Real ExactInf::run() {
if( props.verbose >= 1 )
cerr << "Starting " << identify() << "...";
Factor P;
for( size_t I = 0; I < nrFactors(); I++ )
P *= factor(I);
Real Z = P.sum();
_logZ = std::log(Z);
for( size_t i = 0; i < nrVars(); i++ )
_beliefsV[i] = P.marginal(var(i));
for( size_t I = 0; I < nrFactors(); I++ )
_beliefsF[I] = P.marginal(factor(I).vars());
if( props.verbose >= 1 )
cerr << "finished" << endl;
return 0.0;
}
LC::LC( const FactorGraph & fg, const PropertySet &opts ) : DAIAlgFG(fg), _pancakes(), _cavitydists(), _phis(), _beliefs(), _maxdiff(0.0), _iters(0), props() {
setProperties( opts );
// create pancakes
_pancakes.resize( nrVars() );
// create cavitydists
for( size_t i=0; i < nrVars(); i++ )
_cavitydists.push_back(Factor( delta(i) ));
// create phis
_phis.reserve( nrVars() );
for( size_t i = 0; i < nrVars(); i++ ) {
_phis.push_back( vector<Factor>() );
_phis[i].reserve( nbV(i).size() );
foreach( const Neighbor &I, nbV(i) )
_phis[i].push_back( Factor( factor(I).vars() / var(i) ) );
}
// create beliefs
_beliefs.reserve( nrVars() );
for( size_t i=0; i < nrVars(); i++ )
_beliefs.push_back(Factor(var(i)));
}
void ExactInf::init() {
for( size_t i = 0; i < nrVars(); i++ )
_beliefsV[i].fill( 1.0 );
for( size_t I = 0; I < nrFactors(); I++ )
_beliefsF[I].fill( 1.0 );
}
Real MR::calcCavityCorrelations() {
Real md = 0.0;
for( size_t i = 0; i < nrVars(); i++ ) {
vector<Factor> pairq;
if( props.inits == Properties::InitType::EXACT ) {
JTree jtcav(*this, PropertySet()("updates", string("HUGIN"))("verbose", (size_t)0) );
jtcav.makeCavity( i );
pairq = calcPairBeliefs( jtcav, delta(i), false, true );
} else if( props.inits == Properties::InitType::CLAMPING ) {
BP bpcav(*this, PropertySet()("updates", string("SEQMAX"))("tol", (Real)1.0e-9)("maxiter", (size_t)10000)("verbose", (size_t)0)("logdomain", false));
bpcav.makeCavity( i );
pairq = calcPairBeliefs( bpcav, delta(i), false, true );
md = std::max( md, bpcav.maxDiff() );
} else if( props.inits == Properties::InitType::RESPPROP ) {
BP bpcav(*this, PropertySet()("updates", string("SEQMAX"))("tol", (Real)1.0e-9)("maxiter", (size_t)10000)("verbose", (size_t)0)("logdomain", false));
bpcav.makeCavity( i );
bpcav.makeCavity( i );
bpcav.init();
bpcav.run();
BBP bbp( &bpcav, PropertySet()("verbose",(size_t)0)("tol",(Real)1.0e-9)("maxiter",(size_t)10000)("damping",(Real)0.0)("updates",string("SEQ_MAX")) );
bforeach( const Neighbor &j, G.nb(i) ) {
// Create weights for magnetization of some spin
Prob p( 2, 0.0 );
p.set( 0, -1.0 );
p.set( 1, 1.0 );
// BBP cost function would be the magnetization of spin j
vector<Prob> b1_adj;
b1_adj.reserve( nrVars() );
for( size_t l = 0; l < nrVars(); l++ )
if( l == j )
b1_adj.push_back( p );
else
b1_adj.push_back( Prob( 2, 0.0 ) );
bbp.init_V( b1_adj );
// run BBP to estimate adjoints
bbp.run();
bforeach( const Neighbor &k, G.nb(i) ) {
if( k != j )
cors[i][j.iter][k.iter] = (bbp.adj_psi_V(k)[1] - bbp.adj_psi_V(k)[0]);
else
cors[i][j.iter][k.iter] = 0.0;
}
}
}
if( props.inits != Properties::InitType::RESPPROP ) {
for( size_t jk = 0; jk < pairq.size(); jk++ ) {
VarSet::const_iterator kit = pairq[jk].vars().begin();
size_t j = findVar( *(kit) );
size_t k = findVar( *(++kit) );
pairq[jk].normalize();
Real cor = (pairq[jk][3] - pairq[jk][2] - pairq[jk][1] + pairq[jk][0]) - (pairq[jk][3] + pairq[jk][2] - pairq[jk][1] - pairq[jk][0]) * (pairq[jk][3] - pairq[jk][2] + pairq[jk][1] - pairq[jk][0]);
size_t _j = G.findNb(i,j);
size_t _k = G.findNb(i,k);
cors[i][_j][_k] = cor;
cors[i][_k][_j] = cor;
}
}
}
