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Vx3DHLTAnalyzer.cc
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Vx3DHLTAnalyzer.cc
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/*
\File Vx3DHLTAnalyzer.cc
\Display Beam-spot monitor entirely based on pixel detector information
the monitoring is based on a 3D fit to the vertex cloud
\Author Mauro Dinardo
\Version $ Revision: 3.5 $
\Date $ Date: 2010/23/02 13:15:00 $
*/
#include "DQM/BeamMonitor/plugins/Vx3DHLTAnalyzer.h"
#include "FWCore/Utilities/interface/isFinite.h"
#include "FWCore/Framework/interface/LuminosityBlock.h"
#include <Math/Minimizer.h>
#include <Math/Factory.h>
#include <Math/Functor.h>
// ### Calling namespaces ###
using namespace std;
using namespace edm;
using namespace reco;
Vx3DHLTAnalyzer::Vx3DHLTAnalyzer(const ParameterSet& iConfig) {
debugMode = true;
nLumiFit = 2; // Number of integrated lumis to perform the fit
maxLumiIntegration =
15; // If failing fits, this is the maximum number of integrated lumis after which a reset is issued
nLumiXaxisRange = 5000; // Correspond to about 32h of data taking: 32h * 60min * 60s / 23s per lumi-block = 5009
dataFromFit = true; // The Beam Spot data can be either taken from the histograms or from the fit results
minNentries = 20; // Minimum number of good vertices to perform the fit
xRange = 0.8; // [cm]
xStep = 0.001; // [cm]
yRange = 0.8; // [cm]
yStep = 0.001; // [cm]
zRange = 30.; // [cm]
zStep = 0.04; // [cm]
VxErrCorr = 1.3;
minVxDoF = 10.; // Good-vertex selection cut
// For vertex fitter without track-weight: d.o.f. = 2*NTracks - 3
// For vertex fitter with track-weight: d.o.f. = sum_NTracks(2*track_weight) - 3
minVxWgt = 0.5; // Good-vertex selection cut
fileName = "BeamPixelResults.txt";
vertexCollection = consumes<VertexCollection>(
iConfig.getUntrackedParameter<InputTag>("vertexCollection", InputTag("pixelVertices")));
pixelHitCollection = consumes<SiPixelRecHitCollection>(
iConfig.getUntrackedParameter<InputTag>("pixelHitCollection", InputTag("siPixelRecHits")));
debugMode = iConfig.getParameter<bool>("debugMode");
nLumiFit = iConfig.getParameter<unsigned int>("nLumiFit");
maxLumiIntegration = iConfig.getParameter<unsigned int>("maxLumiIntegration");
nLumiXaxisRange = iConfig.getParameter<unsigned int>("nLumiXaxisRange");
dataFromFit = iConfig.getParameter<bool>("dataFromFit");
minNentries = iConfig.getParameter<unsigned int>("minNentries");
xRange = iConfig.getParameter<double>("xRange");
xStep = iConfig.getParameter<double>("xStep");
yRange = iConfig.getParameter<double>("yRange");
yStep = iConfig.getParameter<double>("yStep");
zRange = iConfig.getParameter<double>("zRange");
zStep = iConfig.getParameter<double>("zStep");
VxErrCorr = iConfig.getParameter<double>("VxErrCorr");
minVxDoF = iConfig.getParameter<double>("minVxDoF");
minVxWgt = iConfig.getParameter<double>("minVxWgt");
fileName = iConfig.getParameter<string>("fileName");
// ### Set internal variables ###
nParams = 9; // Number of free parameters in the fit
internalDebug = false;
considerVxCovariance = true; // Deconvolute vertex covariance matrix
pi = 3.141592653589793238;
// ##############################
}
Vx3DHLTAnalyzer::~Vx3DHLTAnalyzer() {}
void Vx3DHLTAnalyzer::analyze(const Event& iEvent, const EventSetup& iSetup) {
Handle<VertexCollection> Vx3DCollection;
iEvent.getByToken(vertexCollection, Vx3DCollection);
unsigned int i, j;
double det;
VertexType MyVertex;
if (runNumber != iEvent.id().run()) {
reset("scratch");
runNumber = iEvent.id().run();
if (debugMode == true) {
stringstream debugFile;
string tmp(fileName);
if (outputDebugFile.is_open() == true)
outputDebugFile.close();
tmp.erase(strlen(fileName.c_str()) - 4, 4);
debugFile << tmp.c_str() << "_Run" << iEvent.id().run() << ".txt";
outputDebugFile.open(debugFile.str().c_str(), ios::out);
outputDebugFile.close();
outputDebugFile.open(debugFile.str().c_str(), ios::app);
}
dqmBeginLuminosityBlock(iEvent.getLuminosityBlock(), iSetup);
} else if (beginTimeOfFit != 0) {
totalHits += HitCounter(iEvent);
if (internalDebug == true) {
edm::LogInfo("Vx3DHLTAnalyzer") << "\tI found " << totalHits << " pixel hits until now";
edm::LogInfo("Vx3DHLTAnalyzer") << "\tIn this event there are " << Vx3DCollection->size() << " vertex cadidates";
}
for (vector<Vertex>::const_iterator it3DVx = Vx3DCollection->begin(); it3DVx != Vx3DCollection->end(); it3DVx++) {
if (internalDebug == true) {
edm::LogInfo("Vx3DHLTAnalyzer") << "\tVertex selections:";
edm::LogInfo("Vx3DHLTAnalyzer") << "\tEvent ID = " << iEvent.id();
edm::LogInfo("Vx3DHLTAnalyzer") << "\tVertex number = " << it3DVx - Vx3DCollection->begin();
edm::LogInfo("Vx3DHLTAnalyzer") << "\tisValid = " << it3DVx->isValid();
edm::LogInfo("Vx3DHLTAnalyzer") << "\tisFake = " << it3DVx->isFake();
edm::LogInfo("Vx3DHLTAnalyzer") << "\tnodof = " << it3DVx->ndof();
edm::LogInfo("Vx3DHLTAnalyzer") << "\ttracksSize = " << it3DVx->tracksSize();
}
if ((it3DVx->isValid() == true) && (it3DVx->isFake() == false) && (it3DVx->ndof() >= minVxDoF) &&
(it3DVx->tracksSize() > 0) && ((it3DVx->ndof() + 3.) / ((double)it3DVx->tracksSize()) >= 2. * minVxWgt)) {
for (i = 0; i < DIM; i++) {
for (j = 0; j < DIM; j++) {
MyVertex.Covariance[i][j] = it3DVx->covariance(i, j);
if (isNotFinite(MyVertex.Covariance[i][j]) == true)
break;
}
if (j != DIM)
break;
}
if (i == DIM)
det = std::fabs(MyVertex.Covariance[0][0]) *
(std::fabs(MyVertex.Covariance[1][1]) * std::fabs(MyVertex.Covariance[2][2]) -
MyVertex.Covariance[1][2] * MyVertex.Covariance[1][2]) -
MyVertex.Covariance[0][1] * (MyVertex.Covariance[0][1] * std::fabs(MyVertex.Covariance[2][2]) -
MyVertex.Covariance[0][2] * MyVertex.Covariance[1][2]) +
MyVertex.Covariance[0][2] * (MyVertex.Covariance[0][1] * MyVertex.Covariance[1][2] -
MyVertex.Covariance[0][2] * std::fabs(MyVertex.Covariance[1][1]));
if ((i == DIM) && (det > 0.)) {
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tVertex accepted !";
MyVertex.x = it3DVx->x();
MyVertex.y = it3DVx->y();
MyVertex.z = it3DVx->z();
Vertices.push_back(MyVertex);
Vx_X->Fill(it3DVx->x());
Vx_Y->Fill(it3DVx->y());
Vx_Z->Fill(it3DVx->z());
Vx_ZX->Fill(it3DVx->z(), it3DVx->x());
Vx_ZY->Fill(it3DVx->z(), it3DVx->y());
Vx_XY->Fill(it3DVx->x(), it3DVx->y());
Vx_X_Cum->Fill(it3DVx->x());
Vx_Y_Cum->Fill(it3DVx->y());
Vx_Z_Cum->Fill(it3DVx->z());
Vx_ZX_Cum->Fill(it3DVx->z(), it3DVx->x());
Vx_ZY_Cum->Fill(it3DVx->z(), it3DVx->y());
Vx_XY_Cum->Fill(it3DVx->x(), it3DVx->y());
} else if (internalDebug == true) {
edm::LogInfo("Vx3DHLTAnalyzer") << "\tVertex discarded !";
for (i = 0; i < DIM; i++)
for (j = 0; j < DIM; j++)
edm::LogInfo("Vx3DHLTAnalyzer") << "(i,j) --> " << i << "," << j << " --> " << MyVertex.Covariance[i][j];
}
} else if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tVertex discarded !";
}
}
}
unsigned int Vx3DHLTAnalyzer::HitCounter(const Event& iEvent) {
Handle<SiPixelRecHitCollection> rechitspixel;
iEvent.getByToken(pixelHitCollection, rechitspixel);
unsigned int counter = 0;
for (SiPixelRecHitCollection::const_iterator j = rechitspixel->begin(); j != rechitspixel->end(); j++)
for (edmNew::DetSet<SiPixelRecHit>::const_iterator h = j->begin(); h != j->end(); h++)
counter += h->cluster()->size();
return counter;
}
string Vx3DHLTAnalyzer::formatTime(const time_t& t) {
char ts[25];
strftime(ts, sizeof(ts), "%Y.%m.%d %H:%M:%S %Z", gmtime(&t));
string ts_string(ts);
return ts_string;
}
double Vx3DHLTAnalyzer::Gauss3DFunc(const double* par) {
double K[DIM][DIM]; // Covariance Matrix
double M[DIM][DIM]; // K^-1
double det;
double sumlog = 0.;
// par[0] = K(0,0) --> Var[X]
// par[1] = K(1,1) --> Var[Y]
// par[2] = K(2,2) --> Var[Z]
// par[3] = K(0,1) = K(1,0) --> Cov[X,Y]
// par[4] = K(1,2) = K(2,1) --> Cov[Y,Z] --> dy/dz
// par[5] = K(0,2) = K(2,0) --> Cov[X,Z] --> dx/dz
// par[6] = mean x
// par[7] = mean y
// par[8] = mean z
counterVx = 0;
for (unsigned int i = 0; i < Vertices.size(); i++) {
if ((std::sqrt((Vertices[i].x - xPos) * (Vertices[i].x - xPos) + (Vertices[i].y - yPos) * (Vertices[i].y - yPos)) <=
maxTransRadius) &&
(std::fabs(Vertices[i].z - zPos) <= maxLongLength)) {
if (considerVxCovariance == true) {
K[0][0] = std::fabs(par[0]) + VxErrCorr * VxErrCorr * std::fabs(Vertices[i].Covariance[0][0]);
K[1][1] = std::fabs(par[1]) + VxErrCorr * VxErrCorr * std::fabs(Vertices[i].Covariance[1][1]);
K[2][2] = std::fabs(par[2]) + VxErrCorr * VxErrCorr * std::fabs(Vertices[i].Covariance[2][2]);
K[0][1] = K[1][0] = par[3] + VxErrCorr * VxErrCorr * Vertices[i].Covariance[0][1];
K[1][2] = K[2][1] = par[4] * (std::fabs(par[2]) - std::fabs(par[1])) - par[5] * par[3] +
VxErrCorr * VxErrCorr * Vertices[i].Covariance[1][2];
K[0][2] = K[2][0] = par[5] * (std::fabs(par[2]) - std::fabs(par[0])) - par[4] * par[3] +
VxErrCorr * VxErrCorr * Vertices[i].Covariance[0][2];
} else {
K[0][0] = std::fabs(par[0]);
K[1][1] = std::fabs(par[1]);
K[2][2] = std::fabs(par[2]);
K[0][1] = K[1][0] = par[3];
K[1][2] = K[2][1] = par[4] * (std::fabs(par[2]) - std::fabs(par[1])) - par[5] * par[3];
K[0][2] = K[2][0] = par[5] * (std::fabs(par[2]) - std::fabs(par[0])) - par[4] * par[3];
}
det = K[0][0] * (K[1][1] * K[2][2] - K[1][2] * K[1][2]) - K[0][1] * (K[0][1] * K[2][2] - K[0][2] * K[1][2]) +
K[0][2] * (K[0][1] * K[1][2] - K[0][2] * K[1][1]);
M[0][0] = (K[1][1] * K[2][2] - K[1][2] * K[1][2]) / det;
M[1][1] = (K[0][0] * K[2][2] - K[0][2] * K[0][2]) / det;
M[2][2] = (K[0][0] * K[1][1] - K[0][1] * K[0][1]) / det;
M[0][1] = M[1][0] = (K[0][2] * K[1][2] - K[0][1] * K[2][2]) / det;
M[1][2] = M[2][1] = (K[0][2] * K[0][1] - K[1][2] * K[0][0]) / det;
M[0][2] = M[2][0] = (K[0][1] * K[1][2] - K[0][2] * K[1][1]) / det;
sumlog += double(DIM) * std::log(2. * pi) + std::log(std::fabs(det)) +
(M[0][0] * (Vertices[i].x - par[6]) * (Vertices[i].x - par[6]) +
M[1][1] * (Vertices[i].y - par[7]) * (Vertices[i].y - par[7]) +
M[2][2] * (Vertices[i].z - par[8]) * (Vertices[i].z - par[8]) +
2. * M[0][1] * (Vertices[i].x - par[6]) * (Vertices[i].y - par[7]) +
2. * M[1][2] * (Vertices[i].y - par[7]) * (Vertices[i].z - par[8]) +
2. * M[0][2] * (Vertices[i].x - par[6]) * (Vertices[i].z - par[8]));
counterVx++;
}
}
return sumlog;
}
int Vx3DHLTAnalyzer::MyFit(vector<double>* vals) {
// ###############################################
// # RETURN CODE: #
// # >0 == NOT OK - fit status (MINUIT manual) #
// # 0 == OK #
// # -1 == NOT OK - not finite edm #
// # -2 == NOT OK - not enough "minNentries" #
// # -3 == NOT OK - not finite errors #
// # -4 == NOT OK - negative determinant #
// # -5 == NOT OK - maxLumiIntegration reached #
// # -6 == NOT OK - FatalRootError: @SUB=Minuit2 #
// ###############################################
if ((vals != nullptr) && (vals->size() == nParams * 2)) {
double nSigmaXY = 10.;
double nSigmaZ = 10.;
double parDistanceXY = 1e-3; // Unit: [cm]
double parDistanceZ = 1e-2; // Unit: [cm]
double parDistanceddZ = 1e-3; // Unit: [rad]
double parDistanceCxy = 1e-5; // Unit: [cm^2]
double bestEdm;
const unsigned int trials = 4;
double largerDist[trials] = {0.1, 5., 10., 100.};
double covxz, covyz, det;
double deltaMean;
int bestMovementX = 1;
int bestMovementY = 1;
int bestMovementZ = 1;
int goodData;
double edm;
vector<double>::const_iterator it = vals->begin();
ROOT::Math::Minimizer* Gauss3D = ROOT::Math::Factory::CreateMinimizer("Minuit2", "Migrad");
Gauss3D->SetErrorDef(1.0);
if (internalDebug == true)
Gauss3D->SetPrintLevel(3);
else
Gauss3D->SetPrintLevel(0);
ROOT::Math::Functor _Gauss3DFunc(this, &Vx3DHLTAnalyzer::Gauss3DFunc, nParams);
Gauss3D->SetFunction(_Gauss3DFunc);
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\t@@@ START FITTING @@@";
// @@@ Fit at X-deltaMean | X | X+deltaMean @@@
bestEdm = 1.;
for (int i = 0; i < 3; i++) {
deltaMean = (double(i) - 1.) * std::sqrt(*(it + 0));
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tdeltaMean --> " << deltaMean;
Gauss3D->Clear();
Gauss3D->SetVariable(0, "var x ", *(it + 0), parDistanceXY * parDistanceXY);
Gauss3D->SetVariable(1, "var y ", *(it + 1), parDistanceXY * parDistanceXY);
Gauss3D->SetVariable(2, "var z ", *(it + 2), parDistanceZ * parDistanceZ);
Gauss3D->SetVariable(3, "cov xy", *(it + 3), parDistanceCxy);
Gauss3D->SetVariable(4, "dydz ", *(it + 4), parDistanceddZ);
Gauss3D->SetVariable(5, "dxdz ", *(it + 5), parDistanceddZ);
Gauss3D->SetVariable(6, "mean x", *(it + 6) + deltaMean, parDistanceXY);
Gauss3D->SetVariable(7, "mean y", *(it + 7), parDistanceXY);
Gauss3D->SetVariable(8, "mean z", *(it + 8), parDistanceZ);
// Set the central positions of the centroid for vertex rejection
xPos = *(it + 6) + deltaMean;
yPos = *(it + 7);
zPos = *(it + 8);
// Set dimensions of the centroid for vertex rejection
maxTransRadius = nSigmaXY * std::sqrt(std::fabs(*(it + 0)) + std::fabs(*(it + 1)) / 2.);
maxLongLength = nSigmaZ * std::sqrt(std::fabs(*(it + 2)));
try {
Gauss3D->Minimize();
goodData = Gauss3D->Status();
edm = Gauss3D->Edm();
} catch (cms::Exception& er) {
edm::LogError("Vx3DHLTAnalyzer") << "\tCaught Minuit2 exception @ Fit at X: \n" << er.what();
goodData = -6;
edm = 1.;
continue;
}
if (counterVx < minNentries)
goodData = -2;
else if (isNotFinite(edm) == true) {
goodData = -1;
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tNot finite edm !";
} else if (goodData != -6)
for (unsigned int j = 0; j < nParams; j++)
if (isNotFinite(Gauss3D->Errors()[j]) == true) {
goodData = -3;
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tNot finite errors !";
break;
}
if (goodData == 0) {
covyz = Gauss3D->X()[4] * (std::fabs(Gauss3D->X()[2]) - std::fabs(Gauss3D->X()[1])) -
Gauss3D->X()[5] * Gauss3D->X()[3];
covxz = Gauss3D->X()[5] * (std::fabs(Gauss3D->X()[2]) - std::fabs(Gauss3D->X()[0])) -
Gauss3D->X()[4] * Gauss3D->X()[3];
det = std::fabs(Gauss3D->X()[0]) * (std::fabs(Gauss3D->X()[1]) * std::fabs(Gauss3D->X()[2]) - covyz * covyz) -
Gauss3D->X()[3] * (Gauss3D->X()[3] * std::fabs(Gauss3D->X()[2]) - covxz * covyz) +
covxz * (Gauss3D->X()[3] * covyz - covxz * std::fabs(Gauss3D->X()[1]));
if (det < 0.) {
goodData = -4;
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tNegative determinant !";
}
}
if ((goodData == 0) && (std::fabs(edm) < bestEdm)) {
bestEdm = edm;
bestMovementX = i;
}
}
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tFound bestMovementX --> " << bestMovementX;
// @@@ Fit at Y-deltaMean | Y | Y+deltaMean @@@
bestEdm = 1.;
for (int i = 0; i < 3; i++) {
deltaMean = (double(i) - 1.) * std::sqrt(*(it + 1));
if (internalDebug == true) {
edm::LogInfo("Vx3DHLTAnalyzer") << "\tdeltaMean --> " << deltaMean;
edm::LogInfo("Vx3DHLTAnalyzer") << "\tdeltaMean X --> " << (double(bestMovementX) - 1.) * std::sqrt(*(it + 0));
}
Gauss3D->Clear();
Gauss3D->SetVariable(0, "var x ", *(it + 0), parDistanceXY * parDistanceXY);
Gauss3D->SetVariable(1, "var y ", *(it + 1), parDistanceXY * parDistanceXY);
Gauss3D->SetVariable(2, "var z ", *(it + 2), parDistanceZ * parDistanceZ);
Gauss3D->SetVariable(3, "cov xy", *(it + 3), parDistanceCxy);
Gauss3D->SetVariable(4, "dydz ", *(it + 4), parDistanceddZ);
Gauss3D->SetVariable(5, "dxdz ", *(it + 5), parDistanceddZ);
Gauss3D->SetVariable(6, "mean x", *(it + 6) + (double(bestMovementX) - 1.) * std::sqrt(*(it + 0)), parDistanceXY);
Gauss3D->SetVariable(7, "mean y", *(it + 7) + deltaMean, parDistanceXY);
Gauss3D->SetVariable(8, "mean z", *(it + 8), parDistanceZ);
// Set the central positions of the centroid for vertex rejection
xPos = *(it + 6) + (double(bestMovementX) - 1.) * std::sqrt(*(it + 0));
yPos = *(it + 7) + deltaMean;
zPos = *(it + 8);
// Set dimensions of the centroid for vertex rejection
maxTransRadius = nSigmaXY * std::sqrt(std::fabs(*(it + 0)) + std::fabs(*(it + 1)) / 2.);
maxLongLength = nSigmaZ * std::sqrt(std::fabs(*(it + 2)));
try {
Gauss3D->Minimize();
goodData = Gauss3D->Status();
edm = Gauss3D->Edm();
} catch (cms::Exception& er) {
edm::LogError("Vx3DHLTAnalyzer") << "\tCaught Minuit2 exception @ Fit at Y: \n" << er.what();
goodData = -6;
edm = 1.;
continue;
}
if (counterVx < minNentries)
goodData = -2;
else if (isNotFinite(edm) == true) {
goodData = -1;
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tNot finite edm !";
} else if (goodData != -6)
for (unsigned int j = 0; j < nParams; j++)
if (isNotFinite(Gauss3D->Errors()[j]) == true) {
goodData = -3;
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tNot finite errors !";
break;
}
if (goodData == 0) {
covyz = Gauss3D->X()[4] * (std::fabs(Gauss3D->X()[2]) - std::fabs(Gauss3D->X()[1])) -
Gauss3D->X()[5] * Gauss3D->X()[3];
covxz = Gauss3D->X()[5] * (std::fabs(Gauss3D->X()[2]) - std::fabs(Gauss3D->X()[0])) -
Gauss3D->X()[4] * Gauss3D->X()[3];
det = std::fabs(Gauss3D->X()[0]) * (std::fabs(Gauss3D->X()[1]) * std::fabs(Gauss3D->X()[2]) - covyz * covyz) -
Gauss3D->X()[3] * (Gauss3D->X()[3] * std::fabs(Gauss3D->X()[2]) - covxz * covyz) +
covxz * (Gauss3D->X()[3] * covyz - covxz * std::fabs(Gauss3D->X()[1]));
if (det < 0.) {
goodData = -4;
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tNegative determinant !";
}
}
if ((goodData == 0) && (std::fabs(edm) < bestEdm)) {
bestEdm = edm;
bestMovementY = i;
}
}
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tFound bestMovementY --> " << bestMovementY;
// @@@ Fit at Z-deltaMean | Z | Z+deltaMean @@@
bestEdm = 1.;
for (int i = 0; i < 3; i++) {
deltaMean = (double(i) - 1.) * std::sqrt(*(it + 2));
if (internalDebug == true) {
edm::LogInfo("Vx3DHLTAnalyzer") << "\tdeltaMean --> " << deltaMean;
edm::LogInfo("Vx3DHLTAnalyzer") << "\tdeltaMean X --> " << (double(bestMovementX) - 1.) * std::sqrt(*(it + 0));
edm::LogInfo("Vx3DHLTAnalyzer") << "\tdeltaMean Y --> " << (double(bestMovementY) - 1.) * std::sqrt(*(it + 1));
}
Gauss3D->Clear();
Gauss3D->SetVariable(0, "var x ", *(it + 0), parDistanceXY * parDistanceXY);
Gauss3D->SetVariable(1, "var y ", *(it + 1), parDistanceXY * parDistanceXY);
Gauss3D->SetVariable(2, "var z ", *(it + 2), parDistanceZ * parDistanceZ);
Gauss3D->SetVariable(3, "cov xy", *(it + 3), parDistanceCxy);
Gauss3D->SetVariable(4, "dydz ", *(it + 4), parDistanceddZ);
Gauss3D->SetVariable(5, "dxdz ", *(it + 5), parDistanceddZ);
Gauss3D->SetVariable(6, "mean x", *(it + 6) + (double(bestMovementX) - 1.) * std::sqrt(*(it + 0)), parDistanceXY);
Gauss3D->SetVariable(7, "mean y", *(it + 7) + (double(bestMovementY) - 1.) * std::sqrt(*(it + 1)), parDistanceXY);
Gauss3D->SetVariable(8, "mean z", *(it + 8) + deltaMean, parDistanceZ);
// Set the central positions of the centroid for vertex rejection
xPos = *(it + 6) + (double(bestMovementX) - 1.) * std::sqrt(*(it + 0));
yPos = *(it + 7) + (double(bestMovementY) - 1.) * std::sqrt(*(it + 1));
zPos = *(it + 8) + deltaMean;
// Set dimensions of the centroid for vertex rejection
maxTransRadius = nSigmaXY * std::sqrt(std::fabs(*(it + 0)) + std::fabs(*(it + 1)) / 2.);
maxLongLength = nSigmaZ * std::sqrt(std::fabs(*(it + 2)));
try {
Gauss3D->Minimize();
goodData = Gauss3D->Status();
edm = Gauss3D->Edm();
} catch (cms::Exception& er) {
edm::LogError("Vx3DHLTAnalyzer") << "\tCaught Minuit2 exception @ Fit at Z: \n" << er.what();
goodData = -6;
edm = 1.;
continue;
}
if (counterVx < minNentries)
goodData = -2;
else if (isNotFinite(edm) == true) {
goodData = -1;
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tNot finite edm !";
} else if (goodData != -6)
for (unsigned int j = 0; j < nParams; j++)
if (isNotFinite(Gauss3D->Errors()[j]) == true) {
goodData = -3;
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tNot finite errors !";
break;
}
if (goodData == 0) {
covyz = Gauss3D->X()[4] * (std::fabs(Gauss3D->X()[2]) - std::fabs(Gauss3D->X()[1])) -
Gauss3D->X()[5] * Gauss3D->X()[3];
covxz = Gauss3D->X()[5] * (std::fabs(Gauss3D->X()[2]) - std::fabs(Gauss3D->X()[0])) -
Gauss3D->X()[4] * Gauss3D->X()[3];
det = std::fabs(Gauss3D->X()[0]) * (std::fabs(Gauss3D->X()[1]) * std::fabs(Gauss3D->X()[2]) - covyz * covyz) -
Gauss3D->X()[3] * (Gauss3D->X()[3] * std::fabs(Gauss3D->X()[2]) - covxz * covyz) +
covxz * (Gauss3D->X()[3] * covyz - covxz * std::fabs(Gauss3D->X()[1]));
if (det < 0.) {
goodData = -4;
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tNegative determinant !";
}
}
if ((goodData == 0) && (std::fabs(edm) < bestEdm)) {
bestEdm = edm;
bestMovementZ = i;
}
}
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tFound bestMovementZ --> " << bestMovementZ;
Gauss3D->Clear();
// @@@ FINAL FIT @@@
Gauss3D->SetVariable(0, "var x ", *(it + 0), parDistanceXY * parDistanceXY);
Gauss3D->SetVariable(1, "var y ", *(it + 1), parDistanceXY * parDistanceXY);
Gauss3D->SetVariable(2, "var z ", *(it + 2), parDistanceZ * parDistanceZ);
Gauss3D->SetVariable(3, "cov xy", *(it + 3), parDistanceCxy);
Gauss3D->SetVariable(4, "dydz ", *(it + 4), parDistanceddZ);
Gauss3D->SetVariable(5, "dxdz ", *(it + 5), parDistanceddZ);
Gauss3D->SetVariable(6, "mean x", *(it + 6) + (double(bestMovementX) - 1.) * std::sqrt(*(it + 0)), parDistanceXY);
Gauss3D->SetVariable(7, "mean y", *(it + 7) + (double(bestMovementY) - 1.) * std::sqrt(*(it + 1)), parDistanceXY);
Gauss3D->SetVariable(8, "mean z", *(it + 8) + (double(bestMovementZ) - 1.) * std::sqrt(*(it + 2)), parDistanceZ);
// Set the central positions of the centroid for vertex rejection
xPos = *(it + 6) + (double(bestMovementX) - 1.) * std::sqrt(*(it + 0));
yPos = *(it + 7) + (double(bestMovementY) - 1.) * std::sqrt(*(it + 1));
zPos = *(it + 8) + (double(bestMovementZ) - 1.) * std::sqrt(*(it + 2));
// Set dimensions of the centroid for vertex rejection
maxTransRadius = nSigmaXY * std::sqrt(std::fabs(*(it + 0)) + std::fabs(*(it + 1)) / 2.);
maxLongLength = nSigmaZ * std::sqrt(std::fabs(*(it + 2)));
try {
Gauss3D->Minimize();
goodData = Gauss3D->Status();
edm = Gauss3D->Edm();
} catch (cms::Exception& er) {
edm::LogError("Vx3DHLTAnalyzer") << "\tCaught Minuit2 exception @ Final fit: \n" << er.what();
goodData = -6;
edm = 1.;
}
if (counterVx < minNentries)
goodData = -2;
else if (isNotFinite(edm) == true) {
goodData = -1;
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tNot finite edm !";
} else if (goodData != -6)
for (unsigned int j = 0; j < nParams; j++)
if (isNotFinite(Gauss3D->Errors()[j]) == true) {
goodData = -3;
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tNot finite errors !";
break;
}
if (goodData == 0) {
covyz = Gauss3D->X()[4] * (std::fabs(Gauss3D->X()[2]) - std::fabs(Gauss3D->X()[1])) -
Gauss3D->X()[5] * Gauss3D->X()[3];
covxz = Gauss3D->X()[5] * (std::fabs(Gauss3D->X()[2]) - std::fabs(Gauss3D->X()[0])) -
Gauss3D->X()[4] * Gauss3D->X()[3];
det = std::fabs(Gauss3D->X()[0]) * (std::fabs(Gauss3D->X()[1]) * std::fabs(Gauss3D->X()[2]) - covyz * covyz) -
Gauss3D->X()[3] * (Gauss3D->X()[3] * std::fabs(Gauss3D->X()[2]) - covxz * covyz) +
covxz * (Gauss3D->X()[3] * covyz - covxz * std::fabs(Gauss3D->X()[1]));
if (det < 0.) {
goodData = -4;
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tNegative determinant !";
}
}
// @@@ FIT WITH DIFFERENT PARAMETER DISTANCES @@@
for (unsigned int i = 0; i < trials; i++) {
if ((goodData != 0) && (goodData != -2)) {
Gauss3D->Clear();
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tFIT WITH DIFFERENT PARAMETER DISTANCES - STEP " << i + 1;
Gauss3D->SetVariable(0, "var x ", *(it + 0), parDistanceXY * parDistanceXY * largerDist[i]);
Gauss3D->SetVariable(1, "var y ", *(it + 1), parDistanceXY * parDistanceXY * largerDist[i]);
Gauss3D->SetVariable(2, "var z ", *(it + 2), parDistanceZ * parDistanceZ * largerDist[i]);
Gauss3D->SetVariable(3, "cov xy", *(it + 3), parDistanceCxy * largerDist[i]);
Gauss3D->SetVariable(4, "dydz ", *(it + 4), parDistanceddZ * largerDist[i]);
Gauss3D->SetVariable(5, "dxdz ", *(it + 5), parDistanceddZ * largerDist[i]);
Gauss3D->SetVariable(6,
"mean x",
*(it + 6) + (double(bestMovementX) - 1.) * std::sqrt(*(it + 0)),
parDistanceXY * largerDist[i]);
Gauss3D->SetVariable(7,
"mean y",
*(it + 7) + (double(bestMovementY) - 1.) * std::sqrt(*(it + 1)),
parDistanceXY * largerDist[i]);
Gauss3D->SetVariable(
8, "mean z", *(it + 8) + (double(bestMovementZ) - 1.) * std::sqrt(*(it + 2)), parDistanceZ * largerDist[i]);
// Set the central positions of the centroid for vertex rejection
xPos = *(it + 6) + (double(bestMovementX) - 1.) * std::sqrt(*(it + 0));
yPos = *(it + 7) + (double(bestMovementY) - 1.) * std::sqrt(*(it + 1));
zPos = *(it + 8) + (double(bestMovementZ) - 1.) * std::sqrt(*(it + 2));
// Set dimensions of the centroid for vertex rejection
maxTransRadius = nSigmaXY * std::sqrt(std::fabs(*(it + 0)) + std::fabs(*(it + 1)) / 2.);
maxLongLength = nSigmaZ * std::sqrt(std::fabs(*(it + 2)));
try {
Gauss3D->Minimize();
goodData = Gauss3D->Status();
edm = Gauss3D->Edm();
} catch (cms::Exception& er) {
edm::LogError("Vx3DHLTAnalyzer") << "\tCaught Minuit2 exception @ Fit with different distances: \n"
<< er.what();
goodData = -6;
edm = 1.;
continue;
}
if (counterVx < minNentries)
goodData = -2;
else if (isNotFinite(edm) == true) {
goodData = -1;
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tNot finite edm !";
} else if (goodData != -6)
for (unsigned int j = 0; j < nParams; j++)
if (isNotFinite(Gauss3D->Errors()[j]) == true) {
goodData = -3;
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tNot finite errors !";
break;
}
if (goodData == 0) {
covyz = Gauss3D->X()[4] * (std::fabs(Gauss3D->X()[2]) - std::fabs(Gauss3D->X()[1])) -
Gauss3D->X()[5] * Gauss3D->X()[3];
covxz = Gauss3D->X()[5] * (std::fabs(Gauss3D->X()[2]) - std::fabs(Gauss3D->X()[0])) -
Gauss3D->X()[4] * Gauss3D->X()[3];
det = std::fabs(Gauss3D->X()[0]) * (std::fabs(Gauss3D->X()[1]) * std::fabs(Gauss3D->X()[2]) - covyz * covyz) -
Gauss3D->X()[3] * (Gauss3D->X()[3] * std::fabs(Gauss3D->X()[2]) - covxz * covyz) +
covxz * (Gauss3D->X()[3] * covyz - covxz * std::fabs(Gauss3D->X()[1]));
if (det < 0.) {
goodData = -4;
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tNegative determinant !";
}
}
} else
break;
}
if (goodData == 0)
for (unsigned int i = 0; i < nParams; i++) {
vals->operator[](i) = Gauss3D->X()[i];
vals->operator[](i + nParams) = Gauss3D->Errors()[i];
}
delete Gauss3D;
return goodData;
}
return -1;
}
void Vx3DHLTAnalyzer::reset(string ResetType) {
if ((debugMode == true) && (outputDebugFile.is_open() == true)) {
outputDebugFile << "Runnumber " << runNumber << endl;
outputDebugFile << "BeginTimeOfFit " << formatTime(beginTimeOfFit >> 32) << " " << (beginTimeOfFit >> 32) << endl;
outputDebugFile << "BeginLumiRange " << beginLumiOfFit << endl;
outputDebugFile << "EndTimeOfFit " << formatTime(endTimeOfFit >> 32) << " " << (endTimeOfFit >> 32) << endl;
outputDebugFile << "EndLumiRange " << endLumiOfFit << endl;
outputDebugFile << "LumiCounter " << lumiCounter << endl;
outputDebugFile << "LastLumiOfFit " << lastLumiOfFit << endl;
}
if (ResetType == "scratch") {
runNumber = 0;
numberGoodFits = 0;
numberFits = 0;
lastLumiOfFit = 0;
Vx_X->Reset();
Vx_Y->Reset();
Vx_Z->Reset();
Vx_X_Fit->Reset();
Vx_Y_Fit->Reset();
Vx_Z_Fit->Reset();
Vx_ZX->Reset();
Vx_ZY->Reset();
Vx_XY->Reset();
Vx_X_Cum->Reset();
Vx_Y_Cum->Reset();
Vx_Z_Cum->Reset();
Vx_ZX_Cum->Reset();
Vx_ZY_Cum->Reset();
Vx_XY_Cum->Reset();
mXlumi->Reset();
mYlumi->Reset();
mZlumi->Reset();
sXlumi->Reset();
sYlumi->Reset();
sZlumi->Reset();
dxdzlumi->Reset();
dydzlumi->Reset();
hitCounter->Reset();
goodVxCounter->Reset();
statusCounter->Reset();
fitResults->Reset();
reportSummary->Fill(-1);
reportSummaryMap->getTH1()->SetBinContent(1, 1, -1);
Vertices.clear();
lumiCounter = 0;
totalHits = 0;
beginTimeOfFit = 0;
endTimeOfFit = 0;
beginLumiOfFit = 0;
endLumiOfFit = 0;
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tReset issued: scratch";
if ((debugMode == true) && (outputDebugFile.is_open() == true))
outputDebugFile << "Reset -scratch- issued\n" << endl;
} else if (ResetType == "whole") {
Vx_X->Reset();
Vx_Y->Reset();
Vx_Z->Reset();
Vx_ZX->Reset();
Vx_ZY->Reset();
Vx_XY->Reset();
Vertices.clear();
lumiCounter = 0;
totalHits = 0;
beginTimeOfFit = 0;
endTimeOfFit = 0;
beginLumiOfFit = 0;
endLumiOfFit = 0;
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tReset issued: whole";
if ((debugMode == true) && (outputDebugFile.is_open() == true))
outputDebugFile << "Reset -whole- issued\n" << endl;
} else if (ResetType == "fit") {
Vx_X_Fit->Reset();
Vx_Y_Fit->Reset();
Vx_Z_Fit->Reset();
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tReset issued: fit";
if ((debugMode == true) && (outputDebugFile.is_open() == true))
outputDebugFile << "Reset -fit- issued\n" << endl;
} else if (ResetType == "hitCounter") {
totalHits = 0;
if (internalDebug == true)
edm::LogInfo("Vx3DHLTAnalyzer") << "\tReset issued: hitCounter";
if ((debugMode == true) && (outputDebugFile.is_open() == true))
outputDebugFile << "Reset -hitCounter- issued\n" << endl;
}
}
void Vx3DHLTAnalyzer::writeToFile(vector<double>* vals,
TimeValue_t BeginTimeOfFit,
TimeValue_t EndTimeOfFit,
unsigned int BeginLumiOfFit,
unsigned int EndLumiOfFit,
int dataType) {
stringstream BufferString;
BufferString.precision(5);
outputFile.open(fileName.c_str(), ios::out);
if ((outputFile.is_open() == true) && (vals != nullptr) && (vals->size() == (nParams - 1) * 2)) {
vector<double>::const_iterator it = vals->begin();
outputFile << "Runnumber " << runNumber << endl;
outputFile << "BeginTimeOfFit " << formatTime(beginTimeOfFit >> 32) << " " << (beginTimeOfFit >> 32) << endl;
outputFile << "EndTimeOfFit " << formatTime(endTimeOfFit >> 32) << " " << (endTimeOfFit >> 32) << endl;
outputFile << "LumiRange " << beginLumiOfFit << " - " << endLumiOfFit << endl;
outputFile << "Type " << dataType << endl;
// 3D Vertexing with Pixel Tracks:
// Good data = Type 3
// Bad data = Type -1
BufferString << *(it + 0);
outputFile << "X0 " << BufferString.str().c_str() << endl;
BufferString.str("");
BufferString << *(it + 1);
outputFile << "Y0 " << BufferString.str().c_str() << endl;
BufferString.str("");
BufferString << *(it + 2);
outputFile << "Z0 " << BufferString.str().c_str() << endl;
BufferString.str("");
BufferString << *(it + 5);
outputFile << "sigmaZ0 " << BufferString.str().c_str() << endl;
BufferString.str("");
BufferString << *(it + 6);
outputFile << "dxdz " << BufferString.str().c_str() << endl;
BufferString.str("");
BufferString << *(it + 7);
outputFile << "dydz " << BufferString.str().c_str() << endl;
BufferString.str("");
BufferString << *(it + 3);
outputFile << "BeamWidthX " << BufferString.str().c_str() << endl;
BufferString.str("");
BufferString << *(it + 4);
outputFile << "BeamWidthY " << BufferString.str().c_str() << endl;
BufferString.str("");
outputFile << "Cov(0,j) " << *(it + 8) << " 0 0 0 0 0 0" << endl;
outputFile << "Cov(1,j) 0 " << *(it + 9) << " 0 0 0 0 0" << endl;
outputFile << "Cov(2,j) 0 0 " << *(it + 10) << " 0 0 0 0" << endl;
outputFile << "Cov(3,j) 0 0 0 " << *(it + 13) << " 0 0 0" << endl;
outputFile << "Cov(4,j) 0 0 0 0 " << *(it + 14) << " 0 0" << endl;
outputFile << "Cov(5,j) 0 0 0 0 0 " << *(it + 15) << " 0" << endl;
outputFile << "Cov(6,j) 0 0 0 0 0 0 "
<< ((*(it + 11)) + (*(it + 12)) + 2. * std::sqrt((*(it + 11)) * (*(it + 12)))) / 4. << endl;
outputFile << "EmittanceX 0" << endl;
outputFile << "EmittanceY 0" << endl;
outputFile << "BetaStar 0" << endl;
}
outputFile.close();
if ((debugMode == true) && (outputDebugFile.is_open() == true) && (vals != nullptr) &&
(vals->size() == (nParams - 1) * 2)) {
vector<double>::const_iterator it = vals->begin();
outputDebugFile << "Runnumber " << runNumber << endl;
outputDebugFile << "BeginTimeOfFit " << formatTime(beginTimeOfFit >> 32) << " " << (beginTimeOfFit >> 32) << endl;
outputDebugFile << "EndTimeOfFit " << formatTime(endTimeOfFit >> 32) << " " << (endTimeOfFit >> 32) << endl;
outputDebugFile << "LumiRange " << beginLumiOfFit << " - " << endLumiOfFit << endl;
outputDebugFile << "Type " << dataType << endl;
// 3D Vertexing with Pixel Tracks:
// Good data = Type 3
// Bad data = Type -1
BufferString << *(it + 0);
outputDebugFile << "X0 " << BufferString.str().c_str() << endl;
BufferString.str("");
BufferString << *(it + 1);
outputDebugFile << "Y0 " << BufferString.str().c_str() << endl;
BufferString.str("");
BufferString << *(it + 2);
outputDebugFile << "Z0 " << BufferString.str().c_str() << endl;
BufferString.str("");
BufferString << *(it + 5);
outputDebugFile << "sigmaZ0 " << BufferString.str().c_str() << endl;
BufferString.str("");
BufferString << *(it + 6);
outputDebugFile << "dxdz " << BufferString.str().c_str() << endl;
BufferString.str("");
BufferString << *(it + 7);
outputDebugFile << "dydz " << BufferString.str().c_str() << endl;
BufferString.str("");
BufferString << *(it + 3);
outputDebugFile << "BeamWidthX " << BufferString.str().c_str() << endl;
BufferString.str("");
BufferString << *(it + 4);
outputDebugFile << "BeamWidthY " << BufferString.str().c_str() << endl;
BufferString.str("");
outputDebugFile << "Cov(0,j) " << *(it + 8) << " 0 0 0 0 0 0" << endl;
outputDebugFile << "Cov(1,j) 0 " << *(it + 9) << " 0 0 0 0 0" << endl;
outputDebugFile << "Cov(2,j) 0 0 " << *(it + 10) << " 0 0 0 0" << endl;
outputDebugFile << "Cov(3,j) 0 0 0 " << *(it + 13) << " 0 0 0" << endl;
outputDebugFile << "Cov(4,j) 0 0 0 0 " << *(it + 14) << " 0 0" << endl;
outputDebugFile << "Cov(5,j) 0 0 0 0 0 " << *(it + 15) << " 0" << endl;
outputDebugFile << "Cov(6,j) 0 0 0 0 0 0 "
<< ((*(it + 11)) + (*(it + 12)) + 2. * std::sqrt((*(it + 11)) * (*(it + 12)))) / 4. << endl;
outputDebugFile << "EmittanceX 0" << endl;
outputDebugFile << "EmittanceY 0" << endl;
outputDebugFile << "BetaStar 0" << endl;
outputDebugFile << "\nUsed vertices: " << counterVx << "\n" << endl;
}
}
void Vx3DHLTAnalyzer::printFitParams(const vector<double>& fitResults) {
edm::LogInfo("Vx3DHLTAnalyzer") << "var x --> " << fitResults[0] << " +/- " << fitResults[0 + nParams];
edm::LogInfo("Vx3DHLTAnalyzer") << "var y --> " << fitResults[1] << " +/- " << fitResults[1 + nParams];
edm::LogInfo("Vx3DHLTAnalyzer") << "var z --> " << fitResults[2] << " +/- " << fitResults[2 + nParams];
edm::LogInfo("Vx3DHLTAnalyzer") << "cov xy --> " << fitResults[3] << " +/- " << fitResults[3 + nParams];
edm::LogInfo("Vx3DHLTAnalyzer") << "dydz --> " << fitResults[4] << " +/- " << fitResults[4 + nParams];
edm::LogInfo("Vx3DHLTAnalyzer") << "dxdz --> " << fitResults[5] << " +/- " << fitResults[5 + nParams];
edm::LogInfo("Vx3DHLTAnalyzer") << "mean x --> " << fitResults[6] << " +/- " << fitResults[6 + nParams];
edm::LogInfo("Vx3DHLTAnalyzer") << "mean y --> " << fitResults[7] << " +/- " << fitResults[7 + nParams];
edm::LogInfo("Vx3DHLTAnalyzer") << "mean z --> " << fitResults[8] << " +/- " << fitResults[8 + nParams];
}
void Vx3DHLTAnalyzer::dqmBeginLuminosityBlock(const LuminosityBlock& lumiBlock, const EventSetup& iSetup) {
// @@@ If statement to avoid problems with non-sequential lumisections @@@
if ((lumiCounter == 0) && (lumiBlock.luminosityBlock() > lastLumiOfFit)) {
beginTimeOfFit = lumiBlock.beginTime().value();
beginLumiOfFit = lumiBlock.luminosityBlock();
lumiCounter++;
} else if ((lumiCounter != 0) && (lumiBlock.luminosityBlock() >= (beginLumiOfFit + lumiCounter)))
lumiCounter++;
else
reset("scratch");
}
void Vx3DHLTAnalyzer::dqmEndLuminosityBlock(const LuminosityBlock& lumiBlock, const EventSetup& iSetup) {
stringstream histTitle;
double minXfit, maxXfit;
int goodData;
if ((nLumiFit != 0) && (lumiCounter % nLumiFit == 0) && (beginTimeOfFit != 0) && (runNumber != 0)) {
endTimeOfFit = lumiBlock.endTime().value();
endLumiOfFit = lumiBlock.luminosityBlock();
lastLumiOfFit = endLumiOfFit;
vector<double> vals;
hitCounter->getTH1()->SetBinContent(lastLumiOfFit, (double)totalHits);
hitCounter->getTH1()->SetBinError(
lastLumiOfFit,
(totalHits != 0 ? 1.
: 0.)); // It's not sqrt(n) because we want to weight all entries in the same way for the fit
if (dataFromFit == true) {
vector<double> fitResults;
fitResults.push_back(Vx_X->getTH1()->GetRMS() * Vx_X->getTH1()->GetRMS());
fitResults.push_back(Vx_Y->getTH1()->GetRMS() * Vx_Y->getTH1()->GetRMS());
fitResults.push_back(Vx_Z->getTH1()->GetRMS() * Vx_Z->getTH1()->GetRMS());
fitResults.push_back(0.0);
fitResults.push_back(0.0);
fitResults.push_back(0.0);
fitResults.push_back(Vx_X->getTH1()->GetMean());
fitResults.push_back(Vx_Y->getTH1()->GetMean());
fitResults.push_back(Vx_Z->getTH1()->GetMean());