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/*
* See header file for a description of this class.
*
* \author G. Cerminara - INFN Torino
*/
#include "DTOccupancyCluster.h"
#include "FWCore/MessageLogger/interface/MessageLogger.h"
#include "TH2F.h"
#include "TMath.h"
#include <iostream>
using namespace std;
using namespace edm;
DTOccupancyCluster::DTOccupancyCluster(const DTOccupancyPoint& firstPoint, const DTOccupancyPoint& secondPoint)
: 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)
: 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() {}
// Check if the cluster candidate satisfies the quality requirements
bool DTOccupancyCluster::isValid() const { return theValidity; }
// Add a point to the cluster: returns false if the point does not satisfy the
// quality requirement
bool DTOccupancyCluster::addPoint(const DTOccupancyPoint& anotherPoint) {
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;
}
// Compute the distance of a single point from the cluster
// (minimum distance with respect to the cluster points)
double DTOccupancyCluster::distance(const DTOccupancyPoint& point) const {
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;
}
double DTOccupancyCluster::averageMean() const { return theMeanSum / (double)thePoints.size(); }
double DTOccupancyCluster::averageRMS() const { return theRMSSum / (double)thePoints.size(); }
double DTOccupancyCluster::maxMean() const { return theMaxMean; }
double DTOccupancyCluster::maxRMS() const { return theMaxRMS; }
TH2F* DTOccupancyCluster::getHisto(std::string histoName,
int nBinsX,
double minX,
double maxX,
int nBinsY,
double minY,
double maxY,
int fillColor) const {
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;
}
bool DTOccupancyCluster::qualityCriterion(const DTOccupancyPoint& firstPoint, const DTOccupancyPoint& secondPoint) {
if (firstPoint.deltaMean(secondPoint) < computeAverageRMS(firstPoint, secondPoint) &&
firstPoint.deltaRMS(secondPoint) < computeMinRMS(firstPoint, secondPoint)) {
theValidity = true;
return true;
}
theValidity = false;
return false;
}
bool DTOccupancyCluster::qualityCriterion(const DTOccupancyPoint& anotherPoint) {
double minrms = 0;
if (anotherPoint.rms() < averageRMS())
minrms = anotherPoint.rms();
else
minrms = averageRMS();
if (fabs(averageMean() - anotherPoint.mean()) < averageRMS() &&
fabs(averageRMS() - anotherPoint.rms()) < 2 * minrms / 3.) {
theValidity = true;
return true;
}
theValidity = false;
return false;
}
void DTOccupancyCluster::computeRadius() {
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);
}
int DTOccupancyCluster::nPoints() const { return thePoints.size(); }
set<DTLayerId> DTOccupancyCluster::getLayerIDs() const {
set<DTLayerId> ret;
for (vector<DTOccupancyPoint>::const_iterator point = thePoints.begin(); point != thePoints.end(); ++point) {
ret.insert((*point).layerId());
}
return ret;
}
bool clusterIsLessThan(const DTOccupancyCluster& clusterOne, const DTOccupancyCluster& clusterTwo) {
if (clusterTwo.nPoints() == 1 && clusterOne.nPoints() != 1) {
return true;
}
if (clusterTwo.nPoints() != 1 && clusterOne.nPoints() == 1) {
return false;
}
if (clusterOne.nPoints() > clusterTwo.nPoints()) {
return true;
} else if (clusterOne.nPoints() < clusterTwo.nPoints()) {
return false;
} else {
if (fabs(clusterOne.averageRMS() - sqrt(clusterOne.averageMean())) <
fabs(clusterTwo.averageRMS() - sqrt(clusterTwo.averageMean()))) {
return true;
}
}
return false;
}
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