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DTOccupancyClusterBuilder Class Reference

Build clusters of layer occupancies (DTOccupancyCluster) to spot problematic layers. More...

#include <DQM/DTMonitorClient/src/DTOccupancyClusterBuilder.h>

List of all members.

Public Member Functions

void addPoint (const DTOccupancyPoint &point)
 Add an occupancy point for a given layer.
void buildClusters ()
 build the clusters
void drawClusters (std::string canvasName)
 draw a TH2F histograms showing the clusters
 DTOccupancyClusterBuilder ()
 Constructor.
DTOccupancyCluster getBestCluster () const
 get the cluster correspondig to "normal" cell occupancy.
bool isProblematic (DTLayerId layerId) const
virtual ~DTOccupancyClusterBuilder ()
 Destructor.

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
2008/10/16 09:33:39
Revision
1.3
Author:
G. Cerminara - INFN Torino

Definition at line 22 of file DTOccupancyClusterBuilder.h.

Constructor & Destructor Documentation

DTOccupancyClusterBuilder::DTOccupancyClusterBuilder (  ) 

Constructor.

Definition at line 22 of file DTOccupancyClusterBuilder.cc.

00022                                                        : maxMean(-1.),
00023                                                            maxRMS(-1.) {
00024 }

DTOccupancyClusterBuilder::~DTOccupancyClusterBuilder (  )  [virtual]

Destructor.

Definition at line 26 of file DTOccupancyClusterBuilder.cc.

00026 {}

Member Function Documentation

void DTOccupancyClusterBuilder::addPoint ( const DTOccupancyPoint &  point  ) 

Add an occupancy point for a given layer.

Definition at line 30 of file DTOccupancyClusterBuilder.cc.

References theDistances, and thePoints.

Referenced by DTOccupancyTest::runOccupancyTest().

00030                                                                       {
00031   // loop over points already stored
00032   for(set<DTOccupancyPoint>::const_iterator pt = thePoints.begin(); pt != thePoints.end(); ++pt) {
00033     theDistances[(*pt).distance(point)] = make_pair(*pt, point);
00034   }
00035   //   cout << "[DTOccupancyClusterBuilder] Add point with mean: " << point.mean()
00036   //        << " RMS: " << point.rms() << endl;
00037   thePoints.insert(point);
00038 }

void DTOccupancyClusterBuilder::buildClusters (  ) 

build the clusters

Definition at line 41 of file DTOccupancyClusterBuilder.cc.

References buildNewCluster(), lat::endl(), LogTrace, DTOccupancyCluster::maxMean(), maxMean, DTOccupancyCluster::maxRMS(), maxRMS, sortClusters(), theClusters, and thePoints.

Referenced by DTOccupancyTest::runOccupancyTest().

00041                                               {
00042   //   cout << "[DTOccupancyClusterBuilder] buildClusters" << endl;
00043   while(buildNewCluster()) {
00044     //     cout << "New cluster builded" << endl;
00045     //     cout << "# of remaining points: " << thePoints.size() << endl;
00046     if(thePoints.size() <= 1) break;
00047   }
00048     
00049   // build single point clusters with the remaining points
00050   for(set<DTOccupancyPoint>::const_iterator pt = thePoints.begin(); pt != thePoints.end();
00051       ++pt) {
00052     DTOccupancyCluster clusterCandidate(*pt);
00053     theClusters.push_back(clusterCandidate);
00054     // store the range for building the histograms later
00055     if(clusterCandidate.maxMean() > maxMean) maxMean = clusterCandidate.maxMean();
00056     if(clusterCandidate.maxRMS() > maxRMS) maxRMS = clusterCandidate.maxRMS();
00057   }
00058   LogTrace("DTDQM|DTMonitorClient|DTOccupancyTest|DTOccupancyClusterBuilder")
00059     << " # of valid clusters: " << theClusters.size() << endl;
00060   sortClusters();
00061   
00062 }

bool DTOccupancyClusterBuilder::buildNewCluster (  )  [private]

Definition at line 117 of file DTOccupancyClusterBuilder.cc.

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

Referenced by buildClusters().

00117                                                 {
00118   LogTrace("DTDQM|DTMonitorClient|DTOccupancyTest|DTOccupancyClusterBuilder")
00119     << "--------- New Cluster Candidate ----------------------" << endl;
00120   pair<DTOccupancyPoint, DTOccupancyPoint> initialPair = getInitialPair();
00121   LogTrace("DTDQM|DTMonitorClient|DTOccupancyTest|DTOccupancyClusterBuilder")
00122     << "   Initial Pair: " << endl
00123     << "           point1: mean " << initialPair.first.mean()
00124     << " rms " << initialPair.first.rms() << endl
00125     << "           point2: mean " << initialPair.second.mean()
00126     << " rms " << initialPair.second.rms() << endl;
00127   DTOccupancyCluster clusterCandidate(initialPair.first, initialPair.second);
00128   if(clusterCandidate.isValid()) {
00129     //     cout <<   " cluster candidate is valid" << endl;
00130     // remove already used pair
00131     thePoints.erase(initialPair.first);
00132     thePoints.erase(initialPair.second);
00133     if(thePoints.size() != 0) {
00134       computeDistancesToCluster(clusterCandidate);
00135       while(clusterCandidate.addPoint(theDistancesFromTheCluster.begin()->second)) {
00136         thePoints.erase(theDistancesFromTheCluster.begin()->second);
00137         if(thePoints.size() ==0) break;
00138         computeDistancesToCluster(clusterCandidate);
00139       }
00140     }
00141   } else {
00142     return false;
00143   }
00144   LogTrace("DTDQM|DTMonitorClient|DTOccupancyTest|DTOccupancyClusterBuilder")
00145     << "   # of layers: " << clusterCandidate.nPoints()
00146     << " avrg. mean: " << clusterCandidate.averageMean() << " avrg. rms: " << clusterCandidate.averageRMS() << endl;
00147   theClusters.push_back(clusterCandidate);
00148   // store the range for building the histograms later
00149   if(clusterCandidate.maxMean() > maxMean) maxMean = clusterCandidate.maxMean();
00150   if(clusterCandidate.maxRMS() > maxRMS) maxRMS = clusterCandidate.maxRMS();
00151   computePointToPointDistances();
00152   return true;
00153 }

void DTOccupancyClusterBuilder::computeDistancesToCluster ( const DTOccupancyCluster &  cluster  )  [private]

Definition at line 109 of file DTOccupancyClusterBuilder.cc.

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

Referenced by buildNewCluster().

00109                                                                                            {
00110   theDistancesFromTheCluster.clear();
00111   for(set<DTOccupancyPoint>::const_iterator pt = thePoints.begin(); pt != thePoints.end(); ++pt) {
00112     theDistancesFromTheCluster[cluster.distance(*pt)] = *pt;
00113   }
00114 }

void DTOccupancyClusterBuilder::computePointToPointDistances (  )  [private]

Definition at line 94 of file DTOccupancyClusterBuilder.cc.

References theDistances, and thePoints.

Referenced by buildNewCluster().

00094                                                              {
00095   theDistances.clear();
00096   for(set<DTOccupancyPoint>::const_iterator pt_i = thePoints.begin(); pt_i != thePoints.end();
00097       ++pt_i) { // i loopo
00098     for(set<DTOccupancyPoint>::const_iterator pt_j = thePoints.begin(); pt_j != thePoints.end();
00099         ++pt_j) { // j loop
00100       if(*pt_i != *pt_j) {
00101         theDistances[pt_i->distance(*pt_j)] = make_pair(*pt_i, *pt_j);
00102       }
00103     }
00104   }
00105 }

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

draw a TH2F histograms showing the clusters

Definition at line 65 of file DTOccupancyClusterBuilder.cc.

References histo, maxMean, maxRMS, and theClusters.

00065                                                                  {
00066   int nBinsX = 100;
00067   int nBinsY = 100;
00068   int colorMap[12] = {632, 600, 800, 400, 820, 416, 432, 880, 616, 860, 900, 920};
00069 
00070   //   cout << "Draw clusters: " << endl;
00071   //   cout << "    max mean: " << maxMean << " max rms: " << maxRMS << endl;
00072 
00073   TCanvas *canvas = new TCanvas(canvasName.c_str(),canvasName.c_str()); 
00074   canvas->cd();
00075   for(vector<DTOccupancyCluster>::const_iterator cluster = theClusters.begin();
00076       cluster != theClusters.end(); ++cluster) {
00077     stringstream stream;
00078     stream << canvasName << "_" << cluster-theClusters.begin();
00079     string histoName = stream.str();
00080     TH2F *histo = (*cluster).getHisto(histoName, nBinsX, 0, maxMean+3*maxMean/100.,
00081                                       nBinsY, 0, maxRMS+3*maxRMS/100., colorMap[cluster-theClusters.begin()]);
00082     if(cluster == theClusters.begin()) 
00083       histo->Draw("box");
00084     else
00085       histo->Draw("box,same");
00086   }
00087 }

DTOccupancyCluster DTOccupancyClusterBuilder::getBestCluster (  )  const

get the cluster correspondig to "normal" cell occupancy.

Definition at line 173 of file DTOccupancyClusterBuilder.cc.

References theClusters.

Referenced by DTOccupancyTest::runOccupancyTest().

00173                                                                    {
00174   return theClusters.front();
00175 }

std::pair< DTOccupancyPoint, DTOccupancyPoint > DTOccupancyClusterBuilder::getInitialPair (  )  [private]

Definition at line 90 of file DTOccupancyClusterBuilder.cc.

References theDistances.

Referenced by buildNewCluster().

00090                                                                                       {
00091   return theDistances.begin()->second;
00092 }

bool DTOccupancyClusterBuilder::isProblematic ( DTLayerId  layerId  )  const

Definition at line 177 of file DTOccupancyClusterBuilder.cc.

References theProblematicLayers.

Referenced by DTOccupancyTest::runOccupancyTest().

00177                                                                      {
00178   if(theProblematicLayers.find(layerId) != theProblematicLayers.end()) {
00179     return true;
00180   }
00181   return false;
00182 }

void DTOccupancyClusterBuilder::sortClusters (  )  [private]

Definition at line 157 of file DTOccupancyClusterBuilder.cc.

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

Referenced by buildClusters().

00157                                              {
00158   LogTrace("DTDQM|DTMonitorClient|DTOccupancyTest|DTOccupancyClusterBuilder") << " sorting" << endl;
00159   sort(theClusters.begin(), theClusters.end(), clusterIsLessThan);
00160   // we save the detid of the clusters which are not the best one
00161   for(vector<DTOccupancyCluster>::const_iterator cluster = ++(theClusters.begin());
00162       cluster != theClusters.end(); ++cluster) { // loop over clusters skipping the first
00163     set<DTLayerId> clusterLayers = (*cluster).getLayerIDs();
00164     LogTrace("DTDQM|DTMonitorClient|DTOccupancyTest|DTOccupancyClusterBuilder")
00165       << "     # layers in the cluster: " << clusterLayers.size() << endl;
00166     theProblematicLayers.insert(clusterLayers.begin(), clusterLayers.end());
00167   }
00168   LogTrace("DTDQM|DTMonitorClient|DTOccupancyTest|DTOccupancyClusterBuilder")
00169     << " # of problematic layers: " << theProblematicLayers.size() << endl;
00170 }

Member Data Documentation

double DTOccupancyClusterBuilder::maxMean [private]

Definition at line 64 of file DTOccupancyClusterBuilder.h.

Referenced by buildClusters(), buildNewCluster(), and drawClusters().

double DTOccupancyClusterBuilder::maxRMS [private]

Definition at line 65 of file DTOccupancyClusterBuilder.h.

Referenced by buildClusters(), buildNewCluster(), and drawClusters().

std::vector<DTOccupancyCluster> DTOccupancyClusterBuilder::theClusters [private]

Definition at line 61 of file DTOccupancyClusterBuilder.h.

Referenced by buildClusters(), buildNewCluster(), drawClusters(), getBestCluster(), and sortClusters().

std::map<double, std::pair<DTOccupancyPoint, DTOccupancyPoint> > DTOccupancyClusterBuilder::theDistances [private]

Definition at line 59 of file DTOccupancyClusterBuilder.h.

Referenced by addPoint(), computePointToPointDistances(), and getInitialPair().

std::map<double, DTOccupancyPoint> DTOccupancyClusterBuilder::theDistancesFromTheCluster [private]

Definition at line 60 of file DTOccupancyClusterBuilder.h.

Referenced by buildNewCluster(), and computeDistancesToCluster().

std::set<DTOccupancyPoint> DTOccupancyClusterBuilder::thePoints [private]

Definition at line 58 of file DTOccupancyClusterBuilder.h.

Referenced by addPoint(), buildClusters(), buildNewCluster(), computeDistancesToCluster(), and computePointToPointDistances().

std::set<DTLayerId> DTOccupancyClusterBuilder::theProblematicLayers [private]

Definition at line 62 of file DTOccupancyClusterBuilder.h.

Referenced by isProblematic(), and sortClusters().

The documentation for this class was generated from the following files:
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