void mexFunction( int nlhs, mxArray *plhs[], int nrhs, const mxArray*prhs[] ) {
// Check for proper number of arguments
if( ((nrhs < NR_IN) || (nrhs > NR_IN + NR_IN_OPT)) || ((nlhs < NR_OUT) || (nlhs > NR_OUT + NR_OUT_OPT)) ) {
mexErrMsgTxt("Usage: [logZ,q,qv,qf,qmap,margs] = dai_jtree(psi,varsets,opts)\n\n"
"\n"
"INPUT: psi = linear cell array containing the factors\n"
" (psi{i} should be a structure with a Member field\n"
" and a P field).\n"
" varsets = linear cell array containing varsets for which marginals\n"
" are requested.\n"
" opts = string of options.\n"
"\n"
"OUTPUT: logZ = logarithm of the partition sum.\n"
" q = linear cell array containing all calculated marginals.\n"
" qv = linear cell array containing all variable marginals.\n"
" qf = linear cell array containing all factor marginals.\n"
" qmap = linear array containing the MAP state.\n"
" margs = linear cell array containing all requested marginals.\n");
}
// Get psi and construct factorgraph
vector<Factor> factors = mx2Factors(PSI_IN, 0);
FactorGraph fg(factors);
// Get varsets
vector<Permute> perms;
vector<VarSet> varsets = mx2VarSets(VARSETS_IN,fg,0,perms);
// Get options string
char *opts;
size_t buflen = mxGetN( OPTS_IN ) + 1;
opts = (char *)mxCalloc( buflen, sizeof(char) );
mxGetString( OPTS_IN, opts, buflen );
// Convert to options object props
stringstream ss;
ss << opts;
PropertySet props;
ss >> props;
// Construct InfAlg object, init and run
JTree jt = JTree( fg, props );
jt.init();
jt.run();
// Save logZ
double logZ = NAN;
logZ = jt.logZ();
// Hand over results to MATLAB
LOGZ_OUT = mxCreateDoubleMatrix(1,1,mxREAL);
*(mxGetPr(LOGZ_OUT)) = logZ;
Q_OUT = Factors2mx(jt.beliefs());
if( nlhs >= 3 ) {
vector<Factor> qv;
qv.reserve( fg.nrVars() );
for( size_t i = 0; i < fg.nrVars(); i++ )
qv.push_back( jt.belief( fg.var(i) ) );
QV_OUT = Factors2mx( qv );
}
if( nlhs >= 4 ) {
vector<Factor> qf;
qf.reserve( fg.nrFactors() );
for( size_t I = 0; I < fg.nrFactors(); I++ )
qf.push_back( jt.belief( fg.factor(I).vars() ) );
QF_OUT = Factors2mx( qf );
}
if( nlhs >= 5 ) {
std::vector<size_t> map_state;
bool supported = true;
try {
map_state = jt.findMaximum();
} catch( Exception &e ) {
if( e.getCode() == Exception::NOT_IMPLEMENTED )
supported = false;
else
throw;
}
if( supported ) {
QMAP_OUT = mxCreateNumericMatrix(map_state.size(), 1, mxUINT32_CLASS, mxREAL);
uint32_T* qmap_p = reinterpret_cast<uint32_T *>(mxGetPr(QMAP_OUT));
for (size_t n = 0; n < map_state.size(); ++n)
qmap_p[n] = map_state[n];
} else {
mexErrMsgTxt("Calculating a MAP state is not supported by this inference algorithm.");
}
}
if( nlhs >= 6 ) {
vector<Factor> margs;
margs.reserve( varsets.size() );
for( size_t s = 0; s < varsets.size(); s++ ) {
Factor marg;
jt.init();
jt.run();
marg = jt.calcMarginal( varsets[s] );
// permute entries of marg
Factor margperm = marg;
for( size_t li = 0; li < marg.nrStates(); li++ )
margperm.set( li, marg[perms[s].convertLinearIndex(li)] );
margs.push_back( margperm );
}
MARGS_OUT = Factors2mx( margs );
}
return;
}
