#include <DTOccupancyClusterBuilder.h>

Public Member Functions
void	addPoint (const DTOccupancyPoint &point)
	Add an occupancy point for a given layer. More...

void	buildClusters ()
	build the clusters More...

void	drawClusters (std::string canvasName)
	draw a TH2F histograms showing the clusters More...

	DTOccupancyClusterBuilder ()
	Constructor. More...

DTOccupancyCluster	getBestCluster () const
	get the cluster correspondig to "normal" cell occupancy. More...

bool	isProblematic (DTLayerId layerId) const

virtual	~DTOccupancyClusterBuilder ()
	Destructor. More...

Private Member Functions
bool	buildNewCluster ()

void	computeDistancesToCluster (const DTOccupancyCluster &cluster)

void	computePointToPointDistances ()

std::pair< DTOccupancyPoint, DTOccupancyPoint >	getInitialPair ()

void	sortClusters ()

Private Attributes
double	maxMean

double	maxRMS

std::vector< DTOccupancyCluster >	theClusters

std::map< double, std::pair < DTOccupancyPoint, DTOccupancyPoint > >	theDistances

std::map< double, DTOccupancyPoint >	theDistancesFromTheCluster

std::set< DTOccupancyPoint >	thePoints

std::set< DTLayerId >	theProblematicLayers

Detailed Description

Build clusters of layer occupancies (DTOccupancyCluster) to spot problematic layers. It's used by DTOccupancyTest.

Date:: 2008/07/02 16:50:27

Revision:: 1.2

Author: G. Cerminara - INFN Torino

Definition at line 22 of file DTOccupancyClusterBuilder.h.

Constructor & Destructor Documentation

DTOccupancyClusterBuilder::DTOccupancyClusterBuilder ( )

Constructor.

Definition at line 23 of file DTOccupancyClusterBuilder.cc.

                                                        : maxMean(-1.),
                                maxRMS(-1.) {
 }

DTOccupancyClusterBuilder::~DTOccupancyClusterBuilder ( )

virtual

Destructor.

Definition at line 27 of file DTOccupancyClusterBuilder.cc.

27 {}

Member Function Documentation

void DTOccupancyClusterBuilder::addPoint ( const DTOccupancyPoint & point )

Add an occupancy point for a given layer.

Definition at line 31 of file DTOccupancyClusterBuilder.cc.

References ExpressReco_HICollisions_FallBack::pt, theDistances, and thePoints.

Referenced by DTOccupancyTest::runOccupancyTest().

                                                                       {
   // loop over points already stored
   for(set<DTOccupancyPoint>::const_iterator pt = thePoints.begin(); pt != thePoints.end(); ++pt) {
     theDistances[(*pt).distance(point)] = make_pair(*pt, point);
   }
   //   cout << "[DTOccupancyClusterBuilder] Add point with mean: " << point.mean()
   //        << " RMS: " << point.rms() << endl;
   thePoints.insert(point);
 }

void DTOccupancyClusterBuilder::buildClusters ( )

build the clusters

Definition at line 42 of file DTOccupancyClusterBuilder.cc.

References buildNewCluster(), LogTrace, DTOccupancyCluster::maxMean(), maxMean, DTOccupancyCluster::maxRMS(), maxRMS, ExpressReco_HICollisions_FallBack::pt, sortClusters(), theClusters, and thePoints.

Referenced by DTOccupancyTest::runOccupancyTest().

                                               {
   //   cout << "[DTOccupancyClusterBuilder] buildClusters" << endl;
   while(buildNewCluster()) {
     //     cout << "New cluster builded" << endl;
     //     cout << "# of remaining points: " << thePoints.size() << endl;
     if(thePoints.size() <= 1) break;
   }
     
   // build single point clusters with the remaining points
   for(set<DTOccupancyPoint>::const_iterator pt = thePoints.begin(); pt != thePoints.end();
       ++pt) {
     DTOccupancyCluster clusterCandidate(*pt);
     theClusters.push_back(clusterCandidate);
     // store the range for building the histograms later
     if(clusterCandidate.maxMean() > maxMean) maxMean = clusterCandidate.maxMean();
     if(clusterCandidate.maxRMS() > maxRMS) maxRMS = clusterCandidate.maxRMS();
   }
   LogTrace("DTDQM|DTMonitorClient|DTOccupancyTest|DTOccupancyClusterBuilder")
     << " # of valid clusters: " << theClusters.size() << endl;
   sortClusters();
   
 }

bool DTOccupancyClusterBuilder::buildNewCluster ( )

private

Definition at line 118 of file DTOccupancyClusterBuilder.cc.

References DTOccupancyCluster::addPoint(), DTOccupancyCluster::averageMean(), DTOccupancyCluster::averageRMS(), computeDistancesToCluster(), computePointToPointDistances(), getInitialPair(), DTOccupancyCluster::isValid(), LogTrace, DTOccupancyCluster::maxMean(), maxMean, DTOccupancyCluster::maxRMS(), maxRMS, DTOccupancyCluster::nPoints(), theClusters, theDistancesFromTheCluster, and thePoints.

Referenced by buildClusters().

                                                 {
   LogTrace("DTDQM|DTMonitorClient|DTOccupancyTest|DTOccupancyClusterBuilder")
     << "--------- New Cluster Candidate ----------------------" << endl;
   pair<DTOccupancyPoint, DTOccupancyPoint> initialPair = getInitialPair();
   LogTrace("DTDQM|DTMonitorClient|DTOccupancyTest|DTOccupancyClusterBuilder")
     << "   Initial Pair: " << endl
     << "           point1: mean " << initialPair.first.mean()
     << " rms " << initialPair.first.rms() << endl
     << "           point2: mean " << initialPair.second.mean()
     << " rms " << initialPair.second.rms() << endl;
   DTOccupancyCluster clusterCandidate(initialPair.first, initialPair.second);
   if(clusterCandidate.isValid()) {
     //     cout <<   " cluster candidate is valid" << endl;
     // remove already used pair
     thePoints.erase(initialPair.first);
     thePoints.erase(initialPair.second);
     if(thePoints.size() != 0) {
       computeDistancesToCluster(clusterCandidate);
       while(clusterCandidate.addPoint(theDistancesFromTheCluster.begin()->second)) {
     thePoints.erase(theDistancesFromTheCluster.begin()->second);
     if(thePoints.size() ==0) break;
     computeDistancesToCluster(clusterCandidate);
       }
     }
   } else {
     return false;
   }
   LogTrace("DTDQM|DTMonitorClient|DTOccupancyTest|DTOccupancyClusterBuilder")
     << "   # of layers: " << clusterCandidate.nPoints()
     << " avrg. mean: " << clusterCandidate.averageMean() << " avrg. rms: " << clusterCandidate.averageRMS() << endl;
   theClusters.push_back(clusterCandidate);
   // store the range for building the histograms later
   if(clusterCandidate.maxMean() > maxMean) maxMean = clusterCandidate.maxMean();
   if(clusterCandidate.maxRMS() > maxRMS) maxRMS = clusterCandidate.maxRMS();
   computePointToPointDistances();
   return true;
 }

void DTOccupancyClusterBuilder::computeDistancesToCluster ( const DTOccupancyCluster & cluster )

private

Definition at line 110 of file DTOccupancyClusterBuilder.cc.

References DTOccupancyCluster::distance(), ExpressReco_HICollisions_FallBack::pt, theDistancesFromTheCluster, and thePoints.

Referenced by buildNewCluster().

                                                                                            {
   theDistancesFromTheCluster.clear();
   for(set<DTOccupancyPoint>::const_iterator pt = thePoints.begin(); pt != thePoints.end(); ++pt) {
     theDistancesFromTheCluster[cluster.distance(*pt)] = *pt;
   }
 }

void DTOccupancyClusterBuilder::computePointToPointDistances ( )

private

Definition at line 95 of file DTOccupancyClusterBuilder.cc.

References theDistances, and thePoints.

Referenced by buildNewCluster().

                                                              {
   theDistances.clear();
   for(set<DTOccupancyPoint>::const_iterator pt_i = thePoints.begin(); pt_i != thePoints.end();
       ++pt_i) { // i loopo
     for(set<DTOccupancyPoint>::const_iterator pt_j = thePoints.begin(); pt_j != thePoints.end();
     ++pt_j) { // j loop
       if(*pt_i != *pt_j) {
     theDistances[pt_i->distance(*pt_j)] = make_pair(*pt_i, *pt_j);
       }
     }
   }
 }

void DTOccupancyClusterBuilder::drawClusters ( std::string canvasName )

draw a TH2F histograms showing the clusters

Definition at line 66 of file DTOccupancyClusterBuilder.cc.

References svgfig::canvas(), trackerHits::histo, maxMean, maxRMS, and theClusters.

                                                                  {
   int nBinsX = 100;
   int nBinsY = 100;
   int colorMap[12] = {632, 600, 800, 400, 820, 416, 432, 880, 616, 860, 900, 920};
 
   //   cout << "Draw clusters: " << endl;
   //   cout << "    max mean: " << maxMean << " max rms: " << maxRMS << endl;
 
   TCanvas *canvas = new TCanvas(canvasName.c_str(),canvasName.c_str()); 
   canvas->cd();
   for(vector<DTOccupancyCluster>::const_iterator cluster = theClusters.begin();
       cluster != theClusters.end(); ++cluster) {
     stringstream stream;
     stream << canvasName << "_" << cluster-theClusters.begin();
     string histoName = stream.str();
     TH2F *histo = (*cluster).getHisto(histoName, nBinsX, 0, maxMean+3*maxMean/100.,
                       nBinsY, 0, maxRMS+3*maxRMS/100., colorMap[cluster-theClusters.begin()]);
     if(cluster == theClusters.begin()) 
       histo->Draw("box");
     else
       histo->Draw("box,same");
   }
 }

DTOccupancyCluster DTOccupancyClusterBuilder::getBestCluster ( ) const

get the cluster correspondig to "normal" cell occupancy.

Definition at line 174 of file DTOccupancyClusterBuilder.cc.

References theClusters.

Referenced by DTOccupancyTest::runOccupancyTest().

                                                                    {
   return theClusters.front();
 }

std::pair< DTOccupancyPoint, DTOccupancyPoint > DTOccupancyClusterBuilder::getInitialPair ( )

private

Definition at line 91 of file DTOccupancyClusterBuilder.cc.

References theDistances.

Referenced by buildNewCluster().

                                                                                       {
   return theDistances.begin()->second;
 }

bool DTOccupancyClusterBuilder::isProblematic ( DTLayerId layerId ) const

Definition at line 178 of file DTOccupancyClusterBuilder.cc.

References theProblematicLayers.

Referenced by DTOccupancyTest::runOccupancyTest().

                                                                      {
   if(theProblematicLayers.find(layerId) != theProblematicLayers.end()) {
     return true;
   }
   return false;
 }

void DTOccupancyClusterBuilder::sortClusters ( )

private

Definition at line 158 of file DTOccupancyClusterBuilder.cc.

References clusterIsLessThan(), LogTrace, python.multivaluedict::sort(), theClusters, and theProblematicLayers.

Referenced by buildClusters().

                                              {
   LogTrace("DTDQM|DTMonitorClient|DTOccupancyTest|DTOccupancyClusterBuilder") << " sorting" << endl;
   sort(theClusters.begin(), theClusters.end(), clusterIsLessThan);
   // we save the detid of the clusters which are not the best one
   for(vector<DTOccupancyCluster>::const_iterator cluster = ++(theClusters.begin());
       cluster != theClusters.end(); ++cluster) { // loop over clusters skipping the first
     set<DTLayerId> clusterLayers = (*cluster).getLayerIDs();
     LogTrace("DTDQM|DTMonitorClient|DTOccupancyTest|DTOccupancyClusterBuilder")
       << "     # layers in the cluster: " << clusterLayers.size() << endl;
     theProblematicLayers.insert(clusterLayers.begin(), clusterLayers.end());
   }
   LogTrace("DTDQM|DTMonitorClient|DTOccupancyTest|DTOccupancyClusterBuilder")
     << " # of problematic layers: " << theProblematicLayers.size() << endl;
 }