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yap-6.3/packages/CLPBN/horus/Util.cpp

433 lines
8.9 KiB
C++

#include <fstream>
#include "Util.h"
#include "Indexer.h"
#include "ElimGraph.h"
#include "BeliefProp.h"
namespace Globals {
bool logDomain = false;
unsigned verbosity = 0;
LiftedSolverType liftedSolver = LiftedSolverType::LVE;
GroundSolverType groundSolver = GroundSolverType::VE;
};
namespace Util {
template <> std::string
toString (const bool& b)
{
std::stringstream ss;
ss << std::boolalpha << b;
return ss.str();
}
unsigned
stringToUnsigned (string str)
{
int val;
stringstream ss;
ss << str;
ss >> val;
if (val < 0) {
cerr << "Error: the number readed is negative." << endl;
exit (EXIT_FAILURE);
}
return static_cast<unsigned> (val);
}
double
stringToDouble (string str)
{
double val;
stringstream ss;
ss << str;
ss >> val;
return val;
}
double
factorial (unsigned num)
{
double result = 1.0;
for (unsigned i = 1; i <= num; i++) {
result *= i;
}
return result;
}
double
logFactorial (unsigned num)
{
double result = 0.0;
if (num < 150) {
result = std::log (factorial (num));
} else {
for (unsigned i = 1; i <= num; i++) {
result += std::log (i);
}
}
return result;
}
unsigned
nrCombinations (unsigned n, unsigned k)
{
assert (n >= k);
int diff = n - k;
unsigned result = 0;
if (n < 150) {
unsigned prod = 1;
for (int i = n; i > diff; i--) {
prod *= i;
}
result = prod / factorial (k);
} else {
double prod = 0.0;
for (int i = n; i > diff; i--) {
prod += std::log (i);
}
prod -= logFactorial (k);
result = static_cast<unsigned> (std::exp (prod));
}
return result;
}
size_t
sizeExpected (const Ranges& ranges)
{
return std::accumulate (ranges.begin(),
ranges.end(), 1, multiplies<unsigned>());
}
unsigned
nrDigits (int num)
{
unsigned count = 1;
while (num >= 10) {
num /= 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 Params& v, unsigned precision)
{
stringstream ss;
ss.precision (precision);
ss << "[" ;
for (size_t i = 0; i < v.size(); i++) {
if (i != 0) ss << ", " ;
ss << v[i];
}
ss << "]" ;
return ss.str();
}
vector<string>
getStateLines (const Vars& vars)
{
Ranges ranges;
for (size_t i = 0; i < vars.size(); i++) {
ranges.push_back (vars[i]->range());
}
Indexer indexer (ranges);
vector<string> jointStrings;
while (indexer.valid()) {
stringstream ss;
for (size_t i = 0; i < vars.size(); i++) {
if (i != 0) ss << ", " ;
ss << vars[i]->label() << "=" ;
ss << vars[i]->states()[(indexer[i])];
}
jointStrings.push_back (ss.str());
++ indexer;
}
return jointStrings;
}
bool invalidValue (string option, string value)
{
cerr << "Warning: invalid value `" << value << "' " ;
cerr << "for `" << option << "'." ;
cerr << endl;
return false;
}
bool
setHorusFlag (string option, string value)
{
bool returnVal = true;
if (option == "lifted_solver") {
if (value == "lve") Globals::liftedSolver = LiftedSolverType::LVE;
else if (value == "lbp") Globals::liftedSolver = LiftedSolverType::LBP;
else if (value == "lkc") Globals::liftedSolver = LiftedSolverType::LKC;
else returnVal = invalidValue (option, value);
} else if (option == "ground_solver" || option == "solver") {
if (value == "hve") Globals::groundSolver = GroundSolverType::VE;
else if (value == "bp") Globals::groundSolver = GroundSolverType::BP;
else if (value == "cbp") Globals::groundSolver = GroundSolverType::CBP;
else returnVal = invalidValue (option, value);
} else if (option == "verbosity") {
stringstream ss;
ss << value;
ss >> Globals::verbosity;
} else if (option == "use_logarithms") {
if (value == "true") Globals::logDomain = true;
else if (value == "false") Globals::logDomain = false;
else returnVal = invalidValue (option, value);
} else if (option == "hve_elim_heuristic") {
if (value == "sequential")
ElimGraph::setElimHeuristic (ElimHeuristic::SEQUENTIAL);
else if (value == "min_neighbors")
ElimGraph::setElimHeuristic (ElimHeuristic::MIN_NEIGHBORS);
else if (value == "min_weight")
ElimGraph::setElimHeuristic (ElimHeuristic::MIN_WEIGHT);
else if (value == "min_fill")
ElimGraph::setElimHeuristic (ElimHeuristic::MIN_FILL);
else if (value == "weighted_min_fill")
ElimGraph::setElimHeuristic (ElimHeuristic::WEIGHTED_MIN_FILL);
else
returnVal = invalidValue (option, value);
} else if (option == "bp_msg_schedule") {
if (value == "seq_fixed")
BeliefProp::setMsgSchedule (MsgSchedule::SEQ_FIXED);
else if (value == "seq_random")
BeliefProp::setMsgSchedule (MsgSchedule::SEQ_RANDOM);
else if (value == "parallel")
BeliefProp::setMsgSchedule (MsgSchedule::PARALLEL);
else if (value == "max_residual")
BeliefProp::setMsgSchedule (MsgSchedule::MAX_RESIDUAL);
else
returnVal = invalidValue (option, value);
} else if (option == "bp_accuracy") {
stringstream ss;
double acc;
ss << value;
ss >> acc;
BeliefProp::setAccuracy (acc);
} else if (option == "bp_max_iter") {
stringstream ss;
unsigned mi;
ss << value;
ss >> mi;
BeliefProp::setMaxIterations (mi);
} else if (option == "export_libdai") {
if (value == "true") FactorGraph::enableExportToLibDai();
else if (value == "false") FactorGraph::disableExportToLibDai();
else returnVal = invalidValue (option, value);
} else if (option == "export_uai") {
if (value == "true") FactorGraph::enableExportToUai();
else if (value == "false") FactorGraph::disableExportToUai();
else returnVal = invalidValue (option, value);
} else if (option == "export_graphviz") {
if (value == "true") FactorGraph::enableExportToGraphViz();
else if (value == "false") FactorGraph::disableExportToGraphViz();
else returnVal = invalidValue (option, value);
} else if (option == "print_fg") {
if (value == "true") FactorGraph::enablePrintFactorGraph();
else if (value == "false") FactorGraph::disablePrintFactorGraph();
else returnVal = invalidValue (option, value);
} else {
cerr << "Warning: invalid option `" << option << "'" << endl;
returnVal = false;
}
return returnVal;
}
void
printHeader (string header, std::ostream& os)
{
printAsteriskLine (os);
os << header << endl;
printAsteriskLine (os);
}
void
printSubHeader (string header, std::ostream& os)
{
printDashedLine (os);
os << header << endl;
printDashedLine (os);
}
void
printAsteriskLine (std::ostream& os)
{
os << "********************************" ;
os << "********************************" ;
os << endl;
}
void
printDashedLine (std::ostream& os)
{
os << "--------------------------------" ;
os << "--------------------------------" ;
os << endl;
}
}
namespace LogAware {
void
normalize (Params& v)
{
if (Globals::logDomain) {
double sum = std::accumulate (v.begin(), v.end(),
LogAware::addIdenty(), Util::logSum);
assert (sum != -std::numeric_limits<double>::infinity());
v -= sum;
} else {
double sum = std::accumulate (v.begin(), v.end(), 0.0);
assert (sum != 0.0);
v /= sum;
}
}
double
getL1Distance (const Params& v1, const Params& v2)
{
assert (v1.size() == v2.size());
double dist = 0.0;
if (Globals::logDomain) {
dist = std::inner_product (v1.begin(), v1.end(), v2.begin(), 0.0,
std::plus<double>(), FuncObject::abs_diff_exp<double>());
} else {
dist = std::inner_product (v1.begin(), v1.end(), v2.begin(), 0.0,
std::plus<double>(), FuncObject::abs_diff<double>());
}
return dist;
}
double
getMaxNorm (const Params& v1, const Params& v2)
{
assert (v1.size() == v2.size());
double max = 0.0;
if (Globals::logDomain) {
max = std::inner_product (v1.begin(), v1.end(), v2.begin(), 0.0,
FuncObject::max<double>(), FuncObject::abs_diff_exp<double>());
} else {
max = std::inner_product (v1.begin(), v1.end(), v2.begin(), 0.0,
FuncObject::max<double>(), FuncObject::abs_diff<double>());
}
return max;
}
double
pow (double base, unsigned iexp)
{
return Globals::logDomain
? base * iexp
: std::pow (base, iexp);
}
double
pow (double base, double exp)
{
// `expoent' should not be in log domain
return Globals::logDomain
? base * exp
: std::pow (base, exp);
}
void
pow (Params& v, unsigned iexp)
{
if (iexp == 1) {
return;
}
Globals::logDomain ? v *= iexp : v ^= (int)iexp;
}
void
pow (Params& v, double exp)
{
// `expoent' should not be in log domain
Globals::logDomain ? v *= exp : v ^= exp;
}
}