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FinaliseSystematicErrorsCalo_omega_pp.C
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FinaliseSystematicErrorsCalo_omega_pp.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"
Float_t CalculatePi0Pt(Float_t omegaPt){
// Function extraction from gen level simulations
Float_t pi0pt = 0.015899 + 0.326616*omegaPt;
return pi0pt;
}
void FinaliseSystematicErrorsCalo_omega_pp( TString nameDataFileErrors = "",
TString energy = "",
TString meson = "",
Int_t numberOfPtBins = 1 ,
Int_t numberCutStudies = 1,
Double_t startPtSys = 0,
TString additionalName = "",
TString additionalNameOutput = "",
TString suffix = "eps",
Bool_t showBeforeSmoothing = kFALSE,
Int_t mode = 44
){
// ***************************************************************************************************
// ****************************** 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;
TString recoMethod = ReturnFullTextReconstructionProcess(mode);
TString recoMethodForWriting = ReturnTextReconstructionProcessWrite(mode);
printf("INFO: Chosen mode is %i: %s\n",mode,recoMethod.Data());
energyForOutput.ReplaceAll(".","_");
// ***************************************************************************************************
// ******************************* general variable definition **************************************
// ***************************************************************************************************
const Int_t nPtBins = numberOfPtBins;
const Int_t nCuts = numberCutStudies;
Double_t* ptBins = 0;
Double_t* ptBinsErr = 0;
TString nameCutVariationSC[19];
TString nameCutVariationSCCurrent[19] = { "RemovePileUp", // 0
"Calo_NonLin", // 1
"Calo_Timing", // 2
"Calo_TrackMatching", // 3
"Calo_MinEnergy", // 4
"Calo_MinNCells", // 5
"Calo_MinMaxM02", // 6
"Calo_ClusterEnergyScale", // 7
"Clusterizer", // 8
"ChargedPion_ITSRequirement", // 9
"ChargedPion_ClsTPCCut", // 10
"ChargedPion_pTCut", // 11
"ChargedPion_TPCdEdxCutPion", // 12
"ChargedPion_MassCut", // 13
"NeutralPion_SelectionWindows", // 14
"Omega_BackgroundScheme", // 15
"Omega_RecoEfficiency", // 16
"Omega_BranchingRatio", // 17
"YieldExtraction"}; // 18
TString nameCutVariation[19] = {"pileup","#gamma_{clus.} non-linearity","#gamma_{clus.} timing","#gamma_{clus.} trackmatching","#gamma_{clus.} min. energy","#gamma_{clus.} N_{cells,min}","#gamma_{clus.} shape","cluster energy scale", "clusterizer algorithm",
"charged pion N_{cls,ITS}", "#pi^{#pm} rec. N_{cls,TPC}","#pi^{#pm} rec.min p_{T}","#pi^{#pm} rec. PID","M_{#pi^{+}#pi^{-}} cut","#pi^{0} rec. M_{#gamma#gamma} cut","background description",
"reco. efficiency","branching ratio","yield extraction"};
Color_t color[34] = {kTeal+3,
kCyan-2,kGray+2,kViolet+1,kAzure+1,kAzure+4,kPink+4,kOrange,
kBlue,kRed-2,kBlue,kRed+1,kOrange+7,
kRed+1,kOrange+7,kPink+8,
kPink+8,kGreen+2,kYellow+2,
kOrange+2,kBlue+2,
kPink-3,
kCyan-2,kGray+2,kViolet+1,kAzure+1,kAzure+4,kPink+4,kOrange,404,kPink-6,860,kBlue-4,kRed-4};
Color_t markerStyle[23]={25,
27,26,28,30,31,33,23,
24,21,22,23,20,
26,26,27,
26,28,
30,
20,26,26};
// Display names
for (Int_t k =0; k<nCuts; k++ ){
cout << "variation: " << nameCutVariationSCCurrent[k].Data() << endl;
cout << "name for writing: " << nameCutVariationSCCurrent[k].Data() << endl;
cout << "display name: " << nameCutVariation[k].Data() << endl;
}
for (Int_t i = 0; i < numberCutStudies; i++){
nameCutVariationSC[i] = nameCutVariationSCCurrent[i];
}
// ***************************************************************************************************
// ******************************** Booleans for smoothing *******************************************
// ***************************************************************************************************
Bool_t bsmooth[19] = { 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0};
Bool_t bsmoothMBOmega07TeV[19] = { 1, // pileup
1, 1, 1, 1, 1, 1,1,1, // calo
1, 1, 1, 1, 1, // charged pion
1, // neutral pion
1, 1, 1, // omega
0}; // yield extraction
Bool_t bsmoothMBEta07TeV[19] = { 1, // pileup
1, 1, 1, 1, 1, 1, 1, 1, // calo
1, 1, 1, 1, 1, // charged pion
1, // neutral pion
1, 1, 1, // omega
0}; // yield extraction
if(meson.Contains("Eta") && (mode == 45)) bsmoothMBEta07TeV[15] = 1;
Bool_t bsmoothMBOmegaToPi07TeV[16] = { 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0 ,0 , 0, 0, 0, 0}; // currently not used
// get smoothing switches needed for meson
for (Int_t i = 0; i < numberCutStudies; i++){
if (energy.CompareTo("7TeV") == 0){
if (additionalNameOutput.CompareTo("") == 0 && meson.CompareTo("Omega")==0){
bsmooth[i] = bsmoothMBOmega07TeV[i];
} else if (additionalNameOutput.CompareTo("") == 0 && meson.CompareTo("Eta")==0){
bsmooth[i] = bsmoothMBEta07TeV[i];
} else if (additionalNameOutput.CompareTo("") == 0 && meson.CompareTo("OmegaToPi0")==0){
bsmooth[i] = bsmoothMBOmegaToPi07TeV[i]; // not implemented yet
}
}
}
// ***************************************************************************************************
// ****************************** 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 errorsMeanCorrBefore[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 errorsMeanErrCorrBefore[nCuts][nPtBins];
Double_t errorsMeanErrSummed[nPtBins];
Double_t errorsMeanErrCorrSummed[nPtBins];
Double_t errorsMeanErrCorrMatSummed[nPtBins];
TGraphErrors* negativeErrors[nCuts];
TGraphErrors* negativeErrorsSummed;
TGraphErrors* positiveErrors[nCuts];
TGraphErrors* positiveErrorsSummed;
TGraphErrors* negativeErrorsCorr[nCuts];
TGraphErrors* negativeErrorsCorrSummed;
TGraphErrors* positiveErrorsCorr[nCuts];
TGraphErrors* positiveErrorsCorrSummed;
TGraphErrors* meanErrors[nCuts];
TGraphErrors* meanErrorsSummed;
TGraphErrors* meanErrorsCorr[nCuts];
TGraphErrors* meanErrorsCorrBefore[nCuts];
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 **************************************
// ***************************************************************************************************
Bool_t foundHisto[nCuts]; // keep track if histo is found or dummy is used
for(Int_t i = 0; i < nCuts; i++){
foundHisto[i] = kFALSE;
}
TFile* fileErrorInput = new TFile(nameDataFileErrors);
for (Int_t i = 0; i < nCuts; i++){
TGraphAsymmErrors* graphPosErrors = NULL;
TGraphAsymmErrors* graphNegErrors = NULL;
if ( nameCutVariationSC[i].CompareTo("RemovePileUp")==0
|| nameCutVariationSC[i].CompareTo("Calo_NonLin")==0
|| nameCutVariationSC[i].CompareTo("Calo_Timing")==0
|| nameCutVariationSC[i].CompareTo("Calo_TrackMatching")==0
|| nameCutVariationSC[i].CompareTo("Calo_MinEnergy")==0
|| nameCutVariationSC[i].CompareTo("Calo_MinNCells")==0
|| nameCutVariationSC[i].CompareTo("Calo_MinMaxM02")==0
|| nameCutVariationSC[i].CompareTo("ChargedPion_ITSRequirement")==0
|| nameCutVariationSC[i].CompareTo("ChargedPion_ClsTPCCut")==0
|| nameCutVariationSC[i].CompareTo("ChargedPion_pTCut")==0
|| nameCutVariationSC[i].CompareTo("ChargedPion_TPCdEdxCutPion")==0
|| nameCutVariationSC[i].CompareTo("ChargedPion_MassCut")==0
|| nameCutVariationSC[i].CompareTo("NeutralPion_SelectionWindows")==0
|| nameCutVariationSC[i].CompareTo("Omega_BackgroundScheme")==0
|| nameCutVariationSC[i].CompareTo("Omega_NumberBckEvents")==0
|| nameCutVariationSC[i].CompareTo("Omega_RapidityCut")==0){
TString nameGraphPos = Form("%s_SystErrorRelPos_%spp",meson.Data(),nameCutVariationSC[i].Data() );
TString nameGraphNeg = Form("%s_SystErrorRelNeg_%spp",meson.Data(),nameCutVariationSC[i].Data() );
graphPosErrors = (TGraphAsymmErrors*)fileErrorInput->Get(nameGraphPos.Data());
graphNegErrors = (TGraphAsymmErrors*)fileErrorInput->Get(nameGraphNeg.Data());
} else if (nameCutVariationSC[i].CompareTo("YieldExtraction")==0){
TString nameGraphPos = Form("%s_SystErrorRelPos_%s_pp",meson.Data(),nameCutVariationSC[i].Data() );
TString nameGraphNeg = Form("%s_SystErrorRelNeg_%s_pp",meson.Data(),nameCutVariationSC[i].Data() );
graphPosErrors = (TGraphAsymmErrors*)fileErrorInput->Get(nameGraphPos.Data());
graphNegErrors = (TGraphAsymmErrors*)fileErrorInput->Get(nameGraphNeg.Data());
} else if (nameCutVariationSC[i].CompareTo("Clusterizer")==0){
// take pileup graph as dummy
TString nameGraphPos = Form("%s_SystErrorRelPos_%spp",meson.Data(),nameCutVariationSC[0].Data() );
TString nameGraphNeg = Form("%s_SystErrorRelNeg_%spp",meson.Data(),nameCutVariationSC[0].Data() );
graphPosErrors = (TGraphAsymmErrors*)fileErrorInput->Get(nameGraphPos.Data());
graphNegErrors = (TGraphAsymmErrors*)fileErrorInput->Get(nameGraphNeg.Data());
} else {
// name is not in list
printf("WARNING: trying to get %s, but no rule is known. Will try to get it anyways ... \n",nameCutVariationSC[i].Data());
TString nameGraphPos = Form("%s_SystErrorRelPos_%spp",meson.Data(),nameCutVariationSC[i].Data() );
TString nameGraphNeg = Form("%s_SystErrorRelNeg_%spp",meson.Data(),nameCutVariationSC[i].Data() );
graphPosErrors = (TGraphAsymmErrors*)fileErrorInput->Get(nameGraphPos.Data());
graphNegErrors = (TGraphAsymmErrors*)fileErrorInput->Get(nameGraphNeg.Data());
}
// check now if getting the histogram actually worked
if(graphPosErrors==NULL){
printf("WARNING: Didn't find %s graph in file %s!\n",nameCutVariationSC[i].Data(),fileErrorInput->GetName());
printf("WARNING: Will use yield extraction histogram as dummy instead!");
TString nameGraphPos = Form("%s_SystErrorRelPos_%s_pp",meson.Data(),"YieldExtraction" );
TString nameGraphNeg = Form("%s_SystErrorRelNeg_%s_pp",meson.Data(),"YieldExtraction" );
graphPosErrors = (TGraphAsymmErrors*)fileErrorInput->Get(nameGraphPos.Data());
graphNegErrors = (TGraphAsymmErrors*)fileErrorInput->Get(nameGraphNeg.Data());
if(graphPosErrors==NULL){ // still didnt find histo
printf("ERROR: Could't find yield extraction histo either, returning ...");
return;
}
// Set everything to zero
printf("INFO: Using YieldExtraction graph for %s and setting all values to zero ...\n",nameCutVariationSC[i].Data());
for (Int_t k = 0; k< graphPosErrors->GetN(); k++){
graphPosErrors->SetPoint(k, graphPosErrors->GetX()[k],0);
graphPosErrors->SetPointEYhigh (k, 0);
graphPosErrors->SetPointEYlow (k, 0);
graphNegErrors->SetPoint(k, graphNegErrors->GetX()[k],0);
graphNegErrors->SetPointEYhigh (k, 0);
graphNegErrors->SetPointEYlow (k, 0);
}
graphPosErrors->SetName(Form("%s_SystErrorRelPos_%spp",meson.Data(),nameCutVariationSC[i].Data()));
graphNegErrors->SetName(Form("%s_SystErrorRelNeg_%spp",meson.Data(),nameCutVariationSC[i].Data()));
} else{
printf("INFO: Loaded %s.graph succesfully!.. \n",nameCutVariationSC[i].Data());
foundHisto[i]=kTRUE;
}
// remove points below minPt
while (graphPosErrors->GetX()[0] < startPtSys){
graphPosErrors->RemovePoint(0);
graphNegErrors->RemovePoint(0);
}
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;
CalculateMeanSysErr( errorsMean[i], errorsMeanErr[i], errorsPos[i], errorsNeg[i], nPtBins);
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);
CorrectSystematicErrorsWithMean(errorsMean[i], errorsMeanErr[i], errorsMeanCorrBefore[i], errorsMeanErrCorrBefore[i], nPtBins);
// Routine 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]){
Double_t minPt = -10;
Double_t errorReset = -10000;
showBeforeSmoothing = kTRUE;
// pileup
if (nameCutVariationSC[i].CompareTo("RemovePileUp")==0 ){
minPt = startPtSys;
if (!energy.CompareTo("7TeV")) // same for EMCal and PHOS
errorReset = 0.5; // 5% higher yield * 90% efficiency
for (Int_t k = 0; k < nPtBins; k++){
if (ptBins[k] > minPt){
errorsMean[i][k] = errorReset;
errorsMeanErr[i][k] = errorReset*0.01;
errorsMeanCorr[i][k] = errorReset;
errorsMeanErrCorr[i][k] = errorReset*0.01;
}
}
// calo photon nonlin
} else if (nameCutVariationSC[i].CompareTo("Calo_NonLin")==0 ){ // taken from pi0
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
errorReset = 2.5;
if((mode==45) || (mode==65)){
errorReset = 1.;
}
}
if (ptBins[k] > minPt){
errorsMean[i][k] = errorReset;
errorsMeanErr[i][k] = errorReset*0.01;
errorsMeanCorr[i][k] = errorReset;
errorsMeanErrCorr[i][k] = errorReset*0.01;
}
}
// calo photon timing
} else if (nameCutVariationSC[i].CompareTo("Calo_Timing")==0 ){
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
errorReset = 1.;
if((mode==45) || (mode==65)){
errorReset = 1.;
}
}
if (ptBins[k] > minPt){
errorsMean[i][k] = errorReset;
errorsMeanErr[i][k] = errorReset*0.01;
errorsMeanCorr[i][k] = errorReset;
errorsMeanErrCorr[i][k] = errorReset*0.01;
}
}
// calo photon track matching
} else if (nameCutVariationSC[i].CompareTo("Calo_TrackMatching")==0 ){
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
errorReset = 5.;
if((mode==45) || (mode==65)){
errorReset = 13.7687+-1.86235*ptBins[k]+-0.032003*pow(ptBins[k],2)+0.00178513*pow(ptBins[k],4);
if (ptBins[k] >= 7) errorReset = 13.7687+-1.86235*7+-0.032003*pow(7,2)+0.00178513*pow(7,4);
}
//if(ptBins[k]>=7.) errorReset += (0.2)*(ptBins[k]-7.); // adapted from pi0
}
if (ptBins[k] > minPt){
errorsMean[i][k] = errorReset;
errorsMeanErr[i][k] = errorReset*0.01;
errorsMeanCorr[i][k] = errorReset;
errorsMeanErrCorr[i][k] = errorReset*0.01;
}
}
// calo photon min energy
} else if (nameCutVariationSC[i].CompareTo("Calo_MinEnergy")==0 ){
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
if(ptBins[k] < 9.){
errorReset = 1.35091+2328.04/pow(4.21981,ptBins[k]);
}else{
errorReset = 1.35091+2328.04/pow(4.21981,9.);
}
if(mode==45 || mode == 65){ // if PHOS is used, estimate const error at 5GeV as dummy
errorReset = 3.39764+370.666/pow(3.9,ptBins[k]);
}
}
if (ptBins[k] > minPt){
errorsMean[i][k] = errorReset;
errorsMeanErr[i][k] = errorReset*0.01;
errorsMeanCorr[i][k] = errorReset;
errorsMeanErrCorr[i][k] = errorReset*0.01;
}
}
// calo photon min nmb of cells per cluster
} else if (nameCutVariationSC[i].CompareTo("Calo_MinNCells")==0 ){
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
errorReset = 1.;
if(mode==45 || mode == 65){
errorReset = 2.; // 2% flat taken from Pooja pi0 analysis note
}
}
if (ptBins[k] > minPt){
errorsMean[i][k] = errorReset;
errorsMeanErr[i][k] = errorReset*0.01;
errorsMeanCorr[i][k] = errorReset;
errorsMeanErrCorr[i][k] = errorReset*0.01;
}
}
// calo photon cluster shape
} else if (nameCutVariationSC[i].CompareTo("Calo_MinMaxM02")==0 ){
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
//errorReset = 0.9+(-0.007)*ptBins[k]+(0.013)*ptBins[k]*ptBins[k];
errorReset = 3;
if(mode==45 || mode == 65){
errorReset = 4.;
}
}
if (ptBins[k] > minPt){
errorsMean[i][k] = errorReset;
errorsMeanErr[i][k] = errorReset*0.01;
errorsMeanCorr[i][k] = errorReset;
errorsMeanErrCorr[i][k] = errorReset*0.01;
}
}
// cluster energy scale
} else if (nameCutVariationSC[i].CompareTo("Calo_ClusterEnergyScale")==0 ){
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
errorReset = 2.5; // calculated with (1-(1./TMath::Power(1.0039,7))) * 100;
if(mode==45 || mode == 65){
errorReset = 4;//0.01% * 7 =
}
}
if (ptBins[k] > minPt){
errorsMean[i][k] = errorReset;
errorsMeanErr[i][k] = errorReset*0.01;
errorsMeanCorr[i][k] = errorReset;
errorsMeanErrCorr[i][k] = errorReset*0.01;
}
}
// clusterization Energy taken from pi0
} else if (nameCutVariationSC[i].CompareTo("Clusterizer")==0 ){
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
errorReset = TMath::Sqrt(pow(3.0 + 20./pow(10,ptBins[k]),2.)+pow(0.5,2.)); // cell min energy + cell timing
if(mode==45 || mode == 65){
// I have no clue what the uncertainty of the clusterizer is
errorReset = 3.; // dummy value
}
}
if (ptBins[k] > minPt){
errorsMean[i][k] = errorReset;
errorsMeanErr[i][k] = errorReset*0.01;
errorsMeanCorr[i][k] = errorReset;
errorsMeanErrCorr[i][k] = errorReset*0.01;
}
}
// charged pion track cls in ITS
} else if (nameCutVariationSC[i].CompareTo("ChargedPion_ITSRequirement")==0 ){
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
errorReset = -0.21536+0.500256*ptBins[k];
}
if (ptBins[k] > minPt){
errorsMean[i][k] = errorReset;
errorsMeanErr[i][k] = errorReset*0.01;
errorsMeanCorr[i][k] = errorReset;
errorsMeanErrCorr[i][k] = errorReset*0.01;
}
}
// charged pion track cls in TPC
} else if (nameCutVariationSC[i].CompareTo("ChargedPion_ClsTPCCut")==0 ){
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
errorReset = 5.5;
if(mode==45 || mode == 65){
errorReset = 5.5;
}
}
if (ptBins[k] > minPt){
errorsMean[i][k] = errorReset;
errorsMeanErr[i][k] = errorReset*0.01;
errorsMeanCorr[i][k] = errorReset;
errorsMeanErrCorr[i][k] = errorReset*0.01;
}
}
// charged pion pT cut
} else if (nameCutVariationSC[i].CompareTo("ChargedPion_pTCut")==0 ){
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
errorReset = 3.0;
if(mode==45 || mode == 65){
errorReset = 3.;
}
}
if (ptBins[k] > minPt){
errorsMean[i][k] = errorReset;
errorsMeanErr[i][k] = errorReset*0.01;
errorsMeanCorr[i][k] = errorReset;
errorsMeanErrCorr[i][k] = errorReset*0.01;
}
}
// charged pion PID
} else if (nameCutVariationSC[i].CompareTo("ChargedPion_TPCdEdxCutPion")==0 ){
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
errorReset = 3.0;
if(mode==45 || mode == 65){
errorReset = 3.;
}
}
if (ptBins[k] > minPt){
errorsMean[i][k] = errorReset;
errorsMeanErr[i][k] = errorReset*0.01;
errorsMeanCorr[i][k] = errorReset;
errorsMeanErrCorr[i][k] = errorReset*0.01;
}
}
// charged pion pair mass window
} else if (nameCutVariationSC[i].CompareTo("ChargedPion_MassCut")==0 ){
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
errorReset = 2.;
}
if (ptBins[k] > minPt){
errorsMean[i][k] = errorReset;
errorsMeanErr[i][k] = errorReset*0.01;
errorsMeanCorr[i][k] = errorReset;
errorsMeanErrCorr[i][k] = errorReset*0.01;
}
}
// two gamma mass window
} else if (nameCutVariationSC[i].CompareTo("NeutralPion_SelectionWindows")==0 ){
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
errorReset = 9.; // used from conv
if(mode==45 || mode == 65){
errorReset = 9.;
}
}
if (ptBins[k] > minPt){
errorsMean[i][k] = errorReset;
errorsMeanErr[i][k] = errorReset*0.01;
errorsMeanCorr[i][k] = errorReset;
errorsMeanErrCorr[i][k] = errorReset*0.01;
}
}
// omega branching ratio
} else if (nameCutVariationSC[i].CompareTo("Omega_BranchingRatio")==0 ){
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
errorReset = 0.8;
}
if (ptBins[k] > minPt){
errorsMean[i][k] = errorReset;
errorsMeanErr[i][k] = errorReset*0.01;
errorsMeanCorr[i][k] = errorReset;
errorsMeanErrCorr[i][k] = errorReset*0.01;
}
}
// background description
} else if (nameCutVariationSC[i].CompareTo("Omega_BackgroundScheme")==0 ){
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
errorReset = 13-(0.66*ptBins[k]);
if((mode==45) || (mode==65)){ // PHOS
//errorReset = 13-(0.66*ptBins[k]);
//errorReset = 7-(0.66*ptBins[k]);
errorReset = 20.9952+-4.41681*ptBins[k]+0.450559*pow(ptBins[k],2);
}
}
if (ptBins[k] > minPt){
errorsMean[i][k] = errorReset;
errorsMeanErr[i][k] = errorReset*0.01;
errorsMeanCorr[i][k] = errorReset;
errorsMeanErrCorr[i][k] = errorReset*0.01;
}
}
// reconstruction efficiency -> TODO
} else if (nameCutVariationSC[i].CompareTo("Omega_RecoEfficiency")==0 ){
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
errorReset = 2.0; //dummy
}
if (ptBins[k] > minPt){
errorsMean[i][k] = errorReset;
errorsMeanErr[i][k] = errorReset*0.01;
errorsMeanCorr[i][k] = errorReset;
errorsMeanErrCorr[i][k] = errorReset*0.01;
}
}
// Yield Extraction
} else if (nameCutVariationSC[i].CompareTo("YieldExtraction")==0 ){
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
//errorReset = -5.*ptBins[k]+45;
errorReset = 5;
}
if (ptBins[k] > minPt){
errorsMean[i][k] = errorReset;
errorsMeanErr[i][k] = errorReset*0.01;
errorsMeanCorr[i][k] = errorReset;
errorsMeanErrCorr[i][k] = errorReset*0.01;
}
}
}
} // end smoothing
// Quadratic sum of errors except material
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);
}
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] );
meanErrorsCorrBefore[i] = new TGraphErrors(nPtBins,ptBins ,errorsMeanCorrBefore[i] ,ptBinsErr ,errorsMeanErrCorrBefore[i] );
positiveErrorsCorr[i] = new TGraphErrors(nPtBins,ptBins ,errorsPosCorr[i] ,ptBinsErr ,errorsPosErrCorr[i] );
if ( !meson.CompareTo("EtaToPi0") && !nameCutVariationSC[i].CompareTo("YieldExtraction_pp") && i==1){
// set the pi0etabinning yield error to zero as both yield errors are already combined in the eta yield error
for (Int_t k = 0; k < nPtBins; k++){
if (ptBins[k] > -10){
errorsMean[i][k] = 0;
errorsMeanErr[i][k] = 0;
errorsMeanCorr[i][k] = 0;
errorsMeanErrCorr[i][k] = 0;
}
}
}
}
// inner material budget
Double_t errorInnerMaterial = 0.;
// outer material budget from EMCal (only for 2010)
Double_t errorOuterMaterial = 3.;
if((mode==45) || (mode ==65)){ // for PHOS add additiopn 3% due to TRD present in front of it
errorOuterMaterial = pow(pow(errorOuterMaterial,2)+pow(errorOuterMaterial,2),0.5);
}
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(2*errorInnerMaterial ,2.) + pow(errorOuterMaterial,2),0.5);
errorsMeanCorrMatSummed[l] = pow(errorsMeanCorrSummed[l]+ pow(2*errorInnerMaterial ,2.)+ pow(errorOuterMaterial,2),0.5);
errorsNegCorrMatSummed[l] = -pow(errorsNegCorrSummed[l]+ pow(2*errorInnerMaterial ,2.)+ pow(errorOuterMaterial,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;
}
Double_t errorsMat[nPtBins];
Double_t errorsErrMat[nPtBins];
for (Int_t l = 0; l < nPtBins; l++){
errorsMat[l] = pow(pow(errorInnerMaterial,2) + pow(errorOuterMaterial,2),0.5);
errorsErrMat[l] = pow(pow(errorInnerMaterial,2) + pow(errorOuterMaterial,2),0.5)/100;
}
TGraphErrors* graphMaterialError = new TGraphErrors(nPtBins,ptBins ,errorsMat ,ptBinsErr ,errorsErrMat );
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 );
// 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;
if (numberCutStudies> 11)
widthLegend = 0.65;
Double_t heightLegend = 1.05* 0.04 * (numberCutStudies+3);
if (numberCutStudies> 7)
heightLegend = 1.05* 0.03 * (numberCutStudies/2+1);
if (numberCutStudies> 7 && meson.CompareTo("Eta") == 0)
heightLegend = 1.05* 0.035 * (numberCutStudies/2+1);
if (numberCutStudies> 7 && meson.CompareTo("EtaToPi0") == 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("Pi0") ){
histo2DSysErrMean = new TH2D("histo2DSysErrMean", "", 20,0.,ptBins[nPtBins-1]+ptBinsErr[nPtBins-1],1000.,0.,25.);
} else {
histo2DSysErrMean = new TH2D("histo2DSysErrMean", "", 20,0.,ptBins[nPtBins-1]+ptBinsErr[nPtBins-1],1000.,0.,25.);
}
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++){
DrawGammaSetMarkerTGraphErr(meanErrors[i], markerStyle[i], 0.4,color[i],color[i]);
meanErrors[i]->Draw("pE0,csame");
legendMean->AddEntry(meanErrors[i],nameCutVariation[i].Data(),"p");
}
legendMean->SetMargin(0.05);
legendMean->Draw();
// plot labeling
TLatex *labelMeson;
if (meson.CompareTo("EtaToPi0") == 0){
labelMeson= new TLatex(0.95,0.89,Form("#eta/#pi^{0} rec. #gamma_{conv}"));
} else if (meson.Contains("Omega")){
labelMeson= new TLatex(0.95,0.89,Form("#omega #rightarrow #pi^{+}#pi^{-}#pi^{0}"));
} else {
labelMeson= new TLatex(0.95,0.89,Form("#eta #rightarrow #pi^{+}#pi^{-}#pi^{0}"));
}
SetStyleTLatex( labelMeson, 0.038,4,1,42,kTRUE, 311);
labelMeson->SetTextAlign(31);
labelMeson->Draw();
TLatex *labelCentrality = new TLatex(0.95,0.93,Form("%s",collisionSystem.Data() ));
SetStyleTLatex( labelCentrality, 0.038,4,1,42,kTRUE, 11);
labelCentrality->SetTextAlign(31);
labelCentrality->Draw();
TLatex *labelRecoMethod = new TLatex(0.95,0.84,Form("%s",recoMethod.Data() ));
SetStyleTLatex( labelRecoMethod, 0.038,4,1,42,kTRUE, 11);
labelRecoMethod->SetTextAlign(31);
labelRecoMethod->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("Pi0")){
histo2DNewSysErrMean = new TH2D("histo2DNewSysErrMean", "", 20,0.,ptBins[nPtBins-1]+ptBinsErr[nPtBins-1],1000.,-0.5,45.);
} else if (meson.Contains("Eta") && (mode == 45)){
histo2DNewSysErrMean = new TH2D("histo2DNewSysErrMean", "", 20,0.,ptBins[nPtBins-1]+ptBinsErr[nPtBins-1],1000.,-0.5,65.);
} else {
histo2DNewSysErrMean = new TH2D("histo2DNewSysErrMean", "", 20,0.,ptBins[nPtBins-1]+ptBinsErr[nPtBins-1],1000.,-0.5,45.);
}
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);
if(meson.Contains("Eta")) legendMeanNew = GetAndSetLegend2(minXLegend-0.1,maxYLegend-heightLegend,minXLegend+widthLegend,maxYLegend, 30);
if (numberCutStudies> 7) legendMeanNew->SetNColumns(2);
if (numberCutStudies> 11) legendMeanNew->SetNColumns(3);
for(Int_t i = 0;i< numberCutStudies ;i++){
cout << i << "\t"<< additionalNameOutput.Data() << endl;
DrawGammaSetMarkerTGraphErr(meanErrorsCorr[i], markerStyle[i], 1.,color[i],color[i]);
meanErrorsCorr[i]->Draw("p,csame");
legendMeanNew->AddEntry(meanErrorsCorr[i],nameCutVariation[i].Data(),"p");
}
if (meson.CompareTo("EtaToPi0")){
DrawGammaSetMarkerTGraphErr(graphMaterialError, GetMarkerStyleSystematics( "Material"), 1., GetColorSystematics( "Material" ), GetColorSystematics( "Material"));
graphMaterialError->Draw("p,csame");
legendMeanNew->AddEntry(graphMaterialError,"Material","p");
}
DrawGammaSetMarkerTGraphErr(meanErrorsCorrSummedIncMat, 20, 1.,kBlack,kBlack);
meanErrorsCorrSummedIncMat->Draw("p,csame");
legendMeanNew->AddEntry(meanErrorsCorrSummedIncMat,"quad. sum.","p");
legendMeanNew->SetMargin(0.05);
legendMeanNew->Draw();
// labeling
labelMeson->Draw();
labelCentrality->Draw();
labelRecoMethod->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->GetYaxis()->SetRangeUser(0.,40.);
histo2DNewSysErrMean->Draw();
if (!showBeforeSmoothing) continue;
Double_t minPt = startPtSys;
Double_t maxPt = ptBins[nPtBins-1]+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);
bla->SetParameter(0,1.5);
bla->SetParameter(1,50);
bla->SetParameter(2,5);
pol4->SetParLimits(3,0,10);
Double_t fitminPt = minPt;
Double_t fitmaxPt = maxPt;
meanErrorsCorrBefore[cut]->Fit(pol4,"NRMEX0+","",fitminPt,fitmaxPt);
meanErrorsCorrBefore[cut]->Fit(pol2,"NRMEX0+","",fitminPt,fitmaxPt);
meanErrorsCorrBefore[cut]->Fit(pol1,"NRMEX0+","",fitminPt,fitmaxPt);
meanErrorsCorrBefore[cut]->Fit(pol0,"NRMEX0+","",fitminPt,fitmaxPt);
meanErrorsCorrBefore[cut]->Fit(bla,"NRMEX0+","",fitminPt,fitmaxPt);
cout << "The following functional forms can be used for smoothing of sys variation " << cut << endl;
cout << "blk (pol0):\t " << pol0->GetParameter(0) << endl;
cout << "cyan(pol1):\t " << pol1->GetParameter(0) << "+" << pol1->GetParameter(1) << "*ptBins[k]" << endl;
cout << "blue(pol2):\t " << pol2->GetParameter(0) << "+" << pol2->GetParameter(1) << "*ptBins[k]+" << pol2->GetParameter(2) << "*pow(ptBins[k],2)" << endl;
cout << "red (pol4):\t " << pol4->GetParameter(0) <<"+"<< pol4->GetParameter(1)<< "*ptBins[k]+"<< pol4->GetParameter(2)<< "*pow(ptBins[k],2)+"<< pol4->GetParameter(3)<< "*pow(ptBins[k],4)" << endl;
cout << "pink (pow):\t " << bla->GetParameter(0) << "+" << bla->GetParameter(1) << "/pow(" << bla->GetParameter(2) << ",ptBins[k])" << endl;
pol4->SetLineColor(kRed+2);
pol2->SetLineColor(kBlue+2);
pol1->SetLineColor(kCyan+2);
pol0->SetLineColor(kBlack);
bla->SetLineColor(kMagenta+2);
DrawGammaSetMarkerTGraphErr(meanErrorsCorrBefore[cut], 20+cut, 1.,kGray+1,kGray+1);
meanErrorsCorrBefore[cut]->Draw("p,csame");
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");
TLegend* legendMeanNewSingle = GetAndSetLegend2(minXLegend,maxYLegend-heightLegend,minXLegend+widthLegend,maxYLegend, 30);
legendMeanNewSingle->SetMargin(0.1);
legendMeanNewSingle->AddEntry(meanErrorsCorr[cut],nameCutVariation[cut].Data(),"p");
legendMeanNewSingle->Draw();
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/SystematicError%s_%s_%s%s_%s.dat",recoMethodForWriting.Data(),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/SystematicErrorAveraged%s_%s_%s%s_%s.dat",recoMethodForWriting.Data(), 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;
}
SysErrDatAver.close();
const char *SysErrDatnameMeanSingleErr = Form("SystematicErrorsCalculatedCalo/SystematicErrorAveragedSingle%s_%s_%s%s_%s.dat",recoMethodForWriting.Data(),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++){
if(!meson.CompareTo("EtaToPi0")&&i==1)
continue;
SysErrDatAverSingle << nameCutVariationSC[i] << "\t";
}
if(meson.CompareTo("EtaToPi0"))
SysErrDatAverSingle << "Material";
SysErrDatAverSingle << endl;