-/* Copyright (C) 2006-2008 Joris Mooij [j dot mooij at science dot ru dot nl]
- Radboud University Nijmegen, The Netherlands
-
+/* Copyright (C) 2006-2008 Joris Mooij [joris dot mooij at tuebingen dot mpg dot de]
+ Radboud University Nijmegen, The Netherlands /
+ Max Planck Institute for Biological Cybernetics, Germany
+
This file is part of libDAI.
libDAI is free software; you can redistribute it and/or modify
#include <iostream>
+#include <iomanip>
#include <iterator>
#include <map>
#include <set>
#include <string>
#include <algorithm>
#include <functional>
-#include <tr1/unordered_map>
#include <dai/factorgraph.h>
#include <dai/util.h>
+#include <dai/exceptions.h>
namespace dai {
using namespace std;
-FactorGraph::FactorGraph( const std::vector<Factor> &P ) : G(), _undoProbs(), _normtype(Prob::NORMPROB) {
+FactorGraph::FactorGraph( const std::vector<Factor> &P ) : G(), _backup() {
// add factors, obtain variables
- set<Var> _vars;
- factors.reserve( P.size() );
+ set<Var> varset;
+ _factors.reserve( P.size() );
size_t nrEdges = 0;
for( vector<Factor>::const_iterator p2 = P.begin(); p2 != P.end(); p2++ ) {
- factors.push_back( *p2 );
- copy( p2->vars().begin(), p2->vars().end(), inserter( _vars, _vars.begin() ) );
+ _factors.push_back( *p2 );
+ copy( p2->vars().begin(), p2->vars().end(), inserter( varset, varset.begin() ) );
nrEdges += p2->vars().size();
}
- // add _vars
- vars.reserve( _vars.size() );
- for( set<Var>::const_iterator p1 = _vars.begin(); p1 != _vars.end(); p1++ )
- vars.push_back( *p1 );
-
+ // add vars
+ _vars.reserve( varset.size() );
+ for( set<Var>::const_iterator p1 = varset.begin(); p1 != varset.end(); p1++ )
+ _vars.push_back( *p1 );
+
// create graph structure
- createGraph( nrEdges );
+ constructGraph( nrEdges );
}
-/// Part of constructors (creates edges, neighbours and adjacency matrix)
-void FactorGraph::createGraph( size_t nrEdges ) {
+void FactorGraph::constructGraph( size_t nrEdges ) {
// create a mapping for indices
- std::tr1::unordered_map<size_t, size_t> hashmap;
+ hash_map<size_t, size_t> hashmap;
- for( size_t i = 0; i < vars.size(); i++ )
+ for( size_t i = 0; i < vars().size(); i++ )
hashmap[var(i).label()] = i;
// create edge list
}
// create bipartite graph
- G.create( nrVars(), nrFactors(), edges.begin(), edges.end() );
+ G.construct( nrVars(), nrFactors(), edges.begin(), edges.end() );
}
+/// Writes a FactorGraph to an output stream
ostream& operator << (ostream& os, const FactorGraph& fg) {
os << fg.nrFactors() << endl;
nr_nonzeros++;
os << nr_nonzeros << endl;
for( size_t k = 0; k < fg.factor(I).states(); k++ )
- if( fg.factor(I)[k] != 0.0 ) {
- char buf[20];
- sprintf(buf,"%18.14g", fg.factor(I)[k]);
- os << k << " " << buf << endl;
- }
+ if( fg.factor(I)[k] != 0.0 )
+ os << k << " " << setw(os.precision()+4) << fg.factor(I)[k] << endl;
}
return(os);
}
+/// Reads a FactorGraph from an input stream
istream& operator >> (istream& is, FactorGraph& fg) {
long verbose = 0;
- try {
- vector<Factor> factors;
- size_t nr_f;
- string line;
-
+ vector<Factor> facs;
+ size_t nr_Factors;
+ string line;
+
+ while( (is.peek()) == '#' )
+ getline(is,line);
+ is >> nr_Factors;
+ if( is.fail() )
+ DAI_THROW(INVALID_FACTORGRAPH_FILE);
+ if( verbose >= 2 )
+ cerr << "Reading " << nr_Factors << " factors..." << endl;
+
+ getline (is,line);
+ if( is.fail() )
+ DAI_THROW(INVALID_FACTORGRAPH_FILE);
+
+ map<long,size_t> vardims;
+ for( size_t I = 0; I < nr_Factors; I++ ) {
+ if( verbose >= 3 )
+ cerr << "Reading factor " << I << "..." << endl;
+ size_t nr_members;
while( (is.peek()) == '#' )
getline(is,line);
- is >> nr_f;
- if( is.fail() )
- throw "ReadFromFile: unable to read number of Factors";
- if( verbose >= 2 )
- cout << "Reading " << nr_f << " factors..." << endl;
-
- getline (is,line);
- if( is.fail() )
- throw "ReadFromFile: empty line expected";
-
- for( size_t I = 0; I < nr_f; I++ ) {
- if( verbose >= 3 )
- cout << "Reading factor " << I << "..." << endl;
- size_t nr_members;
+ is >> nr_members;
+ if( verbose >= 3 )
+ cerr << " nr_members: " << nr_members << endl;
+
+ vector<long> labels;
+ for( size_t mi = 0; mi < nr_members; mi++ ) {
+ long mi_label;
while( (is.peek()) == '#' )
getline(is,line);
- is >> nr_members;
- if( verbose >= 3 )
- cout << " nr_members: " << nr_members << endl;
-
- vector<long> labels;
- for( size_t mi = 0; mi < nr_members; mi++ ) {
- long mi_label;
- while( (is.peek()) == '#' )
- getline(is,line);
- is >> mi_label;
- labels.push_back(mi_label);
- }
- if( verbose >= 3 ) {
- cout << " labels: ";
- copy (labels.begin(), labels.end(), ostream_iterator<int>(cout, " "));
- cout << endl;
- }
-
- vector<size_t> dims;
- for( size_t mi = 0; mi < nr_members; mi++ ) {
- size_t mi_dim;
- while( (is.peek()) == '#' )
- getline(is,line);
- is >> mi_dim;
- dims.push_back(mi_dim);
- }
- if( verbose >= 3 ) {
- cout << " dimensions: ";
- copy (dims.begin(), dims.end(), ostream_iterator<int>(cout, " "));
- cout << endl;
- }
-
- // add the Factor
- VarSet I_vars;
- for( size_t mi = 0; mi < nr_members; mi++ )
- I_vars |= Var(labels[mi], dims[mi]);
- factors.push_back(Factor(I_vars,0.0));
-
- // calculate permutation sigma (internally, members are sorted)
- vector<size_t> sigma(nr_members,0);
- VarSet::iterator j = I_vars.begin();
- for( size_t mi = 0; mi < nr_members; mi++,j++ ) {
- long search_for = j->label();
- vector<long>::iterator j_loc = find(labels.begin(),labels.end(),search_for);
- sigma[mi] = j_loc - labels.begin();
- }
- if( verbose >= 3 ) {
- cout << " sigma: ";
- copy( sigma.begin(), sigma.end(), ostream_iterator<int>(cout," "));
- cout << endl;
- }
+ is >> mi_label;
+ labels.push_back(mi_label);
+ }
+ if( verbose >= 3 )
+ cerr << " labels: " << labels << endl;
- // calculate multindices
- Permute permindex( dims, sigma );
-
- // read values
- size_t nr_nonzeros;
+ vector<size_t> dims;
+ for( size_t mi = 0; mi < nr_members; mi++ ) {
+ size_t mi_dim;
while( (is.peek()) == '#' )
getline(is,line);
- is >> nr_nonzeros;
- if( verbose >= 3 )
- cout << " nonzeroes: " << nr_nonzeros << endl;
- for( size_t k = 0; k < nr_nonzeros; k++ ) {
- size_t li;
- double val;
- while( (is.peek()) == '#' )
- getline(is,line);
- is >> li;
- while( (is.peek()) == '#' )
- getline(is,line);
- is >> val;
-
- // store value, but permute indices first according
- // to internal representation
- factors.back()[permindex.convert_linear_index( li )] = val;
- }
+ is >> mi_dim;
+ dims.push_back(mi_dim);
}
-
- if( verbose >= 3 ) {
- cout << "factors:" << endl;
- copy(factors.begin(), factors.end(), ostream_iterator<Factor>(cout,"\n"));
+ if( verbose >= 3 )
+ cerr << " dimensions: " << dims << endl;
+
+ // add the Factor
+ VarSet I_vars;
+ for( size_t mi = 0; mi < nr_members; mi++ ) {
+ map<long,size_t>::iterator vdi = vardims.find( labels[mi] );
+ if( vdi != vardims.end() ) {
+ // check whether dimensions are consistent
+ if( vdi->second != dims[mi] )
+ DAI_THROW(INVALID_FACTORGRAPH_FILE);
+ } else
+ vardims[labels[mi]] = dims[mi];
+ I_vars |= Var(labels[mi], dims[mi]);
}
+ facs.push_back( Factor( I_vars, 0.0 ) );
+
+ // calculate permutation sigma (internally, members are sorted)
+ vector<size_t> sigma(nr_members,0);
+ VarSet::iterator j = I_vars.begin();
+ for( size_t mi = 0; mi < nr_members; mi++,j++ ) {
+ long search_for = j->label();
+ vector<long>::iterator j_loc = find(labels.begin(),labels.end(),search_for);
+ sigma[mi] = j_loc - labels.begin();
+ }
+ if( verbose >= 3 )
+ cerr << " sigma: " << sigma << endl;
+
+ // calculate multindices
+ Permute permindex( dims, sigma );
+
+ // read values
+ size_t nr_nonzeros;
+ while( (is.peek()) == '#' )
+ getline(is,line);
+ is >> nr_nonzeros;
+ if( verbose >= 3 )
+ cerr << " nonzeroes: " << nr_nonzeros << endl;
+ for( size_t k = 0; k < nr_nonzeros; k++ ) {
+ size_t li;
+ double val;
+ while( (is.peek()) == '#' )
+ getline(is,line);
+ is >> li;
+ while( (is.peek()) == '#' )
+ getline(is,line);
+ is >> val;
- fg = FactorGraph(factors);
- } catch (char *e) {
- cout << e << endl;
+ // store value, but permute indices first according
+ // to internal representation
+ facs.back()[permindex.convert_linear_index( li )] = val;
+ }
}
+ if( verbose >= 3 )
+ cerr << "factors:" << facs << endl;
+
+ fg = FactorGraph(facs);
+
return is;
}
VarSet FactorGraph::delta( unsigned i ) const {
+ return( Delta(i) / var(i) );
+}
+
+
+VarSet FactorGraph::Delta( unsigned i ) const {
// calculate Markov Blanket
- VarSet del;
+ VarSet Del;
foreach( const Neighbor &I, nbV(i) ) // for all neighboring factors I of i
foreach( const Neighbor &j, nbF(I) ) // for all neighboring variables j of I
- if( j != i )
- del |= var(j);
+ Del |= var(j);
- return del;
+ return Del;
}
-VarSet FactorGraph::Delta( unsigned i ) const {
- return( delta(i) | var(i) );
+VarSet FactorGraph::Delta( const VarSet &ns ) const {
+ VarSet result;
+ for( VarSet::const_iterator n = ns.begin(); n != ns.end(); n++ )
+ result |= Delta(findVar(*n));
+ return result;
}
-void FactorGraph::makeCavity( unsigned i ) {
+void FactorGraph::makeCavity( unsigned i, bool backup ) {
// fills all Factors that include var(i) with ones
+ map<size_t,Factor> newFacs;
foreach( const Neighbor &I, nbV(i) ) // for all neighboring factors I of i
- factor(I).fill( 1.0 );
+ newFacs[I] = Factor(factor(I).vars(), 1.0);
+ setFactors( newFacs, backup );
}
-bool FactorGraph::hasNegatives() const {
- bool result = false;
- for( size_t I = 0; I < nrFactors() && !result; I++ )
- if( factor(I).hasNegatives() )
- result = true;
- return result;
-}
-
-
-long FactorGraph::ReadFromFile(const char *filename) {
+void FactorGraph::ReadFromFile( const char *filename ) {
ifstream infile;
- infile.open (filename);
- if (infile.is_open()) {
+ infile.open( filename );
+ if( infile.is_open() ) {
infile >> *this;
infile.close();
- return 0;
- } else {
- cout << "ERROR OPENING FILE" << endl;
- return 1;
- }
+ } else
+ DAI_THROW(CANNOT_READ_FILE);
}
-long FactorGraph::WriteToFile(const char *filename) const {
+void FactorGraph::WriteToFile( const char *filename, size_t precision ) const {
ofstream outfile;
- outfile.open (filename);
- if (outfile.is_open()) {
- try {
- outfile << *this;
- } catch (char *e) {
- cout << e << endl;
- return 1;
- }
+ outfile.open( filename );
+ if( outfile.is_open() ) {
+ outfile.precision( precision );
+ outfile << *this;
outfile.close();
- return 0;
- } else {
- cout << "ERROR OPENING FILE" << endl;
- return 1;
- }
+ } else
+ DAI_THROW(CANNOT_WRITE_FILE);
}
-long FactorGraph::WriteToDotFile(const char *filename) const {
- ofstream outfile;
- outfile.open (filename);
- if (outfile.is_open()) {
- try {
- outfile << "graph G {" << endl;
- outfile << "graph[size=\"9,9\"];" << endl;
- outfile << "node[shape=circle,width=0.4,fixedsize=true];" << endl;
- for( size_t i = 0; i < nrVars(); i++ )
- outfile << "\tx" << var(i).label() << ";" << endl;
- outfile << "node[shape=box,style=filled,color=lightgrey,width=0.3,height=0.3,fixedsize=true];" << endl;
- for( size_t I = 0; I < nrFactors(); I++ )
- outfile << "\tp" << I << ";" << endl;
- for( size_t i = 0; i < nrVars(); i++ )
- foreach( const Neighbor &I, nbV(i) ) // for all neighboring factors I of i
- outfile << "\tx" << var(i).label() << " -- p" << I << ";" << endl;
- outfile << "}" << endl;
- } catch (char *e) {
- cout << e << endl;
- return 1;
- }
- outfile.close();
- return 0;
- } else {
- cout << "ERROR OPENING FILE" << endl;
- return 1;
- }
-}
-
-
-bool hasShortLoops( const vector<Factor> &P ) {
- bool found = false;
- vector<Factor>::const_iterator I, J;
- for( I = P.begin(); I != P.end(); I++ ) {
- J = I;
- J++;
- for( ; J != P.end(); J++ )
- if( (I->vars() & J->vars()).size() >= 2 ) {
- found = true;
- break;
- }
- if( found )
- break;
- }
- return found;
-}
-
-
-void RemoveShortLoops(vector<Factor> &P) {
- bool found = true;
- while( found ) {
- found = false;
- vector<Factor>::iterator I, J;
- for( I = P.begin(); I != P.end(); I++ ) {
- J = I;
- J++;
- for( ; J != P.end(); J++ )
- if( (I->vars() & J->vars()).size() >= 2 ) {
- found = true;
- break;
- }
- if( found )
- break;
- }
- if( found ) {
- cout << "Merging factors " << I->vars() << " and " << J->vars() << endl;
- *I *= *J;
- P.erase(J);
- }
- }
+void FactorGraph::printDot( std::ostream &os ) const {
+ os << "graph G {" << endl;
+ os << "node[shape=circle,width=0.4,fixedsize=true];" << endl;
+ for( size_t i = 0; i < nrVars(); i++ )
+ os << "\tv" << var(i).label() << ";" << endl;
+ os << "node[shape=box,width=0.3,height=0.3,fixedsize=true];" << endl;
+ for( size_t I = 0; I < nrFactors(); I++ )
+ os << "\tf" << I << ";" << endl;
+ for( size_t i = 0; i < nrVars(); i++ )
+ foreach( const Neighbor &I, nbV(i) ) // for all neighboring factors I of i
+ os << "\tv" << var(i).label() << " -- f" << I << ";" << endl;
+ os << "}" << endl;
}
for( size_t I = 0; I < nrFactors(); I++ ) {
bool maximal = true;
for( size_t J = 0; (J < nrFactors()) && maximal; J++ )
- if( (factor(J).vars() >> factor(I).vars()) && !(factor(J).vars() == factor(I).vars()) )
+ if( (factor(J).vars() >> factor(I).vars()) && (factor(J).vars() != factor(I).vars()) )
maximal = false;
if( maximal )
}
-void FactorGraph::clamp( const Var & n, size_t i ) {
+void FactorGraph::clamp( const Var & n, size_t i, bool backup ) {
assert( i <= n.states() );
// Multiply each factor that contains the variable with a delta function
Factor delta_n_i(n,0.0);
delta_n_i[i] = 1.0;
+ map<size_t, Factor> newFacs;
// For all factors that contain n
for( size_t I = 0; I < nrFactors(); I++ )
if( factor(I).vars().contains( n ) )
// Multiply it with a delta function
- factor(I) *= delta_n_i;
+ newFacs[I] = factor(I) * delta_n_i;
+ setFactors( newFacs, backup );
return;
}
-void FactorGraph::saveProb( size_t I ) {
- map<size_t,Prob>::iterator it = _undoProbs.find( I );
- if( it != _undoProbs.end() )
- cout << "FactorGraph::saveProb: WARNING: _undoProbs[I] already defined!" << endl;
- _undoProbs[I] = factor(I).p();
+void FactorGraph::clampVar( size_t i, const vector<size_t> &is, bool backup ) {
+ Var n = var(i);
+ Factor mask_n( n, 0.0 );
+
+ foreach( size_t i, is ) {
+ assert( i <= n.states() );
+ mask_n[i] = 1.0;
+ }
+
+ map<size_t, Factor> newFacs;
+ for( size_t I = 0; I < nrFactors(); I++ )
+ if( factor(I).vars().contains( n ) ) {
+ newFacs[I] = factor(I) * mask_n;
+ }
+ setFactors( newFacs, backup );
}
-void FactorGraph::undoProb( size_t I ) {
- map<size_t,Prob>::iterator it = _undoProbs.find( I );
- if( it != _undoProbs.end() ) {
- factor(I).p() = (*it).second;
- _undoProbs.erase(it);
+void FactorGraph::clampFactor( size_t I, const vector<size_t> &is, bool backup ) {
+ size_t st = factor(I).states();
+ Factor newF( factor(I).vars(), 0.0 );
+
+ foreach( size_t i, is ) {
+ assert( i <= st );
+ newF[i] = factor(I)[i];
}
+
+ setFactor( I, newF, backup );
}
-void FactorGraph::saveProbs( const VarSet &ns ) {
- if( !_undoProbs.empty() )
- cout << "FactorGraph::saveProbs: WARNING: _undoProbs not empy!" << endl;
+void FactorGraph::backupFactor( size_t I ) {
+ map<size_t,Factor>::iterator it = _backup.find( I );
+ if( it != _backup.end() )
+ DAI_THROW( MULTIPLE_UNDO );
+ _backup[I] = factor(I);
+}
+
+
+void FactorGraph::restoreFactor( size_t I ) {
+ map<size_t,Factor>::iterator it = _backup.find( I );
+ if( it != _backup.end() ) {
+ setFactor(I, it->second);
+ _backup.erase(it);
+ }
+}
+
+
+void FactorGraph::backupFactors( const VarSet &ns ) {
for( size_t I = 0; I < nrFactors(); I++ )
if( factor(I).vars().intersects( ns ) )
- _undoProbs[I] = factor(I).p();
+ backupFactor( I );
}
-void FactorGraph::undoProbs( const VarSet &ns ) {
- for( map<size_t,Prob>::iterator uI = _undoProbs.begin(); uI != _undoProbs.end(); ) {
- if( factor((*uI).first).vars().intersects( ns ) ) {
-// cout << "undoing " << factor((*uI).first).vars() << endl;
-// cout << "from " << factor((*uI).first).p() << " to " << (*uI).second << endl;
- factor((*uI).first).p() = (*uI).second;
- _undoProbs.erase(uI++);
+void FactorGraph::restoreFactors( const VarSet &ns ) {
+ map<size_t,Factor> facs;
+ for( map<size_t,Factor>::iterator uI = _backup.begin(); uI != _backup.end(); ) {
+ if( factor(uI->first).vars().intersects( ns ) ) {
+ facs.insert( *uI );
+ _backup.erase(uI++);
} else
uI++;
}
+ setFactors( facs );
+}
+
+
+void FactorGraph::restoreFactors() {
+ setFactors( _backup );
+ _backup.clear();
+}
+
+
+void FactorGraph::backupFactors( const std::set<size_t> & facs ) {
+ for( std::set<size_t>::const_iterator fac = facs.begin(); fac != facs.end(); fac++ )
+ backupFactor( *fac );
+}
+
+
+bool FactorGraph::isPairwise() const {
+ bool pairwise = true;
+ for( size_t I = 0; I < nrFactors() && pairwise; I++ )
+ if( factor(I).vars().size() > 2 )
+ pairwise = false;
+ return pairwise;
+}
+
+
+bool FactorGraph::isBinary() const {
+ bool binary = true;
+ for( size_t i = 0; i < nrVars() && binary; i++ )
+ if( var(i).states() > 2 )
+ binary = false;
+ return binary;
+}
+
+
+FactorGraph FactorGraph::clamped( const Var & v_i, size_t state ) const {
+ Real zeroth_order = 1.0;
+ vector<Factor> clamped_facs;
+ for( size_t I = 0; I < nrFactors(); I++ ) {
+ VarSet v_I = factor(I).vars();
+ Factor new_factor;
+ if( v_I.intersects( v_i ) )
+ new_factor = factor(I).slice( v_i, state );
+ else
+ new_factor = factor(I);
+
+ if( new_factor.vars().size() != 0 ) {
+ size_t J = 0;
+ // if it can be merged with a previous one, do that
+ for( J = 0; J < clamped_facs.size(); J++ )
+ if( clamped_facs[J].vars() == new_factor.vars() ) {
+ clamped_facs[J] *= new_factor;
+ break;
+ }
+ // otherwise, push it back
+ if( J == clamped_facs.size() || clamped_facs.size() == 0 )
+ clamped_facs.push_back( new_factor );
+ } else
+ zeroth_order *= new_factor[0];
+ }
+ *(clamped_facs.begin()) *= zeroth_order;
+ return FactorGraph( clamped_facs );
+}
+
+
+FactorGraph FactorGraph::maximalFactors() const {
+ vector<size_t> maxfac( nrFactors() );
+ map<size_t,size_t> newindex;
+ size_t nrmax = 0;
+ for( size_t I = 0; I < nrFactors(); I++ ) {
+ maxfac[I] = I;
+ VarSet maxfacvars = factor(maxfac[I]).vars();
+ for( size_t J = 0; J < nrFactors(); J++ ) {
+ VarSet Jvars = factor(J).vars();
+ if( Jvars >> maxfacvars && (Jvars != maxfacvars) ) {
+ maxfac[I] = J;
+ maxfacvars = factor(maxfac[I]).vars();
+ }
+ }
+ if( maxfac[I] == I )
+ newindex[I] = nrmax++;
+ }
+
+ vector<Factor> facs( nrmax );
+ for( size_t I = 0; I < nrFactors(); I++ )
+ facs[newindex[maxfac[I]]] *= factor(I);
+
+ return FactorGraph( facs.begin(), facs.end(), vars().begin(), vars().end(), facs.size(), nrVars() );
}
projects / libdai.git / blobdiff