//---------------------------------------------------------------------------------------
void ScorePlayerCtrl::handle_event(SpEventInfo pEvent)
{
SpEventMouse pEv( static_pointer_cast<EventMouse>(pEvent) );
if (!pEv->is_still_valid())
return;
if (m_fEnabled)
{
if (pEvent->is_mouse_in_event())
{
LOMSE_LOG_DEBUG(Logger::k_events | Logger::k_score_player,
"Mouse in event received");
m_currentColor = m_hoverColor;
m_fFullView = true;
m_pMainBox->set_dirty(true);
}
else if (pEvent->is_mouse_out_event())
{
LOMSE_LOG_DEBUG(Logger::k_events | Logger::k_score_player,
"Mouse out event received");
m_fFullView = false;
m_currentColor = m_normalColor;
m_pMainBox->set_dirty(true);
}
else if (pEvent->is_on_click_event())
{
LOMSE_LOG_DEBUG(Logger::k_events | Logger::k_score_player,
"Mouse on-click event received");
m_fFullView = true;
bool fPlay = (m_playButtonState == k_play );
if (fPlay)
{
set_play_button_state(k_stop);
}
else
{
set_play_button_state(k_play);
}
//create event for user app
EEventType evType = (fPlay ? k_do_play_score_event : k_stop_playback_event); //k_pause_score_event);
WpInteractor wpIntor = pEv->get_interactor();
if (SpInteractor p = wpIntor.lock())
{
ImoScore* pScore = m_pOwnerImo->get_score();
SpEventPlayScore event(
LOMSE_NEW EventPlayScore(evType, wpIntor, pScore, this) );
//AWARE: we notify directly to user app. (to observers of Interactor)
p->notify_observers(event, p.get());
}
}
else
{
LOMSE_LOG_WARN(str(boost::format("Unknown event received. Type=%d")
% pEvent->get_event_type()) );
}
}
}
void CBICLearningEngine::Learn()
{
CEMLearningEngine *pLearn = NULL;
float resultBIC = -FLT_MAX;
CBNet *pResultBNet = NULL;
intVector resultOrder;
pEvidencesVector pEv(m_Vector_pEvidences.size(), NULL );
CModelDomain *pMD = m_pGrModel->GetModelDomain();
int nnodes = m_pGrModel->GetNumberOfNodes();
nodeTypeVector varTypes;
pMD->GetVariableTypes(&varTypes);
intVector varAss( pMD->GetVariableAssociations(), pMD->GetVariableAssociations() + nnodes );
intVector currentAssociation(nnodes);
intVector currentObsNodes(nnodes);
int i;
for( i = 0; i < nnodes; i++ )
{
currentObsNodes[i] = i;
}
CGraph *pGraph = CGraph::Create(nnodes, NULL, NULL, NULL);
CBNet *pBNet;
int lineSz = int( nnodes * ( nnodes - 1 ) / 2 );
intVecVector connect;
intVector indexes(lineSz, 0);
int startNode, endNode;
int ind;
for( ind = 0; ind < lineSz ; )
{
if( indexes[ind] == 1 )
{
FindNodesByNumber(&startNode, &endNode, nnodes, ind);
pGraph->RemoveEdge(startNode, endNode );
indexes[ind] = 0;
ind++;
}
else
{
FindNodesByNumber(&startNode, &endNode, nnodes, ind);
pGraph->AddEdge(startNode, endNode, 1 );
indexes[ind] = 1;
ind = 0;
connect.clear();
pGraph->GetConnectivityComponents(&connect);
if( connect.size() == 1 )
{
do
{
CGraph *pCopyGraph = CGraph::Copy(pGraph);
int j;
for( j = 0; j < nnodes; j++ )
{
currentAssociation[j] = varAss[currentObsNodes[j]];
}
pBNet = CBNet::Create(nnodes, varTypes, currentAssociation, pCopyGraph);
pBNet->AllocFactors();
for( j = 0; j < nnodes; j++ )
{
pBNet->AllocFactor( j );
pBNet->GetFactor(j)->CreateAllNecessaryMatrices();
}
int dimOfModel = DimOfModel(pBNet);
int k;
for( k = 0; k < pEv.size(); k++ )
{
valueVector vls;
m_Vector_pEvidences[k]->GetRawData(&vls);
pEv[k] = CEvidence::Create( pBNet->GetModelDomain(),currentObsNodes, vls );
}
pLearn = CEMLearningEngine::Create(pBNet);
pLearn->SetData(pEv.size(), &pEv.front());
pLearn->Learn();
int nsteps;
const float *score;
pLearn->GetCriterionValue(&nsteps, &score);
float log_lik = score[nsteps-1];
float BIC = log_lik - 0.5f*float( dimOfModel*log(float(pEv.size())) );
if( BIC >= resultBIC )
{
delete pResultBNet;
resultBIC = BIC;
m_critValue.push_back(BIC);
pResultBNet = pBNet;
resultOrder.assign( currentObsNodes.begin(), currentObsNodes.end() );
}
else
{
delete pBNet;
}
for( k = 0; k < pEv.size(); k++ )
{
delete pEv[k];
}
delete pLearn;
}while(std::next_permutation(currentObsNodes.begin(), currentObsNodes.end()));
}
}
}
delete pGraph;
m_pResultGrModel = pResultBNet;
m_resultRenaming.assign(resultOrder.begin(), resultOrder.end());
}
