Exemplo n.º 1
0
Factor LC::NewPancake (size_t i, size_t _I, bool & hasNaNs) {
    size_t I = nbV(i)[_I];
    Factor piet = _pancakes[i];

    // recalculate _pancake[i]
    VarSet Ivars = factor(I).vars();
    Factor A_I;
    for( VarSet::const_iterator k = Ivars.begin(); k != Ivars.end(); k++ )
        if( var(i) != *k )
            A_I *= (_pancakes[findVar(*k)] * factor(I).inverse()).marginal( Ivars / var(i), false );
    if( Ivars.size() > 1 )
        A_I ^= (1.0 / (Ivars.size() - 1));
    Factor A_Ii = (_pancakes[i] * factor(I).inverse() * _phis[i][_I].inverse()).marginal( Ivars / var(i), false );
    Factor quot = A_I / A_Ii;
    if( props.damping != 0.0 )
        quot = (quot^(1.0 - props.damping)) * (_phis[i][_I]^props.damping);

    piet *= quot / _phis[i][_I].normalized();
    _phis[i][_I] = quot.normalized();

    piet.normalize();

    if( piet.hasNaNs() ) {
        cerr << name() << "::NewPancake(" << i << ", " << _I << "):  has NaNs!" << endl;
        hasNaNs = true;
    }

    return piet;
}
Exemplo n.º 2
0
void ParityAggrLit::index(Grounder *g, Groundable *gr, VarSet &bound)
{
	(void)g;
	if(assign_)
	{
		VarSet vars;
		VarVec bind;
		lower_->vars(vars);
		std::set_difference(vars.begin(), vars.end(), bound.begin(), bound.end(), std::back_insert_iterator<VarVec>(bind));
		if(bind.size() > 0)
		{
			bound.insert(bind.begin(), bind.end());
			return;
		}
	}
	gr->instantiator()->append(new MatchIndex(this));
}
Exemplo n.º 3
0
Index *IncLit::index(Grounder *, Formula *, VarSet &bound)
{
	VarSet vars;
	VarVec bind;
	var_->vars(vars);
	std::set_difference(vars.begin(), vars.end(), bound.begin(), bound.end(), std::back_insert_iterator<VarVec>(bind));
	bound.insert(bind.begin(), bind.end());
	return new IncIndex(this);
}
Exemplo n.º 4
0
Factor LC::belief (const VarSet &ns) const {
    if( ns.size() == 0 )
        return Factor();
    else if( ns.size() == 1 )
        return beliefV( findVar( *(ns.begin()) ) );
    else {
        DAI_THROW(BELIEF_NOT_AVAILABLE);
        return Factor();
    }
}
Exemplo n.º 5
0
void findLoopClusters( const FactorGraph & fg, std::set<VarSet> &allcl, VarSet newcl, const Var & root, size_t length, VarSet vars ) {
    for( VarSet::const_iterator in = vars.begin(); in != vars.end(); in++ ) {
        VarSet ind = fg.delta( *in );
        if( (newcl.size()) >= 2 && ind.contains( root ) ) {
            allcl.insert( newcl | *in );
        }
        else if( length > 1 )
            findLoopClusters( fg, allcl, newcl | *in, root, length - 1, ind / newcl );
    }
}
Factor ExactInf::belief( const VarSet &ns ) const {
    if( ns.size() == 0 )
        return Factor();
    else if( ns.size() == 1 ) {
        return beliefV( findVar( *(ns.begin()) ) );
    } else {
        size_t I;
        for( I = 0; I < nrFactors(); I++ )
            if( factor(I).vars() >> ns )
                break;
        if( I == nrFactors() )
            DAI_THROW(BELIEF_NOT_AVAILABLE);
        return beliefF(I).marginal(ns);
    }
}
std::vector<std::map<size_t, int> > AnyPositionCnfCompress::createCounts(size_t &gndFactor, VarSet &superVarSet) {
	// create zero entries for each position
	map<long, map<size_t, int> > countMap;
	foreach (const dai::BipartiteGraph::Neighbor &tmpVar, _cfg.nbF(gndFactor)) {
		Var liftedVar = _varRepr[_varColorVec[tmpVar]];
		size_t pos = find(_cfg.factor(gndFactor).sigma().begin(), _cfg.factor(gndFactor).sigma().end(), tmpVar.iter) - _cfg.factor(gndFactor).sigma().begin();
		countMap[liftedVar.label()][pos] = 0;
	}

	vector<map<size_t, int> > counts;
	size_t posCount;
	size_t negCount;
	for (vector<Var>::const_iterator iter = superVarSet.begin(); iter < superVarSet.end(); iter++) {
		posCount = 0;
		negCount = 0;

		foreach(const dai::BipartiteGraph::Neighbor tmpFac, _cfg.nbV(_cfg.findVar(*iter))) {
			if (_facRepr[_facColorVec[tmpFac]] == gndFactor) {
				size_t pos = find(_cfg.factor(tmpFac).sigma().begin(), _cfg.factor(tmpFac).sigma().end(), tmpFac.dual) - _cfg.factor(tmpFac).sigma().begin();
				double res = log(_cfg.factor(tmpFac).states() - _zeroStates[tmpFac]) /  log(2);
				size_t nrPosLiterals = size_t(res);
				bool sign = (pos < nrPosLiterals);
				if (sign) {
					posCount++;
				} else {
					negCount++;
				}
			}
		}
		map<size_t, int>::iterator posIter=countMap[iter->label()].begin();

		if (posCount > 0) {
			posIter->second = posCount;
		}

		if (negCount > 0) {
			for (size_t j=0;j<posCount; j++, posIter++) {}
			posIter->second = negCount;
		}

		counts.push_back(countMap[iter->label()]);
	}

	return counts;
}
Exemplo n.º 8
0
std::vector<std::map<size_t, int> > CompressInterface::createCounts(size_t &gndFactor, VarSet &superVarSet) {
	// create zero entries for each position
	map<long, map<size_t, int> > countMap;
	foreach (const dai::BipartiteGraph::Neighbor &tmpVar, _cfg.nbF(gndFactor)) {
		Var liftedVar = _varRepr[_varColorVec[tmpVar]];
		size_t pos = find(_cfg.factor(gndFactor).sigma().begin(), _cfg.factor(gndFactor).sigma().end(), tmpVar.iter) - _cfg.factor(gndFactor).sigma().begin();
		countMap[liftedVar.label()][pos] = 0;
	}

	vector<map<size_t, int> > counts;
	for (vector<Var>::const_iterator iter = superVarSet.begin(); iter < superVarSet.end(); iter++) {
		foreach(const dai::BipartiteGraph::Neighbor gndFac, _cfg.nbV(_cfg.findVar(*iter))) {
			if (_facRepr[_facColorVec[gndFac]] == gndFactor) {
				size_t pos = find(_cfg.factor(gndFac).sigma().begin(), _cfg.factor(gndFac).sigma().end(), gndFac.dual) - _cfg.factor(gndFac).sigma().begin();
				countMap[iter->label()][pos]++;
			}
		}
		counts.push_back(countMap[iter->label()]);
	}
	return counts;
}
Exemplo n.º 9
0
/* Convert cell vector of Matlab sets to vector<VarSet> */
vector<VarSet> mx2VarSets(const mxArray *vs, const FactorGraph &fg, long verbose, vector<Permute> &perms) {
    vector<VarSet> varsets;

    int n1 = mxGetM(vs);
    int n2 = mxGetN(vs);
    if( n2 != 1 && n1 != 1 )
        mexErrMsgTxt("varsets should be a Nx1 or 1xN cell matrix.");
    size_t nr_vs = n1;
    if( n1 == 1 )
        nr_vs = n2;

    // interpret vs, linear cell array of varsets
    varsets.reserve( nr_vs );
    perms.clear();
    perms.reserve( nr_vs );
    for( size_t cellind = 0; cellind < nr_vs; cellind++ ) {
        if( verbose >= 3 )
            cerr << "reading varset " << cellind << ": " << endl;
        mxArray *cell = mxGetCell(vs, cellind);
        if( verbose >= 3 )
            cerr << "  got cell " << endl;
        size_t nr_mem = mxGetN(cell);
        if( verbose >= 3 )
            cerr << "  number members: " << nr_mem << endl;
        double *members = mxGetPr(cell);
        if( verbose >= 3 )
            cerr << "  got them! " << endl;

        // add variables
        VarSet vsvars;
        if( verbose >= 3 )
            cerr << "  vars: ";
        vector<long> labels(nr_mem,0);
        vector<size_t> dims(nr_mem,0);
        for( size_t mi = 0; mi < nr_mem; mi++ ) {
            labels[mi] = (long)members[mi];
            dims[mi] = fg.var(labels[mi]).states();
            if( verbose >= 3 )
                cerr << labels[mi] << " ";
            vsvars.insert( fg.var(labels[mi]) );
        }
        if( verbose >= 3 )
            cerr << endl;
        DAI_ASSERT( nr_mem == vsvars.size() );
        varsets.push_back(vsvars);

        // calculate permutation matrix
        vector<size_t> perm(nr_mem,0);
        VarSet::iterator j = vsvars.begin();
        for( size_t mi = 0; mi < nr_mem; mi++,j++ ) {
            long gezocht = j->label();
            vector<long>::iterator piet = find(labels.begin(),labels.end(),gezocht);
            perm[mi] = piet - labels.begin();
        }
        if( verbose >= 3 ) {
            cerr << endl << "  perm: ";
            for( vector<size_t>::iterator r=perm.begin(); r!=perm.end(); r++ )
                cerr << *r << " ";
            cerr << endl;
        }
        // create Permute object
        vector<size_t> di(nr_mem,0);
        size_t prod = 1;
        for( size_t k = 0; k < nr_mem; k++ ) {
            di[k] = dims[k];
            prod *= dims[k];
        }
        Permute permindex( di, perm );
        perms.push_back( permindex );
    }

    if( verbose >= 3 ) {
        for(vector<VarSet>::const_iterator I=varsets.begin(); I!=varsets.end(); I++ )
            cerr << *I << endl;
    }

    return( varsets );
}
Exemplo n.º 10
0
int main( int argc, char *argv[] ) {
    if( argc != 3 ) {
        cout << "Usage: " << argv[0] << " <in.fg> <tw>" << endl << endl;
        cout << "Reports some characteristics of the .fg network." << endl;
        cout << "Also calculates treewidth (which may take some time) unless <tw> == 0." << endl;
        return 1;
    } else {
        // Read factorgraph
        FactorGraph fg;
        char *infile = argv[1];
        int calc_tw = atoi(argv[2]);
        fg.ReadFromFile( infile );

        cout << "Number of variables:   " << fg.nrVars() << endl;
        cout << "Number of factors:     " << fg.nrFactors() << endl;
        cout << "Connected:             " << fg.isConnected() << endl;
        cout << "Tree:                  " << fg.isTree() << endl;
        cout << "Has short loops:       " << hasShortLoops(fg.factors()) << endl;
        cout << "Has negatives:         " << hasNegatives(fg.factors()) << endl;
        cout << "Binary variables?      " << fg.isBinary() << endl;
        cout << "Pairwise interactions? " << fg.isPairwise() << endl;
        if( calc_tw ) {
            std::pair<size_t,size_t> tw = treewidth(fg);
            cout << "Treewidth:           " << tw.first << endl;
            cout << "Largest cluster for JTree has " << tw.second << " states " << endl;
        }
        double stsp = 1.0;
        for( size_t i = 0; i < fg.nrVars(); i++ )
            stsp *= fg.var(i).states();
        cout << "Total state space:   " << stsp << endl;

        double cavsum_lcbp = 0.0;
        double cavsum_lcbp2 = 0.0;
        size_t max_Delta_size = 0;
        map<size_t,size_t> cavsizes;
        for( size_t i = 0; i < fg.nrVars(); i++ ) {
            VarSet di = fg.delta(i);
            if( cavsizes.count(di.size()) )
                cavsizes[di.size()]++;
            else
                cavsizes[di.size()] = 1;
            size_t Ds = fg.Delta(i).nrStates();
            if( Ds > max_Delta_size )
                max_Delta_size = Ds;
            cavsum_lcbp += di.nrStates();
            for( VarSet::const_iterator j = di.begin(); j != di.end(); j++ )
                cavsum_lcbp2 += j->states();
        }
        cout << "Maximum pancake has " << max_Delta_size << " states" << endl;
        cout << "LCBP with full cavities needs " << cavsum_lcbp << " BP runs" << endl;
        cout << "LCBP with only pairinteractions needs " << cavsum_lcbp2 << " BP runs" << endl;
        cout << "Cavity sizes: ";
        for( map<size_t,size_t>::const_iterator it = cavsizes.begin(); it != cavsizes.end(); it++ ) 
            cout << it->first << "(" << it->second << ") ";
        cout << endl;

        cout << "Type: " << (fg.isPairwise() ? "pairwise" : "higher order") << " interactions, " << (fg.isBinary() ? "binary" : "nonbinary") << " variables" << endl;

        if( fg.isPairwise() ) {
            bool girth_reached = false;
            size_t loopdepth;
            for( loopdepth = 2; loopdepth <= fg.nrVars() && !girth_reached; loopdepth++ ) {
                size_t nr_loops = countLoops( fg, loopdepth );
                cout << "Loops up to " << loopdepth << " variables: " << nr_loops << endl;
                if( nr_loops > 0 )
                    girth_reached = true;
            }
            if( girth_reached )
                cout << "Girth: " << loopdepth-1 << endl;
            else
                cout << "Girth: infinity" << endl;
        }

        return 0;
    }
}