3 /* Action constants for simplex and B&B (internal) */ #define ACTION_NONE 0 #define ACTION_ACTIVE 1 #define ACTION_REBASE 2 #define ACTION_RECOMPUTE 4 #define ACTION_REPRICE 8 #define ACTION_REINVERT 16 #define ACTION_TIMEDREINVERT 32 #define ACTION_ITERATE 64 #define ACTION_RESTART 255 /* Solver status values */ #define UNKNOWNERROR -5 #define DATAIGNORED -4 #define NOBFP -3 #define NOMEMORY -2 #define NOTRUN -1 #define OPTIMAL 0 #define SUBOPTIMAL 1 #define INFEASIBLE 2 #define UNBOUNDED 3 #define DEGENERATE 4 #define NUMFAILURE 5 #define USERABORT 6 #define TIMEOUT 7 #define RUNNING 8 #define PRESOLVED 9 /* Branch & Bound and Lagrangean extra status values (internal) */ #define PROCFAIL 10 #define PROCBREAK 11 #define FEASFOUND 12 #define NOFEASFOUND 13 #define FATHOMED 14 /* Status values internal to the solver (internal) */ #define SWITCH_TO_PRIMAL 20 #define SWITCH_TO_DUAL 21 #define SINGULAR_BASIS 22 #define LOSTFEAS 23 #define MATRIXERROR 24 /* Objective testing options for "bb_better" (internal) */ #define OF_RELAXED 0 #define OF_INCUMBENT 1 #define OF_WORKING 2 #define OF_USERBREAK 3 #define OF_HEURISTIC 4 #define OF_DUALLIMIT 5 #define OF_DELTA 8 /* Mode */ #define OF_PROJECTED 16 /* Mode - future, not active */ #define OF_TEST_BT 1 #define OF_TEST_BE 2 #define OF_TEST_NE 3 #define OF_TEST_WE 4 #define OF_TEST_WT 5 #define OF_TEST_RELGAP 8 /* Mode */ /* Name list and sparse matrix storage parameters (internal) */ #define MAT_START_SIZE 10000 #define DELTACOLALLOC 100 #define DELTAROWALLOC 100 #define RESIZEFACTOR 4 /* Fractional increase in selected memory allocations */ /* Default solver parameters and tolerances (internal) */ #define DEF_PARTIALBLOCKS 10 /* The default number of blocks for partial pricing */ #define DEF_MAXRELAX 7 /* Maximum number of non-BB relaxations in MILP */ #define DEF_MAXPIVOTRETRY 10 /* Maximum number of times to retry a div-0 situation */ #define DEF_MAXSINGULARITIES 10 /* Maximum number of singularities in refactorization */ #define MAX_MINITUPDATES 60 /* Maximum number of bound swaps between refactorizations without recomputing the whole vector - contain errors */ #define MIN_REFACTFREQUENCY 5 /* Refactorization frequency indicating an inherent numerical instability of the basis */ #define LAG_SINGULARLIMIT 5 /* Number of times the objective does not change before it is assumed that the Lagrangean constraints are non-binding, and therefore impossible to converge; upper iteration limit is divided by this threshold */ #define MIN_TIMEPIVOT 5.0e-02 /* Minimum time per pivot for reinversion optimization purposes; use active monitoring only if a pivot takes more than MINTIMEPIVOT seconds. 5.0e-2 is roughly suitable for a 1GHz system. */ #define MAX_STALLCOUNT 12 /* The absolute upper limit to the number of stalling or cycling iterations before switching rule */ #define MAX_RULESWITCH 5 /* The maximum number of times to try an alternate pricing rule to recover from stalling; set negative for no limit. */ #define DEF_TIMEDREFACT AUTOMATIC /* Default for timed refactorization in BFPs; can be FALSE, TRUE or AUTOMATIC (dynamic) */ #define DEF_SCALINGLIMIT 5 /* The default maximum number of scaling iterations */ #define DEF_NEGRANGE -1.0e+06 /* Downward limit for expanded variable range before the variable is split into positive and negative components */ #define DEF_BB_LIMITLEVEL -50 /* Relative B&B limit to protect against very deep, memory-consuming trees */ #define MAX_FRACSCALE 6 /* The maximum decimal scan range for simulated integers */ #define RANDSCALE 100 /* Randomization scaling range */ #define DOUBLEROUND 0.0e-02 /* Extra rounding scalar used in btran/ftran calculations; the rationale for 0.0 is that prod_xA() uses rounding as well */ #define DEF_EPSMACHINE 2.22e-16 /* Machine relative precision (doubles) */ #define MIN_STABLEPIVOT 5.0 /* Minimum pivot magnitude assumed to be numerically stable */ /* Precision macros */ /* -------------------------------------------------------------------------------------- */ #define PREC_REDUCEDCOST lp->epsvalue #define PREC_IMPROVEGAP lp->epsdual #define PREC_SUBSTFEASGAP lp->epsprimal #if 1 #define PREC_BASICSOLUTION lp->epsvalue /* Zero-rounding of RHS/basic solution vector */ #else #define PREC_BASICSOLUTION lp->epsmachine /* Zero-rounding of RHS/basic solution vector */ #endif #define LIMIT_ABS_REL 10.0 /* Limit for testing using relative metric */ /* Parameters constants for short-cut setting of tolerances */ /* -------------------------------------------------------------------------------------- */ #define EPS_TIGHT 0 #define EPS_MEDIUM 1 #define EPS_LOOSE 2 #define EPS_BAGGY 3 #define EPS_DEFAULT EPS_TIGHT #if ActivePARAM==ProductionPARAM /* PARAMETER SET FOR PRODUCTION */ /* -------------------------------------------------------------------------------------- */ #define DEF_INFINITE 1.0e+30 /* Limit for dynamic range */ #define DEF_EPSVALUE 1.0e-12 /* High accuracy and feasibility preserving tolerance */ #define DEF_EPSPRIMAL 1.0e-10 /* For rounding primal/RHS values to 0 */ #define DEF_EPSDUAL 1.0e-09 /* For rounding reduced costs to 0 */ #define DEF_EPSPIVOT 2.0e-07 /* Pivot reject threshold */ #define DEF_PERTURB 1.0e-05 /* Perturbation scalar for degenerate problems; must at least be RANDSCALE greater than EPSPRIMAL */ #define DEF_EPSSOLUTION 1.0e-05 /* Margin of error for solution bounds */ #define DEF_EPSINT 1.0e-07 /* Accuracy for considering a float value as integer */ #elif ActivePARAM==OriginalPARAM /* PARAMETER SET FOR LEGACY VERSIONS */ /* -------------------------------------------------------------------------------------- */ #define DEF_INFINITE 1.0e+24 /* Limit for dynamic range */ #define DEF_EPSVALUE 1.0e-08 /* High accuracy and feasibility preserving tolerance */ #define DEF_EPSPRIMAL 5.01e-07 /* For rounding primal/RHS values to 0, infeasibility */ #define DEF_EPSDUAL 1.0e-06 /* For rounding reduced costs to 0 */ #define DEF_EPSPIVOT 1.0e-04 /* Pivot reject threshold */ #define DEF_PERTURB 1.0e-05 /* Perturbation scalar for degenerate problems; must at least be RANDSCALE greater than EPSPRIMAL */ #define DEF_EPSSOLUTION 1.0e-02 /* Margin of error for solution bounds */ #define DEF_EPSINT 1.0e-03 /* Accuracy for considering a float value as integer */ #elif ActivePARAM==ChvatalPARAM /* PARAMETER SET EXAMPLES FROM Vacek Chvatal */ /* -------------------------------------------------------------------------------------- */ #define DEF_INFINITE 1.0e+30 /* Limit for dynamic range */ #define DEF_EPSVALUE 1.0e-10 /* High accuracy and feasibility preserving tolerance */ #define DEF_EPSPRIMAL 10e-07 /* For rounding primal/RHS values to 0 */ #define DEF_EPSDUAL 10e-05 /* For rounding reduced costs to 0 */ #define DEF_EPSPIVOT 10e-05 /* Pivot reject threshold */ #define DEF_PERTURB 10e-03 /* Perturbation scalar for degenerate problems; must at least be RANDSCALE greater than EPSPRIMAL */ #define DEF_EPSSOLUTION 1.0e-05 /* Margin of error for solution bounds */ #define DEF_EPSINT 5.0e-03 /* Accuracy for considering a float value as integer */ #elif ActivePARAM==LoosePARAM /* PARAMETER SET FOR LOOSE TOLERANCES */ /* -------------------------------------------------------------------------------------- */ #define DEF_INFINITE 1.0e+30 /* Limit for dynamic range */ #define DEF_EPSVALUE 1.0e-10 /* High accuracy and feasibility preserving tolerance */ #define DEF_EPSPRIMAL 5.01e-08 /* For rounding primal/RHS values to 0 */ #define DEF_EPSDUAL 1.0e-07 /* For rounding reduced costs to 0 */ #define DEF_EPSPIVOT 1.0e-05 /* Pivot reject threshold */ #define DEF_PERTURB 1.0e-05 /* Perturbation scalar for degenerate problems; must at least be RANDSCALE greater than EPSPRIMAL */ #define DEF_EPSSOLUTION 1.0e-05 /* Margin of error for solution bounds */ #define DEF_EPSINT 1.0e-04 /* Accuracy for considering a float value as integer */ #endif #define DEF_MIP_GAP 1.0e-11 /* The default absolute and relative MIP gap */ #define SCALEDINTFIXRANGE 1.6 /* Epsilon range multiplier < 2 for collapsing bounds to fix */ #define MIN_SCALAR 1.0e-10 /* Smallest allowed scaling adjustment */ #define MAX_SCALAR 1.0e+10 /* Largest allowed scaling adjustment */ #define DEF_SCALINGEPS 1.0e-02 /* Relative scaling convergence criterion for auto_scale */ #define DEF_LAGACCEPT 1.0e-03 /* Default Lagrangean convergence acceptance criterion */ #define DEF_LAGCONTRACT 0.90 /* The contraction parameter for Lagrangean iterations */ #define DEF_LAGMAXITERATIONS 100 /* The maximum number of Lagrangean iterations */ #define DEF_PSEUDOCOSTUPDATES 7 /* The default number of times pseudo-costs are recalculated; experiments indicate that costs tend to stabilize */ #define DEF_PSEUDOCOSTRESTART 0.15 /* The fraction of price updates required for B&B restart when the mode is NODE_RESTARTMODE */ #define DEF_MAXPRESOLVELOOPS 0 /* Upper limit to the number of loops during presolve, <= 0 for no limit. */ /* Hashing prototypes and function headers */ /* ------------------------------------------------------------------------- */ #include "lp_Hash.h" /* Sparse matrix prototypes */ /* ------------------------------------------------------------------------- */ #include "lp_matrix.h" /* Basis storage (mainly for B&B) */ typedef struct _basisrec { int level; int *var_basic; MYBOOL *is_basic; MYBOOL *is_lower; int pivots; struct _basisrec *previous; } basisrec; /* Presolve undo data storage */ typedef struct _presolveundorec { lprec *lp; int orig_rows; int orig_columns; int orig_sum; int *var_to_orig; /* sum_alloc+1 : Mapping of variables from solution to best_solution to account for removed variables and rows during presolve; a non-positive value indicates that the constraint or variable was removed */ int *orig_to_var; /* sum_alloc+1 : Mapping from original variable index to current / working index number */ REAL *fixed_rhs; /* rows_alloc+1 : Storage of values of presolved fixed colums */ REAL *fixed_obj; /* columns_alloc+1: Storage of values of presolved fixed rows */ DeltaVrec *deletedA; /* A matrix of eliminated data from matA */ DeltaVrec *primalundo; /* Affine translation vectors for eliminated primal variables */ DeltaVrec *dualundo; /* Affine translation vectors for eliminated dual variables */ MYBOOL OFcolsdeleted; } presolveundorec; /* Pseudo-cost arrays used during B&B */ typedef struct _BBPSrec { lprec *lp; int pseodotype; int updatelimit; int updatesfinished; REAL restartlimit; MATitem *UPcost; MATitem *LOcost; struct _BBPSrec *secondary; } BBPSrec; #include "lp_mipbb.h" /* Partial pricing block data */ typedef struct _partialrec { lprec *lp; int blockcount; /* ## The number of logical blocks or stages in the model */ int blocknow; /* The currently active block */ int *blockend; /* Array of column indeces giving the start of each block */ int *blockpos; /* Array of column indeces giving the start scan position */ MYBOOL isrow; } partialrec; /* Specially Ordered Sets (SOS) prototypes and settings */ /* ------------------------------------------------------------------------- */ /* SOS storage structure (LINEARSEARCH is typically in the 0-10 range) */ #ifndef LINEARSEARCH #define LINEARSEARCH 0 #endif #include "lp_SOS.h" /* Prototypes for user call-back functions */ /* ------------------------------------------------------------------------- */ typedef int (__WINAPI lphandle_intfunc)(lprec *lp, void *userhandle); typedef void (__WINAPI lphandlestr_func)(lprec *lp, void *userhandle, char *buf); typedef void (__WINAPI lphandleint_func)(lprec *lp, void *userhandle, int message); typedef int (__WINAPI lphandleint_intfunc)(lprec *lp, void *userhandle, int message); /* API typedef definitions */ /* ------------------------------------------------------------------------- */ typedef MYBOOL (__WINAPI add_column_func)(lprec *lp, REAL *column); typedef MYBOOL (__WINAPI add_columnex_func)(lprec *lp, int count, REAL *column, int *rowno); typedef MYBOOL (__WINAPI add_constraint_func)(lprec *lp, REAL *row, int constr_type, REAL rh); typedef MYBOOL (__WINAPI add_constraintex_func)(lprec *lp, int count, REAL *row, int *colno, int constr_type, REAL rh); typedef MYBOOL (__WINAPI add_lag_con_func)(lprec *lp, REAL *row, int con_type, REAL rhs); typedef int (__WINAPI add_SOS_func)(lprec *lp, char *name, int sostype, int priority, int count, int *sosvars, REAL *weights); typedef int (__WINAPI column_in_lp_func)(lprec *lp, REAL *column); typedef lprec * (__WINAPI copy_lp_func)(lprec *lp); typedef void (__WINAPI default_basis_func)(lprec *lp); typedef MYBOOL (__WINAPI del_column_func)(lprec *lp, int colnr); typedef MYBOOL (__WINAPI del_constraint_func)(lprec *lp, int rownr); typedef void (__WINAPI delete_lp_func)(lprec *lp); typedef MYBOOL (__WINAPI dualize_lp_func)(lprec *lp); typedef void (__WINAPI free_lp_func)(lprec **plp); typedef int (__WINAPI get_anti_degen_func)(lprec *lp); typedef MYBOOL (__WINAPI get_basis_func)(lprec *lp, int *bascolumn, MYBOOL nonbasic); typedef int (__WINAPI get_basiscrash_func)(lprec *lp); typedef int (__WINAPI get_bb_depthlimit_func)(lprec *lp); typedef int (__WINAPI get_bb_floorfirst_func)(lprec *lp); typedef int (__WINAPI get_bb_rule_func)(lprec *lp); typedef MYBOOL (__WINAPI get_bounds_tighter_func)(lprec *lp); typedef REAL (__WINAPI get_break_at_value_func)(lprec *lp); typedef char * (__WINAPI get_col_name_func)(lprec *lp, int colnr); typedef MYBOOL (__WINAPI get_column_func)(lprec *lp, int colnr, REAL *column); typedef int (__WINAPI get_columnex_func)(lprec *lp, int colnr, REAL *column, int *nzrow); typedef int (__WINAPI get_constr_type_func)(lprec *lp, int rownr); typedef REAL (__WINAPI get_constr_value_func)(lprec *lp, int rownr, int count, REAL *primsolution, int *nzindex); typedef MYBOOL (__WINAPI get_constraints_func)(lprec *lp, REAL *constr); typedef MYBOOL (__WINAPI get_dual_solution_func)(lprec *lp, REAL *rc); typedef REAL (__WINAPI get_epsb_func)(lprec *lp); typedef REAL (__WINAPI get_epsd_func)(lprec *lp); typedef REAL (__WINAPI get_epsel_func)(lprec *lp); typedef REAL (__WINAPI get_epsint_func)(lprec *lp); typedef REAL (__WINAPI get_epsperturb_func)(lprec *lp); typedef REAL (__WINAPI get_epspivot_func)(lprec *lp); typedef int (__WINAPI get_improve_func)(lprec *lp); typedef REAL (__WINAPI get_infinite_func)(lprec *lp); typedef MYBOOL (__WINAPI get_lambda_func)(lprec *lp, REAL *lambda); typedef REAL (__WINAPI get_lowbo_func)(lprec *lp, int colnr); typedef int (__WINAPI get_lp_index_func)(lprec *lp, int orig_index); typedef char * (__WINAPI get_lp_name_func)(lprec *lp); typedef int (__WINAPI get_Lrows_func)(lprec *lp); typedef REAL (__WINAPI get_mat_func)(lprec *lp, int rownr, int colnr); typedef REAL (__WINAPI get_mat_byindex_func)(lprec *lp, int matindex, MYBOOL isrow, MYBOOL adjustsign); typedef int (__WINAPI get_max_level_func)(lprec *lp); typedef int (__WINAPI get_maxpivot_func)(lprec *lp); typedef REAL (__WINAPI get_mip_gap_func)(lprec *lp, MYBOOL absolute); typedef int (__WINAPI get_multiprice_func)(lprec *lp, MYBOOL getabssize); typedef MYBOOL (__WINAPI is_use_names_func)(lprec *lp, MYBOOL isrow); typedef void (__WINAPI set_use_names_func)(lprec *lp, MYBOOL isrow, MYBOOL use_names); typedef int (__WINAPI get_nameindex_func)(lprec *lp, char *varname, MYBOOL isrow); typedef int (__WINAPI get_Ncolumns_func)(lprec *lp); typedef REAL (__WINAPI get_negrange_func)(lprec *lp); typedef int (__WINAPI get_nz_func)(lprec *lp); typedef int (__WINAPI get_Norig_columns_func)(lprec *lp); typedef int (__WINAPI get_Norig_rows_func)(lprec *lp); typedef int (__WINAPI get_Nrows_func)(lprec *lp); typedef REAL (__WINAPI get_obj_bound_func)(lprec *lp); typedef REAL (__WINAPI get_objective_func)(lprec *lp); typedef int (__WINAPI get_orig_index_func)(lprec *lp, int lp_index); typedef char * (__WINAPI get_origcol_name_func)(lprec *lp, int colnr); typedef char * (__WINAPI get_origrow_name_func)(lprec *lp, int rownr); typedef void (__WINAPI get_partialprice_func)(lprec *lp, int *blockcount, int *blockstart, MYBOOL isrow); typedef int (__WINAPI get_pivoting_func)(lprec *lp); typedef int (__WINAPI get_presolve_func)(lprec *lp); typedef int (__WINAPI get_presolveloops_func)(lprec *lp); typedef MYBOOL (__WINAPI get_primal_solution_func)(lprec *lp, REAL *pv); typedef int (__WINAPI get_print_sol_func)(lprec *lp); typedef MYBOOL (__WINAPI get_pseudocosts_func)(lprec *lp, REAL *clower, REAL *cupper, int *updatelimit); typedef MYBOOL (__WINAPI get_ptr_constraints_func)(lprec *lp, REAL **constr); typedef MYBOOL (__WINAPI get_ptr_dual_solution_func)(lprec *lp, REAL **rc); typedef MYBOOL (__WINAPI get_ptr_lambda_func)(lprec *lp, REAL **lambda); typedef MYBOOL (__WINAPI get_ptr_primal_solution_func)(lprec *lp, REAL **pv); typedef MYBOOL (__WINAPI get_ptr_sensitivity_obj_func)(lprec *lp, REAL **objfrom, REAL **objtill); typedef MYBOOL (__WINAPI get_ptr_sensitivity_objex_func)(lprec *lp, REAL **objfrom, REAL **objtill, REAL **objfromvalue, REAL **objtillvalue); typedef MYBOOL (__WINAPI get_ptr_sensitivity_rhs_func)(lprec *lp, REAL **duals, REAL **dualsfrom, REAL **dualstill); typedef MYBOOL (__WINAPI get_ptr_variables_func)(lprec *lp, REAL **var); typedef REAL (__WINAPI get_rh_func)(lprec *lp, int rownr); typedef REAL (__WINAPI get_rh_range_func)(lprec *lp, int rownr); typedef int (__WINAPI get_rowex_func)(lprec *lp, int rownr, REAL *row, int *colno); typedef MYBOOL (__WINAPI get_row_func)(lprec *lp, int rownr, REAL *row); typedef char * (__WINAPI get_row_name_func)(lprec *lp, int rownr); typedef REAL (__WINAPI get_scalelimit_func)(lprec *lp); typedef int (__WINAPI get_scaling_func)(lprec *lp); typedef MYBOOL (__WINAPI get_sensitivity_obj_func)(lprec *lp, REAL *objfrom, REAL *objtill); typedef MYBOOL (__WINAPI get_sensitivity_objex_func)(lprec *lp, REAL *objfrom, REAL *objtill, REAL *objfromvalue, REAL *objtillvalue); typedef MYBOOL (__WINAPI get_sensitivity_rhs_func)(lprec *lp, REAL *duals, REAL *dualsfrom, REAL *dualstill); typedef int (__WINAPI get_simplextype_func)(lprec *lp); typedef int (__WINAPI get_solutioncount_func)(lprec *lp); typedef int (__WINAPI get_solutionlimit_func)(lprec *lp); typedef int (__WINAPI get_status_func)(lprec *lp); typedef char * (__WINAPI get_statustext_func)(lprec *lp, int statuscode); typedef long (__WINAPI get_timeout_func)(lprec *lp); typedef COUNTER (__WINAPI get_total_iter_func)(lprec *lp); typedef COUNTER (__WINAPI get_total_nodes_func)(lprec *lp); typedef REAL (__WINAPI get_upbo_func)(lprec *lp, int colnr); typedef int (__WINAPI get_var_branch_func)(lprec *lp, int colnr); typedef REAL (__WINAPI get_var_dualresult_func)(lprec *lp, int index); typedef REAL (__WINAPI get_var_primalresult_func)(lprec *lp, int index); typedef int (__WINAPI get_var_priority_func)(lprec *lp, int colnr); typedef MYBOOL (__WINAPI get_variables_func)(lprec *lp, REAL *var); typedef int (__WINAPI get_verbose_func)(lprec *lp); typedef MYBOOL (__WINAPI guess_basis_func)(lprec *lp, REAL *guessvector, int *basisvector); typedef REAL (__WINAPI get_working_objective_func)(lprec *lp); typedef MYBOOL (__WINAPI has_BFP_func)(lprec *lp); typedef MYBOOL (__WINAPI has_XLI_func)(lprec *lp); typedef MYBOOL (__WINAPI is_add_rowmode_func)(lprec *lp); typedef MYBOOL (__WINAPI is_anti_degen_func)(lprec *lp, int testmask); typedef MYBOOL (__WINAPI is_binary_func)(lprec *lp, int colnr); typedef MYBOOL (__WINAPI is_break_at_first_func)(lprec *lp); typedef MYBOOL (__WINAPI is_constr_type_func)(lprec *lp, int rownr, int mask); typedef MYBOOL (__WINAPI is_debug_func)(lprec *lp); typedef MYBOOL (__WINAPI is_feasible_func)(lprec *lp, REAL *values, REAL threshold); typedef MYBOOL (__WINAPI is_unbounded_func)(lprec *lp, int colnr); typedef MYBOOL (__WINAPI is_infinite_func)(lprec *lp, REAL value); typedef MYBOOL (__WINAPI is_int_func)(lprec *lp, int column); typedef MYBOOL (__WINAPI is_integerscaling_func)(lprec *lp); typedef MYBOOL (__WINAPI is_lag_trace_func)(lprec *lp); typedef MYBOOL (__WINAPI is_maxim_func)(lprec *lp); typedef MYBOOL (__WINAPI is_nativeBFP_func)(lprec *lp); typedef MYBOOL (__WINAPI is_nativeXLI_func)(lprec *lp); typedef MYBOOL (__WINAPI is_negative_func)(lprec *lp, int colnr); typedef MYBOOL (__WINAPI is_obj_in_basis_func)(lprec *lp); typedef MYBOOL (__WINAPI is_piv_mode_func)(lprec *lp, int testmask); typedef MYBOOL (__WINAPI is_piv_rule_func)(lprec *lp, int rule); typedef MYBOOL (__WINAPI is_presolve_func)(lprec *lp, int testmask); typedef MYBOOL (__WINAPI is_scalemode_func)(lprec *lp, int testmask); typedef MYBOOL (__WINAPI is_scaletype_func)(lprec *lp, int scaletype); typedef MYBOOL (__WINAPI is_semicont_func)(lprec *lp, int colnr); typedef MYBOOL (__WINAPI is_SOS_var_func)(lprec *lp, int colnr); typedef MYBOOL (__WINAPI is_trace_func)(lprec *lp); typedef void (__WINAPI lp_solve_version_func)(int *majorversion, int *minorversion, int *release, int *build); typedef lprec * (__WINAPI make_lp_func)(int rows, int columns); typedef void (__WINAPI print_constraints_func)(lprec *lp, int columns); typedef MYBOOL (__WINAPI print_debugdump_func)(lprec *lp, char *filename); typedef void (__WINAPI print_duals_func)(lprec *lp); typedef void (__WINAPI print_lp_func)(lprec *lp); typedef void (__WINAPI print_objective_func)(lprec *lp); typedef void (__WINAPI print_scales_func)(lprec *lp); typedef void (__WINAPI print_solution_func)(lprec *lp, int columns); typedef void (__WINAPI print_str_func)(lprec *lp, char *str); typedef void (__WINAPI print_tableau_func)(lprec *lp); typedef void (__WINAPI put_abortfunc_func)(lprec *lp, lphandle_intfunc newctrlc, void *ctrlchandle); typedef void (__WINAPI put_bb_nodefunc_func)(lprec *lp, lphandleint_intfunc newnode, void *bbnodehandle); typedef void (__WINAPI put_bb_branchfunc_func)(lprec *lp, lphandleint_intfunc newbranch, void *bbbranchhandle); typedef void (__WINAPI put_logfunc_func)(lprec *lp, lphandlestr_func newlog, void *loghandle); typedef void (__WINAPI put_msgfunc_func)(lprec *lp, lphandleint_func newmsg, void *msghandle, int mask); typedef lprec * (__WINAPI read_LP_func)(char *filename, int verbose, char *lp_name); typedef lprec * (__WINAPI read_MPS_func)(char *filename, int options); typedef lprec * (__WINAPI read_XLI_func)(char *xliname, char *modelname, char *dataname, char *options, int verbose); typedef MYBOOL (__WINAPI read_basis_func)(lprec *lp, char *filename, char *info); typedef void (__WINAPI reset_basis_func)(lprec *lp); typedef MYBOOL (__WINAPI read_params_func)(lprec *lp, char *filename, char *options); typedef void (__WINAPI reset_params_func)(lprec *lp); typedef MYBOOL (__WINAPI resize_lp_func)(lprec *lp, int rows, int columns); typedef MYBOOL (__WINAPI set_add_rowmode_func)(lprec *lp, MYBOOL turnon); typedef void (__WINAPI set_anti_degen_func)(lprec *lp, int anti_degen); typedef int (__WINAPI set_basisvar_func)(lprec *lp, int basisPos, int enteringCol); typedef MYBOOL (__WINAPI set_basis_func)(lprec *lp, int *bascolumn, MYBOOL nonbasic); typedef void (__WINAPI set_basiscrash_func)(lprec *lp, int mode); typedef void (__WINAPI set_bb_depthlimit_func)(lprec *lp, int bb_maxlevel); typedef void (__WINAPI set_bb_floorfirst_func)(lprec *lp, int bb_floorfirst); typedef void (__WINAPI set_bb_rule_func)(lprec *lp, int bb_rule); typedef MYBOOL (__WINAPI set_BFP_func)(lprec *lp, char *filename); typedef MYBOOL (__WINAPI set_binary_func)(lprec *lp, int colnr, MYBOOL must_be_bin); typedef MYBOOL (__WINAPI set_bounds_func)(lprec *lp, int colnr, REAL lower, REAL upper); typedef void (__WINAPI set_bounds_tighter_func)(lprec *lp, MYBOOL tighten); typedef void (__WINAPI set_break_at_first_func)(lprec *lp, MYBOOL break_at_first); typedef void (__WINAPI set_break_at_value_func)(lprec *lp, REAL break_at_value); typedef MYBOOL (__WINAPI set_column_func)(lprec *lp, int colnr, REAL *column); typedef MYBOOL (__WINAPI set_columnex_func)(lprec *lp, int colnr, int count, REAL *column, int *rowno); typedef MYBOOL (__WINAPI set_col_name_func)(lprec *lp, int colnr, char *new_name); typedef MYBOOL (__WINAPI set_constr_type_func)(lprec *lp, int rownr, int con_type); typedef void (__WINAPI set_debug_func)(lprec *lp, MYBOOL debug); typedef void (__WINAPI set_epsb_func)(lprec *lp, REAL epsb); typedef void (__WINAPI set_epsd_func)(lprec *lp, REAL epsd); typedef void (__WINAPI set_epsel_func)(lprec *lp, REAL epsel); typedef void (__WINAPI set_epsint_func)(lprec *lp, REAL epsint); typedef MYBOOL (__WINAPI set_epslevel_func)(lprec *lp, int epslevel); typedef void (__WINAPI set_epsperturb_func)(lprec *lp, REAL epsperturb); typedef void (__WINAPI set_epspivot_func)(lprec *lp, REAL epspivot); typedef MYBOOL (__WINAPI set_unbounded_func)(lprec *lp, int colnr); typedef void (__WINAPI set_improve_func)(lprec *lp, int improve); typedef void (__WINAPI set_infinite_func)(lprec *lp, REAL infinite); typedef MYBOOL (__WINAPI set_int_func)(lprec *lp, int colnr, MYBOOL must_be_int); typedef void (__WINAPI set_lag_trace_func)(lprec *lp, MYBOOL lag_trace); typedef MYBOOL (__WINAPI set_lowbo_func)(lprec *lp, int colnr, REAL value); typedef MYBOOL (__WINAPI set_lp_name_func)(lprec *lp, char *lpname); typedef MYBOOL (__WINAPI set_mat_func)(lprec *lp, int row, int column, REAL value); typedef void (__WINAPI set_maxim_func)(lprec *lp); typedef void (__WINAPI set_maxpivot_func)(lprec *lp, int max_num_inv); typedef void (__WINAPI set_minim_func)(lprec *lp); typedef void (__WINAPI set_mip_gap_func)(lprec *lp, MYBOOL absolute, REAL mip_gap); typedef MYBOOL (__WINAPI set_multiprice_func)(lprec *lp, int multiblockdiv); typedef void (__WINAPI set_negrange_func)(lprec *lp, REAL negrange); typedef MYBOOL (__WINAPI set_obj_func)(lprec *lp, int colnr, REAL value); typedef void (__WINAPI set_obj_bound_func)(lprec *lp, REAL obj_bound); typedef MYBOOL (__WINAPI set_obj_fn_func)(lprec *lp, REAL *row); typedef MYBOOL (__WINAPI set_obj_fnex_func)(lprec *lp, int count, REAL *row, int *colno); typedef void (__WINAPI set_obj_in_basis_func)(lprec *lp, MYBOOL obj_in_basis); typedef MYBOOL (__WINAPI set_outputfile_func)(lprec *lp, char *filename); typedef void (__WINAPI set_outputstream_func)(lprec *lp, FILE *stream); typedef MYBOOL (__WINAPI set_partialprice_func)(lprec *lp, int blockcount, int *blockstart, MYBOOL isrow); typedef void (__WINAPI set_pivoting_func)(lprec *lp, int piv_rule); typedef void (__WINAPI set_preferdual_func)(lprec *lp, MYBOOL dodual); typedef void (__WINAPI set_presolve_func)(lprec *lp, int presolvemode, int maxloops); typedef void (__WINAPI set_print_sol_func)(lprec *lp, int print_sol); typedef MYBOOL (__WINAPI set_pseudocosts_func)(lprec *lp, REAL *clower, REAL *cupper, int *updatelimit); typedef MYBOOL (__WINAPI set_rh_func)(lprec *lp, int rownr, REAL value); typedef MYBOOL (__WINAPI set_rh_range_func)(lprec *lp, int rownr, REAL deltavalue); typedef void (__WINAPI set_rh_vec_func)(lprec *lp, REAL *rh); typedef MYBOOL (__WINAPI set_row_func)(lprec *lp, int rownr, REAL *row); typedef MYBOOL (__WINAPI set_rowex_func)(lprec *lp, int rownr, int count, REAL *row, int *colno); typedef MYBOOL (__WINAPI set_row_name_func)(lprec *lp, int rownr, char *new_name); typedef void (__WINAPI set_scalelimit_func)(lprec *lp, REAL scalelimit); typedef void (__WINAPI set_scaling_func)(lprec *lp, int scalemode); typedef MYBOOL (__WINAPI set_semicont_func)(lprec *lp, int colnr, MYBOOL must_be_sc); typedef void (__WINAPI set_sense_func)(lprec *lp, MYBOOL maximize); typedef void (__WINAPI set_simplextype_func)(lprec *lp, int simplextype); typedef void (__WINAPI set_solutionlimit_func)(lprec *lp, int limit); typedef void (__WINAPI set_timeout_func)(lprec *lp, long sectimeout); typedef void (__WINAPI set_trace_func)(lprec *lp, MYBOOL trace); typedef MYBOOL (__WINAPI set_upbo_func)(lprec *lp, int colnr, REAL value); typedef MYBOOL (__WINAPI set_var_branch_func)(lprec *lp, int colnr, int branch_mode); typedef MYBOOL (__WINAPI set_var_weights_func)(lprec *lp, REAL *weights); typedef void (__WINAPI set_verbose_func)(lprec *lp, int verbose); typedef MYBOOL (__WINAPI set_XLI_func)(lprec *lp, char *filename); typedef int (__WINAPI solve_func)(lprec *lp); typedef MYBOOL (__WINAPI str_add_column_func)(lprec *lp, char *col_string); typedef MYBOOL (__WINAPI str_add_constraint_func)(lprec *lp, char *row_string ,int constr_type, REAL rh); typedef MYBOOL (__WINAPI str_add_lag_con_func)(lprec *lp, char *row_string, int con_type, REAL rhs); typedef MYBOOL (__WINAPI str_set_obj_fn_func)(lprec *lp, char *row_string); typedef MYBOOL (__WINAPI str_set_rh_vec_func)(lprec *lp, char *rh_string); typedef REAL (__WINAPI time_elapsed_func)(lprec *lp); typedef void (__WINAPI unscale_func)(lprec *lp); typedef MYBOOL (__WINAPI write_lp_func)(lprec *lp, char *filename); typedef MYBOOL (__WINAPI write_LP_func)(lprec *lp, FILE *output); typedef MYBOOL (__WINAPI write_mps_func)(lprec *lp, char *filename); typedef MYBOOL (__WINAPI write_MPS_func)(lprec *lp, FILE *output); typedef MYBOOL (__WINAPI write_freemps_func)(lprec *lp, char *filename); typedef MYBOOL (__WINAPI write_freeMPS_func)(lprec *lp, FILE *output); typedef MYBOOL (__WINAPI write_XLI_func)(lprec *lp, char *filename, char *options, MYBOOL results); typedef MYBOOL (__WINAPI write_basis_func)(lprec *lp, char *filename); typedef MYBOOL (__WINAPI write_params_func)(lprec *lp, char *filename, char *options); /* Prototypes for callbacks from basis inverse/factorization libraries */ /* ------------------------------------------------------------------------- */ typedef MYBOOL (__WINAPI userabortfunc)(lprec *lp, int level); typedef void (__VACALL reportfunc)(lprec *lp, int level, char *format, ...); typedef char * (__VACALL explainfunc)(lprec *lp, char *format, ...); typedef int (__WINAPI getvectorfunc)(lprec *lp, int varin, REAL *pcol, int *nzlist, int *maxabs); typedef int (__WINAPI getpackedfunc)(lprec *lp, int j, int rn[], double bj[]); typedef REAL (__WINAPI get_OF_activefunc)(lprec *lp, int varnr, REAL mult); typedef int (__WINAPI getMDOfunc)(lprec *lp, MYBOOL *usedpos, int *colorder, int *size, MYBOOL symmetric); typedef MYBOOL (__WINAPI invertfunc)(lprec *lp, MYBOOL shiftbounds, MYBOOL final); typedef void (__WINAPI set_actionfunc)(int *actionvar, int actionmask); typedef MYBOOL (__WINAPI is_actionfunc)(int actionvar, int testmask); typedef void (__WINAPI clear_actionfunc)(int *actionvar, int actionmask); /* Prototypes for basis inverse/factorization libraries */ /* ------------------------------------------------------------------------- */ typedef char *(BFP_CALLMODEL BFPchar)(void); typedef void (BFP_CALLMODEL BFP_lp)(lprec *lp); typedef void (BFP_CALLMODEL BFP_lpint)(lprec *lp, int newsize); typedef int (BFP_CALLMODEL BFPint_lp)(lprec *lp); typedef int (BFP_CALLMODEL BFPint_lpint)(lprec *lp, int kind); typedef REAL (BFP_CALLMODEL BFPreal_lp)(lprec *lp); typedef REAL *(BFP_CALLMODEL BFPrealp_lp)(lprec *lp); typedef void (BFP_CALLMODEL BFP_lpbool)(lprec *lp, MYBOOL maximum); typedef int (BFP_CALLMODEL BFPint_lpbool)(lprec *lp, MYBOOL maximum); typedef int (BFP_CALLMODEL BFPint_lpintintboolbool)(lprec *lp, int uservars, int Bsize, MYBOOL *usedpos, MYBOOL final); typedef void (BFP_CALLMODEL BFP_lprealint)(lprec *lp, REAL *pcol, int *nzidx); typedef void (BFP_CALLMODEL BFP_lprealintrealint)(lprec *lp, REAL *prow, int *pnzidx, REAL *drow, int *dnzidx); typedef MYBOOL (BFP_CALLMODEL BFPbool_lp)(lprec *lp); typedef MYBOOL (BFP_CALLMODEL BFPbool_lpbool)(lprec *lp, MYBOOL changesign); typedef MYBOOL (BFP_CALLMODEL BFPbool_lpint)(lprec *lp, int size); typedef MYBOOL (BFP_CALLMODEL BFPbool_lpintintchar)(lprec *lp, int size, int deltasize, char *options); typedef MYBOOL (BFP_CALLMODEL BFPbool_lpintintint)(lprec *lp, int size, int deltasize, int sizeofvar); typedef LREAL (BFP_CALLMODEL BFPlreal_lpintintreal)(lprec *lp, int row_nr, int col_nr, REAL *pcol); typedef REAL (BFP_CALLMODEL BFPreal_lplrealreal)(lprec *lp, LREAL theta, REAL *pcol); typedef int (BFP_CALLMODEL getcolumnex_func)(lprec *lp, int colnr, REAL *nzvalues, int *nzrows, int *mapin); typedef int (BFP_CALLMODEL BFPint_lpintrealcbintint)(lprec *lp, int items, getcolumnex_func cb, int *maprow, int*mapcol); /* Prototypes for external language libraries */ /* ------------------------------------------------------------------------- */ typedef char *(XLI_CALLMODEL XLIchar)(void); typedef MYBOOL (XLI_CALLMODEL XLIbool_lpintintint)(lprec* lp, int size, int deltasize, int sizevar); typedef MYBOOL (XLI_CALLMODEL XLIbool_lpcharcharcharint)(lprec *lp, char *modelname, char *dataname, char *options, int verbose); typedef MYBOOL (XLI_CALLMODEL XLIbool_lpcharcharbool)(lprec *lp, char *filename, char *options, MYBOOL results); /* Main lp_solve prototypes and function definitions */ /* ------------------------------------------------------------------------- */ struct _lprec { /* Full list of exported functions made available in a quasi object-oriented fashion */ add_column_func *add_column; add_columnex_func *add_columnex; add_constraint_func *add_constraint; add_constraintex_func *add_constraintex; add_lag_con_func *add_lag_con; add_SOS_func *add_SOS; column_in_lp_func *column_in_lp; copy_lp_func *copy_lp; default_basis_func *default_basis; del_column_func *del_column; del_constraint_func *del_constraint; delete_lp_func *delete_lp; dualize_lp_func *dualize_lp; free_lp_func *free_lp; get_anti_degen_func *get_anti_degen; get_basis_func *get_basis; get_basiscrash_func *get_basiscrash; get_bb_depthlimit_func *get_bb_depthlimit; get_bb_floorfirst_func *get_bb_floorfirst; get_bb_rule_func *get_bb_rule; get_bounds_tighter_func *get_bounds_tighter; get_break_at_value_func *get_break_at_value; get_col_name_func *get_col_name; get_columnex_func *get_columnex; get_constr_type_func *get_constr_type; get_constr_value_func *get_constr_value; get_constraints_func *get_constraints; get_dual_solution_func *get_dual_solution; get_epsb_func *get_epsb; get_epsd_func *get_epsd; get_epsel_func *get_epsel; get_epsint_func *get_epsint; get_epsperturb_func *get_epsperturb; get_epspivot_func *get_epspivot; get_improve_func *get_improve; get_infinite_func *get_infinite; get_lambda_func *get_lambda; get_lowbo_func *get_lowbo; get_lp_index_func *get_lp_index; get_lp_name_func *get_lp_name; get_Lrows_func *get_Lrows; get_mat_func *get_mat; get_mat_byindex_func *get_mat_byindex; get_max_level_func *get_max_level; get_maxpivot_func *get_maxpivot; get_mip_gap_func *get_mip_gap; get_multiprice_func *get_multiprice; get_nameindex_func *get_nameindex; get_Ncolumns_func *get_Ncolumns; get_negrange_func *get_negrange; get_nz_func *get_nonzeros; get_Norig_columns_func *get_Norig_columns; get_Norig_rows_func *get_Norig_rows; get_Nrows_func *get_Nrows; get_obj_bound_func *get_obj_bound; get_objective_func *get_objective; get_orig_index_func *get_orig_index; get_origcol_name_func *get_origcol_name; get_origrow_name_func *get_origrow_name; get_partialprice_func *get_partialprice; get_pivoting_func *get_pivoting; get_presolve_func *get_presolve; get_presolveloops_func *get_presolveloops; get_primal_solution_func *get_primal_solution; get_print_sol_func *get_print_sol; get_pseudocosts_func *get_pseudocosts; get_ptr_constraints_func *get_ptr_constraints; get_ptr_dual_solution_func *get_ptr_dual_solution; get_ptr_lambda_func *get_ptr_lambda; get_ptr_primal_solution_func *get_ptr_primal_solution; get_ptr_sensitivity_obj_func *get_ptr_sensitivity_obj; get_ptr_sensitivity_objex_func *get_ptr_sensitivity_objex; get_ptr_sensitivity_rhs_func *get_ptr_sensitivity_rhs; get_ptr_variables_func *get_ptr_variables; get_rh_func *get_rh; get_rh_range_func *get_rh_range; get_row_func *get_row; get_rowex_func *get_rowex; get_row_name_func *get_row_name; get_scalelimit_func *get_scalelimit; get_scaling_func *get_scaling; get_sensitivity_obj_func *get_sensitivity_obj; get_sensitivity_objex_func *get_sensitivity_objex; get_sensitivity_rhs_func *get_sensitivity_rhs; get_simplextype_func *get_simplextype; get_solutioncount_func *get_solutioncount; get_solutionlimit_func *get_solutionlimit; get_status_func *get_status; get_statustext_func *get_statustext; get_timeout_func *get_timeout; get_total_iter_func *get_total_iter; get_total_nodes_func *get_total_nodes; get_upbo_func *get_upbo; get_var_branch_func *get_var_branch; get_var_dualresult_func *get_var_dualresult; get_var_primalresult_func *get_var_primalresult; get_var_priority_func *get_var_priority; get_variables_func *get_variables; get_verbose_func *get_verbose; get_working_objective_func *get_working_objective; has_BFP_func *has_BFP; has_XLI_func *has_XLI; is_add_rowmode_func *is_add_rowmode; is_anti_degen_func *is_anti_degen; is_binary_func *is_binary; is_break_at_first_func *is_break_at_first; is_constr_type_func *is_constr_type; is_debug_func *is_debug; is_feasible_func *is_feasible; is_infinite_func *is_infinite; is_int_func *is_int; is_integerscaling_func *is_integerscaling; is_lag_trace_func *is_lag_trace; is_maxim_func *is_maxim; is_nativeBFP_func *is_nativeBFP; is_nativeXLI_func *is_nativeXLI; is_negative_func *is_negative; is_obj_in_basis_func *is_obj_in_basis; is_piv_mode_func *is_piv_mode; is_piv_rule_func *is_piv_rule; is_presolve_func *is_presolve; is_scalemode_func *is_scalemode; is_scaletype_func *is_scaletype; is_semicont_func *is_semicont; is_SOS_var_func *is_SOS_var; is_trace_func *is_trace; is_unbounded_func *is_unbounded; is_use_names_func *is_use_names; lp_solve_version_func *lp_solve_version; make_lp_func *make_lp; print_constraints_func *print_constraints; print_debugdump_func *print_debugdump; print_duals_func *print_duals; print_lp_func *print_lp; print_objective_func *print_objective; print_scales_func *print_scales; print_solution_func *print_solution; print_str_func *print_str; print_tableau_func *print_tableau; put_abortfunc_func *put_abortfunc; put_bb_nodefunc_func *put_bb_nodefunc; put_bb_branchfunc_func *put_bb_branchfunc; put_logfunc_func *put_logfunc; put_msgfunc_func *put_msgfunc; read_LP_func *read_LP; read_MPS_func *read_MPS; read_XLI_func *read_XLI; read_params_func *read_params; read_basis_func *read_basis; reset_basis_func *reset_basis; reset_params_func *reset_params; resize_lp_func *resize_lp; set_add_rowmode_func *set_add_rowmode; set_anti_degen_func *set_anti_degen; set_basisvar_func *set_basisvar; set_basis_func *set_basis; set_basiscrash_func *set_basiscrash; set_bb_depthlimit_func *set_bb_depthlimit; set_bb_floorfirst_func *set_bb_floorfirst; set_bb_rule_func *set_bb_rule; set_BFP_func *set_BFP; set_binary_func *set_binary; set_bounds_func *set_bounds; set_bounds_tighter_func *set_bounds_tighter; set_break_at_first_func *set_break_at_first; set_break_at_value_func *set_break_at_value; set_column_func *set_column; set_columnex_func *set_columnex; set_col_name_func *set_col_name; set_constr_type_func *set_constr_type; set_debug_func *set_debug; set_epsb_func *set_epsb; set_epsd_func *set_epsd; set_epsel_func *set_epsel; set_epsint_func *set_epsint; set_epslevel_func *set_epslevel; set_epsperturb_func *set_epsperturb; set_epspivot_func *set_epspivot; set_unbounded_func *set_unbounded; set_improve_func *set_improve; set_infinite_func *set_infinite; set_int_func *set_int; set_lag_trace_func *set_lag_trace; set_lowbo_func *set_lowbo; set_lp_name_func *set_lp_name; set_mat_func *set_mat; set_maxim_func *set_maxim; set_maxpivot_func *set_maxpivot; set_minim_func *set_minim; set_mip_gap_func *set_mip_gap; set_multiprice_func *set_multiprice; set_negrange_func *set_negrange; set_obj_bound_func *set_obj_bound; set_obj_fn_func *set_obj_fn; set_obj_fnex_func *set_obj_fnex; set_obj_func *set_obj; set_obj_in_basis_func *set_obj_in_basis; set_outputfile_func *set_outputfile; set_outputstream_func *set_outputstream; set_partialprice_func *set_partialprice; set_pivoting_func *set_pivoting; set_preferdual_func *set_preferdual; set_presolve_func *set_presolve; set_print_sol_func *set_print_sol; set_pseudocosts_func *set_pseudocosts; set_rh_func *set_rh; set_rh_range_func *set_rh_range; set_rh_vec_func *set_rh_vec; set_row_func *set_row; set_rowex_func *set_rowex; set_row_name_func *set_row_name; set_scalelimit_func *set_scalelimit; set_scaling_func *set_scaling; set_semicont_func *set_semicont; set_sense_func *set_sense; set_simplextype_func *set_simplextype; set_solutionlimit_func *set_solutionlimit; set_timeout_func *set_timeout; set_trace_func *set_trace; set_upbo_func *set_upbo; set_use_names_func *set_use_names; set_var_branch_func *set_var_branch; set_var_weights_func *set_var_weights; set_verbose_func *set_verbose; set_XLI_func *set_XLI; solve_func *solve; str_add_column_func *str_add_column; str_add_constraint_func *str_add_constraint; str_add_lag_con_func *str_add_lag_con; str_set_obj_fn_func *str_set_obj_fn; str_set_rh_vec_func *str_set_rh_vec; time_elapsed_func *time_elapsed; unscale_func *unscale; write_lp_func *write_lp; write_LP_func *write_LP; write_mps_func *write_mps; write_MPS_func *write_MPS; write_freemps_func *write_freemps; write_freeMPS_func *write_freeMPS; write_XLI_func *write_XLI; write_basis_func *write_basis; write_params_func *write_params; /* Spacer */ int *alignmentspacer; /* Problem description */ char *lp_name; /* The name of the model */ /* Problem sizes */ int sum; /* The total number of variables, including slacks */ int rows; int columns; int equalities; /* No of non-Lagrangean equality constraints in the problem */ int boundedvars; /* Count of bounded variables */ int INTfuture1; /* Memory allocation sizes */ int sum_alloc; /* The allocated memory for row+column-sized data */ int rows_alloc; /* The allocated memory for row-sized data */ int columns_alloc; /* The allocated memory for column-sized data */ /* Model status and solver result variables */ MYBOOL source_is_file; /* The base model was read from a file */ MYBOOL model_is_pure; /* The model has been built entirely from row and column additions */ MYBOOL model_is_valid; /* Has this lp pased the 'test' */ MYBOOL tighten_on_set; /* Specify if bounds will be tightened or overriden at bound setting */ MYBOOL names_used; /* Flag to indicate if names for rows and columns are used */ MYBOOL use_row_names; /* Flag to indicate if names for rows are used */ MYBOOL use_col_names; /* Flag to indicate if names for columns are used */ MYBOOL lag_trace; /* Print information on Lagrange progression */ MYBOOL spx_trace; /* Print information on simplex progression */ MYBOOL bb_trace; /* TRUE to print extra debug information */ MYBOOL streamowned; /* TRUE if the handle should be closed at delete_lp() */ MYBOOL obj_in_basis; /* TRUE if the objective function is in the basis matrix */ int spx_status; /* Simplex solver feasibility/mode code */ int lag_status; /* Extra status variable for lag_solve */ int solutioncount; /* number of equal-valued solutions found (up to solutionlimit) */ int solutionlimit; /* upper number of equal-valued solutions kept track of */ REAL real_solution; /* Optimal non-MIP solution base */ REAL *solution; /* sum_alloc+1 : Solution array of the next to optimal LP, Index 0 : Objective function value, Indeces 1..rows : Slack variable values, Indeced rows+1..sum : Variable values */ REAL *best_solution; /* sum_alloc+1 : Solution array of optimal 'Integer' LP, structured as the solution array above */ REAL *full_solution; /* sum_alloc+1 : Final solution array expanded for deleted variables */ REAL *edgeVector; /* Array of reduced cost scaling norms (DEVEX and Steepest Edge) */ REAL *drow; /* sum+1: Reduced costs of the last simplex */ int *nzdrow; /* sum+1: Indeces of non-zero reduced costs of the last simplex */ REAL *duals; /* rows_alloc+1 : The dual variables of the last LP */ REAL *full_duals; /* sum_alloc+1: Final duals array expanded for deleted variables */ REAL *dualsfrom; /* sum_alloc+1 :The sensitivity on dual variables/reduced costs of the last LP */ REAL *dualstill; /* sum_alloc+1 :The sensitivity on dual variables/reduced costs of the last LP */ REAL *objfrom; /* columns_alloc+1 :The sensitivity on objective function of the last LP */ REAL *objtill; /* columns_alloc+1 :The sensitivity on objective function of the last LP */ REAL *objfromvalue; /* columns_alloc+1 :The value of the variables when objective value is at its from value of the last LP */ REAL *orig_obj; /* Unused pointer - Placeholder for OF not part of B */ REAL *obj; /* Special vector used to temporarily change the OF vector */ COUNTER current_iter; /* Number of iterations in the current/last simplex */ COUNTER total_iter; /* Number of iterations over all B&B steps */ COUNTER current_bswap; /* Number of bound swaps in the current/last simplex */ COUNTER total_bswap; /* Number of bount swaps over all B&B steps */ int solvecount; /* The number of solve() performed in this model */ int max_pivots; /* Number of pivots between refactorizations of the basis */ /* Various execution parameters */ int simplex_strategy; /* Set desired combination of primal and dual simplex algorithms */ int simplex_mode; /* Specifies the current simplex mode during solve; see simplex_strategy */ int verbose; /* Set amount of run-time messages and results */ int print_sol; /* TRUE to print optimal solution; AUTOMATIC skips zeros */ FILE *outstream; /* Output stream, initialized to STDOUT */ /* Main Branch and Bound settings */ MYBOOL *bb_varbranch; /* Determines branching strategy at the individual variable level; the setting here overrides the bb_floorfirst setting */ int piv_strategy; /* Strategy for selecting row and column entering/leaving */ int _piv_rule_; /* Internal working rule-part of piv_strategy above */ int bb_rule; /* Rule for selecting B&B variables */ MYBOOL bb_floorfirst; /* Set BRANCH_FLOOR for B&B to set variables to floor bound first; conversely with BRANCH_CEILING, the ceiling value is set first */ MYBOOL bb_breakfirst; /* TRUE to stop at first feasible solution */ MYBOOL _piv_left_; /* Internal variable indicating active pricing loop order */ MYBOOL BOOLfuture1; REAL scalelimit; /* Relative convergence criterion for iterated scaling */ int scalemode; /* OR-ed codes for data scaling */ int improve; /* Set to non-zero for iterative improvement */ int anti_degen; /* Anti-degen strategy (or none) TRUE to avoid cycling */ int do_presolve; /* PRESOLVE_ parameters for LP presolving */ int presolveloops; /* Maximum number of presolve loops */ int perturb_count; /* The number of bound relaxation retries performed */ /* Row and column names storage variables */ hashelem **row_name; /* rows_alloc+1 */ hashelem **col_name; /* columns_alloc+1 */ hashtable *rowname_hashtab; /* hash table to store row names */ hashtable *colname_hashtab; /* hash table to store column names */ /* Optionally specify continuous rows/column blocks for partial pricing */ partialrec *rowblocks; partialrec *colblocks; /* Row and column type codes */ MYBOOL *var_type; /* sum_alloc+1 : TRUE if variable must be integer */ /* Data for multiple pricing */ multirec *multivars; int multiblockdiv; /* The divisor used to set or augment pricing block */ /* Variable (column) parameters */ int fixedvars; /* The current number of basic fixed variables in the model */ int int_vars; /* Number of variables required to be integer */ int sc_vars; /* Number of semi-continuous variables */ REAL *sc_lobound; /* sum_columns+1 : TRUE if variable is semi-continuous; value replaced by conventional lower bound during solve */ int *var_is_free; /* columns+1: Index of twin variable if variable is free */ int *var_priority; /* columns: Priority-mapping of variables */ SOSgroup *GUB; /* Pointer to record containing GUBs */ int sos_vars; /* Number of variables in the sos_priority list */ int sos_ints; /* Number of integers in SOS'es above */ SOSgroup *SOS; /* Pointer to record containing all SOS'es */ int *sos_priority; /* Priority-sorted list of variables (no duplicates) */ /* Optionally specify list of active rows/columns used in multiple pricing */ REAL *bsolveVal; /* rows+1: bsolved solution vector for reduced costs */ int *bsolveIdx; /* rows+1: Non-zero indeces of bsolveVal */ /* RHS storage */ REAL *orig_rhs; /* rows_alloc+1 : The RHS after scaling and sign changing, but before 'Bound transformation' */ LREAL *rhs; /* rows_alloc+1 : The RHS of the current simplex tableau */ /* Row (constraint) parameters */ int *row_type; /* rows_alloc+1 : Row/constraint type coding */ /* Optionally specify data for dual long-step */ multirec *longsteps; /* Original and working row and variable bounds */ REAL *orig_upbo; /* sum_alloc+1 : Bound before transformations */ REAL *upbo; /* " " : Upper bound after transformation and B&B work */ REAL *orig_lowbo; /* " " */ REAL *lowbo; /* " " : Lower bound after transformation and B&B work */ /* User data and basis factorization matrices (ETA or LU, product form) */ MATrec *matA; INVrec *invB; /* Basis and bounds */ BBrec *bb_bounds; /* The linked list of B&B bounds */ BBrec *rootbounds; /* The bounds at the lowest B&B level */ basisrec *bb_basis; /* The linked list of B&B bases */ basisrec *rootbasis; OBJmonrec *monitor; /* Objective monitoring record for stalling/degeneracy handling */ /* Scaling parameters */ REAL *scalars; /* sum_alloc+1:0..Rows the scaling of the rows, Rows+1..Sum the scaling of the columns */ MYBOOL scaling_used; /* TRUE if scaling is used */ MYBOOL columns_scaled; /* TRUE if the columns are scaled too */ MYBOOL varmap_locked; /* Determines whether the var_to_orig and orig_to_var are fixed */ /* Variable state information */ MYBOOL basis_valid; /* TRUE is the basis is still valid */ int crashmode; /* Basis crashing mode (or none) */ int *var_basic; /* rows_alloc+1: The list of columns in the basis */ REAL *val_nonbasic; /* Array to store current values of non-basic variables */ MYBOOL *is_basic; /* sum_alloc+1: TRUE if the column is in the basis */ MYBOOL *is_lower; /* " " : TRUE if the variable is at its lower bound (or in the basis), FALSE otherwise */ /* Simplex basis indicators */ int *rejectpivot; /* List of unacceptable pivot choices due to division-by-zero */ BBPSrec *bb_PseudoCost; /* Data structure for costing of node branchings */ int bb_PseudoUpdates; /* Maximum number of updates for pseudo-costs */ int bb_strongbranches; /* The number of strong B&B branches performed */ int is_strongbranch; /* Are we currently in a strong branch mode? */ int bb_improvements; /* The number of discrete B&B objective improvement steps */ /* Solver working variables */ REAL rhsmax; /* The maximum |value| of the rhs vector at any iteration */ REAL suminfeas; /* The working sum of primal and dual infeasibilities */ REAL bigM; /* Original objective weighting in primal phase 1 */ REAL P1extraVal; /* Phase 1 OF/RHS offset for feasibility */ int P1extraDim; /* Phase 1 additional columns/rows for feasibility */ int spx_action; /* ACTION_ variables for the simplex routine */ MYBOOL spx_perturbed; /* The variable bounds were relaxed/perturbed into this simplex */ MYBOOL bb_break; /* Solver working variable; signals break of the B&B */ MYBOOL wasPreprocessed; /* The solve preprocessing was performed */ MYBOOL wasPresolved; /* The solve presolver was invoked */ int INTfuture2; /* Lagragean solver storage and parameters */ MATrec *matL; REAL *lag_rhs; /* Array of Lagrangean rhs vector */ int *lag_con_type; /* Array of GT, LT or EQ */ REAL *lambda; /* Lambda values (Lagrangean multipliers) */ REAL lag_bound; /* The Lagrangian lower OF bound */ REAL lag_accept; /* The Lagrangian convergence criterion */ /* Solver thresholds */ REAL infinite; /* Limit for dynamic range */ REAL negrange; /* Limit for negative variable range */ REAL epsmachine; /* Default machine accuracy */ REAL epsvalue; /* Input data precision / rounding of data values to 0 */ REAL epsprimal; /* For rounding RHS values to 0/infeasibility */ REAL epsdual; /* For rounding reduced costs to zero */ REAL epspivot; /* Pivot reject tolerance */ REAL epsperturb; /* Perturbation scalar */ REAL epssolution; /* The solution tolerance for final validation */ /* Branch & Bound working parameters */ int bb_status; /* Indicator that the last solvelp() gave an improved B&B solution */ int bb_level; /* Solver B&B working variable (recursion depth) */ int bb_maxlevel; /* The deepest B&B level of the last solution */ int bb_limitlevel; /* The maximum B&B level allowed */ COUNTER bb_totalnodes; /* Total number of nodes processed in B&B */ int bb_solutionlevel; /* The B&B level of the last / best solution */ int bb_cutpoolsize; /* Size of the B&B cut pool */ int bb_cutpoolused; /* Currently used cut pool */ int bb_constraintOF; /* General purpose B&B parameter (typically for testing) */ int *bb_cuttype; /* The type of the currently used cuts */ int *bb_varactive; /* The B&B state of the variable; 0 means inactive */ DeltaVrec *bb_upperchange; /* Changes to upper bounds during the B&B phase */ DeltaVrec *bb_lowerchange; /* Changes to lower bounds during the B&B phase */ REAL bb_deltaOF; /* Minimum OF step value; computed at beginning of solve() */ REAL bb_breakOF; /* User-settable value for the objective function deemed to be sufficiently good in an integer problem */ REAL bb_limitOF; /* "Dual" bound / limit to final optimal MIP solution */ REAL bb_heuristicOF; /* Set initial "at least better than" guess for objective function (can significantly speed up B&B iterations) */ REAL bb_parentOF; /* The OF value of the previous BB simplex */ REAL bb_workOF; /* The unadjusted OF value for the current best solution */ /* Internal work arrays allocated as required */ presolveundorec *presolve_undo; workarraysrec *workarrays; /* MIP parameters */ REAL epsint; /* Margin of error in determining if a float value is integer */ REAL mip_absgap; /* Absolute MIP gap */ REAL mip_relgap; /* Relative MIP gap */ /* Time/timer variables and extended status text */ double timecreate; double timestart; double timeheuristic; double timepresolved; double timeend; long sectimeout; /* Extended status message text set via explain() */ char *ex_status; /* Refactorization engine interface routines (for dynamic DLL/SO BFPs) */ #if LoadInverseLib == TRUE #ifdef WIN32 HINSTANCE hBFP; #else void *hBFP; #endif #endif BFPchar *bfp_name; BFPbool_lpintintint *bfp_compatible; BFPbool_lpintintchar *bfp_init; BFP_lp *bfp_free; BFPbool_lpint *bfp_resize; BFPint_lp *bfp_memallocated; BFPbool_lp *bfp_restart; BFPbool_lp *bfp_mustrefactorize; BFPint_lp *bfp_preparefactorization; BFPint_lpintintboolbool *bfp_factorize; BFP_lp *bfp_finishfactorization; BFP_lp *bfp_updaterefactstats; BFPlreal_lpintintreal *bfp_prepareupdate; BFPreal_lplrealreal *bfp_pivotRHS; BFPbool_lpbool *bfp_finishupdate; BFP_lprealint *bfp_ftran_prepare; BFP_lprealint *bfp_ftran_normal; BFP_lprealint *bfp_btran_normal; BFP_lprealintrealint *bfp_btran_double; BFPint_lp *bfp_status; BFPint_lpbool *bfp_nonzeros; BFPbool_lp *bfp_implicitslack; BFPint_lp *bfp_indexbase; BFPint_lp *bfp_rowoffset; BFPint_lp *bfp_pivotmax; BFPbool_lpint *bfp_pivotalloc; BFPint_lp *bfp_colcount; BFPbool_lp *bfp_canresetbasis; BFPreal_lp *bfp_efficiency; BFPrealp_lp *bfp_pivotvector; BFPint_lp *bfp_pivotcount; BFPint_lpint *bfp_refactcount; BFPbool_lp *bfp_isSetI; BFPint_lpintrealcbintint *bfp_findredundant; /* External language interface routines (for dynamic DLL/SO XLIs) */ #if LoadLanguageLib == TRUE #ifdef WIN32 HINSTANCE hXLI; #else void *hXLI; #endif #endif XLIchar *xli_name; XLIbool_lpintintint *xli_compatible; XLIbool_lpcharcharcharint *xli_readmodel; XLIbool_lpcharcharbool *xli_writemodel; /* Miscellaneous internal functions made available externally */ userabortfunc *userabort; reportfunc *report; explainfunc *explain; getvectorfunc *get_lpcolumn; getpackedfunc *get_basiscolumn; get_OF_activefunc *get_OF_active; getMDOfunc *getMDO; invertfunc *invert; set_actionfunc *set_action; is_actionfunc *is_action; clear_actionfunc *clear_action; /* User program interface callbacks */ lphandle_intfunc *ctrlc; void *ctrlchandle; /* User-specified "owner process ID" */ lphandlestr_func *writelog; void *loghandle; /* User-specified "owner process ID" */ lphandlestr_func *debuginfo; lphandleint_func *usermessage; int msgmask; void *msghandle; /* User-specified "owner process ID" */ lphandleint_intfunc *bb_usenode; void *bb_nodehandle; /* User-specified "owner process ID" */ lphandleint_intfunc *bb_usebranch; void *bb_branchhandle; /* User-specified "owner process ID" */ /* replacement of static variables */ char *rowcol_name; /* The name of a row/column */ }; #ifdef __cplusplus __EXTERN_C { #endif /* User and system function interfaces */ /* ------------------------------------------------------------------------- */ void __EXPORT_TYPE __WINAPI lp_solve_version(int *majorversion, int *minorversion, int *release, int *build); lprec __EXPORT_TYPE * __WINAPI make_lp(int rows, int columns); MYBOOL __EXPORT_TYPE __WINAPI resize_lp(lprec *lp, int rows, int columns); int __EXPORT_TYPE __WINAPI get_status(lprec *lp); char __EXPORT_TYPE * __WINAPI get_statustext(lprec *lp, int statuscode); MYBOOL __EXPORT_TYPE __WINAPI is_obj_in_basis(lprec *lp); void __EXPORT_TYPE __WINAPI set_obj_in_basis(lprec *lp, MYBOOL obj_in_basis); /* Create and initialise a lprec structure defaults */ lprec __EXPORT_TYPE * __WINAPI copy_lp(lprec *lp); MYBOOL __EXPORT_TYPE __WINAPI dualize_lp(lprec *lp); STATIC MYBOOL memopt_lp(lprec *lp, int rowextra, int colextra, int nzextra); /* Copy or dualize the lp */ void __EXPORT_TYPE __WINAPI delete_lp(lprec *lp); void __EXPORT_TYPE __WINAPI free_lp(lprec **plp); /* Remove problem from memory */ MYBOOL __EXPORT_TYPE __WINAPI set_lp_name(lprec *lp, char *lpname); char __EXPORT_TYPE * __WINAPI get_lp_name(lprec *lp); /* Set and get the problem name */ MYBOOL __EXPORT_TYPE __WINAPI has_BFP(lprec *lp); MYBOOL __EXPORT_TYPE __WINAPI is_nativeBFP(lprec *lp); MYBOOL __EXPORT_TYPE __WINAPI set_BFP(lprec *lp, char *filename); /* Set basis factorization engine */ lprec __EXPORT_TYPE * __WINAPI read_XLI(char *xliname, char *modelname, char *dataname, char *options, int verbose); MYBOOL __EXPORT_TYPE __WINAPI write_XLI(lprec *lp, char *filename, char *options, MYBOOL results); MYBOOL __EXPORT_TYPE __WINAPI has_XLI(lprec *lp); MYBOOL __EXPORT_TYPE __WINAPI is_nativeXLI(lprec *lp); MYBOOL __EXPORT_TYPE __WINAPI set_XLI(lprec *lp, char *filename); /* Set external language interface */ MYBOOL __EXPORT_TYPE __WINAPI set_obj(lprec *lp, int colnr, REAL value); MYBOOL __EXPORT_TYPE __WINAPI set_obj_fn(lprec *lp, REAL *row); MYBOOL __EXPORT_TYPE __WINAPI set_obj_fnex(lprec *lp, int count, REAL *row, int *colno); /* set the objective function (Row 0) of the matrix */ MYBOOL __EXPORT_TYPE __WINAPI str_set_obj_fn(lprec *lp, char *row_string); /* The same, but with string input */ void __EXPORT_TYPE __WINAPI set_sense(lprec *lp, MYBOOL maximize); void __EXPORT_TYPE __WINAPI set_maxim(lprec *lp); void __EXPORT_TYPE __WINAPI set_minim(lprec *lp); MYBOOL __EXPORT_TYPE __WINAPI is_maxim(lprec *lp); /* Set optimization direction for the objective function */ MYBOOL __EXPORT_TYPE __WINAPI add_constraint(lprec *lp, REAL *row, int constr_type, REAL rh); MYBOOL __EXPORT_TYPE __WINAPI add_constraintex(lprec *lp, int count, REAL *row, int *colno, int constr_type, REAL rh); MYBOOL __EXPORT_TYPE __WINAPI set_add_rowmode(lprec *lp, MYBOOL turnon); MYBOOL __EXPORT_TYPE __WINAPI is_add_rowmode(lprec *lp); /* Add a constraint to the problem, row is the constraint row, rh is the right hand side, constr_type is the type of constraint (LE (<=), GE(>=), EQ(=)) */ MYBOOL __EXPORT_TYPE __WINAPI str_add_constraint(lprec *lp, char *row_string, int constr_type, REAL rh); /* The same, but with string input */ MYBOOL __EXPORT_TYPE __WINAPI set_row(lprec *lp, int rownr, REAL *row); MYBOOL __EXPORT_TYPE __WINAPI set_rowex(lprec *lp, int rownr, int count, REAL *row, int *colno); MYBOOL __EXPORT_TYPE __WINAPI get_row(lprec *lp, int rownr, REAL *row); int __EXPORT_TYPE __WINAPI get_rowex(lprec *lp, int rownr, REAL *row, int *colno); /* Fill row with the row row_nr from the problem */ MYBOOL __EXPORT_TYPE __WINAPI del_constraint(lprec *lp, int rownr); STATIC MYBOOL del_constraintex(lprec *lp, LLrec *rowmap); /* Remove constrain nr del_row from the problem */ MYBOOL __EXPORT_TYPE __WINAPI add_lag_con(lprec *lp, REAL *row, int con_type, REAL rhs); /* add a Lagrangian constraint of form Row' x contype Rhs */ MYBOOL __EXPORT_TYPE __WINAPI str_add_lag_con(lprec *lp, char *row_string, int con_type, REAL rhs); /* The same, but with string input */ void __EXPORT_TYPE __WINAPI set_lag_trace(lprec *lp, MYBOOL lag_trace); MYBOOL __EXPORT_TYPE __WINAPI is_lag_trace(lprec *lp); /* Set debugging/tracing mode of the Lagrangean solver */ MYBOOL __EXPORT_TYPE __WINAPI set_constr_type(lprec *lp, int rownr, int con_type); int __EXPORT_TYPE __WINAPI get_constr_type(lprec *lp, int rownr); REAL __EXPORT_TYPE __WINAPI get_constr_value(lprec *lp, int rownr, int count, REAL *primsolution, int *nzindex); MYBOOL __EXPORT_TYPE __WINAPI is_constr_type(lprec *lp, int rownr, int mask); STATIC char *get_str_constr_type(lprec *lp, int con_type); STATIC int get_constr_class(lprec *lp, int rownr); STATIC char *get_str_constr_class(lprec *lp, int con_class); /* Set the type of constraint in row Row (LE, GE, EQ) */ MYBOOL __EXPORT_TYPE __WINAPI set_rh(lprec *lp, int rownr, REAL value); REAL __EXPORT_TYPE __WINAPI get_rh(lprec *lp, int rownr); /* Set and get the right hand side of a constraint row */ MYBOOL __EXPORT_TYPE __WINAPI set_rh_range(lprec *lp, int rownr, REAL deltavalue); REAL __EXPORT_TYPE __WINAPI get_rh_range(lprec *lp, int rownr); /* Set the RHS range; i.e. the lower and upper bounds of a constraint row */ void __EXPORT_TYPE __WINAPI set_rh_vec(lprec *lp, REAL *rh); /* Set the right hand side vector */ MYBOOL __EXPORT_TYPE __WINAPI str_set_rh_vec(lprec *lp, char *rh_string); /* The same, but with string input */ MYBOOL __EXPORT_TYPE __WINAPI add_column(lprec *lp, REAL *column); MYBOOL __EXPORT_TYPE __WINAPI add_columnex(lprec *lp, int count, REAL *column, int *rowno); MYBOOL __EXPORT_TYPE __WINAPI str_add_column(lprec *lp, char *col_string); /* Add a column to the problem */ MYBOOL __EXPORT_TYPE __WINAPI set_column(lprec *lp, int colnr, REAL *column); MYBOOL __EXPORT_TYPE __WINAPI set_columnex(lprec *lp, int colnr, int count, REAL *column, int *rowno); /* Overwrite existing column data */ int __EXPORT_TYPE __WINAPI column_in_lp(lprec *lp, REAL *column); /* Returns the column index if column is already present in lp, otherwise 0. (Does not look at bounds and types, only looks at matrix values */ int __EXPORT_TYPE __WINAPI get_columnex(lprec *lp, int colnr, REAL *column, int *nzrow); MYBOOL __EXPORT_TYPE __WINAPI get_column(lprec *lp, int colnr, REAL *column); /* Fill column with the column col_nr from the problem */ MYBOOL __EXPORT_TYPE __WINAPI del_column(lprec *lp, int colnr); STATIC MYBOOL del_columnex(lprec *lp, LLrec *colmap); /* Delete a column */ MYBOOL __EXPORT_TYPE __WINAPI set_mat(lprec *lp, int rownr, int colnr, REAL value); /* Fill in element (Row,Column) of the matrix Row in [0..Rows] and Column in [1..Columns] */ REAL __EXPORT_TYPE __WINAPI get_mat(lprec *lp, int rownr, int colnr); REAL __EXPORT_TYPE __WINAPI get_mat_byindex(lprec *lp, int matindex, MYBOOL isrow, MYBOOL adjustsign); int __EXPORT_TYPE __WINAPI get_nonzeros(lprec *lp); /* get a single element from the matrix */ /* Name changed from "mat_elm" by KE */ void __EXPORT_TYPE __WINAPI set_bounds_tighter(lprec *lp, MYBOOL tighten); MYBOOL get_bounds(lprec *lp, int column, REAL *lower, REAL *upper); MYBOOL __EXPORT_TYPE __WINAPI get_bounds_tighter(lprec *lp); MYBOOL __EXPORT_TYPE __WINAPI set_upbo(lprec *lp, int colnr, REAL value); REAL __EXPORT_TYPE __WINAPI get_upbo(lprec *lp, int colnr); MYBOOL __EXPORT_TYPE __WINAPI set_lowbo(lprec *lp, int colnr, REAL value); REAL __EXPORT_TYPE __WINAPI get_lowbo(lprec *lp, int colnr); MYBOOL __EXPORT_TYPE __WINAPI set_bounds(lprec *lp, int colnr, REAL lower, REAL upper); MYBOOL __EXPORT_TYPE __WINAPI set_unbounded(lprec *lp, int colnr); MYBOOL __EXPORT_TYPE __WINAPI is_unbounded(lprec *lp, int colnr); /* Set the upper and lower bounds of a variable */ MYBOOL __EXPORT_TYPE __WINAPI set_int(lprec *lp, int colnr, MYBOOL must_be_int); MYBOOL __EXPORT_TYPE __WINAPI is_int(lprec *lp, int colnr); MYBOOL __EXPORT_TYPE __WINAPI set_binary(lprec *lp, int colnr, MYBOOL must_be_bin); MYBOOL __EXPORT_TYPE __WINAPI is_binary(lprec *lp, int colnr); MYBOOL __EXPORT_TYPE __WINAPI set_semicont(lprec *lp, int colnr, MYBOOL must_be_sc); MYBOOL __EXPORT_TYPE __WINAPI is_semicont(lprec *lp, int colnr); MYBOOL __EXPORT_TYPE __WINAPI is_negative(lprec *lp, int colnr); MYBOOL __EXPORT_TYPE __WINAPI set_var_weights(lprec *lp, REAL *weights); int __EXPORT_TYPE __WINAPI get_var_priority(lprec *lp, int colnr); /* Set the type of variable */ MYBOOL __EXPORT_TYPE __WINAPI set_pseudocosts(lprec *lp, REAL *clower, REAL *cupper, int *updatelimit); MYBOOL __EXPORT_TYPE __WINAPI get_pseudocosts(lprec *lp, REAL *clower, REAL *cupper, int *updatelimit); /* Set initial values for, or get computed pseudocost vectors; note that setting of pseudocosts can only happen in response to a call-back function optionally requesting this */ int __EXPORT_TYPE __WINAPI add_SOS(lprec *lp, char *name, int sostype, int priority, int count, int *sosvars, REAL *weights); MYBOOL __EXPORT_TYPE __WINAPI is_SOS_var(lprec *lp, int colnr); /* Add SOS constraints */ MYBOOL __EXPORT_TYPE __WINAPI set_row_name(lprec *lp, int rownr, char *new_name); char __EXPORT_TYPE * __WINAPI get_row_name(lprec *lp, int rownr); char __EXPORT_TYPE * __WINAPI get_origrow_name(lprec *lp, int rownr); /* Set/Get the name of a constraint row */ /* Get added by KE */ MYBOOL __EXPORT_TYPE __WINAPI set_col_name(lprec *lp, int colnr, char *new_name); char __EXPORT_TYPE * __WINAPI get_col_name(lprec *lp, int colnr); char __EXPORT_TYPE * __WINAPI get_origcol_name(lprec *lp, int colnr); /* Set/Get the name of a variable column */ /* Get added by KE */ void __EXPORT_TYPE __WINAPI unscale(lprec *lp); /* Undo previous scaling of the problem */ void __EXPORT_TYPE __WINAPI set_preferdual(lprec *lp, MYBOOL dodual); void __EXPORT_TYPE __WINAPI set_simplextype(lprec *lp, int simplextype); int __EXPORT_TYPE __WINAPI get_simplextype(lprec *lp); /* Set/Get if lp_solve should prefer the dual simplex over the primal -- added by KE */ void __EXPORT_TYPE __WINAPI default_basis(lprec *lp); void __EXPORT_TYPE __WINAPI set_basiscrash(lprec *lp, int mode); int __EXPORT_TYPE __WINAPI get_basiscrash(lprec *lp); int __EXPORT_TYPE __WINAPI set_basisvar(lprec *lp, int basisPos, int enteringCol); MYBOOL __EXPORT_TYPE __WINAPI set_basis(lprec *lp, int *bascolumn, MYBOOL nonbasic); MYBOOL __EXPORT_TYPE __WINAPI get_basis(lprec *lp, int *bascolumn, MYBOOL nonbasic); void __EXPORT_TYPE __WINAPI reset_basis(lprec *lp); /* Set/Get basis for a re-solved system */ /* Added by KE */ MYBOOL __EXPORT_TYPE __WINAPI guess_basis(lprec *lp, REAL *guessvector, int *basisvector); MYBOOL __EXPORT_TYPE __WINAPI is_feasible(lprec *lp, REAL *values, REAL threshold); /* returns TRUE if the vector in values is a feasible solution to the lp */ int __EXPORT_TYPE __WINAPI solve(lprec *lp); /* Solve the problem */ REAL __EXPORT_TYPE __WINAPI time_elapsed(lprec *lp); /* Return the number of seconds since start of solution process */ void __EXPORT_TYPE __WINAPI put_bb_nodefunc(lprec *lp, lphandleint_intfunc newnode, void *bbnodehandle); void __EXPORT_TYPE __WINAPI put_bb_branchfunc(lprec *lp, lphandleint_intfunc newbranch, void *bbbranchhandle); /* Allow the user to override B&B node and branching decisions */ void __EXPORT_TYPE __WINAPI put_abortfunc(lprec *lp, lphandle_intfunc newctrlc, void *ctrlchandle); /* Allow the user to define an interruption callback function */ void __EXPORT_TYPE __WINAPI put_logfunc(lprec *lp, lphandlestr_func newlog, void *loghandle); /* Allow the user to define a logging function */ void __EXPORT_TYPE __WINAPI put_msgfunc(lprec *lp, lphandleint_func newmsg, void *msghandle, int mask); /* Allow the user to define an event-driven message/reporting */ MYBOOL __EXPORT_TYPE __WINAPI get_primal_solution(lprec *lp, REAL *pv); MYBOOL __EXPORT_TYPE __WINAPI get_ptr_primal_solution(lprec *lp, REAL **pv); MYBOOL __EXPORT_TYPE __WINAPI get_dual_solution(lprec *lp, REAL *rc); MYBOOL __EXPORT_TYPE __WINAPI get_ptr_dual_solution(lprec *lp, REAL **rc); MYBOOL __EXPORT_TYPE __WINAPI get_lambda(lprec *lp, REAL *lambda); MYBOOL __EXPORT_TYPE __WINAPI get_ptr_lambda(lprec *lp, REAL **lambda); /* Get the primal, dual/reduced costs and Lambda vectors */ /* Read an MPS file */ lprec __EXPORT_TYPE * __WINAPI read_MPS(char *filename, int options); lprec __EXPORT_TYPE * __WINAPI read_mps(FILE *filename, int options); lprec __EXPORT_TYPE * __WINAPI read_freeMPS(char *filename, int options); lprec __EXPORT_TYPE * __WINAPI read_freemps(FILE *filename, int options); /* Write a MPS file to output */ MYBOOL __EXPORT_TYPE __WINAPI write_mps(lprec *lp, char *filename); MYBOOL __EXPORT_TYPE __WINAPI write_MPS(lprec *lp, FILE *output); MYBOOL __EXPORT_TYPE __WINAPI write_freemps(lprec *lp, char *filename); MYBOOL __EXPORT_TYPE __WINAPI write_freeMPS(lprec *lp, FILE *output); MYBOOL __EXPORT_TYPE __WINAPI write_lp(lprec *lp, char *filename); MYBOOL __EXPORT_TYPE __WINAPI write_LP(lprec *lp, FILE *output); /* Write a LP file to output */ MYBOOL __WINAPI LP_readhandle(lprec **lp, FILE *filename, int verbose, char *lp_name); lprec __EXPORT_TYPE * __WINAPI read_lp(FILE *filename, int verbose, char *lp_name); lprec __EXPORT_TYPE * __WINAPI read_LP(char *filename, int verbose, char *lp_name); /* Old-style lp format file parser */ MYBOOL __EXPORT_TYPE __WINAPI write_basis(lprec *lp, char *filename); MYBOOL __EXPORT_TYPE __WINAPI read_basis(lprec *lp, char *filename, char *info); /* Read and write basis from/to file in CPLEX BAS format */ MYBOOL __EXPORT_TYPE __WINAPI write_params(lprec *lp, char *filename, char *options); MYBOOL __EXPORT_TYPE __WINAPI read_params(lprec *lp, char *filename, char *options); void __EXPORT_TYPE __WINAPI reset_params(lprec *lp); /* Read and write parameter file */ void __EXPORT_TYPE __WINAPI print_lp(lprec *lp); void __EXPORT_TYPE __WINAPI print_tableau(lprec *lp); /* Print the current problem, only useful in very small (test) problems */ void __EXPORT_TYPE __WINAPI print_objective(lprec *lp); void __EXPORT_TYPE __WINAPI print_solution(lprec *lp, int columns); void __EXPORT_TYPE __WINAPI print_constraints(lprec *lp, int columns); /* Print the solution to stdout */ void __EXPORT_TYPE __WINAPI print_duals(lprec *lp); /* Print the dual variables of the solution */ void __EXPORT_TYPE __WINAPI print_scales(lprec *lp); /* If scaling is used, print the scaling factors */ void __EXPORT_TYPE __WINAPI print_str(lprec *lp, char *str); void __EXPORT_TYPE __WINAPI set_outputstream(lprec *lp, FILE *stream); MYBOOL __EXPORT_TYPE __WINAPI set_outputfile(lprec *lp, char *filename); void __EXPORT_TYPE __WINAPI set_verbose(lprec *lp, int verbose); int __EXPORT_TYPE __WINAPI get_verbose(lprec *lp); void __EXPORT_TYPE __WINAPI set_timeout(lprec *lp, long sectimeout); long __EXPORT_TYPE __WINAPI get_timeout(lprec *lp); void __EXPORT_TYPE __WINAPI set_print_sol(lprec *lp, int print_sol); int __EXPORT_TYPE __WINAPI get_print_sol(lprec *lp); void __EXPORT_TYPE __WINAPI set_debug(lprec *lp, MYBOOL debug); MYBOOL __EXPORT_TYPE __WINAPI is_debug(lprec *lp); void __EXPORT_TYPE __WINAPI set_trace(lprec *lp, MYBOOL trace); MYBOOL __EXPORT_TYPE __WINAPI is_trace(lprec *lp); MYBOOL __EXPORT_TYPE __WINAPI print_debugdump(lprec *lp, char *filename); void __EXPORT_TYPE __WINAPI set_anti_degen(lprec *lp, int anti_degen); int __EXPORT_TYPE __WINAPI get_anti_degen(lprec *lp); MYBOOL __EXPORT_TYPE __WINAPI is_anti_degen(lprec *lp, int testmask); void __EXPORT_TYPE __WINAPI set_presolve(lprec *lp, int presolvemode, int maxloops); int __EXPORT_TYPE __WINAPI get_presolve(lprec *lp); int __EXPORT_TYPE __WINAPI get_presolveloops(lprec *lp); MYBOOL __EXPORT_TYPE __WINAPI is_presolve(lprec *lp, int testmask); int __EXPORT_TYPE __WINAPI get_orig_index(lprec *lp, int lp_index); int __EXPORT_TYPE __WINAPI get_lp_index(lprec *lp, int orig_index); void __EXPORT_TYPE __WINAPI set_maxpivot(lprec *lp, int max_num_inv); int __EXPORT_TYPE __WINAPI get_maxpivot(lprec *lp); void __EXPORT_TYPE __WINAPI set_obj_bound(lprec *lp, REAL obj_bound); REAL __EXPORT_TYPE __WINAPI get_obj_bound(lprec *lp); void __EXPORT_TYPE __WINAPI set_mip_gap(lprec *lp, MYBOOL absolute, REAL mip_gap); REAL __EXPORT_TYPE __WINAPI get_mip_gap(lprec *lp, MYBOOL absolute); void __EXPORT_TYPE __WINAPI set_bb_rule(lprec *lp, int bb_rule); int __EXPORT_TYPE __WINAPI get_bb_rule(lprec *lp); MYBOOL __EXPORT_TYPE __WINAPI set_var_branch(lprec *lp, int colnr, int branch_mode); int __EXPORT_TYPE __WINAPI get_var_branch(lprec *lp, int colnr); MYBOOL __EXPORT_TYPE __WINAPI is_infinite(lprec *lp, REAL value); void __EXPORT_TYPE __WINAPI set_infinite(lprec *lp, REAL infinite); REAL __EXPORT_TYPE __WINAPI get_infinite(lprec *lp); void __EXPORT_TYPE __WINAPI set_epsint(lprec *lp, REAL epsint); REAL __EXPORT_TYPE __WINAPI get_epsint(lprec *lp); void __EXPORT_TYPE __WINAPI set_epsb(lprec *lp, REAL epsb); REAL __EXPORT_TYPE __WINAPI get_epsb(lprec *lp); void __EXPORT_TYPE __WINAPI set_epsd(lprec *lp, REAL epsd); REAL __EXPORT_TYPE __WINAPI get_epsd(lprec *lp); void __EXPORT_TYPE __WINAPI set_epsel(lprec *lp, REAL epsel); REAL __EXPORT_TYPE __WINAPI get_epsel(lprec *lp); MYBOOL __EXPORT_TYPE __WINAPI set_epslevel(lprec *lp, int epslevel); void __EXPORT_TYPE __WINAPI set_scaling(lprec *lp, int scalemode); int __EXPORT_TYPE __WINAPI get_scaling(lprec *lp); MYBOOL __EXPORT_TYPE __WINAPI is_scalemode(lprec *lp, int testmask); MYBOOL __EXPORT_TYPE __WINAPI is_scaletype(lprec *lp, int scaletype); MYBOOL __EXPORT_TYPE __WINAPI is_integerscaling(lprec *lp); void __EXPORT_TYPE __WINAPI set_scalelimit(lprec *lp, REAL scalelimit); REAL __EXPORT_TYPE __WINAPI get_scalelimit(lprec *lp); void __EXPORT_TYPE __WINAPI set_improve(lprec *lp, int improve); int __EXPORT_TYPE __WINAPI get_improve(lprec *lp); void __EXPORT_TYPE __WINAPI set_pivoting(lprec *lp, int piv_rule); int __EXPORT_TYPE __WINAPI get_pivoting(lprec *lp); MYBOOL __EXPORT_TYPE __WINAPI set_partialprice(lprec *lp, int blockcount, int *blockstart, MYBOOL isrow); void __EXPORT_TYPE __WINAPI get_partialprice(lprec *lp, int *blockcount, int *blockstart, MYBOOL isrow); MYBOOL __EXPORT_TYPE __WINAPI set_multiprice(lprec *lp, int multiblockdiv); int __EXPORT_TYPE __WINAPI get_multiprice(lprec *lp, MYBOOL getabssize); MYBOOL __EXPORT_TYPE __WINAPI is_use_names(lprec *lp, MYBOOL isrow); void __EXPORT_TYPE __WINAPI set_use_names(lprec *lp, MYBOOL isrow, MYBOOL use_names); int __EXPORT_TYPE __WINAPI get_nameindex(lprec *lp, char *varname, MYBOOL isrow); MYBOOL __EXPORT_TYPE __WINAPI is_piv_mode(lprec *lp, int testmask); MYBOOL __EXPORT_TYPE __WINAPI is_piv_rule(lprec *lp, int rule); void __EXPORT_TYPE __WINAPI set_break_at_first(lprec *lp, MYBOOL break_at_first); MYBOOL __EXPORT_TYPE __WINAPI is_break_at_first(lprec *lp); void __EXPORT_TYPE __WINAPI set_bb_floorfirst(lprec *lp, int bb_floorfirst); int __EXPORT_TYPE __WINAPI get_bb_floorfirst(lprec *lp); void __EXPORT_TYPE __WINAPI set_bb_depthlimit(lprec *lp, int bb_maxlevel); int __EXPORT_TYPE __WINAPI get_bb_depthlimit(lprec *lp); void __EXPORT_TYPE __WINAPI set_break_at_value(lprec *lp, REAL break_at_value); REAL __EXPORT_TYPE __WINAPI get_break_at_value(lprec *lp); void __EXPORT_TYPE __WINAPI set_negrange(lprec *lp, REAL negrange); REAL __EXPORT_TYPE __WINAPI get_negrange(lprec *lp); void __EXPORT_TYPE __WINAPI set_epsperturb(lprec *lp, REAL epsperturb); REAL __EXPORT_TYPE __WINAPI get_epsperturb(lprec *lp); void __EXPORT_TYPE __WINAPI set_epspivot(lprec *lp, REAL epspivot); REAL __EXPORT_TYPE __WINAPI get_epspivot(lprec *lp); int __EXPORT_TYPE __WINAPI get_max_level(lprec *lp); COUNTER __EXPORT_TYPE __WINAPI get_total_nodes(lprec *lp); COUNTER __EXPORT_TYPE __WINAPI get_total_iter(lprec *lp); REAL __EXPORT_TYPE __WINAPI get_objective(lprec *lp); REAL __EXPORT_TYPE __WINAPI get_working_objective(lprec *lp); REAL __EXPORT_TYPE __WINAPI get_var_primalresult(lprec *lp, int index); REAL __EXPORT_TYPE __WINAPI get_var_dualresult(lprec *lp, int index); MYBOOL __EXPORT_TYPE __WINAPI get_variables(lprec *lp, REAL *var); MYBOOL __EXPORT_TYPE __WINAPI get_ptr_variables(lprec *lp, REAL **var); MYBOOL __EXPORT_TYPE __WINAPI get_constraints(lprec *lp, REAL *constr); MYBOOL __EXPORT_TYPE __WINAPI get_ptr_constraints(lprec *lp, REAL **constr); MYBOOL __EXPORT_TYPE __WINAPI get_sensitivity_rhs(lprec *lp, REAL *duals, REAL *dualsfrom, REAL *dualstill); MYBOOL __EXPORT_TYPE __WINAPI get_ptr_sensitivity_rhs(lprec *lp, REAL **duals, REAL **dualsfrom, REAL **dualstill); MYBOOL __EXPORT_TYPE __WINAPI get_sensitivity_obj(lprec *lp, REAL *objfrom, REAL *objtill); MYBOOL __EXPORT_TYPE __WINAPI get_sensitivity_objex(lprec *lp, REAL *objfrom, REAL *objtill, REAL *objfromvalue, REAL *objtillvalue); MYBOOL __EXPORT_TYPE __WINAPI get_ptr_sensitivity_obj(lprec *lp, REAL **objfrom, REAL **objtill); MYBOOL __EXPORT_TYPE __WINAPI get_ptr_sensitivity_objex(lprec *lp, REAL **objfrom, REAL **objtill, REAL **objfromvalue, REAL **objtillvalue); void __EXPORT_TYPE __WINAPI set_solutionlimit(lprec *lp, int limit); int __EXPORT_TYPE __WINAPI get_solutionlimit(lprec *lp); int __EXPORT_TYPE __WINAPI get_solutioncount(lprec *lp); int __EXPORT_TYPE __WINAPI get_Norig_rows(lprec *lp); int __EXPORT_TYPE __WINAPI get_Nrows(lprec *lp); int __EXPORT_TYPE __WINAPI get_Lrows(lprec *lp); int __EXPORT_TYPE __WINAPI get_Norig_columns(lprec *lp); int __EXPORT_TYPE __WINAPI get_Ncolumns(lprec *lp); typedef int (__WINAPI read_modeldata_func)(void *userhandle, char *buf, int max_size); typedef int (__WINAPI write_modeldata_func)(void *userhandle, char *buf); MYBOOL __WINAPI MPS_readex(lprec **newlp, void *userhandle, read_modeldata_func read_modeldata, int typeMPS, int options); /* #if defined develop */ lprec __EXPORT_TYPE * __WINAPI read_lpex(void *userhandle, read_modeldata_func read_modeldata, int verbose, char *lp_name); MYBOOL __EXPORT_TYPE __WINAPI write_lpex(lprec *lp, void *userhandle, write_modeldata_func write_modeldata); lprec __EXPORT_TYPE * __WINAPI read_mpsex(void *userhandle, read_modeldata_func read_modeldata, int options); lprec __EXPORT_TYPE * __WINAPI read_freempsex(void *userhandle, read_modeldata_func read_modeldata, int options); MYBOOL __EXPORT_TYPE __WINAPI MPS_writefileex(lprec *lp, int typeMPS, void *userhandle, write_modeldata_func write_modeldata); /* #endif */ #ifdef __cplusplus } #endif /* Forward definitions of functions used internaly by the lp toolkit */ MYBOOL set_callbacks(lprec *lp); STATIC int yieldformessages(lprec *lp); MYBOOL __WINAPI userabort(lprec *lp, int message); /*char * __VACALL explain(lprec *lp, char *format, ...); void __VACALL report(lprec *lp, int level, char *format, ...);*/ /* Memory management routines */ STATIC MYBOOL append_rows(lprec *lp, int deltarows); STATIC MYBOOL append_columns(lprec *lp, int deltacolumns); STATIC void inc_rows(lprec *lp, int delta); STATIC void inc_columns(lprec *lp, int delta); STATIC MYBOOL init_rowcol_names(lprec *lp); STATIC MYBOOL inc_row_space(lprec *lp, int deltarows); STATIC MYBOOL inc_col_space(lprec *lp, int deltacols); STATIC MYBOOL shift_rowcoldata(lprec *lp, int base, int delta, LLrec *usedmap, MYBOOL isrow); STATIC MYBOOL shift_basis(lprec *lp, int base, int delta, LLrec *usedmap, MYBOOL isrow); STATIC MYBOOL shift_rowdata(lprec *lp, int base, int delta, LLrec *usedmap); STATIC MYBOOL shift_coldata(lprec *lp, int base, int delta, LLrec *usedmap); /* INLINE */ MYBOOL is_chsign(lprec *lp, int rownr); STATIC MYBOOL inc_lag_space(lprec *lp, int deltarows, MYBOOL ignoreMAT); lprec *make_lag(lprec *server); REAL get_rh_upper(lprec *lp, int rownr); REAL get_rh_lower(lprec *lp, int rownr); MYBOOL set_rh_upper(lprec *lp, int rownr, REAL value); MYBOOL set_rh_lower(lprec *lp, int rownr, REAL value); STATIC int bin_count(lprec *lp, MYBOOL working); STATIC int MIP_count(lprec *lp); STATIC int SOS_count(lprec *lp); STATIC int GUB_count(lprec *lp); STATIC int identify_GUB(lprec *lp, MYBOOL mark); STATIC int prepare_GUB(lprec *lp); STATIC MYBOOL refactRecent(lprec *lp); STATIC MYBOOL check_if_less(lprec *lp, REAL x, REAL y, int variable); STATIC MYBOOL feasiblePhase1(lprec *lp, REAL epsvalue); STATIC void free_duals(lprec *lp); STATIC void initialize_solution(lprec *lp, MYBOOL shiftbounds); STATIC void recompute_solution(lprec *lp, MYBOOL shiftbounds); STATIC int verify_solution(lprec *lp, MYBOOL reinvert, char *info); STATIC int check_solution(lprec *lp, int lastcolumn, REAL *solution, REAL *upbo, REAL *lowbo, REAL tolerance); /* INLINE */ MYBOOL is_fixedvar(lprec *lp, int variable); /* INLINE */ MYBOOL is_splitvar(lprec *lp, int colnr); void __WINAPI set_action(int *actionvar, int actionmask); void __WINAPI clear_action(int *actionvar, int actionmask); MYBOOL __WINAPI is_action(int actionvar, int testmask); /* INLINE */ MYBOOL is_bb_rule(lprec *lp, int bb_rule); /* INLINE */ MYBOOL is_bb_mode(lprec *lp, int bb_mask); /* INLINE */ int get_piv_rule(lprec *lp); STATIC char *get_str_piv_rule(int rule); STATIC MYBOOL __WINAPI set_var_priority(lprec *lp); STATIC int find_sc_bbvar(lprec *lp, int *count); STATIC int find_sos_bbvar(lprec *lp, int *count, MYBOOL intsos); STATIC int find_int_bbvar(lprec *lp, int *count, BBrec *BB, MYBOOL *isfeasible); /* Solution-related functions */ STATIC REAL compute_dualslacks(lprec *lp, int target, REAL **dvalues, int **nzdvalues, MYBOOL dosum); STATIC MYBOOL solution_is_int(lprec *lp, int index, MYBOOL checkfixed); STATIC MYBOOL bb_better(lprec *lp, int target, int mode); STATIC void construct_solution(lprec *lp, REAL *target); STATIC void transfer_solution_var(lprec *lp, int uservar); STATIC MYBOOL construct_duals(lprec *lp); STATIC MYBOOL construct_sensitivity_duals(lprec *lp); STATIC MYBOOL construct_sensitivity_obj(lprec *lp); STATIC int add_GUB(lprec *lp, char *name, int priority, int count, int *sosvars); STATIC basisrec *push_basis(lprec *lp, int *basisvar, MYBOOL *isbasic, MYBOOL *islower); STATIC MYBOOL compare_basis(lprec *lp); STATIC MYBOOL restore_basis(lprec *lp); STATIC MYBOOL pop_basis(lprec *lp, MYBOOL restore); STATIC MYBOOL is_BasisReady(lprec *lp); STATIC MYBOOL is_slackbasis(lprec *lp); STATIC MYBOOL verify_basis(lprec *lp); STATIC int unload_basis(lprec *lp, MYBOOL restorelast); STATIC int perturb_bounds(lprec *lp, BBrec *perturbed, MYBOOL doRows, MYBOOL doCols, MYBOOL includeFIXED); STATIC MYBOOL validate_bounds(lprec *lp, REAL *upbo, REAL *lowbo); STATIC MYBOOL impose_bounds(lprec *lp, REAL * upbo, REAL *lowbo); STATIC int unload_BB(lprec *lp); STATIC REAL feasibilityOffset(lprec *lp, MYBOOL isdual); STATIC MYBOOL isP1extra(lprec *lp); STATIC REAL get_refactfrequency(lprec *lp, MYBOOL final); STATIC int findBasicFixedvar(lprec *lp, int afternr, MYBOOL slacksonly); STATIC MYBOOL isBasisVarFeasible(lprec *lp, REAL tol, int basis_row); STATIC MYBOOL isPrimalFeasible(lprec *lp, REAL tol, int infeasibles[], REAL *feasibilitygap); STATIC MYBOOL isDualFeasible(lprec *lp, REAL tol, int *boundflips, int infeasibles[], REAL *feasibilitygap); /* Main simplex driver routines */ STATIC int preprocess(lprec *lp); STATIC void postprocess(lprec *lp); STATIC MYBOOL performiteration(lprec *lp, int rownr, int varin, LREAL theta, MYBOOL primal, MYBOOL allowminit, REAL *prow, int *nzprow, REAL *pcol, int *nzpcol, int *boundswaps); STATIC void transfer_solution_var(lprec *lp, int uservar); STATIC void transfer_solution(lprec *lp, MYBOOL dofinal); /* Scaling utilities */ STATIC REAL scaled_floor(lprec *lp, int colnr, REAL value, REAL epsscale); STATIC REAL scaled_ceil(lprec *lp, int colnr, REAL value, REAL epsscale); /* Variable mapping utility routines */ STATIC void varmap_lock(lprec *lp); STATIC void varmap_clear(lprec *lp); STATIC MYBOOL varmap_canunlock(lprec *lp); STATIC void varmap_addconstraint(lprec *lp); STATIC void varmap_addcolumn(lprec *lp); STATIC void varmap_delete(lprec *lp, int base, int delta, LLrec *varmap); STATIC void varmap_compact(lprec *lp, int prev_rows, int prev_cols); STATIC MYBOOL varmap_validate(lprec *lp, int varno); /* STATIC MYBOOL del_varnameex(lprec *lp, hashelem **namelist, hashtable *ht, int varnr, LLrec *varmap); */ STATIC MYBOOL del_varnameex(lprec *lp, hashelem **namelist, int items, hashtable *ht, int varnr, LLrec *varmap); /* Pseudo-cost routines (internal) */ STATIC BBPSrec *init_pseudocost(lprec *lp, int pseudotype); STATIC void free_pseudocost(lprec *lp); STATIC REAL get_pseudorange(BBPSrec *pc, int mipvar, int varcode); STATIC void update_pseudocost(BBPSrec *pc, int mipvar, int varcode, MYBOOL capupper, REAL varsol); STATIC REAL get_pseudobranchcost(BBPSrec *pc, int mipvar, MYBOOL dofloor); STATIC REAL get_pseudonodecost(BBPSrec *pc, int mipvar, int vartype, REAL varsol); /* Matrix access and equation solving routines */ STATIC void set_OF_override(lprec *lp, REAL *ofVector); STATIC void set_OF_p1extra(lprec *lp, REAL p1extra); STATIC void unset_OF_p1extra(lprec *lp); MYBOOL modifyOF1(lprec *lp, int index, REAL *ofValue, REAL mult); REAL __WINAPI get_OF_active(lprec *lp, int varnr, REAL mult); STATIC MYBOOL is_OF_nz(lprec *lp, int colnr); STATIC int get_basisOF(lprec *lp, int coltarget[], REAL crow[], int colno[]); int __WINAPI get_basiscolumn(lprec *lp, int j, int rn[], double bj[]); int __WINAPI obtain_column(lprec *lp, int varin, REAL *pcol, int *nzlist, int *maxabs); STATIC int compute_theta(lprec *lp, int rownr, LREAL *theta, int isupbound, REAL HarrisScalar, MYBOOL primal); /* Pivot utility routines */ STATIC int findBasisPos(lprec *lp, int notint, int *var_basic); STATIC MYBOOL check_degeneracy(lprec *lp, REAL *pcol, int *degencount); #endif /* HEADER_lp_lib */ MSVMpack1.2/lp_solve_5.5/lp_pricePSE.c0000664000175000017500000003305111141374247016455 0ustar lauerlauer #include #include "commonlib.h" #include "lp_lib.h" #include "lp_report.h" #include "lp_pricePSE.h" #ifdef FORTIFY # include "lp_fortify.h" #endif /* Advanced simplex price scaling modules - w/interface for lp_solve v5.0+ ---------------------------------------------------------------------------------- Author: Kjell Eikland Contact: kjell.eikland@broadpark.no License terms: LGPL. Requires: lp_lib.h Release notes: v1.0.0 1 September 2003 Implementation of DEVEX and STEEPEST EDGE routines for the primal and dual simplex. v1.0.1 1 January 2004 Made initial value of weight of ingoing variable for the standard mode of DEVEX consistent with the initialization at restart; original version could at worst contribute to cycling. v1.0.2 23 March 2004 Added floors to Steepest Edge updates and moved tests for tiny update higher. Previous logic can be simulated by disabling the compiler define ApplySteepestEdgeMinimum. v1.1.0 1 July 2004 Renamed from lp_pricerPSE to lp_pricePSE in conjuction with the creation of a separate price library. v1.2.0 1 March 2005 Changed memory allocation routines to use standard lp_solve functions, improve error handling and return boolean status values. ---------------------------------------------------------------------------------- */ INLINE MYBOOL applyPricer(lprec *lp) { int rule = get_piv_rule(lp); return( (MYBOOL) ((rule == PRICER_DEVEX) || (rule == PRICER_STEEPESTEDGE)) ); } STATIC void simplexPricer(lprec *lp, MYBOOL isdual) { if(lp->edgeVector != NULL) lp->edgeVector[0] = (REAL) isdual; } STATIC void freePricer(lprec *lp) { FREE(lp->edgeVector); } STATIC MYBOOL resizePricer(lprec *lp) { if(!applyPricer(lp)) return( TRUE ); /* Reallocate vector for new size */ if(!allocREAL(lp, &(lp->edgeVector), lp->sum_alloc+1, AUTOMATIC)) return( FALSE ); /* Signal that we have not yet initialized the price vector */ MEMCLEAR(lp->edgeVector, lp->sum_alloc+1); lp->edgeVector[0] = -1; return( TRUE ); } STATIC MYBOOL initPricer(lprec *lp) { if(!applyPricer(lp)) return( FALSE ); /* Free any pre-existing pricer */ freePricer(lp); /* Allocate vector to fit current problem size */ return( resizePricer(lp) ); } STATIC REAL getPricer(lprec *lp, int item, MYBOOL isdual) { REAL value = 1.0; if(!applyPricer(lp)) return( value ); value = *lp->edgeVector; /* Make sure we have a price vector to use */ if(value < 0) { #ifdef Paranoia report(lp, SEVERE, "getPricer: Called without having being initialized!\n"); #endif return( 1.0 ); } /* We may be calling the primal from the dual (and vice-versa) for validation of feasibility; ignore calling origin and simply return 1 */ else if(isdual != value) { return( 1.0 ); } /* Do the normal norm retrieval */ else { if(isdual) item = lp->var_basic[item]; value = lp->edgeVector[item]; if(value == 0) { value = 1.0; report(lp, SEVERE, "getPricer: Detected a zero-valued price at index %d\n", item); } #ifdef Paranoia else if(value < 0) report(lp, SEVERE, "getPricer: Invalid %s reduced cost norm %g at index %d\n", my_if(isdual, "dual", "primal"), value, item); #endif /* Return the norm */ return( sqrt(value) ); } } STATIC MYBOOL restartPricer(lprec *lp, MYBOOL isdual) { REAL *sEdge = NULL, seNorm, hold; int i, j, m; MYBOOL isDEVEX, ok = applyPricer(lp); if(!ok) return( ok ); /* Store the active/current pricing type */ if(isdual == AUTOMATIC) isdual = (MYBOOL) lp->edgeVector[0]; else lp->edgeVector[0] = isdual; m = lp->rows; /* Determine strategy and check if we have strategy fallback for the primal */ isDEVEX = is_piv_rule(lp, PRICER_DEVEX); if(!isDEVEX && !isdual) isDEVEX = is_piv_mode(lp, PRICE_PRIMALFALLBACK); /* Check if we only need to do the simple DEVEX initialization */ if(!is_piv_mode(lp, PRICE_TRUENORMINIT)) { if(isdual) { for(i = 1; i <= m; i++) lp->edgeVector[lp->var_basic[i]] = 1.0; } else { for(i = 1; i <= lp->sum; i++) if(!lp->is_basic[i]) lp->edgeVector[i] = 1.0; } return( ok ); } /* Otherwise do the full Steepest Edge norm initialization */ ok = allocREAL(lp, &sEdge, m+1, FALSE); if(!ok) return( ok ); if(isdual) { /* Extract the rows of the basis inverse and compute their squared norms */ for(i = 1; i <= m; i++) { bsolve(lp, i, sEdge, NULL, 0, 0.0); /* Compute the edge norm */ seNorm = 0; for(j = 1; j <= m; j++) { hold = sEdge[j]; seNorm += hold*hold; } j = lp->var_basic[i]; lp->edgeVector[j] = seNorm; } } else { /* Solve a=Bb for b over all non-basic variables and compute their squared norms */ for(i = 1; i <= lp->sum; i++) { if(lp->is_basic[i]) continue; fsolve(lp, i, sEdge, NULL, 0, 0.0, FALSE); /* Compute the edge norm */ seNorm = 1; for(j = 1; j <= m; j++) { hold = sEdge[j]; seNorm += hold*hold; } lp->edgeVector[i] = seNorm; } } FREE(sEdge); return( ok ); } STATIC MYBOOL formWeights(lprec *lp, int colnr, REAL *pcol, REAL **w) /* This computes Bw = a, where B is the basis and a is a column of A */ { MYBOOL ok = allocREAL(lp, w, lp->rows+1, FALSE); if(ok) { if(pcol == NULL) fsolve(lp, colnr, *w, NULL, 0.0, 0.0, FALSE); else { MEMCOPY(*w, pcol, lp->rows+1); /* *w[0] = 0; */ /* Test */ } } /* if(pcol != NULL) { REAL cEdge, hold; int i; cEdge = 0; for(i = 1; i <= m; i++) { hold = *w[i]-pcol[i]; cEdge += hold*hold; } cEdge /= m; cEdge = sqrt(cEdge); if(cEdge > lp->epspivot) report(lp, SEVERE, "updatePricer: MRS error is %g\n", cEdge); } */ return(ok); } STATIC void freeWeights(REAL *w) { FREE(w); } STATIC MYBOOL updatePricer(lprec *lp, int rownr, int colnr, REAL *pcol, REAL *prow, int *nzprow) { REAL *vEdge = NULL, cEdge, hold, *newEdge, *w = NULL; int i, m, n, exitcol, errlevel = DETAILED; MYBOOL forceRefresh = FALSE, isDual, isDEVEX, ok = FALSE; if(!applyPricer(lp)) return(ok); /* Make sure we have something to update */ hold = lp->edgeVector[0]; if(hold < 0) return(ok); isDual = (MYBOOL) (hold > 0); /* Do common initializations and computations */ m = lp->rows; n = lp->sum; isDEVEX = is_piv_rule(lp, PRICER_DEVEX); exitcol = lp->var_basic[rownr]; /* Solve/copy Bw = a */ #if 0 ok = formWeights(lp, colnr, NULL, &w); /* Compute from scratch - Experimental */ #else ok = formWeights(lp, colnr, pcol, &w); /* Use previously computed values */ #endif if(!ok) return( ok ); /* Price norms for the dual simplex - the basic columns */ if(isDual) { REAL rw; int targetcol; /* Don't need to compute cross-products with DEVEX */ if(!isDEVEX) { ok = allocREAL(lp, &vEdge, m+1, FALSE); if(!ok) return( ok ); /* Extract the row of the inverse containing the leaving variable and then form the dot products against the other variables, i.e. "Tau" */ #if 0 /* Extract row explicitly */ bsolve(lp, rownr, vEdge, 0, 0.0); #else /* Reuse previously extracted row data */ MEMCOPY(vEdge, prow, m+1); vEdge[0] = 0; #endif lp->bfp_ftran_normal(lp, vEdge, NULL); } /* Update the squared steepest edge norms; first store some constants */ cEdge = lp->edgeVector[exitcol]; rw = w[rownr]; if(fabs(rw) < lp->epspivot) { forceRefresh = TRUE; goto Finish2; } /* Deal with the variable entering the basis to become a new leaving candidate */ hold = 1 / rw; lp->edgeVector[colnr] = (hold*hold) * cEdge; #ifdef Paranoia if(lp->edgeVector[colnr] <= lp->epsmachine) report(lp, errlevel, "updatePricer: Invalid dual norm %g at entering index %d - iteration %.0f\n", lp->edgeVector[colnr], rownr, (double) (lp->total_iter+lp->current_iter)); #endif /* Then loop over all basic variables, but skip the leaving row */ for(i = 1; i <= m; i++) { if(i == rownr) continue; targetcol = lp->var_basic[i]; hold = w[i]; if(hold == 0) continue; hold /= rw; if(fabs(hold) < lp->epsmachine) continue; newEdge = &(lp->edgeVector[targetcol]); *newEdge += (hold*hold) * cEdge; if(isDEVEX) { if((*newEdge) > DEVEX_RESTARTLIMIT) { forceRefresh = TRUE; break; } } else { *newEdge -= 2*hold*vEdge[i]; #ifdef xxApplySteepestEdgeMinimum SETMAX(*newEdge, hold*hold+1); /* Kludge; use the primal lower bound */ #else if(*newEdge <= 0) { report(lp, errlevel, "updatePricer: Invalid dual norm %g at index %d - iteration %.0f\n", *newEdge, i, (double) (lp->total_iter+lp->current_iter)); forceRefresh = TRUE; break; } #endif } } } /* Price norms for the primal simplex - the non-basic columns */ else { REAL *vTemp = NULL, *vAlpha = NULL, cAlpha; int *coltarget; ok = allocREAL(lp, &vTemp, m+1, TRUE) && allocREAL(lp, &vAlpha, n+1, TRUE); if(!ok) return( ok ); /* Check if we have strategy fallback for the primal */ if(!isDEVEX) isDEVEX = is_piv_mode(lp, PRICE_PRIMALFALLBACK); /* Initialize column target array */ coltarget = (int *) mempool_obtainVector(lp->workarrays, lp->sum+1, sizeof(*coltarget)); ok = get_colIndexA(lp, SCAN_SLACKVARS+SCAN_USERVARS+USE_NONBASICVARS, coltarget, FALSE); if(!ok) { mempool_releaseVector(lp->workarrays, (char *) coltarget, FALSE); return( ok ); } /* Don't need to compute cross-products with DEVEX */ if(!isDEVEX) { ok = allocREAL(lp, &vEdge, n+1, TRUE); if(!ok) return( ok ); /* Compute v and then N'v */ MEMCOPY(vTemp, w, m+1); bsolve(lp, -1, vTemp, NULL, lp->epsmachine*DOUBLEROUND, 0.0); vTemp[0] = 0; prod_xA(lp, coltarget, vTemp, NULL, lp->epsmachine, 0.0, vEdge, NULL, MAT_ROUNDDEFAULT); } /* Compute Sigma and then Alpha */ bsolve(lp, rownr, vTemp, NULL, 0*DOUBLEROUND, 0.0); vTemp[0] = 0; prod_xA(lp, coltarget, vTemp, NULL, lp->epsmachine, 0.0, vAlpha, NULL, MAT_ROUNDDEFAULT); mempool_releaseVector(lp->workarrays, (char *) coltarget, FALSE); /* Update the squared steepest edge norms; first store some constants */ cEdge = lp->edgeVector[colnr]; cAlpha = vAlpha[colnr]; if(fabs(cAlpha) < lp->epspivot) { forceRefresh = TRUE; goto Finish1; } /* Deal with the variable leaving the basis to become a new entry candidate */ hold = 1 / cAlpha; lp->edgeVector[exitcol] = (hold*hold) * cEdge; #ifdef Paranoia if(lp->edgeVector[exitcol] <= lp->epsmachine) report(lp, errlevel, "updatePricer: Invalid primal norm %g at leaving index %d - iteration %.0f\n", lp->edgeVector[exitcol], exitcol, (double) (lp->total_iter+lp->current_iter)); #endif /* Then loop over all non-basic variables, but skip the entering column */ for(i = 1; i <= lp->sum; i++) { if(lp->is_basic[i] || (i == colnr)) continue; hold = vAlpha[i]; if(hold == 0) continue; hold /= cAlpha; if(fabs(hold) < lp->epsmachine) continue; newEdge = &(lp->edgeVector[i]); *newEdge += (hold*hold) * cEdge; if(isDEVEX) { if((*newEdge) > DEVEX_RESTARTLIMIT) { forceRefresh = TRUE; break; } } else { *newEdge -= 2*hold*vEdge[i]; #ifdef ApplySteepestEdgeMinimum SETMAX(*newEdge, hold*hold+1); #else if(*newEdge < 0) { report(lp, errlevel, "updatePricer: Invalid primal norm %g at index %d - iteration %.0f\n", *newEdge, i, (double) (lp->total_iter+lp->current_iter)); if(lp->spx_trace) report(lp, errlevel, "Error detail: (RelAlpha=%g, vEdge=%g, cEdge=%g)\n", hold, vEdge[i], cEdge); forceRefresh = TRUE; break; } #endif } } Finish1: FREE(vAlpha); FREE(vTemp); } Finish2: FREE(vEdge); freeWeights(w); if(forceRefresh) ok = restartPricer(lp, AUTOMATIC); else ok = TRUE; return( ok ); } STATIC MYBOOL verifyPricer(lprec *lp) { REAL value; int i, n; MYBOOL ok = applyPricer(lp); if(!ok) return( ok ); ok = FALSE; /* Verify */ if(lp->edgeVector == NULL) return( ok ); value = *lp->edgeVector; if(value < 0) return( ok ); /* Check the primal */ n = 1; if(value == 0) { for(n = lp->sum; n > 0; n--) { if(lp->is_basic[n]) continue; value = lp->edgeVector[n]; if(value <= 0) break; } } /* Check the dual */ else { for(i = lp->rows; i > 0; i--) { n = lp->var_basic[i]; value = lp->edgeVector[n]; if(value <= 0) break; } } ok = (MYBOOL) (n == 0); #ifdef Paranoia if(!ok) report(lp, SEVERE, "verifyPricer: Invalid norm %g at index %d\n", value, n); #endif return( ok ); } MSVMpack1.2/lp_solve_5.5/Makefile.msc0000664000175000017500000000527410560217106016365 0ustar lauerlauer# # Makefile for building lp_solve using GNU Make # Usage: # gmake -f Makefile.msc [all | bin | lib | clean] # # $Revision: 1.1 $ # AR = ar ARFLAGS = rv CC = cl LEX = flex YACC = bison INC = -I. -Ibfp -Ibfp/bfp_LUSOL -Ibfp/bfp_LUSOL/LUSOL -Icolamd -Ishared # Uncomment any of the following two depending on your profile #DEBUG = -g -pg DEBUG = /ML /O1 /Zp8 /Gd /W2 /DWIN32 /D_WINDOWS DEFINE = -DNoParanoia -DWIN32 -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine # Uncomment any of the following two depending on how easily compiler messages scare you CFLAGS= $(INC) $(DEBUG) $(DEFINE) -D_CRT_SECURE_NO_DEPRECATE -D_CRT_NONSTDC_NO_DEPRECATE LFLAGS = -L -l YFLAGS = --no-lines -y LDFLAGS = LUSOLSRC = bfp/bfp_LUSOL/lp_LUSOL.c bfp/bfp_LUSOL/LUSOL/lusol.c LUSOLOBJS = bfp/bfp_LUSOL/lp_LUSOL.obj bfp/bfp_LUSOL/LUSOL/lusol.obj OBJECTS = $(LUSOLOBJS) lp_MDO.obj shared/commonlib.obj colamd/colamd.obj \ shared/mmio.obj shared/myblas.obj ini.obj fortify.obj lp_rlp.obj lp_crash.obj \ lp_Hash.obj lp_lib.obj lp_wlp.obj lp_matrix.obj lp_mipbb.obj lp_MPS.obj \ lp_params.obj lp_presolve.obj lp_price.obj lp_pricePSE.obj lp_report.obj \ lp_scale.obj lp_simplex.obj lp_SOS.obj lp_utils.obj yacc_read.obj SRC = $(LUSOLSRC) lp_MDO.c shared/commonlib.c colamd/colamd.c \ shared/mmio.c shared/myblas.c ini.c fortify.c lp_rlp.c lp_crash.c \ lp_Hash.c lp_lib.c lp_wlp.c lp_matrix.c lp_mipbb.c lp_MPS.c \ lp_params.c lp_presolve.c lp_price.c lp_pricePSE.c lp_report.c \ lp_scale.c lp_simplex.c lp_SOS.c lp_utils.c yacc_read.c #LIBRARIES = liblpsolve55.lib liblpsolve55d.lib lpsolve55.dll LIBRARIES = #BINARIES = lp_solve.exe demo.exe BINARIES = lp_solve.exe ALL = $(BINARIES) $(DEMOS) $(LIBRARIES) .PHONY=clean lp_solve all: $(ALL) lib: $(LIBRARIES) bin: $(BINARIES) objects: $(OBJECTS) $(OBJECTS): $(SRC) $(CC) -c $(CFLAGS) $(SRC) lp_rlp.c: lp_rlp.l lp_rlp.y $(LEX) $(LFLAGS) lp_rlp.l sed -e "s/yy/lp_yy/g" lex.yy.c >lp_rlp.h rm -f lex.yy.c $(YACC) $(YFLAGS) lp_rlp.y sed -e "s/yy/lp_yy/g" y.tab.c >lp_rlp.c rm -f y.tab.c $(CC) $(CFLAGS) $(DEBUG) $(DEFINE) $(INC) -c $*.c lp_solve.exe: lp_solve/lp_solve.c $(OBJECTS) $(CC) $(CFLAGS) $(DEBUG) $(DEFINE) $(INC) $< $(OBJECTS) -Felp_solve/lp_solve $(LDFLAGS) demo.exe: demo/demo.c $(OBJECTS) $(CC) $(CFLAGS) $(DEBUG) $(DEFINE) $(INC) $< $(OBJECTS) -Fedemo/demo $(LDFLAGS) lpsolve.res: lpsolve.rc $(RC) lpsolve.rc liblpsolve55.lib: $(OBJECTS) $(LIB) *.obj /OUT:lpsolve55/$@ lpsolve55.dll: $(OBJECTS) $(CC) -fpic -shared -Wl,-Bsymbolic -Wl,-soname,$@ -o lpsolve55/$@ `echo $(SRC)|sed 's/[.]c/.obj/g'` $(LDFLAGS) clean: rm -f $(OBJECTS) *.lib *.dll lp_solve/lp_solve.exe demo/demo.exe lpsolve55/*.dll lpsolve55/*.lib MSVMpack1.2/lp_solve_5.5/ini.h0000664000175000017500000000071711141374241015071 0ustar lauerlauer#include #ifdef __cplusplus __EXTERN_C { #endif extern FILE *ini_create(char *filename); extern FILE *ini_open(char *filename); extern void ini_writecomment(FILE *fp, char *comment); extern void ini_writeheader(FILE *fp, char *header, int addnewline); extern void ini_writedata(FILE *fp, char *name, char *data); extern int ini_readdata(FILE *fp, char *data, int szdata, int withcomment); extern void ini_close(FILE *fp); #ifdef __cplusplus } #endif MSVMpack1.2/lp_solve_5.5/lp_utils.c0000664000175000017500000006334611245561740016156 0ustar lauerlauer#define CODE_lp_utils #include #include "commonlib.h" #include "lp_lib.h" #include "lp_utils.h" #include #include #include "lp_bit.h" #ifdef FORTIFY # include "lp_fortify.h" #endif /* Miscellaneous utilities as implemented for lp_solve v5.0+ ---------------------------------------------------------------------------------- Author: Kjell Eikland Contact: kjell.eikland@broadpark.no License terms: GLPL. Requires: lp_utils.h, lp_lib.h Release notes: v1.0.0 1 January 2003 Memory allocation, sorting, searching, time and doubly linked list functions. v1.1.0 15 May 2004 Added vector packing functionality v1.2.0 10 January 2005 Added vector pushing/popping functionality Modified return values and fixed problem in linked list functions. ---------------------------------------------------------------------------------- */ STATIC MYBOOL allocCHAR(lprec *lp, char **ptr, int size, MYBOOL clear) { if(clear == TRUE) *ptr = (char *) calloc(size, sizeof(**ptr)); else if(clear & AUTOMATIC) { *ptr = (char *) realloc(*ptr, size * sizeof(**ptr)); if(clear & TRUE) MEMCLEAR(*ptr, size); } else *ptr = (char *) malloc(size * sizeof(**ptr)); if(((*ptr) == NULL) && (size > 0)) { lp->report(lp, CRITICAL, "alloc of %d 'char' failed\n", size); lp->spx_status = NOMEMORY; return( FALSE ); } else return( TRUE ); } STATIC MYBOOL allocMYBOOL(lprec *lp, MYBOOL **ptr, int size, MYBOOL clear) { if(clear == TRUE) *ptr = (MYBOOL *) calloc(size, sizeof(**ptr)); else if(clear & AUTOMATIC) { *ptr = (MYBOOL *) realloc(*ptr, size * sizeof(**ptr)); if(clear & TRUE) MEMCLEAR(*ptr, size); } else *ptr = (MYBOOL *) malloc(size * sizeof(**ptr)); if(((*ptr) == NULL) && (size > 0)) { lp->report(lp, CRITICAL, "alloc of %d 'MYBOOL' failed\n", size); lp->spx_status = NOMEMORY; return( FALSE ); } else return( TRUE ); } STATIC MYBOOL allocINT(lprec *lp, int **ptr, int size, MYBOOL clear) { if(clear == TRUE) *ptr = (int *) calloc(size, sizeof(**ptr)); else if(clear & AUTOMATIC) { *ptr = (int *) realloc(*ptr, size * sizeof(**ptr)); if(clear & TRUE) MEMCLEAR(*ptr, size); } else *ptr = (int *) malloc(size * sizeof(**ptr)); if(((*ptr) == NULL) && (size > 0)) { lp->report(lp, CRITICAL, "alloc of %d 'INT' failed\n", size); lp->spx_status = NOMEMORY; return( FALSE ); } else return( TRUE ); } STATIC MYBOOL allocREAL(lprec *lp, REAL **ptr, int size, MYBOOL clear) { if(clear == TRUE) *ptr = (REAL *) calloc(size, sizeof(**ptr)); else if(clear & AUTOMATIC) { *ptr = (REAL *) realloc(*ptr, size * sizeof(**ptr)); if(clear & TRUE) MEMCLEAR(*ptr, size); } else *ptr = (REAL *) malloc(size * sizeof(**ptr)); if(((*ptr) == NULL) && (size > 0)) { lp->report(lp, CRITICAL, "alloc of %d 'REAL' failed\n", size); lp->spx_status = NOMEMORY; return( FALSE ); } else return( TRUE ); } STATIC MYBOOL allocLREAL(lprec *lp, LREAL **ptr, int size, MYBOOL clear) { if(clear == TRUE) *ptr = (LREAL *) calloc(size, sizeof(**ptr)); else if(clear & AUTOMATIC) { *ptr = (LREAL *) realloc(*ptr, size * sizeof(**ptr)); if(clear & TRUE) MEMCLEAR(*ptr, size); } else *ptr = (LREAL *) malloc(size * sizeof(**ptr)); if(((*ptr) == NULL) && (size > 0)) { lp->report(lp, CRITICAL, "alloc of %d 'LREAL' failed\n", size); lp->spx_status = NOMEMORY; return( FALSE ); } else return( TRUE ); } STATIC MYBOOL allocFREE(lprec *lp, void **ptr) { MYBOOL status = TRUE; if(*ptr != NULL) { free(*ptr); *ptr = NULL; } else { status = FALSE; lp->report(lp, CRITICAL, "free() failed on line %d of file %s\n", __LINE__, __FILE__); } return(status); } /* Do hoops to provide debugging info with FORTIFY */ #undef CODE_lp_utils #include "lp_utils.h" /* alloc-routines should always be before this line! */ int comp_bits(MYBOOL *bitarray1, MYBOOL *bitarray2, int items) { int i, items4, left = 0, right = 0; MYBOOL comp1; unsigned long comp4; /* Convert items count to 8-bit representation, if necessary */ if(items > 0) { i = items % 8; items /= 8; if(i) items++; } else items = -items; /* Do the wide unsigned integer part for speed */ items4 = items / sizeof(unsigned long); i = 0; while(i < items4) { comp4 = ((unsigned long *) bitarray1)[i] & ~((unsigned long *) bitarray2)[i]; if(comp4) left++; comp4 = ((unsigned long *) bitarray2)[i] & ~((unsigned long *) bitarray1)[i]; if(comp4) right++; i++; } /* Do the trailing slow narrow unsigned integer part */ i *= sizeof(unsigned long); i++; while(i < items) { comp1 = bitarray1[i] & ~bitarray2[i]; if(comp1) left++; comp1 = bitarray2[i] & ~bitarray1[i]; if(comp1) right++; i++; } /* Determine set comparison outcomes */ if((left > 0) && (right == 0)) /* array1 is a superset of array2 */ i = 1; else if((left == 0) && (right > 0)) /* array2 is a superset of array1 */ i = -1; else if((left == 0) && (right == 0)) /* array1 and array2 are identical */ i = 0; else i = -2; /* indicate all other outcomes */ return( i ); } STATIC workarraysrec *mempool_create(lprec *lp) { workarraysrec *temp; temp = (workarraysrec *) calloc(1, sizeof(workarraysrec)); temp->lp = lp; return( temp ); } STATIC char *mempool_obtainVector(workarraysrec *mempool, int count, int unitsize) { char *newmem = NULL; MYBOOL *bnewmem = NULL; int *inewmem = NULL, size, i, ib, ie, memMargin = 0; REAL *rnewmem = NULL; /* First find the iso-sized window (binary search) */ size = count*unitsize; memMargin += size; ib = 0; ie = mempool->count-1; while(ie >= ib) { i = (ib+ie) / 2; if(abs(mempool->vectorsize[i]) > memMargin) ie = i-1; else if(abs(mempool->vectorsize[i]) < size) ib = i+1; else { /* Find the beginning of the exact-sized array group */ do { ib = i; i--; } while((i >= 0) && (abs(mempool->vectorsize[i]) >= size)); break; } } /* Check if we have a preallocated unused array of sufficient size */ ie = mempool->count-1; for(i = ib; i <= ie; i++) if(mempool->vectorsize[i] < 0) break; /* Obtain and activate existing, unused vector if we are permitted */ if(i <= ie) { #ifdef Paranoia if((mempool->vectorsize[i] > 0) || (abs(mempool->vectorsize[i]) < size)) { lprec *lp = mempool->lp; lp->report(lp, SEVERE, "mempool_obtainVector: Invalid %s existing vector selected\n", (ie < 0 ? "too small" : "occupied")); lp->spx_status = NOMEMORY; lp->bb_break = TRUE; return( newmem ); } #endif newmem = mempool->vectorarray[i]; mempool->vectorsize[i] *= -1; } /* Otherwise allocate a new vector */ else if(unitsize == sizeof(MYBOOL)) { allocMYBOOL(mempool->lp, &bnewmem, count, TRUE); newmem = (char *) bnewmem; } else if(unitsize == sizeof(int)) { allocINT(mempool->lp, &inewmem, count, TRUE); newmem = (char *) inewmem; } else if(unitsize == sizeof(REAL)) { allocREAL(mempool->lp, &rnewmem, count, TRUE); newmem = (char *) rnewmem; } /* Insert into master array if necessary (maintain sort by ascending size) */ if((i > ie) && (newmem != NULL)) { mempool->count++; if(mempool->count >= mempool->size) { mempool->size += 10; mempool->vectorarray = (char **) realloc(mempool->vectorarray, sizeof(*(mempool->vectorarray))*mempool->size); mempool->vectorsize = (int *) realloc(mempool->vectorsize, sizeof(*(mempool->vectorsize))*mempool->size); } ie++; i = ie + 1; if(i < mempool->count) { MEMMOVE(mempool->vectorarray+i, mempool->vectorarray+ie, 1); MEMMOVE(mempool->vectorsize+i, mempool->vectorsize+ie, 1); } mempool->vectorarray[ie] = newmem; mempool->vectorsize[ie] = size; } return( newmem ); } STATIC MYBOOL mempool_releaseVector(workarraysrec *mempool, char *memvector, MYBOOL forcefree) { int i; #if 0 forcefree = TRUE; #endif for(i = mempool->count-1; i >= 0; i--) if(mempool->vectorarray[i] == memvector) break; if((i < 0) || (mempool->vectorsize[i] < 0)) return( FALSE ); if(forcefree) { FREE(mempool->vectorarray[i]); mempool->count--; for(; i < mempool->count; i++) mempool->vectorarray[i] = mempool->vectorarray[i+1]; } else mempool->vectorsize[i] *= -1; return( TRUE ); } STATIC MYBOOL mempool_free(workarraysrec **mempool) { int i = (*mempool)->count; while(i > 0) { i--; if((*mempool)->vectorsize[i] < 0) /* Handle unused vectors */ (*mempool)->vectorsize[i] *= -1; mempool_releaseVector(*mempool, (*mempool)->vectorarray[i], TRUE); } FREE((*mempool)->vectorarray); FREE((*mempool)->vectorsize); FREE(*mempool); return( TRUE ); } REAL *cloneREAL(lprec *lp, REAL *origlist, int size) { REAL *newlist; size += 1; if(allocREAL(lp, &newlist, size, FALSE)) MEMCOPY(newlist, origlist, size); return(newlist); } MYBOOL *cloneMYBOOL(lprec *lp, MYBOOL *origlist, int size) { MYBOOL *newlist; size += 1; if(allocMYBOOL(lp, &newlist, size, FALSE)) MEMCOPY(newlist, origlist, size); return(newlist); } int *cloneINT(lprec *lp, int *origlist, int size) { int *newlist; size += 1; if(allocINT(lp, &newlist, size, FALSE)) MEMCOPY(newlist, origlist, size); return(newlist); } STATIC void roundVector(LREAL *myvector, int endpos, LREAL roundzero) { if(roundzero > 0) for(; endpos >= 0; myvector++, endpos--) if(fabs(*myvector) < roundzero) *myvector = 0; } STATIC REAL normalizeVector(REAL *myvector, int endpos) /* Scale the ingoing vector so that its norm is unit, and return the original length */ { int i; REAL SSQ; /* Cumulate squares */ SSQ = 0; for(i = 0; i <= endpos; myvector++, i++) SSQ += (*myvector) * (*myvector); /* Normalize */ SSQ = sqrt(SSQ); if(SSQ > 0) for(myvector--; i > 0; myvector--, i--) (*myvector) /= SSQ; return( SSQ ); } /* ---------------------------------------------------------------------------------- */ /* Other general utilities */ /* ---------------------------------------------------------------------------------- */ STATIC void swapINT(int *item1, int *item2) { int hold = *item1; *item1 = *item2; *item2 = hold; } STATIC void swapREAL(REAL *item1, REAL *item2) { REAL hold = *item1; *item1 = *item2; *item2 = hold; } STATIC void swapPTR(void **item1, void **item2) { void *hold; hold = *item1; *item1 = *item2; *item2 = hold; } STATIC REAL restoreINT(REAL valREAL, REAL epsilon) { REAL valINT, fracREAL, fracABS; fracREAL = modf(valREAL, &valINT); fracABS = fabs(fracREAL); if(fracABS < epsilon) return(valINT); else if(fracABS > 1-epsilon) { if(fracREAL < 0) return(valINT-1); else return(valINT+1); } return(valREAL); } STATIC REAL roundToPrecision(REAL value, REAL precision) { #if 1 REAL vmod; int vexp2, vexp10; LLONG sign; if(precision == 0) return(value); sign = my_sign(value); value = fabs(value); /* Round to integer if possible */ if(value < precision) return( 0 ); else if(value == floor(value)) return( value*sign ); else if((value < (REAL) MAXINT64) && (modf((REAL) (value+precision), &vmod) < precision)) { /* sign *= (LLONG) (value+precision); */ sign *= (LLONG) (value+0.5); return( (REAL) sign ); } /* Optionally round with base 2 representation for additional precision */ #define roundPrecisionBase2 #ifdef roundPrecisionBase2 value = frexp(value, &vexp2); #else vexp2 = 0; #endif /* Convert to desired precision */ vexp10 = (int) log10(value); precision *= pow(10.0, vexp10); modf(value/precision+0.5, &value); value *= sign*precision; /* Restore base 10 representation if base 2 was active */ if(vexp2 != 0) value = ldexp(value, vexp2); #endif return( value ); } /* ---------------------------------------------------------------------------------- */ /* Searching function specialized for lp_solve */ /* ---------------------------------------------------------------------------------- */ STATIC int searchFor(int target, int *attributes, int size, int offset, MYBOOL absolute) { int beginPos, endPos; int newPos, match; /* Set starting and ending index offsets */ beginPos = offset; endPos = beginPos + size - 1; /* Do binary search logic based on a sorted attribute vector */ newPos = (beginPos + endPos) / 2; match = attributes[newPos]; if(absolute) match = abs(match); while(endPos - beginPos > LINEARSEARCH) { if(match < target) { beginPos = newPos + 1; newPos = (beginPos + endPos) / 2; match = attributes[newPos]; if(absolute) match = abs(match); } else if(match > target) { endPos = newPos - 1; newPos = (beginPos + endPos) / 2; match = attributes[newPos]; if(absolute) match = abs(match); } else { beginPos = newPos; endPos = newPos; } } /* Do linear (unsorted) search logic */ if(endPos - beginPos <= LINEARSEARCH) { match = attributes[beginPos]; if(absolute) match = abs(match); while((beginPos < endPos) && (match != target)) { beginPos++; match = attributes[beginPos]; if(absolute) match = abs(match); } if(match == target) endPos = beginPos; } /* Return the index if a match was found, or signal failure with a -1 */ if((beginPos == endPos) && (match == target)) return(beginPos); else return(-1); } /* ---------------------------------------------------------------------------------- */ /* Other supporting math routines */ /* ---------------------------------------------------------------------------------- */ STATIC MYBOOL isINT(lprec *lp, REAL value) { #if 0 return( (MYBOOL) (modf(fabs(value)+lp->epsint, &value) < 2*lp->epsint) ); #elif 1 value = fabs(value)+lp->epsint; return( (MYBOOL) (my_reldiff(value, floor(value)) < 2*lp->epsint) ); #elif 0 REAL hold; value = fabs(value); hold = pow(10, MIN(-2, log10(value+1)+log10(lp->epsint))); return( (MYBOOL) (modf(value+lp->epsint, &value) < 2*hold) ); #elif 0 value -= (REAL)floor(value); return( (MYBOOL) ((value < lp->epsint) || (value > (1 - lp->epsint)) ); #else value += lp->epsint; return( (MYBOOL) (fabs(value-floor(value)) < 2*lp->epsint) ); #endif } STATIC MYBOOL isOrigFixed(lprec *lp, int varno) { return( (MYBOOL) (lp->orig_upbo[varno] - lp->orig_lowbo[varno] <= lp->epsmachine) ); } STATIC void chsign_bounds(REAL *lobound, REAL *upbound) { REAL temp; temp = *upbound; if(fabs(*lobound) > 0) *upbound = -(*lobound); else *upbound = 0; if(fabs(temp) > 0) *lobound = -temp; else *lobound = 0; } /* ---------------------------------------------------------------------------------- */ /* Define randomization routine */ /* ---------------------------------------------------------------------------------- */ STATIC REAL rand_uniform(lprec *lp, REAL range) { static MYBOOL randomized = FALSE; /* static ok here for reentrancy/multithreading */ if(!randomized) { randomized = TRUE; srand((unsigned) time( NULL )); } range *= (REAL) rand() / (REAL) RAND_MAX; return( range ); } /* ---------------------------------------------------------------------------------- */ /* Define routines for doubly linked lists of integers */ /* ---------------------------------------------------------------------------------- */ STATIC int createLink(int size, LLrec **linkmap, MYBOOL *usedpos) { int i, j; MYBOOL reverse; *linkmap = (LLrec *) calloc(1, sizeof(**linkmap)); if(*linkmap == NULL) return( -1 ); reverse = (MYBOOL) (size < 0); if(reverse) size = -size; (*linkmap)->map = (int *) calloc(2*(size + 1), sizeof(int)); if((*linkmap)->map == NULL) return( -1 ); (*linkmap)->size = size; j = 0; if(usedpos == NULL) (*linkmap)->map[0] = 0; else { for(i = 1; i <= size; i++) if(!usedpos[i] ^ reverse) { /* Set the forward link */ (*linkmap)->map[j] = i; /* Set the backward link */ (*linkmap)->map[size+i] = j; j = i; if((*linkmap)->count == 0) (*linkmap)->firstitem = i; (*linkmap)->lastitem = i; (*linkmap)->count++; } } (*linkmap)->map[2*size+1] = j; return( (*linkmap)->count ); } STATIC MYBOOL freeLink(LLrec **linkmap) { MYBOOL status = TRUE; if((linkmap == NULL) || (*linkmap == NULL)) status = FALSE; else { if((*linkmap)->map != NULL) free((*linkmap)->map); free(*linkmap); *linkmap = NULL; } return( status ); } STATIC int sizeLink(LLrec *linkmap) { return(linkmap->size); } STATIC MYBOOL isActiveLink(LLrec *linkmap, int itemnr) { if((linkmap->map[itemnr] != 0) || (linkmap->map[linkmap->size+itemnr] != 0) || (linkmap->map[0] == itemnr)) return( TRUE ); else return( FALSE ); } STATIC int countActiveLink(LLrec *linkmap) { return(linkmap->count); } STATIC int countInactiveLink(LLrec *linkmap) { return(linkmap->size-linkmap->count); } STATIC int firstActiveLink(LLrec *linkmap) { return(linkmap->map[0]); } STATIC int lastActiveLink(LLrec *linkmap) { return(linkmap->map[2*linkmap->size+1]); } STATIC MYBOOL appendLink(LLrec *linkmap, int newitem) { int k, size; size = linkmap->size; if(linkmap->map[newitem] != 0) return( FALSE ); /* Link forward */ k = linkmap->map[2*size+1]; linkmap->map[k] = newitem; /* Link backward */ linkmap->map[size+newitem] = k; linkmap->map[2*size+1] = newitem; /* Update count and return */ if(linkmap->count == 0) linkmap->firstitem = newitem; linkmap->lastitem = newitem; linkmap->count++; return( TRUE ); } STATIC MYBOOL insertLink(LLrec *linkmap, int afteritem, int newitem) { int k, size; size = linkmap->size; if(linkmap->map[newitem] != 0) return( FALSE ); if(afteritem == linkmap->map[2*size+1]) appendLink(linkmap, newitem); else { /* Link forward */ k = linkmap->map[afteritem]; linkmap->map[afteritem] = newitem; linkmap->map[newitem] = k; /* Link backward */ linkmap->map[size+k] = newitem; linkmap->map[size+newitem] = afteritem; /* Update count */ SETMIN(linkmap->firstitem, newitem); SETMAX(linkmap->lastitem, newitem); linkmap->count++; } return( TRUE ); } STATIC MYBOOL setLink(LLrec *linkmap, int newitem) { if(isActiveLink(linkmap, newitem)) return( FALSE ); else return( insertLink(linkmap, prevActiveLink(linkmap, newitem), newitem) ); } STATIC MYBOOL fillLink(LLrec *linkmap) { int k, size; size = linkmap->size; k = firstActiveLink(linkmap); if(k != 0) return( FALSE ); for(k = 1; k <= size; k++) appendLink(linkmap, k); return( TRUE ); } STATIC int nextActiveLink(LLrec *linkmap, int backitemnr) { if((backitemnr < 0) || (backitemnr > linkmap->size)) return( -1 ); else { if(backitemnr < linkmap->lastitem) while((backitemnr > linkmap->firstitem) && (linkmap->map[backitemnr] == 0)) backitemnr--; return(linkmap->map[backitemnr]); } } STATIC int prevActiveLink(LLrec *linkmap, int forwitemnr) { if((forwitemnr <= 0) || (forwitemnr > linkmap->size+1)) return( -1 ); else { if(forwitemnr > linkmap->lastitem) return( linkmap->lastitem); if(forwitemnr > linkmap->firstitem) { forwitemnr += linkmap->size; while((forwitemnr < linkmap->size + linkmap->lastitem) && (linkmap->map[forwitemnr] == 0)) forwitemnr++; } else forwitemnr += linkmap->size; return(linkmap->map[forwitemnr]); } } STATIC int firstInactiveLink(LLrec *linkmap) { int i, n; if(countInactiveLink(linkmap) == 0) return( 0 ); n = 1; i = firstActiveLink(linkmap); while(i == n) { n++; i = nextActiveLink(linkmap, i); } return( n ); } STATIC int lastInactiveLink(LLrec *linkmap) { int i, n; if(countInactiveLink(linkmap) == 0) return( 0 ); n = linkmap->size; i = lastActiveLink(linkmap); while(i == n) { n--; i = prevActiveLink(linkmap, i); } return( n ); } STATIC int nextInactiveLink(LLrec *linkmap, int backitemnr) { do { backitemnr++; } while((backitemnr <= linkmap->size) && isActiveLink(linkmap, backitemnr)); if(backitemnr <= linkmap->size) return( backitemnr ); else return( 0 ); } STATIC int prevInactiveLink(LLrec *linkmap, int forwitemnr) { return( 0 ); } STATIC int removeLink(LLrec *linkmap, int itemnr) { int size, prevnr, nextnr = -1; size = linkmap->size; if((itemnr <= 0) || (itemnr > size)) return( nextnr ); #ifdef Paranoia if(!isActiveLink(linkmap, itemnr)) return( nextnr ); #endif /* Get link data at the specified position */ nextnr = linkmap->map[itemnr]; prevnr = linkmap->map[size+itemnr]; if(itemnr == linkmap->firstitem) linkmap->firstitem = nextnr; if(itemnr == linkmap->lastitem) linkmap->lastitem = prevnr; /* Update forward link */ linkmap->map[prevnr] = linkmap->map[itemnr]; linkmap->map[itemnr] = 0; /* Update backward link */ if(nextnr == 0) linkmap->map[2*size+1] = prevnr; else linkmap->map[size+nextnr] = linkmap->map[size+itemnr]; linkmap->map[size+itemnr] = 0; /* Decrement the count */ linkmap->count--; /* Return the next active item */ return( nextnr ); } STATIC LLrec *cloneLink(LLrec *sourcemap, int newsize, MYBOOL freesource) { LLrec *testmap = NULL; if((newsize == sourcemap->size) || (newsize <= 0)) { createLink(sourcemap->size, &testmap, NULL); MEMCOPY(testmap->map, sourcemap->map, 2*(sourcemap->size+1)); testmap->firstitem = sourcemap->firstitem; testmap->lastitem = sourcemap->lastitem; testmap->size = sourcemap->size; testmap->count = sourcemap->count; } else { int j; createLink(newsize, &testmap, NULL); for(j = firstActiveLink(sourcemap); (j != 0) && (j <= newsize); j = nextActiveLink(sourcemap, j)) appendLink(testmap, j); } if(freesource) freeLink(&sourcemap); return(testmap); } STATIC int compareLink(LLrec *linkmap1, LLrec *linkmap2) { int test; test = memcmp(&linkmap1->size, &linkmap2->size, sizeof(int)); if(test == 0) test = memcmp(&linkmap1->count, &linkmap2->count, sizeof(int)); if(test == 0) test = memcmp(linkmap1->map, linkmap2->map, sizeof(int)*(2*linkmap1->size+1)); return( test ); } STATIC MYBOOL verifyLink(LLrec *linkmap, int itemnr, MYBOOL doappend) { LLrec *testmap; testmap = cloneLink(linkmap, -1, FALSE); if(doappend) { appendLink(testmap, itemnr); removeLink(testmap, itemnr); } else { int previtem = prevActiveLink(testmap, itemnr); removeLink(testmap, itemnr); insertLink(testmap, previtem, itemnr); } itemnr = compareLink(linkmap, testmap); freeLink(&testmap); return((MYBOOL) (itemnr == 0)); } /* Packed vector routines */ STATIC PVrec *createPackedVector(int size, REAL *values, int *workvector) { int i, k; REGISTER REAL ref; PVrec *newPV = NULL; MYBOOL localWV = (MYBOOL) (workvector == NULL); if(localWV) workvector = (int *) malloc((size+1)*sizeof(*workvector)); /* Tally equal-valued vector entries - also check if it is worth compressing */ k = 0; workvector[k] = 1; ref = values[1]; for(i = 2; i <= size; i++) { if(fabs(ref - values[i]) > DEF_EPSMACHINE) { k++; workvector[k] = i; ref = values[i]; } } if(k > size / 2) { if(localWV) FREE(workvector); return( newPV ); } /* Create the packing object, adjust the position vector and allocate value vector */ newPV = (PVrec *) malloc(sizeof(*newPV)); k++; /* Adjust from index to to count */ newPV->count = k; if(localWV) newPV->startpos = (int *) realloc(workvector, (k + 1)*sizeof(*(newPV->startpos))); else { newPV->startpos = (int *) malloc((k + 1)*sizeof(*(newPV->startpos))); MEMCOPY(newPV->startpos, workvector, k); } newPV->startpos[k] = size + 1; /* Store terminal index + 1 for searching purposes */ newPV->value = (REAL *) malloc(k*sizeof(*(newPV->value))); /* Fill the values vector before returning */ for(i = 0; i < k; i++) newPV->value[i] = values[newPV->startpos[i]]; return( newPV ); } STATIC MYBOOL unpackPackedVector(PVrec *PV, REAL **target) { int i, ii, k; REGISTER REAL ref; /* Test for validity of the target and create it if necessary */ if(target == NULL) return( FALSE ); if(*target == NULL) allocREAL(NULL, target, PV->startpos[PV->count], FALSE); /* Expand the packed vector into the target */ i = PV->startpos[0]; for(k = 0; k < PV->count; k++) { ii = PV->startpos[k+1]; ref = PV->value[k]; while (i < ii) { (*target)[i] = ref; i++; } } return( TRUE ); } STATIC REAL getvaluePackedVector(PVrec *PV, int index) { index = searchFor(index, PV->startpos, PV->count, 0, FALSE); index = abs(index)-1; if(index >= 0) return( PV->value[index] ); else return( 0 ); } STATIC MYBOOL freePackedVector(PVrec **PV) { if((PV == NULL) || (*PV == NULL)) return( FALSE ); FREE((*PV)->value); FREE((*PV)->startpos); FREE(*PV); return( TRUE ); } STATIC void pushPackedVector(PVrec *PV, PVrec *parent) { PV->parent = parent; } STATIC PVrec *popPackedVector(PVrec *PV) { PVrec *parent = PV->parent; freePackedVector(&PV); return( parent ); } MSVMpack1.2/lp_solve_5.5/lp_presolve.h0000664000175000017500000001011311141374247016641 0ustar lauerlauer#ifndef HEADER_lp_presolve #define HEADER_lp_presolve #include "lp_types.h" #include "lp_matrix.h" /* -------------------------------------------------------------------------------------------- */ /* Defines for various presolve options */ /* -------------------------------------------------------------------------------------------- */ #define MAX_PSMERGELOOPS 2 /* Max loops to merge compatible constraints */ #define MAX_PSLINDEPLOOPS 1 /* Max loops to detect linearly dependendent constraints */ #define MAX_PSBOUNDTIGHTENLOOPS 5 /* Maximumn number of loops to allow bound tightenings */ #define MIN_SOS1LENGTH 4 /* Minimum length of a constraint for conversion to SOS1 */ #if 1 #define PRESOLVE_EPSVALUE (0.1*lp->epsprimal) #else #define PRESOLVE_EPSVALUE lp->epsvalue #endif #define PRESOLVE_EPSPIVOT 1.0e-3 /* Looses robustness at values smaller than ~1.0e-3 */ #define PRESOLVE_BOUNDSLACK 10 /* Extra error recovery/tolerance margin */ #define DoPresolveRounding /* Use absolute and directed rounding (disable at own risk) */ /*#define DoPresolveRelativeTest*/ /*#define PresolveForceUpdateMax*/ /*#define DualFeasibilityLogicEQ2*/ /* Add low-order feasibility/accuracy logic to elimEQ2 */ #define DivisorIntegralityLogicEQ2 /* Always prefer integer divisors */ #define FindImpliedEqualities /* Detect equalities (default is enabled) */ #define Eq2Reldiff /*#define SavePresolveEliminated */ /* Enable to activate storage of eliminated matrix data */ /*#define UseDualPresolve */ /* Enable to use full dual information for presolve */ typedef struct _psrec { LLrec *varmap; int **next; int *empty; int *plucount; int *negcount; int *pluneg; int *infcount; REAL *plulower; REAL *neglower; REAL *pluupper; REAL *negupper; int allocsize; } psrec; typedef struct _presolverec { psrec *rows; psrec *cols; LLrec *EQmap; LLrec *LTmap; LLrec *INTmap; REAL *pv_upbo; REAL *pv_lobo; REAL *dv_upbo; REAL *dv_lobo; lprec *lp; REAL epsvalue; REAL epspivot; int innerloops; int middleloops; int outerloops; int nzdeleted; MYBOOL forceupdate; } presolverec; #ifdef __cplusplus extern "C" { #endif /* Put function headers here */ STATIC MYBOOL presolve_createUndo(lprec *lp); STATIC MYBOOL presolve_rebuildUndo(lprec *lp, MYBOOL isprimal); STATIC MYBOOL inc_presolve_space(lprec *lp, int delta, MYBOOL isrows); STATIC MYBOOL presolve_setOrig(lprec *lp, int orig_rows, int orig_cols); STATIC MYBOOL presolve_colfix(presolverec *psdata, int colnr, REAL newvalue, MYBOOL remove, int *tally); STATIC MYBOOL presolve_fillUndo(lprec *lp, int orig_rows, int orig_cols, MYBOOL setOrig); STATIC MYBOOL presolve_freeUndo(lprec *lp); STATIC MYBOOL presolve_updatesums(presolverec *psdata); INLINE int presolve_nextrow(presolverec *psdata, int colnr, int *previtem); INLINE int presolve_nextcol(presolverec *psdata, int rownr, int *previtem); STATIC presolverec *presolve_init(lprec *lp); STATIC void presolve_free(presolverec **psdata); STATIC int presolve_shrink(presolverec *psdata, int *nConRemove, int *nVarRemove); STATIC void presolve_rowremove(presolverec *psdata, int rownr, MYBOOL allowcoldelete); STATIC int presolve_colremove(presolverec *psdata, int colnr, MYBOOL allowrowdelete); STATIC MYBOOL presolve_colfixdual(presolverec *psdata, int colnr, REAL *fixValue, int *status); INLINE int presolve_rowlength(presolverec *psdata, int rownr) { int *items = psdata->rows->next[rownr]; if(items == NULL) return( 0 ); else return( items[0] ); } INLINE int presolve_collength(presolverec *psdata, int colnr) { int *items = psdata->cols->next[colnr]; if(items == NULL) return( 0 ); else return( items[0] ); } STATIC int presolve(lprec *lp); STATIC MYBOOL postsolve(lprec *lp, int status); #ifdef __cplusplus } #endif #endif /* HEADER_lp_presolve */ MSVMpack1.2/lp_solve_5.5/lpkit.h0000664000175000017500000000226011141374241015430 0ustar lauerlauer#include "lp_lib.h" #include "lp_report.h" #define MALLOC(ptr, nr, type)\ ((((nr) == 0) || ((ptr = (type *) malloc((size_t)((nr) * sizeof(*ptr)))) == NULL)) ? \ report(NULL, CRITICAL, "malloc of %d bytes failed on line %d of file %s\n",\ (nr) * sizeof(*ptr), __LINE__, __FILE__), (ptr = NULL /* (void *) 0 */) : \ ptr\ ) #define CALLOC(ptr, nr, type)\ ((((nr) == 0) || ((ptr = (type *) calloc((size_t)(nr), sizeof(*ptr))) == NULL)) ? \ report(NULL, CRITICAL, "calloc of %d bytes failed on line %d of file %s\n",\ (nr) * sizeof(*ptr), __LINE__, __FILE__), (ptr = NULL /* (void *) 0 */) : \ ptr\ ) #define REALLOC(ptr, nr, type)\ ((((nr) == 0) || ((ptr = (type *) realloc(ptr, (size_t)((nr) * sizeof(*ptr)))) == NULL)) ? \ report(NULL, CRITICAL, "realloc of %d bytes failed on line %d of file %s\n",\ (nr) * sizeof(*ptr), __LINE__, __FILE__), (ptr = NULL /* (void *) 0 */) : \ ptr\ ) #if defined FREE # undef FREE #endif #define FREE(ptr) if (ptr != NULL) {free(ptr), ptr = NULL;} else #define MALLOCCPY(nptr, optr, nr, type)\ (MALLOC(nptr, nr, type), (nptr != NULL) ? memcpy(nptr, optr, (size_t)((nr) * sizeof(*optr))) : 0, nptr) MSVMpack1.2/lp_solve_5.5/lp_rlp.l0000664000175000017500000001537411141374251015614 0ustar lauerlauerWS1 [ \t] WS2 [ \t\r\n] LT [A-Za-z] KR [A-Za-z0-9_\[\]\{\}/.&#$%~'@^] DI [0-9] INNM {DI}+ NM (({DI}+\.?{DI}*)|(\.{DI}+))([Ee][-+]?{DI}+)? VR {LT}{KR}*(<{KR}+>)? OPEQ = OPLE [<]=? OPGE [>]=? EOW $|[*+-;<=>]|{WS2}+ INF {WS2}*[-+][Ii][Nn][Ff]([Ii][Nn][Ii][Tt]([Ee]|[Yy]))?{EOW} S_OP [-+ \t\n\r]+ MIN [mM][iI][nN]([iI][mM][iI][zZsS][eE])?{WS1}*: MAX [mM][aA][xX]([iI][mM][iI][zZsS][eE])?{WS1}*: INT ^{WS1}*[Ii][Nn][Tt]([Ee][Gg][Ee][Rr])? BIN ^{WS1}*[Bb][Ii][Nn]([Aa][Rr][Yy])? SEC ^{WS1}*([Ss][Ee][Cc])|([Ss][Ee][Mm][Ii]-[Cc][Oo][Nn][Tt][Ii][Nn][Uu][Oo][Uu][Ss])|([Ss][Ee][Mm][Ii])|([Ss][Ee][Mm][Ii][Ss]) SOS ^{WS1}*([Ss][Oo][Ss][12]*)|([Ss][Ee][Tt][Ss]) FREE ^{WS1}*[Ff][Rr][Ee][Ee] LBL {VR}{WS1}*: SOSD {LBL}: /* made reentrant with help of http://www.usualcoding.eu/post/2007/09/03/Building-a-reentrant-parser-in-C-with-Flex/Bison */ /* Note that a minimum version of flex is needed to be able to compile this. Older version don't know the reentrant code. Version 2.5.4 is not enough. Probably at least v2.5.31 is needed. Tested with v2.5.35 */ /* ** We want the scanner to be reentrant, therefore generate no global variables. ** That what the 'reentrant' option is for. ** 'bison-bridge' is used to create a bison compatible scanner and share yylval */ %option reentrant bison-bridge %option noyywrap %option yylineno %start COMMENT %start LINECOMMENT %% "/*" { BEGIN COMMENT; } /* begin skip comment */ "*/" { BEGIN INITIAL; } /* end skip comment */ . { } \n { } \r { } "//" { BEGIN LINECOMMENT; } /* begin skip LINECOMMENT */ \n { BEGIN INITIAL; } /* end skip LINECOMMENT */ \r { BEGIN INITIAL; } /* end skip LINECOMMENT */ . { } {WS2}+ { } "," { parse_parm *pp = PARM; pp->lineno = yylineno; return(COMMA); } {MIN} { parse_parm *pp = PARM; pp->lineno = yylineno; return(MINIMISE); } {MAX} { parse_parm *pp = PARM; pp->lineno = yylineno; return(MAXIMISE); } {INNM} { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = yylineno; pv->f = atof((char *)yytext); return(INTCONS); } /* f contains the last float */ {NM} { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = yylineno; pv->f = atof((char *)yytext); return(CONS); } /* f contains the last float */ {INF} { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; char *ptr, c; pp->lineno = yylineno; pv->f = DEF_INFINITE; pv->Sign = 0; ptr = (char *)yytext; while (isspace(*ptr)) ptr++; if(*ptr == '-') pv->Sign = 1; if(yyleng > 0) { c = yytext[yyleng - 1]; if(!isalnum(c)) unput(c); } return(INF); } /* f contains the last float */ {S_OP} { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; int x; pp->lineno = yylineno; pv->Sign = 0; for(x = 0; x < yyleng; x++) if(yytext[x] == '-' || yytext[x] == '+') pv->Sign = (pv->Sign == (yytext[x] == '+')); return (TOK_SIGN); /* Sign is TRUE if the sign-string represents a '-'. Otherwise Sign is FALSE */ } {INT} { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = yylineno; if((!pv->Within_int_decl) && (!pv->Within_sec_decl) && (!pv->Within_sos_decl) && (!pv->Within_free_decl)) { pv->Within_int_decl = 1; pv->Within_sos_decl1 = FALSE; } return(SEC_INT); } {BIN} { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = yylineno; if((!pv->Within_int_decl) && (!pv->Within_sec_decl) && (!pv->Within_sos_decl) && (!pv->Within_free_decl)) { pv->Within_int_decl = 2; pv->Within_sos_decl1 = FALSE; } return(SEC_BIN); } {SEC} { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = yylineno; if((!pv->Within_int_decl) && (!pv->Within_sec_decl) && (!pv->Within_sos_decl) && (!pv->Within_free_decl)) { pv->Within_sec_decl = TRUE; pv->Within_sos_decl1 = FALSE; } return(SEC_SEC); } {SOS} { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = yylineno; if(!pv->Within_sos_decl) pv->SOStype0 = (short)atoi(((char *)yytext) + 3); if((!pv->Within_int_decl) && (!pv->Within_sec_decl) && (!pv->Within_sos_decl) && (!pv->Within_free_decl)) pv->Within_sos_decl = TRUE; return(SEC_SOS); } {SOSD} { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = yylineno; FREE(pv->Last_var); pv->Last_var = strdup((char *)yytext); pv->Last_var[strlen(pv->Last_var) - 2] = 0; return(SOSDESCR); } {FREE} { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = yylineno; if((!pv->Within_int_decl) && (!pv->Within_sec_decl) && (!pv->Within_sos_decl) && (!pv->Within_free_decl)) { pv->Within_free_decl = TRUE; pv->Within_sos_decl1 = FALSE; } return(SEC_FREE); } {LBL} { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; char *ptr; pp->lineno = yylineno; FREE(pv->Last_var); pv->Last_var = strdup((char *)yytext); ptr = pv->Last_var + strlen(pv->Last_var); ptr[-1] = ' '; while ((--ptr >= pv->Last_var) && (isspace(*ptr))) *ptr = 0; return(VARIABLECOLON); } {VR} { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = yylineno; FREE(pv->Last_var); pv->Last_var = strdup((char *)yytext); return(VAR); } ":" { parse_parm *pp = PARM; pp->lineno = yylineno; return (COLON); } "*" { parse_parm *pp = PARM; pp->lineno = yylineno; return(AR_M_OP); } {OPEQ} { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = yylineno; pv->OP = *yytext; return(RE_OPEQ); } {OPLE} { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = yylineno; pv->OP = *yytext; return(RE_OPLE); } {OPGE} { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = yylineno; pv->OP = *yytext; return(RE_OPGE); } ";" { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = yylineno; pv->Within_int_decl = pv->Within_sec_decl = pv->Within_sos_decl = pv->Within_free_decl = FALSE; check_int_sec_sos_free_decl(pp, (int) pv->Within_int_decl, (int) pv->Within_sec_decl, (int) pv->Within_sos_decl, (int) pv->Within_free_decl); return(END_C); } . { parse_parm *pp = PARM; pp->lineno = yylineno; report(NULL, CRITICAL, "LEX ERROR : %s lineno %d\n", yytext, yylineno); return(UNDEFINED); } %% MSVMpack1.2/lp_solve_5.5/Makefile.in0000664000175000017500000000603610641503502016204 0ustar lauerlauerPACKAGE_NAME=@PACKAGE_NAME@ PACKAGE_STRING=@PACKAGE_NAME@_@PACKAGE_VERSION@ CCSHARED=@CCSHARED@ prefix = @prefix@ includedir = @includedir@/lpsolve libdir = @libdir@ CFLAGS=@CFLAGS@ INCLUDES=-I. -I./shared -I./bfp -I./bfp/bfp_LUSOL -I./bfp/bfp_LUSOL/LUSOL -I./colamd DEFINES=-DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine @DEF@ LIBS=-lc -lm -ldl INSTALL_DATA = ${INSTALL} -m 644 INSTALL_PROGRAM = ${INSTALL} INSTALL_SCRIPT = ${INSTALL} INSTALL = @INSTALL@ mkdir_p = mkdir -p HEADERS = \ declare.h \ fortify.h \ ini.h \ lp_crash.h \ lp_explicit.h \ lp_fortify.h \ lp_Hash.h \ lpkit.h \ lp_lib.h \ lp_matrix.h \ lp_MDO.h \ lp_mipbb.h \ lp_MPS.h \ lp_presolve.h \ lp_price.h \ lp_pricePSE.h \ lp_report.h \ lp_rlp.h \ lp_scale.h \ lp_simplex.h \ lp_solveDLL.h \ lpsolve.h \ lp_SOS.h \ lp_types.h \ lp_utils.h \ lp_wlp.h \ ufortify.h \ yacc_read.h SOURCES = lp_MDO.c \ shared/commonlib.c \ shared/mmio.c \ shared/myblas.c \ ini.c \ fortify.c \ colamd/colamd.c \ lp_rlp.c \ lp_crash.c \ bfp/bfp_LUSOL/lp_LUSOL.c \ bfp/bfp_LUSOL/LUSOL/lusol.c \ lp_Hash.c \ lp_lib.c \ lp_wlp.c \ lp_matrix.c \ lp_mipbb.c \ lp_MPS.c \ lp_params.c \ lp_presolve.c \ lp_price.c \ lp_pricePSE.c \ lp_report.c \ lp_scale.c \ lp_simplex.c \ lp_SOS.c \ lp_utils.c \ yacc_read.c all: liblpsolve55.a @SHARED_LIB@ # OBJECTS = $(patsubst %.c,%.o,$(SOURCES)) #.c.o: # $(CC) -s -c $(INCLUDES) $(CFLAGS) $(DEFINES) $(SOURCES) liblpsolve55.a: $(SOURCES) $(CC) -s -c $(INCLUDES) $(CFLAGS) $(DEFINES) $(SOURCES) ar rv $@ `echo $(SOURCES)|sed s/[.]c/.o/g|sed 's/[^ ]*\///g'` ranlib $@ liblpsolve55@SO@: $(SOURCES) $(CC) $(CCSHARED) -s -c $(INCLUDES) $(CFLAGS) $(DEFINES) $(SOURCES) $(CC) -shared -Wl,-Bsymbolic -Wl,-soname,$@ -o $@ `echo $(SOURCES)|sed s/[.]c/.o/g|sed 's/[^ ]*\///g'` $(LIBS) install: install-HEADERS install-LIBRARIES install-HEADERS: $(HEADERS) test -d $(includedir) || $(mkdir_p) $(includedir) @list='$(HEADERS)'; for p in $$list; do \ echo " $(INSTALL) $$p $(includedir)/$$f"; \ $(INSTALL) $$p $(includedir)/$$f; \ done install-LIBRARIES: liblpsolve55.a @SHARED_LIB@ test -d $(libdir) || $(mkdir_p) $(libdir) @list='liblpsolve55.a @SHARED_LIB@'; for p in $$list; do \ if test -f $$p; then \ echo " $(INSTALL) $$p $(libdir)/$$f"; \ $(INSTALL) $$p $(libdir)/$$f; \ else :; fi; \ done uninstall-LIBRARIES: @set -x; list='liblpsolve55.a @SHARED_LIB@'; for p in $$list; do \ echo " rm -f $(libdir)/$$f"; \ rm -f "$(libdir)/$$f"; \ done uninstall: uninstall-HEADERS uninstall-LIBRARIES uninstall-HEADERS: @set -x; @list=$(HEADERS); for p in $$list; do \ echo " rm -f $(includedir)/$$f"; \ rm -f "$(includedir)/$$f"; \ done dist: mkdir $(PACKAGE_STRING) tar -cpf- -T MANIFEST | (cd $(PACKAGE_STRING) && tar -xpf- ) tar -czpf $(PACKAGE_STRING).tar.bz2 ./$(PACKAGE_STRING) -rm -fr $(PACKAGE_STRING) CLEANFILES = *.o *.so *.a clean: -rm -f $(CLEANFILES) .PHONY: install install-HEADERS install-LIBRARIES uninstall uninstall-HEADERS uninstall-LIBRARIES all MSVMpack1.2/lp_solve_5.5/bfp/0000775000175000017500000000000012104711130014673 5ustar lauerlauerMSVMpack1.2/lp_solve_5.5/bfp/lp_BFP.h0000664000175000017500000001100011141443437016152 0ustar lauerlauer /* ---------------------------------------------------------------------------------- */ /* lp_solve v5+ headers for basis inversion / factorization libraries */ /* ---------------------------------------------------------------------------------- */ #define BFP_STATUS_RANKLOSS -1 #define BFP_STATUS_SUCCESS 0 #define BFP_STATUS_SINGULAR 1 #define BFP_STATUS_UNSTABLE 2 #define BFP_STATUS_NOPIVOT 3 #define BFP_STATUS_DIMERROR 4 #define BFP_STATUS_DUPLICATE 5 #define BFP_STATUS_NOMEMORY 6 #define BFP_STATUS_ERROR 7 /* Unspecified, command-related error */ #define BFP_STATUS_FATAL 8 #define BFP_STAT_ERROR -1 #define BFP_STAT_REFACT_TOTAL 0 #define BFP_STAT_REFACT_TIMED 1 #define BFP_STAT_REFACT_DENSE 2 #ifndef BFP_CALLMODEL #ifdef WIN32 #define BFP_CALLMODEL __stdcall /* "Standard" call model */ #else #define BFP_CALLMODEL #endif #endif #ifdef RoleIsExternalInvEngine #define __BFP_EXPORT_TYPE __EXPORT_TYPE #else #define __BFP_EXPORT_TYPE #endif /* Routines with UNIQUE implementations for each inversion engine */ /* ---------------------------------------------------------------------------------- */ char __BFP_EXPORT_TYPE *(BFP_CALLMODEL bfp_name)(void); void __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_free)(lprec *lp); MYBOOL __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_resize)(lprec *lp, int newsize); int __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_nonzeros)(lprec *lp, MYBOOL maximum); int __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_memallocated)(lprec *lp); int __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_preparefactorization)(lprec *lp); int __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_factorize)(lprec *lp, int uservars, int Bsize, MYBOOL *usedpos, MYBOOL final); MYBOOL __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_finishupdate)(lprec *lp, MYBOOL changesign); void __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_ftran_normal)(lprec *lp, REAL *pcol, int *nzidx); void __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_ftran_prepare)(lprec *lp, REAL *pcol, int *nzidx); void __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_btran_normal)(lprec *lp, REAL *prow, int *nzidx); int __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_status)(lprec *lp); int __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_findredundant)(lprec *lp, int items, getcolumnex_func cb, int *maprow, int*mapcol); /* Routines SHARED for all inverse implementations; located in lp_BFP1.c */ /* ---------------------------------------------------------------------------------- */ MYBOOL __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_compatible)(lprec *lp, int bfpversion, int lpversion, int sizeofvar); int __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_indexbase)(lprec *lp); int __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_rowoffset)(lprec *lp); int __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_pivotmax)(lprec *lp); REAL __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_efficiency)(lprec *lp); REAL __BFP_EXPORT_TYPE *(BFP_CALLMODEL bfp_pivotvector)(lprec *lp); int __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_pivotcount)(lprec *lp); MYBOOL __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_mustrefactorize)(lprec *lp); int __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_refactcount)(lprec *lp, int kind); MYBOOL __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_isSetI)(lprec *lp); int *bfp_createMDO(lprec *lp, MYBOOL *usedpos, int count, MYBOOL doMDO); void __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_updaterefactstats)(lprec *lp); int BFP_CALLMODEL bfp_rowextra(lprec *lp); /* Routines with OPTIONAL SHARED code; template routines suitable for canned */ /* inverse engines are located in lp_BFP2.c */ /* ---------------------------------------------------------------------------------- */ MYBOOL __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_init)(lprec *lp, int size, int deltasize, char *options); MYBOOL __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_restart)(lprec *lp); MYBOOL __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_implicitslack)(lprec *lp); MYBOOL __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_pivotalloc)(lprec *lp, int newsize); int __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_colcount)(lprec *lp); MYBOOL __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_canresetbasis)(lprec *lp); void __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_finishfactorization)(lprec *lp); LREAL __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_prepareupdate)(lprec *lp, int row_nr, int col_nr, REAL *pcol); REAL __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_pivotRHS)(lprec *lp, LREAL theta, REAL *pcol); void __BFP_EXPORT_TYPE (BFP_CALLMODEL bfp_btran_double)(lprec *lp, REAL *prow, int *pnzidx, REAL *drow, int *dnzidx); MSVMpack1.2/lp_solve_5.5/bfp/lp_BFP1.c0000664000175000017500000001270111141443437016237 0ustar lauerlauer /* Routines located in lp_BFP1.cpp; common for all factorization engines */ /* Cfr. lp_BFP.h for definitions */ /* ---------------------------------------------------------------------------------- */ /* Changes: */ /* 29 May 2004 Corrected calculation of bfp_efficiency(), which required */ /* modifying the max_Bsize to include slack variables. KE. */ /* 16 June 2004 Make the symbolic minimum degree ordering routine available */ /* to BFPs as a routine internal to the library. KE */ /* 1 July 2004 Change due to change in MDO naming. */ /* ---------------------------------------------------------------------------------- */ /* MUST MODIFY */ MYBOOL BFP_CALLMODEL bfp_compatible(lprec *lp, int bfpversion, int lpversion, int sizeofvar) { MYBOOL status = FALSE; if((lp != NULL) && (bfpversion == BFPVERSION) && (sizeof(REAL) == sizeofvar)) { #if 0 if(lpversion == MAJORVERSION) /* Forces BFP renewal at lp_solve major version changes */ #endif status = TRUE; } return( status ); } /* DON'T MODIFY */ int BFP_CALLMODEL bfp_status(lprec *lp) { return(lp->invB->status); } /* DON'T MODIFY */ int BFP_CALLMODEL bfp_indexbase(lprec *lp) { return( MATINDEXBASE ); } /* DON'T MODIFY */ int BFP_CALLMODEL bfp_rowoffset(lprec *lp) { if(lp->obj_in_basis) return( 1 ); else return( 0 ); } /* DON'T MODIFY */ int BFP_CALLMODEL bfp_pivotmax(lprec *lp) { if(lp->max_pivots > 0) return( lp->max_pivots ); else return( DEF_MAXPIVOT ); } /* DON'T MODIFY */ REAL * BFP_CALLMODEL bfp_pivotvector(lprec *lp) { return( lp->invB->pcol ); } /* DON'T MODIFY */ REAL BFP_CALLMODEL bfp_efficiency(lprec *lp) { REAL hold; hold = lp->bfp_nonzeros(lp, AUTOMATIC); if(hold == 0) hold = 1 + lp->rows; hold = lp->bfp_nonzeros(lp, TRUE)/hold; return(hold); } /* DON'T MODIFY */ int BFP_CALLMODEL bfp_pivotcount(lprec *lp) { return(lp->invB->num_pivots); } /* DON'T MODIFY */ int BFP_CALLMODEL bfp_refactcount(lprec *lp, int kind) { if(kind == BFP_STAT_REFACT_TOTAL) return(lp->invB->num_refact); else if(kind == BFP_STAT_REFACT_TIMED) return(lp->invB->num_timed_refact); else if(kind == BFP_STAT_REFACT_DENSE) return(lp->invB->num_dense_refact); else return( BFP_STAT_ERROR ); } /* DON'T MODIFY */ MYBOOL BFP_CALLMODEL bfp_mustrefactorize(lprec *lp) { MYBOOL test = lp->is_action(lp->spx_action, ACTION_REINVERT | ACTION_TIMEDREINVERT); if(!test) { REAL f; INVrec *lu = lp->invB; if(lu->num_pivots > 0) f = (timeNow()-lu->time_refactstart) / (REAL) lu->num_pivots; else f = 0; /* Always refactorize if we are above the set pivot limit */ if(lu->force_refact || (lu->num_pivots >= lp->bfp_pivotmax(lp))) lp->set_action(&lp->spx_action, ACTION_REINVERT); /* Check if we should do an optimal time-based refactorization */ else if(lu->timed_refact && (lu->num_pivots > 1) && (f > MIN_TIMEPIVOT) && (f > lu->time_refactnext)) { /* If we have excessive time usage in automatic mode then treat as untimed case and update optimal time metric, ... */ if((lu->timed_refact == AUTOMATIC) && (lu->num_pivots < 0.4*lp->bfp_pivotmax(lp))) lu->time_refactnext = f; /* ... otherwise set flag for the optimal time-based refactorization */ else lp->set_action(&lp->spx_action, ACTION_TIMEDREINVERT); } /* Otherwise simply update the optimal time metric */ else lu->time_refactnext = f; #if 0 if(lu->num_pivots % 10 == 0) lp->report(lp, NORMAL, "bfp pivot %d - start %f - timestat %f", lu->num_pivots, lu->time_refactstart, f); #endif } test = lp->is_action(lp->spx_action, ACTION_REINVERT | ACTION_TIMEDREINVERT); return(test); } /* DON'T MODIFY */ MYBOOL BFP_CALLMODEL bfp_isSetI(lprec *lp) { return( (MYBOOL) lp->invB->set_Bidentity ); } /* DON'T MODIFY */ int *bfp_createMDO(lprec *lp, MYBOOL *usedpos, int count, MYBOOL doMDO) { int *mdo, i, j, kk; mdo = (int *) malloc((count + 1)*sizeof(*mdo)); /* allocINT(lp, &mdo, count + 1, FALSE); */ /* Fill the mdo[] array with remaining full-pivot basic user variables */ kk = 0; for(j = 1; j <= lp->columns; j++) { i = lp->rows + j; if(usedpos[i] == TRUE) { kk++; mdo[kk] = i; } } mdo[0] = kk; if(kk == 0) goto Process; /* Calculate the approximate minimum degree column ordering */ if(doMDO) { i = lp->getMDO(lp, usedpos, mdo, NULL, FALSE); if(i != 0) { lp->report(lp, CRITICAL, "bfp_createMDO: Internal error %d in minimum degree ordering routine", i); FREE(mdo); } } Process: return( mdo ); } void BFP_CALLMODEL bfp_updaterefactstats(lprec *lp) { INVrec *lu = lp->invB; /* Signal that we are refactorizing */ lu->is_dirty = AUTOMATIC; /* Set time of start of current refactorization cycle */ lu->time_refactstart = timeNow(); lu->time_refactnext = 0; lu->user_colcount = 0; /* Do the numbers */ if(lu->force_refact) lu->num_dense_refact++; else if(lu->timed_refact && lp->is_action(lp->spx_action, ACTION_TIMEDREINVERT)) lu->num_timed_refact++; lu->num_refact++; } int BFP_CALLMODEL bfp_rowextra(lprec *lp) { if(lp->is_obj_in_basis(lp)) return( 1 ); else return( 0 ); } MSVMpack1.2/lp_solve_5.5/bfp/lp_BFP2.c0000664000175000017500000001042511141443437016241 0ustar lauerlauer /* Routines located in lp_BFP2.cpp; optional shared for canned implementations */ /* Cfr. lp_BFP.h for definitions */ /* ---------------------------------------------------------------------------------- */ /* DON'T MODIFY */ MYBOOL BFP_CALLMODEL bfp_init(lprec *lp, int size, int delta, char *options) { INVrec *lu; lp->invB = (INVrec *) calloc(1, sizeof(*(lp->invB))); lu = lp->invB; if((lu == NULL) || !lp->bfp_resize(lp, size) || !lp->bfp_restart(lp)) return( FALSE ); /* Store any passed options */ if(options != NULL) { size_t len = strlen(options); lu->opts = (char *) malloc(len + 1); strcpy(lu->opts, options); } /* Prepare for factorization and undo values reset by bfp_preparefactorization */ lp->bfp_preparefactorization(lp); lu->num_refact = 0; return( TRUE ); } /* DON'T MODIFY */ MYBOOL BFP_CALLMODEL bfp_restart(lprec *lp) { INVrec *lu; lu = lp->invB; if(lu == NULL) return( FALSE ); lu->status = BFP_STATUS_SUCCESS; lu->max_Bsize = 0; /* The largest NZ-count of the B matrix */ lu->max_colcount = 0; /* The maximum number of user columns in B */ lu->max_LUsize = 0; /* The largest NZ-count of LU-files generated */ lu->num_refact = 0; /* The number of times the basis has been factored */ lu->num_timed_refact = 0; lu->num_dense_refact = 0; lu->num_pivots = 0; /* The number of pivots since last factorization */ lu->pcol = NULL; lu->set_Bidentity = FALSE; return( TRUE ); } /* DON'T MODIFY */ MYBOOL BFP_CALLMODEL bfp_implicitslack(lprec *lp) { return( FALSE ); } /* DON'T MODIFY */ int BFP_CALLMODEL bfp_colcount(lprec *lp) { return(lp->invB->user_colcount); } /* DON'T MODIFY */ MYBOOL BFP_CALLMODEL bfp_canresetbasis(lprec *lp) { return( FALSE ); } /* DON'T MODIFY */ MYBOOL BFP_CALLMODEL bfp_pivotalloc(lprec *lp, int newsize) { /* Does nothing in the default implementation */ return( TRUE ); } /* DON'T MODIFY */ void BFP_CALLMODEL bfp_finishfactorization(lprec *lp) { INVrec *lu; lu = lp->invB; SETMAX(lu->max_colcount, lp->bfp_colcount(lp)); SETMAX(lu->max_LUsize, lp->bfp_nonzeros(lp, FALSE)); /* Signal that we done factorizing/reinverting */ lu->is_dirty = FALSE; lp->clear_action(&lp->spx_action, ACTION_REINVERT | ACTION_TIMEDREINVERT); lu->force_refact = FALSE; /* Store information about the current inverse */ lu->num_pivots = 0; } /* DON'T MODIFY */ LREAL BFP_CALLMODEL bfp_prepareupdate(lprec *lp, int row_nr, int col_nr, REAL *pcol) /* Was condensecol() in versions of lp_solve before 4.0.1.8 - KE */ { LREAL pivValue; INVrec *lu; lu = lp->invB; /* Store the incoming pivot value for RHS update purposes */ lu->col_enter = col_nr; /* The index of the new data column */ lu->col_pos = row_nr; /* The basis column to be replaced */ lu->col_leave = lp->var_basic[row_nr]; if(pcol == NULL) pivValue = 0; else pivValue = pcol[row_nr]; lu->theta_enter = pivValue; /* Save reference to the elimination vector */ lu->pcol = pcol; /* Set completion status; but hold if we are reinverting */ if(lu->is_dirty != AUTOMATIC) lu->is_dirty = TRUE; return( pivValue ); } /* DON'T MODIFY */ REAL BFP_CALLMODEL bfp_pivotRHS(lprec *lp, LREAL theta, REAL *pcol) /* This function is used to adjust the RHS in bound swap operations as well as handling the updating of the RHS for normal basis changes. Was rhsmincol(), ie. "rhs minus column" in versions of lp_solve before 4.0.1.8 - KE */ { INVrec *lu; lu = lp->invB; if(pcol == NULL) pcol = lu->pcol; if(theta != 0) { register int i, n = lp->rows; register LREAL roundzero = lp->epsvalue; register LREAL *rhs = lp->rhs, rhsmax = 0; for(i = 0; i <= n; i++, rhs++, pcol++) { (*rhs) -= theta * (*pcol); my_roundzero(*rhs, roundzero); SETMAX(rhsmax, fabs(*rhs)); } lp->rhsmax = rhsmax; } if(pcol == lu->pcol) return( lu->theta_enter ); else return( 0.0 ); } /* DON'T MODIFY */ void BFP_CALLMODEL bfp_btran_double(lprec *lp, REAL *prow, int *pnzidx, REAL *drow, int *dnzidx) { if(prow != NULL) lp->bfp_btran_normal(lp, prow, pnzidx); if(drow != NULL) lp->bfp_btran_normal(lp, drow, dnzidx); } MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/0000775000175000017500000000000012104711130016420 5ustar lauerlauerMSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/lp_LUSOL.c0000664000175000017500000005637711141443432020206 0ustar lauerlauer /* Modularized simplex basis factorization module - w/interface for lp_solve v5.0+ ---------------------------------------------------------------------------------- Author: Kjell Eikland Contact: kjell.eikland@broadpark.no License terms: LGPL. Requires: lusol.h, lp_lib.h, myblas.h Release notes: v2.0.0 1 March 2004 First implementation of the LUSOL v2.0 C translation. v2.0.1 1 April 2004 Added singularity recovery and fast/reuse update logic. v2.0.2 23 May 2004 Moved mustrefact() function into the BFP structure. v2.0.3 5 September 2004 Reworked pivot threshold tightening logic and default values. v2.1.0 18 June 2005 Made changes to allow for "pure" factorization; i.e. without the objective function included. ---------------------------------------------------------------------------------- */ /* Generic include libraries */ #include #include #include "lp_lib.h" /* Include libraries for this factorization system */ #include "myblas.h" #include "commonlib.h" #include "lp_LUSOL.h" #include "lusol.h" #ifdef FORTIFY # include "lp_fortify.h" #endif /* Include routines common to factorization engine implementations */ #include "lp_BFP1.c" #include "lp_BFP2.c" /* MUST MODIFY */ char * BFP_CALLMODEL bfp_name(void) { return( "LUSOL v2.2.1.0" ); } /* MUST MODIFY */ MYBOOL BFP_CALLMODEL bfp_resize(lprec *lp, int newsize) { INVrec *lu; lu = lp->invB; /* Increment dimensionality since we put the objective row at the top */ newsize = newsize + bfp_rowoffset(lp); lu->dimalloc = newsize; /* Allocate index tracker arrays, LU matrices and various work vectors */ if(!allocREAL(lp, &(lu->value), newsize+MATINDEXBASE, AUTOMATIC)) return( FALSE ); /* Data specific to the factorization engine */ if(lu->LUSOL != NULL) { if(newsize > 0) LUSOL_sizeto(lu->LUSOL, newsize, newsize, 0); else { LUSOL_free(lu->LUSOL); lu->LUSOL = NULL; } } else if(newsize > 0) { int asize; REAL bsize; lu->LUSOL = LUSOL_create(NULL, 0, LUSOL_PIVMOD_TPP, bfp_pivotmax(lp)*0); #if 1 lu->LUSOL->luparm[LUSOL_IP_ACCELERATION] = LUSOL_AUTOORDER; lu->LUSOL->parmlu[LUSOL_RP_SMARTRATIO] = 0.50; #endif #if 0 lu->timed_refact = DEF_TIMEDREFACT; #else lu->timed_refact = FALSE; #endif /* The following adjustments seem necessary to make the really tough NETLIB models perform reliably and still performant (e.g. cycle.mps) */ #if 0 lu->LUSOL->parmlu[LUSOL_RP_SMALLDIAG_U] = lu->LUSOL->parmlu[LUSOL_RP_EPSDIAG_U] = lp->epsprimal; #endif #if 0 lu->LUSOL->parmlu[LUSOL_RP_ZEROTOLERANCE] = lp->epsvalue; #endif #if 1 LUSOL_setpivotmodel(lu->LUSOL, LUSOL_PIVMOD_NOCHANGE, LUSOL_PIVTOL_SLIM); #else LUSOL_setpivotmodel(lu->LUSOL, LUSOL_PIVMOD_NOCHANGE, LUSOL_PIVTOL_TIGHT); #endif #ifdef LUSOL_UseBLAS /* if(fileSearchPath("PATH", "myBLAS.DLL", NULL) && load_BLAS("myBLAS")) */ if(is_nativeBLAS() && load_BLAS(libnameBLAS)) lp->report(lp, NORMAL, "Optimized BLAS was successfully loaded for bfp_LUSOL.\n"); #endif /* Try to minimize memory allocation if we have a large number of unit columns */ bsize = (REAL) lp->get_nonzeros(lp); if(newsize > lp->columns) bsize += newsize; else bsize = bsize/lp->columns*newsize; /* Add a "reasonable" delta to allow for B and associated factorizations that are denser than average; this makes reallocations less frequent. Values between 1.2 and 1.5 appear to be reasonable. */ asize = (int) (bsize*MAX_DELTAFILLIN*1.3333); if(!LUSOL_sizeto(lu->LUSOL, newsize, newsize, asize)) return( FALSE ); } lu->dimcount = newsize; return( TRUE ); } /* MUST MODIFY */ void BFP_CALLMODEL bfp_free(lprec *lp) { INVrec *lu; lu = lp->invB; if(lu == NULL) return; /* General arrays */ FREE(lu->opts); FREE(lu->value); /* Data specific to the factorization engine */ LUSOL_free(lu->LUSOL); FREE(lu); lp->invB = NULL; } /* MUST MODIFY */ int BFP_CALLMODEL bfp_nonzeros(lprec *lp, MYBOOL maximum) { INVrec *lu; lu = lp->invB; if(maximum == TRUE) return(lu->max_LUsize); else if(maximum == AUTOMATIC) return(lu->max_Bsize); else return(lu->LUSOL->luparm[LUSOL_IP_NONZEROS_L0]+lu->LUSOL->luparm[LUSOL_IP_NONZEROS_U0]); /* return(lu->LUSOL->luparm[LUSOL_IP_NONZEROS_ROW]); */ } /* MUST MODIFY (or ignore) */ int BFP_CALLMODEL bfp_memallocated(lprec *lp) { int mem; LUSOLrec *LUSOL = lp->invB->LUSOL; mem = sizeof(REAL) * (LUSOL->lena+LUSOL->maxm+LUSOL_RP_LASTITEM); mem += sizeof(int) * (2*LUSOL->lena+5*LUSOL->maxm+5*LUSOL->maxn+LUSOL_IP_LASTITEM); if(LUSOL->luparm[LUSOL_IP_PIVOTTYPE] == LUSOL_PIVMOD_TCP) mem += sizeof(REAL) * LUSOL->maxn + 2*sizeof(REAL)*LUSOL->maxn; else if(LUSOL->luparm[LUSOL_IP_PIVOTTYPE] == LUSOL_PIVMOD_TRP) mem += sizeof(REAL) * LUSOL->maxn; if(!LUSOL->luparm[LUSOL_IP_KEEPLU]) mem += sizeof(REAL) * LUSOL->maxn; return( mem ); } /* MUST MODIFY */ int BFP_CALLMODEL bfp_preparefactorization(lprec *lp) { INVrec *lu = lp->invB; /* Finish any outstanding business */ if(lu->is_dirty == AUTOMATIC) lp->bfp_finishfactorization(lp); /* Clear or resize the existing LU matrices - specific for the factorization engine */ LUSOL_clear(lu->LUSOL, TRUE); if(lu->dimcount != lp->rows + bfp_rowoffset(lp)) lp->bfp_resize(lp, lp->rows); /* Reset additional indicators */ lp->bfp_updaterefactstats(lp); lu->col_pos = 0; return(0); } /* LOCAL HELPER ROUTINE - Replace a basis column with corresponding slack */ int bfp_LUSOLsetcolumn(lprec *lp, int posnr, int colnr) { int nz, inform; nz = lp->get_lpcolumn(lp, colnr, lp->invB->LUSOL->w + bfp_rowoffset(lp), NULL, NULL); inform = LUSOL_replaceColumn(lp->invB->LUSOL, posnr, lp->invB->LUSOL->w); return( inform ); } /* LOCAL HELPER ROUTINE - force the basis to be the identity matrix */ int bfp_LUSOLidentity(lprec *lp, int *rownum) { int i, nz; INVrec *invB = lp->invB; /* Reset the factorization engine */ LUSOL_clear(invB->LUSOL, TRUE); /* Add the basis columns */ lp->invB->set_Bidentity = TRUE; for(i = 1; i <= invB->dimcount; i++) { nz = lp->get_basiscolumn(lp, i, rownum, invB->value); LUSOL_loadColumn(invB->LUSOL, rownum, i, invB->value, nz, 0); } lp->invB->set_Bidentity = FALSE; /* Factorize */ i = LUSOL_factorize(invB->LUSOL); return( i ); } /* LOCAL HELPER ROUTINE */ int bfp_LUSOLfactorize(lprec *lp, MYBOOL *usedpos, int *rownum, int *singular) { int i, j, nz, deltarows = bfp_rowoffset(lp); INVrec *invB = lp->invB; /* Handle normal, presumed nonsingular case */ if(singular == NULL) { /* Optionally do a symbolic minimum degree ordering; not that slack variables should not be processed */ /*#define UsePreprocessMDO*/ #ifdef UsePreprocessMDO int *mdo; mdo = lp->bfp_createMDO(lp, usedpos, lp->rows, TRUE); if(mdo != NULL) { for(i = 1; i <= lp->rows; i++) lp->set_basisvar(lp, i, mdo[i]); FREE(mdo); } #endif /* Reset the factorization engine */ LUSOL_clear(invB->LUSOL, TRUE); /* Add the basis columns in the original order */ for(i = 1; i <= invB->dimcount; i++) { nz = lp->get_basiscolumn(lp, i, rownum, invB->value); LUSOL_loadColumn(invB->LUSOL, rownum, i, invB->value, nz, 0); if((i > deltarows) && (lp->var_basic[i-deltarows] > lp->rows)) lp->invB->user_colcount++; } /* Factorize */ i = LUSOL_factorize(invB->LUSOL); } /* Handle case where a column may be singular */ else { LLrec *map; /* Reset the factorization engine */ i = bfp_LUSOLidentity(lp, rownum); /* Build map of available columns */ nz = createLink(lp->rows, &map, NULL); for(i = 1; i <= lp->rows; i++) { if(lp->var_basic[i] <= lp->rows) removeLink(map, i); } /* Rebuild the basis, column by column, while skipping slack columns */ j = firstActiveLink(map); for(i = 1; i <= lp->rows; i++) { if(lp->var_basic[i] <= lp->rows) continue; nz = bfp_LUSOLsetcolumn(lp, j+deltarows, lp->var_basic[i]); if(nz == LUSOL_INFORM_LUSUCCESS) lp->invB->user_colcount++; else { nz = bfp_LUSOLsetcolumn(lp, j+deltarows, i); lp->set_basisvar(lp, i, i); } j = nextActiveLink(map, j); } /* Sort the basis list */ MEMCOPY(rownum, lp->var_basic, lp->rows+1); sortByINT(lp->var_basic, rownum, lp->rows, 1, TRUE); } return( i ); } /* LOCAL HELPER ROUTINE */ void bfp_LUSOLtighten(lprec *lp) { int infolevel = DETAILED; switch(LUSOL_tightenpivot(lp->invB->LUSOL)) { case FALSE: lp->report(lp, infolevel, "bfp_factorize: Very hard numerics, but cannot tighten LUSOL thresholds further.\n"); break; case TRUE: lp->report(lp, infolevel, "bfp_factorize: Frequent refact pivot count %d at iter %.0f; tightened thresholds.\n", lp->invB->num_pivots, (REAL) lp->get_total_iter(lp)); break; default: lp->report(lp, infolevel, "bfp_factorize: LUSOL switched to %s pivoting model to enhance stability.\n", LUSOL_pivotLabel(lp->invB->LUSOL)); } } #define is_fixedvar is_fixedvar_ /* resolves a compiler warning/error conflict with lp_lib.h */ static MYBOOL is_fixedvar(lprec *lp, int variable) { if((lp->bb_bounds != NULL && lp->bb_bounds->UBzerobased) || (variable <= lp->rows)) return( (MYBOOL) (lp->upbo[variable] < lp->epsprimal) ); else return( (MYBOOL) (lp->upbo[variable]-lp->lowbo[variable] < lp->epsprimal) ); } /* is_fixedvar */ /* MUST MODIFY */ int BFP_CALLMODEL bfp_factorize(lprec *lp, int uservars, int Bsize, MYBOOL *usedpos, MYBOOL final) { int kcol, inform, *rownum = NULL, singularities = 0, dimsize = lp->invB->dimcount; LUSOLrec *LUSOL = lp->invB->LUSOL; /* Set dimensions and create work array */ SETMAX(lp->invB->max_Bsize, Bsize+(1+lp->rows-uservars)); kcol = lp->invB->dimcount; LUSOL->m = kcol; LUSOL->n = kcol; allocINT(lp, &rownum, kcol+1, FALSE); /* Check if the refactorization frequency is low; tighten pivot thresholds if appropriate */ inform = lp->bfp_pivotcount(lp); if(!final && /* No solution update-based refactorization */ !lp->invB->force_refact && /* No sparsity-based refactorization */ !lp->is_action(lp->spx_action, ACTION_TIMEDREINVERT) && /* No optimal time-based refactorization */ (inform > 5) && (inform < 0.25*lp->bfp_pivotmax(lp))) bfp_LUSOLtighten(lp); /* Reload B and factorize */ inform = bfp_LUSOLfactorize(lp, usedpos, rownum, NULL); /* Do some checks */ #ifdef Paranoia if(uservars != lp->invB->user_colcount) { lp->report(lp, SEVERE, "bfp_factorize: User variable count reconciliation failed\n"); return( singularities ); } #endif /* Check result and do further remedial action if necessary */ if(inform != LUSOL_INFORM_LUSUCCESS) { int singularcols, replacedcols = 0; REAL hold; /* Make sure we do not tighten factorization pivot criteria too often, and simply accept the substitution of slack columns into the basis */ if((lp->invB->num_singular+1) % TIGHTENAFTER == 0) bfp_LUSOLtighten(lp); /* Try to restore a non-singular basis by substituting singular columns with slacks */ while((inform == LUSOL_INFORM_LUSINGULAR) && (replacedcols < dimsize)) { int iLeave, jLeave, iEnter; MYBOOL isfixed; singularities++; singularcols = LUSOL->luparm[LUSOL_IP_SINGULARITIES]; hold = (REAL) lp->get_total_iter(lp); lp->report(lp, NORMAL, "bfp_factorize: Resolving %d singularit%s at refact %d, iter %.0f\n", singularcols, my_plural_y(singularcols), lp->invB->num_refact, hold); /* Find the failing / singular column(s) and make slack substitutions */ for(kcol = 1; kcol <= singularcols; kcol++) { /* Determine leaving and entering columns. */ iLeave = LUSOL_getSingularity(LUSOL, kcol); /* This is the singular column as natural index */ iEnter = iLeave; /* This is the target replacement slack */ #if 1 iEnter = LUSOL->iqinv[iEnter]; iEnter = LUSOL->ip[iEnter]; #endif iLeave-= bfp_rowextra(lp); /* This is the original B column/basis index */ jLeave = lp->var_basic[iLeave]; /* This is the IA column index in lp_solve */ /* Express the slack index in original lp_solve [1..rows] reference and check validity */ /* if(B4 != NULL) iEnter = B4->B4_row[iEnter]; v6 FUNCTIONALITY */ iEnter -= bfp_rowextra(lp); if(lp->is_basic[iEnter]) { lp->report(lp, DETAILED, "bfp_factorize: Replacement slack %d is already basic!\n", iEnter); /* See if we can find a good alternative slack variable to enter */ iEnter = 0; for(inform = 1; inform <= lp->rows; inform++) if(!lp->is_basic[inform]) { if((iEnter == 0) || (lp->upbo[inform] > lp->upbo[iEnter])) { iEnter = inform; if(my_infinite(lp, lp->upbo[iEnter])) break; } } if(iEnter == 0) { lp->report(lp, SEVERE, "bfp_factorize: Could not find replacement slack variable!\n"); break; } } /* We should update bound states for both the entering and leaving variables. Note that this may cause (primal or dual) infeasibility, but I assume that lp_solve traps this and takes necessary corrective action. */ isfixed = is_fixedvar(lp, iEnter); if(isfixed) lp->fixedvars++; hold = lp->upbo[jLeave]; lp->is_lower[jLeave] = isfixed || (fabs(hold)>=lp->infinite) || (lp->rhs[iLeave] < hold); lp->is_lower[iEnter] = TRUE; /* Do the basis replacement */ lp->set_basisvar(lp, iLeave, iEnter); } /* Refactorize with slack substitutions */ inform = bfp_LUSOLfactorize(lp, NULL, rownum, NULL); replacedcols += singularcols; } /* Check if we had a fundamental problem */ if(singularities >= dimsize) { lp->report(lp, IMPORTANT, "bfp_factorize: LUSOL was unable to recover from a singular basis\n"); lp->spx_status = NUMFAILURE; } } /* Clean up before returning */ FREE(rownum); /* Update statistics */ /* SETMAX(lp->invB->max_Bsize, (*Bsize)); */ lp->invB->num_singular += singularities; /* The total number of singular updates */ return( singularities ); } /* MUST MODIFY */ MYBOOL BFP_CALLMODEL bfp_finishupdate(lprec *lp, MYBOOL changesign) /* Was addetacol() in versions of lp_solve before 4.0.1.8 - KE */ { int i, k, kcol, deltarows = bfp_rowoffset(lp); REAL DIAG, VNORM; INVrec *lu = lp->invB; LUSOLrec *LUSOL = lu->LUSOL; if(!lu->is_dirty) return( FALSE ); if(lu->is_dirty != AUTOMATIC) lu->is_dirty = FALSE; /* Perform the update */ k = lu->col_pos+deltarows; lu->num_pivots++; if(lu->col_leave > lu->dimcount-deltarows) lu->user_colcount--; if(lu->col_enter > lu->dimcount-deltarows) lu->user_colcount++; kcol = lu->col_pos; lu->col_pos = 0; /* Do standard update */ #ifdef LUSOLSafeFastUpdate /* NB! Defined in lusol.h */ if(TRUE || !changesign) { if(changesign) { REAL *temp = LUSOL->vLU6L; for(i = 1, temp++; i <= lp->rows+deltarows; i++, temp++) if(*temp != 0) *temp = -(*temp); } /* Execute the update using data prepared earlier */ LU8RPC(LUSOL, LUSOL_UPDATE_OLDNONEMPTY, LUSOL_UPDATE_USEPREPARED, k, NULL, NULL, &i, &DIAG, &VNORM); } else #endif { /* Retrieve the data for the entering column (base 0) */ i = lp->get_lpcolumn(lp, lu->col_enter, lu->value+deltarows, NULL, NULL); lu->value[0] = 0; /* Execute the update */ LU8RPC(LUSOL, LUSOL_UPDATE_OLDNONEMPTY, LUSOL_UPDATE_NEWNONEMPTY, k, lu->value, NULL, &i, &DIAG, &VNORM); } if(i == LUSOL_INFORM_LUSUCCESS) { /* Check if we should refactorize based on accumulation of fill-in */ DIAG = LUSOL->luparm[LUSOL_IP_NONZEROS_L]+LUSOL->luparm[LUSOL_IP_NONZEROS_U]; VNORM = LUSOL->luparm[LUSOL_IP_NONZEROS_L0]+LUSOL->luparm[LUSOL_IP_NONZEROS_U0]; #if 0 /* This is Michael Saunder's fixed parameter */ VNORM *= MAX_DELTAFILLIN; #else /* This is Kjell Eikland's dynamic error accumulation measure */ VNORM *= pow(MAX_DELTAFILLIN, pow((0.5*LUSOL->nelem/VNORM), 0.25)); #endif lu->force_refact = (MYBOOL) ((DIAG > VNORM) && (lu->num_pivots > 20)); #if 0 /* Additional KE logic to reduce maximum pivot count based on the density of B */ if(!lu->force_refact) { VNORM = lp->rows+1; VNORM = 1.0 - pow((REAL) LUSOL->nelem/VNORM/VNORM, 0.2); lu->force_refact = (MYBOOL) (lu->num_pivots > VNORM*lp->bfp_pivotmax(lp)); } #endif } /* Handle errors */ else { /* int infolevel = NORMAL; */ int infolevel = DETAILED; lp->report(lp, infolevel, "bfp_finishupdate: Failed at iter %.0f, pivot %d;\n%s\n", (REAL) (lp->total_iter+lp->current_iter), lu->num_pivots, LUSOL_informstr(LUSOL, i)); if(i == LUSOL_INFORM_ANEEDMEM) { /* To compress used memory and realloc, if necessary */ lp->invert(lp, INITSOL_USEZERO, FALSE); if(i != LUSOL_INFORM_LUSUCCESS) lp->report(lp, NORMAL, "bfp_finishupdate: Insufficient memory at iter %.0f;\n%s\n", (REAL) (lp->total_iter+lp->current_iter), LUSOL_informstr(LUSOL, i)); } else if(i == LUSOL_INFORM_RANKLOSS) { /* To fix rank loss and clear cumulative errors */ #if 0 /* This is test code to do pivot in slack BEFORE refactorization (pessimistic approach); assumes that LUSOL returns correct information about the source of the singularity */ kcol = LUSOL->luparm[LUSOL_IP_SINGULARINDEX]; #ifdef MAPSINGULARCOLUMN kcol = LUSOL_findColumnPosition(LUSOL, kcol); #endif lp->set_basisvar(lp, kcol-deltarows, kcol-deltarows); #endif lp->invert(lp, INITSOL_USEZERO, FALSE); i = LUSOL->luparm[LUSOL_IP_INFORM]; if(i != LUSOL_INFORM_LUSUCCESS) lp->report(lp, NORMAL, "bfp_finishupdate: Recovery attempt unsuccessful at iter %.0f;\n%s\n", (REAL) (lp->total_iter+lp->current_iter), LUSOL_informstr(LUSOL, i)); else lp->report(lp, infolevel, "bfp_finishupdate: Correction or recovery was successful.\n"); } } return( (MYBOOL) (i == LUSOL_INFORM_LUSUCCESS) ); } /* bfp_finishupdate */ /* MUST MODIFY */ void BFP_CALLMODEL bfp_ftran_normal(lprec *lp, REAL *pcol, int *nzidx) { int i; INVrec *lu; lu = lp->invB; /* Do the LUSOL ftran */ i = LUSOL_ftran(lu->LUSOL, pcol-bfp_rowoffset(lp), nzidx, FALSE); if(i != LUSOL_INFORM_LUSUCCESS) { lu->status = BFP_STATUS_ERROR; lp->report(lp, NORMAL, "bfp_ftran_normal: Failed at iter %.0f, pivot %d;\n%s\n", (REAL) (lp->total_iter+lp->current_iter), lu->num_pivots, LUSOL_informstr(lu->LUSOL, i)); } } /* MAY MODIFY */ void BFP_CALLMODEL bfp_ftran_prepare(lprec *lp, REAL *pcol, int *nzidx) { int i; INVrec *lu; lu = lp->invB; /* Do the LUSOL ftran */ i = LUSOL_ftran(lu->LUSOL, pcol-bfp_rowoffset(lp), nzidx, TRUE); if(i != LUSOL_INFORM_LUSUCCESS) { lu->status = BFP_STATUS_ERROR; lp->report(lp, NORMAL, "bfp_ftran_prepare: Failed at iter %.0f, pivot %d;\n%s\n", (REAL) (lp->total_iter+lp->current_iter), lu->num_pivots, LUSOL_informstr(lu->LUSOL, i)); } } /* MUST MODIFY */ void BFP_CALLMODEL bfp_btran_normal(lprec *lp, REAL *prow, int *nzidx) { int i; INVrec *lu; lu = lp->invB; /* Do the LUSOL btran */ i = LUSOL_btran(lu->LUSOL, prow-bfp_rowoffset(lp), nzidx); if(i != LUSOL_INFORM_LUSUCCESS) { lu->status = BFP_STATUS_ERROR; lp->report(lp, NORMAL, "bfp_btran_normal: Failed at iter %.0f, pivot %d;\n%s\n", (REAL) (lp->total_iter+lp->current_iter), lu->num_pivots, LUSOL_informstr(lu->LUSOL, i)); } /* Check performance data */ #if 0 if(lu->num_pivots == 1) { if(lu->LUSOL->luparm[LUSOL_IP_ACCELERATION] > 0) lp->report(lp, NORMAL, "RowL0 R:%10.7f C:%10.7f NZ:%10.7f\n", (REAL) lu->LUSOL->luparm[LUSOL_IP_ROWCOUNT_L0] / lu->LUSOL->m, (REAL) lu->LUSOL->luparm[LUSOL_IP_COLCOUNT_L0] / lu->LUSOL->m, (REAL) lu->LUSOL->luparm[LUSOL_IP_NONZEROS_L0] / pow((REAL) lu->LUSOL->m, 2)); else lp->report(lp, NORMAL, "ColL0 C:%10.7f NZ:%10.7f\n", (REAL) lu->LUSOL->luparm[LUSOL_IP_COLCOUNT_L0] / lu->LUSOL->m, (REAL) lu->LUSOL->luparm[LUSOL_IP_NONZEROS_L0] / pow((REAL) lu->LUSOL->m, 2)); } #endif } /* MUST MODIFY - Routine to find maximum rank of equality constraints */ int BFP_CALLMODEL bfp_findredundant(lprec *lp, int items, getcolumnex_func cb, int *maprow, int *mapcol) { int i, j, nz = 0, m = 0, n = 0, *nzrows = NULL; REAL *nzvalues = NULL, *arraymax = NULL; LUSOLrec *LUSOL; /* Are we capable of finding redundancy with this BFP? */ if((maprow == NULL) && (mapcol == NULL)) return( n ); /* If so, initialize memory structures */ if(!allocINT(lp, &nzrows, items, FALSE) || !allocREAL(lp, &nzvalues, items, FALSE)) return( n ); /* Compute the number of non-empty columns */ m = 0; for(j = 1; j <= mapcol[0]; j++) { n = cb(lp, mapcol[j], NULL, NULL, maprow); if(n > 0) { m++; mapcol[m] = mapcol[j]; nz += n; } } mapcol[0] = m; /* Instantiate a LUSOL object */ LUSOL = LUSOL_create(NULL, 0, LUSOL_PIVMOD_TRP, 0); if((LUSOL == NULL) || !LUSOL_sizeto(LUSOL, items, m, nz*LUSOL_MULT_nz_a)) goto Finish; /* Modify relevant LUSOL parameters */ LUSOL->m = items; LUSOL->n = m; #if 0 LUSOL->luparm[LUSOL_IP_KEEPLU] = FALSE; LUSOL->luparm[LUSOL_IP_PIVOTTYPE] = LUSOL_PIVMOD_TRP; LUSOL->parmlu[LUSOL_RP_FACTORMAX_Lij] = 2.0; #endif /* Load the columns into LUSOL */ for(j = 1; j <= m; j++) { n = cb(lp, mapcol[j], nzvalues, nzrows, maprow); i = LUSOL_loadColumn(LUSOL, nzrows, j, nzvalues, n, -1); if(n != i) { lp->report(lp, IMPORTANT, "bfp_findredundant: Error %d while loading column %d with %d nz\n", i, j, n); n = 0; goto Finish; } } /* Scale rows to prevent numerical problems */ if((lp->scalemode != SCALE_NONE) && allocREAL(lp, &arraymax, items+1, TRUE)) { for(i = 1; i <= nz; i++) { SETMAX(arraymax[LUSOL->indc[i]], fabs(LUSOL->a[i])); } for(i = 1; i <= nz; i++) LUSOL->a[i] /= arraymax[LUSOL->indc[i]]; FREE(arraymax); } /* Factorize for maximum rank */ n = 0; i = LUSOL_factorize(LUSOL); /* lp->report(lp, NORMAL, "bfp_findredundant: r=%d c=%d - %s\n", items, m, LUSOL_informstr(LUSOL, i));*/ if((i == LUSOL_INFORM_LUSUCCESS) || (i != LUSOL_INFORM_LUSINGULAR)) goto Finish; /* We have a singular matrix, obtain the indeces of the singular rows */ for(i = LUSOL->luparm[LUSOL_IP_RANK_U] + 1; i <= items; i++) { n++; maprow[n] = LUSOL->ip[i]; } maprow[0] = n; /* Clean up */ Finish: LUSOL_free(LUSOL); FREE(nzrows); FREE(nzvalues); return( n ); } MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/bfp_LUSOL.c0000664000175000017500000000066711141443432020331 0ustar lauerlauer #include "bfp_LUSOL.h" #include "lp_lib.h" #include "lp_LUSOL.h" BOOL APIENTRY DllMain( HANDLE hModule, DWORD ul_reason_for_call, LPVOID lpReserved ) { switch (ul_reason_for_call) { case DLL_PROCESS_ATTACH: case DLL_THREAD_ATTACH: case DLL_THREAD_DETACH: case DLL_PROCESS_DETACH: break; } return TRUE; } #if defined FORTIFY int EndOfPgr(int i) { exit(i); } #endif MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/bfp_LUSOL.h0000664000175000017500000000065111141443432020327 0ustar lauerlauer// stdafx.h : include file for standard system include files, // or project specific include files that are used frequently, but // are changed infrequently // //#pragma once //RoleIsExternalInvEngine;INVERSE_ACTIVE=INVERSE_LUSOL #define WIN32_LEAN_AND_MEAN // Exclude rarely-used stuff from Windows headers // Windows Header Files: #include // TODO: reference additional headers your program requires here MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/lp_LUSOL.h0000664000175000017500000000540211141443432020172 0ustar lauerlauer#ifndef HEADER_lp_LUSOL #define HEADER_lp_LUSOL /* Include libraries for this inverse system */ #include "lp_types.h" #include "lusol.h" /* LUSOL defines */ #ifdef WIN32 # define LUSOL_UseBLAS #endif /*#define MAPSINGULARCOLUMN*/ #define MATINDEXBASE LUSOL_ARRAYOFFSET /* Inversion engine index start for arrays */ #define LU_START_SIZE 10000 /* Start size of LU; realloc'ed if needed */ #define DEF_MAXPIVOT 250 /* Maximum number of pivots before refactorization */ #define MAX_DELTAFILLIN 2.0 /* Do refactorizations based on sparsity considerations */ #define TIGHTENAFTER 10 /* Tighten LU pivot criteria only after this number of singularities */ /* typedef */ struct _INVrec { int status; /* Last operation status code */ int dimcount; /* The actual number of LU rows/columns */ int dimalloc; /* The allocated LU rows/columns size */ int user_colcount; /* The number of user LU columns */ LUSOLrec *LUSOL; int col_enter; /* The full index of the entering column */ int col_leave; /* The full index of the leaving column */ int col_pos; /* The B column to be changed at the next update using data in value[.]*/ REAL *value; REAL *pcol; /* Reference to the elimination vector */ REAL theta_enter; /* Value of the entering column theta */ int max_Bsize; /* The largest B matrix of user variables */ int max_colcount; /* The maximum number of user columns in LU */ int max_LUsize; /* The largest NZ-count of LU-files generated */ int num_refact; /* Number of times the basis was refactored */ int num_timed_refact; int num_dense_refact; double time_refactstart; /* Time since start of last refactorization-pivots cyle */ double time_refactnext; /* Time estimated to next refactorization */ int num_pivots; /* Number of pivots since last refactorization */ int num_singular; /* The total number of singular updates */ char *opts; MYBOOL is_dirty; /* Specifies if a column is incompletely processed */ MYBOOL force_refact; /* Force refactorization at the next opportunity */ MYBOOL timed_refact; /* Set if timer-driven refactorization should be active */ MYBOOL set_Bidentity; /* Force B to be the identity matrix at the next refactorization */ } /* INVrec */; #ifdef __cplusplus /* namespace LUSOL */ extern "C" { #endif /* Put function headers here */ #include "lp_BFP.h" #ifdef __cplusplus } #endif #endif /* HEADER_lp_LUSOL */ MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/0000775000175000017500000000000011141443437017332 5ustar lauerlauerMSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/lusol.c0000664000175000017500000006054111141443433020636 0ustar lauerlauer /* ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ LUSOL routines from the Stanford Optimization Laboratory The parts included are: lusol1 Factor a given matrix A from scratch (lu1fac). lusol2 Heap-management routines for lu1fac. lusol6 Solve with the current LU factors. lusol7 Utilities for all update routines. lusol8 Replace a column (Bartels-Golub update). ------------------------------------------------------------------ 26 Apr 2002: TCP implemented using heap data structure. 01 May 2002: lu1DCP implemented. 07 May 2002: lu1mxc must put 0.0 at top of empty columns. 09 May 2002: lu1mCP implements Markowitz with cols searched in heap order. Often faster (searching 20 or 40 cols) but more dense. 11 Jun 2002: TRP implemented. lu1mRP implements Markowitz with Threshold Rook Pivoting. lu1mxc maintains max col elements (was lu1max.) lu1mxr maintains max row elements. 12 Jun 2002: lu1mCP seems too slow on big problems (e.g. memplus). Disabled it for the moment. (Use lu1mar + TCP.) 14 Dec 2002: TSP implemented. lu1mSP implements Markowitz with TSP. 07 Mar 2003: character*1, character*2 changed to f90 form. Comments changed from * in column to ! in column 1. Comments kept within column 72 to avoid compiler warning. 06 Mar 2004: Translation to C by Kjell Eikland with the addition of data wrappers, parametric constants, various helper routines, and dynamic memory reallocation. 26 May 2004: Added LUSOL_IP_UPDATELIMIT parameter and provided for dynamic memory expansion based on possible forward requirements. 08 Jul 2004: Revised logic in lu6chk based on new code from Michael Saunders. 01 Dec 2005: Add support for CMEX interface (disable by undef MATLAB) Also include various bug fixes (disable by undef YZHANG) Yin Zhang 01 Jan 2006: Added storage of singular indeces, not only the last. ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ */ #include #include #include #include #include #include #include "lusol.h" #include "myblas.h" #ifdef MATLAB #include "mex.h" #endif /* LUSOL Object creation and destruction */ void *clean_realloc(void *oldptr, int width, int newsize, int oldsize) { newsize *= width; oldsize *= width; oldptr = LUSOL_REALLOC(oldptr, newsize); if(newsize > oldsize) /* MEMCLEAR(oldptr+oldsize, newsize-oldsize); */ memset((char *)oldptr+oldsize, '\0', newsize-oldsize); return(oldptr); } MYBOOL LUSOL_realloc_a(LUSOLrec *LUSOL, int newsize) { int oldsize; if(newsize < 0) newsize = LUSOL->lena + MAX(abs(newsize), LUSOL_MINDELTA_a); oldsize = LUSOL->lena; LUSOL->lena = newsize; if(newsize > 0) newsize++; if(oldsize > 0) oldsize++; LUSOL->a = (REAL *) clean_realloc(LUSOL->a, sizeof(*(LUSOL->a)), newsize, oldsize); LUSOL->indc = (int *) clean_realloc(LUSOL->indc, sizeof(*(LUSOL->indc)), newsize, oldsize); LUSOL->indr = (int *) clean_realloc(LUSOL->indr, sizeof(*(LUSOL->indr)), newsize, oldsize); if((newsize == 0) || ((LUSOL->a != NULL) && (LUSOL->indc != NULL) && (LUSOL->indr != NULL))) return( TRUE ); else return( FALSE ); } MYBOOL LUSOL_expand_a(LUSOLrec *LUSOL, int *delta_lena, int *right_shift) { #ifdef StaticMemAlloc return( FALSE ); #else int LENA, NFREE, LFREE; /* Add expansion factor to avoid having to resize too often/too much; (exponential formula suggested by Michael A. Saunders) */ LENA = LUSOL->lena; *delta_lena = DELTA_SIZE(*delta_lena, LENA); /* Expand it! */ if((*delta_lena <= 0) || !LUSOL_realloc_a(LUSOL, LENA+(*delta_lena))) return( FALSE ); /* Make sure we return the actual memory increase of a */ *delta_lena = LUSOL->lena-LENA; /* Shift the used memory area to the right */ LFREE = *right_shift; NFREE = LFREE+*delta_lena; LENA -= LFREE-1; MEMMOVE(LUSOL->a+NFREE, LUSOL->a+LFREE, LENA); MEMMOVE(LUSOL->indr+NFREE, LUSOL->indr+LFREE, LENA); MEMMOVE(LUSOL->indc+NFREE, LUSOL->indc+LFREE, LENA); /* Also return the new starting position for the used memory area of a */ *right_shift = NFREE; LUSOL->expanded_a++; return( TRUE ); #endif } MYBOOL LUSOL_realloc_r(LUSOLrec *LUSOL, int newsize) { int oldsize; if(newsize < 0) newsize = LUSOL->maxm + MAX(abs(newsize), LUSOL_MINDELTA_rc); oldsize = LUSOL->maxm; LUSOL->maxm = newsize; if(newsize > 0) newsize++; if(oldsize > 0) oldsize++; LUSOL->lenr = (int *) clean_realloc(LUSOL->lenr, sizeof(*(LUSOL->lenr)), newsize, oldsize); LUSOL->ip = (int *) clean_realloc(LUSOL->ip, sizeof(*(LUSOL->ip)), newsize, oldsize); LUSOL->iqloc = (int *) clean_realloc(LUSOL->iqloc, sizeof(*(LUSOL->iqloc)), newsize, oldsize); LUSOL->ipinv = (int *) clean_realloc(LUSOL->ipinv, sizeof(*(LUSOL->ipinv)), newsize, oldsize); LUSOL->locr = (int *) clean_realloc(LUSOL->locr, sizeof(*(LUSOL->locr)), newsize, oldsize); if((newsize == 0) || ((LUSOL->lenr != NULL) && (LUSOL->ip != NULL) && (LUSOL->iqloc != NULL) && (LUSOL->ipinv != NULL) && (LUSOL->locr != NULL))) { #ifndef ClassicHamaxR #ifdef AlwaysSeparateHamaxR if(LUSOL->luparm[LUSOL_IP_PIVOTTYPE] == LUSOL_PIVMOD_TRP) #endif { LUSOL->amaxr = (REAL *) clean_realloc(LUSOL->amaxr, sizeof(*(LUSOL->amaxr)), newsize, oldsize); if((newsize > 0) && (LUSOL->amaxr == NULL)) return( FALSE ); } #endif return( TRUE ); } else return( FALSE ); } MYBOOL LUSOL_realloc_c(LUSOLrec *LUSOL, int newsize) { int oldsize; if(newsize < 0) newsize = LUSOL->maxn + MAX(abs(newsize), LUSOL_MINDELTA_rc); oldsize = LUSOL->maxn; LUSOL->maxn = newsize; if(newsize > 0) newsize++; if(oldsize > 0) oldsize++; LUSOL->lenc = (int *) clean_realloc(LUSOL->lenc, sizeof(*(LUSOL->lenc)), newsize, oldsize); LUSOL->iq = (int *) clean_realloc(LUSOL->iq, sizeof(*(LUSOL->iq)), newsize, oldsize); LUSOL->iploc = (int *) clean_realloc(LUSOL->iploc, sizeof(*(LUSOL->iploc)), newsize, oldsize); LUSOL->iqinv = (int *) clean_realloc(LUSOL->iqinv, sizeof(*(LUSOL->iqinv)), newsize, oldsize); LUSOL->locc = (int *) clean_realloc(LUSOL->locc, sizeof(*(LUSOL->locc)), newsize, oldsize); LUSOL->w = (REAL *) clean_realloc(LUSOL->w, sizeof(*(LUSOL->w)), newsize, oldsize); #ifdef LUSOLSafeFastUpdate LUSOL->vLU6L = (REAL *) clean_realloc(LUSOL->vLU6L, sizeof(*(LUSOL->vLU6L)), newsize, oldsize); #else LUSOL->vLU6L = LUSOL->w; #endif if((newsize == 0) || ((LUSOL->w != NULL) && (LUSOL->lenc != NULL) && (LUSOL->iq != NULL) && (LUSOL->iploc != NULL) && (LUSOL->iqinv != NULL) && (LUSOL->locc != NULL))) { #ifndef ClassicHamaxR if(LUSOL->luparm[LUSOL_IP_PIVOTTYPE] == LUSOL_PIVMOD_TCP) { LUSOL->Ha = (REAL *) clean_realloc(LUSOL->Ha, sizeof(*(LUSOL->Ha)), newsize, oldsize); LUSOL->Hj = (int *) clean_realloc(LUSOL->Hj, sizeof(*(LUSOL->Hj)), newsize, oldsize); LUSOL->Hk = (int *) clean_realloc(LUSOL->Hk, sizeof(*(LUSOL->Hk)), newsize, oldsize); if((newsize > 0) && ((LUSOL->Ha == NULL) || (LUSOL->Hj == NULL) || (LUSOL->Hk == NULL))) return( FALSE ); } #endif #ifndef ClassicdiagU if(LUSOL->luparm[LUSOL_IP_KEEPLU] == FALSE) { LUSOL->diagU = (REAL *) clean_realloc(LUSOL->diagU, sizeof(*(LUSOL->diagU)), newsize, oldsize); if((newsize > 0) && (LUSOL->diagU == NULL)) return( FALSE ); } #endif return( TRUE ); } else return( FALSE ); } LUSOLrec *LUSOL_create(FILE *outstream, int msgfil, int pivotmodel, int updatelimit) { LUSOLrec *newLU; newLU = (LUSOLrec *) LUSOL_CALLOC(1, sizeof(*newLU)); if(newLU == NULL) return( newLU ); newLU->luparm[LUSOL_IP_SCALAR_NZA] = LUSOL_MULT_nz_a; newLU->outstream = outstream; newLU->luparm[LUSOL_IP_PRINTUNIT] = msgfil; newLU->luparm[LUSOL_IP_PRINTLEVEL] = LUSOL_MSG_SINGULARITY; LUSOL_setpivotmodel(newLU, pivotmodel, LUSOL_PIVTOL_DEFAULT); newLU->parmlu[LUSOL_RP_GAMMA] = LUSOL_DEFAULT_GAMMA; newLU->parmlu[LUSOL_RP_ZEROTOLERANCE] = 3.0e-13; newLU->parmlu[LUSOL_RP_SMALLDIAG_U] = /*3.7e-11;*/ newLU->parmlu[LUSOL_RP_EPSDIAG_U] = 3.7e-11; newLU->parmlu[LUSOL_RP_COMPSPACE_U] = 3.0e+0; newLU->luparm[LUSOL_IP_MARKOWITZ_MAXCOL] = 5; newLU->parmlu[LUSOL_RP_MARKOWITZ_CONLY] = 0.3e+0; newLU->parmlu[LUSOL_RP_MARKOWITZ_DENSE] = 0.5e+0; newLU->parmlu[LUSOL_RP_SMARTRATIO] = LUSOL_DEFAULT_SMARTRATIO; #ifdef ForceRowBasedL0 newLU->luparm[LUSOL_IP_ACCELERATION] = LUSOL_BASEORDER; #endif newLU->luparm[LUSOL_IP_KEEPLU] = TRUE; newLU->luparm[LUSOL_IP_UPDATELIMIT] = updatelimit; init_BLAS(); return( newLU ); } MYBOOL LUSOL_sizeto(LUSOLrec *LUSOL, int init_r, int init_c, int init_a) { if(init_c == 0) LUSOL_FREE(LUSOL->isingular); if(LUSOL_realloc_a(LUSOL, init_a) && LUSOL_realloc_r(LUSOL, init_r) && LUSOL_realloc_c(LUSOL, init_c)) return( TRUE ); else return( FALSE ); } char *LUSOL_pivotLabel(LUSOLrec *LUSOL) { static /*const*/ char *pivotText[LUSOL_PIVMOD_MAX+1] = {"TPP", "TRP", "TCP", "TSP"}; return(pivotText[LUSOL->luparm[LUSOL_IP_PIVOTTYPE]]); } void LUSOL_setpivotmodel(LUSOLrec *LUSOL, int pivotmodel, int initlevel) { REAL newFM, newUM; /* Set pivotmodel if specified */ if(pivotmodel > LUSOL_PIVMOD_NOCHANGE) { if((pivotmodel <= LUSOL_PIVMOD_DEFAULT) || (pivotmodel > LUSOL_PIVMOD_MAX)) pivotmodel = LUSOL_PIVMOD_TPP; LUSOL->luparm[LUSOL_IP_PIVOTTYPE] = pivotmodel; } /* Check if we need bother about changing tolerances */ if((initlevel <= LUSOL_PIVTOL_NOCHANGE) || (initlevel > LUSOL_PIVTOL_MAX)) return; /* Set default pivot tolerances (note that UPDATEMAX should always be <= FACTORMAX) */ if(initlevel == LUSOL_PIVTOL_BAGGY) { /* Extra-loose pivot thresholds */ newFM = 500.0; newUM = newFM / 20; } else if(initlevel == LUSOL_PIVTOL_LOOSE) { /* Moderately tight pivot tolerances */ newFM = 100.0; newUM = newFM / 10; } else if(initlevel == LUSOL_PIVTOL_NORMAL) { /* Standard pivot tolerances */ newFM = 28.0; newUM = newFM / 4; } else if(initlevel == LUSOL_PIVTOL_SLIM) { /* Better accuracy pivot tolerances */ newFM = 10.0; newUM = newFM / 2; } else if(initlevel == LUSOL_PIVTOL_TIGHT) { /* Enhanced accuracy pivot tolerances */ newFM = 5.0; newUM = newFM / 2; } else if(initlevel == LUSOL_PIVTOL_SUPER) { /* Very tight pivot tolerances for extra accuracy */ newFM = 2.5; newUM = 1.99; } else { /* Extremely tight pivot tolerances for extra accuracy */ newFM = 1.99; newUM = newFM / 1.49; } /* Set the tolerances */ LUSOL->parmlu[LUSOL_RP_FACTORMAX_Lij] = newFM; LUSOL->parmlu[LUSOL_RP_UPDATEMAX_Lij] = newUM; } MYBOOL LUSOL_tightenpivot(LUSOLrec *LUSOL) { #if 0 REAL newvalue; #endif /* Give up tightening if we are already less than limit and we cannot change strategy */ if(MIN(LUSOL->parmlu[LUSOL_RP_FACTORMAX_Lij], LUSOL->parmlu[LUSOL_RP_UPDATEMAX_Lij]) < 1.1) { if(LUSOL->luparm[LUSOL_IP_PIVOTTYPE] >= LUSOL_PIVMOD_TRP) return( FALSE ); LUSOL_setpivotmodel(LUSOL, LUSOL->luparm[LUSOL_IP_PIVOTTYPE]+1, LUSOL_PIVTOL_DEFAULT+1); return( 2 ); } /* Otherwise tighten according to defined schedule */ #if 0 /* This is Michael Saunder's proposed tightening procedure */ newvalue = sqrt(LUSOL->parmlu[LUSOL_RP_FACTORMAX_Lij]); LUSOL->parmlu[LUSOL_RP_FACTORMAX_Lij] = newvalue; SETMIN(LUSOL->parmlu[LUSOL_RP_UPDATEMAX_Lij], newvalue); #elif 0 /* This is Kjell Eikland's schedule #1 */ newvalue = sqrt(LUSOL->parmlu[LUSOL_RP_FACTORMAX_Lij]); LUSOL->parmlu[LUSOL_RP_FACTORMAX_Lij] = newvalue; LUSOL->parmlu[LUSOL_RP_UPDATEMAX_Lij] = 1.0 + (newvalue - 1.0) / 2; #else /* This was Kjell Eikland's schedule #2 */ LUSOL->parmlu[LUSOL_RP_FACTORMAX_Lij] = 1.0 + LUSOL->parmlu[LUSOL_RP_FACTORMAX_Lij]/3.0; LUSOL->parmlu[LUSOL_RP_UPDATEMAX_Lij] = 1.0 + LUSOL->parmlu[LUSOL_RP_UPDATEMAX_Lij]/3.0; #endif return( TRUE ); } MYBOOL LUSOL_addSingularity(LUSOLrec *LUSOL, int singcol, int *inform) { int NSING = LUSOL->luparm[LUSOL_IP_SINGULARITIES], ASING = LUSOL->luparm[LUSOL_IP_SINGULARLISTSIZE]; /* Check if we need to allocated list memory to store multiple singularities */ if((NSING > 0) && (NSING >= ASING)) { /* Increase list in "reasonable" steps */ ASING += (int) (10.0 * (log10((REAL) LUSOL->m)+1.0)); LUSOL->isingular = (int *) LUSOL_REALLOC(LUSOL->isingular, sizeof(*LUSOL->isingular)*(ASING+1)); if(LUSOL->isingular == NULL) { LUSOL->luparm[LUSOL_IP_SINGULARLISTSIZE] = 0; *inform = LUSOL_INFORM_NOMEMLEFT; return( FALSE ); } LUSOL->luparm[LUSOL_IP_SINGULARLISTSIZE] = ASING; /* Transfer the first singularity if the list was just created */ if(NSING == 1) LUSOL->isingular[NSING] = LUSOL->luparm[LUSOL_IP_SINGULARINDEX]; } /* Update singularity count and store its index */ NSING++; if(NSING > 1) { LUSOL->isingular[0] = NSING; LUSOL->isingular[NSING] = singcol; } LUSOL->luparm[LUSOL_IP_SINGULARITIES] = NSING; /* Mimic old logic by keeping the last singularity stored */ LUSOL->luparm[LUSOL_IP_SINGULARINDEX] = singcol; return( TRUE ); } int LUSOL_getSingularity(LUSOLrec *LUSOL, int singitem) { if((singitem > LUSOL->luparm[LUSOL_IP_SINGULARITIES]) || (singitem < 0)) singitem = -1; else if(singitem == 0) singitem = LUSOL->luparm[LUSOL_IP_SINGULARITIES]; else if(singitem > 1) singitem = LUSOL->isingular[singitem]; else singitem = LUSOL->luparm[LUSOL_IP_SINGULARINDEX]; return( singitem ); } int LUSOL_findSingularityPosition(LUSOLrec *LUSOL, int singcol) /* The purpose of this routine is to find the slack row/column in user-index that was singular in the last unsuccessful column update; zero is returned if the search was unsuccessful. By adding a slack at this position this particular singularity should disappear. (Source: Michael A. Saunders; private communication to KE) */ { #if 0 /* Michael Saunders version */ int j; for(j = LUSOL->m; j > 0; j--) if(LUSOL->iq[j] == singcol) break; singcol = j; #else /* Kjell Eikland version (note that iqinv could be invalid in early versions of LUSOL) */ singcol = LUSOL->iqinv[singcol]; #endif return( LUSOL->ip[singcol] ); } char *LUSOL_informstr(LUSOLrec *LUSOL, int inform) { static char *informText[LUSOL_INFORM_MAX-LUSOL_INFORM_MIN+1] = {"LUSOL_RANKLOSS: Lost rank", "LUSOL_LUSUCCESS: Success", "LUSOL_LUSINGULAR: Singular A", "LUSOL_LUUNSTABLE: Unstable factorization", "LUSOL_ADIMERR: Row or column count exceeded", "LUSOL_ADUPLICATE: Duplicate A matrix entry found", "(Undefined message)", "(Undefined message)", "LUSOL_ANEEDMEM: Insufficient memory for factorization", "LUSOL_FATALERR: Fatal internal error", "LUSOL_NOPIVOT: Found no suitable pivot", "LUSOL_NOMEMLEFT: Could not obtain more memory"}; if((inform < LUSOL_INFORM_MIN) || (inform > LUSOL_INFORM_MAX)) inform = LUSOL->luparm[LUSOL_IP_INFORM]; return(informText[inform-LUSOL_INFORM_MIN]); } void LUSOL_clear(LUSOLrec *LUSOL, MYBOOL nzonly) { int len; LUSOL->nelem = 0; if(!nzonly) { /* lena arrays */ len = LUSOL->lena + LUSOL_ARRAYOFFSET; MEMCLEAR(LUSOL->a, len); MEMCLEAR(LUSOL->indc, len); MEMCLEAR(LUSOL->indr, len); /* maxm arrays */ len = LUSOL->maxm + LUSOL_ARRAYOFFSET; MEMCLEAR(LUSOL->lenr, len); MEMCLEAR(LUSOL->ip, len); MEMCLEAR(LUSOL->iqloc, len); MEMCLEAR(LUSOL->ipinv, len); MEMCLEAR(LUSOL->locr, len); #ifndef ClassicHamaxR if((LUSOL->amaxr != NULL) #ifdef AlwaysSeparateHamaxR && (LUSOL->luparm[LUSOL_IP_PIVOTTYPE] == LUSOL_PIVMOD_TRP) #endif ) MEMCLEAR(LUSOL->amaxr, len); #endif /* maxn arrays */ len = LUSOL->maxn + LUSOL_ARRAYOFFSET; MEMCLEAR(LUSOL->lenc, len); MEMCLEAR(LUSOL->iq, len); MEMCLEAR(LUSOL->iploc, len); MEMCLEAR(LUSOL->iqinv, len); MEMCLEAR(LUSOL->locc, len); MEMCLEAR(LUSOL->w, len); if(LUSOL->luparm[LUSOL_IP_PIVOTTYPE] == LUSOL_PIVMOD_TCP) { MEMCLEAR(LUSOL->Ha, len); MEMCLEAR(LUSOL->Hj, len); MEMCLEAR(LUSOL->Hk, len); } #ifndef ClassicdiagU if(LUSOL->luparm[LUSOL_IP_KEEPLU] == FALSE) { MEMCLEAR(LUSOL->diagU, len); } #endif } } MYBOOL LUSOL_assign(LUSOLrec *LUSOL, int iA[], int jA[], REAL Aij[], int nzcount, MYBOOL istriplet) { int k, m, n, ij, kol; /* Adjust the size of the a structure */ if(nzcount > (LUSOL->lena/LUSOL->luparm[LUSOL_IP_SCALAR_NZA]) && !LUSOL_realloc_a(LUSOL, nzcount*LUSOL->luparm[LUSOL_IP_SCALAR_NZA])) return( FALSE ); m = 0; n = 0; kol = 1; for(k = 1; k <= nzcount; k++) { /* First the row indicator */ ij = iA[k]; if(ij > m) { m = ij; if(m > LUSOL->maxm && !LUSOL_realloc_r(LUSOL, -(m / LUSOL_MINDELTA_FACTOR + 1))) return( FALSE ); } LUSOL->indc[k] = ij; /* Then the column indicator; Handle both triplet and column count formats */ if(istriplet) ij = jA[k]; else { if(k >= jA[kol]) kol++; ij = kol; } if(ij > n) { n = ij; if(n > LUSOL->maxn && !LUSOL_realloc_c(LUSOL, -(n / LUSOL_MINDELTA_FACTOR + 1))) return( FALSE ); } LUSOL->indr[k] = ij; /* Lastly the matrix value itself */ LUSOL->a[k] = Aij[k]; } LUSOL->m = m; LUSOL->n = n; LUSOL->nelem = nzcount; return( TRUE ); } int LUSOL_loadColumn(LUSOLrec *LUSOL, int iA[], int jA, REAL Aij[], int nzcount, int offset1) { int i, ii, nz, k; nz = LUSOL->nelem; i = nz + nzcount; if(i > (LUSOL->lena/LUSOL->luparm[LUSOL_IP_SCALAR_NZA]) && !LUSOL_realloc_a(LUSOL, i*LUSOL->luparm[LUSOL_IP_SCALAR_NZA])) return( -1 ); k = 0; for(ii = 1; ii <= nzcount; ii++) { i = ii + offset1; if(Aij[i] == 0) continue; if(iA[i] <= 0 || iA[i] > LUSOL->m || jA <= 0 || jA > LUSOL->n) { LUSOL_report(LUSOL, 0, "Variable index outside of set bounds (r:%d/%d, c:%d/%d)\n", iA[i], LUSOL->m, jA, LUSOL->n); continue; } k++; nz++; LUSOL->a[nz] = Aij[i]; LUSOL->indc[nz] = iA[i]; LUSOL->indr[nz] = jA; } LUSOL->nelem = nz; return( k ); } void LUSOL_free(LUSOLrec *LUSOL) { LUSOL_realloc_a(LUSOL, 0); LUSOL_realloc_r(LUSOL, 0); LUSOL_realloc_c(LUSOL, 0); if(LUSOL->L0 != NULL) LUSOL_matfree(&(LUSOL->L0)); if(LUSOL->U != NULL) LUSOL_matfree(&(LUSOL->U)); if(!is_nativeBLAS()) unload_BLAS(); LUSOL_FREE(LUSOL); } void LUSOL_report(LUSOLrec *LUSOL, int msglevel, char *format, ...) { va_list ap; if(LUSOL == NULL) { va_start(ap, format); vfprintf(stderr, format, ap); va_end(ap); } else if(msglevel >= 0 /*LUSOL->luparm[2]*/) { if(LUSOL->writelog != NULL) { char buff[255]; va_start(ap, format); vsprintf(buff, format, ap); va_end(ap); LUSOL->writelog(LUSOL, LUSOL->loghandle, buff); } if(LUSOL->outstream != NULL) { va_start(ap, format); vfprintf(LUSOL->outstream, format, ap); va_end(ap); fflush(LUSOL->outstream); } } } void LUSOL_timer(LUSOLrec *LUSOL, int timerid, char *text) { LUSOL_report(LUSOL, -1, "TimerID %d at %s - %s\n", timerid, "", text); } int LUSOL_factorize(LUSOLrec *LUSOL) { int inform; LU1FAC( LUSOL, &inform ); return( inform ); } int LUSOL_ftran(LUSOLrec *LUSOL, REAL b[], int NZidx[], MYBOOL prepareupdate) { int inform; REAL *vector; if(prepareupdate) vector = LUSOL->vLU6L; else vector = LUSOL->w; /* Copy RHS vector, but make adjustment for offset since this can create a memory error when the calling program uses a 0-base vector offset back to comply with LUSOL. */ MEMCOPY(vector+1, b+1, LUSOL->n); vector[0] = 0; LU6SOL(LUSOL, LUSOL_SOLVE_Aw_v, vector, b, NZidx, &inform); LUSOL->luparm[LUSOL_IP_FTRANCOUNT]++; return(inform); } int LUSOL_btran(LUSOLrec *LUSOL, REAL b[], int NZidx[]) { int inform; /* Copy RHS vector, but make adjustment for offset since this can create a memory error when the calling program uses a 0-base vector offset back to comply with LUSOL. */ MEMCOPY(LUSOL->w+1, b+1, LUSOL->m); LUSOL->w[0] = 0; LU6SOL(LUSOL, LUSOL_SOLVE_Atv_w, b, LUSOL->w, NZidx, &inform); LUSOL->luparm[LUSOL_IP_BTRANCOUNT]++; return(inform); } int LUSOL_replaceColumn(LUSOLrec *LUSOL, int jcol, REAL v[]) { int inform; REAL DIAG, VNORM; LU8RPC(LUSOL, LUSOL_UPDATE_OLDNONEMPTY, LUSOL_UPDATE_NEWNONEMPTY, jcol, v, NULL, &inform, &DIAG, &VNORM); LUSOL->replaced_c++; return( inform ); } REAL LUSOL_vecdensity(LUSOLrec *LUSOL, REAL V[]) { int I, N = 0; for(I = 1; I <= LUSOL->m; I++) if(fabs(V[I]) > 0) N++; return( (REAL) N / (REAL) LUSOL->m ); } char relationChar(REAL left, REAL right) { if(left > right) return('>'); else if(left == right) return('='); else return('<'); } /* Retrieve the core modules ordered by order of dependency */ #include "lusol2.c" /* Heap management */ #include "lusol6a.c" /* Singularity checking and equation solving */ #include "lusol1.c" /* Factorization and core components */ #include "lusol7a.c" /* Utility routines for updates */ #include "lusol8a.c" /* Column update */ void LUSOL_dump(FILE *output, LUSOLrec *LUSOL) { MYBOOL userfile = (MYBOOL) (output != NULL); if(!userfile) output = fopen("LUSOL.dbg", "w"); blockWriteREAL(output, "a", LUSOL->a, 1, LUSOL->lena); blockWriteINT(output, "indc", LUSOL->indc, 1, LUSOL->lena); blockWriteINT(output, "indr", LUSOL->indr, 1, LUSOL->lena); blockWriteINT(output, "ip", LUSOL->ip, 1, LUSOL->m); blockWriteINT(output, "iq", LUSOL->iq, 1, LUSOL->n); blockWriteINT(output, "lenc", LUSOL->lenc, 1, LUSOL->n); blockWriteINT(output, "lenr", LUSOL->lenr, 1, LUSOL->m); blockWriteINT(output, "locc", LUSOL->locc, 1, LUSOL->n); blockWriteINT(output, "locr", LUSOL->locr, 1, LUSOL->m); blockWriteINT(output, "iploc", LUSOL->iploc, 1, LUSOL->n); blockWriteINT(output, "iqloc", LUSOL->iqloc, 1, LUSOL->m); blockWriteINT(output, "ipinv", LUSOL->ipinv, 1, LUSOL->m); blockWriteINT(output, "iqinv", LUSOL->iqinv, 1, LUSOL->n); if(!userfile) fclose(output); } LUSOLmat *LUSOL_matcreate(int dim, int nz) { LUSOLmat *newm; newm = (LUSOLmat *) LUSOL_CALLOC(1, sizeof(*newm)); if(newm != NULL) { newm->a = (REAL *) LUSOL_MALLOC((nz+1)*sizeof(REAL)); newm->lenx = (int *) LUSOL_MALLOC((dim+1)*sizeof(int)); newm->indx = (int *) LUSOL_MALLOC((dim+1)*sizeof(int)); newm->indr = (int *) LUSOL_MALLOC((nz+1)*sizeof(int)); newm->indc = (int *) LUSOL_MALLOC((nz+1)*sizeof(int)); if((newm->a == NULL) || (newm->lenx == NULL) || (newm->indx == NULL) || (newm->indr == NULL) || (newm->indc == NULL)) LUSOL_matfree(&newm); } return(newm); } void LUSOL_matfree(LUSOLmat **mat) { if((mat == NULL) || (*mat == NULL)) return; LUSOL_FREE((*mat)->a); LUSOL_FREE((*mat)->indc); LUSOL_FREE((*mat)->indr); LUSOL_FREE((*mat)->lenx); LUSOL_FREE((*mat)->indx); LUSOL_FREE(*mat); } MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/lusolio.h0000664000175000017500000000176611141443435021201 0ustar lauerlauer#ifndef HEADER_lusolio #define HEADER_lusolio /* Include necessary libraries */ /* ------------------------------------------------------------------------- */ #include "lusol.h" MYBOOL ctf_read_A(char *filename, int maxm, int maxn, int maxnz, int *m, int *n, int *nnzero, int *iA, int *jA, REAL *Aij); MYBOOL ctf_size_A(char *filename, int *m, int *n, int *nnzero); MYBOOL ctf_read_b(char *filename, int m, REAL *b); MYBOOL mmf_read_A(char *filename, int maxM, int maxN, int maxnz, int *M, int *N, int *nz, int *iA, int *jA, REAL *Aij); MYBOOL mmf_size_A(char *filename, int *M, int *N, int *nz); MYBOOL mmf_read_b(char *filename, int m, REAL *b); MYBOOL hbf_read_A(char *filename, int maxM, int maxN, int maxnz, int *M, int *N, int *nz, int *iA, int *jA, REAL *Aij); MYBOOL hbf_size_A(char *filename, int *M, int *N, int *nz); MYBOOL hbf_read_b(char *filename, int m, REAL *b); #endif /* HEADER_lusolio */ MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/lusol1.c0000664000175000017500000041106111141443433020714 0ustar lauerlauer /* ================================================================== lu1DCP factors a dense m x n matrix A by Gaussian elimination, using Complete Pivoting (row and column interchanges) for stability. This version also uses column interchanges if all elements in a pivot column are smaller than (or equal to) "small". Such columns are changed to zero and permuted to the right-hand end. As in LINPACK's dgefa, ipvt(!) keeps track of pivot rows. Rows of U are interchanged, but we don't have to physically permute rows of L. In contrast, column interchanges are applied directly to the columns of both L and U, and to the column permutation vector iq(*). ------------------------------------------------------------------ On entry: a Array holding the matrix A to be factored. lda The leading dimension of the array a. m The number of rows in A. n The number of columns in A. small A drop tolerance. Must be zero or positive. On exit: a An upper triangular matrix and the multipliers which were used to obtain it. The factorization can be written A = L*U where L is a product of permutation and unit lower triangular matrices and U is upper triangular. nsing Number of singularities detected. ipvt Records the pivot rows. iq A vector to which column interchanges are applied. ------------------------------------------------------------------ 01 May 2002: First dense Complete Pivoting, derived from lu1DPP. 07 May 2002: Another break needed at end of first loop. 07 May 2002: Current version of lu1DCP. ================================================================== */ void LU1DCP(LUSOLrec *LUSOL, REAL DA[], int LDA, int M, int N, REAL SMALL, int *NSING, int IPVT[], int IX[]) { int I, J, K, KP1, L, LAST, LENCOL, IMAX, JMAX, JLAST, JNEW; REAL AIJMAX, AJMAX; register REAL T; #ifdef LUSOLFastDenseIndex register REAL *DA1, *DA2; int IDA1, IDA2; #else register int IDA1, IDA2; #endif *NSING = 0; LENCOL = M+1; LAST = N; /* ----------------------------------------------------------------- Start of elimination loop. ----------------------------------------------------------------- */ for(K = 1; K <= N; K++) { KP1 = K+1; LENCOL--; /* Find the biggest aij in row imax and column jmax. */ AIJMAX = ZERO; IMAX = K; JMAX = K; JLAST = LAST; for(J = K; J <= JLAST; J++) { x10: L = idamax(LENCOL,DA+DAPOS(K,J)-LUSOL_ARRAYOFFSET,1)+K-1; AJMAX = fabs(DA[DAPOS(L,J)]); if(AJMAX<=SMALL) { /* ======================================================== Do column interchange, changing old column to zero. Reduce "last" and try again with same j. ======================================================== */ (*NSING)++; JNEW = IX[LAST]; IX[LAST] = IX[J]; IX[J] = JNEW; #ifdef LUSOLFastDenseIndex DA1 = DA+DAPOS(0,LAST); DA2 = DA+DAPOS(0,J); for(I = 1; I <= K-1; I++) { DA1++; DA2++; T = *DA1; *DA1 = *DA2; *DA2 = T; #else for(I = 1; I <= K-1; I++) { IDA1 = DAPOS(I,LAST); IDA2 = DAPOS(I,J); T = DA[IDA1]; DA[IDA1] = DA[IDA2]; DA[IDA2] = T; #endif } #ifdef LUSOLFastDenseIndex for(I = K; I <= M; I++) { DA1++; DA2++; T = *DA1; *DA1 = ZERO; *DA2 = T; #else for(I = K; I <= M; I++) { IDA1 = DAPOS(I,LAST); IDA2 = DAPOS(I,J); T = DA[IDA1]; DA[IDA1] = ZERO; DA[IDA2] = T; #endif } LAST--; if(J<=LAST) goto x10; break; } /* Check if this column has biggest aij so far. */ if(AIJMAX=LAST) break; } IPVT[K] = IMAX; if(JMAX!=K) { /* ========================================================== Do column interchange (k and jmax). ========================================================== */ JNEW = IX[JMAX]; IX[JMAX] = IX[K]; IX[K] = JNEW; #ifdef LUSOLFastDenseIndex DA1 = DA+DAPOS(0,JMAX); DA2 = DA+DAPOS(0,K); for(I = 1; I <= M; I++) { DA1++; DA2++; T = *DA1; *DA1 = *DA2; *DA2 = T; #else for(I = 1; I <= M; I++) { IDA1 = DAPOS(I,JMAX); IDA2 = DAPOS(I,K); T = DA[IDA1]; DA[IDA1] = DA[IDA2]; DA[IDA2] = T; #endif } } if(M>K) { /* =========================================================== Do row interchange if necessary. =========================================================== */ if(IMAX!=K) { IDA1 = DAPOS(IMAX,K); IDA2 = DAPOS(K,K); T = DA[IDA1]; DA[IDA1] = DA[IDA2]; DA[IDA2] = T; } /* =========================================================== Compute multipliers. Do row elimination with column indexing. =========================================================== */ T = -ONE/DA[DAPOS(K,K)]; dscal(M-K,T,DA+DAPOS(KP1,K)-LUSOL_ARRAYOFFSET,1); for(J = KP1; J <= LAST; J++) { IDA1 = DAPOS(IMAX,J); T = DA[IDA1]; if(IMAX!=K) { IDA2 = DAPOS(K,J); DA[IDA1] = DA[IDA2]; DA[IDA2] = T; } daxpy(M-K,T,DA+DAPOS(KP1,K)-LUSOL_ARRAYOFFSET,1, DA+DAPOS(KP1,J)-LUSOL_ARRAYOFFSET,1); } } else break; if(K>=LAST) break; } /* Set ipvt(*) for singular rows. */ for(K = LAST+1; K <= M; K++) IPVT[K] = K; } /* ================================================================== lu1DPP factors a dense m x n matrix A by Gaussian elimination, using row interchanges for stability, as in dgefa from LINPACK. This version also uses column interchanges if all elements in a pivot column are smaller than (or equal to) "small". Such columns are changed to zero and permuted to the right-hand end. As in LINPACK, ipvt(*) keeps track of pivot rows. Rows of U are interchanged, but we don't have to physically permute rows of L. In contrast, column interchanges are applied directly to the columns of both L and U, and to the column permutation vector iq(*). ------------------------------------------------------------------ On entry: a Array holding the matrix A to be factored. lda The leading dimension of the array a. m The number of rows in A. n The number of columns in A. small A drop tolerance. Must be zero or positive. On exit: a An upper triangular matrix and the multipliers which were used to obtain it. The factorization can be written A = L*U where L is a product of permutation and unit lower triangular matrices and U is upper triangular. nsing Number of singularities detected. ipvt Records the pivot rows. iq A vector to which column interchanges are applied. ------------------------------------------------------------------ 02 May 1989: First version derived from dgefa in LINPACK (version dated 08/14/78). 05 Feb 1994: Generalized to treat rectangular matrices and use column interchanges when necessary. ipvt is retained, but column permutations are applied directly to iq(*). 21 Dec 1994: Bug found via example from Steve Dirkse. Loop 100 added to set ipvt(*) for singular rows. ================================================================== */ void LU1DPP(LUSOLrec *LUSOL, REAL DA[], int LDA, int M, int N, REAL SMALL, int *NSING, int IPVT[], int IX[]) { int I, J, K, KP1, L, LAST, LENCOL; register REAL T; #ifdef LUSOLFastDenseIndex register REAL *DA1, *DA2; int IDA1, IDA2; #else register int IDA1, IDA2; #endif *NSING = 0; K = 1; LAST = N; /* ------------------------------------------------------------------ Start of elimination loop. ------------------------------------------------------------------ */ x10: KP1 = K+1; LENCOL = (M-K)+1; /* Find l, the pivot row. */ L = (idamax(LENCOL,DA+DAPOS(K,K)-LUSOL_ARRAYOFFSET,1)+K)-1; IPVT[K] = L; if(fabs(DA[DAPOS(L,K)])<=SMALL) { /* =============================================================== Do column interchange, changing old pivot column to zero. Reduce "last" and try again with same k. =============================================================== */ (*NSING)++; J = IX[LAST]; IX[LAST] = IX[K]; IX[K] = J; #ifdef LUSOLFastDenseIndex DA1 = DA+DAPOS(0,LAST); DA2 = DA+DAPOS(0,K); for(I = 1; I <= K-1; I++) { DA1++; DA2++; T = *DA1; *DA1 = *DA2; *DA2 = T; #else for(I = 1; I <= K-1; I++) { IDA1 = DAPOS(I,LAST); IDA2 = DAPOS(I,K); T = DA[IDA1]; DA[IDA1] = DA[IDA2]; DA[IDA2] = T; #endif } #ifdef LUSOLFastDenseIndex for(I = K; I <= M; I++) { DA1++; DA2++; T = *DA1; *DA1 = ZERO; *DA2 = T; #else for(I = K; I <= M; I++) { IDA1 = DAPOS(I,LAST); IDA2 = DAPOS(I,K); T = DA[IDA1]; DA[IDA1] = ZERO; DA[IDA2] = T; #endif } LAST = LAST-1; if(K<=LAST) goto x10; } else if(M>K) { /* =============================================================== Do row interchange if necessary. =============================================================== */ if(L!=K) { IDA1 = DAPOS(L,K); IDA2 = DAPOS(K,K); T = DA[IDA1]; DA[IDA1] = DA[IDA2]; DA[IDA2] = T; } /* =============================================================== Compute multipliers. Do row elimination with column indexing. =============================================================== */ T = -ONE/DA[DAPOS(K,K)]; dscal(M-K,T,DA+DAPOS(KP1,K)-LUSOL_ARRAYOFFSET,1); for(J = KP1; J <= LAST; J++) { IDA1 = DAPOS(L,J); T = DA[IDA1]; if(L!=K) { IDA2 = DAPOS(K,J); DA[IDA1] = DA[IDA2]; DA[IDA2] = T; } daxpy(M-K,T,DA+DAPOS(KP1,K)-LUSOL_ARRAYOFFSET,1, DA+DAPOS(KP1,J)-LUSOL_ARRAYOFFSET,1); } K++; if(K<=LAST) goto x10; } /* Set ipvt(*) for singular rows. */ for(K = LAST+1; K <= M; K++) IPVT[K] = K; } /* ================================================================== lu1pq1 constructs a permutation iperm from the array len. ------------------------------------------------------------------ On entry: len(i) holds the number of nonzeros in the i-th row (say) of an m by n matrix. num(*) can be anything (workspace). On exit: iperm contains a list of row numbers in the order rows of length 0, rows of length 1,..., rows of length n. loc(nz) points to the first row containing nz nonzeros, nz = 1, n. inv(i) points to the position of row i within iperm(*). ================================================================== */ void LU1PQ1(LUSOLrec *LUSOL, int M, int N, int LEN[], int IPERM[], int LOC[], int INV[], int NUM[]) { int NZEROS, NZ, I, L; /* Count the number of rows of each length. */ NZEROS = 0; for(NZ = 1; NZ <= N; NZ++) { NUM[NZ] = 0; LOC[NZ] = 0; } for(I = 1; I <= M; I++) { NZ = LEN[I]; if(NZ==0) NZEROS++; else NUM[NZ]++; } /* Set starting locations for each length. */ L = NZEROS+1; for(NZ = 1; NZ <= N; NZ++) { LOC[NZ] = L; L += NUM[NZ]; NUM[NZ] = 0; } /* Form the list. */ NZEROS = 0; for(I = 1; I <= M; I++) { NZ = LEN[I]; if(NZ==0) { NZEROS++; IPERM[NZEROS] = I; } else { L = LOC[NZ]+NUM[NZ]; IPERM[L] = I; NUM[NZ]++; } } /* Define the inverse of iperm. */ for(L = 1; L <= M; L++) { I = IPERM[L]; INV[I] = L; } } /* ================================================================== lu1pq2 frees the space occupied by the pivot row, and updates the column permutation iq. Also used to free the pivot column and update the row perm ip. ------------------------------------------------------------------ nzpiv (input) is the length of the pivot row (or column). nzchng (output) is the net change in total nonzeros. ------------------------------------------------------------------ 14 Apr 1989 First version. ================================================================== */ void LU1PQ2(LUSOLrec *LUSOL, int NZPIV, int *NZCHNG, int IND[], int LENOLD[], int LENNEW[], int IXLOC[], int IX[], int IXINV[]) { int LR, J, NZ, NZNEW, L, NEXT, LNEW, JNEW; *NZCHNG = 0; for(LR = 1; LR <= NZPIV; LR++) { J = IND[LR]; IND[LR] = 0; NZ = LENOLD[LR]; NZNEW = LENNEW[J]; if(NZ!=NZNEW) { L = IXINV[J]; *NZCHNG = (*NZCHNG+NZNEW)-NZ; /* l above is the position of column j in iq (so j = iq(l)). */ if(NZNZNEW) goto x120; } IX[LNEW] = J; IXINV[J] = LNEW; } } } /* ================================================================== lu1pq3 looks at the permutation iperm(*) and moves any entries to the end whose corresponding length len(*) is zero. ------------------------------------------------------------------ 09 Feb 1994: Added work array iw(*) to improve efficiency. ================================================================== */ void LU1PQ3(LUSOLrec *LUSOL, int MN, int LEN[], int IPERM[], int IW[], int *NRANK) { int NZEROS, K, I; *NRANK = 0; NZEROS = 0; for(K = 1; K <= MN; K++) { I = IPERM[K]; if(LEN[I]==0) { NZEROS++; IW[NZEROS] = I; } else { (*NRANK)++; IPERM[*NRANK] = I; } } for(K = 1; K <= NZEROS; K++) IPERM[(*NRANK)+K] = IW[K]; } /* ================================================================== lu1rec ------------------------------------------------------------------ On exit: ltop is the length of useful entries in ind(*), a(*). ind(ltop+1) is "i" such that len(i), loc(i) belong to the last item in ind(*), a(*). ------------------------------------------------------------------ 00 Jun 1983: Original version of lu1rec followed John Reid's compression routine in LA05. It recovered space in ind(*) and optionally a(*) by eliminating entries with ind(l) = 0. The elements of ind(*) could not be negative. If len(i) was positive, entry i contained that many elements, starting at loc(i). Otherwise, entry i was eliminated. 23 Mar 2001: Realised we could have len(i) = 0 in rare cases! (Mostly during TCP when the pivot row contains a column of length 1 that couldn't be a pivot.) Revised storage scheme to keep entries with ind(l) > 0, squeeze out entries with -n <= ind(l) <= 0, and to allow len(i) = 0. Empty items are moved to the end of the compressed ind(*) and/or a(*) arrays are given one empty space. Items with len(i) < 0 are still eliminated. 27 Mar 2001: Decided to use only ind(l) > 0 and = 0 in lu1fad. Still have to keep entries with len(i) = 0. ================================================================== */ void LU1REC(LUSOLrec *LUSOL, int N, MYBOOL REALS, int *LTOP, int IND[], int LEN[], int LOC[]) { int NEMPTY, I, LENI, L, LEND, K, KLAST, ILAST, LPRINT; NEMPTY = 0; for(I = 1; I <= N; I++) { LENI = LEN[I]; if(LENI>0) { L = (LOC[I]+LENI)-1; LEN[I] = IND[L]; IND[L] = -(N+I); } else if(LENI==0) NEMPTY++; } K = 0; /* Previous k */ KLAST = 0; /* Last entry moved. */ ILAST = 0; LEND = *LTOP; for(L = 1; L <= LEND; L++) { I = IND[L]; if(I>0) { K++; IND[K] = I; if(REALS) LUSOL->a[K] = LUSOL->a[L]; } else if(I<-N) { /* This is the end of entry i. */ I = -(N+I); ILAST = I; K++; IND[K] = LEN[I]; if(REALS) LUSOL->a[K] = LUSOL->a[L]; LOC[I] = KLAST+1; LEN[I] = K-KLAST; KLAST = K; } } /* Move any empty items to the end, adding 1 free entry for each. */ if(NEMPTY>0) { for(I = 1; I <= N; I++) { if(LEN[I]==0) { K++; LOC[I] = K; IND[K] = 0; ILAST = I; } } } LPRINT = LUSOL->luparm[LUSOL_IP_PRINTLEVEL]; if(LPRINT>=LUSOL_MSG_PIVOT) LUSOL_report(LUSOL, 0, "lu1rec. File compressed from %d to %d\n", *LTOP,K,REALS,NEMPTY); /* ncp */ LUSOL->luparm[LUSOL_IP_COMPRESSIONS_LU]++; /* Return ilast in ind(ltop + 1). */ *LTOP = K; IND[(*LTOP)+1] = ILAST; } /* ================================================================== lu1slk sets w(j) > 0 if column j is a unit vector. ------------------------------------------------------------------ 21 Nov 2000: First version. lu1fad needs it for TCP. Note that w(*) is nominally an integer array, but the only spare space is the double array w(*). ================================================================== */ void LU1SLK(LUSOLrec *LUSOL) { int J, LC1, LQ, LQ1, LQ2; for(J = 1; J <= LUSOL->n; J++) { LUSOL->w[J] = 0; } LQ1 = (LUSOL->iqloc ? LUSOL->iqloc[1] : LUSOL->n+1); /* LQ1 = LUSOL->iqloc[1]; This is the original version; correction above by Yin Zhang */ LQ2 = LUSOL->n; if(LUSOL->m>1) LQ2 = LUSOL->iqloc[2]-1; for(LQ = LQ1; LQ <= LQ2; LQ++) { J = LUSOL->iq[LQ]; LC1 = LUSOL->locc[J]; if(fabs(LUSOL->a[LC1])==1) { LUSOL->w[J] = 1; } } } /* ================================================================== lu1gau does most of the work for each step of Gaussian elimination. A multiple of the pivot column is added to each other column j in the pivot row. The column list is fully updated. The row list is updated if there is room, but some fill-ins may remain, as indicated by ifill and jfill. ------------------------------------------------------------------ Input: ilast is the row at the end of the row list. jlast is the column at the end of the column list. lfirst is the first column to be processed. lu + 1 is the corresponding element of U in au(*). nfill keeps track of pending fill-in. a(*) contains the nonzeros for each column j. indc(*) contains the row indices for each column j. al(*) contains the new column of L. A multiple of it is used to modify each column. mark(*) has been set to -1, -2, -3, ... in the rows corresponding to nonzero 1, 2, 3, ... of the col of L. au(*) contains the new row of U. Each nonzero gives the required multiple of the column of L. Workspace: markl(*) marks the nonzeros of L actually used. (A different mark, namely j, is used for each column.) Output: ilast New last row in the row list. jlast New last column in the column list. lfirst = 0 if all columns were completed, > 0 otherwise. lu returns the position of the last nonzero of U actually used, in case we come back in again. nfill keeps track of the total extra space needed in the row file. ifill(ll) counts pending fill-in for rows involved in the new column of L. jfill(lu) marks the first pending fill-in stored in columns involved in the new row of U. ------------------------------------------------------------------ 16 Apr 1989: First version of lu1gau. 23 Apr 1989: lfirst, lu, nfill are now input and output to allow re-entry if elimination is interrupted. 23 Mar 2001: Introduced ilast, jlast. 27 Mar 2001: Allow fill-in "in situ" if there is already room up to but NOT INCLUDING the end of the row or column file. Seems safe way to avoid overwriting empty rows/cols at the end. (May not be needed though, now that we have ilast and jlast.) ================================================================== */ void LU1GAU(LUSOLrec *LUSOL, int MELIM, int NSPARE, REAL SMALL, int LPIVC1, int LPIVC2, int *LFIRST, int LPIVR2, int LFREE, int MINFRE, int ILAST, int *JLAST, int *LROW, int *LCOL, int *LU, int *NFILL, int MARK[], REAL AL[], int MARKL[], REAL AU[], int IFILL[], int JFILL[]) { MYBOOL ATEND; int LR, J, LENJ, NFREE, LC1, LC2, NDONE, NDROP, L, I, LL, K, LR1, LAST, LREP, L1, L2, LC, LENI; register REAL UJ; REAL AIJ; for(LR = *LFIRST; LR <= LPIVR2; LR++) { J = LUSOL->indr[LR]; LENJ = LUSOL->lenc[J]; NFREE = LFREE - *LCOL; if(NFREElocc[J]; LC2 = (LC1+LENJ)-1; ATEND = (MYBOOL) (J==*JLAST); NDONE = 0; if(LENJ==0) goto x500; NDROP = 0; for(L = LC1; L <= LC2; L++) { I = LUSOL->indc[L]; LL = -MARK[I]; if(LL>0) { NDONE++; MARKL[LL] = J; LUSOL->a[L] += AL[LL]*UJ; if(fabs(LUSOL->a[L])<=SMALL) { NDROP++; } } } /* --------------------------------------------------------------- Remove any negligible modified nonzeros from both the column file and the row file. --------------------------------------------------------------- */ if(NDROP==0) goto x500; K = LC1; for(L = LC1; L <= LC2; L++) { I = LUSOL->indc[L]; if(fabs(LUSOL->a[L])<=SMALL) goto x460; LUSOL->a[K] = LUSOL->a[L]; LUSOL->indc[K] = I; K++; continue; /* Delete the nonzero from the row file. */ x460: LENJ--; LUSOL->lenr[I]--; LR1 = LUSOL->locr[I]; LAST = LR1+LUSOL->lenr[I]; for(LREP = LR1; LREP <= LAST; LREP++) { if(LUSOL->indr[LREP]==J) break; } LUSOL->indr[LREP] = LUSOL->indr[LAST]; LUSOL->indr[LAST] = 0; if(I==ILAST) (*LROW)--; } /* Free the deleted elements from the column file. */ #ifdef LUSOLFastClear MEMCLEAR(LUSOL->indc+K, LC2-K+1); #else for(L = K; L <= LC2; L++) LUSOL->indc[L] = ZERO; #endif if(ATEND) *LCOL = K-1; /* --------------------------------------------------------------- Deal with the fill-in in column j. --------------------------------------------------------------- */ x500: if(NDONE==MELIM) goto x590; /* See if column j already has room for the fill-in. */ if(ATEND) goto x540; LAST = (LC1+LENJ)-1; L1 = LAST+1; L2 = (LAST+MELIM)-NDONE; /* 27 Mar 2001: Be sure it's not at or past end of the col file. */ if(L2>=*LCOL) goto x520; for(L = L1; L <= L2; L++) { if(LUSOL->indc[L]!=0) goto x520; } goto x540; /* We must move column j to the end of the column file. First, leave some spare room at the end of the current last column. */ x520: #if 1 L1 = (*LCOL)+1; L2 = (*LCOL)+NSPARE; *LCOL = L2; for(L = L1; L <= L2; L++) { #else for(L = (*LCOL)+1; L <= (*LCOL)+NSPARE; L++) { *LCOL = L; /* ****** ERROR ???? */ #endif /* Spare space is free. */ LUSOL->indc[L] = 0; } ATEND = TRUE; *JLAST = J; L1 = LC1; L2 = *LCOL; LC1 = L2+1; LUSOL->locc[J] = LC1; for(L = L1; L <= LAST; L++) { L2++; LUSOL->a[L2] = LUSOL->a[L]; LUSOL->indc[L2] = LUSOL->indc[L]; /* Free space. */ LUSOL->indc[L] = 0; } *LCOL = L2; /* --------------------------------------------------------------- Inner loop for the fill-in in column j. This is usually not very expensive. --------------------------------------------------------------- */ x540: LAST = (LC1+LENJ)-1; LL = 0; for(LC = LPIVC1; LC <= LPIVC2; LC++) { LL++; if(MARKL[LL]==J) continue; AIJ = AL[LL]*UJ; if(fabs(AIJ)<=SMALL) continue; LENJ++; LAST++; LUSOL->a[LAST] = AIJ; I = LUSOL->indc[LC]; LUSOL->indc[LAST] = I; LENI = LUSOL->lenr[I]; /* Add 1 fill-in to row i if there is already room. 27 Mar 2001: Be sure it's not at or past the } of the row file. */ L = LUSOL->locr[I]+LENI; if(L>=*LROW) goto x550; if(LUSOL->indr[L]>0) goto x550; LUSOL->indr[L] = J; LUSOL->lenr[I] = LENI+1; continue; /* Row i does not have room for the fill-in. Increment ifill(ll) to count how often this has happened to row i. Also, add m to the row index indc(last) in column j to mark it as a fill-in that is still pending. If this is the first pending fill-in for row i, nfill includes the current length of row i (since the whole row has to be moved later). If this is the first pending fill-in for column j, jfill(lu) records the current length of column j (to shorten the search for pending fill-ins later). */ x550: if(IFILL[LL]==0) (*NFILL) += LENI+NSPARE; if(JFILL[*LU]==0) JFILL[*LU] = LENJ; (*NFILL)++; IFILL[LL]++; LUSOL->indc[LAST] = LUSOL->m+I; } if(ATEND) *LCOL = LAST; /* End loop for column j. Store its final length. */ x590: LUSOL->lenc[J] = LENJ; } /* Successful completion. */ *LFIRST = 0; return; /* Interruption. We have to come back in after the column file is compressed. Give lfirst a new value. lu and nfill will retain their current values. */ x900: *LFIRST = LR; } /* ================================================================== lu1mar uses a Markowitz criterion to select a pivot element for the next stage of a sparse LU factorization, subject to a Threshold Partial Pivoting stability criterion (TPP) that bounds the elements of L. ------------------------------------------------------------------ gamma is "gamma" in the tie-breaking rule TB4 in the LUSOL paper. ------------------------------------------------------------------ Search cols of length nz = 1, then rows of length nz = 1, then cols of length nz = 2, then rows of length nz = 2, etc. ------------------------------------------------------------------ 00 Jan 1986 Version documented in LUSOL paper: Gill, Murray, Saunders and Wright (1987), Maintaining LU factors of a general sparse matrix, Linear algebra and its applications 88/89, 239-270. 02 Feb 1989 Following Suhl and Aittoniemi (1987), the largest element in each column is now kept at the start of the column, i.e. in position locc(j) of a and indc. This should speed up the Markowitz searches. 26 Apr 1989 Both columns and rows searched during spars1 phase. Only columns searched during spars2 phase. maxtie replaced by maxcol and maxrow. 05 Nov 1993 Initializing "mbest = m * n" wasn't big enough when m = 10, n = 3, and last column had 7 nonzeros. 09 Feb 1994 Realised that "mbest = maxmn * maxmn" might overflow. Changed to "mbest = maxmn * 1000". 27 Apr 2000 On large example from Todd Munson, that allowed "if (mbest .le. nz1**2) go to 900" to exit before any pivot had been found. Introduced kbest = mbest / nz1. Most pivots can be rejected with no integer multiply. TRUE merit is evaluated only if it's as good as the best so far (or better). There should be no danger of integer overflow unless A is incredibly large and dense. 10 Sep 2000 TCP, aijtol added for Threshold Complete Pivoting. ================================================================== */ void LU1MAR(LUSOLrec *LUSOL, int MAXMN, MYBOOL TCP, REAL AIJTOL, REAL LTOL, int MAXCOL, int MAXROW, int *IBEST, int *JBEST, int *MBEST) { int KBEST, NCOL, NROW, NZ1, NZ, LQ1, LQ2, LQ, J, LC1, LC2, LC, I, LEN1, MERIT, LP1, LP2, LP, LR1, LR2, LR; REAL ABEST, LBEST, AMAX, AIJ, CMAX; ABEST = ZERO; LBEST = ZERO; *IBEST = 0; *MBEST = -1; KBEST = MAXMN+1; NCOL = 0; NROW = 0; NZ1 = 0; for(NZ = 1; NZ <= MAXMN; NZ++) { /* nz1 = nz - 1 if (mbest .le. nz1**2) go to 900 */ if(KBEST<=NZ1) goto x900; if(*IBEST>0) { if(NCOL>=MAXCOL) goto x200; } if(NZ>LUSOL->m) goto x200; /* --------------------------------------------------------------- Search the set of columns of length nz. --------------------------------------------------------------- */ LQ1 = LUSOL->iqloc[NZ]; LQ2 = LUSOL->n; if(NZm) LQ2 = LUSOL->iqloc[NZ+1]-1; for(LQ = LQ1; LQ <= LQ2; LQ++) { NCOL = NCOL+1; J = LUSOL->iq[LQ]; LC1 = LUSOL->locc[J]; LC2 = LC1+NZ1; AMAX = fabs(LUSOL->a[LC1]); /* Test all aijs in this column. amax is the largest element (the first in the column). cmax is the largest multiplier if aij becomes pivot. */ if(TCP) { /* Nothing in whole column */ if(AMAXindc[LC]; LEN1 = LUSOL->lenr[I]-1; /* merit = nz1 * len1 if (merit > mbest) continue; */ if(LEN1>KBEST) continue; /* aij has a promising merit. Apply the stability test. We require aij to be sufficiently large compared to all other nonzeros in column j. This is equivalent to requiring cmax to be bounded by Ltol. */ if(LC==LC1) { /* This is the maximum element, amax. Find the biggest element in the rest of the column and hence get cmax. We know cmax .le. 1, but we still want it exactly in order to break ties. 27 Apr 2002: Settle for cmax = 1. */ AIJ = AMAX; CMAX = ONE; /* cmax = zero for (l = lc1 + 1; l <= lc2; l++) cmax = max( cmax, abs( a(l) ) ); cmax = cmax / amax; */ } else { /* aij is not the biggest element, so cmax .ge. 1. Bail out if cmax will be too big. */ AIJ = fabs(LUSOL->a[LC]); /* Absolute test for Complete Pivoting */ if(TCP) { if(AIJparmlu[LUSOL_RP_GAMMA] && CMAX<=LUSOL->parmlu[LUSOL_RP_GAMMA]) { if(ABEST>=AIJ) continue; } else { if(LBEST<=CMAX) continue; } } /* aij is the best pivot so far. */ *IBEST = I; *JBEST = J; KBEST = LEN1; *MBEST = MERIT; ABEST = AIJ; LBEST = CMAX; if(NZ==1) goto x900; } /* Finished with that column. */ if(*IBEST>0) { if(NCOL>=MAXCOL) goto x200; } } /* --------------------------------------------------------------- Search the set of rows of length nz. --------------------------------------------------------------- */ x200: /* if (mbest .le. nz*nz1) go to 900 */ if(KBEST<=NZ) goto x900; if(*IBEST>0) { if(NROW>=MAXROW) goto x290; } if(NZ>LUSOL->n) goto x290; LP1 = LUSOL->iploc[NZ]; LP2 = LUSOL->m; if(NZn) LP2 = LUSOL->iploc[NZ+1]-1; for(LP = LP1; LP <= LP2; LP++) { NROW++; I = LUSOL->ip[LP]; LR1 = LUSOL->locr[I]; LR2 = LR1+NZ1; for(LR = LR1; LR <= LR2; LR++) { J = LUSOL->indr[LR]; LEN1 = LUSOL->lenc[J]-1; /* merit = nz1 * len1 if (merit .gt. mbest) continue */ if(LEN1>KBEST) continue; /* aij has a promising merit. Find where aij is in column j. */ LC1 = LUSOL->locc[J]; LC2 = LC1+LEN1; AMAX = fabs(LUSOL->a[LC1]); for(LC = LC1; LC <= LC2; LC++) { if(LUSOL->indc[LC]==I) break; } /* Apply the same stability test as above. */ AIJ = fabs(LUSOL->a[LC]); /* Absolute test for Complete Pivoting */ if(TCP) { if(AIJparmlu[LUSOL_RP_GAMMA] && CMAX<=LUSOL->parmlu[LUSOL_RP_GAMMA]) { if(ABEST>=AIJ) continue; } else { if(LBEST<=CMAX) continue; } } /* aij is the best pivot so far. */ *IBEST = I; *JBEST = J; *MBEST = MERIT; KBEST = LEN1; ABEST = AIJ; LBEST = CMAX; if(NZ==1) goto x900; } /* Finished with that row. */ if(*IBEST>0) { if(NROW>=MAXROW) goto x290; } } /* See if it's time to quit. */ x290: if(*IBEST>0) { if(NROW>=MAXROW && NCOL>=MAXCOL) goto x900; } /* Press on with next nz. */ NZ1 = NZ; if(*IBEST>0) KBEST = *MBEST/NZ1; } x900: ; } /* ================================================================== lu1mCP uses a Markowitz criterion to select a pivot element for the next stage of a sparse LU factorization, subject to a Threshold Complete Pivoting stability criterion (TCP) that bounds the elements of L and U. ------------------------------------------------------------------ gamma is "gamma" in the tie-breaking rule TB4 in the LUSOL paper. ------------------------------------------------------------------ 09 May 2002: First version of lu1mCP. It searches columns only, using the heap that holds the largest element in each column. 09 May 2002: Current version of lu1mCP. ================================================================== */ void LU1MCP(LUSOLrec *LUSOL, REAL AIJTOL, int *IBEST, int *JBEST, int *MBEST, int HLEN, REAL HA[], int HJ[]) { int J, KHEAP, LC, LC1, LC2, LENJ, MAXCOL, NCOL, NZ1, I, LEN1, MERIT; REAL ABEST, AIJ, AMAX, CMAX, LBEST; /* ------------------------------------------------------------------ Search up to maxcol columns stored at the top of the heap. The very top column helps initialize mbest. ------------------------------------------------------------------ */ ABEST = ZERO; LBEST = ZERO; *IBEST = 0; /* Column at the top of the heap */ *JBEST = HJ[1]; LENJ = LUSOL->lenc[*JBEST]; /* Bigger than any possible merit */ *MBEST = LENJ*HLEN; /* ??? Big question */ MAXCOL = 40; /* No. of columns searched */ NCOL = 0; for(KHEAP = 1; KHEAP <= HLEN; KHEAP++) { AMAX = HA[KHEAP]; if(AMAXlenc[J]; NZ1 = LENJ-1; LC1 = LUSOL->locc[J]; LC2 = LC1+NZ1; /* -- amax = abs( a(lc1) ) Test all aijs in this column. amax is the largest element (the first in the column). cmax is the largest multiplier if aij becomes pivot. */ for(LC = LC1; LC <= LC2; LC++) { I = LUSOL->indc[LC]; LEN1 = LUSOL->lenr[I]-1; MERIT = NZ1*LEN1; if(MERIT>*MBEST) continue; /* aij has a promising merit. */ if(LC==LC1) { /* This is the maximum element, amax. Find the biggest element in the rest of the column and hence get cmax. We know cmax .le. 1, but we still want it exactly in order to break ties. 27 Apr 2002: Settle for cmax = 1. */ AIJ = AMAX; CMAX = ONE; /* cmax = ZERO; for(l = lc1 + 1; l <= lc2; l++) cmax = max( cmax, abs( a(l) ) ) cmax = cmax / amax; */ } else { /* aij is not the biggest element, so cmax .ge. 1. Bail out if cmax will be too big. */ AIJ = fabs(LUSOL->a[LC]); if(AIJparmlu[LUSOL_RP_GAMMA] && CMAX<=LUSOL->parmlu[LUSOL_RP_GAMMA]) { if(ABEST>=AIJ) continue; } else { if(LBEST<=CMAX) continue; } } /* aij is the best pivot so far. */ *IBEST = I; *JBEST = J; *MBEST = MERIT; ABEST = AIJ; LBEST = CMAX; /* Col or row of length 1 */ if(MERIT==0) goto x900; } if(NCOL>=MAXCOL) goto x900; } x900: ; } /* ================================================================== lu1mRP uses a Markowitz criterion to select a pivot element for the next stage of a sparse LU factorization, subject to a Threshold Rook Pivoting stability criterion (TRP) that bounds the elements of L and U. ------------------------------------------------------------------ 11 Jun 2002: First version of lu1mRP derived from lu1mar. 11 Jun 2002: Current version of lu1mRP. ================================================================== */ void LU1MRP(LUSOLrec *LUSOL, int MAXMN, REAL LTOL, int MAXCOL, int MAXROW, int *IBEST, int *JBEST, int *MBEST, REAL AMAXR[]) { int I, J, KBEST, LC, LC1, LC2, LEN1, LP, LP1, LP2, LQ, LQ1, LQ2, LR, LR1, LR2, MERIT, NCOL, NROW, NZ, NZ1; REAL ABEST, AIJ, AMAX, ATOLI, ATOLJ; /* ------------------------------------------------------------------ Search cols of length nz = 1, then rows of length nz = 1, then cols of length nz = 2, then rows of length nz = 2, etc. ------------------------------------------------------------------ */ ABEST = ZERO; *IBEST = 0; KBEST = MAXMN+1; *MBEST = -1; NCOL = 0; NROW = 0; NZ1 = 0; for(NZ = 1; NZ <= MAXMN; NZ++) { /* nz1 = nz - 1 if (mbest .le. nz1**2) go to 900 */ if(KBEST<=NZ1) goto x900; if(*IBEST>0) { if(NCOL>=MAXCOL) goto x200; } if(NZ>LUSOL->m) goto x200; /* --------------------------------------------------------------- Search the set of columns of length nz. --------------------------------------------------------------- */ LQ1 = LUSOL->iqloc[NZ]; LQ2 = LUSOL->n; if(NZm) LQ2 = LUSOL->iqloc[NZ+1]-1; for(LQ = LQ1; LQ <= LQ2; LQ++) { NCOL = NCOL+1; J = LUSOL->iq[LQ]; LC1 = LUSOL->locc[J]; LC2 = LC1+NZ1; AMAX = fabs(LUSOL->a[LC1]); /* Min size of pivots in col j */ ATOLJ = AMAX/LTOL; /* Test all aijs in this column. */ for(LC = LC1; LC <= LC2; LC++) { I = LUSOL->indc[LC]; LEN1 = LUSOL->lenr[I]-1; /* merit = nz1 * len1 if (merit .gt. mbest) continue; */ if(LEN1>KBEST) continue; /* aij has a promising merit. Apply the Threshold Rook Pivoting stability test. First we require aij to be sufficiently large compared to other nonzeros in column j. Then we require aij to be sufficiently large compared to other nonzeros in row i. */ AIJ = fabs(LUSOL->a[LC]); if(AIJ=AIJ) continue; } /* aij is the best pivot so far. */ *IBEST = I; *JBEST = J; KBEST = LEN1; *MBEST = MERIT; ABEST = AIJ; if(NZ==1) goto x900; } /* Finished with that column. */ if(*IBEST>0) { if(NCOL>=MAXCOL) goto x200; } } /* --------------------------------------------------------------- Search the set of rows of length nz. --------------------------------------------------------------- */ x200: /* if (mbest .le. nz*nz1) go to 900 */ if(KBEST<=NZ) goto x900; if(*IBEST>0) { if(NROW>=MAXROW) goto x290; } if(NZ>LUSOL->n) goto x290; LP1 = LUSOL->iploc[NZ]; LP2 = LUSOL->m; if(NZn) LP2 = LUSOL->iploc[NZ+1]-1; for(LP = LP1; LP <= LP2; LP++) { NROW = NROW+1; I = LUSOL->ip[LP]; LR1 = LUSOL->locr[I]; LR2 = LR1+NZ1; /* Min size of pivots in row i */ ATOLI = AMAXR[I]/LTOL; for(LR = LR1; LR <= LR2; LR++) { J = LUSOL->indr[LR]; LEN1 = LUSOL->lenc[J]-1; /* merit = nz1 * len1 if (merit .gt. mbest) continue; */ if(LEN1>KBEST) continue; /* aij has a promising merit. Find where aij is in column j. */ LC1 = LUSOL->locc[J]; LC2 = LC1+LEN1; AMAX = fabs(LUSOL->a[LC1]); for(LC = LC1; LC <= LC2; LC++) { if(LUSOL->indc[LC]==I) break; } /* Apply the Threshold Rook Pivoting stability test. First we require aij to be sufficiently large compared to other nonzeros in row i. Then we require aij to be sufficiently large compared to other nonzeros in column j. */ AIJ = fabs(LUSOL->a[LC]); if(AIJ=AIJ) continue; } /* aij is the best pivot so far. */ *IBEST = I; *JBEST = J; KBEST = LEN1; *MBEST = MERIT; ABEST = AIJ; if(NZ==1) goto x900; } /* Finished with that row. */ if(*IBEST>0) { if(NROW>=MAXROW) goto x290; } } /* See if it's time to quit. */ x290: if(*IBEST>0) { if(NROW>=MAXROW && NCOL>=MAXCOL) goto x900; } /* Press on with next nz. */ NZ1 = NZ; if(*IBEST>0) KBEST = *MBEST/NZ1; } x900: ; } /* ================================================================== lu1mSP is intended for symmetric matrices that are either definite or quasi-definite. lu1mSP uses a Markowitz criterion to select a pivot element for the next stage of a sparse LU factorization of a symmetric matrix, subject to a Threshold Symmetric Pivoting stability criterion (TSP) restricted to diagonal elements to preserve symmetry. This bounds the elements of L and U and should have rank-revealing properties analogous to Threshold Rook Pivoting for unsymmetric matrices. ------------------------------------------------------------------ 14 Dec 2002: First version of lu1mSP derived from lu1mRP. There is no safeguard to ensure that A is symmetric. 14 Dec 2002: Current version of lu1mSP. ================================================================== */ void LU1MSP(LUSOLrec *LUSOL, int MAXMN, REAL LTOL, int MAXCOL, int *IBEST, int *JBEST, int *MBEST) { int I, J, KBEST, LC, LC1, LC2, LQ, LQ1, LQ2, MERIT, NCOL, NZ, NZ1; REAL ABEST, AIJ, AMAX, ATOLJ; /* ------------------------------------------------------------------ Search cols of length nz = 1, then cols of length nz = 2, etc. ------------------------------------------------------------------ */ ABEST = ZERO; *IBEST = 0; *MBEST = -1; KBEST = MAXMN+1; NCOL = 0; NZ1 = 0; for(NZ = 1; NZ <= MAXMN; NZ++) { /* nz1 = nz - 1 if (mbest .le. nz1**2) go to 900 */ if(KBEST<=NZ1) goto x900; if(*IBEST>0) { if(NCOL>=MAXCOL) goto x200; } if(NZ>LUSOL->m) goto x200; /* --------------------------------------------------------------- Search the set of columns of length nz. --------------------------------------------------------------- */ LQ1 = LUSOL->iqloc[NZ]; LQ2 = LUSOL->n; if(NZm) LQ2 = LUSOL->iqloc[NZ+1]-1; for(LQ = LQ1; LQ <= LQ2; LQ++) { NCOL++; J = LUSOL->iq[LQ]; LC1 = LUSOL->locc[J]; LC2 = LC1+NZ1; AMAX = fabs(LUSOL->a[LC1]); /* Min size of pivots in col j */ ATOLJ = AMAX/LTOL; /* Test all aijs in this column. Ignore everything except the diagonal. */ for(LC = LC1; LC <= LC2; LC++) { I = LUSOL->indc[LC]; /* Skip off-diagonals. */ if(I!=J) continue; /* merit = nz1 * nz1 if (merit .gt. mbest) continue; */ if(NZ1>KBEST) continue; /* aij has a promising merit. Apply the Threshold Partial Pivoting stability test (which is equivalent to Threshold Rook Pivoting for symmetric matrices). We require aij to be sufficiently large compared to other nonzeros in column j. */ AIJ = fabs(LUSOL->a[LC]); if(AIJ=AIJ) continue; } /* aij is the best pivot so far. */ *IBEST = I; *JBEST = J; KBEST = NZ1; *MBEST = MERIT; ABEST = AIJ; if(NZ==1) goto x900; } /* Finished with that column. */ if(*IBEST>0) { if(NCOL>=MAXCOL) goto x200; } } /* See if it's time to quit. */ x200: if(*IBEST>0) { if(NCOL>=MAXCOL) goto x900; } /* Press on with next nz. */ NZ1 = NZ; if(*IBEST>0) KBEST = *MBEST/NZ1; } x900: ; } /* ================================================================== lu1mxc moves the largest element in each of columns iq(k1:k2) to the top of its column. If k1 > k2, nothing happens. ------------------------------------------------------------------ 06 May 2002: (and earlier) All columns k1:k2 must have one or more elements. 07 May 2002: Allow for empty columns. The heap routines need to find 0.0 as the "largest element". 29 Nov 2005: Bug fix - avoiding overwriting the next column when the current column is empty (i.e. LENJ==0) Yin Zhang ================================================================== */ void LU1MXC(LUSOLrec *LUSOL, int K1, int K2, int IX[]) { int I, J, K, L, LC, LENJ; REAL AMAX; for(K = K1; K <= K2; K++) { J = IX[K]; LC = LUSOL->locc[J]; LENJ = LUSOL->lenc[J]; if(LENJ==0) /* LUSOL->a[LC] = ZERO; Removal suggested by Yin Zhang to avoid overwriting next column when current is empty */ ; else { L = idamax(LUSOL->lenc[J], LUSOL->a + LC - LUSOL_ARRAYOFFSET,1) + LC - 1; if(L>LC) { AMAX = LUSOL->a[L]; LUSOL->a[L] = LUSOL->a[LC]; LUSOL->a[LC] = AMAX; I = LUSOL->indc[L]; LUSOL->indc[L] = LUSOL->indc[LC]; LUSOL->indc[LC] = I; } } } } /* ================================================================== lu1mxr finds the largest element in each of row ip(k1:k2) and stores it in Amaxr(*). The nonzeros are stored column-wise in (a,indc,lenc,locc) and their structure is row-wise in ( indr,lenr,locr). If k1 > k2, nothing happens. ------------------------------------------------------------------ 11 Jun 2002: First version of lu1mxr. Allow for empty columns. ================================================================== */ void LU1MXR(LUSOLrec *LUSOL, int K1, int K2, int IX[], REAL AMAXR[]) { #define FastMXR #ifdef FastMXR static int I, *J, *IC, K, LC, LC1, LC2, LR, LR1, LR2; static REAL AMAX; #else int I, J, K, LC, LC1, LC2, LR, LR1, LR2; REAL AMAX; #endif for(K = K1; K <= K2; K++) { AMAX = ZERO; I = IX[K]; /* Find largest element in row i. */ LR1 = LUSOL->locr[I]; LR2 = (LR1+LUSOL->lenr[I])-1; #ifdef FastMXR for(LR = LR1, J = LUSOL->indr + LR1; LR <= LR2; LR++, J++) { /* Find where aij is in column j. */ LC1 = LUSOL->locc[*J]; LC2 = LC1+LUSOL->lenc[*J]; for(LC = LC1, IC = LUSOL->indc + LC1; LC < LC2; LC++, IC++) { if(*IC==I) break; } SETMAX(AMAX,fabs(LUSOL->a[LC])); } #else for(LR = LR1; LR <= LR2; LR++) { J = LUSOL->indr[LR]; /* Find where aij is in column j. */ LC1 = LUSOL->locc[J]; LC2 = (LC1+LUSOL->lenc[J])-1; for(LC = LC1; LC <= LC2; LC++) { if(LUSOL->indc[LC]==I) break; } SETMAX(AMAX,fabs(LUSOL->a[LC])); } #endif AMAXR[I] = AMAX; } } /* ================================================================== lu1ful computes a dense (full) LU factorization of the mleft by nleft matrix that remains to be factored at the beginning of the nrowu-th pass through the main loop of lu1fad. ------------------------------------------------------------------ 02 May 1989: First version. 05 Feb 1994: Column interchanges added to lu1DPP. 08 Feb 1994: ipinv reconstructed, since lu1pq3 may alter ip. ================================================================== */ void LU1FUL(LUSOLrec *LUSOL, int LEND, int LU1, MYBOOL TPP, int MLEFT, int NLEFT, int NRANK, int NROWU, int *LENL, int *LENU, int *NSING, MYBOOL KEEPLU, REAL SMALL, REAL D[], int IPVT[]) { int L, I, J, IPBASE, LDBASE, LQ, LC1, LC2, LC, LD, LKK, LKN, LU, K, L1, L2, IBEST, JBEST, LA, LL, NROWD, NCOLD; REAL AI, AJ; /* ------------------------------------------------------------------ If lu1pq3 moved any empty rows, reset ipinv = inverse of ip. ------------------------------------------------------------------ */ if(NRANKm) { for(L = 1; L <= LUSOL->m; L++) { I = LUSOL->ip[L]; LUSOL->ipinv[I] = L; } } /* ------------------------------------------------------------------ Copy the remaining matrix into the dense matrix D. ------------------------------------------------------------------ */ #ifdef LUSOLFastClear MEMCLEAR((D+1), LEND); #else /* dload(LEND, ZERO, D, 1); */ for(J = 1; J <= LEND; J++) D[J] = ZERO; #endif IPBASE = NROWU-1; LDBASE = 1-NROWU; for(LQ = NROWU; LQ <= LUSOL->n; LQ++) { J = LUSOL->iq[LQ]; LC1 = LUSOL->locc[J]; LC2 = (LC1+LUSOL->lenc[J])-1; for(LC = LC1; LC <= LC2; LC++) { I = LUSOL->indc[LC]; LD = LDBASE+LUSOL->ipinv[I]; D[LD] = LUSOL->a[LC]; } LDBASE += MLEFT; } /* ------------------------------------------------------------------ Call our favorite dense LU factorizer. ------------------------------------------------------------------ */ if(TPP) LU1DPP(LUSOL, D,MLEFT,MLEFT,NLEFT,SMALL,NSING,IPVT,LUSOL->iq+NROWU-LUSOL_ARRAYOFFSET); else LU1DCP(LUSOL, D,MLEFT,MLEFT,NLEFT,SMALL,NSING,IPVT,LUSOL->iq+NROWU-LUSOL_ARRAYOFFSET); /* ------------------------------------------------------------------ Move D to the beginning of A, and pack L and U at the top of a, indc, indr. In the process, apply the row permutation to ip. lkk points to the diagonal of U. ------------------------------------------------------------------ */ #ifdef LUSOLFastCopy MEMCOPY(LUSOL->a+1,D+1,LEND); #else dcopy(LEND,D,1,LUSOL->a,1); #endif #ifdef ClassicdiagU LUSOL->diagU = LUSOL->a + (LUSOL->lena-LUSOL->n); #endif LKK = 1; LKN = (LEND-MLEFT)+1; LU = LU1; for(K = 1; K <= MIN(MLEFT,NLEFT); K++) { L1 = IPBASE+K; L2 = IPBASE+IPVT[K]; if(L1!=L2) { I = LUSOL->ip[L1]; LUSOL->ip[L1] = LUSOL->ip[L2]; LUSOL->ip[L2] = I; } IBEST = LUSOL->ip[L1]; JBEST = LUSOL->iq[L1]; if(KEEPLU) { /* =========================================================== Pack the next column of L. =========================================================== */ LA = LKK; LL = LU; NROWD = 1; for(I = K+1; I <= MLEFT; I++) { LA++; AI = LUSOL->a[LA]; if(fabs(AI)>SMALL) { NROWD = NROWD+1; LL--; LUSOL->a[LL] = AI; LUSOL->indc[LL] = LUSOL->ip[IPBASE+I]; LUSOL->indr[LL] = IBEST; } } /* =========================================================== Pack the next row of U. We go backwards through the row of D so the diagonal ends up at the front of the row of U. Beware -- the diagonal may be zero. =========================================================== */ LA = LKN+MLEFT; LU = LL; NCOLD = 0; for(J = NLEFT; J >= K; J--) { LA = LA-MLEFT; AJ = LUSOL->a[LA]; if(fabs(AJ)>SMALL || J==K) { NCOLD++; LU--; LUSOL->a[LU] = AJ; LUSOL->indr[LU] = LUSOL->iq[IPBASE+J]; } } LUSOL->lenr[IBEST] = -NCOLD; LUSOL->lenc[JBEST] = -NROWD; *LENL = ((*LENL)+NROWD)-1; *LENU = (*LENU)+NCOLD; LKN++; } else { /* =========================================================== Store just the diagonal of U, in natural order. =========================================================== */ LUSOL->diagU[JBEST] = LUSOL->a[LKK]; } LKK += MLEFT+1; } } /* ================================================================== lu1or1 organizes the elements of an m by n matrix A as follows. On entry, the parallel arrays a, indc, indr, contain nelem entries of the form aij, i, j, in any order. nelem must be positive. Entries not larger than the input parameter small are treated as zero and removed from a, indc, indr. The remaining entries are defined to be nonzero. numnz returns the number of such nonzeros and Amax returns the magnitude of the largest nonzero. The arrays lenc, lenr return the number of nonzeros in each column and row of A. inform = 0 on exit, except inform = 1 if any of the indices in indc, indr imply that the element aij lies outside the m by n dimensions of A. ------------------------------------------------------------------ xx Feb 1985: Original version. 17 Oct 2000: a, indc, indr now have size lena to allow nelem = 0. ================================================================== */ void LU1OR1(LUSOLrec *LUSOL, REAL SMALL, REAL *AMAX, int *NUMNZ, int *LERR, int *INFORM) { int I, J, L, LDUMMY; #ifdef LUSOLFastClear MEMCLEAR((LUSOL->lenr+1), LUSOL->m); MEMCLEAR((LUSOL->lenc+1), LUSOL->n); #else for(I = 1; I <= LUSOL->m; I++) LUSOL->lenr[I] = ZERO; for(I = 1; I <= LUSOL->n; I++) LUSOL->lenc[I] = ZERO; #endif *AMAX = 0; *NUMNZ = LUSOL->nelem; L = LUSOL->nelem+1; for(LDUMMY = 1; LDUMMY <= LUSOL->nelem; LDUMMY++) { L--; if(fabs(LUSOL->a[L])>SMALL) { I = LUSOL->indc[L]; J = LUSOL->indr[L]; SETMAX(*AMAX,fabs(LUSOL->a[L])); if(I<1 || I>LUSOL->m) goto x910; if(J<1 || J>LUSOL->n) goto x910; LUSOL->lenr[I]++; LUSOL->lenc[J]++; } else { /* Replace a negligible element by last element. Since we are going backwards, we know the last element is ok. */ LUSOL->a[L] = LUSOL->a[*NUMNZ]; LUSOL->indc[L] = LUSOL->indc[*NUMNZ]; LUSOL->indr[L] = LUSOL->indr[*NUMNZ]; (*NUMNZ)--; } } *LERR = 0; *INFORM = LUSOL_INFORM_LUSUCCESS; return; x910: *LERR = L; *INFORM = LUSOL_INFORM_LUSINGULAR; } /* ================================================================== lu1or2 sorts a list of matrix elements a(i,j) into column order, given numa entries a(i,j), i, j in the parallel arrays a, inum, jnum respectively. The matrix is assumed to have n columns and an arbitrary number of rows. On entry, len(*) must contain the length of each column. On exit, a(*) and inum(*) are sorted, jnum(*) = 0, and loc(j) points to the start of column j. lu1or2 is derived from mc20ad, a routine in the Harwell Subroutine Library, author J. K. Reid. ------------------------------------------------------------------ xx Feb 1985: Original version. 17 Oct 2000: a, inum, jnum now have size lena to allow nelem = 0. ================================================================== */ void LU1OR2(LUSOLrec *LUSOL) { REAL ACE, ACEP; int L, J, I, JCE, ICE, ICEP, JCEP, JA, JB; /* Set loc(j) to point to the beginning of column j. */ L = 1; for(J = 1; J <= LUSOL->n; J++) { LUSOL->locc[J] = L; L += LUSOL->lenc[J]; } /* Sort the elements into column order. The algorithm is an in-place sort and is of order numa. */ for(I = 1; I <= LUSOL->nelem; I++) { /* Establish the current entry. */ JCE = LUSOL->indr[I]; if(JCE==0) continue; ACE = LUSOL->a[I]; ICE = LUSOL->indc[I]; LUSOL->indr[I] = 0; /* Chain from current entry. */ for(J = 1; J <= LUSOL->nelem; J++) { /* The current entry is not in the correct position. Determine where to store it. */ L = LUSOL->locc[JCE]; LUSOL->locc[JCE]++; /* Save the contents of that location. */ ACEP = LUSOL->a[L]; ICEP = LUSOL->indc[L]; JCEP = LUSOL->indr[L]; /* Store current entry. */ LUSOL->a[L] = ACE; LUSOL->indc[L] = ICE; LUSOL->indr[L] = 0; /* If next current entry needs to be processed, copy it into current entry. */ if(JCEP==0) break; ACE = ACEP; ICE = ICEP; JCE = JCEP; } } /* Reset loc(j) to point to the start of column j. */ JA = 1; for(J = 1; J <= LUSOL->n; J++) { JB = LUSOL->locc[J]; LUSOL->locc[J] = JA; JA = JB; } } /* ================================================================== lu1or3 looks for duplicate elements in an m by n matrix A defined by the column list indc, lenc, locc. iw is used as a work vector of length m. ------------------------------------------------------------------ xx Feb 1985: Original version. 17 Oct 2000: indc, indr now have size lena to allow nelem = 0. ================================================================== */ void LU1OR3(LUSOLrec *LUSOL, int *LERR, int *INFORM) { int I, J, L1, L2, L; #ifdef LUSOLFastClear MEMCLEAR((LUSOL->ip+1), LUSOL->m); #else for(I = 1; I <= LUSOL->m; I++) LUSOL->ip[I] = ZERO; #endif for(J = 1; J <= LUSOL->n; J++) { if(LUSOL->lenc[J]>0) { L1 = LUSOL->locc[J]; L2 = (L1+LUSOL->lenc[J])-1; for(L = L1; L <= L2; L++) { I = LUSOL->indc[L]; if(LUSOL->ip[I]==J) goto x910; LUSOL->ip[I] = J; } } } *INFORM = LUSOL_INFORM_LUSUCCESS; return; x910: *LERR = L; *INFORM = LUSOL_INFORM_LUSINGULAR; } /* ================================================================== lu1or4 constructs a row list indr, locr from a corresponding column list indc, locc, given the lengths of both columns and rows in lenc, lenr. ------------------------------------------------------------------ xx Feb 1985: Original version. 17 Oct 2000: indc, indr now have size lena to allow nelem = 0. ================================================================== */ void LU1OR4(LUSOLrec *LUSOL) { int L, I, L2, J, JDUMMY, L1, LR; /* Initialize locr(i) to point just beyond where the last component of row i will be stored. */ L = 1; for(I = 1; I <= LUSOL->m; I++) { L += LUSOL->lenr[I]; LUSOL->locr[I] = L; } /* By processing the columns backwards and decreasing locr(i) each time it is accessed, it will end up pointing to the beginning of row i as required. */ L2 = LUSOL->nelem; J = LUSOL->n+1; for(JDUMMY = 1; JDUMMY <= LUSOL->n; JDUMMY++) { J = J-1; if(LUSOL->lenc[J]>0) { L1 = LUSOL->locc[J]; for(L = L1; L <= L2; L++) { I = LUSOL->indc[L]; LR = LUSOL->locr[I]-1; LUSOL->locr[I] = LR; LUSOL->indr[LR] = J; } L2 = L1-1; } } } /* ================================================================== lu1pen deals with pending fill-in in the row file. ------------------------------------------------------------------ ifill(ll) says if a row involved in the new column of L has to be updated. If positive, it is the total length of the final updated row. jfill(lu) says if a column involved in the new row of U contains any pending fill-ins. If positive, it points to the first fill-in in the column that has yet to be added to the row file. ------------------------------------------------------------------ 16 Apr 1989: First version of lu1pen. 23 Mar 2001: ilast used and updated. ================================================================== */ void LU1PEN(LUSOLrec *LUSOL, int NSPARE, int *ILAST, int LPIVC1, int LPIVC2, int LPIVR1, int LPIVR2, int *LROW, int IFILL[], int JFILL[]) { int LL, LC, L, I, LR1, LR2, LR, LU, J, LC1, LC2, LAST; LL = 0; for(LC = LPIVC1; LC <= LPIVC2; LC++) { LL++; if(IFILL[LL]==0) continue; /* Another row has pending fill. First, add some spare space at the } of the current last row. */ #if 1 LC1 = (*LROW)+1; LC2 = (*LROW)+NSPARE; *LROW = LC2; for(L = LC1; L <= LC2; L++) { #else for(L = (*LROW)+1; L <= (*LROW)+NSPARE; L++) { *LROW = L; /* ******* ERROR ???? */ #endif LUSOL->indr[L] = 0; } /* Now move row i to the end of the row file. */ I = LUSOL->indc[LC]; *ILAST = I; LR1 = LUSOL->locr[I]; LR2 = (LR1+LUSOL->lenr[I])-1; LUSOL->locr[I] = (*LROW)+1; for(LR = LR1; LR <= LR2; LR++) { (*LROW)++; LUSOL->indr[*LROW] = LUSOL->indr[LR]; LUSOL->indr[LR] = 0; } (*LROW) += IFILL[LL]; } /* Scan all columns of D and insert the pending fill-in into the row file. */ LU = 1; for(LR = LPIVR1; LR <= LPIVR2; LR++) { LU++; if(JFILL[LU]==0) continue; J = LUSOL->indr[LR]; LC1 = (LUSOL->locc[J]+JFILL[LU])-1; LC2 = (LUSOL->locc[J]+LUSOL->lenc[J])-1; for(LC = LC1; LC <= LC2; LC++) { I = LUSOL->indc[LC]-LUSOL->m; if(I>0) { LUSOL->indc[LC] = I; LAST = LUSOL->locr[I]+LUSOL->lenr[I]; LUSOL->indr[LAST] = J; LUSOL->lenr[I]++; } } } } /* ================================================================== lu1fad is a driver for the numerical phase of lu1fac. At each stage it computes a column of L and a row of U, using a Markowitz criterion to select the pivot element, subject to a stability criterion that bounds the elements of L. ------------------------------------------------------------------ Local variables --------------- lcol is the length of the column file. It points to the last nonzero in the column list. lrow is the analogous quantity for the row file. lfile is the file length (lcol or lrow) after the most recent compression of the column list or row list. nrowd and ncold are the number of rows and columns in the matrix defined by the pivot column and row. They are the dimensions of the submatrix D being altered at this stage. melim and nelim are the number of rows and columns in the same matrix D, excluding the pivot column and row. mleft and nleft are the number of rows and columns still left to be factored. nzchng is the increase in nonzeros in the matrix that remains to be factored after the current elimination (usually negative). nzleft is the number of nonzeros still left to be factored. nspare is the space we leave at the end of the last row or column whenever a row or column is being moved to the } of its file. nspare = 1 or 2 might help reduce the number of file compressions when storage is tight. The row and column ordering permutes A into the form ------------------------ \ | \ U1 | \ | -------------------- |\ | \ | \ P A Q = | \ | \ | -------------- | | | | | | | L1 | A2 | | | | | | | -------------------- where the block A2 is factored as A2 = L2 U2. The phases of the factorization are as follows. Utri is true when U1 is being determined. Any column of length 1 is accepted immediately (if TPP). Ltri is true when L1 is being determined. lu1mar exits as soon as an acceptable pivot is found in a row of length 1. spars1 is true while the density of the (modified) A2 is less than the parameter dens1 = parmlu(7) = 0.3 say. lu1mar searches maxcol columns and maxrow rows, where maxcol = luparm(3), maxrow = maxcol - 1. lu1mxc is used to keep the biggest element at the top of all remaining columns. spars2 is true while the density of the modified A2 is less than the parameter dens2 = parmlu(8) = 0.6 say. lu1mar searches maxcol columns and no rows. lu1mxc could fix up only the first maxcol cols (with TPP). 22 Sep 2000: For simplicity, lu1mxc fixes all modified cols. dense is true once the density of A2 reaches dens2. lu1mar searches only 1 column (the shortest). lu1mxc could fix up only the first column (with TPP). ------------------------------------------------------------------ 00 Jan 1986 Version documented in LUSOL paper: Gill, Murray, Saunders and Wright (1987), Maintaining LU factors of a general sparse matrix, Linear algebra and its applications 88/89, 239-270. 02 Feb 1989 Following Suhl and Aittoniemi (1987), the largest element in each column is now kept at the start of the column, i.e. in position locc(j) of a and indc. This should speed up the Markowitz searches. To save time on highly triangular matrices, we wait until there are no further columns of length 1 before setting and maintaining that property. 12 Apr 1989 ipinv and iqinv added (inverses of ip and iq) to save searching ip and iq for rows and columns altered in each elimination step. (Used in lu1pq2) 19 Apr 1989 Code segmented to reduce its size. lu1gau does most of the Gaussian elimination work. lu1mar does just the Markowitz search. lu1mxc moves biggest elements to top of columns. lu1pen deals with pending fill-in in the row list. lu1pq2 updates the row and column permutations. 26 Apr 1989 maxtie replaced by maxcol, maxrow in the Markowitz search. maxcol, maxrow change as density increases. 25 Oct 1993 keepLU implemented. 07 Feb 1994 Exit main loop early to finish off with a dense LU. densLU tells lu1fad whether to do it. 21 Dec 1994 Bug fixed. nrank was wrong after the call to lu1ful. 12 Nov 1999 A parallel version of dcopy gave trouble in lu1ful during left-shift of dense matrix D within a(*). Fixed this unexpected problem here in lu1fad by making sure the first and second D don't overlap. 13 Sep 2000 TCP (Threshold Complete Pivoting) implemented. lu2max added (finds aijmax from biggest elems in each col). Utri, Ltri and Spars1 phases apply. No switch to Dense CP yet. (Only TPP switches.) 14 Sep 2000 imax needed to remember row containing aijmax. 22 Sep 2000 For simplicity, lu1mxc always fixes all modified cols. (TPP spars2 used to fix just the first maxcol cols.) 08 Nov 2000: Speed up search for aijmax. Don't need to search all columns if the elimination didn't alter the col containing the current aijmax. 21 Nov 2000: lu1slk implemented for Utri phase with TCP to guard against deceptive triangular matrices. (Utri used to have aijtol >= 0.9999 to include slacks, but this allows other 1s to be accepted.) Utri now accepts slacks, but applies normal aijtol test to other pivots. 28 Nov 2000: TCP with empty cols must call lu1mxc and lu2max with ( lq1, n, ... ), not just ( 1, n, ... ). 23 Mar 2001: lu1fad bug with TCP. A col of length 1 might not be accepted as a pivot. Later it appears in a pivot row and temporarily has length 0 (when pivot row is removed but before the column is filled in). If it is the last column in storage, the preceding col also thinks it is "last". Trouble arises when the preceding col needs fill-in -- it overlaps the real "last" column. (Very rarely, same trouble might have happened if the drop tolerance caused columns to have length 0.) Introduced ilast to record the last row in row file, jlast to record the last col in col file. lu1rec returns ilast = indr(lrow + 1) or jlast = indc(lcol + 1). (Should be an output parameter, but didn't want to alter lu1rec's parameter list.) lu1rec also treats empty rows or cols safely. (Doesn't eliminate them!) 26 Apr 2002: Heap routines added for TCP. lu2max no longer needed. imax, jmax used only for printing. 01 May 2002: lu1DCP implemented (dense complete pivoting). Both TPP and TCP now switch to dense LU when density exceeds dens2. 06 May 2002: In dense mode, store diag(U) in natural order. 09 May 2002: lu1mCP implemented (Markowitz TCP via heap). 11 Jun 2002: lu1mRP implemented (Markowitz TRP). 28 Jun 2002: Fixed call to lu1mxr. 14 Dec 2002: lu1mSP implemented (Markowitz TSP). 15 Dec 2002: Both TPP and TSP can grab cols of length 1 during Utri. ================================================================== */ void LU1FAD(LUSOLrec *LUSOL, #ifdef ClassicHamaxR int LENA2, int LENH, REAL HA[], int HJ[], int HK[], REAL AMAXR[], #endif int *INFORM, int *LENL, int *LENU, int *MINLEN, int *MERSUM, int *NUTRI, int *NLTRI, int *NDENS1, int *NDENS2, int *NRANK, REAL *LMAX, REAL *UMAX, REAL *DUMAX, REAL *DUMIN, REAL *AKMAX) { MYBOOL UTRI, LTRI, SPARS1, SPARS2, DENSE, DENSLU, KEEPLU, TCP, TPP, TRP,TSP; int HLEN, HOPS, H, LPIV, LPRINT, MAXCOL, MAXROW, ILAST, JLAST, LFILE, LROW, LCOL, MINMN, MAXMN, NZLEFT, NSPARE, LU1, KK, J, LC, MLEFT, NLEFT, NROWU, LQ1, LQ2, JBEST, LQ, I, IBEST, MBEST, LEND, NFREE, LD, NCOLD, NROWD, MELIM, NELIM, JMAX, IMAX, LL1, LSAVE, LFREE, LIMIT, MINFRE, LPIVR, LPIVR1, LPIVR2, L, LPIVC, LPIVC1, LPIVC2, KBEST, LU, LR, LENJ, LC1, LAST, LL, LS, LENI, LR1, LFIRST, NFILL, NZCHNG, K, MRANK, NSING; REAL LIJ, LTOL, SMALL, USPACE, DENS1, DENS2, AIJMAX, AIJTOL, AMAX, ABEST, DIAG, V; #ifdef ClassicHamaxR int LDIAGU; #else int LENA2 = LUSOL->lena; #endif #ifdef UseTimer int eltime, mktime, ntime; timer ( "start", 3 ); ntime = LUSOL->n / 4; #endif #ifdef ForceInitialization AIJMAX = 0; AIJTOL = 0; HLEN = 0; JBEST = 0; IBEST = 0; MBEST = 0; LEND = 0; LD = 0; #endif LPRINT = LUSOL->luparm[LUSOL_IP_PRINTLEVEL]; MAXCOL = LUSOL->luparm[LUSOL_IP_MARKOWITZ_MAXCOL]; LPIV = LUSOL->luparm[LUSOL_IP_PIVOTTYPE]; KEEPLU = (MYBOOL) (LUSOL->luparm[LUSOL_IP_KEEPLU]!=FALSE); /* Threshold Partial Pivoting (normal). */ TPP = (MYBOOL) (LPIV==LUSOL_PIVMOD_TPP); /* Threshold Rook Pivoting */ TRP = (MYBOOL) (LPIV==LUSOL_PIVMOD_TRP); /* Threshold Complete Pivoting. */ TCP = (MYBOOL) (LPIV==LUSOL_PIVMOD_TCP); /* Threshold Symmetric Pivoting. */ TSP = (MYBOOL) (LPIV==LUSOL_PIVMOD_TSP); DENSLU = FALSE; MAXROW = MAXCOL-1; /* Assume row m is last in the row file. */ ILAST = LUSOL->m; /* Assume col n is last in the col file. */ JLAST = LUSOL->n; LFILE = LUSOL->nelem; LROW = LUSOL->nelem; LCOL = LUSOL->nelem; MINMN = MIN(LUSOL->m,LUSOL->n); MAXMN = MAX(LUSOL->m,LUSOL->n); NZLEFT = LUSOL->nelem; NSPARE = 1; if(KEEPLU) LU1 = LENA2+1; else { /* Store only the diagonals of U in the top of memory. */ #ifdef ClassicdiagU LDIAGU = LENA2-LUSOL->n; LU1 = LDIAGU+1; LUSOL->diagU = LUSOL->a+LDIAGU; #else LU1 = LENA2+1; #endif } LTOL = LUSOL->parmlu[LUSOL_RP_FACTORMAX_Lij]; SMALL = LUSOL->parmlu[LUSOL_RP_ZEROTOLERANCE]; USPACE = LUSOL->parmlu[LUSOL_RP_COMPSPACE_U]; DENS1 = LUSOL->parmlu[LUSOL_RP_MARKOWITZ_CONLY]; DENS2 = LUSOL->parmlu[LUSOL_RP_MARKOWITZ_DENSE]; UTRI = TRUE; LTRI = FALSE; SPARS1 = FALSE; SPARS2 = FALSE; DENSE = FALSE; /* Check parameters. */ SETMAX(LTOL,1.0001E+0); SETMIN(DENS1,DENS2); /* Initialize output parameters. lenL, lenU, minlen, mersum, nUtri, nLtri, ndens1, ndens2, nrank are already initialized by lu1fac. */ *LMAX = ZERO; *UMAX = ZERO; *DUMAX = ZERO; *DUMIN = LUSOL_BIGNUM; if(LUSOL->nelem==0) *DUMIN = ZERO; *AKMAX = ZERO; HOPS = 0; /* More initialization. Don't worry yet about lu1mxc. */ if(TPP || TSP) { AIJMAX = ZERO; AIJTOL = ZERO; HLEN = 1; /* TRP or TCP */ } else { /* Move biggest element to top of each column. Set w(*) to mark slack columns (unit vectors). */ LU1MXC(LUSOL, 1,LUSOL->n,LUSOL->iq); LU1SLK(LUSOL); } if(TRP) /* Find biggest element in each row. */ #ifdef ClassicHamaxR LU1MXR(LUSOL, 1,LUSOL->m,LUSOL->ip,AMAXR); #else LU1MXR(LUSOL, 1,LUSOL->m,LUSOL->ip,LUSOL->amaxr); #endif if(TCP) { /* Set Ha(1:Hlen) = biggest element in each column, Hj(1:Hlen) = corresponding column indices. */ HLEN = 0; for(KK = 1; KK <= LUSOL->n; KK++) { HLEN++; J = LUSOL->iq[KK]; LC = LUSOL->locc[J]; #ifdef ClassicHamaxR HA[HLEN] = fabs(LUSOL->a[LC]); HJ[HLEN] = J; HK[J] = HLEN; #else LUSOL->Ha[HLEN] = fabs(LUSOL->a[LC]); LUSOL->Hj[HLEN] = J; LUSOL->Hk[J] = HLEN; #endif } /* Build the heap, creating new Ha, Hj and setting Hk(1:Hlen). */ #ifdef ClassicHamaxR HBUILD(HA,HJ,HK,HLEN,&HOPS); #else HBUILD(LUSOL->Ha,LUSOL->Hj,LUSOL->Hk,HLEN,&HOPS); #endif } /* ------------------------------------------------------------------ Start of main loop. ------------------------------------------------------------------ */ MLEFT = LUSOL->m+1; NLEFT = LUSOL->n+1; for(NROWU = 1; NROWU <= MINMN; NROWU++) { #ifdef UseTimer mktime = (nrowu / ntime) + 4; eltime = (nrowu / ntime) + 9; #endif MLEFT--; NLEFT--; /* Bail out if there are no nonzero rows left. */ if(LUSOL->iploc[1]>LUSOL->m) goto x900; /* For TCP, the largest Aij is at the top of the heap. */ if(TCP) { /* Marvelously easy */ #ifdef ClassicHamaxR AIJMAX = HA[1]; #else AIJMAX = LUSOL->Ha[1]; #endif SETMAX(*AKMAX,AIJMAX); AIJTOL = AIJMAX/LTOL; } /* =============================================================== Find a suitable pivot element. =============================================================== */ if(UTRI) { /* ------------------------------------------------------------ So far all columns have had length 1. We are still looking for the (backward) triangular part of A that forms the first rows and columns of U. ------------------------------------------------------------ */ LQ1 = LUSOL->iqloc[1]; LQ2 = LUSOL->n; if(LUSOL->m>1) LQ2 = LUSOL->iqloc[2]-1; /* There are more cols of length 1. */ if(LQ1<=LQ2) { if(TPP || TSP) { /* Grab the first one. */ JBEST = LUSOL->iq[LQ1]; /* Scan all columns of length 1 ... TRP or TCP */ } else { JBEST = 0; for(LQ = LQ1; LQ <= LQ2; LQ++) { J = LUSOL->iq[LQ]; /* Accept a slack */ if(LUSOL->w[J]>ZERO) { JBEST = J; goto x250; } LC = LUSOL->locc[J]; AMAX = fabs(LUSOL->a[LC]); if(TRP) { I = LUSOL->indc[LC]; #ifdef ClassicHamaxR AIJTOL = AMAXR[I]/LTOL; #else AIJTOL = LUSOL->amaxr[I]/LTOL; #endif } if(AMAX>=AIJTOL) { JBEST = J; goto x250; } } } x250: if(JBEST>0) { LC = LUSOL->locc[JBEST]; IBEST = LUSOL->indc[LC]; MBEST = 0; goto x300; } } /* This is the end of the U triangle. We will not return to this part of the code. TPP and TSP call lu1mxc for the first time (to move biggest element to top of each column). */ if(LPRINT>=LUSOL_MSG_PIVOT) LUSOL_report(LUSOL, 0, "Utri ended. spars1 = TRUE\n"); UTRI = FALSE; LTRI = TRUE; SPARS1 = TRUE; *NUTRI = NROWU-1; if(TPP || TSP) LU1MXC(LUSOL, LQ1,LUSOL->n,LUSOL->iq); } if(SPARS1) { /* ------------------------------------------------------------ Perform a Markowitz search. Search cols of length 1, then rows of length 1, then cols of length 2, then rows of length 2, etc. ------------------------------------------------------------ */ #ifdef UseTimer timer ( "start", mktime ); #endif /* 12 Jun 2002: Next line disables lu1mCP below if (TPP) then */ if(TPP || TCP) { LU1MAR(LUSOL, MAXMN,TCP,AIJTOL,LTOL,MAXCOL,MAXROW,&IBEST,&JBEST,&MBEST); } else if(TRP) { #ifdef ClassicHamaxR LU1MRP(LUSOL, MAXMN,LTOL,MAXCOL,MAXROW,&IBEST,&JBEST,&MBEST,AMAXR); #else LU1MRP(LUSOL, MAXMN,LTOL,MAXCOL,MAXROW,&IBEST,&JBEST,&MBEST,LUSOL->amaxr); #endif /* else if (TCP) { lu1mCP( m , n , lena , aijtol, ibest, jbest , mbest , a , indc , indr , lenc , lenr , locc , Hlen , Ha , Hj ) */ } else if(TSP) { LU1MSP(LUSOL, MAXMN,LTOL,MAXCOL,&IBEST,&JBEST,&MBEST); if(IBEST==0) goto x990; } #ifdef UseTimer timer ( "finish", mktime ); #endif if(LTRI) { /* So far all rows have had length 1. We are still looking for the (forward) triangle of A that forms the first rows and columns of L. */ if(MBEST>0) { LTRI = FALSE; *NLTRI = NROWU-1-*NUTRI; if(LPRINT>=LUSOL_MSG_PIVOT) LUSOL_report(LUSOL, 0, "Ltri ended.\n"); } } else { /* See if what's left is as dense as dens1. */ if(NZLEFT>=(DENS1*MLEFT)*NLEFT) { SPARS1 = FALSE; SPARS2 = TRUE; *NDENS1 = NLEFT; MAXROW = 0; if(LPRINT>=LUSOL_MSG_PIVOT) LUSOL_report(LUSOL, 0, "spars1 ended. spars2 = TRUE\n"); } } } else if(SPARS2 || DENSE) { /* ------------------------------------------------------------ Perform a restricted Markowitz search, looking at only the first maxcol columns. (maxrow = 0.) ------------------------------------------------------------ */ #ifdef UseTimer timer ( "start", mktime ); #endif /* 12 Jun 2002: Next line disables lu1mCP below if (TPP) then */ if(TPP || TCP) { LU1MAR(LUSOL, MAXMN,TCP,AIJTOL,LTOL,MAXCOL,MAXROW,&IBEST,&JBEST,&MBEST); } else if(TRP) { #ifdef ClassicHamaxR LU1MRP(LUSOL, MAXMN,LTOL,MAXCOL,MAXROW,&IBEST,&JBEST,&MBEST,AMAXR); #else LU1MRP(LUSOL, MAXMN,LTOL,MAXCOL,MAXROW,&IBEST,&JBEST,&MBEST,LUSOL->amaxr); #endif /* else if (TCP) { lu1mCP( m , n , lena , aijtol, ibest, jbest , mbest , a , indc , indr , lenc , lenr , locc , Hlen , Ha , Hj ) */ } else if(TSP) { LU1MSP(LUSOL, MAXMN,LTOL,MAXCOL,&IBEST,&JBEST,&MBEST); if(IBEST==0) goto x985; } #ifdef UseTimer timer ( "finish", mktime ); #endif /* See if what's left is as dense as dens2. */ if(SPARS2) { if(NZLEFT>=(DENS2*MLEFT)*NLEFT) { SPARS2 = FALSE; DENSE = TRUE; *NDENS2 = NLEFT; MAXCOL = 1; if(LPRINT>=LUSOL_MSG_PIVOT) LUSOL_report(LUSOL, 0, "spars2 ended. dense = TRUE\n"); } } } /* --------------------------------------------------------------- See if we can finish quickly. --------------------------------------------------------------- */ if(DENSE) { LEND = MLEFT*NLEFT; NFREE = LU1-1; if(NFREE>=2*LEND) { /* There is room to treat the remaining matrix as a dense matrix D. We may have to compress the column file first. 12 Nov 1999: D used to be put at the beginning of free storage (lD = lcol + 1). Now put it at the end (lD = lu1 - lenD) so the left-shift in lu1ful will not involve overlapping storage (fatal with parallel dcopy). */ DENSLU = TRUE; *NDENS2 = NLEFT; LD = LU1-LEND; if(LCOL>=LD) { LU1REC(LUSOL, LUSOL->n,TRUE,&LCOL, LUSOL->indc,LUSOL->lenc,LUSOL->locc); LFILE = LCOL; JLAST = LUSOL->indc[LCOL+1]; } goto x900; } } /* =============================================================== The best aij has been found. The pivot row ibest and the pivot column jbest Define a dense matrix D of size nrowd by ncold. =============================================================== */ x300: NCOLD = LUSOL->lenr[IBEST]; NROWD = LUSOL->lenc[JBEST]; MELIM = NROWD-1; NELIM = NCOLD-1; (*MERSUM) += MBEST; (*LENL) += MELIM; (*LENU) += NCOLD; if(LPRINT>=LUSOL_MSG_PIVOT) { if(NROWU==1) LUSOL_report(LUSOL, 0, "lu1fad debug:\n"); if(TPP || TRP || TSP) { LUSOL_report(LUSOL, 0, "nrowu:%7d i,jbest:%7d,%7d nrowd,ncold:%6d,%6d\n", NROWU, IBEST,JBEST, NROWD,NCOLD); /* TCP */ } else { #ifdef ClassicHamaxR JMAX = HJ[1]; #else JMAX = LUSOL->Hj[1]; #endif IMAX = LUSOL->indc[LUSOL->locc[JMAX]]; LUSOL_report(LUSOL, 0, "nrowu:%7d i,jbest:%7d,%7d nrowd,ncold:%6d,%6d i,jmax:%7d,%7d aijmax:%g\n", NROWU, IBEST,JBEST, NROWD,NCOLD, IMAX,JMAX, AIJMAX); } } /* =============================================================== Allocate storage for the next column of L and next row of U. Initially the top of a, indc, indr are used as follows: ncold melim ncold melim a |...........|...........|ujbest..ujn|li1......lim| indc |...........| lenr(i) | lenc(j) | markl(i) | indr |...........| iqloc(i) | jfill(j) | ifill(i) | ^ ^ ^ ^ ^ lfree lsave lu1 ll1 oldlu1 Later the correct indices are inserted: indc | | | |i1........im| indr | | |jbest....jn|ibest..ibest| =============================================================== */ if(!KEEPLU) { /* Always point to the top spot. Only the current column of L and row of U will take up space, overwriting the previous ones. */ #ifdef ClassicHamaxR LU1 = LDIAGU+1; #else LU1 = LENA2+1; #endif } /* Update (left-shift) pointers to make room for the new data */ LL1 = LU1-MELIM; LU1 = LL1-NCOLD; LSAVE = LU1-NROWD; LFREE = LSAVE-NCOLD; /* Check if we need to allocate more memory, and allocate if necessary */ #if 0 /* Proposal by Michael A. Saunders (logic based on Markowitz' rule) */ L = NROWD*NCOLD; /* Try to avoid future expansions by anticipating further updates - KE extension */ if(LUSOL->luparm[LUSOL_IP_UPDATELIMIT] > 0) #if 1 L *= (int) (log(LUSOL->luparm[LUSOL_IP_UPDATELIMIT]-LUSOL->luparm[LUSOL_IP_UPDATECOUNT]+2.0) + 1); #else L *= (LUSOL->luparm[LUSOL_IP_UPDATELIMIT]-LUSOL->luparm[LUSOL_IP_UPDATECOUNT]) / 2 + 1; #endif #else /* Version by Kjell Eikland (from luparm[LUSOL_IP_MINIMUMLENA] and safety margin) */ L = (KEEPLU ? MAX(LROW, LCOL) + 2*(LUSOL->m+LUSOL->n) : 0); L *= LUSOL_MULT_nz_a; SETMAX(L, NROWD*NCOLD); #endif /* Do the memory expansion */ if((L > LFREE-LCOL) && LUSOL_expand_a(LUSOL, &L, &LFREE)) { LL1 += L; LU1 += L; LSAVE += L; #ifdef ClassicdiagU LUSOL->diagU += L; #endif #ifdef ClassicHamaxR HA += L; HJ += L; HK += L; AMAXR += L; #endif } LIMIT = (int) (USPACE*LFILE)+LUSOL->m+LUSOL->n+1000; /* Make sure the column file has room. Also force a compression if its length exceeds a certain limit. */ #ifdef StaticMemAlloc MINFRE = NCOLD+MELIM; #else MINFRE = NROWD*NCOLD; #endif NFREE = LFREE-LCOL; if(NFREELIMIT) { LU1REC(LUSOL, LUSOL->n,TRUE,&LCOL, LUSOL->indc,LUSOL->lenc,LUSOL->locc); LFILE = LCOL; JLAST = LUSOL->indc[LCOL+1]; NFREE = LFREE-LCOL; if(NFREELIMIT) { LU1REC(LUSOL, LUSOL->m,FALSE,&LROW, LUSOL->indr,LUSOL->lenr,LUSOL->locr); LFILE = LROW; ILAST = LUSOL->indr[LROW+1]; NFREE = LFREE-LROW; if(NFREElocr[IBEST]; LPIVR1 = LPIVR+1; LPIVR2 = LPIVR+NELIM; for(L = LPIVR; L <= LPIVR2; L++) { if(LUSOL->indr[L]==JBEST) break; } LUSOL->indr[L] = LUSOL->indr[LPIVR]; LUSOL->indr[LPIVR] = JBEST; LPIVC = LUSOL->locc[JBEST]; LPIVC1 = LPIVC+1; LPIVC2 = LPIVC+MELIM; for(L = LPIVC; L <= LPIVC2; L++) { if(LUSOL->indc[L]==IBEST) break; } LUSOL->indc[L] = LUSOL->indc[LPIVC]; LUSOL->indc[LPIVC] = IBEST; ABEST = LUSOL->a[L]; LUSOL->a[L] = LUSOL->a[LPIVC]; LUSOL->a[LPIVC] = ABEST; if(!KEEPLU) /* Store just the diagonal of U, in natural order. !! a[ldiagU + nrowu] = abest ! This was in pivot order. */ LUSOL->diagU[JBEST] = ABEST; /* ============================================================== Delete pivot col from heap. Hk tells us where it is in the heap. ============================================================== */ if(TCP) { #ifdef ClassicHamaxR KBEST = HK[JBEST]; HDELETE(HA,HJ,HK,&HLEN,KBEST,&H); #else KBEST = LUSOL->Hk[JBEST]; HDELETE(LUSOL->Ha,LUSOL->Hj,LUSOL->Hk,&HLEN,KBEST,&H); #endif HOPS += H; } /* =============================================================== Delete the pivot row from the column file and store it as the next row of U. set indr(lu) = 0 to initialize jfill ptrs on columns of D, indc(lu) = lenj to save the original column lengths. =============================================================== */ LUSOL->a[LU1] = ABEST; LUSOL->indr[LU1] = JBEST; LUSOL->indc[LU1] = NROWD; LU = LU1; DIAG = fabs(ABEST); SETMAX(*UMAX,DIAG); SETMAX(*DUMAX,DIAG); SETMIN(*DUMIN,DIAG); for(LR = LPIVR1; LR <= LPIVR2; LR++) { LU++; J = LUSOL->indr[LR]; LENJ = LUSOL->lenc[J]; LUSOL->lenc[J] = LENJ-1; LC1 = LUSOL->locc[J]; LAST = LC1+LUSOL->lenc[J]; for(L = LC1; L <= LAST; L++) { if(LUSOL->indc[L]==IBEST) break; } LUSOL->a[LU] = LUSOL->a[L]; LUSOL->indr[LU] = 0; LUSOL->indc[LU] = LENJ; SETMAX(*UMAX,fabs(LUSOL->a[LU])); LUSOL->a[L] = LUSOL->a[LAST]; LUSOL->indc[L] = LUSOL->indc[LAST]; /* Free entry */ LUSOL->indc[LAST] = 0; /* ??? if (j .eq. jlast) lcol = lcol - 1 */ } /* =============================================================== Delete the pivot column from the row file and store the nonzeros of the next column of L. Set indc(ll) = 0 to initialize markl(*) markers, indr(ll) = 0 to initialize ifill(*) row fill-in cntrs, indc(ls) = leni to save the original row lengths, indr(ls) = iqloc(i) to save parts of iqloc(*), iqloc(i) = lsave - ls to point to the nonzeros of L = -1, -2, -3, ... in mark(*). =============================================================== */ LUSOL->indc[LSAVE] = NCOLD; if(MELIM==0) goto x700; LL = LL1-1; LS = LSAVE; ABEST = ONE/ABEST; for(LC = LPIVC1; LC <= LPIVC2; LC++) { LL++; LS++; I = LUSOL->indc[LC]; LENI = LUSOL->lenr[I]; LUSOL->lenr[I] = LENI-1; LR1 = LUSOL->locr[I]; LAST = LR1+LUSOL->lenr[I]; for(L = LR1; L <= LAST; L++) { if(LUSOL->indr[L]==JBEST) break; } LUSOL->indr[L] = LUSOL->indr[LAST]; /* Free entry */ LUSOL->indr[LAST] = 0; LUSOL->a[LL] = -LUSOL->a[LC]*ABEST; LIJ = fabs(LUSOL->a[LL]); SETMAX(*LMAX,LIJ); LUSOL->indc[LL] = 0; LUSOL->indr[LL] = 0; LUSOL->indc[LS] = LENI; LUSOL->indr[LS] = LUSOL->iqloc[I]; LUSOL->iqloc[I] = LSAVE-LS; } /* =============================================================== Do the Gaussian elimination. This involves adding a multiple of the pivot column to all other columns in the pivot row. Sometimes more than one call to lu1gau is needed to allow compression of the column file. lfirst says which column the elimination should start with. minfre is a bound on the storage needed for any one column. lu points to off-diagonals of u. nfill keeps track of pending fill-in in the row file. =============================================================== */ if(NELIM==0) goto x700; LFIRST = LPIVR1; MINFRE = MLEFT+NSPARE; LU = 1; NFILL = 0; x400: #ifdef UseTimer timer ( "start", eltime ); #endif LU1GAU(LUSOL, MELIM,NSPARE,SMALL,LPIVC1,LPIVC2,&LFIRST,LPIVR2, LFREE,MINFRE,ILAST,&JLAST,&LROW,&LCOL,&LU,&NFILL, LUSOL->iqloc, LUSOL->a+LL1-LUSOL_ARRAYOFFSET, LUSOL->indc+LL1-LUSOL_ARRAYOFFSET, LUSOL->a+LU1-LUSOL_ARRAYOFFSET, LUSOL->indr+LL1-LUSOL_ARRAYOFFSET, LUSOL->indr+LU1-LUSOL_ARRAYOFFSET); #ifdef UseTimer timer ( "finish", eltime ); #endif if(LFIRST>0) { /* The elimination was interrupted. Compress the column file and try again. lfirst, lu and nfill have appropriate new values. */ LU1REC(LUSOL, LUSOL->n,TRUE,&LCOL, LUSOL->indc,LUSOL->lenc,LUSOL->locc); LFILE = LCOL; JLAST = LUSOL->indc[LCOL+1]; LPIVC = LUSOL->locc[JBEST]; LPIVC1 = LPIVC+1; LPIVC2 = LPIVC+MELIM; NFREE = LFREE-LCOL; if(NFREE0) { /* Compress the row file if necessary. lu1gau has set nfill to be the number of pending fill-ins plus the current length of any rows that need to be moved. */ MINFRE = NFILL; NFREE = LFREE-LROW; if(NFREEm,FALSE,&LROW, LUSOL->indr,LUSOL->lenr,LUSOL->locr); LFILE = LROW; ILAST = LUSOL->indr[LROW+1]; LPIVR = LUSOL->locr[IBEST]; LPIVR1 = LPIVR+1; LPIVR2 = LPIVR+NELIM; NFREE = LFREE-LROW; if(NFREEindr+LL1-LUSOL_ARRAYOFFSET,LUSOL->indr+LU1-LUSOL_ARRAYOFFSET); } /* =============================================================== Restore the saved values of iqloc. Insert the correct indices for the col of L and the row of U. =============================================================== */ x700: LUSOL->lenr[IBEST] = 0; LUSOL->lenc[JBEST] = 0; LL = LL1-1; LS = LSAVE; for(LC = LPIVC1; LC <= LPIVC2; LC++) { LL++; LS++; I = LUSOL->indc[LC]; LUSOL->iqloc[I] = LUSOL->indr[LS]; LUSOL->indc[LL] = I; LUSOL->indr[LL] = IBEST; } LU = LU1-1; for(LR = LPIVR; LR <= LPIVR2; LR++) { LU++; LUSOL->indr[LU] = LUSOL->indr[LR]; } /* =============================================================== Free the space occupied by the pivot row and update the column permutation. Then free the space occupied by the pivot column and update the row permutation. nzchng is found in both calls to lu1pq2, but we use it only after the second. =============================================================== */ LU1PQ2(LUSOL, NCOLD, &NZCHNG, LUSOL->indr+LPIVR-LUSOL_ARRAYOFFSET, LUSOL->indc+LU1-LUSOL_ARRAYOFFSET, LUSOL->lenc, LUSOL->iqloc, LUSOL->iq, LUSOL->iqinv); LU1PQ2(LUSOL, NROWD, &NZCHNG, LUSOL->indc+LPIVC-LUSOL_ARRAYOFFSET, LUSOL->indc+LSAVE-LUSOL_ARRAYOFFSET, LUSOL->lenr, LUSOL->iploc, LUSOL->ip, LUSOL->ipinv); NZLEFT += NZCHNG; /* =============================================================== lu1mxr resets Amaxr(i) in each modified row i. lu1mxc moves the largest aij to the top of each modified col j. 28 Jun 2002: Note that cols of L have an implicit diag of 1.0, so lu1mxr is called with ll1, not ll1+1, whereas lu1mxc is called with lu1+1. =============================================================== */ if(UTRI && TPP) { /* Relax -- we're not keeping big elements at the top yet. */ } else { if(TRP && MELIM>0) #ifdef ClassicHamaxR LU1MXR(LUSOL, LL1,LL,LUSOL->indc,AMAXR); #else LU1MXR(LUSOL, LL1,LL,LUSOL->indc,LUSOL->amaxr); #endif if(NELIM>0) { LU1MXC(LUSOL, LU1+1,LU,LUSOL->indr); /* Update modified columns in heap */ if(TCP) { for(KK = LU1+1; KK <= LU; KK++) { J = LUSOL->indr[KK]; #ifdef ClassicHamaxR K = HK[J]; #else K = LUSOL->Hk[J]; #endif /* Biggest aij in column j */ V = fabs(LUSOL->a[LUSOL->locc[J]]); #ifdef ClassicHamaxR HCHANGE(HA,HJ,HK,HLEN,K,V,J,&H); #else HCHANGE(LUSOL->Ha,LUSOL->Hj,LUSOL->Hk,HLEN,K,V,J,&H); #endif HOPS += H; } } } } /* =============================================================== Negate lengths of pivot row and column so they will be eliminated during compressions. =============================================================== */ LUSOL->lenr[IBEST] = -NCOLD; LUSOL->lenc[JBEST] = -NROWD; /* Test for fatal bug: row or column lists overwriting L and U. */ if(LROW>LSAVE || LCOL>LSAVE) goto x980; /* Reset the file lengths if pivot row or col was at the end. */ if(IBEST==ILAST) LROW = LUSOL->locr[IBEST]; if(JBEST==JLAST) LCOL = LUSOL->locc[JBEST]; } /* ------------------------------------------------------------------ End of main loop. ------------------------------------------------------------------ ------------------------------------------------------------------ Normal exit. Move empty rows and cols to the end of ip, iq. Then finish with a dense LU if necessary. ------------------------------------------------------------------ */ x900: *INFORM = LUSOL_INFORM_LUSUCCESS; LU1PQ3(LUSOL, LUSOL->m,LUSOL->lenr,LUSOL->ip,LUSOL->ipinv,&MRANK); LU1PQ3(LUSOL, LUSOL->n,LUSOL->lenc,LUSOL->iq,LUSOL->iqinv,NRANK); SETMIN(*NRANK, MRANK); if(DENSLU) { #ifdef UseTimer timer ( "start", 17 ); #endif LU1FUL(LUSOL, LEND,LU1,TPP,MLEFT,NLEFT,*NRANK,NROWU,LENL,LENU, &NSING,KEEPLU,SMALL,LUSOL->a+LD-LUSOL_ARRAYOFFSET,LUSOL->locr); /* *** 21 Dec 1994: Bug in next line. *** nrank = nrank - nsing */ *NRANK = MINMN-NSING; #ifdef UseTimer timer ( "finish", 17 ); #endif } *MINLEN = (*LENL)+(*LENU)+2*(LUSOL->m+LUSOL->n); goto x990; /* Not enough space free after a compress. Set minlen to an estimate of the necessary value of lena. */ x970: *INFORM = LUSOL_INFORM_ANEEDMEM; *MINLEN = LENA2+LFILE+2*(LUSOL->m+LUSOL->n); goto x990; /* Fatal error. This will never happen! (Famous last words.) */ x980: *INFORM = LUSOL_INFORM_FATALERR; goto x990; /* Fatal error with TSP. Diagonal pivot not found. */ x985: *INFORM = LUSOL_INFORM_NOPIVOT; /* Exit. */ x990: #ifdef UseTimer timer ( "finish", 3 ); #endif ; } /* ================================================================== lu1fac computes a factorization A = L*U, where A is a sparse matrix with m rows and n columns, P*L*P' is lower triangular and P*U*Q is upper triangular for certain permutations P, Q (which are returned in the arrays ip, iq). Stability is ensured by limiting the size of the elements of L. The nonzeros of A are input via the parallel arrays a, indc, indr, which should contain nelem entries of the form aij, i, j in any order. There should be no duplicate pairs i, j. ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ + Beware !!! The row indices i must be in indc, + + and the column indices j must be in indr. + + (Not the other way round!) + ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ It does not matter if some of the entries in a(*) are zero. Entries satisfying abs( a(i) ) .le. parmlu(3) are ignored. Other parameters in luparm and parmlu are described below. The matrix A may be singular. On exit, nsing = luparm(11) gives the number of apparent singularities. This is the number of "small" diagonals of the permuted factor U, as judged by the input tolerances Utol1 = parmlu(4) and Utol2 = parmlu(5). The diagonal element diagj associated with column j of A is "small" if abs( diagj ) .le. Utol1 or abs( diagj ) .le. Utol2 * max( uj ), where max( uj ) is the maximum element in the j-th column of U. The position of such elements is returned in w(*). In general, w(j) = + max( uj ), but if column j is a singularity, w(j) = - max( uj ). Thus, w(j) .le. 0 if column j appears to be dependent on the other columns of A. NOTE: lu1fac (like certain other sparse LU packages) does not treat dense columns efficiently. This means it will be slow on "arrow matrices" of the form A = (x a) ( x b) ( x c) ( x d) (x x x x e) if the numerical values in the dense column allow it to be chosen LATE in the pivot order. With TPP (Threshold Partial Pivoting), the dense column is likely to be chosen late. With TCP (Threshold Complete Pivoting), if any of a,b,c,d is significantly larger than other elements of A, it will be chosen as the first pivot and the dense column will be eliminated, giving reasonably sparse factors. However, if element e is so big that TCP chooses it, the factors will become dense. (It's hard to win on these examples!) ------------------------------------------------------------------ Notes on the array names ------------------------ During the LU factorization, the sparsity pattern of the matrix being factored is stored twice: in a column list and a row list. The column list is ( a, indc, locc, lenc ) where a(*) holds the nonzeros, indc(*) holds the indices for the column list, locc(j) points to the start of column j in a(*) and indc(*), lenc(j) is the number of nonzeros in column j. The row list is ( indr, locr, lenr ) where indr(*) holds the indices for the row list, locr(i) points to the start of row i in indr(*), lenr(i) is the number of nonzeros in row i. At all stages of the LU factorization, ip contains a complete row permutation. At the start of stage k, ip(1), ..., ip(k-1) are the first k-1 rows of the final row permutation P. The remaining rows are stored in an ordered list ( ip, iploc, ipinv ) where iploc(nz) points to the start in ip(*) of the set of rows that currently contain nz nonzeros, ipinv(i) points to the position of row i in ip(*). For example, iploc(1) = k (and this is where rows of length 1 {), iploc(2) = k+p if there are p rows of length 1 (and this is where rows of length 2 {). Similarly for iq, iqloc, iqinv. --------------------------------------------------------------------- INPUT PARAMETERS m (not altered) is the number of rows in A. n (not altered) is the number of columns in A. nelem (not altered) is the number of matrix entries given in the arrays a, indc, indr. lena (not altered) is the dimension of a, indc, indr. This should be significantly larger than nelem. Typically one should have lena > max( 2*nelem, 10*m, 10*n, 10000 ) but some applications may need more. On machines with virtual memory it is safe to have lena "far bigger than necessary", since not all of the arrays will be used. a (overwritten) contains entries Aij in a(1:nelem). indc (overwritten) contains the indices i in indc(1:nelem). indr (overwritten) contains the indices j in indr(1:nelem). luparm input parameters: Typical value luparm( 1) = nout File number for printed messages. 6 luparm( 2) = lprint Print level. 0 < 0 suppresses output. = 0 gives error messages. >= 10 gives statistics about the LU factors. >= 50 gives debug output from lu1fac (the pivot row and column and the no. of rows and columns involved at each elimination step). luparm( 3) = maxcol lu1fac: maximum number of columns 5 searched allowed in a Markowitz-type search for the next pivot element. For some of the factorization, the number of rows searched is maxrow = maxcol - 1. luparm( 6) = 0 => TPP: Threshold Partial Pivoting. 0 = 1 => TRP: Threshold Rook Pivoting. = 2 => TCP: Threshold Complete Pivoting. = 3 => TSP: Threshold Symmetric Pivoting. = 4 => TDP: Threshold Diagonal Pivoting. (TDP not yet implemented). TRP and TCP are more expensive than TPP but more stable and better at revealing rank. Take care with setting parmlu(1), especially with TCP. NOTE: TSP and TDP are for symmetric matrices that are either definite or quasi-definite. TSP is effectively TRP for symmetric matrices. TDP is effectively TCP for symmetric matrices. luparm( 8) = keepLU lu1fac: keepLU = 1 means the numerical 1 factors will be computed if possible. keepLU = 0 means L and U will be discarded but other information such as the row and column permutations will be returned. The latter option requires less storage. parmlu input parameters: Typical value parmlu( 1) = Ltol1 Max Lij allowed during Factor. TPP 10.0 or 100.0 TRP 4.0 or 10.0 TCP 5.0 or 10.0 TSP 4.0 or 10.0 With TRP and TCP (Rook and Complete Pivoting), values less than 25.0 may be expensive on badly scaled data. However, values less than 10.0 may be needed to obtain a reliable rank-revealing factorization. parmlu( 2) = Ltol2 Max Lij allowed during Updates. 10.0 during updates. parmlu( 3) = small Absolute tolerance for eps**0.8 = 3.0d-13 treating reals as zero. parmlu( 4) = Utol1 Absolute tol for flagging eps**0.67= 3.7d-11 small diagonals of U. parmlu( 5) = Utol2 Relative tol for flagging eps**0.67= 3.7d-11 small diagonals of U. (eps = machine precision) parmlu( 6) = Uspace Factor limiting waste space in U. 3.0 In lu1fac, the row or column lists are compressed if their length exceeds Uspace times the length of either file after the last compression. parmlu( 7) = dens1 The density at which the Markowitz 0.3 pivot strategy should search maxcol columns and no rows. (Use 0.3 unless you are experimenting with the pivot strategy.) parmlu( 8) = dens2 the density at which the Markowitz 0.5 strategy should search only 1 column, or (if storage is available) the density at which all remaining rows and columns will be processed by a dense LU code. For example, if dens2 = 0.1 and lena is large enough, a dense LU will be used once more than 10 per cent of the remaining matrix is nonzero. OUTPUT PARAMETERS a, indc, indr contain the nonzero entries in the LU factors of A. If keepLU = 1, they are in a form suitable for use by other parts of the LUSOL package, such as lu6sol. U is stored by rows at the start of a, indr. L is stored by cols at the end of a, indc. If keepLU = 0, only the diagonals of U are stored, at the end of a. ip, iq are the row and column permutations defining the pivot order. For example, row ip(1) and column iq(1) defines the first diagonal of U. lenc(1:numl0) contains the number of entries in nontrivial columns of L (in pivot order). lenr(1:m) contains the number of entries in each row of U (in original order). locc(1:n) = 0 (ready for the LU update routines). locr(1:m) points to the beginning of the rows of U in a, indr. iploc, iqloc, ipinv, iqinv are undefined. w indicates singularity as described above. inform = 0 if the LU factors were obtained successfully. = 1 if U appears to be singular, as judged by lu6chk. = 3 if some index pair indc(l), indr(l) lies outside the matrix dimensions 1:m , 1:n. = 4 if some index pair indc(l), indr(l) duplicates another such pair. = 7 if the arrays a, indc, indr were not large enough. Their length "lena" should be increase to at least the value "minlen" given in luparm(13). = 8 if there was some other fatal error. (Shouldn't happen!) = 9 if no diagonal pivot could be found with TSP or TDP. The matrix must not be sufficiently definite or quasi-definite. luparm output parameters: luparm(10) = inform Return code from last call to any LU routine. luparm(11) = nsing No. of singularities marked in the output array w(*). luparm(12) = jsing Column index of last singularity. luparm(13) = minlen Minimum recommended value for lena. luparm(14) = maxlen ? luparm(15) = nupdat No. of updates performed by the lu8 routines. luparm(16) = nrank No. of nonempty rows of U. luparm(17) = ndens1 No. of columns remaining when the density of the matrix being factorized reached dens1. luparm(18) = ndens2 No. of columns remaining when the density of the matrix being factorized reached dens2. luparm(19) = jumin The column index associated with DUmin. luparm(20) = numL0 No. of columns in initial L. luparm(21) = lenL0 Size of initial L (no. of nonzeros). luparm(22) = lenU0 Size of initial U. luparm(23) = lenL Size of current L. luparm(24) = lenU Size of current U. luparm(25) = lrow Length of row file. luparm(26) = ncp No. of compressions of LU data structures. luparm(27) = mersum lu1fac: sum of Markowitz merit counts. luparm(28) = nUtri lu1fac: triangular rows in U. luparm(29) = nLtri lu1fac: triangular rows in L. luparm(30) = parmlu output parameters: parmlu(10) = Amax Maximum element in A. parmlu(11) = Lmax Maximum multiplier in current L. parmlu(12) = Umax Maximum element in current U. parmlu(13) = DUmax Maximum diagonal in U. parmlu(14) = DUmin Minimum diagonal in U. parmlu(15) = Akmax Maximum element generated at any stage during TCP factorization. parmlu(16) = growth TPP: Umax/Amax TRP, TCP, TSP: Akmax/Amax parmlu(17) = parmlu(18) = parmlu(19) = parmlu(20) = resid lu6sol: residual after solve with U or U'. ... parmlu(30) = ------------------------------------------------------------------ 00 Jun 1983 Original version. 00 Jul 1987 nrank saved in luparm(16). 12 Apr 1989 ipinv, iqinv added as workspace. 26 Apr 1989 maxtie replaced by maxcol in Markowitz search. 16 Mar 1992 jumin saved in luparm(19). 10 Jun 1992 lu1fad has to move empty rows and cols to the bottom (via lu1pq3) before doing the dense LU. 12 Jun 1992 Deleted dense LU (lu1ful, lu1vlu). 25 Oct 1993 keepLU implemented. 07 Feb 1994 Added new dense LU (lu1ful, lu1den). 21 Dec 1994 Bugs fixed in lu1fad (nrank) and lu1ful (ipvt). 08 Aug 1995 Use ip instead of w as parameter to lu1or3 (for F90). 13 Sep 2000 TPP and TCP options implemented. 17 Oct 2000 Fixed troubles due to A = empty matrix (Todd Munson). 01 Dec 2000 Save Lmax, Umax, etc. after both lu1fad and lu6chk. lu1fad sets them when keepLU = false. lu6chk sets them otherwise, and includes items from the dense LU. 11 Mar 2001 lu6chk now looks at diag(U) when keepLU = false. 26 Apr 2002 New TCP implementation using heap routines to store largest element in each column. New workspace arrays Ha, Hj, Hk required. For compatibility, borrow space from a, indc, indr rather than adding new input parameters. 01 May 2002 lu1den changed to lu1DPP (dense partial pivoting). lu1DCP implemented (dense complete pivoting). Both TPP and TCP now switch to dense mode and end. ================================================================== */ void LU1FAC(LUSOLrec *LUSOL, int *INFORM) { MYBOOL KEEPLU, TCP, TPP, TRP, TSP; int LPIV, NELEM0, LPRINT, MINLEN, NUML0, LENL, LENU, LROW, MERSUM, NUTRI, NLTRI, NDENS1, NDENS2, NRANK, NSING, JSING, JUMIN, NUMNZ, LERR, LU, LL, LM, LTOPL, K, I, LENUK, J, LENLK, IDUMMY, LLSAVE, NMOVE, L2, L, NCP, NBUMP; #ifdef ClassicHamaxR int LENH, LENA2, LOCH, LMAXR; #endif REAL LMAX, LTOL, SMALL, AMAX, UMAX, DUMAX, DUMIN, AKMAX, DM, DN, DELEM, DENSTY, AGRWTH, UGRWTH, GROWTH, CONDU, DINCR, AVGMER; /* Free row-based version of L0 (regenerated by LUSOL_btran). */ if(LUSOL->L0 != NULL) LUSOL_matfree(&(LUSOL->L0)); /* Grab relevant input parameters. */ NELEM0 = LUSOL->nelem; LPRINT = LUSOL->luparm[LUSOL_IP_PRINTLEVEL]; LPIV = LUSOL->luparm[LUSOL_IP_PIVOTTYPE]; KEEPLU = (MYBOOL) (LUSOL->luparm[LUSOL_IP_KEEPLU]!=FALSE); /* Limit on size of Lij */ LTOL = LUSOL->parmlu[LUSOL_RP_FACTORMAX_Lij]; /* Drop tolerance */ SMALL = LUSOL->parmlu[LUSOL_RP_ZEROTOLERANCE]; TPP = (MYBOOL) (LPIV==LUSOL_PIVMOD_TPP); TRP = (MYBOOL) (LPIV==LUSOL_PIVMOD_TRP); TCP = (MYBOOL) (LPIV==LUSOL_PIVMOD_TCP); TSP = (MYBOOL) (LPIV==LUSOL_PIVMOD_TSP); /* Initialize output parameters. */ *INFORM = LUSOL_INFORM_LUSUCCESS; LERR = 0; MINLEN = LUSOL->nelem + 2*(LUSOL->m+LUSOL->n); NUML0 = 0; LENL = 0; LENU = 0; LROW = 0; MERSUM = 0; NUTRI = LUSOL->m; NLTRI = 0; NDENS1 = 0; NDENS2 = 0; NRANK = 0; NSING = 0; JSING = 0; JUMIN = 0; AMAX = ZERO; LMAX = ZERO; UMAX = ZERO; DUMAX = ZERO; DUMIN = ZERO; AKMAX = ZERO; /* Float version of dimensions. */ DM = LUSOL->m; DN = LUSOL->n; DELEM = LUSOL->nelem; /* Initialize workspace parameters. */ LUSOL->luparm[LUSOL_IP_COMPRESSIONS_LU] = 0; if(LUSOL->lena < MINLEN) { if(!LUSOL_realloc_a(LUSOL, MINLEN)) goto x970; } /* ------------------------------------------------------------------ Organize the aij's in a, indc, indr. lu1or1 deletes small entries, tests for illegal i,j's, and counts the nonzeros in each row and column. lu1or2 reorders the elements of A by columns. lu1or3 uses the column list to test for duplicate entries (same indices i,j). lu1or4 constructs a row list from the column list. ------------------------------------------------------------------ */ LU1OR1(LUSOL, SMALL,&AMAX,&NUMNZ,&LERR,INFORM); if(LPRINT>=LUSOL_MSG_STATISTICS) { DENSTY = (100*DELEM)/(DM*DN); LUSOL_report(LUSOL, 0, "m:%6d %c n:%6d nzcount:%9d Amax:%g Density:%g\n", LUSOL->m, relationChar(LUSOL->m, LUSOL->n), LUSOL->n, LUSOL->nelem, AMAX, DENSTY); } if(*INFORM!=LUSOL_INFORM_LUSUCCESS) goto x930; LUSOL->nelem = NUMNZ; LU1OR2(LUSOL); LU1OR3(LUSOL, &LERR,INFORM); if(*INFORM!=LUSOL_INFORM_LUSUCCESS) goto x940; LU1OR4(LUSOL); /* ------------------------------------------------------------------ Set up lists of rows and columns with equal numbers of nonzeros, using indc(*) as workspace. ------------------------------------------------------------------ */ LU1PQ1(LUSOL, LUSOL->m,LUSOL->n,LUSOL->lenr, LUSOL->ip,LUSOL->iploc,LUSOL->ipinv, LUSOL->indc+LUSOL->nelem); /* LUSOL_ARRAYOFFSET implied */ LU1PQ1(LUSOL, LUSOL->n,LUSOL->m,LUSOL->lenc, LUSOL->iq,LUSOL->iqloc,LUSOL->iqinv, LUSOL->indc+LUSOL->nelem); /* LUSOL_ARRAYOFFSET implied */ /* ------------------------------------------------------------------ For TCP, Ha, Hj, Hk are allocated separately, similarly amaxr for TRP. Then compute the factorization A = L*U. ------------------------------------------------------------------ */ #ifdef ClassicHamaxR if(TPP || TSP) { LENH = 1; LENA2 = LUSOL->lena; LOCH = LUSOL->lena; LMAXR = 1; } else if(TRP) { LENH = 1; /* Dummy */ LENA2 = LUSOL->lena-LUSOL->m; /* Reduced length of a */ LOCH = LUSOL->lena; /* Dummy */ LMAXR = LENA2+1; /* Start of Amaxr in a */ } else if(TCP) { LENH = LUSOL->n; /* Length of heap */ LENA2 = LUSOL->lena-LENH; /* Reduced length of a, indc, indr */ LOCH = LENA2+1; /* Start of Ha, Hj, Hk in a, indc, indr */ LMAXR = 1; /* Dummy */ } LU1FAD(LUSOL, LENA2,LENH, LUSOL->a+LOCH-LUSOL_ARRAYOFFSET, LUSOL->indc+LOCH-LUSOL_ARRAYOFFSET, LUSOL->indr+LOCH-LUSOL_ARRAYOFFSET, LUSOL->a+LMAXR-LUSOL_ARRAYOFFSET, INFORM,&LENL,&LENU, &MINLEN,&MERSUM,&NUTRI,&NLTRI,&NDENS1,&NDENS2, &NRANK,&LMAX,&UMAX,&DUMAX,&DUMIN,&AKMAX); #else LU1FAD(LUSOL, INFORM,&LENL,&LENU, &MINLEN,&MERSUM,&NUTRI,&NLTRI,&NDENS1,&NDENS2, &NRANK,&LMAX,&UMAX,&DUMAX,&DUMIN,&AKMAX); #endif LUSOL->luparm[LUSOL_IP_RANK_U] = NRANK; LUSOL->luparm[LUSOL_IP_NONZEROS_L] = LENL; if(*INFORM==LUSOL_INFORM_ANEEDMEM) goto x970; if(*INFORM==LUSOL_INFORM_NOPIVOT) goto x985; if(*INFORM>LUSOL_INFORM_LUSUCCESS) goto x980; if(KEEPLU) { /* --------------------------------------------------------------- The LU factors are at the top of a, indc, indr, with the columns of L and the rows of U in the order ( free ) ... ( u3 ) ( l3 ) ( u2 ) ( l2 ) ( u1 ) ( l1 ). Starting with ( l1 ) and ( u1 ), move the rows of U to the left and the columns of L to the right, giving ( u1 ) ( u2 ) ( u3 ) ... ( free ) ... ( l3 ) ( l2 ) ( l1 ). Also, set numl0 = the number of nonempty columns of U. --------------------------------------------------------------- */ LU = 0; LL = LUSOL->lena+1; #ifdef ClassicHamaxR LM = LENA2+1; #else LM = LL; #endif LTOPL = LL-LENL-LENU; LROW = LENU; for(K = 1; K <= NRANK; K++) { I = LUSOL->ip[K]; LENUK = -LUSOL->lenr[I]; LUSOL->lenr[I] = LENUK; J = LUSOL->iq[K]; LENLK = -LUSOL->lenc[J]-1; if(LENLK>0) { NUML0++; LUSOL->iqloc[NUML0] = LENLK; } if(LU+LENUKa[LL] = LUSOL->a[LM]; LUSOL->indc[LL] = LUSOL->indc[LM]; LUSOL->indr[LL] = LUSOL->indr[LM]; } } else { /* ========================================================= There is no room for ( uk ) yet. We have to right-shift the whole of the remaining LU file. Note that ( lk ) ends up in the correct place. ========================================================= */ LLSAVE = LL-LENLK; NMOVE = LM-LTOPL; for(IDUMMY = 1; IDUMMY <= NMOVE; IDUMMY++) { LL--; LM--; LUSOL->a[LL] = LUSOL->a[LM]; LUSOL->indc[LL] = LUSOL->indc[LM]; LUSOL->indr[LL] = LUSOL->indr[LM]; } LTOPL = LL; LL = LLSAVE; LM = LL; } /* ====================================================== Left-shift ( uk ). ====================================================== */ LUSOL->locr[I] = LU+1; L2 = LM-1; LM = LM-LENUK; for(L = LM; L <= L2; L++) { LU = LU+1; LUSOL->a[LU] = LUSOL->a[L]; LUSOL->indr[LU] = LUSOL->indr[L]; } } /* --------------------------------------------------------------- Save the lengths of the nonempty columns of L, and initialize locc(j) for the LU update routines. --------------------------------------------------------------- */ for(K = 1; K <= NUML0; K++) { LUSOL->lenc[K] = LUSOL->iqloc[K]; } for(J = 1; J <= LUSOL->n; J++) { LUSOL->locc[J] = 0; } /* --------------------------------------------------------------- Test for singularity. lu6chk sets nsing, jsing, jumin, Lmax, Umax, DUmax, DUmin (including entries from the dense LU). inform = 1 if there are singularities (nsing gt 0). --------------------------------------------------------------- */ LU6CHK(LUSOL, 1,LUSOL->lena,INFORM); NSING = LUSOL->luparm[LUSOL_IP_SINGULARITIES]; JSING = LUSOL->luparm[LUSOL_IP_SINGULARINDEX]; JUMIN = LUSOL->luparm[LUSOL_IP_COLINDEX_DUMIN]; LMAX = LUSOL->parmlu[LUSOL_RP_MAXMULT_L]; UMAX = LUSOL->parmlu[LUSOL_RP_MAXELEM_U]; DUMAX = LUSOL->parmlu[LUSOL_RP_MAXELEM_DIAGU]; DUMIN = LUSOL->parmlu[LUSOL_RP_MINELEM_DIAGU]; } else { /* --------------------------------------------------------------- keepLU = 0. L and U were not kept, just the diagonals of U. lu1fac will probably be called again soon with keepLU = .true. 11 Mar 2001: lu6chk revised. We can call it with keepLU = 0, but we want to keep Lmax, Umax from lu1fad. 05 May 2002: Allow for TCP with new lu1DCP. Diag(U) starts below lena2, not lena. Need lena2 in next line. --------------------------------------------------------------- */ #ifdef ClassicHamaxR LU6CHK(LUSOL, 1,LENA2,INFORM); #else LU6CHK(LUSOL, 1,LUSOL->lena,INFORM); #endif NSING = LUSOL->luparm[LUSOL_IP_SINGULARITIES]; JSING = LUSOL->luparm[LUSOL_IP_SINGULARINDEX]; JUMIN = LUSOL->luparm[LUSOL_IP_COLINDEX_DUMIN]; DUMAX = LUSOL->parmlu[LUSOL_RP_MAXELEM_DIAGU]; DUMIN = LUSOL->parmlu[LUSOL_RP_MINELEM_DIAGU]; } goto x990; /* ------------ Error exits. ------------ */ x930: *INFORM = LUSOL_INFORM_ADIMERR; if(LPRINT>=LUSOL_MSG_SINGULARITY) LUSOL_report(LUSOL, 0, "lu1fac error...\nentry a[%d] has an illegal row (%d) or column (%d) index\n", LERR,LUSOL->indc[LERR],LUSOL->indr[LERR]); goto x990; x940: *INFORM = LUSOL_INFORM_ADUPLICATE; if(LPRINT>=LUSOL_MSG_SINGULARITY) LUSOL_report(LUSOL, 0, "lu1fac error...\nentry a[%d] is a duplicate with indeces indc=%d, indr=%d\n", LERR,LUSOL->indc[LERR],LUSOL->indr[LERR]); goto x990; x970: *INFORM = LUSOL_INFORM_ANEEDMEM; if(LPRINT>=LUSOL_MSG_SINGULARITY) LUSOL_report(LUSOL, 0, "lu1fac error...\ninsufficient storage; increase lena from %d to at least %d\n", LUSOL->lena, MINLEN); goto x990; x980: *INFORM = LUSOL_INFORM_FATALERR; if(LPRINT>=LUSOL_MSG_SINGULARITY) LUSOL_report(LUSOL, 0, "lu1fac error...\nfatal bug (sorry --- this should never happen)\n"); goto x990; x985: *INFORM = LUSOL_INFORM_NOPIVOT; if(LPRINT>=LUSOL_MSG_SINGULARITY) LUSOL_report(LUSOL, 0, "lu1fac error...\nTSP used but diagonal pivot could not be found\n"); /* Finalize and store output parameters. */ x990: LUSOL->nelem = NELEM0; LUSOL->luparm[LUSOL_IP_SINGULARITIES] = NSING; LUSOL->luparm[LUSOL_IP_SINGULARINDEX] = JSING; LUSOL->luparm[LUSOL_IP_MINIMUMLENA] = MINLEN; LUSOL->luparm[LUSOL_IP_UPDATECOUNT] = 0; LUSOL->luparm[LUSOL_IP_RANK_U] = NRANK; LUSOL->luparm[LUSOL_IP_COLCOUNT_DENSE1] = NDENS1; LUSOL->luparm[LUSOL_IP_COLCOUNT_DENSE2] = NDENS2; LUSOL->luparm[LUSOL_IP_COLINDEX_DUMIN] = JUMIN; LUSOL->luparm[LUSOL_IP_COLCOUNT_L0] = NUML0; LUSOL->luparm[LUSOL_IP_ROWCOUNT_L0] = 0; LUSOL->luparm[LUSOL_IP_NONZEROS_L0] = LENL; LUSOL->luparm[LUSOL_IP_NONZEROS_U0] = LENU; LUSOL->luparm[LUSOL_IP_NONZEROS_L] = LENL; LUSOL->luparm[LUSOL_IP_NONZEROS_U] = LENU; LUSOL->luparm[LUSOL_IP_NONZEROS_ROW] = LROW; LUSOL->luparm[LUSOL_IP_MARKOWITZ_MERIT] = MERSUM; LUSOL->luparm[LUSOL_IP_TRIANGROWS_U] = NUTRI; LUSOL->luparm[LUSOL_IP_TRIANGROWS_L] = NLTRI; LUSOL->parmlu[LUSOL_RP_MAXELEM_A] = AMAX; LUSOL->parmlu[LUSOL_RP_MAXMULT_L] = LMAX; LUSOL->parmlu[LUSOL_RP_MAXELEM_U] = UMAX; LUSOL->parmlu[LUSOL_RP_MAXELEM_DIAGU] = DUMAX; LUSOL->parmlu[LUSOL_RP_MINELEM_DIAGU] = DUMIN; LUSOL->parmlu[LUSOL_RP_MAXELEM_TCP] = AKMAX; AGRWTH = AKMAX/(AMAX+LUSOL_SMALLNUM); UGRWTH = UMAX/(AMAX+LUSOL_SMALLNUM); if(TPP) GROWTH = UGRWTH; /* TRP or TCP or TSP */ else GROWTH = AGRWTH; LUSOL->parmlu[LUSOL_RP_GROWTHRATE] = GROWTH; LUSOL->luparm[LUSOL_IP_FTRANCOUNT] = 0; LUSOL->luparm[LUSOL_IP_BTRANCOUNT] = 0; /* ------------------------------------------------------------------ Set overall status variable. ------------------------------------------------------------------ */ LUSOL->luparm[LUSOL_IP_INFORM] = *INFORM; if(*INFORM == LUSOL_INFORM_NOMEMLEFT) LUSOL_report(LUSOL, 0, "lu1fac error...\ninsufficient memory available\n"); /* ------------------------------------------------------------------ Print statistics for the LU factors. ------------------------------------------------------------------ */ NCP = LUSOL->luparm[LUSOL_IP_COMPRESSIONS_LU]; CONDU = DUMAX/MAX(DUMIN,LUSOL_SMALLNUM); DINCR = (LENL+LENU)-LUSOL->nelem; DINCR = (DINCR*100)/MAX(DELEM,ONE); AVGMER = MERSUM; AVGMER = AVGMER/DM; NBUMP = LUSOL->m-NUTRI-NLTRI; if(LPRINT>=LUSOL_MSG_STATISTICS) { if(TPP) { LUSOL_report(LUSOL, 0, "Merit %g %d %d %d %g %d %d %g %g %d %d %d\n", AVGMER,LENL,LENL+LENU,NCP,DINCR,NUTRI,LENU, LTOL,UMAX,UGRWTH,NLTRI,NDENS1,LMAX); } else { LUSOL_report(LUSOL, 0, "Merit %s %g %d %d %d %g %d %d %g %g %d %d %d %g %g\n", LUSOL_pivotLabel(LUSOL), AVGMER,LENL,LENL+LENU,NCP,DINCR,NUTRI,LENU, LTOL,UMAX,UGRWTH,NLTRI,NDENS1,LMAX,AKMAX,AGRWTH); } LUSOL_report(LUSOL, 0, "bump%9d dense2%7d DUmax%g DUmin%g conDU%g\n", NBUMP,NDENS2,DUMAX,DUMIN,CONDU); } } MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/sherman5_rhs1.mtx0000664000175000017500000016462210354206632022555 0ustar lauerlauer%%MatrixMarket matrix array real general % RBTitle: 1U FULLY IMPLICIT BLACK OIL SIMULATOR 16 BY 23 BY 3 GRID, THREE UNK % RBKey: SHERMAN5 % Right-hand-side: 1 3312 1 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 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-1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 720 721 722 723 724 725 726 727 728 729 730 731 732 733 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1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 1.00000000D+00 MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/myblas.h0000664000175000017500000001271411141443436020776 0ustar lauerlauer#ifndef HEADER_myblas #define HEADER_myblas /* ************************************************************************ */ /* BLAS function interface with local and external loadable versions */ /* Author: Kjell Eikland */ /* Version: Initial version spring 2004 */ /* Licence: LGPL */ /* ************************************************************************ */ /* Changes: 19 September 2004 Moved function pointer variable */ /* declarations from myblas.h to myblas.c */ /* to avoid linker problems with the Mac. */ /* 20 April 2005 Modified all double types to REAL to self- */ /* adjust to global settings. Note that BLAS */ /* as of now does not have double double. */ /* 15 December 2005 Added idamin() */ /* ************************************************************************ */ #define BLAS_BASE 1 #define UseMacroVector #define LoadableBlasLib /* ************************************************************************ */ /* Include necessary libraries */ /* ************************************************************************ */ #include "commonlib.h" #ifdef LoadableBlasLib #if (defined WIN32) || (defined WIN64) #include #else #include #endif #endif #ifdef __cplusplus extern "C" { #endif /* ************************************************************************ */ /* BLAS functions */ /* ************************************************************************ */ #ifndef BLAS_CALLMODEL #if (defined WIN32) || (defined WIN64) #define BLAS_CALLMODEL _cdecl #else #define BLAS_CALLMODEL #endif #endif typedef void (BLAS_CALLMODEL BLAS_dscal_func) (int *n, REAL *da, REAL *dx, int *incx); typedef void (BLAS_CALLMODEL BLAS_dcopy_func) (int *n, REAL *dx, int *incx, REAL *dy, int *incy); typedef void (BLAS_CALLMODEL BLAS_daxpy_func) (int *n, REAL *da, REAL *dx, int *incx, REAL *dy, int *incy); typedef void (BLAS_CALLMODEL BLAS_dswap_func) (int *n, REAL *dx, int *incx, REAL *dy, int *incy); typedef double (BLAS_CALLMODEL BLAS_ddot_func) (int *n, REAL *dx, int *incx, REAL *dy, int *incy); typedef int (BLAS_CALLMODEL BLAS_idamax_func)(int *n, REAL *x, int *is); typedef int (BLAS_CALLMODEL BLAS_idamin_func)(int *n, REAL *x, int *is); typedef void (BLAS_CALLMODEL BLAS_dload_func) (int *n, REAL *da, REAL *dx, int *incx); typedef double (BLAS_CALLMODEL BLAS_dnormi_func)(int *n, REAL *x); #ifndef __WINAPI #if (defined WIN32) || (defined WIN64) #define __WINAPI WINAPI #else #define __WINAPI #endif #endif void init_BLAS(void); MYBOOL is_nativeBLAS(void); MYBOOL load_BLAS(char *libname); MYBOOL unload_BLAS(void); /* ************************************************************************ */ /* User-callable BLAS definitions (C base 1) */ /* ************************************************************************ */ void dscal ( int n, REAL da, REAL *dx, int incx ); void dcopy ( int n, REAL *dx, int incx, REAL *dy, int incy ); void daxpy ( int n, REAL da, REAL *dx, int incx, REAL *dy, int incy ); void dswap ( int n, REAL *dx, int incx, REAL *dy, int incy ); REAL ddot ( int n, REAL *dx, int incx, REAL *dy, int incy ); int idamax( int n, REAL *x, int is ); int idamin( int n, REAL *x, int is ); void dload ( int n, REAL da, REAL *dx, int incx ); REAL dnormi( int n, REAL *x ); /* ************************************************************************ */ /* Locally implemented BLAS functions (C base 0) */ /* ************************************************************************ */ void BLAS_CALLMODEL my_dscal ( int *n, REAL *da, REAL *dx, int *incx ); void BLAS_CALLMODEL my_dcopy ( int *n, REAL *dx, int *incx, REAL *dy, int *incy ); void BLAS_CALLMODEL my_daxpy ( int *n, REAL *da, REAL *dx, int *incx, REAL *dy, int *incy ); void BLAS_CALLMODEL my_dswap ( int *n, REAL *dx, int *incx, REAL *dy, int *incy ); REAL BLAS_CALLMODEL my_ddot ( int *n, REAL *dx, int *incx, REAL *dy, int *incy ); int BLAS_CALLMODEL my_idamax( int *n, REAL *x, int *is ); int BLAS_CALLMODEL my_idamin( int *n, REAL *x, int *is ); void BLAS_CALLMODEL my_dload ( int *n, REAL *da, REAL *dx, int *incx ); REAL BLAS_CALLMODEL my_dnormi( int *n, REAL *x ); /* ************************************************************************ */ /* Subvector and submatrix access routines (Fortran compatibility) */ /* ************************************************************************ */ #ifdef UseMacroVector #define subvec(item) (item - 1) #else int subvec( int item ); #endif int submat( int nrowb, int row, int col ); int posmat( int nrowb, int row, int col ); /* ************************************************************************ */ /* Randomization functions */ /* ************************************************************************ */ void randomseed(int *seeds); void randomdens( int n, REAL *x, REAL r1, REAL r2, REAL densty, int *seeds); void ddrand( int n, REAL *x, int incx, int *seeds ); #ifdef __cplusplus } #endif #endif MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/hbio.h0000664000175000017500000000516611141443433020430 0ustar lauerlauer#ifndef IOHB_H #define IOHB_H #include #include #include #ifdef __cplusplus extern "C" { #endif int readHB_info(const char* filename, int* M, int* N, int* nz, char** Type, int* Nrhs); int readHB_header(FILE* in_file, char* Title, char* Key, char* Type, int* Nrow, int* Ncol, int* Nnzero, int* Nrhs, int* Nrhsix, char* Ptrfmt, char* Indfmt, char* Valfmt, char* Rhsfmt, int* Ptrcrd, int* Indcrd, int* Valcrd, int* Rhscrd, char *Rhstype); int readHB_mat_double(const char* filename, int colptr[], int rowind[], double val[]); int readHB_newmat_double(const char* filename, int* M, int* N, int* nonzeros, int** colptr, int** rowind, double** val); int readHB_aux_double(const char* filename, const char AuxType, double b[]); int readHB_newaux_double(const char* filename, const char AuxType, double** b); int writeHB_mat_double(const char* filename, int M, int N, int nz, const int colptr[], const int rowind[], const double val[], int Nrhs, const double rhs[], const double guess[], const double exact[], const char* Title, const char* Key, const char* Type, char* Ptrfmt, char* Indfmt, char* Valfmt, char* Rhsfmt, const char* Rhstype); int readHB_mat_char(const char* filename, int colptr[], int rowind[], char val[], char* Valfmt); int readHB_newmat_char(const char* filename, int* M, int* N, int* nonzeros, int** colptr, int** rowind, char** val, char** Valfmt); int readHB_aux_char(const char* filename, const char AuxType, char b[]); int readHB_newaux_char(const char* filename, const char AuxType, char** b, char** Rhsfmt); int writeHB_mat_char(const char* filename, int M, int N, int nz, const int colptr[], const int rowind[], const char val[], int Nrhs, const char rhs[], const char guess[], const char exact[], const char* Title, const char* Key, const char* Type, char* Ptrfmt, char* Indfmt, char* Valfmt, char* Rhsfmt, const char* Rhstype); int ParseIfmt(char* fmt, int* perline, int* width); int ParseRfmt(char* fmt, int* perline, int* width, int* prec, int* flag); void IOHBTerminate(char* message); #ifdef __cplusplus } #endif #endif MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/lusolio.c0000664000175000017500000001615111141443435021166 0ustar lauerlauer #include #include #include "mmio.h" #include "hbio.h" #include "lusolio.h" /* Utility routines to read matrix files in the Coordinate Text File format*/ MYBOOL ctf_read_A(char *filename, int maxm, int maxn, int maxnz, int *m, int *n, int *nnzero, int *iA, int *jA, REAL *Aij) { FILE *iofile; int eof; char buffer[100]; int k, i, j; REAL Ak; MYBOOL filldata; *nnzero = 0; *m = 0; *n = 0; iofile = fopen(filename, "r" ); if(iofile == NULL) { printf("A file %s does not exist\n", filename); return( FALSE ); } filldata = (MYBOOL) !((iA == NULL) && (jA == NULL) && (Aij == NULL)); eof = TRUE; for (k = 1; k <= maxnz; k++) { eof = feof(iofile); if(eof) break; eof = fscanf(iofile, "%d %d %s", &i, &j, buffer); if(eof == 0 || eof == EOF || i <= 0 || j <= 0 || strlen(buffer) == 0) break; Ak = atof(buffer); (*nnzero)++; if (filldata) { iA[k] = i; jA[k] = j; Aij[k] = Ak; } if (i > *m) *m = i; if (j > *n) *n = j; } fclose( iofile ); if(!eof) { printf("Too much data in A file. Increase maxnz\n"); printf("Current maxnz = %d\n", maxnz); return( FALSE ); } printf("A read successfully\n"); printf("m = %d n = %d nnzero = %d\n", *m, *n, *nnzero); if (*m > maxm || *n > maxn) { printf("However, matrix dimensions exceed maxm or maxn\n"); return( FALSE ); } return( TRUE ); } MYBOOL ctf_size_A(char *filename, int *m, int *n, int *nnzero) { int maxint = 200000000; return( ctf_read_A(filename, maxint, maxint, maxint, m, n, nnzero, NULL, NULL, NULL) ); } MYBOOL ctf_read_b(char *filename, int m, REAL *b) { FILE *iofile; int eof; char buffer[100]; int i; iofile = fopen(filename, "r"); if(iofile == NULL) { printf("b file %s does not exist\n", filename); return( FALSE ); } for (i = 1; i <= m; i++) { if(feof(iofile)) goto x350; eof = fscanf(iofile, "%s", buffer); if(eof == 0 || eof == EOF) goto x350; b[i] = atof(buffer); } fclose( iofile ); printf("b read successfully\n"); return( TRUE ); x350: fclose( iofile ); printf("Not enough data in b file.\n"); return( FALSE ); } /* Utility routines to read matrix files in the MatrixMarket format*/ #define mmf_recsize 255 MYBOOL mmf_read_A(char *filename, int maxM, int maxN, int maxnz, int *M, int *N, int *nz, int *iA, int *jA, REAL *Aij) { MM_typecode matcode; FILE *f; int i, k, ret_code, ival, jval; REAL Aval; MYBOOL status = FALSE, ispat, filldata; char buf[mmf_recsize]; f = fopen(filename, "r"); if(f == NULL) return( status ); if(mm_read_banner(f, &matcode) != 0) { printf("Could not process Matrix Market banner.\n"); goto x900; } /* Screen matrix types since LUSOL only supports a subset of the Matrix Market data types. */ if(mm_is_complex(matcode) || mm_is_pattern(matcode)) { printf("Sorry, this application does not support "); printf("Market Market type: [%s]\n", mm_typecode_to_str(matcode)); goto x900; } /* Verify that we have sufficient array storage */ filldata = (MYBOOL) !((iA == NULL) && (jA == NULL) && (Aij == NULL)); if(filldata && maxN > 1 && jA == NULL) { printf("Market Market insufficient array storage specified\n"); goto x900; } /* Find out size of sparse matrix .... */ ret_code = mm_read_mtx_crd_size(f, M, N, nz); if(ret_code != 0 || !filldata || (*M > maxM) || (*N > maxN) || (*nz > maxnz)) { status = !filldata; goto x900; } /* NOTE: when reading in doubles, ANSI C requires the use of the "l" */ /* specifier as in "%lg", "%lf", "%le", otherwise errors will occur */ /* (ANSI C X3.159-1989, Sec. 4.9.6.2, p. 136 lines 13-15) */ /* Read dense matrix in column order */ ispat = (MYBOOL) mm_is_pattern(matcode); k = 1; if(mm_is_dense(matcode)) { maxN = MIN(maxN, *N); for (jval = 1; jval <= maxN; jval++) { for (i = 1; i <= *M; i++) { if(fgets(buf, mmf_recsize-1, f) == NULL) break; if(sscanf(buf, "%lg\n", &Aval) == 0) break; if(Aval != 0) { if(iA != NULL) iA[k] = i; if(jA != NULL) jA[k] = jval; /* Make sure we handle dense vector reading properly */ if(iA == NULL && jA == NULL) Aij[i] = Aval; else Aij[k] = Aval; k++; } } } } /* Read sparse matrix by coordinate */ else { for (i = 1; i <= *nz; i++) { if(fgets(buf, mmf_recsize-1, f) == NULL) break; if(buf[0] == '%') continue; if(ispat) { if(sscanf(buf, "%d %d\n", &ival, &jval) == 0) continue; Aij[k] = 1.0; } else if(sscanf(buf, "%d %d %lg\n", &ival, &jval, &Aval) == 0) continue; /* Check if it is a nonzero and we are within column dimension */ if(Aval != 0 && jval <= maxN) { Aij[k] = Aval; if(iA != NULL) iA[k] = ival; if(jA != NULL) jA[k] = jval; k++; } } } *nz = k - 1; /* Handle case where only the lower triangular parts are given */ if(!mm_is_general(matcode)) { if((M != N) || (maxN != maxM) || (2*(*nz) > maxnz)) { printf("Market Market cannot fill in symmetry data\n"); goto x900; } ispat = mm_is_skew(matcode); for(i = 1; i <= *nz; i++) { iA[k] = jA[i]; jA[k] = iA[i]; if(ispat) Aij[k] = -Aij[i]; else Aij[k] = Aij[i]; k++; } *nz = k - 1; } status = TRUE; /* Finish up */ x900: fclose( f ); return( status ); } MYBOOL mmf_size_A(char *filename, int *M, int *N, int *nz) { int maxint = 200000000; return( mmf_read_A(filename, maxint, maxint, maxint, M, N, nz, NULL, NULL, NULL) ); } MYBOOL mmf_read_b(char *filename, int m, REAL *b) { int im, jn, nnzero; return( mmf_read_A(filename, m, 1, m, &im, &jn, &nnzero, NULL, NULL, b)); } /* Utility routines to read matrix files in Harwell-Boeing format*/ MYBOOL hbf_read_A(char *filename, int maxM, int maxN, int maxnz, int *M, int *N, int *nz, int *iA, int *jA, REAL *Aij) { MYBOOL success; success = hbf_size_A(filename, M, N, nz); if(!success) return( success ); Aij[1] = 0; success = (MYBOOL) readHB_mat_double(filename, jA, iA-1, Aij-1); /* Test if we have a pattern matrix and fill it with all zeros */ if(Aij[1] == 0) { int i; for(i = 1; i <= *nz; i++) Aij[i] = 1; } /* Expand the column nz counts to triplet format */ if(success) { int i, j, ii, k; k = *nz; for(j = *N; j > 0; j--) { ii = jA[j]; for(i = jA[j-1]; i < ii; i++, k--) jA[k] = j; } } return( success ); } MYBOOL hbf_size_A(char *filename, int *M, int *N, int *nz) { int Nrhs; char *Type; return( (MYBOOL) readHB_info(filename, M, N, nz, &Type, &Nrhs) ); } MYBOOL hbf_read_b(char *filename, int m, REAL *b) { return( (MYBOOL) readHB_aux_double(filename, 'F', b) ); /* Same format as matrix */ } MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/LUSOL-overview.txt0000664000175000017500000001262311141374613022640 0ustar lauerlauer Notes for Contribution of LUSOL to COIN-OR May 2004 Introduction ============ LUSOL maintains sparse LU factors of a square or rectangular sparse matrix. It includes a Basis Factorization Package (BFP) suitable for implementing simplex and reduced-gradient methods for optimization. It is a set of routines written in ANSI C (adapted from the original Fortran 77 version). LUSOL includes the following features: - A Markowitz-based sparse LU factorization for square, rectangular and possibly singular matrices. - Three options for balancing sparsity and stability: Threshold Partial/Rook/Complete Pivoting (TPP, TRP, TCP). - Rank-revealing properties. TRP and TCP are intended for detecting singularities. - Dynamic storage allocation (C version only). - Stable column replacement as in the method of Bartels and Golub. - Other stable updates: add, replace, or delete row or column (currently F77 version only). - Implementation into an easy-to-use BFP API (C version only). Implementation ============== The Factor routine is similar to the classical Markowitz routines MA28 and LA05 in the Harwell Subroutine Library. The source matrix nonzeros are stored column-wise with the largest entry at the top of each column. Internally, the structure is also accessible row-wise. All entries in a particular column or row are held in contiguous storage. Fill is accommodated by moving a column or row to the beginning of free storage. Occasional compressions recover storage. This scheme is effective for column-oriented TPP. When the remaining matrix reaches a specified density, the factors are completed using dense processing. TRP uses an additional vector of storage to maintain the largest element in each remaining row. TCP uses a heap structure to hold the largest element in each column. The largest element in the remaining matrix is then available at the top of the heap. The final L is stored column-wise (and never changed). The final U is stored row-wise as a triangular or trapezoidal sparse matrix. Column replacements are implemented using a forward sweep of 2-by-2 stabilized elimination matrices. L is updated in product form. U is updated explicitly. The other updates use either forward or backward sweeps. They tend to generate more nonzeros than column replacement. Both the F77 and C versions contain extensive comments, method and implementational information as part of the code. The C version contains a record-based wrapper for the data. Function calls have been simplified by including references to this structure. New maintenance routines enable dynamic instance creation and destruction, and simplifies access to the most frequently used functions. The LUSOL C library is multi-instance and fully re-entrant. All control and output parameters have been given long descriptive names for usability. Benefits ======== Rank-revealing properties and rectangular factors (and updates) have not previously been available in sparse LU software. With sensible parameter settings and reasonably scaled data, all routines are numerically stable. The updates may be called hundreds of times, and the decision to refactorize can be based on sparsity considerations alone. In the Factor routine, rook pivoting (TRP) gives reliable rank determination without catastrophic degradation in sparsity or speed. Complete pivoting (TCP) is included for moderate-sized matrices and for checking pathological cases (but the factors tend to be substantially more dense). To conserve storage, one may request only the row and column pivot orders. The factors are discarded as they are computed. This is useful for basis repair, or for selecting a basis from a rectangular matrix. Known Inefficiencies ==================== LUSOL is usually efficient on sparse matrices with dimensions up to about 100,000 (but not millions). In the Factor routine, row and column lists must be updated each time a row and column is eliminated. Deleting the pivot row and column is inefficient if the original matrix contains unusually dense rows or columns. For TPP, dense columns could be kept aside and incorporated at the end via updates (but dense rows remain a difficulty). For TRP and TCP, all rows and columns must be present to achieve the required numerical properties. For TRP, the current bottleneck is updating the vector containing the largest element in each row. One solution would be to include the matrix nonzeros in the row structure (but this carries its own cost). For TCP, the heap structure is already efficient, but the dense factors (and the extended searching for acceptable pivots) are unavoidable expenses. The triangular Solve routines do not take full of advantage of sparse right-hand sides. Gilbert and Peierls have shown how to solve Lx = (sparse b) efficiently if L is stored column-wise. Their approach could therefore be implemented in LUSOL for solves with L and U(transpose). Solves with L(transpose) and U would need a second copy of L and U. Original Reference ================== P. E. Gill, W. Murray, M. A. Saunders and M. H. Wright, Maintaining LU factors of a general sparse matrix, Linear Algebra and its Applications 88/89, 239-270 (1987). Maintainers =========== F77 version: Michael Saunders (saunders@stanford.edu). C version: Kjell Eikland (kjell.eikland@broadpark.no). Contributors ============ Philip Gill, Walter Murray, Margaret Wright, Michael O'Sullivan. MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/lusol6u.c0000664000175000017500000001144311141443434021107 0ustar lauerlauer /* Create a column-based version of U. This makes it possible to solve Ux=h (ftran) faster for sparse h, since we only run down the rows of U (columns of U') for which the corresponding entry in h is non-zero. */ MYBOOL LU1U0(LUSOLrec *LUSOL, LUSOLmat **mat, int *inform) { MYBOOL status = FALSE; int K, L, LL, LENU, NUMU, J; int *lsumc; /* Assume success */ *inform = LUSOL_INFORM_LUSUCCESS; /* Check if there is anything worth doing */ if(mat == NULL) return( status ); if(*mat != NULL) LUSOL_matfree(mat); NUMU = LUSOL->luparm[LUSOL_IP_RANK_U]; LENU = LUSOL->luparm[LUSOL_IP_NONZEROS_U]; if((NUMU == 0) || (LENU == 0) || (LUSOL->luparm[LUSOL_IP_ACCELERATION] == LUSOL_BASEORDER) || ((LUSOL->luparm[LUSOL_IP_ACCELERATION] & LUSOL_ACCELERATE_U) == 0)) return( status ); /* Allocate temporary array */ lsumc = (int *) LUSOL_CALLOC((LUSOL->n+1), sizeof(*lsumc)); if(lsumc == NULL) { *inform = LUSOL_INFORM_NOMEMLEFT; return( status ); } /* Compute non-zero counts by permuted column index (order is unimportant) */ for(L = 1; L <= LENU; L++) { J = LUSOL->indr[L]; lsumc[J]++; } /* Check if we should apply "smarts" before proceeding to the column matrix creation */ if((LUSOL->luparm[LUSOL_IP_ACCELERATION] & LUSOL_AUTOORDER) && ((REAL) sqrt((REAL) NUMU/LENU) > LUSOL->parmlu[LUSOL_RP_SMARTRATIO])) goto Finish; /* We are Ok to create the new matrix object */ *mat = LUSOL_matcreate(LUSOL->n, LENU); if(*mat == NULL) { *inform = LUSOL_INFORM_NOMEMLEFT; goto Finish; } /* Cumulate row counts to get vector offsets; first column is leftmost (stick with Fortran array offset for consistency) */ (*mat)->lenx[0] = 1; for(K = 1; K <= LUSOL->n; K++) { (*mat)->lenx[K] = (*mat)->lenx[K-1] + lsumc[K]; lsumc[K] = (*mat)->lenx[K-1]; } /* Map the matrix into column order by permuted index; Note: The first permuted column is located leftmost in the array. The row order is irrelevant, since the indeces will refer to constant / resolved values of V[] during solve. */ for(L = 1; L <= LENU; L++) { J = LUSOL->indr[L]; LL = lsumc[J]++; (*mat)->a[LL] = LUSOL->a[L]; (*mat)->indr[LL] = J; (*mat)->indc[LL] = LUSOL->indc[L]; } /* Pack column starting positions, and set mapper from original index to packed */ J = 0; for(L = 1; L <= LUSOL->n; L++) { K = LUSOL->iq[L]; #if 1 /* Deactivate to produce a full-rank version (implicit unit diagonals) */ if((*mat)->lenx[K] > (*mat)->lenx[K-1]) #endif { J++; (*mat)->indx[J] = K; } } /* Confirm that everything went well */ status = TRUE; /* Clean up */ Finish: FREE(lsumc); return( status ); } /* Solve U w = v based on column-based version of U, constructed by LU1U0 */ void LU6U0_v(LUSOLrec *LUSOL, LUSOLmat *mat, REAL V[], REAL W[], int NZidx[], int *INFORM) { #ifdef DoTraceU0 REAL TEMP; #endif int LEN, I, K, L, L1, NRANK, NRANK1, KLAST; REAL SMALL; register REAL T; #if (defined xxLUSOLFastSolve) && !(defined DoTraceU0) REAL *aptr; int *jptr; #else int J; #endif NRANK = LUSOL->luparm[LUSOL_IP_RANK_U]; SMALL = LUSOL->parmlu[LUSOL_RP_ZEROTOLERANCE]; *INFORM = LUSOL_INFORM_LUSUCCESS; NRANK1 = NRANK+1; /* Find the first nonzero in v(1:nrank), counting backwards. */ for(KLAST = NRANK; KLAST >= 1; KLAST--) { I = LUSOL->ip[KLAST]; if(fabs(V[I])>SMALL) break; } L = LUSOL->n; #ifdef xxLUSOLFastSolve for(K = KLAST+1, jptr = LUSOL->iq+K; K <= L; K++, jptr++) W[*jptr] = ZERO; #else for(K = KLAST+1; K <= L; K++) { J = LUSOL->iq[K]; W[J] = ZERO; } #endif /* Loop over the nz columns of U - from the right, going left. */ for(K = NRANK; K > 0; K--) { I = mat->indx[K]; L = mat->lenx[I]; L1 = mat->lenx[I-1]; LEN = L - L1; T = V[I]; if(fabs(T)<=SMALL) { W[K] = ZERO; continue; } T /= mat->a[L1]; /* Should it be L or L1 ? */ W[K] = T; LEN--; /* ***** This loop could be coded specially. */ #ifdef xxLUSOLFastSolve L--; for(aptr = mat->a+L, jptr = mat->indc+L; LEN > 0; LEN--, aptr--, jptr--) V[*jptr] -= T * (*aptr); #else for(; LEN > 0; LEN--) { L--; J = mat->indc[L]; #ifndef DoTraceL0 V[J] -= T * mat->a[L]; #else TEMP = V[J]; V[J] += T * mat->a[L]; printf("V[%3d] = V[%3d] + L[%d,%d]*V[%3d]\n", J, J, I,J, I); printf("%6g = %6g + %6g*%6g\n", V[J], TEMP, mat->a[L], T); #endif } #endif } /* Compute residual for overdetermined systems. */ T = ZERO; for(K = NRANK1; K <= LUSOL->m; K++) { I = LUSOL->ip[K]; T += fabs(V[I]); } /* Exit. */ if(T>ZERO) *INFORM = LUSOL_INFORM_LUSINGULAR; LUSOL->luparm[LUSOL_IP_INFORM] = *INFORM; LUSOL->parmlu[LUSOL_RP_RESIDUAL_U] = (REAL) T; } MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/sherman5.mtx0000664000175000017500000237163410354206632021625 0ustar lauerlauer%%MatrixMarket matrix coordinate real general 3312 3312 20793 1 1 1.0000000000000e+00 2 2 1.0000000000000e+00 3 3 1.0000000000000e+00 4 4 1.0000000000000e+00 5 5 1.0000000000000e+00 6 6 1.0000000000000e+00 7 7 1.0000000000000e+00 8 8 1.0000000000000e+00 9 9 1.0000000000000e+00 10 10 1.0000000000000e+00 11 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1.0000000000000e+00 3289 3289 1.0000000000000e+00 3290 3290 1.0000000000000e+00 3291 3291 1.0000000000000e+00 3292 3292 1.0000000000000e+00 3293 3293 1.0000000000000e+00 3294 3294 1.0000000000000e+00 3295 3295 1.0000000000000e+00 3296 3296 1.0000000000000e+00 3297 3297 1.0000000000000e+00 3298 3298 1.0000000000000e+00 3299 3299 1.0000000000000e+00 3300 3300 1.0000000000000e+00 3301 3301 1.0000000000000e+00 3302 3302 1.0000000000000e+00 3303 3303 1.0000000000000e+00 3304 3304 1.0000000000000e+00 3305 3305 1.0000000000000e+00 3306 3306 1.0000000000000e+00 3307 3307 1.0000000000000e+00 3308 3308 1.0000000000000e+00 3309 3309 1.0000000000000e+00 3310 3310 1.0000000000000e+00 3311 3311 1.0000000000000e+00 3312 3312 1.0000000000000e+00 MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/lusol6a.c0000664000175000017500000006740311141443434021072 0ustar lauerlauer /* ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ File lusol6a lu6sol lu6L lu6Lt lu6U Lu6Ut lu6LD lu6chk ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ 26 Apr 2002: lu6 routines put into a separate file. 15 Dec 2002: lu6sol modularized via lu6L, lu6Lt, lu6U, lu6Ut. lu6LD implemented to allow solves with LDL' or L|D|L'. 15 Dec 2002: Current version of lusol6a.f. ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ */ /* ================================================================== lu6chk looks at the LU factorization A = L*U. If mode = 1, lu6chk is being called by lu1fac. (Other modes not yet implemented.) ------------------------------------------------------------------ The important input parameters are lprint = luparm(2) keepLU = luparm(8) Utol1 = parmlu(4) Utol2 = parmlu(5) and the significant output parameters are inform = luparm(10) nsing = luparm(11) jsing = luparm(12) jumin = luparm(19) Lmax = parmlu(11) Umax = parmlu(12) DUmax = parmlu(13) DUmin = parmlu(14) and w(*). Lmax and Umax return the largest elements in L and U. DUmax and DUmin return the largest and smallest diagonals of U (excluding diagonals that are exactly zero). In general, w(j) is set to the maximum absolute element in the j-th column of U. However, if the corresponding diagonal of U is small in absolute terms or relative to w(j) (as judged by the parameters Utol1, Utol2 respectively), then w(j) is changed to - w(j). Thus, if w(j) is not positive, the j-th column of A appears to be dependent on the other columns of A. The number of such columns, and the position of the last one, are returned as nsing and jsing. Note that nrank is assumed to be set already, and is not altered. Typically, nsing will satisfy nrank + nsing = n, but if Utol1 and Utol2 are rather large, nsing > n - nrank may occur. If keepLU = 0, Lmax and Umax are already set by lu1fac. The diagonals of U are in the top of A. Only Utol1 is used in the singularity test to set w(*). inform = 0 if A appears to have full column rank (nsing = 0). inform = 1 otherwise (nsing .gt. 0). ------------------------------------------------------------------ 00 Jul 1987: Early version. 09 May 1988: f77 version. 11 Mar 2001: Allow for keepLU = 0. 17 Nov 2001: Briefer output for singular factors. 05 May 2002: Comma needed in format 1100 (via Kenneth Holmstrom). 06 May 2002: With keepLU = 0, diags of U are in natural order. They were not being extracted correctly. 23 Apr 2004: TRP can judge singularity better by comparing all diagonals to DUmax. 27 Jun 2004: (PEG) Allow write only if nout .gt. 0. ================================================================== */ #ifdef UseOld_LU6CHK_20040510 void LU6CHK(LUSOLrec *LUSOL, int MODE, int LENA2, int *INFORM) { MYBOOL KEEPLU; int I, J, JUMIN, K, L, L1, L2, LENL, LPRINT, NDEFIC, NRANK; REAL AIJ, DIAG, DUMAX, DUMIN, LMAX, UMAX, UTOL1, UTOL2; LPRINT = LUSOL->luparm[LUSOL_IP_PRINTLEVEL]; KEEPLU = (MYBOOL) (LUSOL->luparm[LUSOL_IP_KEEPLU]!=0); NRANK = LUSOL->luparm[LUSOL_IP_RANK_U]; LENL = LUSOL->luparm[LUSOL_IP_NONZEROS_L]; UTOL1 = LUSOL->parmlu[LUSOL_RP_SMALLDIAG_U]; UTOL2 = LUSOL->parmlu[LUSOL_RP_EPSDIAG_U]; *INFORM = LUSOL_INFORM_LUSUCCESS; LMAX = ZERO; UMAX = ZERO; LUSOL->luparm[LUSOL_IP_SINGULARITIES] = 0; LUSOL->luparm[LUSOL_IP_SINGULARINDEX] = 0; JUMIN = 0; DUMAX = ZERO; DUMIN = LUSOL_BIGNUM; #ifdef LUSOLFastClear MEMCLEAR(LUSOL->w+1, LUSOL->n); #else for(I = 1; I <= LUSOL->n; I++) LUSOL->w[I] = ZERO; #endif if(KEEPLU) { /* -------------------------------------------------------------- Find Lmax. -------------------------------------------------------------- */ for(L = (LENA2+1)-LENL; L <= LENA2; L++) { SETMAX(LMAX,fabs(LUSOL->a[L])); } /* -------------------------------------------------------------- Find Umax and set w(j) = maximum element in j-th column of U. -------------------------------------------------------------- */ for(K = 1; K <= NRANK; K++) { I = LUSOL->ip[K]; L1 = LUSOL->locr[I]; L2 = (L1+LUSOL->lenr[I])-1; for(L = L1; L <= L2; L++) { J = LUSOL->indr[L]; AIJ = fabs(LUSOL->a[L]); SETMAX(LUSOL->w[J],AIJ); SETMAX(UMAX,AIJ); } } /* -------------------------------------------------------------- Negate w(j) if the corresponding diagonal of U is too small in absolute terms or relative to the other elements in the same column of U. Also find DUmax and DUmin, the extreme diagonals of U. -------------------------------------------------------------- */ for(K = 1; K <= LUSOL->n; K++) { J = LUSOL->iq[K]; if(K>NRANK) DIAG = ZERO; else { I = LUSOL->ip[K]; L1 = LUSOL->locr[I]; DIAG = fabs(LUSOL->a[L1]); SETMAX(DUMAX,DIAG); if(DUMIN>DIAG) { DUMIN = DIAG; JUMIN = J; } } if((DIAG<=UTOL1) || (DIAG<=UTOL2*LUSOL->w[J])) { LUSOL_addSingularity(LUSOL, J, INFORM); LUSOL->w[J] = -LUSOL->w[J]; } } LUSOL->parmlu[LUSOL_RP_MAXMULT_L] = LMAX; LUSOL->parmlu[LUSOL_RP_MAXELEM_U] = UMAX; } else { /* -------------------------------------------------------------- keepLU = 0. Only diag(U) is stored. Set w(*) accordingly. -------------------------------------------------------------- */ for(K = 1; K <= LUSOL->n; K++) { J = LUSOL->iq[K]; if(K>NRANK) DIAG = ZERO; else { /* ! diag = abs( diagU(k) ) ! 06 May 2002: Diags are in natural order */ DIAG = fabs(LUSOL->diagU[J]); LUSOL->w[J] = DIAG; SETMAX(DUMAX,DIAG); if(DUMIN>DIAG) { DUMIN = DIAG; JUMIN = J; } } if(DIAG<=UTOL1) { LUSOL_addSingularity(LUSOL, J, INFORM); LUSOL->w[J] = -LUSOL->w[J]; } } } /* ----------------------------------------------------------------- Set output parameters. ----------------------------------------------------------------- */ if(JUMIN==0) DUMIN = ZERO; LUSOL->luparm[LUSOL_IP_COLINDEX_DUMIN] = JUMIN; LUSOL->parmlu[LUSOL_RP_MAXELEM_DIAGU] = DUMAX; LUSOL->parmlu[LUSOL_RP_MINELEM_DIAGU] = DUMIN; /* The matrix has been judged singular. */ if(LUSOL->luparm[LUSOL_IP_SINGULARITIES]>0) { *INFORM = LUSOL_INFORM_LUSINGULAR; NDEFIC = LUSOL->n-NRANK; if(LPRINT>=LUSOL_MSG_SINGULARITY) { LUSOL_report(LUSOL, 0, "Singular(m%cn) rank:%9d n-rank:%8d nsing:%9d\n", relationChar(LUSOL->m, LUSOL->n),NRANK,NDEFIC, LUSOL->luparm[LUSOL_IP_SINGULARITIES]); } } /* Exit. */ LUSOL->luparm[LUSOL_IP_INFORM] = *INFORM; } #else void LU6CHK(LUSOLrec *LUSOL, int MODE, int LENA2, int *INFORM) { MYBOOL KEEPLU, TRP; int I, J, JUMIN, K, L, L1, L2, LENL, LDIAGU, LPRINT, NDEFIC, NRANK; REAL AIJ, DIAG, DUMAX, DUMIN, LMAX, UMAX, UTOL1, UTOL2; LPRINT = LUSOL->luparm[LUSOL_IP_PRINTLEVEL]; KEEPLU = (MYBOOL) (LUSOL->luparm[LUSOL_IP_KEEPLU] != 0); TRP = (MYBOOL) (LUSOL->luparm[LUSOL_IP_PIVOTTYPE] == LUSOL_PIVMOD_TRP); NRANK = LUSOL->luparm[LUSOL_IP_RANK_U]; LENL = LUSOL->luparm[LUSOL_IP_NONZEROS_L]; UTOL1 = LUSOL->parmlu[LUSOL_RP_SMALLDIAG_U]; UTOL2 = LUSOL->parmlu[LUSOL_RP_EPSDIAG_U]; *INFORM = LUSOL_INFORM_LUSUCCESS; LMAX = ZERO; UMAX = ZERO; LUSOL->luparm[LUSOL_IP_SINGULARITIES] = 0; LUSOL->luparm[LUSOL_IP_SINGULARINDEX] = 0; JUMIN = 0; DUMAX = ZERO; DUMIN = LUSOL_BIGNUM; #ifdef LUSOLFastClear MEMCLEAR(LUSOL->w+1, LUSOL->n); #else for(I = 1; I <= LUSOL->n; I++) LUSOL->w[I] = ZERO; #endif if(KEEPLU) { /* -------------------------------------------------------------- Find Lmax. -------------------------------------------------------------- */ for(L = (LENA2+1)-LENL; L <= LENA2; L++) { SETMAX(LMAX,fabs(LUSOL->a[L])); } /* -------------------------------------------------------------- Find Umax and set w(j) = maximum element in j-th column of U. -------------------------------------------------------------- */ for(K = 1; K <= NRANK; K++) { I = LUSOL->ip[K]; L1 = LUSOL->locr[I]; L2 = (L1+LUSOL->lenr[I])-1; for(L = L1; L <= L2; L++) { J = LUSOL->indr[L]; AIJ = fabs(LUSOL->a[L]); SETMAX(LUSOL->w[J],AIJ); SETMAX(UMAX,AIJ); } } LUSOL->parmlu[LUSOL_RP_MAXMULT_L] = LMAX; LUSOL->parmlu[LUSOL_RP_MAXELEM_U] = UMAX; /* -------------------------------------------------------------- Find DUmax and DUmin, the extreme diagonals of U. -------------------------------------------------------------- */ for(K = 1; K <= NRANK; K++) { J = LUSOL->iq[K]; I = LUSOL->ip[K]; L1 = LUSOL->locr[I]; DIAG = fabs(LUSOL->a[L1]); SETMAX( DUMAX, DIAG ); if(DUMIN > DIAG) { DUMIN = DIAG; JUMIN = J; } } } else { /* -------------------------------------------------------------- keepLU = 0. Only diag(U) is stored. Set w(*) accordingly. Find DUmax and DUmin, the extreme diagonals of U. -------------------------------------------------------------- */ LDIAGU = LENA2 - LUSOL->n; for(K = 1; K <= NRANK; K++) { J = LUSOL->iq[K]; DIAG = fabs( LUSOL->a[LDIAGU + J] ); /* are in natural order */ LUSOL->w[J] = DIAG; SETMAX( DUMAX, DIAG ); if(DUMIN > DIAG) { DUMIN = DIAG; JUMIN = J; } } } /* -------------------------------------------------------------- Negate w(j) if the corresponding diagonal of U is too small in absolute terms or relative to the other elements in the same column of U. 23 Apr 2004: TRP ensures that diags are NOT small relative to other elements in their own column. Much better, we can compare all diags to DUmax. -------------------------------------------------------------- */ if((MODE == 1) && TRP) { SETMAX( UTOL1, UTOL2*DUMAX ); } if(KEEPLU) { for(K = 1; K <= LUSOL->n; K++) { J = LUSOL->iq[K]; if(K>NRANK) DIAG = ZERO; else { I = LUSOL->ip[K]; L1 = LUSOL->locr[I]; DIAG = fabs(LUSOL->a[L1]); } if((DIAG<=UTOL1) || (DIAG<=UTOL2*LUSOL->w[J])) { LUSOL_addSingularity(LUSOL, J, INFORM); LUSOL->w[J] = -LUSOL->w[J]; } } } else { /* keepLU = FALSE */ for(K = 1; K <= LUSOL->n; K++) { J = LUSOL->iq[K]; DIAG = LUSOL->w[J]; if(DIAG<=UTOL1) { LUSOL_addSingularity(LUSOL, J, INFORM); LUSOL->w[J] = -LUSOL->w[J]; } } } /* ----------------------------------------------------------------- Set output parameters. ----------------------------------------------------------------- */ if(JUMIN==0) DUMIN = ZERO; LUSOL->luparm[LUSOL_IP_COLINDEX_DUMIN] = JUMIN; LUSOL->parmlu[LUSOL_RP_MAXELEM_DIAGU] = DUMAX; LUSOL->parmlu[LUSOL_RP_MINELEM_DIAGU] = DUMIN; /* The matrix has been judged singular. */ if(LUSOL->luparm[LUSOL_IP_SINGULARITIES]>0) { *INFORM = LUSOL_INFORM_LUSINGULAR; NDEFIC = LUSOL->n-NRANK; if((LUSOL->outstream!=NULL) && (LPRINT>=LUSOL_MSG_SINGULARITY)) { LUSOL_report(LUSOL, 0, "Singular(m%cn) rank:%9d n-rank:%8d nsing:%9d\n", relationChar(LUSOL->m, LUSOL->n),NRANK,NDEFIC, LUSOL->luparm[LUSOL_IP_SINGULARITIES]); } } /* Exit. */ LUSOL->luparm[LUSOL_IP_INFORM] = *INFORM; } #endif /* ------------------------------------------------------------------ Include routines for row-based L0. 20 Apr 2005 Current version - KE. ------------------------------------------------------------------ */ #include "lusol6l0.c" /* ------------------------------------------------------------------ lu6L solves L v = v(input). ------------------------------------------------------------------ 15 Dec 2002: First version derived from lu6sol. 15 Dec 2002: Current version. ------------------------------------------------------------------ */ void LU6L(LUSOLrec *LUSOL, int *INFORM, REAL V[], int NZidx[]) { int JPIV, K, L, L1, LEN, LENL, LENL0, NUML, NUML0; REAL SMALL; register REAL VPIV; #ifdef LUSOLFastSolve REAL *aptr; int *iptr, *jptr; #else int I, J; #endif NUML0 = LUSOL->luparm[LUSOL_IP_COLCOUNT_L0]; LENL0 = LUSOL->luparm[LUSOL_IP_NONZEROS_L0]; LENL = LUSOL->luparm[LUSOL_IP_NONZEROS_L]; SMALL = LUSOL->parmlu[LUSOL_RP_ZEROTOLERANCE]; *INFORM = LUSOL_INFORM_LUSUCCESS; L1 = LUSOL->lena+1; for(K = 1; K <= NUML0; K++) { LEN = LUSOL->lenc[K]; L = L1; L1 -= LEN; JPIV = LUSOL->indr[L1]; VPIV = V[JPIV]; if(fabs(VPIV)>SMALL) { /* ***** This loop could be coded specially. */ #ifdef LUSOLFastSolve L--; for(aptr = LUSOL->a+L, iptr = LUSOL->indc+L; LEN > 0; LEN--, aptr--, iptr--) V[*iptr] += (*aptr) * VPIV; #else for(; LEN > 0; LEN--) { L--; I = LUSOL->indc[L]; V[I] += LUSOL->a[L]*VPIV; } #endif } #ifdef SetSmallToZero else V[JPIV] = 0; #endif } L = (LUSOL->lena-LENL0)+1; NUML = LENL-LENL0; /* ***** This loop could be coded specially. */ #ifdef LUSOLFastSolve L--; for(aptr = LUSOL->a+L, jptr = LUSOL->indr+L, iptr = LUSOL->indc+L; NUML > 0; NUML--, aptr--, jptr--, iptr--) { if(fabs(V[*jptr])>SMALL) V[*iptr] += (*aptr) * V[*jptr]; #ifdef SetSmallToZero else V[*jptr] = 0; #endif } #else for(; NUML > 0; NUML--) { L--; J = LUSOL->indr[L]; if(fabs(V[J])>SMALL) { I = LUSOL->indc[L]; V[I] += LUSOL->a[L]*V[J]; } #ifdef SetSmallToZero else V[J] = 0; #endif } #endif /* Exit. */ LUSOL->luparm[LUSOL_IP_INFORM] = *INFORM; } /* ================================================================== lu6LD assumes lu1fac has computed factors A = LU of a symmetric definite or quasi-definite matrix A, using Threshold Symmetric Pivoting (TSP), luparm(6) = 3, or Threshold Diagonal Pivoting (TDP), luparm(6) = 4. It also assumes that no updates have been performed. In such cases, U = D L', where D = diag(U). lu6LDL returns v as follows: mode 1 v solves L D v = v(input). 2 v solves L|D|v = v(input). ------------------------------------------------------------------ 15 Dec 2002: First version of lu6LD. 15 Dec 2002: Current version. ================================================================== */ void LU6LD(LUSOLrec *LUSOL, int *INFORM, int MODE, REAL V[], int NZidx[]) { int IPIV, K, L, L1, LEN, NUML0; REAL DIAG, SMALL; register REAL VPIV; #ifdef LUSOLFastSolve REAL *aptr; int *jptr; #else int J; #endif /* Solve L D v(new) = v or L|D|v(new) = v, depending on mode. The code for L is the same as in lu6L, but when a nonzero entry of v arises, we divide by the corresponding entry of D or |D|. */ NUML0 = LUSOL->luparm[LUSOL_IP_COLCOUNT_L0]; SMALL = LUSOL->parmlu[LUSOL_RP_ZEROTOLERANCE]; *INFORM = LUSOL_INFORM_LUSUCCESS; L1 = LUSOL->lena+1; for(K = 1; K <= NUML0; K++) { LEN = LUSOL->lenc[K]; L = L1; L1 -= LEN; IPIV = LUSOL->indr[L1]; VPIV = V[IPIV]; if(fabs(VPIV)>SMALL) { /* ***** This loop could be coded specially. */ #ifdef LUSOLFastSolve L--; for(aptr = LUSOL->a+L, jptr = LUSOL->indc+L; LEN > 0; LEN--, aptr--, jptr--) V[*jptr] += (*aptr)*VPIV; #else for(; LEN > 0; LEN--) { L--; J = LUSOL->indc[L]; V[J] += LUSOL->a[L]*VPIV; } #endif /* Find diag = U(ipiv,ipiv) and divide by diag or |diag|. */ L = LUSOL->locr[IPIV]; DIAG = LUSOL->a[L]; if(MODE==2) DIAG = fabs(DIAG); V[IPIV] = VPIV/DIAG; } #ifdef SetSmallToZero else V[IPIV] = 0; #endif } } /* ================================================================== lu6Lt solves L'v = v(input). ------------------------------------------------------------------ 15 Dec 2002: First version derived from lu6sol. 15 Dec 2002: Current version. ================================================================== */ void LU6LT(LUSOLrec *LUSOL, int *INFORM, REAL V[], int NZidx[]) { #ifdef DoTraceL0 REAL TEMP; #endif int K, L, L1, L2, LEN, LENL, LENL0, NUML0; REAL SMALL; register REALXP SUM; register REAL HOLD; #if (defined LUSOLFastSolve) && !(defined DoTraceL0) REAL *aptr; int *iptr, *jptr; #else int I, J; #endif NUML0 = LUSOL->luparm[LUSOL_IP_COLCOUNT_L0]; LENL0 = LUSOL->luparm[LUSOL_IP_NONZEROS_L0]; LENL = LUSOL->luparm[LUSOL_IP_NONZEROS_L]; SMALL = LUSOL->parmlu[LUSOL_RP_ZEROTOLERANCE]; *INFORM = LUSOL_INFORM_LUSUCCESS; L1 = (LUSOL->lena-LENL)+1; L2 = LUSOL->lena-LENL0; /* ***** This loop could be coded specially. */ #if (defined LUSOLFastSolve) && !(defined DoTraceL0) for(L = L1, aptr = LUSOL->a+L1, iptr = LUSOL->indr+L1, jptr = LUSOL->indc+L1; L <= L2; L++, aptr++, iptr++, jptr++) { HOLD = V[*jptr]; if(fabs(HOLD)>SMALL) V[*iptr] += (*aptr)*HOLD; #ifdef SetSmallToZero else V[*jptr] = 0; #endif } #else for(L = L1; L <= L2; L++) { J = LUSOL->indc[L]; HOLD = V[J]; if(fabs(HOLD)>SMALL) { I = LUSOL->indr[L]; V[I] += LUSOL->a[L]*HOLD; } #ifdef SetSmallToZero else V[J] = 0; #endif } #endif /* Do row-based L0 version, if available */ if((LUSOL->L0 != NULL) || ((LUSOL->luparm[LUSOL_IP_BTRANCOUNT] == 0) && LU1L0(LUSOL, &(LUSOL->L0), INFORM))) { LU6L0T_v(LUSOL, LUSOL->L0, V, NZidx, INFORM); } /* Alternatively, do the standard column-based L0 version */ else { /* Perform loop over columns */ for(K = NUML0; K >= 1; K--) { SUM = ZERO; LEN = LUSOL->lenc[K]; L1 = L2+1; L2 += LEN; /* ***** This loop could be coded specially. */ #if (defined LUSOLFastSolve) && !(defined DoTraceL0) for(L = L1, aptr = LUSOL->a+L1, jptr = LUSOL->indc+L1; L <= L2; L++, aptr++, jptr++) SUM += (*aptr) * V[*jptr]; #else for(L = L1; L <= L2; L++) { J = LUSOL->indc[L]; #ifndef DoTraceL0 SUM += LUSOL->a[L]*V[J]; #else TEMP = V[LUSOL->indr[L1]] + SUM; SUM += LUSOL->a[L]*V[J]; printf("V[%3d] = V[%3d] + L[%d,%d]*V[%3d]\n", LUSOL->indr[L1], LUSOL->indr[L1], J,LUSOL->indr[L1], J); printf("%6g = %6g + %6g*%6g\n", V[LUSOL->indr[L1]] + SUM, TEMP, LUSOL->a[L], V[J]); #endif } #endif V[LUSOL->indr[L1]] += (REAL) SUM; } } /* Exit. */ LUSOL->luparm[LUSOL_IP_INFORM] = *INFORM; } void print_L0(LUSOLrec *LUSOL) { int I, J, K, L, L1, L2, LEN, LENL0, NUML0; REAL *denseL0 = (REAL*) calloc(LUSOL->m+1, (LUSOL->n+1)*sizeof(*denseL0)); NUML0 = LUSOL->luparm[LUSOL_IP_COLCOUNT_L0]; LENL0 = LUSOL->luparm[LUSOL_IP_NONZEROS_L0]; L2 = LUSOL->lena-LENL0; for(K = NUML0; K >= 1; K--) { LEN = LUSOL->lenc[K]; L1 = L2+1; L2 += LEN; for(L = L1; L <= L2; L++) { I = LUSOL->indc[L]; I = LUSOL->ipinv[I]; /* Undo row mapping */ J = LUSOL->indr[L]; denseL0[(LUSOL->n+1)*(J-1) + I] = LUSOL->a[L]; } } for(I = 1; I <= LUSOL->n; I++) { for(J = 1; J <= LUSOL->m; J++) fprintf(stdout, "%10g", denseL0[(LUSOL->n+1)*(J-1) + I]); fprintf(stdout, "\n"); } LUSOL_FREE(denseL0); } /* ------------------------------------------------------------------ Include routines for column-based U. 5 Feb 2006 Current version - KE. ------------------------------------------------------------------ */ #include "lusol6u.c" /* ================================================================== lu6U solves U w = v. v is not altered. ------------------------------------------------------------------ 15 Dec 2002: First version derived from lu6sol. 15 Dec 2002: Current version. ================================================================== */ void LU6U(LUSOLrec *LUSOL, int *INFORM, REAL V[], REAL W[], int NZidx[]) { /* Do column-based U version, if available */ if((LUSOL->U != NULL) || ((LUSOL->luparm[LUSOL_IP_FTRANCOUNT] == 0) && LU1U0(LUSOL, &(LUSOL->U), INFORM))) { LU6U0_v(LUSOL, LUSOL->U, V, W, NZidx, INFORM); } /* Alternatively, do the standard column-based L0 version */ else { int I, J, K, KLAST, L, L1, L2, L3, NRANK, NRANK1; REAL SMALL; register REALXP T; #ifdef LUSOLFastSolve REAL *aptr; int *jptr; #endif NRANK = LUSOL->luparm[LUSOL_IP_RANK_U]; SMALL = LUSOL->parmlu[LUSOL_RP_ZEROTOLERANCE]; *INFORM = LUSOL_INFORM_LUSUCCESS; NRANK1 = NRANK+1; /* Find the first nonzero in v(1:nrank), counting backwards. */ for(KLAST = NRANK; KLAST >= 1; KLAST--) { I = LUSOL->ip[KLAST]; if(fabs(V[I])>SMALL) break; } L = LUSOL->n; #ifdef LUSOLFastSolve for(K = KLAST+1, jptr = LUSOL->iq+K; K <= L; K++, jptr++) W[*jptr] = ZERO; #else for(K = KLAST+1; K <= L; K++) { J = LUSOL->iq[K]; W[J] = ZERO; } #endif /* Do the back-substitution, using rows 1:klast of U. */ for(K = KLAST; K >= 1; K--) { I = LUSOL->ip[K]; T = V[I]; L1 = LUSOL->locr[I]; L2 = L1+1; L3 = (L1+LUSOL->lenr[I])-1; /* ***** This loop could be coded specially. */ #ifdef LUSOLFastSolve for(L = L2, aptr = LUSOL->a+L2, jptr = LUSOL->indr+L2; L <= L3; L++, aptr++, jptr++) T -= (*aptr) * W[*jptr]; #else for(L = L2; L <= L3; L++) { J = LUSOL->indr[L]; T -= LUSOL->a[L]*W[J]; } #endif J = LUSOL->iq[K]; if(fabs((REAL) T)<=SMALL) T = ZERO; else T /= LUSOL->a[L1]; W[J] = (REAL) T; } /* Compute residual for overdetermined systems. */ T = ZERO; for(K = NRANK1; K <= LUSOL->m; K++) { I = LUSOL->ip[K]; T += fabs(V[I]); } /* Exit. */ if(T>ZERO) *INFORM = LUSOL_INFORM_LUSINGULAR; LUSOL->luparm[LUSOL_IP_INFORM] = *INFORM; LUSOL->parmlu[LUSOL_RP_RESIDUAL_U] = (REAL) T; } } /* ================================================================== lu6Ut solves U'v = w. w is destroyed. ------------------------------------------------------------------ 15 Dec 2002: First version derived from lu6sol. 15 Dec 2002: Current version. ================================================================== */ void LU6UT(LUSOLrec *LUSOL, int *INFORM, REAL V[], REAL W[], int NZidx[]) { int I, J, K, L, L1, L2, NRANK, NRANK1, *ip = LUSOL->ip + 1, *iq = LUSOL->iq + 1; REAL SMALL; register REAL T; #ifdef LUSOLFastSolve REAL *aptr; int *jptr; #endif NRANK = LUSOL->luparm[LUSOL_IP_RANK_U]; SMALL = LUSOL->parmlu[LUSOL_RP_ZEROTOLERANCE]; *INFORM = LUSOL_INFORM_LUSUCCESS; NRANK1 = NRANK+1; L = LUSOL->m; #ifdef LUSOLFastSolve for(K = NRANK1, jptr = LUSOL->ip+K; K <= L; K++, jptr++) V[*jptr] = ZERO; #else for(K = NRANK1; K <= L; K++) { I = LUSOL->ip[K]; V[I] = ZERO; } #endif /* Do the forward-substitution, skipping columns of U(transpose) when the associated element of w(*) is negligible. */ #if 0 for(K = 1; K <= NRANK; K++) { I = LUSOL->ip[K]; J = LUSOL->iq[K]; #else for(K = 1; K <= NRANK; K++, ip++, iq++) { I = *ip; J = *iq; #endif T = W[J]; if(fabs(T)<=SMALL) { V[I] = ZERO; continue; } L1 = LUSOL->locr[I]; T /= LUSOL->a[L1]; V[I] = T; L2 = (L1+LUSOL->lenr[I])-1; L1++; /* ***** This loop could be coded specially. */ #ifdef LUSOLFastSolve for(L = L1, aptr = LUSOL->a+L1, jptr = LUSOL->indr+L1; L <= L2; L++, aptr++, jptr++) W[*jptr] -= T * (*aptr); #else for(L = L1; L <= L2; L++) { J = LUSOL->indr[L]; W[J] -= T*LUSOL->a[L]; } #endif } /* Compute residual for overdetermined systems. */ T = ZERO; for(K = NRANK1; K <= LUSOL->n; K++) { J = LUSOL->iq[K]; T += fabs(W[J]); } /* Exit. */ if(T>ZERO) *INFORM = LUSOL_INFORM_LUSINGULAR; LUSOL->luparm[LUSOL_IP_INFORM] = *INFORM; LUSOL->parmlu[LUSOL_RP_RESIDUAL_U] = T; } /* ================================================================== lu6sol uses the factorization A = L U as follows: ------------------------------------------------------------------ mode 1 v solves L v = v(input). w is not touched. 2 v solves L'v = v(input). w is not touched. 3 w solves U w = v. v is not altered. 4 v solves U'v = w. w is destroyed. 5 w solves A w = v. v is altered as in 1. 6 v solves A'v = w. w is destroyed. If mode = 3,4,5,6, v and w must not be the same arrays. If lu1fac has just been used to factorize a symmetric matrix A (which must be definite or quasi-definite), the factors A = L U may be regarded as A = LDL', where D = diag(U). In such cases, mode 7 v solves A v = L D L'v = v(input). w is not touched. 8 v solves L |D| L'v = v(input). w is not touched. ip(*), iq(*) hold row and column numbers in pivotal order. lenc(k) is the length of the k-th column of initial L. lenr(i) is the length of the i-th row of U. locc(*) is not used. locr(i) is the start of the i-th row of U. U is assumed to be in upper-trapezoidal form (nrank by n). The first entry for each row is the diagonal element (according to the permutations ip, iq). It is stored at location locr(i) in a(*), indr(*). On exit, inform = 0 except as follows. if(mode = 3,4,5,6 and if U (and hence A) is singular,) inform = 1 if there is a nonzero residual in solving the system involving U. parmlu(20) returns the norm of the residual. ------------------------------------------------------------------ July 1987: Early version. 09 May 1988: f77 version. 27 Apr 2000: Abolished the dreaded "computed go to". But hard to change other "go to"s to "if then else". 15 Dec 2002: lu6L, lu6Lt, lu6U, lu6Ut added to modularize lu6sol. ================================================================== */ void LU6SOL(LUSOLrec *LUSOL, int MODE, REAL V[], REAL W[], int NZidx[], int *INFORM) { if(MODE==LUSOL_SOLVE_Lv_v) { /* Solve L v(new) = v. */ LU6L(LUSOL, INFORM,V, NZidx); } else if(MODE==LUSOL_SOLVE_Ltv_v) { /* Solve L'v(new) = v. */ LU6LT(LUSOL, INFORM,V, NZidx); } else if(MODE==LUSOL_SOLVE_Uw_v) { /* Solve U w = v. */ LU6U(LUSOL, INFORM,V,W, NZidx); } else if(MODE==LUSOL_SOLVE_Utv_w) { /* Solve U'v = w. */ LU6UT(LUSOL, INFORM,V,W, NZidx); } else if(MODE==LUSOL_SOLVE_Aw_v) { /* Solve A w = v (i.e. FTRAN) */ LU6L(LUSOL, INFORM,V, NZidx); /* via L v(new) = v */ LU6U(LUSOL, INFORM,V,W, NULL); /* ... and U w = v(new). */ } else if(MODE==LUSOL_SOLVE_Atv_w) { /* Solve A'v = w (i.e. BTRAN) */ LU6UT(LUSOL, INFORM,V,W, NZidx); /* via U'v = w */ LU6LT(LUSOL, INFORM,V, NULL); /* ... and L'v(new) = v. */ } else if(MODE==LUSOL_SOLVE_Av_v) { /* Solve LDv(bar) = v */ LU6LD(LUSOL, INFORM,1,V, NZidx); /* and L'v(new) = v(bar). */ LU6LT(LUSOL, INFORM,V, NULL); } else if(MODE==LUSOL_SOLVE_LDLtv_v) { /* Solve L|D|v(bar) = v */ LU6LD(LUSOL, INFORM,2,V, NZidx); /* and L'v(new) = v(bar). */ LU6LT(LUSOL, INFORM,V, NULL); } } MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/bfile3.txt0000664000175000017500000000007711141374613021242 0ustar lauerlauer -0.187248E+05 0.112479E+05 0.132356E+05 MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/lusolmain.h0000664000175000017500000000067711141443435021516 0ustar lauerlauer #ifdef StaticMemAlloc #if 0 #define MAXNZ 300000 #define MAXROWS 15000 #elif 0 #define MAXNZ 60000 #define MAXROWS 12500 #elif 1 #define MAXNZ 40000 #define MAXROWS 3500 #else #define MAXNZ 1000 #define MAXROWS 50 #endif #else #define MAXNZ 1000 #define MAXROWS 50 #endif #define MAXCOLS MAXROWS #define MAXLU (LUSOL_MULT_nz_a*MAXNZ) MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/lusolmain.c0000664000175000017500000003646711141443435021517 0ustar lauerlauer /* This program solves a sparse linear system Ax = b using LUSOL. */ #include #include #include #include #include #include "commonlib.h" #include "myblas.h" #include "lusol.h" #include "lusolio.h" #include "lusolmain.h" #if (defined WIN32) || (defined WIN64) void _strupr_(char *s) { _strupr(s); } #else /* Yin Zhang noted that _strupr() is not available on many Unix platforms */ void _strupr_(char *s) { int i; char c; for (i = 0; i < strlen(s); i++) { c = s[i]; if (c <= 'z' && c >= 'a') { s[i] = c - 'a' + 'A'; } } } #endif MYBOOL getFileName(char *filename, char *test) { MYBOOL status; status = (MYBOOL) (('-' != test[0]) && (strlen(test) > 1)); if(status) strcpy(filename, test); return(status); } MYBOOL isNum(char val) { int ord; ord = (int) val - 48; return( (MYBOOL) ((ord >= 0) && (ord <= 9)) ); } void main( int argc, char *argv[], char *envp[] ) { /* Output device */ FILE *outunit = stdout; /* Overall dimensions allocated */ int maxm = MAXROWS, maxn = MAXCOLS, maxnz = MAXNZ, replace = 0, randcol = 0; MYBOOL ftran = TRUE; /* Storage for A, b */ REAL *Aij = NULL, *b = NULL, *xexact = NULL; int *iA = NULL, *jA = NULL; /* Storage for LUSOL */ LUSOLrec *LUSOL = NULL; /* Define local storage variables */ int i , inform, j , k , i1 , m , useropt, lenb, lenx, n , nelem , nnzero; REAL Amax , test , bnorm , rnorm , xnorm, *rhs = NULL, *r = NULL, *x = NULL; char fileext[50], filename[255], blasname[255]; MYBOOL printsolution = FALSE, success = FALSE; /* Check if we have input parameters */ useropt = argc; if(useropt < 2) { printf("LUSOL v%d.%d.%d.%d - Linear equation solver - Development edition.\n", LUSOL_VERMAJOR, LUSOL_VERMINOR, LUSOL_RELEASE, LUSOL_BUILD); printf("Usage: lusol [-p ] [-t ] [-m ]\n"); printf(" [-s] []\n"); printf("Options: -p <0..3> Selects pivot type.\n"); printf(" -t <1..100> Selects diagonal tolerance.\n"); printf(" -m <%d..100> Memory allocation scalar.\n", LUSOL_MULT_nz_a); printf(" -b Solves using btran (rather than ftran).\n"); printf(" -r Randomly replace a column and resolve.\n"); printf(" -s Show the computed solution.\n"); printf(" -blas Activates external optimized BLAS library.\n"); printf("Formats: Conventional RCV .TXT, MatrixMarket .MTX, or Harwell-Boeing .RUA\n"); printf("Author: Michael A. Saunders (original Fortran version)\n"); printf(" Kjell Eikland (modified C version)\n"); return; } /* Create the LUSOL object and set user options */ LUSOL = LUSOL_create(outunit, 0, LUSOL_PIVMOD_TPP, 0); #if 1 LUSOL->luparm[LUSOL_IP_ACCELERATION] = LUSOL_OTHERORDER | LUSOL_ACCELERATE_L0; #elif 0 LUSOL->luparm[LUSOL_IP_ACCELERATION] = LUSOL_AUTOORDER | LUSOL_ACCELERATE_L0; #endif LUSOL->luparm[LUSOL_IP_SCALAR_NZA] = 10; i = 1; n = 0; filename[0] = '\0'; blasname[0] = '\0'; while((n == 0) && (i < argc)) { if(strcmp("-p", argv[i]) == 0) { i1 = i+1; if((i1 < argc) && isNum(argv[i1][0])) { i = i1; m = atoi(argv[i]); if(m < 0 || m > LUSOL_PIVMOD_MAX) continue; LUSOL->luparm[LUSOL_IP_PIVOTTYPE] = m; } } else if(strcmp("-t", argv[i]) == 0) { i1 = i+1; if((i1 < argc) && isNum(argv[i1][0])) { i = i1; Amax = atof(argv[i]); if(Amax < 1 || Amax > 100) continue; LUSOL->parmlu[LUSOL_RP_FACTORMAX_Lij] = Amax; } } else if(strcmp("-m", argv[i]) == 0) { i1 = i+1; if((i1 < argc) && isNum(argv[i1][0])) { i = i1; m = atoi(argv[i]); if(m < LUSOL_MULT_nz_a || m > 100) continue; LUSOL->luparm[LUSOL_IP_SCALAR_NZA] = atoi(argv[i]); } } else if(strcmp("-s", argv[i]) == 0) printsolution = TRUE; else if(strcmp("-b", argv[i]) == 0) ftran = FALSE; else if(strcmp("-r", argv[i]) == 0) { i1 = i+1; if((i1 < argc) && isNum(argv[i1][0])) { i = i1; m = atoi(argv[i]); if(m < 0 || m > 10) continue; } else m = 1; srand((unsigned) time( NULL )); replace = 2*m; } else if(strcmp("-blas", argv[i]) == 0) { i1 = i+1; if((i1 < argc) && getFileName(blasname, argv[i1])) { if(!load_BLAS(blasname)) fprintf(outunit, "Could not load external BLAS library '%s'\n", blasname); i = i1; } else fprintf(outunit, "Ignoring incomplete parameter %d '%s'\n", i, argv[i]); } else { if(getFileName(filename, argv[i])) { useropt = i; break; } else fprintf(outunit, "Ignoring unknown parameter %d '%s'\n", i, argv[i]); } i++; } /* Obtain file extension and see if we must estimate matrix data size */ strcpy(fileext, strchr(argv[useropt], '.')); /* Yin Zhang noted that _strupr() is not available on many Unix platforms. */ _strupr_(fileext); /* _strupr(fileext);*/ /* Read conventional text file format */ if(strcmp(fileext, ".TXT") == 0) { if(!ctf_size_A(filename, &maxm, &maxn, &maxnz)) goto x900; } /* Read MatrixMarket file format */ else if(strcmp(fileext, ".MTX") == 0) { if(!mmf_size_A(filename, &maxm, &maxn, &maxnz)) goto x900; } /* Read Harwell-Boeing file format */ else if(strcmp(fileext, ".RUA") == 0) { if(!hbf_size_A(filename, &maxm, &maxn, &maxnz)) goto x900; } else { fprintf(outunit, "Unrecognized matrix file extension %s\n", fileext); goto x900; } /* Create the arrays */ Aij = (REAL *) LUSOL_CALLOC(maxnz + BLAS_BASE, sizeof(REAL)); iA = (int *) LUSOL_CALLOC(maxnz + BLAS_BASE, sizeof(int)); jA = (int *) LUSOL_CALLOC(maxnz + BLAS_BASE, sizeof(int)); if(ftran) lenb = maxm; else lenb = maxn; b = (REAL *) LUSOL_CALLOC(lenb+BLAS_BASE, sizeof(REAL)); rhs = (REAL *) LUSOL_CALLOC(lenb+BLAS_BASE, sizeof(REAL)); if(ftran) lenx = maxn; else lenx = maxm; xexact = (REAL *) LUSOL_CALLOC(lenx+BLAS_BASE, sizeof(REAL)); r = (REAL *) LUSOL_CALLOC(lenx+BLAS_BASE, sizeof(REAL)); x = (REAL *) LUSOL_CALLOC(lenx+BLAS_BASE, sizeof(REAL)); /* ----------------------------------------------------------------- Read data files. ----------------------------------------------------------------- */ fprintf(stdout, "\n========================================\n"); fprintf(stdout, "LUSOL v%d.%d.%d.%d - Linear equation solver", LUSOL_VERMAJOR, LUSOL_VERMINOR, LUSOL_RELEASE, LUSOL_BUILD); fprintf(stdout, "\n========================================\n"); /* ----------------------------------------------------------------- Read data for A ----------------------------------------------------------------- */ /* Read conventional text file format */ if(strcmp(fileext, ".TXT") == 0) { if(!ctf_read_A(argv[useropt], maxm, maxn, maxnz, &m, &n, &nnzero, iA, jA, Aij)) goto x900; } /* Read MatrixMarket file format */ else if(strcmp(fileext, ".MTX") == 0) { if(!mmf_read_A(argv[useropt], maxm, maxn, maxnz, &m, &n, &nnzero, iA, jA, Aij)) goto x900; } /* Read Harwell-Boeing file format */ else if(strcmp(fileext, ".RUA") == 0) { if(!hbf_read_A(argv[useropt], maxm, maxn, maxnz, &m, &n, &nnzero, iA, jA, Aij)) goto x900; } else { fprintf(outunit, "Error: Unrecognized matrix file extension %s\n", fileext); goto x900; } /* ----------------------------------------------------------------- Read data for b ----------------------------------------------------------------- */ /* Handle Harwell-Boeing case where the file contains a RHS */ i = strcmp(fileext, ".RUA"); if((useropt == argc-1) && (i != 0)) { srand(timeNow()); i1 = m; while(i1 > 0) { test = rand(); i = RAND_MAX; i = (int) ((test/i)*(m-1)); /* b[i+1] = 1.0; */ b[i+1] = i - 5; i1--; } if(printsolution) blockWriteREAL(outunit, "\nGenerated RHS vector", b, 1, lenb); } else { if(i != 0) useropt++; strcpy(fileext, strchr(argv[useropt], '.')); _strupr_(fileext); /* Read conventional text file format */ if(strcmp(fileext, ".TXT") == 0) { if(!ctf_read_b(argv[useropt], lenb, b)) goto x900; } /* Read MatrixMarket file format */ else if(strcmp(fileext, ".MTX") == 0) { if(!mmf_read_b(argv[useropt], lenb, b)) goto x900; } /* Read Harwell-Boeing file format */ else if(strcmp(fileext, ".RUA") == 0) { if(!hbf_read_b(argv[useropt], lenb, b)) goto x900; } else { fprintf(outunit, "Error: Unrecognized vector file extension %s\n", fileext); goto x900; } } success = TRUE; /* ----------------------------------------------------------------- Show data on input ----------------------------------------------------------------- */ fprintf(outunit, "\nData read from:\n%s\n", filename); test = (double) nnzero / ((double) m * (double) n); test *= 100.0; fprintf(outunit, "Rows = %d Columns = %d Non-zeros = %d Density =%8.4f%%\n", m, n, nnzero, test); /* ----------------------------------------------------------------- Load A into (a, indc, indr). ----------------------------------------------------------------- */ #if 0 /* BUG !!! */ if(n != m) LUSOL->luparm[LUSOL_IP_KEEPLU] = FALSE; #endif #ifdef LegacyTesting LUSOL->luparm[LUSOL_IP_SCALAR_NZA] = LUSOL_MULT_nz_a; LUSOL_sizeto(LUSOL, MAXROWS, MAXCOLS, MAXNZ*LUSOL_MULT_nz_a); #endif if(!LUSOL_assign(LUSOL, iA, jA, Aij, nnzero, TRUE)) { fprintf(outunit, "Error: LUSOL failed due to insufficient memory.\n"); goto x900; } /* ------------------------------------------------------------------ Factor A = L U. ------------------------------------------------------------------ */ nelem = nnzero; inform = LUSOL_factorize( LUSOL); if(inform > LUSOL_INFORM_SERIOUS) { fprintf(outunit, "Error:\n%s\n", LUSOL_informstr(LUSOL, inform)); goto x900; } if(n != m) goto x800; /* Get the largest element in A; we use it below as an estimate of ||A||_inf, even though it isn't a proper norm. */ Amax = LUSOL->parmlu[LUSOL_RP_MAXELEM_A]; /* ------------------------------------------------------------------ SOLVE A x = b or x'A = b'. Save b first because lu6sol() overwrites the rhs. ------------------------------------------------------------------ */ MEMCOPY(x, b, lenb+BLAS_BASE); Resolve: if(ftran) inform = LUSOL_ftran(LUSOL, x, NULL, FALSE); else inform = LUSOL_btran(LUSOL, x, NULL); if(inform > LUSOL_INFORM_SERIOUS) { fprintf(outunit, "Error:\n%s\n", LUSOL_informstr(LUSOL, inform)); goto x900; } if(printsolution) blockWriteREAL(outunit, "\nSolution vector", x, 1, lenb); /* ------------------------------------------------------------------ Set r = b - Ax. Find norm of r and x. ------------------------------------------------------------------ */ MEMCOPY(r, b, lenb+BLAS_BASE); for(k = 1; k <= nnzero; k++) { i = iA[k]; /* Row number */ j = jA[k]; /* Column number */ if(ftran) r[i] -= Aij[k]*x[j]; else r[j] -= Aij[k]*x[i]; } /* blockWriteREAL(outunit, "\nResidual vector", r, 1, lenb);*/ bnorm = dnormi( lenb, b ); rnorm = dnormi( lenb, r ); xnorm = dnormi( lenx, x ); /* ------------------------------------------------------------------ Report the findings. ------------------------------------------------------------------ */ if(randcol > 0) fprintf(outunit, "\n\nColumn %d was %s\n", randcol, (mod(replace,2) == 1 ? "replaced with random data" : "restored")); x800: fprintf(outunit, "\nLU size statistics (%d reallocations):\n", LUSOL->expanded_a); test = LUSOL->luparm[LUSOL_IP_NONZEROS_U0]+LUSOL->luparm[LUSOL_IP_NONZEROS_L0]; fprintf(outunit, "L0-size = %d U0-size = %d LU-nonzeros = %d Fill-in = %.1fx\n", LUSOL->luparm[LUSOL_IP_NONZEROS_L0], LUSOL->luparm[LUSOL_IP_NONZEROS_U0], (int) test, test/nnzero); if(n != m) { fprintf(outunit, "%s with a factor tol. of %g identified %d singularities.\n", LUSOL_pivotLabel(LUSOL), LUSOL->parmlu[LUSOL_RP_FACTORMAX_Lij], LUSOL->luparm[LUSOL_IP_SINGULARITIES]); goto x900; } test = rnorm / (Amax*xnorm); fprintf(outunit, "\nAccuracy statistics:\n"); fprintf(outunit, "%s with a factor tol. of %g gave a rel.error of %g and %d singularities.\n", LUSOL_pivotLabel(LUSOL), LUSOL->parmlu[LUSOL_RP_FACTORMAX_Lij], test, LUSOL->luparm[LUSOL_IP_SINGULARITIES]); fprintf(outunit, "Amax = %g bnorm = %g rnorm = %g xnorm = %g\n", Amax, bnorm, rnorm, xnorm); fprintf(outunit, "\n"); if (test <= 1.0e-8) fprintf(outunit, "The equations were solved with very high accuracy.\n"); else if (test <= 1.0e-6) fprintf(outunit, "The equations were solved with reasonably good accuracy.\n"); else { if (test <= 1.0e-4) fprintf(outunit, "Questionable accuracy; the LU factors may not be good enough.\n"); else fprintf(outunit, "Poor accuracy; the LU factorization probably failed.\n"); if(LUSOL->luparm[LUSOL_IP_PIVOTTYPE] == LUSOL_PIVMOD_TRP) fprintf(outunit, "Try a smaller factor tolerance (current is %g).\n", LUSOL->parmlu[LUSOL_RP_FACTORMAX_Lij]); else fprintf(outunit, "Try a smaller factor tolerance and/or TRP pivoting.\n"); } /* Check if we should replace a column and resolve */ if(replace > 0) { replace--; MEMCLEAR(x, lenb+BLAS_BASE); if(mod(replace, 2) == 1) { /* Randomly find a column and replace the column values with random data */ rnorm = rand(); randcol = (int) (n * rnorm / (RAND_MAX+1.0)) + 1; for(i = 1; i < m; i++) x[i] = Amax * rand() / RAND_MAX; } else { /* Put the previously replaced column back and resolve */ for (k = 1; k <= nnzero; k++) { i = iA[k]; j = jA[k]; if(j == randcol) x[i] = Aij[k]; } } inform = LUSOL_replaceColumn(LUSOL, randcol, x); MEMCOPY(b, x, lenb+BLAS_BASE); if(inform != LUSOL_INFORM_LUSUCCESS) fprintf(outunit, "Error:\n%s\n", LUSOL_informstr(LUSOL, inform)); else goto Resolve; } /* Free memory */ x900: if(!success) fprintf(outunit, "Insufficient memory or data file not found.\n"); LUSOL_FREE(Aij); LUSOL_FREE(b); LUSOL_FREE(xexact); LUSOL_FREE(iA); LUSOL_FREE(jA); LUSOL_FREE(rhs); LUSOL_FREE(r); LUSOL_FREE(x); #if 0 LUSOL_dump(NULL, LUSOL); -blas "atlas_AXP_512_360.dll" -b -p 1 "STP3D_A.MTX" "C:\Shared Files\Visual Studio Projects\LU\MatrixMarket\sherman5.mtx" "C:\Shared Files\Visual Studio Projects\LU\MatrixMarket\sherman5_rhs1.mtx" A6805.txt b6805.txt A10009.txt b10009.txt fidap005.mtx fidap005_rhs1.mtx fidapm05.mtx fidapm05_rhs1.mtx -b -p 1 "basis.mtx" -b -p 1 "LU-test3.mtx" #endif LUSOL_free(LUSOL); /* End of main program for Test of LUSOL */ } MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/hbio.c0000664000175000017500000016746011141443432020430 0ustar lauerlauer /* Harwell-Boeing File I/O in C V. 1.0 National Institute of Standards and Technology, MD. K.A. Remington ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ NOTICE Permission to use, copy, modify, and distribute this software and its documentation for any purpose and without fee is hereby granted provided that the above copyright notice appear in all copies and that both the copyright notice and this permission notice appear in supporting documentation. Neither the Author nor the Institution (National Institute of Standards and Technology) make any representations about the suitability of this software for any purpose. This software is provided "as is" without expressed or implied warranty. ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ --------------------- INTERFACE DESCRIPTION --------------------- --------------- QUERY FUNCTIONS --------------- FUNCTION: int readHB_info(const char *filename, int *M, int *N, int *nz, char **Type, int *Nrhs) DESCRIPTION: The readHB_info function opens and reads the header information from the specified Harwell-Boeing file, and reports back the number of rows and columns in the stored matrix (M and N), the number of nonzeros in the matrix (nz), the 3-character matrix type(Type), and the number of right-hand-sides stored along with the matrix (Nrhs). This function is designed to retrieve basic size information which can be used to allocate arrays. FUNCTION: int readHB_header(FILE* in_file, char* Title, char* Key, char* Type, int* Nrow, int* Ncol, int* Nnzero, int* Nrhs, int* Nrhsix, char* Ptrfmt, char* Indfmt, char* Valfmt, char* Rhsfmt, int* Ptrcrd, int* Indcrd, int* Valcrd, int* Rhscrd, char *Rhstype) DESCRIPTION: More detailed than the readHB_info function, readHB_header() reads from the specified Harwell-Boeing file all of the header information. ------------------------------ DOUBLE PRECISION I/O FUNCTIONS ------------------------------ FUNCTION: int readHB_newmat_double(const char *filename, int *M, int *N, *int nz, int **colptr, int **rowind, double**val) int readHB_mat_double(const char *filename, int *colptr, int *rowind, double*val) DESCRIPTION: This function opens and reads the specified file, interpreting its contents as a sparse matrix stored in the Harwell/Boeing standard format. (See readHB_aux_double to read auxillary vectors.) -- Values are interpreted as double precision numbers. -- The "mat" function uses _pre-allocated_ vectors to hold the index and nonzero value information. The "newmat" function allocates vectors to hold the index and nonzero value information, and returns pointers to these vectors along with matrix dimension and number of nonzeros. FUNCTION: int readHB_aux_double(const char* filename, const char AuxType, double b[]) int readHB_newaux_double(const char* filename, const char AuxType, double** b) DESCRIPTION: This function opens and reads from the specified file auxillary vector(s). The char argument Auxtype determines which type of auxillary vector(s) will be read (if present in the file). AuxType = 'F' right-hand-side AuxType = 'G' initial estimate (Guess) AuxType = 'X' eXact solution If Nrhs > 1, all of the Nrhs vectors of the given type are read and stored in column-major order in the vector b. The "newaux" function allocates a vector to hold the values retrieved. The "mat" function uses a _pre-allocated_ vector to hold the values. FUNCTION: int writeHB_mat_double(const char* filename, int M, int N, int nz, const int colptr[], const int rowind[], const double val[], int Nrhs, const double rhs[], const double guess[], const double exact[], const char* Title, const char* Key, const char* Type, char* Ptrfmt, char* Indfmt, char* Valfmt, char* Rhsfmt, const char* Rhstype) DESCRIPTION: The writeHB_mat_double function opens the named file and writes the specified matrix and optional auxillary vector(s) to that file in Harwell-Boeing format. The format arguments (Ptrfmt,Indfmt,Valfmt, and Rhsfmt) are character strings specifying "Fortran-style" output formats -- as they would appear in a Harwell-Boeing file. They are used to produce output which is as close as possible to what would be produced by Fortran code, but note that "D" and "P" edit descriptors are not supported. If NULL, the following defaults will be used: Ptrfmt = Indfmt = "(8I10)" Valfmt = Rhsfmt = "(4E20.13)" ----------------------- CHARACTER I/O FUNCTIONS ----------------------- FUNCTION: int readHB_mat_char(const char* filename, int colptr[], int rowind[], char val[], char* Valfmt) int readHB_newmat_char(const char* filename, int* M, int* N, int* nonzeros, int** colptr, int** rowind, char** val, char** Valfmt) DESCRIPTION: This function opens and reads the specified file, interpreting its contents as a sparse matrix stored in the Harwell/Boeing standard format. (See readHB_aux_char to read auxillary vectors.) -- Values are interpreted as char strings. -- (Used to translate exact values from the file into a new storage format.) The "mat" function uses _pre-allocated_ arrays to hold the index and nonzero value information. The "newmat" function allocates char arrays to hold the index and nonzero value information, and returns pointers to these arrays along with matrix dimension and number of nonzeros. FUNCTION: int readHB_aux_char(const char* filename, const char AuxType, char b[]) int readHB_newaux_char(const char* filename, const char AuxType, char** b, char** Rhsfmt) DESCRIPTION: This function opens and reads from the specified file auxillary vector(s). The char argument Auxtype determines which type of auxillary vector(s) will be read (if present in the file). AuxType = 'F' right-hand-side AuxType = 'G' initial estimate (Guess) AuxType = 'X' eXact solution If Nrhs > 1, all of the Nrhs vectors of the given type are read and stored in column-major order in the vector b. The "newaux" function allocates a character array to hold the values retrieved. The "mat" function uses a _pre-allocated_ array to hold the values. FUNCTION: int writeHB_mat_char(const char* filename, int M, int N, int nz, const int colptr[], const int rowind[], const char val[], int Nrhs, const char rhs[], const char guess[], const char exact[], const char* Title, const char* Key, const char* Type, char* Ptrfmt, char* Indfmt, char* Valfmt, char* Rhsfmt, const char* Rhstype) DESCRIPTION: The writeHB_mat_char function opens the named file and writes the specified matrix and optional auxillary vector(s) to that file in Harwell-Boeing format. The format arguments (Ptrfmt,Indfmt,Valfmt, and Rhsfmt) are character strings specifying "Fortran-style" output formats -- as they would appear in a Harwell-Boeing file. Valfmt and Rhsfmt must accurately represent the character representation of the values stored in val[] and rhs[]. If NULL, the following defaults will be used for the integer vectors: Ptrfmt = Indfmt = "(8I10)" Valfmt = Rhsfmt = "(4E20.13)" */ /*---------------------------------------------------------------------*/ /* If zero-based indexing is desired, _SP_base should be set to 0 */ /* This will cause indices read from H-B files to be decremented by 1 */ /* and indices written to H-B files to be incremented by 1 */ /* <<< Standard usage is _SP_base = 1 >>> */ #ifndef _SP_base #define _SP_base 1 #endif /*---------------------------------------------------------------------*/ #include "hbio.h" #include #include char *substr(const char* S, const int pos, const int len); void upcase(char* S); void IOHBTerminate(char* message); int readHB_info(const char* filename, int* M, int* N, int* nz, char** Type, int* Nrhs) { /****************************************************************************/ /* The readHB_info function opens and reads the header information from */ /* the specified Harwell-Boeing file, and reports back the number of rows */ /* and columns in the stored matrix (M and N), the number of nonzeros in */ /* the matrix (nz), and the number of right-hand-sides stored along with */ /* the matrix (Nrhs). */ /* */ /* For a description of the Harwell Boeing standard, see: */ /* Duff, et al., ACM TOMS Vol.15, No.1, March 1989 */ /* */ /* ---------- */ /* **CAVEAT** */ /* ---------- */ /* ** If the input file does not adhere to the H/B format, the ** */ /* ** results will be unpredictable. ** */ /* */ /****************************************************************************/ FILE *in_file; int Ptrcrd, Indcrd, Valcrd, Rhscrd; int Nrow, Ncol, Nnzero, Nrhsix; char *mat_type; char Title[73], Key[9], Rhstype[4]; char Ptrfmt[17], Indfmt[17], Valfmt[21], Rhsfmt[21]; mat_type = (char *) malloc(4); if ( mat_type == NULL ) IOHBTerminate("Insufficient memory for mat_typen"); if ( (in_file = fopen( filename, "r")) == NULL ) { fprintf(stderr,"Error: Cannot open file: %s\n",filename); return 0; } readHB_header(in_file, Title, Key, mat_type, &Nrow, &Ncol, &Nnzero, Nrhs, &Nrhsix, Ptrfmt, Indfmt, Valfmt, Rhsfmt, &Ptrcrd, &Indcrd, &Valcrd, &Rhscrd, Rhstype); fclose(in_file); *Type = mat_type; *(*Type+3) = (char) NULL; *M = Nrow; *N = Ncol; *nz = Nnzero; if (Rhscrd == 0) {*Nrhs = 0;} /* In verbose mode, print some of the header information: */ /* if (verbose == 1) { printf("Reading from Harwell-Boeing file %s (verbose on)...\n",filename); printf(" Title: %s\n",Title); printf(" Key: %s\n",Key); printf(" The stored matrix is %i by %i with %i nonzeros.\n", *M, *N, *nz ); printf(" %i right-hand--side(s) stored.\n",*Nrhs); } */ return 1; } int readHB_header(FILE* in_file, char* Title, char* Key, char* Type, int* Nrow, int* Ncol, int* Nnzero, int* Nrhs, int* Nrhsix, char* Ptrfmt, char* Indfmt, char* Valfmt, char* Rhsfmt, int* Ptrcrd, int* Indcrd, int* Valcrd, int* Rhscrd, char *Rhstype) { /*************************************************************************/ /* Read header information from the named H/B file... */ /*************************************************************************/ int Totcrd,Neltvl; char line[BUFSIZ]; /* First line: */ fgets(line, BUFSIZ, in_file); if ( sscanf(line,"%*s") < 0 ) IOHBTerminate("iohb.c: Null (or blank) first line of HB file.\n"); (void) sscanf(line, "%72c%8[^\n]", Title, Key); *(Key+8) = (char) NULL; *(Title+72) = (char) NULL; /* Second line: */ fgets(line, BUFSIZ, in_file); if ( sscanf(line,"%*s") < 0 ) IOHBTerminate("iohb.c: Null (or blank) second line of HB file.\n"); if ( sscanf(line,"%i",&Totcrd) != 1) Totcrd = 0; if ( sscanf(line,"%*i%i",Ptrcrd) != 1) *Ptrcrd = 0; if ( sscanf(line,"%*i%*i%i",Indcrd) != 1) *Indcrd = 0; if ( sscanf(line,"%*i%*i%*i%i",Valcrd) != 1) *Valcrd = 0; if ( sscanf(line,"%*i%*i%*i%*i%i",Rhscrd) != 1) *Rhscrd = 0; /* Third line: */ fgets(line, BUFSIZ, in_file); if ( sscanf(line,"%*s") < 0 ) IOHBTerminate("iohb.c: Null (or blank) third line of HB file.\n"); if ( sscanf(line, "%3c", Type) != 1) IOHBTerminate("iohb.c: Invalid Type info, line 3 of Harwell-Boeing file.\n"); upcase(Type); if ( sscanf(line,"%*3c%i",Nrow) != 1) *Nrow = 0 ; if ( sscanf(line,"%*3c%*i%i",Ncol) != 1) *Ncol = 0 ; if ( sscanf(line,"%*3c%*i%*i%i",Nnzero) != 1) *Nnzero = 0 ; if ( sscanf(line,"%*3c%*i%*i%*i%i",&Neltvl) != 1) Neltvl = 0 ; /* Fourth line: */ fgets(line, BUFSIZ, in_file); if ( sscanf(line,"%*s") < 0 ) IOHBTerminate("iohb.c: Null (or blank) fourth line of HB file.\n"); if ( sscanf(line, "%16c",Ptrfmt) != 1) IOHBTerminate("iohb.c: Invalid format info, line 4 of Harwell-Boeing file.\n"); if ( sscanf(line, "%*16c%16c",Indfmt) != 1) IOHBTerminate("iohb.c: Invalid format info, line 4 of Harwell-Boeing file.\n"); if ( sscanf(line, "%*16c%*16c%20c",Valfmt) != 1) IOHBTerminate("iohb.c: Invalid format info, line 4 of Harwell-Boeing file.\n"); sscanf(line, "%*16c%*16c%*20c%20c",Rhsfmt); *(Ptrfmt+16) = (char) NULL; *(Indfmt+16) = (char) NULL; *(Valfmt+20) = (char) NULL; *(Rhsfmt+20) = (char) NULL; /* (Optional) Fifth line: */ if (*Rhscrd != 0 ) { fgets(line, BUFSIZ, in_file); if ( sscanf(line,"%*s") < 0 ) IOHBTerminate("iohb.c: Null (or blank) fifth line of HB file.\n"); if ( sscanf(line, "%3c", Rhstype) != 1) IOHBTerminate("iohb.c: Invalid RHS type information, line 5 of Harwell-Boeing file.\n"); if ( sscanf(line, "%*3c%i", Nrhs) != 1) *Nrhs = 0; if ( sscanf(line, "%*3c%*i%i", Nrhsix) != 1) *Nrhsix = 0; } return 1; } int readHB_mat_double(const char* filename, int colptr[], int rowind[], double val[]) { /****************************************************************************/ /* This function opens and reads the specified file, interpreting its */ /* contents as a sparse matrix stored in the Harwell/Boeing standard */ /* format and creating compressed column storage scheme vectors to hold */ /* the index and nonzero value information. */ /* */ /* ---------- */ /* **CAVEAT** */ /* ---------- */ /* Parsing real formats from Fortran is tricky, and this file reader */ /* does not claim to be foolproof. It has been tested for cases when */ /* the real values are printed consistently and evenly spaced on each */ /* line, with Fixed (F), and Exponential (E or D) formats. */ /* */ /* ** If the input file does not adhere to the H/B format, the ** */ /* ** results will be unpredictable. ** */ /* */ /****************************************************************************/ FILE *in_file; int i,j,ind,col,offset,count,last,Nrhs,Nrhsix; int Ptrcrd, Indcrd, Valcrd, Rhscrd; int Nrow, Ncol, Nnzero, Nentries; int Ptrperline, Ptrwidth, Indperline, Indwidth; int Valperline, Valwidth, Valprec; int Valflag; /* Indicates 'E','D', or 'F' float format */ char* ThisElement; char Title[73], Key[9], Type[4], Rhstype[4]; char Ptrfmt[17], Indfmt[17], Valfmt[21], Rhsfmt[21]; char line[BUFSIZ]; if ( (in_file = fopen( filename, "r")) == NULL ) { fprintf(stderr,"Error: Cannot open file: %s\n",filename); return 0; } readHB_header(in_file, Title, Key, Type, &Nrow, &Ncol, &Nnzero, &Nrhs, &Nrhsix, Ptrfmt, Indfmt, Valfmt, Rhsfmt, &Ptrcrd, &Indcrd, &Valcrd, &Rhscrd, Rhstype); /* Parse the array input formats from Line 3 of HB file */ ParseIfmt(Ptrfmt,&Ptrperline,&Ptrwidth); ParseIfmt(Indfmt,&Indperline,&Indwidth); if ( Type[0] != 'P' ) { /* Skip if pattern only */ ParseRfmt(Valfmt,&Valperline,&Valwidth,&Valprec,&Valflag); } /* Read column pointer array: */ offset = 1-_SP_base; /* if base 0 storage is declared (via macro definition), */ /* then storage entries are offset by 1 */ ThisElement = (char *) malloc(Ptrwidth+1); if ( ThisElement == NULL ) IOHBTerminate("Insufficient memory for ThisElement."); *(ThisElement+Ptrwidth) = (char) NULL; count=0; for (i=0;i Ncol) break; strncpy(ThisElement,line+col,Ptrwidth); /* ThisElement = substr(line,col,Ptrwidth); */ colptr[count] = atoi(ThisElement)-offset; count++; col += Ptrwidth; } } free(ThisElement); /* Read row index array: */ ThisElement = (char *) malloc(Indwidth+1); if ( ThisElement == NULL ) IOHBTerminate("Insufficient memory for ThisElement."); *(ThisElement+Indwidth) = (char) NULL; count = 0; for (i=0;i=0;j--) { ThisElement[j] = ThisElement[j-1]; if ( ThisElement[j] == '+' || ThisElement[j] == '-' ) { ThisElement[j-1] = Valflag; break; } } } val[count] = atof(ThisElement); count++; col += Valwidth; } } free(ThisElement); } fclose(in_file); return 1; } int readHB_newmat_double(const char* filename, int* M, int* N, int* nonzeros, int** colptr, int** rowind, double** val) { int Nrhs; char *Type; readHB_info(filename, M, N, nonzeros, &Type, &Nrhs); *colptr = (int *)malloc((*N+1)*sizeof(int)); if ( *colptr == NULL ) IOHBTerminate("Insufficient memory for colptr.\n"); *rowind = (int *)malloc(*nonzeros*sizeof(int)); if ( *rowind == NULL ) IOHBTerminate("Insufficient memory for rowind.\n"); if ( Type[0] == 'C' ) { /* fprintf(stderr, "Warning: Reading complex data from HB file %s.\n",filename); fprintf(stderr, " Real and imaginary parts will be interlaced in val[].\n"); */ /* Malloc enough space for real AND imaginary parts of val[] */ *val = (double *)malloc(*nonzeros*sizeof(double)*2); if ( *val == NULL ) IOHBTerminate("Insufficient memory for val.\n"); } else { if ( Type[0] != 'P' ) { /* Malloc enough space for real array val[] */ *val = (double *)malloc(*nonzeros*sizeof(double)); if ( *val == NULL ) IOHBTerminate("Insufficient memory for val.\n"); } } /* No val[] space needed if pattern only */ return readHB_mat_double(filename, *colptr, *rowind, *val); } int readHB_aux_double(const char* filename, const char AuxType, double b[]) { /****************************************************************************/ /* This function opens and reads the specified file, placing auxillary */ /* vector(s) of the given type (if available) in b. */ /* Return value is the number of vectors successfully read. */ /* */ /* AuxType = 'F' full right-hand-side vector(s) */ /* AuxType = 'G' initial Guess vector(s) */ /* AuxType = 'X' eXact solution vector(s) */ /* */ /* ---------- */ /* **CAVEAT** */ /* ---------- */ /* Parsing real formats from Fortran is tricky, and this file reader */ /* does not claim to be foolproof. It has been tested for cases when */ /* the real values are printed consistently and evenly spaced on each */ /* line, with Fixed (F), and Exponential (E or D) formats. */ /* */ /* ** If the input file does not adhere to the H/B format, the ** */ /* ** results will be unpredictable. ** */ /* */ /****************************************************************************/ FILE *in_file; int i,j,n,maxcol,start,stride,col,last,linel; int Ptrcrd, Indcrd, Valcrd, Rhscrd; int Nrow, Ncol, Nnzero, Nentries; int Nrhs, Nrhsix, nvecs, rhsi; int Rhsperline, Rhswidth, Rhsprec; int Rhsflag; char *ThisElement; char Title[73], Key[9], Type[4], Rhstype[4]; char Ptrfmt[17], Indfmt[17], Valfmt[21], Rhsfmt[21]; char line[BUFSIZ]; if ((in_file = fopen( filename, "r")) == NULL) { fprintf(stderr,"Error: Cannot open file: %s\n",filename); return 0; } readHB_header(in_file, Title, Key, Type, &Nrow, &Ncol, &Nnzero, &Nrhs, &Nrhsix, Ptrfmt, Indfmt, Valfmt, Rhsfmt, &Ptrcrd, &Indcrd, &Valcrd, &Rhscrd, Rhstype); if (Nrhs <= 0) { fprintf(stderr, "Warn: Attempt to read auxillary vector(s) when none are present.\n"); return 0; } if (Rhstype[0] != 'F' ) { fprintf(stderr,"Warn: Attempt to read auxillary vector(s) which are not stored in Full form.\n"); fprintf(stderr," Rhs must be specified as full. \n"); return 0; } /* If reading complex data, allow for interleaved real and imaginary values. */ if ( Type[0] == 'C' ) { Nentries = 2*Nrow; } else { Nentries = Nrow; } nvecs = 1; if ( Rhstype[1] == 'G' ) nvecs++; if ( Rhstype[2] == 'X' ) nvecs++; if ( AuxType == 'G' && Rhstype[1] != 'G' ) { fprintf(stderr, "Warn: Attempt to read auxillary Guess vector(s) when none are present.\n"); return 0; } if ( AuxType == 'X' && Rhstype[2] != 'X' ) { fprintf(stderr, "Warn: Attempt to read auxillary eXact solution vector(s) when none are present.\n"); return 0; } ParseRfmt(Rhsfmt, &Rhsperline, &Rhswidth, &Rhsprec,&Rhsflag); maxcol = Rhsperline*Rhswidth; /* Lines to skip before starting to read RHS values... */ n = Ptrcrd + Indcrd + Valcrd; for (i = 0; i < n; i++) fgets(line, BUFSIZ, in_file); /* start - number of initial aux vector entries to skip */ /* to reach first vector requested */ /* stride - number of aux vector entries to skip between */ /* requested vectors */ if ( AuxType == 'F' ) start = 0; else if ( AuxType == 'G' ) start = Nentries; else start = (nvecs-1)*Nentries; stride = (nvecs-1)*Nentries; fgets(line, BUFSIZ, in_file); linel= strchr(line,'\n')-line; col = 0; /* Skip to initial offset */ for (i=0;i= ( maxcol= ( maxcol=0;j--) { ThisElement[j] = ThisElement[j-1]; if ( ThisElement[j] == '+' || ThisElement[j] == '-' ) { ThisElement[j-1] = Rhsflag; break; } } } b[i] = atof(ThisElement); col += Rhswidth; } /* Skip any interleaved Guess/eXact vectors */ for (i=0;i= ( maxcol 0 ) { if ( Rhsfmt == NULL ) Rhsfmt = Valfmt; ParseRfmt(Rhsfmt,&Rhsperline,&Rhswidth,&Rhsprec, &Rhsflag); if (Rhsflag == 'F') sprintf(rformat,"%% %d.%df",Rhswidth,Rhsprec); else sprintf(rformat,"%% %d.%dE",Rhswidth,Rhsprec); if (Rhsflag == 'D') *strchr(Rhsfmt,'D') = 'E'; rhscrd = nrhsentries/Rhsperline; if ( nrhsentries%Rhsperline != 0) rhscrd++; if ( Rhstype[1] == 'G' ) rhscrd+=rhscrd; if ( Rhstype[2] == 'X' ) rhscrd+=rhscrd; rhscrd*=Nrhs; } else rhscrd = 0; totcrd = 4+ptrcrd+indcrd+valcrd+rhscrd; /* Print header information: */ fprintf(out_file,"%-72s%-8s\n%14d%14d%14d%14d%14d\n",Title, Key, totcrd, ptrcrd, indcrd, valcrd, rhscrd); fprintf(out_file,"%3s%11s%14d%14d%14d\n",Type," ", M, N, nz); fprintf(out_file,"%-16s%-16s%-20s", Ptrfmt, Indfmt, Valfmt); if ( Nrhs != 0 ) { /* Print Rhsfmt on fourth line and */ /* optional fifth header line for auxillary vector information: */ fprintf(out_file,"%-20s\n%-14s%d\n",Rhsfmt,Rhstype,Nrhs); } else fprintf(out_file,"\n"); offset = 1-_SP_base; /* if base 0 storage is declared (via macro definition), */ /* then storage entries are offset by 1 */ /* Print column pointers: */ for (i=0;i 0 ) { for (i=0;i Ncol) break; strncpy(ThisElement,line+col,Ptrwidth); /*ThisElement = substr(line,col,Ptrwidth);*/ colptr[count] = atoi(ThisElement)-offset; count++; col += Ptrwidth; } } free(ThisElement); /* Read row index array: */ ThisElement = (char *) malloc(Indwidth+1); if ( ThisElement == NULL ) IOHBTerminate("Insufficient memory for ThisElement."); *(ThisElement+Indwidth) = (char) NULL; count = 0; for (i=0;i=0;j--) { ThisElement[j] = ThisElement[j-1]; if ( ThisElement[j] == '+' || ThisElement[j] == '-' ) { ThisElement[j-1] = Valflag; break; } } } count++; col += Valwidth; } } } return 1; } int readHB_newmat_char(const char* filename, int* M, int* N, int* nonzeros, int** colptr, int** rowind, char** val, char** Valfmt) { FILE *in_file; int Nrhs,Nrhsix; int Ptrcrd, Indcrd, Valcrd, Rhscrd; int Valperline, Valwidth, Valprec; int Valflag; /* Indicates 'E','D', or 'F' float format */ char Title[73], Key[9], Type[4], Rhstype[4]; char Ptrfmt[17], Indfmt[17], Rhsfmt[21]; if ((in_file = fopen( filename, "r")) == NULL) { fprintf(stderr,"Error: Cannot open file: %s\n",filename); return 0; } *Valfmt = (char *)malloc(21*sizeof(char)); if ( *Valfmt == NULL ) IOHBTerminate("Insufficient memory for Valfmt."); readHB_header(in_file, Title, Key, Type, M, N, nonzeros, &Nrhs, &Nrhsix, Ptrfmt, Indfmt, (*Valfmt), Rhsfmt, &Ptrcrd, &Indcrd, &Valcrd, &Rhscrd, Rhstype); fclose(in_file); ParseRfmt(*Valfmt,&Valperline,&Valwidth,&Valprec,&Valflag); *colptr = (int *)malloc((*N+1)*sizeof(int)); if ( *colptr == NULL ) IOHBTerminate("Insufficient memory for colptr.\n"); *rowind = (int *)malloc(*nonzeros*sizeof(int)); if ( *rowind == NULL ) IOHBTerminate("Insufficient memory for rowind.\n"); if ( Type[0] == 'C' ) { /* fprintf(stderr, "Warning: Reading complex data from HB file %s.\n",filename); fprintf(stderr, " Real and imaginary parts will be interlaced in val[].\n"); */ /* Malloc enough space for real AND imaginary parts of val[] */ *val = (char *)malloc(*nonzeros*Valwidth*sizeof(char)*2); if ( *val == NULL ) IOHBTerminate("Insufficient memory for val.\n"); } else { if ( Type[0] != 'P' ) { /* Malloc enough space for real array val[] */ *val = (char *)malloc(*nonzeros*Valwidth*sizeof(char)); if ( *val == NULL ) IOHBTerminate("Insufficient memory for val.\n"); } } /* No val[] space needed if pattern only */ return readHB_mat_char(filename, *colptr, *rowind, *val, *Valfmt); } int readHB_aux_char(const char* filename, const char AuxType, char b[]) { /****************************************************************************/ /* This function opens and reads the specified file, placing auxilary */ /* vector(s) of the given type (if available) in b : */ /* Return value is the number of vectors successfully read. */ /* */ /* AuxType = 'F' full right-hand-side vector(s) */ /* AuxType = 'G' initial Guess vector(s) */ /* AuxType = 'X' eXact solution vector(s) */ /* */ /* ---------- */ /* **CAVEAT** */ /* ---------- */ /* Parsing real formats from Fortran is tricky, and this file reader */ /* does not claim to be foolproof. It has been tested for cases when */ /* the real values are printed consistently and evenly spaced on each */ /* line, with Fixed (F), and Exponential (E or D) formats. */ /* */ /* ** If the input file does not adhere to the H/B format, the ** */ /* ** results will be unpredictable. ** */ /* */ /****************************************************************************/ FILE *in_file; int i,j,n,maxcol,start,stride,col,last,linel,nvecs,rhsi; int Nrow, Ncol, Nnzero, Nentries,Nrhs,Nrhsix; int Ptrcrd, Indcrd, Valcrd, Rhscrd; int Rhsperline, Rhswidth, Rhsprec; int Rhsflag; char Title[73], Key[9], Type[4], Rhstype[4]; char Ptrfmt[17], Indfmt[17], Valfmt[21], Rhsfmt[21]; char line[BUFSIZ]; char *ThisElement; if ((in_file = fopen( filename, "r")) == NULL) { fprintf(stderr,"Error: Cannot open file: %s\n",filename); return 0; } readHB_header(in_file, Title, Key, Type, &Nrow, &Ncol, &Nnzero, &Nrhs, &Nrhsix, Ptrfmt, Indfmt, Valfmt, Rhsfmt, &Ptrcrd, &Indcrd, &Valcrd, &Rhscrd, Rhstype); if (Nrhs <= 0) { fprintf(stderr, "Warn: Attempt to read auxillary vector(s) when none are present.\n"); return 0; } if (Rhstype[0] != 'F' ) { fprintf(stderr,"Warn: Attempt to read auxillary vector(s) which are not stored in Full form.\n"); fprintf(stderr," Rhs must be specified as full. \n"); return 0; } /* If reading complex data, allow for interleaved real and imaginary values. */ if ( Type[0] == 'C' ) { Nentries = 2*Nrow; } else { Nentries = Nrow; } nvecs = 1; if ( Rhstype[1] == 'G' ) nvecs++; if ( Rhstype[2] == 'X' ) nvecs++; if ( AuxType == 'G' && Rhstype[1] != 'G' ) { fprintf(stderr, "Warn: Attempt to read auxillary Guess vector(s) when none are present.\n"); return 0; } if ( AuxType == 'X' && Rhstype[2] != 'X' ) { fprintf(stderr, "Warn: Attempt to read auxillary eXact solution vector(s) when none are present.\n"); return 0; } ParseRfmt(Rhsfmt, &Rhsperline, &Rhswidth, &Rhsprec,&Rhsflag); maxcol = Rhsperline*Rhswidth; /* Lines to skip before starting to read RHS values... */ n = Ptrcrd + Indcrd + Valcrd; for (i = 0; i < n; i++) fgets(line, BUFSIZ, in_file); /* start - number of initial aux vector entries to skip */ /* to reach first vector requested */ /* stride - number of aux vector entries to skip between */ /* requested vectors */ if ( AuxType == 'F' ) start = 0; else if ( AuxType == 'G' ) start = Nentries; else start = (nvecs-1)*Nentries; stride = (nvecs-1)*Nentries; fgets(line, BUFSIZ, in_file); linel= strchr(line,'\n')-line; if ( sscanf(line,"%*s") < 0 ) IOHBTerminate("iohb.c: Null (or blank) line in auxillary vector data region of HB file.\n"); col = 0; /* Skip to initial offset */ for (i=0;i= ( maxcol= ( maxcol=0;j--) { ThisElement[j] = ThisElement[j-1]; if ( ThisElement[j] == '+' || ThisElement[j] == '-' ) { ThisElement[j-1] = Rhsflag; break; } } } col += Rhswidth; } b+=Nentries*Rhswidth; /* Skip any interleaved Guess/eXact vectors */ for (i=0;i= ( maxcol 0 ) { if ( Rhsfmt == NULL ) Rhsfmt = Valfmt; ParseRfmt(Rhsfmt,&Rhsperline,&Rhswidth,&Rhsprec, &Rhsflag); sprintf(rformat,"%%%ds",Rhswidth); rhscrd = nrhsentries/Rhsperline; if ( nrhsentries%Rhsperline != 0) rhscrd++; if ( Rhstype[1] == 'G' ) rhscrd+=rhscrd; if ( Rhstype[2] == 'X' ) rhscrd+=rhscrd; rhscrd*=Nrhs; } else rhscrd = 0; totcrd = 4+ptrcrd+indcrd+valcrd+rhscrd; /* Print header information: */ fprintf(out_file,"%-72s%-8s\n%14d%14d%14d%14d%14d\n",Title, Key, totcrd, ptrcrd, indcrd, valcrd, rhscrd); fprintf(out_file,"%3s%11s%14d%14d%14d\n",Type," ", M, N, nz); fprintf(out_file,"%-16s%-16s%-20s", Ptrfmt, Indfmt, Valfmt); if ( Nrhs != 0 ) { /* Print Rhsfmt on fourth line and */ /* optional fifth header line for auxillary vector information: */ fprintf(out_file,"%-20s\n%-14s%d\n",Rhsfmt,Rhstype,Nrhs); } else fprintf(out_file,"\n"); offset = 1-_SP_base; /* if base 0 storage is declared (via macro definition), */ /* then storage entries are offset by 1 */ /* Print column pointers: */ for (i=0;i 0 ) { for (j=0;j void upcase(char* S) { /* Convert S to uppercase */ int i,len; len = strlen(S); for (i=0;i< len;i++) S[i] = toupper(S[i]); } void IOHBTerminate(char* message) { fprintf(stderr,message); exit(1); } MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/sparselib.c0000664000175000017500000005121211141443436021462 0ustar lauerlauer #include #include #include #include #include "commonlib.h" #include "myblas.h" #include "sparselib.h" sparseMatrix *createMatrix(int dimLimit, int lenLimit, int initVectors) { int initsize; sparseMatrix *matrix; if(initVectors < 0) initVectors = 0; if(initVectors == 0) initsize = MIN(INITIALSIZE, dimLimit); else initsize = MAX(INITIALSIZE, initVectors); CALLOC(matrix, 1); matrix->limit = dimLimit; matrix->limitVector = lenLimit; resizeMatrix(matrix, initsize); while(initVectors > 0) { initVectors--; appendMatrix(matrix, createVector(lenLimit, 2)); } return(matrix); } void resizeMatrix(sparseMatrix *matrix, int newSize) { int oldSize; if(matrix == NULL) oldSize = 0; else oldSize = matrix->size; while(oldSize>newSize) { oldSize--; freeVector(matrix->list[oldSize]); return; } REALLOC(matrix->list, newSize); while(oldSizelist[oldSize] = NULL; oldSize++; } if(newSize>0) matrix->size = newSize; } int appendMatrix(sparseMatrix *matrix, sparseVector *newVector) { if(matrix->count == matrix->size) resizeMatrix(matrix, matrix->size + 10); matrix->list[matrix->count] = newVector; matrix->count++; putDiagonalIndex(newVector, matrix->count); return(matrix->count); } int NZcountMatrix(sparseMatrix *matrix) { int i, nz; nz = 0; for(i = 0; i < matrix->count; i++) nz += matrix->list[i]->count; return( nz ); } void freeMatrix(sparseMatrix *matrix) { resizeMatrix(matrix, 0); FREE(matrix); } void printMatrix(int n, sparseMatrix *matrix, int modulo, MYBOOL showEmpty) { int i; for(i = 1; i<=matrix->count; i++) if(matrix->list[i-1] != NULL) { if(showEmpty || matrix->list[i-1]->count>0) printVector(n, matrix->list[i-1], modulo); } } sparseVector *createVector(int dimLimit, int initSize) { sparseVector *newitem; CALLOC(newitem, 1); newitem->limit = dimLimit; initSize = resizeVector(newitem, initSize); return(newitem); } sparseVector *cloneVector(sparseVector *sparse) { sparseVector *hold; hold = createVector(sparse->limit, sparse->count); hold->count = sparse->count; MEMCOPY(&hold->value[0], &sparse->value[0], (sparse->count+1)); MEMCOPY(&hold->index[0], &sparse->index[0], (sparse->count+1)); return(hold); } int redimensionVector(sparseVector *sparse, int newDim) { int olddim, i; olddim = sparse->limit; sparse->limit = newDim; if(lastIndex(sparse)>newDim) { i = sparse->count; while(i>0 && sparse->index[i]>newDim) i--; sparse->count = i; resizeVector(sparse, sparse->count); } return(olddim); } int resizeVector(sparseVector *sparse, int newSize) { int oldsize; oldsize = sparse->size; REALLOC(sparse->value, (newSize+1)); REALLOC(sparse->index, (newSize+1)); sparse->size = newSize; return(oldsize); } void moveVector(sparseVector *sparse, int destPos, int sourcePos, int itemCount) { int i; if(itemCount <= 0 || sourcePos == destPos) return; #if defined DOFASTMATH if(TRUE) { MEMMOVE(&sparse->value[destPos], &sparse->value[sourcePos], itemCount); MEMMOVE(&sparse->index[destPos], &sparse->index[sourcePos], itemCount); } else { int *idxPtr1, *idxPtr2; double *valPtr1, *valPtr2; for(i = 1, idxPtr1 = sparse->index+destPos, idxPtr2 = sparse->index+sourcePos, valPtr1 = sparse->value+destPos, valPtr2 = sparse->value+sourcePos; i<=itemCount; i++, idxPtr1++, idxPtr2++, valPtr1++, valPtr2++) { *idxPtr1 = *idxPtr2; *valPtr1 = *valPtr2; } } #else for(i = 1; i<=itemCount; i++) { sparse->value[destPos] = sparse->value[sourcePos]; sparse->index[destPos] = sparse->index[sourcePos]; destPos++; sourcePos++; } #endif } void rotateVector(sparseVector *sparse, int startPos, int chainSize, int stepDelta) { /* int idxHold; */ /* double valHold; */ } void swapVector(sparseVector *sparse1, sparseVector *sparse2) { int n, m, *idx; REAL *val; n = sparse1->count; sparse1->count = sparse2->count; sparse2->count = n; n = sparse1->size; sparse1->size = sparse2->size; sparse2->size = n; n = sparse1->limit; sparse1->limit = sparse2->limit; sparse2->limit = n; idx = sparse1->index; sparse1->index = sparse2->index; sparse2->index = idx; val = sparse1->value; sparse1->value = sparse2->value; sparse2->value = val; n = getDiagonalIndex(sparse1); m = getDiagonalIndex(sparse2); putDiagonalIndex(sparse1, m); putDiagonalIndex(sparse2, n); } void freeVector(sparseVector *sparse) { if(sparse != NULL) { FREE(sparse->value); FREE(sparse->index); FREE(sparse); } } MYBOOL verifyVector(sparseVector *sparse) { int i, n, k1, k2, kd; int err = 0; double vd; n = sparse->count; kd = sparse->index[0]; vd = sparse->value[0]; if(n <= 1) return(TRUE); k1 = 0; k2 = sparse->index[1]; if(k2 == kd && sparse->value[1] != vd) err = 2; for(i = 2; i <= n && err == 0; i++) { k1 = k2; k2 = sparse->index[i]; if(k1 >= k2) err = 1; if(k2 == kd && sparse->value[i] != vd) err = 2; } if(err == 0) return(TRUE); else if(err == 1) printf("Invalid sparse vector index order"); else if(err == 2) printf("Invalid sparse vector diagonal value"); return(FALSE); } int firstIndex(sparseVector *sparse) { return(sparse->index[1]); } int lastIndex(sparseVector *sparse) { return(sparse->index[sparse->count]); } int getDiagonalIndex(sparseVector *sparse) { return(sparse->index[0]); } int putDiagonalIndex(sparseVector *sparse, int index) { int oldindex; oldindex = sparse->index[0]; if(index > 0) { sparse->index[0] = 0; /* Must temporarily set to zero to force vector search in getItem */ sparse->value[0] = getItem(sparse, index); } else sparse->value[0] = 0; sparse->index[0] = index; return(oldindex); } MYBOOL putDiagonal(sparseVector *sparse, REAL value) { if(sparse->index[0]>0) { putItem(sparse, sparse->index[0], value); return(TRUE); } else return(FALSE); } REAL getDiagonal(sparseVector *sparse) { return(sparse->value[0]); } REAL getItem(sparseVector *sparse, int targetIndex) { /* First check if we want the diagonal element */ if(targetIndex == sparse->index[0]) return(sparse->value[0]); /* If not, search for the variable's position in the index list */ targetIndex = findIndex(targetIndex, sparse->index, sparse->count, BLAS_BASE); if(targetIndex < 0) return(0); else return(sparse->value[targetIndex]); } REAL addtoItem(sparseVector *sparse, int targetIndex, REAL value) { int idx; if(targetIndex > 0) idx = findIndex(targetIndex, sparse->index, sparse->count, BLAS_BASE); else { idx = -targetIndex; if(idx > sparse->count) /* Index error; ignore item */ return(0.0); } if(idx <=0 ) value = putItem(sparse, targetIndex, value); else { value += sparse->value[idx]; putItem(sparse, -idx, value); } return(value); } REAL putItem(sparseVector *sparse, int targetIndex, REAL value) { REAL last = 0.0; int posIndex; if(targetIndex < 0) { posIndex = -targetIndex; if(posIndex > sparse->count) return(last); targetIndex = sparse->index[posIndex]; } else posIndex = findIndex(targetIndex, sparse->index, sparse->count, BLAS_BASE); if(fabs(value) < MACHINEPREC) value = 0; if(targetIndex == sparse->index[0]) sparse->value[0] = value; if(posIndex < 0) { if(value != 0) { if(sparse->count == sparse->size) resizeVector(sparse, sparse->size + RESIZEDELTA); posIndex = -posIndex; sparse->count++; if(posIndex < sparse->count) moveVector(sparse, posIndex+1, posIndex, sparse->count-posIndex); sparse->value[posIndex] = value; sparse->index[posIndex] = targetIndex; } } else { if(value == 0) { last = sparse->value[posIndex]; if(sparse->count > posIndex) moveVector(sparse, posIndex, posIndex+1, sparse->count-posIndex); sparse->count--; } else { sparse->value[posIndex] = value; sparse->index[posIndex] = targetIndex; } } #ifdef DEBUG_SPARSELIB verifyVector(sparse); #endif return(last); } void swapItems(sparseVector *sparse, int firstIndex, int secondIndex) { int i,j,ki,kj; REAL hold; if(firstIndex == secondIndex) return; if(firstIndex > secondIndex) { i = firstIndex; firstIndex = secondIndex; secondIndex = i; } if(FALSE) { i = 1; ki = 0; while(i <= sparse->count && (ki = sparse->index[i])count && (kj = sparse->index[j])index, sparse->count, BLAS_BASE); if(i < 0) i = -i; j = findIndex(secondIndex, sparse->index, sparse->count, BLAS_BASE); if(j < 0) j = -j; } if(i > sparse->count) ki = 0; else ki = sparse->index[i]; if(j > sparse->count) kj = 0; else kj = sparse->index[j]; if(ki == firstIndex && kj == secondIndex) { /* Found both -> swap in place */ hold = sparse->value[i]; sparse->value[i] = sparse->value[j]; sparse->value[j] = hold; if(sparse->index[0] == firstIndex) sparse->value[0] = sparse->value[i]; else if(sparse->index[0] == secondIndex) sparse->value[0] = sparse->value[j]; } else if(ki == firstIndex) { /* Found first, but not the second -> shift left */ j--; if(i < j) { hold = sparse->value[i]; moveVector(sparse, i, i+1, j-i); sparse->value[j] = hold; } sparse->index[j] = secondIndex; if(sparse->index[0] == firstIndex) sparse->value[0] = 0; else if(sparse->index[0] == secondIndex) sparse->value[0] = sparse->value[j]; } else if(kj == secondIndex) { /* Found second, but not the first -> shift right */ if(i < j) { hold = sparse->value[j]; moveVector(sparse, i+1, i, j-i); sparse->value[i] = hold; } sparse->index[i] = firstIndex; if(sparse->index[0] == firstIndex) sparse->value[0] = sparse->value[i]; else if(sparse->index[0] == secondIndex) sparse->value[0] = 0; } #ifdef DEBUG_SPARSELIB verifyVector(sparse); #endif } void clearVector(sparseVector *sparse, int indexStart, int indexEnd) { int i; i = sparse->count; if(i==0) return; if(indexStart<=0) indexStart=sparse->index[1]; if(indexEnd<=0) indexEnd=sparse->index[i]; if(indexStart>indexEnd) return; if(sparse->index[0]>=indexStart && sparse->index[0]<=indexEnd) { sparse->value[0] = 0; } if(indexStart<=sparse->index[1] && indexEnd>=sparse->index[i]) sparse->count = 0; else { while(i>0 && sparse->index[i]>indexEnd) i--; indexEnd = i; while(i>0 && sparse->index[i]>=indexStart) i--; indexStart = i+1; if(indexEnd>=indexStart) { i = sparse->count-indexEnd; moveVector(sparse, indexStart, indexEnd+1, i); sparse->count -= indexEnd-indexStart+1; } } #ifdef DEBUG_SPARSELIB verifyVector(sparse); #endif } int getVector(sparseVector *sparse, REAL *dense, int indexStart, int indexEnd, MYBOOL doClear) { int i,k; i = 1; while(i<=sparse->count && sparse->index[i]count && (k=sparse->index[i])<=indexEnd) { while(indexStartvalue[i]; indexStart++; i++; } while(indexStart<=indexEnd) { dense[indexStart] = 0; indexStart++; } k = sparse->count; if(doClear) { sparse->count = 0; sparse->value[0] = 0; } return(k); } void putVector(sparseVector *sparse, REAL *dense, int indexStart, int indexEnd) { int i,n; n = sparse->count; if(indexStart<=0) indexStart=sparse->index[1]; if(indexEnd<=0) indexEnd=sparse->index[n]; if(n==0 || sparse->index[n]index[0]; if(i>=indexStart && i<=indexEnd) sparse->value[0] = 0; for(i = indexStart; i<=indexEnd; i++) { if(dense[i] == 0) continue; if(sparse->size == sparse->count) resizeVector(sparse, sparse->size + RESIZEDELTA); sparse->count++; sparse->value[sparse->count] = dense[i]; sparse->index[sparse->count] = i; if(i == sparse->index[0]) sparse->value[0] = dense[i]; } } else { while(indexStart <= indexEnd) { putItem(sparse, indexStart, dense[indexStart]); indexStart++; } } #ifdef DEBUG_SPARSELIB verifyVector(sparse); #endif } void fillVector(sparseVector *sparse, int count, REAL value) { int i; if(sparse->count > 0) clearVector(sparse, 0, 0); for(i = 1; i<=count; i++) putItem(sparse, i, value); } REAL dotVector(sparseVector *sparse, REAL *dense, int indexStart, int indexEnd) { int i, n; long REAL sum; n = sparse->count; sum = 0; if(n > 0) { if(indexStart<=0) indexStart=sparse->index[1]; if(indexEnd<=0) indexEnd=sparse->index[n]; if(indexStart > 1) { i = findIndex(indexStart, sparse->index, sparse->count, BLAS_BASE); if(i < 0) { i = -i; if(i > n) return(sum); } } else i = 1; /* CPU intensive loop; provide alternative evaluation models */ #if defined DOFASTMATH { /* Do fast pointer arithmetic */ int *indexptr; REAL *valueptr; /* for(i = 1, indexptr = sparse->index + 1; i <= n && (*indexptr) < indexStart; i++, indexptr++); */ indexptr = sparse->index + i; for(valueptr = sparse->value + i; i <= n && (*indexptr) <= indexEnd; i++, indexptr++, valueptr++) sum += (*valueptr) * dense[(*indexptr)]; } #else { /* Do traditional indexed access */ int k; /* i = 1; */ /* while(i<=n && sparse->index[i]index[i])<=indexEnd) { sum += sparse->value[i] * dense[k]; i++; } } #endif } return(sum); } void daxpyVector1(sparseVector *sparse, REAL scalar, REAL *dense, int indexStart, int indexEnd) { int i, n; if(scalar == 0) return; n = sparse->count; if(indexStart<=0) indexStart=sparse->index[1]; if(indexEnd<=0) indexEnd=sparse->index[n]; /* CPU intensive loop; provide alternative evaluation models */ #if defined DOFASTMATH { /* Do fast pointer arithmetic */ int *indexptr; REAL *valueptr; for(i = 1, indexptr = sparse->index + 1; i <= n && (*indexptr) < indexStart; i++, indexptr++); for(valueptr = sparse->value + i; i <= n && (*indexptr) <= indexEnd; i++, indexptr++, valueptr++) dense[(*indexptr)] += (*valueptr) * scalar; } #else { /* Do traditional indexed access */ int k; for(i = 1; i<= n; i++) { k = sparse->index[i]; if(kindexEnd) break; dense[k] += sparse->value[i] * scalar; } } #endif } void daxpyVector2(REAL *dense, REAL scalar, sparseVector *sparse, int indexStart, int indexEnd) { sparseVector *hold; hold = createVector(sparse->limit, sparse->count); putDiagonalIndex(hold, getDiagonalIndex(sparse)); putVector(hold, dense, indexStart, indexEnd); daxpyVector3(hold, scalar, sparse, indexStart, indexEnd); freeVector(hold); } void daxpyVector3(sparseVector *sparse1, REAL scalar, sparseVector *sparse2, int indexStart, int indexEnd) { int i1, i2, k, p1, p2, c1, c2; sparseVector *hold; if(sparse1->count == 0) return; /* Spool to start positions */ i1 = 1; c1 = sparse1->count; while(i1 <= c1 && sparse1->index[i1] < indexStart) i1++; if(i1 <= c1) p1 = sparse1->index[i1]; else p1 = indexEnd+1; i2 = 1; c2 = sparse2->count; while(i2 <= c2 && sparse2->index[i2] < indexStart) i2++; if(i2 <= c2) p2 = sparse2->index[i2]; else p2 = indexEnd+1; /* Create a temporary vector */ k = c1+c2; if(k > 0) { hold = createVector(MAX(sparse1->limit, sparse2->limit), k); putDiagonalIndex(hold, getDiagonalIndex(sparse2)); } else hold = sparse2; /* Loop over all items in both vectors */ while((i1 <= c1 && p1 <= indexEnd) || (i2 <= c2 && p2 <= indexEnd)) { k = 0; /* Add/spool exclusive right-vector items */ while(i2 <= c2 && p2 < p1) { if(hold != sparse2) putItem(hold, p2, sparse2->value[i2]); i2++; if(i2 <= c2) p2 = sparse2->index[i2]; else p2 = indexEnd+1; k++; } /* Add equal-indexed items */ while(i1 <= c1 && i2 <= c2 && p1 == p2) { /* if(hold != sparse2) */ putItem(hold, p1, scalar*sparse1->value[i1]+sparse2->value[i2]); /* else addtoItem(sparse2, -i2, scalar*sparse1->value[i1]); */ i1++; if(i1 <= c1) p1 = sparse1->index[i1]; else p1 = indexEnd+1; i2++; if(i2 <= c2) p2 = sparse2->index[i2]; else p2 = indexEnd+1; k++; } /* Add exclusive left-vector items */ while(i1 <= c1 && p1 < p2) { putItem(hold, p1, scalar*sparse1->value[i1]); /* if(hold == sparse2) c2++; */ i1++; if(i1 <= c1) p1 = sparse1->index[i1]; else p1 = indexEnd+1; k++; } if(k == 0) break; } /* if(hold != sparse2) */ { swapVector(hold, sparse2); freeVector(hold); } #ifdef DEBUG_SPARSELIB verifyVector(sparse2); #endif } void dswapVector1(sparseVector *sparse, REAL *dense, int indexStart, int indexEnd) { int i, d, n; REAL *x; if(indexStart <= 0) indexStart = 1; n = lastIndex(sparse); if(indexEnd <= 0) indexEnd = n; CALLOC(x, (MAX(indexEnd,n)+1)); getVector(sparse, x, indexStart, n, FALSE); d = getDiagonalIndex(sparse); clearVector(sparse, indexStart, n); for(i = indexStart; i<=indexEnd; i++) { if(dense[i] != 0) putItem(sparse, i, dense[i]); } for(i = indexEnd+1; i<=n; i++) { if(x[i] != 0) putItem(sparse, i, x[i]); } MEMCOPY(&dense[indexStart], &x[indexStart], (indexEnd-indexStart+1)); #ifdef DEBUG_SPARSELIB verifyVector(sparse); #endif FREE(x); } void dswapVector2(REAL *dense, sparseVector *sparse, int indexStart, int indexEnd) { dswapVector1(sparse, dense, indexStart, indexEnd); } void dswapVector3(sparseVector *sparse1, sparseVector *sparse2, int indexStart, int indexEnd) { REAL *dense1, *dense2; if(indexStart<=0) indexStart = 1; if(indexEnd<=0) indexEnd = MAX(lastIndex(sparse1), lastIndex(sparse2)); if(indexStart <= firstIndex(sparse1) && indexStart <= firstIndex(sparse2) && indexEnd >= lastIndex(sparse1) && indexEnd >= lastIndex(sparse2)) { swapVector(sparse1, sparse2); } else { CALLOC(dense1, (indexEnd+1)); CALLOC(dense2, (indexEnd+1)); getVector(sparse1, dense1, indexStart, indexEnd, TRUE); getVector(sparse2, dense2, indexStart, indexEnd, TRUE); clearVector(sparse1, indexStart, indexEnd); clearVector(sparse2, indexStart, indexEnd); putVector(sparse1, dense2, indexStart, indexEnd); putVector(sparse2, dense1, indexStart, indexEnd); FREE(dense1); FREE(dense2); } } int idamaxVector(sparseVector *sparse, int is, REAL *maxValue) { int i, n, imax; REAL xmax; n = sparse->count; imax = 1; if(n == 0) xmax = 0; else { xmax = fabs(sparse->value[imax]); /* CPU intensive loop; provide alternative evaluation models */ #if defined DOFASTMATH { /* Do fast pointer arithmetic */ int *indexptr; REAL *valueptr; for(i = 1, indexptr = sparse->index + 1; i <= n && (*indexptr) <= is; i++, indexptr++); for(valueptr = sparse->value + i; i <= n; i++, indexptr++, valueptr++) { if((*valueptr)>xmax) { xmax = (*valueptr); imax = (*indexptr); } } } #else { REAL xtest; /* Do traditional indexed access */ i = 1; while(i <= n && sparse->index[i] <= is) i++; for(; i<=n; i++) { xtest = fabs(sparse->value[i]); if(xtest>xmax) { xmax = xtest; imax = sparse->index[i]; } } } #endif } if(maxValue != NULL) (*maxValue) = sparse->index[imax]; return(imax); } void printVector(int n, sparseVector *sparse, int modulo ) { int i,j,k; if(sparse == NULL) return; if (modulo <= 0) modulo = 5; for (i = 1, j = 1; j<=n; i++, j++) { if(i<=sparse->count) k = sparse->index[i]; else k = n+1; while (j < k) { if(mod(j, modulo) == 1) printf("\n%2d:%12g", j, 0.0); else printf(" %2d:%12g", j, 0.0); j++; } if(k<=n) { if(mod(j, modulo) == 1) printf("\n%2d:%12g", k, sparse->value[i]); else printf(" %2d:%12g", k, sparse->value[i]); } } if(mod(j, modulo) != 0) printf("\n"); } MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/sparselib.h0000664000175000017500000000563711141443437021502 0ustar lauerlauer #include "commonlib.h" /*#define DEBUG_SPARSELIB*/ #define INITIALSIZE 10 #define RESIZEDELTA 4 #ifndef SPARSELIB #define SPARSELIB typedef struct _sparseVector { int limit; int size; int count; int *index; REAL *value; } sparseVector; typedef struct _sparseMatrix { int limit; int size; int count; int limitVector; sparseVector **list; } sparseMatrix; #endif #ifdef __cplusplus extern "C" { #endif sparseMatrix *createMatrix(int dimLimit, int lenLimit, int initVectors); void resizeMatrix(sparseMatrix *matrix, int newSize); int appendMatrix(sparseMatrix *matrix, sparseVector *newVector); int NZcountMatrix(sparseMatrix *matrix); void freeMatrix(sparseMatrix *matrix); void printMatrix(int n, sparseMatrix *matrix, int modulo, MYBOOL showEmpty); sparseVector *createVector(int dimLimit, int initSize); sparseVector *cloneVector(sparseVector *sparse); int redimensionVector(sparseVector *sparse, int newDim); int resizeVector(sparseVector *sparse, int newSize); void moveVector(sparseVector *sparse, int destPos, int sourcePos, int itemCount); void rotateVector(sparseVector *sparse, int startPos, int chainSize, int stepDelta); void swapVector(sparseVector *sparse1, sparseVector *sparse2); void freeVector(sparseVector *sparse); void printVector(int n, sparseVector *sparse, int modulo); MYBOOL verifyVector(sparseVector *sparse); int firstIndex(sparseVector *sparse); int lastIndex(sparseVector *sparse); int getDiagonalIndex(sparseVector *sparse); int putDiagonalIndex(sparseVector *sparse, int index); MYBOOL putDiagonal(sparseVector *sparse, REAL value); REAL getDiagonal(sparseVector *sparse); REAL getItem(sparseVector *sparse, int targetIndex); REAL putItem(sparseVector *sparse, int targetIndex, REAL value); REAL addtoItem(sparseVector *sparse, int targetIndex, REAL value); void swapItems(sparseVector *sparse, int firstIndex, int secondIndex); void clearVector(sparseVector *sparse, int indexStart, int indexEnd); int getVector(sparseVector *sparse, REAL *dense, int indexStart, int indexEnd, MYBOOL doClear); void putVector(sparseVector *sparse, REAL *dense, int indexStart, int indexEnd); void fillVector(sparseVector *sparse, int count, REAL value); REAL dotVector(sparseVector *sparse, REAL *dense, int indexStart, int indexEnd); void daxpyVector1(sparseVector *sparse, REAL scalar, REAL *dense, int indexStart, int indexEnd); void daxpyVector2(REAL *dense, REAL scalar, sparseVector *sparse, int indexStart, int indexEnd); void daxpyVector3(sparseVector *sparse1, REAL scalar, sparseVector *sparse2, int indexStart, int indexEnd); void dswapVector1(sparseVector *sparse, REAL *dense, int indexStart, int indexEnd); void dswapVector2(REAL *dense, sparseVector *sparse, int indexStart, int indexEnd); void dswapVector3(sparseVector *sparse1, sparseVector *sparse2, int indexStart, int indexEnd); int idamaxVector(sparseVector *sparse, int is, REAL *maxValue); #ifdef __cplusplus } #endif MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/LUSOL_Overview.txt0000664000175000017500000001262311141374614022663 0ustar lauerlauer Notes for Contribution of LUSOL to COIN-OR May 2004 Introduction ============ LUSOL maintains sparse LU factors of a square or rectangular sparse matrix. It includes a Basis Factorization Package (BFP) suitable for implementing simplex and reduced-gradient methods for optimization. It is a set of routines written in ANSI C (adapted from the original Fortran 77 version). LUSOL includes the following features: - A Markowitz-based sparse LU factorization for square, rectangular and possibly singular matrices. - Three options for balancing sparsity and stability: Threshold Partial/Rook/Complete Pivoting (TPP, TRP, TCP). - Rank-revealing properties. TRP and TCP are intended for detecting singularities. - Dynamic storage allocation (C version only). - Stable column replacement as in the method of Bartels and Golub. - Other stable updates: add, replace, or delete row or column (currently F77 version only). - Implementation into an easy-to-use BFP API (C version only). Implementation ============== The Factor routine is similar to the classical Markowitz routines MA28 and LA05 in the Harwell Subroutine Library. The source matrix nonzeros are stored column-wise with the largest entry at the top of each column. Internally, the structure is also accessible row-wise. All entries in a particular column or row are held in contiguous storage. Fill is accommodated by moving a column or row to the beginning of free storage. Occasional compressions recover storage. This scheme is effective for column-oriented TPP. When the remaining matrix reaches a specified density, the factors are completed using dense processing. TRP uses an additional vector of storage to maintain the largest element in each remaining row. TCP uses a heap structure to hold the largest element in each column. The largest element in the remaining matrix is then available at the top of the heap. The final L is stored column-wise (and never changed). The final U is stored row-wise as a triangular or trapezoidal sparse matrix. Column replacements are implemented using a forward sweep of 2-by-2 stabilized elimination matrices. L is updated in product form. U is updated explicitly. The other updates use either forward or backward sweeps. They tend to generate more nonzeros than column replacement. Both the F77 and C versions contain extensive comments, method and implementational information as part of the code. The C version contains a record-based wrapper for the data. Function calls have been simplified by including references to this structure. New maintenance routines enable dynamic instance creation and destruction, and simplifies access to the most frequently used functions. The LUSOL C library is multi-instance and fully re-entrant. All control and output parameters have been given long descriptive names for usability. Benefits ======== Rank-revealing properties and rectangular factors (and updates) have not previously been available in sparse LU software. With sensible parameter settings and reasonably scaled data, all routines are numerically stable. The updates may be called hundreds of times, and the decision to refactorize can be based on sparsity considerations alone. In the Factor routine, rook pivoting (TRP) gives reliable rank determination without catastrophic degradation in sparsity or speed. Complete pivoting (TCP) is included for moderate-sized matrices and for checking pathological cases (but the factors tend to be substantially more dense). To conserve storage, one may request only the row and column pivot orders. The factors are discarded as they are computed. This is useful for basis repair, or for selecting a basis from a rectangular matrix. Known Inefficiencies ==================== LUSOL is usually efficient on sparse matrices with dimensions up to about 100,000 (but not millions). In the Factor routine, row and column lists must be updated each time a row and column is eliminated. Deleting the pivot row and column is inefficient if the original matrix contains unusually dense rows or columns. For TPP, dense columns could be kept aside and incorporated at the end via updates (but dense rows remain a difficulty). For TRP and TCP, all rows and columns must be present to achieve the required numerical properties. For TRP, the current bottleneck is updating the vector containing the largest element in each row. One solution would be to include the matrix nonzeros in the row structure (but this carries its own cost). For TCP, the heap structure is already efficient, but the dense factors (and the extended searching for acceptable pivots) are unavoidable expenses. The triangular Solve routines do not take full of advantage of sparse right-hand sides. Gilbert and Peierls have shown how to solve Lx = (sparse b) efficiently if L is stored column-wise. Their approach could therefore be implemented in LUSOL for solves with L and U(transpose). Solves with L(transpose) and U would need a second copy of L and U. Original Reference ================== P. E. Gill, W. Murray, M. A. Saunders and M. H. Wright, Maintaining LU factors of a general sparse matrix, Linear Algebra and its Applications 88/89, 239-270 (1987). Maintainers =========== F77 version: Michael Saunders (saunders@stanford.edu). C version: Kjell Eikland (kjell.eikland@broadpark.no). Contributors ============ Philip Gill, Walter Murray, Margaret Wright, Michael O'Sullivan. MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/LUSOL_LGPL.txt0000664000175000017500000006347411141374613021624 0ustar lauerlauer GNU LESSER GENERAL PUBLIC LICENSE Version 2.1, February 1999 Copyright (C) 1991, 1999 Free Software Foundation, Inc. 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed. [This is the first released version of the Lesser GPL. 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MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/myblas.c0000664000175000017500000004543211141443436020774 0ustar lauerlauer #include #include /*#include */ #include #include #include "myblas.h" #ifdef FORTIFY # include "lp_fortify.h" #endif /* ************************************************************************ */ /* Initialize BLAS interfacing routines */ /* ************************************************************************ */ MYBOOL mustinitBLAS = TRUE; #if (defined WIN32) || (defined WIN64) HINSTANCE hBLAS = NULL; #else void *hBLAS = NULL; #endif /* ************************************************************************ */ /* Function pointers for external BLAS library (C base 0) */ /* ************************************************************************ */ BLAS_dscal_func *BLAS_dscal; BLAS_dcopy_func *BLAS_dcopy; BLAS_daxpy_func *BLAS_daxpy; BLAS_dswap_func *BLAS_dswap; BLAS_ddot_func *BLAS_ddot; BLAS_idamax_func *BLAS_idamax; BLAS_idamin_func *BLAS_idamin; BLAS_dload_func *BLAS_dload; BLAS_dnormi_func *BLAS_dnormi; /* ************************************************************************ */ /* Define the BLAS interfacing routines */ /* ************************************************************************ */ void init_BLAS(void) { if(mustinitBLAS) { load_BLAS(NULL); mustinitBLAS = FALSE; } } MYBOOL is_nativeBLAS(void) { #ifdef LoadableBlasLib return( (MYBOOL) (hBLAS == NULL) ); #else return( TRUE ); #endif } MYBOOL load_BLAS(char *libname) { MYBOOL result = TRUE; #ifdef LoadableBlasLib if(hBLAS != NULL) { my_FreeLibrary(hBLAS); } #endif if(libname == NULL) { if(!mustinitBLAS && is_nativeBLAS()) return( FALSE ); BLAS_dscal = my_dscal; BLAS_dcopy = my_dcopy; BLAS_daxpy = my_daxpy; BLAS_dswap = my_dswap; BLAS_ddot = my_ddot; BLAS_idamax = my_idamax; BLAS_idamin = my_idamin; BLAS_dload = my_dload; BLAS_dnormi = my_dnormi; if(mustinitBLAS) mustinitBLAS = FALSE; } else { #ifdef LoadableBlasLib #if (defined WIN32) || (defined WIN64) char *blasname = libname; #else /* First standardize UNIX .SO library name format. */ char blasname[260]; if(!so_stdname(blasname, libname, 260)) return( FALSE ); #endif /* Get a handle to the Windows DLL module. */ hBLAS = my_LoadLibrary(blasname); /* If the handle is valid, try to get the function addresses. */ result = (MYBOOL) (hBLAS != NULL); if(result) { BLAS_dscal = (BLAS_dscal_func *) my_GetProcAddress(hBLAS, BLAS_prec "scal"); BLAS_dcopy = (BLAS_dcopy_func *) my_GetProcAddress(hBLAS, BLAS_prec "copy"); BLAS_daxpy = (BLAS_daxpy_func *) my_GetProcAddress(hBLAS, BLAS_prec "axpy"); BLAS_dswap = (BLAS_dswap_func *) my_GetProcAddress(hBLAS, BLAS_prec "swap"); BLAS_ddot = (BLAS_ddot_func *) my_GetProcAddress(hBLAS, BLAS_prec "dot"); BLAS_idamax = (BLAS_idamax_func *) my_GetProcAddress(hBLAS, "i" BLAS_prec "amax"); BLAS_idamin = (BLAS_idamin_func *) my_GetProcAddress(hBLAS, "i" BLAS_prec "amin"); #if 0 BLAS_dload = (BLAS_dload_func *) my_GetProcAddress(hBLAS, BLAS_prec "load"); BLAS_dnormi = (BLAS_dnormi_func *) my_GetProcAddress(hBLAS, BLAS_prec "normi"); #endif } #endif /* Do validation */ if(!result || ((BLAS_dscal == NULL) || (BLAS_dcopy == NULL) || (BLAS_daxpy == NULL) || (BLAS_dswap == NULL) || (BLAS_ddot == NULL) || (BLAS_idamax == NULL) || (BLAS_idamin == NULL) || (BLAS_dload == NULL) || (BLAS_dnormi == NULL)) ) { load_BLAS(NULL); result = FALSE; } } return( result ); } MYBOOL unload_BLAS(void) { return( load_BLAS(NULL) ); } /* ************************************************************************ */ /* Now define the unoptimized local BLAS functions */ /* ************************************************************************ */ void daxpy( int n, REAL da, REAL *dx, int incx, REAL *dy, int incy) { dx++; dy++; BLAS_daxpy( &n, &da, dx, &incx, dy, &incy); } void BLAS_CALLMODEL my_daxpy( int *_n, REAL *_da, REAL *dx, int *_incx, REAL *dy, int *_incy) { /* constant times a vector plus a vector. uses unrolled loops for increments equal to one. jack dongarra, linpack, 3/11/78. modified 12/3/93, array[1] declarations changed to array[*] */ int i, ix, iy; #ifndef DOFASTMATH int m, mp1; #endif register REAL rda; REAL da = *_da; int n = *_n, incx = *_incx, incy = *_incy; if (n <= 0) return; if (da == 0.0) return; dx--; dy--; ix = 1; iy = 1; if (incx < 0) ix = (-n+1)*incx + 1; if (incy < 0) iy = (-n+1)*incy + 1; rda = da; /* CPU intensive loop; option to do pointer arithmetic */ #if defined DOFASTMATH { REAL *xptr, *yptr; for (i = 1, xptr = dx + ix, yptr = dy + iy; i <= n; i++, xptr += incx, yptr += incy) (*yptr) += rda*(*xptr); } #else if (incx==1 && incy==1) goto x20; /* code for unequal increments or equal increments not equal to 1 */ for (i = 1; i<=n; i++) { dy[iy]+= rda*dx[ix]; ix+= incx; iy+= incy; } return; /* code for both increments equal to 1 */ /* clean-up loop */ x20: m = n % 4; if (m == 0) goto x40; for (i = 1; i<=m; i++) dy[i]+= rda*dx[i]; if(n < 4) return; x40: mp1 = m + 1; for (i = mp1; i<=n; i=i+4) { dy[i]+= rda*dx[i]; dy[i + 1]+= rda*dx[i + 1]; dy[i + 2]+= rda*dx[i + 2]; dy[i + 3]+= rda*dx[i + 3]; } #endif } /* ************************************************************************ */ void dcopy( int n, REAL *dx, int incx, REAL *dy, int incy) { dx++; dy++; BLAS_dcopy( &n, dx, &incx, dy, &incy); } void BLAS_CALLMODEL my_dcopy (int *_n, REAL *dx, int *_incx, REAL *dy, int *_incy) { /* copies a vector, x, to a vector, y. uses unrolled loops for increments equal to one. jack dongarra, linpack, 3/11/78. modified 12/3/93, array[1] declarations changed to array[*] */ int i, ix, iy; #ifndef DOFASTMATH int m, mp1; #endif int n = *_n, incx = *_incx, incy = *_incy; if(n<=0) return; dx--; dy--; ix = 1; iy = 1; if(incx<0) ix = (-n+1)*incx + 1; if(incy<0) iy = (-n+1)*incy + 1; /* CPU intensive loop; option to do pointer arithmetic */ #if defined DOFASTMATH { REAL *xptr, *yptr; for (i = 1, xptr = dx + ix, yptr = dy + iy; i <= n; i++, xptr += incx, yptr += incy) (*yptr) = (*xptr); } #else if(incx==1 && incy==1) goto x20; /* code for unequal increments or equal increments not equal to 1 */ for(i = 1; i<=n; i++) { dy[iy] = dx[ix]; ix+= incx; iy+= incy; } return; /* code for both increments equal to 1 */ /* version with fast machine copy logic (requires memory.h or string.h) */ x20: m = n % 7; if (m == 0) goto x40; for (i = 1; i<=m; i++) dy[i] = dx[i]; if (n < 7) return; x40: mp1 = m + 1; for (i = mp1; i<=n; i=i+7) { dy[i] = dx[i]; dy[i + 1] = dx[i + 1]; dy[i + 2] = dx[i + 2]; dy[i + 3] = dx[i + 3]; dy[i + 4] = dx[i + 4]; dy[i + 5] = dx[i + 5]; dy[i + 6] = dx[i + 6]; } #endif } /* ************************************************************************ */ void dscal (int n, REAL da, REAL *dx, int incx) { dx++; BLAS_dscal (&n, &da, dx, &incx); } void BLAS_CALLMODEL my_dscal (int *_n, REAL *_da, REAL *dx, int *_incx) { /* Multiply a vector by a constant. --Input-- N number of elements in input vector(s) DA double precision scale factor DX double precision vector with N elements INCX storage spacing between elements of DX --Output-- DX double precision result (unchanged if N.LE.0) Replace double precision DX by double precision DA*DX. For I = 0 to N-1, replace DX(IX+I*INCX) with DA * DX(IX+I*INCX), where IX = 1 if INCX .GE. 0, else IX = 1+(1-N)*INCX. */ int i; #ifndef DOFASTMATH int m, mp1, ix; #endif register REAL rda; REAL da = *_da; int n = *_n, incx = *_incx; if (n <= 0) return; rda = da; dx--; /* Optionally do fast pointer arithmetic */ #if defined DOFASTMATH { REAL *xptr; for (i = 1, xptr = dx + 1; i <= n; i++, xptr += incx) (*xptr) *= rda; } #else if (incx == 1) goto x20; /* Code for increment not equal to 1 */ ix = 1; if (incx < 0) ix = (-n+1)*incx + 1; for(i = 1; i <= n; i++, ix += incx) dx[ix] *= rda; return; /* Code for increment equal to 1. */ /* Clean-up loop so remaining vector length is a multiple of 5. */ x20: m = n % 5; if (m == 0) goto x40; for( i = 1; i <= m; i++) dx[i] *= rda; if (n < 5) return; x40: mp1 = m + 1; for(i = mp1; i <= n; i += 5) { dx[i] *= rda; dx[i+1] *= rda; dx[i+2] *= rda; dx[i+3] *= rda; dx[i+4] *= rda; } #endif } /* ************************************************************************ */ REAL ddot(int n, REAL *dx, int incx, REAL *dy, int incy) { dx++; dy++; return( BLAS_ddot (&n, dx, &incx, dy, &incy) ); } REAL BLAS_CALLMODEL my_ddot(int *_n, REAL *dx, int *_incx, REAL *dy, int *_incy) { /* forms the dot product of two vectors. uses unrolled loops for increments equal to one. jack dongarra, linpack, 3/11/78. modified 12/3/93, array[1] declarations changed to array[*] */ register REAL dtemp; int i, ix, iy; #ifndef DOFASTMATH int m, mp1; #endif int n = *_n, incx = *_incx, incy = *_incy; dtemp = 0.0; if (n<=0) return( (REAL) dtemp); dx--; dy--; ix = 1; iy = 1; if (incx<0) ix = (-n+1)*incx + 1; if (incy<0) iy = (-n+1)*incy + 1; /* CPU intensive loop; option to do pointer arithmetic */ #if defined DOFASTMATH { REAL *xptr, *yptr; for (i = 1, xptr = dx + ix, yptr = dy + iy; i <= n; i++, xptr += incx, yptr += incy) dtemp+= (*yptr)*(*xptr); } #else if (incx==1 && incy==1) goto x20; /* code for unequal increments or equal increments not equal to 1 */ for (i = 1; i<=n; i++) { dtemp+= dx[ix]*dy[iy]; ix+= incx; iy+= incy; } return(dtemp); /* code for both increments equal to 1 */ /* clean-up loop */ x20: m = n % 5; if (m == 0) goto x40; for (i = 1; i<=m; i++) dtemp+= dx[i]*dy[i]; if (n < 5) goto x60; x40: mp1 = m + 1; for (i = mp1; i<=n; i=i+5) dtemp+= dx[i]*dy[i] + dx[i + 1]*dy[i + 1] + dx[i + 2]*dy[i + 2] + dx[i + 3]*dy[i + 3] + dx[i + 4]*dy[i + 4]; x60: #endif return(dtemp); } /* ************************************************************************ */ void dswap( int n, REAL *dx, int incx, REAL *dy, int incy ) { dx++; dy++; BLAS_dswap( &n, dx, &incx, dy, &incy ); } void BLAS_CALLMODEL my_dswap( int *_n, REAL *dx, int *_incx, REAL *dy, int *_incy ) { int i, ix, iy; #ifndef DOFASTMATH int m, mp1, ns; REAL dtemp2, dtemp3; #endif register REAL dtemp1; int n = *_n, incx = *_incx, incy = *_incy; if (n <= 0) return; dx--; dy--; ix = 1; iy = 1; if (incx < 0) ix = (-n+1)*incx + 1; if (incy < 0) iy = (-n+1)*incy + 1; /* CPU intensive loop; option to do pointer arithmetic */ #if defined DOFASTMATH { REAL *xptr, *yptr; for (i = 1, xptr = dx + ix, yptr = dy + iy; i <= n; i++, xptr += incx, yptr += incy) { dtemp1 = (*xptr); (*xptr) = (*yptr); (*yptr) = dtemp1; } } #else if (incx == incy) { if (incx <= 0) goto x5; if (incx == 1) goto x20; goto x60; } /* code for unequal or nonpositive increments. */ x5: for (i = 1; i<=n; i++) { dtemp1 = dx[ix]; dx[ix] = dy[iy]; dy[iy] = dtemp1; ix+= incx; iy+= incy; } return; /* code for both increments equal to 1. clean-up loop so remaining vector length is a multiple of 3. */ x20: m = n % 3; if (m == 0) goto x40; for (i = 1; i<=m; i++) { dtemp1 = dx[i]; dx[i] = dy[i]; dy[i] = dtemp1; } if (n < 3) return; x40: mp1 = m + 1; for (i = mp1; i<=n; i=i+3) { dtemp1 = dx[i]; dtemp2 = dx[i+1]; dtemp3 = dx[i+2]; dx[i] = dy[i]; dx[i+1] = dy[i+1]; dx[i+2] = dy[i+2]; dy[i] = dtemp1; dy[i+1] = dtemp2; dy[i+2] = dtemp3; } return; /* code for equal, positive, non-unit increments. */ x60: ns = n*incx; for (i = 1; i<=ns; i=i+incx) { dtemp1 = dx[i]; dx[i] = dy[i]; dy[i] = dtemp1; } #endif } /* ************************************************************************ */ void dload(int n, REAL da, REAL *dx, int incx) { dx++; BLAS_dload (&n, &da, dx, &incx); } void BLAS_CALLMODEL my_dload (int *_n, REAL *_da, REAL *dx, int *_incx) { /* copies a scalar, a, to a vector, x. uses unrolled loops when incx equals one. To change the precision of this program, run the change program on dload.f Alternatively, to make a single precision version append a comment character to the start of all lines between sequential precision > double and end precision > double comments and delete the comment character at the start of all lines between sequential precision > single and end precision > single comments. To make a double precision version interchange the append and delete operations in these instructions. */ int i, ix, m, mp1; REAL da = *_da; int n = *_n, incx = *_incx; if (n<=0) return; dx--; if (incx==1) goto x20; /* code for incx not equal to 1 */ ix = 1; if (incx<0) ix = (-n+1)*incx + 1; for (i = 1; i<=n; i++) { dx[ix] = da; ix+= incx; } return; /* code for incx equal to 1 and clean-up loop */ x20: m = n % 7; if (m == 0) goto x40; for (i = 1; i<=m; i++) dx[i] = da; if (n < 7) return; x40: mp1 = m + 1; for (i = mp1; i<=n; i=i+7) { dx[i] = da; dx[i + 1] = da; dx[i + 2] = da; dx[i + 3] = da; dx[i + 4] = da; dx[i + 5] = da; dx[i + 6] = da; } } /* ************************************************************************ */ int idamax( int n, REAL *x, int is ) { x++; return ( BLAS_idamax( &n, x, &is ) ); } int idamin( int n, REAL *x, int is ) { x++; return ( BLAS_idamin( &n, x, &is ) ); } int BLAS_CALLMODEL my_idamax( int *_n, REAL *x, int *_is ) { register REAL xmax, xtest; int i, imax = 0; #if !defined DOFASTMATH int ii; #endif int n = *_n, is = *_is; if((n < 1) || (is <= 0)) return(imax); imax = 1; if(n == 1) return(imax); #if defined DOFASTMATH xmax = fabs(*x); for (i = 2, x += is; i <= n; i++, x += is) { xtest = fabs(*x); if(xtest > xmax) { xmax = xtest; imax = i; } } #else x--; ii = 1; xmax = fabs(x[ii]); for(i = 2, ii+ = is; i <= n; i++, ii+ = is) { xtest = fabs(x[ii]); if(xtest > xmax) { xmax = xtest; imax = i; } } #endif return(imax); } int BLAS_CALLMODEL my_idamin( int *_n, REAL *x, int *_is ) { register REAL xmin, xtest; int i, imin = 0; #if !defined DOFASTMATH int ii; #endif int n = *_n, is = *_is; if((n < 1) || (is <= 0)) return(imin); imin = 1; if(n == 1) return(imin); #if defined DOFASTMATH xmin = fabs(*x); for (i = 2, x += is; i <= n; i++, x += is) { xtest = fabs(*x); if(xtest < xmin) { xmin = xtest; imin = i; } } #else x--; ii = 1; xmin = fabs(x[ii]); for(i = 2, ii+ = is; i <= n; i++, ii+ = is) { xtest = fabs(x[ii]); if(xtest < xmin) { xmin = xtest; imin = i; } } #endif return(imin); } /* ************************************************************************ */ REAL dnormi( int n, REAL *x ) { x++; return( BLAS_dnormi( &n, x ) ); } REAL BLAS_CALLMODEL my_dnormi( int *_n, REAL *x ) { /* =============================================================== dnormi returns the infinity-norm of the vector x. =============================================================== */ int j; register REAL hold, absval; int n = *_n; x--; hold = 0.0; /* for(j = 1; j <= n; j++) */ for(j = n; j > 0; j--) { absval = fabs(x[j]); hold = MAX( hold, absval ); } return( hold ); } /* ************************************************************************ */ /* Subvector and submatrix access routines (Fortran compatibility) */ /* ************************************************************************ */ #ifndef UseMacroVector int subvec( int item) { return( item-1 ); } #endif int submat( int nrowb, int row, int col) { return( nrowb*(col-1) + subvec(row) ); } int posmat( int nrowb, int row, int col) { return( submat(nrowb, row, col)+BLAS_BASE ); } /* ************************************************************************ */ /* Randomization functions */ /* ************************************************************************ */ void randomseed(int seeds[]) /* Simply create some default seed values */ { seeds[1] = 123456; seeds[2] = 234567; seeds[3] = 345678; } void randomdens( int n, REAL *x, REAL r1, REAL r2, REAL densty, int *seeds ) { /* ------------------------------------------------------------------ random generates a vector x[*] of random numbers in the range (r1, r2) with (approximate) specified density. seeds[*] must be initialized before the first call. ------------------------------------------------------------------ */ int i; REAL *y; y = (REAL *) malloc(sizeof(*y) * (n+1)); ddrand( n, x, 1, seeds ); ddrand( n, y, 1, seeds ); for (i = 1; i<=n; i++) { if (y[i] < densty) x[i] = r1 + (r2 - r1) * x[i]; else x[i] = 0.0; } free(y); } /* ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ */ void ddrand( int n, REAL *x, int incx, int *seeds ) { /* ------------------------------------------------------------------ ddrand fills a vector x with uniformly distributed random numbers in the interval (0, 1) using a method due to Wichman and Hill. seeds[1..3] should be set to integer values between 1 and 30000 before the first entry. Integer arithmetic up to 30323 is required. Blatantly copied from Wichman and Hill 19-January-1987. 14-Feb-94. Original version. 30 Jun 1999. seeds stored in an array. 30 Jun 1999. This version of ddrand. ------------------------------------------------------------------ */ int ix, xix; if (n < 1) return; for (ix = 1; ix<=1+(n-1)*incx; ix=ix+incx) { seeds[1] = 171*(seeds[1] % 177) - 2*(seeds[1]/177); seeds[2] = 172*(seeds[2] % 176) - 35*(seeds[2]/176); seeds[3] = 170*(seeds[3] % 178) - 63*(seeds[3]/178); if (seeds[1] < 0) seeds[1] = seeds[1] + 30269; if (seeds[2] < 0) seeds[2] = seeds[2] + 30307; if (seeds[3] < 0) seeds[3] = seeds[3] + 30323; x[ix] = ((REAL) seeds[1])/30269.0 + ((REAL) seeds[2])/30307.0 + ((REAL) seeds[3])/30323.0; xix = (int) x[ix]; x[ix] = fabs(x[ix] - xix); } } MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/lusol.h0000664000175000017500000003332511141443433020643 0ustar lauerlauer#ifndef HEADER_LUSOL #define HEADER_LUSOL /* Include necessary libraries */ /* ------------------------------------------------------------------------- */ #include #include "commonlib.h" /* Version information */ /* ------------------------------------------------------------------------- */ #define LUSOL_VERMAJOR 2 #define LUSOL_VERMINOR 2 #define LUSOL_RELEASE 2 #define LUSOL_BUILD 0 /* Dynamic memory management macros */ /* ------------------------------------------------------------------------- */ #ifdef MATLAB #define LUSOL_MALLOC(bytesize) mxMalloc(bytesize) #define LUSOL_CALLOC(count, recsize) mxCalloc(count, recsize) #define LUSOL_REALLOC(ptr, bytesize) mxRealloc((void *) ptr, bytesize) #define LUSOL_FREE(ptr) {mxFree(ptr); ptr=NULL;} #else #define LUSOL_MALLOC(bytesize) malloc(bytesize) #define LUSOL_CALLOC(count, recsize) calloc(count, recsize) #define LUSOL_REALLOC(ptr, bytesize) realloc((void *) ptr, bytesize) #define LUSOL_FREE(ptr) {free(ptr); ptr=NULL;} #endif /* Performance compiler options */ /* ------------------------------------------------------------------------- */ #if 1 #define ForceInitialization /* Satisfy compilers, check during debugging! */ #define LUSOLFastDenseIndex /* Increment the linearized dense address */ #define LUSOLFastClear /* Use intrinsic functions for memory zeroing */ #define LUSOLFastMove /* Use intrinsic functions for memory moves */ #define LUSOLFastCopy /* Use intrinsic functions for memory copy */ #define LUSOLFastSolve /* Use pointer operations in equation solving */ #define LUSOLSafeFastUpdate /* Use separate array for LU6L result storage */ /*#define UseOld_LU6CHK_20040510 */ /*#define AlwaysSeparateHamaxR */ /* Enabled when the pivot model is fixed */ #if 0 #define ForceRowBasedL0 /* Create a row-sorted version of L0 */ #endif /* #define SetSmallToZero*/ /* #define DoTraceL0 */ #endif /*#define UseTimer */ /* Legacy compatibility and testing options (Fortran-LUSOL) */ /* ------------------------------------------------------------------------- */ #if 0 #define LegacyTesting #define StaticMemAlloc /* Preallocated vs. dynamic memory allocation */ #define ClassicdiagU /* Store diagU at end of a */ #define ClassicHamaxR /* Store H+AmaxR at end of a/indc/indr */ #endif /* General constants and data type definitions */ /* ------------------------------------------------------------------------- */ #define LUSOL_ARRAYOFFSET 1 #ifndef ZERO #define ZERO 0 #endif #ifndef ONE #define ONE 1 #endif #ifndef FALSE #define FALSE 0 #endif #ifndef TRUE #define TRUE 1 #endif #ifndef NULL #define NULL 0 #endif #ifndef REAL #define REAL double #endif #ifndef REALXP #define REALXP long double #endif #ifndef MYBOOL #define MYBOOL unsigned char #endif /* User-settable default parameter values */ /* ------------------------------------------------------------------------- */ #define LUSOL_DEFAULT_GAMMA 2.0 #define LUSOL_SMALLNUM 1.0e-20 /* IAEE doubles have precision 2.22e-16 */ #define LUSOL_BIGNUM 1.0e+20 #define LUSOL_MINDELTA_FACTOR 4 #define LUSOL_MINDELTA_a 10000 #if 1 #define LUSOL_MULT_nz_a 2 /* Suggested by Yin Zhang */ #else #define LUSOL_MULT_nz_a 5 /* Could consider 6 or 7 */ #endif #define LUSOL_MINDELTA_rc 1000 #define LUSOL_DEFAULT_SMARTRATIO 0.667 /* Fixed system parameters (changeable only by developers) */ /* ------------------------------------------------------------------------- */ /* parmlu INPUT parameters: */ #define LUSOL_RP_SMARTRATIO 0 #define LUSOL_RP_FACTORMAX_Lij 1 #define LUSOL_RP_UPDATEMAX_Lij 2 #define LUSOL_RP_ZEROTOLERANCE 3 #define LUSOL_RP_SMALLDIAG_U 4 #define LUSOL_RP_EPSDIAG_U 5 #define LUSOL_RP_COMPSPACE_U 6 #define LUSOL_RP_MARKOWITZ_CONLY 7 #define LUSOL_RP_MARKOWITZ_DENSE 8 #define LUSOL_RP_GAMMA 9 /* parmlu OUPUT parameters: */ #define LUSOL_RP_MAXELEM_A 10 #define LUSOL_RP_MAXMULT_L 11 #define LUSOL_RP_MAXELEM_U 12 #define LUSOL_RP_MAXELEM_DIAGU 13 #define LUSOL_RP_MINELEM_DIAGU 14 #define LUSOL_RP_MAXELEM_TCP 15 #define LUSOL_RP_GROWTHRATE 16 #define LUSOL_RP_USERDATA_1 17 #define LUSOL_RP_USERDATA_2 18 #define LUSOL_RP_USERDATA_3 19 #define LUSOL_RP_RESIDUAL_U 20 #define LUSOL_RP_LASTITEM LUSOL_RP_RESIDUAL_U /* luparm INPUT parameters: */ #define LUSOL_IP_USERDATA_0 0 #define LUSOL_IP_PRINTUNIT 1 #define LUSOL_IP_PRINTLEVEL 2 #define LUSOL_IP_MARKOWITZ_MAXCOL 3 #define LUSOL_IP_SCALAR_NZA 4 #define LUSOL_IP_UPDATELIMIT 5 #define LUSOL_IP_PIVOTTYPE 6 #define LUSOL_IP_ACCELERATION 7 #define LUSOL_IP_KEEPLU 8 #define LUSOL_IP_SINGULARLISTSIZE 9 /* luparm OUTPUT parameters: */ #define LUSOL_IP_INFORM 10 #define LUSOL_IP_SINGULARITIES 11 #define LUSOL_IP_SINGULARINDEX 12 #define LUSOL_IP_MINIMUMLENA 13 #define LUSOL_IP_MAXLEN 14 #define LUSOL_IP_UPDATECOUNT 15 #define LUSOL_IP_RANK_U 16 #define LUSOL_IP_COLCOUNT_DENSE1 17 #define LUSOL_IP_COLCOUNT_DENSE2 18 #define LUSOL_IP_COLINDEX_DUMIN 19 #define LUSOL_IP_COLCOUNT_L0 20 #define LUSOL_IP_NONZEROS_L0 21 #define LUSOL_IP_NONZEROS_U0 22 #define LUSOL_IP_NONZEROS_L 23 #define LUSOL_IP_NONZEROS_U 24 #define LUSOL_IP_NONZEROS_ROW 25 #define LUSOL_IP_COMPRESSIONS_LU 26 #define LUSOL_IP_MARKOWITZ_MERIT 27 #define LUSOL_IP_TRIANGROWS_U 28 #define LUSOL_IP_TRIANGROWS_L 29 #define LUSOL_IP_FTRANCOUNT 30 #define LUSOL_IP_BTRANCOUNT 31 #define LUSOL_IP_ROWCOUNT_L0 32 #define LUSOL_IP_LASTITEM LUSOL_IP_ROWCOUNT_L0 /* Macros for matrix-based access for dense part of A and timer mapping */ /* ------------------------------------------------------------------------- */ #define DAPOS(row, col) (row + (col-1)*LDA) #define timer(text, id) LUSOL_timer(LUSOL, id, text) /* Parameter/option defines */ /* ------------------------------------------------------------------------- */ #define LUSOL_MSG_NONE -1 #define LUSOL_MSG_SINGULARITY 0 #define LUSOL_MSG_STATISTICS 10 #define LUSOL_MSG_PIVOT 50 #define LUSOL_BASEORDER 0 #define LUSOL_OTHERORDER 1 #define LUSOL_AUTOORDER 2 #define LUSOL_ACCELERATE_L0 4 #define LUSOL_ACCELERATE_U 8 #define LUSOL_PIVMOD_NOCHANGE -2 /* Don't change active pivoting model */ #define LUSOL_PIVMOD_DEFAULT -1 /* Set pivoting model to default */ #define LUSOL_PIVMOD_TPP 0 /* Threshold Partial pivoting (normal) */ #define LUSOL_PIVMOD_TRP 1 /* Threshold Rook pivoting */ #define LUSOL_PIVMOD_TCP 2 /* Threshold Complete pivoting */ #define LUSOL_PIVMOD_TSP 3 /* Threshold Symmetric pivoting */ #define LUSOL_PIVMOD_MAX LUSOL_PIVMOD_TSP #define LUSOL_PIVTOL_NOCHANGE 0 #define LUSOL_PIVTOL_BAGGY 1 #define LUSOL_PIVTOL_LOOSE 2 #define LUSOL_PIVTOL_NORMAL 3 #define LUSOL_PIVTOL_SLIM 4 #define LUSOL_PIVTOL_TIGHT 5 #define LUSOL_PIVTOL_SUPER 6 #define LUSOL_PIVTOL_CORSET 7 #define LUSOL_PIVTOL_DEFAULT LUSOL_PIVTOL_SLIM #define LUSOL_PIVTOL_MAX LUSOL_PIVTOL_CORSET #define LUSOL_UPDATE_OLDEMPTY 0 /* No/empty current column. */ #define LUSOL_UPDATE_OLDNONEMPTY 1 /* Current column need not have been empty. */ #define LUSOL_UPDATE_NEWEMPTY 0 /* New column is taken to be zero. */ #define LUSOL_UPDATE_NEWNONEMPTY 1 /* v(*) contains the new column; on exit, v(*) satisfies L*v = a(new). */ #define LUSOL_UPDATE_USEPREPARED 2 /* v(*) must satisfy L*v = a(new). */ #define LUSOL_SOLVE_Lv_v 1 /* v solves L v = v(input). w is not touched. */ #define LUSOL_SOLVE_Ltv_v 2 /* v solves L'v = v(input). w is not touched. */ #define LUSOL_SOLVE_Uw_v 3 /* w solves U w = v. v is not altered. */ #define LUSOL_SOLVE_Utv_w 4 /* v solves U'v = w. w is destroyed. */ #define LUSOL_SOLVE_Aw_v 5 /* w solves A w = v. v is altered as in 1. */ #define LUSOL_FTRAN LUSOL_SOLVE_Aw_v #define LUSOL_SOLVE_Atv_w 6 /* v solves A'v = w. w is destroyed. */ #define LUSOL_BTRAN LUSOL_SOLVE_Atv_w /* If mode = 3,4,5,6, v and w must not be the same arrays. If lu1fac has just been used to factorize a symmetric matrix A (which must be definite or quasi-definite), the factors A = L U may be regarded as A = LDL', where D = diag(U). In such cases, the following (faster) solve codes may be used: */ #define LUSOL_SOLVE_Av_v 7 /* v solves A v = L D L'v = v(input). w is not touched. */ #define LUSOL_SOLVE_LDLtv_v 8 /* v solves L |D| L'v = v(input). w is not touched. */ #define LUSOL_INFORM_RANKLOSS -1 #define LUSOL_INFORM_LUSUCCESS 0 #define LUSOL_INFORM_LUSINGULAR 1 #define LUSOL_INFORM_LUUNSTABLE 2 #define LUSOL_INFORM_ADIMERR 3 #define LUSOL_INFORM_ADUPLICATE 4 #define LUSOL_INFORM_ANEEDMEM 7 /* Set lena >= luparm[LUSOL_IP_MINIMUMLENA] */ #define LUSOL_INFORM_FATALERR 8 #define LUSOL_INFORM_NOPIVOT 9 /* No diagonal pivot found with TSP or TDP. */ #define LUSOL_INFORM_NOMEMLEFT 10 #define LUSOL_INFORM_MIN LUSOL_INFORM_RANKLOSS #define LUSOL_INFORM_MAX LUSOL_INFORM_NOMEMLEFT #define LUSOL_INFORM_GETLAST 10 /* Code for LUSOL_informstr. */ #define LUSOL_INFORM_SERIOUS LUSOL_INFORM_LUUNSTABLE /* Prototypes for call-back functions */ /* ------------------------------------------------------------------------- */ typedef void LUSOLlogfunc(void *lp, void *userhandle, char *buf); /* Sparse matrix data */ typedef struct _LUSOLmat { REAL *a; int *lenx, *indr, *indc, *indx; } LUSOLmat; /* The main LUSOL data record */ /* ------------------------------------------------------------------------- */ typedef struct _LUSOLrec { /* General data */ FILE *outstream; /* Output stream, initialized to STDOUT */ LUSOLlogfunc *writelog; void *loghandle; LUSOLlogfunc *debuginfo; /* Parameter storage arrays */ int luparm[LUSOL_IP_LASTITEM + 1]; REAL parmlu[LUSOL_RP_LASTITEM + 1]; /* Arrays of length lena+1 */ int lena, nelem; int *indc, *indr; REAL *a; /* Arrays of length maxm+1 (row storage) */ int maxm, m; int *lenr, *ip, *iqloc, *ipinv, *locr; /* Arrays of length maxn+1 (column storage) */ int maxn, n; int *lenc, *iq, *iploc, *iqinv, *locc; REAL *w, *vLU6L; /* List of singular columns, with dynamic size allocation */ int *isingular; /* Extra arrays of length n for TCP and keepLU == FALSE */ REAL *Ha, *diagU; int *Hj, *Hk; /* Extra arrays of length m for TRP*/ REAL *amaxr; /* Extra array for L0 and U stored by row/column for faster btran/ftran */ LUSOLmat *L0; LUSOLmat *U; /* Miscellaneous data */ int expanded_a; int replaced_c; int replaced_r; } LUSOLrec; LUSOLrec *LUSOL_create(FILE *outstream, int msgfil, int pivotmodel, int updatelimit); MYBOOL LUSOL_sizeto(LUSOLrec *LUSOL, int init_r, int init_c, int init_a); MYBOOL LUSOL_assign(LUSOLrec *LUSOL, int iA[], int jA[], REAL Aij[], int nzcount, MYBOOL istriplet); void LUSOL_clear(LUSOLrec *LUSOL, MYBOOL nzonly); void LUSOL_free(LUSOLrec *LUSOL); LUSOLmat *LUSOL_matcreate(int dim, int nz); void LUSOL_matfree(LUSOLmat **mat); int LUSOL_loadColumn(LUSOLrec *LUSOL, int iA[], int jA, REAL Aij[], int nzcount, int offset1); void LUSOL_setpivotmodel(LUSOLrec *LUSOL, int pivotmodel, int initlevel); int LUSOL_factorize(LUSOLrec *LUSOL); int LUSOL_replaceColumn(LUSOLrec *LUSOL, int jcol, REAL v[]); MYBOOL LUSOL_tightenpivot(LUSOLrec *LUSOL); MYBOOL LUSOL_addSingularity(LUSOLrec *LUSOL, int singcol, int *inform); int LUSOL_getSingularity(LUSOLrec *LUSOL, int singitem); int LUSOL_findSingularityPosition(LUSOLrec *LUSOL, int singcol); char *LUSOL_pivotLabel(LUSOLrec *LUSOL); char *LUSOL_informstr(LUSOLrec *LUSOL, int inform); REAL LUSOL_vecdensity(LUSOLrec *LUSOL, REAL V[]); void LUSOL_report(LUSOLrec *LUSOL, int msglevel, char *format, ...); void LUSOL_timer(LUSOLrec *LUSOL, int timerid, char *text); int LUSOL_ftran(LUSOLrec *LUSOL, REAL b[], int NZidx[], MYBOOL prepareupdate); int LUSOL_btran(LUSOLrec *LUSOL, REAL b[], int NZidx[]); void LU1FAC(LUSOLrec *LUSOL, int *INFORM); MYBOOL LU1L0(LUSOLrec *LUSOL, LUSOLmat **mat, int *inform); void LU6SOL(LUSOLrec *LUSOL, int MODE, REAL V[], REAL W[], int NZidx[], int *INFORM); void LU8RPC(LUSOLrec *LUSOL, int MODE1, int MODE2, int JREP, REAL V[], REAL W[], int *INFORM, REAL *DIAG, REAL *VNORM); void LUSOL_dump(FILE *output, LUSOLrec *LUSOL); void print_L0(LUSOLrec *LUSOL); #endif /* HEADER_LUSOL */ MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/lusol8a.c0000664000175000017500000002564711141443435021101 0ustar lauerlauer /* ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ File lusol8a lu8rpc Sparse LU update: Replace Column LUSOL's sparse implementation of the Bartels-Golub update. 01 May 2002: Derived from LUSOL's original lu8a.f file. 01 May 2002: Current version of lusol8a.f. ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ */ /* ================================================================== lu8rpc updates the LU factorization A = L*U when column jrep is replaced by some vector a(new). lu8rpc is an implementation of the Bartels-Golub update, designed for the case where A is rectangular and/or singular. L is a product of stabilized eliminations (m x m, nonsingular). P U Q is upper trapezoidal (m x n, rank nrank). If mode1 = 0, the old column is taken to be zero (so it does not have to be removed from U). If mode1 = 1, the old column need not have been zero. If mode2 = 0, the new column is taken to be zero. v(*) is not used or altered. If mode2 = 1, v(*) must contain the new column a(new). On exit, v(*) will satisfy L*v = a(new). If mode2 = 2, v(*) must satisfy L*v = a(new). The array w(*) is not used or altered. On entry, all elements of locc are assumed to be zero. On a successful exit (inform != 7), this will again be true. On exit: inform = -1 if the rank of U decreased by 1. inform = 0 if the rank of U stayed the same. inform = 1 if the rank of U increased by 1. inform = 2 if the update seemed to be unstable (diag much bigger than vnorm). inform = 7 if the update was not completed (lack of storage). inform = 8 if jrep is not between 1 and n. ------------------------------------------------------------------ -- Jan 1985: Original F66 version. -- Jul 1987: Modified to maintain U in trapezoidal form. 10 May 1988: First f77 version. 16 Oct 2000: Added test for instability (inform = 2). ================================================================== */ void LU8RPC(LUSOLrec *LUSOL, int MODE1, int MODE2, int JREP, REAL V[], REAL W[], int *INFORM, REAL *DIAG, REAL *VNORM) { MYBOOL SINGLR; int LPRINT, NRANK, LENL, LENU, LROW, NRANK0, KREP, KLAST, IW, L1, J1, JSING; REAL UTOL1, UTOL2; LPRINT = LUSOL->luparm[LUSOL_IP_PRINTLEVEL]; NRANK = LUSOL->luparm[LUSOL_IP_RANK_U]; LENL = LUSOL->luparm[LUSOL_IP_NONZEROS_L]; LENU = LUSOL->luparm[LUSOL_IP_NONZEROS_U]; LROW = LUSOL->luparm[LUSOL_IP_NONZEROS_ROW]; UTOL1 = LUSOL->parmlu[LUSOL_RP_SMALLDIAG_U]; UTOL2 = LUSOL->parmlu[LUSOL_RP_EPSDIAG_U]; NRANK0 = NRANK; *DIAG = ZERO; *VNORM = ZERO; if(JREP<1) goto x980; if(JREP>LUSOL->n) goto x980; /* ------------------------------------------------------------------ If mode1 = 0, there are no elements to be removed from U but we still have to set krep (using a backward loop). Otherwise, use lu7zap to remove column jrep from U and set krep at the same time. ------------------------------------------------------------------ */ if(MODE1==LUSOL_UPDATE_OLDEMPTY) { KREP = LUSOL->n+1; x10: KREP--; if(LUSOL->iq[KREP]!=JREP) goto x10; } else LU7ZAP(LUSOL, JREP,&KREP,&LENU,&LROW,NRANK); /* ------------------------------------------------------------------ Insert a new column of u and find klast. ------------------------------------------------------------------ */ if(MODE2==LUSOL_UPDATE_NEWEMPTY) { KLAST = 0; } else { if(MODE2==LUSOL_UPDATE_NEWNONEMPTY) { /* Transform v = a(new) to satisfy L*v = a(new). */ LU6SOL(LUSOL, LUSOL_SOLVE_Lv_v, V,W, NULL, INFORM); } else if(V==NULL) /* Otherwise, the V vector is taken to satisfy this already, or stored earlier. */ V=LUSOL->vLU6L; /* Insert into U any nonzeros in the top of v. row ip(klast) will contain the last nonzero in pivotal order. Note that klast will be in the range ( 0, nrank ). */ LU7ADD(LUSOL, JREP,V,LENL,&LENU,&LROW,NRANK,INFORM,&KLAST,VNORM); if(*INFORM==LUSOL_INFORM_ANEEDMEM) goto x970; } /* ------------------------------------------------------------------ In general, the new column causes U to look like this: krep n krep n ....a......... ..........a... . a . . a . . a . . a . .a . . a . P U Q = a . or . a . b. . . a . b . . . a . b . . . a . b ...... ..a... nrank c c c c c c m klast points to the last nonzero "a" or "b". klast = 0 means all "a" and "b" entries are zero. ------------------------------------------------------------------ */ if(MODE2==LUSOL_UPDATE_NEWEMPTY) { if(KREP>NRANK) goto x900; } else if(NRANKm) { /* Eliminate any "c"s (in either case). Row nrank + 1 may end up containing one nonzero. */ LU7ELM(LUSOL, JREP,V,&LENL,&LROW,NRANK,INFORM,DIAG); if(*INFORM==LUSOL_INFORM_ANEEDMEM) goto x970; if(*INFORM==LUSOL_INFORM_LUSINGULAR) { /* The nonzero is apparently significant. Increase nrank by 1 and make klast point to the bottom. */ NRANK++; KLAST = NRANK; } } if(NRANKn) { /* The column rank is low. In the first case, we want the new column to end up in position nrank, so the trapezoidal columns will have a chance later on (in lu7rnk) to pivot in that position. Otherwise the new column is not part of the triangle. We swap it into position nrank so we can judge it for singularity. lu7rnk might choose some other trapezoidal column later. */ if(KREPiq[KREP] = LUSOL->iq[NRANK]; LUSOL->iq[NRANK] = JREP; KREP = NRANK; } } /* ------------------------------------------------------------------ If krep .lt. klast, there are some "b"s to eliminate: krep ....a......... . a . . a . .a . P U Q = a . krep b. . b . . b . . b ...... nrank If krep .eq. klast, there are no "b"s, but the last "a" still has to be moved to the front of row krep (by lu7for). ------------------------------------------------------------------ */ if(KREP<=KLAST) { /* Perform a cyclic permutation on the current pivotal order, and eliminate the resulting row spike. krep becomes klast. The final diagonal (if any) will be correctly positioned at the front of the new krep-th row. nrank stays the same. */ LU7CYC(LUSOL, KREP,KLAST,LUSOL->ip); LU7CYC(LUSOL, KREP,KLAST,LUSOL->iq); LU7FOR(LUSOL, KREP,KLAST,&LENL,&LENU,&LROW,INFORM,DIAG); if(*INFORM==LUSOL_INFORM_ANEEDMEM) goto x970; KREP = KLAST; /* Test for instability (diag much bigger than vnorm). */ SINGLR = (MYBOOL) ((*VNORM)ip[KREP]; SINGLR = (MYBOOL) (LUSOL->lenr[IW]==0); if(!SINGLR) { L1 = LUSOL->locr[IW]; J1 = LUSOL->indr[L1]; SINGLR = (MYBOOL) (J1!=JREP); if(!SINGLR) { *DIAG = LUSOL->a[L1]; SINGLR = (MYBOOL) (fabs(*DIAG)<=UTOL1 || fabs(*DIAG)<=UTOL2*(*VNORM)); } } if(SINGLR && (KREPip); LU7CYC(LUSOL, KREP,LUSOL->n,LUSOL->iq); LU7FOR(LUSOL, KREP,NRANK,&LENL,&LENU,&LROW,INFORM,DIAG); if(*INFORM==LUSOL_INFORM_ANEEDMEM) goto x970; } /* Find the best column to be in position nrank. If singlr, it can't be the new column, jrep. If nothing satisfactory exists, nrank will be decreased. */ if(SINGLR || (NRANKn)) { JSING = 0; if(SINGLR) JSING = JREP; LU7RNK(LUSOL, JSING,&LENU,&LROW,&NRANK,INFORM,DIAG); } /* ------------------------------------------------------------------ Update indeces of optional row-based version of L0. ------------------------------------------------------------------ */ #if 0 if(LUSOL->L0 != NULL) LU1L0UPD(LUSOL, INFORM); #endif /* ------------------------------------------------------------------ Set inform for exit. ------------------------------------------------------------------ */ x900: if(NRANK==NRANK0) *INFORM = LUSOL_INFORM_LUSUCCESS; else if(NRANKn) { if(LPRINT>=LUSOL_MSG_SINGULARITY) LUSOL_report(LUSOL, 0, "lu8rpc warning...\nSingularity after replacing column. jrep=%8d diag=%g\n", JREP,DIAG); } } else *INFORM = LUSOL_INFORM_LUSINGULAR; goto x990; /* Instability. */ x920: *INFORM = LUSOL_INFORM_LUUNSTABLE; if(LPRINT>=LUSOL_MSG_SINGULARITY) LUSOL_report(LUSOL, 0, "lu8rpc warning...\nInstability after replacing column. jrep=%8d diag=%g\n", JREP,DIAG); goto x990; /* Not enough storage. */ x970: *INFORM = LUSOL_INFORM_ANEEDMEM; if(LPRINT>=LUSOL_MSG_SINGULARITY) LUSOL_report(LUSOL, 0, "lu8rpc error...\nInsufficient memory. lena=%8d\n", LUSOL->lena); goto x990; /* jrep is out of range. */ x980: *INFORM = LUSOL_INFORM_FATALERR; if(LPRINT>=LUSOL_MSG_SINGULARITY) LUSOL_report(LUSOL, 0, "lu8rpc error...\njrep is out of range. m=%8d n=%8d jrep=%8d\n", LUSOL->m,LUSOL->n,JREP); /* Exit. */ x990: LUSOL->luparm[LUSOL_IP_UPDATECOUNT]++; LUSOL->luparm[LUSOL_IP_RANK_U] = NRANK; LUSOL->luparm[LUSOL_IP_NONZEROS_L] = LENL; LUSOL->luparm[LUSOL_IP_NONZEROS_U] = LENU; LUSOL->luparm[LUSOL_IP_NONZEROS_ROW] = LROW; LUSOL->luparm[LUSOL_IP_INFORM] = *INFORM; } MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/lusol2.c0000664000175000017500000001444511141443433020722 0ustar lauerlauer /* ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ File lusol2 LUSOL heap management routines Hbuild Hchange Hdelete Hdown Hinsert Hup Heap-management routines for LUSOL's lu1fac. May be useful for other applications. ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ For LUSOL, the heap structure involves three arrays of length N. N is the current number of entries in the heap. Ha(1:N) contains the values that the heap is partially sorting. For LUSOL they are double precision values -- the largest element in each remaining column of the updated matrix. The biggest entry is in Ha(1), the top of the heap. Hj(1:N) contains column numbers j. Ha(k) is the biggest entry in column j = Hj(k). Hk(1:N) contains indices within the heap. It is the inverse of Hj(1:N), so k = Hk(j) <=> j = Hj(k). Column j is entry k in the heap. hops is the number of heap operations, i.e., the number of times an entry is moved (the number of "hops" up or down the heap). Together, Hj and Hk let us find values inside the heap whenever we want to change one of the values in Ha. For other applications, Ha may need to be some other data type, like the keys that sort routines operate on. ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ 11 Feb 2002: MATLAB version derived from "Algorithms" by R. Sedgewick 03 Mar 2002: F77 version derived from MATLAB version. 07 May 2002: Safeguard input parameters k, N, Nk. We don't want them to be output! 07 May 2002: Current version of lusol2.f. ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ */ /* ================================================================== Hdown updates heap by moving down tree from node k. ------------------------------------------------------------------ 01 May 2002: Need Nk for length of Hk. 05 May 2002: Change input paramter k to kk to stop k being output. 05 May 2002: Current version of Hdown. ================================================================== */ void HDOWN(REAL HA[], int HJ[], int HK[], int N, int K, int *HOPS) { int J, JJ, JV, N2; REAL V; *HOPS = 0; V = HA[K]; JV = HJ[K]; N2 = N/2; /* while 1 break */ x100: if(K>N2) goto x200; (*HOPS)++; J = K+K; if(J=HA[J]) goto x200; HA[K] = HA[J]; JJ = HJ[J]; HJ[K] = JJ; HK[JJ] = K; K = J; goto x100; /* end while */ x200: HA[K] = V; HJ[K] = JV; HK[JV] = K; } /* ================================================================== Hup updates heap by moving up tree from node k. ------------------------------------------------------------------ 01 May 2002: Need Nk for length of Hk. 05 May 2002: Change input paramter k to kk to stop k being output. 05 May 2002: Current version of Hup. ================================================================== */ void HUP(REAL HA[], int HJ[], int HK[], int K, int *HOPS) { int J, JV, K2; REAL V; *HOPS = 0; V = HA[K]; JV = HJ[K]; /* while 1 break */ x100: if(K<2) goto x200; K2 = K/2; /* break */ if(V #include #include #include #include "mmio.h" int mm_read_unsymmetric_sparse(const char *fname, int *M_, int *N_, int *nz_, double **val_, int **I_, int **J_) { FILE *f; MM_typecode matcode; int M, N, nz; int i; double *val; int *I, *J; if ((f = fopen(fname, "r")) == NULL) return -1; if (mm_read_banner(f, &matcode) != 0) { printf("mm_read_unsymetric: Could not process Matrix Market banner "); printf(" in file [%s]\n", fname); return -1; } if ( !(mm_is_real(matcode) && mm_is_matrix(matcode) && mm_is_sparse(matcode))) { fprintf(stderr, "Sorry, this application does not support "); fprintf(stderr, "Market Market type: [%s]\n", mm_typecode_to_str(matcode)); return -1; } /* find out size of sparse matrix: M, N, nz .... */ if (mm_read_mtx_crd_size(f, &M, &N, &nz) !=0) { fprintf(stderr, "read_unsymmetric_sparse(): could not parse matrix size.\n"); return -1; } *M_ = M; *N_ = N; *nz_ = nz; /* reseve memory for matrices */ I = (int *) malloc(nz * sizeof(int)); J = (int *) malloc(nz * sizeof(int)); val = (double *) malloc(nz * sizeof(double)); *val_ = val; *I_ = I; *J_ = J; /* NOTE: when reading in doubles, ANSI C requires the use of the "l" */ /* specifier as in "%lg", "%lf", "%le", otherwise errors will occur */ /* (ANSI C X3.159-1989, Sec. 4.9.6.2, p. 136 lines 13-15) */ for (i=0; i= 2) return 0; else do { num_items_read = fscanf(f, "%d %d %d", M, N, nz); if (num_items_read == EOF) return MM_PREMATURE_EOF; } while (num_items_read < 2); return 0; } int mm_read_mtx_array_size(FILE *f, int *M, int *N) { char line[MM_MAX_LINE_LENGTH]; int num_items_read; /* set return null parameter values, in case we exit with errors */ *M = *N = 0; /* now continue scanning until you reach the end-of-comments */ do { if (fgets(line,MM_MAX_LINE_LENGTH,f) == NULL) return MM_PREMATURE_EOF; }while (line[0] == '%'); /* line[] is either blank or has M,N, nz */ if (sscanf(line, "%d %d", M, N) == 2) return 0; else /* we have a blank line */ do { num_items_read = fscanf(f, "%d %d", M, N); if (num_items_read == EOF) return MM_PREMATURE_EOF; } while (num_items_read != 2); return 0; } int mm_write_mtx_array_size(FILE *f, int M, int N) { if (fprintf(f, "%d %d\n", M, N) < 0) return MM_COULD_NOT_WRITE_FILE; else return 0; } /*-------------------------------------------------------------------------*/ /******************************************************************/ /* use when I[], J[], and val[]J, and val[] are already allocated */ /******************************************************************/ int mm_read_mtx_crd_data(FILE *f, int M, int N, int nz, int I[], int J[], double val[], MM_typecode matcode) { int i; if (mm_is_complex(matcode)) { for (i=0; iluparm[LUSOL_IP_COLCOUNT_L0]; LENL0 = LUSOL->luparm[LUSOL_IP_NONZEROS_L0]; if((NUML0 == 0) || (LENL0 == 0) || (LUSOL->luparm[LUSOL_IP_ACCELERATION] == LUSOL_BASEORDER) || ((LUSOL->luparm[LUSOL_IP_ACCELERATION] & LUSOL_ACCELERATE_L0) == 0)) return( status ); /* Allocate temporary array */ lsumr = (int *) LUSOL_CALLOC((LUSOL->m+1), sizeof(*lsumr)); if(lsumr == NULL) { *inform = LUSOL_INFORM_NOMEMLEFT; return( status ); } /* Compute non-zero counts by permuted row index (order is unimportant) */ K = 0; L2 = LUSOL->lena; L1 = L2-LENL0+1; for(L = L1; L <= L2; L++) { I = LUSOL->indc[L]; lsumr[I]++; if(lsumr[I] == 1) K++; } LUSOL->luparm[LUSOL_IP_ROWCOUNT_L0] = K; /* Check if we should apply "smarts" before proceeding to the row matrix creation */ if((LUSOL->luparm[LUSOL_IP_ACCELERATION] & LUSOL_AUTOORDER) && ((REAL) LUSOL->luparm[LUSOL_IP_ROWCOUNT_L0] / #if 0 LUSOL->luparm[LUSOL_IP_COLCOUNT_L0] #else LUSOL->m #endif > LUSOL->parmlu[LUSOL_RP_SMARTRATIO])) goto Finish; /* We are Ok to create the new matrix object */ *mat = LUSOL_matcreate(LUSOL->m, LENL0); if(*mat == NULL) { *inform = LUSOL_INFORM_NOMEMLEFT; goto Finish; } /* Cumulate row counts to get vector offsets; first row is leftmost (stick with Fortran array offset for consistency) */ (*mat)->lenx[0] = 1; for(K = 1; K <= LUSOL->m; K++) { (*mat)->lenx[K] = (*mat)->lenx[K-1] + lsumr[K]; lsumr[K] = (*mat)->lenx[K-1]; } /* Map the matrix into row order by permuted index; Note: The first permuted row is located leftmost in the array. The column order is irrelevant, since the indeces will refer to constant / resolved values of V[] during solve. */ L2 = LUSOL->lena; L1 = L2-LENL0+1; for(L = L1; L <= L2; L++) { I = LUSOL->indc[L]; LL = lsumr[I]++; (*mat)->a[LL] = LUSOL->a[L]; (*mat)->indr[LL] = LUSOL->indr[L]; (*mat)->indc[LL] = I; } /* Pack row starting positions, and set mapper from original index to packed */ I = 0; for(L = 1; L <= LUSOL->m; L++) { K = LUSOL->ip[L]; if((*mat)->lenx[K] > (*mat)->lenx[K-1]) { I++; (*mat)->indx[I] = K; } } /* Confirm that everything went well */ status = TRUE; /* Clean up */ Finish: FREE(lsumr); return( status ); } /* Solve L0' v = v based on row-based version of L0, constructed by LU1L0 */ void LU6L0T_v(LUSOLrec *LUSOL, LUSOLmat *mat, REAL V[], int NZidx[], int *INFORM) { #ifdef DoTraceL0 REAL TEMP; #endif int LEN, K, KK, L, L1, NUML0; REAL SMALL; register REAL VPIV; #if (defined LUSOLFastSolve) && !(defined DoTraceL0) REAL *aptr; int *jptr; #else int J; #endif NUML0 = LUSOL->luparm[LUSOL_IP_ROWCOUNT_L0]; SMALL = LUSOL->parmlu[LUSOL_RP_ZEROTOLERANCE]; /* Loop over the nz columns of L0' - from the end, going forward. */ for(K = NUML0; K > 0; K--) { KK = mat->indx[K]; L = mat->lenx[KK]; L1 = mat->lenx[KK-1]; LEN = L - L1; if(LEN == 0) continue; /* Get value of the corresponding active entry of V[] */ VPIV = V[KK]; /* Only process the column of L0' if the value of V[] is non-zero */ if(fabs(VPIV)>SMALL) { /* ***** This loop could be coded specially. */ #if (defined LUSOLFastSolve) && !(defined DoTraceL0) L--; for(aptr = mat->a+L, jptr = mat->indr+L; LEN > 0; LEN--, aptr--, jptr--) V[*jptr] += VPIV * (*aptr); #else for(; LEN > 0; LEN--) { L--; J = mat->indr[L]; #ifndef DoTraceL0 V[J] += VPIV * mat->a[L]; #else TEMP = V[J]; V[J] += VPIV * mat->a[L]; printf("V[%3d] = V[%3d] + L[%d,%d]*V[%3d]\n", J, J, KK,J, KK); printf("%6g = %6g + %6g*%6g\n", V[J], TEMP, mat->a[L], VPIV); #endif } #endif } #ifdef SetSmallToZero else V[KK] = 0; #endif } } MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/LUSOL_README.txt0000664000175000017500000000414611141374614022013 0ustar lauerlauerREADME.TXT for LUSOL - Advanced LU solver with enhanced numerical stability options ----------------------------------------------------------------------------------- LUSOL - pronounced "L-U-SOL" - was developed by Prof. Michael Saunders at the Stanford (University) Optimization Laboratory over a period of 2 decades of progressive improvements. It is a particularly capable matrix factorization system and includes sparsity-preserving column updates and equation solving. It is therefore particularly well suited to be part of a system to solve tough mathematical programming problems. Further details can be found in the file "LUSOL-overview.txt." A big step has been made in converting the original Fortran code into a much more easily accessible and modularized system based on ANSI C as part of the release of lp_solve v5. LUSOL is fully implemented as a "Basis Factorization Package", BFP in lp_solve and is the BFP of choice for large and complex models, if not all. As part of the conversion to C, processor optimized BLAS functionality has been enabled, and future enhancements to LUSOL may make increasing use of this, ensuring top performance. For the lp_solve release of LUSOL, a stand-alone equation solving system has also been developed. A pre-compiled Windows command-line executable version is included in the standard distribution of LUSOL. In addition, the program options illustrate several advanced uses of LUSOL. The equation solving utility features reading of standard matrix files in the Harwell-Boeing, MatrixMarket and text formats. Sample matrix models are provided for Harwell-Boeing (.RUA) and MatrixMarket (.mtx). The LUSOL code is released under the GNU Lesser General Public Licence. Confer the file "Licence_LGPL.txt" for the full terms of this licence. These terms make lp_solve and LUSOL available and distributable on equal licencing terms. It is expected that LUSOL will have an official repository in the near future, but the LUSOL archive at the Yahoo lp_solve group will be an official copy and the formal repository until further notice. Kjell Eikland 14 July 2004 Oslo, Norway MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/Row-based L0.txt0000664000175000017500000000206210233535016022146 0ustar lauerlauerTraditional column-based L0 --------------------------- V[ 3] = V[ 3] + L[1,3]*V[ 1] 0.9375 = -1.26316 + -0.789474*-2.7875 V[ 2] = V[ 2] + L[1,2]*V[ 1] -0.846875 = -0.15 + 0.25*-2.7875 V[ 2] = V[ 2] + L[3,2]*V[ 3] -0.925 = -0.846875 + -0.0833333*0.9375 V[ 4] = V[ 4] + L[3,4]*V[ 3] -0.3125 = 0 + -0.333333*0.9375 Solution vector -2.7875 -0.925 0.9375 -0.3125 New row-based L0 ---------------- V[ 4] = V[ 4] + L[3,4]*V[ 3] 0.421053 = 0 + -0.333333*-1.26316 V[ 2] = V[ 2] + L[3,2]*V[ 3] -0.0447368 = -0.15 + -0.0833333*-1.26316 V[ 2] = V[ 2] + L[1,2]*V[ 1] -0.741612 = -0.0447368 + 0.25*-2.7875 V[ 3] = V[ 3] + L[1,3]*V[ 1] 0.9375 = -1.26316 + -0.789474*-2.7875 Solution vector -2.7875 -0.741612 0.9375 0.421053 L0 generated ---------------- 0 0 0 0 0 0 0 0 0 0.25 -0.789474 0 0-0.0833333 0 -0.333333MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/lusol7a.c0000664000175000017500000005324511141443434021072 0ustar lauerlauer /* ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ File lusol7a lu7add lu7cyc lu7elm lu7for lu7rnk lu7zap Utilities for LUSOL's update routines. lu7for is the most important -- the forward sweep. 01 May 2002: Derived from LUSOL's original lu7a.f file. 01 May 2002: Current version of lusol7a.f. ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ */ /* ================================================================== lu7add inserts the first nrank elements of the vector v(*) as column jadd of U. We assume that U does not yet have any entries in this column. Elements no larger than parmlu(3) are treated as zero. klast will be set so that the last row to be affected (in pivotal order) is row ip(klast). ------------------------------------------------------------------ 09 May 1988: First f77 version. ================================================================== */ void LU7ADD(LUSOLrec *LUSOL, int JADD, REAL V[], int LENL, int *LENU, int *LROW, int NRANK, int *INFORM, int *KLAST, REAL *VNORM) { REAL SMALL; int K, I, LENI, MINFRE, NFREE, LR1, LR2, L; #ifndef LUSOLFastMove int J; #endif SMALL = LUSOL->parmlu[LUSOL_RP_ZEROTOLERANCE]; *VNORM = ZERO; *KLAST = 0; for(K = 1; K <= NRANK; K++) { I = LUSOL->ip[K]; if(fabs(V[I])<=SMALL) continue; *KLAST = K; (*VNORM) += fabs(V[I]); LENI = LUSOL->lenr[I]; /* Compress row file if necessary. */ MINFRE = LENI+1; NFREE = LUSOL->lena - LENL - *LROW; if(NFREEm, TRUE,LROW,LUSOL->indr,LUSOL->lenr,LUSOL->locr); NFREE = LUSOL->lena - LENL - *LROW; if(NFREElocr[I] = (*LROW) + 1; LR1 = LUSOL->locr[I]; LR2 = (LR1+LENI)-1; if(LR2==*LROW) goto x150; if(LUSOL->indr[LR2+1]==0) goto x180; LUSOL->locr[I] = (*LROW) + 1; #ifdef LUSOLFastMove L = LR2-LR1+1; if(L > 0) { LR2 = (*LROW)+1; MEMMOVE(LUSOL->a+LR2, LUSOL->a+LR1, L); MEMMOVE(LUSOL->indr+LR2, LUSOL->indr+LR1, L); MEMCLEAR(LUSOL->indr+LR1, L); *LROW += L; } #else for(L = LR1; L <= LR2; L++) { (*LROW)++; LUSOL->a[*LROW] = LUSOL->a[L]; J = LUSOL->indr[L]; LUSOL->indr[L] = 0; LUSOL->indr[*LROW] = J; } #endif x150: LR2 = *LROW; (*LROW)++; /* Add the element of v. */ x180: LR2++; LUSOL->a[LR2] = V[I]; LUSOL->indr[LR2] = JADD; LUSOL->lenr[I] = LENI+1; (*LENU)++; } /* Normal exit. */ *INFORM = LUSOL_INFORM_LUSUCCESS; goto x990; /* Not enough storage. */ x970: *INFORM = LUSOL_INFORM_ANEEDMEM; x990: ; } /* ================================================================== lu7cyc performs a cyclic permutation on the row or column ordering stored in ip, moving entry kfirst down to klast. If kfirst .ge. klast, lu7cyc should not be called. Sometimes klast = 0 and nothing should happen. ------------------------------------------------------------------ 09 May 1988: First f77 version. ================================================================== */ void LU7CYC(LUSOLrec *LUSOL, int KFIRST, int KLAST, int IX[]) { if(KFIRST 0, y has just become column jelm of the matrix A. lu7elm should not be called unless m is greater than nrank. inform = 0 if y contained no subdiagonal nonzeros to eliminate. inform = 1 if y contained at least one nontrivial subdiagonal. inform = 7 if there is insufficient storage. ------------------------------------------------------------------ 09 May 1988: First f77 version. No longer calls lu7for at end. lu8rpc, lu8mod do so. ================================================================== */ void LU7ELM(LUSOLrec *LUSOL, int JELM, REAL V[], int *LENL, int *LROW, int NRANK, int *INFORM, REAL *DIAG) { REAL VI, VMAX, SMALL; int NRANK1, MINFRE, NFREE, KMAX, L, K, I, LMAX, IMAX, L1, L2; #ifdef ForceInitialization LMAX = 0; #endif SMALL = LUSOL->parmlu[LUSOL_RP_ZEROTOLERANCE]; NRANK1 = NRANK+1; *DIAG = ZERO; /* Compress row file if necessary. */ MINFRE = LUSOL->m-NRANK; NFREE = LUSOL->lena-(*LENL)-(*LROW); if(NFREE>=MINFRE) goto x100; LU1REC(LUSOL, LUSOL->m,TRUE,LROW,LUSOL->indr,LUSOL->lenr,LUSOL->locr); NFREE = LUSOL->lena-(*LENL)-(*LROW); if(NFREElena-(*LENL))+1; for(K = NRANK1; K <= LUSOL->m; K++) { I = LUSOL->ip[K]; VI = fabs(V[I]); if(VI<=SMALL) continue; L--; LUSOL->a[L] = V[I]; LUSOL->indc[L] = I; if(VMAX>=VI) continue; VMAX = VI; KMAX = K; LMAX = L; } if(KMAX==0) goto x900; /* ------------------------------------------------------------------ Remove vmax by overwriting it with the last packed v(i). Then set the multipliers in L for the other elements. ------------------------------------------------------------------ */ IMAX = LUSOL->ip[KMAX]; VMAX = LUSOL->a[LMAX]; LUSOL->a[LMAX] = LUSOL->a[L]; LUSOL->indc[LMAX] = LUSOL->indc[L]; L1 = L+1; L2 = LUSOL->lena-(*LENL); *LENL = ((*LENL)+L2)-L; for(L = L1; L <= L2; L++) { LUSOL->a[L] /= -VMAX; LUSOL->indr[L] = IMAX; } /* Move the row containing vmax to pivotal position nrank + 1. */ LUSOL->ip[KMAX] = LUSOL->ip[NRANK1]; LUSOL->ip[NRANK1] = IMAX; *DIAG = VMAX; /* ------------------------------------------------------------------ If jelm is positive, insert vmax into a new row of U. This is now the only subdiagonal element. ------------------------------------------------------------------ */ if(JELM>0) { (*LROW)++; LUSOL->locr[IMAX] = *LROW; LUSOL->lenr[IMAX] = 1; LUSOL->a[*LROW] = VMAX; LUSOL->indr[*LROW] = JELM; } *INFORM = LUSOL_INFORM_LUSINGULAR; goto x990; /* No elements to eliminate. */ x900: *INFORM = LUSOL_INFORM_LUSUCCESS; goto x990; /* Not enough storage. */ x970: *INFORM = LUSOL_INFORM_ANEEDMEM; x990: ; } /* ================================================================== lu7for (forward sweep) updates the LU factorization A = L*U when row iw = ip(klast) of U is eliminated by a forward sweep of stabilized row operations, leaving ip * U * iq upper triangular. The row permutation ip is updated to preserve stability and/or sparsity. The column permutation iq is not altered. kfirst is such that row ip(kfirst) is the first row involved in eliminating row iw. (Hence, kfirst marks the first nonzero in row iw in pivotal order.) If kfirst is unknown it may be input as 1. klast is such that row ip(klast) is the row being eliminated. klast is not altered. lu7for should be called only if kfirst .le. klast. If kfirst = klast, there are no nonzeros to eliminate, but the diagonal element of row ip(klast) may need to be moved to the front of the row. ------------------------------------------------------------------ On entry, locc(*) must be zero. On exit: inform = 0 if row iw has a nonzero diagonal (could be small). inform = 1 if row iw has no diagonal. inform = 7 if there is not enough storage to finish the update. On a successful exit (inform le 1), locc(*) will again be zero. ------------------------------------------------------------------ Jan 1985: Final f66 version. 09 May 1988: First f77 version. ================================================================== */ void LU7FOR(LUSOLrec *LUSOL, int KFIRST, int KLAST, int *LENL, int *LENU, int *LROW, int *INFORM, REAL *DIAG) { MYBOOL SWAPPD; int KBEGIN, IW, LENW, LW1, LW2, JFIRST, MINFRE, NFREE, L, J, KSTART, KSTOP, K, LFIRST, IV, LENV, LV1, JLAST, LV2, LV3, LV, JV, LW, LDIAG, LIMIT; REAL AMULT, LTOL, USPACE, SMALL, VJ, WJ; LTOL = LUSOL->parmlu[LUSOL_RP_UPDATEMAX_Lij]; SMALL = LUSOL->parmlu[LUSOL_RP_ZEROTOLERANCE]; USPACE = LUSOL->parmlu[LUSOL_RP_COMPSPACE_U]; KBEGIN = KFIRST; SWAPPD = FALSE; /* We come back here from below if a row interchange is performed. */ x100: IW = LUSOL->ip[KLAST]; LENW = LUSOL->lenr[IW]; if(LENW==0) goto x910; LW1 = LUSOL->locr[IW]; LW2 = (LW1+LENW)-1; JFIRST = LUSOL->iq[KBEGIN]; if(KBEGIN>=KLAST) goto x700; /* Make sure there is room at the end of the row file in case row iw is moved there and fills in completely. */ MINFRE = LUSOL->n+1; NFREE = LUSOL->lena-(*LENL)-(*LROW); if(NFREEm,TRUE,LROW,LUSOL->indr,LUSOL->lenr,LUSOL->locr); LW1 = LUSOL->locr[IW]; LW2 = (LW1+LENW)-1; NFREE = LUSOL->lena-(*LENL)-(*LROW); if(NFREEindr[L]; LUSOL->locc[J] = L; } /* ================================================================== Main elimination loop. ================================================================== */ KSTART = KBEGIN; KSTOP = MIN(KLAST,LUSOL->n); for(K = KSTART; K <= KSTOP; K++) { JFIRST = LUSOL->iq[K]; LFIRST = LUSOL->locc[JFIRST]; if(LFIRST==0) goto x490; /* Row iw has its first element in column jfirst. */ WJ = LUSOL->a[LFIRST]; if(K==KLAST) goto x490; /* --------------------------------------------------------------- We are about to use the first element of row iv to eliminate the first element of row iw. However, we may wish to interchange the rows instead, to preserve stability and/or sparsity. --------------------------------------------------------------- */ IV = LUSOL->ip[K]; LENV = LUSOL->lenr[IV]; LV1 = LUSOL->locr[IV]; VJ = ZERO; if(LENV==0) goto x150; if(LUSOL->indr[LV1]!=JFIRST) goto x150; VJ = LUSOL->a[LV1]; if(SWAPPD) goto x200; if(LTOL*fabs(WJ)ip[KLAST] = IV; LUSOL->ip[K] = IW; KBEGIN = K; SWAPPD = TRUE; goto x600; /* --------------------------------------------------------------- Delete the eliminated element from row iw by overwriting it with the last element. --------------------------------------------------------------- */ x200: LUSOL->a[LFIRST] = LUSOL->a[LW2]; JLAST = LUSOL->indr[LW2]; LUSOL->indr[LFIRST] = JLAST; LUSOL->indr[LW2] = 0; LUSOL->locc[JLAST] = LFIRST; LUSOL->locc[JFIRST] = 0; LENW--; (*LENU)--; if(*LROW==LW2) (*LROW)--; LW2 = LW2-1; /* --------------------------------------------------------------- Form the multiplier and store it in the L file. --------------------------------------------------------------- */ if(fabs(WJ)<=SMALL) goto x490; AMULT = -WJ/VJ; L = LUSOL->lena-(*LENL); LUSOL->a[L] = AMULT; LUSOL->indr[L] = IV; LUSOL->indc[L] = IW; (*LENL)++; /* --------------------------------------------------------------- Add the appropriate multiple of row iv to row iw. We use two different inner loops. The first one is for the case where row iw is not at the end of storage. --------------------------------------------------------------- */ if(LENV==1) goto x490; LV2 = LV1+1; LV3 = (LV1+LENV)-1; if(LW2==*LROW) goto x400; /* ............................................................... This inner loop will be interrupted only if fill-in occurs enough to bump into the next row. ............................................................... */ for(LV = LV2; LV <= LV3; LV++) { JV = LUSOL->indr[LV]; LW = LUSOL->locc[JV]; if(LW>0) { /* No fill-in. */ LUSOL->a[LW] += AMULT*LUSOL->a[LV]; if(fabs(LUSOL->a[LW])<=SMALL) { /* Delete small computed element. */ LUSOL->a[LW] = LUSOL->a[LW2]; J = LUSOL->indr[LW2]; LUSOL->indr[LW] = J; LUSOL->indr[LW2] = 0; LUSOL->locc[J] = LW; LUSOL->locc[JV] = 0; (*LENU)--; LENW--; LW2--; } } else { /* Row iw doesn't have an element in column jv yet so there is a fill-in. */ if(LUSOL->indr[LW2+1]!=0) goto x360; (*LENU)++; LENW++; LW2++; LUSOL->a[LW2] = AMULT*LUSOL->a[LV]; LUSOL->indr[LW2] = JV; LUSOL->locc[JV] = LW2; } } goto x490; /* Fill-in interrupted the previous loop. Move row iw to the end of the row file. */ x360: LV2 = LV; LUSOL->locr[IW] = (*LROW)+1; #ifdef LUSOLFastMove L = LW2-LW1+1; if(L > 0) { int loci, *locp; for(loci = LW1, locp = LUSOL->indr+LW1; loci <= LW2; loci++, locp++) { (*LROW)++; LUSOL->locc[*locp] = *LROW; } LW2 = (*LROW)-L+1; MEMMOVE(LUSOL->a+LW2, LUSOL->a+LW1, L); MEMMOVE(LUSOL->indr+LW2, LUSOL->indr+LW1, L); MEMCLEAR(LUSOL->indr+LW1, L); } #else for(L = LW1; L <= LW2; L++) { (*LROW)++; LUSOL->a[*LROW] = LUSOL->a[L]; J = LUSOL->indr[L]; LUSOL->indr[L] = 0; LUSOL->indr[*LROW] = J; LUSOL->locc[J] = *LROW; } #endif LW1 = LUSOL->locr[IW]; LW2 = *LROW; /* ............................................................... Inner loop with row iw at the end of storage. ............................................................... */ x400: for(LV = LV2; LV <= LV3; LV++) { JV = LUSOL->indr[LV]; LW = LUSOL->locc[JV]; if(LW>0) { /* No fill-in. */ LUSOL->a[LW] += AMULT*LUSOL->a[LV]; if(fabs(LUSOL->a[LW])<=SMALL) { /* Delete small computed element. */ LUSOL->a[LW] = LUSOL->a[LW2]; J = LUSOL->indr[LW2]; LUSOL->indr[LW] = J; LUSOL->indr[LW2] = 0; LUSOL->locc[J] = LW; LUSOL->locc[JV] = 0; (*LENU)--; LENW--; LW2--; } } else { /* Row iw doesn't have an element in column jv yet so there is a fill-in. */ (*LENU)++; LENW++; LW2++; LUSOL->a[LW2] = AMULT*LUSOL->a[LV]; LUSOL->indr[LW2] = JV; LUSOL->locc[JV] = LW2; } } *LROW = LW2; /* The k-th element of row iw has been processed. Reset swappd before looking at the next element. */ x490: SWAPPD = FALSE; } /* ================================================================== End of main elimination loop. ================================================================== Cancel markers on row iw. */ x600: LUSOL->lenr[IW] = LENW; if(LENW==0) goto x910; for(L = LW1; L <= LW2; L++) { J = LUSOL->indr[L]; LUSOL->locc[J] = 0; } /* Move the diagonal element to the front of row iw. At this stage, lenw gt 0 and klast le n. */ x700: for(L = LW1; L <= LW2; L++) { LDIAG = L; if(LUSOL->indr[L]==JFIRST) goto x730; } goto x910; x730: *DIAG = LUSOL->a[LDIAG]; LUSOL->a[LDIAG] = LUSOL->a[LW1]; LUSOL->a[LW1] = *DIAG; LUSOL->indr[LDIAG] = LUSOL->indr[LW1]; LUSOL->indr[LW1] = JFIRST; /* If an interchange is needed, repeat from the beginning with the new row iw, knowing that the opposite interchange cannot occur. */ if(SWAPPD) goto x100; *INFORM = LUSOL_INFORM_LUSUCCESS; goto x950; /* Singular. */ x910: *DIAG = ZERO; *INFORM = LUSOL_INFORM_LUSINGULAR; /* Force a compression if the file for U is much longer than the no. of nonzeros in U (i.e. if lrow is much bigger than lenU). This should prevent memory fragmentation when there is far more memory than necessary (i.e. when lena is huge). */ x950: LIMIT = (int) (USPACE*(*LENU))+LUSOL->m+LUSOL->n+1000; if(*LROW>LIMIT) LU1REC(LUSOL, LUSOL->m,TRUE,LROW,LUSOL->indr,LUSOL->lenr,LUSOL->locr); goto x990; /* Not enough storage. */ x970: *INFORM = LUSOL_INFORM_ANEEDMEM; /* Exit. */ x990: ; } /* ================================================================== lu7rnk (check rank) assumes U is currently nrank by n and determines if row nrank contains an acceptable pivot. If not, the row is deleted and nrank is decreased by 1. jsing is an input parameter (not altered). If jsing is positive, column jsing has already been judged dependent. A substitute (if any) must be some other column. ------------------------------------------------------------------ -- Jul 1987: First version. 09 May 1988: First f77 version. ================================================================== */ void LU7RNK(LUSOLrec *LUSOL, int JSING, int *LENU, int *LROW, int *NRANK, int *INFORM, REAL *DIAG) { REAL UTOL1, UMAX; int IW, LENW, L1, L2, LMAX, L, JMAX, KMAX; #ifdef ForceInitialization L1 = 0; L2 = 0; #endif UTOL1 = LUSOL->parmlu[LUSOL_RP_SMALLDIAG_U]; *DIAG = ZERO; /* Find Umax, the largest element in row nrank. */ IW = LUSOL->ip[*NRANK]; LENW = LUSOL->lenr[IW]; if(LENW==0) goto x400; L1 = LUSOL->locr[IW]; L2 = (L1+LENW)-1; UMAX = ZERO; LMAX = L1; for(L = L1; L <= L2; L++) { if(UMAXa[L])) { UMAX = fabs(LUSOL->a[L]); LMAX = L; } } /* Find which column that guy is in (in pivotal order). Interchange him with column nrank, then move him to be the new diagonal at the front of row nrank. */ *DIAG = LUSOL->a[LMAX]; JMAX = LUSOL->indr[LMAX]; for(KMAX = *NRANK; KMAX <= LUSOL->n; KMAX++) { if(LUSOL->iq[KMAX]==JMAX) break; } LUSOL->iq[KMAX] = LUSOL->iq[*NRANK]; LUSOL->iq[*NRANK] = JMAX; LUSOL->a[LMAX] = LUSOL->a[L1]; LUSOL->a[L1] = *DIAG; LUSOL->indr[LMAX] = LUSOL->indr[L1]; LUSOL->indr[L1] = JMAX; /* See if the new diagonal is big enough. */ if(UMAX<=UTOL1) goto x400; if(JMAX==JSING) goto x400; /* ------------------------------------------------------------------ The rank stays the same. ------------------------------------------------------------------ */ *INFORM = LUSOL_INFORM_LUSUCCESS; return; /* ------------------------------------------------------------------ The rank decreases by one. ------------------------------------------------------------------ */ x400: *INFORM = LUSOL_INFORM_RANKLOSS; (*NRANK)--; if(LENW>0) { /* Delete row nrank from U. */ LENU = LENU-LENW; LUSOL->lenr[IW] = 0; for(L = L1; L <= L2; L++) { LUSOL->indr[L] = 0; } if(L2==*LROW) { /* This row was at the end of the data structure. We have to reset lrow. Preceding rows might already have been deleted, so we have to be prepared to go all the way back to 1. */ for(L = 1; L <= L2; L++) { if(LUSOL->indr[*LROW]>0) goto x900; (*LROW)--; } } } x900: ; } /* ================================================================== lu7zap eliminates all nonzeros in column jzap of U. It also sets kzap to the position of jzap in pivotal order. Thus, on exit we have iq(kzap) = jzap. ------------------------------------------------------------------ -- Jul 1987: nrank added. 10 May 1988: First f77 version. ================================================================== */ void LU7ZAP(LUSOLrec *LUSOL, int JZAP, int *KZAP, int *LENU, int *LROW, int NRANK) { int K, I, LENI, LR1, LR2, L; for(K = 1; K <= NRANK; K++) { I = LUSOL->ip[K]; LENI = LUSOL->lenr[I]; if(LENI==0) goto x90; LR1 = LUSOL->locr[I]; LR2 = (LR1+LENI)-1; for(L = LR1; L <= LR2; L++) { if(LUSOL->indr[L]==JZAP) goto x60; } goto x90; /* Delete the old element. */ x60: LUSOL->a[L] = LUSOL->a[LR2]; LUSOL->indr[L] = LUSOL->indr[LR2]; LUSOL->indr[LR2] = 0; LUSOL->lenr[I] = LENI-1; (*LENU)--; /* Stop if we know there are no more rows containing jzap. */ x90: *KZAP = K; if(LUSOL->iq[K]==JZAP) goto x800; } /* nrank must be smaller than n because we haven't found kzap yet. */ L = LUSOL->n; for(K = NRANK+1; K <= L; K++) { *KZAP = K; if(LUSOL->iq[K]==JZAP) break; } /* See if we zapped the last element in the file. */ x800: if(*LROW>0) { if(LUSOL->indr[*LROW]==0) (*LROW)--; } } MSVMpack1.2/lp_solve_5.5/bfp/bfp_LUSOL/LUSOL/mmio.h0000664000175000017500000001034011141443436020441 0ustar lauerlauer/* * Matrix Market I/O library for ANSI C * * See http://math.nist.gov/MatrixMarket for details. * * */ #ifndef MM_IO_H #define MM_IO_H #define MM_MAX_LINE_LENGTH 1025 #define MatrixMarketBanner "%%MatrixMarket" #define MM_MAX_TOKEN_LENGTH 64 typedef char MM_typecode[4]; char *mm_typecode_to_str(MM_typecode matcode); int mm_read_banner(FILE *f, MM_typecode *matcode); int mm_read_mtx_crd_size(FILE *f, int *M, int *N, int *nz); int mm_read_mtx_array_size(FILE *f, int *M, int *N); int mm_write_banner(FILE *f, MM_typecode matcode); int mm_write_mtx_crd_size(FILE *f, int M, int N, int nz); int mm_write_mtx_array_size(FILE *f, int M, int N); /********************* MM_typecode query fucntions ***************************/ #define mm_is_matrix(typecode) ((typecode)[0]=='M') #define mm_is_sparse(typecode) ((typecode)[1]=='C') #define mm_is_coordinate(typecode)((typecode)[1]=='C') #define mm_is_dense(typecode) ((typecode)[1]=='A') #define mm_is_array(typecode) ((typecode)[1]=='A') #define mm_is_complex(typecode) ((typecode)[2]=='C') #define mm_is_real(typecode) ((typecode)[2]=='R') #define mm_is_pattern(typecode) ((typecode)[2]=='P') #define mm_is_integer(typecode) ((typecode)[2]=='I') #define mm_is_symmetric(typecode)((typecode)[3]=='S') #define mm_is_general(typecode) ((typecode)[3]=='G') #define mm_is_skew(typecode) ((typecode)[3]=='K') #define mm_is_hermitian(typecode)((typecode)[3]=='H') int mm_is_valid(MM_typecode matcode); /* too complex for a macro */ /********************* MM_typecode modify fucntions ***************************/ #define mm_set_matrix(typecode) ((*typecode)[0]='M') #define mm_set_coordinate(typecode) ((*typecode)[1]='C') #define mm_set_array(typecode) ((*typecode)[1]='A') #define mm_set_dense(typecode) mm_set_array(typecode) #define mm_set_sparse(typecode) mm_set_coordinate(typecode) #define mm_set_complex(typecode)((*typecode)[2]='C') #define mm_set_real(typecode) ((*typecode)[2]='R') #define mm_set_pattern(typecode)((*typecode)[2]='P') #define mm_set_integer(typecode)((*typecode)[2]='I') #define mm_set_symmetric(typecode)((*typecode)[3]='S') #define mm_set_general(typecode)((*typecode)[3]='G') #define mm_set_skew(typecode) ((*typecode)[3]='K') #define mm_set_hermitian(typecode)((*typecode)[3]='H') #define mm_clear_typecode(typecode) ((*typecode)[0]=(*typecode)[1]= \ (*typecode)[2]=' ',(*typecode)[3]='G') #define mm_initialize_typecode(typecode) mm_clear_typecode(typecode) /********************* Matrix Market error codes ***************************/ #define MM_COULD_NOT_READ_FILE 11 #define MM_PREMATURE_EOF 12 #define MM_NOT_MTX 13 #define MM_NO_HEADER 14 #define MM_UNSUPPORTED_TYPE 15 #define MM_LINE_TOO_LONG 16 #define MM_COULD_NOT_WRITE_FILE 17 /******************** Matrix Market internal definitions ******************** MM_matrix_typecode: 4-character sequence ojbect sparse/ data storage dense type scheme string position: [0] [1] [2] [3] Matrix typecode: M(atrix) C(oord) R(eal) G(eneral) A(array) C(omplex) H(ermitian) P(attern) S(ymmetric) I(nteger) K(kew) ***********************************************************************/ #define MM_MTX_STR "matrix" #define MM_ARRAY_STR "array" #define MM_DENSE_STR "array" #define MM_COORDINATE_STR "coordinate" #define MM_SPARSE_STR "coordinate" #define MM_COMPLEX_STR "complex" #define MM_REAL_STR "real" #define MM_INT_STR "integer" #define MM_GENERAL_STR "general" #define MM_SYMM_STR "symmetric" #define MM_HERM_STR "hermitian" #define MM_SKEW_STR "skew-symmetric" #define MM_PATTERN_STR "pattern" /* high level routines */ int mm_write_mtx_crd(char fname[], int M, int N, int nz, int I[], int J[], double val[], MM_typecode matcode); int mm_read_mtx_crd_data(FILE *f, int M, int N, int nz, int I[], int J[], double val[], MM_typecode matcode); int mm_read_mtx_crd_entry(FILE *f, int *I, int *J, double *real, double *img, MM_typecode matcode); int mm_read_unsymmetric_sparse(const char *fname, int *M_, int *N_, int *nz_, double **val_, int **I_, int **J_); #endif MSVMpack1.2/lp_solve_5.5/yacc_read.h0000664000175000017500000000370611141374612016227 0ustar lauerlauer/* prototypes of functions used in the parser */ #include #ifndef __READ_H__ #define __READ_H__ struct _tmp_store_struct { char *name; int row; REAL value; REAL rhs_value; short relat; }; typedef struct parse_parm_s { void *scanner; long lineno; int Verbose; jmp_buf jump_buf; long Rows, Columns, Non_zeros, Lin_term_count; struct rside *First_rside, *rs; short SOStype; /* SOS type */ char Ignore_int_decl, int_decl, Ignore_sec_decl, Ignore_free_decl, sos_decl, Maximise; hashtable *Hash_tab, *Hash_constraints; struct structcoldata *coldata; struct structSOS *FirstSOS, *LastSOS; struct _tmp_store_struct tmp_store; char *title; short *relat; void *parse_vars; } parse_parm; void lex_fatal_error(parse_parm *, void *, char *); int set_title(parse_parm *pp, char *name); int add_constraint_name(parse_parm *pp, char *name); int store_re_op(parse_parm *pp, char OP, int HadConstraint, int HadVar, int Had_lineair_sum); void null_tmp_store(parse_parm *pp, int init_Lin_term_count); int store_bounds(parse_parm *pp, int warn); void storevarandweight(parse_parm *pp, char *name); int set_sos_type(parse_parm *pp, int SOStype); int set_sos_weight(parse_parm *pp, double weight, int sos_decl); int set_sec_threshold(parse_parm *pp, char *name, REAL threshold); int rhs_store(parse_parm *pp, REAL value, int HadConstraint, int HadVar, int Had_lineair_sum); int var_store(parse_parm *pp, char *var, REAL value, int HadConstraint, int HadVar, int Had_lineair_sum); int negate_constraint(parse_parm *pp); void add_row(parse_parm *pp); void add_sos_row(parse_parm *pp, short SOStype); void read_error(parse_parm *, void *, char *); void check_int_sec_sos_free_decl(parse_parm *, int, int, int, int); lprec *yacc_read(lprec *lp, int verbose, char *lp_name, int (*parse) (parse_parm *pp), parse_parm *pp, void (*delete_allocated_memory) (parse_parm *pp)); #define set_obj_dir(pp, maximise) pp->Maximise = maximise #endif MSVMpack1.2/lp_solve_5.5/fortify.c0000664000175000017500000017135111164512462015776 0ustar lauerlauer/* * FILE: * fortify.c * * DESCRIPTION: * A fortified shell for malloc, realloc, calloc, strdup, getcwd, tempnam * and free. * To use Fortify, each source file will need to #include "fortify.h". To * enable Fortify, define the symbol FORTIFY. If FORTIFY is not defined, it * will compile away to nothing. If you do not have stderr available, you may * wish to set an alternate output function. See _Fortify_SetOutputFunc(), * below. * You will also need to link in fortify.o * * None of the functions in this file should really be called * directly; they really should be called through the macros * defined in fortify.h * */ #if defined FORTIFY #include #include #include #include #if defined MSDOS || defined __BORLANDC__ || defined WIN32 || defined __HIGHC__ # include #endif extern int EndOfPgr(int); #define __FORTIFY_C__ /* So fortify.h knows to not define the fortify macros */ #include "fortify.h" #include "ufortify.h" /* the user's options */ char *_Fortify_file=NULL; int _Fortify_line=0; #ifndef FORTIFY_TRANSPARENT #include #include #include #include #if defined MSDOS || defined __BORLANDC__ || defined WIN32 || defined __HIGHC__ # if !defined WIN32 # undef MSDOS # define MSDOS # endif # include #else # include # include # define getch() getchar() #endif #if defined _WINDOWS # include "windows.h" # if !defined WIN32 # include "toolhelp.h" # endif #endif #if defined LONGNAME # include "longname.h" #endif #if !defined MIN # define MIN(a, b) ((a) < (b) ? (a) : (b)) #endif struct Header { char *File; /* The sourcefile of the caller */ unsigned short Line; /* The sourceline of the caller */ size_t Size; /* The size of the malloc'd block */ struct Header *Prev, /* List pointers */ *Next; int Checksum; /* For validating the Header structure; see ChecksumHeader() */ unsigned char Scope; }; #if defined AViiON || defined __GNUC__ || defined _MSC_VER # define _static static #else # define _static #endif _static char *address __OF((void *addr)); _static int TimeToCheck __OF((void)); _static int CheckBlock __OF((struct Header *h, char *file, unsigned long line)); _static int CheckPointer __OF((unsigned char *ptr, unsigned long size, char *file, unsigned long line)); _static int CheckFortification __OF((unsigned char *ptr, unsigned char value, size_t size)); _static void SetFortification __OF((unsigned char *ptr, unsigned char value, size_t size)); _static void OutputFortification __OF((unsigned char *ptr, unsigned char value, size_t size)); _static int IsHeaderValid __OF((struct Header *h)); _static void MakeHeaderValid __OF((struct Header *h)); _static int ChecksumHeader __OF((struct Header *h)); _static int IsOnList __OF((struct Header *h)); _static void OutputHeader __OF((struct Header *h)); _static void OutputMemory __OF((struct Header *h)); _static void st_DefaultOutput __OF((char *String)); _static void WaitIfstdOutput __OF((void)); static char stdOutput = 0; /* If true, did some stderr output */ static OutputFuncPtr st_Output = st_DefaultOutput; /* Output function for errors */ #if !defined MSDOS && !defined WIN32 static int strnicmp(s1,s2,maxlen) char *s1,*s2; size_t maxlen; { while ((maxlen) && (*s1) && (*s2) && (toupper(*s1)==toupper(*s2))) { maxlen--; s1++; s2++; } return((maxlen) ? toupper(*s1)-toupper(*s2) : 0); } static int stricmp(s1,s2) char *s1,*s2; { return(strnicmp(s1,s2,strlen(s1)+1)); } #endif static char *address(void *addr) { static char str[80]; #if defined KNOWS_POINTER_TYPE sprintf(str,"%p",addr); #else sprintf(str,"%lx",(unsigned long) addr); #endif return(str); } #ifdef FORTIFY_CheckInterval int TimeToCheck() { static time_t lastcheck=0L; time_t t; int ret = 0; time(&t); if ((lastcheck==0L) || (t-lastcheck>=FORTIFY_CheckInterval)) { lastcheck = t; ret = 1; } return(ret); } #endif static FILE *gfile=NULL; static int Nchars=0,Nlines=0; static char flag=0; static void _Fortify_NoOutput() { } static void st_DefaultOutput(char *String) { static FILE *file; static char first=1; if (first) { file=stderr; first=0; } if (stdOutput==0) { Nchars=Nlines=0; if (gfile!=NULL) rewind(gfile); } if (flag==0) { char *ptr; file=stderr; flag = 1; if ((ptr=getenv("FORTIFY_OUTPUT"))!=NULL) { if ((stricmp(ptr,"null")==0) || (stricmp(ptr,"nul")==0)) file=NULL; else if (stricmp(ptr,"stderr")==0) file=stderr; else if (stricmp(ptr,"stdout")==0) file=stdout; #if defined MSDOS && !defined _WINDOWS && !defined WIN32 else if (stricmp(ptr,"stdprn")==0) file=stdprn; #endif else if ((file=fopen(ptr,"w"))==NULL) { #if !defined _WINDOWS fprintf(stderr,"\r\nFortify: Unable to create logfile %s\r\n",ptr); EndOfPgr(4); #else { char str[255]; sprintf(str,"Unable to create logfile\n \"%s\"",ptr); MessageBox((HWND) NULL,(LPCSTR) str,(LPCSTR) "Fortify",(UINT) MB_ICONSTOP); #if 0 #if defined WIN32 /* TerminateProcess(GetCurrentProcess(),65535); */ ExitProcess(65535); #else TerminateApp((HTASK) NULL,(WORD) NO_UAE_BOX); #endif #else EndOfPgr(1); #endif } #endif } } if ((file!=NULL) && (file!=stderr) && (file!=stdout)) { time_t t; time(&t); fprintf(file,"Generated on: %s%s\n", ctime(&t), (file==stdout) || (file==stderr) ? "\r" : "" ); } } if (file!=NULL) { #if defined _WINDOWS if ((file==stdout) || (file==stderr)) { #if defined LINE_BY_LINE if (MessageBox((HWND) NULL,(LPCSTR) String,(LPCSTR) "Fortify",(UINT) MB_OKCANCEL /* |MB_ICONINFORMATION */)==IDCANCEL) #if 0 #if defined WIN32 /* TerminateProcess(GetCurrentProcess(),65535); */ ExitProcess(65535); #else TerminateApp((HTASK) NULL,(WORD) NO_UAE_BOX); #endif #else EndOfPgr(1); #endif #else { char *ptr; ptr="fortify.tmp"; if ((ptr==NULL) || ((file=gfile=fopen(ptr,"w+"))==NULL)) { char str[255]; sprintf(str,"Unable to create temporary file\n \"%s\"",(ptr==NULL) ? "(NULL)" : ptr); MessageBox((HWND) NULL,(LPCSTR) str,(LPCSTR) "Fortify",(UINT) MB_ICONSTOP); #if 0 #if defined WIN32 /* TerminateProcess(GetCurrentProcess(),65535); */ ExitProcess(65535); #else TerminateApp((HTASK) NULL,(WORD) NO_UAE_BOX); #endif #else EndOfPgr(1); #endif } } #endif } if ((file!=stdout) && (file!=stderr)) #endif { int i,ch=-1; for (i=0;(String[i]) && (Nlines<30);i++) if (String[i]=='\n') Nlines++; if ((String[i]) && (String[i+1])) { ch=String[i+1]; String[i+1]=0; } if ((file==stdout) || (file==stderr)) { char *ptr=String; int i; do { for (i=0;(ptr[i]) && (ptr[i]!='\r') && (ptr[i]!='\n');i++); Nchars+=fprintf(file,"%-*.*s%s", i,i, ptr, (ptr[i]) ? "\r\n" : "" ); ptr+=i; if (ptr[0]=='\r') ptr++; if (ptr[0]=='\n') ptr++; } while (*ptr); } else Nchars+=fprintf(file,String); if (ch>=0) String[i+1]=(char)ch; if (Nlines>=30) { WaitIfstdOutput(); Nchars=Nlines=0; stdOutput = 0; if ((String[i]) && (String[i+1])) { if ((file==stderr) || (file==stdout) || ((gfile!=NULL) && (Nchars))) stdOutput = 1; st_DefaultOutput(String+i); } } } if ((file==stderr) || (file==stdout) || ((gfile!=NULL) && (Nchars))) stdOutput = 1; } } static void WaitIfstdOutput() { #if !defined _WINDOWS if((stdOutput) && (st_Output != (OutputFuncPtr) _Fortify_NoOutput)) { #ifdef FORTIFY_WAIT_FOR_KEY static signed char wait_on_key=-1; if(wait_on_key<0) { char *ptr; if (((ptr=getenv("FORTIFY_WAIT_FOR_KEY"))!=NULL) && (tolower(*ptr)=='n')) wait_on_key = 0; else wait_on_key = 1; } if(wait_on_key) { char c; #if !defined MSDOS && !defined WIN32 struct termio tio,tiobak; char flag; if ((flag=ioctl(0,TCGETA,&tio))==0) /* handle 0 is stdin */ { tiobak=tio; tio.c_lflag&=~ICANON; tio.c_lflag&=~ECHO; tio.c_cc[VMIN]=1; ioctl(0,TCSETA,&tio); } #endif /* !MSDOS */ c = (char)getch(); #if !defined MSDOS && !defined WIN32 if (flag==0) ioctl(0,TCSETA,&tiobak); #endif /* !MSDOS */ if ((c == 3) || (c == 0x1b)) EndOfPgr(3); } #endif /* FORTIFY_WAIT_FOR_KEY */ } #else # if !defined LINE_BY_LINE if ((stdOutput) && (gfile!=NULL) && (Nchars)) { char *ptr; ptr=(char *) malloc(Nchars+1); if (ptr!=NULL) { int n=0,l=0; rewind(gfile); while ((n 0) { if(rand() % 100 < st_MallocFailRate) { #ifdef WARN_ON_FALSE_FAIL sprintf(st_Buffer, "\nFortify: %s.%ld\n malloc(%ld) \"false\" failed\n", file, line, (unsigned long)size); st_Output(st_Buffer); #endif FORTIFY_UNLOCK(); WaitIfstdOutput(); return(0); } } /* * malloc the memory, including the space for the header and fortification * buffers */ #ifdef WARN_ON_SIZE_T_OVERFLOW { size_t private_size = sizeof(struct Header) + FORTIFY_BEFORE_SIZE + size + FORTIFY_AFTER_SIZE; if(private_size < size) /* Check to see if the added baggage is larger than size_t */ { sprintf(st_Buffer, "\nFortify: %s.%ld\n malloc(%ld) has overflowed size_t.\n", file, line, (unsigned long)size); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(0); } } #endif ptr = (unsigned char *) malloc(sizeof(struct Header) + FORTIFY_BEFORE_SIZE + size + FORTIFY_AFTER_SIZE); if(!ptr) { #ifdef WARN_ON_MALLOC_FAIL sprintf(st_Buffer, "\nFortify: %s.%ld\n malloc(%ld) failed\n", file, line, (unsigned long)size); st_Output(st_Buffer); #endif FORTIFY_UNLOCK(); WaitIfstdOutput(); return(0); } /* * Initialize and validate the header */ h = (struct Header *)ptr; h->Size = size; h->File = file; h->Line = (unsigned short) line; h->Next = st_Head; h->Prev = 0; h->Scope = st_Scope; if(st_Head) { st_Head->Prev = h; MakeHeaderValid(st_Head); } st_Head = h; MakeHeaderValid(h); /* * Initialize the fortifications */ SetFortification(ptr + sizeof(struct Header), FORTIFY_BEFORE_VALUE, FORTIFY_BEFORE_SIZE); SetFortification(ptr + sizeof(struct Header) + FORTIFY_BEFORE_SIZE + size, FORTIFY_AFTER_VALUE, FORTIFY_AFTER_SIZE); #ifdef FILL_ON_MALLOC /* * Fill the actual user memory */ SetFortification(ptr + sizeof(struct Header) + FORTIFY_BEFORE_SIZE, FILL_ON_MALLOC_VALUE, size); #endif /* * We return the address of the user's memory, not the start of the block, * which points to our magic cookies */ FORTIFY_UNLOCK(); WaitIfstdOutput(); return((void *) (ptr + sizeof(struct Header) + FORTIFY_BEFORE_SIZE)); } /* * _Fortify_free() - This free must be used for all memory allocated with * _Fortify_malloc(). * * Features: * + Pointers are validated before attempting a free - the pointer * must point to a valid malloc'd bit of memory. * + Detects attempts at freeing the same block of memory twice * + Can clear out memory as it is free'd, to prevent code from using * the memory after it's been freed. * + Checks the sentinals of the memory being freed. * + Can check the sentinals of all memory. */ void FORTIFY_STORAGE _Fortify_free(void *uptr,char *file,unsigned long line) { unsigned char *ptr; struct Header *h; if(uptr == NULL) return; ptr = (unsigned char *)uptr - sizeof(struct Header) - FORTIFY_BEFORE_SIZE; h = (struct Header *)ptr; stdOutput = 0; FORTIFY_LOCK(); if(st_Disabled) { free(uptr); FORTIFY_UNLOCK(); WaitIfstdOutput(); return; } #ifdef CHECK_ALL_MEMORY_ON_FREE #ifdef FORTIFY_CheckInterval if (TimeToCheck()) #endif _Fortify_CheckAllMemory(file, line); #endif #ifdef PARANOID_FREE if(!IsOnList(h)) { sprintf(st_Buffer, "\nFortify: %s.%ld\n Invalid pointer, corrupted header, or possible free twice\n", file, line); st_Output(st_Buffer); OutputLastVerifiedPoint(); goto fail; } #endif if(!CheckBlock(h, file, line)) goto fail; /* * Remove the block from the list */ if(h->Prev) { if(!CheckBlock(h->Prev, file, line)) goto fail; h->Prev->Next = h->Next; MakeHeaderValid(h->Prev); } else st_Head = h->Next; if(h->Next) { if(!CheckBlock(h->Next, file, line)) goto fail; h->Next->Prev = h->Prev; MakeHeaderValid(h->Next); } #ifdef FILL_ON_FREE /* * Nuke out all memory that is about to be freed */ SetFortification(ptr, FILL_ON_FREE_VALUE, sizeof(struct Header) + FORTIFY_BEFORE_SIZE + h->Size + FORTIFY_AFTER_SIZE); #endif /* * And do the actual free */ free(ptr); FORTIFY_UNLOCK(); WaitIfstdOutput(); return; fail: sprintf(st_Buffer, " free(%s) failed\n", address(uptr)); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); } /* * _Fortify_realloc() - Uses _Fortify_malloc() and _Fortify_free() to implement * realloc(). * * Features: * + The realloc'd block is ALWAYS moved. * + The pointer passed to realloc() is verified in the same way that * _Fortify_free() verifies pointers before it frees them. * + All the _Fortify_malloc() and _Fortify_free() protection */ void *FORTIFY_STORAGE _Fortify_realloc(void *ptr,size_t new_size,char *file,unsigned long line) { void *new_ptr; struct Header *h; if(new_size == 0) { _Fortify_free(ptr,file,line); return(NULL); } h = (struct Header *)((unsigned char *)ptr - sizeof(struct Header) - FORTIFY_BEFORE_SIZE); stdOutput = 0; if(st_Disabled) { FORTIFY_LOCK(); new_ptr = (void *) realloc(ptr, new_size); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(new_ptr); } if(!ptr) { void *FORTIFY_STORAGE ret = _Fortify_malloc(new_size, file, line); WaitIfstdOutput(); return(ret); } FORTIFY_LOCK(); if(!IsOnList(h)) { sprintf(st_Buffer, "\nFortify: %s.%ld\n Invalid pointer or corrupted header passed to realloc\n", file, line); st_Output(st_Buffer); goto fail; } if(!CheckBlock(h, file, line)) goto fail; new_ptr = _Fortify_malloc(new_size, file, line); if(!new_ptr) { FORTIFY_UNLOCK(); WaitIfstdOutput(); return(0); } if(h->Size < new_size) memcpy(new_ptr, ptr, h->Size); else memcpy(new_ptr, ptr, new_size); _Fortify_free(ptr, file, line); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(new_ptr); fail: sprintf(st_Buffer, " realloc(%s, %ld) failed\n", address(ptr), (unsigned long)new_size); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(NULL); } /* * __Fortify_CheckPointer() - Returns true if the uptr points to a valid * piece of _Fortify_malloc()'d memory. The memory must be on the malloc'd * list, and it's sentinals must be in tact. * If anything is wrong, an error message is issued. * * (Note - if fortify is disabled, this function always returns true). */ static int FORTIFY_STORAGE __Fortify_CheckPointer(void *uptr,char OnlyStart,unsigned long size,char *file,unsigned long line) { unsigned char *ptr = (unsigned char *)uptr - sizeof(struct Header) - FORTIFY_BEFORE_SIZE; int r = 1, StartPointer; stdOutput = 0; if(st_Disabled) { WaitIfstdOutput(); return(1); } FORTIFY_LOCK(); StartPointer = IsOnList((struct Header *)ptr); if((OnlyStart) && (!StartPointer)) { sprintf(st_Buffer, "\nFortify: %s.%ld\n Invalid pointer or corrupted header detected (%s)\n", file, line, address(uptr)); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(0); } if((OnlyStart) || (StartPointer)) r = CheckBlock((struct Header *)ptr, file, line); if(!OnlyStart) r = CheckPointer((unsigned char *)uptr, size, file, line); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(r); } int FORTIFY_STORAGE _Fortify_CheckPointer(void *uptr,char *file,unsigned long line) { return(__Fortify_CheckPointer(uptr,1,0,file,line)); } /* * Fortify_SetOutputFunc(OutputFuncPtr Output) - Sets the function used to * output all error and diagnostic messages by fortify. The output function * takes a single unsigned char * argument, and must be able to handle newlines. * The function returns the old pointer. */ Fortify_OutputFuncPtr FORTIFY_STORAGE _Fortify_SetOutputFunc(Fortify_OutputFuncPtr Output) { OutputFuncPtr Old = st_Output; st_Output = (OutputFuncPtr) Output; return((Fortify_OutputFuncPtr FORTIFY_STORAGE) Old); } /* * _Fortify_SetMallocFailRate(int Percent) - _Fortify_malloc() will make the * malloc attempt fail this Percent of the time, even if the memory is * available. Useful to "stress-test" an application. Returns the old * value. The fail rate defaults to 0. */ int FORTIFY_STORAGE _Fortify_SetMallocFailRate(int Percent) { int Old = st_MallocFailRate; st_MallocFailRate = Percent; return(Old); } /* * _Fortify_CheckAllMemory() - Checks the sentinals of all malloc'd memory. * Returns the number of blocks that failed. * * (If Fortify is disabled, this function always returns 0). */ int FORTIFY_STORAGE _Fortify_CheckAllMemory(char *file,unsigned long line) { struct Header *curr = st_Head; int count = 0; stdOutput = 0; if(st_Disabled) { WaitIfstdOutput(); return(0); } FORTIFY_LOCK(); while(curr) { if(!CheckBlock(curr, file, line)) count++; curr = curr->Next; } if(file) { st_LastVerifiedFile = file; st_LastVerifiedLine = (short) line; } FORTIFY_UNLOCK(); WaitIfstdOutput(); return(count); } /* _Fortify_EnterScope - enters a new Fortify scope level. * returns the new scope level. */ int FORTIFY_STORAGE _Fortify_EnterScope(char *file,unsigned long line) { return((int) ++st_Scope); } /* _Fortify_LeaveScope - leaves a Fortify scope level, * also prints a memory dump of all non-freed memory that was allocated * during the scope being exited. */ int FORTIFY_STORAGE _Fortify_LeaveScope(char *file,unsigned long line) { struct Header *curr = st_Head; int count = 0; size_t size = 0; stdOutput = 0; if(st_Disabled) { WaitIfstdOutput(); return(0); } FORTIFY_LOCK(); st_Scope--; while(curr) { if(curr->Scope > st_Scope) { if(count == 0) { sprintf(st_Buffer, "\nFortify: Memory Dump at %s.%ld\n", file, line); st_Output(st_Buffer); OutputLastVerifiedPoint(); sprintf(st_Buffer, "%11s %8s %s\n", "Address", "Size", "Allocator"); st_Output(st_Buffer); } OutputHeader(curr); count++; size += curr->Size; } curr = curr->Next; } if(count) { sprintf(st_Buffer, "%11s %8ld bytes overhead\n", "and", (unsigned long)(count * (sizeof(struct Header) + FORTIFY_BEFORE_SIZE + FORTIFY_AFTER_SIZE))); st_Output(st_Buffer); sprintf(st_Buffer,"%11s %8ld bytes in %d blocks\n", "total", size, count); st_Output(st_Buffer); } FORTIFY_UNLOCK(); WaitIfstdOutput(); return(count); } /* * _Fortify_OutputAllMemory() - Outputs the entire list of currently * malloc'd memory. For each malloc'd block is output it's Address, * Size, and the SourceFile and Line that allocated it. * * If there is no memory on the list, this function outputs nothing. * * It returns the number of blocks on the list, unless fortify has been * disabled, in which case it always returns 0. */ int FORTIFY_STORAGE _Fortify_OutputAllMemory(char *file,unsigned long line) { struct Header *curr = st_Head; int count = 0; size_t size = 0; stdOutput = 0; if(st_Disabled) { WaitIfstdOutput(); return(0); } FORTIFY_LOCK(); if(curr) { sprintf(st_Buffer, "\nFortify: Memory Dump at %s.%ld\n", file, line); st_Output(st_Buffer); OutputLastVerifiedPoint(); sprintf(st_Buffer, "%11s %8s %s\n", "Address", "Size", "Allocator"); st_Output(st_Buffer); while(curr) { OutputHeader(curr); count++; size += curr->Size; curr = curr->Next; } sprintf(st_Buffer, "%11s %8ld bytes overhead\n", "and", (unsigned long)(count * (sizeof(struct Header) + FORTIFY_BEFORE_SIZE + FORTIFY_AFTER_SIZE))); st_Output(st_Buffer); sprintf(st_Buffer,"%11s %8ld bytes in %d blocks\n", "total", size, count); st_Output(st_Buffer); } FORTIFY_UNLOCK(); WaitIfstdOutput(); return(count); } /* _Fortify_DumpAllMemory(Scope) - Outputs the entire list of currently * new'd memory within the specified scope. For each new'd block is output * it's Address, Size, the SourceFile and Line that allocated it, a hex dump * of the contents of the memory and an ascii dump of printable characters. * * If there is no memory on the list, this function outputs nothing. * * It returns the number of blocks on the list, unless Fortify has been * disabled, in which case it always returns 0. */ int FORTIFY_STORAGE _Fortify_DumpAllMemory(int scope,char *file,unsigned long line) { struct Header *curr = st_Head; int count = 0; size_t size = 0; stdOutput = 0; if(st_Disabled) { WaitIfstdOutput(); return(0); } FORTIFY_LOCK(); while(curr) { if(curr->Scope >= scope) { if(count == 0) { sprintf(st_Buffer, "\nFortify: Memory Dump at %s.%ld\n", file, line); st_Output(st_Buffer); OutputLastVerifiedPoint(); sprintf(st_Buffer, "%11s %8s %s\n", "Address", "Size", "Allocator"); st_Output(st_Buffer); } OutputHeader(curr); OutputMemory(curr); st_Output("\n"); count++; size += curr->Size; } curr = curr->Next; } if(count) { sprintf(st_Buffer, "%11s %8ld bytes overhead\n", "and", (unsigned long)(count * (sizeof(struct Header) + FORTIFY_BEFORE_SIZE + FORTIFY_AFTER_SIZE))); st_Output(st_Buffer); sprintf(st_Buffer,"%11s %8ld bytes in %d blocks\n", "total", size, count); st_Output(st_Buffer); } FORTIFY_UNLOCK(); WaitIfstdOutput(); return(count); } /* * _Fortify_Disable() - This function provides a mechanism to disable Fortify * without recompiling all the sourcecode. * If 'how' is zero then it can only be called when there is no memory on the * Fortify malloc'd list. (Ideally, at the start of the program before any * memory has been allocated). If you call this function when there IS * memory on the Fortify malloc'd list, it will issue an error, and fortify * will not be disabled. * If 'how' is nonzero then output will only be disabled. This can always be * done. */ int FORTIFY_STORAGE _Fortify_Disable(char *file,unsigned long line,int how) { int result; if (how <= 0) { stdOutput = 0; FORTIFY_LOCK(); if((st_Head) && (how == 0)) { sprintf(st_Buffer, "Fortify: %s.%d\n", file, line); st_Output(st_Buffer); st_Output(" Fortify_Disable failed\n"); st_Output(" (because there is memory on the Fortify memory list)\n"); _Fortify_OutputAllMemory(file, line); result = 0; } else { st_Disabled = (how >= -1 ? 1 : 0); result = 1; } FORTIFY_UNLOCK(); WaitIfstdOutput(); } else { _Fortify_SetOutputFunc((Fortify_OutputFuncPtr) _Fortify_NoOutput); result = 1; } return(result); } /* * Check a block's header and fortifications. */ static int CheckBlock(struct Header *h,char *file,unsigned long line) { unsigned char *ptr = (unsigned char *)h; int result = 1; stdOutput = 0; if(!IsHeaderValid(h)) { sprintf(st_Buffer, "\nFortify: %s.%ld\n Invalid pointer or corrupted header detected (%s)\n", file, line, address(ptr + sizeof(struct Header) + FORTIFY_BEFORE_SIZE)); st_Output(st_Buffer); OutputLastVerifiedPoint(); WaitIfstdOutput(); return(0); } if(!CheckFortification(ptr + sizeof(struct Header), FORTIFY_BEFORE_VALUE, FORTIFY_BEFORE_SIZE)) { sprintf(st_Buffer, "\nFortify: %s.%ld\n Memory overrun detected before block\n", file, line); st_Output(st_Buffer); sprintf(st_Buffer," (%s,%ld,%s.%u)\n", address(ptr + sizeof(struct Header) + FORTIFY_BEFORE_SIZE), (unsigned long)h->Size, h->File, h->Line); st_Output(st_Buffer); OutputFortification(ptr + sizeof(struct Header), FORTIFY_BEFORE_VALUE, FORTIFY_BEFORE_SIZE); OutputLastVerifiedPoint(); result = 0; } if(!CheckFortification(ptr + sizeof(struct Header) + FORTIFY_BEFORE_SIZE + h->Size, FORTIFY_AFTER_VALUE, FORTIFY_AFTER_SIZE)) { sprintf(st_Buffer, "\nFortify: %s.%ld\n Memory overrun detected after block\n", file, line); st_Output(st_Buffer); sprintf(st_Buffer," (%s,%ld,%s.%u)\n", address(ptr + sizeof(struct Header) + FORTIFY_BEFORE_SIZE), (unsigned long)h->Size, h->File, h->Line); st_Output(st_Buffer); OutputFortification(ptr + sizeof(struct Header) + FORTIFY_BEFORE_SIZE + h->Size, FORTIFY_AFTER_VALUE, FORTIFY_AFTER_SIZE); OutputLastVerifiedPoint(); result = 0; } WaitIfstdOutput(); return(result); } static int CheckPointer(unsigned char *ptr,unsigned long size,char *file,unsigned long line) { struct Header *curr; unsigned char *ptr1; curr = st_Head; while(curr) { ptr1 = (unsigned char *)curr + sizeof(struct Header) + FORTIFY_BEFORE_SIZE; if(ptr + size <= (unsigned char *)curr) ; else if(ptr >= ptr1) ; else { sprintf(st_Buffer, "\nFortify: %s.%ld\n Memory access detected before block\n", file, line); st_Output(st_Buffer); sprintf(st_Buffer," (%s,%ld,%s.%u)\n", address(ptr1), (unsigned long)curr->Size, curr->File, curr->Line); st_Output(st_Buffer); WaitIfstdOutput(); return(0); } if(ptr + size <= ptr1 + curr->Size) ; else if(ptr >= ptr1 + curr->Size + FORTIFY_AFTER_SIZE) ; else { sprintf(st_Buffer, "\nFortify: %s.%ld\n Memory access detected after block\n", file, line); st_Output(st_Buffer); sprintf(st_Buffer," (%s,%ld,%s.%u)\n", address(ptr1), (unsigned long)curr->Size, curr->File, curr->Line); st_Output(st_Buffer); WaitIfstdOutput(); return(0); } if((ptr >= ptr1) && (ptr < ptr1 + curr->Size) && (ptr + size > ptr1 + curr->Size)) { sprintf(st_Buffer, "\nFortify: %s.%ld\n Memory access detected after block\n", file, line); st_Output(st_Buffer); sprintf(st_Buffer," (%s,%ld,%s.%u)\n", address(ptr + sizeof(struct Header) + FORTIFY_BEFORE_SIZE), (unsigned long)curr->Size, curr->File, curr->Line); st_Output(st_Buffer); WaitIfstdOutput(); return(0); } curr = curr->Next; } return(1); } /* * Checks if the _size_ bytes from _ptr_ are all set to _value_ */ static int CheckFortification(unsigned char *ptr,unsigned char value,size_t size) { while(size--) if(*ptr++ != value) return(0); return(1); } /* * Set the _size_ bytes from _ptr_ to _value_. */ static void SetFortification(unsigned char *ptr,unsigned char value,size_t size) { memset(ptr, value, size); } /* * Output the corrupted section of the fortification */ /* Output the corrupted section of the fortification */ static void OutputFortification(unsigned char *ptr,unsigned char value,size_t size) { unsigned long offset, column; char ascii[17]; st_Output("Address Offset Data"); offset = 0; column = 0; while(offset < size) { if(column == 0) { sprintf(st_Buffer, "\n%8s %8d ", address(ptr), offset); st_Output(st_Buffer); } sprintf(st_Buffer, "%02x ", *ptr); st_Output(st_Buffer); ascii[ (int) column ] = isprint( *ptr ) ? (char)(*ptr) : (char)(' '); ascii[ (int) (column + 1) ] = '\0'; ptr++; offset++; column++; if(column == 16) { st_Output( " \"" ); st_Output( ascii ); st_Output( "\"" ); column = 0; } } if ( column != 0 ) { while ( column ++ < 16 ) { st_Output( " " ); } st_Output( " \"" ); st_Output( ascii ); st_Output( "\"" ); } st_Output("\n"); } /* * Returns true if the supplied pointer does indeed point to a real Header */ static int IsHeaderValid(struct Header *h) { return(!ChecksumHeader(h)); } /* * Updates the checksum to make the header valid */ static void MakeHeaderValid(struct Header *h) { h->Checksum = 0; h->Checksum = -ChecksumHeader(h); } /* * Calculate (and return) the checksum of the header. (Including the Checksum * variable itself. If all is well, the checksum returned by this function should * be 0. */ static int ChecksumHeader(struct Header *h) { register int c, checksum, *p; for(c = 0, checksum = 0, p = (int *)h; c < sizeof(struct Header)/sizeof(int); c++) checksum += *p++; return(checksum); } /* * Examines the malloc'd list to see if the given header is on it. */ static int IsOnList(struct Header *h) { struct Header *curr; curr = st_Head; while(curr) { if(curr == h) return(1); curr = curr->Next; } return(0); } /* * Hex and ascii dump the memory */ static void OutputMemory(struct Header *h) { OutputFortification((unsigned char*)h + sizeof(struct Header) + FORTIFY_BEFORE_SIZE, 0, h->Size); } /* * Output the header... */ static void OutputHeader(struct Header *h) { sprintf(st_Buffer, "%11s %8ld %s.%u (%d)\n", address((unsigned char*)h + sizeof(struct Header) + FORTIFY_BEFORE_SIZE), (unsigned long)h->Size, h->File, h->Line, (int) h->Scope); st_Output(st_Buffer); } static void OutputLastVerifiedPoint() { sprintf(st_Buffer, "\nLast Verified point: %s.%u\n", st_LastVerifiedFile, st_LastVerifiedLine); st_Output(st_Buffer); } #else /* FORTIFY_TRANSPARENT */ void *FORTIFY_STORAGE _Fortify_malloc(size,file,line) size_t size; char *file; unsigned long line; { return(malloc(size)); } void FORTIFY_STORAGE _Fortify_free(uptr,file,line) void *uptr; char *file; unsigned long line; { free(uptr); } void *FORTIFY_STORAGE _Fortify_realloc(ptr,new_size,file,line) void *ptr; size_t new_size; char *file; unsigned long line; { return(realloc(ptr, new_size)); } int FORTIFY_STORAGE _Fortify_CheckPointer(uptr,file,line) void *uptr; char *file; unsigned long line; { return(1); } Fortify_OutputFuncPtr FORTIFY_STORAGE _Fortify_SetOutputFunc(Output) Fortify_OutputFuncPtr Output; { return(0); } int FORTIFY_STORAGE _Fortify_SetMallocFailRate(Percent) int Percent; { return(0); } int FORTIFY_STORAGE _Fortify_CheckAllMemory(file,line) char *file; unsigned long line; { return(0); } int FORTIFY_STORAGE _Fortify_EnterScope(file,line) char *file; unsigned long line; { return(0); } int FORTIFY_STORAGE _Fortify_LeaveScope(file,line) char *file; unsigned long line; { return(0); } int FORTIFY_STORAGE _Fortify_OutputAllMemory(file,line) char *file; unsigned long line; { return(0); } int FORTIFY_STORAGE _Fortify_DumpAllMemory(scope,file,line) int scope; char *file; unsigned long line; { return(0); } int FORTIFY_STORAGE _Fortify_Disable(file,line) char *file; unsigned long line; { return(1); } #endif /* !FORTIFY_TRANSPARENT */ /* function that use _Fortify_malloc(), _Fortify_realloc(), _Fortify_free() */ /* * Fortifty_calloc() - Uses _Fortify_malloc() to implement calloc(). Much * the same protection as _Fortify_malloc(). */ void *FORTIFY_STORAGE _Fortify_calloc(size_t nitems,size_t size,char *file,unsigned long line) { void *ptr; ptr = _Fortify_malloc(nitems * size, file, line); if(ptr) memset(ptr, 0, nitems * size); return(ptr); } /* * Fortifty_strdup() - Uses _Fortify_malloc() to implement strdup(). Much * the same protection as _Fortify_malloc(). * The library function is not used because it is not certain that getpwd * uses the library malloc function (if linked with an alternate library) * and if the memory is freed then strange things can happen */ char *FORTIFY_STORAGE _Fortify_strdup(char *str,char *file,unsigned long line) { char *ptr; unsigned long l; if(str == NULL) { sprintf(st_Buffer, "\nFortify: %s.%ld\n ", file, line); sprintf(st_Buffer + strlen(st_Buffer), "%s", "strdup pointer is NULL", file, line); strcat(st_Buffer, "\n"); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(0); } l = (int) strlen(str) + 1; __Fortify_CheckPointer(str,0,l,file,line); ptr = (char *) _Fortify_malloc(l, file, line); if(ptr) strcpy(ptr, str); return(ptr); } /* * Fortifty_getpwd() - Uses _Fortify_malloc() to implement getpwd(). Much * the same protection as _Fortify_malloc(). * Memory is not allocated bu getcwd but by our routine for the same reason * as for strdup */ char *FORTIFY_STORAGE _Fortify_getcwd(char *buf,int size,char *file,unsigned long line) { char *ptr; if(buf!=NULL) ptr = buf; else ptr = (char *) _Fortify_malloc(size + 1, file, line); if(ptr) ptr = getcwd(ptr, size); return(ptr); } /* * Fortifty_tempnam() - Uses _Fortify_strdup() to implement tempnam(). Much * the same protection as _Fortify_malloc(). */ char *FORTIFY_STORAGE _Fortify_tempnam(char *dir,char *pfx,char *file,unsigned long line) { char *ptr1, *ptr2; ptr1 = tempnam(dir,pfx); if(ptr1) { ptr2=_Fortify_strdup(ptr1,file,line); free(ptr1); ptr1=ptr2; } return(ptr1); } /* * Fortify_memcpy() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ void *FORTIFY_STORAGE _Fortify_memcpy(void *to,void *from,size_t size,char *file,unsigned long line) { if((from == NULL) || (to == NULL)) { sprintf(st_Buffer, "\nFortify: %s.%ld\n ", file, line); if(from == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s", "memcpy from pointer is NULL", file, line); if(to == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s%s", (from == NULL) ? "" : " and ", "memcpy to pointer is NULL", file, line); strcat(st_Buffer, "\n"); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(NULL); } __Fortify_CheckPointer(to,0,size,file,line); __Fortify_CheckPointer(from,0,size,file,line); return(memcpy(to,from,size)); } /* * Fortify_memmove() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ void *FORTIFY_STORAGE _Fortify_memmove(void *to,void *from,size_t size,char *file,unsigned long line) { if((from == NULL) || (to == NULL)) { sprintf(st_Buffer, "\nFortify: %s.%ld\n ", file, line); if(from == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s", "memmove from pointer is NULL", file, line); if(to == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s%s", (from == NULL) ? "" : " and ", "memmove to pointer is NULL", file, line); strcat(st_Buffer, "\n"); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(NULL); } __Fortify_CheckPointer(to,0,size,file,line); __Fortify_CheckPointer(from,0,size,file,line); return(memmove(to,from,size)); } /* * Fortify_memccpy() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ void *FORTIFY_STORAGE _Fortify_memccpy(void *to,void *from,int c,size_t size,char *file,unsigned long line) { if((from == NULL) || (to == NULL)) { sprintf(st_Buffer, "\nFortify: %s.%ld\n ", file, line); if(from == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s", "memccpy from pointer is NULL", file, line); if(to == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s%s", (from == NULL) ? "" : " and ", "memccpy to pointer is NULL", file, line); strcat(st_Buffer, "\n"); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(NULL); } __Fortify_CheckPointer(to,0,size,file,line); __Fortify_CheckPointer(from,0,size,file,line); return(memccpy(to,from,c,size)); } /* * Fortify_memset() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ void *FORTIFY_STORAGE _Fortify_memset(void *buffer,int c,size_t size,char *file,unsigned long line) { if(buffer == NULL) { sprintf(st_Buffer, "\nFortify: %s.%ld\n memset pointer is NULL\n", file, line); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(NULL); } __Fortify_CheckPointer(buffer,0,size,file,line); return(memset(buffer,c,size)); } /* * Fortify_memchr() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ void *FORTIFY_STORAGE _Fortify_memchr(void *buffer,int c,size_t size,char *file,unsigned long line) { if(buffer == NULL) { sprintf(st_Buffer, "\nFortify: %s.%ld\n memchr pointer is NULL\n", file, line); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(NULL); } __Fortify_CheckPointer(buffer,0,size,file,line); return(memchr(buffer,c,size)); } /* * Fortify_memcmp() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ int FORTIFY_STORAGE _Fortify_memcmp(void *buffer1,void *buffer2,size_t size,char *file,unsigned long line) { if((buffer1 == NULL) || (buffer2 == NULL)) { sprintf(st_Buffer, "\nFortify: %s.%ld\n ", file, line); if(buffer1 == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s", "memcmp first pointer is NULL", file, line); if(buffer2 == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s%s", (buffer2 == NULL) ? "" : " and ", "memcmp second pointer is NULL", file, line); strcat(st_Buffer, "\n"); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(0); } __Fortify_CheckPointer(buffer1,0,size,file,line); __Fortify_CheckPointer(buffer2,0,size,file,line); return(memcmp(buffer1,buffer2,size)); } /* * Fortify_memicmp() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ int FORTIFY_STORAGE _Fortify_memicmp(void *buffer1,void *buffer2,size_t size,char *file,unsigned long line) { if((buffer1 == NULL) || (buffer2 == NULL)) { sprintf(st_Buffer, "\nFortify: %s.%ld\n ", file, line); if(buffer1 == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s", "memicmp first pointer is NULL", file, line); if(buffer2 == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s%s", (buffer2 == NULL) ? "" : " and ", "memicmp second pointer is NULL", file, line); strcat(st_Buffer, "\n"); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(0); } __Fortify_CheckPointer(buffer1,0,size,file,line); __Fortify_CheckPointer(buffer2,0,size,file,line); return(memicmp(buffer1,buffer2,size)); } /* * Fortify_strcoll() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ int FORTIFY_STORAGE _Fortify_strcoll(char *buffer1,char *buffer2,char *file,unsigned long line) { if((buffer1 == NULL) || (buffer2 == NULL)) { sprintf(st_Buffer, "\nFortify: %s.%ld\n ", file, line); if(buffer1 == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s", "strcoll first pointer is NULL", file, line); if(buffer2 == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s%s", (buffer2 == NULL) ? "" : " and ", "strcoll second pointer is NULL", file, line); strcat(st_Buffer, "\n"); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(0); } __Fortify_CheckPointer(buffer1,0,strlen(buffer1)+1,file,line); __Fortify_CheckPointer(buffer2,0,strlen(buffer2)+1,file,line); return(strcoll(buffer1,buffer2)); } /* * Fortify_strcspn() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ size_t FORTIFY_STORAGE _Fortify_strcspn(char *buffer1,char *buffer2,char *file,unsigned long line) { if((buffer1 == NULL) || (buffer2 == NULL)) { sprintf(st_Buffer, "\nFortify: %s.%ld\n ", file, line); if(buffer1 == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s", "strcspn first pointer is NULL", file, line); if(buffer2 == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s%s", (buffer2 == NULL) ? "" : " and ", "strcspn second pointer is NULL", file, line); strcat(st_Buffer, "\n"); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(0); } __Fortify_CheckPointer(buffer1,0,strlen(buffer1)+1,file,line); __Fortify_CheckPointer(buffer2,0,strlen(buffer2)+1,file,line); return(strcspn(buffer1,buffer2)); } /* * Fortify_strcmp() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ int FORTIFY_STORAGE _Fortify_strcmp(char *buffer1,char *buffer2,char *file,unsigned long line) { if((buffer1 == NULL) || (buffer2 == NULL)) { sprintf(st_Buffer, "\nFortify: %s.%ld\n ", file, line); if(buffer1 == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s", "strcmp first pointer is NULL", file, line); if(buffer2 == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s%s", (buffer2 == NULL) ? "" : " and ", "strcmp second pointer is NULL", file, line); strcat(st_Buffer, "\n"); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(0); } __Fortify_CheckPointer(buffer1,0,strlen(buffer1)+1,file,line); __Fortify_CheckPointer(buffer2,0,strlen(buffer2)+1,file,line); return(strcmp(buffer1,buffer2)); } /* * Fortify_strcmpi() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ int FORTIFY_STORAGE _Fortify_strcmpi(char *buffer1,char *buffer2,char *file,unsigned long line) { if((buffer1 == NULL) || (buffer2 == NULL)) { sprintf(st_Buffer, "\nFortify: %s.%ld\n ", file, line); if(buffer1 == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s", "strcmpi first pointer is NULL", file, line); if(buffer2 == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s%s", (buffer2 == NULL) ? "" : " and ", "strcmpi second pointer is NULL", file, line); strcat(st_Buffer, "\n"); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(0); } __Fortify_CheckPointer(buffer1,0,strlen(buffer1)+1,file,line); __Fortify_CheckPointer(buffer2,0,strlen(buffer2)+1,file,line); return(strcmpi(buffer1,buffer2)); } /* * Fortify_strncmp() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ int FORTIFY_STORAGE _Fortify_strncmp(char *buffer1,char *buffer2,size_t size,char *file,unsigned long line) { if((buffer1 == NULL) || (buffer2 == NULL)) { sprintf(st_Buffer, "\nFortify: %s.%ld\n ", file, line); if(buffer1 == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s", "strncmp first pointer is NULL", file, line); if(buffer2 == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s%s", (buffer2 == NULL) ? "" : " and ", "strncmp second pointer is NULL", file, line); strcat(st_Buffer, "\n"); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(0); } __Fortify_CheckPointer(buffer1,0,MIN(strlen(buffer1)+1,size),file,line); __Fortify_CheckPointer(buffer2,0,MIN(strlen(buffer2)+1,size),file,line); return(strncmp(buffer1,buffer2,size)); } /* * Fortify_strnicmp() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ int FORTIFY_STORAGE _Fortify_strnicmp(char *buffer1,char *buffer2,size_t size,char *file,unsigned long line) { if((buffer1 == NULL) || (buffer2 == NULL)) { sprintf(st_Buffer, "\nFortify: %s.%ld\n ", file, line); if(buffer1 == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s", "strnicmp first pointer is NULL", file, line); if(buffer2 == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s%s", (buffer2 == NULL) ? "" : " and ", "strnicmp second pointer is NULL", file, line); strcat(st_Buffer, "\n"); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(0); } __Fortify_CheckPointer(buffer1,0,MIN(strlen(buffer1)+1,size),file,line); __Fortify_CheckPointer(buffer2,0,MIN(strlen(buffer2)+1,size),file,line); return(strnicmp(buffer1,buffer2,size)); } /* * Fortify_strchr() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ char *FORTIFY_STORAGE _Fortify_strchr(char *buffer,int c,char *file,unsigned long line) { if(buffer == NULL) { sprintf(st_Buffer, "\nFortify: %s.%ld\n strchr pointer is NULL\n", file, line); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(NULL); } __Fortify_CheckPointer(buffer,0,strlen(buffer)+1,file,line); return(strchr(buffer,c)); } /* * Fortify_strrchr() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ char *FORTIFY_STORAGE _Fortify_strrchr(char *buffer,int c,char *file,unsigned long line) { if(buffer == NULL) { sprintf(st_Buffer, "\nFortify: %s.%ld\n strchr pointer is NULL\n", file, line); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(NULL); } __Fortify_CheckPointer(buffer,0,strlen(buffer)+1,file,line); return(strrchr(buffer,c)); } /* * Fortify_strlwr() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ char *FORTIFY_STORAGE _Fortify_strlwr(char *buffer,char *file,unsigned long line) { if(buffer == NULL) { sprintf(st_Buffer, "\nFortify: %s.%ld\n strlwr pointer is NULL\n", file, line); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(NULL); } __Fortify_CheckPointer(buffer,0,strlen(buffer)+1,file,line); return(strlwr(buffer)); } /* * Fortify_strlwr() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ char *FORTIFY_STORAGE _Fortify_strupr(char *buffer,char *file,unsigned long line) { if(buffer == NULL) { sprintf(st_Buffer, "\nFortify: %s.%ld\n strupr pointer is NULL\n", file, line); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(NULL); } __Fortify_CheckPointer(buffer,0,strlen(buffer)+1,file,line); return(strupr(buffer)); } /* * Fortify_strrev() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ char *FORTIFY_STORAGE _Fortify_strrev(char *buffer,char *file,unsigned long line) { if(buffer == NULL) { sprintf(st_Buffer, "\nFortify: %s.%ld\n strrev pointer is NULL\n", file, line); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(NULL); } __Fortify_CheckPointer(buffer,0,strlen(buffer)+1,file,line); return(strrev(buffer)); } /* * Fortify_strlen() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ size_t FORTIFY_STORAGE _Fortify_strlen(char *buffer,char *file,unsigned long line) { unsigned long l; if(buffer == NULL) { sprintf(st_Buffer, "\nFortify: %s.%ld\n strlen pointer is NULL\n", file, line); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(0); } l = strlen(buffer); __Fortify_CheckPointer(buffer,0,l+1,file,line); return(l); } /* * Fortify_strcat() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ char *FORTIFY_STORAGE _Fortify_strcat(char *buffer1,char *buffer2,char *file,unsigned long line) { unsigned long l; if((buffer1 == NULL) || (buffer2 == NULL)) { sprintf(st_Buffer, "\nFortify: %s.%ld\n ", file, line); if(buffer1 == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s", "strcat first pointer is NULL", file, line); if(buffer2 == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s%s", (buffer2 == NULL) ? "" : " and ", "strcat second pointer is NULL", file, line); strcat(st_Buffer, "\n"); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(0); } l = strlen(buffer2)+1; __Fortify_CheckPointer(buffer1,0,l,file,line); __Fortify_CheckPointer(buffer2,0,l,file,line); return(strcat(buffer1,buffer2)); } /* * Fortify_strpbrk() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ char *FORTIFY_STORAGE _Fortify_strpbrk(char *buffer1,char *buffer2,char *file,unsigned long line) { unsigned long l; if((buffer1 == NULL) || (buffer2 == NULL)) { sprintf(st_Buffer, "\nFortify: %s.%ld\n ", file, line); if(buffer1 == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s", "strpbrk first pointer is NULL", file, line); if(buffer2 == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s%s", (buffer2 == NULL) ? "" : " and ", "strpbrk second pointer is NULL", file, line); strcat(st_Buffer, "\n"); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(0); } l = strlen(buffer2)+1; __Fortify_CheckPointer(buffer1,0,strlen(buffer1)+1,file,line); __Fortify_CheckPointer(buffer2,0,l,file,line); return(strpbrk(buffer1,buffer2)); } /* * Fortify_strstr() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ char *FORTIFY_STORAGE _Fortify_strstr(char *buffer1,char *buffer2,char *file,unsigned long line) { unsigned long l; if((buffer1 == NULL) || (buffer2 == NULL)) { sprintf(st_Buffer, "\nFortify: %s.%ld\n ", file, line); if(buffer1 == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s", "strstr first pointer is NULL", file, line); if(buffer2 == NULL) sprintf(st_Buffer + strlen(st_Buffer), "%s%s", (buffer2 == NULL) ? "" : " and ", "strstr second pointer is NULL", file, line); strcat(st_Buffer, "\n"); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(0); } l = strlen(buffer2)+1; __Fortify_CheckPointer(buffer1,0,strlen(buffer1)+1,file,line); __Fortify_CheckPointer(buffer2,0,l,file,line); return(strstr(buffer1,buffer2)); } /* * Fortify_strtol() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ long FORTIFY_STORAGE _Fortify_strtol(char *buffer1,char **buffer2,int n,char *file,unsigned long line) { if(buffer1 == NULL) { sprintf(st_Buffer, "\nFortify: %s.%ld\n ", file, line); sprintf(st_Buffer + strlen(st_Buffer), "%s", "strtol first pointer is NULL", file, line); strcat(st_Buffer, "\n"); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(0); } __Fortify_CheckPointer(buffer1,0,strlen(buffer1)+1,file,line); return(strtol(buffer1,buffer2,n)); } /* * Fortify_atoi() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ int FORTIFY_STORAGE _Fortify_atoi(char *buffer1,char *file,unsigned long line) { if(buffer1 == NULL) { sprintf(st_Buffer, "\nFortify: %s.%ld\n ", file, line); sprintf(st_Buffer + strlen(st_Buffer), "%s", "atoi first pointer is NULL", file, line); strcat(st_Buffer, "\n"); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(0); } __Fortify_CheckPointer(buffer1,0,strlen(buffer1)+1,file,line); return(atoi(buffer1)); } /* * Fortify_atol() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ long FORTIFY_STORAGE _Fortify_atol(char *buffer1,char *file,unsigned long line) { if(buffer1 == NULL) { sprintf(st_Buffer, "\nFortify: %s.%ld\n ", file, line); sprintf(st_Buffer + strlen(st_Buffer), "%s", "atol first pointer is NULL", file, line); strcat(st_Buffer, "\n"); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(0); } __Fortify_CheckPointer(buffer1,0,strlen(buffer1)+1,file,line); return(atol(buffer1)); } /* * Fortify_atod() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ double FORTIFY_STORAGE _Fortify_atof(char *buffer1,char *file,unsigned long line) { if(buffer1 == NULL) { sprintf(st_Buffer, "\nFortify: %s.%ld\n ", file, line); sprintf(st_Buffer + strlen(st_Buffer), "%s", "atod first pointer is NULL", file, line); strcat(st_Buffer, "\n"); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(0); } __Fortify_CheckPointer(buffer1,0,strlen(buffer1)+1,file,line); return(atof(buffer1)); } /* * Fortify_strtoul() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ unsigned long FORTIFY_STORAGE _Fortify_strtoul(char *buffer1,char **buffer2,int n,char *file,unsigned long line) { if(buffer1 == NULL) { sprintf(st_Buffer, "\nFortify: %s.%ld\n ", file, line); sprintf(st_Buffer + strlen(st_Buffer), "%s", "strtoul first pointer is NULL", file, line); strcat(st_Buffer, "\n"); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(0); } __Fortify_CheckPointer(buffer1,0,strlen(buffer1)+1,file,line); return(strtoul(buffer1,buffer2,n)); } /* * Fortify_strtod() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ double FORTIFY_STORAGE _Fortify_strtod(char *buffer1,char **buffer2,char *file,unsigned long line) { if(buffer1 == NULL) { sprintf(st_Buffer, "\nFortify: %s.%ld\n ", file, line); sprintf(st_Buffer + strlen(st_Buffer), "%s", "strtod first pointer is NULL", file, line); strcat(st_Buffer, "\n"); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(0); } __Fortify_CheckPointer(buffer1,0,strlen(buffer1)+1,file,line); return(strtod(buffer1,buffer2)); } /* * Fortify_strset() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ char *FORTIFY_STORAGE _Fortify_strset(char *buffer,int c,char *file,unsigned long line) { if(buffer == NULL) { sprintf(st_Buffer, "\nFortify: %s.%ld\n strset pointer is NULL\n", file, line); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(NULL); } __Fortify_CheckPointer(buffer,0,strlen(buffer)+1,file,line); return(strset(buffer,c)); } /* * Fortify_strnset() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ char *FORTIFY_STORAGE _Fortify_strnset(char *buffer,int c,size_t size,char *file,unsigned long line) { if(buffer == NULL) { sprintf(st_Buffer, "\nFortify: %s.%ld\n strnset pointer is NULL\n", file, line); st_Output(st_Buffer); FORTIFY_UNLOCK(); WaitIfstdOutput(); return(NULL); } __Fortify_CheckPointer(buffer,0,strlen(buffer)+1,file,line); return(strnset(buffer,c,size)); } /* * Fortify_strncpy() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ static char *FORTIFY_STORAGE __Fortify_strncpy(char *to,char *from,size_t size,int usesize,char *file,unsigned long line) { size_t size1; size1 = strlen(from) + 1; if(usesize) { if(size < size1) size1 = size; } return((char *) _Fortify_memcpy(to,from,size1,file,line)); } /* * Fortify_strncpy() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ char *FORTIFY_STORAGE _Fortify_strncpy(char *to,char *from,size_t size,char *file,unsigned long line) { return(__Fortify_strncpy(to,from,size,1,file,line)); } /* * Fortify_strncpy() - check if from/to is in allocated space and if so, then check if start/end is not outside allocated space. */ char *FORTIFY_STORAGE _Fortify_strcpy(char *to,char *from,char *file,unsigned long line) { return(__Fortify_strncpy(to,from,0,0,file,line)); } #endif /* FORTIFY */ MSVMpack1.2/lp_solve_5.5/lp_simplex.h0000664000175000017500000000204111141374252016460 0ustar lauerlauer#ifndef HEADER_lp_simplex #define HEADER_lp_simplex #include "lp_types.h" #define ForceDualSimplexInBB /* Force use/switch of dual simplex in B&B */ #define AssumeHighAccuracyInBB /* No iteration of simplex solves at infeasibility */ /*#define UseLongStepPruning*/ /*#define UseLongStepDualPhase1*/ #define primal_UseRejectionList #define dual_UseRejectionList #define dual_RemoveBasicFixedVars /*#define dual_Phase1PriceEqualities */ /* Force elimination of equality slacks */ #define AcceptMarginalAccuracy #ifdef __cplusplus extern "C" { #endif /* Put function headers here */ STATIC int primloop(lprec *lp, MYBOOL primalfeasible, REAL primaloffset); STATIC int dualloop(lprec *lp, MYBOOL dualfeasible, int dualinfeasibles[], REAL dualoffset); STATIC int spx_run(lprec *lp, MYBOOL validInvB); STATIC int spx_solve(lprec *lp); STATIC int lag_solve(lprec *lp, REAL start_bound, int num_iter); STATIC int heuristics(lprec *lp, int mode); STATIC int lin_solve(lprec *lp); #ifdef __cplusplus } #endif #endif /* HEADER_lp_simplex */ MSVMpack1.2/lp_solve_5.5/lp_crash.c0000664000175000017500000006133311210025161016070 0ustar lauerlauer /* ---------------------------------------------------------------------------------- Crash management routines in lp_solve v5.0+ ---------------------------------------------------------------------------------- Author: Kjell Eikland Contact: kjell.eikland@broadpark.no License terms: LGPL. Requires: lp_lib.h, lp_utils.h, lp_matrix.h Release notes: v1.0.0 1 April 2004 First version. v1.1.0 20 July 2004 Reworked with flexible matrix storage model. ---------------------------------------------------------------------------------- */ #include #include "commonlib.h" #include "lp_lib.h" #include "lp_scale.h" #include "lp_utils.h" #include "lp_report.h" #include "lp_matrix.h" #include "lp_crash.h" #ifdef FORTIFY # include "lp_fortify.h" #endif MYBOOL crash_basis(lprec *lp) { int i; MATrec *mat = lp->matA; MYBOOL ok = TRUE; /* Initialize basis indicators */ if(lp->basis_valid) lp->var_basic[0] = FALSE; else default_basis(lp); /* Set initial partial pricing blocks */ if(lp->rowblocks != NULL) lp->rowblocks->blocknow = 1; if(lp->colblocks != NULL) lp->colblocks->blocknow = ((lp->crashmode == CRASH_NONE) || (lp->colblocks->blockcount == 1) ? 1 : 2); /* Construct a basis that is in some measure the "most feasible" */ if((lp->crashmode == CRASH_MOSTFEASIBLE) && mat_validate(mat)) { /* The logic here follows Maros */ LLrec *rowLL = NULL, *colLL = NULL; int ii, rx, cx, ix, nz; REAL wx, tx, *rowMAX = NULL, *colMAX = NULL; int *rowNZ = NULL, *colNZ = NULL, *rowWT = NULL, *colWT = NULL; REAL *value; int *rownr, *colnr; report(lp, NORMAL, "crash_basis: 'Most feasible' basis crashing selected\n"); /* Tally row and column non-zero counts */ ok = allocINT(lp, &rowNZ, lp->rows+1, TRUE) && allocINT(lp, &colNZ, lp->columns+1, TRUE) && allocREAL(lp, &rowMAX, lp->rows+1, FALSE) && allocREAL(lp, &colMAX, lp->columns+1, FALSE); if(!ok) goto Finish; nz = mat_nonzeros(mat); rownr = &COL_MAT_ROWNR(0); colnr = &COL_MAT_COLNR(0); value = &COL_MAT_VALUE(0); for(i = 0; i < nz; i++, rownr += matRowColStep, colnr += matRowColStep, value += matValueStep) { rx = *rownr; cx = *colnr; wx = fabs(*value); rowNZ[rx]++; colNZ[cx]++; if(i == 0) { rowMAX[rx] = wx; colMAX[cx] = wx; colMAX[0] = wx; } else { SETMAX(rowMAX[rx], wx); SETMAX(colMAX[cx], wx); SETMAX(colMAX[0], wx); } } /* Reduce counts for small magnitude to preserve stability */ rownr = &COL_MAT_ROWNR(0); colnr = &COL_MAT_COLNR(0); value = &COL_MAT_VALUE(0); for(i = 0; i < nz; i++, rownr += matRowColStep, colnr += matRowColStep, value += matValueStep) { rx = *rownr; cx = *colnr; wx = fabs(*value); #ifdef CRASH_SIMPLESCALE if(wx < CRASH_THRESHOLD * colMAX[0]) { rowNZ[rx]--; colNZ[cx]--; } #else if(wx < CRASH_THRESHOLD * rowMAX[rx]) rowNZ[rx]--; if(wx < CRASH_THRESHOLD * colMAX[cx]) colNZ[cx]--; #endif } /* Set up priority tables */ ok = allocINT(lp, &rowWT, lp->rows+1, TRUE); createLink(lp->rows, &rowLL, NULL); ok &= (rowLL != NULL); if(!ok) goto Finish; for(i = 1; i <= lp->rows; i++) { if(get_constr_type(lp, i)==EQ) ii = 3; else if(lp->upbo[i] < lp->infinite) ii = 2; else if(fabs(lp->rhs[i]) < lp->infinite) ii = 1; else ii = 0; rowWT[i] = ii; if(ii > 0) appendLink(rowLL, i); } ok = allocINT(lp, &colWT, lp->columns+1, TRUE); createLink(lp->columns, &colLL, NULL); ok &= (colLL != NULL); if(!ok) goto Finish; for(i = 1; i <= lp->columns; i++) { ix = lp->rows+i; if(is_unbounded(lp, i)) ii = 3; else if(lp->upbo[ix] >= lp->infinite) ii = 2; else if(fabs(lp->upbo[ix]-lp->lowbo[ix]) > lp->epsmachine) ii = 1; else ii = 0; colWT[i] = ii; if(ii > 0) appendLink(colLL, i); } /* Loop over all basis variables */ for(i = 1; i <= lp->rows; i++) { /* Select row */ rx = 0; wx = -lp->infinite; for(ii = firstActiveLink(rowLL); ii > 0; ii = nextActiveLink(rowLL, ii)) { tx = rowWT[ii] - CRASH_SPACER*rowNZ[ii]; if(tx > wx) { rx = ii; wx = tx; } } if(rx == 0) break; removeLink(rowLL, rx); /* Select column */ cx = 0; wx = -lp->infinite; for(ii = mat->row_end[rx-1]; ii < mat->row_end[rx]; ii++) { /* Update NZ column counts for row selected above */ tx = fabs(ROW_MAT_VALUE(ii)); ix = ROW_MAT_COLNR(ii); #ifdef CRASH_SIMPLESCALE if(tx >= CRASH_THRESHOLD * colMAX[0]) #else if(tx >= CRASH_THRESHOLD * colMAX[ix]) #endif colNZ[ix]--; if(!isActiveLink(colLL, ix) || (tx < CRASH_THRESHOLD * rowMAX[rx])) continue; /* Now do the test for best pivot */ tx = my_sign(lp->orig_obj[ix]) - my_sign(ROW_MAT_VALUE(ii)); tx = colWT[ix] + CRASH_WEIGHT*tx - CRASH_SPACER*colNZ[ix]; if(tx > wx) { cx = ix; wx = tx; } } if(cx == 0) break; removeLink(colLL, cx); /* Update row NZ counts */ ii = mat->col_end[cx-1]; rownr = &COL_MAT_ROWNR(ii); value = &COL_MAT_VALUE(ii); for(; ii < mat->col_end[cx]; ii++, rownr += matRowColStep, value += matValueStep) { wx = fabs(*value); ix = *rownr; #ifdef CRASH_SIMPLESCALE if(wx >= CRASH_THRESHOLD * colMAX[0]) #else if(wx >= CRASH_THRESHOLD * rowMAX[ix]) #endif rowNZ[ix]--; } /* Set new basis variable */ set_basisvar(lp, rx, lp->rows+cx); } /* Clean up */ Finish: FREE(rowNZ); FREE(colNZ); FREE(rowMAX); FREE(colMAX); FREE(rowWT); FREE(colWT); freeLink(&rowLL); freeLink(&colLL); } /* Construct a basis that is in some measure the "least degenerate" */ else if((lp->crashmode == CRASH_LEASTDEGENERATE) && mat_validate(mat)) { /* The logic here follows Maros */ LLrec *rowLL = NULL, *colLL = NULL; int ii, rx, cx, ix, nz, *merit = NULL; REAL *value, wx, hold, *rhs = NULL, *eta = NULL; int *rownr, *colnr; report(lp, NORMAL, "crash_basis: 'Least degenerate' basis crashing selected\n"); /* Create temporary arrays */ ok = allocINT(lp, &merit, lp->columns + 1, FALSE) && allocREAL(lp, &eta, lp->rows + 1, FALSE) && allocREAL(lp, &rhs, lp->rows + 1, FALSE); createLink(lp->columns, &colLL, NULL); createLink(lp->rows, &rowLL, NULL); ok &= (colLL != NULL) && (rowLL != NULL); if(!ok) goto FinishLD; MEMCOPY(rhs, lp->orig_rhs, lp->rows + 1); for(i = 1; i <= lp->columns; i++) appendLink(colLL, i); for(i = 1; i <= lp->rows; i++) appendLink(rowLL, i); /* Loop until we have found enough new bases */ while(colLL->count > 0) { /* Tally non-zeros matching in RHS and each active column */ nz = mat_nonzeros(mat); rownr = &COL_MAT_ROWNR(0); colnr = &COL_MAT_COLNR(0); ii = 0; MEMCLEAR(merit, lp->columns + 1); for(i = 0; i < nz; i++, rownr += matRowColStep, colnr += matRowColStep) { rx = *rownr; cx = *colnr; if(isActiveLink(colLL, cx) && (rhs[rx] != 0)) { merit[cx]++; ii++; } } if(ii == 0) break; /* Find maximal match; break ties with column length */ i = firstActiveLink(colLL); cx = i; for(i = nextActiveLink(colLL, i); i != 0; i = nextActiveLink(colLL, i)) { if(merit[i] >= merit[cx]) { if((merit[i] > merit[cx]) || (mat_collength(mat, i) > mat_collength(mat, cx))) cx = i; } } /* Determine the best pivot row */ i = mat->col_end[cx-1]; nz = mat->col_end[cx]; rownr = &COL_MAT_ROWNR(i); value = &COL_MAT_VALUE(i); rx = 0; wx = 0; MEMCLEAR(eta, lp->rows + 1); for(; i < nz; i++, rownr += matRowColStep, value += matValueStep) { ix = *rownr; hold = *value; eta[ix] = rhs[ix] / hold; hold = fabs(hold); if(isActiveLink(rowLL, ix) && (hold > wx)) { wx = hold; rx = ix; } } /* Set new basis variable */ if(rx > 0) { /* We have to update the rhs vector for the implied transformation in order to be able to find the new RHS non-zero pattern */ for(i = 1; i <= lp->rows; i++) rhs[i] -= wx * eta[i]; rhs[rx] = wx; /* Do the exchange */ set_basisvar(lp, rx, lp->rows+cx); removeLink(rowLL, rx); } removeLink(colLL, cx); } /* Clean up */ FinishLD: FREE(merit); FREE(rhs); freeLink(&rowLL); freeLink(&colLL); } return( ok ); } #if 0 MYBOOL __WINAPI guess_basis(lprec *lp, REAL *guessvector, int *basisvector) { MYBOOL status = FALSE; REAL *values = NULL, *violation = NULL, *value, error, upB, loB, sortorder = 1.0; int i, n, *rownr, *colnr; MATrec *mat = lp->matA; if(!mat_validate(lp->matA)) return( status ); /* Create helper arrays */ if(!allocREAL(lp, &values, lp->sum+1, TRUE) || !allocREAL(lp, &violation, lp->sum+1, TRUE)) goto Finish; /* Compute values of slack variables for given guess vector */ i = 0; n = get_nonzeros(lp); rownr = &COL_MAT_ROWNR(i); colnr = &COL_MAT_COLNR(i); value = &COL_MAT_VALUE(i); for(; i < n; i++, rownr += matRowColStep, colnr += matRowColStep, value += matValueStep) values[*rownr] += unscaled_mat(lp, my_chsign(is_chsign(lp, *rownr), *value), *rownr, *colnr) * guessvector[*colnr]; MEMMOVE(values+lp->rows+1, guessvector+1, lp->columns); /* Initialize constraint bound violation measures */ for(i = 1; i <= lp->rows; i++) { upB = get_rh_upper(lp, i); loB = get_rh_lower(lp, i); error = values[i] - upB; if(error > lp->epsprimal) violation[i] = sortorder*error; else { error = loB - values[i]; if(error > lp->epsprimal) violation[i] = sortorder*error; else if(is_infinite(lp, loB) && is_infinite(lp, upB)) ; else if(is_infinite(lp, upB)) violation[i] = sortorder*(loB - values[i]); else if(is_infinite(lp, loB)) violation[i] = sortorder*(values[i] - upB); else violation[i] = - sortorder*MAX(upB - values[i], values[i] - loB); } basisvector[i] = i; } /* Initialize user variable bound violation measures */ for(i = 1; i <= lp->columns; i++) { n = lp->rows+i; upB = get_upbo(lp, i); loB = get_lowbo(lp, i); error = guessvector[i] - upB; if(error > lp->epsprimal) violation[n] = sortorder*error; else { error = loB - values[n]; if(error > lp->epsprimal) violation[n] = sortorder*error; else if(is_infinite(lp, loB) && is_infinite(lp, upB)) ; else if(is_infinite(lp, upB)) violation[n] = sortorder*(loB - values[n]); else if(is_infinite(lp, loB)) violation[n] = sortorder*(values[n] - upB); else violation[n] = - sortorder*MAX(upB - values[n], values[n] - loB); } basisvector[n] = n; } /* Sort decending by violation; this means that variables with the largest violations will be designated as basic */ sortByREAL(basisvector, violation, lp->sum, 1, FALSE); /* Adjust the non-basic indeces for the (proximal) bound state */ error = lp->epsprimal; for(i = lp->rows+1, rownr = basisvector+i; i <= lp->sum; i++, rownr++) { if(*rownr <= lp->rows) { if(values[*rownr] <= get_rh_lower(lp, *rownr)+error) *rownr = -(*rownr); } else if(values[i] <= get_lowbo(lp, (*rownr)-lp->rows)+error) *rownr = -(*rownr); } /* Clean up and return status */ status = (MYBOOL) (violation[1] == 0); Finish: FREE(values); FREE(violation); return( status ); } #endif #if 0 MYBOOL __WINAPI guess_basis(lprec *lp, REAL *guessvector, int *basisvector) { MYBOOL *isnz, status = FALSE; REAL *values = NULL, *violation = NULL, eps = lp->epsprimal, *value, error, upB, loB, sortorder = 1.0; int i, j, n, *rownr, *colnr, *slkpos, nrows = lp->rows, ncols = lp->columns; MATrec *mat = lp->matA; if(!mat_validate(mat)) return( status ); /* Create helper arrays */ if(!allocREAL(lp, &values, lp->sum+1, TRUE) || !allocREAL(lp, &violation, lp->sum+1, TRUE)) goto Finish; /* Compute values of slack variables for given guess vector */ i = 0; n = get_nonzeros(lp); rownr = &COL_MAT_ROWNR(i); colnr = &COL_MAT_COLNR(i); value = &COL_MAT_VALUE(i); for(; i < n; i++, rownr += matRowColStep, colnr += matRowColStep, value += matValueStep) values[*rownr] += unscaled_mat(lp, my_chsign(is_chsign(lp, *rownr), *value), *rownr, *colnr) * guessvector[*colnr]; MEMMOVE(values+nrows+1, guessvector+1, ncols); /* Initialize constraint bound violation measures (expressed as positive values) */ for(i = 1; i <= nrows; i++) { upB = get_rh_upper(lp, i); loB = get_rh_lower(lp, i); error = values[i] - upB; if(error > eps) violation[i] = sortorder*error; else { error = loB - values[i]; if(error > eps) violation[i] = sortorder*error; else if(my_infinite(lp, loB) && my_infinite(lp, upB)) ; else if(my_infinite(lp, upB)) violation[i] = sortorder*(loB - values[i]); else if(my_infinite(lp, loB)) violation[i] = sortorder*(values[i] - upB); else violation[i] = -sortorder*MAX(upB - values[i], values[i] - loB); } basisvector[i] = i; } /* Initialize user variable bound violation measures (expressed as positive values) */ for(i = 1; i <= ncols; i++) { n = nrows+i; upB = get_upbo(lp, i); loB = get_lowbo(lp, i); error = guessvector[i] - upB; if(error > eps) violation[n] = sortorder*error; else { error = loB - values[n]; if(error > eps) violation[n] = sortorder*error; else if(my_infinite(lp, loB) && my_infinite(lp, upB)) ; else if(my_infinite(lp, upB)) violation[n] = sortorder*(loB - values[n]); else if(my_infinite(lp, loB)) violation[n] = sortorder*(values[n] - upB); else violation[n] = -sortorder*MAX(upB - values[n], values[n] - loB); } basisvector[n] = n; } /* Sort decending by violation; this means that variables with the largest violations will be designated as basic */ sortByREAL(basisvector, violation, lp->sum, 1, FALSE); error = violation[1]; /* Adjust the non-basic indeces for the (proximal) bound state */ for(i = nrows+1, rownr = basisvector+i; i <= lp->sum; i++, rownr++) { if(*rownr <= nrows) { if(values[*rownr] <= get_rh_lower(lp, *rownr)+eps) *rownr = -(*rownr); } else if(values[i] <= get_lowbo(lp, (*rownr)-nrows)+eps) *rownr = -(*rownr); } #if 1 /* Let us check for obvious row singularities and try to fix these; First assemble necessary basis statistics... */ isnz = (MYBOOL *) values; MEMCLEAR(isnz, nrows+1); slkpos = (int *) violation; MEMCLEAR(slkpos, nrows+1); for(i = 1; i <= nrows; i++) { j = abs(basisvector[i]); if(j <= nrows) { isnz[j] = TRUE; slkpos[j] = i; } else { j-= nrows; j = mat->col_end[j-1]; isnz[COL_MAT_ROWNR(j)] = TRUE; /*isnz[COL_MAT_ROWNR(j+1)] = TRUE;*/ } } for(; i <= lp->sum; i++) { j = abs(basisvector[i]); if(j <= nrows) slkpos[j] = i; } /* ...then set the corresponding slacks basic for row rank deficient positions */ for(j = 1; j <= nrows; j++) { #ifdef Paranoia if(slkpos[j] == 0) report(lp, SEVERE, "guess_basis: Internal error"); #endif if(!isnz[j]) { isnz[j] = TRUE; i = slkpos[j]; swapINT(&basisvector[i], &basisvector[j]); basisvector[j] = abs(basisvector[j]); } } #endif /* Clean up and return status */ status = (MYBOOL) (error <= eps); Finish: FREE(values); FREE(violation); return( status ); } #endif #if 0 MYBOOL __WINAPI guess_basis(lprec *lp, REAL *guessvector, int *basisvector) { MYBOOL *isnz, status = FALSE; REAL *values = NULL, *violation = NULL, eps = lp->epsprimal, *value, error, upB, loB, sortorder = 1.0; int i, j, jj, n, *rownr, *colnr, *slkpos, nrows = lp->rows, ncols = lp->columns; MATrec *mat = lp->matA; if(!mat_validate(mat)) return( status ); /* Create helper arrays */ if(!allocREAL(lp, &values, lp->sum+1, TRUE) || !allocREAL(lp, &violation, lp->sum+1, TRUE)) goto Finish; /* Compute values of slack variables for given guess vector */ i = 0; n = get_nonzeros(lp); rownr = &COL_MAT_ROWNR(i); colnr = &COL_MAT_COLNR(i); value = &COL_MAT_VALUE(i); for(; i < n; i++, rownr += matRowColStep, colnr += matRowColStep, value += matValueStep) values[*rownr] += unscaled_mat(lp, my_chsign(is_chsign(lp, *rownr), *value), *rownr, *colnr) * guessvector[*colnr]; MEMMOVE(values+nrows+1, guessvector+1, ncols); /* Initialize constraint bound violation measures (expressed as positive values) */ for(i = 1; i <= nrows; i++) { upB = get_rh_upper(lp, i); loB = get_rh_lower(lp, i); error = values[i] - upB; if(error > -eps) violation[i] = sortorder*MAX(0,error); else { error = loB - values[i]; if(error > -eps) violation[i] = sortorder*MAX(0,error); else if(my_infinite(lp, loB) && my_infinite(lp, upB)) ; else if(my_infinite(lp, upB)) violation[i] = sortorder*(loB - values[i]); else if(my_infinite(lp, loB)) violation[i] = sortorder*(values[i] - upB); else violation[i] = -sortorder*MAX(upB - values[i], values[i] - loB); } basisvector[i] = i; } /* Initialize user variable bound violation measures (expressed as positive values) */ for(i = 1; i <= ncols; i++) { n = nrows+i; upB = get_upbo(lp, i); loB = get_lowbo(lp, i); error = guessvector[i] - upB; if(error > -eps) violation[n] = sortorder*MAX(0,error); else { error = loB - values[n]; if(error > -eps) violation[n] = sortorder*MAX(0,error); else if(my_infinite(lp, loB) && my_infinite(lp, upB)) ; else if(my_infinite(lp, upB)) violation[n] = sortorder*(loB - values[n]); else if(my_infinite(lp, loB)) violation[n] = sortorder*(values[n] - upB); else violation[n] = -sortorder*MAX(upB - values[n], values[n] - loB); } basisvector[n] = n; } /* Sort decending by violation; this means that variables with the largest violations will be designated as basic */ sortByREAL(basisvector, violation, lp->sum, 1, FALSE); error = violation[1]; /* Adjust the non-basic indeces for the (proximal) bound state */ for(i = nrows+1, rownr = basisvector+i; i <= lp->sum; i++, rownr++) { if(*rownr <= nrows) { values[*rownr] -= lp->orig_rhs[*rownr]; if(values[*rownr] <= eps) *rownr = -(*rownr); } else if(values[i] <= get_lowbo(lp, (*rownr)-nrows)+eps) *rownr = -(*rownr); } /* Let us check for obvious row singularities and try to fix these; First assemble necessary basis statistics... */ isnz = (MYBOOL *) values; MEMCLEAR(isnz, nrows+1); slkpos = (int *) violation; MEMCLEAR(slkpos, nrows+1); for(i = 1; i <= nrows; i++) { j = abs(basisvector[i]); if(j <= nrows) { isnz[j] = TRUE; slkpos[j] = i; } else { j-= nrows; jj = mat->col_end[j-1]; isnz[COL_MAT_ROWNR(jj)] = TRUE; /* if(++jj < mat->col_end[j]) isnz[COL_MAT_ROWNR(jj)] = TRUE; */ } } for(; i <= lp->sum; i++) { j = abs(basisvector[i]); if(j <= nrows) slkpos[j] = i; } /* ...then set the corresponding slacks basic for row rank deficient positions */ for(j = 1; j <= nrows; j++) { #ifdef Paranoia if(slkpos[j] == 0) report(lp, SEVERE, "guess_basis: Internal error"); #endif if(!isnz[j]) { isnz[j] = TRUE; i = slkpos[j]; swapINT(&basisvector[i], &basisvector[j]); basisvector[j] = abs(basisvector[j]); } } /* Lastly normalize all basic variables to be coded as lower-bounded */ for(i = 1; i <= nrows; i++) basisvector[i] = -abs(basisvector[i]); /* Clean up and return status */ status = (MYBOOL) (error <= eps); Finish: FREE(values); FREE(violation); return( status ); } #endif MYBOOL __WINAPI guess_basis(lprec *lp, REAL *guessvector, int *basisvector) { MYBOOL *isnz = NULL, status = FALSE; REAL *values = NULL, *violation = NULL, eps = lp->epsprimal, *value, error, upB, loB, sortorder = -1.0; int i, j, jj, n, *rownr, *colnr, *slkpos = NULL, nrows = lp->rows, ncols = lp->columns, nsum = lp->sum; int *basisnr; MATrec *mat = lp->matA; if(!mat_validate(mat)) return( status ); /* Create helper arrays, providing for multiple use of the violation array */ if(!allocREAL(lp, &values, nsum+1, TRUE) || !allocREAL(lp, &violation, nsum+1, TRUE)) goto Finish; /* Compute the values of the constraints for the given guess vector */ i = 0; n = get_nonzeros(lp); rownr = &COL_MAT_ROWNR(i); colnr = &COL_MAT_COLNR(i); value = &COL_MAT_VALUE(i); for(; i < n; i++, rownr += matRowColStep, colnr += matRowColStep, value += matValueStep) values[*rownr] += unscaled_mat(lp, my_chsign(is_chsign(lp, *rownr), *value), *rownr, *colnr) * guessvector[*colnr]; MEMMOVE(values+nrows+1, guessvector+1, ncols); /* Initialize bound "violation" or primal non-degeneracy measures, expressed as the absolute value of the differences from the closest bound. */ for(i = 1; i <= nsum; i++) { if(i <= nrows) { loB = get_rh_lower(lp, i); upB = get_rh_upper(lp, i); } else { loB = get_lowbo(lp, i-nrows); upB = get_upbo(lp, i-nrows); } /* Free constraints/variables */ if(my_infinite(lp, loB) && my_infinite(lp, upB)) error = 0; /* Violated constraints/variable bounds */ else if(values[i]+eps < loB) error = loB-values[i]; else if(values[i]-eps > upB) error = values[i]-upB; /* Non-violated constraints/variables bounds */ else if(my_infinite(lp, upB)) error = MAX(0, values[i]-loB); else if(my_infinite(lp, loB)) error = MAX(0, upB-values[i]); else error = MIN(upB-values[i], values[i]-loB); /* MAX(upB-values[i], values[i]-loB); */ if(error != 0) violation[i] = sortorder*error; basisvector[i] = i; } /* Sort decending , meaning that variables with the largest "violations" will be designated basic. Effectively, we are performing a greedy type algorithm, but start at the "least interesting" end. */ sortByREAL(basisvector, violation, nsum, 1, FALSE); error = violation[1]; /* Used for setting the return value */ /* Let us check for obvious row singularities and try to fix these. Note that we reuse the memory allocated to the violation array. First assemble necessary basis statistics... */ slkpos = (int *) violation; n = nrows+1; MEMCLEAR(slkpos, n); isnz = (MYBOOL *) (slkpos+n+1); MEMCLEAR(isnz, n); for(i = 1; i <= nrows; i++) { j = abs(basisvector[i]); if(j <= nrows) { isnz[j] = TRUE; slkpos[j] = i; } else { j-= nrows; jj = mat->col_end[j-1]; jj = COL_MAT_ROWNR(jj); isnz[jj] = TRUE; } } for(; i <= nsum; i++) { j = abs(basisvector[i]); if(j <= nrows) slkpos[j] = i; } /* ...then set the corresponding slacks basic for row rank deficient positions */ for(j = 1; j <= nrows; j++) { if(slkpos[j] == 0) report(lp, SEVERE, "guess_basis: Internal error"); if(!isnz[j]) { isnz[j] = TRUE; i = slkpos[j]; swapINT(&basisvector[i], &basisvector[j]); basisvector[j] = abs(basisvector[j]); } } /* Adjust the non-basic indeces for the (proximal) bound state */ for(i = nrows+1, basisnr = basisvector+i; i <= nsum; i++, basisnr++) { n = *basisnr; if(n <= nrows) { values[n] -= get_rh_lower(lp, n); if(values[n] <= eps) *basisnr = -(*basisnr); } else if(values[n]-eps <= get_lowbo(lp, n-nrows)) *basisnr = -(*basisnr); } /* Lastly normalize all basic variables to be coded as lower-bounded, or effectively zero-based in the case of free variables. */ for(i = 1; i <= nrows; i++) basisvector[i] = -abs(basisvector[i]); /* Clean up and return status */ status = (MYBOOL) (error <= eps); Finish: FREE(values); FREE(violation); return( status ); } MSVMpack1.2/lp_solve_5.5/colamd/0000775000175000017500000000000011141443440015371 5ustar lauerlauerMSVMpack1.2/lp_solve_5.5/colamd/colamd.h0000664000175000017500000002312211141443440017001 0ustar lauerlauer/* ========================================================================== */ /* === colamd/symamd prototypes and definitions ============================= */ /* ========================================================================== */ /* You must include this file (colamd.h) in any routine that uses colamd, symamd, or the related macros and definitions. Authors: The authors of the code itself are Stefan I. Larimore and Timothy A. Davis (davis@cise.ufl.edu), University of Florida. The algorithm was developed in collaboration with John Gilbert, Xerox PARC, and Esmond Ng, Oak Ridge National Laboratory. Date: May 4, 2001. Version 2.1. Acknowledgements: This work was supported by the National Science Foundation, under grants DMS-9504974 and DMS-9803599. Notice: Copyright (c) 1998-2001 by the University of Florida. All Rights Reserved. THIS MATERIAL IS PROVIDED AS IS, WITH ABSOLUTELY NO WARRANTY EXPRESSED OR IMPLIED. ANY USE IS AT YOUR OWN RISK. Permission is hereby granted to use or copy this program for any purpose, provided the above notices are retained on all copies. User documentation of any code that uses this code must cite the Authors, the Copyright, and "Used by permission." If this code is accessible from within Matlab, then typing "help colamd" and "help symamd" must cite the Authors. Permission to modify the code and to distribute modified code is granted, provided the above notices are retained, and a notice that the code was modified is included with the above copyright notice. You must also retain the Availability information below, of the original version. This software is provided free of charge. Availability: The colamd/symamd library is available at http://www.cise.ufl.edu/research/sparse/colamd This is the http://www.cise.ufl.edu/research/sparse/colamd/colamd.h file. It is required by the colamd.c, colamdmex.c, and symamdmex.c files, and by any C code that calls the routines whose prototypes are listed below, or that uses the colamd/symamd definitions listed below. */ #ifndef COLAMD_H #define COLAMD_H /* ========================================================================== */ /* === Include files ======================================================== */ /* ========================================================================== */ #include /* ========================================================================== */ /* === Knob and statistics definitions ====================================== */ /* ========================================================================== */ /* size of the knobs [ ] array. Only knobs [0..1] are currently used. */ #define COLAMD_KNOBS 20 /* number of output statistics. Only stats [0..6] are currently used. */ #define COLAMD_STATS 20 /* knobs [0] and stats [0]: dense row knob and output statistic. */ #define COLAMD_DENSE_ROW 0 /* knobs [1] and stats [1]: dense column knob and output statistic. */ #define COLAMD_DENSE_COL 1 /* stats [2]: memory defragmentation count output statistic */ #define COLAMD_DEFRAG_COUNT 2 /* stats [3]: colamd status: zero OK, > 0 warning or notice, < 0 error */ #define COLAMD_STATUS 3 /* stats [4..6]: error info, or info on jumbled columns */ #define COLAMD_INFO1 4 #define COLAMD_INFO2 5 #define COLAMD_INFO3 6 /* error codes returned in stats [3]: */ #define COLAMD_OK (0) #define COLAMD_OK_BUT_JUMBLED (1) #define COLAMD_ERROR_A_not_present (-1) #define COLAMD_ERROR_p_not_present (-2) #define COLAMD_ERROR_nrow_negative (-3) #define COLAMD_ERROR_ncol_negative (-4) #define COLAMD_ERROR_nnz_negative (-5) #define COLAMD_ERROR_p0_nonzero (-6) #define COLAMD_ERROR_A_too_small (-7) #define COLAMD_ERROR_col_length_negative (-8) #define COLAMD_ERROR_row_index_out_of_bounds (-9) #define COLAMD_ERROR_out_of_memory (-10) #define COLAMD_ERROR_internal_error (-999) /* ========================================================================== */ /* === Row and Column structures ============================================ */ /* ========================================================================== */ /* User code that makes use of the colamd/symamd routines need not directly */ /* reference these structures. They are used only for the COLAMD_RECOMMENDED */ /* macro. */ typedef struct Colamd_Col_struct { int start ; /* index for A of first row in this column, or DEAD */ /* if column is dead */ int length ; /* number of rows in this column */ union { int thickness ; /* number of original columns represented by this */ /* col, if the column is alive */ int parent ; /* parent in parent tree super-column structure, if */ /* the column is dead */ } shared1 ; union { int score ; /* the score used to maintain heap, if col is alive */ int order ; /* pivot ordering of this column, if col is dead */ } shared2 ; union { int headhash ; /* head of a hash bucket, if col is at the head of */ /* a degree list */ int hash ; /* hash value, if col is not in a degree list */ int prev ; /* previous column in degree list, if col is in a */ /* degree list (but not at the head of a degree list) */ } shared3 ; union { int degree_next ; /* next column, if col is in a degree list */ int hash_next ; /* next column, if col is in a hash list */ } shared4 ; } Colamd_Col ; typedef struct Colamd_Row_struct { int start ; /* index for A of first col in this row */ int length ; /* number of principal columns in this row */ union { int degree ; /* number of principal & non-principal columns in row */ int p ; /* used as a row pointer in init_rows_cols () */ } shared1 ; union { int mark ; /* for computing set differences and marking dead rows*/ int first_column ;/* first column in row (used in garbage collection) */ } shared2 ; } Colamd_Row ; /* ========================================================================== */ /* === Colamd recommended memory size ======================================= */ /* ========================================================================== */ /* The recommended length Alen of the array A passed to colamd is given by the COLAMD_RECOMMENDED (nnz, n_row, n_col) macro. It returns -1 if any argument is negative. 2*nnz space is required for the row and column indices of the matrix. COLAMD_C (n_col) + COLAMD_R (n_row) space is required for the Col and Row arrays, respectively, which are internal to colamd. An additional n_col space is the minimal amount of "elbow room", and nnz/5 more space is recommended for run time efficiency. This macro is not needed when using symamd. */ #define COLAMD_C(n_col) (((n_col) + 1) * sizeof (Colamd_Col) / sizeof (int)) #define COLAMD_R(n_row) (((n_row) + 1) * sizeof (Colamd_Row) / sizeof (int)) #define COLAMD_RECOMMENDED(nnz, n_row, n_col) \ ( \ ((nnz) < 0 || (n_row) < 0 || (n_col) < 0) \ ? \ (-1) \ : \ (int) (2 * (nnz) + COLAMD_C (n_col) + COLAMD_R (n_row) + (n_col) + ((nnz) / 5)) \ ) /* ========================================================================== */ /* === Prototypes of user-callable routines ================================= */ /* ========================================================================== */ /* #ifdef __cplusplus #define __EXTERN_C extern "C" #else #define __EXTERN_C #endif */ #ifndef __BORLANDC__ #ifdef __cplusplus #define __EXTERN_C extern "C" #else #define __EXTERN_C #endif #else /* Otherwise set up for the Borland compiler */ #define __EXTERN_C extern "C" #endif #ifdef __cplusplus __EXTERN_C { #endif int colamd_recommended /* returns recommended value of Alen, */ /* or (-1) if input arguments are erroneous */ ( int nnz, /* nonzeros in A */ int n_row, /* number of rows in A */ int n_col /* number of columns in A */ ) ; void colamd_set_defaults /* sets default parameters */ ( /* knobs argument is modified on output */ double knobs [COLAMD_KNOBS] /* parameter settings for colamd */ ) ; int colamd /* returns (1) if successful, (0) otherwise*/ ( /* A and p arguments are modified on output */ int n_row, /* number of rows in A */ int n_col, /* number of columns in A */ int Alen, /* size of the array A */ int A [], /* row indices of A, of size Alen */ int p [], /* column pointers of A, of size n_col+1 */ double knobs [COLAMD_KNOBS],/* parameter settings for colamd */ int stats [COLAMD_STATS] /* colamd output statistics and error codes */ ) ; int symamd /* return (1) if OK, (0) otherwise */ ( int n, /* number of rows and columns of A */ int A [], /* row indices of A */ int p [], /* column pointers of A */ int perm [], /* output permutation, size n_col+1 */ double knobs [COLAMD_KNOBS], /* parameters (uses defaults if NULL) */ int stats [COLAMD_STATS], /* output statistics and error codes */ void * (*allocate) (size_t, size_t), /* pointer to calloc (ANSI C) or */ /* mxCalloc (for Matlab mexFunction) */ void (*release) (void *) /* pointer to free (ANSI C) or */ /* mxFree (for Matlab mexFunction) */ ) ; void colamd_report ( int stats [COLAMD_STATS] ) ; void symamd_report ( int stats [COLAMD_STATS] ) ; #endif /* COLAMD_H */ #ifdef __cplusplus } #endif MSVMpack1.2/lp_solve_5.5/colamd/colamd.c0000664000175000017500000031120111141443437017000 0ustar lauerlauer/* ========================================================================== */ /* === colamd/symamd - a sparse matrix column ordering algorithm ============ */ /* ========================================================================== */ /* colamd: an approximate minimum degree column ordering algorithm, for LU factorization of symmetric or unsymmetric matrices, QR factorization, least squares, interior point methods for linear programming problems, and other related problems. symamd: an approximate minimum degree ordering algorithm for Cholesky factorization of symmetric matrices. Purpose: Colamd computes a permutation Q such that the Cholesky factorization of (AQ)'(AQ) has less fill-in and requires fewer floating point operations than A'A. This also provides a good ordering for sparse partial pivoting methods, P(AQ) = LU, where Q is computed prior to numerical factorization, and P is computed during numerical factorization via conventional partial pivoting with row interchanges. Colamd is the column ordering method used in SuperLU, part of the ScaLAPACK library. It is also available as built-in function in Matlab Version 6, available from MathWorks, Inc. (http://www.mathworks.com). This routine can be used in place of colmmd in Matlab. By default, the \ and / operators in Matlab perform a column ordering (using colmmd or colamd) prior to LU factorization using sparse partial pivoting, in the built-in Matlab lu(A) routine. Symamd computes a permutation P of a symmetric matrix A such that the Cholesky factorization of PAP' has less fill-in and requires fewer floating point operations than A. Symamd constructs a matrix M such that M'M has the same nonzero pattern of A, and then orders the columns of M using colmmd. The column ordering of M is then returned as the row and column ordering P of A. Authors: The authors of the code itself are Stefan I. Larimore and Timothy A. Davis (davis@cise.ufl.edu), University of Florida. The algorithm was developed in collaboration with John Gilbert, Xerox PARC, and Esmond Ng, Oak Ridge National Laboratory. Date: May 4, 2001. Version 2.1. Acknowledgements: This work was supported by the National Science Foundation, under grants DMS-9504974 and DMS-9803599. Notice: Copyright (c) 1998-2001 by the University of Florida. All Rights Reserved. THIS MATERIAL IS PROVIDED AS IS, WITH ABSOLUTELY NO WARRANTY EXPRESSED OR IMPLIED. ANY USE IS AT YOUR OWN RISK. Permission is hereby granted to use or copy this program for any purpose, provided the above notices are retained on all copies. User documentation of any code that uses this code must cite the Authors, the Copyright, and "Used by permission." If this code is accessible from within Matlab, then typing "help colamd" and "help symamd" must cite the Authors. Permission to modify the code and to distribute modified code is granted, provided the above notices are retained, and a notice that the code was modified is included with the above copyright notice. You must also retain the Availability information below, of the original version. This software is provided free of charge. Availability: The colamd/symamd library is available at http://www.cise.ufl.edu/research/sparse/colamd/ This is the http://www.cise.ufl.edu/research/sparse/colamd/colamd.c file. It requires the colamd.h file. It is required by the colamdmex.c and symamdmex.c files, for the Matlab interface to colamd and symamd. Changes to the colamd library since Version 1.0 and 1.1: No bugs were found in version 1.1. These changes merely add new functionality. * added the COLAMD_RECOMMENDED (nnz, n_row, n_col) macro. * moved the output statistics, from A, to a separate output argument. The arguments changed for the C-callable routines. * added colamd_report and symamd_report. * added a C-callable symamd routine. Formerly, symamd was only available as a mexFunction from Matlab. * added error-checking to symamd. Formerly, it assumed its input was error-free. * added the optional stats and knobs arguments to the symamd mexFunction * deleted colamd_help. A help message is still available from "help colamd" and "help symamd" in Matlab. * deleted colamdtree.m and symamdtree.m. Now, colamd.m and symamd.m also do the elimination tree post-ordering. The Version 1.1 colamd and symamd mexFunctions, which do not do the post- ordering, are now visible as colamdmex and symamdmex from Matlab. Essentialy, the post-ordering is now the default behavior of colamd.m and symamd.m, to match the behavior of colmmd and symmmd. The post-ordering is only available in the Matlab interface, not the C-callable interface. * made a slight change to the dense row/column detection in symamd, to match the stated specifications. Changes from Version 2.0 to 2.1: * TRUE and FALSE are predefined on some systems, so they are defined here only if not already defined. * web site changed * UNIX Makefile modified, to handle the case if "." is not in your path. */ /* ========================================================================== */ /* === Description of user-callable routines ================================ */ /* ========================================================================== */ /* ---------------------------------------------------------------------------- colamd_recommended: ---------------------------------------------------------------------------- C syntax: #include "colamd.h" int colamd_recommended (int nnz, int n_row, int n_col) ; or as a C macro #include "colamd.h" Alen = COLAMD_RECOMMENDED (int nnz, int n_row, int n_col) ; Purpose: Returns recommended value of Alen for use by colamd. Returns -1 if any input argument is negative. The use of this routine or macro is optional. Note that the macro uses its arguments more than once, so be careful for side effects, if you pass expressions as arguments to COLAMD_RECOMMENDED. Not needed for symamd, which dynamically allocates its own memory. Arguments (all input arguments): int nnz ; Number of nonzeros in the matrix A. This must be the same value as p [n_col] in the call to colamd - otherwise you will get a wrong value of the recommended memory to use. int n_row ; Number of rows in the matrix A. int n_col ; Number of columns in the matrix A. ---------------------------------------------------------------------------- colamd_set_defaults: ---------------------------------------------------------------------------- C syntax: #include "colamd.h" colamd_set_defaults (int knobs [COLAMD_KNOBS]) ; Purpose: Sets the default parameters. The use of this routine is optional. Arguments: double knobs [COLAMD_KNOBS] ; Output only. Colamd: rows with more than (knobs [COLAMD_DENSE_ROW] * n_col) entries are removed prior to ordering. Columns with more than (knobs [COLAMD_DENSE_COL] * n_row) entries are removed prior to ordering, and placed last in the output column ordering. Symamd: uses only knobs [COLAMD_DENSE_ROW], which is knobs [0]. Rows and columns with more than (knobs [COLAMD_DENSE_ROW] * n) entries are removed prior to ordering, and placed last in the output ordering. COLAMD_DENSE_ROW and COLAMD_DENSE_COL are defined as 0 and 1, respectively, in colamd.h. Default values of these two knobs are both 0.5. Currently, only knobs [0] and knobs [1] are used, but future versions may use more knobs. If so, they will be properly set to their defaults by the future version of colamd_set_defaults, so that the code that calls colamd will not need to change, assuming that you either use colamd_set_defaults, or pass a (double *) NULL pointer as the knobs array to colamd or symamd. ---------------------------------------------------------------------------- colamd: ---------------------------------------------------------------------------- C syntax: #include "colamd.h" int colamd (int n_row, int n_col, int Alen, int *A, int *p, double knobs [COLAMD_KNOBS], int stats [COLAMD_STATS]) ; Purpose: Computes a column ordering (Q) of A such that P(AQ)=LU or (AQ)'AQ=LL' have less fill-in and require fewer floating point operations than factorizing the unpermuted matrix A or A'A, respectively. Returns: TRUE (1) if successful, FALSE (0) otherwise. Arguments: int n_row ; Input argument. Number of rows in the matrix A. Restriction: n_row >= 0. Colamd returns FALSE if n_row is negative. int n_col ; Input argument. Number of columns in the matrix A. Restriction: n_col >= 0. Colamd returns FALSE if n_col is negative. int Alen ; Input argument. Restriction (see note): Alen >= 2*nnz + 6*(n_col+1) + 4*(n_row+1) + n_col Colamd returns FALSE if these conditions are not met. Note: this restriction makes an modest assumption regarding the size of the two typedef's structures in colamd.h. We do, however, guarantee that Alen >= colamd_recommended (nnz, n_row, n_col) or equivalently as a C preprocessor macro: Alen >= COLAMD_RECOMMENDED (nnz, n_row, n_col) will be sufficient. int A [Alen] ; Input argument, undefined on output. A is an integer array of size Alen. Alen must be at least as large as the bare minimum value given above, but this is very low, and can result in excessive run time. For best performance, we recommend that Alen be greater than or equal to colamd_recommended (nnz, n_row, n_col), which adds nnz/5 to the bare minimum value given above. On input, the row indices of the entries in column c of the matrix are held in A [(p [c]) ... (p [c+1]-1)]. The row indices in a given column c need not be in ascending order, and duplicate row indices may be be present. However, colamd will work a little faster if both of these conditions are met (Colamd puts the matrix into this format, if it finds that the the conditions are not met). The matrix is 0-based. That is, rows are in the range 0 to n_row-1, and columns are in the range 0 to n_col-1. Colamd returns FALSE if any row index is out of range. The contents of A are modified during ordering, and are undefined on output. int p [n_col+1] ; Both input and output argument. p is an integer array of size n_col+1. On input, it holds the "pointers" for the column form of the matrix A. Column c of the matrix A is held in A [(p [c]) ... (p [c+1]-1)]. The first entry, p [0], must be zero, and p [c] <= p [c+1] must hold for all c in the range 0 to n_col-1. The value p [n_col] is thus the total number of entries in the pattern of the matrix A. Colamd returns FALSE if these conditions are not met. On output, if colamd returns TRUE, the array p holds the column permutation (Q, for P(AQ)=LU or (AQ)'(AQ)=LL'), where p [0] is the first column index in the new ordering, and p [n_col-1] is the last. That is, p [k] = j means that column j of A is the kth pivot column, in AQ, where k is in the range 0 to n_col-1 (p [0] = j means that column j of A is the first column in AQ). If colamd returns FALSE, then no permutation is returned, and p is undefined on output. double knobs [COLAMD_KNOBS] ; Input argument. See colamd_set_defaults for a description. int stats [COLAMD_STATS] ; Output argument. Statistics on the ordering, and error status. See colamd.h for related definitions. Colamd returns FALSE if stats is not present. stats [0]: number of dense or empty rows ignored. stats [1]: number of dense or empty columns ignored (and ordered last in the output permutation p) Note that a row can become "empty" if it contains only "dense" and/or "empty" columns, and similarly a column can become "empty" if it only contains "dense" and/or "empty" rows. stats [2]: number of garbage collections performed. This can be excessively high if Alen is close to the minimum required value. stats [3]: status code. < 0 is an error code. > 1 is a warning or notice. 0 OK. Each column of the input matrix contained row indices in increasing order, with no duplicates. 1 OK, but columns of input matrix were jumbled (unsorted columns or duplicate entries). Colamd had to do some extra work to sort the matrix first and remove duplicate entries, but it still was able to return a valid permutation (return value of colamd was TRUE). stats [4]: highest numbered column that is unsorted or has duplicate entries. stats [5]: last seen duplicate or unsorted row index. stats [6]: number of duplicate or unsorted row indices. -1 A is a null pointer -2 p is a null pointer -3 n_row is negative stats [4]: n_row -4 n_col is negative stats [4]: n_col -5 number of nonzeros in matrix is negative stats [4]: number of nonzeros, p [n_col] -6 p [0] is nonzero stats [4]: p [0] -7 A is too small stats [4]: required size stats [5]: actual size (Alen) -8 a column has a negative number of entries stats [4]: column with < 0 entries stats [5]: number of entries in col -9 a row index is out of bounds stats [4]: column with bad row index stats [5]: bad row index stats [6]: n_row, # of rows of matrx -10 (unused; see symamd.c) -999 (unused; see symamd.c) Future versions may return more statistics in the stats array. Example: See http://www.cise.ufl.edu/research/sparse/colamd/example.c for a complete example. To order the columns of a 5-by-4 matrix with 11 nonzero entries in the following nonzero pattern x 0 x 0 x 0 x x 0 x x 0 0 0 x x x x 0 0 with default knobs and no output statistics, do the following: #include "colamd.h" #define ALEN COLAMD_RECOMMENDED (11, 5, 4) int A [ALEN] = {1, 2, 5, 3, 5, 1, 2, 3, 4, 2, 4} ; int p [ ] = {0, 3, 5, 9, 11} ; int stats [COLAMD_STATS] ; colamd (5, 4, ALEN, A, p, (double *) NULL, stats) ; The permutation is returned in the array p, and A is destroyed. ---------------------------------------------------------------------------- symamd: ---------------------------------------------------------------------------- C syntax: #include "colamd.h" int symamd (int n, int *A, int *p, int *perm, int knobs [COLAMD_KNOBS], int stats [COLAMD_STATS], void (*allocate) (size_t, size_t), void (*release) (void *)) ; Purpose: The symamd routine computes an ordering P of a symmetric sparse matrix A such that the Cholesky factorization PAP' = LL' remains sparse. It is based on a column ordering of a matrix M constructed so that the nonzero pattern of M'M is the same as A. The matrix A is assumed to be symmetric; only the strictly lower triangular part is accessed. You must pass your selected memory allocator (usually calloc/free or mxCalloc/mxFree) to symamd, for it to allocate memory for the temporary matrix M. Returns: TRUE (1) if successful, FALSE (0) otherwise. Arguments: int n ; Input argument. Number of rows and columns in the symmetrix matrix A. Restriction: n >= 0. Symamd returns FALSE if n is negative. int A [nnz] ; Input argument. A is an integer array of size nnz, where nnz = p [n]. The row indices of the entries in column c of the matrix are held in A [(p [c]) ... (p [c+1]-1)]. The row indices in a given column c need not be in ascending order, and duplicate row indices may be present. However, symamd will run faster if the columns are in sorted order with no duplicate entries. The matrix is 0-based. That is, rows are in the range 0 to n-1, and columns are in the range 0 to n-1. Symamd returns FALSE if any row index is out of range. The contents of A are not modified. int p [n+1] ; Input argument. p is an integer array of size n+1. On input, it holds the "pointers" for the column form of the matrix A. Column c of the matrix A is held in A [(p [c]) ... (p [c+1]-1)]. The first entry, p [0], must be zero, and p [c] <= p [c+1] must hold for all c in the range 0 to n-1. The value p [n] is thus the total number of entries in the pattern of the matrix A. Symamd returns FALSE if these conditions are not met. The contents of p are not modified. int perm [n+1] ; Output argument. On output, if symamd returns TRUE, the array perm holds the permutation P, where perm [0] is the first index in the new ordering, and perm [n-1] is the last. That is, perm [k] = j means that row and column j of A is the kth column in PAP', where k is in the range 0 to n-1 (perm [0] = j means that row and column j of A are the first row and column in PAP'). The array is used as a workspace during the ordering, which is why it must be of length n+1, not just n. double knobs [COLAMD_KNOBS] ; Input argument. See colamd_set_defaults for a description. int stats [COLAMD_STATS] ; Output argument. Statistics on the ordering, and error status. See colamd.h for related definitions. Symamd returns FALSE if stats is not present. stats [0]: number of dense or empty row and columns ignored (and ordered last in the output permutation perm). Note that a row/column can become "empty" if it contains only "dense" and/or "empty" columns/rows. stats [1]: (same as stats [0]) stats [2]: number of garbage collections performed. stats [3]: status code. < 0 is an error code. > 1 is a warning or notice. 0 OK. Each column of the input matrix contained row indices in increasing order, with no duplicates. 1 OK, but columns of input matrix were jumbled (unsorted columns or duplicate entries). Symamd had to do some extra work to sort the matrix first and remove duplicate entries, but it still was able to return a valid permutation (return value of symamd was TRUE). stats [4]: highest numbered column that is unsorted or has duplicate entries. stats [5]: last seen duplicate or unsorted row index. stats [6]: number of duplicate or unsorted row indices. -1 A is a null pointer -2 p is a null pointer -3 (unused, see colamd.c) -4 n is negative stats [4]: n -5 number of nonzeros in matrix is negative stats [4]: # of nonzeros (p [n]). -6 p [0] is nonzero stats [4]: p [0] -7 (unused) -8 a column has a negative number of entries stats [4]: column with < 0 entries stats [5]: number of entries in col -9 a row index is out of bounds stats [4]: column with bad row index stats [5]: bad row index stats [6]: n_row, # of rows of matrx -10 out of memory (unable to allocate temporary workspace for M or count arrays using the "allocate" routine passed into symamd). -999 internal error. colamd failed to order the matrix M, when it should have succeeded. This indicates a bug. If this (and *only* this) error code occurs, please contact the authors. Don't contact the authors if you get any other error code. Future versions may return more statistics in the stats array. void * (*allocate) (size_t, size_t) A pointer to a function providing memory allocation. The allocated memory must be returned initialized to zero. For a C application, this argument should normally be a pointer to calloc. For a Matlab mexFunction, the routine mxCalloc is passed instead. void (*release) (size_t, size_t) A pointer to a function that frees memory allocated by the memory allocation routine above. For a C application, this argument should normally be a pointer to free. For a Matlab mexFunction, the routine mxFree is passed instead. ---------------------------------------------------------------------------- colamd_report: ---------------------------------------------------------------------------- C syntax: #include "colamd.h" colamd_report (int stats [COLAMD_STATS]) ; Purpose: Prints the error status and statistics recorded in the stats array on the standard error output (for a standard C routine) or on the Matlab output (for a mexFunction). Arguments: int stats [COLAMD_STATS] ; Input only. Statistics from colamd. ---------------------------------------------------------------------------- symamd_report: ---------------------------------------------------------------------------- C syntax: #include "colamd.h" symamd_report (int stats [COLAMD_STATS]) ; Purpose: Prints the error status and statistics recorded in the stats array on the standard error output (for a standard C routine) or on the Matlab output (for a mexFunction). Arguments: int stats [COLAMD_STATS] ; Input only. Statistics from symamd. */ /* ========================================================================== */ /* === Scaffolding code definitions ======================================== */ /* ========================================================================== */ /* Ensure that debugging is turned off: */ #ifndef NDEBUG #define NDEBUG #endif /* NDEBUG */ /* Our "scaffolding code" philosophy: In our opinion, well-written library code should keep its "debugging" code, and just normally have it turned off by the compiler so as not to interfere with performance. This serves several purposes: (1) assertions act as comments to the reader, telling you what the code expects at that point. All assertions will always be true (unless there really is a bug, of course). (2) leaving in the scaffolding code assists anyone who would like to modify the code, or understand the algorithm (by reading the debugging output, one can get a glimpse into what the code is doing). (3) (gasp!) for actually finding bugs. This code has been heavily tested and "should" be fully functional and bug-free ... but you never know... To enable debugging, comment out the "#define NDEBUG" above. For a Matlab mexFunction, you will also need to modify mexopts.sh to remove the -DNDEBUG definition. The code will become outrageously slow when debugging is enabled. To control the level of debugging output, set an environment variable D to 0 (little), 1 (some), 2, 3, or 4 (lots). When debugging, you should see the following message on the standard output: colamd: debug version, D = 1 (THIS WILL BE SLOW!) or a similar message for symamd. If you don't, then debugging has not been enabled. */ /* ========================================================================== */ /* === Include files ======================================================== */ /* ========================================================================== */ #include "colamd.h" #include #ifdef MATLAB_MEX_FILE #include "mex.h" #include "matrix.h" #else #include #include #endif /* MATLAB_MEX_FILE */ #ifdef FORTIFY # include "lp_fortify.h" #endif /* ========================================================================== */ /* === Definitions ========================================================== */ /* ========================================================================== */ /* Routines are either PUBLIC (user-callable) or PRIVATE (not user-callable) */ #define PUBLIC #define PRIVATE static #define MAX(a,b) (((a) > (b)) ? (a) : (b)) #define MIN(a,b) (((a) < (b)) ? (a) : (b)) #define ONES_COMPLEMENT(r) (-(r)-1) /* -------------------------------------------------------------------------- */ /* Change for version 2.1: define TRUE and FALSE only if not yet defined */ /* -------------------------------------------------------------------------- */ #ifndef TRUE #define TRUE (1) #endif #ifndef FALSE #define FALSE (0) #endif /* -------------------------------------------------------------------------- */ #define EMPTY (-1) /* Row and column status */ #define ALIVE (0) #define DEAD (-1) /* Column status */ #define DEAD_PRINCIPAL (-1) #define DEAD_NON_PRINCIPAL (-2) /* Macros for row and column status update and checking. */ #define ROW_IS_DEAD(r) ROW_IS_MARKED_DEAD (Row[r].shared2.mark) #define ROW_IS_MARKED_DEAD(row_mark) (row_mark < ALIVE) #define ROW_IS_ALIVE(r) (Row [r].shared2.mark >= ALIVE) #define COL_IS_DEAD(c) (Col [c].start < ALIVE) #define COL_IS_ALIVE(c) (Col [c].start >= ALIVE) #define COL_IS_DEAD_PRINCIPAL(c) (Col [c].start == DEAD_PRINCIPAL) #define KILL_ROW(r) { Row [r].shared2.mark = DEAD ; } #define KILL_PRINCIPAL_COL(c) { Col [c].start = DEAD_PRINCIPAL ; } #define KILL_NON_PRINCIPAL_COL(c) { Col [c].start = DEAD_NON_PRINCIPAL ; } /* ========================================================================== */ /* === Colamd reporting mechanism =========================================== */ /* ========================================================================== */ #ifdef MATLAB_MEX_FILE /* use mexPrintf in a Matlab mexFunction, for debugging and statistics output */ #define PRINTF mexPrintf /* In Matlab, matrices are 1-based to the user, but 0-based internally */ #define INDEX(i) ((i)+1) #else /* Use printf in standard C environment, for debugging and statistics output. */ /* Output is generated only if debugging is enabled at compile time, or if */ /* the caller explicitly calls colamd_report or symamd_report. */ #define PRINTF printf /* In C, matrices are 0-based and indices are reported as such in *_report */ #define INDEX(i) (i) #endif /* MATLAB_MEX_FILE */ /* ========================================================================== */ /* === Prototypes of PRIVATE routines ======================================= */ /* ========================================================================== */ PRIVATE int init_rows_cols ( int n_row, int n_col, Colamd_Row Row [], Colamd_Col Col [], int A [], int p [], int stats [COLAMD_STATS] ) ; PRIVATE void init_scoring ( int n_row, int n_col, Colamd_Row Row [], Colamd_Col Col [], int A [], int head [], double knobs [COLAMD_KNOBS], int *p_n_row2, int *p_n_col2, int *p_max_deg ) ; PRIVATE int find_ordering ( int n_row, int n_col, int Alen, Colamd_Row Row [], Colamd_Col Col [], int A [], int head [], int n_col2, int max_deg, int pfree ) ; PRIVATE void order_children ( int n_col, Colamd_Col Col [], int p [] ) ; PRIVATE void detect_super_cols ( #ifndef NDEBUG int n_col, Colamd_Row Row [], #endif /* NDEBUG */ Colamd_Col Col [], int A [], int head [], int row_start, int row_length ) ; PRIVATE int garbage_collection ( int n_row, int n_col, Colamd_Row Row [], Colamd_Col Col [], int A [], int *pfree ) ; PRIVATE int clear_mark ( int n_row, Colamd_Row Row [] ) ; PRIVATE void print_report ( char *method, int stats [COLAMD_STATS] ) ; /* ========================================================================== */ /* === Debugging prototypes and definitions ================================= */ /* ========================================================================== */ #ifndef NDEBUG /* colamd_debug is the *ONLY* global variable, and is only */ /* present when debugging */ PRIVATE int colamd_debug ; /* debug print level */ #define DEBUG0(params) { (void) PRINTF params ; } #define DEBUG1(params) { if (colamd_debug >= 1) (void) PRINTF params ; } #define DEBUG2(params) { if (colamd_debug >= 2) (void) PRINTF params ; } #define DEBUG3(params) { if (colamd_debug >= 3) (void) PRINTF params ; } #define DEBUG4(params) { if (colamd_debug >= 4) (void) PRINTF params ; } #ifdef MATLAB_MEX_FILE #define ASSERT(expression) (mxAssert ((expression), "")) #else #define ASSERT(expression) (assert (expression)) #endif /* MATLAB_MEX_FILE */ PRIVATE void colamd_get_debug /* gets the debug print level from getenv */ ( char *method ) ; PRIVATE void debug_deg_lists ( int n_row, int n_col, Colamd_Row Row [], Colamd_Col Col [], int head [], int min_score, int should, int max_deg ) ; PRIVATE void debug_mark ( int n_row, Colamd_Row Row [], int tag_mark, int max_mark ) ; PRIVATE void debug_matrix ( int n_row, int n_col, Colamd_Row Row [], Colamd_Col Col [], int A [] ) ; PRIVATE void debug_structures ( int n_row, int n_col, Colamd_Row Row [], Colamd_Col Col [], int A [], int n_col2 ) ; #else /* NDEBUG */ /* === No debugging ========================================================= */ #define DEBUG0(params) ; #define DEBUG1(params) ; #define DEBUG2(params) ; #define DEBUG3(params) ; #define DEBUG4(params) ; #define ASSERT(expression) ((void) 0) #endif /* NDEBUG */ /* ========================================================================== */ /* ========================================================================== */ /* === USER-CALLABLE ROUTINES: ============================================== */ /* ========================================================================== */ /* ========================================================================== */ /* === colamd_recommended =================================================== */ /* ========================================================================== */ /* The colamd_recommended routine returns the suggested size for Alen. This value has been determined to provide good balance between the number of garbage collections and the memory requirements for colamd. If any argument is negative, a -1 is returned as an error condition. This function is also available as a macro defined in colamd.h, so that you can use it for a statically-allocated array size. */ PUBLIC int colamd_recommended /* returns recommended value of Alen. */ ( /* === Parameters ======================================================= */ int nnz, /* number of nonzeros in A */ int n_row, /* number of rows in A */ int n_col /* number of columns in A */ ) { return (COLAMD_RECOMMENDED (nnz, n_row, n_col)) ; } /* ========================================================================== */ /* === colamd_set_defaults ================================================== */ /* ========================================================================== */ /* The colamd_set_defaults routine sets the default values of the user- controllable parameters for colamd: knobs [0] rows with knobs[0]*n_col entries or more are removed prior to ordering in colamd. Rows and columns with knobs[0]*n_col entries or more are removed prior to ordering in symamd and placed last in the output ordering. knobs [1] columns with knobs[1]*n_row entries or more are removed prior to ordering in colamd, and placed last in the column permutation. Symamd ignores this knob. knobs [2..19] unused, but future versions might use this */ PUBLIC void colamd_set_defaults ( /* === Parameters ======================================================= */ double knobs [COLAMD_KNOBS] /* knob array */ ) { /* === Local variables ================================================== */ int i ; if (!knobs) { return ; /* no knobs to initialize */ } for (i = 0 ; i < COLAMD_KNOBS ; i++) { knobs [i] = 0 ; } knobs [COLAMD_DENSE_ROW] = 0.5 ; /* ignore rows over 50% dense */ knobs [COLAMD_DENSE_COL] = 0.5 ; /* ignore columns over 50% dense */ } /* ========================================================================== */ /* === symamd =============================================================== */ /* ========================================================================== */ PUBLIC int symamd /* return TRUE if OK, FALSE otherwise */ ( /* === Parameters ======================================================= */ int n, /* number of rows and columns of A */ int A [], /* row indices of A */ int p [], /* column pointers of A */ int perm [], /* output permutation, size n+1 */ double knobs [COLAMD_KNOBS], /* parameters (uses defaults if NULL) */ int stats [COLAMD_STATS], /* output statistics and error codes */ void * (*allocate) (size_t, size_t), /* pointer to calloc (ANSI C) or */ /* mxCalloc (for Matlab mexFunction) */ void (*release) (void *) /* pointer to free (ANSI C) or */ /* mxFree (for Matlab mexFunction) */ ) { /* === Local variables ================================================== */ int *count ; /* length of each column of M, and col pointer*/ int *mark ; /* mark array for finding duplicate entries */ int *M ; /* row indices of matrix M */ int Mlen ; /* length of M */ int n_row ; /* number of rows in M */ int nnz ; /* number of entries in A */ int i ; /* row index of A */ int j ; /* column index of A */ int k ; /* row index of M */ int mnz ; /* number of nonzeros in M */ int pp ; /* index into a column of A */ int last_row ; /* last row seen in the current column */ int length ; /* number of nonzeros in a column */ double cknobs [COLAMD_KNOBS] ; /* knobs for colamd */ double default_knobs [COLAMD_KNOBS] ; /* default knobs for colamd */ int cstats [COLAMD_STATS] ; /* colamd stats */ #ifndef NDEBUG colamd_get_debug ("symamd") ; #endif /* NDEBUG */ /* === Check the input arguments ======================================== */ if (!stats) { DEBUG0 (("symamd: stats not present\n")) ; return (FALSE) ; } for (i = 0 ; i < COLAMD_STATS ; i++) { stats [i] = 0 ; } stats [COLAMD_STATUS] = COLAMD_OK ; stats [COLAMD_INFO1] = -1 ; stats [COLAMD_INFO2] = -1 ; if (!A) { stats [COLAMD_STATUS] = COLAMD_ERROR_A_not_present ; DEBUG0 (("symamd: A not present\n")) ; return (FALSE) ; } if (!p) /* p is not present */ { stats [COLAMD_STATUS] = COLAMD_ERROR_p_not_present ; DEBUG0 (("symamd: p not present\n")) ; return (FALSE) ; } if (n < 0) /* n must be >= 0 */ { stats [COLAMD_STATUS] = COLAMD_ERROR_ncol_negative ; stats [COLAMD_INFO1] = n ; DEBUG0 (("symamd: n negative %d\n", n)) ; return (FALSE) ; } nnz = p [n] ; if (nnz < 0) /* nnz must be >= 0 */ { stats [COLAMD_STATUS] = COLAMD_ERROR_nnz_negative ; stats [COLAMD_INFO1] = nnz ; DEBUG0 (("symamd: number of entries negative %d\n", nnz)) ; return (FALSE) ; } if (p [0] != 0) { stats [COLAMD_STATUS] = COLAMD_ERROR_p0_nonzero ; stats [COLAMD_INFO1] = p [0] ; DEBUG0 (("symamd: p[0] not zero %d\n", p [0])) ; return (FALSE) ; } /* === If no knobs, set default knobs =================================== */ if (!knobs) { colamd_set_defaults (default_knobs) ; knobs = default_knobs ; } /* === Allocate count and mark ========================================== */ count = (int *) ((*allocate) (n+1, sizeof (int))) ; if (!count) { stats [COLAMD_STATUS] = COLAMD_ERROR_out_of_memory ; DEBUG0 (("symamd: allocate count (size %d) failed\n", n+1)) ; return (FALSE) ; } mark = (int *) ((*allocate) (n+1, sizeof (int))) ; if (!mark) { stats [COLAMD_STATUS] = COLAMD_ERROR_out_of_memory ; (*release) ((void *) count) ; DEBUG0 (("symamd: allocate mark (size %d) failed\n", n+1)) ; return (FALSE) ; } /* === Compute column counts of M, check if A is valid ================== */ stats [COLAMD_INFO3] = 0 ; /* number of duplicate or unsorted row indices*/ for (i = 0 ; i < n ; i++) { mark [i] = -1 ; } for (j = 0 ; j < n ; j++) { last_row = -1 ; length = p [j+1] - p [j] ; if (length < 0) { /* column pointers must be non-decreasing */ stats [COLAMD_STATUS] = COLAMD_ERROR_col_length_negative ; stats [COLAMD_INFO1] = j ; stats [COLAMD_INFO2] = length ; (*release) ((void *) count) ; (*release) ((void *) mark) ; DEBUG0 (("symamd: col %d negative length %d\n", j, length)) ; return (FALSE) ; } for (pp = p [j] ; pp < p [j+1] ; pp++) { i = A [pp] ; if (i < 0 || i >= n) { /* row index i, in column j, is out of bounds */ stats [COLAMD_STATUS] = COLAMD_ERROR_row_index_out_of_bounds ; stats [COLAMD_INFO1] = j ; stats [COLAMD_INFO2] = i ; stats [COLAMD_INFO3] = n ; (*release) ((void *) count) ; (*release) ((void *) mark) ; DEBUG0 (("symamd: row %d col %d out of bounds\n", i, j)) ; return (FALSE) ; } if (i <= last_row || mark [i] == j) { /* row index is unsorted or repeated (or both), thus col */ /* is jumbled. This is a notice, not an error condition. */ stats [COLAMD_STATUS] = COLAMD_OK_BUT_JUMBLED ; stats [COLAMD_INFO1] = j ; stats [COLAMD_INFO2] = i ; (stats [COLAMD_INFO3]) ++ ; DEBUG1 (("symamd: row %d col %d unsorted/duplicate\n", i, j)) ; } if (i > j && mark [i] != j) { /* row k of M will contain column indices i and j */ count [i]++ ; count [j]++ ; } /* mark the row as having been seen in this column */ mark [i] = j ; last_row = i ; } } if (stats [COLAMD_STATUS] == COLAMD_OK) { /* if there are no duplicate entries, then mark is no longer needed */ (*release) ((void *) mark) ; } /* === Compute column pointers of M ===================================== */ /* use output permutation, perm, for column pointers of M */ perm [0] = 0 ; for (j = 1 ; j <= n ; j++) { perm [j] = perm [j-1] + count [j-1] ; } for (j = 0 ; j < n ; j++) { count [j] = perm [j] ; } /* === Construct M ====================================================== */ mnz = perm [n] ; n_row = mnz / 2 ; Mlen = colamd_recommended (mnz, n_row, n) ; M = (int *) ((*allocate) (Mlen, sizeof (int))) ; DEBUG0 (("symamd: M is %d-by-%d with %d entries, Mlen = %d\n", n_row, n, mnz, Mlen)) ; if (!M) { stats [COLAMD_STATUS] = COLAMD_ERROR_out_of_memory ; (*release) ((void *) count) ; (*release) ((void *) mark) ; DEBUG0 (("symamd: allocate M (size %d) failed\n", Mlen)) ; return (FALSE) ; } k = 0 ; if (stats [COLAMD_STATUS] == COLAMD_OK) { /* Matrix is OK */ for (j = 0 ; j < n ; j++) { ASSERT (p [j+1] - p [j] >= 0) ; for (pp = p [j] ; pp < p [j+1] ; pp++) { i = A [pp] ; ASSERT (i >= 0 && i < n) ; if (i > j) { /* row k of M contains column indices i and j */ M [count [i]++] = k ; M [count [j]++] = k ; k++ ; } } } } else { /* Matrix is jumbled. Do not add duplicates to M. Unsorted cols OK. */ DEBUG0 (("symamd: Duplicates in A.\n")) ; for (i = 0 ; i < n ; i++) { mark [i] = -1 ; } for (j = 0 ; j < n ; j++) { ASSERT (p [j+1] - p [j] >= 0) ; for (pp = p [j] ; pp < p [j+1] ; pp++) { i = A [pp] ; ASSERT (i >= 0 && i < n) ; if (i > j && mark [i] != j) { /* row k of M contains column indices i and j */ M [count [i]++] = k ; M [count [j]++] = k ; k++ ; mark [i] = j ; } } } (*release) ((void *) mark) ; } /* count and mark no longer needed */ (*release) ((void *) count) ; ASSERT (k == n_row) ; /* === Adjust the knobs for M =========================================== */ for (i = 0 ; i < COLAMD_KNOBS ; i++) { cknobs [i] = knobs [i] ; } /* there are no dense rows in M */ cknobs [COLAMD_DENSE_ROW] = 1.0 ; if (n_row != 0 && n < n_row) { /* On input, the knob is a fraction of 1..n, the number of rows of A. */ /* Convert it to a fraction of 1..n_row, of the number of rows of M. */ cknobs [COLAMD_DENSE_COL] = (knobs [COLAMD_DENSE_ROW] * n) / n_row ; } else { /* no dense columns in M */ cknobs [COLAMD_DENSE_COL] = 1.0 ; } DEBUG0 (("symamd: dense col knob for M: %g\n", cknobs [COLAMD_DENSE_COL])) ; /* === Order the columns of M =========================================== */ if (!colamd (n_row, n, Mlen, M, perm, cknobs, cstats)) { /* This "cannot" happen, unless there is a bug in the code. */ stats [COLAMD_STATUS] = COLAMD_ERROR_internal_error ; (*release) ((void *) M) ; DEBUG0 (("symamd: internal error!\n")) ; return (FALSE) ; } /* Note that the output permutation is now in perm */ /* === get the statistics for symamd from colamd ======================== */ /* note that a dense column in colamd means a dense row and col in symamd */ stats [COLAMD_DENSE_ROW] = cstats [COLAMD_DENSE_COL] ; stats [COLAMD_DENSE_COL] = cstats [COLAMD_DENSE_COL] ; stats [COLAMD_DEFRAG_COUNT] = cstats [COLAMD_DEFRAG_COUNT] ; /* === Free M =========================================================== */ (*release) ((void *) M) ; DEBUG0 (("symamd: done.\n")) ; return (TRUE) ; } /* ========================================================================== */ /* === colamd =============================================================== */ /* ========================================================================== */ /* The colamd routine computes a column ordering Q of a sparse matrix A such that the LU factorization P(AQ) = LU remains sparse, where P is selected via partial pivoting. The routine can also be viewed as providing a permutation Q such that the Cholesky factorization (AQ)'(AQ) = LL' remains sparse. */ PUBLIC int colamd /* returns TRUE if successful, FALSE otherwise*/ ( /* === Parameters ======================================================= */ int n_row, /* number of rows in A */ int n_col, /* number of columns in A */ int Alen, /* length of A */ int A [], /* row indices of A */ int p [], /* pointers to columns in A */ double knobs [COLAMD_KNOBS],/* parameters (uses defaults if NULL) */ int stats [COLAMD_STATS] /* output statistics and error codes */ ) { /* === Local variables ================================================== */ int i ; /* loop index */ int nnz ; /* nonzeros in A */ int Row_size ; /* size of Row [], in integers */ int Col_size ; /* size of Col [], in integers */ int need ; /* minimum required length of A */ Colamd_Row *Row ; /* pointer into A of Row [0..n_row] array */ Colamd_Col *Col ; /* pointer into A of Col [0..n_col] array */ int n_col2 ; /* number of non-dense, non-empty columns */ int n_row2 ; /* number of non-dense, non-empty rows */ int ngarbage ; /* number of garbage collections performed */ int max_deg ; /* maximum row degree */ double default_knobs [COLAMD_KNOBS] ; /* default knobs array */ #ifndef NDEBUG colamd_get_debug ("colamd") ; #endif /* NDEBUG */ /* === Check the input arguments ======================================== */ if (!stats) { DEBUG0 (("colamd: stats not present\n")) ; return (FALSE) ; } for (i = 0 ; i < COLAMD_STATS ; i++) { stats [i] = 0 ; } stats [COLAMD_STATUS] = COLAMD_OK ; stats [COLAMD_INFO1] = -1 ; stats [COLAMD_INFO2] = -1 ; if (!A) /* A is not present */ { stats [COLAMD_STATUS] = COLAMD_ERROR_A_not_present ; DEBUG0 (("colamd: A not present\n")) ; return (FALSE) ; } if (!p) /* p is not present */ { stats [COLAMD_STATUS] = COLAMD_ERROR_p_not_present ; DEBUG0 (("colamd: p not present\n")) ; return (FALSE) ; } if (n_row < 0) /* n_row must be >= 0 */ { stats [COLAMD_STATUS] = COLAMD_ERROR_nrow_negative ; stats [COLAMD_INFO1] = n_row ; DEBUG0 (("colamd: nrow negative %d\n", n_row)) ; return (FALSE) ; } if (n_col < 0) /* n_col must be >= 0 */ { stats [COLAMD_STATUS] = COLAMD_ERROR_ncol_negative ; stats [COLAMD_INFO1] = n_col ; DEBUG0 (("colamd: ncol negative %d\n", n_col)) ; return (FALSE) ; } nnz = p [n_col] ; if (nnz < 0) /* nnz must be >= 0 */ { stats [COLAMD_STATUS] = COLAMD_ERROR_nnz_negative ; stats [COLAMD_INFO1] = nnz ; DEBUG0 (("colamd: number of entries negative %d\n", nnz)) ; return (FALSE) ; } if (p [0] != 0) { stats [COLAMD_STATUS] = COLAMD_ERROR_p0_nonzero ; stats [COLAMD_INFO1] = p [0] ; DEBUG0 (("colamd: p[0] not zero %d\n", p [0])) ; return (FALSE) ; } /* === If no knobs, set default knobs =================================== */ if (!knobs) { colamd_set_defaults (default_knobs) ; knobs = default_knobs ; } /* === Allocate the Row and Col arrays from array A ===================== */ Col_size = COLAMD_C (n_col) ; Row_size = COLAMD_R (n_row) ; need = 2*nnz + n_col + Col_size + Row_size ; if (need > Alen) { /* not enough space in array A to perform the ordering */ stats [COLAMD_STATUS] = COLAMD_ERROR_A_too_small ; stats [COLAMD_INFO1] = need ; stats [COLAMD_INFO2] = Alen ; DEBUG0 (("colamd: Need Alen >= %d, given only Alen = %d\n", need,Alen)); return (FALSE) ; } Alen -= Col_size + Row_size ; Col = (Colamd_Col *) &A [Alen] ; Row = (Colamd_Row *) &A [Alen + Col_size] ; /* === Construct the row and column data structures ===================== */ if (!init_rows_cols (n_row, n_col, Row, Col, A, p, stats)) { /* input matrix is invalid */ DEBUG0 (("colamd: Matrix invalid\n")) ; return (FALSE) ; } /* === Initialize scores, kill dense rows/columns ======================= */ init_scoring (n_row, n_col, Row, Col, A, p, knobs, &n_row2, &n_col2, &max_deg) ; /* === Order the supercolumns =========================================== */ ngarbage = find_ordering (n_row, n_col, Alen, Row, Col, A, p, n_col2, max_deg, 2*nnz) ; /* === Order the non-principal columns ================================== */ order_children (n_col, Col, p) ; /* === Return statistics in stats ======================================= */ stats [COLAMD_DENSE_ROW] = n_row - n_row2 ; stats [COLAMD_DENSE_COL] = n_col - n_col2 ; stats [COLAMD_DEFRAG_COUNT] = ngarbage ; DEBUG0 (("colamd: done.\n")) ; return (TRUE) ; } /* ========================================================================== */ /* === colamd_report ======================================================== */ /* ========================================================================== */ PUBLIC void colamd_report ( int stats [COLAMD_STATS] ) { print_report ("colamd", stats) ; } /* ========================================================================== */ /* === symamd_report ======================================================== */ /* ========================================================================== */ PUBLIC void symamd_report ( int stats [COLAMD_STATS] ) { print_report ("symamd", stats) ; } /* ========================================================================== */ /* === NON-USER-CALLABLE ROUTINES: ========================================== */ /* ========================================================================== */ /* There are no user-callable routines beyond this point in the file */ /* ========================================================================== */ /* === init_rows_cols ======================================================= */ /* ========================================================================== */ /* Takes the column form of the matrix in A and creates the row form of the matrix. Also, row and column attributes are stored in the Col and Row structs. If the columns are un-sorted or contain duplicate row indices, this routine will also sort and remove duplicate row indices from the column form of the matrix. Returns FALSE if the matrix is invalid, TRUE otherwise. Not user-callable. */ PRIVATE int init_rows_cols /* returns TRUE if OK, or FALSE otherwise */ ( /* === Parameters ======================================================= */ int n_row, /* number of rows of A */ int n_col, /* number of columns of A */ Colamd_Row Row [], /* of size n_row+1 */ Colamd_Col Col [], /* of size n_col+1 */ int A [], /* row indices of A, of size Alen */ int p [], /* pointers to columns in A, of size n_col+1 */ int stats [COLAMD_STATS] /* colamd statistics */ ) { /* === Local variables ================================================== */ int col ; /* a column index */ int row ; /* a row index */ int *cp ; /* a column pointer */ int *cp_end ; /* a pointer to the end of a column */ int *rp ; /* a row pointer */ int *rp_end ; /* a pointer to the end of a row */ int last_row ; /* previous row */ /* === Initialize columns, and check column pointers ==================== */ for (col = 0 ; col < n_col ; col++) { Col [col].start = p [col] ; Col [col].length = p [col+1] - p [col] ; if (Col [col].length < 0) { /* column pointers must be non-decreasing */ stats [COLAMD_STATUS] = COLAMD_ERROR_col_length_negative ; stats [COLAMD_INFO1] = col ; stats [COLAMD_INFO2] = Col [col].length ; DEBUG0 (("colamd: col %d length %d < 0\n", col, Col [col].length)) ; return (FALSE) ; } Col [col].shared1.thickness = 1 ; Col [col].shared2.score = 0 ; Col [col].shared3.prev = EMPTY ; Col [col].shared4.degree_next = EMPTY ; } /* p [0..n_col] no longer needed, used as "head" in subsequent routines */ /* === Scan columns, compute row degrees, and check row indices ========= */ stats [COLAMD_INFO3] = 0 ; /* number of duplicate or unsorted row indices*/ for (row = 0 ; row < n_row ; row++) { Row [row].length = 0 ; Row [row].shared2.mark = -1 ; } for (col = 0 ; col < n_col ; col++) { last_row = -1 ; cp = &A [p [col]] ; cp_end = &A [p [col+1]] ; while (cp < cp_end) { row = *cp++ ; /* make sure row indices within range */ if (row < 0 || row >= n_row) { stats [COLAMD_STATUS] = COLAMD_ERROR_row_index_out_of_bounds ; stats [COLAMD_INFO1] = col ; stats [COLAMD_INFO2] = row ; stats [COLAMD_INFO3] = n_row ; DEBUG0 (("colamd: row %d col %d out of bounds\n", row, col)) ; return (FALSE) ; } if (row <= last_row || Row [row].shared2.mark == col) { /* row index are unsorted or repeated (or both), thus col */ /* is jumbled. This is a notice, not an error condition. */ stats [COLAMD_STATUS] = COLAMD_OK_BUT_JUMBLED ; stats [COLAMD_INFO1] = col ; stats [COLAMD_INFO2] = row ; (stats [COLAMD_INFO3]) ++ ; DEBUG1 (("colamd: row %d col %d unsorted/duplicate\n",row,col)); } if (Row [row].shared2.mark != col) { Row [row].length++ ; } else { /* this is a repeated entry in the column, */ /* it will be removed */ Col [col].length-- ; } /* mark the row as having been seen in this column */ Row [row].shared2.mark = col ; last_row = row ; } } /* === Compute row pointers ============================================= */ /* row form of the matrix starts directly after the column */ /* form of matrix in A */ Row [0].start = p [n_col] ; Row [0].shared1.p = Row [0].start ; Row [0].shared2.mark = -1 ; for (row = 1 ; row < n_row ; row++) { Row [row].start = Row [row-1].start + Row [row-1].length ; Row [row].shared1.p = Row [row].start ; Row [row].shared2.mark = -1 ; } /* === Create row form ================================================== */ if (stats [COLAMD_STATUS] == COLAMD_OK_BUT_JUMBLED) { /* if cols jumbled, watch for repeated row indices */ for (col = 0 ; col < n_col ; col++) { cp = &A [p [col]] ; cp_end = &A [p [col+1]] ; while (cp < cp_end) { row = *cp++ ; if (Row [row].shared2.mark != col) { A [(Row [row].shared1.p)++] = col ; Row [row].shared2.mark = col ; } } } } else { /* if cols not jumbled, we don't need the mark (this is faster) */ for (col = 0 ; col < n_col ; col++) { cp = &A [p [col]] ; cp_end = &A [p [col+1]] ; while (cp < cp_end) { A [(Row [*cp++].shared1.p)++] = col ; } } } /* === Clear the row marks and set row degrees ========================== */ for (row = 0 ; row < n_row ; row++) { Row [row].shared2.mark = 0 ; Row [row].shared1.degree = Row [row].length ; } /* === See if we need to re-create columns ============================== */ if (stats [COLAMD_STATUS] == COLAMD_OK_BUT_JUMBLED) { DEBUG0 (("colamd: reconstructing column form, matrix jumbled\n")) ; #ifndef NDEBUG /* make sure column lengths are correct */ for (col = 0 ; col < n_col ; col++) { p [col] = Col [col].length ; } for (row = 0 ; row < n_row ; row++) { rp = &A [Row [row].start] ; rp_end = rp + Row [row].length ; while (rp < rp_end) { p [*rp++]-- ; } } for (col = 0 ; col < n_col ; col++) { ASSERT (p [col] == 0) ; } /* now p is all zero (different than when debugging is turned off) */ #endif /* NDEBUG */ /* === Compute col pointers ========================================= */ /* col form of the matrix starts at A [0]. */ /* Note, we may have a gap between the col form and the row */ /* form if there were duplicate entries, if so, it will be */ /* removed upon the first garbage collection */ Col [0].start = 0 ; p [0] = Col [0].start ; for (col = 1 ; col < n_col ; col++) { /* note that the lengths here are for pruned columns, i.e. */ /* no duplicate row indices will exist for these columns */ Col [col].start = Col [col-1].start + Col [col-1].length ; p [col] = Col [col].start ; } /* === Re-create col form =========================================== */ for (row = 0 ; row < n_row ; row++) { rp = &A [Row [row].start] ; rp_end = rp + Row [row].length ; while (rp < rp_end) { A [(p [*rp++])++] = row ; } } } /* === Done. Matrix is not (or no longer) jumbled ====================== */ return (TRUE) ; } /* ========================================================================== */ /* === init_scoring ========================================================= */ /* ========================================================================== */ /* Kills dense or empty columns and rows, calculates an initial score for each column, and places all columns in the degree lists. Not user-callable. */ PRIVATE void init_scoring ( /* === Parameters ======================================================= */ int n_row, /* number of rows of A */ int n_col, /* number of columns of A */ Colamd_Row Row [], /* of size n_row+1 */ Colamd_Col Col [], /* of size n_col+1 */ int A [], /* column form and row form of A */ int head [], /* of size n_col+1 */ double knobs [COLAMD_KNOBS],/* parameters */ int *p_n_row2, /* number of non-dense, non-empty rows */ int *p_n_col2, /* number of non-dense, non-empty columns */ int *p_max_deg /* maximum row degree */ ) { /* === Local variables ================================================== */ int c ; /* a column index */ int r, row ; /* a row index */ int *cp ; /* a column pointer */ int deg ; /* degree of a row or column */ int *cp_end ; /* a pointer to the end of a column */ int *new_cp ; /* new column pointer */ int col_length ; /* length of pruned column */ int score ; /* current column score */ int n_col2 ; /* number of non-dense, non-empty columns */ int n_row2 ; /* number of non-dense, non-empty rows */ int dense_row_count ; /* remove rows with more entries than this */ int dense_col_count ; /* remove cols with more entries than this */ int min_score ; /* smallest column score */ int max_deg ; /* maximum row degree */ int next_col ; /* Used to add to degree list.*/ #ifndef NDEBUG int debug_count ; /* debug only. */ #endif /* NDEBUG */ /* === Extract knobs ==================================================== */ dense_row_count = (int) MAX (0, MIN (knobs [COLAMD_DENSE_ROW] * n_col, n_col)) ; dense_col_count = (int) MAX (0, MIN (knobs [COLAMD_DENSE_COL] * n_row, n_row)) ; DEBUG1 (("colamd: densecount: %d %d\n", dense_row_count, dense_col_count)) ; max_deg = 0 ; n_col2 = n_col ; n_row2 = n_row ; /* === Kill empty columns =============================================== */ /* Put the empty columns at the end in their natural order, so that LU */ /* factorization can proceed as far as possible. */ for (c = n_col-1 ; c >= 0 ; c--) { deg = Col [c].length ; if (deg == 0) { /* this is a empty column, kill and order it last */ Col [c].shared2.order = --n_col2 ; KILL_PRINCIPAL_COL (c) ; } } DEBUG1 (("colamd: null columns killed: %d\n", n_col - n_col2)) ; /* === Kill dense columns =============================================== */ /* Put the dense columns at the end, in their natural order */ for (c = n_col-1 ; c >= 0 ; c--) { /* skip any dead columns */ if (COL_IS_DEAD (c)) { continue ; } deg = Col [c].length ; if (deg > dense_col_count) { /* this is a dense column, kill and order it last */ Col [c].shared2.order = --n_col2 ; /* decrement the row degrees */ cp = &A [Col [c].start] ; cp_end = cp + Col [c].length ; while (cp < cp_end) { Row [*cp++].shared1.degree-- ; } KILL_PRINCIPAL_COL (c) ; } } DEBUG1 (("colamd: Dense and null columns killed: %d\n", n_col - n_col2)) ; /* === Kill dense and empty rows ======================================== */ for (r = 0 ; r < n_row ; r++) { deg = Row [r].shared1.degree ; ASSERT (deg >= 0 && deg <= n_col) ; if (deg > dense_row_count || deg == 0) { /* kill a dense or empty row */ KILL_ROW (r) ; --n_row2 ; } else { /* keep track of max degree of remaining rows */ max_deg = MAX (max_deg, deg) ; } } DEBUG1 (("colamd: Dense and null rows killed: %d\n", n_row - n_row2)) ; /* === Compute initial column scores ==================================== */ /* At this point the row degrees are accurate. They reflect the number */ /* of "live" (non-dense) columns in each row. No empty rows exist. */ /* Some "live" columns may contain only dead rows, however. These are */ /* pruned in the code below. */ /* now find the initial matlab score for each column */ for (c = n_col-1 ; c >= 0 ; c--) { /* skip dead column */ if (COL_IS_DEAD (c)) { continue ; } score = 0 ; cp = &A [Col [c].start] ; new_cp = cp ; cp_end = cp + Col [c].length ; while (cp < cp_end) { /* get a row */ row = *cp++ ; /* skip if dead */ if (ROW_IS_DEAD (row)) { continue ; } /* compact the column */ *new_cp++ = row ; /* add row's external degree */ score += Row [row].shared1.degree - 1 ; /* guard against integer overflow */ score = MIN (score, n_col) ; } /* determine pruned column length */ col_length = (int) (new_cp - &A [Col [c].start]) ; if (col_length == 0) { /* a newly-made null column (all rows in this col are "dense" */ /* and have already been killed) */ DEBUG2 (("Newly null killed: %d\n", c)) ; Col [c].shared2.order = --n_col2 ; KILL_PRINCIPAL_COL (c) ; } else { /* set column length and set score */ ASSERT (score >= 0) ; ASSERT (score <= n_col) ; Col [c].length = col_length ; Col [c].shared2.score = score ; } } DEBUG1 (("colamd: Dense, null, and newly-null columns killed: %d\n", n_col-n_col2)) ; /* At this point, all empty rows and columns are dead. All live columns */ /* are "clean" (containing no dead rows) and simplicial (no supercolumns */ /* yet). Rows may contain dead columns, but all live rows contain at */ /* least one live column. */ #ifndef NDEBUG debug_structures (n_row, n_col, Row, Col, A, n_col2) ; #endif /* NDEBUG */ /* === Initialize degree lists ========================================== */ #ifndef NDEBUG debug_count = 0 ; #endif /* NDEBUG */ /* clear the hash buckets */ for (c = 0 ; c <= n_col ; c++) { head [c] = EMPTY ; } min_score = n_col ; /* place in reverse order, so low column indices are at the front */ /* of the lists. This is to encourage natural tie-breaking */ for (c = n_col-1 ; c >= 0 ; c--) { /* only add principal columns to degree lists */ if (COL_IS_ALIVE (c)) { DEBUG4 (("place %d score %d minscore %d ncol %d\n", c, Col [c].shared2.score, min_score, n_col)) ; /* === Add columns score to DList =============================== */ score = Col [c].shared2.score ; ASSERT (min_score >= 0) ; ASSERT (min_score <= n_col) ; ASSERT (score >= 0) ; ASSERT (score <= n_col) ; ASSERT (head [score] >= EMPTY) ; /* now add this column to dList at proper score location */ next_col = head [score] ; Col [c].shared3.prev = EMPTY ; Col [c].shared4.degree_next = next_col ; /* if there already was a column with the same score, set its */ /* previous pointer to this new column */ if (next_col != EMPTY) { Col [next_col].shared3.prev = c ; } head [score] = c ; /* see if this score is less than current min */ min_score = MIN (min_score, score) ; #ifndef NDEBUG debug_count++ ; #endif /* NDEBUG */ } } #ifndef NDEBUG DEBUG1 (("colamd: Live cols %d out of %d, non-princ: %d\n", debug_count, n_col, n_col-debug_count)) ; ASSERT (debug_count == n_col2) ; debug_deg_lists (n_row, n_col, Row, Col, head, min_score, n_col2, max_deg) ; #endif /* NDEBUG */ /* === Return number of remaining columns, and max row degree =========== */ *p_n_col2 = n_col2 ; *p_n_row2 = n_row2 ; *p_max_deg = max_deg ; } /* ========================================================================== */ /* === find_ordering ======================================================== */ /* ========================================================================== */ /* Order the principal columns of the supercolumn form of the matrix (no supercolumns on input). Uses a minimum approximate column minimum degree ordering method. Not user-callable. */ PRIVATE int find_ordering /* return the number of garbage collections */ ( /* === Parameters ======================================================= */ int n_row, /* number of rows of A */ int n_col, /* number of columns of A */ int Alen, /* size of A, 2*nnz + n_col or larger */ Colamd_Row Row [], /* of size n_row+1 */ Colamd_Col Col [], /* of size n_col+1 */ int A [], /* column form and row form of A */ int head [], /* of size n_col+1 */ int n_col2, /* Remaining columns to order */ int max_deg, /* Maximum row degree */ int pfree /* index of first free slot (2*nnz on entry) */ ) { /* === Local variables ================================================== */ int k ; /* current pivot ordering step */ int pivot_col ; /* current pivot column */ int *cp ; /* a column pointer */ int *rp ; /* a row pointer */ int pivot_row ; /* current pivot row */ int *new_cp ; /* modified column pointer */ int *new_rp ; /* modified row pointer */ int pivot_row_start ; /* pointer to start of pivot row */ int pivot_row_degree ; /* number of columns in pivot row */ int pivot_row_length ; /* number of supercolumns in pivot row */ int pivot_col_score ; /* score of pivot column */ int needed_memory ; /* free space needed for pivot row */ int *cp_end ; /* pointer to the end of a column */ int *rp_end ; /* pointer to the end of a row */ int row ; /* a row index */ int col ; /* a column index */ int max_score ; /* maximum possible score */ int cur_score ; /* score of current column */ unsigned int hash ; /* hash value for supernode detection */ int head_column ; /* head of hash bucket */ int first_col ; /* first column in hash bucket */ int tag_mark ; /* marker value for mark array */ int row_mark ; /* Row [row].shared2.mark */ int set_difference ; /* set difference size of row with pivot row */ int min_score ; /* smallest column score */ int col_thickness ; /* "thickness" (no. of columns in a supercol) */ int max_mark ; /* maximum value of tag_mark */ int pivot_col_thickness ; /* number of columns represented by pivot col */ int prev_col ; /* Used by Dlist operations. */ int next_col ; /* Used by Dlist operations. */ int ngarbage ; /* number of garbage collections performed */ #ifndef NDEBUG int debug_d ; /* debug loop counter */ int debug_step = 0 ; /* debug loop counter */ #endif /* NDEBUG */ /* === Initialization and clear mark ==================================== */ max_mark = INT_MAX - n_col ; /* INT_MAX defined in */ tag_mark = clear_mark (n_row, Row) ; min_score = 0 ; ngarbage = 0 ; DEBUG1 (("colamd: Ordering, n_col2=%d\n", n_col2)) ; /* === Order the columns ================================================ */ for (k = 0 ; k < n_col2 ; /* 'k' is incremented below */) { #ifndef NDEBUG if (debug_step % 100 == 0) { DEBUG2 (("\n... Step k: %d out of n_col2: %d\n", k, n_col2)) ; } else { DEBUG3 (("\n----------Step k: %d out of n_col2: %d\n", k, n_col2)) ; } debug_step++ ; debug_deg_lists (n_row, n_col, Row, Col, head, min_score, n_col2-k, max_deg) ; debug_matrix (n_row, n_col, Row, Col, A) ; #endif /* NDEBUG */ /* === Select pivot column, and order it ============================ */ /* make sure degree list isn't empty */ ASSERT (min_score >= 0) ; ASSERT (min_score <= n_col) ; ASSERT (head [min_score] >= EMPTY) ; #ifndef NDEBUG for (debug_d = 0 ; debug_d < min_score ; debug_d++) { ASSERT (head [debug_d] == EMPTY) ; } #endif /* NDEBUG */ /* get pivot column from head of minimum degree list */ while (head [min_score] == EMPTY && min_score < n_col) { min_score++ ; } pivot_col = head [min_score] ; ASSERT (pivot_col >= 0 && pivot_col <= n_col) ; next_col = Col [pivot_col].shared4.degree_next ; head [min_score] = next_col ; if (next_col != EMPTY) { Col [next_col].shared3.prev = EMPTY ; } ASSERT (COL_IS_ALIVE (pivot_col)) ; DEBUG3 (("Pivot col: %d\n", pivot_col)) ; /* remember score for defrag check */ pivot_col_score = Col [pivot_col].shared2.score ; /* the pivot column is the kth column in the pivot order */ Col [pivot_col].shared2.order = k ; /* increment order count by column thickness */ pivot_col_thickness = Col [pivot_col].shared1.thickness ; k += pivot_col_thickness ; ASSERT (pivot_col_thickness > 0) ; /* === Garbage_collection, if necessary ============================= */ needed_memory = MIN (pivot_col_score, n_col - k) ; if (pfree + needed_memory >= Alen) { pfree = garbage_collection (n_row, n_col, Row, Col, A, &A [pfree]) ; ngarbage++ ; /* after garbage collection we will have enough */ ASSERT (pfree + needed_memory < Alen) ; /* garbage collection has wiped out the Row[].shared2.mark array */ tag_mark = clear_mark (n_row, Row) ; #ifndef NDEBUG debug_matrix (n_row, n_col, Row, Col, A) ; #endif /* NDEBUG */ } /* === Compute pivot row pattern ==================================== */ /* get starting location for this new merged row */ pivot_row_start = pfree ; /* initialize new row counts to zero */ pivot_row_degree = 0 ; /* tag pivot column as having been visited so it isn't included */ /* in merged pivot row */ Col [pivot_col].shared1.thickness = -pivot_col_thickness ; /* pivot row is the union of all rows in the pivot column pattern */ cp = &A [Col [pivot_col].start] ; cp_end = cp + Col [pivot_col].length ; while (cp < cp_end) { /* get a row */ row = *cp++ ; DEBUG4 (("Pivot col pattern %d %d\n", ROW_IS_ALIVE (row), row)) ; /* skip if row is dead */ if (ROW_IS_DEAD (row)) { continue ; } rp = &A [Row [row].start] ; rp_end = rp + Row [row].length ; while (rp < rp_end) { /* get a column */ col = *rp++ ; /* add the column, if alive and untagged */ col_thickness = Col [col].shared1.thickness ; if (col_thickness > 0 && COL_IS_ALIVE (col)) { /* tag column in pivot row */ Col [col].shared1.thickness = -col_thickness ; ASSERT (pfree < Alen) ; /* place column in pivot row */ A [pfree++] = col ; pivot_row_degree += col_thickness ; } } } /* clear tag on pivot column */ Col [pivot_col].shared1.thickness = pivot_col_thickness ; max_deg = MAX (max_deg, pivot_row_degree) ; #ifndef NDEBUG DEBUG3 (("check2\n")) ; debug_mark (n_row, Row, tag_mark, max_mark) ; #endif /* NDEBUG */ /* === Kill all rows used to construct pivot row ==================== */ /* also kill pivot row, temporarily */ cp = &A [Col [pivot_col].start] ; cp_end = cp + Col [pivot_col].length ; while (cp < cp_end) { /* may be killing an already dead row */ row = *cp++ ; DEBUG3 (("Kill row in pivot col: %d\n", row)) ; KILL_ROW (row) ; } /* === Select a row index to use as the new pivot row =============== */ pivot_row_length = pfree - pivot_row_start ; if (pivot_row_length > 0) { /* pick the "pivot" row arbitrarily (first row in col) */ pivot_row = A [Col [pivot_col].start] ; DEBUG3 (("Pivotal row is %d\n", pivot_row)) ; } else { /* there is no pivot row, since it is of zero length */ pivot_row = EMPTY ; ASSERT (pivot_row_length == 0) ; } ASSERT (Col [pivot_col].length > 0 || pivot_row_length == 0) ; /* === Approximate degree computation =============================== */ /* Here begins the computation of the approximate degree. The column */ /* score is the sum of the pivot row "length", plus the size of the */ /* set differences of each row in the column minus the pattern of the */ /* pivot row itself. The column ("thickness") itself is also */ /* excluded from the column score (we thus use an approximate */ /* external degree). */ /* The time taken by the following code (compute set differences, and */ /* add them up) is proportional to the size of the data structure */ /* being scanned - that is, the sum of the sizes of each column in */ /* the pivot row. Thus, the amortized time to compute a column score */ /* is proportional to the size of that column (where size, in this */ /* context, is the column "length", or the number of row indices */ /* in that column). The number of row indices in a column is */ /* monotonically non-decreasing, from the length of the original */ /* column on input to colamd. */ /* === Compute set differences ====================================== */ DEBUG3 (("** Computing set differences phase. **\n")) ; /* pivot row is currently dead - it will be revived later. */ DEBUG3 (("Pivot row: ")) ; /* for each column in pivot row */ rp = &A [pivot_row_start] ; rp_end = rp + pivot_row_length ; while (rp < rp_end) { col = *rp++ ; ASSERT (COL_IS_ALIVE (col) && col != pivot_col) ; DEBUG3 (("Col: %d\n", col)) ; /* clear tags used to construct pivot row pattern */ col_thickness = -Col [col].shared1.thickness ; ASSERT (col_thickness > 0) ; Col [col].shared1.thickness = col_thickness ; /* === Remove column from degree list =========================== */ cur_score = Col [col].shared2.score ; prev_col = Col [col].shared3.prev ; next_col = Col [col].shared4.degree_next ; ASSERT (cur_score >= 0) ; ASSERT (cur_score <= n_col) ; ASSERT (cur_score >= EMPTY) ; if (prev_col == EMPTY) { head [cur_score] = next_col ; } else { Col [prev_col].shared4.degree_next = next_col ; } if (next_col != EMPTY) { Col [next_col].shared3.prev = prev_col ; } /* === Scan the column ========================================== */ cp = &A [Col [col].start] ; cp_end = cp + Col [col].length ; while (cp < cp_end) { /* get a row */ row = *cp++ ; row_mark = Row [row].shared2.mark ; /* skip if dead */ if (ROW_IS_MARKED_DEAD (row_mark)) { continue ; } ASSERT (row != pivot_row) ; set_difference = row_mark - tag_mark ; /* check if the row has been seen yet */ if (set_difference < 0) { ASSERT (Row [row].shared1.degree <= max_deg) ; set_difference = Row [row].shared1.degree ; } /* subtract column thickness from this row's set difference */ set_difference -= col_thickness ; ASSERT (set_difference >= 0) ; /* absorb this row if the set difference becomes zero */ if (set_difference == 0) { DEBUG3 (("aggressive absorption. Row: %d\n", row)) ; KILL_ROW (row) ; } else { /* save the new mark */ Row [row].shared2.mark = set_difference + tag_mark ; } } } #ifndef NDEBUG debug_deg_lists (n_row, n_col, Row, Col, head, min_score, n_col2-k-pivot_row_degree, max_deg) ; #endif /* NDEBUG */ /* === Add up set differences for each column ======================= */ DEBUG3 (("** Adding set differences phase. **\n")) ; /* for each column in pivot row */ rp = &A [pivot_row_start] ; rp_end = rp + pivot_row_length ; while (rp < rp_end) { /* get a column */ col = *rp++ ; ASSERT (COL_IS_ALIVE (col) && col != pivot_col) ; hash = 0 ; cur_score = 0 ; cp = &A [Col [col].start] ; /* compact the column */ new_cp = cp ; cp_end = cp + Col [col].length ; DEBUG4 (("Adding set diffs for Col: %d.\n", col)) ; while (cp < cp_end) { /* get a row */ row = *cp++ ; ASSERT(row >= 0 && row < n_row) ; row_mark = Row [row].shared2.mark ; /* skip if dead */ if (ROW_IS_MARKED_DEAD (row_mark)) { continue ; } ASSERT (row_mark > tag_mark) ; /* compact the column */ *new_cp++ = row ; /* compute hash function */ hash += row ; /* add set difference */ cur_score += row_mark - tag_mark ; /* integer overflow... */ cur_score = MIN (cur_score, n_col) ; } /* recompute the column's length */ Col [col].length = (int) (new_cp - &A [Col [col].start]) ; /* === Further mass elimination ================================= */ if (Col [col].length == 0) { DEBUG4 (("further mass elimination. Col: %d\n", col)) ; /* nothing left but the pivot row in this column */ KILL_PRINCIPAL_COL (col) ; pivot_row_degree -= Col [col].shared1.thickness ; ASSERT (pivot_row_degree >= 0) ; /* order it */ Col [col].shared2.order = k ; /* increment order count by column thickness */ k += Col [col].shared1.thickness ; } else { /* === Prepare for supercolumn detection ==================== */ DEBUG4 (("Preparing supercol detection for Col: %d.\n", col)) ; /* save score so far */ Col [col].shared2.score = cur_score ; /* add column to hash table, for supercolumn detection */ hash %= n_col + 1 ; DEBUG4 ((" Hash = %d, n_col = %d.\n", hash, n_col)) ; ASSERT (hash <= n_col) ; head_column = head [hash] ; if (head_column > EMPTY) { /* degree list "hash" is non-empty, use prev (shared3) of */ /* first column in degree list as head of hash bucket */ first_col = Col [head_column].shared3.headhash ; Col [head_column].shared3.headhash = col ; } else { /* degree list "hash" is empty, use head as hash bucket */ first_col = - (head_column + 2) ; head [hash] = - (col + 2) ; } Col [col].shared4.hash_next = first_col ; /* save hash function in Col [col].shared3.hash */ Col [col].shared3.hash = (int) hash ; ASSERT (COL_IS_ALIVE (col)) ; } } /* The approximate external column degree is now computed. */ /* === Supercolumn detection ======================================== */ DEBUG3 (("** Supercolumn detection phase. **\n")) ; detect_super_cols ( #ifndef NDEBUG n_col, Row, #endif /* NDEBUG */ Col, A, head, pivot_row_start, pivot_row_length) ; /* === Kill the pivotal column ====================================== */ KILL_PRINCIPAL_COL (pivot_col) ; /* === Clear mark =================================================== */ tag_mark += (max_deg + 1) ; if (tag_mark >= max_mark) { DEBUG2 (("clearing tag_mark\n")) ; tag_mark = clear_mark (n_row, Row) ; } #ifndef NDEBUG DEBUG3 (("check3\n")) ; debug_mark (n_row, Row, tag_mark, max_mark) ; #endif /* NDEBUG */ /* === Finalize the new pivot row, and column scores ================ */ DEBUG3 (("** Finalize scores phase. **\n")) ; /* for each column in pivot row */ rp = &A [pivot_row_start] ; /* compact the pivot row */ new_rp = rp ; rp_end = rp + pivot_row_length ; while (rp < rp_end) { col = *rp++ ; /* skip dead columns */ if (COL_IS_DEAD (col)) { continue ; } *new_rp++ = col ; /* add new pivot row to column */ A [Col [col].start + (Col [col].length++)] = pivot_row ; /* retrieve score so far and add on pivot row's degree. */ /* (we wait until here for this in case the pivot */ /* row's degree was reduced due to mass elimination). */ cur_score = Col [col].shared2.score + pivot_row_degree ; /* calculate the max possible score as the number of */ /* external columns minus the 'k' value minus the */ /* columns thickness */ max_score = n_col - k - Col [col].shared1.thickness ; /* make the score the external degree of the union-of-rows */ cur_score -= Col [col].shared1.thickness ; /* make sure score is less or equal than the max score */ cur_score = MIN (cur_score, max_score) ; ASSERT (cur_score >= 0) ; /* store updated score */ Col [col].shared2.score = cur_score ; /* === Place column back in degree list ========================= */ ASSERT (min_score >= 0) ; ASSERT (min_score <= n_col) ; ASSERT (cur_score >= 0) ; ASSERT (cur_score <= n_col) ; ASSERT (head [cur_score] >= EMPTY) ; next_col = head [cur_score] ; Col [col].shared4.degree_next = next_col ; Col [col].shared3.prev = EMPTY ; if (next_col != EMPTY) { Col [next_col].shared3.prev = col ; } head [cur_score] = col ; /* see if this score is less than current min */ min_score = MIN (min_score, cur_score) ; } #ifndef NDEBUG debug_deg_lists (n_row, n_col, Row, Col, head, min_score, n_col2-k, max_deg) ; #endif /* NDEBUG */ /* === Resurrect the new pivot row ================================== */ if (pivot_row_degree > 0) { /* update pivot row length to reflect any cols that were killed */ /* during super-col detection and mass elimination */ Row [pivot_row].start = pivot_row_start ; Row [pivot_row].length = (int) (new_rp - &A[pivot_row_start]) ; Row [pivot_row].shared1.degree = pivot_row_degree ; Row [pivot_row].shared2.mark = 0 ; /* pivot row is no longer dead */ } } /* === All principal columns have now been ordered ====================== */ return (ngarbage) ; } /* ========================================================================== */ /* === order_children ======================================================= */ /* ========================================================================== */ /* The find_ordering routine has ordered all of the principal columns (the representatives of the supercolumns). The non-principal columns have not yet been ordered. This routine orders those columns by walking up the parent tree (a column is a child of the column which absorbed it). The final permutation vector is then placed in p [0 ... n_col-1], with p [0] being the first column, and p [n_col-1] being the last. It doesn't look like it at first glance, but be assured that this routine takes time linear in the number of columns. Although not immediately obvious, the time taken by this routine is O (n_col), that is, linear in the number of columns. Not user-callable. */ PRIVATE void order_children ( /* === Parameters ======================================================= */ int n_col, /* number of columns of A */ Colamd_Col Col [], /* of size n_col+1 */ int p [] /* p [0 ... n_col-1] is the column permutation*/ ) { /* === Local variables ================================================== */ int i ; /* loop counter for all columns */ int c ; /* column index */ int parent ; /* index of column's parent */ int order ; /* column's order */ /* === Order each non-principal column ================================== */ for (i = 0 ; i < n_col ; i++) { /* find an un-ordered non-principal column */ ASSERT (COL_IS_DEAD (i)) ; if (!COL_IS_DEAD_PRINCIPAL (i) && Col [i].shared2.order == EMPTY) { parent = i ; /* once found, find its principal parent */ do { parent = Col [parent].shared1.parent ; } while (!COL_IS_DEAD_PRINCIPAL (parent)) ; /* now, order all un-ordered non-principal columns along path */ /* to this parent. collapse tree at the same time */ c = i ; /* get order of parent */ order = Col [parent].shared2.order ; do { ASSERT (Col [c].shared2.order == EMPTY) ; /* order this column */ Col [c].shared2.order = order++ ; /* collaps tree */ Col [c].shared1.parent = parent ; /* get immediate parent of this column */ c = Col [c].shared1.parent ; /* continue until we hit an ordered column. There are */ /* guarranteed not to be anymore unordered columns */ /* above an ordered column */ } while (Col [c].shared2.order == EMPTY) ; /* re-order the super_col parent to largest order for this group */ Col [parent].shared2.order = order ; } } /* === Generate the permutation ========================================= */ for (c = 0 ; c < n_col ; c++) { p [Col [c].shared2.order] = c ; } } /* ========================================================================== */ /* === detect_super_cols ==================================================== */ /* ========================================================================== */ /* Detects supercolumns by finding matches between columns in the hash buckets. Check amongst columns in the set A [row_start ... row_start + row_length-1]. The columns under consideration are currently *not* in the degree lists, and have already been placed in the hash buckets. The hash bucket for columns whose hash function is equal to h is stored as follows: if head [h] is >= 0, then head [h] contains a degree list, so: head [h] is the first column in degree bucket h. Col [head [h]].headhash gives the first column in hash bucket h. otherwise, the degree list is empty, and: -(head [h] + 2) is the first column in hash bucket h. For a column c in a hash bucket, Col [c].shared3.prev is NOT a "previous column" pointer. Col [c].shared3.hash is used instead as the hash number for that column. The value of Col [c].shared4.hash_next is the next column in the same hash bucket. Assuming no, or "few" hash collisions, the time taken by this routine is linear in the sum of the sizes (lengths) of each column whose score has just been computed in the approximate degree computation. Not user-callable. */ PRIVATE void detect_super_cols ( /* === Parameters ======================================================= */ #ifndef NDEBUG /* these two parameters are only needed when debugging is enabled: */ int n_col, /* number of columns of A */ Colamd_Row Row [], /* of size n_row+1 */ #endif /* NDEBUG */ Colamd_Col Col [], /* of size n_col+1 */ int A [], /* row indices of A */ int head [], /* head of degree lists and hash buckets */ int row_start, /* pointer to set of columns to check */ int row_length /* number of columns to check */ ) { /* === Local variables ================================================== */ int hash ; /* hash value for a column */ int *rp ; /* pointer to a row */ int c ; /* a column index */ int super_c ; /* column index of the column to absorb into */ int *cp1 ; /* column pointer for column super_c */ int *cp2 ; /* column pointer for column c */ int length ; /* length of column super_c */ int prev_c ; /* column preceding c in hash bucket */ int i ; /* loop counter */ int *rp_end ; /* pointer to the end of the row */ int col ; /* a column index in the row to check */ int head_column ; /* first column in hash bucket or degree list */ int first_col ; /* first column in hash bucket */ /* === Consider each column in the row ================================== */ rp = &A [row_start] ; rp_end = rp + row_length ; while (rp < rp_end) { col = *rp++ ; if (COL_IS_DEAD (col)) { continue ; } /* get hash number for this column */ hash = Col [col].shared3.hash ; ASSERT (hash <= n_col) ; /* === Get the first column in this hash bucket ===================== */ head_column = head [hash] ; if (head_column > EMPTY) { first_col = Col [head_column].shared3.headhash ; } else { first_col = - (head_column + 2) ; } /* === Consider each column in the hash bucket ====================== */ for (super_c = first_col ; super_c != EMPTY ; super_c = Col [super_c].shared4.hash_next) { ASSERT (COL_IS_ALIVE (super_c)) ; ASSERT (Col [super_c].shared3.hash == hash) ; length = Col [super_c].length ; /* prev_c is the column preceding column c in the hash bucket */ prev_c = super_c ; /* === Compare super_c with all columns after it ================ */ for (c = Col [super_c].shared4.hash_next ; c != EMPTY ; c = Col [c].shared4.hash_next) { ASSERT (c != super_c) ; ASSERT (COL_IS_ALIVE (c)) ; ASSERT (Col [c].shared3.hash == hash) ; /* not identical if lengths or scores are different */ if (Col [c].length != length || Col [c].shared2.score != Col [super_c].shared2.score) { prev_c = c ; continue ; } /* compare the two columns */ cp1 = &A [Col [super_c].start] ; cp2 = &A [Col [c].start] ; for (i = 0 ; i < length ; i++) { /* the columns are "clean" (no dead rows) */ ASSERT (ROW_IS_ALIVE (*cp1)) ; ASSERT (ROW_IS_ALIVE (*cp2)) ; /* row indices will same order for both supercols, */ /* no gather scatter nessasary */ if (*cp1++ != *cp2++) { break ; } } /* the two columns are different if the for-loop "broke" */ if (i != length) { prev_c = c ; continue ; } /* === Got it! two columns are identical =================== */ ASSERT (Col [c].shared2.score == Col [super_c].shared2.score) ; Col [super_c].shared1.thickness += Col [c].shared1.thickness ; Col [c].shared1.parent = super_c ; KILL_NON_PRINCIPAL_COL (c) ; /* order c later, in order_children() */ Col [c].shared2.order = EMPTY ; /* remove c from hash bucket */ Col [prev_c].shared4.hash_next = Col [c].shared4.hash_next ; } } /* === Empty this hash bucket ======================================= */ if (head_column > EMPTY) { /* corresponding degree list "hash" is not empty */ Col [head_column].shared3.headhash = EMPTY ; } else { /* corresponding degree list "hash" is empty */ head [hash] = EMPTY ; } } } /* ========================================================================== */ /* === garbage_collection =================================================== */ /* ========================================================================== */ /* Defragments and compacts columns and rows in the workspace A. Used when all avaliable memory has been used while performing row merging. Returns the index of the first free position in A, after garbage collection. The time taken by this routine is linear is the size of the array A, which is itself linear in the number of nonzeros in the input matrix. Not user-callable. */ PRIVATE int garbage_collection /* returns the new value of pfree */ ( /* === Parameters ======================================================= */ int n_row, /* number of rows */ int n_col, /* number of columns */ Colamd_Row Row [], /* row info */ Colamd_Col Col [], /* column info */ int A [], /* A [0 ... Alen-1] holds the matrix */ int *pfree /* &A [0] ... pfree is in use */ ) { /* === Local variables ================================================== */ int *psrc ; /* source pointer */ int *pdest ; /* destination pointer */ int j ; /* counter */ int r ; /* a row index */ int c ; /* a column index */ int length ; /* length of a row or column */ #ifndef NDEBUG int debug_rows ; DEBUG2 (("Defrag..\n")) ; for (psrc = &A[0] ; psrc < pfree ; psrc++) ASSERT (*psrc >= 0) ; debug_rows = 0 ; #endif /* NDEBUG */ /* === Defragment the columns =========================================== */ pdest = &A[0] ; for (c = 0 ; c < n_col ; c++) { if (COL_IS_ALIVE (c)) { psrc = &A [Col [c].start] ; /* move and compact the column */ ASSERT (pdest <= psrc) ; Col [c].start = (int) (pdest - &A [0]) ; length = Col [c].length ; for (j = 0 ; j < length ; j++) { r = *psrc++ ; if (ROW_IS_ALIVE (r)) { *pdest++ = r ; } } Col [c].length = (int) (pdest - &A [Col [c].start]) ; } } /* === Prepare to defragment the rows =================================== */ for (r = 0 ; r < n_row ; r++) { if (ROW_IS_ALIVE (r)) { if (Row [r].length == 0) { /* this row is of zero length. cannot compact it, so kill it */ DEBUG3 (("Defrag row kill\n")) ; KILL_ROW (r) ; } else { /* save first column index in Row [r].shared2.first_column */ psrc = &A [Row [r].start] ; Row [r].shared2.first_column = *psrc ; ASSERT (ROW_IS_ALIVE (r)) ; /* flag the start of the row with the one's complement of row */ *psrc = ONES_COMPLEMENT (r) ; #ifndef NDEBUG debug_rows++ ; #endif /* NDEBUG */ } } } /* === Defragment the rows ============================================== */ psrc = pdest ; while (psrc < pfree) { /* find a negative number ... the start of a row */ if (*psrc++ < 0) { psrc-- ; /* get the row index */ r = ONES_COMPLEMENT (*psrc) ; ASSERT (r >= 0 && r < n_row) ; /* restore first column index */ *psrc = Row [r].shared2.first_column ; ASSERT (ROW_IS_ALIVE (r)) ; /* move and compact the row */ ASSERT (pdest <= psrc) ; Row [r].start = (int) (pdest - &A [0]) ; length = Row [r].length ; for (j = 0 ; j < length ; j++) { c = *psrc++ ; if (COL_IS_ALIVE (c)) { *pdest++ = c ; } } Row [r].length = (int) (pdest - &A [Row [r].start]) ; #ifndef NDEBUG debug_rows-- ; #endif /* NDEBUG */ } } /* ensure we found all the rows */ ASSERT (debug_rows == 0) ; /* === Return the new value of pfree ==================================== */ return ((int) (pdest - &A [0])) ; } /* ========================================================================== */ /* === clear_mark =========================================================== */ /* ========================================================================== */ /* Clears the Row [].shared2.mark array, and returns the new tag_mark. Return value is the new tag_mark. Not user-callable. */ PRIVATE int clear_mark /* return the new value for tag_mark */ ( /* === Parameters ======================================================= */ int n_row, /* number of rows in A */ Colamd_Row Row [] /* Row [0 ... n_row-1].shared2.mark is set to zero */ ) { /* === Local variables ================================================== */ int r ; for (r = 0 ; r < n_row ; r++) { if (ROW_IS_ALIVE (r)) { Row [r].shared2.mark = 0 ; } } return (1) ; } /* ========================================================================== */ /* === print_report ========================================================= */ /* ========================================================================== */ PRIVATE void print_report ( char *method, int stats [COLAMD_STATS] ) { int i1, i2, i3 ; if (!stats) { PRINTF ("%s: No statistics available.\n", method) ; return ; } i1 = stats [COLAMD_INFO1] ; i2 = stats [COLAMD_INFO2] ; i3 = stats [COLAMD_INFO3] ; if (stats [COLAMD_STATUS] >= 0) { PRINTF ("%s: OK. ", method) ; } else { PRINTF ("%s: ERROR. ", method) ; } switch (stats [COLAMD_STATUS]) { case COLAMD_OK_BUT_JUMBLED: PRINTF ("Matrix has unsorted or duplicate row indices.\n") ; PRINTF ("%s: number of duplicate or out-of-order row indices: %d\n", method, i3) ; PRINTF ("%s: last seen duplicate or out-of-order row index: %d\n", method, INDEX (i2)) ; PRINTF ("%s: last seen in column: %d", method, INDEX (i1)) ; /* no break - fall through to next case instead */ case COLAMD_OK: PRINTF ("\n") ; PRINTF ("%s: number of dense or empty rows ignored: %d\n", method, stats [COLAMD_DENSE_ROW]) ; PRINTF ("%s: number of dense or empty columns ignored: %d\n", method, stats [COLAMD_DENSE_COL]) ; PRINTF ("%s: number of garbage collections performed: %d\n", method, stats [COLAMD_DEFRAG_COUNT]) ; break ; case COLAMD_ERROR_A_not_present: PRINTF ("Array A (row indices of matrix) not present.\n") ; break ; case COLAMD_ERROR_p_not_present: PRINTF ("Array p (column pointers for matrix) not present.\n") ; break ; case COLAMD_ERROR_nrow_negative: PRINTF ("Invalid number of rows (%d).\n", i1) ; break ; case COLAMD_ERROR_ncol_negative: PRINTF ("Invalid number of columns (%d).\n", i1) ; break ; case COLAMD_ERROR_nnz_negative: PRINTF ("Invalid number of nonzero entries (%d).\n", i1) ; break ; case COLAMD_ERROR_p0_nonzero: PRINTF ("Invalid column pointer, p [0] = %d, must be zero.\n", i1) ; break ; case COLAMD_ERROR_A_too_small: PRINTF ("Array A too small.\n") ; PRINTF (" Need Alen >= %d, but given only Alen = %d.\n", i1, i2) ; break ; case COLAMD_ERROR_col_length_negative: PRINTF ("Column %d has a negative number of nonzero entries (%d).\n", INDEX (i1), i2) ; break ; case COLAMD_ERROR_row_index_out_of_bounds: PRINTF ("Row index (row %d) out of bounds (%d to %d) in column %d.\n", INDEX (i2), INDEX (0), INDEX (i3-1), INDEX (i1)) ; break ; case COLAMD_ERROR_out_of_memory: PRINTF ("Out of memory.\n") ; break ; case COLAMD_ERROR_internal_error: /* if this happens, there is a bug in the code */ PRINTF ("Internal error! Please contact authors (davis@cise.ufl.edu).\n") ; break ; } } /* ========================================================================== */ /* === colamd debugging routines ============================================ */ /* ========================================================================== */ /* When debugging is disabled, the remainder of this file is ignored. */ #ifndef NDEBUG /* ========================================================================== */ /* === debug_structures ===================================================== */ /* ========================================================================== */ /* At this point, all empty rows and columns are dead. All live columns are "clean" (containing no dead rows) and simplicial (no supercolumns yet). Rows may contain dead columns, but all live rows contain at least one live column. */ PRIVATE void debug_structures ( /* === Parameters ======================================================= */ int n_row, int n_col, Colamd_Row Row [], Colamd_Col Col [], int A [], int n_col2 ) { /* === Local variables ================================================== */ int i ; int c ; int *cp ; int *cp_end ; int len ; int score ; int r ; int *rp ; int *rp_end ; int deg ; /* === Check A, Row, and Col ============================================ */ for (c = 0 ; c < n_col ; c++) { if (COL_IS_ALIVE (c)) { len = Col [c].length ; score = Col [c].shared2.score ; DEBUG4 (("initial live col %5d %5d %5d\n", c, len, score)) ; ASSERT (len > 0) ; ASSERT (score >= 0) ; ASSERT (Col [c].shared1.thickness == 1) ; cp = &A [Col [c].start] ; cp_end = cp + len ; while (cp < cp_end) { r = *cp++ ; ASSERT (ROW_IS_ALIVE (r)) ; } } else { i = Col [c].shared2.order ; ASSERT (i >= n_col2 && i < n_col) ; } } for (r = 0 ; r < n_row ; r++) { if (ROW_IS_ALIVE (r)) { i = 0 ; len = Row [r].length ; deg = Row [r].shared1.degree ; ASSERT (len > 0) ; ASSERT (deg > 0) ; rp = &A [Row [r].start] ; rp_end = rp + len ; while (rp < rp_end) { c = *rp++ ; if (COL_IS_ALIVE (c)) { i++ ; } } ASSERT (i > 0) ; } } } /* ========================================================================== */ /* === debug_deg_lists ====================================================== */ /* ========================================================================== */ /* Prints the contents of the degree lists. Counts the number of columns in the degree list and compares it to the total it should have. Also checks the row degrees. */ PRIVATE void debug_deg_lists ( /* === Parameters ======================================================= */ int n_row, int n_col, Colamd_Row Row [], Colamd_Col Col [], int head [], int min_score, int should, int max_deg ) { /* === Local variables ================================================== */ int deg ; int col ; int have ; int row ; /* === Check the degree lists =========================================== */ if (n_col > 10000 && colamd_debug <= 0) { return ; } have = 0 ; DEBUG4 (("Degree lists: %d\n", min_score)) ; for (deg = 0 ; deg <= n_col ; deg++) { col = head [deg] ; if (col == EMPTY) { continue ; } DEBUG4 (("%d:", deg)) ; while (col != EMPTY) { DEBUG4 ((" %d", col)) ; have += Col [col].shared1.thickness ; ASSERT (COL_IS_ALIVE (col)) ; col = Col [col].shared4.degree_next ; } DEBUG4 (("\n")) ; } DEBUG4 (("should %d have %d\n", should, have)) ; ASSERT (should == have) ; /* === Check the row degrees ============================================ */ if (n_row > 10000 && colamd_debug <= 0) { return ; } for (row = 0 ; row < n_row ; row++) { if (ROW_IS_ALIVE (row)) { ASSERT (Row [row].shared1.degree <= max_deg) ; } } } /* ========================================================================== */ /* === debug_mark =========================================================== */ /* ========================================================================== */ /* Ensures that the tag_mark is less that the maximum and also ensures that each entry in the mark array is less than the tag mark. */ PRIVATE void debug_mark ( /* === Parameters ======================================================= */ int n_row, Colamd_Row Row [], int tag_mark, int max_mark ) { /* === Local variables ================================================== */ int r ; /* === Check the Row marks ============================================== */ ASSERT (tag_mark > 0 && tag_mark <= max_mark) ; if (n_row > 10000 && colamd_debug <= 0) { return ; } for (r = 0 ; r < n_row ; r++) { ASSERT (Row [r].shared2.mark < tag_mark) ; } } /* ========================================================================== */ /* === debug_matrix ========================================================= */ /* ========================================================================== */ /* Prints out the contents of the columns and the rows. */ PRIVATE void debug_matrix ( /* === Parameters ======================================================= */ int n_row, int n_col, Colamd_Row Row [], Colamd_Col Col [], int A [] ) { /* === Local variables ================================================== */ int r ; int c ; int *rp ; int *rp_end ; int *cp ; int *cp_end ; /* === Dump the rows and columns of the matrix ========================== */ if (colamd_debug < 3) { return ; } DEBUG3 (("DUMP MATRIX:\n")) ; for (r = 0 ; r < n_row ; r++) { DEBUG3 (("Row %d alive? %d\n", r, ROW_IS_ALIVE (r))) ; if (ROW_IS_DEAD (r)) { continue ; } DEBUG3 (("start %d length %d degree %d\n", Row [r].start, Row [r].length, Row [r].shared1.degree)) ; rp = &A [Row [r].start] ; rp_end = rp + Row [r].length ; while (rp < rp_end) { c = *rp++ ; DEBUG4 ((" %d col %d\n", COL_IS_ALIVE (c), c)) ; } } for (c = 0 ; c < n_col ; c++) { DEBUG3 (("Col %d alive? %d\n", c, COL_IS_ALIVE (c))) ; if (COL_IS_DEAD (c)) { continue ; } DEBUG3 (("start %d length %d shared1 %d shared2 %d\n", Col [c].start, Col [c].length, Col [c].shared1.thickness, Col [c].shared2.score)) ; cp = &A [Col [c].start] ; cp_end = cp + Col [c].length ; while (cp < cp_end) { r = *cp++ ; DEBUG4 ((" %d row %d\n", ROW_IS_ALIVE (r), r)) ; } } } PRIVATE void colamd_get_debug ( char *method ) { colamd_debug = 0 ; /* no debug printing */ /* get "D" environment variable, which gives the debug printing level */ if (getenv ("D")) { colamd_debug = atoi (getenv ("D")) ; } DEBUG0 (("%s: debug version, D = %d (THIS WILL BE SLOW!)\n", method, colamd_debug)) ; } #endif /* NDEBUG */ MSVMpack1.2/lp_solve_5.5/ini.c0000664000175000017500000000227311141374241015063 0ustar lauerlauer#include #include #include #include "lp_lib.h" #include "ini.h" FILE *ini_create(char *filename) { FILE *fp; fp = fopen(filename, "w"); return(fp); } FILE *ini_open(char *filename) { FILE *fp; fp = fopen(filename, "r"); return(fp); } void ini_writecomment(FILE *fp, char *comment) { fprintf(fp, "; %s\n", comment); } void ini_writeheader(FILE *fp, char *header, int addnewline) { if((addnewline) && (ftell(fp) > 0)) fputs("\n", fp); fprintf(fp, "[%s]\n", header); } void ini_writedata(FILE *fp, char *name, char *data) { if(name != NULL) fprintf(fp, "%s=%s\n", name, data); else fprintf(fp, "%s\n", data); } int ini_readdata(FILE *fp, char *data, int szdata, int withcomment) { int l; char *ptr; if(fgets(data, szdata, fp) == NULL) return(0); if(!withcomment) { ptr = strchr(data, ';'); if(ptr != NULL) *ptr = 0; } l = (int) strlen(data); while((l > 0) && (isspace(data[l - 1]))) l--; data[l] = 0; if((l >= 2) && (data[0] == '[') && (data[l - 1] == ']')) { memcpy(data, data + 1, l - 2); data[l - 2] = 0; return(1); } return(2); } void ini_close(FILE *fp) { fclose(fp); } MSVMpack1.2/lp_solve_5.5/lp_rlp.h0000664000175000017500000022043211250515162015600 0ustar lauerlauer #define YY_INT_ALIGNED short int /* A lexical scanner generated by flex */ #define FLEX_SCANNER #define YY_FLEX_MAJOR_VERSION 2 #define YY_FLEX_MINOR_VERSION 5 #define YY_FLEX_SUBMINOR_VERSION 35 #if YY_FLEX_SUBMINOR_VERSION > 0 #define FLEX_BETA #endif /* First, we deal with platform-specific or compiler-specific issues. */ /* begin standard C headers. */ #include #include #include #include /* end standard C headers. */ /* flex integer type definitions */ #ifndef FLEXINT_H #define FLEXINT_H /* C99 systems have . Non-C99 systems may or may not. */ #if defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L /* C99 says to define __STDC_LIMIT_MACROS before including stdint.h, * if you want the limit (max/min) macros for int types. */ #ifndef __STDC_LIMIT_MACROS #define __STDC_LIMIT_MACROS 1 #endif #include typedef int8_t flex_int8_t; typedef uint8_t flex_uint8_t; typedef int16_t flex_int16_t; typedef uint16_t flex_uint16_t; typedef int32_t flex_int32_t; typedef uint32_t flex_uint32_t; #else typedef signed char flex_int8_t; typedef short int flex_int16_t; typedef int flex_int32_t; typedef unsigned char flex_uint8_t; typedef unsigned short int flex_uint16_t; typedef unsigned int flex_uint32_t; #endif /* ! C99 */ /* Limits of integral types. */ #ifndef INT8_MIN #define INT8_MIN (-128) #endif #ifndef INT16_MIN #define INT16_MIN (-32767-1) #endif #ifndef INT32_MIN #define INT32_MIN (-2147483647-1) #endif #ifndef INT8_MAX #define INT8_MAX (127) #endif #ifndef INT16_MAX #define INT16_MAX (32767) #endif #ifndef INT32_MAX #define INT32_MAX (2147483647) #endif #ifndef UINT8_MAX #define UINT8_MAX (255U) #endif #ifndef UINT16_MAX #define UINT16_MAX (65535U) #endif #ifndef UINT32_MAX #define UINT32_MAX (4294967295U) #endif #endif /* ! FLEXINT_H */ #ifdef __cplusplus /* The "const" storage-class-modifier is valid. */ #define YY_USE_CONST #else /* ! __cplusplus */ /* C99 requires __STDC__ to be defined as 1. */ #if defined (__STDC__) #define YY_USE_CONST #endif /* defined (__STDC__) */ #endif /* ! __cplusplus */ #ifdef YY_USE_CONST #define lp_yyconst const #else #define lp_yyconst #endif /* Returned upon end-of-file. */ #define YY_NULL 0 /* Promotes a possibly negative, possibly signed char to an unsigned * integer for use as an array index. If the signed char is negative, * we want to instead treat it as an 8-bit unsigned char, hence the * double cast. */ #define YY_SC_TO_UI(c) ((unsigned int) (unsigned char) c) /* An opaque pointer. */ #ifndef YY_TYPEDEF_YY_SCANNER_T #define YY_TYPEDEF_YY_SCANNER_T typedef void* lp_yyscan_t; #endif /* For convenience, these vars (plus the bison vars far below) are macros in the reentrant scanner. */ #define lp_yyin lp_yyg->lp_yyin_r #define lp_yyout lp_yyg->lp_yyout_r #define lp_yyextra lp_yyg->lp_yyextra_r #define lp_yyleng lp_yyg->lp_yyleng_r #define lp_yytext lp_yyg->lp_yytext_r #define lp_yylineno (YY_CURRENT_BUFFER_LVALUE->lp_yy_bs_lineno) #define lp_yycolumn (YY_CURRENT_BUFFER_LVALUE->lp_yy_bs_column) #define lp_yy_flex_debug lp_yyg->lp_yy_flex_debug_r /* Enter a start condition. This macro really ought to take a parameter, * but we do it the disgusting crufty way forced on us by the ()-less * definition of BEGIN. */ #define BEGIN lp_yyg->lp_yy_start = 1 + 2 * /* Translate the current start state into a value that can be later handed * to BEGIN to return to the state. The YYSTATE alias is for lex * compatibility. */ #define YY_START ((lp_yyg->lp_yy_start - 1) / 2) #define YYSTATE YY_START /* Action number for EOF rule of a given start state. */ #define YY_STATE_EOF(state) (YY_END_OF_BUFFER + state + 1) /* Special action meaning "start processing a new file". */ #define YY_NEW_FILE lp_yyrestart(lp_yyin ,lp_yyscanner ) #define YY_END_OF_BUFFER_CHAR 0 /* Size of default input buffer. */ #ifndef YY_BUF_SIZE #define YY_BUF_SIZE 16384 #endif /* The state buf must be large enough to hold one state per character in the main buffer. */ #define YY_STATE_BUF_SIZE ((YY_BUF_SIZE + 2) * sizeof(lp_yy_state_type)) #ifndef YY_TYPEDEF_YY_BUFFER_STATE #define YY_TYPEDEF_YY_BUFFER_STATE typedef struct lp_yy_buffer_state *YY_BUFFER_STATE; #endif #define EOB_ACT_CONTINUE_SCAN 0 #define EOB_ACT_END_OF_FILE 1 #define EOB_ACT_LAST_MATCH 2 /* Note: We specifically omit the test for lp_yy_rule_can_match_eol because it requires * access to the local variable lp_yy_act. Since lp_yyless() is a macro, it would break * existing scanners that call lp_yyless() from OUTSIDE lp_yylex. * One obvious solution it to make lp_yy_act a global. I tried that, and saw * a 5% performance hit in a non-lp_yylineno scanner, because lp_yy_act is * normally declared as a register variable-- so it is not worth it. */ #define YY_LESS_LINENO(n) \ do { \ int lp_yyl;\ for ( lp_yyl = n; lp_yyl < lp_yyleng; ++lp_yyl )\ if ( lp_yytext[lp_yyl] == '\n' )\ --lp_yylineno;\ }while(0) /* Return all but the first "n" matched characters back to the input stream. */ #define lp_yyless(n) \ do \ { \ /* Undo effects of setting up lp_yytext. */ \ int lp_yyless_macro_arg = (n); \ YY_LESS_LINENO(lp_yyless_macro_arg);\ *lp_yy_cp = lp_yyg->lp_yy_hold_char; \ YY_RESTORE_YY_MORE_OFFSET \ lp_yyg->lp_yy_c_buf_p = lp_yy_cp = lp_yy_bp + lp_yyless_macro_arg - YY_MORE_ADJ; \ YY_DO_BEFORE_ACTION; /* set up lp_yytext again */ \ } \ while ( 0 ) #define unput(c) lp_yyunput( c, lp_yyg->lp_yytext_ptr , lp_yyscanner ) #ifndef YY_TYPEDEF_YY_SIZE_T #define YY_TYPEDEF_YY_SIZE_T typedef size_t lp_yy_size_t; #endif #ifndef YY_STRUCT_YY_BUFFER_STATE #define YY_STRUCT_YY_BUFFER_STATE struct lp_yy_buffer_state { FILE *lp_yy_input_file; char *lp_yy_ch_buf; /* input buffer */ char *lp_yy_buf_pos; /* current position in input buffer */ /* Size of input buffer in bytes, not including room for EOB * characters. */ lp_yy_size_t lp_yy_buf_size; /* Number of characters read into lp_yy_ch_buf, not including EOB * characters. */ int lp_yy_n_chars; /* Whether we "own" the buffer - i.e., we know we created it, * and can realloc() it to grow it, and should free() it to * delete it. */ int lp_yy_is_our_buffer; /* Whether this is an "interactive" input source; if so, and * if we're using stdio for input, then we want to use getc() * instead of fread(), to make sure we stop fetching input after * each newline. */ int lp_yy_is_interactive; /* Whether we're considered to be at the beginning of a line. * If so, '^' rules will be active on the next match, otherwise * not. */ int lp_yy_at_bol; int lp_yy_bs_lineno; /**< The line count. */ int lp_yy_bs_column; /**< The column count. */ /* Whether to try to fill the input buffer when we reach the * end of it. */ int lp_yy_fill_buffer; int lp_yy_buffer_status; #define YY_BUFFER_NEW 0 #define YY_BUFFER_NORMAL 1 /* When an EOF's been seen but there's still some text to process * then we mark the buffer as YY_EOF_PENDING, to indicate that we * shouldn't try reading from the input source any more. We might * still have a bunch of tokens to match, though, because of * possible backing-up. * * When we actually see the EOF, we change the status to "new" * (via lp_yyrestart()), so that the user can continue scanning by * just pointing lp_yyin at a new input file. */ #define YY_BUFFER_EOF_PENDING 2 }; #endif /* !YY_STRUCT_YY_BUFFER_STATE */ /* We provide macros for accessing buffer states in case in the * future we want to put the buffer states in a more general * "scanner state". * * Returns the top of the stack, or NULL. */ #define YY_CURRENT_BUFFER ( lp_yyg->lp_yy_buffer_stack \ ? lp_yyg->lp_yy_buffer_stack[lp_yyg->lp_yy_buffer_stack_top] \ : NULL) /* Same as previous macro, but useful when we know that the buffer stack is not * NULL or when we need an lvalue. For internal use only. */ #define YY_CURRENT_BUFFER_LVALUE lp_yyg->lp_yy_buffer_stack[lp_yyg->lp_yy_buffer_stack_top] void lp_yyrestart (FILE *input_file ,lp_yyscan_t lp_yyscanner ); void lp_yy_switch_to_buffer (YY_BUFFER_STATE new_buffer ,lp_yyscan_t lp_yyscanner ); YY_BUFFER_STATE lp_yy_create_buffer (FILE *file,int size ,lp_yyscan_t lp_yyscanner ); void lp_yy_delete_buffer (YY_BUFFER_STATE b ,lp_yyscan_t lp_yyscanner ); void lp_yy_flush_buffer (YY_BUFFER_STATE b ,lp_yyscan_t lp_yyscanner ); void lp_yypush_buffer_state (YY_BUFFER_STATE new_buffer ,lp_yyscan_t lp_yyscanner ); void lp_yypop_buffer_state (lp_yyscan_t lp_yyscanner ); static void lp_yyensure_buffer_stack (lp_yyscan_t lp_yyscanner ); static void lp_yy_load_buffer_state (lp_yyscan_t lp_yyscanner ); static void lp_yy_init_buffer (YY_BUFFER_STATE b,FILE *file ,lp_yyscan_t lp_yyscanner ); #define YY_FLUSH_BUFFER lp_yy_flush_buffer(YY_CURRENT_BUFFER ,lp_yyscanner) YY_BUFFER_STATE lp_yy_scan_buffer (char *base,lp_yy_size_t size ,lp_yyscan_t lp_yyscanner ); YY_BUFFER_STATE lp_yy_scan_string (lp_yyconst char *lp_yy_str ,lp_yyscan_t lp_yyscanner ); YY_BUFFER_STATE lp_yy_scan_bytes (lp_yyconst char *bytes,int len ,lp_yyscan_t lp_yyscanner ); void *lp_yyalloc (lp_yy_size_t ,lp_yyscan_t lp_yyscanner ); void *lp_yyrealloc (void *,lp_yy_size_t ,lp_yyscan_t lp_yyscanner ); void lp_yyfree (void * ,lp_yyscan_t lp_yyscanner ); #define lp_yy_new_buffer lp_yy_create_buffer #define lp_yy_set_interactive(is_interactive) \ { \ if ( ! YY_CURRENT_BUFFER ){ \ lp_yyensure_buffer_stack (lp_yyscanner); \ YY_CURRENT_BUFFER_LVALUE = \ lp_yy_create_buffer(lp_yyin,YY_BUF_SIZE ,lp_yyscanner); \ } \ YY_CURRENT_BUFFER_LVALUE->lp_yy_is_interactive = is_interactive; \ } #define lp_yy_set_bol(at_bol) \ { \ if ( ! YY_CURRENT_BUFFER ){\ lp_yyensure_buffer_stack (lp_yyscanner); \ YY_CURRENT_BUFFER_LVALUE = \ lp_yy_create_buffer(lp_yyin,YY_BUF_SIZE ,lp_yyscanner); \ } \ YY_CURRENT_BUFFER_LVALUE->lp_yy_at_bol = at_bol; \ } #define YY_AT_BOL() (YY_CURRENT_BUFFER_LVALUE->lp_yy_at_bol) /* Begin user sect3 */ #define lp_yywrap(n) 1 #define YY_SKIP_YYWRAP typedef unsigned char YY_CHAR; typedef int lp_yy_state_type; #define lp_yytext_ptr lp_yytext_r static lp_yy_state_type lp_yy_get_previous_state (lp_yyscan_t lp_yyscanner ); static lp_yy_state_type lp_yy_try_NUL_trans (lp_yy_state_type current_state ,lp_yyscan_t lp_yyscanner); static int lp_yy_get_next_buffer (lp_yyscan_t lp_yyscanner ); static void lp_yy_fatal_error (lp_yyconst char msg[] ,lp_yyscan_t lp_yyscanner ); /* Done after the current pattern has been matched and before the * corresponding action - sets up lp_yytext. */ #define YY_DO_BEFORE_ACTION \ lp_yyg->lp_yytext_ptr = lp_yy_bp; \ lp_yyleng = (size_t) (lp_yy_cp - lp_yy_bp); \ lp_yyg->lp_yy_hold_char = *lp_yy_cp; \ *lp_yy_cp = '\0'; \ lp_yyg->lp_yy_c_buf_p = lp_yy_cp; #define YY_NUM_RULES 33 #define YY_END_OF_BUFFER 34 /* This struct is not used in this scanner, but its presence is necessary. */ struct lp_yy_trans_info { flex_int32_t lp_yy_verify; flex_int32_t lp_yy_nxt; }; static lp_yyconst flex_int16_t lp_yy_accept[144] = { 0, 0, 0, 0, 0, 0, 0, 34, 32, 10, 10, 27, 17, 11, 32, 32, 14, 26, 31, 29, 28, 30, 25, 25, 10, 25, 25, 25, 25, 3, 4, 3, 3, 9, 7, 8, 10, 17, 17, 0, 15, 1, 6, 15, 14, 0, 29, 30, 0, 25, 24, 0, 25, 25, 10, 0, 0, 0, 0, 25, 25, 25, 25, 25, 2, 0, 15, 0, 15, 22, 0, 25, 25, 0, 0, 0, 0, 0, 19, 25, 18, 20, 25, 25, 21, 0, 25, 0, 13, 25, 0, 12, 25, 19, 0, 18, 20, 21, 25, 23, 25, 20, 21, 21, 16, 16, 0, 25, 25, 0, 23, 0, 21, 25, 25, 0, 0, 25, 25, 0, 0, 19, 25, 0, 0, 25, 25, 19, 0, 18, 0, 0, 25, 25, 18, 0, 0, 0, 0, 0, 0, 0, 0, 0 } ; static lp_yyconst flex_int32_t lp_yy_ec[256] = { 0, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 1, 1, 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 5, 6, 5, 5, 5, 1, 1, 7, 8, 9, 10, 11, 12, 13, 14, 14, 13, 13, 13, 13, 13, 13, 13, 15, 16, 17, 18, 19, 1, 5, 20, 21, 22, 23, 24, 25, 26, 23, 27, 23, 23, 23, 28, 29, 30, 23, 23, 31, 32, 33, 34, 23, 23, 35, 36, 37, 5, 1, 5, 5, 5, 1, 20, 21, 22, 23, 24, 25, 26, 23, 27, 23, 23, 23, 28, 29, 30, 23, 23, 31, 32, 33, 34, 23, 23, 35, 36, 37, 5, 1, 5, 5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 } ; static lp_yyconst flex_int32_t lp_yy_meta[38] = { 0, 1, 2, 3, 3, 4, 5, 6, 3, 6, 3, 5, 5, 5, 5, 7, 6, 7, 6, 6, 4, 4, 4, 4, 4, 4, 4, 8, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 } ; static lp_yyconst flex_int16_t lp_yy_base[150] = { 0, 0, 36, 36, 38, 43, 45, 366, 388, 48, 62, 388, 338, 388, 40, 48, 60, 388, 388, 346, 388, 326, 60, 65, 91, 81, 74, 85, 102, 388, 388, 388, 330, 388, 388, 388, 125, 313, 134, 308, 96, 388, 388, 117, 132, 139, 388, 388, 88, 146, 320, 0, 149, 152, 0, 307, 301, 294, 83, 153, 156, 157, 189, 160, 388, 286, 126, 65, 108, 388, 289, 181, 185, 272, 273, 250, 249, 220, 199, 203, 208, 192, 211, 219, 227, 243, 109, 163, 225, 202, 174, 224, 215, 213, 207, 191, 388, 189, 227, 228, 231, 244, 240, 253, 276, 388, 170, 260, 262, 166, 388, 169, 179, 263, 241, 166, 159, 270, 272, 149, 155, 284, 288, 130, 124, 296, 303, 388, 103, 300, 96, 45, 324, 328, 388, 82, 311, 79, 68, 54, 56, 25, 12, 388, 345, 353, 360, 367, 372, 379 } ; static lp_yyconst flex_int16_t lp_yy_def[150] = { 0, 143, 1, 144, 144, 145, 145, 143, 143, 143, 143, 143, 146, 143, 143, 143, 143, 143, 143, 143, 143, 143, 147, 147, 143, 147, 147, 147, 147, 143, 143, 143, 143, 143, 143, 143, 143, 146, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 147, 143, 148, 147, 147, 24, 143, 143, 143, 143, 147, 147, 147, 147, 147, 143, 143, 143, 143, 143, 143, 148, 147, 147, 143, 143, 143, 143, 143, 147, 147, 147, 147, 147, 147, 147, 149, 143, 143, 143, 62, 143, 143, 62, 143, 143, 143, 143, 143, 62, 62, 62, 62, 62, 62, 143, 143, 143, 62, 62, 143, 143, 143, 143, 62, 62, 143, 143, 62, 62, 143, 143, 62, 62, 143, 143, 62, 62, 143, 143, 62, 143, 143, 147, 147, 143, 143, 149, 143, 143, 143, 143, 143, 143, 0, 143, 143, 143, 143, 143, 143 } ; static lp_yyconst flex_int16_t lp_yy_nxt[426] = { 0, 8, 9, 10, 9, 8, 8, 11, 12, 13, 12, 14, 15, 16, 16, 17, 18, 19, 20, 21, 22, 22, 22, 22, 22, 22, 22, 22, 23, 22, 22, 22, 22, 22, 22, 22, 22, 22, 24, 30, 31, 30, 31, 32, 96, 32, 34, 35, 34, 35, 36, 36, 36, 40, 40, 41, 37, 25, 37, 142, 42, 26, 48, 27, 36, 36, 36, 48, 28, 136, 37, 43, 37, 44, 44, 50, 48, 51, 68, 68, 50, 136, 51, 48, 45, 52, 141, 48, 140, 50, 48, 51, 53, 54, 36, 36, 50, 139, 51, 37, 50, 37, 51, 50, 48, 60, 138, 76, 59, 40, 40, 48, 55, 77, 61, 137, 56, 50, 57, 51, 45, 68, 68, 58, 50, 135, 62, 36, 36, 36, 66, 66, 63, 37, 134, 37, 38, 38, 38, 66, 66, 45, 38, 43, 38, 44, 44, 67, 48, 67, 45, 48, 68, 68, 48, 48, 45, 131, 48, 48, 130, 50, 48, 51, 50, 87, 51, 50, 50, 51, 51, 50, 50, 51, 51, 50, 90, 51, 88, 128, 79, 72, 78, 87, 71, 127, 124, 90, 123, 91, 80, 48, 84, 112, 48, 120, 88, 119, 51, 116, 91, 48, 51, 112, 50, 48, 51, 50, 89, 51, 48, 81, 92, 48, 50, 111, 51, 82, 50, 98, 51, 48, 83, 50, 49, 51, 50, 99, 51, 48, 107, 110, 100, 109, 50, 49, 51, 49, 101, 69, 69, 103, 50, 108, 51, 104, 104, 104, 49, 49, 49, 102, 97, 49, 115, 49, 49, 114, 113, 49, 49, 49, 49, 49, 49, 122, 49, 103, 49, 49, 106, 96, 49, 49, 49, 49, 81, 49, 104, 104, 104, 49, 49, 95, 49, 49, 49, 117, 49, 118, 49, 49, 49, 49, 49, 49, 49, 94, 49, 121, 49, 93, 125, 49, 126, 49, 49, 125, 86, 126, 49, 85, 49, 104, 104, 104, 49, 49, 49, 129, 132, 49, 49, 75, 49, 49, 87, 133, 49, 49, 90, 49, 74, 49, 73, 69, 49, 65, 143, 88, 39, 51, 64, 91, 47, 51, 29, 29, 29, 29, 29, 29, 29, 29, 33, 33, 33, 33, 33, 33, 33, 33, 38, 38, 46, 39, 143, 143, 38, 49, 143, 49, 49, 143, 49, 49, 70, 70, 143, 143, 70, 105, 105, 143, 105, 105, 105, 105, 7, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143 } ; static lp_yyconst flex_int16_t lp_yy_chk[426] = { 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 3, 4, 4, 3, 142, 4, 5, 5, 6, 6, 9, 9, 9, 14, 14, 15, 9, 2, 9, 141, 15, 2, 22, 2, 10, 10, 10, 23, 2, 131, 10, 16, 10, 16, 16, 22, 26, 22, 67, 67, 23, 131, 23, 25, 16, 23, 140, 27, 139, 26, 48, 26, 23, 24, 24, 24, 25, 138, 25, 24, 27, 24, 27, 48, 28, 26, 137, 58, 25, 40, 40, 86, 24, 58, 27, 135, 24, 28, 24, 28, 40, 68, 68, 24, 86, 130, 28, 36, 36, 36, 43, 43, 28, 36, 128, 36, 38, 38, 38, 66, 66, 43, 38, 44, 38, 44, 44, 45, 49, 45, 66, 52, 45, 45, 53, 59, 44, 124, 60, 61, 123, 49, 63, 49, 52, 87, 52, 53, 59, 53, 59, 60, 61, 60, 61, 63, 90, 63, 87, 120, 60, 53, 59, 71, 52, 119, 116, 72, 115, 90, 61, 62, 63, 112, 81, 111, 71, 109, 71, 106, 72, 78, 72, 97, 62, 79, 62, 81, 71, 81, 80, 62, 72, 82, 78, 95, 78, 62, 79, 78, 79, 83, 62, 80, 89, 80, 82, 79, 82, 84, 89, 94, 80, 93, 83, 89, 83, 92, 82, 91, 88, 84, 84, 92, 84, 85, 85, 85, 92, 98, 99, 83, 77, 100, 101, 98, 99, 100, 98, 100, 98, 99, 102, 114, 100, 114, 101, 103, 102, 114, 85, 76, 101, 102, 114, 103, 101, 101, 104, 104, 104, 103, 107, 75, 108, 113, 103, 107, 107, 108, 108, 113, 117, 107, 118, 108, 113, 74, 117, 113, 118, 73, 117, 117, 118, 118, 121, 117, 70, 118, 122, 65, 121, 136, 136, 136, 122, 121, 125, 122, 125, 122, 129, 57, 125, 126, 132, 126, 129, 125, 133, 126, 56, 129, 55, 50, 126, 39, 136, 132, 37, 132, 32, 133, 21, 133, 144, 144, 144, 144, 144, 144, 144, 144, 145, 145, 145, 145, 145, 145, 145, 145, 146, 146, 19, 12, 7, 0, 146, 147, 0, 147, 147, 0, 147, 147, 148, 148, 0, 0, 148, 149, 149, 0, 149, 149, 149, 149, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143 } ; /* Table of booleans, true if rule could match eol. */ static lp_yyconst flex_int32_t lp_yy_rule_can_match_eol[34] = { 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, }; /* The intent behind this definition is that it'll catch * any uses of REJECT which flex missed. */ #define REJECT reject_used_but_not_detected #define lp_yymore() lp_yymore_used_but_not_detected #define YY_MORE_ADJ 0 #define YY_RESTORE_YY_MORE_OFFSET /* made reentrant with help of http://www.usualcoding.eu/post/2007/09/03/Building-a-reentrant-parser-in-C-with-Flex/Bison */ /* Note that a minimum version of flex is needed to be able to compile this. Older version don't know the reentrant code. Version 2.5.4 is not enough. Probably at least v2.5.31 is needed. Tested with v2.5.35 */ /* ** We want the scanner to be reentrant, therefore generate no global variables. ** That what the 'reentrant' option is for. ** 'bison-bridge' is used to create a bison compatible scanner and share lp_yylval */ #define INITIAL 0 #define COMMENT 1 #define LINECOMMENT 2 #ifndef YY_NO_UNISTD_H /* Special case for "unistd.h", since it is non-ANSI. We include it way * down here because we want the user's section 1 to have been scanned first. * The user has a chance to override it with an option. */ #include #endif #ifndef YY_EXTRA_TYPE #define YY_EXTRA_TYPE void * #endif /* Holds the entire state of the reentrant scanner. */ struct lp_yyguts_t { /* User-defined. Not touched by flex. */ YY_EXTRA_TYPE lp_yyextra_r; /* The rest are the same as the globals declared in the non-reentrant scanner. */ FILE *lp_yyin_r, *lp_yyout_r; size_t lp_yy_buffer_stack_top; /**< index of top of stack. */ size_t lp_yy_buffer_stack_max; /**< capacity of stack. */ YY_BUFFER_STATE * lp_yy_buffer_stack; /**< Stack as an array. */ char lp_yy_hold_char; int lp_yy_n_chars; int lp_yyleng_r; char *lp_yy_c_buf_p; int lp_yy_init; int lp_yy_start; int lp_yy_did_buffer_switch_on_eof; int lp_yy_start_stack_ptr; int lp_yy_start_stack_depth; int *lp_yy_start_stack; lp_yy_state_type lp_yy_last_accepting_state; char* lp_yy_last_accepting_cpos; int lp_yylineno_r; int lp_yy_flex_debug_r; char *lp_yytext_r; int lp_yy_more_flag; int lp_yy_more_len; YYSTYPE * lp_yylval_r; }; /* end struct lp_yyguts_t */ static int lp_yy_init_globals (lp_yyscan_t lp_yyscanner ); /* This must go here because YYSTYPE and YYLTYPE are included * from bison output in section 1.*/ # define lp_yylval lp_yyg->lp_yylval_r int lp_yylex_init (lp_yyscan_t* scanner); int lp_yylex_init_extra (YY_EXTRA_TYPE user_defined,lp_yyscan_t* scanner); /* Accessor methods to globals. These are made visible to non-reentrant scanners for convenience. */ int lp_yylex_destroy (lp_yyscan_t lp_yyscanner ); int lp_yyget_debug (lp_yyscan_t lp_yyscanner ); void lp_yyset_debug (int debug_flag ,lp_yyscan_t lp_yyscanner ); YY_EXTRA_TYPE lp_yyget_extra (lp_yyscan_t lp_yyscanner ); void lp_yyset_extra (YY_EXTRA_TYPE user_defined ,lp_yyscan_t lp_yyscanner ); FILE *lp_yyget_in (lp_yyscan_t lp_yyscanner ); void lp_yyset_in (FILE * in_str ,lp_yyscan_t lp_yyscanner ); FILE *lp_yyget_out (lp_yyscan_t lp_yyscanner ); void lp_yyset_out (FILE * out_str ,lp_yyscan_t lp_yyscanner ); int lp_yyget_leng (lp_yyscan_t lp_yyscanner ); char *lp_yyget_text (lp_yyscan_t lp_yyscanner ); int lp_yyget_lineno (lp_yyscan_t lp_yyscanner ); void lp_yyset_lineno (int line_number ,lp_yyscan_t lp_yyscanner ); YYSTYPE * lp_yyget_lval (lp_yyscan_t lp_yyscanner ); void lp_yyset_lval (YYSTYPE * lp_yylval_param ,lp_yyscan_t lp_yyscanner ); /* Macros after this point can all be overridden by user definitions in * section 1. */ #ifndef YY_SKIP_YYWRAP #ifdef __cplusplus extern "C" int lp_yywrap (lp_yyscan_t lp_yyscanner ); #else extern int lp_yywrap (lp_yyscan_t lp_yyscanner ); #endif #endif static void lp_yyunput (int c,char *buf_ptr ,lp_yyscan_t lp_yyscanner); #ifndef lp_yytext_ptr static void lp_yy_flex_strncpy (char *,lp_yyconst char *,int ,lp_yyscan_t lp_yyscanner); #endif #ifdef YY_NEED_STRLEN static int lp_yy_flex_strlen (lp_yyconst char * ,lp_yyscan_t lp_yyscanner); #endif #ifndef YY_NO_INPUT #ifdef __cplusplus static int lp_yyinput (lp_yyscan_t lp_yyscanner ); #else static int input (lp_yyscan_t lp_yyscanner ); #endif #endif /* Amount of stuff to slurp up with each read. */ #ifndef YY_READ_BUF_SIZE #define YY_READ_BUF_SIZE 8192 #endif /* Copy whatever the last rule matched to the standard output. */ #ifndef ECHO /* This used to be an fputs(), but since the string might contain NUL's, * we now use fwrite(). */ #define ECHO fwrite( lp_yytext, lp_yyleng, 1, lp_yyout ) #endif /* Gets input and stuffs it into "buf". number of characters read, or YY_NULL, * is returned in "result". */ #ifndef YY_INPUT #define YY_INPUT(buf,result,max_size) \ if ( YY_CURRENT_BUFFER_LVALUE->lp_yy_is_interactive ) \ { \ int c = '*'; \ int n; \ for ( n = 0; n < max_size && \ (c = getc( lp_yyin )) != EOF && c != '\n'; ++n ) \ buf[n] = (char) c; \ if ( c == '\n' ) \ buf[n++] = (char) c; \ if ( c == EOF && ferror( lp_yyin ) ) \ YY_FATAL_ERROR( "input in flex scanner failed" ); \ result = n; \ } \ else \ { \ errno=0; \ while ( (result = fread(buf, 1, max_size, lp_yyin))==0 && ferror(lp_yyin)) \ { \ if( errno != EINTR) \ { \ YY_FATAL_ERROR( "input in flex scanner failed" ); \ break; \ } \ errno=0; \ clearerr(lp_yyin); \ } \ }\ \ #endif /* No semi-colon after return; correct usage is to write "lp_yyterminate();" - * we don't want an extra ';' after the "return" because that will cause * some compilers to complain about unreachable statements. */ #ifndef lp_yyterminate #define lp_yyterminate() return YY_NULL #endif /* Number of entries by which start-condition stack grows. */ #ifndef YY_START_STACK_INCR #define YY_START_STACK_INCR 25 #endif /* Report a fatal error. */ #ifndef YY_FATAL_ERROR #define YY_FATAL_ERROR(msg) lp_yy_fatal_error( msg , lp_yyscanner) #endif /* end tables serialization structures and prototypes */ /* Default declaration of generated scanner - a define so the user can * easily add parameters. */ #ifndef YY_DECL #define YY_DECL_IS_OURS 1 extern int lp_yylex \ (YYSTYPE * lp_yylval_param ,lp_yyscan_t lp_yyscanner); #define YY_DECL int lp_yylex \ (YYSTYPE * lp_yylval_param , lp_yyscan_t lp_yyscanner) #endif /* !YY_DECL */ /* Code executed at the beginning of each rule, after lp_yytext and lp_yyleng * have been set up. */ #ifndef YY_USER_ACTION #define YY_USER_ACTION #endif /* Code executed at the end of each rule. */ #ifndef YY_BREAK #define YY_BREAK break; #endif #define YY_RULE_SETUP \ if ( lp_yyleng > 0 ) \ YY_CURRENT_BUFFER_LVALUE->lp_yy_at_bol = \ (lp_yytext[lp_yyleng - 1] == '\n'); \ YY_USER_ACTION /** The main scanner function which does all the work. */ YY_DECL { register lp_yy_state_type lp_yy_current_state; register char *lp_yy_cp, *lp_yy_bp; register int lp_yy_act; struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; lp_yylval = lp_yylval_param; if ( !lp_yyg->lp_yy_init ) { lp_yyg->lp_yy_init = 1; #ifdef YY_USER_INIT YY_USER_INIT; #endif if ( ! lp_yyg->lp_yy_start ) lp_yyg->lp_yy_start = 1; /* first start state */ if ( ! lp_yyin ) lp_yyin = stdin; if ( ! lp_yyout ) lp_yyout = stdout; if ( ! YY_CURRENT_BUFFER ) { lp_yyensure_buffer_stack (lp_yyscanner); YY_CURRENT_BUFFER_LVALUE = lp_yy_create_buffer(lp_yyin,YY_BUF_SIZE ,lp_yyscanner); } lp_yy_load_buffer_state(lp_yyscanner ); } while ( 1 ) /* loops until end-of-file is reached */ { lp_yy_cp = lp_yyg->lp_yy_c_buf_p; /* Support of lp_yytext. */ *lp_yy_cp = lp_yyg->lp_yy_hold_char; /* lp_yy_bp points to the position in lp_yy_ch_buf of the start of * the current run. */ lp_yy_bp = lp_yy_cp; lp_yy_current_state = lp_yyg->lp_yy_start; lp_yy_current_state += YY_AT_BOL(); lp_yy_match: do { register YY_CHAR lp_yy_c = lp_yy_ec[YY_SC_TO_UI(*lp_yy_cp)]; if ( lp_yy_accept[lp_yy_current_state] ) { lp_yyg->lp_yy_last_accepting_state = lp_yy_current_state; lp_yyg->lp_yy_last_accepting_cpos = lp_yy_cp; } while ( lp_yy_chk[lp_yy_base[lp_yy_current_state] + lp_yy_c] != lp_yy_current_state ) { lp_yy_current_state = (int) lp_yy_def[lp_yy_current_state]; if ( lp_yy_current_state >= 144 ) lp_yy_c = lp_yy_meta[(unsigned int) lp_yy_c]; } lp_yy_current_state = lp_yy_nxt[lp_yy_base[lp_yy_current_state] + (unsigned int) lp_yy_c]; ++lp_yy_cp; } while ( lp_yy_base[lp_yy_current_state] != 388 ); lp_yy_find_action: lp_yy_act = lp_yy_accept[lp_yy_current_state]; if ( lp_yy_act == 0 ) { /* have to back up */ lp_yy_cp = lp_yyg->lp_yy_last_accepting_cpos; lp_yy_current_state = lp_yyg->lp_yy_last_accepting_state; lp_yy_act = lp_yy_accept[lp_yy_current_state]; } YY_DO_BEFORE_ACTION; if ( lp_yy_act != YY_END_OF_BUFFER && lp_yy_rule_can_match_eol[lp_yy_act] ) { int lp_yyl; for ( lp_yyl = 0; lp_yyl < lp_yyleng; ++lp_yyl ) if ( lp_yytext[lp_yyl] == '\n' ) do{ lp_yylineno++; lp_yycolumn=0; }while(0) ; } do_action: /* This label is used only to access EOF actions. */ switch ( lp_yy_act ) { /* beginning of action switch */ case 0: /* must back up */ /* undo the effects of YY_DO_BEFORE_ACTION */ *lp_yy_cp = lp_yyg->lp_yy_hold_char; lp_yy_cp = lp_yyg->lp_yy_last_accepting_cpos; lp_yy_current_state = lp_yyg->lp_yy_last_accepting_state; goto lp_yy_find_action; case 1: YY_RULE_SETUP { BEGIN COMMENT; } /* begin skip comment */ YY_BREAK case 2: YY_RULE_SETUP { BEGIN INITIAL; } /* end skip comment */ YY_BREAK case 3: YY_RULE_SETUP { } YY_BREAK case 4: /* rule 4 can match eol */ YY_RULE_SETUP { } YY_BREAK case 5: YY_RULE_SETUP { } YY_BREAK case 6: YY_RULE_SETUP { BEGIN LINECOMMENT; } /* begin skip LINECOMMENT */ YY_BREAK case 7: /* rule 7 can match eol */ YY_RULE_SETUP { BEGIN INITIAL; } /* end skip LINECOMMENT */ YY_BREAK case 8: YY_RULE_SETUP { BEGIN INITIAL; } /* end skip LINECOMMENT */ YY_BREAK case 9: YY_RULE_SETUP { } YY_BREAK case 10: /* rule 10 can match eol */ YY_RULE_SETUP { } YY_BREAK case 11: YY_RULE_SETUP { parse_parm *pp = PARM; pp->lineno = lp_yylineno; return(COMMA); } YY_BREAK case 12: YY_RULE_SETUP { parse_parm *pp = PARM; pp->lineno = lp_yylineno; return(MINIMISE); } YY_BREAK case 13: YY_RULE_SETUP { parse_parm *pp = PARM; pp->lineno = lp_yylineno; return(MAXIMISE); } YY_BREAK case 14: YY_RULE_SETUP { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = lp_yylineno; pv->f = atof((char *)lp_yytext); return(INTCONS); } /* f contains the last float */ YY_BREAK case 15: YY_RULE_SETUP { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = lp_yylineno; pv->f = atof((char *)lp_yytext); return(CONS); } /* f contains the last float */ YY_BREAK case 16: /* rule 16 can match eol */ YY_RULE_SETUP { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; char *ptr, c; pp->lineno = lp_yylineno; pv->f = DEF_INFINITE; pv->Sign = 0; ptr = (char *)lp_yytext; while (isspace(*ptr)) ptr++; if(*ptr == '-') pv->Sign = 1; if(lp_yyleng > 0) { c = lp_yytext[lp_yyleng - 1]; if(!isalnum(c)) unput(c); } return(INF); } /* f contains the last float */ YY_BREAK case 17: /* rule 17 can match eol */ YY_RULE_SETUP { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; int x; pp->lineno = lp_yylineno; pv->Sign = 0; for(x = 0; x < lp_yyleng; x++) if(lp_yytext[x] == '-' || lp_yytext[x] == '+') pv->Sign = (pv->Sign == (lp_yytext[x] == '+')); return (TOK_SIGN); /* Sign is TRUE if the sign-string represents a '-'. Otherwise Sign is FALSE */ } YY_BREAK case 18: YY_RULE_SETUP { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = lp_yylineno; if((!pv->Within_int_decl) && (!pv->Within_sec_decl) && (!pv->Within_sos_decl) && (!pv->Within_free_decl)) { pv->Within_int_decl = 1; pv->Within_sos_decl1 = FALSE; } return(SEC_INT); } YY_BREAK case 19: YY_RULE_SETUP { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = lp_yylineno; if((!pv->Within_int_decl) && (!pv->Within_sec_decl) && (!pv->Within_sos_decl) && (!pv->Within_free_decl)) { pv->Within_int_decl = 2; pv->Within_sos_decl1 = FALSE; } return(SEC_BIN); } YY_BREAK case 20: YY_RULE_SETUP { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = lp_yylineno; if((!pv->Within_int_decl) && (!pv->Within_sec_decl) && (!pv->Within_sos_decl) && (!pv->Within_free_decl)) { pv->Within_sec_decl = TRUE; pv->Within_sos_decl1 = FALSE; } return(SEC_SEC); } YY_BREAK case 21: YY_RULE_SETUP { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = lp_yylineno; if(!pv->Within_sos_decl) pv->SOStype0 = (short)atoi(((char *)lp_yytext) + 3); if((!pv->Within_int_decl) && (!pv->Within_sec_decl) && (!pv->Within_sos_decl) && (!pv->Within_free_decl)) pv->Within_sos_decl = TRUE; return(SEC_SOS); } YY_BREAK case 22: YY_RULE_SETUP { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = lp_yylineno; FREE(pv->Last_var); pv->Last_var = strdup((char *)lp_yytext); pv->Last_var[strlen(pv->Last_var) - 2] = 0; return(SOSDESCR); } YY_BREAK case 23: YY_RULE_SETUP { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = lp_yylineno; if((!pv->Within_int_decl) && (!pv->Within_sec_decl) && (!pv->Within_sos_decl) && (!pv->Within_free_decl)) { pv->Within_free_decl = TRUE; pv->Within_sos_decl1 = FALSE; } return(SEC_FREE); } YY_BREAK case 24: YY_RULE_SETUP { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; char *ptr; pp->lineno = lp_yylineno; FREE(pv->Last_var); pv->Last_var = strdup((char *)lp_yytext); ptr = pv->Last_var + strlen(pv->Last_var); ptr[-1] = ' '; while ((--ptr >= pv->Last_var) && (isspace(*ptr))) *ptr = 0; return(VARIABLECOLON); } YY_BREAK case 25: YY_RULE_SETUP { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = lp_yylineno; FREE(pv->Last_var); pv->Last_var = strdup((char *)lp_yytext); return(VAR); } YY_BREAK case 26: YY_RULE_SETUP { parse_parm *pp = PARM; pp->lineno = lp_yylineno; return (COLON); } YY_BREAK case 27: YY_RULE_SETUP { parse_parm *pp = PARM; pp->lineno = lp_yylineno; return(AR_M_OP); } YY_BREAK case 28: YY_RULE_SETUP { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = lp_yylineno; pv->OP = *lp_yytext; return(RE_OPEQ); } YY_BREAK case 29: YY_RULE_SETUP { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = lp_yylineno; pv->OP = *lp_yytext; return(RE_OPLE); } YY_BREAK case 30: YY_RULE_SETUP { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = lp_yylineno; pv->OP = *lp_yytext; return(RE_OPGE); } YY_BREAK case 31: YY_RULE_SETUP { parse_parm *pp = PARM; parse_vars *pv = (parse_vars *) pp->parse_vars; pp->lineno = lp_yylineno; pv->Within_int_decl = pv->Within_sec_decl = pv->Within_sos_decl = pv->Within_free_decl = FALSE; check_int_sec_sos_free_decl(pp, (int) pv->Within_int_decl, (int) pv->Within_sec_decl, (int) pv->Within_sos_decl, (int) pv->Within_free_decl); return(END_C); } YY_BREAK case 32: YY_RULE_SETUP { parse_parm *pp = PARM; pp->lineno = lp_yylineno; report(NULL, CRITICAL, "LEX ERROR : %s lineno %d\n", lp_yytext, lp_yylineno); return(UNDEFINED); } YY_BREAK case 33: YY_RULE_SETUP ECHO; YY_BREAK case YY_STATE_EOF(INITIAL): case YY_STATE_EOF(COMMENT): case YY_STATE_EOF(LINECOMMENT): lp_yyterminate(); case YY_END_OF_BUFFER: { /* Amount of text matched not including the EOB char. */ int lp_yy_amount_of_matched_text = (int) (lp_yy_cp - lp_yyg->lp_yytext_ptr) - 1; /* Undo the effects of YY_DO_BEFORE_ACTION. */ *lp_yy_cp = lp_yyg->lp_yy_hold_char; YY_RESTORE_YY_MORE_OFFSET if ( YY_CURRENT_BUFFER_LVALUE->lp_yy_buffer_status == YY_BUFFER_NEW ) { /* We're scanning a new file or input source. It's * possible that this happened because the user * just pointed lp_yyin at a new source and called * lp_yylex(). If so, then we have to assure * consistency between YY_CURRENT_BUFFER and our * globals. Here is the right place to do so, because * this is the first action (other than possibly a * back-up) that will match for the new input source. */ lp_yyg->lp_yy_n_chars = YY_CURRENT_BUFFER_LVALUE->lp_yy_n_chars; YY_CURRENT_BUFFER_LVALUE->lp_yy_input_file = lp_yyin; YY_CURRENT_BUFFER_LVALUE->lp_yy_buffer_status = YY_BUFFER_NORMAL; } /* Note that here we test for lp_yy_c_buf_p "<=" to the position * of the first EOB in the buffer, since lp_yy_c_buf_p will * already have been incremented past the NUL character * (since all states make transitions on EOB to the * end-of-buffer state). Contrast this with the test * in input(). */ if ( lp_yyg->lp_yy_c_buf_p <= &YY_CURRENT_BUFFER_LVALUE->lp_yy_ch_buf[lp_yyg->lp_yy_n_chars] ) { /* This was really a NUL. */ lp_yy_state_type lp_yy_next_state; lp_yyg->lp_yy_c_buf_p = lp_yyg->lp_yytext_ptr + lp_yy_amount_of_matched_text; lp_yy_current_state = lp_yy_get_previous_state( lp_yyscanner ); /* Okay, we're now positioned to make the NUL * transition. We couldn't have * lp_yy_get_previous_state() go ahead and do it * for us because it doesn't know how to deal * with the possibility of jamming (and we don't * want to build jamming into it because then it * will run more slowly). */ lp_yy_next_state = lp_yy_try_NUL_trans( lp_yy_current_state , lp_yyscanner); lp_yy_bp = lp_yyg->lp_yytext_ptr + YY_MORE_ADJ; if ( lp_yy_next_state ) { /* Consume the NUL. */ lp_yy_cp = ++lp_yyg->lp_yy_c_buf_p; lp_yy_current_state = lp_yy_next_state; goto lp_yy_match; } else { lp_yy_cp = lp_yyg->lp_yy_c_buf_p; goto lp_yy_find_action; } } else switch ( lp_yy_get_next_buffer( lp_yyscanner ) ) { case EOB_ACT_END_OF_FILE: { lp_yyg->lp_yy_did_buffer_switch_on_eof = 0; if ( lp_yywrap(lp_yyscanner ) ) { /* Note: because we've taken care in * lp_yy_get_next_buffer() to have set up * lp_yytext, we can now set up * lp_yy_c_buf_p so that if some total * hoser (like flex itself) wants to * call the scanner after we return the * YY_NULL, it'll still work - another * YY_NULL will get returned. */ lp_yyg->lp_yy_c_buf_p = lp_yyg->lp_yytext_ptr + YY_MORE_ADJ; lp_yy_act = YY_STATE_EOF(YY_START); goto do_action; } else { if ( ! lp_yyg->lp_yy_did_buffer_switch_on_eof ) YY_NEW_FILE; } break; } case EOB_ACT_CONTINUE_SCAN: lp_yyg->lp_yy_c_buf_p = lp_yyg->lp_yytext_ptr + lp_yy_amount_of_matched_text; lp_yy_current_state = lp_yy_get_previous_state( lp_yyscanner ); lp_yy_cp = lp_yyg->lp_yy_c_buf_p; lp_yy_bp = lp_yyg->lp_yytext_ptr + YY_MORE_ADJ; goto lp_yy_match; case EOB_ACT_LAST_MATCH: lp_yyg->lp_yy_c_buf_p = &YY_CURRENT_BUFFER_LVALUE->lp_yy_ch_buf[lp_yyg->lp_yy_n_chars]; lp_yy_current_state = lp_yy_get_previous_state( lp_yyscanner ); lp_yy_cp = lp_yyg->lp_yy_c_buf_p; lp_yy_bp = lp_yyg->lp_yytext_ptr + YY_MORE_ADJ; goto lp_yy_find_action; } break; } default: YY_FATAL_ERROR( "fatal flex scanner internal error--no action found" ); } /* end of action switch */ } /* end of scanning one token */ } /* end of lp_yylex */ /* lp_yy_get_next_buffer - try to read in a new buffer * * Returns a code representing an action: * EOB_ACT_LAST_MATCH - * EOB_ACT_CONTINUE_SCAN - continue scanning from current position * EOB_ACT_END_OF_FILE - end of file */ static int lp_yy_get_next_buffer (lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; register char *dest = YY_CURRENT_BUFFER_LVALUE->lp_yy_ch_buf; register char *source = lp_yyg->lp_yytext_ptr; register int number_to_move, i; int ret_val; if ( lp_yyg->lp_yy_c_buf_p > &YY_CURRENT_BUFFER_LVALUE->lp_yy_ch_buf[lp_yyg->lp_yy_n_chars + 1] ) YY_FATAL_ERROR( "fatal flex scanner internal error--end of buffer missed" ); if ( YY_CURRENT_BUFFER_LVALUE->lp_yy_fill_buffer == 0 ) { /* Don't try to fill the buffer, so this is an EOF. */ if ( lp_yyg->lp_yy_c_buf_p - lp_yyg->lp_yytext_ptr - YY_MORE_ADJ == 1 ) { /* We matched a single character, the EOB, so * treat this as a final EOF. */ return EOB_ACT_END_OF_FILE; } else { /* We matched some text prior to the EOB, first * process it. */ return EOB_ACT_LAST_MATCH; } } /* Try to read more data. */ /* First move last chars to start of buffer. */ number_to_move = (int) (lp_yyg->lp_yy_c_buf_p - lp_yyg->lp_yytext_ptr) - 1; for ( i = 0; i < number_to_move; ++i ) *(dest++) = *(source++); if ( YY_CURRENT_BUFFER_LVALUE->lp_yy_buffer_status == YY_BUFFER_EOF_PENDING ) /* don't do the read, it's not guaranteed to return an EOF, * just force an EOF */ YY_CURRENT_BUFFER_LVALUE->lp_yy_n_chars = lp_yyg->lp_yy_n_chars = 0; else { int num_to_read = YY_CURRENT_BUFFER_LVALUE->lp_yy_buf_size - number_to_move - 1; while ( num_to_read <= 0 ) { /* Not enough room in the buffer - grow it. */ /* just a shorter name for the current buffer */ YY_BUFFER_STATE b = YY_CURRENT_BUFFER; int lp_yy_c_buf_p_offset = (int) (lp_yyg->lp_yy_c_buf_p - b->lp_yy_ch_buf); if ( b->lp_yy_is_our_buffer ) { int new_size = b->lp_yy_buf_size * 2; if ( new_size <= 0 ) b->lp_yy_buf_size += b->lp_yy_buf_size / 8; else b->lp_yy_buf_size *= 2; b->lp_yy_ch_buf = (char *) /* Include room in for 2 EOB chars. */ lp_yyrealloc((void *) b->lp_yy_ch_buf,b->lp_yy_buf_size + 2 ,lp_yyscanner ); } else /* Can't grow it, we don't own it. */ b->lp_yy_ch_buf = 0; if ( ! b->lp_yy_ch_buf ) YY_FATAL_ERROR( "fatal error - scanner input buffer overflow" ); lp_yyg->lp_yy_c_buf_p = &b->lp_yy_ch_buf[lp_yy_c_buf_p_offset]; num_to_read = YY_CURRENT_BUFFER_LVALUE->lp_yy_buf_size - number_to_move - 1; } if ( num_to_read > YY_READ_BUF_SIZE ) num_to_read = YY_READ_BUF_SIZE; /* Read in more data. */ YY_INPUT( (&YY_CURRENT_BUFFER_LVALUE->lp_yy_ch_buf[number_to_move]), lp_yyg->lp_yy_n_chars, (size_t) num_to_read ); YY_CURRENT_BUFFER_LVALUE->lp_yy_n_chars = lp_yyg->lp_yy_n_chars; } if ( lp_yyg->lp_yy_n_chars == 0 ) { if ( number_to_move == YY_MORE_ADJ ) { ret_val = EOB_ACT_END_OF_FILE; lp_yyrestart(lp_yyin ,lp_yyscanner); } else { ret_val = EOB_ACT_LAST_MATCH; YY_CURRENT_BUFFER_LVALUE->lp_yy_buffer_status = YY_BUFFER_EOF_PENDING; } } else ret_val = EOB_ACT_CONTINUE_SCAN; if ((lp_yy_size_t) (lp_yyg->lp_yy_n_chars + number_to_move) > YY_CURRENT_BUFFER_LVALUE->lp_yy_buf_size) { /* Extend the array by 50%, plus the number we really need. */ lp_yy_size_t new_size = lp_yyg->lp_yy_n_chars + number_to_move + (lp_yyg->lp_yy_n_chars >> 1); YY_CURRENT_BUFFER_LVALUE->lp_yy_ch_buf = (char *) lp_yyrealloc((void *) YY_CURRENT_BUFFER_LVALUE->lp_yy_ch_buf,new_size ,lp_yyscanner ); if ( ! YY_CURRENT_BUFFER_LVALUE->lp_yy_ch_buf ) YY_FATAL_ERROR( "out of dynamic memory in lp_yy_get_next_buffer()" ); } lp_yyg->lp_yy_n_chars += number_to_move; YY_CURRENT_BUFFER_LVALUE->lp_yy_ch_buf[lp_yyg->lp_yy_n_chars] = YY_END_OF_BUFFER_CHAR; YY_CURRENT_BUFFER_LVALUE->lp_yy_ch_buf[lp_yyg->lp_yy_n_chars + 1] = YY_END_OF_BUFFER_CHAR; lp_yyg->lp_yytext_ptr = &YY_CURRENT_BUFFER_LVALUE->lp_yy_ch_buf[0]; return ret_val; } /* lp_yy_get_previous_state - get the state just before the EOB char was reached */ static lp_yy_state_type lp_yy_get_previous_state (lp_yyscan_t lp_yyscanner) { register lp_yy_state_type lp_yy_current_state; register char *lp_yy_cp; struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; lp_yy_current_state = lp_yyg->lp_yy_start; lp_yy_current_state += YY_AT_BOL(); for ( lp_yy_cp = lp_yyg->lp_yytext_ptr + YY_MORE_ADJ; lp_yy_cp < lp_yyg->lp_yy_c_buf_p; ++lp_yy_cp ) { register YY_CHAR lp_yy_c = (*lp_yy_cp ? lp_yy_ec[YY_SC_TO_UI(*lp_yy_cp)] : 1); if ( lp_yy_accept[lp_yy_current_state] ) { lp_yyg->lp_yy_last_accepting_state = lp_yy_current_state; lp_yyg->lp_yy_last_accepting_cpos = lp_yy_cp; } while ( lp_yy_chk[lp_yy_base[lp_yy_current_state] + lp_yy_c] != lp_yy_current_state ) { lp_yy_current_state = (int) lp_yy_def[lp_yy_current_state]; if ( lp_yy_current_state >= 144 ) lp_yy_c = lp_yy_meta[(unsigned int) lp_yy_c]; } lp_yy_current_state = lp_yy_nxt[lp_yy_base[lp_yy_current_state] + (unsigned int) lp_yy_c]; } return lp_yy_current_state; } /* lp_yy_try_NUL_trans - try to make a transition on the NUL character * * synopsis * next_state = lp_yy_try_NUL_trans( current_state ); */ static lp_yy_state_type lp_yy_try_NUL_trans (lp_yy_state_type lp_yy_current_state , lp_yyscan_t lp_yyscanner) { register int lp_yy_is_jam; struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; /* This var may be unused depending upon options. */ register char *lp_yy_cp = lp_yyg->lp_yy_c_buf_p; register YY_CHAR lp_yy_c = 1; if ( lp_yy_accept[lp_yy_current_state] ) { lp_yyg->lp_yy_last_accepting_state = lp_yy_current_state; lp_yyg->lp_yy_last_accepting_cpos = lp_yy_cp; } while ( lp_yy_chk[lp_yy_base[lp_yy_current_state] + lp_yy_c] != lp_yy_current_state ) { lp_yy_current_state = (int) lp_yy_def[lp_yy_current_state]; if ( lp_yy_current_state >= 144 ) lp_yy_c = lp_yy_meta[(unsigned int) lp_yy_c]; } lp_yy_current_state = lp_yy_nxt[lp_yy_base[lp_yy_current_state] + (unsigned int) lp_yy_c]; lp_yy_is_jam = (lp_yy_current_state == 143); return lp_yy_is_jam ? 0 : lp_yy_current_state; } static void lp_yyunput (int c, register char * lp_yy_bp , lp_yyscan_t lp_yyscanner) { register char *lp_yy_cp; struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; lp_yy_cp = lp_yyg->lp_yy_c_buf_p; /* undo effects of setting up lp_yytext */ *lp_yy_cp = lp_yyg->lp_yy_hold_char; if ( lp_yy_cp < YY_CURRENT_BUFFER_LVALUE->lp_yy_ch_buf + 2 ) { /* need to shift things up to make room */ /* +2 for EOB chars. */ register int number_to_move = lp_yyg->lp_yy_n_chars + 2; register char *dest = &YY_CURRENT_BUFFER_LVALUE->lp_yy_ch_buf[ YY_CURRENT_BUFFER_LVALUE->lp_yy_buf_size + 2]; register char *source = &YY_CURRENT_BUFFER_LVALUE->lp_yy_ch_buf[number_to_move]; while ( source > YY_CURRENT_BUFFER_LVALUE->lp_yy_ch_buf ) *--dest = *--source; lp_yy_cp += (int) (dest - source); lp_yy_bp += (int) (dest - source); YY_CURRENT_BUFFER_LVALUE->lp_yy_n_chars = lp_yyg->lp_yy_n_chars = YY_CURRENT_BUFFER_LVALUE->lp_yy_buf_size; if ( lp_yy_cp < YY_CURRENT_BUFFER_LVALUE->lp_yy_ch_buf + 2 ) YY_FATAL_ERROR( "flex scanner push-back overflow" ); } *--lp_yy_cp = (char) c; if ( c == '\n' ){ --lp_yylineno; } lp_yyg->lp_yytext_ptr = lp_yy_bp; lp_yyg->lp_yy_hold_char = *lp_yy_cp; lp_yyg->lp_yy_c_buf_p = lp_yy_cp; } #ifndef YY_NO_INPUT #ifdef __cplusplus static int lp_yyinput (lp_yyscan_t lp_yyscanner) #else static int input (lp_yyscan_t lp_yyscanner) #endif { int c; struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; *lp_yyg->lp_yy_c_buf_p = lp_yyg->lp_yy_hold_char; if ( *lp_yyg->lp_yy_c_buf_p == YY_END_OF_BUFFER_CHAR ) { /* lp_yy_c_buf_p now points to the character we want to return. * If this occurs *before* the EOB characters, then it's a * valid NUL; if not, then we've hit the end of the buffer. */ if ( lp_yyg->lp_yy_c_buf_p < &YY_CURRENT_BUFFER_LVALUE->lp_yy_ch_buf[lp_yyg->lp_yy_n_chars] ) /* This was really a NUL. */ *lp_yyg->lp_yy_c_buf_p = '\0'; else { /* need more input */ int offset = lp_yyg->lp_yy_c_buf_p - lp_yyg->lp_yytext_ptr; ++lp_yyg->lp_yy_c_buf_p; switch ( lp_yy_get_next_buffer( lp_yyscanner ) ) { case EOB_ACT_LAST_MATCH: /* This happens because lp_yy_g_n_b() * sees that we've accumulated a * token and flags that we need to * try matching the token before * proceeding. But for input(), * there's no matching to consider. * So convert the EOB_ACT_LAST_MATCH * to EOB_ACT_END_OF_FILE. */ /* Reset buffer status. */ lp_yyrestart(lp_yyin ,lp_yyscanner); /*FALLTHROUGH*/ case EOB_ACT_END_OF_FILE: { if ( lp_yywrap(lp_yyscanner ) ) return EOF; if ( ! lp_yyg->lp_yy_did_buffer_switch_on_eof ) YY_NEW_FILE; #ifdef __cplusplus return lp_yyinput(lp_yyscanner); #else return input(lp_yyscanner); #endif } case EOB_ACT_CONTINUE_SCAN: lp_yyg->lp_yy_c_buf_p = lp_yyg->lp_yytext_ptr + offset; break; } } } c = *(unsigned char *) lp_yyg->lp_yy_c_buf_p; /* cast for 8-bit char's */ *lp_yyg->lp_yy_c_buf_p = '\0'; /* preserve lp_yytext */ lp_yyg->lp_yy_hold_char = *++lp_yyg->lp_yy_c_buf_p; YY_CURRENT_BUFFER_LVALUE->lp_yy_at_bol = (c == '\n'); if ( YY_CURRENT_BUFFER_LVALUE->lp_yy_at_bol ) do{ lp_yylineno++; lp_yycolumn=0; }while(0) ; return c; } #endif /* ifndef YY_NO_INPUT */ /** Immediately switch to a different input stream. * @param input_file A readable stream. * @param lp_yyscanner The scanner object. * @note This function does not reset the start condition to @c INITIAL . */ void lp_yyrestart (FILE * input_file , lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; if ( ! YY_CURRENT_BUFFER ){ lp_yyensure_buffer_stack (lp_yyscanner); YY_CURRENT_BUFFER_LVALUE = lp_yy_create_buffer(lp_yyin,YY_BUF_SIZE ,lp_yyscanner); } lp_yy_init_buffer(YY_CURRENT_BUFFER,input_file ,lp_yyscanner); lp_yy_load_buffer_state(lp_yyscanner ); } /** Switch to a different input buffer. * @param new_buffer The new input buffer. * @param lp_yyscanner The scanner object. */ void lp_yy_switch_to_buffer (YY_BUFFER_STATE new_buffer , lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; /* TODO. We should be able to replace this entire function body * with * lp_yypop_buffer_state(); * lp_yypush_buffer_state(new_buffer); */ lp_yyensure_buffer_stack (lp_yyscanner); if ( YY_CURRENT_BUFFER == new_buffer ) return; if ( YY_CURRENT_BUFFER ) { /* Flush out information for old buffer. */ *lp_yyg->lp_yy_c_buf_p = lp_yyg->lp_yy_hold_char; YY_CURRENT_BUFFER_LVALUE->lp_yy_buf_pos = lp_yyg->lp_yy_c_buf_p; YY_CURRENT_BUFFER_LVALUE->lp_yy_n_chars = lp_yyg->lp_yy_n_chars; } YY_CURRENT_BUFFER_LVALUE = new_buffer; lp_yy_load_buffer_state(lp_yyscanner ); /* We don't actually know whether we did this switch during * EOF (lp_yywrap()) processing, but the only time this flag * is looked at is after lp_yywrap() is called, so it's safe * to go ahead and always set it. */ lp_yyg->lp_yy_did_buffer_switch_on_eof = 1; } static void lp_yy_load_buffer_state (lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; lp_yyg->lp_yy_n_chars = YY_CURRENT_BUFFER_LVALUE->lp_yy_n_chars; lp_yyg->lp_yytext_ptr = lp_yyg->lp_yy_c_buf_p = YY_CURRENT_BUFFER_LVALUE->lp_yy_buf_pos; lp_yyin = YY_CURRENT_BUFFER_LVALUE->lp_yy_input_file; lp_yyg->lp_yy_hold_char = *lp_yyg->lp_yy_c_buf_p; } /** Allocate and initialize an input buffer state. * @param file A readable stream. * @param size The character buffer size in bytes. When in doubt, use @c YY_BUF_SIZE. * @param lp_yyscanner The scanner object. * @return the allocated buffer state. */ YY_BUFFER_STATE lp_yy_create_buffer (FILE * file, int size , lp_yyscan_t lp_yyscanner) { YY_BUFFER_STATE b; b = (YY_BUFFER_STATE) lp_yyalloc(sizeof( struct lp_yy_buffer_state ) ,lp_yyscanner ); if ( ! b ) YY_FATAL_ERROR( "out of dynamic memory in lp_yy_create_buffer()" ); b->lp_yy_buf_size = size; /* lp_yy_ch_buf has to be 2 characters longer than the size given because * we need to put in 2 end-of-buffer characters. */ b->lp_yy_ch_buf = (char *) lp_yyalloc(b->lp_yy_buf_size + 2 ,lp_yyscanner ); if ( ! b->lp_yy_ch_buf ) YY_FATAL_ERROR( "out of dynamic memory in lp_yy_create_buffer()" ); b->lp_yy_is_our_buffer = 1; lp_yy_init_buffer(b,file ,lp_yyscanner); return b; } /** Destroy the buffer. * @param b a buffer created with lp_yy_create_buffer() * @param lp_yyscanner The scanner object. */ void lp_yy_delete_buffer (YY_BUFFER_STATE b , lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; if ( ! b ) return; if ( b == YY_CURRENT_BUFFER ) /* Not sure if we should pop here. */ YY_CURRENT_BUFFER_LVALUE = (YY_BUFFER_STATE) 0; if ( b->lp_yy_is_our_buffer ) lp_yyfree((void *) b->lp_yy_ch_buf ,lp_yyscanner ); lp_yyfree((void *) b ,lp_yyscanner ); } #ifndef __cplusplus extern int isatty (int ); #endif /* __cplusplus */ /* Initializes or reinitializes a buffer. * This function is sometimes called more than once on the same buffer, * such as during a lp_yyrestart() or at EOF. */ static void lp_yy_init_buffer (YY_BUFFER_STATE b, FILE * file , lp_yyscan_t lp_yyscanner) { int oerrno = errno; struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; lp_yy_flush_buffer(b ,lp_yyscanner); b->lp_yy_input_file = file; b->lp_yy_fill_buffer = 1; /* If b is the current buffer, then lp_yy_init_buffer was _probably_ * called from lp_yyrestart() or through lp_yy_get_next_buffer. * In that case, we don't want to reset the lineno or column. */ if (b != YY_CURRENT_BUFFER){ b->lp_yy_bs_lineno = 1; b->lp_yy_bs_column = 0; } b->lp_yy_is_interactive = file ? (isatty( fileno(file) ) > 0) : 0; errno = oerrno; } /** Discard all buffered characters. On the next scan, YY_INPUT will be called. * @param b the buffer state to be flushed, usually @c YY_CURRENT_BUFFER. * @param lp_yyscanner The scanner object. */ void lp_yy_flush_buffer (YY_BUFFER_STATE b , lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; if ( ! b ) return; b->lp_yy_n_chars = 0; /* We always need two end-of-buffer characters. The first causes * a transition to the end-of-buffer state. The second causes * a jam in that state. */ b->lp_yy_ch_buf[0] = YY_END_OF_BUFFER_CHAR; b->lp_yy_ch_buf[1] = YY_END_OF_BUFFER_CHAR; b->lp_yy_buf_pos = &b->lp_yy_ch_buf[0]; b->lp_yy_at_bol = 1; b->lp_yy_buffer_status = YY_BUFFER_NEW; if ( b == YY_CURRENT_BUFFER ) lp_yy_load_buffer_state(lp_yyscanner ); } /** Pushes the new state onto the stack. The new state becomes * the current state. This function will allocate the stack * if necessary. * @param new_buffer The new state. * @param lp_yyscanner The scanner object. */ void lp_yypush_buffer_state (YY_BUFFER_STATE new_buffer , lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; if (new_buffer == NULL) return; lp_yyensure_buffer_stack(lp_yyscanner); /* This block is copied from lp_yy_switch_to_buffer. */ if ( YY_CURRENT_BUFFER ) { /* Flush out information for old buffer. */ *lp_yyg->lp_yy_c_buf_p = lp_yyg->lp_yy_hold_char; YY_CURRENT_BUFFER_LVALUE->lp_yy_buf_pos = lp_yyg->lp_yy_c_buf_p; YY_CURRENT_BUFFER_LVALUE->lp_yy_n_chars = lp_yyg->lp_yy_n_chars; } /* Only push if top exists. Otherwise, replace top. */ if (YY_CURRENT_BUFFER) lp_yyg->lp_yy_buffer_stack_top++; YY_CURRENT_BUFFER_LVALUE = new_buffer; /* copied from lp_yy_switch_to_buffer. */ lp_yy_load_buffer_state(lp_yyscanner ); lp_yyg->lp_yy_did_buffer_switch_on_eof = 1; } /** Removes and deletes the top of the stack, if present. * The next element becomes the new top. * @param lp_yyscanner The scanner object. */ void lp_yypop_buffer_state (lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; if (!YY_CURRENT_BUFFER) return; lp_yy_delete_buffer(YY_CURRENT_BUFFER ,lp_yyscanner); YY_CURRENT_BUFFER_LVALUE = NULL; if (lp_yyg->lp_yy_buffer_stack_top > 0) --lp_yyg->lp_yy_buffer_stack_top; if (YY_CURRENT_BUFFER) { lp_yy_load_buffer_state(lp_yyscanner ); lp_yyg->lp_yy_did_buffer_switch_on_eof = 1; } } /* Allocates the stack if it does not exist. * Guarantees space for at least one push. */ static void lp_yyensure_buffer_stack (lp_yyscan_t lp_yyscanner) { int num_to_alloc; struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; if (!lp_yyg->lp_yy_buffer_stack) { /* First allocation is just for 2 elements, since we don't know if this * scanner will even need a stack. We use 2 instead of 1 to avoid an * immediate realloc on the next call. */ num_to_alloc = 1; lp_yyg->lp_yy_buffer_stack = (struct lp_yy_buffer_state**)lp_yyalloc (num_to_alloc * sizeof(struct lp_yy_buffer_state*) , lp_yyscanner); if ( ! lp_yyg->lp_yy_buffer_stack ) YY_FATAL_ERROR( "out of dynamic memory in lp_yyensure_buffer_stack()" ); memset(lp_yyg->lp_yy_buffer_stack, 0, num_to_alloc * sizeof(struct lp_yy_buffer_state*)); lp_yyg->lp_yy_buffer_stack_max = num_to_alloc; lp_yyg->lp_yy_buffer_stack_top = 0; return; } if (lp_yyg->lp_yy_buffer_stack_top >= (lp_yyg->lp_yy_buffer_stack_max) - 1){ /* Increase the buffer to prepare for a possible push. */ int grow_size = 8 /* arbitrary grow size */; num_to_alloc = lp_yyg->lp_yy_buffer_stack_max + grow_size; lp_yyg->lp_yy_buffer_stack = (struct lp_yy_buffer_state**)lp_yyrealloc (lp_yyg->lp_yy_buffer_stack, num_to_alloc * sizeof(struct lp_yy_buffer_state*) , lp_yyscanner); if ( ! lp_yyg->lp_yy_buffer_stack ) YY_FATAL_ERROR( "out of dynamic memory in lp_yyensure_buffer_stack()" ); /* zero only the new slots.*/ memset(lp_yyg->lp_yy_buffer_stack + lp_yyg->lp_yy_buffer_stack_max, 0, grow_size * sizeof(struct lp_yy_buffer_state*)); lp_yyg->lp_yy_buffer_stack_max = num_to_alloc; } } /** Setup the input buffer state to scan directly from a user-specified character buffer. * @param base the character buffer * @param size the size in bytes of the character buffer * @param lp_yyscanner The scanner object. * @return the newly allocated buffer state object. */ YY_BUFFER_STATE lp_yy_scan_buffer (char * base, lp_yy_size_t size , lp_yyscan_t lp_yyscanner) { YY_BUFFER_STATE b; if ( size < 2 || base[size-2] != YY_END_OF_BUFFER_CHAR || base[size-1] != YY_END_OF_BUFFER_CHAR ) /* They forgot to leave room for the EOB's. */ return 0; b = (YY_BUFFER_STATE) lp_yyalloc(sizeof( struct lp_yy_buffer_state ) ,lp_yyscanner ); if ( ! b ) YY_FATAL_ERROR( "out of dynamic memory in lp_yy_scan_buffer()" ); b->lp_yy_buf_size = size - 2; /* "- 2" to take care of EOB's */ b->lp_yy_buf_pos = b->lp_yy_ch_buf = base; b->lp_yy_is_our_buffer = 0; b->lp_yy_input_file = 0; b->lp_yy_n_chars = b->lp_yy_buf_size; b->lp_yy_is_interactive = 0; b->lp_yy_at_bol = 1; b->lp_yy_fill_buffer = 0; b->lp_yy_buffer_status = YY_BUFFER_NEW; lp_yy_switch_to_buffer(b ,lp_yyscanner ); return b; } /** Setup the input buffer state to scan a string. The next call to lp_yylex() will * scan from a @e copy of @a str. * @param lp_yystr a NUL-terminated string to scan * @param lp_yyscanner The scanner object. * @return the newly allocated buffer state object. * @note If you want to scan bytes that may contain NUL values, then use * lp_yy_scan_bytes() instead. */ YY_BUFFER_STATE lp_yy_scan_string (lp_yyconst char * lp_yystr , lp_yyscan_t lp_yyscanner) { return lp_yy_scan_bytes(lp_yystr,strlen(lp_yystr) ,lp_yyscanner); } /** Setup the input buffer state to scan the given bytes. The next call to lp_yylex() will * scan from a @e copy of @a bytes. * @param bytes the byte buffer to scan * @param len the number of bytes in the buffer pointed to by @a bytes. * @param lp_yyscanner The scanner object. * @return the newly allocated buffer state object. */ YY_BUFFER_STATE lp_yy_scan_bytes (lp_yyconst char * lp_yybytes, int _lp_yybytes_len , lp_yyscan_t lp_yyscanner) { YY_BUFFER_STATE b; char *buf; lp_yy_size_t n; int i; /* Get memory for full buffer, including space for trailing EOB's. */ n = _lp_yybytes_len + 2; buf = (char *) lp_yyalloc(n ,lp_yyscanner ); if ( ! buf ) YY_FATAL_ERROR( "out of dynamic memory in lp_yy_scan_bytes()" ); for ( i = 0; i < _lp_yybytes_len; ++i ) buf[i] = lp_yybytes[i]; buf[_lp_yybytes_len] = buf[_lp_yybytes_len+1] = YY_END_OF_BUFFER_CHAR; b = lp_yy_scan_buffer(buf,n ,lp_yyscanner); if ( ! b ) YY_FATAL_ERROR( "bad buffer in lp_yy_scan_bytes()" ); /* It's okay to grow etc. this buffer, and we should throw it * away when we're done. */ b->lp_yy_is_our_buffer = 1; return b; } #ifndef YY_EXIT_FAILURE #define YY_EXIT_FAILURE 2 #endif static void lp_yy_fatal_error (lp_yyconst char* msg , lp_yyscan_t lp_yyscanner) { (void) fprintf( stderr, "%s\n", msg ); exit( YY_EXIT_FAILURE ); } /* Redefine lp_yyless() so it works in section 3 code. */ #undef lp_yyless #define lp_yyless(n) \ do \ { \ /* Undo effects of setting up lp_yytext. */ \ int lp_yyless_macro_arg = (n); \ YY_LESS_LINENO(lp_yyless_macro_arg);\ lp_yytext[lp_yyleng] = lp_yyg->lp_yy_hold_char; \ lp_yyg->lp_yy_c_buf_p = lp_yytext + lp_yyless_macro_arg; \ lp_yyg->lp_yy_hold_char = *lp_yyg->lp_yy_c_buf_p; \ *lp_yyg->lp_yy_c_buf_p = '\0'; \ lp_yyleng = lp_yyless_macro_arg; \ } \ while ( 0 ) /* Accessor methods (get/set functions) to struct members. */ /** Get the user-defined data for this scanner. * @param lp_yyscanner The scanner object. */ YY_EXTRA_TYPE lp_yyget_extra (lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; return lp_yyextra; } /** Get the current line number. * @param lp_yyscanner The scanner object. */ int lp_yyget_lineno (lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; if (! YY_CURRENT_BUFFER) return 0; return lp_yylineno; } /** Get the current column number. * @param lp_yyscanner The scanner object. */ int lp_yyget_column (lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; if (! YY_CURRENT_BUFFER) return 0; return lp_yycolumn; } /** Get the input stream. * @param lp_yyscanner The scanner object. */ FILE *lp_yyget_in (lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; return lp_yyin; } /** Get the output stream. * @param lp_yyscanner The scanner object. */ FILE *lp_yyget_out (lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; return lp_yyout; } /** Get the length of the current token. * @param lp_yyscanner The scanner object. */ int lp_yyget_leng (lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; return lp_yyleng; } /** Get the current token. * @param lp_yyscanner The scanner object. */ char *lp_yyget_text (lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; return lp_yytext; } /** Set the user-defined data. This data is never touched by the scanner. * @param user_defined The data to be associated with this scanner. * @param lp_yyscanner The scanner object. */ void lp_yyset_extra (YY_EXTRA_TYPE user_defined , lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; lp_yyextra = user_defined ; } /** Set the current line number. * @param line_number * @param lp_yyscanner The scanner object. */ void lp_yyset_lineno (int line_number , lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; /* lineno is only valid if an input buffer exists. */ if (! YY_CURRENT_BUFFER ) lp_yy_fatal_error( "lp_yyset_lineno called with no buffer" , lp_yyscanner); lp_yylineno = line_number; } /** Set the current column. * @param line_number * @param lp_yyscanner The scanner object. */ void lp_yyset_column (int column_no , lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; /* column is only valid if an input buffer exists. */ if (! YY_CURRENT_BUFFER ) lp_yy_fatal_error( "lp_yyset_column called with no buffer" , lp_yyscanner); lp_yycolumn = column_no; } /** Set the input stream. This does not discard the current * input buffer. * @param in_str A readable stream. * @param lp_yyscanner The scanner object. * @see lp_yy_switch_to_buffer */ void lp_yyset_in (FILE * in_str , lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; lp_yyin = in_str ; } void lp_yyset_out (FILE * out_str , lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; lp_yyout = out_str ; } int lp_yyget_debug (lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; return lp_yy_flex_debug; } void lp_yyset_debug (int bdebug , lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; lp_yy_flex_debug = bdebug ; } /* Accessor methods for lp_yylval and lp_yylloc */ YYSTYPE * lp_yyget_lval (lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; return lp_yylval; } void lp_yyset_lval (YYSTYPE * lp_yylval_param , lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; lp_yylval = lp_yylval_param; } /* User-visible API */ /* lp_yylex_init is special because it creates the scanner itself, so it is * the ONLY reentrant function that doesn't take the scanner as the last argument. * That's why we explicitly handle the declaration, instead of using our macros. */ int lp_yylex_init(lp_yyscan_t* ptr_lp_yy_globals) { if (ptr_lp_yy_globals == NULL){ errno = EINVAL; return 1; } *ptr_lp_yy_globals = (lp_yyscan_t) lp_yyalloc ( sizeof( struct lp_yyguts_t ), NULL ); if (*ptr_lp_yy_globals == NULL){ errno = ENOMEM; return 1; } /* By setting to 0xAA, we expose bugs in lp_yy_init_globals. Leave at 0x00 for releases. */ memset(*ptr_lp_yy_globals,0x00,sizeof(struct lp_yyguts_t)); return lp_yy_init_globals ( *ptr_lp_yy_globals ); } /* lp_yylex_init_extra has the same functionality as lp_yylex_init, but follows the * convention of taking the scanner as the last argument. Note however, that * this is a *pointer* to a scanner, as it will be allocated by this call (and * is the reason, too, why this function also must handle its own declaration). * The user defined value in the first argument will be available to lp_yyalloc in * the lp_yyextra field. */ int lp_yylex_init_extra(YY_EXTRA_TYPE lp_yy_user_defined,lp_yyscan_t* ptr_lp_yy_globals ) { struct lp_yyguts_t dummy_lp_yyguts; lp_yyset_extra (lp_yy_user_defined, &dummy_lp_yyguts); if (ptr_lp_yy_globals == NULL){ errno = EINVAL; return 1; } *ptr_lp_yy_globals = (lp_yyscan_t) lp_yyalloc ( sizeof( struct lp_yyguts_t ), &dummy_lp_yyguts ); if (*ptr_lp_yy_globals == NULL){ errno = ENOMEM; return 1; } /* By setting to 0xAA, we expose bugs in lp_yy_init_globals. Leave at 0x00 for releases. */ memset(*ptr_lp_yy_globals,0x00,sizeof(struct lp_yyguts_t)); lp_yyset_extra (lp_yy_user_defined, *ptr_lp_yy_globals); return lp_yy_init_globals ( *ptr_lp_yy_globals ); } static int lp_yy_init_globals (lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; /* Initialization is the same as for the non-reentrant scanner. * This function is called from lp_yylex_destroy(), so don't allocate here. */ lp_yyg->lp_yy_buffer_stack = 0; lp_yyg->lp_yy_buffer_stack_top = 0; lp_yyg->lp_yy_buffer_stack_max = 0; lp_yyg->lp_yy_c_buf_p = (char *) 0; lp_yyg->lp_yy_init = 0; lp_yyg->lp_yy_start = 0; lp_yyg->lp_yy_start_stack_ptr = 0; lp_yyg->lp_yy_start_stack_depth = 0; lp_yyg->lp_yy_start_stack = NULL; /* Defined in main.c */ #ifdef YY_STDINIT lp_yyin = stdin; lp_yyout = stdout; #else lp_yyin = (FILE *) 0; lp_yyout = (FILE *) 0; #endif /* For future reference: Set errno on error, since we are called by * lp_yylex_init() */ return 0; } /* lp_yylex_destroy is for both reentrant and non-reentrant scanners. */ int lp_yylex_destroy (lp_yyscan_t lp_yyscanner) { struct lp_yyguts_t * lp_yyg = (struct lp_yyguts_t*)lp_yyscanner; /* Pop the buffer stack, destroying each element. */ while(YY_CURRENT_BUFFER){ lp_yy_delete_buffer(YY_CURRENT_BUFFER ,lp_yyscanner ); YY_CURRENT_BUFFER_LVALUE = NULL; lp_yypop_buffer_state(lp_yyscanner); } /* Destroy the stack itself. */ lp_yyfree(lp_yyg->lp_yy_buffer_stack ,lp_yyscanner); lp_yyg->lp_yy_buffer_stack = NULL; /* Destroy the start condition stack. */ lp_yyfree(lp_yyg->lp_yy_start_stack ,lp_yyscanner ); lp_yyg->lp_yy_start_stack = NULL; /* Reset the globals. This is important in a non-reentrant scanner so the next time * lp_yylex() is called, initialization will occur. */ lp_yy_init_globals( lp_yyscanner); /* Destroy the main struct (reentrant only). */ lp_yyfree ( lp_yyscanner , lp_yyscanner ); lp_yyscanner = NULL; return 0; } /* * Internal utility routines. */ #ifndef lp_yytext_ptr static void lp_yy_flex_strncpy (char* s1, lp_yyconst char * s2, int n , lp_yyscan_t lp_yyscanner) { register int i; for ( i = 0; i < n; ++i ) s1[i] = s2[i]; } #endif #ifdef YY_NEED_STRLEN static int lp_yy_flex_strlen (lp_yyconst char * s , lp_yyscan_t lp_yyscanner) { register int n; for ( n = 0; s[n]; ++n ) ; return n; } #endif void *lp_yyalloc (lp_yy_size_t size , lp_yyscan_t lp_yyscanner) { return (void *) malloc( size ); } void *lp_yyrealloc (void * ptr, lp_yy_size_t size , lp_yyscan_t lp_yyscanner) { /* The cast to (char *) in the following accommodates both * implementations that use char* generic pointers, and those * that use void* generic pointers. It works with the latter * because both ANSI C and C++ allow castless assignment from * any pointer type to void*, and deal with argument conversions * as though doing an assignment. */ return (void *) realloc( (char *) ptr, size ); } void lp_yyfree (void * ptr , lp_yyscan_t lp_yyscanner) { free( (char *) ptr ); /* see lp_yyrealloc() for (char *) cast */ } #define YYTABLES_NAME "lp_yytables" MSVMpack1.2/lp_solve_5.5/lp_solve.def0000664000175000017500000001041411127446346016451 0ustar lauerlauerEXPORTS add_SOS add_column add_columnex add_constraint add_constraintex add_lag_con column_in_lp copy_lp default_basis del_column del_constraint delete_lp dualize_lp free_lp get_Lrows get_Ncolumns get_Norig_columns get_Norig_rows get_Nrows get_pseudocosts get_anti_degen get_basis get_basiscrash get_bb_depthlimit get_bb_floorfirst get_bb_rule get_bounds_tighter get_break_at_value get_col_name get_column get_columnex get_constr_type get_constr_value get_constraints get_dual_solution get_epsb get_epsd get_epsel get_epsint get_epsperturb get_epspivot get_improve get_infinite get_lambda get_lowbo get_lp_index get_lp_name get_mat get_mat_byindex get_max_level get_maxpivot get_mip_gap get_multiprice get_nameindex get_negrange get_nonzeros get_obj_bound get_objective get_orig_index get_origcol_name get_origrow_name get_partialprice get_pivoting get_presolve get_presolveloops get_primal_solution get_print_sol get_ptr_constraints get_ptr_dual_solution get_ptr_lambda get_ptr_primal_solution get_ptr_sensitivity_obj get_ptr_sensitivity_objex get_ptr_sensitivity_rhs get_ptr_variables get_rh get_rh_range get_row get_rowex get_row_name get_scalelimit get_scaling get_sensitivity_obj get_sensitivity_objex get_sensitivity_rhs get_simplextype get_solutioncount get_solutionlimit get_status get_statustext get_timeout get_total_iter get_total_nodes get_upbo get_var_branch get_var_dualresult get_var_primalresult get_var_priority get_variables get_verbose get_working_objective guess_basis has_BFP has_XLI is_SOS_var is_add_rowmode is_anti_degen is_binary is_break_at_first is_constr_type is_debug is_feasible is_unbounded is_infinite is_int is_integerscaling is_lag_trace is_maxim is_nativeBFP is_nativeXLI is_negative is_obj_in_basis is_piv_mode is_piv_rule is_presolve is_scalemode is_scaletype is_semicont is_trace is_use_names lp_solve_version make_lp print_constraints print_debugdump print_duals print_lp print_objective print_scales print_solution print_str print_tableau put_abortfunc put_bb_nodefunc put_bb_branchfunc put_logfunc put_msgfunc read_LP read_MPS read_XLI read_freeMPS read_freemps read_lp read_lpex read_mps read_basis read_params reset_basis reset_params resize_lp set_BFP set_pseudocosts set_XLI set_add_rowmode set_anti_degen set_basis set_basiscrash set_basisvar set_bb_depthlimit set_bb_floorfirst set_bb_rule set_binary set_bounds set_bounds_tighter set_break_at_first set_break_at_value set_col_name set_column set_columnex set_constr_type set_debug set_epsb set_epsd set_epsel set_epsint set_epslevel set_epsperturb set_epspivot set_unbounded set_improve set_infinite set_int set_lag_trace set_lowbo set_lp_name set_mat set_maxim set_maxpivot set_minim set_mip_gap set_multiprice set_negrange set_obj set_obj_bound set_obj_fn set_obj_fnex set_obj_in_basis set_outputfile set_outputstream set_partialprice set_pivoting set_preferdual set_presolve set_print_sol set_rh set_rh_range set_rh_vec set_row set_row_name set_rowex set_scalelimit set_scaling set_semicont set_sense set_simplextype set_solutionlimit set_timeout set_trace set_upbo set_use_names set_var_branch set_var_weights set_verbose solve str_add_column str_add_constraint str_add_lag_con str_set_obj_fn str_set_rh_vec time_elapsed unscale write_LP write_MPS write_XLI write_freeMPS write_freemps MPS_writefileex write_lp write_lpex write_mps write_basis write_params MSVMpack1.2/lp_solve_5.5/lp_solveDLL.h0000664000175000017500000000141111250516360016462 0ustar lauerlauer// stdafx.h : include file for standard system include files, // or project specific include files that are used frequently, but // are changed infrequently // #if !defined(AFX_STDAFX_H__22BF6D92_917F_4BDF_B806_0954721EBA95__INCLUDED_) #define AFX_STDAFX_H__22BF6D92_917F_4BDF_B806_0954721EBA95__INCLUDED_ #if _MSC_VER > 1000 #pragma once #endif // _MSC_VER > 1000 // Insert your headers here #define WIN32_LEAN_AND_MEAN // Exclude rarely-used stuff from Windows headers #include // TODO: reference additional headers your program requires here //{{AFX_INSERT_LOCATION}} // Microsoft Visual C++ will insert additional declarations immediately before the previous line. #endif // !defined(AFX_STDAFX_H__22BF6D92_917F_4BDF_B806_0954721EBA95__INCLUDED_) MSVMpack1.2/lp_solve_5.5/Makefile0000664000175000017500000001142010725613522015577 0ustar lauerlauerCC= gcc MINGW_EXTRA = c:/cygwin/mingw MINGW_INCDIR = $(MINGW_EXTRA)/include MINGW_LIBDIR = $(MINGW_EXTRA)/lib AS = as DLLTOOL = dlltool DLLWRAP = dllwrap DLLWRAP_FLAGS = --dlltool-name=$(DLLTOOL) --as=$(AS) --driver-name=$(CC) \ --target=i386-mingw32 DLL_LDFLAGS = -L$(MINGW_LIBDIR) -mno-cygwin -mwindows DLL_LDLIBS = liblpk.a # # Beginning of supplied stuff # #should be OK in most situations: #CFLAGS= -O # HP/UX 9.0X optimized code #CFLAGS= +O3 +Oaggressive +Olibcalls -Aa -D_POSIX_SOURCE -DCHECK +FP VZOUiD # HP/UX 9.0X debugging #CFLAGS= -g -Aa -D_POSIX_SOURCE -DCHECK +FP VZOUiD # nice for gcc CFLAGS= -O3 -Wall -pedantic -ansi -mrtd #CFLAGS= -g -Wall -pedantic -ansi INCLUDE=-Ibfp -Ibfp/bfp_etaPFI -I. -Icolamd -Ishared CFLAGS= -O3 -Wall -pedantic -ansi -mrtd -mno-cygwin -I$(MINGW_INCDIR)\ -DINTEGERTIME -DPARSER_LP -DYY_INTERACTIVE -DWIN32 $(INCLUDE) \ -DBUILDING_FOR_R -DWIN32 -g # Option -DCHECK checks for numerical problems during rounding of numbers. # It will slow things down a bit. # You can add a -DREAL= to the CFLAGS, to change the default float # type used in lp_solve (double) to float or 'long double'. However, type float # might be fast on your computer, but it is not accurate enough to solve even # moderately sized problems without running into numerical problems. # The use of long doubles does increase the numerical stability of lp_solve, # if your compiler actually implements them with more bits than a double. But # it slows down things quite a bit. # Choose your favorite or available version of lex and yacc #YACC= yacc #especially for linux: YACC= bison -y #LEX= lex #especially for linux: LEX= flex -l #LEXLIB= -ll #especially for linux: LEXLIB= -lfl #ANSI math lib #MATHLIB= -lM #non-ANSI math lib, should also work MATHLIB= -lm LPKSRC.c= $(wildcard *.c) lp_MDO.c \ colamd/colamd.c shared/commonlib.c shared/myblas.c LEXFILE.l= lp_rlp.l YACCFILE.y= lp_rlp.y LPKLIB=liblpk.a LEXFILE.c= $(LEXFILE.l:.l=.c) YACCFILE.c= $(YACCFILE.y:.y=.c) YACCFILE.o= $(YACCFILE.y:.y=.o) CSOURCES=$(LEXFILE.c) $(YACCFILE.c) $(wildcard *.c) # commonlib.c fortify.c lp_Hash.c \ # lp_LUMOD.c lp_MPS.c lp_SOS.c lp_crash.c lp_lib.c lp_matrix.c lp_mipbb.c \ # lp_presolve.c lp_price.c lp_pricePSE.c lp_report.c lp_rlp.c lp_scale.c \ # lp_simplex.c lp_solveDLL.c lp_utils.c lp_wlp.c lpslink.c myblas.c \ # yacc_read.c COBJ=$(CSOURCES:.c=.o) LPKSRC= $(LPKSRC.c) $(YACCFILE.c) LPKOBJ= $(LPKSRC:.c=.o) HEADERS=*.h all: lpslink.dll q8.exe: q8.o $(CC) -o q8.exe $(CFLAGS) \ --allow-multiple-definition \ q8.o colamd/colamd.o shared/commonlib.o \ fortify.o ini.o \ lp_Hash.o lp_LUSOL.o lp_MDO.o lp_MPS.o lp_SOS.o lp_crash.o lp_lib.o \ lp_matrix.o lp_mipbb.o lp_params.o lp_presolve.o lp_price.o lp_pricePSE.o \ lp_report.o lp_rlp.o lp_scale.o lp_simplex.o lp_utils.o lp_wlp.o lpslink.o \ lusol.o mmio.o shared/myblas.o yacc_read.o \ $(MATHLIB) $(LPKLIB) \ -Wl,--allow-multiple-definition $(COBJ): $(HEADERS) purify: lp_solve.o $(LPKLIB) purify $(CC) -o $(TARGET) $(CFLAGS) lp_solve.o $(LPKLIB) $(LEXLIB) $(MATHLIB) quantify: lp_solve.o $(LPKLIB) quantify $(CC) -o $(TARGET) $(CFLAGS) lp_solve.o $(LPKLIB) $(LEXLIB) $(MATHLIB) $(LPKLIB): $(LPKOBJ) ar rv $@ $(LPKOBJ) ranlib $(LPKLIB) $(YACCFILE.o): $(LEXFILE.c) $(LEXFILE.c): $(LEXFILE.l) $(LEX) $(LEXFILE.l) mv lex.yy.c $(LEXFILE.c) $(YACCFILE.c): $(YACCFILE.y) $(YACC) $(YACCFILE.y) mv y.tab.c $(YACCFILE.c) # liblpk.def: lpslink.o # dlltool -z liblpk.def -e exports.o -l liblpk.lib lpslink.o lpslink.dll: lpslink.o liblpk.def liblpk.a $(DLLWRAP) $(DLLWRAP_FLAGS) -o $@ --def liblpk.def \ lpslink.o $(DLL_LDFLAGS) $(DLL_LDLIBS) test: -for i in $(TESTFILES1); do\ ./$(TARGET) -s -S3 -time < $$i > xxx.tmp;\ if diff xxx.tmp lp_examples/`basename $$i .lp`.out > /dev/null; then\ echo "$$i gives the correct result";\ else\ echo "*** $$i gives different result, please check ***";\ fi;\ done;\ for i in $(TESTFILES2); do\ ./$(TARGET) -mps -s -S3 -time < $$i > xxx.tmp;\ if diff xxx.tmp lp_examples/`basename $$i .mps`.out > /dev/null; then\ echo "$$i gives the correct result";\ else\ echo "*** $$i gives different result, please check ***";\ fi;\ done;\ rm xxx.tmp mktest: -for i in $(TESTFILES1); do\ ./$(TARGET) -s -S3 -time < $$i > lp_examples/`basename $$i .lp`.out;\ done;\ for i in $(TESTFILES2); do\ ./$(TARGET) -mps -s -S3 -time < $$i > lp_examples/`basename $$i .mps`.out;\ done;\ $(TARGET).man: $(TARGET).1 nroff -man $(TARGET).1 > $(TARGET).man MANIFEST: clean ls -lR > MANIFEST; ls -lR > MANIFEST clean: rm -f *.a *.o TAGS $(LEXFILE.c) $(YACCFILE.c) demo $(TARGET) lp2mps mps2lp .pure .softdebughist datafile TAGS: etags *.[chyl] MSVMpack1.2/lp_solve_5.5/lp_fortify.h0000664000175000017500000000005511141374243016464 0ustar lauerlauer#ifdef FORTIFY #include "fortify.h" #endif MSVMpack1.2/lp_solve_5.5/lp_matrix.c0000664000175000017500000032157211250514513016310 0ustar lauerlauer #include #include "commonlib.h" #include "lp_lib.h" #include "lp_scale.h" #include "lp_report.h" #include "lp_price.h" #include "lp_pricePSE.h" #include "lp_matrix.h" #ifdef FORTIFY # include "lp_fortify.h" #endif /* ------------------------------------------------------------------------- Basic matrix routines in lp_solve v5.0+ ------------------------------------------------------------------------- Author: Michel Berkelaar (to lp_solve v3.2), Kjell Eikland (v4.0 and forward) Contact: kjell.eikland@broadpark.no License terms: LGPL. Requires: lp_lib.h, lp_pricerPSE.h, lp_matrix.h Release notes: v5.0.0 1 January 2004 First integrated and repackaged version. v5.0.1 7 May 2004 Added matrix transpose function. v5.1.0 20 July 2004 Reworked with flexible matrix storage model. v5.2.0 10 January 2005 Added fast deletion methods. Added data extraction to matrix method. Changed to explicit OF storage mode. ------------------------------------------------------------------------- */ STATIC MATrec *mat_create(lprec *lp, int rows, int columns, REAL epsvalue) { MATrec *newmat; newmat = (MATrec *) calloc(1, sizeof(*newmat)); newmat->lp = lp; newmat->rows_alloc = 0; newmat->columns_alloc = 0; newmat->mat_alloc = 0; inc_matrow_space(newmat, rows); newmat->rows = rows; inc_matcol_space(newmat, columns); newmat->columns = columns; inc_mat_space(newmat, 0); newmat->epsvalue = epsvalue; return( newmat ); } STATIC void mat_free(MATrec **matrix) { if((matrix == NULL) || (*matrix == NULL)) return; #if MatrixColAccess==CAM_Record FREE((*matrix)->col_mat); #else /*if MatrixColAccess==CAM_Vector*/ FREE((*matrix)->col_mat_colnr); FREE((*matrix)->col_mat_rownr); FREE((*matrix)->col_mat_value); #endif FREE((*matrix)->col_end); FREE((*matrix)->col_tag); #if MatrixRowAccess==RAM_Index FREE((*matrix)->row_mat); #elif MatrixColAccess==CAM_Record FREE((*matrix)->row_mat); #else /*if MatrixRowAccess==COL_Vector*/ FREE((*matrix)->row_mat_colnr); FREE((*matrix)->row_mat_rownr); FREE((*matrix)->row_mat_value); #endif FREE((*matrix)->row_end); FREE((*matrix)->row_tag); FREE((*matrix)->colmax); FREE((*matrix)->rowmax); FREE(*matrix); } STATIC MYBOOL mat_memopt(MATrec *mat, int rowextra, int colextra, int nzextra) { MYBOOL status = TRUE; int matalloc, colalloc, rowalloc; if((mat == NULL) || #if 0 (++rowextra < 1) || (++colextra < 1) || (++nzextra < 1)) #else (rowextra < 0) || (colextra < 0) || (nzextra < 0)) #endif return( FALSE ); mat->rows_alloc = MIN(mat->rows_alloc, mat->rows + rowextra); mat->columns_alloc = MIN(mat->columns_alloc, mat->columns + colextra); mat->mat_alloc = MIN(mat->mat_alloc, mat->col_end[mat->columns] + nzextra); #if 0 rowalloc = mat->rows_alloc; colalloc = mat->columns_alloc; matalloc = mat->mat_alloc; #else rowalloc = mat->rows_alloc + 1; colalloc = mat->columns_alloc + 1; matalloc = mat->mat_alloc + 1; #endif #if MatrixColAccess==CAM_Record mat->col_mat = (MATitem *) realloc(mat->col_mat, matalloc * sizeof(*(mat->col_mat))); status &= (mat->col_mat != NULL); #else /*if MatrixColAccess==CAM_Vector*/ status &= allocINT(mat->lp, &(mat->col_mat_colnr), matalloc, AUTOMATIC) && allocINT(mat->lp, &(mat->col_mat_rownr), matalloc, AUTOMATIC) && allocREAL(mat->lp, &(mat->col_mat_value), matalloc, AUTOMATIC); #endif status &= allocINT(mat->lp, &mat->col_end, colalloc, AUTOMATIC); if(mat->col_tag != NULL) status &= allocINT(mat->lp, &mat->col_tag, colalloc, AUTOMATIC); #if MatrixRowAccess==RAM_Index status &= allocINT(mat->lp, &(mat->row_mat), matalloc, AUTOMATIC); #elif MatrixColAccess==CAM_Record mat->row_mat = (MATitem *) realloc(mat->row_mat, matalloc * sizeof(*(mat->row_mat))); status &= (mat->row_mat != NULL); #else /*if MatrixRowAccess==COL_Vector*/ status &= allocINT(mat->lp, &(mat->row_mat_colnr), matalloc, AUTOMATIC) && allocINT(mat->lp, &(mat->row_mat_rownr), matalloc, AUTOMATIC) && allocREAL(mat->lp, &(mat->row_mat_value), matalloc, AUTOMATIC); #endif status &= allocINT(mat->lp, &mat->row_end, rowalloc, AUTOMATIC); if(mat->row_tag != NULL) status &= allocINT(mat->lp, &mat->row_tag, rowalloc, AUTOMATIC); if(mat->colmax != NULL) status &= allocREAL(mat->lp, &(mat->colmax), colalloc, AUTOMATIC); if(mat->rowmax != NULL) status &= allocREAL(mat->lp, &(mat->rowmax), rowalloc, AUTOMATIC); return( status ); } STATIC MYBOOL inc_mat_space(MATrec *mat, int mindelta) { int spaceneeded, nz = mat_nonzeros(mat); if(mindelta <= 0) mindelta = MAX(mat->rows, mat->columns) + 1; spaceneeded = DELTA_SIZE(mindelta, nz); SETMAX(mindelta, spaceneeded); if(mat->mat_alloc == 0) spaceneeded = mindelta; else spaceneeded = nz + mindelta; if(spaceneeded >= mat->mat_alloc) { /* Let's allocate at least MAT_START_SIZE entries */ if(mat->mat_alloc < MAT_START_SIZE) mat->mat_alloc = MAT_START_SIZE; /* Increase the size by RESIZEFACTOR each time it becomes too small */ while(spaceneeded >= mat->mat_alloc) mat->mat_alloc += mat->mat_alloc / RESIZEFACTOR; #if MatrixColAccess==CAM_Record mat->col_mat = (MATitem *) realloc(mat->col_mat, (mat->mat_alloc) * sizeof(*(mat->col_mat))); #else /*if MatrixColAccess==CAM_Vector*/ allocINT(mat->lp, &(mat->col_mat_colnr), mat->mat_alloc, AUTOMATIC); allocINT(mat->lp, &(mat->col_mat_rownr), mat->mat_alloc, AUTOMATIC); allocREAL(mat->lp, &(mat->col_mat_value), mat->mat_alloc, AUTOMATIC); #endif #if MatrixRowAccess==RAM_Index allocINT(mat->lp, &(mat->row_mat), mat->mat_alloc, AUTOMATIC); #elif MatrixColAccess==CAM_Record mat->row_mat = (MATitem *) realloc(mat->row_mat, (mat->mat_alloc) * sizeof(*(mat->row_mat))); #else /*if MatrixColAccess==CAM_Vector*/ allocINT(mat->lp, &(mat->row_mat_colnr), mat->mat_alloc, AUTOMATIC); allocINT(mat->lp, &(mat->row_mat_rownr), mat->mat_alloc, AUTOMATIC); allocREAL(mat->lp, &(mat->row_mat_value), mat->mat_alloc, AUTOMATIC); #endif } return(TRUE); } STATIC MYBOOL inc_matrow_space(MATrec *mat, int deltarows) { int rowsum, oldrowsalloc; MYBOOL status = TRUE; /* Adjust lp row structures */ if(mat->rows+deltarows >= mat->rows_alloc) { /* Update memory allocation and sizes */ oldrowsalloc = mat->rows_alloc; deltarows = DELTA_SIZE(deltarows, mat->rows); SETMAX(deltarows, DELTAROWALLOC); mat->rows_alloc += deltarows; rowsum = mat->rows_alloc + 1; /* Update row pointers */ status = allocINT(mat->lp, &mat->row_end, rowsum, AUTOMATIC); mat->row_end_valid = FALSE; } return( status ); } STATIC MYBOOL inc_matcol_space(MATrec *mat, int deltacols) { int i, colsum, oldcolsalloc; MYBOOL status = TRUE; /* Adjust lp column structures */ if(mat->columns+deltacols >= mat->columns_alloc) { /* Update memory allocation and sizes */ oldcolsalloc = mat->columns_alloc; deltacols = DELTA_SIZE(deltacols, mat->columns); SETMAX(deltacols, DELTACOLALLOC); mat->columns_alloc += deltacols; colsum = mat->columns_alloc + 1; status = allocINT(mat->lp, &mat->col_end, colsum, AUTOMATIC); /* Update column pointers */ if(oldcolsalloc == 0) mat->col_end[0] = 0; for(i = MIN(oldcolsalloc, mat->columns) + 1; i < colsum; i++) mat->col_end[i] = mat->col_end[i-1]; mat->row_end_valid = FALSE; } return( status ); } STATIC int mat_collength(MATrec *mat, int colnr) { return( mat->col_end[colnr] - mat->col_end[colnr-1] ); } STATIC int mat_rowlength(MATrec *mat, int rownr) { if(mat_validate(mat)) { if(rownr <= 0) return( mat->row_end[0] ); else return( mat->row_end[rownr] - mat->row_end[rownr-1] ); } else return( 0 ); } STATIC int mat_nonzeros(MATrec *mat) { return( mat->col_end[mat->columns] ); } STATIC MYBOOL mat_indexrange(MATrec *mat, int index, MYBOOL isrow, int *startpos, int *endpos) { #ifdef Paranoia if(isrow && ((index < 0) || (index > mat->rows))) return( FALSE ); else if(!isrow && ((index < 1) || (index > mat->columns))) return( FALSE ); #endif if(isrow && mat_validate(mat)) { if(index == 0) *startpos = 0; else *startpos = mat->row_end[index-1]; *endpos = mat->row_end[index]; } else { *startpos = mat->col_end[index-1]; *endpos = mat->col_end[index]; } return( TRUE ); } STATIC int mat_shiftrows(MATrec *mat, int *bbase, int delta, LLrec *varmap) { int j, k, i, ii, thisrow, *colend, base; MYBOOL preparecompact = FALSE; int *rownr; if(delta == 0) return( 0 ); base = abs(*bbase); if(delta > 0) { /* Insert row by simply incrementing existing row indeces */ if(base <= mat->rows) { k = mat_nonzeros(mat); rownr = &COL_MAT_ROWNR(0); for(ii = 0; ii < k; ii++, rownr += matRowColStep) { if(*rownr >= base) *rownr += delta; } } /* Set defaults (actual basis set in separate procedure) */ for(i = 0; i < delta; i++) { ii = base + i; mat->row_end[ii] = 0; } } else if(base <= mat->rows) { /* Check for preparation of mass-deletion of rows */ preparecompact = (MYBOOL) (varmap != NULL); if(preparecompact) { /* Create the offset array */ int *newrowidx = NULL; allocINT(mat->lp, &newrowidx, mat->rows+1, FALSE); newrowidx[0] = 0; delta = 0; for(j = 1; j <= mat->rows; j++) { if(isActiveLink(varmap, j)) { delta++; newrowidx[j] = delta; } else newrowidx[j] = -1; } k = 0; delta = 0; base = mat_nonzeros(mat); rownr = &COL_MAT_ROWNR(0); for(i = 0; i < base; i++, rownr += matRowColStep) { thisrow = newrowidx[*rownr]; if(thisrow < 0) { *rownr = -1; delta++; } else *rownr = thisrow; } FREE(newrowidx); return(delta); } /* Check if we should prepare for compacting later (this is in order to speed up multiple row deletions) */ preparecompact = (MYBOOL) (*bbase < 0); if(preparecompact) *bbase = my_flipsign((*bbase)); /* First make sure we don't cross the row count border */ if(base-delta-1 > mat->rows) delta = base - mat->rows - 1; /* Then scan over all entries shifting and updating rows indeces */ if(preparecompact) { k = 0; for(j = 1, colend = mat->col_end + 1; j <= mat->columns; j++, colend++) { i = k; k = *colend; rownr = &COL_MAT_ROWNR(i); for(; i < k; i++, rownr += matRowColStep) { thisrow = *rownr; if(thisrow < base) continue; else if(thisrow >= base-delta) *rownr += delta; else *rownr = -1; } } } else { k = 0; ii = 0; for(j = 1, colend = mat->col_end + 1; j <= mat->columns; j++, colend++) { i = k; k = *colend; rownr = &COL_MAT_ROWNR(i); for(; i < k; i++, rownr += matRowColStep) { thisrow = *rownr; if(thisrow >= base) { if(thisrow >= base-delta) *rownr += delta; else continue; } if(ii != i) { COL_MAT_COPY(ii, i); } ii++; } *colend = ii; } } } return( 0 ); } /* Map-based compacting+insertion of matrix elements without changing row and column indeces. When mat2 is NULL, a simple compacting of non-deleted rows and columns is done. */ STATIC int mat_mapreplace(MATrec *mat, LLrec *rowmap, LLrec *colmap, MATrec *mat2) { lprec *lp = mat->lp; int i, ib, ie, ii, j, jj, jb, je, nz, *colend, *rownr, *rownr2, *indirect = NULL; REAL *value, *value2; /* Check if there is something to insert */ if((mat2 != NULL) && ((mat2->col_tag == NULL) || (mat2->col_tag[0] <= 0) || (mat_nonzeros(mat2) == 0))) return( 0 ); /* Create map and sort by increasing index in "mat" */ if(mat2 != NULL) { jj = mat2->col_tag[0]; allocINT(lp, &indirect, jj+1, FALSE); indirect[0] = jj; for(i = 1; i <= jj; i++) indirect[i] = i; hpsortex(mat2->col_tag, jj, 1, sizeof(*indirect), FALSE, compareINT, indirect); } /* Do the compacting */ mat->row_end_valid = FALSE; nz = mat->col_end[mat->columns]; ie = 0; ii = 0; if((mat2 == NULL) || (indirect[0] == 0)) { je = mat->columns + 1; jj = 1; jb = 0; } else { je = indirect[0]; jj = 0; do { jj++; jb = mat2->col_tag[jj]; } while(jb <= 0); } for(j = 1, colend = mat->col_end + 1; j <= mat->columns; j++, colend++) { ib = ie; ie = *colend; /* Always skip (condense) replacement columns */ if(j == jb) { jj++; if(jj <= je) jb = mat2->col_tag[jj]; else jb = mat->columns + 1; } /* Only include active columns */ else if(isActiveLink(colmap, j)) { rownr = &COL_MAT_ROWNR(ib); for(; ib < ie; ib++, rownr += matRowColStep) { /* Also make sure the row is active */ if(isActiveLink(rowmap, *rownr)) { if(ii != ib) { COL_MAT_COPY(ii, ib); } ii++; } } } *colend = ii; } if(mat2 == NULL) goto Finish; /* Tally non-zero insertions */ i = 0; for(j = 1; j <= mat2->col_tag[0]; j++) { jj = mat2->col_tag[j]; if((jj > 0) && isActiveLink(colmap, jj)) { jj = indirect[j]; je = mat2->col_end[jj]; jb = mat2->col_end[jj-1]; rownr2 = &COL_MAT2_ROWNR(jb); for(; jb < je; jb++, rownr2 += matRowColStep) { if((*rownr2 > 0) && isActiveLink(rowmap, *rownr2)) i++; } } } /* Make sure we have enough matrix space */ ii = mat->col_end[mat->columns] + i; if(mat->mat_alloc <= ii) inc_mat_space(mat, i); /* Do shifting and insertion - loop from the end going forward */ jj = indirect[0]; jj = mat2->col_tag[jj]; for(j = mat->columns, colend = mat->col_end + mat->columns, ib = *colend; j > 0; j--) { /* Update indeces for this loop */ ie = ib; *colend = ii; colend--; ib = *colend; /* Insert new values */ if(j == jj) { /* Only include an active column */ if(isActiveLink(colmap, j)) { jj = indirect[0]; jj = indirect[jj]; rownr = &COL_MAT_ROWNR(ii-1); value = &COL_MAT_VALUE(ii-1); jb = mat2->col_end[jj-1]; je = mat2->col_end[jj] - 1; rownr2 = &COL_MAT2_ROWNR(je); value2 = &COL_MAT2_VALUE(je); /* Process constraint coefficients */ for(; je >= jb; je--, rownr2 -= matRowColStep, value2 -= matValueStep) { i = *rownr2; if(i == 0) { i = -1; break; } else if(isActiveLink(rowmap, i)) { ii--; *rownr = i; rownr -= matRowColStep; *value = my_chsign(is_chsign(lp, i), *value2); value -= matValueStep; } } /* Then handle the objective */ if(i == -1) { lp->orig_obj[j] = my_chsign(is_maxim(lp), *value2); rownr2 -= matRowColStep; value2 -= matValueStep; } else lp->orig_obj[j] = 0; } /* Update replacement column index or break if no more candidates */ jj = --indirect[0]; if(jj == 0) break; jj = mat2->col_tag[jj]; if(jj <= 0) break; } /* Shift existing values down */ else { if(isActiveLink(colmap, j)) while(ie > ib) { ii--; ie--; if(ie != ii) { COL_MAT_COPY(ii, ie); } } } } /* Return the delta number of non-zero elements */ Finish: nz -= mat->col_end[mat->columns]; FREE(indirect); return( nz ); } /* Routines to compact rows in matrix based on precoded entries */ STATIC int mat_zerocompact(MATrec *mat) { return( mat_rowcompact(mat, TRUE) ); } STATIC int mat_rowcompact(MATrec *mat, MYBOOL dozeros) { int i, ie, ii, j, nn, *colend, *rownr; REAL *value; nn = 0; ie = 0; ii = 0; for(j = 1, colend = mat->col_end + 1; j <= mat->columns; j++, colend++) { i = ie; ie = *colend; rownr = &COL_MAT_ROWNR(i); value = &COL_MAT_VALUE(i); for(; i < ie; i++, rownr += matRowColStep, value += matValueStep) { if((*rownr < 0) || (dozeros && (fabs(*value) < mat->epsvalue))) { nn++; continue; } if(ii != i) { COL_MAT_COPY(ii, i); } ii++; } *colend = ii; } return( nn ); } /* Routines to compact columns and their indeces based on precoded entries */ STATIC int mat_colcompact(MATrec *mat, int prev_rows, int prev_cols) { int i, ii, j, k, n_del, n_sum, *colend, *newcolend, *colnr, newcolnr; MYBOOL deleted; lprec *lp = mat->lp; presolveundorec *lpundo = lp->presolve_undo; n_sum = 0; k = 0; ii = 0; newcolnr = 1; for(j = 1, colend = newcolend = mat->col_end + 1; j <= prev_cols; j++, colend++) { n_del = 0; i = k; k = *colend; for(colnr = &COL_MAT_COLNR(i); i < k; i++, colnr += matRowColStep) { if(*colnr < 0) { n_del++; n_sum++; continue; } if(ii < i) { COL_MAT_COPY(ii, i); } if(newcolnr < j) { COL_MAT_COLNR(ii) = newcolnr; } ii++; } *newcolend = ii; deleted = (MYBOOL) (n_del > 0); #if 1 /* Do hoops in case there was an empty column */ deleted |= (MYBOOL) (!lp->wasPresolved && (lpundo->var_to_orig[prev_rows+j] < 0)); #endif /* Increment column variables if current column was not deleted */ if(!deleted) { newcolend++; newcolnr++; } } return(n_sum); } STATIC int mat_shiftcols(MATrec *mat, int *bbase, int delta, LLrec *varmap) { int i, ii, k, n, base; k = 0; if(delta == 0) return( k ); base = abs(*bbase); if(delta > 0) { /* Shift pointers right */ for(ii = mat->columns; ii > base; ii--) { i = ii + delta; mat->col_end[i] = mat->col_end[ii]; } /* Set defaults */ for(i = 0; i < delta; i++) { ii = base + i; mat->col_end[ii] = mat->col_end[ii-1]; } } else { /* Check for preparation of mass-deletion of columns */ MYBOOL preparecompact = (MYBOOL) (varmap != NULL); if(preparecompact) { /* Create the offset array */ int j, *colnr, *colend; n = 0; k = 0; base = 0; for(j = 1, colend = mat->col_end + 1; j <= mat->columns; j++, colend++) { i = k; k = *colend; if(isActiveLink(varmap, j)) { base++; ii = base; } else ii = -1; if(ii < 0) n += k - i; colnr = &COL_MAT_COLNR(i); for(; i < k; i++, colnr += matRowColStep) *colnr = ii; } return(n); } /* Check if we should prepare for compacting later (this is in order to speed up multiple column deletions) */ preparecompact = (MYBOOL) (*bbase < 0); if(preparecompact) *bbase = my_flipsign((*bbase)); /* First make sure we don't cross the column count border */ if(base-delta-1 > mat->columns) delta = base - mat->columns - 1; /* Then scan over all entries shifting and updating column indeces */ if(preparecompact) { int *colnr; n = 0; i = mat->col_end[base-1]; k = mat->col_end[base-delta-1]; for(colnr = &COL_MAT_COLNR(i); i < k; i++, colnr += matRowColStep) { n++; *colnr = -1; } k = n; } else { /* Delete sparse matrix data, if required */ if(base <= mat->columns) { i = mat->col_end[base-1]; /* Beginning of data to be deleted */ ii = mat->col_end[base-delta-1]; /* Beginning of data to be shifted left */ n = mat_nonzeros(mat); /* Total number of non-zeros */ k = ii-i; /* Number of entries to be deleted */ if((k > 0) && (n > i)) { n -= ii; COL_MAT_MOVE(i, ii, n); } /* Update indexes */ for(i = base; i <= mat->columns + delta; i++) { ii = i - delta; mat->col_end[i] = mat->col_end[ii] - k; } } } } return( k ); } STATIC MATrec *mat_extractmat(MATrec *mat, LLrec *rowmap, LLrec *colmap, MYBOOL negated) { int *rownr, *colnr, xa, na; REAL *value; MATrec *newmat = mat_create(mat->lp, mat->rows, mat->columns, mat->epsvalue); /* Initialize */ na = mat_nonzeros(mat); rownr = &COL_MAT_ROWNR(0); colnr = &COL_MAT_COLNR(0); value = &COL_MAT_VALUE(0); /* Loop over the indeces, picking out values in qualifying rows and colums (note that the loop could be speeded up for dense matrices by making an outer loop for columns and inner loop for rows) */ for(xa = 0; xa < na; xa++, rownr += matRowColStep, colnr += matRowColStep, value += matValueStep) { if((isActiveLink(colmap, *colnr) ^ negated) && (isActiveLink(rowmap, *rownr) ^ negated)) mat_setvalue(newmat, *rownr, *colnr, *value, FALSE); } /* Return the populated new matrix */ return( newmat ); } STATIC MYBOOL mat_setcol(MATrec *mat, int colno, int count, REAL *column, int *rowno, MYBOOL doscale, MYBOOL checkrowmode) { int i, jj = 0, elmnr, orignr, newnr, firstrow; MYBOOL *addto = NULL, isA, isNZ; REAL value, saved = 0; lprec *lp = mat->lp; /* Check if we are in row order mode and should add as row instead; the matrix will be transposed at a later stage */ if(checkrowmode && mat->is_roworder) return( mat_setrow(mat, colno, count, column, rowno, doscale, FALSE) ); /* Initialize and validate */ isA = (MYBOOL) (mat == mat->lp->matA); isNZ = (MYBOOL) (rowno != NULL); if(!isNZ) count = mat->lp->rows; else if((count < 0) || (count > mat->rows+((mat->is_roworder) ? 0 : 1))) return( FALSE ); if(isNZ && (count > 0)) { if(count > 1) sortREALByINT(column, rowno, count, 0, TRUE); if((rowno[0] < 0) || (rowno[count-1] > mat->rows)) return( FALSE ); } /* Capture OF definition in column mode */ if(isA && !mat->is_roworder) { if(isNZ && (count > 0) && (rowno[0] == 0)) { value = column[0]; #ifdef DoMatrixRounding value = roundToPrecision(value, mat->epsvalue); #endif if(doscale) value = scaled_mat(lp, value, 0, colno); value = my_chsign(is_maxim(lp), value); lp->orig_obj[colno] = value; count--; column++; rowno++; } else if(!isNZ && (column[0] != 0)) { value = saved = column[0]; #ifdef DoMatrixRounding value = roundToPrecision(value, mat->epsvalue); #endif if(doscale) value = scaled_mat(lp, value, 0, colno); value = my_chsign(is_maxim(lp), value); lp->orig_obj[colno] = value; column[0] = 0; } else lp->orig_obj[colno] = 0; } /* Optionally tally and map the new non-zero values */ firstrow = mat->rows + 1; if(isNZ) { newnr = count; if(newnr) { firstrow = rowno[0]; jj = rowno[newnr - 1]; } } else { newnr = 0; if(!allocMYBOOL(lp, &addto, mat->rows + 1, TRUE)) { return( FALSE ); } for(i = mat->rows; i >= 0; i--) { if(fabs(column[i]) > mat->epsvalue) { addto[i] = TRUE; firstrow = i; newnr++; } } } /* Make sure we have enough matrix space */ if(!inc_mat_space(mat, newnr)) { newnr = 0; goto Done; } /* Shift existing column data and adjust position indeces */ orignr = mat_collength(mat, colno); elmnr = newnr - orignr; i = mat_nonzeros(mat) - mat->col_end[colno]; if((elmnr != 0) && (i > 0)) { COL_MAT_MOVE(mat->col_end[colno] + elmnr, mat->col_end[colno], i); } if(elmnr != 0) for(i = colno; i <= mat->columns; i++) mat->col_end[i] += elmnr; /* We are now ready to copy the new data */ jj = mat->col_end[colno-1]; if(isNZ) { for(i = 0; i < count; jj++, i++) { value = column[i]; #ifdef DoMatrixRounding value = roundToPrecision(value, mat->epsvalue); #endif if(mat->is_roworder) { /* Fix following Ingmar Stein bug report 12.10.2006 */ if(isA && doscale) value = scaled_mat(lp, value, colno, rowno[i]); if(isA) value = my_chsign(is_chsign(lp, colno), value); } else { if(isA && doscale) value = scaled_mat(lp, value, rowno[i], colno); if(isA) value = my_chsign(is_chsign(lp, rowno[i]), value); } SET_MAT_ijA(jj, rowno[i], colno, value); } } else { for(i = firstrow; i <= mat->rows; i++) { if(!addto[i]) continue; value = column[i]; #ifdef DoMatrixRounding value = roundToPrecision(value, mat->epsvalue); #endif if(mat->is_roworder) { /* Fix following Ingmar Stein bug report 12.10.2006 */ if(isA && doscale) value = scaled_mat(lp, value, colno, i); if(isA) value = my_chsign(is_chsign(lp, colno), value); } else { if(isA && doscale) value = scaled_mat(lp, value, i, colno); if(isA) value = my_chsign(is_chsign(lp, i), value); } SET_MAT_ijA(jj, i, colno, value); jj++; } } mat->row_end_valid = FALSE; /* Finish and return */ Done: if(saved != 0) column[0] = saved; FREE(addto); return( TRUE ); } STATIC MYBOOL mat_mergemat(MATrec *target, MATrec *source, MYBOOL usecolmap) { lprec *lp = target->lp; int i, ix, iy, n, *colmap = NULL; REAL *colvalue = NULL; if((target->rows < source->rows) || !allocREAL(lp, &colvalue, target->rows+1, FALSE)) return( FALSE ); if(usecolmap) { n = source->col_tag[0]; allocINT(lp, &colmap, n+1, FALSE); for(i = 1; i <= n; i++) colmap[i] = i; hpsortex(source->col_tag, n, 1, sizeof(*colmap), FALSE, compareINT, colmap); } else n = source->columns; for(i = 1; i <= n; i++) { if(!usecolmap && (mat_collength(source, i) == 0)) continue; if(usecolmap) { ix = colmap[i]; if(ix <= 0) continue; iy = source->col_tag[i]; if(iy <= 0) continue; } else ix = iy = i; mat_expandcolumn(source, ix, colvalue, NULL, FALSE); mat_setcol(target, iy, 0, colvalue, NULL, FALSE, FALSE); } FREE( colvalue ); FREE( colmap ); return( TRUE ); } STATIC int mat_nz_unused(MATrec *mat) { return( mat->mat_alloc - mat->col_end[mat->columns] ); } #if 0 STATIC MYBOOL mat_setrow(MATrec *mat, int rowno, int count, REAL *row, int *colno, MYBOOL doscale, MYBOOL checkrowmode) { lprec *lp = mat->lp; int delta; int k, kk, i, ii, j, jj = 0, jj_j, elmnr, orignr, newnr, firstcol, rownr, colnr, matz = 0; MYBOOL *addto = NULL, isA, isNZ; REAL value = 0.0, saved = 0; /* Check if we are in row order mode and should add as column instead; the matrix will be transposed at a later stage */ if(checkrowmode && mat->is_roworder) return( mat_setcol(mat, rowno, count, row, colno, doscale, FALSE) ); /* Do initialization and validation */ if(!mat_validate(mat)) return( FALSE ); isA = (MYBOOL) (mat == lp->matA); isNZ = (MYBOOL) (colno != NULL); if(!isNZ) count = mat->columns; else if((count < 0) || (count > mat->columns)) return( FALSE ); if(isNZ && (count > 0)) { if(count > 1) sortREALByINT(row, (int *) colno, count, 0, TRUE); if((colno[0] < 1) || (colno[count-1] > mat->columns)) return( FALSE ); } /* Capture OF definition in row mode */ if(isA && mat->is_roworder) { lp->orig_obj[rowno] = 0; if(isNZ && (count > 0) && (colno[0] == 0)) { value = row[0]; if(doscale) value = scaled_mat(lp, value, 0, rowno); value = my_chsign(is_maxim(lp), value); #ifdef DoMatrixRounding value = roundToPrecision(value, mat->epsvalue); #endif lp->orig_obj[rowno] = value; count--; row++; colno++; } else if(!isNZ && (row[0] != 0)) { value = saved = row[0]; if(doscale) value = scaled_mat(lp, value, 0, rowno); value = my_chsign(is_maxim(lp), value); #ifdef DoMatrixRounding value = roundToPrecision(value, mat->epsvalue); #endif lp->orig_obj[rowno] = value; row[0] = 0; } else { lp->orig_obj[rowno] = 0; value = 0; } } /* Optionally tally and map the new non-zero values */ i = mat->row_end[rowno-1]; ii = mat->row_end[rowno]; // ****** KE 20070106 - was "-1" firstcol = mat->columns + 1; if(isNZ) { /* See if we can do fast in-place replacements of leading items */ colnr = 1; /* initialise in case of an empty row */ while((i < ii) /* && (count > 0) */ && ((colnr = ROW_MAT_COLNR(i)) == *colno) && (count > 0)) { value = *row; // ****** KE 20080111 - Added line if(mat->is_roworder) { if(isA && doscale) value = scaled_mat(lp, value, colnr, rowno); if(isA) value = my_chsign(is_chsign(lp, colnr), value); } else { if(isA && doscale) value = scaled_mat(lp, value, rowno, colnr); if(isA) value = my_chsign(is_chsign(lp, rowno), value); } #ifdef DoMatrixRounding value = roundToPrecision(value, mat->epsvalue); if(value == 0) matz++; #endif ROW_MAT_VALUE(i) = value; i++; count--; row++; colno++; } if(i >= ii) colnr = 0; /* Proceed with remaining entries */ newnr = count; if(newnr > 0) firstcol = colno[0]; } else { newnr = 0; kk = mat->columns; if(i < ii) colnr = ROW_MAT_COLNR(i); else colnr = 0; for(k = 1; k <= kk; k++) { value = row[k]; // ****** KE 20080111 - Added line if(fabs(value) > mat->epsvalue) { /* See if we can do fast in-place replacements of leading items */ if((addto == NULL) && (i < ii) && (colnr == k)) { if(mat->is_roworder) { if(isA && doscale) value = scaled_mat(lp, value, colnr, rowno); if(isA) value = my_chsign(is_chsign(lp, colnr), value); } else { if(isA && doscale) value = scaled_mat(lp, value, rowno, colnr); if(isA) value = my_chsign(is_chsign(lp, rowno), value); } #ifdef DoMatrixRounding value = roundToPrecision(value, mat->epsvalue); if(value == 0) matz++; #endif ROW_MAT_VALUE(i) = value; i++; if(i < ii) colnr = ROW_MAT_COLNR(i); else colnr = 0; } /* Otherwise update addto-list */ else { if(addto == NULL) { if(!allocMYBOOL(lp, &addto, mat->columns + 1, TRUE)) return( FALSE ); firstcol = k; } addto[k] = TRUE; newnr++; } } } } if(newnr == 0) if (FALSE) return( TRUE ); /* Make sure we have enough matrix space */ if((newnr > 0) && (mat_nz_unused(mat) <= newnr) && !inc_mat_space(mat, newnr)) { newnr = 0; goto Done; } /* Pack initial entries if existing row data has a lower column start index than the first index of the new vector */ orignr = mat_nonzeros(mat); /* delta = newnr - mat_rowlength(mat, rowno);*/ kk = 0; if(rowno == 0) ii = 0; else ii = mat->row_end[rowno-1]; if((orignr == 0) || (ii >= orignr)) j = firstcol; else if(isNZ||TRUE) j = colnr; else j = ROW_MAT_COLNR(ii); /* first column with a value on that row */ jj = mat->col_end[firstcol-1]; /* Set the index of the insertion point for the first new value */ if(jj >= orignr) colnr = firstcol; else colnr = COL_MAT_COLNR(jj); /* first column with a value starting from firstcol */ if((j > 0) && (j < colnr)) { jj = elmnr = mat->col_end[j-1]; for( ; j < colnr; j++) { /* Shift entries in current column */ k = mat->col_end[j]; for( ; jj < k; jj++) { if(COL_MAT_ROWNR(jj) != rowno) { COL_MAT_COPY(elmnr, jj); elmnr++; } } /* Update next column start index */ mat->col_end[j] = elmnr; } delta = elmnr - jj; /* The shrinkage count */ } else { delta = 0; /* Adjust for case where we simply append values - jj is initially the first column item */ if((mat->col_end[firstcol] == orignr) && 0) jj = orignr; } /* Make sure we have sufficient space for any additional entries and move existing data down; this ensures that we only have to relocate matrix elements up in the next stage */ jj_j = MAX(0, newnr + delta); if(jj_j > 0) { if(!inc_mat_space(mat, jj_j)) { FREE(addto); return( FALSE ); } if(orignr-jj > 0) { COL_MAT_MOVE(jj+jj_j, jj, orignr-jj); } jj += jj_j; } /* Handle case where the matrix was empty before (or we can simply append) */ if((delta >= 0) && (mat->col_end[firstcol] == orignr) && 0) { if(isNZ) elmnr = count; else elmnr = mat->columns; jj_j = mat->col_end[firstcol]; for(newnr = 0; newnr < elmnr; newnr++) { if(isNZ) colnr = colno[newnr]; else colnr = newnr + 1; /* Update column start position if we have crossed a column */ while(colnr > firstcol) { mat->col_end[firstcol] = jj_j; firstcol++; } if(isNZ || ((addto != NULL) && addto[colnr])) { if(isNZ) value = row[newnr]; else value = row[colnr]; if(isA && doscale) value = scaled_mat(lp, value, rowno, colnr); if(isA) value = my_chsign(is_chsign(lp, rowno), value); #ifdef DoMatrixRounding value = roundToPrecision(value, mat->epsvalue); if(value == 0) matz++; #endif SET_MAT_ijA(jj_j, rowno, colnr, value); jj_j++; /* Update last column start position */ mat->col_end[firstcol] = jj_j; firstcol++; } } /* Make sure we update tail empty column offsets */ while(firstcol <= mat->columns) { mat->col_end[firstcol] = jj_j; firstcol++; } jj_j = 0; } /* Start from the top of the first non-zero column of the new row */ elmnr = orignr + jj_j; if(jj <= elmnr) { if(isNZ) newnr = 0; else newnr = firstcol - 1; j = jj - mat->col_end[firstcol-1]; colnr = firstcol; while((jj < elmnr) || (newnr < count)) { /* Update column start position if we have crossed a column */ while(colnr > firstcol) { mat->col_end[firstcol] = kk; firstcol++; } /* See if we have a row equal to or greater than the target row */ jj_j = jj - j; if(jj < elmnr) { rownr = COL_MAT_ROWNR(jj); colnr = COL_MAT_COLNR(jj); } else { rownr = rowno; if(!isNZ) /* KE added this conditional on 13.9.2006 */ colnr = firstcol + 1; else colnr = mat->columns + 1; } if(isNZ) { if(newnr < count) kk = colno[newnr]; else kk = mat->columns + 1; } else kk = newnr + 1; /* Test if there is an available new item ... */ if((isNZ && (kk > colnr)) || /* If this is not the case */ (!isNZ && ((kk > colnr) || (!addto[kk])))) { /* DELETE if there is an existing value */ if(!isNZ && (kk <= colnr)) newnr++; if(rownr == rowno) { kk = jj_j; j++; jj++; continue; } /* KEEP otherwise and move entry up */ if(!isNZ && (colnr > kk)) { colnr = kk; kk = jj_j; continue; } } else if((colnr > kk) || /* Existing column index > new => INSERT */ ((colnr == kk) && (rownr >= rowno)) ) { /* Same column index, existing row >= target row => INSERT/REPLACE */ if(isNZ) value = row[newnr]; else value = row[newnr+1]; newnr++; if(isA && doscale) value = scaled_mat(lp, value, rowno, kk); if(isA) value = my_chsign(is_chsign(lp, rowno), value); #ifdef DoMatrixRounding value = roundToPrecision(value, mat->epsvalue); if(value == 0) matz++; #endif SET_MAT_ijA(jj_j, rowno, kk, value); /* Adjust if we have inserted an element */ if((colnr > kk) || (rownr > rowno)) { j--; jj--; } colnr = kk; kk = jj_j; jj++; continue; } /* Shift the matrix element up by the active difference */ if(jj_j != jj) { COL_MAT_COPY(jj_j, jj); } kk = jj_j; jj++; } /* Update pending / incomplete column start position */ while(colnr > firstcol) { mat->col_end[firstcol] = kk; firstcol++; } /* Make sure we update tail column offsets */ jj_j = jj - j; while(firstcol <= mat->columns) { mat->col_end[firstcol] = jj_j; firstcol++; } } /* Compact in the case that we added zeros and set flag for row index update */ if(matz > 0) mat_zerocompact(mat); mat->row_end_valid = FALSE; Done: if(saved != 0) row[0] = saved; FREE(addto); return( (MYBOOL) (newnr > 0) ); } #else STATIC MYBOOL mat_setrow(MATrec *mat, int rowno, int count, REAL *row, int *colno, MYBOOL doscale, MYBOOL checkrowmode) { lprec *lp = mat->lp; int delta; int k, i, ii, j, jj_j, lendense, origidx = 0, newidx, orignz, newnz, rownr, colnr, colnr1; MYBOOL isA, isNZ; REAL value = 0.0; /* Check if we are in row order mode and should add as column instead; the matrix will be transposed at a later stage */ if(checkrowmode && mat->is_roworder) return( mat_setcol(mat, rowno, count, row, colno, doscale, FALSE) ); /* Do initialization and validation */ if(!mat_validate(mat)) return( FALSE ); isA = (MYBOOL) (mat == lp->matA); if(doscale && isA && !lp->scaling_used) doscale = FALSE; isNZ = (MYBOOL) (colno != NULL); lendense = (mat->is_roworder ? lp->rows : lp->columns); if((count < 0) || (count > lendense)) return( FALSE ); colnr1 = lendense + 1; /* Capture OF definition in row mode */ if(isA && mat->is_roworder) { lp->orig_obj[rowno] = 0; if((count > 0) && (colno[0] == 0)) { value = row[0]; if(doscale) value = scaled_mat(lp, value, 0, rowno); value = my_chsign(is_maxim(lp), value); #ifdef DoMatrixRounding value = roundToPrecision(value, mat->epsvalue); #endif lp->orig_obj[rowno] = value; if(isNZ) { colno++; row++; count--; } } else { lp->orig_obj[rowno] = 0; value = 0; } } /* Make local working data copies */ if(!isNZ) { REAL *tmprow = NULL; if(!allocINT(lp, &colno, lendense+1, FALSE)) return( FALSE ); newnz = 0; for(i = 1; i <= lendense; i++) if((value = row[i]) != 0) { if((tmprow == NULL) && !allocREAL(lp, &tmprow, lendense-i+1, FALSE)) { FREE(colno); return( FALSE ); } tmprow[newnz] = value; colno[newnz++] = i; } count = newnz; row = tmprow; } else { int *tmpcolno = NULL; if(!allocINT(lp, &tmpcolno, lendense, FALSE)) return( FALSE ); newnz = count; MEMCOPY(tmpcolno, colno, newnz); colno = tmpcolno; if(newnz > 1) sortREALByINT(row, (int *) colno, newnz, 0, TRUE); if((newnz > 0) && ((colno[0] < 0) || (colno[newnz-1] > lendense))) { FREE(colno); newnz = 0; return( FALSE ); } } /* Make sure we have enough matrix space */ i = mat->row_end[rowno-1]; ii = mat->row_end[rowno]; delta = count - (ii-i); if((delta > 0) && (mat_nz_unused(mat) <= delta) && !inc_mat_space(mat, delta)) { newnz = 0; goto Done; } colnr1 = (newnz > 0 ? colno[0] : lendense+1); /* Pack initial entries if existing row data has a lower column start index than the first index of the new vector */ orignz = mat_nonzeros(mat); j = (i >= orignz ? colnr1 : ROW_MAT_COLNR(i)); /* Index of the column-top insertion point for the first new value */ origidx = mat->col_end[colnr1-1]; colnr = (origidx >= orignz ? colnr1 : COL_MAT_COLNR(origidx)); if(j < colnr) { origidx = newidx = mat->col_end[j-1]; for( ; j < colnr; j++) { /* Shift entries in current column */ jj_j = mat->col_end[j]; for( ; origidx < jj_j; origidx++) { if(COL_MAT_ROWNR(origidx) != rowno) { if(newidx != origidx) { COL_MAT_COPY(newidx, origidx); } newidx++; } } /* Update next column start index */ mat->col_end[j] = newidx; } delta = newidx - origidx; /* The first stage element shrinkage count */ } else { delta = 0; newidx = origidx; } /* Make sure we have sufficient space for any additional entries and move existing data down; this ensures that we only have to relocate matrix elements up in the next stage */ jj_j = MAX(0, (int) newnz + delta); if((jj_j > 0) && (orignz-origidx > 0)) { COL_MAT_MOVE(origidx+jj_j, origidx, orignz-origidx); origidx += jj_j; orignz += jj_j; } /* Start from the top of the first non-zero column of the new row */ newnz = 0; j = origidx - mat->col_end[colnr1-1]; k = colnr1; /* Last column for which col_end is valid/updated */ while((colnr1 <= lendense) || (origidx < orignz)) { /* Get the column index of the active update item */ if(newnz < count) colnr1 = colno[newnz]; else colnr1 = lendense + 1; /* Get coordinate of active existing matrix entries */ if(origidx < orignz) { rownr = COL_MAT_ROWNR(origidx); colnr = COL_MAT_COLNR(origidx); } else { if(colnr1 > lendense) break; rownr = rowno; colnr = lendense + 1; } /* Update column start position if we just crossed into a column */ jj_j = origidx - j; i = MIN(colnr, colnr1); for(; k < i; k++) mat->col_end[k] = jj_j; /* Test if there is an available new item ... */ if(colnr1 > colnr) { /* If this is not the case */ /* DELETE if there is an existing value */ if(rownr == rowno) { ForceDelete: j++; delta--; origidx++; continue; } } else if((colnr > colnr1) || /* Existing column index > new => INSERT */ ((colnr == colnr1) && (rownr >= rowno)) ) { /* Same column index, existing row >= target row => INSERT/REPLACE */ value = row[newnz]; newnz++; if(isA && doscale) value = scaled_mat(lp, value, rowno, colnr1); if(isA) value = my_chsign(is_chsign(lp, rowno), value); #ifdef DoMatrixRounding value = roundToPrecision(value, mat->epsvalue); if(value == 0) { if((colnr > colnr1) || (rownr > rowno)) ; else goto ForceDelete; } #endif SET_MAT_ijA(jj_j, rowno, colnr1, value); /* Adjust if we have inserted an element */ if((colnr > colnr1) || (rownr > rowno)) { j--; origidx--; jj_j++; delta++; } origidx++; continue; } /* Shift the matrix element up by the active difference */ if(jj_j != origidx) { COL_MAT_COPY(jj_j, origidx); } origidx++; } /* Update pending / incomplete column start position */ jj_j = origidx - j; for(; k <= lendense; k++) mat->col_end[k] = jj_j; mat->row_end_valid = FALSE; Done: if(!isNZ) FREE(row); FREE(colno); return( (MYBOOL) (newnz > 0) ); } /* mat_setrow */ #endif STATIC int mat_appendrow(MATrec *mat, int count, REAL *row, int *colno, REAL mult, MYBOOL checkrowmode) { int i, j, jj = 0, stcol, elmnr, orignr, newnr, firstcol; MYBOOL *addto = NULL, isA, isNZ; REAL value, saved = 0; lprec *lp = mat->lp; /* Check if we are in row order mode and should add as column instead; the matrix will be transposed at a later stage */ if(checkrowmode && mat->is_roworder) return( mat_appendcol(mat, count, row, colno, mult, FALSE) ); /* Do initialization and validation */ isA = (MYBOOL) (mat == lp->matA); isNZ = (MYBOOL) (colno != NULL); if(isNZ && (count > 0)) { if(count > 1) sortREALByINT(row, colno, count, 0, TRUE); if((colno[0] < 1) || (colno[count-1] > mat->columns)) return( 0 ); } /* else if((row != NULL) && !mat->is_roworder) */ else if(!isNZ && (row != NULL) && !mat->is_roworder) row[0] = 0; /* Capture OF definition in row mode */ if(isA && mat->is_roworder) { if(isNZ && (colno[0] == 0)) { value = row[0]; #ifdef DoMatrixRounding value = roundToPrecision(value, mat->epsvalue); #endif value = scaled_mat(lp, value, 0, lp->columns); value = my_chsign(is_maxim(lp), value); lp->orig_obj[lp->columns] = value; count--; row++; colno++; } else if(!isNZ && (row != NULL) && (row[0] != 0)) { value = saved = row[0]; #ifdef DoMatrixRounding value = roundToPrecision(value, mat->epsvalue); #endif value = scaled_mat(lp, value, 0, lp->columns); value = my_chsign(is_maxim(lp), value); lp->orig_obj[lp->columns] = value; row[0] = 0; } else lp->orig_obj[lp->columns] = 0; } /* Optionally tally and map the new non-zero values */ firstcol = mat->columns + 1; if(isNZ) { newnr = count; if(newnr) { firstcol = colno[0]; jj = colno[newnr - 1]; } } else { newnr = 0; if(row != NULL) { if(!allocMYBOOL(lp, &addto, mat->columns + 1, TRUE)) { return( newnr ); } for(i = mat->columns; i >= 1; i--) { if(fabs(row[i]) > mat->epsvalue) { addto[i] = TRUE; firstcol = i; newnr++; } } } } /* Make sure we have sufficient space */ if(!inc_mat_space(mat, newnr)) { newnr = 0; goto Done; } /* Insert the non-zero constraint values */ orignr = mat_nonzeros(mat) - 1; elmnr = orignr + newnr; for(j = mat->columns; j >= firstcol; j--) { stcol = mat->col_end[j] - 1; mat->col_end[j] = elmnr + 1; /* Add a new non-zero entry */ if(((isNZ) && (j == jj)) || ((addto != NULL) && (addto[j]))) { newnr--; if(isNZ) { value = row[newnr]; if(newnr) jj = colno[newnr - 1]; else jj = 0; } else value = row[j]; #ifdef DoMatrixRounding value = roundToPrecision(value, mat->epsvalue); #endif value *= mult; if(isA) { if(mat->is_roworder) value = my_chsign(is_chsign(lp, j), value); value = scaled_mat(lp, value, mat->rows, j); } SET_MAT_ijA(elmnr, mat->rows, j, value); elmnr--; } /* Shift previous column entries down */ i = stcol - mat->col_end[j-1] + 1; if(i > 0) { orignr -= i; elmnr -= i; COL_MAT_MOVE(elmnr+1, orignr+1, i); } } Done: if(saved != 0) row[0] = saved; FREE(addto); return( newnr ); } STATIC int mat_appendcol(MATrec *mat, int count, REAL *column, int *rowno, REAL mult, MYBOOL checkrowmode) { int i, row, elmnr, lastnr; REAL value; MYBOOL isA, isNZ; lprec *lp = mat->lp; /* Check if we are in row order mode and should add as row instead; the matrix will be transposed at a later stage */ if(checkrowmode && mat->is_roworder) return( mat_appendrow(mat, count, column, rowno, mult, FALSE) ); /* Make sure we have enough space */ /* if(!inc_mat_space(mat, mat->rows+1)) return( 0 ); */ if(column == NULL) i = 0; else if(rowno != NULL) i = count; else { int nrows = mat->rows; elmnr = 0; for(i = 1; i <= nrows; i++) if(column[i] != 0) elmnr++; i = elmnr; } if((mat_nz_unused(mat) <= i) && !inc_mat_space(mat, i)) return( 0 ); /* Do initialization and validation */ isA = (MYBOOL) (mat == lp->matA); isNZ = (MYBOOL) (column == NULL || rowno != NULL); if(isNZ && (count > 0)) { if(count > 1) sortREALByINT(column, rowno, count, 0, TRUE); if((rowno[0] < 0)) return( 0 ); } if(rowno != NULL) count--; /* Append sparse regular constraint values */ elmnr = mat->col_end[mat->columns - 1]; if(column != NULL) { row = -1; for(i = ((isNZ || !mat->is_roworder) ? 0 : 1); i <= count ; i++) { value = column[i]; if(fabs(value) > mat->epsvalue) { if(isNZ) { lastnr = row; row = rowno[i]; /* Check if we have come to the Lagrangean constraints */ if(row > mat->rows) break; if(row <= lastnr) return( -1 ); } else row = i; #ifdef DoMatrixRounding value = roundToPrecision(value, mat->epsvalue); #endif if(mat->is_roworder) value *= mult; else if(isA) { value = my_chsign(is_chsign(lp, row), value); value = scaled_mat(lp, value, row, mat->columns); if(!mat->is_roworder && (row == 0)) { lp->orig_obj[mat->columns] = value; continue; } } /* Store the item and update counters */ SET_MAT_ijA(elmnr, row, mat->columns, value); elmnr++; } } /* Fill dense Lagrangean constraints */ if(get_Lrows(lp) > 0) mat_appendcol(lp->matL, get_Lrows(lp), column+mat->rows, NULL, mult, checkrowmode); } /* Set end of data */ mat->col_end[mat->columns] = elmnr; return( mat->col_end[mat->columns] - mat->col_end[mat->columns-1] ); } STATIC int mat_checkcounts(MATrec *mat, int *rownum, int *colnum, MYBOOL freeonexit) { int i, j, n; int *rownr; if(rownum == NULL) allocINT(mat->lp, &rownum, mat->rows + 1, TRUE); if(colnum == NULL) allocINT(mat->lp, &colnum, mat->columns + 1, TRUE); for(i = 1 ; i <= mat->columns; i++) { j = mat->col_end[i - 1]; n = mat->col_end[i]; rownr = &COL_MAT_ROWNR(j); for(; j < n; j++, rownr += matRowColStep) { colnum[i]++; rownum[*rownr]++; } } n = 0; if((mat->lp->do_presolve != PRESOLVE_NONE) && (mat->lp->spx_trace || (mat->lp->verbose > NORMAL))) { for(j = 1; j <= mat->columns; j++) if(colnum[j] == 0) { n++; report(mat->lp, FULL, "mat_checkcounts: Variable %s is not used in any constraints\n", get_col_name(mat->lp, j)); } for(i = 0; i <= mat->rows; i++) if(rownum[i] == 0) { n++; report(mat->lp, FULL, "mat_checkcounts: Constraint %s empty\n", get_row_name(mat->lp, i)); } } if(freeonexit) { FREE(rownum); FREE(colnum); } return( n ); } STATIC MYBOOL mat_validate(MATrec *mat) /* Routine to make sure that row mapping arrays are valid */ { int i, j, je, *rownum; int *rownr, *colnr; if(!mat->row_end_valid) { MEMCLEAR(mat->row_end, mat->rows + 1); allocINT(mat->lp, &rownum, mat->rows + 1, TRUE); /* First tally row counts and then cumulate them */ j = mat_nonzeros(mat); rownr = &COL_MAT_ROWNR(0); for(i = 0; i < j; i++, rownr += matRowColStep) mat->row_end[*rownr]++; for(i = 1; i <= mat->rows; i++) mat->row_end[i] += mat->row_end[i - 1]; /* Calculate the column index for every non-zero */ for(i = 1; i <= mat->columns; i++) { j = mat->col_end[i - 1]; je = mat->col_end[i]; rownr = &COL_MAT_ROWNR(j); colnr = &COL_MAT_COLNR(j); for(; j < je; j++, rownr += matRowColStep, colnr += matRowColStep) { #ifdef Paranoia if(/*(*colnr < 0) || (*colnr > mat->columns) || (Normally violated in primal phase 1) */ (*rownr < 0) || (*rownr > mat->rows)) { report(mat->lp, SEVERE, "mat_validate: Matrix value storage error row %d [0..%d], column %d [1..%d]\n", *rownr, mat->rows, *colnr, mat->columns); mat->lp->spx_status = UNKNOWNERROR; return(FALSE); } #endif *colnr = i; if(*rownr == 0) mat_set_rowmap(mat, rownum[*rownr], *rownr, i, j); else mat_set_rowmap(mat, mat->row_end[*rownr - 1] + rownum[*rownr], *rownr, i, j); rownum[*rownr]++; } } FREE(rownum); mat->row_end_valid = TRUE; } if(mat == mat->lp->matA) mat->lp->model_is_valid = TRUE; return( TRUE ); } MYBOOL mat_get_data(lprec *lp, int matindex, MYBOOL isrow, int **rownr, int **colnr, REAL **value) { MATrec *mat = lp->matA; #if MatrixRowAccess == RAM_Index if(isrow) matindex = mat->row_mat[matindex]; if(rownr != NULL) *rownr = &COL_MAT_ROWNR(matindex); if(colnr != NULL) *colnr = &COL_MAT_COLNR(matindex); if(value != NULL) *value = &COL_MAT_VALUE(matindex); #else if(isrow) { if(rownr != NULL) *rownr = &ROW_MAT_ROWNR(matindex); if(colnr != NULL) *colnr = &ROW_MAT_COLNR(matindex); if(value != NULL) *value = &ROW_MAT_VALUE(matindex); } else { if(rownr != NULL) *rownr = &COL_MAT_ROWNR(matindex); if(colnr != NULL) *colnr = &COL_MAT_COLNR(matindex); if(value != NULL) *value = &COL_MAT_VALUE(matindex); } #endif return( TRUE ); } MYBOOL mat_set_rowmap(MATrec *mat, int row_mat_index, int rownr, int colnr, int col_mat_index) { #if MatrixRowAccess == RAM_Index mat->row_mat[row_mat_index] = col_mat_index; #elif MatrixColAccess==CAM_Record mat->row_mat[row_mat_index].rownr = rownr; mat->row_mat[row_mat_index].colnr = colnr; mat->row_mat[row_mat_index].value = COL_MAT_VALUE(col_mat_index); #else /* if MatrixColAccess==CAM_Vector */ mat->row_mat_rownr[row_mat_index] = rownr; mat->row_mat_colnr[row_mat_index] = colnr; mat->row_mat_value[row_mat_index] = COL_MAT_VALUE(col_mat_index); #endif return( TRUE ); } /* Implement combined binary/linear sub-search for matrix look-up */ int mat_findelm(MATrec *mat, int row, int column) { int low, high, mid, item; #if 0 if(mat->row_end_valid && (row > 0) && (ROW_MAT_COLNR(mat->row_mat[(low = mat->row_end[row-1])]) == column)) return(low); #endif if((column < 1) || (column > mat->columns)) { report(mat->lp, IMPORTANT, "mat_findelm: Column %d out of range\n", column); return( -1 ); } if((row < 0) || (row > mat->rows)) { report(mat->lp, IMPORTANT, "mat_findelm: Row %d out of range\n", row); return( -1 ); } low = mat->col_end[column - 1]; high = mat->col_end[column] - 1; if(low > high) return( -2 ); /* Do binary search logic */ mid = (low+high) / 2; item = COL_MAT_ROWNR(mid); while(high - low > LINEARSEARCH) { if(item < row) { low = mid + 1; mid = (low+high) / 2; item = COL_MAT_ROWNR(mid); } else if(item > row) { high = mid - 1; mid = (low+high) / 2; item = COL_MAT_ROWNR(mid); } else { low = mid; high = mid; } } /* Do linear scan search logic */ if((high > low) && (high - low <= LINEARSEARCH)) { item = COL_MAT_ROWNR(low); while((low < high) && (item < row)) { low++; item = COL_MAT_ROWNR(low); } if(item == row) high = low; } if((low == high) && (row == item)) return( low ); else return( -2 ); } int mat_findins(MATrec *mat, int row, int column, int *insertpos, MYBOOL validate) { int low, high, mid, item, exitvalue, insvalue; #if 0 if(mat->row_end_valid && (row > 0) && (ROW_MAT_COLNR(mat->row_mat[(low = mat->row_end[row-1])]) == column)) { insvalue = low; exitvalue = low; goto Done; } #endif insvalue = -1; if((column < 1) || (column > mat->columns)) { if((column > 0) && !validate) { insvalue = mat->col_end[mat->columns]; exitvalue = -2; goto Done; } report(mat->lp, IMPORTANT, "mat_findins: Column %d out of range\n", column); exitvalue = -1; goto Done; } if((row < 0) || (row > mat->rows)) { if((row >= 0) && !validate) { insvalue = mat->col_end[column]; exitvalue = -2; goto Done; } report(mat->lp, IMPORTANT, "mat_findins: Row %d out of range\n", row); exitvalue = -1; goto Done; } low = mat->col_end[column - 1]; insvalue = low; high = mat->col_end[column] - 1; if(low > high) { exitvalue = -2; goto Done; } /* Do binary search logic */ mid = (low+high) / 2; item = COL_MAT_ROWNR(mid); while(high - low > LINEARSEARCH) { if(item < row) { low = mid + 1; mid = (low+high) / 2; item = COL_MAT_ROWNR(mid); } else if(item > row) { high = mid - 1; mid = (low+high) / 2; item = COL_MAT_ROWNR(mid); } else { low = mid; high = mid; } } /* Do linear scan search logic */ if((high > low) && (high - low <= LINEARSEARCH)) { item = COL_MAT_ROWNR(low); while((low < high) && (item < row)) { low++; item = COL_MAT_ROWNR(low); } if(item == row) high = low; } insvalue = low; if((low == high) && (row == item)) exitvalue = low; else { if((low < mat->col_end[column]) && (COL_MAT_ROWNR(low) < row)) insvalue++; exitvalue = -2; } Done: if(insertpos != NULL) (*insertpos) = insvalue; return( exitvalue ); } STATIC REAL mat_getitem(MATrec *mat, int row, int column) { int elmnr; #ifdef DirectOverrideOF if((row == 0) && (mat == mat->lp->matA) && (mat->lp->OF_override != NULL)) return( mat->lp->OF_override[column] ); else #endif { elmnr = mat_findelm(mat, row, column); if(elmnr >= 0) return( COL_MAT_VALUE(elmnr) ); else return( 0 ); } } STATIC MYBOOL mat_additem(MATrec *mat, int row, int column, REAL delta) { int elmnr; #ifdef DirectOverrideOF if((row == 0) && (mat == mat->lp->matA) && (mat->lp->OF_override != NULL)) return( mat->lp->OF_override[column] ); else #endif { elmnr = mat_findelm(mat, row, column); if(elmnr >= 0) { COL_MAT_VALUE(elmnr) += delta; return( TRUE ); } else { mat_setitem(mat, row, column, delta); return( FALSE ); } } } STATIC MYBOOL mat_setitem(MATrec *mat, int row, int column, REAL value) { return( mat_setvalue(mat, row, column, value, FALSE) ); } STATIC void mat_multrow(MATrec *mat, int row_nr, REAL mult) { int i, k1, k2; #if 0 if(row_nr == 0) { k2 = mat->col_end[0]; for(i = 1; i <= mat->columns; i++) { k1 = k2; k2 = mat->col_end[i]; if((k1 < k2) && (COL_MAT_ROWNR(k1) == row_nr)) COL_MAT_VALUE(k1) *= mult; } } else if(mat_validate(mat)) { if(row_nr == 0) k1 = 0; else #else if(mat_validate(mat)) { if(row_nr == 0) k1 = 0; else #endif k1 = mat->row_end[row_nr-1]; k2 = mat->row_end[row_nr]; for(i = k1; i < k2; i++) ROW_MAT_VALUE(i) *= mult; } } STATIC void mat_multcol(MATrec *mat, int col_nr, REAL mult, MYBOOL DoObj) { int i, ie; MYBOOL isA; #ifdef Paranoia if((col_nr < 1) || (col_nr > mat->columns)) { report(mat->lp, IMPORTANT, "mult_column: Column %d out of range\n", col_nr); return; } #endif if(mult == 1.0) return; isA = (MYBOOL) (mat == mat->lp->matA); ie = mat->col_end[col_nr]; for(i = mat->col_end[col_nr - 1]; i < ie; i++) COL_MAT_VALUE(i) *= mult; if(isA) { if(DoObj) mat->lp->orig_obj[col_nr] *= mult; if(get_Lrows(mat->lp) > 0) mat_multcol(mat->lp->matL, col_nr, mult, DoObj); } } STATIC void mat_multadd(MATrec *mat, REAL *lhsvector, int varnr, REAL mult) { int colnr; register int ib, ie, *matRownr; register REAL *matValue; /* Handle case of a slack variable */ if(varnr <= mat->lp->rows) { lhsvector[varnr] += mult; return; } /* Do operation on the objective */ if(mat->lp->matA == mat) lhsvector[0] += get_OF_active(mat->lp, varnr, mult); /* Scan the constraint matrix target columns */ colnr = varnr - mat->lp->rows; ib = mat->col_end[colnr - 1]; ie = mat->col_end[colnr]; if(ib < ie) { /* Initialize pointers */ matRownr = &COL_MAT_ROWNR(ib); matValue = &COL_MAT_VALUE(ib); /* Then loop over all regular rows */ for(; ib < ie; ib++, matValue += matValueStep, matRownr += matRowColStep) { lhsvector[*matRownr] += mult * (*matValue); } } } STATIC MYBOOL mat_setvalue(MATrec *mat, int Row, int Column, REAL Value, MYBOOL doscale) { int elmnr, lastelm, i, RowA = Row, ColumnA = Column; MYBOOL isA; /* This function is inefficient if used to add new matrix entries in other places than at the end of the matrix. OK for replacing existing a non-zero value with another non-zero value */ isA = (MYBOOL) (mat == mat->lp->matA); if(mat->is_roworder) swapINT(&Row, &Column); /* Set small numbers to zero */ if(fabs(Value) < mat->epsvalue) Value = 0; #ifdef DoMatrixRounding else Value = roundToPrecision(Value, mat->epsvalue); #endif /* Check if we need to update column space */ if(Column > mat->columns) { if(isA) inc_col_space(mat->lp, ColumnA - mat->columns); else inc_matcol_space(mat, Column - mat->columns); } /* Find out if we already have such an entry, or return insertion point */ i = mat_findins(mat, Row, Column, &elmnr, FALSE); if(i == -1) return(FALSE); if(isA) set_action(&mat->lp->spx_action, ACTION_REBASE | ACTION_RECOMPUTE | ACTION_REINVERT); if(i >= 0) { /* there is an existing entry */ if(fabs(Value) > mat->epsvalue) { /* we replace it by something non-zero */ if(isA) { Value = my_chsign(is_chsign(mat->lp, RowA), Value); if(doscale && mat->lp->scaling_used) Value = scaled_mat(mat->lp, Value, RowA, ColumnA); } COL_MAT_VALUE(elmnr) = Value; } else { /* setting existing non-zero entry to zero. Remove the entry */ /* This might remove an entire column, or leave just a bound. No nice solution for that yet */ /* Shift up tail end of the matrix */ lastelm = mat_nonzeros(mat); #if 0 for(i = elmnr; i < lastelm ; i++) { COL_MAT_COPY(i, i + 1); } #else lastelm -= elmnr; COL_MAT_MOVE(elmnr, elmnr + 1, lastelm); #endif for(i = Column; i <= mat->columns; i++) mat->col_end[i]--; mat->row_end_valid = FALSE; } } else if(fabs(Value) > mat->epsvalue) { /* no existing entry. make new one only if not nearly zero */ /* check if more space is needed for matrix */ if(!inc_mat_space(mat, 1)) return(FALSE); if(Column > mat->columns) { i = mat->columns + 1; if(isA) shift_coldata(mat->lp, i, ColumnA - mat->columns, NULL); else mat_shiftcols(mat, &i, Column - mat->columns, NULL); } /* Shift down tail end of the matrix by one */ lastelm = mat_nonzeros(mat); #if 1 /* Does compiler optimization work better here? */ for(i = lastelm; i > elmnr ; i--) { COL_MAT_COPY(i, i - 1); } #else lastelm -= elmnr - 1; COL_MAT_MOVE(elmnr + 1, elmnr, lastelm); #endif /* Set new element */ if(isA) { Value = my_chsign(is_chsign(mat->lp, RowA), Value); if(doscale) Value = scaled_mat(mat->lp, Value, RowA, ColumnA); } SET_MAT_ijA(elmnr, Row, Column, Value); /* Update column indexes */ for(i = Column; i <= mat->columns; i++) mat->col_end[i]++; mat->row_end_valid = FALSE; } if(isA && (mat->lp->var_is_free != NULL) && (mat->lp->var_is_free[ColumnA] > 0)) return( mat_setvalue(mat, RowA, mat->lp->var_is_free[ColumnA], -Value, doscale) ); return(TRUE); } STATIC MYBOOL mat_appendvalue(MATrec *mat, int Row, REAL Value) { int *elmnr, Column = mat->columns; /* Set small numbers to zero */ if(fabs(Value) < mat->epsvalue) Value = 0; #ifdef DoMatrixRounding else Value = roundToPrecision(Value, mat->epsvalue); #endif /* Check if more space is needed for matrix */ if(!inc_mat_space(mat, 1)) return(FALSE); #ifdef Paranoia /* Check valid indeces */ if((Row < 0) || (Row > mat->rows)) { report(mat->lp, SEVERE, "mat_appendvalue: Invalid row index %d specified\n", Row); return(FALSE); } #endif /* Get insertion point and set value */ elmnr = mat->col_end + Column; SET_MAT_ijA((*elmnr), Row, Column, Value); /* Update column count */ (*elmnr)++; mat->row_end_valid = FALSE; return(TRUE); } STATIC MYBOOL mat_equalRows(MATrec *mat, int baserow, int comprow) { MYBOOL status = FALSE; if(mat_validate(mat)) { int bj1 = 0, ej1, bj2 = 0, ej2; /* Get starting and ending positions */ if(baserow >= 0) bj1 = mat->row_end[baserow-1]; ej1 = mat->row_end[baserow]; if(comprow >= 0) bj2 = mat->row_end[comprow-1]; ej2 = mat->row_end[comprow]; /* Fail if row lengths are unequal */ if((ej1-bj1) != (ej2-bj2)) return( status ); /* Compare column index and value, element by element */ for(; bj1 < ej1; bj1++, bj2++) { if(COL_MAT_COLNR(bj1) != COL_MAT_COLNR(bj2)) break; #if 1 if(fabs(get_mat_byindex(mat->lp, bj1, TRUE, FALSE)-get_mat_byindex(mat->lp, bj2, TRUE, FALSE)) > mat->lp->epsprimal) #else if(fabs(COL_MAT_VALUE(bj1)-COL_MAT_VALUE(bj2)) > mat->lp->epsprimal) #endif break; } status = (MYBOOL) (bj1 == ej1); } return( status ); } STATIC int mat_findcolumn(MATrec *mat, int matindex) { int j; for(j = 1; j <= mat->columns; j++) { if(matindex < mat->col_end[j]) break; } return(j); } STATIC int mat_expandcolumn(MATrec *mat, int colnr, REAL *column, int *nzlist, MYBOOL signedA) { MYBOOL isA = (MYBOOL) (mat->lp->matA == mat); int i, ie, j, nzcount = 0; REAL *matValue; int *matRownr; signedA &= isA; /* Retrieve a column from the user data matrix A */ MEMCLEAR(column, mat->rows + 1); if(isA) { column[0] = mat->lp->orig_obj[colnr]; if(signedA && is_chsign(mat->lp, 0)) column[0] = -column[0]; } i = mat->col_end[colnr - 1]; ie = mat->col_end[colnr]; matRownr = &COL_MAT_ROWNR(i); matValue = &COL_MAT_VALUE(i); for(; i < ie; i++, matRownr += matRowColStep, matValue += matValueStep) { j = *matRownr; column[j] = *matValue; if(signedA && is_chsign(mat->lp, j)) column[j] = -column[j]; nzcount++; if(nzlist != NULL) nzlist[nzcount] = j; } if(nzlist != NULL) nzlist[0] = nzcount; return( nzcount ); } STATIC MYBOOL mat_computemax(MATrec *mat) { int *rownr = &COL_MAT_ROWNR(0), *colnr = &COL_MAT_COLNR(0), i = 0, ie = mat->col_end[mat->columns], ez = 0; REAL *value = &COL_MAT_VALUE(0), epsmachine = mat->lp->epsmachine, absvalue; /* Prepare arrays */ if(!allocREAL(mat->lp, &mat->colmax, mat->columns_alloc+1, AUTOMATIC) || !allocREAL(mat->lp, &mat->rowmax, mat->rows_alloc+1, AUTOMATIC)) return( FALSE ); MEMCLEAR(mat->colmax, mat->columns+1); MEMCLEAR(mat->rowmax, mat->rows+1); /* Obtain the row and column maxima in one sweep */ mat->dynrange = mat->lp->infinite; for(; i < ie; i++, rownr += matRowColStep, colnr += matRowColStep, value += matValueStep) { absvalue = fabs(*value); SETMAX(mat->colmax[*colnr], absvalue); SETMAX(mat->rowmax[*rownr], absvalue); SETMIN(mat->dynrange, absvalue); if(absvalue < epsmachine) ez++; } /* Lastly, compute the global maximum and get the dynamic range */ for(i = 1; i <= mat->rows; i++) SETMAX(mat->rowmax[0], mat->rowmax[i]); mat->infnorm = mat->colmax[0] = mat->rowmax[0]; if(mat->dynrange == 0) { report(mat->lp, SEVERE, "%d matrix contains zero-valued coefficients.\n", ez); mat->dynrange = mat->lp->infinite; } else { mat->dynrange = mat->infnorm / mat->dynrange; if(ez > 0) report(mat->lp, IMPORTANT, "%d matrix coefficients below machine precision were found.\n", ez); } return( TRUE ); } STATIC MYBOOL mat_transpose(MATrec *mat) { int i, j, nz, k; MYBOOL status; status = mat_validate(mat); if(status) { /* Create a column-ordered sparse element list; "column" index must be shifted */ nz = mat_nonzeros(mat); if(nz > 0) { #if MatrixColAccess==CAM_Record MATitem *newmat; newmat = (MATitem *) malloc((mat->mat_alloc) * sizeof(*(mat->col_mat))); j = mat->row_end[0]; for(i = nz-1; i >= j ; i--) { k = i-j; newmat[k] = mat->col_mat[mat->row_mat[i]]; newmat[k].row_nr = newmat[k].col_nr; } for(i = j-1; i >= 0 ; i--) { k = nz-j+i; newmat[k] = mat->col_mat[mat->row_mat[i]]; newmat[k].row_nr = newmat[k].col_nr; } swapPTR((void **) &mat->col_mat, (void **) &newmat); FREE(newmat); #else /*if MatrixColAccess==CAM_Vector*/ REAL *newValue = NULL; int *newRownr = NULL; allocREAL(mat->lp, &newValue, mat->mat_alloc, FALSE); allocINT(mat->lp, &newRownr, mat->mat_alloc, FALSE); j = mat->row_end[0]; for(i = nz-1; i >= j ; i--) { k = i-j; newValue[k] = ROW_MAT_VALUE(i); newRownr[k] = ROW_MAT_COLNR(i); } for(i = j-1; i >= 0 ; i--) { k = nz-j+i; newValue[k] = ROW_MAT_VALUE(i); newRownr[k] = ROW_MAT_COLNR(i); } swapPTR((void **) &mat->col_mat_rownr, (void **) &newRownr); swapPTR((void **) &mat->col_mat_value, (void **) &newValue); FREE(newValue); FREE(newRownr); #endif } /* Transfer row start to column start position; must adjust for different offsets */ if(mat->rows == mat->rows_alloc) inc_matcol_space(mat, 1); j = mat->row_end[0]; for(i = mat->rows; i >= 1; i--) mat->row_end[i] -= j; mat->row_end[mat->rows] = nz; swapPTR((void **) &mat->row_end, (void **) &mat->col_end); /* Swap arrays of maximum values */ swapPTR((void **) &mat->rowmax, (void **) &mat->colmax); /* Swap array sizes */ swapINT(&mat->rows, &mat->columns); swapINT(&mat->rows_alloc, &mat->columns_alloc); /* Finally set current storage mode */ mat->is_roworder = (MYBOOL) !mat->is_roworder; mat->row_end_valid = FALSE; } return(status); } /* ---------------------------------------------------------------------------------- */ /* Change-tracking routines */ /* ---------------------------------------------------------------------------------- */ STATIC DeltaVrec *createUndoLadder(lprec *lp, int levelitems, int maxlevels) { DeltaVrec *hold; hold = (DeltaVrec *) malloc(sizeof(*hold)); hold->lp = lp; hold->activelevel = 0; hold->tracker = mat_create(lp, levelitems, 0, 0.0); inc_matcol_space(hold->tracker, maxlevels); return( hold ); } STATIC int incrementUndoLadder(DeltaVrec *DV) { DV->activelevel++; inc_matcol_space(DV->tracker, 1); mat_shiftcols(DV->tracker, &(DV->activelevel), 1, NULL); DV->tracker->columns++; return(DV->activelevel); } STATIC MYBOOL modifyUndoLadder(DeltaVrec *DV, int itemno, REAL target[], REAL newvalue) { MYBOOL status; int varindex = itemno; REAL oldvalue = target[itemno]; #ifndef UseMilpSlacksRCF /* Check if we should include ranged constraints */ varindex -= DV->lp->rows; #endif status = mat_appendvalue(DV->tracker, varindex, oldvalue); target[itemno] = newvalue; return(status); } STATIC int countsUndoLadder(DeltaVrec *DV) { if(DV->activelevel > 0) return( mat_collength(DV->tracker, DV->activelevel) ); else return( 0 ); } STATIC int restoreUndoLadder(DeltaVrec *DV, REAL target[]) { int iD = 0; if(DV->activelevel > 0) { MATrec *mat = DV->tracker; int iB = mat->col_end[DV->activelevel-1], iE = mat->col_end[DV->activelevel], *matRownr = &COL_MAT_ROWNR(iB); REAL *matValue = &COL_MAT_VALUE(iB), oldvalue; /* Restore the values */ iD = iE-iB; for(; iB < iE; iB++, matValue += matValueStep, matRownr += matRowColStep) { oldvalue = *matValue; #ifdef UseMilpSlacksRCF /* Check if we should include ranged constraints */ target[(*matRownr)] = oldvalue; #else target[DV->lp->rows+(*matRownr)] = oldvalue; #endif } /* Get rid of the changes */ mat_shiftcols(DV->tracker, &(DV->activelevel), -1, NULL); } return(iD); } STATIC int decrementUndoLadder(DeltaVrec *DV) { int deleted = 0; if(DV->activelevel > 0) { deleted = mat_shiftcols(DV->tracker, &(DV->activelevel), -1, NULL); DV->activelevel--; DV->tracker->columns--; } return(deleted); } STATIC MYBOOL freeUndoLadder(DeltaVrec **DV) { if((DV == NULL) || (*DV == NULL)) return(FALSE); mat_free(&((*DV)->tracker)); FREE(*DV); return(TRUE); } STATIC MYBOOL appendUndoPresolve(lprec *lp, MYBOOL isprimal, REAL beta, int colnrDep) { MATrec *mat; /* Point to correct undo structure */ if(isprimal) mat = lp->presolve_undo->primalundo->tracker; else mat = lp->presolve_undo->dualundo->tracker; /* Append the data */ if((colnrDep > 0) && (beta != 0) && (mat != NULL) && (mat->col_tag[0] > 0)) { int ix = mat->col_tag[0]; #if 0 report(lp, NORMAL, "appendUndoPresolve: %s %g * x%d\n", ( beta < 0 ? "-" : "+"), fabs(beta), colnrDep); #endif /* Do normal user variable case */ if(colnrDep <= lp->columns) mat_setvalue(mat, colnrDep, ix, beta, FALSE); /* Handle case where a slack variable is referenced */ else { int ipos, jx = mat->col_tag[ix]; mat_setvalue(mat, jx, ix, beta, FALSE); jx = mat_findins(mat, jx, ix, &ipos, FALSE); COL_MAT_ROWNR(ipos) = colnrDep; } return( TRUE ); } else return( FALSE ); } STATIC MYBOOL addUndoPresolve(lprec *lp, MYBOOL isprimal, int colnrElim, REAL alpha, REAL beta, int colnrDep) { int ix; DeltaVrec **DV; MATrec *mat; presolveundorec *psdata = lp->presolve_undo; /* Point to and initialize undo structure at first call */ if(isprimal) { DV = &(psdata->primalundo); if(*DV == NULL) { *DV = createUndoLadder(lp, lp->columns+1, lp->columns); mat = (*DV)->tracker; mat->epsvalue = lp->matA->epsvalue; allocINT(lp, &(mat->col_tag), lp->columns+1, FALSE); mat->col_tag[0] = 0; } } else { DV = &(psdata->dualundo); if(*DV == NULL) { *DV = createUndoLadder(lp, lp->rows+1, lp->rows); mat = (*DV)->tracker; mat->epsvalue = lp->matA->epsvalue; allocINT(lp, &(mat->col_tag), lp->rows+1, FALSE); mat->col_tag[0] = 0; } } mat = (*DV)->tracker; #if 0 report(lp, NORMAL, "addUndoPresolve: x%d = %g %s %g * x%d\n", colnrElim, alpha, ( beta < 0 ? "-" : "+"), fabs(beta), colnrDep); #endif /* Add the data */ ix = mat->col_tag[0] = incrementUndoLadder(*DV); mat->col_tag[ix] = colnrElim; if(alpha != 0) mat_setvalue(mat, 0, ix, alpha, FALSE); /* mat_appendvalue(*mat, 0, alpha);*/ if((colnrDep > 0) && (beta != 0)) { if(colnrDep > lp->columns) return( appendUndoPresolve(lp, isprimal, beta, colnrDep) ); else mat_setvalue(mat, colnrDep, ix, beta, FALSE); } return( TRUE ); } /* ---------------------------------------------------------------------------------- */ /* High level matrix inverse and product routines in lp_solve */ /* ---------------------------------------------------------------------------------- */ /* ---------------------------------------------------------------------------------- */ /* A brief description of the basis inverse and factorization logic in lp_solve */ /* ---------------------------------------------------------------------------------- */ /* In order to better understand the legacy code for operating with the basis and its factorization in lp_solve I (KE) will briefly explain the conventions and associated matrix algebra. Note that with lp_solve version 5.5, it is also possible to direct lp_solve to use the traditional (textbook) format by setting the obj_in_B parameter to FALSE. The matrix description of a linear program (as represented by lp_solve) goes like this: maximize c'x subject to r <= Ax <= b where l <= x <= u The matrix A is partitioned into two column sets [B|N], where B is a square matrix of "basis" variables containing non-fixed variables of the linear program at any given stage and N is the submatrix of corresponding non-basic, fixed variables. The variables (columns) in N may be fixed at their lower or upper levels. Similarly, the c vector is partitioned into the basic and non-basic parts [z|n]. While lp_solve stores the objective vector c in a dense format, and the constraint matrix A in a (fairly standard) sparse format, the column vectors passed to the factorization routine include the objective coefficient at row index 0. (In versions of lp_solve before v5.2, c was actually explicitly stored as the 0-th row of A). The expanded matrix may be called the "A~" form and looks like this: A~ = [ c ] [ A ] Linear programming involves solving linear equations based on the square basis matrix B, which includes is a subset of columns from A~. The implications of the common storage of c and A (e.g. A~) vs. the inverse / factorization of B for the operations and updates performed by the simplex routine therefore needs to be understood. As a consquence of A~, in lp_solve B is stored in an expanded, bordered format using the following (non-singular) representation: B~ = [ 1 z ] [ 0 B ] Any basis inversion / factorization engine used by lp_solve must therefore explicitly represent and handle the implications of this structure for associated matrix operations. The standard matrix formula for computing the inverse of a bordered matrix shows what the inversion of B~ actually produces: Inv(B~) = [ 1 -z*Inv(B) ] [ 0 Inv(B) ] The A~ and B~ representations require awareness by the developer of the side effects of the presence of the top row when doing product operations such as b'N, btran and ftran. Note in particular z*Inv(B) in the top row of Inv(B~), which is actually the dual solution vector of the given basis. This fact makes a very common update in the simplex algorithm (reduced costs) returnable as a vector simply by setting 1 at the top of a vector being pre-multiplied with Inv(B~). However, if the objective vector (c) is changed, the expanded representation requires that B / B~ be refactorized. Also, when doing FTRAN, BTRAN and x'A-type operations, you will patently get the incorrect result if you simply copy the operations given in textbooks. First I'll show the results of an FTRAN operation: Bx = a ==> x = FTRAN(a) In lp_solve, this operation solves: [ 1 z ] [y] = [d] [ 0 B ] [x] [a] Using the Inv(B~) expression earlier, the FTRAN result is therefore: [y] = [ 1 -z*Inv(B) ] [d] = [ d - z*Inv(B)*a ] [x] [ 0 Inv(B) ] [a] [ Inv(B)*a ] As an example, the value of the dual objective can be returned at the 0-th index by passing the active RHS vector with 0 at the 0-th position. Similarily, doing the left solve - performing the BTRAN calculation: [x y] [ 1 z ] = [d a'] [ 0 B ] ... will produce the following result in lp_solve: [x y] = [d a'] [ 1 -z*Inv(B) ] = [ d | -d*z*Inv(B) + a'*Inv(B) ] [ 0 Inv(B) ] So, if you thought you were simply computing "a'*Inv(B)", look again. In order to produce the desired result, you have to set d to 0 before the BTRAN operation. On the other hand, if you set d to 1 and a to 0, then you are very conveniently on your way to obtain the reduced costs (needs a further matrix premultiplication with non-basic variables). Incidentally, the BTRAN with [1 0] that yields [ 1 | -z*Inv(B) ] can also be used as a fast way of checking the accuracy of the current factorization. Equipped with this understanding, I hope that you see that the approach in lp_solve is actually pretty convenient. It also becomes easier to extend functionality in lp_solve by drawing on formulas and expressions from LP literature that otherwise assume the non-bordered syntax and representation. Kjell Eikland -- November 2003 KE update -- April 2005 KE update -- June 2005 */ STATIC MYBOOL __WINAPI invert(lprec *lp, MYBOOL shiftbounds, MYBOOL final) { MYBOOL *usedpos, resetbasis; REAL test; int k, i, j; int singularities, usercolB; /* Make sure the tags are correct */ if(!mat_validate(lp->matA)) { lp->spx_status = INFEASIBLE; return(FALSE); } /* Create the inverse management object at the first call to invert() */ if(lp->invB == NULL) lp->bfp_init(lp, lp->rows, 0, NULL); else lp->bfp_preparefactorization(lp); singularities = 0; /* Must save spx_status since it is used to carry information about the presence and handling of singular columns in the matrix */ if(userabort(lp, MSG_INVERT)) return(FALSE); #ifdef Paranoia if(lp->spx_trace) report(lp, DETAILED, "invert: Iter %10g, fact-length %7d, OF " RESULTVALUEMASK ".\n", (double) get_total_iter(lp), lp->bfp_colcount(lp), (double) -lp->rhs[0]); #endif /* Store state of pre-existing basis, and at the same time check if the basis is I; in this case take the easy way out */ if(!allocMYBOOL(lp, &usedpos, lp->sum + 1, TRUE)) { lp->bb_break = TRUE; return(FALSE); } usedpos[0] = TRUE; usercolB = 0; for(i = 1; i <= lp->rows; i++) { k = lp->var_basic[i]; if(k > lp->rows) usercolB++; usedpos[k] = TRUE; } #ifdef Paranoia if(!verify_basis(lp)) report(lp, SEVERE, "invert: Invalid basis detected (iter %g).\n", (double) get_total_iter(lp)); #endif /* Tally matrix nz-counts and check if we should reset basis indicators to all slacks */ resetbasis = (MYBOOL) ((usercolB > 0) && lp->bfp_canresetbasis(lp)); k = 0; for(i = 1; i <= lp->rows; i++) { if(lp->var_basic[i] > lp->rows) k += mat_collength(lp->matA, lp->var_basic[i] - lp->rows) + (is_OF_nz(lp,lp->var_basic[i] - lp->rows) ? 1 : 0); if(resetbasis) { j = lp->var_basic[i]; if(j > lp->rows) lp->is_basic[j] = FALSE; lp->var_basic[i] = i; lp->is_basic[i] = TRUE; } } /* Now do the refactorization */ singularities = lp->bfp_factorize(lp, usercolB, k, usedpos, final); /* Do user reporting */ if(userabort(lp, MSG_INVERT)) goto Cleanup; /* Finalize factorization/inversion */ lp->bfp_finishfactorization(lp); /* Recompute the RHS ( Ref. lp_solve inverse logic and Chvatal p. 121 ) */ #ifdef DebugInv blockWriteLREAL(stdout, "RHS-values pre invert", lp->rhs, 0, lp->rows); #endif recompute_solution(lp, shiftbounds); restartPricer(lp, AUTOMATIC); #ifdef DebugInv blockWriteLREAL(stdout, "RHS-values post invert", lp->rhs, 0, lp->rows); #endif Cleanup: /* Check for numerical instability indicated by frequent refactorizations */ test = get_refactfrequency(lp, FALSE); if(test < MIN_REFACTFREQUENCY) { test = get_refactfrequency(lp, TRUE); report(lp, NORMAL, "invert: Refactorization frequency %.1g indicates numeric instability.\n", test); lp->spx_status = NUMFAILURE; } FREE(usedpos); return((MYBOOL) (singularities <= 0)); } /* invert */ STATIC MYBOOL fimprove(lprec *lp, REAL *pcol, int *nzidx, REAL roundzero) { REAL *errors, sdp; int j; MYBOOL Ok = TRUE; allocREAL(lp, &errors, lp->rows + 1, FALSE); if(errors == NULL) { Ok = FALSE; return(Ok); } MEMCOPY(errors, pcol, lp->rows + 1); lp->bfp_ftran_normal(lp, pcol, nzidx); prod_Ax(lp, NULL, pcol, NULL, 0.0, -1, errors, NULL, MAT_ROUNDDEFAULT); lp->bfp_ftran_normal(lp, errors, NULL); sdp = 0; for(j = 1; j <= lp->rows; j++) if(fabs(errors[j])>sdp) sdp = fabs(errors[j]); if(sdp > lp->epsmachine) { report(lp, DETAILED, "Iterative FTRAN correction metric %g", sdp); for(j = 1; j <= lp->rows; j++) { pcol[j] += errors[j]; my_roundzero(pcol[j], roundzero); } } FREE(errors); return(Ok); } STATIC MYBOOL bimprove(lprec *lp, REAL *rhsvector, int *nzidx, REAL roundzero) { int j; REAL *errors, err, maxerr; MYBOOL Ok = TRUE; allocREAL(lp, &errors, lp->sum + 1, FALSE); if(errors == NULL) { Ok = FALSE; return(Ok); } MEMCOPY(errors, rhsvector, lp->sum + 1); /* Solve Ax=b for x, compute b back */ lp->bfp_btran_normal(lp, errors, nzidx); prod_xA(lp, NULL, errors, NULL, 0.0, 1.0, errors, NULL, MAT_ROUNDDEFAULT); /* Take difference with ingoing values, while shifting the column values to the rows section and zeroing the columns again */ for(j = 1; j <= lp->rows; j++) errors[j] = errors[lp->rows+lp->var_basic[j]] - rhsvector[j]; for(j = lp->rows; j <= lp->sum; j++) errors[j] = 0; /* Solve the b errors for the iterative x adjustment */ lp->bfp_btran_normal(lp, errors, NULL); /* Generate the adjustments and compute statistic */ maxerr = 0; for(j = 1; j <= lp->rows; j++) { if(lp->var_basic[j]<=lp->rows) continue; err = errors[lp->rows+lp->var_basic[j]]; if(fabs(err)>maxerr) maxerr = fabs(err); } if(maxerr > lp->epsmachine) { report(lp, DETAILED, "Iterative BTRAN correction metric %g", maxerr); for(j = 1; j <= lp->rows; j++) { if(lp->var_basic[j]<=lp->rows) continue; rhsvector[j] += errors[lp->rows+lp->var_basic[j]]; my_roundzero(rhsvector[j], roundzero); } } FREE(errors); return(Ok); } STATIC void ftran(lprec *lp, REAL *rhsvector, int *nzidx, REAL roundzero) { #if 0 if(is_action(lp->improve, IMPROVE_SOLUTION) && lp->bfp_pivotcount(lp)) fimprove(lp, rhsvector, nzidx, roundzero); else #endif lp->bfp_ftran_normal(lp, rhsvector, nzidx); } STATIC void btran(lprec *lp, REAL *rhsvector, int *nzidx, REAL roundzero) { #if 0 if(is_action(lp->improve, IMPROVE_SOLUTION) && lp->bfp_pivotcount(lp)) bimprove(lp, rhsvector, nzidx, roundzero); else #endif lp->bfp_btran_normal(lp, rhsvector, nzidx); } STATIC MYBOOL fsolve(lprec *lp, int varin, REAL *pcol, int *nzidx, REAL roundzero, REAL ofscalar, MYBOOL prepareupdate) /* Was setpivcol in versions earlier than 4.0.1.8 - KE */ { MYBOOL ok = TRUE; if(varin > 0) obtain_column(lp, varin, pcol, nzidx, NULL); /* Solve, adjusted for objective function scalar */ pcol[0] *= ofscalar; if(prepareupdate) lp->bfp_ftran_prepare(lp, pcol, nzidx); else ftran(lp, pcol, nzidx, roundzero); return(ok); } /* fsolve */ STATIC MYBOOL bsolve(lprec *lp, int row_nr, REAL *rhsvector, int *nzidx, REAL roundzero, REAL ofscalar) { MYBOOL ok = TRUE; if(row_nr >= 0) /* Note that row_nr == 0 returns the [1, 0...0 ] vector */ row_nr = obtain_column(lp, row_nr, rhsvector, nzidx, NULL); /* Solve, adjusted for objective function scalar */ rhsvector[0] *= ofscalar; btran(lp, rhsvector, nzidx, roundzero); return(ok); } /* bsolve */ /* Vector compression and expansion routines */ STATIC MYBOOL vec_compress(REAL *densevector, int startpos, int endpos, REAL epsilon, REAL *nzvector, int *nzindex) { int n; if((densevector == NULL) || (nzindex == NULL) || (startpos > endpos)) return( FALSE ); n = 0; densevector += startpos; while(startpos <= endpos) { if(fabs(*densevector) > epsilon) { /* Apply zero-threshold */ if(nzvector != NULL) /* Only produce index if no nzvector is given */ nzvector[n] = *densevector; n++; nzindex[n] = startpos; } startpos++; densevector++; } nzindex[0] = n; return( TRUE ); } STATIC MYBOOL vec_expand(REAL *nzvector, int *nzindex, REAL *densevector, int startpos, int endpos) { int i, n; n = nzindex[0]; i = nzindex[n]; densevector += endpos; while(endpos >= startpos) { /* Loop from behind to allow densevector == nzvector */ if(endpos == i) { n--; *densevector = nzvector[n]; i = nzindex[n]; } else *densevector = 0; endpos--; densevector--; } return( TRUE ); } /* ----------------------------------------------------------------------- */ /* Sparse matrix product routines and utility */ /* ----------------------------------------------------------------------- */ STATIC MYBOOL get_colIndexA(lprec *lp, int varset, int *colindex, MYBOOL append) { int i, varnr, P1extraDim, vb, ve, n, nrows = lp->rows, nsum = lp->sum; MYBOOL omitfixed, omitnonfixed; REAL v; /* Find what variable range to scan - default is {SCAN_USERVARS} */ /* First determine the starting position; add from the top, going down */ P1extraDim = abs(lp->P1extraDim); vb = nrows + 1; if(varset & SCAN_ARTIFICIALVARS) vb = nsum - P1extraDim + 1; if(varset & SCAN_USERVARS) vb = nrows + 1; if(varset & SCAN_SLACKVARS) vb = 1; /* Then determine the ending position, add from the bottom, going up */ ve = nsum; if(varset & SCAN_SLACKVARS) ve = nrows; if(varset & SCAN_USERVARS) ve = nsum - P1extraDim; if(varset & SCAN_ARTIFICIALVARS) ve = nsum; /* Adjust for partial pricing */ if(varset & SCAN_PARTIALBLOCK) { SETMAX(vb, partial_blockStart(lp, FALSE)); SETMIN(ve, partial_blockEnd(lp, FALSE)); } /* Determine exclusion columns */ omitfixed = (MYBOOL) ((varset & OMIT_FIXED) != 0); omitnonfixed = (MYBOOL) ((varset & OMIT_NONFIXED) != 0); if(omitfixed && omitnonfixed) return(FALSE); /* Scan the target colums */ if(append) n = colindex[0]; else n = 0; for(varnr = vb; varnr <= ve; varnr++) { /* Skip gap in the specified column scan range (possibly user variables) */ if(varnr > nrows) { if((varnr <= nsum-P1extraDim) && !(varset & SCAN_USERVARS)) continue; #if 1 /* Skip empty columns */ if(/*(lp->P1extraVal == 0) &&*/ (mat_collength(lp->matA, varnr-nrows) == 0)) continue; #endif } /* Find if the variable is in the scope - default is {Ø} */ i = lp->is_basic[varnr]; if((varset & USE_BASICVARS) > 0 && (i)) ; else if((varset & USE_NONBASICVARS) > 0 && (!i)) ; else continue; v = lp->upbo[varnr]; if((omitfixed && (v == 0)) || (omitnonfixed && (v != 0))) continue; /* Append to list */ n++; colindex[n] = varnr; } colindex[0] = n; return(TRUE); } STATIC int prod_Ax(lprec *lp, int *coltarget, REAL *input, int *nzinput, REAL roundzero, REAL ofscalar, REAL *output, int *nzoutput, int roundmode) /* prod_Ax is only used in fimprove; note that it is NOT VALIDATED/verified as of 20030801 - KE */ { int j, colnr, ib, ie, vb, ve; MYBOOL localset, localnz = FALSE, isRC; MATrec *mat = lp->matA; REAL sdp; REAL *value; int *rownr; /* Find what variable range to scan - default is {SCAN_USERVARS} */ /* Define default column target if none was provided */ isRC = (MYBOOL) ((roundmode & MAT_ROUNDRC) != 0); localset = (MYBOOL) (coltarget == NULL); if(localset) { int varset = SCAN_SLACKVARS | SCAN_USERVARS | USE_BASICVARS | OMIT_FIXED; if(isRC && is_piv_mode(lp, PRICE_PARTIAL) && !is_piv_mode(lp, PRICE_FORCEFULL)) varset |= SCAN_PARTIALBLOCK; coltarget = (int *) mempool_obtainVector(lp->workarrays, lp->sum+1, sizeof(*coltarget)); if(!get_colIndexA(lp, varset, coltarget, FALSE)) { mempool_releaseVector(lp->workarrays, (char *) coltarget, FALSE); return(FALSE); } } localnz = (MYBOOL) (nzinput == NULL); if(localnz) { nzinput = (int *) mempool_obtainVector(lp->workarrays, lp->rows+1, sizeof(*nzinput)); vec_compress(input, 0, lp->rows, lp->matA->epsvalue, NULL, nzinput); } /* Scan the columns */ vb = 1; ve = coltarget[0]; for(vb = 1; vb <= coltarget[0]; vb++) { colnr = coltarget[vb]; j = lp->is_basic[colnr]; /* Perform the multiplication */ sdp = ofscalar*input[j]; if(colnr <= lp->rows) /* A slack variable is in the basis */ output[colnr] += sdp; else { /* A normal variable is in the basis */ colnr -= lp->rows; ib = mat->col_end[colnr - 1]; ie = mat->col_end[colnr]; rownr = &COL_MAT_ROWNR(ib); value = &COL_MAT_VALUE(ib); for(; ib < ie; ib++, rownr += matRowColStep, value += matValueStep) { output[*rownr] += (*value)*sdp; } } } roundVector(output+1, lp->rows-1, roundzero); /* Clean up and return */ if(localset) mempool_releaseVector(lp->workarrays, (char *) coltarget, FALSE); if(localnz) mempool_releaseVector(lp->workarrays, (char *) nzinput, FALSE); return(TRUE); } STATIC int prod_xA(lprec *lp, int *coltarget, REAL *input, int *nzinput, REAL roundzero, REAL ofscalar, REAL *output, int *nzoutput, int roundmode) /* Note that the dot product xa is stored at the active column index of A, i.e. of a. This means that if the basis only contains non-slack variables, output may point to the same vector as input, without overwriting the [0..rows] elements. */ { int colnr, rownr, varnr, ib, ie, vb, ve, nrows = lp->rows; MYBOOL localset, localnz = FALSE, includeOF, isRC; REALXP vmax; register REALXP v; int inz, *rowin, countNZ = 0; MATrec *mat = lp->matA; register REAL *matValue; register int *matRownr; /* Clean output area (only necessary if we are returning the full vector) */ isRC = (MYBOOL) ((roundmode & MAT_ROUNDRC) != 0); if(nzoutput == NULL) { if(input == output) MEMCLEAR(output+nrows+1, lp->columns); else MEMCLEAR(output, lp->sum+1); } /* Find what variable range to scan - default is {SCAN_USERVARS} */ /* Define default column target if none was provided */ localset = (MYBOOL) (coltarget == NULL); if(localset) { int varset = SCAN_SLACKVARS | SCAN_USERVARS | USE_NONBASICVARS | OMIT_FIXED; if(isRC && is_piv_mode(lp, PRICE_PARTIAL) && !is_piv_mode(lp, PRICE_FORCEFULL)) varset |= SCAN_PARTIALBLOCK; coltarget = (int *) mempool_obtainVector(lp->workarrays, lp->sum+1, sizeof(*coltarget)); if(!get_colIndexA(lp, varset, coltarget, FALSE)) { mempool_releaseVector(lp->workarrays, (char *) coltarget, FALSE); return(FALSE); } } /*#define UseLocalNZ*/ #ifdef UseLocalNZ localnz = (MYBOOL) (nzinput == NULL); if(localnz) { nzinput = (int *) mempool_obtainVector(lp->workarrays, nrows+1, sizeof(*nzinput)); vec_compress(input, 0, nrows, lp->matA->epsvalue, NULL, nzinput); } #endif includeOF = (MYBOOL) (((nzinput == NULL) || (nzinput[1] == 0)) && (input[0] != 0) && lp->obj_in_basis); /* Scan the target colums */ vmax = 0; ve = coltarget[0]; for(vb = 1; vb <= ve; vb++) { varnr = coltarget[vb]; if(varnr <= nrows) { v = input[varnr]; } else { colnr = varnr - nrows; v = 0; ib = mat->col_end[colnr - 1]; ie = mat->col_end[colnr]; if(ib < ie) { /* Do dense input vector version */ #ifdef UseLocalNZ if(localnz || (nzinput == NULL)) { #else if(nzinput == NULL) { #endif /* Do the OF */ if(includeOF) #ifdef DirectArrayOF v += input[0] * lp->obj[colnr] * ofscalar; #else v += input[0] * get_OF_active(lp, varnr, ofscalar); #endif /* Initialize pointers */ matRownr = &COL_MAT_ROWNR(ib); matValue = &COL_MAT_VALUE(ib); /* Do extra loop optimization based on target window overlaps */ #ifdef UseLocalNZ if((ib < ie) && (colnr <= *nzinput) && (COL_MAT_ROWNR(ie-1) >= nzinput[colnr]) && (*matRownr <= nzinput[*nzinput]) ) #endif #ifdef NoLoopUnroll /* Then loop over all regular rows */ for(; ib < ie; ib++) { v += input[*matRownr] * (*matValue); matValue += matValueStep; matRownr += matRowColStep; } #else /* Prepare for simple loop unrolling */ if(((ie-ib) % 2) == 1) { v += input[*matRownr] * (*matValue); ib++; matValue += matValueStep; matRownr += matRowColStep; } /* Then loop over remaining pairs of regular rows */ while(ib < ie) { v += input[*matRownr] * (*matValue); v += input[*(matRownr+matRowColStep)] * (*(matValue+matValueStep)); ib += 2; matValue += 2*matValueStep; matRownr += 2*matRowColStep; } #endif } /* Do sparse input vector version */ else { /* Do the OF */ if(includeOF) #ifdef DirectArrayOF v += input[0] * lp->obj[colnr] * ofscalar; #else v += input[0] * get_OF_active(lp, varnr, ofscalar); #endif /* Initialize pointers */ inz = 1; rowin = nzinput+inz; matRownr = &COL_MAT_ROWNR(ib); matValue = &COL_MAT_VALUE(ib); ie--; /* Then loop over all non-OF rows */ while((inz <= *nzinput) && (ib <= ie)) { /* Try to synchronize at right */ while((*rowin > *matRownr) && (ib < ie)) { ib++; matValue += matValueStep; matRownr += matRowColStep; } /* Try to synchronize at left */ while((*rowin < *matRownr) && (inz < *nzinput)) { inz++; rowin++; } /* Perform dot product operation if there was a match */ if(*rowin == *matRownr) { v += input[*rowin] * (*matValue); /* Step forward at left */ inz++; rowin++; } } } } if((roundmode & MAT_ROUNDABS) != 0) { my_roundzero(v, roundzero); } } /* Special handling of small reduced cost values */ if(!isRC || (my_chsign(lp->is_lower[varnr], v) < 0)) { SETMAX(vmax, fabs((REAL) v)); } if(v != 0) { countNZ++; if(nzoutput != NULL) nzoutput[countNZ] = varnr; } output[varnr] = (REAL) v; } /* Compute reduced cost if this option is active */ if(isRC && !lp->obj_in_basis) countNZ = get_basisOF(lp, coltarget, output, nzoutput); /* Check if we should do relative rounding */ if((roundmode & MAT_ROUNDREL) != 0) { if((roundzero > 0) && (nzoutput != NULL)) { ie = 0; if(isRC) { SETMAX(vmax, MAT_ROUNDRCMIN); /* Make sure we don't use very small values */ } vmax *= roundzero; for(ib = 1; ib <= countNZ; ib++) { rownr = nzoutput[ib]; if(fabs(output[rownr]) < vmax) output[rownr] = 0; else { ie++; nzoutput[ie] = rownr; } } countNZ = ie; } } /* Clean up and return */ if(localset) mempool_releaseVector(lp->workarrays, (char *) coltarget, FALSE); if(localnz) mempool_releaseVector(lp->workarrays, (char *) nzinput, FALSE); if(nzoutput != NULL) *nzoutput = countNZ; return(countNZ); } STATIC MYBOOL prod_xA2(lprec *lp, int *coltarget, REAL *prow, REAL proundzero, int *nzprow, REAL *drow, REAL droundzero, int *nzdrow, REAL ofscalar, int roundmode) { int varnr, colnr, ib, ie, vb, ve, nrows = lp->rows; MYBOOL includeOF, isRC; REALXP dmax, pmax; register REALXP d, p; MATrec *mat = lp->matA; REAL value; register REAL *matValue; register int *matRownr; MYBOOL localset; /* Find what variable range to scan - default is {SCAN_USERVARS} */ /* First determine the starting position; add from the top, going down */ localset = (MYBOOL) (coltarget == NULL); if(localset) { int varset = SCAN_SLACKVARS + SCAN_USERVARS + /*SCAN_ALLVARS +*/ /*SCAN_PARTIALBLOCK+*/ USE_NONBASICVARS+OMIT_FIXED; coltarget = (int *) mempool_obtainVector(lp->workarrays, lp->sum+1, sizeof(*coltarget)); if(!get_colIndexA(lp, varset, coltarget, FALSE)) { mempool_releaseVector(lp->workarrays, (char *) coltarget, FALSE); return(FALSE); } } /* Initialize variables */ isRC = (MYBOOL) ((roundmode & MAT_ROUNDRC) != 0); pmax = 0; dmax = 0; if(nzprow != NULL) *nzprow = 0; if(nzdrow != NULL) *nzdrow = 0; includeOF = (MYBOOL) (((prow[0] != 0) || (drow[0] != 0)) && lp->obj_in_basis); /* Scan the target colums */ ve = coltarget[0]; for(vb = 1; vb <= ve; vb++) { varnr = coltarget[vb]; if(varnr <= nrows) { p = prow[varnr]; d = drow[varnr]; } else { colnr = varnr - nrows; p = 0; d = 0; ib = mat->col_end[colnr - 1]; ie = mat->col_end[colnr]; if(ib < ie) { /* Do the OF */ if(includeOF) { #ifdef DirectArrayOF value = lp->obj[colnr] * ofscalar; #else value = get_OF_active(lp, varnr, ofscalar); #endif p += prow[0] * value; d += drow[0] * value; } /* Then loop over all regular rows */ matRownr = &COL_MAT_ROWNR(ib); matValue = &COL_MAT_VALUE(ib); #ifdef NoLoopUnroll for( ; ib < ie; ib++) { p += prow[*matRownr] * (*matValue); d += drow[*matRownr] * (*matValue); matValue += matValueStep; matRownr += matRowColStep; } #else /* Prepare for simple loop unrolling */ if(((ie-ib) % 2) == 1) { p += prow[*matRownr] * (*matValue); d += drow[*matRownr] * (*matValue); ib++; matValue += matValueStep; matRownr += matRowColStep; } /* Then loop over remaining pairs of regular rows */ while(ib < ie) { p += prow[*matRownr] * (*matValue); p += prow[*(matRownr+matRowColStep)] * (*(matValue+matValueStep)); d += drow[*matRownr] * (*matValue); d += drow[*(matRownr+matRowColStep)] * (*(matValue+matValueStep)); ib += 2; matValue += 2*matValueStep; matRownr += 2*matRowColStep; } #endif } if((roundmode & MAT_ROUNDABS) != 0) { my_roundzero(p, proundzero); my_roundzero(d, droundzero); } } SETMAX(pmax, fabs((REAL) p)); prow[varnr] = (REAL) p; if((nzprow != NULL) && (p != 0)) { (*nzprow)++; nzprow[*nzprow] = varnr; } /* Special handling of reduced cost rounding */ if(!isRC || (my_chsign(lp->is_lower[varnr], d) < 0)) { SETMAX(dmax, fabs((REAL) d)); } drow[varnr] = (REAL) d; if((nzdrow != NULL) && (d != 0)) { (*nzdrow)++; nzdrow[*nzdrow] = varnr; } } /* Compute reduced cost here if this option is active */ if((drow != 0) && !lp->obj_in_basis) get_basisOF(lp, coltarget, drow, nzdrow); /* Check if we should do relative rounding */ if((roundmode & MAT_ROUNDREL) != 0) { if((proundzero > 0) && (nzprow != NULL)) { ie = 0; pmax *= proundzero; for(ib = 1; ib <= *nzprow; ib++) { varnr = nzprow[ib]; if(fabs(prow[varnr]) < pmax) prow[varnr] = 0; else { ie++; nzprow[ie] = varnr; } } *nzprow = ie; } if((droundzero > 0) && (nzdrow != NULL)) { ie = 0; if(isRC) { SETMAX(dmax, MAT_ROUNDRCMIN); /* Make sure we don't use very small values */ } dmax *= droundzero; for(ib = 1; ib <= *nzdrow; ib++) { varnr = nzdrow[ib]; if(fabs(drow[varnr]) < dmax) drow[varnr] = 0; else { ie++; nzdrow[ie] = varnr; } } *nzdrow = ie; } } /* Clean up and return */ if(localset) mempool_releaseVector(lp->workarrays, (char *) coltarget, FALSE); return( TRUE ); } STATIC void bsolve_xA2(lprec *lp, int* coltarget, int row_nr1, REAL *vector1, REAL roundzero1, int *nzvector1, int row_nr2, REAL *vector2, REAL roundzero2, int *nzvector2, int roundmode) { REAL ofscalar = 1.0; /* Clear and initialize first vector */ if(nzvector1 == NULL) MEMCLEAR(vector1, lp->sum + 1); else MEMCLEAR(vector1, lp->rows + 1); vector1[row_nr1] = 1; /* workINT[0] = 1; workINT[1] = row_nr1; */ if(vector2 == NULL) { lp->bfp_btran_normal(lp, vector1, NULL); prod_xA(lp, coltarget, vector1, NULL, roundzero1, ofscalar*0, vector1, nzvector1, roundmode); } else { /* Clear and initialize second vector */ if(nzvector2 == NULL) MEMCLEAR(vector2, lp->sum + 1); else MEMCLEAR(vector2, lp->rows + 1); if(lp->obj_in_basis || (row_nr2 > 0)) { vector2[row_nr2] = 1; /* workINT[2] = 1; workINT[3] = row_nr2; */ } else get_basisOF(lp, NULL, vector2, nzvector2); /* A double BTRAN equation solver process is implemented "in-line" below in order to save time and to implement different rounding for the two */ lp->bfp_btran_double(lp, vector1, NULL, vector2, NULL); /* Multiply solution vectors with matrix values */ prod_xA2(lp, coltarget, vector1, roundzero1, nzvector1, vector2, roundzero2, nzvector2, ofscalar, roundmode); } } MSVMpack1.2/lp_solve_5.5/lp_MPS.h0000664000175000017500000000153611141374246015451 0ustar lauerlauer#ifndef HEADER_lp_MPS #define HEADER_lp_MPS #include "lp_types.h" /* For MPS file reading and writing */ #define ROWNAMEMASK "R%d" #define ROWNAMEMASK2 "r%d" #define COLNAMEMASK "C%d" #define COLNAMEMASK2 "c%d" #ifdef __cplusplus extern "C" { #endif /* Read an MPS file */ MYBOOL MPS_readfile(lprec **newlp, char *filename, int typeMPS, int verbose); MYBOOL __WINAPI MPS_readhandle(lprec **newlp, FILE *filehandle, int typeMPS, int verbose); /* Write a MPS file to output */ MYBOOL MPS_writefile(lprec *lp, int typeMPS, char *filename); MYBOOL MPS_writehandle(lprec *lp, int typeMPS, FILE *output); /* Read and write BAS files */ MYBOOL MPS_readBAS(lprec *lp, int typeMPS, char *filename, char *info); MYBOOL MPS_writeBAS(lprec *lp, int typeMPS, char *filename); #ifdef __cplusplus } #endif #endif /* HEADER_lp_MPS */ MSVMpack1.2/lp_solve_5.5/shared/0000775000175000017500000000000011141374260015403 5ustar lauerlauerMSVMpack1.2/lp_solve_5.5/shared/commonlib.h0000664000175000017500000002225511245552432017545 0ustar lauerlauer#ifndef HEADER_commonlib #define HEADER_commonlib #include #include #ifdef WIN32 #include #endif /* static char SpaceChars[3] = {" " "\7"}; */ /* static char NumChars[14] = {"0123456789-+."}; */ #define BIGNUMBER 1.0e+30 #define TINYNUMBER 1.0e-04 #define MACHINEPREC 2.22e-16 #define MATHPREC 1.0e-16 #define ERRLIMIT 1.0e-06 #ifndef LINEARSEARCH #define LINEARSEARCH 5 #endif #if 0 #define INTEGERTIME #endif /* ************************************************************************ */ /* Define loadable library function headers */ /* ************************************************************************ */ #if (defined WIN32) || (defined WIN64) #define my_LoadLibrary(name) LoadLibrary(name) #define my_GetProcAddress(handle, name) GetProcAddress(handle, name) #define my_FreeLibrary(handle) FreeLibrary(handle); \ handle = NULL #else #define my_LoadLibrary(name) dlopen(name, RTLD_LAZY) #define my_GetProcAddress(handle, name) dlsym(handle, name) #define my_FreeLibrary(handle) dlclose(handle); \ handle = NULL #endif /* ************************************************************************ */ /* Define sizes of standard number types */ /* ************************************************************************ */ #ifndef LLONG #if defined __BORLANDC__ #define LLONG __int64 #elif !defined _MSC_VER || _MSC_VER >= 1310 #define LLONG long long #else #define LLONG __int64 #endif #endif #ifndef MYBOOL #if 0 #define MYBOOL unsigned int #else #define MYBOOL unsigned char #endif #endif #ifndef REAL #define REAL double #endif #ifndef BLAS_prec #define BLAS_prec "d" /* The BLAS precision prefix must correspond to the REAL type */ #endif #ifndef REALXP #if 1 #define REALXP long double /* Set local accumulation variable as long double */ #else #define REALXP REAL /* Set local accumulation as default precision */ #endif #endif #ifndef my_boolstr #define my_boolstr(x) (!(x) ? "FALSE" : "TRUE") #endif #ifndef NULL #define NULL 0 #endif #ifndef FALSE #define FALSE 0 #define TRUE 1 #endif #ifndef DEF_STRBUFSIZE #define DEF_STRBUFSIZE 512 #endif #ifndef MAXINT32 #define MAXINT32 2147483647 #endif #ifndef MAXUINT32 #define MAXUINT32 4294967295 #endif #ifndef MAXINT64 #if defined _LONGLONG || defined __LONG_LONG_MAX__ || defined LLONG_MAX #define MAXINT64 9223372036854775807ll #else #define MAXINT64 9223372036854775807l #endif #endif #ifndef MAXUINT64 #if defined _LONGLONG || defined __LONG_LONG_MAX__ || defined LLONG_MAX #define MAXUINT64 18446744073709551615ll #else #define MAXUINT64 18446744073709551615l #endif #endif #ifndef DOFASTMATH #define DOFASTMATH #endif #ifndef CALLOC #define CALLOC(ptr, nr)\ if(!((void *) ptr = calloc((size_t)(nr), sizeof(*ptr))) && nr) {\ printf("calloc of %d bytes failed on line %d of file %s\n",\ (size_t) nr * sizeof(*ptr), __LINE__, __FILE__);\ } #endif #ifndef MALLOC #define MALLOC(ptr, nr)\ if(!((void *) ptr = malloc((size_t)((size_t) (nr) * sizeof(*ptr)))) && nr) {\ printf("malloc of %d bytes failed on line %d of file %s\n",\ (size_t) nr * sizeof(*ptr), __LINE__, __FILE__);\ } #endif #ifndef REALLOC #define REALLOC(ptr, nr)\ if(!((void *) ptr = realloc(ptr, (size_t)((size_t) (nr) * sizeof(*ptr)))) && nr) {\ printf("realloc of %d bytes failed on line %d of file %s\n",\ (size_t) nr * sizeof(*ptr), __LINE__, __FILE__);\ } #endif #ifndef FREE #define FREE(ptr)\ if((void *) ptr != NULL) {\ free(ptr);\ ptr = NULL; \ } #endif #ifndef MEMCOPY #define MEMCOPY(nptr, optr, nr)\ memcpy((nptr), (optr), (size_t)((size_t)(nr) * sizeof(*(optr)))) #endif #ifndef MEMMOVE #define MEMMOVE(nptr, optr, nr)\ memmove((nptr), (optr), (size_t)((size_t)(nr) * sizeof(*(optr)))) #endif #ifndef MEMALLOCCOPY #define MEMALLOCCOPY(nptr, optr, nr)\ {MALLOC(nptr, (size_t)(nr));\ MEMCOPY(nptr, optr, (size_t)(nr));} #endif #ifndef STRALLOCCOPY #define STRALLOCCOPY(nstr, ostr)\ {nstr = (char *) malloc((size_t) (strlen(ostr) + 1));\ strcpy(nstr, ostr);} #endif #ifndef MEMCLEAR /*#define useMMX*/ #ifdef useMMX #define MEMCLEAR(ptr, nr)\ mem_set((ptr), '\0', (size_t)((size_t)(nr) * sizeof(*(ptr)))) #else #define MEMCLEAR(ptr, nr)\ memset((ptr), '\0', (size_t)((size_t)(nr) * sizeof(*(ptr)))) #endif #endif #define MIN(x, y) ((x) < (y) ? (x) : (y)) #define MAX(x, y) ((x) > (y) ? (x) : (y)) #define SETMIN(x, y) if((x) > (y)) x = y #define SETMAX(x, y) if((x) < (y)) x = y #define LIMIT(lo, x, hi) ((x < (lo) ? lo : ((x) > hi ? hi : x))) #define BETWEEN(x, a, b) (MYBOOL) (((x)-(a)) * ((x)-(b)) <= 0) #define IF(t, x, y) ((t) ? (x) : (y)) #define SIGN(x) ((x) < 0 ? -1 : 1) #define DELTA_SIZE(newSize, oldSize) ((int) ((newSize) * MIN(1.33, pow(1.5, fabs((double)newSize)/((oldSize+newSize)+1))))) #ifndef CMP_CALLMODEL #if (defined WIN32) || (defined WIN64) #define CMP_CALLMODEL _cdecl #else #define CMP_CALLMODEL #endif #endif typedef int (CMP_CALLMODEL findCompare_func)(const void *current, const void *candidate); #define CMP_COMPARE(current, candidate) ( current < candidate ? -1 : (current > candidate ? 1 : 0) ) #define CMP_ATTRIBUTES(item) (((char *) attributes)+(item)*recsize) #define CMP_TAGS(item) (((char *) tags)+(item)*tagsize) #ifndef UNIONTYPE #ifdef __cplusplus #define UNIONTYPE #else #define UNIONTYPE union #endif #endif /* This defines a 16 byte sort record (in both 32 and 64 bit OS-es) */ typedef struct _QSORTrec1 { void *ptr; void *ptr2; } QSORTrec1; typedef struct _QSORTrec2 { void *ptr; double realval; } QSORTrec2; typedef struct _QSORTrec3 { void *ptr; int intval; int intpar1; } QSORTrec3; typedef struct _QSORTrec4 { REAL realval; int intval; int intpar1; } QSORTrec4; typedef struct _QSORTrec5 { double realval; long int longval; } QSORTrec5; typedef struct _QSORTrec6 { double realval; double realpar1; } QSORTrec6; typedef struct _QSORTrec7 { int intval; int intpar1; int intpar2; int intpar3; } QSORTrec7; union QSORTrec { QSORTrec1 pvoid2; QSORTrec2 pvoidreal; QSORTrec3 pvoidint2; QSORTrec4 realint2; QSORTrec5 reallong; QSORTrec6 real2; QSORTrec7 int4; }; #ifdef __cplusplus extern "C" { #endif int intpow(int base, int exponent); int mod(int n, int d); void strtoup(char *s); void strtolo(char *s); void strcpyup(char *t, char *s); void strcpylo(char *t, char *s); MYBOOL so_stdname(char *stdname, char *descname, int buflen); int gcd(LLONG a, LLONG b, int *c, int *d); int findIndex(int target, int *attributes, int count, int offset); int findIndexEx(void *target, void *attributes, int count, int offset, int recsize, findCompare_func findCompare, MYBOOL ascending); void qsortex_swap(void *attributes, int l, int r, int recsize, void *tags, int tagsize, char *save, char *savetag); int qsortex(void *attributes, int count, int offset, int recsize, MYBOOL descending, findCompare_func findCompare, void *tags, int tagsize); int CMP_CALLMODEL compareCHAR(const void *current, const void *candidate); int CMP_CALLMODEL compareINT(const void *current, const void *candidate); int CMP_CALLMODEL compareREAL(const void *current, const void *candidate); void hpsort(void *attributes, int count, int offset, int recsize, MYBOOL descending, findCompare_func findCompare); void hpsortex(void *attributes, int count, int offset, int recsize, MYBOOL descending, findCompare_func findCompare, int *tags); void QS_swap(UNIONTYPE QSORTrec a[], int i, int j); int QS_addfirst(UNIONTYPE QSORTrec a[], void *mydata); int QS_append(UNIONTYPE QSORTrec a[], int ipos, void *mydata); void QS_replace(UNIONTYPE QSORTrec a[], int ipos, void *mydata); void QS_insert(UNIONTYPE QSORTrec a[], int ipos, void *mydata, int epos); void QS_delete(UNIONTYPE QSORTrec a[], int ipos, int epos); MYBOOL QS_execute(UNIONTYPE QSORTrec a[], int count, findCompare_func findCompare, int *nswaps); int sortByREAL(int *item, REAL *weight, int size, int offset, MYBOOL unique); int sortByINT(int *item, int *weight, int size, int offset, MYBOOL unique); REAL sortREALByINT(REAL *item, int *weight, int size, int offset, MYBOOL unique); double timeNow(void); void blockWriteBOOL(FILE *output, char *label, MYBOOL *myvector, int first, int last, MYBOOL asRaw); void blockWriteINT(FILE *output, char *label, int *myvector, int first, int last); void blockWriteREAL(FILE *output, char *label, REAL *myvector, int first, int last); void printvec( int n, REAL *x, int modulo ); void printmatSQ( int size, int n, REAL *X, int modulo ); void printmatUT( int size, int n, REAL *U, int modulo ); unsigned int catchFPU(unsigned int mask); #if defined _MSC_VER int fileCount( char *filemask ); MYBOOL fileSearchPath( char *envvar, char *searchfile, char *foundpath ); #endif #ifdef __cplusplus } #endif #endif /* HEADER_commonlib */ MSVMpack1.2/lp_solve_5.5/shared/myblas.h0000664000175000017500000001232511141374260017046 0ustar lauerlauer#ifndef HEADER_myblas #define HEADER_myblas /* ************************************************************************ */ /* BLAS function interface with local and external loadable versions */ /* Author: Kjell Eikland */ /* Version: Initial version spring 2004 */ /* Licence: LGPL */ /* ************************************************************************ */ /* Changes: 19 September 2004 Moved function pointer variable */ /* declarations from myblas.h to myblas.c */ /* to avoid linker problems with the Mac. */ /* 20 April 2005 Modified all double types to REAL to self- */ /* adjust to global settings. Note that BLAS */ /* as of now does not have double double. */ /* ************************************************************************ */ #define BLAS_BASE 1 #define UseMacroVector #if defined LoadableBlasLib # if LoadableBlasLib == 0 # undef LoadableBlasLib # endif #else # define LoadableBlasLib #endif /* ************************************************************************ */ /* Include necessary libraries */ /* ************************************************************************ */ #include "commonlib.h" #ifdef LoadableBlasLib #ifdef WIN32 #include #else #include #endif #endif #ifdef __cplusplus extern "C" { #endif /* ************************************************************************ */ /* BLAS functions */ /* ************************************************************************ */ #ifndef BLAS_CALLMODEL #ifdef WIN32 # define BLAS_CALLMODEL _cdecl #else # define BLAS_CALLMODEL #endif #endif typedef void (BLAS_CALLMODEL BLAS_dscal_func) (int *n, REAL *da, REAL *dx, int *incx); typedef void (BLAS_CALLMODEL BLAS_dcopy_func) (int *n, REAL *dx, int *incx, REAL *dy, int *incy); typedef void (BLAS_CALLMODEL BLAS_daxpy_func) (int *n, REAL *da, REAL *dx, int *incx, REAL *dy, int *incy); typedef void (BLAS_CALLMODEL BLAS_dswap_func) (int *n, REAL *dx, int *incx, REAL *dy, int *incy); typedef double (BLAS_CALLMODEL BLAS_ddot_func) (int *n, REAL *dx, int *incx, REAL *dy, int *incy); typedef int (BLAS_CALLMODEL BLAS_idamax_func)(int *n, REAL *x, int *is); typedef void (BLAS_CALLMODEL BLAS_dload_func) (int *n, REAL *da, REAL *dx, int *incx); typedef double (BLAS_CALLMODEL BLAS_dnormi_func)(int *n, REAL *x); #ifndef __WINAPI # ifdef WIN32 # define __WINAPI WINAPI # else # define __WINAPI # endif #endif void init_BLAS(void); MYBOOL is_nativeBLAS(void); MYBOOL load_BLAS(char *libname); MYBOOL unload_BLAS(void); /* ************************************************************************ */ /* User-callable BLAS definitions (C base 1) */ /* ************************************************************************ */ void dscal ( int n, REAL da, REAL *dx, int incx ); void dcopy ( int n, REAL *dx, int incx, REAL *dy, int incy ); void daxpy ( int n, REAL da, REAL *dx, int incx, REAL *dy, int incy ); void dswap ( int n, REAL *dx, int incx, REAL *dy, int incy ); REAL ddot ( int n, REAL *dx, int incx, REAL *dy, int incy ); int idamax( int n, REAL *x, int is ); void dload ( int n, REAL da, REAL *dx, int incx ); REAL dnormi( int n, REAL *x ); /* ************************************************************************ */ /* Locally implemented BLAS functions (C base 0) */ /* ************************************************************************ */ void BLAS_CALLMODEL my_dscal ( int *n, REAL *da, REAL *dx, int *incx ); void BLAS_CALLMODEL my_dcopy ( int *n, REAL *dx, int *incx, REAL *dy, int *incy ); void BLAS_CALLMODEL my_daxpy ( int *n, REAL *da, REAL *dx, int *incx, REAL *dy, int *incy ); void BLAS_CALLMODEL my_dswap ( int *n, REAL *dx, int *incx, REAL *dy, int *incy ); REAL BLAS_CALLMODEL my_ddot ( int *n, REAL *dx, int *incx, REAL *dy, int *incy ); int BLAS_CALLMODEL my_idamax( int *n, REAL *x, int *is ); void BLAS_CALLMODEL my_dload ( int *n, REAL *da, REAL *dx, int *incx ); REAL BLAS_CALLMODEL my_dnormi( int *n, REAL *x ); /* ************************************************************************ */ /* Subvector and submatrix access routines (Fortran compatibility) */ /* ************************************************************************ */ #ifdef UseMacroVector #define subvec(item) (item - 1) #else int subvec( int item ); #endif int submat( int nrowb, int row, int col ); int posmat( int nrowb, int row, int col ); /* ************************************************************************ */ /* Randomization functions */ /* ************************************************************************ */ void randomseed(int *seeds); void randomdens( int n, REAL *x, REAL r1, REAL r2, REAL densty, int *seeds); void ddrand( int n, REAL *x, int incx, int *seeds ); #ifdef __cplusplus } #endif #endif MSVMpack1.2/lp_solve_5.5/shared/commonlib.c0000664000175000017500000006110611141374257017540 0ustar lauerlauer #include #if defined INTEGERTIME || defined CLOCKTIME || defined PosixTime # include #elif defined EnhTime # include #else # include #endif #include #include #ifdef WIN32 # include /* Used in file search functions */ #endif #include #include #include #include #include "commonlib.h" #ifdef FORTIFY # include "lp_fortify.h" #endif #if defined FPUexception /* FPU exception masks */ unsigned int clearFPU() { return( _clearfp() ); } unsigned int resetFPU(unsigned int mask) { _clearfp(); mask = _controlfp( mask, 0xfffff); return( mask ); } unsigned int catchFPU(unsigned int mask) { /* Always call _clearfp before enabling/unmasking a FPU exception */ unsigned int u = _clearfp(); /* Set the new mask by not-and'ing it with the previous settings */ u = _controlfp(0, 0); mask = u & ~mask; mask = _controlfp(mask, _MCW_EM); /* Return the previous mask */ return( u ); } #endif /* Math operator equivalence function */ int intpow(int base, int exponent) { int result = 1; while(exponent > 0) { result *= base; exponent--; } while(exponent < 0) { result /= base; exponent++; } return( result ); } int mod(int n, int d) { return(n % d); } /* Some string functions */ void strtoup(char *s) { if(s != NULL) while (*s) { *s = toupper(*s); s++; } } void strtolo(char *s) { if(s != NULL) while (*s) { *s = tolower(*s); s++; } } void strcpyup(char *t, char *s) { if((s != NULL) && (t != NULL)) { while (*s) { *t = toupper(*s); t++; s++; } *t = '\0'; } } void strcpylo(char *t, char *s) { if((s != NULL) && (t != NULL)) { while (*s) { *t = tolower(*s); t++; s++; } *t = '\0'; } } /* Unix library naming utility function */ MYBOOL so_stdname(char *stdname, char *descname, int buflen) { char *ptr; if((descname == NULL) || (stdname == NULL) || (((int) strlen(descname)) >= buflen - 6)) return( FALSE ); strcpy(stdname, descname); if((ptr = strrchr(descname, '/')) == NULL) ptr = descname; else ptr++; stdname[(int) (ptr - descname)] = 0; if(strncmp(ptr, "lib", 3)) strcat(stdname, "lib"); strcat(stdname, ptr); if(strcmp(stdname + strlen(stdname) - 3, ".so")) strcat(stdname, ".so"); return( TRUE ); } /* Return the greatest common divisor of a and b, or -1 if it is not defined. Return through the pointer arguments the integers such that gcd(a,b) = c*a + b*d. */ int gcd(LLONG a, LLONG b, int *c, int *d) { LLONG q,r,t; int cret,dret,C,D,rval, sgn_a = 1,sgn_b = 1, swap = 0; if((a == 0) || (b == 0)) return( -1 ); /* Use local multiplier instances, if necessary */ if(c == NULL) c = &cret; if(d == NULL) d = &dret; /* Normalize so that 0 < a <= b */ if(a < 0){ a = -a; sgn_a = -1; } if(b < 0){ b = -b; sgn_b = -1; } if(b < a){ t = b; b = a; a = t; swap = 1; } /* Now a <= b and both >= 1. */ q = b/a; r = b - a*q; if(r == 0) { if(swap){ *d = 1; *c = 0; } else { *c = 1; *d = 0; } *c = sgn_a*(*c); *d = sgn_b*(*d); return( (int) a ); } rval = gcd(a,r,&C,&D); if(swap){ *d = (int) (C-D*q); *c = D; } else { *d = D; *c = (int) (C-D*q); } *c = sgn_a*(*c); *d = sgn_b*(*d); return( rval ); } /* Array search functions */ int findIndex(int target, int *attributes, int count, int offset) { int focusPos, beginPos, endPos; int focusAttrib, beginAttrib, endAttrib; /* Set starting and ending index offsets */ beginPos = offset; endPos = beginPos + count - 1; if(endPos < beginPos) return(-1); /* Do binary search logic based on a sorted (decending) attribute vector */ focusPos = (beginPos + endPos) / 2; beginAttrib = attributes[beginPos]; focusAttrib = attributes[focusPos]; endAttrib = attributes[endPos]; while(endPos - beginPos > LINEARSEARCH) { if(beginAttrib == target) { focusAttrib = beginAttrib; endPos = beginPos; } else if(endAttrib == target) { focusAttrib = endAttrib; beginPos = endPos; } else if(focusAttrib < target) { beginPos = focusPos + 1; beginAttrib = attributes[beginPos]; focusPos = (beginPos + endPos) / 2; focusAttrib = attributes[focusPos]; } else if(focusAttrib > target) { endPos = focusPos - 1; endAttrib = attributes[endPos]; focusPos = (beginPos + endPos) / 2; focusAttrib = attributes[focusPos]; } else { beginPos = focusPos; endPos = focusPos; } } /* Do linear (unsorted) search logic */ if(endPos - beginPos <= LINEARSEARCH) { /* CPU intensive loop; provide alternative evaluation models */ #if defined DOFASTMATH /* Do fast pointer arithmetic */ int *attptr = attributes + beginPos; while((beginPos < endPos) && ((*attptr) < target)) { beginPos++; attptr++; } focusAttrib = (*attptr); #else /* Do traditional indexed access */ focusAttrib = attributes[beginPos]; while((beginPos < endPos) && (focusAttrib < target)) { beginPos++; focusAttrib = attributes[beginPos]; } #endif } /* Return the index if a match was found, or signal failure with a -1 */ if(focusAttrib == target) /* Found; return retrieval index */ return(beginPos); else if(focusAttrib > target) /* Not found; last item */ return(-beginPos); else if(beginPos > offset+count-1) return(-(endPos+1)); /* Not found; end of list */ else return(-(beginPos+1)); /* Not found; intermediate point */ } int findIndexEx(void *target, void *attributes, int count, int offset, int recsize, findCompare_func findCompare, MYBOOL ascending) { int focusPos, beginPos, endPos, compare, order; void *focusAttrib, *beginAttrib, *endAttrib; /* Set starting and ending index offsets */ beginPos = offset; endPos = beginPos + count - 1; if(endPos < beginPos) return(-1); order = (ascending ? -1 : 1); /* Do binary search logic based on a sorted attribute vector */ focusPos = (beginPos + endPos) / 2; beginAttrib = CMP_ATTRIBUTES(beginPos); focusAttrib = CMP_ATTRIBUTES(focusPos); endAttrib = CMP_ATTRIBUTES(endPos); compare = 0; while(endPos - beginPos > LINEARSEARCH) { if(findCompare(target, beginAttrib) == 0) { focusAttrib = beginAttrib; endPos = beginPos; } else if(findCompare(target, endAttrib) == 0) { focusAttrib = endAttrib; beginPos = endPos; } else { compare = findCompare(target, focusAttrib)*order; if(compare < 0) { beginPos = focusPos + 1; beginAttrib = CMP_ATTRIBUTES(beginPos); focusPos = (beginPos + endPos) / 2; focusAttrib = CMP_ATTRIBUTES(focusPos); } else if(compare > 0) { endPos = focusPos - 1; endAttrib = CMP_ATTRIBUTES(endPos); focusPos = (beginPos + endPos) / 2; focusAttrib = CMP_ATTRIBUTES(focusPos); } else { beginPos = focusPos; endPos = focusPos; } } } /* Do linear (unsorted) search logic */ if(endPos - beginPos <= LINEARSEARCH) { /* Do traditional indexed access */ focusAttrib = CMP_ATTRIBUTES(beginPos); if(beginPos == endPos) compare = findCompare(target, focusAttrib)*order; else while((beginPos < endPos) && ((compare = findCompare(target, focusAttrib)*order) < 0)) { beginPos++; focusAttrib = CMP_ATTRIBUTES(beginPos); } } /* Return the index if a match was found, or signal failure with a -1 */ if(compare == 0) /* Found; return retrieval index */ return(beginPos); else if(compare > 0) /* Not found; last item */ return(-beginPos); else if(beginPos > offset+count-1) return(-(endPos+1)); /* Not found; end of list */ else return(-(beginPos+1)); /* Not found; intermediate point */ } /* Simple sorting and searching comparison "operators" */ int CMP_CALLMODEL compareCHAR(const void *current, const void *candidate) { return( CMP_COMPARE( *(char *) current, *(char *) candidate ) ); } int CMP_CALLMODEL compareINT(const void *current, const void *candidate) { return( CMP_COMPARE( *(int *) current, *(int *) candidate ) ); } int CMP_CALLMODEL compareREAL(const void *current, const void *candidate) { return( CMP_COMPARE( *(REAL *) current, *(REAL *) candidate ) ); } /* Heap sort function (procedurally based on the Numerical Recipes version, but expanded and generalized to hande any object with the use of qsort-style comparison operator). An expanded version is also implemented, where interchanges are reflected in a caller-initialized integer "tags" list. */ void hpsort(void *attributes, int count, int offset, int recsize, MYBOOL descending, findCompare_func findCompare) { register int i, j, k, ir, order; register char *hold, *base; char *save; if(count < 2) return; offset -= 1; attributes = CMP_ATTRIBUTES(offset); base = CMP_ATTRIBUTES(1); save = (char *) malloc(recsize); if(descending) order = -1; else order = 1; k = (count >> 1) + 1; ir = count; for(;;) { if(k > 1) { MEMCOPY(save, CMP_ATTRIBUTES(--k), recsize); } else { hold = CMP_ATTRIBUTES(ir); MEMCOPY(save, hold, recsize); MEMCOPY(hold, base, recsize); if(--ir == 1) { MEMCOPY(base, save, recsize); break; } } i = k; j = k << 1; while(j <= ir) { hold = CMP_ATTRIBUTES(j); if( (j < ir) && (findCompare(hold, CMP_ATTRIBUTES(j+1))*order < 0) ) { hold += recsize; j++; } if(findCompare(save, hold)*order < 0) { MEMCOPY(CMP_ATTRIBUTES(i), hold, recsize); i = j; j <<= 1; } else break; } MEMCOPY(CMP_ATTRIBUTES(i), save, recsize); } FREE(save); } void hpsortex(void *attributes, int count, int offset, int recsize, MYBOOL descending, findCompare_func findCompare, int *tags) { if(count < 2) return; if(tags == NULL) { hpsort(attributes, count, offset, recsize, descending, findCompare); return; } else { register int i, j, k, ir, order; register char *hold, *base; char *save; int savetag; offset -= 1; attributes = CMP_ATTRIBUTES(offset); tags += offset; base = CMP_ATTRIBUTES(1); save = (char *) malloc(recsize); if(descending) order = -1; else order = 1; k = (count >> 1) + 1; ir = count; for(;;) { if(k > 1) { MEMCOPY(save, CMP_ATTRIBUTES(--k), recsize); savetag = tags[k]; } else { hold = CMP_ATTRIBUTES(ir); MEMCOPY(save, hold, recsize); MEMCOPY(hold, base, recsize); savetag = tags[ir]; tags[ir] = tags[1]; if(--ir == 1) { MEMCOPY(base, save, recsize); tags[1] = savetag; break; } } i = k; j = k << 1; while(j <= ir) { hold = CMP_ATTRIBUTES(j); if( (j < ir) && (findCompare(hold, CMP_ATTRIBUTES(j+1))*order < 0) ) { hold += recsize; j++; } if(findCompare(save, hold)*order < 0) { MEMCOPY(CMP_ATTRIBUTES(i), hold, recsize); tags[i] = tags[j]; i = j; j <<= 1; } else break; } MEMCOPY(CMP_ATTRIBUTES(i), save, recsize); tags[i] = savetag; } FREE(save); } } /* This is a "specialized generic" version of C.A.R Hoare's Quick Sort algorithm. It will handle arrays that are already sorted, and arrays with duplicate keys. There are two versions here; one extended conventional with optional tag data for each sortable value, and a version for the QSORTrec format. The QSORTrec format i.a. includes the ability for to do linked list sorting. If the passed comparison operator is NULL, the comparison is assumed to be for integers. */ #define QS_IS_switch LINEARSEARCH /* Threshold for switching to insertion sort */ void qsortex_swap(void *attributes, int l, int r, int recsize, void *tags, int tagsize, char *save, char *savetag) { MEMCOPY(save, CMP_ATTRIBUTES(l), recsize); MEMCOPY(CMP_ATTRIBUTES(l), CMP_ATTRIBUTES(r), recsize); MEMCOPY(CMP_ATTRIBUTES(r), save, recsize); if(tags != NULL) { MEMCOPY(savetag, CMP_TAGS(l), tagsize); MEMCOPY(CMP_TAGS(l), CMP_TAGS(r), tagsize); MEMCOPY(CMP_TAGS(r), savetag, tagsize); } } int qsortex_sort(void *attributes, int l, int r, int recsize, int sortorder, findCompare_func findCompare, void *tags, int tagsize, char *save, char *savetag) { register int i, j, nmove = 0; char *v; /* Perform the a fast QuickSort */ if((r-l) > QS_IS_switch) { i = (r+l)/2; /* Tri-Median Method */ if(sortorder*findCompare(CMP_ATTRIBUTES(l), CMP_ATTRIBUTES(i)) > 0) { nmove++; qsortex_swap(attributes, l,i, recsize, tags, tagsize, save, savetag); } if(sortorder*findCompare(CMP_ATTRIBUTES(l), CMP_ATTRIBUTES(r)) > 0) { nmove++; qsortex_swap(attributes, l,r, recsize, tags, tagsize, save, savetag); } if(sortorder*findCompare(CMP_ATTRIBUTES(i), CMP_ATTRIBUTES(r)) > 0) { nmove++; qsortex_swap(attributes, i,r, recsize, tags, tagsize, save, savetag); } j = r-1; qsortex_swap(attributes, i,j, recsize, tags, tagsize, save, savetag); i = l; v = CMP_ATTRIBUTES(j); for(;;) { while(sortorder*findCompare(CMP_ATTRIBUTES(++i), v) < 0); while(sortorder*findCompare(CMP_ATTRIBUTES(--j), v) > 0); if(j < i) break; nmove++; qsortex_swap(attributes, i,j, recsize, tags, tagsize, save, savetag); } nmove++; qsortex_swap(attributes, i,r-1, recsize, tags, tagsize, save, savetag); nmove += qsortex_sort(attributes, l,j, recsize, sortorder, findCompare, tags, tagsize, save, savetag); nmove += qsortex_sort(attributes, i+1,r, recsize, sortorder, findCompare, tags, tagsize, save, savetag); } return( nmove ); } int qsortex_finish(void *attributes, int lo0, int hi0, int recsize, int sortorder, findCompare_func findCompare, void *tags, int tagsize, char *save, char *savetag) { int i, j, nmove = 0; /* This is actually InsertionSort, which is faster for local sorts */ for(i = lo0+1; i <= hi0; i++) { /* Save bottom-most item */ MEMCOPY(save, CMP_ATTRIBUTES(i), recsize); if(tags != NULL) MEMCOPY(savetag, CMP_TAGS(i), tagsize); /* Shift down! */ j = i; while ((j > lo0) && (sortorder*findCompare(CMP_ATTRIBUTES(j-1), save) > 0)) { MEMCOPY(CMP_ATTRIBUTES(j), CMP_ATTRIBUTES(j-1), recsize); if(tags != NULL) MEMCOPY(CMP_TAGS(j), CMP_TAGS(j-1), tagsize); j--; nmove++; } /* Store bottom-most item at the top */ MEMCOPY(CMP_ATTRIBUTES(j), save, recsize); if(tags != NULL) MEMCOPY(CMP_TAGS(j), savetag, tagsize); } return( nmove ); } int qsortex(void *attributes, int count, int offset, int recsize, MYBOOL descending, findCompare_func findCompare, void *tags, int tagsize) { int iswaps = 0, sortorder = (descending ? -1 : 1); char *save = NULL, *savetag = NULL; /* Check and initialize to zero-based arrays */ if(count <= 1) goto Finish; attributes = (void *) CMP_ATTRIBUTES(offset); save = (char *) malloc(recsize); if((tagsize <= 0) && (tags != NULL)) tags = NULL; else if(tags != NULL) { tags = (void *) CMP_TAGS(offset); savetag = (char *) malloc(tagsize); } count--; /* Perform sort */ iswaps = qsortex_sort(attributes, 0, count, recsize, sortorder, findCompare, tags, tagsize, save, savetag); #if QS_IS_switch > 0 iswaps += qsortex_finish(attributes, 0, count, recsize, sortorder, findCompare, tags, tagsize, save, savetag); #endif Finish: FREE(save); FREE(savetag); return( iswaps ); } #undef QS_IS_switch /* This is a "specialized generic" version of C.A.R Hoare's Quick Sort algorithm. It will handle arrays that are already sorted, and arrays with duplicate keys. The implementation here requires the user to pass a comparison operator and assumes that the array passed has the QSORTrec format, which i.a. includes the ability for to do linked list sorting. If the passed comparison operator is NULL, the comparison is assumed to be for integers. */ #define QS_IS_switch 4 /* Threshold for switching to insertion sort */ void QS_swap(UNIONTYPE QSORTrec a[], int i, int j) { UNIONTYPE QSORTrec T = a[i]; a[i] = a[j]; a[j] = T; } int QS_addfirst(UNIONTYPE QSORTrec a[], void *mydata) { a[0].pvoid2.ptr = mydata; return( 0 ); } int QS_append(UNIONTYPE QSORTrec a[], int ipos, void *mydata) { if(ipos <= 0) ipos = QS_addfirst(a, mydata); else a[ipos].pvoid2.ptr = mydata; return( ipos ); } void QS_replace(UNIONTYPE QSORTrec a[], int ipos, void *mydata) { a[ipos].pvoid2.ptr = mydata; } void QS_insert(UNIONTYPE QSORTrec a[], int ipos, void *mydata, int epos) { for(; epos > ipos; epos--) a[epos] = a[epos-1]; a[ipos].pvoid2.ptr = mydata; } void QS_delete(UNIONTYPE QSORTrec a[], int ipos, int epos) { for(; epos > ipos; epos--) a[epos] = a[epos-1]; } int QS_sort(UNIONTYPE QSORTrec a[], int l, int r, findCompare_func findCompare) { register int i, j, nmove = 0; UNIONTYPE QSORTrec v; /* Perform the a fast QuickSort */ if((r-l) > QS_IS_switch) { i = (r+l)/2; /* Tri-Median Method */ if(findCompare((char *) &a[l], (char *) &a[i]) > 0) { nmove++; QS_swap(a,l,i); } if(findCompare((char *) &a[l], (char *) &a[r]) > 0) { nmove++; QS_swap(a,l,r); } if(findCompare((char *) &a[i], (char *) &a[r]) > 0) { nmove++; QS_swap(a,i,r); } j = r-1; QS_swap(a,i,j); i = l; v = a[j]; for(;;) { while(findCompare((char *) &a[++i], (char *) &v) < 0); while(findCompare((char *) &a[--j], (char *) &v) > 0); if(j < i) break; nmove++; QS_swap (a,i,j); } nmove++; QS_swap(a,i,r-1); nmove += QS_sort(a,l,j,findCompare); nmove += QS_sort(a,i+1,r,findCompare); } return( nmove ); } int QS_finish(UNIONTYPE QSORTrec a[], int lo0, int hi0, findCompare_func findCompare) { int i, j, nmove = 0; UNIONTYPE QSORTrec v; /* This is actually InsertionSort, which is faster for local sorts */ for(i = lo0+1; i <= hi0; i++) { /* Save bottom-most item */ v = a[i]; /* Shift down! */ j = i; while ((j > lo0) && (findCompare((char *) &a[j-1], (char *) &v) > 0)) { a[j] = a[j-1]; j--; nmove++; } /* Store bottom-most item at the top */ a[j] = v; } return( nmove ); } MYBOOL QS_execute(UNIONTYPE QSORTrec a[], int count, findCompare_func findCompare, int *nswaps) { int iswaps = 0; /* Check and initialize */ if(count <= 1) goto Finish; count--; /* Perform sort */ iswaps = QS_sort(a, 0, count, findCompare); #if QS_IS_switch > 0 iswaps += QS_finish(a, 0, count, findCompare); #endif Finish: if(nswaps != NULL) *nswaps = iswaps; return( TRUE ); } /* Simple specialized bubble/insertion sort functions */ int sortByREAL(int *item, REAL *weight, int size, int offset, MYBOOL unique) { int i, ii, saveI; REAL saveW; for(i = 1; i < size; i++) { ii = i+offset-1; while ((ii >= offset) && (weight[ii] >= weight[ii+1])) { if(weight[ii] == weight[ii+1]) { if(unique) return(item[ii]); } else { saveI = item[ii]; saveW = weight[ii]; item[ii] = item[ii+1]; weight[ii] = weight[ii+1]; item[ii+1] = saveI; weight[ii+1] = saveW; } ii--; } } return(0); } int sortByINT(int *item, int *weight, int size, int offset, MYBOOL unique) { int i, ii, saveI; int saveW; for(i = 1; i < size; i++) { ii = i+offset-1; while ((ii >= offset) && (weight[ii] >= weight[ii+1])) { if(weight[ii] == weight[ii+1]) { if(unique) return(item[ii]); } else { saveI = item[ii]; saveW = weight[ii]; item[ii] = item[ii+1]; weight[ii] = weight[ii+1]; item[ii+1] = saveI; weight[ii+1] = saveW; } ii--; } } return(0); } REAL sortREALByINT(REAL *item, int *weight, int size, int offset, MYBOOL unique) { int i, ii, saveW; REAL saveI; for(i = 1; i < size; i++) { ii = i+offset-1; while ((ii >= offset) && (weight[ii] >= weight[ii+1])) { if(weight[ii] == weight[ii+1]) { if(unique) return(item[ii]); } else { saveI = item[ii]; saveW = weight[ii]; item[ii] = item[ii+1]; weight[ii] = weight[ii+1]; item[ii+1] = saveI; weight[ii+1] = saveW; } ii--; } } return(0); } /* Time and message functions */ double timeNow(void) { #ifdef INTEGERTIME return((double)time(NULL)); #elif defined CLOCKTIME return((double)clock()/CLOCKS_PER_SEC /* CLK_TCK */); #elif defined PosixTime struct timespec t; # if 0 clock_gettime(CLOCK_REALTIME, &t); return( (double) t.tv_sec + (double) t.tv_nsec/1.0e9 ); # else static double timeBase; clock_gettime(CLOCK_MONOTONIC, &t); if(timeBase == 0) timeBase = clockNow() - ((double) t.tv_sec + (double) t.tv_nsec/1.0e9); return( timeBase + (double) t.tv_sec + (double) t.tv_nsec/1.0e9 ); # endif #elif defined EnhTime static LARGE_INTEGER freq; static double timeBase; LARGE_INTEGER now; QueryPerformanceCounter(&now); if(timeBase == 0) { QueryPerformanceFrequency(&freq); timeBase = clockNow() - (double) now.QuadPart/(double) freq.QuadPart; } return( timeBase + (double) now.QuadPart/(double) freq.QuadPart ); #else struct timeb buf; ftime(&buf); return((double)buf.time+((double) buf.millitm)/1000.0); #endif } /* Miscellaneous reporting functions */ /* List a vector of INT values for the given index range */ void blockWriteINT(FILE *output, char *label, int *myvector, int first, int last) { int i, k = 0; fprintf(output, "%s", label); fprintf(output, "\n"); for(i = first; i <= last; i++) { fprintf(output, " %5d", myvector[i]); k++; if(k % 12 == 0) { fprintf(output, "\n"); k = 0; } } if(k % 12 != 0) fprintf(output, "\n"); } /* List a vector of MYBOOL values for the given index range */ void blockWriteBOOL(FILE *output, char *label, MYBOOL *myvector, int first, int last, MYBOOL asRaw) { int i, k = 0; fprintf(output, "%s", label); fprintf(output, "\n"); for(i = first; i <= last; i++) { if(asRaw) fprintf(output, " %1d", myvector[i]); else fprintf(output, " %5s", my_boolstr(myvector[i])); k++; if(k % 36 == 0) { fprintf(output, "\n"); k = 0; } } if(k % 36 != 0) fprintf(output, "\n"); } /* List a vector of REAL values for the given index range */ void blockWriteREAL(FILE *output, char *label, REAL *myvector, int first, int last) { int i, k = 0; fprintf(output, "%s", label); fprintf(output, "\n"); for(i = first; i <= last; i++) { fprintf(output, " %18g", myvector[i]); k++; if(k % 4 == 0) { fprintf(output, "\n"); k = 0; } } if(k % 4 != 0) fprintf(output, "\n"); } /* CONSOLE vector and matrix printing routines */ void printvec( int n, REAL *x, int modulo ) { int i; if (modulo <= 0) modulo = 5; for (i = 1; i<=n; i++) { if(mod(i, modulo) == 1) printf("\n%2d:%12g", i, x[i]); else printf(" %2d:%12g", i, x[i]); } if(i % modulo != 0) printf("\n"); } void printmatUT( int size, int n, REAL *U, int modulo) { int i, ll; ll = 0; for(i = 1; i<=n; i++) { printvec(n-i+1, &U[ll], modulo); ll += size-i+1; } } void printmatSQ( int size, int n, REAL *X, int modulo) { int i, ll; ll = 0; for(i = 1; i<=n; i++) { printvec(n, &X[ll], modulo); ll += size; } } /* Miscellaneous file functions */ #if defined _MSC_VER /* Check MS versions before 7 */ #if _MSC_VER < 1300 # define intptr_t long #endif int fileCount( char *filemask ) { struct _finddata_t c_file; intptr_t hFile; int count = 0; /* Find first .c file in current directory */ if( (hFile = _findfirst( filemask, &c_file )) == -1L ) ; /* Iterate over all matching names */ else { while( _findnext( hFile, &c_file ) == 0 ) count++; _findclose( hFile ); } return( count ); } MYBOOL fileSearchPath( char *envvar, char *searchfile, char *foundpath ) { char pathbuffer[_MAX_PATH]; _searchenv( searchfile, envvar, pathbuffer ); if(pathbuffer[0] == '\0') return( FALSE ); else { if(foundpath != NULL) strcpy(foundpath, pathbuffer); return( TRUE ); } } #endif MSVMpack1.2/lp_solve_5.5/shared/myblas.c0000664000175000017500000004604511141374260017047 0ustar lauerlauer #include #include /*#include */ #include #include #include "myblas.h" #ifdef FORTIFY # include "lp_fortify.h" #endif /* ************************************************************************ */ /* Initialize BLAS interfacing routines */ /* ************************************************************************ */ MYBOOL mustinitBLAS = TRUE; #ifdef WIN32 HINSTANCE hBLAS = NULL; #else void *hBLAS = NULL; #endif /* ************************************************************************ */ /* Function pointers for external BLAS library (C base 0) */ /* ************************************************************************ */ BLAS_dscal_func *BLAS_dscal; BLAS_dcopy_func *BLAS_dcopy; BLAS_daxpy_func *BLAS_daxpy; BLAS_dswap_func *BLAS_dswap; BLAS_ddot_func *BLAS_ddot; BLAS_idamax_func *BLAS_idamax; BLAS_dload_func *BLAS_dload; BLAS_dnormi_func *BLAS_dnormi; /* ************************************************************************ */ /* Define the BLAS interfacing routines */ /* ************************************************************************ */ void init_BLAS(void) { if(mustinitBLAS) { load_BLAS(NULL); mustinitBLAS = FALSE; } } MYBOOL is_nativeBLAS(void) { #ifdef LoadableBlasLib return( (MYBOOL) (hBLAS == NULL) ); #else return( TRUE ); #endif } MYBOOL load_BLAS(char *libname) { MYBOOL result = TRUE; #ifdef LoadableBlasLib if(hBLAS != NULL) { #ifdef WIN32 FreeLibrary(hBLAS); #else dlclose(hBLAS); #endif hBLAS = NULL; } #endif if(libname == NULL) { if(!mustinitBLAS && is_nativeBLAS()) return( FALSE ); BLAS_dscal = my_dscal; BLAS_dcopy = my_dcopy; BLAS_daxpy = my_daxpy; BLAS_dswap = my_dswap; BLAS_ddot = my_ddot; BLAS_idamax = my_idamax; BLAS_dload = my_dload; BLAS_dnormi = my_dnormi; if(mustinitBLAS) mustinitBLAS = FALSE; } else { #ifdef LoadableBlasLib #ifdef WIN32 /* Get a handle to the Windows DLL module. */ hBLAS = LoadLibrary(libname); /* If the handle is valid, try to get the function addresses. */ result = (MYBOOL) (hBLAS != NULL); if(result) { BLAS_dscal = (BLAS_dscal_func *) GetProcAddress(hBLAS, BLAS_prec "scal"); BLAS_dcopy = (BLAS_dcopy_func *) GetProcAddress(hBLAS, BLAS_prec "copy"); BLAS_daxpy = (BLAS_daxpy_func *) GetProcAddress(hBLAS, BLAS_prec "axpy"); BLAS_dswap = (BLAS_dswap_func *) GetProcAddress(hBLAS, BLAS_prec "swap"); BLAS_ddot = (BLAS_ddot_func *) GetProcAddress(hBLAS, BLAS_prec "dot"); BLAS_idamax = (BLAS_idamax_func *) GetProcAddress(hBLAS, "i" BLAS_prec "amax"); #if 0 BLAS_dload = (BLAS_dload_func *) GetProcAddress(hBLAS, BLAS_prec "load"); BLAS_dnormi = (BLAS_dnormi_func *) GetProcAddress(hBLAS, BLAS_prec "normi"); #endif } #else /* First standardize UNIX .SO library name format. */ char blasname[260], *ptr; strcpy(blasname, libname); if((ptr = strrchr(libname, '/')) == NULL) ptr = libname; else ptr++; blasname[(int) (ptr - libname)] = 0; if(strncmp(ptr, "lib", 3)) strcat(blasname, "lib"); strcat(blasname, ptr); if(strcmp(blasname + strlen(blasname) - 3, ".so")) strcat(blasname, ".so"); /* Get a handle to the module. */ hBLAS = dlopen(blasname, RTLD_LAZY); /* If the handle is valid, try to get the function addresses. */ result = (MYBOOL) (hBLAS != NULL); if(result) { BLAS_dscal = (BLAS_dscal_func *) dlsym(hBLAS, BLAS_prec "scal"); BLAS_dcopy = (BLAS_dcopy_func *) dlsym(hBLAS, BLAS_prec "copy"); BLAS_daxpy = (BLAS_daxpy_func *) dlsym(hBLAS, BLAS_prec "axpy"); BLAS_dswap = (BLAS_dswap_func *) dlsym(hBLAS, BLAS_prec "swap"); BLAS_ddot = (BLAS_ddot_func *) dlsym(hBLAS, BLAS_prec "dot"); BLAS_idamax = (BLAS_idamax_func *) dlsym(hBLAS, "i" BLAS_prec "amax"); #if 0 BLAS_dload = (BLAS_dload_func *) dlsym(hBLAS, BLAS_prec "load"); BLAS_dnormi = (BLAS_dnormi_func *) dlsym(hBLAS, BLAS_prec "normi"); #endif } #endif #endif /* Do validation */ if(!result || ((BLAS_dscal == NULL) || (BLAS_dcopy == NULL) || (BLAS_daxpy == NULL) || (BLAS_dswap == NULL) || (BLAS_ddot == NULL) || (BLAS_idamax == NULL) || (BLAS_dload == NULL) || (BLAS_dnormi == NULL)) ) { load_BLAS(NULL); result = FALSE; } } return( result ); } MYBOOL unload_BLAS(void) { return( load_BLAS(NULL) ); } /* ************************************************************************ */ /* Now define the unoptimized local BLAS functions */ /* ************************************************************************ */ void daxpy( int n, REAL da, REAL *dx, int incx, REAL *dy, int incy) { dx++; dy++; BLAS_daxpy( &n, &da, dx, &incx, dy, &incy); } void BLAS_CALLMODEL my_daxpy( int *_n, REAL *_da, REAL *dx, int *_incx, REAL *dy, int *_incy) { /* constant times a vector plus a vector. uses unrolled loops for increments equal to one. jack dongarra, linpack, 3/11/78. modified 12/3/93, array[1] declarations changed to array[*] */ int i, ix, iy; #if !defined DOFASTMATH int m, mp1; #endif register REAL rda; REAL da = *_da; int n = *_n, incx = *_incx, incy = *_incy; if (n <= 0) return; if (da == 0.0) return; dx--; dy--; ix = 1; iy = 1; if (incx < 0) ix = (-n+1)*incx + 1; if (incy < 0) iy = (-n+1)*incy + 1; rda = da; /* CPU intensive loop; option to do pointer arithmetic */ #if defined DOFASTMATH { REAL *xptr, *yptr; for (i = 1, xptr = dx + ix, yptr = dy + iy; i <= n; i++, xptr += incx, yptr += incy) (*yptr) += rda*(*xptr); return; } #else if (incx==1 && incy==1) goto x20; /* code for unequal increments or equal increments not equal to 1 */ for (i = 1; i<=n; i++) { dy[iy]+= rda*dx[ix]; ix+= incx; iy+= incy; } return; /* code for both increments equal to 1 */ /* clean-up loop */ x20: m = n % 4; if (m == 0) goto x40; for (i = 1; i<=m; i++) dy[i]+= rda*dx[i]; if(n < 4) return; x40: mp1 = m + 1; for (i = mp1; i<=n; i=i+4) { dy[i]+= rda*dx[i]; dy[i + 1]+= rda*dx[i + 1]; dy[i + 2]+= rda*dx[i + 2]; dy[i + 3]+= rda*dx[i + 3]; } #endif } /* ************************************************************************ */ void dcopy( int n, REAL *dx, int incx, REAL *dy, int incy) { dx++; dy++; BLAS_dcopy( &n, dx, &incx, dy, &incy); } void BLAS_CALLMODEL my_dcopy (int *_n, REAL *dx, int *_incx, REAL *dy, int *_incy) { /* copies a vector, x, to a vector, y. uses unrolled loops for increments equal to one. jack dongarra, linpack, 3/11/78. modified 12/3/93, array[1] declarations changed to array[*] */ int i, ix, iy; #if !defined DOFASTMATH int m, mp1; #endif int n = *_n, incx = *_incx, incy = *_incy; if (n<=0) return; dx--; dy--; ix = 1; iy = 1; if (incx<0) ix = (-n+1)*incx + 1; if (incy<0) iy = (-n+1)*incy + 1; /* CPU intensive loop; option to do pointer arithmetic */ #if defined DOFASTMATH { REAL *xptr, *yptr; for (i = 1, xptr = dx + ix, yptr = dy + iy; i <= n; i++, xptr += incx, yptr += incy) (*yptr) = (*xptr); return; } #else if (incx==1 && incy==1) goto x20; /* code for unequal increments or equal increments not equal to 1 */ for (i = 1; i<=n; i++) { dy[iy] = dx[ix]; ix+= incx; iy+= incy; } return; /* code for both increments equal to 1 */ /* version with fast machine copy logic (requires memory.h or string.h) */ x20: #if defined DOFASTMATH MEMCOPY(&dy[1], &dx[1], n); return; #else m = n % 7; if (m == 0) goto x40; for (i = 1; i<=m; i++) dy[i] = dx[i]; if (n < 7) return; x40: mp1 = m + 1; for (i = mp1; i<=n; i=i+7) { dy[i] = dx[i]; dy[i + 1] = dx[i + 1]; dy[i + 2] = dx[i + 2]; dy[i + 3] = dx[i + 3]; dy[i + 4] = dx[i + 4]; dy[i + 5] = dx[i + 5]; dy[i + 6] = dx[i + 6]; } #endif #endif } /* ************************************************************************ */ void dscal (int n, REAL da, REAL *dx, int incx) { dx++; BLAS_dscal (&n, &da, dx, &incx); } void BLAS_CALLMODEL my_dscal (int *_n, REAL *_da, REAL *dx, int *_incx) { /* Multiply a vector by a constant. --Input-- N number of elements in input vector(s) DA double precision scale factor DX double precision vector with N elements INCX storage spacing between elements of DX --Output-- DX double precision result (unchanged if N.LE.0) Replace double precision DX by double precision DA*DX. For I = 0 to N-1, replace DX(IX+I*INCX) with DA * DX(IX+I*INCX), where IX = 1 if INCX .GE. 0, else IX = 1+(1-N)*INCX. */ int i; #if !defined DOFASTMATH int ix, m, mp1; #endif register REAL rda; REAL da = *_da; int n = *_n, incx = *_incx; if (n <= 0) return; rda = da; dx--; /* Optionally do fast pointer arithmetic */ #if defined DOFASTMATH { REAL *xptr; for (i = 1, xptr = dx + 1; i <= n; i++, xptr += incx) (*xptr) *= rda; return; } #else if (incx == 1) goto x20; /* Code for increment not equal to 1 */ ix = 1; if (incx < 0) ix = (-n+1)*incx + 1; for(i = 1; i <= n; i++, ix += incx) dx[ix] *= rda; return; /* Code for increment equal to 1. */ /* Clean-up loop so remaining vector length is a multiple of 5. */ x20: m = n % 5; if (m == 0) goto x40; for( i = 1; i <= m; i++) dx[i] *= rda; if (n < 5) return; x40: mp1 = m + 1; for(i = mp1; i <= n; i += 5) { dx[i] *= rda; dx[i+1] *= rda; dx[i+2] *= rda; dx[i+3] *= rda; dx[i+4] *= rda; } #endif } /* ************************************************************************ */ REAL ddot(int n, REAL *dx, int incx, REAL *dy, int incy) { dx++; dy++; return( BLAS_ddot (&n, dx, &incx, dy, &incy) ); } REAL BLAS_CALLMODEL my_ddot(int *_n, REAL *dx, int *_incx, REAL *dy, int *_incy) { /* forms the dot product of two vectors. uses unrolled loops for increments equal to one. jack dongarra, linpack, 3/11/78. modified 12/3/93, array[1] declarations changed to array[*] */ register REAL dtemp; int i, ix, iy; #if !defined DOFASTMATH int m, mp1; #endif int n = *_n, incx = *_incx, incy = *_incy; dtemp = 0.0; if (n<=0) return( (REAL) dtemp); dx--; dy--; ix = 1; iy = 1; if (incx<0) ix = (-n+1)*incx + 1; if (incy<0) iy = (-n+1)*incy + 1; /* CPU intensive loop; option to do pointer arithmetic */ #if defined DOFASTMATH { REAL *xptr, *yptr; for (i = 1, xptr = dx + ix, yptr = dy + iy; i <= n; i++, xptr += incx, yptr += incy) dtemp+= (*yptr)*(*xptr); return(dtemp); } #else if (incx==1 && incy==1) goto x20; /* code for unequal increments or equal increments not equal to 1 */ for (i = 1; i<=n; i++) { dtemp+= dx[ix]*dy[iy]; ix+= incx; iy+= incy; } return(dtemp); /* code for both increments equal to 1 */ /* clean-up loop */ x20: m = n % 5; if (m == 0) goto x40; for (i = 1; i<=m; i++) dtemp+= dx[i]*dy[i]; if (n < 5) goto x60; x40: mp1 = m + 1; for (i = mp1; i<=n; i=i+5) dtemp+= dx[i]*dy[i] + dx[i + 1]*dy[i + 1] + dx[i + 2]*dy[i + 2] + dx[i + 3]*dy[i + 3] + dx[i + 4]*dy[i + 4]; x60: return(dtemp); #endif } /* ************************************************************************ */ void dswap( int n, REAL *dx, int incx, REAL *dy, int incy ) { dx++; dy++; BLAS_dswap( &n, dx, &incx, dy, &incy ); } void BLAS_CALLMODEL my_dswap( int *_n, REAL *dx, int *_incx, REAL *dy, int *_incy ) { int i, ix, iy; #if !defined DOFASTMATH int m, mp1, ns; REAL dtemp2, dtemp3; #endif REAL dtemp1; int n = *_n, incx = *_incx, incy = *_incy; if (n <= 0) return; dx--; dy--; ix = 1; iy = 1; if (incx < 0) ix = (-n+1)*incx + 1; if (incy < 0) iy = (-n+1)*incy + 1; /* CPU intensive loop; option to do pointer arithmetic */ #if defined DOFASTMATH { REAL *xptr, *yptr; for (i = 1, xptr = dx + ix, yptr = dy + iy; i <= n; i++, xptr += incx, yptr += incy) { dtemp1 = (*xptr); (*xptr) = (*yptr); (*yptr) = dtemp1; } return; } #else if (incx == incy) { if (incx <= 0) goto x5; if (incx == 1) goto x20; goto x60; } /* code for unequal or nonpositive increments. */ x5: for (i = 1; i<=n; i++) { dtemp1 = dx[ix]; dx[ix] = dy[iy]; dy[iy] = dtemp1; ix+= incx; iy+= incy; } return; /* code for both increments equal to 1. clean-up loop so remaining vector length is a multiple of 3. */ x20: m = n % 3; if (m == 0) goto x40; for (i = 1; i<=m; i++) { dtemp1 = dx[i]; dx[i] = dy[i]; dy[i] = dtemp1; } if (n < 3) return; x40: mp1 = m + 1; for (i = mp1; i<=n; i=i+3) { dtemp1 = dx[i]; dtemp2 = dx[i+1]; dtemp3 = dx[i+2]; dx[i] = dy[i]; dx[i+1] = dy[i+1]; dx[i+2] = dy[i+2]; dy[i] = dtemp1; dy[i+1] = dtemp2; dy[i+2] = dtemp3; } return; /* code for equal, positive, non-unit increments. */ x60: ns = n*incx; for (i = 1; i<=ns; i=i+incx) { dtemp1 = dx[i]; dx[i] = dy[i]; dy[i] = dtemp1; } #endif } /* ************************************************************************ */ void dload(int n, REAL da, REAL *dx, int incx) { dx++; BLAS_dload (&n, &da, dx, &incx); } void BLAS_CALLMODEL my_dload (int *_n, REAL *_da, REAL *dx, int *_incx) { /* copies a scalar, a, to a vector, x. uses unrolled loops when incx equals one. To change the precision of this program, run the change program on dload.f Alternatively, to make a single precision version append a comment character to the start of all lines between sequential precision > double and end precision > double comments and delete the comment character at the start of all lines between sequential precision > single and end precision > single comments. To make a double precision version interchange the append and delete operations in these instructions. */ int i, ix, m, mp1; REAL da = *_da; int n = *_n, incx = *_incx; if (n<=0) return; dx--; if (incx==1) goto x20; /* code for incx not equal to 1 */ ix = 1; if (incx<0) ix = (-n+1)*incx + 1; for (i = 1; i<=n; i++) { dx[ix] = da; ix+= incx; } return; /* code for incx equal to 1 and clean-up loop */ x20: m = n % 7; if (m == 0) goto x40; for (i = 1; i<=m; i++) dx[i] = da; if (n < 7) return; x40: mp1 = m + 1; for (i = mp1; i<=n; i=i+7) { dx[i] = da; dx[i + 1] = da; dx[i + 2] = da; dx[i + 3] = da; dx[i + 4] = da; dx[i + 5] = da; dx[i + 6] = da; } } /* ************************************************************************ */ int idamax( int n, REAL *x, int is ) { x++; return ( BLAS_idamax( &n, x, &is ) ); } int BLAS_CALLMODEL my_idamax( int *_n, REAL *x, int *_is ) { register REAL xmax, xtest; int i, imax = 0; #if !defined DOFASTMATH int ii; #endif int n = *_n, is = *_is; if((n < 1) || (is <= 0)) return(imax); imax = 1; if(n == 1) return(imax); #if defined DOFASTMATH xmax = fabs(*x); for (i = 2, x += is; i <= n; i++, x += is) { xtest = fabs(*x); if(xtest > xmax) { xmax = xtest; imax = i; } } #else x--; ii = 1; xmax = fabs(x[ii]); for(i = 2, ii+ = is; i <= n; i++, ii+ = is) { xtest = fabs(x[ii]); if(xtest > xmax) { xmax = xtest; imax = i; } } #endif return(imax); } /* ************************************************************************ */ REAL dnormi( int n, REAL *x ) { x++; return( BLAS_dnormi( &n, x ) ); } REAL BLAS_CALLMODEL my_dnormi( int *_n, REAL *x ) { /* =============================================================== dnormi returns the infinity-norm of the vector x. =============================================================== */ int j; register REAL hold, absval; int n = *_n; x--; hold = 0.0; /* for(j = 1; j <= n; j++) */ for(j = n; j > 0; j--) { absval = fabs(x[j]); hold = MAX( hold, absval ); } return( hold ); } /* ************************************************************************ */ /* Subvector and submatrix access routines (Fortran compatibility) */ /* ************************************************************************ */ #ifndef UseMacroVector int subvec( int item) { return( item-1 ); } #endif int submat( int nrowb, int row, int col) { return( nrowb*(col-1) + subvec(row) ); } int posmat( int nrowb, int row, int col) { return( submat(nrowb, row, col)+BLAS_BASE ); } /* ************************************************************************ */ /* Randomization functions */ /* ************************************************************************ */ void randomseed(int seeds[]) /* Simply create some default seed values */ { seeds[1] = 123456; seeds[2] = 234567; seeds[3] = 345678; } void randomdens( int n, REAL *x, REAL r1, REAL r2, REAL densty, int *seeds ) { /* ------------------------------------------------------------------ random generates a vector x[*] of random numbers in the range (r1, r2) with (approximate) specified density. seeds[*] must be initialized before the first call. ------------------------------------------------------------------ */ int i; REAL *y; y = (REAL *) malloc(sizeof(*y) * (n+1)); ddrand( n, x, 1, seeds ); ddrand( n, y, 1, seeds ); for (i = 1; i<=n; i++) { if (y[i] < densty) x[i] = r1 + (r2 - r1) * x[i]; else x[i] = 0.0; } free(y); } /* ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ */ void ddrand( int n, REAL *x, int incx, int *seeds ) { /* ------------------------------------------------------------------ ddrand fills a vector x with uniformly distributed random numbers in the interval (0, 1) using a method due to Wichman and Hill. seeds[1..3] should be set to integer values between 1 and 30000 before the first entry. Integer arithmetic up to 30323 is required. Blatantly copied from Wichman and Hill 19-January-1987. 14-Feb-94. Original version. 30 Jun 1999. seeds stored in an array. 30 Jun 1999. This version of ddrand. ------------------------------------------------------------------ */ int ix, xix; if (n < 1) return; for (ix = 1; ix<=1+(n-1)*incx; ix=ix+incx) { seeds[1] = 171*(seeds[1] % 177) - 2*(seeds[1]/177); seeds[2] = 172*(seeds[2] % 176) - 35*(seeds[2]/176); seeds[3] = 170*(seeds[3] % 178) - 63*(seeds[3]/178); if (seeds[1] < 0) seeds[1] = seeds[1] + 30269; if (seeds[2] < 0) seeds[2] = seeds[2] + 30307; if (seeds[3] < 0) seeds[3] = seeds[3] + 30323; x[ix] = ((REAL) seeds[1])/30269.0 + ((REAL) seeds[2])/30307.0 + ((REAL) seeds[3])/30323.0; xix = (int) x[ix]; x[ix] = fabs(x[ix] - xix); } } MSVMpack1.2/lp_solve_5.5/shared/mmio.c0000664000175000017500000003042311141374257016520 0ustar lauerlauer/* * Matrix Market I/O library for ANSI C * * See http://math.nist.gov/MatrixMarket for details. * * (Version 1.01, 5/2003) */ #include #include #include #include #include "mmio.h" int mm_read_unsymmetric_sparse(const char *fname, int *M_, int *N_, int *nz_, double **val_, int **I_, int **J_) { FILE *f; MM_typecode matcode; int M, N, nz; int i; double *val; int *I, *J; int x; if ((f = fopen(fname, "r")) == NULL) return -1; if (mm_read_banner(f, &matcode) != 0) { printf("mm_read_unsymetric: Could not process Matrix Market banner "); printf(" in file [%s]\n", fname); return -1; } if ( !(mm_is_real(matcode) && mm_is_matrix(matcode) && mm_is_sparse(matcode))) { fprintf(stderr, "Sorry, this application does not support "); fprintf(stderr, "Market Market type: [%s]\n", mm_typecode_to_str(matcode)); return -1; } /* find out size of sparse matrix: M, N, nz .... */ if (mm_read_mtx_crd_size(f, &M, &N, &nz) !=0) { fprintf(stderr, "read_unsymmetric_sparse(): could not parse matrix size.\n"); return -1; } *M_ = M; *N_ = N; *nz_ = nz; /* reseve memory for matrices */ I = (int *) malloc(nz * sizeof(int)); J = (int *) malloc(nz * sizeof(int)); val = (double *) malloc(nz * sizeof(double)); *val_ = val; *I_ = I; *J_ = J; /* NOTE: when reading in doubles, ANSI C requires the use of the "l" */ /* specifier as in "%lg", "%lf", "%le", otherwise errors will occur */ /* (ANSI C X3.159-1989, Sec. 4.9.6.2, p. 136 lines 13-15) */ for (i=0; i= 2) return 0; else do { num_items_read = fscanf(f, "%d %d %d", M, N, nz); if (num_items_read == EOF) return MM_PREMATURE_EOF; } while (num_items_read < 2); return 0; } int mm_read_mtx_array_size(FILE *f, int *M, int *N) { char line[MM_MAX_LINE_LENGTH]; int num_items_read; /* set return null parameter values, in case we exit with errors */ *M = *N = 0; /* now continue scanning until you reach the end-of-comments */ do { if (fgets(line,MM_MAX_LINE_LENGTH,f) == NULL) return MM_PREMATURE_EOF; }while (line[0] == '%'); /* line[] is either blank or has M,N, nz */ if (sscanf(line, "%d %d", M, N) == 2) return 0; else /* we have a blank line */ do { num_items_read = fscanf(f, "%d %d", M, N); if (num_items_read == EOF) return MM_PREMATURE_EOF; } while (num_items_read != 2); return 0; } int mm_write_mtx_array_size(FILE *f, int M, int N) { if (fprintf(f, "%d %d\n", M, N) < 0) return MM_COULD_NOT_WRITE_FILE; else return 0; } /*-------------------------------------------------------------------------*/ /******************************************************************/ /* use when I[], J[], and val[]J, and val[] are already allocated */ /******************************************************************/ int mm_read_mtx_crd_data(FILE *f, int M, int N, int nz, int I[], int J[], double val[], MM_typecode matcode) { int i; if (mm_is_complex(matcode)) { for (i=0; i #include "commonlib.h" #include "lp_lib.h" #include "lp_report.h" #include "lp_SOS.h" #ifdef FORTIFY # include "lp_fortify.h" #endif /* Specially Ordered Set (SOS) routines - w/interface for lp_solve v5.0+ ---------------------------------------------------------------------------------- Author: Kjell Eikland Contact: kjell.eikland@broadpark.no License terms: LGPL. Requires: lp_lib.h Release notes: v1.0 1 September 2003 Complete package for SOS creation and use in a LP setting. Notable feature of this implementation compared to those in other commercial systems is the generalization to SOS'es of "unlimited" order. v1.1 8 December 2003 Added variable (index) deletion method. v1.2 17 December 2004 Added bound change tracking functionality. v1.3 18 September 2005 Added sparse SOS handling to speed up processing of large number of SOS'es. ---------------------------------------------------------------------------------- */ /* SOS group functions */ STATIC SOSgroup *create_SOSgroup(lprec *lp) { SOSgroup *group; group = (SOSgroup *) calloc(1, sizeof(*group)); group->lp = lp; group->sos_alloc = SOS_START_SIZE; group->sos_list = (SOSrec **) malloc((group->sos_alloc) * sizeof(*group->sos_list)); return(group); } STATIC void resize_SOSgroup(SOSgroup *group) { if(group->sos_count == group->sos_alloc) { group->sos_alloc = (int)((double) group->sos_alloc*RESIZEFACTOR); group->sos_list = (SOSrec **) realloc(group->sos_list, (group->sos_alloc) * sizeof(*group->sos_list)); } } STATIC int append_SOSgroup(SOSgroup *group, SOSrec *SOS) { int i, k; SOSrec *SOSHold; /* Check if we should resize */ resize_SOSgroup(group); /* First append to the end of the list */ group->sos_list[group->sos_count] = SOS; group->sos_count++; i = abs(SOS->type); SETMAX(group->maxorder, i); if(i == 1) group->sos1_count++; k = group->sos_count; SOS->tagorder = k; /* Sort the SOS list by given priority */ for(i = group->sos_count-1; i > 0; i--) { if(group->sos_list[i]->priority < group->sos_list[i-1]->priority) { SOSHold = group->sos_list[i]; group->sos_list[i] = group->sos_list[i-1]; group->sos_list[i-1] = SOSHold; if(SOSHold == SOS) k = i; /* This is the index in the [1..> range */ } else break; } /* Return the list index of the new SOS */ return( k ); } STATIC int clean_SOSgroup(SOSgroup *group, MYBOOL forceupdatemap) { int i, n, k; SOSrec *SOS; if(group == NULL) return( 0 ); /* Delete any SOS without members or trivial member count */ n = 0; if(group->sos_alloc > 0) { group->maxorder = 0; for(i = group->sos_count; i > 0; i--) { SOS = group->sos_list[i-1]; k = SOS->members[0]; if((k == 0) || /* Empty */ ((k == abs(SOS->type)) && (k <= 2))) { /* Trivial */ delete_SOSrec(group, i); n++; } else { SETMAX(group->maxorder, abs(SOS->type)); } } if((n > 0) || forceupdatemap) SOS_member_updatemap(group); } return( n ); } STATIC void free_SOSgroup(SOSgroup **group) { int i; if((group == NULL) || (*group == NULL)) return; if((*group)->sos_alloc > 0) { for(i = 0; i < (*group)->sos_count; i++) free_SOSrec((*group)->sos_list[i]); FREE((*group)->sos_list); FREE((*group)->membership); FREE((*group)->memberpos); } FREE(*group); } /* SOS record functions */ STATIC SOSrec *create_SOSrec(SOSgroup *group, char *name, int type, int priority, int size, int *variables, REAL *weights) { SOSrec *SOS; SOS = (SOSrec *) calloc(1 , sizeof(*SOS)); SOS->parent = group; SOS->type = type; if(name == NULL) SOS->name = NULL; else { allocCHAR(group->lp, &SOS->name, (int) (strlen(name)+1), FALSE); strcpy(SOS->name, name); } if(type < 0) type = abs(type); SOS->tagorder = 0; SOS->size = 0; SOS->priority = priority; SOS->members = NULL; SOS->weights = NULL; SOS->membersSorted = NULL; SOS->membersMapped = NULL; if(size > 0) size = append_SOSrec(SOS, size, variables, weights); return(SOS); } STATIC int append_SOSrec(SOSrec *SOS, int size, int *variables, REAL *weights) { int i, oldsize, newsize, nn; lprec *lp = SOS->parent->lp; oldsize = SOS->size; newsize = oldsize + size; nn = abs(SOS->type); /* Shift existing active data right (normally zero) */ if(SOS->members == NULL) allocINT(lp, &SOS->members, 1+newsize+1+nn, TRUE); else { allocINT(lp, &SOS->members, 1+newsize+1+nn, AUTOMATIC); for(i = newsize+1+nn; i > newsize+1; i--) SOS->members[i] = SOS->members[i-size]; } SOS->members[0] = newsize; SOS->members[newsize+1] = nn; /* Copy the new data into the arrays */ if(SOS->weights == NULL) allocREAL(lp, &SOS->weights, 1+newsize, TRUE); else allocREAL(lp, &SOS->weights, 1+newsize, AUTOMATIC); for(i = oldsize+1; i <= newsize; i++) { SOS->members[i] = variables[i-oldsize-1]; if((SOS->members[i] < 1) || (SOS->members[i] > lp->columns)) report(lp, IMPORTANT, "append_SOS_rec: Invalid SOS variable definition for index %d\n", SOS->members[i]); else { if(SOS->isGUB) lp->var_type[SOS->members[i]] |= ISGUB; else lp->var_type[SOS->members[i]] |= ISSOS; } if(weights == NULL) SOS->weights[i] = i; /* Follow standard, which is sorted ascending */ else SOS->weights[i] = weights[i-oldsize-1]; SOS->weights[0] += SOS->weights[i]; } /* Sort the new paired lists ascending by weight (simple bubble sort) */ i = sortByREAL(SOS->members, SOS->weights, newsize, 1, TRUE); if(i > 0) report(lp, DETAILED, "append_SOS_rec: Non-unique SOS variable weight for index %d\n", i); /* Define mapping arrays to search large SOS's faster */ allocINT(lp, &SOS->membersSorted, newsize, AUTOMATIC); allocINT(lp, &SOS->membersMapped, newsize, AUTOMATIC); for(i = oldsize+1; i <= newsize; i++) { SOS->membersSorted[i - 1] = SOS->members[i]; SOS->membersMapped[i - 1] = i; } sortByINT(SOS->membersMapped, SOS->membersSorted, newsize, 0, TRUE); /* Confirm the new size */ SOS->size = newsize; return(newsize); } STATIC int make_SOSchain(lprec *lp, MYBOOL forceresort) { int i, j, k, n; MYBOOL *hold = NULL; REAL *order, sum, weight; SOSgroup *group = lp->SOS; /* PART A: Resort individual SOS member lists, if specified */ if(forceresort) SOS_member_sortlist(group, 0); /* PART B: Tally SOS variables and create master SOS variable list */ n = 0; for(i = 0; i < group->sos_count; i++) n += group->sos_list[i]->size; lp->sos_vars = n; if(lp->sos_vars > 0) /* Prevent memory loss in case of multiple solves */ FREE(lp->sos_priority); allocINT(lp, &lp->sos_priority, n, FALSE); allocREAL(lp, &order, n, FALSE); /* Move variable data to the master SOS list and sort by ascending weight */ n = 0; sum = 0; for(i = 0; i < group->sos_count; i++) { for(j = 1; j <= group->sos_list[i]->size; j++) { lp->sos_priority[n] = group->sos_list[i]->members[j]; weight = group->sos_list[i]->weights[j]; sum += weight; order[n] = sum; n++; } } hpsortex(order, n, 0, sizeof(*order), FALSE, compareREAL, lp->sos_priority); FREE(order); /* Remove duplicate SOS variables */ allocMYBOOL(lp, &hold, lp->columns+1, TRUE); k = 0; for(i = 0; i < n; i++) { j = lp->sos_priority[i]; if(!hold[j]) { hold[j] = TRUE; if(k < i) lp->sos_priority[k] = j; k++; } } FREE(hold); /* Adjust the size of the master variable list, if necessary */ if(k < lp->sos_vars) { allocINT(lp, &lp->sos_priority, k, AUTOMATIC); lp->sos_vars = k; } return( k ); } STATIC MYBOOL delete_SOSrec(SOSgroup *group, int sosindex) { #ifdef Paranoia if((sosindex <= 0) || (sosindex > group->sos_count)) { report(group->lp, IMPORTANT, "delete_SOSrec: Invalid SOS index %d\n", sosindex); return(FALSE); } #endif /* Delete and free the SOS record */ if(abs(SOS_get_type(group, sosindex)) == 1) group->sos1_count--; free_SOSrec(group->sos_list[sosindex-1]); while(sosindex < group->sos_count) { group->sos_list[sosindex-1] = group->sos_list[sosindex]; sosindex++; } group->sos_count--; /* Update maxorder */ group->maxorder = 0; for(sosindex = 0; sosindex < group->sos_count; sosindex++) { SETMAX(group->maxorder, abs(group->sos_list[sosindex]->type)); } return(TRUE); } STATIC void free_SOSrec(SOSrec *SOS) { if(SOS->name != NULL) FREE(SOS->name); if(SOS->size > 0) { FREE(SOS->members); FREE(SOS->weights); FREE(SOS->membersSorted); FREE(SOS->membersMapped); } FREE(SOS); } STATIC MYBOOL SOS_member_sortlist(SOSgroup *group, int sosindex) /* Routine to (re-)sort SOS member arrays for faster access to large SOSes */ { int i, n; int *list; lprec *lp = group->lp; SOSrec *SOS; #ifdef Paranoia if((sosindex < 0) || (sosindex > group->sos_count)) { report(lp, IMPORTANT, "SOS_member_sortlist: Invalid SOS index %d\n", sosindex); return(FALSE); } #endif if((sosindex == 0) && (group->sos_count == 1)) sosindex = 1; if(sosindex == 0) { for(i = 1; i <= group->sos_count; i++) { if(!SOS_member_sortlist(group, i)) return(FALSE); } } else { SOS = group->sos_list[sosindex-1]; list = SOS->members; n = list[0]; /* Make sure that the arrays are properly allocated and sized */ if(n != group->sos_list[sosindex-1]->size) { allocINT(lp, &SOS->membersSorted, n, AUTOMATIC); allocINT(lp, &SOS->membersMapped, n, AUTOMATIC); group->sos_list[sosindex-1]->size = n; } /* Reload the arrays and do the sorting */ for(i = 1; i <= n; i++) { SOS->membersSorted[i - 1] = list[i]; SOS->membersMapped[i - 1] = i; } sortByINT(SOS->membersMapped, SOS->membersSorted, n, 0, TRUE); } return( TRUE ); } STATIC int SOS_member_updatemap(SOSgroup *group) { int i, j, k, n, nvars = 0, *list, *tally = NULL; SOSrec *rec; lprec *lp = group->lp; /* (Re)-initialize usage arrays */ allocINT(lp, &group->memberpos, lp->columns+1, AUTOMATIC); allocINT(lp, &tally, lp->columns+1, TRUE); /* Get each variable's SOS membership count */ for(i = 0; i < group->sos_count; i++) { rec = group->sos_list[i]; n = rec->size; list = rec->members; for(j = 1; j <= n; j++) { k = list[j]; #ifdef Paranoia if((k < 1) || (k > lp->columns)) report(lp, SEVERE, "SOS_member_updatemap: Member %j of SOS number %d is out of column range (%d)\n", j, i+1, k); #endif tally[k]++; } } /* Compute pointer into column-sorted array */ group->memberpos[0] = 0; for(i = 1; i <= lp->columns; i++) { n = tally[i]; if(n > 0) nvars++; group->memberpos[i] = group->memberpos[i-1] + n; } n = group->memberpos[lp->columns]; MEMCOPY(tally+1, group->memberpos, lp->columns); /* Load the column-sorted SOS indeces / pointers */ allocINT(lp, &group->membership, n+1, AUTOMATIC); for(i = 0; i < group->sos_count; i++) { rec = group->sos_list[i]; n = rec->size; list = rec->members; for(j = 1; j <= n; j++) { k = tally[list[j]]++; #ifdef Paranoia if(k > group->memberpos[lp->columns]) report(lp, SEVERE, "SOS_member_updatemap: Member mapping for variable %j of SOS number %d is invalid\n", list[j], i+1); #endif group->membership[k] = i+1; } } FREE(tally); return( nvars ); } STATIC MYBOOL SOS_shift_col(SOSgroup *group, int sosindex, int column, int delta, LLrec *usedmap, MYBOOL forceresort) /* Routine to adjust SOS indeces for variable insertions or deletions; Note: SOS_shift_col must be called before make_SOSchain! */ { int i, ii, n, nn, nr; int changed; int *list; REAL *weights; #ifdef Paranoia lprec *lp = group->lp; if((sosindex < 0) || (sosindex > group->sos_count)) { report(lp, IMPORTANT, "SOS_shift_col: Invalid SOS index %d\n", sosindex); return(FALSE); } else if((column < 1) || (delta == 0)) { report(lp, IMPORTANT, "SOS_shift_col: Invalid column %d specified with delta %d\n", column, delta); return(FALSE); } #endif if((sosindex == 0) && (group->sos_count == 1)) sosindex = 1; if(sosindex == 0) { for(i = 1; i <= group->sos_count; i++) { if(!SOS_shift_col(group, i, column, delta, usedmap, forceresort)) return(FALSE); } } else { list = group->sos_list[sosindex-1]->members; weights = group->sos_list[sosindex-1]->weights; n = list[0]; nn = list[n+1]; /* Case where variable indeces are to be incremented */ if(delta > 0) { for(i = 1; i <= n; i++) { if(list[i] >= column) list[i] += delta; } } /* Case where variables are to be deleted/indeces decremented */ else { changed = 0; if(usedmap != NULL) { int *newidx = NULL; /* Defer creation of index mapper until we are sure that a member of this SOS is actually targeted for deletion */ if(newidx == NULL) { allocINT(group->lp, &newidx, group->lp->columns+1, TRUE); for(i = firstActiveLink(usedmap), ii = 1; i != 0; i = nextActiveLink(usedmap, i), ii++) newidx[i] = ii; } for(i = 1, ii = 0; i <= n; i++) { nr = list[i]; /* Check if this SOS variable should be deleted */ if(!isActiveLink(usedmap, nr)) continue; /* If the index is "high" then make adjustment and shift */ changed++; ii++; list[ii] = newidx[nr]; weights[ii] = weights[i]; } FREE(newidx); } else for(i = 1, ii = 0; i <= n; i++) { nr = list[i]; /* Check if this SOS variable should be deleted */ if((nr >= column) && (nr < column-delta)) continue; /* If the index is "high" then decrement */ if(nr > column) { changed++; nr += delta; } ii++; list[ii] = nr; weights[ii] = weights[i]; } /* Update the SOS length / type indicators */ if(ii < n) { list[0] = ii; list[ii+1] = nn; } /* Update mapping arrays to search large SOS's faster */ if(forceresort && ((ii < n) || (changed > 0))) SOS_member_sortlist(group, sosindex); } } return(TRUE); } int SOS_member_count(SOSgroup *group, int sosindex) { SOSrec *SOS; #ifdef Paranoia if((sosindex < 0) || (sosindex > group->sos_count)) { report(group->lp, IMPORTANT, "SOS_member_count: Invalid SOS index %d\n", sosindex); return( -1 ); } #endif SOS = group->sos_list[sosindex-1]; return( SOS->members[0] ); } int SOS_member_delete(SOSgroup *group, int sosindex, int member) { int *list, i, i2, k, n, nn = 0; SOSrec *SOS; lprec *lp = group->lp; #ifdef Paranoia if((sosindex < 0) || (sosindex > group->sos_count)) { report(group->lp, IMPORTANT, "SOS_member_delete: Invalid SOS index %d\n", sosindex); return( -1 ); } #endif if(sosindex == 0) { for(i = group->memberpos[member-1]; i < group->memberpos[member]; i++) { k = group->membership[i]; n = SOS_member_delete(group, k, member); if(n >= 0) nn += n; else return( n ); } /* We must update the mapper */ k = group->memberpos[member]; i = group->memberpos[member-1]; n = group->memberpos[lp->columns] - k; if(n > 0) MEMCOPY(group->membership + i, group->membership + k, n); for(i = member; i <= lp->columns; i++) group->memberpos[i] = group->memberpos[i-1]; } else { SOS = group->sos_list[sosindex-1]; list = SOS->members; n = list[0]; /* Find the offset of the member */ i = 1; while((i <= n) && (abs(list[i]) != member)) i++; if(i > n) return( -1 ); nn++; /* Shift remaining members *and* the active count one position left */ while(i <= n) { list[i] = list[i+1]; i++; } list[0]--; SOS->size--; /* Do the same with the active list one position left */ i = n + 1; i2 = i + list[n]; k = i + 1; while(i < i2) { if(abs(list[k]) == member) k++; list[i] = list[k]; i++; k++; } } return( nn ); } int SOS_get_type(SOSgroup *group, int sosindex) { #ifdef Paranoia if((sosindex < 1) || (sosindex > group->sos_count)) { report(group->lp, IMPORTANT, "SOS_get_type: Invalid SOS index %d\n", sosindex); return(FALSE); } #endif return(group->sos_list[sosindex-1]->type); } int SOS_infeasible(SOSgroup *group, int sosindex) { int i, n, nn, varnr, failindex, *list; lprec *lp = group->lp; #ifdef Paranoia if((sosindex < 0) || (sosindex > group->sos_count)) { report(lp, IMPORTANT, "SOS_infeasible: Invalid SOS index %d\n", sosindex); return(FALSE); } #endif if(sosindex == 0 && group->sos_count == 1) sosindex = 1; failindex = 0; if(sosindex == 0) { for(i = 1; i <= group->sos_count; i++) { failindex = SOS_infeasible(group, i); if(failindex > 0) break; } } else { list = group->sos_list[sosindex-1]->members; n = list[0]; nn = list[n+1]; /* Find index of next lower-bounded variable */ for(i = 1; i <= n; i++) { varnr = abs(list[i]); if((lp->orig_lowbo[lp->rows + varnr] > 0) && !((lp->sc_vars > 0) && is_semicont(lp, varnr))) break; } /* Find if there is another lower-bounded variable beyond the type window */ i = i+nn; while(i <= n) { varnr = abs(list[i]); if((lp->orig_lowbo[lp->rows + varnr] > 0) && !((lp->sc_vars > 0) && is_semicont(lp, varnr))) break; i++; } if(i <= n) failindex = abs(list[i]); } return(failindex); } int SOS_member_index(SOSgroup *group, int sosindex, int member) { int n; SOSrec *SOS; SOS = group->sos_list[sosindex-1]; n = SOS->members[0]; n = searchFor(member, SOS->membersSorted, n, 0, FALSE); if(n >= 0) n = SOS->membersMapped[n]; return(n); } int SOS_memberships(SOSgroup *group, int varnr) { int i, n = 0; lprec *lp; /* Check if there is anything to do */ if((group == NULL) || (SOS_count(lp = group->lp) == 0)) return( n ); #ifdef Paranoia if((varnr < 0) || (varnr > lp->columns)) { report(lp, IMPORTANT, "SOS_memberships: Invalid variable index %d given\n", varnr); return( n ); } #endif if(varnr == 0) { for(i = 1; i <= lp->columns; i++) if(group->memberpos[i] > group->memberpos[i-1]) n++; } else n = group->memberpos[varnr] - group->memberpos[varnr-1]; return( n ); } int SOS_is_member(SOSgroup *group, int sosindex, int column) { int i, n = FALSE, *list; lprec *lp; if(group == NULL) return( FALSE ); lp = group->lp; #ifdef Paranoia if((sosindex < 0) || (sosindex > group->sos_count)) { report(lp, IMPORTANT, "SOS_is_member: Invalid SOS index %d\n", sosindex); return(n); } #endif if(sosindex == 0) { if(lp->var_type[column] & (ISSOS | ISGUB)) n = (MYBOOL) (SOS_memberships(group, column) > 0); } else if(lp->var_type[column] & (ISSOS | ISGUB)) { /* Search for the variable */ i = SOS_member_index(group, sosindex, column); /* Signal active status if found, otherwise return FALSE */ if(i > 0) { list = group->sos_list[sosindex-1]->members; if(list[i] < 0) n = -TRUE; else n = TRUE; } } return(n); } MYBOOL SOS_is_member_of_type(SOSgroup *group, int column, int sostype) { int i, k, n; if(group != NULL) for(i = group->memberpos[column-1]; i < group->memberpos[column]; i++) { k = group->membership[i]; n = SOS_get_type(group, k); if(((n == sostype) || ((sostype == SOSn) && (n > 2))) && SOS_is_member(group, k, column)) return(TRUE); } return(FALSE); } MYBOOL SOS_set_GUB(SOSgroup *group, int sosindex, MYBOOL state) { int i; #ifdef Paranoia if((sosindex < 0) || (sosindex > group->sos_count)) { report(group->lp, IMPORTANT, "SOS_set_GUB: Invalid SOS index %d\n", sosindex); return(FALSE); } #endif if((sosindex == 0) && (group->sos_count == 1)) sosindex = 1; if(sosindex == 0) { for(i = 1; i <= group->sos_count; i++) SOS_set_GUB(group, i, state); } else group->sos_list[sosindex-1]->isGUB = state; return(TRUE); } MYBOOL SOS_is_GUB(SOSgroup *group, int sosindex) { int i; #ifdef Paranoia if((sosindex < 0) || (sosindex > group->sos_count)) { report(group->lp, IMPORTANT, "SOS_is_GUB: Invalid SOS index %d\n", sosindex); return(FALSE); } #endif if((sosindex == 0) && (group->sos_count == 1)) sosindex = 1; if(sosindex == 0) { for(i = 1; i <= group->sos_count; i++) { if(SOS_is_GUB(group, i)) return(TRUE); } return(FALSE); } else return( group->sos_list[sosindex-1]->isGUB ); } MYBOOL SOS_is_marked(SOSgroup *group, int sosindex, int column) { int i, k, n, *list; lprec *lp; if(group == NULL) return( FALSE ); lp = group->lp; #ifdef Paranoia if((sosindex < 0) || (sosindex > group->sos_count)) { report(lp, IMPORTANT, "SOS_is_marked: Invalid SOS index %d\n", sosindex); return(FALSE); } #endif if(!(lp->var_type[column] & (ISSOS | ISGUB))) return(FALSE); if(sosindex == 0) { for(i = group->memberpos[column-1]; i < group->memberpos[column]; i++) { k = group->membership[i]; n = SOS_is_marked(group, k, column); if(n) return(TRUE); } } else { list = group->sos_list[sosindex-1]->members; n = list[0]; /* Search for the variable (normally always faster to do linear search here) */ column = -column; for(i = 1; i <= n; i++) if(list[i] == column) return(TRUE); } return(FALSE); } MYBOOL SOS_is_active(SOSgroup *group, int sosindex, int column) { int i, n, nn, *list; lprec *lp = group->lp; #ifdef Paranoia if((sosindex < 0) || (sosindex > group->sos_count)) { report(lp, IMPORTANT, "SOS_is_active: Invalid SOS index %d\n", sosindex); return(FALSE); } #endif if(!(lp->var_type[column] & (ISSOS | ISGUB))) return(FALSE); if(sosindex == 0) { for(i = group->memberpos[column-1]; i < group->memberpos[column]; i++) { nn = group->membership[i]; n = SOS_is_active(group, nn, column); if(n) return(TRUE); } } else { list = group->sos_list[sosindex-1]->members; n = list[0]+1; nn = list[n]; /* Scan the active (non-zero) SOS index list */ for(i = 1; (i <= nn) && (list[n+i] != 0); i++) if(list[n+i] == column) return(TRUE); } return(FALSE); } MYBOOL SOS_is_full(SOSgroup *group, int sosindex, int column, MYBOOL activeonly) { int i, nn, n, *list; lprec *lp = group->lp; #ifdef Paranoia if((sosindex < 0) || (sosindex > group->sos_count)) { report(lp, IMPORTANT, "SOS_is_full: Invalid SOS index %d\n", sosindex); return(FALSE); } #endif if(!(lp->var_type[column] & (ISSOS | ISGUB))) return(FALSE); if(sosindex == 0) { for(i = group->memberpos[column-1]; i < group->memberpos[column]; i++) { nn = group->membership[i]; if(SOS_is_full(group, nn, column, activeonly)) return(TRUE); } } else if(SOS_is_member(group, sosindex, column)) { list = group->sos_list[sosindex-1]->members; n = list[0]+1; nn = list[n]; /* Info: Last item in the active list is non-zero if the current SOS is full */ if(list[n+nn] != 0) return(TRUE); if(!activeonly) { /* Spool to last active variable */ for(i = nn-1; (i > 0) && (list[n+i] == 0); i--); /* Having found it, check if subsequent variables are set (via bounds) as inactive */ if(i > 0) { nn -= i; /* Compute unused active slots */ i = SOS_member_index(group, sosindex, list[n+i]); for(; (nn > 0) && (list[i] < 0); i++, nn--); if(nn == 0) return(TRUE); } } } return(FALSE); } MYBOOL SOS_can_activate(SOSgroup *group, int sosindex, int column) { int i, n, nn, nz, *list; lprec *lp; if(group == NULL) return( FALSE ); lp = group->lp; #ifdef Paranoia if((sosindex < 0) || (sosindex > group->sos_count)) { report(lp, IMPORTANT, "SOS_can_activate: Invalid SOS index %d\n", sosindex); return(FALSE); } #endif if(!(lp->var_type[column] & (ISSOS | ISGUB))) return(FALSE); if(sosindex == 0) { for(i = group->memberpos[column-1]; i < group->memberpos[column]; i++) { nn = group->membership[i]; n = SOS_can_activate(group, nn, column); if(n == FALSE) return(FALSE); } } else if(SOS_is_member(group, sosindex, column)) { list = group->sos_list[sosindex-1]->members; n = list[0]+1; nn = list[n]; #if 0 /* Accept if the SOS is empty */ if(list[n+1] == 0) return(TRUE); #endif /* Cannot activate a variable if the SOS is full */ if(list[n+nn] != 0) return(FALSE); /* Check if there are variables quasi-active via non-zero lower bounds */ nz = 0; for(i = 1; i < n; i++) if(lp->bb_bounds->lowbo[lp->rows+abs(list[i])] > 0) { nz++; /* Reject outright if selected column has a non-zero lower bound */ if(list[i] == column) return(FALSE); } #ifdef Paranoia if(nz > nn) report(lp, SEVERE, "SOS_can_activate: Found too many non-zero member variables for SOS index %d\n", sosindex); #endif for(i = 1; i <= nn; i++) { if(list[n+i] == 0) break; if(lp->bb_bounds->lowbo[lp->rows+list[n+i]] == 0) nz++; } if(nz == nn) return(FALSE); /* Accept if the SOS is empty */ if(list[n+1] == 0) return(TRUE); /* Check if we can set variable active in SOS2..SOSn (must check left and right neighbours if one variable is already active) */ if(nn > 1) { /* Find the variable that was last activated; Also check that the candidate variable is not already active */ for(i = 1; i <= nn; i++) { if(list[n+i] == 0) break; if(list[n+i] == column) return(FALSE); } i--; nn = list[n+i]; /* SOS accepts an additional variable; confirm neighbourness of candidate; Search for the SOS set index of the last activated variable */ n = list[0]; for(i = 1; i <= n; i++) if(abs(list[i]) == nn) break; if(i > n) { report(lp, CRITICAL, "SOS_can_activate: Internal index error at SOS %d\n", sosindex); return(FALSE); } /* SOS accepts an additional variable; confirm neighbourness of candidate */ /* Check left neighbour */ if((i > 1) && (list[i-1] == column)) return(TRUE); /* Check right neighbour */ if((i < n) && (list[i+1] == column)) return(TRUE); /* It is not the right neighbour; return false */ return(FALSE); } } return(TRUE); } MYBOOL SOS_set_marked(SOSgroup *group, int sosindex, int column, MYBOOL asactive) { int i, n, nn, *list; lprec *lp = group->lp; #ifdef Paranoia if((sosindex < 0) || (sosindex > group->sos_count)) { report(lp, IMPORTANT, "SOS_set_marked: Invalid SOS index %d\n", sosindex); return(FALSE); } #endif if(!(lp->var_type[column] & (ISSOS | ISGUB))) return(FALSE); if(sosindex == 0) { /* Define an IBM-"SOS3" member variable temporarily as integer, if it is not already a permanent integer; is reset in SOS_unmark */ if(asactive && !is_int(lp, column) && SOS_is_member_of_type(group, column, SOS3)) { lp->var_type[column] |= ISSOSTEMPINT; set_int(lp, column, TRUE); } nn = 0; for(i = group->memberpos[column-1]; i < group->memberpos[column]; i++) { n = group->membership[i]; if(SOS_set_marked(group, n, column, asactive)) nn++; } return((MYBOOL) (nn == group->sos_count)); } else { list = group->sos_list[sosindex-1]->members; n = list[0]+1; nn = list[n]; /* Search for the variable */ i = SOS_member_index(group, sosindex, column); /* First mark active in the set member list as used */ if((i > 0) && (list[i] > 0)) list[i] *= -1; else return(TRUE); /* Then move the variable to the live list */ if(asactive) { for(i = 1; i <= nn; i++) { if(list[n+i] == column) return(FALSE); else if(list[n+i] == 0) { list[n+i] = column; return(FALSE); } } } return(TRUE); } } MYBOOL SOS_unmark(SOSgroup *group, int sosindex, int column) { int i, n, nn, *list; MYBOOL isactive; lprec *lp = group->lp; #ifdef Paranoia if((sosindex < 0) || (sosindex > group->sos_count)) { report(lp, IMPORTANT, "SOS_unmark: Invalid SOS index %d\n", sosindex); return(FALSE); } #endif if(!(lp->var_type[column] & (ISSOS | ISGUB))) return(FALSE); if(sosindex == 0) { /* Undefine a SOS3 member variable that has temporarily been set as integer */ if(lp->var_type[column] & ISSOSTEMPINT) { lp->var_type[column] &= !ISSOSTEMPINT; set_int(lp, column, FALSE); } nn = 0; for(i = group->memberpos[column-1]; i < group->memberpos[column]; i++) { n = group->membership[i]; if(SOS_unmark(group, n, column)) nn++; } return((MYBOOL) (nn == group->sos_count)); } else { list = group->sos_list[sosindex-1]->members; n = list[0]+1; nn = list[n]; /* Search for the variable */ i = SOS_member_index(group, sosindex, column); /* Restore sign in main list */ if((i > 0) && (list[i] < 0)) list[i] *= -1; else return(TRUE); /* Find the variable in the active list... */ isactive = SOS_is_active(group, sosindex, column); if(isactive) { for(i = 1; i <= nn; i++) if(list[n+i] == column) break; /* ...shrink the list if found, otherwise return error */ if(i <= nn) { for(; ilp; #ifdef Paranoia if((sosindex < 0) || (sosindex > group->sos_count)) { report(lp, IMPORTANT, "SOS_fix_unmarked: Invalid SOS index %d\n", sosindex); return(FALSE); } #endif count = 0; if(sosindex == 0) { for(i = group->memberpos[variable-1]; i < group->memberpos[variable]; i++) { n = group->membership[i]; count += SOS_fix_unmarked(group, n, variable, bound, value, isupper, diffcount, changelog); } } else { list = group->sos_list[sosindex-1]->members; n = list[0]+1; /* Count the number of active and free SOS variables */ nn = list[n]; for(i = 1; i <= nn; i++) { if(list[n+i] == 0) break; } i--; i = nn - i; /* Establish the number of unused slots */ /* Determine the free SOS variable window */ if(i == nn) { nLeft = 0; nRight = SOS_member_index(group, sosindex, variable); } else { nLeft = SOS_member_index(group, sosindex, list[n+1]); if(variable == list[n+1]) nRight = nLeft; else nRight = SOS_member_index(group, sosindex, variable); } nRight += i; /* Loop (nRight+1)..n */ /* Fix variables outside of the free SOS variable window */ for(i = 1; i < n; i++) { /* Skip the SOS variable window */ if((i >= nLeft) && (i <= nRight)) continue; /* Otherwise proceed to set bound */ ii = list[i]; if(ii > 0) { ii += lp->rows; if(bound[ii] != value) { /* Verify that we don't violate original bounds */ if(isupper && (value < lp->orig_lowbo[ii])) return(-ii); else if(!isupper && (value > lp->orig_upbo[ii])) return(-ii); /* OK, set the new bound */ count++; if(changelog == NULL) bound[ii] = value; else modifyUndoLadder(changelog, ii, bound, value); } if((diffcount != NULL) && (lp->solution[ii] != value)) (*diffcount)++; } } } return(count); } int *SOS_get_candidates(SOSgroup *group, int sosindex, int column, MYBOOL excludetarget, REAL *upbound, REAL *lobound) { int i, ii, j, n, nn = 0, *list, *candidates = NULL; lprec *lp = group->lp; if(group == NULL) return( candidates ); #ifdef Paranoia if(sosindex > group->sos_count) { report(lp, IMPORTANT, "SOS_get_candidates: Invalid index %d\n", sosindex); return( candidates ); } #endif /* Determine SOS target(s); note that if "sosindex" is negative, only the first non-empty SOS where "column" is a member is processed */ if(sosindex <= 0) { i = 0; ii = group->sos_count; } else { i = sosindex - 1; ii = sosindex; } /* Tally candidate usage */ allocINT(lp, &candidates, lp->columns+1, TRUE); for(; i < ii; i++) { if(!SOS_is_member(group, i+1, column)) continue; list = group->sos_list[i]->members; n = list[0]; while(n > 0) { j = list[n]; if((j > 0) && (upbound[lp->rows+j] > 0)) { if(lobound[lp->rows+j] > 0) { report(lp, IMPORTANT, "SOS_get_candidates: Invalid non-zero lower bound setting\n"); n = 0; goto Finish; } if(candidates[j] == 0) nn++; candidates[j]++; } n--; } if((sosindex < 0) && (nn > 1)) break; } /* Condense the list into indeces */ n = 0; for(i = 1; i <= lp->columns; i++) { if((candidates[i] > 0) && (!excludetarget || (i != column))) { n++; candidates[n] = i; } } /* Finalize */ Finish: candidates[0] = n; if(n == 0) FREE(candidates); return( candidates); } int SOS_fix_list(SOSgroup *group, int sosindex, int variable, REAL *bound, int *varlist, MYBOOL isleft, DeltaVrec *changelog) { int i, ii, jj, count = 0; REAL value = 0; lprec *lp = group->lp; #ifdef Paranoia if((sosindex < 0) || (sosindex > group->sos_count)) { report(lp, IMPORTANT, "SOS_fix_list: Invalid index %d\n", sosindex); return(FALSE); } #endif if(sosindex == 0) { for(i = group->memberpos[variable-1]; i < group->memberpos[variable]; i++) { ii = group->membership[i]; count += SOS_fix_list(group, ii, variable, bound, varlist, isleft, changelog); } } else { /* Establish the number of unmarked variables in the left window (note that "variable" should have been marked previously) */ ii = varlist[0] / 2; if(isleft) { i = 1; if(isleft == AUTOMATIC) ii = varlist[0]; } else { i = ii + 1; ii = varlist[0]; } /* Loop over members to fix values at the new bound (zero) */ while(i <= ii) { if(SOS_is_member(group, sosindex, varlist[i])) { jj = lp->rows + varlist[i]; /* Verify that we don't violate original bounds */ if(value < lp->orig_lowbo[jj]) return( -jj ); /* OK, set the new bound */ count++; if(changelog == NULL) bound[jj] = value; else modifyUndoLadder(changelog, jj, bound, value); } i++; } } return( count ); } int SOS_is_satisfied(SOSgroup *group, int sosindex, REAL *solution) /* Determine if the SOS is satisfied for the current solution vector; The return code is in the range [-2..+2], depending on the type of satisfaction. Positive return value means too many non-zero values, negative value means set incomplete: -2: Set member count not full (SOS3) -1: Set member count not full 0: Set is full (also returned if the SOS index is invalid) 1: Too many non-zero sequential variables 2: Set consistency error */ { int i, n, nn, count, *list; int type, status = 0; lprec *lp = group->lp; #ifdef Paranoia if((sosindex < 0) || (sosindex > group->sos_count)) { report(lp, IMPORTANT, "SOS_is_satisfied: Invalid index %d\n", sosindex); return( SOS_COMPLETE ); } #endif if((sosindex == 0) && (group->sos_count == 1)) sosindex = 1; if(sosindex == 0) { for(i = 1; i <= group->sos_count; i++) { status = SOS_is_satisfied(group, i, solution); if((status != SOS_COMPLETE) && (status != SOS_INCOMPLETE)) break; } } else { type = SOS_get_type(group, sosindex); list = group->sos_list[sosindex-1]->members; n = list[0]+1; nn = list[n]; /* Count the number of active SOS variables */ for(i = 1; i <= nn; i++) { if(list[n+i] == 0) break; } count = i-1; if(count == nn) status = SOS_COMPLETE; /* Set is full */ else status = SOS_INCOMPLETE; /* Set is partial */ /* Find index of the first active variable; fail if some are non-zero */ if(count > 0) { nn = list[n+1]; for(i = 1; i < n; i++) { if((abs(list[i]) == nn) || (solution[lp->rows + abs(list[i])] != 0)) break; } if(abs(list[i]) != nn) status = SOS_INTERNALERROR; /* Set consistency error (leading set variables are non-zero) */ else { /* Scan active SOS variables until we find a non-zero value */ while(count > 0) { if(solution[lp->rows + abs(list[i])] != 0) break; i++; count--; } /* Scan active non-zero SOS variables; break at first non-zero (rest required to be zero) */ while(count > 0) { if(solution[lp->rows + abs(list[i])] == 0) break; i++; count--; } if(count > 0) status = SOS_INTERNALERROR; /* Set consistency error (active set variables are zero) */ } } else { i = 1; /* There are no active variables; see if we have happened to find a valid header */ while((i < n) && (solution[lp->rows + abs(list[i])] == 0)) i++; count = 0; while((i < n) && (count <= nn) && (solution[lp->rows + abs(list[i])] != 0)) { count++; i++; } if(count > nn) status = SOS_INFEASIBLE; /* Too-many sequential non-zero variables */ } /* Scan the trailing set of SOS variables; fail if some are non-zero */ if(status <= 0) { n--; while(i <= n) { if(solution[lp->rows + abs(list[i])] != 0) break; i++; } if(i <= n) status = SOS_INFEASIBLE; /* Too-many sequential non-zero variables */ /* Code member deficiency for SOS3 separately */ else if((status == -1) && (type <= SOS3)) status = SOS3_INCOMPLETE; } } return( status ); } MYBOOL SOS_is_feasible(SOSgroup *group, int sosindex, REAL *solution) /* Determine if the SOS is feasible up to the current SOS variable */ { int i, n, nn, *list; MYBOOL status = TRUE; lprec *lp = group->lp; #ifdef Paranoia if((sosindex < 0) || (sosindex > group->sos_count)) { report(lp, IMPORTANT, "SOS_is_feasible: Invalid SOS index %d\n", sosindex); return( 0 ); } #endif if((sosindex == 0) && (group->sos_count == 1)) sosindex = 1; if(sosindex == 0) { for(i = 1; status && (i <= group->sos_count); i++) { status = SOS_is_feasible(group, i, solution); } } else { list = group->sos_list[sosindex-1]->members; n = list[0]+1; nn = list[n]; if(nn <= 2) return(status); /* Find if we have a gap in the non-zero solution values */ i = 1; sosindex = 0; while((i <= nn) && (list[n+i] != 0)) { while((i <= nn) && (list[n+i] != 0) && (solution[lp->rows+list[n+i]] == 0)) i++; if((i <= nn) && (list[n+i] != 0)) { i++; /* Step to next */ while((i <= nn) && (list[n+i] != 0) && (solution[lp->rows+list[n+i]] != 0)) i++; sosindex++; } i++; /* Step to next */ } status = (MYBOOL) (sosindex <= 1); } return(status); } MSVMpack1.2/lp_solve_5.5/lp_explicit.h0000664000175000017500000014547711244000030016625 0ustar lauerlauer#define HEADER_lp_report #include "lp_lib.h" #if defined LPSOLVEAPIFROMLPRECDEF # define LPSOLVEAPIFROMLPREC # define LPSOLVEAPIDEF #endif #if defined LPSOLVEAPIFROMLIBDEF # define LPSOLVEAPIFROMLIB # define LPSOLVEAPIDEF #endif #if !defined LPSOLVEAPIDEF # define LPSOLVEAPIDEF extern #endif /* entries for lp structure */ LPSOLVEAPIDEF add_column_func *_add_column; LPSOLVEAPIDEF add_columnex_func *_add_columnex; LPSOLVEAPIDEF add_constraint_func *_add_constraint; LPSOLVEAPIDEF add_constraintex_func *_add_constraintex; LPSOLVEAPIDEF add_lag_con_func *_add_lag_con; LPSOLVEAPIDEF add_SOS_func *_add_SOS; LPSOLVEAPIDEF column_in_lp_func *_column_in_lp; LPSOLVEAPIDEF copy_lp_func *_copy_lp; LPSOLVEAPIDEF default_basis_func *_default_basis; LPSOLVEAPIDEF del_column_func *_del_column; LPSOLVEAPIDEF del_constraint_func *_del_constraint; LPSOLVEAPIDEF delete_lp_func *_delete_lp; LPSOLVEAPIDEF dualize_lp_func *_dualize_lp; LPSOLVEAPIDEF free_lp_func *_free_lp; LPSOLVEAPIDEF get_anti_degen_func *_get_anti_degen; LPSOLVEAPIDEF get_basis_func *_get_basis; LPSOLVEAPIDEF get_basiscrash_func *_get_basiscrash; LPSOLVEAPIDEF get_bb_depthlimit_func *_get_bb_depthlimit; LPSOLVEAPIDEF get_bb_floorfirst_func *_get_bb_floorfirst; LPSOLVEAPIDEF get_bb_rule_func *_get_bb_rule; LPSOLVEAPIDEF get_bounds_tighter_func *_get_bounds_tighter; LPSOLVEAPIDEF get_break_at_value_func *_get_break_at_value; LPSOLVEAPIDEF get_col_name_func *_get_col_name; LPSOLVEAPIDEF get_column_func *_get_column; LPSOLVEAPIDEF get_columnex_func *_get_columnex; LPSOLVEAPIDEF get_constr_type_func *_get_constr_type; LPSOLVEAPIDEF get_constr_value_func *_get_constr_value; LPSOLVEAPIDEF get_constraints_func *_get_constraints; LPSOLVEAPIDEF get_dual_solution_func *_get_dual_solution; LPSOLVEAPIDEF get_epsb_func *_get_epsb; LPSOLVEAPIDEF get_epsd_func *_get_epsd; LPSOLVEAPIDEF get_epsel_func *_get_epsel; LPSOLVEAPIDEF get_epsint_func *_get_epsint; LPSOLVEAPIDEF get_epsperturb_func *_get_epsperturb; LPSOLVEAPIDEF get_epspivot_func *_get_epspivot; LPSOLVEAPIDEF get_improve_func *_get_improve; LPSOLVEAPIDEF get_infinite_func *_get_infinite; LPSOLVEAPIDEF get_lambda_func *_get_lambda; LPSOLVEAPIDEF get_lowbo_func *_get_lowbo; LPSOLVEAPIDEF get_lp_index_func *_get_lp_index; LPSOLVEAPIDEF get_lp_name_func *_get_lp_name; LPSOLVEAPIDEF get_Lrows_func *_get_Lrows; LPSOLVEAPIDEF get_mat_func *_get_mat; LPSOLVEAPIDEF get_mat_byindex_func *_get_mat_byindex; LPSOLVEAPIDEF get_max_level_func *_get_max_level; LPSOLVEAPIDEF get_maxpivot_func *_get_maxpivot; LPSOLVEAPIDEF get_mip_gap_func *_get_mip_gap; LPSOLVEAPIDEF get_multiprice_func *_get_multiprice; LPSOLVEAPIDEF get_nameindex_func *_get_nameindex; LPSOLVEAPIDEF get_Ncolumns_func *_get_Ncolumns; LPSOLVEAPIDEF get_negrange_func *_get_negrange; LPSOLVEAPIDEF get_nz_func *_get_nonzeros; LPSOLVEAPIDEF get_Norig_columns_func *_get_Norig_columns; LPSOLVEAPIDEF get_Norig_rows_func *_get_Norig_rows; LPSOLVEAPIDEF get_Nrows_func *_get_Nrows; LPSOLVEAPIDEF get_obj_bound_func *_get_obj_bound; LPSOLVEAPIDEF get_objective_func *_get_objective; LPSOLVEAPIDEF get_orig_index_func *_get_orig_index; LPSOLVEAPIDEF get_origcol_name_func *_get_origcol_name; LPSOLVEAPIDEF get_origrow_name_func *_get_origrow_name; LPSOLVEAPIDEF get_partialprice_func *_get_partialprice; LPSOLVEAPIDEF get_pivoting_func *_get_pivoting; LPSOLVEAPIDEF get_presolve_func *_get_presolve; LPSOLVEAPIDEF get_presolveloops_func *_get_presolveloops; LPSOLVEAPIDEF get_primal_solution_func *_get_primal_solution; LPSOLVEAPIDEF get_print_sol_func *_get_print_sol; LPSOLVEAPIDEF get_pseudocosts_func *_get_pseudocosts; LPSOLVEAPIDEF get_ptr_constraints_func *_get_ptr_constraints; LPSOLVEAPIDEF get_ptr_dual_solution_func *_get_ptr_dual_solution; LPSOLVEAPIDEF get_ptr_lambda_func *_get_ptr_lambda; LPSOLVEAPIDEF get_ptr_primal_solution_func *_get_ptr_primal_solution; LPSOLVEAPIDEF get_ptr_sensitivity_obj_func *_get_ptr_sensitivity_obj; LPSOLVEAPIDEF get_ptr_sensitivity_objex_func *_get_ptr_sensitivity_objex; LPSOLVEAPIDEF get_ptr_sensitivity_rhs_func *_get_ptr_sensitivity_rhs; LPSOLVEAPIDEF get_ptr_variables_func *_get_ptr_variables; LPSOLVEAPIDEF get_rh_func *_get_rh; LPSOLVEAPIDEF get_rh_range_func *_get_rh_range; LPSOLVEAPIDEF get_row_func *_get_row; LPSOLVEAPIDEF get_rowex_func *_get_rowex; LPSOLVEAPIDEF get_row_name_func *_get_row_name; LPSOLVEAPIDEF get_scalelimit_func *_get_scalelimit; LPSOLVEAPIDEF get_scaling_func *_get_scaling; LPSOLVEAPIDEF get_sensitivity_obj_func *_get_sensitivity_obj; LPSOLVEAPIDEF get_sensitivity_objex_func *_get_sensitivity_objex; LPSOLVEAPIDEF get_sensitivity_rhs_func *_get_sensitivity_rhs; LPSOLVEAPIDEF get_simplextype_func *_get_simplextype; LPSOLVEAPIDEF get_solutioncount_func *_get_solutioncount; LPSOLVEAPIDEF get_solutionlimit_func *_get_solutionlimit; LPSOLVEAPIDEF get_status_func *_get_status; LPSOLVEAPIDEF get_statustext_func *_get_statustext; LPSOLVEAPIDEF get_timeout_func *_get_timeout; LPSOLVEAPIDEF get_total_iter_func *_get_total_iter; LPSOLVEAPIDEF get_total_nodes_func *_get_total_nodes; LPSOLVEAPIDEF get_upbo_func *_get_upbo; LPSOLVEAPIDEF get_var_branch_func *_get_var_branch; LPSOLVEAPIDEF get_var_dualresult_func *_get_var_dualresult; LPSOLVEAPIDEF get_var_primalresult_func *_get_var_primalresult; LPSOLVEAPIDEF get_var_priority_func *_get_var_priority; LPSOLVEAPIDEF get_variables_func *_get_variables; LPSOLVEAPIDEF get_verbose_func *_get_verbose; LPSOLVEAPIDEF get_working_objective_func *_get_working_objective; LPSOLVEAPIDEF guess_basis_func *_guess_basis; LPSOLVEAPIDEF has_BFP_func *_has_BFP; LPSOLVEAPIDEF has_XLI_func *_has_XLI; LPSOLVEAPIDEF is_add_rowmode_func *_is_add_rowmode; LPSOLVEAPIDEF is_anti_degen_func *_is_anti_degen; LPSOLVEAPIDEF is_binary_func *_is_binary; LPSOLVEAPIDEF is_break_at_first_func *_is_break_at_first; LPSOLVEAPIDEF is_constr_type_func *_is_constr_type; LPSOLVEAPIDEF is_debug_func *_is_debug; LPSOLVEAPIDEF is_feasible_func *_is_feasible; LPSOLVEAPIDEF is_unbounded_func *_is_unbounded; LPSOLVEAPIDEF is_infinite_func *_is_infinite; LPSOLVEAPIDEF is_int_func *_is_int; LPSOLVEAPIDEF is_integerscaling_func *_is_integerscaling; LPSOLVEAPIDEF is_lag_trace_func *_is_lag_trace; LPSOLVEAPIDEF is_maxim_func *_is_maxim; LPSOLVEAPIDEF is_nativeBFP_func *_is_nativeBFP; LPSOLVEAPIDEF is_nativeXLI_func *_is_nativeXLI; LPSOLVEAPIDEF is_negative_func *_is_negative; LPSOLVEAPIDEF is_piv_mode_func *_is_piv_mode; LPSOLVEAPIDEF is_piv_rule_func *_is_piv_rule; LPSOLVEAPIDEF is_presolve_func *_is_presolve; LPSOLVEAPIDEF is_scalemode_func *_is_scalemode; LPSOLVEAPIDEF is_scaletype_func *_is_scaletype; LPSOLVEAPIDEF is_semicont_func *_is_semicont; LPSOLVEAPIDEF is_SOS_var_func *_is_SOS_var; LPSOLVEAPIDEF is_trace_func *_is_trace; LPSOLVEAPIDEF is_use_names_func *_is_use_names; LPSOLVEAPIDEF lp_solve_version_func *_lp_solve_version; LPSOLVEAPIDEF make_lp_func *_make_lp; LPSOLVEAPIDEF print_constraints_func *_print_constraints; LPSOLVEAPIDEF print_debugdump_func *_print_debugdump; LPSOLVEAPIDEF print_duals_func *_print_duals; LPSOLVEAPIDEF print_lp_func *_print_lp; LPSOLVEAPIDEF print_objective_func *_print_objective; LPSOLVEAPIDEF print_scales_func *_print_scales; LPSOLVEAPIDEF print_solution_func *_print_solution; LPSOLVEAPIDEF print_str_func *_print_str; LPSOLVEAPIDEF print_tableau_func *_print_tableau; LPSOLVEAPIDEF put_abortfunc_func *_put_abortfunc; LPSOLVEAPIDEF put_bb_nodefunc_func *_put_bb_nodefunc; LPSOLVEAPIDEF put_bb_branchfunc_func *_put_bb_branchfunc; LPSOLVEAPIDEF put_logfunc_func *_put_logfunc; LPSOLVEAPIDEF put_msgfunc_func *_put_msgfunc; LPSOLVEAPIDEF read_LP_func *_read_LP; LPSOLVEAPIDEF read_MPS_func *_read_MPS; LPSOLVEAPIDEF read_XLI_func *_read_XLI; LPSOLVEAPIDEF read_params_func *_read_params; LPSOLVEAPIDEF read_basis_func *_read_basis; LPSOLVEAPIDEF reset_basis_func *_reset_basis; LPSOLVEAPIDEF reset_params_func *_reset_params; LPSOLVEAPIDEF reportfunc *_report; LPSOLVEAPIDEF resize_lp_func *_resize_lp; LPSOLVEAPIDEF set_add_rowmode_func *_set_add_rowmode; LPSOLVEAPIDEF set_anti_degen_func *_set_anti_degen; LPSOLVEAPIDEF set_basisvar_func *_set_basisvar; LPSOLVEAPIDEF set_basis_func *_set_basis; LPSOLVEAPIDEF set_basiscrash_func *_set_basiscrash; LPSOLVEAPIDEF set_bb_depthlimit_func *_set_bb_depthlimit; LPSOLVEAPIDEF set_bb_floorfirst_func *_set_bb_floorfirst; LPSOLVEAPIDEF set_bb_rule_func *_set_bb_rule; LPSOLVEAPIDEF set_BFP_func *_set_BFP; LPSOLVEAPIDEF set_binary_func *_set_binary; LPSOLVEAPIDEF set_bounds_func *_set_bounds; LPSOLVEAPIDEF set_bounds_tighter_func *_set_bounds_tighter; LPSOLVEAPIDEF set_break_at_first_func *_set_break_at_first; LPSOLVEAPIDEF set_break_at_value_func *_set_break_at_value; LPSOLVEAPIDEF set_column_func *_set_column; LPSOLVEAPIDEF set_columnex_func *_set_columnex; LPSOLVEAPIDEF set_col_name_func *_set_col_name; LPSOLVEAPIDEF set_constr_type_func *_set_constr_type; LPSOLVEAPIDEF set_debug_func *_set_debug; LPSOLVEAPIDEF set_epsb_func *_set_epsb; LPSOLVEAPIDEF set_epsd_func *_set_epsd; LPSOLVEAPIDEF set_epsel_func *_set_epsel; LPSOLVEAPIDEF set_epsint_func *_set_epsint; LPSOLVEAPIDEF set_epslevel_func *_set_epslevel; LPSOLVEAPIDEF set_epsperturb_func *_set_epsperturb; LPSOLVEAPIDEF set_epspivot_func *_set_epspivot; LPSOLVEAPIDEF set_unbounded_func *_set_unbounded; LPSOLVEAPIDEF set_improve_func *_set_improve; LPSOLVEAPIDEF set_infinite_func *_set_infinite; LPSOLVEAPIDEF set_int_func *_set_int; LPSOLVEAPIDEF set_lag_trace_func *_set_lag_trace; LPSOLVEAPIDEF set_lowbo_func *_set_lowbo; LPSOLVEAPIDEF set_lp_name_func *_set_lp_name; LPSOLVEAPIDEF set_mat_func *_set_mat; LPSOLVEAPIDEF set_maxim_func *_set_maxim; LPSOLVEAPIDEF set_maxpivot_func *_set_maxpivot; LPSOLVEAPIDEF set_minim_func *_set_minim; LPSOLVEAPIDEF set_mip_gap_func *_set_mip_gap; LPSOLVEAPIDEF set_multiprice_func *_set_multiprice; LPSOLVEAPIDEF set_negrange_func *_set_negrange; LPSOLVEAPIDEF set_obj_bound_func *_set_obj_bound; LPSOLVEAPIDEF set_obj_fn_func *_set_obj_fn; LPSOLVEAPIDEF set_obj_fnex_func *_set_obj_fnex; LPSOLVEAPIDEF set_obj_func *_set_obj; LPSOLVEAPIDEF set_outputfile_func *_set_outputfile; LPSOLVEAPIDEF set_outputstream_func *_set_outputstream; LPSOLVEAPIDEF set_partialprice_func *_set_partialprice; LPSOLVEAPIDEF set_pivoting_func *_set_pivoting; LPSOLVEAPIDEF set_preferdual_func *_set_preferdual; LPSOLVEAPIDEF set_presolve_func *_set_presolve; LPSOLVEAPIDEF set_print_sol_func *_set_print_sol; LPSOLVEAPIDEF set_pseudocosts_func *_set_pseudocosts; LPSOLVEAPIDEF set_rh_func *_set_rh; LPSOLVEAPIDEF set_rh_range_func *_set_rh_range; LPSOLVEAPIDEF set_rh_vec_func *_set_rh_vec; LPSOLVEAPIDEF set_row_func *_set_row; LPSOLVEAPIDEF set_rowex_func *_set_rowex; LPSOLVEAPIDEF set_row_name_func *_set_row_name; LPSOLVEAPIDEF set_scalelimit_func *_set_scalelimit; LPSOLVEAPIDEF set_scaling_func *_set_scaling; LPSOLVEAPIDEF set_semicont_func *_set_semicont; LPSOLVEAPIDEF set_sense_func *_set_sense; LPSOLVEAPIDEF set_simplextype_func *_set_simplextype; LPSOLVEAPIDEF set_solutionlimit_func *_set_solutionlimit; LPSOLVEAPIDEF set_timeout_func *_set_timeout; LPSOLVEAPIDEF set_trace_func *_set_trace; LPSOLVEAPIDEF set_upbo_func *_set_upbo; LPSOLVEAPIDEF set_var_branch_func *_set_var_branch; LPSOLVEAPIDEF set_var_weights_func *_set_var_weights; LPSOLVEAPIDEF set_verbose_func *_set_verbose; LPSOLVEAPIDEF set_XLI_func *_set_XLI; LPSOLVEAPIDEF solve_func *_solve; LPSOLVEAPIDEF str_add_column_func *_str_add_column; LPSOLVEAPIDEF str_add_constraint_func *_str_add_constraint; LPSOLVEAPIDEF str_add_lag_con_func *_str_add_lag_con; LPSOLVEAPIDEF str_set_obj_fn_func *_str_set_obj_fn; LPSOLVEAPIDEF str_set_rh_vec_func *_str_set_rh_vec; LPSOLVEAPIDEF time_elapsed_func *_time_elapsed; LPSOLVEAPIDEF unscale_func *_unscale; LPSOLVEAPIDEF write_lp_func *_write_lp; LPSOLVEAPIDEF write_LP_func *_write_LP; LPSOLVEAPIDEF write_mps_func *_write_mps; LPSOLVEAPIDEF write_MPS_func *_write_MPS; LPSOLVEAPIDEF write_freemps_func *_write_freemps; LPSOLVEAPIDEF write_freeMPS_func *_write_freeMPS; LPSOLVEAPIDEF write_XLI_func *_write_XLI; LPSOLVEAPIDEF write_basis_func *_write_basis; LPSOLVEAPIDEF write_params_func *_write_params; #if defined LPSOLVEAPIFROMLPREC static int init_lpsolve(lprec *lp) { _add_column = lp->add_column; _add_columnex = lp->add_columnex; _add_constraint = lp->add_constraint; _add_constraintex = lp->add_constraintex; _add_lag_con = lp->add_lag_con; _add_SOS = lp->add_SOS; _column_in_lp = lp->column_in_lp; _copy_lp = lp->copy_lp; _default_basis = lp->default_basis; _del_column = lp->del_column; _del_constraint = lp->del_constraint; _delete_lp = lp->delete_lp; _dualize_lp = lp->dualize_lp; _free_lp = lp->free_lp; _get_anti_degen = lp->get_anti_degen; _get_basis = lp->get_basis; _get_basiscrash = lp->get_basiscrash; _get_bb_depthlimit = lp->get_bb_depthlimit; _get_bb_floorfirst = lp->get_bb_floorfirst; _get_bb_rule = lp->get_bb_rule; _get_bounds_tighter = lp->get_bounds_tighter; _get_break_at_value = lp->get_break_at_value; _get_col_name = lp->get_col_name; _get_columnex = lp->get_columnex; _get_constr_type = lp->get_constr_type; _get_constr_value = lp->get_constr_value; _get_constraints = lp->get_constraints; _get_dual_solution = lp->get_dual_solution; _get_epsb = lp->get_epsb; _get_epsd = lp->get_epsd; _get_epsel = lp->get_epsel; _get_epsint = lp->get_epsint; _get_epsperturb = lp->get_epsperturb; _get_epspivot = lp->get_epspivot; _get_improve = lp->get_improve; _get_infinite = lp->get_infinite; _get_lambda = lp->get_lambda; _get_lowbo = lp->get_lowbo; _get_lp_index = lp->get_lp_index; _get_lp_name = lp->get_lp_name; _get_Lrows = lp->get_Lrows; _get_mat = lp->get_mat; _get_mat_byindex = lp->get_mat_byindex; _get_max_level = lp->get_max_level; _get_maxpivot = lp->get_maxpivot; _get_mip_gap = lp->get_mip_gap; _get_multiprice = lp->get_multiprice; _get_nameindex = lp->get_nameindex; _get_Ncolumns = lp->get_Ncolumns; _get_negrange = lp->get_negrange; _get_nonzeros = lp->get_nonzeros; _get_Norig_columns = lp->get_Norig_columns; _get_Norig_rows = lp->get_Norig_rows; _get_Nrows = lp->get_Nrows; _get_obj_bound = lp->get_obj_bound; _get_objective = lp->get_objective; _get_orig_index = lp->get_orig_index; _get_origcol_name = lp->get_origcol_name; _get_origrow_name = lp->get_origrow_name; _get_partialprice = lp->get_partialprice; _get_pivoting = lp->get_pivoting; _get_presolve = lp->get_presolve; _get_presolveloops = lp->get_presolveloops; _get_primal_solution = lp->get_primal_solution; _get_print_sol = lp->get_print_sol; _get_pseudocosts = lp->get_pseudocosts; _get_ptr_constraints = lp->get_ptr_constraints; _get_ptr_dual_solution = lp->get_ptr_dual_solution; _get_ptr_lambda = lp->get_ptr_lambda; _get_ptr_primal_solution = lp->get_ptr_primal_solution; _get_ptr_sensitivity_obj = lp->get_ptr_sensitivity_obj; _get_ptr_sensitivity_objex = lp->get_ptr_sensitivity_objex; _get_ptr_sensitivity_rhs = lp->get_ptr_sensitivity_rhs; _get_ptr_variables = lp->get_ptr_variables; _get_rh = lp->get_rh; _get_rh_range = lp->get_rh_range; _get_row = lp->get_row; _get_rowex = lp->get_rowex; _get_row_name = lp->get_row_name; _get_scalelimit = lp->get_scalelimit; _get_scaling = lp->get_scaling; _get_sensitivity_obj = lp->get_sensitivity_obj; _get_sensitivity_objex = lp->get_sensitivity_objex; _get_sensitivity_rhs = lp->get_sensitivity_rhs; _get_simplextype = lp->get_simplextype; _get_solutioncount = lp->get_solutioncount; _get_solutionlimit = lp->get_solutionlimit; _get_status = lp->get_status; _get_statustext = lp->get_statustext; _get_timeout = lp->get_timeout; _get_total_iter = lp->get_total_iter; _get_total_nodes = lp->get_total_nodes; _get_upbo = lp->get_upbo; _get_var_branch = lp->get_var_branch; _get_var_dualresult = lp->get_var_dualresult; _get_var_primalresult = lp->get_var_primalresult; _get_var_priority = lp->get_var_priority; _get_variables = lp->get_variables; _get_verbose = lp->get_verbose; _get_working_objective = lp->get_working_objective; _has_BFP = lp->has_BFP; _has_XLI = lp->has_XLI; _is_add_rowmode = lp->is_add_rowmode; _is_anti_degen = lp->is_anti_degen; _is_binary = lp->is_binary; _is_break_at_first = lp->is_break_at_first; _is_constr_type = lp->is_constr_type; _is_debug = lp->is_debug; _is_feasible = lp->is_feasible; _is_unbounded = lp->is_unbounded; _is_infinite = lp->is_infinite; _is_int = lp->is_int; _is_integerscaling = lp->is_integerscaling; _is_lag_trace = lp->is_lag_trace; _is_maxim = lp->is_maxim; _is_nativeBFP = lp->is_nativeBFP; _is_nativeXLI = lp->is_nativeXLI; _is_negative = lp->is_negative; _is_piv_mode = lp->is_piv_mode; _is_piv_rule = lp->is_piv_rule; _is_presolve = lp->is_presolve; _is_scalemode = lp->is_scalemode; _is_scaletype = lp->is_scaletype; _is_semicont = lp->is_semicont; _is_SOS_var = lp->is_SOS_var; _is_trace = lp->is_trace; _is_use_names = lp->is_use_names; _lp_solve_version = lp->lp_solve_version; _make_lp = lp->make_lp; _print_constraints = lp->print_constraints; _print_debugdump = lp->print_debugdump; _print_duals = lp->print_duals; _print_lp = lp->print_lp; _print_objective = lp->print_objective; _print_scales = lp->print_scales; _print_solution = lp->print_solution; _print_str = lp->print_str; _print_tableau = lp->print_tableau; _put_abortfunc = lp->put_abortfunc; _put_bb_nodefunc = lp->put_bb_nodefunc; _put_bb_branchfunc = lp->put_bb_branchfunc; _put_logfunc = lp->put_logfunc; _put_msgfunc = lp->put_msgfunc; _read_LP = lp->read_LP; _read_MPS = lp->read_MPS; _read_XLI = lp->read_XLI; _read_params = lp->read_params; _read_basis = lp->read_basis; _reset_basis = lp->reset_basis; _reset_params = lp->reset_params; _report = lp->report; _resize_lp = lp->resize_lp; _set_add_rowmode = lp->set_add_rowmode; _set_anti_degen = lp->set_anti_degen; _set_basisvar = lp->set_basisvar; _set_basis = lp->set_basis; _set_basiscrash = lp->set_basiscrash; _set_bb_depthlimit = lp->set_bb_depthlimit; _set_bb_floorfirst = lp->set_bb_floorfirst; _set_bb_rule = lp->set_bb_rule; _set_BFP = lp->set_BFP; _set_binary = lp->set_binary; _set_bounds = lp->set_bounds; _set_bounds_tighter = lp->set_bounds_tighter; _set_break_at_first = lp->set_break_at_first; _set_break_at_value = lp->set_break_at_value; _set_column = lp->set_column; _set_columnex = lp->set_columnex; _set_col_name = lp->set_col_name; _set_constr_type = lp->set_constr_type; _set_debug = lp->set_debug; _set_epsb = lp->set_epsb; _set_epsd = lp->set_epsd; _set_epsel = lp->set_epsel; _set_epsint = lp->set_epsint; _set_epslevel = lp->set_epslevel; _set_epsperturb = lp->set_epsperturb; _set_epspivot = lp->set_epspivot; _set_unbounded = lp->set_unbounded; _set_improve = lp->set_improve; _set_infinite = lp->set_infinite; _set_int = lp->set_int; _set_lag_trace = lp->set_lag_trace; _set_lowbo = lp->set_lowbo; _set_lp_name = lp->set_lp_name; _set_mat = lp->set_mat; _set_maxim = lp->set_maxim; _set_maxpivot = lp->set_maxpivot; _set_minim = lp->set_minim; _set_mip_gap = lp->set_mip_gap; _set_multiprice = lp->set_multiprice; _set_negrange = lp->set_negrange; _set_obj_bound = lp->set_obj_bound; _set_obj_fn = lp->set_obj_fn; _set_obj_fnex = lp->set_obj_fnex; _set_obj = lp->set_obj; _set_outputfile = lp->set_outputfile; _set_outputstream = lp->set_outputstream; _set_partialprice = lp->set_partialprice; _set_pivoting = lp->set_pivoting; _set_preferdual = lp->set_preferdual; _set_presolve = lp->set_presolve; _set_print_sol = lp->set_print_sol; _set_pseudocosts = lp->set_pseudocosts; _set_rh = lp->set_rh; _set_rh_range = lp->set_rh_range; _set_rh_vec = lp->set_rh_vec; _set_row = lp->set_row; _set_rowex = lp->set_rowex; _set_row_name = lp->set_row_name; _set_scalelimit = lp->set_scalelimit; _set_scaling = lp->set_scaling; _set_semicont = lp->set_semicont; _set_sense = lp->set_sense; _set_simplextype = lp->set_simplextype; _set_solutionlimit = lp->set_solutionlimit; _set_timeout = lp->set_timeout; _set_trace = lp->set_trace; _set_upbo = lp->set_upbo; _set_var_branch = lp->set_var_branch; _set_var_weights = lp->set_var_weights; _set_verbose = lp->set_verbose; _set_XLI = lp->set_XLI; _solve = lp->solve; _str_add_column = lp->str_add_column; _str_add_constraint = lp->str_add_constraint; _str_add_lag_con = lp->str_add_lag_con; _str_set_obj_fn = lp->str_set_obj_fn; _str_set_rh_vec = lp->str_set_rh_vec; _time_elapsed = lp->time_elapsed; _unscale = lp->unscale; _write_lp = lp->write_lp; _write_LP = lp->write_LP; _write_mps = lp->write_mps; _write_MPS = lp->write_MPS; _write_freemps = lp->write_freemps; _write_freeMPS = lp->write_freeMPS; _write_XLI = lp->write_XLI; _write_basis = lp->write_basis; _write_params = lp->write_params; return(TRUE); } #elif defined LPSOLVEAPIFROMLIB #ifdef WIN32 # include #else # include #endif #if defined WIN32 # define hlpsolve HINSTANCE #else # define hlpsolve void * #endif static hlpsolve open_lpsolve_lib(char *filename) { hlpsolve lpsolve; # if defined WIN32 /* Get a handle to the Windows DLL module. */ lpsolve = LoadLibrary("lpsolve55.dll"); # else lpsolve = dlopen("liblpsolve55.so", RTLD_LAZY);; # endif return(lpsolve); } static int close_lpsolve_lib(hlpsolve lpsolve) { #ifdef WIN32 FreeLibrary(lpsolve); #else dlclose(lpsolve); #endif return(TRUE); } static int init_lpsolve(hlpsolve lpsolve) { # if defined WIN32 # define AddressOf GetProcAddress # else # define AddressOf dlsym # endif /* assign API functions to lp structure */ _add_column = (add_column_func *) AddressOf(lpsolve, "add_column"); _add_columnex = (add_columnex_func *) AddressOf(lpsolve, "add_columnex"); _add_constraint = (add_constraint_func *) AddressOf(lpsolve, "add_constraint"); _add_constraintex = (add_constraintex_func *) AddressOf(lpsolve, "add_constraintex"); _add_lag_con = (add_lag_con_func *) AddressOf(lpsolve, "add_lag_con"); _add_SOS = (add_SOS_func *) AddressOf(lpsolve, "add_SOS"); _column_in_lp = (column_in_lp_func *) AddressOf(lpsolve, "column_in_lp"); _copy_lp = (copy_lp_func *) AddressOf(lpsolve, "copy_lp"); _default_basis = (default_basis_func *) AddressOf(lpsolve, "default_basis"); _del_column = (del_column_func *) AddressOf(lpsolve, "del_column"); _del_constraint = (del_constraint_func *) AddressOf(lpsolve, "del_constraint"); _delete_lp = (delete_lp_func *) AddressOf(lpsolve, "delete_lp"); _dualize_lp = (dualize_lp_func *) AddressOf(lpsolve, "dualize_lp"); _free_lp = (free_lp_func *) AddressOf(lpsolve, "free_lp"); _get_anti_degen = (get_anti_degen_func *) AddressOf(lpsolve, "get_anti_degen"); _get_basis = (get_basis_func *) AddressOf(lpsolve, "get_basis"); _get_basiscrash = (get_basiscrash_func *) AddressOf(lpsolve, "get_basiscrash"); _get_bb_depthlimit = (get_bb_depthlimit_func *) AddressOf(lpsolve, "get_bb_depthlimit"); _get_bb_floorfirst = (get_bb_floorfirst_func *) AddressOf(lpsolve, "get_bb_floorfirst"); _get_bb_rule = (get_bb_rule_func *) AddressOf(lpsolve, "get_bb_rule"); _get_bounds_tighter = (get_bounds_tighter_func *) AddressOf(lpsolve, "get_bounds_tighter"); _get_break_at_value = (get_break_at_value_func *) AddressOf(lpsolve, "get_break_at_value"); _get_col_name = (get_col_name_func *) AddressOf(lpsolve, "get_col_name"); _get_column = (get_column_func *) AddressOf(lpsolve, "get_column"); _get_columnex = (get_columnex_func *) AddressOf(lpsolve, "get_columnex"); _get_constr_type = (get_constr_type_func *) AddressOf(lpsolve, "get_constr_type"); _get_constr_value = (get_constr_value_func *) AddressOf(lpsolve, "get_constr_value"); _get_constraints = (get_constraints_func *) AddressOf(lpsolve, "get_constraints"); _get_dual_solution = (get_dual_solution_func *) AddressOf(lpsolve, "get_dual_solution"); _get_epsb = (get_epsb_func *) AddressOf(lpsolve, "get_epsb"); _get_epsd = (get_epsd_func *) AddressOf(lpsolve, "get_epsd"); _get_epsel = (get_epsel_func *) AddressOf(lpsolve, "get_epsel"); _get_epsint = (get_epsint_func *) AddressOf(lpsolve, "get_epsint"); _get_epsperturb = (get_epsperturb_func *) AddressOf(lpsolve, "get_epsperturb"); _get_epspivot = (get_epspivot_func *) AddressOf(lpsolve, "get_epspivot"); _get_improve = (get_improve_func *) AddressOf(lpsolve, "get_improve"); _get_infinite = (get_infinite_func *) AddressOf(lpsolve, "get_infinite"); _get_lambda = (get_lambda_func *) AddressOf(lpsolve, "get_lambda"); _get_lowbo = (get_lowbo_func *) AddressOf(lpsolve, "get_lowbo"); _get_lp_index = (get_lp_index_func *) AddressOf(lpsolve, "get_lp_index"); _get_lp_name = (get_lp_name_func *) AddressOf(lpsolve, "get_lp_name"); _get_Lrows = (get_Lrows_func *) AddressOf(lpsolve, "get_Lrows"); _get_mat = (get_mat_func *) AddressOf(lpsolve, "get_mat"); _get_mat_byindex = (get_mat_byindex_func *) AddressOf(lpsolve, "get_mat_byindex"); _get_max_level = (get_max_level_func *) AddressOf(lpsolve, "get_max_level"); _get_maxpivot = (get_maxpivot_func *) AddressOf(lpsolve, "get_maxpivot"); _get_mip_gap = (get_mip_gap_func *) AddressOf(lpsolve, "get_mip_gap"); _get_multiprice = (get_multiprice_func *) AddressOf(lpsolve, "get_multiprice"); _get_nameindex = (get_nameindex_func *) AddressOf(lpsolve, "get_nameindex"); _get_Ncolumns = (get_Ncolumns_func *) AddressOf(lpsolve, "get_Ncolumns"); _get_negrange = (get_negrange_func *) AddressOf(lpsolve, "get_negrange"); _get_nonzeros = (get_nz_func *) AddressOf(lpsolve, "get_nonzeros"); _get_Norig_columns = (get_Norig_columns_func *) AddressOf(lpsolve, "get_Norig_columns"); _get_Norig_rows = (get_Norig_rows_func *) AddressOf(lpsolve, "get_Norig_rows"); _get_Nrows = (get_Nrows_func *) AddressOf(lpsolve, "get_Nrows"); _get_obj_bound = (get_obj_bound_func *) AddressOf(lpsolve, "get_obj_bound"); _get_objective = (get_objective_func *) AddressOf(lpsolve, "get_objective"); _get_orig_index = (get_orig_index_func *) AddressOf(lpsolve, "get_orig_index"); _get_origcol_name = (get_origcol_name_func *) AddressOf(lpsolve, "get_origcol_name"); _get_origrow_name = (get_origrow_name_func *) AddressOf(lpsolve, "get_origrow_name"); _get_partialprice = (get_partialprice_func *) AddressOf(lpsolve, "get_partialprice"); _get_pivoting = (get_pivoting_func *) AddressOf(lpsolve, "get_pivoting"); _get_presolve = (get_presolve_func *) AddressOf(lpsolve, "get_presolve"); _get_presolveloops = (get_presolveloops_func *) AddressOf(lpsolve, "get_presolveloops"); _get_primal_solution = (get_primal_solution_func *) AddressOf(lpsolve, "get_primal_solution"); _get_print_sol = (get_print_sol_func *) AddressOf(lpsolve, "get_print_sol"); _get_pseudocosts = (get_pseudocosts_func *) AddressOf(lpsolve, "get_pseudocosts"); _get_ptr_constraints = (get_ptr_constraints_func *) AddressOf(lpsolve, "get_ptr_constraints"); _get_ptr_dual_solution = (get_ptr_dual_solution_func *) AddressOf(lpsolve, "get_ptr_dual_solution"); _get_ptr_lambda = (get_ptr_lambda_func *) AddressOf(lpsolve, "get_ptr_lambda"); _get_ptr_primal_solution = (get_ptr_primal_solution_func *) AddressOf(lpsolve, "get_ptr_primal_solution"); _get_ptr_sensitivity_obj = (get_ptr_sensitivity_obj_func *) AddressOf(lpsolve, "get_ptr_sensitivity_obj"); _get_ptr_sensitivity_objex = (get_ptr_sensitivity_objex_func *) AddressOf(lpsolve, "get_ptr_sensitivity_objex"); _get_ptr_sensitivity_rhs = (get_ptr_sensitivity_rhs_func *) AddressOf(lpsolve, "get_ptr_sensitivity_rhs"); _get_ptr_variables = (get_ptr_variables_func *) AddressOf(lpsolve, "get_ptr_variables"); _get_rh = (get_rh_func *) AddressOf(lpsolve, "get_rh"); _get_rh_range = (get_rh_range_func *) AddressOf(lpsolve, "get_rh_range"); _get_row = (get_row_func *) AddressOf(lpsolve, "get_row"); _get_rowex = (get_rowex_func *) AddressOf(lpsolve, "get_rowex"); _get_row_name = (get_row_name_func *) AddressOf(lpsolve, "get_row_name"); _get_scalelimit = (get_scalelimit_func *) AddressOf(lpsolve, "get_scalelimit"); _get_scaling = (get_scaling_func *) AddressOf(lpsolve, "get_scaling"); _get_sensitivity_obj = (get_sensitivity_obj_func *) AddressOf(lpsolve, "get_sensitivity_obj"); _get_sensitivity_objex = (get_sensitivity_objex_func *) AddressOf(lpsolve, "get_sensitivity_objex"); _get_sensitivity_rhs = (get_sensitivity_rhs_func *) AddressOf(lpsolve, "get_sensitivity_rhs"); _get_simplextype = (get_simplextype_func *) AddressOf(lpsolve, "get_simplextype"); _get_solutioncount = (get_solutioncount_func *) AddressOf(lpsolve, "get_solutioncount"); _get_solutionlimit = (get_solutionlimit_func *) AddressOf(lpsolve, "get_solutionlimit"); _get_status = (get_status_func *) AddressOf(lpsolve, "get_status"); _get_statustext = (get_statustext_func *) AddressOf(lpsolve, "get_statustext"); _get_timeout = (get_timeout_func *) AddressOf(lpsolve, "get_timeout"); _get_total_iter = (get_total_iter_func *) AddressOf(lpsolve, "get_total_iter"); _get_total_nodes = (get_total_nodes_func *) AddressOf(lpsolve, "get_total_nodes"); _get_upbo = (get_upbo_func *) AddressOf(lpsolve, "get_upbo"); _get_var_branch = (get_var_branch_func *) AddressOf(lpsolve, "get_var_branch"); _get_var_dualresult = (get_var_dualresult_func *) AddressOf(lpsolve, "get_var_dualresult"); _get_var_primalresult = (get_var_primalresult_func *) AddressOf(lpsolve, "get_var_primalresult"); _get_var_priority = (get_var_priority_func *) AddressOf(lpsolve, "get_var_priority"); _get_variables = (get_variables_func *) AddressOf(lpsolve, "get_variables"); _get_verbose = (get_verbose_func *) AddressOf(lpsolve, "get_verbose"); _get_working_objective = (get_working_objective_func *) AddressOf(lpsolve, "get_working_objective"); _guess_basis = (guess_basis_func *) AddressOf(lpsolve, "guess_basis"); _has_BFP = (has_BFP_func *) AddressOf(lpsolve, "has_BFP"); _has_XLI = (has_XLI_func *) AddressOf(lpsolve, "has_XLI"); _is_add_rowmode = (is_add_rowmode_func *) AddressOf(lpsolve, "is_add_rowmode"); _is_anti_degen = (is_anti_degen_func *) AddressOf(lpsolve, "is_anti_degen"); _is_binary = (is_binary_func *) AddressOf(lpsolve, "is_binary"); _is_break_at_first = (is_break_at_first_func *) AddressOf(lpsolve, "is_break_at_first"); _is_constr_type = (is_constr_type_func *) AddressOf(lpsolve, "is_constr_type"); _is_debug = (is_debug_func *) AddressOf(lpsolve, "is_debug"); _is_feasible = (is_feasible_func *) AddressOf(lpsolve, "is_feasible"); _is_unbounded = (is_unbounded_func *) AddressOf(lpsolve, "is_unbounded"); _is_infinite = (is_infinite_func *) AddressOf(lpsolve, "is_infinite"); _is_int = (is_int_func *) AddressOf(lpsolve, "is_int"); _is_integerscaling = (is_integerscaling_func *) AddressOf(lpsolve, "is_integerscaling"); _is_lag_trace = (is_lag_trace_func *) AddressOf(lpsolve, "is_lag_trace"); _is_maxim = (is_maxim_func *) AddressOf(lpsolve, "is_maxim"); _is_nativeBFP = (is_nativeBFP_func *) AddressOf(lpsolve, "is_nativeBFP"); _is_nativeXLI = (is_nativeXLI_func *) AddressOf(lpsolve, "is_nativeXLI"); _is_negative = (is_negative_func *) AddressOf(lpsolve, "is_negative"); _is_piv_mode = (is_piv_mode_func *) AddressOf(lpsolve, "is_piv_mode"); _is_piv_rule = (is_piv_rule_func *) AddressOf(lpsolve, "is_piv_rule"); _is_presolve = (is_presolve_func *) AddressOf(lpsolve, "is_presolve"); _is_scalemode = (is_scalemode_func *) AddressOf(lpsolve, "is_scalemode"); _is_scaletype = (is_scaletype_func *) AddressOf(lpsolve, "is_scaletype"); _is_semicont = (is_semicont_func *) AddressOf(lpsolve, "is_semicont"); _is_SOS_var = (is_SOS_var_func *) AddressOf(lpsolve, "is_SOS_var"); _is_trace = (is_trace_func *) AddressOf(lpsolve, "is_trace"); _is_use_names = (is_use_names_func *) AddressOf(lpsolve, "is_use_names"); _lp_solve_version = (lp_solve_version_func *) AddressOf(lpsolve, "lp_solve_version"); _make_lp = (make_lp_func *) AddressOf(lpsolve, "make_lp"); _print_constraints = (print_constraints_func *) AddressOf(lpsolve, "print_constraints"); _print_debugdump = (print_debugdump_func *) AddressOf(lpsolve, "print_debugdump"); _print_duals = (print_duals_func *) AddressOf(lpsolve, "print_duals"); _print_lp = (print_lp_func *) AddressOf(lpsolve, "print_lp"); _print_objective = (print_objective_func *) AddressOf(lpsolve, "print_objective"); _print_scales = (print_scales_func *) AddressOf(lpsolve, "print_scales"); _print_solution = (print_solution_func *) AddressOf(lpsolve, "print_solution"); _print_str = (print_str_func *) AddressOf(lpsolve, "print_str"); _print_tableau = (print_tableau_func *) AddressOf(lpsolve, "print_tableau"); _put_abortfunc = (put_abortfunc_func *) AddressOf(lpsolve, "put_abortfunc"); _put_bb_nodefunc = (put_bb_nodefunc_func *) AddressOf(lpsolve, "put_bb_nodefunc"); _put_bb_branchfunc = (put_bb_branchfunc_func *) AddressOf(lpsolve, "put_bb_branchfunc"); _put_logfunc = (put_logfunc_func *) AddressOf(lpsolve, "put_logfunc"); _put_msgfunc = (put_msgfunc_func *) AddressOf(lpsolve, "put_msgfunc"); _read_LP = (read_LP_func *) AddressOf(lpsolve, "read_LP"); _read_MPS = (read_MPS_func *) AddressOf(lpsolve, "read_MPS"); _read_XLI = (read_XLI_func *) AddressOf(lpsolve, "read_XLI"); _read_params = (read_params_func *) AddressOf(lpsolve, "read_params"); _read_basis = (read_basis_func *) AddressOf(lpsolve, "read_basis"); _reset_basis = (reset_basis_func *) AddressOf(lpsolve, "reset_basis"); _reset_params = (reset_params_func *) AddressOf(lpsolve, "reset_params"); _report = (reportfunc *) AddressOf(lpsolve, "report"); _resize_lp = (resize_lp_func *) AddressOf(lpsolve, "resize_lp"); _set_add_rowmode = (set_add_rowmode_func *) AddressOf(lpsolve, "set_add_rowmode"); _set_anti_degen = (set_anti_degen_func *) AddressOf(lpsolve, "set_anti_degen"); _set_basisvar = (set_basisvar_func *) AddressOf(lpsolve, "set_basisvar"); _set_basis = (set_basis_func *) AddressOf(lpsolve, "set_basis"); _set_basiscrash = (set_basiscrash_func *) AddressOf(lpsolve, "set_basiscrash"); _set_bb_depthlimit = (set_bb_depthlimit_func *) AddressOf(lpsolve, "set_bb_depthlimit"); _set_bb_floorfirst = (set_bb_floorfirst_func *) AddressOf(lpsolve, "set_bb_floorfirst"); _set_bb_rule = (set_bb_rule_func *) AddressOf(lpsolve, "set_bb_rule"); _set_BFP = (set_BFP_func *) AddressOf(lpsolve, "set_BFP"); _set_binary = (set_binary_func *) AddressOf(lpsolve, "set_binary"); _set_bounds = (set_bounds_func *) AddressOf(lpsolve, "set_bounds"); _set_bounds_tighter = (set_bounds_tighter_func *) AddressOf(lpsolve, "set_bounds_tighter"); _set_break_at_first = (set_break_at_first_func *) AddressOf(lpsolve, "set_break_at_first"); _set_break_at_value = (set_break_at_value_func *) AddressOf(lpsolve, "set_break_at_value"); _set_column = (set_column_func *) AddressOf(lpsolve, "set_column"); _set_columnex = (set_columnex_func *) AddressOf(lpsolve, "set_columnex"); _set_col_name = (set_col_name_func *) AddressOf(lpsolve, "set_col_name"); _set_constr_type = (set_constr_type_func *) AddressOf(lpsolve, "set_constr_type"); _set_debug = (set_debug_func *) AddressOf(lpsolve, "set_debug"); _set_epsb = (set_epsb_func *) AddressOf(lpsolve, "set_epsb"); _set_epsd = (set_epsd_func *) AddressOf(lpsolve, "set_epsd"); _set_epsel = (set_epsel_func *) AddressOf(lpsolve, "set_epsel"); _set_epsint = (set_epsint_func *) AddressOf(lpsolve, "set_epsint"); _set_epslevel = (set_epslevel_func *) AddressOf(lpsolve, "set_epslevel"); _set_epsperturb = (set_epsperturb_func *) AddressOf(lpsolve, "set_epsperturb"); _set_epspivot = (set_epspivot_func *) AddressOf(lpsolve, "set_epspivot"); _set_unbounded = (set_unbounded_func *) AddressOf(lpsolve, "set_unbounded"); _set_improve = (set_improve_func *) AddressOf(lpsolve, "set_improve"); _set_infinite = (set_infinite_func *) AddressOf(lpsolve, "set_infinite"); _set_int = (set_int_func *) AddressOf(lpsolve, "set_int"); _set_lag_trace = (set_lag_trace_func *) AddressOf(lpsolve, "set_lag_trace"); _set_lowbo = (set_lowbo_func *) AddressOf(lpsolve, "set_lowbo"); _set_lp_name = (set_lp_name_func *) AddressOf(lpsolve, "set_lp_name"); _set_mat = (set_mat_func *) AddressOf(lpsolve, "set_mat"); _set_maxim = (set_maxim_func *) AddressOf(lpsolve, "set_maxim"); _set_maxpivot = (set_maxpivot_func *) AddressOf(lpsolve, "set_maxpivot"); _set_minim = (set_minim_func *) AddressOf(lpsolve, "set_minim"); _set_mip_gap = (set_mip_gap_func *) AddressOf(lpsolve, "set_mip_gap"); _set_multiprice = (set_multiprice_func *) AddressOf(lpsolve, "set_multiprice"); _set_negrange = (set_negrange_func *) AddressOf(lpsolve, "set_negrange"); _set_obj_bound = (set_obj_bound_func *) AddressOf(lpsolve, "set_obj_bound"); _set_obj_fn = (set_obj_fn_func *) AddressOf(lpsolve, "set_obj_fn"); _set_obj_fnex = (set_obj_fnex_func *) AddressOf(lpsolve, "set_obj_fnex"); _set_obj = (set_obj_func *) AddressOf(lpsolve, "set_obj"); _set_outputfile = (set_outputfile_func *) AddressOf(lpsolve, "set_outputfile"); _set_outputstream = (set_outputstream_func *) AddressOf(lpsolve, "set_outputstream"); _set_partialprice = (set_partialprice_func *) AddressOf(lpsolve, "set_partialprice"); _set_pivoting = (set_pivoting_func *) AddressOf(lpsolve, "set_pivoting"); _set_preferdual = (set_preferdual_func *) AddressOf(lpsolve, "set_preferdual"); _set_presolve = (set_presolve_func *) AddressOf(lpsolve, "set_presolve"); _set_print_sol = (set_print_sol_func *) AddressOf(lpsolve, "set_print_sol"); _set_pseudocosts = (set_pseudocosts_func *) AddressOf(lpsolve, "set_pseudocosts"); _set_rh = (set_rh_func *) AddressOf(lpsolve, "set_rh"); _set_rh_range = (set_rh_range_func *) AddressOf(lpsolve, "set_rh_range"); _set_rh_vec = (set_rh_vec_func *) AddressOf(lpsolve, "set_rh_vec"); _set_row = (set_row_func *) AddressOf(lpsolve, "set_row"); _set_rowex = (set_rowex_func *) AddressOf(lpsolve, "set_rowex"); _set_row_name = (set_row_name_func *) AddressOf(lpsolve, "set_row_name"); _set_scalelimit = (set_scalelimit_func *) AddressOf(lpsolve, "set_scalelimit"); _set_scaling = (set_scaling_func *) AddressOf(lpsolve, "set_scaling"); _set_semicont = (set_semicont_func *) AddressOf(lpsolve, "set_semicont"); _set_sense = (set_sense_func *) AddressOf(lpsolve, "set_sense"); _set_simplextype = (set_simplextype_func *) AddressOf(lpsolve, "set_simplextype"); _set_solutionlimit = (set_solutionlimit_func *) AddressOf(lpsolve, "set_solutionlimit"); _set_timeout = (set_timeout_func *) AddressOf(lpsolve, "set_timeout"); _set_trace = (set_trace_func *) AddressOf(lpsolve, "set_trace"); _set_upbo = (set_upbo_func *) AddressOf(lpsolve, "set_upbo"); _set_var_branch = (set_var_branch_func *) AddressOf(lpsolve, "set_var_branch"); _set_var_weights = (set_var_weights_func *) AddressOf(lpsolve, "set_var_weights"); _set_verbose = (set_verbose_func *) AddressOf(lpsolve, "set_verbose"); _set_XLI = (set_XLI_func *) AddressOf(lpsolve, "set_XLI"); _solve = (solve_func *) AddressOf(lpsolve, "solve"); _str_add_column = (str_add_column_func *) AddressOf(lpsolve, "str_add_column"); _str_add_constraint = (str_add_constraint_func *) AddressOf(lpsolve, "str_add_constraint"); _str_add_lag_con = (str_add_lag_con_func *) AddressOf(lpsolve, "str_add_lag_con"); _str_set_obj_fn = (str_set_obj_fn_func *) AddressOf(lpsolve, "str_set_obj_fn"); _str_set_rh_vec = (str_set_rh_vec_func *) AddressOf(lpsolve, "str_set_rh_vec"); _time_elapsed = (time_elapsed_func *) AddressOf(lpsolve, "time_elapsed"); _unscale = (unscale_func *) AddressOf(lpsolve, "unscale"); _write_lp = (write_lp_func *) AddressOf(lpsolve, "write_lp"); _write_LP = (write_LP_func *) AddressOf(lpsolve, "write_LP"); _write_mps = (write_mps_func *) AddressOf(lpsolve, "write_mps"); _write_MPS = (write_MPS_func *) AddressOf(lpsolve, "write_MPS"); _write_freemps = (write_freemps_func *) AddressOf(lpsolve, "write_freemps"); _write_freeMPS = (write_freeMPS_func *) AddressOf(lpsolve, "write_freeMPS"); _write_XLI = (write_XLI_func *) AddressOf(lpsolve, "write_XLI"); _write_basis = (write_basis_func *) AddressOf(lpsolve, "write_basis"); _write_params = (write_params_func *) AddressOf(lpsolve, "write_params"); return(TRUE); # undef AddressOf } #else # error Either LPSOLVEAPIFROMLPREC or LPSOLVEAPIFROMLIB must be defined #endif #define add_column _add_column #define add_columnex _add_columnex #define add_constraint _add_constraint #define add_constraintex _add_constraintex #define add_lag_con _add_lag_con #define add_SOS _add_SOS #define column_in_lp _column_in_lp #define copy_lp _copy_lp #define default_basis _default_basis #define del_column _del_column #define del_constraint _del_constraint #define delete_lp _delete_lp #define dualize_lp _dualize_lp #define free_lp _free_lp #define get_anti_degen _get_anti_degen #define get_basis _get_basis #define get_basiscrash _get_basiscrash #define get_bb_depthlimit _get_bb_depthlimit #define get_bb_floorfirst _get_bb_floorfirst #define get_bb_rule _get_bb_rule #define get_bounds_tighter _get_bounds_tighter #define get_break_at_value _get_break_at_value #define get_col_name _get_col_name #define get_column _get_column #define get_columnex _get_columnex #define get_constr_type _get_constr_type #define get_constr_value _get_constr_value #define get_constraints _get_constraints #define get_dual_solution _get_dual_solution #define get_epsb _get_epsb #define get_epsd _get_epsd #define get_epsel _get_epsel #define get_epsint _get_epsint #define get_epsperturb _get_epsperturb #define get_epspivot _get_epspivot #define get_improve _get_improve #define get_infinite _get_infinite #define get_lambda _get_lambda #define get_lowbo _get_lowbo #define get_lp_index _get_lp_index #define get_lp_name _get_lp_name #define get_Lrows _get_Lrows #define get_mat _get_mat #define get_mat_byindex _get_mat_byindex #define get_max_level _get_max_level #define get_maxpivot _get_maxpivot #define get_mip_gap _get_mip_gap #define get_multiprice _get_multiprice #define get_nameindex _get_nameindex #define get_Ncolumns _get_Ncolumns #define get_negrange _get_negrange #define get_nonzeros _get_nonzeros #define get_Norig_columns _get_Norig_columns #define get_Norig_rows _get_Norig_rows #define get_Nrows _get_Nrows #define get_obj_bound _get_obj_bound #define get_objective _get_objective #define get_orig_index _get_orig_index #define get_origcol_name _get_origcol_name #define get_origrow_name _get_origrow_name #define get_partialprice _get_partialprice #define get_pivoting _get_pivoting #define get_presolve _get_presolve #define get_presolveloops _get_presolveloops #define get_primal_solution _get_primal_solution #define get_print_sol _get_print_sol #define get_pseudocosts _get_pseudocosts #define get_ptr_constraints _get_ptr_constraints #define get_ptr_dual_solution _get_ptr_dual_solution #define get_ptr_lambda _get_ptr_lambda #define get_ptr_primal_solution _get_ptr_primal_solution #define get_ptr_sensitivity_obj _get_ptr_sensitivity_obj #define get_ptr_sensitivity_objex _get_ptr_sensitivity_objex #define get_ptr_sensitivity_rhs _get_ptr_sensitivity_rhs #define get_ptr_variables _get_ptr_variables #define get_rh _get_rh #define get_rh_range _get_rh_range #define get_row _get_row #define get_rowex _get_rowex #define get_row_name _get_row_name #define get_scalelimit _get_scalelimit #define get_scaling _get_scaling #define get_sensitivity_obj _get_sensitivity_obj #define get_sensitivity_objex _get_sensitivity_objex #define get_sensitivity_rhs _get_sensitivity_rhs #define get_simplextype _get_simplextype #define get_solutioncount _get_solutioncount #define get_solutionlimit _get_solutionlimit #define get_status _get_status #define get_statustext _get_statustext #define get_timeout _get_timeout #define get_total_iter _get_total_iter #define get_total_nodes _get_total_nodes #define get_upbo _get_upbo #define get_var_branch _get_var_branch #define get_var_dualresult _get_var_dualresult #define get_var_primalresult _get_var_primalresult #define get_var_priority _get_var_priority #define get_variables _get_variables #define get_verbose _get_verbose #define get_working_objective _get_working_objective #define guess_basis _guess_basis #define has_BFP _has_BFP #define has_XLI _has_XLI #define is_add_rowmode _is_add_rowmode #define is_anti_degen _is_anti_degen #define is_binary _is_binary #define is_break_at_first _is_break_at_first #define is_constr_type _is_constr_type #define is_debug _is_debug #define is_feasible _is_feasible #define is_unbounded _is_unbounded #define is_infinite _is_infinite #define is_int _is_int #define is_integerscaling _is_integerscaling #define is_lag_trace _is_lag_trace #define is_maxim _is_maxim #define is_nativeBFP _is_nativeBFP #define is_nativeXLI _is_nativeXLI #define is_negative _is_negative #define is_piv_mode _is_piv_mode #define is_piv_rule _is_piv_rule #define is_presolve _is_presolve #define is_scalemode _is_scalemode #define is_scaletype _is_scaletype #define is_semicont _is_semicont #define is_SOS_var _is_SOS_var #define is_trace _is_trace #define is_use_names _is_use_names #define lp_solve_version _lp_solve_version #define make_lp _make_lp #define print_constraints _print_constraints #define print_debugdump _print_debugdump #define print_duals _print_duals #define print_lp _print_lp #define print_objective _print_objective #define print_scales _print_scales #define print_solution _print_solution #define print_str _print_str #define print_tableau _print_tableau #define put_abortfunc _put_abortfunc #define put_bb_nodefunc _put_bb_nodefunc #define put_bb_branchfunc _put_bb_branchfunc #define put_logfunc _put_logfunc #define put_msgfunc _put_msgfunc #define read_LP _read_LP #define read_MPS _read_MPS #define read_XLI _read_XLI #define read_params _read_params #define read_basis _read_basis #define reset_basis _reset_basis #define reset_params _reset_params #define report _report #define resize_lp _resize_lp #define set_add_rowmode _set_add_rowmode #define set_anti_degen _set_anti_degen #define set_basisvar _set_basisvar #define set_basis _set_basis #define set_basiscrash _set_basiscrash #define set_bb_depthlimit _set_bb_depthlimit #define set_bb_floorfirst _set_bb_floorfirst #define set_bb_rule _set_bb_rule #define set_BFP _set_BFP #define set_binary _set_binary #define set_bounds _set_bounds #define set_bounds_tighter _set_bounds_tighter #define set_break_at_first _set_break_at_first #define set_break_at_value _set_break_at_value #define set_column _set_column #define set_columnex _set_columnex #define set_col_name _set_col_name #define set_constr_type _set_constr_type #define set_debug _set_debug #define set_epsb _set_epsb #define set_epsd _set_epsd #define set_epsel _set_epsel #define set_epsint _set_epsint #define set_epslevel _set_epslevel #define set_epsperturb _set_epsperturb #define set_epspivot _set_epspivot #define set_unbounded _set_unbounded #define set_improve _set_improve #define set_infinite _set_infinite #define set_int _set_int #define set_lag_trace _set_lag_trace #define set_lowbo _set_lowbo #define set_lp_name _set_lp_name #define set_mat _set_mat #define set_maxim _set_maxim #define set_maxpivot _set_maxpivot #define set_minim _set_minim #define set_mip_gap _set_mip_gap #define set_multiprice _set_multiprice #define set_negrange _set_negrange #define set_obj_bound _set_obj_bound #define set_obj_fn _set_obj_fn #define set_obj_fnex _set_obj_fnex #define set_obj _set_obj #define set_outputfile _set_outputfile #define set_outputstream _set_outputstream #define set_partialprice _set_partialprice #define set_pivoting _set_pivoting #define set_preferdual _set_preferdual #define set_presolve _set_presolve #define set_print_sol _set_print_sol #define set_pseudocosts _set_pseudocosts #define set_rh _set_rh #define set_rh_range _set_rh_range #define set_rh_vec _set_rh_vec #define set_row _set_row #define set_rowex _set_rowex #define set_row_name _set_row_name #define set_scalelimit _set_scalelimit #define set_scaling _set_scaling #define set_semicont _set_semicont #define set_sense _set_sense #define set_simplextype _set_simplextype #define set_solutionlimit _set_solutionlimit #define set_timeout _set_timeout #define set_trace _set_trace #define set_upbo _set_upbo #define set_var_branch _set_var_branch #define set_var_weights _set_var_weights #define set_verbose _set_verbose #define set_XLI _set_XLI #define solve _solve #define str_add_column _str_add_column #define str_add_constraint _str_add_constraint #define str_add_lag_con _str_add_lag_con #define str_set_obj_fn _str_set_obj_fn #define str_set_rh_vec _str_set_rh_vec #define time_elapsed _time_elapsed #define unscale _unscale #define write_lp _write_lp #define write_LP _write_LP #define write_mps _write_mps #define write_MPS _write_MPS #define write_freemps _write_freemps #define write_freeMPS _write_freeMPS #define write_XLI _write_XLI #define write_basis _write_basis #define write_params _write_params MSVMpack1.2/lp_solve_5.5/declare.h0000664000175000017500000000060511141443440015703 0ustar lauerlauer#ifndef __DECLARE_H__ #define __DECLARE_H__ #if !defined ANSI_PROTOTYPES # if defined MSDOS || defined __BORLANDC__ || defined __HIGHC__ || defined SCO_UNIX || defined AViiON # define ANSI_PROTOTYPES 1 # endif #endif #if ANSI_PROTOTYPES!=0 # define __OF(args) args #else # define __OF(args) () #endif #if defined __HIGHC__ # define VARARG ... #else # define VARARG #endif #endif MSVMpack1.2/lp_solve_5.5/lp_bit.h0000664000175000017500000000071111245562131015557 0ustar lauerlauer#include "lp_types.h" #if defined INLINE # define MYINLINE INLINE #else # define MYINLINE static #endif MYINLINE void set_biton(MYBOOL *bitarray, int item) { bitarray[item / 8] |= (1 << (item % 8)); } MYINLINE void set_bitoff(MYBOOL *bitarray, int item) { bitarray[item / 8] &= ~(1 << (item % 8)); } MYINLINE MYBOOL is_biton(MYBOOL *bitarray, int item) { return( (MYBOOL) ((bitarray[item / 8] & (1 << (item % 8))) != 0) ); } MSVMpack1.2/lp_solve_5.5/lp_scale.c0000664000175000017500000007127211245564033016100 0ustar lauerlauer #include #include "commonlib.h" #include "lp_lib.h" #include "lp_report.h" #include "lp_scale.h" #ifdef FORTIFY # include "lp_fortify.h" #endif /* Scaling routines for lp_solve v5.0+ ---------------------------------------------------------------------------------- Author: Kjell Eikland Contact: kjell.eikland@broadpark.no License terms: LGPL. Requires: lp_lib.h, lp_scale.h Release notes: v5.0.0 1 January 2004 Significantly expanded and repackaged scaling routines. v5.0.1 20 February 2004 Modified rounding behaviour in several areas. v5.1.0 20 July 2004 Reworked with flexible matrix storage model. v5.2.0 20 February 2005 Converted to matrix storage model without the OF. ---------------------------------------------------------------------------------- */ /* First define scaling and unscaling primitives */ REAL scaled_value(lprec *lp, REAL value, int index) { if(fabs(value) < lp->infinite) { if(lp->scaling_used) { if(index > lp->rows) value /= lp->scalars[index]; else value *= lp->scalars[index]; } } else value = my_sign(value)*lp->infinite; return(value); } REAL unscaled_value(lprec *lp, REAL value, int index) { if(fabs(value) < lp->infinite) { if(lp->scaling_used) { if(index > lp->rows) value *= lp->scalars[index]; else value /= lp->scalars[index]; } } else value = my_sign(value)*lp->infinite; return(value); } STATIC REAL scaled_mat(lprec *lp, REAL value, int rownr, int colnr) { if(lp->scaling_used) value *= lp->scalars[rownr] * lp->scalars[lp->rows + colnr]; return( value ); } STATIC REAL unscaled_mat(lprec *lp, REAL value, int rownr, int colnr) { if(lp->scaling_used) value /= lp->scalars[rownr] * lp->scalars[lp->rows + colnr]; return( value ); } /* Compute the scale factor by the formulae: FALSE: SUM (log |Aij|) ^ 2 TRUE: SUM (log |Aij| - RowScale[i] - ColScale[j]) ^ 2 */ REAL CurtisReidMeasure(lprec *lp, MYBOOL _Advanced, REAL *FRowScale, REAL *FColScale) { int i, nz; REAL absvalue, logvalue; register REAL result; MATrec *mat = lp->matA; REAL *value; int *rownr, *colnr; /* Do OF part */ result = 0; for(i = 1; i <= lp->columns; i++) { absvalue = fabs(lp->orig_obj[i]); if(absvalue > 0) { logvalue = log(absvalue); if(_Advanced) logvalue -= FRowScale[0] + FColScale[i]; result += logvalue*logvalue; } } /* Do constraint matrix part */ mat_validate(mat); value = &(COL_MAT_VALUE(0)); rownr = &(COL_MAT_ROWNR(0)); colnr = &(COL_MAT_COLNR(0)); nz = get_nonzeros(lp); for(i = 0; i < nz; i++, value += matValueStep, rownr += matRowColStep, colnr += matRowColStep) { absvalue = fabs(*value); if(absvalue > 0) { logvalue = log(absvalue); if(_Advanced) logvalue -= FRowScale[*rownr] + FColScale[*colnr]; result += logvalue*logvalue; } } return( result ); } /* Implementation of the Curtis-Reid scaling based on the paper "On the Automatic Scaling of Matrices for Gaussian Elimination," Journal of the Institute of Mathematics and Its Applications (1972) 10, 118-124. Solve the system | M E | (r) (sigma) | | ( ) = ( ) | E^T N | (c) ( tau ) by the conjugate gradient method (clever recurrences). E is the matrix A with all elements = 1 M is diagonal matrix of row counts (RowCount) N is diagonal matrix of column counts (ColCount) sigma is the vector of row logarithm sums (RowSum) tau is the vector of column logarithm sums (ColSum) r, c are resulting row and column scalings (RowScale, ColScale) */ int CurtisReidScales(lprec *lp, MYBOOL _Advanced, REAL *FRowScale, REAL *FColScale) { int i, row, col, ent, nz; REAL *RowScalem2, *ColScalem2, *RowSum, *ColSum, *residual_even, *residual_odd; REAL sk, qk, ek, skm1, qkm1, ekm1, qkm2, qkqkm1, ekm2, ekekm1, absvalue, logvalue, StopTolerance; int *RowCount, *ColCount, colMax; int Result; MATrec *mat = lp->matA; REAL *value; int *rownr, *colnr; if(CurtisReidMeasure(lp, _Advanced, FRowScale, FColScale)<0.1*get_nonzeros(lp)) return(0); /* Allocate temporary memory and find RowSum and ColSum measures */ nz = get_nonzeros(lp); colMax = lp->columns; allocREAL(lp, &RowSum, lp->rows+1, TRUE); allocINT(lp, &RowCount, lp->rows+1, TRUE); allocREAL(lp, &residual_odd, lp->rows+1, TRUE); allocREAL(lp, &ColSum, colMax+1, TRUE); allocINT(lp, &ColCount, colMax+1, TRUE); allocREAL(lp, &residual_even, colMax+1, TRUE); allocREAL(lp, &RowScalem2, lp->rows+1, FALSE); allocREAL(lp, &ColScalem2, colMax+1, FALSE); /* Set origin for row scaling */ for(i = 1; i <= colMax; i++) { absvalue=fabs(lp->orig_obj[i]); if(absvalue>0) { logvalue = log(absvalue); ColSum[i] += logvalue; RowSum[0] += logvalue; ColCount[i]++; RowCount[0]++; } } value = &(COL_MAT_VALUE(0)); rownr = &(COL_MAT_ROWNR(0)); colnr = &(COL_MAT_COLNR(0)); for(i = 0; i < nz; i++, value += matValueStep, rownr += matRowColStep, colnr += matRowColStep) { absvalue=fabs(*value); if(absvalue>0) { logvalue = log(absvalue); ColSum[*colnr] += logvalue; RowSum[*rownr] += logvalue; ColCount[*colnr]++; RowCount[*rownr]++; } } /* Make sure we dont't have division by zero errors */ for(row = 0; row <= lp->rows; row++) if(RowCount[row] == 0) RowCount[row] = 1; for(col = 1; col <= colMax; col++) if(ColCount[col] == 0) ColCount[col] = 1; /* Initialize to RowScale = RowCount-1 RowSum ColScale = 0.0 residual = ColSum - ET RowCount-1 RowSum */ StopTolerance= MAX(lp->scalelimit-floor(lp->scalelimit), DEF_SCALINGEPS); StopTolerance *= (REAL) nz; for(row = 0; row <= lp->rows; row++) { FRowScale[row] = RowSum[row] / (REAL) RowCount[row]; RowScalem2[row] = FRowScale[row]; } /* Compute initial residual */ for(col = 1; col <= colMax; col++) { FColScale[col] = 0; ColScalem2[col] = 0; residual_even[col] = ColSum[col]; if(lp->orig_obj[col] != 0) residual_even[col] -= RowSum[0] / (REAL) RowCount[0]; i = mat->col_end[col-1]; rownr = &(COL_MAT_ROWNR(i)); ent = mat->col_end[col]; for(; i < ent; i++, rownr += matRowColStep) { residual_even[col] -= RowSum[*rownr] / (REAL) RowCount[*rownr]; } } /* Compute sk */ sk = 0; skm1 = 0; for(col = 1; col <= colMax; col++) sk += (residual_even[col]*residual_even[col]) / (REAL) ColCount[col]; Result = 0; qk=1; qkm1=0; qkm2=0; ek=0; ekm1=0; ekm2=0; while(sk>StopTolerance) { /* Given the values of residual and sk, construct ColScale (when pass is even) RowScale (when pass is odd) */ qkqkm1 = qk * qkm1; ekekm1 = ek * ekm1; if((Result % 2) == 0) { /* pass is even; construct RowScale[pass+1] */ if(Result != 0) { for(row = 0; row <= lp->rows; row++) RowScalem2[row] = FRowScale[row]; if(qkqkm1 != 0) { for(row = 0; row <= lp->rows; row++) FRowScale[row]*=(1 + ekekm1 / qkqkm1); for(row = 0; row<=lp->rows; row++) FRowScale[row]+=(residual_odd[row] / (qkqkm1 * (REAL) RowCount[row]) - RowScalem2[row] * ekekm1 / qkqkm1); } } } else { /* pass is odd; construct ColScale[pass+1] */ for(col = 1; col <= colMax; col++) ColScalem2[col] = FColScale[col]; if(qkqkm1 != 0) { for(col = 1; col <= colMax; col++) FColScale[col] *= (1 + ekekm1 / qkqkm1); for(col = 1; col <= colMax; col++) FColScale[col] += (residual_even[col] / ((REAL) ColCount[col] * qkqkm1) - ColScalem2[col] * ekekm1 / qkqkm1); } } /* update residual and sk (pass + 1) */ if((Result % 2) == 0) { /* even */ /* residual */ for(row = 0; row <= lp->rows; row++) residual_odd[row] *= ek; for(i = 1; i <= colMax; i++) if(lp->orig_obj[i] != 0) residual_odd[0] += (residual_even[i] / (REAL) ColCount[i]); rownr = &(COL_MAT_ROWNR(0)); colnr = &(COL_MAT_COLNR(0)); for(i = 0; i < nz; i++, rownr += matRowColStep, colnr += matRowColStep) { residual_odd[*rownr] += (residual_even[*colnr] / (REAL) ColCount[*colnr]); } for(row = 0; row <= lp->rows; row++) residual_odd[row] *= (-1 / qk); /* sk */ skm1 = sk; sk = 0; for(row = 0; row <= lp->rows; row++) sk += (residual_odd[row]*residual_odd[row]) / (REAL) RowCount[row]; } else { /* odd */ /* residual */ for(col = 1; col <= colMax; col++) residual_even[col] *= ek; for(i = 1; i <= colMax; i++) if(lp->orig_obj[i] != 0) residual_even[i] += (residual_odd[0] / (REAL) RowCount[0]); rownr = &(COL_MAT_ROWNR(0)); colnr = &(COL_MAT_COLNR(0)); for(i = 0; i < nz; i++, rownr += matRowColStep, colnr += matRowColStep) { residual_even[*colnr] += (residual_odd[*rownr] / (REAL) RowCount[*rownr]); } for(col = 1; col <= colMax; col++) residual_even[col] *= (-1 / qk); /* sk */ skm1 = sk; sk = 0; for(col = 1; col <= colMax; col++) sk += (residual_even[col]*residual_even[col]) / (REAL) ColCount[col]; } /* Compute ek and qk */ ekm2=ekm1; ekm1=ek; ek=qk * sk / skm1; qkm2=qkm1; qkm1=qk; qk=1-ek; Result++; } /* Synchronize the RowScale and ColScale vectors */ ekekm1 = ek * ekm1; if(qkm1 != 0) { if((Result % 2) == 0) { /* pass is even, compute RowScale */ for(row = 0; row<=lp->rows; row++) FRowScale[row]*=(1.0 + ekekm1 / qkm1); for(row = 0; row<=lp->rows; row++) FRowScale[row]+=(residual_odd[row] / (qkm1 * (REAL) RowCount[row]) - RowScalem2[row] * ekekm1 / qkm1); } else { /* pass is odd, compute ColScale */ for(col=1; col<=colMax; col++) FColScale[col]*=(1 + ekekm1 / qkm1); for(col=1; col<=colMax; col++) FColScale[col]+=(residual_even[col] / ((REAL) ColCount[col] * qkm1) - ColScalem2[col] * ekekm1 / qkm1); } } /* Do validation, if indicated */ if(FALSE && mat_validate(mat)){ double check, error; /* CHECK: M RowScale + E ColScale = RowSum */ error = 0; for(row = 0; row <= lp->rows; row++) { check = (REAL) RowCount[row] * FRowScale[row]; if(row == 0) { for(i = 1; i <= colMax; i++) { if(lp->orig_obj[i] != 0) check += FColScale[i]; } } else { i = mat->row_end[row-1]; ent = mat->row_end[row]; for(; i < ent; i++) { col = ROW_MAT_COLNR(i); check += FColScale[col]; } } check -= RowSum[row]; error += check*check; } /* CHECK: E^T RowScale + N ColScale = ColSum */ error = 0; for(col = 1; col <= colMax; col++) { check = (REAL) ColCount[col] * FColScale[col]; if(lp->orig_obj[col] != 0) check += FRowScale[0]; i = mat->col_end[col-1]; ent = mat->col_end[col]; rownr = &(COL_MAT_ROWNR(i)); for(; i < ent; i++, rownr += matRowColStep) { check += FRowScale[*rownr]; } check -= ColSum[col]; error += check*check; } } /* Convert to scaling factors (rounding to nearest power of 2 can optionally be done as a separate step later) */ for(col = 1; col <= colMax; col++) { absvalue = exp(-FColScale[col]); if(absvalue < MIN_SCALAR) absvalue = MIN_SCALAR; if(absvalue > MAX_SCALAR) absvalue = MAX_SCALAR; if(!is_int(lp,col) || is_integerscaling(lp)) FColScale[col] = absvalue; else FColScale[col] = 1; } for(row = 0; row <= lp->rows; row++) { absvalue = exp(-FRowScale[row]); if(absvalue < MIN_SCALAR) absvalue = MIN_SCALAR; if(absvalue > MAX_SCALAR) absvalue = MAX_SCALAR; FRowScale[row] = absvalue; } /* free temporary memory */ FREE(RowSum); FREE(ColSum); FREE(RowCount); FREE(ColCount); FREE(residual_even); FREE(residual_odd); FREE(RowScalem2); FREE(ColScalem2); return(Result); } STATIC MYBOOL scaleCR(lprec *lp, REAL *scaledelta) { REAL *scalechange = NULL; int Result; if(!lp->scaling_used) { allocREAL(lp, &lp->scalars, lp->sum_alloc + 1, FALSE); for(Result = 0; Result <= lp->sum; Result++) lp->scalars[Result] = 1; lp->scaling_used = TRUE; } if(scaledelta == NULL) allocREAL(lp, &scalechange, lp->sum + 1, FALSE); else scalechange = scaledelta; Result=CurtisReidScales(lp, FALSE, scalechange, &scalechange[lp->rows]); if(Result>0) { /* Do the scaling*/ if(scale_updaterows(lp, scalechange, TRUE) || scale_updatecolumns(lp, &scalechange[lp->rows], TRUE)) lp->scalemode |= SCALE_CURTISREID; set_action(&lp->spx_action, ACTION_REBASE | ACTION_REINVERT | ACTION_RECOMPUTE); } if(scaledelta == NULL) FREE(scalechange); return((MYBOOL) (Result > 0)); } STATIC MYBOOL transform_for_scale(lprec *lp, REAL *value) { MYBOOL Accept = TRUE; *value = fabs(*value); #ifdef Paranoia if(*value < lp->epsmachine) { Accept = FALSE; report(lp, SEVERE, "transform_for_scale: A zero-valued entry was passed\n"); } else #endif if(is_scalemode(lp, SCALE_LOGARITHMIC)) *value = log(*value); else if(is_scalemode(lp, SCALE_QUADRATIC)) (*value) *= (*value); return( Accept ); } STATIC void accumulate_for_scale(lprec *lp, REAL *min, REAL *max, REAL value) { if(transform_for_scale(lp, &value)) { if(is_scaletype(lp, SCALE_MEAN)) { *max += value; *min += 1; } else { SETMAX(*max, value); SETMIN(*min, value); } } } STATIC REAL minmax_to_scale(lprec *lp, REAL min, REAL max, int itemcount) { REAL scale; /* Initialize according to transformation / weighting model */ if(is_scalemode(lp, SCALE_LOGARITHMIC)) scale = 0; else scale = 1; if(itemcount <= 0) return(scale); /* Compute base scalar according to chosen scaling type */ if(is_scaletype(lp, SCALE_MEAN)) { if(min > 0) scale = max / min; } else if(is_scaletype(lp, SCALE_RANGE)) scale = (max + min) / 2; else if(is_scaletype(lp, SCALE_GEOMETRIC)) scale = sqrt(min*max); else if(is_scaletype(lp, SCALE_EXTREME)) scale = max; /* Compute final scalar according to transformation / weighting model */ if(is_scalemode(lp, SCALE_LOGARITHMIC)) scale = exp(-scale); else if(is_scalemode(lp, SCALE_QUADRATIC)) { if(scale == 0) scale = 1; else scale = 1 / sqrt(scale); } else { if(scale == 0) scale = 1; else scale = 1 / scale; } /* Make sure we are within acceptable scaling ranges */ SETMAX(scale, MIN_SCALAR); SETMIN(scale, MAX_SCALAR); return(scale); } STATIC REAL roundPower2(REAL scale) /* Purpose is to round a number to it nearest power of 2; in a system with binary number representation, this avoids rounding errors when scale is used to normalize another value */ { long int power2; MYBOOL isSmall = FALSE; if(scale == 1) return( scale ); /* Obtain the fractional power of 2 */ if(scale < 2) { scale = 2 / scale; isSmall = TRUE; } else scale /= 2; scale = log(scale)/log(2.0); /* Find the desired nearest power of two and compute the associated scalar */ power2 = (long) ceil(scale-0.5); scale = 1 << power2; if(isSmall) scale = 1.0 / scale; return( scale ); } STATIC MYBOOL scale_updatecolumns(lprec *lp, REAL *scalechange, MYBOOL updateonly) { int i, j; /* Verify that the scale change is significant (different from the unit) */ for(i = lp->columns; i > 0; i--) if(fabs(scalechange[i]-1) > lp->epsprimal) break; if(i <= 0) return( FALSE ); /* Update the pre-existing column scalar */ if(updateonly) for(i = 1, j = lp->rows + 1; j <= lp->sum; i++, j++) lp->scalars[j] *= scalechange[i]; else for(i = 1, j = lp->rows + 1; j <= lp->sum; i++, j++) lp->scalars[j] = scalechange[i]; return( TRUE ); } STATIC MYBOOL scale_updaterows(lprec *lp, REAL *scalechange, MYBOOL updateonly) { int i; /* Verify that the scale change is significant (different from the unit) */ for(i = lp->rows; i >= 0; i--) { if(fabs(scalechange[i]-1) > lp->epsprimal) break; } if(i < 0) return( FALSE ); /* Update the pre-existing row scalar */ if(updateonly) for(i = 0; i <= lp->rows; i++) lp->scalars[i] *= scalechange[i]; else for(i = 0; i <= lp->rows; i++) lp->scalars[i] = scalechange[i]; return( TRUE ); } STATIC MYBOOL scale_columns(lprec *lp, REAL *scaledelta) { int i,j, colMax, nz; REAL *scalechange; REAL *value; int *colnr; MATrec *mat = lp->matA; /* Check that columns are in fact targeted */ if((lp->scalemode & SCALE_ROWSONLY) != 0) return( TRUE ); if(scaledelta == NULL) scalechange = &lp->scalars[lp->rows]; else scalechange = &scaledelta[lp->rows]; colMax = lp->columns; /* Scale matrix entries (including any Lagrangean constraints) */ for(i = 1; i <= lp->columns; i++) { lp->orig_obj[i] *= scalechange[i]; } mat_validate(lp->matA); nz = get_nonzeros(lp); value = &(COL_MAT_VALUE(0)); colnr = &(COL_MAT_COLNR(0)); for(i = 0; i < nz; i++, value += matValueStep, colnr += matRowColStep) { (*value) *= scalechange[*colnr]; } /* Scale variable bounds as well */ for(i = 1, j = lp->rows + 1; j <= lp->sum; i++, j++) { if(lp->orig_lowbo[j] > -lp->infinite) lp->orig_lowbo[j] /= scalechange[i]; if(lp->orig_upbo[j] < lp->infinite) lp->orig_upbo[j] /= scalechange[i]; if(lp->sc_lobound[i] != 0) lp->sc_lobound[i] /= scalechange[i]; } lp->columns_scaled = TRUE; set_action(&lp->spx_action, ACTION_REBASE | ACTION_REINVERT | ACTION_RECOMPUTE); return( TRUE ); } STATIC MYBOOL scale_rows(lprec *lp, REAL *scaledelta) { int i, j, nz, colMax; REAL *scalechange; REAL *value; int *rownr; MATrec *mat = lp->matA; /* Check that rows are in fact targeted */ if((lp->scalemode & SCALE_COLSONLY) != 0) return( TRUE ); if(scaledelta == NULL) scalechange = lp->scalars; else scalechange = scaledelta; colMax = lp->columns; /* First row-scale the matrix (including the objective function) */ for(i = 1; i <= colMax; i++) { lp->orig_obj[i] *= scalechange[0]; } nz = get_nonzeros(lp); value = &(COL_MAT_VALUE(0)); rownr = &(COL_MAT_ROWNR(0)); for(i = 0; i < nz; i++, value += matValueStep, rownr += matRowColStep) { (*value) *= scalechange[*rownr]; } /* ...and scale the rhs and the row bounds (RANGES in MPS!!) */ for(i = 0; i <= lp->rows; i++) { if(fabs(lp->orig_rhs[i]) < lp->infinite) lp->orig_rhs[i] *= scalechange[i]; j = lp->presolve_undo->var_to_orig[i]; if(j != 0) lp->presolve_undo->fixed_rhs[j] *= scalechange[i]; if(lp->orig_upbo[i] < lp->infinite) /* This is the range */ lp->orig_upbo[i] *= scalechange[i]; if((lp->orig_lowbo[i] != 0) && (fabs(lp->orig_lowbo[i]) < lp->infinite)) lp->orig_lowbo[i] *= scalechange[i]; } set_action(&lp->spx_action, ACTION_REBASE | ACTION_REINVERT | ACTION_RECOMPUTE); return( TRUE ); } STATIC REAL scale(lprec *lp, REAL *scaledelta) { int i, j, nz, row_count, nzOF = 0; REAL *row_max, *row_min, *scalechange = NULL, absval; REAL col_max, col_min; MYBOOL rowscaled, colscaled; MATrec *mat = lp->matA; REAL *value; int *rownr; if(is_scaletype(lp, SCALE_NONE)) return(0.0); if(!lp->scaling_used) { allocREAL(lp, &lp->scalars, lp->sum_alloc + 1, FALSE); for(i = 0; i <= lp->sum; i++) { lp->scalars[i] = 1; } lp->scaling_used = TRUE; } #ifdef Paranoia else for(i = 0; i <= lp->sum; i++) { if(lp->scalars[i] == 0) report(lp, SEVERE, "scale: Zero-valued scalar found at index %d\n", i); } #endif if(scaledelta == NULL) allocREAL(lp, &scalechange, lp->sum + 1, FALSE); else scalechange = scaledelta; /* Must initialize due to computation of scaling statistic - KE */ for(i = 0; i <= lp->sum; i++) scalechange[i] = 1; row_count = lp->rows; allocREAL(lp, &row_max, row_count + 1, TRUE); allocREAL(lp, &row_min, row_count + 1, FALSE); /* Initialise min and max values of rows */ for(i = 0; i <= row_count; i++) { if(is_scaletype(lp, SCALE_MEAN)) row_min[i] = 0; /* Carries the count of elements */ else row_min[i] = lp->infinite; /* Carries the minimum element */ } /* Calculate row scaling data */ for(j = 1; j <= lp->columns; j++) { absval = lp->orig_obj[j]; if(absval != 0) { absval = scaled_mat(lp, absval, 0, j); accumulate_for_scale(lp, &row_min[0], &row_max[0], absval); nzOF++; } i = mat->col_end[j - 1]; value = &(COL_MAT_VALUE(i)); rownr = &(COL_MAT_ROWNR(i)); nz = mat->col_end[j]; for(; i < nz; i++, value += matValueStep, rownr += matRowColStep) { absval = scaled_mat(lp, *value, *rownr, j); accumulate_for_scale(lp, &row_min[*rownr], &row_max[*rownr], absval); } } /* Calculate scale factors for rows */ i = 0; for(; i <= lp->rows; i++) { if(i == 0) nz = nzOF; else nz = mat_rowlength(lp->matA, i); absval = minmax_to_scale(lp, row_min[i], row_max[i], nzOF); if(absval == 0) absval = 1; scalechange[i] = absval; } FREE(row_max); FREE(row_min); /* Row-scale the matrix (including the objective function and Lagrangean constraints) */ rowscaled = scale_updaterows(lp, scalechange, TRUE); /* Calculate column scales */ i = 1; for(j = 1; j <= lp->columns; j++) { if(is_int(lp,j) && !is_integerscaling(lp)) { /* do not scale integer columns */ scalechange[lp->rows + j] = 1; } else { col_max = 0; if(is_scaletype(lp, SCALE_MEAN)) col_min = 0; else col_min = lp->infinite; absval = lp->orig_obj[j]; if(absval != 0) { absval = scaled_mat(lp, absval, 0, j); accumulate_for_scale(lp, &col_min, &col_max, absval); } i = mat->col_end[j - 1]; value = &(COL_MAT_VALUE(i)); rownr = &(COL_MAT_ROWNR(i)); nz = mat->col_end[j]; for(; i < nz; i++, value += matValueStep, rownr += matRowColStep) { absval = scaled_mat(lp, *value, *rownr, j); accumulate_for_scale(lp, &col_min, &col_max, absval); } nz = mat_collength(lp->matA, j); if(fabs(lp->orig_obj[j]) > 0) nz++; scalechange[lp->rows + j] = minmax_to_scale(lp, col_min, col_max, nz); } } /* ... and then column-scale the already row-scaled matrix */ colscaled = scale_updatecolumns(lp, &scalechange[lp->rows], TRUE); /* Create a geometric mean-type measure of the extent of scaling performed; */ /* ideally, upon successive calls to scale() the value should converge to 0 */ if(rowscaled || colscaled) { col_max = 0; for(j = 1; j <= lp->columns; j++) col_max += log(scalechange[lp->rows + j]); col_max = exp(col_max/lp->columns); i = 0; col_min = 0; for(; i <= lp->rows; i++) col_min += log(scalechange[i]); col_min = exp(col_min/row_count); } else { col_max = 1; col_min = 1; } if(scaledelta == NULL) FREE(scalechange); return(1 - sqrt(col_max*col_min)); } STATIC MYBOOL finalize_scaling(lprec *lp, REAL *scaledelta) { int i; /* Check if we should equilibrate */ if(is_scalemode(lp, SCALE_EQUILIBRATE) && !is_scaletype(lp, SCALE_CURTISREID)) { int oldmode; oldmode = lp->scalemode; lp->scalemode = SCALE_LINEAR + SCALE_EXTREME; scale(lp, scaledelta); lp->scalemode = oldmode; } /* Check if we should prevent rounding errors */ if(is_scalemode(lp, SCALE_POWER2)) { REAL *scalars; if(scaledelta == NULL) scalars = lp->scalars; else scalars = scaledelta; for(i = 0; i <= lp->sum; i++) scalars[i] = roundPower2(scalars[i]); } /* Then transfer the scalars to the model's data */ return( scale_rows(lp, scaledelta) && scale_columns(lp, scaledelta) ); } STATIC REAL auto_scale(lprec *lp) { int n = 1; REAL scalingmetric = 0, *scalenew = NULL; if(lp->scaling_used && ((((lp->scalemode & SCALE_DYNUPDATE) == 0)) || (lp->bb_level > 0))) return( scalingmetric); if(lp->scalemode != SCALE_NONE) { /* Allocate array for incremental scaling if appropriate */ if((lp->solvecount > 1) && (lp->bb_level < 1) && ((lp->scalemode & SCALE_DYNUPDATE) != 0)) allocREAL(lp, &scalenew, lp->sum + 1, FALSE); if(is_scaletype(lp, SCALE_CURTISREID)) { scalingmetric = scaleCR(lp, scalenew); } else { REAL scalinglimit, scalingdelta; int count; /* Integer value of scalelimit holds the maximum number of iterations; default to 1 */ count = (int) floor(lp->scalelimit); scalinglimit = lp->scalelimit; if((count == 0) || (scalinglimit == 0)) { if(scalinglimit > 0) count = DEF_SCALINGLIMIT; /* A non-zero convergence has been given, default to max 5 iterations */ else count = 1; } else scalinglimit -= count; /* Scale to desired relative convergence or iteration limit */ n = 0; scalingdelta = 1.0; scalingmetric = 1.0; while((n < count) && (fabs(scalingdelta) > scalinglimit)) { n++; scalingdelta = scale(lp, scalenew); scalingmetric = scalingmetric*(1+scalingdelta); } scalingmetric -= 1; } } /* Update the inf norm of the elements of the matrix (excluding the OF) */ mat_computemax(lp->matA); /* Check if we really have to do scaling */ if(lp->scaling_used && (fabs(scalingmetric) >= lp->epsprimal)) /* Ok, do it */ finalize_scaling(lp, scalenew); else { /* Otherwise reset scaling variables */ if(lp->scalars != NULL) { FREE(lp->scalars); } lp->scaling_used = FALSE; lp->columns_scaled = FALSE; } if(scalenew != NULL) FREE(scalenew); return(scalingmetric); } STATIC void unscale_columns(lprec *lp) { int i, j, nz; MATrec *mat = lp->matA; REAL *value; int *rownr, *colnr; if(!lp->columns_scaled) return; /* Unscale OF */ for(j = 1; j <= lp->columns; j++) { lp->orig_obj[j] = unscaled_mat(lp, lp->orig_obj[j], 0, j); } /* Unscale mat */ mat_validate(mat); nz = get_nonzeros(lp); value = &(COL_MAT_VALUE(0)); rownr = &(COL_MAT_ROWNR(0)); colnr = &(COL_MAT_COLNR(0)); for(j = 0; j < nz; j++, value += matValueStep, rownr += matRowColStep, colnr += matRowColStep) { *value = unscaled_mat(lp, *value, *rownr, *colnr); } /* Unscale bounds as well */ for(i = lp->rows + 1, j = 1; i <= lp->sum; i++, j++) { lp->orig_lowbo[i] = unscaled_value(lp, lp->orig_lowbo[i], i); lp->orig_upbo[i] = unscaled_value(lp, lp->orig_upbo[i], i); lp->sc_lobound[j] = unscaled_value(lp, lp->sc_lobound[j], i); } for(i = lp->rows + 1; i<= lp->sum; i++) lp->scalars[i] = 1; lp->columns_scaled = FALSE; set_action(&lp->spx_action, ACTION_REBASE | ACTION_REINVERT | ACTION_RECOMPUTE); } void undoscale(lprec *lp) { int i, j, nz; MATrec *mat = lp->matA; REAL *value; int *rownr, *colnr; if(lp->scaling_used) { /* Unscale the OF */ for(j = 1; j <= lp->columns; j++) { lp->orig_obj[j] = unscaled_mat(lp, lp->orig_obj[j], 0, j); } /* Unscale the matrix */ mat_validate(mat); nz = get_nonzeros(lp); value = &(COL_MAT_VALUE(0)); rownr = &(COL_MAT_ROWNR(0)); colnr = &(COL_MAT_COLNR(0)); for(j = 0; j < nz; j++, value += matValueStep, rownr += matRowColStep, colnr += matRowColStep) { *value = unscaled_mat(lp, *value, *rownr, *colnr); } /* Unscale variable bounds */ for(i = lp->rows + 1, j = 1; i <= lp->sum; i++, j++) { lp->orig_lowbo[i] = unscaled_value(lp, lp->orig_lowbo[i], i); lp->orig_upbo[i] = unscaled_value(lp, lp->orig_upbo[i], i); lp->sc_lobound[j] = unscaled_value(lp, lp->sc_lobound[j], i); } /* Unscale the rhs, upper and lower bounds... */ for(i = 0; i <= lp->rows; i++) { lp->orig_rhs[i] = unscaled_value(lp, lp->orig_rhs[i], i); j = lp->presolve_undo->var_to_orig[i]; if(j != 0) lp->presolve_undo->fixed_rhs[j] = unscaled_value(lp, lp->presolve_undo->fixed_rhs[j], i); lp->orig_lowbo[i] = unscaled_value(lp, lp->orig_lowbo[i], i); lp->orig_upbo[i] = unscaled_value(lp, lp->orig_upbo[i], i); } FREE(lp->scalars); lp->scaling_used = FALSE; lp->columns_scaled = FALSE; set_action(&lp->spx_action, ACTION_REBASE | ACTION_REINVERT | ACTION_RECOMPUTE); } } MSVMpack1.2/lp_solve_5.5/Makefile.Linux0000664000175000017500000000500010557467270016704 0ustar lauerlauer# # Makefile for building lp_solve using GNU Make # Usage: # make -f Makefile.Linux [all | bin | lib | clean] # # $Revision: 1.1 $ # AR = ar ARFLAGS = rv CC = gcc LEX = flex YACC = bison INCLUDE = -I. -Ibfp -Ibfp/bfp_LUSOL -Ibfp/bfp_LUSOL/LUSOL -Icolamd -Ishared # Uncomment any of the following two depending on your profile #DEBUG = -g -pg DEBUG = -O2 DEFINE = -DYY_NEVER_INTERACTIVE -DPARSER_LP -DINVERSE_ACTIVE=INVERSE_LUSOL -DRoleIsExternalInvEngine # Uncomment any of the following two depending on how easily compiler messages scare you #CFLAGS= $(INCLUDE) $(DEBUG) $(DEFINE) -fpic -Wall -pedantic -trigraphs CFLAGS= $(INCLUDE) $(DEBUG) $(DEFINE) -fpic LFLAGS = -L -l YFLAGS = --no-lines -y LDFLAGS = -lm -ldl LUSOLSRC = bfp/bfp_LUSOL/lp_LUSOL.c bfp/bfp_LUSOL/LUSOL/lusol.c LUSOLOBJS = bfp/bfp_LUSOL/lp_LUSOL.o bfp/bfp_LUSOL/LUSOL/lusol.o OBJECTS = $(LUSOLOBJS) lp_MDO.o shared/commonlib.o colamd/colamd.o \ shared/mmio.o shared/myblas.o ini.o fortify.o lp_rlp.o lp_crash.o \ lp_Hash.o lp_lib.o lp_wlp.o lp_matrix.o lp_mipbb.o lp_MPS.o \ lp_params.o lp_presolve.o lp_price.o lp_pricePSE.o lp_report.o \ lp_scale.o lp_simplex.o lp_SOS.o lp_utils.o yacc_read.o SRC = $(LUSOLSRC) lp_MDO.c shared/commonlib.c colamd/colamd.c \ shared/mmio.c shared/myblas.c ini.c fortify.c lp_rlp.c lp_crash.c \ lp_Hash.c lp_lib.c lp_wlp.c lp_matrix.c lp_mipbb.c lp_MPS.c \ lp_params.c lp_presolve.c lp_price.c lp_pricePSE.c lp_report.c \ lp_scale.c lp_simplex.c lp_SOS.c lp_utils.c yacc_read.c LIBRARIES = liblpsolve55.a liblpsolve55.so BINARIES = lp_solve demo ALL = $(BINARIES) $(DEMOS) $(LIBRARIES) .PHONY=clean lp_solve all: $(ALL) lib: $(LIBRARIES) bin: $(BINARIES) objects: $(OBJECTS) lp_rlp.o: lp_rlp.l lp_rlp.y $(LEX) $(LFLAGS) lp_rlp.l sed -e "s/yy/lp_yy/g" lex.yy.c >lp_rlp.h rm -f lex.yy.c $(YACC) $(YFLAGS) lp_rlp.y sed -e "s/yy/lp_yy/g" y.tab.c >lp_rlp.c rm -f y.tab.c $(CC) $(CFLAGS) $(DEBUG) $(DEFINE) $(INCLUDE) -c $*.c lp_solve: lp_solve/lp_solve.c $(OBJECTS) $(CC) $(CFLAGS) $(DEBUG) $(DEFINE) $(INCLUDE) $< $(OBJECTS) -o lp_solve/lp_solve $(LDFLAGS) demo: demo/demo.c $(OBJECTS) $(CC) $(CFLAGS) $(DEBUG) $(DEFINE) $(INCLUDE) $< $(OBJECTS) -o demo/demo $(LDFLAGS) liblpsolve55.a: $(OBJECTS) $(AR) $(ARFLAGS) lpsolve55/$@ `echo $(SRC)|sed 's/[.]c/.o/g'` ranlib lpsolve55/$@ liblpsolve55.so: $(OBJECTS) $(CC) -fpic -shared -Wl,-Bsymbolic -Wl,-soname,$@ -o lpsolve55/$@ `echo $(SRC)|sed 's/[.]c/.o/g'` $(LDFLAGS) clean: rm -f $(OBJECTS) *.so *.a lp_solve/lp_solve demo/demo lpsolve55/*.so lpsolve55/*.a MSVMpack1.2/lp_solve_5.5/lp_mipbb.c0000664000175000017500000013747211250516633016106 0ustar lauerlauer /* Mixed integer programming optimization drivers for lp_solve v5.0+ ---------------------------------------------------------------------------------- Author: Michel Berkelaar (to lp_solve v3.2) Kjell Eikland (v4.0 and forward) Contact: License terms: LGPL. Requires: string.h, float.h, commonlib.h, lp_lib.h, lp_report.h, lp_simplex.h Release notes: v5.0.0 31 January 2004 New unit isolating B&B routines. v5.0.1 01 February 2004 Complete rewrite into non-recursive version. v5.0.2 05 April 2004 Expanded pseudocosting with options for MIP fraction counts and "cost/benefit" ratio (KE special!). Added GUB functionality based on SOS structures. v5.0.3 1 May 2004 Changed routine names to be more intuitive. v5.0.4 15 May 2004 Added functinality to pack bounds in order to conserve memory in B&B-processing large MIP models. v5.1.0 25 July 2004 Added functions for dynamic cut generation. v5.2.0 15 December 2004 Added functions for reduced cost variable fixing and converted to delta-model of B&B bound storage. ---------------------------------------------------------------------------------- */ #include #include #include "commonlib.h" #include "lp_lib.h" #include "lp_scale.h" #include "lp_report.h" #include "lp_simplex.h" #include "lp_mipbb.h" #ifdef FORTIFY # include "lp_fortify.h" #endif /* Allocation routine for the BB record structure */ STATIC BBrec *create_BB(lprec *lp, BBrec *parentBB, MYBOOL dofullcopy) { BBrec *newBB; newBB = (BBrec *) calloc(1, sizeof(*newBB)); if(newBB != NULL) { if(parentBB == NULL) { allocREAL(lp, &newBB->upbo, lp->sum + 1, FALSE); allocREAL(lp, &newBB->lowbo, lp->sum + 1, FALSE); MEMCOPY(newBB->upbo, lp->orig_upbo, lp->sum + 1); MEMCOPY(newBB->lowbo, lp->orig_lowbo, lp->sum + 1); } else if(dofullcopy) { allocREAL(lp, &newBB->upbo, lp->sum + 1, FALSE); allocREAL(lp, &newBB->lowbo, lp->sum + 1, FALSE); MEMCOPY(newBB->upbo, parentBB->upbo, lp->sum + 1); MEMCOPY(newBB->lowbo, parentBB->lowbo, lp->sum + 1); } else { newBB->upbo = parentBB->upbo; newBB->lowbo = parentBB->lowbo; } newBB->contentmode = dofullcopy; newBB->lp = lp; /* Set parent by default, but not child */ newBB->parent = parentBB; } return( newBB ); } /* Pushing and popping routines for the B&B structure */ STATIC BBrec *push_BB(lprec *lp, BBrec *parentBB, int varno, int vartype, int varcus) /* Push ingoing bounds and B&B data onto the stack */ { BBrec *newBB; /* Do initialization and updates */ if(parentBB == NULL) parentBB = lp->bb_bounds; newBB = create_BB(lp, parentBB, FALSE); if(newBB != NULL) { newBB->varno = varno; newBB->vartype = vartype; newBB->lastvarcus = varcus; incrementUndoLadder(lp->bb_lowerchange); newBB->LBtrack++; incrementUndoLadder(lp->bb_upperchange); newBB->UBtrack++; /* Adjust variable fixing/bound tightening based on the last reduced cost */ if((parentBB != NULL) && (parentBB->lastrcf > 0)) { MYBOOL isINT; int k, ii, nfixed = 0, ntighten = 0; REAL deltaUL; for(k = 1; k <= lp->nzdrow[0]; k++) { ii = lp->nzdrow[k]; #ifdef UseMilpSlacksRCF /* Check if we should include ranged constraints */ isINT = FALSE; #else if(ii <= lp->rows) continue; isINT = is_int(lp, ii-lp->rows); #endif #ifndef UseMilpExpandedRCF /* Don't include non-integers if it is not defined */ if(!isINT) continue; #endif switch(abs(rcfbound_BB(newBB, ii, isINT, &deltaUL, NULL))) { case LE: SETMIN(deltaUL, newBB->upbo[ii]); SETMAX(deltaUL, newBB->lowbo[ii]); modifyUndoLadder(lp->bb_upperchange, ii, newBB->upbo, deltaUL); break; case GE: SETMAX(deltaUL, newBB->lowbo[ii]); SETMIN(deltaUL, newBB->upbo[ii]); modifyUndoLadder(lp->bb_lowerchange, ii, newBB->lowbo, deltaUL); break; default: continue; } if(newBB->upbo[ii] == newBB->lowbo[ii]) nfixed++; else ntighten++; } if(lp->bb_trace) { report(lp, DETAILED, "push_BB: Used reduced cost to fix %d variables and tighten %d bounds\n", nfixed, ntighten); } } /* Handle case where we are pushing at the end */ if(parentBB == lp->bb_bounds) lp->bb_bounds = newBB; /* Handle case where we are pushing in the middle */ else newBB->child = parentBB->child; if(parentBB != NULL) parentBB->child = newBB; lp->bb_level++; if(lp->bb_level > lp->bb_maxlevel) lp->bb_maxlevel = lp->bb_level; if(!initbranches_BB(newBB)) newBB = pop_BB(newBB); else if(MIP_count(lp) > 0) { if( (lp->bb_level <= 1) && (lp->bb_varactive == NULL) && (!allocINT(lp, &lp->bb_varactive, lp->columns+1, TRUE) || !initcuts_BB(lp)) ) newBB = pop_BB(newBB); if(varno > 0) { lp->bb_varactive[varno-lp->rows]++; } } } return( newBB ); } STATIC MYBOOL free_BB(BBrec **BB) { MYBOOL parentreturned = FALSE; if((BB != NULL) && (*BB != NULL)) { BBrec *parent = (*BB)->parent; if((parent == NULL) || (*BB)->contentmode) { FREE((*BB)->upbo); FREE((*BB)->lowbo); } FREE((*BB)->varmanaged); FREE(*BB); parentreturned = (MYBOOL) (parent != NULL); if(parentreturned) *BB = parent; } return( parentreturned ); } STATIC BBrec *pop_BB(BBrec *BB) /* Pop / free the previously "pushed" / saved bounds */ { int k; BBrec *parentBB; lprec *lp = BB->lp; if(BB == NULL) return( BB ); /* Handle case where we are popping the end of the chain */ parentBB = BB->parent; if(BB == lp->bb_bounds) { lp->bb_bounds = parentBB; if(parentBB != NULL) parentBB->child = NULL; } /* Handle case where we are popping inside or at the beginning of the chain */ else { if(parentBB != NULL) parentBB->child = BB->child; if(BB->child != NULL) BB->child->parent = parentBB; } /* Unwind other variables */ if(lp->bb_upperchange != NULL) { restoreUndoLadder(lp->bb_upperchange, BB->upbo); for(; BB->UBtrack > 0; BB->UBtrack--) { decrementUndoLadder(lp->bb_upperchange); restoreUndoLadder(lp->bb_upperchange, BB->upbo); } } if(lp->bb_lowerchange != NULL) { restoreUndoLadder(lp->bb_lowerchange, BB->lowbo); for(; BB->LBtrack > 0; BB->LBtrack--) { decrementUndoLadder(lp->bb_lowerchange); restoreUndoLadder(lp->bb_lowerchange, BB->lowbo); } } lp->bb_level--; k = BB->varno - lp->rows; if(lp->bb_level == 0) { if(lp->bb_varactive != NULL) { FREE(lp->bb_varactive); freecuts_BB(lp); } if(lp->int_vars+lp->sc_vars > 0) free_pseudocost(lp); pop_basis(lp, FALSE); lp->rootbounds = NULL; } else lp->bb_varactive[k]--; /* Undo SOS/GUB markers */ if(BB->isSOS && (BB->vartype != BB_INT)) SOS_unmark(lp->SOS, 0, k); else if(BB->isGUB) SOS_unmark(lp->GUB, 0, k); /* Undo the SC marker */ if(BB->sc_canset) lp->sc_lobound[k] *= -1; /* Pop the associated basis */ #if 1 /* Original version that does not restore previous basis */ pop_basis(lp, FALSE); #else /* Experimental version that restores previous basis */ pop_basis(lp, BB->isSOS); #endif /* Finally free the B&B object */ free_BB(&BB); /* Return the parent BB */ return( parentBB ); } /* Here are heuristic routines to see if we need bother with branching further 1. A probing routine to see of the best OF can be better than incumbent 2. A presolve routine to fix other variables and detect infeasibility THIS IS INACTIVE CODE, PLACEHOLDERS FOR FUTURE DEVELOPMENT!!! */ STATIC REAL probe_BB(BBrec *BB) { int i, ii; REAL coefOF, sum = 0; lprec *lp = BB->lp; /* Loop over all ints to see if the best possible solution stands any chance of being better than the incumbent solution */ if(lp->solutioncount == 0) return( lp->infinite ); for(i = 1; i <= lp->columns; i++) { if(!is_int(lp, i)) continue; ii = lp->rows + i; coefOF = lp->obj[i]; if(coefOF < 0) { if(is_infinite(lp, BB->lowbo[ii])) return( lp->infinite ); sum += coefOF * (lp->solution[ii]-BB->lowbo[ii]); } else { if(is_infinite(lp, BB->upbo[ii])) return( lp->infinite ); sum += coefOF * (BB->upbo[ii] - lp->solution[ii]); } } return( sum ); } STATIC REAL presolve_BB(BBrec *BB) { return( 0 ); } /* Node and branch management routines */ STATIC MYBOOL initbranches_BB(BBrec *BB) { REAL new_bound, temp; int k; lprec *lp = BB->lp; /* Create and initialize local bounds and basis */ BB->nodestatus = NOTRUN; BB->noderesult = lp->infinite; push_basis(lp, NULL, NULL, NULL); /* Set default number of branches at the current B&B branch */ if(BB->vartype == BB_REAL) BB->nodesleft = 1; else { /* The default is a binary up-low branching */ BB->nodesleft = 2; /* Initialize the MIP status code pair and set reference values */ k = BB->varno - lp->rows; BB->lastsolution = lp->solution[BB->varno]; /* Determine if we must process in the B&B SOS mode */ BB->isSOS = (MYBOOL) ((BB->vartype == BB_SOS) || SOS_is_member(lp->SOS, 0, k)); #ifdef Paranoia if((BB->vartype == BB_SOS) && !SOS_is_member(lp->SOS, 0, k)) report(lp, SEVERE, "initbranches_BB: Inconsistent identification of SOS variable %s (%d)\n", get_col_name(lp, k), k); #endif /* Check if we have a GUB-member variable that needs a triple-branch */ BB->isGUB = (MYBOOL) ((BB->vartype == BB_INT) && SOS_can_activate(lp->GUB, 0, k)); if(BB->isGUB) { /* Obtain variable index list from applicable GUB - now the first GUB is used, but we could also consider selecting the longest */ BB->varmanaged = SOS_get_candidates(lp->GUB, -1, k, TRUE, BB->upbo, BB->lowbo); BB->nodesleft++; } /* Set local pruning info, automatic, or user-defined strategy */ if(BB->vartype == BB_SOS) { if(!SOS_can_activate(lp->SOS, 0, k)) { BB->nodesleft--; BB->isfloor = TRUE; } else BB->isfloor = (MYBOOL) (BB->lastsolution == 0); } /* First check if the user wishes to select the branching direction */ else if(lp->bb_usebranch != NULL) BB->isfloor = (MYBOOL) lp->bb_usebranch(lp, lp->bb_branchhandle, k); /* Otherwise check if we should do automatic branching */ else if(get_var_branch(lp, k) == BRANCH_AUTOMATIC) { new_bound = modf(BB->lastsolution/get_pseudorange(lp->bb_PseudoCost, k, BB->vartype), &temp); if(isnan(new_bound)) new_bound = 0; else if(new_bound < 0) new_bound += 1.0; BB->isfloor = (MYBOOL) (new_bound <= 0.5); /* Set direction by OF value; note that a zero-value in the OF gives priority to floor_first = TRUE */ if(is_bb_mode(lp, NODE_GREEDYMODE)) { if(is_bb_mode(lp, NODE_PSEUDOCOSTMODE)) BB->sc_bound = get_pseudonodecost(lp->bb_PseudoCost, k, BB->vartype, BB->lastsolution); else BB->sc_bound = mat_getitem(lp->matA, 0, k); new_bound -= 0.5; BB->sc_bound *= new_bound; BB->isfloor = (MYBOOL) (BB->sc_bound > 0); } /* Set direction by pseudocost (normally used in tandem with NODE_PSEUDOxxxSELECT) */ else if(is_bb_mode(lp, NODE_PSEUDOCOSTMODE)) { BB->isfloor = (MYBOOL) (get_pseudobranchcost(lp->bb_PseudoCost, k, TRUE) > get_pseudobranchcost(lp->bb_PseudoCost, k, FALSE)); if(is_maxim(lp)) BB->isfloor = !BB->isfloor; } /* Check for reversal */ if(is_bb_mode(lp, NODE_BRANCHREVERSEMODE)) BB->isfloor = !BB->isfloor; } else BB->isfloor = (MYBOOL) (get_var_branch(lp, k) == BRANCH_FLOOR); /* SC logic: If the current SC variable value is in the [0..NZLOBOUND> range, then UP: Set lower bound to NZLOBOUND, upper bound is the original LO: Fix the variable by setting upper/lower bound to zero ... indicate that the variable is B&B-active by reversing sign of sc_lobound[]. */ new_bound = fabs(lp->sc_lobound[k]); BB->sc_bound = new_bound; BB->sc_canset = (MYBOOL) (new_bound != 0); /* Must make sure that we handle fractional lower bounds properly; also to ensure that we do a full binary tree search */ new_bound = unscaled_value(lp, new_bound, BB->varno); if(is_int(lp, k) && ((new_bound > 0) && (BB->lastsolution > floor(new_bound)))) { if(BB->lastsolution < ceil(new_bound)) BB->lastsolution += 1; modifyUndoLadder(lp->bb_lowerchange, BB->varno, BB->lowbo, scaled_floor(lp, BB->varno, BB->lastsolution, 1)); } } /* Now initialize the brances and set to first */ return( fillbranches_BB(BB) ); } STATIC MYBOOL fillbranches_BB(BBrec *BB) { int K, k; REAL ult_upbo, ult_lowbo; REAL new_bound, SC_bound, intmargin = BB->lp->epsprimal; lprec *lp = BB->lp; MYBOOL OKstatus = FALSE; if(lp->bb_break || userabort(lp, MSG_MILPSTRATEGY)) return( OKstatus ); K = BB->varno; if(K > 0) { /* Shortcut variables */ k = BB->varno - lp->rows; ult_upbo = lp->orig_upbo[K]; ult_lowbo = lp->orig_lowbo[K]; SC_bound = unscaled_value(lp, BB->sc_bound, K); /* First, establish the upper bound to be applied (when isfloor == TRUE) --------------------------------------------------------------------- */ /*SetUB:*/ BB->UPbound = lp->infinite; /* Handle SC-variables for the [0-LoBound> range */ if((SC_bound > 0) && (fabs(BB->lastsolution) < SC_bound-intmargin)) { new_bound = 0; } /* Handle pure integers (non-SOS, non-SC) */ else if(BB->vartype == BB_INT) { #if 1 if(((ult_lowbo >= 0) && ((floor(BB->lastsolution) < /* Skip cases where the lower bound becomes violated */ unscaled_value(lp, MAX(ult_lowbo, fabs(lp->sc_lobound[k])), K)-intmargin))) || ((ult_upbo <= 0) && /* Was ((ult_lowbo < 0) && */ ((floor(BB->lastsolution) > /* Skip cases where the upper bound becomes violated */ unscaled_value(lp, MIN(ult_upbo, -fabs(lp->sc_lobound[k])), K)-intmargin)))) { #else if((floor(BB->lastsolution) < /* Skip cases where the lower bound becomes violated */ unscaled_value(lp, MAX(ult_lowbo, fabs(lp->sc_lobound[k])), K)-intmargin)) { #endif BB->nodesleft--; goto SetLB; } new_bound = scaled_floor(lp, K, BB->lastsolution, 1); } else if(BB->isSOS) { /* Handle all SOS variants */ new_bound = ult_lowbo; if(is_int(lp, k)) new_bound = scaled_ceil(lp, K, unscaled_value(lp, new_bound, K), -1); } else /* Handle all other variable incarnations */ new_bound = BB->sc_bound; /* Check if the new bound might conflict and possibly make adjustments */ if(new_bound < BB->lowbo[K]) new_bound = BB->lowbo[K] - my_avoidtiny(new_bound-BB->lowbo[K], intmargin); if(new_bound < BB->lowbo[K]) { #ifdef Paranoia debug_print(lp, "fillbranches_BB: New upper bound value %g conflicts with old lower bound %g\n", new_bound, BB->lowbo[K]); #endif BB->nodesleft--; goto SetLB; } #ifdef Paranoia /* Do additional consistency checking */ else if(!check_if_less(lp, new_bound, BB->upbo[K], K)) { BB->nodesleft--; goto SetLB; } #endif /* Bound (at least near) feasible */ else { /* Makes a difference with models like QUEEN (note consistent use of epsint for scaled integer variables) */ if(fabs(new_bound - BB->lowbo[K]) < intmargin*SCALEDINTFIXRANGE) new_bound = BB->lowbo[K]; } BB->UPbound = new_bound; /* Next, establish the lower bound to be applied (when isfloor == FALSE) --------------------------------------------------------------------- */ SetLB: BB->LObound = -lp->infinite; /* Handle SC-variables for the [0-LoBound> range */ if((SC_bound > 0) && (fabs(BB->lastsolution) < SC_bound)) { if(is_int(lp, k)) new_bound = scaled_ceil(lp, K, SC_bound, 1); else new_bound = BB->sc_bound; } /* Handle pure integers (non-SOS, non-SC, but Ok for GUB!) */ else if((BB->vartype == BB_INT)) { if(((ceil(BB->lastsolution) == BB->lastsolution)) || /* Skip branch 0 if the current solution is integer */ (ceil(BB->lastsolution) > /* Skip cases where the upper bound becomes violated */ unscaled_value(lp, ult_upbo, K)+intmargin) || (BB->isSOS && (BB->lastsolution == 0))) { /* Don't branch 0 since this is handled in SOS logic */ BB->nodesleft--; goto Finish; } new_bound = scaled_ceil(lp, K, BB->lastsolution, 1); } else if(BB->isSOS) { /* Handle all SOS variants */ if(SOS_is_member_of_type(lp->SOS, k, SOS3)) new_bound = scaled_floor(lp, K, 1, 1); else { new_bound = ult_lowbo; if(is_int(lp, k)) new_bound = scaled_floor(lp, K, unscaled_value(lp, new_bound, K), 1); /* If we have a high-order SOS (SOS3+) and this variable is "intermediate" between members previously lower-bounded at a non-zero level, then we should set this and similar neighbouring variables at non-zero lowbo-values (remember that SOS3+ members are all either integers or semi-continuous). Flag this situation and prune tree, since we cannot lower-bound. */ if((lp->SOS->maxorder > 2) && (BB->lastsolution == 0) && SOS_is_member_of_type(lp->SOS, k, SOSn)) { BB->isSOS = AUTOMATIC; } } } else /* Handle all other variable incarnations */ new_bound = BB->sc_bound; /* Check if the new bound might conflict and possibly make adjustments */ if(new_bound > BB->upbo[K]) new_bound = BB->upbo[K] + my_avoidtiny(new_bound-BB->upbo[K], intmargin); if(new_bound > BB->upbo[K]) { #ifdef Paranoia debug_print(lp, "fillbranches_BB: New lower bound value %g conflicts with old upper bound %g\n", new_bound, BB->upbo[K]); #endif BB->nodesleft--; goto Finish; } #ifdef Paranoia /* Do additional consistency checking */ else if(!check_if_less(lp, BB->lowbo[K], new_bound, K)) { BB->nodesleft--; goto Finish; } #endif /* Bound (at least near-)feasible */ else { /* Makes a difference with models like QUEEN (note consistent use of lp->epsprimal for scaled integer variables) */ if(fabs(BB->upbo[K]-new_bound) < intmargin*SCALEDINTFIXRANGE) new_bound = BB->upbo[K]; } BB->LObound = new_bound; /* Prepare for the first branch by making sure we are pointing correctly */ Finish: if(BB->nodesleft > 0) { /* Make sure the change tracker levels are "clean" for the B&B */ if(countsUndoLadder(lp->bb_upperchange) > 0) { incrementUndoLadder(lp->bb_upperchange); BB->UBtrack++; } if(countsUndoLadder(lp->bb_lowerchange) > 0) { incrementUndoLadder(lp->bb_lowerchange); BB->LBtrack++; } /* Do adjustments */ if((BB->vartype != BB_SOS) && (fabs(BB->LObound-BB->UPbound) < intmargin)) { BB->nodesleft--; if(fabs(BB->lowbo[K]-BB->LObound) < intmargin) BB->isfloor = FALSE; else if(fabs(BB->upbo[K]-BB->UPbound) < intmargin) BB->isfloor = TRUE; else report(BB->lp, IMPORTANT, "fillbranches_BB: Inconsistent equal-valued bounds for %s\n", get_col_name(BB->lp, k)); } if((BB->nodesleft == 1) && ((BB->isfloor && (BB->UPbound >= lp->infinite)) || (!BB->isfloor && (BB->LObound <= -lp->infinite)))) BB->isfloor = !BB->isfloor; /* Header initialization */ BB->isfloor = !BB->isfloor; while(!OKstatus && /* !userabort(lp, -1) */ lp->spx_status != TIMEOUT && !lp->bb_break && (BB->nodesleft > 0)) OKstatus = nextbranch_BB( BB ); } /* Set an SC variable active, if necessary */ if(BB->sc_canset) lp->sc_lobound[k] *= -1; } else { BB->nodesleft--; OKstatus = TRUE; } return( OKstatus ); } STATIC MYBOOL nextbranch_BB(BBrec *BB) { int k; lprec *lp = BB->lp; MYBOOL OKstatus = FALSE; /* Undo the most recently imposed B&B bounds using the data in the last level of change tracker; this code handles changes to both upper and lower bounds */ if(BB->nodessolved > 0) { restoreUndoLadder(lp->bb_upperchange, BB->upbo); restoreUndoLadder(lp->bb_lowerchange, BB->lowbo); } if(lp->bb_break || userabort(lp, MSG_MILPSTRATEGY)) { /* Handle the special case of B&B restart; (typically used with the restart after pseudocost initialization) */ if((lp->bb_level == 1) && (lp->bb_break == AUTOMATIC)) { lp->bb_break = FALSE; OKstatus = TRUE; } return( OKstatus ); } if(BB->nodesleft > 0) { /* Step and update remaining branch count */ k = BB->varno - lp->rows; BB->isfloor = !BB->isfloor; BB->nodesleft--; /* Special SOS handling: 1) Undo and set new marker for k, 2) In case that previous branch was ceiling restore upper bounds of the non-k variables outside of the SOS window set to 0 */ if(BB->isSOS && (BB->vartype != BB_INT)) { /* First undo previous marker */ if((BB->nodessolved > 0) || ((BB->nodessolved == 0) && (BB->nodesleft == 0))) { if(BB->isfloor) { if((BB->nodesleft == 0) && (lp->orig_lowbo[BB->varno] != 0)) return( OKstatus ); } SOS_unmark(lp->SOS, 0, k); } /* Set new SOS marker */ if(BB->isfloor) { SOS_set_marked(lp->SOS, 0, k, (MYBOOL) (BB->UPbound != 0)); /* Do case of high-order SOS where intervening variables need to be set */ if(BB->isSOS == AUTOMATIC) { /* SOS_fix_list(lp->SOS, 0, k, BB->lowbo, NULL, AUTOMATIC, lp->bb_lowerchange); */ } } else { SOS_set_marked(lp->SOS, 0, k, TRUE); if(SOS_fix_unmarked(lp->SOS, 0, k, BB->upbo, 0, TRUE, NULL, lp->bb_upperchange) < 0) return( OKstatus ); } } /* Special GUB handling (three branches): 1) Undo and set new marker for k, 2) Restore upper bounds of the left/right/all non-k variables set to 0 in the previous branch 3) Set new upper bounds for the non-k variables (k is set later) */ else if(BB->isGUB) { /* First undo previous marker */ if(BB->nodessolved > 0) SOS_unmark(lp->GUB, 0, k); /* Make sure we take floor bound twice */ if((BB->nodesleft == 0) && !BB->isfloor) BB->isfloor = !BB->isfloor; /* Handle two floor instances; (selected variable and left/right halves of non-selected variables at 0) */ SOS_set_marked(lp->GUB, 0, k, (MYBOOL) !BB->isfloor); if(BB->isfloor) { if(SOS_fix_list(lp->GUB, 0, k, BB->upbo, BB->varmanaged, (MYBOOL) (BB->nodesleft > 0), lp->bb_upperchange) < 0) return( OKstatus ); } /* Handle one ceil instance; (selected variable at 1, all other at 0) */ else { if(SOS_fix_unmarked(lp->GUB, 0, k, BB->upbo, 0, TRUE, NULL, lp->bb_upperchange) < 0) return( OKstatus ); } } OKstatus = TRUE; } /* Initialize simplex status variables */ if(OKstatus) { lp->bb_totalnodes++; BB->nodestatus = NOTRUN; BB->noderesult = lp->infinite; } return( OKstatus ); } /* Cut generation and management routines */ STATIC MYBOOL initcuts_BB(lprec *lp) { return( TRUE ); } STATIC int updatecuts_BB(lprec *lp) { return( 0 ); } STATIC MYBOOL freecuts_BB(lprec *lp) { if(lp->bb_cuttype != NULL) FREE(lp->bb_cuttype); return( TRUE ); } /* B&B solver routines */ STATIC int solve_LP(lprec *lp, BBrec *BB) { int tilted, restored, status; REAL testOF, *upbo = BB->upbo, *lowbo = BB->lowbo; BBrec *perturbed = NULL; if(lp->bb_break) return(PROCBREAK); #ifdef Paranoia debug_print(lp, "solve_LP: Starting solve for iter %.0f, B&B node level %d.\n", (double) lp->total_iter, lp->bb_level); if(lp->bb_trace && !validate_bounds(lp, upbo, lowbo)) report(lp, SEVERE, "solve_LP: Inconsistent bounds at iter %.0f, B&B node level %d.\n", (double) lp->total_iter, lp->bb_level); #endif /* Copy user-specified entering bounds into lp_solve working bounds */ impose_bounds(lp, upbo, lowbo); /* Restore previously pushed / saved basis for this level if we are in the B&B mode and it is not the first call of the binary tree */ if(BB->nodessolved > 1) restore_basis(lp); /* Solve and possibly handle degeneracy cases via bound relaxations */ status = RUNNING; tilted = 0; restored = 0; while(status == RUNNING) { /* Copy user-specified entering bounds into lp_solve working bounds and run */ status = spx_run(lp, (MYBOOL) (tilted+restored > 0)); lp->bb_status = status; lp->spx_perturbed = FALSE; if(tilted < 0) break; else if((status == OPTIMAL) && (tilted > 0)) { if(lp->spx_trace) report(lp, DETAILED, "solve_LP: Restoring relaxed bounds at level %d.\n", tilted); /* Restore original pre-perturbed problem bounds, and solve again using the basis found for the perturbed problem; also make sure we rebase and recompute. */ free_BB(&perturbed); if((perturbed == NULL) || (perturbed == BB)) { perturbed = NULL; impose_bounds(lp, upbo, lowbo); } else impose_bounds(lp, perturbed->upbo, perturbed->lowbo); set_action(&lp->spx_action, ACTION_REBASE | ACTION_RECOMPUTE); BB->UBzerobased = FALSE; if(lp->bb_totalnodes == 0) lp->real_solution = lp->infinite; status = RUNNING; tilted--; restored++; lp->spx_perturbed = TRUE; } else if(((lp->bb_level <= 1) || is_anti_degen(lp, ANTIDEGEN_DURINGBB)) && (((status == LOSTFEAS) && is_anti_degen(lp, ANTIDEGEN_LOSTFEAS)) || ((status == INFEASIBLE) && is_anti_degen(lp, ANTIDEGEN_INFEASIBLE)) || ((status == NUMFAILURE) && is_anti_degen(lp, ANTIDEGEN_NUMFAILURE)) || ((status == DEGENERATE) && is_anti_degen(lp, ANTIDEGEN_STALLING)))) { /* Allow up to .. consecutive relaxations for non-B&B phases */ if((tilted <= DEF_MAXRELAX) && /* Conventional recovery case,... */ !((tilted == 0) && (restored > DEF_MAXRELAX))) { /* but not iterating infeasibility */ /* Create working copy of ingoing bounds if this is the first perturbation */ if(tilted == 0) perturbed = BB; perturbed = create_BB(lp, perturbed, TRUE); /* Perturb/shift variable bounds; also make sure we rebase and recompute (no refactorization is necessary, since the basis is unchanged) */ #if 1 perturb_bounds(lp, perturbed, TRUE, TRUE, TRUE); #else perturb_bounds(lp, perturbed, TRUE, TRUE, FALSE); #endif impose_bounds(lp, perturbed->upbo, perturbed->lowbo); set_action(&lp->spx_action, ACTION_REBASE | ACTION_RECOMPUTE); BB->UBzerobased = FALSE; status = RUNNING; tilted++; lp->perturb_count++; lp->spx_perturbed = TRUE; if(lp->spx_trace) report(lp, DETAILED, "solve_LP: Starting bound relaxation #%d ('%s')\n", tilted, get_statustext(lp, status)); } else { if(lp->spx_trace) report(lp, DETAILED, "solve_LP: Relaxation limit exceeded in resolving infeasibility\n"); while((perturbed != NULL) && (perturbed != BB)) free_BB(&perturbed); perturbed = NULL; } } } /* Handle the different simplex outcomes */ if(status != OPTIMAL) { if(lp->bb_level <= 1) lp->bb_parentOF = lp->infinite; if((status == USERABORT) || (status == TIMEOUT)) { /* Construct the last feasible solution, if available */ if((lp->solutioncount == 0) && /* 30/01/08 added MIP_count test because in following situation thing were wrong: - The model contains integers - A break at first is set - A timeout is set - The timeout occurs before a first integer solution is found - When the timeout occurs, the simplex algorithm is in phase 2 and has a feasible (but non-integer) solution, but not optimal yet. If above situation occurs then a (sub-optimal) solution was returned while no integer solution isn't found yet at this time */ (MIP_count(lp) == 0) && ((lp->simplex_mode & (SIMPLEX_Phase2_PRIMAL | SIMPLEX_Phase2_DUAL)) > 0)) { lp->solutioncount++; construct_solution(lp, NULL); transfer_solution(lp, TRUE); } /* Return messages */ report(lp, NORMAL, "\nlp_solve optimization was stopped %s.\n", ((status == USERABORT) ? "by the user" : "due to time-out")); } else if(BB->varno == 0) report(lp, NORMAL, "The model %s\n", (status == UNBOUNDED) ? "is UNBOUNDED" : ((status == INFEASIBLE) ? "is INFEASIBLE" : "FAILED")); else { #ifdef Paranoia if((status != FATHOMED) && (status != INFEASIBLE)) report(lp, SEVERE, "spx_solve: Invalid return code %d during B&B\n", status); #endif /* If we fathomed a node due to an inferior OF having been detected, return infeasible */ if(status == FATHOMED) lp->spx_status = INFEASIBLE; } } else { /* ... there is a good solution */ construct_solution(lp, NULL); if((lp->bb_level <= 1) && (restored > 0)) report(lp, DETAILED, "%s numerics encountered; validate accuracy\n", (restored == 1) ? "Difficult" : "Severe"); /* Handle case where a user bound on the OF was found to have been set too aggressively, giving an infeasible model */ if(lp->spx_status != OPTIMAL) status = lp->spx_status; else if((lp->bb_totalnodes == 0) && (MIP_count(lp) > 0)) { if(lp->lag_status != RUNNING) { report(lp, NORMAL, "\nRelaxed solution " RESULTVALUEMASK " after %10.0f iter is B&B base.\n", lp->solution[0], (double) lp->total_iter); report(lp, NORMAL, " \n"); } if((lp->usermessage != NULL) && (lp->msgmask & MSG_LPOPTIMAL)) { REAL *best_solution = lp->best_solution; /* transfer_solution(lp, TRUE); */ lp->best_solution = lp->solution; lp->usermessage(lp, lp->msghandle, MSG_LPOPTIMAL); lp->best_solution = best_solution; } set_var_priority(lp); } /* Check if we have a numeric problem (an earlier version of this code used the absolute difference, but it is not robust for large-valued OFs) */ testOF = my_chsign(is_maxim(lp), my_reldiff(lp->solution[0], lp->real_solution)); if(testOF < -lp->epsprimal) { report(lp, DETAILED, "solve_LP: A MIP subproblem returned a value better than the base.\n"); status = INFEASIBLE; lp->spx_status = status; set_action(&lp->spx_action, ACTION_REBASE | ACTION_REINVERT | ACTION_RECOMPUTE); } else if(testOF < 0) /* Avoid problems later (could undo integer roundings, but usually Ok) */ lp->solution[0] = lp->real_solution; } /* status can have the following values: OPTIMAL, SUBOPTIMAL, TIMEOUT, USERABORT, PROCFAIL, UNBOUNDED and INFEASIBLE. */ return( status ); } /* solve_LP */ STATIC BBrec *findself_BB(BBrec *BB) { int varno = BB->varno, vartype = BB->vartype; BB = BB->parent; while((BB != NULL) && (BB->vartype != vartype) && (BB->varno != varno)) BB = BB->parent; return( BB ); } /* Function to determine the opportunity for variable fixing and bound tightening based on a previous best MILP solution and a variable's reduced cost at the current relaxation - inspired by Wolsley */ STATIC int rcfbound_BB(BBrec *BB, int varno, MYBOOL isINT, REAL *newbound, MYBOOL *isfeasible) { int i = FR; lprec *lp = BB->lp; REAL deltaRC, rangeLU, deltaOF, lowbo, upbo; /* Make sure we only accept non-basic variables */ if(lp->is_basic[varno]) return( i ); /* Make sure we only accept non-fixed variables */ lowbo = BB->lowbo[varno]; upbo = BB->upbo[varno]; rangeLU = upbo - lowbo; if(rangeLU > lp->epsprimal) { #if 1 /* v5.5 problematic - Gap between current node and the current best bound */ deltaOF = lp->rhs[0] - lp->bb_workOF; #elif 0 /* v6 less aggressive - Gap between current best bound and the relaxed problem */ deltaOF = my_chsign(is_maxim(lp), lp->real_solution) - lp->bb_workOF; #else /* v6 more aggressive - Gap between current node and the relaxed problem */ deltaOF = my_chsign(is_maxim(lp), lp->real_solution) - lp->rhs[0]; #endif deltaRC = my_chsign(!lp->is_lower[varno], lp->drow[varno]); /* Protect against divisions with tiny numbers and stray sign reversals of the reduced cost */ if(deltaRC < lp->epspivot) return( i ); deltaRC = deltaOF / deltaRC; /* Should always be a positive number! */ #ifdef Paranoia if(deltaRC <= 0) report(lp, SEVERE, "rcfbound_BB: A negative bound fixing level was encountered after node %.0f\n", (double) lp->bb_totalnodes); #endif /* Check if bound implied by the reduced cost is less than existing range */ if(deltaRC < rangeLU + lp->epsint) { if(lp->is_lower[varno]) { if(isINT) deltaRC = scaled_floor(lp, varno, unscaled_value(lp, deltaRC, varno)+lp->epsprimal, 1); upbo = lowbo + deltaRC; deltaRC = upbo; i = LE; /* Sets the upper bound */ } else { if(isINT) deltaRC = scaled_ceil(lp, varno, unscaled_value(lp, deltaRC, varno)+lp->epsprimal, 1); lowbo = upbo - deltaRC; deltaRC = lowbo; i = GE; /* Sets the lower bound */ } /* Check and set feasibility status */ if((isfeasible != NULL) && (upbo - lowbo < -lp->epsprimal)) *isfeasible = FALSE; /* Flag that we can fix the variable by returning the relation code negated */ else if(fabs(upbo - lowbo) < lp->epsprimal) i = -i; if(newbound != NULL) { my_roundzero(deltaRC, lp->epsprimal); *newbound = deltaRC; } } } return( i ); } STATIC MYBOOL findnode_BB(BBrec *BB, int *varno, int *vartype, int *varcus) { int countsossc, countnint, k, reasonmsg = MSG_NONE; REAL varsol; MYBOOL is_better = FALSE, is_equal = FALSE, is_feasible = TRUE; lprec *lp = BB->lp; /* Initialize result and return variables */ *varno = 0; *vartype = BB_REAL; *varcus = 0; countnint = 0; BB->nodestatus = lp->spx_status; BB->noderesult = lp->solution[0]; /* If this solution is worse than the best so far, this branch dies. If we can only have integer OF values, and we only need the first solution then the OF must be at least (unscaled) 1 better than the best so far */ if((lp->bb_limitlevel != 1) && (MIP_count(lp) > 0)) { /* Check that we don't have a limit on the recursion level; two versions supported: 1) Absolute B&B level (bb_limitlevel > 0), and 2) B&B level relative to the "B&B order" (bb_limitlevel < 0). */ countsossc = lp->sos_vars + lp->sc_vars; if((lp->bb_limitlevel > 0) && (lp->bb_level > lp->bb_limitlevel+countsossc)) return( FALSE ); else if((lp->bb_limitlevel < 0) && (lp->bb_level > 2*(lp->int_vars+countsossc)*abs(lp->bb_limitlevel))) { if(lp->bb_limitlevel == DEF_BB_LIMITLEVEL) report(lp, IMPORTANT, "findnode_BB: Default B&B limit reached at %d; optionally change strategy or limit.\n\n", lp->bb_level); return( FALSE ); } /* First initialize or update pseudo-costs from previous optimal solution */ if(BB->varno == 0) { varsol = lp->infinite; if((lp->int_vars+lp->sc_vars > 0) && (lp->bb_PseudoCost == NULL)) lp->bb_PseudoCost = init_pseudocost(lp, get_bb_rule(lp)); } else { varsol = lp->solution[BB->varno]; if( ((lp->int_vars > 0) && (BB->vartype == BB_INT)) || ((lp->sc_vars > 0) && (BB->vartype == BB_SC) && !is_int(lp, BB->varno-lp->rows)) ) update_pseudocost(lp->bb_PseudoCost, BB->varno-lp->rows, BB->vartype, BB->isfloor, varsol); } /* Make sure we don't have numeric problems (typically due to integer scaling) */ if((lp->bb_totalnodes > 0) && !bb_better(lp, OF_RELAXED, OF_TEST_WE)) { if(lp->bb_trace) report(lp, IMPORTANT, "findnode_BB: Simplex failure due to loss of numeric accuracy\n"); lp->spx_status = NUMFAILURE; return( FALSE ); } /* Abandon this branch if the solution is "worse" than a heuristically determined limit or the previous best MIP solution */ if(((lp->solutioncount == 0) && !bb_better(lp, OF_HEURISTIC, OF_TEST_BE)) || ((lp->solutioncount > 0) && (!bb_better(lp, OF_INCUMBENT | OF_DELTA, OF_TEST_BE | OF_TEST_RELGAP) || !bb_better(lp, OF_INCUMBENT | OF_DELTA, OF_TEST_BE)))) { return( FALSE ); } /* Collect violated SC variables (since they can also be real-valued); the approach is to get them out of the way, since a 0-value is assumed to be "cheap" */ if(lp->sc_vars > 0) { *varno = find_sc_bbvar(lp, &countnint); if(*varno > 0) *vartype = BB_SC; } /* Look among SOS variables if no SC candidate was found */ if((SOS_count(lp) > 0) && (*varno == 0)) { *varno = find_sos_bbvar(lp, &countnint, FALSE); if(*varno < 0) *varno = 0; else if(*varno > 0) *vartype = BB_SOS; } /* Then collect INTS that are not integer valued, and verify bounds */ if((lp->int_vars > 0) && (*varno == 0)) { *varno = find_int_bbvar(lp, &countnint, BB, &is_feasible); if(*varno > 0) { *vartype = BB_INT; if((countnint == 1) && !is_feasible) { BB->lastrcf = 0; return( FALSE ); } } } #if 1 /* peno */ /* Check if we have reached the depth limit for any individual variable (protects against infinite recursions of mainly integer variables) */ k = *varno-lp->rows; if((*varno > 0) && (lp->bb_limitlevel != 0) && (lp->bb_varactive[k] >= abs(lp->bb_limitlevel) /* abs(DEF_BB_LIMITLEVEL) */)) { /* if(!is_action(lp->nomessage, NOMSG_BBLIMIT)) {*/ /* report(lp, IMPORTANT, "findnode_BB: Reached B&B depth limit %d for variable %d; will not dive further.\n\n", lp->bb_varactive[k], k); */ /* set_action(&lp->nomessage, NOMSG_BBLIMIT); */ /* } */ return( FALSE ); } #endif /* Check if the current MIP solution is optimal; equal or better */ if(*varno == 0) { is_better = (MYBOOL) (lp->solutioncount == 0) || bb_better(lp, OF_INCUMBENT | OF_DELTA, OF_TEST_BT); #if 1 is_better &= bb_better(lp, OF_INCUMBENT | OF_DELTA, OF_TEST_BT | OF_TEST_RELGAP); #else /* Check if we can determine clear improvement */ is_better = (MYBOOL) (lp->solutioncount == 0) || (MYBOOL) ((lp->bb_deltaOF > 0) && (my_chsign(is_maxim(lp), lp->solution[0]-lp->best_solution[0]) < 0)); /* Apply gap-based improvement testing if the current solution is not clearly better */ if(!is_better) { is_better = bb_better(lp, OF_INCUMBENT | OF_DELTA, OF_TEST_BT); is_better |= bb_better(lp, OF_INCUMBENT | OF_DELTA, OF_TEST_BT | OF_TEST_RELGAP); } #endif is_equal = !is_better; if(is_equal) { if((lp->solutionlimit <= 0) || (lp->solutioncount < lp->solutionlimit)) { lp->solutioncount++; SETMIN(lp->bb_solutionlevel, lp->bb_level); reasonmsg = MSG_MILPEQUAL; } } /* Current solution is better */ else if(is_better) { /* Update grand total solution count and check if we should go from depth-first to best-first variable selection mode */ if(lp->bb_varactive != NULL) { lp->bb_varactive[0]++; if((lp->bb_varactive[0] == 1) && is_bb_mode(lp, NODE_DEPTHFIRSTMODE) && is_bb_mode(lp, NODE_DYNAMICMODE)) lp->bb_rule &= !NODE_DEPTHFIRSTMODE; } if(lp->bb_trace || ((lp->verbose >= NORMAL) && (lp->print_sol == FALSE) && (lp->lag_status != RUNNING))) { report(lp, IMPORTANT, "%s solution " RESULTVALUEMASK " after %10.0f iter, %9.0f nodes (gap %.1f%%)\n", (lp->bb_improvements == 0) ? "Feasible" : "Improved", lp->solution[0], (double) lp->total_iter, (double) lp->bb_totalnodes, 100.0*fabs(my_reldiff(lp->solution[0], lp->bb_limitOF))); } if(MIP_count(lp) > 0) { if(lp->bb_improvements == 0) reasonmsg = MSG_MILPFEASIBLE; else reasonmsg = MSG_MILPBETTER; } lp->bb_status = FEASFOUND; lp->bb_solutionlevel = lp->bb_level; lp->solutioncount = 1; lp->bb_improvements++; lp->bb_workOF = lp->rhs[0]; if(lp->bb_breakfirst || (!is_infinite(lp, lp->bb_breakOF) && bb_better(lp, OF_USERBREAK, OF_TEST_BE))) lp->bb_break = TRUE; } } } else { is_better = TRUE; lp->solutioncount = 1; } /* Transfer the successful solution vector */ if(is_better || is_equal) { #ifdef ParanoiaMIP if((lp->bb_level > 0) && (check_solution(lp, lp->columns, lp->solution, lp->orig_upbo, lp->orig_lowbo, lp->epssolution) != OPTIMAL)) { lp->solutioncount = 0; lp->spx_status = NUMFAILURE; lp->bb_status = lp->spx_status; lp->bb_break = TRUE; return( FALSE ); } #endif transfer_solution(lp, (MYBOOL) ((lp->do_presolve & PRESOLVE_LASTMASKMODE) != PRESOLVE_NONE)); if((MIP_count(lp) > 0) && (lp->bb_totalnodes > 0)) { if ((!construct_duals(lp)) || (is_presolve(lp, PRESOLVE_SENSDUALS) && (!construct_sensitivity_duals(lp) || !construct_sensitivity_obj(lp)) ) ) { } } if((reasonmsg != MSG_NONE) && (lp->msgmask & reasonmsg) && (lp->usermessage != NULL)) lp->usermessage(lp, lp->msghandle, reasonmsg); if(lp->print_sol != FALSE) { print_objective(lp); print_solution(lp, 1); } } /* Do tracing and determine if we have arrived at the estimated lower MIP limit */ *varcus = countnint; if(MIP_count(lp) > 0) { if((countnint == 0) && (lp->solutioncount == 1) && (lp->solutionlimit == 1) && (bb_better(lp, OF_DUALLIMIT, OF_TEST_BE) || bb_better(lp, OF_USERBREAK, OF_TEST_BE | OF_TEST_RELGAP))) { lp->bb_break = (MYBOOL) (countnint == 0); return( FALSE ); } else if(lp->bb_level > 0) { #ifdef MIPboundWithOF if((lp->constraintOF > 0) && (countnint == 0)) set_rh(lp, lp->constraintOF, lp->solution[0] + my_chsign(!is_maxim(lp), lp->bb_deltaOF)); #endif if(lp->spx_trace) report(lp, DETAILED, "B&B level %5d OPT %16s value " RESULTVALUEMASK "\n", lp->bb_level, (*varno) ? " " : "INT", lp->solution[0]); } return( (MYBOOL) (*varno > 0)); } else return( FALSE ); } STATIC int solve_BB(BBrec *BB) { int K, status; lprec *lp = BB->lp; /* Protect against infinite recursions do to integer rounding effects */ status = PROCFAIL; /* Shortcut variables, set default bounds */ K = BB->varno; /* Load simple MIP bounds */ if(K > 0) { /* Update cuts, if specified */ updatecuts_BB(lp); /* BRANCH_FLOOR: Force the variable to be smaller than the B&B upper bound */ if(BB->isfloor) modifyUndoLadder(lp->bb_upperchange, K, BB->upbo, BB->UPbound); /* BRANCH_CEILING: Force the variable to be greater than the B&B lower bound */ else modifyUndoLadder(lp->bb_lowerchange, K, BB->lowbo, BB->LObound); /* Update MIP node count */ BB->nodessolved++; } /* Solve! */ status = solve_LP(lp, BB); /* Do special feasibility assessment of high order SOS'es */ #if 1 if((status == OPTIMAL) && (BB->vartype == BB_SOS) && !SOS_is_feasible(lp->SOS, 0, lp->solution)) status = INFEASIBLE; #endif return( status ); } /* Routine to compute a "strong" pseudo-cost update for a node */ STATIC MYBOOL strongbranch_BB(lprec *lp, BBrec *BB, int varno, int vartype, int varcus) { MYBOOL success = FALSE; int i; BBrec *strongBB; /* Create new B&B level and solve each of the branches */ lp->is_strongbranch = TRUE; push_basis(lp, lp->var_basic, lp->is_basic, lp->is_lower); strongBB = push_BB(lp, BB, lp->rows+varno, vartype, varcus); if(strongBB == BB) return( success ); do { /* Solve incremental problem to local optimality */ lp->bb_strongbranches++; /* set_action(&lp->spx_action, ACTION_REBASE | ACTION_RECOMPUTE); */ if(solve_BB(strongBB) == OPTIMAL) { /* Update result indicator*/ success |= 1 << strongBB->isfloor; /* Compute new count of non-ints */ strongBB->lastvarcus = 0; for(i = 1; i <= lp->columns; i++) { if(is_int(lp, i) && !solution_is_int(lp, lp->rows+i, FALSE)) strongBB->lastvarcus++; } /* Perform the pseudo-cost update */ update_pseudocost(lp->bb_PseudoCost, varno, strongBB->vartype, strongBB->isfloor, lp->solution[strongBB->varno]); } } while(nextbranch_BB(strongBB)); strongBB = pop_BB(strongBB); if(strongBB != BB) report(lp, SEVERE, "strongbranch_BB: Invalid bound settings restored for variable %d\n", varno); pop_basis(lp, TRUE); set_action(&lp->spx_action, ACTION_REBASE | ACTION_REINVERT | ACTION_RECOMPUTE); lp->is_strongbranch = FALSE; return( success ); } /* Future functions */ STATIC MYBOOL pre_BB(lprec *lp) { return( TRUE ); } STATIC MYBOOL post_BB(lprec *lp) { return( TRUE ); } /* This is the non-recursive B&B driver routine - beautifully simple, yet so subtle! */ STATIC int run_BB(lprec *lp) { BBrec *currentBB; int varno, vartype, varcus, prevsolutions; int status = NOTRUN; /* Initialize */ pre_BB(lp); prevsolutions = lp->solutioncount; #ifdef UseMilpSlacksRCF /* Check if we should include ranged constraints */ varno = lp->sum; #else varno = lp->columns; #endif lp->bb_upperchange = createUndoLadder(lp, varno, 2*MIP_count(lp)); lp->bb_lowerchange = createUndoLadder(lp, varno, 2*MIP_count(lp)); lp->rootbounds = currentBB = push_BB(lp, NULL, 0, BB_REAL, 0); /* Perform the branch & bound loop */ while(lp->bb_level > 0) { status = solve_BB(currentBB); #if 0 if((lp->bb_level == 1) && (MIP_count(lp) > 0)) { if(status == RUNNING) ; /* Check if there was an integer solution of an aborted model */ else if((status == SUBOPTIMAL) && (lp->solutioncount == 1) && findnode_BB(currentBB, &varno, &vartype, &varcus)) status = USERABORT; } #endif if((status == OPTIMAL) && findnode_BB(currentBB, &varno, &vartype, &varcus)) currentBB = push_BB(lp, currentBB, varno, vartype, varcus); else while((lp->bb_level > 0) && !nextbranch_BB(currentBB)) currentBB = pop_BB(currentBB); } /* Finalize */ freeUndoLadder(&(lp->bb_upperchange)); freeUndoLadder(&(lp->bb_lowerchange)); /* Check if we should adjust status */ if(lp->solutioncount > prevsolutions) { if((status == PROCBREAK) || (status == USERABORT) || (status == TIMEOUT) || userabort(lp, -1)) status = SUBOPTIMAL; else status = OPTIMAL; if(lp->bb_totalnodes > 0) lp->spx_status = OPTIMAL; } post_BB(lp); return( status ); } MSVMpack1.2/lp_solve_5.5/lp_MPS.c0000664000175000017500000016377011250514734015454 0ustar lauerlauer #include #include #include #include "commonlib.h" #include "lp_lib.h" #include "lp_scale.h" #include "lp_report.h" #include "lp_MPS.h" #ifdef FORTIFY # include "lp_fortify.h" #endif /* Define buffer-size controled function mapping */ # if defined _MSC_VER # define vsnprintf _vsnprintf # endif /* MPS file input and output routines for lp_solve */ /* ------------------------------------------------------------------------- */ /* A: MPS format was named after an early IBM LP product and has emerged as a de facto standard ASCII medium among most of the commercial LP codes. Essentially all commercial LP codes accept this format, but if you are using public domain software and have MPS files, you may need to write your own reader routine for this. It's not too hard. The main things to know about MPS format are that it is column oriented (as opposed to entering the model as equations), and everything (variables, rows, etc.) gets a name. MPS format is described in more detail in Murtagh's book, referenced in another section. Also, ftp://softlib.cs.rice.edu/pub/miplib/mps_format is a nice short introduction. exports MPS is an old format, so it is set up as though you were using punch cards, and is not free format. Fields start in column 1, 5, 15, 25, 40 and 50. Sections of an MPS file are marked by so-called header cards, which are distinguished by their starting in column 1. Although it is typical to use upper-case throughout the file (like I said, MPS has long historical roots), many MPS-readers will accept mixed-case for anything except the header cards, and some allow mixed-case anywhere. The names that you choose for the individual entities (constraints or variables) are not important to the solver; you should pick names that are meaningful to you, or will be easy for a post-processing code to read. Here is a little sample model written in MPS format (explained in more detail below): NAME TESTPROB ROWS N COST L LIM1 G LIM2 E MYEQN COLUMNS XONE COST 1 LIM1 1 XONE LIM2 1 YTWO COST 4 LIM1 1 YTWO MYEQN -1 ZTHREE COST 9 LIM2 1 ZTHREE MYEQN 1 RHS RHS1 LIM1 5 LIM2 10 RHS1 MYEQN 7 BOUNDS UP BND1 XONE 4 LO BND1 YTWO -1 UP BND1 YTWO 1 ENDATA means: Optimize COST: XONE + 4 YTWO + 9 ZTHREE Subject To LIM1: XONE + YTWO <= 5 LIM2: XONE + ZTHREE >= 10 MYEQN: - YTWO + ZTHREE = 7 Bounds 0 <= XONE <= 4 -1 <= YTWO <= 1 End */ /* copy a MPS name, only trailing spaces are removed. In MPS, names can have embedded spaces! */ STATIC void namecpy(char *into, char *from) { int i; /* copy at most 8 characters of from, stop at end of string or newline */ for(i = 0; (from[i] != '\0') && (from[i] != '\n') && (from[i] != '\r') && (i < 8); i++) into[i] = from[i]; /* end with end of string */ into[i] = '\0'; /* remove trailing spaces, if any */ for(i--; (i >= 0) && (into[i] == ' '); i--) into[i] = '\0'; } /* scan an MPS line, and pick up the information in the fields that are present */ /* scan_line for fixed MPS format */ STATIC int scan_lineFIXED(lprec *lp, int section, char* line, char *field1, char *field2, char *field3, double *field4, char *field5, double *field6) { int items = 0, line_len; char buf[16], *ptr1, *ptr2; line_len = (int) strlen(line); while ((line_len) && ((line[line_len-1] == '\n') || (line[line_len-1] == '\r') || (line[line_len-1] == ' '))) line_len--; if(line_len >= 1) { /* spaces or N/L/G/E or UP/LO */ strncpy(buf, line, 4); buf[4] = '\0'; sscanf(buf, "%s", field1); items++; } else field1[0] = '\0'; line += 4; if(line_len >= 5) { /* name */ if (line[-1] != ' ') { report(lp, IMPORTANT, "MPS_readfile: invalid data card; column 4 must be blank\n"); return(-1); } namecpy(field2, line); items++; } else field2[0] = '\0'; line += 10; if(line_len >= 14) { /* name */ if (line[-1] != ' ' || line[-2] != ' ') { report(lp, IMPORTANT, "MPS_readfile: invalid data card; columns 13-14 must be blank\n"); return(-1); } namecpy(field3, line); items++; } else field3[0] = '\0'; line += 10; if(line_len >= 25) { /* number */ if (line[-1] != ' ' || line[-2] != ' ') { report(lp, IMPORTANT, "MPS_readfile: invalid data card; columns 23-24 must be blank\n"); return(-1); } strncpy(buf, line, 15); buf[15] = '\0'; for(ptr1 = ptr2 = buf; ; ptr1++) if(!isspace((unsigned char) *ptr1)) if((*(ptr2++) = *ptr1) == 0) break; /* *field4 = atof(buf); */ *field4 = strtod(buf, &ptr1); if(*ptr1) { report(lp, IMPORTANT, "MPS_readfile: invalid number in columns 25-36 \n"); return(-1); } items++; } else *field4 = 0; line += 15; if(line_len >= 40) { /* name */ if (line[-1] != ' ' || line[-2] != ' ' || line[-3] != ' ') { report(lp, IMPORTANT, "MPS_readfile: invalid data card; columns 37-39 must be blank\n"); return(-1); } namecpy(field5, line); items++; } else field5[0] = '\0'; line += 10; if(line_len >= 50) { /* number */ if (line[-1] != ' ' || line[-2] != ' ') { report(lp, IMPORTANT, "MPS_readfile: invalid data card; columns 48-49 must be blank\n"); return(-1); } strncpy(buf, line, 15); buf[15] = '\0'; for(ptr1 = ptr2 = buf; ; ptr1++) if(!isspace((unsigned char) *ptr1)) if((*(ptr2++) = *ptr1) == 0) break; /* *field6 = atof(buf); */ *field6 = strtod(buf, &ptr1); if(*ptr1) { report(lp, IMPORTANT, "MPS_readfile: invalid number in columns 50-61 \n"); return(-1); } items++; } else *field6 = 0; return(items); } STATIC int spaces(char *line, int line_len) { int l; char *line1 = line; while (*line1 == ' ') line1++; l = (int) (line1 - line); if (line_len < l) l = line_len; return(l); } STATIC int lenfield(char *line, int line_len) { int l; char *line1 = line; while ((*line1) && (*line1 != ' ')) line1++; l = (int) (line1 - line); if (line_len < l) l = line_len; return(l); } /* scan_line for fixed MPS format */ STATIC int scan_lineFREE(lprec *lp, int section, char* line, char *field1, char *field2, char *field3, double *field4, char *field5, double *field6) { int items = 0, line_len, len; char buf[256], *ptr1, *ptr2; line_len = (int) strlen(line); while ((line_len) && ((line[line_len-1] == '\n') || (line[line_len-1] == '\r') || (line[line_len-1] == ' '))) line_len--; len = spaces(line, line_len); line += len; line_len -= len; if ((section == MPSCOLUMNS) || (section == MPSRHS) || (section == MPSRANGES)) { field1[0] = '\0'; items++; } else { len = lenfield(line, line_len); if(line_len >= 1) { /* spaces or N/L/G/E or UP/LO */ strncpy(buf, line, len); buf[len] = '\0'; sscanf(buf, "%s", field1); if(section == MPSBOUNDS) { for(ptr1 = field1; *ptr1; ptr1++) *ptr1=(char)toupper(*ptr1); } items++; } else field1[0] = '\0'; line += len; line_len -= len; len = spaces(line, line_len); line += len; line_len -= len; } len = lenfield(line, line_len); if(line_len >= 1) { /* name */ strncpy(field2, line, len); field2[len] = '\0'; items++; } else field2[0] = '\0'; line += len; line_len -= len; len = spaces(line, line_len); line += len; line_len -= len; len = lenfield(line, line_len); if(line_len >= 1) { /* name */ strncpy(field3, line, len); field3[len] = '\0'; items++; } else field3[0] = '\0'; line += len; line_len -= len; len = spaces(line, line_len); line += len; line_len -= len; if (*field3) { if((section == MPSCOLUMNS) && (strcmp(field3, "'MARKER'") == 0)) { *field4 = 0; items++; ptr1 = field3; } else if((section == MPSBOUNDS) && ((strcmp(field1, "FR") == 0) || (strcmp(field1, "MI") == 0) || (strcmp(field1, "PL") == 0) || (strcmp(field1, "BV") == 0))) /* field3 *is* the variable name */; else { /* Some free MPS formats allow that field 2 is not provided after the first time. The fieldname is then the same as the the defined field the line before. In that case field2 shifts to field3, field1 shifts to field 2. This situation is tested by checking if field3 is numerical AND there are an even number of fields after. */ char *line1 = line; int line_len1 = line_len; int items1 = 0; while (line_len1 > 0) { len = lenfield(line1, line_len1); if (len > 0) { line1 += len; line_len1 -= len; items1++; } len = spaces(line1, line_len1); line1 += len; line_len1 -= len; } if ((items1 % 2) == 0) { *field4 = strtod(field3, &ptr1); if(*ptr1 == 0) { strcpy(field3, field2); if ((section == MPSROWS) || (section == MPSBOUNDS) /* || (section == MPSSOS) */) *field2 = 0; else { strcpy(field2, field1); *field1 = 0; } items++; } else ptr1 = NULL; } else ptr1 = NULL; } } else { ptr1 = NULL; if((section == MPSBOUNDS) && ((strcmp(field1, "FR") == 0) || (strcmp(field1, "MI") == 0) || (strcmp(field1, "PL") == 0) || (strcmp(field1, "BV") == 0))) { strcpy(field3, field2); *field2 = 0; items++; } } if(ptr1 == NULL) { len = lenfield(line, line_len); if(line_len >= 1) { /* number */ strncpy(buf, line, len); buf[len] = '\0'; for(ptr1 = ptr2 = buf; ; ptr1++) if(!isspace((unsigned char) *ptr1)) if((*(ptr2++) = *ptr1) == 0) break; /* *field4 = atof(buf); */ *field4 = strtod(buf, &ptr1); if(*ptr1) return(-1); items++; } else *field4 = 0; line += len; line_len -= len; len = spaces(line, line_len); line += len; line_len -= len; } len = lenfield(line, line_len); if(line_len >= 1) { /* name */ strncpy(field5, line, len); field5[len] = '\0'; items++; } else field5[0] = '\0'; line += len; line_len -= len; len = spaces(line, line_len); line += len; line_len -= len; len = lenfield(line, line_len); if(line_len >= 1) { /* number */ strncpy(buf, line, len); buf[len] = '\0'; for(ptr1 = ptr2 = buf; ; ptr1++) if(!isspace((unsigned char) *ptr1)) if((*(ptr2++) = *ptr1) == 0) break; /* *field6 = atof(buf); */ *field6 = strtod(buf, &ptr1); if(*ptr1) return(-1); items++; } else *field6 = 0; if((section == MPSSOS) && (items == 2)) { strcpy(field3, field2); strcpy(field2, field1); *field1 = 0; } if((section != MPSOBJNAME) && (section != MPSBOUNDS)) { for(ptr1 = field1; *ptr1; ptr1++) *ptr1=(char)toupper(*ptr1); } return(items); } STATIC int addmpscolumn(lprec *lp, MYBOOL Int_section, int typeMPS, MYBOOL *Column_ready, int *count, REAL *Last_column, int *Last_columnno, char *Last_col_name) { int ok = TRUE; if (*Column_ready) { ok = add_columnex(lp, *count, Last_column, Last_columnno); if (ok) { ok = set_col_name(lp, lp->columns, Last_col_name); } if (ok) { set_int(lp, lp->columns, Int_section); if ((Int_section) && (typeMPS & MPSIBM)) set_bounds(lp, lp->columns, 10.0 / DEF_INFINITE, DEF_INFINITE / 10.0); } } *Column_ready = FALSE; *count = 0; return(ok); } #if 0 STATIC MYBOOL appendmpsitem(int *count, int rowIndex[], REAL rowValue[]) { int i = *count; if(rowValue[i] == 0) return( FALSE ); while((i > 0) && (rowIndex[i] < rowIndex[i-1])) { swapINT (rowIndex+i, rowIndex+i-1); swapREAL(rowValue+i, rowValue+i-1); i--; } (*count)++; return( TRUE ); } #endif STATIC MYBOOL appendmpsitem(int *count, int rowIndex[], REAL rowValue[]) { int i = *count; /* Check for non-negativity of the index */ if(rowIndex[i] < 0) return( FALSE ); /* Move the element so that the index list is sorted ascending */ while((i > 0) && (rowIndex[i] < rowIndex[i-1])) { swapINT (rowIndex+i, rowIndex+i-1); swapREAL(rowValue+i, rowValue+i-1); i--; } /* Add same-indexed items (which is rarely encountered), and shorten the list */ if((i < *count) && (rowIndex[i] == rowIndex[i+1])) { int ii = i + 1; rowValue[i] += rowValue[ii]; (*count)--; while(ii < *count) { rowIndex[ii] = rowIndex[ii+1]; rowValue[ii] = rowValue[ii+1]; ii++; } } /* Update the count and return */ (*count)++; return( TRUE ); } MYBOOL MPS_readfile(lprec **newlp, char *filename, int typeMPS, int verbose) { MYBOOL status = FALSE; FILE *fpin; fpin = fopen(filename, "r"); if(fpin != NULL) { status = MPS_readhandle(newlp, fpin, typeMPS, verbose); fclose(fpin); } return( status ); } static int __WINAPI MPS_input(void *fpin, char *buf, int max_size) { return(fgets(buf, max_size, (FILE *) fpin) != NULL); } MYBOOL __WINAPI MPS_readhandle(lprec **newlp, FILE *filehandle, int typeMPS, int verbose) { return(MPS_readex(newlp, (void *) filehandle, MPS_input, typeMPS, verbose)); } MYBOOL __WINAPI MPS_readex(lprec **newlp, void *userhandle, read_modeldata_func read_modeldata, int typeMPS, int verbose) { char field1[BUFSIZ], field2[BUFSIZ], field3[BUFSIZ], field5[BUFSIZ], line[BUFSIZ], tmp[BUFSIZ], Last_col_name[BUFSIZ], probname[BUFSIZ], OBJNAME[BUFSIZ], *ptr; int items, row, Lineno, var, section = MPSUNDEF, variant = 0, NZ = 0, SOS = 0; MYBOOL Int_section, Column_ready, Column_ready1, Unconstrained_rows_found = FALSE, OF_found = FALSE, CompleteStatus = FALSE; double field4, field6; REAL *Last_column = NULL; int count = 0, *Last_columnno = NULL; int OBJSENSE = ROWTYPE_EMPTY; lprec *lp; int (*scan_line)(lprec *lp, int section, char* line, char *field1, char *field2, char *field3, double *field4, char *field5, double *field6); if(newlp == NULL) return( CompleteStatus ); else if(*newlp == NULL) lp = make_lp(0, 0); else lp = *newlp; if((typeMPS & MPSFIXED) == MPSFIXED) scan_line = scan_lineFIXED; else if((typeMPS & MPSFREE) == MPSFREE) scan_line = scan_lineFREE; else { report(lp, IMPORTANT, "MPS_readfile: Unrecognized MPS line type.\n"); if (*newlp == NULL) delete_lp(lp); return( CompleteStatus ); } if (lp != NULL) { lp->source_is_file = TRUE; lp->verbose = verbose; strcpy(Last_col_name, ""); strcpy(OBJNAME, ""); Int_section = FALSE; Column_ready = FALSE; Lineno = 0; /* let's initialize line to all zero's */ MEMCLEAR(line, BUFSIZ); while(read_modeldata(userhandle, line, BUFSIZ - 1)) { Lineno++; for(ptr = line; (*ptr) && (isspace((unsigned char) *ptr)); ptr++); /* skip lines which start with "*", they are comment */ if((line[0] == '*') || (*ptr == 0) || (*ptr == '\n') || (*ptr == '\r')) { report(lp, FULL, "Comment on line %d: %s", Lineno, line); continue; } report(lp, FULL, "Line %6d: %s", Lineno, line); /* first check for "special" lines: NAME, ROWS, BOUNDS .... */ /* this must start in the first position of line */ if(line[0] != ' ') { sscanf(line, "%s", tmp); if(strcmp(tmp, "NAME") == 0) { section = MPSNAME; *probname = 0; sscanf(line, "NAME %s", probname); if (!set_lp_name(lp, probname)) break; } else if(((typeMPS & MPSFREE) == MPSFREE) && (strcmp(tmp, "OBJSENSE") == 0)) { section = MPSOBJSENSE; report(lp, FULL, "Switching to OBJSENSE section\n"); } else if(((typeMPS & MPSFREE) == MPSFREE) && (strcmp(tmp, "OBJNAME") == 0)) { section = MPSOBJNAME; report(lp, FULL, "Switching to OBJNAME section\n"); } else if(strcmp(tmp, "ROWS") == 0) { section = MPSROWS; report(lp, FULL, "Switching to ROWS section\n"); } else if(strcmp(tmp, "COLUMNS") == 0) { allocREAL(lp, &Last_column, lp->rows + 1, TRUE); allocINT(lp, &Last_columnno, lp->rows + 1, TRUE); count = 0; if ((Last_column == NULL) || (Last_columnno == NULL)) break; section = MPSCOLUMNS; report(lp, FULL, "Switching to COLUMNS section\n"); } else if(strcmp(tmp, "RHS") == 0) { if (!addmpscolumn(lp, Int_section, typeMPS, &Column_ready, &count, Last_column, Last_columnno, Last_col_name)) break; section = MPSRHS; report(lp, FULL, "Switching to RHS section\n"); } else if(strcmp(tmp, "BOUNDS") == 0) { section = MPSBOUNDS; report(lp, FULL, "Switching to BOUNDS section\n"); } else if(strcmp(tmp, "RANGES") == 0) { section = MPSRANGES; report(lp, FULL, "Switching to RANGES section\n"); } else if((strcmp(tmp, "SOS") == 0) || (strcmp(tmp, "SETS") == 0)) { section = MPSSOS; if(strcmp(tmp, "SOS") == 0) variant = 0; else variant = 1; report(lp, FULL, "Switching to %s section\n", tmp); } else if(strcmp(tmp, "ENDATA") == 0) { report(lp, FULL, "Finished reading MPS file\n"); CompleteStatus = TRUE; break; } else { /* line does not start with space and does not match above */ report(lp, IMPORTANT, "Unrecognized MPS line %d: %s\n", Lineno, line); break; } } else { /* normal line, process */ items = scan_line(lp, section, line, field1, field2, field3, &field4, field5, &field6); if(items < 0){ report(lp, IMPORTANT, "Syntax error on line %d: %s\n", Lineno, line); break; } switch(section) { case MPSNAME: report(lp, IMPORTANT, "Error, extra line under NAME line\n"); break; case MPSOBJSENSE: if(OBJSENSE != ROWTYPE_EMPTY) { report(lp, IMPORTANT, "Error, extra line under OBJSENSE line\n"); break; } if((strcmp(field1, "MAXIMIZE") == 0) || (strcmp(field1, "MAX") == 0)) { OBJSENSE = ROWTYPE_OFMAX; set_maxim(lp); } else if((strcmp(field1, "MINIMIZE") == 0) || (strcmp(field1, "MIN") == 0)) { OBJSENSE = ROWTYPE_OFMIN; set_minim(lp); } else { report(lp, SEVERE, "Unknown OBJSENSE direction '%s' on line %d\n", field1, Lineno); break; } continue; case MPSOBJNAME: if(*OBJNAME) { report(lp, IMPORTANT, "Error, extra line under OBJNAME line\n"); break; } strcpy(OBJNAME, field1); continue; /* Process entries in the ROWS section */ case MPSROWS: /* field1: rel. operator; field2: name of constraint */ report(lp, FULL, "Row %5d: %s %s\n", lp->rows + 1, field1, field2); if(strcmp(field1, "N") == 0) { if((*OBJNAME) && (strcmp(field2, OBJNAME))) /* Ignore this objective name since it is not equal to the OBJNAME name */; else if(!OF_found) { /* take the first N row as OF, ignore others */ if (!set_row_name(lp, 0, field2)) break; OF_found = TRUE; } else if(!Unconstrained_rows_found) { report(lp, IMPORTANT, "Unconstrained row %s ignored\n", field2); report(lp, IMPORTANT, "Further messages of this kind will be suppressed\n"); Unconstrained_rows_found = TRUE; } } else if(strcmp(field1, "L") == 0) { if ((!str_add_constraint(lp, "" ,LE ,0)) || (!set_row_name(lp, lp->rows, field2))) break; } else if(strcmp(field1, "G") == 0) { if ((!str_add_constraint(lp, "" ,GE ,0)) || (!set_row_name(lp, lp->rows, field2))) break; } else if(strcmp(field1, "E") == 0) { if ((!str_add_constraint(lp, "",EQ ,0)) || (!set_row_name(lp, lp->rows, field2))) break; } else { report(lp, SEVERE, "Unknown relation code '%s' on line %d\n", field1, Lineno); break; } continue; /* Process entries in the COLUMNS section */ case MPSCOLUMNS: /* field2: variable; field3: constraint; field4: coef */ /* optional: field5: constraint; field6: coef */ report(lp, FULL, "Column %4d: %s %s %g %s %g\n", lp->columns + 1, field2, field3, field4, field5, field6); if((items == 4) || (items == 5) || (items == 6)) { if (NZ == 0) strcpy(Last_col_name, field2); else if(*field2) { Column_ready1 = (MYBOOL) (strcmp(field2, Last_col_name) != 0); if(Column_ready1) { if (find_var(lp, field2, FALSE) >= 0) { report(lp, SEVERE, "Variable name (%s) is already used!\n", field2); break; } if(Column_ready) { /* Added ability to handle non-standard "same as above" column name */ if (addmpscolumn(lp, Int_section, typeMPS, &Column_ready, &count, Last_column, Last_columnno, Last_col_name)) { strcpy(Last_col_name, field2); NZ = 0; } else break; } } } if(items == 5) { /* there might be an INTEND or INTORG marker */ /* look for " 'MARKER' 'INTORG'" or " 'MARKER' 'INTEND'" */ if(strcmp(field3, "'MARKER'") != 0) break; if(strcmp(field5, "'INTORG'") == 0) { Int_section = TRUE; report(lp, FULL, "Switching to integer section\n"); } else if(strcmp(field5, "'INTEND'") == 0) { Int_section = FALSE; report(lp, FULL, "Switching to non-integer section\n"); } else report(lp, IMPORTANT, "Unknown marker (ignored) at line %d: %s\n", Lineno, field5); } else if((row = find_row(lp, field3, Unconstrained_rows_found)) >= 0) { if(row > lp->rows) report(lp, CRITICAL, "Invalid row %s encountered in the MPS file\n", field3); Last_columnno[count] = row; Last_column[count] = (REAL)field4; if(appendmpsitem(&count, Last_columnno, Last_column)) { NZ++; Column_ready = TRUE; } } } if(items == 6) { if((row = find_row(lp, field5, Unconstrained_rows_found)) >= 0) { if(row > lp->rows) report(lp, CRITICAL, "Invalid row %s encountered in the MPS file\n", field5); Last_columnno[count] = row; Last_column[count] = (REAL)field6; if(appendmpsitem(&count, Last_columnno, Last_column)) { NZ++; Column_ready = TRUE; } } } if((items < 4) || (items > 6)) { /* Wrong! */ report(lp, CRITICAL, "Wrong number of items (%d) in COLUMNS section (line %d)\n", items, Lineno); break; } continue; /* Process entries in the RHS section */ /* field2: uninteresting name; field3: constraint name */ /* field4: value */ /* optional: field5: constraint name; field6: value */ case MPSRHS: report(lp, FULL, "RHS line: %s %s %g %s %g\n", field2, field3, field4, field5, field6); if((items != 4) && (items != 6)) { report(lp, CRITICAL, "Wrong number of items (%d) in RHS section line %d\n", items, Lineno); break; } if((row = find_row(lp, field3, Unconstrained_rows_found)) >= 0) { if ((row == 0) && ((typeMPS & MPSNEGOBJCONST) == MPSNEGOBJCONST)) field4 = -field4; set_rh(lp, row, (REAL)field4); } if(items == 6) { if((row = find_row(lp, field5, Unconstrained_rows_found)) >= 0) { if ((row == 0) && ((typeMPS & MPSNEGOBJCONST) == MPSNEGOBJCONST)) field6 = -field6; set_rh(lp, row, (REAL)field6); } } continue; /* Process entries in the BOUNDS section */ /* field1: bound type; field2: uninteresting name; */ /* field3: variable name; field4: value */ case MPSBOUNDS: report(lp, FULL, "BOUNDS line: %s %s %s %g\n", field1, field2, field3, field4); var = find_var(lp, field3, FALSE); if(var < 0){ /* bound on undefined var in COLUMNS section ... */ Column_ready = TRUE; if (!addmpscolumn(lp, FALSE, typeMPS, &Column_ready, &count, Last_column, Last_columnno, field3)) break; Column_ready = TRUE; var = find_var(lp, field3, TRUE); } if(var < 0) /* undefined var and could add ... */; else if(strcmp(field1, "UP") == 0) { /* upper bound */ /* if(!set_bounds(lp, var, get_lowbo(lp, var), field4)) */ if(!set_upbo(lp, var, field4)) break; } else if(strcmp(field1, "SC") == 0) { /* upper bound */ if(field4 == 0) field4 = lp->infinite; /* if(!set_bounds(lp, var, get_lowbo(lp, var), field4)) */ if(!set_upbo(lp, var, field4)) break; set_semicont(lp, var, TRUE); } else if(strcmp(field1, "SI") == 0) { /* upper bound */ if(field4 == 0) field4 = lp->infinite; /* if(!set_bounds(lp, var, get_lowbo(lp, var), field4)) */ if(!set_upbo(lp, var, field4)) break; set_int(lp, var, TRUE); set_semicont(lp, var, TRUE); } else if(strcmp(field1, "LO") == 0) { /* lower bound */ /* if(!set_bounds(lp, var, field4, get_upbo(lp, var))) */ if(!set_lowbo(lp, var, field4)) break; } else if(strcmp(field1, "PL") == 0) { /* plus-ranged variable */ /* if(!set_bounds(lp, var, get_lowbo(lp, var), lp->infinite)) */ if(!set_upbo(lp, var, lp->infinite)) break; } else if(strcmp(field1, "MI") == 0) { /* minus-ranged variable */ /* if(!set_bounds(lp, var, -lp->infinite, get_upbo(lp, var))) */ if(!set_lowbo(lp, var, -lp->infinite)) break; } else if(strcmp(field1, "FR") == 0) { /* free variable */ set_unbounded(lp, var); } else if(strcmp(field1, "FX") == 0) { /* fixed, upper _and_ lower */ if(!set_bounds(lp, var, field4, field4)) break; } else if(strcmp(field1, "BV") == 0) { /* binary variable */ set_binary(lp, var, TRUE); } /* AMPL bounds type UI and LI added by E.Imamura (CRIEPI) */ else if(strcmp(field1, "UI") == 0) { /* upper bound for integer variable */ /* if(!set_bounds(lp, var, get_lowbo(lp, var), field4)) */ if(!set_upbo(lp, var, field4)) break; set_int(lp, var, TRUE); } else if(strcmp(field1, "LI") == 0) { /* lower bound for integer variable - corrected by KE */ /* if(!set_bounds(lp, var, field4, get_upbo(lp, var))) */ if(!set_lowbo(lp, var, field4)) break; set_int(lp, var, TRUE); } else { report(lp, CRITICAL, "BOUND type %s on line %d is not supported", field1, Lineno); break; } continue; /* Process entries in the BOUNDS section */ /* We have to implement the following semantics: D. The RANGES section is for constraints of the form: h <= constraint <= u . The range of the constraint is r = u - h . The value of r is specified in the RANGES section, and the value of u or h is specified in the RHS section. If b is the value entered in the RHS section, and r is the value entered in the RANGES section, then u and h are thus defined: row type sign of r h u ---------------------------------------------- G + or - b b + |r| L + or - b - |r| b E + b b + |r| E - b - |r| b */ /* field2: uninteresting name; field3: constraint name */ /* field4: value */ /* optional: field5: constraint name; field6: value */ case MPSRANGES: report(lp, FULL, "RANGES line: %s %s %g %s %g", field2, field3, field4, field5, field6); if((items != 4) && (items != 6)) { report(lp, CRITICAL, "Wrong number of items (%d) in RANGES section line %d", items, Lineno); break; } if((row = find_row(lp, field3, Unconstrained_rows_found)) >= 0) { /* Determine constraint type */ if(fabs(field4) >= lp->infinite) { report(lp, IMPORTANT, "Warning, Range for row %s >= infinity (value %g) on line %d, ignored", field3, field4, Lineno); } else if(field4 == 0) { /* Change of a GE or LE to EQ */ if(lp->orig_upbo[row] != 0) set_constr_type(lp, row, EQ); } else if(is_chsign(lp, row)) { /* GE */ lp->orig_upbo[row] = fabs(field4); } else if((lp->orig_upbo[row] == 0) && (field4 >= 0)) { /* EQ with positive sign of r value */ set_constr_type(lp, row, GE); lp->orig_upbo[row] = field4; } else if(lp->orig_upbo[row] == lp->infinite) { /* LE */ lp->orig_upbo[row] = fabs(field4); } else if((lp->orig_upbo[row] == 0) && (field4 < 0)) { /* EQ with negative sign of r value */ set_constr_type(lp, row, LE); lp->orig_upbo[row] = my_flipsign(field4); } else { /* let's be paranoid */ report(lp, IMPORTANT, "Cannot figure out row type, row = %d, is_chsign = %d, upbo = %g on line %d", row, is_chsign(lp, row), (double)lp->orig_upbo[row], Lineno); } } if(items == 6) { if((row = find_row(lp, field5, Unconstrained_rows_found)) >= 0) { /* Determine constraint type */ if(fabs(field6) >= lp->infinite) { report(lp, IMPORTANT, "Warning, Range for row %s >= infinity (value %g) on line %d, ignored", field5, field6, Lineno); } else if(field6 == 0) { /* Change of a GE or LE to EQ */ if(lp->orig_upbo[row] != 0) set_constr_type(lp, row, EQ); } else if(is_chsign(lp, row)) { /* GE */ lp->orig_upbo[row] = fabs(field6); } else if(lp->orig_upbo[row] == 0 && field6 >= 0) { /* EQ with positive sign of r value */ set_constr_type(lp, row, GE); lp->orig_upbo[row] = field6; } else if(lp->orig_upbo[row] == lp->infinite) { /* LE */ lp->orig_upbo[row] = fabs(field6); } else if((lp->orig_upbo[row] == 0) && (field6 < 0)) { /* EQ with negative sign of r value */ set_constr_type(lp, row, LE); lp->orig_upbo[row] = my_flipsign(field6); } else { /* let's be paranoid */ report(lp, IMPORTANT, "Cannot figure out row type, row = %d, is_chsign = %d, upbo = %g on line %d", row, is_chsign(lp,row), (double) lp->orig_upbo[row], Lineno); } } } continue; /* Process entries in the SOS section */ /* We have to implement the following semantics: E. The SOS section is for ordered variable sets of the form: x1, x2, x3 ... xn where only a given number of consequtive variables may be non-zero. Each set definition is prefaced by type, name and priority data. Each set member has an optional weight that determines its order. There are two forms supported; a full format and a reduced CPLEX-like format. */ case MPSSOS: report(lp, FULL, "SOS line: %s %s %g %s %g", field2, field3, field4, field5, field6); if((items == 0) || (items > 4)) { report(lp, IMPORTANT, "Invalid number of items (%d) in SOS section line %d\n", items, Lineno); break; } if(strlen(field1) == 0) items--; /* fix scanline anomoly! */ /* Check if this is the start of a new SOS */ if(items == 1 || items == 4) { row = (int) (field1[1] - '0'); if((row <= 0) || (row > 9)) { report(lp, IMPORTANT, "Error: Invalid SOS type %s line %d\n", field1, Lineno); break; } field1[0] = '\0'; /* fix scanline anomoly! */ /* lp_solve needs a name for the SOS */ if(variant == 0) { if(strlen(field3) == 0) /* CPLEX format does not provide a SOS name; create one */ sprintf(field3, "SOS_%d", SOS_count(lp) + 1); } else { /* Remap XPRESS format name */ strcpy(field3, field1); } /* Obtain the SOS priority */ if(items == 4) SOS = (int) field4; else SOS = 1; /* Define a new SOS instance */ SOS = add_SOS(lp, field3, (int) row, SOS, 0, NULL, NULL); } /* Otherwise, add set members to the active SOS */ else { char *field = (items == 3) ? field3 /* Native lp_solve and XPRESS formats */ : field2 /* CPLEX format */; var = find_var(lp, field, FALSE); /* Native lp_solve and XPRESS formats */ if(var < 0){ /* SOS on undefined var in COLUMNS section ... */ Column_ready = TRUE; if (!addmpscolumn(lp, FALSE, typeMPS, &Column_ready, &count, Last_column, Last_columnno, field)) break; Column_ready = TRUE; var = find_var(lp, field, TRUE); } if((var < 0) || (SOS < 1)) /* undefined var and could add ... */; else append_SOSrec(lp->SOS->sos_list[SOS-1], 1, &var, &field4); } continue; } /* If we got here there was an error "upstream" */ report(lp, IMPORTANT, "Error: Cannot handle line %d\n", Lineno); break; } } if((*OBJNAME) && (!OF_found)) { report(lp, IMPORTANT, "Error: Objective function specified by OBJNAME card not found\n"); CompleteStatus = FALSE; } if(CompleteStatus == FALSE) { if (*newlp == NULL) delete_lp(lp); } else { if (typeMPS & MPSIBM) { REAL lower, upper; for (var = 1; var <= lp->columns; var++) if (is_int(lp, var)) { lower = get_lowbo(lp, var); upper = get_upbo(lp, var); if ((lower == 10.0 / DEF_INFINITE) && (upper == DEF_INFINITE / 10.0)) upper = 1.0; if (lower == 10.0 / DEF_INFINITE) lower = 0.0; if (upper == DEF_INFINITE / 10.0) upper = lp->infinite; set_bounds(lp, var, lower, upper); } } *newlp = lp; } if(Last_column != NULL) FREE(Last_column); if(Last_columnno != NULL) FREE(Last_columnno); } return( CompleteStatus ); } static void number(char *str,REAL value) { char __str[80], *_str; int i; /* sprintf(_str,"%12.6G",value); */ _str=__str+2; if (value>=0.0) if ((value!=0.0) && ((value>0.99999999e12) || (value<0.0001))) { int n=15; do { n--; i=sprintf(_str,"%*.*E",n,n-6,(double) value); if (i>12) { char *ptr=strchr(_str,'E'); if (ptr!=NULL) { if (*(++ptr)=='-') ptr++; while ((i>12) && ((*ptr=='+') || (*ptr=='0'))) { strcpy(ptr,ptr+1); i--; } } } } while (i>12); } else if (value>=1.0e10) { int n=13; do { i=sprintf(_str,"%*.0f",--n,(double) value); } while (i>12); } else { if (((i=sprintf(_str,"%12.10f",(double) value))>12) && (_str[12]>='5')) { for (i=11;i>=0;i--) if (_str[i]!='.') { if (++_str[i]>'9') _str[i]='0'; else break; } if (i<0) { *(--_str)='1'; *(--_str)=' '; } } } else if ((value<-0.99999999e11) || (value>-0.0001)) { int n=15; do { n--; i=sprintf(_str,"%*.*E",n,n-7,(double) value); if (i>12) { char *ptr=strchr(_str,'E'); if (ptr!=NULL) { if (*(++ptr)=='-') ptr++; while ((i>12) && ((*ptr=='+') || (*ptr=='0'))) { strcpy(ptr,ptr+1); i--; } } } } while (i>12); } else if (value<=-1.0e9) { int n=13; do { i=sprintf(_str,"%*.0f",--n,(double) value); } while (i>12); } else if (((i=sprintf(_str,"%12.9f",(double) value))>12) && (_str[12]>='5')) { for (i=11;i>=1;i--) if (_str[i]!='.') { if (++_str[i]>'9') _str[i]='0'; else break; } if (i<1) { *_str='1'; *(--_str)='-'; *(--_str)=' '; } } strncpy(str,_str,12); } static char *formatnumber12(char *numberbuffer, double a) { #if 0 return(sprintf(numberbuffer, "%12g", a)); #else number(numberbuffer, a); return(numberbuffer); #endif } STATIC char *MPSnameFIXED(char *name0, char *name) { sprintf(name0, "%-8.8s", name); return(name0); } STATIC char *MPSnameFREE(char *name0, char *name) { if(strlen(name) < 8) return(MPSnameFIXED(name0, name)); else return(name); } static void write_data(void *userhandle, write_modeldata_func write_modeldata, char *format, ...) { char buff[DEF_STRBUFSIZE+1]; va_list ap; va_start(ap, format); vsnprintf(buff, DEF_STRBUFSIZE, format, ap); va_end(ap); write_modeldata(userhandle, buff); } MYBOOL __WINAPI MPS_writefileex(lprec *lp, int typeMPS, void *userhandle, write_modeldata_func write_modeldata) { int i, j, jj, je, k, marker, putheader, ChangeSignObj = FALSE, *idx, *idx1; MYBOOL ok = TRUE, names_used; REAL a, *val, *val1; char * (*MPSname)(char *name0, char *name); char numberbuffer[15]; char name0[9]; if((typeMPS & MPSFIXED) == MPSFIXED) { MPSname = MPSnameFIXED; ChangeSignObj = is_maxim(lp); } else if((typeMPS & MPSFREE) == MPSFREE) { MPSname = MPSnameFREE; } else { report(lp, IMPORTANT, "MPS_writefile: unrecognized MPS name type.\n"); return(FALSE); } names_used = lp->names_used; if((typeMPS & MPSFIXED) == MPSFIXED) { /* Check if there is no variable name where the first 8 charachters are equal to the first 8 characters of anothe variable */ if(names_used) for(i = 1; (i <= lp->columns) && (ok); i++) if((lp->col_name[i] != NULL) && (lp->col_name[i]->name != NULL) && (!is_splitvar(lp, i)) && (strlen(lp->col_name[i]->name) > 8)) for(j = 1; (j < i) && (ok); j++) if((lp->col_name[j] != NULL) && (lp->col_name[j]->name != NULL) && (!is_splitvar(lp, j))) if(strncmp(lp->col_name[i]->name, lp->col_name[j]->name, 8) == 0) ok = FALSE; } if(!ok) { lp->names_used = FALSE; ok = TRUE; } memset(numberbuffer, 0, sizeof(numberbuffer)); marker = 0; /* First write metadata in structured comment form (lp_solve style) */ write_data(userhandle, write_modeldata, "*\n", (int) MAJORVERSION, (int) MINORVERSION); write_data(userhandle, write_modeldata, "*\n", lp->rows); write_data(userhandle, write_modeldata, "*\n", lp->columns); write_data(userhandle, write_modeldata, "*\n", lp->equalities); if(SOS_count(lp) > 0) write_data(userhandle, write_modeldata, "*\n", SOS_count(lp)); write_data(userhandle, write_modeldata, "*\n", lp->int_vars); if(lp->sc_vars > 0) write_data(userhandle, write_modeldata, "*\n", lp->sc_vars); write_data(userhandle, write_modeldata, "*\n", (is_maxim(lp) ? "MAX" : "MIN")); write_data(userhandle, write_modeldata, "*\n"); /* Write the MPS content */ write_data(userhandle, write_modeldata, "NAME %s\n", MPSname(name0, get_lp_name(lp))); if(((typeMPS & MPSFREE) == MPSFREE) && (is_maxim(lp))) write_data(userhandle, write_modeldata, "OBJSENSE\n MAX\n"); write_data(userhandle, write_modeldata, "ROWS\n"); for(i = 0; i <= lp->rows; i++) { if(i == 0) write_data(userhandle, write_modeldata, " N "); else if(lp->orig_upbo[i] != 0) { if(is_chsign(lp,i)) write_data(userhandle, write_modeldata, " G "); else write_data(userhandle, write_modeldata, " L "); } else write_data(userhandle, write_modeldata, " E "); write_data(userhandle, write_modeldata, "%s\n", MPSname(name0, get_row_name(lp, i))); } allocREAL(lp, &val, 1 + lp->rows, TRUE); allocINT(lp, &idx, 1 + lp->rows, TRUE); write_data(userhandle, write_modeldata, "COLUMNS\n"); for(i = 1; i <= lp->columns; i++) { if(!is_splitvar(lp, i)) { if(is_int(lp,i) && (marker % 2) == 0) { write_data(userhandle, write_modeldata, " MARK%04d 'MARKER' 'INTORG'\n", marker); marker++; } if(!is_int(lp,i) && (marker % 2) == 1) { write_data(userhandle, write_modeldata, " MARK%04d 'MARKER' 'INTEND'\n", marker); marker++; } /* Loop over non-zero column entries */ je = get_columnex(lp, i, val, idx); for(k = 1, val1 = val, idx1 = idx, jj = 0; jj < je; jj++) { k = 1 - k; j = *(idx1++); a = *(val1++); if (k == 0) { write_data(userhandle, write_modeldata, " %s", MPSname(name0, get_col_name(lp, i))); write_data(userhandle, write_modeldata, " %s %s", MPSname(name0, get_row_name(lp, j)), /* formatnumber12(numberbuffer, (double) a)); */ formatnumber12(numberbuffer, (double) (a * (j == 0 && ChangeSignObj ? -1 : 1)))); } else write_data(userhandle, write_modeldata, " %s %s\n", MPSname(name0, get_row_name(lp, j)), formatnumber12(numberbuffer, (double) (a * (j == 0 && ChangeSignObj ? -1 : 1)))); /* formatnumber12(numberbuffer, (double) a)); */ } if(k == 0) write_data(userhandle, write_modeldata, "\n"); } } if((marker % 2) == 1) { write_data(userhandle, write_modeldata, " MARK%04d 'MARKER' 'INTEND'\n", marker); /* marker++; */ /* marker not used after this */ } FREE(idx); FREE(val); write_data(userhandle, write_modeldata, "RHS\n"); for(k = 1, i = 0; i <= lp->rows; i++) { a = lp->orig_rhs[i]; if(a) { a = unscaled_value(lp, a, i); if ((i == 0) && ((typeMPS & MPSNEGOBJCONST) == MPSNEGOBJCONST)) a = -a; if((i == 0) || is_chsign(lp, i)) a = my_flipsign(a); k = 1 - k; if(k == 0) write_data(userhandle, write_modeldata, " RHS %s %s", MPSname(name0, get_row_name(lp, i)), formatnumber12(numberbuffer, (double)a)); else write_data(userhandle, write_modeldata, " %s %s\n", MPSname(name0, get_row_name(lp, i)), formatnumber12(numberbuffer, (double)a)); } } if(k == 0) write_data(userhandle, write_modeldata, "\n"); putheader = TRUE; for(k = 1, i = 1; i <= lp->rows; i++){ a = 0; if((lp->orig_upbo[i] < lp->infinite) && (lp->orig_upbo[i] != 0.0)) a = lp->orig_upbo[i]; if(a) { if(putheader) { write_data(userhandle, write_modeldata, "RANGES\n"); putheader = FALSE; } a = unscaled_value(lp, a, i); k = 1 - k; if(k == 0) write_data(userhandle, write_modeldata, " RGS %s %s", MPSname(name0, get_row_name(lp, i)), formatnumber12(numberbuffer, (double)a)); else write_data(userhandle, write_modeldata, " %s %s\n", MPSname(name0, get_row_name(lp, i)), formatnumber12(numberbuffer, (double)a)); } } if(k == 0) write_data(userhandle, write_modeldata, "\n"); putheader = TRUE; for(i = lp->rows + 1; i <= lp->sum; i++) if(!is_splitvar(lp, i - lp->rows)) { j = i - lp->rows; if((lp->orig_lowbo[i] != 0) && (lp->orig_upbo[i] < lp->infinite) && (lp->orig_lowbo[i] == lp->orig_upbo[i])) { a = lp->orig_upbo[i]; a = unscaled_value(lp, a, i); if(putheader) { write_data(userhandle, write_modeldata, "BOUNDS\n"); putheader = FALSE; } write_data(userhandle, write_modeldata, " FX BND %s %s\n", MPSname(name0, get_col_name(lp, j)), formatnumber12(numberbuffer, (double)a)); } else if(is_binary(lp, j)) { if(putheader) { write_data(userhandle, write_modeldata, "BOUNDS\n"); putheader = FALSE; } write_data(userhandle, write_modeldata, " BV BND %s\n", MPSname(name0, get_col_name(lp, j))); } else if(is_unbounded(lp, j)) { if(putheader) { write_data(userhandle, write_modeldata, "BOUNDS\n"); putheader = FALSE; } write_data(userhandle, write_modeldata, " FR BND %s\n", MPSname(name0, get_col_name(lp, j))); } else { if((lp->orig_lowbo[i] != 0) || (is_int(lp, j))) { /* Some solvers like CPLEX need to have a bound on a variable if it is integer, but not binary else it is interpreted as binary which is not ment */ a = lp->orig_lowbo[i]; a = unscaled_value(lp, a, i); if(putheader) { write_data(userhandle, write_modeldata, "BOUNDS\n"); putheader = FALSE; } if(lp->orig_lowbo[i] != -lp->infinite) write_data(userhandle, write_modeldata, " LO BND %s %s\n", MPSname(name0, get_col_name(lp, j)), formatnumber12(numberbuffer, (double)a)); else write_data(userhandle, write_modeldata, " MI BND %s\n", MPSname(name0, get_col_name(lp, j))); } if((lp->orig_upbo[i] < lp->infinite) || (is_semicont(lp, j))) { a = lp->orig_upbo[i]; if(a < lp->infinite) a = unscaled_value(lp, a, i); if(putheader) { write_data(userhandle, write_modeldata, "BOUNDS\n"); putheader = FALSE; } if(is_semicont(lp, j)) { if(is_int(lp, j)) write_data(userhandle, write_modeldata, " SI BND %s %s\n", MPSname(name0, get_col_name(lp, j)), (a < lp->infinite) ? formatnumber12(numberbuffer, (double)a) : " "); else write_data(userhandle, write_modeldata, " SC BND %s %s\n", MPSname(name0, get_col_name(lp, j)), (a < lp->infinite) ? formatnumber12(numberbuffer, (double)a) : " "); } else write_data(userhandle, write_modeldata, " UP BND %s %s\n", MPSname(name0, get_col_name(lp, j)), formatnumber12(numberbuffer, (double)a)); } } } /* Write optional SOS section */ putheader = TRUE; for(i = 0; i < SOS_count(lp); i++) { SOSgroup *SOS = lp->SOS; if(putheader) { write_data(userhandle, write_modeldata, "SOS\n"); putheader = FALSE; } write_data(userhandle, write_modeldata, " S%1d SOS %s %s\n", SOS->sos_list[i]->type, MPSname(name0, SOS->sos_list[i]->name), formatnumber12(numberbuffer, (double) SOS->sos_list[i]->priority)); for(j = 1; j <= SOS->sos_list[i]->size; j++) { write_data(userhandle, write_modeldata, " SOS %s %s\n", MPSname(name0, get_col_name(lp, SOS->sos_list[i]->members[j])), formatnumber12(numberbuffer, (double) SOS->sos_list[i]->weights[j])); } } write_data(userhandle, write_modeldata, "ENDATA\n"); lp->names_used = names_used; return(ok); } static int __WINAPI write_lpdata(void *userhandle, char *buf) { fputs(buf, (FILE *) userhandle); return(TRUE); } MYBOOL MPS_writefile(lprec *lp, int typeMPS, char *filename) { FILE *output = stdout; MYBOOL ok; if (filename != NULL) { ok = ((output = fopen(filename, "w")) != NULL); if(!ok) return(ok); } else output = lp->outstream; ok = MPS_writefileex(lp, typeMPS, (void *) output, write_lpdata); if (filename != NULL) fclose(output); return(ok); } MYBOOL MPS_writehandle(lprec *lp, int typeMPS, FILE *output) { MYBOOL ok; if (output != NULL) set_outputstream(lp, output); output = lp->outstream; ok = MPS_writefileex(lp, typeMPS, (void *) output, write_lpdata); return(ok); } /* Read and write BAS files */ /* #define OldNameMatch */ #ifdef OldNameMatch static int MPS_getnameidx(lprec *lp, char *varname, MYBOOL isrow) { int in = -1; in = get_nameindex(lp, varname, isrow); if((in < 0) && (strncmp(varname, (isrow ? ROWNAMEMASK : COLNAMEMASK), 1) == 0)) { if(sscanf(varname + 1, "%d", &in) != 1) in = -1; } return( in ); } #else static int MPS_getnameidx(lprec *lp, char *varname, MYBOOL tryrowfirst) { int in = -1; /* Have we defined our own variable names? */ if(lp->names_used) { /* First check the primary name list */ in = get_nameindex(lp, varname, tryrowfirst); if((in > 0) && !tryrowfirst) in += lp->rows; /* If we were unsuccessful, try the secondary name list */ else if(in < 0) { in = get_nameindex(lp, varname, (MYBOOL) !tryrowfirst); if((in > 0) && tryrowfirst) in += lp->rows; } } /* If not, see if we can match the standard name mask */ if(in == -1) { if(strncmp(varname, (tryrowfirst ? ROWNAMEMASK : COLNAMEMASK), 1) == 0) { /* Fail if we did not successfully scan as a valid integer */ if((sscanf(varname + 1, "%d", &in) != 1) || (in < (tryrowfirst ? 0 : 1)) || (in > (tryrowfirst ? lp->rows : lp->columns))) in = -1; } else if(strncmp(varname, (!tryrowfirst ? ROWNAMEMASK : COLNAMEMASK), 1) == 0) { /* Fail if we did not successfully scan as a valid integer */ if((sscanf(varname + 1, "%d", &in) != 1) || (in < (tryrowfirst ? 0 : 1)) || (in > (tryrowfirst ? lp->rows : lp->columns))) in = -1; } } return( in ); } #endif MYBOOL MPS_readBAS(lprec *lp, int typeMPS, char *filename, char *info) { char field1[BUFSIZ], field2[BUFSIZ], field3[BUFSIZ], field5[BUFSIZ], line[BUFSIZ], tmp[BUFSIZ], *ptr; double field4, field6; int ib, in, items, Lineno = 0; MYBOOL ok; FILE *input = stdin; int (*scan_line)(lprec *lp, int section, char* line, char *field1, char *field2, char *field3, double *field4, char *field5, double *field6); if((typeMPS & MPSFIXED) == MPSFIXED) scan_line = scan_lineFIXED; else if((typeMPS & MPSFREE) == MPSFREE) scan_line = scan_lineFREE; else { report(lp, IMPORTANT, "MPS_readBAS: unrecognized MPS line type.\n"); return(FALSE); } ok = (MYBOOL) ((filename != NULL) && ((input = fopen(filename,"r")) != NULL)); if(!ok) return(ok); default_basis(lp); /* Let's initialize line to all zero's */ MEMCLEAR(line, BUFSIZ); ok = FALSE; while(fgets(line, BUFSIZ - 1, input)) { Lineno++; for(ptr = line; (*ptr) && (isspace((unsigned char) *ptr)); ptr++); /* skip lines which start with "*", they are comment */ if((line[0] == '*') || (*ptr == 0) || (*ptr == '\n') || (*ptr == '\r')) { report(lp, FULL, "Comment on line %d: %s", Lineno, line); continue; } report(lp, FULL, "Line %6d: %s", Lineno, line); /* first check for "special" lines: in our case only NAME and ENDATA, ...this must start in the first position of line */ if(line[0] != ' ') { sscanf(line, "%s", tmp); if(strcmp(tmp, "NAME") == 0) { if(info != NULL) { *info = 0; for(ptr = line + 4; (*ptr) && (isspace((unsigned char) *ptr)); ptr++); in = (int) strlen(ptr); while ((in > 0) && ((ptr[in - 1] == '\r') || (ptr[in - 1] == '\n') || isspace(ptr[in - 1]))) in--; ptr[in] = 0; strcpy(info, ptr); } } else if(strcmp(tmp, "ENDATA") == 0) { report(lp, FULL, "Finished reading BAS file\n"); ok = TRUE; break; } else { /* line does not start with space and does not match above */ report(lp, IMPORTANT, "Unrecognized BAS line %d: %s\n", Lineno, line); break; } } else { /* normal line, process */ items = scan_line(lp, /* MPSRHS */ MPSBOUNDS, line, field1, field2, field3, &field4, field5, &field6); if(items < 0){ report(lp, IMPORTANT, "Syntax error on line %d: %s\n", Lineno, line); break; } /* find first variable index value */ in = MPS_getnameidx(lp, field2, FALSE); #ifdef OldNameMatch if(in < 0) in = MPS_getnameidx(lp, field2, TRUE); else in += lp->rows; #endif if(in < 0) break; /* check if we have the basic/non-basic variable format */ if(field1[0] == 'X') { /* find second variable index value */ ib = in; in = MPS_getnameidx(lp, field3, FALSE); #ifdef OldNameMatch if(in < 0) in = MPS_getnameidx(lp, field3, TRUE); else in += lp->rows; #endif if(in < 0) break; lp->is_lower[in] = (MYBOOL) (field1[1] == 'L'); lp->is_basic[ib] = TRUE; } else lp->is_lower[in] = (MYBOOL) (field1[0] == 'L'); lp->is_basic[in] = FALSE; } } /* Update the basis index-to-variable array */ ib = 0; items = lp->sum; for(in = 1; in <= items; in++) if(lp->is_basic[in]) { ib++; lp->var_basic[ib] = in; } fclose(input); return( ok ); } MYBOOL MPS_writeBAS(lprec *lp, int typeMPS, char *filename) { int ib, in; MYBOOL ok; char name1[100], name2[100]; FILE *output = stdout; char * (*MPSname)(char *name0, char *name); char name0[9]; /* Set name formatter */ if((typeMPS & MPSFIXED) == MPSFIXED) MPSname = MPSnameFIXED; else if((typeMPS & MPSFREE) == MPSFREE) MPSname = MPSnameFREE; else { report(lp, IMPORTANT, "MPS_writeBAS: unrecognized MPS name type.\n"); return(FALSE); } /* Open the file for writing */ ok = (MYBOOL) ((filename == NULL) || ((output = fopen(filename,"w")) != NULL)); if(!ok) return(ok); if(filename == NULL && lp->outstream != NULL) output = lp->outstream; fprintf(output, "NAME %s Rows %d Cols %d Iters %.0f\n", get_lp_name(lp), lp->rows, lp->columns, (double) get_total_iter(lp)); ib = lp->rows; in = 0; while ((ib < lp->sum) || (in < lp->sum)) { /* Find next basic variable (skip slacks) */ ib++; while((ib <= lp->sum) && !lp->is_basic[ib]) ib++; /* Find next non-basic variable (skip lower-bounded structural variables) */ in++; while((in <= lp->sum) && (lp->is_basic[in] || ((in > lp->rows) && lp->is_lower[in]))) in++; /* Check if we have a basic/non-basic variable pair */ if((ib <= lp->sum) && (in <= lp->sum)) { strcpy(name1, MPSname(name0, (ib <= lp->rows ? get_row_name(lp, ib) : get_col_name(lp, ib-lp->rows)))); strcpy(name2, MPSname(name0, (in <= lp->rows ? get_row_name(lp, in) : get_col_name(lp, in-lp->rows)))); fprintf(output, " %2s %s %s\n", (lp->is_lower[in] ? "XL" : "XU"), name1, name2); } /* Otherwise just write the bound state of the non-basic variable */ else if(in <= lp->sum) { strcpy(name1, MPSname(name0, (in <= lp->rows ? get_row_name(lp, in) : get_col_name(lp, in-lp->rows)))); fprintf(output, " %2s %s\n", (lp->is_lower[in] ? "LL" : "UL"), name1); } } fprintf(output, "ENDATA\n"); if(filename != NULL) fclose(output); return( ok ); } MSVMpack1.2/lp_solve_5.5/lp_presolve.c0000664000175000017500000057176711250515044016660 0ustar lauerlauer /* ------------------------------------------------------------------------- Presolve routines for lp_solve v5.0+ ------------------------------------------------------------------------- Author: Kjell Eikland Contact: kjell.eikland@broadpark.no License terms: LGPL. Requires: lp_lib.h, lp_presolve, lp_crash.h, lp_scale.h, lp_report.h Release notes: v1.0.0 1 January 2003 Initial crude version used with lp_solve v4. v5.0.0 1 January 2004 Significantly expanded and repackaged presolve routines for lp_solve v5 release. v5.0.1 1 April 2004 Added reference to new crash module v5.1.0 20 August 2004 Reworked infeasibility detection. Added encapsulation of presolve undo logic. v5.1.1 10 September 2004 Added variable bound tightening based on full-constraint information, as well as variable fixing by duality. v5.2.0 1 January 2005 Fixes to bound fixing handling. Added fast batch compression after presolve. Restructured calls by adding presolve wrapper. Major optimization of identification logic along with bug fixes. Enabled storage of eliminated matrix data. Added function to report on constraint classes. v5.5.0 1 June 2005 Added implied slack presolve, restructured looping logic to be more modular, and made active row/column selection logic faster. v5.5.1 18 June 2005 Finished sparsity-enhancing logic and added initial version of column aggregation code. ------------------------------------------------------------------------- */ #include #include "commonlib.h" #include "lp_lib.h" #include "lp_presolve.h" #include "lp_crash.h" #include "lp_scale.h" #include "lp_report.h" #ifdef FORTIFY # include "lp_fortify.h" #endif #define presolve_setstatus(one, two) presolve_setstatusex(one, two, __LINE__, __FILE__) STATIC int presolve_setstatusex(presolverec *psdata, int status, int lineno, char *filename) { if((status == INFEASIBLE) || (status == UNBOUNDED)) { report(psdata->lp, #ifdef Paranoia NORMAL, #else DETAILED, #endif "presolve_setstatus: Status set to '%s' on code line %d, file '%s'\n", (status == INFEASIBLE ? "INFEASIBLE" : "UNBOUNDED"), lineno, (filename == NULL ? "Unknown" : filename)); } return( status ); } STATIC MYBOOL presolve_statuscheck(presolverec *psdata, int *status) { if(*status == RUNNING) { lprec *lp = psdata->lp; if(!mat_validate(lp->matA)) *status = MATRIXERROR; else if(userabort(lp, -1)) *status = lp->spx_status; } return( (MYBOOL) (*status == RUNNING) ); } STATIC MYBOOL presolve_createUndo(lprec *lp) { if(lp->presolve_undo != NULL) presolve_freeUndo(lp); lp->presolve_undo = (presolveundorec *) calloc(1, sizeof(presolveundorec)); lp->presolve_undo->lp = lp; if(lp->presolve_undo == NULL) return( FALSE ); return( TRUE ); } STATIC MYBOOL inc_presolve_space(lprec *lp, int delta, MYBOOL isrows) { int i, ii, oldrowcolalloc, rowcolsum, oldrowalloc, oldcolalloc; presolveundorec *psundo = lp->presolve_undo; if(psundo == NULL) { presolve_createUndo(lp); psundo = lp->presolve_undo; } /* Set constants */ oldrowalloc = lp->rows_alloc-delta; oldcolalloc = lp->columns_alloc-delta; oldrowcolalloc = lp->sum_alloc-delta; rowcolsum = lp->sum_alloc + 1; /* Reallocate lp memory */ if(isrows) allocREAL(lp, &psundo->fixed_rhs, lp->rows_alloc+1, AUTOMATIC); else allocREAL(lp, &psundo->fixed_obj, lp->columns_alloc+1, AUTOMATIC); allocINT(lp, &psundo->var_to_orig, rowcolsum, AUTOMATIC); allocINT(lp, &psundo->orig_to_var, rowcolsum, AUTOMATIC); /* Fill in default values, where appropriate */ if(isrows) ii = oldrowalloc+1; else ii = oldcolalloc+1; for(i = oldrowcolalloc+1; i < rowcolsum; i++, ii++) { psundo->var_to_orig[i] = 0; psundo->orig_to_var[i] = 0; if(isrows) psundo->fixed_rhs[ii] = 0; else psundo->fixed_obj[ii] = 0; } return(TRUE); } STATIC MYBOOL presolve_setOrig(lprec *lp, int orig_rows, int orig_cols) { presolveundorec *psundo = lp->presolve_undo; if(psundo == NULL) return( FALSE ); psundo->orig_rows = orig_rows; psundo->orig_columns = orig_cols; psundo->orig_sum = orig_rows + orig_cols; if(lp->wasPresolved) presolve_fillUndo(lp, orig_rows, orig_cols, FALSE); return( TRUE ); } STATIC MYBOOL presolve_fillUndo(lprec *lp, int orig_rows, int orig_cols, MYBOOL setOrig) { int i; presolveundorec *psundo = lp->presolve_undo; for(i = 0; i <= orig_rows; i++) { psundo->var_to_orig[i] = i; psundo->orig_to_var[i] = i; psundo->fixed_rhs[i] = 0; } for(i = 1; i <= orig_cols; i++) { psundo->var_to_orig[orig_rows + i] = i; psundo->orig_to_var[orig_rows + i] = i; psundo->fixed_obj[i] = 0; } if(setOrig) presolve_setOrig(lp, orig_rows, orig_cols); return( TRUE ); } STATIC MYBOOL presolve_rebuildUndo(lprec *lp, MYBOOL isprimal) { int ik, ie, ix, j, k, *colnrDep; REAL hold, *value, *solution, *slacks; presolveundorec *psdata = lp->presolve_undo; MATrec *mat = NULL; /* Point to and initialize undo structure at first call */ if(isprimal) { if(psdata->primalundo != NULL) mat = psdata->primalundo->tracker; solution = lp->full_solution + lp->presolve_undo->orig_rows; slacks = lp->full_solution; } else { if(psdata->dualundo != NULL) mat = psdata->dualundo->tracker; solution = lp->full_duals; slacks = lp->full_duals + lp->presolve_undo->orig_rows; } if(mat == NULL) return( FALSE ); /* Loop backward over the undo chain */ for(j = mat->col_tag[0]; j > 0; j--) { ix = mat->col_tag[j]; ik = mat->col_end[j-1]; ie = mat->col_end[j]; colnrDep = &COL_MAT_ROWNR(ik); value = &COL_MAT_VALUE(ik); hold = 0; k = 0; for(; ik < ie; ik++, colnrDep += matRowColStep, value += matValueStep) { /* Constant term */ if(*colnrDep == 0) hold += *value; /* Special case with dependence on a slack variable */ else if(isprimal && (*colnrDep > lp->presolve_undo->orig_columns)) { k = (*colnrDep) - lp->presolve_undo->orig_columns; hold -= (*value) * slacks[k]; slacks[k] = 0; } else if(!isprimal && (*colnrDep > lp->presolve_undo->orig_rows)) { k = (*colnrDep) - lp->presolve_undo->orig_rows; hold -= (*value) * slacks[k]; slacks[k] = 0; } /* Dependence on other user variable */ else hold -= (*value) * solution[*colnrDep]; *value = 0; } if(fabs(hold) > lp->epsvalue) solution[ix] = hold; } return( TRUE ); } STATIC MYBOOL presolve_freeUndo(lprec *lp) { presolveundorec *psundo = lp->presolve_undo; if(psundo == NULL) return( FALSE ); FREE(psundo->orig_to_var); FREE(psundo->var_to_orig); FREE(psundo->fixed_rhs); FREE(psundo->fixed_obj); if(psundo->deletedA != NULL) freeUndoLadder(&(psundo->deletedA)); if(psundo->primalundo != NULL) freeUndoLadder(&(psundo->primalundo)); if(psundo->dualundo != NULL) freeUndoLadder(&(psundo->dualundo)); FREE(lp->presolve_undo); return( TRUE ); } STATIC void presolve_storeDualUndo(presolverec *psdata, int rownr, int colnr) { lprec *lp = psdata->lp; MYBOOL firstdone = FALSE; int ix, iix, item; REAL Aij = get_mat(lp, rownr, colnr); MATrec *mat = lp->matA; if(presolve_collength(psdata, colnr) == 0) return; /* Add undo information for the dual of the deleted constraint */ item = 0; for(ix = presolve_nextrow(psdata, colnr, &item); ix >= 0; ix = presolve_nextrow(psdata, colnr, &item)) { iix = COL_MAT_ROWNR(ix); if(iix == rownr) continue; if(!firstdone) firstdone = addUndoPresolve(lp, FALSE, rownr, get_mat(lp, 0, colnr)/Aij, get_mat_byindex(lp, ix, FALSE, TRUE)/Aij, iix); else appendUndoPresolve(lp, FALSE, get_mat_byindex(lp, ix, FALSE, TRUE)/Aij, iix); } } /* ----------------------------------------------------------------------------- */ /* Presolve debugging routines */ /* ----------------------------------------------------------------------------- */ STATIC MYBOOL presolve_SOScheck(presolverec *psdata) { MYBOOL status = TRUE; lprec *lp = psdata->lp; int *list, i, j, n, k, nk, colnr, nSOS = SOS_count(lp), nerr = 0; SOSrec *SOS; if(nSOS == 0) return( status ); /* For each SOS and each member check validity */ for(i = 1; i<= nSOS; i++) { SOS = lp->SOS->sos_list[i-1]; list = SOS->members; n = list[0]; for(j = 1; j<= n; j++) { colnr = list[j]; /* Check valid range */ if((colnr < 1) || (colnr > lp->columns)) { nerr++; report(lp, IMPORTANT, "presolve_SOScheck: A - Column index %d is outside of valid range\n", colnr); } /* Check for deletion */ if(!isActiveLink(psdata->cols->varmap, colnr)) { nerr++; report(lp, IMPORTANT, "presolve_SOScheck: B - Column index %d has been marked for deletion\n", colnr); } /* Check if sorted member array is Ok */ if(SOS_member_index(lp->SOS, i, colnr) != j) { nerr++; report(lp, IMPORTANT, "presolve_SOScheck: C - Column index %d not found in fast search array\n", colnr); } /* Check for variable membership in this SOS record of the sparse storage */ k = lp->SOS->memberpos[colnr-1]; nk = lp->SOS->memberpos[colnr]; while((k < nk) && (lp->SOS->membership[k] != i)) k++; if(k >= nk) { nerr++; report(lp, IMPORTANT, "presolve_SOScheck: D - Column index %d was not found in sparse array\n", colnr); } } } /* Check that all members in the sparse array can be validated as SOS members */ for(colnr = 1; colnr <= lp->columns; colnr++) { k = lp->SOS->memberpos[colnr-1]; nk = lp->SOS->memberpos[colnr]; for(; k < nk; k++) { if(!SOS_is_member(lp->SOS, lp->SOS->membership[k], colnr)) { nerr++; report(lp, IMPORTANT, "presolve_SOScheck: E - Sparse array did not indicate column index %d as member of SOS %d\n", colnr, lp->SOS->membership[k]); } } } status = (MYBOOL) (nerr == 0); if(!status) report(lp, IMPORTANT, "presolve_SOScheck: There were %d errors\n", nerr); return( status ); } /* ----------------------------------------------------------------------------- */ /* Presolve routines for tightening the model */ /* ----------------------------------------------------------------------------- */ INLINE REAL presolve_roundrhs(lprec *lp, REAL value, MYBOOL isGE) { #ifdef DoPresolveRounding REAL eps = PRESOLVE_EPSVALUE*1000, /* REAL eps = PRESOLVE_EPSVALUE*pow(10.0,MAX(0,log10(1+fabs(value)))), */ testout = my_precision(value, eps); #if 1 if(my_chsign(isGE, value-testout) < 0) value = testout; #elif 0 if(my_chsign(isGE, value-testout) < 0) value = testout; else if(value != testout) value += my_chsign(isGE, (value-testout)/2); /* value = testout + my_chsign(isGE, (value-testout)/2); */ #else if(testout != value) value += my_chsign(isGE, eps*1000); /* BASE OPTION */ #endif #endif return( value ); } INLINE REAL presolve_roundval(lprec *lp, REAL value) { #ifdef DoPresolveRounding /* value = my_precision(value, PRESOLVE_EPSVALUE*MAX(1,log10(1+fabs(value)))); */ value = my_precision(value, PRESOLVE_EPSVALUE); /* BASE OPTION */ #endif return( value ); } INLINE MYBOOL presolve_mustupdate(lprec *lp, int colnr) { #if 0 return( my_infinite(lp, get_lowbo(lp, colnr)) || my_infinite(lp, get_upbo(lp, colnr)) ); #else return( my_infinite(lp, lp->orig_lowbo[lp->rows+colnr]) || my_infinite(lp, lp->orig_upbo[lp->rows+colnr]) ); #endif } INLINE REAL presolve_sumplumin(lprec *lp, int item, psrec *ps, MYBOOL doUpper) { REAL *plu = (doUpper ? ps->pluupper : ps->plulower), *neg = (doUpper ? ps->negupper : ps->neglower); if(fabs(plu[item]) >= lp->infinite) return( plu[item] ); else if(fabs(neg[item]) >= lp->infinite) return( neg[item] ); else return( plu[item]+neg[item] ); } INLINE void presolve_range(lprec *lp, int rownr, psrec *ps, REAL *loValue, REAL *hiValue) { *loValue = presolve_sumplumin(lp, rownr, ps, FALSE); *hiValue = presolve_sumplumin(lp, rownr, ps, TRUE); } STATIC void presolve_rangeorig(lprec *lp, int rownr, psrec *ps, REAL *loValue, REAL *hiValue, REAL delta) { delta = my_chsign(is_chsign(lp, rownr), lp->presolve_undo->fixed_rhs[rownr] + delta); *loValue = presolve_sumplumin(lp, rownr, ps, FALSE) + delta; *hiValue = presolve_sumplumin(lp, rownr, ps, TRUE) + delta; } STATIC MYBOOL presolve_rowfeasible(presolverec *psdata, int rownr, MYBOOL userowmap) { lprec *lp = psdata->lp; MYBOOL status = TRUE; int contype, origrownr = rownr; REAL LHS, RHS, value; /* Optionally loop across all active rows in the provided map (debugging) */ if(userowmap) rownr = firstActiveLink(psdata->rows->varmap); /* Now do once for ingoing rownr or loop across rowmap */ while((status == TRUE) && (rownr != 0)) { /* Check the lower bound */ value = presolve_sumplumin(lp, rownr, psdata->rows, TRUE); LHS = get_rh_lower(lp, rownr); if(value < LHS-lp->epssolution) { contype = get_constr_type(lp, rownr); report(lp, NORMAL, "presolve_rowfeasible: Lower bound infeasibility in %s row %s (%g << %g)\n", get_str_constr_type(lp, contype), get_row_name(lp, rownr), value, LHS); if(rownr != origrownr) report(lp, NORMAL, " ... Input row base used for testing was %s\n", get_row_name(lp, origrownr)); status = FALSE; } /* Check the upper bound */ value = presolve_sumplumin(lp, rownr, psdata->rows, FALSE); RHS = get_rh_upper(lp, rownr); if(value > RHS+lp->epssolution) { contype = get_constr_type(lp, rownr); report(lp, NORMAL, "presolve_rowfeasible: Upper bound infeasibility in %s row %s (%g >> %g)\n", get_str_constr_type(lp, contype), get_row_name(lp, rownr), value, RHS); status = FALSE; } if(userowmap) rownr = nextActiveLink(psdata->rows->varmap, rownr); else rownr = 0; } return( status ); } STATIC MYBOOL presolve_debugmap(presolverec *psdata, char *caption) { lprec *lp = psdata->lp; MATrec *mat = lp->matA; int colnr, ix, ie, nx, jx, je, *cols, *rows, n; int nz = mat->col_end[lp->columns] - 1; MYBOOL status = FALSE; for(colnr = 1; colnr <= lp->columns; colnr++) { rows = psdata->cols->next[colnr]; if(!isActiveLink(psdata->cols->varmap, colnr)) { if(rows != NULL) { report(lp, SEVERE, "presolve_debugmap: Inactive column %d is non-empty\n", colnr); goto Done; } else continue; } if(rows == NULL) report(lp, SEVERE, "presolve_debugmap: Active column %d is empty\n", colnr); je = *rows; rows++; for(jx = 1; jx <= je; jx++, rows++) { if((*rows < 0) || (*rows > nz)) { report(lp, SEVERE, "presolve_debugmap: NZ index %d for column %d out of range (index %d<=%d)\n", *rows, colnr, jx, je); goto Done; } cols = psdata->rows->next[COL_MAT_ROWNR(*rows)]; ie = cols[0]; n = 0; for(ix = 1; ix <= ie; ix++) { nx = cols[ix]; if((nx < 0) || (nx > nz)) { report(lp, SEVERE, "presolve_debugmap: NZ index %d for column %d to row %d out of range\n", nx, colnr, jx); goto Done; } } } } status = TRUE; Done: if(!status && (caption != NULL)) report(lp, SEVERE, "...caller was '%s'\n", caption); return( status ); } STATIC MYBOOL presolve_validate(presolverec *psdata, MYBOOL forceupdate) { int i, ie, j, je, k, rownr, *items; REAL upbound, lobound, value; lprec *lp = psdata->lp; MATrec *mat = lp->matA; MYBOOL status = mat->row_end_valid && !forceupdate; if(status) return( status ); else if(!mat->row_end_valid) status = mat_validate(mat); else status = forceupdate; if(status) { /* First update rows... */ for(i = 1; i <= lp->rows; i++) { psdata->rows->plucount[i] = 0; psdata->rows->negcount[i] = 0; psdata->rows->pluneg[i] = 0; if(!isActiveLink(psdata->rows->varmap, i)) { FREE(psdata->rows->next[i]); } else { /* Create next column pointers by row */ k = mat_rowlength(mat, i); allocINT(lp, &(psdata->rows->next[i]), k+1, AUTOMATIC); items = psdata->rows->next[i]; je = mat->row_end[i]; k = 0; for(j = mat->row_end[i-1]; j < je; j++) if(isActiveLink(psdata->cols->varmap, ROW_MAT_COLNR(j))) { k++; items[k] = j; } items[0] = k; } } /* ...then update columns */ for(j = 1; j <= lp->columns; j++) { psdata->cols->plucount[j] = 0; psdata->cols->negcount[j] = 0; psdata->cols->pluneg[j] = 0; if(!isActiveLink(psdata->cols->varmap, j)) { FREE(psdata->cols->next[j]); } else { upbound = get_upbo(lp, j); lobound = get_lowbo(lp, j); if(is_semicont(lp, j) && (upbound > lobound)) { if(lobound > 0) lobound = 0; else if(upbound < 0) upbound = 0; } /* Create next row pointers by column */ k = mat_collength(mat, j); allocINT(lp, &(psdata->cols->next[j]), k+1, AUTOMATIC); items = psdata->cols->next[j]; ie = mat->col_end[j]; k = 0; for(i = mat->col_end[j-1]; i < ie; i++) { rownr = COL_MAT_ROWNR(i); if(isActiveLink(psdata->rows->varmap, rownr)) { k++; items[k] = i; /* Cumulate counts */ value = COL_MAT_VALUE(i); if(my_chsign(is_chsign(lp, rownr), value) > 0) { psdata->rows->plucount[rownr]++; psdata->cols->plucount[j]++; } else { psdata->rows->negcount[rownr]++; psdata->cols->negcount[j]++; } if((lobound < 0) && (upbound >= 0)) { psdata->rows->pluneg[rownr]++; psdata->cols->pluneg[j]++; } } } items[0] = k; } } #ifdef Paranoia presolve_debugmap(psdata, "presolve_validate"); #endif } return( status ); } STATIC MYBOOL presolve_rowtallies(presolverec *psdata, int rownr, int *plu, int *neg, int *pluneg) { REAL value; lprec *lp = psdata->lp; MATrec *mat = lp->matA; int ix, jx, ib = 0; MYBOOL chsign = is_chsign(lp, rownr); /* Initialize */ *plu = 0; *neg = 0; *pluneg = 0; /* Loop over still active row members */ for(ix = presolve_nextcol(psdata, rownr, &ib); ix >= 0; ix = presolve_nextcol(psdata, rownr, &ib)) { /* Get matrix column and value */ jx = ROW_MAT_COLNR(ix); value = ROW_MAT_VALUE(ix); /* Cumulate counts */ if(my_chsign(chsign, value) > 0) (*plu)++; else (*neg)++; if((get_lowbo(lp, jx) < 0) && (get_upbo(lp, jx) >= 0)) (*pluneg)++; } return( TRUE ); } STATIC MYBOOL presolve_debugrowtallies(presolverec *psdata) { lprec *lp = psdata->lp; int i, plu, neg, pluneg, nerr = 0; for(i = 1; i <= lp->rows; i++) if(isActiveLink(psdata->rows->varmap, i) && presolve_rowtallies(psdata, i, &plu, &neg, &pluneg)) { if((psdata->rows->plucount[i] != plu) || (psdata->rows->negcount[i] != neg) || (psdata->rows->pluneg[i] != pluneg)) { nerr++; report(lp, SEVERE, "presolve_debugrowtallies: Detected inconsistent count for row %d\n", i); } } return( (MYBOOL) (nerr == 0) ); } STATIC int presolve_debugcheck(lprec *lp, LLrec *rowmap, LLrec *colmap) { int i, j, errc = 0; /* Validate constraint bounds */ for(i = 1; i < lp->rows; i++) { if((rowmap != NULL) && !isActiveLink(rowmap, i)) continue; /* Check if we have a negative range */ if(lp->orig_upbo[i] < 0) { errc++; report(lp, SEVERE, "presolve_debugcheck: Detected negative range %g for row %d\n", lp->orig_upbo[i], i); } } /* Validate variables */ for(j = 1; j < lp->columns; j++) { if((colmap != NULL) && !isActiveLink(colmap, j)) continue; i = lp->rows+j; /* Check if we have infeasible bounds */ if(lp->orig_lowbo[i] > lp->orig_upbo[i]) { errc++; report(lp, SEVERE, "presolve_debugcheck: Detected UB < LB for column %d\n", j); } } /* Return total number of errors */ return( errc ); } STATIC MYBOOL presolve_candeletevar(presolverec *psdata, int colnr) { lprec *lp = psdata->lp; int usecount = SOS_memberships(lp->SOS, colnr); return( (MYBOOL) ((lp->SOS == NULL) || (usecount == 0) || (/*is_presolve(lp, PRESOLVE_SOS) &&*/ (((lp->SOS->sos1_count == lp->SOS->sos_count)) || (usecount == SOS_is_member_of_type(lp->SOS, colnr, SOS1))))) ); } STATIC int presolve_rowlengthex(presolverec *psdata, int rownr) { int j1 = psdata->rows->plucount[rownr] + psdata->rows->negcount[rownr]; #ifdef Paranoia int j2 = presolve_rowlength(psdata, rownr); if(j1 != j2) { report(psdata->lp, SEVERE, "presolve_rowlengthex: Expected row length %d, but found %d in row %s\n", j2, j1, get_row_name(psdata->lp, rownr)); j1 = -j1; } #endif return( j1 ); } STATIC int presolve_rowlengthdebug(presolverec *psdata) { int rownr, n = 0; for(rownr = firstActiveLink(psdata->rows->varmap); rownr != 0; rownr = nextActiveLink(psdata->rows->varmap, rownr)) n += presolve_rowlengthex(psdata, rownr); return( n ); } INLINE int presolve_nextrecord(psrec *ps, int recnr, int *previtem) { int *nzlist = ps->next[recnr], nzcount = nzlist[0], status = -1; /* Check if we simply wish the last active column */ if(previtem == NULL) { if(nzlist != NULL) status = nzlist[*nzlist]; return( status ); } /* Step to next */ #ifdef Paranoia else if((*previtem < 0) || (*previtem > nzcount)) return( status ); #endif (*previtem)++; /* Set the return values */ if(*previtem > nzcount) (*previtem) = 0; else status = nzlist[*previtem]; return( status ); } INLINE int presolve_nextcol(presolverec *psdata, int rownr, int *previtem) /* Find the first active (non-eliminated) nonzero column in rownr after prevcol */ { return( presolve_nextrecord(psdata->rows, rownr, previtem) ); } INLINE int presolve_lastcol(presolverec *psdata, int rownr) { return( presolve_nextrecord(psdata->rows, rownr, NULL) ); } INLINE int presolve_nextrow(presolverec *psdata, int colnr, int *previtem) /* Find the first active (non-eliminated) nonzero row in colnr after prevrow */ { return( presolve_nextrecord(psdata->cols, colnr, previtem) ); } INLINE int presolve_lastrow(presolverec *psdata, int colnr) { return( presolve_nextrecord(psdata->cols, colnr, NULL) ); } INLINE void presolve_adjustrhs(presolverec *psdata, int rownr, REAL fixdelta, REAL epsvalue) { lprec *lp = psdata->lp; lp->orig_rhs[rownr] -= fixdelta; if(epsvalue > 0) #if 1 my_roundzero(lp->orig_rhs[rownr], epsvalue); #else lp->orig_rhs[rownr] = presolve_roundrhs(lp, lp->orig_rhs[rownr], FALSE); #endif lp->presolve_undo->fixed_rhs[rownr] += fixdelta; } STATIC int presolve_shrink(presolverec *psdata, int *nConRemove, int *nVarRemove) { SOSgroup *SOS = psdata->lp->SOS; int status = RUNNING, countR = 0, countC = 0, i, ix, n, *list; REAL fixValue; /* Remove empty rows */ list = psdata->rows->empty; if(list != NULL) { n = list[0]; for(i = 1; i <= n; i++) if(isActiveLink(psdata->rows->varmap, list[i])) { presolve_rowremove(psdata, list[i], FALSE); countR++; } if(nConRemove != NULL) (*nConRemove) += countR; list[0] = 0; } /* Fix and remove empty columns (unless they are in a SOS) */ list = psdata->cols->empty; if(list != NULL) { n = list[0]; for(i = 1; i <= n; i++) { ix = list[i]; if(isActiveLink(psdata->cols->varmap, ix)) { if(presolve_colfixdual(psdata, ix, &fixValue, &status)) { if(!presolve_colfix(psdata, ix, fixValue, TRUE, nVarRemove)) { status = presolve_setstatus(psdata, INFEASIBLE); break; } presolve_colremove(psdata, ix, FALSE); countC++; } else if(SOS_is_member(SOS, 0, ix)) report(psdata->lp, DETAILED, "presolve_shrink: Empty column %d is member of a SOS\n", ix); } } list[0] = 0; } return( status ); } STATIC void presolve_rowremove(presolverec *psdata, int rownr, MYBOOL allowcoldelete) { lprec *lp = psdata->lp; MATrec *mat = lp->matA; int ix, ie, nx, jx, je, *cols, *rows, n, colnr; #ifdef Paranoia if((rownr < 1) || (rownr > lp->rows)) report(lp, SEVERE, "presolve_rowremove: Row %d out of range\n", rownr); #endif /* Remove this row for each column that is active in the row */ cols = psdata->rows->next[rownr]; ie = *cols; cols++; for(ix = 1; ix <= ie; ix++, cols++) { n = 0; colnr = ROW_MAT_COLNR(*cols); rows = psdata->cols->next[colnr]; je = rows[0]; /* See if we can narrow the search window */ jx = je / 2; if((jx > 5) && (rownr >= COL_MAT_ROWNR(rows[jx]))) n = jx-1; else jx = 1; /* Do the compression loop */ for(; jx <= je; jx++) { nx = rows[jx]; if(COL_MAT_ROWNR(nx) != rownr) { n++; rows[n] = nx; } } rows[0] = n; /* Make sure we delete columns that have become empty */ #if 1 if((n == 0) && allowcoldelete) { int *list = psdata->cols->empty; n = ++list[0]; list[n] = colnr; } #endif } FREE(psdata->rows->next[rownr]); removeLink(psdata->rows->varmap, rownr); switch(get_constr_type(lp, rownr)) { case LE: removeLink(psdata->LTmap, rownr); break; case EQ: removeLink(psdata->EQmap, rownr); break; } if(isActiveLink(psdata->INTmap, rownr)) removeLink(psdata->INTmap, rownr); } STATIC int presolve_colremove(presolverec *psdata, int colnr, MYBOOL allowrowdelete) { lprec *lp = psdata->lp; #ifdef Paranoia if((colnr < 1) || (colnr > lp->columns)) report(lp, SEVERE, "presolve_colremove: Column %d out of range\n", colnr); if(!isActiveLink(psdata->cols->varmap, colnr) || !presolve_candeletevar(psdata, colnr)) colnr = -1; else #endif { MATrec *mat = lp->matA; int ix, ie, nx, jx, je, *cols, *rows, n, rownr; /* Remove this column for each row that is active in the column */ rows = psdata->cols->next[colnr]; je = *rows; rows++; for(jx = 1; jx <= je; jx++, rows++) { n = 0; rownr = COL_MAT_ROWNR(*rows); cols = psdata->rows->next[rownr]; ie = cols[0]; /* See if we can narrow the search window */ ix = ie / 2; if((ix > 5) && (colnr >= ROW_MAT_COLNR(cols[ix]))) n = ix-1; else ix = 1; /* Do the compression loop */ for(; ix <= ie; ix++) { nx = cols[ix]; if(ROW_MAT_COLNR(nx) != colnr) { n++; cols[n] = nx; } } cols[0] = n; /* Make sure we delete rows that become empty */ #if 1 if((n == 0) && allowrowdelete) { int *list = psdata->rows->empty; n = ++list[0]; list[n] = rownr; } #endif } FREE(psdata->cols->next[colnr]); /* Update other counts */ if(SOS_is_member(lp->SOS, 0, colnr)) { if(lp->sos_priority != NULL) { lp->sos_vars--; if(is_int(lp, colnr)) lp->sos_ints--; } SOS_member_delete(lp->SOS, 0, colnr); clean_SOSgroup(lp->SOS, TRUE); if(SOS_count(lp) == 0) free_SOSgroup(&(lp->SOS)); } /* Finally remove the column from the active column list */ colnr = removeLink(psdata->cols->varmap, colnr); } return( colnr ); } STATIC int presolve_redundantSOS(presolverec *psdata, int *nb, int *nSum) { lprec *lp = psdata->lp; int i, ii, k, kk, j, nrows = lp->rows, *fixed = NULL, iBoundTighten = 0, status = RUNNING; SOSrec *SOS; /* Is there anything to do? */ i = ii = SOS_count(lp); if(ii == 0) return( status ); /* Allocate working member list */ if(!allocINT(lp, &fixed, lp->columns+1, FALSE) ) return( lp->spx_status ); /* Check if we have SOS'es that are already satisfied or fixable/satisfiable */ while(i > 0) { SOS = lp->SOS->sos_list[i-1]; kk = SOS->members[0]; fixed[0] = 0; for(k = 1; k <= kk; k++) { j = SOS->members[k]; if((get_lowbo(lp, j) > 0) && !is_semicont(lp, j)) { fixed[++fixed[0]] = k; /* Abort if we have identified SOS infeasibility */ if(fixed[0] > SOS->type) { status = presolve_setstatus(psdata, INFEASIBLE); goto Done; } } } /* If there were an exact number of non-zero SOS members, check their sequentiality */ if(fixed[0] == SOS->type) { /* Check sequentiality of members with non-zero lower bounds */ for(k = 2; k <= fixed[0]; k++) { if(fixed[k] != fixed[k-1]+1) { status = presolve_setstatus(psdata, INFEASIBLE); goto Done; } } /* Fix other member variables to zero, if necessary */ for(k = kk; k > 0; k--) { j = SOS->members[k]; if((get_lowbo(lp, j) > 0) && !is_semicont(lp, j)) continue; if(!presolve_colfix(psdata, j, 0.0, AUTOMATIC, &iBoundTighten)) { status = presolve_setstatus(psdata, INFEASIBLE); goto Done; } } /* Remove the SOS */ delete_SOSrec(lp->SOS, i /* , FALSE */); } /* Otherwise, try to fix variables outside the SOS type window */ else if(fixed[0] > 0) { for(k = kk; k > 0; k--) { if((k > fixed[fixed[0]]-SOS->type) && /* After leading entries */ (k < fixed[1]+SOS->type)) /* Before trailing entries */ continue; j = SOS->members[k]; SOS_member_delete(lp->SOS, i, j); /* if(get_upbo(lp, j) - get_lowbo(lp, j) < lp->epsprimal) */ if(is_fixedvar(lp, nrows+j)) continue; if(!presolve_colfix(psdata, j, 0.0, AUTOMATIC, &iBoundTighten)) { status = presolve_setstatus(psdata, INFEASIBLE); goto Done; } } } i--; } /* Update the sparse member map if there were SOS deletions; Remember that delete_SOSrec() above specified deferred updating! */ i = SOS_count(lp); if((i < ii) || (iBoundTighten > 0)) { SOS_member_updatemap(lp->SOS); } /* Update tag orders */ for(; i > 0; i--) lp->SOS->sos_list[i-1]->tagorder = i; Done: FREE(fixed); (*nb) += iBoundTighten; (*nSum) += iBoundTighten; return( status ); } STATIC MYBOOL presolve_fixSOS1(presolverec *psdata, int colnr, REAL fixvalue, int *nr, int *nv) { lprec *lp = psdata->lp; int i, k, j; SOSrec *SOS; REAL newvalue; MYBOOL *fixed = NULL, status = FALSE; /* Allocate working member list */ if(!allocMYBOOL(lp, &fixed, lp->columns+1, TRUE) ) return(FALSE); /* Fix variables in SOS's where colnr is a member */ i = SOS_count(lp); while(i > 0) { /* Set next SOS target (note that colnr has been tested earlier as not being a member of a higher order SOS) */ SOS = lp->SOS->sos_list[i-1]; if(SOS_is_member(lp->SOS, i, colnr)) { for(k = SOS->members[0]; k > 0; k--) { j = SOS->members[k]; if(fixed[j]) continue; if(j == colnr) { fixed[j] = TRUE; newvalue = fixvalue; } else { fixed[j] = AUTOMATIC; newvalue = 0.0; } /* If it is a member of a higher order SOS then just change bounds */ if(!presolve_candeletevar(psdata, j)) { set_bounds(lp, j, newvalue, newvalue); fixed[j] = TRUE | AUTOMATIC; psdata->forceupdate = TRUE; } /* Otherwise fix it in preparation for removal */ else if(!presolve_colfix(psdata, j, newvalue, TRUE, nv)) goto Done; } } i--; } /* Delete SOS'es or SOS member variables where we can */ k = i = SOS_count(lp); while(i > 0) { /* Set next SOS target */ SOS = lp->SOS->sos_list[i-1]; if(SOS_is_member(lp->SOS, i, colnr)) { /* Always delete SOS1's */ if(SOS->type == SOS1) delete_SOSrec(lp->SOS, i /* , FALSE */); /* Only delete leading or trailing SOS members in higher-order SOS'es that are fixed at 0; (note that this section of the code will never be called in the current setup) */ else { /* First the leading entries... */ for(j = 1; j <= SOS->members[0]; j++) { if(fixed[SOS->members[j]] == AUTOMATIC) SOS_member_delete(lp->SOS, i, SOS->members[j]); } /* ...then trailing entries */ for(j = SOS->members[0]; j > 0; j--) { if(fixed[SOS->members[j]] == AUTOMATIC) SOS_member_delete(lp->SOS, i, SOS->members[j]); } } } i--; } /* Update the sparse member map if there were SOS deletions; delete_SOSrec() above specified deferred updating */ i = SOS_count(lp); if(i < k) SOS_member_updatemap(lp->SOS); /* Delete the variables that have been fixed */ k = 0; for(j = lp->columns; j > 0; j--) { if((fixed[j] == TRUE) || (fixed[j] == AUTOMATIC)) { presolve_colremove(psdata, j, TRUE); k++; } } /* Update tag orders */ i = SOS_count(lp); for(; i > 0; i--) lp->SOS->sos_list[i-1]->tagorder = i; status = TRUE; Done: FREE(fixed); return( status ); } STATIC void presolve_setEQ(presolverec *psdata, int rownr) { lprec *lp = psdata->lp; if(is_constr_type(lp, rownr, LE)) removeLink(psdata->LTmap, rownr); setLink(psdata->EQmap, rownr); set_constr_type(lp, rownr, EQ); psdata->dv_lobo[rownr] = -lp->infinite; psdata->dv_upbo[rownr] = lp->infinite; } STATIC MYBOOL presolve_singletonbounds(presolverec *psdata, int rownr, int colnr, REAL *lobound, REAL *upbound, REAL *aval) { lprec *lp = psdata->lp; REAL coeff_a, epsvalue = psdata->epsvalue; MYBOOL isneg; /* Compute row singleton variable range */ if(is_constr_type(lp, rownr, EQ) && (fabs(*lobound) < epsvalue)) *lobound = *upbound = 0; else { if(aval == NULL) coeff_a = get_mat(lp, rownr, colnr); else coeff_a = *aval; isneg = (MYBOOL) (coeff_a < 0); if(*lobound > -lp->infinite) *lobound /= coeff_a; else if(isneg) *lobound = -(*lobound); if(*upbound < lp->infinite) *upbound /= coeff_a; else if(isneg) *upbound = -(*upbound); if(isneg) swapREAL(lobound, upbound); } /* Check against bound - handle SC variables specially */ if(is_semicont(lp, colnr)) { coeff_a = get_lowbo(lp, colnr); if(coeff_a > 0) { SETMAX(*lobound, 0.0); SETMIN(*upbound, get_upbo(lp, colnr)); } else { coeff_a = get_upbo(lp, colnr); if(coeff_a > 0) { SETMAX(*lobound, get_lowbo(lp, colnr)); SETMIN(*upbound, 0.0); } } } else { SETMAX(*lobound, get_lowbo(lp, colnr)); SETMIN(*upbound, get_upbo(lp, colnr)); } /* Return with consistency status */ #ifdef DoPresolveRelativeTest isneg = (MYBOOL) (my_reldiff(*upbound, *lobound) >= - epsvalue); #else isneg = (MYBOOL) (*upbound >= *lobound - epsvalue); #endif if(!isneg) { /* Attempt bound-related error correction */ if(fabs(my_reldiff(*lobound, get_upbo(lp, colnr))) < PRESOLVE_BOUNDSLACK*epsvalue) *lobound = get_upbo(lp, colnr); else if(fabs(my_reldiff(*upbound, get_lowbo(lp, colnr))) < PRESOLVE_BOUNDSLACK*epsvalue) *upbound = get_lowbo(lp, colnr); #ifdef DoPresolveRelativeTest isneg = (MYBOOL) (my_reldiff(*upbound, *lobound) >= - epsvalue); #else isneg = (MYBOOL) (*upbound >= *lobound - epsvalue); #endif if(!isneg) report(lp, NORMAL, "presolve_singletonbounds: Singleton variable %s in row %s infeasibility (%g << %g)\n", get_col_name(lp, colnr), get_row_name(lp, rownr), *lobound, *upbound); } return( isneg ); } STATIC MYBOOL presolve_altsingletonvalid(presolverec *psdata, int rownr, int colnr, REAL reflotest, REAL refuptest) { lprec *lp = psdata->lp; REAL coeff_bl, coeff_bu, epsvalue = psdata->epsvalue; coeff_bl = get_rh_lower(lp, rownr); coeff_bu = get_rh_upper(lp, rownr); /* Check base data validity */ #ifdef DoPresolveRelativeTest if((my_reldiff(refuptest, reflotest) < -epsvalue) || #else if((reflotest > refuptest + epsvalue) || #endif !presolve_singletonbounds(psdata, rownr, colnr, &coeff_bl, &coeff_bu, NULL)) return( FALSE ); /* Base data is Ok, now check against against each other */ epsvalue = MAX(reflotest-coeff_bu, coeff_bl-refuptest) / epsvalue; if(epsvalue > PRESOLVE_BOUNDSLACK) { report(lp, NORMAL, "presolve_altsingletonvalid: Singleton variable %s in row %s infeasible (%g)\n", get_col_name(lp, colnr), get_row_name(lp, rownr), MAX(reflotest-coeff_bu, coeff_bl-refuptest)); return( FALSE ); } else return( TRUE ); } STATIC MYBOOL presolve_multibounds(presolverec *psdata, int rownr, int colnr, REAL *lobound, REAL *upbound, REAL *aval, MYBOOL *rowbinds) { lprec *lp = psdata->lp; MYBOOL rowbindsvar = FALSE, status = FALSE; REAL coeff_a, LHS, RHS, netX, Xupper, Xlower, epsvalue = psdata->epsvalue; /* Get variable bounds for netting */ LHS = *lobound; RHS = *upbound; Xlower = get_lowbo(lp, colnr); Xupper = get_upbo(lp, colnr); /* Identify opportunity for bound tightening */ if(aval == NULL) coeff_a = get_mat(lp, rownr, colnr); else coeff_a = *aval; netX = presolve_sumplumin(lp, rownr, psdata->rows, TRUE); if(!my_infinite(lp, LHS) && !my_infinite(lp, netX)) { if(coeff_a > 0) { LHS -= netX-coeff_a*Xupper; LHS /= coeff_a; if(LHS > Xlower + epsvalue) { Xlower = presolve_roundrhs(lp, LHS, TRUE); status = TRUE; } else if(LHS > Xlower - epsvalue) rowbindsvar = TRUE; } else { LHS -= netX-coeff_a*Xlower; LHS /= coeff_a; if(LHS < Xupper - epsvalue) { Xupper = presolve_roundrhs(lp, LHS, FALSE); status = AUTOMATIC; } else if(LHS < Xupper + epsvalue) rowbindsvar = AUTOMATIC; } } netX = presolve_sumplumin(lp, rownr, psdata->rows, FALSE); if(!my_infinite(lp, RHS) && !my_infinite(lp, netX)) { if(coeff_a < 0) { if(!my_infinite(lp, Xupper)) { RHS -= netX-coeff_a*Xupper; RHS /= coeff_a; if(RHS > Xlower + epsvalue) { Xlower = presolve_roundrhs(lp, RHS, TRUE); status |= TRUE; } else if(RHS > Xlower - epsvalue) rowbindsvar |= TRUE; } } else if(!my_infinite(lp, Xlower)) { RHS -= netX-coeff_a*Xlower; RHS /= coeff_a; if(RHS < Xupper - epsvalue) { Xupper = presolve_roundrhs(lp, RHS, FALSE); status |= AUTOMATIC; } else if(RHS < Xupper + epsvalue) rowbindsvar |= AUTOMATIC; } } *lobound = Xlower; *upbound = Xupper; if(rowbinds != NULL) *rowbinds = rowbindsvar; return(status); } STATIC MYBOOL isnz_origobj(lprec *lp, int colnr) { return( (MYBOOL) (lp->orig_obj[colnr] != 0) ); } STATIC MYBOOL presolve_testrow(presolverec *psdata, int lastrow) { if(psdata->forceupdate) { presolve_updatesums(psdata); psdata->forceupdate = FALSE; } if(!presolve_rowfeasible(psdata, 0, TRUE)) return( FALSE ); else return( TRUE ); } STATIC MYBOOL presolve_coltighten(presolverec *psdata, int colnr, REAL LOnew, REAL UPnew, int *count) { lprec *lp = psdata->lp; int elmnr, elmend, k, oldcount = 0, newcount = 0, deltainf; REAL LOold, UPold, Value, margin = psdata->epsvalue; MATrec *mat = lp->matA; REAL *value; int *rownr; /* Attempt correction of marginally equal, but inconsistent input values */ Value = UPnew - LOnew; if((Value <= -margin) && (Value > -lp->epsprimal)) { if(fabs(fmod(UPnew, 1.0)) < margin) LOnew = UPnew; else UPnew = LOnew; } /* Check if there is anything to do */ LOold = get_lowbo(lp, colnr); UPold = get_upbo(lp, colnr); #ifdef Paranoia if(((LOold > LOnew) && !is_semicont(lp, colnr)) || (UPold < UPnew)) { report(lp, SEVERE, "presolve_coltighten: Inconsistent new bounds requested for column %d\n", colnr); return( FALSE ); } #endif if(count != NULL) newcount = *count; oldcount = newcount; /* Modify inf-count */ deltainf = 0; if((UPold < lp->infinite) || (LOold > -lp->infinite)) deltainf -= 1; if((UPnew < lp->infinite) || (LOnew > -lp->infinite)) deltainf += 1; if(isnz_origobj(lp, colnr)) psdata->rows->infcount[0] += deltainf; elmnr = mat->col_end[colnr-1]; elmend = mat->col_end[colnr]; rownr = &COL_MAT_ROWNR(elmnr); for(; elmnr < elmend; elmnr++, rownr += matRowColStep) { k = *rownr; if(isActiveLink(psdata->rows->varmap, k)) psdata->rows->infcount[k] += deltainf; } /* Look for opportunity to tighten upper variable bound */ if((UPnew < lp->infinite) && (UPnew+margin < UPold)) { if(is_int(lp, colnr)) UPnew = floor(UPnew+margin); if(UPold < lp->infinite) { /* First do OF */ k = 0; Value = my_chsign(is_chsign(lp, k), lp->orig_obj[colnr]); if((Value > 0) && (psdata->rows->pluupper[k] < lp->infinite)) psdata->rows->pluupper[k] += (UPnew-UPold)*Value; else if((Value < 0) && (psdata->rows->negupper[k] < lp->infinite)) psdata->rows->negupper[k] += (LOnew-LOold)*Value; psdata->rows->infcount[k] += deltainf; /* Then scan the constraint rows */ elmnr = mat->col_end[colnr-1]; elmend = mat->col_end[colnr]; rownr = &COL_MAT_ROWNR(elmnr); value = &COL_MAT_VALUE(elmnr); for(; elmnr < elmend; elmnr++, rownr += matRowColStep, value += matValueStep) { k = *rownr; if(!isActiveLink(psdata->rows->varmap, k)) continue; Value = my_chsign(is_chsign(lp, k), *value); if((Value > 0) && (psdata->rows->pluupper[k] < lp->infinite)) psdata->rows->pluupper[k] += (UPnew-UPold)*Value; else if((Value < 0) && (psdata->rows->negupper[k] < lp->infinite)) psdata->rows->negupper[k] += (LOnew-LOold)*Value; } } else psdata->forceupdate = TRUE; if(UPnew < UPold) { UPold = UPnew; newcount++; } } /* Look for opportunity to tighten lower variable bound */ if((LOnew > -lp->infinite) && (LOnew-margin > LOold)) { if(is_int(lp, colnr)) LOnew = ceil(LOnew-margin); if(LOold > -lp->infinite) { /* First do OF */ k = 0; Value = my_chsign(is_chsign(lp, k), lp->orig_obj[colnr]); if((Value > 0) && (psdata->rows->plulower[k] > -lp->infinite)) psdata->rows->plulower[k] += (LOnew-LOold)*Value; else if((Value < 0) && (psdata->rows->neglower[k] > -lp->infinite)) psdata->rows->neglower[k] += (UPnew-UPold)*Value; /* Then scan the constraint rows */ elmnr = mat->col_end[colnr-1]; elmend = mat->col_end[colnr]; rownr = &COL_MAT_ROWNR(elmnr); value = &COL_MAT_VALUE(elmnr); for(; elmnr < elmend; elmnr++, rownr += matRowColStep, value += matValueStep) { k = *rownr; if(!isActiveLink(psdata->rows->varmap, k)) continue; Value = my_chsign(is_chsign(lp, k), *value); if((Value > 0) && (psdata->rows->plulower[k] > -lp->infinite)) psdata->rows->plulower[k] += (LOnew-LOold)*Value; else if((Value < 0) && (psdata->rows->neglower[k] > -lp->infinite)) psdata->rows->neglower[k] += (UPnew-UPold)*Value; } } else psdata->forceupdate = TRUE; if(LOnew > LOold) { LOold = LOnew; newcount++; } } /* Now set the new variable bounds, if they are tighter */ if(newcount > oldcount) { UPnew = presolve_roundval(lp, UPnew); LOnew = presolve_roundval(lp, LOnew); if(LOnew > UPnew) { if(LOnew-UPnew < margin) { LOnew = UPnew; } else { report(lp, NORMAL, "presolve_coltighten: Found column %s with LB %g > UB %g\n", get_col_name(lp, colnr), LOnew, UPnew); return( FALSE ); } } if(lp->spx_trace || (lp->verbose > DETAILED)) report(lp, NORMAL, "presolve_coltighten: Replaced bounds on column %s to [%g ... %g]\n", get_col_name(lp, colnr), LOnew, UPnew); set_bounds(lp, colnr, LOnew, UPnew); } if(count != NULL) *count = newcount; return( TRUE ); } STATIC int presolve_rowtighten(presolverec *psdata, int rownr, int *tally, MYBOOL intsonly) { lprec *lp = psdata->lp; MYBOOL rowbinds; int item = 0, jx, jjx, ix, idxn = 0, *idxbound = NULL, status = RUNNING; REAL *newbound = NULL, RHlo = get_rh_lower(lp, rownr), RHup = get_rh_upper(lp, rownr), VARlo, VARup, Aval; MATrec *mat = lp->matA; jx = presolve_rowlength(psdata, rownr); allocREAL(lp, &newbound, 2*jx, TRUE); allocINT (lp, &idxbound, 2*jx, TRUE); /* Identify bound tightening for each active variable in the constraint */ for(jx = presolve_nextcol(psdata, rownr, &item); jx >= 0; jx = presolve_nextcol(psdata, rownr, &item)) { jjx = ROW_MAT_COLNR(jx); Aval = ROW_MAT_VALUE(jx); Aval = my_chsign(rownr, Aval); VARlo = RHlo; VARup = RHup; presolve_multibounds(psdata, rownr,jjx, &VARlo, &VARup, &Aval, &rowbinds); if(rowbinds & TRUE) { idxbound[idxn] = -jjx; newbound[idxn] = VARlo; idxn++; } if(rowbinds & AUTOMATIC) { idxbound[idxn] = jjx; newbound[idxn] = VARup; idxn++; } } /* Loop over the bounds identified for tightening and perform update */ ix = 0; while(ix < idxn) { jjx = idxbound[ix]; jx = abs(jjx); /* Skip free variables and non-ints, if specified */ if(is_unbounded(lp, jx) || (intsonly && !is_int(lp, jx))) continue; VARlo = get_lowbo(lp, jx); VARup = get_upbo(lp, jx); /* while((ix < idxn) && (jx == abs(jjx))) { */ while((ix < idxn) && (jx == abs((jjx = idxbound[ix])))) { if(jjx < 0) VARlo = newbound[ix]; else VARup = newbound[ix]; ix++; } if(!presolve_coltighten(psdata, jx, VARlo, VARup, tally)) { status = presolve_setstatus(psdata, INFEASIBLE); break; } } FREE(newbound); FREE(idxbound); return(status); } STATIC void set_dv_bounds(presolverec *psdata, int rownr, REAL lowbo, REAL upbo) { psdata->dv_lobo[rownr] = lowbo; psdata->dv_upbo[rownr] = upbo; } STATIC REAL get_dv_lower(presolverec *psdata, int rownr) { return( psdata->dv_lobo[rownr] ); } STATIC REAL get_dv_upper(presolverec *psdata, int rownr) { return( psdata->dv_upbo[rownr] ); } STATIC MYBOOL presolve_rowfix(presolverec *psdata, int rownr, REAL newvalue, MYBOOL remove, int *tally) { lprec *lp = psdata->lp; int i, ix, ie; MYBOOL isneg, lofinite, upfinite, doupdate = FALSE, chsign = is_chsign(lp, rownr); REAL lobound, upbound, lovalue, upvalue, Value, fixvalue, fixprod, mult; MATrec *mat = lp->matA; psrec *ps = psdata->cols; /* Set "fixed" value in case we are deleting a variable */ upbound = get_dv_upper(psdata, rownr); lobound = get_dv_lower(psdata, rownr); if(remove) { if(upbound-lobound < psdata->epsvalue) { if((newvalue > lobound) && (newvalue < upbound)) fixvalue = newvalue; else fixvalue = lobound; } else { if(my_infinite(lp, newvalue) && (get_rh(lp, rownr) == 0)) fixvalue = ((lobound <= 0) && (upbound >= 0) ? 0 : MIN(upbound, lobound)); else fixvalue = newvalue; } set_dv_bounds(psdata, rownr, fixvalue, fixvalue); if(fixvalue != 0) addUndoPresolve(lp, FALSE, rownr, fixvalue, 0, 0); mult = -1; } else { mult = 1; fixvalue = 0; } /* Loop over rows to update statistics */ ix = mat->row_end[rownr - 1]; ie = mat->row_end[rownr]; for(; ix < ie; ix++) { /* Retrieve row data and adjust RHS if we are deleting a variable */ i = ROW_MAT_COLNR(ix); Value = ROW_MAT_VALUE(ix); if(Value == 0) continue; if(remove && (fixvalue != 0)) { fixprod = Value*fixvalue; lp->orig_obj[i] -= fixprod; my_roundzero(lp->orig_obj[i], psdata->epsvalue); lp->presolve_undo->fixed_obj[i] += fixprod; } /* Prepare for further processing */ Value = my_chsign(chsign, Value); isneg = (MYBOOL) (Value < 0); /* Reduce row variable counts if we are removing the variable */ if(!isActiveLink(ps->varmap, i)) continue; if(remove) { if(isneg) { ps->negcount[i]--; } else { ps->plucount[i]--; } if((lobound < 0) && (upbound >= 0)) { ps->pluneg[i]--; } } /* Compute associated constraint contribution values */ upfinite = (MYBOOL) (upbound < lp->infinite); lofinite = (MYBOOL) (lobound > -lp->infinite); if(upfinite || lofinite) { if(remove) ps->infcount[i]--; else ps->infcount[i]++; } upvalue = my_if(upfinite, Value*upbound, my_chsign(isneg, lp->infinite)); lovalue = my_if(lofinite, Value*lobound, my_chsign(isneg, -lp->infinite)); /* Cumulate effective upper column bound (only bother with non-finite bound) */ if(isneg) { if((ps->negupper[i] < lp->infinite) && lofinite) { ps->negupper[i] += mult*lovalue; ps->negupper[i] = presolve_roundrhs(lp, ps->negupper[i], FALSE); } else if(remove && !lofinite) doupdate = TRUE; else ps->negupper[i] = lp->infinite; } else { if((ps->pluupper[i] < lp->infinite) && upfinite) { ps->pluupper[i] += mult*upvalue; ps->pluupper[i] = presolve_roundrhs(lp, ps->pluupper[i], FALSE); } else if(remove && !upfinite) doupdate = TRUE; else ps->pluupper[i] = lp->infinite; } /* Cumulate effective lower column bound (only bother with non-finite bound) */ if(isneg) { if((ps->neglower[i] > -lp->infinite) && upfinite) { ps->neglower[i] += mult*upvalue; ps->neglower[i] = presolve_roundrhs(lp, ps->neglower[i], TRUE); } else if(remove && !upfinite) doupdate = TRUE; else ps->neglower[i] = -lp->infinite; } else { if((ps->plulower[i] > -lp->infinite) && lofinite) { ps->plulower[i] += mult*lovalue; ps->plulower[i] = presolve_roundrhs(lp, ps->plulower[i], TRUE); } else if(remove && !lofinite) doupdate = TRUE; else ps->plulower[i] = -lp->infinite; } /* Validate consistency of eliminated singleton */ if(remove && ((i == 0) || (ps->next[i][0] == 1)) && !psdata->forceupdate) { presolve_range(lp, i, ps, &lovalue, &upvalue); Value = get_mat(lp, 0, i); if((upvalue < Value) || (lovalue > Value)) { report(lp, IMPORTANT, "presolve: Row %s (%g << %g) infeasibility in column %s (OF=%g)\n", get_row_name(lp, rownr), lovalue, upvalue, get_col_name(lp, i), Value); return( FALSE ); } } } if(remove) { psdata->forceupdate |= doupdate; if(tally != NULL) (*tally)++; } return( TRUE ); } STATIC int presolve_colsingleton(presolverec *psdata, int i, int j, int *count) { lprec *lp = psdata->lp; REAL RHlow, RHup, LObound, UPbound, Value; #ifdef Paranoia if(!isActiveLink(psdata->cols->varmap, j)) report(lp, SEVERE, "presolve_colsingleton: Nothing to do, column %d was eliminated earlier\n", j); #endif Value = get_mat(lp,i,j); if(Value == 0) return( RUNNING ); /* Initialize and identify semicontinuous variable */ LObound = get_lowbo(lp, j); UPbound = get_upbo(lp, j); if(is_semicont(lp, j) && (UPbound > LObound)) { if(LObound > 0) LObound = 0; else if(UPbound < 0) UPbound = 0; } /* Get singleton variable bounds */ RHlow = get_rh_lower(lp, i); RHup = get_rh_upper(lp, i); if(!presolve_singletonbounds(psdata, i,j, &RHlow, &RHup, &Value)) return( presolve_setstatus(psdata, INFEASIBLE) ); if(presolve_coltighten(psdata, j, RHlow, RHup, count)) return( RUNNING ); else return( presolve_setstatus(psdata, INFEASIBLE) ); } STATIC MYBOOL presolve_colfix(presolverec *psdata, int colnr, REAL newvalue, MYBOOL remove, int *tally) { lprec *lp = psdata->lp; int i, ix, ie; MYBOOL isneg, lofinite, upfinite, doupdate = FALSE, doOF = TRUE; REAL lobound, upbound, lovalue, upvalue, Value, fixvalue, mult; MATrec *mat = lp->matA; psrec *ps = psdata->rows; REAL *value; int *rownr; /* Set "fixed" value in case we are deleting a variable */ upbound = get_upbo(lp, colnr); lobound = get_lowbo(lp, colnr); if(remove) { if(upbound-lobound < psdata->epsvalue) { if((newvalue > lobound) && (newvalue < upbound)) fixvalue = newvalue; else fixvalue = lobound; } else { if(my_infinite(lp, newvalue) && (get_mat(lp, 0, colnr) == 0)) fixvalue = ((lobound <= 0) && (upbound >= 0) ? 0 : MIN(upbound, lobound)); else fixvalue = newvalue; } #if 1 /* Fast normal version */ set_bounds(lp, colnr, fixvalue, fixvalue); #else /* Slower version that can be used for debugging/control purposes */ presolve_coltighten(psdata, colnr, fixvalue, fixvalue, NULL); lobound = fixvalue; upbound = fixvalue; #endif if(fixvalue != 0) addUndoPresolve(lp, TRUE, colnr, fixvalue, 0, 0); mult = -1; } else { mult = 1; fixvalue = 0; } /* Adjust semi-continuous variable bounds to zero-base */ if(is_semicont(lp, colnr) && (upbound > lobound)) { if(lobound > 0) lobound = 0; else if(upbound < 0) upbound = 0; } /* Loop over rows to update statistics */ ix = mat->col_end[colnr - 1]; ie = mat->col_end[colnr]; rownr = &COL_MAT_ROWNR(ix); value = &COL_MAT_VALUE(ix); for(; doOF || (ix < ie); ix++, rownr += matRowColStep, value += matValueStep) { /* Retrieve row data and adjust RHS if we are deleting a variable */ Restart: if(doOF) { i = 0; Value = lp->orig_obj[colnr]; } else { i = *rownr; Value = *value; if(!isActiveLink(ps->varmap, i)) continue; } if(Value == 0) goto BlockEnd; if(remove && (fixvalue != 0)) presolve_adjustrhs(psdata, i, Value*fixvalue, psdata->epsvalue); /* Prepare for further processing */ Value = my_chsign(is_chsign(lp, i), Value); isneg = (MYBOOL) (Value < 0); /* Reduce row variable counts if we are removing the variable */ if(remove == TRUE) { if(isneg) { ps->negcount[i]--; } else { ps->plucount[i]--; } if((lobound < 0) && (upbound >= 0)) { ps->pluneg[i]--; } } /* Compute associated constraint contribution values */ upfinite = (MYBOOL) (upbound < lp->infinite); lofinite = (MYBOOL) (lobound > -lp->infinite); if(upfinite || lofinite) { if(remove) ps->infcount[i]--; else ps->infcount[i]++; } upvalue = my_if(upfinite, Value*upbound, my_chsign(isneg, lp->infinite)); lovalue = my_if(lofinite, Value*lobound, my_chsign(isneg, -lp->infinite)); /* Cumulate effective upper row bound (only bother with non-finite bound) */ if(isneg) { if((ps->negupper[i] < lp->infinite) && lofinite) { ps->negupper[i] += mult*lovalue; ps->negupper[i] = presolve_roundrhs(lp, ps->negupper[i], FALSE); } else if(remove && !lofinite) doupdate = TRUE; else ps->negupper[i] = lp->infinite; } else { if((ps->pluupper[i] < lp->infinite) && upfinite) { ps->pluupper[i] += mult*upvalue; ps->pluupper[i] = presolve_roundrhs(lp, ps->pluupper[i], FALSE); } else if(remove && !upfinite) doupdate = TRUE; else ps->pluupper[i] = lp->infinite; } /* Cumulate effective lower row bound (only bother with non-finite bound) */ if(isneg) { if((ps->neglower[i] > -lp->infinite) && upfinite) { ps->neglower[i] += mult*upvalue; ps->neglower[i] = presolve_roundrhs(lp, ps->neglower[i], TRUE); } else if(remove && !upfinite) doupdate = TRUE; else ps->neglower[i] = -lp->infinite; } else { if((ps->plulower[i] > -lp->infinite) && lofinite) { ps->plulower[i] += mult*lovalue; ps->plulower[i] = presolve_roundrhs(lp, ps->plulower[i], TRUE); } else if(remove && !lofinite) doupdate = TRUE; else ps->plulower[i] = -lp->infinite; } /* Validate consistency of eliminated singleton */ if(remove && ((i == 0) || (ps->next[i][0] == 1)) && !psdata->forceupdate) { if(i == 0) { lovalue = get_rh_lower(lp, i); upvalue = get_rh_upper(lp, i); report(lp, DETAILED, "presolve_colfix: Objective determined by presolve as %18g\n", (is_maxim(lp) ? upvalue : lovalue)); } else { presolve_range(lp, i, ps, &lovalue, &upvalue); #if 1 Value = 0; #else Value = MAX(fabs(upvalue), fabs(lovalue)); Value = psdata->epsvalue * MAX(1, Value); #endif if((upvalue < get_rh_lower(lp, i)-Value) || (lovalue > get_rh_upper(lp, i)+Value)) { report(lp, NORMAL, "presolve_colfix: Variable %s (%g << %g) infeasibility in row %s (%g << %g)\n", get_col_name(lp, colnr), lovalue, upvalue, get_row_name(lp, i), get_rh_lower(lp,i), get_rh_upper(lp, i)); return( FALSE ); } } } BlockEnd: if(doOF) { doOF = FALSE; if(ix < ie) goto Restart; } } if(remove) { psdata->forceupdate |= doupdate; if(tally != NULL) (*tally)++; } return( TRUE ); } /* Delete the columns of the specified row, but make sure we don't delete SOS variables. Note that we cannot use presolve_nextcol() here, since the variables are deleted. */ STATIC int presolve_rowfixzero(presolverec *psdata, int rownr, int *nv) { lprec *lp = psdata->lp; MATrec *mat = lp->matA; int ix, jx, ib = mat->row_end[rownr-1]; for(ix = mat->row_end[rownr]-1; ix >= ib; ix--) { jx = ROW_MAT_COLNR(ix); if(isActiveLink(psdata->cols->varmap, jx)) { if(!presolve_colfix(psdata, jx, 0.0, TRUE, nv)) return( presolve_setstatus(psdata, INFEASIBLE) ); if(presolve_candeletevar(psdata, jx)) presolve_colremove(psdata, jx, TRUE); } } #ifdef xxParanoia if(!presolve_debugrowtallies(psdata)) return( INFEASIBLE ); #endif return( RUNNING ); } /* Function to find if a variable can be fixed based on considering the dual */ STATIC MYBOOL presolve_colfixdual(presolverec *psdata, int colnr, REAL *fixValue, int *status) { lprec *lp = psdata->lp; MYBOOL hasOF, isMI, isDualFREE = TRUE; int i, ix, ie, *rownr, signOF; REAL *value, loX, upX, eps = psdata->epsvalue; MATrec *mat = lp->matA; /* First check basic variable range */ loX = get_lowbo(lp, colnr); upX = get_upbo(lp, colnr); if(((loX < 0) && (upX > 0)) || (fabs(upX-loX) < lp->epsvalue) || SOS_is_member_of_type(lp->SOS, colnr, SOSn)) return( FALSE ); isMI = (MYBOOL) (upX <= 0); /* Retrieve OF (standard form assuming maximization) */ ix = mat->col_end[colnr - 1]; ie = mat->col_end[colnr]; rownr = &COL_MAT_ROWNR(ix); value = &COL_MAT_VALUE(ix); hasOF = isnz_origobj(lp, colnr); if(hasOF) signOF = my_sign(lp->orig_obj[colnr]); else signOF = 0; /* Loop over all constraints involving active variable (standard form with LE constraints)*/ for(; (ix < ie) && isDualFREE; ix++, rownr += matRowColStep, value += matValueStep) { i = *rownr; if(!isActiveLink(psdata->rows->varmap, i)) continue; if(presolve_rowlength(psdata, i) == 1) { REAL val = my_chsign(is_chsign(lp, i), *value), loR = get_rh_lower(lp, i), upR = get_rh_upper(lp, i); if(!presolve_singletonbounds(psdata, i, colnr, &loR, &upR, &val)) { *status = presolve_setstatus(psdata, INFEASIBLE); return( FALSE ); } if(loR > loX + psdata->epsvalue) loX = presolve_roundrhs(lp, loR, TRUE); if(upR < upX - psdata->epsvalue) upX = presolve_roundrhs(lp, upR, FALSE); continue; } else isDualFREE = my_infinite(lp, get_rh_range(lp, i)) || /* Explicitly free */ ((presolve_sumplumin(lp, i, psdata->rows, TRUE)-eps <= get_rh_upper(lp, i)) && /* Implicitly free */ (presolve_sumplumin(lp, i, psdata->rows, FALSE)+eps >= get_rh_lower(lp, i))); if(isDualFREE) { if(signOF == 0) /* Test on the basis of identical signs in the constraints */ signOF = my_sign(*value); else /* Test on the basis of constraint sign equal to OF sign */ isDualFREE = (MYBOOL) (signOF == my_sign(*value)); } } /* Set fixing value if we were successful */ if(isDualFREE) { if(signOF == 0) { SETMAX(loX, 0); *fixValue = MIN(loX, upX); } else if(signOF > 0) { if(my_infinite(lp, loX)) isDualFREE = FALSE; else { if(is_int(lp, colnr)) *fixValue = ceil(loX-PRESOLVE_EPSVALUE); else *fixValue = loX; } } else { if(my_infinite(lp, upX)) isDualFREE = FALSE; else { if(is_int(lp, colnr) && (upX != 0)) *fixValue = floor(upX+PRESOLVE_EPSVALUE); else *fixValue = upX; } } if((*fixValue != 0) && SOS_is_member(lp->SOS, 0, colnr)) return( FALSE ); } return( isDualFREE ); } #if 0 STATIC MYBOOL presolve_probefix01(presolverec *psdata, int colnr, REAL *fixvalue) { lprec *lp = psdata->lp; int i, ix, item; REAL loLim, absvalue, epsvalue = psdata->epsvalue; MATrec *mat = lp->matA; MYBOOL chsign, canfix = FALSE; if(!is_binary(lp, colnr)) return( canfix ); /* Loop over all active rows to search for fixing opportunity */ item = 0; for(ix = presolve_nextrow(psdata, colnr, &item); (ix >= 0) && !canfix; ix = presolve_nextrow(psdata, colnr, &item)) { i = COL_MAT_ROWNR(ix); *fixvalue = COL_MAT_VALUE(ix); chsign = is_chsign(lp, i); /* First check the lower bound of the normalized constraint */ loLim = presolve_sumplumin(lp, i, psdata->rows, chsign); loLim = my_chsign(chsign, loLim); absvalue = fabs(*fixvalue); canfix = (MYBOOL) ((loLim + absvalue > lp->orig_rhs[i]+epsvalue*MAX(1, absvalue))); /* If we were unsuccessful in fixing above, try the upper bound of the normalized constraint - if it is finite */ if(!canfix && !my_infinite(lp, get_rh_range(lp, i))) { loLim = presolve_sumplumin(lp, i, psdata->rows, (MYBOOL) !chsign); loLim = my_chsign(!chsign, loLim); *fixvalue = -(*fixvalue); canfix = (MYBOOL) ((loLim + absvalue > get_rh_range(lp, i)-lp->orig_rhs[i]+epsvalue*MAX(1, absvalue))); } } /* Check if we were successful in identifying fixing opportunity */ if(canfix) { if(*fixvalue < 0) *fixvalue = 1; else *fixvalue = 0; } return( canfix ); } #else STATIC MYBOOL presolve_probefix01(presolverec *psdata, int colnr, REAL *fixvalue) { lprec *lp = psdata->lp; int i, ix, item; REAL loLim, upLim, range, absvalue, epsvalue = psdata->epsvalue, tolgap; MATrec *mat = lp->matA; MYBOOL chsign, status = FALSE; if(!is_binary(lp, colnr)) return( status ); /* Loop over all active rows to search for fixing opportunity. The logic is that if a constraint gets violated by setting a variable at one of its bounds, then it can be fixed at its opposite bound. */ item = 0; for(ix = presolve_nextrow(psdata, colnr, &item); (ix >= 0); ix = presolve_nextrow(psdata, colnr, &item)) { i = COL_MAT_ROWNR(ix); *fixvalue = COL_MAT_VALUE(ix); absvalue = fabs(*fixvalue); SETMIN(absvalue, 100); tolgap = epsvalue*MAX(1, absvalue); chsign = is_chsign(lp, i); /* Get the constraint value limits based on variable bounds, normalized to LE constraint */ loLim = presolve_sumplumin(lp, i, psdata->rows, FALSE); upLim = presolve_sumplumin(lp, i, psdata->rows, TRUE); if(chsign) { loLim = my_chsign(chsign, loLim); upLim = my_chsign(chsign, upLim); swapREAL(&loLim, &upLim); } /* Check the upper constraint bound for possible violation if the value were to be fixed at 1 */ if(loLim + *fixvalue > lp->orig_rhs[i]+tolgap) { if(*fixvalue < 0) presolve_setstatus(psdata, INFEASIBLE); *fixvalue = 0; break; } /* Check the lower constraint bound for possible violation if the value were to be fixed at 1 */ range = get_rh_range(lp, i); if(!my_infinite(lp, range) && (upLim + *fixvalue < lp->orig_rhs[i]-range-tolgap)) { if(*fixvalue > 0) presolve_setstatus(psdata, INFEASIBLE); *fixvalue = 0; break; } /* Check if we have to fix the value at 1 to avoid constraint infeasibility */ if(psdata->rows->infcount[i] >= 1) continue; if(((*fixvalue < 0) && (upLim + *fixvalue >= loLim-tolgap) && (upLim > lp->orig_rhs[i]+tolgap)) || ((*fixvalue > 0) && (loLim + *fixvalue <= upLim+tolgap) && (loLim < lp->orig_rhs[i]-range-tolgap) && !my_infinite(lp, range))) { *fixvalue = 1; break; } } status = (MYBOOL) (ix >= 0); /* Returns TRUE if fixing opportunity was identified */ return( status ); } #endif STATIC int presolve_probetighten01(presolverec *psdata, int colnr) { lprec *lp = psdata->lp; MYBOOL chsign; int i, ix, item, n = 0; REAL upLim, value, absvalue, epsvalue = psdata->epsvalue; MATrec *mat = lp->matA; #if 0 /* Handled in calling routine */ if(!is_binary(lp, colnr)) return( n ); #endif /* Loop over all active rows and do coefficient tightening for qualifying constraints */ item = 0; for(ix = presolve_nextrow(psdata, colnr, &item); ix >= 0; ix = presolve_nextrow(psdata, colnr, &item)) { i = COL_MAT_ROWNR(ix); value = COL_MAT_VALUE(ix); chsign = is_chsign(lp, i); upLim = presolve_sumplumin(lp, i, psdata->rows, (MYBOOL) !chsign); upLim = my_chsign(chsign, upLim); /* Does this constraint qualify for coefficient tightening? */ absvalue = fabs(value); if(upLim - absvalue < lp->orig_rhs[i]-epsvalue*MAX(1, absvalue)) { REAL delta = lp->orig_rhs[i] - upLim; lp->orig_rhs[i] = upLim; upLim = value - my_chsign(value < 0, delta); COL_MAT_VALUE(ix) = upLim; if(my_sign(value) != my_sign(upLim)) { if(chsign) { psdata->rows->negcount[i]--; psdata->rows->plucount[i]++; } else { psdata->rows->negcount[i]++; psdata->rows->plucount[i]--; } } n++; } } return( n ); } STATIC int presolve_mergerows(presolverec *psdata, int *nRows, int *nSum) { lprec *lp = psdata->lp; MYBOOL candelete; int status = RUNNING, item1, item2, firstix, RT1, RT2, i, ix, iix, j, jjx, n = 0; REAL Value1, Value2, bound; MATrec *mat = lp->matA; for(i = lastActiveLink(psdata->rows->varmap); (i > 0) && (status == RUNNING); ) { /* First scan for rows with identical row lengths */ ix = prevActiveLink(psdata->rows->varmap, i); if(ix == 0) break; /* Don't bother about empty rows or row singletons, since they are handled by PRESOLVE_ROWS */ j = presolve_rowlength(psdata, i); if(j <= 1) { i = ix; continue; } #if 0 /* Enable this to scan all rows back */ RT2 = lp->rows; /* Check abort since this section can be pretty "expensive" */ if(!presolve_statuscheck(psdata, &status)) return( status ); #else RT2 = 2+1; #endif firstix = ix; for(RT1 = 0; (ix > 0) && (RT1 < RT2) && (status == RUNNING); ix = prevActiveLink(psdata->rows->varmap, ix), RT1++) { candelete = FALSE; if(presolve_rowlength(psdata, ix) != j) continue; /* Check if the beginning columns are identical; if not, continue */ item1 = 0; iix = presolve_nextcol(psdata, ix, &item1); item2 = 0; jjx = presolve_nextcol(psdata, i, &item2); if(ROW_MAT_COLNR(iix) != ROW_MAT_COLNR(jjx)) continue; /* We have a candidate row; check if the entries have a fixed non-zero ratio */ Value1 = get_mat_byindex(lp, iix, TRUE, FALSE); Value2 = get_mat_byindex(lp, jjx, TRUE, FALSE); bound = Value1 / Value2; Value1 = bound; /* Loop over remaining entries */ jjx = presolve_nextcol(psdata, i, &item2); for(; (jjx >= 0) && (Value1 == bound); jjx = presolve_nextcol(psdata, i, &item2)) { iix = presolve_nextcol(psdata, ix, &item1); if(ROW_MAT_COLNR(iix) != ROW_MAT_COLNR(jjx)) break; Value1 = get_mat_byindex(lp, iix, TRUE, FALSE); Value2 = get_mat_byindex(lp, jjx, TRUE, FALSE); /* If the ratio is different from the reference value we have a mismatch */ Value1 = Value1 / Value2; if(bound == lp->infinite) bound = Value1; else if(fabs(Value1 - bound) > psdata->epsvalue) break; } /* Check if we found a match (we traversed all active columns without a break) */ if(jjx < 0) { /* Get main reference values */ Value1 = lp->orig_rhs[ix]; Value2 = lp->orig_rhs[i] * bound; /* First check for inconsistent equalities */ if((fabs(Value1 - Value2) > psdata->epsvalue) && ((get_constr_type(lp, ix) == EQ) && (get_constr_type(lp, i) == EQ))) { report(lp, NORMAL, "presolve_mergerows: Inconsistent equalities %d and %d found\n", ix, i); status = presolve_setstatus(psdata, INFEASIBLE); } else { /* Update lower and upper bounds */ if(is_chsign(lp, i) != is_chsign(lp, ix)) bound = -bound; Value1 = get_rh_lower(lp, i); if(Value1 <= -lp->infinite) Value1 *= my_sign(bound); else Value1 *= bound; my_roundzero(Value1, lp->epsdual); /* Extra rounding tolerance *** */ Value2 = get_rh_upper(lp, i); if(Value2 >= lp->infinite) Value2 *= my_sign(bound); else Value2 *= bound; my_roundzero(Value2, lp->epsdual); /* Extra rounding tolerance *** */ if((bound < 0)) swapREAL(&Value1, &Value2); bound = get_rh_lower(lp, ix); if(Value1 > bound + psdata->epsvalue) set_rh_lower(lp, ix, Value1); else Value1 = bound; bound = get_rh_upper(lp, ix); if(Value2 < bound - psdata->epsvalue) set_rh_upper(lp, ix, Value2); else Value2 = bound; /* Check results and make equality if appropriate */ if(fabs(Value2-Value1) < psdata->epsvalue) presolve_setEQ(psdata, ix); else if(Value2 < Value1) { status = presolve_setstatus(psdata, INFEASIBLE); } /* Verify if we can continue */ candelete = (MYBOOL) (status == RUNNING); if(!candelete) { report(lp, NORMAL, "presolve: Range infeasibility found involving rows %s and %s\n", get_row_name(lp, ix), get_row_name(lp, i)); } } } /* Perform i-row deletion if authorized */ if(candelete) { presolve_rowremove(psdata, i, TRUE); n++; break; } } i = firstix; } (*nRows) += n; (*nSum) += n; return( status ); } STATIC MYBOOL presolve_reduceGCD(presolverec *psdata, int *nn, int *nb, int *nsum) { lprec *lp = psdata->lp; MYBOOL status = TRUE; int i, jx, je, in = 0, ib = 0; LLONG GCDvalue; REAL *Avalue, Rvalue, epsvalue = psdata->epsvalue; MATrec *mat = lp->matA; for(i = firstActiveLink(psdata->INTmap); i != 0; i = nextActiveLink(psdata->INTmap, i)) { /* Obtain the row GCD */ jx = mat->row_end[i - 1]; je = mat->row_end[i]; Rvalue = ROW_MAT_VALUE(jx); GCDvalue = abs((int) Rvalue); jx++; if(jx < je) for(; (jx < je) && (GCDvalue > 1); jx++) { Rvalue = fabs(ROW_MAT_VALUE(jx)); GCDvalue = gcd((LLONG) Rvalue, GCDvalue, NULL, NULL); } /* Reduce the coefficients, if possible */ if(GCDvalue > 1) { jx = mat->row_end[i - 1]; je = mat->row_end[i]; for(; jx < je; jx++) { Avalue = &ROW_MAT_VALUE(jx); *Avalue /= GCDvalue; in++; } Rvalue = (lp->orig_rhs[i] / GCDvalue) + epsvalue; lp->orig_rhs[i] = floor(Rvalue); Rvalue = fabs(lp->orig_rhs[i]-Rvalue); if(is_constr_type(lp, i, EQ) && (Rvalue > epsvalue)) { report(lp, NORMAL, "presolve_reduceGCD: Infeasible equality constraint %d\n", i); status = FALSE; break; } if(!my_infinite(lp, lp->orig_upbo[i])) lp->orig_upbo[i] = floor(lp->orig_upbo[i] / GCDvalue); ib++; } } if(status && (in > 0)) report(lp, DETAILED, "presolve_reduceGCD: Did %d constraint coefficient reductions.\n", in); (*nn) += in; (*nb) += ib; (*nsum) += in + ib; return( status ); } STATIC int presolve_knapsack(presolverec *psdata, int *nn) { lprec *lp = psdata->lp; int m, n, i, ix, j, jx, colnr, *rownr = NULL, status = RUNNING; REAL *colOF = lp->orig_obj, value, *ratio = NULL; LLrec *map = psdata->EQmap; MATrec *mat = lp->matA; /* Check if it is worth trying */ m = mat->row_end[0]; if((map->count == 0) || (m < 2)) return( status ); /* Get the OF row */ allocINT(lp, &rownr, map->count+1, FALSE); allocREAL(lp, &ratio, map->count+1, FALSE); /* Loop over each row trying to find equal entries in the OF */ rownr[0] = 0; for(i = firstActiveLink(map); i != 0; i = nextActiveLink(map, i)) { if(get_rh(lp, i) <= 0) continue; jx = mat->row_end[i]; n = 0; for(j = mat->row_end[i-1]; j < jx; j++, n++) { colnr = ROW_MAT_COLNR(j); value = ROW_MAT_VALUE(j); if(colOF[colnr] == 0) break; if(n == 0) { ratio[0] = colOF[colnr] / value; } else if(fabs(value * ratio[0] - colOF[colnr]) > psdata->epsvalue) { n = -1; break; } } /* Register row if we were successful (and row long enough) */ if(n >= 2) { ix = ++rownr[0]; rownr[ix] = i; ratio[ix] = ratio[0]; } } n = rownr[0]; if(n == 0) goto Finish; /* Process the identified rows, eliminating the OF value */ for(ix = 1; ix <= n; ix++) { i = rownr[ix]; jx = mat->row_end[i]; for(j = mat->row_end[i-1]; j < jx; j++) { colnr = ROW_MAT_COLNR(j); colOF[colnr] = 0; } } /* Update key mapper structures */ j = lp->columns; psdata->cols->varmap = cloneLink(psdata->cols->varmap, j+n, TRUE); psdata->forceupdate = TRUE; /* Finally, add helper columns */ for(ix = 1; ix <= n; ix++) { i = rownr[ix]; rownr[0] = 0; colOF[0] = my_chsign(is_maxim(lp), ratio[ix]); rownr[1] = i; colOF[1] = -1; value = get_rh(lp, i); /* j = get_constr_type(lp, i); */ add_columnex(lp, 2, colOF, rownr); set_bounds(lp, lp->columns, value, value); /* presolve_setEQ(psdata, i); */ set_rh(lp, i, 0); appendLink(psdata->cols->varmap, j+ix); } presolve_validate(psdata, TRUE); /* Clean up before returning */ Finish: FREE(rownr); FREE(ratio); (*nn) += n; return( status ); } STATIC MYBOOL presolve_invalideq2(lprec *lp, presolverec *psdata) { int jx, jjx, i = 0, item; MATrec *mat = lp->matA; MYBOOL error = FALSE; do { if(i == 0) i = firstActiveLink(psdata->EQmap); else i = nextActiveLink(psdata->EQmap, i); if(i == 0) return( error ); /* Get the row index of the first 2-element equality */ for(; i > 0; i = nextActiveLink(psdata->EQmap, i)) if(presolve_rowlength(psdata, i) == 2) break; if(i == 0) return( error ); /* Get the first column */ item = 0; jx = presolve_nextcol(psdata, i, &item); if(jx < 0) error = TRUE; jx = ROW_MAT_COLNR(jx); /* Get the second column */ jjx = presolve_nextcol(psdata, i, &item); if(jjx < 0) error = AUTOMATIC; } while(!error); return( error ); } /* Callback to obtain the non-zero rows of equality constraints */ int BFP_CALLMODEL presolve_getcolumnEQ(lprec *lp, int colnr, REAL nzvalues[], int nzrows[], int mapin[]) { int i, ib, ie, nn = 0; MATrec *mat = lp->matA; ib = mat->col_end[colnr-1]; ie = mat->col_end[colnr]; for(; ib < ie; ib++) { i = COL_MAT_ROWNR(ib); if(!is_constr_type(lp, i, EQ) || /* It has to be an equality constraint */ (mapin[i] == 0)) /* And it should not already have been deleted */ continue; if(nzvalues != NULL) { nzrows[nn] = mapin[i]; nzvalues[nn] = COL_MAT_VALUE(ib); } nn++; } return( nn ); } STATIC int presolve_singularities(presolverec *psdata, int *nn, int *nr, int *nv, int *nSum) { lprec *lp = psdata->lp; int i, j, n, *rmapin = NULL, *rmapout = NULL, *cmapout = NULL; if(lp->bfp_findredundant(lp, 0, NULL, NULL, NULL) == 0) return( 0 ); /* Create condensed row map */ allocINT(lp, &rmapin, lp->rows+1, TRUE); allocINT(lp, &rmapout, psdata->EQmap->count+1, FALSE); allocINT(lp, &cmapout, lp->columns+1, FALSE); n = 0; for(i = firstActiveLink(psdata->EQmap); i != 0; i = nextActiveLink(psdata->EQmap, i)) { n++; rmapout[n] = i; rmapin[i] = n; } rmapout[0] = n; n = 0; for(i = firstActiveLink(psdata->cols->varmap); i != 0; i = nextActiveLink(psdata->cols->varmap, i)) { n++; cmapout[n] = i; } cmapout[0] = n; /* Do the rank-revealing factorization */ n = lp->bfp_findredundant(lp, psdata->EQmap->count, presolve_getcolumnEQ, rmapin, cmapout); /* Delete the redundant rows */ for(i = 1; i <= n; i++) { j = rmapin[i]; j = rmapout[j]; presolve_rowremove(psdata, j, TRUE); } (*nn) += n; (*nr) += n; (*nSum) += n; /* Clean up */ FREE(rmapout); FREE(rmapin); FREE(cmapout); return( n ); } STATIC int presolve_elimeq2(presolverec *psdata, int *nn, int *nr, int *nc, int *nSum) { lprec *lp = psdata->lp; int n, i, jx, jjx, k, item, *plucount, *negcount, colplu, colneg, iCoeffChanged = 0, iRowsRemoved = 0, iVarsFixed = 0, nrows = lp->rows, status = RUNNING, *colindex = NULL; MYBOOL freshupdate; REAL Coeff1, Coeff2, Value1, Value2, lobound, upbound, bound, test, product, *colvalue = NULL, *delvalue = NULL, *colitem; MATrec *mat = lp->matA, *rev = NULL; DeltaVrec *DV = NULL; LLrec *EQ2 = NULL; /* See if there is anything to do */ if(psdata->EQmap->count == 0) { (*nSum) = 0; return( status ); } /* Tally counts */ createLink(lp->rows, &EQ2, NULL); if((EQ2 == NULL) || !allocREAL(lp, &colvalue, nrows+1, FALSE) || !allocREAL(lp, &delvalue, nrows+1, FALSE)) goto Finish; for(i = firstActiveLink(psdata->EQmap); i > 0; i = nextActiveLink(psdata->EQmap, i)) { if(presolve_rowlength(psdata, i) == 2) appendLink(EQ2, i); } if(EQ2->count == 0) goto Finish; n = 0; /* Do the elimination loop for all identified 2-element equalities */ for(i = firstActiveLink(EQ2); i > 0; i = nextActiveLink(EQ2, i)) { /* Check if the constraint has been modified by a previous elimination */ if(presolve_rowlength(psdata, i) != 2) continue; /* Get the column indeces of NZ-values of the "pivot" row */ item = 0; jx = presolve_nextcol(psdata, i, &item); /* Eliminated variable coefficient b */ #ifdef Paranoia if(jx < 0) report(lp, SEVERE, "presolve_elimeq2: No qualifying %dst column was found in row %s (ostensible length %d)\n", 1, get_row_name(lp, i), presolve_rowlength(psdata, i)); #endif Coeff2 = ROW_MAT_VALUE(jx); jx = ROW_MAT_COLNR(jx); jjx = presolve_nextcol(psdata, i, &item); /* Non-eliminated variable coefficient a */ #ifdef Paranoia if(jjx < 0) report(lp, SEVERE, "presolve_elimeq2: No qualifying %dnd column was found in row %s (ostensible length %d)\n", 2, get_row_name(lp, i), presolve_rowlength(psdata, i)); #endif Coeff1 = ROW_MAT_VALUE(jjx); jjx = ROW_MAT_COLNR(jjx); /* Check if at least one of the coefficients is large enough to preserve stability; use opposing maximum column values for stability testing. */ if((fabs(Coeff1) < psdata->epspivot*mat->colmax[jx]) && ((fabs(Coeff1) != 1) && (fabs(Coeff2) != 1)) && (fabs(Coeff2) < psdata->epspivot*mat->colmax[jjx])) continue; /* Cannot eliminate a variable if both are SOS members or SC variables */ if((is_semicont(lp, jx) && is_semicont(lp, jjx)) || (SOS_is_member(lp->SOS, 0, jx) && SOS_is_member(lp->SOS, 0, jjx))) continue; /* First check if we are allowed to swap; set swap "blockers" */ k = 0; if(!is_int(lp, jx) && is_int(lp, jjx)) k += 1; else if(!is_semicont(lp, jx) && is_semicont(lp, jjx)) k += 2; else if(!SOS_is_member(lp->SOS, 0, jx) && SOS_is_member(lp->SOS, 0, jjx)) k += 4; /* If there were no blockers, determine if we MUST swap the variable to be eliminated */ if(k == 0) { if(is_int(lp, jx) && !is_int(lp, jjx)) k += 8; else if(is_semicont(lp, jx) && !is_semicont(lp, jjx)) k += 16; else if(SOS_is_member(lp->SOS, 0, jx) && !SOS_is_member(lp->SOS, 0, jjx)) k += 32; /* If we are not forced to swap, decide if it otherwise makes sense - high order */ if(k == 0) { if((fabs(Coeff2) < psdata->epspivot*mat->colmax[jjx]) && (fabs(Coeff1) > psdata->epspivot*mat->colmax[jx])) k += 64; else if(presolve_collength(psdata, jx) > presolve_collength(psdata, jjx)) k += 128; } /* If we are not forced to swap, decide if it otherwise makes sense - low order */ if(k == 0) { Value2 = Coeff1/Coeff2; #ifdef DualFeasibilityLogicEQ2 if((Value2*lp->orig_obj[jx] < 0) && (Value2*lp->orig_obj[jjx] > 0)) /* Seek increased dual feasibility */ k += 256; #endif #ifdef DivisorIntegralityLogicEQ2 if((fabs(modf(Coeff2, &Value2)) >= lp->epsvalue) && /* Seek integrality of result */ (fabs(modf(Coeff1, &Value2)) < lp->epsvalue)) k += 512; else if((fabs(fabs(Coeff2)-1) >= lp->epsvalue) && /* Seek integrality of divisor */ (fabs(fabs(Coeff1)-1) < lp->epsvalue)) k += 1024; #endif } } else k = 0; /* Perform variable index swap if indicated */ if(k != 0) { swapINT(&jx, &jjx); swapREAL(&Coeff1, &Coeff2); } Value1 = lp->orig_rhs[i]/Coeff2; /* Delta constant term */ Value2 = Coeff1/Coeff2; /* Delta variable term */ upbound = lp->orig_upbo[lp->rows+jx]; lobound = lp->orig_lowbo[lp->rows+jx]; if(lp->spx_trace) { report(lp, DETAILED, "Row %3d : Elim %g %s - %d\n", i, Coeff2, get_col_name(lp, jx), jx); report(lp, DETAILED, " Keep %g %s - %d\n", Coeff1, get_col_name(lp, jjx), jjx); } /* Get the coefficient vectors of the independent (jjx) and dependent (jx) columns; the dependent column will be deleted and reconstructed during postsolve. */ freshupdate = (MYBOOL) ((colindex == NULL) || (colindex[jjx] == 0)); if(freshupdate) mat_expandcolumn(mat, jjx, colvalue, NULL, TRUE); else mat_expandcolumn(rev, colindex[jjx], colvalue, NULL, FALSE); if((colindex == NULL) || (colindex[jx] == 0)) mat_expandcolumn(mat, jx, delvalue, NULL, TRUE); else mat_expandcolumn(rev, colindex[jx], delvalue, NULL, FALSE); /* Add variable reconstruction information */ addUndoPresolve(lp, TRUE, jx, Value1, Value2, jjx); /* If possible, tighten the bounds of the uneliminated variable based on the bounds of the eliminated variable. Also handle roundings and attempt precision management. */ bound = lobound; k = nrows+jjx; if(bound > -lp->infinite) { bound = (lp->orig_rhs[i] - Coeff2*bound) / Coeff1; if(Value2 > 0) { test = lp->orig_upbo[k]; if(bound < test - psdata->epsvalue) { if(is_int(lp, jjx)) lp->orig_upbo[k] = floor(bound + lp->epsint); else lp->orig_upbo[k] = presolve_roundrhs(lp, bound, FALSE); } } else { test = lp->orig_lowbo[k]; if(bound > test + psdata->epsvalue) { if(is_int(lp, jjx)) lp->orig_lowbo[k] = ceil(bound - lp->epsint); else lp->orig_lowbo[k] = presolve_roundrhs(lp, bound, TRUE); } } } bound = upbound; if(bound < lp->infinite) { bound = (lp->orig_rhs[i] - Coeff2*bound) / Coeff1; if(Value2 < 0) { test = lp->orig_upbo[k]; if(bound < test - psdata->epsvalue) { if(is_int(lp, jjx)) lp->orig_upbo[k] = floor(bound + lp->epsint); else lp->orig_upbo[k] = presolve_roundrhs(lp, bound, FALSE); } } else { test = lp->orig_lowbo[k]; if(bound > test + psdata->epsvalue) { if(is_int(lp, jjx)) lp->orig_lowbo[k] = ceil(bound - lp->epsint); else lp->orig_lowbo[k] = presolve_roundrhs(lp, bound, TRUE); } } } #ifdef Eq2Reldiff test = 2*lp->epsvalue; #else test = psdata->epsvalue; #endif if(/*(lp->orig_upbo[k] < lp->orig_lowbo[k]) ||*/ #ifdef Eq2Reldiff (fabs(my_reldiff(lp->orig_upbo[k],lp->orig_lowbo[k])) < test)) { #else (fabs(lp->orig_upbo[k] - lp->orig_lowbo[k]) < test)) { #endif my_roundzero(lp->orig_lowbo[k], test); lp->orig_upbo[k] = lp->orig_lowbo[k]; } else { my_roundzero(lp->orig_upbo[k], test); my_roundzero(lp->orig_lowbo[k], test); } if(/*(upbound < lobound) ||*/ #ifdef Eq2Reldiff (fabs(my_reldiff(upbound, lobound)) < test)) { #else (fabs(upbound - lobound) < test)) { #endif my_roundzero(lobound, test); lp->orig_upbo[nrows+jx] = lobound; upbound = lobound; } /* Loop over the non-zero rows of the column (jx) to be eliminated; substitute jx-variable by updating rhs and jjx coefficients */ colitem = colvalue; plucount = psdata->rows->plucount; negcount = psdata->rows->negcount; colplu = 0; colneg = 0; /* Count of non-zeros in the independent column jjx */ item = presolve_collength(psdata, jjx) - 1; if(isnz_origobj(lp, jjx)) item++; for(k = 0; k <= nrows; k++, colitem++) { bound = delvalue[k]; if((k == i) || (bound == 0) || ((k > 0) && !isActiveLink(psdata->rows->varmap, k))) continue; /* Do constraint and nz-count updates for the substituted variable */ product = bound*Value1; /* "Raw"/unsigned data */ presolve_adjustrhs(psdata, k, my_chsign(is_chsign(lp, k), product), test); /* Change back to signed part */ if(*colitem != 0) { if(*colitem > 0) { colplu--; plucount[k]--; } else { colneg--; negcount[k]--; } if((lobound < 0) && (upbound >= 0)) { psdata->cols->pluneg[jjx]--; psdata->rows->pluneg[k]--; } item--; } (*colitem) -= bound*Value2; iCoeffChanged++; /* Update counts */ if(fabs(*colitem) >= mat->epsvalue) { if(*colitem > 0) { colplu++; plucount[k]++; } else { colneg++; negcount[k]++; } if((lobound < 0) && (upbound >= 0)) { psdata->cols->pluneg[jjx]++; psdata->rows->pluneg[k]++; } item++; } else { *colitem = 0; } /* Also reduce count if the row contains the deleted variable */ if(bound > 0) plucount[k]--; else negcount[k]--; } psdata->cols->plucount[jjx] += colplu; psdata->cols->negcount[jjx] += colneg; /* Save the new column */ if(rev == NULL) { DV = createUndoLadder(lp, nrows, lp->columns / RESIZEFACTOR); rev = DV->tracker; rev->epsvalue = mat->epsvalue; allocINT(lp, &(rev->col_tag), mat->columns_alloc+1, FALSE); allocINT(lp, &colindex, lp->columns+1, TRUE); rev->col_tag[0] = 0; } n = rev->col_tag[0] = incrementUndoLadder(DV); mat_setcol(rev, n, 0, colvalue, NULL, FALSE, FALSE); rev->col_tag[n] = jjx; /* Save index to updated vector, but specially handle case where we have the same independent variable for multiple equations! */ if(!freshupdate) rev->col_tag[colindex[jjx]] *= -1; colindex[jjx] = n; /* Delete the column dependent variable */ jx = presolve_colremove(psdata, jx, FALSE); iVarsFixed++; /* Check if we have been lucky enough to have eliminated the independent variable via substitution of the dependent variable */ if(item == 0) { #ifdef Paranoia report(lp, DETAILED, "presolve_elimeq2: Was able to remove variables %d and %d in row %s\n", jx, jjx, get_row_name(lp, i)); #endif if(presolve_colfix(psdata, jjx, 0.0, TRUE, nc)) jjx = presolve_colremove(psdata, jjx, FALSE); } /* Delete the row */ presolve_rowremove(psdata, i, FALSE); iRowsRemoved++; } /* Perform the column updates collected above */ if(n > 0) { mat_mapreplace(mat, psdata->rows->varmap, psdata->cols->varmap, rev); presolve_validate(psdata, TRUE); #ifdef PresolveForceUpdateMax mat_computemax(mat /* , FALSE */); #endif psdata->forceupdate = TRUE; } /* Free work arrays */ Finish: if(DV != NULL) freeUndoLadder(&DV); freeLink(&EQ2); FREE(colvalue); FREE(delvalue); FREE(colindex); /* Update counters */ (*nn) += iCoeffChanged; (*nr) += iRowsRemoved; (*nc) += iVarsFixed; (*nSum) += iCoeffChanged + iRowsRemoved + iVarsFixed; return( status ); } STATIC MYBOOL presolve_impliedfree(lprec *lp, presolverec *psdata, int colnr) { int i, ix, ie; REAL Tlower, Tupper; MYBOOL status, rowbinds, isfree = FALSE; MATrec *mat = lp->matA; if(my_infinite(lp, get_lowbo(lp, colnr)) && my_infinite(lp, get_upbo(lp, colnr))) return( TRUE ); ie = mat->col_end[colnr]; for(ix = mat->col_end[colnr-1]; (isfree != (TRUE | AUTOMATIC)) && (ix < ie); ix++) { i = COL_MAT_ROWNR(ix); if(!isActiveLink(psdata->rows->varmap, i)) continue; Tlower = get_rh_lower(lp, i); Tupper = get_rh_upper(lp, i); status = presolve_multibounds(psdata, i, colnr, &Tlower, &Tupper, NULL, &rowbinds); isfree = isfree | status | rowbinds; } return( (MYBOOL) (isfree == (TRUE | AUTOMATIC)) ); } STATIC MYBOOL presolve_impliedcolfix(presolverec *psdata, int rownr, int colnr, MYBOOL isfree) { lprec *lp = psdata->lp; MYBOOL signflip, undoadded = FALSE; MATrec *mat = lp->matA; int jx, i, ib, ie = mat->row_end[rownr]; REAL varLo = 0, varHi = 0, varRange, conRange = 0, matValue = 0, dual, RHS = lp->orig_rhs[rownr], pivot, matAij = mat_getitem(mat, rownr, colnr), *vecOF = lp->orig_obj; /* We cannot have semi-continuous or non-qualifying integers */ if(is_semicont(lp, colnr) || is_SOS_var(lp, colnr)) return( FALSE ); if(is_int(lp, colnr)) { if(!isActiveLink(psdata->INTmap, rownr) || !is_presolve(lp, PRESOLVE_KNAPSACK)) return( FALSE ); /* colnr must have a coefficient equal to the smallest in the row */ varRange = lp->infinite; i = 0; pivot = 0; for(ib = presolve_nextcol(psdata, rownr, &i); i != 0; ib = presolve_nextcol(psdata, rownr, &i)) { jx = ROW_MAT_COLNR(ib); dual = fabs(ROW_MAT_VALUE(ib)); /* Check if we have the target column and save the pivot value */ if(jx == colnr) { /* Always accept unit coefficient */ if(fabs(dual - 1) < psdata->epsvalue) break; pivot = dual; /* Otherwise continue scan */ } /* Cannot accept case where result can be fractional */ else if((pivot > dual + psdata->epsvalue) || ((pivot > 0) && (fabs(fmod(dual, pivot)) > psdata->epsvalue))) return( FALSE ); } } /* Ascertain that the pivot value is large enough to preserve stability */ pivot = matAij; if(fabs(pivot) < psdata->epspivot*mat->colmax[colnr]) return( FALSE ); /* Must ascertain that the row variables are not SOS'es; this is because the eliminated variable will be a function of another variable. */ if(SOS_count(lp) > 0) { for(ib = mat->row_end[rownr-1]; ib < ie; ib++) if(SOS_is_member(lp->SOS, 0, ROW_MAT_COLNR(ib))) return( FALSE ); } /* Calculate the dual value */ dual = vecOF[colnr]/pivot; /* Here we have free variable in an equality constraint; this means we can can adjust the OF for the deleted variable and also delete the constraint. */ if(isfree && is_constr_type(lp, rownr, EQ)) { matValue = RHS/pivot; if(matValue != 0) undoadded = addUndoPresolve(lp, TRUE, colnr, matValue, 0.0, 0); } else { /* IMPLIEDFREE: For simplicity, ensure that we can keep the slack based at 0, and not its upper bound. Effectively, we consider the constraint an equality, using the information of the sign of the dual. IMPLIEDSLK: Since we already have an equality constraint, we wish to make sure that the ensuing inequality constraint will have an RHS that is non-infinite. */ if(isfree) { SETMIN(RHS, presolve_sumplumin(lp, rownr, psdata->rows, TRUE)); matValue = presolve_sumplumin(lp, rownr, psdata->rows, FALSE); conRange = get_rh_lower(lp, rownr); conRange = RHS - MAX(matValue, conRange); signflip = (MYBOOL) ((dual > 0) && !my_infinite(lp, conRange)); } else { varLo = get_lowbo(lp, colnr); varLo *= (my_infinite(lp, varLo) ? my_sign(pivot) : pivot); varHi = get_upbo(lp, colnr); varHi *= (my_infinite(lp, varHi) ? my_sign(pivot) : pivot); if(pivot < 0) swapREAL(&varHi, &varLo); signflip = my_infinite(lp, varLo); } if(signflip) { mat_multrow(mat, rownr, -1); RHS -= conRange; RHS = -RHS; lp->orig_rhs[rownr] = RHS; pivot = -pivot; dual = -dual; if(!isfree) { varLo = -varLo; varHi = -varHi; swapREAL(&varHi, &varLo); } } matValue = RHS/pivot; /* Prepare for deleting free or implied free variable in inequality constraint. Different strategies need to be used: ACTUAL: Find the proper constraint bound and store undo information for recovering the value of the implied free variable. The constraint is then deleted. We have to adjust the objective function if the OF coefficient for the implied free variable is non-zero. IMPLIED: Convert the constraint to an inequality at the proper bound. For given models, the new equality constraint can later provide an implied slack, which means that a further variable is eliminated, and the constraint again becomes an inequality constraint. Note that this version only implements the ACTUAL mode */ if(isfree) { /* Add undo information connecting the deleted variable to the RHS */ if(matValue != 0) undoadded = addUndoPresolve(lp, TRUE, colnr, matValue, 0.0, 0); /* Add undo information for the dual of the deleted constraint */ if(dual != 0) addUndoPresolve(lp, FALSE, rownr, dual, 0.0, 0); } /* Prepare for deleting implied slack variable. The following two cases are handled: 1. Equality constraint: Convert the constraint to an inequality constraint that is possibly ranged 2. Other constraints: Expand existing slack variable / constraint range, if required. */ else { if(my_infinite(lp, varHi)) varRange = lp->infinite; #ifdef Paranoia else if(my_infinite(lp, varLo)) { report(lp, SEVERE, "presolve_impliedcolfix: Negative infinite limit for variable %d\n", colnr); varRange = lp->infinite; } #endif else varRange = my_precision(fabs(varHi - varLo) + lp->epsvalue, psdata->epsvalue); presolve_adjustrhs(psdata, rownr, varLo, psdata->epsvalue); /* Handle case 1 of an equality constraint */ if(is_constr_type(lp, rownr, EQ)) { /* Make sure we actually have a ranged constraint */ if(varRange > 0) { set_constr_type(lp, rownr, LE); if(!my_infinite(lp, varRange)) lp->orig_upbo[rownr] = varRange; setLink(psdata->LTmap, rownr); removeLink(psdata->EQmap, rownr); } } /* Handle case 2 of an inequality constraint (UNDER CONSTRUCTION!)*/ else { if(!my_infinite(lp, lp->orig_upbo[rownr])) { if(my_infinite(lp, varRange)) lp->orig_upbo[rownr] = lp->infinite; else lp->orig_upbo[rownr] += varHi - varLo; } } /* Update counts */ if(matAij > 0) psdata->rows->plucount[rownr]--; else psdata->rows->negcount[rownr]--; if(my_sign(varLo) != my_sign(varHi)) psdata->rows->pluneg[rownr]--; /* Add undo information for the deleted variable; note that we cannot link the deleted variable to the slack, since it may not be available during undo. We really should have a mini LP to compute this allocation ex-post. */ if(RHS != 0) undoadded = addUndoPresolve(lp, TRUE, colnr, RHS/pivot, 0.0, 0); } } /* Update the OF constant */ if(dual != 0) { presolve_adjustrhs(psdata, 0, dual * RHS, 0); /* lp->orig_rhs[0] -= dual * RHS; */ vecOF[colnr] = 0; } /* Do affine transformation with the constraint row */ i = 0; for(ib = presolve_nextcol(psdata, rownr, &i); ib >= 0; ib = presolve_nextcol(psdata, rownr, &i)) { /* Get the constraint element */ jx = ROW_MAT_COLNR(ib); if(jx == colnr) continue; matValue = ROW_MAT_VALUE(ib); /* Adjust OF for the variable to be deleted */ if(dual != 0) vecOF[jx] -= dual * matValue; /* Add reconstruction/undo parameters for the deleted variable */ if(!undoadded) undoadded = addUndoPresolve(lp, TRUE, colnr, 0.0, matValue/pivot, jx); else appendUndoPresolve(lp, TRUE, matValue/pivot, jx); } return( TRUE ); } STATIC psrec *presolve_initpsrec(lprec *lp, int size) { psrec *ps = (psrec *) calloc(1, sizeof(*ps)); createLink(size, &ps->varmap, NULL); fillLink(ps->varmap); size++; allocINT(lp, &ps->empty, size, FALSE); ps->empty[0] = 0; allocREAL(lp, &ps->pluupper, size, FALSE); allocREAL(lp, &ps->negupper, size, FALSE); allocREAL(lp, &ps->plulower, size, FALSE); allocREAL(lp, &ps->neglower, size, FALSE); allocINT(lp, &ps->infcount, size, FALSE); ps->next = (int **) calloc(size, sizeof(*(ps->next))); allocINT(lp, &ps->plucount, size, TRUE); allocINT(lp, &ps->negcount, size, TRUE); allocINT(lp, &ps->pluneg, size, TRUE); ps->allocsize = size; return( ps ); } STATIC void presolve_freepsrec(psrec **ps) { FREE((*ps)->plucount); FREE((*ps)->negcount); FREE((*ps)->pluneg); FREE((*ps)->infcount); if((*ps)->next != NULL) { int i, n = (*ps)->allocsize; for(i = 0; i < n; i++) FREE((*ps)->next[i]); FREE((*ps)->next); } FREE((*ps)->plulower); FREE((*ps)->neglower); FREE((*ps)->pluupper); FREE((*ps)->negupper); FREE((*ps)->empty); freeLink(&(*ps)->varmap); FREE(*ps); } STATIC presolverec *presolve_init(lprec *lp) { int k, i, ix, ixx, colnr, ncols = lp->columns, nrows = lp->rows; REAL hold; MATrec *mat = lp->matA; presolverec *psdata = NULL; /* Optimize memory usage if we have a very large model; this is to reduce the risk of out-of-memory situations. */ ix = get_nonzeros(lp); ixx = lp->matA->mat_alloc; if((ixx - ix > MAT_START_SIZE) && ((ixx - ix) * 20 > ixx)) mat_memopt(lp->matA, nrows / 20, ncols / 20, ix / 20); psdata = (presolverec *) calloc(1, sizeof(*psdata)); psdata->lp = lp; psdata->rows = presolve_initpsrec(lp, nrows); psdata->cols = presolve_initpsrec(lp, ncols); psdata->epsvalue = PRESOLVE_EPSVALUE; psdata->epspivot = PRESOLVE_EPSPIVOT; psdata->forceupdate = TRUE; /* Save incoming primal bounds */ k = lp->sum + 1; allocREAL(lp, &psdata->pv_lobo, k, FALSE); MEMCOPY(psdata->pv_lobo, lp->orig_lowbo, k); allocREAL(lp, &psdata->pv_upbo, k, FALSE); MEMCOPY(psdata->pv_upbo, lp->orig_upbo, k); /* Create and initialize dual value (Langrangean and slack) limits */ allocREAL(lp, &psdata->dv_lobo, k, FALSE); allocREAL(lp, &psdata->dv_upbo, k, FALSE); for(i = 0; i <= nrows; i++) { psdata->dv_lobo[i] = (is_constr_type(lp, i, EQ) ? -lp->infinite : 0); psdata->dv_upbo[i] = lp->infinite; } k--; for(; i <= k; i++) { psdata->dv_lobo[i] = 0; psdata->dv_upbo[i] = lp->infinite; } /* Create NZ count and sign arrays, and do general initialization of row bounds */ createLink(nrows, &psdata->EQmap, NULL); createLink(nrows, &psdata->LTmap, NULL); createLink(nrows, &psdata->INTmap, NULL); for(i = 1; i <= nrows; i++) { switch (get_constr_type(lp, i)) { case LE: appendLink(psdata->LTmap, i); break; case EQ: appendLink(psdata->EQmap, i); break; } k = mat_rowlength(mat, i); if((lp->int_vars > 0) && (k > 0)) appendLink(psdata->INTmap, i); } /* Seek to reduce set of sum(INT*INT) rows (mainly for GCD coefficient reductions) */ if(psdata->INTmap->count > 0) for(i = 1; i <= nrows; i++) { if(!isActiveLink(psdata->INTmap, i)) continue; /* Disqualify if there is a non-int variable, otherwise find smallest absolute fractional row value */ ix = mat->row_end[i - 1]; ixx = mat->row_end[i]; colnr = 0; for(; ix < ixx; ix++) { if(!is_int(lp, ROW_MAT_COLNR(ix))) { removeLink(psdata->INTmap, i); break; } hold = fabs(ROW_MAT_VALUE(ix)); hold = fmod(hold, 1); /* Adjust colnr to be a decimal scalar */ for(k = 0; (k <= MAX_FRACSCALE) && (hold+psdata->epsvalue < 1); k++) hold *= 10; if(k > MAX_FRACSCALE) { removeLink(psdata->INTmap, i); break; } SETMAX(colnr, k); } if(!isActiveLink(psdata->INTmap, i)) continue; hold = pow(10.0, colnr); /* Also disqualify if the RHS is fractional after scaling */ if(fabs(fmod(lp->orig_rhs[i] * hold, 1)) > psdata->epsvalue) { removeLink(psdata->INTmap, i); continue; } /* We have an all-int constraint, see if we should scale it up */ if(k > 0) { ix = mat->row_end[i - 1]; for(; ix < ixx; ix++) { ROW_MAT_VALUE(ix) *= hold; } lp->orig_rhs[i] *= hold; if(!my_infinite(lp, lp->orig_upbo[i])) lp->orig_upbo[i] *= hold; /* KE: Fix due to Andy Loto - 20070619 */ } } /* Do the real tallying and ordering work */ presolve_validate(psdata, TRUE); return( psdata ); } STATIC void presolve_free(presolverec **psdata) { presolve_freepsrec(&(*psdata)->rows); presolve_freepsrec(&(*psdata)->cols); FREE((*psdata)->dv_lobo); FREE((*psdata)->dv_upbo); FREE((*psdata)->pv_lobo); FREE((*psdata)->pv_upbo); freeLink(&(*psdata)->EQmap); freeLink(&(*psdata)->LTmap); freeLink(&(*psdata)->INTmap); FREE(*psdata); } STATIC int presolve_makefree(presolverec *psdata) { lprec *lp = psdata->lp; int i, ix, j, nn = 0; REAL Xlower, Xupper, losum, upsum, lorhs, uprhs, freeinf = lp->infinite / 10; MATrec *mat = lp->matA; LLrec *colLL = NULL; /* First see if we can relax ranged constraints */ for(i = firstActiveLink(psdata->rows->varmap); i != 0; i = nextActiveLink(psdata->rows->varmap, i)) { if(is_constr_type(lp, i, EQ)) continue; presolve_range(lp, i, psdata->rows, &losum, &upsum); lorhs = get_rh_lower(lp, i); uprhs = get_rh_upper(lp, i); /* Look for opportunity to relax constraint bounds */ if(presolve_rowlength(psdata, i) > 1) { if((is_constr_type(lp, i, GE) && (upsum <= uprhs)) || (is_constr_type(lp, i, LE) && (losum >= lorhs))) set_rh_range(lp, i, lp->infinite); } } /* Collect columns available for bound relaxation (find implied free variables) (consider sorting the list in decending order of column lengths or do call to COLAMD to maximize impact) */ createLink(lp->columns, &colLL, NULL); for(j = firstActiveLink(psdata->cols->varmap); j != 0; j = nextActiveLink(psdata->cols->varmap, j)) if(presolve_impliedfree(lp, psdata, j)) appendLink(colLL, j); /* Find what columns to relax (ideally one per row) */ if(colLL->count > 0) { LLrec *rowLL = NULL; MYBOOL canfree; /* Create row tracker */ createLink(lp->rows, &rowLL, NULL); fillLink(rowLL); /* Loop over all column candidates */ for(j = firstActiveLink(colLL); (j > 0) && (rowLL->count > 0); j = nextActiveLink(colLL, j)) { /* Verify that the variable is applicable */ canfree = TRUE; for(ix = mat->col_end[j-1]; canfree && (ix < mat->col_end[j]); ix++) canfree = isActiveLink(rowLL, COL_MAT_ROWNR(ix)); /* If so, then open the bounds and update the row availability mapper */ if(canfree) { nn++; Xlower = get_lowbo(lp, j); Xupper = get_upbo(lp, j); if(Xlower >= 0) set_bounds(lp, j, 0, freeinf); else if(Xupper <= 0) set_bounds(lp, j, -freeinf, 0); else /* set_bounds(lo, j, -freeinf, freeinf); */ set_unbounded(lp, j); for(ix = mat->col_end[j-1]; ix < mat->col_end[j]; ix++) removeLink(rowLL, COL_MAT_ROWNR(ix)); } } freeLink(&rowLL); } /* Free list and return */ freeLink(&colLL); return( nn ); } STATIC MYBOOL presolve_updatesums(presolverec *psdata) { lprec *lp = psdata->lp; int j; /* Initialize row accumulation arrays */ MEMCLEAR(psdata->rows->pluupper, lp->rows + 1); MEMCLEAR(psdata->rows->negupper, lp->rows + 1); MEMCLEAR(psdata->rows->plulower, lp->rows + 1); MEMCLEAR(psdata->rows->neglower, lp->rows + 1); MEMCLEAR(psdata->rows->infcount, lp->rows + 1); /* Loop over active columns */ for(j = firstActiveLink(psdata->cols->varmap); j != 0; j = nextActiveLink(psdata->cols->varmap, j)) { presolve_colfix(psdata, j, lp->infinite, FALSE, NULL); } #ifdef UseDualPresolve /* Initialize column accumulation arrays */ MEMCLEAR(psdata->cols->pluupper, lp->columns + 1); MEMCLEAR(psdata->cols->negupper, lp->columns + 1); MEMCLEAR(psdata->cols->plulower, lp->columns + 1); MEMCLEAR(psdata->cols->neglower, lp->columns + 1); MEMCLEAR(psdata->cols->infcount, lp->columns + 1); /* Loop over active rows */ for(j = firstActiveLink(psdata->rows->varmap); j != 0; j = nextActiveLink(psdata->rows->varmap, j)) { presolve_rowfix(psdata, j, lp->infinite, FALSE, NULL); } #endif return( TRUE ); } STATIC MYBOOL presolve_finalize(presolverec *psdata) { lprec *lp = psdata->lp; MYBOOL compactvars = FALSE; int ke, n; /* Save eliminated rows and columns for restoration purposes */ #ifdef SavePresolveEliminated psdata->deletedA = mat_extractmat(lp->matA, rowmap, colmap, TRUE); if(!mat_validate(psdata->deletedA)) report(lp, SEVERE, "presolve_finalize: Could not validate matrix with undo data\n"); #endif /* Check if OF columns are to be deleted */ lp->presolve_undo->OFcolsdeleted = FALSE; for(n = firstInactiveLink(psdata->cols->varmap); (n != 0) && !lp->presolve_undo->OFcolsdeleted; n = nextInactiveLink(psdata->cols->varmap, n)) lp->presolve_undo->OFcolsdeleted = (MYBOOL) (lp->orig_obj[n] != 0); /* Delete eliminated columns */ ke = lastInactiveLink(psdata->cols->varmap); n = countInactiveLink(psdata->cols->varmap); if((n > 0) && (ke > 0)) { del_columnex(lp, psdata->cols->varmap); mat_colcompact(lp->matA, lp->presolve_undo->orig_rows, lp->presolve_undo->orig_columns); compactvars = TRUE; } /* Delete eliminated rows */ ke = lastInactiveLink(psdata->rows->varmap); n = countInactiveLink(psdata->rows->varmap); if((n > 0) && (ke > 0)) { del_constraintex(lp, psdata->rows->varmap); mat_rowcompact(lp->matA, TRUE); compactvars = TRUE; } else if(psdata->nzdeleted > 0) mat_zerocompact(lp->matA); /* Do compacting and updating of variable maps */ if(compactvars) varmap_compact(lp, lp->presolve_undo->orig_rows, lp->presolve_undo->orig_columns); /* Reduce memory usage of postsolve matrices */ if(lp->presolve_undo->primalundo != NULL) mat_memopt(lp->presolve_undo->primalundo->tracker, 0, 0, 0); if(lp->presolve_undo->dualundo != NULL) mat_memopt(lp->presolve_undo->dualundo->tracker, 0, 0, 0); /* Round near-zero objective function coefficients and RHS values */ ke = lp->columns; for(n = 1; n <= ke; n++) my_roundzero(lp->orig_obj[n], lp->epsvalue); ke = lp->rows; for(n = 1; n <= ke; n++) my_roundzero(lp->orig_rhs[n], lp->epsvalue); /* Update the SOS sparse mapping */ if(SOS_count(lp) > 0) SOS_member_updatemap(lp->SOS); /* Validate matrix and reconstruct row indexation */ return(mat_validate(lp->matA)); } STATIC MYBOOL presolve_debugdump(lprec *lp, presolverec *psdata, char *filename, MYBOOL doappend) { FILE *output = stdout; int size; MYBOOL ok; ok = (MYBOOL) ((filename == NULL) || ((output = fopen(filename, my_if(doappend, "a", "w"))) != NULL)); if(!ok) return(ok); if((filename == NULL) && (lp->outstream != NULL)) output = lp->outstream; fprintf(output, "\nPRESOLVE - Status at loop %d:%d:%d\n", psdata->outerloops, psdata->middleloops, psdata->innerloops); fprintf(output, "Model size: %d rows (%d equalities, %d less than), %d columns\n", psdata->rows->varmap->count, psdata->EQmap->count, psdata->LTmap->count, psdata->cols->varmap->count); fprintf(output, "\nMAPPERS\n-------\n\n"); size = 1; blockWriteINT(output, "colmap", psdata->cols->varmap->map, 0, size*psdata->cols->varmap->size); blockWriteINT(output, "rowmap", psdata->rows->varmap->map, 0, size*psdata->rows->varmap->size); blockWriteINT(output, "EQmap", psdata->EQmap->map, 0, size*psdata->EQmap->size); blockWriteINT(output, "LTmap", psdata->LTmap->map, 0, size*psdata->LTmap->size); fprintf(output, "\nCOUNTS\n------\n\n"); blockWriteINT(output, "plucount", psdata->rows->plucount, 0, lp->rows); blockWriteINT(output, "negcount", psdata->rows->negcount, 0, lp->rows); blockWriteINT(output, "pluneg", psdata->rows->pluneg, 0, lp->rows); fprintf(output, "\nSUMS\n----\n\n"); blockWriteREAL(output, "pluupper", psdata->rows->pluupper, 0, lp->rows); blockWriteREAL(output, "negupper", psdata->rows->negupper, 0, lp->rows); blockWriteREAL(output, "plulower", psdata->rows->pluupper, 0, lp->rows); blockWriteREAL(output, "neglower", psdata->rows->negupper, 0, lp->rows); if(filename != NULL) fclose(output); return(ok); } int CMP_CALLMODEL compRedundant(const UNIONTYPE QSORTrec *current, const UNIONTYPE QSORTrec *candidate) { int start1 = (int) (current->int4.intpar1), start2 = (int) (candidate->int4.intpar1), result = CMP_COMPARE(start1, start2); if(result == 0) { start1 = (int) (current->int4.intpar2); start2 = (int) (candidate->int4.intpar2); result = -CMP_COMPARE(start1, start2); } return( result ); } int CMP_CALLMODEL compSparsity(const UNIONTYPE QSORTrec *current, const UNIONTYPE QSORTrec *candidate) { int start1 = (int) (current->int4.intpar1), start2 = (int) (candidate->int4.intpar1), result = CMP_COMPARE(start1, start2); if(result == 0) { start1 = (int) (current->int4.intpar2); start2 = (int) (candidate->int4.intpar2); result = -CMP_COMPARE(start1, start2); } if(result == 0) { start1 = (int) (current->int4.intval); start2 = (int) (candidate->int4.intval); result = CMP_COMPARE(start1, start2); } return( result ); } int CMP_CALLMODEL compAggregate(const UNIONTYPE QSORTrec *current, const UNIONTYPE QSORTrec *candidate) { int index1 = (int) (current->pvoidint2.intval), index2 = (int) (candidate->pvoidint2.intval); lprec *lp = (lprec *) current->pvoidint2.ptr; REAL value1 = lp->orig_obj[index1], value2 = lp->orig_obj[index2]; /* Smallest objective coefficient (largest contribution to OF) */ int result = CMP_COMPARE(value1, value2); /* Smallest lower variable bound */ if(result == 0) { index1 += lp->rows; index2 += lp->rows; value1 = lp->orig_lowbo[index1]; value2 = lp->orig_lowbo[index2]; result = CMP_COMPARE(value1, value2); } /* Largest upper variable bound */ if(result == 0) { value1 = lp->orig_upbo[index1]; value2 = lp->orig_upbo[index2]; result = -CMP_COMPARE(value1, value2); } return( result ); } STATIC int presolve_rowdominance(presolverec *psdata, int *nCoeffChanged, int *nRowsRemoved, int *nVarsFixed, int *nSum) { lprec *lp = psdata->lp; MATrec *mat = lp->matA; int i, ii, ib, ie, n, jb, je, jx, *coldel = NULL, status = RUNNING, item, iCoeffChanged = 0, iRowRemoved = 0, iVarFixed = 0; REAL ratio, *rowvalues = NULL; UNIONTYPE QSORTrec *QS = (UNIONTYPE QSORTrec *) calloc(lp->rows+1, sizeof(*QS)); /* Check if we were able to obtain working memory */ if(QS == NULL) return( status); /* A dominating row of variables always satisfy the following criteria: 1) The starting column position is never lower, but could be the same 2) The non-zero row count is always lower */ n = 0; for(i = firstActiveLink(psdata->EQmap); i != 0; i = nextActiveLink(psdata->EQmap, i)) { /* Make sure we have no SOS or semi-continuous variables */ jb = je = 0; if((SOS_count(lp) > 0) || (lp->sc_vars > 0)) { item = 0; for(jb = presolve_nextcol(psdata, i, &item); jb >= 0; jb = presolve_nextcol(psdata, i, &item)) { jx = ROW_MAT_COLNR(jb); if(SOS_is_member(lp->SOS, 0, jx) || is_semicont(lp, jx)) break; } } /* Add to list if we are Ok */ if(jb < 0) { QS[n].int4.intval = i; item = 0; ii = presolve_nextcol(psdata, i, &item); QS[n].int4.intpar1 = ROW_MAT_COLNR(ii); QS[n].int4.intpar2 = presolve_rowlength(psdata, i); n++; } } if(n <= 1) goto Finish; QS_execute(QS, n, (findCompare_func *) compRedundant, NULL); /* Let us start from the top of the list, going forward and looking for the longest possible dominating row */ if(!allocREAL(lp, &rowvalues, lp->columns + 1, TRUE) || !allocINT(lp, &coldel, lp->columns + 1, FALSE)) goto Finish; for(ib = 0; ib < n; ib++) { /* Get row and check if it was previously eliminated */ i = QS[ib].int4.intval; if(i < 0) continue; /* Load the non-zero row values */ item = 0; for(jb = presolve_nextcol(psdata, i, &item); jb >= 0; jb = presolve_nextcol(psdata, i, &item)) { jx = ROW_MAT_COLNR(jb); rowvalues[jx] = ROW_MAT_VALUE(jb); } for(ie = ib+1; ie < n; ie++) { /* Get row and check if it was previously eliminated */ ii = QS[ie].int4.intval; if(ii < 0) continue; #ifdef Paranoia if((QS[ib].int4.intpar1 > QS[ie].int4.intpar1) || ((QS[ib].int4.intpar1 == QS[ie].int4.intpar1) && (QS[ib].int4.intpar2 < QS[ie].int4.intpar2))) report(lp, SEVERE, "presolve_rowdominance: Invalid sorted row order\n"); #endif /* Loop over every row member to confirm that the candidate actually dominates in every position */ if((lp->orig_rhs[i] == 0) && (lp->orig_rhs[ii] == 0)) ratio = 0; else if((lp->orig_rhs[i] != 0) && (lp->orig_rhs[ii] != 0)) ratio = lp->orig_rhs[i] / lp->orig_rhs[ii]; else continue; item = 0; for(jb = presolve_nextcol(psdata, ii, &item); jb >= 0; jb = presolve_nextcol(psdata, ii, &item)) { jx = ROW_MAT_COLNR(jb); if(rowvalues[jx] == 0) break; if(ratio == 0) ratio = rowvalues[jx] / ROW_MAT_VALUE(jb); else if(fabs(rowvalues[jx] - ratio*ROW_MAT_VALUE(jb)) > psdata->epsvalue) break; } /* "We have contact" */ if(jb < 0) { int sign_1 = 0, sign_j = 0; /* Need to fix any superset columns, but require that they have equal signs */ coldel[0] = 0; item = 0; for(jb = presolve_nextcol(psdata, i, &item); jb >= 0; jb = presolve_nextcol(psdata, i, &item)) { jx = ROW_MAT_COLNR(jb); if(mat_findelm(mat, ii, jx) <= 0) { /* Cancel if we detect a free or "quasi-free" variable */ if((lp->orig_lowbo[lp->rows + jx] < 0) && (lp->orig_upbo[lp->rows + jx] > 0)) { coldel[0] = -1; break; } /* Ensure that we are feasible */ else if((lp->orig_lowbo[lp->rows + jx] > 0) || (lp->orig_upbo[lp->rows + jx] < 0)) { report(lp, DETAILED, "presolve_rowdominate: Column %s is infeasible due to conflict in rows %s and %s\n", get_col_name(lp, jx), get_row_name(lp, i), get_row_name(lp, ii)); coldel[0] = -1; break; } /* Check consistency / uniformity of signs */ sign_j = my_sign(ROW_MAT_VALUE(jb)); sign_j = my_chsign(is_negative(lp, jx), sign_j); if(coldel[0] == 0) { sign_1 = sign_j; coldel[++coldel[0]] = jx; } else if(sign_j == sign_1) { coldel[++coldel[0]] = jx; } else { coldel[0] = -1; break; } } } /* Force break / continuation if the superset columns were incompatible */ if(coldel[0] < 0) continue; /* Do the column fixing and deletion (check for infeasibility in the process) */ for(jb = 1; jb <= coldel[0]; jb++) { jx = coldel[jb]; if(!presolve_colfix(psdata, jx, 0, TRUE, &iVarFixed)) { status = presolve_setstatus(psdata, INFEASIBLE); goto Finish; } presolve_colremove(psdata, jx, TRUE); rowvalues[jx] = 0; } /* Then delete the row */ presolve_rowremove(psdata, ii, TRUE); iRowRemoved++; QS[ie].int4.intval = -ii; } } /* Clear the non-zero row values ahead of the next row candidate */ ie = mat->row_end[i-1]; ii = mat->row_end[i]; for(; ie < ii; ie++) rowvalues[ROW_MAT_COLNR(ie)] = 0; } Finish: FREE(QS); FREE(rowvalues); FREE(coldel); (*nCoeffChanged) += iCoeffChanged; (*nRowsRemoved) += iRowRemoved; (*nVarsFixed) += iVarFixed; (*nSum) += iCoeffChanged + iRowRemoved + iVarFixed; return( status ); } #if 0 STATIC int presolve_coldominance01(presolverec *psdata, int *nConRemoved, int *nVarsFixed, int *nSum) /* The current version of this routine eliminates binary variables that are dominated via set coverage or unit knapsack constraints */ { lprec *lp = psdata->lp; MATrec *mat = lp->matA; MYBOOL first; int i, ii, ib, ie, n, jb, je, jx, jj, item, item2, *coldel = NULL, status = RUNNING, iVarFixed = 0; REAL scale, rhsval, *colvalues = NULL; UNIONTYPE QSORTrec *QS = (UNIONTYPE QSORTrec *) calloc(lp->columns+1, sizeof(*QS)); /* Check if we were able to obtain working memory */ if(QS == NULL) return( status); if(lp->int_vars == 0) goto Finish; /* A column dominates another binary variable column with the following criteria: 1) The relative matrix non-zero entries are identical 2) The relative objective coefficient is worse than the other; if the OF coefficients are identical, we can delete an arbitrary variable */ n = 0; for(i = firstActiveLink(psdata->cols->varmap); i != 0; i = nextActiveLink(psdata->cols->varmap, i)) if(is_binary(lp, i) && !SOS_is_member(lp->SOS, 0, i)) { /* Make sure we have an all-binary, unit-coefficient row */ je = mat->col_end[i]; item = 0; for(jb = presolve_nextrow(psdata, i, &item); jb >= 0; jb = presolve_nextrow(psdata, i, &item)) { jx = COL_MAT_ROWNR(jb); if(COL_MAT_VALUE(jb) != 1) break; } /* Add to list if we are Ok */ if(jb < 0) { QS[n].int4.intval = i; item = 0; ii = presolve_nextrow(psdata, i, &item); QS[n].int4.intpar1 = COL_MAT_ROWNR(ii); ii = presolve_collength(psdata, i); QS[n].int4.intpar2 = ii; n++; } } if(n <= 1) { FREE(QS); return( status ); } QS_execute(QS, n, (findCompare_func *) compRedundant, NULL); /* Let us start from the top of the list, going forward and looking for the longest possible dominated column */ if(!allocREAL(lp, &colvalues, lp->rows + 1, TRUE) || !allocINT(lp, &coldel, lp->columns + 1, FALSE)) goto Finish; for(ib = 0; ib < n; ib++) { /* Get column and check if it was previously eliminated */ i = QS[ib].int4.intval; if(i < 0) continue; /* Load the non-zero column values */ item = 0; for(jb = presolve_nextrow(psdata, i, &item); jb >= 0; jb = presolve_nextrow(psdata, i, &item)) { jx = COL_MAT_ROWNR(jb); colvalues[jx] = COL_MAT_VALUE(jb); } coldel[0] = 0; for(ie = ib+1; ie < n; ie++) { /* Insist on identical column lengths (sort is decending in column lengths) */ ii = QS[ib].int4.intpar2 - QS[ie].int4.intpar2; if(ii != 0) break; /* Also insist on identical starting positions */ ii = QS[ib].int4.intpar1 - QS[ie].int4.intpar1; if(ii != 0) break; /* Get column and check if it was previously eliminated */ ii = QS[ie].int4.intval; if(ii < 0) continue; /* Also make sure that the variables have "compatible" bounds */ #if 1 if((fabs(my_reldiff(lp->orig_lowbo[lp->rows + i], lp->orig_lowbo[lp->rows + ii])) > psdata->epsvalue) || (fabs(my_reldiff(lp->orig_upbo[lp->rows + i], lp->orig_upbo[lp->rows + ii] )) > psdata->epsvalue)) continue; #endif #ifdef Paranoia if((QS[ib].int4.intpar1 > QS[ie].int4.intpar1) || ((QS[ib].int4.intpar1 == QS[ie].int4.intpar1) && (QS[ib].int4.intpar2 < QS[ie].int4.intpar2))) report(lp, SEVERE, "presolve_coldominance01: Invalid sorted column order\n"); #endif /* Loop over every column member to confirm that the candidate is relatively identical in every position */ first = TRUE; item = 0; item2 = 0; scale = 1; for(jb = presolve_nextrow(psdata, ii, &item), jj = presolve_nextrow(psdata, i, &item2); jb >= 0; jb = presolve_nextrow(psdata, ii, &item), jj = presolve_nextrow(psdata, i, &item2)) { jx = COL_MAT_ROWNR(jb); if(jx != COL_MAT_ROWNR(jj)) break; if(first) { first = !first; scale = colvalues[jx] / COL_MAT_VALUE(jb); } else { if(fabs(colvalues[jx] - scale * COL_MAT_VALUE(jb)) > psdata->epsvalue) break; } /* Also make sure we have a compatible RHS (since this version of the dominance logic only applies to "sets") */ rhsval = scale*lp->orig_rhs[jx] - 1.0; /* if((rhsval < 0) || (rhsval > 1 + psdata->epsvalue)) */ if(fabs(rhsval) > psdata->epsvalue) break; } /* "We have contact" */ if(jb < 0) { coldel[++coldel[0]] = ii; QS[ie].int4.intval = -ii; } } /* Find the dominant column and delete / fix the others; if there is a tie, simply delete the second candidate */ ii = i; for(jb = 1; jb <= coldel[0]; jb++) { jx = coldel[jb]; if(lp->orig_obj[jx] < lp->orig_obj[ii]) swapINT(&ii, &coldel[jb]); } for(jb = 1; jb <= coldel[0]; jb++) { jx = coldel[jb]; if(!presolve_colfix(psdata, jx, lp->orig_lowbo[lp->rows+jx], TRUE, &iVarFixed)) { status = presolve_setstatus(psdata, INFEASIBLE); goto Finish; } presolve_colremove(psdata, jx, TRUE); } /* Clear the non-zero row values ahead of the next row candidate */ if(ib + 1 < n) { ie = mat->col_end[i-1]; ii = mat->col_end[i]; for(; ie < ii; ie++) colvalues[COL_MAT_ROWNR(ie)] = 0; } } Finish: FREE(QS); FREE(colvalues); FREE(coldel); (*nVarsFixed) += iVarFixed; (*nSum) += iVarFixed; return( status ); } #else /* DEVELOPMENT/TEST CODE FOR POSSIBLE REPLACEMENT OF SIMILAR FUNCTION IN lp_presolve.c */ #define NATURAL int STATIC int presolve_coldominance01(presolverec *psdata, NATURAL *nConRemoved, NATURAL *nVarsFixed, NATURAL *nSum) /* The current version of this routine eliminates binary variables that are dominated via set coverage or unit knapsack constraints */ { lprec *lp = psdata->lp; MATrec *mat = lp->matA; NATURAL i, ib, ie, jx, item, item2, n = lp->int_vars, iVarFixed = 0, nrows = lp->rows, *coldel = NULL; int jb, jj, ii, status = RUNNING; REAL rhsval = 0.0, *colvalues = NULL, *colobj = NULL; LLrec *sets = NULL; UNIONTYPE QSORTrec *QS = (UNIONTYPE QSORTrec *) calloc(n+1, sizeof(*QS)); /* Check if we were able to obtain working memory */ if(QS == NULL) return( status); if(n == 0) goto Finish; /* Create list of set coverage and knapsack constraints */ createLink(nrows, &sets, NULL); for(i = firstActiveLink(psdata->rows->varmap); i != 0; i = nextActiveLink(psdata->rows->varmap, i)) { if((lp->orig_rhs[i] < 0) || (psdata->rows->negcount[i] > 0)) continue; item = 0; for(jb = presolve_nextcol(psdata, i, &item); jb >= 0; jb = presolve_nextcol(psdata, i, &item)) { jx = ROW_MAT_COLNR(jb); if(!is_binary(lp, jx)) break; rhsval = ROW_MAT_VALUE(jb) - 1; if(fabs(rhsval) > lp->epsvalue) break; } if(jb < 0) setLink(sets, i); } if(countActiveLink(sets) == 0) goto Finish; /* A column dominates another binary variable column with the following criteria: 1) The relative matrix non-zero entries are identical 2) The relative objective coefficient is worse than the other; if the OF coefficients are identical, we can delete an arbitrary variable */ n = 0; for(i = firstActiveLink(psdata->cols->varmap); i != 0; i = nextActiveLink(psdata->cols->varmap, i)) if(is_binary(lp, i) && !SOS_is_member(lp->SOS, 0, i)) { /* Make sure the column is member of at least one set */ item = 0; for(jb = presolve_nextrow(psdata, i, &item); jb >= 0; jb = presolve_nextrow(psdata, i, &item)) { jx = COL_MAT_ROWNR(jb); if(isActiveLink(sets, jx)) break; } /* Add to list if set membership test is Ok */ if(jb >= 0) { QS[n].int4.intval = i; item = 0; ii = presolve_nextrow(psdata, i, &item); QS[n].int4.intpar1 = COL_MAT_ROWNR(ii); ii = presolve_collength(psdata, i); QS[n].int4.intpar2 = ii; n++; } } if(n <= 1) { FREE(QS); return( status ); } QS_execute(QS, n, (findCompare_func *) compRedundant, NULL); /* Let us start from the top of the list, going forward and looking for the longest possible dominated column */ if(!allocREAL(lp, &colvalues, nrows + 1, TRUE) || !allocREAL(lp, &colobj, n + 1, FALSE) || !allocINT(lp, &coldel, n + 1, FALSE)) goto Finish; for(ib = 0; ib < n; ib++) { /* Get column and check if it was previously eliminated */ i = QS[ib].int4.intval; if(!isActiveLink(psdata->cols->varmap, i)) continue; /* Load the non-zero column values */ item = 0; for(jb = presolve_nextrow(psdata, i, &item); jb >= 0; jb = presolve_nextrow(psdata, i, &item)) { jx = COL_MAT_ROWNR(jb); colvalues[jx] = COL_MAT_VALUE(jb); } /* Store data for current column */ coldel[0] = 1; coldel[1] = i; colobj[1] = lp->orig_obj[i]; /* Loop over all other columns to see if they have equal constraint coefficients */ for(ie = ib+1; ie < n; ie++) { /* Check if this column was previously eliminated */ ii = QS[ie].int4.intval; if(!isActiveLink(psdata->cols->varmap, ii)) continue; /* Insist on identical column lengths (sort is decending in column lengths) */ ii = QS[ib].int4.intpar2 - QS[ie].int4.intpar2; if(ii != 0) break; /* Also insist on identical starting positions */ ii = QS[ib].int4.intpar1 - QS[ie].int4.intpar1; if(ii != 0) break; /* Get column and check if it was previously eliminated */ ii = QS[ie].int4.intval; #ifdef Paranoia if((QS[ib].int4.intpar1 > QS[ie].int4.intpar1) || ((QS[ib].int4.intpar1 == QS[ie].int4.intpar1) && (QS[ib].int4.intpar2 < QS[ie].int4.intpar2))) report(lp, SEVERE, "presolve_coldominance01: Invalid sorted column order\n"); #endif /* Loop over every column member to confirm that the candidate is identical in every row; we also compute the minimal set order */ rhsval = lp->infinite; item = 0; item2 = 0; for(jb = presolve_nextrow(psdata, ii, &item), jj = presolve_nextrow(psdata, i, &item2); jb >= 0; jb = presolve_nextrow(psdata, ii, &item), jj = presolve_nextrow(psdata, i, &item2)) { jx = COL_MAT_ROWNR(jb); if(jx != COL_MAT_ROWNR(jj)) break; if(isActiveLink(sets, jx)) SETMIN(rhsval, lp->orig_rhs[jx]); } /* "We have contact" */ if(jb < 0) { coldel[++coldel[0]] = ii; colobj[coldel[0]] = lp->orig_obj[ii]; } } /* Find the dominant columns, fix and delete the others */ if(coldel[0] > 1) { qsortex(colobj+1, coldel[0], 0, sizeof(*colobj), FALSE, compareREAL, coldel+1, sizeof(*coldel)); /* if(rhsval+lp->epsvalue < lp->infinite) { */ jb = (NATURAL) (rhsval+lp->epsvalue); /* printf("%f / %d\n", rhsval, jb); */ for(jb++; jb <= coldel[0]; jb++) { jx = coldel[jb]; if(!presolve_colfix(psdata, jx, lp->orig_lowbo[nrows+jx], TRUE, &iVarFixed)) { status = presolve_setstatus(psdata, INFEASIBLE); goto Finish; } presolve_colremove(psdata, jx, TRUE); } /*} */ } /* Clear the non-zero row values ahead of the next row candidate */ if(ib + 1 < n) { ie = mat->col_end[i-1]; ii = mat->col_end[i]; for(; ie < ii; ie++) colvalues[COL_MAT_ROWNR(ie)] = 0; } } Finish: freeLink(&sets); FREE(QS); FREE(colvalues); FREE(coldel); FREE(colobj); (*nVarsFixed) += iVarFixed; (*nSum) += iVarFixed; return( status ); } #endif STATIC int presolve_aggregate(presolverec *psdata, int *nConRemoved, int *nVarsFixed, int *nSum) /* This routine combines compatible or identical columns */ { lprec *lp = psdata->lp; MATrec *mat = lp->matA; MYBOOL first; int i, ii, ib, ie, ix, n, jb, je, jx, jj, item, item2, *coldel = NULL, status = RUNNING, iVarFixed = 0; REAL scale, *colvalues = NULL; UNIONTYPE QSORTrec *QScand = (UNIONTYPE QSORTrec *) calloc(lp->columns+1, sizeof(*QScand)); /* Check if we were able to obtain working memory */ if(QScand == NULL) return( status); /* Obtain the list of qualifying columns to be sorted */ n = 0; for(i = firstActiveLink(psdata->cols->varmap); i != 0; i = nextActiveLink(psdata->cols->varmap, i)) if(!is_semicont(lp, i) && !SOS_is_member(lp->SOS, 0, i)) { QScand[n].int4.intval = i; item = 0; ii = presolve_nextrow(psdata, i, &item); QScand[n].int4.intpar1 = COL_MAT_ROWNR(ii); ii = presolve_collength(psdata, i); QScand[n].int4.intpar2 = ii; n++; } if(n <= 1) { FREE(QScand); return( status ); } QS_execute(QScand, n, (findCompare_func *) compRedundant, NULL); /* Let us start from the top of the list, going forward and looking for the longest possible identical column */ if(!allocREAL(lp, &colvalues, lp->rows + 1, TRUE) || !allocINT(lp, &coldel, lp->columns + 1, FALSE)) goto Finish; for(ib = 0; ib < n; ib++) { /* Get column and check if it was previously eliminated */ i = QScand[ib].int4.intval; if(i < 0) continue; /* Load the non-zero column values of this active/reference column */ item = 0; for(jb = presolve_nextrow(psdata, i, &item); jb >= 0; jb = presolve_nextrow(psdata, i, &item)) { jx = COL_MAT_ROWNR(jb); colvalues[jx] = COL_MAT_VALUE(jb); } coldel[0] = 0; for(ie = ib+1; ie < n; ie++) { /* Insist on identical column lengths (sort is decending in column lengths) */ ii = QScand[ib].int4.intpar2 - QScand[ie].int4.intpar2; if(ii != 0) break; /* Also insist on identical starting positions */ ii = QScand[ib].int4.intpar1 - QScand[ie].int4.intpar1; if(ii != 0) break; /* Get column and check if it was previously eliminated */ ii = QScand[ie].int4.intval; if(ii < 0) continue; /* Loop over every column member to confirm that the candidate is relatively identical in every position */ first = TRUE; item = 0; item2 = 0; scale = 1; for(jb = presolve_nextrow(psdata, ii, &item), jj = presolve_nextrow(psdata, i, &item2); jb >= 0; jb = presolve_nextrow(psdata, ii, &item), jj = presolve_nextrow(psdata, i, &item2)) { jx = COL_MAT_ROWNR(jb); if(jx != COL_MAT_ROWNR(jj)) break; if(first) { first = !first; scale = colvalues[jx] / COL_MAT_VALUE(jb); } else { if(fabs(colvalues[jx] - scale * COL_MAT_VALUE(jb)) > psdata->epsvalue) break; } } /* "We have contact", store the column in the aggregation list */ if(jb < 0) { coldel[++coldel[0]] = ii; QScand[ie].int4.intval = -ii; } } /* Sort the aggregation list if we have aggregation candidates */ if(coldel[0] > 1) { REAL of, ofelim, fixvalue; MYBOOL isint; UNIONTYPE QSORTrec *QSagg = (UNIONTYPE QSORTrec *) calloc(coldel[0], sizeof(*QSagg)); for(jb = 1; jb <= coldel[0]; jb++) { ii = jb - 1; QSagg[ii].pvoidint2.intval = coldel[jb]; QSagg[ii].pvoidint2.ptr = (void *) lp; } QS_execute(QSagg, coldel[0], (findCompare_func *) compAggregate, NULL); /* Process columns with identical OF coefficients */ jb = 0; while((status == RUNNING) && (jb < coldel[0])) { ii = QSagg[jb].pvoidint2.intval; of = lp->orig_obj[ii]; isint = is_int(lp, ii); je = jb + 1; while((status == RUNNING) && (je < coldel[0]) && (fabs(lp->orig_obj[ix = QSagg[je].pvoidint2.intval] - of) < psdata->epsvalue)) { /* We now have two columns with equal OFs; the following cases are possible: 1) The first column has Inf upper bound, which means that it can "absorb" compatible columns, which are then fixed at the appropriate bounds (or zero in case of free variables). 2) The first column has a -Inf lower bound, and further columns are Inf upper bounds, which means steps towards forming a free variable can be made. 3) The first column is a non-Inf upper bound, in which case the bounds are summed into a helper variable and the variable simply deleted. The deleted variables' value are allocated/distributed via a simple linear programming routine at postsolve. In the current version of this code, we only handle case 1. */ if(is_int(lp, ix) == isint) { ofelim = lp->orig_obj[ix]; if(of == 0) scale = 1; else scale = ofelim / of; if(my_infinite(lp, lp->orig_upbo[lp->rows+ii])) { /* Case 1 (recipe.mps) */ if(is_unbounded(lp, ix)) fixvalue = 0; else if(ofelim < 0) fixvalue = lp->orig_upbo[lp->rows+ix]; else fixvalue = lp->orig_lowbo[lp->rows+ix]; if(my_infinite(lp, fixvalue)) status = presolve_setstatus(psdata, UNBOUNDED); else if(!presolve_colfix(psdata, ix, fixvalue, TRUE, &iVarFixed)) status = presolve_setstatus(psdata, INFEASIBLE); else presolve_colremove(psdata, ix, TRUE); } else if(my_infinite(lp, lp->orig_lowbo[lp->rows+ii])) { /* Case 2 */ /* Do nothing */ } else { /* Case 3 */ #if 0 /* Do nothing */ #else if(ofelim >= 0) { fixvalue = lp->orig_lowbo[lp->rows+ix]; lp->orig_upbo[lp->rows+ii] += scale * (lp->orig_upbo[lp->rows+ix] - fixvalue); } else { fixvalue = lp->orig_upbo[lp->rows+ix]; lp->orig_upbo[lp->rows+ii] -= scale * (fixvalue - lp->orig_lowbo[lp->rows+ix]); } if(my_infinite(lp, fixvalue)) status = presolve_setstatus(psdata, UNBOUNDED); else if(!presolve_colfix(psdata, ix, fixvalue, TRUE, &iVarFixed)) status = presolve_setstatus(psdata, INFEASIBLE); else presolve_colremove(psdata, ix, TRUE); #ifdef xxParanoia if(presolve_rowlengthdebug(psdata) > 0) report(lp, SEVERE, "presolve_aggregate: Invalid row count\n"); #endif psdata->forceupdate = TRUE; #endif } } je++; } jb = je; } FREE(QSagg); } /* Clear the non-zero row values ahead of the next row candidate */ if(ib + 1 < n) { ie = mat->col_end[i-1]; ii = mat->col_end[i]; for(; ie < ii; ie++) colvalues[COL_MAT_ROWNR(ie)] = 0; } } Finish: FREE(QScand); FREE(colvalues); FREE(coldel); (*nVarsFixed) += iVarFixed; (*nSum) += iVarFixed; return( status ); } STATIC int presolve_makesparser(presolverec *psdata, int *nCoeffChanged, int *nConRemove, int *nVarFixed, int *nSum) { lprec *lp = psdata->lp; MATrec *mat = lp->matA; MYBOOL chsign; int i, ii, ib, ix, k, n, jb, je, jl, jjb, jje, jjl, jx, jjx, item, itemEQ, *nzidx = NULL, status = RUNNING, iObjChanged = 0, iCoeffChanged = 0, iConRemove = 0; REAL test, ratio, value, valueEQ, *valptr; LLrec *EQlist = NULL; UNIONTYPE QSORTrec *QS = (UNIONTYPE QSORTrec *) calloc(lp->rows, sizeof(*QS)); /* Check if we were able to obtain working memory */ if((QS == NULL) || (psdata->rows->varmap->count == 0) || (psdata->EQmap->count == 0)) return( status); /* Sort rows in 1) increasing order of start index, 2) decreasing length, and 3) non-equalities (i.e. equalities last) */ n = 0; for(i = firstActiveLink(psdata->rows->varmap); i != 0; i = nextActiveLink(psdata->rows->varmap, i)) { k = presolve_rowlength(psdata, i); if(k >= 2) { item = 0; ii = presolve_nextcol(psdata, i, &item); #ifdef Paranoia if((ii < 0) || (item == 0)) { report(lp, SEVERE, "presolve_makesparser: Unexpected zero-length row %d\n", i); continue; } #endif QS[n].int4.intval = my_chsign(is_constr_type(lp, i, EQ), i); QS[n].int4.intpar1 = ROW_MAT_COLNR(ii); QS[n].int4.intpar2 = k; n++; } } if(n <= 1) { FREE(QS); return( status ); } QS_execute(QS, n, (findCompare_func *) compSparsity, NULL); /* Create associated sorted map of indeces to equality constraints; note that we need to have a unit offset for compatibility. */ allocINT(lp, &nzidx, lp->columns + 1, FALSE); createLink(lp->rows, &EQlist, NULL); for(ib = 0; ib < n; ib++) { i = QS[ib].int4.intval; if(i < 0) appendLink(EQlist, ib + 1); } /* Loop over all equality masks */ for(ix = firstActiveLink(EQlist); ix != 0; ) { /* Get row starting and ending positions of the mask */ ii = abs(QS[ix-1].int4.intval); jjb = QS[ix-1].int4.intpar1; jje = presolve_lastcol(psdata, ii); jje = ROW_MAT_COLNR(jje); jjl = QS[ix-1].int4.intpar2; /* Scan the OF */ i = 0; chsign = is_chsign(lp, i); test = ratio = 0.0; itemEQ = 0; nzidx[0] = 0; while(((jjx = presolve_nextcol(psdata, ii, &itemEQ)) >= 0) && /*(itemEQ > 0) && */ (fabs(test-ratio) < psdata->epsvalue)) { valueEQ = ROW_MAT_VALUE(jjx); if(valueEQ == 0) continue; k = ROW_MAT_COLNR(jjx); value = lp->orig_obj[k]; if(fabs(value) < psdata->epsvalue) break; if(ratio == 0.0) { test = ratio = value / valueEQ; } else test = value / valueEQ; /* Store nz index */ nzidx[++nzidx[0]] = k; } /* We were successful if the equality was completely traversed; we will then zero-out the OF coefficients and update the constant term. */ if((itemEQ == 0) && (nzidx[0] > 0) && (fabs(test-ratio) < psdata->epsvalue)) { for(k = 1; k <= nzidx[0]; k++) { /* We should add recovery data for the zero'ed coefficient here */ jx = nzidx[k]; value = lp->orig_obj[jx]; lp->orig_obj[jx] = 0.0; /* Update counts */ value = my_chsign(chsign, value); if(value < 0) { psdata->rows->negcount[i]--; psdata->cols->negcount[jx]--; } else { psdata->rows->plucount[i]--; psdata->cols->plucount[jx]--; } iObjChanged++; } value = ratio * lp->orig_rhs[ii]; presolve_adjustrhs(psdata, i, value, psdata->epsvalue); } /* Scan for compatible constraints that can be masked for sparsity elimination */ for(ib = 1; ib < ix; ib++) { /* Get row starting and ending positions of the target constraint */ i = abs(QS[ib-1].int4.intval); jb = QS[ib-1].int4.intpar1; je = presolve_lastcol(psdata, i); je = ROW_MAT_COLNR(je); jl = QS[ib-1].int4.intpar2; /* Check if there is a window mismatch */ if((jjb < jb) || (jje > je) || (jjl > jl)) goto NextEQ; /* We have a window match; now check if there is a (scalar) member-by-member match as well. We approach this in the following manner: 1) Get first (or next) member of active equality 2) Loop to matching member in the target constraint, but abandon if no match 3) Set ratio if this is the first match, otherwise compare ratio and abandon on mismatch 4) Go to 1) of there are more elements in the active equality 5) Proceed to do sparsity elimination if we were successful. */ chsign = is_chsign(lp, i); test = ratio = 0.0; itemEQ = 0; item = 0; nzidx[0] = 0; while(((jjx = presolve_nextcol(psdata, ii, &itemEQ)) >= 0) && /*(itemEQ > 0) &&*/ (fabs(test-ratio) < psdata->epsvalue)) { valueEQ = ROW_MAT_VALUE(jjx); if(valueEQ == 0) continue; jx = 0; jjx = ROW_MAT_COLNR(jjx); for(k = presolve_nextcol(psdata, i, &item); (jx < jjx) && (item > 0); k = presolve_nextcol(psdata, i, &item)) { jx = ROW_MAT_COLNR(k); /* Do we have a column index match? */ if(jx == jjx) { value = ROW_MAT_VALUE(k); /* Abandon if we have a zero value */ if(value == 0) goto NextEQ; if(ratio == 0.0) { test = ratio = value / valueEQ; } else test = value / valueEQ; /* Store nz index */ nzidx[++nzidx[0]] = k; break; } /* Give up matching if there is overshooting */ else if(jx > jjx) goto NextEQ; } } /* We were successful if the equality was completely traversed */ if((itemEQ == 0) && (nzidx[0] > 0) && (fabs(test-ratio) < psdata->epsvalue)) { /* Check if we have found parametrically indentical constraints */ if(presolve_rowlength(psdata, i) == presolve_rowlength(psdata,ii)) { value = lp->orig_rhs[i]; valueEQ = lp->orig_rhs[ii]; /* Are they both equalities? */ if(is_constr_type(lp, i, EQ)) { /* Determine applicable ratio for the RHS */ if(fabs(valueEQ) < psdata->epsvalue) { if(fabs(value) < psdata->epsvalue) test = ratio; else test = lp->infinite; } else test = value / valueEQ; /* Check for infeasibility */ if(fabs(test-ratio) > psdata->epsvalue) { report(lp, NORMAL, "presolve_sparser: Infeasibility of relatively equal constraints %d and %d\n", i, ii); status = presolve_setstatus(psdata, INFEASIBLE); goto Finish; } /* Otherwise we can delete a redundant constraint */ else { removeLink(EQlist, i); presolve_rowremove(psdata, i, TRUE); MEMCOPY(&QS[ib-1], &QS[ib], n-ib); n--; iConRemove++; } } /* ... if not, then delete the inequality, since the equality dominates */ else { /* First verify feasibility of the RHS */ if((value+psdata->epsvalue < valueEQ) || (value-get_rh_range(lp, i)-psdata->epsvalue > valueEQ)) { report(lp, NORMAL, "presolve_sparser: Infeasibility of relatively equal RHS values for %d and %d\n", i, ii); status = presolve_setstatus(psdata, INFEASIBLE); goto Finish; } presolve_rowremove(psdata, i, TRUE); MEMCOPY(&QS[ib-1], &QS[ib], n-ib); n--; iConRemove++; } } /* Otherwise zero-out the target constraint coefficients and update the RHS */ else { for(k = 1; k <= nzidx[0]; k++) { /* We should add recovery data for the zero'ed coefficient here */ jjx = nzidx[k]; jx = ROW_MAT_COLNR(jjx); valptr = &ROW_MAT_VALUE(jjx); value = *valptr; *valptr = 0.0; /* Update counts */ value = my_chsign(chsign, value); if(value < 0) { psdata->rows->negcount[i]--; psdata->cols->negcount[jx]--; } else { psdata->rows->plucount[i]--; psdata->cols->plucount[jx]--; } iCoeffChanged++; } value = ratio * lp->orig_rhs[ii]; presolve_adjustrhs(psdata, i, value, psdata->epsvalue); } } } /* Get next equality index */ NextEQ: ix = nextActiveLink(EQlist, ix); } Finish: FREE(QS); freeLink(&EQlist); FREE(nzidx); /* Let us condense the matrix if we modified the constraint matrix */ if(iCoeffChanged > 0) { mat->row_end_valid = FALSE; mat_zerocompact(mat); presolve_validate(psdata, TRUE); #ifdef PresolveForceUpdateMax mat_computemax(mat /* , FALSE */); #endif psdata->forceupdate = TRUE; } (*nConRemove) += iConRemove; (*nCoeffChanged) += iCoeffChanged + iObjChanged; (*nSum) += iCoeffChanged + iObjChanged + iConRemove; return( status ); } STATIC int presolve_SOS1(presolverec *psdata, int *nCoeffChanged, int *nConRemove, int *nVarFixed, int *nSOS, int *nSum) { lprec *lp = psdata->lp; MYBOOL candelete, SOS_GUBactive = FALSE; int iCoeffChanged = 0, iConRemove = 0, iSOS = 0, i,ix,iix, j,jx,jjx, status = RUNNING; REAL Value1; MATrec *mat = lp->matA; for(i = lastActiveLink(psdata->rows->varmap); i > 0; ) { candelete = FALSE; Value1 = get_rh(lp, i); jx = get_constr_type(lp, i); if((Value1 == 1) && (presolve_rowlength(psdata, i) >= MIN_SOS1LENGTH) && ((SOS_GUBactive && (jx != GE)) || (!SOS_GUBactive && (jx == LE)))) { jjx = mat->row_end[i-1]; iix = mat->row_end[i]; for(; jjx < iix; jjx++) { j = ROW_MAT_COLNR(jjx); if(!isActiveLink(psdata->cols->varmap, j)) continue; if(!is_binary(lp, j) || (ROW_MAT_VALUE(jjx) != 1)) break; } if(jjx >= iix) { char SOSname[16]; /* Define a new SOS instance */ ix = SOS_count(lp) + 1; sprintf(SOSname, "SOS_%d", ix); ix = add_SOS(lp, SOSname, 1, ix, 0, NULL, NULL); if(jx == EQ) SOS_set_GUB(lp->SOS, ix, TRUE); Value1 = 0; jjx = mat->row_end[i-1]; for(; jjx < iix; jjx++) { j = ROW_MAT_COLNR(jjx); if(!isActiveLink(psdata->cols->varmap, j)) continue; Value1 += 1; append_SOSrec(lp->SOS->sos_list[ix-1], 1, &j, &Value1); } candelete = TRUE; iSOS++; } } /* Get next row and do the deletion of the previous, if indicated */ ix = i; i = prevActiveLink(psdata->rows->varmap, i); if(candelete) { presolve_rowremove(psdata, ix, TRUE); iConRemove++; } } if(iSOS) report(lp, DETAILED, "presolve_SOS1: Converted %5d constraints to SOS1.\n", iSOS); clean_SOSgroup(lp->SOS, (MYBOOL) (iSOS > 0)); (*nCoeffChanged) += iCoeffChanged; (*nConRemove) += iConRemove; (*nSOS) += iSOS; (*nSum) += iCoeffChanged+iConRemove+iSOS; return( status ); } STATIC int presolve_boundconflict(presolverec *psdata, int baserowno, int colno) { REAL Value1, Value2; lprec *lp = psdata->lp; MATrec *mat = lp->matA; int ix, item = 0, status = RUNNING; if(baserowno <= 0) do { ix = presolve_nextrow(psdata, colno, &item); if(ix < 0) return( status ); baserowno = COL_MAT_ROWNR(ix); } while(presolve_rowlength(psdata, baserowno) != 1); Value1 = get_rh_upper(lp, baserowno), Value2 = get_rh_lower(lp, baserowno); if(presolve_singletonbounds(psdata, baserowno, colno, &Value2, &Value1, NULL)) { int iix; item = 0; for(ix = presolve_nextrow(psdata, colno, &item); ix >= 0; ix = presolve_nextrow(psdata, colno, &item)) { iix = COL_MAT_ROWNR(ix); if((iix != baserowno) && (presolve_rowlength(psdata, iix) == 1) && !presolve_altsingletonvalid(psdata, iix, colno, Value2, Value1)) { status = presolve_setstatus(psdata, INFEASIBLE); break; } } } else status = presolve_setstatus(psdata, INFEASIBLE); return( status ); } STATIC int presolve_columns(presolverec *psdata, int *nCoeffChanged, int *nConRemove, int *nVarFixed, int *nBoundTighten, int *nSum) { lprec *lp = psdata->lp; MYBOOL candelete, isOFNZ, unbounded, probefix = is_presolve(lp, PRESOLVE_PROBEFIX), #if 0 probereduce = is_presolve(lp, PRESOLVE_PROBEREDUCE), #endif colfixdual = is_presolve(lp, PRESOLVE_COLFIXDUAL); int iCoeffChanged = 0, iConRemove = 0, iVarFixed = 0, iBoundTighten = 0, status = RUNNING, ix, j, countNZ, item; REAL Value1; for(j = firstActiveLink(psdata->cols->varmap); (j != 0) && (status == RUNNING); ) { /* Don't presolve members SOS'es */ if(SOS_is_member(lp->SOS, 0, j)) { j = nextActiveLink(psdata->cols->varmap, j); continue; } /* Initialize */ countNZ = presolve_collength(psdata, j); isOFNZ = isnz_origobj(lp, j); Value1 = get_lowbo(lp, j); unbounded = is_unbounded(lp, j); /* Clear unnecessary semicont-definitions */ if((lp->sc_vars > 0) && (Value1 == 0) && is_semicont(lp, j)) set_semicont(lp, j, FALSE); candelete = FALSE; item = 0; ix = lp->rows + j; /* Check if the variable is unused */ if((countNZ == 0) && !isOFNZ) { if(Value1 != 0) report(lp, DETAILED, "presolve_columns: Eliminated unused variable %s\n", get_col_name(lp,j)); candelete = TRUE; } /* Check if the variable has a cost, but is not limited by constraints */ else if((countNZ == 0) && isOFNZ) { if(lp->orig_obj[j] < 0) Value1 = get_upbo(lp, j); if(fabs(Value1) >= lp->infinite) { report(lp, DETAILED, "presolve_columns: Unbounded variable %s\n", get_col_name(lp,j)); status = presolve_setstatus(psdata, UNBOUNDED); } else { /* Fix the value at its best bound */ report(lp, DETAILED, "presolve_columns: Eliminated trivial variable %s fixed at %g\n", get_col_name(lp,j), Value1); candelete = TRUE; } } /* Check if the variable can be eliminated because it is fixed */ else if(isOrigFixed(lp, ix)) { if(countNZ > 0) { status = presolve_boundconflict(psdata, -1, j); if(status != RUNNING) break; } report(lp, DETAILED, "presolve_columns: Eliminated variable %s fixed at %g\n", get_col_name(lp,j), Value1); candelete = TRUE; } #if 0 /* Merge OF-constraint column doubleton in equality constraint (if it has not been captured by the singleton free variable rule above) */ else if((countNZ == 1) && isOFNZ && ((i = presolve_nextrow(psdata, j, &item)) >= 0) && is_constr_type(lp, i = COL_MAT_ROWNR(i), EQ)) { MATrec *mat = lp->matA; /* Merge the constraint into the OF */ Value1 = lp->orig_obj[j] / get_mat(lp, i, j); for(jx = mat->row_end[i-1]; jx < mat->row_end[i]; jx++) { jjx = ROW_MAT_COLNR(jx); lp->orig_obj[jjx] -= Value1 * ROW_MAT_VALUE(jx); } Value2 = lp->orig_rhs[i]; presolve_adjustrhs(psdata, 0, Value1 * Value2, 0.0); /* Verify feasibility */ Value2 /= get_mat(lp, i, j); if((Value2 < get_lowbo(lp, j)) || (Value2 > get_upbo(lp, j))) { status = presolve_setstatus(psdata, INFEASIBLE); break; } /* Do column (and flag row) deletion */ presolve_rowremove(psdata, i, TRUE); psdata->forceupdate = TRUE; iConRemove++; candelete = TRUE; } #endif /* Look for opportunity to fix column based on the dual */ else if(colfixdual && presolve_colfixdual(psdata, j, &Value1, &status)) { if(my_infinite(lp, Value1)) { report(lp, DETAILED, "presolve_columns: Unbounded variable %s\n", get_col_name(lp,j)); status = presolve_setstatus(psdata, UNBOUNDED); } else { /* Fix the value at its best bound */ report(lp, DETAILED, "presolve_columns: Eliminated dual-zero variable %s fixed at %g\n", get_col_name(lp,j), Value1); candelete = TRUE; } } /* Do probing of binary variables to see if we can fix them */ else if(probefix && is_binary(lp, j) && presolve_probefix01(psdata, j, &Value1)) { report(lp, DETAILED, "presolve_columns: Fixed binary variable %s at %g\n", get_col_name(lp,j), Value1); candelete = TRUE; } #if 0 /* Do probing of binary variables to see if we can tighten their coefficients */ else if(probereduce && is_binary(lp, j) && (ix = presolve_probetighten01(psdata, j) > 0)) { report(lp, DETAILED, "presolve_columns: Tightened coefficients for binary variable %s in %d rows\n", get_col_name(lp,j), ix); iCoeffChanged += ix; psdata->forceupdate = TRUE; } #endif /* Perform fixing and deletion, if indicated */ if(candelete) { /* If we have a SOS1 member variable fixed at a non-zero value, then we must fix the other member variables at zero and delete the SOS(es) */ if((Value1 != 0) && SOS_is_member(lp->SOS, 0, j)) { ix = iVarFixed; if(!presolve_fixSOS1(psdata, j, Value1, &iConRemove, &iVarFixed)) status = presolve_setstatus(psdata, INFEASIBLE); if(iVarFixed > ix) psdata->forceupdate = TRUE; break; } else { if(!presolve_colfix(psdata, j, Value1, TRUE, &iVarFixed)) { status = presolve_setstatus(psdata, INFEASIBLE); break; } j = presolve_colremove(psdata, j, TRUE); } } else j = nextActiveLink(psdata->cols->varmap, j); } /* Remove any "hanging" empty row and columns */ if(status == RUNNING) status = presolve_shrink(psdata, &iConRemove, &iVarFixed); (*nCoeffChanged) += iCoeffChanged; (*nConRemove) += iConRemove; (*nVarFixed) += iVarFixed; (*nBoundTighten) += iBoundTighten; (*nSum) += iCoeffChanged+iConRemove+iVarFixed+iBoundTighten; return( status ); } STATIC int presolve_freeandslacks(presolverec *psdata, int *nCoeffChanged, int *nConRemove, int *nVarFixed, int *nSum) { lprec *lp = psdata->lp; MYBOOL isOFNZ, unbounded, impliedfree = is_presolve(lp, PRESOLVE_IMPLIEDFREE), impliedslack = is_presolve(lp, PRESOLVE_IMPLIEDSLK); int iCoeffChanged = 0, iConRemove = 0, iVarFixed = 0, status = RUNNING, i, ix, j, countNZ; REAL coeff_bl, coeff_bu; MATrec *mat = lp->matA; if(impliedfree || impliedslack) for(j = firstActiveLink(psdata->cols->varmap); j != 0; ) { /* Check and initialize */ if((presolve_collength(psdata, j) != 1) || is_int(lp, j) || is_semicont(lp, j) || !presolve_candeletevar(psdata, j)) { j = nextActiveLink(psdata->cols->varmap, j); continue; } ix = 0; i = COL_MAT_ROWNR(presolve_nextrow(psdata, j, &ix)); isOFNZ = isnz_origobj(lp, j); countNZ = presolve_rowlength(psdata, i); coeff_bu = get_upbo(lp, j); coeff_bl = get_lowbo(lp, j); unbounded = my_infinite(lp, coeff_bl) && my_infinite(lp, coeff_bu); ix = lp->rows + j; /* Eliminate singleton free variable and its associated constraint */ if(impliedfree && unbounded && presolve_impliedcolfix(psdata, i, j, TRUE)) { report(lp, DETAILED, "presolve_freeandslacks: Eliminated free variable %s and row %s\n", get_col_name(lp, j), get_row_name(lp, i)); presolve_rowremove(psdata, i, TRUE); iConRemove++; j = presolve_colremove(psdata, j, TRUE); iVarFixed++; } /* Check for implied slack variable in equality constraint */ else if(impliedslack && (countNZ > 1) && is_constr_type(lp, i, EQ) && presolve_impliedcolfix(psdata, i, j, FALSE)) { report(lp, DETAILED, "presolve_freeandslacks: Eliminated implied slack variable %s via row %s\n", get_col_name(lp, j), get_row_name(lp, i)); psdata->forceupdate = TRUE; j = presolve_colremove(psdata, j, TRUE); iVarFixed++; } /* Check for implied (generalized) slack variable in inequality constraint */ else if(impliedslack && !isOFNZ && my_infinite(lp, coeff_bu) && /* Consider removing this test */ #if 0 /* Force zero-bounded implicit slack */ (coeff_bl == 0)) && #else !my_infinite(lp, coeff_bl) && #endif (countNZ > 1) && !is_constr_type(lp, i, EQ)) { REAL *target, ValueA = COL_MAT_VALUE(presolve_lastrow(psdata, j)); #if 0 coeff_bu = get_rh_upper(lp, i); coeff_bl = get_rh_lower(lp, i); if(!presolve_singletonbounds(psdata, i, j, &coeff_bl, &coeff_bu, &ValueA)) { status = presolve_setstatus(psdata, INFEASIBLE); break; } #endif if((coeff_bl != 0) && !my_infinite(lp, coeff_bl) && !my_infinite(lp, coeff_bu)) coeff_bu -= coeff_bl; /* If the coefficient is negative, reduce the lower bound / increase range */ if(ValueA > 0) { target = &lp->orig_upbo[i]; if(!my_infinite(lp, *target)) { if(my_infinite(lp, coeff_bu)) { *target = lp->infinite; psdata->forceupdate = TRUE; } else { *target += ValueA * coeff_bu; *target = presolve_roundrhs(lp, *target, FALSE); } } } /* Otherwise see if the upper bound should be changed */ else { target = &lp->orig_rhs[i]; if(my_infinite(lp, coeff_bu) || my_infinite(lp, *target)) { /* Do we suddenly find that the constraint becomes redundant? (e226.mps) */ if(my_infinite(lp, lp->orig_upbo[i])) { presolve_rowremove(psdata, i, TRUE); iConRemove++; } /* Or does the upper bound of a ranged constraint become Inf? */ else { *target -= lp->orig_upbo[i]; *target = -(*target); mat_multrow(mat, i, -1); lp->orig_upbo[i] = lp->infinite; psdata->forceupdate = TRUE; } } else { *target -= ValueA * coeff_bu; *target = presolve_roundrhs(lp, *target, FALSE); } } presolve_colfix(psdata, j, coeff_bl, TRUE, &iVarFixed); report(lp, DETAILED, "presolve_freeandslacks: Eliminated duplicate slack variable %s via row %s\n", get_col_name(lp, j), get_row_name(lp, i)); j = presolve_colremove(psdata, j, TRUE); } /* Go to next column */ else j = nextActiveLink(psdata->cols->varmap, j); } (*nCoeffChanged) += iCoeffChanged; (*nConRemove) += iConRemove; (*nVarFixed) += iVarFixed; (*nSum) += iCoeffChanged+iConRemove+iVarFixed; return( status ); } STATIC int presolve_preparerows(presolverec *psdata, int *nBoundTighten, int *nSum) { lprec *lp = psdata->lp; MYBOOL impliedfree = is_presolve(lp, PRESOLVE_IMPLIEDFREE), tightenbounds = is_presolve(lp, PRESOLVE_BOUNDS); int iRangeTighten = 0, iBoundTighten = 0, status = RUNNING, i, j; REAL losum, upsum, lorhs, uprhs, epsvalue = psdata->epsvalue; MATrec *mat = lp->matA; for(i = lastActiveLink(psdata->rows->varmap); i > 0; i = prevActiveLink(psdata->rows->varmap, i)) { /* First identify any full row infeasibilities */ j = presolve_rowlengthex(psdata, i); #ifdef Paranoia if(!presolve_testrow(psdata, nextActiveLink(psdata->rows->varmap, i))) { #else if((j > 1) && !psdata->forceupdate && !presolve_rowfeasible(psdata, i, FALSE)) { #endif status = presolve_setstatus(psdata, INFEASIBLE); break; } /* Do bound (LHS) or constraint range (RHS) tightening if we will later identify implied free variables (tends to produce degeneracy otherwise) */ if(impliedfree && (j > 1) && mat_validate(mat)){ /* Look for opportunity to tighten constraint bounds (and check for feasibility again) */ presolve_range(lp, i, psdata->rows, &losum, &upsum); lorhs = get_rh_lower(lp, i); uprhs = get_rh_upper(lp, i); if((losum > MIN(upsum, uprhs)+epsvalue) || (upsum < MAX(losum, lorhs)-epsvalue)) { report(lp, NORMAL, "presolve_preparerows: Variable bound / constraint value infeasibility in row %s.\n", get_row_name(lp, i)); status = presolve_setstatus(psdata, INFEASIBLE); break; } if(losum > lorhs+epsvalue) { set_rh_lower(lp, i, presolve_roundrhs(lp, losum, TRUE)); iRangeTighten++; } if(upsum < uprhs-epsvalue) { set_rh_upper(lp, i, presolve_roundrhs(lp, upsum, FALSE)); iRangeTighten++; } } /* Seek to tighten bounds on individual variables */ if(tightenbounds && mat_validate(mat)) { #if 1 if(j > 1) status = presolve_rowtighten(psdata, i, &iBoundTighten, FALSE); #else if((MIP_count(lp) > 0) && (j > 1)) status = presolve_rowtighten(psdata, i, &iBoundTighten, TRUE); #endif } /* Look for opportunity to convert ranged constraint to equality-type */ if(!is_constr_type(lp, i, EQ) && (get_rh_range(lp, i) < epsvalue)) { presolve_setEQ(psdata, i); iRangeTighten++; } } psdata->forceupdate |= (MYBOOL) (iBoundTighten > 0); (*nBoundTighten) += iBoundTighten+iRangeTighten; (*nSum) += iBoundTighten+iRangeTighten; return( status ); } STATIC int presolve_rows(presolverec *psdata, int *nCoeffChanged, int *nConRemove, int *nVarFixed, int *nBoundTighten, int *nSum) { lprec *lp = psdata->lp; MYBOOL candelete; int iCoeffChanged = 0, iConRemove = 0, iVarFixed = 0, iBoundTighten = 0, status = RUNNING, i,ix, j,jx, item; REAL Value1, Value2, losum, upsum, lorhs, uprhs, epsvalue = psdata->epsvalue; MATrec *mat = lp->matA; for(i = lastActiveLink(psdata->rows->varmap); (i > 0) && (status == RUNNING); ) { candelete = FALSE; /* First identify any full row infeasibilities Note: Handle singletons below to ensure that conflicting multiple singleton rows with this variable do not provoke notice of infeasibility */ j = presolve_rowlengthex(psdata, i); if((j > 1) && !psdata->forceupdate && !presolve_rowfeasible(psdata, i, FALSE)) { status = presolve_setstatus(psdata, INFEASIBLE); break; } presolve_range(lp, i, psdata->rows, &losum, &upsum); lorhs = get_rh_lower(lp, i); uprhs = get_rh_upper(lp, i); #ifdef Paranoia if((losum>uprhs+epsvalue) || (upsum= -epsvalue)) { #else /* Version that deletes bound-fixed columns here */ if((j == 1) && (uprhs-lorhs >= -epsvalue)) { #endif item = 0; jx = presolve_nextcol(psdata, i, &item); j = ROW_MAT_COLNR(jx); /* Make sure we don't have conflicting other singleton rows with this variable */ Value1 = lp->infinite; Value2 = -Value1; if(presolve_collength(psdata, j) > 1) status = presolve_boundconflict(psdata, i, j); else if(is_constr_type(lp, i, EQ)) { Value2 = ROW_MAT_VALUE(jx); Value1 = lp->orig_rhs[i] / Value2; if(Value2 < 0) swapREAL(&losum, &upsum); if((Value1 < losum / my_if(my_infinite(lp, losum), my_sign(Value2), Value2) - epsvalue) || (Value1 > upsum / my_if(my_infinite(lp, upsum), my_sign(Value2), Value2) + epsvalue)) status = presolve_setstatus(psdata, INFEASIBLE); Value2 = Value1; } /* Proceed to fix and remove variable (if it is not a SOS member) */ if(status == RUNNING) { if((fabs(Value2-Value1) < epsvalue) && (fabs(Value2) > epsvalue)) { MYBOOL isSOS = (MYBOOL) (SOS_is_member(lp->SOS, 0, j) != FALSE), deleteSOS = isSOS && presolve_candeletevar(psdata, j); if((Value1 != 0) && deleteSOS) { if(!presolve_fixSOS1(psdata, j, Value1, &iConRemove, &iVarFixed)) status = presolve_setstatus(psdata, INFEASIBLE); psdata->forceupdate = TRUE; } else { if(!presolve_colfix(psdata, j, Value1, (MYBOOL) !isSOS, NULL)) status = presolve_setstatus(psdata, INFEASIBLE); else if(isSOS && !deleteSOS) iBoundTighten++; else { presolve_colremove(psdata, j, TRUE); iVarFixed++; } } } else status = presolve_colsingleton(psdata, i, j, &iBoundTighten); } if(status == INFEASIBLE) { break; } if(psdata->forceupdate != AUTOMATIC) { /* Store dual recovery information and code for deletion */ presolve_storeDualUndo(psdata, i, j); candelete = TRUE; } } /* Delete non-empty rows and variables that are completely determined at zero */ else if((j > 0) /* Only examine non-empty rows, */ && (fabs(lp->orig_rhs[i]) < epsvalue) /* .. and the current RHS is zero, */ && ((psdata->rows->plucount[i] == 0) || (psdata->rows->negcount[i] == 0)) /* .. and the parameter signs are all equal, */ && (psdata->rows->pluneg[i] == 0) /* .. and no (quasi) free variables, */ && (is_constr_type(lp, i, EQ) #ifdef FindImpliedEqualities || (fabs(lorhs-upsum) < epsvalue) /* Convert to equalities */ || (fabs(uprhs-losum) < epsvalue) /* Convert to equalities */ #endif ) ) { /* Delete the columns we can delete */ status = presolve_rowfixzero(psdata, i, &iVarFixed); /* Then delete the row, which is redundant */ if(status == RUNNING) candelete = TRUE; } /* Check if we have a constraint made redundant through bounds on individual variables; such constraints are often referred to as "forcing constraints" */ else if((losum >= lorhs-epsvalue) && (upsum <= uprhs+epsvalue)) { /* Check if we can also fix all the variables */ if(fabs(losum-upsum) < epsvalue) { item = 0; jx = presolve_nextcol(psdata, i, &item); while((status == RUNNING) && (jx >= 0)) { j = ROW_MAT_COLNR(jx); Value1 = get_lowbo(lp, j); if(presolve_colfix(psdata, j, Value1, TRUE, &iVarFixed)) { presolve_colremove(psdata, j, TRUE); iVarFixed++; jx = presolve_nextcol(psdata, i, &item); } else status = presolve_setstatus(psdata, INFEASIBLE); } } candelete = TRUE; } /* Get next row and do the deletion of the previous, if indicated */ ix = i; i = prevActiveLink(psdata->rows->varmap, i); if(candelete) { presolve_rowremove(psdata, ix, TRUE); iConRemove++; } } /* Remove any "hanging" empty row and columns */ if(status == RUNNING) status = presolve_shrink(psdata, &iConRemove, &iVarFixed); (*nCoeffChanged) += iCoeffChanged; (*nConRemove) += iConRemove; (*nVarFixed) += iVarFixed; (*nBoundTighten) += iBoundTighten; (*nSum) += iCoeffChanged+iConRemove+iVarFixed+iBoundTighten; return( status ); } /* Top level presolve routine */ STATIC int presolve(lprec *lp) { int status = RUNNING, i, j = 0, jx = 0, jjx = 0, k, oSum, iCoeffChanged = 0, iConRemove = 0, iVarFixed = 0, iBoundTighten = 0, iSOS = 0, iSum = 0, nCoeffChanged = 0, nConRemove = 0, nVarFixed = 0, nBoundTighten = 0, nSOS = 0, nSum = 0; REAL Value1, Value2, initrhs0 = lp->orig_rhs[0]; presolverec *psdata = NULL; MATrec *mat = lp->matA; #if 0 lp->do_presolve = PRESOLVE_ROWS; report(lp, IMPORTANT, "presolve: Debug override of presolve setting to %d\n", lp->do_presolve); #endif /* Lock the variable mapping arrays and counts ahead of any row/column deletion or creation in the course of presolve, solvelp or postsolve */ if(!lp->varmap_locked) varmap_lock(lp); /* Check if we have already done presolve */ mat_validate(mat); if(lp->wasPresolved) { if(SOS_count(lp) > 0) { SOS_member_updatemap(lp->SOS); make_SOSchain(lp, (MYBOOL) ((lp->do_presolve & PRESOLVE_LASTMASKMODE) != PRESOLVE_NONE)); } if((lp->solvecount > 1) && (lp->bb_level < 1) && ((lp->scalemode & SCALE_DYNUPDATE) != 0)) auto_scale(lp); if(!lp->basis_valid) { crash_basis(lp); report(lp, DETAILED, "presolve: Had to repair broken basis.\n"); } lp->timepresolved = timeNow(); return(status); } /* Produce original model statistics (do hoops to produce correct stats if we have SOS'es) */ i = SOS_count(lp); if(i > 0) { SOS_member_updatemap(lp->SOS); lp->sos_vars = SOS_memberships(lp->SOS, 0); } REPORT_modelinfo(lp, TRUE, "SUBMITTED"); report(lp, NORMAL, " \n"); if(i > 0) lp->sos_vars = 0; /* Finalize basis indicators; if no basis was created earlier via set_basis or crash_basis then simply set the default basis. */ if(!lp->basis_valid) lp->var_basic[0] = AUTOMATIC; /* Flag that we are presolving */ #if 0 write_lp(lp, "test_in.lp"); /* Write to lp-formatted file for debugging */ /*write_mps(lp, "test_in.mps");*/ /* Write to lp-formatted file for debugging */ #endif /* Update inf norms and check for potential factorization trouble */ mat_computemax(mat /*, FALSE */); #if 0 Value1 = fabs(lp->negrange); if(is_obj_in_basis(lp) && (mat->dynrange < Value1) && vec_computeext(lp->orig_obj, 1, lp->columns, TRUE, &i, &j)) { /* Compute relative scale metric */ Value2 = fabs(lp->orig_obj[j]/lp->orig_obj[i]) / mat->dynrange; if(Value2 < 1.0) Value2 = 1.0 / Value2; /* Determine if we should alert modeler and possibly move the OF out of the coefficient matrix */ if((Value2 > Value1) /* Case with extreme scale difference */ #if 1 || (mat->dynrange == 1.0) /* Case where we have an all-unit coefficient matrix, possibly totally unimodular */ #endif ) if((lp->simplex_strategy & SIMPLEX_DYNAMIC) > 0) { clear_action(&lp->algopt, ALGOPT_OBJINBASIS); report(lp, NORMAL, "Moved objective function out of the basis matrix to enhance factorization accuracy.\n"); } else if(mat->dynrange > 1.0) report(lp, IMPORTANT, "Warning: Objective/matrix coefficient magnitude differences will cause inaccuracy!\n"); } #endif /* Do traditional simple presolve */ yieldformessages(lp); if((lp->do_presolve & PRESOLVE_LASTMASKMODE) == PRESOLVE_NONE) { mat_checkcounts(mat, NULL, NULL, TRUE); i = 0; } else { if(lp->full_solution == NULL) allocREAL(lp, &lp->full_solution, lp->sum_alloc+1, TRUE); /* Identify infeasible SOS'es prior to any pruning */ j = 0; for(i = 1; i <= SOS_count(lp); i++) { k = SOS_infeasible(lp->SOS, i); if(k > 0) { presolverec psdata; psdata.lp = lp; report(lp, NORMAL, "presolve: Found SOS %d (type %d) to be range-infeasible on variable %d\n", i, SOS_get_type(lp->SOS, i), k); status = presolve_setstatus(&psdata, INFEASIBLE); j++; } } if(j > 0) goto Finish; /* Create and initialize the presolve data structures */ psdata = presolve_init(lp); /* Reentry point for the outermost, computationally expensive presolve loop */ psdata->outerloops = 0; do { psdata->outerloops++; iCoeffChanged = 0; iConRemove = 0; iVarFixed = 0; iBoundTighten = 0; iSOS = 0; oSum = nSum; /* Do the middle elimination loop */ do { psdata->middleloops++; nSum += iSum; iSum = 0; /* Accumulate constraint bounds based on bounds on individual variables. */ j = 0; while(presolve_statuscheck(psdata, &status) && psdata->forceupdate) { psdata->forceupdate = FALSE; /* Update sums, but limit iteration count to avoid possible "endless" loops with only marginal bound improvements */ if(presolve_updatesums(psdata) && (j < MAX_PSBOUNDTIGHTENLOOPS)) { /* Do row preparation useful for subsequent column and row presolve operations */ if((psdata->outerloops == 1) && (psdata->middleloops == 1)) status = presolve_preparerows(psdata, &iBoundTighten, &iSum); nBoundTighten += iBoundTighten; iBoundTighten = 0; nSum += iSum; iSum = 0; j++; if(status != RUNNING) report(lp, NORMAL, "presolve: Break after bound tightening iteration %d.\n", j); } } if(status != RUNNING) break; /* Do the relatively cheap innermost elimination loop */ do { psdata->innerloops++; nSum += iSum; iSum = 0; /* Eliminate empty rows, convert row singletons to bounds, tighten bounds, and remove always satisfied rows */ if(presolve_statuscheck(psdata, &status) && is_presolve(lp, PRESOLVE_ROWS)) status = presolve_rows(psdata, &iCoeffChanged, &iConRemove, &iVarFixed, &iBoundTighten, &iSum); /* Eliminate empty or fixed columns (including trivial OF column singletons) */ if(presolve_statuscheck(psdata, &status) && is_presolve(lp, PRESOLVE_COLS)) status = presolve_columns(psdata, &iCoeffChanged, &iConRemove, &iVarFixed, &iBoundTighten, &iSum); /* Presolve SOS'es if possible (always do this) */ if(presolve_statuscheck(psdata, &status)) status = presolve_redundantSOS(psdata, &iBoundTighten, &iSum); } while((status == RUNNING) && (iSum > 0)); if(status != RUNNING) break; /* Merge compatible similar rows; loop backwards over every row */ if(presolve_statuscheck(psdata, &status) && (psdata->outerloops == 1) && (psdata->middleloops <= MAX_PSMERGELOOPS) && is_presolve(lp, PRESOLVE_MERGEROWS)) status = presolve_mergerows(psdata, &iConRemove, &iSum); /* Eliminate dominated rows */ if(presolve_statuscheck(psdata, &status) && is_presolve(lp, PRESOLVE_ROWDOMINATE)) presolve_rowdominance(psdata, &iCoeffChanged, &iConRemove, &iVarFixed, &iSum); /* See if we can convert some constraints to SOSes (only SOS1 handled) */ if(presolve_statuscheck(psdata, &status) && (MIP_count(lp) > 0) && is_presolve(lp, PRESOLVE_SOS)) status = presolve_SOS1(psdata, &iCoeffChanged, &iConRemove, &iVarFixed, &iSOS, &iSum); /* Eliminate dominated columns in set coverage models */ if(presolve_statuscheck(psdata, &status) && (lp->int_vars > 1) && is_presolve(lp, PRESOLVE_COLDOMINATE)) presolve_coldominance01(psdata, &iConRemove, &iVarFixed, &iSum); /* Aggregate compatible columns */ if(presolve_statuscheck(psdata, &status) && /*TRUE ||*/ is_presolve(lp, PRESOLVE_AGGREGATE)) presolve_aggregate(psdata, &iConRemove, &iVarFixed, &iSum); /* Eliminate free variables and implied slacks */ if(presolve_statuscheck(psdata, &status) && /* !is_presolve(lp, PRESOLVE_ELIMEQ2) && */ is_presolve(lp, PRESOLVE_IMPLIEDSLK | PRESOLVE_IMPLIEDFREE)) status = presolve_freeandslacks(psdata, &iCoeffChanged, &iConRemove, &iVarFixed, &iSum); } while((status == RUNNING) && (iSum > 0)); if(status != RUNNING) break; /* Check if we can do elimination of rank-deficient equality constraints */ if(presolve_statuscheck(psdata, &status) && (psdata->EQmap->count > 1) && is_presolve(lp, PRESOLVE_LINDEP)) { #if 0 REPORT_mat_mmsave(lp, "A.mtx", NULL, FALSE, "Constraint matrix A"); #endif presolve_singularities(psdata, &iCoeffChanged, &iConRemove, &iVarFixed, &iSum); } /* Eliminate variable and tighten bounds using 2-element EQs; note that this involves modifying the coefficients of A and can therefore be a slow operation. */ if(presolve_statuscheck(psdata, &status) && is_presolve(lp, PRESOLVE_ELIMEQ2)) { jjx = 0; do { jjx += iSum; status = presolve_elimeq2(psdata, &iCoeffChanged, &iConRemove, &iVarFixed, &iSum); } while((status == RUNNING) && (iSum > jjx)); iSum = jjx; #if 0 /* Eliminate free variables and implied slacks */ if(presolve_statuscheck(psdata, &status) && is_presolve(lp, PRESOLVE_IMPLIEDSLK | PRESOLVE_IMPLIEDFREE)) status = presolve_freeandslacks(psdata, &iCoeffChanged, &iConRemove, &iVarFixed, &iSum); #endif } /* Increase A matrix sparsity by discovering common subsets using EQs */ if(presolve_statuscheck(psdata, &status) && (psdata->EQmap->count > 0) && is_presolve(lp, PRESOLVE_SPARSER)) status = presolve_makesparser(psdata, &iCoeffChanged, &iConRemove, &iVarFixed, &iSum); /* Do GCD-based coefficient reductions (also does row scaling, even if no rhs INT truncations are possible) */ if(presolve_statuscheck(psdata, &status) && (psdata->INTmap->count > 0) && is_presolve(lp, PRESOLVE_REDUCEGCD)) if(!presolve_reduceGCD(psdata, &iCoeffChanged, &iBoundTighten, &iSum)) status = presolve_setstatus(psdata, INFEASIBLE); /* Simplify knapsack or set coverage models where OF coefficients are duplicated in the constraints. At the cost of adding helper columns, this increases sparsity and facilitates identification of lower and upper bounds. */ if(presolve_statuscheck(psdata, &status) && is_presolve(lp, PRESOLVE_KNAPSACK)) { i = iCoeffChanged; status = presolve_knapsack(psdata, &iCoeffChanged); } /* Remove any "hanging" empty row and columns */ if(status == RUNNING) status = presolve_shrink(psdata, &iConRemove, &iVarFixed); nCoeffChanged += iCoeffChanged; nConRemove += iConRemove; nVarFixed += iVarFixed; nBoundTighten += iBoundTighten; nSOS += iSOS; nSum += iSum; iSum = iConRemove + iVarFixed + iBoundTighten + iCoeffChanged; if(iSum > 0) report(lp, NORMAL, "Presolve O:%d -> Reduced rows:%5d, cols:%5d --- changed bnds:%5d, Ab:%5d.\n", psdata->outerloops, iConRemove, iVarFixed, iBoundTighten, iCoeffChanged); /* Do the outermost loop again if we were successful in this presolve sequences */ } while(presolve_statuscheck(psdata, &status) && (psdata->forceupdate || (oSum < nSum)) && (psdata->outerloops < get_presolveloops(lp)) && (psdata->rows->varmap->count+psdata->cols->varmap->count > 0)); /* Finalize presolve */ #ifdef Paranoia i = presolve_debugcheck(lp, psdata->rows->varmap, psdata->cols->varmap); if(i > 0) report(lp, SEVERE, "presolve: %d internal consistency failure%s\n", i, my_plural_std(i)); if((SOS_count(lp) > 0) && !presolve_SOScheck(psdata)) report(lp, SEVERE, "presolve: SOS sparse member mapping problem - part 1\n"); #endif /* Perform bound relaxation to reduce chance of degeneracy. */ if((status == RUNNING) && !is_presolve(lp, PRESOLVE_IMPLIEDFREE)) jjx = presolve_makefree(psdata); else jjx = 0; /* Finalize the presolve */ if(!presolve_finalize(psdata)) report(lp, SEVERE, "presolve: Unable to construct internal data representation\n"); /* Report summary information */ i = NORMAL; iVarFixed = lp->presolve_undo->orig_columns - psdata->cols->varmap->count; iConRemove = lp->presolve_undo->orig_rows - psdata->rows->varmap->count; if(nSum > 0) report(lp, i, "PRESOLVE Elimination loops performed.......... O%d:M%d:I%d\n", psdata->outerloops, psdata->middleloops, psdata->innerloops); if(nVarFixed) report(lp, i, " %8d empty or fixed variables............. %s.\n", nVarFixed, "REMOVED"); if(nConRemove) report(lp, i, " %8d empty or redundant constraints....... %s.\n", nConRemove, "REMOVED"); if(nBoundTighten) report(lp, i, " %8d bounds............................... %s.\n", nBoundTighten, "TIGHTENED"); if(nCoeffChanged) report(lp, i, " %8d matrix coefficients.................. %s.\n", nCoeffChanged, "CHANGED"); if(jjx > 0) report(lp, i, " %8d variables' final bounds.............. %s.\n", jjx, "RELAXED"); if(nSOS) report(lp, i, " %8d constraints detected as SOS1......... %s.\n", nSOS, "CONVERTED"); /* Report optimality or infeasibility */ if(status == UNBOUNDED) report(lp, NORMAL, "%20s Solution status detected............. %s.\n", "", "UNBOUNDED"); else if(status == INFEASIBLE) report(lp, NORMAL, "%20s Solution status detected............. %s.\n", "", "INFEASIBLE"); else { if(psdata->cols->varmap->count == 0) Value1 = Value2 = lp->presolve_undo->fixed_rhs[0] -initrhs0; else presolve_rangeorig(lp, 0, psdata->rows, &Value1, &Value2, -initrhs0); if((fabs(Value1 - Value2) < psdata->epsvalue) || (fabs(my_reldiff(Value1, Value2)) < psdata->epsvalue)) { if((lp->rows == 0) && (lp->columns == 0)) { status = PRESOLVED; Value1 = my_chsign(is_maxim(lp), Value1); lp->solution[0] = Value1; lp->best_solution[0] = Value1; lp->full_solution[0] = Value1; } report(lp, NORMAL, "%20s OPTIMAL solution found............... %-g", "", Value1); } else if((status == RUNNING) && (i >= NORMAL)) { char lonum[20], upnum[20]; if(my_infinite(lp, Value1)) sprintf(lonum, "%13s", "-Inf"); else sprintf(lonum, "%+12g", Value1); if(my_infinite(lp, Value2)) sprintf(upnum, "%-13s", "Inf"); else sprintf(upnum, "%+-12g", Value2); report(lp, i, "%20s [ %s < Z < %s ]\n", "", lonum, upnum); } /* Update values for dual limit and best heuristic values */ if((MIP_count(lp) > 0) || (get_Lrows(lp) > 0)) { if(is_maxim(lp)) { SETMAX(lp->bb_heuristicOF, Value1); SETMIN(lp->bb_limitOF, Value2); } else { SETMIN(lp->bb_heuristicOF, Value2); SETMAX(lp->bb_limitOF, Value1); } } } report(lp, NORMAL, " \n"); /* Clean up (but save counts of constraint types for display later) */ j = psdata->LTmap->count; jx = psdata->EQmap->count; jjx = lp->rows - j - jx; presolve_free(&psdata); } /* Signal that we are done presolving */ if((lp->usermessage != NULL) && ((lp->do_presolve & PRESOLVE_LASTMASKMODE) != 0) && (lp->msgmask & MSG_PRESOLVE)) lp->usermessage(lp, lp->msghandle, MSG_PRESOLVE); /* Create master SOS variable list */ if(SOS_count(lp) > 0) { /*SOS_member_updatemap(lp->SOS); */ make_SOSchain(lp, (MYBOOL) ((lp->do_presolve & PRESOLVE_LASTMASKMODE) != PRESOLVE_NONE)); } /* Finalize model not identified as infeasible or unbounded */ if(status == RUNNING) { /* Resolve GUBs */ if(is_bb_mode(lp, NODE_GUBMODE)) identify_GUB(lp, TRUE); #if 0 /* Mark rows containing hidden identity matrices so that supporting factorization engines can use this structural information to boost efficiency */ if(is_algopt(lp, ALGOPT_COMPACTBPF)) lp->bfpoptimize = (MYBOOL) (assist_factorization(lp, ROWTYPE_LOGICAL, &lp->rowset1, &lp->rowno1) > 0); #endif /* Scale the model based on current settings */ auto_scale(lp); /* Crash the basis, if specified */ crash_basis(lp); /* Produce presolved model statistics */ if(nConRemove+nVarFixed+nBoundTighten+nVarFixed+nCoeffChanged > 0) { REPORT_modelinfo(lp, FALSE, "REDUCED"); if(nSum > 0) { report(lp, NORMAL, "Row-types: %7d LE, %7d GE, %7d EQ.\n", j, jjx, jx); report(lp, NORMAL, " \n"); } } } /* Optionally produce data on constraint classes */ if(lp->verbose > NORMAL) { report(lp, NORMAL, " \n"); REPORT_constraintinfo(lp, "CONSTRAINT CLASSES"); report(lp, NORMAL, " \n"); } Finish: lp->wasPresolved = TRUE; lp->timepresolved = timeNow(); #if 0 /* write_mps(lp, "test_out.mps"); */ /* Must put here due to variable name mapping */ write_lp(lp, "test_out.lp"); /* Must put here due to variable name mapping */ #endif #if 0 REPORT_debugdump(lp, "testint2.txt", FALSE); #endif return( status ); } STATIC MYBOOL postsolve(lprec *lp, int status) { /* Verify solution */ if(lp->lag_status != RUNNING) { int itemp; if(status == PRESOLVED) status = OPTIMAL; if((status == OPTIMAL) || (status == SUBOPTIMAL)) { itemp = check_solution(lp, lp->columns, lp->best_solution, lp->orig_upbo, lp->orig_lowbo, lp->epssolution); if((itemp != OPTIMAL) && (lp->spx_status == OPTIMAL)) lp->spx_status = itemp; else if((itemp == OPTIMAL) && ((status == SUBOPTIMAL) || (lp->spx_status == PRESOLVED))) lp->spx_status = status; } else if(status != PRESOLVED) { report(lp, NORMAL, "lp_solve unsuccessful after %.0f iter and a last best value of %g\n", (double) get_total_iter(lp), lp->best_solution[0]); if(lp->bb_totalnodes > 0) report(lp, NORMAL, "lp_solve explored %.0f nodes before termination\n", (double) get_total_nodes(lp)); } else lp->spx_status = OPTIMAL; /* Only rebuild primal solution here, since the dual is only computed on request */ presolve_rebuildUndo(lp, TRUE); } /* Check if we can clear the variable map */ if(varmap_canunlock(lp)) lp->varmap_locked = FALSE; #if 0 REPORT_mat_mmsave(lp, "basis.mtx", NULL, FALSE); /* Write the current basis matrix (no OF) */ #endif return( TRUE ); } MSVMpack1.2/lp_solve_5.5/lp_Hash.h0000664000175000017500000000216511141374244015672 0ustar lauerlauer#ifndef HEADER_lp_hash #define HEADER_lp_hash /* For row and column name hash tables */ typedef struct _hashelem { char *name; int index; struct _hashelem *next; struct _hashelem *nextelem; } hashelem; typedef struct /* _hashtable */ { hashelem **table; int size; int base; int count; struct _hashelem *first; struct _hashelem *last; } hashtable; #ifdef __cplusplus extern "C" { #endif STATIC hashtable *create_hash_table(int size, int base); STATIC void free_hash_table(hashtable *ht); STATIC hashelem *findhash(const char *name, hashtable *ht); STATIC hashelem *puthash(const char *name, int index, hashelem **list, hashtable *ht); STATIC void drophash(const char *name, hashelem **list, hashtable *ht); STATIC void free_hash_item(hashelem **hp); STATIC hashtable *copy_hash_table(hashtable *ht, hashelem **list, int newsize); STATIC int find_var(lprec *lp, char *name, MYBOOL verbose); STATIC int find_row(lprec *lp, char *name, MYBOOL Unconstrained_rows_found); #ifdef __cplusplus } #endif #endif /* HEADER_lp_hash */ MSVMpack1.2/lp_solve_5.5/lp_scale.h0000664000175000017500000000176011141374251016074 0ustar lauerlauer#ifndef HEADER_lp_scale #define HEADER_lp_scale #include "lp_types.h" #ifdef __cplusplus extern "C" { #endif /* Put function headers here */ STATIC MYBOOL scale_updatecolumns(lprec *lp, REAL *scalechange, MYBOOL updateonly); STATIC MYBOOL scale_updaterows(lprec *lp, REAL *scalechange, MYBOOL updateonly); STATIC MYBOOL scale_rows(lprec *lp, REAL *scaledelta); STATIC MYBOOL scale_columns(lprec *lp, REAL *scaledelta); STATIC void unscale_columns(lprec *lp); STATIC REAL scale(lprec *lp, REAL *scaledelta); STATIC REAL scaled_mat(lprec *lp, REAL value, int rownr, int colnr); STATIC REAL unscaled_mat(lprec *lp, REAL value, int rownr, int colnr); STATIC REAL scaled_value(lprec *lp, REAL value, int index); STATIC REAL unscaled_value(lprec *lp, REAL value, int index); STATIC MYBOOL scaleCR(lprec *lp, REAL *scaledelta); STATIC MYBOOL finalize_scaling(lprec *lp, REAL *scaledelta); STATIC REAL auto_scale(lprec *lp); void undoscale(lprec *lp); #ifdef __cplusplus } #endif #endif /* HEADER_lp_scale */ MSVMpack1.2/doc/0000755000175000017500000000000011723354345012476 5ustar lauerlauerMSVMpack1.2/doc/myTestData0000644000175000017500000000251311644772171014504 0ustar lauerlauer30 4 5.000000 3.500000 1.300000 0.300000 1.000000 4.500000 2.300000 1.300000 0.300000 1.000000 4.400000 3.200000 1.300000 0.200000 1.000000 5.000000 3.500000 1.600000 0.600000 1.000000 5.100000 3.800000 1.900000 0.400000 1.000000 4.800000 3.000000 1.400000 0.300000 1.000000 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3.400000 5.400000 2.300000 3.000000 5.900000 3.000000 5.100000 1.800000 3.000000 MSVMpack1.2/doc/example.c0000644000175000017500000000574011645752703014306 0ustar lauerlauer#include "libMSVM.h" // Generic structure and function declarations #include "libtrainMSVM.h" // Training functions (not required for predictions only) #include "libevalMSVM.h" // Evaluation functions (also used during training) int main(void) { struct Model *model; // declare a model struct Data *training_set, *test_set; // declare the datasets long status; // for MSVM_train return code double accuracy = 0.98; // desired accuracy level of 98% long chunk_size = 4; // size of the chunk used for training int cache_memory = 1024; // Maximal amount of cache memory in MB int nprocs = get_nprocs(); // Number of available CPUs long *labels; printf("This is a simple example showing how to use\n MSVMpack through the C API.\n\n"); model = MSVM_make_model(MSVM2); // Create an empty model with default parameters if(model == NULL) { printf("Error in model creation\n"); exit(1); } else printf("M-SVM model successfully created with defaults:\n MSVM2-type, kernel type = %d.\n", model->nature_kernel); // Change some parameters model->nature_kernel = RBF; printf("Changed the kernel type in model to Gaussian RBF.\n"); MSVM_model_set_C(1.0, 3, model); printf("Initialized the hyperparameters C to %1.2lf for all %ld classes.\n",model->C[1],model->Q); model->C[2] = 2.0; model->C[3] = 3.0; printf("Changed hyperparameters C_2 to %1.2lf and C_3 to %1.2lf.\n",model->C[2],model->C[3]); printf("Loading the data... \n"); // The data format can be either DOUBLE, FLOAT, INT, SHORT, BYTE, or BIT training_set = MSVM_make_dataset("myTrainingData",DOUBLE); // load the training data test_set = MSVM_make_dataset("myTestData",DOUBLE); // load the test data printf("Calling MSVM_train()...\n"); /* Train the model on the training_set with default initialization (first NULL) no periodic saving of alpha (second NULL) no log file (third NULL) */ status = MSVM_train(model, training_set, chunk_size, accuracy, cache_memory, nprocs, NULL, NULL, NULL); if(status >= 0) { printf("Training done without error, will now classify the test set.\n"); /* Allocate the array for predicted labels (size should be (size of test set + 1) ) */ labels = (long *)malloc(sizeof(long) * (test_set->nb_data + 1)); /* Classify the test set, store the predicted labels in 'labels' and print outputs on screen (because filename=NULL) */ MSVM_classify_set(labels, test_set->X, test_set->y, test_set->nb_data, NULL, model, nprocs); } else printf("Error in training.\n"); // Free the memory free(labels); MSVM_delete_model(model); MSVM_delete_dataset(training_set); MSVM_delete_dataset(test_set); return 0; } MSVMpack1.2/doc/myTrainingData0000644000175000017500000001243611644772171015345 0ustar lauerlauer120 4 5.100000 3.500000 1.400000 0.200000 1.000000 4.900000 3.000000 1.400000 0.200000 1.000000 4.700000 3.200000 1.300000 0.200000 1.000000 4.600000 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directory <-- This should be changed in your own Makefiles MSVMPACK_DIR= ../ # Header files directory INCLUDEDIR= -I$(MSVMPACK_DIR)include/ # Static library directory LIBDIR= -L$(MSVMPACK_DIR)lib/ # Required libraries LIB=-lmsvm -lm -ldl -lpthread # Make rule example: example.c gcc -o example example.c $(INCLUDEDIR) $(LIBDIR) $(LIB) @echo "Successfully compiled example.c" # -lmsvm : link with MSVMpack static library (libmsvm.a) # -lm : math library # -ldl : required by lp_solve # -lpthread : POSIX threads library (for parallel implementation) MSVMpack1.2/mongoose/0000755000175000017500000000000011557453204013556 5ustar lauerlauerMSVMpack1.2/mongoose/mongoose.10000644000175000017500000001366111557453204015475 0ustar lauerlauer.\" Process this file with .\" groff -man -Tascii mongoose.1 .\" $Id: mongoose.1,v 1.12 2008/11/29 15:32:42 drozd Exp $ .Dd Aug 31, 2010 .Dt mongoose 1 .Sh NAME .Nm mongoose .Nd lightweight web server .Sh SYNOPSIS .Nm .Op Ar config_file .Nm .Op Ar OPTIONS .Nm .Fl A Ar htpasswd_file domain_name user_name password .Sh DESCRIPTION .Nm is small, fast and easy to use web server with CGI, SSL, MD5 authorization, and basic SSI support. .Pp .Nm does not detach from terminal, and uses current working directory as the web root, unless .Fl r option is specified. It is possible to specify multiple ports to listen on. For example, to make mongoose listen on HTTP port 80 and HTTPS port 443, one should start it as: .Nm .Fl s Ar cert.pem Fl p Ar 80,443s .Pp Unlike other web servers, .Nm does not expect CGI scripts to be put in a special directory. CGI scripts can be anywhere. CGI (and SSI) files are recognized by the file extension. .Pp If no arguments are given, .Nm searches for a configuration file called "mongoose.conf" in the same directory where mongoose binary is located. Alternatively, a file name could be specified in the command line. Format of the configuration file is the same as for the command line options except that each option must be specified on a separate line, leading dashes for option names must be omitted. Lines beginning with '#' and empty lines are ignored. .Pp .Sh OPTIONS .Bl -tag -width indent .It Fl A Ar htpasswd_file domain_name user_name password Add/edit user's password in the passwords file. Deleting users can be done with any text editor. Functionality is similar to Apache's .Ic htdigest utility. .It Fl C Ar cgi_extensions Comma-separated list of CGI extensions. All files having these extensions are treated as CGI scripts. Default: ".cgi,.pl,.php" .It Fl E Ar cgi_environment Extra environment variables to be passed to the CGI script in addition to standard ones. The list must be comma-separated list of X=Y pairs, like this: "VARIABLE1=VALUE1,VARIABLE2=VALUE2". Default: "" .It Fl G Ar put_delete_passwords_file PUT and DELETE passwords file. This must be specified if PUT or DELETE methods are used. Default: "" .It Fl I Ar cgi_interpreter Use .Ar cgi_interpreter as a CGI interpreter for all CGI scripts regardless script extension. Default: "". Mongoose decides which interpreter to use by looking at the first line of a CGI script. .It Fl M Ar max_request_size Maximum HTTP request size in bytes. Default: "16384" .It Fl P Ar protect_uri Comma separated list of URI=PATH pairs, specifying that given URIs must be protected with respected password files. Default: "" .It Fl R Ar authentication_domain Authorization realm. Default: "mydomain.com" .It Fl S Ar ssi_extensions Comma separated list of SSI extensions. Unknown SSI directives are silently ignored. Currently, two SSI directives supported, "include" and "exec". Default: "shtml,shtm" .It Fl a Ar access_log_file Access log file. Default: "", no logging is done. .It Fl d Ar enable_directory_listing Enable/disable directory listing. Default: "yes" .It Fl e Ar error_log_file Error log file. Default: "", no errors are logged. .It Fl g Ar global_passwords_file Location of a global passwords file. If set, per-directory .htpasswd files are ignored, and all requests must be authorised against that file. Default: "" .It Fl i Ar index_files Comma-separated list of files to be treated as directory index files. Default: "index.html,index.htm,index.cgi" .It Fl l Ar access_control_list Specify access control list (ACL). ACL is a comma separated list of IP subnets, each subnet is prepended by '-' or '+' sign. Plus means allow, minus means deny. If subnet mask is omitted, like "-1.2.3.4", then it means single IP address. Mask may vary from 0 to 32 inclusive. On each request, full list is traversed, and last match wins. Default setting is to allow all. For example, to allow only 192.168/16 subnet to connect, run "mongoose -0.0.0.0/0,+192.168/16". Default: "" .It Fl m Ar extra_mime_types Extra mime types to recognize, in form "extension1=type1,extension2=type2,...". Extension must include dot. Example: "mongoose -m .cpp=plain/text,.java=plain/text". Default: "" .It Fl p Ar listening_ports Comma-separated list of ports to listen on. If the port is SSL, a letter 's' must be appeneded, for example, "-p 80,443s" will open port 80 and port 443, and connections on port 443 will be SSL-ed. It is possible to specify an IP address to bind to. In this case, an IP address and a colon must be prepended to the port number. For example, to bind to a loopback interface on port 80 and to all interfaces on HTTPS port 443, use "mongoose -p 127.0.0.1:80,443s". Default: "8080" .It Fl r Ar document_root Location of the WWW root directory. A comma separated list of URI_PREFIX=DIRECTORY pairs could be appended to it, allowing Mongoose to serve from multiple directories. For example, "mongoose -p /var/www,/config=/etc,/garbage=/tmp". Default: "." .It Fl s Ar ssl_certificate Location of SSL certificate file. Default: "" .It Fl t Ar num_threads Number of worker threads to start. Default: "10" .It Fl u Ar run_as_user Switch to given user's credentials after startup. Default: "" .El .Pp .Sh EMBEDDING .Nm was designed to be embeddable into C/C++ applications. Since the source code is contained in single C file, it is fairly easy to embed it and follow the updates. Please refer to http://code.google.com/p/mongoose for details. .Pp .Sh EXAMPLES .Bl -tag -width indent .It Nm Fl r Ar /var/www,/aa=/tmp,/bb=/etc Fl s Ar /etc/cert.pem Fl p Ar 8080,8043s Start listening on port 8080 for HTTP, and 8043 for HTTPS connections. Use /etc/cert.pem as SSL certificate file. Web root is /var/www. In addition, map directory /tmp to URI /aa, directory /etc to URI /bb. .It Nm Fl l Ar -0.0.0.0/0,+10.0.0.0/8,+1.2.3.4 Deny connections from everywhere, allow only IP address 1.2.3.4 and all IP addresses from 10.0.0.0/8 subnet to connect. .El .Pp .Sh COPYRIGHT .Nm is licensed under the terms of the MIT license. .Sh AUTHOR .An Sergey Lyubka Aq valenok@gmail.com . MSVMpack1.2/mongoose/main.c0000644000175000017500000003612611557453204014656 0ustar lauerlauer// Copyright (c) 2004-2009 Sergey Lyubka // // 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. #if defined(_WIN32) #define _CRT_SECURE_NO_WARNINGS // Disable deprecation warning in VS2005 #else #define _XOPEN_SOURCE 600 // For PATH_MAX on linux #endif #include #include #include #include #include #include #include #include #include #include "mongoose.h" #ifdef _WIN32 #include #include #define PATH_MAX MAX_PATH #define S_ISDIR(x) ((x) & _S_IFDIR) #define DIRSEP '\\' #define snprintf _snprintf #define vsnprintf _vsnprintf #define sleep(x) Sleep((x) * 1000) #define WINCDECL __cdecl #else #include #include #define DIRSEP '/' #define WINCDECL #endif // _WIN32 #define MAX_OPTIONS 40 static int exit_flag; static char server_name[40]; // Set by init_server_name() static char config_file[PATH_MAX]; // Set by process_command_line_arguments() static struct mg_context *ctx; // Set by start_mongoose() #if !defined(CONFIG_FILE) #define CONFIG_FILE "mongoose.conf" #endif /* !CONFIG_FILE */ static void WINCDECL signal_handler(int sig_num) { exit_flag = sig_num; } static void die(const char *fmt, ...) { va_list ap; char msg[200]; va_start(ap, fmt); vsnprintf(msg, sizeof(msg), fmt, ap); va_end(ap); #if defined(_WIN32) MessageBox(NULL, msg, "Error", MB_OK); #else fprintf(stderr, "%s\n", msg); #endif exit(EXIT_FAILURE); } static void show_usage_and_exit(void) { const char **names; int i; fprintf(stderr, "Mongoose version %s (c) Sergey Lyubka\n", mg_version()); fprintf(stderr, "Usage:\n"); fprintf(stderr, " mongoose -A \n"); fprintf(stderr, " mongoose \n"); fprintf(stderr, " mongoose [-option value ...]\n"); fprintf(stderr, "OPTIONS:\n"); names = mg_get_valid_option_names(); for (i = 0; names[i] != NULL; i += 3) { fprintf(stderr, " -%s %s (default: \"%s\")\n", names[i], names[i + 1], names[i + 2] == NULL ? "" : names[i + 2]); } fprintf(stderr, "See http://code.google.com/p/mongoose/wiki/MongooseManual" " for more details.\n"); fprintf(stderr, "Example:\n mongoose -s cert.pem -p 80,443s -d no\n"); exit(EXIT_FAILURE); } static void verify_document_root(const char *root) { const char *p, *path; char buf[PATH_MAX]; struct stat st; path = root; if ((p = strchr(root, ',')) != NULL && (size_t) (p - root) < sizeof(buf)) { memcpy(buf, root, p - root); buf[p - root] = '\0'; path = buf; } if (stat(path, &st) != 0 || !S_ISDIR(st.st_mode)) { die("Invalid root directory: [%s]: %s", root, strerror(errno)); } } static char *sdup(const char *str) { char *p; if ((p = (char *) malloc(strlen(str) + 1)) != NULL) { strcpy(p, str); } return p; } static void set_option(char **options, const char *name, const char *value) { int i; if (!strcmp(name, "document_root") || !(strcmp(name, "r"))) { verify_document_root(value); } for (i = 0; i < MAX_OPTIONS - 3; i++) { if (options[i] == NULL) { options[i] = sdup(name); options[i + 1] = sdup(value); options[i + 2] = NULL; break; } } if (i == MAX_OPTIONS - 3) { die("%s", "Too many options specified"); } } static void process_command_line_arguments(char *argv[], char **options) { char line[512], opt[512], val[512], *p; FILE *fp = NULL; size_t i, line_no = 0; options[0] = NULL; // Should we use a config file ? if (argv[1] != NULL && argv[2] == NULL) { snprintf(config_file, sizeof(config_file), "%s", argv[1]); } else if ((p = strrchr(argv[0], DIRSEP)) == NULL) { // No command line flags specified. Look where binary lives snprintf(config_file, sizeof(config_file), "%s", CONFIG_FILE); } else { snprintf(config_file, sizeof(config_file), "%.*s%c%s", (int) (p - argv[0]), argv[0], DIRSEP, CONFIG_FILE); } fp = fopen(config_file, "r"); // If config file was set in command line and open failed, exit if (argv[1] != NULL && argv[2] == NULL && fp == NULL) { die("Cannot open config file %s: %s", config_file, strerror(errno)); } // Load config file settings first if (fp != NULL) { fprintf(stderr, "Loading config file %s\n", config_file); // Loop over the lines in config file while (fgets(line, sizeof(line), fp) != NULL) { line_no++; // Ignore empty lines and comments if (line[0] == '#' || line[0] == '\n') continue; if (sscanf(line, "%s %[^\r\n#]", opt, val) != 2) { die("%s: line %d is invalid", config_file, (int) line_no); } set_option(options, opt, val); } (void) fclose(fp); } // Now handle command line flags. They override config file settings. for (i = 1; argv[i] != NULL; i += 2) { if (argv[i][0] != '-' || argv[i + 1] == NULL) { show_usage_and_exit(); } set_option(options, &argv[i][1], argv[i + 1]); } } static void init_server_name(void) { snprintf(server_name, sizeof(server_name), "Mongoose web server v.%s", mg_version()); } static void start_mongoose(int argc, char *argv[]) { char *options[MAX_OPTIONS]; int i; /* Edit passwords file if -A option is specified */ if (argc > 1 && argv[1][0] == '-' && argv[1][1] == 'A') { if (argc != 6) { show_usage_and_exit(); } exit(mg_modify_passwords_file(argv[2], argv[3], argv[4], argv[5]) ? EXIT_SUCCESS : EXIT_FAILURE); } /* Show usage if -h or --help options are specified */ if (argc == 2 && (!strcmp(argv[1], "-h") || !strcmp(argv[1], "--help"))) { show_usage_and_exit(); } /* Update config based on command line arguments */ process_command_line_arguments(argv, options); /* Setup signal handler: quit on Ctrl-C */ signal(SIGTERM, signal_handler); signal(SIGINT, signal_handler); /* Start Mongoose */ ctx = mg_start(NULL, NULL, (const char **) options); for (i = 0; options[i] != NULL; i++) { free(options[i]); } if (ctx == NULL) { die("%s", "Failed to start Mongoose. Maybe some options are " "assigned bad values?\nTry to run with '-e error_log.txt' " "and check error_log.txt for more information."); } } #ifdef _WIN32 static SERVICE_STATUS ss; static SERVICE_STATUS_HANDLE hStatus; static const char *service_magic_argument = "--"; static void WINAPI ControlHandler(DWORD code) { if (code == SERVICE_CONTROL_STOP || code == SERVICE_CONTROL_SHUTDOWN) { ss.dwWin32ExitCode = 0; ss.dwCurrentState = SERVICE_STOPPED; } SetServiceStatus(hStatus, &ss); } static void WINAPI ServiceMain(void) { ss.dwServiceType = SERVICE_WIN32; ss.dwCurrentState = SERVICE_RUNNING; ss.dwControlsAccepted = SERVICE_ACCEPT_STOP | SERVICE_ACCEPT_SHUTDOWN; hStatus = RegisterServiceCtrlHandler(server_name, ControlHandler); SetServiceStatus(hStatus, &ss); while (ss.dwCurrentState == SERVICE_RUNNING) { Sleep(1000); } mg_stop(ctx); ss.dwCurrentState = SERVICE_STOPPED; ss.dwWin32ExitCode = (DWORD) -1; SetServiceStatus(hStatus, &ss); } #define ID_TRAYICON 100 #define ID_QUIT 101 #define ID_EDIT_CONFIG 102 #define ID_SEPARATOR 103 #define ID_INSTALL_SERVICE 104 #define ID_REMOVE_SERVICE 105 #define ID_ICON 200 static NOTIFYICONDATA TrayIcon; static void edit_config_file(void) { const char **names, *value; FILE *fp; int i; char cmd[200]; // Create config file if it is not present yet if ((fp = fopen(config_file, "r")) != NULL) { fclose(fp); } else if ((fp = fopen(config_file, "a+")) != NULL) { fprintf(fp, "# Mongoose web server configuration file.\n" "# Lines starting with '#' and empty lines are ignored.\n" "# For detailed description of every option, visit\n" "# http://code.google.com/p/mongoose/wiki/MongooseManual\n\n"); names = mg_get_valid_option_names(); for (i = 0; names[i] != NULL; i += 3) { value = mg_get_option(ctx, names[i]); fprintf(fp, "# %s %s\n", names[i + 1], *value ? value : ""); } fclose(fp); } snprintf(cmd, sizeof(cmd), "notepad.exe %s", config_file); WinExec(cmd, SW_SHOW); } static void show_error(void) { char buf[256]; FormatMessage(FORMAT_MESSAGE_FROM_SYSTEM | FORMAT_MESSAGE_IGNORE_INSERTS, NULL, GetLastError(), MAKELANGID(LANG_NEUTRAL, SUBLANG_DEFAULT), buf, sizeof(buf), NULL); MessageBox(NULL, buf, "Error", MB_OK); } static int manage_service(int action) { static const char *service_name = "Mongoose"; SC_HANDLE hSCM = NULL, hService = NULL; SERVICE_DESCRIPTION descr = {server_name}; char path[PATH_MAX + 20]; // Path to executable plus magic argument int success = 1; if ((hSCM = OpenSCManager(NULL, NULL, action == ID_INSTALL_SERVICE ? GENERIC_WRITE : GENERIC_READ)) == NULL) { success = 0; show_error(); } else if (action == ID_INSTALL_SERVICE) { GetModuleFileName(NULL, path, sizeof(path)); strncat(path, " ", sizeof(path)); strncat(path, service_magic_argument, sizeof(path)); hService = CreateService(hSCM, service_name, service_name, SERVICE_ALL_ACCESS, SERVICE_WIN32_OWN_PROCESS, SERVICE_AUTO_START, SERVICE_ERROR_NORMAL, path, NULL, NULL, NULL, NULL, NULL); if (hService) { ChangeServiceConfig2(hService, SERVICE_CONFIG_DESCRIPTION, &descr); } else { show_error(); } } else if (action == ID_REMOVE_SERVICE) { if ((hService = OpenService(hSCM, service_name, DELETE)) == NULL || !DeleteService(hService)) { show_error(); } } else if ((hService = OpenService(hSCM, service_name, SERVICE_QUERY_STATUS)) == NULL) { success = 0; } CloseServiceHandle(hService); CloseServiceHandle(hSCM); return success; } static LRESULT CALLBACK WindowProc(HWND hWnd, UINT msg, WPARAM wParam, LPARAM lParam) { static SERVICE_TABLE_ENTRY service_table[] = { {server_name, (LPSERVICE_MAIN_FUNCTION) ServiceMain}, {NULL, NULL} }; int service_installed; char buf[200], *service_argv[] = {__argv[0], NULL}; POINT pt; HMENU hMenu; switch (msg) { case WM_CREATE: if (__argv[1] != NULL && !strcmp(__argv[1], service_magic_argument)) { start_mongoose(1, service_argv); StartServiceCtrlDispatcher(service_table); exit(EXIT_SUCCESS); } else { start_mongoose(__argc, __argv); } break; case WM_COMMAND: switch (LOWORD(wParam)) { case ID_QUIT: mg_stop(ctx); Shell_NotifyIcon(NIM_DELETE, &TrayIcon); PostQuitMessage(0); break; case ID_EDIT_CONFIG: edit_config_file(); break; case ID_INSTALL_SERVICE: case ID_REMOVE_SERVICE: manage_service(LOWORD(wParam)); break; } break; case WM_USER: switch (lParam) { case WM_RBUTTONUP: case WM_LBUTTONUP: case WM_LBUTTONDBLCLK: hMenu = CreatePopupMenu(); AppendMenu(hMenu, MF_STRING | MF_GRAYED, ID_SEPARATOR, server_name); AppendMenu(hMenu, MF_SEPARATOR, ID_SEPARATOR, ""); service_installed = manage_service(0); snprintf(buf, sizeof(buf), "NT service: %s installed", service_installed ? "" : "not"); AppendMenu(hMenu, MF_STRING | MF_GRAYED, ID_SEPARATOR, buf); AppendMenu(hMenu, MF_STRING | (service_installed ? MF_GRAYED : 0), ID_INSTALL_SERVICE, "Install"); AppendMenu(hMenu, MF_STRING | (!service_installed ? MF_GRAYED : 0), ID_REMOVE_SERVICE, "Deinstall"); AppendMenu(hMenu, MF_SEPARATOR, ID_SEPARATOR, ""); AppendMenu(hMenu, MF_STRING, ID_EDIT_CONFIG, "Edit config file"); AppendMenu(hMenu, MF_STRING, ID_QUIT, "Exit"); GetCursorPos(&pt); SetForegroundWindow(hWnd); TrackPopupMenu(hMenu, 0, pt.x, pt.y, 0, hWnd, NULL); PostMessage(hWnd, WM_NULL, 0, 0); DestroyMenu(hMenu); break; } break; } return DefWindowProc(hWnd, msg, wParam, lParam); } int WINAPI WinMain(HINSTANCE hInst, HINSTANCE hPrev, LPSTR cmdline, int show) { WNDCLASS cls; HWND hWnd; MSG msg; init_server_name(); memset(&cls, 0, sizeof(cls)); cls.lpfnWndProc = (WNDPROC) WindowProc; cls.hIcon = LoadIcon(NULL, IDI_APPLICATION); cls.lpszClassName = server_name; RegisterClass(&cls); hWnd = CreateWindow(cls.lpszClassName, server_name, WS_OVERLAPPEDWINDOW, 0, 0, 0, 0, NULL, NULL, NULL, NULL); ShowWindow(hWnd, SW_HIDE); TrayIcon.cbSize = sizeof(TrayIcon); TrayIcon.uID = ID_TRAYICON; TrayIcon.uFlags = NIF_ICON | NIF_MESSAGE | NIF_TIP; TrayIcon.hIcon = LoadImage(GetModuleHandle(NULL), MAKEINTRESOURCE(ID_ICON), IMAGE_ICON, 16, 16, 0); TrayIcon.hWnd = hWnd; snprintf(TrayIcon.szTip, sizeof(TrayIcon.szTip), "%s", server_name); TrayIcon.uCallbackMessage = WM_USER; Shell_NotifyIcon(NIM_ADD, &TrayIcon); while (GetMessage(&msg, hWnd, 0, 0)) { TranslateMessage(&msg); DispatchMessage(&msg); } } #else int main(int argc, char *argv[]) { init_server_name(); start_mongoose(argc, argv); printf("%s started on port(s) %s with web root [%s]\n", server_name, mg_get_option(ctx, "listening_ports"), mg_get_option(ctx, "document_root")); while (exit_flag == 0) { sleep(1); } printf("Exiting on signal %d, waiting for all threads to finish...", exit_flag); fflush(stdout); mg_stop(ctx); printf("%s", " done.\n"); return EXIT_SUCCESS; } #endif /* _WIN32 */ MSVMpack1.2/mongoose/win32/0000755000175000017500000000000011557453204014520 5ustar lauerlauerMSVMpack1.2/mongoose/win32/res.rc0000644000175000017500000000004311557453204015634 0ustar lauerlauer200 ICON DISCARDABLE "systray.ico" MSVMpack1.2/mongoose/win32/ssl_cert.pem0000644000175000017500000000566011557453204017050 0ustar lauerlauer-----BEGIN RSA PRIVATE KEY----- MIIEogIBAAKCAQEAwONaLOP7EdegqjRuQKSDXzvHmFMZfBufjhELhNjo5KsL4ieH hMSGCcSV6y32hzhqR5lvTViaQez+xhc58NZRu+OUgEhodRBW/vAOjpz/xdMz5HaC EhP3E9W1pkitVseS8B5rrgJo1BfCGai1fPav1nutPq2Kj7vMy24+g460Lonf6ln1 di4aTIRtAqXtUU6RFpPJP35PkCXbTK65O8HJSxxt/XtfoezHCU5+UIwmZGYx46UB Wzg3IfK6bGPSiHU3pdiTol0uMPt/GUK+x4NyZJ4/ImsNAicRwMBdja4ywHKXJehH gXBthsVIHbL21x+4ibsg9eVM/XioTV6tW3IrdwIDAQABAoIBACFfdLutmkQFBcRN HAJNNHmmsyr0vcUOVnXTFyYeDXV67qxrYHQlOHe6LqIpKq1Mon7O2kYMnWvooFAP trOnsS6L+qaTYJdYg2TKjgo4ubw1hZXytyB/mdExuaMSkgMgtpia+tB5lD+V+LxN x1DesZ+veFMO3Zluyckswt4qM5yVa04YFrt31H0E1rJfIen61lidXIKYmHHWuRxK SadjFfbcqJ6P9ZF22BOkleg5Fm5NaxJmyQynOWaAkSZa5w1XySFfRjRfsbDr64G6 +LSG8YtRuvfxnvUNhynVPHcpE40eiPo6v8Ho6yZKXpV5klCKciodXAORsswSoGJa N3nnu/ECgYEA6Yb2rM3QUEPIALdL8f/OzZ1GBSdiQB2WSAxzl9pR/dLF2H+0pitS to0830mk92ppVmRVD3JGxYDRZQ56tlFXyGaCzJBMRIcsotAhBoNbjV0i9n5bLJYf BmjU9yvWcgsTt0tr3B0FrtYyp2tCvwHqlxvFpFdUCj2oRw2uGpkhmNkCgYEA03M6 WxFhsix3y6eVCVvShfbLBSOqp8l0qiTEty+dgVQcWN4CO/5eyaZXKxlCG9KMmKxy Yx+YgxZrDhfaZ0cxhHGPRKEAxM3IKwT2C8/wCaSiLWXZZpTifnSD99vtOt4wEfrG +AghNd5kamFiM9tU0AyvhJc2vdJFuXrfeC7ntM8CgYBGDA+t4cZcbRhu7ow/OKYF kulP3nJgHP/Y+LMrl3cEldZ2jEfZmCElVNQvfd2XwTl7injhOzvzPiKRF3jDez7D g8w0JAxceddvttJRK9GoY4l7OoeKpjUELSnEQkf+yUfOsTbXPXVY7jMfeNL6jE6b qN7t3qv8rmXtejMBE3G6cQKBgGR5W2BMiRSlxqKx1cKlrApV87BUe1HRCyuR3xuA d6Item7Lx1oEi7vb242yKdSYnpApWQ06xTh83Y/Ly87JaIEbiM0+h+P8OEIg0F1a iB+86AcUX1I8KseVy+Np0HbpfwP8GrFfA5DaRPK7pXMopEtby8cAJ1XZZaI1/ZvZ BebHAoGAcQU9WvCkT+nIp9FpXfBybYUsvgkaizMIqp66/l3GYgYAq8p1VLGvN4v5 ec0dW58SJrCpqsM3NP78DtEzQf9OOsk+FsjBFzDU2RkeUreyt2/nQBj/2mN/+hEy hYN0Zii2yTb63jGxKY6gH1R/r9dL8kXaJmcZrfSa3AgywnteJWg= -----END RSA PRIVATE KEY----- -----BEGIN CERTIFICATE----- MIIDBjCCAe4CCQCX05m0b053QzANBgkqhkiG9w0BAQQFADBFMQswCQYDVQQGEwJB VTETMBEGA1UECBMKU29tZS1TdGF0ZTEhMB8GA1UEChMYSW50ZXJuZXQgV2lkZ2l0 cyBQdHkgTHRkMB4XDTA4MTIwNzEwMjUyMloXDTE4MTIwNTEwMjUyMlowRTELMAkG A1UEBhMCQVUxEzARBgNVBAgTClNvbWUtU3RhdGUxITAfBgNVBAoTGEludGVybmV0 IFdpZGdpdHMgUHR5IEx0ZDCCASIwDQYJKoZIhvcNAQEBBQADggEPADCCAQoCggEB AMDjWizj+xHXoKo0bkCkg187x5hTGXwbn44RC4TY6OSrC+Inh4TEhgnElest9oc4 akeZb01YmkHs/sYXOfDWUbvjlIBIaHUQVv7wDo6c/8XTM+R2ghIT9xPVtaZIrVbH kvAea64CaNQXwhmotXz2r9Z7rT6tio+7zMtuPoOOtC6J3+pZ9XYuGkyEbQKl7VFO kRaTyT9+T5Al20yuuTvByUscbf17X6HsxwlOflCMJmRmMeOlAVs4NyHyumxj0oh1 N6XYk6JdLjD7fxlCvseDcmSePyJrDQInEcDAXY2uMsBylyXoR4FwbYbFSB2y9tcf uIm7IPXlTP14qE1erVtyK3cCAwEAATANBgkqhkiG9w0BAQQFAAOCAQEAW4yZdqpB oIdiuXRosr86Sg9FiMg/cn+2OwQ0QIaA8ZBwKsc+wIIHEgXCS8J6316BGQeUvMD+ plNe0r4GWzzmlDMdobeQ5arPRB89qd9skE6pAMdLg3FyyfEjz3A0VpskolW5VBMr P5R7uJ1FLgH12RyAjZCWYcCRqEMOffqvyMCH6oAjyDmQOA5IssRKX/HsHntSH/HW W7slTcP45ty1b44Nq22/ubYk0CJRQgqKOIQ3cLgPomN1jNFQbAbfVTaK1DpEysrQ 5V8a8gNW+3sVZmV6d1Mj3pN2Le62wUKuV2g6BNU7iiwcoY8HI68aRxz2hVMS+t5f SEGI4JSxV56lYg== -----END CERTIFICATE----- -----BEGIN DH PARAMETERS----- MEYCQQD+ef8hZ4XbdoyIpJyCTF2UrUEfX6mYDvxuS5O1UNYcslUqlj6JkA11e/yS 6DK8Z86W6mSj5CEk4IjbyEOECXH7AgEC -----END DH PARAMETERS----- MSVMpack1.2/mongoose/win32/systray.ico0000644000175000017500000000206611557453204016736 0ustar lauerlauer è&(( @€€€€€€€€€€ÀÀÀ€€€ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿþhttp_headers array, // and if the header is present in the array, returns its value. If it is // not present, NULL is returned. const char *mg_get_header(const struct mg_connection *, const char *name); // Get a value of particular form variable. // // Parameters: // data: pointer to form-uri-encoded buffer. This could be either POST data, // or request_info.query_string. // data_len: length of the encoded data. // var_name: variable name to decode from the buffer // buf: destination buffer for the decoded variable // buf_len: length of the destination buffer // // Return: // On success, length of the decoded variable. // On error, -1 (variable not found, or destination buffer is too small). // // Destination buffer is guaranteed to be '\0' - terminated. In case of // failure, dst[0] == '\0'. int mg_get_var(const char *data, size_t data_len, const char *var_name, char *buf, size_t buf_len); // Fetch value of certain cookie variable into the destination buffer. // // Destination buffer is guaranteed to be '\0' - terminated. In case of // failure, dst[0] == '\0'. Note that RFC allows many occurrences of the same // parameter. This function returns only first occurrence. // // Return: // On success, value length. // On error, -1 (either "Cookie:" header is not present at all, or the // requested parameter is not found, or destination buffer is too small // to hold the value). int mg_get_cookie(const struct mg_connection *, const char *cookie_name, char *buf, size_t buf_len); // Return Mongoose version. const char *mg_version(void); // MD5 hash given strings. // Buffer 'buf' must be 33 bytes long. Varargs is a NULL terminated list of // asciiz strings. When function returns, buf will contain human-readable // MD5 hash. Example: // char buf[33]; // mg_md5(buf, "aa", "bb", NULL); void mg_md5(char *buf, ...); #ifdef __cplusplus } #endif // __cplusplus #endif // MONGOOSE_HEADER_INCLUDED MSVMpack1.2/mongoose/bindings/0000755000175000017500000000000012104711130015333 5ustar lauerlauerMSVMpack1.2/mongoose/bindings/python/0000755000175000017500000000000011557453204016674 5ustar lauerlauerMSVMpack1.2/mongoose/bindings/python/example.py0000644000175000017500000000436611557453204020712 0ustar lauerlauer# This is Python example on how to use Mongoose embeddable web server, # http://code.google.com/p/mongoose # # Before using the mongoose module, make sure that Mongoose shared library is # built and present in the current (or system library) directory import mongoose import sys # Handle /show and /form URIs. def EventHandler(event, conn, info): if event == mongoose.HTTP_ERROR: conn.printf('%s', 'HTTP/1.0 200 OK\r\n') conn.printf('%s', 'Content-Type: text/plain\r\n\r\n') conn.printf('HTTP error: %d\n', info.status_code) return True elif event == mongoose.NEW_REQUEST and info.uri == '/show': conn.printf('%s', 'HTTP/1.0 200 OK\r\n') conn.printf('%s', 'Content-Type: text/plain\r\n\r\n') conn.printf('%s %s\n', info.request_method, info.uri) if info.request_method == 'POST': content_len = conn.get_header('Content-Length') post_data = conn.read(int(content_len)) my_var = conn.get_var(post_data, 'my_var') else: my_var = conn.get_var(info.query_string, 'my_var') conn.printf('my_var: %s\n', my_var or '') conn.printf('HEADERS: \n') for header in info.http_headers[:info.num_headers]: conn.printf(' %s: %s\n', header.name, header.value) return True elif event == mongoose.NEW_REQUEST and info.uri == '/form': conn.write('HTTP/1.0 200 OK\r\n' 'Content-Type: text/html\r\n\r\n' 'Use GET: link' '
' 'Use POST: type text and submit: ' '' '' '
') return True else: return False # Create mongoose object, and register '/foo' URI handler # List of options may be specified in the contructor server = mongoose.Mongoose(EventHandler, document_root='/tmp', listening_ports='8080') print ('Mongoose started on port %s, press enter to quit' % server.get_option('listening_ports')) sys.stdin.read(1) # Deleting server object stops all serving threads print 'Stopping server.' del server MSVMpack1.2/mongoose/bindings/python/mongoose.py0000644000175000017500000001262711557453204021104 0ustar lauerlauer# Copyright (c) 2004-2009 Sergey Lyubka # # 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. # # $Id: mongoose.py 471 2009-08-30 14:30:21Z valenok $ """ This module provides python binding for the Mongoose web server. There are two classes defined: Connection: - wraps all functions that accept struct mg_connection pointer as first argument. Mongoose: wraps all functions that accept struct mg_context pointer as first argument. Creating Mongoose object automatically starts server, deleting object automatically stops it. There is no need to call mg_start() or mg_stop(). """ import ctypes import os NEW_REQUEST = 0 HTTP_ERROR = 1 EVENT_LOG = 2 INIT_SSL = 3 class mg_header(ctypes.Structure): """A wrapper for struct mg_header.""" _fields_ = [ ('name', ctypes.c_char_p), ('value', ctypes.c_char_p), ] class mg_request_info(ctypes.Structure): """A wrapper for struct mg_request_info.""" _fields_ = [ ('user_data', ctypes.c_char_p), ('request_method', ctypes.c_char_p), ('uri', ctypes.c_char_p), ('http_version', ctypes.c_char_p), ('query_string', ctypes.c_char_p), ('remote_user', ctypes.c_char_p), ('log_message', ctypes.c_char_p), ('remote_ip', ctypes.c_long), ('remote_port', ctypes.c_int), ('status_code', ctypes.c_int), ('is_ssl', ctypes.c_int), ('num_headers', ctypes.c_int), ('http_headers', mg_header * 64), ] mg_callback_t = ctypes.CFUNCTYPE(ctypes.c_void_p, ctypes.c_int, ctypes.c_void_p, ctypes.POINTER(mg_request_info)) class Connection(object): """A wrapper class for all functions that take struct mg_connection * as the first argument.""" def __init__(self, mongoose, connection): self.m = mongoose self.conn = ctypes.c_void_p(connection) def get_header(self, name): val = self.m.dll.mg_get_header(self.conn, name) return ctypes.c_char_p(val).value def get_var(self, data, name): size = data and len(data) or 0 buf = ctypes.create_string_buffer(size) n = self.m.dll.mg_get_var(data, size, name, buf, size) return n >= 0 and buf or None def printf(self, fmt, *args): val = self.m.dll.mg_printf(self.conn, fmt, *args) return ctypes.c_int(val).value def write(self, data): val = self.m.dll.mg_write(self.conn, data, len(data)) return ctypes.c_int(val).value def read(self, size): buf = ctypes.create_string_buffer(size) n = self.m.dll.mg_read(self.conn, buf, size) return n <= 0 and None or buf[:n] class Mongoose(object): """A wrapper class for Mongoose shared library.""" def __init__(self, callback, **kwargs): dll_extension = os.name == 'nt' and 'dll' or 'so' self.dll = ctypes.CDLL('_mongoose.%s' % dll_extension) self.dll.mg_start.restype = ctypes.c_void_p self.dll.mg_modify_passwords_file.restype = ctypes.c_int self.dll.mg_read.restype = ctypes.c_int self.dll.mg_write.restype = ctypes.c_int self.dll.mg_printf.restype = ctypes.c_int self.dll.mg_get_header.restype = ctypes.c_char_p self.dll.mg_get_var.restype = ctypes.c_int self.dll.mg_get_cookie.restype = ctypes.c_int self.dll.mg_get_option.restype = ctypes.c_char_p if callback: # Create a closure that will be called by the shared library. def func(event, connection, request_info): # Wrap connection pointer into the connection # object and call Python callback conn = Connection(self, connection) return callback(event, conn, request_info.contents) and 1 or 0 # Convert the closure into C callable object self.callback = mg_callback_t(func) self.callback.restype = ctypes.c_char_p else: self.callback = ctypes.c_void_p(0) args = [y for x in kwargs.items() for y in x] + [None] options = (ctypes.c_char_p * len(args))(*args) ret = self.dll.mg_start(self.callback, 0, options) self.ctx = ctypes.c_void_p(ret) def __del__(self): """Destructor, stop Mongoose instance.""" self.dll.mg_stop(self.ctx) def get_option(self, name): return self.dll.mg_get_option(self.ctx, name) MSVMpack1.2/mongoose/bindings/csharp/0000755000175000017500000000000012104711130016613 5ustar lauerlauerMSVMpack1.2/mongoose/bindings/csharp/example.cs0000644000175000017500000000437411557453204020625 0ustar lauerlauer// This is C# example on how to use Mongoose embeddable web server, // http://code.google.com/p/mongoose // // Before using the mongoose module, make sure that Mongoose shared library is // built and present in the current (or system library) directory using System; using System.Runtime.InteropServices; public class Program { // This function is called when user types in his browser http://127.0.0.1:8080/foo static private void UriHandler(MongooseConnection conn, MongooseRequestInfo ri) { conn.write("HTTP/1.1 200 OK\r\n\r\n"); conn.write("Hello from C#!\n"); conn.write("Your user-agent is: " + conn.get_header("User-Agent") + "\n"); } static private void UriDumpInfo(MongooseConnection conn, MongooseRequestInfo ri) { conn.write("HTTP/1.1 200 OK\r\nContent-Type: text/html\r\n\r\n"); conn.write("Calling Info"); conn.write("

Request: " + ri.request_method + "

"); conn.write("

URI: " + ri.uri + "

"); conn.write("

Query: " + ri.query_string + "

"); if (ri.post_data_len > 0) conn.write("

Post(" + ri.post_data_len + ")[@" + ri.post_data + "]: '" + Marshal.PtrToStringAnsi(ri.post_data) + "'

"); conn.write("

User:" + ri.remote_user + "

"); conn.write("

IP: " + ri.remote_ip + "

"); conn.write("

HTTP: " + ri.http_version + "

"); conn.write("

Port: " + ri.remote_port + "

"); conn.write("

NUM Headers: " + ri.num_headers + "

"); for (int i = 0; i < Math.Min(64, ri.num_headers); i++) { conn.write("

" + i + ":" + Marshal.PtrToStringAnsi(ri.http_headers[i].name) + ":" + Marshal.PtrToStringAnsi(ri.http_headers[i].value) + "

"); } conn.write(""); } static void Main() { Mongoose web_server = new Mongoose(); // Set options and /foo URI handler web_server.set_option("ports", "8080"); web_server.set_option("root", "c:\\"); web_server.set_uri_callback("/foo", new MongooseCallback(UriHandler)); web_server.set_uri_callback("/dumpinfo", new MongooseCallback(UriDumpInfo)); // Serve requests until user presses "enter" on a keyboard Console.ReadLine(); } } MSVMpack1.2/mongoose/bindings/csharp/mongoose.cs0000644000175000017500000001351411557453204021014 0ustar lauerlauer// Copyright (c) 2004-2009 Sergey Lyubka // // 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. // // $Id: mongoose.cs 472 2009-08-30 22:40:29Z spsone1 $ using System; using System.Runtime.InteropServices; [StructLayout(LayoutKind.Sequential)] public struct MongooseHeader { public IntPtr name; // Using IntPtr here because if we use strings here, public IntPtr value; // it won't be properly marshalled. }; // This is "struct mg_request_info" from mongoose.h header file [StructLayout(LayoutKind.Sequential)] public struct MongooseRequestInfo { public string request_method; public string uri; public string http_version; public string query_string; public IntPtr post_data; public string remote_user; public int remote_ip; //int to match the 32bit declaration in c public int remote_port; public int post_data_len; public int status_code; public int num_headers; [MarshalAs(UnmanagedType.ByValArray,SizeConst=64)] public MongooseHeader[] http_headers; }; // This is a delegate for mg_callback_t from mongoose.h header file [UnmanagedFunctionPointer(CallingConvention.Cdecl)] public delegate void MongooseCallback2(IntPtr conn, ref MongooseRequestInfo ri, IntPtr user_data); // This is a delegate to be used by the application public delegate void MongooseCallback(MongooseConnection conn, MongooseRequestInfo ri); public class Mongoose { public string version; private IntPtr ctx; //These two events are here to store a ref to the callbacks while they are over in unmanaged code. private event MongooseCallback2 delegates2; private event MongooseCallback delegates1; [DllImport("_mongoose",CallingConvention=CallingConvention.Cdecl)] private static extern IntPtr mg_start(); [DllImport("_mongoose",CallingConvention=CallingConvention.Cdecl)] private static extern void mg_stop(IntPtr ctx); [DllImport("_mongoose",CallingConvention=CallingConvention.Cdecl)] private static extern string mg_version(); [DllImport("_mongoose",CallingConvention=CallingConvention.Cdecl)] private static extern int mg_set_option(IntPtr ctx, string name, string value); [DllImport("_mongoose",CallingConvention=CallingConvention.Cdecl)] private static extern string mg_get_option(IntPtr ctx, string name); [DllImport("_mongoose",CallingConvention=CallingConvention.Cdecl)] private static extern void mg_set_uri_callback(IntPtr ctx, string uri_regex, MulticastDelegate func, IntPtr data); [DllImport("_mongoose",CallingConvention=CallingConvention.Cdecl)] private static extern void mg_set_log_callback(IntPtr ctx, MulticastDelegate func); public Mongoose() { ctx = mg_start(); version = mg_version(); } ~Mongoose() { mg_stop(this.ctx); this.ctx = IntPtr.Zero; } public int set_option(string option_name, string option_value) { return mg_set_option(this.ctx, option_name, option_value); } public string get_option(string option_name) { return mg_get_option(this.ctx, option_name); } public void set_uri_callback(string uri_regex, MongooseCallback func) { // Build a closure around user function. Initialize connection object there which wraps // mg_write() and other useful methods, and then call user specified handler. MongooseCallback2 callback = delegate(IntPtr conn, ref MongooseRequestInfo ri, IntPtr user_data) { MongooseConnection connection = new MongooseConnection(conn, this); func(connection, ri); }; // store a reference to the callback so it won't be GC'ed while its over in unmanged code delegates2 += callback; mg_set_uri_callback(this.ctx, uri_regex, callback, IntPtr.Zero); } public void set_log_callback(MongooseCallback func) { delegates1 += func; mg_set_log_callback(this.ctx, func); } } public class MongooseConnection { public Mongoose mongoose; private IntPtr conn; [DllImport("_mongoose",CallingConvention=CallingConvention.Cdecl)] private static extern string mg_get_header(IntPtr ctx, string name); [DllImport("_mongoose",CallingConvention=CallingConvention.Cdecl)] private static extern string mg_get_var(IntPtr ctx, string name); [DllImport("_mongoose",CallingConvention=CallingConvention.Cdecl)] private static extern void mg_free(IntPtr ptr); [DllImport("_mongoose",CallingConvention=CallingConvention.Cdecl)] public static extern int mg_write(IntPtr conn, string data, int length); public MongooseConnection(IntPtr conn_, Mongoose mongoose_) { mongoose = mongoose_; conn = conn_; } public string get_header(string header_name) { return mg_get_header(this.conn, header_name); } public string get_var(string header_name) { string s = mg_get_var(this.conn, header_name); string copy = "" + s; mg_free(Marshal.StringToHGlobalAnsi(s)); return copy; } public int write(string data) { return mg_write(this.conn, data, data.Length); } } MSVMpack1.2/mongoose/mongoose.c0000644000175000017500000037731211557453204015565 0ustar lauerlauer// Copyright (c) 2004-2010 Sergey Lyubka // // 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. #if defined(_WIN32) #define _CRT_SECURE_NO_WARNINGS // Disable deprecation warning in VS2005 #else #define _XOPEN_SOURCE 600 // For flockfile() on Linux #define _LARGEFILE_SOURCE // Enable 64-bit file offsets #define __STDC_FORMAT_MACROS // wants this for C++ #endif #if defined(__SYMBIAN32__) #define NO_SSL // SSL is not supported #define NO_CGI // CGI is not supported #define PATH_MAX FILENAME_MAX #endif // __SYMBIAN32__ #ifndef _WIN32_WCE // Some ANSI #includes are not available on Windows CE #include #include #include #include #include #endif // !_WIN32_WCE #include #include #include #include #include #include #include #include #include #if defined(_WIN32) && !defined(__SYMBIAN32__) // Windows specific #define _WIN32_WINNT 0x0400 // To make it link in VS2005 #include #ifndef PATH_MAX #define PATH_MAX MAX_PATH #endif #ifndef _WIN32_WCE #include #include #include #else // _WIN32_WCE #include #define NO_CGI // WinCE has no pipes typedef long off_t; #define BUFSIZ 4096 #define errno GetLastError() #define strerror(x) _ultoa(x, (char *) _alloca(sizeof(x) *3 ), 10) #endif // _WIN32_WCE #define MAKEUQUAD(lo, hi) ((uint64_t)(((uint32_t)(lo)) | \ ((uint64_t)((uint32_t)(hi))) << 32)) #define RATE_DIFF 10000000 // 100 nsecs #define EPOCH_DIFF MAKEUQUAD(0xd53e8000, 0x019db1de) #define SYS2UNIX_TIME(lo, hi) \ (time_t) ((MAKEUQUAD((lo), (hi)) - EPOCH_DIFF) / RATE_DIFF) // Visual Studio 6 does not know __func__ or __FUNCTION__ // The rest of MS compilers use __FUNCTION__, not C99 __func__ // Also use _strtoui64 on modern M$ compilers #if defined(_MSC_VER) && _MSC_VER < 1300 #define STRX(x) #x #define STR(x) STRX(x) #define __func__ "line " STR(__LINE__) #define strtoull(x, y, z) strtoul(x, y, z) #define strtoll(x, y, z) strtol(x, y, z) #else #define __func__ __FUNCTION__ #define strtoull(x, y, z) _strtoui64(x, y, z) #define strtoll(x, y, z) _strtoi64(x, y, z) #endif // _MSC_VER #define ERRNO GetLastError() #define NO_SOCKLEN_T #define SSL_LIB "ssleay32.dll" #define CRYPTO_LIB "libeay32.dll" #define DIRSEP '\\' #define IS_DIRSEP_CHAR(c) ((c) == '/' || (c) == '\\') #define O_NONBLOCK 0 #if !defined(EWOULDBLOCK) #define EWOULDBLOCK WSAEWOULDBLOCK #endif // !EWOULDBLOCK #define _POSIX_ #define INT64_FMT "I64d" #define WINCDECL __cdecl #define SHUT_WR 1 #define snprintf _snprintf #define vsnprintf _vsnprintf #define sleep(x) Sleep((x) * 1000) #define pipe(x) _pipe(x, BUFSIZ, _O_BINARY) #define popen(x, y) _popen(x, y) #define pclose(x) _pclose(x) #define close(x) _close(x) #define dlsym(x,y) GetProcAddress((HINSTANCE) (x), (y)) #define RTLD_LAZY 0 #define fseeko(x, y, z) fseek((x), (y), (z)) #define fdopen(x, y) _fdopen((x), (y)) #define write(x, y, z) _write((x), (y), (unsigned) z) #define read(x, y, z) _read((x), (y), (unsigned) z) #define flockfile(x) (void) 0 #define funlockfile(x) (void) 0 #if !defined(fileno) #define fileno(x) _fileno(x) #endif // !fileno MINGW #defines fileno typedef HANDLE pthread_mutex_t; typedef struct {HANDLE signal, broadcast;} pthread_cond_t; typedef DWORD pthread_t; #define pid_t HANDLE // MINGW typedefs pid_t to int. Using #define here. struct timespec { long tv_nsec; long tv_sec; }; static int pthread_mutex_lock(pthread_mutex_t *); static int pthread_mutex_unlock(pthread_mutex_t *); static FILE *mg_fopen(const char *path, const char *mode); #if defined(HAVE_STDINT) #include #else typedef unsigned int uint32_t; typedef unsigned short uint16_t; typedef unsigned __int64 uint64_t; typedef __int64 int64_t; #define INT64_MAX 9223372036854775807 #endif // HAVE_STDINT // POSIX dirent interface struct dirent { char d_name[PATH_MAX]; }; typedef struct DIR { HANDLE handle; WIN32_FIND_DATAW info; struct dirent result; } DIR; #else // UNIX specific #include #include #include #include #include #include #include #include #include #include #include #include #if !defined(NO_SSL_DL) && !defined(NO_SSL) #include #endif #include #if defined(__MACH__) #define SSL_LIB "libssl.dylib" #define CRYPTO_LIB "libcrypto.dylib" #else #if !defined(SSL_LIB) #define SSL_LIB "libssl.so" #endif #if !defined(CRYPTO_LIB) #define CRYPTO_LIB "libcrypto.so" #endif #endif #define DIRSEP '/' #define IS_DIRSEP_CHAR(c) ((c) == '/') #ifndef O_BINARY #define O_BINARY 0 #endif // O_BINARY #define closesocket(a) close(a) #define mg_fopen(x, y) fopen(x, y) #define mg_mkdir(x, y) mkdir(x, y) #define mg_remove(x) remove(x) #define mg_rename(x, y) rename(x, y) #define ERRNO errno #define INVALID_SOCKET (-1) #define INT64_FMT PRId64 typedef int SOCKET; #define WINCDECL #endif // End of Windows and UNIX specific includes #include "mongoose.h" #define MONGOOSE_VERSION "3.0" #define PASSWORDS_FILE_NAME ".htpasswd" #define CGI_ENVIRONMENT_SIZE 4096 #define MAX_CGI_ENVIR_VARS 64 #define ARRAY_SIZE(array) (sizeof(array) / sizeof(array[0])) #if defined(DEBUG) #define DEBUG_TRACE(x) do { \ flockfile(stdout); \ printf("*** %lu.%p.%s.%d: ", \ (unsigned long) time(NULL), (void *) pthread_self(), \ __func__, __LINE__); \ printf x; \ putchar('\n'); \ fflush(stdout); \ funlockfile(stdout); \ } while (0) #else #define DEBUG_TRACE(x) #endif // DEBUG // Darwin prior to 7.0 and Win32 do not have socklen_t #ifdef NO_SOCKLEN_T typedef int socklen_t; #endif // NO_SOCKLEN_T typedef void * (*mg_thread_func_t)(void *); static const char *http_500_error = "Internal Server Error"; // Snatched from OpenSSL includes. I put the prototypes here to be independent // from the OpenSSL source installation. Having this, mongoose + SSL can be // built on any system with binary SSL libraries installed. typedef struct ssl_st SSL; typedef struct ssl_method_st SSL_METHOD; typedef struct ssl_ctx_st SSL_CTX; #define SSL_ERROR_WANT_READ 2 #define SSL_ERROR_WANT_WRITE 3 #define SSL_FILETYPE_PEM 1 #define CRYPTO_LOCK 1 #if defined(NO_SSL_DL) extern void SSL_free(SSL *); extern int SSL_accept(SSL *); extern int SSL_connect(SSL *); extern int SSL_read(SSL *, void *, int); extern int SSL_write(SSL *, const void *, int); extern int SSL_get_error(const SSL *, int); extern int SSL_set_fd(SSL *, int); extern SSL *SSL_new(SSL_CTX *); extern SSL_CTX *SSL_CTX_new(SSL_METHOD *); extern SSL_METHOD *SSLv23_server_method(void); extern int SSL_library_init(void); extern void SSL_load_error_strings(void); extern int SSL_CTX_use_PrivateKey_file(SSL_CTX *, const char *, int); extern int SSL_CTX_use_certificate_file(SSL_CTX *, const char *, int); extern int SSL_CTX_use_certificate_chain_file(SSL_CTX *, const char *); extern void SSL_CTX_set_default_passwd_cb(SSL_CTX *, mg_callback_t); extern void SSL_CTX_free(SSL_CTX *); extern unsigned long ERR_get_error(void); extern char *ERR_error_string(unsigned long, char *); extern int CRYPTO_num_locks(void); extern void CRYPTO_set_locking_callback(void (*)(int, int, const char *, int)); extern void CRYPTO_set_id_callback(unsigned long (*)(void)); #else // Dynamically loaded SSL functionality struct ssl_func { const char *name; // SSL function name void (*ptr)(void); // Function pointer }; #define SSL_free (* (void (*)(SSL *)) ssl_sw[0].ptr) #define SSL_accept (* (int (*)(SSL *)) ssl_sw[1].ptr) #define SSL_connect (* (int (*)(SSL *)) ssl_sw[2].ptr) #define SSL_read (* (int (*)(SSL *, void *, int)) ssl_sw[3].ptr) #define SSL_write (* (int (*)(SSL *, const void *,int)) ssl_sw[4].ptr) #define SSL_get_error (* (int (*)(SSL *, int)) ssl_sw[5].ptr) #define SSL_set_fd (* (int (*)(SSL *, SOCKET)) ssl_sw[6].ptr) #define SSL_new (* (SSL * (*)(SSL_CTX *)) ssl_sw[7].ptr) #define SSL_CTX_new (* (SSL_CTX * (*)(SSL_METHOD *)) ssl_sw[8].ptr) #define SSLv23_server_method (* (SSL_METHOD * (*)(void)) ssl_sw[9].ptr) #define SSL_library_init (* (int (*)(void)) ssl_sw[10].ptr) #define SSL_CTX_use_PrivateKey_file (* (int (*)(SSL_CTX *, \ const char *, int)) ssl_sw[11].ptr) #define SSL_CTX_use_certificate_file (* (int (*)(SSL_CTX *, \ const char *, int)) ssl_sw[12].ptr) #define SSL_CTX_set_default_passwd_cb \ (* (void (*)(SSL_CTX *, mg_callback_t)) ssl_sw[13].ptr) #define SSL_CTX_free (* (void (*)(SSL_CTX *)) ssl_sw[14].ptr) #define SSL_load_error_strings (* (void (*)(void)) ssl_sw[15].ptr) #define SSL_CTX_use_certificate_chain_file \ (* (int (*)(SSL_CTX *, const char *)) ssl_sw[16].ptr) #define CRYPTO_num_locks (* (int (*)(void)) crypto_sw[0].ptr) #define CRYPTO_set_locking_callback \ (* (void (*)(void (*)(int, int, const char *, int))) crypto_sw[1].ptr) #define CRYPTO_set_id_callback \ (* (void (*)(unsigned long (*)(void))) crypto_sw[2].ptr) #define ERR_get_error (* (unsigned long (*)(void)) crypto_sw[3].ptr) #define ERR_error_string (* (char * (*)(unsigned long,char *)) crypto_sw[4].ptr) // set_ssl_option() function updates this array. // It loads SSL library dynamically and changes NULLs to the actual addresses // of respective functions. The macros above (like SSL_connect()) are really // just calling these functions indirectly via the pointer. static struct ssl_func ssl_sw[] = { {"SSL_free", NULL}, {"SSL_accept", NULL}, {"SSL_connect", NULL}, {"SSL_read", NULL}, {"SSL_write", NULL}, {"SSL_get_error", NULL}, {"SSL_set_fd", NULL}, {"SSL_new", NULL}, {"SSL_CTX_new", NULL}, {"SSLv23_server_method", NULL}, {"SSL_library_init", NULL}, {"SSL_CTX_use_PrivateKey_file", NULL}, {"SSL_CTX_use_certificate_file",NULL}, {"SSL_CTX_set_default_passwd_cb",NULL}, {"SSL_CTX_free", NULL}, {"SSL_load_error_strings", NULL}, {"SSL_CTX_use_certificate_chain_file", NULL}, {NULL, NULL} }; // Similar array as ssl_sw. These functions could be located in different lib. static struct ssl_func crypto_sw[] = { {"CRYPTO_num_locks", NULL}, {"CRYPTO_set_locking_callback", NULL}, {"CRYPTO_set_id_callback", NULL}, {"ERR_get_error", NULL}, {"ERR_error_string", NULL}, {NULL, NULL} }; #endif // NO_SSL_DL static const char *month_names[] = { "Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec" }; // Unified socket address. For IPv6 support, add IPv6 address structure // in the union u. struct usa { socklen_t len; union { struct sockaddr sa; struct sockaddr_in sin; } u; }; // Describes a string (chunk of memory). struct vec { const char *ptr; size_t len; }; // Structure used by mg_stat() function. Uses 64 bit file length. struct mgstat { int is_directory; // Directory marker int64_t size; // File size time_t mtime; // Modification time }; // Describes listening socket, or socket which was accept()-ed by the master // thread and queued for future handling by the worker thread. struct socket { struct socket *next; // Linkage SOCKET sock; // Listening socket struct usa lsa; // Local socket address struct usa rsa; // Remote socket address int is_ssl; // Is socket SSL-ed int is_proxy; }; enum { CGI_EXTENSIONS, CGI_ENVIRONMENT, PUT_DELETE_PASSWORDS_FILE, CGI_INTERPRETER, PROTECT_URI, AUTHENTICATION_DOMAIN, SSI_EXTENSIONS, ACCESS_LOG_FILE, SSL_CHAIN_FILE, ENABLE_DIRECTORY_LISTING, ERROR_LOG_FILE, GLOBAL_PASSWORDS_FILE, INDEX_FILES, ENABLE_KEEP_ALIVE, ACCESS_CONTROL_LIST, MAX_REQUEST_SIZE, EXTRA_MIME_TYPES, LISTENING_PORTS, DOCUMENT_ROOT, SSL_CERTIFICATE, NUM_THREADS, RUN_AS_USER, NUM_OPTIONS }; static const char *config_options[] = { "C", "cgi_extensions", ".cgi,.pl,.php", "E", "cgi_environment", NULL, "G", "put_delete_passwords_file", NULL, "I", "cgi_interpreter", NULL, "P", "protect_uri", NULL, "R", "authentication_domain", "mydomain.com", "S", "ssi_extensions", ".shtml,.shtm", "a", "access_log_file", NULL, "c", "ssl_chain_file", NULL, "d", "enable_directory_listing", "yes", "e", "error_log_file", NULL, "g", "global_passwords_file", NULL, "i", "index_files", "index.html,index.htm,index.cgi", "k", "enable_keep_alive", "no", "l", "access_control_list", NULL, "M", "max_request_size", "16384", "m", "extra_mime_types", NULL, "p", "listening_ports", "8080", "r", "document_root", ".", "s", "ssl_certificate", NULL, "t", "num_threads", "10", "u", "run_as_user", NULL, NULL }; #define ENTRIES_PER_CONFIG_OPTION 3 struct mg_context { volatile int stop_flag; // Should we stop event loop SSL_CTX *ssl_ctx; // SSL context char *config[NUM_OPTIONS]; // Mongoose configuration parameters mg_callback_t user_callback; // User-defined callback function void *user_data; // User-defined data struct socket *listening_sockets; volatile int num_threads; // Number of threads pthread_mutex_t mutex; // Protects (max|num)_threads pthread_cond_t cond; // Condvar for tracking workers terminations struct socket queue[20]; // Accepted sockets volatile int sq_head; // Head of the socket queue volatile int sq_tail; // Tail of the socket queue pthread_cond_t sq_full; // Singaled when socket is produced pthread_cond_t sq_empty; // Signaled when socket is consumed }; struct mg_connection { struct mg_connection *peer; // Remote target in proxy mode struct mg_request_info request_info; struct mg_context *ctx; SSL *ssl; // SSL descriptor struct socket client; // Connected client time_t birth_time; // Time connection was accepted int64_t num_bytes_sent; // Total bytes sent to client int64_t content_len; // Content-Length header value int64_t consumed_content; // How many bytes of content is already read char *buf; // Buffer for received data int buf_size; // Buffer size int request_len; // Size of the request + headers in a buffer int data_len; // Total size of data in a buffer }; const char **mg_get_valid_option_names(void) { return config_options; } static void *call_user(struct mg_connection *conn, enum mg_event event) { conn->request_info.user_data = conn->ctx->user_data; return conn->ctx->user_callback == NULL ? NULL : conn->ctx->user_callback(event, conn, &conn->request_info); } static int get_option_index(const char *name) { int i; for (i = 0; config_options[i] != NULL; i += ENTRIES_PER_CONFIG_OPTION) { if (strcmp(config_options[i], name) == 0 || strcmp(config_options[i + 1], name) == 0) { return i / ENTRIES_PER_CONFIG_OPTION; } } return -1; } const char *mg_get_option(const struct mg_context *ctx, const char *name) { int i; if ((i = get_option_index(name)) == -1) { return NULL; } else if (ctx->config[i] == NULL) { return ""; } else { return ctx->config[i]; } } // Print error message to the opened error log stream. static void cry(struct mg_connection *conn, const char *fmt, ...) { char buf[BUFSIZ]; va_list ap; FILE *fp; time_t timestamp; va_start(ap, fmt); (void) vsnprintf(buf, sizeof(buf), fmt, ap); va_end(ap); // Do not lock when getting the callback value, here and below. // I suppose this is fine, since function cannot disappear in the // same way string option can. conn->request_info.log_message = buf; if (call_user(conn, MG_EVENT_LOG) == NULL) { fp = conn->ctx->config[ERROR_LOG_FILE] == NULL ? NULL : mg_fopen(conn->ctx->config[ERROR_LOG_FILE], "a+"); if (fp != NULL) { flockfile(fp); timestamp = time(NULL); (void) fprintf(fp, "[%010lu] [error] [client %s] ", (unsigned long) timestamp, inet_ntoa(conn->client.rsa.u.sin.sin_addr)); if (conn->request_info.request_method != NULL) { (void) fprintf(fp, "%s %s: ", conn->request_info.request_method, conn->request_info.uri); } (void) fprintf(fp, "%s", buf); fputc('\n', fp); funlockfile(fp); if (fp != stderr) { fclose(fp); } } } conn->request_info.log_message = NULL; } // Return OpenSSL error message static const char *ssl_error(void) { unsigned long err; err = ERR_get_error(); return err == 0 ? "" : ERR_error_string(err, NULL); } // Return fake connection structure. Used for logging, if connection // is not applicable at the moment of logging. static struct mg_connection *fc(struct mg_context *ctx) { static struct mg_connection fake_connection; fake_connection.ctx = ctx; return &fake_connection; } const char *mg_version(void) { return MONGOOSE_VERSION; } static void mg_strlcpy(register char *dst, register const char *src, size_t n) { for (; *src != '\0' && n > 1; n--) { *dst++ = *src++; } *dst = '\0'; } static int lowercase(const char *s) { return tolower(* (const unsigned char *) s); } static int mg_strncasecmp(const char *s1, const char *s2, size_t len) { int diff = 0; if (len > 0) do { diff = lowercase(s1++) - lowercase(s2++); } while (diff == 0 && s1[-1] != '\0' && --len > 0); return diff; } static int mg_strcasecmp(const char *s1, const char *s2) { int diff; do { diff = lowercase(s1++) - lowercase(s2++); } while (diff == 0 && s1[-1] != '\0'); return diff; } static char * mg_strndup(const char *ptr, size_t len) { char *p; if ((p = (char *) malloc(len + 1)) != NULL) { mg_strlcpy(p, ptr, len + 1); } return p; } static char * mg_strdup(const char *str) { return mg_strndup(str, strlen(str)); } // Like snprintf(), but never returns negative value, or the value // that is larger than a supplied buffer. // Thanks to Adam Zeldis to pointing snprintf()-caused vulnerability // in his audit report. static int mg_vsnprintf(struct mg_connection *conn, char *buf, size_t buflen, const char *fmt, va_list ap) { int n; if (buflen == 0) return 0; n = vsnprintf(buf, buflen, fmt, ap); if (n < 0) { cry(conn, "vsnprintf error"); n = 0; } else if (n >= (int) buflen) { cry(conn, "truncating vsnprintf buffer: [%.*s]", n > 200 ? 200 : n, buf); n = (int) buflen - 1; } buf[n] = '\0'; return n; } static int mg_snprintf(struct mg_connection *conn, char *buf, size_t buflen, const char *fmt, ...) { va_list ap; int n; va_start(ap, fmt); n = mg_vsnprintf(conn, buf, buflen, fmt, ap); va_end(ap); return n; } // Skip the characters until one of the delimiters characters found. // 0-terminate resulting word. Skip the delimiter and following whitespaces if any. // Advance pointer to buffer to the next word. Return found 0-terminated word. // Delimiters can be quoted with quotechar. static char *skip_quoted(char **buf, const char *delimiters, const char *whitespace, char quotechar) { char *p, *begin_word, *end_word, *end_whitespace; begin_word = *buf; end_word = begin_word + strcspn(begin_word, delimiters); /* Check for quotechar */ if (end_word > begin_word) { p = end_word - 1; while (*p == quotechar) { /* If there is anything beyond end_word, copy it */ if (*end_word == '\0') { *p = '\0'; break; } else { size_t end_off = strcspn(end_word + 1, delimiters); memmove (p, end_word, end_off + 1); p += end_off; /* p must correspond to end_word - 1 */ end_word += end_off + 1; } } for (p++; p < end_word; p++) { *p = '\0'; } } if (*end_word == '\0') { *buf = end_word; } else { end_whitespace = end_word + 1 + strspn(end_word + 1, whitespace); for (p = end_word; p < end_whitespace; p++) { *p = '\0'; } *buf = end_whitespace; } return begin_word; } // Simplified version of skip_quoted without quote char // and whitespace == delimiters static char *skip(char **buf, const char *delimiters) { return skip_quoted(buf, delimiters, delimiters, 0); } // Return HTTP header value, or NULL if not found. static const char *get_header(const struct mg_request_info *ri, const char *name) { int i; for (i = 0; i < ri->num_headers; i++) if (!mg_strcasecmp(name, ri->http_headers[i].name)) return ri->http_headers[i].value; return NULL; } const char *mg_get_header(const struct mg_connection *conn, const char *name) { return get_header(&conn->request_info, name); } // A helper function for traversing comma separated list of values. // It returns a list pointer shifted to the next value, of NULL if the end // of the list found. // Value is stored in val vector. If value has form "x=y", then eq_val // vector is initialized to point to the "y" part, and val vector length // is adjusted to point only to "x". static const char *next_option(const char *list, struct vec *val, struct vec *eq_val) { if (list == NULL || *list == '\0') { /* End of the list */ list = NULL; } else { val->ptr = list; if ((list = strchr(val->ptr, ',')) != NULL) { /* Comma found. Store length and shift the list ptr */ val->len = list - val->ptr; list++; } else { /* This value is the last one */ list = val->ptr + strlen(val->ptr); val->len = list - val->ptr; } if (eq_val != NULL) { /* * Value has form "x=y", adjust pointers and lengths * so that val points to "x", and eq_val points to "y". */ eq_val->len = 0; eq_val->ptr = (const char *) memchr(val->ptr, '=', val->len); if (eq_val->ptr != NULL) { eq_val->ptr++; /* Skip over '=' character */ eq_val->len = val->ptr + val->len - eq_val->ptr; val->len = (eq_val->ptr - val->ptr) - 1; } } } return list; } #if !defined(NO_CGI) static int match_extension(const char *path, const char *ext_list) { struct vec ext_vec; size_t path_len; path_len = strlen(path); while ((ext_list = next_option(ext_list, &ext_vec, NULL)) != NULL) if (ext_vec.len < path_len && mg_strncasecmp(path + path_len - ext_vec.len, ext_vec.ptr, ext_vec.len) == 0) return 1; return 0; } #endif // !NO_CGI // HTTP 1.1 assumes keep alive if "Connection:" header is not set // This function must tolerate situations when connection info is not // set up, for example if request parsing failed. static int should_keep_alive(const struct mg_connection *conn) { const char *http_version = conn->request_info.http_version; const char *header = mg_get_header(conn, "Connection"); return (header == NULL && http_version && !strcmp(http_version, "1.1")) || (header != NULL && !mg_strcasecmp(header, "keep-alive")); } static const char *suggest_connection_header(const struct mg_connection *conn) { return should_keep_alive(conn) ? "keep-alive" : "close"; } static void send_http_error(struct mg_connection *conn, int status, const char *reason, const char *fmt, ...) { char buf[BUFSIZ]; va_list ap; int len; conn->request_info.status_code = status; if (call_user(conn, MG_HTTP_ERROR) == NULL) { buf[0] = '\0'; len = 0; /* Errors 1xx, 204 and 304 MUST NOT send a body */ if (status > 199 && status != 204 && status != 304) { len = mg_snprintf(conn, buf, sizeof(buf), "Error %d: %s", status, reason); cry(conn, "%s", buf); buf[len++] = '\n'; va_start(ap, fmt); len += mg_vsnprintf(conn, buf + len, sizeof(buf) - len, fmt, ap); va_end(ap); } DEBUG_TRACE(("[%s]", buf)); mg_printf(conn, "HTTP/1.1 %d %s\r\n" "Content-Type: text/plain\r\n" "Content-Length: %d\r\n" "Connection: %s\r\n\r\n", status, reason, len, suggest_connection_header(conn)); conn->num_bytes_sent += mg_printf(conn, "%s", buf); } } #if defined(_WIN32) && !defined(__SYMBIAN32__) static int pthread_mutex_init(pthread_mutex_t *mutex, void *unused) { unused = NULL; *mutex = CreateMutex(NULL, FALSE, NULL); return *mutex == NULL ? -1 : 0; } static int pthread_mutex_destroy(pthread_mutex_t *mutex) { return CloseHandle(*mutex) == 0 ? -1 : 0; } static int pthread_mutex_lock(pthread_mutex_t *mutex) { return WaitForSingleObject(*mutex, INFINITE) == WAIT_OBJECT_0? 0 : -1; } static int pthread_mutex_unlock(pthread_mutex_t *mutex) { return ReleaseMutex(*mutex) == 0 ? -1 : 0; } static int pthread_cond_init(pthread_cond_t *cv, const void *unused) { unused = NULL; cv->signal = CreateEvent(NULL, FALSE, FALSE, NULL); cv->broadcast = CreateEvent(NULL, TRUE, FALSE, NULL); return cv->signal != NULL && cv->broadcast != NULL ? 0 : -1; } static int pthread_cond_wait(pthread_cond_t *cv, pthread_mutex_t *mutex) { HANDLE handles[] = {cv->signal, cv->broadcast}; ReleaseMutex(*mutex); WaitForMultipleObjects(2, handles, FALSE, INFINITE); return WaitForSingleObject(*mutex, INFINITE) == WAIT_OBJECT_0? 0 : -1; } static int pthread_cond_signal(pthread_cond_t *cv) { return SetEvent(cv->signal) == 0 ? -1 : 0; } static int pthread_cond_broadcast(pthread_cond_t *cv) { // Implementation with PulseEvent() has race condition, see // http://www.cs.wustl.edu/~schmidt/win32-cv-1.html return PulseEvent(cv->broadcast) == 0 ? -1 : 0; } static int pthread_cond_destroy(pthread_cond_t *cv) { return CloseHandle(cv->signal) && CloseHandle(cv->broadcast) ? 0 : -1; } static pthread_t pthread_self(void) { return GetCurrentThreadId(); } // For Windows, change all slashes to backslashes in path names. static void change_slashes_to_backslashes(char *path) { int i; for (i = 0; path[i] != '\0'; i++) { if (path[i] == '/') path[i] = '\\'; // i > 0 check is to preserve UNC paths, like \\server\file.txt if (path[i] == '\\' && i > 0) while (path[i + 1] == '\\' || path[i + 1] == '/') (void) memmove(path + i + 1, path + i + 2, strlen(path + i + 1)); } } // Encode 'path' which is assumed UTF-8 string, into UNICODE string. // wbuf and wbuf_len is a target buffer and its length. static void to_unicode(const char *path, wchar_t *wbuf, size_t wbuf_len) { char buf[PATH_MAX], *p; mg_strlcpy(buf, path, sizeof(buf)); change_slashes_to_backslashes(buf); // Point p to the end of the file name p = buf + strlen(buf) - 1; // Trim trailing backslash character while (p > buf && *p == '\\' && p[-1] != ':') { *p-- = '\0'; } // Protect from CGI code disclosure. // This is very nasty hole. Windows happily opens files with // some garbage in the end of file name. So fopen("a.cgi ", "r") // actually opens "a.cgi", and does not return an error! if (*p == 0x20 || // No space at the end (*p == 0x2e && p > buf) || // No '.' but allow '.' as full path *p == 0x2b || // No '+' (*p & ~0x7f)) { // And generally no non-ascii chars (void) fprintf(stderr, "Rejecting suspicious path: [%s]", buf); buf[0] = '\0'; } (void) MultiByteToWideChar(CP_UTF8, 0, buf, -1, wbuf, (int) wbuf_len); } #if defined(_WIN32_WCE) static time_t time(time_t *ptime) { time_t t; SYSTEMTIME st; FILETIME ft; GetSystemTime(&st); SystemTimeToFileTime(&st, &ft); t = SYS2UNIX_TIME(ft.dwLowDateTime, ft.dwHighDateTime); if (ptime != NULL) { *ptime = t; } return t; } static time_t mktime(struct tm *ptm) { SYSTEMTIME st; FILETIME ft, lft; st.wYear = ptm->tm_year + 1900; st.wMonth = ptm->tm_mon + 1; st.wDay = ptm->tm_mday; st.wHour = ptm->tm_hour; st.wMinute = ptm->tm_min; st.wSecond = ptm->tm_sec; st.wMilliseconds = 0; SystemTimeToFileTime(&st, &ft); LocalFileTimeToFileTime(&ft, &lft); return (time_t) ((MAKEUQUAD(lft.dwLowDateTime, lft.dwHighDateTime) - EPOCH_DIFF) / RATE_DIFF); } static struct tm *localtime(const time_t *ptime, struct tm *ptm) { int64_t t = ((int64_t) *ptime) * RATE_DIFF + EPOCH_DIFF; FILETIME ft, lft; SYSTEMTIME st; TIME_ZONE_INFORMATION tzinfo; if (ptm == NULL) { return NULL; } * (int64_t *) &ft = t; FileTimeToLocalFileTime(&ft, &lft); FileTimeToSystemTime(&lft, &st); ptm->tm_year = st.wYear - 1900; ptm->tm_mon = st.wMonth - 1; ptm->tm_wday = st.wDayOfWeek; ptm->tm_mday = st.wDay; ptm->tm_hour = st.wHour; ptm->tm_min = st.wMinute; ptm->tm_sec = st.wSecond; ptm->tm_yday = 0; // hope nobody uses this ptm->tm_isdst = GetTimeZoneInformation(&tzinfo) == TIME_ZONE_ID_DAYLIGHT ? 1 : 0; return ptm; } static size_t strftime(char *dst, size_t dst_size, const char *fmt, const struct tm *tm) { (void) snprintf(dst, dst_size, "implement strftime() for WinCE"); return 0; } #endif static int mg_rename(const char* oldname, const char* newname) { wchar_t woldbuf[PATH_MAX]; wchar_t wnewbuf[PATH_MAX]; to_unicode(oldname, woldbuf, ARRAY_SIZE(woldbuf)); to_unicode(newname, wnewbuf, ARRAY_SIZE(wnewbuf)); return MoveFileW(woldbuf, wnewbuf) ? 0 : -1; } static FILE *mg_fopen(const char *path, const char *mode) { wchar_t wbuf[PATH_MAX], wmode[20]; to_unicode(path, wbuf, ARRAY_SIZE(wbuf)); MultiByteToWideChar(CP_UTF8, 0, mode, -1, wmode, ARRAY_SIZE(wmode)); return _wfopen(wbuf, wmode); } static int mg_stat(const char *path, struct mgstat *stp) { int ok = -1; // Error wchar_t wbuf[PATH_MAX]; WIN32_FILE_ATTRIBUTE_DATA info; to_unicode(path, wbuf, ARRAY_SIZE(wbuf)); if (GetFileAttributesExW(wbuf, GetFileExInfoStandard, &info) != 0) { stp->size = MAKEUQUAD(info.nFileSizeLow, info.nFileSizeHigh); stp->mtime = SYS2UNIX_TIME(info.ftLastWriteTime.dwLowDateTime, info.ftLastWriteTime.dwHighDateTime); stp->is_directory = info.dwFileAttributes & FILE_ATTRIBUTE_DIRECTORY; ok = 0; // Success } return ok; } static int mg_remove(const char *path) { wchar_t wbuf[PATH_MAX]; to_unicode(path, wbuf, ARRAY_SIZE(wbuf)); return DeleteFileW(wbuf) ? 0 : -1; } static int mg_mkdir(const char *path, int mode) { char buf[PATH_MAX]; wchar_t wbuf[PATH_MAX]; mode = 0; // Unused mg_strlcpy(buf, path, sizeof(buf)); change_slashes_to_backslashes(buf); (void) MultiByteToWideChar(CP_UTF8, 0, buf, -1, wbuf, sizeof(wbuf)); return CreateDirectoryW(wbuf, NULL) ? 0 : -1; } // Implementation of POSIX opendir/closedir/readdir for Windows. static DIR * opendir(const char *name) { DIR *dir = NULL; wchar_t wpath[PATH_MAX]; DWORD attrs; if (name == NULL) { SetLastError(ERROR_BAD_ARGUMENTS); } else if ((dir = (DIR *) malloc(sizeof(*dir))) == NULL) { SetLastError(ERROR_NOT_ENOUGH_MEMORY); } else { to_unicode(name, wpath, ARRAY_SIZE(wpath)); attrs = GetFileAttributesW(wpath); if (attrs != 0xFFFFFFFF && ((attrs & FILE_ATTRIBUTE_DIRECTORY) == FILE_ATTRIBUTE_DIRECTORY)) { (void) wcscat(wpath, L"\\*"); dir->handle = FindFirstFileW(wpath, &dir->info); dir->result.d_name[0] = '\0'; } else { free(dir); dir = NULL; } } return dir; } static int closedir(DIR *dir) { int result = 0; if (dir != NULL) { if (dir->handle != INVALID_HANDLE_VALUE) result = FindClose(dir->handle) ? 0 : -1; free(dir); } else { result = -1; SetLastError(ERROR_BAD_ARGUMENTS); } return result; } struct dirent * readdir(DIR *dir) { struct dirent *result = 0; if (dir) { if (dir->handle != INVALID_HANDLE_VALUE) { result = &dir->result; (void) WideCharToMultiByte(CP_UTF8, 0, dir->info.cFileName, -1, result->d_name, sizeof(result->d_name), NULL, NULL); if (!FindNextFileW(dir->handle, &dir->info)) { (void) FindClose(dir->handle); dir->handle = INVALID_HANDLE_VALUE; } } else { SetLastError(ERROR_FILE_NOT_FOUND); } } else { SetLastError(ERROR_BAD_ARGUMENTS); } return result; } #define set_close_on_exec(fd) // No FD_CLOEXEC on Windows static int start_thread(struct mg_context *ctx, mg_thread_func_t func, void *param) { HANDLE hThread; ctx = NULL; // Unused hThread = CreateThread(NULL, 0, (LPTHREAD_START_ROUTINE) func, param, 0, NULL); if (hThread != NULL) { (void) CloseHandle(hThread); } return hThread == NULL ? -1 : 0; } static HANDLE dlopen(const char *dll_name, int flags) { wchar_t wbuf[PATH_MAX]; flags = 0; // Unused to_unicode(dll_name, wbuf, ARRAY_SIZE(wbuf)); return LoadLibraryW(wbuf); } #if !defined(NO_CGI) #define SIGKILL 0 static int kill(pid_t pid, int sig_num) { (void) TerminateProcess(pid, sig_num); (void) CloseHandle(pid); return 0; } static pid_t spawn_process(struct mg_connection *conn, const char *prog, char *envblk, char *envp[], int fd_stdin, int fd_stdout, const char *dir) { HANDLE me; char *p, *interp, cmdline[PATH_MAX], buf[PATH_MAX]; FILE *fp; STARTUPINFOA si; PROCESS_INFORMATION pi; envp = NULL; // Unused (void) memset(&si, 0, sizeof(si)); (void) memset(&pi, 0, sizeof(pi)); // TODO(lsm): redirect CGI errors to the error log file si.cb = sizeof(si); si.dwFlags = STARTF_USESTDHANDLES | STARTF_USESHOWWINDOW; si.wShowWindow = SW_HIDE; me = GetCurrentProcess(); (void) DuplicateHandle(me, (HANDLE) _get_osfhandle(fd_stdin), me, &si.hStdInput, 0, TRUE, DUPLICATE_SAME_ACCESS); (void) DuplicateHandle(me, (HANDLE) _get_osfhandle(fd_stdout), me, &si.hStdOutput, 0, TRUE, DUPLICATE_SAME_ACCESS); // If CGI file is a script, try to read the interpreter line interp = conn->ctx->config[CGI_INTERPRETER]; if (interp == NULL) { buf[2] = '\0'; if ((fp = fopen(cmdline, "r")) != NULL) { (void) fgets(buf, sizeof(buf), fp); if (buf[0] != '#' || buf[1] != '!') { // First line does not start with "#!". Do not set interpreter. buf[2] = '\0'; } else { // Trim whitespaces in interpreter name for (p = &buf[strlen(buf) - 1]; p > buf && isspace(*p); p--) { *p = '\0'; } } (void) fclose(fp); } interp = buf + 2; } (void) mg_snprintf(conn, cmdline, sizeof(cmdline), "%s%s%s%c%s", interp, interp[0] == '\0' ? "" : " ", dir, DIRSEP, prog); DEBUG_TRACE(("Running [%s]", cmdline)); if (CreateProcessA(NULL, cmdline, NULL, NULL, TRUE, CREATE_NEW_PROCESS_GROUP, envblk, dir, &si, &pi) == 0) { cry(conn, "%s: CreateProcess(%s): %d", __func__, cmdline, ERRNO); pi.hProcess = (pid_t) -1; } else { (void) close(fd_stdin); (void) close(fd_stdout); } (void) CloseHandle(si.hStdOutput); (void) CloseHandle(si.hStdInput); (void) CloseHandle(pi.hThread); return (pid_t) pi.hProcess; } #endif /* !NO_CGI */ static int set_non_blocking_mode(SOCKET sock) { unsigned long on = 1; return ioctlsocket(sock, FIONBIO, &on); } #else static int mg_stat(const char *path, struct mgstat *stp) { struct stat st; int ok; if (stat(path, &st) == 0) { ok = 0; stp->size = st.st_size; stp->mtime = st.st_mtime; stp->is_directory = S_ISDIR(st.st_mode); } else { ok = -1; } return ok; } static void set_close_on_exec(int fd) { (void) fcntl(fd, F_SETFD, FD_CLOEXEC); } static int start_thread(struct mg_context *ctx, mg_thread_func_t func, void *param) { pthread_t thread_id; pthread_attr_t attr; int retval; (void) pthread_attr_init(&attr); (void) pthread_attr_setdetachstate(&attr, PTHREAD_CREATE_DETACHED); // TODO(lsm): figure out why mongoose dies on Linux if next line is enabled // (void) pthread_attr_setstacksize(&attr, sizeof(struct mg_connection) * 5); if ((retval = pthread_create(&thread_id, &attr, func, param)) != 0) { cry(fc(ctx), "%s: %s", __func__, strerror(retval)); } return retval; } #ifndef NO_CGI static pid_t spawn_process(struct mg_connection *conn, const char *prog, char *envblk, char *envp[], int fd_stdin, int fd_stdout, const char *dir) { pid_t pid; const char *interp; envblk = NULL; // Unused if ((pid = fork()) == -1) { // Parent send_http_error(conn, 500, http_500_error, "fork(): %s", strerror(ERRNO)); } else if (pid == 0) { // Child if (chdir(dir) != 0) { cry(conn, "%s: chdir(%s): %s", __func__, dir, strerror(ERRNO)); } else if (dup2(fd_stdin, 0) == -1) { cry(conn, "%s: dup2(%d, 0): %s", __func__, fd_stdin, strerror(ERRNO)); } else if (dup2(fd_stdout, 1) == -1) { cry(conn, "%s: dup2(%d, 1): %s", __func__, fd_stdout, strerror(ERRNO)); } else { (void) dup2(fd_stdout, 2); (void) close(fd_stdin); (void) close(fd_stdout); // Execute CGI program. No need to lock: new process interp = conn->ctx->config[CGI_INTERPRETER]; if (interp == NULL) { (void) execle(prog, prog, NULL, envp); cry(conn, "%s: execle(%s): %s", __func__, prog, strerror(ERRNO)); } else { (void) execle(interp, interp, prog, NULL, envp); cry(conn, "%s: execle(%s %s): %s", __func__, interp, prog, strerror(ERRNO)); } } exit(EXIT_FAILURE); } else { // Parent. Close stdio descriptors (void) close(fd_stdin); (void) close(fd_stdout); } return pid; } #endif // !NO_CGI static int set_non_blocking_mode(SOCKET sock) { int flags; flags = fcntl(sock, F_GETFL, 0); (void) fcntl(sock, F_SETFL, flags | O_NONBLOCK); return 0; } #endif // _WIN32 // Write data to the IO channel - opened file descriptor, socket or SSL // descriptor. Return number of bytes written. static int64_t push(FILE *fp, SOCKET sock, SSL *ssl, const char *buf, int64_t len) { int64_t sent; int n, k; sent = 0; while (sent < len) { /* How many bytes we send in this iteration */ k = len - sent > INT_MAX ? INT_MAX : (int) (len - sent); if (ssl != NULL) { n = SSL_write(ssl, buf + sent, k); } else if (fp != NULL) { n = fwrite(buf + sent, 1, (size_t)k, fp); if (ferror(fp)) n = -1; } else { n = send(sock, buf + sent, (size_t)k, 0); } if (n < 0) break; sent += n; } return sent; } // Read from IO channel - opened file descriptor, socket, or SSL descriptor. // Return number of bytes read. static int pull(FILE *fp, SOCKET sock, SSL *ssl, char *buf, int len) { int nread; if (ssl != NULL) { nread = SSL_read(ssl, buf, len); } else if (fp != NULL) { // Use read() instead of fread(), because if we're reading from the CGI // pipe, fread() may block until IO buffer is filled up. We cannot afford // to block and must pass all read bytes immediately to the client. nread = read(fileno(fp), buf, (size_t) len); if (ferror(fp)) nread = -1; } else { nread = recv(sock, buf, (size_t) len, 0); } return nread; } int mg_read(struct mg_connection *conn, void *buf, size_t len) { int n, buffered_len, nread; const char *buffered; assert((conn->content_len == -1 && conn->consumed_content == 0) || conn->consumed_content <= conn->content_len); DEBUG_TRACE(("%p %zu %lld %lld", buf, len, conn->content_len, conn->consumed_content)); nread = 0; if (conn->consumed_content < conn->content_len) { // Adjust number of bytes to read. int64_t to_read = conn->content_len - conn->consumed_content; if (to_read < (int64_t) len) { len = (int) to_read; } // How many bytes of data we have buffered in the request buffer? buffered = conn->buf + conn->request_len + conn->consumed_content; buffered_len = conn->data_len - conn->request_len; assert(buffered_len >= 0); // Return buffered data back if we haven't done that yet. if (conn->consumed_content < (int64_t) buffered_len) { buffered_len -= (int) conn->consumed_content; if (len < (size_t) buffered_len) { buffered_len = len; } memcpy(buf, buffered, (size_t)buffered_len); len -= buffered_len; buf = (char *) buf + buffered_len; conn->consumed_content += buffered_len; nread = buffered_len; } // We have returned all buffered data. Read new data from the remote socket. while (len > 0) { n = pull(NULL, conn->client.sock, conn->ssl, (char *) buf, (int) len); if (n <= 0) { break; } buf = (char *) buf + n; conn->consumed_content += n; nread += n; len -= n; } } return nread; } int mg_write(struct mg_connection *conn, const void *buf, size_t len) { return (int) push(NULL, conn->client.sock, conn->ssl, (const char *) buf, (int64_t) len); } int mg_printf(struct mg_connection *conn, const char *fmt, ...) { char buf[BUFSIZ]; int len; va_list ap; va_start(ap, fmt); len = mg_vsnprintf(conn, buf, sizeof(buf), fmt, ap); va_end(ap); return mg_write(conn, buf, (size_t)len); } // URL-decode input buffer into destination buffer. // 0-terminate the destination buffer. Return the length of decoded data. // form-url-encoded data differs from URI encoding in a way that it // uses '+' as character for space, see RFC 1866 section 8.2.1 // http://ftp.ics.uci.edu/pub/ietf/html/rfc1866.txt static size_t url_decode(const char *src, size_t src_len, char *dst, size_t dst_len, int is_form_url_encoded) { size_t i, j; int a, b; #define HEXTOI(x) (isdigit(x) ? x - '0' : x - 'W') for (i = j = 0; i < src_len && j < dst_len - 1; i++, j++) { if (src[i] == '%' && isxdigit(* (const unsigned char *) (src + i + 1)) && isxdigit(* (const unsigned char *) (src + i + 2))) { a = tolower(* (const unsigned char *) (src + i + 1)); b = tolower(* (const unsigned char *) (src + i + 2)); dst[j] = (char) ((HEXTOI(a) << 4) | HEXTOI(b)); i += 2; } else if (is_form_url_encoded && src[i] == '+') { dst[j] = ' '; } else { dst[j] = src[i]; } } dst[j] = '\0'; /* Null-terminate the destination */ return j; } // Scan given buffer and fetch the value of the given variable. // It can be specified in query string, or in the POST data. // Return NULL if the variable not found, or allocated 0-terminated value. // It is caller's responsibility to free the returned value. int mg_get_var(const char *buf, size_t buf_len, const char *name, char *dst, size_t dst_len) { const char *p, *e, *s; size_t name_len, len; name_len = strlen(name); e = buf + buf_len; len = -1; dst[0] = '\0'; // buf is "var1=val1&var2=val2...". Find variable first for (p = buf; p != NULL && p + name_len < e; p++) { if ((p == buf || p[-1] == '&') && p[name_len] == '=' && !mg_strncasecmp(name, p, name_len)) { // Point p to variable value p += name_len + 1; // Point s to the end of the value s = (const char *) memchr(p, '&', (size_t)(e - p)); if (s == NULL) { s = e; } assert(s >= p); // Decode variable into destination buffer if ((size_t) (s - p) < dst_len) { len = url_decode(p, (size_t)(s - p), dst, dst_len, 1); } break; } } return len; } int mg_get_cookie(const struct mg_connection *conn, const char *cookie_name, char *dst, size_t dst_size) { const char *s, *p, *end; int name_len, len = -1; dst[0] = '\0'; if ((s = mg_get_header(conn, "Cookie")) == NULL) { return 0; } name_len = strlen(cookie_name); end = s + strlen(s); for (; (s = strstr(s, cookie_name)) != NULL; s += name_len) if (s[name_len] == '=') { s += name_len + 1; if ((p = strchr(s, ' ')) == NULL) p = end; if (p[-1] == ';') p--; if (*s == '"' && p[-1] == '"' && p > s + 1) { s++; p--; } if ((size_t) (p - s) < dst_size) { len = (p - s) + 1; mg_strlcpy(dst, s, (size_t)len); } break; } return len; } // Mongoose allows to specify multiple directories to serve, // like /var/www,/~bob=/home/bob. That means that root directory depends on URI. // This function returns root dir for given URI. static int get_document_root(const struct mg_connection *conn, struct vec *document_root) { const char *root, *uri; int len_of_matched_uri; struct vec uri_vec, path_vec; uri = conn->request_info.uri; len_of_matched_uri = 0; root = next_option(conn->ctx->config[DOCUMENT_ROOT], document_root, NULL); while ((root = next_option(root, &uri_vec, &path_vec)) != NULL) { if (memcmp(uri, uri_vec.ptr, uri_vec.len) == 0) { *document_root = path_vec; len_of_matched_uri = uri_vec.len; break; } } return len_of_matched_uri; } static void convert_uri_to_file_name(struct mg_connection *conn, const char *uri, char *buf, size_t buf_len) { struct vec vec; int match_len; match_len = get_document_root(conn, &vec); mg_snprintf(conn, buf, buf_len, "%.*s%s", vec.len, vec.ptr, uri + match_len); #if defined(_WIN32) && !defined(__SYMBIAN32__) change_slashes_to_backslashes(buf); #endif /* _WIN32 */ DEBUG_TRACE(("[%s] -> [%s], [%.*s]", uri, buf, (int) vec.len, vec.ptr)); } static int sslize(struct mg_connection *conn, int (*func)(SSL *)) { return (conn->ssl = SSL_new(conn->ctx->ssl_ctx)) != NULL && SSL_set_fd(conn->ssl, conn->client.sock) == 1 && func(conn->ssl) == 1; } static struct mg_connection *mg_connect(struct mg_connection *conn, const char *host, int port, int use_ssl) { struct mg_connection *newconn = NULL; struct sockaddr_in sin; struct hostent *he; int sock; if (conn->ctx->ssl_ctx == NULL && use_ssl) { cry(conn, "%s: SSL is not initialized", __func__); } else if ((he = gethostbyname(host)) == NULL) { cry(conn, "%s: gethostbyname(%s): %s", __func__, host, strerror(ERRNO)); } else if ((sock = socket(PF_INET, SOCK_STREAM, 0)) == INVALID_SOCKET) { cry(conn, "%s: socket: %s", __func__, strerror(ERRNO)); } else { sin.sin_family = AF_INET; sin.sin_port = htons((uint16_t) port); sin.sin_addr = * (struct in_addr *) he->h_addr_list[0]; if (connect(sock, (struct sockaddr *) &sin, sizeof(sin)) != 0) { cry(conn, "%s: connect(%s:%d): %s", __func__, host, port, strerror(ERRNO)); closesocket(sock); } else if ((newconn = (struct mg_connection *) calloc(1, sizeof(*newconn))) == NULL) { cry(conn, "%s: calloc: %s", __func__, strerror(ERRNO)); closesocket(sock); } else { newconn->client.sock = sock; newconn->client.rsa.u.sin = sin; if (use_ssl) { sslize(newconn, SSL_connect); } } } return newconn; } // Check whether full request is buffered. Return: // -1 if request is malformed // 0 if request is not yet fully buffered // >0 actual request length, including last \r\n\r\n static int get_request_len(const char *buf, int buflen) { const char *s, *e; int len = 0; DEBUG_TRACE(("buf: %p, len: %d", buf, buflen)); for (s = buf, e = s + buflen - 1; len <= 0 && s < e; s++) // Control characters are not allowed but >=128 is. if (!isprint(* (const unsigned char *) s) && *s != '\r' && *s != '\n' && * (const unsigned char *) s < 128) { len = -1; } else if (s[0] == '\n' && s[1] == '\n') { len = (int) (s - buf) + 2; } else if (s[0] == '\n' && &s[1] < e && s[1] == '\r' && s[2] == '\n') { len = (int) (s - buf) + 3; } return len; } // Convert month to the month number. Return -1 on error, or month number static int month_number_to_month_name(const char *s) { size_t i; for (i = 0; i < ARRAY_SIZE(month_names); i++) if (!strcmp(s, month_names[i])) return (int) i; return -1; } // Parse date-time string, and return the corresponding time_t value static time_t parse_date_string(const char *s) { time_t current_time; struct tm tm, *tmp; char mon[32]; int sec, min, hour, mday, month, year; (void) memset(&tm, 0, sizeof(tm)); sec = min = hour = mday = month = year = 0; if (((sscanf(s, "%d/%3s/%d %d:%d:%d", &mday, mon, &year, &hour, &min, &sec) == 6) || (sscanf(s, "%d %3s %d %d:%d:%d", &mday, mon, &year, &hour, &min, &sec) == 6) || (sscanf(s, "%*3s, %d %3s %d %d:%d:%d", &mday, mon, &year, &hour, &min, &sec) == 6) || (sscanf(s, "%d-%3s-%d %d:%d:%d", &mday, mon, &year, &hour, &min, &sec) == 6)) && (month = month_number_to_month_name(mon)) != -1) { tm.tm_mday = mday; tm.tm_mon = month; tm.tm_year = year; tm.tm_hour = hour; tm.tm_min = min; tm.tm_sec = sec; } if (tm.tm_year > 1900) { tm.tm_year -= 1900; } else if (tm.tm_year < 70) { tm.tm_year += 100; } // Set Daylight Saving Time field current_time = time(NULL); tmp = localtime(¤t_time); tm.tm_isdst = tmp->tm_isdst; return mktime(&tm); } // Protect against directory disclosure attack by removing '..', // excessive '/' and '\' characters static void remove_double_dots_and_double_slashes(char *s) { char *p = s; while (*s != '\0') { *p++ = *s++; if (s[-1] == '/' || s[-1] == '\\') { // Skip all following slashes and backslashes while (*s == '/' || *s == '\\') { s++; } // Skip all double-dots while (*s == '.' && s[1] == '.') { s += 2; } } } *p = '\0'; } static const struct { const char *extension; size_t ext_len; const char *mime_type; size_t mime_type_len; } builtin_mime_types[] = { {".html", 5, "text/html", 9}, {".htm", 4, "text/html", 9}, {".shtm", 5, "text/html", 9}, {".shtml", 6, "text/html", 9}, {".css", 4, "text/css", 8}, {".js", 3, "application/x-javascript", 24}, {".ico", 4, "image/x-icon", 12}, {".gif", 4, "image/gif", 9}, {".jpg", 4, "image/jpeg", 10}, {".jpeg", 5, "image/jpeg", 10}, {".png", 4, "image/png", 9}, {".svg", 4, "image/svg+xml", 13}, {".torrent", 8, "application/x-bittorrent", 24}, {".wav", 4, "audio/x-wav", 11}, {".mp3", 4, "audio/x-mp3", 11}, {".mid", 4, "audio/mid", 9}, {".m3u", 4, "audio/x-mpegurl", 15}, {".ram", 4, "audio/x-pn-realaudio", 20}, {".xml", 4, "text/xml", 8}, {".xslt", 5, "application/xml", 15}, {".ra", 3, "audio/x-pn-realaudio", 20}, {".doc", 4, "application/msword", 19}, {".exe", 4, "application/octet-stream", 24}, {".zip", 4, "application/x-zip-compressed", 28}, {".xls", 4, "application/excel", 17}, {".tgz", 4, "application/x-tar-gz", 20}, {".tar", 4, "application/x-tar", 17}, {".gz", 3, "application/x-gunzip", 20}, {".arj", 4, "application/x-arj-compressed", 28}, {".rar", 4, "application/x-arj-compressed", 28}, {".rtf", 4, "application/rtf", 15}, {".pdf", 4, "application/pdf", 15}, {".swf", 4, "application/x-shockwave-flash",29}, {".mpg", 4, "video/mpeg", 10}, {".mpeg", 5, "video/mpeg", 10}, {".asf", 4, "video/x-ms-asf", 14}, {".avi", 4, "video/x-msvideo", 15}, {".bmp", 4, "image/bmp", 9}, {NULL, 0, NULL, 0} }; // Look at the "path" extension and figure what mime type it has. // Store mime type in the vector. static void get_mime_type(struct mg_context *ctx, const char *path, struct vec *vec) { struct vec ext_vec, mime_vec; const char *list, *ext; size_t i, path_len; path_len = strlen(path); // Scan user-defined mime types first, in case user wants to // override default mime types. list = ctx->config[EXTRA_MIME_TYPES]; while ((list = next_option(list, &ext_vec, &mime_vec)) != NULL) { // ext now points to the path suffix ext = path + path_len - ext_vec.len; if (mg_strncasecmp(ext, ext_vec.ptr, ext_vec.len) == 0) { *vec = mime_vec; return; } } // Now scan built-in mime types for (i = 0; builtin_mime_types[i].extension != NULL; i++) { ext = path + (path_len - builtin_mime_types[i].ext_len); if (path_len > builtin_mime_types[i].ext_len && mg_strcasecmp(ext, builtin_mime_types[i].extension) == 0) { vec->ptr = builtin_mime_types[i].mime_type; vec->len = builtin_mime_types[i].mime_type_len; return; } } // Nothing found. Fall back to "text/plain" vec->ptr = "text/plain"; vec->len = 10; } #ifndef HAVE_MD5 typedef struct MD5Context { uint32_t buf[4]; uint32_t bits[2]; unsigned char in[64]; } MD5_CTX; #if defined(__BYTE_ORDER) && (__BYTE_ORDER == 1234) #define byteReverse(buf, len) // Do nothing #else static void byteReverse(unsigned char *buf, unsigned longs) { uint32_t t; do { t = (uint32_t) ((unsigned) buf[3] << 8 | buf[2]) << 16 | ((unsigned) buf[1] << 8 | buf[0]); *(uint32_t *) buf = t; buf += 4; } while (--longs); } #endif #define F1(x, y, z) (z ^ (x & (y ^ z))) #define F2(x, y, z) F1(z, x, y) #define F3(x, y, z) (x ^ y ^ z) #define F4(x, y, z) (y ^ (x | ~z)) #define MD5STEP(f, w, x, y, z, data, s) \ ( w += f(x, y, z) + data, w = w<>(32-s), w += x ) // Start MD5 accumulation. Set bit count to 0 and buffer to mysterious // initialization constants. static void MD5Init(MD5_CTX *ctx) { ctx->buf[0] = 0x67452301; ctx->buf[1] = 0xefcdab89; ctx->buf[2] = 0x98badcfe; ctx->buf[3] = 0x10325476; ctx->bits[0] = 0; ctx->bits[1] = 0; } static void MD5Transform(uint32_t buf[4], uint32_t const in[16]) { register uint32_t a, b, c, d; a = buf[0]; b = buf[1]; c = buf[2]; d = buf[3]; MD5STEP(F1, a, b, c, d, in[0] + 0xd76aa478, 7); MD5STEP(F1, d, a, b, c, in[1] + 0xe8c7b756, 12); MD5STEP(F1, c, d, a, b, in[2] + 0x242070db, 17); MD5STEP(F1, b, c, d, a, in[3] + 0xc1bdceee, 22); MD5STEP(F1, a, b, c, d, in[4] + 0xf57c0faf, 7); MD5STEP(F1, d, a, b, c, in[5] + 0x4787c62a, 12); MD5STEP(F1, c, d, a, b, in[6] + 0xa8304613, 17); MD5STEP(F1, b, c, d, a, in[7] + 0xfd469501, 22); MD5STEP(F1, a, b, c, d, in[8] + 0x698098d8, 7); MD5STEP(F1, d, a, b, c, in[9] + 0x8b44f7af, 12); MD5STEP(F1, c, d, a, b, in[10] + 0xffff5bb1, 17); MD5STEP(F1, b, c, d, a, in[11] + 0x895cd7be, 22); MD5STEP(F1, a, b, c, d, in[12] + 0x6b901122, 7); MD5STEP(F1, d, a, b, c, in[13] + 0xfd987193, 12); MD5STEP(F1, c, d, a, b, in[14] + 0xa679438e, 17); MD5STEP(F1, b, c, d, a, in[15] + 0x49b40821, 22); MD5STEP(F2, a, b, c, d, in[1] + 0xf61e2562, 5); MD5STEP(F2, d, a, b, c, in[6] + 0xc040b340, 9); MD5STEP(F2, c, d, a, b, in[11] + 0x265e5a51, 14); MD5STEP(F2, b, c, d, a, in[0] + 0xe9b6c7aa, 20); MD5STEP(F2, a, b, c, d, in[5] + 0xd62f105d, 5); MD5STEP(F2, d, a, b, c, in[10] + 0x02441453, 9); MD5STEP(F2, c, d, a, b, in[15] + 0xd8a1e681, 14); MD5STEP(F2, b, c, d, a, in[4] + 0xe7d3fbc8, 20); MD5STEP(F2, a, b, c, d, in[9] + 0x21e1cde6, 5); MD5STEP(F2, d, a, b, c, in[14] + 0xc33707d6, 9); MD5STEP(F2, c, d, a, b, in[3] + 0xf4d50d87, 14); MD5STEP(F2, b, c, d, a, in[8] + 0x455a14ed, 20); MD5STEP(F2, a, b, c, d, in[13] + 0xa9e3e905, 5); MD5STEP(F2, d, a, b, c, in[2] + 0xfcefa3f8, 9); MD5STEP(F2, c, d, a, b, in[7] + 0x676f02d9, 14); MD5STEP(F2, b, c, d, a, in[12] + 0x8d2a4c8a, 20); MD5STEP(F3, a, b, c, d, in[5] + 0xfffa3942, 4); MD5STEP(F3, d, a, b, c, in[8] + 0x8771f681, 11); MD5STEP(F3, c, d, a, b, in[11] + 0x6d9d6122, 16); MD5STEP(F3, b, c, d, a, in[14] + 0xfde5380c, 23); MD5STEP(F3, a, b, c, d, in[1] + 0xa4beea44, 4); MD5STEP(F3, d, a, b, c, in[4] + 0x4bdecfa9, 11); MD5STEP(F3, c, d, a, b, in[7] + 0xf6bb4b60, 16); MD5STEP(F3, b, c, d, a, in[10] + 0xbebfbc70, 23); MD5STEP(F3, a, b, c, d, in[13] + 0x289b7ec6, 4); MD5STEP(F3, d, a, b, c, in[0] + 0xeaa127fa, 11); MD5STEP(F3, c, d, a, b, in[3] + 0xd4ef3085, 16); MD5STEP(F3, b, c, d, a, in[6] + 0x04881d05, 23); MD5STEP(F3, a, b, c, d, in[9] + 0xd9d4d039, 4); MD5STEP(F3, d, a, b, c, in[12] + 0xe6db99e5, 11); MD5STEP(F3, c, d, a, b, in[15] + 0x1fa27cf8, 16); MD5STEP(F3, b, c, d, a, in[2] + 0xc4ac5665, 23); MD5STEP(F4, a, b, c, d, in[0] + 0xf4292244, 6); MD5STEP(F4, d, a, b, c, in[7] + 0x432aff97, 10); MD5STEP(F4, c, d, a, b, in[14] + 0xab9423a7, 15); MD5STEP(F4, b, c, d, a, in[5] + 0xfc93a039, 21); MD5STEP(F4, a, b, c, d, in[12] + 0x655b59c3, 6); MD5STEP(F4, d, a, b, c, in[3] + 0x8f0ccc92, 10); MD5STEP(F4, c, d, a, b, in[10] + 0xffeff47d, 15); MD5STEP(F4, b, c, d, a, in[1] + 0x85845dd1, 21); MD5STEP(F4, a, b, c, d, in[8] + 0x6fa87e4f, 6); MD5STEP(F4, d, a, b, c, in[15] + 0xfe2ce6e0, 10); MD5STEP(F4, c, d, a, b, in[6] + 0xa3014314, 15); MD5STEP(F4, b, c, d, a, in[13] + 0x4e0811a1, 21); MD5STEP(F4, a, b, c, d, in[4] + 0xf7537e82, 6); MD5STEP(F4, d, a, b, c, in[11] + 0xbd3af235, 10); MD5STEP(F4, c, d, a, b, in[2] + 0x2ad7d2bb, 15); MD5STEP(F4, b, c, d, a, in[9] + 0xeb86d391, 21); buf[0] += a; buf[1] += b; buf[2] += c; buf[3] += d; } static void MD5Update(MD5_CTX *ctx, unsigned char const *buf, unsigned len) { uint32_t t; t = ctx->bits[0]; if ((ctx->bits[0] = t + ((uint32_t) len << 3)) < t) ctx->bits[1]++; ctx->bits[1] += len >> 29; t = (t >> 3) & 0x3f; if (t) { unsigned char *p = (unsigned char *) ctx->in + t; t = 64 - t; if (len < t) { memcpy(p, buf, len); return; } memcpy(p, buf, t); byteReverse(ctx->in, 16); MD5Transform(ctx->buf, (uint32_t *) ctx->in); buf += t; len -= t; } while (len >= 64) { memcpy(ctx->in, buf, 64); byteReverse(ctx->in, 16); MD5Transform(ctx->buf, (uint32_t *) ctx->in); buf += 64; len -= 64; } memcpy(ctx->in, buf, len); } static void MD5Final(unsigned char digest[16], MD5_CTX *ctx) { unsigned count; unsigned char *p; count = (ctx->bits[0] >> 3) & 0x3F; p = ctx->in + count; *p++ = 0x80; count = 64 - 1 - count; if (count < 8) { memset(p, 0, count); byteReverse(ctx->in, 16); MD5Transform(ctx->buf, (uint32_t *) ctx->in); memset(ctx->in, 0, 56); } else { memset(p, 0, count - 8); } byteReverse(ctx->in, 14); ((uint32_t *) ctx->in)[14] = ctx->bits[0]; ((uint32_t *) ctx->in)[15] = ctx->bits[1]; MD5Transform(ctx->buf, (uint32_t *) ctx->in); byteReverse((unsigned char *) ctx->buf, 4); memcpy(digest, ctx->buf, 16); memset((char *) ctx, 0, sizeof(*ctx)); } #endif // !HAVE_MD5 // Stringify binary data. Output buffer must be twice as big as input, // because each byte takes 2 bytes in string representation static void bin2str(char *to, const unsigned char *p, size_t len) { static const char *hex = "0123456789abcdef"; for (; len--; p++) { *to++ = hex[p[0] >> 4]; *to++ = hex[p[0] & 0x0f]; } *to = '\0'; } // Return stringified MD5 hash for list of vectors. Buffer must be 33 bytes. void mg_md5(char *buf, ...) { unsigned char hash[16]; const char *p; va_list ap; MD5_CTX ctx; MD5Init(&ctx); va_start(ap, buf); while ((p = va_arg(ap, const char *)) != NULL) { MD5Update(&ctx, (const unsigned char *) p, (unsigned) strlen(p)); } va_end(ap); MD5Final(hash, &ctx); bin2str(buf, hash, sizeof(hash)); } // Check the user's password, return 1 if OK static int check_password(const char *method, const char *ha1, const char *uri, const char *nonce, const char *nc, const char *cnonce, const char *qop, const char *response) { char ha2[32 + 1], expected_response[32 + 1]; // Some of the parameters may be NULL if (method == NULL || nonce == NULL || nc == NULL || cnonce == NULL || qop == NULL || response == NULL) { return 0; } // NOTE(lsm): due to a bug in MSIE, we do not compare the URI // TODO(lsm): check for authentication timeout if (// strcmp(dig->uri, c->ouri) != 0 || strlen(response) != 32 // || now - strtoul(dig->nonce, NULL, 10) > 3600 ) { return 0; } mg_md5(ha2, method, ":", uri, NULL); mg_md5(expected_response, ha1, ":", nonce, ":", nc, ":", cnonce, ":", qop, ":", ha2, NULL); return mg_strcasecmp(response, expected_response) == 0; } // Use the global passwords file, if specified by auth_gpass option, // or search for .htpasswd in the requested directory. static FILE *open_auth_file(struct mg_connection *conn, const char *path) { struct mg_context *ctx = conn->ctx; char name[PATH_MAX]; const char *p, *e; struct mgstat st; FILE *fp; if (ctx->config[GLOBAL_PASSWORDS_FILE] != NULL) { // Use global passwords file fp = mg_fopen(ctx->config[GLOBAL_PASSWORDS_FILE], "r"); if (fp == NULL) cry(fc(ctx), "fopen(%s): %s", ctx->config[GLOBAL_PASSWORDS_FILE], strerror(ERRNO)); } else if (!mg_stat(path, &st) && st.is_directory) { (void) mg_snprintf(conn, name, sizeof(name), "%s%c%s", path, DIRSEP, PASSWORDS_FILE_NAME); fp = mg_fopen(name, "r"); } else { // Try to find .htpasswd in requested directory. for (p = path, e = p + strlen(p) - 1; e > p; e--) if (IS_DIRSEP_CHAR(*e)) break; (void) mg_snprintf(conn, name, sizeof(name), "%.*s%c%s", (int) (e - p), p, DIRSEP, PASSWORDS_FILE_NAME); fp = mg_fopen(name, "r"); } return fp; } // Parsed Authorization header struct ah { char *user, *uri, *cnonce, *response, *qop, *nc, *nonce; }; static int parse_auth_header(struct mg_connection *conn, char *buf, size_t buf_size, struct ah *ah) { char *name, *value, *s; const char *auth_header; if ((auth_header = mg_get_header(conn, "Authorization")) == NULL || mg_strncasecmp(auth_header, "Digest ", 7) != 0) { return 0; } // Make modifiable copy of the auth header (void) mg_strlcpy(buf, auth_header + 7, buf_size); s = buf; (void) memset(ah, 0, sizeof(*ah)); // Parse authorization header for (;;) { // Gobble initial spaces while (isspace(* (unsigned char *) s)) { s++; } name = skip_quoted(&s, "=", " ", 0); /* Value is either quote-delimited, or ends at first comma or space. */ if (s[0] == '\"') { s++; value = skip_quoted(&s, "\"", " ", '\\'); if (s[0] == ',') { s++; } } else { value = skip_quoted(&s, ", ", " ", 0); // IE uses commas, FF uses spaces } if (*name == '\0') { break; } if (!strcmp(name, "username")) { ah->user = value; } else if (!strcmp(name, "cnonce")) { ah->cnonce = value; } else if (!strcmp(name, "response")) { ah->response = value; } else if (!strcmp(name, "uri")) { ah->uri = value; } else if (!strcmp(name, "qop")) { ah->qop = value; } else if (!strcmp(name, "nc")) { ah->nc = value; } else if (!strcmp(name, "nonce")) { ah->nonce = value; } } // CGI needs it as REMOTE_USER if (ah->user != NULL) { conn->request_info.remote_user = mg_strdup(ah->user); } else { return 0; } return 1; } // Authorize against the opened passwords file. Return 1 if authorized. static int authorize(struct mg_connection *conn, FILE *fp) { struct ah ah; char line[256], f_user[256], ha1[256], f_domain[256], buf[BUFSIZ]; if (!parse_auth_header(conn, buf, sizeof(buf), &ah)) { return 0; } // Loop over passwords file while (fgets(line, sizeof(line), fp) != NULL) { if (sscanf(line, "%[^:]:%[^:]:%s", f_user, f_domain, ha1) != 3) { continue; } if (!strcmp(ah.user, f_user) && !strcmp(conn->ctx->config[AUTHENTICATION_DOMAIN], f_domain)) return check_password( conn->request_info.request_method, ha1, ah.uri, ah.nonce, ah.nc, ah.cnonce, ah.qop, ah.response); } return 0; } // Return 1 if request is authorised, 0 otherwise. static int check_authorization(struct mg_connection *conn, const char *path) { FILE *fp; char fname[PATH_MAX]; struct vec uri_vec, filename_vec; const char *list; int authorized; fp = NULL; authorized = 1; list = conn->ctx->config[PROTECT_URI]; while ((list = next_option(list, &uri_vec, &filename_vec)) != NULL) { if (!memcmp(conn->request_info.uri, uri_vec.ptr, uri_vec.len)) { (void) mg_snprintf(conn, fname, sizeof(fname), "%.*s", filename_vec.len, filename_vec.ptr); if ((fp = mg_fopen(fname, "r")) == NULL) { cry(conn, "%s: cannot open %s: %s", __func__, fname, strerror(errno)); } break; } } if (fp == NULL) { fp = open_auth_file(conn, path); } if (fp != NULL) { authorized = authorize(conn, fp); (void) fclose(fp); } return authorized; } static void send_authorization_request(struct mg_connection *conn) { conn->request_info.status_code = 401; (void) mg_printf(conn, "HTTP/1.1 401 Unauthorized\r\n" "WWW-Authenticate: Digest qop=\"auth\", " "realm=\"%s\", nonce=\"%lu\"\r\n\r\n", conn->ctx->config[AUTHENTICATION_DOMAIN], (unsigned long) time(NULL)); } static int is_authorized_for_put(struct mg_connection *conn) { FILE *fp; int ret = 0; fp = conn->ctx->config[PUT_DELETE_PASSWORDS_FILE] == NULL ? NULL : mg_fopen(conn->ctx->config[PUT_DELETE_PASSWORDS_FILE], "r"); if (fp != NULL) { ret = authorize(conn, fp); (void) fclose(fp); } return ret; } int mg_modify_passwords_file(const char *fname, const char *domain, const char *user, const char *pass) { int found; char line[512], u[512], d[512], ha1[33], tmp[PATH_MAX]; FILE *fp, *fp2; found = 0; fp = fp2 = NULL; // Regard empty password as no password - remove user record. if (pass[0] == '\0') { pass = NULL; } (void) snprintf(tmp, sizeof(tmp), "%s.tmp", fname); // Create the file if does not exist if ((fp = mg_fopen(fname, "a+")) != NULL) { (void) fclose(fp); } // Open the given file and temporary file if ((fp = mg_fopen(fname, "r")) == NULL) { return 0; } else if ((fp2 = mg_fopen(tmp, "w+")) == NULL) { fclose(fp); return 0; } // Copy the stuff to temporary file while (fgets(line, sizeof(line), fp) != NULL) { if (sscanf(line, "%[^:]:%[^:]:%*s", u, d) != 2) { continue; } if (!strcmp(u, user) && !strcmp(d, domain)) { found++; if (pass != NULL) { mg_md5(ha1, user, ":", domain, ":", pass, NULL); fprintf(fp2, "%s:%s:%s\n", user, domain, ha1); } } else { (void) fprintf(fp2, "%s", line); } } // If new user, just add it if (!found && pass != NULL) { mg_md5(ha1, user, ":", domain, ":", pass, NULL); (void) fprintf(fp2, "%s:%s:%s\n", user, domain, ha1); } // Close files (void) fclose(fp); (void) fclose(fp2); // Put the temp file in place of real file (void) mg_remove(fname); (void) mg_rename(tmp, fname); return 1; } struct de { struct mg_connection *conn; char *file_name; struct mgstat st; }; static void url_encode(const char *src, char *dst, size_t dst_len) { static const char *dont_escape = "._-$,;~()"; static const char *hex = "0123456789abcdef"; const char *end = dst + dst_len - 1; for (; *src != '\0' && dst < end; src++, dst++) { if (isalnum(*(const unsigned char *) src) || strchr(dont_escape, * (const unsigned char *) src) != NULL) { *dst = *src; } else if (dst + 2 < end) { dst[0] = '%'; dst[1] = hex[(* (const unsigned char *) src) >> 4]; dst[2] = hex[(* (const unsigned char *) src) & 0xf]; dst += 2; } } *dst = '\0'; } static void print_dir_entry(struct de *de) { char size[64], mod[64], href[PATH_MAX]; if (de->st.is_directory) { (void) mg_snprintf(de->conn, size, sizeof(size), "%s", "[DIRECTORY]"); } else { // We use (signed) cast below because MSVC 6 compiler cannot // convert unsigned __int64 to double. Sigh. if (de->st.size < 1024) { (void) mg_snprintf(de->conn, size, sizeof(size), "%lu", (unsigned long) de->st.size); } else if (de->st.size < 1024 * 1024) { (void) mg_snprintf(de->conn, size, sizeof(size), "%.1fk", (double) de->st.size / 1024.0); } else if (de->st.size < 1024 * 1024 * 1024) { (void) mg_snprintf(de->conn, size, sizeof(size), "%.1fM", (double) de->st.size / 1048576); } else { (void) mg_snprintf(de->conn, size, sizeof(size), "%.1fG", (double) de->st.size / 1073741824); } } (void) strftime(mod, sizeof(mod), "%d-%b-%Y %H:%M", localtime(&de->st.mtime)); url_encode(de->file_name, href, sizeof(href)); de->conn->num_bytes_sent += mg_printf(de->conn, "%s%s" " %s  %s\n", de->conn->request_info.uri, href, de->st.is_directory ? "/" : "", de->file_name, de->st.is_directory ? "/" : "", mod, size); } // This function is called from send_directory() and used for // sorting directory entries by size, or name, or modification time. // On windows, __cdecl specification is needed in case if project is built // with __stdcall convention. qsort always requires __cdels callback. static int WINCDECL compare_dir_entries(const void *p1, const void *p2) { const struct de *a = (const struct de *) p1, *b = (const struct de *) p2; const char *query_string = a->conn->request_info.query_string; int cmp_result = 0; if (query_string == NULL) { query_string = "na"; } if (a->st.is_directory && !b->st.is_directory) { return -1; // Always put directories on top } else if (!a->st.is_directory && b->st.is_directory) { return 1; // Always put directories on top } else if (*query_string == 'n') { cmp_result = strcmp(a->file_name, b->file_name); } else if (*query_string == 's') { cmp_result = a->st.size == b->st.size ? 0 : a->st.size > b->st.size ? 1 : -1; } else if (*query_string == 'd') { cmp_result = a->st.mtime == b->st.mtime ? 0 : a->st.mtime > b->st.mtime ? 1 : -1; } return query_string[1] == 'd' ? -cmp_result : cmp_result; } static void handle_directory_request(struct mg_connection *conn, const char *dir) { struct dirent *dp; DIR *dirp; struct de *entries = NULL; char path[PATH_MAX]; int i, sort_direction, num_entries = 0, arr_size = 128; if ((dirp = opendir(dir)) == NULL) { send_http_error(conn, 500, "Cannot open directory", "Error: opendir(%s): %s", path, strerror(ERRNO)); return; } (void) mg_printf(conn, "%s", "HTTP/1.1 200 OK\r\n" "Connection: close\r\n" "Content-Type: text/html; charset=utf-8\r\n\r\n"); sort_direction = conn->request_info.query_string != NULL && conn->request_info.query_string[1] == 'd' ? 'a' : 'd'; while ((dp = readdir(dirp)) != NULL) { // Do not show current dir and passwords file if (!strcmp(dp->d_name, ".") || !strcmp(dp->d_name, "..") || !strcmp(dp->d_name, PASSWORDS_FILE_NAME)) continue; if (entries == NULL || num_entries >= arr_size) { arr_size *= 2; entries = (struct de *) realloc(entries, arr_size * sizeof(entries[0])); } if (entries == NULL) { closedir(dirp); send_http_error(conn, 500, "Cannot open directory", "%s", "Error: cannot allocate memory"); return; } mg_snprintf(conn, path, sizeof(path), "%s%c%s", dir, DIRSEP, dp->d_name); // If we don't memset stat structure to zero, mtime will have // garbage and strftime() will segfault later on in // print_dir_entry(). memset is required only if mg_stat() // fails. For more details, see // http://code.google.com/p/mongoose/issues/detail?id=79 if (mg_stat(path, &entries[num_entries].st) != 0) { memset(&entries[num_entries].st, 0, sizeof(entries[num_entries].st)); } entries[num_entries].conn = conn; entries[num_entries].file_name = mg_strdup(dp->d_name); num_entries++; } (void) closedir(dirp); conn->num_bytes_sent += mg_printf(conn, "Index of %s" "" "

Index of %s

"
      ""
      ""
      ""
      "",
      conn->request_info.uri, conn->request_info.uri,
      sort_direction, sort_direction, sort_direction);

  // Print first entry - link to a parent directory
  conn->num_bytes_sent += mg_printf(conn,
      ""
      "\n",
      conn->request_info.uri, "..", "Parent directory", "-", "-");

  // Sort and print directory entries
  qsort(entries, (size_t)num_entries, sizeof(entries[0]), compare_dir_entries);
  for (i = 0; i < num_entries; i++) {
    print_dir_entry(&entries[i]);
    free(entries[i].file_name);
  }
  free(entries);

  conn->num_bytes_sent += mg_printf(conn, "%s", "
NameModifiedSize
%s %s  %s
");
  conn->request_info.status_code = 200;
}

// Send len bytes from the opened file to the client.
static void send_file_data(struct mg_connection *conn, FILE *fp, int64_t len) {
  char buf[BUFSIZ];
  int to_read, num_read, num_written;

  while (len > 0) {
    // Calculate how much to read from the file in the buffer
    to_read = sizeof(buf);
    if ((int64_t) to_read > len)
      to_read = (int) len;

    // Read from file, exit the loop on error
    if ((num_read = fread(buf, 1, (size_t)to_read, fp)) == 0)
      break;

    // Send read bytes to the client, exit the loop on error
    if ((num_written = mg_write(conn, buf, (size_t)num_read)) != num_read)
      break;

    // Both read and were successful, adjust counters
    conn->num_bytes_sent += num_written;
    len -= num_written;
  }
}

static int parse_range_header(const char *header, int64_t *a, int64_t *b) {
  return sscanf(header, "bytes=%" INT64_FMT "-%" INT64_FMT, a, b);
}

static void handle_file_request(struct mg_connection *conn, const char *path,
                                struct mgstat *stp) {
  char date[64], lm[64], etag[64], range[64];
  const char *fmt = "%a, %d %b %Y %H:%M:%S %Z", *msg = "OK", *hdr;
  time_t curtime = time(NULL);
  int64_t cl, r1, r2;
  struct vec mime_vec;
  FILE *fp;
  int n;

  get_mime_type(conn->ctx, path, &mime_vec);
  cl = stp->size;
  conn->request_info.status_code = 200;
  range[0] = '\0';

  if ((fp = mg_fopen(path, "rb")) == NULL) {
    send_http_error(conn, 500, http_500_error,
        "fopen(%s): %s", path, strerror(ERRNO));
    return;
  }
  set_close_on_exec(fileno(fp));

  // If Range: header specified, act accordingly
  r1 = r2 = 0;
  hdr = mg_get_header(conn, "Range");
  if (hdr != NULL && (n = parse_range_header(hdr, &r1, &r2)) > 0) {
    conn->request_info.status_code = 206;
    (void) fseeko(fp, (off_t) r1, SEEK_SET);
    cl = n == 2 ? r2 - r1 + 1: cl - r1;
    (void) mg_snprintf(conn, range, sizeof(range),
        "Content-Range: bytes "
        "%" INT64_FMT "-%"
        INT64_FMT "/%" INT64_FMT "\r\n",
        r1, r1 + cl - 1, stp->size);
    msg = "Partial Content";
  }

  // Prepare Etag, Date, Last-Modified headers
  (void) strftime(date, sizeof(date), fmt, localtime(&curtime));
  (void) strftime(lm, sizeof(lm), fmt, localtime(&stp->mtime));
  (void) mg_snprintf(conn, etag, sizeof(etag), "%lx.%lx",
      (unsigned long) stp->mtime, (unsigned long) stp->size);

  (void) mg_printf(conn,
      "HTTP/1.1 %d %s\r\n"
      "Date: %s\r\n"
      "Last-Modified: %s\r\n"
      "Etag: \"%s\"\r\n"
      "Content-Type: %.*s\r\n"
      "Content-Length: %" INT64_FMT "\r\n"
      "Connection: %s\r\n"
      "Accept-Ranges: bytes\r\n"
      "%s\r\n",
      conn->request_info.status_code, msg, date, lm, etag,
      mime_vec.len, mime_vec.ptr, cl, suggest_connection_header(conn), range);

  if (strcmp(conn->request_info.request_method, "HEAD") != 0) {
    send_file_data(conn, fp, cl);
  }
  (void) fclose(fp);
}

// Parse HTTP headers from the given buffer, advance buffer to the point
// where parsing stopped.
static void parse_http_headers(char **buf, struct mg_request_info *ri) {
  int i;

  for (i = 0; i < (int) ARRAY_SIZE(ri->http_headers); i++) {
    ri->http_headers[i].name = skip_quoted(buf, ":", " ", 0);
    ri->http_headers[i].value = skip(buf, "\r\n");
    if (ri->http_headers[i].name[0] == '\0')
      break;
    ri->num_headers = i + 1;
  }
}

static int is_valid_http_method(const char *method) {
  return !strcmp(method, "GET") || !strcmp(method, "POST") ||
    !strcmp(method, "HEAD") || !strcmp(method, "CONNECT") ||
    !strcmp(method, "PUT") || !strcmp(method, "DELETE");
}

// Parse HTTP request, fill in mg_request_info structure.
static int parse_http_request(char *buf, struct mg_request_info *ri) {
  int status = 0;

  // RFC says that all initial whitespaces should be ingored
  while (*buf != '\0' && isspace(* (unsigned char *) buf)) {
    buf++;
  }

  ri->request_method = skip(&buf, " ");
  ri->uri = skip(&buf, " ");
  ri->http_version = skip(&buf, "\r\n");

  if (is_valid_http_method(ri->request_method) &&
      strncmp(ri->http_version, "HTTP/", 5) == 0) {
    ri->http_version += 5;   /* Skip "HTTP/" */
    parse_http_headers(&buf, ri);
    status = 1;
  }

  return status;
}

// Keep reading the input (either opened file descriptor fd, or socket sock,
// or SSL descriptor ssl) into buffer buf, until \r\n\r\n appears in the
// buffer (which marks the end of HTTP request). Buffer buf may already
// have some data. The length of the data is stored in nread.
// Upon every read operation, increase nread by the number of bytes read.
static int read_request(FILE *fp, SOCKET sock, SSL *ssl, char *buf, int bufsiz,
                        int *nread) {
  int n, request_len;

  request_len = 0;
  while (*nread < bufsiz && request_len == 0) {
    n = pull(fp, sock, ssl, buf + *nread, bufsiz - *nread);
    if (n <= 0) {
      break;
    } else {
      *nread += n;
      request_len = get_request_len(buf, *nread);
    }
  }

  return request_len;
}

// For given directory path, substitute it to valid index file.
// Return 0 if index file has been found, -1 if not found.
// If the file is found, it's stats is returned in stp.
static int substitute_index_file(struct mg_connection *conn, char *path,
                                 size_t path_len, struct mgstat *stp) {
  const char *list = conn->ctx->config[INDEX_FILES];
  struct mgstat st;
  struct vec filename_vec;
  size_t n = strlen(path);
  int found = 0;

  // The 'path' given to us points to the directory. Remove all trailing
  // directory separator characters from the end of the path, and
  // then append single directory separator character.
  while (n > 0 && IS_DIRSEP_CHAR(path[n - 1])) {
    n--;
  }
  path[n] = DIRSEP;

  // Traverse index files list. For each entry, append it to the given
  // path and see if the file exists. If it exists, break the loop
  while ((list = next_option(list, &filename_vec, NULL)) != NULL) {

    // Ignore too long entries that may overflow path buffer
    if (filename_vec.len > path_len - n)
      continue;

    // Prepare full path to the index file
    (void) mg_strlcpy(path + n + 1, filename_vec.ptr, filename_vec.len + 1);

    // Does it exist?
    if (mg_stat(path, &st) == 0) {
      // Yes it does, break the loop
      *stp = st;
      found = 1;
      break;
    }
  }

  // If no index file exists, restore directory path
  if (!found) {
    path[n] = '\0';
  }

  return found;
}

// Return True if we should reply 304 Not Modified.
static int is_not_modified(const struct mg_connection *conn,
                           const struct mgstat *stp) {
  const char *ims = mg_get_header(conn, "If-Modified-Since");
  return ims != NULL && stp->mtime <= parse_date_string(ims);
}

static int forward_body_data(struct mg_connection *conn, FILE *fp,
                             SOCKET sock, SSL *ssl) {
  const char *expect, *buffered;
  char buf[BUFSIZ];
  int to_read, nread, buffered_len, success = 0;

  expect = mg_get_header(conn, "Expect");
  assert(fp != NULL);

  if (conn->content_len == -1) {
    send_http_error(conn, 411, "Length Required", "");
  } else if (expect != NULL && mg_strcasecmp(expect, "100-continue")) {
    send_http_error(conn, 417, "Expectation Failed", "");
  } else {
    if (expect != NULL) {
      (void) mg_printf(conn, "%s", "HTTP/1.1 100 Continue\r\n\r\n");
    }

    buffered = conn->buf + conn->request_len;
    buffered_len = conn->data_len - conn->request_len;
    assert(buffered_len >= 0);
    assert(conn->consumed_content == 0);

    if (buffered_len > 0) {
      if ((int64_t) buffered_len > conn->content_len) {
        buffered_len = (int) conn->content_len;
      }
      push(fp, sock, ssl, buffered, (int64_t) buffered_len);
      conn->consumed_content += buffered_len;
    }

    while (conn->consumed_content < conn->content_len) {
      to_read = sizeof(buf);
      if ((int64_t) to_read > conn->content_len - conn->consumed_content) {
        to_read = (int) (conn->content_len - conn->consumed_content);
      }
      nread = pull(NULL, conn->client.sock, conn->ssl, buf, to_read);
      if (nread <= 0 || push(fp, sock, ssl, buf, nread) != nread) {
        break;
      }
      conn->consumed_content += nread;
    }

    if (conn->consumed_content == conn->content_len) {
      success = 1;
    }

    // Each error code path in this function must send an error
    if (!success) {
      send_http_error(conn, 577, http_500_error, "");
    }
  }

  return success;
}

#if !defined(NO_CGI)
// This structure helps to create an environment for the spawned CGI program.
// Environment is an array of "VARIABLE=VALUE\0" ASCIIZ strings,
// last element must be NULL.
// However, on Windows there is a requirement that all these VARIABLE=VALUE\0
// strings must reside in a contiguous buffer. The end of the buffer is
// marked by two '\0' characters.
// We satisfy both worlds: we create an envp array (which is vars), all
// entries are actually pointers inside buf.
struct cgi_env_block {
  struct mg_connection *conn;
  char buf[CGI_ENVIRONMENT_SIZE]; // Environment buffer
  int len; // Space taken
  char *vars[MAX_CGI_ENVIR_VARS]; // char **envp
  int nvars; // Number of variables
};

// Append VARIABLE=VALUE\0 string to the buffer, and add a respective
// pointer into the vars array.
static char *addenv(struct cgi_env_block *block, const char *fmt, ...) {
  int n, space;
  char *added;
  va_list ap;

  // Calculate how much space is left in the buffer
  space = sizeof(block->buf) - block->len - 2;
  assert(space >= 0);

  // Make a pointer to the free space int the buffer
  added = block->buf + block->len;

  // Copy VARIABLE=VALUE\0 string into the free space
  va_start(ap, fmt);
  n = mg_vsnprintf(block->conn, added, (size_t) space, fmt, ap);
  va_end(ap);

  // Make sure we do not overflow buffer and the envp array
  if (n > 0 && n < space &&
      block->nvars < (int) ARRAY_SIZE(block->vars) - 2) {
    // Append a pointer to the added string into the envp array
    block->vars[block->nvars++] = block->buf + block->len;
    // Bump up used length counter. Include \0 terminator
    block->len += n + 1;
  }

  return added;
}

static void prepare_cgi_environment(struct mg_connection *conn,
                                    const char *prog,
                                    struct cgi_env_block *blk) {
  const char *s, *slash;
  struct vec var_vec, root;
  char *p;
  int  i;

  blk->len = blk->nvars = 0;
  blk->conn = conn;

  get_document_root(conn, &root);

  addenv(blk, "SERVER_NAME=%s", conn->ctx->config[AUTHENTICATION_DOMAIN]);
  addenv(blk, "SERVER_ROOT=%.*s", root.len, root.ptr);
  addenv(blk, "DOCUMENT_ROOT=%.*s", root.len, root.ptr);

  // Prepare the environment block
  addenv(blk, "%s", "GATEWAY_INTERFACE=CGI/1.1");
  addenv(blk, "%s", "SERVER_PROTOCOL=HTTP/1.1");
  addenv(blk, "%s", "REDIRECT_STATUS=200"); // For PHP
  addenv(blk, "SERVER_PORT=%d", ntohs(conn->client.lsa.u.sin.sin_port));
  addenv(blk, "REQUEST_METHOD=%s", conn->request_info.request_method);
  addenv(blk, "REMOTE_ADDR=%s",
      inet_ntoa(conn->client.rsa.u.sin.sin_addr));
  addenv(blk, "REMOTE_PORT=%d", conn->request_info.remote_port);
  addenv(blk, "REQUEST_URI=%s", conn->request_info.uri);

  // SCRIPT_NAME
  assert(conn->request_info.uri[0] == '/');
  slash = strrchr(conn->request_info.uri, '/');
  if ((s = strrchr(prog, '/')) == NULL)
    s = prog;
  addenv(blk, "SCRIPT_NAME=%.*s%s", slash - conn->request_info.uri,
         conn->request_info.uri, s);

  addenv(blk, "SCRIPT_FILENAME=%s", prog);
  addenv(blk, "PATH_TRANSLATED=%s", prog);
  addenv(blk, "HTTPS=%s", conn->ssl == NULL ? "off" : "on");

  if ((s = mg_get_header(conn, "Content-Type")) != NULL)
    addenv(blk, "CONTENT_TYPE=%s", s);

  if (conn->request_info.query_string != NULL)
    addenv(blk, "QUERY_STRING=%s", conn->request_info.query_string);

  if ((s = mg_get_header(conn, "Content-Length")) != NULL)
    addenv(blk, "CONTENT_LENGTH=%s", s);

  if ((s = getenv("PATH")) != NULL)
    addenv(blk, "PATH=%s", s);

#if defined(_WIN32)
  if ((s = getenv("COMSPEC")) != NULL)
    addenv(blk, "COMSPEC=%s", s);
  if ((s = getenv("SYSTEMROOT")) != NULL)
    addenv(blk, "SYSTEMROOT=%s", s);
#else
  if ((s = getenv("LD_LIBRARY_PATH")) != NULL)
    addenv(blk, "LD_LIBRARY_PATH=%s", s);
#endif /* _WIN32 */

  if ((s = getenv("PERLLIB")) != NULL)
    addenv(blk, "PERLLIB=%s", s);

  if (conn->request_info.remote_user != NULL) {
    addenv(blk, "REMOTE_USER=%s", conn->request_info.remote_user);
    addenv(blk, "%s", "AUTH_TYPE=Digest");
  }

  // Add all headers as HTTP_* variables
  for (i = 0; i < conn->request_info.num_headers; i++) {
    p = addenv(blk, "HTTP_%s=%s",
        conn->request_info.http_headers[i].name,
        conn->request_info.http_headers[i].value);

    // Convert variable name into uppercase, and change - to _
    for (; *p != '=' && *p != '\0'; p++) {
      if (*p == '-')
        *p = '_';
      *p = (char) toupper(* (unsigned char *) p);
    }
  }

  // Add user-specified variables
  s = conn->ctx->config[CGI_ENVIRONMENT];
  while ((s = next_option(s, &var_vec, NULL)) != NULL) {
    addenv(blk, "%.*s", var_vec.len, var_vec.ptr);
  }

  blk->vars[blk->nvars++] = NULL;
  blk->buf[blk->len++] = '\0';

  assert(blk->nvars < (int) ARRAY_SIZE(blk->vars));
  assert(blk->len > 0);
  assert(blk->len < (int) sizeof(blk->buf));
}

static void handle_cgi_request(struct mg_connection *conn, const char *prog) {
  int headers_len, data_len, i, fd_stdin[2], fd_stdout[2];
  const char *status;
  char buf[BUFSIZ], *pbuf, dir[PATH_MAX], *p;
  struct mg_request_info ri;
  struct cgi_env_block blk;
  FILE *in, *out;
  pid_t pid;

  prepare_cgi_environment(conn, prog, &blk);

  // CGI must be executed in its own directory. 'dir' must point to the
  // directory containing executable program, 'p' must point to the
  // executable program name relative to 'dir'.
  (void) mg_snprintf(conn, dir, sizeof(dir), "%s", prog);
  if ((p = strrchr(dir, DIRSEP)) != NULL) {
    *p++ = '\0';
  } else {
    dir[0] = '.', dir[1] = '\0';
    p = (char *) prog;
  }

  pid = (pid_t) -1;
  fd_stdin[0] = fd_stdin[1] = fd_stdout[0] = fd_stdout[1] = -1;
  in = out = NULL;

  if (pipe(fd_stdin) != 0 || pipe(fd_stdout) != 0) {
    send_http_error(conn, 500, http_500_error,
        "Cannot create CGI pipe: %s", strerror(ERRNO));
    goto done;
  } else if ((pid = spawn_process(conn, p, blk.buf, blk.vars,
          fd_stdin[0], fd_stdout[1], dir)) == (pid_t) -1) {
    goto done;
  } else if ((in = fdopen(fd_stdin[1], "wb")) == NULL ||
      (out = fdopen(fd_stdout[0], "rb")) == NULL) {
    send_http_error(conn, 500, http_500_error,
        "fopen: %s", strerror(ERRNO));
    goto done;
  }

  setbuf(in, NULL);
  setbuf(out, NULL);

  // spawn_process() must close those!
  // If we don't mark them as closed, close() attempt before
  // return from this function throws an exception on Windows.
  // Windows does not like when closed descriptor is closed again.
  fd_stdin[0] = fd_stdout[1] = -1;

  // Send POST data to the CGI process if needed
  if (!strcmp(conn->request_info.request_method, "POST") &&
      !forward_body_data(conn, in, INVALID_SOCKET, NULL)) {
    goto done;
  }

  // Now read CGI reply into a buffer. We need to set correct
  // status code, thus we need to see all HTTP headers first.
  // Do not send anything back to client, until we buffer in all
  // HTTP headers.
  data_len = 0;
  headers_len = read_request(out, INVALID_SOCKET, NULL,
      buf, sizeof(buf), &data_len);
  if (headers_len <= 0) {
    send_http_error(conn, 500, http_500_error,
                    "CGI program sent malformed HTTP headers: [%.*s]",
                    data_len, buf);
    goto done;
  }
  pbuf = buf;
  buf[headers_len - 1] = '\0';
  parse_http_headers(&pbuf, &ri);

  // Make up and send the status line
  status = get_header(&ri, "Status");
  conn->request_info.status_code = status == NULL ? 200 : atoi(status);
  (void) mg_printf(conn, "HTTP/1.1 %d OK\r\n", conn->request_info.status_code);

  // Send headers
  for (i = 0; i < ri.num_headers; i++) {
    mg_printf(conn, "%s: %s\r\n",
              ri.http_headers[i].name, ri.http_headers[i].value);
  }
  (void) mg_write(conn, "\r\n", 2);

  // Send chunk of data that may be read after the headers
  conn->num_bytes_sent += mg_write(conn, buf + headers_len,
                                   (size_t)(data_len - headers_len));

  // Read the rest of CGI output and send to the client
  send_file_data(conn, out, INT64_MAX);

done:
  if (pid != (pid_t) -1) {
    kill(pid, SIGKILL);
#if !defined(_WIN32)
    do {} while (waitpid(-1, &i, WNOHANG) > 0);
#endif
  }
  if (fd_stdin[0] != -1) {
    (void) close(fd_stdin[0]);
  }
  if (fd_stdout[1] != -1) {
    (void) close(fd_stdout[1]);
  }

  if (in != NULL) {
    (void) fclose(in);
  } else if (fd_stdin[1] != -1) {
    (void) close(fd_stdin[1]);
  }

  if (out != NULL) {
    (void) fclose(out);
  } else if (fd_stdout[0] != -1) {
    (void) close(fd_stdout[0]);
  }
}
#endif // !NO_CGI

// For a given PUT path, create all intermediate subdirectories
// for given path. Return 0 if the path itself is a directory,
// or -1 on error, 1 if OK.
static int put_dir(const char *path) {
  char buf[PATH_MAX];
  const char *s, *p;
  struct mgstat st;
  size_t len;

  for (s = p = path + 2; (p = strchr(s, '/')) != NULL; s = ++p) {
    len = p - path;
    assert(len < sizeof(buf));
    (void) memcpy(buf, path, len);
    buf[len] = '\0';

    // Try to create intermediate directory
    if (mg_stat(buf, &st) == -1 && mg_mkdir(buf, 0755) != 0) {
      return -1;
    }

    // Is path itself a directory?
    if (p[1] == '\0') {
      return 0;
    }
  }

  return 1;
}

static void put_file(struct mg_connection *conn, const char *path) {
  struct mgstat st;
  const char *range;
  int64_t r1, r2;
  FILE *fp;
  int rc;

  conn->request_info.status_code = mg_stat(path, &st) == 0 ? 200 : 201;

  if ((rc = put_dir(path)) == 0) {
    mg_printf(conn, "HTTP/1.1 %d OK\r\n\r\n", conn->request_info.status_code);
  } else if (rc == -1) {
    send_http_error(conn, 500, http_500_error,
        "put_dir(%s): %s", path, strerror(ERRNO));
  } else if ((fp = mg_fopen(path, "wb+")) == NULL) {
    send_http_error(conn, 500, http_500_error,
        "fopen(%s): %s", path, strerror(ERRNO));
  } else {
    set_close_on_exec(fileno(fp));
    range = mg_get_header(conn, "Content-Range");
    r1 = r2 = 0;
    if (range != NULL && parse_range_header(range, &r1, &r2) > 0) {
      conn->request_info.status_code = 206;
      // TODO(lsm): handle seek error
      (void) fseeko(fp, (off_t) r1, SEEK_SET);
    }
    if (forward_body_data(conn, fp, INVALID_SOCKET, NULL))
      (void) mg_printf(conn, "HTTP/1.1 %d OK\r\n\r\n",
          conn->request_info.status_code);
    (void) fclose(fp);
  }
}

static void send_ssi_file(struct mg_connection *, const char *, FILE *, int);

static void do_ssi_include(struct mg_connection *conn, const char *ssi,
                           char *tag, int include_level) {
  char file_name[BUFSIZ], path[PATH_MAX], *p;
  struct vec root;
  int is_ssi;
  FILE *fp;

  get_document_root(conn, &root);

  // sscanf() is safe here, since send_ssi_file() also uses buffer
  // of size BUFSIZ to get the tag. So strlen(tag) is always < BUFSIZ.
  if (sscanf(tag, " virtual=\"%[^\"]\"", file_name) == 1) {
    // File name is relative to the webserver root
    (void) mg_snprintf(conn, path, sizeof(path), "%.*s%c%s",
        root.len, root.ptr, DIRSEP, file_name);
  } else if (sscanf(tag, " file=\"%[^\"]\"", file_name) == 1) {
    // File name is relative to the webserver working directory
    // or it is absolute system path
    (void) mg_snprintf(conn, path, sizeof(path), "%s", file_name);
  } else if (sscanf(tag, " \"%[^\"]\"", file_name) == 1) {
    // File name is relative to the currect document
    (void) mg_snprintf(conn, path, sizeof(path), "%s", ssi);
    if ((p = strrchr(path, DIRSEP)) != NULL) {
      p[1] = '\0';
    }
    (void) mg_snprintf(conn, path + strlen(path),
        sizeof(path) - strlen(path), "%s", file_name);
  } else {
    cry(conn, "Bad SSI #include: [%s]", tag);
    return;
  }

  if ((fp = mg_fopen(path, "rb")) == NULL) {
    cry(conn, "Cannot open SSI #include: [%s]: fopen(%s): %s",
        tag, path, strerror(ERRNO));
  } else {
    set_close_on_exec(fileno(fp));
    is_ssi = match_extension(path, conn->ctx->config[SSI_EXTENSIONS]);
    if (is_ssi) {
      send_ssi_file(conn, path, fp, include_level + 1);
    } else {
      send_file_data(conn, fp, INT64_MAX);
    }
    (void) fclose(fp);
  }
}

#if !defined(NO_POPEN)
static void do_ssi_exec(struct mg_connection *conn, char *tag) {
  char cmd[BUFSIZ];
  FILE *fp;

  if (sscanf(tag, " \"%[^\"]\"", cmd) != 1) {
    cry(conn, "Bad SSI #exec: [%s]", tag);
  } else if ((fp = popen(cmd, "r")) == NULL) {
    cry(conn, "Cannot SSI #exec: [%s]: %s", cmd, strerror(ERRNO));
  } else {
    send_file_data(conn, fp, INT64_MAX);
    (void) pclose(fp);
  }
}
#endif // !NO_POPEN

static void send_ssi_file(struct mg_connection *conn, const char *path,
                          FILE *fp, int include_level) {
  char buf[BUFSIZ];
  int ch, len, in_ssi_tag;

  if (include_level > 10) {
    cry(conn, "SSI #include level is too deep (%s)", path);
    return;
  }

  in_ssi_tag = 0;
  len = 0;

  while ((ch = fgetc(fp)) != EOF) {
    if (in_ssi_tag && ch == '>') {
      in_ssi_tag = 0;
      buf[len++] = (char) ch;
      buf[len] = '\0';
      assert(len <= (int) sizeof(buf));
      if (len < 6 || memcmp(buf, "
ssi_end
MSVMpack1.2/mongoose/test/ssi9.shtml0000644000175000017500000000006311557453204016474 0ustar lauerlauerssi_begin ssi_end MSVMpack1.2/mongoose/test/ssi5.shtml0000644000175000017500000000012511557453204016467 0ustar lauerlauer
ssi_begin

ssi_end
MSVMpack1.2/mongoose/test/hello.txt0000644000175000017500000000002111557453204016372 0ustar lauerlauersimple text file MSVMpack1.2/mongoose/test/.leading.dot.txt0000644000175000017500000000000711557453204017541 0ustar lauerlauerabc123 MSVMpack1.2/mongoose/test/ssi3.shtml0000644000175000017500000000010711557453204016465 0ustar lauerlauer
ssi_begin

ssi_end
MSVMpack1.2/mongoose/test/ssi1.shtml0000644000175000017500000000012211557453204016460 0ustar lauerlauer
ssi_begin

ssi_end
MSVMpack1.2/mongoose/test/sh.cgi0000755000175000017500000000012211557453204015631 0ustar lauerlauer#!/bin/sh echo "Content-Type: text/plain" echo echo "This is shell script CGI." MSVMpack1.2/mongoose/test/passfile0000644000175000017500000000016111557453204016264 0ustar lauerlauerguest:mydomain.com:485264dcc977a1925370b89d516a1477 Administrator:mydomain.com:e32daa3028eba04dc53e2d781e6fc983 MSVMpack1.2/mongoose/test/ssi4.shtml0000644000175000017500000000011011557453204016460 0ustar lauerlauer
ssi_begin

ssi_end
MSVMpack1.2/mongoose/test/test.pl0000644000175000017500000004246211557453204016061 0ustar lauerlauer#!/usr/bin/env perl # This script is used to test Mongoose web server # $Id: test.pl 516 2010-05-03 12:54:37Z valenok $ use IO::Socket; use File::Path; use strict; use warnings; #use diagnostics; sub on_windows { $^O =~ /win32/i; } my $port = 23456; my $pid = undef; my $num_requests; my $dir_separator = on_windows() ? '\\' : '/'; my $copy_cmd = on_windows() ? 'copy' : 'cp'; my $test_dir_uri = "test_dir"; my $root = 'test'; my $test_dir = $root . $dir_separator. $test_dir_uri; my $config = 'mongoose.conf'; my $exe = '.' . $dir_separator . 'mongoose'; my $embed_exe = '.' . $dir_separator . 'embed'; my $unit_test_exe = '.' . $dir_separator . 'unit_test'; my $exit_code = 0; my @files_to_delete = ('debug.log', 'access.log', $config, "$root/put.txt", "$root/a+.txt", "$root/.htpasswd", "$root/binary_file", $embed_exe, $unit_test_exe); END { unlink @files_to_delete; kill_spawned_child(); File::Path::rmtree($test_dir); exit $exit_code; } sub fail { print "FAILED: @_\n"; $exit_code = 1; exit 1; } sub get_num_of_log_entries { open FD, "access.log" or return 0; my @lines = (); close FD; return scalar @lines; } # Send the request to the 127.0.0.1:$port and return the reply sub req { my ($request, $inc, $timeout) = @_; my $sock = IO::Socket::INET->new(Proto=>"tcp", PeerAddr=>'127.0.0.1', PeerPort=>$port); fail("Cannot connect: $!") unless $sock; $sock->autoflush(1); foreach my $byte (split //, $request) { last unless print $sock $byte; select undef, undef, undef, .001 if length($request) < 256; } my ($out, $buf) = ('', ''); eval { alarm $timeout if $timeout; $out .= $buf while (sysread($sock, $buf, 1024) > 0); alarm 0 if $timeout; }; close $sock; $num_requests += defined($inc) ? $inc : 1; my $num_logs = get_num_of_log_entries(); unless ($num_requests == $num_logs) { fail("Request has not been logged: [$request], output: [$out]"); } return $out; } # Send the request. Compare with the expected reply. Fail if no match sub o { my ($request, $expected_reply, $message, $num_logs) = @_; print "==> $message ... "; my $reply = req($request, $num_logs); if ($reply =~ /$expected_reply/s) { print "OK\n"; } else { fail("Requested: [$request]\nExpected: [$expected_reply], got: [$reply]"); } } # Spawn a server listening on specified port sub spawn { my ($cmdline) = @_; print 'Executing: ', @_, "\n"; if (on_windows()) { my @args = split /\s+/, $cmdline; my $executable = $args[0]; $executable .= '.exe'; Win32::Spawn($executable, $cmdline, $pid); die "Cannot spawn @_: $!" unless $pid; } else { unless ($pid = fork()) { exec $cmdline; die "cannot exec [$cmdline]: $!\n"; } } sleep 1; } sub write_file { open FD, ">$_[0]" or fail "Cannot open $_[0]: $!"; binmode FD; print FD $_[1]; close FD; } sub read_file { open FD, $_[0] or fail "Cannot open $_[0]: $!"; my @lines = ; close FD; return join '', @lines; } sub kill_spawned_child { if (defined($pid)) { kill(9, $pid); waitpid($pid, 0); } } ####################################################### ENTRY POINT unlink @files_to_delete; $SIG{PIPE} = 'IGNORE'; $SIG{ALRM} = sub { die "timeout\n" }; #local $| =1; # Make sure we export only symbols that start with "mg_", and keep local # symbols static. if ($^O =~ /darwin|bsd|linux/) { my $out = `(cc -c mongoose.c && nm mongoose.o) | grep ' T '`; foreach (split /\n/, $out) { /T\s+_?mg_.+/ or fail("Exported symbol $_") } } if (scalar(@ARGV) > 0 and $ARGV[0] eq 'embedded') { do_embedded_test(); exit 0; } # Make sure we load config file if no options are given write_file($config, "listening_ports 12345\n"); spawn("$exe -a access.log"); my $saved_port = $port; $port = 12345; o("GET /test/hello.txt HTTP/1.0\n\n", 'HTTP/1.1 200 OK', 'Loading config file'); $port = $saved_port; unlink $config; kill_spawned_child(); # Spawn the server on port $port my $cmd = "$exe -listening_ports $port -access_log_file access.log ". "-error_log_file debug.log ". "-cgi_environment CGI_FOO=foo,CGI_BAR=bar,CGI_BAZ=baz " . "-extra_mime_types .bar=foo/bar,.tar.gz=blah,.baz=foo " . '-put_delete_passwords_file test/passfile ' . '-access_control_list -0.0.0.0/0,+127.0.0.1 ' . "-document_root $root,/aiased=/etc/,/ta=$test_dir"; $cmd .= ' -cgi_interpreter perl' if on_windows(); spawn($cmd); # Try to overflow: Send very long request req('POST ' . '/..' x 100 . 'ABCD' x 3000 . "\n\n", 0); # don't log this one o("GET /hello.txt HTTP/1.0\n\n", 'HTTP/1.1 200 OK', 'GET regular file'); o("GET /hello.txt HTTP/1.0\n\n", 'Content-Length: 17\s', 'GET regular file Content-Length'); o("GET /%68%65%6c%6c%6f%2e%74%78%74 HTTP/1.0\n\n", 'HTTP/1.1 200 OK', 'URL-decoding'); # Break CGI reading after 1 second. We must get full output. # Since CGI script does sleep, we sleep as well and increase request count # manually. my $slow_cgi_reply; print "==> Slow CGI output ... "; fail('Slow CGI output forward reply=', $slow_cgi_reply) unless ($slow_cgi_reply = req("GET /timeout.cgi HTTP/1.0\r\n\r\n", 0, 1)) =~ /Some data/s; print "OK\n"; sleep 3; $num_requests++; # '+' in URI must not be URL-decoded to space write_file("$root/a+.txt", ''); o("GET /a+.txt HTTP/1.0\n\n", 'HTTP/1.1 200 OK', 'URL-decoding, + in URI'); #o("GET /hh HTTP/1.0\n\n", 'HTTP/1.1 200 OK', 'GET admin URI'); # Test HTTP version parsing o("GET / HTTPX/1.0\r\n\r\n", '400 Bad Request', 'Bad HTTP Version', 0); o("GET / HTTP/x.1\r\n\r\n", '505 HTTP', 'Bad HTTP maj Version'); o("GET / HTTP/1.1z\r\n\r\n", '505 HTTP', 'Bad HTTP min Version'); o("GET / HTTP/02.0\r\n\r\n", '505 HTTP version not supported', 'HTTP Version >1.1'); # File with leading single dot o("GET /.leading.dot.txt HTTP/1.0\n\n", 'abc123', 'Leading dot 1'); o("GET /...leading.dot.txt HTTP/1.0\n\n", 'abc123', 'Leading dot 2'); o("GET /../\\\\/.//...leading.dot.txt HTTP/1.0\n\n", 'abc123', 'Leading dot 3'); o("GET .. HTTP/1.0\n\n", '400 Bad Request', 'Leading dot 4', 0); mkdir $test_dir unless -d $test_dir; o("GET /$test_dir_uri/not_exist HTTP/1.0\n\n", 'HTTP/1.1 404', 'PATH_INFO loop problem'); o("GET /$test_dir_uri HTTP/1.0\n\n", 'HTTP/1.1 301', 'Directory redirection'); o("GET /$test_dir_uri/ HTTP/1.0\n\n", 'Modified', 'Directory listing'); write_file("$test_dir/index.html", "tralala"); o("GET /$test_dir_uri/ HTTP/1.0\n\n", 'tralala', 'Index substitution'); o("GET / HTTP/1.0\n\n", 'embed.c', 'Directory listing - file name'); o("GET /ta/ HTTP/1.0\n\n", 'Modified', 'Aliases'); o("GET /not-exist HTTP/1.0\r\n\n", 'HTTP/1.1 404', 'Not existent file'); mkdir $test_dir . $dir_separator . 'x'; my $path = $test_dir . $dir_separator . 'x' . $dir_separator . 'index.cgi'; write_file($path, read_file($root . $dir_separator . 'env.cgi')); chmod 0755, $path; o("GET /$test_dir_uri/x/ HTTP/1.0\n\n", "Content-Type: text/html\r\n\r\n", 'index.cgi execution'); o("GET /$test_dir_uri/x/ HTTP/1.0\n\n", "SCRIPT_FILENAME=test/test_dir/x/index.cgi", 'SCRIPT_FILENAME'); o("GET /ta/x/ HTTP/1.0\n\n", "SCRIPT_NAME=/ta/x/index.cgi", 'Aliases SCRIPT_NAME'); #o("GET /hello.txt HTTP/1.1\n\n GET /hello.txt HTTP/1.0\n\n", # 'HTTP/1.1 200.+keep-alive.+HTTP/1.1 200.+close', # 'Request pipelining', 2); o("GET * HTTP/1.0\n\n", "^HTTP/1.1 404", '* URI'); my $mime_types = { html => 'text/html', htm => 'text/html', txt => 'text/plain', unknown_extension => 'text/plain', js => 'application/x-javascript', css => 'text/css', jpg => 'image/jpeg', c => 'text/plain', 'tar.gz' => 'blah', bar => 'foo/bar', baz => 'foo', }; foreach my $key (keys %$mime_types) { my $filename = "_mime_file_test.$key"; write_file("$root/$filename", ''); o("GET /$filename HTTP/1.0\n\n", "Content-Type: $mime_types->{$key}", ".$key mime type"); unlink "$root/$filename"; } # Get binary file and check the integrity my $binary_file = 'binary_file'; my $f2 = ''; foreach (0..123456) { $f2 .= chr(int(rand() * 255)); } write_file("$root/$binary_file", $f2); my $f1 = req("GET /$binary_file HTTP/1.0\r\n\n"); while ($f1 =~ /^.*\r\n/) { $f1 =~ s/^.*\r\n// } $f1 eq $f2 or fail("Integrity check for downloaded binary file"); my $range_request = "GET /hello.txt HTTP/1.1\nConnection: close\n". "Range: bytes=3-5\r\n\r\n"; o($range_request, '206 Partial Content', 'Range: 206 status code'); o($range_request, 'Content-Length: 3\s', 'Range: Content-Length'); o($range_request, 'Content-Range: bytes 3-5/17', 'Range: Content-Range'); o($range_request, '\nple$', 'Range: body content'); # Test directory sorting. Sleep between file creation for 1.1 seconds, # to make sure modification time are different. mkdir "$test_dir/sort"; write_file("$test_dir/sort/11", 'xx'); select undef, undef, undef, 1.1; write_file("$test_dir/sort/aa", 'xxxx'); select undef, undef, undef, 1.1; write_file("$test_dir/sort/bb", 'xxx'); select undef, undef, undef, 1.1; write_file("$test_dir/sort/22", 'x'); o("GET /$test_dir_uri/sort/?n HTTP/1.0\n\n", '200 OK.+>11<.+>22<.+>aa<.+>bb<', 'Directory listing (name, ascending)'); o("GET /$test_dir_uri/sort/?nd HTTP/1.0\n\n", '200 OK.+>bb<.+>aa<.+>22<.+>11<', 'Directory listing (name, descending)'); o("GET /$test_dir_uri/sort/?s HTTP/1.0\n\n", '200 OK.+>22<.+>11<.+>bb<.+>aa<', 'Directory listing (size, ascending)'); o("GET /$test_dir_uri/sort/?sd HTTP/1.0\n\n", '200 OK.+>aa<.+>bb<.+>11<.+>22<', 'Directory listing (size, descending)'); o("GET /$test_dir_uri/sort/?d HTTP/1.0\n\n", '200 OK.+>11<.+>aa<.+>bb<.+>22<', 'Directory listing (modification time, ascending)'); o("GET /$test_dir_uri/sort/?dd HTTP/1.0\n\n", '200 OK.+>22<.+>bb<.+>aa<.+>11<', 'Directory listing (modification time, descending)'); unless (scalar(@ARGV) > 0 and $ARGV[0] eq "basic_tests") { # Check that .htpasswd file existence trigger authorization write_file("$root/.htpasswd", 'user with space, " and comma:mydomain.com:5deda12442309cbdcdffc6b2737a894f'); o("GET /hello.txt HTTP/1.1\n\n", '401 Unauthorized', '.htpasswd - triggering auth on file request'); o("GET / HTTP/1.1\n\n", '401 Unauthorized', '.htpasswd - triggering auth on directory request'); # Test various funky things in an authentication header. o("GET /hello.txt HTTP/1.0\nAuthorization: Digest eq== empty=\"\", empty2=, quoted=\"blah foo bar, baz\\\"\\\" more\\\"\", unterminatedquoted=\" doesn't stop\n\n", '401 Unauthorized', 'weird auth values should not cause crashes'); my $auth_header = "Digest username=\"user with space, \\\" and comma\", ". "realm=\"mydomain.com\", nonce=\"1291376417\", uri=\"/\",". "response=\"e8dec0c2a1a0c8a7e9a97b4b5ea6a6e6\", qop=auth, nc=00000001, cnonce=\"1a49b53a47a66e82\""; o("GET /hello.txt HTTP/1.0\nAuthorization: $auth_header\n\n", 'HTTP/1.1 200 OK', 'GET regular file with auth'); unlink "$root/.htpasswd"; o("GET /env.cgi HTTP/1.0\n\r\n", 'HTTP/1.1 200 OK', 'GET CGI file'); o("GET /sh.cgi HTTP/1.0\n\r\n", 'shell script CGI', 'GET sh CGI file') unless on_windows(); o("GET /env.cgi?var=HELLO HTTP/1.0\n\n", 'QUERY_STRING=var=HELLO', 'QUERY_STRING wrong'); o("POST /env.cgi HTTP/1.0\r\nContent-Length: 9\r\n\r\nvar=HELLO", 'var=HELLO', 'CGI POST wrong'); o("POST /env.cgi HTTP/1.0\r\nContent-Length: 9\r\n\r\nvar=HELLO", '\x0aCONTENT_LENGTH=9', 'Content-Length not being passed to CGI'); o("GET /env.cgi HTTP/1.0\nMy-HdR: abc\n\r\n", 'HTTP_MY_HDR=abc', 'HTTP_* env'); o("GET /env.cgi HTTP/1.0\n\r\nSOME_TRAILING_DATA_HERE", 'HTTP/1.1 200 OK', 'GET CGI with trailing data'); o("GET /env.cgi%20 HTTP/1.0\n\r\n", 'HTTP/1.1 404', 'CGI Win32 code disclosure (%20)'); o("GET /env.cgi%ff HTTP/1.0\n\r\n", 'HTTP/1.1 404', 'CGI Win32 code disclosure (%ff)'); o("GET /env.cgi%2e HTTP/1.0\n\r\n", 'HTTP/1.1 404', 'CGI Win32 code disclosure (%2e)'); o("GET /env.cgi%2b HTTP/1.0\n\r\n", 'HTTP/1.1 404', 'CGI Win32 code disclosure (%2b)'); o("GET /env.cgi HTTP/1.0\n\r\n", '\nHTTPS=off\n', 'CGI HTTPS'); o("GET /env.cgi HTTP/1.0\n\r\n", '\nCGI_FOO=foo\n', '-cgi_env 1'); o("GET /env.cgi HTTP/1.0\n\r\n", '\nCGI_BAR=bar\n', '-cgi_env 2'); o("GET /env.cgi HTTP/1.0\n\r\n", '\nCGI_BAZ=baz\n', '-cgi_env 3'); # Check that CGI's current directory is set to script's directory my $copy_cmd = on_windows() ? 'copy' : 'cp'; system("$copy_cmd $root" . $dir_separator . "env.cgi $test_dir" . $dir_separator . 'env.cgi'); o("GET /$test_dir_uri/env.cgi HTTP/1.0\n\n", "CURRENT_DIR=.*$root/$test_dir_uri", "CGI chdir()"); # SSI tests o("GET /ssi1.shtml HTTP/1.0\n\n", 'ssi_begin.+CFLAGS.+ssi_end', 'SSI #include file='); o("GET /ssi2.shtml HTTP/1.0\n\n", 'ssi_begin.+Unit test.+ssi_end', 'SSI #include virtual='); my $ssi_exec = on_windows() ? 'ssi4.shtml' : 'ssi3.shtml'; o("GET /$ssi_exec HTTP/1.0\n\n", 'ssi_begin.+Makefile.+ssi_end', 'SSI #exec'); my $abs_path = on_windows() ? 'ssi6.shtml' : 'ssi5.shtml'; my $word = on_windows() ? 'boot loader' : 'root'; o("GET /$abs_path HTTP/1.0\n\n", "ssi_begin.+$word.+ssi_end", 'SSI #include file= (absolute)'); o("GET /ssi7.shtml HTTP/1.0\n\n", 'ssi_begin.+Unit test.+ssi_end', 'SSI #include "..."'); o("GET /ssi8.shtml HTTP/1.0\n\n", 'ssi_begin.+CFLAGS.+ssi_end', 'SSI nested #includes'); # Manipulate the passwords file my $path = 'test_htpasswd'; unlink $path; system("$exe -A $path a b c") == 0 or fail("Cannot add user in a passwd file"); system("$exe -A $path a b c2") == 0 or fail("Cannot edit user in a passwd file"); my $content = read_file($path); $content =~ /^b:a:\w+$/gs or fail("Bad content of the passwd file"); unlink $path; do_PUT_test(); kill_spawned_child(); do_embedded_test(); } sub do_PUT_test { # This only works because mongoose currently doesn't look at the nonce. # It should really be rejected... my $auth_header = "Authorization: Digest username=guest, ". "realm=mydomain.com, nonce=1145872809, uri=/put.txt, ". "response=896327350763836180c61d87578037d9, qop=auth, ". "nc=00000002, cnonce=53eddd3be4e26a98\n"; o("PUT /put.txt HTTP/1.0\nContent-Length: 7\n$auth_header\n1234567", "HTTP/1.1 201 OK", 'PUT file, status 201'); fail("PUT content mismatch") unless read_file("$root/put.txt") eq '1234567'; o("PUT /put.txt HTTP/1.0\nContent-Length: 4\n$auth_header\nabcd", "HTTP/1.1 200 OK", 'PUT file, status 200'); fail("PUT content mismatch") unless read_file("$root/put.txt") eq 'abcd'; o("PUT /put.txt HTTP/1.0\n$auth_header\nabcd", "HTTP/1.1 411 Length Required", 'PUT 411 error'); o("PUT /put.txt HTTP/1.0\nExpect: blah\nContent-Length: 1\n". "$auth_header\nabcd", "HTTP/1.1 417 Expectation Failed", 'PUT 417 error'); o("PUT /put.txt HTTP/1.0\nExpect: 100-continue\nContent-Length: 4\n". "$auth_header\nabcd", "HTTP/1.1 100 Continue.+HTTP/1.1 200", 'PUT 100-Continue'); } sub do_embedded_test { my $cmd = "cc -W -Wall -o $embed_exe $root/embed.c mongoose.c -I. ". "-pthread -DNO_SSL -DLISTENING_PORT=\\\"$port\\\""; if (on_windows()) { $cmd = "cl $root/embed.c mongoose.c /I. /nologo /DNO_SSL ". "/DLISTENING_PORT=\\\"$port\\\" /link /out:$embed_exe.exe ws2_32.lib "; } print $cmd, "\n"; system($cmd) == 0 or fail("Cannot compile embedded unit test"); spawn("./$embed_exe"); o("GET /test_get_header HTTP/1.0\nHost: blah\n\n", 'Value: \[blah\]', 'mg_get_header', 0); o("GET /test_get_var?a=b&my_var=foo&c=d HTTP/1.0\n\n", 'Value: \[foo\]', 'mg_get_var 1', 0); o("GET /test_get_var?my_var=foo&c=d HTTP/1.0\n\n", 'Value: \[foo\]', 'mg_get_var 2', 0); o("GET /test_get_var?a=b&my_var=foo HTTP/1.0\n\n", 'Value: \[foo\]', 'mg_get_var 3', 0); o("POST /test_get_var HTTP/1.0\nContent-Length: 10\n\n". "my_var=foo", 'Value: \[foo\]', 'mg_get_var 4', 0); o("POST /test_get_var HTTP/1.0\nContent-Length: 18\n\n". "a=b&my_var=foo&c=d", 'Value: \[foo\]', 'mg_get_var 5', 0); o("POST /test_get_var HTTP/1.0\nContent-Length: 14\n\n". "a=b&my_var=foo", 'Value: \[foo\]', 'mg_get_var 6', 0); o("GET /test_get_var?a=one%2btwo&my_var=foo& HTTP/1.0\n\n", 'Value: \[foo\]', 'mg_get_var 7', 0); o("GET /test_get_var?my_var=one%2btwo&b=two%2b HTTP/1.0\n\n", 'Value: \[one\+two\]', 'mg_get_var 8', 0); # + in form data MUST be decoded to space o("POST /test_get_var HTTP/1.0\nContent-Length: 10\n\n". "my_var=b+c", 'Value: \[b c\]', 'mg_get_var 9', 0); # Test that big POSTed vars are not truncated my $my_var = 'x' x 64000; o("POST /test_get_var HTTP/1.0\nContent-Length: 64007\n\n". "my_var=$my_var", 'Value size: \[64000\]', 'mg_get_var 10', 0); # Other methods should also work o("PUT /test_get_var HTTP/1.0\nContent-Length: 10\n\n". "my_var=foo", 'Value: \[foo\]', 'mg_get_var 11', 0); o("POST /test_get_request_info?xx=yy HTTP/1.0\nFoo: bar\n". "Content-Length: 3\n\na=b", 'Method: \[POST\].URI: \[/test_get_request_info\].'. 'HTTP version: \[1.0\].HTTP header \[Foo\]: \[bar\].'. 'HTTP header \[Content-Length\]: \[3\].'. 'Query string: \[xx=yy\].'. 'Remote IP: \[\d+\].Remote port: \[\d+\].'. 'Remote user: \[\]' , 'request_info', 0); o("GET /not_exist HTTP/1.0\n\n", 'Error: \[404\]', '404 handler', 0); o("bad request\n\n", 'Error: \[400\]', '* error handler', 0); # o("GET /foo/secret HTTP/1.0\n\n", # '401 Unauthorized', 'mg_protect_uri', 0); # o("GET /foo/secret HTTP/1.0\nAuthorization: Digest username=bill\n\n", # '401 Unauthorized', 'mg_protect_uri (bill)', 0); # o("GET /foo/secret HTTP/1.0\nAuthorization: Digest username=joe\n\n", # '200 OK', 'mg_protect_uri (joe)', 0); kill_spawned_child(); } print "SUCCESS! All tests passed.\n"; MSVMpack1.2/mongoose/test/env.cgi0000755000175000017500000000140111557453204016010 0ustar lauerlauer#!/usr/bin/env perl use Cwd; use CGI; use vars '%in'; CGI::ReadParse(); print "Content-Type: text/html\r\n\r\n"; print "
\n";
foreach my $key (sort keys %ENV) {
	print "$key=$ENV{$key}\n";
}

print "\n";

foreach my $key (sort keys %in) {
	print "$key=$in{$key}\n";
}

print "\n";

#sleep 10;

print 'CURRENT_DIR=' . getcwd() . "\n";
print "
\n"; my $stuff = < function set_val() { }
EOP system('some shit'); #print STDERR "fuck!!!\n\n"; print $stuff; MSVMpack1.2/mongoose/test/ssi6.shtml0000644000175000017500000000012511557453204016470 0ustar lauerlauer
ssi_begin

ssi_end
MSVMpack1.2/mongoose/test/embed.c0000644000175000017500000001332211557453204015756 0ustar lauerlauer// Copyright (c) 2004-2009 Sergey Lyubka // // 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. // // Unit test for the mongoose web server. Tests embedded API. #include #include #include #ifndef _WIN32 #include #endif #include "mongoose.h" #if !defined(LISTENING_PORT) #define LISTENING_PORT "23456" #endif static const char *standard_reply = "HTTP/1.1 200 OK\r\n" "Content-Type: text/plain\r\n" "Connection: close\r\n\r\n"; static void test_get_var(struct mg_connection *conn, const struct mg_request_info *ri) { char *var, *buf; size_t buf_len; const char *cl; int var_len; mg_printf(conn, "%s", standard_reply); buf_len = 0; var = buf = NULL; cl = mg_get_header(conn, "Content-Length"); mg_printf(conn, "cl: %p\n", cl); if ((!strcmp(ri->request_method, "POST") || !strcmp(ri->request_method, "PUT")) && cl != NULL) { buf_len = atoi(cl); buf = malloc(buf_len); /* Read in two pieces, to test continuation */ if (buf_len > 2) { mg_read(conn, buf, 2); mg_read(conn, buf + 2, buf_len - 2); } else { mg_read(conn, buf, buf_len); } } else if (ri->query_string != NULL) { buf_len = strlen(ri->query_string); buf = malloc(buf_len + 1); strcpy(buf, ri->query_string); } var = malloc(buf_len + 1); var_len = mg_get_var(buf, buf_len, "my_var", var, buf_len + 1); mg_printf(conn, "Value: [%s]\n", var); mg_printf(conn, "Value size: [%d]\n", var_len); free(buf); free(var); } static void test_get_header(struct mg_connection *conn, const struct mg_request_info *ri) { const char *value; int i; mg_printf(conn, "%s", standard_reply); printf("HTTP headers: %d\n", ri->num_headers); for (i = 0; i < ri->num_headers; i++) { printf("[%s]: [%s]\n", ri->http_headers[i].name, ri->http_headers[i].value); } value = mg_get_header(conn, "Host"); if (value != NULL) { mg_printf(conn, "Value: [%s]", value); } } static void test_get_request_info(struct mg_connection *conn, const struct mg_request_info *ri) { int i; mg_printf(conn, "%s", standard_reply); mg_printf(conn, "Method: [%s]\n", ri->request_method); mg_printf(conn, "URI: [%s]\n", ri->uri); mg_printf(conn, "HTTP version: [%s]\n", ri->http_version); for (i = 0; i < ri->num_headers; i++) { mg_printf(conn, "HTTP header [%s]: [%s]\n", ri->http_headers[i].name, ri->http_headers[i].value); } mg_printf(conn, "Query string: [%s]\n", ri->query_string ? ri->query_string: ""); mg_printf(conn, "Remote IP: [%lu]\n", ri->remote_ip); mg_printf(conn, "Remote port: [%d]\n", ri->remote_port); mg_printf(conn, "Remote user: [%s]\n", ri->remote_user ? ri->remote_user : ""); } static void test_error(struct mg_connection *conn, const struct mg_request_info *ri) { mg_printf(conn, "HTTP/1.1 %d XX\r\n" "Conntection: close\r\n\r\n", ri->status_code); mg_printf(conn, "Error: [%d]", ri->status_code); } static void test_post(struct mg_connection *conn, const struct mg_request_info *ri) { const char *cl; char *buf; int len; mg_printf(conn, "%s", standard_reply); if (strcmp(ri->request_method, "POST") == 0 && (cl = mg_get_header(conn, "Content-Length")) != NULL) { len = atoi(cl); if ((buf = malloc(len)) != NULL) { mg_write(conn, buf, len); free(buf); } } } static const struct test_config { enum mg_event event; const char *uri; void (*func)(struct mg_connection *, const struct mg_request_info *); } test_config[] = { {MG_NEW_REQUEST, "/test_get_header", &test_get_header}, {MG_NEW_REQUEST, "/test_get_var", &test_get_var}, {MG_NEW_REQUEST, "/test_get_request_info", &test_get_request_info}, {MG_NEW_REQUEST, "/test_post", &test_post}, {MG_HTTP_ERROR, "", &test_error}, {0, NULL, NULL} }; static void *callback(enum mg_event event, struct mg_connection *conn, const struct mg_request_info *request_info) { int i; for (i = 0; test_config[i].uri != NULL; i++) { if (event == test_config[i].event && (event == MG_HTTP_ERROR || !strcmp(request_info->uri, test_config[i].uri))) { test_config[i].func(conn, request_info); return "processed"; } } return NULL; } int main(void) { struct mg_context *ctx; const char *options[] = {"listening_ports", LISTENING_PORT, NULL}; ctx = mg_start(callback, NULL, options); pause(); return 0; } MSVMpack1.2/mongoose/test/timeout.cgi0000755000175000017500000000052011557453204016707 0ustar lauerlauer#!/usr/bin/env perl # Make stdout unbuffered use FileHandle; STDOUT->autoflush(1); # This script outputs some content, then sleeps for 5 seconds, then exits. # Web server should return the content immediately after it is sent, # not waiting until the script exits. print "Content-Type: text/html\r\n\r\n"; print "Some data"; sleep 3; MSVMpack1.2/mongoose/test/hello.cgi0000755000175000017500000000010411557453204016322 0ustar lauerlauer#!/bin/sh echo "Content-Type: text/plain" echo echo $QUERY_STRING MSVMpack1.2/mongoose/test/test_all_build_flags.pl0000644000175000017500000000142411557453204021235 0ustar lauerlauer#!/usr/bin/env perl @flags = ("NO_SSI", "NO_SSL", "NDEBUG", "DEBUG", "NO_CGI"); my $num_flags = @flags; sub fail { print "FAILED: @_\n"; exit 1; } my $platform = $ARGV[0] || "linux"; for (my $i = 0; $i < 2 ** $num_flags; $i++) { my $bitmask = sprintf("%*.*b", $num_flags, $num_flags, $i); my @combination = (); for (my $j = 0; $j < $num_flags; $j++) { push @combination, $flags[$j] if substr($bitmask, $j, 1); } my $defines = join(" ", map { "-D$_" } @combination); my $cmd = "CFLAGS=\"$defines\" make clean $platform >/dev/null"; system($cmd) == 0 or fail "build failed: $_"; print "Build succeeded, flags: [$defines]\n"; system("perl test/test.pl basic_tests >/dev/null") == 0 or fail "basic tests"; print "Basic tests: OK\n"; } print "PASS: All builds passed!\n"; MSVMpack1.2/mongoose/test/ssi2.shtml0000644000175000017500000000012411557453204016463 0ustar lauerlauer
ssi_begin

ssi_end
MSVMpack1.2/mongoose/test/ssi8.shtml0000644000175000017500000000003611557453204016473 0ustar lauerlauer MSVMpack1.2/mongoose/examples/0000755000175000017500000000000012104711130015354 5ustar lauerlauerMSVMpack1.2/mongoose/examples/ssl_cert.pem0000644000175000017500000000566011557453204017724 0ustar lauerlauer-----BEGIN RSA PRIVATE KEY----- MIIEogIBAAKCAQEAwONaLOP7EdegqjRuQKSDXzvHmFMZfBufjhELhNjo5KsL4ieH hMSGCcSV6y32hzhqR5lvTViaQez+xhc58NZRu+OUgEhodRBW/vAOjpz/xdMz5HaC EhP3E9W1pkitVseS8B5rrgJo1BfCGai1fPav1nutPq2Kj7vMy24+g460Lonf6ln1 di4aTIRtAqXtUU6RFpPJP35PkCXbTK65O8HJSxxt/XtfoezHCU5+UIwmZGYx46UB Wzg3IfK6bGPSiHU3pdiTol0uMPt/GUK+x4NyZJ4/ImsNAicRwMBdja4ywHKXJehH gXBthsVIHbL21x+4ibsg9eVM/XioTV6tW3IrdwIDAQABAoIBACFfdLutmkQFBcRN HAJNNHmmsyr0vcUOVnXTFyYeDXV67qxrYHQlOHe6LqIpKq1Mon7O2kYMnWvooFAP trOnsS6L+qaTYJdYg2TKjgo4ubw1hZXytyB/mdExuaMSkgMgtpia+tB5lD+V+LxN x1DesZ+veFMO3Zluyckswt4qM5yVa04YFrt31H0E1rJfIen61lidXIKYmHHWuRxK SadjFfbcqJ6P9ZF22BOkleg5Fm5NaxJmyQynOWaAkSZa5w1XySFfRjRfsbDr64G6 +LSG8YtRuvfxnvUNhynVPHcpE40eiPo6v8Ho6yZKXpV5klCKciodXAORsswSoGJa N3nnu/ECgYEA6Yb2rM3QUEPIALdL8f/OzZ1GBSdiQB2WSAxzl9pR/dLF2H+0pitS to0830mk92ppVmRVD3JGxYDRZQ56tlFXyGaCzJBMRIcsotAhBoNbjV0i9n5bLJYf BmjU9yvWcgsTt0tr3B0FrtYyp2tCvwHqlxvFpFdUCj2oRw2uGpkhmNkCgYEA03M6 WxFhsix3y6eVCVvShfbLBSOqp8l0qiTEty+dgVQcWN4CO/5eyaZXKxlCG9KMmKxy Yx+YgxZrDhfaZ0cxhHGPRKEAxM3IKwT2C8/wCaSiLWXZZpTifnSD99vtOt4wEfrG +AghNd5kamFiM9tU0AyvhJc2vdJFuXrfeC7ntM8CgYBGDA+t4cZcbRhu7ow/OKYF kulP3nJgHP/Y+LMrl3cEldZ2jEfZmCElVNQvfd2XwTl7injhOzvzPiKRF3jDez7D g8w0JAxceddvttJRK9GoY4l7OoeKpjUELSnEQkf+yUfOsTbXPXVY7jMfeNL6jE6b qN7t3qv8rmXtejMBE3G6cQKBgGR5W2BMiRSlxqKx1cKlrApV87BUe1HRCyuR3xuA d6Item7Lx1oEi7vb242yKdSYnpApWQ06xTh83Y/Ly87JaIEbiM0+h+P8OEIg0F1a iB+86AcUX1I8KseVy+Np0HbpfwP8GrFfA5DaRPK7pXMopEtby8cAJ1XZZaI1/ZvZ BebHAoGAcQU9WvCkT+nIp9FpXfBybYUsvgkaizMIqp66/l3GYgYAq8p1VLGvN4v5 ec0dW58SJrCpqsM3NP78DtEzQf9OOsk+FsjBFzDU2RkeUreyt2/nQBj/2mN/+hEy hYN0Zii2yTb63jGxKY6gH1R/r9dL8kXaJmcZrfSa3AgywnteJWg= -----END RSA PRIVATE KEY----- -----BEGIN CERTIFICATE----- MIIDBjCCAe4CCQCX05m0b053QzANBgkqhkiG9w0BAQQFADBFMQswCQYDVQQGEwJB VTETMBEGA1UECBMKU29tZS1TdGF0ZTEhMB8GA1UEChMYSW50ZXJuZXQgV2lkZ2l0 cyBQdHkgTHRkMB4XDTA4MTIwNzEwMjUyMloXDTE4MTIwNTEwMjUyMlowRTELMAkG A1UEBhMCQVUxEzARBgNVBAgTClNvbWUtU3RhdGUxITAfBgNVBAoTGEludGVybmV0 IFdpZGdpdHMgUHR5IEx0ZDCCASIwDQYJKoZIhvcNAQEBBQADggEPADCCAQoCggEB AMDjWizj+xHXoKo0bkCkg187x5hTGXwbn44RC4TY6OSrC+Inh4TEhgnElest9oc4 akeZb01YmkHs/sYXOfDWUbvjlIBIaHUQVv7wDo6c/8XTM+R2ghIT9xPVtaZIrVbH kvAea64CaNQXwhmotXz2r9Z7rT6tio+7zMtuPoOOtC6J3+pZ9XYuGkyEbQKl7VFO kRaTyT9+T5Al20yuuTvByUscbf17X6HsxwlOflCMJmRmMeOlAVs4NyHyumxj0oh1 N6XYk6JdLjD7fxlCvseDcmSePyJrDQInEcDAXY2uMsBylyXoR4FwbYbFSB2y9tcf uIm7IPXlTP14qE1erVtyK3cCAwEAATANBgkqhkiG9w0BAQQFAAOCAQEAW4yZdqpB oIdiuXRosr86Sg9FiMg/cn+2OwQ0QIaA8ZBwKsc+wIIHEgXCS8J6316BGQeUvMD+ plNe0r4GWzzmlDMdobeQ5arPRB89qd9skE6pAMdLg3FyyfEjz3A0VpskolW5VBMr P5R7uJ1FLgH12RyAjZCWYcCRqEMOffqvyMCH6oAjyDmQOA5IssRKX/HsHntSH/HW W7slTcP45ty1b44Nq22/ubYk0CJRQgqKOIQ3cLgPomN1jNFQbAbfVTaK1DpEysrQ 5V8a8gNW+3sVZmV6d1Mj3pN2Le62wUKuV2g6BNU7iiwcoY8HI68aRxz2hVMS+t5f SEGI4JSxV56lYg== -----END CERTIFICATE----- -----BEGIN DH PARAMETERS----- MEYCQQD+ef8hZ4XbdoyIpJyCTF2UrUEfX6mYDvxuS5O1UNYcslUqlj6JkA11e/yS 6DK8Z86W6mSj5CEk4IjbyEOECXH7AgEC -----END DH PARAMETERS----- MSVMpack1.2/mongoose/examples/chat.c0000644000175000017500000003173111557453204016464 0ustar lauerlauer/* * This file is part of the Mongoose project, http://code.google.com/p/mongoose * It implements an online chat server. For more details, * see the documentation on the project web site. * To test the application, * 1. type "make" in the directory where this file lives * 2. point your browser to http://127.0.0.1:8081 * * NOTE(lsm): this file follows Google style, not BSD style as the rest of * Mongoose code. */ #include #include #include #include #include #include #include #include "mongoose.h" #define MAX_USER_LEN 20 #define MAX_MESSAGE_LEN 100 #define MAX_MESSAGES 5 #define MAX_SESSIONS 2 #define SESSION_TTL 120 static const char *authorize_url = "/authorize"; static const char *login_url = "/login.html"; static const char *ajax_reply_start = "HTTP/1.1 200 OK\r\n" "Cache: no-cache\r\n" "Content-Type: application/x-javascript\r\n" "\r\n"; // Describes single message sent to a chat. If user is empty (0 length), // the message is then originated from the server itself. struct message { long id; // Message ID char user[MAX_USER_LEN]; // User that have sent the message char text[MAX_MESSAGE_LEN]; // Message text time_t timestamp; // Message timestamp, UTC }; // Describes web session. struct session { char session_id[33]; // Session ID, must be unique char random[20]; // Random data used for extra user validation char user[MAX_USER_LEN]; // Authenticated user time_t expire; // Expiration timestamp, UTC }; static struct message messages[MAX_MESSAGES]; // Ringbuffer for messages static struct session sessions[MAX_SESSIONS]; // Current sessions static long last_message_id; // Protects messages, sessions, last_message_id static pthread_rwlock_t rwlock = PTHREAD_RWLOCK_INITIALIZER; // Get session object for the connection. Caller must hold the lock. static struct session *get_session(const struct mg_connection *conn) { int i; char session_id[33]; time_t now = time(NULL); mg_get_cookie(conn, "session", session_id, sizeof(session_id)); for (i = 0; i < MAX_SESSIONS; i++) { if (sessions[i].expire != 0 && sessions[i].expire > now && strcmp(sessions[i].session_id, session_id) == 0) { break; } } return i == MAX_SESSIONS ? NULL : &sessions[i]; } static void get_qsvar(const struct mg_request_info *request_info, const char *name, char *dst, size_t dst_len) { const char *qs = request_info->query_string; mg_get_var(qs, strlen(qs == NULL ? "" : qs), name, dst, dst_len); } // Get a get of messages with IDs greater than last_id and transform them // into a JSON string. Return that string to the caller. The string is // dynamically allocated, caller must free it. If there are no messages, // NULL is returned. static char *messages_to_json(long last_id) { const struct message *message; int max_msgs, len; char buf[sizeof(messages)]; // Large enough to hold all messages // Read-lock the ringbuffer. Loop over all messages, making a JSON string. pthread_rwlock_rdlock(&rwlock); len = 0; max_msgs = sizeof(messages) / sizeof(messages[0]); // If client is too far behind, return all messages. if (last_message_id - last_id > max_msgs) { last_id = last_message_id - max_msgs; } for (; last_id < last_message_id; last_id++) { message = &messages[last_id % max_msgs]; if (message->timestamp == 0) { break; } // buf is allocated on stack and hopefully is large enough to hold all // messages (it may be too small if the ringbuffer is full and all // messages are large. in this case asserts will trigger). len += snprintf(buf + len, sizeof(buf) - len, "{user: '%s', text: '%s', timestamp: %lu, id: %lu},", message->user, message->text, message->timestamp, message->id); assert(len > 0); assert((size_t) len < sizeof(buf)); } pthread_rwlock_unlock(&rwlock); return len == 0 ? NULL : strdup(buf); } // If "callback" param is present in query string, this is JSONP call. // Return 1 in this case, or 0 if "callback" is not specified. // Wrap an output in Javascript function call. static int handle_jsonp(struct mg_connection *conn, const struct mg_request_info *request_info) { char cb[64]; get_qsvar(request_info, "callback", cb, sizeof(cb)); if (cb[0] != '\0') { mg_printf(conn, "%s(", cb); } return cb[0] == '\0' ? 0 : 1; } // A handler for the /ajax/get_messages endpoint. // Return a list of messages with ID greater than requested. static void ajax_get_messages(struct mg_connection *conn, const struct mg_request_info *request_info) { char last_id[32], *json; int is_jsonp; mg_printf(conn, "%s", ajax_reply_start); is_jsonp = handle_jsonp(conn, request_info); get_qsvar(request_info, "last_id", last_id, sizeof(last_id)); if ((json = messages_to_json(strtoul(last_id, NULL, 10))) != NULL) { mg_printf(conn, "[%s]", json); free(json); } if (is_jsonp) { mg_printf(conn, "%s", ")"); } } // Allocate new message. Caller must hold the lock. static struct message *new_message(void) { static int size = sizeof(messages) / sizeof(messages[0]); struct message *message = &messages[last_message_id % size]; message->id = last_message_id++; message->timestamp = time(0); return message; } static void my_strlcpy(char *dst, const char *src, size_t len) { strncpy(dst, src, len); dst[len - 1] = '\0'; } // A handler for the /ajax/send_message endpoint. static void ajax_send_message(struct mg_connection *conn, const struct mg_request_info *request_info) { struct message *message; struct session *session; char text[sizeof(message->text) - 1]; int is_jsonp; mg_printf(conn, "%s", ajax_reply_start); is_jsonp = handle_jsonp(conn, request_info); get_qsvar(request_info, "text", text, sizeof(text)); if (text[0] != '\0') { // We have a message to store. Write-lock the ringbuffer, // grab the next message and copy data into it. pthread_rwlock_wrlock(&rwlock); message = new_message(); // TODO(lsm): JSON-encode all text strings session = get_session(conn); assert(session != NULL); my_strlcpy(message->text, text, sizeof(text)); my_strlcpy(message->user, session->user, sizeof(message->user)); pthread_rwlock_unlock(&rwlock); } mg_printf(conn, "%s", text[0] == '\0' ? "false" : "true"); if (is_jsonp) { mg_printf(conn, "%s", ")"); } } // Redirect user to the login form. In the cookie, store the original URL // we came from, so that after the authorization we could redirect back. static void redirect_to_login(struct mg_connection *conn, const struct mg_request_info *request_info) { mg_printf(conn, "HTTP/1.1 302 Found\r\n" "Set-Cookie: original_url=%s\r\n" "Location: %s\r\n\r\n", request_info->uri, login_url); } // Return 1 if username/password is allowed, 0 otherwise. static int check_password(const char *user, const char *password) { // In production environment we should ask an authentication system // to authenticate the user. // Here however we do trivial check that user and password are not empty return (user[0] && password[0]); } // Allocate new session object static struct session *new_session(void) { int i; time_t now = time(NULL); pthread_rwlock_wrlock(&rwlock); for (i = 0; i < MAX_SESSIONS; i++) { if (sessions[i].expire == 0 || sessions[i].expire < now) { sessions[i].expire = time(0) + SESSION_TTL; break; } } pthread_rwlock_unlock(&rwlock); return i == MAX_SESSIONS ? NULL : &sessions[i]; } // Generate session ID. buf must be 33 bytes in size. // Note that it is easy to steal session cookies by sniffing traffic. // This is why all communication must be SSL-ed. static void generate_session_id(char *buf, const char *random, const char *user) { mg_md5(buf, random, user, NULL); } static void send_server_message(const char *fmt, ...) { va_list ap; struct message *message; pthread_rwlock_wrlock(&rwlock); message = new_message(); message->user[0] = '\0'; // Empty user indicates server message va_start(ap, fmt); vsnprintf(message->text, sizeof(message->text), fmt, ap); va_end(ap); pthread_rwlock_unlock(&rwlock); } // A handler for the /authorize endpoint. // Login page form sends user name and password to this endpoint. static void authorize(struct mg_connection *conn, const struct mg_request_info *request_info) { char user[MAX_USER_LEN], password[MAX_USER_LEN]; struct session *session; // Fetch user name and password. get_qsvar(request_info, "user", user, sizeof(user)); get_qsvar(request_info, "password", password, sizeof(password)); if (check_password(user, password) && (session = new_session()) != NULL) { // Authentication success: // 1. create new session // 2. set session ID token in the cookie // 3. remove original_url from the cookie - not needed anymore // 4. redirect client back to the original URL // // The most secure way is to stay HTTPS all the time. However, just to // show the technique, we redirect to HTTP after the successful // authentication. The danger of doing this is that session cookie can // be stolen and an attacker may impersonate the user. // Secure application must use HTTPS all the time. my_strlcpy(session->user, user, sizeof(session->user)); snprintf(session->random, sizeof(session->random), "%d", rand()); generate_session_id(session->session_id, session->random, session->user); send_server_message("<%s> joined", session->user); mg_printf(conn, "HTTP/1.1 302 Found\r\n" "Set-Cookie: session=%s; max-age=3600; http-only\r\n" // Session ID "Set-Cookie: user=%s\r\n" // Set user, needed by Javascript code "Set-Cookie: original_url=/; max-age=0\r\n" // Delete original_url "Location: /\r\n\r\n", session->session_id, session->user); } else { // Authentication failure, redirect to login. redirect_to_login(conn, request_info); } } // Return 1 if request is authorized, 0 otherwise. static int is_authorized(const struct mg_connection *conn, const struct mg_request_info *request_info) { struct session *session; char valid_id[33]; int authorized = 0; // Always authorize accesses to login page and to authorize URI if (!strcmp(request_info->uri, login_url) || !strcmp(request_info->uri, authorize_url)) { return 1; } pthread_rwlock_rdlock(&rwlock); if ((session = get_session(conn)) != NULL) { generate_session_id(valid_id, session->random, session->user); if (strcmp(valid_id, session->session_id) == 0) { session->expire = time(0) + SESSION_TTL; authorized = 1; } } pthread_rwlock_unlock(&rwlock); return authorized; } static void redirect_to_ssl(struct mg_connection *conn, const struct mg_request_info *request_info) { const char *p, *host = mg_get_header(conn, "Host"); if (host != NULL && (p = strchr(host, ':')) != NULL) { mg_printf(conn, "HTTP/1.1 302 Found\r\n" "Location: https://%.*s:8082/%s:8082\r\n\r\n", p - host, host, request_info->uri); } else { mg_printf(conn, "%s", "HTTP/1.1 500 Error\r\n\r\nHost: header is not set"); } } static void *event_handler(enum mg_event event, struct mg_connection *conn, const struct mg_request_info *request_info) { void *processed = "yes"; if (event == MG_NEW_REQUEST) { if (!request_info->is_ssl) { redirect_to_ssl(conn, request_info); } else if (!is_authorized(conn, request_info)) { redirect_to_login(conn, request_info); } else if (strcmp(request_info->uri, authorize_url) == 0) { authorize(conn, request_info); } else if (strcmp(request_info->uri, "/ajax/get_messages") == 0) { ajax_get_messages(conn, request_info); } else if (strcmp(request_info->uri, "/ajax/send_message") == 0) { ajax_send_message(conn, request_info); } else { // No suitable handler found, mark as not processed. Mongoose will // try to serve the request. processed = NULL; } } else { processed = NULL; } return processed; } static const char *options[] = { "document_root", "html", "listening_ports", "8081,8082s", "ssl_certificate", "ssl_cert.pem", "num_threads", "5", NULL }; int main(void) { struct mg_context *ctx; // Initialize random number generator. It will be used later on for // the session identifier creation. srand((unsigned) time(0)); // Setup and start Mongoose ctx = mg_start(&event_handler, NULL, options); assert(ctx != NULL); // Wait until enter is pressed, then exit printf("Chat server started on ports %s, press enter to quit.\n", mg_get_option(ctx, "listening_ports")); getchar(); mg_stop(ctx); printf("%s\n", "Chat server stopped."); return EXIT_SUCCESS; } // vim:ts=2:sw=2:et MSVMpack1.2/mongoose/examples/Makefile0000644000175000017500000000027211557453204017035 0ustar lauerlauerPROG= chat CFLAGS= -W -Wall -I.. -pthread -g all: OS=`uname`; \ test "$$OS" = Linux && LIBS="-ldl" ; \ $(CC) $(CFLAGS) chat.c ../mongoose.c $$LIBS $(ADD) -o $(PROG) ./$(PROG) MSVMpack1.2/mongoose/examples/html/0000755000175000017500000000000012104711130016320 5ustar lauerlauerMSVMpack1.2/mongoose/examples/html/favicon.ico0000644000175000017500000000257611557453204020473 0ustar lauerlauerh( œxQÿÿ€€ŸùŸù˜˜™™™™˜˜ŸùŸù€€ÿÿMSVMpack1.2/mongoose/examples/html/logo.png0000644000175000017500000000310111557453204020001 0ustar lauerlauer‰PNG  IHDR (y,ñ˜IDATxÚí[=Ž³<Æ(EŠT4TéÒm™’6-55=} ä¹@NÀ ¸AŽÀò商OÖhf<ãìF«•ÉÚ3¶ÏŸ!Ë~_¯v‚Ö½Zž¦$ᓸ¾ÚÓkxF ý.¯vÒ›°}µæÕêWk_íû¨áxÀ?¹cZß_ðöÏÑ3ËͺÙodœ ó›ÃæHn†'àøg˜¬l'k2• ³ù%}ôtÚ'Þý¼^í8[n®r5 çµO’Ïß8ïêôÉ1ÄÀ¬}N¬Wý’ßEÀdz`‚}™ UêÙGïZ.t#mþ'ø}OìÀì bä3ƒ'ø'wÝè· ÞÝÓ­äðz­Þ¡Pè]Àúž öï˜ønax£N@B¼* xC(SâÉY’@׿w%Ë…ŸE§ùŠ *Gˆ»0–À}!î]]ß.@ÀÁ›¯õç õôÄaWC\¿a÷Œ‰1±›€5Ð9 Ÿ+6‰{Xu²Ê—‚ÜÅàiÖvP¯gÖÉ»ã¶UŒ Ç‘­Bv§É¹›ŒB A@l%{p5RvtVgê´g «NVùI¹¨š±>ÁBZʼn0wƧg®Q²_‹þÔV$$Åz%I(Wµä}bM›h è˜ xÆÒÉ*-x%„'3á c2.© ú¡¬nÖ™+Ïàrfúï}¤õV§Ñ’E¤°c&À⇇7xËBŒ»˜¼¾­:ÅŒa&b¸™ø³±+cY«Üá°¾µà†€wf®gÁ ž «œ’¶(r…蚉Åj!f<ÉGÀ‰éã*ÄgVbÆ€çíò#c#Ä°œÜ+ SŠjï•G¨÷(A…à s©ç†¬È]¬q¶CMÌC1aO„ù¯æÞªSÌ(@ƒ†²ÊEé²jÁ°-<Ïëå÷¿(¸÷âà› ?Z©<0A6FMÔ™!ÎÖ`=¶„UÌ&é‰Ý}”—B:ÅŒ¡cÈ„ItPOC@g8 ,ÓSH<{c5`<¨¹pã¨óÐ/F‰†±2®âè©]ñ ¸^+ã¥NVy\“›+P),àây [g¡Ÿš‰—VV.ˆ€µP§¢”¨™60;¼eúY”5FÍÉU'« Mongoose chat server
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').addClass('message-row').appendTo('#mml'); var timestamp = (new Date(entry.timestamp * 1000)).toLocaleTimeString(); $('') .addClass('message-timestamp') .html('[' + timestamp + ']') .prependTo(row); $('') .addClass('message-user') .addClass(entry.user ? '' : 'message-user-server') .html(chat.normalizeText((entry.user || '[server]') + ':')) .appendTo(row); $('') .addClass('message-text') .addClass(entry.user ? '' : 'message-text-server') .html(chat.normalizeText(entry.text)) .appendTo(row); chat.lastMessageId = Math.max(chat.lastMessageId, entry.id) + 1; }); // Keep only chat.maxVisibleMessages, delete older ones. while ($('#mml').children().length > chat.maxVisibleMessages) { $('#mml div:first-child').remove(); } }; chat.getMessages = function() { $.ajax({ dataType: 'jsonp', url: chat.backendUrl + '/ajax/get_messages', data: {last_id: chat.lastMessageId}, success: chat.refresh, error: function() { }, }); window.setTimeout(chat.getMessages, chat.getMessagesIntervalMs); }; chat.handleMenuItemClick = function(ev) { $('.menu-item').removeClass('menu-item-selected'); // Deselect menu buttons $(this).addClass('menu-item-selected'); // Select clicked button $('.main').addClass('hidden'); // Hide all main windows $('#' + $(this).attr('name')).removeClass('hidden'); // Show main window }; chat.showError = function(message) { $('#error').html(message).fadeIn('fast'); window.clearTimeout(chat.errorMessageFadeOutTimer); chat.errorMessageFadeOutTimer = window.setTimeout(function() { $('#error').fadeOut('slow'); }, chat.errorMessageFadeOutTimeoutMs); }; chat.handleMessageInput = function(ev) { var input = ev.target; if (ev.keyCode != 13 || !input.value) return; //input.disabled = true; $.ajax({ dataType: 'jsonp', url: chat.backendUrl + '/ajax/send_message', data: {text: input.value}, success: function(ev) { input.value = ''; input.disabled = false; chat.getMessages(); }, error: function(ev) { chat.showError('Error sending message'); input.disabled = false; }, }); }; $(document).ready(function() { $('.menu-item').click(chat.handleMenuItemClick); $('.message-input').keypress(chat.handleMessageInput); chat.getMessages(); }); // vim:ts=2:sw=2:et MSVMpack1.2/mongoose/examples/html/login.html0000644000175000017500000000307511557453204020343 0ustar lauerlauer Mongoose chat: login

Mongoose chat server login

Username and password can be any non-empty strings.



MSVMpack1.2/mongoose/Makefile0000644000175000017500000001145111557453204015220 0ustar lauerlauer# This file is part of Mongoose project, http://code.google.com/p/mongoose # $Id: Makefile 473 2009-09-02 11:20:06Z valenok $ PROG= mongoose all: @echo "make (linux|bsd|solaris|mac|windows|mingw)" # Possible COPT values: (in brackets are rough numbers for 'gcc -O2' on i386) # -DHAVE_MD5 - use system md5 library (-2kb) # -DNDEBUG - strip off all debug code (-5kb) # -DDEBUG - build debug version (very noisy) (+7kb) # -DNO_CGI - disable CGI support (-5kb) # -DNO_SSL - disable SSL functionality (-2kb) # -DCONFIG_FILE=\"file\" - use `file' as the default config file # -DHAVE_STRTOUI64 - use system strtoui64() function for strtoull() # -DSSL_LIB=\"libssl.so.\" - use system versioned SSL shared object # -DCRYPTO_LIB=\"libcrypto.so.\" - use system versioned CRYPTO so ########################################################################## ### UNIX build: linux, bsd, mac, rtems ########################################################################## CFLAGS= -W -Wall -std=c99 -pedantic -O2 $(COPT) MAC_SHARED= -flat_namespace -bundle -undefined suppress LINFLAGS= -ldl -pthread $(CFLAGS) LIB= _$(PROG).so # Make sure that the compiler flags come last in the compilation string. # If not so, this can break some on some Linux distros which use # "-Wl,--as-needed" turned on by default in cc command. # Also, this is turned in many other distros in static linkage builds. linux: $(CC) mongoose.c -shared -fPIC -fpic -o $(LIB) $(LINFLAGS) $(CC) mongoose.c main.c -o $(PROG) $(LINFLAGS) bsd: $(CC) mongoose.c -shared -pthread -fpic -fPIC -o $(LIB) $(CFLAGS) $(CC) mongoose.c main.c -pthread -o $(PROG) $(CFLAGS) mac: $(CC) mongoose.c -pthread -o $(LIB) $(MAC_SHARED) $(CFLAGS) $(CC) mongoose.c main.c -pthread -o $(PROG) $(CFLAGS) solaris: gcc mongoose.c -pthread -lnsl \ -lsocket -fpic -fPIC -shared -o $(LIB) $(CFLAGS) gcc mongoose.c main.c -pthread -lnsl -lsocket -o $(PROG) $(CFLAGS) ########################################################################## ### WINDOWS build: Using Visual Studio or Mingw ########################################################################## # Using Visual Studio 6.0. To build Mongoose: # o Set VC variable below to where VS 6.0 is installed on your system # o Run "PATH_TO_VC6\bin\nmake windows" VC= z: CYA= y: #DBG= /Zi /DDEBUG /Od DBG= /DNDEBUG /O1 CL= cl /MD /TC /nologo $(DBG) /Gz /W3 /DNO_SSL_DL GUILIB= user32.lib shell32.lib LINK= /link /incremental:no /libpath:$(VC)\lib /subsystem:windows \ ws2_32.lib advapi32.lib cyassl.lib CYAFL= /c /I $(CYA)\ctaocrypt\include /I $(CYA)\include /D_LIB CYASRC= $(CYA)/src/cyassl_int.c \ $(CYA)/src/cyassl_io.c \ $(CYA)/src/keys.c \ $(CYA)/src/tls.c \ $(CYA)/ctaocrypt/src/aes.c \ $(CYA)/ctaocrypt/src/arc4.c \ $(CYA)/ctaocrypt/src/asn.c \ $(CYA)/ctaocrypt/src/des3.c \ $(CYA)/ctaocrypt/src/dh.c \ $(CYA)/ctaocrypt/src/dsa.c \ $(CYA)/ctaocrypt/src/hc128.c \ $(CYA)/ctaocrypt/src/hmac.c \ $(CYA)/ctaocrypt/src/integer.c \ $(CYA)/ctaocrypt/src/md4.c \ $(CYA)/ctaocrypt/src/md5.c \ $(CYA)/ctaocrypt/src/misc.c \ $(CYA)/ctaocrypt/src/rabbit.c \ $(CYA)/ctaocrypt/src/random.c \ $(CYA)/ctaocrypt/src/ripemd.c \ $(CYA)/ctaocrypt/src/rsa.c \ $(CYA)/ctaocrypt/src/sha.c \ $(CYA)/ctaocrypt/src/sha256.c cyassl: $(CL) $(CYA)/src/ssl.c $(CYA)/ctaocrypt/src/coding.c \ $(CYAFL) /DOPENSSL_EXTRA $(CL) $(CYASRC) $(CYAFL) lib *.obj /out:cyassl.lib windows: rc win32\res.rc $(CL) main.c mongoose.c /GA $(LINK) win32\res.res \ $(GUILIB) /out:$(PROG).exe $(CL) mongoose.c /GD $(LINK) /DLL /DEF:win32\dll.def /out:_$(PROG).dll # Build for Windows under MinGW #MINGWDBG= -DDEBUG -O0 MINGWDBG= -DNDEBUG -Os #MINGWOPT= -W -Wall -mthreads -Wl,--subsystem,console $(MINGWDBG) -DHAVE_STDINT MINGWOPT= -W -Wall -mthreads -Wl,--subsystem,windows $(MINGWDBG) mingw: windres win32\res.rc win32\res.o gcc $(MINGWOPT) mongoose.c -lws2_32 \ -shared -Wl,--out-implib=$(PROG).lib -o _$(PROG).dll gcc $(MINGWOPT) mongoose.c main.c win32\res.o -lws2_32 -ladvapi32 \ -o $(PROG).exe ########################################################################## ### Manuals, cleanup, test, release ########################################################################## man: groff -man -T ascii mongoose.1 | col -b > mongoose.txt groff -man -T ascii mongoose.1 | less # "TEST=unit make test" - perform unit test only # "TEST=embedded" - test embedded API by building and testing test/embed.c # "TEST=basic_tests" - perform basic tests only (no CGI, SSI..) test: do_test do_test: perl test/test.pl $(TEST) release: clean F=mongoose-`perl -lne '/define\s+MONGOOSE_VERSION\s+"(\S+)"/ and print $$1' mongoose.c`.tgz ; cd .. && tar --exclude \*.hg --exclude \*.svn --exclude \*.swp --exclude \*.nfs\* -czf x mongoose && mv x mongoose/$$F clean: rm -rf *.o *.core $(PROG) *.obj *.so $(PROG).txt *.dSYM *.tgz MSVMpack1.2/gpl.txt0000644000175000017500000004313111644772171013261 0ustar lauerlauer GNU GENERAL PUBLIC LICENSE Version 2, June 1991 Copyright (C) 1989, 1991 Free Software Foundation, Inc. 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed. 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MSVMpack1.2/src/0000755000175000017500000000000012104705371012511 5ustar lauerlauerMSVMpack1.2/src/libevalMSVM_CS.c0000644000175000017500000002175711644772425015413 0ustar lauerlauer/* Copyright 2001, 2002, 2003 Yann Guermeur and Andre Elisseeff */ /* 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 2 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, write to the Free Software */ /* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA */ /*----------------------------------------------------------------------------*/ /* Name : libevalMSVM_CS.c */ /* Version : 2.0 */ /* Creation : 04/30/00 */ /* Last update : 01/20/11 */ /* Subject : Implementation of the M-SVM of Crammer and Singer */ /* Module : Evaluation functions */ /* Author : Fabien Lauer and Yann Guermeur Yann.Guermeur@loria.fr */ /*----------------------------------------------------------------------------*/ #include "libevalMSVM_CS.h" /* Main evaluation function for CS: compute the ratio (dual / upper bound) */ double MSVM_CS_eval(double *best_primal_upper_bound, double **H_alpha, struct Model *model, const int verbose, FILE *fp) { const long Q = model->Q; double R_emp, ratio; struct Cache cache; cache.H_alpha = H_alpha; cache.verbose = verbose; long **mat_conf = matrix_l(Q,Q); long i,training_errors; CS_check_feasible_sol(model,NULL,verbose); R_emp = CS_eval_training(cache.H_alpha,mat_conf,model); // Compute training error training_errors = model->nb_data; for(i=1;i<=Q;i++) training_errors -= mat_conf[i][i]; model->training_error = (double)training_errors/(double)model->nb_data; // Compute the ratio dual/upper bound (stopping criterion) CS_compute_obj_dual(&cache,model); CS_compute_obj_primal(R_emp,&cache,model); // Make sure the upper bound does not increase if(cache.primal > *best_primal_upper_bound) cache.primal = *best_primal_upper_bound; else *best_primal_upper_bound = cache.primal; ratio = cache.dual / cache.primal; if(verbose) { printf("\nDifference between the primal and the dual: %lf -> %lf", cache.primal, cache.dual); printf("\n(ratio %5.2lf \%%)\n", 100.0 * ratio); printf("\n*** Training performance\n"); display_stats(Q, mat_conf); display_full_stats(Q, mat_conf); } // Log info if(fp != NULL) fprintf(fp, "%lf %lf \n",cache.dual,cache.primal); // Free memory free(mat_conf[1]); free(mat_conf); return ratio; } /* output = CS_function( k, x, model) Compute the real-valued output of model for the k-th category on pattern x */ double CS_function(long category, void *vector, const struct Model *model) { const long nb_data = model->nb_data; const long Q = model->Q; const enum Kernel_type nature_kernel = model->nature_kernel; const double *kernel_par = model->kernel_par; long dim_input = model->dim_input; long i,k; double partial, result = 0.0; for(i=1; i<=nb_data; i++) { if(model->y[i] == category) { partial = 0.0; for(k=1; k<=Q; k++) if(k != category) partial += model->alpha[i][k]; } else partial = - model->alpha[i][category]; if(partial != 0.0) result += partial * ker(nature_kernel, model->X[i], vector, dim_input, kernel_par); } return result; } /* label = CS_classify(x, model, real_outputs) Classify x and output the label. If real_outputs is not NULL, also compute the Q real-valued outputs of the model and store them in (real_outputs[1]...real_outpust[Q]). Note: this function is faster than calling Q times CS_function */ long CS_classify(void *vector, const struct Model *model, double *real_outputs) { const long nb_data = model->nb_data; const long Q = model->Q; const enum Kernel_type nature_kernel = model->nature_kernel; const double *kernel_par = model->kernel_par; long dim_input = model->dim_input; long i,k; long label = 1; double maxoutput,partial, kernel; int isSV, use_real_outputs = true; if(real_outputs==NULL) { real_outputs = (double *)malloc(sizeof(double) * (Q+1)); use_real_outputs = false; } for(k=1;k<=Q;k++) real_outputs[k] = 0.0; // No bias term in CS model for(i=1; i<=nb_data; i++) { partial = 0.0; isSV = false; for(k=1; k<=Q; k++) { partial += model->alpha[i][k]; if(k != model->y[i] && model->alpha[i][k] != 0.0) isSV = true; } if(isSV) { kernel = ker(nature_kernel, model->X[i], vector, dim_input, kernel_par); for (k=1; k<=Q; k++) { if(model->y[i] == k) real_outputs[k] += (partial - model->alpha[i][k]) * kernel; else real_outputs[k] -= model->alpha[i][k] * kernel; } } } maxoutput = real_outputs[1]; for(k=2; k<=Q; k++) if(real_outputs[k] > maxoutput) { maxoutput = real_outputs[k]; label = k; } if(!use_real_outputs) free(real_outputs); return label; } void CS_check_feasible_sol(const struct Model *model, char *alpha_file,int verbose) { char command[taille]; const long Q = model->Q; const long nb_data = model->nb_data; const double *C = model->C; double partial; int rc; long i,k; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) if((model->alpha[i][k] < 0.0) || (model->alpha[i][k] > C[model->y[i]])) { printf("\nNo feasible solution: alpha[%ld][%ld] = %1.12lf > %lf\n\n", i, k, model->alpha[i][k], C[model->y[i]]); exit(0); } for(i=1; i<=nb_data; i++) { partial = 0.0; for(k=1; k<=Q; k++) partial += model->alpha[i][k]; if(fabs(partial - C[model->y[i]]) > very_small) { printf("\nLarge deviation of the equality constraint: sum_alpha = %1.10lf ~= %lf = C\n",partial,C[model->y[i]]); exit(0); } } if(alpha_file != NULL) { sprintf(command, "cp %s Save_alpha/.", alpha_file); rc = system(command); } } /* Compute the training error */ double CS_eval_training(double **H_alpha, long **mat_conf, const struct Model *model) { long i,k,l,y_i; const long Q = model->Q; const long nb_data = model->nb_data; long ind_max = 0; double xi_ik, maxi = HUGE_VAL; double R_emp = 0.0; if(mat_conf != NULL) { for(k=1; k<=Q; k++) for(l=1; l<=Q; l++) mat_conf[k][l] = 0; } for(i=1; i<=nb_data; i++) { maxi = 0.0; ind_max = 0; y_i = model->y[i]; for(k=1; k<=Q; k++) if(k != y_i) { xi_ik = 1.0 - H_alpha[i][k]; if(xi_ik < 0.0) xi_ik = 0.0; if(xi_ik > maxi) { maxi = xi_ik; ind_max = k; } } R_emp += model->C[y_i] * maxi; if(mat_conf != NULL) { if(maxi > 1.0) mat_conf[y_i][ind_max]++; else mat_conf[y_i][y_i]++; } } return R_emp; } void CS_compute_W(struct Model *model) { const long Q = model->Q; const long nb_data = model->nb_data; const long dim_input = model->dim_input; long i,j,k,l; double partial; if(model->W == NULL) model->W = matrix(dim_input, Q); for(j=1; j<=dim_input; j++) for(k=1; k<=Q; k++) model->W[j][k] = 0.0; for(k=1; k<=Q; k++) for(i=1; i<=nb_data; i++) { if((model->y[i]) == k) { partial = 0.0; for(l=1; l<=Q; l++) partial += model->alpha[i][l]; for(j=1; j<=dim_input; j++) model->W[j][k] += partial * model_get_Xij(model,i,j); } else for(j=1; j<=dim_input; j++) model->W[j][k] -= model->alpha[i][k] * model_get_Xij(model,i,j); } } void CS_compute_obj_dual(struct Cache *cache, struct Model *model) { long i,k; const long Q = model->Q; const long nb_data = model->nb_data; double alpha_H_alpha = 0.0; double sum_Ci_minus_alpha_iyi = 0.0; for(i=1; i<=nb_data; i++) { for(k=1; k<=Q; k++) { alpha_H_alpha += cache->H_alpha[i][k] * model->alpha[i][k]; } sum_Ci_minus_alpha_iyi += model->C[model->y[i]] - model->alpha[i][model->y[i]]; } cache->alpha_H_alpha = alpha_H_alpha; cache->dual = -0.5*alpha_H_alpha + sum_Ci_minus_alpha_iyi; } void CS_compute_obj_primal(double R_emp, struct Cache *cache, const struct Model *model) { cache->primal = 0.5 * cache->alpha_H_alpha + R_emp; if(cache->primal < cache->dual) { printf("\nInconsistency in the values of the objective functions...\n primal = %lf + %lf = %lf < %lf (dual)\n", 0.5 * cache->alpha_H_alpha, R_emp , cache->primal, cache->dual); /* exit(0); */ } } MSVMpack1.2/src/trainMSVM.c0000644000175000017500000004136212104675657014520 0ustar lauerlauer/* Copyright 2010 Fabien Lauer */ /* 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 2 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, write to the Free Software */ /* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA*/ /*--------------------------------------------------------------------------*/ /* Name : trainMSVM.c */ /* Version : 2.0 */ /* Creation : 04/27/10 */ /* Last update : 02/25/12 */ /* Subject : MSVMpack: a multi-class SVM package */ /* Algo. : Training command-line tool */ /* Author : Fabien Lauer fabien.lauer@loria.fr */ /*--------------------------------------------------------------------------*/ #include #include #include #include #include #include #include "libMSVM.h" #include "libevalMSVM.h" #include "libtrainMSVM.h" /* Handling user interruption */ void ctrlC_handler(int sig) { if(EVAL) { printf(" Double Ctrl-C causes the program to break \n"); printf(" (all is lost, nothing is saved). \n"); exit(0); } else EVAL = 1; } /* Main */ int main(int argc, char *argv[]) { // Install the handler of SIGINT (Ctrl+C) signal, // which will force the call to MSVM_eval on demand struct sigaction newhandler,oldhandler; memset(&newhandler, 0, sizeof(newhandler)); newhandler.sa_handler = &ctrlC_handler; sigaction(SIGINT, &newhandler, &oldhandler); // Some local variables char com_file[taille], training_file[taille], model_file[taille], alpha0_file[taille], model_tmp_file[taille], alpha_file[taille], test_file[taille], outputs_file[taille], log_file[taille], yesno; long training_status; int i, k, n_kernel_par; long Q; FILE *fstdout=NULL; FILE *fkp; time_t realtime,starttime = time(NULL); clock_t cputime,startcputime = clock(); // Default parameter values enum MSVM_type model_type = MSVM2; double C = DEFAULT_C; double accuracy = 0.98; // 98% optimization accuracy level long chunk_size = 4; // 4 points considered at each iteration int sparse_model_format = false; // Do not use sparse model file format // this allows retraining from an existing model int retrain = false; // Assumes an empty model int do_normalize = 0; // Test if normalization needed int cache_memory = 1024; // Use 1 GB of memory for kernel cache int nprocs = get_nprocessors(); // Use all processors // Default filenames strcpy(model_file, "msvm.model"); // save model to "msvm.model" char *alpha0 = NULL; // initialize with all alpha = 0 (except for CS-type) char *alpha = NULL; // backward compatibility char *test = NULL; // Do not test model on a test set (training only) char *outputs = NULL; // so no output on test set to record char *log = NULL; // Do not log the values of dual objective and upper bounds strcpy(log_file, ""); /* Parse command line and initialize model for training */ if(argc<2 || check_argv(argc,argv, "-help") || check_argv_eq(argc,argv, "-h") ) { printf("This is MSVMpack: a Multi-class Support Vector Machine package\n"); printf("-- Version: %1.1f \n\n",VERSION); printf("Training tool used to train an M-SVM model from data. \n\n"); printf("Usage: \n"); printf(" trainmsvm training_file [file.model] [params]\n"); printf(" or trainmsvm comfile.com [file.model]\n\n"); printf(" where 'params' is a list of parameters specified as e.g.: \n -c 2.5 -k 1 \n\n"); printf("Optional parameters: \n"); printf(" -m : model type (WW,CS,LLW,MSVM2) (default is MSVM2)\n"); printf(" -k : nature of the kernel function (default is 1)\n"); printf(" 1 -> linear kernel k(x,z) = x^T z\n"); printf(" 2 -> Gaussian RBF kernel k(x,z) = exp(-||x - z||^2 / 2*par^2)\n"); printf(" 3 -> homogeneous polynomial kernel k(x,z) = (x^T z)^par \n"); printf(" 4 -> non-homo. polynomial kernel k(x,z) = (x^T z + 1)^par \n"); printf(" 5 -> custom kernel 1\n"); printf(" 6 -> custom kernel 2\n"); printf(" 7 -> custom kernel 3\n"); printf(" -p : kernel parameter par (default is sqrt(5*dim(x)) (RBF) or 2 (POLY))\n"); printf(" -P : list of space-separated kernel parameters starting with #parameters\n"); printf(" -c : soft-margin (or trade-off) hyperparameter (default C = 10.0)\n"); printf(" -C : list of space-separated hyperparameters C_k (default C_k = C)\n"); printf(" -n : use normalized data for training (mean=0 and std=1 for all features)\n"); printf(" -u : use unnormalized data for training (bypass the normalization test) \n"); printf(" -x : maximal cache memory size in MB (default is 1024)\n"); printf(" -t : number of working threads in [1, %d] (default is #CPUs=%d)\n",nprocs,nprocs); printf(" -f : faster computations with single-precision floating-point data format\n"); printf(" -I : faster computations with integer data format\n"); printf(" -i : faster computations with short integer data format\n"); printf(" -B : faster computations with byte data format\n"); printf(" -b : faster computations with bit data format\n"); printf(" -o : optimization method: 0 -> Franke-Wolfe (default), 1 -> Rosen\n"); printf(" -w : size of the chunk (default is 10 for WW and 4 for others)\n"); printf(" -a : optimization accuracy within [0,1] (default is 0.98)\n"); printf(" -r : retrain model (resume training)\n"); printf(" -s : save model using sparse format\n"); printf(" -S : convert existing model to sparse format without training\n"); printf(" -q : be quiet\n\n"); printf("These optional files can be specified on the command line:\n"); printf(" file.test : Test data file\n"); printf(" file.outputs : Computed outputs on the test set\n"); //printf(" file.alpha : Backup file for alpha\n"); printf(" file.init : Initialization file for alpha\n"); printf(" file.log : Log optimization information\n\n"); printf("See also 'predmsvm' to classify new data with a trained M-SVM. \n\n"); exit(0); } i = check_argv_eq(argc,argv, "-q"); if(i) { fstdout = freopen(".trainmsvm_quiet.log", "w", stdout); if(fstdout == NULL) printf("Cannot set quiet mode (error in stdout redirection)\n"); } i = check_argv_eq(argc,argv, "-m"); if(i) model_type = str2model_type(argv[i+1]); // Make model struct Model *model = MSVM_make_model(model_type); if (model == NULL) { printf("Unknown model type -m %s.\n",argv[i+1]); exit(1); } // Set a different default chunk_size for WW models if(model_type == WW) chunk_size = 10; // check if first argument is a .com file if(strstr(argv[1], ".com") != NULL ) { // Read all info from the .com file strcpy(com_file, argv[1]); printf("Reading parameters from %s ...\n ", com_file); chunk_size = MSVM_init_train_comfile(model, com_file, training_file, alpha0_file, alpha_file, log_file); alpha0 = alpha0_file; alpha = alpha_file; } else { // First argument must be the training data file (if not a .com file) strcpy(training_file, argv[1]); // If a .com file is found at another position, use it to set the parameters only i = check_argv(argc,argv, ".com"); if(i) { strcpy(com_file, argv[i]); chunk_size = MSVM_init_model(model, com_file); } } // Parse filenames i = check_argv(argc,argv, ".outputs"); if(i) { strcpy(outputs_file,argv[i]); outputs = outputs_file; } i = check_argv(argc,argv, ".test"); if(i) { strcpy(test_file, argv[i]); test = test_file; } i = check_argv(argc,argv, ".alpha"); if(i) { strcpy(alpha_file,argv[i]); alpha = alpha_file; } i = check_argv(argc,argv, ".init"); if(i) { strcpy(alpha0_file,argv[i]); alpha0 = alpha0_file; } i = check_argv(argc,argv, ".model"); if(i) { strcpy(model_file,argv[i]); } i = check_argv(argc,argv, ".log"); if(i) { strcpy(log_file,argv[i]); log = log_file; } else if(strlen(log_file) > 0) log = log_file; // Parse parameters from the command line // (this overrides values from a .com file) i = check_argv_eq(argc,argv, "-w"); if(i) chunk_size = atoi(argv[i+1]); i = check_argv_eq(argc,argv, "-c"); if(i) C = atof(argv[i+1]); // see below for multiple C i = check_argv_eq(argc,argv, "-k"); if(i) { model->nature_kernel = atoi(argv[i+1]); } i = check_argv_eq(argc,argv, "-f"); if(i) { model->datatype = FLOAT; model->nature_kernel += 10; } i = check_argv_eq(argc,argv, "-I"); if(i) { model->datatype = INT; model->nature_kernel += 20; do_normalize = 0; } i = check_argv_eq(argc,argv, "-i"); if(i) { model->datatype = SHORT; model->nature_kernel += 30; do_normalize = 0; } i = check_argv_eq(argc,argv, "-B"); if(i) { model->datatype = BYTE; model->nature_kernel += 40; do_normalize = 0; } i = check_argv_eq(argc,argv, "-b"); if(i) { model->datatype = BIT; model->nature_kernel += 50; do_normalize = 0; } i = check_argv_eq(argc,argv, "-p"); if(i) { model->kernel_par = (double*)realloc(model->kernel_par, sizeof(double) * 2); model->kernel_par[0] = 1; model->kernel_par[1] = atof(argv[i+1]); } i = check_argv_eq(argc,argv, "-P"); if(i) { if(argv[i+1][0] >= '0' && argv[i+1][0] <= '9') { n_kernel_par = atoi(argv[i+1]); model->kernel_par = (double*)realloc(model->kernel_par, sizeof(double) * (n_kernel_par + 1)); model->kernel_par[0] = n_kernel_par; if(n_kernel_par > 0 && argv[i+2][0] >= '0' && argv[i+2][0] <= '9') { for(k=1;k<=n_kernel_par;k++) model->kernel_par[k] = atof(argv[i+1+k]); } else if (n_kernel_par > 0){ // Kernel parameter values in file fkp = fopen(argv[i+2], "r"); if(fkp == NULL) { printf("Cannot read kernel parameter file %s\n",argv[i+2]); exit(1); } for(k=1;k<=n_kernel_par;k++) i=fscanf(fkp, "%lf", &model->kernel_par[k]); fclose(fkp); } } else { // Kernel parameter list is a file name fkp = fopen(argv[i+1], "r"); if(fkp == NULL) { printf("Cannot read kernel parameter file %s\n",argv[i+1]); exit(1); } i=fscanf(fkp, "%d", &n_kernel_par); model->kernel_par = (double*)realloc(model->kernel_par, sizeof(double) * (n_kernel_par + 1)); model->kernel_par[0] = n_kernel_par; for(k=1;k<=n_kernel_par;k++) i=fscanf(fkp, "%lf", &model->kernel_par[k]); fclose(fkp); } } i = check_argv_eq(argc,argv, "-a"); if(i) { accuracy = atof(argv[i+1]); if (accuracy < 0 || accuracy > 1) { printf("\n Wrong accuracy level -a %lf (not in [0,1])",accuracy); printf("\n Falling back to default (0.98).\n"); accuracy = 0.98; } } i = check_argv_eq(argc,argv, "-n"); if(i) do_normalize = 1; i = check_argv_eq(argc,argv, "-u"); if(i) do_normalize = -1; i = check_argv_eq(argc,argv, "-x"); if(i) { cache_memory = atoi(argv[i+1]); if(cache_memory <= 0) { printf("Cache memory size set with -x must be a positive integer.\n"); exit(1); } } i = check_argv_eq(argc,argv, "-t"); if(i) { if(atoi(argv[i+1]) > nprocs) { printf("Unattended request of a number of working threads above the number of available processors (%d)\n",nprocs); } else nprocs = atoi(argv[i+1]); } i = check_argv_eq(argc,argv, "-r"); if(i) { printf("\nRetrain model %s ...\n", model_file); if(!check_argv_eq(argc,argv, "-w")) printf("Using default chunk size: %ld\n (this may be different from what was previously used to train %s ).\n",chunk_size, model_file); retrain = true; MSVM_delete_model(model); model = MSVM_load_model(model_file); } i = check_argv_eq(argc,argv, "-o"); if(i) { if(atoi(argv[i+1]) == 1) { if(model->type == MSVM2) model->algorithm=Rosen; else printf("Rosen's algorithm is not available for this M-SVM, \n using Franke-Wolfe algorithm.\n"); } } i = check_argv_eq(argc,argv, "-s"); if(i) { sparse_model_format = true; } i = check_argv_eq(argc,argv, "-S"); if(i) { MSVM_delete_model(model); model = MSVM_load_model(model_file); if(model == NULL) exit(1); printf("\nConverting model %s in sparse format...\n", model_file); printf("Note that the sparse format does not allow retraining.\n\n"); MSVM_save_model_sparse(model, model_file); MSVM_delete_model_with_data(model); exit(0); } // --- End of parsing the command line --- /* Load training data */ struct Data *training_set, *test_set; if(!retrain) { training_set = MSVM_make_dataset(training_file, model->datatype); if(training_set == NULL) { printf("Error: wrong or missing training data file. \n"); printf("Note: the training data file should always be the first argument,\n"); printf(" e.g.: trainmsvm myTrainingData myMSVM.model\n\n"); exit(0); } Q = training_set->Q; } else { training_set = NULL; // resume training with data already in model Q = model->Q; } /* Normalize data */ if(do_normalize==1) { // user asked for normalization MSVM_normalize_data(training_set, model); } else if(do_normalize==0){ // check if normalization needed if(MSVM_normalize_data(training_set, NULL) > 10) { printf("**\n** Columns of the data matrix show a large difference\n"); printf("** between their standard deviations (> 10).\n"); printf("** This could affect the performance of the classifier. \n\n"); printf(" Do you want the data to be normalized ([y]/n)? \n"); printf(" (Use the -n flag to force normalization from the command line\n"); printf(" or the -u flag to bypass this test and use unnormalized data)\n"); i=scanf("%c",&yesno); getchar(); if(yesno != 'n') { MSVM_normalize_data(training_set, model); } } } /* Set the list of C hyperparameters */ i = check_argv_eq(argc,argv, "-C"); if(i) { MSVM_model_set_C(C, Q, model); for(k=1;k<=Q;k++) model->C[k] = atof(argv[i+k]); } else { MSVM_model_set_C(C, Q, model); } /* Set filename for monitoring (periodic saving of model in case something bad happens) */ sprintf(model_tmp_file, "%s.tmp", model_file); /* Launch training */ training_status = MSVM_train(model, training_set, chunk_size, accuracy, cache_memory, nprocs, alpha0, model_tmp_file, log); realtime = time(NULL) - starttime; cputime = clock() - startcputime; // Print output information if(training_status == 0) { printf("\n Optimum found with desired accuracy level (%3.2lf \%%)\n", 100*accuracy); if ((long unsigned int)realtime > 1) printf("after %lu seconds (actual CPU time over all processors = %1.2lf sec.). \n", (long unsigned int)realtime, (double) cputime / (double)CLOCKS_PER_SEC); else printf("after %lu second (actual CPU time over all threads = %1.2lf sec.). \n", (long unsigned int)realtime, (double) cputime / (double)CLOCKS_PER_SEC); } else if(training_status == 1) printf("\n Stopped training after maximum number of iterations (%ld). \n", MSVM_TRAIN_MAXIT); else if(training_status > 1) printf("\n Stopped by user after %ld iterations. \n", training_status); else { printf("Error in training MSVM. No model saved. \n"); exit(0); } // Output trianing error rate if((double)((int)(10000 * model->training_error)) == 10000 * model->training_error) printf("Training error rate = %3.2lf %%\n",100*model->training_error); else printf("Training error rate = %3.4lf %%\n",100*model->training_error); // Write model to file if(sparse_model_format) { printf("\nSaving model in sparse format to %s...\n", model_file); printf("Note that the sparse format does not allow retraining.\n\n"); MSVM_save_model_sparse(model, model_file); } else { MSVM_save_model(model, model_file); printf("M-SVM model saved in %s.\n",model_file); } // and remove temporary file remove(model_tmp_file); // Compute test error (if test_file is provided) if(test != NULL) { test_set = MSVM_make_dataset(test_file, model->datatype); // Compute output on test set MSVM_classify_set(NULL, test_set->X, test_set->y, test_set->nb_data, outputs, model, nprocs); MSVM_delete_dataset(test_set); } // Free all if(retrain) MSVM_delete_model_with_data(model); else { MSVM_delete_model(model); MSVM_delete_dataset(training_set); } return 0; } MSVMpack1.2/src/biblio.c0000644000175000017500000000576411644772425014145 0ustar lauerlauer/*--------------------------------------------------------------------------*/ /* Name : biblio.c */ /* Version : 1.0 */ /* Creation : 07/12/96 */ /* Last update : 01/01/10 */ /* Subject : Implementation of a classifier */ /* Module : Measures of the prediction accuracy */ /* Author : Yann Guermeur Yann.Guermeur@loria.fr */ /*--------------------------------------------------------------------------*/ #include #include #include #include "algebra.h" /* Display the recognition rate only */ void display_stats(long classes, long **matrice) { long ind1, ind2; double nb_ex = 0.0, nb_rec = 0.0; for(ind1=1; ind1<=classes; ind1++) for(ind2=1; ind2<=classes; ind2++) { nb_ex += matrice[ind1][ind2]; if(ind1 == ind2) nb_rec += matrice[ind1][ind2]; } printf("\nRecognition rate: %6.2lf \%%\n", (nb_rec*100.0)/nb_ex); } /* Display the values of all the measures of accuracy */ void display_full_stats(long classes, long **matrice) { long ind1, ind2, disp_size; double *nb, *pred, denominator, nb_ex=0.0, nb_rec=0.0, *C_matt, *p, *o, *n, *u; p = (double *) calloc(classes+1, sizeof(double)); o = (double *) calloc(classes+1, sizeof(double)); n = (double *) calloc(classes+1, sizeof(double)); u = (double *) calloc(classes+1, sizeof(double)); nb = (double *) calloc(classes+1, sizeof(double)); pred = (double *) calloc(classes+1, sizeof(double)); C_matt = (double *) calloc(classes+1, sizeof(double)); for(ind1=1; ind1<=classes; ind1++) for(ind2=1; ind2<=classes; ind2++) { nb_ex += matrice[ind1][ind2]; nb[ind1] += matrice[ind1][ind2]; pred[ind2] += matrice[ind1][ind2]; } disp_size = (long) ceil(log10(nb_ex)); printf("\nConfusion matrix:\n"); display_mat_l(matrice, classes, classes, disp_size); for(ind1=1; ind1<=classes; ind1++) { p[ind1] = matrice[ind1][ind1]; nb_rec += p[ind1]; } for(ind1=1; ind1<=classes; ind1++) { u[ind1] = nb[ind1] - p[ind1]; o[ind1] = pred[ind1] - p[ind1]; } for(ind1=1; ind1<=classes; ind1++) n[ind1] = nb_ex - (pred[ind1] + u[ind1]); for(ind1=1; ind1<=classes; ind1++) { denominator = sqrt(n[ind1]+u[ind1]) * sqrt(n[ind1]+o[ind1]) * sqrt(p[ind1]+u[ind1]) * sqrt(p[ind1]+o[ind1]); if(denominator != 0.0) C_matt[ind1] = (p[ind1] * n[ind1] - u[ind1] * o[ind1]) / denominator; else C_matt[ind1] = 0.0; } printf("Recognition rate: %6.2lf \%%\n", (nb_rec*100.0)/nb_ex); printf("\nMatthews coefficients:\n\n"); for(ind1=1; ind1<=classes; ind1++) printf("C%ld: %c%4.2lf\n", ind1, (C_matt[ind1] >= 0) ? ' ' : '-', fabs(C_matt[ind1])); printf("\n"); free(p); free(o); free(n); free(u); free(nb); free(pred); free(C_matt); } MSVMpack1.2/src/libtrainMSVM_2fw.c~0000644000175000017500000006314111761347604016156 0ustar lauerlauer/* Copyright 2000-2010 Yann Guermeur */ /* 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 2 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, write to the Free Software */ /* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA*/ /*--------------------------------------------------------------------------*/ /* Name : libtrainMSVM_2fw.c */ /* Version : 2.0 */ /* Creation : 04/27/00 */ /* Last update : 11/29/10 */ /* Subject : Training algorithm of the M-SVM^2 */ /* Algo. : Frank-Wolfe algorithm + decomposition method */ /* Author : Fabien Lauer and Yann Guermeur Yann.Guermeur@loria.fr */ /*--------------------------------------------------------------------------*/ #include "libtrainMSVM_2fw.h" /* MSVM2 training function (Frank-Wolfe algorithm) Solves the dual problem wrt alpha: min 1/2 alpha' H_tilde alpha - (1/Q-1) sum (alpha) s.t. alpha_ik >= 0, for all i,k, such that 1 <= i <= m, 1 <= k != y_i <= Q sum_i (alpha_ik - average_alpha_k) = 0, for all k, 1 <= k <= Q where H_tilde_ik,jl = (delta_k,l - 1/Q) ( k(x_i,x_j) + (1/2C)delta_i,j ) */ long MSVM_2fw_train(struct Model *model, struct Data *training_set, long chunk_size, const double accuracy, int cache_memory, const int nprocs, char *alpha0_file, char *model_tmp_file, char *log_file) { long return_status = -1; FILE *fp; int t; pthread_t *threads = (pthread_t *)malloc(sizeof(pthread_t) * nprocs); // threads id void *status; // for pthread_join int rc; // return code of pthread functions pthread_t thread_monitor; enum AlphaInitType alphaiszero; if(training_set != NULL) { // Initialize model for this particular training set model_load_data(model, training_set); // Check if a kernel_par has been set if(model->nature_kernel != LINEAR && model->kernel_par == NULL) set_default_kernel_par(model); } if(model->nb_data > 2147483647) { printf("Cannot compute table chunk: number of data above random number limit\n"); exit(0); } // Log file if (log_file != NULL) { printf("\nLog training info in %s ...\n", log_file); fp = fopen(log_file,"a"); } else fp = NULL; // Initialize alpha and b if(training_set != NULL) // otherwise resume training init_alpha_b(model, alpha0_file); // use init_alpha_b(model, NULL); to initialize all alpha to 0 if(training_set == NULL || alpha0_file != NULL) alphaiszero = ALPHA_NOT_ZERO; else alphaiszero = ALPHA_IS_ZERO; EVAL = 0; // triggered by signal handler to call eval STOP = 0; // triggered by user to stop training iter = 1; // number of iterations (over all threads) // Prepare monitoring of model struct MonitorData monitor_data; monitor_data.model_tmp_file = model_tmp_file; monitor_data.period = MONITOR_PERIOD; monitor_data.model = model; pthread_create(&thread_monitor, NULL, MSVM_monitor_model_thread, (void *) &monitor_data); // Allocate memory for shared ressources double **gradient = matrix(model->nb_data, model->Q); double **H_alpha = matrix(model->nb_data, model->Q); double **H_tilde_alpha = matrix(model->nb_data, model->Q); double best_primal_upper_bound = HUGE_VAL; int *activeset = (int *)calloc(model->nb_data+1, sizeof(int)); double *lp_rhs = (double*)calloc(model->Q, sizeof(double)); // including the kernel cache: struct KernelCache kc; unsigned long cache_size = (unsigned long)cache_memory * MBYTES; kernel_initialize_cache(cache_size, &kc, model); printf("Initialization... ");fflush(stdout); // Initialize gradient MSVM2fw_init_gradient(alphaiszero, gradient, H_alpha,H_tilde_alpha, model); printf("Done.\n"); // Initialize display if(accuracy>0) print_training_info(0,0,0,model->type); else { printf("Training...");fflush(stdout); } // Prepare data for computing threads long nb_SV = 0; struct ThreadData thread_data; thread_data.nprocs = nprocs; thread_data.model = model; thread_data.kernelcache = &kc; thread_data.chunk_size = chunk_size; thread_data.accuracy = accuracy; thread_data.gradient = gradient; thread_data.H_alpha = H_alpha; thread_data.H_tilde_alpha = H_tilde_alpha; thread_data.best_primal_upper_bound = &best_primal_upper_bound; thread_data.activeset = activeset; thread_data.nb_SV = &nb_SV; thread_data.lp_rhs = lp_rhs; thread_data.logfile_ptr = fp; // Launch computing threads for(t=0;tthread_id; const int nprocs = data->nprocs; struct Model *model = data->model; struct KernelCache *kernelcache = data->kernelcache; long chunk_size = data->chunk_size; const double accuracy = data->accuracy; double **gradient = data->gradient; double **H_alpha = data->H_alpha; double **H_tilde_alpha = data->H_tilde_alpha; double *best_primal_upper_bound = data->best_primal_upper_bound; int *activeset = data->activeset; long *nb_SV = data->nb_SV; double *lp_rhs = data->lp_rhs; FILE *fp = data->logfile_ptr; pthread_mutex_unlock(&thread_data_mutex); // Release thread_data for next thread // Local variables int do_eval; char yesno; long return_status = -1; // Prepare the cache struct TrainingCache cache; cache.chunk_size = chunk_size; MSVM2fw_alloc_memory(&cache, model->Q, model->nb_data, chunk_size); cache.kc = kernelcache; cache.activeset = activeset; cache.lp_rhs = lp_rhs; double **delta = matrix(chunk_size, model->Q); double theta_opt; int jump = false; if(accuracy == 0) do_eval = 0; else do_eval = 1; /* Prepare parallel gradient computations: - the gradient vector is split into NUMTHREADS_GRAD parts (along i) - each part is updated by a different thread */ // max number of threads for gradient updates is nprocs pthread_t *grad_threads = (pthread_t *)malloc(sizeof(pthread_t) * nprocs); // start with 1 thread (main load on kernel evaluations) int numthreads_grad = 1; void *status; int rc; long k; struct ThreadGradient_data *grad_data = (struct ThreadGradient_data *)malloc(sizeof(struct ThreadGradient_data) * nprocs); // Disable parallel gradient computation for small data sets int parallel_gradient_update = 1; if(model->nb_data < 5000) parallel_gradient_update = 0; if(parallel_gradient_update) { for(k=0;knb_data / numthreads_grad; for(k=1;knb_data / numthreads_grad -1; } if(numthreads_grad>1) { grad_data[numthreads_grad-1].start_i = grad_data[numthreads_grad-2].end_i + 1; grad_data[numthreads_grad-1].end_i = model->nb_data; } } // Switch to nprocs/4 threads for gradient update when 25% of the kernel matrix is cached int percentage_step = 1; long percentage = model->nb_data / 4; int next_numthreads_grad = nprocs/4; if(next_numthreads_grad == 0) next_numthreads_grad = 1; // Main loop double ratio = 0.0; // stopping criterion (dual / upper bound) int thread_stop = 0; do { if((TRAIN_SMALL_STEP < TRAIN_STEP) && (iter%TRAIN_SMALL_STEP) == 0) { printf("."); fflush(stdout); } // Select a random chunk of data to optimize select_random_chunk(&cache,model); // Compute the kernel submatrix for this chunk compute_K(&cache,model); // Enter Critical Section (using and modifying the model) pthread_mutex_lock(&model_mutex); jump = MSVM2fw_solve_lp(gradient, &cache, model); if(jump == false) jump = MSVM2fw_check_opt_sol(gradient,&cache,model); if(jump == false) { MSVM2fw_compute_delta(delta,&cache,model); theta_opt = MSVM2fw_compute_theta_opt(delta, &cache, model); *nb_SV += MSVM2fw_compute_new_alpha(theta_opt,&cache,model); if(parallel_gradient_update && numthreads_grad > 1) { // Update gradient in parallel for(k=0;ktype); if(do_eval && ratio > accuracy) STOP = 1; if(EVAL) // if interrupted by user (otherwise let the ratio decide if we go on training) { printf("\n *** Do you want to continue training ([y]/n)? "); yesno = getchar(); if(yesno=='n') { STOP = 1; } EVAL = 0; // reset interruption trigger } } // Release kernel submatrix in cache release_K(&cache); // Check if a sufficient % of the kernel matrix is cached if( parallel_gradient_update && cache.kc->max_idx >= percentage ) { // and switch thread to compute gradient upates instead of kernel rows if it is thread_stop = switch_thread(nprocs, &numthreads_grad, &next_numthreads_grad, &percentage, &percentage_step, grad_data, thread_id, model->nb_data); // (threads are actually stopped to leave the CPUs // to other threads that will compute gradient updates) } iter++; // Release mutex: End of critical section (see below) pthread_mutex_unlock(&model_mutex); } while(iter <= MSVM_TRAIN_MAXIT && (!do_eval || ratio < accuracy) && !STOP && !thread_stop); // Compute return_status if(do_eval && ratio >= accuracy) return_status = 0; // optimum reached. // Free memory MSVM2fw_free_memory(&cache); free(delta[1]);free(delta); free(grad_threads); free(grad_data); pthread_exit((void*)return_status); } /* Allocate the memory for the cache */ void MSVM2fw_alloc_memory(struct TrainingCache *cache, const long Q, const long nb_data, const long chunk_size) { cache->table_chunk = (long *) calloc(chunk_size+1, sizeof(long)); cache->out_of_chunk = (long *) calloc(nb_data+1, sizeof(long)); cache->in_chunk = (long *) calloc(nb_data+1, sizeof(long)); cache->lp_sol = matrix(chunk_size, Q); cache->K = (double **)malloc(sizeof(double *) * (chunk_size+1)); cache->H_delta = matrix(chunk_size, Q); cache->alpha_update = matrix(chunk_size, Q); } /* Free the cache memory */ void MSVM2fw_free_memory(struct TrainingCache *cache) { free(cache->table_chunk); free(cache->out_of_chunk); free(cache->in_chunk); free(cache->K); free(cache->lp_sol[1]);free(cache->lp_sol); free(cache->H_delta[1]);free(cache->H_delta); free(cache->alpha_update[1]);free(cache->alpha_update); } /* Solve the LP subproblem by calling lp_solve API */ int MSVM2fw_solve_lp(double **gradient, const struct TrainingCache *cache, const struct Model *model) { long i,k,l,ind_pattern,y_i; const long Q = model->Q; const double Qd = (double)Q; const long chunk_size = cache->chunk_size; const int nRows = Q-1; const int nCols = chunk_size * (Q-1); double *obj = (double*)malloc(sizeof(double) * (1+nCols)); double *row = (double*)malloc(sizeof(double) * (1+nCols)); double *rhs = (double*)malloc(sizeof(double) * Q); long **lp_sol_table = matrix_l(nCols, 2); long **lp_sol_table_inv = matrix_l(chunk_size, Q); double *sol = (double*)malloc(sizeof(double) * (1+nRows+nCols)); double epsel; // Make LP lprec *lp = make_lp(0, nCols); set_add_rowmode(lp, TRUE); // Make objective function int col = 1; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; y_i = model->y[ind_pattern]; for(k=1; k<=Q; k++) if(k != y_i) { obj[col] = gradient[ind_pattern][k]; lp_sol_table[col][1] = i; // keep a table of correspondance between lp_sol_table[col][2] = k; // LPSOLVE vector of variables and lp_sol matrix lp_sol_table_inv[i][k] = col++; // lp_sol[i][k] = the 'lp_solve_table_inv[i][k]'-th variable for LPSOLVE } else cache->lp_sol[i][k] = 0; } set_obj_fn(lp, obj); /* // Make RHS of constraints // -- complete computation -- for(k=1; kin_chunk[i] == 0) { for(l=1; l<=Q; l++) rhs[k] += model->alpha[i][l]; rhs[k] -= Qd * model->alpha[i][k]; } } */ // Make RHS of constraints // -- updates to cache->rhs are made in compute_new_alpha() // to keep track of rhs // we only need to remove the contribution of the examples in the chunk for(k=1; klp_rhs[k]; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; for(l=1; l<=Q; l++) rhs[k] -= model->alpha[ind_pattern][l]; rhs[k] += Qd * model->alpha[ind_pattern][k]; } } // Make constraints for(k=1; ktable_chunk[i]; y_i = model->y[ind_pattern]; for(l=1; l<=Q; l++) if(l != y_i) { row[lp_sol_table_inv[i][l]] = -1.0; if(l == k) row[lp_sol_table_inv[i][l]] += Qd; } } add_constraint(lp, row, EQ, rhs[k]); } // No upper bound constraints of the type alpha <= C for MSVM2 // But we need an upper bound anyway for(col=1;col<=nCols;col++) set_upbo(lp, col, 1000); // End of LP making set_add_rowmode(lp, FALSE); //print_lp(lp); // Solve LP int jump = false; set_outputfile(lp,""); if(solve(lp)) { printf("Problem with the LP... \n"); jump = true; } else { // Recover solution in the matrix lp_sol get_primal_solution(lp, sol); // sol: template for lp_solve solution format // sol=[obj, constraints, variables] epsel = get_epsel(lp); // tolerance in lp_solve // Put solution into lp_sol for(col=1; col<= nCols; col++) { // Check feasibility of the col-th variable if(sol[nRows+col] < -epsel) { jump = true; break; } // Round off tolerance if(fabs(sol[nRows+col]) < epsel) sol[nRows+col] = 0.0; // Set the value in lp_sol matrix cache->lp_sol[lp_sol_table[col][1]][lp_sol_table[col][2]] = sol[nRows+col]; } } delete_lp(lp); free(obj); free(row); free(rhs); free(lp_sol_table[1]);free(lp_sol_table); free(lp_sol_table_inv[1]);free(lp_sol_table_inv); free(sol); return jump; } /* MSVM2fw_init_gradient({ALPHA_IS_ZERO,ALPHA_NOT_ZERO}, gradient, cache, model) */ void MSVM2fw_init_gradient(const enum AlphaInitType alpha_init_type, double **gradient, double **H_alpha, double **H_tilde_alpha, const struct Model *model) { long i,j,k,l,y_i; const long nb_data = model->nb_data; const long Q = model->Q; const double Qd = (double)Q; const double Qinv = 1. / (Qd-1.0); const enum Kernel_type nature_kernel = model->nature_kernel; const double *kernel_par = model->kernel_par; long dim_input = model->dim_input; double partial, H_alpha_ik, H_tilde_alpha_ik, partial2; if(alpha_init_type == ALPHA_IS_ZERO) { // Fast initialization for(i=1; i<=nb_data; i++) { for(k=1; k<=Q; k++) { gradient[i][k] = -Qinv; H_alpha[i][k] = 0.0; H_tilde_alpha[i][k] = 0.0; } gradient[i][model->y[i]] = 0.0; } } else { // Do a proper initialization based on the values of alpha for(i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { H_tilde_alpha_ik = 0.0; H_alpha_ik = 0.0; for(j=1; j<=nb_data; j++) { partial = 0.0; for(l=1; l<=Q; l++) partial -= model->alpha[j][l]; partial /= Qd; partial += model->alpha[j][k]; if(partial != 0.0) { partial2 = partial * ker(nature_kernel, model->X[i], model->X[j], dim_input,kernel_par); H_alpha_ik += partial2; H_tilde_alpha_ik += partial2; if(j==i) H_tilde_alpha_ik += partial / (2*model->C[y_i]); } } gradient[i][k] = H_tilde_alpha_ik - Qinv; H_alpha[i][k] = H_alpha_ik; H_tilde_alpha[i][k] = H_tilde_alpha_ik; } else { gradient[i][k] = 0.0; H_alpha[i][k] = 0.0; H_tilde_alpha[i][k] = 0.0; } } } } } /* Thread for updates of the gradient in parallel (spawn by main computing thread MSVM2fw_train_thread) */ void *MSVM2fw_update_gradient_thread(void *th_data) { // Recover thread data struct ThreadGradient_data *data = (struct ThreadGradient_data *) th_data; double **gradient = data->gradient; double **H_alpha = data->H_alpha; double **H_tilde_alpha = data->H_tilde_alpha; struct TrainingCache *cache = data->cache; const struct Model *model = data->model; const long start_i = data->start_i; const long end_i = data->end_i; // Local variables long i,j,k,l,y_i,ind_pattern; const long Q = model->Q; const double Qd = (double)Q; const long chunk_size = cache->chunk_size; double partial, H_tilde_alpha_update_ik, H_alpha_update_ik; for(i=start_i; i<=end_i; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { H_tilde_alpha_update_ik = 0.0; H_alpha_update_ik = 0.0; for(j=1; j<=chunk_size; j++) { ind_pattern = cache->table_chunk[j]; partial = 0.0; for(l=1; l<=Q; l++) partial -= cache->alpha_update[j][l]; partial /= Qd; partial += cache->alpha_update[j][k]; if(partial != 0.0) { H_tilde_alpha_update_ik += partial * cache->K[j][i]; H_alpha_update_ik += partial * cache->K[j][i]; if(ind_pattern==i) H_alpha_update_ik -= partial / (2.*model->C[y_i]); } } gradient[i][k] += H_tilde_alpha_update_ik; H_alpha[i][k] += H_alpha_update_ik; H_tilde_alpha[i][k] += H_tilde_alpha_update_ik; } } } pthread_exit(EXIT_SUCCESS); } /* Old-style non-threaded gradient update */ void MSVM2fw_update_gradient(double **gradient, double **H_alpha,double **H_tilde_alpha, struct TrainingCache *cache, const struct Model *model) { long i,j,k,l,y_i,ind_pattern; const long nb_data = model->nb_data; const long Q = model->Q; const double Qd = (double)Q; const long chunk_size = cache->chunk_size; double partial, H_tilde_alpha_update_ik, H_alpha_update_ik; for(i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { H_tilde_alpha_update_ik = 0.0; H_alpha_update_ik = 0.0; for(j=1; j<=chunk_size; j++) { ind_pattern = cache->table_chunk[j]; partial = 0.0; for(l=1; l<=Q; l++) partial -= cache->alpha_update[j][l]; partial /= Qd; partial += cache->alpha_update[j][k]; if(partial != 0.0) { H_tilde_alpha_update_ik += partial * cache->K[j][i]; H_alpha_update_ik += partial * cache->K[j][i]; if(ind_pattern==i) H_alpha_update_ik -= partial / (2.*model->C[y_i]); } } gradient[i][k] += H_tilde_alpha_update_ik; H_alpha[i][k] += H_alpha_update_ik; H_tilde_alpha[i][k] += H_tilde_alpha_update_ik; } } } } /* Same as WW_compute_H_delta() and LLW */ void MSVM2fw_compute_H_delta(double **delta, struct TrainingCache *cache, const struct Model *model) { long i,k,j,y_i,l; const long Q = model->Q; const double Qd = (double)Q; const long chunk_size = cache->chunk_size; double partial; for(i=1; i<=chunk_size; i++) { y_i = model->y[cache->table_chunk[i]]; for(k=1; k<=Q; k++) { cache->H_delta[i][k] = 0.0; if(k != y_i) { for(j=1; j<=chunk_size; j++) { partial = 0.0; for(l=1; l<=Q; l++) partial -= delta[j][l]; partial /= Qd; partial += delta[j][k]; cache->H_delta[i][k] += partial * cache->K[i][cache->table_chunk[j]]; } } } } } int MSVM2fw_check_opt_sol(double **gradient, struct TrainingCache *cache, const struct Model *model) { double gradient_alpha = 0.0; double gradient_Gamma = 0.0; double gradient_diff = 0.0; long i,k,ind_pattern, y_i; const long Q = model->Q; const long chunk_size = cache->chunk_size; int jump = false; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; y_i = model->y[ind_pattern]; for(k=1; k<=Q; k++) if(k != y_i) { gradient_alpha += gradient[ind_pattern][k] * model->alpha[ind_pattern][k]; gradient_Gamma += gradient[ind_pattern][k] * cache->lp_sol[i][k]; } } gradient_diff = gradient_alpha - gradient_Gamma; if(gradient_diff <= 0.0) { if(gradient_diff < -small) { printf("\nInappropriate subset selection...\n"); printf("\ngradient^T (alpha - gamma): %lf", gradient_diff); } jump = true; } cache->gradient_diff = gradient_diff; return jump; } /* Update model paramaters alpha_ik Return the difference in number of SVs */ long MSVM2fw_compute_new_alpha(const double theta_opt, const struct TrainingCache *cache, struct Model *model) { long i,k,l,ind_pattern; const long Q = model->Q; const double Qd = (double)Q; const long chunk_size = cache->chunk_size; long nb_SV = 0; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; model->partial_average_alpha[ind_pattern] = 0.0; // Assume x_i is not a SV if(cache->activeset[ind_pattern]) { cache->activeset[ind_pattern] = 0; nb_SV--; } for(k=1; k<=Q; k++) { if(k!=model->y[ind_pattern]) { cache->alpha_update[i][k] = theta_opt * ( cache->lp_sol[i][k] - model->alpha[ind_pattern][k] ); model->alpha[ind_pattern][k] += cache->alpha_update[i][k]; model->sum_all_alpha += cache->alpha_update[i][k]; if(model->alpha[ind_pattern][k] < 0.0) { cache->alpha_update[i][k] -= model->alpha[ind_pattern][k]; model->alpha[ind_pattern][k] = 0.0; } else if(model->alpha[ind_pattern][k] != 0.0 ) { // Update nb_SV and activeset if(cache->activeset[ind_pattern] == 0) { cache->activeset[ind_pattern] = 1; nb_SV++; } } model->partial_average_alpha[ind_pattern] += model->alpha[ind_pattern][k]; } else cache->alpha_update[i][k] = 0; } model->partial_average_alpha[ind_pattern] /= Qd; // Update RHS of constraints in LP for(k=1; klp_rhs[k] += cache->alpha_update[i][l]; cache->lp_rhs[k] -= Qd * cache->alpha_update[i][k]; } } return nb_SV; } void MSVM2fw_compute_delta(double **delta, const struct TrainingCache *cache, const struct Model *model) { long i,k,ind_pattern; const long Q = model->Q; const long chunk_size = cache->chunk_size; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; for(k=1; k<=Q; k++) delta[i][k] = model->alpha[ind_pattern][k] - cache->lp_sol[i][k]; } } double MSVM2fw_compute_theta_opt(double **delta, struct TrainingCache *cache, const struct Model *model) { long i,k; const long chunk_size = cache->chunk_size; const long Q = model->Q; double theta_opt, denominator = 0.0; MSVM2fw_compute_H_delta(delta, cache,model); for(i=1; i<=chunk_size; i++) { for(k=1; k<=Q; k++) denominator += delta[i][k] * cache->H_delta[i][k]; } if(denominator <= 0) { printf("\nWrong estimate of theta: denominator= %e\n", denominator); exit(0); } theta_opt = cache->gradient_diff / denominator; if(theta_opt > 1.0) theta_opt = 1.0; return theta_opt; } MSVMpack1.2/src/libevalMSVM_LLW.c0000644000175000017500000002651411644772425015540 0ustar lauerlauer/* Copyright 2001, 2002, 2003 Yann Guermeur and Andre Elisseeff */ /* 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 2 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, write to the Free Software */ /* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA */ /*----------------------------------------------------------------------------*/ /* Name : libevalMSVM_LLW.c */ /* Version : 2.0 */ /* Creation : 04/30/00 */ /* Last update : 01/20/11 */ /* Subject : Implementation of the M-SVM of Lee, Lin and Wahba */ /* Module : evaluation functions */ /* Author : Fabien Lauer and Yann Guermeur Yann.Guermeur@loria.fr */ /*----------------------------------------------------------------------------*/ #include "libevalMSVM_LLW.h" /* Main evaluation function for LLW: compute the ratio (dual / upper bound) */ double MSVM_LLW_eval(double *best_primal_upper_bound, double **gradient, double **H_alpha, struct Model *model, const int verbose, FILE *fp) { const long Q = model->Q; const long nb_data = model->nb_data; double R_emp, ratio; struct Cache cache; cache.H_alpha = H_alpha; cache.verbose = verbose; long **mat_conf = matrix_l(Q,Q); long i,training_errors; long **margin_vect = matrix_l(nb_data, Q); long *nb_margin_vect = (long*)malloc(sizeof(long) * (Q+1)); LLW_check_feasible_sol(model,NULL,verbose); LLW_check_margin_vect(margin_vect,nb_margin_vect,model); LLW_estimate_b(gradient, margin_vect, nb_margin_vect, &cache, model); R_emp = LLW_eval_training(gradient,mat_conf,&cache,model); // Compute training error training_errors = model->nb_data; for(i=1;i<=Q;i++) training_errors -= mat_conf[i][i]; model->training_error = (double)training_errors/(double)model->nb_data; // Compute the ratio dual/upper bound (stopping criterion) LLW_compute_obj_dual(&cache,model); LLW_compute_obj_primal(R_emp,&cache,model); // Make sure the upper bound does not increase if(cache.primal > *best_primal_upper_bound) cache.primal = *best_primal_upper_bound; else *best_primal_upper_bound = cache.primal; ratio = cache.dual / cache.primal; if(verbose) { printf("\nDifference between the primal and the dual: %lf -> %lf", cache.primal, cache.dual); printf("\n(ratio %5.2lf \%%)\n", 100.0 * ratio); printf("\n*** Training performance\n"); display_stats(Q, mat_conf); display_full_stats(Q, mat_conf); } // Log info if(fp != NULL) fprintf(fp, "%lf %lf \n",cache.dual,cache.primal); // Free memory free(mat_conf[1]); free(mat_conf); free(margin_vect[1]); free(margin_vect); free(nb_margin_vect); return ratio; } /* output = LLW_function( k, x, model) Compute the real-valued output of model (without bias term) for the k-th category on pattern x */ double LLW_function(long category, void *vector, const struct Model *model) { const long nb_data = model->nb_data; const long Q = model->Q; const double Qd = (double)Q; const enum Kernel_type nature_kernel = model->nature_kernel; const double *kernel_par = model->kernel_par; long dim_input = model->dim_input; long i,k; double partial, result = 0.0; for(i=1; i<=nb_data; i++) { partial = 0.0; for(k=1; k<=Q; k++) partial += model->alpha[i][k]; partial /= Qd; partial -= model->alpha[i][category]; if(partial != 0.0) result += partial * ker(nature_kernel, model->X[i], vector, dim_input, kernel_par); } return result; } /* label = LLW_classify(x, model, real_outputs) Classify x and output the label. If real_outputs is not NULL, also compute the Q real-valued outputs of the model and store them in (real_outputs[1]...real_outpust[Q]). Note: this function is faster than calling Q times LLW_function */ long LLW_classify(void *vector, const struct Model *model, double *real_outputs) { const long nb_data = model->nb_data; const long Q = model->Q; const double Qd = (double)Q; const enum Kernel_type nature_kernel = model->nature_kernel; const double *kernel_par = model->kernel_par; long dim_input = model->dim_input; long i,k; long label = 1; double maxoutput,partial, kernel; int use_real_outputs = true; if(real_outputs==NULL) { real_outputs = (double *)malloc(sizeof(double) * (Q+1)); use_real_outputs = false; } for(k=1;k<=Q;k++) real_outputs[k] = model->b_SVM[k]; for(i=1; i<=nb_data; i++) { partial = 0.0; for(k=1; k<=Q; k++) partial += model->alpha[i][k]; if(partial != 0.0) { partial /= Qd; kernel = ker(nature_kernel, model->X[i], vector, dim_input, kernel_par); for (k=1; k<=Q; k++) real_outputs[k] += (partial - model->alpha[i][k]) * kernel; } } maxoutput = real_outputs[1]; for(k=2; k<=Q; k++) if(real_outputs[k] > maxoutput) { maxoutput = real_outputs[k]; label = k; } if(!use_real_outputs) free(real_outputs); return label; } void LLW_check_feasible_sol(const struct Model *model, char *alpha_file,int verbose) { char command[taille]; const long Q = model->Q; const long nb_data = model->nb_data; const double *C = model->C; double norm; int rc; long i,k; double *constraints, sum_all_alpha = 0.0; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) if((model->alpha[i][k] < 0.0) || (model->alpha[i][k] > C[model->y[i]])) { printf("\nNo feasible solution: alpha[%ld][%ld] = %1.12lf > %lf\n\n", i, k, model->alpha[i][k], C[model->y[i]]); exit(0); } constraints = (double *) calloc(Q+1, sizeof(double)); for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) sum_all_alpha += model->alpha[i][k]; for(k=1; k<=Q; k++) constraints[k] = sum_all_alpha; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) constraints[k] -= Q * model->alpha[i][k]; for(k=1; k<=Q; k++) constraints[k] /= Q; if(verbose) { printf("\nSatisfaction of the equality constraints:\n\n"); for(k=1; k<=Q; k++) printf("%11.8lf\n", constraints[k]); } norm = 0.0; for(k=1; k<=Q; k++) norm += constraints[k] * constraints[k]; norm = sqrt(norm); if(norm >= 1e-4) { printf("\nLarge deviation of the equality constraints (%lf)...\n",norm); exit(0); } if(alpha_file != NULL) { sprintf(command, "cp %s Save_alpha/.", alpha_file); rc = system(command); } free(constraints); } void LLW_check_margin_vect(long **margin_vect, long *nb_margin_vect, const struct Model *model) { long i,k,l,y_i; const long Q = model->Q; const long nb_data = model->nb_data; const double *C = model->C; int over=false; double *average = (double*)malloc(sizeof(double) * (Q+1)); double *radius = (double*)malloc(sizeof(double) * (Q+1)); const double radius_step = 1000.0; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) margin_vect[i][k] = 0; for(k=1; k<=Q; k++) { average[k] = C[k] / 2.0;; radius[k] = C[k] / radius_step; } while(over == false) { for(k=1; k<=Q; k++) nb_margin_vect[k] = 0; for(i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) if((k != y_i) && fabs(model->alpha[i][k] - average[model->y[i]]) <= radius[k]) { margin_vect[i][k] = 1; nb_margin_vect[k]++; } } over = true; for(k=1; k<=Q; k++) if(nb_margin_vect[k] == 0) { over = false; if((average[k] - radius[k]) > (average[k] / 5000.0)) radius[k] += average[k] / radius_step; else radius[k] = (radius[k] + average[k]) / 2.0; } } free(radius); free(average); } /* Compute the training error */ double LLW_eval_training(double **gradient, long **mat_conf, const struct Cache *cache, const struct Model *model) { long i,k,l,y_i; const long Q = model->Q; const long nb_data = model->nb_data; long ind_max = 0; double maximum, xi_ik; double *output = (double *)malloc((Q+1) * sizeof(double)); double R_emp = 0.0; if(mat_conf != NULL) { for(k=1; k<=Q; k++) for(l=1; l<=Q; l++) mat_conf[k][l] = 0; } for(i=1; i<=nb_data; i++) { y_i = model->y[i]; output[y_i] = 0.0; for(k=1; k<=Q; k++) if(k != y_i) { output[k] = -cache->H_alpha[i][k] + model->b_SVM[k]; output[y_i] -= output[k]; xi_ik = -gradient[i][k] + model->b_SVM[k]; if(xi_ik > 0.0) R_emp += model->C[y_i] * xi_ik; } ind_max = 1; maximum = output[1]; for(k=2; k<=Q; k++) if(output[k] > maximum) { maximum = output[k]; ind_max = k; } if(mat_conf != NULL) mat_conf[y_i][ind_max]++; } free(output); return R_emp; } void LLW_estimate_b(double **gradient, long **margin_vect, long *nb_margin_vect, const struct Cache *cache, struct Model *model) { long i,k; const long Q = model->Q; const long nb_data = model->nb_data; double sum = 0.0, max_alpha = 0.0; for(k=1; k<=Q; k++) model->b_SVM[k] = 0.0; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) if(margin_vect[i][k] == 1) model->b_SVM[k] += gradient[i][k]; if(cache->verbose) printf("\nVector b before centering\n\n"); for(k=1; k<=Q; k++) { if(nb_margin_vect[k] > 0) model->b_SVM[k] /= (double) nb_margin_vect[k]; else printf("*** in LLW_estimate_b: nb_sum_vect[%ld] = 0\n", k); sum += model->b_SVM[k]; if(cache->verbose) printf(" b_%1ld = %lf\n", k, model->b_SVM[k]); } sum /= Q; max_alpha = 0.0; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) if(model->alpha[i][k] > max_alpha) max_alpha = model->alpha[i][k]; if(max_alpha > 0.0) for(k=1; k<=Q; k++) model->b_SVM[k] -= sum; else for(k=1; k<=Q; k++) model->b_SVM[k] = 0.0; } void LLW_compute_obj_dual(struct Cache *cache, struct Model *model) { long i,k; const long Q = model->Q; const long nb_data = model->nb_data; double alpha_H_alpha = 0; double L_form_dual = 0; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) { alpha_H_alpha += cache->H_alpha[i][k] * model->alpha[i][k]; L_form_dual += model->alpha[i][k]; } model->sum_all_alpha = L_form_dual; cache->alpha_H_alpha = alpha_H_alpha; cache->dual = -0.5*alpha_H_alpha + (L_form_dual / ((double)Q - 1.0)); } void LLW_compute_obj_primal(double R_emp, struct Cache *cache, const struct Model *model) { cache->primal = 0.5 * cache->alpha_H_alpha + R_emp; if(cache->primal < cache->dual) { printf("\nInconsistency in the values of the objective functions...\n primal = %lf + %lf = %lf < %lf (dual)\n", 0.5 * cache->alpha_H_alpha, R_emp , cache->primal, cache->dual); /* exit(0); */ } } MSVMpack1.2/src/libevalMSVM.c0000644000175000017500000002773711651473743015031 0ustar lauerlauer/* Copyright 2008-2010 Yann Guermeur */ /* 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 2 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, write to the Free Software */ /* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA*/ /*--------------------------------------------------------------------------*/ /* Name : libevalMSVM.c */ /* Version : 2.0 */ /* Creation : 06/20/08 */ /* Last update : 02/04/11 */ /* Subject : Evaluation functions for MSVMpack */ /* Module : Wrapper functions */ /* Author : Fabien Lauer and Yann Guermeur Yann.Guermeur@loria.fr */ /*--------------------------------------------------------------------------*/ #include "libevalMSVM.h" #include "libevalMSVM_WW.h" #include "libevalMSVM_CS.h" #include "libevalMSVM_LLW.h" #include "libevalMSVM_2.h" /* ratio = MSVM_eval(&ub, gradient, H_alpha, {H_tilde_alpha,NULL}, model, verbose, fp) Evaluate the ratio between the value of the dual objective function and the upper bound on the optimum. use verbose = 0 to avoid printed output fp: FILE_ptr to the log file recording the values of the upper bound and dual objective function (use fp = NULL to deactivate the log file) This is a wrapper function calling the appropriate eval function for the model type */ double MSVM_eval(double *best_primal_upper_bound, double **gradient, double **H_alpha, double **H_tilde_alpha, struct Model *model, const int verbose, FILE *fp) { double ratio; switch (model->type) { case WW: ratio = MSVM_WW_eval(best_primal_upper_bound, gradient, H_alpha, model, verbose, fp); break; case CS: ratio = MSVM_CS_eval(best_primal_upper_bound, H_alpha, model, verbose, fp); break; case LLW: ratio = MSVM_LLW_eval(best_primal_upper_bound, gradient, H_alpha, model, verbose, fp); break; case MSVM2: ratio = MSVM_2_eval(best_primal_upper_bound, gradient, H_alpha, H_tilde_alpha, model, verbose, fp); break; default: printf("MSVM_eval: unknown model type.\n"); ratio = 0; break; } return ratio; } /* Standardize the vector b such that sum(b_k) = 0 */ void standardize_b(double *b_SVM, const long Q) { long k; double sum_b = 0.0; for(k=1; k<=Q; k++) sum_b += b_SVM[k]; sum_b /= Q; for(k=1; k<=Q; k++) b_SVM[k] -= sum_b; } /* label = MSVM_classify(x, model, real_outputs) Compute the label of x WITHOUT TAKING CARE OF NORMALIZATION. (use MSVM_classify_set() to include normalization) If real_outputs is not NULL, also provide the Q real-valued outputs of the model in (real_outputs[1]...real_outputs[Q]). This is a wrapper function calling the appropriate classification function for the model type */ long MSVM_classify(void *x, const struct Model *model, double *real_outputs) { long label; switch(model->type) { case WW: label = WW_classify(x, model, real_outputs); break; case CS: label = CS_classify(x, model, real_outputs); break; case LLW: label = LLW_classify(x, model, real_outputs); break; case MSVM2: label = MSVM_2_classify(x, model, real_outputs) ; break; default: printf("MSVM_classify: unknown model type.\n"); return 0; } return label; } void MSVM_print_outputs(double **outputs, long *labels, long *y, long nb_data, long Q, char *outputs_file) { long i,k; FILE *fc; if(outputs_file != NULL) { if((fc=fopen(outputs_file, "w"))==NULL) printf("\nFile of outputs %s cannot be open, using standard output.\n", outputs_file); } if(outputs_file == NULL || fc == NULL) { for(i=1;i<=nb_data;i++) { for(k=1; k<=Q; k++) printf("%12.6lf ", outputs[i][k]); printf("\t-> %ld",labels[i]); if(y != NULL) { if(labels[i] == y[i]) printf(" OK"); else printf(" WRONG: true label is %ld",y[i]); } printf("\n"); } } else { for(i=1;i<=nb_data;i++) { for(k=1; k<=Q; k++) fprintf(fc, "%12.6lf ", outputs[i][k]); fprintf(fc, "%ld\n",labels[i]); } } } /* MSVM_classify_set(labels, X, y, m, outputs_file, model, nprocs) Compute the predicted labels of an M-SVM for a set of m data points X. Also compute the test error and some statistics if y is not NULL. Resulting output is saved into outputs_file or printed on screen only if outputs_file is NULL. If labels is NULL, the predicted labels are not stored in memory. Note: this function takes care of data normalization if needed (X should not be normalized). The function launches nprocs threads to compute in parallel over nprocs CPUs. The SET_SIZE constant defined in libevalMSVM.h defines the size of the data subsets on which the computations are performed in parallel. */ void MSVM_classify_set(long *labels, void **X, long *y, long nb_data, char *outputs_file, struct Model *model, int nprocs) { // Check number of threads if (nprocs <= 0 || nprocs >= get_nprocessors()) nprocs = get_nprocessors(); int t; pthread_t *threads=(pthread_t *)malloc(sizeof(pthread_t) * nprocs); // threads id void *status; // for pthread_join int rc; // return code of pthread functions int running_threads; long **mat_conf, ***mat_confs; long l,k; const long Q = model->Q; double **outputs = matrix(nb_data, Q); int free_labels = false; if(labels==NULL) { labels = (long *)malloc(sizeof(long) * (nb_data+1)); free_labels = true; } // Prepare data for computing threads struct ThreadClassifyData thread_data; thread_data.model = model; if(y != NULL) { mat_conf = matrix_l(Q,Q); for(k=1; k<=Q; k++) for(l=1; l<=Q; l++) mat_conf[k][l] = 0; mat_confs = (long***)malloc(sizeof(long***) * nprocs); for(t=0;t SET_SIZE) { thread_data.nb_data = SET_SIZE; } thread_data.thread_id = t; thread_data.X = &X[next_set_index]; thread_data.labels = &labels[next_set_index]; thread_data.outputs = &outputs[next_set_index]; if(y != NULL) { thread_data.mat_conf = mat_confs[t]; thread_data.y = &y[next_set_index]; } rc = pthread_create(&threads[t], NULL, MSVM_classify_set_thread, (void *) &thread_data); next_set_index += thread_data.nb_data; running_threads++; t++; } // Wait for threads to terminate for(t=0;tthread_id; const struct Model *model = data->model; void **X = data->X; long *labels = data->labels ; const long nb_data =data->nb_data; long **mat_conf = data->mat_conf; long *y=data->y; double **outputs = data->outputs; pthread_mutex_unlock(&thread_classify_data_mutex); // Release thread_data for next thread // Local variables long i,k,l,label,dim_bit; const long dim_input = model->dim_input; void *x; double *xd, **Xd; float *xf, **Xf; int *xi, **Xi; short int *xs, **Xs; unsigned char *xb, **Xb; const enum Datatype datatype = model->datatype; // Allocate a temporary vector (aligned) switch(datatype) { case DOUBLE: xd = MALLOC(double,dim_input+1); Xd = (double**)X; x = (void*)(xd + ALIGNMENT(double)); break; case FLOAT: xf = MALLOC(float, dim_input+1); Xf = (float**)X; x = (void*)(xf + ALIGNMENT(float)); break; case INT: xi = MALLOC(int, dim_input+1); Xi = (int**)X; x = (void*)(xi + ALIGNMENT(int)); break; case SHORT: xs = MALLOC(short int, dim_input+1); Xs = (short int**)X; x = (void*)(xs + ALIGNMENT(short int)); break; case BYTE: xb = MALLOC(unsigned char, dim_input+1); Xb = (unsigned char**)X; x = (void*)(xb + ALIGNMENT(unsigned char)); break; case BIT: dim_bit = dim_input/32; if(dim_input%32) dim_bit++; xi = MALLOC(int, dim_bit+1); Xi = (int**)X; x = (void*)(xi + ALIGNMENT(int)); break; default: printf("MSVM_classify_set(): Unknown data type.\n"); exit(0); } int do_matconf = false; if(y != NULL && mat_conf != NULL) { for(k=1; k<=model->Q; k++) for(l=1; l<=model->Q; l++) mat_conf[k][l] = 0; do_matconf = true; } for(i=1; i<=nb_data; i++) { switch(datatype) { case DOUBLE: if (model->normalization == NULL) { for (k=1;k<=dim_input;k++) xd[k + ALIGNMENT(double)] = Xd[i][k]; } else { for (k=1;k<=dim_input;k++) { if(model->normalization[2][k] != 0.0) xd[k + ALIGNMENT(double)] = (Xd[i][k] - model->normalization[1][k]) / model->normalization[2][k]; else xd[k + ALIGNMENT(double)] = Xd[i][k]; } } break; case FLOAT: if (model->normalization == NULL) { for (k=1;k<=dim_input;k++) xf[k + ALIGNMENT(float)] = Xf[i][k]; } else { for (k=1;k<=dim_input;k++) { if(model->normalization[2][k] != 0.0) xf[k + ALIGNMENT(float)] = (Xf[i][k] - (float)model->normalization[1][k]) / (float)model->normalization[2][k]; else xf[k + ALIGNMENT(float)] = Xf[i][k]; } } break; case INT: for (k=1;k<=dim_input;k++) xi[k + ALIGNMENT(int)] = Xi[i][k]; break; case SHORT: for (k=1;k<=dim_input;k++) xs[k + ALIGNMENT(short int)] = Xs[i][k]; break; case BYTE: for (k=1;k<=dim_input;k++) xb[k + ALIGNMENT(unsigned char)] = Xb[i][k]; break; case BIT: for (k=1;k<=dim_bit;k++) xi[k + ALIGNMENT(int)] = Xi[i][k]; break; default: break; } label = MSVM_classify(x, model, outputs[i]); labels[i] = label; if(do_matconf) mat_conf[y[i]][label]++; if((i % step) == 0) { printf("."); fflush(stdout); } } switch(datatype) { case DOUBLE: FREE(xd); break; case FLOAT: FREE(xf); break; case INT: FREE(xi); break; case SHORT: FREE(xs); break; case BYTE: FREE(xb); break; case BIT: FREE(xi); break; default: break; } pthread_exit(EXIT_SUCCESS); } MSVMpack1.2/src/libtrainMSVM_2.c~0000644000175000017500000011205611761347766015632 0ustar lauerlauer/* Copyright 2008-2010 Yann Guermeur */ /* 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 2 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, write to the Free Software */ /* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA*/ /*--------------------------------------------------------------------------*/ /* Name : libtrainMSVM_2.c */ /* Version : 2.0 */ /* Creation : 06/20/08 */ /* Last update : 01/20/11 */ /* Subject : Training algorithm of the M-SVM^2 */ /* Algo. : Rosen's algorithm + decomposition method */ /* Author : Fabien Lauer and Yann Guermeur Yann.Guermeur@loria.fr */ /*--------------------------------------------------------------------------*/ #include "libtrainMSVM_2.h" /* MSVM2 training function (Rosen algorithm) Solves the dual problem wrt alpha: min 1/2 alpha' H_tilde alpha - (1/Q-1) sum (alpha) s.t. alpha_ik >= 0, for all i,k, such that 1 <= i <= m, 1 <= k != y_i <= Q sum_i (alpha_ik - average_alpha_k) = 0, for all k, 1 <= k <= Q where H_tilde_ik,jl = (delta_k,l - 1/Q) ( k(x_i,x_j) + (1/2C)delta_i,j ) */ long MSVM_2_train(struct Model *model, struct Data *training_set, long chunk_size, const double accuracy, int cache_memory, const int nprocs, char *alpha0_file, char *model_tmp_file, char *log_file) { long return_status = -1; FILE *fp; int t; pthread_t *threads = (pthread_t *)malloc(sizeof(pthread_t) * nprocs); // threads id void *status; // for pthread_join int rc; // return code of pthread functions int feasible; pthread_t thread_monitor; enum AlphaInitType alphaiszero; if(training_set != NULL) { // Initialize model for this particular training set model_load_data(model, training_set); // Chetck if a kernel_par has been set if(model->nature_kernel != LINEAR && model->kernel_par == NULL) set_default_kernel_par(model); } // Log file if (log_file != NULL) { printf("\nLog training info in %s ...\n", log_file); fp = fopen(log_file,"a"); } else fp = NULL; // Initialize alpha and b if(training_set != NULL) // otherwise resume training init_alpha_b(model, alpha0_file); // use init_alpha_b(model, NULL); to initialize all alpha to 0 feasible = MSVM_2_check_feasible_sol_init(model); if(feasible == true) printf("\nVector alpha is a feasible solution...\n"); else { printf("\n Initial alpha_0 is not a feasible solution.\n"); return -1; } if(training_set == NULL || alpha0_file != NULL) alphaiszero = ALPHA_NOT_ZERO; else alphaiszero = ALPHA_IS_ZERO; EVAL = 0; // triggered by signal handler to call eval STOP = 0; // triggered by user to stop training iter = 1; // number of iterations (over all threads) // Prepare monitoring of model struct MonitorData monitor_data; monitor_data.model_tmp_file = model_tmp_file; monitor_data.period = MONITOR_PERIOD; monitor_data.model = model; pthread_create(&thread_monitor, NULL, MSVM_monitor_model_thread, (void *) &monitor_data); /* Allocate memory for shared ressources */ double **gradient = matrix(model->nb_data, model->Q); double **H_alpha = matrix(model->nb_data, model->Q); double **H_tilde_alpha = matrix(model->nb_data, model->Q); double best_primal_upper_bound = HUGE_VAL; int *activeset = (int *)calloc(model->nb_data+1, sizeof(int)); // including the kernel cache: struct KernelCache kc; unsigned long cache_size = (unsigned long)cache_memory * MBYTES; kernel_initialize_cache(cache_size, &kc, model); printf("Initialization... ");fflush(stdout); // Initialize gradient MSVM_2_init_gradient(alphaiszero, gradient, H_alpha, H_tilde_alpha, model); printf("Done.\n"); // Initialize display if(accuracy>0) print_training_info(0,0,0,model->type); else { printf("Training...");fflush(stdout); } // Prepare data for computing threads long nb_SV = 0; struct ThreadData thread_data; thread_data.nprocs = nprocs; thread_data.model = model; thread_data.kernelcache = &kc; thread_data.chunk_size = chunk_size; thread_data.accuracy = accuracy; thread_data.gradient = gradient; thread_data.H_alpha = H_alpha; thread_data.H_tilde_alpha = H_tilde_alpha; thread_data.best_primal_upper_bound = &best_primal_upper_bound; thread_data.activeset = activeset; thread_data.nb_SV = &nb_SV; thread_data.logfile_ptr = fp; // Launch computing threads for(t=0;tthread_id; const int nprocs = data->nprocs; struct Model *model = data->model; struct KernelCache *kernelcache = data->kernelcache; long chunk_size = data->chunk_size; const double accuracy = data->accuracy; double **gradient = data->gradient; double **H_alpha = data->H_alpha; double **H_tilde_alpha = data->H_tilde_alpha; double *best_primal_upper_bound = data->best_primal_upper_bound; int *activeset = data->activeset; long *nb_SV = data->nb_SV; FILE *fp = data->logfile_ptr; pthread_mutex_unlock(&thread_data_mutex); // Release thread_data for next thread // Local variables long return_status = -1; int do_eval, optimum, descent, feasible; char yesno; // Prepare the cache struct TrainingCache cache; cache.chunk_size = chunk_size; MSVM_2_alloc_memory(&cache, model->Q, model->nb_data, chunk_size); cache.activeset = activeset; cache.kc = kernelcache; double **vector_u = matrix(cache.nb_constraints, 1); double **vector_y_bar = matrix(cache.nb_variables, 1); double **vector_gradient = matrix(cache.nb_variables, 1); double theta_max, theta_opt; if(accuracy == 0) do_eval = 0; else do_eval = 1; /* Prepare parallel gradient computations: - the gradient vector is split into NUMTHREADS_GRAD parts (along i) - each part is updated by a different thread */ // max number of threads for gradient updates is nprocs pthread_t *grad_threads = (pthread_t *)malloc(sizeof(pthread_t) * nprocs); // start with 1 thread (main load on kernel evaluations) int numthreads_grad = 1; void *status; int rc; long k; struct ThreadGradient_data *grad_data = (struct ThreadGradient_data *)malloc(sizeof(struct ThreadGradient_data) * nprocs); // Disable parallel gradient computation for small data sets int parallel_gradient_update = 1; if(model->nb_data < 5000) parallel_gradient_update = 0; if(parallel_gradient_update) { for(k=0;knb_data / numthreads_grad; for(k=1;knb_data / numthreads_grad -1; } if(numthreads_grad>1) { grad_data[numthreads_grad-1].start_i = grad_data[numthreads_grad-2].end_i + 1; grad_data[numthreads_grad-1].end_i = model->nb_data; } } // Switch to nprocs/4 threads for gradient update when 25% of the kernel matrix is cached int percentage_step = 1; long percentage = model->nb_data / 4; int next_numthreads_grad = nprocs/4; if(next_numthreads_grad == 0) next_numthreads_grad = 1; // Main loop double ratio = 0.0; // stopping criterion (dual / upper bound) int thread_stop = 0; do { if((TRAIN_SMALL_STEP < TRAIN_STEP) && (iter%TRAIN_SMALL_STEP) == 0) { printf("."); fflush(stdout); } // Select a random chunk of data to optimize select_random_chunk(&cache,model); // Compute the kernel submatrix for this chunk compute_K(&cache,model); // Enter Critical Section (using and modifying the model) pthread_mutex_lock(&model_mutex); MSVM_2_compute_gradient_chunk(vector_gradient,gradient, &cache,model); MSVM_2_compute_A0(&cache,model); MSVM_2_compute_vector_u(vector_u,vector_gradient,&cache,model); optimum = MSVM_2_check_vector_u(vector_u,vector_gradient,&cache,model); if(optimum == 0 ) // u is correct and optimum not reached yet { MSVM_2_compute_vector_y_bar(vector_y_bar, vector_u, vector_gradient, &cache, model); descent = MSVM_2_check_vector_y_bar(vector_y_bar,vector_u,vector_gradient, &cache,model); if(descent == 0) while((descent == 0) && (optimum == 0)) { MSVM_2_simplify_A0(vector_u, &cache,model); MSVM_2_compute_vector_u(vector_u,vector_gradient,&cache,model); optimum = MSVM_2_check_vector_u(vector_u,vector_gradient,&cache,model); if((optimum == 0)) { MSVM_2_compute_vector_y_bar(vector_y_bar,vector_u,vector_gradient, &cache,model); descent = MSVM_2_check_vector_y_bar(vector_y_bar,vector_u,vector_gradient, &cache,model); } } if((optimum == 0) && (descent > 0)) { theta_max = MSVM_2_compute_theta_max(&cache,model); theta_opt = MSVM_2_compute_theta_opt(theta_max,&cache,model); *nb_SV += MSVM_2_compute_new_alpha(theta_opt,&cache,model); if(parallel_gradient_update) { // Update gradient in parallel for(k=0;ktype); if(do_eval && ratio > accuracy) STOP = 1; if(EVAL) // if interrupted by user (otherwise let the ratio decide if we go on training) { printf("\n *** Do you want to continue training ([y]/n)? "); yesno = getchar(); if(yesno=='n') { STOP = 1; } EVAL = 0; // reset interruption trigger } } // Release kernel submatrix in cache release_K(&cache); // Check if a sufficient % of the kernel matrix is cached if( parallel_gradient_update && cache.kc->max_idx >= percentage ) { // and switch thread to compute gradient upates instead of kernel rows if it is thread_stop = switch_thread(nprocs, &numthreads_grad, &next_numthreads_grad, &percentage, &percentage_step, grad_data, thread_id, model->nb_data); // (threads are actually stopped to leave the CPUs // to other threads that will compute gradient updates) } iter++; // Release mutex: End of critical section (see below) pthread_mutex_unlock(&model_mutex); } while(iter <= MSVM_TRAIN_MAXIT && (!do_eval || ratio < accuracy) && !STOP && !thread_stop); // Compute return_status if(do_eval && ratio >= accuracy) return_status = 0; // optimum reached. // Free memory MSVM_2_free_memory(&cache); free(vector_u[1]);free(vector_u); free(vector_y_bar[1]); free(vector_y_bar); free(vector_gradient[1]); free(vector_gradient); free(grad_threads); free(grad_data); pthread_exit((void*)return_status); } /* Allocate the memory for the cache */ void MSVM_2_alloc_memory(struct TrainingCache *cache, const long Q, const long nb_data, const long chunk_size) { long nb_variables = chunk_size * (Q-1); long nb_constraints = nb_variables + (Q-1); cache->in_chunk = (long *) calloc(nb_data+1, sizeof(long)); cache->out_of_chunk = (long *) malloc((nb_data+1) * sizeof(long)); cache->table_chunk = (long *) calloc(chunk_size+1, sizeof(long)); cache->K = (double **)malloc(sizeof(double *) * (chunk_size+1)); cache->A0 = matrix(nb_constraints, nb_variables); cache->A0T = matrix(nb_variables, nb_constraints); cache->A0A0T = matrix(nb_constraints, nb_constraints); cache->A0A0T_ref = matrix(nb_constraints, nb_constraints); cache->A0A0T_1 = matrix(nb_constraints, nb_constraints); cache->vector_z_bar = matrix(nb_variables, 1); cache->H_y_bar = matrix(chunk_size, Q); cache->matrix_y_bar = matrix(chunk_size, Q); cache->alpha_update = matrix(chunk_size, Q); // Computational templates cache->eigenvalues = (double *) calloc(nb_constraints+1, sizeof(double)); cache->working_matrix1 = matrix(nb_constraints, nb_constraints); cache->working_matrix2 = matrix(nb_constraints, nb_constraints); // For debug purposes (used in study_unfeasible) cache->constraints = (double *) calloc(Q+1, sizeof(double)); cache->nb_constraints = nb_constraints; cache->nb_variables = nb_variables; } /* Free the cache memory */ void MSVM_2_free_memory(struct TrainingCache *cache) { free(cache->table_chunk); free(cache->in_chunk); free(cache->out_of_chunk); free(cache->K); free(cache->A0[1]);free(cache->A0); free(cache->A0T[1]);free(cache->A0T); free(cache->A0A0T[1]);free(cache->A0A0T); free(cache->A0A0T_1[1]);free(cache->A0A0T_1); free(cache->A0A0T_ref[1]);free(cache->A0A0T_ref); free(cache->vector_z_bar[1]);free(cache->vector_z_bar); free(cache->H_y_bar[1]);free(cache->H_y_bar); free(cache->matrix_y_bar[1]);free(cache->matrix_y_bar); free(cache->eigenvalues); free(cache->working_matrix1[1]);free(cache->working_matrix1); free(cache->working_matrix2[1]);free(cache->working_matrix2); free(cache->constraints); free(cache->alpha_update[1]);free(cache->alpha_update); } /* MSVM_2_compute_gradient_chunk(vector_gradient,cache,model) Compute the components of the gradient vector corresponding to the chunk */ void MSVM_2_compute_gradient_chunk(double **vector_gradient, double **gradient, struct TrainingCache *cache, const struct Model *model) { long i,k,y_i,ind_pattern; const long Q = model->Q; const long chunk_size = cache->chunk_size; long row = 0; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; y_i = model->y[ind_pattern]; for(k=1; k<=Q; k++) { if(k != y_i) { row++; vector_gradient[row][1] = gradient[ind_pattern][k]; } } } } /* MSVM_2_init_gradient({ALPHA_IS_ZERO,ALPHA_NOT_ZERO}, gradient, cache, model) */ void MSVM_2_init_gradient(const enum AlphaInitType alpha_init_type, double **gradient, double **H_alpha, double **H_tilde_alpha, const struct Model *model) { long i,j,k,l,y_i; const long nb_data = model->nb_data; const long Q = model->Q; const double Qd = (double)Q; const double Qinv = 1. / (Qd-1.0); const enum Kernel_type nature_kernel = model->nature_kernel; const double *kernel_par = model->kernel_par; long dim_input = model->dim_input; double partial, H_alpha_ik, H_tilde_alpha_ik, partial2; if(alpha_init_type == ALPHA_IS_ZERO) { // Fast initialization for(i=1; i<=nb_data; i++) { for(k=1; k<=Q; k++) { gradient[i][k] = -Qinv; H_alpha[i][k] = 0.0; H_tilde_alpha[i][k] = 0.0; } gradient[i][model->y[i]] = 0.0; } } else { // Do a proper initialization based on the values of alpha for(i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { H_tilde_alpha_ik = 0.0; H_alpha_ik = 0.0; for(j=1; j<=nb_data; j++) { partial = 0.0; for(l=1; l<=Q; l++) partial -= model->alpha[j][l]; partial /= Qd; partial += model->alpha[j][k]; if(partial != 0.0) { partial2 = partial * ker(nature_kernel, model->X[i], model->X[j], dim_input,kernel_par); H_alpha_ik += partial2; H_tilde_alpha_ik += partial2; if(j==i) H_tilde_alpha_ik += partial / (2*model->C[y_i]); } } gradient[i][k] = H_tilde_alpha_ik - Qinv; H_alpha[i][k] = H_alpha_ik; H_tilde_alpha[i][k] = H_tilde_alpha_ik; } else { gradient[i][k] = 0.0; H_alpha[i][k] = 0.0; H_tilde_alpha[i][k] = 0.0; } } } } } /* Thread for updates of the gradient in parallel (spawn by main computing thread MSVM2_train_thread) */ void *MSVM2_update_gradient_thread(void *th_data) { // Recover thread data struct ThreadGradient_data *data = (struct ThreadGradient_data *) th_data; double **gradient = data->gradient; double **H_alpha = data->H_alpha; double **H_tilde_alpha = data->H_tilde_alpha; struct TrainingCache *cache = data->cache; const struct Model *model = data->model; const long start_i = data->start_i; const long end_i = data->end_i; // Local variables long i,j,k,l,y_i,ind_pattern; const long Q = model->Q; const double Qd = (double)Q; const long chunk_size = cache->chunk_size; double partial, H_tilde_alpha_update_ik, H_alpha_update_ik; for(i=start_i; i<=end_i; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { H_tilde_alpha_update_ik = 0.0; H_alpha_update_ik = 0.0; for(j=1; j<=chunk_size; j++) { ind_pattern = cache->table_chunk[j]; partial = 0.0; for(l=1; l<=Q; l++) partial -= cache->alpha_update[j][l]; partial /= Qd; partial += cache->alpha_update[j][k]; if(partial != 0.0) { H_tilde_alpha_update_ik += partial * cache->K[j][i]; H_alpha_update_ik += partial * cache->K[j][i]; if(ind_pattern==i) H_alpha_update_ik -= partial / (2*model->C[y_i]); } } gradient[i][k] += H_tilde_alpha_update_ik; H_alpha[i][k] += H_alpha_update_ik; H_tilde_alpha[i][k] += H_tilde_alpha_update_ik; } } } pthread_exit(EXIT_SUCCESS); } /* Old-style non-threaded gradient update */ void MSVM_2_update_gradient(double **gradient, double **H_alpha,double **H_tilde_alpha, struct TrainingCache *cache, const struct Model *model) { long i,j,k,l,y_i,ind_pattern; const long nb_data = model->nb_data; const long Q = model->Q; const double Qd = (double)Q; const long chunk_size = cache->chunk_size; double partial, H_tilde_alpha_update_ik, H_alpha_update_ik; for(i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { H_tilde_alpha_update_ik = 0.0; H_alpha_update_ik = 0.0; for(j=1; j<=chunk_size; j++) { ind_pattern = cache->table_chunk[j]; partial = 0.0; for(l=1; l<=Q; l++) partial -= cache->alpha_update[j][l]; partial /= Qd; partial += cache->alpha_update[j][k]; if(partial != 0.0) { H_tilde_alpha_update_ik += partial * cache->K[j][i]; H_alpha_update_ik += partial * cache->K[j][i]; if(ind_pattern==i) H_alpha_update_ik -= partial / (2*model->C[y_i]); } } gradient[i][k] += H_tilde_alpha_update_ik; H_alpha[i][k] += H_alpha_update_ik; H_tilde_alpha[i][k] += H_tilde_alpha_update_ik; } } } } /* Computation of the matrices A0 and A0T */ void MSVM_2_compute_A0(struct TrainingCache *cache, const struct Model *model) { long i,k,l,ind_pattern,y_i; const long Q = model->Q; double Qd = (double)Q; const long chunk_size = cache->chunk_size; long nb_constraints = cache->nb_constraints; long nb_variables = cache->nb_variables; long row=0; long column=0; for(k=1; k<=nb_constraints; k++) for(l=1; l<=nb_variables; l++) cache->A0[k][l] = 0.0; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; y_i = model->y[ind_pattern]; for(k=1; k<=Q; k++) { if(k != y_i) { column++; if(model->alpha[ind_pattern][k] == 0.0) { row++; cache->A0[row][column] = -1.0; } } } } column=0; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; y_i = model->y[ind_pattern]; for(l=1; l<=Q; l++) if(l != y_i) { column++; for(k=1; kA0[row+k][column] = (l != k) ? 1.0 : 1.0-Qd; } } cache->nb_sat = row+Q-1; trans_mat(cache->A0, cache->A0T, cache->nb_sat, nb_variables); } /* Computation of the vector u satisfying A0A0T u = - A0 grad J(alpha)*/ void MSVM_2_compute_vector_u(double **vector_u, double **vector_gradient, struct TrainingCache *cache, const struct Model *model) { long nb_variables = cache->nb_variables; long nb_sat = cache->nb_sat; mult_mat(cache->A0, cache->A0T, cache->A0A0T, nb_sat, nb_variables, nb_sat); MSVM_2_compute_pseudo_inverse(cache); mult_mat(cache->A0, vector_gradient, cache->working_matrix1, nb_sat, nb_variables, 1); mult_mat(cache->A0A0T_1, cache->working_matrix1, cache->working_matrix2, nb_sat, nb_sat, 1); scal_mat(-1.0, cache->working_matrix2, vector_u, nb_sat, 1); } /* optimum = MSVM_2_check_vector_u(u, gradient, cache, model) Check the equation defining vector u and returns 1 if optimal conditions are satisfied 0 if u is correct and optimal conditions not reached yet -1 if u is not correct (problem in pseudo-inverse) */ int MSVM_2_check_vector_u(double **vector_u, double **vector_gradient, struct TrainingCache *cache, const struct Model *model) { long k; long nb_sat = cache->nb_sat; long nb_variables = cache->nb_variables; const long Q = model->Q; int optimum = 1; mult_mat(cache->A0A0T_ref, vector_u, cache->working_matrix1, nb_sat, nb_sat, 1); mult_mat(cache->A0, vector_gradient, cache->working_matrix2, nb_sat, nb_variables, 1); for(k=1; k<=nb_sat; k++) cache->working_matrix2[k][1] *= -1.0; if(compare(cache->working_matrix1, cache->working_matrix2, nb_sat, 1, very_small) == false) { return -1; } k=1; while((k<=nb_sat-Q+1) && (optimum == 1)) { if(vector_u[k][1] < 0.0) optimum=0; else k++; } return optimum; } /* MSVM_2_compute_vector_y_bar(vector_y_bar, vector_u, vector_gradient, cache, model) Compute the new direction of descent */ void MSVM_2_compute_vector_y_bar(double **vector_y_bar, double **vector_u, double **vector_gradient, struct TrainingCache *cache, const struct Model *model) { long i,k,y_i; const long Q = model->Q; const long chunk_size = cache->chunk_size; long nb_sat = cache->nb_sat; long nb_variables = cache->nb_variables; long row = 0; mult_mat(cache->A0T, vector_u, cache->vector_z_bar, nb_variables, nb_sat, 1); add_mat(vector_gradient, cache->vector_z_bar, cache->working_matrix1, nb_variables, 1); scal_mat(-1.0, cache->working_matrix1, vector_y_bar, nb_variables, 1); for(k=1; k<=nb_variables; k++) if(fabs(vector_y_bar[k][1]) < 0.01 * very_small) vector_y_bar[k][1] = 0.0; for(i=1; i<=chunk_size; i++) { y_i = model->y[cache->table_chunk[i]]; for(k=1; k<=Q; k++) { if(k != y_i) { row++; cache->matrix_y_bar[i][k] = vector_y_bar[row][1]; } else cache->matrix_y_bar[i][k] = 0.0; } } } /* descent = MSVM_2_check_vector_y_bar(...) = 1 if non-zero norm feasible direction = 0 if zero-norm = -1 if non-zero norm infeasible direction Check the feasibility of the new direction of descent */ int MSVM_2_check_vector_y_bar(double **vector_y_bar, double **vector_u, double **vector_gradient, struct TrainingCache *cache, const struct Model *model) { long i,k,row, y_i; const long Q = model->Q; const long chunk_size = cache->chunk_size; long nb_sat = cache->nb_sat; long nb_variables = cache->nb_variables; int nullity, descent = 0; double norm, norm_y_bar=0.0; for(k=1; k<=nb_variables; k++) norm_y_bar += vector_y_bar[k][1] * vector_y_bar[k][1]; norm_y_bar = sqrt(norm_y_bar); cache->initial_norm_y_bar = norm_y_bar; if(norm_y_bar <= very_small) nullity=true; else nullity=false; if(nullity == false) { row=0; for(i=1; i<=chunk_size; i++) { y_i = model->y[cache->table_chunk[i]]; for(k=1; k<=Q; k++) { if(k != y_i) { row++; vector_y_bar[row][1] /= norm_y_bar; cache->matrix_y_bar[i][k] = vector_y_bar[row][1]; } else cache->matrix_y_bar[i][k] = 0.0; } } descent=1; mult_mat(cache->A0, vector_y_bar, cache->working_matrix1, nb_sat, nb_variables, 1); norm=0.0; for(k=1; k<=nb_sat; k++) norm += cache->working_matrix1[k][1] * cache->working_matrix1[k][1]; norm = sqrt(norm); if(norm > sqrt(nb_sat) * very_small) { /* printf("\nbar{y} does not belong to the null space of A0: ||A0 bar{y}||= %e\n", norm); */ descent=-1; } cache->gradientT_y_bar=0.0; for(k=1; k<=nb_variables; k++) cache->gradientT_y_bar += vector_y_bar[k][1] * vector_gradient[k][1]; if(cache->gradientT_y_bar > 0.0) { if(cache->gradientT_y_bar > very_small) { /* printf("\ngradient^T bar{y} = %e: bar{y} is not a direction of descent...\n", cache->gradientT_y_bar); */ } descent=-1; } } return descent; } /* Relax one of the constraints to be satisfied by the direction of descent */ void MSVM_2_simplify_A0(double **vector_u, struct TrainingCache *cache, const struct Model *model) { long k,l; const long Q = model->Q; long nb_sat = cache->nb_sat; long nb_variables = cache->nb_variables; double smallest_u = 0.0; long index_smallest_u = 1; for(k=1; k<=nb_sat-Q+1; k++) if(vector_u[k][1] < smallest_u) { smallest_u = vector_u[k][1]; index_smallest_u = k; } nb_sat--; for(k=index_smallest_u; k<=nb_sat; k++) for(l=1; l<=nb_variables; l++) cache->A0[k][l] = cache->A0[k+1][l]; trans_mat(cache->A0, cache->A0T, nb_sat, nb_variables); cache->nb_sat = nb_sat; } /* theta_max = MSVM_2_compute_theta_max(cache,model) Computation of the largest feasible value for theta */ double MSVM_2_compute_theta_max(const struct TrainingCache *cache, const struct Model *model) { long i,k,ind_pattern; const long Q = model->Q; const long chunk_size = cache->chunk_size; double theta_partial; double theta_max = HUGE_VAL; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; for(k=1; k<=Q; k++) if((k != model->y[ind_pattern]) && (cache->matrix_y_bar[i][k] < 0.0)) { theta_partial = - model->alpha[ind_pattern][k] / cache->matrix_y_bar[i][k]; if(theta_partial < theta_max) theta_max = theta_partial; } } return theta_max; } /* Computation of the vector H bar{y} used in compute_theta_opt */ void MSVM_2_compute_H_y_bar(struct TrainingCache *cache, const struct Model *model) { long i,j,k,l,ind_pattern, y_i; const long Q = model->Q; double Qd = (double)Q; const long chunk_size = cache->chunk_size; double partial, partial_sum_y_bar = 0.0; for(i=1; i<=chunk_size; i++) { y_i = model->y[cache->table_chunk[i]]; for(k=1; k<=Q; k++) { cache->H_y_bar[i][k] = 0.0; if(k != y_i) { for(j=1; j<=chunk_size; j++) { ind_pattern = cache->table_chunk[j]; partial_sum_y_bar = 0.0; for(l=1; l<=Q; l++) if(l != model->y[ind_pattern]) partial_sum_y_bar += cache->matrix_y_bar[j][l]; partial = cache->matrix_y_bar[j][k] - (partial_sum_y_bar / Qd); cache->H_y_bar[i][k] += partial * cache->K[i][ind_pattern]; } } } } } /* theta_opt = MSVM_2_compute_theta_opt(theta_max,cache,model) Computation of the optimal value for theta */ double MSVM_2_compute_theta_opt(const double theta_max, struct TrainingCache *cache, const struct Model *model) { long i,k, y_i; const long Q = model->Q; const long chunk_size = cache->chunk_size; double y_barT_H_y_bar=0.0; double theta_opt = 0.0; MSVM_2_compute_H_y_bar(cache,model); for(i=1; i<=chunk_size; i++) { y_i = model->y[cache->table_chunk[i]]; for(k=1; k<=Q; k++) if(k != y_i) y_barT_H_y_bar += cache->matrix_y_bar[i][k] * cache->H_y_bar[i][k]; } if(y_barT_H_y_bar <= 0.0) { printf("\nThe value of the quadratic form is: %e\n", y_barT_H_y_bar); printf("\nMatrix bar{y}\n"); display_mat(cache->matrix_y_bar, chunk_size, Q, 7, 4); exit(0); } if(y_barT_H_y_bar > tiny) theta_opt = minimum (- cache->gradientT_y_bar / y_barT_H_y_bar, theta_max); else { printf("\nbar{y}^T H bar{y} is too small: %e", y_barT_H_y_bar); theta_opt = 0.0; } return theta_opt; } /* delta_nb_SV = compute_new_alpha(theta_opt,cache,model) Computation of the new value of the vector of dual variables alpha and return the difference in number of SVs */ long MSVM_2_compute_new_alpha(const double theta_opt, const struct TrainingCache *cache, struct Model *model) { long i,k,ind_pattern; const long Q = model->Q; const double Qd = (double)Q; const long chunk_size = cache->chunk_size; long nb_SV = 0; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; model->partial_average_alpha[ind_pattern] = 0.0; // Assume x_i is not a SV if(cache->activeset[ind_pattern]) { cache->activeset[ind_pattern] = 0; nb_SV--; } for(k=1; k<=Q; k++) if(k != model->y[ind_pattern]) { cache->alpha_update[i][k] = theta_opt * cache->matrix_y_bar[i][k]; model->alpha[ind_pattern][k] += cache->alpha_update[i][k]; if(model->alpha[ind_pattern][k] < 0.0) model->alpha[ind_pattern][k] = 0.0; else if (model->alpha[ind_pattern][k] != 0.0) { // Update nb_SV and activeset if(cache->activeset[ind_pattern] == 0) { cache->activeset[ind_pattern] = 1; nb_SV++; } } model->partial_average_alpha[ind_pattern] += model->alpha[ind_pattern][k]; } else cache->alpha_update[i][k] = 0.0; model->partial_average_alpha[ind_pattern] /= Qd; } return nb_SV; } /* Check the feasibility of the initial alpha */ int MSVM_2_check_feasible_sol_init(struct Model *model) { long i,k; const long Q = model->Q; const long nb_data = model->nb_data; double norm; int feasible = true; double *constraints = (double *) calloc(Q+1, sizeof(double)); model->sum_all_alpha = 0.0; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) if(((k == model->y[i]) && (model->alpha[i][k] != 0.0)) || (model->alpha[i][k] < 0.0)) { printf("\nNo feasible solution: alpha[%ld][%ld] = %e\n\n", i, k, model->alpha[i][k]); feasible = false; break; } else model->sum_all_alpha += model->alpha[i][k]; for(k=1; k<=Q; k++) constraints[k] = model->sum_all_alpha / Q; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) constraints[k] -= model->alpha[i][k]; norm = 0.0; for(k=1; k<=Q; k++) norm += constraints[k] * constraints[k]; norm = sqrt(norm); if(norm >= very_small) { feasible = false; printf("\n\nLarge deviation of the equality constraints...\n\n"); } free(constraints); return feasible; } /* Check the feasibility of the current solution alpha */ int MSVM_2_check_feasible_sol_train(struct Model *model, struct TrainingCache *cache) { long i,k; const long Q = model->Q; const long nb_data = model->nb_data; double norm; int feasible = true; model->sum_all_alpha = 0.0; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) if(((k == model->y[i]) && (model->alpha[i][k] != 0.0)) || (model->alpha[i][k] < 0.0)) { printf("\nNo feasible solution: alpha[%ld][%ld] = %e\n\n", i, k, model->alpha[i][k]); feasible = false; break; } else model->sum_all_alpha += model->alpha[i][k]; for(k=1; k<=Q; k++) cache->constraints[k] = model->sum_all_alpha / Q; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) cache->constraints[k] -= model->alpha[i][k]; norm = 0.0; for(k=1; k<=Q; k++) norm += cache->constraints[k] * cache->constraints[k]; norm = sqrt(norm); if(norm >= very_small) { feasible = false; printf("\n\nLarge deviation of the equality constraints...\n\n"); } return feasible; } /* Characterize the achieving of an unfeasible solution */ void MSVM_2_study_unfeasible_sol(const int descent, double **vector_u, double **vector_y_bar, const struct TrainingCache *cache, const struct Model *model) { long k; const long Q = model->Q; const long chunk_size = cache->chunk_size; long nb_sat = cache->nb_sat; long nb_variables = cache->nb_variables; for(k=1; k<=Q; k++) printf("%s%e\n", cache->constraints[k] < 0.0 ? " " : " ", cache->constraints[k]); printf("\nMatrix A0\n"); display_mat(cache->A0, nb_sat, nb_variables, 7, 4); if(descent == 0) printf("\nbar{y} is the null vector"); else printf("\nbar{y} is not the null vector"); printf("\nNorm of bar{y}: %e\n", cache->initial_norm_y_bar); printf("\nVector u\n"); display_mat(vector_u, nb_sat, 1, 7, 4); printf("\nVector bar{y}\n"); display_mat(cache->matrix_y_bar, chunk_size, Q, 7, 4); mult_mat(cache->A0, vector_y_bar, cache->working_matrix1, nb_sat, nb_variables, 1); printf("\nA0 bar{y}\n"); display_mat(cache->working_matrix1, nb_sat, 1, 9, 6); exit(0); } /* val_obj_function = MSVM_2_compute_objective_function(model, former_val_obj_function) Computation of the value J(alpha) of the objective function */ double MSVM_2_compute_objective_function(const struct Model *model, double former_val_obj_function) { long i,j,k,l; const long Q = model->Q; double Qd = (double)Q; const long nb_data = model->nb_data; long dim_input = model->dim_input; const enum Kernel_type nature_kernel = model->nature_kernel; const double *kernel_par = model->kernel_par; double Q_term=0.0, L_term=0.0, partial_1, partial_2, kernel, val_obj_function; for(i=1; i<=nb_data; i++) for(j=1; j<=nb_data; j++) { partial_1 = 0.0; for(k=1; k<=Q; k++) for(l=1; l<=Q; l++) { partial_2 = -1.0; if(k == l) partial_2 += Qd; partial_1 += partial_2 * model->alpha[i][k] * model->alpha[j][l]; } if(partial_1 != 0.0) { kernel = ker(nature_kernel, model->X[i], model->X[j], dim_input, kernel_par); if(i == j) kernel += 1 / (2*model->C[model->y[i]]); Q_term += partial_1 * kernel; } } Q_term /= Qd; L_term = model->sum_all_alpha / (Qd - 1.0); val_obj_function = -0.5 * Q_term + L_term; printf("\n Objective function: %e", val_obj_function); if(val_obj_function < former_val_obj_function) if(former_val_obj_function - val_obj_function > very_small) { printf("\nThe value of the objective function has decreased...\n"); printf("%e < %e\n\n", val_obj_function, former_val_obj_function); exit(0); } return val_obj_function; } /* MSVM_2_compute_pseudo_inverse(cache) Computation of the pseudo_inverse of A0A0T */ void MSVM_2_compute_pseudo_inverse(struct TrainingCache *cache) { long i,k; long nb_sat = cache->nb_sat; double diag_kk_inv; copy(cache->A0A0T, cache->A0A0T_ref, nb_sat, nb_sat); diagonalize(cache->A0A0T, nb_sat, cache->eigenvalues); // copy(A0A0T, eigenvectors, nb_sat, nb_sat); // A0A0T replaces eigenvectors // trans_mat(A0A0T, eigenvectorsT, nb_sat, nb_sat); // use A0A0T[j][i] for eigenvectorsT[i][j] // mult_mat(new_diagonal_matrix, eigenvectorsT, working_matrix1, // nb_sat, nb_sat, nb_sat); // This mulplication by a diagonal matrix is done in the loop below: for(k=1; k<=nb_sat; k++) if(fabs(cache->eigenvalues[k]) > very_small) { diag_kk_inv = 1.0 / cache->eigenvalues[k]; for(i=1;i<=nb_sat;i++) cache->working_matrix1[k][i] = diag_kk_inv * cache->A0A0T[i][k]; // = diaginv * eigenvectorsT[k][i]; } else { for(i=1;i<=nb_sat;i++) cache->working_matrix1[k][i] = 0.0; } mult_mat(cache->A0A0T, cache->working_matrix1, cache->A0A0T_1, nb_sat, nb_sat, nb_sat); } MSVMpack1.2/src/trainMSVM.c~0000644000175000017500000004136211761345261014707 0ustar lauerlauer/* Copyright 2010 Fabien Lauer */ /* 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 2 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, write to the Free Software */ /* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA*/ /*--------------------------------------------------------------------------*/ /* Name : trainMSVM.c */ /* Version : 2.0 */ /* Creation : 04/27/10 */ /* Last update : 02/04/11 */ /* Subject : MSVMpack: a multi-class SVM package */ /* Algo. : Training command-line tool */ /* Author : Fabien Lauer fabien.lauer@loria.fr */ /*--------------------------------------------------------------------------*/ #include #include #include #include #include #include #include "libMSVM.h" #include "libevalMSVM.h" #include "libtrainMSVM.h" /* Handling user interruption */ void ctrlC_handler(int sig) { if(EVAL) { printf(" Double Ctrl-C causes the program to break \n"); printf(" (all is lost, nothing is saved). \n"); exit(0); } else EVAL = 1; } /* Main */ int main(int argc, char *argv[]) { // Install the handler of SIGINT (Ctrl+C) signal, // which will force the call to MSVM_eval on demand struct sigaction newhandler,oldhandler; memset(&newhandler, 0, sizeof(newhandler)); newhandler.sa_handler = &ctrlC_handler; sigaction(SIGINT, &newhandler, &oldhandler); // Some local variables char com_file[taille], training_file[taille], model_file[taille], alpha0_file[taille], model_tmp_file[taille], alpha_file[taille], test_file[taille], outputs_file[taille], log_file[taille], yesno; long training_status; int i, k, n_kernel_par; long Q; FILE *fstdout=NULL; FILE *fkp; time_t realtime,starttime = time(NULL); clock_t cputime,startcputime = clock(); // Default parameter values enum MSVM_type model_type = MSVM2; double C = DEFAULT_C; double accuracy = 0.98; // 98% optimization accuracy level long chunk_size = 4; // 4 points considered at each iteration int sparse_model_format = false; // Do not use sparse model file format // this allows retraining from an existing model int retrain = false; // Assumes an empty model int do_normalize = 0; // Test if normalization needed int cache_memory = 1024; // Use 1 GB of memory for kernel cache int nprocs = get_nprocessors(); // Use all processors // Default filenames strcpy(model_file, "msvm.model"); // save model to "msvm.model" char *alpha0 = NULL; // initialize with all alpha = 0 (except for CS-type) char *alpha = NULL; // backward compatibility char *test = NULL; // Do not test model on a test set (training only) char *outputs = NULL; // so no output on test set to record char *log = NULL; // Do not log the values of dual objective and upper bounds strcpy(log_file, ""); /* Parse command line and initialize model for training */ if(argc<2 || check_argv(argc,argv, "-help") || check_argv_eq(argc,argv, "-h") ) { printf("This is MSVMpack: a Multi-class Support Vector Machine package\n"); printf("-- Version: %1.1f \n\n",VERSION); printf("Training tool used to train an M-SVM model from data. \n\n"); printf("Usage: \n"); printf(" trainmsvm training_file [file.model] [params]\n"); printf(" or trainmsvm comfile.com [file.model]\n\n"); printf(" where 'params' is a list of parameters specified as e.g.: \n -c 2.5 -k 1 \n\n"); printf("Optional parameters: \n"); printf(" -m : model type (WW,CS,LLW,MSVM2) (default is MSVM2)\n"); printf(" -k : nature of the kernel function (default is 1)\n"); printf(" 1 -> linear kernel k(x,z) = x^T z\n"); printf(" 2 -> Gaussian RBF kernel k(x,z) = exp(-||x - z||^2 / 2*par^2)\n"); printf(" 3 -> homogeneous polynomial kernel k(x,z) = (x^T z)^par \n"); printf(" 4 -> non-homo. polynomial kernel k(x,z) = (x^T z + 1)^par \n"); printf(" 5 -> custom kernel 1\n"); printf(" 6 -> custom kernel 2\n"); printf(" 7 -> custom kernel 3\n"); printf(" -p : kernel parameter par (default is sqrt(5*dim(x)) (RBF) or 2 (POLY))\n"); printf(" -P : list of space-separated kernel parameters starting with #parameters\n"); printf(" -c : soft-margin (or trade-off) hyperparameter (default C = 10.0)\n"); printf(" -C : list of space-separated hyperparameters C_k (default C_k = C)\n"); printf(" -n : use normalized data for training (mean=0 and std=1 for all features)\n"); printf(" -u : use unnormalized data for training (bypass the normalization test) \n"); printf(" -x : maximal cache memory size in MB (default is 1024)\n"); printf(" -t : number of working threads in [1, %d] (default is #CPUs=%d)\n",nprocs,nprocs); printf(" -f : faster computations with single-precision floating-point data format\n"); printf(" -I : faster computations with integer data format\n"); printf(" -i : faster computations with short integer data format\n"); printf(" -B : faster computations with byte data format\n"); printf(" -b : faster computations with bit data format\n"); printf(" -o : optimization method: 0 -> Franke-Wolfe (default), 1 -> Rosen\n"); printf(" -w : size of the chunk (default is 10 for WW and 4 for others)\n"); printf(" -a : optimization accuracy within [0,1] (default is 0.98)\n"); printf(" -r : retrain model (resume training)\n"); printf(" -s : save model using sparse format\n"); printf(" -S : convert existing model to sparse format without training\n"); printf(" -q : be quiet\n\n"); printf("These optional files can be specified on the command line:\n"); printf(" file.test : Test data file\n"); printf(" file.outputs : Computed outputs on the test set\n"); //printf(" file.alpha : Backup file for alpha\n"); printf(" file.init : Initialization file for alpha\n"); printf(" file.log : Log optimization information\n\n"); printf("See also 'predmsvm' to classify new data with a trained M-SVM. \n\n"); exit(0); } i = check_argv_eq(argc,argv, "-q"); if(i) { fstdout = freopen(".trainmsvm_quiet.log", "w", stdout); if(fstdout == NULL) printf("Cannot set quiet mode (error in stdout redirection)\n"); } i = check_argv_eq(argc,argv, "-m"); if(i) model_type = str2model_type(argv[i+1]); // Make model struct Model *model = MSVM_make_model(model_type); if (model == NULL) { printf("Unknown model type -m %s.\n",argv[i+1]); exit(1); } // Set a different default chunk_size for WW models if(model_type == WW) chunk_size = 10; // check if first argument is a .com file if(strstr(argv[1], ".com") != NULL ) { // Read all info from the .com file strcpy(com_file, argv[1]); printf("Reading parameters from %s ...\n ", com_file); chunk_size = MSVM_init_train_comfile(model, com_file, training_file, alpha0_file, alpha_file, log_file); alpha0 = alpha0_file; alpha = alpha_file; } else { // First argument must be the training data file (if not a .com file) strcpy(training_file, argv[1]); // If a .com file is found at another position, use it to set the parameters only i = check_argv(argc,argv, ".com"); if(i) { strcpy(com_file, argv[i]); chunk_size = MSVM_init_model(model, com_file); } } // Parse filenames i = check_argv(argc,argv, ".outputs"); if(i) { strcpy(outputs_file,argv[i]); outputs = outputs_file; } i = check_argv(argc,argv, ".test"); if(i) { strcpy(test_file, argv[i]); test = test_file; } i = check_argv(argc,argv, ".alpha"); if(i) { strcpy(alpha_file,argv[i]); alpha = alpha_file; } i = check_argv(argc,argv, ".init"); if(i) { strcpy(alpha0_file,argv[i]); alpha0 = alpha0_file; } i = check_argv(argc,argv, ".model"); if(i) { strcpy(model_file,argv[i]); } i = check_argv(argc,argv, ".log"); if(i) { strcpy(log_file,argv[i]); log = log_file; } else if(strlen(log_file) > 0) log = log_file; // Parse parameters from the command line // (this overrides values from a .com file) i = check_argv_eq(argc,argv, "-w"); if(i) chunk_size = atoi(argv[i+1]); i = check_argv_eq(argc,argv, "-c"); if(i) C = atof(argv[i+1]); // see below for multiple C i = check_argv_eq(argc,argv, "-k"); if(i) { model->nature_kernel = atoi(argv[i+1]); } i = check_argv_eq(argc,argv, "-f"); if(i) { model->datatype = FLOAT; model->nature_kernel += 10; } i = check_argv_eq(argc,argv, "-I"); if(i) { model->datatype = INT; model->nature_kernel += 20; do_normalize = 0; } i = check_argv_eq(argc,argv, "-i"); if(i) { model->datatype = SHORT; model->nature_kernel += 30; do_normalize = 0; } i = check_argv_eq(argc,argv, "-B"); if(i) { model->datatype = BYTE; model->nature_kernel += 40; do_normalize = 0; } i = check_argv_eq(argc,argv, "-b"); if(i) { model->datatype = BIT; model->nature_kernel += 50; do_normalize = 0; } i = check_argv_eq(argc,argv, "-p"); if(i) { model->kernel_par = (double*)realloc(model->kernel_par, sizeof(double) * 2); model->kernel_par[0] = 1; model->kernel_par[1] = atof(argv[i+1]); } i = check_argv_eq(argc,argv, "-P"); if(i) { if(argv[i+1][0] >= '0' && argv[i+1][0] <= '9') { n_kernel_par = atoi(argv[i+1]); model->kernel_par = (double*)realloc(model->kernel_par, sizeof(double) * (n_kernel_par + 1)); model->kernel_par[0] = n_kernel_par; if(n_kernel_par > 0 && argv[i+2][0] >= '0' && argv[i+2][0] <= '9') { for(k=1;k<=n_kernel_par;k++) model->kernel_par[k] = atof(argv[i+1+k]); } else if (n_kernel_par > 0){ // Kernel parameter values in file fkp = fopen(argv[i+2], "r"); if(fkp == NULL) { printf("Cannot read kernel parameter file %s\n",argv[i+2]); exit(1); } for(k=1;k<=n_kernel_par;k++) i=fscanf(fkp, "%lf", &model->kernel_par[k]); fclose(fkp); } } else { // Kernel parameter list is a file name fkp = fopen(argv[i+1], "r"); if(fkp == NULL) { printf("Cannot read kernel parameter file %s\n",argv[i+1]); exit(1); } i=fscanf(fkp, "%d", &n_kernel_par); model->kernel_par = (double*)realloc(model->kernel_par, sizeof(double) * (n_kernel_par + 1)); model->kernel_par[0] = n_kernel_par; for(k=1;k<=n_kernel_par;k++) i=fscanf(fkp, "%lf", &model->kernel_par[k]); fclose(fkp); } } i = check_argv_eq(argc,argv, "-a"); if(i) { accuracy = atof(argv[i+1]); if (accuracy < 0 || accuracy > 1) { printf("\n Wrong accuracy level -a %lf (not in [0,1])",accuracy); printf("\n Falling back to default (0.98).\n"); accuracy = 0.98; } } i = check_argv_eq(argc,argv, "-n"); if(i) do_normalize = 1; i = check_argv_eq(argc,argv, "-u"); if(i) do_normalize = -1; i = check_argv_eq(argc,argv, "-x"); if(i) { cache_memory = atoi(argv[i+1]); if(cache_memory <= 0) { printf("Cache memory size set with -x must be a positive integer.\n"); exit(1); } } i = check_argv_eq(argc,argv, "-t"); if(i) { if(atoi(argv[i+1]) > nprocs) { printf("Unattended request of a number of working threads above the number of available processors (%d)\n",nprocs); } else nprocs = atoi(argv[i+1]); } i = check_argv_eq(argc,argv, "-r"); if(i) { printf("\nRetrain model %s ...\n", model_file); if(!check_argv_eq(argc,argv, "-w")) printf("Using default chunk size: %ld\n (this may be different from what was previously used to train %s ).\n",chunk_size, model_file); retrain = true; MSVM_delete_model(model); model = MSVM_load_model(model_file); } i = check_argv_eq(argc,argv, "-o"); if(i) { if(atoi(argv[i+1]) == 1) { if(model->type == MSVM2) model->algorithm=Rosen; else printf("Rosen's algorithm is not available for this M-SVM, \n using Franke-Wolfe algorithm.\n"); } } i = check_argv_eq(argc,argv, "-s"); if(i) { sparse_model_format = true; } i = check_argv_eq(argc,argv, "-S"); if(i) { MSVM_delete_model(model); model = MSVM_load_model(model_file); if(model == NULL) exit(1); printf("\nConverting model %s in sparse format...\n", model_file); printf("Note that the sparse format does not allow retraining.\n\n"); MSVM_save_model_sparse(model, model_file); MSVM_delete_model_with_data(model); exit(0); } // --- End of parsing the command line --- /* Load training data */ struct Data *training_set, *test_set; if(!retrain) { training_set = MSVM_make_dataset(training_file, model->datatype); if(training_set == NULL) { printf("Error: wrong or missing training data file. \n"); printf("Note: the training data file should always be the first argument,\n"); printf(" e.g.: trainmsvm myTrainingData myMSVM.model\n\n"); exit(0); } Q = training_set->Q; } else { training_set = NULL; // resume training with data already in model Q = model->Q; } /* Normalize data */ if(do_normalize==1) { // user asked for normalization MSVM_normalize_data(training_set, model); } else if(do_normalize==0){ // check if normalization needed if(MSVM_normalize_data(training_set, NULL) > 10) { printf("**\n** Columns of the data matrix show a large difference\n"); printf("** between their standard deviations (> 10).\n"); printf("** This could affect the performance of the classifier. \n\n"); printf(" Do you want the data to be normalized ([y]/n)? \n"); printf(" (Use the -n flag to force normalization from the command line\n"); printf(" or the -u flag to bypass this test and use unnormalized data)\n"); i=scanf("%c",&yesno); getchar(); if(yesno != 'n') { MSVM_normalize_data(training_set, model); } } } /* Set the list of C hyperparameters */ i = check_argv_eq(argc,argv, "-C"); if(i) { MSVM_model_set_C(C, Q, model); for(k=1;k<=Q;k++) model->C[k] = atof(argv[i+k]); } else { MSVM_model_set_C(C, Q, model); } /* Set filename for monitoring (periodic saving of model in case something bad happens) */ sprintf(model_tmp_file, "%s.tmp", model_file); /* Launch training */ training_status = MSVM_train(model, training_set, chunk_size, accuracy, cache_memory, nprocs, alpha0, model_tmp_file, log); realtime = time(NULL) - starttime; cputime = clock() - startcputime; // Print output information if(training_status == 0) { printf("\n Optimum found with desired accuracy level (%3.2lf \%%)\n", 100*accuracy); if ((long unsigned int)realtime > 1) printf("after %lu seconds (actual CPU time over all processors = %1.2lf sec.). \n", (long unsigned int)realtime, (double) cputime / (double)CLOCKS_PER_SEC); else printf("after %lu second (actual CPU time over all threads = %1.2lf sec.). \n", (long unsigned int)realtime, (double) cputime / (double)CLOCKS_PER_SEC); } else if(training_status == 1) printf("\n Stopped training after maximum number of iterations (%ld). \n", MSVM_TRAIN_MAXIT); else if(training_status > 1) printf("\n Stopped by user after %ld iterations. \n", training_status); else { printf("Error in training MSVM. No model saved. \n"); exit(0); } // Output trianing error rate if((double)((int)(10000 * model->training_error)) == 10000 * model->training_error) printf("Training error rate = %3.2lf %%\n",100*model->training_error); else printf("Training error rate = %3.4lf %%\n",100*model->training_error); // Write model to file if(sparse_model_format) { printf("\nSaving model in sparse format to %s...\n", model_file); printf("Note that the sparse format does not allow retraining.\n\n"); MSVM_save_model_sparse(model, model_file); } else { MSVM_save_model(model, model_file); printf("M-SVM model saved in %s.\n",model_file); } // and remove temporary file remove(model_tmp_file); // Compute test error (if test_file is provided) if(test != NULL) { test_set = MSVM_make_dataset(test_file, model->datatype); // Compute output on test set MSVM_classify_set(NULL, test_set->X, test_set->y, test_set->nb_data, outputs, model, nprocs); MSVM_delete_dataset(test_set); } // Free all if(retrain) MSVM_delete_model_with_data(model); else { MSVM_delete_model(model); MSVM_delete_dataset(training_set); } return 0; } MSVMpack1.2/src/libtrainMSVM_WW.c0000644000175000017500000006452111761350133015611 0ustar lauerlauer/* Copyright 2000-2010 Yann Guermeur */ /* 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 2 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, write to the Free Software */ /* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA*/ /*--------------------------------------------------------------------------*/ /* Name : libtrainMSVM_WW.c */ /* Version : 2.0 */ /* Creation : 04/27/00 */ /* Last update : 11/29/10 */ /* Subject : Training algorithm of the M-SVM of Weston and Watkins */ /* Algo. : Frank-Wolfe algorithm + decomposition method */ /* Author : Fabien Lauer and Yann Guermeur Yann.Guermeur@loria.fr */ /*--------------------------------------------------------------------------*/ #include "libtrainMSVM_WW.h" /* Weston and Watkins (WW) MSVM training function Solves the dual problem wrt alpha: min 1/2 alpha' H alpha - sum (alpha) s.t. 0 <= alpha_ik <= C, for all i,k, such that 1 <= i <= m, 1 <= k != y_i <= Q sum_{y_i=k} sum_l alpha_il - sum_i alpha_ik = 0, for all k, 1 <= k <= Q-1 where H_ik,jl = (delta_yi,yj - delta_yi,l - delta_yj,k + delta_k,l) k(x_i,x_j) */ long MSVM_WW_train(struct Model *model, struct Data *training_set, long chunk_size, const double accuracy, int cache_memory, const int nprocs, char *alpha0_file, char *model_tmp_file, char *log_file) { long return_status = -1; FILE *fp; int t; pthread_t *threads = (pthread_t *)malloc(sizeof(pthread_t) * nprocs); // threads id void *status; // for pthread_join int rc; // return code of pthread functions pthread_t thread_monitor; enum AlphaInitType alphaiszero; if(training_set != NULL) { // Initialize model for this particular training set model_load_data(model, training_set); // Check if a kernel_par has been set if(model->nature_kernel != LINEAR && model->kernel_par == NULL) set_default_kernel_par(model); // Check that chunk_size >= Q if(chunk_size < model->Q) chunk_size = model->Q; } if(model->nb_data > 2147483647) { printf("Cannot compute table chunk: number of data above random number limit\n"); exit(0); } // Log file if (log_file != NULL) { printf("\nLog training info in %s ...\n", log_file); fp = fopen(log_file,"a"); } else fp = NULL; // Initialize alpha and b if(training_set != NULL) // otherwise resume training init_alpha_b(model, alpha0_file); // use init_alpha_b(model, NULL); to initialize all alpha to 0 if(training_set == NULL || alpha0_file != NULL) alphaiszero = ALPHA_NOT_ZERO; else alphaiszero = ALPHA_IS_ZERO; EVAL = 0; // triggered by signal handler to call eval STOP = 0; // triggered by user to stop training iter = 1; // number of iterations (over all threads) // Prepare monitoring of model struct MonitorData monitor_data; monitor_data.model_tmp_file = model_tmp_file; monitor_data.period = MONITOR_PERIOD; monitor_data.model = model; pthread_create(&thread_monitor, NULL, MSVM_monitor_model_thread, (void *) &monitor_data); // Allocate memory for shared ressources double **gradient = matrix(model->nb_data, model->Q); double **H_alpha = matrix(model->nb_data, model->Q); double best_primal_upper_bound = HUGE_VAL; int *activeset = (int *)calloc(model->nb_data+1, sizeof(int)); double *lp_rhs = (double*)calloc(model->Q, sizeof(double)); // including the kernel cache: struct KernelCache kc; unsigned long cache_size = (unsigned long)cache_memory * MBYTES; kernel_initialize_cache(cache_size, &kc, model); printf("Initialization... ");fflush(stdout); // Initialize gradient WW_init_gradient(alphaiszero, gradient, H_alpha,model); printf("Done.\n"); // Initialize display if(accuracy>0) print_training_info(0,0,0,model->type); else { printf("Training...");fflush(stdout); } // Prepare data for computing threads long nb_SV = 0; struct ThreadData thread_data; thread_data.nprocs = nprocs; thread_data.model = model; thread_data.kernelcache = &kc; thread_data.chunk_size = chunk_size; thread_data.accuracy = accuracy; thread_data.gradient = gradient; thread_data.H_alpha = H_alpha; thread_data.best_primal_upper_bound = &best_primal_upper_bound; thread_data.activeset = activeset; thread_data.nb_SV = &nb_SV; thread_data.lp_rhs = lp_rhs; thread_data.logfile_ptr = fp; // Launch computing threads for(t=0;tthread_id; const int nprocs = data->nprocs; struct Model *model = data->model; struct KernelCache *kernelcache = data->kernelcache; long chunk_size = data->chunk_size; const double accuracy = data->accuracy; double **gradient = data->gradient; double **H_alpha = data->H_alpha; double *best_primal_upper_bound = data->best_primal_upper_bound; int *activeset = data->activeset; long *nb_SV = data->nb_SV; double *lp_rhs = data->lp_rhs; FILE *fp = data->logfile_ptr; pthread_mutex_unlock(&thread_data_mutex); // Release thread_data for next thread // Local variables int do_eval; char yesno; long return_status = -1; double **delta = matrix(chunk_size, model->Q); double theta_opt; int jump = false; if(accuracy == 0) do_eval = 0; else do_eval = 1; // Prepare the cache struct TrainingCache cache; cache.chunk_size = chunk_size; WW_alloc_memory(&cache, model->Q, model->nb_data, chunk_size); cache.kc = kernelcache; cache.activeset = activeset; cache.lp_rhs = lp_rhs; /* Prepare parallel gradient computations: - the gradient vector is split into NUMTHREADS_GRAD parts (along i) - each part is updated by a different thread */ // max number of threads for gradient updates is nprocs pthread_t *grad_threads = (pthread_t *)malloc(sizeof(pthread_t) * nprocs); // start with 1 thread (main load on kernel evaluations) int numthreads_grad = 1; // More CPUs for gradient updates if Q > dimension of data if(model->dim_input < model->Q) numthreads_grad = nprocs; void *status; int rc; long k; struct ThreadGradient_data *grad_data = (struct ThreadGradient_data *)malloc(sizeof(struct ThreadGradient_data) * nprocs); // Disable parallel gradient computation for small data sets int parallel_gradient_update = 1; if(model->nb_data < 5000) parallel_gradient_update = 0; if(parallel_gradient_update) { for(k=0;knb_data / numthreads_grad; for(k=1;knb_data / numthreads_grad -1; } if(numthreads_grad>1) { grad_data[numthreads_grad-1].start_i = grad_data[numthreads_grad-2].end_i + 1; grad_data[numthreads_grad-1].end_i = model->nb_data; } } // Switch to nprocs/4 threads for gradient update when 25% of the kernel matrix is cached int percentage_step = 1; long percentage = model->nb_data / 4; int next_numthreads_grad = nprocs/4; if(next_numthreads_grad == 0) next_numthreads_grad = 1; // No thread switches if Q > dimension of data (keep all CPUs for gradient updates) if(model->dim_input < model->Q) percentage = 2*model->nb_data; // Main loop double ratio = 0.0; // stopping criterion (dual / upper bound) int thread_stop = 0; do { if((TRAIN_SMALL_STEP < TRAIN_STEP) && (iter%TRAIN_SMALL_STEP) == 0) { printf("."); fflush(stdout); } // Select a random chunk of data to optimize select_random_chunk(&cache,model); // Compute the kernel submatrix for this chunk compute_K(&cache,model); jump = WW_check_gradient_chunk(gradient,&cache,model); if(jump > 1) STOP = 1; // Enter Critical Section (using and modifying the model) pthread_mutex_lock(&model_mutex); if(jump == false) jump = WW_solve_lp(gradient, &cache, model); if(jump == false) jump = WW_check_opt_sol(gradient,&cache,model); if(jump == false) { WW_compute_delta(delta,&cache,model); theta_opt = WW_compute_theta_opt(delta, &cache, model); *nb_SV += WW_compute_new_alpha(theta_opt,&cache,model); if(parallel_gradient_update) { // Update gradient in parallel for(k=0;ktype); if(do_eval && ratio > accuracy) STOP = 1; if(EVAL) // if interrupted by user (otherwise let the ratio decide if we go on training) { printf("\n *** Do you want to continue training ([y]/n)? "); yesno = getchar(); if(yesno=='n') { STOP = 1; } EVAL = 0; // reset interruption trigger } } // Release kernel submatrix in cache release_K(&cache); // Check if a sufficient % of the kernel matrix is cached if( parallel_gradient_update && cache.kc->max_idx >= percentage ) { // and switch thread to compute gradient upates instead of kernel rows if it is thread_stop = switch_thread(nprocs, &numthreads_grad, &next_numthreads_grad, &percentage, &percentage_step, grad_data, thread_id, model->nb_data); // (threads are actually stopped to leave the CPUs // to other threads that will compute gradient updates) } iter++; // Release mutex: End of critical section pthread_mutex_unlock(&model_mutex); } while(iter <= MSVM_TRAIN_MAXIT && (!do_eval || ratio < accuracy) && !STOP && !thread_stop); // Compute return_status if(do_eval && ratio >= accuracy) return_status = 0; // optimum reached. // Free memory WW_free_memory(&cache); free(delta[1]);free(delta); free(grad_threads); free(grad_data); pthread_exit((void*)return_status); } /* Allocate the memory for the cache */ void WW_alloc_memory(struct TrainingCache *cache, const long Q, const long nb_data, const long chunk_size) { cache->table_chunk = (long *) calloc(chunk_size+1, sizeof(long)); cache->out_of_chunk = (long *) calloc(nb_data+1, sizeof(long)); cache->in_chunk = (long *) calloc(nb_data+1, sizeof(long)); cache->lp_sol = matrix(chunk_size, Q); cache->K = (double **)malloc(sizeof(double *) * (chunk_size+1)); cache->H_delta = matrix(chunk_size, Q); cache->alpha_update = matrix(chunk_size, Q); } /* Free the cache memory */ void WW_free_memory(struct TrainingCache *cache) { free(cache->table_chunk); free(cache->out_of_chunk); free(cache->in_chunk); free(cache->K); free(cache->lp_sol[1]);free(cache->lp_sol); free(cache->H_delta[1]);free(cache->H_delta); free(cache->alpha_update[1]);free(cache->alpha_update); } /* Solve the LP subproblem by calling lp_solve API */ int WW_solve_lp(double **gradient, const struct TrainingCache *cache, const struct Model *model) { long i,k,l, y_i, ind_pattern ; const long Q = model->Q; const long chunk_size = cache->chunk_size; const double *C = model->C; const int nRows = Q-1; const int nCols = chunk_size * (Q-1); double *obj = (double*)malloc(sizeof(double) * (1+nCols)); double *row = (double*)malloc(sizeof(double) * (1+nCols)); double *rhs = (double*)malloc(sizeof(double) * Q); long **lp_sol_table = matrix_l(nCols, 2); long **lp_sol_table_inv = matrix_l(chunk_size, Q); double *sol = (double*)malloc(sizeof(double) * (1+nRows+nCols)); double epsel; // Make LP lprec *lp = make_lp(0, nCols); set_add_rowmode(lp, TRUE); // Make objective function int col = 1; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; y_i = model->y[ind_pattern]; for(k=1; k<=Q; k++) if(k != y_i) { obj[col] = gradient[ind_pattern][k]; lp_sol_table[col][1] = i; // keep a table of correspondance between lp_sol_table[col][2] = k; // LPSOLVE vector of variables and lp_sol matrix lp_sol_table_inv[i][k] = col++; // lp_sol[i][k] = the 'lp_solve_table_inv[i][k]'-th variable for LPSOLVE } } set_obj_fn(lp, obj); /* // Make RHS of constraints // -- complete computation -- for(k=1; kin_chunk[i] == 0) { y_i = model->y[i]; for(l=1; l<=Q; l++) { if((y_i == k) && (l != k)) rhs[k] += model->alpha[i][l]; else if((y_i != k) && (l == k)) rhs[k] -= model->alpha[i][l]; } } } */ // Make RHS of constraints // -- updates to cache->rhs are made in compute_new_alpha() // to keep track of rhs // we only need to remove the contribution of the examples in the chunk for(k=1; klp_rhs[k]; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; y_i = model->y[ind_pattern]; for(l=1; l<=Q; l++){ if((y_i == k) && (l != k)) rhs[k] -= model->alpha[ind_pattern][l]; else if((y_i != k) && (l == k)) rhs[k] += model->alpha[ind_pattern][l]; } } } // Make constraints for(k=1; ktable_chunk[i]; y_i = model->y[ind_pattern]; if(y_i == k) { for(l=1; l<=Q; l++) { if(l != k) { row[lp_sol_table_inv[i][l]] = -1.0; } } } else row[lp_sol_table_inv[i][k]] = +1.0; } add_constraint(lp, row, EQ, rhs[k]); } // Upper bound on variables: alpha_ik <= C for(col=1;col<=nCols;col++) set_upbo(lp, col, C[model->y[cache->table_chunk[lp_sol_table[col][1]]]]); // End of LP making set_add_rowmode(lp, FALSE); //print_lp(lp); // Solve LP int jump = false; set_outputfile(lp,""); if(solve(lp)) { printf("Problem with the LP... \n (perhaps you need to increase the chunk size with '-w size') \n"); jump = true; } else { // Recover solution in the matrix lp_sol get_primal_solution(lp, sol); // sol: template for lp_solve solution format // sol=[obj, constraints, variables] epsel = get_epsel(lp); // tolerance in lp_solve // Set unused elements in lp_sol for(i=1; i<=chunk_size; i++) cache->lp_sol[i][model->y[cache->table_chunk[i]]] = 0.0; // Put solution into lp_sol for(col=1; col<= nCols; col++) { // Check feasibility of the col-th variable if((sol[nRows+col] < -epsel) || (sol[nRows+col] > C[model->y[cache->table_chunk[lp_sol_table[col][1]]]] + epsel)) { jump = true; break; } // Round off tolerance if(fabs(sol[nRows+col]) < epsel) sol[nRows+col] = 0.0; else if(fabs(sol[nRows+col] - C[model->y[cache->table_chunk[lp_sol_table[col][1]]]]) < epsel) sol[nRows+col] = C[model->y[cache->table_chunk[lp_sol_table[col][1]]]]; // Set the value in lp_sol matrix cache->lp_sol[lp_sol_table[col][1]][lp_sol_table[col][2]] = sol[nRows+col]; } } delete_lp(lp); free(obj); free(row); free(rhs); free(lp_sol_table[1]);free(lp_sol_table); free(lp_sol_table_inv[1]);free(lp_sol_table_inv); free(sol); return jump; } /* WW_init_gradient({ALPHA_IS_ZERO,ALPHA_NOT_ZERO}, gradient, cache, model) */ void WW_init_gradient(const enum AlphaInitType alpha_init_type, double **gradient, double **H_alpha, const struct Model *model) { long i,j,k,l,y_i,y_j; const long nb_data = model->nb_data; const long Q = model->Q; const enum Kernel_type nature_kernel = model->nature_kernel; const double *kernel_par = model->kernel_par; const long dim_input = model->dim_input; double partial, gradient_ik; if(alpha_init_type == ALPHA_IS_ZERO) { // Fast initialization for(i=1; i<=nb_data; i++) { for(k=1; k<=Q; k++) { gradient[i][k] = -1.0; H_alpha[i][k] = 0.0; } gradient[i][model->y[i]] = 0.0; } } else { // Do a proper initialization based on the values of alpha for(i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { gradient_ik = 0.0; for(j=1; j<=nb_data; j++) { y_j = model->y[j]; partial = 0.0; if(y_j == y_i) for(l=1; l<=Q; l++) partial += model->alpha[j][l]; if(y_j == k) for(l=1; l<=Q; l++) partial -= model->alpha[j][l]; partial += model->alpha[j][k] - model->alpha[j][y_i]; if(partial != 0.0) gradient_ik += partial * ker(nature_kernel, model->X[i], model->X[j], dim_input,kernel_par); } gradient[i][k] = gradient_ik - 1.0; H_alpha[i][k] = gradient_ik; } else { gradient[i][k] = 0.0; H_alpha[i][k] = 0.0; } } } } } /* Thread for updates of the gradient in parallel (spawn by main computing thread WW_train_thread) */ void *WW_update_gradient_thread(void *th_data) { // Recover thread data struct ThreadGradient_data *data = (struct ThreadGradient_data *) th_data; double **gradient = data->gradient; double **H_alpha = data->H_alpha; struct TrainingCache *cache = data->cache; const struct Model *model = data->model; const long start_i = data->start_i; const long end_i = data->end_i; // Local variables long i,j,k,l,y_i,y_j,ind_pattern; const long Q = model->Q; const long chunk_size = cache->chunk_size; double partial, gradient_update_ik; for(i=start_i; i<=end_i; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { gradient_update_ik = 0.0; for(j=1; j<=chunk_size; j++) { ind_pattern = cache->table_chunk[j]; y_j = model->y[ind_pattern]; partial = 0.0; if(y_j == y_i) for(l=1; l<=Q; l++) partial += cache->alpha_update[j][l]; else if(y_j == k) for(l=1; l<=Q; l++) partial -= cache->alpha_update[j][l]; partial += cache->alpha_update[j][k] - cache->alpha_update[j][y_i]; // Use the symmetry of K: cache->K[i][ind_pattern] = K(ind_pattern, i) = cache->K[j][i] gradient_update_ik += partial * cache->K[j][i]; } gradient[i][k] += gradient_update_ik; H_alpha[i][k] += gradient_update_ik; } } } pthread_exit(EXIT_SUCCESS); } /* Old-style non-threaded gradient update */ void WW_update_gradient(double **gradient, double **H_alpha, struct TrainingCache *cache, const struct Model *model) { long i,j,k,l,y_i,y_j,ind_pattern; const long nb_data = model->nb_data; const long Q = model->Q; const long chunk_size = cache->chunk_size; double partial, gradient_update_ik; for(i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { gradient_update_ik = 0.0; for(j=1; j<=chunk_size; j++) { ind_pattern = cache->table_chunk[j]; y_j = model->y[ind_pattern]; partial = 0.0; if(y_j == y_i) for(l=1; l<=Q; l++) partial += cache->alpha_update[j][l]; if(y_j == k) for(l=1; l<=Q; l++) partial -= cache->alpha_update[j][l]; partial += cache->alpha_update[j][k] - cache->alpha_update[j][y_i]; // Use the symmetry of K: cache->K[i][ind_pattern] = K(ind_pattern, i) = cache->K[j][i] gradient_update_ik += partial * cache->K[j][i]; } gradient[i][k] += gradient_update_ik; H_alpha[i][k] += gradient_update_ik; } } } } /* Check norm of gradient in chunk */ int WW_check_gradient_chunk(double **gradient, struct TrainingCache *cache, const struct Model *model) { long i,k; const long Q = model->Q; const long chunk_size = cache->chunk_size; int jump = 0; double norm = 0.0; for(i=1; i<=chunk_size; i++) for(k=1; k<=Q; k++) norm += gradient[cache->table_chunk[i]][k] * gradient[cache->table_chunk[i]][k]; norm = sqrt(norm); if(norm < small_enough) { printf("\nNorm of the gradient vector: %e\n", norm); if(chunk_size < model->nb_data) jump = true; else { printf("\n\nAn optimal solution has been found !\n\n"); jump = 2; } printf("\nGradient vector\n"); display_mat(gradient, chunk_size, Q, 10, 6); Pause("Proceed after gradient display...\n"); } return jump; } void WW_compute_H_delta(double **delta, struct TrainingCache *cache, const struct Model *model) { long i,k,j,y_i,y_j,l; const long Q = model->Q; const long chunk_size = cache->chunk_size; double partial; for(i=1; i<=chunk_size; i++) { y_i = model->y[cache->table_chunk[i]]; for(k=1; k<=Q; k++) { cache->H_delta[i][k] = 0.0; if(k != y_i) { for(j=1; j<=chunk_size; j++) { y_j = model->y[cache->table_chunk[j]]; partial = 0.0; if(y_j == y_i) for(l=1; l<=Q; l++) partial += delta[j][l]; if(y_j == k) for(l=1; l<=Q; l++) partial -= delta[j][l]; partial += delta[j][k] - delta[j][y_i]; cache->H_delta[i][k] += partial * cache->K[i][cache->table_chunk[j]]; } } } } } int WW_check_opt_sol(double **gradient, struct TrainingCache *cache, const struct Model *model) { double gradient_alpha = 0.0; double gradient_Gamma = 0.0; double gradient_diff = 0.0; long i,k,ind_pattern,y_i; const long Q = model->Q; const long chunk_size = cache->chunk_size; int jump = false; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; y_i = model->y[ind_pattern]; for(k=1; k<=Q; k++) if(k != y_i) { gradient_alpha += gradient[ind_pattern][k] * model->alpha[ind_pattern][k]; gradient_Gamma += gradient[ind_pattern][k] * cache->lp_sol[i][k]; } } gradient_diff = gradient_alpha - gradient_Gamma; if(gradient_diff <= 0.0) jump = true; cache->gradient_diff = gradient_diff; return jump; } /* Update model paramaters alpha_ik Return the difference in number of SVs */ long WW_compute_new_alpha(const double theta_opt, const struct TrainingCache *cache, struct Model *model) { long i,k,ind_pattern,l,y_i; const long Q = model->Q; const double *C = model->C; const long chunk_size = cache->chunk_size; double alpha_tmp; long nb_SV = 0; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; y_i = model->y[ind_pattern]; // Assume x_i is not a SV if(cache->activeset[ind_pattern]) { cache->activeset[ind_pattern] = 0; nb_SV--; } for(k=1; k<=Q; k++) { cache->alpha_update[i][k] = theta_opt * ( cache->lp_sol[i][k] - model->alpha[ind_pattern][k] ); alpha_tmp = model->alpha[ind_pattern][k] + cache->alpha_update[i][k]; if(alpha_tmp > C[y_i] && alpha_tmp < C[y_i] * ( 1.0 + small_enough)) { cache->alpha_update[i][k] = C[y_i] - model->alpha[ind_pattern][k]; model->alpha[ind_pattern][k] = C[y_i]; } else { model->alpha[ind_pattern][k] = alpha_tmp; if(alpha_tmp > 0.0 && alpha_tmp < C[y_i]) { // Update nb_SV and activeset if(cache->activeset[ind_pattern] == 0) { cache->activeset[ind_pattern] = 1; nb_SV++; } } } } // Update RHS of constraints in LP for(k=1; klp_rhs[k] += cache->alpha_update[i][l]; else if((y_i != k) && (l == k)) cache->lp_rhs[k] -= cache->alpha_update[i][l]; } } } return nb_SV; } void WW_compute_delta(double **delta, const struct TrainingCache *cache, const struct Model *model) { long i,k,ind_pattern; const long Q = model->Q; const long chunk_size = cache->chunk_size; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; for(k=1; k<=Q; k++) delta[i][k] = model->alpha[ind_pattern][k] - cache->lp_sol[i][k]; } } double WW_compute_theta_opt(double **delta, struct TrainingCache *cache, const struct Model *model) { long i,k; const long chunk_size = cache->chunk_size; const long Q = model->Q; double theta_opt, denominator = 0.0; WW_compute_H_delta(delta, cache,model); for(i=1; i<=chunk_size; i++) for(k=1; k<=Q; k++) denominator += delta[i][k] * cache->H_delta[i][k]; if(denominator <=0) { printf("\nWrong estimate of theta: %e\n", denominator); exit(0); } theta_opt = cache->gradient_diff / denominator; if(theta_opt > 1.0) theta_opt = 1.0; return theta_opt; } MSVMpack1.2/src/libtrainMSVM_WW.c~0000644000175000017500000006434511761350122016011 0ustar lauerlauer/* Copyright 2000-2010 Yann Guermeur */ /* 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 2 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, write to the Free Software */ /* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA*/ /*--------------------------------------------------------------------------*/ /* Name : libtrainMSVM_WW.c */ /* Version : 2.0 */ /* Creation : 04/27/00 */ /* Last update : 11/29/10 */ /* Subject : Training algorithm of the M-SVM of Weston and Watkins */ /* Algo. : Frank-Wolfe algorithm + decomposition method */ /* Author : Fabien Lauer and Yann Guermeur Yann.Guermeur@loria.fr */ /*--------------------------------------------------------------------------*/ #include "libtrainMSVM_WW.h" /* Weston and Watkins (WW) MSVM training function Solves the dual problem wrt alpha: min 1/2 alpha' H alpha - sum (alpha) s.t. 0 <= alpha_ik <= C, for all i,k, such that 1 <= i <= m, 1 <= k != y_i <= Q sum_{y_i=k} sum_l alpha_il - sum_i alpha_ik = 0, for all k, 1 <= k <= Q-1 where H_ik,jl = (delta_yi,yj - delta_yi,l - delta_yj,k + delta_k,l) k(x_i,x_j) */ long MSVM_WW_train(struct Model *model, struct Data *training_set, long chunk_size, const double accuracy, int cache_memory, const int nprocs, char *alpha0_file, char *model_tmp_file, char *log_file) { long return_status = -1; FILE *fp; int t; pthread_t *threads = (pthread_t *)malloc(sizeof(pthread_t) * nprocs); // threads id void *status; // for pthread_join int rc; // return code of pthread functions pthread_t thread_monitor; enum AlphaInitType alphaiszero; if(training_set != NULL) { // Initialize model for this particular training set model_load_data(model, training_set); // Check if a kernel_par has been set if(model->nature_kernel != LINEAR && model->kernel_par == NULL) set_default_kernel_par(model); // Check that chunk_size >= Q if(chunk_size < model->Q) chunk_size = model->Q; } if(model->nb_data > 2147483647) { printf("Cannot compute table chunk: number of data above random number limit\n"); exit(0); } // Log file if (log_file != NULL) { printf("\nLog training info in %s ...\n", log_file); fp = fopen(log_file,"a"); } else fp = NULL; // Initialize alpha and b if(training_set != NULL) // otherwise resume training init_alpha_b(model, alpha0_file); // use init_alpha_b(model, NULL); to initialize all alpha to 0 if(training_set == NULL || alpha0_file != NULL) alphaiszero = ALPHA_NOT_ZERO; else alphaiszero = ALPHA_IS_ZERO; EVAL = 0; // triggered by signal handler to call eval STOP = 0; // triggered by user to stop training iter = 1; // number of iterations (over all threads) // Prepare monitoring of model struct MonitorData monitor_data; monitor_data.model_tmp_file = model_tmp_file; monitor_data.period = MONITOR_PERIOD; monitor_data.model = model; pthread_create(&thread_monitor, NULL, MSVM_monitor_model_thread, (void *) &monitor_data); // Allocate memory for shared ressources double **gradient = matrix(model->nb_data, model->Q); double **H_alpha = matrix(model->nb_data, model->Q); double best_primal_upper_bound = HUGE_VAL; int *activeset = (int *)calloc(model->nb_data+1, sizeof(int)); double *lp_rhs = (double*)calloc(model->Q, sizeof(double)); // including the kernel cache: struct KernelCache kc; unsigned long cache_size = (unsigned long)cache_memory * MBYTES; kernel_initialize_cache(cache_size, &kc, model); printf("Initialization... ");fflush(stdout); // Initialize gradient WW_init_gradient(alphaiszero, gradient, H_alpha,model); printf("Done.\n"); // Initialize display if(accuracy>0) print_training_info(0,0,0,model->type); else { printf("Training...");fflush(stdout); } // Prepare data for computing threads long nb_SV = 0; struct ThreadData thread_data; thread_data.nprocs = nprocs; thread_data.model = model; thread_data.kernelcache = &kc; thread_data.chunk_size = chunk_size; thread_data.accuracy = accuracy; thread_data.gradient = gradient; thread_data.H_alpha = H_alpha; thread_data.best_primal_upper_bound = &best_primal_upper_bound; thread_data.activeset = activeset; thread_data.nb_SV = &nb_SV; thread_data.lp_rhs = lp_rhs; thread_data.logfile_ptr = fp; // Launch computing threads for(t=0;tthread_id; const int nprocs = data->nprocs; struct Model *model = data->model; struct KernelCache *kernelcache = data->kernelcache; long chunk_size = data->chunk_size; const double accuracy = data->accuracy; double **gradient = data->gradient; double **H_alpha = data->H_alpha; double *best_primal_upper_bound = data->best_primal_upper_bound; int *activeset = data->activeset; long *nb_SV = data->nb_SV; double *lp_rhs = data->lp_rhs; FILE *fp = data->logfile_ptr; pthread_mutex_unlock(&thread_data_mutex); // Release thread_data for next thread // Local variables int do_eval; char yesno; long return_status = -1; double **delta = matrix(chunk_size, model->Q); double theta_opt; int jump = false; if(accuracy == 0) do_eval = 0; else do_eval = 1; // Prepare the cache struct TrainingCache cache; cache.chunk_size = chunk_size; WW_alloc_memory(&cache, model->Q, model->nb_data, chunk_size); cache.kc = kernelcache; cache.activeset = activeset; cache.lp_rhs = lp_rhs; /* Prepare parallel gradient computations: - the gradient vector is split into NUMTHREADS_GRAD parts (along i) - each part is updated by a different thread */ // max number of threads for gradient updates is nprocs pthread_t *grad_threads = (pthread_t *)malloc(sizeof(pthread_t) * nprocs); // start with 1 thread (main load on kernel evaluations) int numthreads_grad = 1; // More CPUs for gradient updates if Q > dimension of data if(model->dim_input < model->Q) numthreads_grad = nprocs; void *status; int rc; long k; struct ThreadGradient_data *grad_data = (struct ThreadGradient_data *)malloc(sizeof(struct ThreadGradient_data) * nprocs); // Disable parallel gradient computation for small data sets int parallel_gradient_update = 1; if(model->nb_data < 5000) parallel_gradient_update = 0; if(parallel_gradient_update) { for(k=0;knb_data / numthreads_grad; for(k=1;knb_data / numthreads_grad -1; } if(numthreads_grad>1) { grad_data[numthreads_grad-1].start_i = grad_data[numthreads_grad-2].end_i + 1; grad_data[numthreads_grad-1].end_i = model->nb_data; } } // Switch to nprocs/4 threads for gradient update when 25% of the kernel matrix is cached int percentage_step = 1; long percentage = model->nb_data / 4; int next_numthreads_grad = nprocs/4; if(next_numthreads_grad == 0) next_numthreads_grad = 1; // No thread switches if Q > dimension of data (keep all CPUs for gradient updates) if(model->dim_input < model->Q) percentage = 2*model->nb_data; // Main loop double ratio = 0.0; // stopping criterion (dual / upper bound) int thread_stop = 0; do { if((TRAIN_SMALL_STEP < TRAIN_STEP) && (iter%TRAIN_SMALL_STEP) == 0) { printf("."); fflush(stdout); } // Select a random chunk of data to optimize select_random_chunk(&cache,model); // Compute the kernel submatrix for this chunk compute_K(&cache,model); jump = WW_check_gradient_chunk(gradient,&cache,model); if(jump > 1) STOP = 1; // Enter Critical Section (using and modifying the model) pthread_mutex_lock(&model_mutex); if(jump == false) jump = WW_solve_lp(gradient, &cache, model); if(jump == false) jump = WW_check_opt_sol(gradient,&cache,model); if(jump == false) { WW_compute_delta(delta,&cache,model); theta_opt = WW_compute_theta_opt(delta, &cache, model); *nb_SV += WW_compute_new_alpha(theta_opt,&cache,model); if(parallel_gradient_update) { // Update gradient in parallel for(k=0;ktype); if(do_eval && ratio > accuracy) STOP = 1; if(EVAL) // if interrupted by user (otherwise let the ratio decide if we go on training) { printf("\n *** Do you want to continue training ([y]/n)? "); yesno = getchar(); if(yesno=='n') { STOP = 1; } EVAL = 0; // reset interruption trigger } } // Release kernel submatrix in cache release_K(&cache); // Check if a sufficient % of the kernel matrix is cached if( parallel_gradient_update && cache.kc->max_idx >= percentage ) { // and switch thread to compute gradient upates instead of kernel rows if it is thread_stop = switch_thread(nprocs, &numthreads_grad, &next_numthreads_grad, &percentage, &percentage_step, grad_data, thread_id, model->nb_data); // (threads are actually stopped to leave the CPUs // to other threads that will compute gradient updates) } iter++; // Release mutex: End of critical section pthread_mutex_unlock(&model_mutex); } while(iter <= MSVM_TRAIN_MAXIT && (!do_eval || ratio < accuracy) && !STOP && !thread_stop); // Compute return_status if(do_eval && ratio >= accuracy) return_status = 0; // optimum reached. // Free memory WW_free_memory(&cache); free(delta[1]);free(delta); free(grad_threads); free(grad_data); pthread_exit((void*)return_status); } /* Allocate the memory for the cache */ void WW_alloc_memory(struct TrainingCache *cache, const long Q, const long nb_data, const long chunk_size) { cache->table_chunk = (long *) calloc(chunk_size+1, sizeof(long)); cache->out_of_chunk = (long *) calloc(nb_data+1, sizeof(long)); cache->in_chunk = (long *) calloc(nb_data+1, sizeof(long)); cache->lp_sol = matrix(chunk_size, Q); cache->K = (double **)malloc(sizeof(double *) * (chunk_size+1)); cache->H_delta = matrix(chunk_size, Q); cache->alpha_update = matrix(chunk_size, Q); } /* Free the cache memory */ void WW_free_memory(struct TrainingCache *cache) { free(cache->table_chunk); free(cache->out_of_chunk); free(cache->in_chunk); free(cache->K); free(cache->lp_sol[1]);free(cache->lp_sol); free(cache->H_delta[1]);free(cache->H_delta); free(cache->alpha_update[1]);free(cache->alpha_update); } /* Solve the LP subproblem by calling lp_solve API */ int WW_solve_lp(double **gradient, const struct TrainingCache *cache, const struct Model *model) { long i,k,l, y_i, ind_pattern ; const long Q = model->Q; const long chunk_size = cache->chunk_size; const double *C = model->C; const int nRows = Q-1; const int nCols = chunk_size * (Q-1); double *obj = (double*)malloc(sizeof(double) * (1+nCols)); double *row = (double*)malloc(sizeof(double) * (1+nCols)); double *rhs = (double*)malloc(sizeof(double) * Q); long **lp_sol_table = matrix_l(nCols, 2); long **lp_sol_table_inv = matrix_l(chunk_size, Q); double *sol = (double*)malloc(sizeof(double) * (1+nRows+nCols)); double epsel; // Make LP lprec *lp = make_lp(0, nCols); set_add_rowmode(lp, TRUE); // Make objective function int col = 1; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; y_i = model->y[ind_pattern]; for(k=1; k<=Q; k++) if(k != y_i) { obj[col] = gradient[ind_pattern][k]; lp_sol_table[col][1] = i; // keep a table of correspondance between lp_sol_table[col][2] = k; // LPSOLVE vector of variables and lp_sol matrix lp_sol_table_inv[i][k] = col++; // lp_sol[i][k] = the 'lp_solve_table_inv[i][k]'-th variable for LPSOLVE } } set_obj_fn(lp, obj); /* // Make RHS of constraints // -- complete computation -- for(k=1; kin_chunk[i] == 0) { y_i = model->y[i]; for(l=1; l<=Q; l++) { if((y_i == k) && (l != k)) rhs[k] += model->alpha[i][l]; else if((y_i != k) && (l == k)) rhs[k] -= model->alpha[i][l]; } } } */ // Make RHS of constraints // -- updates to cache->rhs are made in compute_new_alpha() // to keep track of rhs // we only need to remove the contribution of the examples in the chunk for(k=1; klp_rhs[k]; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; y_i = model->y[ind_pattern]; for(l=1; l<=Q; l++){ if((y_i == k) && (l != k)) rhs[k] -= model->alpha[ind_pattern][l]; else if((y_i != k) && (l == k)) rhs[k] += model->alpha[ind_pattern][l]; } } } // Make constraints for(k=1; ktable_chunk[i]; y_i = model->y[ind_pattern]; if(y_i == k) { for(l=1; l<=Q; l++) { if(l != k) { row[lp_sol_table_inv[i][l]] = -1.0; } } } else row[lp_sol_table_inv[i][k]] = +1.0; } add_constraint(lp, row, EQ, rhs[k]); } // Upper bound on variables: alpha_ik <= C for(col=1;col<=nCols;col++) set_upbo(lp, col, C[model->y[cache->table_chunk[lp_sol_table[col][1]]]]); // End of LP making set_add_rowmode(lp, FALSE); //print_lp(lp); // Solve LP int jump = false; set_outputfile(lp,""); if(solve(lp)) { printf("Problem with the LP... \n (perhaps you need to increase the chunk size with '-w size') \n"); jump = true; } else { // Recover solution in the matrix lp_sol get_primal_solution(lp, sol); // sol: template for lp_solve solution format // sol=[obj, constraints, variables] epsel = get_epsel(lp); // tolerance in lp_solve // Set unused elements in lp_sol for(i=1; i<=chunk_size; i++) cache->lp_sol[i][model->y[cache->table_chunk[i]]] = 0.0; // Put solution into lp_sol for(col=1; col<= nCols; col++) { // Check feasibility of the col-th variable if((sol[nRows+col] < -epsel) || (sol[nRows+col] > C[model->y[cache->table_chunk[lp_sol_table[col][1]]]] + epsel)) { jump = true; break; } // Round off tolerance if(fabs(sol[nRows+col]) < epsel) sol[nRows+col] = 0.0; else if(fabs(sol[nRows+col] - C[model->y[cache->table_chunk[lp_sol_table[col][1]]]]) < epsel) sol[nRows+col] = C[model->y[cache->table_chunk[lp_sol_table[col][1]]]]; // Set the value in lp_sol matrix cache->lp_sol[lp_sol_table[col][1]][lp_sol_table[col][2]] = sol[nRows+col]; } } delete_lp(lp); free(obj); free(row); free(rhs); free(lp_sol_table[1]);free(lp_sol_table); free(lp_sol_table_inv[1]);free(lp_sol_table_inv); free(sol); return jump; } /* WW_init_gradient({ALPHA_IS_ZERO,ALPHA_NOT_ZERO}, gradient, cache, model) */ void WW_init_gradient(const enum AlphaInitType alpha_init_type, double **gradient, double **H_alpha, const struct Model *model) { long i,j,k,l,y_i,y_j; const long nb_data = model->nb_data; const long Q = model->Q; const enum Kernel_type nature_kernel = model->nature_kernel; const double *kernel_par = model->kernel_par; const long dim_input = model->dim_input; double partial, gradient_ik; if(alpha_init_type == ALPHA_IS_ZERO) { // Fast initialization for(i=1; i<=nb_data; i++) { for(k=1; k<=Q; k++) { gradient[i][k] = -1.0; H_alpha[i][k] = 0.0; } gradient[i][model->y[i]] = 0.0; } } else { // Do a proper initialization based on the values of alpha for(i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { gradient_ik = 0.0; for(j=1; j<=nb_data; j++) { y_j = model->y[j]; partial = 0.0; if(y_j == y_i) for(l=1; l<=Q; l++) partial += model->alpha[j][l]; if(y_j == k) for(l=1; l<=Q; l++) partial -= model->alpha[j][l]; partial += model->alpha[j][k] - model->alpha[j][y_i]; if(partial != 0.0) gradient_ik += partial * ker(nature_kernel, model->X[i], model->X[j], dim_input,kernel_par); } gradient[i][k] = gradient_ik - 1.0; H_alpha[i][k] = gradient_ik; } else { gradient[i][k] = 0.0; H_alpha[i][k] = 0.0; } } } } } /* Thread for updates of the gradient in parallel (spawn by main computing thread WW_train_thread) */ void *WW_update_gradient_thread(void *th_data) { // Recover thread data struct ThreadGradient_data *data = (struct ThreadGradient_data *) th_data; double **gradient = data->gradient; double **H_alpha = data->H_alpha; struct TrainingCache *cache = data->cache; const struct Model *model = data->model; const long start_i = data->start_i; const long end_i = data->end_i; // Local variables long i,j,k,l,y_i,y_j,ind_pattern; const long Q = model->Q; const long chunk_size = cache->chunk_size; double partial, gradient_update_ik; for(i=start_i; i<=end_i; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { gradient_update_ik = 0.0; for(j=1; j<=chunk_size; j++) { ind_pattern = cache->table_chunk[j]; y_j = model->y[ind_pattern]; partial = 0.0; if(y_j == y_i) for(l=1; l<=Q; l++) partial += cache->alpha_update[j][l]; else if(y_j == k) for(l=1; l<=Q; l++) partial -= cache->alpha_update[j][l]; partial += cache->alpha_update[j][k] - cache->alpha_update[j][y_i]; // Use the symmetry of K: cache->K[i][ind_pattern] = K(ind_pattern, i) = cache->K[j][i] gradient_update_ik += partial * cache->K[j][i]; } gradient[i][k] += gradient_update_ik; H_alpha[i][k] += gradient_update_ik; } } } pthread_exit(EXIT_SUCCESS); } /* Old-style non-threaded gradient update */ void WW_update_gradient(double **gradient, double **H_alpha, struct TrainingCache *cache, const struct Model *model) { long i,j,k,l,y_i,y_j,ind_pattern; const long nb_data = model->nb_data; const long Q = model->Q; const long chunk_size = cache->chunk_size; double partial, gradient_update_ik; for(i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { gradient_update_ik = 0.0; for(j=1; j<=chunk_size; j++) { ind_pattern = cache->table_chunk[j]; y_j = model->y[ind_pattern]; partial = 0.0; if(y_j == y_i) for(l=1; l<=Q; l++) partial += cache->alpha_update[j][l]; if(y_j == k) for(l=1; l<=Q; l++) partial -= cache->alpha_update[j][l]; partial += cache->alpha_update[j][k] - cache->alpha_update[j][y_i]; // Use the symmetry of K: cache->K[i][ind_pattern] = K(ind_pattern, i) = cache->K[j][i] gradient_update_ik += partial * cache->K[j][i]; } gradient[i][k] += gradient_update_ik; H_alpha[i][k] += gradient_update_ik; } } } } /* Check norm of gradient in chunk */ int WW_check_gradient_chunk(double **gradient, struct TrainingCache *cache, const struct Model *model) { long i,k; const long Q = model->Q; const long chunk_size = cache->chunk_size; int jump = 0; double norm = 0.0; for(i=1; i<=chunk_size; i++) for(k=1; k<=Q; k++) norm += gradient[cache->table_chunk[i]][k] * gradient[cache->table_chunk[i]][k]; norm = sqrt(norm); if(norm < small_enough) { printf("\nNorm of the gradient vector: %e\n", norm); if(chunk_size < model->nb_data) jump = true; else { printf("\n\nAn optimal solution has been found !\n\n"); jump = 2; } printf("\nGradient vector\n"); display_mat(gradient, chunk_size, Q, 10, 6); Pause("Proceed after gradient display...\n"); } return jump; } void WW_compute_H_delta(double **delta, struct TrainingCache *cache, const struct Model *model) { long i,k,j,y_i,y_j,l; const long Q = model->Q; const long chunk_size = cache->chunk_size; double partial; for(i=1; i<=chunk_size; i++) { y_i = model->y[cache->table_chunk[i]]; for(k=1; k<=Q; k++) { cache->H_delta[i][k] = 0.0; if(k != y_i) { for(j=1; j<=chunk_size; j++) { y_j = model->y[cache->table_chunk[j]]; partial = 0.0; if(y_j == y_i) for(l=1; l<=Q; l++) partial += delta[j][l]; if(y_j == k) for(l=1; l<=Q; l++) partial -= delta[j][l]; partial += delta[j][k] - delta[j][y_i]; cache->H_delta[i][k] += partial * cache->K[i][cache->table_chunk[j]]; } } } } } int WW_check_opt_sol(double **gradient, struct TrainingCache *cache, const struct Model *model) { double gradient_alpha = 0.0; double gradient_Gamma = 0.0; double gradient_diff = 0.0; long i,k,ind_pattern,y_i; const long Q = model->Q; const long chunk_size = cache->chunk_size; int jump = false; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; y_i = model->y[ind_pattern]; for(k=1; k<=Q; k++) if(k != y_i) { gradient_alpha += gradient[ind_pattern][k] * model->alpha[ind_pattern][k]; gradient_Gamma += gradient[ind_pattern][k] * cache->lp_sol[i][k]; } } gradient_diff = gradient_alpha - gradient_Gamma; if(gradient_diff <= 0.0) jump = true; cache->gradient_diff = gradient_diff; return jump; } /* Update model paramaters alpha_ik Return the difference in number of SVs */ long WW_compute_new_alpha(const double theta_opt, const struct TrainingCache *cache, struct Model *model) { long i,k,ind_pattern,l,y_i; const long Q = model->Q; const double *C = model->C; const long chunk_size = cache->chunk_size; double alpha_tmp; long nb_SV = 0; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; y_i = model->y[ind_pattern]; // Assume x_i is not a SV if(cache->activeset[ind_pattern]) { cache->activeset[ind_pattern] = 0; nb_SV--; } for(k=1; k<=Q; k++) { cache->alpha_update[i][k] = theta_opt * ( cache->lp_sol[i][k] - model->alpha[ind_pattern][k] ); alpha_tmp = model->alpha[ind_pattern][k] + cache->alpha_update[i][k]; if(alpha_tmp > C[y_i] && alpha_tmp < C[y_i] * ( 1.0 + small_enough)) { cache->alpha_update[i][k] = C[y_i] - model->alpha[ind_pattern][k]; model->alpha[ind_pattern][k] = C[y_i]; } else { model->alpha[ind_pattern][k] = alpha_tmp; if(alpha_tmp > 0.0 && alpha_tmp < C[y_i]) { // Update nb_SV and activeset if(cache->activeset[ind_pattern] == 0) { cache->activeset[ind_pattern] = 1; nb_SV++; } } } } // Update RHS of constraints in LP for(k=1; klp_rhs[k] += cache->alpha_update[i][l]; else if((y_i != k) && (l == k)) cache->lp_rhs[k] -= cache->alpha_update[i][l]; } } } return nb_SV; } void WW_compute_delta(double **delta, const struct TrainingCache *cache, const struct Model *model) { long i,k,ind_pattern; const long Q = model->Q; const long chunk_size = cache->chunk_size; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; for(k=1; k<=Q; k++) delta[i][k] = model->alpha[ind_pattern][k] - cache->lp_sol[i][k]; } } double WW_compute_theta_opt(double **delta, struct TrainingCache *cache, const struct Model *model) { long i,k; const long chunk_size = cache->chunk_size; const long Q = model->Q; double theta_opt, denominator = 0.0; WW_compute_H_delta(delta, cache,model); for(i=1; i<=chunk_size; i++) for(k=1; k<=Q; k++) denominator += delta[i][k] * cache->H_delta[i][k]; if(denominator <=0) { printf("\nWrong estimate of theta: %e\n", denominator); exit(0); } theta_opt = cache->gradient_diff / denominator; if(theta_opt > 1.0) theta_opt = 1.0; return theta_opt; } MSVMpack1.2/src/algebra.c0000644000175000017500000003162211651473744014272 0ustar lauerlauer/*--------------------------------------------------------------------------*/ /* Name : algebra.c */ /* Version : 1.0 */ /* Creation : 12/22/95 */ /* Last update : 02/04/11 */ /* Subject : Additional math libraries */ /* Module : Unit including algebra functions */ /* Author : Fabien Lauer and Yann Guermeur Yann.Guermeur@loria.fr */ /*--------------------------------------------------------------------------*/ #include #include #include #include #include #include "algebra.h" #define true 1 #define false 0 #define sign(a,b) ((b) > 0.0 ? fabs(a) : -fabs(a)) /* Allocate matrices with 16-byte aligned rows */ /* Allocate a DOUBLE aligned matrix */ double **matrix_aligned(long nrow, long ncol) { long ind1; double **m; m = (double **) malloc((size_t)((nrow+1)*sizeof(double*))); if(m == NULL) { printf("\nallocation failure 1 in matrix_aligned()"); exit(0); } // Complete each row with this amount of empty elements: int fill_row_to_align = 2 - (ncol %2); // Allocate an aligned memory block m[0] = MALLOC(double, nrow*(ncol+1 + fill_row_to_align)); if(m[0] == NULL) { printf("\nallocation failure 2 in matrix_aligned()\n"); exit(0); } // Align the first element of the first row accessed by m[1][1] m[1] = m[0] + ALIGNMENT(double); // Assign aligned pointers to rows if(fill_row_to_align != 0) for(ind1=2;ind1<=nrow;ind1++){ m[ind1] = m[ind1-1]+ncol+ fill_row_to_align; } else { for(ind1=2;ind1<=nrow;ind1++) m[ind1] = m[ind1-1]+ncol; } return m; } /* Allocate a FLOAT aligned matrix */ float **matrix_f_aligned(long nrow, long ncol) { long ind1; float **m; m = (float **) malloc((size_t)((nrow+1)*sizeof(float*))); if(m == NULL) { printf("\nallocation failure 1 in matrix_f_aligned()\n"); exit(0); } int fill_row_to_align = 4 - (ncol %4); m[0] = MALLOC(float, nrow*(ncol+1 + fill_row_to_align)); m[1] = m[0] + ALIGNMENT(float); // to align m[1][1] if(m[0]==NULL) { printf("\nallocation failure 2 in matrix_f_aligned()"); exit(0); } if(fill_row_to_align != 0) for(ind1=2;ind1<=nrow;ind1++){ m[ind1] = m[ind1-1] + ncol + fill_row_to_align; } else { for(ind1=2;ind1<=nrow;ind1++) m[ind1] = m[ind1-1]+ncol; } return m; } /* Allocate a INT aligned matrix */ int **matrix_i_aligned(long nrow, long ncol) { long ind1; int **m; m = (int **) malloc((size_t)((nrow+1)*sizeof(int*))); if(!m) { printf("\nallocation failure 1 in matrix_i_aligned()"); exit(0); } int fill_row_to_align = 4 - (ncol %4); m[0] = MALLOC(int, nrow*(ncol+1 + fill_row_to_align)); m[1] = m[0] + ALIGNMENT(int); // to align m[1][1] if(m[0]==NULL) { printf("\nallocation failure 2 in matrix_i_aligned()"); exit(0); } if(fill_row_to_align != 0) for(ind1=2;ind1<=nrow;ind1++){ m[ind1] = m[ind1-1] + ncol + fill_row_to_align; } else { for(ind1=2;ind1<=nrow;ind1++) m[ind1] = m[ind1-1]+ncol; } return m; } /* Allocate a SHORT INT aligned matrix */ short int **matrix_s_aligned(long nrow, long ncol) { long ind1; short int **m; m = (short int **) malloc((size_t)((nrow+1)*sizeof(short int*))); if(!m) { printf("\nallocation failure 1 in matrix_s_aligned()"); exit(0); } int fill_row_to_align = 8 - (ncol % 8); m[0] = MALLOC(short int, nrow*(ncol+1 + fill_row_to_align)); m[1] = m[0] + ALIGNMENT(short int); // to align m[1][1] if(m[0]==NULL) { printf("\nallocation failure 2 in matrix_s_aligned()"); exit(0); } if(fill_row_to_align != 0) for(ind1=2;ind1<=nrow;ind1++){ m[ind1] = m[ind1-1] + ncol + fill_row_to_align; } else { for(ind1=2;ind1<=nrow;ind1++) m[ind1] = m[ind1-1]+ncol; } return m; } /* Allocate a BYTE (unsigned char) aligned matrix */ unsigned char **matrix_b_aligned(long nrow, long ncol) { long ind1; unsigned char **m; m = (unsigned char **) malloc((size_t)((nrow+1)*sizeof(unsigned char*))); if(!m) { printf("\nallocation failure 1 in matrix_b_aligned()"); exit(0); } int fill_row_to_align = 16 - (ncol % 16); m[0] = MALLOC(unsigned char, nrow*(ncol+1 + fill_row_to_align)); m[1] = m[0] + ALIGNMENT(unsigned char); // to align m[1][1] if(m[0]==NULL) { printf("\nallocation failure 2 in matrix_b_aligned()"); exit(0); } if(fill_row_to_align != 0) for(ind1=2;ind1<=nrow;ind1++){ m[ind1] = m[ind1-1] + ncol + fill_row_to_align; } else { for(ind1=2;ind1<=nrow;ind1++) m[ind1] = m[ind1-1]+ncol; } return m; } /* Free aligned matrices */ void free_mat_aligned(double **m) { FREE(m[0]); free(m); } void free_mat_f_aligned(float **m) { FREE(m[0]); free(m); } void free_mat_i_aligned(int **m) { FREE(m[0]); free(m); } void free_mat_s_aligned(short int **m) { FREE(m[0]); free(m); } void free_mat_b_aligned(unsigned char **m) { FREE(m[0]); free(m); } /* Unaligned alloc function */ long **matrix_l(long nrow, long ncol) /* Allocate a long matrix */ { long ind1, **m; m = (long **) malloc((size_t)((nrow+1)*sizeof(long*))); if(!m) { printf("\nallocation failure 1 in matrix_l()"); exit(0); } m[1] = (long *) malloc((size_t)((nrow*(ncol+1))*sizeof(long))); if(!m[1]) { printf("\nallocation failure 2 in matrix_l()"); exit(0); } for(ind1=2;ind1<=nrow;ind1++) m[ind1]=m[ind1-1]+ncol; return m; } int **matrix_i(long nrow, long ncol) /* Allocate a long matrix */ { long ind1; int **m = (int **) malloc((size_t)((nrow+1)*sizeof(int*))); if(!m) { printf("\nallocation failure 1 in matrix_l()"); exit(0); } m[1] = (int *) malloc((size_t)((nrow*(ncol+1))*sizeof(int))); if(!m[1]) { printf("\nallocation failure 2 in matrix_l()"); exit(0); } for(ind1=2;ind1<=nrow;ind1++) m[ind1]=m[ind1-1]+ncol; return m; } double **matrix(long nrow, long ncol) /* Allocate a double matrix */ { long ind1; double **m; m = (double **) malloc((size_t)((nrow+1)*sizeof(double*))); if(!m) { printf("\nallocation failure 1 in matrix()"); exit(0); } m[1] = (double *) malloc((size_t)((nrow*(ncol+1))*sizeof(double))); if(!m[1]) { printf("\nallocation failure 2 in matrix()"); exit(0); } for(ind1=2;ind1<=nrow;ind1++) m[ind1]=m[ind1-1]+ncol; return m; } float **matrix_f(long nrow, long ncol) /* Allocate a float matrix */ { long ind1; float **m; m = (float **) malloc((size_t)((nrow+1)*sizeof(float*))); if(!m) { printf("\nallocation failure 1 in matrix_f()"); exit(0); } m[1] = (float *) malloc((size_t)((nrow*(ncol+1))*sizeof(float))); if(!m[1]) { printf("\nallocation failure 2 in matrix_f()"); exit(0); } for(ind1=2;ind1<=nrow;ind1++) m[ind1]=m[ind1-1]+ncol; return m; } void trans_mat(double **mat1, double **mat2, long dim1, long dim2) /* Transpose a matrix */ { long ind1, ind2; for(ind1=1; ind1<=dim1; ind1++) for(ind2=1; ind2<=dim2; ind2++) mat2[ind2][ind1] = mat1[ind1][ind2]; } /* Transpose a matrix */ void trans_mat_float(float **mat1, float **mat2, long dim1, long dim2) { long ind1, ind2; for(ind1=1; ind1<=dim1; ind1++) for(ind2=1; ind2<=dim2; ind2++) mat2[ind2][ind1] = mat1[ind1][ind2]; } /* Transpose a matrix */ void trans_mat_int(int **mat1, int **mat2, long dim1, long dim2) { long ind1, ind2; for(ind1=1; ind1<=dim1; ind1++) for(ind2=1; ind2<=dim2; ind2++) mat2[ind2][ind1] = mat1[ind1][ind2]; } void add_mat(double **mat1, double **mat2, double **mat3, long dim1, long dim2) /* Addition of two matrices */ { long ind1, ind2; for(ind1=1; ind1<=dim1; ind1++) for(ind2=1; ind2<=dim2; ind2++) mat3[ind1][ind2] = mat1[ind1][ind2] + mat2[ind1][ind2]; } void scal_mat(double coeff, double **mat1, double **mat2, long dim1, long dim2) /* Multiplication of a matrix by a scalar */ { long ind1, ind2; for(ind1=1; ind1<=dim1; ind1++) for(ind2=1; ind2<=dim2; ind2++) mat2[ind1][ind2] = coeff * mat1[ind1][ind2]; } double prod_scal(const double *vect1, const double *vect2, const long dim) /* Dot product of two vectors (of same dimension) */ { long ind1; double product = 0.0; for(ind1=1; ind1<=dim; ind1++) product += vect1[ind1] * vect2[ind1]; return product; } void mult_mat(double **mat1, double **mat2, double **mat3, long dim1, long dim2, long dim3) /* Matrix product of any dimensions (assumed to be compatible) */ { int ind1, ind2, ind3; for(ind1=1; ind1<=dim1; ind1++) for(ind2=1; ind2<=dim3; ind2++) { mat3[ind1][ind2] = 0.0; for(ind3=1; ind3<=dim2; ind3++) mat3[ind1][ind2] += mat1[ind1][ind3] * mat2[ind3][ind2]; } } void display_mat_l(long **mat, long dim1, long dim2, int par1) { long ind1, ind2; printf("\n"); for(ind1=1; ind1<=dim1; ind1++) { for(ind2=1; ind2<=dim2; ind2++) printf("%*ld ", par1, mat[ind1][ind2]); printf("\n"); } printf("\n"); } void display_mat(double **mat, long dim1, long dim2, int par1, int par2) { long ind1, ind2; printf("\n"); for(ind1=1; ind1<=dim1; ind1++) { for(ind2=1; ind2<=dim2; ind2++) printf("%*.*lf ",par1,par2,mat[ind1][ind2]); printf("\n"); } printf("\n"); } void copy(double **mat1, double **mat2, long dim1, long dim2) { long ind1, ind2; for(ind1=1; ind1<=dim1; ind1++) for(ind2=1; ind2<=dim2; ind2++) mat2[ind1][ind2] = mat1[ind1][ind2]; } int compare(double **mat1, double **mat2, long dim1, long dim2, double seuil) { long ind1, ind2, id = true, end_mat = false; ind1 = ind2 = 1; while((id == true) && (end_mat == false)) { if(fabs(mat1[ind1][ind2] - mat2[ind1][ind2]) > seuil) id = false; else { if(ind2 < dim2) ind2++; else { if(ind1 < dim1) { ind1++; ind2 = 1; } else end_mat = true; } } } return id; } void diagonalize(double **mat, long dim, double *diagonal) /* Diagonalize a symmetric matrix */ { long i, j, k, l, m, iter; double scale, s, r, p, g, f, h, hh, dd, c, b, *off_diagonal; off_diagonal = (double *) calloc(dim+1, sizeof(double)); for(i=dim;i>=2;i--) { l=i-1; h=scale=0.0; if(l > 1) { for(k=1;k<=l;k++) scale += fabs(mat[i][k]); if(scale == 0.0) off_diagonal[i] = mat[i][l]; else { for(k=1;k<=l;k++) { mat[i][k] /= scale; h += mat[i][k] * mat[i][k]; } f = mat[i][l]; g = (f > 0.0 ? -sqrt(h) : sqrt(h)); off_diagonal[i] = scale * g; h -= f*g; mat[i][l] = f-g; f = 0.0; for(j=1;j<=l;j++) { mat[j][i] = mat[i][j]/h; g = 0.0; for(k=1;k<=j;k++) g += mat[j][k] * mat[i][k]; for(k=j+1;k<=l;k++) g += mat[k][j] * mat[i][k]; off_diagonal[j] = g/h; f += off_diagonal[j] * mat[i][j]; } hh = f / (h+h); for(j=1;j<=l;j++) { f = mat[i][j]; off_diagonal[j] = g = off_diagonal[j] - hh * f; for(k=1;k<=j;k++) mat[j][k] -= (f*off_diagonal[k]+g*mat[i][k]); } } } else off_diagonal[i] = mat[i][l]; diagonal[i] = h; } diagonal[1] = 0.0; off_diagonal[1] = 0.0; for(i=1;i<=dim;i++) { l=i-1; if(diagonal[i]) { for(j=1;j<=l;j++) { g = 0.0; for(k=1;k<=l;k++) g += mat[i][k] * mat[k][j]; for(k=1;k<=l;k++) mat[k][j] -= g * mat[k][i]; } } diagonal[i] = mat[i][i]; mat[i][i] = 1.0; for(j=1;j<=l;j++) mat[j][i] = mat[i][j] = 0.0; } for(i=2;i<=dim;i++) off_diagonal[i-1] = off_diagonal[i]; off_diagonal[dim] = 0.0; for(l=1;l<=dim;l++) { iter=0; do { for(m=l;m<=dim-1;m++) { dd = fabs(diagonal[m]) + fabs(diagonal[m+1]); if((fabs(off_diagonal[m])+dd) == dd) break; } if(m != l) { if(iter++ == 1000) { printf("\nToo many iterations in tqli...\n\n"); exit(0); } g = (diagonal[l+1]-diagonal[l]) / (2.0*off_diagonal[l]); r = sqrt(g*g + 1.0); g = diagonal[m]-diagonal[l]+off_diagonal[l] / (g+sign(r,g)); s = c = 1.0; p = 0.0; for(i=m-1;i>=l;i--) { f = s*off_diagonal[i]; b = c*off_diagonal[i]; off_diagonal[i+1] = (r = sqrt(f*f + g*g)); if(r == 0.0) { diagonal[i+1] -= p; off_diagonal[m] = 0.0; break; } s = f/r; c = g/r; g = diagonal[i+1]-p; r = (diagonal[i]-g)*s+2.0*c*b; diagonal[i+1] = g+(p=s*r); g = c*r-b; for(k=1;k<=dim;k++) { f=mat[k][i+1]; mat[k][i+1] = s*mat[k][i]+c*f; mat[k][i] = c*mat[k][i]-s*f; } } if(r == 0.0 && i >= 1) continue; diagonal[l] -= p; off_diagonal[l] = g; off_diagonal[m] = 0.0; } } while(m != l); } free(off_diagonal); } MSVMpack1.2/src/web/0000775000175000017500000000000012104703316013265 5ustar lauerlauerMSVMpack1.2/src/web/delete.c0000644000175000017500000000525111672406533014706 0ustar lauerlauer#include #include #include #include #ifndef _SC_NPROCESSORS_ONLN #include // for BSD #endif /* Return the number of available processors */ int get_nprocessors(void) { int nprocs; #ifdef _SC_NPROCESSORS_ONLN // Linux nprocs = (int)sysconf(_SC_NPROCESSORS_ONLN); #else // BSD int mib[4]; size_t len = sizeof(nprocs); mib[0] = CTL_HW; #ifdef HW_AVAILCPU mib[1] = HW_AVAILCPU; #else mib[1] = HW_NCPU; #endif sysctl(mib, 2, &nprocs, &len, NULL, 0); #endif // Make sure nprocs >= 1 if( nprocs < 1 ) nprocs = 1; return nprocs; } void HTMLheader(void) { printf("Content-Type: text/html;charset=UTF-8\n\n"); printf("\n"); printf("\n"); printf("\n"); printf("MSVMpack Server\n"); printf("\n"); printf("\n"); printf("

MSVMpack Server

\n"); } void HTMLfooter(void) { printf("
\n"); printf("
\n"); printf("MSVMpack Server version 1.1, last modified: Nov. 2011\n"); printf("
\n"); printf("\n"); } int main(void) { char cmd[1000]; char *data = NULL; data = getenv("QUERY_STRING"); char *pstr; char buf[80], file[80], modeltest[80]; char trainfile[200]; // Default options char serverconf[200] = "./server.conf"; char path_to_data[400] = "Data/"; char path_to_models[400] = "Models/"; int rc; enum {DELETEDATA,DELETEMODELS} action; char actionstr[20]; FILE *fc = fopen(serverconf, "r"); if (fc != NULL) { fscanf(fc,"%s",path_to_data); fscanf(fc,"%s",path_to_models); fclose(fc); } HTMLheader(); if(data != NULL) { // Which action? pstr = strstr(data, "action="); sscanf(pstr,"action=%[^&]",actionstr); if( strcmp(actionstr, "deletedata") == 0) action = DELETEDATA; else if ( strcmp(actionstr, "deletemodels") == 0) action = DELETEMODELS; // Get file names pstr = data; while( pstr < data+strlen(data) - strlen("action=") - strlen(actionstr) ) { sscanf(pstr,"%[^=&]",file); switch (action) { case DELETEDATA: sprintf(cmd,"../%s%s",path_to_data,file); break; case DELETEMODELS: sprintf(cmd,"../%s%s",path_to_models,file); break; default: break; } rc = remove(cmd); if(rc) printf("Cannot remove file %s
\n",cmd+3); // +3 not to print '../' else printf("Removed %s
\n",cmd+3); pstr += strlen(file) + strlen("=on&"); } } printf("

Back to MSVMpack server homepage\n"); printf("or the admin page

\n"); HTMLfooter(); } MSVMpack1.2/src/web/Server.c0000644000175000017500000001111711706244543014707 0ustar lauerlauer#include #include #include void HTMLheader(void) { printf("Content-Type: text/html;charset=UTF-8\n\n"); printf("\n"); printf("\n"); // printf("\n\n"); printf("\n"); printf("MSVMpack\n"); printf("\n"); printf("\n"); printf("

MSVMpack Server

"); } int main(void) { char cmd[2000], cmdline[2000]; char *data = NULL; data = getenv("QUERY_STRING"); char *pstr, *save_ptr, *token; char buf[250], file[80]; char trainfile[400]; char freeargs[200]; char outfile[405] = " > training.out &"; double C = 10.0; int kernel = 1; double kernelpar=1.0; char msvm[8]; int nprocs,cachemem; char modelfile[400]; char serverconf[200] = "admin/server.conf"; char path_to_data[400] = "Data/"; char path_to_models[400] = "Models/"; FILE *fp; int alreadytraining = 0; FILE *fc = fopen(serverconf, "r"); if (fc != NULL) { fscanf(fc,"%s",path_to_data); fscanf(fc,"%s",path_to_models); fclose(fc); } strcpy(cmd, "./trainmsvm "); if(data != NULL) { pstr = strstr(data, "trainfile="); if(pstr != NULL) { sscanf(pstr,"trainfile=%[^&]",file); sprintf(trainfile," %s%s",path_to_data,file); strcat(cmd, trainfile); } else { printf("error no train file\n"); exit(0); } pstr = strstr(data, "model="); if(pstr != NULL) { sscanf(pstr,"model=%[^&]",modelfile); sprintf(buf," %s%s.model",path_to_models,modelfile); strcat(cmd, buf); } pstr = strstr(data, "msvm="); if(pstr != NULL) { sscanf(pstr,"msvm=%[^&]",msvm); sprintf(buf," -m %s",msvm); strcat(cmd, buf); } pstr = strstr(data, "Clist="); if(pstr != NULL) { // Parse list of C values pstr += strlen("Clist="); sprintf(buf, " -C "); do{ token=strtok_r(pstr, "+&", &save_ptr); if(token != NULL && *token != '\0' && ( (*token >= '0' && *token <= '9') || *token == '.')) { //sscanf(token,"%lf",&C ); strcat(buf, token); strcat(buf, " "); } pstr = NULL; } while(token != NULL && ( (*token >= '0' && *token <= '9') || *token == '.')); strcat(cmd, buf); } else { pstr = strstr(data, "C="); if(pstr != NULL) { sscanf(pstr,"C=%lf",&C); sprintf(buf," -c %lf",C); strcat(cmd, buf); } } pstr = strstr(data, "kernel="); if(pstr != NULL) { sscanf(pstr,"kernel=%d",&kernel); sprintf(buf," -k %d",kernel); strcat(cmd, buf); } if(kernel != 1) { pstr = strstr(data, "kernelpar="); if(pstr != NULL) { sscanf(pstr,"kernelpar=%lf",&kernelpar); sprintf(buf," -p %lf",kernelpar); strcat(cmd, buf); } } pstr = strstr(data, "normalization=on"); if(pstr != NULL) sprintf(buf," -n"); else sprintf(buf," -u"); strcat(cmd, buf); pstr = strstr(data, "cachemem="); if(pstr != NULL) { sscanf(pstr,"cachemem=%d",&cachemem); sprintf(buf," -x %d",cachemem); strcat(cmd, buf); } pstr = strstr(data, "nprocs="); if(pstr != NULL) { sscanf(pstr,"nprocs=%d",&nprocs); sprintf(buf," -t %d",nprocs); strcat(cmd, buf); } pstr = strstr(data, "freeargs="); if(pstr != NULL) { freeargs[0] = '\0'; sscanf(pstr,"freeargs=%[^&]", freeargs); pstr = freeargs; sprintf(buf," "); do{ token=strtok_r(pstr, "+&", &save_ptr); if(token != NULL && *token != '\0') { strcat(buf, token); strcat(buf, " "); } pstr = NULL; } while(token != NULL); strcat(cmd, buf); } } // Check if another training is going on with the same model name sprintf(outfile, "%s.model.training",modelfile); if( (fp = fopen (outfile, "r") ) != NULL) { alreadytraining = 1; fclose(fp); } else { // start training strcpy(cmdline,cmd); sprintf(outfile, " > %s.model.training &",modelfile); strcat(cmd, outfile); system(cmd); } // HTML output HTMLheader(); if(alreadytraining) { printf("%s.model cannot be trained:
a model with the same name is currently being trained.
\n", modelfile); printf("Go back to homepage.\n",file); } else { printf("Training started.
\n"); printf("WATCH",file,modelfile,path_to_models); printf(" or CANCEL",file,modelfile,path_to_models); printf("
\n"); printf("MSVMpack Command-line:\n 
 %s
\n",cmdline); } printf("\n"); } MSVMpack1.2/src/web/admin.c~0000644000175000017500000001404311706034641014724 0ustar lauerlauer#include #include #include #include #ifndef _SC_NPROCESSORS_ONLN #include // for BSD #endif /* Return the number of available processors */ int get_nprocessors(void) { int nprocs; #ifdef _SC_NPROCESSORS_ONLN // Linux nprocs = (int)sysconf(_SC_NPROCESSORS_ONLN); #else // BSD int mib[4]; size_t len = sizeof(nprocs); mib[0] = CTL_HW; #ifdef HW_AVAILCPU mib[1] = HW_AVAILCPU; #else mib[1] = HW_NCPU; #endif sysctl(mib, 2, &nprocs, &len, NULL, 0); #endif // Make sure nprocs >= 1 if( nprocs < 1 ) nprocs = 1; return nprocs; } void HTMLheader(void) { printf("Content-Type: text/html;charset=UTF-8\n\n"); printf("\n"); printf("\n"); printf("\n"); printf("MSVMpack Server\n"); printf("\n"); printf("\n"); printf("

MSVMpack Server

\n"); } void HTMLfooter(void) { printf("
\n"); printf("
\n"); printf("MSVMpack Server version %1.1f\n",VERSION); printf("
\n"); printf("\n"); } int main(void) { char cmd[1000]; char *data = NULL; data = getenv("QUERY_STRING"); char *pstr; char buf[80], file[80], modeltest[80]; char trainfile[200]; // Default options char serverconf[200] = "./server.conf"; char path_to_data[400] = "Data/"; char path_to_models[400] = "Models/"; int cachemem = 1024; double C = 10.0; int kernel = 1; FILE *fp; int maxnprocs = get_nprocessors(); int nprocs = maxnprocs; int i; int printinfo = 0; int config = 0; // Table variables int ncols = 4; int col = 0; FILE *fc = fopen(serverconf, "r"); if (fc == NULL) { // Conf file does not exist yet config = 1; /* fp = popen("cd ../Data; pwd","r"); fscanf(fp,"%s",path_to_data); pclose(fp); fp = popen("cd ../Models; pwd","r"); fscanf(fp,"%s",path_to_models); pclose(fp); */ } HTMLheader(); if( !config) { // Menu links printf("HOME"); } printf("
\n"); if (!config) { fscanf(fc,"%s",path_to_data); fscanf(fc,"%s",path_to_models); fscanf(fc,"%d",&cachemem); fscanf(fc,"%d",&nprocs); fclose(fc); // FORM printf("

Files

\n"); // Training file printf("\n

Data

\n"); printf("
\n"); printf(""); // Table sprintf(cmd,"ls -c -1 ../%s",path_to_data); fp = popen(cmd,"r"); i = 0; while(fgets(buf,80,fp) != NULL) { strncpy(file,buf,strlen(buf)-1); file[strlen(buf)-1] = '\0'; if(col < ncols) { printf("\n"); if (col >= ncols) printf("\n"); i++; } pclose(fp); if(col < ncols) printf(""); printf("
\n"); col++; } else { printf("
"); col = 1; } printf(" %s\n",i,file,path_to_data,file,file); printf("
\n"); printf("

Action: \n"); printf("

\n"); // --- Models printf("

Models

\n"); printf("
\n"); printf(""); // Table sprintf(cmd,"ls -c -1 ../%s",path_to_models); fp = popen(cmd,"r"); i=0; while(fgets(buf,80,fp) != NULL) { strncpy(file,buf,strlen(buf)-1); file[strlen(buf)-1] = '\0'; if(col < ncols) { printf("\n"); if (col >= ncols) printf("\n"); i++; } pclose(fp); if(col < ncols) printf(""); printf("
\n"); col++; } else { printf("
"); col = 1; } printf(" %s\n",i,file,path_to_models,file,file); printf("
\n"); printf("

Action: \n"); printf("

\n"); } // --- Settings printf("

Settings

\n"); printf("
\n"); // Paths printf("

File paths

\n"); // printf("

Path to data repository: ",path_to_data); printf("

Path to data repository:

\n",path_to_data); printf("

Path to model files:

",path_to_models); printf("

Ressources

\n"); // cache memory printf("

Default memory for kernel cache: MB

\n",cachemem); // nprocs printf("

Max. number of processors:

\n"); if(!config) printf("\n"); else printf("\n"); // FORM printf("
\n"); printf("

Administrator password

\n"); printf("

Password: \n"); printf("

\n"); HTMLfooter(); } MSVMpack1.2/src/web/msvmserver.c~0000644000175000017500000001534411706000026016040 0ustar lauerlauer#include #include #include #include #include #include #include #include #include #include #ifndef NI_MAXHOST #define NI_MAXHOST 1025 #endif #ifndef DIR #define DIR "./" #endif void printaddr(int port) { struct ifaddrs *ifaddr, *ifa; int family, s; char host[NI_MAXHOST]; char host_numeric[NI_MAXHOST]; if (getifaddrs(&ifaddr) == -1) { perror("getifaddrs"); exit(EXIT_FAILURE); } printf("MSVMpack Server is now available at \n\n"); /* Walk through linked list, maintaining head pointer so we can free list later */ for (ifa = ifaddr; ifa != NULL; ifa = ifa->ifa_next) { family = ifa->ifa_addr->sa_family; if (family == AF_INET) { s = getnameinfo(ifa->ifa_addr, sizeof(struct sockaddr_in),host, NI_MAXHOST, NULL, 0, 0); if (s != 0) { printf("getnameinfo() failed: %s\n", gai_strerror(s)); exit(EXIT_FAILURE); } if (port != 80) printf(" http://%s:%d/", host,port); else printf(" http://%s/", host,port); if(host[0] < '0' || host[0] > '9') { s = getnameinfo(ifa->ifa_addr, sizeof(struct sockaddr_in),host_numeric, NI_MAXHOST, NULL, 0, NI_NUMERICHOST); if (port != 80) printf("\n\t ( http://%s:%d/ )", host_numeric,port); else printf("\n\t ( http://%s/ )", host_numeric,port); } printf("\n"); } } printf("\n"); freeifaddrs(ifaddr); return; } void printusage(void) { printf("Usage:\n"); printf("\t msvmserver start [port]\n"); printf("\t msvmserver restart [port]\n"); printf("\t msvmserver stop\n"); printf("\t msvmserver status\n\n"); printf(" By default msvmserver will use port 8080.\n\n"); return; } void start(int port, char *argv[]) { FILE *fp; char pidfile[400]; char cmd[200]; char homedir[400]; char mongoose[600]; int pid; uid_t userID = getuid(); sprintf(pidfile,"%s/msvmserver.pid",DIR); sprintf(homedir,"%s/webpages",DIR); sprintf(mongoose,"%s/mongoose/mongoose",DIR); sprintf(cmd, "%d",port); if(port < 1024) { if(userID != 0 ) { printf("You need to be root to use port %d.\n" , port); printf("Try 'sudo %s start %d' to get the permission to do that.\n",argv[0],port); exit(0); } } printf("Listening on port %d...\n",port); daemon(1,1); pid = getpid(); fp = fopen(pidfile,"w"); if( fp == NULL) { printf("Error: cannot write PID file.\n"); exit(1); } fprintf(fp,"%d\n",pid); fclose(fp); printaddr(port); execlp(mongoose,mongoose,"-p",cmd,"-r",homedir,(char *)NULL); } /* Check if PID in pidfile is correct Returns 0 : PID in pidfile is OK 1 : no pidfile 2 : no process with this PID 3 : no permission on the process with this PID */ int checkpid(char *pidfile, int *pid) { int check; FILE *fp = fopen(pidfile, "r"); if( fp == NULL) { check = 1; // No PID file } else { fscanf(fp,"%d",pid); fclose(fp); if( kill(*pid, 0) != 0) { if(errno == ESRCH) { /* Wrong PID file, probably due to a server stop unhandled by msvmserver */ check = 2; remove(pidfile); } else { check = 3; } } else { check = 0; // PID OK (is a running process) } } return check; } int main(int argc, char *argv[]) { int port = 8080; int pid; char pidfile[400]; int pidcheck; FILE *fp; if(argc < 2) { printusage(); exit(0); } sprintf(pidfile,"%s/msvmserver.pid",DIR); if(strcmp(argv[1],"start") == 0) { pidcheck = checkpid(pidfile, &pid); switch(pidcheck) { case 0: printf("MSVMpack Server is already running.\n"); break; case 1: printf("Starting MSVMpack Server...\n"); break; case 2: printf("Starting MSVMpack Server...\n"); break; case 3: printf("MSVMpack Server is already running (started by another user).\n"); printf("Try 'sudo %s stop' to stop this instance before starting a new one.\n",argv[0]); exit(0); break; default: break; } if (argc < 3) { printf("Will use port 8080 (use 'msvmserver start n' to use port n)\n"); } else { port = atoi(argv[2]); } start(port,argv); } else if (strcmp(argv[1],"stop") == 0) { pidcheck = checkpid(pidfile, &pid); switch(pidcheck) { case 0: printf("MSVMpack Server is going to stop...\n"); kill(pid, SIGTERM); // Kill the process if it did not terminate sleep(1); if( kill(pid, 0) == 0) { kill(pid, SIGKILL); } remove(pidfile); break; case 1: printf("MSVMpack Server is not running.\n"); break; case 2: printf("MSVMpack Server is not running.\n"); break; case 3: printf("Cannot stop the MSVMpack Server started by another user.\n"); printf("Try 'sudo %s stop' to get the permission to do that.\n",argv[0]); break; default: break; } } else if (strcmp(argv[1],"status") == 0) { pidcheck = checkpid(pidfile, &pid); switch(pidcheck) { case 0: printf("MSVMpack Server is running (pid %d).\n",pid); break; case 1: printf("MSVMpack Server is stopped.\n"); break; case 2: printf("MSVMpack Server is stopped (probably killed by another program).\n"); break; case 3: printf("MSVMpack Server is running (started by another user).\n"); printf("Try 'sudo %s {stop|restart}' to take control.\n",argv[0]); break; default: break; } } else if (strcmp(argv[1],"restart") == 0) { pidcheck = checkpid(pidfile, &pid); switch(pidcheck) { case 0: printf("MSVMpack Server is going to restart...\n"); kill(pid, SIGTERM); remove(pidfile); break; case 1: printf("MSVMpack Server was not running, starting now.\n"); break; case 2: printf("MSVMpack Server was not running, starting now.\n"); break; case 3: printf("Cannot stop the MSVMpack Server started by another user.\n"); printf("Try 'sudo %s restart' to get the permission to do that.\n",argv[0]); exit(0); break; default: break; } if (argc < 3) { printf("Will use port 8080 (use 'msvmserver [re]start n' to use port n)\n"); } else { port = atoi(argv[2]); } start(port,argv); } else { printf("Unknown command '%s'.\n\n",argv[1]); printusage(); } return 0; } MSVMpack1.2/src/web/upload_raw.c0000644000175000017500000000425711703751624015605 0ustar lauerlauer #include #include void HTMLheader(void) { printf("Content-Type: text/html;charset=UTF-8\n\n"); printf("\n"); printf("\n"); printf("\n"); printf("MSVMpack\n"); printf("\n"); printf("\n"); printf("

MSVMpack Server

"); } int main(char ** argv, int argc) { FILE * fp, *fc; char tmp[1024]; char buf[10]; char filename[80]; char fullfilename[500]; char path_to_data[400] = "Data/"; char path_to_models[400] = "Models/"; int notdone = 1; char *rc; int rcf; char *pstr = NULL; HTMLheader(); // Load server configuration fc = fopen("admin/server.conf","r"); if(fc != NULL) { rcf = fscanf(fc,"%s",path_to_data); rcf = fscanf(fc,"%s",path_to_models); fclose(fc); } fgets(tmp,1024,stdin); while((pstr = strstr(tmp,"filename=")) == NULL) { fgets(tmp,1024,stdin); // printf("%s
\n",tmp); } sscanf(pstr,"filename=\"%[^\"]",filename); sprintf(fullfilename,"%s%s",path_to_data,filename); printf("Upload data file: %s.
\n",filename); printf("Back to Homepage"); printf("
\n"); fp = fopen(fullfilename, "w" ); fgets(tmp,1024,stdin); while((pstr = strstr(tmp,"application/octet-stream")) == NULL) { // printf("%s
\n",tmp); fgets(tmp,1024,stdin); } fgets(tmp,1024,stdin); while(notdone) { rc = fgets(tmp,1024,stdin); if(rc != NULL) strncpy(buf,tmp,6); if(rc == NULL || (strncmp(buf,"------",6) == 0)) { notdone = 0; } else { //printf("%s
", tmp); BREAKS for large files fprintf(fp,"%s",tmp); } } fclose(fp); printf("

File upload done.

\n" ); // Call converter char cmd[2000]; sprintf(cmd, "./convert %s %s%s `cat %s | wc -l` 5",fullfilename,path_to_data,"convert.tmp",fullfilename); system(cmd); if((fp = fopen("convert.tmp","r") ) == NULL) { printf("Error while converting to MSVMpack format. Please check the original file format.
\n"); } else { fclose(fp); rename("convert.tmp",fullfilename); printf("

File converted from RAW to MSVMpack format.

\n" ); } printf("\n"); return 0; } MSVMpack1.2/src/web/admin.c0000644000175000017500000001404511706040410014517 0ustar lauerlauer#include #include #include #include #ifndef _SC_NPROCESSORS_ONLN #include // for BSD #endif /* Return the number of available processors */ int get_nprocessors(void) { int nprocs; #ifdef _SC_NPROCESSORS_ONLN // Linux nprocs = (int)sysconf(_SC_NPROCESSORS_ONLN); #else // BSD int mib[4]; size_t len = sizeof(nprocs); mib[0] = CTL_HW; #ifdef HW_AVAILCPU mib[1] = HW_AVAILCPU; #else mib[1] = HW_NCPU; #endif sysctl(mib, 2, &nprocs, &len, NULL, 0); #endif // Make sure nprocs >= 1 if( nprocs < 1 ) nprocs = 1; return nprocs; } void HTMLheader(void) { printf("Content-Type: text/html;charset=UTF-8\n\n"); printf("\n"); printf("\n"); printf("\n"); printf("MSVMpack Server\n"); printf("\n"); printf("\n"); printf("

MSVMpack Server

\n"); } void HTMLfooter(void) { printf("
\n"); printf("
\n"); printf("MSVMpack Server version %1.1f\n",VERSION); printf("
\n"); printf("\n"); } int main(void) { char cmd[1000]; char *data = NULL; data = getenv("QUERY_STRING"); char *pstr; char buf[80], file[80], modeltest[80]; char trainfile[200]; // Default options char serverconf[200] = "./server.conf"; char path_to_data[400] = "Data/"; char path_to_models[400] = "Models/"; int cachemem = 1024; double C = 10.0; int kernel = 1; FILE *fp; int maxnprocs = get_nprocessors(); int nprocs = maxnprocs; int i; int printinfo = 0; int config = 0; // Table variables int ncols = 4; int col = 0; FILE *fc = fopen(serverconf, "r"); if (fc == NULL) { // Conf file does not exist yet config = 1; /* fp = popen("cd ../Data; pwd","r"); fscanf(fp,"%s",path_to_data); pclose(fp); fp = popen("cd ../Models; pwd","r"); fscanf(fp,"%s",path_to_models); pclose(fp); */ } HTMLheader(); if( !config) { // Menu links printf("HOME"); } printf("
\n"); if (!config) { fscanf(fc,"%s",path_to_data); fscanf(fc,"%s",path_to_models); fscanf(fc,"%d",&cachemem); fscanf(fc,"%d",&nprocs); fclose(fc); // FORM printf("

Files

\n"); // Training file printf("\n

Data

\n"); printf("
\n"); printf(""); // Table sprintf(cmd,"ls -c -1 ../%s",path_to_data); fp = popen(cmd,"r"); i = 0; while(fgets(buf,80,fp) != NULL) { strncpy(file,buf,strlen(buf)-1); file[strlen(buf)-1] = '\0'; if(col < ncols) { printf("\n"); if (col >= ncols) printf("\n"); i++; } pclose(fp); if(col < ncols) printf(""); printf("
\n"); col++; } else { printf("
"); col = 1; } printf(" %s\n",i,file,path_to_data,file,file); printf("
\n"); printf("

Action: \n"); printf("

\n"); // --- Models printf("

Models

\n"); printf("
\n"); printf(""); // Table sprintf(cmd,"ls -c -1 ../%s",path_to_models); fp = popen(cmd,"r"); i=0; while(fgets(buf,80,fp) != NULL) { strncpy(file,buf,strlen(buf)-1); file[strlen(buf)-1] = '\0'; if(col < ncols) { printf("\n"); if (col >= ncols) printf("\n"); i++; } pclose(fp); if(col < ncols) printf(""); printf("
\n"); col++; } else { printf("
"); col = 1; } printf(" %s\n",i,file,path_to_models,file,file); printf("
\n"); printf("

Action: \n"); printf("

\n"); } // --- Settings printf("

Settings

\n"); printf("
\n"); // Paths printf("

File paths

\n"); // printf("

Path to data repository: ",path_to_data); printf("

Path to data repository:

\n",path_to_data); printf("

Path to model files:

",path_to_models); printf("

Ressources

\n"); // cache memory printf("

Default memory for kernel cache: MB

\n",cachemem); // nprocs printf("

Max. number of processors:

\n"); if(!config) printf("\n"); else printf("\n"); // FORM printf("
\n"); printf("

Administrator password

\n"); printf("

Password: \n"); printf("

\n"); HTMLfooter(); } MSVMpack1.2/src/web/home.c0000644000175000017500000002657611723361263014406 0ustar lauerlauer#include #include #include #include #ifndef _SC_NPROCESSORS_ONLN #include // for BSD #endif /* Return the number of available processors */ int get_nprocessors(void) { int nprocs; #ifdef _SC_NPROCESSORS_ONLN // Linux nprocs = (int)sysconf(_SC_NPROCESSORS_ONLN); #else // BSD int mib[4]; size_t len = sizeof(nprocs); mib[0] = CTL_HW; #ifdef HW_AVAILCPU mib[1] = HW_AVAILCPU; #else mib[1] = HW_NCPU; #endif sysctl(mib, 2, &nprocs, &len, NULL, 0); #endif // Make sure nprocs >= 1 if( nprocs < 1 ) nprocs = 1; return nprocs; } void HTMLheader(void) { printf("Content-Type: text/html;charset=UTF-8\n\n"); printf("\n"); printf("\n"); printf("\n"); printf("\n"); printf("MSVMpack Server\n"); printf("\n"); printf("\n"); printf("

MSVMpack Server

\n"); } void HTMLfooter(void) { printf("
\n"); printf("
\n"); printf("MSVMpack Server version 1.2\n"); printf("
\n"); printf("\n"); } int main(void) { char cmd[1000]; char *data = NULL; data = getenv("QUERY_STRING"); char *pstr; char buf[80], file[80], modeltest[80]; char trainfile[200]; double C = 10.0; int kernel = 1; FILE *fp, *fc; int nprocs = get_nprocessors(); int cachemem = 1024; int i; int printinfo = 0; int printdatainfo = 0; long nb_data = 0; long dim = 0; char serverconf[200] = "admin/server.conf"; char path_to_data[400] = "Data/"; char path_to_models[400] = "Models/"; int rc; HTMLheader(); // Load server configuration fc = fopen("admin/server.conf","r"); if(fc == NULL) { printf("Please go to the admin page to setup the server before the first use.
\n"); HTMLfooter(); exit(0); } else { rc = fscanf(fc,"%s",path_to_data); rc = fscanf(fc,"%s",path_to_models); rc = fscanf(fc,"%d",&cachemem); rc = fscanf(fc,"%d",&nprocs); fclose(fc); } // Menu links printf("DATA"); printf(" -- TRAIN"); printf(" -- TEST"); printf(" -- ADMIN"); printf(" -- HELP"); printf("
\n"); // UPLOAD printf("
"); printf("\n

Upload data files

\n"); printf(""); printf("",path_to_data); printf("
\n"); printf("This data file is in the\n"); printf(""); printf(""); printf(""); // FORM TRAIN printf("

Train a model

\n"); printf("
\n"); // ========== Training file ========== // Get info on selected file if(data != NULL) { pstr = strstr(data, "trainfile="); if(pstr != NULL) { sscanf(pstr,"trainfile=%[^&]",trainfile); sprintf(file,"%s%s",path_to_data,trainfile); fp=fopen(file, "r"); if(fp != NULL) { rc = fscanf(fp, "%ld", &nb_data); rc = fscanf(fp, "%ld", &dim); fclose(fp); printdatainfo = 1; } } } if(printdatainfo = 1 && dim != 0) { printf("\n",dim); } printf("\n

Choose a training data file

From the uploaded file list: \n"); pclose(fp); if(printdatainfo) printf("#instances = %ld, #features = %ld\n",nb_data,dim); printf("

Data format:

\n"); // Table printf("\n"); // --- Algo printf("\n\n"); // --- Resources printf("

Algorithm

\n"); // MSVM printf("

M-SVM type:

\n"); // Kernel printf("

Kernel:

\n"); printf("

Kernel parameter value:

\n"); // C printf("

Regularization constant C:
\n"); printf("

\n"); // Normalization printf("

\n"); printf("

Resources

\n"); // cache memory printf("

Memory for kernel cache:
MB

\n", cachemem); // nprocs printf("

Number of processors:

\n"); printf("

Additional parameters

\n"); printf("\n"); printf("
\n"); // Model printf("

Choose a model name

\n"); printf("

Save model in: .model

\n"); // End printf("

\n"); // FORM TEST printf("
\n"); printf("

Predict class labels / Test a model

\n"); // Model if(data != NULL) { pstr = strstr(data, "modeltest="); if(pstr != NULL) { sscanf(pstr,"modeltest=%[^&]",modeltest); printinfo = 1; } } printf("\n

Choose a model

From the list: \n"); pclose(fp); printf(" \n",path_to_models); if(printinfo) { printf("
\n");
		fflush(stdout);
		sprintf(cmd,"cd %s;../predmsvm -i %s;cd ..",path_to_models,modeltest);
		rc = system(cmd);
		printf("
\n"); } // Test data file printf("\n

Choose a test data file

From the list: \n"); pclose(fp); printf(" \n",path_to_data); printf("

\n"); HTMLfooter(); } MSVMpack1.2/src/web/convert.c0000664000175000017500000002620411703751702015123 0ustar lauerlauer#include #include #include /* Convert a data file in the Crammer&Singer format to MSVMpack format */ long convert_data_CrammerSinger(char *data_file, char *output, long nb_data) { FILE *fs, *fp; long i,j,dim_input; double value_y,value_X; char buf[10000]; long nr = 0; char *token; char *pbuf, *save_ptr; if((fs=fopen(data_file, "r"))==NULL) { printf("\nFile of data %s cannot be open.\n", data_file); exit(0); } // Get first line... if(fgets(buf, 10000, fs) == NULL) { printf("Error while reading data file.\n"); exit(1); } // ... to set dim_input dim_input = -1; pbuf = buf; do{ token=strtok_r(pbuf, " ", &save_ptr); if(token != NULL && *token != '\0' && *token != '\n' && *token != '\r') { dim_input++; printf("diminput = %ld ; token = %s\n",dim_input,token); } pbuf = NULL; } while(token != NULL); printf("diminput = %ld\n",dim_input); // Prepare files rewind(fs); // for input // and output if((fp=fopen(output, "w"))==NULL) { printf("\n Output file %s cannot be open.\n", output); exit(0); } fprintf(fp,"%ld\n",nb_data); fprintf(fp,"%ld\n",dim_input); // Read data for(i=1; i<=nb_data; i++) { nr += fscanf(fs, "%lf", &value_y); for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%lf", &value_X); fprintf(fp,"%lf ",value_X); } // write label fprintf(fp,"%ld\n",(long)value_y); } fclose(fs); fclose(fp); return; } /* Convert MSVMpack data set to CS data file */ long convert_data_to_CrammerSinger(char *input_file, char *data_file) { FILE *fs, *fp; long i,j; long dim_input; long nb_data; double value_y,value_X; char buf[10000]; long nr = 0; if((fs=fopen(input_file, "r"))==NULL) { printf("\nFile of data %s cannot be open.\n", input_file); exit(0); } if((fp=fopen(data_file, "w"))==NULL) { printf("\nFile of data %s cannot be open.\n", data_file); exit(0); } nr += fscanf(fs, "%ld", &nb_data); nr += fscanf(fs, "%ld", &dim_input); double *X = (double*)malloc(sizeof(double) * (dim_input+1)); // Read first line with data for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%lf", &value_X); X[j] = value_X; } // Check if there is a label at the end of the line if(fgets(buf, 10000, fs) == NULL) { printf("Error while reading data file.\n"); exit(1); } if(sscanf(buf, "%lf", &value_y) > 0) { fprintf(fp, "%ld ",(long) value_y -1 ); for(j=1; j<=dim_input; j++) fprintf(fp,"%1.8lf ",X[j]); } else { printf("Conversion in CS format cannot work without labels in data file.\n"); exit(0); } fprintf(fp,"\n"); // Read the rest of the file for(i=2; i<=nb_data; i++) { for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%lf", &value_X); X[j] = value_X; } nr += fscanf(fs, "%lf", &value_y); fprintf(fp, "%ld ",(long)value_y - 1);// Labels must be in the range [0,Q-1] for(j=1; j<=dim_input; j++) { fprintf(fp,"%1.8lf ",X[j]); } fprintf(fp,"\n"); } fclose(fp); fclose(fs); if(nr < dim_input * nb_data) printf("\nError in reading file %s, not enough data.\n", data_file); free(X); return; } /* Convert MSVMpack data set to Libsvm data file */ long convert_data_to_libsvm(char *input_file, char *data_file) { FILE *fs, *fp; long i,j; long dim_input; long nb_data; double value_y=0,value_X; char buf[10000]; long nr = 0; if((fs=fopen(input_file, "r"))==NULL) { printf("\nFile of data %s cannot be open.\n", input_file); exit(0); } if((fp=fopen(data_file, "w"))==NULL) { printf("\nFile of data %s cannot be open.\n", data_file); exit(0); } nr += fscanf(fs, "%ld", &nb_data); nr += fscanf(fs, "%ld", &dim_input); double *X = (double*)malloc(sizeof(double) * (dim_input+1)); // Read first line with data for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%lf", &value_X); X[j] = value_X; } // Check if there is a label at the end of the line if(fgets(buf, 10000, fs) == NULL) { printf("Error while reading data file.\n"); exit(1); } if(sscanf(buf, "%lf", &value_y) > 0) { fprintf(fp, "%ld ",(long) value_y -1 ); for(j=1; j<=dim_input; j++) fprintf(fp,"%ld:%1.8lf ",j,X[j]); } else { value_y=0; fprintf(fp, "0 "); for(j=1; j<=dim_input; j++) fprintf(fp,"%ld:%1.8lf ",j,X[j]); } fprintf(fp,"\n"); // Read the rest of the file for(i=2; i<=nb_data; i++) { for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%lf", &value_X); X[j] = value_X; } if(value_y == 0) fprintf(fp, "0 ");// dummy label else { nr += fscanf(fs, "%lf", &value_y); fprintf(fp, "%ld ",(long)value_y - 1);// Labels in the range [0,Q-1] } for(j=1; j<=dim_input; j++) { fprintf(fp,"%ld:%1.8lf ",j,X[j]); } fprintf(fp,"\n"); } fclose(fp); fclose(fs); if(nr < dim_input * nb_data) printf("\nError in reading file %s, not enough data.\n", data_file); free(X); return; } /* Convert a data file in libsvm format to MSVMpack format */ long convert_data_libsvm_int(char *data_file, char *output, long nb_data) { FILE *fs, *fp; long i,j,dim_input; int value_y,value_X; char buf[10000]; long nr = 0; char *token; char *pbuf, *save_ptr; if((fs=fopen(data_file, "r"))==NULL) { printf("\nFile of data %s cannot be open.\n", data_file); exit(0); } // Get first line... if(fgets(buf, 10000, fs) == NULL) { printf("Error while reading data file.\n"); exit(1); } // ... to set dim_input dim_input = -1; pbuf = buf; do{ token=strtok_r(pbuf, " ", &save_ptr); if(token != NULL && *token != '\0' && *token != '\n' && *token != '\r') { dim_input++; //printf("diminput = %ld ; token = %s\n",dim_input,token); } pbuf = NULL; } while(token != NULL); printf("diminput = %ld\n",dim_input); // Prepare files rewind(fs); // for input // and output if((fp=fopen(output, "w"))==NULL) { printf("\n Output file %s cannot be open.\n", output); exit(0); } fprintf(fp,"%ld\n",nb_data); fprintf(fp,"%ld\n",dim_input); // Read data for(i=1; i<=nb_data; i++) { nr += fscanf(fs, "%d", &value_y); for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%d:", &value_X); nr += fscanf(fs, "%d", &value_X); fprintf(fp,"%d ",value_X); } // write label fprintf(fp,"%d\n",value_y); } fclose(fs); fclose(fp); return; } /* Convert a data file in libsvm format to MSVMpack format */ long convert_data_libsvm(char *data_file, char *output, long nb_data) { FILE *fs, *fp; long i,j,dim_input,index; int value_y; double value_X, *Xi; char buf[10000]; char tmp[20]; long nr = 0; char *token; char *pbuf, *save_ptr; if((fs=fopen(data_file, "r"))==NULL) { printf("\nFile of data %s cannot be open.\n", data_file); exit(0); } dim_input = -1; // Set dim_input : for(i = 0; i< nb_data; i++) { // Get line if(fgets(buf, 10000, fs) == NULL) { printf("Error while reading data file.\n"); exit(1); } // Find number of features pbuf = buf; save_ptr = NULL; token=strtok_r(pbuf, " ", &save_ptr); // Skip label pbuf = NULL; do{ token=strtok_r(pbuf, " ", &save_ptr); if(token != NULL && *token != '\0' && *token != '\n' && *token != '\r') { sscanf(token,"%ld",&index ); if(index > dim_input) dim_input = index; //printf("diminput = %ld ; token = %s\n",dim_input,token); } } while(token != NULL); } rewind(fs); printf("Found %ld features... \n",dim_input); // Read data Xi = calloc(dim_input, sizeof(double)); // and write output if((fp=fopen(output, "w"))==NULL) { printf("\n Output file %s cannot be open.\n", output); exit(0); } fprintf(fp,"%ld\n",nb_data); fprintf(fp,"%ld\n",dim_input); for (i=0;i #include void HTMLheader(void) { printf("Content-Type: text/html;charset=UTF-8\n\n"); printf("\n"); printf("\n"); printf("\n"); printf("MSVMpack\n"); printf("\n"); printf("\n"); printf("

MSVMpack Server

"); } int main(char ** argv, int argc) { FILE * fp, *fc; char tmp[1024]; char buf[10]; char filename[80]; char fullfilename[500]; char path_to_data[400] = "Data/"; char path_to_models[400] = "Models/"; int notdone = 1; char *rc; int rcf; char *pstr = NULL; HTMLheader(); // Load server configuration fc = fopen("admin/server.conf","r"); if(fc != NULL) { rcf = fscanf(fc,"%s",path_to_data); rcf = fscanf(fc,"%s",path_to_models); fclose(fc); } fgets(tmp,1024,stdin); while((pstr = strstr(tmp,"filename=")) == NULL) { fgets(tmp,1024,stdin); // printf("%s
\n",tmp); } sscanf(pstr,"filename=\"%[^\"]",filename); sprintf(fullfilename,"%s%s",path_to_data,filename); printf("Upload data file: %s.
\n",filename); printf("Back to Homepage"); printf("
\n"); fp = fopen(fullfilename, "w" ); fgets(tmp,1024,stdin); while((pstr = strstr(tmp,"application/octet-stream")) == NULL) { // printf("%s
\n",tmp); fgets(tmp,1024,stdin); } fgets(tmp,1024,stdin); while(notdone) { rc = fgets(tmp,1024,stdin); if(rc != NULL) strncpy(buf,tmp,6); if(rc == NULL || (strncmp(buf,"------",6) == 0)) { notdone = 0; } else { //printf("%s
", tmp); BREAKS for large files fprintf(fp,"%s",tmp); } } fclose(fp); printf("

File upload done.

\n" ); // Call converter char cmd[2000]; sprintf(cmd, "./convert %s %s%s `cat %s | wc -l` 4",fullfilename,path_to_data,"convert.tmp",fullfilename); system(cmd); if((fp = fopen("convert.tmp","r") ) == NULL) { printf("Error while converting to MSVMpack format. Please check the original file format.
\n"); } else { fclose(fp); rename("convert.tmp",fullfilename); printf("

File converted from LibSVM to MSVMpack format.

\n" ); } printf("\n"); return 0; } MSVMpack1.2/src/web/Server.c~0000644000175000017500000001110411706244521015075 0ustar lauerlauer#include #include #include void HTMLheader(void) { printf("Content-Type: text/html;charset=UTF-8\n\n"); printf("\n"); printf("\n"); // printf("\n\n"); printf("\n"); printf("MSVMpack\n"); printf("\n"); printf("\n"); printf("

MSVMpack Server

"); } int main(void) { char cmd[2000], cmdline[2000]; char *data = NULL; data = getenv("QUERY_STRING"); char *pstr, *save_ptr, *token; char buf[250], file[80]; char trainfile[400]; char freeargs[200]; char outfile[405] = " > training.out &"; double C = 10.0; int kernel = 1; double kernelpar=1.0; char msvm[8]; int nprocs,cachemem; char modelfile[400]; char serverconf[200] = "admin/server.conf"; char path_to_data[400] = "Data/"; char path_to_models[400] = "Models/"; FILE *fp; int alreadytraining = 0; FILE *fc = fopen(serverconf, "r"); if (fc != NULL) { fscanf(fc,"%s",path_to_data); fscanf(fc,"%s",path_to_models); fclose(fc); } strcpy(cmd, "./trainmsvm "); if(data != NULL) { pstr = strstr(data, "trainfile="); if(pstr != NULL) { sscanf(pstr,"trainfile=%[^&]",file); sprintf(trainfile," %s%s",path_to_data,file); strcat(cmd, trainfile); } else { printf("error no train file\n"); exit(0); } pstr = strstr(data, "model="); if(pstr != NULL) { sscanf(pstr,"model=%[^&]",modelfile); sprintf(buf," %s%s.model",path_to_models,modelfile); strcat(cmd, buf); } pstr = strstr(data, "msvm="); if(pstr != NULL) { sscanf(pstr,"msvm=%[^&]",msvm); sprintf(buf," -m %s",msvm); strcat(cmd, buf); } pstr = strstr(data, "Clist="); if(pstr != NULL) { // Parse list of C values pstr += strlen("Clist="); sprintf(buf, " -C "); do{ token=strtok_r(pstr, "+&", &save_ptr); if(token != NULL && *token != '\0' && ( (*token >= '0' && *token <= '9') || *token == '.')) { //sscanf(token,"%lf",&C ); strcat(buf, token); strcat(buf, " "); } pstr = NULL; } while(token != NULL && ( (*token >= '0' && *token <= '9') || *token == '.')); strcat(cmd, buf); } else { pstr = strstr(data, "C="); if(pstr != NULL) { sscanf(pstr,"C=%lf",&C); sprintf(buf," -c %lf",C); strcat(cmd, buf); } } pstr = strstr(data, "kernel="); if(pstr != NULL) { sscanf(pstr,"kernel=%d",&kernel); sprintf(buf," -k %d",kernel); strcat(cmd, buf); } if(kernel != 1) { pstr = strstr(data, "kernelpar="); if(pstr != NULL) { sscanf(pstr,"kernelpar=%lf",&kernelpar); sprintf(buf," -p %lf",kernelpar); strcat(cmd, buf); } } pstr = strstr(data, "normalization=on"); if(pstr != NULL) sprintf(buf," -n"); else sprintf(buf," -u"); strcat(cmd, buf); pstr = strstr(data, "cachemem="); if(pstr != NULL) { sscanf(pstr,"cachemem=%d",&cachemem); sprintf(buf," -x %d",cachemem); strcat(cmd, buf); } pstr = strstr(data, "nprocs="); if(pstr != NULL) { sscanf(pstr,"nprocs=%d",&nprocs); sprintf(buf," -t %d",nprocs); strcat(cmd, buf); } pstr = strstr(data, "freeargs="); if(pstr != NULL) { freeargs[0] = '\0'; sscanf(pstr,"freeargs=%[^&]", freeargs); pstr = freeargs; sprintf(buf," "); do{ token=strtok_r(pstr, "+&", &save_ptr); if(token != NULL && *token != '\0') { strcat(buf, token); strcat(buf, " "); } pstr = NULL; } while(token != NULL); strcat(cmd, buf); } } // Check if another training is going on with the same model name sprintf(outfile, "%s.model.training",modelfile); if( (fp = fopen (outfile, "r") ) != NULL) { alreadytraining = 1; fclose(fp); } else { // start training strcpy(cmdline,cmd); sprintf(outfile, " > %s.model.training &",modelfile); strcat(cmd, outfile); system(cmd); } // HTML output HTMLheader(); if(alreadytraining) { printf("%s.model cannot be trained:
a model with the same name is currently being trained.
\n"); printf("Go back to homepage.\n",file); } else { printf("Training started.
\n"); printf("WATCH",file,modelfile,path_to_models); printf(" or CANCEL",file,modelfile,path_to_models); printf("
\n"); printf("MSVMpack Command-line:\n 
 %s
\n",cmdline); } printf("\n"); } MSVMpack1.2/src/web/upload.c0000644000175000017500000000336211703343601014720 0ustar lauerlauer #include #include void HTMLheader(void) { printf("Content-Type: text/html;charset=UTF-8\n\n"); printf("\n"); printf("\n"); printf("\n"); printf("MSVMpack\n"); printf("\n"); printf("\n"); printf("

MSVMpack Server

"); } int main(char ** argv, int argc) { FILE * fp, *fc; char tmp[1024]; char buf[10]; char filename[80]; char fullfilename[500]; char path_to_data[400] = "Data/"; char path_to_models[400] = "Models/"; int notdone = 1; char *rc; int rcf; char *pstr = NULL; HTMLheader(); // Load server configuration fc = fopen("admin/server.conf","r"); if(fc != NULL) { rcf = fscanf(fc,"%s",path_to_data); rcf = fscanf(fc,"%s",path_to_models); fclose(fc); } fgets(tmp,1024,stdin); while((pstr = strstr(tmp,"filename=")) == NULL) { fgets(tmp,1024,stdin); // printf("%s
\n",tmp); } sscanf(pstr,"filename=\"%[^\"]",filename); sprintf(fullfilename,"%s%s",path_to_data,filename); printf("Upload data file: %s.
\n",filename); printf("Back to Homepage"); printf("
\n"); fp = fopen(fullfilename, "w" ); fgets(tmp,1024,stdin); while((pstr = strstr(tmp,"application/octet-stream")) == NULL) { // printf("%s
\n",tmp); fgets(tmp,1024,stdin); } fgets(tmp,1024,stdin); while(notdone) { rc = fgets(tmp,1024,stdin); if(rc != NULL) strncpy(buf,tmp,6); if(rc == NULL || (strncmp(buf,"------",6) == 0)) { notdone = 0; } else { //printf("%s
", tmp); BREAKS for large files fprintf(fp,"%s",tmp); } } fclose(fp); printf("

File upload done.

\n" ); printf("\n"); return 0; } MSVMpack1.2/src/web/msvmserver.c0000644000175000017500000001535612104703316015652 0ustar lauerlauer#include #include #include #include #include #include #include #include #include #include #ifndef NI_MAXHOST #define NI_MAXHOST 1025 #endif #ifndef DIR #define DIR "./" #endif void printaddr(int port) { struct ifaddrs *ifaddr, *ifa; int family, s; char host[NI_MAXHOST]; char host_numeric[NI_MAXHOST]; if (getifaddrs(&ifaddr) == -1) { perror("getifaddrs"); exit(EXIT_FAILURE); } printf("MSVMpack Server is now available at \n\n"); /* Walk through linked list, maintaining head pointer so we can free list later */ for (ifa = ifaddr; ifa != NULL; ifa = ifa->ifa_next) { family = ifa->ifa_addr->sa_family; if (family == AF_INET) { s = getnameinfo(ifa->ifa_addr, sizeof(struct sockaddr_in),host, NI_MAXHOST, NULL, 0, 0); if (s != 0) { printf("getnameinfo() failed: %s\n", gai_strerror(s)); exit(EXIT_FAILURE); } if (port != 80) printf(" http://%s:%d/", host,port); else printf(" http://%s/", host,port); if(host[0] < '0' || host[0] > '9') { s = getnameinfo(ifa->ifa_addr, sizeof(struct sockaddr_in),host_numeric, NI_MAXHOST, NULL, 0, NI_NUMERICHOST); if (port != 80) printf("\n\t ( http://%s:%d/ )", host_numeric,port); else printf("\n\t ( http://%s/ )", host_numeric,port); } printf("\n"); } } printf("\n"); freeifaddrs(ifaddr); return; } void printusage(void) { printf("Usage:\n"); printf("\t msvmserver start [port]\n"); printf("\t msvmserver restart [port]\n"); printf("\t msvmserver stop\n"); printf("\t msvmserver status\n\n"); printf(" By default msvmserver will use port 8080.\n\n"); return; } void start(int port, char *argv[]) { FILE *fp; char pidfile[400]; char cmd[200]; char homedir[400]; char mongoose[600]; int pid; uid_t userID = getuid(); sprintf(pidfile,"%s/msvmserver.pid",DIR); sprintf(homedir,"%s/webpages",DIR); sprintf(mongoose,"%s/mongoose/mongoose",DIR); sprintf(cmd, "%d",port); if(port < 1024) { if(userID != 0 ) { printf("You need to be root to use port %d.\n" , port); printf("Try 'sudo %s start %d' to get the permission to do that.\n",argv[0],port); exit(0); } } printf("Listening on port %d...\n",port); daemon(1,1); pid = getpid(); fp = fopen(pidfile,"w"); if( fp == NULL) { printf("Error: cannot write PID file.\n"); exit(1); } fprintf(fp,"%d\n",pid); fclose(fp); printaddr(port); execlp(mongoose,mongoose,"-d","no","-p",cmd,"-r",homedir,(char *)NULL); } /* Check if PID in pidfile is correct Returns 0 : PID in pidfile is OK 1 : no pidfile 2 : no process with this PID 3 : no permission on the process with this PID */ int checkpid(char *pidfile, int *pid) { int check; FILE *fp = fopen(pidfile, "r"); if( fp == NULL) { check = 1; // No PID file } else { fscanf(fp,"%d",pid); fclose(fp); if( kill(*pid, 0) != 0) { if(errno == ESRCH) { /* Wrong PID file, probably due to a server stop unhandled by msvmserver */ check = 2; remove(pidfile); } else { check = 3; } } else { check = 0; // PID OK (is a running process) } } return check; } int main(int argc, char *argv[]) { int port = 8080; int pid; char pidfile[400]; int pidcheck; FILE *fp; if(argc < 2) { printusage(); exit(0); } sprintf(pidfile,"%s/msvmserver.pid",DIR); if(strcmp(argv[1],"start") == 0) { pidcheck = checkpid(pidfile, &pid); switch(pidcheck) { case 0: printf("MSVMpack Server is already running.\n"); break; case 1: printf("Starting MSVMpack Server...\n"); break; case 2: printf("Starting MSVMpack Server...\n"); break; case 3: printf("MSVMpack Server is already running (started by another user).\n"); printf("Try 'sudo %s stop' to stop this instance before starting a new one.\n",argv[0]); exit(0); break; default: break; } if (argc < 3) { printf("Will use port 8080 (use 'msvmserver start n' to use port n)\n"); } else { port = atoi(argv[2]); } start(port,argv); } else if (strcmp(argv[1],"stop") == 0) { pidcheck = checkpid(pidfile, &pid); switch(pidcheck) { case 0: printf("MSVMpack Server is going to stop...\n"); kill(pid, SIGTERM); // Kill the process if it did not terminate sleep(1); if( kill(pid, 0) == 0) { kill(pid, SIGKILL); } remove(pidfile); break; case 1: printf("MSVMpack Server is not running.\n"); break; case 2: printf("MSVMpack Server is not running.\n"); break; case 3: printf("Cannot stop the MSVMpack Server started by another user.\n"); printf("Try 'sudo %s stop' to get the permission to do that.\n",argv[0]); break; default: break; } } else if (strcmp(argv[1],"status") == 0) { pidcheck = checkpid(pidfile, &pid); switch(pidcheck) { case 0: printf("MSVMpack Server is running (pid %d).\n",pid); break; case 1: printf("MSVMpack Server is stopped.\n"); break; case 2: printf("MSVMpack Server is stopped (probably killed by another program).\n"); break; case 3: printf("MSVMpack Server is running (started by another user).\n"); printf("Try 'sudo %s {stop|restart}' to take control.\n",argv[0]); break; default: break; } } else if (strcmp(argv[1],"restart") == 0) { pidcheck = checkpid(pidfile, &pid); switch(pidcheck) { case 0: printf("MSVMpack Server is going to restart...\n"); kill(pid, SIGTERM); remove(pidfile); break; case 1: printf("MSVMpack Server was not running, starting now.\n"); break; case 2: printf("MSVMpack Server was not running, starting now.\n"); break; case 3: printf("Cannot stop the MSVMpack Server started by another user.\n"); printf("Try 'sudo %s restart' to get the permission to do that.\n",argv[0]); exit(0); break; default: break; } if (argc < 3) { printf("Will use port 8080 (use 'msvmserver [re]start n' to use port n)\n"); } else { port = atoi(argv[2]); } start(port,argv); } else { printf("Unknown command '%s'.\n\n",argv[1]); printusage(); } return 0; } MSVMpack1.2/src/web/home.c~0000644000175000017500000002653611723361034014574 0ustar lauerlauer#include #include #include #include #ifndef _SC_NPROCESSORS_ONLN #include // for BSD #endif /* Return the number of available processors */ int get_nprocessors(void) { int nprocs; #ifdef _SC_NPROCESSORS_ONLN // Linux nprocs = (int)sysconf(_SC_NPROCESSORS_ONLN); #else // BSD int mib[4]; size_t len = sizeof(nprocs); mib[0] = CTL_HW; #ifdef HW_AVAILCPU mib[1] = HW_AVAILCPU; #else mib[1] = HW_NCPU; #endif sysctl(mib, 2, &nprocs, &len, NULL, 0); #endif // Make sure nprocs >= 1 if( nprocs < 1 ) nprocs = 1; return nprocs; } void HTMLheader(void) { printf("Content-Type: text/html;charset=UTF-8\n\n"); printf("\n"); printf("\n"); printf("\n"); printf("\n"); printf("MSVMpack Server\n"); printf("\n"); printf("\n"); printf("

MSVMpack Server

\n"); } void HTMLfooter(void) { printf("
\n"); printf("
\n"); printf("MSVMpack Server version 1.2\n"); printf("
\n"); printf("\n"); } int main(void) { char cmd[1000]; char *data = NULL; data = getenv("QUERY_STRING"); char *pstr; char buf[80], file[80], modeltest[80]; char trainfile[200]; double C = 10.0; int kernel = 1; FILE *fp, *fc; int nprocs = get_nprocessors(); int cachemem = 1024; int i; int printinfo = 0; int printdatainfo = 0; long nb_data = 0; long dim = 0; char serverconf[200] = "admin/server.conf"; char path_to_data[400] = "Data/"; char path_to_models[400] = "Models/"; int rc; HTMLheader(); // Load server configuration fc = fopen("admin/server.conf","r"); if(fc == NULL) { printf("Please go to the admin page to setup the server before the first use.
\n"); HTMLfooter(); exit(0); } else { rc = fscanf(fc,"%s",path_to_data); rc = fscanf(fc,"%s",path_to_models); rc = fscanf(fc,"%d",&cachemem); rc = fscanf(fc,"%d",&nprocs); fclose(fc); } // Menu links printf("DATA"); printf(" -- TRAIN"); printf(" -- TEST"); printf(" -- ADMIN"); printf(" -- HELP"); printf("
\n"); // UPLOAD printf("
"); printf("\n

Upload data files

\n"); printf(""); printf("",path_to_data); printf("
\n"); printf("This data file is in the\n"); printf(""); printf(""); printf(""); // FORM TRAIN printf("

Train a model

\n"); printf("
\n"); // ========== Training file ========== // Get info on selected file if(data != NULL) { pstr = strstr(data, "trainfile="); if(pstr != NULL) { sscanf(pstr,"trainfile=%[^&]",trainfile); sprintf(file,"%s%s",path_to_data,trainfile); fp=fopen(file, "r"); if(fp != NULL) { rc = fscanf(fp, "%ld", &nb_data); rc = fscanf(fp, "%ld", &dim); fclose(fp); printdatainfo = 1; } } } if(printdatainfo = 1 && dim != 0) { printf("\n",dim); } printf("\n

Choose a training data file

From the uploaded file list: \n"); pclose(fp); if(printdatainfo) printf("#instances = %ld, #features = %ld\n",nb_data,dim); printf("

Data format:

\n"); // Table printf("\n"); // --- Algo printf("\n\n"); // --- Resources printf("

Algorithm

\n"); // MSVM printf("

M-SVM type:

\n"); // Kernel printf("

Kernel:

\n"); printf("

Kernel parameter value:

\n"); // C printf("

Regularization constant C:
\n"); printf("

\n"); // Normalization printf("

\n"); printf("

Resources

\n"); // cache memory printf("

Memory for kernel cache:
MB

\n", cachemem); // nprocs printf("

Number of processors:

\n"); printf("

Additional parameters

\n"); printf("\n"); printf("
\n"); // Model printf("

Choose a model name

\n"); printf("

Save model in: .model

\n"); // End printf("

\n"); // FORM TEST printf("
\n"); printf("

Predict class labels / Test a model

\n"); // Model if(data != NULL) { pstr = strstr(data, "modeltest="); if(pstr != NULL) { sscanf(pstr,"modeltest=%[^&]",modeltest); printinfo = 1; } } printf("\n

Choose a model

From the list: \n"); pclose(fp); printf(" \n",path_to_models); if(printinfo) { printf("
\n");
		fflush(stdout);
		sprintf(cmd,"cd %s;../predmsvm -i %s;cd ..",path_to_models,modeltest);
		rc = system(cmd);
		printf("
\n"); } // Test data file printf("\n

Choose a test data file

From the list: \n"); pclose(fp); printf(" \n",path_to_data); printf("

\n"); HTMLfooter(); } MSVMpack1.2/src/libevalMSVM_WW.c0000644000175000017500000005146411644772425015441 0ustar lauerlauer/* Copyright 2001, 2002, 2003 Yann Guermeur and Andre Elisseeff */ /* 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 2 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, write to the Free Software */ /* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA */ /*----------------------------------------------------------------------------*/ /* Name : libevalMSVM_WW.c */ /* Version : 2.0 */ /* Creation : 04/30/00 */ /* Last update : 01/20/11 */ /* Subject : Implementation of the M-SVM of Weston and Watkins */ /* Module : Evaluation functions */ /* Author : Fabien Lauer and Yann Guermeur Yann.Guermeur@loria.fr */ /*----------------------------------------------------------------------------*/ #include "libevalMSVM_WW.h" void WW_estimate_b_fast(double **gradient, const struct Cache *cache, struct Model *model) { long i,k,l; const long Q = model->Q; const long nb_data = model->nb_data; const double *C = model->C; double **delta_b_SVM = matrix(Q, Q); double *average = (double*)malloc(sizeof(double) * (Q+1)); double *min_dist = (double *)malloc(sizeof(double) * (Q+1)); long *closest_i = (long *)malloc(sizeof(long) * (Q+1)); long *closest_y_i = (long *)malloc(sizeof(long) * (Q+1)); for(k=1; k<=Q; k++) { average[k] = C[k] / 2.0;; min_dist[k] = C[k]/2.0; closest_i[k] = 0; closest_y_i[k] = 0; } // Find the alpha_ik closest to C/2 for each i and k for(i=1; i<=nb_data; i++) { for(k=1; k<=Q; k++) if(fabs(model->alpha[i][k] - average[k]) < min_dist[k]) { min_dist[k] = fabs(model->alpha[i][k] - average[k]); closest_i[k] = i; closest_y_i[k] = model->y[i]; } } /* Check the presence of margin SV for all pairs of classes for(k=1; k<=Q-1; k++) if(closest_i[k] == 0) for(l=k+1; l<=Q; l++) if(closest_y_i[l] != k) { printf("No margin SV for classes %ld/%ld\n",k,l); } */ // init b values for(k=1; k<=Q; k++) model->b_SVM[k] = 0.0; // and delta_b for(k=1; k<=Q; k++) for(l=1; l<=Q; l++) delta_b_SVM[k][l] = 0.0; // compute delta_b for(k=1; k<=Q; k++) if(closest_i[k] != 0) delta_b_SVM[closest_y_i[k]][k] = -gradient[closest_i[k]][k]; // compute _b_tilde for(k=2; k<=Q; k++) model->b_SVM[k] = (delta_b_SVM[k][1] - delta_b_SVM[1][k]) / 2.0; // compute b standardize_b(model->b_SVM,Q); if(cache->verbose) { printf("\nComponents of the b vector:\n"); printf("\n"); for(k=1; k<=Q; k++) printf("%11.6f\n", model->b_SVM[k]); } free(delta_b_SVM[1]); free(delta_b_SVM); free(average); free(min_dist); free(closest_i);free(closest_y_i); } /* Main evalutaion function for WW: compute the ratio dual/upper bound */ double MSVM_WW_eval(double *best_primal_upper_bound, double **gradient, double **H_alpha, struct Model *model, const int verbose, FILE *fp) { long i,k,check; const long Q = model->Q; const long nb_data = model->nb_data; double R_emp, ratio, max_alpha = 0; int bad_b = false; char choice='a'; // default to automatic choice struct Cache cache; cache.verbose = verbose; cache.H_alpha = H_alpha; long **mat_conf = matrix_l(Q,Q); long training_errors; long **margin_vect = matrix_l(nb_data, Q); long **nb_margin_vect = matrix_l(Q, Q); int test_NoAlphaCloseToC; WW_check_feasible_sol(model,NULL,verbose); if(verbose) WW_check_sup_vect(model); WW_check_margin_vect(margin_vect,nb_margin_vect,model); if(model->nature_kernel == 1 && verbose) { // compute the weights of the linear model WW_compute_W(model); printf("\nMatrix of the vectors defining the separating hyperplanes\n"); display_mat(model->W, model->dim_input, Q, 12, 6); Pause(""); } WW_estimate_b(gradient, margin_vect, nb_margin_vect, &cache, model); // WW_estimate_b_fast(gradient, &cache, model); R_emp = WW_eval_training(gradient,mat_conf,model); // Compute training error training_errors = model->nb_data; for(i=1;i<=Q;i++) training_errors -= mat_conf[i][i]; model->training_error = (double)training_errors/(double)model->nb_data; // Compute the ratio dual/upper bound (stopping criterion) WW_compute_obj_dual(&cache,model); WW_compute_obj_primal(R_emp,&cache,model); // Make sure the upper bound does not increase if(cache.primal > *best_primal_upper_bound) cache.primal = *best_primal_upper_bound; else *best_primal_upper_bound = cache.primal; test_NoAlphaCloseToC = 1; for(i=1; i<=nb_data; i++) for(k=1;k<=Q; k++) { if(model->alpha[i][k] > max_alpha) max_alpha = model->alpha[i][k]; if(model->alpha[i][k] > model->C[model->y[i]] * (1.0 - small)) test_NoAlphaCloseToC = 0; } if(test_NoAlphaCloseToC && (0.5 * cache.alpha_H_alpha >= cache.dual)) { check = 0; for(k=1; k<=Q; k++) check += mat_conf[k][k]; if(check == nb_data) { bad_b = true; if(cache.primal > (1.5 * 0.5 * cache.alpha_H_alpha)) printf("\nBeware, very poor estimates of the bias (primal = %lf)\n", cache.primal); cache.primal = 0.5 * cache.alpha_H_alpha; } } ratio = cache.dual / cache.primal; if(verbose) { printf("\nDifference between the primal and the dual: %lf -> %lf", cache.primal, cache.dual); printf("\n(ratio %5.2lf \%%)\n", 100.0 * ratio); printf("\n*** Training performance\n"); display_stats(Q, mat_conf); display_full_stats(Q, mat_conf); printf("Do you want vector b to be optimized "); printf("(this is not recommended for Q > 4 ) ([y]/n)? "); choice = getchar(); } if((choice == 'y') || (choice == 'Y') || (choice == 'a' && Q<=4 && ratio > 0.90)) { /* if automatic choice: do not optimize b for Q > 4 (too large dimension for the grid search) do not optimize b before reaching a ratio of 75 % */ WW_optimize_b(gradient, &cache, model); if(cache.primal > *best_primal_upper_bound) cache.primal = *best_primal_upper_bound; else *best_primal_upper_bound = cache.primal; ratio = cache.dual / cache.primal; if(verbose) { printf("\nDifference between the primal and the dual: %lf -> %lf", cache.primal, cache.dual); printf("\n(ratio %5.2lf \%%)\n", 100.0 * ratio); } if(bad_b) printf("\nWith optimal values for the biases, the primal should be: %lf\n", 0.5*cache.alpha_H_alpha); if(verbose) { printf("\n*** Training performance\n"); display_stats(Q, mat_conf); display_full_stats(Q, mat_conf); Pause(""); } // Update training error with new b R_emp = WW_eval_training(gradient,mat_conf,model); training_errors = model->nb_data; for(i=1;i<=Q;i++) training_errors -= mat_conf[i][i]; model->training_error = (double)training_errors/(double)model->nb_data; } else if(choice != 'a') choice = getchar(); if((model->nature_kernel == 1) && (model->dim_input == 2) && (Q == 3) && (max_alpha > 0.0) && verbose) WW_compute_boundaries(model); // Log info if(fp != NULL) fprintf(fp, "%lf %lf\n ",cache.dual,cache.primal); // Free memory free(mat_conf[1]); free(mat_conf); free(margin_vect[1]); free(margin_vect); free(nb_margin_vect[1]); free(nb_margin_vect); return ratio; } /* output = WW_function( k, x, model) Compute the real-valued output of the model corresponding to the k-th category on the pattern x. */ double WW_function(long category, void *vector, const struct Model *model) { const long nb_data = model->nb_data; const long Q = model->Q; const enum Kernel_type nature_kernel = model->nature_kernel; const double *kernel_par = model->kernel_par; long dim_input = model->dim_input; long i,k; double partial, result = 0.0; for(i=1; i<=nb_data; i++) { if(model->y[i] == category) { partial = 0.0; for(k=1; k<=Q; k++) partial += model->alpha[i][k]; } else partial = - model->alpha[i][category]; if(partial != 0.0) result += partial * ker(nature_kernel, model->X[i], vector, dim_input, kernel_par); } return result; } /* label = WW_classify(x, model, real_outputs) Classify x and output the label. If real_outputs is not NULL, also compute the Q real-valued outputs of the model and store them in (real_outputs[1]...real_outpust[Q]). Note: this function is faster than calling Q times WW_function */ long WW_classify(void *vector, const struct Model *model, double *real_outputs) { const long nb_data = model->nb_data; const long Q = model->Q; const enum Kernel_type nature_kernel = model->nature_kernel; const double *kernel_par = model->kernel_par; long dim_input = model->dim_input; long i,k; long label = 1; double maxoutput,partial, kernel; int isSV, use_real_outputs = true; if(real_outputs==NULL) { real_outputs = (double *)malloc(sizeof(double) * (Q+1)); use_real_outputs = false; } for(k=1;k<=Q;k++) real_outputs[k] = model->b_SVM[k]; for(i=1; i<=nb_data; i++) { partial = 0.0; isSV = false; for(k=1; k<=Q; k++) { partial += model->alpha[i][k]; if(model->alpha[i][k] != 0.0) isSV = true; } if(isSV) { kernel = ker(nature_kernel, model->X[i], vector, dim_input, kernel_par); for (k=1; k<=Q; k++) { if(model->y[i] == k) real_outputs[k] += partial * kernel; else real_outputs[k] -= model->alpha[i][k] * kernel; } } } maxoutput = real_outputs[1]; for(k=2; k<=Q; k++) if(real_outputs[k] > maxoutput) { maxoutput = real_outputs[k]; label = k; } if(!use_real_outputs) free(real_outputs); return label; } void WW_optimize_b(double **gradient, struct Cache *cache, struct Model *model) { const long Q = model->Q; long count, portion, class, Iteration, k; long max_count = 10; for(k=0;k 1000000) { printf("Too large Q, b will not be optimized.\n"); return; } double bstep = 0.1; double *grid_index = (double *) calloc(Q+1, sizeof(double)); double *b_SVM_base = (double *) calloc(Q+1, sizeof(double)); double *best_b_SVM = (double *) calloc(Q+1, sizeof(double)); double R_emp; double R_emp_min = WW_eval_training(gradient, NULL, model); for(class=1; class<=Q; class++) best_b_SVM[class] = model->b_SVM[class]; grid_index[1] = 0.0; b_SVM_base[1] = 0.0; for(Iteration=1; Iteration <=10; Iteration++) { for(k=2; k<=Q; k++) b_SVM_base[k] = model->b_SVM[k] - (5.0 * bstep); for(count=0; countb_SVM[class] = b_SVM_base[class] + (grid_index[class] * bstep); R_emp = WW_eval_training(gradient, NULL, model); if(R_emp < R_emp_min) { R_emp_min = R_emp; for(class=1; class<=Q; class++) best_b_SVM[class] = model->b_SVM[class]; } } for(class=1; class<=Q; class++) model->b_SVM[class] = best_b_SVM[class]; R_emp = WW_eval_training(gradient, NULL, model); if(R_emp < R_emp_min) { R_emp_min = R_emp; for(class=1; class<=Q; class++) best_b_SVM[class] = model->b_SVM[class]; } bstep /= 2.0; } standardize_b(model->b_SVM,Q); if(cache->verbose) { printf("\nNew components of the b vector:\n"); printf("\n"); for(class=1; class<=Q; class++) printf("%11.6f\n", model->b_SVM[class]); } WW_compute_obj_primal(R_emp,cache,model); free(grid_index); free(b_SVM_base); free(best_b_SVM); } void WW_check_feasible_sol(const struct Model *model, char *alpha_file,int verbose) { char command[taille]; const long Q = model->Q; const long nb_data = model->nb_data; const double *C = model->C; double norm; int rc; long i,k,l; double *constraints; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) if((model->alpha[i][k] < 0.0) || (model->alpha[i][k] > C[model->y[i]])) { printf("\nNo feasible solution: alpha[%ld][%ld] = %1.12lf > %lf\n\n", i, k, model->alpha[i][k], C[model->y[i]]); exit(0); } constraints = (double *)calloc(Q+1, sizeof(double)); for(k=1; k<=Q; k++) constraints[k] = 0.0; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) { if(model->y[i] == k) for(l=1; l<=Q; l++) constraints[k] -= model->alpha[i][l]; else constraints[k] += model->alpha[i][k]; } if(verbose) { printf("\nSatisfaction of the equality constraints:\n\n"); for(k=1; k<=Q; k++) printf("%11.8lf\n", constraints[k]); } norm = 0.0; for(k=1; k<=Q; k++) norm += constraints[k] * constraints[k]; norm = sqrt(norm); if(norm >= 1e-4) { printf("\nLarge deviation of the equality constraints (%lf)...\n",norm); exit(0); } if(alpha_file != NULL) { sprintf(command, "cp %s Save_alpha/.", alpha_file); rc = system(command); } free(constraints); } void WW_check_sup_vect(const struct Model *model) { long i,k,l; const long Q = model->Q; const long nb_data = model->nb_data; long **sup_vect = matrix_l(nb_data, Q); long **nb_sup_vect = matrix_l(Q, Q); for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) sup_vect[i][k] = 0; for(k=1; k<=Q; k++) for(l=1; l<=Q; l++) nb_sup_vect[k][l] = 0; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) if(model->alpha[i][k] > model->C[model->y[i]] * small_enough) { sup_vect[i][k] = 1; nb_sup_vect[model->y[i]][k]++; } printf("\nDistribution matrix of the support vectors\n"); display_mat_l(nb_sup_vect, Q, Q, 6); free(sup_vect[1]); free(sup_vect); free(nb_sup_vect[1]); free(nb_sup_vect); } void WW_check_margin_vect(long **margin_vect, long **nb_margin_vect, const struct Model *model) { long i,k,l,y_i; const long Q = model->Q; const long nb_data = model->nb_data; const double *C = model->C; int over=false; double *average = (double*)malloc(sizeof(double) * (Q+1)); double **radius = matrix(Q, Q); const double radius_step = 1000.0; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) margin_vect[i][k] = 0; for(k=1; k<=Q; k++) { average[k] = C[k] / 2.0;; for(l=1; l<=k; l++) { radius[k][l] = C[k] / radius_step; radius[l][k] = C[k] / radius_step; } } while(over == false) { for(k=1; k<=Q; k++) for(l=1; l<=Q; l++) nb_margin_vect[k][l] = 0; for(i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) if(fabs(model->alpha[i][k] - average[model->y[i]]) <= radius[y_i][k]) { margin_vect[i][k] = 1; nb_margin_vect[y_i][k]++; } } over = true; for(k=1; k<=Q-1; k++) for(l=k+1; l<=Q; l++) if((nb_margin_vect[k][l] == 0) && (nb_margin_vect[l][k] == 0)) { over = false; if((average[k] - radius[k][l]) > (average[k] / 5000.0)) radius[k][l] += average[k] / radius_step; else radius[k][l] = (radius[k][l] + average[k]) / 2.0; radius[l][k] = radius[k][l]; } } free(radius[1]); free(radius); free(average); } double WW_eval_training(double **gradient, long **mat_conf, const struct Model *model) { long i,k,l,y_i; const long Q = model->Q; const long nb_data = model->nb_data; long ind_min = 0; double mini = HUGE_VAL, delta = 0.0; double R_emp = 0.0; if(mat_conf != NULL) { for(k=1; k<=Q; k++) for(l=1; l<=Q; l++) mat_conf[k][l] = 0; } for(i=1; i<=nb_data; i++) { mini = HUGE_VAL; ind_min = 0; y_i = model->y[i]; /* Do " for(k=1; k<=Q; k++) if(k != y_i) ... " in 2 loops without if */ for(k=1;kb_SVM[y_i] - model->b_SVM[k]; if(delta < 0.0) R_emp -= model->C[y_i] * delta; if(delta < mini) { mini = delta; ind_min = k; } } for(k=y_i+1;k<=Q;k++) { delta = gradient[i][k] + model->b_SVM[y_i] - model->b_SVM[k]; if(delta < 0.0) R_emp -= model->C[y_i] * delta; if(delta < mini) { mini = delta; ind_min = k; } } if(mat_conf != NULL) { if(mini <= -1.0) mat_conf[y_i][ind_min]++; else mat_conf[y_i][y_i]++; } } return R_emp; } void WW_compute_W(struct Model *model) { const long Q = model->Q; const long nb_data = model->nb_data; const long dim_input = model->dim_input; long i,j,k,l; double partial; if(model->W == NULL) model->W = matrix(dim_input, Q); for(j=1; j<=dim_input; j++) for(k=1; k<=Q; k++) model->W[j][k] = 0.0; for(k=1; k<=Q; k++) for(i=1; i<=nb_data; i++) { if((model->y[i]) == k) { partial = 0.0; for(l=1; l<=Q; l++) partial += model->alpha[i][l]; for(j=1; j<=dim_input; j++) model->W[j][k] += partial * model_get_Xij(model,i,j); } else for(j=1; j<=dim_input; j++) model->W[j][k] -= model->alpha[i][k] * model_get_Xij(model,i,j); } } void WW_estimate_b(double **gradient, long **margin_vect, long **nb_margin_vect, const struct Cache *cache, struct Model *model) { long i,k,l; const long Q = model->Q; const long nb_data = model->nb_data; double **delta_b_SVM = matrix(Q, Q); for(k=1; k<=Q; k++) model->b_SVM[k] = 0.0; for(k=1; k<=Q; k++) for(l=1; l<=Q; l++) delta_b_SVM[k][l] = 0.0; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) if(margin_vect[i][k] == 1) delta_b_SVM[model->y[i]][k] -= gradient[i][k]; for(k=1; k<=Q; k++) for(l=1; l<=Q; l++) if(k != l) if(nb_margin_vect[k][l] != 0) delta_b_SVM[k][l] /= (double)nb_margin_vect[k][l]; for(k=2; k<=Q; k++) if(nb_margin_vect[k][1] + nb_margin_vect[1][k] > 0) { model->b_SVM[k] = (nb_margin_vect[k][1] * delta_b_SVM[k][1] - nb_margin_vect[1][k] * delta_b_SVM[1][k]) / (double)(nb_margin_vect[k][1] + nb_margin_vect[1][k]); } standardize_b(model->b_SVM,Q); if(cache->verbose) { printf("\nComponents of the b vector:\n"); printf("\n"); for(k=1; k<=Q; k++) printf("%11.6f\n", model->b_SVM[k]); } free(delta_b_SVM[1]); free(delta_b_SVM); } void WW_compute_obj_dual(struct Cache *cache, struct Model *model) { long i,k; const long Q = model->Q; const long nb_data = model->nb_data; double alpha_H_alpha = 0; double L_form_dual = 0; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) alpha_H_alpha += cache->H_alpha[i][k] * model->alpha[i][k]; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) L_form_dual += model->alpha[i][k]; model->sum_all_alpha = L_form_dual; cache->alpha_H_alpha = alpha_H_alpha; cache->dual = -0.5*alpha_H_alpha + L_form_dual; } void WW_compute_obj_primal(double R_emp, struct Cache *cache, const struct Model *model) { cache->primal = 0.5 * cache->alpha_H_alpha + R_emp; if(cache->primal < cache->dual) { printf("\nInconsistency in the values of the objective functions...\n primal = %lf + %lf = %lf < %lf (dual)\n", 0.5 * cache->alpha_H_alpha, R_emp , cache->primal, cache->dual); /* exit(0); */ } } void WW_compute_boundaries(const struct Model *model) { if(model->W == NULL) { printf("Cannot compute_boundaries(): no linear weights W in model.\n"); return; } double slope, y_at_origin; slope = (model->W[1][1] - model->W[1][2]) / (model->W[2][2] - model->W[2][1]); y_at_origin = (model->b_SVM[1] - model->b_SVM[2]) / (model->W[2][2] - model->W[2][1]); printf("\nSlope : %lf", slope); printf("\nOrdinate at the origin : %lf\n", y_at_origin); Pause(""); slope = (model->W[1][1] - model->W[1][3]) / (model->W[2][3] - model->W[2][1]); y_at_origin = (model->b_SVM[1] - model->b_SVM[3]) / (model->W[2][3] - model->W[2][1]); printf("\nSlope : %lf", slope); printf("\nOrdinate at the origin : %lf\n", y_at_origin); Pause(""); slope = (model->W[1][2] - model->W[1][3]) / (model->W[2][3] - model->W[2][2]); y_at_origin = (model->b_SVM[2] - model->b_SVM[3]) / (model->W[2][3] - model->W[2][2]); printf("\nSlope : %lf", slope); printf("\nOrdinate at the origin : %lf\n", y_at_origin); Pause(""); } MSVMpack1.2/src/predMSVM.c~0000644000175000017500000002020511705772322014515 0ustar lauerlauer/* Copyright 2010 Fabien Lauer */ /* 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 2 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, write to the Free Software */ /* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA*/ /*--------------------------------------------------------------------------*/ /* Name : predMSVM.c */ /* Version : 2.0 */ /* Creation : 04/27/10 */ /* Last update : 01/20/11 */ /* Subject : MSVMpack: a multi-class SVM package */ /* Algo. : Prediction command-line tool */ /* Author : Fabien Lauer fabien.lauer@loria.fr */ /*--------------------------------------------------------------------------*/ /* predMSVM.c -- Command line tool to classify a dataset with an M-SVM model previously trained by trainmsvm from MSVMpack */ #include #include #include #include #include "libMSVM.h" #include "libevalMSVM.h" int main(int argc, char *argv[]) { char data_file[taille], outputs_file[taille], model_file[taille]; int i,n_kernel_par,multipleC; long k; char *outputs = NULL; strcpy(model_file,"msvm.model"); int nprocs = get_nprocessors(); // Parse command line if(argc<2) { printf("MSVMpack prediction tool\n"); printf("-- Version: %1.1f (Oct. 10, 2011) \n\n", VERSION); printf("Usage: \n"); printf("\tpredmsvm data_file [MSVM.model] [pred.outputs] [-t N]\n\n"); printf("computes the output of an M-SVM on the given data_file\n"); printf("using N processors (default N = %d on this computer).\n\n",nprocs); printf(" Or:\n\tpredmsvm -i [MSVM.model] \n\n"); printf("prints model information.\n\n"); exit(0); } strcpy(data_file, argv[1]); // Data file must be the first argument // except for the -i option i = check_argv(argc,argv, ".model"); if(i) { strcpy(model_file,argv[i]); } i = check_argv(argc,argv, ".outputs"); if(i) { strcpy(outputs_file,argv[i]); outputs = outputs_file; } // Load model struct Model *model; model = MSVM_load_model(model_file); if (model == NULL) exit(1); // Check -i option and print model information if needed i = check_argv(argc,argv, "-i"); if(i) { printf("\n%s\t : ", model_file); switch(model->type) { case MSVM2 : printf("M-SVM^2 (MSVM2)\n"); break; case WW : printf("Weston and Watkins M-SVM (WW) \n"); break; case CS : printf("Crammer and Singer M-SVM (CS) \n"); break; case LLW : printf("Lee, Lin and Wahba M-SVM (LLW) \n"); break; default : printf("Unknown\n"); break; } printf(" version\t : MSVMpack %1.1f\n",model->version); printf(" training set\t : %s",model->training_set_name); if(model->normalization != NULL) printf("\t (data normalized)\n"); else printf("\n"); printf(" training error\t : %3.2lf %%\n",100 * model->training_error); enum Kernel_type kerneltype = model->nature_kernel; switch(model->datatype) { case DOUBLE: printf(" data format\t : double precision floating-point (64-bit)\n"); break; case FLOAT: printf(" data format\t : single precision floating-point (32-bit)\n"); kerneltype -= 10; break; case INT: printf(" data format\t : integer (32-bit)\n"); kerneltype -= 20; break; case SHORT: printf(" data format\t : short integer (16-bit)\n"); kerneltype -= 30; break; case BYTE: printf(" data format\t : byte (8-bit unsigned integer)\n"); kerneltype -= 40; break; case BIT: printf(" data format\t : 0-1 bit \n"); kerneltype -= 50; break; default: printf(" data format\t : unknown (%d)\n",model->datatype); } printf("\t Q\t : %ld\n",model->Q); n_kernel_par = 0; if(model->kernel_par != NULL ) n_kernel_par = (int)model->kernel_par[0]; switch(kerneltype) { case LINEAR: printf("\t kernel\t : linear\n"); break; case RBF: printf("\t kernel\t : Gaussian RBF (sigma = %lf)\n", model->kernel_par[1]); break; case POLY_H: printf("\t kernel\t : Homogeneous polynomial (degree = %d)\n", (int)model->kernel_par[1]); break; case POLY: printf("\t kernel\t : Non-homogeneous polynomial (degree = %d)\n", (int)model->kernel_par[1]); break; case CUSTOM1: if(n_kernel_par==0) printf("\t kernel\t : %s (no parameter)",CUSTOM_KERNEL_1_NAME); else if (n_kernel_par==1) printf("\t kernel\t : %s (parameter = %lf)\n", CUSTOM_KERNEL_1_NAME,model->kernel_par[1]); else if (model->kernel_par[0]<5) { printf("\t kernel\t : %s (parameters = %lf", CUSTOM_KERNEL_1_NAME,model->kernel_par[1]); for(i=2;i<=n_kernel_par;i++) printf(" %lf", model->kernel_par[i]); printf(")\n"); } else printf("\t kernel\t : %s (%d parameters)\n", CUSTOM_KERNEL_1_NAME,n_kernel_par); break; case CUSTOM2: if(n_kernel_par==0) printf("\t kernel\t : %s (no parameter)",CUSTOM_KERNEL_2_NAME); else if (n_kernel_par==1) printf("\t kernel\t : %s (parameter = %lf)\n", CUSTOM_KERNEL_2_NAME, model->kernel_par[1]); else if (model->kernel_par[0]<5) { printf("\t kernel\t : %s (parameters = %lf", CUSTOM_KERNEL_2_NAME, model->kernel_par[1]); for(i=2;i<=n_kernel_par;i++) printf(" %lf", model->kernel_par[i]); printf(")\n"); } else printf("\t kernel\t : %s (%d parameters)\n", CUSTOM_KERNEL_2_NAME,n_kernel_par); break; case CUSTOM3: if(n_kernel_par==0) printf("\t kernel\t : %s (no parameter)",CUSTOM_KERNEL_3_NAME); else if (n_kernel_par==1) printf("\t kernel\t : %s (parameter = %lf)\n", CUSTOM_KERNEL_3_NAME,model->kernel_par[1]); else if (model->kernel_par[0]<5) { printf("\t kernel\t : %s (parameters = %lf", CUSTOM_KERNEL_3_NAME,model->kernel_par[1]); for(i=2;i<=n_kernel_par;i++) printf(" %lf", model->kernel_par[i]); printf(")\n"); } else printf("\t kernel\t : %s (%d parameters)\n", CUSTOM_KERNEL_3_NAME,n_kernel_par); break; default: printf("\t kernel\t : unknown\n"); break; } multipleC = 0; for(k=2;k<=model->Q;k++) if(model->C[k] != model->C[1]) multipleC = 1; if(multipleC) { for(k=1;k<=model->Q;k++) { if(model->C[k] > 0.001) printf("\t C_%ld\t : %1.3lf\n",k,model->C[k]); else printf("\t C_%ld\t : %1.3e\n",k,model->C[k]); } } else { if(model->C[1] > 0.001) printf("\t C\t : %1.3lf\n",model->C[1]); else printf("\t C\t : %1.3e\n",model->C[1]); } printf("\t nSV\t : %ld\n",model->nb_data); exit(0); } // Load data struct Data *data_set; data_set = MSVM_make_dataset(data_file,model->datatype); if(data_set->dim != model->dim_input) { printf("Error: wrong data dimension (%ld) for model %s\n", data_set->dim, model_file); printf("\t (expected input dimension is %ld).\n",model->dim_input); exit(1); } // Set number of threads / CPUs i = check_argv(argc,argv, "-t"); if(i) { if(atoi(argv[i+1]) > nprocs) { printf("Unattended request of a number of working threads above the number of available processors (%d)\n",nprocs); } else nprocs = atoi(argv[i+1]); } // Predict MSVM_classify_set(NULL, data_set->X, data_set->y, data_set->nb_data, outputs, model, nprocs); // Free memory MSVM_delete_dataset(data_set); MSVM_delete_model_with_data(model); return 0; } MSVMpack1.2/src/libevalMSVM_2.c0000644000175000017500000006633511651467546015253 0ustar lauerlauer/* Copyright 2008-2010 Yann Guermeur */ /* 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 2 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, write to the Free Software */ /* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA*/ /*--------------------------------------------------------------------------*/ /* Name : libevalMSVM_2.c */ /* Version : 2.0 */ /* Creation : 06/20/08 */ /* Last update : 01/20/11 */ /* Subject : Implementation of the M-SVM^2 */ /* Module : Evaluation functions */ /* Author : Fabien Lauer and Yann Guermeur Yann.Guermeur@loria.fr */ /*--------------------------------------------------------------------------*/ #include "libevalMSVM_2.h" /* Main evaluation function for the M-SVM^2: compute the ratio (dual / upper bound) */ double MSVM_2_eval(double *best_primal_upper_bound, double **gradient, double **H_alpha, double **H_tilde_alpha, struct Model *model, const int verbose, FILE *fp) { long i,k; const long Q = model->Q; const long nb_data = model->nb_data; double ratio; static double best_primal_cheap_upper_bound = HUGE_VAL; struct Cache cache; cache.H_alpha = H_alpha; cache.H_tilde_alpha = H_tilde_alpha; cache.verbose = verbose; double **xi_opt = matrix(nb_data, Q); double **xi_save; static int maxiter_xi = 200; // MSVM_2_compute_gradient(gradient, &cache, model); // will use -gradient for maximization of dual MSVM_2_estimate_b(gradient, &cache, model); // here MSVM_2_compute_xi_opt(xi_opt, &cache, model); MSVM_2_check_xi_opt(xi_opt,gradient,&cache,model); // and here MSVM_2_compute_obj_dual(&cache,model); MSVM_2_compute_obj_primal(&cache,xi_opt,model); // this is not a true value of the primal // should only be used for testing purposes if(fp != NULL) fprintf(fp, "%lf %lf ",cache.dual,cache.primal); /* ---- Choose upper bound method here: */ static int upperbound = 2; // start with fast method switch(upperbound) { case 1 : // simple gradient projection over xi cache.primal = *best_primal_upper_bound; MSVM_2_correct_xi_opt(xi_opt,&cache,model,maxiter_xi); // Make sure the upper bound does not increase if(cache.primal > *best_primal_upper_bound) cache.primal = *best_primal_upper_bound; else *best_primal_upper_bound = cache.primal; if(cache.primal_cheap > best_primal_cheap_upper_bound) cache.primal_cheap = best_primal_cheap_upper_bound; else best_primal_cheap_upper_bound = cache.primal_cheap; // Write to log file if(fp != NULL) fprintf(fp, "%lf %lf ",cache.primal_cheap,cache.primal); break; case 2 : MSVM_2_minimal_xi(1,xi_opt,&cache,model); cache.primal = MSVM_2_compute_primal_obj(xi_opt, &cache, model); // Make sure the upper bound does not increase if(cache.primal > *best_primal_upper_bound) cache.primal = *best_primal_upper_bound; else *best_primal_upper_bound = cache.primal; cache.primal_cheap = cache.primal; // Write to log file if(fp != NULL) fprintf(fp, "%lf %lf ",cache.primal_cheap,cache.primal); break; case 4 : // grid search over b + optimization over xi MSVM_2_correct_xi_opt(xi_opt,&cache,model,maxiter_xi); if(fp != NULL) fprintf(fp, "%lf %lf ",cache.primal_cheap,cache.primal); MSVM_2_optimize_b(xi_opt, &cache, model); if(fp != NULL) fprintf(fp, "%lf %lf ",cache.primal_cheap,cache.primal); break; case 5 : // minimum xi /* Save the current xi_opt*/ xi_save = matrix(nb_data,Q); for(i=1;i<=nb_data;i++) for(k=1;k<=Q;k++) xi_save[i][k] = xi_opt[i][k]; MSVM_2_minimal_xi(1,xi_opt,&cache,model); cache.primal_cheap = MSVM_2_compute_primal_obj(xi_opt,&cache,model); MSVM_2_minimal_xi(0,xi_opt,&cache,model); cache.primal = MSVM_2_compute_primal_obj(xi_opt,&cache,model); /* Restore original xi_opt */ for(i=1;i<=nb_data;i++) for(k=1;k<=Q;k++) xi_opt[i][k] = xi_save[i][k]; if(fp != NULL) fprintf(fp, "%lf %lf ",cache.primal_cheap,cache.primal); MSVM_2_optimize_b(xi_opt, &cache, model); if(fp != NULL) fprintf(fp, "%lf %lf ",cache.primal_cheap,cache.primal); free(xi_save[1]);free(xi_save); break; default : //printf("Do nothing .\n"); break; } if(fp != NULL) fprintf(fp,"\n"); // Compute ratio ratio = cache.dual / cache.primal; // Comput training error long **mat_conf = matrix_l(Q,Q); long training_errors = MSVM_2_eval_training(mat_conf, &cache, model); model->training_error = (double)training_errors/(double)model->nb_data; // Switch to slower but more accurate method after 75% // (gradient projection optimization of xi) // but only for a small number of categories Q < 20 if(ratio > 0.75 && model->Q < 20) upperbound = 1; // Increase the number of iterations in the optimization of xi if(ratio > 0.90) maxiter_xi = 500; // after 90% if(ratio > 0.95) maxiter_xi = 1000; // after 95% // Free memory free(xi_opt[1]); free(xi_opt); free(mat_conf[1]);free(mat_conf); return ratio; } /* output = MSVM_2_function( k, x, model) Compute the real-valued output of model (without bias term) for the k-th category on pattern x */ double MSVM_2_function(long category, void *vector, const struct Model *model) { const long nb_data = model->nb_data; const enum Kernel_type nature_kernel = model->nature_kernel; const double *kernel_par = model->kernel_par; long dim_input = model->dim_input; long index; double partial, result = 0.0; for(index=1; index<=nb_data; index++) { partial = model->partial_average_alpha[index] - model->alpha[index][category]; if(partial != 0.0) result += partial * ker(nature_kernel, model->X[index], vector, dim_input, kernel_par); } return result; } /* label = MSVM_2_classify(x, model, real_outputs) Classify x and output the label. If real_outputs is not NULL, also compute the Q real-valued outputs of the model and store them in (real_outputs[1]...real_outpust[Q]). Note: this function is faster than calling Q times MSVM_2_function */ long MSVM_2_classify(void *vector, const struct Model *model, double *real_outputs) { const long nb_data = model->nb_data; const long Q = model->Q; const enum Kernel_type nature_kernel = model->nature_kernel; const double *kernel_par = model->kernel_par; long dim_input = model->dim_input; long i,k; long label = 1; double maxoutput,partial, kernel; int use_real_outputs = true; if(real_outputs==NULL) { real_outputs = (double *)malloc(sizeof(double) * (Q+1)); use_real_outputs = false; } for(k=1;k<=Q;k++) real_outputs[k] = model->b_SVM[k]; for(i=1; i<=nb_data; i++) { partial = model->partial_average_alpha[i]; if(partial != 0.0) { kernel = ker(nature_kernel, model->X[i], vector, dim_input, kernel_par); for (k=1; k<=Q; k++) real_outputs[k] += (partial - model->alpha[i][k]) * kernel; } } maxoutput = real_outputs[1]; for(k=2; k<=Q; k++) if(real_outputs[k] > maxoutput) { maxoutput = real_outputs[k]; label = k; } if(!use_real_outputs) free(real_outputs); return label; } int MSVM_2_check_feasible_sol(const struct Model *model, char *alpha_file) { long i,k; char command[taille]; const long Q = model->Q; const long nb_data = model->nb_data; double *constraints, norm; int feasible = true; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) if(((k == model->y[i]) && (model->alpha[i][k] != 0.0)) || (model->alpha[i][k] < 0.0)) { printf("\nNo feasible solution: alpha[%ld][%ld] = %lf\n\n", i, k, model->alpha[i][k]); feasible = false; } constraints = (double *) calloc(Q+1, sizeof(double)); for(k=1; k<=Q; k++) constraints[k] = model->sum_all_alpha / Q; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) constraints[k] -= model->alpha[i][k]; printf("\nSatisfaction of the equality constraints:\n\n"); for(k=1; k<=Q; k++) printf("%s%e\n", constraints[k] < 0.0 ? " " : " ", constraints[k]); norm = 0.0; for(k=1; k<=Q; k++) norm += constraints[k] * constraints[k]; norm = sqrt(norm); if(norm >= very_small) { printf("\nLarge deviation of the equality constraints...\n"); feasible = false; Pause(""); } sprintf(command, "cp %s Feasible/.", alpha_file); int rc = system(command); free(constraints); return feasible; } void MSVM_2_compute_gradient(double **gradient, struct Cache *cache, const struct Model *model) { long i,j,k,y_i; double partial,kernel; const long Q = model->Q; const long nb_data = model->nb_data; const enum Kernel_type nature_kernel = model->nature_kernel; const double *kernel_par = model->kernel_par; const long dim_input = model->dim_input; const double Qinv = 1. / (Q-1.0); if(cache->verbose) printf("\nStart of the gradient computation...\n"); for(i=1; i<=nb_data; i++) { if((i%step) == 0 && cache->verbose) printf("\n%9ld", i); y_i = model->y[i]; for(k=1; k<=Q; k++) { cache->H_alpha[i][k] = 0.0; cache->H_tilde_alpha[i][k] = 0.0; if(k != y_i) { for(j=1; j<=nb_data; j++) { partial = model->alpha[j][k] - model->partial_average_alpha[j]; if(partial != 0.0) { kernel = ker(nature_kernel, model->X[i], model->X[j], dim_input, kernel_par); cache->H_alpha[i][k] += partial * kernel; if(i == j) kernel += 1./(2 * model->C[y_i]); cache->H_tilde_alpha[i][k] += partial * kernel; } } gradient[i][k] = - cache->H_tilde_alpha[i][k] + Qinv; } else gradient[i][k] = 0.0; } } if(cache->verbose) printf("\n\nEnd of the gradient computation...\n"); } /* Evaluate the training error */ long MSVM_2_eval_training(long **mat_conf, const struct Cache *cache, const struct Model *model) { long i,k,l,y_i,ind_max; const long Q = model->Q; const long nb_data = model->nb_data; double *output = (double *) calloc(Q+1, sizeof(double)); double maximum; long errors=0; if(mat_conf != NULL) { for(k=1; k<=Q; k++) for(l=1; l<=Q; l++) mat_conf[k][l] = 0; } for(i=1; i<=nb_data; i++) { y_i = model->y[i]; output[y_i] = 0.0; for(k=1; k<=Q; k++) if(k != y_i) { output[k] = -cache->H_alpha[i][k] + model->b_SVM[k]; output[y_i] -= output[k]; } ind_max = 1; maximum = output[1]; for(k=2; k<=Q; k++) if(output[k] > maximum) { maximum = output[k]; ind_max = k; } if(mat_conf != NULL) mat_conf[y_i][ind_max]++; if(y_i != ind_max) errors++; } free(output); return errors; } void MSVM_2_compute_xi_opt(double **xi_opt, struct Cache *cache, const struct Model *model) { long i,k,y_i; const long Q = model->Q; const long nb_data = model->nb_data; cache->sum_all_xi_opt = 0.0; for(i=1; i<=nb_data; i++) { y_i = model->y[i]; xi_opt[i][y_i] = 0.0; for(k=1; k<=Q; k++) if(k != y_i) { xi_opt[i][k] = (model->alpha[i][k] - model->partial_average_alpha[i]) / (2 * model->C[y_i]); cache->sum_all_xi_opt += xi_opt[i][k]; } } } void MSVM_2_check_xi_opt(double **xi_opt, double **gradient, const struct Cache *cache, const struct Model *model) { long i,k,y_i; const long Q = model->Q; const long nb_data = model->nb_data; const double Qinv = 1. / (Q-1.0); double partial; for(i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) if(k != y_i) { partial = cache->H_alpha[i][k] - Qinv + xi_opt[i][k] - gradient[i][k]; if(fabs(partial) > very_small) { printf("\nProblem in the computation of the slack variables...\n"); printf(" Ha_ik - Qinv + xi_ik + g_ik = %lf - %lf + %lf + %lf = %lf\n",cache->H_alpha[i][k],Qinv , xi_opt[i][k], -gradient[i][k],partial); printf("(sum_all_alpha = %lf)\n",model->sum_all_alpha); exit(0); } } } if(cache->verbose) printf("\nThe values of the slack variables have been checked...\n"); } double MSVM_2_compute_primal_obj(double **xi_opt, const struct Cache *cache, const struct Model *model) { long i,k,l,y_i; const long Q = model->Q; const long nb_data = model->nb_data; double J_xi_i; double J_xi = 0; for(i=1; i<=nb_data; i++) { y_i = model->y[i]; J_xi_i = 0; for(k=1; k<=Q; k++) if(k != y_i) { for(l=1; l<=Q; l++) { if(l != y_i) J_xi_i += xi_opt[i][k] * xi_opt[i][l]; } J_xi_i += xi_opt[i][k] * xi_opt[i][k]; } J_xi += model->C[y_i] * J_xi_i; } return (0.5 * cache->alpha_H_alpha + J_xi); } /* Put xi on the constraints */ void MSVM_2_minimal_xi(const int keepok,double **xi_opt, const struct Cache *cache, const struct Model *model) { long i,k,y_i; double bound; const long Q = model->Q; const long nb_data = model->nb_data; const double Qd = (1.0 / (Q - 1.0)); if (keepok) { // keep previous values of xi that are feasible for(i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) if(k != y_i) { bound = -cache->H_alpha[i][k] + model->b_SVM[k] + Qd ; if(xi_opt[i][k] < bound) xi_opt[i][k] = bound; } } } else { // completely reinitialize xi for(i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) if(k != y_i) { xi_opt[i][k] = -cache->H_alpha[i][k] + model->b_SVM[k] + Qd; } } } } /* Compute an upper bound on the optimum with gradient projection */ void MSVM_2_correct_xi_opt(double **xi_opt, struct Cache *cache, const struct Model *model, const int MaxIter) { const double *C = model->C; const long Q = model->Q; const long nb_data = model->nb_data; double **bound_xi = matrix(nb_data, Q); double **gradient_xi = matrix(nb_data, Q); double **descent_xi = matrix(nb_data, Q); long **activeset_xi = matrix_l(nb_data, Q); int converged_xi,nA; double gamma,gamma_max,gamma_denominateur,J_xi,J_xi_i,norm_descent,minu; long i,k,l,y_i,i_minu=0,k_minu=0; const double epsilon_xi = 0.0001; const int computeCost = 0; // Compute the constraints on the slack variables for(i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) if(k != y_i) { bound_xi[i][k] = -cache->H_alpha[i][k] + model->b_SVM[k] + (1.0 / (Q - 1.0)) ; // Push the slack variable into the feasible set for initialization if(xi_opt[i][k] < bound_xi[i][k]) xi_opt[i][k] = bound_xi[i][k]; } } // compute a rough upper bound on the primal (take the first feasible point) //compute J_xi(xi) J_xi = 0; for(i=1; i<=nb_data; i++) { y_i = model->y[i]; J_xi_i = 0; for(k=1; k<=Q; k++) if(k != y_i) { for(l=1; l<=Q; l++) { if(l != y_i) J_xi_i += xi_opt[i][k] * xi_opt[i][l]; } J_xi_i += xi_opt[i][k] * xi_opt[i][k]; } J_xi += model->C[y_i] * J_xi_i; } cache->primal_cheap = 0.5 * cache->alpha_H_alpha + J_xi; if(cache->verbose) printf(" Cheap upper bound on primal objective: %lf (ratio = %3.6lf \%%)\n", cache->primal_cheap,100*cache->dual/cache->primal_cheap); // Gradient projection algorithm for xi int iter_xi = 0; converged_xi = 0; int stop_because_useless = 0; // stop if cost J_xi too large compared to best_J_xi after MaxIter/2 // best_J_xi is computed from best_primal_upper_bound stored in cache->primal const double best_J_xi = (cache->primal*(1.+10./(double)MaxIter) - 0.5 * cache->alpha_H_alpha); // Compute the active set nA = 0; for(i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) if(k != y_i) { if(xi_opt[i][k] <= bound_xi[i][k]) { activeset_xi[i][k] = 1; nA++; } else activeset_xi[i][k] = 0; } } // Main loop do { // inner computations norm_descent = 0; gamma_max = HUGE_VAL; for (i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) if(k != y_i) { // Compute gradient of cost wrt to xi = 4*xi_ik + 2*sum_l\k xi_il = 2*(xi_ik + sum_l xi_il) gradient_xi[i][k] = xi_opt[i][k]; for(l=1; l<=Q; l++) { if(l != y_i) gradient_xi[i][k] += xi_opt[i][l]; } gradient_xi[i][k] *= 2; // descent direction (project -gradient on the constraints) if( activeset_xi[i][k]) { // descent direction is 0 along the constraints descent_xi[i][k] = 0.0; } else { descent_xi[i][k] = -gradient_xi[i][k]; // norm of descent to check convergence norm_descent += descent_xi[i][k] * descent_xi[i][k]; // maximal step size if(descent_xi[i][k] < 0) { gamma = (bound_xi[i][k] - xi_opt[i][k]) / descent_xi[i][k]; if (gamma < gamma_max) gamma_max = gamma; } } } } norm_descent = sqrt(norm_descent); // Check convergence if(norm_descent < epsilon_xi) { // Compute vector u // u = gradient_xi[i][k] for (i,k) in active set, 0 for the others // check negative entries in u (if none then optimum found and stop) converged_xi = 1; minu = -epsilon_xi; for(i=1;i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) if(k != y_i && activeset_xi[i][k] && gradient_xi[i][k] < minu) { // equivalent to u<-epsilon converged_xi=0; minu = gradient_xi[i][k]; i_minu = i; k_minu = k; } } // relax the constraint with minimum u if (!converged_xi) { activeset_xi[i_minu][k_minu] = 0; nA--; descent_xi[i_minu][k_minu] = -minu; norm_descent = -minu; //printf("relaxing constraint (%ld,%ld) : descent = %lf\n",i_minu,k_minu,descent_xi[i_minu][k_minu]); } } if(!converged_xi) { // Line search for gradient projection step in xi // gamma^* = -gradient^T d / 2*d^T M d gamma_denominateur = 0; gamma = 0; for(i=1;i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) if(k != y_i && !activeset_xi[i][k]) { gamma -= gradient_xi[i][k] * descent_xi[i][k]; gamma_denominateur += descent_xi[i][k] * descent_xi[i][k]; for(l=1; l<=Q; l++) { if(l != y_i) { gamma_denominateur += descent_xi[i][k] * descent_xi[i][l]; } } } } gamma /= 2*gamma_denominateur; if(gamma > gamma_max) gamma = gamma_max; // Take a step for(i=1;i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) if(k != y_i && !activeset_xi[i][k]) { xi_opt[i][k] += gamma * descent_xi[i][k]; // Update the active set if(xi_opt[i][k] <= bound_xi[i][k]) { activeset_xi[i][k] = 1; nA++; } /* else { activeset_xi[i][k] = 0; nA--; }*/ } } if(computeCost || (iter_xi == MaxIter/2)) { //evaluate the objective function J_xi(xi) J_xi = 0; for(i=1; i<=nb_data; i++) { y_i = model->y[i]; J_xi_i = 0; for(k=1; k<=Q; k++) if(k != y_i) { for(l=1; l<=Q; l++) { if(l != y_i) J_xi_i += xi_opt[i][k] * xi_opt[i][l]; } J_xi_i += xi_opt[i][k] * xi_opt[i][k]; } J_xi += model->C[y_i] * J_xi_i; } } if(iter_xi == MaxIter/2 ) { if(J_xi > best_J_xi) { //printf("stopping useless optimimization at iter = %d...\n",iter_xi); stop_because_useless = 1; } } } iter_xi++; } while (!converged_xi && iter_xi < MaxIter && !stop_because_useless); //printf("iter=%d, %d active constraints / %ld; norm_d = %lf : J_xi(xi) = %3.15lf \n",iter_xi,nA,nb_data*(Q-1),norm_descent,J_xi); // Compute optimized upper bound if(!computeCost && !stop_because_useless) { J_xi = 0; for(i=1; i<=nb_data; i++) { y_i = model->y[i]; J_xi_i = 0; for(k=1; k<=Q; k++) if(k != y_i) { for(l=1; l<=Q; l++) { if(l != y_i) J_xi_i += xi_opt[i][k] * xi_opt[i][l]; } J_xi_i += xi_opt[i][k] * xi_opt[i][k]; } J_xi += model->C[y_i] * J_xi_i; } } /* if(0.5 * cache->alpha_H_alpha + J_xi > cache->primal) printf("USELESS optim at iter = %d... %lf / %lf\n",iter_xi, 0.5 * cache->alpha_H_alpha + J_xi,cache->primal); */ cache->primal = 0.5 * cache->alpha_H_alpha + J_xi; if(cache->verbose) printf("Optimized upper bound on primal objective: %lf (ratio = %3.6lf \%%)\n\n", cache->primal,100*cache->dual/cache->primal); free(bound_xi[1]); free(bound_xi); free(descent_xi[1]); free(descent_xi); free(gradient_xi[1]); free(gradient_xi); free(activeset_xi[1]); free(activeset_xi); return; } void MSVM_2_optimize_b(double **xi_opt, struct Cache *cache, struct Model *model) { const long Q = model->Q; const long nb_data = model->nb_data; long i,k,compteur, portion, class, Iteration; double *grid_index, *b_SVM_base, *best_b_SVM; double minprimal = cache->primal; double primal; double minprimalcheap = cache->primal_cheap; double bstep = 0.1; double **xi_save = matrix(nb_data,Q); for(i=1;i<=nb_data;i++) for(k=1;k<=Q;k++) xi_save[i][k] = xi_opt[i][k]; grid_index = (double *) calloc(Q+1, sizeof(double)); b_SVM_base = (double *) calloc(Q+1, sizeof(double)); best_b_SVM = (double *) calloc(Q+1, sizeof(double)); for(class=1; class<=Q; class++) best_b_SVM[class] = model->b_SVM[class]; grid_index[1] = 0.0; b_SVM_base[1] = 0.0; for(Iteration=1; Iteration <=10; Iteration++) { printf("Iteration = %ld\n",Iteration); for(k=2; k<=Q; k++) b_SVM_base[k] = model->b_SVM[k] - (5.0 * bstep); for(compteur=0; compteur<(long)pow(10.0, (double)(Q-1)); compteur++) { /* printf("\nPosition in the grid: %6d\n", compteur); */ portion = compteur; for(class=2; class<=Q; class++) { grid_index[class] = (double) (portion / (long) pow(10.0, (double) (Q-class))); portion -= (long) (grid_index[class] * pow(10.0, (double) (Q-class))); } for(class=2; class<=Q; class++) model->b_SVM[class] = b_SVM_base[class] + (grid_index[class] * bstep); standardize_b(model->b_SVM,Q); //correct_xi_opt(); MSVM_2_minimal_xi(0,xi_opt,cache,model); primal = MSVM_2_compute_primal_obj(xi_opt,cache,model); /* Restore original xi_opt */ for(i=1;i<=nb_data;i++) for(k=1;k<=Q;k++) xi_opt[i][k] = xi_save[i][k]; MSVM_2_minimal_xi(1,xi_opt,cache,model); cache->primal_cheap = MSVM_2_compute_primal_obj(xi_opt,cache,model); if(primal < minprimal) { minprimal = primal; for(class=1; class<=Q; class++) best_b_SVM[class] = model->b_SVM[class]; } if(cache->primal_cheap < minprimalcheap) minprimalcheap = cache->primal_cheap; } for(class=1; class<=Q; class++) model->b_SVM[class] = best_b_SVM[class]; standardize_b(model->b_SVM,Q); //correct_xi_opt(); MSVM_2_minimal_xi(0,xi_opt,cache,model); primal = MSVM_2_compute_primal_obj(xi_opt,cache,model); /* Restore original xi_opt */ for(i=1;i<=nb_data;i++) for(k=1;k<=Q;k++) xi_opt[i][k] = xi_save[i][k]; MSVM_2_minimal_xi(1,xi_opt,cache,model); cache->primal_cheap = MSVM_2_compute_primal_obj(xi_opt,cache,model); if(primal < minprimal) { minprimal = primal; for(class=1; class<=Q; class++) best_b_SVM[class] = model->b_SVM[class]; } if(cache->primal_cheap < minprimalcheap) minprimalcheap = cache->primal_cheap; bstep /= 2.0; } cache->primal = minprimal; cache->primal_cheap = minprimalcheap; //standardize_b(); if(cache->verbose) { printf("\nNew components of the b vector:\n"); printf("\n"); for(class=1; class<=Q; class++) printf("%11.6f\n", model->b_SVM[class]); } // Free templates free(xi_save[1]);free(xi_save); free(grid_index); free(b_SVM_base); free(best_b_SVM); } void MSVM_2_estimate_b(double **gradient, const struct Cache *cache, struct Model *model) { long i,k; const long Q = model->Q; const long nb_data = model->nb_data; long *nb_sup_vect = (long *) calloc(Q+1, sizeof(long)); for(k=1; k<=Q; k++) { nb_sup_vect[k] = 0; model->b_SVM[k] = 0.0; } double sum = 0.0; if(cache->verbose) printf("\nVector b before centering\n\n"); for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) if(model->alpha[i][k] > 0) { nb_sup_vect[k]++; model->b_SVM[k] += gradient[i][k]; // should be '-=' but we have '-gradient' in gradient } for(k=1; k<=Q; k++) { if(nb_sup_vect[k] > 0) model->b_SVM[k] /= (double) nb_sup_vect[k]; if(cache->verbose) printf(" b_%1ld = %c%e\n", k, (model->b_SVM[k] >= 0) ? ' ': '-', fabs(model->b_SVM[k])); sum += model->b_SVM[k]; } if(cache->verbose) { printf("\nSum of the components of b: %e\n", sum); Pause(""); } if(sum != 0.0) { sum /= Q; for(k=1; k<=Q; k++) model->b_SVM[k] -= sum; } free(nb_sup_vect); } void MSVM_2_compute_obj_dual(struct Cache *cache, const struct Model *model) { long i,k; const long Q = model->Q; const long nb_data = model->nb_data; double alpha_H_alpha = 0; double alpha_H_tilde_alpha = 0; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) { alpha_H_alpha += cache->H_alpha[i][k] * model->alpha[i][k]; alpha_H_tilde_alpha += cache->H_tilde_alpha[i][k] * model->alpha[i][k]; } double Q_form_dual = alpha_H_tilde_alpha; double L_form_dual = model->sum_all_alpha / (Q - 1.0); cache->alpha_H_alpha = alpha_H_alpha; cache->alpha_H_tilde_alpha = alpha_H_tilde_alpha; cache->dual = -0.5 * Q_form_dual + L_form_dual; } void MSVM_2_compute_obj_primal(struct Cache *cache, double **xi_opt, const struct Model *model) { long i,k,l; const long Q = model->Q; double *C = model->C; const long nb_data = model->nb_data; double partial,primal, ratio; double xi_M_xi = 0.0; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) for(l=1; l<=Q; l++) { partial = (k == l) ? 2.0 : 1.0; xi_M_xi += C[model->y[i]] * partial * xi_opt[i][k] * xi_opt[i][l]; } primal = 0.5 * cache->alpha_H_alpha + xi_M_xi; if(cache->verbose) { printf("\nEmpirical contribution to the primal objective function: %lf\n", xi_M_xi); if(fabs(model->sum_all_alpha - 2.0 * Q * cache->sum_all_xi_opt) < very_small) printf("1^T alpha = 2Q 1^T xi = %e\n", model->sum_all_alpha); printf("\n Dual objective function: %e", cache->dual); printf("\nUnconstrained primal objective function: %e", primal); if(primal != 0.0) { ratio = cache->dual / primal; printf("\n(ratio %5.2lf\%% )\n", 100.0 * ratio); } Pause(""); } cache->primal = primal; } MSVMpack1.2/src/kernel.c~0000644000175000017500000004261011707263036014343 0ustar lauerlauer#include // Include user-defined custom kernels #include "custom_kernels.c" /* Common kernel functions */ #ifdef __SSE4_1__ /* Vectorized code with SSE4.1 intrinsics (only for Intel processors) */ #include /* Dot product (linear kernel function) */ double dot_double(const double *a, const double *b, const long dim) { double dot; long i; __m128d num1, num2, num4; num4= _mm_setzero_pd(); //sets sum to zero for(i=1; i<=dim-1; i+=2) { num1 = _mm_load_pd(a+i); num2 = _mm_load_pd(b+i); num2 = _mm_dp_pd(num1,num2,0x31); // dot product num4 = _mm_add_sd(num4, num2); // vertical addition (global sum) } _mm_store_sd(&dot,num4); // Epilog: if(dim%2 != 0) { dot += a[dim]*b[dim]; } return dot; } double dot_float(const float *a, const float *b, const long dim) { float dot; long i; __m128 num1, num2, num4; num4= _mm_setzero_ps(); //sets sum to zero for(i=1; i<=dim-3; i+=4) { num1 = _mm_load_ps(a+i); num2 = _mm_load_ps(b+i); num2 = _mm_dp_ps(num1,num2,0xf1); // dot product num4 = _mm_add_ss(num4, num2); // vertical addition } _mm_store_ss(&dot,num4); int epilog = dim%4; switch (epilog) { case 1: dot += (a[dim]*b[dim]); break; case 2: dot += (a[dim]*b[dim]) + (a[dim-1]*b[dim-1]); break; case 3: dot += (a[dim]*b[dim]) + (a[dim-1]*b[dim-1]) + (a[dim-2]*b[dim-2]); break; default: break; } return (double)dot; } /* Gaussian RBF kernel k(x,z) = exp(-||x - z||^2 / 2sigma^2) */ double rbf_double(const double *a, const double *b, const long dim, const double sigma) { double ker_val; long i; __m128d num1, num2, num3, num4; num4= _mm_setzero_pd(); //sets sum to zero for(i=1; i<=dim-1; i+=2) { num1 = _mm_load_pd(a+i); num2 = _mm_load_pd(b+i); num3 = _mm_sub_pd(num1, num2); // substraction num3 = _mm_dp_pd(num3,num3,0x31); // dot product num4 = _mm_sub_sd(num4, num3); // vertical addition } _mm_store_sd(&ker_val,num4); // Epilog: if(dim%2 != 0) { ker_val -= (a[dim]-b[dim])*(a[dim]-b[dim]); } return exp(ker_val / (2 * sigma * sigma)); } double rbf_float(const float *a, const float *b, const long dim, const double sigma) { float ker_val; long i; __m128 num1, num2, num3, num4; num4= _mm_setzero_ps(); //sets sum to zero for(i=1; i<=dim-3; i+=4) { num1 = _mm_load_ps(a+i); //loads aligned array a into num1 num1= a[3] a[2] a[1] a[0] num2 = _mm_load_ps(b+i); //loads aligned array b into num2 num2= b[3] b[2] b[1] b[0] num3 = _mm_sub_ps(num1, num2); // parallel substraction num3 = num1 - num2 num3 = _mm_dp_ps(num3,num3,0xf1); // dot product: num3[0] = num3[0]^2 + ... + num3[4]^2 num4 = _mm_sub_ss(num4, num3); // vertical addition } _mm_store_ss(&ker_val,num4); // Epilog int epilog = dim%4; switch (epilog) { case 1: ker_val -= (a[dim]-b[dim])*(a[dim]-b[dim]); break; case 2: ker_val -= (a[dim]-b[dim])*(a[dim]-b[dim]) + (a[dim-1]-b[dim-1])*(a[dim-1]-b[dim-1]); break; case 3: ker_val -= (a[dim]-b[dim])*(a[dim]-b[dim]) + (a[dim-1]-b[dim-1])*(a[dim-1]-b[dim-1]) + (a[dim-2]-b[dim-2])*(a[dim-2]-b[dim-2]); break; default: break; } return exp((double)ker_val / (2 * sigma * sigma)); } #else #ifdef __SSE3__ /* Vectorized code with SSE3 intrinsics (this should be available on most Intel & AMD processors) */ #include /* Dot product (linear kernel function) */ double dot_double(const double *a, const double *b, const long dim) { double dot; long i; __m128d num1, num2, num3, num4; num4= _mm_setzero_pd(); //sets sum to zero for(i=1; i<=dim-1; i+=2) { num1 = _mm_load_pd(a+i); num2 = _mm_load_pd(b+i); num3 = _mm_mul_pd(num1,num2); // multiplication num3 = _mm_hadd_pd(num3, num3); // horizontal addition num4 = _mm_add_sd(num4, num3); // vertical summation } _mm_store_sd(&dot,num4); // Epilog: if(dim%2 != 0) { dot += a[dim]*b[dim]; } return dot; } double dot_float(const float *a, const float *b, const long dim) { float dot; long i; __m128 num1, num2, num3, num4; num4= _mm_setzero_ps(); //sets sum to zero for(i=1; i<=dim-3; i+=4) { num1 = _mm_load_ps(a+i); num2 = _mm_load_ps(b+i); num3 = _mm_mul_ps(num1,num2); // product: num3[0] = num1[0]*num2[0], num3[1]=num1[0]*num2[0]... num3 = _mm_hadd_ps(num3, num3); // horizontal addition: num3[0] = num3[0]+num3[1], num4 = _mm_add_ps(num4, num3); // vertical addition } num4= _mm_hadd_ps(num4, num4); // last horizontal addition _mm_store_ss(&dot,num4); int epilog = dim%4; switch (epilog) { case 1: dot += (a[dim]*b[dim]); break; case 2: dot += (a[dim]*b[dim]) + (a[dim-1]*b[dim-1]); break; case 3: dot += (a[dim]*b[dim]) + (a[dim-1]*b[dim-1]) + (a[dim-2]*b[dim-2]); break; default: break; } return (double)dot; } /* Gaussian RBF kernel k(x,z) = exp(-||x - z||^2 / 2sigma^2) */ double rbf_double(const double *a, const double *b, const long dim, const double sigma) { double ker_val; long i; __m128d num1, num2, num3, num4; num4= _mm_setzero_pd(); //sets sum to zero for(i=1; i<=dim-1; i+=2) { num1 = _mm_load_pd(a+i); num2 = _mm_load_pd(b+i); num3 = _mm_sub_pd(num1, num2); // substraction // dot product: num3 = _mm_mul_pd(num3,num3); // multiplication num3 = _mm_hadd_pd(num3, num3); // horizontal addition num4 = _mm_sub_sd(num4, num3); // vertical addition } _mm_store_sd(&ker_val,num4); // Epilog: if(dim%2 != 0) { ker_val -= (a[dim]-b[dim])*(a[dim]-b[dim]); } return exp(ker_val / (2 * sigma * sigma)); } double rbf_float(const float *a, const float *b, const long dim, const double sigma) { float ker_val; long i; __m128 num1, num2, num3, num4; num4= _mm_setzero_ps(); //sets sum to zero for(i=1; i<=dim-3; i+=4) { num1 = _mm_load_ps(a+i); //loads aligned array a into num1 num1= a[3] a[2] a[1] a[0] num2 = _mm_load_ps(b+i); //loads aligned array b into num2 num2= b[3] b[2] b[1] b[0] num3 = _mm_sub_ps(num1, num2); // parallel substraction num3 = num1 - num2 num3 = _mm_mul_ps(num3,num3); // product: num3[0] = num3[0]^2... num3 = _mm_hadd_ps(num3, num3); // horizontal addition: num3[0] = num3[0]+num3[1], // num3[1] = num3[2]+num3[3] num4 = _mm_sub_ps(num4, num3); // vertical addition } num4= _mm_hadd_ps(num4, num4); // last horizontal addition _mm_store_ss(&ker_val,num4); // Epilog int epilog = dim%4; switch (epilog) { case 1: ker_val -= (a[dim]-b[dim])*(a[dim]-b[dim]); break; case 2: ker_val -= (a[dim]-b[dim])*(a[dim]-b[dim]) + (a[dim-1]-b[dim-1])*(a[dim-1]-b[dim-1]); break; case 3: ker_val -= (a[dim]-b[dim])*(a[dim]-b[dim]) + (a[dim-1]-b[dim-1])*(a[dim-1]-b[dim-1]) + (a[dim-2]-b[dim-2])*(a[dim-2]-b[dim-2]); break; default: break; } return exp((double)ker_val / (2 * sigma * sigma)); } #else /* If SSE3 is not available: Use standard (non-vectorized) operations (no intrinsics) */ /* Dot product (linear kernel function) */ double dot_double(const double *a , const double *b , const long dim) { long i; double result=0.0; for(i = 1; i<=dim; i++) result += a[i] * b[i]; return result; } double dot_float(const float *a , const float *b , const long dim) { long i; float result = 0.0; for(i = 1; i<=dim; i++) result += a[i] * b[i]; return (double)result; } /* Gaussian RBF kernel k(x,z) = exp(-||x - z||^2 / 2sigma^2) */ double rbf_double(const double *a, const double *b, const long dim, const double sigma) { long i; double result=0.0; for(i=1;i<=dim;i++) result -= (a[i] - b[i]) * (a[i] - b[i]); result /= (2 * sigma * sigma); return exp(result); } double rbf_float(const float *a, const float *b, const long dim, const double sigma) { long i; float result=0.0; for(i=1;i<=dim;i++) result -= (a[i] - b[i]) * (a[i] - b[i]); return exp((double)result/(2 * sigma * sigma)); } #endif #endif /* Vectorized code with SSE2 intrinsics (this should be available on all processors released since 2003) */ #include /* Linear kernel for SHORT INT data */ double dot_short_int(const short int *a, const short int *b, const long dim) { int dot; long i; __m128i num1, num2, num3, num4; num4= _mm_setzero_si128(); //sets sum to zero for(i=1; i<=dim-7; i+=8) { num1 = _mm_load_si128((__m128i *)(a+i)); num2 = _mm_load_si128((__m128i *)(b+i)); num3 = _mm_madd_epi16(num1,num2); // dot product num4 = _mm_add_epi32(num4, num3); // vertical addition } // Final horizontal addition num3 = _mm_srli_si128(num4,4); num4 = _mm_add_epi32(num3,num4); num3 = _mm_srli_si128(num3,4); num4 = _mm_add_epi32(num3,num4); num3 = _mm_srli_si128(num3,4); num4 = _mm_add_epi32(num3,num4); dot = _mm_cvtsi128_si32(num4); int epilog = dim%8; switch (epilog) { case 1: dot += (a[dim]*b[dim]); break; case 2: dot += (a[dim]*b[dim]) + (a[dim-1]*b[dim-1]); break; case 3: dot += (a[dim]*b[dim]) + (a[dim-1]*b[dim-1]) + (a[dim-2]*b[dim-2]); break; case 4: dot += (a[dim]*b[dim]) + (a[dim-1]*b[dim-1]) + (a[dim-2]*b[dim-2]) + (a[dim-3]*b[dim-3]); break; case 5: dot += (a[dim]*b[dim]) + (a[dim-1]*b[dim-1]) + (a[dim-2]*b[dim-2]) + (a[dim-3]*b[dim-3]) + (a[dim-4]*b[dim-4]); break; case 6: dot += (a[dim]*b[dim]) + (a[dim-1]*b[dim-1]) + (a[dim-2]*b[dim-2])+ (a[dim-3]*b[dim-3]) + (a[dim-5]*b[dim-5]); break; case 7: dot += (a[dim]*b[dim]) + (a[dim-1]*b[dim-1]) + (a[dim-2]*b[dim-2])+ (a[dim-3]*b[dim-3]) + (a[dim-5]*b[dim-5]) + (a[dim-6]*b[dim-6]); break; default: break; } return (double)dot; } /* Gaussian RBF kernel for SHORT INT data */ double rbf_short_int(const short int *a, const short int *b, const long dim, const double sigma) { int dot; long i; __m128i num1, num2, num3, num4; num4= _mm_setzero_si128(); //sets sum to zero for(i=1; i<=dim-7; i+=8) { num1 = _mm_load_si128((__m128i *)(a+i)); num2 = _mm_load_si128((__m128i *)(b+i)); num3 = _mm_sub_epi16(num1, num2); // substraction num3 = _mm_madd_epi16(num3,num3); // dot product num4 = _mm_add_epi32(num4, num3); // vertical addition } // Final horizontal addition num3 = _mm_srli_si128(num4,4); num4 = _mm_add_epi32(num3,num4); num3 = _mm_srli_si128(num3,4); num4 = _mm_add_epi32(num3,num4); num3 = _mm_srli_si128(num3,4); num4 = _mm_add_epi32(num3,num4); dot = _mm_cvtsi128_si32(num4); int epilog = dim%8; switch (epilog) { case 1: dot += (a[dim]-b[dim])*(a[dim]-b[dim]); break; case 2: dot += (a[dim]-b[dim])*(a[dim]-b[dim]) + (a[dim-1]-b[dim-1])*(a[dim-1]-b[dim-1]); break; case 3: dot += (a[dim]-b[dim])*(a[dim]-b[dim]) + (a[dim-1]-b[dim-1])*(a[dim-1]-b[dim-1]) + (a[dim-2]-b[dim-2])*(a[dim-2]-b[dim-2]); break; case 4: dot += (a[dim]-b[dim])*(a[dim]-b[dim]) + (a[dim-1]-b[dim-1])*(a[dim-1]-b[dim-1]) + (a[dim-2]-b[dim-2])*(a[dim-2]-b[dim-2])+ (a[dim-3]-b[dim-3])*(a[dim-3]-b[dim-3]); break; case 5: dot += (a[dim]-b[dim])*(a[dim]-b[dim]) + (a[dim-1]-b[dim-1])*(a[dim-1]-b[dim-1]) + (a[dim-2]-b[dim-2])*(a[dim-2]-b[dim-2])+ (a[dim-3]-b[dim-3])*(a[dim-3]-b[dim-3])+ (a[dim-4]-b[dim-4])*(a[dim-4]-b[dim-4]); break; case 6: dot += (a[dim]-b[dim])*(a[dim]-b[dim]) + (a[dim-1]-b[dim-1])*(a[dim-1]-b[dim-1]) + (a[dim-2]-b[dim-2])*(a[dim-2]-b[dim-2])+ (a[dim-3]-b[dim-3])*(a[dim-3]-b[dim-3]) + (a[dim-4]-b[dim-4])*(a[dim-4]-b[dim-4]) + (a[dim-5]-b[dim-5])*(a[dim-5]-b[dim-5]); break; case 7: dot += (a[dim]-b[dim])*(a[dim]-b[dim]) + (a[dim-1]-b[dim-1])*(a[dim-1]-b[dim-1]) + (a[dim-2]-b[dim-2])*(a[dim-2]-b[dim-2])+ (a[dim-3]-b[dim-3])*(a[dim-3]-b[dim-3]) + (a[dim-4]-b[dim-4])*(a[dim-4]-b[dim-4]) + (a[dim-5]-b[dim-5])*(a[dim-5]-b[dim-5]) + (a[dim-6]-b[dim-6])*(a[dim-6]-b[dim-6]); break; default: break; } return exp(-(double)dot / (2 * sigma * sigma)); } /* ---- Non-vectorized part of code ---- */ /* Linear kernal */ double dot_int(const int *a , const int *b , const long dim) { long i; int result = 0; for(i = 1; i<=dim; i++) result += a[i] * b[i]; return (double)result; } double dot_byte(const unsigned char *a , const unsigned char *b , const long dim) { long i; int result = 0; for(i = 1; i<=dim; i++) result += a[i] * b[i]; return (double)result; } /* Gaussian RBF kernel */ double rbf_int(const int *a, const int *b, const long dim, const double sigma) { long i; int result=0; for(i=1;i<=dim;i++) result -= (a[i] - b[i]) * (a[i] - b[i]); return exp((double)result/(2 * sigma * sigma)); } double rbf_byte(const unsigned char *a, const unsigned char *b, const long dim, const double sigma) { long i; unsigned int result=0; for(i=1;i<=dim;i++) result += (a[i] - b[i]) * (a[i] - b[i]); return exp(- (double)result/(2 * sigma * sigma)); } /* Homogeneous Polynomial kernel k(x,z) = (x^T z)^deg */ double polynomial_homo_double(const double *a , const double *b , const long dim, const int deg) { int i; double result = dot_double(a,b,dim); for(i = 1; i < deg; i++) result *= result; return result; } double polynomial_homo_float(const float *a , const float *b , const long dim, const int deg) { int i; // The dot product is computed with single precision floats double result = dot_float(a,b,dim); // But the power is computed with double precision for(i = 1; i < deg; i++) result *= result; return result; } double polynomial_homo_int(const int *a , const int *b , const long dim, const int deg) { int i; long result = 0; for(i = 1; i<=dim; i++) result += a[i] * b[i]; for(i = 1; i < deg; i++) result *= result; return (double)result; } double polynomial_homo_short_int(const short int *a , const short int *b , const long dim, const int deg) { int i; int result = 0; for(i = 1; i<=dim; i++) result += a[i] * b[i]; // could be vectorized in SSE2 for(i = 1; i < deg; i++) result *= result; return (double)result; } double polynomial_homo_byte(const unsigned char *a , const unsigned char *b , const long dim, const int deg) { int i; unsigned int result = 0; for(i = 1; i<=dim; i++) result += a[i] * b[i]; for(i = 1; i < deg; i++) result *= result; return (double)result; } /* Non-homogeneous Polynomial kernel k(x,z) = (x^T z + 1)^deg */ double polynomial_double(const double *a , const double *b , const long dim, const int deg) { int i; double result= 1.0 + dot_double(a,b,dim); for(i = 1; i < deg; i++) result *= result; return result; } double polynomial_float(const float *a , const float *b , const long dim, const int deg) { int i; // The dot product is computed with single precision floats double result = 1.0 + dot_float(a,b,dim); // But the power is computer with double precision for(i = 1; i < deg; i++) result *= result; return result; } double polynomial_int(const int *a , const int *b , const long dim, const int deg) { int i; long result = 1; for(i = 1; i<=dim; i++) result += a[i] * b[i]; for(i = 1; i < deg; i++) result *= result; return (double)result; } double polynomial_short_int(const short int *a , const short int *b , const long dim, const int deg) { int i; int result = 1; for(i = 1; i<=dim; i++) result += a[i] * b[i]; // could be vectorized in SSE2 for(i = 1; i < deg; i++) result *= result; return (double)result; } double polynomial_byte(const unsigned char *a , const unsigned char *b , const long dim, const int deg) { int i; int result = 1; for(i = 1; i<=dim; i++) result += a[i] * b[i]; for(i = 1; i < deg; i++) result *= result; return (double)result; } /* Linear kernel for BIT data k(x,z) = x^T z = sum (x[i] == z[i]) */ double dot_bit(const int *a, const int *b, const long dim) { long i=1; unsigned int res; int num_bits = 0; long true_dim = dim/32; if(dim%32 != 0) true_dim++; for(i=1;i<=true_dim ; i++) { res = a[i] & b[i]; num_bits += __builtin_popcount(res); // fast popcount on SSE4.2/SSE4a processors } return (double)num_bits; } /* Gaussian RBF kernel for BIT data with Hamming distance k(x,z) = exp(- (sum (x[i] != z[i]))^2 / 2 sigma^2 ) */ double rbf_bit(const int *a, const int *b, const long dim, const double sigma) { long i=1; unsigned int res; int dist = 0; long true_dim = dim/32; if(dim%32 != 0) true_dim++; for(i=1;i<=true_dim ; i++) { res = ~(a[i] & b[i]); dist += __builtin_popcount(res); } return exp( (double)( -dist * dist) / (2 * sigma * sigma)); } /* Homogeneous polynomial kernel for BIT data k(x,z) = (x^T z)^deg = (sum (x[i] == z[i]) )^deg */ double polynomial_homo_bit(const int *a, const int *b, const long dim, const int deg) { long i=1; unsigned int res; int num_bits = 0; long true_dim = dim/32; if(dim%32 != 0) true_dim++; for(i=1;i<=true_dim ; i++) { res = a[i] & b[i]; num_bits += __builtin_popcount(res); } for(i = 1; i < deg; i++) num_bits *= num_bits; return (double)num_bits; } /* Non-homogeneous polynomial kernel for BIT data */ double polynomial_bit(const int *a, const int *b, const long dim, const int deg) { long i=1; unsigned int res; int num_bits = 1; long true_dim = dim/32; if(dim%32 != 0) true_dim++; for(i=1;i<=true_dim ; i++) { res = a[i] & b[i]; num_bits += __builtin_popcount(res); } for(i = 1; i < deg; i++) num_bits *= num_bits; return (double)num_bits; } MSVMpack1.2/src/libMSVM.c0000644000175000017500000014057711705772166014160 0ustar lauerlauer/* MSVMpack - libMSVM.c General purpose functions for handling M-SVM models */ #include "libMSVM.h" #include "kernel.h" /* model_ptr = MSVM_make_model(type) Create an empty MSVM model of a given type (MSVM2, WW, CS, LLW) and returns a pointer to it or NULL in case of failure. */ struct Model *MSVM_make_model(enum MSVM_type type) { struct Model *model = (struct Model *)malloc(sizeof(struct Model)); if(model == NULL) return NULL; switch(type) { case MSVM2 : case WW : case CS : case LLW : model->version = VERSION; model->type = type; model->algorithm = FrankWolfe; model->nature_kernel = LINEAR; model->kernel_par = NULL; model->datatype = DOUBLE; model->Q = 0; model->C = NULL; model->training_error = 0.0; model->alpha = NULL; model->partial_average_alpha = NULL; model->b_SVM = NULL; model->training_set_name = NULL; model->X = NULL; model->y = NULL; model->normalization = NULL; model->W = NULL; model->X_double = NULL; model->X_float = NULL; model->X_int = NULL; model->X_short = NULL; model->X_byte = NULL; break; default : printf("\n Sorry, this type of M-SVM (%d) is not included in MSVMpack.\n",type); return NULL; } // Return the pointer to the created model return model; } /* MSVM_init_model(model_ptr, fichcom_file) Sets the parameters Q, C and nature_kernel from a file and returns chunk_size */ long MSVM_init_model(struct Model *model, char *com_file) { long k,chunk_size; unsigned int kernel_type; // Read com_file for hyperparameters FILE *fs; long nr = 0; if((fs=fopen(com_file, "r"))==NULL) { printf("\nFile of parameters %s cannot be open.\n", com_file); exit(0); } nr += fscanf(fs, "%ld", &(model->Q)); nr += fscanf(fs, "%d", &kernel_type); model->nature_kernel = kernel_type; set_default_kernel_par(model); model->C = (double*)realloc(model->C, sizeof(double) * (model->Q + 1)); for(k=1;k<=model->Q;k++) nr += fscanf(fs, "%lf", &(model->C[k])); if (fscanf(fs, "%ld", &chunk_size) == EOF) chunk_size = 0; // eval-type com_file, no chunk size if(nr < 3) printf("\nError in reading com file, not enough data.\n"); return chunk_size; } void allocate_model_data(struct Model *model, const long nb_data, const long dim_input) { // Data type can be deduced from the kernel type: switch(model->nature_kernel / 10) { case 1: model->datatype = FLOAT; break; case 2: model->datatype = INT; break; case 3: model->datatype = SHORT; break; case 4: model->datatype = BYTE; break; case 5: model->datatype = BIT; break; case 0: default: model->datatype = DOUBLE; break; } // Allocate the corresponding storage: switch (model->datatype) { case FLOAT: model->X_float = matrix_f_aligned(nb_data,dim_input); model->X = (void **)model->X_float; break; case INT: model->X_int = matrix_i_aligned(nb_data,dim_input); model->X = (void **)model->X_int; break; case SHORT: model->X_short = matrix_s_aligned(nb_data,dim_input); model->X = (void **)model->X_short; break; case BYTE: model->X_byte = matrix_b_aligned(nb_data,dim_input); model->X = (void **)model->X_byte; break; case BIT: model->X_int = matrix_i_aligned(nb_data,dim_input/32 + (dim_input%32 != 0) ); model->X = (void **)model->X_int; break; case DOUBLE: model->X_double = matrix_aligned(nb_data,dim_input); model->X = (void **)model->X_double; break; default: printf("Unknown data format in allocate_model_data().\n"); exit(1); } } void free_model_data(struct Model *model) { if(model->X_double != NULL) free_mat_aligned(model->X_double); if(model->X_float != NULL) free_mat_f_aligned(model->X_float); if(model->X_int != NULL) free_mat_i_aligned(model->X_int); if(model->X_short != NULL) free_mat_s_aligned(model->X_short); if(model->X_byte != NULL) free_mat_b_aligned(model->X_byte); model->X = NULL; } /* MSVM_delete_model(model_ptr) Delete the model pointed by model_ptr */ void MSVM_delete_model(struct Model *model) { if (model == NULL) return; switch(model->type) { case MSVM2 : case WW : case CS : case LLW : if(model->C != NULL) { free(model->C); } if(model->alpha != NULL) { free(model->alpha[1]); free(model->alpha); } if(model->partial_average_alpha != NULL) { free(model->partial_average_alpha); } if(model->b_SVM != NULL) { free(model->b_SVM); } if(model->normalization != NULL){ free(model->normalization[1]); free(model->normalization); } if(model->W != NULL) { free(model->W[1]); free(model->W); } if(model->training_set_name != NULL) { free(model->training_set_name); } if(model->kernel_par != NULL) { free(model->kernel_par); } break; default : printf("\n Unknown MSVM type. Nothing to delete.\n"); break; } free(model); return; } /* MSVM_delete_model_with_data(model_ptr) Delete the model pointed by model_ptr and the data in model_ptr->(X, y) */ void MSVM_delete_model_with_data(struct Model *model) { if (model == NULL) return; switch(model->type) { case MSVM2 : case WW : case CS : case LLW : if(model->C != NULL) { free(model->C); } if(model->alpha != NULL) { free(model->alpha[1]); free(model->alpha); } if(model->partial_average_alpha != NULL) { free(model->partial_average_alpha); } if(model->b_SVM != NULL) { free(model->b_SVM); } if(model->normalization != NULL){ free(model->normalization[1]); free(model->normalization); } if(model->W != NULL) { free(model->W[1]); free(model->W); } if(model->training_set_name != NULL) { free(model->training_set_name); } if(model->kernel_par != NULL) { free(model->kernel_par); } break; default : printf("\n Unknown MSVM type. Nothing to delete.\n"); break; } // Free data memory free_model_data(model); if(model->y != NULL) { free(model->y); } free(model); return; } /* Save an MSVM model to a file (with all training data as SVs) Returns the number of SVs written to model_file (0 usually means failure) */ int MSVM_save_model(const struct Model *model, char *model_file) { long i,k, dim_bit; long nb_data = model->nb_data; long dim_input = model->dim_input; long Q = model->Q; long nSV = 0; FILE *fp; char training_set[255]; if((fp=fopen(model_file, "w"))==NULL) { printf("\n Model file %s cannot be open.\n", model_file); return 0; } // Write model information fprintf(fp, "%1.1f\n",model->version); remove_spaces(model->training_set_name, training_set,255); fprintf(fp, "%d\n", model->type); fprintf(fp, "%ld\n", Q); fprintf(fp, "%d\n", model->nature_kernel); if(model->kernel_par != NULL) { fprintf(fp, "%d ", (int) (model->kernel_par[0])); for(i=1;i<=(int) (model->kernel_par[0]); i++) fprintf(fp, "%lf ", model->kernel_par[i]); fprintf(fp,"\n"); } else fprintf(fp, "0\n"); fprintf(fp, "%s\n", training_set); fprintf(fp, "%lf\n", model->training_error); fprintf(fp, "%ld\n", nb_data); fprintf(fp, "%ld\n", dim_input); for(k=1;k<=Q;k++) fprintf(fp, "%1.10lf ", model->C[k]); fprintf(fp, "\n"); // Write data normalization information if(model->normalization != NULL) { for(k=1;k<=dim_input;k++) fprintf(fp, "%1.10lf ", model->normalization[2][k]); // std fprintf(fp, "\n"); for(k=1;k<=dim_input;k++) fprintf(fp, "%1.10lf ", model->normalization[1][k]); // mean fprintf(fp, "\n"); } else { // Do not use data normalization fprintf(fp, "-1\n"); } // Write vector b if(model->type != CS) { for(k=1; k<=Q; k++) fprintf(fp, "%1.10lf ", model->b_SVM[k]); fprintf(fp,"\n"); } // True dimension for BIT data dim_bit = dim_input/32; if(dim_input%32) dim_bit++; // Write support vectors and corresponding alpha for(i=1; i <= nb_data; i++) { // Write [alpha_i1 ... alpha_iQ] for(k = 1; k <= Q; k++) { if(model->alpha[i][k] == 0.0) fprintf(fp,"0.0 "); else if (model->alpha[i][k] < 1e-8) fprintf(fp,"%1.10e ", model->alpha[i][k]); else fprintf(fp,"%1.10lf ", model->alpha[i][k]); } fprintf(fp, "\n"); // Write x_i switch(model->datatype) { case DOUBLE: for(k=1;k<=dim_input;k++) fprintf(fp,"%1.10lf ", model->X_double[i][k]); break; case FLOAT: for(k=1;k<=dim_input;k++) fprintf(fp,"%1.8f ", model->X_float[i][k]); break; case INT: for(k=1;k<=dim_input;k++) fprintf(fp,"%d ", model->X_int[i][k]); break; case SHORT: for(k=1;k<=dim_input;k++) fprintf(fp,"%hd ", model->X_short[i][k]); break; case BYTE: for(k=1;k<=dim_input;k++) fprintf(fp,"%hhu ", model->X_byte[i][k]); break; case BIT: // Write compressed format for(k=1;k<=dim_bit;k++) fprintf(fp,"%d ", model->X_int[i][k]); break; default: printf("Error in MSVM_model_save(): unknown data format (%d).\n",model->datatype); exit(1); } // Write y_i fprintf(fp, "%ld\n", model->y[i]); nSV++; } fclose(fp); return nSV; } /* Save only the SVs of an MSVM model to a file Returns the number of SVs written to model_file (0 usually means failure) */ int MSVM_save_model_sparse(const struct Model *model, char *model_file) { long i,k,dim_bit; long nb_data = model->nb_data; long dim_input = model->dim_input; long Q = model->Q; long nSV = 0; int is_SV; int linear_model = false; FILE *fp; char training_set[255]; if((fp=fopen(model_file, "w"))==NULL) { printf("\n Model file %s: cannot be open.\n", model_file); return 0; } if(model->nature_kernel == LINEAR && model->type == WW) linear_model = true; // Find the number of SVs if(linear_model) nSV = Q; else { for(i=1; i <= nb_data; i++) { if(model->type == CS) { for(k = 1; k <= Q; k++) if(k != model->y[i] && model->alpha[i][k] != 0.0) { nSV++; break; } } else { for(k = 1; k <= Q; k++) if(model->alpha[i][k] != 0.0) { nSV++; break; } } } } // Write model information fprintf(fp, "%1.1f\n",model->version); remove_spaces(model->training_set_name, training_set,255); fprintf(fp, "%d\n", model->type); fprintf(fp, "%ld\n", Q); fprintf(fp, "%d\n", model->nature_kernel); if(model->kernel_par != NULL) { fprintf(fp, "%d ", (int) (model->kernel_par[0])); for(i=1;i<=(int) (model->kernel_par[0]); i++) fprintf(fp, "%lf ", model->kernel_par[i]); fprintf(fp,"\n"); } else fprintf(fp, "0\n"); fprintf(fp, "%s\n", training_set); fprintf(fp, "%lf\n", model->training_error); fprintf(fp, "%ld\n", nSV); fprintf(fp, "%ld\n", dim_input); for(k=1;k<=Q;k++) fprintf(fp, "%1.10lf ", model->C[k]); fprintf(fp, "\n"); // Write data normalization information if(model->normalization != NULL) { for(k=1;k<=dim_input;k++) fprintf(fp, "%1.10lf ", model->normalization[2][k]); // std fprintf(fp, "\n"); for(k=1;k<=dim_input;k++) fprintf(fp, "%1.10lf ", model->normalization[1][k]); // mean fprintf(fp, "\n"); } else { // Do not use data normalization fprintf(fp, "-1\n"); } // Write vector b if(model->type != CS) { for(k=1; k<=Q; k++) fprintf(fp, "%1.10lf ", model->b_SVM[k]); fprintf(fp,"\n"); } // True dimension for BIT data dim_bit = dim_input/32; if(dim_input%32) dim_bit++; // Write support vectors and corresponding alpha if(linear_model) { nSV = 0; WW_compute_W(model); for(i=1; i<=Q; i++) { for(k = 1; k <= Q; k++) { if(i==k) fprintf(fp,"1.0 "); else fprintf(fp,"0.0 "); } for(k=1;k<=dim_input;k++) { fprintf(fp,"%1.10lf ", model->W[k][i]); } fprintf(fp,"%ld ", i); nSV++; } } else{ nSV = 0; for(i=1; i <= nb_data; i++) { is_SV = 0; if(model->type == CS) { for(k = 1; k <= Q; k++) if(k != model->y[i] && model->alpha[i][k] != 0.0) { is_SV = 1; break; } } else { for(k = 1; k <= Q; k++) if(model->alpha[i][k] != 0.0) { is_SV = 1; break; } } if(is_SV) { // Write [alpha_i1 ... alpha_iQ] for(k = 1; k <= Q; k++) { if(model->alpha[i][k] == 0.0) fprintf(fp,"0.0 "); else if (model->alpha[i][k] < 1e-8) fprintf(fp,"%1.10e ", model->alpha[i][k]); else fprintf(fp,"%1.10lf ", model->alpha[i][k]); } fprintf(fp, "\n"); // Write x_i switch(model->datatype) { case FLOAT: for(k=1;k<=dim_input;k++) fprintf(fp,"%1.8f ", model->X_float[i][k]); break; case INT: for(k=1;k<=dim_input;k++) fprintf(fp,"%d ", model->X_int[i][k]); break; case SHORT: for(k=1;k<=dim_input;k++) fprintf(fp,"%hd ", model->X_short[i][k]); break; case BYTE: for(k=1;k<=dim_input;k++) fprintf(fp,"%hhu ", model->X_byte[i][k]); break; case BIT: // Write compressed format for(k=1;k<=dim_bit;k++) fprintf(fp,"%d ", model->X_int[i][k]); break; case DOUBLE: default: for(k=1;k<=dim_input;k++) fprintf(fp,"%1.10lf ", model->X_double[i][k]); break; } // Write y_i fprintf(fp, "%ld\n", model->y[i]); nSV++; } } } fclose(fp); return nSV; } /* Load an MSVM model from a file */ struct Model *MSVM_load_model(char *model_file) { long i,k, nb_data, Q, dim_input, dim_bit; double alpha,normalization; FILE *fp; long nr=0; float version; unsigned int type, kernel_type; char buffer[200]; int n_kernel_par; if((fp=fopen(model_file, "r"))==NULL) { printf("\n Model file %s cannot be open.\n", model_file); return NULL; } struct Model *model = (struct Model *)malloc(sizeof(struct Model)); if(model == NULL) return NULL; nr += fscanf(fp, "%s", buffer); if(strlen(buffer) < 3 ){ version = 1.0; // no version number = version 1.0 type = atoi(buffer); } else { version = atof(buffer); nr += fscanf(fp, "%d", &type); } model->version = version; model->type = type; model->algorithm = FrankWolfe; // default back to Frank-Wolfe method // use -o 1 to retrain with Rosen's method nr += fscanf(fp, "%ld", &Q); model->Q = Q; nr += fscanf(fp, "%d", &kernel_type); model->nature_kernel = kernel_type; nr += fscanf(fp, "%d", &n_kernel_par); model->kernel_par = (double *)malloc(sizeof(double) * (n_kernel_par + 1)); model->kernel_par[0] = (double)n_kernel_par; for(i=1;i<=n_kernel_par;i++) nr += fscanf(fp, "%lf", &(model->kernel_par[i])); nr += fscanf(fp,"%s", buffer); model->training_set_name = (char*)malloc(sizeof(char) * (strlen(buffer) + 1)); strcpy(model->training_set_name, buffer); nr += fscanf(fp, "%lf", &(model->training_error)); nr += fscanf(fp, "%ld", &nb_data); model->nb_data = nb_data; nr += fscanf(fp, "%ld", &dim_input); model->dim_input = dim_input; dim_bit = dim_input/32; // true dimension for BIT data if(dim_input%32) dim_bit++; // C hyperparameters model->C = (double*) malloc(sizeof(double) * (Q+1)); if (version > 1.0) { for(k=1;k<=Q;k++) nr += fscanf(fp, "%lf", &(model->C[k])); } else { nr += fscanf(fp, "%lf", &(model->C[1])); for(k=2;k<=Q;k++) model->C[k] = model->C[1]; } nr += fscanf(fp, "%lf", &normalization); if(nr < 10){ printf("Error, cannot read model file %s.\n",model_file); exit(0); } if(normalization >= 0.0) { model->normalization = matrix(2,dim_input); model->normalization[2][1] = normalization; for(k=2;k<=dim_input;k++) nr = fscanf(fp, "%lf", &(model->normalization[2][k])); for(k=1;k<=dim_input;k++) nr = fscanf(fp, "%lf", &(model->normalization[1][k])); } else model->normalization = NULL; nr = 0; // Model file format could change with MSVM type // The following loads the model accordingly switch(type) { case MSVM2 : // Allocate memory for model parameters model->alpha = matrix(nb_data,Q); model->partial_average_alpha = (double *) malloc(sizeof(double) * (nb_data+1)); model->b_SVM = (double *)malloc((Q+1) * sizeof(double)); // Allocate model->X and set model->datatype allocate_model_data(model, nb_data, dim_input); model->y = (long*)malloc(sizeof(long) * (nb_data+1)); // Read b for(k=1; k<=Q; k++) nr += fscanf(fp, "%lf", &(model->b_SVM[k])); for(i=1; i <= nb_data; i++) { model->partial_average_alpha[i] = 0.0; // Read [alpha_i1 ... alpha_iQ] for(k = 1; k <= Q; k++) { nr += fscanf(fp, "%lf", &alpha); model->alpha[i][k] = alpha; model->sum_all_alpha += alpha; model->partial_average_alpha[i] += alpha; } model->partial_average_alpha[i] /= Q; // Read x_i switch (model->datatype) { case DOUBLE: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%lf", &(model->X_double[i][k])); break; case FLOAT: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%f", &(model->X_float[i][k])); break; case INT: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%d", &(model->X_int[i][k])); break; case SHORT: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%hd", &(model->X_short[i][k])); break; case BYTE: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%hhu", &(model->X_byte[i][k])); break; case BIT: // Load compressed format for(k=1;k<=dim_bit;k++) nr += fscanf(fp, "%d", &(model->X_int[i][k])); break; default: printf("Error: unknown data format (%d) in MSVM_load_model().\n",model->datatype); exit(1); } // Read y_i nr += fscanf(fp, "%ld", &(model->y[i])); } if((model->datatype != BIT && nr < Q+(Q+dim_input+1)*nb_data) || (model->datatype == BIT && nr < Q+(Q+dim_bit+1)*nb_data)) printf("\nError in reading model file, not enough data.\n"); break; case WW : // Allocate memory for model parameters model->alpha = matrix(nb_data,Q); model->b_SVM = (double *)malloc((Q+1) * sizeof(double)); // Allocate model->X and set model->datatype allocate_model_data(model, nb_data, dim_input); model->y = (long*)malloc(sizeof(long) * (nb_data+1)); // Read b for(k=1; k<=Q; k++) nr += fscanf(fp, "%lf", &(model->b_SVM[k])); for(i=1; i <= nb_data; i++) { // Read [alpha_i1 ... alpha_iQ] for(k = 1; k <= Q; k++) { nr += fscanf(fp, "%lf", &alpha); model->alpha[i][k] = alpha; model->sum_all_alpha += alpha; } // Read x_i switch (model->datatype) { case DOUBLE: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%lf", &(model->X_double[i][k])); break; case FLOAT: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%f", &(model->X_float[i][k])); break; case INT: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%d", &(model->X_int[i][k])); break; case SHORT: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%hd", &(model->X_short[i][k])); break; case BYTE: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%hhu", &(model->X_byte[i][k])); break; case BIT: // Load compressed format for(k=1;k<=dim_bit;k++) nr += fscanf(fp, "%d", &(model->X_int[i][k])); break; default: printf("Error: unknown data format (%d) in MSVM_load_model().\n",model->datatype); exit(1); } // Read y_i nr += fscanf(fp, "%ld", &(model->y[i])); } if((model->datatype != BIT && nr < Q+(Q+dim_input+1)*nb_data) || (model->datatype == BIT && nr < Q+(Q+dim_bit+1)*nb_data)) printf("\nError in reading model file, not enough data.\n"); break; case CS : // Allocate memory for model parameters model->alpha = matrix(nb_data,Q); // Allocate model->X and set model->datatype allocate_model_data(model, nb_data, dim_input); model->y = (long*)malloc(sizeof(long) * (nb_data+1)); for(i=1; i <= nb_data; i++) { // Read [alpha_i1 ... alpha_iQ] for(k = 1; k <= Q; k++) { nr += fscanf(fp, "%lf", &alpha); model->alpha[i][k] = alpha; model->sum_all_alpha += alpha; } // Read x_i switch (model->datatype) { case DOUBLE: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%lf", &(model->X_double[i][k])); break; case FLOAT: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%f", &(model->X_float[i][k])); break; case INT: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%d", &(model->X_int[i][k])); break; case SHORT: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%hd", &(model->X_short[i][k])); break; case BYTE: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%hhu", &(model->X_byte[i][k])); break; case BIT: // Load compressed format for(k=1;k<=dim_bit;k++) nr += fscanf(fp, "%d", &(model->X_int[i][k])); break; default: printf("Error: unknown data format (%d) in MSVM_load_model().\n",model->datatype); exit(1); } // Read y_i nr += fscanf(fp, "%ld", &(model->y[i])); } if((model->datatype != BIT && nr < (Q+dim_input+1)*nb_data) || (model->datatype == BIT && nr < (Q+dim_bit+1)*nb_data)) printf("\nError in reading model file, not enough data.\n"); break; case LLW : // Allocate memory for model parameters model->alpha = matrix(nb_data,Q); model->b_SVM = (double *)malloc((Q+1) * sizeof(double)); // Allocate model->X and set model->datatype allocate_model_data(model, nb_data, dim_input); model->y = (long*)malloc(sizeof(long) * (nb_data+1)); // Read b for(k=1; k<=Q; k++) nr += fscanf(fp, "%lf", &(model->b_SVM[k])); for(i=1; i <= nb_data; i++) { // Read [alpha_i1 ... alpha_iQ] for(k = 1; k <= Q; k++) { nr += fscanf(fp, "%lf", &alpha); model->alpha[i][k] = alpha; model->sum_all_alpha += alpha; } // Read x_i switch (model->datatype) { case DOUBLE: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%lf", &(model->X_double[i][k])); break; case FLOAT: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%f", &(model->X_float[i][k])); break; case INT: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%d", &(model->X_int[i][k])); break; case SHORT: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%hd", &(model->X_short[i][k])); break; case BYTE: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%hhu", &(model->X_byte[i][k])); break; case BIT: // Load compressed format for(k=1;k<=dim_bit;k++) nr += fscanf(fp, "%d", &(model->X_int[i][k])); break; default: printf("Error: unknown data format (%d) in MSVM_load_model().\n",model->datatype); exit(1); } // Read y_i nr += fscanf(fp, "%ld", &(model->y[i])); } if((model->datatype != BIT && nr < Q+(Q+dim_input+1)*nb_data) || (model->datatype == BIT && nr < Q+(Q+dim_bit+1)*nb_data)) printf("\nError in reading model file, not enough data.\n"); break; default : printf("Unknown MSVM model type in file %s . \n", model_file); return NULL; break; } fclose(fp); return model; } /* Load a dataset into a model */ void model_load_data(struct Model *model, const struct Data *training_set) { long k; if(training_set->name != NULL) { model->training_set_name = (char *)malloc(sizeof(char) * (strlen(training_set->name) + 1)); strcpy(model->training_set_name, training_set->name); } model->nb_data = training_set->nb_data; model->dim_input = training_set->dim; model->y = training_set->y; model->Q = training_set->Q; if(model->C == NULL) { model->C = (double*)malloc(sizeof(double) * (model->Q + 1)); for (k=1;k<=model->Q;k++) model->C[k] = DEFAULT_C; } model->datatype = training_set->datatype; switch(model->datatype) { case DOUBLE: model->X_double = training_set->X_double; break; case FLOAT: model->X_float = training_set->X_float; break; case INT: model->X_int = training_set->X_int; break; case SHORT: model->X_short = training_set->X_short; break; case BYTE: model->X_byte = training_set->X_byte; break; case BIT: model->X_int = training_set->X_int; break; default: printf("Error: Unknown training set data format (%d).\n",model->datatype); exit(1); break; } model->X = training_set->X; } /* dataset_ptr = MSVM_make_dataset(data_file) Create an empty dataset and load data from data_file if data_file is not NULL */ struct Data *MSVM_make_dataset(char *data_file, enum Datatype datatype) { struct Data *dataset = (struct Data *)malloc(sizeof(struct Data)); if(dataset != NULL) { dataset->name = NULL; dataset->X = NULL; dataset->y = NULL; dataset->dim = 0; dataset->nb_data = 0; dataset->Q = 0; dataset->X_double = NULL; dataset->X_float = NULL; dataset->X_int = NULL; dataset->X_short = NULL; dataset->X_byte = NULL; } if(data_file != NULL) { dataset->name = (char *)malloc(sizeof(char) * (strlen(data_file)+1)); strcpy(dataset->name, data_file); dataset->Q = read_data(dataset, datatype, data_file); } // Return the pointer to the created dataset return dataset; } void free_dataset_data(struct Data *dataset) { if(dataset->X_double != NULL) free_mat_aligned(dataset->X_double); if(dataset->X_float != NULL) free_mat_f_aligned(dataset->X_float); if(dataset->X_int != NULL) free_mat_i_aligned(dataset->X_int); if(dataset->X_short != NULL) free_mat_s_aligned(dataset->X_short); if(dataset->X_byte != NULL) free_mat_b_aligned(dataset->X_byte); dataset->X = NULL; } /* MSVM_delete_dataset(dataset_ptr) Delete a dataset */ void MSVM_delete_dataset(struct Data *dataset) { if(dataset == NULL) return; if(dataset->name != NULL) { free(dataset->name); } if(dataset->y != NULL) { free(dataset->y); } free_dataset_data(dataset); free(dataset); return; } /* Normalize a dataset by setting the mean and std of all columns of X to 0 and 1 or according to an already defined model->normalization and returns the difference between the largest and smallest std. On output, model->normalization[1][j] contains the mean of the jth column and model->normalization[2][j] contains the std of the jth column. If model is NULL the data are left unnormalized (this can be used to check if normalization is needed). */ double MSVM_normalize_data(struct Data *dataset, struct Model *model) { if(dataset == NULL) return 0; const long nb_data = dataset->nb_data; const long dim = dataset->dim; double **X = dataset->X_double; float **Xf = dataset->X_float; long i,j; double mean,std, large_std=0, small_std=0; int compute_mean_std = 1; switch(dataset->datatype) { case FLOAT: if(model != NULL) { if(model->normalization == NULL) model->normalization = matrix(2,dim); else compute_mean_std = 0; } if(compute_mean_std) { // Compute mean and std before normalizing for(j=1;j<=dim;j++) { mean = 0.; std = 0.; for(i=1;i<=nb_data; i++) { mean += (double)Xf[i][j]; std += (double)Xf[i][j]*Xf[i][j]; } mean /= (double)nb_data; std = sqrt( (std/(double)nb_data) - mean*mean); if(j==1 || std > large_std) large_std = std; if(j==1 || std < small_std) small_std = std; if(std == 0.0) printf("Warning: std of feature #%ld = 0\n",j); if (model != NULL && std > 0.0) { // Do normalize for(i=1;i<=nb_data; i++) { Xf[i][j] = (Xf[i][j] - (float)mean) / (float)std; } model->normalization[1][j] = mean; model->normalization[2][j] = std; } } } else { // Use given normalization coefficients for(i=1;i<=nb_data; i++) { for(j=1;j<=dim;j++) if(model->normalization[2][j] != 0.0) Xf[i][j] = (Xf[i][j] - (float)model->normalization[1][j]) / (float)model->normalization[2][j]; } } break; case INT: return 0; break; case SHORT: return 0; break; case BYTE: return 0; break; case BIT: return 0; break; case DOUBLE: default: if(model != NULL) { if(model->normalization == NULL) model->normalization = matrix(2,dim); else compute_mean_std = 0; } if(compute_mean_std) { // Compute mean and std before normalizing for(j=1;j<=dim;j++) { mean = 0.; std = 0.; for(i=1;i<=nb_data; i++) { mean += X[i][j]; std += X[i][j]*X[i][j]; } mean /= (double)nb_data; std = sqrt( (std/(double)nb_data) - mean*mean); if(j==1 || std > large_std) large_std = std; if(j==1 || std < small_std) small_std = std; if(std == 0.0) printf("Warning: std of feature #%ld = 0\n",j); if (model != NULL && std > 0.0) { // Do normalize for(i=1;i<=nb_data; i++) { X[i][j] = (X[i][j] - mean) / std; } model->normalization[1][j] = mean; model->normalization[2][j] = std; } } } else { // Use given normalization coefficients for(i=1;i<=nb_data; i++) { for(j=1;j<=dim;j++) if(model->normalization[2][j] != 0.0) { X[i][j] = (X[i][j] - model->normalization[1][j]) / model->normalization[2][j]; } } } break; } return (large_std - small_std); } /* Load a dataset from a file Returns the number of classes computed as max(y_i) */ long read_data(struct Data *dataset, enum Datatype datatype, char *data_file) { FILE *fs; long i,j,nb_data,dim_input; double value_y,value_X; float value_yf,value_Xf; int value_yi,value_Xi; short int value_Xs; unsigned char value_Xb; long Q=0; long min_y = 1000; char buf[taille]; long nr = 0; long dim; if((fs=fopen(data_file, "r"))==NULL) { printf("\nFile of data %s cannot be open.\n", data_file); exit(0); } nr += fscanf(fs, "%ld", &nb_data); nr += fscanf(fs, "%ld", &dim_input); switch(datatype) { case FLOAT: // (Re)allocate memory free_dataset_data(dataset); dataset->X_float = matrix_f_aligned(nb_data, dim_input); // Read first line with data for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%f", &value_Xf); dataset->X_float[1][j] = value_Xf; } // Check if there is a label at the end of the line if(fgets(buf, taille, fs) == NULL) { printf("Error while reading data file.\n"); exit(1); } if(sscanf(buf, "%f", &value_yf) > 0) { dataset->y = (long *) realloc(dataset->y, (nb_data+1) * sizeof(long)); dataset->y[1] = (long) value_yf; } else if (dataset->y != NULL) { free(dataset->y); dataset->y = NULL; } // Read the rest of the file for(i=2; i<=nb_data; i++) { for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%f", &value_Xf); dataset->X_float[i][j] = value_Xf; } if(dataset->y != NULL) { nr += fscanf(fs, "%f", &value_yf); dataset->y[i] = (long) value_yf; if(dataset->y[i] > Q) Q = dataset->y[i]; if(dataset->y[i] < min_y) min_y = dataset->y[i]; } } // Set X to point to the FLOAT storage dataset->X = (void**)dataset->X_float; break; case INT: // (Re)allocate memory free_dataset_data(dataset); dataset->X_int = matrix_i(nb_data, dim_input); // Read first line with data for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%d", &value_Xi); dataset->X_int[1][j] = value_Xi; } // Check if there is a label at the end of the line if(fgets(buf, taille, fs) == NULL) { printf("Error while reading data file.\n"); exit(1); } if(sscanf(buf, "%d", &value_yi) > 0) { dataset->y = (long *) realloc(dataset->y, (nb_data+1) * sizeof(long)); dataset->y[1] = (long) value_yi; } else if (dataset->y != NULL) { free(dataset->y); dataset->y = NULL; } // Read the rest of the file for(i=2; i<=nb_data; i++) { for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%d", &value_Xi); dataset->X_int[i][j] = value_Xi; } if(dataset->y != NULL) { nr += fscanf(fs, "%d", &value_yi); dataset->y[i] = (long) value_yi; if(dataset->y[i] > Q) Q = dataset->y[i]; if(dataset->y[i] < min_y) min_y = dataset->y[i]; } } // Set X to point to the INT storage dataset->X = (void**)dataset->X_int; break; case SHORT: // (Re)allocate memory free_dataset_data(dataset); dataset->X_short = matrix_s_aligned(nb_data, dim_input); // Read first line with data for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%hd", &value_Xs); dataset->X_short[1][j] = value_Xs; } // Check if there is a label at the end of the line if(fgets(buf, taille, fs) == NULL) { printf("Error while reading data file.\n"); exit(1); } if(sscanf(buf, "%d", &value_yi) > 0) { dataset->y = (long *) realloc(dataset->y, (nb_data+1) * sizeof(long)); dataset->y[1] = (long) value_yi; } else if (dataset->y != NULL) { free(dataset->y); dataset->y = NULL; } // Read the rest of the file for(i=2; i<=nb_data; i++) { for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%hd", &value_Xs); dataset->X_short[i][j] = value_Xs; } if(dataset->y != NULL) { nr += fscanf(fs, "%d", &value_yi); dataset->y[i] = (long) value_yi; if(dataset->y[i] > Q) Q = dataset->y[i]; if(dataset->y[i] < min_y) min_y = dataset->y[i]; } } // Set X to point to the INT storage dataset->X = (void**)dataset->X_short; break; case BYTE: // (Re)allocate memory free_dataset_data(dataset); dataset->X_byte = matrix_b_aligned(nb_data, dim_input); // Read first line with data for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%hhu", &value_Xb); dataset->X_byte[1][j] = value_Xb; } // Check if there is a label at the end of the line if(fgets(buf, taille, fs) == NULL) { printf("Error while reading data file.\n"); exit(1); } if(sscanf(buf, "%d", &value_yi) > 0) { dataset->y = (long *) realloc(dataset->y, (nb_data+1) * sizeof(long)); dataset->y[1] = (long) value_yi; } else if (dataset->y != NULL) { free(dataset->y); dataset->y = NULL; } // Read the rest of the file for(i=2; i<=nb_data; i++) { for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%hhu", &value_Xb); dataset->X_byte[i][j] = value_Xb; } if(dataset->y != NULL) { nr += fscanf(fs, "%d", &value_yi); dataset->y[i] = (long) value_yi; if(dataset->y[i] > Q) Q = dataset->y[i]; if(dataset->y[i] < min_y) min_y = dataset->y[i]; } } // Set X to point to the INT storage dataset->X = (void**)dataset->X_byte; break; case BIT: /* BIT data are loaded in INT storage (32 bits per int, completed with zeros) */ // How many INT needed to store the BITS ? dim = dim_input/32; if (dim_input%32 != 0) dim++; long j_int=0; unsigned int mask; // (Re)allocate memory free_dataset_data(dataset); dataset->X_int = matrix_i_aligned(nb_data, dim); // Read first line with data for(j=1; j<=dim_input; j++) { if(j%32 == 1) { j_int++; dataset->X_int[1][j_int] = 0; } nr += fscanf(fs, "%d", &value_Xi); if(value_Xi) { mask = 0x1; mask <<= (j%32) - 1; dataset->X_int[1][j_int] |= mask; } } // Fill in rest of row with zeros for (j=0; j< 4 - j_int;j++ ) { dataset->X_int[1][j_int] = 0; } // Check if there is a label at the end of the line if(fgets(buf, taille, fs) == NULL) { printf("Error while reading data file.\n"); exit(1); } if(sscanf(buf, "%d", &value_yi) > 0) { dataset->y = (long *) realloc(dataset->y, (nb_data+1) * sizeof(long)); dataset->y[1] = (long) value_yi; } else if (dataset->y != NULL) { free(dataset->y); dataset->y = NULL; } // Read the rest of the file for(i=2; i<=nb_data; i++) { j_int = 0; for(j=1; j<=dim_input; j++) { if(j%32 == 1) { j_int++; dataset->X_int[i][j_int] = 0; } nr += fscanf(fs, "%d", &value_Xi); if(value_Xi) { mask = 0x1; mask <<= (j%32) - 1; dataset->X_int[i][j_int] |= mask; } } // Fill in rest of row with zeros for (j=0; j< 4 - j_int;j++ ) { dataset->X_int[1][j_int] = 0; } if(dataset->y != NULL) { nr += fscanf(fs, "%d", &value_yi); dataset->y[i] = (long) value_yi; if(dataset->y[i] > Q) Q = dataset->y[i]; if(dataset->y[i] < min_y) min_y = dataset->y[i]; } } // Set X to point to the INT storage dataset->X = (void**)dataset->X_int; break; case DOUBLE: default: // (Re)allocate memory free_dataset_data(dataset); dataset->X_double = matrix_aligned(nb_data, dim_input); // Read first line with data for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%lf", &value_X); dataset->X_double[1][j] = value_X; } // Check if there is a label at the end of the line if(fgets(buf, taille, fs) == NULL) { printf("Error while reading data file.\n"); exit(1); } if(sscanf(buf, "%lf", &value_y) > 0) { dataset->y = (long *) realloc(dataset->y, (nb_data+1) * sizeof(long)); dataset->y[1] = (long) value_y; } else if (dataset->y != NULL) { free(dataset->y); dataset->y = NULL; } // Read the rest of the file for(i=2; i<=nb_data; i++) { for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%lf", &value_X); dataset->X_double[i][j] = value_X; } if(dataset->y != NULL) { nr += fscanf(fs, "%lf", &value_y); dataset->y[i] = (long) value_y; if(dataset->y[i] > Q) Q = dataset->y[i]; if(dataset->y[i] < min_y) min_y = dataset->y[i]; } } // Set X to point to the DOUBLE storage dataset->X = (void**)dataset->X_double; datatype = DOUBLE; break; } fclose(fs); // Labels must be in the range [1,Q] if( min_y == 0 ) { for(i=1; i<=nb_data; i++) dataset->y[i]++; Q++; } else if (min_y < 0) { printf("\nWrong numbering of the categories in %s, minimal value is: %ld\n", data_file, min_y); exit(0); } if((datatype != BIT && nr < dim_input * nb_data) || (datatype == BIT && nr < dim * nb_data)) printf("\nError in reading file %s, not enough data.\n", data_file); // Set the dimensions of the dataset dataset->nb_data = nb_data; dataset->dim = dim_input; dataset->datatype = datatype; return Q; } /* Load alpha from a file into a model and returns the maximum value of alpha */ double read_alpha(struct Model *model, char *alpha_file) { FILE *fs; long nr = 0; long i,k; long Q = model->Q; long nb_data = model->nb_data; double alpha, max_alpha=0.0; model->sum_all_alpha = 0; if((fs=fopen(alpha_file, "r"))==NULL) { printf("\nError: File of dual variables %s cannot be open.\n", alpha_file); exit(0); } if (model->alpha != NULL) { free(model->alpha[1]); free(model->alpha); } model->alpha = matrix(nb_data, Q); model->partial_average_alpha = (double *) realloc(model->partial_average_alpha, sizeof(double) * (nb_data+1)); for(i=1; i<=nb_data; i++) { model->partial_average_alpha[i] = 0.0; for(k=1; k<=Q; k++) { nr += fscanf(fs, "%lf", &alpha); model->alpha[i][k] = alpha; model->sum_all_alpha += alpha; model->partial_average_alpha[i] += alpha; if(alpha > max_alpha) max_alpha = alpha; } model->partial_average_alpha[i] /= Q; } fclose(fs); if(nr < Q*nb_data) printf("\nError in reading alpha file %s, not enough data.\n", alpha_file); return max_alpha; } /* Converts a string to an MSVM type */ enum MSVM_type str2model_type(char *str) { enum MSVM_type type; if(strcmp(str, "MSVM2") == 0) type = MSVM2; else if (strcmp(str, "WW") == 0) type = WW; else if (strcmp(str, "CS") == 0) type = CS; else if (strcmp(str, "LLW") == 0) type = LLW; else { printf("\nWarning: -m argument is not in the list of known MSVM types"); printf("\n (WW, CS, LLW, MSVM2). Falling back to MSVM2. \n"); type = MSVM2; } return type; } /* k = ker(kernel_type, x1, x2, dim, kernel_par) General wrapper for the kernel functions (which are defined in kernel.c) */ double ker(const enum Kernel_type type, const void *x1, const void *x2, const long dim, const double *par) { double res; switch(type) { case LINEAR: res = dot_double((double *) x1, (double *) x2, dim); break; case RBF: res = rbf_double((double *) x1, (double *) x2, dim, par[1]); break; case POLY_H: res = polynomial_homo_double((double *) x1, (double *) x2, dim, (int)par[1]); break; case POLY: res = polynomial_double((double *) x1, (double *) x2, dim, (int)par[1]); break; case CUSTOM1: res = custom_kernel_1((double *) x1, (double *) x2, dim, par); break; case CUSTOM2: res = custom_kernel_2((double *) x1, (double *) x2, dim, par); break; case CUSTOM3: res = custom_kernel_3((double *) x1, (double *) x2, dim, par); break; // Kernel functions for FLOAT data type case LINEAR_FLOAT: res = dot_float((float *) x1, (float *) x2, dim); break; case RBF_FLOAT: res = rbf_float((float *) x1, (float *) x2, dim, par[1]); break; case POLY_H_FLOAT: res = polynomial_homo_float((float *) x1, (float *) x2, dim, (int)par[1]); break; case POLY_FLOAT: res = polynomial_float((float *) x1, (float *) x2, dim, (int)par[1]); break; case CUSTOM1_FLOAT: res = custom_kernel_1_float((float *) x1, (float *) x2, dim, par); break; case CUSTOM2_FLOAT: res = custom_kernel_2_float((float *) x1, (float *) x2, dim, par); break; case CUSTOM3_FLOAT: res = custom_kernel_3_float((float *) x1, (float *) x2, dim, par); break; // Kernel functions for INT data type case LINEAR_INT: res = dot_int((int *) x1, (int *) x2, dim); break; case RBF_INT: res = rbf_int((int *) x1, (int *) x2, dim, par[1]); break; case POLY_H_INT: res = polynomial_homo_int((int *) x1, (int *) x2, dim, (int)par[1]); break; case POLY_INT: res = polynomial_int((int *) x1, (int *) x2, dim, (int)par[1]); break; case CUSTOM1_INT: res = custom_kernel_1_int((int *) x1, (int *) x2, dim, par); break; case CUSTOM2_INT: res = custom_kernel_2_int((int *) x1, (int *) x2, dim, par); break; case CUSTOM3_INT: res = custom_kernel_3_int((int *) x1, (int *) x2, dim, par); break; // Kernel functions for SHORT INT data type case LINEAR_SHORT: res = dot_short_int((short int *) x1, (short int *) x2, dim); break; case RBF_SHORT: res = rbf_short_int((short int *) x1, (short int *) x2, dim, par[1]); break; case POLY_H_SHORT: res = polynomial_homo_short_int((short int *) x1, (short int *) x2, dim, (int)par[1]); break; case POLY_SHORT: res = polynomial_short_int((short int *) x1, (short int *) x2, dim, (int)par[1]); break; case CUSTOM1_SHORT: res = custom_kernel_1_short_int((short int *) x1, (short int *) x2, dim, par); break; case CUSTOM2_SHORT: res = custom_kernel_2_short_int((short int *) x1, (short int *) x2, dim, par); break; case CUSTOM3_SHORT: res = custom_kernel_3_short_int((short int *) x1, (short int *) x2, dim, par); break; // Kernel functions for BYTE data type case LINEAR_BYTE: res = dot_byte((unsigned char *) x1, (unsigned char *) x2, dim); break; case RBF_BYTE: res = rbf_byte((unsigned char *) x1, (unsigned char *) x2, dim, par[1]); break; case POLY_H_BYTE: res = polynomial_homo_byte((unsigned char *) x1, (unsigned char *) x2, dim, (int)par[1]); break; case POLY_BYTE: res = polynomial_byte((unsigned char *) x1, (unsigned char *) x2, dim, (int)par[1]); break; case CUSTOM1_BYTE: res = custom_kernel_1_byte((unsigned char *) x1, (unsigned char *) x2, dim, par); break; case CUSTOM2_BYTE: res = custom_kernel_2_byte((unsigned char *) x1, (unsigned char *) x2, dim, par); break; case CUSTOM3_BYTE: res = custom_kernel_3_byte((unsigned char *) x1, (unsigned char *) x2, dim, par); break; // Kernel functions for BIT data type case LINEAR_BIT: res = dot_bit((int *) x1, (int *) x2, dim); break; case RBF_BIT: res = rbf_bit((int *) x1, (int *) x2, dim, par[1]); break; case POLY_H_BIT: res = polynomial_homo_bit((int *) x1, (int *) x2, dim, (int)par[1]); break; case POLY_BIT: res = polynomial_bit((int *) x1, (int *) x2, dim, (int)par[1]); break; case CUSTOM1_BIT: res = custom_kernel_1_bit((int *) x1, (int *) x2, dim, par); break; case CUSTOM2_BIT: res = custom_kernel_2_bit((int *) x1, (int *) x2, dim, par); break; case CUSTOM3_BIT: res = custom_kernel_3_bit((int *) x1, (int *) x2, dim, par); break; default: printf("\n\nUnknown kernel type (%d).\n\n", type); exit(0); } return res; } /* Set default kernel parameter values See kernel.h for the definition of these values */ void set_default_kernel_par(struct Model *model) { enum Kernel_type kernel_type = model->nature_kernel; // Use same defaults for DOUBLE, FLOAT, INT... data types kernel_type %= 10; // But different defaults depending on the kernel type switch (kernel_type) { case LINEAR: model->kernel_par = NULL; break; case RBF: model->kernel_par = (double*)realloc(model->kernel_par, sizeof(double) * 2); model->kernel_par[0] = 1; model->kernel_par[1] = DEFAULT_RBF_KERNEL_PAR; break; case POLY_H: model->kernel_par = (double*)realloc(model->kernel_par, sizeof(double) * 2); model->kernel_par[0] = 1; model->kernel_par[1] = DEFAULT_POLY_KERNEL_PAR; break; case POLY: model->kernel_par = (double*)realloc(model->kernel_par, sizeof(double) * 2); model->kernel_par[0] = 1; model->kernel_par[1] = DEFAULT_POLY_KERNEL_PAR; break; case CUSTOM1: model->kernel_par = (double*)realloc(model->kernel_par, sizeof(double) * 2); model->kernel_par[0] = 1; model->kernel_par[1] = DEFAULT_CUSTOM_KERNEL_1_PAR; break; case CUSTOM2: model->kernel_par = (double*)realloc(model->kernel_par, sizeof(double) * 2); model->kernel_par[0] = 1; model->kernel_par[1] = DEFAULT_CUSTOM_KERNEL_2_PAR; break; case CUSTOM3: model->kernel_par = (double*)realloc(model->kernel_par, sizeof(double) * 2); model->kernel_par[0] = 1; model->kernel_par[1] = DEFAULT_CUSTOM_KERNEL_3_PAR; break; default: // do nothing for an unknown kernel break; } } /* Set the values of C_k in a model to C for the Q classes also set Q in the model */ void MSVM_model_set_C(double C, long Q, struct Model *model) { long k; model->C = (double*) realloc(model->C, sizeof(double) * (Q+1) ); for(k=1;k<=Q;k++) { model->C[k] = C; } model->Q = Q; } /* Access typed data in model as a double This function should not be used for intensive computations */ double model_get_Xij(struct Model *model, const long i, const long j) { int x_bit; unsigned int mask; switch(model->datatype) { case DOUBLE: return model->X_double[i][j]; case FLOAT: return (double)model->X_float[i][j]; case INT: return (double)model->X_int[i][j]; case SHORT: return (double)model->X_short[i][j]; case BYTE: return (double)model->X_byte[i][j]; case BIT: x_bit = model->X_int[i][j/32]; mask = 0x1; mask <<= j%32; return (double)(x_bit & mask); default: printf("Cannot access model->X[i][j] with unknown data type in model.\n"); exit(0); } } /* Ex.: i = check_argv(argc,argv,".model") Check if any argument of the command line contains ".model" and returns the corresponding index of argv. Returns 0 if ".model" cannot be found. */ int check_argv(int argc, char *argv[], char *str) { int i; int arg_str = 0; for(i = 1; i < argc; i++) if(strstr(argv[i], str) != NULL ) { arg_str = i; break; } return arg_str; } /* Ex.: i = check_argv_eq(argc,argv,"-f") Check if any argument of the command line is "-f" and returns the corresponding index of argv. Returns 0 if "-f" cannot be found. */ int check_argv_eq(int argc, char *argv[], char *str) { int i; int arg_str = 0; for(i = 1; i < argc; i++) if(strcmp(argv[i], str) == 0 ) { arg_str = i; break; } return arg_str; } /* Make a pause and wait for user to press RETURN */ void Pause(char *message) { if(message!=NULL) printf("%s\n",message); printf("\a""=> New Line to proceed... \n"); while(getchar()!='\n'); return; } /* Remove spaces from string */ void remove_spaces(char *string, char *str_nospaces, const int maxchar) { int i = 0; while(*string != '\0') { if(*string != ' ' && i= 1 if( nprocs < 1 ) nprocs = 1; return nprocs; } MSVMpack1.2/src/libtrainMSVM_2.c0000644000175000017500000011223411761350003015404 0ustar lauerlauer/* Copyright 2008-2010 Yann Guermeur */ /* 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 2 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, write to the Free Software */ /* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA*/ /*--------------------------------------------------------------------------*/ /* Name : libtrainMSVM_2.c */ /* Version : 2.0 */ /* Creation : 06/20/08 */ /* Last update : 01/20/11 */ /* Subject : Training algorithm of the M-SVM^2 */ /* Algo. : Rosen's algorithm + decomposition method */ /* Author : Fabien Lauer and Yann Guermeur Yann.Guermeur@loria.fr */ /*--------------------------------------------------------------------------*/ #include "libtrainMSVM_2.h" /* MSVM2 training function (Rosen algorithm) Solves the dual problem wrt alpha: min 1/2 alpha' H_tilde alpha - (1/Q-1) sum (alpha) s.t. alpha_ik >= 0, for all i,k, such that 1 <= i <= m, 1 <= k != y_i <= Q sum_i (alpha_ik - average_alpha_k) = 0, for all k, 1 <= k <= Q where H_tilde_ik,jl = (delta_k,l - 1/Q) ( k(x_i,x_j) + (1/2C)delta_i,j ) */ long MSVM_2_train(struct Model *model, struct Data *training_set, long chunk_size, const double accuracy, int cache_memory, const int nprocs, char *alpha0_file, char *model_tmp_file, char *log_file) { long return_status = -1; FILE *fp; int t; pthread_t *threads = (pthread_t *)malloc(sizeof(pthread_t) * nprocs); // threads id void *status; // for pthread_join int rc; // return code of pthread functions int feasible; pthread_t thread_monitor; enum AlphaInitType alphaiszero; if(training_set != NULL) { // Initialize model for this particular training set model_load_data(model, training_set); // Chetck if a kernel_par has been set if(model->nature_kernel != LINEAR && model->kernel_par == NULL) set_default_kernel_par(model); } // Log file if (log_file != NULL) { printf("\nLog training info in %s ...\n", log_file); fp = fopen(log_file,"a"); } else fp = NULL; // Initialize alpha and b if(training_set != NULL) // otherwise resume training init_alpha_b(model, alpha0_file); // use init_alpha_b(model, NULL); to initialize all alpha to 0 feasible = MSVM_2_check_feasible_sol_init(model); if(feasible == true) printf("\nVector alpha is a feasible solution...\n"); else { printf("\n Initial alpha_0 is not a feasible solution.\n"); return -1; } if(training_set == NULL || alpha0_file != NULL) alphaiszero = ALPHA_NOT_ZERO; else alphaiszero = ALPHA_IS_ZERO; EVAL = 0; // triggered by signal handler to call eval STOP = 0; // triggered by user to stop training iter = 1; // number of iterations (over all threads) // Prepare monitoring of model struct MonitorData monitor_data; monitor_data.model_tmp_file = model_tmp_file; monitor_data.period = MONITOR_PERIOD; monitor_data.model = model; pthread_create(&thread_monitor, NULL, MSVM_monitor_model_thread, (void *) &monitor_data); /* Allocate memory for shared ressources */ double **gradient = matrix(model->nb_data, model->Q); double **H_alpha = matrix(model->nb_data, model->Q); double **H_tilde_alpha = matrix(model->nb_data, model->Q); double best_primal_upper_bound = HUGE_VAL; int *activeset = (int *)calloc(model->nb_data+1, sizeof(int)); // including the kernel cache: struct KernelCache kc; unsigned long cache_size = (unsigned long)cache_memory * MBYTES; kernel_initialize_cache(cache_size, &kc, model); printf("Initialization... ");fflush(stdout); // Initialize gradient MSVM_2_init_gradient(alphaiszero, gradient, H_alpha, H_tilde_alpha, model); printf("Done.\n"); // Initialize display if(accuracy>0) print_training_info(0,0,0,model->type); else { printf("Training...");fflush(stdout); } // Prepare data for computing threads long nb_SV = 0; struct ThreadData thread_data; thread_data.nprocs = nprocs; thread_data.model = model; thread_data.kernelcache = &kc; thread_data.chunk_size = chunk_size; thread_data.accuracy = accuracy; thread_data.gradient = gradient; thread_data.H_alpha = H_alpha; thread_data.H_tilde_alpha = H_tilde_alpha; thread_data.best_primal_upper_bound = &best_primal_upper_bound; thread_data.activeset = activeset; thread_data.nb_SV = &nb_SV; thread_data.logfile_ptr = fp; // Launch computing threads for(t=0;tthread_id; const int nprocs = data->nprocs; struct Model *model = data->model; struct KernelCache *kernelcache = data->kernelcache; long chunk_size = data->chunk_size; const double accuracy = data->accuracy; double **gradient = data->gradient; double **H_alpha = data->H_alpha; double **H_tilde_alpha = data->H_tilde_alpha; double *best_primal_upper_bound = data->best_primal_upper_bound; int *activeset = data->activeset; long *nb_SV = data->nb_SV; FILE *fp = data->logfile_ptr; pthread_mutex_unlock(&thread_data_mutex); // Release thread_data for next thread // Local variables long return_status = -1; int do_eval, optimum, descent, feasible; char yesno; // Prepare the cache struct TrainingCache cache; cache.chunk_size = chunk_size; MSVM_2_alloc_memory(&cache, model->Q, model->nb_data, chunk_size); cache.activeset = activeset; cache.kc = kernelcache; double **vector_u = matrix(cache.nb_constraints, 1); double **vector_y_bar = matrix(cache.nb_variables, 1); double **vector_gradient = matrix(cache.nb_variables, 1); double theta_max, theta_opt; if(accuracy == 0) do_eval = 0; else do_eval = 1; /* Prepare parallel gradient computations: - the gradient vector is split into NUMTHREADS_GRAD parts (along i) - each part is updated by a different thread */ // max number of threads for gradient updates is nprocs pthread_t *grad_threads = (pthread_t *)malloc(sizeof(pthread_t) * nprocs); // start with 1 thread (main load on kernel evaluations) int numthreads_grad = 1; void *status; int rc; long k; struct ThreadGradient_data *grad_data = (struct ThreadGradient_data *)malloc(sizeof(struct ThreadGradient_data) * nprocs); // Disable parallel gradient computation for small data sets int parallel_gradient_update = 1; if(model->nb_data < 5000) parallel_gradient_update = 0; if(parallel_gradient_update) { for(k=0;knb_data / numthreads_grad; for(k=1;knb_data / numthreads_grad -1; } if(numthreads_grad>1) { grad_data[numthreads_grad-1].start_i = grad_data[numthreads_grad-2].end_i + 1; grad_data[numthreads_grad-1].end_i = model->nb_data; } } // Switch to nprocs/4 threads for gradient update when 25% of the kernel matrix is cached int percentage_step = 1; long percentage = model->nb_data / 4; int next_numthreads_grad = nprocs/4; if(next_numthreads_grad == 0) next_numthreads_grad = 1; // Main loop double ratio = 0.0; // stopping criterion (dual / upper bound) int thread_stop = 0; do { if((TRAIN_SMALL_STEP < TRAIN_STEP) && (iter%TRAIN_SMALL_STEP) == 0) { printf("."); fflush(stdout); } // Select a random chunk of data to optimize select_random_chunk(&cache,model); // Compute the kernel submatrix for this chunk compute_K(&cache,model); // Enter Critical Section (using and modifying the model) pthread_mutex_lock(&model_mutex); MSVM_2_compute_gradient_chunk(vector_gradient,gradient, &cache,model); MSVM_2_compute_A0(&cache,model); MSVM_2_compute_vector_u(vector_u,vector_gradient,&cache,model); optimum = MSVM_2_check_vector_u(vector_u,vector_gradient,&cache,model); if(optimum == 0 ) // u is correct and optimum not reached yet { MSVM_2_compute_vector_y_bar(vector_y_bar, vector_u, vector_gradient, &cache, model); descent = MSVM_2_check_vector_y_bar(vector_y_bar,vector_u,vector_gradient, &cache,model); if(descent == 0) while((descent == 0) && (optimum == 0)) { MSVM_2_simplify_A0(vector_u, &cache,model); MSVM_2_compute_vector_u(vector_u,vector_gradient,&cache,model); optimum = MSVM_2_check_vector_u(vector_u,vector_gradient,&cache,model); if((optimum == 0)) { MSVM_2_compute_vector_y_bar(vector_y_bar,vector_u,vector_gradient, &cache,model); descent = MSVM_2_check_vector_y_bar(vector_y_bar,vector_u,vector_gradient, &cache,model); } } if((optimum == 0) && (descent > 0)) { theta_max = MSVM_2_compute_theta_max(&cache,model); theta_opt = MSVM_2_compute_theta_opt(theta_max,&cache,model); *nb_SV += MSVM_2_compute_new_alpha(theta_opt,&cache,model); if(parallel_gradient_update) { // Update gradient in parallel for(k=0;ktype); if(do_eval && ratio > accuracy) STOP = 1; if(EVAL) // if interrupted by user (otherwise let the ratio decide if we go on training) { printf("\n *** Do you want to continue training ([y]/n)? "); yesno = getchar(); if(yesno=='n') { STOP = 1; } EVAL = 0; // reset interruption trigger } } // Release kernel submatrix in cache release_K(&cache); // Check if a sufficient % of the kernel matrix is cached if( parallel_gradient_update && cache.kc->max_idx >= percentage ) { // and switch thread to compute gradient upates instead of kernel rows if it is thread_stop = switch_thread(nprocs, &numthreads_grad, &next_numthreads_grad, &percentage, &percentage_step, grad_data, thread_id, model->nb_data); // (threads are actually stopped to leave the CPUs // to other threads that will compute gradient updates) } iter++; // Release mutex: End of critical section (see below) pthread_mutex_unlock(&model_mutex); } while(iter <= MSVM_TRAIN_MAXIT && (!do_eval || ratio < accuracy) && !STOP && !thread_stop); // Compute return_status if(do_eval && ratio >= accuracy) return_status = 0; // optimum reached. // Free memory MSVM_2_free_memory(&cache); free(vector_u[1]);free(vector_u); free(vector_y_bar[1]); free(vector_y_bar); free(vector_gradient[1]); free(vector_gradient); free(grad_threads); free(grad_data); pthread_exit((void*)return_status); } /* Allocate the memory for the cache */ void MSVM_2_alloc_memory(struct TrainingCache *cache, const long Q, const long nb_data, const long chunk_size) { long nb_variables = chunk_size * (Q-1); long nb_constraints = nb_variables + (Q-1); cache->in_chunk = (long *) calloc(nb_data+1, sizeof(long)); cache->out_of_chunk = (long *) malloc((nb_data+1) * sizeof(long)); cache->table_chunk = (long *) calloc(chunk_size+1, sizeof(long)); cache->K = (double **)malloc(sizeof(double *) * (chunk_size+1)); cache->A0 = matrix(nb_constraints, nb_variables); cache->A0T = matrix(nb_variables, nb_constraints); cache->A0A0T = matrix(nb_constraints, nb_constraints); cache->A0A0T_ref = matrix(nb_constraints, nb_constraints); cache->A0A0T_1 = matrix(nb_constraints, nb_constraints); cache->vector_z_bar = matrix(nb_variables, 1); cache->H_y_bar = matrix(chunk_size, Q); cache->matrix_y_bar = matrix(chunk_size, Q); cache->alpha_update = matrix(chunk_size, Q); // Computational templates cache->eigenvalues = (double *) calloc(nb_constraints+1, sizeof(double)); cache->working_matrix1 = matrix(nb_constraints, nb_constraints); cache->working_matrix2 = matrix(nb_constraints, nb_constraints); // For debug purposes (used in study_unfeasible) cache->constraints = (double *) calloc(Q+1, sizeof(double)); cache->nb_constraints = nb_constraints; cache->nb_variables = nb_variables; } /* Free the cache memory */ void MSVM_2_free_memory(struct TrainingCache *cache) { free(cache->table_chunk); free(cache->in_chunk); free(cache->out_of_chunk); free(cache->K); free(cache->A0[1]);free(cache->A0); free(cache->A0T[1]);free(cache->A0T); free(cache->A0A0T[1]);free(cache->A0A0T); free(cache->A0A0T_1[1]);free(cache->A0A0T_1); free(cache->A0A0T_ref[1]);free(cache->A0A0T_ref); free(cache->vector_z_bar[1]);free(cache->vector_z_bar); free(cache->H_y_bar[1]);free(cache->H_y_bar); free(cache->matrix_y_bar[1]);free(cache->matrix_y_bar); free(cache->eigenvalues); free(cache->working_matrix1[1]);free(cache->working_matrix1); free(cache->working_matrix2[1]);free(cache->working_matrix2); free(cache->constraints); free(cache->alpha_update[1]);free(cache->alpha_update); } /* MSVM_2_compute_gradient_chunk(vector_gradient,cache,model) Compute the components of the gradient vector corresponding to the chunk */ void MSVM_2_compute_gradient_chunk(double **vector_gradient, double **gradient, struct TrainingCache *cache, const struct Model *model) { long i,k,y_i,ind_pattern; const long Q = model->Q; const long chunk_size = cache->chunk_size; long row = 0; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; y_i = model->y[ind_pattern]; for(k=1; k<=Q; k++) { if(k != y_i) { row++; vector_gradient[row][1] = gradient[ind_pattern][k]; } } } } /* MSVM_2_init_gradient({ALPHA_IS_ZERO,ALPHA_NOT_ZERO}, gradient, cache, model) */ void MSVM_2_init_gradient(const enum AlphaInitType alpha_init_type, double **gradient, double **H_alpha, double **H_tilde_alpha, const struct Model *model) { long i,j,k,l,y_i; const long nb_data = model->nb_data; const long Q = model->Q; const double Qd = (double)Q; const double Qinv = 1. / (Qd-1.0); const enum Kernel_type nature_kernel = model->nature_kernel; const double *kernel_par = model->kernel_par; long dim_input = model->dim_input; double partial, H_alpha_ik, H_tilde_alpha_ik, partial2; if(alpha_init_type == ALPHA_IS_ZERO) { // Fast initialization for(i=1; i<=nb_data; i++) { for(k=1; k<=Q; k++) { gradient[i][k] = -Qinv; H_alpha[i][k] = 0.0; H_tilde_alpha[i][k] = 0.0; } gradient[i][model->y[i]] = 0.0; } } else { // Do a proper initialization based on the values of alpha for(i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { H_tilde_alpha_ik = 0.0; H_alpha_ik = 0.0; for(j=1; j<=nb_data; j++) { partial = 0.0; for(l=1; l<=Q; l++) partial -= model->alpha[j][l]; partial /= Qd; partial += model->alpha[j][k]; if(partial != 0.0) { partial2 = partial * ker(nature_kernel, model->X[i], model->X[j], dim_input,kernel_par); H_alpha_ik += partial2; H_tilde_alpha_ik += partial2; if(j==i) H_tilde_alpha_ik += partial / (2*model->C[y_i]); } } gradient[i][k] = H_tilde_alpha_ik - Qinv; H_alpha[i][k] = H_alpha_ik; H_tilde_alpha[i][k] = H_tilde_alpha_ik; } else { gradient[i][k] = 0.0; H_alpha[i][k] = 0.0; H_tilde_alpha[i][k] = 0.0; } } } } } /* Thread for updates of the gradient in parallel (spawn by main computing thread MSVM2_train_thread) */ void *MSVM2_update_gradient_thread(void *th_data) { // Recover thread data struct ThreadGradient_data *data = (struct ThreadGradient_data *) th_data; double **gradient = data->gradient; double **H_alpha = data->H_alpha; double **H_tilde_alpha = data->H_tilde_alpha; struct TrainingCache *cache = data->cache; const struct Model *model = data->model; const long start_i = data->start_i; const long end_i = data->end_i; // Local variables long i,j,k,l,y_i,ind_pattern; const long Q = model->Q; const double Qd = (double)Q; const long chunk_size = cache->chunk_size; double partial, H_tilde_alpha_update_ik, H_alpha_update_ik; for(i=start_i; i<=end_i; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { H_tilde_alpha_update_ik = 0.0; H_alpha_update_ik = 0.0; for(j=1; j<=chunk_size; j++) { ind_pattern = cache->table_chunk[j]; partial = 0.0; for(l=1; l<=Q; l++) partial -= cache->alpha_update[j][l]; partial /= Qd; partial += cache->alpha_update[j][k]; if(partial != 0.0) { H_tilde_alpha_update_ik += partial * cache->K[j][i]; H_alpha_update_ik += partial * cache->K[j][i]; if(ind_pattern==i) H_alpha_update_ik -= partial / (2*model->C[y_i]); } } gradient[i][k] += H_tilde_alpha_update_ik; H_alpha[i][k] += H_alpha_update_ik; H_tilde_alpha[i][k] += H_tilde_alpha_update_ik; } } } pthread_exit(EXIT_SUCCESS); } /* Old-style non-threaded gradient update */ void MSVM_2_update_gradient(double **gradient, double **H_alpha,double **H_tilde_alpha, struct TrainingCache *cache, const struct Model *model) { long i,j,k,l,y_i,ind_pattern; const long nb_data = model->nb_data; const long Q = model->Q; const double Qd = (double)Q; const long chunk_size = cache->chunk_size; double partial, H_tilde_alpha_update_ik, H_alpha_update_ik; for(i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { H_tilde_alpha_update_ik = 0.0; H_alpha_update_ik = 0.0; for(j=1; j<=chunk_size; j++) { ind_pattern = cache->table_chunk[j]; partial = 0.0; for(l=1; l<=Q; l++) partial -= cache->alpha_update[j][l]; partial /= Qd; partial += cache->alpha_update[j][k]; if(partial != 0.0) { H_tilde_alpha_update_ik += partial * cache->K[j][i]; H_alpha_update_ik += partial * cache->K[j][i]; if(ind_pattern==i) H_alpha_update_ik -= partial / (2*model->C[y_i]); } } gradient[i][k] += H_tilde_alpha_update_ik; H_alpha[i][k] += H_alpha_update_ik; H_tilde_alpha[i][k] += H_tilde_alpha_update_ik; } } } } /* Computation of the matrices A0 and A0T */ void MSVM_2_compute_A0(struct TrainingCache *cache, const struct Model *model) { long i,k,l,ind_pattern,y_i; const long Q = model->Q; double Qd = (double)Q; const long chunk_size = cache->chunk_size; long nb_constraints = cache->nb_constraints; long nb_variables = cache->nb_variables; long row=0; long column=0; for(k=1; k<=nb_constraints; k++) for(l=1; l<=nb_variables; l++) cache->A0[k][l] = 0.0; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; y_i = model->y[ind_pattern]; for(k=1; k<=Q; k++) { if(k != y_i) { column++; if(model->alpha[ind_pattern][k] == 0.0) { row++; cache->A0[row][column] = -1.0; } } } } column=0; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; y_i = model->y[ind_pattern]; for(l=1; l<=Q; l++) if(l != y_i) { column++; for(k=1; kA0[row+k][column] = (l != k) ? 1.0 : 1.0-Qd; } } cache->nb_sat = row+Q-1; trans_mat(cache->A0, cache->A0T, cache->nb_sat, nb_variables); } /* Computation of the vector u satisfying A0A0T u = - A0 grad J(alpha)*/ void MSVM_2_compute_vector_u(double **vector_u, double **vector_gradient, struct TrainingCache *cache, const struct Model *model) { long nb_variables = cache->nb_variables; long nb_sat = cache->nb_sat; mult_mat(cache->A0, cache->A0T, cache->A0A0T, nb_sat, nb_variables, nb_sat); MSVM_2_compute_pseudo_inverse(cache); mult_mat(cache->A0, vector_gradient, cache->working_matrix1, nb_sat, nb_variables, 1); mult_mat(cache->A0A0T_1, cache->working_matrix1, cache->working_matrix2, nb_sat, nb_sat, 1); scal_mat(-1.0, cache->working_matrix2, vector_u, nb_sat, 1); } /* optimum = MSVM_2_check_vector_u(u, gradient, cache, model) Check the equation defining vector u and returns 1 if optimal conditions are satisfied 0 if u is correct and optimal conditions not reached yet -1 if u is not correct (problem in pseudo-inverse) */ int MSVM_2_check_vector_u(double **vector_u, double **vector_gradient, struct TrainingCache *cache, const struct Model *model) { long k; long nb_sat = cache->nb_sat; long nb_variables = cache->nb_variables; const long Q = model->Q; int optimum = 1; mult_mat(cache->A0A0T_ref, vector_u, cache->working_matrix1, nb_sat, nb_sat, 1); mult_mat(cache->A0, vector_gradient, cache->working_matrix2, nb_sat, nb_variables, 1); for(k=1; k<=nb_sat; k++) cache->working_matrix2[k][1] *= -1.0; if(compare(cache->working_matrix1, cache->working_matrix2, nb_sat, 1, very_small) == false) { return -1; } k=1; while((k<=nb_sat-Q+1) && (optimum == 1)) { if(vector_u[k][1] < 0.0) optimum=0; else k++; } return optimum; } /* MSVM_2_compute_vector_y_bar(vector_y_bar, vector_u, vector_gradient, cache, model) Compute the new direction of descent */ void MSVM_2_compute_vector_y_bar(double **vector_y_bar, double **vector_u, double **vector_gradient, struct TrainingCache *cache, const struct Model *model) { long i,k,y_i; const long Q = model->Q; const long chunk_size = cache->chunk_size; long nb_sat = cache->nb_sat; long nb_variables = cache->nb_variables; long row = 0; mult_mat(cache->A0T, vector_u, cache->vector_z_bar, nb_variables, nb_sat, 1); add_mat(vector_gradient, cache->vector_z_bar, cache->working_matrix1, nb_variables, 1); scal_mat(-1.0, cache->working_matrix1, vector_y_bar, nb_variables, 1); for(k=1; k<=nb_variables; k++) if(fabs(vector_y_bar[k][1]) < 0.01 * very_small) vector_y_bar[k][1] = 0.0; for(i=1; i<=chunk_size; i++) { y_i = model->y[cache->table_chunk[i]]; for(k=1; k<=Q; k++) { if(k != y_i) { row++; cache->matrix_y_bar[i][k] = vector_y_bar[row][1]; } else cache->matrix_y_bar[i][k] = 0.0; } } } /* descent = MSVM_2_check_vector_y_bar(...) = 1 if non-zero norm feasible direction = 0 if zero-norm = -1 if non-zero norm infeasible direction Check the feasibility of the new direction of descent */ int MSVM_2_check_vector_y_bar(double **vector_y_bar, double **vector_u, double **vector_gradient, struct TrainingCache *cache, const struct Model *model) { long i,k,row, y_i; const long Q = model->Q; const long chunk_size = cache->chunk_size; long nb_sat = cache->nb_sat; long nb_variables = cache->nb_variables; int nullity, descent = 0; double norm, norm_y_bar=0.0; for(k=1; k<=nb_variables; k++) norm_y_bar += vector_y_bar[k][1] * vector_y_bar[k][1]; norm_y_bar = sqrt(norm_y_bar); cache->initial_norm_y_bar = norm_y_bar; if(norm_y_bar <= very_small) nullity=true; else nullity=false; if(nullity == false) { row=0; for(i=1; i<=chunk_size; i++) { y_i = model->y[cache->table_chunk[i]]; for(k=1; k<=Q; k++) { if(k != y_i) { row++; vector_y_bar[row][1] /= norm_y_bar; cache->matrix_y_bar[i][k] = vector_y_bar[row][1]; } else cache->matrix_y_bar[i][k] = 0.0; } } descent=1; mult_mat(cache->A0, vector_y_bar, cache->working_matrix1, nb_sat, nb_variables, 1); norm=0.0; for(k=1; k<=nb_sat; k++) norm += cache->working_matrix1[k][1] * cache->working_matrix1[k][1]; norm = sqrt(norm); if(norm > sqrt(nb_sat) * very_small) { /* printf("\nbar{y} does not belong to the null space of A0: ||A0 bar{y}||= %e\n", norm); */ descent=-1; } cache->gradientT_y_bar=0.0; for(k=1; k<=nb_variables; k++) cache->gradientT_y_bar += vector_y_bar[k][1] * vector_gradient[k][1]; if(cache->gradientT_y_bar > 0.0) { if(cache->gradientT_y_bar > very_small) { /* printf("\ngradient^T bar{y} = %e: bar{y} is not a direction of descent...\n", cache->gradientT_y_bar); */ } descent=-1; } } return descent; } /* Relax one of the constraints to be satisfied by the direction of descent */ void MSVM_2_simplify_A0(double **vector_u, struct TrainingCache *cache, const struct Model *model) { long k,l; const long Q = model->Q; long nb_sat = cache->nb_sat; long nb_variables = cache->nb_variables; double smallest_u = 0.0; long index_smallest_u = 1; for(k=1; k<=nb_sat-Q+1; k++) if(vector_u[k][1] < smallest_u) { smallest_u = vector_u[k][1]; index_smallest_u = k; } nb_sat--; for(k=index_smallest_u; k<=nb_sat; k++) for(l=1; l<=nb_variables; l++) cache->A0[k][l] = cache->A0[k+1][l]; trans_mat(cache->A0, cache->A0T, nb_sat, nb_variables); cache->nb_sat = nb_sat; } /* theta_max = MSVM_2_compute_theta_max(cache,model) Computation of the largest feasible value for theta */ double MSVM_2_compute_theta_max(const struct TrainingCache *cache, const struct Model *model) { long i,k,ind_pattern; const long Q = model->Q; const long chunk_size = cache->chunk_size; double theta_partial; double theta_max = HUGE_VAL; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; for(k=1; k<=Q; k++) if((k != model->y[ind_pattern]) && (cache->matrix_y_bar[i][k] < 0.0)) { theta_partial = - model->alpha[ind_pattern][k] / cache->matrix_y_bar[i][k]; if(theta_partial < theta_max) theta_max = theta_partial; } } return theta_max; } /* Computation of the vector H bar{y} used in compute_theta_opt */ void MSVM_2_compute_H_y_bar(struct TrainingCache *cache, const struct Model *model) { long i,j,k,l,ind_pattern, y_i; const long Q = model->Q; double Qd = (double)Q; const long chunk_size = cache->chunk_size; double partial, partial_sum_y_bar = 0.0; for(i=1; i<=chunk_size; i++) { y_i = model->y[cache->table_chunk[i]]; for(k=1; k<=Q; k++) { cache->H_y_bar[i][k] = 0.0; if(k != y_i) { for(j=1; j<=chunk_size; j++) { ind_pattern = cache->table_chunk[j]; partial_sum_y_bar = 0.0; for(l=1; l<=Q; l++) if(l != model->y[ind_pattern]) partial_sum_y_bar += cache->matrix_y_bar[j][l]; partial = cache->matrix_y_bar[j][k] - (partial_sum_y_bar / Qd); cache->H_y_bar[i][k] += partial * cache->K[i][ind_pattern]; } } } } } /* theta_opt = MSVM_2_compute_theta_opt(theta_max,cache,model) Computation of the optimal value for theta */ double MSVM_2_compute_theta_opt(const double theta_max, struct TrainingCache *cache, const struct Model *model) { long i,k, y_i; const long Q = model->Q; const long chunk_size = cache->chunk_size; double y_barT_H_y_bar=0.0; double theta_opt = 0.0; MSVM_2_compute_H_y_bar(cache,model); for(i=1; i<=chunk_size; i++) { y_i = model->y[cache->table_chunk[i]]; for(k=1; k<=Q; k++) if(k != y_i) y_barT_H_y_bar += cache->matrix_y_bar[i][k] * cache->H_y_bar[i][k]; } if(y_barT_H_y_bar <= 0.0) { printf("\nThe value of the quadratic form is: %e\n", y_barT_H_y_bar); printf("\nMatrix bar{y}\n"); display_mat(cache->matrix_y_bar, chunk_size, Q, 7, 4); exit(0); } if(y_barT_H_y_bar > tiny) theta_opt = minimum (- cache->gradientT_y_bar / y_barT_H_y_bar, theta_max); else { printf("\nbar{y}^T H bar{y} is too small: %e", y_barT_H_y_bar); theta_opt = 0.0; } return theta_opt; } /* delta_nb_SV = compute_new_alpha(theta_opt,cache,model) Computation of the new value of the vector of dual variables alpha and return the difference in number of SVs */ long MSVM_2_compute_new_alpha(const double theta_opt, const struct TrainingCache *cache, struct Model *model) { long i,k,ind_pattern; const long Q = model->Q; const double Qd = (double)Q; const long chunk_size = cache->chunk_size; long nb_SV = 0; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; model->partial_average_alpha[ind_pattern] = 0.0; // Assume x_i is not a SV if(cache->activeset[ind_pattern]) { cache->activeset[ind_pattern] = 0; nb_SV--; } for(k=1; k<=Q; k++) if(k != model->y[ind_pattern]) { cache->alpha_update[i][k] = theta_opt * cache->matrix_y_bar[i][k]; model->alpha[ind_pattern][k] += cache->alpha_update[i][k]; if(model->alpha[ind_pattern][k] < 0.0) model->alpha[ind_pattern][k] = 0.0; else if (model->alpha[ind_pattern][k] != 0.0) { // Update nb_SV and activeset if(cache->activeset[ind_pattern] == 0) { cache->activeset[ind_pattern] = 1; nb_SV++; } } model->partial_average_alpha[ind_pattern] += model->alpha[ind_pattern][k]; } else cache->alpha_update[i][k] = 0.0; model->partial_average_alpha[ind_pattern] /= Qd; } return nb_SV; } /* Check the feasibility of the initial alpha */ int MSVM_2_check_feasible_sol_init(struct Model *model) { long i,k; const long Q = model->Q; const long nb_data = model->nb_data; double norm; int feasible = true; double *constraints = (double *) calloc(Q+1, sizeof(double)); model->sum_all_alpha = 0.0; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) if(((k == model->y[i]) && (model->alpha[i][k] != 0.0)) || (model->alpha[i][k] < 0.0)) { printf("\nNo feasible solution: alpha[%ld][%ld] = %e\n\n", i, k, model->alpha[i][k]); feasible = false; break; } else model->sum_all_alpha += model->alpha[i][k]; for(k=1; k<=Q; k++) constraints[k] = model->sum_all_alpha / Q; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) constraints[k] -= model->alpha[i][k]; norm = 0.0; for(k=1; k<=Q; k++) norm += constraints[k] * constraints[k]; norm = sqrt(norm); if(norm >= very_small) { feasible = false; printf("\n\nLarge deviation of the equality constraints...\n\n"); } free(constraints); return feasible; } /* Check the feasibility of the current solution alpha */ int MSVM_2_check_feasible_sol_train(struct Model *model, struct TrainingCache *cache) { long i,k; const long Q = model->Q; const long nb_data = model->nb_data; double norm; int feasible = true; model->sum_all_alpha = 0.0; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) if(((k == model->y[i]) && (model->alpha[i][k] != 0.0)) || (model->alpha[i][k] < 0.0)) { printf("\nNo feasible solution: alpha[%ld][%ld] = %e\n\n", i, k, model->alpha[i][k]); feasible = false; break; } else model->sum_all_alpha += model->alpha[i][k]; for(k=1; k<=Q; k++) cache->constraints[k] = model->sum_all_alpha / Q; for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) cache->constraints[k] -= model->alpha[i][k]; norm = 0.0; for(k=1; k<=Q; k++) norm += cache->constraints[k] * cache->constraints[k]; norm = sqrt(norm); if(norm >= very_small) { feasible = false; printf("\n\nLarge deviation of the equality constraints...\n\n"); } return feasible; } /* Characterize the achieving of an unfeasible solution */ void MSVM_2_study_unfeasible_sol(const int descent, double **vector_u, double **vector_y_bar, const struct TrainingCache *cache, const struct Model *model) { long k; const long Q = model->Q; const long chunk_size = cache->chunk_size; long nb_sat = cache->nb_sat; long nb_variables = cache->nb_variables; for(k=1; k<=Q; k++) printf("%s%e\n", cache->constraints[k] < 0.0 ? " " : " ", cache->constraints[k]); printf("\nMatrix A0\n"); display_mat(cache->A0, nb_sat, nb_variables, 7, 4); if(descent == 0) printf("\nbar{y} is the null vector"); else printf("\nbar{y} is not the null vector"); printf("\nNorm of bar{y}: %e\n", cache->initial_norm_y_bar); printf("\nVector u\n"); display_mat(vector_u, nb_sat, 1, 7, 4); printf("\nVector bar{y}\n"); display_mat(cache->matrix_y_bar, chunk_size, Q, 7, 4); mult_mat(cache->A0, vector_y_bar, cache->working_matrix1, nb_sat, nb_variables, 1); printf("\nA0 bar{y}\n"); display_mat(cache->working_matrix1, nb_sat, 1, 9, 6); exit(0); } /* val_obj_function = MSVM_2_compute_objective_function(model, former_val_obj_function) Computation of the value J(alpha) of the objective function */ double MSVM_2_compute_objective_function(const struct Model *model, double former_val_obj_function) { long i,j,k,l; const long Q = model->Q; double Qd = (double)Q; const long nb_data = model->nb_data; long dim_input = model->dim_input; const enum Kernel_type nature_kernel = model->nature_kernel; const double *kernel_par = model->kernel_par; double Q_term=0.0, L_term=0.0, partial_1, partial_2, kernel, val_obj_function; for(i=1; i<=nb_data; i++) for(j=1; j<=nb_data; j++) { partial_1 = 0.0; for(k=1; k<=Q; k++) for(l=1; l<=Q; l++) { partial_2 = -1.0; if(k == l) partial_2 += Qd; partial_1 += partial_2 * model->alpha[i][k] * model->alpha[j][l]; } if(partial_1 != 0.0) { kernel = ker(nature_kernel, model->X[i], model->X[j], dim_input, kernel_par); if(i == j) kernel += 1 / (2*model->C[model->y[i]]); Q_term += partial_1 * kernel; } } Q_term /= Qd; L_term = model->sum_all_alpha / (Qd - 1.0); val_obj_function = -0.5 * Q_term + L_term; printf("\n Objective function: %e", val_obj_function); if(val_obj_function < former_val_obj_function) if(former_val_obj_function - val_obj_function > very_small) { printf("\nThe value of the objective function has decreased...\n"); printf("%e < %e\n\n", val_obj_function, former_val_obj_function); exit(0); } return val_obj_function; } /* MSVM_2_compute_pseudo_inverse(cache) Computation of the pseudo_inverse of A0A0T */ void MSVM_2_compute_pseudo_inverse(struct TrainingCache *cache) { long i,k; long nb_sat = cache->nb_sat; double diag_kk_inv; copy(cache->A0A0T, cache->A0A0T_ref, nb_sat, nb_sat); diagonalize(cache->A0A0T, nb_sat, cache->eigenvalues); // copy(A0A0T, eigenvectors, nb_sat, nb_sat); // A0A0T replaces eigenvectors // trans_mat(A0A0T, eigenvectorsT, nb_sat, nb_sat); // use A0A0T[j][i] for eigenvectorsT[i][j] // mult_mat(new_diagonal_matrix, eigenvectorsT, working_matrix1, // nb_sat, nb_sat, nb_sat); // This mulplication by a diagonal matrix is done in the loop below: for(k=1; k<=nb_sat; k++) if(fabs(cache->eigenvalues[k]) > very_small) { diag_kk_inv = 1.0 / cache->eigenvalues[k]; for(i=1;i<=nb_sat;i++) cache->working_matrix1[k][i] = diag_kk_inv * cache->A0A0T[i][k]; // = diaginv * eigenvectorsT[k][i]; } else { for(i=1;i<=nb_sat;i++) cache->working_matrix1[k][i] = 0.0; } mult_mat(cache->A0A0T, cache->working_matrix1, cache->A0A0T_1, nb_sat, nb_sat, nb_sat); } MSVMpack1.2/src/libtrainMSVM_2fw.c0000644000175000017500000006331711761347626015771 0ustar lauerlauer/* Copyright 2000-2010 Yann Guermeur */ /* 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 2 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, write to the Free Software */ /* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA*/ /*--------------------------------------------------------------------------*/ /* Name : libtrainMSVM_2fw.c */ /* Version : 2.0 */ /* Creation : 04/27/00 */ /* Last update : 11/29/10 */ /* Subject : Training algorithm of the M-SVM^2 */ /* Algo. : Frank-Wolfe algorithm + decomposition method */ /* Author : Fabien Lauer and Yann Guermeur Yann.Guermeur@loria.fr */ /*--------------------------------------------------------------------------*/ #include "libtrainMSVM_2fw.h" /* MSVM2 training function (Frank-Wolfe algorithm) Solves the dual problem wrt alpha: min 1/2 alpha' H_tilde alpha - (1/Q-1) sum (alpha) s.t. alpha_ik >= 0, for all i,k, such that 1 <= i <= m, 1 <= k != y_i <= Q sum_i (alpha_ik - average_alpha_k) = 0, for all k, 1 <= k <= Q where H_tilde_ik,jl = (delta_k,l - 1/Q) ( k(x_i,x_j) + (1/2C)delta_i,j ) */ long MSVM_2fw_train(struct Model *model, struct Data *training_set, long chunk_size, const double accuracy, int cache_memory, const int nprocs, char *alpha0_file, char *model_tmp_file, char *log_file) { long return_status = -1; FILE *fp; int t; pthread_t *threads = (pthread_t *)malloc(sizeof(pthread_t) * nprocs); // threads id void *status; // for pthread_join int rc; // return code of pthread functions pthread_t thread_monitor; enum AlphaInitType alphaiszero; if(training_set != NULL) { // Initialize model for this particular training set model_load_data(model, training_set); // Check if a kernel_par has been set if(model->nature_kernel != LINEAR && model->kernel_par == NULL) set_default_kernel_par(model); } if(model->nb_data > 2147483647) { printf("Cannot compute table chunk: number of data above random number limit\n"); exit(0); } // Log file if (log_file != NULL) { printf("\nLog training info in %s ...\n", log_file); fp = fopen(log_file,"a"); } else fp = NULL; // Initialize alpha and b if(training_set != NULL) // otherwise resume training init_alpha_b(model, alpha0_file); // use init_alpha_b(model, NULL); to initialize all alpha to 0 if(training_set == NULL || alpha0_file != NULL) alphaiszero = ALPHA_NOT_ZERO; else alphaiszero = ALPHA_IS_ZERO; EVAL = 0; // triggered by signal handler to call eval STOP = 0; // triggered by user to stop training iter = 1; // number of iterations (over all threads) // Prepare monitoring of model struct MonitorData monitor_data; monitor_data.model_tmp_file = model_tmp_file; monitor_data.period = MONITOR_PERIOD; monitor_data.model = model; pthread_create(&thread_monitor, NULL, MSVM_monitor_model_thread, (void *) &monitor_data); // Allocate memory for shared ressources double **gradient = matrix(model->nb_data, model->Q); double **H_alpha = matrix(model->nb_data, model->Q); double **H_tilde_alpha = matrix(model->nb_data, model->Q); double best_primal_upper_bound = HUGE_VAL; int *activeset = (int *)calloc(model->nb_data+1, sizeof(int)); double *lp_rhs = (double*)calloc(model->Q, sizeof(double)); // including the kernel cache: struct KernelCache kc; unsigned long cache_size = (unsigned long)cache_memory * MBYTES; kernel_initialize_cache(cache_size, &kc, model); printf("Initialization... ");fflush(stdout); // Initialize gradient MSVM2fw_init_gradient(alphaiszero, gradient, H_alpha,H_tilde_alpha, model); printf("Done.\n"); // Initialize display if(accuracy>0) print_training_info(0,0,0,model->type); else { printf("Training...");fflush(stdout); } // Prepare data for computing threads long nb_SV = 0; struct ThreadData thread_data; thread_data.nprocs = nprocs; thread_data.model = model; thread_data.kernelcache = &kc; thread_data.chunk_size = chunk_size; thread_data.accuracy = accuracy; thread_data.gradient = gradient; thread_data.H_alpha = H_alpha; thread_data.H_tilde_alpha = H_tilde_alpha; thread_data.best_primal_upper_bound = &best_primal_upper_bound; thread_data.activeset = activeset; thread_data.nb_SV = &nb_SV; thread_data.lp_rhs = lp_rhs; thread_data.logfile_ptr = fp; // Launch computing threads for(t=0;tthread_id; const int nprocs = data->nprocs; struct Model *model = data->model; struct KernelCache *kernelcache = data->kernelcache; long chunk_size = data->chunk_size; const double accuracy = data->accuracy; double **gradient = data->gradient; double **H_alpha = data->H_alpha; double **H_tilde_alpha = data->H_tilde_alpha; double *best_primal_upper_bound = data->best_primal_upper_bound; int *activeset = data->activeset; long *nb_SV = data->nb_SV; double *lp_rhs = data->lp_rhs; FILE *fp = data->logfile_ptr; pthread_mutex_unlock(&thread_data_mutex); // Release thread_data for next thread // Local variables int do_eval; char yesno; long return_status = -1; // Prepare the cache struct TrainingCache cache; cache.chunk_size = chunk_size; MSVM2fw_alloc_memory(&cache, model->Q, model->nb_data, chunk_size); cache.kc = kernelcache; cache.activeset = activeset; cache.lp_rhs = lp_rhs; double **delta = matrix(chunk_size, model->Q); double theta_opt; int jump = false; if(accuracy == 0) do_eval = 0; else do_eval = 1; /* Prepare parallel gradient computations: - the gradient vector is split into NUMTHREADS_GRAD parts (along i) - each part is updated by a different thread */ // max number of threads for gradient updates is nprocs pthread_t *grad_threads = (pthread_t *)malloc(sizeof(pthread_t) * nprocs); // start with 1 thread (main load on kernel evaluations) int numthreads_grad = 1; void *status; int rc; long k; struct ThreadGradient_data *grad_data = (struct ThreadGradient_data *)malloc(sizeof(struct ThreadGradient_data) * nprocs); // Disable parallel gradient computation for small data sets int parallel_gradient_update = 1; if(model->nb_data < 5000) parallel_gradient_update = 0; if(parallel_gradient_update) { for(k=0;knb_data / numthreads_grad; for(k=1;knb_data / numthreads_grad -1; } if(numthreads_grad>1) { grad_data[numthreads_grad-1].start_i = grad_data[numthreads_grad-2].end_i + 1; grad_data[numthreads_grad-1].end_i = model->nb_data; } } // Switch to nprocs/4 threads for gradient update when 25% of the kernel matrix is cached int percentage_step = 1; long percentage = model->nb_data / 4; int next_numthreads_grad = nprocs/4; if(next_numthreads_grad == 0) next_numthreads_grad = 1; // Main loop double ratio = 0.0; // stopping criterion (dual / upper bound) int thread_stop = 0; do { if((TRAIN_SMALL_STEP < TRAIN_STEP) && (iter%TRAIN_SMALL_STEP) == 0) { printf("."); fflush(stdout); } // Select a random chunk of data to optimize select_random_chunk(&cache,model); // Compute the kernel submatrix for this chunk compute_K(&cache,model); // Enter Critical Section (using and modifying the model) pthread_mutex_lock(&model_mutex); jump = MSVM2fw_solve_lp(gradient, &cache, model); if(jump == false) jump = MSVM2fw_check_opt_sol(gradient,&cache,model); if(jump == false) { MSVM2fw_compute_delta(delta,&cache,model); theta_opt = MSVM2fw_compute_theta_opt(delta, &cache, model); *nb_SV += MSVM2fw_compute_new_alpha(theta_opt,&cache,model); if(parallel_gradient_update && numthreads_grad > 1) { // Update gradient in parallel for(k=0;ktype); if(do_eval && ratio > accuracy) STOP = 1; if(EVAL) // if interrupted by user (otherwise let the ratio decide if we go on training) { printf("\n *** Do you want to continue training ([y]/n)? "); yesno = getchar(); if(yesno=='n') { STOP = 1; } EVAL = 0; // reset interruption trigger } } // Release kernel submatrix in cache release_K(&cache); // Check if a sufficient % of the kernel matrix is cached if( parallel_gradient_update && cache.kc->max_idx >= percentage ) { // and switch thread to compute gradient upates instead of kernel rows if it is thread_stop = switch_thread(nprocs, &numthreads_grad, &next_numthreads_grad, &percentage, &percentage_step, grad_data, thread_id, model->nb_data); // (threads are actually stopped to leave the CPUs // to other threads that will compute gradient updates) } iter++; // Release mutex: End of critical section (see below) pthread_mutex_unlock(&model_mutex); } while(iter <= MSVM_TRAIN_MAXIT && (!do_eval || ratio < accuracy) && !STOP && !thread_stop); // Compute return_status if(do_eval && ratio >= accuracy) return_status = 0; // optimum reached. // Free memory MSVM2fw_free_memory(&cache); free(delta[1]);free(delta); free(grad_threads); free(grad_data); pthread_exit((void*)return_status); } /* Allocate the memory for the cache */ void MSVM2fw_alloc_memory(struct TrainingCache *cache, const long Q, const long nb_data, const long chunk_size) { cache->table_chunk = (long *) calloc(chunk_size+1, sizeof(long)); cache->out_of_chunk = (long *) calloc(nb_data+1, sizeof(long)); cache->in_chunk = (long *) calloc(nb_data+1, sizeof(long)); cache->lp_sol = matrix(chunk_size, Q); cache->K = (double **)malloc(sizeof(double *) * (chunk_size+1)); cache->H_delta = matrix(chunk_size, Q); cache->alpha_update = matrix(chunk_size, Q); } /* Free the cache memory */ void MSVM2fw_free_memory(struct TrainingCache *cache) { free(cache->table_chunk); free(cache->out_of_chunk); free(cache->in_chunk); free(cache->K); free(cache->lp_sol[1]);free(cache->lp_sol); free(cache->H_delta[1]);free(cache->H_delta); free(cache->alpha_update[1]);free(cache->alpha_update); } /* Solve the LP subproblem by calling lp_solve API */ int MSVM2fw_solve_lp(double **gradient, const struct TrainingCache *cache, const struct Model *model) { long i,k,l,ind_pattern,y_i; const long Q = model->Q; const double Qd = (double)Q; const long chunk_size = cache->chunk_size; const int nRows = Q-1; const int nCols = chunk_size * (Q-1); double *obj = (double*)malloc(sizeof(double) * (1+nCols)); double *row = (double*)malloc(sizeof(double) * (1+nCols)); double *rhs = (double*)malloc(sizeof(double) * Q); long **lp_sol_table = matrix_l(nCols, 2); long **lp_sol_table_inv = matrix_l(chunk_size, Q); double *sol = (double*)malloc(sizeof(double) * (1+nRows+nCols)); double epsel; // Make LP lprec *lp = make_lp(0, nCols); set_add_rowmode(lp, TRUE); // Make objective function int col = 1; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; y_i = model->y[ind_pattern]; for(k=1; k<=Q; k++) if(k != y_i) { obj[col] = gradient[ind_pattern][k]; lp_sol_table[col][1] = i; // keep a table of correspondance between lp_sol_table[col][2] = k; // LPSOLVE vector of variables and lp_sol matrix lp_sol_table_inv[i][k] = col++; // lp_sol[i][k] = the 'lp_solve_table_inv[i][k]'-th variable for LPSOLVE } else cache->lp_sol[i][k] = 0; } set_obj_fn(lp, obj); /* // Make RHS of constraints // -- complete computation -- for(k=1; kin_chunk[i] == 0) { for(l=1; l<=Q; l++) rhs[k] += model->alpha[i][l]; rhs[k] -= Qd * model->alpha[i][k]; } } */ // Make RHS of constraints // -- updates to cache->rhs are made in compute_new_alpha() // to keep track of rhs // we only need to remove the contribution of the examples in the chunk for(k=1; klp_rhs[k]; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; for(l=1; l<=Q; l++) rhs[k] -= model->alpha[ind_pattern][l]; rhs[k] += Qd * model->alpha[ind_pattern][k]; } } // Make constraints for(k=1; ktable_chunk[i]; y_i = model->y[ind_pattern]; for(l=1; l<=Q; l++) if(l != y_i) { row[lp_sol_table_inv[i][l]] = -1.0; if(l == k) row[lp_sol_table_inv[i][l]] += Qd; } } add_constraint(lp, row, EQ, rhs[k]); } // No upper bound constraints of the type alpha <= C for MSVM2 // But we need an upper bound anyway for(col=1;col<=nCols;col++) set_upbo(lp, col, 1000); // End of LP making set_add_rowmode(lp, FALSE); //print_lp(lp); // Solve LP int jump = false; set_outputfile(lp,""); if(solve(lp)) { printf("Problem with the LP... \n"); jump = true; } else { // Recover solution in the matrix lp_sol get_primal_solution(lp, sol); // sol: template for lp_solve solution format // sol=[obj, constraints, variables] epsel = get_epsel(lp); // tolerance in lp_solve // Put solution into lp_sol for(col=1; col<= nCols; col++) { // Check feasibility of the col-th variable if(sol[nRows+col] < -epsel) { jump = true; break; } // Round off tolerance if(fabs(sol[nRows+col]) < epsel) sol[nRows+col] = 0.0; // Set the value in lp_sol matrix cache->lp_sol[lp_sol_table[col][1]][lp_sol_table[col][2]] = sol[nRows+col]; } } delete_lp(lp); free(obj); free(row); free(rhs); free(lp_sol_table[1]);free(lp_sol_table); free(lp_sol_table_inv[1]);free(lp_sol_table_inv); free(sol); return jump; } /* MSVM2fw_init_gradient({ALPHA_IS_ZERO,ALPHA_NOT_ZERO}, gradient, cache, model) */ void MSVM2fw_init_gradient(const enum AlphaInitType alpha_init_type, double **gradient, double **H_alpha, double **H_tilde_alpha, const struct Model *model) { long i,j,k,l,y_i; const long nb_data = model->nb_data; const long Q = model->Q; const double Qd = (double)Q; const double Qinv = 1. / (Qd-1.0); const enum Kernel_type nature_kernel = model->nature_kernel; const double *kernel_par = model->kernel_par; long dim_input = model->dim_input; double partial, H_alpha_ik, H_tilde_alpha_ik, partial2; if(alpha_init_type == ALPHA_IS_ZERO) { // Fast initialization for(i=1; i<=nb_data; i++) { for(k=1; k<=Q; k++) { gradient[i][k] = -Qinv; H_alpha[i][k] = 0.0; H_tilde_alpha[i][k] = 0.0; } gradient[i][model->y[i]] = 0.0; } } else { // Do a proper initialization based on the values of alpha for(i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { H_tilde_alpha_ik = 0.0; H_alpha_ik = 0.0; for(j=1; j<=nb_data; j++) { partial = 0.0; for(l=1; l<=Q; l++) partial -= model->alpha[j][l]; partial /= Qd; partial += model->alpha[j][k]; if(partial != 0.0) { partial2 = partial * ker(nature_kernel, model->X[i], model->X[j], dim_input,kernel_par); H_alpha_ik += partial2; H_tilde_alpha_ik += partial2; if(j==i) H_tilde_alpha_ik += partial / (2*model->C[y_i]); } } gradient[i][k] = H_tilde_alpha_ik - Qinv; H_alpha[i][k] = H_alpha_ik; H_tilde_alpha[i][k] = H_tilde_alpha_ik; } else { gradient[i][k] = 0.0; H_alpha[i][k] = 0.0; H_tilde_alpha[i][k] = 0.0; } } } } } /* Thread for updates of the gradient in parallel (spawn by main computing thread MSVM2fw_train_thread) */ void *MSVM2fw_update_gradient_thread(void *th_data) { // Recover thread data struct ThreadGradient_data *data = (struct ThreadGradient_data *) th_data; double **gradient = data->gradient; double **H_alpha = data->H_alpha; double **H_tilde_alpha = data->H_tilde_alpha; struct TrainingCache *cache = data->cache; const struct Model *model = data->model; const long start_i = data->start_i; const long end_i = data->end_i; // Local variables long i,j,k,l,y_i,ind_pattern; const long Q = model->Q; const double Qd = (double)Q; const long chunk_size = cache->chunk_size; double partial, H_tilde_alpha_update_ik, H_alpha_update_ik; for(i=start_i; i<=end_i; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { H_tilde_alpha_update_ik = 0.0; H_alpha_update_ik = 0.0; for(j=1; j<=chunk_size; j++) { ind_pattern = cache->table_chunk[j]; partial = 0.0; for(l=1; l<=Q; l++) partial -= cache->alpha_update[j][l]; partial /= Qd; partial += cache->alpha_update[j][k]; if(partial != 0.0) { H_tilde_alpha_update_ik += partial * cache->K[j][i]; H_alpha_update_ik += partial * cache->K[j][i]; if(ind_pattern==i) H_alpha_update_ik -= partial / (2.*model->C[y_i]); } } gradient[i][k] += H_tilde_alpha_update_ik; H_alpha[i][k] += H_alpha_update_ik; H_tilde_alpha[i][k] += H_tilde_alpha_update_ik; } } } pthread_exit(EXIT_SUCCESS); } /* Old-style non-threaded gradient update */ void MSVM2fw_update_gradient(double **gradient, double **H_alpha,double **H_tilde_alpha, struct TrainingCache *cache, const struct Model *model) { long i,j,k,l,y_i,ind_pattern; const long nb_data = model->nb_data; const long Q = model->Q; const double Qd = (double)Q; const long chunk_size = cache->chunk_size; double partial, H_tilde_alpha_update_ik, H_alpha_update_ik; for(i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { H_tilde_alpha_update_ik = 0.0; H_alpha_update_ik = 0.0; for(j=1; j<=chunk_size; j++) { ind_pattern = cache->table_chunk[j]; partial = 0.0; for(l=1; l<=Q; l++) partial -= cache->alpha_update[j][l]; partial /= Qd; partial += cache->alpha_update[j][k]; if(partial != 0.0) { H_tilde_alpha_update_ik += partial * cache->K[j][i]; H_alpha_update_ik += partial * cache->K[j][i]; if(ind_pattern==i) H_alpha_update_ik -= partial / (2.*model->C[y_i]); } } gradient[i][k] += H_tilde_alpha_update_ik; H_alpha[i][k] += H_alpha_update_ik; H_tilde_alpha[i][k] += H_tilde_alpha_update_ik; } } } } /* Same as WW_compute_H_delta() and LLW */ void MSVM2fw_compute_H_delta(double **delta, struct TrainingCache *cache, const struct Model *model) { long i,k,j,y_i,l; const long Q = model->Q; const double Qd = (double)Q; const long chunk_size = cache->chunk_size; double partial; for(i=1; i<=chunk_size; i++) { y_i = model->y[cache->table_chunk[i]]; for(k=1; k<=Q; k++) { cache->H_delta[i][k] = 0.0; if(k != y_i) { for(j=1; j<=chunk_size; j++) { partial = 0.0; for(l=1; l<=Q; l++) partial -= delta[j][l]; partial /= Qd; partial += delta[j][k]; cache->H_delta[i][k] += partial * cache->K[i][cache->table_chunk[j]]; } } } } } int MSVM2fw_check_opt_sol(double **gradient, struct TrainingCache *cache, const struct Model *model) { double gradient_alpha = 0.0; double gradient_Gamma = 0.0; double gradient_diff = 0.0; long i,k,ind_pattern, y_i; const long Q = model->Q; const long chunk_size = cache->chunk_size; int jump = false; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; y_i = model->y[ind_pattern]; for(k=1; k<=Q; k++) if(k != y_i) { gradient_alpha += gradient[ind_pattern][k] * model->alpha[ind_pattern][k]; gradient_Gamma += gradient[ind_pattern][k] * cache->lp_sol[i][k]; } } gradient_diff = gradient_alpha - gradient_Gamma; if(gradient_diff <= 0.0) { if(gradient_diff < -small) { printf("\nInappropriate subset selection...\n"); printf("\ngradient^T (alpha - gamma): %lf", gradient_diff); } jump = true; } cache->gradient_diff = gradient_diff; return jump; } /* Update model paramaters alpha_ik Return the difference in number of SVs */ long MSVM2fw_compute_new_alpha(const double theta_opt, const struct TrainingCache *cache, struct Model *model) { long i,k,l,ind_pattern; const long Q = model->Q; const double Qd = (double)Q; const long chunk_size = cache->chunk_size; long nb_SV = 0; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; model->partial_average_alpha[ind_pattern] = 0.0; // Assume x_i is not a SV if(cache->activeset[ind_pattern]) { cache->activeset[ind_pattern] = 0; nb_SV--; } for(k=1; k<=Q; k++) { if(k!=model->y[ind_pattern]) { cache->alpha_update[i][k] = theta_opt * ( cache->lp_sol[i][k] - model->alpha[ind_pattern][k] ); model->alpha[ind_pattern][k] += cache->alpha_update[i][k]; model->sum_all_alpha += cache->alpha_update[i][k]; if(model->alpha[ind_pattern][k] < 0.0) { cache->alpha_update[i][k] -= model->alpha[ind_pattern][k]; model->alpha[ind_pattern][k] = 0.0; } else if(model->alpha[ind_pattern][k] != 0.0 ) { // Update nb_SV and activeset if(cache->activeset[ind_pattern] == 0) { cache->activeset[ind_pattern] = 1; nb_SV++; } } model->partial_average_alpha[ind_pattern] += model->alpha[ind_pattern][k]; } else cache->alpha_update[i][k] = 0; } model->partial_average_alpha[ind_pattern] /= Qd; // Update RHS of constraints in LP for(k=1; klp_rhs[k] += cache->alpha_update[i][l]; cache->lp_rhs[k] -= Qd * cache->alpha_update[i][k]; } } return nb_SV; } void MSVM2fw_compute_delta(double **delta, const struct TrainingCache *cache, const struct Model *model) { long i,k,ind_pattern; const long Q = model->Q; const long chunk_size = cache->chunk_size; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; for(k=1; k<=Q; k++) delta[i][k] = model->alpha[ind_pattern][k] - cache->lp_sol[i][k]; } } double MSVM2fw_compute_theta_opt(double **delta, struct TrainingCache *cache, const struct Model *model) { long i,k; const long chunk_size = cache->chunk_size; const long Q = model->Q; double theta_opt, denominator = 0.0; MSVM2fw_compute_H_delta(delta, cache,model); for(i=1; i<=chunk_size; i++) { for(k=1; k<=Q; k++) denominator += delta[i][k] * cache->H_delta[i][k]; } if(denominator <= 0) { printf("\nWrong estimate of theta: denominator= %e\n", denominator); exit(0); } theta_opt = cache->gradient_diff / denominator; if(theta_opt > 1.0) theta_opt = 1.0; return theta_opt; } MSVMpack1.2/src/custom_kernels.c0000644000175000017500000002427411644772425015737 0ustar lauerlauer/* Custom kernel functions for MSVMpack This file contains templates for 3 custom kernel functions. Edit this file to implement new kernels and use them by calling trainmain -k 5 -p kernel_par (for custom kernel 1) trainmain -k 6 -p kernel_par (for custom kernel 2) trainmain -k 7 -p kernel_par (for custom kernel 3) Each custom kernel function must return the value k(x1,x2) and takes the following inputs: x1, x2 : two vectors dim : dimension of the vectors kernel_par : vector of parameters of the kernel function Remember to use indexes from 1 to dim to access vector components, e.g., to compute the inner product k(x1,x2) = < x1, x2 >, write for(i = 1; i<=dim; i++) kernel_value += x1[i] * x2[i]; Kernel parameters are stored in an array of DOUBLE of size (1 + #parameters): kernel_par[0] = #parameters kernel_par[1] ... kernel_par[(int)kernel_par[0]] = parameter values If the function takes a single parameter, its default value can be defined in 'include/kernel.h'. Names of custom kernel functions can also be defined in 'include/kernel.h'. */ #include #include double custom_kernel_1(const double *x1 , const double *x2 , const long dim, const double *kernel_par) { double kernel_value = 0.0; /* Add code to compute custom kernel function here and remove the next 4 lines. */ printf("Error: custom kernel 1 is undefined.\n"); printf(" Open MSVMpack/src/custom_kernels.c and edit the \n"); printf(" function custom_kernel_1() to implement your new kernel.\n"); exit(1); return kernel_value; } double custom_kernel_2(const double *x1 , const double *x2 , const long dim, const double *kernel_par) { double kernel_value = 0.0; /* Add code to compute custom kernel function here and remove the next 4 lines. */ printf("Error: custom kernel 2 is undefined.\n"); printf(" Open MSVMpack/src/custom_kernels.c and edit the \n"); printf(" function custom_kernel_2() to implement your new kernel.\n"); exit(1); return kernel_value; } double custom_kernel_3(const double *x1 , const double *x2 , const long dim, const double *kernel_par) { double kernel_value = 0.0; /* Add code to compute custom kernel function here and remove the next 4 lines. */ printf("Error: custom kernel 3 is undefined.\n"); printf(" Open MSVMpack/src/custom_kernels.c and edit the \n"); printf(" function custom_kernel_3() to implement your new kernel.\n"); exit(1); return kernel_value; } /* The following functions can be used to compute similar kernels with FLOAT data type Note that the same default values for kernel_par as defined above apply to these functions. */ double custom_kernel_1_float(const float *x1 , const float *x2 , const long dim, const double *kernel_par) { double kernel_value = 0.0; /* Add code to compute custom kernel function here and remove the next 4 lines. */ printf("Error: custom kernel 1 is undefined for FLOAT data type.\n"); printf(" Open MSVMpack/src/custom_kernels.c and edit the \n"); printf(" function custom_kernel_1_float() to implement your new kernel.\n"); exit(1); return kernel_value; } double custom_kernel_2_float(const float *x1 , const float *x2 , const long dim, const double *kernel_par) { double kernel_value = 0.0; /* Add code to compute custom kernel function here and remove the next 4 lines. */ printf("Error: custom kernel 2 is undefined for FLOAT data type.\n"); printf(" Open MSVMpack/src/custom_kernels.c and edit the \n"); printf(" function custom_kernel_2_float() to implement your new kernel.\n"); exit(1); return kernel_value; } double custom_kernel_3_float(const float *x1 , const float *x2 , const long dim, const double *kernel_par) { double kernel_value = 0.0; /* Add code to compute custom kernel function here and remove the next 4 lines. */ printf("Error: custom kernel 3 is undefined for FLOAT data type.\n"); printf(" Open MSVMpack/src/custom_kernels.c and edit the \n"); printf(" function custom_kernel_3_float() to implement your new kernel.\n"); exit(1); return kernel_value; } /* Custom kernel functions for INT data type */ double custom_kernel_1_int(const int *x1 , const int *x2 , const long dim, const double *kernel_par) { double kernel_value = 0.0; /* Add code to compute custom kernel function here and remove the next 4 lines. */ printf("Error: custom kernel 1 is undefined for INT data type.\n"); printf(" Open MSVMpack/src/custom_kernels.c and edit the \n"); printf(" function custom_kernel_1_int() to implement your new kernel.\n"); exit(1); return kernel_value; } double custom_kernel_2_int(const int *x1 , const int *x2 , const long dim, const double *kernel_par) { double kernel_value = 0.0; /* Add code to compute custom kernel function here and remove the next 4 lines. */ printf("Error: custom kernel 2 is undefined for INT data type.\n"); printf(" Open MSVMpack/src/custom_kernels.c and edit the \n"); printf(" function custom_kernel_2_int() to implement your new kernel.\n"); exit(1); return kernel_value; } double custom_kernel_3_int(const int *x1 , const int *x2 , const long dim, const double *kernel_par) { double kernel_value = 0.0; /* Add code to compute custom kernel function here and remove the next 4 lines. */ printf("Error: custom kernel 3 is undefined for INT data type.\n"); printf(" Open MSVMpack/src/custom_kernels.c and edit the \n"); printf(" function custom_kernel_3_int() to implement your new kernel.\n"); exit(1); return kernel_value; } /* Custom kernel functions for SHORT INT data type */ double custom_kernel_1_short_int(const short int *x1 , const short int *x2 , const long dim, const double *kernel_par) { double kernel_value = 0.0; /* Add code to compute custom kernel function here and remove the next 4 lines. */ printf("Error: custom kernel 1 is undefined for SHORT INT data type.\n"); printf(" Open MSVMpack/src/custom_kernels.c and edit the \n"); printf(" function custom_kernel_1_short_int() to implement your new kernel.\n"); exit(1); return kernel_value; } double custom_kernel_2_short_int(const short int *x1 , const short int *x2 , const long dim, const double *kernel_par) { double kernel_value = 0.0; /* Add code to compute custom kernel function here and remove the next 4 lines. */ printf("Error: custom kernel 2 is undefined for SHORT INT data type.\n"); printf(" Open MSVMpack/src/custom_kernels.c and edit the \n"); printf(" function custom_kernel_2_short_int() to implement your new kernel.\n"); exit(1); return kernel_value; } double custom_kernel_3_short_int(const short int *x1 , const short int *x2 , const long dim, const double *kernel_par) { double kernel_value = 0.0; /* Add code to compute custom kernel function here and remove the next 4 lines. */ printf("Error: custom kernel 3 is undefined for SHORT INT data type.\n"); printf(" Open MSVMpack/src/custom_kernels.c and edit the \n"); printf(" function custom_kernel_3_short_int() to implement your new kernel.\n"); exit(1); return kernel_value; } /* Custom kernel functions for BYTE data type */ double custom_kernel_1_byte(const unsigned char *x1 , const unsigned char *x2 , const long dim, const double *kernel_par) { double kernel_value = 0.0; /* Add code to compute custom kernel function here and remove the next 4 lines. */ printf("Error: custom kernel 1 is undefined for BYTE data type.\n"); printf(" Open MSVMpack/src/custom_kernels.c and edit the \n"); printf(" function custom_kernel_1_byte() to implement your new kernel.\n"); exit(1); return kernel_value; } double custom_kernel_2_byte(const unsigned char *x1 , const unsigned char *x2 , const long dim, const double *kernel_par) { double kernel_value = 0.0; /* Add code to compute custom kernel function here and remove the next 4 lines. */ printf("Error: custom kernel 2 is undefined for BYTE data type.\n"); printf(" Open MSVMpack/src/custom_kernels.c and edit the \n"); printf(" function custom_kernel_2_byte() to implement your new kernel.\n"); exit(1); return kernel_value; } double custom_kernel_3_byte(const unsigned char *x1 , const unsigned char *x2 , const long dim, const double *kernel_par) { double kernel_value = 0.0; /* Add code to compute custom kernel function here and remove the next 4 lines. */ printf("Error: custom kernel 3 is undefined for BYTE data type.\n"); printf(" Open MSVMpack/src/custom_kernels.c and edit the \n"); printf(" function custom_kernel_3_byte() to implement your new kernel.\n"); exit(1); return kernel_value; } /* Custom kernel functions for BIT data type Data format: - each x1[i] is an INT containing 32 bits - dim is the number of bits in a data vector, so the dimension of x1 is true_dim = (dim/32) + (dim%32 != 0) - if dim%32 != 0, the last component x1[true_dim] is completed with zeros */ double custom_kernel_1_bit(const int *x1 , const int *x2 , const long dim, const double *kernel_par) { double kernel_value = 0.0; /* Add code to compute custom kernel function here and remove the next 4 lines. */ printf("Error: custom kernel 1 is undefined for BIT data type.\n"); printf(" Open MSVMpack/src/custom_kernels.c and edit the \n"); printf(" function custom_kernel_1_bit() to implement your new kernel.\n"); exit(1); return kernel_value; } double custom_kernel_2_bit(const int *x1 , const int *x2 , const long dim, const double *kernel_par) { double kernel_value = 0.0; /* Add code to compute custom kernel function here and remove the next 4 lines. */ printf("Error: custom kernel 2 is undefined for BIT data type.\n"); printf(" Open MSVMpack/src/custom_kernels.c and edit the \n"); printf(" function custom_kernel_2_bit() to implement your new kernel.\n"); exit(1); return kernel_value; } double custom_kernel_3_bit(const int *x1 , const int *x2 , const long dim, const double *kernel_par) { double kernel_value = 0.0; /* Add code to compute custom kernel function here and remove the next 4 lines. */ printf("Error: custom kernel 3 is undefined for BIT data type.\n"); printf(" Open MSVMpack/src/custom_kernels.c and edit the \n"); printf(" function custom_kernel_3_bit() to implement your new kernel.\n"); exit(1); return kernel_value; } MSVMpack1.2/src/libtrainMSVM_LLW.c~0000644000175000017500000006236211761346310016113 0ustar lauerlauer/* Copyright 2000-2010 Yann Guermeur */ /* 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 2 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, write to the Free Software */ /* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA*/ /*--------------------------------------------------------------------------*/ /* Name : libtrainMSVM_LLW.c */ /* Version : 2.0 */ /* Creation : 04/27/00 */ /* Last update : 11/29/10 */ /* Subject : Training algorithm of the M-SVM of Lee, Lin and Wahba */ /* Algo. : Frank-Wolfe algorithm + decomposition method */ /* Author : Fabien Lauer and Yann Guermeur Yann.Guermeur@loria.fr */ /*--------------------------------------------------------------------------*/ #include "libtrainMSVM_LLW.h" /* Lee,Lin, and Wahba (LLW) MSVM training function Solves the dual problem wrt alpha: min 1/2 alpha' H alpha - (1/Q-1) sum (alpha) s.t. 0 <= alpha_ik <= C, for all i,k, such that 1 <= i <= m, 1 <= k != y_i <= Q sum_i (alpha_ik - average_alpha_k) = 0, for all k, 1 <= k <= Q where H_ik,jl = (delta_k,l - 1/Q) k(x_i,x_j) */ long MSVM_LLW_train(struct Model *model, struct Data *training_set, long chunk_size, const double accuracy, int cache_memory, const int nprocs, char *alpha0_file, char *model_tmp_file, char *log_file) { long return_status = -1; FILE *fp; int t; pthread_t *threads = (pthread_t *)malloc(sizeof(pthread_t) * nprocs); // threads id void *status; // for pthread_join int rc; // return code of pthread functions pthread_t thread_monitor; enum AlphaInitType alphaiszero; if(training_set != NULL) { // Initialize model for this particular training set model_load_data(model, training_set); // Check if a kernel_par has been set if(model->nature_kernel != LINEAR && model->kernel_par == NULL) set_default_kernel_par(model); } if(model->nb_data > 2147483647) { printf("Cannot compute table chunk: number of data above random number limit\n"); exit(0); } // Log file if (log_file != NULL) { printf("\nLog training info in %s ...\n", log_file); fp = fopen(log_file,"a"); } else fp = NULL; // Initialize alpha and b if(training_set != NULL) // otherwise resume training init_alpha_b(model, alpha0_file); // use init_alpha_b(model, NULL); to initialize all alpha to 0 if(training_set == NULL || alpha0_file != NULL) alphaiszero = ALPHA_NOT_ZERO; else alphaiszero = ALPHA_IS_ZERO; EVAL = 0; // triggered by signal handler to call eval STOP = 0; // triggered by user to stop training iter = 1; // number of iterations (over all threads) // Prepare monitoring of model struct MonitorData monitor_data; monitor_data.model_tmp_file = model_tmp_file; monitor_data.period = MONITOR_PERIOD; monitor_data.model = model; pthread_create(&thread_monitor, NULL, MSVM_monitor_model_thread, (void *) &monitor_data); // Allocate memory for shared ressources double **gradient = matrix(model->nb_data, model->Q); double **H_alpha = matrix(model->nb_data, model->Q); double best_primal_upper_bound = HUGE_VAL; int *activeset = (int *)calloc(model->nb_data+1, sizeof(int)); double *lp_rhs = (double*)calloc(model->Q, sizeof(double)); // including the kernel cache: struct KernelCache kc; unsigned long cache_size = (unsigned long)cache_memory * MBYTES; kernel_initialize_cache(cache_size, &kc, model); printf("Initialization... ");fflush(stdout); // Initialize gradient LLW_init_gradient(alphaiszero, gradient, H_alpha,model); printf("Done.\n"); // Initialize display if(accuracy>0) print_training_info(0,0,0,model->type); else { printf("Training...");fflush(stdout); } // Prepare data for computing threads long nb_SV = 0; struct ThreadData thread_data; thread_data.nprocs = nprocs; thread_data.model = model; thread_data.kernelcache = &kc; thread_data.chunk_size = chunk_size; thread_data.accuracy = accuracy; thread_data.gradient = gradient; thread_data.H_alpha = H_alpha; thread_data.best_primal_upper_bound = &best_primal_upper_bound; thread_data.activeset = activeset; thread_data.nb_SV = &nb_SV; thread_data.lp_rhs = lp_rhs; thread_data.logfile_ptr = fp; // Launch computing threads for(t=0;tthread_id; const int nprocs = data->nprocs; struct Model *model = data->model; struct KernelCache *kernelcache = data->kernelcache; long chunk_size = data->chunk_size; const double accuracy = data->accuracy; double **gradient = data->gradient; double **H_alpha = data->H_alpha; double *best_primal_upper_bound = data->best_primal_upper_bound; int *activeset = data->activeset; long *nb_SV = data->nb_SV; double *lp_rhs = data->lp_rhs; FILE *fp = data->logfile_ptr; pthread_mutex_unlock(&thread_data_mutex); // Release thread_data for next thread // Local variables int do_eval; char yesno; long return_status = -1; // Prepare the cache struct TrainingCache cache; cache.chunk_size = chunk_size; LLW_alloc_memory(&cache, model->Q, model->nb_data, chunk_size); cache.kc = kernelcache; cache.activeset = activeset; cache.lp_rhs = lp_rhs; double **delta = matrix(chunk_size, model->Q); double theta_opt; int jump = false; if(accuracy == 0) do_eval = 0; else do_eval = 1; /* Prepare parallel gradient computations: - the gradient vector is split into NUMTHREADS_GRAD parts (along i) - each part is updated by a different thread */ // max number of threads for gradient updates is nprocs pthread_t *grad_threads = (pthread_t *)malloc(sizeof(pthread_t) * nprocs); // start with 1 thread (main load on kernel evaluations) int numthreads_grad = 1; void *status; int rc; long k; struct ThreadGradient_data *grad_data = (struct ThreadGradient_data *)malloc(sizeof(struct ThreadGradient_data) * nprocs); // Disable parallel gradient computation for small data sets int parallel_gradient_update = 1; if(model->nb_data < 5000) parallel_gradient_update = 0; if(parallel_gradient_update) { for(k=0;knb_data / numthreads_grad; for(k=1;knb_data / numthreads_grad -1; } if(numthreads_grad>1) { grad_data[numthreads_grad-1].start_i = grad_data[numthreads_grad-2].end_i + 1; grad_data[numthreads_grad-1].end_i = model->nb_data; } } // Switch to nprocs/4 threads for gradient update when 25% of the kernel matrix is cached int percentage_step = 1; long percentage = model->nb_data / 4; int next_numthreads_grad = nprocs/4; if(next_numthreads_grad == 0) next_numthreads_grad = 1; // Main loop double ratio = 0.0; // stopping criterion (dual / upper bound) int thread_stop = 0; do { if((TRAIN_SMALL_STEP < TRAIN_STEP) && (iter%TRAIN_SMALL_STEP) == 0) { printf("."); fflush(stdout); } // Select a random chunk of data to optimize select_random_chunk(&cache,model); // Compute the kernel submatrix for this chunk compute_K(&cache,model); // Enter Critical Section (using and modifying the model) pthread_mutex_lock(&model_mutex); jump = LLW_solve_lp(gradient, &cache, model); if(jump == false) jump = LLW_check_opt_sol(gradient,&cache,model); if(jump == false) { LLW_compute_delta(delta,&cache,model); theta_opt = LLW_compute_theta_opt(delta, &cache, model); *nb_SV += LLW_compute_new_alpha(theta_opt,&cache,model); if(parallel_gradient_update) { // Update gradient in parallel for(k=0;ktype); if(do_eval && ratio > accuracy) STOP = 1; if(EVAL) // if interrupted by user (otherwise let the ratio decide if we go on training) { printf("\n *** Do you want to continue training ([y]/n)? "); yesno = getchar(); if(yesno=='n') { STOP = 1; } EVAL = 0; // reset interruption trigger } } // Release kernel submatrix in cache release_K(&cache); // Check if a sufficient % of the kernel matrix is cached if( parallel_gradient_update && cache.kc->max_idx >= percentage ) { // and switch thread to compute gradient upates instead of kernel rows if it is thread_stop = switch_thread(nprocs, &numthreads_grad, &next_numthreads_grad, &percentage, &percentage_step, grad_data, thread_id, model->nb_data); // (threads are actually stopped to leave the CPUs // to other threads that will compute gradient updates) } iter++; // Release mutex: End of critical section pthread_mutex_unlock(&model_mutex); } while(iter <= MSVM_TRAIN_MAXIT && (!do_eval || ratio < accuracy) && !STOP && !thread_stop); // Release mutex: End of critical section (see below) pthread_mutex_unlock(&model_mutex); // compute return_status if(do_eval && ratio >= accuracy) return_status = 0; // optimum reached. // Free memory LLW_free_memory(&cache); free(delta[1]);free(delta); free(grad_threads); free(grad_data); pthread_exit((void*)return_status); } /* Allocate the memory for the cache */ void LLW_alloc_memory(struct TrainingCache *cache, const long Q, const long nb_data, const long chunk_size) { cache->table_chunk = (long *) calloc(chunk_size+1, sizeof(long)); cache->out_of_chunk = (long *) calloc(nb_data+1, sizeof(long)); cache->in_chunk = (long *) calloc(nb_data+1, sizeof(long)); cache->lp_sol = matrix(chunk_size, Q); cache->K = (double **)malloc(sizeof(double *) * (chunk_size+1)); cache->H_delta = matrix(chunk_size, Q); cache->alpha_update = matrix(chunk_size, Q); } /* Free the cache memory */ void LLW_free_memory(struct TrainingCache *cache) { free(cache->table_chunk); free(cache->out_of_chunk); free(cache->in_chunk); free(cache->K); free(cache->lp_sol[1]);free(cache->lp_sol); free(cache->H_delta[1]);free(cache->H_delta); free(cache->alpha_update[1]);free(cache->alpha_update); } /* Solve the LP subproblem by calling lp_solve API */ int LLW_solve_lp(double **gradient, const struct TrainingCache *cache, const struct Model *model) { long i,k,l,ind_pattern,y_i; const long Q = model->Q; const double Qd = (double)Q; const long chunk_size = cache->chunk_size; const double *C = model->C; const int nRows = Q-1; const int nCols = chunk_size * Q; double *obj = (double*)malloc(sizeof(double) * (1+nCols)); double *row = (double*)malloc(sizeof(double) * (1+nCols)); double *rhs = (double*)malloc(sizeof(double) * Q); long **lp_sol_table = matrix_l(nCols, 2); long **lp_sol_table_inv = matrix_l(chunk_size, Q); double *sol = (double*)malloc(sizeof(double) * (1+nRows+nCols)); double epsel; // Make LP lprec *lp = make_lp(0, nCols); set_add_rowmode(lp, TRUE); // Make objective function int col = 1; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; for(k=1; k<=Q; k++) { obj[col] = gradient[ind_pattern][k]; lp_sol_table[col][1] = i; // keep a table of correspondance between lp_sol_table[col][2] = k; // LPSOLVE vector of variables and lp_sol matrix lp_sol_table_inv[i][k] = col++; // lp_sol[i][k] = the 'lp_solve_table_inv[i][k]'-th variable for LPSOLVE } } set_obj_fn(lp, obj); /* // Make RHS of constraints // -- complete computation -- for(k=1; kin_chunk[i] == 0) { for(l=1; l<=Q; l++) rhs[k] += model->alpha[i][l]; rhs[k] -= Qd * model->alpha[i][k]; } } */ // Make RHS of constraints // -- updates to cache->rhs are made in compute_new_alpha() // to keep track of rhs // we only need to remove the contribution of the examples in the chunk for(k=1; klp_rhs[k]; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; for(l=1; l<=Q; l++) rhs[k] -= model->alpha[ind_pattern][l]; rhs[k] += Qd * model->alpha[ind_pattern][k]; } } // Make constraints for(k=1; ktable_chunk[i]; y_i = model->y[ind_pattern]; for(l=1; l<=Q; l++) if(l != y_i) { row[lp_sol_table_inv[i][l]] = -1.0; if(l == k) row[lp_sol_table_inv[i][l]] += Qd; } } add_constraint(lp, row, EQ, rhs[k]); } // Upper bound constraints: alpha <= Cy_i for(col=1;col<=nCols;col++) set_upbo(lp, col, C[model->y[cache->table_chunk[lp_sol_table[col][1]]]]); /* for(i=1; i<=chunk_size; i++) { for(k=1; k<=Q; k++) if(k != model->y[cache->table_chunk[i]]) { col = (int)lp_sol_table_inv[i][k]; set_upbo(lp, col, C); } } */ // End of LP making set_add_rowmode(lp, FALSE); //print_lp(lp); // Solve LP int jump = false; set_outputfile(lp,""); if(solve(lp)) { printf("Problem with the LP... \n"); jump = true; } else { // Recover solution in the matrix lp_sol get_primal_solution(lp, sol); // sol: template for lp_solve solution format // sol=[obj, constraints, variables] epsel = get_epsel(lp); // tolerance in lp_solve // Put solution into lp_sol for(col=1; col<= nCols; col++) { // Check feasibility of the col-th variable if((sol[nRows+col] < -epsel) || (sol[nRows+col] > C[model->y[cache->table_chunk[lp_sol_table[col][1]]]] + epsel)) { jump = true; break; } // Round off tolerance if(fabs(sol[nRows+col]) < epsel) sol[nRows+col] = 0.0; else if(fabs(sol[nRows+col] - C[model->y[cache->table_chunk[lp_sol_table[col][1]]]]) < epsel) sol[nRows+col] = C[model->y[cache->table_chunk[lp_sol_table[col][1]]]]; // Set the value in lp_sol matrix cache->lp_sol[lp_sol_table[col][1]][lp_sol_table[col][2]] = sol[nRows+col]; } } delete_lp(lp); free(obj); free(row); free(rhs); free(lp_sol_table[1]);free(lp_sol_table); free(lp_sol_table_inv[1]);free(lp_sol_table_inv); free(sol); return jump; } /* nb_SV = LLW_compute_table_chunk(model) Select a subset of the training set for the next step of optimization */ long LLW_compute_table_chunk(struct TrainingCache *cache, const struct Model *model) { long i,j,random_num,row; const long nb_data = model->nb_data; const long chunk_size = cache->chunk_size; long nb_SV = 0; for(i=1; i<=nb_data; i++) { cache->out_of_chunk[i] = i; cache->in_chunk[i] = 0; if(cache->activeset[i]) nb_SV++; } for(i=1; i<=chunk_size; i++) { random_num = nrand48(xi); row = (random_num % (nb_data-i+1))+1; cache->table_chunk[i] = cache->out_of_chunk[row]; for(j=row; j<=nb_data-i; j++) cache->out_of_chunk[j] = cache->out_of_chunk[j+1]; cache->in_chunk[cache->table_chunk[i]] = 1; } return nb_SV; } /* LLW_init_gradient({ALPHA_IS_ZERO,ALPHA_NOT_ZERO}, gradient, cache, model) */ void LLW_init_gradient(const enum AlphaInitType alpha_init_type, double **gradient, double **H_alpha, const struct Model *model) { long i,j,k,l,y_i; const long nb_data = model->nb_data; const long Q = model->Q; const double Qd = (double)Q; const double Qinv = 1. / (Qd-1.0); const enum Kernel_type nature_kernel = model->nature_kernel; const double *kernel_par = model->kernel_par; long dim_input = model->dim_input; double partial, gradient_ik; if(alpha_init_type == ALPHA_IS_ZERO) { // Fast initialization for(i=1; i<=nb_data; i++) { for(k=1; k<=Q; k++) { gradient[i][k] = -Qinv; H_alpha[i][k] = 0.0; } gradient[i][model->y[i]] = 0.0; } } else { // Do a proper initialization based on the values of alpha for(i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { gradient_ik = 0.0; for(j=1; j<=nb_data; j++) { partial = 0.0; for(l=1; l<=Q; l++) partial -= model->alpha[j][l]; partial /= Qd; partial += model->alpha[j][k]; if(partial != 0.0) gradient_ik += partial * ker(nature_kernel, model->X[i], model->X[j], dim_input,kernel_par); } gradient[i][k] = gradient_ik - Qinv; H_alpha[i][k] = gradient_ik; } else { gradient[i][k] = 0.0; H_alpha[i][k] = 0.0; } } } } } /* Thread for updates of the gradient in parallel (spawn by main computing thread LLW_train_thread) */ void *LLW_update_gradient_thread(void *th_data) { // Recover thread data struct ThreadGradient_data *data = (struct ThreadGradient_data *) th_data; double **gradient = data->gradient; double **H_alpha = data->H_alpha; struct TrainingCache *cache = data->cache; const struct Model *model = data->model; const long start_i = data->start_i; const long end_i = data->end_i; // Local variables long i,j,k,l,y_i,ind_pattern; const long Q = model->Q; const double Qd = (double)Q; const long chunk_size = cache->chunk_size; double partial, gradient_update_ik; for(i=start_i; i<=end_i; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { gradient_update_ik = 0.0; for(j=1; j<=chunk_size; j++) { ind_pattern = cache->table_chunk[j]; partial = 0.0; for(l=1; l<=Q; l++) partial -= cache->alpha_update[j][l]; partial /= Qd; partial += cache->alpha_update[j][k]; if(partial != 0.0) gradient_update_ik += partial * cache->K[j][i]; } gradient[i][k] += gradient_update_ik; H_alpha[i][k] += gradient_update_ik; } } } pthread_exit(EXIT_SUCCESS); } /* Old-style non-threaded gradient update */ void LLW_update_gradient(double **gradient, double **H_alpha, struct TrainingCache *cache, const struct Model *model) { long i,j,k,l,y_i,ind_pattern; const long nb_data = model->nb_data; const long Q = model->Q; const double Qd = (double)Q; const long chunk_size = cache->chunk_size; double partial, gradient_update_ik; for(i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { gradient_update_ik = 0.0; for(j=1; j<=chunk_size; j++) { ind_pattern = cache->table_chunk[j]; partial = 0.0; for(l=1; l<=Q; l++) partial -= cache->alpha_update[j][l]; partial /= Qd; partial += cache->alpha_update[j][k]; if(partial != 0.0) gradient_update_ik += partial * cache->K[j][i]; } gradient[i][k] += gradient_update_ik; H_alpha[i][k] += gradient_update_ik; } } } } /* Same as WW_compute_H_delta() */ void LLW_compute_H_delta(double **delta, struct TrainingCache *cache, const struct Model *model) { long i,k,j,y_i,l; const long Q = model->Q; const double Qd = (double)Q; const long chunk_size = cache->chunk_size; double partial; for(i=1; i<=chunk_size; i++) { y_i = model->y[cache->table_chunk[i]]; for(k=1; k<=Q; k++) { cache->H_delta[i][k] = 0.0; if(k != y_i) { for(j=1; j<=chunk_size; j++) { partial = 0.0; for(l=1; l<=Q; l++) partial -= delta[j][l]; partial /= Qd; partial += delta[j][k]; cache->H_delta[i][k] += partial * cache->K[i][cache->table_chunk[j]]; } } } } } int LLW_check_opt_sol(double **gradient, struct TrainingCache *cache, const struct Model *model) { double gradient_alpha = 0.0; double gradient_Gamma = 0.0; double gradient_diff = 0.0; long i,k,ind_pattern, y_i; const long Q = model->Q; const long chunk_size = cache->chunk_size; int jump = false; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; y_i = model->y[ind_pattern]; for(k=1; k<=Q; k++) if(k != y_i) { gradient_alpha += gradient[ind_pattern][k] * model->alpha[ind_pattern][k]; gradient_Gamma += gradient[ind_pattern][k] * cache->lp_sol[i][k]; } } gradient_diff = gradient_alpha - gradient_Gamma; if(gradient_diff <= 0.0) { if(gradient_diff < -small) { printf("\nInappropriate subset selection...\n"); printf("\ngradient^T (alpha - gamma): %lf", gradient_diff); } jump = true; } cache->gradient_diff = gradient_diff; return jump; } long LLW_compute_new_alpha(const double theta_opt, const struct TrainingCache *cache, struct Model *model) { long i,k,ind_pattern,l,y_i; const long Q = model->Q; const double Qd = (double)Q; const double *C = model->C; const long chunk_size = cache->chunk_size; double alpha_tmp; long nb_SV = 0; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; y_i = model->y[ind_pattern]; // Assume x_i is not a SV if(cache->activeset[ind_pattern]) { cache->activeset[ind_pattern] = 0; nb_SV--; } for(k=1; k<=Q; k++) { cache->alpha_update[i][k] = theta_opt * ( cache->lp_sol[i][k] - model->alpha[ind_pattern][k] ); alpha_tmp = model->alpha[ind_pattern][k] + cache->alpha_update[i][k]; if(alpha_tmp > C[y_i] && alpha_tmp < C[y_i] * ( 1.0 + small_enough)) { cache->alpha_update[i][k] = C[y_i] - model->alpha[ind_pattern][k]; model->alpha[ind_pattern][k] = C[y_i]; } else { model->alpha[ind_pattern][k] = alpha_tmp; if(alpha_tmp > 0.0 && alpha_tmp < C[y_i]) { // Update nb_SV and activeset if(cache->activeset[ind_pattern] == 0) { cache->activeset[ind_pattern] = 1; nb_SV++; } } } } // Update RHS of constraints in LP for(k=1; klp_rhs[k] += cache->alpha_update[i][l]; cache->lp_rhs[k] -= Qd * cache->alpha_update[i][k]; } } return nb_SV; } void LLW_compute_delta(double **delta, const struct TrainingCache *cache, const struct Model *model) { long i,k,ind_pattern; const long Q = model->Q; const long chunk_size = cache->chunk_size; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; for(k=1; k<=Q; k++) delta[i][k] = model->alpha[ind_pattern][k] - cache->lp_sol[i][k]; } } double LLW_compute_theta_opt(double **delta, struct TrainingCache *cache, const struct Model *model) { long i,k; const long chunk_size = cache->chunk_size; const long Q = model->Q; double theta_opt, denominator = 0.0; LLW_compute_H_delta(delta, cache,model); for(i=1; i<=chunk_size; i++) { for(k=1; k<=Q; k++) denominator += delta[i][k] * cache->H_delta[i][k]; } if(denominator <= 0) { printf("\nWrong estimate of theta: denominator= %e\n", denominator); exit(0); } theta_opt = cache->gradient_diff / denominator; if(theta_opt > 1.0) theta_opt = 1.0; return theta_opt; } MSVMpack1.2/src/libtrainMSVM_CS.c~0000644000175000017500000007631511761346511015770 0ustar lauerlauer/* Copyright 2000-2010 Yann Guermeur */ /* 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 2 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, write to the Free Software */ /* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA*/ /*--------------------------------------------------------------------------*/ /* Name : libtrainMSVM_CS.c */ /* Version : 2.0 */ /* Creation : 04/27/00 */ /* Last update : 02/04/11 */ /* Subject : Training algorithm of the M-SVM of Crammer and Singer */ /* Algo. : Frank-Wolfe algorithm + decomposition method */ /* Author : Fabien Lauer and Yann Guermeur Yann.Guermeur@loria.fr */ /*--------------------------------------------------------------------------*/ #include "libtrainMSVM_CS.h" /* Crammer and Singer (CS) MSVM training function Solves the dual problem wrt alpha: min 1/2 alpha' H alpha + sum_i,k ( delta_yi,k alpha_ik ) s.t. alpha_ik >= 0, for all i,k, such that 1 <= i <= m, 1 <= k <= Q sum_k alpha_ik = C, for all i, 1 <= i <= m where H_ik,jl = (delta_yi,yj - delta_yi,l - delta_yj,k + delta_k,l) k(x_i,x_j) */ long MSVM_CS_train(struct Model *model, struct Data *training_set, long chunk_size, const double accuracy, int cache_memory, const int nprocs, char *alpha0_file, char *model_tmp_file, char *log_file) { long return_status = -1; FILE *fp; int t; pthread_t *threads = (pthread_t *)malloc(sizeof(pthread_t) * nprocs); // threads id void *status; // for pthread_join int rc; // return code of pthread functions pthread_t thread_monitor; enum AlphaInitType alphaiszero; if(training_set != NULL) { // Initialize model for this particular training set model_load_data(model, training_set); // Check if a kernel_par has been set if(model->nature_kernel != LINEAR && model->kernel_par == NULL) set_default_kernel_par(model); } if(model->nb_data > 2147483647) { printf("Cannot compute table chunk: number of data above random number limit\n"); exit(0); } // Log file if (log_file != NULL) { printf("\nLog training info in %s ...\n", log_file); fp = fopen(log_file,"a"); } else fp = NULL; double **gradient = matrix(model->nb_data, model->Q); double **H_alpha = matrix(model->nb_data, model->Q); double best_primal_upper_bound = HUGE_VAL; int *activeset = (int *)calloc(model->nb_data+1, sizeof(int)); // including the kernel cache: struct KernelCache kc; unsigned long cache_size = (unsigned long)cache_memory * MBYTES; kernel_initialize_cache(cache_size, &kc, model); printf("Initialization...");fflush(stdout); // Initialize alpha and b if(training_set != NULL) // otherwise resume training CS_init_alpha(model, alpha0_file); if(training_set == NULL || alpha0_file != NULL) alphaiszero = ALPHA_NOT_ZERO; else alphaiszero = ALPHA_IS_ZERO; // Initialize gradient CS_init_gradient(alphaiszero, gradient,H_alpha,model); printf(" Done.\n"); // Initialize display if(accuracy>0) print_training_info(0,0,0,model->type); else { printf("Training...");fflush(stdout); } EVAL = 0; // triggered by signal handler to call eval STOP = 0; // triggered by user to stop training iter = 1; // number of iterations (over all threads) // Prepare monitoring of model struct MonitorData monitor_data; monitor_data.model_tmp_file = model_tmp_file; monitor_data.period = MONITOR_PERIOD; monitor_data.model = model; pthread_create(&thread_monitor, NULL, MSVM_monitor_model_thread, (void *) &monitor_data); // Prepare data for computing threads long nb_SV = 0; struct ThreadData thread_data; thread_data.nprocs = nprocs; thread_data.model = model; thread_data.kernelcache = &kc; thread_data.chunk_size = chunk_size; thread_data.accuracy = accuracy; thread_data.gradient = gradient; thread_data.H_alpha = H_alpha; thread_data.best_primal_upper_bound = &best_primal_upper_bound; thread_data.activeset = activeset; thread_data.nb_SV = &nb_SV; thread_data.logfile_ptr = fp; // Launch nprocs (= #CPUs) computing threads int numthreads=nprocs; if(model->nb_data >= 5000) { // Except if working set selection is used // then retain 25% of CPUs for gradient updates numthreads = nprocs - nprocs/4 + 1; if(numthreads > nprocs) numthreads=nprocs; } for(t=0;tthread_id; const int nprocs = data->nprocs; struct Model *model = data->model; struct KernelCache *kernelcache = data->kernelcache; long chunk_size = data->chunk_size; const double accuracy = data->accuracy; double **gradient = data->gradient; double **H_alpha = data->H_alpha; double *best_primal_upper_bound = data->best_primal_upper_bound; int *activeset = data->activeset; long *nb_SV = data->nb_SV; FILE *fp = data->logfile_ptr; pthread_mutex_unlock(&thread_data_mutex); // Release thread_data for next thread // Prepare the cache struct TrainingCache cache; cache.chunk_size = chunk_size; CS_alloc_memory(&cache, model->Q, model->nb_data, chunk_size); cache.kc = kernelcache; cache.activeset = activeset; // Disable parallel gradient computation and working set selection for small data sets int parallel_gradient_update = 1; int workingset_selection = 1; if(model->nb_data < 5000) { parallel_gradient_update = 0; workingset_selection = 0; } /* Prepare parallel gradient computations: - the gradient vector is split into numthreads_grad parts (along i) - each part is updated by a different thread */ // max number of threads for gradient updates is nprocs pthread_t *grad_threads = (pthread_t *)malloc(sizeof(pthread_t) * nprocs); // start with 1 thread (main load on kernel evaluations) int numthreads_grad = 1; if(workingset_selection) numthreads_grad = nprocs/4; // or #CPUS/4 threads if working set selection is used if(numthreads_grad==0) numthreads_grad = 1; // More CPUs for gradient updates if Q > dimension of data if(model->dim_input < model->Q) numthreads_grad = nprocs; void *status; int rc; long k; struct ThreadGradient_data *grad_data = (struct ThreadGradient_data *)malloc(sizeof(struct ThreadGradient_data) * nprocs); if(parallel_gradient_update) { for(k=0;knb_data / numthreads_grad; for(k=1;knb_data / numthreads_grad -1; } if(numthreads_grad>1) { grad_data[numthreads_grad-1].start_i = grad_data[numthreads_grad-2].end_i + 1; grad_data[numthreads_grad-1].end_i = model->nb_data; } } // Switch to #CPUs/4 threads for gradient update when 25% of the kernel matrix is cached int percentage_step = 1; long percentage = model->nb_data / 4; int next_numthreads_grad = nprocs/4; if(workingset_selection) { // Switch to #CPUs/2 threads for gradient update when 10% of the kernel matrix is cached percentage = model->nb_data / 10; next_numthreads_grad = nprocs/2; } if(next_numthreads_grad == 0) next_numthreads_grad = 1; // No thread switches if Q > dimension of data (keep all CPUs for gradient updates) if(model->dim_input < model->Q) percentage = 2*model->nb_data; // Local variables int verbose = 0; int do_eval; char yesno; long return_status = -1; double **delta = matrix(chunk_size, model->Q); double theta_opt; int jump = false; if(accuracy == 0) do_eval = 0; else do_eval = 1; double ratio = 0.0; // stopping criterion (dual / upper bound) int thread_stop = 0; double psi_max = HUGE_VAL; // Select a random chunk of data for the first step select_random_chunk(&cache,model); do { if((TRAIN_SMALL_STEP < TRAIN_STEP) && (iter%TRAIN_SMALL_STEP) == 0) { printf("."); fflush(stdout); } // Compute the kernel submatrix for the chunk compute_K(&cache,model); // Enter Critical Section (using and modifying the model) pthread_mutex_lock(&model_mutex); jump = CS_solve_lp(gradient, &cache, model); if(jump == false) jump = CS_check_opt_sol(gradient,&cache,model); if(jump == false) { CS_compute_delta(delta,&cache,model); theta_opt = CS_compute_theta_opt(delta, &cache, model); *nb_SV += CS_compute_new_alpha(theta_opt,&cache,model); if(parallel_gradient_update) { // Update gradient in parallel for(k=0;ktype); if(verbose && workingset_selection) printf("\t\t\t\t\t\t (psi = %e )\n",psi_max); if(do_eval && ratio > accuracy) STOP = 1; if(EVAL) // if interrupted by user (otherwise let the ratio decide if we go on training) { printf("\n *** Do you want to continue training ([y]/n)? "); yesno = getchar(); if(yesno=='n') { STOP = 1; } EVAL = 0; // reset interruption trigger } } // Release kernel submatrix in cache release_K(&cache); // Select working set (for next iteration) if(workingset_selection) psi_max = CS_workingset_selection(gradient,&cache,model); else (void)CS_compute_table_chunk(&cache,model); // Check if a sufficient % of the kernel matrix is cached if( parallel_gradient_update && cache.kc->max_idx >= percentage ) { /* and switch thread to compute gradient upates instead of kernel rows if it is (threads are actually stopped to leave the CPUs to other threads that will compute gradient updates) */ if(workingset_selection) thread_stop = CS_switch_thread(nprocs, &numthreads_grad, &next_numthreads_grad, &percentage, &percentage_step, grad_data, thread_id, model->nb_data); else thread_stop = switch_thread(nprocs, &numthreads_grad, &next_numthreads_grad, &percentage, &percentage_step, grad_data, thread_id, model->nb_data); } iter++; // Release mutex: End of critical section pthread_mutex_unlock(&model_mutex); } while(iter <= MSVM_TRAIN_MAXIT && (!do_eval || ratio < accuracy) && !STOP && !thread_stop); // Compute return_status if(do_eval && ratio >= accuracy) return_status = 0; // optimum reached. // Free memory CS_free_memory(&cache); free(delta[1]);free(delta); free(grad_threads); free(grad_data); pthread_exit((void*)return_status); } /* CS_init_alpha(model_ptr, alpha_filename) Initialize the alpha of the model pointed by model_ptr by reading them from the file alpha_filename or setting all alpha to 0 except one for each point */ void CS_init_alpha(struct Model *model, char *alpha_file) { long i,k; const long Q = model->Q; const long nb_data = model->nb_data; const double *C = model->C; // Initialize alpha if(alpha_file == NULL) { if (model->alpha != NULL) { free(model->alpha[1]); free(model->alpha); } model->alpha = matrix(nb_data, Q); model->sum_all_alpha = 0; for(i=1; i<=nb_data; i++) { for(k=1; k<=Q; k++) // Set all alpha_ik to 0 model->alpha[i][k] = 0.0; model->alpha[i][model->y[i]] = C[model->y[i]]; // except alpha_iy_i set to C_yi model->sum_all_alpha += C[model->y[i]]; } } else read_alpha(model, alpha_file); return; } /* Allocate the memory for the cache */ void CS_alloc_memory(struct TrainingCache *cache, const long Q, const long nb_data, const long chunk_size) { cache->table_chunk = (long *) calloc(chunk_size+1, sizeof(long)); cache->table_active = (long *) calloc(nb_data+1, sizeof(long)); cache->out_of_chunk = (long *) calloc(nb_data+1, sizeof(long)); cache->in_chunk = (long *) calloc(nb_data+1, sizeof(long)); cache->lp_sol = matrix(chunk_size, Q); cache->K = (double **)malloc(sizeof(double *) * (chunk_size+1)); cache->H_delta = matrix(chunk_size, Q); cache->alpha_update = matrix(chunk_size, Q); cache->psi = (double *)malloc(sizeof(double) * (nb_data + 1)); } /* Free the cache memory */ void CS_free_memory(struct TrainingCache *cache) { free(cache->table_chunk); free(cache->table_active); free(cache->in_chunk); free(cache->out_of_chunk); free(cache->K); free(cache->lp_sol[1]);free(cache->lp_sol); free(cache->H_delta[1]);free(cache->H_delta); free(cache->alpha_update[1]);free(cache->alpha_update); free(cache->psi); } /* Solve the LP subproblem by calling lp_solve API */ int CS_solve_lp(double **gradient, const struct TrainingCache *cache, const struct Model *model) { long i,k,ind_pattern; const long Q = model->Q; const long chunk_size = cache->chunk_size; const double *C = model->C; const int nRows = chunk_size; const int nCols = chunk_size * Q; double *obj = (double*)malloc(sizeof(double) * (1+nCols)); double *row = (double*)malloc(sizeof(double) * Q); int *cols = (int*)malloc(sizeof(int) * Q); long **lp_sol_table = matrix_l(nCols, 2); long **lp_sol_table_inv = matrix_l(chunk_size, Q); double *sol = (double*)malloc(sizeof(double) * (1+nRows+nCols)); double epsel; // Make LP lprec *lp = make_lp(0, nCols); set_add_rowmode(lp, TRUE); // Make objective function int col = 1; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; for(k=1; k<=Q; k++) { obj[col] = gradient[ind_pattern][k]; lp_sol_table[col][1] = i; // keep a table of correspondance between lp_sol_table[col][2] = k; // LPSOLVE vector of variables and lp_sol matrix lp_sol_table_inv[i][k] = col++; // lp_sol[i][k] = the 'lp_solve_table_inv[i][k]'-th variable for LPSOLVE } } set_obj_fn(lp, obj); // Make constraints : forall i, sum_k alpha_ik = C_yi for(i=1; i<=chunk_size; i++) { for(k=1; k<=Q; k++) { cols[k-1] = (int)lp_sol_table_inv[i][k]; row[k-1] = 1.0; } add_constraintex(lp, Q, row, cols, EQ, C[model->y[cache->table_chunk[i]]]); } // End of LP making set_add_rowmode(lp, FALSE); //print_lp(lp); // Solve LP int jump = false; set_outputfile(lp,""); if(solve(lp)) { printf("Problem with the LP... \n"); jump = true; } else { // Recover solution in the matrix lp_sol get_primal_solution(lp, sol); // sol: template for lp_solve solution format // sol=[obj, constraints, variables] epsel = get_epsel(lp); // tolerance in lp_solve // Put solution into lp_sol for(col=1; col<= nCols; col++) { // Check feasibility of the col-th variable if((sol[nRows+col] < -epsel) || (sol[nRows+col] > C[model->y[cache->table_chunk[lp_sol_table[col][1]]]] + epsel)) { jump = true; break; } // Round off tolerance if(fabs(sol[nRows+col]) < epsel) sol[nRows+col] = 0.0; else if(fabs(sol[nRows+col] - C[model->y[cache->table_chunk[lp_sol_table[col][1]]]]) < epsel) sol[nRows+col] = C[model->y[cache->table_chunk[lp_sol_table[col][1]]]]; // Set the value in lp_sol matrix cache->lp_sol[lp_sol_table[col][1]][lp_sol_table[col][2]] = sol[nRows+col]; } } delete_lp(lp); free(obj); free(row); free(cols); free(lp_sol_table[1]);free(lp_sol_table); free(lp_sol_table_inv[1]);free(lp_sol_table_inv); free(sol); return jump; } /* nb_SV = CS_compute_table_chunk(model) Select a subset of the training set for the next step of optimization */ long CS_compute_table_chunk(struct TrainingCache *cache, const struct Model *model) { long i,random_num,rank; const long nb_data = model->nb_data; const long chunk_size = cache->chunk_size; const long half_chunk_size = chunk_size / 2; long nb_points_chunk,nb_active_var_in_chunk,nb_active_var = 0; for(i=1; i<=nb_data; i++) { cache->in_chunk[i] = 0; if(cache->activeset[i]) cache->table_active[++nb_active_var] = i; } nb_points_chunk = 0; nb_active_var_in_chunk = nb_active_var; if(nb_active_var_in_chunk > half_chunk_size) nb_active_var_in_chunk = half_chunk_size; if(nb_active_var_in_chunk == nb_active_var) for(nb_points_chunk=1; nb_points_chunk <= nb_active_var; nb_points_chunk++) { cache->table_chunk[nb_points_chunk] = cache->table_active[nb_points_chunk]; cache->in_chunk[cache->table_active[nb_points_chunk]] = 1; } else while(nb_points_chunk < nb_active_var_in_chunk) { random_num = nrand48(xi); rank = (random_num % nb_active_var)+1; if(cache->in_chunk[cache->table_active[rank]] == 0) { cache->in_chunk[cache->table_active[rank]] = 1; nb_points_chunk++; cache->table_chunk[nb_points_chunk] = cache->table_active[rank]; } } nb_points_chunk = nb_active_var_in_chunk; while(nb_points_chunk < chunk_size) { random_num = nrand48(xi); rank = (random_num % nb_data)+1; if(cache->in_chunk[rank] == 0) { cache->in_chunk[rank] = 1; nb_points_chunk++; cache->table_chunk[nb_points_chunk] = rank; } } return nb_active_var; } void CS_init_gradient(const enum AlphaInitType alpha_init_type, double **gradient, double **H_alpha, const struct Model *model) { long i,j,k,l,y_i,y_j; const long nb_data = model->nb_data; const long Q = model->Q; const enum Kernel_type nature_kernel = model->nature_kernel; const double *kernel_par = model->kernel_par; const long dim_input = model->dim_input; double partial, gradient_ik; if(alpha_init_type == ALPHA_IS_ZERO) { // Fast initialization /* Matrix alpha is not really zero, but only alpha_i_y_i = C, which results in gradient_ik = 0 except for gradient_i_y_i = 1 */ for(i=1; i<=nb_data; i++) { for(k=1; k<=Q; k++) { gradient[i][k] = 0.0; H_alpha[i][k] = 0.0; } gradient[i][model->y[i]] = 1.0; } } else { // Do a proper initialization based on the values of alpha for(i=1; i<=nb_data; i++) { if(i%1000 == 0) { printf("."); fflush(stdout); } y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { gradient_ik = 0.0; for(j=1; j<=nb_data; j++) { y_j = model->y[j]; partial = 0.0; if(y_j == y_i) for(l=1; l<=Q; l++) partial += model->alpha[j][l]; if(y_j == k) for(l=1; l<=Q; l++) partial -= model->alpha[j][l]; partial += model->alpha[j][k] - model->alpha[j][y_i]; if(partial != 0.0) gradient_ik += partial * ker(nature_kernel, model->X[i], model->X[j], dim_input,kernel_par); } gradient[i][k] = gradient_ik; H_alpha[i][k] = gradient_ik; } else { gradient[i][k] = 1.0; H_alpha[i][k] = 0.0; } } } } } /* Thread for updates of the gradient in parallel (spawn by main computing thread CS_train_thread) */ void *CS_update_gradient_thread(void *th_data) { // Recover thread data struct ThreadGradient_data *data = (struct ThreadGradient_data *) th_data; double **gradient = data->gradient; double **H_alpha = data->H_alpha; struct TrainingCache *cache = data->cache; const struct Model *model = data->model; const long start_i = data->start_i; const long end_i = data->end_i; // Local variables long i,j,k,l,y_i,y_j,ind_pattern; const long Q = model->Q; const long chunk_size = cache->chunk_size; double partial, gradient_update_ik; for(i=start_i; i<=end_i; i++) { y_i = model->y[i]; for(k=1;k<=Q;k++) { if(k != y_i) { gradient_update_ik = 0.0; for(j=1; j<=chunk_size; j++) { ind_pattern = cache->table_chunk[j]; y_j = model->y[ind_pattern]; partial = 0.0; if(y_j == y_i) for(l=1; l<=Q; l++) partial += cache->alpha_update[j][l]; if(y_j == k) for(l=1; l<=Q; l++) partial -= cache->alpha_update[j][l]; partial += cache->alpha_update[j][k] - cache->alpha_update[j][y_i]; gradient_update_ik += partial * cache->K[j][i]; } gradient[i][k] += gradient_update_ik; H_alpha[i][k] += gradient_update_ik; } } } pthread_exit(EXIT_SUCCESS); } /* Old-style non-threaded gradient update */ void CS_update_gradient(double **gradient, double **H_alpha, struct TrainingCache *cache, const struct Model *model) { long i,j,k,l,y_i,y_j,ind_pattern; const long nb_data = model->nb_data; const long Q = model->Q; const long chunk_size = cache->chunk_size; double partial, gradient_update_ik; for(i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { gradient_update_ik = 0.0; for(j=1; j<=chunk_size; j++) { ind_pattern = cache->table_chunk[j]; y_j = model->y[ind_pattern]; partial = 0.0; if(y_j == y_i) for(l=1; l<=Q; l++) partial += cache->alpha_update[j][l]; if(y_j == k) for(l=1; l<=Q; l++) partial -= cache->alpha_update[j][l]; partial += cache->alpha_update[j][k] - cache->alpha_update[j][y_i]; gradient_update_ik += partial * cache->K[j][i]; } gradient[i][k] += gradient_update_ik; H_alpha[i][k] += gradient_update_ik; } } } } /* Same as WW_compute_H_delta() */ void CS_compute_H_delta(double **delta, struct TrainingCache *cache, const struct Model *model) { long i,k,j,y_i,y_j,l; const long Q = model->Q; const long chunk_size = cache->chunk_size; double partial; for(i=1; i<=chunk_size; i++) { y_i = model->y[cache->table_chunk[i]]; for(k=1; k<=Q; k++) { cache->H_delta[i][k] = 0.0; if(k != y_i) { for(j=1; j<=chunk_size; j++) { y_j = model->y[cache->table_chunk[j]]; partial = 0.0; if(y_j == y_i) for(l=1; l<=Q; l++) partial += delta[j][l]; if(y_j == k) for(l=1; l<=Q; l++) partial -= delta[j][l]; partial += delta[j][k] - delta[j][y_i]; cache->H_delta[i][k] += partial * cache->K[i][cache->table_chunk[j]]; } } } } } int CS_check_opt_sol(double **gradient, struct TrainingCache *cache, const struct Model *model) { double gradient_alpha = 0.0; double gradient_Gamma = 0.0; double gradient_diff = 0.0; long i,k,ind_pattern; const long Q = model->Q; const long chunk_size = cache->chunk_size; int jump = false; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; for(k=1; k<=Q; k++) { gradient_alpha += gradient[ind_pattern][k] * model->alpha[ind_pattern][k]; gradient_Gamma += gradient[ind_pattern][k] * cache->lp_sol[i][k]; } } gradient_diff = gradient_alpha - gradient_Gamma; if(gradient_diff <= 0.0) { if(gradient_diff < -small) { printf("\nInappropriate subset selection...\n"); printf("\ngradient^T (alpha - gamma): %lf", gradient_diff); } jump = true; } cache->gradient_diff = gradient_diff; return jump; } /* Update model paramaters alpha_ik Return the difference in number of SVs */ long CS_compute_new_alpha(const double theta_opt, const struct TrainingCache *cache, struct Model *model) { long i,k,ind_pattern,y_i; const long Q = model->Q; const double *C = model->C; const long chunk_size = cache->chunk_size; double alpha_tmp; long nb_SV = 0; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; y_i = model->y[ind_pattern]; // Assume x_i is not a SV if(cache->activeset[ind_pattern]) { cache->activeset[ind_pattern] = 0; nb_SV--; } // Update alpha_ik for(k=1; k<=Q; k++) { cache->alpha_update[i][k] = theta_opt * ( cache->lp_sol[i][k] - model->alpha[ind_pattern][k] ); alpha_tmp = model->alpha[ind_pattern][k] + cache->alpha_update[i][k]; if(alpha_tmp > C[y_i] && alpha_tmp < C[y_i] * ( 1.0 + small_enough)) { cache->alpha_update[i][k] = C[y_i] - model->alpha[ind_pattern][k]; model->alpha[ind_pattern][k] = C[y_i]; } else { model->alpha[ind_pattern][k] = alpha_tmp; if(alpha_tmp > 0.0 && alpha_tmp < C[y_i]) { // Update nb_SV and activeset if(cache->activeset[ind_pattern] == 0) { cache->activeset[ind_pattern] = 1; nb_SV++; } } } } } return nb_SV; } void CS_compute_delta(double **delta, const struct TrainingCache *cache, const struct Model *model) { long i,k,ind_pattern; const long Q = model->Q; const long chunk_size = cache->chunk_size; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; for(k=1; k<=Q; k++) delta[i][k] = model->alpha[ind_pattern][k] - cache->lp_sol[i][k]; } } double CS_compute_theta_opt(double **delta, struct TrainingCache *cache, const struct Model *model) { long i,k, y_i; const long chunk_size = cache->chunk_size; const long Q = model->Q; double theta_opt, denominator = 0.0; CS_compute_H_delta(delta, cache,model); for(i=1; i<=chunk_size; i++) { y_i = model->y[cache->table_chunk[i]]; for(k=1; k<=Q; k++) if(k != y_i) denominator += delta[i][k] * cache->H_delta[i][k]; } if(denominator < 0) { printf("\nWrong estimate of theta: denominator= %e\n", denominator); exit(0); } else if (denominator == 0) theta_opt = 0.0; else theta_opt = cache->gradient_diff / denominator; if(theta_opt > 1.0) theta_opt = 1.0; return theta_opt; } /* Working set selection based on KKT condition select points with maximal violation of the KKT condition as measured by psi_i = max_{k, alpha_ik>0} gradient_ik - min_k gradient_ik returns max_i (psi_i) */ double CS_workingset_selection(double **Fmatrix, struct TrainingCache *cache, const struct Model *model) { //int isSV=0; long i,j; const long chunk_size = cache->chunk_size; long *next_chunk = cache->table_chunk; double *psi = cache->psi; const long Q = model->Q; const long nb_data = model->nb_data; long k,ind_pattern; double Fmax, Fmin,Fik, psi_max; for(j=1; j<=chunk_size; j++) next_chunk[j] = 0; for(i=1; i<=nb_data; i++) { Fmax = -HUGE_VAL; Fmin = HUGE_VAL; for(k=1; k<=Q; k++) { Fik = Fmatrix[i][k]; if(Fik > Fmax && (model->alpha[i][k] > 0.001)) Fmax = Fik; if(Fik < Fmin ) Fmin = Fik; } // Update psi_i psi[i] = Fmax - Fmin; // and the ordered list of maximal psi for(j=1; j<=chunk_size; j++) { ind_pattern = next_chunk[j]; if(ind_pattern == 0 || psi[i] > psi[ind_pattern]) { // Insert i here for(k=chunk_size;k>j;k--) next_chunk[k] = next_chunk[k-1]; next_chunk[j] = i; break; } } } psi_max = psi[next_chunk[1]]; /* for(j=1; j<=chunk_size; j++) { if(model->alpha[next_chunk[j]][model->y[next_chunk[j]]] < model->C) isSV++; } if(isSV < chunk_size) printf("isSV=%d\n",isSV); */ return psi_max; } /* This function overrides switch_thread() from libtrainMSVM.C with better thresholds when nonrandom working set selection is used. Switch working load between threads from main (kernel) computations to gradient updates As as result, the number of threads used for gradient updates increases while main computing threads (CS_train_thread) are terminated returns 1 if the calling main thread must stop */ int __inline__ CS_switch_thread(const int nprocs, int *numthreads_grad, int *next_numthreads_grad, long *percentage, int *percentage_step, struct ThreadGradient_data *grad_data, int thread_id, long nb_data) { int k; // Keep (nprocs - next_numthreads_grad + 1) main computing threads // for kernel evaluations if(thread_id < nprocs - *next_numthreads_grad + 1){ // This calling thread continues with more children to compute gradient updates *numthreads_grad = *next_numthreads_grad; // Update splits of the gradient vector grad_data[0].start_i = 1; grad_data[0].end_i = nb_data / *numthreads_grad; for(k=1;k<*numthreads_grad-1;k++) { grad_data[k].start_i = grad_data[k-1].end_i + 1; grad_data[k].end_i = grad_data[k].start_i + nb_data / *numthreads_grad -1; } if(*numthreads_grad>1) { grad_data[*numthreads_grad-1].start_i = grad_data[*numthreads_grad-2].end_i + 1; grad_data[*numthreads_grad-1].end_i = nb_data; } // Update percentage for next step switch(*percentage_step) { case 1: *percentage = nb_data / 5; // 20% of kernel matrix *next_numthreads_grad = 3*nprocs/4; // -> 75% of CPUs for gradient break; case 2: *percentage = nb_data / 3; // 33% *next_numthreads_grad = nprocs-1; // -> all CPUs - 1 break; case 3: *percentage = nb_data / 2; // 50% *next_numthreads_grad = nprocs; // -> all CPUs break; default: *percentage = 2*nb_data; // no more steps break; } if(*next_numthreads_grad == 0) *next_numthreads_grad = 1; *percentage_step += 1; return 0; } else { // The calling thread must stop (enough kernel rows have been computed) //printf("%ld rows of kernel matrix cached, stopping thread %d... \n",percentage,thread_id); return 1; } } MSVMpack1.2/src/libtrainMSVM_LLW.c0000644000175000017500000006236311761347353015726 0ustar lauerlauer/* Copyright 2000-2010 Yann Guermeur */ /* 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 2 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, write to the Free Software */ /* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA*/ /*--------------------------------------------------------------------------*/ /* Name : libtrainMSVM_LLW.c */ /* Version : 2.0 */ /* Creation : 04/27/00 */ /* Last update : 11/29/10 */ /* Subject : Training algorithm of the M-SVM of Lee, Lin and Wahba */ /* Algo. : Frank-Wolfe algorithm + decomposition method */ /* Author : Fabien Lauer and Yann Guermeur Yann.Guermeur@loria.fr */ /*--------------------------------------------------------------------------*/ #include "libtrainMSVM_LLW.h" /* Lee,Lin, and Wahba (LLW) MSVM training function Solves the dual problem wrt alpha: min 1/2 alpha' H alpha - (1/Q-1) sum (alpha) s.t. 0 <= alpha_ik <= C, for all i,k, such that 1 <= i <= m, 1 <= k != y_i <= Q sum_i (alpha_ik - average_alpha_k) = 0, for all k, 1 <= k <= Q where H_ik,jl = (delta_k,l - 1/Q) k(x_i,x_j) */ long MSVM_LLW_train(struct Model *model, struct Data *training_set, long chunk_size, const double accuracy, int cache_memory, const int nprocs, char *alpha0_file, char *model_tmp_file, char *log_file) { long return_status = -1; FILE *fp; int t; pthread_t *threads = (pthread_t *)malloc(sizeof(pthread_t) * nprocs); // threads id void *status; // for pthread_join int rc; // return code of pthread functions pthread_t thread_monitor; enum AlphaInitType alphaiszero; if(training_set != NULL) { // Initialize model for this particular training set model_load_data(model, training_set); // Check if a kernel_par has been set if(model->nature_kernel != LINEAR && model->kernel_par == NULL) set_default_kernel_par(model); } if(model->nb_data > 2147483647) { printf("Cannot compute table chunk: number of data above random number limit\n"); exit(0); } // Log file if (log_file != NULL) { printf("\nLog training info in %s ...\n", log_file); fp = fopen(log_file,"a"); } else fp = NULL; // Initialize alpha and b if(training_set != NULL) // otherwise resume training init_alpha_b(model, alpha0_file); // use init_alpha_b(model, NULL); to initialize all alpha to 0 if(training_set == NULL || alpha0_file != NULL) alphaiszero = ALPHA_NOT_ZERO; else alphaiszero = ALPHA_IS_ZERO; EVAL = 0; // triggered by signal handler to call eval STOP = 0; // triggered by user to stop training iter = 1; // number of iterations (over all threads) // Prepare monitoring of model struct MonitorData monitor_data; monitor_data.model_tmp_file = model_tmp_file; monitor_data.period = MONITOR_PERIOD; monitor_data.model = model; pthread_create(&thread_monitor, NULL, MSVM_monitor_model_thread, (void *) &monitor_data); // Allocate memory for shared ressources double **gradient = matrix(model->nb_data, model->Q); double **H_alpha = matrix(model->nb_data, model->Q); double best_primal_upper_bound = HUGE_VAL; int *activeset = (int *)calloc(model->nb_data+1, sizeof(int)); double *lp_rhs = (double*)calloc(model->Q, sizeof(double)); // including the kernel cache: struct KernelCache kc; unsigned long cache_size = (unsigned long)cache_memory * MBYTES; kernel_initialize_cache(cache_size, &kc, model); printf("Initialization... ");fflush(stdout); // Initialize gradient LLW_init_gradient(alphaiszero, gradient, H_alpha,model); printf("Done.\n"); // Initialize display if(accuracy>0) print_training_info(0,0,0,model->type); else { printf("Training...");fflush(stdout); } // Prepare data for computing threads long nb_SV = 0; struct ThreadData thread_data; thread_data.nprocs = nprocs; thread_data.model = model; thread_data.kernelcache = &kc; thread_data.chunk_size = chunk_size; thread_data.accuracy = accuracy; thread_data.gradient = gradient; thread_data.H_alpha = H_alpha; thread_data.best_primal_upper_bound = &best_primal_upper_bound; thread_data.activeset = activeset; thread_data.nb_SV = &nb_SV; thread_data.lp_rhs = lp_rhs; thread_data.logfile_ptr = fp; // Launch computing threads for(t=0;tthread_id; const int nprocs = data->nprocs; struct Model *model = data->model; struct KernelCache *kernelcache = data->kernelcache; long chunk_size = data->chunk_size; const double accuracy = data->accuracy; double **gradient = data->gradient; double **H_alpha = data->H_alpha; double *best_primal_upper_bound = data->best_primal_upper_bound; int *activeset = data->activeset; long *nb_SV = data->nb_SV; double *lp_rhs = data->lp_rhs; FILE *fp = data->logfile_ptr; pthread_mutex_unlock(&thread_data_mutex); // Release thread_data for next thread // Local variables int do_eval; char yesno; long return_status = -1; // Prepare the cache struct TrainingCache cache; cache.chunk_size = chunk_size; LLW_alloc_memory(&cache, model->Q, model->nb_data, chunk_size); cache.kc = kernelcache; cache.activeset = activeset; cache.lp_rhs = lp_rhs; double **delta = matrix(chunk_size, model->Q); double theta_opt; int jump = false; if(accuracy == 0) do_eval = 0; else do_eval = 1; /* Prepare parallel gradient computations: - the gradient vector is split into NUMTHREADS_GRAD parts (along i) - each part is updated by a different thread */ // max number of threads for gradient updates is nprocs pthread_t *grad_threads = (pthread_t *)malloc(sizeof(pthread_t) * nprocs); // start with 1 thread (main load on kernel evaluations) int numthreads_grad = 1; void *status; int rc; long k; struct ThreadGradient_data *grad_data = (struct ThreadGradient_data *)malloc(sizeof(struct ThreadGradient_data) * nprocs); // Disable parallel gradient computation for small data sets int parallel_gradient_update = 1; if(model->nb_data < 5000) parallel_gradient_update = 0; if(parallel_gradient_update) { for(k=0;knb_data / numthreads_grad; for(k=1;knb_data / numthreads_grad -1; } if(numthreads_grad>1) { grad_data[numthreads_grad-1].start_i = grad_data[numthreads_grad-2].end_i + 1; grad_data[numthreads_grad-1].end_i = model->nb_data; } } // Switch to nprocs/4 threads for gradient update when 25% of the kernel matrix is cached int percentage_step = 1; long percentage = model->nb_data / 4; int next_numthreads_grad = nprocs/4; if(next_numthreads_grad == 0) next_numthreads_grad = 1; // Main loop double ratio = 0.0; // stopping criterion (dual / upper bound) int thread_stop = 0; do { if((TRAIN_SMALL_STEP < TRAIN_STEP) && (iter%TRAIN_SMALL_STEP) == 0) { printf("."); fflush(stdout); } // Select a random chunk of data to optimize select_random_chunk(&cache,model); // Compute the kernel submatrix for this chunk compute_K(&cache,model); // Enter Critical Section (using and modifying the model) pthread_mutex_lock(&model_mutex); jump = LLW_solve_lp(gradient, &cache, model); if(jump == false) jump = LLW_check_opt_sol(gradient,&cache,model); if(jump == false) { LLW_compute_delta(delta,&cache,model); theta_opt = LLW_compute_theta_opt(delta, &cache, model); *nb_SV += LLW_compute_new_alpha(theta_opt,&cache,model); if(parallel_gradient_update) { // Update gradient in parallel for(k=0;ktype); if(do_eval && ratio > accuracy) STOP = 1; if(EVAL) // if interrupted by user (otherwise let the ratio decide if we go on training) { printf("\n *** Do you want to continue training ([y]/n)? "); yesno = getchar(); if(yesno=='n') { STOP = 1; } EVAL = 0; // reset interruption trigger } } // Release kernel submatrix in cache release_K(&cache); // Check if a sufficient % of the kernel matrix is cached if( parallel_gradient_update && cache.kc->max_idx >= percentage ) { // and switch thread to compute gradient upates instead of kernel rows if it is thread_stop = switch_thread(nprocs, &numthreads_grad, &next_numthreads_grad, &percentage, &percentage_step, grad_data, thread_id, model->nb_data); // (threads are actually stopped to leave the CPUs // to other threads that will compute gradient updates) } iter++; // Release mutex: End of critical section pthread_mutex_unlock(&model_mutex); } while(iter <= MSVM_TRAIN_MAXIT && (!do_eval || ratio < accuracy) && !STOP && !thread_stop); // Release mutex: End of critical section (see below) pthread_mutex_unlock(&model_mutex); // compute return_status if(do_eval && ratio >= accuracy) return_status = 0; // optimum reached. // Free memory LLW_free_memory(&cache); free(delta[1]);free(delta); free(grad_threads); free(grad_data); pthread_exit((void*)return_status); } /* Allocate the memory for the cache */ void LLW_alloc_memory(struct TrainingCache *cache, const long Q, const long nb_data, const long chunk_size) { cache->table_chunk = (long *) calloc(chunk_size+1, sizeof(long)); cache->out_of_chunk = (long *) calloc(nb_data+1, sizeof(long)); cache->in_chunk = (long *) calloc(nb_data+1, sizeof(long)); cache->lp_sol = matrix(chunk_size, Q); cache->K = (double **)malloc(sizeof(double *) * (chunk_size+1)); cache->H_delta = matrix(chunk_size, Q); cache->alpha_update = matrix(chunk_size, Q); } /* Free the cache memory */ void LLW_free_memory(struct TrainingCache *cache) { free(cache->table_chunk); free(cache->out_of_chunk); free(cache->in_chunk); free(cache->K); free(cache->lp_sol[1]);free(cache->lp_sol); free(cache->H_delta[1]);free(cache->H_delta); free(cache->alpha_update[1]);free(cache->alpha_update); } /* Solve the LP subproblem by calling lp_solve API */ int LLW_solve_lp(double **gradient, const struct TrainingCache *cache, const struct Model *model) { long i,k,l,ind_pattern,y_i; const long Q = model->Q; const double Qd = (double)Q; const long chunk_size = cache->chunk_size; const double *C = model->C; const int nRows = Q-1; const int nCols = chunk_size * Q; double *obj = (double*)malloc(sizeof(double) * (1+nCols)); double *row = (double*)malloc(sizeof(double) * (1+nCols)); double *rhs = (double*)malloc(sizeof(double) * Q); long **lp_sol_table = matrix_l(nCols, 2); long **lp_sol_table_inv = matrix_l(chunk_size, Q); double *sol = (double*)malloc(sizeof(double) * (1+nRows+nCols)); double epsel; // Make LP lprec *lp = make_lp(0, nCols); set_add_rowmode(lp, TRUE); // Make objective function int col = 1; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; for(k=1; k<=Q; k++) { obj[col] = gradient[ind_pattern][k]; lp_sol_table[col][1] = i; // keep a table of correspondance between lp_sol_table[col][2] = k; // LPSOLVE vector of variables and lp_sol matrix lp_sol_table_inv[i][k] = col++; // lp_sol[i][k] = the 'lp_solve_table_inv[i][k]'-th variable for LPSOLVE } } set_obj_fn(lp, obj); /* // Make RHS of constraints // -- complete computation -- for(k=1; kin_chunk[i] == 0) { for(l=1; l<=Q; l++) rhs[k] += model->alpha[i][l]; rhs[k] -= Qd * model->alpha[i][k]; } } */ // Make RHS of constraints // -- updates to cache->rhs are made in compute_new_alpha() // to keep track of rhs // we only need to remove the contribution of the examples in the chunk for(k=1; klp_rhs[k]; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; for(l=1; l<=Q; l++) rhs[k] -= model->alpha[ind_pattern][l]; rhs[k] += Qd * model->alpha[ind_pattern][k]; } } // Make constraints for(k=1; ktable_chunk[i]; y_i = model->y[ind_pattern]; for(l=1; l<=Q; l++) if(l != y_i) { row[lp_sol_table_inv[i][l]] = -1.0; if(l == k) row[lp_sol_table_inv[i][l]] += Qd; } } add_constraint(lp, row, EQ, rhs[k]); } // Upper bound constraints: alpha <= Cy_i for(col=1;col<=nCols;col++) set_upbo(lp, col, C[model->y[cache->table_chunk[lp_sol_table[col][1]]]]); /* for(i=1; i<=chunk_size; i++) { for(k=1; k<=Q; k++) if(k != model->y[cache->table_chunk[i]]) { col = (int)lp_sol_table_inv[i][k]; set_upbo(lp, col, C); } } */ // End of LP making set_add_rowmode(lp, FALSE); //print_lp(lp); // Solve LP int jump = false; set_outputfile(lp,""); if(solve(lp)) { printf("Problem with the LP... \n"); jump = true; } else { // Recover solution in the matrix lp_sol get_primal_solution(lp, sol); // sol: template for lp_solve solution format // sol=[obj, constraints, variables] epsel = get_epsel(lp); // tolerance in lp_solve // Put solution into lp_sol for(col=1; col<= nCols; col++) { // Check feasibility of the col-th variable if((sol[nRows+col] < -epsel) || (sol[nRows+col] > C[model->y[cache->table_chunk[lp_sol_table[col][1]]]] + epsel)) { jump = true; break; } // Round off tolerance if(fabs(sol[nRows+col]) < epsel) sol[nRows+col] = 0.0; else if(fabs(sol[nRows+col] - C[model->y[cache->table_chunk[lp_sol_table[col][1]]]]) < epsel) sol[nRows+col] = C[model->y[cache->table_chunk[lp_sol_table[col][1]]]]; // Set the value in lp_sol matrix cache->lp_sol[lp_sol_table[col][1]][lp_sol_table[col][2]] = sol[nRows+col]; } } delete_lp(lp); free(obj); free(row); free(rhs); free(lp_sol_table[1]);free(lp_sol_table); free(lp_sol_table_inv[1]);free(lp_sol_table_inv); free(sol); return jump; } /* nb_SV = LLW_compute_table_chunk(model) Select a subset of the training set for the next step of optimization */ long LLW_compute_table_chunk(struct TrainingCache *cache, const struct Model *model) { long i,j,random_num,row; const long nb_data = model->nb_data; const long chunk_size = cache->chunk_size; long nb_SV = 0; for(i=1; i<=nb_data; i++) { cache->out_of_chunk[i] = i; cache->in_chunk[i] = 0; if(cache->activeset[i]) nb_SV++; } for(i=1; i<=chunk_size; i++) { random_num = nrand48(xi); row = (random_num % (nb_data-i+1))+1; cache->table_chunk[i] = cache->out_of_chunk[row]; for(j=row; j<=nb_data-i; j++) cache->out_of_chunk[j] = cache->out_of_chunk[j+1]; cache->in_chunk[cache->table_chunk[i]] = 1; } return nb_SV; } /* LLW_init_gradient({ALPHA_IS_ZERO,ALPHA_NOT_ZERO}, gradient, cache, model) */ void LLW_init_gradient(const enum AlphaInitType alpha_init_type, double **gradient, double **H_alpha, const struct Model *model) { long i,j,k,l,y_i; const long nb_data = model->nb_data; const long Q = model->Q; const double Qd = (double)Q; const double Qinv = 1. / (Qd-1.0); const enum Kernel_type nature_kernel = model->nature_kernel; const double *kernel_par = model->kernel_par; long dim_input = model->dim_input; double partial, gradient_ik; if(alpha_init_type == ALPHA_IS_ZERO) { // Fast initialization for(i=1; i<=nb_data; i++) { for(k=1; k<=Q; k++) { gradient[i][k] = -Qinv; H_alpha[i][k] = 0.0; } gradient[i][model->y[i]] = 0.0; } } else { // Do a proper initialization based on the values of alpha for(i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { gradient_ik = 0.0; for(j=1; j<=nb_data; j++) { partial = 0.0; for(l=1; l<=Q; l++) partial -= model->alpha[j][l]; partial /= Qd; partial += model->alpha[j][k]; if(partial != 0.0) gradient_ik += partial * ker(nature_kernel, model->X[i], model->X[j], dim_input,kernel_par); } gradient[i][k] = gradient_ik - Qinv; H_alpha[i][k] = gradient_ik; } else { gradient[i][k] = 0.0; H_alpha[i][k] = 0.0; } } } } } /* Thread for updates of the gradient in parallel (spawn by main computing thread LLW_train_thread) */ void *LLW_update_gradient_thread(void *th_data) { // Recover thread data struct ThreadGradient_data *data = (struct ThreadGradient_data *) th_data; double **gradient = data->gradient; double **H_alpha = data->H_alpha; struct TrainingCache *cache = data->cache; const struct Model *model = data->model; const long start_i = data->start_i; const long end_i = data->end_i; // Local variables long i,j,k,l,y_i,ind_pattern; const long Q = model->Q; const double Qd = (double)Q; const long chunk_size = cache->chunk_size; double partial, gradient_update_ik; for(i=start_i; i<=end_i; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { gradient_update_ik = 0.0; for(j=1; j<=chunk_size; j++) { ind_pattern = cache->table_chunk[j]; partial = 0.0; for(l=1; l<=Q; l++) partial -= cache->alpha_update[j][l]; partial /= Qd; partial += cache->alpha_update[j][k]; if(partial != 0.0) gradient_update_ik += partial * cache->K[j][i]; } gradient[i][k] += gradient_update_ik; H_alpha[i][k] += gradient_update_ik; } } } pthread_exit(EXIT_SUCCESS); } /* Old-style non-threaded gradient update */ void LLW_update_gradient(double **gradient, double **H_alpha, struct TrainingCache *cache, const struct Model *model) { long i,j,k,l,y_i,ind_pattern; const long nb_data = model->nb_data; const long Q = model->Q; const double Qd = (double)Q; const long chunk_size = cache->chunk_size; double partial, gradient_update_ik; for(i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { gradient_update_ik = 0.0; for(j=1; j<=chunk_size; j++) { ind_pattern = cache->table_chunk[j]; partial = 0.0; for(l=1; l<=Q; l++) partial -= cache->alpha_update[j][l]; partial /= Qd; partial += cache->alpha_update[j][k]; if(partial != 0.0) gradient_update_ik += partial * cache->K[j][i]; } gradient[i][k] += gradient_update_ik; H_alpha[i][k] += gradient_update_ik; } } } } /* Same as WW_compute_H_delta() */ void LLW_compute_H_delta(double **delta, struct TrainingCache *cache, const struct Model *model) { long i,k,j,y_i,l; const long Q = model->Q; const double Qd = (double)Q; const long chunk_size = cache->chunk_size; double partial; for(i=1; i<=chunk_size; i++) { y_i = model->y[cache->table_chunk[i]]; for(k=1; k<=Q; k++) { cache->H_delta[i][k] = 0.0; if(k != y_i) { for(j=1; j<=chunk_size; j++) { partial = 0.0; for(l=1; l<=Q; l++) partial -= delta[j][l]; partial /= Qd; partial += delta[j][k]; cache->H_delta[i][k] += partial * cache->K[i][cache->table_chunk[j]]; } } } } } int LLW_check_opt_sol(double **gradient, struct TrainingCache *cache, const struct Model *model) { double gradient_alpha = 0.0; double gradient_Gamma = 0.0; double gradient_diff = 0.0; long i,k,ind_pattern, y_i; const long Q = model->Q; const long chunk_size = cache->chunk_size; int jump = false; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; y_i = model->y[ind_pattern]; for(k=1; k<=Q; k++) if(k != y_i) { gradient_alpha += gradient[ind_pattern][k] * model->alpha[ind_pattern][k]; gradient_Gamma += gradient[ind_pattern][k] * cache->lp_sol[i][k]; } } gradient_diff = gradient_alpha - gradient_Gamma; if(gradient_diff <= 0.0) { if(gradient_diff < -small) { printf("\nInappropriate subset selection...\n"); printf("\ngradient^T (alpha - gamma): %lf", gradient_diff); } jump = true; } cache->gradient_diff = gradient_diff; return jump; } long LLW_compute_new_alpha(const double theta_opt, const struct TrainingCache *cache, struct Model *model) { long i,k,ind_pattern,l,y_i; const long Q = model->Q; const double Qd = (double)Q; const double *C = model->C; const long chunk_size = cache->chunk_size; double alpha_tmp; long nb_SV = 0; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; y_i = model->y[ind_pattern]; // Assume x_i is not a SV if(cache->activeset[ind_pattern]) { cache->activeset[ind_pattern] = 0; nb_SV--; } for(k=1; k<=Q; k++) { cache->alpha_update[i][k] = theta_opt * ( cache->lp_sol[i][k] - model->alpha[ind_pattern][k] ); alpha_tmp = model->alpha[ind_pattern][k] + cache->alpha_update[i][k]; if(alpha_tmp > C[y_i] && alpha_tmp < C[y_i] * ( 1.0 + small_enough)) { cache->alpha_update[i][k] = C[y_i] - model->alpha[ind_pattern][k]; model->alpha[ind_pattern][k] = C[y_i]; } else { model->alpha[ind_pattern][k] = alpha_tmp; if(alpha_tmp > 0.0 && alpha_tmp < C[y_i]) { // Update nb_SV and activeset if(cache->activeset[ind_pattern] == 0) { cache->activeset[ind_pattern] = 1; nb_SV++; } } } } // Update RHS of constraints in LP for(k=1; klp_rhs[k] += cache->alpha_update[i][l]; cache->lp_rhs[k] -= Qd * cache->alpha_update[i][k]; } } return nb_SV; } void LLW_compute_delta(double **delta, const struct TrainingCache *cache, const struct Model *model) { long i,k,ind_pattern; const long Q = model->Q; const long chunk_size = cache->chunk_size; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; for(k=1; k<=Q; k++) delta[i][k] = model->alpha[ind_pattern][k] - cache->lp_sol[i][k]; } } double LLW_compute_theta_opt(double **delta, struct TrainingCache *cache, const struct Model *model) { long i,k; const long chunk_size = cache->chunk_size; const long Q = model->Q; double theta_opt, denominator = 0.0; LLW_compute_H_delta(delta, cache,model); for(i=1; i<=chunk_size; i++) { for(k=1; k<=Q; k++) denominator += delta[i][k] * cache->H_delta[i][k]; } if(denominator <= 0) { printf("\nWrong estimate of theta: denominator= %e\n", denominator); exit(0); } theta_opt = cache->gradient_diff / denominator; if(theta_opt > 1.0) theta_opt = 1.0; return theta_opt; } MSVMpack1.2/src/libtrainMSVM_CS.c0000644000175000017500000007631611761347366015604 0ustar lauerlauer/* Copyright 2000-2010 Yann Guermeur */ /* 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 2 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, write to the Free Software */ /* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA*/ /*--------------------------------------------------------------------------*/ /* Name : libtrainMSVM_CS.c */ /* Version : 2.0 */ /* Creation : 04/27/00 */ /* Last update : 02/04/11 */ /* Subject : Training algorithm of the M-SVM of Crammer and Singer */ /* Algo. : Frank-Wolfe algorithm + decomposition method */ /* Author : Fabien Lauer and Yann Guermeur Yann.Guermeur@loria.fr */ /*--------------------------------------------------------------------------*/ #include "libtrainMSVM_CS.h" /* Crammer and Singer (CS) MSVM training function Solves the dual problem wrt alpha: min 1/2 alpha' H alpha + sum_i,k ( delta_yi,k alpha_ik ) s.t. alpha_ik >= 0, for all i,k, such that 1 <= i <= m, 1 <= k <= Q sum_k alpha_ik = C, for all i, 1 <= i <= m where H_ik,jl = (delta_yi,yj - delta_yi,l - delta_yj,k + delta_k,l) k(x_i,x_j) */ long MSVM_CS_train(struct Model *model, struct Data *training_set, long chunk_size, const double accuracy, int cache_memory, const int nprocs, char *alpha0_file, char *model_tmp_file, char *log_file) { long return_status = -1; FILE *fp; int t; pthread_t *threads = (pthread_t *)malloc(sizeof(pthread_t) * nprocs); // threads id void *status; // for pthread_join int rc; // return code of pthread functions pthread_t thread_monitor; enum AlphaInitType alphaiszero; if(training_set != NULL) { // Initialize model for this particular training set model_load_data(model, training_set); // Check if a kernel_par has been set if(model->nature_kernel != LINEAR && model->kernel_par == NULL) set_default_kernel_par(model); } if(model->nb_data > 2147483647) { printf("Cannot compute table chunk: number of data above random number limit\n"); exit(0); } // Log file if (log_file != NULL) { printf("\nLog training info in %s ...\n", log_file); fp = fopen(log_file,"a"); } else fp = NULL; double **gradient = matrix(model->nb_data, model->Q); double **H_alpha = matrix(model->nb_data, model->Q); double best_primal_upper_bound = HUGE_VAL; int *activeset = (int *)calloc(model->nb_data+1, sizeof(int)); // including the kernel cache: struct KernelCache kc; unsigned long cache_size = (unsigned long)cache_memory * MBYTES; kernel_initialize_cache(cache_size, &kc, model); printf("Initialization...");fflush(stdout); // Initialize alpha and b if(training_set != NULL) // otherwise resume training CS_init_alpha(model, alpha0_file); if(training_set == NULL || alpha0_file != NULL) alphaiszero = ALPHA_NOT_ZERO; else alphaiszero = ALPHA_IS_ZERO; // Initialize gradient CS_init_gradient(alphaiszero, gradient,H_alpha,model); printf(" Done.\n"); // Initialize display if(accuracy>0) print_training_info(0,0,0,model->type); else { printf("Training...");fflush(stdout); } EVAL = 0; // triggered by signal handler to call eval STOP = 0; // triggered by user to stop training iter = 1; // number of iterations (over all threads) // Prepare monitoring of model struct MonitorData monitor_data; monitor_data.model_tmp_file = model_tmp_file; monitor_data.period = MONITOR_PERIOD; monitor_data.model = model; pthread_create(&thread_monitor, NULL, MSVM_monitor_model_thread, (void *) &monitor_data); // Prepare data for computing threads long nb_SV = 0; struct ThreadData thread_data; thread_data.nprocs = nprocs; thread_data.model = model; thread_data.kernelcache = &kc; thread_data.chunk_size = chunk_size; thread_data.accuracy = accuracy; thread_data.gradient = gradient; thread_data.H_alpha = H_alpha; thread_data.best_primal_upper_bound = &best_primal_upper_bound; thread_data.activeset = activeset; thread_data.nb_SV = &nb_SV; thread_data.logfile_ptr = fp; // Launch nprocs (= #CPUs) computing threads int numthreads=nprocs; if(model->nb_data >= 5000) { // Except if working set selection is used // then retain 25% of CPUs for gradient updates numthreads = nprocs - nprocs/4 + 1; if(numthreads > nprocs) numthreads=nprocs; } for(t=0;tthread_id; const int nprocs = data->nprocs; struct Model *model = data->model; struct KernelCache *kernelcache = data->kernelcache; long chunk_size = data->chunk_size; const double accuracy = data->accuracy; double **gradient = data->gradient; double **H_alpha = data->H_alpha; double *best_primal_upper_bound = data->best_primal_upper_bound; int *activeset = data->activeset; long *nb_SV = data->nb_SV; FILE *fp = data->logfile_ptr; pthread_mutex_unlock(&thread_data_mutex); // Release thread_data for next thread // Prepare the cache struct TrainingCache cache; cache.chunk_size = chunk_size; CS_alloc_memory(&cache, model->Q, model->nb_data, chunk_size); cache.kc = kernelcache; cache.activeset = activeset; // Disable parallel gradient computation and working set selection for small data sets int parallel_gradient_update = 1; int workingset_selection = 1; if(model->nb_data < 5000) { parallel_gradient_update = 0; workingset_selection = 0; } /* Prepare parallel gradient computations: - the gradient vector is split into numthreads_grad parts (along i) - each part is updated by a different thread */ // max number of threads for gradient updates is nprocs pthread_t *grad_threads = (pthread_t *)malloc(sizeof(pthread_t) * nprocs); // start with 1 thread (main load on kernel evaluations) int numthreads_grad = 1; if(workingset_selection) numthreads_grad = nprocs/4; // or #CPUS/4 threads if working set selection is used if(numthreads_grad==0) numthreads_grad = 1; // More CPUs for gradient updates if Q > dimension of data if(model->dim_input < model->Q) numthreads_grad = nprocs; void *status; int rc; long k; struct ThreadGradient_data *grad_data = (struct ThreadGradient_data *)malloc(sizeof(struct ThreadGradient_data) * nprocs); if(parallel_gradient_update) { for(k=0;knb_data / numthreads_grad; for(k=1;knb_data / numthreads_grad -1; } if(numthreads_grad>1) { grad_data[numthreads_grad-1].start_i = grad_data[numthreads_grad-2].end_i + 1; grad_data[numthreads_grad-1].end_i = model->nb_data; } } // Switch to #CPUs/4 threads for gradient update when 25% of the kernel matrix is cached int percentage_step = 1; long percentage = model->nb_data / 4; int next_numthreads_grad = nprocs/4; if(workingset_selection) { // Switch to #CPUs/2 threads for gradient update when 10% of the kernel matrix is cached percentage = model->nb_data / 10; next_numthreads_grad = nprocs/2; } if(next_numthreads_grad == 0) next_numthreads_grad = 1; // No thread switches if Q > dimension of data (keep all CPUs for gradient updates) if(model->dim_input < model->Q) percentage = 2*model->nb_data; // Local variables int verbose = 0; int do_eval; char yesno; long return_status = -1; double **delta = matrix(chunk_size, model->Q); double theta_opt; int jump = false; if(accuracy == 0) do_eval = 0; else do_eval = 1; double ratio = 0.0; // stopping criterion (dual / upper bound) int thread_stop = 0; double psi_max = HUGE_VAL; // Select a random chunk of data for the first step select_random_chunk(&cache,model); do { if((TRAIN_SMALL_STEP < TRAIN_STEP) && (iter%TRAIN_SMALL_STEP) == 0) { printf("."); fflush(stdout); } // Compute the kernel submatrix for the chunk compute_K(&cache,model); // Enter Critical Section (using and modifying the model) pthread_mutex_lock(&model_mutex); jump = CS_solve_lp(gradient, &cache, model); if(jump == false) jump = CS_check_opt_sol(gradient,&cache,model); if(jump == false) { CS_compute_delta(delta,&cache,model); theta_opt = CS_compute_theta_opt(delta, &cache, model); *nb_SV += CS_compute_new_alpha(theta_opt,&cache,model); if(parallel_gradient_update) { // Update gradient in parallel for(k=0;ktype); if(verbose && workingset_selection) printf("\t\t\t\t\t\t (psi = %e )\n",psi_max); if(do_eval && ratio > accuracy) STOP = 1; if(EVAL) // if interrupted by user (otherwise let the ratio decide if we go on training) { printf("\n *** Do you want to continue training ([y]/n)? "); yesno = getchar(); if(yesno=='n') { STOP = 1; } EVAL = 0; // reset interruption trigger } } // Release kernel submatrix in cache release_K(&cache); // Select working set (for next iteration) if(workingset_selection) psi_max = CS_workingset_selection(gradient,&cache,model); else (void)CS_compute_table_chunk(&cache,model); // Check if a sufficient % of the kernel matrix is cached if( parallel_gradient_update && cache.kc->max_idx >= percentage ) { /* and switch thread to compute gradient upates instead of kernel rows if it is (threads are actually stopped to leave the CPUs to other threads that will compute gradient updates) */ if(workingset_selection) thread_stop = CS_switch_thread(nprocs, &numthreads_grad, &next_numthreads_grad, &percentage, &percentage_step, grad_data, thread_id, model->nb_data); else thread_stop = switch_thread(nprocs, &numthreads_grad, &next_numthreads_grad, &percentage, &percentage_step, grad_data, thread_id, model->nb_data); } iter++; // Release mutex: End of critical section pthread_mutex_unlock(&model_mutex); } while(iter <= MSVM_TRAIN_MAXIT && (!do_eval || ratio < accuracy) && !STOP && !thread_stop); // Compute return_status if(do_eval && ratio >= accuracy) return_status = 0; // optimum reached. // Free memory CS_free_memory(&cache); free(delta[1]);free(delta); free(grad_threads); free(grad_data); pthread_exit((void*)return_status); } /* CS_init_alpha(model_ptr, alpha_filename) Initialize the alpha of the model pointed by model_ptr by reading them from the file alpha_filename or setting all alpha to 0 except one for each point */ void CS_init_alpha(struct Model *model, char *alpha_file) { long i,k; const long Q = model->Q; const long nb_data = model->nb_data; const double *C = model->C; // Initialize alpha if(alpha_file == NULL) { if (model->alpha != NULL) { free(model->alpha[1]); free(model->alpha); } model->alpha = matrix(nb_data, Q); model->sum_all_alpha = 0; for(i=1; i<=nb_data; i++) { for(k=1; k<=Q; k++) // Set all alpha_ik to 0 model->alpha[i][k] = 0.0; model->alpha[i][model->y[i]] = C[model->y[i]]; // except alpha_iy_i set to C_yi model->sum_all_alpha += C[model->y[i]]; } } else read_alpha(model, alpha_file); return; } /* Allocate the memory for the cache */ void CS_alloc_memory(struct TrainingCache *cache, const long Q, const long nb_data, const long chunk_size) { cache->table_chunk = (long *) calloc(chunk_size+1, sizeof(long)); cache->table_active = (long *) calloc(nb_data+1, sizeof(long)); cache->out_of_chunk = (long *) calloc(nb_data+1, sizeof(long)); cache->in_chunk = (long *) calloc(nb_data+1, sizeof(long)); cache->lp_sol = matrix(chunk_size, Q); cache->K = (double **)malloc(sizeof(double *) * (chunk_size+1)); cache->H_delta = matrix(chunk_size, Q); cache->alpha_update = matrix(chunk_size, Q); cache->psi = (double *)malloc(sizeof(double) * (nb_data + 1)); } /* Free the cache memory */ void CS_free_memory(struct TrainingCache *cache) { free(cache->table_chunk); free(cache->table_active); free(cache->in_chunk); free(cache->out_of_chunk); free(cache->K); free(cache->lp_sol[1]);free(cache->lp_sol); free(cache->H_delta[1]);free(cache->H_delta); free(cache->alpha_update[1]);free(cache->alpha_update); free(cache->psi); } /* Solve the LP subproblem by calling lp_solve API */ int CS_solve_lp(double **gradient, const struct TrainingCache *cache, const struct Model *model) { long i,k,ind_pattern; const long Q = model->Q; const long chunk_size = cache->chunk_size; const double *C = model->C; const int nRows = chunk_size; const int nCols = chunk_size * Q; double *obj = (double*)malloc(sizeof(double) * (1+nCols)); double *row = (double*)malloc(sizeof(double) * Q); int *cols = (int*)malloc(sizeof(int) * Q); long **lp_sol_table = matrix_l(nCols, 2); long **lp_sol_table_inv = matrix_l(chunk_size, Q); double *sol = (double*)malloc(sizeof(double) * (1+nRows+nCols)); double epsel; // Make LP lprec *lp = make_lp(0, nCols); set_add_rowmode(lp, TRUE); // Make objective function int col = 1; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; for(k=1; k<=Q; k++) { obj[col] = gradient[ind_pattern][k]; lp_sol_table[col][1] = i; // keep a table of correspondance between lp_sol_table[col][2] = k; // LPSOLVE vector of variables and lp_sol matrix lp_sol_table_inv[i][k] = col++; // lp_sol[i][k] = the 'lp_solve_table_inv[i][k]'-th variable for LPSOLVE } } set_obj_fn(lp, obj); // Make constraints : forall i, sum_k alpha_ik = C_yi for(i=1; i<=chunk_size; i++) { for(k=1; k<=Q; k++) { cols[k-1] = (int)lp_sol_table_inv[i][k]; row[k-1] = 1.0; } add_constraintex(lp, Q, row, cols, EQ, C[model->y[cache->table_chunk[i]]]); } // End of LP making set_add_rowmode(lp, FALSE); //print_lp(lp); // Solve LP int jump = false; set_outputfile(lp,""); if(solve(lp)) { printf("Problem with the LP... \n"); jump = true; } else { // Recover solution in the matrix lp_sol get_primal_solution(lp, sol); // sol: template for lp_solve solution format // sol=[obj, constraints, variables] epsel = get_epsel(lp); // tolerance in lp_solve // Put solution into lp_sol for(col=1; col<= nCols; col++) { // Check feasibility of the col-th variable if((sol[nRows+col] < -epsel) || (sol[nRows+col] > C[model->y[cache->table_chunk[lp_sol_table[col][1]]]] + epsel)) { jump = true; break; } // Round off tolerance if(fabs(sol[nRows+col]) < epsel) sol[nRows+col] = 0.0; else if(fabs(sol[nRows+col] - C[model->y[cache->table_chunk[lp_sol_table[col][1]]]]) < epsel) sol[nRows+col] = C[model->y[cache->table_chunk[lp_sol_table[col][1]]]]; // Set the value in lp_sol matrix cache->lp_sol[lp_sol_table[col][1]][lp_sol_table[col][2]] = sol[nRows+col]; } } delete_lp(lp); free(obj); free(row); free(cols); free(lp_sol_table[1]);free(lp_sol_table); free(lp_sol_table_inv[1]);free(lp_sol_table_inv); free(sol); return jump; } /* nb_SV = CS_compute_table_chunk(model) Select a subset of the training set for the next step of optimization */ long CS_compute_table_chunk(struct TrainingCache *cache, const struct Model *model) { long i,random_num,rank; const long nb_data = model->nb_data; const long chunk_size = cache->chunk_size; const long half_chunk_size = chunk_size / 2; long nb_points_chunk,nb_active_var_in_chunk,nb_active_var = 0; for(i=1; i<=nb_data; i++) { cache->in_chunk[i] = 0; if(cache->activeset[i]) cache->table_active[++nb_active_var] = i; } nb_points_chunk = 0; nb_active_var_in_chunk = nb_active_var; if(nb_active_var_in_chunk > half_chunk_size) nb_active_var_in_chunk = half_chunk_size; if(nb_active_var_in_chunk == nb_active_var) for(nb_points_chunk=1; nb_points_chunk <= nb_active_var; nb_points_chunk++) { cache->table_chunk[nb_points_chunk] = cache->table_active[nb_points_chunk]; cache->in_chunk[cache->table_active[nb_points_chunk]] = 1; } else while(nb_points_chunk < nb_active_var_in_chunk) { random_num = nrand48(xi); rank = (random_num % nb_active_var)+1; if(cache->in_chunk[cache->table_active[rank]] == 0) { cache->in_chunk[cache->table_active[rank]] = 1; nb_points_chunk++; cache->table_chunk[nb_points_chunk] = cache->table_active[rank]; } } nb_points_chunk = nb_active_var_in_chunk; while(nb_points_chunk < chunk_size) { random_num = nrand48(xi); rank = (random_num % nb_data)+1; if(cache->in_chunk[rank] == 0) { cache->in_chunk[rank] = 1; nb_points_chunk++; cache->table_chunk[nb_points_chunk] = rank; } } return nb_active_var; } void CS_init_gradient(const enum AlphaInitType alpha_init_type, double **gradient, double **H_alpha, const struct Model *model) { long i,j,k,l,y_i,y_j; const long nb_data = model->nb_data; const long Q = model->Q; const enum Kernel_type nature_kernel = model->nature_kernel; const double *kernel_par = model->kernel_par; const long dim_input = model->dim_input; double partial, gradient_ik; if(alpha_init_type == ALPHA_IS_ZERO) { // Fast initialization /* Matrix alpha is not really zero, but only alpha_i_y_i = C, which results in gradient_ik = 0 except for gradient_i_y_i = 1 */ for(i=1; i<=nb_data; i++) { for(k=1; k<=Q; k++) { gradient[i][k] = 0.0; H_alpha[i][k] = 0.0; } gradient[i][model->y[i]] = 1.0; } } else { // Do a proper initialization based on the values of alpha for(i=1; i<=nb_data; i++) { if(i%1000 == 0) { printf("."); fflush(stdout); } y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { gradient_ik = 0.0; for(j=1; j<=nb_data; j++) { y_j = model->y[j]; partial = 0.0; if(y_j == y_i) for(l=1; l<=Q; l++) partial += model->alpha[j][l]; if(y_j == k) for(l=1; l<=Q; l++) partial -= model->alpha[j][l]; partial += model->alpha[j][k] - model->alpha[j][y_i]; if(partial != 0.0) gradient_ik += partial * ker(nature_kernel, model->X[i], model->X[j], dim_input,kernel_par); } gradient[i][k] = gradient_ik; H_alpha[i][k] = gradient_ik; } else { gradient[i][k] = 1.0; H_alpha[i][k] = 0.0; } } } } } /* Thread for updates of the gradient in parallel (spawn by main computing thread CS_train_thread) */ void *CS_update_gradient_thread(void *th_data) { // Recover thread data struct ThreadGradient_data *data = (struct ThreadGradient_data *) th_data; double **gradient = data->gradient; double **H_alpha = data->H_alpha; struct TrainingCache *cache = data->cache; const struct Model *model = data->model; const long start_i = data->start_i; const long end_i = data->end_i; // Local variables long i,j,k,l,y_i,y_j,ind_pattern; const long Q = model->Q; const long chunk_size = cache->chunk_size; double partial, gradient_update_ik; for(i=start_i; i<=end_i; i++) { y_i = model->y[i]; for(k=1;k<=Q;k++) { if(k != y_i) { gradient_update_ik = 0.0; for(j=1; j<=chunk_size; j++) { ind_pattern = cache->table_chunk[j]; y_j = model->y[ind_pattern]; partial = 0.0; if(y_j == y_i) for(l=1; l<=Q; l++) partial += cache->alpha_update[j][l]; if(y_j == k) for(l=1; l<=Q; l++) partial -= cache->alpha_update[j][l]; partial += cache->alpha_update[j][k] - cache->alpha_update[j][y_i]; gradient_update_ik += partial * cache->K[j][i]; } gradient[i][k] += gradient_update_ik; H_alpha[i][k] += gradient_update_ik; } } } pthread_exit(EXIT_SUCCESS); } /* Old-style non-threaded gradient update */ void CS_update_gradient(double **gradient, double **H_alpha, struct TrainingCache *cache, const struct Model *model) { long i,j,k,l,y_i,y_j,ind_pattern; const long nb_data = model->nb_data; const long Q = model->Q; const long chunk_size = cache->chunk_size; double partial, gradient_update_ik; for(i=1; i<=nb_data; i++) { y_i = model->y[i]; for(k=1; k<=Q; k++) { if(k != y_i) { gradient_update_ik = 0.0; for(j=1; j<=chunk_size; j++) { ind_pattern = cache->table_chunk[j]; y_j = model->y[ind_pattern]; partial = 0.0; if(y_j == y_i) for(l=1; l<=Q; l++) partial += cache->alpha_update[j][l]; if(y_j == k) for(l=1; l<=Q; l++) partial -= cache->alpha_update[j][l]; partial += cache->alpha_update[j][k] - cache->alpha_update[j][y_i]; gradient_update_ik += partial * cache->K[j][i]; } gradient[i][k] += gradient_update_ik; H_alpha[i][k] += gradient_update_ik; } } } } /* Same as WW_compute_H_delta() */ void CS_compute_H_delta(double **delta, struct TrainingCache *cache, const struct Model *model) { long i,k,j,y_i,y_j,l; const long Q = model->Q; const long chunk_size = cache->chunk_size; double partial; for(i=1; i<=chunk_size; i++) { y_i = model->y[cache->table_chunk[i]]; for(k=1; k<=Q; k++) { cache->H_delta[i][k] = 0.0; if(k != y_i) { for(j=1; j<=chunk_size; j++) { y_j = model->y[cache->table_chunk[j]]; partial = 0.0; if(y_j == y_i) for(l=1; l<=Q; l++) partial += delta[j][l]; if(y_j == k) for(l=1; l<=Q; l++) partial -= delta[j][l]; partial += delta[j][k] - delta[j][y_i]; cache->H_delta[i][k] += partial * cache->K[i][cache->table_chunk[j]]; } } } } } int CS_check_opt_sol(double **gradient, struct TrainingCache *cache, const struct Model *model) { double gradient_alpha = 0.0; double gradient_Gamma = 0.0; double gradient_diff = 0.0; long i,k,ind_pattern; const long Q = model->Q; const long chunk_size = cache->chunk_size; int jump = false; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; for(k=1; k<=Q; k++) { gradient_alpha += gradient[ind_pattern][k] * model->alpha[ind_pattern][k]; gradient_Gamma += gradient[ind_pattern][k] * cache->lp_sol[i][k]; } } gradient_diff = gradient_alpha - gradient_Gamma; if(gradient_diff <= 0.0) { if(gradient_diff < -small) { printf("\nInappropriate subset selection...\n"); printf("\ngradient^T (alpha - gamma): %lf", gradient_diff); } jump = true; } cache->gradient_diff = gradient_diff; return jump; } /* Update model paramaters alpha_ik Return the difference in number of SVs */ long CS_compute_new_alpha(const double theta_opt, const struct TrainingCache *cache, struct Model *model) { long i,k,ind_pattern,y_i; const long Q = model->Q; const double *C = model->C; const long chunk_size = cache->chunk_size; double alpha_tmp; long nb_SV = 0; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; y_i = model->y[ind_pattern]; // Assume x_i is not a SV if(cache->activeset[ind_pattern]) { cache->activeset[ind_pattern] = 0; nb_SV--; } // Update alpha_ik for(k=1; k<=Q; k++) { cache->alpha_update[i][k] = theta_opt * ( cache->lp_sol[i][k] - model->alpha[ind_pattern][k] ); alpha_tmp = model->alpha[ind_pattern][k] + cache->alpha_update[i][k]; if(alpha_tmp > C[y_i] && alpha_tmp < C[y_i] * ( 1.0 + small_enough)) { cache->alpha_update[i][k] = C[y_i] - model->alpha[ind_pattern][k]; model->alpha[ind_pattern][k] = C[y_i]; } else { model->alpha[ind_pattern][k] = alpha_tmp; if(alpha_tmp > 0.0 && alpha_tmp < C[y_i]) { // Update nb_SV and activeset if(cache->activeset[ind_pattern] == 0) { cache->activeset[ind_pattern] = 1; nb_SV++; } } } } } return nb_SV; } void CS_compute_delta(double **delta, const struct TrainingCache *cache, const struct Model *model) { long i,k,ind_pattern; const long Q = model->Q; const long chunk_size = cache->chunk_size; for(i=1; i<=chunk_size; i++) { ind_pattern = cache->table_chunk[i]; for(k=1; k<=Q; k++) delta[i][k] = model->alpha[ind_pattern][k] - cache->lp_sol[i][k]; } } double CS_compute_theta_opt(double **delta, struct TrainingCache *cache, const struct Model *model) { long i,k, y_i; const long chunk_size = cache->chunk_size; const long Q = model->Q; double theta_opt, denominator = 0.0; CS_compute_H_delta(delta, cache,model); for(i=1; i<=chunk_size; i++) { y_i = model->y[cache->table_chunk[i]]; for(k=1; k<=Q; k++) if(k != y_i) denominator += delta[i][k] * cache->H_delta[i][k]; } if(denominator < 0) { printf("\nWrong estimate of theta: denominator= %e\n", denominator); exit(0); } else if (denominator == 0) theta_opt = 0.0; else theta_opt = cache->gradient_diff / denominator; if(theta_opt > 1.0) theta_opt = 1.0; return theta_opt; } /* Working set selection based on KKT condition select points with maximal violation of the KKT condition as measured by psi_i = max_{k, alpha_ik>0} gradient_ik - min_k gradient_ik returns max_i (psi_i) */ double CS_workingset_selection(double **Fmatrix, struct TrainingCache *cache, const struct Model *model) { //int isSV=0; long i,j; const long chunk_size = cache->chunk_size; long *next_chunk = cache->table_chunk; double *psi = cache->psi; const long Q = model->Q; const long nb_data = model->nb_data; long k,ind_pattern; double Fmax, Fmin,Fik, psi_max; for(j=1; j<=chunk_size; j++) next_chunk[j] = 0; for(i=1; i<=nb_data; i++) { Fmax = -HUGE_VAL; Fmin = HUGE_VAL; for(k=1; k<=Q; k++) { Fik = Fmatrix[i][k]; if(Fik > Fmax && (model->alpha[i][k] > 0.001)) Fmax = Fik; if(Fik < Fmin ) Fmin = Fik; } // Update psi_i psi[i] = Fmax - Fmin; // and the ordered list of maximal psi for(j=1; j<=chunk_size; j++) { ind_pattern = next_chunk[j]; if(ind_pattern == 0 || psi[i] > psi[ind_pattern]) { // Insert i here for(k=chunk_size;k>j;k--) next_chunk[k] = next_chunk[k-1]; next_chunk[j] = i; break; } } } psi_max = psi[next_chunk[1]]; /* for(j=1; j<=chunk_size; j++) { if(model->alpha[next_chunk[j]][model->y[next_chunk[j]]] < model->C) isSV++; } if(isSV < chunk_size) printf("isSV=%d\n",isSV); */ return psi_max; } /* This function overrides switch_thread() from libtrainMSVM.C with better thresholds when nonrandom working set selection is used. Switch working load between threads from main (kernel) computations to gradient updates As as result, the number of threads used for gradient updates increases while main computing threads (CS_train_thread) are terminated returns 1 if the calling main thread must stop */ int __inline__ CS_switch_thread(const int nprocs, int *numthreads_grad, int *next_numthreads_grad, long *percentage, int *percentage_step, struct ThreadGradient_data *grad_data, int thread_id, long nb_data) { int k; // Keep (nprocs - next_numthreads_grad + 1) main computing threads // for kernel evaluations if(thread_id < nprocs - *next_numthreads_grad + 1){ // This calling thread continues with more children to compute gradient updates *numthreads_grad = *next_numthreads_grad; // Update splits of the gradient vector grad_data[0].start_i = 1; grad_data[0].end_i = nb_data / *numthreads_grad; for(k=1;k<*numthreads_grad-1;k++) { grad_data[k].start_i = grad_data[k-1].end_i + 1; grad_data[k].end_i = grad_data[k].start_i + nb_data / *numthreads_grad -1; } if(*numthreads_grad>1) { grad_data[*numthreads_grad-1].start_i = grad_data[*numthreads_grad-2].end_i + 1; grad_data[*numthreads_grad-1].end_i = nb_data; } // Update percentage for next step switch(*percentage_step) { case 1: *percentage = nb_data / 5; // 20% of kernel matrix *next_numthreads_grad = 3*nprocs/4; // -> 75% of CPUs for gradient break; case 2: *percentage = nb_data / 3; // 33% *next_numthreads_grad = nprocs-1; // -> all CPUs - 1 break; case 3: *percentage = nb_data / 2; // 50% *next_numthreads_grad = nprocs; // -> all CPUs break; default: *percentage = 2*nb_data; // no more steps break; } if(*next_numthreads_grad == 0) *next_numthreads_grad = 1; *percentage_step += 1; return 0; } else { // The calling thread must stop (enough kernel rows have been computed) //printf("%ld rows of kernel matrix cached, stopping thread %d... \n",percentage,thread_id); return 1; } } MSVMpack1.2/src/libtrainMSVM.c0000644000175000017500000004464211761347400015201 0ustar lauerlauer/* Copyright 2008-2010 Yann Guermeur */ /* 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 2 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, write to the Free Software */ /* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA*/ /*--------------------------------------------------------------------------*/ /* Name : libtrainMSVM.c */ /* Version : 2.0 */ /* Creation : 06/20/08 */ /* Last update : 02/04/11 */ /* Subject : Training functions for MSVMpack */ /* Algo. : Wrapper functions only */ /* Author : Fabien Lauer and Yann Guermeur fabien.lauer@loria.fr */ /*--------------------------------------------------------------------------*/ #include "libtrainMSVM.h" #include "libtrainMSVM_WW.h" #include "libtrainMSVM_CS.h" #include "libtrainMSVM_LLW.h" #include "libtrainMSVM_2.h" #include "libtrainMSVM_2fw.h" /* status = MSVM_train(model, training_set, chunk_size, accuracy, cache_memory, nprocs, cache_size_in_mb, alpha0_file, model_tmp_file, log_file) use accuracy = 0 for infinite training use alpha0_file = NULL for default initialization of alpha use model_tmp_file = NULL to deactivate periodic saving of model use log_file = NULL to deactivate optimization log Return value: -1 : Error (infeasible initial alpha or unknown model type) 0 : Optimum found with desired accuracy level 1 : Stopped after maximum number of iterations N > 1 : Stopped by user after N iterations */ long MSVM_train(struct Model *model, struct Data *training_set, long chunk_size, const double accuracy, int cache_memory, int nprocs, char *alpha0_file, char *model_tmp_file, char *log_file) { long return_status; // Check number of threads if (nprocs <= 0 || nprocs > get_nprocessors()) nprocs = get_nprocessors(); printf("Using %d processor(s) for training.\n",nprocs); // Launch training for this model type switch (model->type) { case WW: return_status = MSVM_WW_train(model,training_set,chunk_size,accuracy, cache_memory, nprocs, alpha0_file,model_tmp_file,log_file); break; case CS: return_status = MSVM_CS_train(model,training_set,chunk_size,accuracy, cache_memory, nprocs, alpha0_file,model_tmp_file,log_file); break; case LLW: return_status = MSVM_LLW_train(model,training_set,chunk_size,accuracy, cache_memory, nprocs, alpha0_file,model_tmp_file,log_file); break; case MSVM2: if(model->algorithm == Rosen) { printf("Starting Rosen's algorithm to train an M-SVM^2...\n"); return_status = MSVM_2_train(model,training_set,chunk_size,accuracy, cache_memory, nprocs, alpha0_file,model_tmp_file,log_file); } else return_status = MSVM_2fw_train(model,training_set,chunk_size,accuracy, cache_memory, nprocs, alpha0_file,model_tmp_file,log_file); break; default: printf("MSVM_train: Unknown model type. \n"); return_status = -1; break; } return return_status; } /* Initializes the parameters and filenames used for training an M-SVM from a .com file. */ long MSVM_init_train_comfile(struct Model *model, char *com_file, char *training_file, char *alpha0_file, char *alpha_file, char *log_file) { long k,chunk_size; unsigned int kernel_type; FILE *fs; long nr = 0; if((fs=fopen(com_file, "r"))==NULL) { printf("\n.com file %s cannot be open.\n", com_file); exit(0); } nr += fscanf(fs, "%ld", &(model->Q)); nr += fscanf(fs, "%d", &kernel_type); model->nature_kernel = kernel_type; set_default_kernel_par(model); model->C = (double*)realloc(model->C, sizeof(double) * (model->Q + 1)); for(k=1;k<=model->Q;k++) nr += fscanf(fs, "%lf", &(model->C[k])); nr += fscanf(fs, "%ld", &chunk_size); nr += fscanf(fs, "%s", training_file); printf("\nThe file of the training data is: %s", training_file); nr += fscanf(fs, "%s", alpha0_file); nr += fscanf(fs, "%s", alpha_file); nr += fscanf(fs, "%s", log_file); fclose(fs); if(nr < 5) printf("\nError in reading com file %s, not enough data.\n", com_file); return chunk_size; } /* init_alpha_b(model_ptr, alpha_file) Initialize the alpha of the model pointed by model_ptr by reading them from the file alpha_file or setting all alpha to 0 if alpha_file is NULL Also (re)allocate memory for the vector b */ void init_alpha_b(struct Model *model, char *alpha_file) { long i,k; const long Q = model->Q; const long nb_data = model->nb_data; if(model->type == CS) { printf("Do not use init_alpha_b() with CS-type M-SVM:\n This M-SVM has no vector b and cannot initalize all alpha to 0.\n Use CS_init_alpha() instead.\n"); exit(0); } // Initialize alpha if(alpha_file == NULL) { if (model->alpha != NULL) { free(model->alpha[1]); free(model->alpha); } model->alpha = matrix(nb_data, Q); model->partial_average_alpha = (double *) realloc(model->partial_average_alpha, sizeof(double) * (nb_data+1)); for(i=1; i<=nb_data; i++) { model->partial_average_alpha[i] = 0.0; for(k=1; k<=Q; k++) model->alpha[i][k] = 0.0; } model->sum_all_alpha = 0.0; } else read_alpha(model, alpha_file); // Initialize b model->b_SVM = (double *)realloc(model->b_SVM, (Q+1) * sizeof(double)); return; } /* compute_K(cache,model) Compute the submatrix of the Kernel matrix corresponding to the chunk */ void compute_K(struct TrainingCache *cache, const struct Model *model) { long i; const long chunk_size = cache->chunk_size; for(i=1; i<=chunk_size; i++) { cache->K[i] = kernel_get_row(cache->table_chunk[i], cache->kc, model); } } /* Release the cache space reserved for the kernel submatrix corresponding to the chunk */ void release_K(struct TrainingCache *cache) { long i; const long chunk_size = cache->chunk_size; // Take mutex on in_use pthread_mutex_lock(&kernelcache_inuse_mutex); for (i=1;i<=chunk_size;i++) { cache->kc->in_use[cache->kc->rows_idx[cache->table_chunk[i]]]--; } // Release mutex on in_use pthread_mutex_unlock(&kernelcache_inuse_mutex); } void kernel_initialize_cache(unsigned long cache_size, struct KernelCache *kc, const struct Model *model) { long nb_data = model->nb_data; long i; unsigned long size_row = sizeof(double) * (nb_data + 1); // Size of a kernel row unsigned long size_max = (size_row + 1) * (nb_data + 1); // Maximal necessary cache size if(cache_size < size_row) cache_size = 0; // Allign cache_size with size_row if(cache_size % size_row > 0) cache_size -= cache_size % size_row; // Limit cache_size to what is necessary if(cache_size > size_max) cache_size = size_max; // Allocate maximal cache memory kc->K = NULL; while (kc->K == NULL && cache_size>0) { kc->K = (double *)malloc(cache_size); if(kc->K == NULL) cache_size -= size_row; } if(kc->K == NULL) { printf("no more memory, abording.\n"); exit(1); } // How many rows allocated? long nrows = (cache_size/size_row) - 1; // Pointers to rows kc->rows_ptr = (double **)malloc(sizeof(double *) * (nrows + 1)); for (i=0;i<=nrows;i++) { kc->rows_ptr[i] = NULL; // NULL means row not available; } // Which cache_index for these rows? kc->rows_idx = (long *)calloc(nb_data+1, sizeof(long)); kc->rows_idx_inv = (long *)calloc(nrows+1, sizeof(long)); // Which rows are in use (and by how many threads)? kc->in_use = (int *)calloc(nrows+1, sizeof(int)); if(kc->in_use == NULL) { printf("initializing kernel cache: not enough memory.\n"); exit(1); } else { printf("Allocated %lu MB of memory to cache %ld rows (%ld %%) of the kernel matrix.\n",cache_size/MBYTES + 1, nrows,100 * nrows/nb_data); } kc->nrows = nrows; kc->max_idx = 1; // first free row index kc->is_full = 0; // Initialize mutexes and condition variables kernelcache_rowptr_mutex = (pthread_mutex_t *)malloc(sizeof(pthread_mutex_t) * (nrows+1)); kernelcache_rowptr_cond = (pthread_cond_t *)malloc(sizeof(pthread_cond_t) * (nrows+1)); for(i=1;i<=nrows;i++) { pthread_mutex_init(&kernelcache_rowptr_mutex[i], NULL); pthread_cond_init (&kernelcache_rowptr_cond[i], NULL); } return ; } void kernel_free_cache(struct KernelCache *kc) { free(kc->K); free(kc->rows_ptr); free(kc->rows_idx); free(kc->rows_idx_inv); free(kc->in_use); long i; for(i=1;i<=kc->nrows;i++) { pthread_mutex_destroy(&kernelcache_rowptr_mutex[i]); pthread_cond_destroy (&kernelcache_rowptr_cond[i]); } free(kernelcache_rowptr_mutex); free(kernelcache_rowptr_cond); } /* Fetch a pointer to the row in cache corresponding to X_index */ double *kernel_get_row(long index, struct KernelCache *kc, const struct Model *model) { long i=0; // Make sure no other thread modifies the in_use table during this check pthread_mutex_lock(&kernelcache_inuse_mutex); // is the row already available? if(kc->rows_idx[index] != 0 && kc->rows_ptr[kc->rows_idx[index]] != NULL ) { // Yes, so mark it as "in use" kc->in_use[kc->rows_idx[index]]++; pthread_mutex_unlock(&kernelcache_inuse_mutex); // and return pointer to row data return kc->rows_ptr[kc->rows_idx[index]]; } else if (kc->rows_idx[index] != 0 && kc->rows_ptr[kc->rows_idx[index]] == NULL) { // The row is being computed by another thread, // so mark it as "in use" by one more thread (this one) kc->in_use[kc->rows_idx[index]]++; pthread_mutex_unlock(&kernelcache_inuse_mutex); // do not block other threads while waiting // and wait for it to be ready pthread_mutex_lock(&kernelcache_rowptr_mutex[kc->rows_idx[index]]); while(kc->rows_ptr[kc->rows_idx[index]] == NULL) { pthread_cond_wait(&kernelcache_rowptr_cond[kc->rows_idx[index]], &kernelcache_rowptr_mutex[kc->rows_idx[index]]); } pthread_mutex_unlock(&kernelcache_rowptr_mutex[kc->rows_idx[index]]); if(kc->rows_ptr[kc->rows_idx[index]] != NULL) { // return pointer to the computed row in cache return kc->rows_ptr[kc->rows_idx[index]]; } else { printf("Error in kernel_get_row: row not really available.\n"); printf("row_idx = %ld, index = %ld\n",kc->rows_idx[index], index); exit(1); } } // Row is not currently available, so compute kernel row if(kc->is_full) { // Cache already full, so search for the first row not currently in use i = 1; while(i<=kc->nrows && kc->in_use[i] > 0) { i++; } if(i > kc->nrows) { printf("Not enough memory for kernel caching. Reduce the number of CPUs or increase kernel cache memory.\n"); exit(0); } } else { // Append row at the end of cache i = kc->max_idx; kc->max_idx++; if(kc->max_idx > kc->nrows){ kc->is_full = 1; } } kc->in_use[i]++; // Mark row as in use kc->rows_ptr[i] = NULL; // but as not available (going to overwrite it) kc->rows_idx[index] = i; // and currently computing kc->rows_idx[kc->rows_idx_inv[i]] = 0; // mark previously cached row as unavailable // Release mutex on in_use pthread_mutex_unlock(&kernelcache_inuse_mutex); // Compute and cache the kernel row for X_index at location i in the kernel cache compute_kernel_row(index, i, kc, model); // do the computation pthread_mutex_lock(&kernelcache_rowptr_mutex[i]); // pthread_cond_broadcast(&kernelcache_rowptr_cond[i]); // signal that the row is ready pthread_mutex_unlock(&kernelcache_rowptr_mutex[i]); // and unlock other waiting threads // Return the row_ptr to the row just computed return kc->rows_ptr[i]; } void compute_kernel_row(const long index, const long cache_index, struct KernelCache *kc, const struct Model *model) { const long nb_data = model->nb_data; const long nature_kernel = model->nature_kernel; const long dim_input = model->dim_input; const double *kernel_par = model->kernel_par; double *row_ptr = &(kc->K[(cache_index-1)*(nb_data+1)]); // base address of row in cache memory long j; double *k = row_ptr + 1; // Compute row for(j=1; j<=nb_data; j++) { *k++ = ker(nature_kernel, model->X[index], model->X[j], dim_input, kernel_par); } if(model->type == MSVM2) { row_ptr[index] += 1. /(2 * model->C[model->y[index]]); } // Mark row as available kc->rows_idx_inv[cache_index] = index; kc->rows_ptr[cache_index] = row_ptr; } /* Switch working load between threads from main (kernel) computations to gradient updates As as result, the number of threads used for gradient updates increases while main computing threads (XX_train_thread) are terminated returns 1 if the calling main thread must stop */ int __inline__ switch_thread(const int nprocs, int *numthreads_grad, int *next_numthreads_grad, long *percentage, int *percentage_step, struct ThreadGradient_data *grad_data, int thread_id, long nb_data) { int k; // Keep (nprocs - next_numthreads_grad + 1) main computing threads // for kernel evaluations if(thread_id < nprocs - *next_numthreads_grad + 1){ // This calling thread continues with more children to compute gradient updates *numthreads_grad = *next_numthreads_grad; // Update splits of the gradient vector grad_data[0].start_i = 1; grad_data[0].end_i = nb_data / *numthreads_grad; for(k=1;k<*numthreads_grad-1;k++) { grad_data[k].start_i = grad_data[k-1].end_i + 1; grad_data[k].end_i = grad_data[k].start_i + nb_data / *numthreads_grad -1; } if(*numthreads_grad>1) { grad_data[*numthreads_grad-1].start_i = grad_data[*numthreads_grad-2].end_i + 1; grad_data[*numthreads_grad-1].end_i = nb_data; } // Update percentage for next step switch(*percentage_step) { case 1: *percentage = nb_data / 2; // 50% of kernel matrix *next_numthreads_grad = nprocs/2; // -> 50% of CPUs for gradient break; case 2: *percentage = 3 * nb_data / 4; // 75% *next_numthreads_grad = 3*nprocs/4; // -> 3/4 of CPUs break; case 3: *percentage = 19 * nb_data / 20; // 95% *next_numthreads_grad = nprocs-1; // -> all CPUs - 1 break; case 4: *percentage = nb_data; // 100% (entire kernel matrix in memory) *next_numthreads_grad = nprocs; // -> all CPUs for gradient updates break; default: *percentage = 2*nb_data; // no more steps break; } if(*next_numthreads_grad == 0) *next_numthreads_grad = 1; *percentage_step += 1; return 0; } else { // The calling thread must stop (enough kernel rows have been computed) //printf("%ld rows of kernel matrix cached, stopping thread %d... \n",percentage,thread_id); return 1; } } /* Randomly select a chunk of data (working set) At each training step, only the variables alpha_ik corresponding to this chunk are optimized. */ void select_random_chunk(struct TrainingCache *cache, const struct Model *model) { long i,j,random_num,row; const long nb_data = model->nb_data; const long chunk_size = cache->chunk_size; for(i=1; i<=nb_data; i++) { cache->out_of_chunk[i] = i; cache->in_chunk[i] = 0; } for(i=1; i<=chunk_size; i++) { random_num = nrand48(xi); row = (random_num % (nb_data-i+1))+1; cache->table_chunk[i] = cache->out_of_chunk[row]; for(j=row; j<=nb_data-i; j++) cache->out_of_chunk[j] = cache->out_of_chunk[j+1]; cache->in_chunk[cache->table_chunk[i]] = 1; } return; } /* Write a vector/matrix to a file (used for the vector alpha) */ void write_vector(double **vector, const long nb_data, const long Q, char *file) { long i,k; FILE *fc; int rc; char command[taille]; if((fc=fopen(file, "w"))==NULL) { printf("\nThe file %s cannot be open.\n", file); exit(0); } for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) fprintf(fc, "%15.10f %c", vector[i][k], (k==Q) ? '\n': ' '); fclose(fc); sprintf(command, "cp %s Save_alpha/.", file); rc = system(command); } /* Monitor the model while training: Save model in a temporary file on demand (do_save=1) and every 'period' seconds at most. */ void *MSVM_monitor_model_thread(void *monitor_data) { struct MonitorData * md = (struct MonitorData *)monitor_data; char *model_tmp_file = md->model_tmp_file; int period = md->period; struct Model * model = md->model; int nSV = 0; if ( model_tmp_file == NULL) { pthread_exit(EXIT_SUCCESS); } while(!STOP) { // Wait for period sleep (period) ; // Block training and updates of alpha // while writing model pthread_mutex_lock(&model_mutex); // Save model nSV = MSVM_save_model(model, model_tmp_file); //printf("Temporary model saved in %s\n",model_tmp_file); // Release training pthread_mutex_unlock(&model_mutex); } pthread_exit(EXIT_SUCCESS); } /* Print info during training */ void print_training_info(const long iter, const long nb_SV, const double ratio, const enum MSVM_type type) { char iter_str[20], nb_SV_str[20]; int i,num_spaces; if(iter == 0) { if(type == MSVM2) printf("\n Iteration\t Number of Support Vectors\t Ratio dual/primal\n"); else printf("\n Iteration\t Number of margin Sup. Vec.\t Ratio dual/primal\n"); printf("-------------------------------------------------------------------\n"); } sprintf(iter_str, "%ld",iter); num_spaces = (TRAIN_STEP/TRAIN_SMALL_STEP) - strlen(iter_str) - 1; for(i=0;i 0.0001) printf("\r %s %s %3.2lf %%\n",iter_str, nb_SV_str, 100*ratio); else if(ratio < 0.999999 && ratio > 0.000001) printf("\r %s %s %3.4lf %%\n",iter_str, nb_SV_str, 100*ratio); else printf("\r %s %s %3.8lf %%\n",iter_str, nb_SV_str, 100*ratio); } MSVMpack1.2/src/libMSVM.c~0000644000175000017500000014057311651447773014355 0ustar lauerlauer/* MSVMpack - libMSVM.c General purpose functions for handling M-SVM models */ #include "libMSVM.h" #include "kernel.h" /* model_ptr = MSVM_make_model(type) Create an empty MSVM model of a given type (MSVM2, WW, CS, LLW) and returns a pointer to it or NULL in case of failure. */ struct Model *MSVM_make_model(enum MSVM_type type) { struct Model *model = (struct Model *)malloc(sizeof(struct Model)); if(model == NULL) return NULL; switch(type) { case MSVM2 : case WW : case CS : case LLW : model->version = 1.1; model->type = type; model->algorithm = FrankWolfe; model->nature_kernel = LINEAR; model->kernel_par = NULL; model->datatype = DOUBLE; model->Q = 0; model->C = NULL; model->training_error = 0.0; model->alpha = NULL; model->partial_average_alpha = NULL; model->b_SVM = NULL; model->training_set_name = NULL; model->X = NULL; model->y = NULL; model->normalization = NULL; model->W = NULL; model->X_double = NULL; model->X_float = NULL; model->X_int = NULL; model->X_short = NULL; model->X_byte = NULL; break; default : printf("\n Sorry, this type of M-SVM (%d) is not included in MSVMpack.\n",type); return NULL; } // Return the pointer to the created model return model; } /* MSVM_init_model(model_ptr, fichcom_file) Sets the parameters Q, C and nature_kernel from a file and returns chunk_size */ long MSVM_init_model(struct Model *model, char *com_file) { long k,chunk_size; unsigned int kernel_type; // Read com_file for hyperparameters FILE *fs; long nr = 0; if((fs=fopen(com_file, "r"))==NULL) { printf("\nFile of parameters %s cannot be open.\n", com_file); exit(0); } nr += fscanf(fs, "%ld", &(model->Q)); nr += fscanf(fs, "%d", &kernel_type); model->nature_kernel = kernel_type; set_default_kernel_par(model); model->C = (double*)realloc(model->C, sizeof(double) * (model->Q + 1)); for(k=1;k<=model->Q;k++) nr += fscanf(fs, "%lf", &(model->C[k])); if (fscanf(fs, "%ld", &chunk_size) == EOF) chunk_size = 0; // eval-type com_file, no chunk size if(nr < 3) printf("\nError in reading com file, not enough data.\n"); return chunk_size; } void allocate_model_data(struct Model *model, const long nb_data, const long dim_input) { // Data type can be deduced from the kernel type: switch(model->nature_kernel / 10) { case 1: model->datatype = FLOAT; break; case 2: model->datatype = INT; break; case 3: model->datatype = SHORT; break; case 4: model->datatype = BYTE; break; case 5: model->datatype = BIT; break; case 0: default: model->datatype = DOUBLE; break; } // Allocate the corresponding storage: switch (model->datatype) { case FLOAT: model->X_float = matrix_f_aligned(nb_data,dim_input); model->X = (void **)model->X_float; break; case INT: model->X_int = matrix_i_aligned(nb_data,dim_input); model->X = (void **)model->X_int; break; case SHORT: model->X_short = matrix_s_aligned(nb_data,dim_input); model->X = (void **)model->X_short; break; case BYTE: model->X_byte = matrix_b_aligned(nb_data,dim_input); model->X = (void **)model->X_byte; break; case BIT: model->X_int = matrix_i_aligned(nb_data,dim_input/32 + (dim_input%32 != 0) ); model->X = (void **)model->X_int; break; case DOUBLE: model->X_double = matrix_aligned(nb_data,dim_input); model->X = (void **)model->X_double; break; default: printf("Unknown data format in allocate_model_data().\n"); exit(1); } } void free_model_data(struct Model *model) { if(model->X_double != NULL) free_mat_aligned(model->X_double); if(model->X_float != NULL) free_mat_f_aligned(model->X_float); if(model->X_int != NULL) free_mat_i_aligned(model->X_int); if(model->X_short != NULL) free_mat_s_aligned(model->X_short); if(model->X_byte != NULL) free_mat_b_aligned(model->X_byte); model->X = NULL; } /* MSVM_delete_model(model_ptr) Delete the model pointed by model_ptr */ void MSVM_delete_model(struct Model *model) { if (model == NULL) return; switch(model->type) { case MSVM2 : case WW : case CS : case LLW : if(model->C != NULL) { free(model->C); } if(model->alpha != NULL) { free(model->alpha[1]); free(model->alpha); } if(model->partial_average_alpha != NULL) { free(model->partial_average_alpha); } if(model->b_SVM != NULL) { free(model->b_SVM); } if(model->normalization != NULL){ free(model->normalization[1]); free(model->normalization); } if(model->W != NULL) { free(model->W[1]); free(model->W); } if(model->training_set_name != NULL) { free(model->training_set_name); } if(model->kernel_par != NULL) { free(model->kernel_par); } break; default : printf("\n Unknown MSVM type. Nothing to delete.\n"); break; } free(model); return; } /* MSVM_delete_model_with_data(model_ptr) Delete the model pointed by model_ptr and the data in model_ptr->(X, y) */ void MSVM_delete_model_with_data(struct Model *model) { if (model == NULL) return; switch(model->type) { case MSVM2 : case WW : case CS : case LLW : if(model->C != NULL) { free(model->C); } if(model->alpha != NULL) { free(model->alpha[1]); free(model->alpha); } if(model->partial_average_alpha != NULL) { free(model->partial_average_alpha); } if(model->b_SVM != NULL) { free(model->b_SVM); } if(model->normalization != NULL){ free(model->normalization[1]); free(model->normalization); } if(model->W != NULL) { free(model->W[1]); free(model->W); } if(model->training_set_name != NULL) { free(model->training_set_name); } if(model->kernel_par != NULL) { free(model->kernel_par); } break; default : printf("\n Unknown MSVM type. Nothing to delete.\n"); break; } // Free data memory free_model_data(model); if(model->y != NULL) { free(model->y); } free(model); return; } /* Save an MSVM model to a file (with all training data as SVs) Returns the number of SVs written to model_file (0 usually means failure) */ int MSVM_save_model(const struct Model *model, char *model_file) { long i,k, dim_bit; long nb_data = model->nb_data; long dim_input = model->dim_input; long Q = model->Q; long nSV = 0; FILE *fp; char training_set[255]; if((fp=fopen(model_file, "w"))==NULL) { printf("\n Model file %s cannot be open.\n", model_file); return 0; } // Write model information fprintf(fp, "%1.1f\n",model->version); remove_spaces(model->training_set_name, training_set,255); fprintf(fp, "%d\n", model->type); fprintf(fp, "%ld\n", Q); fprintf(fp, "%d\n", model->nature_kernel); if(model->kernel_par != NULL) { fprintf(fp, "%d ", (int) (model->kernel_par[0])); for(i=1;i<=(int) (model->kernel_par[0]); i++) fprintf(fp, "%lf ", model->kernel_par[i]); fprintf(fp,"\n"); } else fprintf(fp, "0\n"); fprintf(fp, "%s\n", training_set); fprintf(fp, "%lf\n", model->training_error); fprintf(fp, "%ld\n", nb_data); fprintf(fp, "%ld\n", dim_input); for(k=1;k<=Q;k++) fprintf(fp, "%1.10lf ", model->C[k]); fprintf(fp, "\n"); // Write data normalization information if(model->normalization != NULL) { for(k=1;k<=dim_input;k++) fprintf(fp, "%1.10lf ", model->normalization[2][k]); // std fprintf(fp, "\n"); for(k=1;k<=dim_input;k++) fprintf(fp, "%1.10lf ", model->normalization[1][k]); // mean fprintf(fp, "\n"); } else { // Do not use data normalization fprintf(fp, "-1\n"); } // Write vector b if(model->type != CS) { for(k=1; k<=Q; k++) fprintf(fp, "%1.10lf ", model->b_SVM[k]); fprintf(fp,"\n"); } // True dimension for BIT data dim_bit = dim_input/32; if(dim_input%32) dim_bit++; // Write support vectors and corresponding alpha for(i=1; i <= nb_data; i++) { // Write [alpha_i1 ... alpha_iQ] for(k = 1; k <= Q; k++) { if(model->alpha[i][k] == 0.0) fprintf(fp,"0.0 "); else if (model->alpha[i][k] < 1e-8) fprintf(fp,"%1.10e ", model->alpha[i][k]); else fprintf(fp,"%1.10lf ", model->alpha[i][k]); } fprintf(fp, "\n"); // Write x_i switch(model->datatype) { case DOUBLE: for(k=1;k<=dim_input;k++) fprintf(fp,"%1.10lf ", model->X_double[i][k]); break; case FLOAT: for(k=1;k<=dim_input;k++) fprintf(fp,"%1.8f ", model->X_float[i][k]); break; case INT: for(k=1;k<=dim_input;k++) fprintf(fp,"%d ", model->X_int[i][k]); break; case SHORT: for(k=1;k<=dim_input;k++) fprintf(fp,"%hd ", model->X_short[i][k]); break; case BYTE: for(k=1;k<=dim_input;k++) fprintf(fp,"%hhu ", model->X_byte[i][k]); break; case BIT: // Write compressed format for(k=1;k<=dim_bit;k++) fprintf(fp,"%d ", model->X_int[i][k]); break; default: printf("Error in MSVM_model_save(): unknown data format (%d).\n",model->datatype); exit(1); } // Write y_i fprintf(fp, "%ld\n", model->y[i]); nSV++; } fclose(fp); return nSV; } /* Save only the SVs of an MSVM model to a file Returns the number of SVs written to model_file (0 usually means failure) */ int MSVM_save_model_sparse(const struct Model *model, char *model_file) { long i,k,dim_bit; long nb_data = model->nb_data; long dim_input = model->dim_input; long Q = model->Q; long nSV = 0; int is_SV; int linear_model = false; FILE *fp; char training_set[255]; if((fp=fopen(model_file, "w"))==NULL) { printf("\n Model file %s: cannot be open.\n", model_file); return 0; } if(model->nature_kernel == LINEAR && model->type == WW) linear_model = true; // Find the number of SVs if(linear_model) nSV = Q; else { for(i=1; i <= nb_data; i++) { if(model->type == CS) { for(k = 1; k <= Q; k++) if(k != model->y[i] && model->alpha[i][k] != 0.0) { nSV++; break; } } else { for(k = 1; k <= Q; k++) if(model->alpha[i][k] != 0.0) { nSV++; break; } } } } // Write model information fprintf(fp, "%1.1f\n",model->version); remove_spaces(model->training_set_name, training_set,255); fprintf(fp, "%d\n", model->type); fprintf(fp, "%ld\n", Q); fprintf(fp, "%d\n", model->nature_kernel); if(model->kernel_par != NULL) { fprintf(fp, "%d ", (int) (model->kernel_par[0])); for(i=1;i<=(int) (model->kernel_par[0]); i++) fprintf(fp, "%lf ", model->kernel_par[i]); fprintf(fp,"\n"); } else fprintf(fp, "0\n"); fprintf(fp, "%s\n", training_set); fprintf(fp, "%lf\n", model->training_error); fprintf(fp, "%ld\n", nSV); fprintf(fp, "%ld\n", dim_input); for(k=1;k<=Q;k++) fprintf(fp, "%1.10lf ", model->C[k]); fprintf(fp, "\n"); // Write data normalization information if(model->normalization != NULL) { for(k=1;k<=dim_input;k++) fprintf(fp, "%1.10lf ", model->normalization[2][k]); // std fprintf(fp, "\n"); for(k=1;k<=dim_input;k++) fprintf(fp, "%1.10lf ", model->normalization[1][k]); // mean fprintf(fp, "\n"); } else { // Do not use data normalization fprintf(fp, "-1\n"); } // Write vector b if(model->type != CS) { for(k=1; k<=Q; k++) fprintf(fp, "%1.10lf ", model->b_SVM[k]); fprintf(fp,"\n"); } // True dimension for BIT data dim_bit = dim_input/32; if(dim_input%32) dim_bit++; // Write support vectors and corresponding alpha if(linear_model) { nSV = 0; WW_compute_W(model); for(i=1; i<=Q; i++) { for(k = 1; k <= Q; k++) { if(i==k) fprintf(fp,"1.0 "); else fprintf(fp,"0.0 "); } for(k=1;k<=dim_input;k++) { fprintf(fp,"%1.10lf ", model->W[k][i]); } fprintf(fp,"%ld ", i); nSV++; } } else{ nSV = 0; for(i=1; i <= nb_data; i++) { is_SV = 0; if(model->type == CS) { for(k = 1; k <= Q; k++) if(k != model->y[i] && model->alpha[i][k] != 0.0) { is_SV = 1; break; } } else { for(k = 1; k <= Q; k++) if(model->alpha[i][k] != 0.0) { is_SV = 1; break; } } if(is_SV) { // Write [alpha_i1 ... alpha_iQ] for(k = 1; k <= Q; k++) { if(model->alpha[i][k] == 0.0) fprintf(fp,"0.0 "); else if (model->alpha[i][k] < 1e-8) fprintf(fp,"%1.10e ", model->alpha[i][k]); else fprintf(fp,"%1.10lf ", model->alpha[i][k]); } fprintf(fp, "\n"); // Write x_i switch(model->datatype) { case FLOAT: for(k=1;k<=dim_input;k++) fprintf(fp,"%1.8f ", model->X_float[i][k]); break; case INT: for(k=1;k<=dim_input;k++) fprintf(fp,"%d ", model->X_int[i][k]); break; case SHORT: for(k=1;k<=dim_input;k++) fprintf(fp,"%hd ", model->X_short[i][k]); break; case BYTE: for(k=1;k<=dim_input;k++) fprintf(fp,"%hhu ", model->X_byte[i][k]); break; case BIT: // Write compressed format for(k=1;k<=dim_bit;k++) fprintf(fp,"%d ", model->X_int[i][k]); break; case DOUBLE: default: for(k=1;k<=dim_input;k++) fprintf(fp,"%1.10lf ", model->X_double[i][k]); break; } // Write y_i fprintf(fp, "%ld\n", model->y[i]); nSV++; } } } fclose(fp); return nSV; } /* Load an MSVM model from a file */ struct Model *MSVM_load_model(char *model_file) { long i,k, nb_data, Q, dim_input, dim_bit; double alpha,normalization; FILE *fp; long nr=0; float version; unsigned int type, kernel_type; char buffer[200]; int n_kernel_par; if((fp=fopen(model_file, "r"))==NULL) { printf("\n Model file %s cannot be open.\n", model_file); return NULL; } struct Model *model = (struct Model *)malloc(sizeof(struct Model)); if(model == NULL) return NULL; nr += fscanf(fp, "%s", buffer); if(strlen(buffer) < 3 ){ version = 1.0; // no version number = version 1.0 type = atoi(buffer); } else { version = atof(buffer); nr += fscanf(fp, "%d", &type); } model->version = version; model->type = type; model->algorithm = FrankWolfe; // default back to Frank-Wolfe method // use -o 1 to retrain with Rosen's method nr += fscanf(fp, "%ld", &Q); model->Q = Q; nr += fscanf(fp, "%d", &kernel_type); model->nature_kernel = kernel_type; nr += fscanf(fp, "%d", &n_kernel_par); model->kernel_par = (double *)malloc(sizeof(double) * (n_kernel_par + 1)); model->kernel_par[0] = (double)n_kernel_par; for(i=1;i<=n_kernel_par;i++) nr += fscanf(fp, "%lf", &(model->kernel_par[i])); nr += fscanf(fp,"%s", buffer); model->training_set_name = (char*)malloc(sizeof(char) * (strlen(buffer) + 1)); strcpy(model->training_set_name, buffer); nr += fscanf(fp, "%lf", &(model->training_error)); nr += fscanf(fp, "%ld", &nb_data); model->nb_data = nb_data; nr += fscanf(fp, "%ld", &dim_input); model->dim_input = dim_input; dim_bit = dim_input/32; // true dimension for BIT data if(dim_input%32) dim_bit++; // C hyperparameters model->C = (double*) malloc(sizeof(double) * (Q+1)); if (version > 1.0) { for(k=1;k<=Q;k++) nr += fscanf(fp, "%lf", &(model->C[k])); } else { nr += fscanf(fp, "%lf", &(model->C[1])); for(k=2;k<=Q;k++) model->C[k] = model->C[1]; } nr += fscanf(fp, "%lf", &normalization); if(nr < 10){ printf("Error, cannot read model file %s.\n",model_file); exit(0); } if(normalization >= 0.0) { model->normalization = matrix(2,dim_input); model->normalization[2][1] = normalization; for(k=2;k<=dim_input;k++) nr = fscanf(fp, "%lf", &(model->normalization[2][k])); for(k=1;k<=dim_input;k++) nr = fscanf(fp, "%lf", &(model->normalization[1][k])); } else model->normalization = NULL; nr = 0; // Model file format could change with MSVM type // The following loads the model accordingly switch(type) { case MSVM2 : // Allocate memory for model parameters model->alpha = matrix(nb_data,Q); model->partial_average_alpha = (double *) malloc(sizeof(double) * (nb_data+1)); model->b_SVM = (double *)malloc((Q+1) * sizeof(double)); // Allocate model->X and set model->datatype allocate_model_data(model, nb_data, dim_input); model->y = (long*)malloc(sizeof(long) * (nb_data+1)); // Read b for(k=1; k<=Q; k++) nr += fscanf(fp, "%lf", &(model->b_SVM[k])); for(i=1; i <= nb_data; i++) { model->partial_average_alpha[i] = 0.0; // Read [alpha_i1 ... alpha_iQ] for(k = 1; k <= Q; k++) { nr += fscanf(fp, "%lf", &alpha); model->alpha[i][k] = alpha; model->sum_all_alpha += alpha; model->partial_average_alpha[i] += alpha; } model->partial_average_alpha[i] /= Q; // Read x_i switch (model->datatype) { case DOUBLE: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%lf", &(model->X_double[i][k])); break; case FLOAT: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%f", &(model->X_float[i][k])); break; case INT: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%d", &(model->X_int[i][k])); break; case SHORT: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%hd", &(model->X_short[i][k])); break; case BYTE: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%hhu", &(model->X_byte[i][k])); break; case BIT: // Load compressed format for(k=1;k<=dim_bit;k++) nr += fscanf(fp, "%d", &(model->X_int[i][k])); break; default: printf("Error: unknown data format (%d) in MSVM_load_model().\n",model->datatype); exit(1); } // Read y_i nr += fscanf(fp, "%ld", &(model->y[i])); } if((model->datatype != BIT && nr < Q+(Q+dim_input+1)*nb_data) || (model->datatype == BIT && nr < Q+(Q+dim_bit+1)*nb_data)) printf("\nError in reading model file, not enough data.\n"); break; case WW : // Allocate memory for model parameters model->alpha = matrix(nb_data,Q); model->b_SVM = (double *)malloc((Q+1) * sizeof(double)); // Allocate model->X and set model->datatype allocate_model_data(model, nb_data, dim_input); model->y = (long*)malloc(sizeof(long) * (nb_data+1)); // Read b for(k=1; k<=Q; k++) nr += fscanf(fp, "%lf", &(model->b_SVM[k])); for(i=1; i <= nb_data; i++) { // Read [alpha_i1 ... alpha_iQ] for(k = 1; k <= Q; k++) { nr += fscanf(fp, "%lf", &alpha); model->alpha[i][k] = alpha; model->sum_all_alpha += alpha; } // Read x_i switch (model->datatype) { case DOUBLE: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%lf", &(model->X_double[i][k])); break; case FLOAT: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%f", &(model->X_float[i][k])); break; case INT: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%d", &(model->X_int[i][k])); break; case SHORT: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%hd", &(model->X_short[i][k])); break; case BYTE: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%hhu", &(model->X_byte[i][k])); break; case BIT: // Load compressed format for(k=1;k<=dim_bit;k++) nr += fscanf(fp, "%d", &(model->X_int[i][k])); break; default: printf("Error: unknown data format (%d) in MSVM_load_model().\n",model->datatype); exit(1); } // Read y_i nr += fscanf(fp, "%ld", &(model->y[i])); } if((model->datatype != BIT && nr < Q+(Q+dim_input+1)*nb_data) || (model->datatype == BIT && nr < Q+(Q+dim_bit+1)*nb_data)) printf("\nError in reading model file, not enough data.\n"); break; case CS : // Allocate memory for model parameters model->alpha = matrix(nb_data,Q); // Allocate model->X and set model->datatype allocate_model_data(model, nb_data, dim_input); model->y = (long*)malloc(sizeof(long) * (nb_data+1)); for(i=1; i <= nb_data; i++) { // Read [alpha_i1 ... alpha_iQ] for(k = 1; k <= Q; k++) { nr += fscanf(fp, "%lf", &alpha); model->alpha[i][k] = alpha; model->sum_all_alpha += alpha; } // Read x_i switch (model->datatype) { case DOUBLE: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%lf", &(model->X_double[i][k])); break; case FLOAT: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%f", &(model->X_float[i][k])); break; case INT: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%d", &(model->X_int[i][k])); break; case SHORT: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%hd", &(model->X_short[i][k])); break; case BYTE: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%hhu", &(model->X_byte[i][k])); break; case BIT: // Load compressed format for(k=1;k<=dim_bit;k++) nr += fscanf(fp, "%d", &(model->X_int[i][k])); break; default: printf("Error: unknown data format (%d) in MSVM_load_model().\n",model->datatype); exit(1); } // Read y_i nr += fscanf(fp, "%ld", &(model->y[i])); } if((model->datatype != BIT && nr < (Q+dim_input+1)*nb_data) || (model->datatype == BIT && nr < (Q+dim_bit+1)*nb_data)) printf("\nError in reading model file, not enough data.\n"); break; case LLW : // Allocate memory for model parameters model->alpha = matrix(nb_data,Q); model->b_SVM = (double *)malloc((Q+1) * sizeof(double)); // Allocate model->X and set model->datatype allocate_model_data(model, nb_data, dim_input); model->y = (long*)malloc(sizeof(long) * (nb_data+1)); // Read b for(k=1; k<=Q; k++) nr += fscanf(fp, "%lf", &(model->b_SVM[k])); for(i=1; i <= nb_data; i++) { // Read [alpha_i1 ... alpha_iQ] for(k = 1; k <= Q; k++) { nr += fscanf(fp, "%lf", &alpha); model->alpha[i][k] = alpha; model->sum_all_alpha += alpha; } // Read x_i switch (model->datatype) { case DOUBLE: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%lf", &(model->X_double[i][k])); break; case FLOAT: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%f", &(model->X_float[i][k])); break; case INT: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%d", &(model->X_int[i][k])); break; case SHORT: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%hd", &(model->X_short[i][k])); break; case BYTE: for(k=1;k<=dim_input;k++) nr += fscanf(fp, "%hhu", &(model->X_byte[i][k])); break; case BIT: // Load compressed format for(k=1;k<=dim_bit;k++) nr += fscanf(fp, "%d", &(model->X_int[i][k])); break; default: printf("Error: unknown data format (%d) in MSVM_load_model().\n",model->datatype); exit(1); } // Read y_i nr += fscanf(fp, "%ld", &(model->y[i])); } if((model->datatype != BIT && nr < Q+(Q+dim_input+1)*nb_data) || (model->datatype == BIT && nr < Q+(Q+dim_bit+1)*nb_data)) printf("\nError in reading model file, not enough data.\n"); break; default : printf("Unknown MSVM model type in file %s . \n", model_file); return NULL; break; } fclose(fp); return model; } /* Load a dataset into a model */ void model_load_data(struct Model *model, const struct Data *training_set) { long k; if(training_set->name != NULL) { model->training_set_name = (char *)malloc(sizeof(char) * (strlen(training_set->name) + 1)); strcpy(model->training_set_name, training_set->name); } model->nb_data = training_set->nb_data; model->dim_input = training_set->dim; model->y = training_set->y; model->Q = training_set->Q; if(model->C == NULL) { model->C = (double*)malloc(sizeof(double) * (model->Q + 1)); for (k=1;k<=model->Q;k++) model->C[k] = DEFAULT_C; } model->datatype = training_set->datatype; switch(model->datatype) { case DOUBLE: model->X_double = training_set->X_double; break; case FLOAT: model->X_float = training_set->X_float; break; case INT: model->X_int = training_set->X_int; break; case SHORT: model->X_short = training_set->X_short; break; case BYTE: model->X_byte = training_set->X_byte; break; case BIT: model->X_int = training_set->X_int; break; default: printf("Error: Unknown training set data format (%d).\n",model->datatype); exit(1); break; } model->X = training_set->X; } /* dataset_ptr = MSVM_make_dataset(data_file) Create an empty dataset and load data from data_file if data_file is not NULL */ struct Data *MSVM_make_dataset(char *data_file, enum Datatype datatype) { struct Data *dataset = (struct Data *)malloc(sizeof(struct Data)); if(dataset != NULL) { dataset->name = NULL; dataset->X = NULL; dataset->y = NULL; dataset->dim = 0; dataset->nb_data = 0; dataset->Q = 0; dataset->X_double = NULL; dataset->X_float = NULL; dataset->X_int = NULL; dataset->X_short = NULL; dataset->X_byte = NULL; } if(data_file != NULL) { dataset->name = (char *)malloc(sizeof(char) * (strlen(data_file)+1)); strcpy(dataset->name, data_file); dataset->Q = read_data(dataset, datatype, data_file); } // Return the pointer to the created dataset return dataset; } void free_dataset_data(struct Data *dataset) { if(dataset->X_double != NULL) free_mat_aligned(dataset->X_double); if(dataset->X_float != NULL) free_mat_f_aligned(dataset->X_float); if(dataset->X_int != NULL) free_mat_i_aligned(dataset->X_int); if(dataset->X_short != NULL) free_mat_s_aligned(dataset->X_short); if(dataset->X_byte != NULL) free_mat_b_aligned(dataset->X_byte); dataset->X = NULL; } /* MSVM_delete_dataset(dataset_ptr) Delete a dataset */ void MSVM_delete_dataset(struct Data *dataset) { if(dataset == NULL) return; if(dataset->name != NULL) { free(dataset->name); } if(dataset->y != NULL) { free(dataset->y); } free_dataset_data(dataset); free(dataset); return; } /* Normalize a dataset by setting the mean and std of all columns of X to 0 and 1 or according to an already defined model->normalization and returns the difference between the largest and smallest std. On output, model->normalization[1][j] contains the mean of the jth column and model->normalization[2][j] contains the std of the jth column. If model is NULL the data are left unnormalized (this can be used to check if normalization is needed). */ double MSVM_normalize_data(struct Data *dataset, struct Model *model) { if(dataset == NULL) return 0; const long nb_data = dataset->nb_data; const long dim = dataset->dim; double **X = dataset->X_double; float **Xf = dataset->X_float; long i,j; double mean,std, large_std=0, small_std=0; int compute_mean_std = 1; switch(dataset->datatype) { case FLOAT: if(model != NULL) { if(model->normalization == NULL) model->normalization = matrix(2,dim); else compute_mean_std = 0; } if(compute_mean_std) { // Compute mean and std before normalizing for(j=1;j<=dim;j++) { mean = 0.; std = 0.; for(i=1;i<=nb_data; i++) { mean += (double)Xf[i][j]; std += (double)Xf[i][j]*Xf[i][j]; } mean /= (double)nb_data; std = sqrt( (std/(double)nb_data) - mean*mean); if(j==1 || std > large_std) large_std = std; if(j==1 || std < small_std) small_std = std; if(std == 0.0) printf("Warning: std of feature #%ld = 0\n",j); if (model != NULL && std > 0.0) { // Do normalize for(i=1;i<=nb_data; i++) { Xf[i][j] = (Xf[i][j] - (float)mean) / (float)std; } model->normalization[1][j] = mean; model->normalization[2][j] = std; } } } else { // Use given normalization coefficients for(i=1;i<=nb_data; i++) { for(j=1;j<=dim;j++) if(model->normalization[2][j] != 0.0) Xf[i][j] = (Xf[i][j] - (float)model->normalization[1][j]) / (float)model->normalization[2][j]; } } break; case INT: return 0; break; case SHORT: return 0; break; case BYTE: return 0; break; case BIT: return 0; break; case DOUBLE: default: if(model != NULL) { if(model->normalization == NULL) model->normalization = matrix(2,dim); else compute_mean_std = 0; } if(compute_mean_std) { // Compute mean and std before normalizing for(j=1;j<=dim;j++) { mean = 0.; std = 0.; for(i=1;i<=nb_data; i++) { mean += X[i][j]; std += X[i][j]*X[i][j]; } mean /= (double)nb_data; std = sqrt( (std/(double)nb_data) - mean*mean); if(j==1 || std > large_std) large_std = std; if(j==1 || std < small_std) small_std = std; if(std == 0.0) printf("Warning: std of feature #%ld = 0\n",j); if (model != NULL && std > 0.0) { // Do normalize for(i=1;i<=nb_data; i++) { X[i][j] = (X[i][j] - mean) / std; } model->normalization[1][j] = mean; model->normalization[2][j] = std; } } } else { // Use given normalization coefficients for(i=1;i<=nb_data; i++) { for(j=1;j<=dim;j++) if(model->normalization[2][j] != 0.0) { X[i][j] = (X[i][j] - model->normalization[1][j]) / model->normalization[2][j]; } } } break; } return (large_std - small_std); } /* Load a dataset from a file Returns the number of classes computed as max(y_i) */ long read_data(struct Data *dataset, enum Datatype datatype, char *data_file) { FILE *fs; long i,j,nb_data,dim_input; double value_y,value_X; float value_yf,value_Xf; int value_yi,value_Xi; short int value_Xs; unsigned char value_Xb; long Q=0; long min_y = 1000; char buf[taille]; long nr = 0; long dim; if((fs=fopen(data_file, "r"))==NULL) { printf("\nFile of data %s cannot be open.\n", data_file); exit(0); } nr += fscanf(fs, "%ld", &nb_data); nr += fscanf(fs, "%ld", &dim_input); switch(datatype) { case FLOAT: // (Re)allocate memory free_dataset_data(dataset); dataset->X_float = matrix_f_aligned(nb_data, dim_input); // Read first line with data for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%f", &value_Xf); dataset->X_float[1][j] = value_Xf; } // Check if there is a label at the end of the line if(fgets(buf, taille, fs) == NULL) { printf("Error while reading data file.\n"); exit(1); } if(sscanf(buf, "%f", &value_yf) > 0) { dataset->y = (long *) realloc(dataset->y, (nb_data+1) * sizeof(long)); dataset->y[1] = (long) value_yf; } else if (dataset->y != NULL) { free(dataset->y); dataset->y = NULL; } // Read the rest of the file for(i=2; i<=nb_data; i++) { for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%f", &value_Xf); dataset->X_float[i][j] = value_Xf; } if(dataset->y != NULL) { nr += fscanf(fs, "%f", &value_yf); dataset->y[i] = (long) value_yf; if(dataset->y[i] > Q) Q = dataset->y[i]; if(dataset->y[i] < min_y) min_y = dataset->y[i]; } } // Set X to point to the FLOAT storage dataset->X = (void**)dataset->X_float; break; case INT: // (Re)allocate memory free_dataset_data(dataset); dataset->X_int = matrix_i(nb_data, dim_input); // Read first line with data for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%d", &value_Xi); dataset->X_int[1][j] = value_Xi; } // Check if there is a label at the end of the line if(fgets(buf, taille, fs) == NULL) { printf("Error while reading data file.\n"); exit(1); } if(sscanf(buf, "%d", &value_yi) > 0) { dataset->y = (long *) realloc(dataset->y, (nb_data+1) * sizeof(long)); dataset->y[1] = (long) value_yi; } else if (dataset->y != NULL) { free(dataset->y); dataset->y = NULL; } // Read the rest of the file for(i=2; i<=nb_data; i++) { for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%d", &value_Xi); dataset->X_int[i][j] = value_Xi; } if(dataset->y != NULL) { nr += fscanf(fs, "%d", &value_yi); dataset->y[i] = (long) value_yi; if(dataset->y[i] > Q) Q = dataset->y[i]; if(dataset->y[i] < min_y) min_y = dataset->y[i]; } } // Set X to point to the INT storage dataset->X = (void**)dataset->X_int; break; case SHORT: // (Re)allocate memory free_dataset_data(dataset); dataset->X_short = matrix_s_aligned(nb_data, dim_input); // Read first line with data for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%hd", &value_Xs); dataset->X_short[1][j] = value_Xs; } // Check if there is a label at the end of the line if(fgets(buf, taille, fs) == NULL) { printf("Error while reading data file.\n"); exit(1); } if(sscanf(buf, "%d", &value_yi) > 0) { dataset->y = (long *) realloc(dataset->y, (nb_data+1) * sizeof(long)); dataset->y[1] = (long) value_yi; } else if (dataset->y != NULL) { free(dataset->y); dataset->y = NULL; } // Read the rest of the file for(i=2; i<=nb_data; i++) { for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%hd", &value_Xs); dataset->X_short[i][j] = value_Xs; } if(dataset->y != NULL) { nr += fscanf(fs, "%d", &value_yi); dataset->y[i] = (long) value_yi; if(dataset->y[i] > Q) Q = dataset->y[i]; if(dataset->y[i] < min_y) min_y = dataset->y[i]; } } // Set X to point to the INT storage dataset->X = (void**)dataset->X_short; break; case BYTE: // (Re)allocate memory free_dataset_data(dataset); dataset->X_byte = matrix_b_aligned(nb_data, dim_input); // Read first line with data for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%hhu", &value_Xb); dataset->X_byte[1][j] = value_Xb; } // Check if there is a label at the end of the line if(fgets(buf, taille, fs) == NULL) { printf("Error while reading data file.\n"); exit(1); } if(sscanf(buf, "%d", &value_yi) > 0) { dataset->y = (long *) realloc(dataset->y, (nb_data+1) * sizeof(long)); dataset->y[1] = (long) value_yi; } else if (dataset->y != NULL) { free(dataset->y); dataset->y = NULL; } // Read the rest of the file for(i=2; i<=nb_data; i++) { for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%hhu", &value_Xb); dataset->X_byte[i][j] = value_Xb; } if(dataset->y != NULL) { nr += fscanf(fs, "%d", &value_yi); dataset->y[i] = (long) value_yi; if(dataset->y[i] > Q) Q = dataset->y[i]; if(dataset->y[i] < min_y) min_y = dataset->y[i]; } } // Set X to point to the INT storage dataset->X = (void**)dataset->X_byte; break; case BIT: /* BIT data are loaded in INT storage (32 bits per int, completed with zeros) */ // How many INT needed to store the BITS ? dim = dim_input/32; if (dim_input%32 != 0) dim++; long j_int=0; unsigned int mask; // (Re)allocate memory free_dataset_data(dataset); dataset->X_int = matrix_i_aligned(nb_data, dim); // Read first line with data for(j=1; j<=dim_input; j++) { if(j%32 == 1) { j_int++; dataset->X_int[1][j_int] = 0; } nr += fscanf(fs, "%d", &value_Xi); if(value_Xi) { mask = 0x1; mask <<= (j%32) - 1; dataset->X_int[1][j_int] |= mask; } } // Fill in rest of row with zeros for (j=0; j< 4 - j_int;j++ ) { dataset->X_int[1][j_int] = 0; } // Check if there is a label at the end of the line if(fgets(buf, taille, fs) == NULL) { printf("Error while reading data file.\n"); exit(1); } if(sscanf(buf, "%d", &value_yi) > 0) { dataset->y = (long *) realloc(dataset->y, (nb_data+1) * sizeof(long)); dataset->y[1] = (long) value_yi; } else if (dataset->y != NULL) { free(dataset->y); dataset->y = NULL; } // Read the rest of the file for(i=2; i<=nb_data; i++) { j_int = 0; for(j=1; j<=dim_input; j++) { if(j%32 == 1) { j_int++; dataset->X_int[i][j_int] = 0; } nr += fscanf(fs, "%d", &value_Xi); if(value_Xi) { mask = 0x1; mask <<= (j%32) - 1; dataset->X_int[i][j_int] |= mask; } } // Fill in rest of row with zeros for (j=0; j< 4 - j_int;j++ ) { dataset->X_int[1][j_int] = 0; } if(dataset->y != NULL) { nr += fscanf(fs, "%d", &value_yi); dataset->y[i] = (long) value_yi; if(dataset->y[i] > Q) Q = dataset->y[i]; if(dataset->y[i] < min_y) min_y = dataset->y[i]; } } // Set X to point to the INT storage dataset->X = (void**)dataset->X_int; break; case DOUBLE: default: // (Re)allocate memory free_dataset_data(dataset); dataset->X_double = matrix_aligned(nb_data, dim_input); // Read first line with data for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%lf", &value_X); dataset->X_double[1][j] = value_X; } // Check if there is a label at the end of the line if(fgets(buf, taille, fs) == NULL) { printf("Error while reading data file.\n"); exit(1); } if(sscanf(buf, "%lf", &value_y) > 0) { dataset->y = (long *) realloc(dataset->y, (nb_data+1) * sizeof(long)); dataset->y[1] = (long) value_y; } else if (dataset->y != NULL) { free(dataset->y); dataset->y = NULL; } // Read the rest of the file for(i=2; i<=nb_data; i++) { for(j=1; j<=dim_input; j++) { nr += fscanf(fs, "%lf", &value_X); dataset->X_double[i][j] = value_X; } if(dataset->y != NULL) { nr += fscanf(fs, "%lf", &value_y); dataset->y[i] = (long) value_y; if(dataset->y[i] > Q) Q = dataset->y[i]; if(dataset->y[i] < min_y) min_y = dataset->y[i]; } } // Set X to point to the DOUBLE storage dataset->X = (void**)dataset->X_double; datatype = DOUBLE; break; } fclose(fs); // Labels must be in the range [1,Q] if( min_y == 0 ) { for(i=1; i<=nb_data; i++) dataset->y[i]++; Q++; } else if (min_y < 0) { printf("\nWrong numbering of the categories in %s, minimal value is: %ld\n", data_file, min_y); exit(0); } if((datatype != BIT && nr < dim_input * nb_data) || (datatype == BIT && nr < dim * nb_data)) printf("\nError in reading file %s, not enough data.\n", data_file); // Set the dimensions of the dataset dataset->nb_data = nb_data; dataset->dim = dim_input; dataset->datatype = datatype; return Q; } /* Load alpha from a file into a model and returns the maximum value of alpha */ double read_alpha(struct Model *model, char *alpha_file) { FILE *fs; long nr = 0; long i,k; long Q = model->Q; long nb_data = model->nb_data; double alpha, max_alpha=0.0; model->sum_all_alpha = 0; if((fs=fopen(alpha_file, "r"))==NULL) { printf("\nError: File of dual variables %s cannot be open.\n", alpha_file); exit(0); } if (model->alpha != NULL) { free(model->alpha[1]); free(model->alpha); } model->alpha = matrix(nb_data, Q); model->partial_average_alpha = (double *) realloc(model->partial_average_alpha, sizeof(double) * (nb_data+1)); for(i=1; i<=nb_data; i++) { model->partial_average_alpha[i] = 0.0; for(k=1; k<=Q; k++) { nr += fscanf(fs, "%lf", &alpha); model->alpha[i][k] = alpha; model->sum_all_alpha += alpha; model->partial_average_alpha[i] += alpha; if(alpha > max_alpha) max_alpha = alpha; } model->partial_average_alpha[i] /= Q; } fclose(fs); if(nr < Q*nb_data) printf("\nError in reading alpha file %s, not enough data.\n", alpha_file); return max_alpha; } /* Converts a string to an MSVM type */ enum MSVM_type str2model_type(char *str) { enum MSVM_type type; if(strcmp(str, "MSVM2") == 0) type = MSVM2; else if (strcmp(str, "WW") == 0) type = WW; else if (strcmp(str, "CS") == 0) type = CS; else if (strcmp(str, "LLW") == 0) type = LLW; else { printf("\nWarning: -m argument is not in the list of known MSVM types"); printf("\n (WW, CS, LLW, MSVM2). Falling back to MSVM2. \n"); type = MSVM2; } return type; } /* k = ker(kernel_type, x1, x2, dim, kernel_par) General wrapper for the kernel functions (which are defined in kernel.c) */ double ker(const enum Kernel_type type, const void *x1, const void *x2, const long dim, const double *par) { double res; switch(type) { case LINEAR: res = dot_double((double *) x1, (double *) x2, dim); break; case RBF: res = rbf_double((double *) x1, (double *) x2, dim, par[1]); break; case POLY_H: res = polynomial_homo_double((double *) x1, (double *) x2, dim, (int)par[1]); break; case POLY: res = polynomial_double((double *) x1, (double *) x2, dim, (int)par[1]); break; case CUSTOM1: res = custom_kernel_1((double *) x1, (double *) x2, dim, par); break; case CUSTOM2: res = custom_kernel_2((double *) x1, (double *) x2, dim, par); break; case CUSTOM3: res = custom_kernel_3((double *) x1, (double *) x2, dim, par); break; // Kernel functions for FLOAT data type case LINEAR_FLOAT: res = dot_float((float *) x1, (float *) x2, dim); break; case RBF_FLOAT: res = rbf_float((float *) x1, (float *) x2, dim, par[1]); break; case POLY_H_FLOAT: res = polynomial_homo_float((float *) x1, (float *) x2, dim, (int)par[1]); break; case POLY_FLOAT: res = polynomial_float((float *) x1, (float *) x2, dim, (int)par[1]); break; case CUSTOM1_FLOAT: res = custom_kernel_1_float((float *) x1, (float *) x2, dim, par); break; case CUSTOM2_FLOAT: res = custom_kernel_2_float((float *) x1, (float *) x2, dim, par); break; case CUSTOM3_FLOAT: res = custom_kernel_3_float((float *) x1, (float *) x2, dim, par); break; // Kernel functions for INT data type case LINEAR_INT: res = dot_int((int *) x1, (int *) x2, dim); break; case RBF_INT: res = rbf_int((int *) x1, (int *) x2, dim, par[1]); break; case POLY_H_INT: res = polynomial_homo_int((int *) x1, (int *) x2, dim, (int)par[1]); break; case POLY_INT: res = polynomial_int((int *) x1, (int *) x2, dim, (int)par[1]); break; case CUSTOM1_INT: res = custom_kernel_1_int((int *) x1, (int *) x2, dim, par); break; case CUSTOM2_INT: res = custom_kernel_2_int((int *) x1, (int *) x2, dim, par); break; case CUSTOM3_INT: res = custom_kernel_3_int((int *) x1, (int *) x2, dim, par); break; // Kernel functions for SHORT INT data type case LINEAR_SHORT: res = dot_short_int((short int *) x1, (short int *) x2, dim); break; case RBF_SHORT: res = rbf_short_int((short int *) x1, (short int *) x2, dim, par[1]); break; case POLY_H_SHORT: res = polynomial_homo_short_int((short int *) x1, (short int *) x2, dim, (int)par[1]); break; case POLY_SHORT: res = polynomial_short_int((short int *) x1, (short int *) x2, dim, (int)par[1]); break; case CUSTOM1_SHORT: res = custom_kernel_1_short_int((short int *) x1, (short int *) x2, dim, par); break; case CUSTOM2_SHORT: res = custom_kernel_2_short_int((short int *) x1, (short int *) x2, dim, par); break; case CUSTOM3_SHORT: res = custom_kernel_3_short_int((short int *) x1, (short int *) x2, dim, par); break; // Kernel functions for BYTE data type case LINEAR_BYTE: res = dot_byte((unsigned char *) x1, (unsigned char *) x2, dim); break; case RBF_BYTE: res = rbf_byte((unsigned char *) x1, (unsigned char *) x2, dim, par[1]); break; case POLY_H_BYTE: res = polynomial_homo_byte((unsigned char *) x1, (unsigned char *) x2, dim, (int)par[1]); break; case POLY_BYTE: res = polynomial_byte((unsigned char *) x1, (unsigned char *) x2, dim, (int)par[1]); break; case CUSTOM1_BYTE: res = custom_kernel_1_byte((unsigned char *) x1, (unsigned char *) x2, dim, par); break; case CUSTOM2_BYTE: res = custom_kernel_2_byte((unsigned char *) x1, (unsigned char *) x2, dim, par); break; case CUSTOM3_BYTE: res = custom_kernel_3_byte((unsigned char *) x1, (unsigned char *) x2, dim, par); break; // Kernel functions for BIT data type case LINEAR_BIT: res = dot_bit((int *) x1, (int *) x2, dim); break; case RBF_BIT: res = rbf_bit((int *) x1, (int *) x2, dim, par[1]); break; case POLY_H_BIT: res = polynomial_homo_bit((int *) x1, (int *) x2, dim, (int)par[1]); break; case POLY_BIT: res = polynomial_bit((int *) x1, (int *) x2, dim, (int)par[1]); break; case CUSTOM1_BIT: res = custom_kernel_1_bit((int *) x1, (int *) x2, dim, par); break; case CUSTOM2_BIT: res = custom_kernel_2_bit((int *) x1, (int *) x2, dim, par); break; case CUSTOM3_BIT: res = custom_kernel_3_bit((int *) x1, (int *) x2, dim, par); break; default: printf("\n\nUnknown kernel type (%d).\n\n", type); exit(0); } return res; } /* Set default kernel parameter values See kernel.h for the definition of these values */ void set_default_kernel_par(struct Model *model) { enum Kernel_type kernel_type = model->nature_kernel; // Use same defaults for DOUBLE, FLOAT, INT... data types kernel_type %= 10; // But different defaults depending on the kernel type switch (kernel_type) { case LINEAR: model->kernel_par = NULL; break; case RBF: model->kernel_par = (double*)realloc(model->kernel_par, sizeof(double) * 2); model->kernel_par[0] = 1; model->kernel_par[1] = DEFAULT_RBF_KERNEL_PAR; break; case POLY_H: model->kernel_par = (double*)realloc(model->kernel_par, sizeof(double) * 2); model->kernel_par[0] = 1; model->kernel_par[1] = DEFAULT_POLY_KERNEL_PAR; break; case POLY: model->kernel_par = (double*)realloc(model->kernel_par, sizeof(double) * 2); model->kernel_par[0] = 1; model->kernel_par[1] = DEFAULT_POLY_KERNEL_PAR; break; case CUSTOM1: model->kernel_par = (double*)realloc(model->kernel_par, sizeof(double) * 2); model->kernel_par[0] = 1; model->kernel_par[1] = DEFAULT_CUSTOM_KERNEL_1_PAR; break; case CUSTOM2: model->kernel_par = (double*)realloc(model->kernel_par, sizeof(double) * 2); model->kernel_par[0] = 1; model->kernel_par[1] = DEFAULT_CUSTOM_KERNEL_2_PAR; break; case CUSTOM3: model->kernel_par = (double*)realloc(model->kernel_par, sizeof(double) * 2); model->kernel_par[0] = 1; model->kernel_par[1] = DEFAULT_CUSTOM_KERNEL_3_PAR; break; default: // do nothing for an unknown kernel break; } } /* Set the values of C_k in a model to C for the Q classes also set Q in the model */ void MSVM_model_set_C(double C, long Q, struct Model *model) { long k; model->C = (double*) realloc(model->C, sizeof(double) * (Q+1) ); for(k=1;k<=Q;k++) { model->C[k] = C; } model->Q = Q; } /* Access typed data in model as a double This function should not be used for intensive computations */ double model_get_Xij(struct Model *model, const long i, const long j) { int x_bit; unsigned int mask; switch(model->datatype) { case DOUBLE: return model->X_double[i][j]; case FLOAT: return (double)model->X_float[i][j]; case INT: return (double)model->X_int[i][j]; case SHORT: return (double)model->X_short[i][j]; case BYTE: return (double)model->X_byte[i][j]; case BIT: x_bit = model->X_int[i][j/32]; mask = 0x1; mask <<= j%32; return (double)(x_bit & mask); default: printf("Cannot access model->X[i][j] with unknown data type in model.\n"); exit(0); } } /* Ex.: i = check_argv(argc,argv,".model") Check if any argument of the command line contains ".model" and returns the corresponding index of argv. Returns 0 if ".model" cannot be found. */ int check_argv(int argc, char *argv[], char *str) { int i; int arg_str = 0; for(i = 1; i < argc; i++) if(strstr(argv[i], str) != NULL ) { arg_str = i; break; } return arg_str; } /* Ex.: i = check_argv_eq(argc,argv,"-f") Check if any argument of the command line is "-f" and returns the corresponding index of argv. Returns 0 if "-f" cannot be found. */ int check_argv_eq(int argc, char *argv[], char *str) { int i; int arg_str = 0; for(i = 1; i < argc; i++) if(strcmp(argv[i], str) == 0 ) { arg_str = i; break; } return arg_str; } /* Make a pause and wait for user to press RETURN */ void Pause(char *message) { if(message!=NULL) printf("%s\n",message); printf("\a""=> New Line to proceed... \n"); while(getchar()!='\n'); return; } /* Remove spaces from string */ void remove_spaces(char *string, char *str_nospaces, const int maxchar) { int i = 0; while(*string != '\0') { if(*string != ' ' && i= 1 if( nprocs < 1 ) nprocs = 1; return nprocs; } MSVMpack1.2/src/libtrainMSVM.c~0000644000175000017500000004471611761347272015410 0ustar lauerlauer/* Copyright 2008-2010 Yann Guermeur */ /* 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 2 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, write to the Free Software */ /* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA*/ /*--------------------------------------------------------------------------*/ /* Name : libtrainMSVM.c */ /* Version : 2.0 */ /* Creation : 06/20/08 */ /* Last update : 02/04/11 */ /* Subject : Training functions for MSVMpack */ /* Algo. : Wrapper functions only */ /* Author : Fabien Lauer and Yann Guermeur fabien.lauer@loria.fr */ /*--------------------------------------------------------------------------*/ #include "libtrainMSVM.h" #include "libtrainMSVM_WW.h" #include "libtrainMSVM_CS.h" #include "libtrainMSVM_LLW.h" #include "libtrainMSVM_2.h" #include "libtrainMSVM_2fw.h" /* status = MSVM_train(model, training_set, chunk_size, accuracy, cache_memory, nprocs, cache_size_in_mb, alpha0_file, model_tmp_file, log_file) use accuracy = 0 for infinite training use alpha0_file = NULL for default initialization of alpha use model_tmp_file = NULL to deactivate periodic saving of model use log_file = NULL to deactivate optimization log Return value: -1 : Error (infeasible initial alpha or unknown model type) 0 : Optimum found with desired accuracy level 1 : Stopped after maximum number of iterations N > 1 : Stopped by user after N iterations */ long MSVM_train(struct Model *model, struct Data *training_set, long chunk_size, const double accuracy, int cache_memory, int nprocs, char *alpha0_file, char *model_tmp_file, char *log_file) { long return_status; // Check number of threads if (nprocs <= 0 || nprocs > get_nprocessors()) nprocs = get_nprocessors(); printf("Using %d processor(s) for training.\n",nprocs); // Launch training for this model type switch (model->type) { case WW: return_status = MSVM_WW_train(model,training_set,chunk_size,accuracy, cache_memory, nprocs, alpha0_file,model_tmp_file,log_file); break; case CS: return_status = MSVM_CS_train(model,training_set,chunk_size,accuracy, cache_memory, nprocs, alpha0_file,model_tmp_file,log_file); break; case LLW: return_status = MSVM_LLW_train(model,training_set,chunk_size,accuracy, cache_memory, nprocs, alpha0_file,model_tmp_file,log_file); break; case MSVM2: if(model->algorithm == Rosen) { printf("Starting Rosen's algorithm to train an M-SVM^2...\n"); return_status = MSVM_2_train(model,training_set,chunk_size,accuracy, cache_memory, nprocs, alpha0_file,model_tmp_file,log_file); } else return_status = MSVM_2fw_train(model,training_set,chunk_size,accuracy, cache_memory, nprocs, alpha0_file,model_tmp_file,log_file); break; default: printf("MSVM_train: Unknown model type. \n"); return_status = -1; break; } return return_status; } /* Initializes the parameters and filenames used for training an M-SVM from a .com file. */ long MSVM_init_train_comfile(struct Model *model, char *com_file, char *training_file, char *alpha0_file, char *alpha_file, char *log_file) { long k,chunk_size; unsigned int kernel_type; FILE *fs; long nr = 0; if((fs=fopen(com_file, "r"))==NULL) { printf("\n.com file %s cannot be open.\n", com_file); exit(0); } nr += fscanf(fs, "%ld", &(model->Q)); nr += fscanf(fs, "%d", &kernel_type); model->nature_kernel = kernel_type; set_default_kernel_par(model); model->C = (double*)realloc(model->C, sizeof(double) * (model->Q + 1)); for(k=1;k<=model->Q;k++) nr += fscanf(fs, "%lf", &(model->C[k])); nr += fscanf(fs, "%ld", &chunk_size); nr += fscanf(fs, "%s", training_file); printf("\nThe file of the training data is: %s", training_file); nr += fscanf(fs, "%s", alpha0_file); nr += fscanf(fs, "%s", alpha_file); nr += fscanf(fs, "%s", log_file); fclose(fs); if(nr < 5) printf("\nError in reading com file %s, not enough data.\n", com_file); return chunk_size; } /* init_alpha_b(model_ptr, alpha_file) Initialize the alpha of the model pointed by model_ptr by reading them from the file alpha_file or setting all alpha to 0 if alpha_file is NULL Also (re)allocate memory for the vector b */ void init_alpha_b(struct Model *model, char *alpha_file) { long i,k; const long Q = model->Q; const long nb_data = model->nb_data; if(model->type == CS) { printf("Do not use init_alpha_b() with CS-type M-SVM:\n This M-SVM has no vector b and cannot initalize all alpha to 0.\n Use CS_init_alpha() instead.\n"); exit(0); } // Initialize alpha if(alpha_file == NULL) { if (model->alpha != NULL) { free(model->alpha[1]); free(model->alpha); } model->alpha = matrix(nb_data, Q); model->partial_average_alpha = (double *) realloc(model->partial_average_alpha, sizeof(double) * (nb_data+1)); for(i=1; i<=nb_data; i++) { model->partial_average_alpha[i] = 0.0; for(k=1; k<=Q; k++) model->alpha[i][k] = 0.0; } model->sum_all_alpha = 0.0; } else read_alpha(model, alpha_file); // Initialize b model->b_SVM = (double *)realloc(model->b_SVM, (Q+1) * sizeof(double)); return; } /* compute_K(cache,model) Compute the submatrix of the Kernel matrix corresponding to the chunk */ void compute_K(struct TrainingCache *cache, const struct Model *model) { long i; const long chunk_size = cache->chunk_size; for(i=1; i<=chunk_size; i++) { cache->K[i] = kernel_get_row(cache->table_chunk[i], cache->kc, model); } } /* Release the cache space reserved for the kernel submatrix corresponding to the chunk */ void release_K(struct TrainingCache *cache) { long i; const long chunk_size = cache->chunk_size; // Take mutex on in_use pthread_mutex_lock(&kernelcache_inuse_mutex); for (i=1;i<=chunk_size;i++) { cache->kc->in_use[cache->kc->rows_idx[cache->table_chunk[i]]]--; } // Release mutex on in_use pthread_mutex_unlock(&kernelcache_inuse_mutex); } void kernel_initialize_cache(unsigned long cache_size, struct KernelCache *kc, const struct Model *model) { long nb_data = model->nb_data; long i; unsigned long size_row = sizeof(double) * (nb_data + 1); // Size of a kernel row unsigned long size_max = (size_row + 1) * (nb_data + 1); // Maximal necessary cache size if(cache_size < size_row) cache_size = 0; // Allign cache_size with size_row if(cache_size % size_row > 0) cache_size -= cache_size % size_row; // Limit cache_size to what is necessary if(cache_size > size_max) cache_size = size_max; // Allocate maximal cache memory kc->K = NULL; while (kc->K == NULL && cache_size>0) { kc->K = (double *)malloc(cache_size); if(kc->K == NULL) cache_size -= size_row; } if(kc->K == NULL) { printf("no more memory, abording.\n"); exit(1); } // How many rows allocated? long nrows = (cache_size/size_row) - 1; // Pointers to rows kc->rows_ptr = (double **)malloc(sizeof(double *) * (nrows + 1)); for (i=0;i<=nrows;i++) { kc->rows_ptr[i] = NULL; // NULL means row not available; } // Which cache_index for these rows? kc->rows_idx = (long *)calloc(nb_data+1, sizeof(long)); kc->rows_idx_inv = (long *)calloc(nrows+1, sizeof(long)); // Which rows are in use (and by how many threads)? kc->in_use = (int *)calloc(nrows+1, sizeof(int)); if(kc->in_use == NULL) { printf("initializing kernel cache: not enough memory.\n"); exit(1); } else { printf("Allocated %lu MB of memory to cache %ld rows (%ld %%) of the kernel matrix.\n",cache_size/MBYTES + 1, nrows,100 * nrows/nb_data); } kc->nrows = nrows; kc->max_idx = 1; // first free row index kc->is_full = 0; // Initialize mutexes and condition variables kernelcache_rowptr_mutex = (pthread_mutex_t *)malloc(sizeof(pthread_mutex_t) * (nrows+1)); kernelcache_rowptr_cond = (pthread_cond_t *)malloc(sizeof(pthread_cond_t) * (nrows+1)); for(i=1;i<=nrows;i++) { pthread_mutex_init(&kernelcache_rowptr_mutex[i], NULL); pthread_cond_init (&kernelcache_rowptr_cond[i], NULL); } return ; } void kernel_free_cache(struct KernelCache *kc) { free(kc->K); free(kc->rows_ptr); free(kc->rows_idx); free(kc->rows_idx_inv); free(kc->in_use); long i; for(i=1;i<=kc->nrows;i++) { pthread_mutex_destroy(&kernelcache_rowptr_mutex[i]); pthread_cond_destroy (&kernelcache_rowptr_cond[i]); } free(kernelcache_rowptr_mutex); free(kernelcache_rowptr_cond); } /* Fetch a pointer to the row in cache corresponding to X_index */ double *kernel_get_row(long index, struct KernelCache *kc, const struct Model *model) { long i=0; // Make sure no other thread modifies the in_use table during this check pthread_mutex_lock(&kernelcache_inuse_mutex); // is the row already available? if(kc->rows_idx[index] != 0 && kc->rows_ptr[kc->rows_idx[index]] != NULL ) { // Yes, so mark it as "in use" kc->in_use[kc->rows_idx[index]]++; pthread_mutex_unlock(&kernelcache_inuse_mutex); // and return pointer to row data return kc->rows_ptr[kc->rows_idx[index]]; } else if (kc->rows_idx[index] != 0 && kc->rows_ptr[kc->rows_idx[index]] == NULL) { // The row is being computed by another thread, // so mark it as "in use" by one more thread (this one) kc->in_use[kc->rows_idx[index]]++; pthread_mutex_unlock(&kernelcache_inuse_mutex); // do not block other threads while waiting // and wait for it to be ready pthread_mutex_lock(&kernelcache_rowptr_mutex[kc->rows_idx[index]]); while(kc->rows_ptr[kc->rows_idx[index]] == NULL) { pthread_cond_wait(&kernelcache_rowptr_cond[kc->rows_idx[index]], &kernelcache_rowptr_mutex[kc->rows_idx[index]]); } pthread_mutex_unlock(&kernelcache_rowptr_mutex[kc->rows_idx[index]]); if(kc->rows_ptr[kc->rows_idx[index]] != NULL) { // return pointer to the computed row in cache return kc->rows_ptr[kc->rows_idx[index]]; } else { printf("Error in kernel_get_row: row not really available.\n"); printf("row_idx = %ld, index = %ld\n",kc->rows_idx[index], index); exit(1); } } // Row is not currently available, so compute kernel row if(kc->is_full) { // Cache already full, so search for the first row not currently in use i = 1; while(i<=kc->nrows && kc->in_use[i] > 0) { i++; } if(i > kc->nrows) { printf("Not enough memory for kernel caching. Reduce the number of CPUs or increase kernel cache memory.\n"); exit(0); } } else { // Append row at the end of cache i = kc->max_idx; kc->max_idx++; if(kc->max_idx > kc->nrows){ kc->is_full = 1; } } kc->in_use[i]++; // Mark row as in use kc->rows_ptr[i] = NULL; // but as not available (going to overwrite it) kc->rows_idx[index] = i; // and currently computing kc->rows_idx[kc->rows_idx_inv[i]] = 0; // mark previously cached row as unavailable // Release mutex on in_use pthread_mutex_unlock(&kernelcache_inuse_mutex); // Compute and cache the kernel row for X_index at location i in the kernel cache compute_kernel_row(index, i, kc, model); // do the computation pthread_mutex_lock(&kernelcache_rowptr_mutex[i]); // pthread_cond_broadcast(&kernelcache_rowptr_cond[i]); // signal that the row is ready pthread_mutex_unlock(&kernelcache_rowptr_mutex[i]); // and unlock other waiting threads // Return the row_ptr to the row just computed return kc->rows_ptr[i]; } void compute_kernel_row(const long index, const long cache_index, struct KernelCache *kc, const struct Model *model) { const long nb_data = model->nb_data; const long nature_kernel = model->nature_kernel; const long dim_input = model->dim_input; const double *kernel_par = model->kernel_par; double *row_ptr = &(kc->K[(cache_index-1)*(nb_data+1)]); // base address of row in cache memory long j; double *k = row_ptr + 1; // Compute row for(j=1; j<=nb_data; j++) { *k++ = ker(nature_kernel, model->X[index], model->X[j], dim_input, kernel_par); } if(model->type == MSVM2) { row_ptr[index] += 1. /(2 * model->C[model->y[index]]); } // Mark row as available kc->rows_idx_inv[cache_index] = index; kc->rows_ptr[cache_index] = row_ptr; } /* Switch working load between threads from main (kernel) computations to gradient updates As as result, the number of threads used for gradient updates increases while main computing threads (XX_train_thread) are terminated returns 1 if the calling main thread must stop */ int __inline__ switch_thread(const int nprocs, int *numthreads_grad, int *next_numthreads_grad, long *percentage, int *percentage_step, struct ThreadGradient_data *grad_data, int thread_id, long nb_data) { int k; // Keep (nprocs - next_numthreads_grad + 1) main computing threads // for kernel evaluations if(thread_id < nprocs - *next_numthreads_grad + 1){ // This calling thread continues with more children to compute gradient updates *numthreads_grad = *next_numthreads_grad; // Update splits of the gradient vector grad_data[0].start_i = 1; grad_data[0].end_i = nb_data / *numthreads_grad; for(k=1;k<*numthreads_grad-1;k++) { grad_data[k].start_i = grad_data[k-1].end_i + 1; grad_data[k].end_i = grad_data[k].start_i + nb_data / *numthreads_grad -1; } if(*numthreads_grad>1) { grad_data[*numthreads_grad-1].start_i = grad_data[*numthreads_grad-2].end_i + 1; grad_data[*numthreads_grad-1].end_i = nb_data; } // Update percentage for next step switch(*percentage_step) { case 1: *percentage = nb_data / 2; // 50% of kernel matrix *next_numthreads_grad = nprocs/2; // -> 50% of CPUs for gradient break; case 2: *percentage = 3 * nb_data / 4; // 75% *next_numthreads_grad = 3*nprocs/4; // -> 3/4 of CPUs break; case 3: *percentage = 19 * nb_data / 20; // 95% *next_numthreads_grad = nprocs-1; // -> all CPUs - 1 break; case 4: *percentage = nb_data; // 100% (entire kernel matrix in memory) *next_numthreads_grad = nprocs; // -> all CPUs for gradient updates break; default: *percentage = 2*nb_data; // no more steps break; } if(*next_numthreads_grad == 0) *next_numthreads_grad = 1; *percentage_step += 1; return 0; } else { // The calling thread must stop (enough kernel rows have been computed) //printf("%ld rows of kernel matrix cached, stopping thread %d... \n",percentage,thread_id); return 1; } } /* Randomly select a chunk of data (working set) At each training step, only the variables alpha_ik corresponding to this chunk are optimized. */ void select_random_chunk(struct TrainingCache *cache, const struct Model *model) { long i,j,random_num,row; const long nb_data = model->nb_data; const long chunk_size = cache->chunk_size; for(i=1; i<=nb_data; i++) { cache->out_of_chunk[i] = i; cache->in_chunk[i] = 0; } for(i=1; i<=chunk_size; i++) { random_num = nrand48(xi); row = (random_num % (nb_data-i+1))+1; cache->table_chunk[i] = cache->out_of_chunk[row]; for(j=row; j<=nb_data-i; j++) cache->out_of_chunk[j] = cache->out_of_chunk[j+1]; cache->in_chunk[cache->table_chunk[i]] = 1; } return; } /* Write a vector/matrix to a file (used for the vector alpha) */ void write_vector(double **vector, const long nb_data, const long Q, char *file) { long i,k; FILE *fc; int rc; char command[taille]; if((fc=fopen(file, "w"))==NULL) { printf("\nThe file %s cannot be open.\n", file); exit(0); } for(i=1; i<=nb_data; i++) for(k=1; k<=Q; k++) fprintf(fc, "%15.10f %c", vector[i][k], (k==Q) ? '\n': ' '); fclose(fc); sprintf(command, "cp %s Save_alpha/.", file); rc = system(command); } /* Monitor the model while training: Save model in a temporary file on demand (do_save=1) and every 'period' seconds at most. */ void *MSVM_monitor_model_thread(void *monitor_data) { struct MonitorData * md = (struct MonitorData *)monitor_data; char *model_tmp_file = md->model_tmp_file; int period = md->period; struct Model * model = md->model; int nSV = 0; if ( model_tmp_file == NULL) { pthread_exit(EXIT_SUCCESS); } while(!STOP) { printf("waiting save for %d ...\n",period); // Wait for period sleep (period) ; // Block training and updates of alpha // while writing model pthread_mutex_lock(&model_mutex); // Save model nSV = MSVM_save_model(model, model_tmp_file); printf("Temporary model saved in %s\n",model_tmp_file); // Release training pthread_mutex_unlock(&model_mutex); } pthread_exit(EXIT_SUCCESS); } /* Print info during training */ void print_training_info(const long iter, const long nb_SV, const double ratio, const enum MSVM_type type) { char iter_str[20], nb_SV_str[20]; int i,num_spaces; if(iter == 0) { if(type == MSVM2) printf("\n Iteration\t Number of Support Vectors\t Ratio dual/primal\n"); else printf("\n Iteration\t Number of margin Sup. Vec.\t Ratio dual/primal\n"); printf("-------------------------------------------------------------------\n"); } sprintf(iter_str, "%ld",iter); num_spaces = (TRAIN_STEP/TRAIN_SMALL_STEP) - strlen(iter_str) - 1; for(i=0;i 0.0001) printf("\r %s %s %3.2lf %%\n",iter_str, nb_SV_str, 100*ratio); else if(ratio < 0.999999 && ratio > 0.000001) printf("\r %s %s %3.4lf %%\n",iter_str, nb_SV_str, 100*ratio); else printf("\r %s %s %3.8lf %%\n",iter_str, nb_SV_str, 100*ratio); } MSVMpack1.2/src/kernel.c0000644000175000017500000004273411707263252014154 0ustar lauerlauer#include // Include user-defined custom kernels #include "custom_kernels.c" /* Common kernel functions */ #ifdef __SSE4_1__ /* Vectorized code with SSE4.1 intrinsics (only for Intel processors) */ #include /* Dot product (linear kernel function) */ double dot_double(const double *a, const double *b, const long dim) { double dot; long i; __m128d num1, num2, num4; num4= _mm_setzero_pd(); //sets sum to zero for(i=1; i<=dim-1; i+=2) { num1 = _mm_load_pd(a+i); num2 = _mm_load_pd(b+i); num2 = _mm_dp_pd(num1,num2,0x31); // dot product num4 = _mm_add_sd(num4, num2); // vertical addition (global sum) } _mm_store_sd(&dot,num4); // Epilog: if(dim%2 != 0) { dot += a[dim]*b[dim]; } return dot; } double dot_float(const float *a, const float *b, const long dim) { float dot; long i; __m128 num1, num2, num4; num4= _mm_setzero_ps(); //sets sum to zero for(i=1; i<=dim-3; i+=4) { num1 = _mm_load_ps(a+i); num2 = _mm_load_ps(b+i); num2 = _mm_dp_ps(num1,num2,0xf1); // dot product num4 = _mm_add_ss(num4, num2); // vertical addition } _mm_store_ss(&dot,num4); int epilog = dim%4; switch (epilog) { case 1: dot += (a[dim]*b[dim]); break; case 2: dot += (a[dim]*b[dim]) + (a[dim-1]*b[dim-1]); break; case 3: dot += (a[dim]*b[dim]) + (a[dim-1]*b[dim-1]) + (a[dim-2]*b[dim-2]); break; default: break; } return (double)dot; } /* Gaussian RBF kernel k(x,z) = exp(-||x - z||^2 / 2sigma^2) */ double rbf_double(const double *a, const double *b, const long dim, const double sigma) { double ker_val; long i; __m128d num1, num2, num3, num4; num4= _mm_setzero_pd(); //sets sum to zero for(i=1; i<=dim-1; i+=2) { num1 = _mm_load_pd(a+i); num2 = _mm_load_pd(b+i); num3 = _mm_sub_pd(num1, num2); // substraction num3 = _mm_dp_pd(num3,num3,0x31); // dot product num4 = _mm_sub_sd(num4, num3); // vertical addition } _mm_store_sd(&ker_val,num4); // Epilog: if(dim%2 != 0) { ker_val -= (a[dim]-b[dim])*(a[dim]-b[dim]); } return exp(ker_val / (2 * sigma * sigma)); } double rbf_float(const float *a, const float *b, const long dim, const double sigma) { float ker_val; long i; __m128 num1, num2, num3, num4; num4= _mm_setzero_ps(); //sets sum to zero for(i=1; i<=dim-3; i+=4) { num1 = _mm_load_ps(a+i); //loads aligned array a into num1 num1= a[3] a[2] a[1] a[0] num2 = _mm_load_ps(b+i); //loads aligned array b into num2 num2= b[3] b[2] b[1] b[0] num3 = _mm_sub_ps(num1, num2); // parallel substraction num3 = num1 - num2 num3 = _mm_dp_ps(num3,num3,0xf1); // dot product: num3[0] = num3[0]^2 + ... + num3[4]^2 num4 = _mm_sub_ss(num4, num3); // vertical addition } _mm_store_ss(&ker_val,num4); // Epilog int epilog = dim%4; switch (epilog) { case 1: ker_val -= (a[dim]-b[dim])*(a[dim]-b[dim]); break; case 2: ker_val -= (a[dim]-b[dim])*(a[dim]-b[dim]) + (a[dim-1]-b[dim-1])*(a[dim-1]-b[dim-1]); break; case 3: ker_val -= (a[dim]-b[dim])*(a[dim]-b[dim]) + (a[dim-1]-b[dim-1])*(a[dim-1]-b[dim-1]) + (a[dim-2]-b[dim-2])*(a[dim-2]-b[dim-2]); break; default: break; } return exp((double)ker_val / (2 * sigma * sigma)); } #else #ifdef __SSE3__ /* Vectorized code with SSE3 intrinsics (this should be available on most Intel & AMD processors) */ #include /* Dot product (linear kernel function) */ double dot_double(const double *a, const double *b, const long dim) { double dot; long i; __m128d num1, num2, num3, num4; num4= _mm_setzero_pd(); //sets sum to zero for(i=1; i<=dim-1; i+=2) { num1 = _mm_load_pd(a+i); num2 = _mm_load_pd(b+i); num3 = _mm_mul_pd(num1,num2); // multiplication num3 = _mm_hadd_pd(num3, num3); // horizontal addition num4 = _mm_add_sd(num4, num3); // vertical summation } _mm_store_sd(&dot,num4); // Epilog: if(dim%2 != 0) { dot += a[dim]*b[dim]; } return dot; } double dot_float(const float *a, const float *b, const long dim) { float dot; long i; __m128 num1, num2, num3, num4; num4= _mm_setzero_ps(); //sets sum to zero for(i=1; i<=dim-3; i+=4) { num1 = _mm_load_ps(a+i); num2 = _mm_load_ps(b+i); num3 = _mm_mul_ps(num1,num2); // product: num3[0] = num1[0]*num2[0], num3[1]=num1[0]*num2[0]... num3 = _mm_hadd_ps(num3, num3); // horizontal addition: num3[0] = num3[0]+num3[1],num3[1]=num3[2]+num3[3] num4 = _mm_add_ps(num4, num3); // vertical addition: num4[0] += num3[0], num4[1]+=num3[1] } num4= _mm_hadd_ps(num4, num4); // last horizontal addition: num4[0] = num4[0]+num4[1] _mm_store_ss(&dot,num4); int epilog = dim%4; switch (epilog) { case 1: dot += (a[dim]*b[dim]); break; case 2: dot += (a[dim]*b[dim]) + (a[dim-1]*b[dim-1]); break; case 3: dot += (a[dim]*b[dim]) + (a[dim-1]*b[dim-1]) + (a[dim-2]*b[dim-2]); break; default: break; } return (double)dot; } /* Gaussian RBF kernel k(x,z) = exp(-||x - z||^2 / 2sigma^2) */ double rbf_double(const double *a, const double *b, const long dim, const double sigma) { double ker_val; long i; __m128d num1, num2, num3, num4; num4= _mm_setzero_pd(); //sets sum to zero for(i=1; i<=dim-1; i+=2) { num1 = _mm_load_pd(a+i); num2 = _mm_load_pd(b+i); num3 = _mm_sub_pd(num1, num2); // substraction // dot product: num3 = _mm_mul_pd(num3,num3); // multiplication num3 = _mm_hadd_pd(num3, num3); // horizontal addition num4 = _mm_sub_sd(num4, num3); // vertical addition } _mm_store_sd(&ker_val,num4); // Epilog: if(dim%2 != 0) { ker_val -= (a[dim]-b[dim])*(a[dim]-b[dim]); } return exp(ker_val / (2 * sigma * sigma)); } double rbf_float(const float *a, const float *b, const long dim, const double sigma) { float ker_val; long i; __m128 num1, num2, num3, num4; num4= _mm_setzero_ps(); //sets sum to zero for(i=1; i<=dim-3; i+=4) { num1 = _mm_load_ps(a+i); //loads aligned array a into num1 num1= a[3] a[2] a[1] a[0] num2 = _mm_load_ps(b+i); //loads aligned array b into num2 num2= b[3] b[2] b[1] b[0] num3 = _mm_sub_ps(num1, num2); // parallel substraction num3 = num1 - num2 num3 = _mm_mul_ps(num3,num3); // product: num3[0] = num3[0]^2... num3 = _mm_hadd_ps(num3, num3); // horizontal addition: num3[0] = num3[0]+num3[1], // num3[1] = num3[2]+num3[3] num4 = _mm_sub_ps(num4, num3); // vertical addition } num4= _mm_hadd_ps(num4, num4); // last horizontal addition _mm_store_ss(&ker_val,num4); // Epilog int epilog = dim%4; switch (epilog) { case 1: ker_val -= (a[dim]-b[dim])*(a[dim]-b[dim]); break; case 2: ker_val -= (a[dim]-b[dim])*(a[dim]-b[dim]) + (a[dim-1]-b[dim-1])*(a[dim-1]-b[dim-1]); break; case 3: ker_val -= (a[dim]-b[dim])*(a[dim]-b[dim]) + (a[dim-1]-b[dim-1])*(a[dim-1]-b[dim-1]) + (a[dim-2]-b[dim-2])*(a[dim-2]-b[dim-2]); break; default: break; } return exp((double)ker_val / (2 * sigma * sigma)); } #else /* If SSE3 is not available: Use standard (non-vectorized) operations (no intrinsics) */ /* Dot product (linear kernel function) */ double dot_double(const double *a , const double *b , const long dim) { long i; double result=0.0; for(i = 1; i<=dim; i++) result += a[i] * b[i]; return result; } double dot_float(const float *a , const float *b , const long dim) { long i; float result = 0.0; for(i = 1; i<=dim; i++) result += a[i] * b[i]; return (double)result; } /* Gaussian RBF kernel k(x,z) = exp(-||x - z||^2 / 2sigma^2) */ double rbf_double(const double *a, const double *b, const long dim, const double sigma) { long i; double result=0.0; for(i=1;i<=dim;i++) result -= (a[i] - b[i]) * (a[i] - b[i]); result /= (2 * sigma * sigma); return exp(result); } double rbf_float(const float *a, const float *b, const long dim, const double sigma) { long i; float result=0.0; for(i=1;i<=dim;i++) result -= (a[i] - b[i]) * (a[i] - b[i]); return exp((double)result/(2 * sigma * sigma)); } #endif #endif /* Vectorized code with SSE2 intrinsics (this should be available on all processors released since 2003) */ #include /* Linear kernel for SHORT INT data */ double dot_short_int(const short int *a, const short int *b, const long dim) { int dot; long i; __m128i num1, num2, num3, num4; num4= _mm_setzero_si128(); //sets sum to zero for(i=1; i<=dim-7; i+=8) { num1 = _mm_load_si128((__m128i *)(a+i)); num2 = _mm_load_si128((__m128i *)(b+i)); num3 = _mm_madd_epi16(num1,num2); // dot product num4 = _mm_add_epi32(num4, num3); // vertical addition } // Final horizontal addition num3 = _mm_srli_si128(num4,4); num4 = _mm_add_epi32(num3,num4); num3 = _mm_srli_si128(num3,4); num4 = _mm_add_epi32(num3,num4); num3 = _mm_srli_si128(num3,4); num4 = _mm_add_epi32(num3,num4); dot = _mm_cvtsi128_si32(num4); int epilog = dim%8; switch (epilog) { case 1: dot += (a[dim]*b[dim]); break; case 2: dot += (a[dim]*b[dim]) + (a[dim-1]*b[dim-1]); break; case 3: dot += (a[dim]*b[dim]) + (a[dim-1]*b[dim-1]) + (a[dim-2]*b[dim-2]); break; case 4: dot += (a[dim]*b[dim]) + (a[dim-1]*b[dim-1]) + (a[dim-2]*b[dim-2]) + (a[dim-3]*b[dim-3]); break; case 5: dot += (a[dim]*b[dim]) + (a[dim-1]*b[dim-1]) + (a[dim-2]*b[dim-2]) + (a[dim-3]*b[dim-3]) + (a[dim-4]*b[dim-4]); break; case 6: dot += (a[dim]*b[dim]) + (a[dim-1]*b[dim-1]) + (a[dim-2]*b[dim-2])+ (a[dim-3]*b[dim-3]) + (a[dim-5]*b[dim-5]); break; case 7: dot += (a[dim]*b[dim]) + (a[dim-1]*b[dim-1]) + (a[dim-2]*b[dim-2])+ (a[dim-3]*b[dim-3]) + (a[dim-5]*b[dim-5]) + (a[dim-6]*b[dim-6]); break; default: break; } return (double)dot; } /* Gaussian RBF kernel for SHORT INT data */ double rbf_short_int(const short int *a, const short int *b, const long dim, const double sigma) { int dot; long i; __m128i num1, num2, num3, num4; num4= _mm_setzero_si128(); //sets sum to zero for(i=1; i<=dim-7; i+=8) { num1 = _mm_load_si128((__m128i *)(a+i)); num2 = _mm_load_si128((__m128i *)(b+i)); num3 = _mm_sub_epi16(num1, num2); // substraction num3 = _mm_madd_epi16(num3,num3); // dot product num4 = _mm_add_epi32(num4, num3); // vertical addition } // Final horizontal addition num3 = _mm_srli_si128(num4,4); num4 = _mm_add_epi32(num3,num4); num3 = _mm_srli_si128(num3,4); num4 = _mm_add_epi32(num3,num4); num3 = _mm_srli_si128(num3,4); num4 = _mm_add_epi32(num3,num4); dot = _mm_cvtsi128_si32(num4); int epilog = dim%8; switch (epilog) { case 1: dot += (a[dim]-b[dim])*(a[dim]-b[dim]); break; case 2: dot += (a[dim]-b[dim])*(a[dim]-b[dim]) + (a[dim-1]-b[dim-1])*(a[dim-1]-b[dim-1]); break; case 3: dot += (a[dim]-b[dim])*(a[dim]-b[dim]) + (a[dim-1]-b[dim-1])*(a[dim-1]-b[dim-1]) + (a[dim-2]-b[dim-2])*(a[dim-2]-b[dim-2]); break; case 4: dot += (a[dim]-b[dim])*(a[dim]-b[dim]) + (a[dim-1]-b[dim-1])*(a[dim-1]-b[dim-1]) + (a[dim-2]-b[dim-2])*(a[dim-2]-b[dim-2])+ (a[dim-3]-b[dim-3])*(a[dim-3]-b[dim-3]); break; case 5: dot += (a[dim]-b[dim])*(a[dim]-b[dim]) + (a[dim-1]-b[dim-1])*(a[dim-1]-b[dim-1]) + (a[dim-2]-b[dim-2])*(a[dim-2]-b[dim-2])+ (a[dim-3]-b[dim-3])*(a[dim-3]-b[dim-3])+ (a[dim-4]-b[dim-4])*(a[dim-4]-b[dim-4]); break; case 6: dot += (a[dim]-b[dim])*(a[dim]-b[dim]) + (a[dim-1]-b[dim-1])*(a[dim-1]-b[dim-1]) + (a[dim-2]-b[dim-2])*(a[dim-2]-b[dim-2])+ (a[dim-3]-b[dim-3])*(a[dim-3]-b[dim-3]) + (a[dim-4]-b[dim-4])*(a[dim-4]-b[dim-4]) + (a[dim-5]-b[dim-5])*(a[dim-5]-b[dim-5]); break; case 7: dot += (a[dim]-b[dim])*(a[dim]-b[dim]) + (a[dim-1]-b[dim-1])*(a[dim-1]-b[dim-1]) + (a[dim-2]-b[dim-2])*(a[dim-2]-b[dim-2])+ (a[dim-3]-b[dim-3])*(a[dim-3]-b[dim-3]) + (a[dim-4]-b[dim-4])*(a[dim-4]-b[dim-4]) + (a[dim-5]-b[dim-5])*(a[dim-5]-b[dim-5]) + (a[dim-6]-b[dim-6])*(a[dim-6]-b[dim-6]); break; default: break; } return exp(-(double)dot / (2 * sigma * sigma)); } /* ---- Non-vectorized part of code ---- */ /* Linear kernal */ double dot_int(const int *a , const int *b , const long dim) { long i; int result = 0; for(i = 1; i<=dim; i++) result += a[i] * b[i]; return (double)result; } double dot_byte(const unsigned char *a , const unsigned char *b , const long dim) { long i; int result = 0; for(i = 1; i<=dim; i++) result += a[i] * b[i]; return (double)result; } /* Gaussian RBF kernel */ double rbf_int(const int *a, const int *b, const long dim, const double sigma) { long i; int result=0; for(i=1;i<=dim;i++) result -= (a[i] - b[i]) * (a[i] - b[i]); return exp((double)result/(2 * sigma * sigma)); } double rbf_byte(const unsigned char *a, const unsigned char *b, const long dim, const double sigma) { long i; unsigned int result=0; for(i=1;i<=dim;i++) result += (a[i] - b[i]) * (a[i] - b[i]); return exp(- (double)result/(2 * sigma * sigma)); } /* Homogeneous Polynomial kernel k(x,z) = (x^T z)^deg */ double polynomial_homo_double(const double *a , const double *b , const long dim, const int deg) { int i; double result = dot_double(a,b,dim); for(i = 1; i < deg; i++) result *= result; return result; } double polynomial_homo_float(const float *a , const float *b , const long dim, const int deg) { int i; // The dot product is computed with single precision floats double result = dot_float(a,b,dim); // But the power is computed with double precision for(i = 1; i < deg; i++) result *= result; return result; } double polynomial_homo_int(const int *a , const int *b , const long dim, const int deg) { int i; long result = 0; for(i = 1; i<=dim; i++) result += a[i] * b[i]; for(i = 1; i < deg; i++) result *= result; return (double)result; } double polynomial_homo_short_int(const short int *a , const short int *b , const long dim, const int deg) { int i; int result = 0; for(i = 1; i<=dim; i++) result += a[i] * b[i]; // could be vectorized in SSE2 for(i = 1; i < deg; i++) result *= result; return (double)result; } double polynomial_homo_byte(const unsigned char *a , const unsigned char *b , const long dim, const int deg) { int i; unsigned int result = 0; for(i = 1; i<=dim; i++) result += a[i] * b[i]; for(i = 1; i < deg; i++) result *= result; return (double)result; } /* Non-homogeneous Polynomial kernel k(x,z) = (x^T z + 1)^deg */ double polynomial_double(const double *a , const double *b , const long dim, const int deg) { int i; double result= 1.0 + dot_double(a,b,dim); for(i = 1; i < deg; i++) result *= result; return result; } double polynomial_float(const float *a , const float *b , const long dim, const int deg) { int i; // The dot product is computed with single precision floats double result = 1.0 + dot_float(a,b,dim); // But the power is computer with double precision for(i = 1; i < deg; i++) result *= result; return result; } double polynomial_int(const int *a , const int *b , const long dim, const int deg) { int i; long result = 1; for(i = 1; i<=dim; i++) result += a[i] * b[i]; for(i = 1; i < deg; i++) result *= result; return (double)result; } double polynomial_short_int(const short int *a , const short int *b , const long dim, const int deg) { int i; int result = 1; for(i = 1; i<=dim; i++) result += a[i] * b[i]; // could be vectorized in SSE2 for(i = 1; i < deg; i++) result *= result; return (double)result; } double polynomial_byte(const unsigned char *a , const unsigned char *b , const long dim, const int deg) { int i; int result = 1; for(i = 1; i<=dim; i++) result += a[i] * b[i]; for(i = 1; i < deg; i++) result *= result; return (double)result; } /* Linear kernel for BIT data k(x,z) = x^T z = sum (x[i] == z[i]) */ double dot_bit(const int *a, const int *b, const long dim) { long i=1; unsigned int res; int num_bits = 0; long true_dim = dim/32; if(dim%32 != 0) true_dim++; for(i=1;i<=true_dim ; i++) { res = a[i] & b[i]; num_bits += __builtin_popcount(res); // fast popcount on SSE4.2/SSE4a processors } return (double)num_bits; } /* Gaussian RBF kernel for BIT data with Hamming distance k(x,z) = exp(- (sum (x[i] != z[i]))^2 / 2 sigma^2 ) */ double rbf_bit(const int *a, const int *b, const long dim, const double sigma) { long i=1; unsigned int res; int dist = 0; long true_dim = dim/32; if(dim%32 != 0) true_dim++; for(i=1;i<=true_dim ; i++) { res = ~(a[i] & b[i]); dist += __builtin_popcount(res); } return exp( (double)( -dist * dist) / (2 * sigma * sigma)); } /* Homogeneous polynomial kernel for BIT data k(x,z) = (x^T z)^deg = (sum (x[i] == z[i]) )^deg */ double polynomial_homo_bit(const int *a, const int *b, const long dim, const int deg) { long i=1; unsigned int res; int num_bits = 0; long true_dim = dim/32; if(dim%32 != 0) true_dim++; for(i=1;i<=true_dim ; i++) { res = a[i] & b[i]; num_bits += __builtin_popcount(res); } for(i = 1; i < deg; i++) num_bits *= num_bits; return (double)num_bits; } /* Non-homogeneous polynomial kernel for BIT data */ double polynomial_bit(const int *a, const int *b, const long dim, const int deg) { long i=1; unsigned int res; int num_bits = 1; long true_dim = dim/32; if(dim%32 != 0) true_dim++; for(i=1;i<=true_dim ; i++) { res = a[i] & b[i]; num_bits += __builtin_popcount(res); } for(i = 1; i < deg; i++) num_bits *= num_bits; return (double)num_bits; } MSVMpack1.2/src/predMSVM.c0000644000175000017500000002016511706205165014321 0ustar lauerlauer/* Copyright 2010 Fabien Lauer */ /* 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 2 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, write to the Free Software */ /* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA*/ /*--------------------------------------------------------------------------*/ /* Name : predMSVM.c */ /* Version : 2.0 */ /* Creation : 04/27/10 */ /* Last update : 01/20/11 */ /* Subject : MSVMpack: a multi-class SVM package */ /* Algo. : Prediction command-line tool */ /* Author : Fabien Lauer fabien.lauer@loria.fr */ /*--------------------------------------------------------------------------*/ /* predMSVM.c -- Command line tool to classify a dataset with an M-SVM model previously trained by trainmsvm from MSVMpack */ #include #include #include #include #include "libMSVM.h" #include "libevalMSVM.h" int main(int argc, char *argv[]) { char data_file[taille], outputs_file[taille], model_file[taille]; int i,n_kernel_par,multipleC; long k; char *outputs = NULL; strcpy(model_file,"msvm.model"); int nprocs = get_nprocessors(); // Parse command line if(argc<2) { printf("MSVMpack prediction tool\n"); printf("-- Version: %1.1f \n\n", VERSION); printf("Usage: \n"); printf("\tpredmsvm data_file [MSVM.model] [pred.outputs] [-t N]\n\n"); printf("computes the output of an M-SVM on the given data_file\n"); printf("using N processors (default N = %d on this computer).\n\n",nprocs); printf(" Or:\n\tpredmsvm -i [MSVM.model] \n\n"); printf("prints model information.\n\n"); exit(0); } strcpy(data_file, argv[1]); // Data file must be the first argument // except for the -i option i = check_argv(argc,argv, ".model"); if(i) { strcpy(model_file,argv[i]); } i = check_argv(argc,argv, ".outputs"); if(i) { strcpy(outputs_file,argv[i]); outputs = outputs_file; } // Load model struct Model *model; model = MSVM_load_model(model_file); if (model == NULL) exit(1); // Check -i option and print model information if needed i = check_argv(argc,argv, "-i"); if(i) { printf("\n%s\t : ", model_file); switch(model->type) { case MSVM2 : printf("M-SVM^2 (MSVM2)\n"); break; case WW : printf("Weston and Watkins M-SVM (WW) \n"); break; case CS : printf("Crammer and Singer M-SVM (CS) \n"); break; case LLW : printf("Lee, Lin and Wahba M-SVM (LLW) \n"); break; default : printf("Unknown\n"); break; } printf(" version\t : MSVMpack %1.1f\n",model->version); printf(" training set\t : %s",model->training_set_name); if(model->normalization != NULL) printf("\t (data normalized)\n"); else printf("\n"); printf(" training error\t : %3.2lf %%\n",100 * model->training_error); enum Kernel_type kerneltype = model->nature_kernel; switch(model->datatype) { case DOUBLE: printf(" data format\t : double precision floating-point (64-bit)\n"); break; case FLOAT: printf(" data format\t : single precision floating-point (32-bit)\n"); kerneltype -= 10; break; case INT: printf(" data format\t : integer (32-bit)\n"); kerneltype -= 20; break; case SHORT: printf(" data format\t : short integer (16-bit)\n"); kerneltype -= 30; break; case BYTE: printf(" data format\t : byte (8-bit unsigned integer)\n"); kerneltype -= 40; break; case BIT: printf(" data format\t : 0-1 bit \n"); kerneltype -= 50; break; default: printf(" data format\t : unknown (%d)\n",model->datatype); } printf("\t Q\t : %ld\n",model->Q); n_kernel_par = 0; if(model->kernel_par != NULL ) n_kernel_par = (int)model->kernel_par[0]; switch(kerneltype) { case LINEAR: printf("\t kernel\t : linear\n"); break; case RBF: printf("\t kernel\t : Gaussian RBF (sigma = %lf)\n", model->kernel_par[1]); break; case POLY_H: printf("\t kernel\t : Homogeneous polynomial (degree = %d)\n", (int)model->kernel_par[1]); break; case POLY: printf("\t kernel\t : Non-homogeneous polynomial (degree = %d)\n", (int)model->kernel_par[1]); break; case CUSTOM1: if(n_kernel_par==0) printf("\t kernel\t : %s (no parameter)",CUSTOM_KERNEL_1_NAME); else if (n_kernel_par==1) printf("\t kernel\t : %s (parameter = %lf)\n", CUSTOM_KERNEL_1_NAME,model->kernel_par[1]); else if (model->kernel_par[0]<5) { printf("\t kernel\t : %s (parameters = %lf", CUSTOM_KERNEL_1_NAME,model->kernel_par[1]); for(i=2;i<=n_kernel_par;i++) printf(" %lf", model->kernel_par[i]); printf(")\n"); } else printf("\t kernel\t : %s (%d parameters)\n", CUSTOM_KERNEL_1_NAME,n_kernel_par); break; case CUSTOM2: if(n_kernel_par==0) printf("\t kernel\t : %s (no parameter)",CUSTOM_KERNEL_2_NAME); else if (n_kernel_par==1) printf("\t kernel\t : %s (parameter = %lf)\n", CUSTOM_KERNEL_2_NAME, model->kernel_par[1]); else if (model->kernel_par[0]<5) { printf("\t kernel\t : %s (parameters = %lf", CUSTOM_KERNEL_2_NAME, model->kernel_par[1]); for(i=2;i<=n_kernel_par;i++) printf(" %lf", model->kernel_par[i]); printf(")\n"); } else printf("\t kernel\t : %s (%d parameters)\n", CUSTOM_KERNEL_2_NAME,n_kernel_par); break; case CUSTOM3: if(n_kernel_par==0) printf("\t kernel\t : %s (no parameter)",CUSTOM_KERNEL_3_NAME); else if (n_kernel_par==1) printf("\t kernel\t : %s (parameter = %lf)\n", CUSTOM_KERNEL_3_NAME,model->kernel_par[1]); else if (model->kernel_par[0]<5) { printf("\t kernel\t : %s (parameters = %lf", CUSTOM_KERNEL_3_NAME,model->kernel_par[1]); for(i=2;i<=n_kernel_par;i++) printf(" %lf", model->kernel_par[i]); printf(")\n"); } else printf("\t kernel\t : %s (%d parameters)\n", CUSTOM_KERNEL_3_NAME,n_kernel_par); break; default: printf("\t kernel\t : unknown\n"); break; } multipleC = 0; for(k=2;k<=model->Q;k++) if(model->C[k] != model->C[1]) multipleC = 1; if(multipleC) { for(k=1;k<=model->Q;k++) { if(model->C[k] > 0.001) printf("\t C_%ld\t : %1.3lf\n",k,model->C[k]); else printf("\t C_%ld\t : %1.3e\n",k,model->C[k]); } } else { if(model->C[1] > 0.001) printf("\t C\t : %1.3lf\n",model->C[1]); else printf("\t C\t : %1.3e\n",model->C[1]); } printf("\t nSV\t : %ld\n",model->nb_data); exit(0); } // Load data struct Data *data_set; data_set = MSVM_make_dataset(data_file,model->datatype); if(data_set->dim != model->dim_input) { printf("Error: wrong data dimension (%ld) for model %s\n", data_set->dim, model_file); printf("\t (expected input dimension is %ld).\n",model->dim_input); exit(1); } // Set number of threads / CPUs i = check_argv(argc,argv, "-t"); if(i) { if(atoi(argv[i+1]) > nprocs) { printf("Unattended request of a number of working threads above the number of available processors (%d)\n",nprocs); } else nprocs = atoi(argv[i+1]); } // Predict MSVM_classify_set(NULL, data_set->X, data_set->y, data_set->nb_data, outputs, model, nprocs); // Free memory MSVM_delete_dataset(data_set); MSVM_delete_model_with_data(model); return 0; } MSVMpack1.2/include/0000755000175000017500000000000012104675717013357 5ustar lauerlauerMSVMpack1.2/include/libtrainMSVM_CS.h0000644000175000017500000000420611645563113016421 0ustar lauerlauer/* Training Crammer and Singer MSVM -- Header file */ #ifndef _LIBTRAINMSVMCS_H #define _LIBTRAINMSVMCS_H #include #include #include #include #include "algebra.h" #include "libMSVM.h" #include "libtrainMSVM.h" // For lp_solve API #include "lp_lib.h" // Crammer and Singer M-SVM training function long MSVM_CS_train(struct Model *model, struct Data *training_set, long chunk_size, const double accuracy, int cache_memory, const int nprocs, char *alpha0_file, char *alpha_file, char *log_file); // Main computing function void *CS_train_thread(void *th_data); /* Other functions included in libtrainMSVM_CS.c */ void CS_alloc_memory(struct TrainingCache *cache, const long Q, const long nb_data, const long chunk_size); void CS_free_memory(struct TrainingCache *cache); long CS_compute_table_chunk(struct TrainingCache *cache, const struct Model *model); void CS_init_gradient(const enum AlphaInitType alpha_init_type, double **gradient, double **H_alpha, const struct Model *model); void *CS_update_gradient_thread(void *th_data); void CS_update_gradient(double **gradient, double **H_alpha, struct TrainingCache *cache, const struct Model *model); void CS_compute_H_delta(double **delta, struct TrainingCache *cache, const struct Model *model); double CS_compute_theta_opt(double **delta, struct TrainingCache *cache, const struct Model *model); void CS_compute_delta(double **delta, const struct TrainingCache *cache, const struct Model *model); long CS_compute_new_alpha(const double theta_opt, const struct TrainingCache *cache, struct Model *model); int CS_check_opt_sol(double **gradient, struct TrainingCache *cache, const struct Model *model); int CS_solve_lp(double **gradient, const struct TrainingCache *cache, const struct Model *model); void CS_init_alpha(struct Model *model, char *alpha_file); double CS_workingset_selection(double **Fmatrix, struct TrainingCache *cache, const struct Model *model); int __inline__ CS_switch_thread(const int nprocs, int *numthreads_grad, int *next_numthreads_grad, long *percentage, int *percentage_step, struct ThreadGradient_data *grad_data, int thread_id, long nb_data); #endif MSVMpack1.2/include/libtrainMSVM_WW.h0000644000175000017500000000361611645057164016461 0ustar lauerlauer/* Training Weston and Watkins MSVM -- Header file */ #ifndef _LIBTRAINMSVMWW_H #define _LIBTRAINMSVMWW_H #include #include #include #include #include "algebra.h" #include "libMSVM.h" #include "libtrainMSVM.h" // For lp_solve API #include "lp_lib.h" // Weston and Watkins M-SVM training function long MSVM_WW_train(struct Model *model, struct Data *training_set, long chunk_size, const double accuracy, int cache_memory, const int nprocs, char *alpha0_file, char *alpha_file, char *log_file); // Main computing function void *WW_train_thread(void *th_data); /* Other functions included in libtrainMSVM_WW.c */ void WW_alloc_memory(struct TrainingCache *cache, const long Q, const long nb_data, const long chunk_size); void WW_free_memory(struct TrainingCache *cache); int WW_compute_gradient_chunk(double **gradient, struct TrainingCache *cache, const struct Model *model); void WW_compute_H_delta(double **delta, struct TrainingCache *cache, const struct Model *model); double WW_compute_theta_opt(double **delta, struct TrainingCache *cache, const struct Model *model); void WW_compute_delta(double **delta, const struct TrainingCache *cache, const struct Model *model); long WW_compute_new_alpha(const double theta_opt, const struct TrainingCache *cache, struct Model *model); int WW_check_opt_sol(double **gradient, struct TrainingCache *cache, const struct Model *model); int WW_solve_lp(double **gradient, const struct TrainingCache *cache, const struct Model *model); void WW_init_gradient(const enum AlphaInitType alpha_init_type, double **gradient, double **H_alpha, const struct Model *model); int WW_check_gradient_chunk(double **gradient, struct TrainingCache *cache, const struct Model *model); void *WW_update_gradient_thread(void *th_data); void WW_update_gradient(double **gradient, double **H_alpha, struct TrainingCache *cache, const struct Model *model); #endif MSVMpack1.2/include/libevalMSVM_WW.h0000644000175000017500000000266211644772455016301 0ustar lauerlauer/* LibevalMSVM_WW - Header file */ #ifndef _LIBEVALSVMWW_H #define _LIBEVALSVMWW_H #include #include #include #include #include #include "algebra.h" #include "biblio.h" #include "libMSVM.h" #include "libevalMSVM.h" // Main evaluation functions for the WW-MSVM double MSVM_WW_eval(double *best_primal_upper_bound, double **gradient, double **H_alpha, struct Model *model, const int verbose, FILE *fp); long WW_classify(void *vector, const struct Model *model, double *real_outputs); double WW_function(long category, void *vector, const struct Model *model); /* Other functions included in this program */ void WW_optimize_b(double **gradient, struct Cache *cache, struct Model *model); void WW_check_feasible_sol(const struct Model *model, char *alpha_file, int verbose); void WW_check_sup_vect(const struct Model *model); void WW_check_margin_vect(long **margin_vect, long **nb_margin_vect, const struct Model *model); double WW_eval_training(double **gradient, long **mat_conf, const struct Model *model); void WW_estimate_b(double **gradient, long **margin_vect, long **nb_margin_vect, const struct Cache *cache, struct Model *model); void WW_compute_obj_dual(struct Cache *cache, struct Model *model); void WW_compute_obj_primal(double R_emp, struct Cache *cache, const struct Model *model); void WW_compute_W(struct Model *model); void WW_compute_boundaries(const struct Model *model); #endif MSVMpack1.2/include/kernel.h0000644000175000017500000001423411644772455015021 0ustar lauerlauer/* Types of kernel functions */ #ifndef _KERNEL_FCT_H_ #define _KERNEL_FCT_H_ /* Default values for kernel parameters */ #define DEFAULT_RBF_KERNEL_PAR sqrt(5.0 * (model->dim_input)) #define DEFAULT_POLY_KERNEL_PAR 2 #define DEFAULT_CUSTOM_KERNEL_1_PAR 0 #define DEFAULT_CUSTOM_KERNEL_2_PAR 0 #define DEFAULT_CUSTOM_KERNEL_3_PAR 0 /* Names of custom kernel functions */ #define CUSTOM_KERNEL_1_NAME "custom 1" #define CUSTOM_KERNEL_2_NAME "custom 2" #define CUSTOM_KERNEL_3_NAME "custom 3" /* Kernel types */ enum Kernel_type { // kernel functions for DOUBLE datatype LINEAR=1, // linear RBF=2, // Gaussian RBF POLY_H=3, // Homogeneous polynomial POLY=4, // Non-homogeneous polynomial CUSTOM1=5, // Custom kernels CUSTOM2=6, CUSTOM3=7, // same for FLOAT datatype LINEAR_FLOAT=11, RBF_FLOAT=12, POLY_H_FLOAT=13, POLY_FLOAT=14, CUSTOM1_FLOAT=15, CUSTOM2_FLOAT=16, CUSTOM3_FLOAT=17, // kernels for INT datatype LINEAR_INT=21, RBF_INT=22, POLY_H_INT=23, POLY_INT=24, CUSTOM1_INT=25, CUSTOM2_INT=26, CUSTOM3_INT=27, // kernels for SHORT INT datatype LINEAR_SHORT=31, RBF_SHORT=32, POLY_H_SHORT=33, POLY_SHORT=34, CUSTOM1_SHORT=35, CUSTOM2_SHORT=36, CUSTOM3_SHORT=37, // kernels for BYTE datatype LINEAR_BYTE=41, RBF_BYTE=42, POLY_H_BYTE=43, POLY_BYTE=44, CUSTOM1_BYTE=45, CUSTOM2_BYTE=46, CUSTOM3_BYTE=47, // kernels for BIT datatype LINEAR_BIT=51, RBF_BIT=52, POLY_H_BIT=53, POLY_BIT=54, CUSTOM1_BIT=55, CUSTOM2_BIT=56, CUSTOM3_BIT=57, }; /* Kernel functions Suffix indicates the format of data the function takes as input */ double dot_double(const double *a, const double *b, const long dim); double dot_float(const float *a, const float *b, const long dim); double dot_int(const int *a , const int *b , const long dim); double dot_short_int(const short int *a, const short int *b, const long dim); double dot_byte(const unsigned char *a, const unsigned char *b, const long dim); double dot_bit(const int *a, const int *b, const long dim); double rbf_double(const double *a, const double *b, const long dim, const double sigma); double rbf_float(const float *a, const float *b, const long dim, const double sigma); double rbf_int(const int *a, const int *b, const long dim, const double sigma); double rbf_short_int(const short int *a, const short int *b, const long dim, const double sigma); double rbf_byte(const unsigned char *a, const unsigned char *b, const long dim, const double sigma); double rbf_bit(const int *a, const int *b, const long dim, const double sigma); double polynomial_homo_double(const double *a , const double *b , const long dim, const int deg); double polynomial_homo_float(const float *a , const float *b , const long dim, const int deg); double polynomial_homo_int(const int *a , const int *b , const long dim, const int deg); double polynomial_homo_short_int(const short int *a , const short int *b , const long dim, const int deg); double polynomial_homo_byte(const unsigned char *a , const unsigned char *b , const long dim, const int deg); double polynomial_homo_bit(const int *a, const int *b, const long dim, const int deg); double polynomial_double(const double *a , const double *b , const long dim, const int deg); double polynomial_float(const float *a , const float *b , const long dim, const int deg); double polynomial_int(const int *a , const int *b , const long dim, const int deg); double polynomial_short_int(const short int *a , const short int *b , const long dim, const int deg); double polynomial_byte(const unsigned char *a , const unsigned char *b , const long dim, const int deg); double polynomial_bit(const int *a, const int *b, const long dim, const int deg); double custom_kernel_1(const double *x1 , const double *x2 , const long dim, const double *kernel_par); double custom_kernel_2(const double *x1 , const double *x2 , const long dim, const double *kernel_par); double custom_kernel_3(const double *x1 , const double *x2 , const long dim, const double *kernel_par); double custom_kernel_1_float(const float *x1 , const float *x2 , const long dim, const double *kernel_par); double custom_kernel_2_float(const float *x1 , const float *x2 , const long dim, const double *kernel_par); double custom_kernel_3_float(const float *x1 , const float *x2 , const long dim, const double *kernel_par); double custom_kernel_1_int(const int *x1 , const int *x2 , const long dim, const double *kernel_par); double custom_kernel_2_int(const int *x1 , const int *x2 , const long dim, const double *kernel_par); double custom_kernel_3_int(const int *x1 , const int *x2 , const long dim, const double *kernel_par); double custom_kernel_1_short_int(const short int *x1 , const short int *x2 , const long dim, const double *kernel_par); double custom_kernel_2_short_int(const short int *x1 , const short int *x2 , const long dim, const double *kernel_par); double custom_kernel_3_short_int(const short int *x1 , const short int *x2 , const long dim, const double *kernel_par); double custom_kernel_1_byte(const unsigned char *x1 , const unsigned char *x2 , const long dim, const double *kernel_par); double custom_kernel_2_byte(const unsigned char *x1 , const unsigned char *x2 , const long dim, const double *kernel_par); double custom_kernel_3_byte(const unsigned char *x1 , const unsigned char *x2 , const long dim, const double *kernel_par); double custom_kernel_1_bit(const int *x1 , const int *x2 , const long dim, const double *kernel_par); double custom_kernel_2_bit(const int *x1 , const int *x2 , const long dim, const double *kernel_par); double custom_kernel_3_bit(const int *x1 , const int *x2 , const long dim, const double *kernel_par); // Custom kernel functions can be defined in custom_kernels.c #endif MSVMpack1.2/include/algebra.h0000644000175000017500000000364411651473571015134 0ustar lauerlauer/* Linear Algebra routines -- Header file */ #ifndef _ALGEBRA_H #define _ALGEBRA_H // Get SSE definitions #ifdef __SSE__ #include #endif // Number of elements to add to 16-byte align type a #define ALIGNMENT(a) (128/sizeof(a) - 1) // Allocate a 16-byte aligned block of b elements of type a #define MALLOC(a,b) ((a *)_mm_malloc((b + ALIGNMENT(a)) * sizeof(a),16)) #define FREE(a) _mm_free(a) double **matrix_aligned(long nrow, long ncol); float **matrix_f_aligned(long nrow, long ncol); int **matrix_i_aligned(long nrow, long ncol); short int **matrix_s_aligned(long nrow, long ncol); unsigned char **matrix_b_aligned(long nrow, long ncol); void free_mat_aligned(double **m); void free_mat_f_aligned(float **m); void free_mat_i_aligned(int **m); void free_mat_s_aligned(short int **m); void free_mat_b_aligned(unsigned char **m); double **matrix(long nrow, long ncol); int **matrix_i(long nrow, long ncol); float **matrix_f(long nrow, long ncol); long **matrix_l(long nrow, long ncol); extern double prod_scal(const double *vect1, const double *vect2, const long dim); void trans_mat(double **mat1, double **mat2, long dim1, long dim2); void trans_mat_float(float **mat1, float **mat2, long dim1, long dim2); void trans_mat_int(int **mat1, int **mat2, long dim1, long dim2); void add_mat(double **mat1, double **mat2, double **mat3, long dim1, long dim2); void scal_mat(double coeff, double **mat1, double **mat2, long dim1, long dim2); void mult_mat(double **mat1, double **mat2, double **mat3, long dim1, long dim2, long dim3); void display_mat_l(long **mat, long dim1, long dim2, int par1); void display_mat(double **mat, long dim1, long dim2, int par1, int par2); void copy(double **mat1, double **mat2, long dim1, long dim2); extern int compare(double **mat1, double **mat2, long dim1, long dim2, double seuil); void diagonalize(double **mat, long dim, double *diagonal); #endif /* _ALGEBRA_H */ MSVMpack1.2/include/libtrainMSVM.h0000644000175000017500000001150311761356323016034 0ustar lauerlauer/* LibtrainMSVM - Generic header file for training an MSVM */ #ifndef _LIBTRAINMSVM_H #define _LIBTRAINMSVM_H #include #include #include #include #include #include "algebra.h" #include "libMSVM.h" #define MSVM_TRAIN_MAXIT 1000000000L // maximum numer of iterations #define TRAIN_STEP 1000 // print status every TRAIN_STEP iterations #define TRAIN_SMALL_STEP 100 #define MBYTES 1048576 // how many bytes in 1 MB #define MONITOR_PERIOD 60*20 // save model.tmp every MONITOR_PERIOD seconds /* Cache structures */ // Structure for kernel cache struct KernelCache { double *K; // Flat 1-dim array containing all the kernel cache data double **rows_ptr; // Array of pointers to rows inside K long *rows_idx; // Table of conversion of indexes from general kernel matrix to cached matrix long *rows_idx_inv; // Inverse table int *in_use; // Keep track of how many threads are using a row of K long nrows; // Number of kernel rows in cache long max_idx; int is_full; }; // Main training thread cache struct TrainingCache { // For all M-SVMs struct KernelCache *kc; long chunk_size; long *in_chunk; long *out_of_chunk; long *table_chunk; long *table_active; double **K; double **H_alpha; double **alpha_update; int *activeset; // For Frank-Wolfe algorithm double **H_delta; double **lp_sol; double gradient_diff; double *lp_rhs; // For Rosen's algorithm (M-SVM^2) long nb_variables; long nb_constraints; long nb_sat; double initial_norm_y_bar; double gradientT_y_bar; double **A0; double **A0T; double **A0A0T; double **A0A0T_1; double **A0A0T_ref; double **working_matrix1; double **working_matrix2; double **matrix_y_bar; double **vector_z_bar; double **H_y_bar; double *eigenvalues; double *constraints; // For CS chunk selection double *psi; }; #include "libevalMSVM.h" static unsigned short xi[3]; // seed for the random number generator used in select_random_chunk int EVAL; // triggered by the signal 'SIGINT' handler // to call for the evaluation of the machine // Global variables for synchronization of threads: static int STOP; // triggered by user to stop training static long iter; // number of iterations (over all threads) static pthread_mutex_t model_mutex = PTHREAD_MUTEX_INITIALIZER; static pthread_mutex_t thread_data_mutex = PTHREAD_MUTEX_INITIALIZER; static pthread_mutex_t kernelcache_inuse_mutex = PTHREAD_MUTEX_INITIALIZER; static pthread_mutex_t *kernelcache_rowptr_mutex; static pthread_cond_t *kernelcache_rowptr_cond; static pthread_mutex_t grad_data_mutex = PTHREAD_MUTEX_INITIALIZER; // data structures for thread arguments struct ThreadData { // Main thread for parallel kernel computations int thread_id; int nprocs; struct Model *model; struct KernelCache *kernelcache; long chunk_size; double accuracy; double **gradient; double **H_alpha; double **H_tilde_alpha; double *best_primal_upper_bound; int *activeset; long *nb_SV; double *lp_rhs; char *alpha_file; FILE *logfile_ptr; }; struct ThreadGradient_data { // Thread for gradient updates double **gradient; double **H_alpha; double **H_tilde_alpha; struct TrainingCache *cache; struct Model *model; long start_i; long end_i; }; struct MonitorData { // Monitor data char *model_tmp_file; int period; struct Model * model; }; // Main functions long MSVM_train(struct Model *model, struct Data *training_set, long chunk_size, const double accuracy, int cache_memory, int nprocs, char *alpha0_file, char *alpha_file, char *log_file); long MSVM_init_train_comfile(struct Model *model, char *com_file, char *training_file, char *alpha0_file, char *alpha_file, char *log_file); void init_alpha_b(struct Model *model, char *alpha_file); /* Other functions included in libtrainMSVM.c */ void compute_K(struct TrainingCache *cache, const struct Model *model); void release_K(struct TrainingCache *cache); void kernel_initialize_cache(unsigned long cache_size, struct KernelCache *kc, const struct Model *model); void kernel_free_cache(struct KernelCache *kc); double *kernel_get_row(long index, struct KernelCache *kc, const struct Model *model); void compute_kernel_row(const long index, const long cache_index, struct KernelCache *kc, const struct Model *model); int __inline__ switch_thread(const int nprocs, int *numthreads_grad, int *next_numthreads_grad, long *percentage, int *percentage_step, struct ThreadGradient_data *grad_data, int thread_id, long nb_data); void select_random_chunk(struct TrainingCache *cache, const struct Model *model); void *MSVM_monitor_model_thread(void *monitor_data); void write_vector(double **vector, const long nb_data, const long Q, char *fichier); void print_training_info(const long iter, const long nb_SV, const double ratio, const enum MSVM_type type); // Other definitions enum AlphaInitType {ALPHA_IS_ZERO=0, ALPHA_NOT_ZERO=1}; #endif MSVMpack1.2/include/libevalMSVM_LLW.h0000644000175000017500000000252211644772455016375 0ustar lauerlauer/* LibevalMSVM_LLW - Header file */ #ifndef _LIBEVALSVMLLW_H #define _LIBEVALSVMLLW_H #include #include #include #include #include #include "algebra.h" #include "biblio.h" #include "libMSVM.h" #include "libevalMSVM.h" // Main evaluation functions for the LLW-MSVM double MSVM_LLW_eval(double *best_primal_upper_bound, double **gradient, double **H_alpha, struct Model *model, const int verbose, FILE *fp); long LLW_classify(void *vector, const struct Model *model, double *real_outputs); double LLW_function(long category, void *vector, const struct Model *model); /* Other functions included in this program */ void LLW_check_feasible_sol(const struct Model *model, char *alpha_file, int verbose); void LLW_compute_gradient(double **gradient, struct Cache *cache, const struct Model *model); void LLW_check_margin_vect(long **margin_vect, long *nb_margin_vect, const struct Model *model); double LLW_eval_training(double **gradient, long **mat_conf, const struct Cache *cache, const struct Model *model); void LLW_estimate_b(double **gradient, long **margin_vect, long *nb_margin_vect, const struct Cache *cache, struct Model *model); void LLW_compute_obj_dual(struct Cache *cache, struct Model *model); void LLW_compute_obj_primal(double R_emp, struct Cache *cache, const struct Model *model); #endif MSVMpack1.2/include/libevalMSVM_2.h0000644000175000017500000000347311644772455016106 0ustar lauerlauer/* LibevalMSVM_2 - Header file */ #ifndef _LIBEVALMSVM2_H #define _LIBEVALMSVM2_H #include #include #include #include #include #include "algebra.h" #include "biblio.h" #include "libMSVM.h" #include "libevalMSVM.h" // Evaluation functions for the MSVM2 double MSVM_2_eval(double *best_primal_upper_bound, double **gradient, double **H_alpha, double **H_tilde_alpha, struct Model *model, const int verbose, FILE *fp); long MSVM_2_classify(void *vector, const struct Model *model, double *real_outputs); double MSVM_2_function(long category, void *vector, const struct Model *model); /* Other functions included in this program */ int MSVM_2_check_feasible_sol(const struct Model *model, char *alpha_file); void MSVM_2_compute_gradient(double **gradient, struct Cache *cache, const struct Model *model); void MSVM_2_compute_xi_opt(double **xi_opt, struct Cache *cache, const struct Model *model); void MSVM_2_check_xi_opt(double **xi_opt, double **gradient, const struct Cache *cache, const struct Model *model); void MSVM_2_correct_xi_opt(double **xi_opt, struct Cache *cache, const struct Model *model, const int MaxIter); void MSVM_2_optimize_b(double **xi_opt, struct Cache *cache, struct Model *model); double MSVM_2_compute_primal_obj(double **xi_opt, const struct Cache *cache, const struct Model *model); void MSVM_2_minimal_xi(const int keepok,double **xi_opt, const struct Cache *cache, const struct Model *model); void MSVM_2_estimate_b(double **gradient, const struct Cache *cache, struct Model *model); void MSVM_2_compute_obj_dual(struct Cache *cache, const struct Model *model); void MSVM_2_compute_obj_primal(struct Cache *cache, double **xi_opt, const struct Model *model); long MSVM_2_eval_training(long **mat_conf, const struct Cache *cache, const struct Model *model); #endif MSVMpack1.2/include/libevalMSVM.h0000644000175000017500000000271411645054172015650 0ustar lauerlauer/* LibevalMSVM - Header file */ #ifndef _LIBEVALMSVM_H #define _LIBEVALMSVM_H #include #include #include #include #include #include "algebra.h" #include "biblio.h" #include "libMSVM.h" #include "libtrainMSVM.h" #define step 100 #define SET_SIZE 2000 /* Cache Structure for evaluation purposes */ struct Cache { double **H_alpha; double **H_tilde_alpha; double alpha_H_alpha; double alpha_H_tilde_alpha; double sum_all_xi_opt; double primal; double primal_cheap; double dual; int verbose; }; // For thread synchronization static pthread_mutex_t thread_classify_data_mutex = PTHREAD_MUTEX_INITIALIZER; // data structures for threads struct ThreadClassifyData { int thread_id; struct Model *model; void **X; long *labels; long nb_data; long **mat_conf; long *y; double **outputs; }; // Main functions double MSVM_eval(double *best_primal_upper_bound, double **gradient, double **H_alpha, double **H_tilde_alpha, struct Model *model, const int verbose, FILE *fp); long MSVM_classify(void *x, const struct Model *model, double *real_outputs); void MSVM_classify_set(long *labels, void **X, long *y, long nb_data, char *outputs_file, struct Model *model, int nprocs); // Other functions included void standardize_b(double *b_SVM, const long Q); void *MSVM_classify_set_thread(void *th_data); void MSVM_print_outputs(double **outputs, long *labels, long *y, long nb_data, long Q, char *outputs_file); #endif MSVMpack1.2/include/libtrainMSVM_2.h0000644000175000017500000000547111645746161016270 0ustar lauerlauer/* Training an MSVM^2 -- Header file */ #ifndef _LIBTRAINMSVM2_H #define _LIBTRAINMSVM2_H #include #include #include #include #include "algebra.h" #include "libMSVM.h" #include "libtrainMSVM.h" // MSVM2 training function long MSVM_2_train(struct Model *model, struct Data *training_set, long chunk_size, const double accuracy, int cache_memory, const int nprocs, char *alpha0_file, char *alpha_file, char *log_file); // Main computing thread void *MSVM_2_train_thread(void *th_data); /* Other functions included in libtrainMSVM_2.c */ void MSVM_2_alloc_memory(struct TrainingCache *cache, const long Q, const long nb_data, const long chunk_size); void MSVM_2_free_memory(struct TrainingCache *cache); void MSVM_2_init_gradient(const enum AlphaInitType alpha_init_type, double **gradient, double **H_alpha, double **H_tilde_alpha, const struct Model *model); void MSVM_2_update_gradient(double **gradient, double **H_alpha, double **H_tilde_alpha, struct TrainingCache *cache, const struct Model *model); void *MSVM2_update_gradient_thread(void *th_data); void MSVM_2_compute_gradient_chunk(double **vector_gradient, double **gradient, struct TrainingCache *cache, const struct Model *model); void MSVM_2_compute_A0(struct TrainingCache *cache, const struct Model *model); void MSVM_2_compute_vector_u(double **vector_u, double **vector_gradient, struct TrainingCache *cache, const struct Model *model); int MSVM_2_check_vector_u(double **vector_u, double **vector_gradient, struct TrainingCache *cache, const struct Model *model); void MSVM_2_compute_vector_y_bar(double **vector_y_bar, double **vector_u, double **vector_gradient, struct TrainingCache *cache, const struct Model *model); int MSVM_2_check_vector_y_bar(double **vector_y_bar, double **vector_u, double **vector_gradient, struct TrainingCache *cache, const struct Model *model); void MSVM_2_simplify_A0(double **vector_u, struct TrainingCache *cache, const struct Model *model); double MSVM_2_compute_theta_max(const struct TrainingCache *cache, const struct Model *model); void MSVM_2_compute_H_y_bar(struct TrainingCache *cache, const struct Model *model); double MSVM_2_compute_theta_opt(const double theta_max, struct TrainingCache *cache, const struct Model *model); long MSVM_2_compute_new_alpha(const double theta_opt, const struct TrainingCache *cache, struct Model *model); int MSVM_2_check_feasible_sol_train(struct Model *model, struct TrainingCache *cache); int MSVM_2_check_feasible_sol_init(struct Model *model); void MSVM_2_study_unfeasible_sol(const int descent, double **vector_u, double **vector_y_bar, const struct TrainingCache *cache, const struct Model *model); double MSVM_2_compute_objective_function(const struct Model *model, double former_val_obj_function); void MSVM_2_compute_pseudo_inverse(struct TrainingCache *cache); #endif MSVMpack1.2/include/libtrainMSVM_LLW.h0000644000175000017500000000344111645561054016554 0ustar lauerlauer/* Training Lee, Lin and Wahba MSVM -- Header file */ #ifndef _LIBTRAINMSVMLLW_H #define _LIBTRAINMSVMLLW_H #include #include #include #include #include "algebra.h" #include "libMSVM.h" #include "libtrainMSVM.h" // For lp_solve API #include "lp_lib.h" // Lee, Lin and Wahba M-SVM training function long MSVM_LLW_train(struct Model *model, struct Data *training_set, long chunk_size, const double accuracy, int cache_memory, const int nprocs, char *alpha0_file, char *alpha_file, char *log_file); // Main computing function void *LLW_train_thread(void *th_data); /* Other functions included in libtrainMSVM_LLW.c */ void LLW_alloc_memory(struct TrainingCache *cache, const long Q, const long nb_data, const long chunk_size); void LLW_free_memory(struct TrainingCache *cache); long LLW_compute_table_chunk(struct TrainingCache *cache, const struct Model *model); void LLW_compute_H_delta(double **delta, struct TrainingCache *cache, const struct Model *model); double LLW_compute_theta_opt(double **delta, struct TrainingCache *cache, const struct Model *model); void LLW_compute_delta(double **delta, const struct TrainingCache *cache, const struct Model *model); long LLW_compute_new_alpha(const double theta_opt, const struct TrainingCache *cache, struct Model *model); int LLW_check_opt_sol(double **gradient, struct TrainingCache *cache, const struct Model *model); int LLW_solve_lp(double **gradient, const struct TrainingCache *cache, const struct Model *model); void LLW_init_gradient(const enum AlphaInitType alpha_init_type, double **gradient, double **H_alpha, const struct Model *model); void LLW_update_gradient(double **gradient, double **H_alpha, struct TrainingCache *cache, const struct Model *model); void *LLW_update_gradient_thread(void *th_data); #endif MSVMpack1.2/include/libtrainMSVM_2fw.h0000644000175000017500000000347111645746546016632 0ustar lauerlauer/* Training M-SVM^2 with Franke-Wolfe algorithm -- Header file */ #ifndef _LIBTRAINMSVM_2fw_H #define _LIBTRAINMSVM_2fw_H #include #include #include #include #include "algebra.h" #include "libMSVM.h" #include "libtrainMSVM.h" // For lp_solve API #include "lp_lib.h" // Lee, Lin and Wahba M-SVM training function long MSVM_2fw_train(struct Model *model, struct Data *training_set, long chunk_size, const double accuracy, int cache_memory, const int nprocs, char *alpha0_file, char *alpha_file, char *log_file); // Main computing function void *MSVM2fw_train_thread(void *th_data); /* Other functions included in libtrainMSVM_LLW.c */ void MSVM2fw_alloc_memory(struct TrainingCache *cache, const long Q, const long nb_data, const long chunk_size); void MSVM2fw_free_memory(struct TrainingCache *cache); void MSVM2fw_compute_H_delta(double **delta, struct TrainingCache *cache, const struct Model *model); double MSVM2fw_compute_theta_opt(double **delta, struct TrainingCache *cache, const struct Model *model); void MSVM2fw_compute_delta(double **delta, const struct TrainingCache *cache, const struct Model *model); long MSVM2fw_compute_new_alpha(const double theta_opt, const struct TrainingCache *cache, struct Model *model); int MSVM2fw_check_opt_sol(double **gradient, struct TrainingCache *cache, const struct Model *model); int MSVM2fw_solve_lp(double **gradient, const struct TrainingCache *cache, const struct Model *model); void MSVM2fw_init_gradient(const enum AlphaInitType alpha_init_type, double **gradient, double **H_alpha, double **H_tilde_alpha, const struct Model *model); void MSVM2fw_update_gradient(double **gradient, double **H_alpha, double **H_tilde_alpha, struct TrainingCache *cache, const struct Model *model); void *MSVM2fw_update_gradient_thread(void *th_data); #endif MSVMpack1.2/include/libMSVM.h0000644000175000017500000000750411761336713015005 0ustar lauerlauer/* LibMSVM.h: general Header file including common object definitions for MSVMpack */ #ifndef _LIBMSVM_H #define _LIBMSVM_H #include #include #include #include #include #ifndef _SC_NPROCESSORS_ONLN #include // for BSD #endif #include "algebra.h" #include "kernel.h" // Useful macros #define true 1 #define false 0 #define taille 500 #define small 1e-4 #define very_small 1e-6 #define small_enough 1e-8 #define tiny 1e-12 #define minimum(a,b) ((a)<=(b)?(a):(b)) #define maximum(a,b) ((a)>=(b)?(a):(b)) // Default parameters #define DEFAULT_C 10.0; /* Type (and precision) of data */ enum Datatype {DOUBLE=1, FLOAT=2, INT=3, SHORT=4, BYTE=5, BIT=6}; /* Model structure */ struct Model { float version; // MSVMpack model version enum MSVM_type {WW=0,CS=1, LLW=2,MSVM2=3} type; // Type of the M-SVM enum Algorithm {FrankWolfe=0, Rosen=1} algorithm; // Optimization method long Q; // number of classes char *training_set_name; // name of training set long nb_data; // number of SVs long dim_input; // dimension of x enum Datatype datatype; // type of data enum Kernel_type nature_kernel; // type of kernel double *kernel_par; // kernel function parameter double *C; // soft-margin parameters double training_error; // training error rate double **alpha; // (nb_data x Q) matrix of alpha double *partial_average_alpha; double sum_all_alpha; double *b_SVM; // vector b void **X; // support vectors long *y; // labels of the SVs double **normalization; // (mean,std) used to normalize data (or NULL) double **W; // Weights of the linear model // Format-specific data storage double **X_double; float **X_float; int **X_int; short int **X_short; unsigned char **X_byte; }; /* Generic Data structure for a dataset */ struct Data { char *name; long nb_data; long dim; void **X; long *y; long Q; // number of classes in dataset double **X_double; float **X_float; int **X_int; short int **X_short; unsigned char **X_byte; enum Datatype datatype; }; /* Model and Data handling functions */ struct Model *MSVM_make_model(enum MSVM_type type); void MSVM_delete_model(struct Model *model); void MSVM_delete_model_with_data(struct Model *model); long MSVM_init_model(struct Model *model, char *fichcom_file); int MSVM_save_model(const struct Model *model, char *model_file); int MSVM_save_model_sparse(const struct Model *model, char *model_file); struct Model *MSVM_load_model(char *model_file); void MSVM_model_set_C(double C, long Q, struct Model *model); struct Data *MSVM_make_dataset(char *data_file, enum Datatype datatype); void MSVM_delete_dataset(struct Data *dataset); double MSVM_normalize_data(struct Data *dataset, struct Model *model); /* General wrapper for kernel functions */ double ker(const enum Kernel_type type, const void *x1, const void *x2, const long dim, const double *par); void set_default_kernel_par(struct Model *model); /* File I/O functions */ long read_data(struct Data *dataset, enum Datatype datatype, char *data_file); double read_alpha(struct Model *model, char *alpha_file); /* Others */ void model_load_data(struct Model *model, const struct Data *training_set); double normalize_data(struct Model *model, const int check_only); double model_get_Xij(struct Model *model, const long i, const long j); void Pause(char *message); int check_argv(int argc, char *argv[], char *str); int check_argv_eq(int argc, char *argv[], char *str); enum MSVM_type str2model_type(char *str); void remove_spaces(char *string, char *str_nospaces, const int maxchar); #endif MSVMpack1.2/include/biblio.h0000644000175000017500000000015111644772455014772 0ustar lauerlauervoid display_stats(long classes, long **matrice); void display_full_stats(long classes, long **matrice); MSVMpack1.2/include/libevalMSVM_CS.h0000644000175000017500000000206511644772455016246 0ustar lauerlauer/* LibevalMSVM_CS - Header file */ #ifndef _LIBEVALSVMCS_H #define _LIBEVALSVMCS_H #include #include #include #include #include #include "algebra.h" #include "biblio.h" #include "libMSVM.h" #include "libevalMSVM.h" // Main evaluation functions for the CS-MSVM double MSVM_CS_eval(double *best_primal_upper_bound, double **H_alpha, struct Model *model, const int verbose, FILE *fp); long CS_classify(void *vector, const struct Model *model, double *real_outputs); double CS_function(long category, void *vector, const struct Model *model); /* Other functions included in this program */ void CS_check_feasible_sol(const struct Model *model, char *alpha_file, int verbose); void CS_compute_gradient(double **gradient, struct Cache *cache, const struct Model *model); double CS_eval_training(double **gradient, long **mat_conf, const struct Model *model); void CS_compute_obj_dual(struct Cache *cache, struct Model *model); void CS_compute_obj_primal(double R_emp, struct Cache *cache, const struct Model *model); #endif MSVMpack1.2/Alpha/0000755000175000017500000000000011706231676012760 5ustar lauerlauerMSVMpack1.2/Alpha/bio.alpha.init0000644000175000017500000034100011644772171015501 0ustar lauerlauer0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 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28.3403838616 0.0000000000 0.0000000000 14.6453667270 0.0000000000 24.7752989645 33.6380221325 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 15.5428002950 0.0000000000 27.5530217134 28.7903696754 0.0000000000 27.2351961166 29.8589529552 0.0000000000 25.1806946680 23.6012855434 0.0000000000 26.6844158063 21.7932341291 0.0000000000 28.9006287579 29.4701188316 0.0000000000 27.5516087786 28.7724964307 0.0000000000 33.1720126938 29.9772255089 0.0000000000 0.0000000000 16.8625325654 0.0000000000 0.0000000000 16.6148450350 0.0000000000 0.0000000000 13.6040589116 0.0000000000 13.9540133846 0.0000000000 0.0000000000 26.8531030628 31.9340528297 0.0000000000 31.2207445266 28.8742640967 0.0000000000 28.8741865115 29.7338591979 0.0000000000 14.9378080714 0.0000000000 0.0000000000 0.0000000000 14.7427353467 0.0000000000 0.0000000000 14.9013399707 0.0000000000 13.4172477547 0.0000000000 0.0000000000 24.0644574041 32.2700707487 0.0000000000 0.0000000000 14.4523011533 0.0000000000 27.1115349319 30.8420051870 0.0000000000 0.0000000000 15.7986859533 0.0000000000 27.4780454944 29.3969143849 0.0000000000 13.2708184939 0.0000000000 0.0000000000 33.5792931569 30.8633736472 0.0000000000 0.0000000000 17.8352985942 0.0000000000 29.2293393079 29.0066729545 0.0000000000 0.0000000000 23.0449513394 0.0000000000 12.1183928467 0.0000000000 0.0000000000 17.7678889360 0.0000000000 0.0000000000 29.7628684369 32.9136433494 0.0000000000 0.0000000000 15.7437583141 0.0000000000 0.0000000000 16.5708036245 0.0000000000 29.8942285135 29.9998355398 0.0000000000 29.8571847557 29.5623410789 0.0000000000 36.3206218359 34.5009935996 0.0000000000 31.1239005377 29.9090158932 0.0000000000 0.0000000000 14.5780045193 0.0000000000 0.0000000000 16.8356414996 0.0000000000 0.0000000000 14.5483741527 0.0000000000 15.8127466014 0.0000000000 0.0000000000 29.9999635999 30.7769336959 0.0000000000 0.0000000000 14.4177604275 0.0000000000 MSVMpack1.2/README0000644000175000017500000000326111706011107012576 0ustar lauerlauerThis is MSVMpack: a Multi-class Support Vector Machine package To build the library and command-line tools, run: make For a system-wide install of the tools, run (with root privileges): make install To train an M-SVM, use: trainmsvm mydata myMSVM.model To classify data, use: predmsvm mydata myMSVM.model To start the web server, use: msvmserver start See the documentation in doc/ for further options or just run trainmsvm Contents of the directory MSVMpack/ doc/ --> Documentation and example program using the API include/ --> Header files lib/ --> Static libraries src/ --> C source files lp_solve_5.5/ --> lp_solve source files (*) mongoose/ --> mongoose source files (*) Comfiles/ --> Some example .com files Data/ --> Some example data files Alpha/ --> Example initialization files Save_alpha/ --> Saved alpha for examples tools/ --> Scripts for plotting the .log files webpages/ --> MSVMpack Server pages gpl.txt --> Licence Makefile --> Rules for building MSVMpack After building the library: trainmsvm --> command-line tool for training an M-SVM predmsvm --> command-line tool for making predictions msvmserver --> command-line tool for controling the web server Homepage: http://www.loria.fr/~lauer/MSVMpack/ Reference: F. Lauer and Y. Guermeur, MSVMpack: a Multi-class Support Vector Machine Package, Journal of Machine Learning Research, 12:2269-2272, 2011. (*) MSVMpack includes lp_solve and mongoose as third-party tools without any modification. Note that, lp_solve is distributed under the LGPL and mongoose is distrubted under the MIT Licence. Further information can be found in their respective directories. MSVMpack1.2/webpages/0000775000175000017500000000000012104705371013521 5ustar lauerlauerMSVMpack1.2/webpages/Data/0000755000175000017500000000000012104705371014370 5ustar lauerlauerMSVMpack1.2/webpages/admin/0000755000175000017500000000000012104711130014575 5ustar lauerlauerMSVMpack1.2/webpages/admin/settings.cgi0000755000175000017500000000203211705776017017146 0ustar lauerlauer#!/bin/bash echo "Content-Type: text/html;charset=UTF-8" echo PATHDATA=`echo "$QUERY_STRING" | sed -n 's/^.*pathdata=\([^&]*\).*$/\1/p' | sed "s/%20/ /g" | sed "s/%2F/\//g"` PATHMODELS=`echo "$QUERY_STRING" | sed -n 's/^.*pathmodels=\([^&]*\).*$/\1/p' | sed "s/%20/ /g" | sed "s/%2F/\//g"` CACHEMEM=`echo "$QUERY_STRING" | sed -n 's/^.*cachemem=\([^&]*\).*$/\1/p' | sed "s/%20/ /g"` NPROCS=`echo "$QUERY_STRING" | sed -n 's/^.*nprocs=\([^&]*\).*$/\1/p' | sed "s/%20/ /g"` echo echo "" echo "" echo "" echo "MSVMpack" echo "" echo "" echo "

MSVMpack Server

" echo $PATHDATA > server.conf echo $PATHMODELS >> server.conf echo $CACHEMEM >> server.conf echo $NPROCS >> server.conf echo "Settings saved." echo "You can now go to MSVMpack server homepage" echo "or back to admin page" echo "
" echo "" MSVMpack1.2/webpages/admin/models.cgi0000755000175000017500000000140711662763505016576 0ustar lauerlauer#!/bin/bash echo "Content-Type: text/html;charset=UTF-8" echo ACTION=`echo "$QUERY_STRING" | sed -n 's/^.*action=\([^&]*\).*$/\1/p' | sed "s/%20/ /g"` FILE0=`echo "$QUERY_STRING" | sed -n 's/^.*modelfile0_\([^&=]*\).*$/\1/p' | sed "s/%20/ /g"` FILE1=`echo "$QUERY_STRING" | sed -n 's/^.*modelfile1_\([^&=]*\).*$/\1/p' | sed "s/%20/ /g"` echo echo "" echo "" # echo "" echo "" echo "MSVMpack" echo "" echo "" echo "

MSVMpack Server

" echo "$ACTION files $FILE0 $FILE1" echo "Back to admin page" echo "
" echo "" MSVMpack1.2/webpages/admin/styleadmin.css0000644000175000017500000000162511706007724017502 0ustar lauerlauerbody { width: 710px; margin-left: 100px; background-color: #FFFFFF; font-family: verdana,trebuchet,arial,sans-serif; font-size: 80%; } td { padding: 0px; padding-right: 10px; text-align: left; } h1 { color: #D00000; /* D0D0D0 */ font-weight: normal; letter-spacing: .3em; padding-left: .3em; border-bottom-style: solid; border-bottom-width: 5pt; border-bottom-color: #B00000;/* #F0F0F0; */ border-top-style: solid; border-top-width: 1pt; border-top-color: #B00000; } h2 { color: #FFFFFF; /* 000000 */ background-color: #B00000; padding-top: 3pt; padding-bottom: 3pt; padding-left: 1em; font-weight: bold; font-size: 110%; } a:link { color: #900000; text-decoration: underline; } a:visited { color: #900000; text-decoration: underline; } a:hover { /* color: #0000B0;*/ background-color: #D0D0D0; text-decoration: underline; } #footer { font-size: 80%; font-style: italic; } MSVMpack1.2/webpages/admin/passwd.cgi0000755000175000017500000000117311662762375016620 0ustar lauerlauer#!/bin/bash echo "Content-Type: text/html;charset=UTF-8" echo PASSWD=`echo "$QUERY_STRING" | sed -n 's/^.*passwd=\([^&]*\).*$/\1/p' | sed "s/%20/ /g"` echo echo "" echo "" # echo "" echo "" echo "MSVMpack" echo "" echo "" echo "

MSVMpack Server

" mongoose -A .htpasswd "mydomain.com" "admin" "$PASSWD" echo "Password changed." echo "Back to admin page" echo "
" echo "" MSVMpack1.2/webpages/admin/.htpasswd0000664000175000017500000000006412104711130016435 0ustar lauerlaueradmin:mydomain.com:e9577134315f974d33c488f0ef93cb6d MSVMpack1.2/webpages/index.html0000664000175000017500000000017011701632675015524 0ustar lauerlauer MSVMpack Server MSVMpack1.2/webpages/home.js0000644000175000017500000000366311705565523015026 0ustar lauerlauervar dimension = 0; function chooseKernel() { var kernel = document.getElementById("kernel"); var kernelpar = document.getElementById("kernelpar"); if(kernel.value == "1") { kernelpar.disabled=true; } else { kernelpar.disabled=false; } // set default kernelpar value switch (kernel.value) { case "2": // for Gaussian kernel if(dimension > 0) kernelpar.value = Math.round(1000 * Math.sqrt(5 * dimension)) / 1000; break; case "3": case "4": kernelpar.value = "3"; // for polynomial kernel break; case "5": case "6": case "7": kernelpar.value = "1.0"; // for custom kernels break; default: break; } } function printInfo() { var model = document.getElementById("modeltest"); if(model.value != "") { //window.open("home.cgi?modeltest=" + model.value + "#test"); window.location.href="home.cgi?modeltest=" + model.value + "#test"; } } function printDataInfo() { var data = document.getElementById("trainfile"); if(data.value != "") { window.location.href="home.cgi?trainfile=" + data.value; // + "#train"; } } function UploadMSVMpack() { var formupload = document.getElementById("formupload"); formupload.action = "upload.cgi"; } function UploadLibSVM() { var formupload = document.getElementById("formupload"); formupload.action = "upload_libsvm.cgi"; } function UploadRaw() { var formupload = document.getElementById("formupload"); formupload.action = "upload_raw.cgi"; } function setMultipleC() { var Clist = document.getElementsByName("Clist"); var c= document.getElementsByName("C"); var checkC = document.getElementsByName("multipleC"); if(checkC.item(0).checked == false) { Clist.item(0).disabled = true; c.item(0).disabled = false; } else { Clist.item(0).disabled = false; c.item(0).disabled = true; } } MSVMpack1.2/webpages/Models/0000755000175000017500000000000011761355250014747 5ustar lauerlauerMSVMpack1.2/webpages/style.css0000644000175000017500000000157511706007663015407 0ustar lauerlauerbody { width: 710px; margin-left: 100px; background-color: #FFFFFF; font-family: verdana,trebuchet,arial,sans-serif; font-size: 80%; } td { padding: 5px; text-align: left; } h1 { color: #00A0D0; /* D0D0D0 */ font-weight: normal; letter-spacing: .3em; padding-left: .3em; border-bottom-style: solid; border-bottom-width: 5pt; border-bottom-color: #0080B0;/* #F0F0F0; */ border-top-style: solid; border-top-width: 1pt; border-top-color: #0080B0; } h2 { color: #FFFFFF; /* 000000 */ background-color: #0080B0; padding-top: 3pt; padding-bottom: 3pt; padding-left: 1em; font-weight: bold; font-size: 110%; } a:link { color: #006090; text-decoration: underline; } a:visited { color: #006090; text-decoration: underline; } a:hover { /* color: #0000B0;*/ background-color: #D0D0D0; text-decoration: underline; } #footer { font-size: 80%; font-style: italic; } MSVMpack1.2/webpages/test.cgi0000755000175000017500000000210311672430300015155 0ustar lauerlauer#!/bin/bash echo "Content-Type: text/html;charset=UTF-8" echo TESTFILE=`echo "$QUERY_STRING" | sed -n 's/^.*testfile=\([^&]*\).*$/\1/p' | sed "s/%20/ /g"` PATHDATA=`echo "$QUERY_STRING" | sed -n 's/^.*pathdata=\([^&]*\).*$/\1/p' | sed "s/%20/ /g" | sed "s/%2F/\//g"` MODELFILE=`echo "$QUERY_STRING" | sed -n 's/^.*modeltest=\([^&]*\).*$/\1/p' | sed "s/%20/ /g"` PATHMODELS=`echo "$QUERY_STRING" | sed -n 's/^.*pathmodels=\([^&]*\).*$/\1/p' | sed "s/%20/ /g" | sed "s/%2F/\//g"` OUTFILE=pred.outputs echo "" echo "" # echo "" echo "" echo "MSVMpack" echo "" echo "" echo "

MSVMpack Server

" echo "Testing $MODELFILE on data file $TESTFILE
" echo "Back to homepage" echo "or download the output file " echo "
" echo "
"
./predmsvm $PATHDATA$TESTFILE $PATHMODELS$MODELFILE $OUTFILE
echo "
" echo "" MSVMpack1.2/webpages/convert.cgi0000755000175000017500000000124411703235357015675 0ustar lauerlauer#!/bin/bash echo "Content-Type: text/html;charset=UTF-8" echo FILE=`echo "$QUERY_STRING" | sed -n 's/^.*file=\([^&]*\).*$/\1/p' | sed "s/%20/ /g"` PATHDATA=`echo "$QUERY_STRING" | sed -n 's/^.*pathdata=\([^&]*\).*$/\1/p' | sed "s/%20/ /g" | sed "s/%2F/\//g"` echo "" echo "" echo "" echo "MSVMpack" echo "" echo "" echo "

MSVMpack Server

" echo "HOME " echo "
" echo "
"
./convert $PATHDATA$FILE $PATHDATA$FILE.mpd `cat $PATHDATA$FILE | wc -l` 4
echo "
" echo "" MSVMpack1.2/webpages/.ps0000664000175000017500000001147211723417425014157 0ustar lauerlauerCOMMAND /sbin/init [kthreadd] [ksoftirqd/0] [migration/0] [migration/1] [ksoftirqd/1] [kworker/0:1] [cpuset] [khelper] [netns] [sync_supers] [bdi-default] [kintegrityd] [kblockd] [ata_sff] [khubd] [md] [kworker/1:1] [khungtaskd] [kswapd0] [ksmd] [khugepaged] [fsnotify_mark] [ecryptfs-kthrea] [crypto] [kthrotld] [firewire] [scsi_eh_0] [scsi_eh_1] [scsi_eh_2] [scsi_eh_3] [scsi_eh_4] [scsi_eh_5] [kworker/u:4] [kworker/u:5] [kworker/u:6] [kworker/1:2] [jbd2/sda1-8] [ext4-dio-unwrit] upstart-udev-bridge --daemon udevd --daemon udevd --daemon udevd --daemon [cfg80211] [kpsmoused] [iwlagn] [pccardd] [kworker/0:3] [hd-audio0] rpcbind -w upstart-socket-bridge --daemon /usr/sbin/sshd -D rsyslogd -c5 dbus-daemon --system --fork --activation=upstart /usr/sbin/modem-manager avahi-daemon: running [pc-lauer.local] avahi-daemon: chroot helper NetworkManager rpc.statd -L /usr/lib/policykit-1/polkitd /usr/sbin/cupsd -F /usr/lib/i386-linux-gnu/colord/colord [l2cap] [hci0] /sbin/getty -8 38400 tty4 /sbin/getty -8 38400 tty5 lightdm /sbin/getty -8 38400 tty2 /sbin/getty -8 38400 tty3 /sbin/getty -8 38400 tty6 /usr/sbin/ifdhandler -H -p ccid usb /dev/bus/usb/005/002 acpid -c /etc/acpi/events -s /var/run/acpid.socket /sbin/wpa_supplicant -u -s -O /var/run/wpa_supplicant cron atd /usr/bin/X :0 -auth /var/run/lightdm/root/:0 -nolisten tcp vt7 -novtswitch -background none [iprt] /usr/sbin/bluetoothd [krfcommd] [flush-8:0] /usr/lib/accountsservice/accounts-daemon /usr/sbin/console-kit-daemon --no-daemon /usr/lib/upower/upowerd /usr/lib/rtkit/rtkit-daemon /sbin/getty -8 38400 tty1 /usr/bin/gnome-keyring-daemon --daemonize --login /usr/bin/gnome-session --session=ubuntu /usr/bin/ssh-agent /usr/bin/dbus-launch --exit-with-session /usr/bin/gnome-session --session=ubuntu /usr/bin/dbus-launch --exit-with-session /usr/bin/gnome-session --session=ubuntu //bin/dbus-daemon --fork --print-pid 8 --print-address 10 --session /usr/lib/gvfs/gvfsd /usr/lib/gvfs//gvfs-fuse-daemon /home/lauer/.gvfs /usr/lib/libgconf2-4/gconfd-2 /usr/lib/gnome-settings-daemon/gnome-settings-daemon /usr/lib/gnome-settings-daemon/gsd-printer compiz /usr/bin/gnome-screensaver --no-daemon /usr/bin/pulseaudio --start --log-target=syslog /usr/lib/gvfs/gvfsd-metadata nm-applet /usr/lib/policykit-1-gnome/polkit-gnome-authentication-agent-1 nautilus -n bluetooth-applet /usr/bin/python /usr/bin/indicator-sysmonitor xpad /usr/lib/gnome-settings-daemon/gnome-fallback-mount-helper /usr/lib/notify-osd/notify-osd /usr/lib/gvfs/gvfs-gdu-volume-monitor /usr/lib/udisks/udisks-daemon udisks-daemon: polling /dev/sr0 /usr/lib/gvfs/gvfs-afc-volume-monitor /usr/lib/gvfs/gvfs-gphoto2-volume-monitor /usr/lib/pulseaudio/pulse/gconf-helper /usr/lib/gvfs/gvfsd-trash --spawner :1.1 /org/gtk/gvfs/exec_spaw/0 /usr/lib/d-conf/dconf-service /usr/lib/gvfs/gvfsd-burn --spawner :1.1 /org/gtk/gvfs/exec_spaw/1 /sbin/dhclient -d -4 -sf /usr/lib/NetworkManager/nm-dhcp-client.action -pf /var/run/dhclient-wlan0.pid -lf /var/lib/dhcp/dhclient-a00e6682-973b-455c-afb3-0fbb976fbcc8-wlan0.lease -cf /var/run/nm-dhclient-wlan0.conf wlan0 /bin/sh -c /usr/bin/compiz-decorator /usr/bin/unity-window-decorator /usr/lib/unity/unity-panel-service /usr/lib/bamf/bamfdaemon /usr/lib/indicator-datetime/indicator-datetime-service /usr/lib/indicator-messages/indicator-messages-service /usr/lib/indicator-session/indicator-session-service /usr/lib/indicator-sound/indicator-sound-service /usr/lib/indicator-application/indicator-application-service /usr/lib/geoclue/geoclue-master /usr/lib/ubuntu-geoip/ubuntu-geoip-provider /usr/lib/gnome-online-accounts/goa-daemon telepathy-indicator /usr/lib/telepathy/mission-control-5 /usr/lib/firefox-10.0.2/firefox /usr/lib/gnome-disk-utility/gdu-notification-daemon /usr/lib/unity-lens-applications/unity-applications-daemon /usr/lib/unity-lens-music/unity-music-daemon /usr/lib/unity-lens-files/unity-files-daemon /usr/bin/python /usr/bin/zeitgeist-daemon /usr/lib/unity-lens-music/unity-musicstore-daemon /bin/cat zeitgeist-datahub /usr/bin/python /usr/share/system-config-printer/applet.py /usr/lib/evolution/3.2/evolution-alarm-notify /usr/lib/evolution/e-calendar-factory /usr/lib/evolution/e-addressbook-factory evolution gnome-terminal gnome-pty-helper bash /usr/lib/virtualbox/VirtualBox /usr/lib/virtualbox/VBoxXPCOMIPCD /usr/lib/virtualbox/VBoxSVC --auto-shutdown update-notifier /usr/bin/python /usr/lib/system-service/system-service-d /usr/lib/deja-dup/deja-dup/deja-dup-monitor /usr/lib/virtualbox/VirtualBox --comment win7 --startvm 27486b34-8d96-4bfb-bc54-f21959e5e8bb --no-startvm-errormsgbox /home/lauer/Documents/RECHERCHE/projects/MSVMpack/MSVMpack1.2/mongoose/mongoose -p 8080 -r /home/lauer/Documents/RECHERCHE/projects/MSVMpack/MSVMpack1.2/webpages [kworker/0:0] [kworker/1:0] [kworker/1:3] upload.cgi ./trainmsvm Data/usps.train Models/msvm.model -m WW -c 10.000000 -k 1 -u -x 1024 -t 2 /bin/bash result.cgi ps -Ao args MSVMpack1.2/webpages/stop.cgi0000755000175000017500000000214511706243340015175 0ustar lauerlauer#!/bin/bash echo "Content-Type: text/html;charset=UTF-8" echo TRAINFILE=`echo "$QUERY_STRING" | sed -n 's/^.*trainfile=\([^&]*\).*$/\1/p' | sed "s/%20/ /g"` MODELFILE=`echo "$QUERY_STRING" | sed -n 's/^.*modelfile=\([^&]*\).*$/\1/p' | sed "s/%20/ /g"` PATHMODELS=`echo "$QUERY_STRING" | sed -n 's/^.*pathmodels=\([^&]*\).*$/\1/p' | sed "s/%20/ /g" | sed "s/%2F/\//g"` DONE=`echo "$QUERY_STRING" | sed -n 's/^.*done=\([^&]*\).*$/\1/p'` echo "" echo "" # echo "" echo "" echo "MSVMpack Server" echo "" echo "" echo "

MSVMpack Server

" if [ "$DONE" == "no" ] then pkill -f $MODELFILE fi echo "Training stopped." echo "Back to homepage" if [ "$DONE" == "yes" ] then echo "or download the trained model: $MODELFILE " fi echo "
" echo "
"
echo "$(cat $MODELFILE.training)"
echo "
" rm $MODELFILE.training echo "" MSVMpack1.2/webpages/result.cgi0000755000175000017500000000237311706242745015541 0ustar lauerlauer#!/bin/bash echo "Content-Type: text/html;charset=UTF-8" echo TRAINFILE=`echo "$QUERY_STRING" | sed -n 's/^.*trainfile=\([^&]*\).*$/\1/p' | sed "s/%20/ /g"` MODELFILE=`echo "$QUERY_STRING" | sed -n 's/^.*modelfile=\([^&]*\).*$/\1/p' | sed "s/%20/ /g"` PATHMODELS=`echo "$QUERY_STRING" | sed -n 's/^.*pathmodels=\([^&]*\).*$/\1/p' | sed "s/%20/ /g" | sed "s/%2F/\//g"` ps -Ao args > .ps if cat .ps | grep trainmsvm | grep $PATHMODELS$MODELFILE > /dev/null then URL="result.cgi?trainfile=$TRAINFILE&modelfile=$MODELFILE&pathmodels=$PATHMODELS" DONE="no" else DONE="yes" URL="stop.cgi?trainfile=$TRAINFILE&modelfile=$MODELFILE&pathmodels=$PATHMODELS&done=$DONE" fi echo "" echo "" echo "" echo "" echo "MSVMpack" echo "" echo "" echo "

MSVMpack Server

" echo "Running on $(hostname -s)
" echo "Training $MODELFILE on data file: $TRAINFILE
" echo "STOP " echo "
" echo "
"
echo "$(cat $MODELFILE.training)"
echo "
" echo "" MSVMpack1.2/lib/0000755000175000017500000000000012104705371012470 5ustar lauerlauerMSVMpack1.2/Comfiles/0000755000175000017500000000000011706231676013474 5ustar lauerlauerMSVMpack1.2/Comfiles/train_SVM.com.chimie0000644000175000017500000000012011645003750017254 0ustar lauerlauer3 1 10.0 10.0 10.0 4 Data/chimie.app Alpha/chimie.alpha.init Alpha/chimie.alpha MSVMpack1.2/Comfiles/train_SVM.com0000644000175000017500000000010211645003634016020 0ustar lauerlauer3 2 10.0 10.0 10.0 4 Data/Lee.app Alpha/Lee.alpha Alpha/Lee.alpha MSVMpack1.2/Comfiles/train_SVM.com.Lee0000644000175000017500000000010711645004003016520 0ustar lauerlauer3 2 10.0 10.0 10.0 4 Data/Lee.app Alpha/Lee.alpha.init Alpha/Lee.alpha MSVMpack1.2/Comfiles/train_SVM.com.toy0000644000175000017500000000011211645004014016624 0ustar lauerlauer3 1 100.0 100.0 100.0 4 Data/toy.app Alpha/toy.alpha.init Alpha/toy.alpha MSVMpack1.2/Comfiles/train_SVM.com.gaussians0000644000175000017500000000012611645003760020022 0ustar lauerlauer3 1 0.1 0.1 0.1 4 Data/gaussians.app Alpha/gaussians.alpha.init Alpha/gaussians.alpha MSVMpack1.2/Comfiles/train_SVM.com.bio0000644000175000017500000000011011645003646016572 0ustar lauerlauer4 1 0.2 0.2 0.2 0.2 2 Data/bio.app Alpha/bio.alpha.init Alpha/bio.alpha MSVMpack1.2/Comfiles/train_SVM.com.iris0000644000175000017500000000011211645003772016771 0ustar lauerlauer3 2 10.0 10.0 10.0 4 Data/iris.app Alpha/iris.alpha.init Alpha/iris.alpha MSVMpack1.2/Makefile0000644000175000017500000002277312104674703013401 0ustar lauerlauer# Version VERSION=1.2 # Platform UNAME := $(shell uname -s) # Detect SSE instruction set (SSE2, SSE3 or SSE4.1...) SSE=`TESTSSE42=\`cat /proc/cpuinfo | grep sse4_2 | wc -l;\`; if [ $$TESTSSE42 -eq 0 ]; then (TESTSSE41=\`cat /proc/cpuinfo | grep sse4_1 | wc -l;\`; if [ $$TESTSSE41 -eq 0 ]; then (TESTSSE3=\`cat /proc/cpuinfo | grep sse3 | wc -l;\` ; if [ $$TESTSSE3 -eq 0 ]; then echo -msse2; else echo -msse3; fi); else echo -msse4.1; fi); else echo -msse4.2; fi` # Default flags for GCC: use level 3 optimization DEBUG=-O3 CFLAGS=$(DEBUG) $(SSE) -mfpmath=sse -DVERSION=$(VERSION) # Flags required by lp_solve LPSOLVELINK= -ldl # Default directories for MSVMpack include and lib INCLUDE= -Iinclude/ -Ilp_solve_5.5/ LIB= -Llib/ CURRENT_DIR= `pwd` # Directories for web server WEBDIR=webpages/ WEBSRC=src/web/ DIR=\"`pwd`\" MONGOOSEDIR=mongoose/ # Default rule: use 'make' to build all welcome: ifeq ($(UNAME),Darwin) @make -f Makefile.osx else @echo @echo "... Building MSVMpack $(VERSION) ..." @echo "(parallel implementation for Linux)" @echo @echo "Using SSE flag '$(SSE)' for vectorized kernels... " @echo "(use e.g. 'make SSE=-msse2' to change that)" @echo @make all @echo @echo "**************************************" @echo "MSVMpack build completed successfully." @echo "Static library 'libmsvm.a' stored in $(CURRENT_DIR)/lib/." @echo "You can now use 'trainmsvm' and 'predmsvm' command-line tools." @echo "**************************************" @echo @echo "... Now building MSVMpack Server ..." @echo @make server endif all: lib/libmsvm.a trainmsvm predmsvm # Debugging rules: use 'make debug' to build for debugging purposes debug: make DEBUG="-g -O0" SSE="-msse2" # or 'make profile' for performance analysis profile: make DEBUG="-g -pg -O3" # Use 'make clean' to remove all compiled objects, library and executables clean: server-clean rm -f lib/*.a src/*.o trainmsvm predmsvm # Use 'make install' for a system-wide install of the command-line tools install: trainmsvm predmsvm cp trainmsvm /usr/local/bin/ cp predmsvm /usr/local/bin/ cp tools/plotlog /usr/local/bin/ cp tools/plotlog_msvm2 /usr/local/bin/ # Use 'make uninstall' to remove the system-wide install # (does not remove the MSVMpack directory) uninstall: rm -f /usr/local/bin/trainmsvm /usr/local/bin/predmsvm /usr/local/bin/plotlog # Use 'make package' to generate a clean archive MSVMpackX.X.tar.gz # (this requires 'lp_solve_5.5.0.15_source.tar.gz' in the parent directory) # Note that this will REMOVE ALL MODEL FILES from the MSVMpack directory package: clean server-package rm -f *.model *.tmp *.outputs *.log .*.log .*.gnuplot *.ps *.out *~ doc/*~ doc/*.outputs doc/*.model doc/*.src/*~ include/*~ Save_alpha/* -rm -rf lp_solve_5.5 -rm -f doc/example -rm -rf package tar -zxvf ../lp_solve_5.5.0.15_source.tar.gz cd .. ; tar -zcvf MSVMpack$(VERSION).tar.gz MSVMpack$(VERSION) --exclude-vcs mkdir package mv ../MSVMpack$(VERSION).tar.gz package/ #### Rules for internal use ### # Make the MSVMpack static library 'libmsvm.a' lib/libmsvm.a: src/libMSVM.o src/kernel.o src/libtrainMSVM.o src/libevalMSVM.o src/libtrainMSVM_WW.o src/libevalMSVM_WW.o src/libtrainMSVM_CS.o src/libevalMSVM_CS.o src/libtrainMSVM_LLW.o src/libevalMSVM_LLW.o src/libtrainMSVM_2.o src/libtrainMSVM_2fw.o src/libevalMSVM_2.o src/biblio.o src/algebra.o lib/liblpsolve55.a @cd lib ; ar x liblpsolve55.a @ar rcs lib/libmsvm.a src/libMSVM.o src/kernel.o src/libtrainMSVM.o src/libtrainMSVM_WW.o src/libevalMSVM.o src/libevalMSVM_WW.o src/libtrainMSVM_CS.o src/libevalMSVM_CS.o src/libtrainMSVM_LLW.o src/libevalMSVM_LLW.o src/libtrainMSVM_2.o src/libtrainMSVM_2fw.o src/libevalMSVM_2.o src/biblio.o src/algebra.o lib/*.o @rm lib/*.o @echo libmsvm.a... # Get either ux32/liblpsolve55.a or ux64/liblpsolve55.a lib/liblpsolve55.a: lp_solve_5.5/lpsolve55/bin/liblpsolve55.a -@cp lp_solve_5.5/lpsolve55/bin/liblpsolve55.a lib/ # This builds the lp_solve API lp_solve_5.5/lpsolve55/bin/liblpsolve55.a: @echo "Building lp_solve library (this may take some time)..." @cd lp_solve_5.5/lpsolve55 ; sh ccc -@cp lp_solve_5.5/lpsolve55/bin/ux32/liblpsolve55.a lp_solve_5.5/lpsolve55/bin/ 2>/dev/null -@cp lp_solve_5.5/lpsolve55/bin/ux64/liblpsolve55.a lp_solve_5.5/lpsolve55/bin/ 2>/dev/null # Make object files src/libMSVM.o: src/libMSVM.c src/custom_kernels.c @gcc -o src/libMSVM.o -c src/libMSVM.c $(CFLAGS) $(INCLUDE) @echo libMSVM.o... src/kernel.o: src/kernel.c src/custom_kernels.c @gcc -o src/kernel.o -c src/kernel.c $(CFLAGS) $(INCLUDE) @echo kernel.o... src/libtrainMSVM.o: src/libtrainMSVM.c @gcc -o src/libtrainMSVM.o -c src/libtrainMSVM.c $(CFLAGS) $(INCLUDE) @echo libtrainMSVM.o... src/libevalMSVM.o: src/libevalMSVM.c @gcc -c src/libevalMSVM.c -o src/libevalMSVM.o $(CFLAGS) $(INCLUDE) @echo libevalMSVM.o... src/libtrainMSVM_2.o: src/libtrainMSVM_2.c @gcc -o src/libtrainMSVM_2.o -c src/libtrainMSVM_2.c $(CFLAGS) $(INCLUDE) @echo libtrainMSVM_2.o... src/libtrainMSVM_2fw.o: src/libtrainMSVM_2fw.c @gcc -o src/libtrainMSVM_2fw.o -c src/libtrainMSVM_2fw.c $(CFLAGS) $(INCLUDE) @echo libtrainMSVM_2fw.o... src/libevalMSVM_2.o: src/libevalMSVM_2.c @gcc -c src/libevalMSVM_2.c -o src/libevalMSVM_2.o $(CFLAGS) $(INCLUDE) @echo libevalMSVM_2.o... src/libtrainMSVM_WW.o: src/libtrainMSVM_WW.c @gcc -o src/libtrainMSVM_WW.o -c src/libtrainMSVM_WW.c $(CFLAGS) $(INCLUDE) @echo libtrainMSVM_WW.o... src/libevalMSVM_WW.o: src/libevalMSVM_WW.c @gcc -c src/libevalMSVM_WW.c -o src/libevalMSVM_WW.o $(CFLAGS) $(INCLUDE) @echo libevalMSVM_WW.o... src/libtrainMSVM_CS.o: src/libtrainMSVM_CS.c @gcc -o src/libtrainMSVM_CS.o -c src/libtrainMSVM_CS.c $(CFLAGS) $(INCLUDE) @echo libtrainMSVM_CS.o... src/libevalMSVM_CS.o: src/libevalMSVM_CS.c @gcc -c src/libevalMSVM_CS.c -o src/libevalMSVM_CS.o $(CFLAGS) $(INCLUDE) @echo libevalMSVM_CS.o... src/libtrainMSVM_LLW.o: src/libtrainMSVM_LLW.c @gcc -o src/libtrainMSVM_LLW.o -c src/libtrainMSVM_LLW.c $(CFLAGS) $(INCLUDE) @echo libtrainMSVM_LLW.o... src/libevalMSVM_LLW.o: src/libevalMSVM_LLW.c @gcc -c src/libevalMSVM_LLW.c -o src/libevalMSVM_LLW.o $(CFLAGS) $(INCLUDE) @echo libevalMSVM_LLW.o... src/algebra.o: src/algebra.c @gcc -c src/algebra.c -o src/algebra.o $(CFLAGS) $(INCLUDE) @echo algebra.o... src/biblio.o: src/biblio.c @gcc -c src/biblio.c -o src/biblio.o $(CFLAGS) $(INCLUDE) @echo biblio.o... # Make command-line tools # # use '-Llib/ -lmsvm' to link with the MSVMpack library # trainmsvm: src/trainMSVM.c lib/libmsvm.a @gcc -o trainmsvm src/trainMSVM.c $(CFLAGS) $(INCLUDE) $(LIB) -lmsvm -lm -lpthread $(LPSOLVELINK) @echo trainmsvm... predmsvm: src/predMSVM.c lib/libmsvm.a @gcc -o predmsvm src/predMSVM.c $(CFLAGS) $(INCLUDE) $(LIB) -lmsvm -lm -lpthread @echo predmsvm... # Make MSVMpack web server # server: $(WEBDIR)trainmsvm $(WEBDIR)predmsvm $(WEBDIR)home.cgi $(WEBDIR)Server.cgi $(WEBDIR)upload.cgi $(WEBDIR)upload_libsvm.cgi $(WEBDIR)upload_raw.cgi $(WEBDIR)admin/admin.cgi $(WEBDIR)admin/delete.cgi $(WEBDIR)convert datadir msvmserver @echo @echo "**************************************" @echo MSVMpack Server build completed. @echo @echo "Use 'msvmserver start' in " @echo $(DIR) @echo to start the server. @echo "**************************************" @echo # Copy MSVMpack binaries to server $(WEBDIR)trainmsvm: trainmsvm @echo "trainmsvm..." @cp trainmsvm $(WEBDIR) $(WEBDIR)predmsvm: predmsvm @echo "predmsvm..." @cp predmsvm $(WEBDIR) # Web CGI pages $(WEBDIR)home.cgi: $(WEBSRC)home.c @echo home.cgi... @gcc -O3 -o $(WEBDIR)home.cgi $(WEBSRC)home.c -DVERSION=$(VERSION) $(WEBDIR)Server.cgi: $(WEBSRC)Server.c @echo Server.cgi... @gcc -Wno-unused-result -O3 -o $(WEBDIR)Server.cgi $(WEBSRC)Server.c -DVERSION=$(VERSION) $(WEBDIR)upload.cgi: $(WEBSRC)upload.c @echo upload.cgi... @gcc -Wno-unused-result -O3 -o $(WEBDIR)upload.cgi $(WEBSRC)upload.c $(WEBDIR)upload_libsvm.cgi: $(WEBSRC)upload_libsvm.c @echo upload_libsvm.cgi... @gcc -Wno-unused-result -O3 -o $(WEBDIR)upload_libsvm.cgi $(WEBSRC)upload_libsvm.c $(WEBDIR)upload_raw.cgi: $(WEBSRC)upload_raw.c @echo upload_raw.cgi... @gcc -Wno-unused-result -O3 -o $(WEBDIR)upload_raw.cgi $(WEBSRC)upload_raw.c $(WEBDIR)admin/admin.cgi: $(WEBSRC)admin.c @echo admin.cgi... @gcc -Wno-unused-result -O3 -o $(WEBDIR)admin/admin.cgi $(WEBSRC)admin.c -DVERSION=$(VERSION) $(WEBDIR)admin/delete.cgi: $(WEBSRC)delete.c @echo delete.cgi... @gcc -o $(WEBDIR)admin/delete.cgi $(WEBSRC)delete.c $(WEBDIR)convert: $(WEBSRC)convert.c @echo convert... @gcc -o $(WEBDIR)convert $(WEBSRC)convert.c datadir: @echo "Data/..." @cp Data/* $(WEBDIR)Data/ # Server executable $(MONGOOSEDIR)mongoose: @echo "Building mongoose http server..." @cd $(MONGOOSEDIR); make CFLAGS=" -W -Wno-unused-but-set-parameter -std=c99 -pedantic -O2" linux msvmserver: $(WEBSRC)msvmserver.c $(MONGOOSEDIR)mongoose @echo msvmserver... @gcc -Wno-unused-result -O3 -o msvmserver $(WEBSRC)msvmserver.c -DDIR=$(DIR) # Clean web server server-clean: -./msvmserver stop rm -f $(WEBDIR)home.cgi $(WEBDIR)Server.cgi $(WEBDIR)upload.cgi $(WEBDIR)upload_libsvm.cgi $(WEBDIR)upload_raw.cgi $(WEBDIR)admin/admin.cgi $(WEBDIR)admin/delete.cgi $(WEBDIR)trainmsvm $(WEBDIR)predmsvm $(WEBDIR)convert msvmserver # Package web server server-package: server-clean -rm -f $(WEBDIR)training.out -rm -f $(WEBDIR)Data/* -rm -f $(WEBDIR)Models/* -rm -f $(WEBDIR)admin/server.conf -rm -f $(WEBDIR)*~ $(WEBDIR)*.outputs -rm -f $(WEBDIR)admin/*~ # reset admin passwd mongoose -A $(WEBDIR)admin/.htpasswd "mydomain.com" "admin" "admin" -rm -rf mongoose tar -zxvf ../mongoose-3.0.tgz MSVMpack1.2/tools/0000755000175000017500000000000011706231676013073 5ustar lauerlauerMSVMpack1.2/tools/plotlog0000755000175000017500000000165111644772171014505 0ustar lauerlauer#!/bin/bash SCRIPT=".plotlog.gnuplot" # Plot the log file of trainmsvm with gnuplot # and save plot to a .ps file GNUPLOT=`command -v gnuplot -e quit` if [ "$GNUPLOT" = "" ] then echo "Gnuplot not found. Cannot plot log file." exit fi if [ $# -lt 1 ]; then echo "Usage: plotlog logfile.log [plotfile.ps]" exit fi LOGFILE=$1 if [ -f $LOGFILE ]; then echo "Plotting log file $LOGFILE..." else echo "Log file $LOGFILE not found." exit fi if [ $# -gt 1 ] ; then PSFILE=$2 else PSFILE=$LOGFILE.ps fi echo "set term postscript enhanced color" > $SCRIPT echo "set output \"$PSFILE\" ; set size .8,.8" >> $SCRIPT echo "plot \"$LOGFILE\" using 1:2 lt 1 title \"value of the dual objective\" with linespoints, \"$LOGFILE\" using 1:3 lt 2 title \"upper bound on the optimum\" with linespoints" >> $SCRIPT echo "set term wxt ; set output ; set size 1.,1. ; replot" >> $SCRIPT gnuplot -persist $SCRIPT echo "Plot saved as $PSFILE" MSVMpack1.2/tools/plotlog_msvm20000755000175000017500000000205211644772171015625 0ustar lauerlauer#!/bin/bash SCRIPT=".plotlog.gnuplot" # Plot the log file of trainmsvm with gnuplot # and save plot to a .ps file GNUPLOT=`command -v gnuplot -e quit` if [ "$GNUPLOT" = "" ] then echo "Gnuplot not found. Cannot plot log file." exit fi if [ $# -lt 1 ]; then echo "Usage: plotlog_msvm2 logfile.log [plotfile.ps]" exit fi LOGFILE=$1 if [ -f $LOGFILE ]; then echo "Plotting log file $LOGFILE..." else echo "Log file $LOGFILE not found." exit fi if [ $# -gt 1 ] ; then PSFILE=$2 else PSFILE=$LOGFILE.ps fi echo "set term postscript enhanced color" > $SCRIPT echo "set output \"$PSFILE\" ; set size .8,.8" >> $SCRIPT echo "plot \"$LOGFILE\" using 1:2 lt 1 title \"dual\" with linespoints, \"$LOGFILE\" using 1:3 lt 2 title \"unconstrained primal\" with linespoints, \"$LOGFILE\" using 1:4 lt 3 title \"cheap upper bound\" with linespoints, \"$LOGFILE\" using 1:5 lt 4 title \"optimized upper bound\" with linespoints" >> $SCRIPT echo "set term wxt ; set output ; set size 1.,1. ; replot" >> $SCRIPT gnuplot -persist $SCRIPT echo "Plot saved as $PSFILE"