This repository has been archived on 2023-08-20. You can view files and clone it, but cannot push or open issues or pull requests.
yap-6.3/packages/CLPBN/clpbn/bp/Util.cpp
2011-12-12 15:29:51 +00:00

479 lines
11 KiB
C++

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