577 lines
14 KiB
C++
577 lines
14 KiB
C++
#include <cassert>
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#include <algorithm>
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#include <iostream>
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#include <iomanip>
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#include <sstream>
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#include "BeliefProp.h"
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#include "Indexer.h"
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#include "Horus.h"
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namespace Horus {
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double BeliefProp::accuracy_ = 0.0001;
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unsigned BeliefProp::maxIter_ = 1000;
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BeliefProp::MsgSchedule BeliefProp::schedule_ =
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MsgSchedule::seqFixedSch;
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BeliefProp::BeliefProp (const FactorGraph& fg)
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: GroundSolver (fg), nIters_(0), runned_(false)
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{
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}
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BeliefProp::~BeliefProp()
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{
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for (size_t i = 0; i < links_.size(); i++) {
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delete links_[i];
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}
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links_.clear();
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}
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Params
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BeliefProp::solveQuery (VarIds queryVids)
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{
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assert (queryVids.empty() == false);
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return queryVids.size() == 1
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? getPosterioriOf (queryVids[0])
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: getJointDistributionOf (queryVids);
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}
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void
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BeliefProp::printSolverFlags() const
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{
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std::stringstream ss;
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ss << "belief propagation [" ;
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ss << "bp_msg_schedule=" ;
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switch (schedule_) {
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case MsgSchedule::seqFixedSch: ss << "seq_fixed"; break;
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case MsgSchedule::seqRandomSch: ss << "seq_random"; break;
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case MsgSchedule::parallelSch: ss << "parallel"; break;
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case MsgSchedule::maxResidualSch: ss << "max_residual"; break;
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}
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ss << ",bp_max_iter=" << Util::toString (maxIter_);
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ss << ",bp_accuracy=" << Util::toString (accuracy_);
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ss << ",log_domain=" << Util::toString (Globals::logDomain);
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ss << "]" ;
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std::cout << ss.str() << std::endl;
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}
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Params
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BeliefProp::getPosterioriOf (VarId vid)
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{
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if (runned_ == false) {
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runSolver();
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}
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assert (fg.getVarNode (vid));
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VarNode* var = fg.getVarNode (vid);
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Params probs;
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if (var->hasEvidence()) {
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probs.resize (var->range(), LogAware::noEvidence());
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probs[var->getEvidence()] = LogAware::withEvidence();
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} else {
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probs.resize (var->range(), LogAware::multIdenty());
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const BpLinks& links = getLinks (var);
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if (Globals::logDomain) {
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for (size_t i = 0; i < links.size(); i++) {
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probs += links[i]->message();
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}
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LogAware::normalize (probs);
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Util::exp (probs);
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} else {
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for (size_t i = 0; i < links.size(); i++) {
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probs *= links[i]->message();
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}
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LogAware::normalize (probs);
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}
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}
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return probs;
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}
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Params
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BeliefProp::getJointDistributionOf (const VarIds& jointVarIds)
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{
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if (runned_ == false) {
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runSolver();
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}
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VarNode* vn = fg.getVarNode (jointVarIds[0]);
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const FacNodes& facNodes = vn->neighbors();
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size_t idx = facNodes.size();
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for (size_t i = 0; i < facNodes.size(); i++) {
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if (facNodes[i]->factor().contains (jointVarIds)) {
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idx = i;
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break;
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}
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}
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if (idx == facNodes.size()) {
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return getJointByConditioning (jointVarIds);
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}
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return getFactorJoint (facNodes[idx], jointVarIds);
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}
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Params
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BeliefProp::getFactorJoint (
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FacNode* fn,
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const VarIds& jointVarIds)
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{
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if (runned_ == false) {
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runSolver();
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}
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Factor res (fn->factor());
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const BpLinks& links = getLinks( fn);
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for (size_t i = 0; i < links.size(); i++) {
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Factor msg ({links[i]->varNode()->varId()},
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{links[i]->varNode()->range()},
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getVarToFactorMsg (links[i]));
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res.multiply (msg);
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}
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res.sumOutAllExcept (jointVarIds);
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res.reorderArguments (jointVarIds);
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res.normalize();
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Params jointDist = res.params();
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if (Globals::logDomain) {
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Util::exp (jointDist);
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}
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return jointDist;
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}
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BeliefProp::BpLink::BpLink (FacNode* fn, VarNode* vn)
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{
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fac_ = fn;
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var_ = vn;
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v1_.resize (vn->range(), LogAware::log (1.0 / vn->range()));
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v2_.resize (vn->range(), LogAware::log (1.0 / vn->range()));
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currMsg_ = &v1_;
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nextMsg_ = &v2_;
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residual_ = 0.0;
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}
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void
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BeliefProp::BpLink::clearResidual()
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{
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residual_ = 0.0;
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}
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void
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BeliefProp::BpLink::updateResidual()
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{
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residual_ = LogAware::getMaxNorm (v1_, v2_);
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}
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void
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BeliefProp::BpLink::updateMessage()
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{
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swap (currMsg_, nextMsg_);
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}
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std::string
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BeliefProp::BpLink::toString() const
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{
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std::stringstream ss;
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ss << fac_->getLabel();
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ss << " -- " ;
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ss << var_->label();
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return ss.str();
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}
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void
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BeliefProp::calculateAndUpdateMessage (BpLink* link, bool calcResidual)
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{
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if (Globals::verbosity > 2) {
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std::cout << "calculating & updating " << link->toString();
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std::cout << std::endl;
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}
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calcFactorToVarMsg (link);
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if (calcResidual) {
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link->updateResidual();
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}
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link->updateMessage();
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}
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void
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BeliefProp::calculateMessage (BpLink* link, bool calcResidual)
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{
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if (Globals::verbosity > 2) {
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std::cout << "calculating " << link->toString();
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std::cout << std::endl;
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}
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calcFactorToVarMsg (link);
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if (calcResidual) {
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link->updateResidual();
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}
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}
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void
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BeliefProp::updateMessage (BpLink* link)
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{
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link->updateMessage();
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if (Globals::verbosity > 2) {
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std::cout << "updating " << link->toString();
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std::cout << std::endl;
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}
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}
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void
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BeliefProp::runSolver()
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{
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initializeSolver();
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nIters_ = 0;
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while (!converged() && nIters_ < maxIter_) {
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nIters_ ++;
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if (Globals::verbosity > 1) {
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Util::printHeader (std::string ("Iteration ")
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+ Util::toString (nIters_));
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}
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switch (schedule_) {
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case MsgSchedule::seqRandomSch:
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std::random_shuffle (links_.begin(), links_.end());
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// no break
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case MsgSchedule::seqFixedSch:
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for (size_t i = 0; i < links_.size(); i++) {
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calculateAndUpdateMessage (links_[i]);
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}
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break;
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case MsgSchedule::parallelSch:
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for (size_t i = 0; i < links_.size(); i++) {
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calculateMessage (links_[i]);
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}
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for (size_t i = 0; i < links_.size(); i++) {
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updateMessage(links_[i]);
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}
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break;
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case MsgSchedule::maxResidualSch:
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maxResidualSchedule();
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break;
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}
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}
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if (Globals::verbosity > 0) {
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if (nIters_ < maxIter_) {
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std::cout << "Belief propagation converged in " ;
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std::cout << nIters_ << " iterations" << std::endl;
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} else {
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std::cout << "The maximum number of iterations was hit," ;
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std::cout << " terminating..." ;
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std::cout << std::endl;
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}
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std::cout << std::endl;
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}
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runned_ = true;
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}
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void
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BeliefProp::createLinks()
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{
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const FacNodes& facNodes = fg.facNodes();
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for (size_t i = 0; i < facNodes.size(); i++) {
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const VarNodes& neighbors = facNodes[i]->neighbors();
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for (size_t j = 0; j < neighbors.size(); j++) {
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links_.push_back (new BpLink (facNodes[i], neighbors[j]));
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}
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}
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}
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void
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BeliefProp::maxResidualSchedule()
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{
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if (nIters_ == 1) {
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for (size_t i = 0; i < links_.size(); i++) {
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calculateMessage (links_[i]);
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SortedOrder::iterator it = sortedOrder_.insert (links_[i]);
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linkMap_.insert (make_pair (links_[i], it));
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}
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return;
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}
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for (size_t c = 0; c < links_.size(); c++) {
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if (Globals::verbosity > 1) {
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std::cout << "current residuals:" << std::endl;
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for (SortedOrder::iterator it = sortedOrder_.begin();
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it != sortedOrder_.end(); ++it) {
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std::cout << " " << std::setw (30) << std::left;
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std::cout << (*it)->toString();
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std::cout << "residual = " << (*it)->residual();
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std::cout << std::endl;
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}
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}
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SortedOrder::iterator it = sortedOrder_.begin();
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BpLink* link = *it;
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if (link->residual() < accuracy_) {
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return;
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}
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updateMessage (link);
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link->clearResidual();
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sortedOrder_.erase (it);
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linkMap_.find (link)->second = sortedOrder_.insert (link);
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// update the messages that depend on message source --> destin
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const FacNodes& factorNeighbors = link->varNode()->neighbors();
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for (size_t i = 0; i < factorNeighbors.size(); i++) {
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if (factorNeighbors[i] != link->facNode()) {
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const BpLinks& links = getLinks (factorNeighbors[i]);
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for (size_t j = 0; j < links.size(); j++) {
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if (links[j]->varNode() != link->varNode()) {
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calculateMessage (links[j]);
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BpLinkMap::iterator iter = linkMap_.find (links[j]);
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sortedOrder_.erase (iter->second);
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iter->second = sortedOrder_.insert (links[j]);
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}
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}
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}
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}
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if (Globals::verbosity > 1) {
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Util::printDashedLine();
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}
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}
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}
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void
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BeliefProp::calcFactorToVarMsg (BpLink* link)
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{
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FacNode* src = link->facNode();
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const VarNode* dst = link->varNode();
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const BpLinks& links = getLinks (src);
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// calculate the product of messages that were sent
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// to factor `src', except from var `dst'
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unsigned reps = 1;
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unsigned msgSize = Util::sizeExpected (src->factor().ranges());
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Params msgProduct (msgSize, LogAware::multIdenty());
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if (Globals::logDomain) {
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for (size_t i = links.size(); i-- > 0; ) {
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if (links[i]->varNode() != dst) {
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if (Constants::showBpCalcs) {
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std::cout << " message from " << links[i]->varNode()->label();
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std::cout << ": " ;
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}
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Util::apply_n_times (msgProduct, getVarToFactorMsg (links[i]),
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reps, std::plus<double>());
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if (Constants::showBpCalcs) {
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std::cout << std::endl;
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}
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}
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reps *= links[i]->varNode()->range();
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}
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} else {
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for (size_t i = links.size(); i-- > 0; ) {
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if (links[i]->varNode() != dst) {
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if (Constants::showBpCalcs) {
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std::cout << " message from " << links[i]->varNode()->label();
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std::cout << ": " ;
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}
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Util::apply_n_times (msgProduct, getVarToFactorMsg (links[i]),
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reps, std::multiplies<double>());
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if (Constants::showBpCalcs) {
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std::cout << std::endl;
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}
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}
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reps *= links[i]->varNode()->range();
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}
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}
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Factor result (src->factor().arguments(),
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src->factor().ranges(), msgProduct);
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result.multiply (src->factor());
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if (Constants::showBpCalcs) {
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std::cout << " message product: " << msgProduct << std::endl;
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std::cout << " original factor: " << src->factor().params();
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std::cout << std::endl;
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std::cout << " factor product: " << result.params() << std::endl;
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}
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result.sumOutAllExcept (dst->varId());
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if (Constants::showBpCalcs) {
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std::cout << " marginalized: " << result.params() << std::endl;
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}
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link->nextMessage() = result.params();
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LogAware::normalize (link->nextMessage());
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if (Constants::showBpCalcs) {
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std::cout << " curr msg: " << link->message() << std::endl;
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std::cout << " next msg: " << link->nextMessage() << std::endl;
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}
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}
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Params
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BeliefProp::getVarToFactorMsg (const BpLink* link)
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{
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const VarNode* src = link->varNode();
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Params msg;
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if (src->hasEvidence()) {
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msg.resize (src->range(), LogAware::noEvidence());
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msg[src->getEvidence()] = LogAware::withEvidence();
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} else {
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msg.resize (src->range(), LogAware::one());
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}
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if (Constants::showBpCalcs) {
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std::cout << msg;
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}
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BpLinks::const_iterator it;
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const BpLinks& links = getLinks (src);
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if (Globals::logDomain) {
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for (it = links.begin(); it != links.end(); ++it) {
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if (*it != link) {
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msg += (*it)->message();
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}
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if (Constants::showBpCalcs) {
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std::cout << " x " << (*it)->message();
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}
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}
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} else {
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for (it = links.begin(); it != links.end(); ++it) {
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if (*it != link) {
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msg *= (*it)->message();
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}
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if (Constants::showBpCalcs) {
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std::cout << " x " << (*it)->message();
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}
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}
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}
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if (Constants::showBpCalcs) {
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std::cout << " = " << msg;
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}
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return msg;
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}
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Params
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BeliefProp::getJointByConditioning (const VarIds& jointVarIds) const
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{
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return GroundSolver::getJointByConditioning (
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GroundSolverType::bpSolver, fg, jointVarIds);
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}
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void
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BeliefProp::initializeSolver()
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{
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const VarNodes& varNodes = fg.varNodes();
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varsLinks_.reserve (varNodes.size());
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for (size_t i = 0; i < varNodes.size(); i++) {
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varsLinks_.push_back (BpLinks());
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}
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const FacNodes& facNodes = fg.facNodes();
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facsLinks_.reserve (facNodes.size());
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for (size_t i = 0; i < facNodes.size(); i++) {
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facsLinks_.push_back (BpLinks());
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}
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createLinks();
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for (size_t i = 0; i < links_.size(); i++) {
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FacNode* src = links_[i]->facNode();
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VarNode* dst = links_[i]->varNode();
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getLinks (dst).push_back (links_[i]);
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getLinks (src).push_back (links_[i]);
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}
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}
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bool
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BeliefProp::converged()
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{
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if (links_.empty()) {
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return true;
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}
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if (nIters_ == 0) {
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return false;
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}
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if (Globals::verbosity > 2) {
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std::cout << std::endl;
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}
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if (nIters_ == 1) {
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if (Globals::verbosity > 1) {
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std::cout << "no residuals" << std::endl << std::endl;
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}
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return false;
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}
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bool converged = true;
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if (schedule_ == MsgSchedule::maxResidualSch) {
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double maxResidual = (*(sortedOrder_.begin()))->residual();
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if (maxResidual > accuracy_) {
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converged = false;
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} else {
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converged = true;
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}
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} else {
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for (size_t i = 0; i < links_.size(); i++) {
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double residual = links_[i]->residual();
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if (Globals::verbosity > 1) {
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std::cout << links_[i]->toString() + " residual = " << residual;
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std::cout << std::endl;
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}
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if (residual > accuracy_) {
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converged = false;
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if (Globals::verbosity < 2) {
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break;
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}
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}
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}
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if (Globals::verbosity > 1) {
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std::cout << std::endl;
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}
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}
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return converged;
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}
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void
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BeliefProp::printLinkInformation() const
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{
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using std::cout;
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using std::endl;
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for (size_t i = 0; i < links_.size(); i++) {
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BpLink* l = links_[i];
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cout << l->toString() << ":" << endl;
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cout << " curr msg = " ;
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cout << l->message() << endl;
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cout << " next msg = " ;
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cout << l->nextMessage() << endl;
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cout << " residual = " << l->residual() << endl;
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}
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}
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} // namespace Horus
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