#include <DTOccupancyCluster.h>

Public Member Functions
bool	addPoint (const DTOccupancyPoint &anotherPoint)
double	averageMean () const
	average cell occupancy of the layers in the cluster
double	averageRMS () const
	average RMS of the cell occpuancy distributions of the layers in the cluster
double	distance (const DTOccupancyPoint &point) const
	DTOccupancyCluster (const DTOccupancyPoint &firstPoint, const DTOccupancyPoint &secondPoint)
	Constructor.
	DTOccupancyCluster (const DTOccupancyPoint &singlePoint)
	Constructor.
TH2F *	getHisto (std::string histoName, int nBinsX, double minX, double maxX, int nBinsY, double minY, double maxY, int fillColor) const
	get a TH2F displaying the cluster
std::set< DTLayerId >	getLayerIDs () const
bool	isValid () const
	Check if the cluster candidate satisfies the quality requirements.
double	maxMean () const
	max average cell occupancy of the layers in the cluster
double	maxRMS () const
	max RMS of the cell occpuancy distributions of the layers in the cluster
int	nPoints () const
	# of layers belonging to the cluster
virtual	~DTOccupancyCluster ()
	Destructor.
Private Member Functions
void	computeRadius ()
bool	qualityCriterion (const DTOccupancyPoint &firstPoint, const DTOccupancyPoint &secondPoint)
bool	qualityCriterion (const DTOccupancyPoint &anotherPoint)
Private Attributes
double	radius
double	theMaxMean
double	theMaxRMS
double	theMeanSum
std::vector< DTOccupancyPoint >	thePoints
double	theRMSSum
bool	theValidity

Detailed Description

Cluster of DTOccupancyPoint used bt DTOccupancyTest to spot problematic layers. Layers are clusterized in the plane average cell occupancy - RMS of the cell occupancies.

Date:: 2008/10/16 09:33:39

Revision:: 1.3

Author:: G. Cerminara - INFN Torino

Definition at line 22 of file DTOccupancyCluster.h.

Constructor & Destructor Documentation

DTOccupancyCluster::DTOccupancyCluster	(	const DTOccupancyPoint &	firstPoint,
		const DTOccupancyPoint &	secondPoint
	)

Constructor.

Definition at line 22 of file DTOccupancyCluster.cc.

References computeRadius(), DTOccupancyPoint::mean(), qualityCriterion(), DTOccupancyPoint::rms(), theMaxMean, theMaxRMS, theMeanSum, thePoints, theRMSSum, and theValidity.

                                                                            : radius(0),
                                                                              theMaxMean(-1.),
                                                                              theMaxRMS(-1.),
                                                                              theMeanSum(0.),
                                                                              theRMSSum(0.) {
  if(!qualityCriterion(firstPoint,secondPoint)) {
    theValidity = false;
  } else {
    // compute the cluster quantities
    thePoints.push_back(firstPoint);
    thePoints.push_back(secondPoint);
    if(firstPoint.mean() > secondPoint.mean()) theMaxMean = firstPoint.mean();
    else theMaxMean = secondPoint.mean();

    if(firstPoint.rms() > secondPoint.rms()) theMaxRMS = firstPoint.rms();
    else theMaxRMS = secondPoint.rms();
    theMeanSum += firstPoint.mean();
    theRMSSum += firstPoint.rms();

    theMeanSum += secondPoint.mean();
    theRMSSum += secondPoint.rms();


    computeRadius();
  }
}

DTOccupancyCluster::DTOccupancyCluster ( const DTOccupancyPoint & singlePoint )

Constructor.

Definition at line 52 of file DTOccupancyCluster.cc.

References thePoints, and theValidity.

                                                                          : radius(0),
                                                                              theMaxMean(singlePoint.mean()),
                                                                              theMaxRMS(singlePoint.rms()),
                                                                              theMeanSum(singlePoint.mean()),
                                                                              theRMSSum(singlePoint.rms()) {
  theValidity = true;

  // compute the cluster quantities
  thePoints.push_back(singlePoint);
}

DTOccupancyCluster::~DTOccupancyCluster ( ) [virtual]

Destructor.

Definition at line 65 of file DTOccupancyCluster.cc.

{}

Member Function Documentation

bool DTOccupancyCluster::addPoint ( const DTOccupancyPoint & anotherPoint )

Add a point to the cluster: returns false if the point does not satisfy the quality requirement

Definition at line 78 of file DTOccupancyCluster.cc.

References computeRadius(), LogTrace, DTOccupancyPoint::mean(), qualityCriterion(), DTOccupancyPoint::rms(), theMaxMean, theMaxRMS, theMeanSum, thePoints, and theRMSSum.

Referenced by DTOccupancyClusterBuilder::buildNewCluster().

                                                                      {
  LogTrace("DTDQM|DTMonitorClient|DTOccupancyTest|DTOccupancyCluster")
    << "   Add a point to the cluster: mean: " << anotherPoint.mean()
    << " rms: " << anotherPoint.rms() << endl;
  if(qualityCriterion(anotherPoint)) {
    LogTrace("DTDQM|DTMonitorClient|DTOccupancyTest|DTOccupancyCluster") << "   point is valid" << endl;
    thePoints.push_back(anotherPoint);
    // Compute the new cluster size
    computeRadius();
    // compute the max mean and RMS
    if(anotherPoint.mean() > theMaxMean) {
      theMaxMean = anotherPoint.mean();
    }
    if(anotherPoint.rms() > theMaxRMS) {
      theMaxRMS = anotherPoint.rms();
    }
    theMeanSum += anotherPoint.mean();
    theRMSSum += anotherPoint.rms();
    return true;
  } 
  return false;
}

double DTOccupancyCluster::averageMean ( ) const

average cell occupancy of the layers in the cluster

Definition at line 120 of file DTOccupancyCluster.cc.

References theMeanSum, and thePoints.

Referenced by DTOccupancyClusterBuilder::buildNewCluster(), clusterIsLessThan(), qualityCriterion(), and DTOccupancyTest::runOccupancyTest().

                                              {
  return theMeanSum/(double)thePoints.size();
}

double DTOccupancyCluster::averageRMS ( ) const

average RMS of the cell occpuancy distributions of the layers in the cluster

Definition at line 126 of file DTOccupancyCluster.cc.

References thePoints, and theRMSSum.

Referenced by DTOccupancyClusterBuilder::buildNewCluster(), clusterIsLessThan(), qualityCriterion(), and DTOccupancyTest::runOccupancyTest().

                                             {
  return theRMSSum/(double)thePoints.size();
}

void DTOccupancyCluster::computeRadius ( ) [private]

Definition at line 216 of file DTOccupancyCluster.cc.

References radius, mathSSE::sqrt(), and thePoints.

Referenced by addPoint(), and DTOccupancyCluster().

                                       {
  double radius_squared = 0;
  for(vector<DTOccupancyPoint>::const_iterator pt_i = thePoints.begin();
      pt_i != thePoints.end(); ++pt_i) {
    for(vector<DTOccupancyPoint>::const_iterator pt_j = thePoints.begin();
        pt_j != thePoints.end(); ++pt_j) {
      radius_squared += TMath::Power(pt_i->distance(*pt_j),2);
    }
  }
  radius_squared = radius_squared/(2*TMath::Power(thePoints.size()+1,2));
  radius = sqrt(radius_squared);
  //   cout << "    the new cluster radius is: " << radius << endl;
}

double DTOccupancyCluster::distance ( const DTOccupancyPoint & point ) const

Compute the distance of a single point from the cluster (minimum distance with respect to the cluster points)

Definition at line 105 of file DTOccupancyCluster.cc.

References DTOccupancyPoint::distance(), and thePoints.

Referenced by DTOccupancyClusterBuilder::computeDistancesToCluster().

                                                                       {
  double dist = 99999999;
  // compute the minimum distance from a point
  for(vector<DTOccupancyPoint>::const_iterator pt = thePoints.begin();
      pt != thePoints.end(); ++pt) {
    double distance = point.distance(*pt);
    if(distance < dist) {
      dist = distance;
    }
  }
  return dist;
}

TH2F * DTOccupancyCluster::getHisto	(	std::string	histoName,
		int	nBinsX,
		double	minX,
		double	maxX,
		int	nBinsY,
		double	minY,
		double	maxY,
		int	fillColor
	)		const

get a TH2F displaying the cluster

Definition at line 144 of file DTOccupancyCluster.cc.

References timingPdfMaker::histo, and thePoints.

                                                                                               {
  TH2F *histo = new TH2F(histoName.c_str(),histoName.c_str(),
                         nBinsX, minX, maxX, nBinsY, minY, maxY);
  histo->SetFillColor(fillColor);
  for(vector<DTOccupancyPoint>::const_iterator pt = thePoints.begin();
      pt != thePoints.end(); ++pt) {
    histo->Fill((*pt).mean(), (*pt).rms());
  }
  return histo;
}

set< DTLayerId > DTOccupancyCluster::getLayerIDs ( ) const

Definition at line 237 of file DTOccupancyCluster.cc.

References point, run_regression::ret, and thePoints.

                                                     {
  set<DTLayerId> ret;
  for(vector<DTOccupancyPoint>::const_iterator point = thePoints.begin();
      point != thePoints.end(); ++point) {
    ret.insert((*point).layerId());
  }
  return ret;
}

bool DTOccupancyCluster::isValid ( void ) const

Check if the cluster candidate satisfies the quality requirements.

Definition at line 70 of file DTOccupancyCluster.cc.

References theValidity.

Referenced by DTOccupancyClusterBuilder::buildNewCluster().

                                       {
  return theValidity;
}

double DTOccupancyCluster::maxMean ( ) const

max average cell occupancy of the layers in the cluster

Definition at line 132 of file DTOccupancyCluster.cc.

References theMaxMean.

Referenced by DTOccupancyClusterBuilder::buildClusters(), and DTOccupancyClusterBuilder::buildNewCluster().

                                          {
  return theMaxMean;
}

double DTOccupancyCluster::maxRMS ( ) const

max RMS of the cell occpuancy distributions of the layers in the cluster

Definition at line 138 of file DTOccupancyCluster.cc.

References theMaxRMS.

Referenced by DTOccupancyClusterBuilder::buildClusters(), and DTOccupancyClusterBuilder::buildNewCluster().

                                         {
  return theMaxRMS;
}

int DTOccupancyCluster::nPoints ( ) const

# of layers belonging to the cluster

Definition at line 232 of file DTOccupancyCluster.cc.

References thePoints.

Referenced by DTOccupancyClusterBuilder::buildNewCluster(), and clusterIsLessThan().

                                      {
  return thePoints.size();
}

bool DTOccupancyCluster::qualityCriterion	(	const DTOccupancyPoint &	firstPoint,
		const DTOccupancyPoint &	secondPoint
	)		`[private]`

Definition at line 158 of file DTOccupancyCluster.cc.

References computeAverageRMS(), computeMinRMS(), DTOccupancyPoint::deltaMean(), DTOccupancyPoint::deltaRMS(), and theValidity.

Referenced by addPoint(), and DTOccupancyCluster().

                                                                               {
  //   cout << "   Seed qualityCriterion results: " << endl;
  //   cout << "      delta mean: " << firstPoint.deltaMean(secondPoint) << endl;
  //   cout << "      delta rms: " << firstPoint.deltaRMS(secondPoint) << endl;
  //   cout << "      average rms: " << computeAverageRMS(firstPoint, secondPoint) << endl;
  //   cout << "      min rms: " << computeMinRMS(firstPoint, secondPoint) << endl;
  if(firstPoint.deltaMean(secondPoint) <  computeAverageRMS(firstPoint, secondPoint) &&
     firstPoint.deltaRMS(secondPoint) < computeMinRMS(firstPoint, secondPoint)) {
    theValidity = true;
    //     cout << "    seed is valid!" << endl;
    return true;
  }  
  //   cout << "    seed is not valid!" << endl;
  theValidity = false;
  return false;
}

bool DTOccupancyCluster::qualityCriterion ( const DTOccupancyPoint & anotherPoint ) [private]

Definition at line 179 of file DTOccupancyCluster.cc.

References averageMean(), averageRMS(), DTOccupancyPoint::mean(), DTOccupancyPoint::rms(), and theValidity.

                                                                               {
  //   double minDistance = distance(anotherPoint);

  double minrms = 0;
  if(anotherPoint.rms() < averageRMS()) minrms = anotherPoint.rms();
  else minrms = averageRMS();

  //   cout << "  delta mean: " <<   fabs(averageMean() - anotherPoint.mean()) << endl;
  //   cout << "  average RMS: " << fabs(averageRMS() + anotherPoint.rms())/2. << endl;
  //   cout << "  delta rms: " <<  fabs(averageRMS() - anotherPoint.rms()) << endl;
  //   cout << " min rms: " << minrms << endl;
  //   if(fabs(averageMean() - anotherPoint.mean()) < fabs(averageRMS() + anotherPoint.rms())/2. &&
  //      fabs(averageRMS() - anotherPoint.rms()) < minrms) {

  if(fabs(averageMean() - anotherPoint.mean()) < averageRMS() &&
     fabs(averageRMS() - anotherPoint.rms()) < 2*minrms/3.) {
    theValidity = true;
    //     cout << "    point is valid!" << endl;
    return true;
  }  
  //   cout << "    point is not valid!" << endl;
  theValidity = false;
  return false;

  //   if(thePoints.size() == 1) return false;
  //   // Get the minimum distance from the point
  //   double minDistance = distance(anotherPoint);
  //   cout << "     min distance from cluster is: " << minDistance << endl;
  //   cout << "     radius is: " << radius << endl;
  //   // compare the minimum distance with the radius;
  //   if(minDistance < 2*radius) return true;
  //   else return false;
}