318 lines
10 KiB
C++
318 lines
10 KiB
C++
#include <cstdlib>
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#include <vector>
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#include <iostream>
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#include <sstream>
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#include <YapInterface.h>
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#include "BayesNet.h"
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#include "FactorGraph.h"
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#include "VarElimSolver.h"
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#include "BnBpSolver.h"
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#include "FgBpSolver.h"
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#include "CbpSolver.h"
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#include "ElimGraph.h"
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using namespace std;
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int
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createNetwork (void)
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{
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Statistics::incrementPrimaryNetworksCounting();
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// cout << "creating network number " ;
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// cout << Statistics::getPrimaryNetworksCounting() << endl;
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// if (Statistics::getPrimaryNetworksCounting() > 98) {
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// Statistics::writeStatisticsToFile ("../../compressing.stats");
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// }
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BayesNet* bn = new BayesNet();
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YAP_Term varList = YAP_ARG1;
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BnNodeSet nodes;
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vector<VarIdSet> parents;
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while (varList != YAP_TermNil()) {
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YAP_Term var = YAP_HeadOfTerm (varList);
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VarId vid = (VarId) YAP_IntOfTerm (YAP_ArgOfTerm (1, var));
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unsigned dsize = (unsigned) YAP_IntOfTerm (YAP_ArgOfTerm (2, var));
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int evidence = (int) YAP_IntOfTerm (YAP_ArgOfTerm (3, var));
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YAP_Term parentL = YAP_ArgOfTerm (4, var);
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unsigned distId = (unsigned) YAP_IntOfTerm (YAP_ArgOfTerm (5, var));
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parents.push_back (VarIdSet());
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while (parentL != YAP_TermNil()) {
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unsigned parentId = (unsigned) YAP_IntOfTerm (YAP_HeadOfTerm (parentL));
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parents.back().push_back (parentId);
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parentL = YAP_TailOfTerm (parentL);
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}
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Distribution* dist = bn->getDistribution (distId);
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if (!dist) {
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dist = new Distribution (distId);
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bn->addDistribution (dist);
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}
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assert (bn->getBayesNode (vid) == 0);
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nodes.push_back (bn->addNode (vid, dsize, evidence, dist));
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varList = YAP_TailOfTerm (varList);
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}
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for (unsigned i = 0; i < nodes.size(); i++) {
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BnNodeSet ps;
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for (unsigned j = 0; j < parents[i].size(); j++) {
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assert (bn->getBayesNode (parents[i][j]) != 0);
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ps.push_back (bn->getBayesNode (parents[i][j]));
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}
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nodes[i]->setParents (ps);
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}
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bn->setIndexes();
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YAP_Int p = (YAP_Int) (bn);
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return YAP_Unify (YAP_MkIntTerm (p), YAP_ARG2);
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}
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int
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setExtraVarsInfo (void)
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{
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// BayesNet* bn = (BayesNet*) YAP_IntOfTerm (YAP_ARG1);
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GraphicalModel::clearVariablesInformation();
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YAP_Term varsInfoL = YAP_ARG2;
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while (varsInfoL != YAP_TermNil()) {
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YAP_Term head = YAP_HeadOfTerm (varsInfoL);
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VarId vid = YAP_IntOfTerm (YAP_ArgOfTerm (1, head));
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YAP_Atom label = YAP_AtomOfTerm (YAP_ArgOfTerm (2, head));
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YAP_Term statesL = YAP_ArgOfTerm (3, head);
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States states;
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while (statesL != YAP_TermNil()) {
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YAP_Atom atom = YAP_AtomOfTerm (YAP_HeadOfTerm (statesL));
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states.push_back ((char*) YAP_AtomName (atom));
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statesL = YAP_TailOfTerm (statesL);
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}
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GraphicalModel::addVariableInformation (vid,
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(char*) YAP_AtomName (label), states);
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varsInfoL = YAP_TailOfTerm (varsInfoL);
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}
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return TRUE;
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}
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int
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setParameters (void)
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{
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BayesNet* bn = (BayesNet*) YAP_IntOfTerm (YAP_ARG1);
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YAP_Term distList = YAP_ARG2;
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while (distList != YAP_TermNil()) {
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YAP_Term dist = YAP_HeadOfTerm (distList);
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unsigned distId = (unsigned) YAP_IntOfTerm (YAP_ArgOfTerm (1, dist));
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YAP_Term paramL = YAP_ArgOfTerm (2, dist);
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ParamSet params;
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while (paramL!= YAP_TermNil()) {
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params.push_back ((double) YAP_FloatOfTerm (YAP_HeadOfTerm (paramL)));
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paramL = YAP_TailOfTerm (paramL);
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}
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if (NSPACE == NumberSpace::LOGARITHM) {
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Util::toLog (params);
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}
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bn->getDistribution(distId)->updateParameters (params);
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distList = YAP_TailOfTerm (distList);
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}
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return TRUE;
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}
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int
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runSolver (void)
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{
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BayesNet* bn = (BayesNet*) YAP_IntOfTerm (YAP_ARG1);
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YAP_Term taskList = YAP_ARG2;
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vector<VarIdSet> tasks;
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std::set<VarId> vids;
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while (taskList != YAP_TermNil()) {
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if (YAP_IsPairTerm (YAP_HeadOfTerm (taskList))) {
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tasks.push_back (VarIdSet());
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YAP_Term jointList = YAP_HeadOfTerm (taskList);
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while (jointList != YAP_TermNil()) {
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VarId vid = (unsigned) YAP_IntOfTerm (YAP_HeadOfTerm (jointList));
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assert (bn->getBayesNode (vid));
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tasks.back().push_back (vid);
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vids.insert (vid);
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jointList = YAP_TailOfTerm (jointList);
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}
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} else {
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VarId vid = (unsigned) YAP_IntOfTerm (YAP_HeadOfTerm (taskList));
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assert (bn->getBayesNode (vid));
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tasks.push_back (VarIdSet() = {vid});
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vids.insert (vid);
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}
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taskList = YAP_TailOfTerm (taskList);
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}
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Solver* bpSolver = 0;
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GraphicalModel* graphicalModel = 0;
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CFactorGraph::disableCheckForIdenticalFactors();
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if (InfAlgorithms::infAlgorithm != InfAlgorithms::VE) {
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BayesNet* mrn = bn->getMinimalRequesiteNetwork (
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VarIdSet (vids.begin(), vids.end()));
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if (InfAlgorithms::infAlgorithm == InfAlgorithms::BN_BP) {
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graphicalModel = mrn;
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bpSolver = new BnBpSolver (*static_cast<BayesNet*> (graphicalModel));
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} else if (InfAlgorithms::infAlgorithm == InfAlgorithms::FG_BP) {
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graphicalModel = new FactorGraph (*mrn);
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bpSolver = new FgBpSolver (*static_cast<FactorGraph*> (graphicalModel));
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delete mrn;
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} else if (InfAlgorithms::infAlgorithm == InfAlgorithms::CBP) {
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graphicalModel = new FactorGraph (*mrn);
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bpSolver = new CbpSolver (*static_cast<FactorGraph*> (graphicalModel));
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delete mrn;
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}
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bpSolver->runSolver();
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}
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vector<ParamSet> results;
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results.reserve (tasks.size());
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for (unsigned i = 0; i < tasks.size(); i++) {
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//if (i == 1) exit (0);
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if (InfAlgorithms::infAlgorithm == InfAlgorithms::VE) {
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BayesNet* mrn = bn->getMinimalRequesiteNetwork (tasks[i]);
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VarElimSolver* veSolver = new VarElimSolver (*mrn);
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if (tasks[i].size() == 1) {
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results.push_back (veSolver->getPosterioriOf (tasks[i][0]));
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} else {
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results.push_back (veSolver->getJointDistributionOf (tasks[i]));
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}
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delete mrn;
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delete veSolver;
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} else {
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if (tasks[i].size() == 1) {
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results.push_back (bpSolver->getPosterioriOf (tasks[i][0]));
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} else {
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results.push_back (bpSolver->getJointDistributionOf (tasks[i]));
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}
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}
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}
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delete bpSolver;
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delete graphicalModel;
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YAP_Term list = YAP_TermNil();
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for (int i = results.size() - 1; i >= 0; i--) {
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const ParamSet& beliefs = results[i];
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YAP_Term queryBeliefsL = YAP_TermNil();
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for (int j = beliefs.size() - 1; j >= 0; j--) {
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YAP_Int sl1 = YAP_InitSlot (list);
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YAP_Term belief = YAP_MkFloatTerm (beliefs[j]);
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queryBeliefsL = YAP_MkPairTerm (belief, queryBeliefsL);
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list = YAP_GetFromSlot (sl1);
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YAP_RecoverSlots (1);
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}
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list = YAP_MkPairTerm (queryBeliefsL, list);
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}
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return YAP_Unify (list, YAP_ARG3);
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}
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int
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setSolverParameter (void)
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{
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string key ((char*) YAP_AtomName (YAP_AtomOfTerm (YAP_ARG1)));
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if (key == "inf_alg") {
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string value ((char*) YAP_AtomName (YAP_AtomOfTerm (YAP_ARG2)));
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if ( value == "ve") {
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InfAlgorithms::infAlgorithm = InfAlgorithms::VE;
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} else if (value == "bn_bp") {
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InfAlgorithms::infAlgorithm = InfAlgorithms::BN_BP;
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} else if (value == "fg_bp") {
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InfAlgorithms::infAlgorithm = InfAlgorithms::FG_BP;
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} else if (value == "cbp") {
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InfAlgorithms::infAlgorithm = InfAlgorithms::CBP;
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} else {
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cerr << "warning: invalid value `" << value << "' " ;
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cerr << "for `" << key << "'" << endl;
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return FALSE;
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}
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} else if (key == "elim_heuristic") {
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string value ((char*) YAP_AtomName (YAP_AtomOfTerm (YAP_ARG2)));
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if ( value == "min_neighbors") {
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ElimGraph::setEliminationHeuristic (ElimHeuristic::MIN_NEIGHBORS);
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} else if (value == "min_weight") {
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ElimGraph::setEliminationHeuristic (ElimHeuristic::MIN_WEIGHT);
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} else if (value == "min_fill") {
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ElimGraph::setEliminationHeuristic (ElimHeuristic::MIN_FILL);
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} else if (value == "weighted_min_fill") {
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ElimGraph::setEliminationHeuristic (ElimHeuristic::WEIGHTED_MIN_FILL);
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} else {
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cerr << "warning: invalid value `" << value << "' " ;
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cerr << "for `" << key << "'" << endl;
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return FALSE;
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}
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} else if (key == "schedule") {
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string value ((char*) YAP_AtomName (YAP_AtomOfTerm (YAP_ARG2)));
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if ( value == "seq_fixed") {
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BpOptions::schedule = BpOptions::Schedule::SEQ_FIXED;
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} else if (value == "seq_random") {
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BpOptions::schedule = BpOptions::Schedule::SEQ_RANDOM;
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} else if (value == "parallel") {
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BpOptions::schedule = BpOptions::Schedule::PARALLEL;
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} else if (value == "max_residual") {
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BpOptions::schedule = BpOptions::Schedule::MAX_RESIDUAL;
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} else {
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cerr << "warning: invalid value `" << value << "' " ;
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cerr << "for `" << key << "'" << endl;
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return FALSE;
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}
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} else if (key == "accuracy") {
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BpOptions::accuracy = (double) YAP_FloatOfTerm (YAP_ARG2);
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} else if (key == "max_iter") {
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BpOptions::maxIter = (int) YAP_IntOfTerm (YAP_ARG2);
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} else if (key == "always_loopy_solver") {
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string value ((char*) YAP_AtomName (YAP_AtomOfTerm (YAP_ARG2)));
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if (value == "true") {
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BpOptions::useAlwaysLoopySolver = true;
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} else if (value == "false") {
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BpOptions::useAlwaysLoopySolver = false;
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} else {
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cerr << "warning: invalid value `" << value << "' " ;
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cerr << "for `" << key << "'" << endl;
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return FALSE;
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}
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} else {
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cerr << "warning: invalid key `" << key << "'" << endl;
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return FALSE;
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}
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return TRUE;
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}
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int useLogSpace (void)
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{
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NSPACE = NumberSpace::LOGARITHM;
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return TRUE;
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}
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int
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freeBayesNetwork (void)
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{
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//Statistics::writeStatisticsToFile ("stats.txt");
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BayesNet* bn = (BayesNet*) YAP_IntOfTerm (YAP_ARG1);
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bn->freeDistributions();
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delete bn;
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return TRUE;
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}
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extern "C" void
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init_predicates (void)
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{
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YAP_UserCPredicate ("create_network", createNetwork, 2);
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YAP_UserCPredicate ("set_extra_vars_info", setExtraVarsInfo, 2);
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YAP_UserCPredicate ("set_parameters", setParameters, 2);
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YAP_UserCPredicate ("run_solver", runSolver, 3);
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YAP_UserCPredicate ("set_solver_parameter", setSolverParameter, 2);
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YAP_UserCPredicate ("use_log_space", useLogSpace, 0);
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YAP_UserCPredicate ("free_bayesian_network", freeBayesNetwork, 1);
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}
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