#include #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 (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 (std::exp (prod)); } return result; } size_t sizeExpected (const Ranges& ranges) { return std::accumulate (ranges.begin(), ranges.end(), 1, multiplies()); } 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 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 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::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(), FuncObject::abs_diff_exp()); } else { dist = std::inner_product (v1.begin(), v1.end(), v2.begin(), 0.0, std::plus(), FuncObject::abs_diff()); } 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(), FuncObject::abs_diff_exp()); } else { max = std::inner_product (v1.begin(), v1.end(), v2.begin(), 0.0, FuncObject::max(), FuncObject::abs_diff()); } 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; } }