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FinaliseSystematicErrorsCalo_pp900GeV.C
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FinaliseSystematicErrorsCalo_pp900GeV.C
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#include <Riostream.h>
#include <fstream>
#include "TMath.h"
#include <stdlib.h>
#include <fstream>
#include <math.h>
#include <TROOT.h>
#include <TApplication.h>
#include <TPaveLabel.h>
#include <TSystem.h>
#include <TFrame.h>
#include <TStyle.h>
#include <TString.h>
#include "TGaxis.h"
#include "TFile.h"
#include "TH1F.h"
#include "TH1D.h"
#include "TH2F.h"
#include "TF1.h"
#include "TVirtualFitter.h"
#include "TObject.h"
#include "TCanvas.h"
#include "TMultiGraph.h"
#include "TLegend.h"
#include "TDatabasePDG.h"
#include "TMinuit.h"
#include "TBenchmark.h"
#include "TRandom.h"
#include "TLatex.h"
#include "TASImage.h"
#include "TPostScript.h"
#include "TGraphErrors.h"
#include "TArrow.h"
#include "TGraphAsymmErrors.h"
#include "TGaxis.h"
#include "TMarker.h"
#include "CommonHeaders/PlottingGammaConversionHistos.h"
#include "CommonHeaders/PlottingGammaConversionAdditional.h"
#include "CommonHeaders/FittingGammaConversion.h"
#include "CommonHeaders/ConversionFunctionsBasicsAndLabeling.h"
#include "CommonHeaders/ConversionFunctions.h"
void FinaliseSystematicErrorsCalo_pp900GeV( const char* nameDataFileErrors = "",
TString energy = "",
TString meson = "",
Int_t numberOfPtBins = 1,
Int_t numberCutStudies = 1,
Double_t startPtSys = 0,
TString additionalName = "pp",
TString additionalNameOutput = "",
TString suffix = "eps"
){
// ***************************************************************************************************
// ****************************** General style settings *********************************************
// ***************************************************************************************************
StyleSettingsThesis();
SetPlotStyle();
// ***************************************************************************************************
// ****************************** Create output directory ********************************************
// ***************************************************************************************************
gSystem->Exec("mkdir -p SystematicErrorsCalculatedCalo");
// ***************************************************************************************************
// ***************************** labeling and color settings *****************************************
// ***************************************************************************************************
TString date = ReturnDateString();
TString dateForOutput = ReturnDateStringForOutput();
TString collisionSystem = ReturnFullCollisionsSystem(energy);
TString energyForOutput = energy;
energyForOutput.ReplaceAll(".","_");
// ***************************************************************************************************
// ******************************* general variable definition **************************************
// ***************************************************************************************************
const Int_t nPtBins = numberOfPtBins;
const Int_t nCuts = numberCutStudies;
Double_t* ptBins = 0x0;
Double_t* ptBinsErr = 0x0;
const Int_t nMaxVar = 16;
TString nameCutVariation[nMaxVar];
TString nameCutVariationSC[nMaxVar];
TString nameCutVariationSC900GeV[nMaxVar] = { "YieldExtraction", "OpeningAngle", "ClusterMinEnergy", "ClusterNCells", "ClusterNonLinearity",
"ClusterTrackMatchingCalo", "ClusterM02","ClusterMaterialTRD", "ClusterEnergyScale" , "CellTiming",
"PileUp", "Efficiency", "ClusterTime", "ClusterizationEnergy", "Secondary",
"YieldExtractionPi0"};
Color_t color[nMaxVar];
Color_t markerStyle[nMaxVar];
for (Int_t k =0; k<nMaxVar; k++ ){
color[k] = GetColorSystematics( nameCutVariationSC900GeV[k], 4 );
markerStyle[k] = GetMarkerStyleSystematics( nameCutVariationSC900GeV[k], 4 );
}
for (Int_t i = 0; i < numberCutStudies; i++){
nameCutVariation[i] = GetSystematicsName(nameCutVariationSC900GeV[i]);
nameCutVariationSC[i] = nameCutVariationSC900GeV[i];
}
if (meson.CompareTo("Pi0EtaBinning") == 0){
nameCutVariation[0] = "Yield extraction #eta";
}
// ***************************************************************************************************
// ******************************** Booleans for smoothing *******************************************
// ***************************************************************************************************
Bool_t bsmooth[nMaxVar] = { 0, 0, 0, 0, 0,
0, 0, 0, 0, 0,
0, 0, 0, 0, 0,
0};
Bool_t bsmoothMBPi0[nMaxVar] = { 1, 1, 1, 1, 1,
1, 1, 1, 1, 1,
1, 1, 1, 1, 1,
0};
Bool_t bsmoothMBEta[nMaxVar] = { 1, 1, 1, 1, 1,
1, 1, 1, 1, 1,
1, 1, 1, 1, 1,
0};
Bool_t bsmoothMBPi0EtaBinning[nMaxVar] = { 1, 1, 1, 1, 1,
1, 1, 1, 1, 1,
1, 1, 1, 1, 1,
1};
for (Int_t i = 0; i < numberCutStudies; i++){
if (additionalNameOutput.CompareTo("") == 0 && meson.CompareTo("Pi0")==0){
bsmooth[i] = bsmoothMBPi0[i];
} else if (additionalNameOutput.CompareTo("") == 0 && meson.CompareTo("Eta")==0){
bsmooth[i] = bsmoothMBEta[i];
} else if (additionalNameOutput.CompareTo("") == 0 && meson.CompareTo("Pi0EtaBinning")==0){
bsmooth[i] = bsmoothMBPi0EtaBinning[i];
}
}
// ***************************************************************************************************
// ****************************** Initialize error vectors & graphs **********************************
// ***************************************************************************************************
Double_t* errorsNeg [nCuts];
Double_t errorsNegCorr [nCuts][nPtBins];
Double_t errorsNegSummed [nPtBins];
Double_t errorsNegCorrSummed [nPtBins];
Double_t errorsNegCorrMatSummed [nPtBins];
Double_t* errorsNegErr [nCuts];
Double_t errorsNegErrCorr [nCuts][nPtBins];
Double_t errorsNegErrSummed [nPtBins];
Double_t errorsNegErrCorrSummed [nPtBins];
Double_t* errorsPos [nCuts];
Double_t errorsPosCorr [nCuts][nPtBins];
Double_t errorsPosSummed [nPtBins];
Double_t errorsPosCorrSummed [nPtBins];
Double_t errorsPosCorrMatSummed [nPtBins];
Double_t* errorsPosErr [nCuts];
Double_t errorsPosErrSummed [nPtBins];
Double_t errorsPosErrCorr [nCuts][nPtBins];
Double_t errorsPosErrCorrSummed [nPtBins];
Double_t errorsMean [nCuts][nPtBins];
Double_t errorsMeanCorr [nCuts][nPtBins];
Double_t errorsMeanSummed [nPtBins];
Double_t errorsMeanCorrSummed [nPtBins];
Double_t errorsMeanCorrMatSummed [nPtBins];
Double_t errorsMeanErr [nCuts][nPtBins];
Double_t errorsMeanErrCorr [nCuts][nPtBins];
Double_t errorsMeanErrSummed [nPtBins];
Double_t errorsMeanErrCorrSummed [nPtBins];
Double_t errorsMeanErrCorrMatSummed [nPtBins];
TGraphErrors* negativeErrors [nCuts];
TGraphErrors* positiveErrors [nCuts];
TGraphErrors* negativeErrorsCorr [nCuts];
TGraphErrors* positiveErrorsCorr [nCuts];
TGraphErrors* meanErrors [nCuts];
TGraphErrors* meanErrorsCorr [nCuts];
TGraphErrors* negativeErrorsSummed;
TGraphErrors* positiveErrorsSummed;
TGraphErrors* negativeErrorsCorrSummed;
TGraphErrors* positiveErrorsCorrSummed;
TGraphErrors* meanErrorsSummed;
TGraphErrors* meanErrorsCorrSummed;
TGraphErrors* meanErrorsCorrSummedIncMat;
for (Int_t l = 0;l < nPtBins;l++){
errorsPosSummed[l] = 0.;
errorsNegSummed[l] = 0.;
errorsMeanSummed[l] = 0.;
errorsPosCorrSummed[l] = 0.;
errorsNegCorrSummed[l] = 0.;
errorsMeanCorrSummed[l] = 0.;
}
// ***************************************************************************************************
// ****************************** Read & process data from file **************************************
// ***************************************************************************************************
TFile* fileErrorInput= new TFile(nameDataFileErrors);
TString sFilePi0EtaBinning = "~/data/work/pcgGit/AnalysisSoftware/900GeV_CaloSystematics/CutStudies/900GeV/Eta_data_SystematicErrorCuts.root";
TFile* filePi0EtaBinning = new TFile(sFilePi0EtaBinning);
for (Int_t i = 0;i < nCuts;i++){
// read data
TGraphAsymmErrors* graphPosErrors;
TGraphAsymmErrors* graphNegErrors;
//if(i>=0){
if (i == 0 || i == 7 || i == 8 || i == 11 || i == 13 || i == 14 || (i == 9 && meson.CompareTo("Pi0EtaBinning") == 0)){// special treatment for Yield extraction error and calculated erros
TString nameGraphPos = "";
TString nameGraphNeg = "";
if ( meson.CompareTo("Pi0EtaBinning") != 0 ){
nameGraphPos = Form("%s_SystErrorRelPos_YieldExtraction_%s",meson.Data(),additionalName.Data() );
nameGraphNeg = Form("%s_SystErrorRelNeg_YieldExtraction_%s",meson.Data(),additionalName.Data() );
} else {
nameGraphPos = Form("Eta_SystErrorRelPos_YieldExtraction_%s",additionalName.Data() );
nameGraphNeg = Form("Eta_SystErrorRelNeg_YieldExtraction_%s",additionalName.Data() );
}
cout << "Cutstudies " << i<< "\t" <<nameGraphPos.Data() << "\t" << nameGraphNeg.Data()<< endl;
if ( meson.CompareTo("Pi0EtaBinning") == 0 ){
graphPosErrors = (TGraphAsymmErrors*)filePi0EtaBinning->Get(nameGraphPos.Data());
graphNegErrors = (TGraphAsymmErrors*)filePi0EtaBinning->Get(nameGraphNeg.Data());
}else{
graphPosErrors = (TGraphAsymmErrors*)fileErrorInput->Get(nameGraphPos.Data());
graphNegErrors = (TGraphAsymmErrors*)fileErrorInput->Get(nameGraphNeg.Data());
}
} else if ( i == 15) { // special treatment for eta to pi0 ratio
TString nameGraphPos = Form("Pi0EtaBinning_SystErrorRelPos_YieldExtraction_%s",additionalName.Data() );
TString nameGraphNeg = Form("Pi0EtaBinning_SystErrorRelNeg_YieldExtraction_%s",additionalName.Data() );
cout << "Cutstudies " << i<< "\t" <<nameGraphPos.Data() << "\t" << nameGraphNeg.Data()<< endl;
graphPosErrors = (TGraphAsymmErrors*)fileErrorInput->Get(nameGraphPos.Data());
graphNegErrors = (TGraphAsymmErrors*)fileErrorInput->Get(nameGraphNeg.Data());
} else {// read graphs from input file
TString nameGraphPos = Form("%s_SystErrorRelPos_%s%s",meson.Data(),nameCutVariationSC[i].Data(),additionalNameOutput.Data() );
TString nameGraphNeg = Form("%s_SystErrorRelNeg_%s%s",meson.Data(),nameCutVariationSC[i].Data(),additionalNameOutput.Data() );
cout << "Cutstudies " << i<< "\t" <<nameGraphPos.Data() << "\t" << nameGraphNeg.Data()<< endl;
graphPosErrors = (TGraphAsymmErrors*)fileErrorInput->Get(nameGraphPos.Data());
graphNegErrors = (TGraphAsymmErrors*)fileErrorInput->Get(nameGraphNeg.Data());
}
// take out offsets
while (graphPosErrors->GetX()[0] < startPtSys){
graphPosErrors->RemovePoint(0);
graphNegErrors->RemovePoint(0);
}
cout << "****************************************************"<< endl;
graphPosErrors->Print();
cout << "****************************************************"<< endl;
cout << "****************************************************"<< endl;
cout << "****************************************************\n\n\n"<< endl;
// Filling arrays
if (i == 0) {
ptBins = graphNegErrors->GetX();
ptBinsErr = graphNegErrors->GetEXhigh();
}
errorsNeg[i] = graphNegErrors->GetY();
errorsNegErr[i] = graphNegErrors->GetEYhigh();
errorsPos[i] = graphPosErrors->GetY();
errorsPosErr[i] = graphPosErrors->GetEYhigh();
cout << nameCutVariationSC[i].Data() << endl;
// Averaging of upper and lower errors
CalculateMeanSysErr(errorsMean[i], errorsMeanErr[i], errorsPos[i], errorsNeg[i], nPtBins);
// Automatic smoothing of 0 bins according to adjoining bins
CorrectSystematicErrorsWithMean(errorsPos[i],errorsPosErr[i], errorsPosCorr[i], errorsPosErrCorr[i], nPtBins);
CorrectSystematicErrorsWithMean(errorsNeg[i],errorsNegErr[i], errorsNegCorr[i], errorsNegErrCorr[i], nPtBins);
CorrectSystematicErrorsWithMean(errorsMean[i], errorsMeanErr[i], errorsMeanCorr[i], errorsMeanErrCorr[i], nPtBins);
// Routing for manual smoothing of systematic errors
// ATTTENTION! you have to do this manually for each data set/trigger never trust the values mentioned here
if (bsmooth[i]){
// manual smoothing for Yield extraction errors - variation 0
if (nameCutVariationSC[i].CompareTo("YieldExtraction") == 0){
cout << "Yield extraction smoothing" << endl;
if (meson.Contains("Pi0")){
Double_t error = 0.;
for (Int_t k = 0;k < nPtBins;k++){
error = 2.0+50./pow(8.,ptBins[k]);
if(ptBins[k]>=3.) error += 0.8*(ptBins[k]-3) ;
errorsMean[i][k] = error;
errorsMeanErr[i][k] = error*0.01;
errorsMeanCorr[i][k] = error;
errorsMeanErrCorr[i][k] = error*0.01;
}
}
}
// manual smoothing for OpeningAngle errors - variation 1
if (nameCutVariationSC[i].CompareTo("OpeningAngle") == 0){
cout << "Opening Angle smoothing" << endl;
for (Int_t k = 0;k < nPtBins;k++){
Double_t error = 0.5;
errorsMean[i][k] = error;
errorsMeanErr[i][k] = error*0.01;
errorsMeanCorr[i][k] = error;
errorsMeanErrCorr[i][k] = error*0.01;
}
}
// manual smoothing for minimum cluster energy errors - variation 2
if (nameCutVariationSC[i].CompareTo("ClusterMinEnergy")==0 ){
cout << "Cluster minimum energy smoothing" << endl;
if(meson.Contains("Pi0")){
Double_t error = 0;
for (Int_t k = 0;k < nPtBins;k++){
error = 0.8+36./pow(6.,ptBins[k]);
errorsMean[i][k] = error;
errorsMeanErr[i][k] = 0.01*error;
errorsMeanCorr[i][k] = error;
errorsMeanErrCorr[i][k] = 0.01*error;
}
}
}
// manual smoothing for minimum number of cells in cluster errors - variation 3
if (nameCutVariationSC[i].CompareTo("ClusterNCells")==0 ){
cout << "Cluster NCells smoothing" << endl;
for (Int_t k = 0;k < nPtBins;k++){
Double_t error = 0.5;
errorsMean[i][k] = error;
errorsMeanErr[i][k] = error*0.01;
errorsMeanCorr[i][k] = error;
errorsMeanErrCorr[i][k] = error*0.01;
}
}
// manual smoothing for energy calibration errors - variation 4
if (nameCutVariationSC[i].CompareTo("ClusterNonLinearity")==0 ){//&& meson.Contains("Pi0")
cout << "Cluster non linearity smoothing" << endl;
for (Int_t k = 0;k < nPtBins;k++){
Double_t error = 1.;
errorsMean[i][k] = error;
errorsMeanErr[i][k] = error*0.01;
errorsMeanCorr[i][k] = error;
errorsMeanErrCorr[i][k] = error*0.01;
}
}
// manual smoothing for cluster matching errors - variation 5
if (nameCutVariationSC[i].CompareTo("ClusterTrackMatchingCalo")==0 ){
cout << "Cluster track matching smoothing" << endl;
if ( meson.Contains("Pi0") && meson.CompareTo("Pi0EtaBinning") != 0){
for (Int_t k = 0;k < nPtBins;k++){
Double_t error = 1.5 + 8./pow(4.,ptBins[k]);
if(ptBins[k]>=7.) error += (0.1)*(ptBins[k]-7.);
errorsMean[i][k] = error;
errorsMeanErr[i][k] = 0.01*error;
errorsMeanCorr[i][k] = error;
errorsMeanErrCorr[i][k] = 0.01*error;
}
}
}
// manual smoothing for cluster shape errors - variation 6
if (nameCutVariationSC[i].CompareTo("ClusterM02")==0 ){//&& meson.Contains("Pi0")
cout << "Cluster M02 smoothing" << endl;
for (Int_t k = 0;k < nPtBins;k++){
Double_t error = 0.5+(-0.007)*ptBins[k]+(0.008)*ptBins[k]*ptBins[k];
errorsMean[i][k] = error;
errorsMeanErr[i][k] = error*0.01;
errorsMeanCorr[i][k] = error;
errorsMeanErrCorr[i][k] = error*0.01;
}
}
// manual smoothing for Material infront of EMCal - variation 7
if (nameCutVariationSC[i].CompareTo("ClusterMaterialTRD")==0 ){
cout << "Material smoothing" << endl;
Double_t error = TMath::Sqrt(3.*3.+3.*3.); //(3% for TRD mat, 3% for TOF mat added in quadrature)
for (Int_t k = 0;k < nPtBins;k++){
errorsMean[i][k] = error;
errorsMeanErr[i][k] = error*0.01;
errorsMeanCorr[i][k] = error;
errorsMeanErrCorr[i][k] = error*0.01;
}
}
// manual smoothing for energy scale errors (derived from mass difference MC & Data) - variation 8
if (nameCutVariationSC[i].CompareTo("ClusterEnergyScale")==0 ){//&& meson.Contains("Pi0")
cout << "Cluster energy scale errors smoothing" << endl;
for (Int_t k = 0;k < nPtBins;k++){
Double_t error = 2.0+15./pow(20,ptBins[k]);
errorsMean[i][k] = error;
errorsMeanErr[i][k] = error*0.01;
errorsMeanCorr[i][k] = error;
errorsMeanErrCorr[i][k] = error*0.01;
}
}
// manual smoothing for cell time uncertainties - variation 9
if (nameCutVariationSC[i].CompareTo("CellTiming") == 0){
cout << "Cell time smoothing" << endl;
for (Int_t k = 0;k < nPtBins;k++){
Double_t error = 0.5;
errorsMean[i][k] = error;
errorsMeanErr[i][k] = error*0.01;
errorsMeanCorr[i][k] = error;
errorsMeanErrCorr[i][k] = error*0.01;
}
}
// manual smoothing for PileUp uncertainties - variation 10
if (nameCutVariationSC[i].CompareTo("PileUp") == 0){
cout << "PileUp smoothing" << endl;
for (Int_t k = 0;k < nPtBins;k++){
Double_t error = 0.2; //0.2% error from pileUp: with pileUp+SPDtrackCluster cut and without
errorsMean[i][k] = error;
errorsMeanErr[i][k] = error*0.01;
errorsMeanCorr[i][k] = error;
errorsMeanErrCorr[i][k] = error*0.01;
}
}
// manual smoothing for Efficiency uncertainties - variation 11
if (nameCutVariationSC[i].CompareTo("Efficiency") == 0){
cout << "Efficiency smoothing" << endl;
for (Int_t k = 0;k < nPtBins;k++){
Double_t error = 1.;
Double_t errorPi0 = 2.;
Double_t errorEta = 4.;
if (meson.CompareTo("Pi0EtaBinning")==0){
error = TMath::Sqrt(errorPi0*errorPi0+errorEta*errorEta);
} else if (meson.CompareTo("Pi0")==0) {
error = TMath::Sqrt(errorPi0*errorPi0+1.5*1.5); // add 'period' unc.
} else {
error = TMath::Sqrt(errorEta*errorEta+1.5*1.5); // add 'period' unc.
}
errorsMean[i][k] = error;
errorsMeanErr[i][k] = error*0.01;
errorsMeanCorr[i][k] = error;
errorsMeanErrCorr[i][k] = error*0.01;
}
}
// manual smoothing for ClusterTime uncertainties - variation 12
if (nameCutVariationSC[i].CompareTo("ClusterTime")==0 ){
cout << "ClusterTime smoothing" << endl;
Double_t error = 0.1;
for (Int_t k = 0;k < nPtBins;k++){
errorsMean[i][k] = error;
errorsMeanErr[i][k] = error*0.01;
errorsMeanCorr[i][k] = error;
errorsMeanErrCorr[i][k] = error*0.01;
}
}
// manual smoothing for ClusterizationEnergy uncertainties - variation 13
if (nameCutVariationSC[i].CompareTo("ClusterizationEnergy")==0 ){
cout << "ClusterizationEnergy smoothing" << endl;
Double_t error = 2.;
for (Int_t k = 0;k < nPtBins;k++){
error = 3.0 + 20./pow(10,ptBins[k]);
errorsMean[i][k] = error;
errorsMeanErr[i][k] = error*0.01;
errorsMeanCorr[i][k] = error;
errorsMeanErrCorr[i][k] = error*0.01;
}
}
// manual smoothing for SecondaryCorrection uncertainties - variation 14
if (nameCutVariationSC[i].CompareTo("Secondary")==0 ){
cout << "Seconday smoothing" << endl;
Double_t error = 0.5;
for (Int_t k = 0;k < nPtBins;k++){
errorsMean[i][k] = error;
errorsMeanErr[i][k] = error*0.01;
errorsMeanCorr[i][k] = error;
errorsMeanErrCorr[i][k] = error*0.01;
}
}
// manual smoothing for pi0 in eta binning - variation 15
if (i==15 && nameCutVariationSC[i].CompareTo("YieldExtractionPi0")==0 ){
cout << "pi0etabinning smoothing" << endl;
Double_t error = 0.;
for (Int_t k = 0;k < nPtBins;k++){
errorsMean[i][k] = error;
errorsMeanErr[i][k] = error*0.01;
errorsMeanCorr[i][k] = error;
errorsMeanErrCorr[i][k] = error*0.01;
}
}
} else {
for (Int_t k = 0;k < nPtBins;k++){
errorsMeanErr[i][k] = 0.03;
errorsMeanErrCorr[i][k] = 0.03;
}
}
// Quadratic sum of errors except material error infront of EMCal & inner material
if (!nameCutVariationSC[i].CompareTo("ClusterMaterialTRD")==0){
cout << "errors added quadratically" << endl;
for (Int_t l = 0;l < nPtBins;l++){
errorsPosSummed[l] = errorsPosSummed[l]+pow(errorsPos[i][l],2);
errorsNegSummed[l] = errorsNegSummed[l]+ pow(errorsNeg[i][l],2);
errorsMeanSummed[l] = errorsMeanSummed[l]+ pow(errorsMean[i][l],2);
errorsPosCorrSummed[l] = errorsPosCorrSummed[l]+pow(errorsPosCorr[i][l],2);
errorsNegCorrSummed[l] = errorsNegCorrSummed[l] +pow(errorsNegCorr[i][l],2);
errorsMeanCorrSummed[l] = errorsMeanCorrSummed[l]+ pow(errorsMeanCorr[i][l],2);
}
}
// fill error graphs for plotting
negativeErrors[i] = new TGraphErrors(nPtBins,ptBins ,errorsNeg[i] ,ptBinsErr ,errorsNegErr[i] );
meanErrors[i] = new TGraphErrors(nPtBins,ptBins ,errorsMean[i] ,ptBinsErr ,errorsMeanErr[i] );
positiveErrors[i] = new TGraphErrors(nPtBins,ptBins ,errorsPos[i] ,ptBinsErr ,errorsPosErr[i] );
negativeErrorsCorr[i] = new TGraphErrors(nPtBins,ptBins ,errorsNegCorr[i] ,ptBinsErr ,errorsNegErrCorr[i] );
meanErrorsCorr[i] = new TGraphErrors(nPtBins,ptBins ,errorsMeanCorr[i] ,ptBinsErr ,errorsMeanErrCorr[i] );
positiveErrorsCorr[i] = new TGraphErrors(nPtBins,ptBins ,errorsPosCorr[i] ,ptBinsErr ,errorsPosErrCorr[i] );
}
// Error for inner material budget
Double_t errorMaterial = 0;
// Calculate sqrt of summed errors for final errors, add material budget errors
for (Int_t l = 0;l < nPtBins;l++){
errorsPosSummed[l] = pow(errorsPosSummed[l],0.5);
errorsMeanSummed[l] = pow(errorsMeanSummed[l],0.5);
errorsPosErrSummed[l] = errorsPosSummed[l]*0.001;
errorsMeanErrSummed[l] = errorsMeanSummed[l]*0.001;
errorsNegSummed[l] = -pow(errorsNegSummed[l],0.5);
errorsNegErrSummed[l] = errorsNegSummed[l]*0.001;
// add EMCal material errors
errorsPosCorrMatSummed[l] = pow(errorsPosCorrSummed[l]+ pow(errorMaterial ,2.) + pow(errorsPosCorr[7][l],2) ,0.5);
errorsMeanCorrMatSummed[l] = pow(errorsMeanCorrSummed[l]+ pow(errorMaterial ,2.)+ pow(errorsMeanCorr[7][l],2),0.5);
errorsNegCorrMatSummed[l] = -pow(errorsNegCorrSummed[l]+ pow(errorMaterial ,2.)+ pow(errorsNegCorr[7][l],2),0.5);
errorsPosCorrSummed[l] = pow(errorsPosCorrSummed[l],0.5);
errorsMeanCorrSummed[l] = pow(errorsMeanCorrSummed[l],0.5);
errorsPosErrCorrSummed[l] = errorsPosCorrSummed[l]*0.001;
errorsMeanErrCorrSummed[l] = errorsMeanCorrSummed[l]*0.001;
errorsMeanErrCorrMatSummed[l] = errorsMeanCorrMatSummed[l]*0.001;
errorsNegCorrSummed[l] = -pow(errorsNegCorrSummed[l],0.5);
errorsNegErrCorrSummed[l] = errorsNegCorrSummed[l]*0.001;
}
// Create all other summed graphs
cout << __LINE__ << endl;
negativeErrorsSummed = new TGraphErrors(nPtBins,ptBins ,errorsNegSummed ,ptBinsErr ,errorsNegErrSummed );
negativeErrorsCorrSummed = new TGraphErrors(nPtBins,ptBins ,errorsNegCorrSummed ,ptBinsErr ,errorsNegErrCorrSummed );
positiveErrorsSummed = new TGraphErrors(nPtBins,ptBins ,errorsPosSummed ,ptBinsErr ,errorsPosErrSummed );
positiveErrorsCorrSummed = new TGraphErrors(nPtBins,ptBins ,errorsPosCorrSummed ,ptBinsErr ,errorsPosErrCorrSummed );
meanErrorsSummed = new TGraphErrors(nPtBins,ptBins ,errorsMeanSummed ,ptBinsErr ,errorsMeanErrSummed );
meanErrorsCorrSummed = new TGraphErrors(nPtBins,ptBins ,errorsMeanCorrSummed ,ptBinsErr ,errorsMeanErrCorrSummed );
meanErrorsCorrSummedIncMat = new TGraphErrors(nPtBins,ptBins ,errorsMeanCorrMatSummed ,ptBinsErr ,errorsMeanErrCorrMatSummed );
cout << __LINE__ << endl;
// Give legend position for plotting
Double_t minXLegend = 0.12;
Double_t maxYLegend = 0.95;
if (meson.CompareTo("Eta") == 0){
minXLegend = 0.23;
}
Double_t widthLegend = 0.25;
if (numberCutStudies> 7)
widthLegend = 0.5;
Double_t heightLegend = 1.05* 0.035 * (numberCutStudies+3);
if (numberCutStudies> 7)
heightLegend = 1.05* 0.035 * (numberCutStudies/2+1);
if (numberCutStudies> 7 && meson.CompareTo("Eta") == 0)
heightLegend = 1.05* 0.035 * (numberCutStudies/2+1);
if (numberCutStudies> 7 && meson.CompareTo("Pi0EtaBinning") == 0)
heightLegend = 1.05* 0.035 * (numberCutStudies/2);
// ***************************************************************************************************
// ****************************** Plot all mean erros separately *************************************
// ***************************************************************************************************
TCanvas* canvasSysErrMean = new TCanvas("canvasSysErrMean","",200,10,1350,900);// gives the page size
DrawGammaCanvasSettings( canvasSysErrMean, 0.08, 0.01, 0.015, 0.09);
// create dummy histo
TH2D *histo2DSysErrMean ;
if (meson.Contains("Eta") ){
Double_t max = 30;
histo2DSysErrMean = new TH2D("histo2DSysErrMean", "", 20,0.,ptBins[nPtBins-1]+ptBinsErr[nPtBins-1],1000.,0.,max);
} else {
Double_t max = 20;
histo2DSysErrMean = new TH2D("histo2DSysErrMean", "", 20,0.,ptBins[nPtBins-1]+ptBinsErr[nPtBins-1],1000.,0.,max);
}
SetStyleHistoTH2ForGraphs( histo2DSysErrMean, "#it{p}_{T} (GeV/#it{c})", "mean systematic Err %", 0.03, 0.04, 0.03, 0.04,
1,0.9, 510, 510);
histo2DSysErrMean->Draw();
// create legend
TLegend* legendMean = GetAndSetLegend2(minXLegend,maxYLegend-heightLegend,minXLegend+widthLegend,maxYLegend, 30);
if (numberCutStudies> 7) legendMean->SetNColumns(2);
for(Int_t i = 0;i< numberCutStudies ;i++){
if ( meson.CompareTo("Eta") == 0 && (i == 1 || i == 14)){
cout << "not drawing: " << nameCutVariation[i].Data() << endl;
continue;
}
if ( meson.CompareTo("Pi0EtaBinning") == 0 && (i == 7 || i == 10 || i == 9 || i == 12) ){
cout << "not drawing: " << nameCutVariation[i].Data() << endl;
continue;
}
DrawGammaSetMarkerTGraphErr(meanErrors[i], markerStyle[i], 1.,color[i],color[i]);
meanErrors[i]->Draw("pE0,csame");
legendMean->AddEntry(meanErrors[i],nameCutVariation[i].Data(),"p");
}
legendMean->Draw();
// plot labeling
TLatex *labelMeson;
if (meson.CompareTo("Pi0EtaBinning") == 0){
labelMeson= new TLatex(0.75,0.89,Form("#eta/#pi^{0} rec. #gamma_{calo}"));
} else if (meson.Contains("Pi0")){
labelMeson= new TLatex(0.75,0.89,Form("#pi^{0} #rightarrow #gamma_{calo}#gamma_{calo}"));
} else {
labelMeson= new TLatex(0.75,0.89,Form("#eta #rightarrow #gamma_{calo}#gamma_{calo}"));
}
SetStyleTLatex( labelMeson, 0.038,4);
labelMeson->Draw();
TLatex *labelCentrality = new TLatex(0.75,0.93,Form("%s",collisionSystem.Data() ));
SetStyleTLatex( labelCentrality, 0.038,4);
labelCentrality->Draw();
TLatex *labelTrig= new TLatex(0.75,0.84,Form("LHC10c - INT1"));
if(labelTrig){
SetStyleTLatex( labelTrig, 0.038,4);
labelTrig->Draw();
}
canvasSysErrMean->Update();
canvasSysErrMean->SaveAs(Form("SystematicErrorsCalculatedCalo/SysMean_%s_%s%s_%s.%s",meson.Data(), energyForOutput.Data(),additionalNameOutput.Data(),dateForOutput.Data(),suffix.Data()));
delete canvasSysErrMean;
// ***************************************************************************************************
// ********************* Plot all mean erros separately after smoothing ******************************
// ***************************************************************************************************
TCanvas* canvasNewSysErrMean = new TCanvas("canvasNewSysErrMean","",200,10,1350,900);// gives the page size
DrawGammaCanvasSettings( canvasNewSysErrMean, 0.08, 0.01, 0.015, 0.09);
// create dummy histo
TH2D *histo2DNewSysErrMean ;
if (meson.Contains("Eta")){
Double_t max = 40;
histo2DNewSysErrMean = new TH2D("histo2DNewSysErrMean", "", 20,0.,ptBins[nPtBins-1]+ptBinsErr[nPtBins-1],1000.,-0.5,max);
} else {
Double_t max = 20;
histo2DNewSysErrMean = new TH2D("histo2DNewSysErrMean", "", 20,0.,ptBins[nPtBins-1]+ptBinsErr[nPtBins-1],1000.,-0.5,max);
}
SetStyleHistoTH2ForGraphs( histo2DNewSysErrMean, "#it{p}_{T} (GeV/#it{c})", "mean smoothed systematic Err %", 0.03, 0.04, 0.03, 0.04,
1,0.9, 510, 510);
histo2DNewSysErrMean->Draw();
// create legend
TLegend* legendMeanNew = GetAndSetLegend2(minXLegend,maxYLegend-heightLegend,minXLegend+widthLegend,maxYLegend, 30);
legendMeanNew->SetMargin(0.1);
if (numberCutStudies> 7) legendMeanNew->SetNColumns(2);
for(Int_t i = 0;i< numberCutStudies ;i++){
cout << i << "\t"<< additionalNameOutput.Data() << endl;
if ( meson.CompareTo("Eta") == 0 && i == 1 && additionalNameOutput.CompareTo("")==0){
cout << "not drawing: " << nameCutVariation[i].Data() << endl;
continue;
}
if ( meson.CompareTo("Eta") == 0 && (i == 14) ){
cout << "not drawing: " << nameCutVariation[i].Data() << endl;
continue;
}
if ( meson.CompareTo("Pi0EtaBinning") == 0 && (i == 7 || i == 10 || i == 9 || i == 12) ){
cout << "not drawing: " << nameCutVariation[i].Data() << endl;
continue;
}
DrawGammaSetMarkerTGraphErr(meanErrorsCorr[i], markerStyle[i], 1.,color[i],color[i]);
meanErrorsCorr[i]->Draw("pX0,csame");
legendMeanNew->AddEntry(meanErrorsCorr[i],nameCutVariation[i].Data(),"p");
}
DrawGammaSetMarkerTGraphErr(meanErrorsCorrSummedIncMat, 20, 1.,kBlack,kBlack);
meanErrorsCorrSummedIncMat->Draw("p,csame");
legendMeanNew->AddEntry(meanErrorsCorrSummedIncMat,"quad. sum.","p");
legendMeanNew->Draw();
// labeling
labelMeson->Draw();
labelCentrality->Draw();
labelTrig->Draw();
canvasNewSysErrMean->Update();
canvasNewSysErrMean->SaveAs(Form("SystematicErrorsCalculatedCalo/SysMeanNewWithMean_%s_%s%s_%s.%s",meson.Data(), energyForOutput.Data(),additionalNameOutput.Data(),dateForOutput.Data(),suffix.Data()));
// ***************************************************************************************************
// ********************* Plot unsmoothed errors with fits ********************************************
// ***************************************************************************************************
for (Int_t cut =0 ;cut < numberCutStudies;cut++ ){
canvasNewSysErrMean->cd();
histo2DNewSysErrMean->Draw();
if (bsmooth[cut]) continue;
cout <<endl << endl<< "variation: " << cut << " \t"<< nameCutVariation[cut].Data() << endl;
Double_t minPt = startPtSys;
Double_t maxPt = ptBins[nPtBins-2]+1;
TF1* pol0 = new TF1("pol0","[0]",minPt,maxPt);//
TF1* pol1 = new TF1("pol1","[0]+[1]*x",minPt,maxPt);//
TF1* pol2 = new TF1("pol2","[0]+[1]*x+[2]*x*x",minPt,maxPt);//
TF1* pol4 = new TF1("pol4","[0]+[1]*x+[2]*x*x+[3]*x*x*x*x",minPt,maxPt);//
TF1* bla = new TF1("bla","[0]+[1]/pow([2],x)",minPt,maxPt);
// TF1* bla = new TF1("bla","1.5+50/pow(5,x)",minPt,maxPt);
bla->SetParameter(0,1.5);
bla->SetParameter(1,50);
bla->SetParameter(2,5);
pol4->SetParLimits(3,0,10);
cout << "red: " << endl;
meanErrorsCorr[cut]->Fit(pol4,"NRMEX0+","",minPt,maxPt);
cout << "blue: " << endl;
meanErrorsCorr[cut]->Fit(pol2,"NRMEX0+","",minPt,maxPt);
cout << "cyan: " << endl;
meanErrorsCorr[cut]->Fit(pol1,"NRMEX0+","",minPt,maxPt);
cout << "black: " << endl;
meanErrorsCorr[cut]->Fit(pol0,"NRMEX0+","",minPt,maxPt);
cout << "magenta: " << endl;
meanErrorsCorr[cut]->Fit(bla,"NRMEX0+","",minPt,maxPt);
pol4->SetLineColor(kRed+2);
pol2->SetLineColor(kBlue+2);
pol1->SetLineColor(kCyan+2);
pol0->SetLineColor(kBlack);
bla->SetLineColor(kMagenta+2);
DrawGammaSetMarkerTGraphErr(meanErrorsCorr[cut], 20+cut, 1.,color[cut],color[cut]);
meanErrorsCorr[cut]->Draw("p,csame");
pol4->Draw("same");
pol2->Draw("same");
pol1->Draw("same");
pol0->Draw("same");
bla->Draw("same");
canvasNewSysErrMean->SaveAs(Form("SystematicErrorsCalculatedCalo/SysMeanNewWithMeanSingle_%s_%s%s_%s_Variation%d.%s",meson.Data(), energyForOutput.Data(),additionalNameOutput.Data(),dateForOutput.Data(),cut,suffix.Data()));
}
// ***************************************************************************************************
// ********************* Create output files with errors *********************************************
// ***************************************************************************************************
const char *SysErrDatname = Form("SystematicErrorsCalculatedCalo/SystematicErrorEMCEMC_%s_%s%s_%s.dat",meson.Data(),energyForOutput.Data(),additionalNameOutput.Data(),dateForOutput.Data());
fstream SysErrDat;
cout << SysErrDatname << endl;
SysErrDat.open(SysErrDatname, ios::out);
for (Int_t l=0;l< nPtBins;l++){
SysErrDat << ptBins[l] << "\t" <<errorsNegCorrMatSummed[l] << "\t" <<errorsPosCorrMatSummed[l] << "\t" <<errorsNegCorrSummed[l] << "\t" <<errorsPosCorrSummed[l] << endl;
}
SysErrDat.close();
const char *SysErrDatnameMean = Form("SystematicErrorsCalculatedCalo/SystematicErrorAveragedEMCEMC_%s_%s%s_%s.dat",meson.Data(),energyForOutput.Data(),additionalNameOutput.Data(),dateForOutput.Data());
fstream SysErrDatAver;
cout << SysErrDatnameMean << endl;
SysErrDatAver.open(SysErrDatnameMean, ios::out);
for (Int_t l=0;l< nPtBins;l++){
SysErrDatAver << ptBins[l] << "\t" << "-"<< errorsMeanCorrMatSummed[l] << "\t" <<errorsMeanCorrMatSummed[l] << "\t" << "-"<< errorsMeanCorrSummed[l] << "\t" <<errorsMeanCorrSummed[l] << endl;
}
const char *SysErrDatnameMeanSingleErr = Form("SystematicErrorsCalculatedCalo/SystematicErrorAveragedSingleEMCEMC_%s_%s%s_%s.dat",meson.Data(),energyForOutput.Data(),additionalNameOutput.Data(),dateForOutput.Data());
fstream SysErrDatAverSingle;
cout << SysErrDatnameMeanSingleErr << endl;
SysErrDatAverSingle.open(SysErrDatnameMeanSingleErr, ios::out);
SysErrDatAverSingle << "Pt bin\t" ;
for (Int_t i= 0; i< numberCutStudies; i++){
SysErrDatAverSingle << nameCutVariationSC[i] << "\t";
}
SysErrDatAverSingle << endl;
for (Int_t l=0;l< nPtBins;l++){
SysErrDatAverSingle << ptBins[l] << "\t";
for (Int_t i= 0; i< numberCutStudies; i++){
SysErrDatAverSingle << errorsMeanCorr[i][l] << "\t";
}
SysErrDatAverSingle << errorsMeanCorrMatSummed[l] << endl;
}
SysErrDatAverSingle.close();
// ***************************************************************************************************
// ********************* Group errors according to topic *********************************************
// ***************************************************************************************************
Double_t errorsMeanCorrSignalExtraction[nPtBins];
Double_t errorsMeanCorrClusterEnergy[nPtBins];
Double_t errorsMeanCorrClusterDescription[nPtBins];
Double_t errorsMeanCorrCellTiming[nPtBins];
for (Int_t l=0;l< nPtBins;l++){
// "YieldExtraction"-0,"OpeningAngle"-1, "ClusterMinEnergy"-2, "ClusterNCells"-3, "NonLinearity"-4, "ClusterTrackMatchingCalo" -5, "ClusterM02" -6, "ClusterMaterialTRD" -7, "ClusterEnergyScale" -8
// "Cell Timing" -9 , "PileUp" - 10, "Efficiency" -11, "ClusterTime" -12, "ClusterizationEnergy" -13, "Secondary" - 14, "YieldExtraction Pi0EtaBinning" -15
// grouping:
// Signal extraction: Yield extraction 0, Open-Angle 1
errorsMeanCorrSignalExtraction[l] = TMath::Sqrt(errorsMeanCorr[0][l]*errorsMeanCorr[0][l]+errorsMeanCorr[1][l]*errorsMeanCorr[1][l]+errorsMeanCorr[14][l]*errorsMeanCorr[14][l]);
if (meson.CompareTo("Pi0EtaBinning") == 0)
errorsMeanCorrSignalExtraction[l] = TMath::Sqrt(errorsMeanCorr[0][l]*errorsMeanCorr[0][l]+errorsMeanCorr[1][l]*errorsMeanCorr[1][l]+errorsMeanCorr[14][l]*errorsMeanCorr[14][l]+errorsMeanCorr[15][l]*errorsMeanCorr[15][l]);
// Cluster energy extraction: NonLinearity 4 , Energy Scale 8
errorsMeanCorrClusterEnergy[l] = TMath::Sqrt(errorsMeanCorr[4][l]*errorsMeanCorr[4][l]+errorsMeanCorr[8][l]*errorsMeanCorr[8][l]);
// cluster description in MC: ClusterMinEnergy 2, ClusterNCells 3, ClusterM02 6, Clusterization Energy-13
errorsMeanCorrClusterDescription[l] = TMath::Sqrt(errorsMeanCorr[2][l]*errorsMeanCorr[2][l]+errorsMeanCorr[3][l]*errorsMeanCorr[3][l]+errorsMeanCorr[6][l]*errorsMeanCorr[6][l]+errorsMeanCorr[13][l]*errorsMeanCorr[13][l]);
// cell timing: cell timing - -9, clusterTime - 12
errorsMeanCorrCellTiming[l] = TMath::Sqrt(errorsMeanCorr[9][l]*errorsMeanCorr[9][l]+errorsMeanCorr[12][l]*errorsMeanCorr[12][l]);
}
TGraphErrors* meanErrorsSignalExtraction = new TGraphErrors(nPtBins,ptBins ,errorsMeanCorrSignalExtraction ,ptBinsErr ,errorsMeanErrCorrSummed );
TGraphErrors* meanErrorsClusterDescrip = new TGraphErrors(nPtBins,ptBins ,errorsMeanCorrClusterDescription ,ptBinsErr ,errorsMeanErrCorrSummed );
TGraphErrors* meanErrorsClusterEnergy = new TGraphErrors(nPtBins,ptBins ,errorsMeanCorrClusterEnergy ,ptBinsErr ,errorsMeanErrCorrSummed );
TGraphErrors* meanErrorsCellTiming = new TGraphErrors(nPtBins,ptBins ,errorsMeanCorrCellTiming ,ptBinsErr ,errorsMeanErrCorrSummed );
// ***************************************************************************************************
// ********************* Plot grouped errors for better understanding ********************************
// ***************************************************************************************************
Double_t minXLegend2 = 0.13;
Double_t maxYLegend2 = 0.95;
if (meson.CompareTo("Eta") == 0){
minXLegend2 = 0.20;
}
Double_t widthLegend2 = 0.52;
Double_t heightLegend2 = 0.15;
TCanvas* canvasSummedErrMean = new TCanvas("canvasSummedErrMean","",200,10,1350,900);// gives the page size
DrawGammaCanvasSettings( canvasSummedErrMean, 0.08, 0.01, 0.015, 0.09);
// create dummy histo
TH2D *histo2DSummedErrMean ;
if (meson.Contains("Eta") ){
Double_t max = 30.;
histo2DSummedErrMean = new TH2D("histo2DSummedErrMean", "", 20,0.,ptBins[nPtBins-1]+ptBinsErr[nPtBins-1],1000.,-0.5,max);
} else {
Double_t max = 17;
histo2DSummedErrMean = new TH2D("histo2DSummedErrMean", "", 20,0.,ptBins[nPtBins-1]+ptBinsErr[nPtBins-1],1000.,-0.5,max);
}
SetStyleHistoTH2ForGraphs( histo2DSummedErrMean, "#it{p}_{T} (GeV/#it{c})", "mean smoothed systematic Err %", 0.03, 0.04, 0.03, 0.04,
1,0.9, 510, 510);
histo2DSummedErrMean->Draw();
// create legend
TLegend* legendSummedMeanNew = GetAndSetLegend2(minXLegend2,maxYLegend2-heightLegend2,minXLegend2+widthLegend2,maxYLegend2, 30);
legendSummedMeanNew->SetNColumns(2);
legendSummedMeanNew->SetMargin(0.1);
// Signal extraction error
DrawGammaSetMarkerTGraphErr(meanErrorsSignalExtraction, 20, 1.,color[0],color[0]);
meanErrorsSignalExtraction->Draw("pX0,csame");
// Cluster description in MC
DrawGammaSetMarkerTGraphErr(meanErrorsClusterDescrip, 22, 1.,color[1],color[1]);
meanErrorsClusterDescrip->Draw("pX0,csame");
// Track matching to EMCAL
DrawGammaSetMarkerTGraphErr(meanErrorsCorr[5], 25, 1.,color[2],color[2]);
meanErrorsCorr[5]->Draw("pX0,csame");
// Material infront of EMCAL
if (meson.CompareTo("Pi0EtaBinning") != 0){
DrawGammaSetMarkerTGraphErr(meanErrorsCorr[7], 21, 1.,kMagenta+2,kMagenta+2);
meanErrorsCorr[7]->Draw("pX0,csame");
}
// Cluster energy description
DrawGammaSetMarkerTGraphErr(meanErrorsClusterEnergy, 20, 1.,color[4],color[4]);
meanErrorsClusterEnergy->Draw("pX0,csame");
// timing errors
if (meson.CompareTo("Pi0EtaBinning") != 0){
DrawGammaSetMarkerTGraphErr(meanErrorsCellTiming, 23, 1.,color[5],color[5]);
meanErrorsCellTiming->Draw("pX0,csame");
}
// efficiency errors
if (numberCutStudies>11){
DrawGammaSetMarkerTGraphErr(meanErrorsCorr[10], 23, 1.,color[8],color[8]);
meanErrorsCorr[11]->Draw("pX0,csame");
}
// PileUp errors
if (numberCutStudies>10 /*&& !(additionalNameOutput.CompareTo("") == 0 || additionalNameOutput.CompareTo("INT7") ==0 )*/ && meson.CompareTo("Pi0EtaBinning") != 0){
DrawGammaSetMarkerTGraphErr(meanErrorsCorr[10], 25, 1.,color[6],color[6]);
meanErrorsCorr[10]->Draw("pX0,csame");
}
//period error
// if (meson.CompareTo("Pi0EtaBinning") != 0){
// DrawGammaSetMarkerTGraphErr(meanErrorsCorr[14], 26, 1.,color[6],color[6]);
// meanErrorsCorr[14]->Draw("pX0,csame");
// }
legendSummedMeanNew->AddEntry(meanErrorsSignalExtraction,"signal extraction","p");
legendSummedMeanNew->AddEntry(meanErrorsClusterDescrip,"cluster description","p");
legendSummedMeanNew->AddEntry(meanErrorsClusterEnergy,"cluster energy description","p");
legendSummedMeanNew->AddEntry(meanErrorsCorr[5],"track match. to cluster","p");
if (meson.CompareTo("Pi0EtaBinning") != 0)legendSummedMeanNew->AddEntry(meanErrorsCorr[7],"mat. infront of EMCal","p");
if (meson.CompareTo("Pi0EtaBinning") != 0)legendSummedMeanNew->AddEntry(meanErrorsCellTiming,"cell timing","p");
if (numberCutStudies>11) legendSummedMeanNew->AddEntry(meanErrorsCorr[11],"efficiency","p");
if (numberCutStudies>10 /*&& !(additionalNameOutput.CompareTo("") == 0) */&& meson.CompareTo("Pi0EtaBinning") != 0)
legendSummedMeanNew->AddEntry(meanErrorsCorr[10],"SPD pileup","p");
DrawGammaSetMarkerTGraphErr(meanErrorsCorrSummedIncMat, 20, 1.,kBlack,kBlack);
meanErrorsCorrSummedIncMat->Draw("p,csame");
legendSummedMeanNew->AddEntry(meanErrorsCorrSummedIncMat,"quad. sum.","p");
legendSummedMeanNew->Draw();
labelMeson->Draw();
labelCentrality->Draw();
labelTrig->Draw();
canvasSummedErrMean->Update();
canvasSummedErrMean->SaveAs(Form("SystematicErrorsCalculatedCalo/SysErrorSummedVisu_%s_%s%s_%s.%s",meson.Data(), energyForOutput.Data(),additionalNameOutput.Data(),dateForOutput.Data(),suffix.Data()));
delete canvasSummedErrMean;
//
//
//
// const char *SysErrDatnameMeanPaper = Form("SystematicErrorsCalculatedConvCalo/SystematicErrorAveragedPaper_%s_%s%s_%s.dat",meson.Data(),energyForOutput.Data(),additionalNameOutput.Data(),dateForOutput.Data());
// fstream SysErrDatAverPaper;
// cout << SysErrDatnameMeanPaper << endl;
// SysErrDatAverPaper.open(SysErrDatnameMeanPaper, ios::out);
// SysErrDatAverPaper << "#it{p}_{T}" << "\t Material \t Yield Extraction \t PID \t photon reco \t track recon \t summed" << endl;
// for (Int_t l=0;l< nPtBins;l++){
// SysErrDatAverPaper << ptBins[l] <<"\t" << errorMaterial*2 << "\t" << errorsMeanCorrSignalExtraction[l] << "\t" << errorsMeanCorrPID[l]<< "\t" << errorsMeanCorrPhotonReco[l]<< "\t" <<errorsMeanCorrTrackReco[l] <<"\t" << errorsMeanCorrMatSummed[l]<< endl;
// }
//
// SysErrDatAverPaper.close();
}