void HillClimber::constructInternalObject( void )
{
// we free the memory first
delete value;
const RevBayesCore::Model& mdl = static_cast<const Model &>( model->getRevObject() ).getValue();
const WorkspaceVector<Monitor> & ws_vec_mntr = static_cast<const WorkspaceVector<Monitor> &>( monitors->getRevObject() );
RevBayesCore::RbVector<RevBayesCore::Monitor> mntr;
for ( size_t i = 0; i < ws_vec_mntr.size(); ++i )
{
mntr.push_back( ws_vec_mntr[i].getValue() );
}
const WorkspaceVector<Move>& ws_vec_mvs = static_cast<const WorkspaceVector<Move> &>( moves->getRevObject() );
RevBayesCore::RbVector<RevBayesCore::Move> mvs;
for ( size_t i = 0; i < ws_vec_mvs.size(); ++i )
{
mvs.push_back( ws_vec_mvs[i].getValue() );
}
const std::string & sched = static_cast<const RlString &>( moveschedule->getRevObject() ).getValue();
RevBayesCore::HillClimber *m = new RevBayesCore::HillClimber(mdl, mvs, mntr);
m->setScheduleType( sched );
value = new RevBayesCore::MaximumLikelihoodAnalysis(m);
}
RevPtr<RevVariable> Func_Mcmcmc::execute( void )
{
const RevBayesCore::Model& mdl = static_cast<const Model &>( args[0].getVariable()->getRevObject() ).getValue();
const WorkspaceVector<Monitor> & ws_vec_mntr = static_cast<const WorkspaceVector<Monitor> &>( args[1].getVariable()->getRevObject() );
RevBayesCore::RbVector<RevBayesCore::Monitor> mntr;
for ( size_t i = 0; i < ws_vec_mntr.size(); ++i )
{
mntr.push_back( ws_vec_mntr[i].getValue() );
}
const WorkspaceVector<Move>& ws_vec_mvs = static_cast<const WorkspaceVector<Move> &>( args[2].getVariable()->getRevObject() );
RevBayesCore::RbVector<RevBayesCore::Move> mvs;
for ( size_t i = 0; i < ws_vec_mvs.size(); ++i )
{
mvs.push_back( ws_vec_mvs[i].getValue() );
}
const std::string & sched = static_cast<const RlString &>( args[3].getVariable()->getRevObject() ).getValue();
int nchains = static_cast<const Natural &>( args[4].getVariable()->getRevObject() ).getValue();
int si = static_cast<const Natural &>( args[5].getVariable()->getRevObject() ).getValue();
double delta = static_cast<const RealPos &>( args[6].getVariable()->getRevObject() ).getValue();
int nreps = static_cast<const Natural &>( args[7].getVariable()->getRevObject() ).getValue();
RevBayesCore::Mcmcmc *m = new RevBayesCore::Mcmcmc(mdl, mvs, mntr, sched, nchains, si, delta);
// m->setScheduleType( sched );
RevBayesCore::MonteCarloAnalysis *a = new RevBayesCore::MonteCarloAnalysis(m,nreps);
return new RevVariable( new MonteCarloAnalysis( a ) );
}
void PowerPosteriorAnalysis::constructInternalObject( void )
{
// we free the memory first
delete value;
// now allocate a new sliding move
const RevBayesCore::Model& mdl = static_cast<const Model &>( model->getRevObject() ).getValue();
const WorkspaceVector<Move>& rlmvs = static_cast<const WorkspaceVector<Move> &>( moves->getRevObject() );
const WorkspaceVector<Monitor>& rlmntr = static_cast<const WorkspaceVector<Monitor> &>( monitors->getRevObject() );
RevBayesCore::RbVector<RevBayesCore::Monitor> mntr;
for ( size_t i = 0; i < rlmntr.size(); ++i )
{
mntr.push_back( rlmntr[i].getValue() );
}
RevBayesCore::RbVector<RevBayesCore::Move> mvs;
for ( size_t i = 0; i < rlmvs.size(); ++i )
{
mvs.push_back( rlmvs[i].getValue() );
}
const std::string& fn = static_cast<const RlString &>( filename->getRevObject() ).getValue();
const double alpha = static_cast<const RealPos &>( alphaVal->getRevObject() ).getValue();
const int sf = static_cast<const Natural &>( sampFreq->getRevObject() ).getValue();
const int k = static_cast<const Natural &>( proc_per_lik->getRevObject() ).getValue();
RevBayesCore::Mcmc *m = new RevBayesCore::Mcmc(mdl, mvs, mntr);
m->setScheduleType( "random" );
value = new RevBayesCore::PowerPosteriorAnalysis( m, fn, size_t(k) );
std::vector<double> beta;
if ( powers->getRevObject() != RevNullObject::getInstance() )
{
beta = static_cast<const ModelVector<RealPos> &>( powers->getRevObject() ).getValue();
}
else
{
int k = static_cast<const Natural &>( cats->getRevObject() ).getValue();
for (int i = k; i >= 0; --i)
{
double b = RevBayesCore::RbStatistics::Beta::quantile(alpha,1.0,i / double(k));
beta.push_back( b );
}
}
value->setPowers( beta );
value->setSampleFreq( sf );
}
/* Map calls to member methods */
RevPtr<RevVariable> RlAtlas::executeMethod(std::string const &name, const std::vector<Argument> &args, bool &found)
{
if (name == "nAreas")
{
found = true;
return new RevVariable(new Natural((int)this->dagNode->getValue().getNumAreas())) ;
}
else if (name == "nEpochs")
{
found = true;
return new RevVariable(new Natural((int)this->dagNode->getValue().getNumEpochs())) ;
}
else if (name == "names")
{
found = true;
ModelVector<RlString> *n = new ModelVector<RlString>();
const std::vector<std::vector<RevBayesCore::GeographicArea*> >& areas = this->dagNode->getValue().getAreas();
for (size_t i = 0; i < areas[0].size(); ++i)
{
std::string name = areas[0][i]->getName();
n->push_back( name );
}
return new RevVariable( n );
}
else if (name == "epochTimes")
{
found = true;
ModelVector<RealPos> *n = new ModelVector<RealPos>( this->dagNode->getValue().getEpochs() );
return new RevVariable( n );
}
else if (name == "getValues")
{
found = true;
// get the member with give index
std::string value = static_cast<const RlString &>( args[0].getVariable()->getRevObject() ).getValue();
std::vector<std::vector<RevBayesCore::GeographicArea*> > areas = this->dagNode->getValue().getAreas();
ModelVector<ModelVector<ModelVector<Real > > > *f = new ModelVector<ModelVector<ModelVector<Real > > >();
for (size_t i = 0; i < areas.size(); i++)
{
RevBayesCore::RbVector<RevBayesCore::RbVector<double> > v;
for (size_t j = 0; j < areas[i].size(); j++)
{
if (value == "dispersal")
v.push_back(areas[i][j]->getDispersalValues());
else if (value == "dispersal-upper")
v.push_back(areas[i][j]->getDispersalValues());
else if (value == "extinction")
v.push_back(areas[i][j]->getExtinctionValues());
else if (value == "latlon")
v.push_back(areas[i][j]->getLatlon());
else if (value == "altitude")
v.push_back( RevBayesCore::RbVector<double>(1, areas[i][j]->getAltitude()) );
else if (value == "size")
v.push_back( RevBayesCore::RbVector<double>(1, areas[i][j]->getSize()) );
}
f->push_back( ModelVector<ModelVector<Real> >(v) );
}
return new RevVariable(f);
}
return ModelObject<RevBayesCore::TimeAtlas>::executeMethod( name, args, found );
}