const ind_t ind = index(i,_I);
for( size_t r = 0; r < prod.size(); ++r )
marg[ind[r]] += prod[r];
- marg.normalize( _normtype );
+ marg.normalize( Prob::NORMPROB );
// Store result
if( props.logdomain )
}
-Complex BP::logZ() const {
- Complex sum = 0.0;
+Real BP::logZ() const {
+ Real sum = 0.0;
for(size_t i = 0; i < nrVars(); ++i )
- sum += Complex(1.0 - nbV(i).size()) * beliefV(i).entropy();
+ sum += (1.0 - nbV(i).size()) * beliefV(i).entropy();
for( size_t I = 0; I < nrFactors(); ++I )
sum -= KL_dist( beliefF(I), factor(I) );
return sum;