SharedParameters::SharedParameters( std::istream &is, const FactorGraph &fg )
: _varsets(), _perms(), _varorders(), _estimation(NULL), _ownEstimation(true)
{
// Read the desired parameter estimation method from the stream
std::string est_method;
PropertySet props;
is >> est_method;
is >> props;
// Construct a corresponding object
_estimation = ParameterEstimation::construct( est_method, props );
// Read in the factors that are to be estimated
size_t num_factors;
is >> num_factors;
for( size_t sp_i = 0; sp_i < num_factors; ++sp_i ) {
std::string line;
while( line.size() == 0 && getline(is, line) )
;
std::vector<std::string> fields;
tokenizeString(line, fields, " \t");
// Lookup the factor in the factorgraph
if( fields.size() < 1 )
DAI_THROWE(INVALID_EMALG_FILE,"Empty line unexpected");
std::istringstream iss;
iss.str( fields[0] );
size_t factor;
iss >> factor;
const VarSet &vs = fg.factor(factor).vars();
if( fields.size() != vs.size() + 1 )
DAI_THROWE(INVALID_EMALG_FILE,"Number of fields does not match factor size");
// Construct the vector of Vars
std::vector<Var> var_order;
var_order.reserve( vs.size() );
for( size_t fi = 1; fi < fields.size(); ++fi ) {
// Lookup a single variable by label
size_t label;
std::istringstream labelparse( fields[fi] );
labelparse >> label;
VarSet::const_iterator vsi = vs.begin();
for( ; vsi != vs.end(); ++vsi )
if( vsi->label() == label )
break;
if( vsi == vs.end() )
DAI_THROWE(INVALID_EMALG_FILE,"Specified variables do not match the factor variables");
var_order.push_back( *vsi );
}
_varorders[factor] = var_order;
}
// Calculate the necessary permutations
setPermsAndVarSetsFromVarOrders();
}
ParameterEstimation* ParameterEstimation::construct( const std::string &method, const PropertySet &p ) {
if( _registry == NULL )
loadDefaultRegistry();
std::map<std::string, ParamEstFactory>::iterator i = _registry->find(method);
if( i == _registry->end() )
DAI_THROWE(UNKNOWN_PARAMETER_ESTIMATION_METHOD, "Unknown parameter estimation method: " + method);
ParamEstFactory factory = i->second;
return factory(p);
}
Real BBPCostFunction::evaluate( const InfAlg &ia, const vector<size_t> *stateP ) const {
Real cf = 0.0;
const FactorGraph &fg = ia.fg();
switch( (size_t)(*this) ) {
case CFN_BETHE_ENT: // ignores state
cf = -ia.logZ();
break;
case CFN_VAR_ENT: // ignores state
for( size_t i = 0; i < fg.nrVars(); i++ )
cf += -ia.beliefV(i).entropy();
break;
case CFN_FACTOR_ENT: // ignores state
for( size_t I = 0; I < fg.nrFactors(); I++ )
cf += -ia.beliefF(I).entropy();
break;
case CFN_GIBBS_B:
case CFN_GIBBS_B2:
case CFN_GIBBS_EXP: {
DAI_ASSERT( stateP != NULL );
vector<size_t> state = *stateP;
DAI_ASSERT( state.size() == fg.nrVars() );
for( size_t i = 0; i < fg.nrVars(); i++ ) {
Real b = ia.beliefV(i)[state[i]];
switch( (size_t)(*this) ) {
case CFN_GIBBS_B:
cf += b;
break;
case CFN_GIBBS_B2:
cf += b * b / 2.0;
break;
case CFN_GIBBS_EXP:
cf += exp( b );
break;
default:
DAI_THROW(UNKNOWN_ENUM_VALUE);
}
}
break;
} case CFN_GIBBS_B_FACTOR:
case CFN_GIBBS_B2_FACTOR:
case CFN_GIBBS_EXP_FACTOR: {
DAI_ASSERT( stateP != NULL );
vector<size_t> state = *stateP;
DAI_ASSERT( state.size() == fg.nrVars() );
for( size_t I = 0; I < fg.nrFactors(); I++ ) {
size_t x_I = getFactorEntryForState( fg, I, state );
Real b = ia.beliefF(I)[x_I];
switch( (size_t)(*this) ) {
case CFN_GIBBS_B_FACTOR:
cf += b;
break;
case CFN_GIBBS_B2_FACTOR:
cf += b * b / 2.0;
break;
case CFN_GIBBS_EXP_FACTOR:
cf += exp( b );
break;
default:
DAI_THROW(UNKNOWN_ENUM_VALUE);
}
}
break;
} default:
DAI_THROWE(UNKNOWN_ENUM_VALUE, "Unknown cost function " + std::string(*this));
}
return cf;
}
