--- /dev/null
+/* This file is part of libDAI - http://www.libdai.org/
+ *
+ * libDAI is licensed under the terms of the GNU General Public License version
+ * 2, or (at your option) any later version. libDAI is distributed without any
+ * warranty. See the file COPYING for more details.
+ *
+ * Copyright (C) 2008-2010 Joris Mooij [joris dot mooij at libdai dot org]
+ */
+
+
+#include <iostream>
+#include <fstream>
+#include <ostream>
+#include <cstdlib>
+#include <dai/alldai.h>
+#include <dai/util.h>
+#include <dai/index.h>
+#include <dai/jtree.h>
+
+
+using namespace std;
+using namespace dai;
+
+
+// Type for storing a joint state of all variables
+typedef std::vector<size_t> stateVec;
+
+
+struct PRbest {
+ Real value;
+ Real maxdiff;
+ bool ready;
+ PRbest() : value(0.0), maxdiff(INFINITY), ready(false) {}
+};
+
+struct MARbest {
+ vector<Factor> beliefs;
+ Real maxdiff;
+ bool ready;
+ MARbest() : beliefs(), maxdiff(INFINITY), ready(false) {}
+};
+
+struct MPEbest {
+ Real value;
+ stateVec state;
+ bool ready;
+ MPEbest() : value(-INFINITY), state(), ready(false) {}
+};
+
+
+/// Reads "evidence" (a mapping from observed variable labels to the observed values) from a UAI evidence file
+vector<map<size_t, size_t> > ReadUAIEvidenceFile( char* filename, size_t verbose ) {
+ vector<map<size_t, size_t> > evid;
+
+ // open file
+ ifstream is;
+ is.open( filename );
+ if( is.is_open() ) {
+ // read number of evidence cases
+ size_t nr_evid;
+ is >> nr_evid;
+ if( is.fail() )
+ DAI_THROWE(INVALID_EVIDENCE_FILE,"Cannot read number of evidence cases");
+ if( verbose >= 2 )
+ cout << "Reading " << nr_evid << " evidence cases..." << endl;
+
+ evid.resize( nr_evid );
+ for( size_t i = 0; i < nr_evid; i++ ) {
+ // read number of variables
+ size_t nr_obs;
+ is >> nr_obs;
+ if( is.fail() )
+ DAI_THROWE(INVALID_EVIDENCE_FILE,"Evidence case " + toString(i) + ": Cannot read number of observations");
+ if( verbose >= 2 )
+ cout << "Evidence case " << i << ": reading " << nr_obs << " observations..." << endl;
+
+ // for each observation, read the variable label and the observed value
+ for( size_t j = 0; j < nr_obs; j++ ) {
+ size_t label, val;
+ is >> label;
+ if( is.fail() )
+ DAI_THROWE(INVALID_EVIDENCE_FILE,"Evidence case " + toString(i) + ": Cannot read label for " + toString(j) + "'th observed variable");
+ is >> val;
+ if( is.fail() )
+ DAI_THROWE(INVALID_EVIDENCE_FILE,"Evidence case " + toString(i) + ": Cannot read value of " + toString(j) + "'th observed variable");
+ if( verbose >= 3 )
+ cout << " variable: " << label << ", value: " << val << endl;
+ evid[i][label] = val;
+ }
+ }
+
+ // close file
+ is.close();
+ } else
+ DAI_THROWE(CANNOT_READ_FILE,"Cannot read from file " + std::string(filename));
+
+ if( evid.size() == 0 )
+ evid.resize( 1 );
+
+ return evid;
+}
+
+
+/// Reads factor graph (as a pair of a variable vector and factor vector) from a UAI factor graph file
+void ReadUAIFGFile( const char *filename, size_t verbose, vector<Var>& vars, vector<Factor>& factors, vector<Permute>& permutations ) {
+ vars.clear();
+ factors.clear();
+ permutations.clear();
+
+ // open file
+ ifstream is;
+ is.open( filename );
+ if( is.is_open() ) {
+ size_t nrFacs, nrVars;
+ string line;
+
+ // read header line
+ getline(is,line);
+ if( is.fail() || (line != "BAYES" && line != "MARKOV" && line != "BAYES\r" && line != "MARKOV\r") )
+ DAI_THROWE(INVALID_FACTORGRAPH_FILE,"UAI factor graph file should start with \"BAYES\" or \"MARKOV\"");
+ if( verbose >= 2 )
+ cout << "Reading " << line << " network..." << endl;
+
+ // read number of variables
+ is >> nrVars;
+ if( is.fail() )
+ DAI_THROWE(INVALID_FACTORGRAPH_FILE,"Cannot read number of variables");
+ if( verbose >= 2 )
+ cout << "Reading " << nrVars << " variables..." << endl;
+
+ // for each variable, read its number of states
+ vars.reserve( nrVars );
+ for( size_t i = 0; i < nrVars; i++ ) {
+ size_t dim;
+ is >> dim;
+ if( is.fail() )
+ DAI_THROWE(INVALID_FACTORGRAPH_FILE,"Cannot read number of states of " + toString(i) + "'th variable");
+ vars.push_back( Var( i, dim ) );
+ }
+
+ // read number of factors
+ is >> nrFacs;
+ if( is.fail() )
+ DAI_THROWE(INVALID_FACTORGRAPH_FILE,"Cannot read number of factors");
+ if( verbose >= 2 )
+ cout << "Reading " << nrFacs << " factors..." << endl;
+
+ // for each factor, read the variables on which it depends
+ vector<vector<Var> > factorVars;
+ factors.reserve( nrFacs );
+ factorVars.reserve( nrFacs );
+ for( size_t I = 0; I < nrFacs; I++ ) {
+ if( verbose >= 3 )
+ cout << "Reading factor " << I << "..." << endl;
+
+ // read number of variables for factor I
+ size_t I_nrVars;
+ is >> I_nrVars;
+ if( is.fail() )
+ DAI_THROWE(INVALID_FACTORGRAPH_FILE,"Cannot read number of variables for " + toString(I) + "'th factor");
+ if( verbose >= 3 )
+ cout << " which depends on " << I_nrVars << " variables" << endl;
+
+ // read the variable labels
+ vector<long> I_labels;
+ vector<size_t> I_dims;
+ I_labels.reserve( I_nrVars );
+ I_dims.reserve( I_nrVars );
+ factorVars[I].reserve( I_nrVars );
+ for( size_t _i = 0; _i < I_nrVars; _i++ ) {
+ long label;
+ is >> label;
+ if( is.fail() )
+ DAI_THROWE(INVALID_FACTORGRAPH_FILE,"Cannot read variable labels for " + toString(I) + "'th factor");
+ I_labels.push_back( label );
+ I_dims.push_back( vars[label].states() );
+ factorVars[I].push_back( vars[label] );
+ }
+ if( verbose >= 3 )
+ cout << " labels: " << I_labels << ", dimensions " << I_dims << endl;
+
+ // add the factor and the labels
+ factors.push_back( Factor( VarSet( factorVars[I].begin(), factorVars[I].end(), factorVars[I].size() ), (Real)0 ) );
+ }
+
+ // for each factor, read its values
+ permutations.reserve( nrFacs );
+ for( size_t I = 0; I < nrFacs; I++ ) {
+ if( verbose >= 3 )
+ cout << "Reading factor " << I << "..." << endl;
+
+ // calculate permutation object, reversing the indexing in factorVars[I] first
+ Permute permindex( factorVars[I], true );
+ permutations.push_back( permindex );
+
+ // read factor values
+ size_t nrNonZeros;
+ is >> nrNonZeros;
+ if( is.fail() )
+ DAI_THROWE(INVALID_FACTORGRAPH_FILE,"Cannot read number of nonzero factor values for " + toString(I) + "'th factor");
+ if( verbose >= 3 )
+ cout << " number of nonzero values: " << nrNonZeros << endl;
+ DAI_ASSERT( nrNonZeros == factors[I].nrStates() );
+ for( size_t li = 0; li < nrNonZeros; li++ ) {
+ Real val;
+ is >> val;
+ if( is.fail() )
+ DAI_THROWE(INVALID_FACTORGRAPH_FILE,"Cannot read factor values of " + toString(I) + "'th factor");
+ // assign value after calculating its linear index corresponding to the permutation
+ if( verbose >= 4 )
+ cout << " " << li << "'th value " << val << " corresponds with index " << permindex.convertLinearIndex(li) << endl;
+ factors[I].set( permindex.convertLinearIndex( li ), val );
+ }
+ }
+ if( verbose >= 3 )
+ cout << "variables:" << vars << endl;
+ if( verbose >= 3 )
+ cout << "factors:" << factors << endl;
+
+ // close file
+ is.close();
+ } else
+ DAI_THROWE(CANNOT_READ_FILE,"Cannot read from file " + std::string(filename));
+}
+
+
+int main( int argc, char *argv[] ) {
+ if ( argc != 5 ) {
+ cout << "This program is part of libDAI - http://www.libdai.org/" << endl << endl;
+ cout << "It is one of the winning solvers that participated in the" << endl;
+ cout << "UAI 2010 Approximate Inference Challenge" << endl;
+ cout << "(see http://www.cs.huji.ac.il/project/UAI10/)" << endl << endl;
+ cout << "Usage: " << argv[0] << " <filename.uai> <filename.uai.evid> <seed> <task>" << endl << endl;
+ return 1;
+ } else {
+ double starttic = toc();
+
+ size_t verbose = 1;
+ size_t ia_verbose = 0;
+ bool surgery = true;
+ if( verbose )
+ cout << "Solver: " << argv[0] << endl;
+
+ // set random seed
+ size_t seed = fromString<size_t>( argv[3] );
+ rnd_seed( seed );
+ if( verbose )
+ cout << "Seed: " << seed << endl;
+
+ // check whether the task is valid
+ string task( argv[4] );
+ if( task != string("PR") && task != string("MPE") && task != string("MAR") )
+ DAI_THROWE(RUNTIME_ERROR,"Unknown task");
+ if( verbose )
+ cout << "Task: " << task << endl;
+
+ // output other command line options
+ if( verbose ) {
+ cout << "Factorgraph filename: " << argv[1] << endl;
+ cout << "Evidence filename: " << argv[2] << endl;
+ }
+
+ // get time and memory limits
+ char *buf = getenv( "UAI_TIME" );
+ double UAI_time = INFINITY;
+ if( buf != NULL )
+ UAI_time = fromString<double>( buf );
+ buf = getenv( "UAI_MEMORY" );
+ size_t UAI_memory = 0;
+ if( buf != NULL ) {
+ UAI_memory = fromString<double>( buf ) * 1024 * 1024 * 1024;
+ }
+ if( verbose ) {
+ cout << "Time limit: " << UAI_time << endl;
+ cout << "Memory limit: " << UAI_memory << endl;
+ }
+
+ // build output file name
+ vector<string> pathComponents;
+ tokenizeString( string(argv[1]), pathComponents, "/" );
+ string outfile = pathComponents.back() + "." + task;
+ if( verbose )
+ cout << "Output filename: " << outfile << endl;
+
+ // open output stream
+ ofstream os;
+ os.open( outfile.c_str() );
+ if( !os.is_open() )
+ DAI_THROWE(CANNOT_WRITE_FILE,"Cannot write to file " + outfile);
+ if( verbose )
+ cout << "Opened output stream" << endl;
+
+ // read factor graph
+ vector<Var> vars;
+ vector<Factor> facs0;
+ vector<Permute> permutations;
+ if( verbose )
+ cout << "Reading factor graph..." << endl;
+ ReadUAIFGFile( argv[1], verbose, vars, facs0, permutations );
+ if( verbose )
+ cout << "Successfully read factor graph" << endl;
+
+ // check if it could be a grid
+ bool couldBeGrid = true;
+ FactorGraph fg0( facs0.begin(), facs0.end(), vars.begin(), vars.end(), facs0.size(), vars.size() );
+ for( size_t i = 0; i < fg0.nrVars(); i++ )
+ if( fg0.delta(i).size() > 4 ) {
+ couldBeGrid = false;
+ break;
+ }
+ if( couldBeGrid )
+ for( size_t I = 0; I < fg0.nrFactors(); I++ )
+ if( fg0.factor(I).vars().size() > 2 ) {
+ couldBeGrid = false;
+ break;
+ }
+ if( verbose ) {
+ if( couldBeGrid )
+ cout << "This could be a grid!" << endl;
+ else
+ cout << "This cannot be a grid!" << endl;
+ }
+
+ // read evidence
+ if( verbose )
+ cout << "Reading evidence..." << endl;
+ vector<map<size_t,size_t> > evid = ReadUAIEvidenceFile( argv[2], verbose );
+ if( verbose )
+ cout << "Successfully read " << evid.size() << " evidence cases" << endl;
+
+ // write output header
+ if( verbose )
+ cout << " Writing header to file..." << endl;
+ os << task << endl;
+
+ // construct clamped factor graphs
+ if( verbose )
+ cout << "Constructing clamped factor graphs..." << endl;
+ vector<FactorGraph> fgs;
+ fgs.reserve( evid.size() );
+ for( size_t ev = 0; ev < evid.size(); ev++ ) {
+ if( verbose )
+ cout << " Evidence case " << ev << "..." << endl;
+ // copy vector of factors
+ vector<Factor> facs( facs0 );
+
+ // change factor graph to reflect observed evidence
+ if( verbose )
+ cout << " Applying evidence..." << endl;
+ if( surgery ) {
+ // replace factors with clamped variables with slices
+ for( size_t I = 0; I < facs.size(); I++ ) {
+ for( map<size_t,size_t>::const_iterator e = evid[ev].begin(); e != evid[ev].end(); e++ ) {
+ if( facs[I].vars() >> vars[e->first] ) {
+ if( verbose >= 2 )
+ cout << " Clamping " << e->first << " to value " << e->second << " in factor " << I << " = " << facs[I].vars() << endl;
+ facs[I] = facs[I].slice( vars[e->first], e->second );
+ if( verbose >= 2 )
+ cout << " ...remaining vars: " << facs[I].vars() << endl;
+ }
+ }
+ }
+ // remove empty factors
+ Real logZcorr = 0.0;
+ for( vector<Factor>::iterator I = facs.begin(); I != facs.end(); )
+ if( I->vars().size() == 0 ) {
+ logZcorr += std::log( (Real)(*I)[0] );
+ I = facs.erase( I );
+ } else
+ I++;
+ // multiply with logZcorr constant
+ if( facs.size() == 0 )
+ facs.push_back( Factor( VarSet(), std::exp(logZcorr) ) );
+ else
+ facs.front() *= std::exp(logZcorr);
+ }
+ // add delta factors corresponding to observed variable values
+ for( map<size_t,size_t>::const_iterator e = evid[ev].begin(); e != evid[ev].end(); e++ )
+ facs.push_back( createFactorDelta( vars[e->first], e->second ) );
+
+ // construct clamped factor graph
+ if( verbose )
+ cout << " Constructing factor graph..." << endl;
+ fgs.push_back( FactorGraph( facs.begin(), facs.end(), vars.begin(), vars.end(), facs.size(), vars.size() ) );
+ }
+
+ // variables for storing best results so far
+ vector<PRbest> bestPR( evid.size() );
+ vector<MARbest> bestMAR( evid.size() );
+ vector<MPEbest> bestMPE( evid.size() );
+ for( size_t ev = 0; ev < evid.size(); ev++ )
+ bestMPE[ev].state = stateVec( fgs[ev].nrVars(), 0 );
+ vector<size_t> ev2go;
+ ev2go.reserve( evid.size() );
+ for( size_t ev = 0; ev < evid.size(); ev++ )
+ ev2go.push_back( ev );
+
+ // solve inference problems
+ if( verbose )
+ cout << "Solving inference problems..." << endl;
+ bool first = true;
+ size_t nrsolvers = 3;
+ vector<size_t> nrsubsolvers( nrsolvers );
+ nrsubsolvers[0] = 2;
+ nrsubsolvers[1] = 1;
+ nrsubsolvers[2] = 1;
+ double MPEdamping = 0.49;
+ // for each (sub)solver
+ for( size_t solver = 0; solver < nrsolvers; solver++ ) {
+ if( verbose )
+ cout << " Solver " << solver << endl;
+
+ // for each evidence case
+ size_t subsolver = 0;
+ for( long _ev = 0; _ev < (long)ev2go.size(); ) {
+ bool improved = false;
+ size_t ev = ev2go[_ev];
+ if( verbose )
+ cout << " Evidence case " << ev << ", subsolver = " << subsolver << "..." << endl;
+
+ // construct inference algorithm on clamped factor graph
+ if( verbose )
+ cout << " Constructing inference algorithm..." << endl;
+ InfAlg *ia;
+ double tic = toc();
+ bool failed = false;
+ try {
+ // construct
+ if( solver == 0 ) { // the quick one
+ double remtime = (UAI_time - (toc() - starttic)) * 0.9;
+ if( remtime < 1.0 )
+ remtime = 1.0 ;
+ double maxtime = remtime / (ev2go.size() - _ev);
+ if( verbose ) {
+ cout << " Past time: " << (toc() - starttic) << endl;
+ cout << " Remaining time:" << remtime << endl;
+ cout << " Allotted time: " << maxtime << endl;
+ }
+ string maxtimestr;
+ if( maxtime != INFINITY )
+ maxtimestr = ",maxtime=" + toString(maxtime);
+ // quick and dirty...
+ if( task == "MPE" )
+ ia = newInfAlgFromString( "BP[inference=MAXPROD,updates=SEQRND,logdomain=" + toString(subsolver) + ",tol=1e-9,maxiter=10000" + maxtimestr + ",damping=0.1,verbose=" + toString(ia_verbose) + "]", fgs[ev] );
+ else {
+ if( couldBeGrid )
+ ia = newInfAlgFromString( "HAK[doubleloop=1,clusters=LOOP,init=UNIFORM,loopdepth=4,tol=1e-9,maxiter=10000" + maxtimestr + ",verbose=" + toString(ia_verbose) + "]", fgs[ev] );
+ else
+ ia = newInfAlgFromString( "BP[inference=SUMPROD,updates=SEQRND,logdomain=" + toString(subsolver) + ",tol=1e-9,maxiter=10000" + maxtimestr + ",damping=0.0,verbose=" + toString(ia_verbose) + "]", fgs[ev] );
+ }
+ } else if( solver == 1 ) { // the exact one
+ string maxmemstr;
+ if( UAI_memory != 0 )
+ maxmemstr = ",maxmem=" + toString(UAI_memory);
+ if( task == "MPE" )
+ ia = newInfAlgFromString( "JTREE[inference=MAXPROD,updates=HUGIN" + maxmemstr + ",verbose=" + toString(ia_verbose) + "]", fgs[ev] );
+ else
+ ia = newInfAlgFromString( "JTREE[inference=SUMPROD,updates=HUGIN" + maxmemstr + ",verbose=" + toString(ia_verbose) + "]", fgs[ev] );
+ } else if( solver == 2 ) { // the decent one
+ double remtime = (UAI_time - (toc() - starttic));
+ if( remtime < 1.0 )
+ remtime = 1.0;
+ double maxtime = 0.95 * remtime / (ev2go.size() - _ev);
+ if( verbose ) {
+ cout << " Past time: " << (toc() - starttic) << endl;
+ cout << " Remaining time:" << remtime << endl;
+ cout << " Allotted time: " << maxtime << endl;
+ }
+ if( task == "MPE" )
+ maxtime /= fgs[ev].nrVars();
+ string maxtimestr;
+ if( maxtime != INFINITY )
+ maxtimestr = ",maxtime=" + toString(maxtime);
+ if( task == "MPE" )
+ ia = newInfAlgFromString( "DECMAP[ianame=BP,iaopts=[inference=MAXPROD,updates=SEQRND,logdomain=1,tol=1e-9,maxiter=10000" + maxtimestr + ",damping=" + toString(MPEdamping) + ",verbose=0],reinit=1,verbose=" + toString(ia_verbose) + "]", fgs[ev] );
+ else {
+ if( couldBeGrid )
+ ia = newInfAlgFromString( "HAK[doubleloop=1,clusters=LOOP,init=UNIFORM,loopdepth=4,tol=1e-9" + maxtimestr + ",maxiter=100000,verbose=" + toString(ia_verbose) + "]", fgs[ev] );
+ else {
+ if( task == "PR" )
+ ia = newInfAlgFromString( "HAK[doubleloop=1,clusters=MIN,init=UNIFORM,tol=1e-9" + maxtimestr + ",maxiter=100000,verbose=" + toString(ia_verbose) + "]", fgs[ev] );
+ else
+ ia = newInfAlgFromString( "GIBBS[maxiter=1000000000,burnin=1000,restart=10000000" + maxtimestr + ",verbose=" + toString(ia_verbose) + "]", fgs[ev] );
+ }
+ }
+ }
+
+ // initialize
+ if( verbose )
+ cout << " Initializing inference algorithm..." << endl;
+ ia->init();
+ // run
+ if( verbose )
+ cout << " Running inference algorithm..." << endl;
+ ia->run();
+ if( verbose )
+ cout << " Inference algorithm finished..." << endl;
+ } catch( Exception &e ) {
+ failed = true;
+ if( verbose ) {
+ cout << " Inference algorithm failed...!" << endl;
+ cout << " Exception: " << e.what() << endl;
+ }
+ }
+
+ if( verbose )
+ cout << " Used time: " << toc() - tic << endl;
+ if( !failed && verbose ) {
+ try {
+ cout << " Number of iterations: " << ia->Iterations() << endl;
+ } catch( Exception &e ) {
+ cout << " Number of iterations: N/A" << endl;
+ }
+ try {
+ cout << " Final maxdiff: " << ia->maxDiff() << endl;
+ } catch( Exception &e ) {
+ cout << " Final maxdiff: N/A" << endl;
+ }
+ }
+
+ // update results for inference task
+ if( !failed ) {
+ if( task == "PR" ) {
+ PRbest cur;
+
+ // calculate PR value
+ cur.value = ia->logZ() / dai::log((Real)10.0);
+
+ // get maxdiff
+ try {
+ cur.maxdiff = ia->maxDiff();
+ } catch( Exception &e ) {
+ cur.maxdiff = 1e-9;
+ }
+
+ // only update if this run has converged
+ if( ((cur.maxdiff <= 1e-9) || (cur.maxdiff <= bestPR[ev].maxdiff)) && !dai::isnan(cur.value) ) {
+ // if this was exact inference, we are ready
+ if( solver == 1 ) {
+ ev2go.erase( ev2go.begin() + _ev );
+ _ev--;
+ cur.ready = true;
+ }
+
+ if( verbose )
+ cout << " Replacing best PR value so far (" << bestPR[ev].value << ") with new value " << cur.value << endl;
+ bestPR[ev] = cur;
+ improved = true;
+ } else {
+ if( verbose )
+ cout << " Discarding PR value " << cur.value << endl;
+ }
+ } else if( task == "MAR" ) {
+ MARbest cur;
+
+ // get variable beliefs
+ bool hasnans = false;
+ cur.beliefs.reserve( fgs[ev].nrVars() );
+ for( size_t i = 0; i < fgs[ev].nrVars(); i++ ) {
+ cur.beliefs.push_back( ia->beliefV(i) );
+ if( cur.beliefs.back().hasNaNs() )
+ hasnans = true;
+ }
+
+ // get maxdiff
+ try {
+ cur.maxdiff = ia->maxDiff();
+ } catch( Exception &e ) {
+ cur.maxdiff = 1e-9;
+ }
+
+ // only update if this run has converged
+ if( ((cur.maxdiff <= 1e-9) || (cur.maxdiff <= bestMAR[ev].maxdiff)) && !hasnans ) {
+ // if this was exact inference, we are ready
+ if( solver == 1 ) {
+ ev2go.erase( ev2go.begin() + _ev );
+ _ev--;
+ cur.ready = true;
+ }
+
+ if( verbose )
+ cout << " Replacing best beliefs so far with new beliefs" << endl;
+ bestMAR[ev] = cur;
+ improved = true;
+ } else {
+ if( verbose )
+ cout << " Discarding beliefs" << endl;
+ }
+ } else if( task == "MPE" ) {
+ MPEbest cur;
+
+ // calculate MPE state
+ cur.state = ia->findMaximum();
+
+ // calculate MPE value
+ cur.value = fgs[ev].logScore( cur.state );
+
+ // update best MPE state and value
+ if( cur.value > bestMPE[ev].value && !dai::isnan(cur.value) ) {
+ // if this was exact inference, we are ready
+ if( solver == 1 ) {
+ ev2go.erase( ev2go.begin() + _ev );
+ _ev--;
+ cur.ready = true;
+ }
+
+ if( verbose )
+ cout << " Replacing best MPE value so far (" << bestMPE[ev].value << ") with new value " << cur.value << endl;
+ bestMPE[ev] = cur;
+ improved = true;
+ } else {
+ if( verbose )
+ cout << " New MPE value " << cur.value << " not better than best one so far " << bestMPE[ev].value << endl;
+ }
+ }
+ }
+
+ // remove inference algorithm
+ if( verbose )
+ cout << " Cleaning up..." << endl;
+ if( !failed )
+ delete ia;
+
+ // write current best output to stream
+ if( improved ) {
+ if( verbose )
+ cout << " Writing output..." << endl;
+ if( first )
+ first = false;
+ else
+ os << "-BEGIN-" << endl;
+ os << evid.size() << endl;
+ for( size_t ev = 0; ev < evid.size(); ev++ ) {
+ if( task == "PR" ) {
+ // output probability of evidence
+ os << bestPR[ev].value << endl;
+ } else if( task == "MAR" ) {
+ // output variable marginals
+ os << bestMAR[ev].beliefs.size() << " ";
+ for( size_t i = 0; i < bestMAR[ev].beliefs.size(); i++ ) {
+ os << bestMAR[ev].beliefs[i].nrStates() << " ";
+ for( size_t s = 0; s < bestMAR[ev].beliefs[i].nrStates(); s++ )
+ os << bestMAR[ev].beliefs[i][s] << " ";
+ }
+ os << endl;
+ } else if( task == "MPE" ) {
+ // output MPE state
+ os << fgs[ev].nrVars() << " ";
+ for( size_t i = 0; i < fgs[ev].nrVars(); i++ )
+ os << bestMPE[ev].state[i] << " ";
+ os << endl;
+ }
+ }
+ os.flush();
+ }
+
+ if( verbose )
+ cout << " Done..." << endl;
+
+ if( !improved )
+ subsolver++;
+ if( improved || subsolver >= nrsubsolvers[solver] || couldBeGrid ) {
+ subsolver = 0;
+ _ev++;
+ }
+ }
+
+ if( task == "MPE" && solver == 2 && (toc() - starttic) < UAI_time && MPEdamping != 0.0 ) {
+ MPEdamping /= 2.0;
+ solver--; // repeat this one
+ }
+ if( ev2go.size() == 0 )
+ break;
+ }
+
+ // close output file
+ if( verbose )
+ cout << "Closing output file..." << endl;
+ os.close();
+
+ if( verbose )
+ cout << "Done!" << endl;
+ }
+
+ return 0;
+}
projects / libdai.git / commitdiff