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FinaliseSystematicErrorsConvCalo_omega_pp.C
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FinaliseSystematicErrorsConvCalo_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 FinaliseSystematicErrorsConvCalo_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 = 41
){
// ***************************************************************************************************
// ****************************** General style settings *********************************************
// ***************************************************************************************************
StyleSettingsThesis();
SetPlotStyle();
// ***************************************************************************************************
// ****************************** Create output directory ********************************************
// ***************************************************************************************************
gSystem->Exec("mkdir -p SystematicErrorsCalculatedConvCalo");
// ***************************************************************************************************
// ***************************** 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[26];
TString nameCutVariationSCCurrent[26] = { "RemovePileUp", // 0
"Conversion_SinglePtCut", // 1
"Conversion_ClsTPCCut", // 2
"Conversion_TPCdEdxCutElectron", // 3
"Conversion_TPCdEdxCutPion", // 4
"Conversion_QtMaxCut", // 5
"Conversion_Chi2GammaCut", // 6
"Conversion_PsiPair", // 7
"Calo_NonLin", // 8
"Calo_Timing", // 9
"Calo_TrackMatching", // 10
"Calo_MinEnergy", // 11
"Calo_MinNCells", // 12
"Calo_MinMaxM02", // 13
"Calo_ClusterEnergyScale", // 14
"Clusterizer", // 15
"ChargedPion_ITSRequirement", // 16
"ChargedPion_ClsTPCCut", // 17
"ChargedPion_pTCut", // 18
"ChargedPion_TPCdEdxCutPion", // 19
"ChargedPion_MassCut", // 20
"NeutralPion_SelectionWindows", // 21
"Omega_BackgroundScheme", // 22
"Omega_RecoEfficiency", // 23
"Omega_BranchingRatio", // 24
"YieldExtraction"}; // 25
TString nameCutVariation[26] = {"pileup","conv. track p_{T}","conv. track N_{cls,TPC}","conv. electron PID","conv. pion rej.","conv. photon q_{T}","conv. photon #chi^{2}","conv. photon #psi_{pair}","cluster non-linearity","cluster timing","cluster trackmatching","cluster min. energy","cluster N_{cells,min}","cluster shape",
"cluster energy scale","clusterizer algorithm","charged pion N_{cls,ITS}","charged pion N_{cls,TPC}","charged pion min p_{T}","charged pion PID","M_{#pi^{+}#pi^{-}} cut"
,"M_{#gamma#gamma} cut","background description",
"reco. efficiency","branching ratio","yield extraction"};
Color_t color[30] = {kTeal+3,
kTeal-5,800,kBlue-7,kCyan+4,kSpring+2,kTeal-7,kAzure-5,kRed-2,
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
};
Color_t markerStyle[27]={25,
24,28,33,29,24,30,28,
27,26,28,30,31,33,23,
24,21,22,23,20,
26,26,27,
26,28,
30
};
// 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[26] = { 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0};
Bool_t bsmoothMBOmega07TeV[26] = { 1, // pileup
1, 1, 1, 1, 1, 1, 1, // conv. cuts
1, 1, 1, 1, 1, 1, 1, 1, // calo cuts
1, 1, 1, 1, 1, // charged pion cuts
1, // neutral pion cuts
1, 1, 1, // omega cuts
0}; // yield extraction
Bool_t bsmoothMBEta07TeV[26] = { 1, // pileup
1, 1, 1, 1, 1, 1, 1, // conv. cuts
1, 1, 1, 1, 1, 1, 1, 1, // calo cuts
1, 1, 1, 1, 1, // charged pion cuts
1, // neutral pion cuts
1, 1, 1, // omega cuts
0}; // yield extraction
if(mode==42) bsmoothMBEta07TeV[23] = 1; // smooth eta signal extraction for PCM-PHOS
Bool_t bsmoothMBOmegaToPi07TeV[24] = { 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0 , 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0};
// 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("Conversion_SinglePtCut")==0
|| nameCutVariationSC[i].CompareTo("Conversion_ClsTPCCut")==0
|| nameCutVariationSC[i].CompareTo("Conversion_TPCdEdxCutElectron")==0
|| nameCutVariationSC[i].CompareTo("Conversion_TPCdEdxCutPion")==0
|| nameCutVariationSC[i].CompareTo("Conversion_QtMaxCut")==0
|| nameCutVariationSC[i].CompareTo("Conversion_Chi2GammaCut")==0
|| nameCutVariationSC[i].CompareTo("Conversion_PsiPair")==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"))
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;
}
}
// min pt of conversion track
} else if (nameCutVariationSC[i].CompareTo("Conversion_SinglePtCut")==0 ){
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
//errorReset = 0.5;
Float_t pi0Pt = CalculatePi0Pt(ptBins[k]);
errorReset= 0.8+40/pow(100,pi0Pt); // parametrisation
}
if (ptBins[k] > minPt){
errorsMean[i][k] = errorReset;
errorsMeanErr[i][k] = errorReset*0.01;
errorsMeanCorr[i][k] = errorReset;
errorsMeanErrCorr[i][k] = errorReset*0.01;
}
}
// min cls in TPC for conversion track
} else if (nameCutVariationSC[i].CompareTo("Conversion_ClsTPCCut")==0 ){
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
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;
}
}
// PID cut for conversion electron
} else if (nameCutVariationSC[i].CompareTo("Conversion_TPCdEdxCutElectron")==0 ){
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
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;
}
}
// rejection of pions when looking at conversion tracks
} else if (nameCutVariationSC[i].CompareTo("Conversion_TPCdEdxCutPion")==0 ){
minPt = startPtSys;
if (!energy.CompareTo("7TeV"))
errorReset = 1.; //
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;
}
}
// conversion qt cut
} else if (nameCutVariationSC[i].CompareTo("Conversion_QtMaxCut")==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;
}
}
// conversion chi2 cut
} else if (nameCutVariationSC[i].CompareTo("Conversion_Chi2GammaCut")==0 ){
minPt =startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
errorReset = 2.5;
}
if (ptBins[k] > minPt){
errorsMean[i][k] = errorReset;
errorsMeanErr[i][k] = errorReset*0.01;
errorsMeanCorr[i][k] = errorReset;
errorsMeanErrCorr[i][k] = errorReset*0.01;
}
}
// conversion psipair
} else if (nameCutVariationSC[i].CompareTo("Conversion_PsiPair")==0 ){
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
errorReset = 2.5;
}
if (ptBins[k] > minPt){
errorsMean[i][k] = errorReset;
errorsMeanErr[i][k] = errorReset*0.01;
errorsMeanCorr[i][k] = errorReset;
errorsMeanErrCorr[i][k] = errorReset*0.01;
}
}
// calo photon nonlin
} else if (nameCutVariationSC[i].CompareTo("Calo_NonLin")==0 ){
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
errorReset = 1.5;
}
if (ptBins[k] > minPt){
errorsMean[i][k] = errorReset;
errorsMeanErr[i][k] = errorReset*0.01;
errorsMeanCorr[i][k] = errorReset;
errorsMeanErrCorr[i][k] = errorReset*0.01;
}
}
// 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 (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")){ // taken from pi0
errorReset = 1.0+40/pow(100,ptBins[k]);
if(ptBins[k]>=4) errorReset += 2E-3*(ptBins[k]-4)*(ptBins[k]-4)+0.2*(ptBins[k]-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;
}
}
// 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")){
errorReset = 1.5;
}
if (ptBins[k] > minPt){
errorsMean[i][k] = errorReset;
errorsMeanErr[i][k] = errorReset*0.01;
errorsMeanCorr[i][k] = errorReset;
errorsMeanErrCorr[i][k] = errorReset*0.01;
}
}
// 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 = 1.0;
}
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")){
Float_t pi0Pt = CalculatePi0Pt(ptBins[k]);
errorReset = 0.9;
if(pi0Pt>=5.) errorReset+= 0.15*(pi0Pt-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;
}
}
// calo photon cluster shape
} else if (nameCutVariationSC[i].CompareTo("Calo_ClusterEnergyScale")==0 ){
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
errorReset = 0.8; // 0.133%*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;
}
}
// all systematics related to clusterization algorithm -> 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(2.0,2)+pow(0.25,2)); //clusterization energy + cell timing
}
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_ITSRequirement")==0 ){
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
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;
}
}
// 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 (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 = 4.0;
}
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 = 10.0;
}
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 = 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;
}
}
// 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 (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.;
}
if (ptBins[k] > minPt){
errorsMean[i][k] = errorReset;
errorsMeanErr[i][k] = errorReset*0.01;
errorsMeanCorr[i][k] = errorReset;
errorsMeanErrCorr[i][k] = errorReset*0.01;
}
}
// 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;
}
}
// Yield Extraction
} else if (nameCutVariationSC[i].CompareTo("YieldExtraction")==0 ){
minPt = startPtSys;
for (Int_t k = 0; k < nPtBins; k++){
if (!energy.CompareTo("7TeV")){
errorReset = 20.; // used for eta PCM-PHOS
}
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] );
}
// inner material budget
Double_t errorInnerMaterial = 4.5;
// outer material budget from EMCal
Double_t errorOuterMaterial = 1.5;
//calculate sqrt of summed 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(errorInnerMaterial ,2.) + pow(errorOuterMaterial,2),0.5);
errorsMeanCorrMatSummed[l] = pow(errorsMeanCorrSummed[l]+ pow(errorInnerMaterial ,2.)+ pow(errorOuterMaterial,2),0.5);
errorsNegCorrMatSummed[l] = -pow(errorsNegCorrSummed[l]+ pow(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 = 0.75;
if (numberCutStudies> 20)
widthLegend = 0.5;
Double_t heightLegend = 1.05* 0.04 * (numberCutStudies+3);
if (numberCutStudies> 7)
heightLegend = 1.05* 0.03 * (numberCutStudies/2+1);
if (numberCutStudies> 20)
heightLegend = 1.05* 0.02 * (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], 1.,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("SystematicErrorsCalculatedConvCalo/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 == 42)){
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;
if(meson.Contains("Eta")){
legendMeanNew = GetAndSetLegend2(minXLegend-0.1,maxYLegend-heightLegend,minXLegend+(0.9*widthLegend),maxYLegend, 30);
if(mode==42) legendMeanNew = GetAndSetLegend2(minXLegend-0.1,maxYLegend-(0.9*heightLegend),minXLegend+(0.9*widthLegend),maxYLegend, 30);
} else{
legendMeanNew = GetAndSetLegend2(minXLegend,maxYLegend-heightLegend,minXLegend+widthLegend,maxYLegend, 30);
}
legendMeanNew->SetMargin(0.05);
if (numberCutStudies> 7) legendMeanNew->SetNColumns(2);
if (numberCutStudies> 11) legendMeanNew->SetNColumns(3);
if (numberCutStudies> 20) legendMeanNew->SetTextSize(20);
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("SystematicErrorsCalculatedConvCalo/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-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);
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;