void HillClimber::initializeSampler( void )
{
std::vector<DagNode *>& dagNodes = model->getDagNodes();
std::vector<DagNode *> orderedStochNodes = model->getOrderedStochasticNodes( );
// Get rid of previous move schedule, if any
if ( schedule )
{
delete schedule;
}
schedule = NULL;
// Get initial lnProbability of model
// first we touch all nodes so that the likelihood is dirty
for (std::vector<DagNode *>::iterator i=dagNodes.begin(); i!=dagNodes.end(); i++)
{
DagNode *the_node = *i;
the_node->setMcmcMode( true );
the_node->setPriorOnly( false );
the_node->touch();
}
int numTries = 0;
int maxNumTries = 100;
double lnProbability = 0.0;
for ( ; numTries < maxNumTries; numTries ++ )
{
// a flag if we failed to find a valid starting value
bool failed = false;
lnProbability = 0.0;
for (std::vector<DagNode *>::iterator i=dagNodes.begin(); i!=dagNodes.end(); i++)
{
DagNode* node = (*i);
node->touch();
double lnProb = node->getLnProbability();
if ( !RbMath::isAComputableNumber(lnProb) )
{
std::stringstream ss;
ss << "Could not compute lnProb for node " << node->getName() << "." << std::endl;
node->printValue( ss );
ss << std::endl;
RBOUT( ss.str() );
// set the flag
failed = true;
break;
}
lnProbability += lnProb;
}
// now we keep all nodes so that the likelihood is stored
for (std::vector<DagNode *>::iterator i=dagNodes.begin(); i!=dagNodes.end(); i++)
{
(*i)->keep();
}
if ( failed == true )
{
std::cout << "Drawing new initial states ... " << std::endl;
for (std::vector<DagNode *>::iterator i=orderedStochNodes.begin(); i!=orderedStochNodes.end(); i++)
{
if ( !(*i)->isClamped() && (*i)->isStochastic() )
{
(*i)->redraw();
(*i)->reInitialized();
}
else if ( (*i)->isClamped() )
{
// make sure that the clamped node also recompute their probabilities
(*i)->reInitialized();
(*i)->touch();
}
}
}
else
{
break;
}
}
if ( numTries == maxNumTries )
{
std::stringstream msg;
msg << "Unable to find a starting state with computable probability";
if ( numTries > 1 )
{
msg << " after " << numTries << " tries";
}
throw RbException( msg.str() );
}
// Create the move scheduler
if ( scheduleType == "sequential" )
{
schedule = new SequentialMoveSchedule( &moves );
}
else if ( scheduleType == "single" )
{
schedule = new SingleRandomMoveSchedule( &moves );
}
else
{
schedule = new RandomMoveSchedule( &moves );
}
generation = 0;
}
/** Monitor value at generation gen */
void ScreenMonitor::monitor(unsigned long gen) {
// get the printing frequency
unsigned long samplingFrequency = printgen;
if (gen % samplingFrequency == 0) {
// print the iteration number first
std::cout << gen;
if ( posterior ) {
// add a separator before every new element
std::cout << separator;
const std::vector<DagNode*> &n = model->getDagNodes();
double pp = 0.0;
for (std::vector<DagNode*>::const_iterator it = n.begin(); it != n.end(); ++it) {
pp += (*it)->getLnProbability();
}
std::cout << pp;
}
if ( likelihood ) {
// add a separator before every new element
std::cout << separator;
const std::vector<DagNode*> &n = model->getDagNodes();
double pp = 0.0;
for (std::vector<DagNode*>::const_iterator it = n.begin(); it != n.end(); ++it) {
if ( (*it)->isClamped() ) {
pp += (*it)->getLnProbability();
}
}
std::cout << pp;
}
if ( prior ) {
// add a separator before every new element
std::cout << separator;
const std::vector<DagNode*> &n = model->getDagNodes();
double pp = 0.0;
for (std::vector<DagNode*>::const_iterator it = n.begin(); it != n.end(); ++it) {
if ( !(*it)->isClamped() ) {
pp += (*it)->getLnProbability();
}
}
std::cout << pp;
}
for (std::vector<DagNode*>::iterator i = nodes.begin(); i != nodes.end(); ++i) {
// add a separator before every new element
std::cout << separator;
// get the node
DagNode *node = *i;
// print the value
node->printValue(std::cout, separator);
}
std::cout << std::endl;
}
}
