479 lines
11 KiB
C++
479 lines
11 KiB
C++
#include <sstream>
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#include "BayesNet.h"
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#include "VarNode.h"
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#include "Shared.h"
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#include "StatesIndexer.h"
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namespace InfAlgorithms {
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InfAlgs infAlgorithm = InfAlgorithms::VE;
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//InfAlgs infAlgorithm = InfAlgorithms::BN_BP;
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//InfAlgs infAlgorithm = InfAlgorithms::FG_BP;
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//InfAlgs infAlgorithm = InfAlgorithms::CBP;
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}
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namespace BpOptions {
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Schedule schedule = BpOptions::Schedule::SEQ_FIXED;
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//Schedule schedule = BpOptions::Schedule::SEQ_RANDOM;
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//Schedule schedule = BpOptions::Schedule::PARALLEL;
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//Schedule schedule = BpOptions::Schedule::MAX_RESIDUAL;
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double accuracy = 0.0001;
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unsigned maxIter = 1000;
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bool useAlwaysLoopySolver = true;
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}
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NumberSpace::ns NSPACE = NumberSpace::NORMAL;
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unordered_map<VarId,VariableInfo> GraphicalModel::varsInfo_;
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vector<NetInfo> Statistics::netInfo_;
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vector<CompressInfo> Statistics::compressInfo_;
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unsigned Statistics::primaryNetCount_;
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namespace Util {
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void
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toLog (ParamSet& v)
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{
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for (unsigned i = 0; i < v.size(); i++) {
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v[i] = log (v[i]);
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}
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}
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void
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fromLog (ParamSet& v)
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{
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for (unsigned i = 0; i < v.size(); i++) {
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v[i] = exp (v[i]);
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}
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}
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void
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normalize (ParamSet& v)
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{
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double sum;
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switch (NSPACE) {
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case NumberSpace::NORMAL:
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sum = 0.0;
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for (unsigned i = 0; i < v.size(); i++) {
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sum += v[i];
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}
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assert (sum != 0.0);
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for (unsigned i = 0; i < v.size(); i++) {
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v[i] /= sum;
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}
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break;
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case NumberSpace::LOGARITHM:
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sum = addIdenty();
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for (unsigned i = 0; i < v.size(); i++) {
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logSum (sum, v[i]);
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}
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assert (sum != -numeric_limits<Param>::infinity());
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for (unsigned i = 0; i < v.size(); i++) {
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v[i] -= sum;
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}
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}
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}
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void
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pow (ParamSet& v, unsigned expoent)
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{
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if (expoent == 1) {
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return; // optimization
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}
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switch (NSPACE) {
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case NumberSpace::NORMAL:
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for (unsigned i = 0; i < v.size(); i++) {
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double value = 1.0;
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for (unsigned j = 0; j < expoent; j++) {
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value *= v[i];
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}
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v[i] = value;
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}
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break;
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case NumberSpace::LOGARITHM:
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for (unsigned i = 0; i < v.size(); i++) {
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v[i] *= expoent;
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}
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}
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}
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Param
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pow (Param p, unsigned expoent)
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{
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double value = 1.0;
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switch (NSPACE) {
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case NumberSpace::NORMAL:
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for (unsigned i = 0; i < expoent; i++) {
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value *= p;
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}
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break;
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case NumberSpace::LOGARITHM:
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value = p * expoent;
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}
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return value;
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}
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double
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getL1Distance (const ParamSet& v1, const ParamSet& v2)
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{
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assert (v1.size() == v2.size());
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double dist = 0.0;
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switch (NSPACE) {
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case NumberSpace::NORMAL:
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for (unsigned i = 0; i < v1.size(); i++) {
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dist += abs (v1[i] - v2[i]);
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}
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break;
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case NumberSpace::LOGARITHM:
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for (unsigned i = 0; i < v1.size(); i++) {
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dist += abs (exp(v1[i]) - exp(v2[i]));
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}
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}
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return dist;
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}
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double
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getMaxNorm (const ParamSet& v1, const ParamSet& v2)
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{
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assert (v1.size() == v2.size());
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double max = 0.0;
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switch (NSPACE) {
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case NumberSpace::NORMAL:
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for (unsigned i = 0; i < v1.size(); i++) {
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double diff = abs (v1[i] - v2[i]);
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if (diff > max) {
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max = diff;
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}
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}
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break;
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case NumberSpace::LOGARITHM:
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for (unsigned i = 0; i < v1.size(); i++) {
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double diff = abs (exp(v1[i]) - exp(v2[i]));
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if (diff > max) {
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max = diff;
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}
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}
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}
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return max;
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}
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unsigned
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getNumberOfDigits (int number) {
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unsigned count = 1;
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while (number >= 10) {
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number /= 10;
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count ++;
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}
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return count;
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}
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bool
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isInteger (const string& s)
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{
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stringstream ss1 (s);
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stringstream ss2;
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int integer;
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ss1 >> integer;
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ss2 << integer;
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return (ss1.str() == ss2.str());
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}
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string
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parametersToString (const ParamSet& v, unsigned precision)
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{
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stringstream ss;
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ss.precision (precision);
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ss << "[" ;
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for (unsigned i = 0; i < v.size() - 1; i++) {
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ss << v[i] << ", " ;
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}
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if (v.size() != 0) {
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ss << v[v.size() - 1];
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}
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ss << "]" ;
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return ss.str();
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}
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BayesNet*
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generateBayesianNetworkTreeWithLevel (unsigned level)
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{
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BayesNet* bn = new BayesNet();
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Distribution* dist = new Distribution (ParamSet() = {0.1, 0.5, 0.2, 0.7});
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BayesNode* root = bn->addNode (0, 2, -1, BnNodeSet() = {},
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new Distribution (ParamSet() = {0.1, 0.5}));
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BnNodeSet prevLevel = { root };
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BnNodeSet currLevel;
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VarId vidCount = 1;
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for (unsigned l = 1; l < level; l++) {
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currLevel.clear();
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for (unsigned i = 0; i < prevLevel.size(); i++) {
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currLevel.push_back (
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bn->addNode (vidCount, 2, -1, BnNodeSet() = {prevLevel[i]}, dist));
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vidCount ++;
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currLevel.push_back (
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bn->addNode (vidCount, 2, -1, BnNodeSet() = {prevLevel[i]}, dist));
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vidCount ++;
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}
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prevLevel = currLevel;
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}
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for (unsigned i = 0; i < prevLevel.size(); i++) {
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prevLevel[i]->setEvidence (0);
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}
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bn->setIndexes();
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return bn;
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}
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vector<DConf>
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getDomainConfigurations (const VarNodes& vars)
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{
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// TODO this method must die
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unsigned nConfs = 1;
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for (unsigned i = 0; i < vars.size(); i++) {
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nConfs *= vars[i]->nrStates();
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}
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vector<DConf> confs (nConfs);
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for (unsigned i = 0; i < nConfs; i++) {
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confs[i].resize (vars.size());
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}
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unsigned nReps = 1;
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for (int i = vars.size() - 1; i >= 0; i--) {
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unsigned index = 0;
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while (index < nConfs) {
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for (unsigned j = 0; j < vars[i]->nrStates(); j++) {
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for (unsigned r = 0; r < nReps; r++) {
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confs[index][i] = j;
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index++;
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}
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}
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}
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nReps *= vars[i]->nrStates();
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}
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return confs;
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}
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vector<string>
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getJointStateStrings (const VarNodes& vars)
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{
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StatesIndexer idx (vars);
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vector<string> jointStrings;
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while (idx.valid()) {
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stringstream ss;
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for (unsigned i = 0; i < vars.size(); i++) {
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if (i != 0) ss << ", " ;
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ss << vars[i]->label() << "=" << vars[i]->states()[(idx[i])];
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}
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jointStrings.push_back (ss.str());
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++ idx;
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}
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return jointStrings;
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}
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}
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unsigned
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Statistics::getSolvedNetworksCounting (void)
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{
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return netInfo_.size();
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}
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void
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Statistics::incrementPrimaryNetworksCounting (void)
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{
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primaryNetCount_ ++;
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}
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unsigned
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Statistics::getPrimaryNetworksCounting (void)
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{
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return primaryNetCount_;
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}
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void
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Statistics::updateStatistics (unsigned size, bool loopy,
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unsigned nIters, double time)
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{
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netInfo_.push_back (NetInfo (size, loopy, nIters, time));
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}
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void
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Statistics::printStatistics (void)
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{
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cout << getStatisticString();
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}
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void
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Statistics::writeStatisticsToFile (const char* fileName)
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{
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ofstream out (fileName);
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if (!out.is_open()) {
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cerr << "error: cannot open file to write at " ;
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cerr << "Statistics::writeStatisticsToFile()" << endl;
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abort();
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}
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out << getStatisticString();
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out.close();
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}
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void
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Statistics::updateCompressingStatistics (unsigned nGroundVars,
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unsigned nGroundFactors,
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unsigned nClusterVars,
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unsigned nClusterFactors,
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unsigned nWithoutNeighs) {
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compressInfo_.push_back (CompressInfo (nGroundVars, nGroundFactors,
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nClusterVars, nClusterFactors, nWithoutNeighs));
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}
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string
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Statistics::getStatisticString (void)
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{
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stringstream ss2, ss3, ss4, ss1;
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ss1 << "running mode: " ;
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switch (InfAlgorithms::infAlgorithm) {
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case InfAlgorithms::VE: ss1 << "ve" << endl; break;
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case InfAlgorithms::BN_BP: ss1 << "bn_bp" << endl; break;
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case InfAlgorithms::FG_BP: ss1 << "fg_bp" << endl; break;
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case InfAlgorithms::CBP: ss1 << "cbp" << endl; break;
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}
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ss1 << "message schedule: " ;
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switch (BpOptions::schedule) {
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case BpOptions::Schedule::SEQ_FIXED: ss1 << "sequential fixed" << endl; break;
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case BpOptions::Schedule::SEQ_RANDOM: ss1 << "sequential random" << endl; break;
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case BpOptions::Schedule::PARALLEL: ss1 << "parallel" << endl; break;
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case BpOptions::Schedule::MAX_RESIDUAL: ss1 << "max residual" << endl; break;
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}
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ss1 << "max iterations: " << BpOptions::maxIter << endl;
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ss1 << "accuracy " << BpOptions::accuracy << endl;
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if (BpOptions::useAlwaysLoopySolver) {
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ss1 << "always loopy solver: yes" << endl;
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} else {
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ss1 << "always loopy solver: no" << endl;
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}
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ss1 << endl << endl;
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ss2 << "---------------------------------------------------" << endl;
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ss2 << " Network information" << endl;
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ss2 << "---------------------------------------------------" << endl;
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ss2 << left;
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ss2 << setw (15) << "Network Size" ;
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ss2 << setw (9) << "Loopy" ;
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ss2 << setw (15) << "Iterations" ;
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ss2 << setw (15) << "Solving Time" ;
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ss2 << endl;
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unsigned nLoopyNets = 0;
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unsigned nUnconvergedRuns = 0;
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double totalSolvingTime = 0.0;
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for (unsigned i = 0; i < netInfo_.size(); i++) {
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ss2 << setw (15) << netInfo_[i].size;
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if (netInfo_[i].loopy) {
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ss2 << setw (9) << "yes";
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nLoopyNets ++;
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} else {
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ss2 << setw (9) << "no";
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}
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if (netInfo_[i].nIters == 0) {
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ss2 << setw (15) << "n/a" ;
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} else {
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ss2 << setw (15) << netInfo_[i].nIters;
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if (netInfo_[i].nIters > BpOptions::maxIter) {
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nUnconvergedRuns ++;
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}
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}
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ss2 << setw (15) << netInfo_[i].time;
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totalSolvingTime += netInfo_[i].time;
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ss2 << endl;
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}
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ss2 << endl << endl;
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unsigned c1 = 0, c2 = 0, c3 = 0, c4 = 0;
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if (compressInfo_.size() > 0) {
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ss3 << "---------------------------------------------------" << endl;
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ss3 << " Compression information" << endl;
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ss3 << "---------------------------------------------------" << endl;
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ss3 << left;
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ss3 << "Ground Cluster Ground Cluster Neighborless" << endl;
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ss3 << "Vars Vars Factors Factors Vars" << endl;
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for (unsigned i = 0; i < compressInfo_.size(); i++) {
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ss3 << setw (9) << compressInfo_[i].nGroundVars;
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ss3 << setw (10) << compressInfo_[i].nClusterVars;
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ss3 << setw (10) << compressInfo_[i].nGroundFactors;
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ss3 << setw (10) << compressInfo_[i].nClusterFactors;
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ss3 << setw (10) << compressInfo_[i].nWithoutNeighs;
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ss3 << endl;
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c1 += compressInfo_[i].nGroundVars - compressInfo_[i].nWithoutNeighs;
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c2 += compressInfo_[i].nClusterVars;
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c3 += compressInfo_[i].nGroundFactors - compressInfo_[i].nWithoutNeighs;
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c4 += compressInfo_[i].nClusterFactors;
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if (compressInfo_[i].nWithoutNeighs != 0) {
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c2 --;
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c4 --;
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}
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}
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ss3 << endl << endl;
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}
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ss4 << "primary networks: " << primaryNetCount_ << endl;
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ss4 << "solved networks: " << netInfo_.size() << endl;
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ss4 << "loopy networks: " << nLoopyNets << endl;
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ss4 << "unconverged runs: " << nUnconvergedRuns << endl;
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ss4 << "total solving time: " << totalSolvingTime << endl;
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if (compressInfo_.size() > 0) {
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double pc1 = (1.0 - (c2 / (double)c1)) * 100.0;
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double pc2 = (1.0 - (c4 / (double)c3)) * 100.0;
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ss4 << setprecision (5);
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ss4 << "variable compression: " << pc1 << "%" << endl;
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ss4 << "factor compression: " << pc2 << "%" << endl;
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}
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ss4 << endl << endl;
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ss1 << ss4.str() << ss2.str() << ss3.str();
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return ss1.str();
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}
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