/************************************************************************* * Copyright(c) 1998-2008, ALICE Experiment at CERN, All rights reserved. * * * * Author: The ALICE Off-line Project. * * Contributors are mentioned in the code where appropriate. * * * * Permission to use, copy, modify and distribute this software and its * * documentation strictly for non-commercial purposes is hereby granted * * without fee, provided that the above copyright notice appears in all * * copies and that both the copyright notice and this permission notice * * appear in the supporting documentation. The authors make no claims * * about the suitability of this software for any purpose. It is * * provided "as is" without express or implied warranty. * **************************************************************************/ /********************************** * flow analysis with Q-cumulants * * * * author: Ante Bilandzic * * (abilandzic@gmail.com) * *********************************/ #define AliFlowAnalysisWithQCumulants_cxx #include "Riostream.h" #include "AliFlowCommonConstants.h" #include "AliFlowCommonHist.h" #include "AliFlowCommonHistResults.h" #include "TChain.h" #include "TFile.h" #include "TList.h" #include "TGraph.h" #include "TParticle.h" #include "TRandom3.h" #include "TStyle.h" #include "TProfile.h" #include "TProfile2D.h" #include "TProfile3D.h" #include "TMath.h" #include "TArrow.h" #include "TPaveLabel.h" #include "TCanvas.h" #include "AliFlowEventSimple.h" #include "AliFlowTrackSimple.h" #include "AliFlowAnalysisWithQCumulants.h" #include "TArrayD.h" #include "TRandom.h" #include "TF1.h" class TH1; class TH2; class TGraph; class TPave; class TLatex; class TMarker; class TRandom3; class TObjArray; class TList; class TCanvas; class TSystem; class TROOT; class AliFlowVector; class TVector; //================================================================================================================ ClassImp(AliFlowAnalysisWithQCumulants) AliFlowAnalysisWithQCumulants::AliFlowAnalysisWithQCumulants(): // 0.) base: fHistList(NULL), // 1.) common: fCommonHists(NULL), fCommonHists2nd(NULL), fCommonHists4th(NULL), fCommonHists6th(NULL), fCommonHists8th(NULL), fCommonHistsResults2nd(NULL), fCommonHistsResults4th(NULL), fCommonHistsResults6th(NULL), fCommonHistsResults8th(NULL), fnBinsPhi(0), fPhiMin(0), fPhiMax(0), fPhiBinWidth(0), fnBinsPt(0), fPtMin(0), fPtMax(0), fPtBinWidth(0), fnBinsEta(0), fEtaMin(0), fEtaMax(0), fEtaBinWidth(0), fHarmonic(2), fAnalysisLabel(NULL), // 2a.) particle weights: fWeightsList(NULL), fUsePhiWeights(kFALSE), fUsePtWeights(kFALSE), fUseEtaWeights(kFALSE), fUseParticleWeights(NULL), fPhiWeights(NULL), fPtWeights(NULL), fEtaWeights(NULL), // 2b.) event weights: fMultiplicityWeight(NULL), // 3.) integrated flow: fIntFlowList(NULL), fIntFlowProfiles(NULL), fIntFlowResults(NULL), fIntFlowFlags(NULL), fApplyCorrectionForNUA(kTRUE), fApplyCorrectionForNUAVsM(kFALSE), fnBinsMult(10000), fMinMult(0.), fMaxMult(10000.), fPropagateErrorFromCorrelations(kFALSE), fCalculateCumulantsVsM(kTRUE), fMinimumBiasReferenceFlow(kTRUE), fReQ(NULL), fImQ(NULL), fSMpk(NULL), fIntFlowCorrelationsEBE(NULL), fIntFlowEventWeightsForCorrelationsEBE(NULL), fIntFlowCorrelationsAllEBE(NULL), fAvMultiplicity(NULL), fIntFlowCorrelationsPro(NULL), fIntFlowCorrelationsAllPro(NULL), fIntFlowExtraCorrelationsPro(NULL), fIntFlowProductOfCorrelationsPro(NULL), fIntFlowProductOfCorrectionTermsForNUAPro(NULL), fIntFlowCorrelationsHist(NULL), fIntFlowCorrelationsAllHist(NULL), fIntFlowCovariances(NULL), fIntFlowSumOfProductOfEventWeights(NULL), fIntFlowCovariancesNUA(NULL), fIntFlowSumOfProductOfEventWeightsNUA(NULL), fIntFlowQcumulants(NULL), fIntFlowQcumulantsRebinnedInM(NULL), fIntFlow(NULL), fIntFlowRebinnedInM(NULL), fIntFlowDetectorBias(NULL), // 4.) differential flow: fDiffFlowList(NULL), fDiffFlowProfiles(NULL), fDiffFlowResults(NULL), fDiffFlowFlags(NULL), fCalculate2DFlow(kFALSE), // 5.) distributions: fDistributionsList(NULL), fDistributionsFlags(NULL), fStoreDistributions(kFALSE), // x.) debugging and cross-checking: fNestedLoopsList(NULL), fEvaluateIntFlowNestedLoops(kFALSE), fEvaluateDiffFlowNestedLoops(kFALSE), fMaxAllowedMultiplicity(10), fEvaluateNestedLoops(NULL), fIntFlowDirectCorrelations(NULL), fIntFlowExtraDirectCorrelations(NULL), fCrossCheckInPtBinNo(10), fCrossCheckInEtaBinNo(20), fNoOfParticlesInBin(NULL) { // constructor // base list to hold all output objects: fHistList = new TList(); fHistList->SetName("cobjQC"); fHistList->SetOwner(kTRUE); // list to hold histograms with phi, pt and eta weights: fWeightsList = new TList(); // multiplicity weight: fMultiplicityWeight = new TString("combinations"); // analysis label; fAnalysisLabel = new TString(); // initialize all arrays: this->InitializeArraysForIntFlow(); this->InitializeArraysForDiffFlow(); this->InitializeArraysForDistributions(); this->InitializeArraysForNestedLoops(); } // end of constructor //================================================================================================================ AliFlowAnalysisWithQCumulants::~AliFlowAnalysisWithQCumulants() { // destructor delete fHistList; } // end of AliFlowAnalysisWithQCumulants::~AliFlowAnalysisWithQCumulants() //================================================================================================================ void AliFlowAnalysisWithQCumulants::Init() { // a) Cross check if the settings make sense before starting the QC adventure; // b) Access all common constants; // c) Book all objects; // d) Store flags for integrated and differential flow; // e) Store flags for distributions of corelations; // f) Store harmonic which will be estimated. //save old value and prevent histograms from being added to directory //to avoid name clashes in case multiple analaysis objects are used //in an analysis Bool_t oldHistAddStatus = TH1::AddDirectoryStatus(); TH1::AddDirectory(kFALSE); // a) Cross check if the settings make sense before starting the QC adventure; this->CrossCheckSettings(); // b) Access all common constants: this->AccessConstants(); // c) Book all objects: this->BookAndFillWeightsHistograms(); this->BookAndNestAllLists(); this->BookCommonHistograms(); this->BookEverythingForIntegratedFlow(); this->BookEverythingForDifferentialFlow(); this->BookEverythingForDistributions(); this->BookEverythingForNestedLoops(); // d) Store flags for integrated and differential flow: this->StoreIntFlowFlags(); this->StoreDiffFlowFlags(); // e) Store flags for distributions of corelations: this->StoreFlagsForDistributions(); // f) Store harmonic which will be estimated: this->StoreHarmonic(); TH1::AddDirectory(oldHistAddStatus); } // end of void AliFlowAnalysisWithQCumulants::Init() //================================================================================================================ void AliFlowAnalysisWithQCumulants::Make(AliFlowEventSimple* anEvent) { // Running over data only in this method. // a) Check all pointers used in this method; // b) Define local variables; // c) Fill the common control histograms and call the method to fill fAvMultiplicity; // d) Loop over data and calculate e-b-e quantities; // e) Call all the methods which calculate correlations for reference flow; // f) Call all the methods which calculate correlations for differential flow; // g) Distributions of correlations; // h) Debugging and cross-checking (evaluate nested loops); // i) Reset all event-by-event quantities. // a) Check all pointers used in this method: this->CheckPointersUsedInMake(); // b) Define local variables: Double_t dPhi = 0.; // azimuthal angle in the laboratory frame Double_t dPt = 0.; // transverse momentum Double_t dEta = 0.; // pseudorapidity Double_t wPhi = 1.; // phi weight Double_t wPt = 1.; // pt weight Double_t wEta = 1.; // eta weight Int_t nRP = anEvent->GetEventNSelTracksRP(); // number of RPs (i.e. number of particles used to determine the reaction plane) // c) Fill the common control histograms and call the method to fill fAvMultiplicity: this->FillCommonControlHistograms(anEvent); this->FillAverageMultiplicities(nRP); // d) Loop over data and calculate e-b-e quantities: Int_t nPrim = anEvent->NumberOfTracks(); // nPrim = total number of primary tracks, i.e. nPrim = nRP + nPOI where: // nRP = # of particles used to determine the reaction plane; // nPOI = # of particles of interest for a detailed flow analysis; AliFlowTrackSimple *aftsTrack = NULL; for(Int_t i=0;iGetTrack(i); if(aftsTrack) { if(!(aftsTrack->InRPSelection() || aftsTrack->InPOISelection())) continue; // consider only tracks which are RPs or POIs Int_t n = fHarmonic; // shortcut for the harmonic if(aftsTrack->InRPSelection()) // RP condition: { dPhi = aftsTrack->Phi(); dPt = aftsTrack->Pt(); dEta = aftsTrack->Eta(); if(fUsePhiWeights && fPhiWeights && fnBinsPhi) // determine phi weight for this particle: { wPhi = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(dPhi*fnBinsPhi/TMath::TwoPi()))); } if(fUsePtWeights && fPtWeights && fnBinsPt) // determine pt weight for this particle: { wPt = fPtWeights->GetBinContent(1+(Int_t)(TMath::Floor((dPt-fPtMin)/fPtBinWidth))); } if(fUseEtaWeights && fEtaWeights && fEtaBinWidth) // determine eta weight for this particle: { wEta = fEtaWeights->GetBinContent(1+(Int_t)(TMath::Floor((dEta-fEtaMin)/fEtaBinWidth))); } // integrated flow: // calculate Re[Q_{m*n,k}] and Im[Q_{m*n,k}], m = 1,2,3,4, for this event: for(Int_t m=0;m<4;m++) { for(Int_t k=0;k<9;k++) { (*fReQ)(m,k)+=pow(wPhi*wPt*wEta,k)*TMath::Cos((m+1)*n*dPhi); (*fImQ)(m,k)+=pow(wPhi*wPt*wEta,k)*TMath::Sin((m+1)*n*dPhi); } } // calculate S^{M}_{p,k} for this event // Remark: final calculation of S^{M}_{p,k} follows after the loop over data bellow: for(Int_t p=0;p<8;p++) { for(Int_t k=0;k<9;k++) { (*fSMpk)(p,k)+=pow(wPhi*wPt*wEta,k); } } // differential flow: // 1D (pt): // (r_{m*m,k}(pt)): for(Int_t m=0;m<4;m++) { for(Int_t k=0;k<9;k++) { fReRPQ1dEBE[0][0][m][k]->Fill(dPt,pow(wPhi*wPt*wEta,k)*TMath::Cos((m+1.)*n*dPhi),1.); fImRPQ1dEBE[0][0][m][k]->Fill(dPt,pow(wPhi*wPt*wEta,k)*TMath::Sin((m+1.)*n*dPhi),1.); } } // s_{k}(pt) for RPs // to be improved (clarified) // Remark: final calculation of s_{p,k}(pt) follows after the loop over data bellow: for(Int_t k=0;k<9;k++) { fs1dEBE[0][0][k]->Fill(dPt,pow(wPhi*wPt*wEta,k),1.); } // 1D (eta): // (r_{m*m,k}(eta)): for(Int_t m=0;m<4;m++) { for(Int_t k=0;k<9;k++) { fReRPQ1dEBE[0][1][m][k]->Fill(dEta,pow(wPhi*wPt*wEta,k)*TMath::Cos((m+1.)*n*dPhi),1.); fImRPQ1dEBE[0][1][m][k]->Fill(dEta,pow(wPhi*wPt*wEta,k)*TMath::Sin((m+1.)*n*dPhi),1.); } } // s_{k}(eta) for RPs // to be improved (clarified) // Remark: final calculation of s_{p,k}(eta) follows after the loop over data bellow: for(Int_t k=0;k<9;k++) { fs1dEBE[0][1][k]->Fill(dEta,pow(wPhi*wPt*wEta,k),1.); } /* // 2D (pt,eta): if(fCalculate2DFlow) { // (r_{m*m,k}(pt,eta)): for(Int_t m=0;m<4;m++) { for(Int_t k=0;k<9;k++) { fReRPQ2dEBE[0][m][k]->Fill(dPt,dEta,pow(wPhi*wPt*wEta,k)*TMath::Cos((m+1.)*n*dPhi),1.); fImRPQ2dEBE[0][m][k]->Fill(dPt,dEta,pow(wPhi*wPt*wEta,k)*TMath::Sin((m+1.)*n*dPhi),1.); } } // s_{k}(pt,eta) for RPs // to be improved (clarified) // Remark: final calculation of s_{p,k}(pt,eta) follows after the loop over data bellow: for(Int_t k=0;k<9;k++) { fs2dEBE[0][k]->Fill(dPt,dEta,pow(wPhi*wPt*wEta,k),1.); } } // end of if(fCalculate2DFlow) */ if(aftsTrack->InPOISelection()) { // 1D (pt): // (q_{m*m,k}(pt)): for(Int_t m=0;m<4;m++) { for(Int_t k=0;k<9;k++) { fReRPQ1dEBE[2][0][m][k]->Fill(dPt,pow(wPhi*wPt*wEta,k)*TMath::Cos((m+1.)*n*dPhi),1.); fImRPQ1dEBE[2][0][m][k]->Fill(dPt,pow(wPhi*wPt*wEta,k)*TMath::Sin((m+1.)*n*dPhi),1.); } } // s_{k}(pt) for RP&&POIs // to be improved (clarified) // Remark: final calculation of s_{p,k}(pt,eta) follows after the loop over data bellow: for(Int_t k=0;k<9;k++) { fs1dEBE[2][0][k]->Fill(dPt,pow(wPhi*wPt*wEta,k),1.); } // 1D (eta): // (q_{m*m,k}(eta)): for(Int_t m=0;m<4;m++) { for(Int_t k=0;k<9;k++) { fReRPQ1dEBE[2][1][m][k]->Fill(dEta,pow(wPhi*wPt*wEta,k)*TMath::Cos((m+1.)*n*dPhi),1.); fImRPQ1dEBE[2][1][m][k]->Fill(dEta,pow(wPhi*wPt*wEta,k)*TMath::Sin((m+1.)*n*dPhi),1.); } } // s_{k}(eta) for RP&&POIs // to be improved (clarified) // Remark: final calculation of s_{p,k}(pt,eta) follows after the loop over data bellow: for(Int_t k=0;k<9;k++) { fs1dEBE[2][1][k]->Fill(dEta,pow(wPhi*wPt*wEta,k),1.); } /* // 2D (pt,eta) if(fCalculate2DFlow) { // (q_{m*m,k}(pt,eta)): for(Int_t m=0;m<4;m++) { for(Int_t k=0;k<9;k++) { fReRPQ2dEBE[2][m][k]->Fill(dPt,dEta,pow(wPhi*wPt*wEta,k)*TMath::Cos((m+1.)*n*dPhi),1.); fImRPQ2dEBE[2][m][k]->Fill(dPt,dEta,pow(wPhi*wPt*wEta,k)*TMath::Sin((m+1.)*n*dPhi),1.); } } // s_{k}(pt,eta) for RP&&POIs // to be improved (clarified) // Remark: final calculation of s_{p,k}(pt,eta) follows after the loop over data bellow: for(Int_t k=0;k<9;k++) { fs2dEBE[2][k]->Fill(dPt,dEta,pow(wPhi*wPt*wEta,k),1.); } } // end of if(fCalculate2DFlow) */ } // end of if(aftsTrack->InPOISelection()) } // end of if(pTrack->InRPSelection()) if(aftsTrack->InPOISelection()) { dPhi = aftsTrack->Phi(); dPt = aftsTrack->Pt(); dEta = aftsTrack->Eta(); // 1D (pt) // p_n(m*n,0): for(Int_t m=0;m<4;m++) { fReRPQ1dEBE[1][0][m][0]->Fill(dPt,TMath::Cos((m+1.)*n*dPhi),1.); fImRPQ1dEBE[1][0][m][0]->Fill(dPt,TMath::Sin((m+1.)*n*dPhi),1.); } // 1D (eta) // p_n(m*n,0): for(Int_t m=0;m<4;m++) { fReRPQ1dEBE[1][1][m][0]->Fill(dEta,TMath::Cos((m+1.)*n*dPhi),1.); fImRPQ1dEBE[1][1][m][0]->Fill(dEta,TMath::Sin((m+1.)*n*dPhi),1.); } /* // 2D (pt,eta): if(fCalculate2DFlow) { // p_n(m*n,0): for(Int_t m=0;m<4;m++) { fReRPQ2dEBE[1][m][0]->Fill(dPt,dEta,TMath::Cos((m+1.)*n*dPhi),1.); fImRPQ2dEBE[1][m][0]->Fill(dPt,dEta,TMath::Sin((m+1.)*n*dPhi),1.); } } // end of if(fCalculate2DFlow) */ } // end of if(pTrack->InPOISelection() ) } else // to if(aftsTrack) { cout<1) this->CalculateIntFlowCorrelations(); // without using particle weights } else // to if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) { if(nRP>1) this->CalculateIntFlowCorrelationsUsingParticleWeights(); // with using particle weights } if(nRP>3) this->CalculateIntFlowProductOfCorrelations(); if(nRP>1) this->CalculateIntFlowSumOfEventWeights(); if(nRP>1) this->CalculateIntFlowSumOfProductOfEventWeights(); if(fApplyCorrectionForNUA) { if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) { if(nRP>0) this->CalculateIntFlowCorrectionsForNUASinTerms(); if(nRP>0) this->CalculateIntFlowCorrectionsForNUACosTerms(); } else // to if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) { if(nRP>0) this->CalculateIntFlowCorrectionsForNUASinTermsUsingParticleWeights(); if(nRP>0) this->CalculateIntFlowCorrectionsForNUACosTermsUsingParticleWeights(); } if(nRP>0) this->CalculateIntFlowProductOfCorrectionTermsForNUA(); if(nRP>0) this->CalculateIntFlowSumOfEventWeightsNUA(); if(nRP>0) this->CalculateIntFlowSumOfProductOfEventWeightsNUA(); } // end of if(fApplyCorrectionForNUA) } // end of if(!fEvaluateIntFlowNestedLoops) // f) Call all the methods which calculate correlations for differential flow: if(!fEvaluateDiffFlowNestedLoops) { if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) { // without using particle weights: this->CalculateDiffFlowCorrelations("RP","Pt"); this->CalculateDiffFlowCorrelations("RP","Eta"); this->CalculateDiffFlowCorrelations("POI","Pt"); this->CalculateDiffFlowCorrelations("POI","Eta"); if(fApplyCorrectionForNUA) { this->CalculateDiffFlowCorrectionsForNUASinTerms("RP","Pt"); this->CalculateDiffFlowCorrectionsForNUASinTerms("RP","Eta"); this->CalculateDiffFlowCorrectionsForNUASinTerms("POI","Pt"); this->CalculateDiffFlowCorrectionsForNUASinTerms("POI","Eta"); this->CalculateDiffFlowCorrectionsForNUACosTerms("RP","Pt"); this->CalculateDiffFlowCorrectionsForNUACosTerms("RP","Eta"); this->CalculateDiffFlowCorrectionsForNUACosTerms("POI","Pt"); this->CalculateDiffFlowCorrectionsForNUACosTerms("POI","Eta"); } // end of if(fApplyCorrectionForNUA) } else // to if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) { // with using particle weights: this->CalculateDiffFlowCorrelationsUsingParticleWeights("RP","Pt"); this->CalculateDiffFlowCorrelationsUsingParticleWeights("RP","Eta"); this->CalculateDiffFlowCorrelationsUsingParticleWeights("POI","Pt"); this->CalculateDiffFlowCorrelationsUsingParticleWeights("POI","Eta"); if(fApplyCorrectionForNUA) { this->CalculateDiffFlowCorrectionsForNUASinTermsUsingParticleWeights("RP","Pt"); this->CalculateDiffFlowCorrectionsForNUASinTermsUsingParticleWeights("RP","Eta"); this->CalculateDiffFlowCorrectionsForNUASinTermsUsingParticleWeights("POI","Pt"); this->CalculateDiffFlowCorrectionsForNUASinTermsUsingParticleWeights("POI","Eta"); this->CalculateDiffFlowCorrectionsForNUACosTermsUsingParticleWeights("RP","Pt"); this->CalculateDiffFlowCorrectionsForNUACosTermsUsingParticleWeights("RP","Eta"); this->CalculateDiffFlowCorrectionsForNUACosTermsUsingParticleWeights("POI","Pt"); this->CalculateDiffFlowCorrectionsForNUACosTermsUsingParticleWeights("POI","Eta"); } // end of if(fApplyCorrectionForNUA) } // whether or not using particle weights the following is calculated in the same way: this->CalculateDiffFlowProductOfCorrelations("RP","Pt"); this->CalculateDiffFlowProductOfCorrelations("RP","Eta"); this->CalculateDiffFlowProductOfCorrelations("POI","Pt"); this->CalculateDiffFlowProductOfCorrelations("POI","Eta"); this->CalculateDiffFlowSumOfEventWeights("RP","Pt"); this->CalculateDiffFlowSumOfEventWeights("RP","Eta"); this->CalculateDiffFlowSumOfEventWeights("POI","Pt"); this->CalculateDiffFlowSumOfEventWeights("POI","Eta"); this->CalculateDiffFlowSumOfProductOfEventWeights("RP","Pt"); this->CalculateDiffFlowSumOfProductOfEventWeights("RP","Eta"); this->CalculateDiffFlowSumOfProductOfEventWeights("POI","Pt"); this->CalculateDiffFlowSumOfProductOfEventWeights("POI","Eta"); } // end of if(!fEvaluateDiffFlowNestedLoops) // with weights: // ... /* // 2D differential flow if(fCalculate2DFlow) { // without weights: if(nRP>1) this->CalculateCorrelationsForDifferentialFlow2D("RP"); if(nRP>1) this->CalculateCorrelationsForDifferentialFlow2D("POI"); // with weights: if(fUsePhiWeights||fUsePtWeights||fUseEtaWeights) { if(nRP>1) this->CalculateWeightedCorrelationsForDifferentialFlow2D("RP"); if(nRP>1) this->CalculateWeightedCorrelationsForDifferentialFlow2D("POI"); } } // end of if(fCalculate2DFlow) */ // g) Distributions of correlations; if(fStoreDistributions) { this->StoreDistributionsOfCorrelations(); } // h) Debugging and cross-checking (evaluate nested loops): // h1) cross-checking results for integrated flow: if(fEvaluateIntFlowNestedLoops) { if(nPrim>0 && nPrim<=fMaxAllowedMultiplicity) // by default fMaxAllowedMultiplicity = 10 { // without using particle weights: if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) { // correlations: this->CalculateIntFlowCorrelations(); // from Q-vectors this->EvaluateIntFlowCorrelationsWithNestedLoops(anEvent); // from nested loops (to be improved: do I have to pass here anEvent or not?) // correction for non-uniform acceptance: this->CalculateIntFlowCorrectionsForNUASinTerms(); // from Q-vectors (sin terms) this->CalculateIntFlowCorrectionsForNUACosTerms(); // from Q-vectors (cos terms) this->EvaluateIntFlowCorrectionsForNUAWithNestedLoops(anEvent); // from nested loops (both sin and cos terms) } // using particle weights: if(fUsePhiWeights||fUsePtWeights||fUseEtaWeights) { // correlations: this->CalculateIntFlowCorrelationsUsingParticleWeights(); // from Q-vectors this->EvaluateIntFlowCorrelationsWithNestedLoopsUsingParticleWeights(anEvent); // from nested loops (to be improved: do I have to pass here anEvent or not?) // correction for non-uniform acceptance: this->CalculateIntFlowCorrectionsForNUASinTermsUsingParticleWeights(); // from Q-vectors (sin terms) this->CalculateIntFlowCorrectionsForNUACosTermsUsingParticleWeights(); // from Q-vectors (cos terms) this->EvaluateIntFlowCorrectionsForNUAWithNestedLoopsUsingParticleWeights(anEvent); // from nested loops (both sin and cos terms) } } else if (nPrim>fMaxAllowedMultiplicity) // to if(nPrim>0 && nPrim<=fMaxAllowedMultiplicity) { cout<0 && nPrim<=fMaxAllowedMultiplicity) // by default fMaxAllowedMultiplicity = 10 { // without using particle weights: if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) { // reduced correlations: // Q-vectors: this->CalculateDiffFlowCorrelations("RP","Pt"); this->CalculateDiffFlowCorrelations("RP","Eta"); this->CalculateDiffFlowCorrelations("POI","Pt"); this->CalculateDiffFlowCorrelations("POI","Eta"); // nested loops: this->EvaluateDiffFlowCorrelationsWithNestedLoops(anEvent,"RP","Pt"); this->EvaluateDiffFlowCorrelationsWithNestedLoops(anEvent,"RP","Eta"); this->EvaluateDiffFlowCorrelationsWithNestedLoops(anEvent,"POI","Pt"); this->EvaluateDiffFlowCorrelationsWithNestedLoops(anEvent,"POI","Eta"); // reduced corrections for non-uniform acceptance: // Q-vectors: this->CalculateDiffFlowCorrectionsForNUASinTerms("RP","Pt"); this->CalculateDiffFlowCorrectionsForNUASinTerms("RP","Eta"); this->CalculateDiffFlowCorrectionsForNUASinTerms("POI","Pt"); this->CalculateDiffFlowCorrectionsForNUASinTerms("POI","Eta"); this->CalculateDiffFlowCorrectionsForNUACosTerms("RP","Pt"); this->CalculateDiffFlowCorrectionsForNUACosTerms("RP","Eta"); this->CalculateDiffFlowCorrectionsForNUACosTerms("POI","Pt"); this->CalculateDiffFlowCorrectionsForNUACosTerms("POI","Eta"); // nested loops: this->EvaluateDiffFlowCorrectionTermsForNUAWithNestedLoops(anEvent,"RP","Pt"); this->EvaluateDiffFlowCorrectionTermsForNUAWithNestedLoops(anEvent,"RP","Eta"); this->EvaluateDiffFlowCorrectionTermsForNUAWithNestedLoops(anEvent,"POI","Pt"); this->EvaluateDiffFlowCorrectionTermsForNUAWithNestedLoops(anEvent,"POI","Eta"); } // end of if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) // using particle weights: if(fUsePhiWeights||fUsePtWeights||fUseEtaWeights) { this->CalculateDiffFlowCorrelationsUsingParticleWeights("RP","Pt"); this->CalculateDiffFlowCorrelationsUsingParticleWeights("RP","Eta"); this->CalculateDiffFlowCorrelationsUsingParticleWeights("POI","Pt"); this->CalculateDiffFlowCorrelationsUsingParticleWeights("POI","Eta"); this->CalculateDiffFlowCorrectionsForNUASinTermsUsingParticleWeights("RP","Pt"); this->CalculateDiffFlowCorrectionsForNUASinTermsUsingParticleWeights("RP","Eta"); this->CalculateDiffFlowCorrectionsForNUASinTermsUsingParticleWeights("POI","Pt"); this->CalculateDiffFlowCorrectionsForNUASinTermsUsingParticleWeights("POI","Eta"); this->CalculateDiffFlowCorrectionsForNUACosTermsUsingParticleWeights("RP","Pt"); this->CalculateDiffFlowCorrectionsForNUACosTermsUsingParticleWeights("RP","Eta"); this->CalculateDiffFlowCorrectionsForNUACosTermsUsingParticleWeights("POI","Pt"); this->CalculateDiffFlowCorrectionsForNUACosTermsUsingParticleWeights("POI","Eta"); this->EvaluateDiffFlowCorrelationsWithNestedLoopsUsingParticleWeights(anEvent,"RP","Pt"); this->EvaluateDiffFlowCorrelationsWithNestedLoopsUsingParticleWeights(anEvent,"RP","Eta"); this->EvaluateDiffFlowCorrelationsWithNestedLoopsUsingParticleWeights(anEvent,"POI","Pt"); this->EvaluateDiffFlowCorrelationsWithNestedLoopsUsingParticleWeights(anEvent,"POI","Eta"); this->EvaluateDiffFlowCorrectionTermsForNUAWithNestedLoopsUsingParticleWeights(anEvent,"RP","Pt"); this->EvaluateDiffFlowCorrectionTermsForNUAWithNestedLoopsUsingParticleWeights(anEvent,"RP","Eta"); this->EvaluateDiffFlowCorrectionTermsForNUAWithNestedLoopsUsingParticleWeights(anEvent,"POI","Pt"); this->EvaluateDiffFlowCorrectionTermsForNUAWithNestedLoopsUsingParticleWeights(anEvent,"POI","Eta"); } // end of if(fUsePhiWeights||fUsePtWeights||fUseEtaWeights) } // end of if(nPrim>0 && nPrim<=fMaxAllowedMultiplicity) // by default fMaxAllowedMultiplicity = 10 } // end of if(fEvaluateDiffFlowNestedLoops) // i) Reset all event-by-event quantities. this->ResetEventByEventQuantities(); } // end of AliFlowAnalysisWithQCumulants::Make(AliFlowEventSimple* anEvent) //================================================================================================================================ void AliFlowAnalysisWithQCumulants::Finish() { // Calculate the final results. // a) Check all pointers used in this method; // b) Acces the constants; // c) Access the flags; // d) Calculate the final results for reference flow (without/with weights); // e) Correct the results for reference flow (without/with weights) for effects of non-uniform acceptance (NUA); // f) Store results for reference flow in AliFlowCommonHistResults and print them on the screen; // g) Calculate the final results for differential flow (without/with weights); // h) Correct the results for differential flow (without/with weights) for effects of non-uniform acceptance (NUA); // i) Calculate the final results for integrated flow (RP/POI) and store in AliFlowCommonHistResults; // j) Store results for differential flow in AliFlowCommonHistResults; // k) Print the final results for integrated flow (RP/POI) on the screen; // l) Cross-checking: Results from Q-vectors vs results from nested loops. // a) Check all pointers used in this method: this->CheckPointersUsedInFinish(); // b) Acces the constants: this->AccessConstants(); if(fCommonHists && fCommonHists->GetHarmonic()) // to be improved (moved somewhere else) { fHarmonic = (Int_t)(fCommonHists->GetHarmonic())->GetBinContent(1); } // c) Access the flags: // to be improved (implement a method for this) fUsePhiWeights = (Bool_t)fUseParticleWeights->GetBinContent(1); fUsePtWeights = (Bool_t)fUseParticleWeights->GetBinContent(2); fUseEtaWeights = (Bool_t)fUseParticleWeights->GetBinContent(3); fApplyCorrectionForNUA = (Bool_t)fIntFlowFlags->GetBinContent(3); fPrintFinalResults[0] = (Bool_t)fIntFlowFlags->GetBinContent(4); fPrintFinalResults[1] = (Bool_t)fIntFlowFlags->GetBinContent(5); fPrintFinalResults[2] = (Bool_t)fIntFlowFlags->GetBinContent(6); fPrintFinalResults[3] = (Bool_t)fIntFlowFlags->GetBinContent(7); fApplyCorrectionForNUAVsM = (Bool_t)fIntFlowFlags->GetBinContent(8); fPropagateErrorFromCorrelations = (Bool_t)fIntFlowFlags->GetBinContent(9); fCalculateCumulantsVsM = (Bool_t)fIntFlowFlags->GetBinContent(10); fMinimumBiasReferenceFlow = (Bool_t)fIntFlowFlags->GetBinContent(11); fEvaluateIntFlowNestedLoops = (Bool_t)fEvaluateNestedLoops->GetBinContent(1); fEvaluateDiffFlowNestedLoops = (Bool_t)fEvaluateNestedLoops->GetBinContent(2); fCrossCheckInPtBinNo = (Int_t)fEvaluateNestedLoops->GetBinContent(3); fCrossCheckInEtaBinNo = (Int_t)fEvaluateNestedLoops->GetBinContent(4); // d) Calculate the final results for reference flow (without/with weights): this->FinalizeCorrelationsIntFlow(); this->CalculateCovariancesIntFlow(); this->CalculateCumulantsIntFlow(); this->CalculateIntFlow(); // e) Correct the results for reference flow (without/with weights) for effects of non-uniform acceptance (NUA): if(fApplyCorrectionForNUA) { this->FinalizeCorrectionTermsForNUAIntFlow(); // this->CalculateCovariancesNUAIntFlow(); // to be improved (enabled eventually) this->CalculateQcumulantsCorrectedForNUAIntFlow(); this->CalculateIntFlowCorrectedForNUA(); this->CalculateDetectorEffectsForTrueCorrelations(); } // f) Store results for reference flow in AliFlowCommonHistResults and print them on the screen: this->FillCommonHistResultsIntFlow(); if(fPrintFinalResults[0]){this->PrintFinalResultsForIntegratedFlow("RF");} if(fPrintFinalResults[3] && fCalculateCumulantsVsM){this->PrintFinalResultsForIntegratedFlow("RF, rebinned in M");} // g) Calculate the final results for differential flow (without/with weights): this->FinalizeReducedCorrelations("RP","Pt"); this->FinalizeReducedCorrelations("RP","Eta"); this->FinalizeReducedCorrelations("POI","Pt"); this->FinalizeReducedCorrelations("POI","Eta"); this->CalculateDiffFlowCovariances("RP","Pt"); this->CalculateDiffFlowCovariances("RP","Eta"); this->CalculateDiffFlowCovariances("POI","Pt"); this->CalculateDiffFlowCovariances("POI","Eta"); this->CalculateDiffFlowCumulants("RP","Pt"); this->CalculateDiffFlowCumulants("RP","Eta"); this->CalculateDiffFlowCumulants("POI","Pt"); this->CalculateDiffFlowCumulants("POI","Eta"); this->CalculateDiffFlow("RP","Pt"); this->CalculateDiffFlow("RP","Eta"); this->CalculateDiffFlow("POI","Pt"); this->CalculateDiffFlow("POI","Eta"); // h) Correct the results for differential flow (without/with weights) for effects of non-uniform acceptance (NUA): if(fApplyCorrectionForNUA) { this->FinalizeCorrectionTermsForNUADiffFlow("RP","Pt"); this->FinalizeCorrectionTermsForNUADiffFlow("RP","Eta"); this->FinalizeCorrectionTermsForNUADiffFlow("POI","Pt"); this->FinalizeCorrectionTermsForNUADiffFlow("POI","Eta"); this->CalculateDiffFlowCumulantsCorrectedForNUA("RP","Pt"); this->CalculateDiffFlowCumulantsCorrectedForNUA("RP","Eta"); this->CalculateDiffFlowCumulantsCorrectedForNUA("POI","Pt"); this->CalculateDiffFlowCumulantsCorrectedForNUA("POI","Eta"); this->CalculateDiffFlowCorrectedForNUA("RP","Pt"); this->CalculateDiffFlowCorrectedForNUA("RP","Eta"); this->CalculateDiffFlowCorrectedForNUA("POI","Pt"); this->CalculateDiffFlowCorrectedForNUA("POI","Eta"); } // i) Calculate the final results for integrated flow (RP/POI) and store in AliFlowCommonHistResults: this->CalculateFinalResultsForRPandPOIIntegratedFlow("RP"); this->CalculateFinalResultsForRPandPOIIntegratedFlow("POI"); // j) Store results for differential flow in AliFlowCommonHistResults: this->FillCommonHistResultsDiffFlow("RP"); this->FillCommonHistResultsDiffFlow("POI"); // k) Print the final results for integrated flow (RP/POI) on the screen: if(fPrintFinalResults[1]){this->PrintFinalResultsForIntegratedFlow("RP");} if(fPrintFinalResults[2]){this->PrintFinalResultsForIntegratedFlow("POI");} // l) Cross-checking: Results from Q-vectors vs results from nested loops: // l1) Reference flow: if(fEvaluateIntFlowNestedLoops) { this->CrossCheckIntFlowCorrelations(); this->CrossCheckIntFlowCorrectionTermsForNUA(); if(fUsePhiWeights||fUsePtWeights||fUseEtaWeights) this->CrossCheckIntFlowExtraCorrelations(); } // end of if(fEvaluateIntFlowNestedLoops) // l2) Differential flow: if(fEvaluateDiffFlowNestedLoops) { // Correlations: this->PrintNumberOfParticlesInSelectedBin(); this->CrossCheckDiffFlowCorrelations("RP","Pt"); this->CrossCheckDiffFlowCorrelations("RP","Eta"); this->CrossCheckDiffFlowCorrelations("POI","Pt"); this->CrossCheckDiffFlowCorrelations("POI","Eta"); // Correction terms for non-uniform acceptance: this->CrossCheckDiffFlowCorrectionTermsForNUA("RP","Pt"); this->CrossCheckDiffFlowCorrectionTermsForNUA("RP","Eta"); this->CrossCheckDiffFlowCorrectionTermsForNUA("POI","Pt"); this->CrossCheckDiffFlowCorrectionTermsForNUA("POI","Eta"); } // end of if(fEvaluateDiffFlowNestedLoops) } // end of AliFlowAnalysisWithQCumulants::Finish() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CalculateIntFlowCorrectionsForNUACosTerms() { // calculate corrections for non-uniform acceptance of the detector for no-name integrated flow (cos terms) // multiplicity: Double_t dMult = (*fSMpk)(0,0); // real and imaginary parts of non-weighted Q-vectors evaluated in harmonics n, 2n, 3n and 4n: Double_t dReQ1n = (*fReQ)(0,0); Double_t dReQ2n = (*fReQ)(1,0); //Double_t dReQ3n = (*fReQ)(2,0); //Double_t dReQ4n = (*fReQ)(3,0); Double_t dImQ1n = (*fImQ)(0,0); Double_t dImQ2n = (*fImQ)(1,0); //Double_t dImQ3n = (*fImQ)(2,0); //Double_t dImQ4n = (*fImQ)(3,0); // ************************************************************* // **** corrections for non-uniform acceptance (cos terms): **** // ************************************************************* // // Remark 1: corrections for non-uniform acceptance (cos terms) calculated with non-weighted Q-vectors // are stored in 1D profile fQCorrectionsCos. // Remark 2: binning of fIntFlowCorrectionTermsForNUAPro[1] is organized as follows: // -------------------------------------------------------------------------------------------------------------------- // 1st bin: <> = cosP1n // 2nd bin: <> = cosP1nP1n // 3rd bin: <> = cosP1nM1nM1n // 4th bin: <> = cosP2nM1n // -------------------------------------------------------------------------------------------------------------------- // 1-particle: Double_t cosP1n = 0.; // <> if(dMult>0) { cosP1n = dReQ1n/dMult; // average non-weighted 1-particle correction (cos terms) for non-uniform acceptance for single event: fIntFlowCorrectionTermsForNUAEBE[1]->SetBinContent(1,cosP1n); // event weights for NUA terms: fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->SetBinContent(1,dMult); // final average non-weighted 1-particle correction (cos terms) for non-uniform acceptance for all events: fIntFlowCorrectionTermsForNUAPro[1]->Fill(0.5,cosP1n,dMult); if(fCalculateCumulantsVsM){fIntFlowCorrectionTermsForNUAVsMPro[1][0]->Fill(dMult+0.5,cosP1n,dMult);} } // 2-particle: Double_t cosP1nP1n = 0.; // <> Double_t cosP2nM1n = 0.; // <> if(dMult>1) { cosP1nP1n = (pow(dReQ1n,2)-pow(dImQ1n,2)-dReQ2n)/(dMult*(dMult-1)); cosP2nM1n = (dReQ2n*dReQ1n+dImQ2n*dImQ1n-dReQ1n)/(dMult*(dMult-1)); // average non-weighted 2-particle correction (cos terms) for non-uniform acceptance for single event: fIntFlowCorrectionTermsForNUAEBE[1]->SetBinContent(2,cosP1nP1n); fIntFlowCorrectionTermsForNUAEBE[1]->SetBinContent(4,cosP2nM1n); // event weights for NUA terms: fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->SetBinContent(2,dMult*(dMult-1)); fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->SetBinContent(4,dMult*(dMult-1)); // final average non-weighted 2-particle correction (cos terms) for non-uniform acceptance for all events: fIntFlowCorrectionTermsForNUAPro[1]->Fill(1.5,cosP1nP1n,dMult*(dMult-1)); fIntFlowCorrectionTermsForNUAPro[1]->Fill(3.5,cosP2nM1n,dMult*(dMult-1)); if(fCalculateCumulantsVsM) { fIntFlowCorrectionTermsForNUAVsMPro[1][1]->Fill(dMult+0.5,cosP1nP1n,dMult*(dMult-1)); fIntFlowCorrectionTermsForNUAVsMPro[1][3]->Fill(dMult+0.5,cosP2nM1n,dMult*(dMult-1)); } } // 3-particle: Double_t cosP1nM1nM1n = 0.; // <> if(dMult>2) { cosP1nM1nM1n = (dReQ1n*(pow(dReQ1n,2)+pow(dImQ1n,2))-dReQ1n*dReQ2n-dImQ1n*dImQ2n-2.*(dMult-1)*dReQ1n) / (dMult*(dMult-1)*(dMult-2)); // average non-weighted 3-particle correction (cos terms) for non-uniform acceptance for single event: fIntFlowCorrectionTermsForNUAEBE[1]->SetBinContent(3,cosP1nM1nM1n); // event weights for NUA terms: fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->SetBinContent(3,dMult*(dMult-1)*(dMult-2)); // final average non-weighted 3-particle correction (cos terms) for non-uniform acceptance for all events: fIntFlowCorrectionTermsForNUAPro[1]->Fill(2.5,cosP1nM1nM1n,dMult*(dMult-1)*(dMult-2)); if(fCalculateCumulantsVsM){fIntFlowCorrectionTermsForNUAVsMPro[1][2]->Fill(dMult+0.5,cosP1nM1nM1n,dMult*(dMult-1)*(dMult-2));} } } // end of AliFlowAnalysisWithQCumulants::CalculateIntFlowCorrectionsForNUACosTerms() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CalculateIntFlowCorrectionsForNUASinTerms() { // calculate corrections for non-uniform acceptance of the detector for no-name integrated flow (sin terms) // multiplicity: Double_t dMult = (*fSMpk)(0,0); // real and imaginary parts of non-weighted Q-vectors evaluated in harmonics n, 2n, 3n and 4n: Double_t dReQ1n = (*fReQ)(0,0); Double_t dReQ2n = (*fReQ)(1,0); //Double_t dReQ3n = (*fReQ)(2,0); //Double_t dReQ4n = (*fReQ)(3,0); Double_t dImQ1n = (*fImQ)(0,0); Double_t dImQ2n = (*fImQ)(1,0); //Double_t dImQ3n = (*fImQ)(2,0); //Double_t dImQ4n = (*fImQ)(3,0); // ************************************************************* // **** corrections for non-uniform acceptance (sin terms): **** // ************************************************************* // // Remark 1: corrections for non-uniform acceptance (sin terms) calculated with non-weighted Q-vectors // are stored in 1D profile fQCorrectionsSin. // Remark 2: binning of fIntFlowCorrectionTermsForNUAPro[0] is organized as follows: // -------------------------------------------------------------------------------------------------------------------- // 1st bin: <> = sinP1n // 2nd bin: <> = sinP1nP1n // 3rd bin: <> = sinP1nM1nM1n // 4th bin: <> = sinP2nM1n // -------------------------------------------------------------------------------------------------------------------- // 1-particle: Double_t sinP1n = 0.; // if(dMult>0) { sinP1n = dImQ1n/dMult; // average non-weighted 1-particle correction (sin terms) for non-uniform acceptance for single event: fIntFlowCorrectionTermsForNUAEBE[0]->SetBinContent(1,sinP1n); // event weights for NUA terms: fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->SetBinContent(1,dMult); // final average non-weighted 1-particle correction (sin terms) for non-uniform acceptance for all events: fIntFlowCorrectionTermsForNUAPro[0]->Fill(0.5,sinP1n,dMult); if(fCalculateCumulantsVsM){fIntFlowCorrectionTermsForNUAVsMPro[0][0]->Fill(dMult+0.5,sinP1n,dMult);} } // 2-particle: Double_t sinP1nP1n = 0.; // <> Double_t sinP2nM1n = 0.; // <> if(dMult>1) { sinP1nP1n = (2.*dReQ1n*dImQ1n-dImQ2n)/(dMult*(dMult-1)); sinP2nM1n = (dImQ2n*dReQ1n-dReQ2n*dImQ1n-dImQ1n)/(dMult*(dMult-1)); // average non-weighted 2-particle correction (sin terms) for non-uniform acceptance for single event: fIntFlowCorrectionTermsForNUAEBE[0]->SetBinContent(2,sinP1nP1n); fIntFlowCorrectionTermsForNUAEBE[0]->SetBinContent(4,sinP2nM1n); // event weights for NUA terms: fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->SetBinContent(2,dMult*(dMult-1)); fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->SetBinContent(4,dMult*(dMult-1)); // final average non-weighted 1-particle correction (sin terms) for non-uniform acceptance for all events: fIntFlowCorrectionTermsForNUAPro[0]->Fill(1.5,sinP1nP1n,dMult*(dMult-1)); fIntFlowCorrectionTermsForNUAPro[0]->Fill(3.5,sinP2nM1n,dMult*(dMult-1)); if(fCalculateCumulantsVsM) { fIntFlowCorrectionTermsForNUAVsMPro[0][1]->Fill(dMult+0.5,sinP1nP1n,dMult*(dMult-1)); fIntFlowCorrectionTermsForNUAVsMPro[0][3]->Fill(dMult+0.5,sinP2nM1n,dMult*(dMult-1)); } } // 3-particle: Double_t sinP1nM1nM1n = 0.; // <> if(dMult>2) { sinP1nM1nM1n = (-dImQ1n*(pow(dReQ1n,2)+pow(dImQ1n,2))+dReQ1n*dImQ2n-dImQ1n*dReQ2n+2.*(dMult-1)*dImQ1n) / (dMult*(dMult-1)*(dMult-2)); // average non-weighted 3-particle correction (sin terms) for non-uniform acceptance for single event: fIntFlowCorrectionTermsForNUAEBE[0]->SetBinContent(3,sinP1nM1nM1n); // event weights for NUA terms: fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->SetBinContent(3,dMult*(dMult-1)*(dMult-2)); // final average non-weighted 3-particle correction (sin terms) for non-uniform acceptance for all events: fIntFlowCorrectionTermsForNUAPro[0]->Fill(2.5,sinP1nM1nM1n,dMult*(dMult-1)*(dMult-2)); if(fCalculateCumulantsVsM){fIntFlowCorrectionTermsForNUAVsMPro[0][2]->Fill(dMult+0.5,sinP1nM1nM1n,dMult*(dMult-1)*(dMult-2));} } } // end of AliFlowAnalysisWithQCumulants::CalculateIntFlowCorrectionsForNUASinTerms() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::GetOutputHistograms(TList *outputListHistos) { // a) Get pointers for common control and common result histograms and profiles. // b) Get pointers for histograms with particle weights. // c) Get pointers for histograms and profiles relevant for integrated flow. // d) Get pointers for histograms and profiles relevant for differental flow. // e) Get pointers for histograms and profiles holding results obtained with nested loops. if(outputListHistos) { this->SetHistList(outputListHistos); if(!fHistList) { cout<GetPointersForCommonHistograms(); this->GetPointersForParticleWeightsHistograms(); this->GetPointersForIntFlowHistograms(); this->GetPointersForDiffFlowHistograms(); this->GetPointersForNestedLoopsHistograms(); } else { cout<GetNbinsX(); Double_t dPtMin = (profilePtEta->GetXaxis())->GetXmin(); Double_t dPtMax = (profilePtEta->GetXaxis())->GetXmax(); Int_t nBinsEta = profilePtEta->GetNbinsY(); TProfile *profilePt = new TProfile("","",nBinsPt,dPtMin,dPtMax); for(Int_t p=1;p<=nBinsPt;p++) { Double_t contentPt = 0.; Double_t entryPt = 0.; Double_t spreadPt = 0.; Double_t sum1 = 0.; Double_t sum2 = 0.; Double_t sum3 = 0.; for(Int_t e=1;e<=nBinsEta;e++) { contentPt += (profilePtEta->GetBinContent(profilePtEta->GetBin(p,e))) * (profilePtEta->GetBinEntries(profilePtEta->GetBin(p,e))); entryPt += (profilePtEta->GetBinEntries(profilePtEta->GetBin(p,e))); sum1 += (profilePtEta->GetBinEntries(profilePtEta->GetBin(p,e))) * (pow(profilePtEta->GetBinError(profilePtEta->GetBin(p,e)),2.) + pow(profilePtEta->GetBinContent(profilePtEta->GetBin(p,e)),2.)); sum2 += (profilePtEta->GetBinEntries(profilePtEta->GetBin(p,e))); sum3 += (profilePtEta->GetBinEntries(profilePtEta->GetBin(p,e))) * (profilePtEta->GetBinContent(profilePtEta->GetBin(p,e))); } if(sum2>0. && sum1/sum2-pow(sum3/sum2,2.) > 0.) { spreadPt = pow(sum1/sum2-pow(sum3/sum2,2.),0.5); } profilePt->SetBinContent(p,contentPt); profilePt->SetBinEntries(p,entryPt); { profilePt->SetBinError(p,spreadPt); } } return profilePt; } // end of TProfile* AliFlowAnalysisWithQCumulants::MakePtProjection(TProfile2D *profilePtEta) //================================================================================================================================ TProfile* AliFlowAnalysisWithQCumulants::MakeEtaProjection(TProfile2D *profilePtEta) const { // project 2D profile onto eta axis to get 1D profile Int_t nBinsEta = profilePtEta->GetNbinsY(); Double_t dEtaMin = (profilePtEta->GetYaxis())->GetXmin(); Double_t dEtaMax = (profilePtEta->GetYaxis())->GetXmax(); Int_t nBinsPt = profilePtEta->GetNbinsX(); TProfile *profileEta = new TProfile("","",nBinsEta,dEtaMin,dEtaMax); for(Int_t e=1;e<=nBinsEta;e++) { Double_t contentEta = 0.; Double_t entryEta = 0.; for(Int_t p=1;p<=nBinsPt;p++) { contentEta += (profilePtEta->GetBinContent(profilePtEta->GetBin(p,e))) * (profilePtEta->GetBinEntries(profilePtEta->GetBin(p,e))); entryEta += (profilePtEta->GetBinEntries(profilePtEta->GetBin(p,e))); } profileEta->SetBinContent(e,contentEta); profileEta->SetBinEntries(e,entryEta); } return profileEta; } // end of TProfile* AliFlowAnalysisWithQCumulants::MakeEtaProjection(TProfile2D *profilePtEta) //================================================================================================================================ void AliFlowAnalysisWithQCumulants::PrintFinalResultsForIntegratedFlow(TString type) { // Printing on the screen the final results for integrated flow (RF, POI and RP). Int_t n = fHarmonic; Double_t dVn[4] = {0.}; // array to hold Vn{2}, Vn{4}, Vn{6} and Vn{8} Double_t dVnErr[4] = {0.}; // array to hold errors of Vn{2}, Vn{4}, Vn{6} and Vn{8} if(type == "RF") { for(Int_t b=0;b<4;b++) { dVn[b] = fIntFlow->GetBinContent(b+1); dVnErr[b] = fIntFlow->GetBinError(b+1); } } else if(type == "RP") { dVn[0] = (fCommonHistsResults2nd->GetHistIntFlowRP())->GetBinContent(1); dVnErr[0] = (fCommonHistsResults2nd->GetHistIntFlowRP())->GetBinError(1); dVn[1] = (fCommonHistsResults4th->GetHistIntFlowRP())->GetBinContent(1); dVnErr[1] = (fCommonHistsResults4th->GetHistIntFlowRP())->GetBinError(1); dVn[2] = (fCommonHistsResults6th->GetHistIntFlowRP())->GetBinContent(1); dVnErr[2] = (fCommonHistsResults6th->GetHistIntFlowRP())->GetBinError(1); dVn[3] = (fCommonHistsResults8th->GetHistIntFlowRP())->GetBinContent(1); dVnErr[3] = (fCommonHistsResults8th->GetHistIntFlowRP())->GetBinError(1); } else if(type == "POI") { dVn[0] = (fCommonHistsResults2nd->GetHistIntFlowPOI())->GetBinContent(1); dVnErr[0] = (fCommonHistsResults2nd->GetHistIntFlowPOI())->GetBinError(1); dVn[1] = (fCommonHistsResults4th->GetHistIntFlowPOI())->GetBinContent(1); dVnErr[1] = (fCommonHistsResults4th->GetHistIntFlowPOI())->GetBinError(1); dVn[2] = (fCommonHistsResults6th->GetHistIntFlowPOI())->GetBinContent(1); dVnErr[2] = (fCommonHistsResults6th->GetHistIntFlowPOI())->GetBinError(1); dVn[3] = (fCommonHistsResults8th->GetHistIntFlowPOI())->GetBinContent(1); dVnErr[3] = (fCommonHistsResults8th->GetHistIntFlowPOI())->GetBinError(1); } else if(type == "RF, rebinned in M") { for(Int_t b=0;b<4;b++) { dVn[b] = fIntFlowRebinnedInM->GetBinContent(b+1); dVnErr[b] = fIntFlowRebinnedInM->GetBinError(b+1); } } TString title = " flow estimates from Q-cumulants"; TString subtitle = " ("; TString subtitle2 = " (rebinned in M)"; if(type != "RF, rebinned in M") { if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) { subtitle.Append(type); subtitle.Append(", without weights)"); } else { subtitle.Append(type); subtitle.Append(", with weights)"); } } else { if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) { subtitle.Append("RF"); subtitle.Append(", without weights)"); } else { subtitle.Append("RF"); subtitle.Append(", with weights)"); } } cout< = "<<(Double_t)fCommonHists->GetHistMultRP()->GetMean()< = "<<(Double_t)fCommonHists->GetHistMultRP()->GetMean()< = "<<(Double_t)fCommonHists->GetHistMultPOI()->GetMean()<WriteObject(fHistList, "cobjQC","SingleKey"); fHistList->Write(fHistList->GetName(), TObject::kSingleKey); delete output; } //================================================================================================================================ void AliFlowAnalysisWithQCumulants::WriteHistograms(TDirectoryFile *outputFileName) { //store the final results in output .root file fHistList->SetName("cobjQC"); fHistList->SetOwner(kTRUE); outputFileName->Add(fHistList); outputFileName->Write(outputFileName->GetName(), TObject::kSingleKey); } //================================================================================================================================ void AliFlowAnalysisWithQCumulants::BookCommonHistograms() { // Book common control histograms and common histograms for final results. // common control histogram (ALL events) TString commonHistsName = "AliFlowCommonHistQC"; commonHistsName += fAnalysisLabel->Data(); fCommonHists = new AliFlowCommonHist(commonHistsName.Data()); fHistList->Add(fCommonHists); // common control histogram (for events with 2 and more particles) TString commonHists2ndOrderName = "AliFlowCommonHist2ndOrderQC"; commonHists2ndOrderName += fAnalysisLabel->Data(); fCommonHists2nd = new AliFlowCommonHist(commonHists2ndOrderName.Data()); fHistList->Add(fCommonHists2nd); // common control histogram (for events with 4 and more particles) TString commonHists4thOrderName = "AliFlowCommonHist4thOrderQC"; commonHists4thOrderName += fAnalysisLabel->Data(); fCommonHists4th = new AliFlowCommonHist(commonHists4thOrderName.Data()); fHistList->Add(fCommonHists4th); // common control histogram (for events with 6 and more particles) TString commonHists6thOrderName = "AliFlowCommonHist6thOrderQC"; commonHists6thOrderName += fAnalysisLabel->Data(); fCommonHists6th = new AliFlowCommonHist(commonHists6thOrderName.Data()); fHistList->Add(fCommonHists6th); // common control histogram (for events with 8 and more particles) TString commonHists8thOrderName = "AliFlowCommonHist8thOrderQC"; commonHists8thOrderName += fAnalysisLabel->Data(); fCommonHists8th = new AliFlowCommonHist(commonHists8thOrderName.Data()); fHistList->Add(fCommonHists8th); // common histograms for final results (calculated for events with 2 and more particles) TString commonHistResults2ndOrderName = "AliFlowCommonHistResults2ndOrderQC"; commonHistResults2ndOrderName += fAnalysisLabel->Data(); fCommonHistsResults2nd = new AliFlowCommonHistResults(commonHistResults2ndOrderName.Data()); fHistList->Add(fCommonHistsResults2nd); // common histograms for final results (calculated for events with 4 and more particles) TString commonHistResults4thOrderName = "AliFlowCommonHistResults4thOrderQC"; commonHistResults4thOrderName += fAnalysisLabel->Data(); fCommonHistsResults4th = new AliFlowCommonHistResults(commonHistResults4thOrderName.Data()); fHistList->Add(fCommonHistsResults4th); // common histograms for final results (calculated for events with 6 and more particles) TString commonHistResults6thOrderName = "AliFlowCommonHistResults6thOrderQC"; commonHistResults6thOrderName += fAnalysisLabel->Data(); fCommonHistsResults6th = new AliFlowCommonHistResults(commonHistResults6thOrderName.Data()); fHistList->Add(fCommonHistsResults6th); // common histograms for final results (calculated for events with 8 and more particles) TString commonHistResults8thOrderName = "AliFlowCommonHistResults8thOrderQC"; commonHistResults8thOrderName += fAnalysisLabel->Data(); fCommonHistsResults8th = new AliFlowCommonHistResults(commonHistResults8thOrderName.Data()); fHistList->Add(fCommonHistsResults8th); } // end of void AliFlowAnalysisWithQCumulants::BookCommonHistograms() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::BookAndFillWeightsHistograms() { // book and fill histograms which hold phi, pt and eta weights if(!fWeightsList) { cout<<"WARNING: fWeightsList is NULL in AFAWQC::BAFWH() !!!!"<Data(); fUseParticleWeights = new TProfile(fUseParticleWeightsName.Data(),"0 = particle weight not used, 1 = particle weight used ",3,0,3); fUseParticleWeights->SetLabelSize(0.06); (fUseParticleWeights->GetXaxis())->SetBinLabel(1,"w_{#phi}"); (fUseParticleWeights->GetXaxis())->SetBinLabel(2,"w_{p_{T}}"); (fUseParticleWeights->GetXaxis())->SetBinLabel(3,"w_{#eta}"); fUseParticleWeights->Fill(0.5,(Int_t)fUsePhiWeights); fUseParticleWeights->Fill(1.5,(Int_t)fUsePtWeights); fUseParticleWeights->Fill(2.5,(Int_t)fUseEtaWeights); fWeightsList->Add(fUseParticleWeights); if(fUsePhiWeights) { if(fWeightsList->FindObject("phi_weights")) { fPhiWeights = dynamic_cast(fWeightsList->FindObject("phi_weights")); if(TMath::Abs(fPhiWeights->GetBinWidth(1)-fPhiBinWidth)>pow(10.,-6.)) { cout<FindObject(\"phi_weights\") is NULL in AFAWQC::BAFWH() !!!!"<FindObject("pt_weights")) { fPtWeights = dynamic_cast(fWeightsList->FindObject("pt_weights")); if(TMath::Abs(fPtWeights->GetBinWidth(1)-fPtBinWidth)>pow(10.,-6.)) { cout<FindObject(\"pt_weights\") is NULL in AFAWQC::BAFWH() !!!!"<FindObject("eta_weights")) { fEtaWeights = dynamic_cast(fWeightsList->FindObject("eta_weights")); if(TMath::Abs(fEtaWeights->GetBinWidth(1)-fEtaBinWidth)>pow(10.,-6.)) { cout<FindObject(\"eta_weights\") is NULL in AFAWQC::BAFWH() !!!!"<Data(); fIntFlowFlags = new TProfile(intFlowFlagsName.Data(),"Flags for Integrated Flow",11,0,11); fIntFlowFlags->SetTickLength(-0.01,"Y"); fIntFlowFlags->SetMarkerStyle(25); fIntFlowFlags->SetLabelSize(0.05); fIntFlowFlags->SetLabelOffset(0.02,"Y"); fIntFlowFlags->GetXaxis()->SetBinLabel(1,"Particle Weights"); fIntFlowFlags->GetXaxis()->SetBinLabel(2,"Event Weights"); fIntFlowFlags->GetXaxis()->SetBinLabel(3,"Corrected for NUA?"); fIntFlowFlags->GetXaxis()->SetBinLabel(4,"Print RF results"); fIntFlowFlags->GetXaxis()->SetBinLabel(5,"Print RP results"); fIntFlowFlags->GetXaxis()->SetBinLabel(6,"Print POI results"); fIntFlowFlags->GetXaxis()->SetBinLabel(7,"Print RF (rebinned in M) results"); fIntFlowFlags->GetXaxis()->SetBinLabel(8,"Corrected for NUA vs M?"); fIntFlowFlags->GetXaxis()->SetBinLabel(9,"Propagate errors to v_{n} from correlations?"); fIntFlowFlags->GetXaxis()->SetBinLabel(10,"Calculate cumulants vs M"); fIntFlowFlags->GetXaxis()->SetBinLabel(11,"fMinimumBiasReferenceFlow"); fIntFlowList->Add(fIntFlowFlags); // b) Book event-by-event quantities: // Re[Q_{m*n,k}], Im[Q_{m*n,k}] and S_{p,k}^M: fReQ = new TMatrixD(4,9); fImQ = new TMatrixD(4,9); fSMpk = new TMatrixD(8,9); // average correlations <2>, <4>, <6> and <8> for single event (bining is the same as in fIntFlowCorrelationsPro and fIntFlowCorrelationsHist): TString intFlowCorrelationsEBEName = "fIntFlowCorrelationsEBE"; intFlowCorrelationsEBEName += fAnalysisLabel->Data(); fIntFlowCorrelationsEBE = new TH1D(intFlowCorrelationsEBEName.Data(),intFlowCorrelationsEBEName.Data(),4,0,4); // weights for average correlations <2>, <4>, <6> and <8> for single event: TString intFlowEventWeightsForCorrelationsEBEName = "fIntFlowEventWeightsForCorrelationsEBE"; intFlowEventWeightsForCorrelationsEBEName += fAnalysisLabel->Data(); fIntFlowEventWeightsForCorrelationsEBE = new TH1D(intFlowEventWeightsForCorrelationsEBEName.Data(),intFlowEventWeightsForCorrelationsEBEName.Data(),4,0,4); // average all correlations for single event (bining is the same as in fIntFlowCorrelationsAllPro and fIntFlowCorrelationsAllHist): TString intFlowCorrelationsAllEBEName = "fIntFlowCorrelationsAllEBE"; intFlowCorrelationsAllEBEName += fAnalysisLabel->Data(); fIntFlowCorrelationsAllEBE = new TH1D(intFlowCorrelationsAllEBEName.Data(),intFlowCorrelationsAllEBEName.Data(),32,0,32); // average correction terms for non-uniform acceptance for single event // (binning is the same as in fIntFlowCorrectionTermsForNUAPro[2] and fIntFlowCorrectionTermsForNUAHist[2]): TString fIntFlowCorrectionTermsForNUAEBEName = "fIntFlowCorrectionTermsForNUAEBE"; fIntFlowCorrectionTermsForNUAEBEName += fAnalysisLabel->Data(); for(Int_t sc=0;sc<2;sc++) // sin or cos terms { fIntFlowCorrectionTermsForNUAEBE[sc] = new TH1D(Form("%s: %s terms",fIntFlowCorrectionTermsForNUAEBEName.Data(),sinCosFlag[sc].Data()),Form("Correction terms for non-uniform acceptance (%s terms)",sinCosFlag[sc].Data()),10,0,10); } // event weights for terms for non-uniform acceptance: TString fIntFlowEventWeightForCorrectionTermsForNUAEBEName = "fIntFlowEventWeightForCorrectionTermsForNUAEBE"; fIntFlowEventWeightForCorrectionTermsForNUAEBEName += fAnalysisLabel->Data(); for(Int_t sc=0;sc<2;sc++) // sin or cos terms { fIntFlowEventWeightForCorrectionTermsForNUAEBE[sc] = new TH1D(Form("%s: %s terms",fIntFlowEventWeightForCorrectionTermsForNUAEBEName.Data(),sinCosFlag[sc].Data()),Form("Event weights for terms for non-uniform acceptance (%s terms)",sinCosFlag[sc].Data()),10,0,10); } // c) Book profiles: // to be improved (comment) // profile to hold average multiplicities and number of events for events with nRP>=0, nRP>=1, ... , and nRP>=8: TString avMultiplicityName = "fAvMultiplicity"; avMultiplicityName += fAnalysisLabel->Data(); fAvMultiplicity = new TProfile(avMultiplicityName.Data(),"Average Multiplicities of RPs",9,0,9); fAvMultiplicity->SetTickLength(-0.01,"Y"); fAvMultiplicity->SetMarkerStyle(25); fAvMultiplicity->SetLabelSize(0.05); fAvMultiplicity->SetLabelOffset(0.02,"Y"); fAvMultiplicity->SetYTitle("Average Multiplicity"); (fAvMultiplicity->GetXaxis())->SetBinLabel(1,"all evts"); (fAvMultiplicity->GetXaxis())->SetBinLabel(2,"n_{RP} #geq 1"); (fAvMultiplicity->GetXaxis())->SetBinLabel(3,"n_{RP} #geq 2"); (fAvMultiplicity->GetXaxis())->SetBinLabel(4,"n_{RP} #geq 3"); (fAvMultiplicity->GetXaxis())->SetBinLabel(5,"n_{RP} #geq 4"); (fAvMultiplicity->GetXaxis())->SetBinLabel(6,"n_{RP} #geq 5"); (fAvMultiplicity->GetXaxis())->SetBinLabel(7,"n_{RP} #geq 6"); (fAvMultiplicity->GetXaxis())->SetBinLabel(8,"n_{RP} #geq 7"); (fAvMultiplicity->GetXaxis())->SetBinLabel(9,"n_{RP} #geq 8"); fIntFlowProfiles->Add(fAvMultiplicity); // average correlations <<2>>, <<4>>, <<6>> and <<8>> for all events (with wrong errors!): TString correlationFlag[4] = {"<<2>>","<<4>>","<<6>>","<<8>>"}; TString intFlowCorrelationsProName = "fIntFlowCorrelationsPro"; intFlowCorrelationsProName += fAnalysisLabel->Data(); fIntFlowCorrelationsPro = new TProfile(intFlowCorrelationsProName.Data(),"Average correlations for all events",4,0,4,"s"); fIntFlowCorrelationsPro->SetTickLength(-0.01,"Y"); fIntFlowCorrelationsPro->SetMarkerStyle(25); fIntFlowCorrelationsPro->SetLabelSize(0.06); fIntFlowCorrelationsPro->SetLabelOffset(0.01,"Y"); for(Int_t b=0;b<4;b++) { (fIntFlowCorrelationsPro->GetXaxis())->SetBinLabel(b+1,correlationFlag[b].Data()); } fIntFlowProfiles->Add(fIntFlowCorrelationsPro); // average correlations <<2>>, <<4>>, <<6>> and <<8>> versus multiplicity for all events (with wrong errors): if(fCalculateCumulantsVsM) { for(Int_t ci=0;ci<4;ci++) // correlation index { TString intFlowCorrelationsVsMProName = "fIntFlowCorrelationsVsMPro"; intFlowCorrelationsVsMProName += fAnalysisLabel->Data(); fIntFlowCorrelationsVsMPro[ci] = new TProfile(Form("%s, %s",intFlowCorrelationsVsMProName.Data(),correlationFlag[ci].Data()), Form("%s vs multiplicity",correlationFlag[ci].Data()), fnBinsMult,fMinMult,fMaxMult,"s"); fIntFlowCorrelationsVsMPro[ci]->GetYaxis()->SetTitle(correlationFlag[ci].Data()); fIntFlowCorrelationsVsMPro[ci]->GetXaxis()->SetTitle("M"); fIntFlowProfiles->Add(fIntFlowCorrelationsVsMPro[ci]); } // end of for(Int_t ci=0;ci<4;ci++) // correlation index } // end of if(fCalculateCumulantsVsM) // averaged all correlations for all events (with wrong errors!): TString intFlowCorrelationsAllProName = "fIntFlowCorrelationsAllPro"; intFlowCorrelationsAllProName += fAnalysisLabel->Data(); fIntFlowCorrelationsAllPro = new TProfile(intFlowCorrelationsAllProName.Data(),"Average correlations for all events",32,0,32,"s"); fIntFlowCorrelationsAllPro->SetTickLength(-0.01,"Y"); fIntFlowCorrelationsAllPro->SetMarkerStyle(25); fIntFlowCorrelationsAllPro->SetLabelSize(0.03); fIntFlowCorrelationsAllPro->SetLabelOffset(0.01,"Y"); // 2-p correlations: (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(1,"<<2>>_{n|n}"); (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(2,"<<2>>_{2n|2n}"); (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(3,"<<2>>_{3n|3n}"); (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(4,"<<2>>_{4n|4n}"); // 3-p correlations: (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(6,"<<3>>_{2n|n,n}"); (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(7,"<<3>>_{3n|2n,n}"); (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(8,"<<3>>_{4n|2n,2n}"); (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(9,"<<3>>_{4n|3n,n}"); // 4-p correlations: (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(11,"<<4>>_{n,n|n,n}"); (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(12,"<<4>>_{2n,n|2n,n}"); (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(13,"<<4>>_{2n,2n|2n,2n}"); (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(14,"<<4>>_{3n|n,n,n}"); (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(15,"<<4>>_{3n,n|3n,n}"); (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(16,"<<4>>_{3n,n|2n,2n}"); (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(17,"<<4>>_{4n|2n,n,n}"); // 5-p correlations: (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(19,"<<5>>_{2n|n,n,n,n}"); (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(20,"<<5>>_{2n,2n|2n,n,n}"); (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(21,"<<5>>_{3n,n|2n,n,n}"); (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(22,"<<5>>_{4n|n,n,n,n}"); // 6-p correlations: (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(24,"<<6>>_{n,n,n|n,n,n}"); (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(25,"<<6>>_{2n,n,n|2n,n,n}"); (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(26,"<<6>>_{2n,2n|n,n,n,n}"); (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(27,"<<6>>_{3n,n|n,n,n,n}"); // 7-p correlations: (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(29,"<<7>>_{2n,n,n|n,n,n,n}"); // 8-p correlations: (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(31,"<<8>>_{n,n,n,n|n,n,n,n}"); fIntFlowProfiles->Add(fIntFlowCorrelationsAllPro); // when particle weights are used some extra correlations appear: if(fUsePhiWeights||fUsePtWeights||fUseEtaWeights) { TString intFlowExtraCorrelationsProName = "fIntFlowExtraCorrelationsPro"; intFlowExtraCorrelationsProName += fAnalysisLabel->Data(); fIntFlowExtraCorrelationsPro = new TProfile(intFlowExtraCorrelationsProName.Data(),"Average extra correlations for all events",100,0,100,"s"); fIntFlowExtraCorrelationsPro->SetTickLength(-0.01,"Y"); fIntFlowExtraCorrelationsPro->SetMarkerStyle(25); fIntFlowExtraCorrelationsPro->SetLabelSize(0.03); fIntFlowExtraCorrelationsPro->SetLabelOffset(0.01,"Y"); // extra 2-p correlations: (fIntFlowExtraCorrelationsPro->GetXaxis())->SetBinLabel(1,"<>"); (fIntFlowExtraCorrelationsPro->GetXaxis())->SetBinLabel(2,"<>"); fIntFlowProfiles->Add(fIntFlowExtraCorrelationsPro); } // end of if(fUsePhiWeights||fUsePtWeights||fUseEtaWeights) // average product of correlations <2>, <4>, <6> and <8>: TString productFlag[6] = {"<<2><4>>","<<2><6>>","<<2><8>>","<<4><6>>","<<4><8>>","<<6><8>>"}; TString intFlowProductOfCorrelationsProName = "fIntFlowProductOfCorrelationsPro"; intFlowProductOfCorrelationsProName += fAnalysisLabel->Data(); fIntFlowProductOfCorrelationsPro = new TProfile(intFlowProductOfCorrelationsProName.Data(),"Average products of correlations",6,0,6); fIntFlowProductOfCorrelationsPro->SetTickLength(-0.01,"Y"); fIntFlowProductOfCorrelationsPro->SetMarkerStyle(25); fIntFlowProductOfCorrelationsPro->SetLabelSize(0.05); fIntFlowProductOfCorrelationsPro->SetLabelOffset(0.01,"Y"); for(Int_t b=0;b<6;b++) { (fIntFlowProductOfCorrelationsPro->GetXaxis())->SetBinLabel(b+1,productFlag[b].Data()); } fIntFlowProfiles->Add(fIntFlowProductOfCorrelationsPro); // average product of correlations <2>, <4>, <6> and <8> versus multiplicity // [0=<<2><4>>,1=<<2><6>>,2=<<2><8>>,3=<<4><6>>,4=<<4><8>>,5=<<6><8>>] if(fCalculateCumulantsVsM) { TString intFlowProductOfCorrelationsVsMProName = "fIntFlowProductOfCorrelationsVsMPro"; intFlowProductOfCorrelationsVsMProName += fAnalysisLabel->Data(); for(Int_t pi=0;pi<6;pi++) { fIntFlowProductOfCorrelationsVsMPro[pi] = new TProfile(Form("%s, %s",intFlowProductOfCorrelationsVsMProName.Data(),productFlag[pi].Data()), Form("%s versus multiplicity",productFlag[pi].Data()), fnBinsMult,fMinMult,fMaxMult); fIntFlowProductOfCorrelationsVsMPro[pi]->GetXaxis()->SetTitle("M"); fIntFlowProfiles->Add(fIntFlowProductOfCorrelationsVsMPro[pi]); } // end of for(Int_t pi=0;pi<6;pi++) } // end of if(fCalculateCumulantsVsM) // average product of correction terms for NUA: TString intFlowProductOfCorrectionTermsForNUAProName = "fIntFlowProductOfCorrectionTermsForNUAPro"; intFlowProductOfCorrectionTermsForNUAProName += fAnalysisLabel->Data(); fIntFlowProductOfCorrectionTermsForNUAPro = new TProfile(intFlowProductOfCorrectionTermsForNUAProName.Data(),"Average products of correction terms for NUA",27,0,27); fIntFlowProductOfCorrectionTermsForNUAPro->SetTickLength(-0.01,"Y"); fIntFlowProductOfCorrectionTermsForNUAPro->SetMarkerStyle(25); fIntFlowProductOfCorrectionTermsForNUAPro->SetLabelSize(0.05); fIntFlowProductOfCorrectionTermsForNUAPro->SetLabelOffset(0.01,"Y"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(1,"<<2>>"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(2,"<<2>>"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(3,"<>"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(4,"Cov(<2>,)"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(5,"Cov(<2>,)"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(6,"Cov(<2>,)"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(7,"Cov(<2>,)"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(8,"Cov(<4>,)"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(9,"Cov(<4>,)"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(10,"Cov(<4>,)"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(11,"Cov(<4>,)"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(12,"Cov(<4>,>)"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(13,"Cov(<4>,>)"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(14,"Cov(,)"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(15,"Cov(,)"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(16,"Cov(,)"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(17,"Cov(,)"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(18,"Cov(,)"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(19,"Cov(,)"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(20,"Cov(,)"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(21,"Cov(,)"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(22,"Cov(,)"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(23,"Cov(,)"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(24,"Cov(,)"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(25,"Cov(,)"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(26,"Cov(,)"); (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(27,"Cov(,)"); fIntFlowProfiles->Add(fIntFlowProductOfCorrectionTermsForNUAPro); // average correction terms for non-uniform acceptance (with wrong errors!): for(Int_t sc=0;sc<2;sc++) // sin or cos terms { TString intFlowCorrectionTermsForNUAProName = "fIntFlowCorrectionTermsForNUAPro"; intFlowCorrectionTermsForNUAProName += fAnalysisLabel->Data(); fIntFlowCorrectionTermsForNUAPro[sc] = new TProfile(Form("%s: %s terms",intFlowCorrectionTermsForNUAProName.Data(),sinCosFlag[sc].Data()),Form("Correction terms for non-uniform acceptance (%s terms)",sinCosFlag[sc].Data()),10,0,10,"s"); fIntFlowCorrectionTermsForNUAPro[sc]->SetTickLength(-0.01,"Y"); fIntFlowCorrectionTermsForNUAPro[sc]->SetMarkerStyle(25); fIntFlowCorrectionTermsForNUAPro[sc]->SetLabelSize(0.03); fIntFlowCorrectionTermsForNUAPro[sc]->SetLabelOffset(0.01,"Y"); (fIntFlowCorrectionTermsForNUAPro[sc]->GetXaxis())->SetBinLabel(1,Form("<<%s(n(phi1))>>",sinCosFlag[sc].Data())); (fIntFlowCorrectionTermsForNUAPro[sc]->GetXaxis())->SetBinLabel(2,Form("<<%s(n(phi1+phi2))>>",sinCosFlag[sc].Data())); (fIntFlowCorrectionTermsForNUAPro[sc]->GetXaxis())->SetBinLabel(3,Form("<<%s(n(phi1-phi2-phi3))>>",sinCosFlag[sc].Data())); (fIntFlowCorrectionTermsForNUAPro[sc]->GetXaxis())->SetBinLabel(4,Form("<<%s(n(2phi1-phi2))>>",sinCosFlag[sc].Data())); fIntFlowProfiles->Add(fIntFlowCorrectionTermsForNUAPro[sc]); // versus multiplicity: if(fCalculateCumulantsVsM) { TString correctionTermFlag[4] = {"(n(phi1))","(n(phi1+phi2))","(n(phi1-phi2-phi3))","(n(2phi1-phi2))"}; // to be improved - hardwired 4 for(Int_t ci=0;ci<4;ci++) // correction term index (to be improved - hardwired 4) { TString intFlowCorrectionTermsForNUAVsMProName = "fIntFlowCorrectionTermsForNUAVsMPro"; intFlowCorrectionTermsForNUAVsMProName += fAnalysisLabel->Data(); fIntFlowCorrectionTermsForNUAVsMPro[sc][ci] = new TProfile(Form("%s: #LT#LT%s%s#GT#GT",intFlowCorrectionTermsForNUAVsMProName.Data(),sinCosFlag[sc].Data(),correctionTermFlag[ci].Data()),Form("#LT#LT%s%s#GT#GT vs M",sinCosFlag[sc].Data(),correctionTermFlag[ci].Data()),fnBinsMult,fMinMult,fMaxMult,"s"); fIntFlowProfiles->Add(fIntFlowCorrectionTermsForNUAVsMPro[sc][ci]); } } // end of if(fCalculateCumulantsVsM) } // end of for(Int_t sc=0;sc<2;sc++) // d) Book histograms holding the final results: // average correlations <<2>>, <<4>>, <<6>> and <<8>> for all events (with correct errors!): TString intFlowCorrelationsHistName = "fIntFlowCorrelationsHist"; intFlowCorrelationsHistName += fAnalysisLabel->Data(); fIntFlowCorrelationsHist = new TH1D(intFlowCorrelationsHistName.Data(),"Average correlations for all events",4,0,4); fIntFlowCorrelationsHist->SetTickLength(-0.01,"Y"); fIntFlowCorrelationsHist->SetMarkerStyle(25); fIntFlowCorrelationsHist->SetLabelSize(0.06); fIntFlowCorrelationsHist->SetLabelOffset(0.01,"Y"); (fIntFlowCorrelationsHist->GetXaxis())->SetBinLabel(1,"<<2>>"); (fIntFlowCorrelationsHist->GetXaxis())->SetBinLabel(2,"<<4>>"); (fIntFlowCorrelationsHist->GetXaxis())->SetBinLabel(3,"<<6>>"); (fIntFlowCorrelationsHist->GetXaxis())->SetBinLabel(4,"<<8>>"); fIntFlowResults->Add(fIntFlowCorrelationsHist); // average correlations <<2>>, <<4>>, <<6>> and <<8>> for all events (with correct errors!) vs M: if(fCalculateCumulantsVsM) { for(Int_t ci=0;ci<4;ci++) // correlation index { TString intFlowCorrelationsVsMHistName = "fIntFlowCorrelationsVsMHist"; intFlowCorrelationsVsMHistName += fAnalysisLabel->Data(); fIntFlowCorrelationsVsMHist[ci] = new TH1D(Form("%s, %s",intFlowCorrelationsVsMHistName.Data(),correlationFlag[ci].Data()), Form("%s vs multiplicity",correlationFlag[ci].Data()), fnBinsMult,fMinMult,fMaxMult); fIntFlowCorrelationsVsMHist[ci]->GetYaxis()->SetTitle(correlationFlag[ci].Data()); fIntFlowCorrelationsVsMHist[ci]->GetXaxis()->SetTitle("M"); fIntFlowResults->Add(fIntFlowCorrelationsVsMHist[ci]); } // end of for(Int_t ci=0;ci<4;ci++) // correlation index } // end of if(fCalculateCumulantsVsM) // average all correlations for all events (with correct errors!): TString intFlowCorrelationsAllHistName = "fIntFlowCorrelationsAllHist"; intFlowCorrelationsAllHistName += fAnalysisLabel->Data(); fIntFlowCorrelationsAllHist = new TH1D(intFlowCorrelationsAllHistName.Data(),"Average correlations for all events",32,0,32); fIntFlowCorrelationsAllHist->SetTickLength(-0.01,"Y"); fIntFlowCorrelationsAllHist->SetMarkerStyle(25); fIntFlowCorrelationsAllHist->SetLabelSize(0.03); fIntFlowCorrelationsAllHist->SetLabelOffset(0.01,"Y"); // 2-p correlations: (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(1,"<<2>>_{n|n}"); (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(2,"<<2>>_{2n|2n}"); (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(3,"<<2>>_{3n|3n}"); (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(4,"<<2>>_{4n|4n}"); // 3-p correlations: (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(6,"<<3>>_{2n|n,n}"); (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(7,"<<3>>_{3n|2n,n}"); (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(8,"<<3>>_{4n|2n,2n}"); (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(9,"<<3>>_{4n|3n,n}"); // 4-p correlations: (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(11,"<<4>>_{n,n|n,n}"); (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(12,"<<4>>_{2n,n|2n,n}"); (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(13,"<<4>>_{2n,2n|2n,2n}"); (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(14,"<<4>>_{3n|n,n,n}"); (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(15,"<<4>>_{3n,n|3n,n}"); (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(16,"<<4>>_{3n,n|2n,2n}"); (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(17,"<<4>>_{4n|2n,n,n}"); // 5-p correlations: (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(19,"<<5>>_{2n|n,n,n,n}"); (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(20,"<<5>>_{2n,2n|2n,n,n}"); (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(21,"<<5>>_{3n,n|2n,n,n}"); (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(22,"<<5>>_{4n|n,n,n,n}"); // 6-p correlations: (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(24,"<<6>>_{n,n,n|n,n,n}"); (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(25,"<<6>>_{2n,n,n|2n,n,n}"); (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(26,"<<6>>_{2n,2n|n,n,n,n}"); (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(27,"<<6>>_{3n,n|n,n,n,n}"); // 7-p correlations: (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(29,"<<7>>_{2n,n,n|n,n,n,n}"); // 8-p correlations: (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(31,"<<8>>_{n,n,n,n|n,n,n,n}"); fIntFlowResults->Add(fIntFlowCorrelationsAllHist); // average correction terms for non-uniform acceptance (with correct errors!): for(Int_t sc=0;sc<2;sc++) // sin or cos terms { TString intFlowCorrectionTermsForNUAHistName = "fIntFlowCorrectionTermsForNUAHist"; intFlowCorrectionTermsForNUAHistName += fAnalysisLabel->Data(); fIntFlowCorrectionTermsForNUAHist[sc] = new TH1D(Form("%s: %s terms",intFlowCorrectionTermsForNUAHistName.Data(),sinCosFlag[sc].Data()),Form("Correction terms for non-uniform acceptance (%s terms)",sinCosFlag[sc].Data()),10,0,10); fIntFlowCorrectionTermsForNUAHist[sc]->SetTickLength(-0.01,"Y"); fIntFlowCorrectionTermsForNUAHist[sc]->SetMarkerStyle(25); fIntFlowCorrectionTermsForNUAHist[sc]->SetLabelSize(0.03); fIntFlowCorrectionTermsForNUAHist[sc]->SetLabelOffset(0.01,"Y"); // ......................................................................... // 1-p terms: (fIntFlowCorrectionTermsForNUAHist[sc]->GetXaxis())->SetBinLabel(1,Form("%s(n(#phi_{1}))>",sinCosFlag[sc].Data())); // 2-p terms: // 3-p terms: // ... // ......................................................................... fIntFlowResults->Add(fIntFlowCorrectionTermsForNUAHist[sc]); } // end of for(Int_t sc=0;sc<2;sc++) // covariances (multiplied with weight dependent prefactor): TString intFlowCovariancesName = "fIntFlowCovariances"; intFlowCovariancesName += fAnalysisLabel->Data(); fIntFlowCovariances = new TH1D(intFlowCovariancesName.Data(),"Covariances (multiplied with weight dependent prefactor)",6,0,6); fIntFlowCovariances->SetLabelSize(0.04); fIntFlowCovariances->SetMarkerStyle(25); (fIntFlowCovariances->GetXaxis())->SetBinLabel(1,"Cov(<2>,<4>)"); (fIntFlowCovariances->GetXaxis())->SetBinLabel(2,"Cov(<2>,<6>)"); (fIntFlowCovariances->GetXaxis())->SetBinLabel(3,"Cov(<2>,<8>)"); (fIntFlowCovariances->GetXaxis())->SetBinLabel(4,"Cov(<4>,<6>)"); (fIntFlowCovariances->GetXaxis())->SetBinLabel(5,"Cov(<4>,<8>)"); (fIntFlowCovariances->GetXaxis())->SetBinLabel(6,"Cov(<6>,<8>)"); fIntFlowResults->Add(fIntFlowCovariances); // sum of linear and quadratic event weights for <2>, <4>, <6> and <8>: TString intFlowSumOfEventWeightsName = "fIntFlowSumOfEventWeights"; intFlowSumOfEventWeightsName += fAnalysisLabel->Data(); for(Int_t power=0;power<2;power++) { fIntFlowSumOfEventWeights[power] = new TH1D(Form("%s: %s",intFlowSumOfEventWeightsName.Data(),powerFlag[power].Data()),Form("Sum of %s event weights for correlations",powerFlag[power].Data()),4,0,4); fIntFlowSumOfEventWeights[power]->SetLabelSize(0.05); fIntFlowSumOfEventWeights[power]->SetMarkerStyle(25); if(power == 0) { (fIntFlowSumOfEventWeights[power]->GetXaxis())->SetBinLabel(1,"#sum_{i=1}^{N} w_{<2>}"); (fIntFlowSumOfEventWeights[power]->GetXaxis())->SetBinLabel(2,"#sum_{i=1}^{N} w_{<4>}"); (fIntFlowSumOfEventWeights[power]->GetXaxis())->SetBinLabel(3,"#sum_{i=1}^{N} w_{<6>}"); (fIntFlowSumOfEventWeights[power]->GetXaxis())->SetBinLabel(4,"#sum_{i=1}^{N} w_{<8>}"); } else if (power == 1) { (fIntFlowSumOfEventWeights[power]->GetXaxis())->SetBinLabel(1,"#sum_{i=1}^{N} w_{<2>}^{2}"); (fIntFlowSumOfEventWeights[power]->GetXaxis())->SetBinLabel(2,"#sum_{i=1}^{N} w_{<4>}^{2}"); (fIntFlowSumOfEventWeights[power]->GetXaxis())->SetBinLabel(3,"#sum_{i=1}^{N} w_{<6>}^{2}"); (fIntFlowSumOfEventWeights[power]->GetXaxis())->SetBinLabel(4,"#sum_{i=1}^{N} w_{<8>}^{2}"); } fIntFlowResults->Add(fIntFlowSumOfEventWeights[power]); } // sum of products of event weights for correlations <2>, <4>, <6> and <8>: TString intFlowSumOfProductOfEventWeightsName = "fIntFlowSumOfProductOfEventWeights"; intFlowSumOfProductOfEventWeightsName += fAnalysisLabel->Data(); fIntFlowSumOfProductOfEventWeights = new TH1D(intFlowSumOfProductOfEventWeightsName.Data(),"Sum of product of event weights for correlations",6,0,6); fIntFlowSumOfProductOfEventWeights->SetLabelSize(0.05); fIntFlowSumOfProductOfEventWeights->SetMarkerStyle(25); (fIntFlowSumOfProductOfEventWeights->GetXaxis())->SetBinLabel(1,"#sum_{i=1}^{N} w_{<2>} w_{<4>}"); (fIntFlowSumOfProductOfEventWeights->GetXaxis())->SetBinLabel(2,"#sum_{i=1}^{N} w_{<2>} w_{<6>}"); (fIntFlowSumOfProductOfEventWeights->GetXaxis())->SetBinLabel(3,"#sum_{i=1}^{N} w_{<2>} w_{<8>}"); (fIntFlowSumOfProductOfEventWeights->GetXaxis())->SetBinLabel(4,"#sum_{i=1}^{N} w_{<4>} w_{<6>}"); (fIntFlowSumOfProductOfEventWeights->GetXaxis())->SetBinLabel(5,"#sum_{i=1}^{N} w_{<4>} w_{<8>}"); (fIntFlowSumOfProductOfEventWeights->GetXaxis())->SetBinLabel(6,"#sum_{i=1}^{N} w_{<6>} w_{<8>}"); fIntFlowResults->Add(fIntFlowSumOfProductOfEventWeights); // final result for covariances of correlations (multiplied with weight dependent prefactor) versus M // [0=Cov(2,4),1=Cov(2,6),2=Cov(2,8),3=Cov(4,6),4=Cov(4,8),5=Cov(6,8)]: if(fCalculateCumulantsVsM) { TString intFlowCovariancesVsMName = "fIntFlowCovariancesVsM"; intFlowCovariancesVsMName += fAnalysisLabel->Data(); TString covarianceFlag[6] = {"Cov(<2>,<4>)","Cov(<2>,<6>)","Cov(<2>,<8>)","Cov(<4>,<6>)","Cov(<4>,<8>)","Cov(<6>,<8>)"}; for(Int_t ci=0;ci<6;ci++) { fIntFlowCovariancesVsM[ci] = new TH1D(Form("%s, %s",intFlowCovariancesVsMName.Data(),covarianceFlag[ci].Data()), Form("%s vs multiplicity",covarianceFlag[ci].Data()), fnBinsMult,fMinMult,fMaxMult); fIntFlowCovariancesVsM[ci]->GetYaxis()->SetTitle(covarianceFlag[ci].Data()); fIntFlowCovariancesVsM[ci]->GetXaxis()->SetTitle("M"); fIntFlowResults->Add(fIntFlowCovariancesVsM[ci]); } } // end of if(fCalculateCumulantsVsM) // sum of linear and quadratic event weights for <2>, <4>, <6> and <8> versus multiplicity // [0=sum{w_{<2>}},1=sum{w_{<4>}},2=sum{w_{<6>}},3=sum{w_{<8>}}][0=linear 1,1=quadratic]: if(fCalculateCumulantsVsM) { TString intFlowSumOfEventWeightsVsMName = "fIntFlowSumOfEventWeightsVsM"; intFlowSumOfEventWeightsVsMName += fAnalysisLabel->Data(); TString sumFlag[2][4] = {{"#sum_{i=1}^{N} w_{<2>}","#sum_{i=1}^{N} w_{<4>}","#sum_{i=1}^{N} w_{<6>}","#sum_{i=1}^{N} w_{<8>}"}, {"#sum_{i=1}^{N} w_{<2>}^{2}","#sum_{i=1}^{N} w_{<4>}^{2}","#sum_{i=1}^{N} w_{<6>}^{2}","#sum_{i=1}^{N} w_{<8>}^{2}"}}; for(Int_t si=0;si<4;si++) { for(Int_t power=0;power<2;power++) { fIntFlowSumOfEventWeightsVsM[si][power] = new TH1D(Form("%s, %s",intFlowSumOfEventWeightsVsMName.Data(),sumFlag[power][si].Data()), Form("%s vs multiplicity",sumFlag[power][si].Data()), fnBinsMult,fMinMult,fMaxMult); fIntFlowSumOfEventWeightsVsM[si][power]->GetYaxis()->SetTitle(sumFlag[power][si].Data()); fIntFlowSumOfEventWeightsVsM[si][power]->GetXaxis()->SetTitle("M"); fIntFlowResults->Add(fIntFlowSumOfEventWeightsVsM[si][power]); } // end of for(Int_t power=0;power<2;power++) } // end of for(Int_t si=0;si<4;si++) } // end of if(fCalculateCumulantsVsM) // sum of products of event weights for correlations <2>, <4>, <6> and <8> vs M // [0=sum{w_{<2>}w_{<4>}},1=sum{w_{<2>}w_{<6>}},2=sum{w_{<2>}w_{<8>}}, // 3=sum{w_{<4>}w_{<6>}},4=sum{w_{<4>}w_{<8>}},5=sum{w_{<6>}w_{<8>}}]: if(fCalculateCumulantsVsM) { TString intFlowSumOfProductOfEventWeightsVsMName = "fIntFlowSumOfProductOfEventWeightsVsM"; intFlowSumOfProductOfEventWeightsVsMName += fAnalysisLabel->Data(); TString sopowFlag[6] = {"#sum_{i=1}^{N} w_{<2>} w_{<4>}","#sum_{i=1}^{N} w_{<2>} w_{<6>}","#sum_{i=1}^{N} w_{<2>} w_{<8>}", "#sum_{i=1}^{N} w_{<4>} w_{<6>}","#sum_{i=1}^{N} w_{<4>} w_{<8>}","#sum_{i=1}^{N} w_{<6>} w_{<8>}"}; for(Int_t pi=0;pi<6;pi++) { fIntFlowSumOfProductOfEventWeightsVsM[pi] = new TH1D(Form("%s, %s",intFlowSumOfProductOfEventWeightsVsMName.Data(),sopowFlag[pi].Data()), Form("%s versus multiplicity",sopowFlag[pi].Data()), fnBinsMult,fMinMult,fMaxMult); fIntFlowSumOfProductOfEventWeightsVsM[pi]->GetXaxis()->SetTitle("M"); fIntFlowSumOfProductOfEventWeightsVsM[pi]->GetYaxis()->SetTitle(sopowFlag[pi].Data()); fIntFlowResults->Add(fIntFlowSumOfProductOfEventWeightsVsM[pi]); } // end of for(Int_t pi=0;pi<6;pi++) } // end of if(fCalculateCumulantsVsM) // covariances of NUA terms (multiplied with weight dependent prefactor): TString intFlowCovariancesNUAName = "fIntFlowCovariancesNUA"; intFlowCovariancesNUAName += fAnalysisLabel->Data(); fIntFlowCovariancesNUA = new TH1D(intFlowCovariancesNUAName.Data(),"Covariances for NUA (multiplied with weight dependent prefactor)",27,0,27); fIntFlowCovariancesNUA->SetLabelSize(0.04); fIntFlowCovariancesNUA->SetMarkerStyle(25); fIntFlowCovariancesNUA->GetXaxis()->SetLabelSize(0.02); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(1,"Cov(<2>,"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(2,"Cov(<2>,)"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(3,"Cov(,)"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(4,"Cov(<2>,)"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(5,"Cov(<2>,)"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(6,"Cov(<2>,)"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(7,"Cov(<2>,)"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(8,"Cov(<4>,)"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(9,"Cov(<4>,)"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(10,"Cov(<4>,)"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(11,"Cov(<4>,)"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(12,"Cov(<4>,>)"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(13,"Cov(<4>,>)"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(14,"Cov(,)"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(15,"Cov(,)"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(16,"Cov(,)"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(17,"Cov(,)"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(18,"Cov(,)"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(19,"Cov(,)"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(20,"Cov(,)"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(21,"Cov(,)"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(22,"Cov(,)"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(23,"Cov(,)"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(24,"Cov(,)"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(25,"Cov(,)"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(26,"Cov(,)"); (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(27,"Cov(,)"); fIntFlowResults->Add(fIntFlowCovariancesNUA); // sum of linear and quadratic event weights for NUA terms: TString intFlowSumOfEventWeightsNUAName = "fIntFlowSumOfEventWeightsNUA"; intFlowSumOfEventWeightsNUAName += fAnalysisLabel->Data(); for(Int_t sc=0;sc<2;sc++) { for(Int_t power=0;power<2;power++) { fIntFlowSumOfEventWeightsNUA[sc][power] = new TH1D(Form("%s: %s, %s",intFlowSumOfEventWeightsNUAName.Data(),powerFlag[power].Data(),sinCosFlag[sc].Data()),Form("Sum of %s event weights for NUA %s terms",powerFlag[power].Data(),sinCosFlag[sc].Data()),3,0,3); fIntFlowSumOfEventWeightsNUA[sc][power]->SetLabelSize(0.05); fIntFlowSumOfEventWeightsNUA[sc][power]->SetMarkerStyle(25); if(power == 0) { (fIntFlowSumOfEventWeightsNUA[sc][power]->GetXaxis())->SetBinLabel(1,Form("#sum_{i=1}^{N} w_{<%s(#phi)>}",sinCosFlag[sc].Data())); (fIntFlowSumOfEventWeightsNUA[sc][power]->GetXaxis())->SetBinLabel(2,Form("#sum_{i=1}^{N} w_{<%s(#phi_{1}+#phi_{2})>}",sinCosFlag[sc].Data())); (fIntFlowSumOfEventWeightsNUA[sc][power]->GetXaxis())->SetBinLabel(3,Form("#sum_{i=1}^{N} w_{<%s(#phi_{1}-#phi_{2}-#phi_{3})>}",sinCosFlag[sc].Data())); } else if(power == 1) { (fIntFlowSumOfEventWeightsNUA[sc][power]->GetXaxis())->SetBinLabel(1,Form("#sum_{i=1}^{N} w_{<%s(#phi)>}^{2}",sinCosFlag[sc].Data())); (fIntFlowSumOfEventWeightsNUA[sc][power]->GetXaxis())->SetBinLabel(2,Form("#sum_{i=1}^{N} w_{<%s(#phi_{1}+#phi_{2})>}^{2}",sinCosFlag[sc].Data())); (fIntFlowSumOfEventWeightsNUA[sc][power]->GetXaxis())->SetBinLabel(3,Form("#sum_{i=1}^{N} w_{<%s(#phi_{1}-#phi_{2}-#phi_{3})>}^{2}",sinCosFlag[sc].Data())); } fIntFlowResults->Add(fIntFlowSumOfEventWeightsNUA[sc][power]); } } // sum of products of event weights for NUA terms: TString intFlowSumOfProductOfEventWeightsNUAName = "fIntFlowSumOfProductOfEventWeightsNUA"; intFlowSumOfProductOfEventWeightsNUAName += fAnalysisLabel->Data(); fIntFlowSumOfProductOfEventWeightsNUA = new TH1D(intFlowSumOfProductOfEventWeightsNUAName.Data(),"Sum of product of event weights for NUA terms",27,0,27); fIntFlowSumOfProductOfEventWeightsNUA->SetLabelSize(0.05); fIntFlowSumOfProductOfEventWeightsNUA->SetMarkerStyle(25); (fIntFlowSumOfProductOfEventWeightsNUA->GetXaxis())->SetBinLabel(1,"#sum_{i=1}^{N} w_{<2>} w_{}"); (fIntFlowSumOfProductOfEventWeightsNUA->GetXaxis())->SetBinLabel(2,"#sum_{i=1}^{N} w_{<2>} w_{}"); (fIntFlowSumOfProductOfEventWeightsNUA->GetXaxis())->SetBinLabel(3,"#sum_{i=1}^{N} w_{} w_{}"); // .... // to be improved - add labels for remaining bins // .... fIntFlowResults->Add(fIntFlowSumOfProductOfEventWeightsNUA); // Final results for reference Q-cumulants: TString cumulantFlag[4] = {"QC{2}","QC{4}","QC{6}","QC{8}"}; TString intFlowQcumulantsName = "fIntFlowQcumulants"; intFlowQcumulantsName += fAnalysisLabel->Data(); fIntFlowQcumulants = new TH1D(intFlowQcumulantsName.Data(),"Integrated Q-cumulants",4,0,4); fIntFlowQcumulants->SetLabelSize(0.05); fIntFlowQcumulants->SetMarkerStyle(25); for(Int_t b=0;b<4;b++) { (fIntFlowQcumulants->GetXaxis())->SetBinLabel(b+1,cumulantFlag[b].Data()); } fIntFlowResults->Add(fIntFlowQcumulants); // Final results for reference Q-cumulants rebinned in M: if(fCalculateCumulantsVsM) { TString intFlowQcumulantsRebinnedInMName = "fIntFlowQcumulantsRebinnedInM"; intFlowQcumulantsRebinnedInMName += fAnalysisLabel->Data(); fIntFlowQcumulantsRebinnedInM = new TH1D(intFlowQcumulantsRebinnedInMName.Data(),"Reference Q-cumulants rebinned in M",4,0,4); fIntFlowQcumulantsRebinnedInM->SetLabelSize(0.05); fIntFlowQcumulantsRebinnedInM->SetMarkerStyle(25); for(Int_t b=0;b<4;b++) { (fIntFlowQcumulantsRebinnedInM->GetXaxis())->SetBinLabel(b+1,cumulantFlag[b].Data()); } fIntFlowResults->Add(fIntFlowQcumulantsRebinnedInM); } // end of if(fCalculateCumulantsVsM) // final results for integrated Q-cumulants versus multiplicity: if(fCalculateCumulantsVsM) { TString intFlowQcumulantsVsMName = "fIntFlowQcumulantsVsM"; intFlowQcumulantsVsMName += fAnalysisLabel->Data(); for(Int_t co=0;co<4;co++) // cumulant order { fIntFlowQcumulantsVsM[co] = new TH1D(Form("%s, %s",intFlowQcumulantsVsMName.Data(),cumulantFlag[co].Data()), Form("%s vs multipicity",cumulantFlag[co].Data()), fnBinsMult,fMinMult,fMaxMult); fIntFlowQcumulantsVsM[co]->GetXaxis()->SetTitle("M"); fIntFlowQcumulantsVsM[co]->GetYaxis()->SetTitle(cumulantFlag[co].Data()); fIntFlowResults->Add(fIntFlowQcumulantsVsM[co]); } // end of for(Int_t co=0;co<4;co++) // cumulant order } // end of if(fCalculateCumulantsVsM) // final integrated flow estimates from Q-cumulants: TString flowFlag[4] = {Form("v_{%d}{2,QC}",fHarmonic),Form("v_{%d}{4,QC}",fHarmonic),Form("v_{%d}{6,QC}",fHarmonic),Form("v_{%d}{8,QC}",fHarmonic)}; TString intFlowName = "fIntFlow"; intFlowName += fAnalysisLabel->Data(); // integrated flow from Q-cumulants: fIntFlow = new TH1D(intFlowName.Data(),"Reference flow estimates from Q-cumulants",4,0,4); fIntFlow->SetLabelSize(0.05); fIntFlow->SetMarkerStyle(25); for(Int_t b=0;b<4;b++) { (fIntFlow->GetXaxis())->SetBinLabel(b+1,flowFlag[b].Data()); } fIntFlowResults->Add(fIntFlow); // Reference flow vs M rebinned in one huge bin: if(fCalculateCumulantsVsM) { TString intFlowRebinnedInMName = "fIntFlowRebinnedInM"; intFlowRebinnedInMName += fAnalysisLabel->Data(); fIntFlowRebinnedInM = new TH1D(intFlowRebinnedInMName.Data(),"Reference flow estimates from Q-cumulants (rebinned in M)",4,0,4); fIntFlowRebinnedInM->SetLabelSize(0.05); fIntFlowRebinnedInM->SetMarkerStyle(25); for(Int_t b=0;b<4;b++) { (fIntFlowRebinnedInM->GetXaxis())->SetBinLabel(b+1,flowFlag[b].Data()); } fIntFlowResults->Add(fIntFlowRebinnedInM); } // integrated flow from Q-cumulants: versus multiplicity: if(fCalculateCumulantsVsM) { TString intFlowVsMName = "fIntFlowVsM"; intFlowVsMName += fAnalysisLabel->Data(); for(Int_t co=0;co<4;co++) // cumulant order { fIntFlowVsM[co] = new TH1D(Form("%s, %s",intFlowVsMName.Data(),flowFlag[co].Data()), Form("%s vs multipicity",flowFlag[co].Data()), fnBinsMult,fMinMult,fMaxMult); fIntFlowVsM[co]->GetXaxis()->SetTitle("M"); fIntFlowVsM[co]->GetYaxis()->SetTitle(flowFlag[co].Data()); fIntFlowResults->Add(fIntFlowVsM[co]); } // end of for(Int_t co=0;co<4;co++) // cumulant order } // end of if(fCalculateCumulantsVsM) // quantifying detector effects effects to correlations: TString intFlowDetectorBiasName = "fIntFlowDetectorBias"; intFlowDetectorBiasName += fAnalysisLabel->Data(); fIntFlowDetectorBias = new TH1D(intFlowDetectorBiasName.Data(),"Quantifying detector bias",4,0,4); fIntFlowDetectorBias->SetLabelSize(0.05); fIntFlowDetectorBias->SetMarkerStyle(25); for(Int_t ci=0;ci<4;ci++) { (fIntFlowDetectorBias->GetXaxis())->SetBinLabel(ci+1,Form("#frac{corrected}{measured} %s",cumulantFlag[ci].Data())); } fIntFlowResults->Add(fIntFlowDetectorBias); // quantifying detector effects to correlations versus multiplicity: if(fCalculateCumulantsVsM) { TString intFlowDetectorBiasVsMName = "fIntFlowDetectorBiasVsM"; intFlowDetectorBiasVsMName += fAnalysisLabel->Data(); for(Int_t ci=0;ci<4;ci++) // correlation index { fIntFlowDetectorBiasVsM[ci] = new TH1D(Form("%s for %s",intFlowDetectorBiasVsMName.Data(),cumulantFlag[ci].Data()), Form("Quantifying detector bias for %s vs multipicity",cumulantFlag[ci].Data()), fnBinsMult,fMinMult,fMaxMult); fIntFlowDetectorBiasVsM[ci]->GetXaxis()->SetTitle("M"); fIntFlowDetectorBiasVsM[ci]->GetYaxis()->SetTitle("#frac{corrected}{measured}"); if(fApplyCorrectionForNUAVsM){fIntFlowResults->Add(fIntFlowDetectorBiasVsM[ci]);} } // end of for(Int_t co=0;co<4;co++) // cumulant order } // end of if(fCalculateCumulantsVsM) /* // to be improved (removed): // final average weighted multi-particle correlations for all events calculated from Q-vectors fQCorrelations[1] = new TProfile("Weighted correlations","final average multi-particle correlations from weighted Q-vectors",200,0,200,"s"); fQCorrelations[1]->SetTickLength(-0.01,"Y"); fQCorrelations[1]->SetMarkerStyle(25); fQCorrelations[1]->SetLabelSize(0.03); fQCorrelations[1]->SetLabelOffset(0.01,"Y"); // 2-particle correlations: (fQCorrelations[1]->GetXaxis())->SetBinLabel(1,""); (fQCorrelations[1]->GetXaxis())->SetBinLabel(2,""); (fQCorrelations[1]->GetXaxis())->SetBinLabel(3,""); (fQCorrelations[1]->GetXaxis())->SetBinLabel(4,""); (fQCorrelations[1]->GetXaxis())->SetBinLabel(5,""); (fQCorrelations[1]->GetXaxis())->SetBinLabel(6,""); // 3-particle correlations: (fQCorrelations[1]->GetXaxis())->SetBinLabel(21,""); // 4-particle correlations: (fQCorrelations[1]->GetXaxis())->SetBinLabel(41,""); // add fQCorrelations[1] to the list fIntFlowList: fIntFlowList->Add(fQCorrelations[1]); */ } // end of AliFlowAnalysisWithQCumulants::BookEverythingForIntegratedFlow() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::InitializeArraysForNestedLoops() { // Initialize arrays of all objects relevant for calculations with nested loops. // integrated flow: for(Int_t sc=0;sc<2;sc++) // sin or cos terms { fIntFlowDirectCorrectionTermsForNUA[sc] = NULL; } // differential flow: // correlations: for(Int_t t=0;t<2;t++) // type: RP or POI { for(Int_t pe=0;pe<2;pe++) // pt or eta { for(Int_t ci=0;ci<4;ci++) // correlation index { fDiffFlowDirectCorrelations[t][pe][ci] = NULL; } // end of for(Int_t ci=0;ci<4;ci++) // correlation index } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta } // end of for(Int_t t=0;t<2;t++) // type: RP or POI // correction terms for non-uniform acceptance: for(Int_t t=0;t<2;t++) // type: RP or POI { for(Int_t pe=0;pe<2;pe++) // pt or eta { for(Int_t sc=0;sc<2;sc++) // sin or cos terms { for(Int_t cti=0;cti<9;cti++) // correction term index { fDiffFlowDirectCorrectionTermsForNUA[t][pe][sc][cti] = NULL; } } } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta } // end of for(Int_t t=0;t<2;t++) // type: RP or POI } // end of void AliFlowAnalysisWithQCumulants::InitializeArraysForNestedLoops() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::BookEverythingForNestedLoops() { // Book all objects relevant for calculations with nested loops. TString sinCosFlag[2] = {"sin","cos"}; // to be improved (should I promote this to data members?) TString typeFlag[2] = {"RP","POI"}; // to be improved (should I promote this to data members?) TString ptEtaFlag[2] = {"p_{T}","#eta"}; // to be improved (should I promote this to data members?) TString reducedCorrelationIndex[4] = {"<2'>","<4'>","<6'>","<8'>"}; // to be improved (should I promote this to data members?) Double_t lowerPtEtaEdge[2] = {fPtMin+(fCrossCheckInPtBinNo-1)*fPtBinWidth,fEtaMin+(fCrossCheckInEtaBinNo-1)*fEtaBinWidth}; Double_t upperPtEtaEdge[2] = {fPtMin+fCrossCheckInPtBinNo*fPtBinWidth,fEtaMin+fCrossCheckInEtaBinNo*fEtaBinWidth}; TString evaluateNestedLoopsName = "fEvaluateNestedLoops"; evaluateNestedLoopsName += fAnalysisLabel->Data(); fEvaluateNestedLoops = new TProfile(evaluateNestedLoopsName.Data(),"Flags for nested loops",4,0,4); fEvaluateNestedLoops->SetLabelSize(0.03); (fEvaluateNestedLoops->GetXaxis())->SetBinLabel(1,"fEvaluateIntFlowNestedLoops"); (fEvaluateNestedLoops->GetXaxis())->SetBinLabel(2,"fEvaluateDiffFlowNestedLoops"); (fEvaluateNestedLoops->GetXaxis())->SetBinLabel(3,"fCrossCheckInPtBinNo"); (fEvaluateNestedLoops->GetXaxis())->SetBinLabel(4,"fCrossCheckInEtaBinNo"); fEvaluateNestedLoops->Fill(0.5,(Int_t)fEvaluateIntFlowNestedLoops); fEvaluateNestedLoops->Fill(1.5,(Int_t)fEvaluateDiffFlowNestedLoops); fEvaluateNestedLoops->Fill(2.5,fCrossCheckInPtBinNo); fEvaluateNestedLoops->Fill(3.5,fCrossCheckInEtaBinNo); fNestedLoopsList->Add(fEvaluateNestedLoops); // nested loops for integrated flow: if(fEvaluateIntFlowNestedLoops) { // correlations: TString intFlowDirectCorrelationsName = "fIntFlowDirectCorrelations"; intFlowDirectCorrelationsName += fAnalysisLabel->Data(); fIntFlowDirectCorrelations = new TProfile(intFlowDirectCorrelationsName.Data(),"Multiparticle correlations calculated with nested loops (for int. flow)",32,0,32,"s"); fNestedLoopsList->Add(fIntFlowDirectCorrelations); if(fUsePhiWeights||fUsePtWeights||fUseEtaWeights) { TString intFlowExtraDirectCorrelationsName = "fIntFlowExtraDirectCorrelations"; intFlowExtraDirectCorrelationsName += fAnalysisLabel->Data(); fIntFlowExtraDirectCorrelations = new TProfile(intFlowExtraDirectCorrelationsName.Data(),"Extra multiparticle correlations calculated with nested loops (for int. flow)",100,0,100,"s"); fNestedLoopsList->Add(fIntFlowExtraDirectCorrelations); } // end of if(fUsePhiWeights||fUsePtWeights||fUseEtaWeights) // correction terms for non-uniform acceptance: for(Int_t sc=0;sc<2;sc++) // sin or cos terms { TString intFlowDirectCorrectionTermsForNUAName = "fIntFlowDirectCorrectionTermsForNUA"; intFlowDirectCorrectionTermsForNUAName += fAnalysisLabel->Data(); fIntFlowDirectCorrectionTermsForNUA[sc] = new TProfile(Form("%s: %s terms",intFlowDirectCorrectionTermsForNUAName.Data(),sinCosFlag[sc].Data()),Form("Correction terms for non-uniform acceptance (%s terms)",sinCosFlag[sc].Data()),10,0,10,"s"); fNestedLoopsList->Add(fIntFlowDirectCorrectionTermsForNUA[sc]); } // end of for(Int_t sc=0;sc<2;sc++) } // end of if(fEvaluateIntFlowNestedLoops) // nested loops for differential flow: if(fEvaluateDiffFlowNestedLoops) { // reduced correlations: TString diffFlowDirectCorrelationsName = "fDiffFlowDirectCorrelations"; diffFlowDirectCorrelationsName += fAnalysisLabel->Data(); for(Int_t t=0;t<2;t++) // type: RP or POI { for(Int_t pe=0;pe<2;pe++) // pt or eta { for(Int_t rci=0;rci<4;rci++) // reduced correlation index { // reduced correlations: fDiffFlowDirectCorrelations[t][pe][rci] = new TProfile(Form("%s, %s, %s, %s",diffFlowDirectCorrelationsName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedCorrelationIndex[rci].Data()),Form("%s, %s, %s, %s",diffFlowDirectCorrelationsName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedCorrelationIndex[rci].Data()),1,lowerPtEtaEdge[pe],upperPtEtaEdge[pe],"s"); fDiffFlowDirectCorrelations[t][pe][rci]->SetXTitle(ptEtaFlag[pe].Data()); fNestedLoopsList->Add(fDiffFlowDirectCorrelations[t][pe][rci]); // to be improved (add dedicated list to hold reduced correlations) } // end of for(Int_t rci=0;rci<4;rci++) // correlation index } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta } // end of for(Int_t t=0;t<2;t++) // type: RP or POI // correction terms for non-uniform acceptance: TString diffFlowDirectCorrectionTermsForNUAName = "fDiffFlowDirectCorrectionTermsForNUA"; diffFlowDirectCorrectionTermsForNUAName += fAnalysisLabel->Data(); for(Int_t t=0;t<2;t++) // typeFlag (0 = RP, 1 = POI) { for(Int_t pe=0;pe<2;pe++) // pt or eta { for(Int_t sc=0;sc<2;sc++) // sin or cos { for(Int_t cti=0;cti<9;cti++) // correction term index { fDiffFlowDirectCorrectionTermsForNUA[t][pe][sc][cti] = new TProfile(Form("%s, %s, %s, %s, cti = %d",diffFlowDirectCorrectionTermsForNUAName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),sinCosFlag[sc].Data(),cti+1),Form("%s, %s, %s, %s, cti = %d",diffFlowDirectCorrectionTermsForNUAName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),sinCosFlag[sc].Data(),cti+1),1,lowerPtEtaEdge[pe],upperPtEtaEdge[pe],"s"); fNestedLoopsList->Add(fDiffFlowDirectCorrectionTermsForNUA[t][pe][sc][cti]); } } } } // number of RPs and POIs in selected pt and eta bins for cross-checkings: TString noOfParticlesInBinName = "fNoOfParticlesInBin"; fNoOfParticlesInBin = new TH1D(noOfParticlesInBinName.Data(),"Number of RPs and POIs in selected p_{T} and #eta bin",4,0,4); fNoOfParticlesInBin->GetXaxis()->SetBinLabel(1,"# of RPs in p_{T} bin"); fNoOfParticlesInBin->GetXaxis()->SetBinLabel(2,"# of RPs in #eta bin"); fNoOfParticlesInBin->GetXaxis()->SetBinLabel(3,"# of POIs in p_{T} bin"); fNoOfParticlesInBin->GetXaxis()->SetBinLabel(4,"# of POIs in #eta bin"); fNestedLoopsList->Add(fNoOfParticlesInBin); } // end of if(fEvaluateDiffFlowNestedLoops) } // end of AliFlowAnalysisWithQCumulants::BookEverythingForNestedLoops() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CalculateIntFlowCorrelations() { // calculate all correlations needed for integrated flow // multiplicity: Double_t dMult = (*fSMpk)(0,0); // real and imaginary parts of non-weighted Q-vectors evaluated in harmonics n, 2n, 3n and 4n: Double_t dReQ1n = (*fReQ)(0,0); Double_t dReQ2n = (*fReQ)(1,0); Double_t dReQ3n = (*fReQ)(2,0); Double_t dReQ4n = (*fReQ)(3,0); Double_t dImQ1n = (*fImQ)(0,0); Double_t dImQ2n = (*fImQ)(1,0); Double_t dImQ3n = (*fImQ)(2,0); Double_t dImQ4n = (*fImQ)(3,0); // real and imaginary parts of some expressions involving various combinations of Q-vectors evaluated in harmonics n, 2n, 3n and 4n: // (these expression appear in the Eqs. for the multi-particle correlations bellow) // Re[Q_{2n} Q_{n}^* Q_{n}^*] Double_t reQ2nQ1nstarQ1nstar = pow(dReQ1n,2.)*dReQ2n + 2.*dReQ1n*dImQ1n*dImQ2n - pow(dImQ1n,2.)*dReQ2n; // Im[Q_{2n} Q_{n}^* Q_{n}^*] //Double_t imQ2nQ1nstarQ1nstar = pow(dReQ1n,2.)*dImQ2n-2.*dReQ1n*dImQ1n*dReQ2n-pow(dImQ1n,2.)*dImQ2n; // Re[Q_{n} Q_{n} Q_{2n}^*] = Re[Q_{2n} Q_{n}^* Q_{n}^*] Double_t reQ1nQ1nQ2nstar = reQ2nQ1nstarQ1nstar; // Re[Q_{3n} Q_{n} Q_{2n}^* Q_{2n}^*] Double_t reQ3nQ1nQ2nstarQ2nstar = (pow(dReQ2n,2.)-pow(dImQ2n,2.))*(dReQ3n*dReQ1n-dImQ3n*dImQ1n) + 2.*dReQ2n*dImQ2n*(dReQ3n*dImQ1n+dImQ3n*dReQ1n); // Im[Q_{3n} Q_{n} Q_{2n}^* Q_{2n}^*] //Double_t imQ3nQ1nQ2nstarQ2nstar = calculate and implement this (deleteMe) // Re[Q_{2n} Q_{2n} Q_{3n}^* Q_{1n}^*] = Re[Q_{3n} Q_{n} Q_{2n}^* Q_{2n}^*] Double_t reQ2nQ2nQ3nstarQ1nstar = reQ3nQ1nQ2nstarQ2nstar; // Re[Q_{4n} Q_{2n}^* Q_{2n}^*] Double_t reQ4nQ2nstarQ2nstar = pow(dReQ2n,2.)*dReQ4n+2.*dReQ2n*dImQ2n*dImQ4n-pow(dImQ2n,2.)*dReQ4n; // Im[Q_{4n} Q_{2n}^* Q_{2n}^*] //Double_t imQ4nQ2nstarQ2nstar = calculate and implement this (deleteMe) // Re[Q_{2n} Q_{2n} Q_{4n}^*] = Re[Q_{4n} Q_{2n}^* Q_{2n}^*] Double_t reQ2nQ2nQ4nstar = reQ4nQ2nstarQ2nstar; // Re[Q_{4n} Q_{3n}^* Q_{n}^*] Double_t reQ4nQ3nstarQ1nstar = dReQ4n*(dReQ3n*dReQ1n-dImQ3n*dImQ1n)+dImQ4n*(dReQ3n*dImQ1n+dImQ3n*dReQ1n); // Re[Q_{3n} Q_{n} Q_{4n}^*] = Re[Q_{4n} Q_{3n}^* Q_{n}^*] Double_t reQ3nQ1nQ4nstar = reQ4nQ3nstarQ1nstar; // Im[Q_{4n} Q_{3n}^* Q_{n}^*] //Double_t imQ4nQ3nstarQ1nstar = calculate and implement this (deleteMe) // Re[Q_{3n} Q_{2n}^* Q_{n}^*] Double_t reQ3nQ2nstarQ1nstar = dReQ3n*dReQ2n*dReQ1n-dReQ3n*dImQ2n*dImQ1n+dImQ3n*dReQ2n*dImQ1n + dImQ3n*dImQ2n*dReQ1n; // Re[Q_{2n} Q_{n} Q_{3n}^*] = Re[Q_{3n} Q_{2n}^* Q_{n}^*] Double_t reQ2nQ1nQ3nstar = reQ3nQ2nstarQ1nstar; // Im[Q_{3n} Q_{2n}^* Q_{n}^*] //Double_t imQ3nQ2nstarQ1nstar; //calculate and implement this (deleteMe) // Re[Q_{3n} Q_{n}^* Q_{n}^* Q_{n}^*] Double_t reQ3nQ1nstarQ1nstarQ1nstar = dReQ3n*pow(dReQ1n,3)-3.*dReQ1n*dReQ3n*pow(dImQ1n,2) + 3.*dImQ1n*dImQ3n*pow(dReQ1n,2)-dImQ3n*pow(dImQ1n,3); // Im[Q_{3n} Q_{n}^* Q_{n}^* Q_{n}^*] //Double_t imQ3nQ1nstarQ1nstarQ1nstar; //calculate and implement this (deleteMe) // |Q_{2n}|^2 |Q_{n}|^2 Double_t dQ2nQ1nQ2nstarQ1nstar = (pow(dReQ2n,2.)+pow(dImQ2n,2.))*(pow(dReQ1n,2.)+pow(dImQ1n,2.)); // Re[Q_{4n} Q_{2n}^* Q_{n}^* Q_{n}^*] Double_t reQ4nQ2nstarQ1nstarQ1nstar = (dReQ4n*dReQ2n+dImQ4n*dImQ2n)*(pow(dReQ1n,2)-pow(dImQ1n,2)) + 2.*dReQ1n*dImQ1n*(dImQ4n*dReQ2n-dReQ4n*dImQ2n); // Im[Q_{4n} Q_{2n}^* Q_{n}^* Q_{n}^*] //Double_t imQ4nQ2nstarQ1nstarQ1nstar; //calculate and implement this (deleteMe) // Re[Q_{2n} Q_{n} Q_{n}^* Q_{n}^* Q_{n}^*] Double_t reQ2nQ1nQ1nstarQ1nstarQ1nstar = (dReQ2n*dReQ1n-dImQ2n*dImQ1n)*(pow(dReQ1n,3)-3.*dReQ1n*pow(dImQ1n,2)) + (dReQ2n*dImQ1n+dReQ1n*dImQ2n)*(3.*dImQ1n*pow(dReQ1n,2)-pow(dImQ1n,3)); // Im[Q_{2n} Q_{n} Q_{n}^* Q_{n}^* Q_{n}^*] //Double_t imQ2nQ1nQ1nstarQ1nstarQ1nstar; //calculate and implement this (deleteMe) // Re[Q_{2n} Q_{2n} Q_{2n}^* Q_{n}^* Q_{n}^*] Double_t reQ2nQ2nQ2nstarQ1nstarQ1nstar = (pow(dReQ2n,2.)+pow(dImQ2n,2.)) * (dReQ2n*(pow(dReQ1n,2.)-pow(dImQ1n,2.)) + 2.*dImQ2n*dReQ1n*dImQ1n); // Im[Q_{2n} Q_{2n} Q_{2n}^* Q_{n}^* Q_{n}^*] //Double_t imQ2nQ2nQ2nstarQ1nstarQ1nstar = (pow(dReQ2n,2.)+pow(dImQ2n,2.)) // * (dImQ2n*(pow(dReQ1n,2.)-pow(dImQ1n,2.)) - 2.*dReQ2n*dReQ1n*dImQ1n); // Re[Q_{4n} Q_{n}^* Q_{n}^* Q_{n}^* Q_{n}^*] Double_t reQ4nQ1nstarQ1nstarQ1nstarQ1nstar = pow(dReQ1n,4.)*dReQ4n-6.*pow(dReQ1n,2.)*dReQ4n*pow(dImQ1n,2.) + pow(dImQ1n,4.)*dReQ4n+4.*pow(dReQ1n,3.)*dImQ1n*dImQ4n - 4.*pow(dImQ1n,3.)*dReQ1n*dImQ4n; // Im[Q_{4n} Q_{n}^* Q_{n}^* Q_{n}^* Q_{n}^*] //Double_t imQ4nQ1nstarQ1nstarQ1nstarQ1nstar = pow(dReQ1n,4.)*dImQ4n-6.*pow(dReQ1n,2.)*dImQ4n*pow(dImQ1n,2.) // + pow(dImQ1n,4.)*dImQ4n+4.*pow(dImQ1n,3.)*dReQ1n*dReQ4n // - 4.*pow(dReQ1n,3.)*dImQ1n*dReQ4n; // Re[Q_{3n} Q_{n} Q_{2n}^* Q_{n}^* Q_{n}^*] Double_t reQ3nQ1nQ2nstarQ1nstarQ1nstar = (pow(dReQ1n,2.)+pow(dImQ1n,2.)) * (dReQ1n*dReQ2n*dReQ3n-dReQ3n*dImQ1n*dImQ2n+dReQ2n*dImQ1n*dImQ3n+dReQ1n*dImQ2n*dImQ3n); // Im[Q_{3n} Q_{n} Q_{2n}^* Q_{n}^* Q_{n}^*] //Double_t imQ3nQ1nQ2nstarQ1nstarQ1nstar = (pow(dReQ1n,2.)+pow(dImQ1n,2.)) // * (-dReQ2n*dReQ3n*dImQ1n-dReQ1n*dReQ3n*dImQ2n+dReQ1n*dReQ2n*dImQ3n-dImQ1n*dImQ2n*dImQ3n); // Re[Q_{2n} Q_{2n} Q_{n}^* Q_{n}^* Q_{n}^* Q_{n}^*] Double_t reQ2nQ2nQ1nstarQ1nstarQ1nstarQ1nstar = (pow(dReQ1n,2.)*dReQ2n-2.*dReQ1n*dReQ2n*dImQ1n-dReQ2n*pow(dImQ1n,2.) + dImQ2n*pow(dReQ1n,2.)+2.*dReQ1n*dImQ1n*dImQ2n-pow(dImQ1n,2.)*dImQ2n) * (pow(dReQ1n,2.)*dReQ2n+2.*dReQ1n*dReQ2n*dImQ1n-dReQ2n*pow(dImQ1n,2.) - dImQ2n*pow(dReQ1n,2.)+2.*dReQ1n*dImQ1n*dImQ2n+pow(dImQ1n,2.)*dImQ2n); // Im[Q_{2n} Q_{2n} Q_{n}^* Q_{n}^* Q_{n}^* Q_{n}^*] //Double_t imQ2nQ2nQ1nstarQ1nstarQ1nstarQ1nstar = 2.*(pow(dReQ1n,2.)*dReQ2n-dReQ2n*pow(dImQ1n,2.) // + 2.*dReQ1n*dImQ1n*dImQ2n)*(pow(dReQ1n,2.)*dImQ2n // - 2.*dReQ1n*dImQ1n*dReQ2n-pow(dImQ1n,2.)*dImQ2n); // Re[Q_{3n} Q_{n} Q_{n}^* Q_{n}^* Q_{n}^* Q_{n}^*] Double_t reQ3nQ1nQ1nstarQ1nstarQ1nstarQ1nstar = (pow(dReQ1n,2.)+pow(dImQ1n,2.)) * (pow(dReQ1n,3.)*dReQ3n-3.*dReQ1n*dReQ3n*pow(dImQ1n,2.) + 3.*pow(dReQ1n,2.)*dImQ1n*dImQ3n-pow(dImQ1n,3.)*dImQ3n); // Im[Q_{3n} Q_{n} Q_{n}^* Q_{n}^* Q_{n}^* Q_{n}^*] //Double_t imQ3nQ1nQ1nstarQ1nstarQ1nstarQ1nstar = (pow(dReQ1n,2.)+pow(dImQ1n,2.)) // * (pow(dImQ1n,3.)*dReQ3n-3.*dImQ1n*dReQ3n*pow(dReQ1n,2.) // - 3.*pow(dImQ1n,2.)*dReQ1n*dImQ3n+pow(dReQ1n,3.)*dImQ3n); // |Q_{2n}|^2 |Q_{n}|^4 Double_t dQ2nQ1nQ1nQ2nstarQ1nstarQ1nstar = (pow(dReQ2n,2.)+pow(dImQ2n,2.))*pow((pow(dReQ1n,2.)+pow(dImQ1n,2.)),2.); // Re[Q_{2n} Q_{n} Q_{n} Q_{n}^* Q_{n}^* Q_{n}^* Q_{n}^*] Double_t reQ2nQ1nQ1nQ1nstarQ1nstarQ1nstarQ1nstar = pow((pow(dReQ1n,2.)+pow(dImQ1n,2.)),2.) * (pow(dReQ1n,2.)*dReQ2n-dReQ2n*pow(dImQ1n,2.) + 2.*dReQ1n*dImQ1n*dImQ2n); // Im[Q_{2n} Q_{n} Q_{n} Q_{n}^* Q_{n}^* Q_{n}^* Q_{n}^*] //Double_t imQ2nQ1nQ1nQ1nstarQ1nstarQ1nstarQ1nstar = pow((pow(dReQ1n,2.)+pow(dImQ1n,2.)),2.) // * (pow(dReQ1n,2.)*dImQ2n-dImQ2n*pow(dImQ1n,2.) // - 2.*dReQ1n*dReQ2n*dImQ1n); // ************************************** // **** multi-particle correlations: **** // ************************************** // // Remark 1: multi-particle correlations calculated with non-weighted Q-vectors are stored in 1D profile fQCorrelations[0]. // to be improved (wrong profiles) // Remark 2: binning of fQCorrelations[0] is organized as follows: // to be improved (wrong profiles) // -------------------------------------------------------------------------------------------------------------------- // 1st bin: <2>_{1n|1n} = two1n1n = cos(n*(phi1-phi2))> // 2nd bin: <2>_{2n|2n} = two2n2n = cos(2n*(phi1-phi2))> // 3rd bin: <2>_{3n|3n} = two3n3n = cos(3n*(phi1-phi2))> // 4th bin: <2>_{4n|4n} = two4n4n = cos(4n*(phi1-phi2))> // 5th bin: ---- EMPTY ---- // 6th bin: <3>_{2n|1n,1n} = three2n1n1n = // 7th bin: <3>_{3n|2n,1n} = three3n2n1n = // 8th bin: <3>_{4n|2n,2n} = three4n2n2n = // 9th bin: <3>_{4n|3n,1n} = three4n3n1n = // 10th bin: ---- EMPTY ---- // 11th bin: <4>_{1n,1n|1n,1n} = four1n1n1n1n = // 12th bin: <4>_{2n,1n|2n,1n} = four2n1n2n1n = // 13th bin: <4>_{2n,2n|2n,2n} = four2n2n2n2n = // 14th bin: <4>_{3n|1n,1n,1n} = four3n1n1n1n = // 15th bin: <4>_{3n,1n|3n,1n} = four3n1n3n1n = // 16th bin: <4>_{3n,1n|2n,2n} = four3n1n2n2n = // 17th bin: <4>_{4n|2n,1n,1n} = four4n2n1n1n = // 18th bin: ---- EMPTY ---- // 19th bin: <5>_{2n|1n,1n,1n,1n} = five2n1n1n1n1n = // 20th bin: <5>_{2n,2n|2n,1n,1n} = five2n2n2n1n1n = // 21st bin: <5>_{3n,1n|2n,1n,1n} = five3n1n2n1n1n = // 22nd bin: <5>_{4n|1n,1n,1n,1n} = five4n1n1n1n1n = // 23rd bin: ---- EMPTY ---- // 24th bin: <6>_{1n,1n,1n|1n,1n,1n} = six1n1n1n1n1n1n = // 25th bin: <6>_{2n,1n,1n|2n,1n,1n} = six2n1n1n2n1n1n = // 26th bin: <6>_{2n,2n|1n,1n,1n,1n} = six2n2n1n1n1n1n = // 27th bin: <6>_{3n,1n|1n,1n,1n,1n} = six3n1n1n1n1n1n = // 28th bin: ---- EMPTY ---- // 29th bin: <7>_{2n,1n,1n|1n,1n,1n,1n} = seven2n1n1n1n1n1n1n = // 30th bin: ---- EMPTY ---- // 31st bin: <8>_{1n,1n,1n,1n|1n,1n,1n,1n} = eight1n1n1n1n1n1n1n1n = // -------------------------------------------------------------------------------------------------------------------- // 2-particle: Double_t two1n1n = 0.; // Double_t two2n2n = 0.; // Double_t two3n3n = 0.; // Double_t two4n4n = 0.; // if(dMult>1) { two1n1n = (pow(dReQ1n,2.)+pow(dImQ1n,2.)-dMult)/(dMult*(dMult-1.)); two2n2n = (pow(dReQ2n,2.)+pow(dImQ2n,2.)-dMult)/(dMult*(dMult-1.)); two3n3n = (pow(dReQ3n,2.)+pow(dImQ3n,2.)-dMult)/(dMult*(dMult-1.)); two4n4n = (pow(dReQ4n,2.)+pow(dImQ4n,2.)-dMult)/(dMult*(dMult-1.)); // average 2-particle correlations for single event: fIntFlowCorrelationsAllEBE->SetBinContent(1,two1n1n); fIntFlowCorrelationsAllEBE->SetBinContent(2,two2n2n); fIntFlowCorrelationsAllEBE->SetBinContent(3,two3n3n); fIntFlowCorrelationsAllEBE->SetBinContent(4,two4n4n); // average 2-particle correlations for all events: fIntFlowCorrelationsAllPro->Fill(0.5,two1n1n,dMult*(dMult-1.)); fIntFlowCorrelationsAllPro->Fill(1.5,two2n2n,dMult*(dMult-1.)); fIntFlowCorrelationsAllPro->Fill(2.5,two3n3n,dMult*(dMult-1.)); fIntFlowCorrelationsAllPro->Fill(3.5,two4n4n,dMult*(dMult-1.)); // store separetately <2> (to be improved: do I really need this?) fIntFlowCorrelationsEBE->SetBinContent(1,two1n1n); // <2> // to be improved (this can be implemented better): Double_t mWeight2p = 0.; if(!strcmp(fMultiplicityWeight->Data(),"combinations")) { mWeight2p = dMult*(dMult-1.); } else if(!strcmp(fMultiplicityWeight->Data(),"unit")) { mWeight2p = 1.; } else if(!strcmp(fMultiplicityWeight->Data(),"multiplicity")) { mWeight2p = dMult; } fIntFlowEventWeightsForCorrelationsEBE->SetBinContent(1,mWeight2p); // eW_<2> fIntFlowCorrelationsPro->Fill(0.5,two1n1n,mWeight2p); if(fCalculateCumulantsVsM){fIntFlowCorrelationsVsMPro[0]->Fill(dMult+0.5,two1n1n,mWeight2p);} // distribution of : //f2pDistribution->Fill(two1n1n,dMult*(dMult-1.)); } // end of if(dMult>1) // 3-particle: Double_t three2n1n1n = 0.; // Double_t three3n2n1n = 0.; // Double_t three4n2n2n = 0.; // Double_t three4n3n1n = 0.; // if(dMult>2) { three2n1n1n = (reQ2nQ1nstarQ1nstar-2.*(pow(dReQ1n,2.)+pow(dImQ1n,2.)) - (pow(dReQ2n,2.)+pow(dImQ2n,2.))+2.*dMult) / (dMult*(dMult-1.)*(dMult-2.)); three3n2n1n = (reQ3nQ2nstarQ1nstar-(pow(dReQ3n,2.)+pow(dImQ3n,2.)) - (pow(dReQ2n,2.)+pow(dImQ2n,2.)) - (pow(dReQ1n,2.)+pow(dImQ1n,2.))+2.*dMult) / (dMult*(dMult-1.)*(dMult-2.)); three4n2n2n = (reQ4nQ2nstarQ2nstar-2.*(pow(dReQ2n,2.)+pow(dImQ2n,2.)) - (pow(dReQ4n,2.)+pow(dImQ4n,2.))+2.*dMult) / (dMult*(dMult-1.)*(dMult-2.)); three4n3n1n = (reQ4nQ3nstarQ1nstar-(pow(dReQ4n,2.)+pow(dImQ4n,2.)) - (pow(dReQ3n,2.)+pow(dImQ3n,2.)) - (pow(dReQ1n,2.)+pow(dImQ1n,2.))+2.*dMult) / (dMult*(dMult-1.)*(dMult-2.)); // average 3-particle correlations for single event: fIntFlowCorrelationsAllEBE->SetBinContent(6,three2n1n1n); fIntFlowCorrelationsAllEBE->SetBinContent(7,three3n2n1n); fIntFlowCorrelationsAllEBE->SetBinContent(8,three4n2n2n); fIntFlowCorrelationsAllEBE->SetBinContent(9,three4n3n1n); // average 3-particle correlations for all events: fIntFlowCorrelationsAllPro->Fill(5.5,three2n1n1n,dMult*(dMult-1.)*(dMult-2.)); fIntFlowCorrelationsAllPro->Fill(6.5,three3n2n1n,dMult*(dMult-1.)*(dMult-2.)); fIntFlowCorrelationsAllPro->Fill(7.5,three4n2n2n,dMult*(dMult-1.)*(dMult-2.)); fIntFlowCorrelationsAllPro->Fill(8.5,three4n3n1n,dMult*(dMult-1.)*(dMult-2.)); } // end of if(dMult>2) // 4-particle: Double_t four1n1n1n1n = 0.; // Double_t four2n2n2n2n = 0.; // Double_t four2n1n2n1n = 0.; // Double_t four3n1n1n1n = 0.; // Double_t four4n2n1n1n = 0.; // Double_t four3n1n2n2n = 0.; // Double_t four3n1n3n1n = 0.; // if(dMult>3) { four1n1n1n1n = (2.*dMult*(dMult-3.)+pow((pow(dReQ1n,2.)+pow(dImQ1n,2.)),2.)-4.*(dMult-2.)*(pow(dReQ1n,2.) + pow(dImQ1n,2.))-2.*reQ2nQ1nstarQ1nstar+(pow(dReQ2n,2.)+pow(dImQ2n,2.))) / (dMult*(dMult-1)*(dMult-2.)*(dMult-3.)); four2n2n2n2n = (2.*dMult*(dMult-3.)+pow((pow(dReQ2n,2.)+pow(dImQ2n,2.)),2.)-4.*(dMult-2.)*(pow(dReQ2n,2.) + pow(dImQ2n,2.))-2.*reQ4nQ2nstarQ2nstar+(pow(dReQ4n,2.)+pow(dImQ4n,2.))) / (dMult*(dMult-1)*(dMult-2.)*(dMult-3.)); four2n1n2n1n = (dQ2nQ1nQ2nstarQ1nstar-2.*reQ3nQ2nstarQ1nstar-2.*reQ2nQ1nstarQ1nstar) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)) - ((dMult-5.)*(pow(dReQ1n,2.)+pow(dImQ1n,2.)) + (dMult-4.)*(pow(dReQ2n,2.)+pow(dImQ2n,2.))-(pow(dReQ3n,2.)+pow(dImQ3n,2.))) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)) + (dMult-6.)/((dMult-1.)*(dMult-2.)*(dMult-3.)); four3n1n1n1n = (reQ3nQ1nstarQ1nstarQ1nstar-3.*reQ3nQ2nstarQ1nstar-3.*reQ2nQ1nstarQ1nstar) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)) + (2.*(pow(dReQ3n,2.)+pow(dImQ3n,2.))+3.*(pow(dReQ2n,2.)+pow(dImQ2n,2.)) + 6.*(pow(dReQ1n,2.)+pow(dImQ1n,2.))-6.*dMult) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)); four4n2n1n1n = (reQ4nQ2nstarQ1nstarQ1nstar-2.*reQ4nQ3nstarQ1nstar-reQ4nQ2nstarQ2nstar-2.*reQ3nQ2nstarQ1nstar) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)) - (reQ2nQ1nstarQ1nstar-2.*(pow(dReQ4n,2.)+pow(dImQ4n,2.))-2.*(pow(dReQ3n,2.)+pow(dImQ3n,2.)) - 3.*(pow(dReQ2n,2.)+pow(dImQ2n,2.))-4.*(pow(dReQ1n,2.)+pow(dImQ1n,2.))) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)) - 6./((dMult-1.)*(dMult-2.)*(dMult-3.)); four3n1n2n2n = (reQ3nQ1nQ2nstarQ2nstar-reQ4nQ2nstarQ2nstar-reQ3nQ1nQ4nstar-2.*reQ3nQ2nstarQ1nstar) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)) - (2.*reQ1nQ1nQ2nstar-(pow(dReQ4n,2.)+pow(dImQ4n,2.))-2.*(pow(dReQ3n,2.)+pow(dImQ3n,2.)) - 4.*(pow(dReQ2n,2.)+pow(dImQ2n,2.))-4.*(pow(dReQ1n,2.)+pow(dImQ1n,2.))) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)) - 6./((dMult-1.)*(dMult-2.)*(dMult-3.)); four3n1n3n1n = ((pow(dReQ3n,2.)+pow(dImQ3n,2.))*(pow(dReQ1n,2.)+pow(dImQ1n,2.)) - 2.*reQ4nQ3nstarQ1nstar-2.*reQ3nQ2nstarQ1nstar) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)) + ((pow(dReQ4n,2.)+pow(dImQ4n,2.))-(dMult-4.)*(pow(dReQ3n,2.)+pow(dImQ3n,2.)) + (pow(dReQ2n,2.)+pow(dImQ2n,2.))-(dMult-4.)*(pow(dReQ1n,2.)+pow(dImQ1n,2.))) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)) + (dMult-6.)/((dMult-1.)*(dMult-2.)*(dMult-3.)); // average 4-particle correlations for single event: fIntFlowCorrelationsAllEBE->SetBinContent(11,four1n1n1n1n); fIntFlowCorrelationsAllEBE->SetBinContent(12,four2n1n2n1n); fIntFlowCorrelationsAllEBE->SetBinContent(13,four2n2n2n2n); fIntFlowCorrelationsAllEBE->SetBinContent(14,four3n1n1n1n); fIntFlowCorrelationsAllEBE->SetBinContent(15,four3n1n3n1n); fIntFlowCorrelationsAllEBE->SetBinContent(16,four3n1n2n2n); fIntFlowCorrelationsAllEBE->SetBinContent(17,four4n2n1n1n); // average 4-particle correlations for all events: fIntFlowCorrelationsAllPro->Fill(10.5,four1n1n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)); fIntFlowCorrelationsAllPro->Fill(11.5,four2n1n2n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)); fIntFlowCorrelationsAllPro->Fill(12.5,four2n2n2n2n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)); fIntFlowCorrelationsAllPro->Fill(13.5,four3n1n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)); fIntFlowCorrelationsAllPro->Fill(14.5,four3n1n3n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)); fIntFlowCorrelationsAllPro->Fill(15.5,four3n1n2n2n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)); fIntFlowCorrelationsAllPro->Fill(16.5,four4n2n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)); // store separetately <4> (to be improved: do I really need this?) fIntFlowCorrelationsEBE->SetBinContent(2,four1n1n1n1n); // <4> // to be improved (this can be implemented better): Double_t mWeight4p = 0.; if(!strcmp(fMultiplicityWeight->Data(),"combinations")) { mWeight4p = dMult*(dMult-1.)*(dMult-2.)*(dMult-3.); } else if(!strcmp(fMultiplicityWeight->Data(),"unit")) { mWeight4p = 1.; } else if(!strcmp(fMultiplicityWeight->Data(),"multiplicity")) { mWeight4p = dMult; } fIntFlowEventWeightsForCorrelationsEBE->SetBinContent(2,mWeight4p); // eW_<4> fIntFlowCorrelationsPro->Fill(1.5,four1n1n1n1n,mWeight4p); if(fCalculateCumulantsVsM){fIntFlowCorrelationsVsMPro[1]->Fill(dMult+0.5,four1n1n1n1n,mWeight4p);} // distribution of //f4pDistribution->Fill(four1n1n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)); } // end of if(dMult>3) // 5-particle: Double_t five2n1n1n1n1n = 0.; // Double_t five2n2n2n1n1n = 0.; // Double_t five3n1n2n1n1n = 0.; // Double_t five4n1n1n1n1n = 0.; // if(dMult>4) { five2n1n1n1n1n = (reQ2nQ1nQ1nstarQ1nstarQ1nstar-reQ3nQ1nstarQ1nstarQ1nstar+6.*reQ3nQ2nstarQ1nstar) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) - (reQ2nQ1nQ3nstar+3.*(dMult-6.)*reQ2nQ1nstarQ1nstar+3.*reQ1nQ1nQ2nstar) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) - (2.*(pow(dReQ3n,2.)+pow(dImQ3n,2.)) + 3.*(pow(dReQ1n,2.)+pow(dImQ1n,2.))*(pow(dReQ2n,2.)+pow(dImQ2n,2.)) - 3.*(dMult-4.)*(pow(dReQ2n,2.)+pow(dImQ2n,2.))) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) - 3.*(pow((pow(dReQ1n,2.)+pow(dImQ1n,2.)),2.) - 2.*(2*dMult-5.)*(pow(dReQ1n,2.)+pow(dImQ1n,2.))+2.*dMult*(dMult-4.)) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)); five2n2n2n1n1n = (reQ2nQ2nQ2nstarQ1nstarQ1nstar-reQ4nQ2nstarQ1nstarQ1nstar-2.*reQ2nQ2nQ3nstarQ1nstar) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) + 2.*(reQ4nQ2nstarQ2nstar+4.*reQ3nQ2nstarQ1nstar+reQ3nQ1nQ4nstar) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) + (reQ2nQ2nQ4nstar-2.*(dMult-5.)*reQ2nQ1nstarQ1nstar+2.*reQ1nQ1nQ2nstar) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) - (2.*(pow(dReQ4n,2.)+pow(dImQ4n,2.))+4.*(pow(dReQ3n,2.)+pow(dImQ3n,2.)) + 1.*pow((pow(dReQ2n,2.)+pow(dImQ2n,2.)),2.) - 2.*(3.*dMult-10.)*(pow(dReQ2n,2.)+pow(dImQ2n,2.))) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) - (4.*(pow(dReQ1n,2.)+pow(dImQ1n,2.))*(pow(dReQ2n,2.)+pow(dImQ2n,2.)) - 4.*(dMult-5.)*(pow(dReQ1n,2.)+pow(dImQ1n,2.))+4.*dMult*(dMult-6.)) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)); five4n1n1n1n1n = (reQ4nQ1nstarQ1nstarQ1nstarQ1nstar-6.*reQ4nQ2nstarQ1nstarQ1nstar-4.*reQ3nQ1nstarQ1nstarQ1nstar) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) + (8.*reQ4nQ3nstarQ1nstar+3.*reQ4nQ2nstarQ2nstar+12.*reQ3nQ2nstarQ1nstar+12.*reQ2nQ1nstarQ1nstar) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) - (6.*(pow(dReQ4n,2.)+pow(dImQ4n,2.))+8.*(pow(dReQ3n,2.)+pow(dImQ3n,2.)) + 12.*(pow(dReQ2n,2.)+pow(dImQ2n,2.))+24.*(pow(dReQ1n,2.)+pow(dImQ1n,2.))-24.*dMult) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)); five3n1n2n1n1n = (reQ3nQ1nQ2nstarQ1nstarQ1nstar-reQ4nQ2nstarQ1nstarQ1nstar-reQ3nQ1nstarQ1nstarQ1nstar) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) - (reQ3nQ1nQ2nstarQ2nstar-3.*reQ4nQ3nstarQ1nstar-reQ4nQ2nstarQ2nstar) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) - ((2.*dMult-13.)*reQ3nQ2nstarQ1nstar-reQ3nQ1nQ4nstar-9.*reQ2nQ1nstarQ1nstar) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) - (2.*reQ1nQ1nQ2nstar+2.*(pow(dReQ4n,2.)+pow(dImQ4n,2.)) - 2.*(dMult-5.)*(pow(dReQ3n,2.)+pow(dImQ3n,2.))+2.*(pow(dReQ3n,2.) + pow(dImQ3n,2.))*(pow(dReQ1n,2.)+pow(dImQ1n,2.))) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) + (2.*(dMult-6.)*(pow(dReQ2n,2.)+pow(dImQ2n,2.)) - 2.*(pow(dReQ2n,2.)+pow(dImQ2n,2.))*(pow(dReQ1n,2.)+pow(dImQ1n,2.)) - pow((pow(dReQ1n,2.)+pow(dImQ1n,2.)),2.) + 2.*(3.*dMult-11.)*(pow(dReQ1n,2.)+pow(dImQ1n,2.))) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) - 4.*(dMult-6.)/((dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)); // average 5-particle correlations for single event: fIntFlowCorrelationsAllEBE->SetBinContent(19,five2n1n1n1n1n); fIntFlowCorrelationsAllEBE->SetBinContent(20,five2n2n2n1n1n); fIntFlowCorrelationsAllEBE->SetBinContent(21,five3n1n2n1n1n); fIntFlowCorrelationsAllEBE->SetBinContent(22,five4n1n1n1n1n); // average 5-particle correlations for all events: fIntFlowCorrelationsAllPro->Fill(18.5,five2n1n1n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)); fIntFlowCorrelationsAllPro->Fill(19.5,five2n2n2n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)); fIntFlowCorrelationsAllPro->Fill(20.5,five3n1n2n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)); fIntFlowCorrelationsAllPro->Fill(21.5,five4n1n1n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)); } // end of if(dMult>4) // 6-particle: Double_t six1n1n1n1n1n1n = 0.; // Double_t six2n2n1n1n1n1n = 0.; // Double_t six3n1n1n1n1n1n = 0.; // Double_t six2n1n1n2n1n1n = 0.; // if(dMult>5) { six1n1n1n1n1n1n = (pow(pow(dReQ1n,2.)+pow(dImQ1n,2.),3.)+9.*dQ2nQ1nQ2nstarQ1nstar-6.*reQ2nQ1nQ1nstarQ1nstarQ1nstar) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)) + 4.*(reQ3nQ1nstarQ1nstarQ1nstar-3.*reQ3nQ2nstarQ1nstar) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)) + 2.*(9.*(dMult-4.)*reQ2nQ1nstarQ1nstar+2.*(pow(dReQ3n,2.)+pow(dImQ3n,2.))) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)) - 9.*(pow((pow(dReQ1n,2.)+pow(dImQ1n,2.)),2.)+(pow(dReQ2n,2.)+pow(dImQ2n,2.))) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-5.)) + (18.*(pow(dReQ1n,2.)+pow(dImQ1n,2.))) / (dMult*(dMult-1)*(dMult-3)*(dMult-4)) - 6./((dMult-1.)*(dMult-2.)*(dMult-3.)); six2n1n1n2n1n1n = (dQ2nQ1nQ1nQ2nstarQ1nstarQ1nstar-dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.) * (2.*five2n2n2n1n1n+4.*five2n1n1n1n1n+4.*five3n1n2n1n1n+4.*four2n1n2n1n+1.*four1n1n1n1n) - dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(4.*four1n1n1n1n+4.*two1n1n + 2.*three2n1n1n+2.*three2n1n1n+4.*four3n1n1n1n+8.*three2n1n1n+2.*four4n2n1n1n + 4.*four2n1n2n1n+2.*two2n2n+8.*four2n1n2n1n+4.*four3n1n3n1n+8.*three3n2n1n + 4.*four3n1n2n2n+4.*four1n1n1n1n+4.*four2n1n2n1n+1.*four2n2n2n2n) - dMult*(dMult-1.)*(dMult-2.)*(2.*three2n1n1n+8.*two1n1n+4.*two1n1n+2. + 4.*two1n1n+4.*three2n1n1n+2.*two2n2n+4.*three2n1n1n+8.*three3n2n1n + 8.*two2n2n+4.*three4n3n1n+4.*two3n3n+4.*three3n2n1n+4.*two1n1n + 8.*three2n1n1n+4.*two1n1n+4.*three3n2n1n+4.*three2n1n1n+2.*two2n2n + 4.*three3n2n1n+2.*three4n2n2n)-dMult*(dMult-1.) * (4.*two1n1n+4.+4.*two1n1n+2.*two2n2n+1.+4.*two1n1n+4.*two2n2n+4.*two3n3n + 1.+2.*two2n2n+1.*two4n4n)-dMult) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)); // to be improved (direct formula needed) six2n2n1n1n1n1n = (reQ2nQ2nQ1nstarQ1nstarQ1nstarQ1nstar-dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.) * (five4n1n1n1n1n+8.*five2n1n1n1n1n+6.*five2n2n2n1n1n)-dMult*(dMult-1.)*(dMult-2.)*(dMult-3.) * (4.*four3n1n1n1n+6.*four4n2n1n1n+12.*three2n1n1n+12.*four1n1n1n1n+24.*four2n1n2n1n + 4.*four3n1n2n2n+3.*four2n2n2n2n)-dMult*(dMult-1.)*(dMult-2.)*(6.*three2n1n1n+12.*three3n2n1n + 4.*three4n3n1n+3.*three4n2n2n+8.*three2n1n1n+24.*two1n1n+12.*two2n2n+12.*three2n1n1n+8.*three3n2n1n + 1.*three4n2n2n)-dMult*(dMult-1.)*(4.*two1n1n+6.*two2n2n+4.*two3n3n+1.*two4n4n+2.*two2n2n+8.*two1n1n+6.)-dMult) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)); // to be improved (direct formula needed) six3n1n1n1n1n1n = (reQ3nQ1nQ1nstarQ1nstarQ1nstarQ1nstar-dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.) * (five4n1n1n1n1n+4.*five2n1n1n1n1n+6.*five3n1n2n1n1n+4.*four3n1n1n1n) - dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(4.*four3n1n1n1n+6.*four4n2n1n1n+6.*four1n1n1n1n + 12.*three2n1n1n+12.*four2n1n2n1n+6.*four3n1n1n1n+12.*three3n2n1n+4.*four3n1n3n1n+3.*four3n1n2n2n) - dMult*(dMult-1.)*(dMult-2.)*(6.*three2n1n1n+12.*three3n2n1n+4.*three4n3n1n+3.*three4n2n2n+4.*two1n1n + 12.*two1n1n+6.*three2n1n1n+12.*three2n1n1n+4.*three3n2n1n+12.*two2n2n+4.*three3n2n1n+4.*two3n3n+1.*three4n3n1n + 6.*three3n2n1n)-dMult*(dMult-1.)*(4.*two1n1n+6.*two2n2n+4.*two3n3n+1.*two4n4n+1.*two1n1n+4.+6.*two1n1n+4.*two2n2n + 1.*two3n3n)-dMult)/(dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)); // to be improved (direct formula needed) // average 6-particle correlations for single event: fIntFlowCorrelationsAllEBE->SetBinContent(24,six1n1n1n1n1n1n); fIntFlowCorrelationsAllEBE->SetBinContent(25,six2n1n1n2n1n1n); fIntFlowCorrelationsAllEBE->SetBinContent(26,six2n2n1n1n1n1n); fIntFlowCorrelationsAllEBE->SetBinContent(27,six3n1n1n1n1n1n); // average 6-particle correlations for all events: fIntFlowCorrelationsAllPro->Fill(23.5,six1n1n1n1n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)); fIntFlowCorrelationsAllPro->Fill(24.5,six2n1n1n2n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)); fIntFlowCorrelationsAllPro->Fill(25.5,six2n2n1n1n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)); fIntFlowCorrelationsAllPro->Fill(26.5,six3n1n1n1n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)); // store separetately <6> (to be improved: do I really need this?) fIntFlowCorrelationsEBE->SetBinContent(3,six1n1n1n1n1n1n); // <6> // to be improved (this can be implemented better): Double_t mWeight6p = 0.; if(!strcmp(fMultiplicityWeight->Data(),"combinations")) { mWeight6p = dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.); } else if(!strcmp(fMultiplicityWeight->Data(),"unit")) { mWeight6p = 1.; } else if(!strcmp(fMultiplicityWeight->Data(),"multiplicity")) { mWeight6p = dMult; } fIntFlowEventWeightsForCorrelationsEBE->SetBinContent(3,mWeight6p); // eW_<6> fIntFlowCorrelationsPro->Fill(2.5,six1n1n1n1n1n1n,mWeight6p); if(fCalculateCumulantsVsM){fIntFlowCorrelationsVsMPro[2]->Fill(dMult+0.5,six1n1n1n1n1n1n,mWeight6p);} // distribution of //f6pDistribution->Fill(six1n1n1n1n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)); } // end of if(dMult>5) // 7-particle: Double_t seven2n1n1n1n1n1n1n = 0.; // if(dMult>6) { seven2n1n1n1n1n1n1n = (reQ2nQ1nQ1nQ1nstarQ1nstarQ1nstarQ1nstar-dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.) * (2.*six3n1n1n1n1n1n+4.*six1n1n1n1n1n1n+1.*six2n2n1n1n1n1n+6.*six2n1n1n2n1n1n+8.*five2n1n1n1n1n) - dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(1.*five4n1n1n1n1n +8.*five2n1n1n1n1n+8.*four3n1n1n1n + 12.*five3n1n2n1n1n+4.*five2n1n1n1n1n+3.*five2n2n2n1n1n+6.*five2n2n2n1n1n+6.*four1n1n1n1n+24.*four1n1n1n1n + 12.*five2n1n1n1n1n+12.*five2n1n1n1n1n+12.*three2n1n1n+24.*four2n1n2n1n+4.*five3n1n2n1n1n+4.*five2n1n1n1n1n) - dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(4.*four3n1n1n1n+6.*four4n2n1n1n+12.*four1n1n1n1n+24.*three2n1n1n + 24.*four2n1n2n1n+12.*four3n1n1n1n+24.*three3n2n1n+8.*four3n1n3n1n+6.*four3n1n2n2n+6.*three2n1n1n+12.*four1n1n1n1n + 12.*four2n1n2n1n+6.*three2n1n1n+12.*four2n1n2n1n+4.*four3n1n2n2n+3.*four2n2n2n2n+4.*four1n1n1n1n+6.*three2n1n1n + 24.*two1n1n+24.*four1n1n1n1n+4.*four3n1n1n1n+24.*two1n1n+24.*three2n1n1n+12.*two2n2n+24.*three2n1n1n+12.*four2n1n2n1n + 8.*three3n2n1n+8.*four2n1n2n1n+1.*four4n2n1n1n)-dMult*(dMult-1.)*(dMult-2.)*(6.*three2n1n1n+1.*three2n1n1n+8.*two1n1n + 12.*three3n2n1n+24.*two1n1n+12.*three2n1n1n+4.*three2n1n1n+8.*two1n1n+4.*three4n3n1n+24.*three2n1n1n+8.*three3n2n1n + 12.*two1n1n+12.*two1n1n+3.*three4n2n2n+24.*two2n2n+6.*two2n2n+12.+12.*three3n2n1n+8.*two3n3n+12.*three2n1n1n+24.*two1n1n + 4.*three3n2n1n+8.*three3n2n1n+2.*three4n3n1n+12.*two1n1n+8.*three2n1n1n+4.*three2n1n1n+2.*three3n2n1n+6.*two2n2n+8.*two2n2n + 1.*three4n2n2n+4.*three3n2n1n+6.*three2n1n1n)-dMult*(dMult-1.)*(4.*two1n1n+2.*two1n1n+6.*two2n2n+8.+1.*two2n2n+4.*two3n3n + 12.*two1n1n+4.*two1n1n+1.*two4n4n+8.*two2n2n+6.+2.*two3n3n+4.*two1n1n+1.*two2n2n)-dMult) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)*(dMult-6.)); // to be improved (direct formula needed) // average 7-particle correlations for single event: fIntFlowCorrelationsAllEBE->SetBinContent(29,seven2n1n1n1n1n1n1n); // average 7-particle correlations for all events: fIntFlowCorrelationsAllPro->Fill(28.5,seven2n1n1n1n1n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)*(dMult-6.)); } // end of if(dMult>6) // 8-particle: Double_t eight1n1n1n1n1n1n1n1n = 0.; // if(dMult>7) { eight1n1n1n1n1n1n1n1n = (pow(pow(dReQ1n,2.)+pow(dImQ1n,2.),4.)-dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)*(dMult-6.) * (12.*seven2n1n1n1n1n1n1n+16.*six1n1n1n1n1n1n)-dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.) * (8.*six3n1n1n1n1n1n+48.*six1n1n1n1n1n1n+6.*six2n2n1n1n1n1n+96.*five2n1n1n1n1n+72.*four1n1n1n1n+36.*six2n1n1n2n1n1n) - dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(2.*five4n1n1n1n1n+32.*five2n1n1n1n1n+36.*four1n1n1n1n + 32.*four3n1n1n1n+48.*five2n1n1n1n1n+48.*five3n1n2n1n1n+144.*five2n1n1n1n1n+288.*four1n1n1n1n+36.*five2n2n2n1n1n + 144.*three2n1n1n+96.*two1n1n+144.*four2n1n2n1n)-dMult*(dMult-1.)*(dMult-2.)*(dMult-3.) * (8.*four3n1n1n1n+48.*four1n1n1n1n+12.*four4n2n1n1n+96.*four2n1n2n1n+96.*three2n1n1n+72.*three2n1n1n+144.*two1n1n + 16.*four3n1n3n1n+48.*four3n1n1n1n+144.*four1n1n1n1n+72.*four1n1n1n1n+96.*three3n2n1n+24.*four3n1n2n2n+144.*four2n1n2n1n + 288.*two1n1n+288.*three2n1n1n+9.*four2n2n2n2n+72.*two2n2n+24.)-dMult*(dMult-1.)*(dMult-2.)*(12.*three2n1n1n+16.*two1n1n + 24.*three3n2n1n+48.*three2n1n1n+96.*two1n1n+8.*three4n3n1n+32.*three3n2n1n+96.*three2n1n1n+144.*two1n1n+6.*three4n2n2n + 96.*two2n2n+36.*two2n2n+72.+48.*three3n2n1n+16.*two3n3n+72.*three2n1n1n+144.*two1n1n)-dMult*(dMult-1.)*(8.*two1n1n + 12.*two2n2n+16.+8.*two3n3n+48.*two1n1n+1.*two4n4n+16.*two2n2n+18.)-dMult) / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)*(dMult-6.)*(dMult-7.)); // to be improved (direct formula needed) // average 8-particle correlations for single event: fIntFlowCorrelationsAllEBE->SetBinContent(31,eight1n1n1n1n1n1n1n1n); // average 8-particle correlations for all events: fIntFlowCorrelationsAllPro->Fill(30.5,eight1n1n1n1n1n1n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)*(dMult-6.)*(dMult-7.)); // store separetately <8> (to be improved: do I really need this?) fIntFlowCorrelationsEBE->SetBinContent(4,eight1n1n1n1n1n1n1n1n); // <8> // to be improved (this can be implemented better): Double_t mWeight8p = 0.; if(!strcmp(fMultiplicityWeight->Data(),"combinations")) { mWeight8p = dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)*(dMult-6.)*(dMult-7.); } else if(!strcmp(fMultiplicityWeight->Data(),"unit")) { mWeight8p = 1.; } else if(!strcmp(fMultiplicityWeight->Data(),"multiplicity")) { mWeight8p = dMult; } fIntFlowEventWeightsForCorrelationsEBE->SetBinContent(4,mWeight8p); // eW_<8> fIntFlowCorrelationsPro->Fill(3.5,eight1n1n1n1n1n1n1n1n,mWeight8p); if(fCalculateCumulantsVsM){fIntFlowCorrelationsVsMPro[3]->Fill(dMult+0.5,eight1n1n1n1n1n1n1n1n,mWeight8p);} // distribution of //f8pDistribution->Fill(eight1n1n1n1n1n1n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)*(dMult-6.)*(dMult-7.)); } // end of if(dMult>7) } // end of AliFlowAnalysisWithQCumulants::CalculateIntFlowCorrelations() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CalculateIntFlowProductOfCorrelations() { // Calculate averages of products of correlations for integrated flow. // multiplicity: Double_t dMult = (*fSMpk)(0,0); Int_t counter = 0; for(Int_t ci1=1;ci1<4;ci1++) { for(Int_t ci2=ci1+1;ci2<=4;ci2++) { fIntFlowProductOfCorrelationsPro->Fill(0.5+counter, fIntFlowCorrelationsEBE->GetBinContent(ci1)* fIntFlowCorrelationsEBE->GetBinContent(ci2), fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(ci1)* fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(ci2)); // products versus multiplicity: // [0=<<2><4>>,1=<<2><6>>,2=<<2><8>>,3=<<4><6>>,4=<<4><8>>,5=<<6><8>>] if(fCalculateCumulantsVsM) { fIntFlowProductOfCorrelationsVsMPro[counter]->Fill(dMult+0.5, // to be improved: dMult => sum of weights ? fIntFlowCorrelationsEBE->GetBinContent(ci1)* fIntFlowCorrelationsEBE->GetBinContent(ci2), fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(ci1)* fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(ci2)); } // end of if(fCalculateCumulantsVsM) counter++; } } } // end of AliFlowAnalysisWithQCumulants::CalculateIntFlowProductOfCorrelations() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CalculateIntFlowProductOfCorrectionTermsForNUA() { // Calculate averages of products of correction terms for NUA. // a) Binning of fIntFlowProductOfCorrectionTermsForNUAPro is organized as follows: // 1st bin: <<2>> // 2nd bin: <<2>> // 3rd bin: <> // 4th bin: <<2>> // 5th bin: <<2>> // 6th bin: <<2>> // 7th bin: <<2>> // 8th bin: <<4>> // 9th bin: <<4>> // 10th bin: <<4>> // 11th bin: <<4>> // 12th bin: <<4>> // 13th bin: <<4>> // 14th bin: <> // 15th bin: <> // 16th bin: <> // 17th bin: <> // 18th bin: <> // 19th bin: <> // 20th bin: <> // 21st bin: <> // 22nd bin: <> // 23rd bin: <> // 24th bin: <> // 25th bin: <> // 26th bin: <> // 27th bin: <> // <<2>>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(0.5, fIntFlowCorrelationsEBE->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(1), fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1)); // <<2>>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(1.5, fIntFlowCorrelationsEBE->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(1), fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1)); // <>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(2.5, fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(1), fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1)); // <<2>>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(3.5, fIntFlowCorrelationsEBE->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(2), fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2)); // <<2>>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(4.5, fIntFlowCorrelationsEBE->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(2), fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2)); // <<2>>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(5.5, fIntFlowCorrelationsEBE->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(3), fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)); // <<2>>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(6.5, fIntFlowCorrelationsEBE->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(3), fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); // <<4>>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(7.5, fIntFlowCorrelationsEBE->GetBinContent(2)*fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(1), fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1)); // <<4>>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(8.5, fIntFlowCorrelationsEBE->GetBinContent(2)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(1), fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1)); // <<4>>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(9.5, fIntFlowCorrelationsEBE->GetBinContent(2)*fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(2), fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2)); // <<4>>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(10.5, fIntFlowCorrelationsEBE->GetBinContent(2)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(2), fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2)); // <<4>>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(11.5, fIntFlowCorrelationsEBE->GetBinContent(2)*fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(3), fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)); // <<4>>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(12.5, fIntFlowCorrelationsEBE->GetBinContent(2)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(3), fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); // <>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(13.5, fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(2), fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2)); // <>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(14.5, fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(2), fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2)); // <>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(15.5, fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(3), fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)); // <>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(16.5, fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(3), fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); // <>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(17.5, fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(2), fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2)); // <>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(18.5, fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(2), fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2)); // <>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(19.5, fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(3), fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)); // <>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(20.5, fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(3), fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); // <>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(21.5, fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(2)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(2), fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2)); // <>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(22.5, fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(2)*fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(3), fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)); // <>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(23.5, fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(2)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(3), fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); // <>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(24.5, fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(2)*fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(3), fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)); // <>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(25.5, fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(2)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(3), fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); // <>: fIntFlowProductOfCorrectionTermsForNUAPro->Fill(26.5, fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(3)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(3), fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3) *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); } // end of AliFlowAnalysisWithQCumulants::CalculateIntFlowProductOfCorrectionTermsForNUA() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CalculateCovariancesIntFlow() { // a) Calculate unbiased estimators Cov(<2>,<4>), Cov(<2>,<6>), Cov(<2>,<8>), Cov(<4>,<6>), Cov(<4>,<8>) and Cov(<6>,<8>) // for covariances V_(<2>,<4>), V_(<2>,<6>), V_(<2>,<8>), V_(<4>,<6>), V_(<4>,<8>) and V_(<6>,<8>). // b) Store in histogram fIntFlowCovariances for instance the following: // // Cov(<2>,<4>) * (sum_{i=1}^{N} w_{<2>}_i w_{<4>}_i )/[(sum_{i=1}^{N} w_{<2>}_i) * (sum_{j=1}^{N} w_{<4>}_j)] // // where N is the number of events, w_{<2>} is event weight for <2> and w_{<4>} is event weight for <4>. // c) Binning of fIntFlowCovariances is organized as follows: // // 1st bin: Cov(<2>,<4>) * (sum_{i=1}^{N} w_{<2>}_i w_{<4>}_i )/[(sum_{i=1}^{N} w_{<2>}_i) * (sum_{j=1}^{N} w_{<4>}_j)] // 2nd bin: Cov(<2>,<6>) * (sum_{i=1}^{N} w_{<2>}_i w_{<6>}_i )/[(sum_{i=1}^{N} w_{<2>}_i) * (sum_{j=1}^{N} w_{<6>}_j)] // 3rd bin: Cov(<2>,<8>) * (sum_{i=1}^{N} w_{<2>}_i w_{<8>}_i )/[(sum_{i=1}^{N} w_{<2>}_i) * (sum_{j=1}^{N} w_{<8>}_j)] // 4th bin: Cov(<4>,<6>) * (sum_{i=1}^{N} w_{<4>}_i w_{<6>}_i )/[(sum_{i=1}^{N} w_{<4>}_i) * (sum_{j=1}^{N} w_{<6>}_j)] // 5th bin: Cov(<4>,<8>) * (sum_{i=1}^{N} w_{<4>}_i w_{<8>}_i )/[(sum_{i=1}^{N} w_{<4>}_i) * (sum_{j=1}^{N} w_{<8>}_j)] // 6th bin: Cov(<6>,<8>) * (sum_{i=1}^{N} w_{<6>}_i w_{<8>}_i )/[(sum_{i=1}^{N} w_{<6>}_i) * (sum_{j=1}^{N} w_{<8>}_j)] // // Average 2-, 4-, 6- and 8-particle correlations for all events: Double_t correlation[4] = {0.}; for(Int_t ci=0;ci<4;ci++) { correlation[ci] = fIntFlowCorrelationsPro->GetBinContent(ci+1); } // Average products of 2-, 4-, 6- and 8-particle correlations: Double_t productOfCorrelations[4][4] = {{0.}}; Int_t productOfCorrelationsLabel = 1; // Denominators in the expressions for the unbiased estimator for covariance: Double_t denominator[4][4] = {{0.}}; Int_t sumOfProductOfEventWeightsLabel1 = 1; // Weight dependent prefactor which multiply unbiased estimators for covariances: Double_t wPrefactor[4][4] = {{0.}}; Int_t sumOfProductOfEventWeightsLabel2 = 1; for(Int_t c1=0;c1<4;c1++) { for(Int_t c2=c1+1;c2<4;c2++) { productOfCorrelations[c1][c2] = fIntFlowProductOfCorrelationsPro->GetBinContent(productOfCorrelationsLabel); if(TMath::Abs(fIntFlowSumOfEventWeights[0]->GetBinContent(c1+1)) > 1.e-44 && TMath::Abs(fIntFlowSumOfEventWeights[0]->GetBinContent(c2+1)) > 1.e-44) { denominator[c1][c2] = 1.-(fIntFlowSumOfProductOfEventWeights->GetBinContent(sumOfProductOfEventWeightsLabel1)) / (fIntFlowSumOfEventWeights[0]->GetBinContent(c1+1) * fIntFlowSumOfEventWeights[0]->GetBinContent(c2+1)); wPrefactor[c1][c2] = fIntFlowSumOfProductOfEventWeights->GetBinContent(sumOfProductOfEventWeightsLabel2) / (fIntFlowSumOfEventWeights[0]->GetBinContent(c1+1) * fIntFlowSumOfEventWeights[0]->GetBinContent(c2+1)); } productOfCorrelationsLabel++; // to be improved - do I need here all 3 counters? sumOfProductOfEventWeightsLabel1++; sumOfProductOfEventWeightsLabel2++; } // end of for(Int_t c2=c1+1;c2<4;c2++) } // end of for(Int_t c1=0;c1<4;c1++) Int_t covarianceLabel = 1; for(Int_t c1=0;c1<4;c1++) { for(Int_t c2=c1+1;c2<4;c2++) { if(TMath::Abs(denominator[c1][c2]) > 1.e-44) { // Covariances: Double_t cov = (productOfCorrelations[c1][c2]-correlation[c1]*correlation[c2])/denominator[c1][c2]; // Covariances multiplied with weight dependent prefactor: Double_t wCov = cov * wPrefactor[c1][c2]; fIntFlowCovariances->SetBinContent(covarianceLabel,wCov); } covarianceLabel++; } // end of for(Int_t c2=c1+1;c2<4;c2++) } // end of for(Int_t c1=0;c1<4;c1++) // Versus multiplicity: if(!fCalculateCumulantsVsM){return;} Int_t nBins = fIntFlowCorrelationsVsMPro[0]->GetNbinsX(); // to be improved (hardwired 0) for(Int_t b=1;b<=nBins;b++) { // Average 2-, 4-, 6- and 8-particle correlations for all events: Double_t correlationVsM[4] = {0.}; for(Int_t ci=0;ci<4;ci++) { correlationVsM[ci] = fIntFlowCorrelationsVsMPro[ci]->GetBinContent(b); } // end of for(Int_t ci=0;ci<4;ci++) // Average products of 2-, 4-, 6- and 8-particle correlations: Double_t productOfCorrelationsVsM[4][4] = {{0.}}; Int_t productOfCorrelationsLabelVsM = 1; // Denominators in the expressions for the unbiased estimator for covariance: Double_t denominatorVsM[4][4] = {{0.}}; Int_t sumOfProductOfEventWeightsLabel1VsM = 1; // Weight dependent prefactor which multiply unbiased estimators for covariances: Double_t wPrefactorVsM[4][4] = {{0.}}; Int_t sumOfProductOfEventWeightsLabel2VsM = 1; for(Int_t c1=0;c1<4;c1++) { for(Int_t c2=c1+1;c2<4;c2++) { productOfCorrelationsVsM[c1][c2] = fIntFlowProductOfCorrelationsVsMPro[productOfCorrelationsLabelVsM-1]->GetBinContent(b); if(TMath::Abs(fIntFlowSumOfEventWeightsVsM[c1][0]->GetBinContent(b)) > 1.e-44 && TMath::Abs(fIntFlowSumOfEventWeightsVsM[c2][0]->GetBinContent(b)) > 1.e-44) { denominatorVsM[c1][c2] = 1.-(fIntFlowSumOfProductOfEventWeightsVsM[sumOfProductOfEventWeightsLabel1VsM-1]->GetBinContent(b)) / (fIntFlowSumOfEventWeightsVsM[c1][0]->GetBinContent(b) * fIntFlowSumOfEventWeightsVsM[c2][0]->GetBinContent(b)); wPrefactorVsM[c1][c2] = fIntFlowSumOfProductOfEventWeightsVsM[sumOfProductOfEventWeightsLabel2VsM-1]->GetBinContent(b) / (fIntFlowSumOfEventWeightsVsM[c1][0]->GetBinContent(b) * fIntFlowSumOfEventWeightsVsM[c2][0]->GetBinContent(b)); } productOfCorrelationsLabelVsM++; sumOfProductOfEventWeightsLabel1VsM++; sumOfProductOfEventWeightsLabel2VsM++; } // end of for(Int_t c1=0;c1<4;c1++) } // end of for(Int_t c2=c1+1;c2<4;c2++) Int_t covarianceLabelVsM = 1; for(Int_t c1=0;c1<4;c1++) { for(Int_t c2=c1+1;c2<4;c2++) { if(TMath::Abs(denominatorVsM[c1][c2]) > 1.e-44) { // Covariances: Double_t covVsM = (productOfCorrelationsVsM[c1][c2]-correlationVsM[c1]*correlationVsM[c2])/denominatorVsM[c1][c2]; // Covariances multiplied with weight dependent prefactor: Double_t wCovVsM = covVsM * wPrefactorVsM[c1][c2]; fIntFlowCovariancesVsM[covarianceLabelVsM-1]->SetBinContent(b,wCovVsM); } covarianceLabelVsM++; } // end of for(Int_t c2=c1+1;c2<4;c2++) } // end of for(Int_t c1=0;c1<4;c1++) } // end of for(Int_t b=1;b<=nBins;b++) } // end of AliFlowAnalysisWithQCumulants::CalculateCovariancesIntFlow() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CalculateCovariancesNUAIntFlow() { // a) Calculate unbiased estimators Cov(*,*) for true covariances V_(*,*) for NUA terms. // b) Store in histogram fIntFlowCovariancesNUA for instance the following: // // Cov(<2>,) * (sum_{i=1}^{N} w_{<2>}_i w_{}_i )/[(sum_{i=1}^{N} w_{<2>}_i) * (sum_{j=1}^{N} w_{}_j)] // // where N is the number of events, w_{<2>} is event weight for <2> and w_{} is event weight for . // c) Binning of fIntFlowCovariancesNUA is organized as follows: // // 1st bin: Cov(<2>,) * (sum_{i=1}^{N} w_{<2>}_i w_{}_i )/[(sum_{i=1}^{N} w_{<2>}_i) * (sum_{j=1}^{N} w_{}_j)] // 2nd bin: Cov(<2>,) * (sum_{i=1}^{N} w_{<2>}_i w_{}_i )/[(sum_{i=1}^{N} w_{<2>}_i) * (sum_{j=1}^{N} w_{}_j)] // 3rd bin: Cov(,) * (sum_{i=1}^{N} w_{}_i w_{}_i )/[(sum_{i=1}^{N} w_{}_i) * (sum_{j=1}^{N} w_{}_j)] // ... // Cov(<2>,): Double_t product1 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(1); // <<2>> Double_t term1st1 = fIntFlowCorrelationsPro->GetBinContent(1); // <<2>> Double_t term2nd1 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(1); // <> Double_t sumOfW1st1 = fIntFlowSumOfEventWeights[0]->GetBinContent(1); // W_{<2>} Double_t sumOfW2nd1 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(1); // W_{} Double_t sumOfWW1 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(1); // W_{<2>} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator1 = product1 - term1st1*term2nd1; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator1 = 1.-sumOfWW1/(sumOfW1st1*sumOfW2nd1); // covariance: Double_t covariance1 = numerator1/denominator1; // weight dependent prefactor for covariance: Double_t wPrefactor1 = sumOfWW1/(sumOfW1st1*sumOfW2nd1); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(1,wPrefactor1*covariance1); // Cov(<2>,): Double_t product2 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(2); // <<2>> Double_t term1st2 = fIntFlowCorrelationsPro->GetBinContent(1); // <<2>> Double_t term2nd2 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(1); // <> Double_t sumOfW1st2 = fIntFlowSumOfEventWeights[0]->GetBinContent(1); // W_{<2>} Double_t sumOfW2nd2 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(1); // W_{} Double_t sumOfWW2 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(2); // W_{<2>} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator2 = product2 - term1st2*term2nd2; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator2 = 1.-sumOfWW2/(sumOfW1st2*sumOfW2nd2); // covariance: Double_t covariance2 = numerator2/denominator2; // weight dependent prefactor for covariance: Double_t wPrefactor2 = sumOfWW2/(sumOfW1st2*sumOfW2nd2); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(2,wPrefactor2*covariance2); // Cov(,): Double_t product3 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(3); // <> Double_t term1st3 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(1); // <> Double_t term2nd3 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(1); // <> Double_t sumOfW1st3 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(1); // W_{} Double_t sumOfW2nd3 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(1); // W_{} Double_t sumOfWW3 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(3); // W_{} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator3 = product3 - term1st3*term2nd3; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator3 = 1.-sumOfWW3/(sumOfW1st3*sumOfW2nd3); // covariance: Double_t covariance3 = numerator3/denominator3; // weight dependent prefactor for covariance: Double_t wPrefactor3 = sumOfWW3/(sumOfW1st3*sumOfW2nd3); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(3,wPrefactor3*covariance3); // Cov(<2>,): Double_t product4 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(4); // <<2>> Double_t term1st4 = fIntFlowCorrelationsPro->GetBinContent(1); // <<2>> Double_t term2nd4 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(2); // <> Double_t sumOfW1st4 = fIntFlowSumOfEventWeights[0]->GetBinContent(1); // W_{<2>} Double_t sumOfW2nd4 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(2); // W_{} Double_t sumOfWW4 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(4); // W_{<2>} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator4 = product4 - term1st4*term2nd4; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator4 = 1.-sumOfWW4/(sumOfW1st4*sumOfW2nd4); // covariance: Double_t covariance4 = numerator4/denominator4; // weight dependent prefactor for covariance: Double_t wPrefactor4 = sumOfWW4/(sumOfW1st4*sumOfW2nd4); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(4,wPrefactor4*covariance4); // Cov(<2>,): Double_t product5 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(5); // <<2>> Double_t term1st5 = fIntFlowCorrelationsPro->GetBinContent(1); // <<2>> Double_t term2nd5 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(2); // <> Double_t sumOfW1st5 = fIntFlowSumOfEventWeights[0]->GetBinContent(1); // W_{<2>} Double_t sumOfW2nd5 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(2); // W_{} Double_t sumOfWW5 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(5); // W_{<2>} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator5 = product5 - term1st5*term2nd5; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator5 = 1.-sumOfWW5/(sumOfW1st5*sumOfW2nd5); // covariance: Double_t covariance5 = numerator5/denominator5; // weight dependent prefactor for covariance: Double_t wPrefactor5 = sumOfWW5/(sumOfW1st5*sumOfW2nd5); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(5,wPrefactor5*covariance5); // Cov(<2>,): Double_t product6 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(6); // <<2>> Double_t term1st6 = fIntFlowCorrelationsPro->GetBinContent(1); // <<2>> Double_t term2nd6 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(3); // <> Double_t sumOfW1st6 = fIntFlowSumOfEventWeights[0]->GetBinContent(1); // W_{<2>} Double_t sumOfW2nd6 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(3); // W_{} Double_t sumOfWW6 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(6); // W_{<2>} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator6 = product6 - term1st6*term2nd6; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator6 = 1.-sumOfWW6/(sumOfW1st6*sumOfW2nd6); // covariance: Double_t covariance6 = numerator6/denominator6; // weight dependent prefactor for covariance: Double_t wPrefactor6 = sumOfWW6/(sumOfW1st6*sumOfW2nd6); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(6,wPrefactor6*covariance6); // Cov(<2>,): Double_t product7 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(7); // <<2>> Double_t term1st7 = fIntFlowCorrelationsPro->GetBinContent(1); // <<2>> Double_t term2nd7 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(3); // <> Double_t sumOfW1st7 = fIntFlowSumOfEventWeights[0]->GetBinContent(1); // W_{<2>} Double_t sumOfW2nd7 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(3); // W_{} Double_t sumOfWW7 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(7); // W_{<2>} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator7 = product7 - term1st7*term2nd7; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator7 = 1.-sumOfWW7/(sumOfW1st7*sumOfW2nd7); // covariance: Double_t covariance7 = numerator7/denominator7; // weight dependent prefactor for covariance: Double_t wPrefactor7 = sumOfWW7/(sumOfW1st7*sumOfW2nd7); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(7,wPrefactor7*covariance7); // Cov(<4>,): Double_t product8 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(8); // <<4>> Double_t term1st8 = fIntFlowCorrelationsPro->GetBinContent(2); // <<4>> Double_t term2nd8 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(1); // <> Double_t sumOfW1st8 = fIntFlowSumOfEventWeights[0]->GetBinContent(2); // W_{<4>} Double_t sumOfW2nd8 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(1); // W_{} Double_t sumOfWW8 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(8); // W_{<4>} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator8 = product8 - term1st8*term2nd8; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator8 = 1.-sumOfWW8/(sumOfW1st8*sumOfW2nd8); // covariance: Double_t covariance8 = numerator8/denominator8; // weight dependent prefactor for covariance: Double_t wPrefactor8 = sumOfWW8/(sumOfW1st8*sumOfW2nd8); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(8,wPrefactor8*covariance8); // Cov(<4>,): Double_t product9 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(9); // <<4>> Double_t term1st9 = fIntFlowCorrelationsPro->GetBinContent(2); // <<4>> Double_t term2nd9 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(1); // <> Double_t sumOfW1st9 = fIntFlowSumOfEventWeights[0]->GetBinContent(2); // W_{<4>} Double_t sumOfW2nd9 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(1); // W_{} Double_t sumOfWW9 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(9); // W_{<4>} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator9 = product9 - term1st9*term2nd9; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator9 = 1.-sumOfWW9/(sumOfW1st9*sumOfW2nd9); // covariance: Double_t covariance9 = numerator9/denominator9; // weight dependent prefactor for covariance: Double_t wPrefactor9 = sumOfWW9/(sumOfW1st9*sumOfW2nd9); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(9,wPrefactor9*covariance9); // Cov(<4>,): Double_t product10 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(10); // <<4>> Double_t term1st10 = fIntFlowCorrelationsPro->GetBinContent(2); // <<4>> Double_t term2nd10 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(2); // <> Double_t sumOfW1st10 = fIntFlowSumOfEventWeights[0]->GetBinContent(2); // W_{<4>} Double_t sumOfW2nd10 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(2); // W_{} Double_t sumOfWW10 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(10); // W_{<4>} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator10 = product10 - term1st10*term2nd10; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator10 = 1.-sumOfWW10/(sumOfW1st10*sumOfW2nd10); // covariance: Double_t covariance10 = numerator10/denominator10; // weight dependent prefactor for covariance: Double_t wPrefactor10 = sumOfWW10/(sumOfW1st10*sumOfW2nd10); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(10,wPrefactor10*covariance10); // Cov(<4>,): Double_t product11 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(11); // <<4>> Double_t term1st11 = fIntFlowCorrelationsPro->GetBinContent(2); // <<4>> Double_t term2nd11 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(2); // <> Double_t sumOfW1st11 = fIntFlowSumOfEventWeights[0]->GetBinContent(2); // W_{<4>} Double_t sumOfW2nd11 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(2); // W_{} Double_t sumOfWW11 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(11); // W_{<4>} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator11 = product11 - term1st11*term2nd11; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator11 = 1.-sumOfWW11/(sumOfW1st11*sumOfW2nd11); // covariance: Double_t covariance11 = numerator11/denominator11; // weight dependent prefactor for covariance: Double_t wPrefactor11 = sumOfWW11/(sumOfW1st11*sumOfW2nd11); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(11,wPrefactor11*covariance11); // Cov(<4>,): Double_t product12 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(12); // <<4>> Double_t term1st12 = fIntFlowCorrelationsPro->GetBinContent(2); // <<4>> Double_t term2nd12 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(3); // <> Double_t sumOfW1st12 = fIntFlowSumOfEventWeights[0]->GetBinContent(2); // W_{<4>} Double_t sumOfW2nd12 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(3); // W_{} Double_t sumOfWW12 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(12); // W_{<4>} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator12 = product12 - term1st12*term2nd12; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator12 = 1.-sumOfWW12/(sumOfW1st12*sumOfW2nd12); // covariance: Double_t covariance12 = numerator12/denominator12; // weight dependent prefactor for covariance: Double_t wPrefactor12 = sumOfWW12/(sumOfW1st12*sumOfW2nd12); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(12,wPrefactor12*covariance12); // Cov(<4>,): Double_t product13 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(13); // <<4>> Double_t term1st13 = fIntFlowCorrelationsPro->GetBinContent(2); // <<4>> Double_t term2nd13 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(3); // <> Double_t sumOfW1st13 = fIntFlowSumOfEventWeights[0]->GetBinContent(2); // W_{<4>} Double_t sumOfW2nd13 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(3); // W_{} Double_t sumOfWW13 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(13); // W_{<4>} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator13 = product13 - term1st13*term2nd13; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator13 = 1.-sumOfWW13/(sumOfW1st13*sumOfW2nd13); // covariance: Double_t covariance13 = numerator13/denominator13; // weight dependent prefactor for covariance: Double_t wPrefactor13 = sumOfWW13/(sumOfW1st13*sumOfW2nd13); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(13,wPrefactor13*covariance13); // Cov(,): Double_t product14 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(14); // <> Double_t term1st14 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(1); // <> Double_t term2nd14 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(2); // <> Double_t sumOfW1st14 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(1); // W_{} Double_t sumOfW2nd14 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(2); // W_{} Double_t sumOfWW14 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(14); // W_{} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator14 = product14 - term1st14*term2nd14; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator14 = 1.-sumOfWW14/(sumOfW1st14*sumOfW2nd14); // covariance: Double_t covariance14 = numerator14/denominator14; // weight dependent prefactor for covariance: Double_t wPrefactor14 = sumOfWW14/(sumOfW1st14*sumOfW2nd14); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(14,wPrefactor14*covariance14); // Cov(,): Double_t product15 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(15); // <> Double_t term1st15 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(1); // <> Double_t term2nd15 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(2); // <> Double_t sumOfW1st15 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(1); // W_{} Double_t sumOfW2nd15 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(2); // W_{} Double_t sumOfWW15 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(15); // W_{} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator15 = product15 - term1st15*term2nd15; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator15 = 1.-sumOfWW15/(sumOfW1st15*sumOfW2nd15); // covariance: Double_t covariance15 = numerator15/denominator15; // weight dependent prefactor for covariance: Double_t wPrefactor15 = sumOfWW15/(sumOfW1st15*sumOfW2nd15); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(15,wPrefactor15*covariance15); // Cov(,): Double_t product16 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(16); // <> Double_t term1st16 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(1); // <> Double_t term2nd16 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(3); // <> Double_t sumOfW1st16 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(1); // W_{} Double_t sumOfW2nd16 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(3); // W_{} Double_t sumOfWW16 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(16); // W_{} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator16 = product16 - term1st16*term2nd16; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator16 = 1.-sumOfWW16/(sumOfW1st16*sumOfW2nd16); // covariance: Double_t covariance16 = numerator16/denominator16; // weight dependent prefactor for covariance: Double_t wPrefactor16 = sumOfWW16/(sumOfW1st16*sumOfW2nd16); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(16,wPrefactor16*covariance16); // Cov(,): Double_t product17 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(17); // <> Double_t term1st17 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(1); // <> Double_t term2nd17 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(3); // <> Double_t sumOfW1st17 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(1); // W_{} Double_t sumOfW2nd17 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(3); // W_{} Double_t sumOfWW17 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(17); // W_{} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator17 = product17 - term1st17*term2nd17; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator17 = 1.-sumOfWW17/(sumOfW1st17*sumOfW2nd17); // covariance: Double_t covariance17 = numerator17/denominator17; // weight dependent prefactor for covariance: Double_t wPrefactor17 = sumOfWW17/(sumOfW1st17*sumOfW2nd17); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(17,wPrefactor17*covariance17); // Cov(,): Double_t product18 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(18); // <> Double_t term1st18 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(1); // <> Double_t term2nd18 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(2); // <> Double_t sumOfW1st18 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(1); // W_{} Double_t sumOfW2nd18 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(2); // W_{} Double_t sumOfWW18 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(18); // W_{} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator18 = product18 - term1st18*term2nd18; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator18 = 1.-sumOfWW18/(sumOfW1st18*sumOfW2nd18); // covariance: Double_t covariance18 = numerator18/denominator18; // weight dependent prefactor for covariance: Double_t wPrefactor18 = sumOfWW18/(sumOfW1st18*sumOfW2nd18); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(18,wPrefactor18*covariance18); // Cov(,): Double_t product19 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(19); // <> Double_t term1st19 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(1); // <> Double_t term2nd19 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(2); // <> Double_t sumOfW1st19 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(1); // W_{} Double_t sumOfW2nd19 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(2); // W_{} Double_t sumOfWW19 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(19); // W_{} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator19 = product19 - term1st19*term2nd19; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator19 = 1.-sumOfWW19/(sumOfW1st19*sumOfW2nd19); // covariance: Double_t covariance19 = numerator19/denominator19; // weight dependent prefactor for covariance: Double_t wPrefactor19 = sumOfWW19/(sumOfW1st19*sumOfW2nd19); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(19,wPrefactor19*covariance19); // Cov(,): Double_t product20 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(20); // <> Double_t term1st20 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(1); // <> Double_t term2nd20 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(3); // <> Double_t sumOfW1st20 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(1); // W_{} Double_t sumOfW2nd20 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(3); // W_{} Double_t sumOfWW20 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(20); // W_{} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator20 = product20 - term1st20*term2nd20; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator20 = 1.-sumOfWW20/(sumOfW1st20*sumOfW2nd20); // covariance: Double_t covariance20 = numerator20/denominator20; // weight dependent prefactor for covariance: Double_t wPrefactor20 = sumOfWW20/(sumOfW1st20*sumOfW2nd20); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(20,wPrefactor20*covariance20); // Cov(,): Double_t product21 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(21); // <> Double_t term1st21 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(1); // <> Double_t term2nd21 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(3); // <> Double_t sumOfW1st21 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(1); // W_{} Double_t sumOfW2nd21 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(3); // W_{} Double_t sumOfWW21 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(21); // W_{} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator21 = product21 - term1st21*term2nd21; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator21 = 1.-sumOfWW21/(sumOfW1st21*sumOfW2nd21); // covariance: Double_t covariance21 = numerator21/denominator21; // weight dependent prefactor for covariance: Double_t wPrefactor21 = sumOfWW21/(sumOfW1st21*sumOfW2nd21); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(21,wPrefactor21*covariance21); // Cov(,): Double_t product22 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(22); // <> Double_t term1st22 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(2); // <> Double_t term2nd22 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(2); // <> Double_t sumOfW1st22 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(2); // W_{} Double_t sumOfW2nd22 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(2); // W_{} Double_t sumOfWW22 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(22); // W_{} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator22 = product22 - term1st22*term2nd22; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator22 = 1.-sumOfWW22/(sumOfW1st22*sumOfW2nd22); // covariance: Double_t covariance22 = numerator22/denominator22; // weight dependent prefactor for covariance: Double_t wPrefactor22 = sumOfWW22/(sumOfW1st22*sumOfW2nd22); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(22,wPrefactor22*covariance22); // Cov(,): Double_t product23 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(23); // <> Double_t term1st23 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(2); // <> Double_t term2nd23 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(3); // <> Double_t sumOfW1st23 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(2); // W_{} Double_t sumOfW2nd23 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(3); // W_{} Double_t sumOfWW23 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(23); // W_{} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator23 = product23 - term1st23*term2nd23; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator23 = 1.-sumOfWW23/(sumOfW1st23*sumOfW2nd23); // covariance: Double_t covariance23 = numerator23/denominator23; // weight dependent prefactor for covariance: Double_t wPrefactor23 = sumOfWW23/(sumOfW1st23*sumOfW2nd23); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(23,wPrefactor23*covariance23); // Cov(,): Double_t product24 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(24); // <> Double_t term1st24 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(2); // <> Double_t term2nd24 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(3); // <> Double_t sumOfW1st24 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(2); // W_{} Double_t sumOfW2nd24 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(3); // W_{} Double_t sumOfWW24 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(24); // W_{} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator24 = product24 - term1st24*term2nd24; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator24 = 1.-sumOfWW24/(sumOfW1st24*sumOfW2nd24); // covariance: Double_t covariance24 = numerator24/denominator24; // weight dependent prefactor for covariance: Double_t wPrefactor24 = sumOfWW24/(sumOfW1st24*sumOfW2nd24); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(24,wPrefactor24*covariance24); // Cov(,): Double_t product25 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(25); // <> Double_t term1st25 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(2); // <> Double_t term2nd25 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(3); // <> Double_t sumOfW1st25 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(2); // W_{} Double_t sumOfW2nd25 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(3); // W_{} Double_t sumOfWW25 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(25); // W_{} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator25 = product25 - term1st25*term2nd25; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator25 = 1.-sumOfWW25/(sumOfW1st25*sumOfW2nd25); // covariance: Double_t covariance25 = numerator25/denominator25; // weight dependent prefactor for covariance: Double_t wPrefactor25 = sumOfWW25/(sumOfW1st25*sumOfW2nd25); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(25,wPrefactor25*covariance25); // Cov(,): Double_t product26 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(26); // <> Double_t term1st26 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(2); // <> Double_t term2nd26 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(3); // <> Double_t sumOfW1st26 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(2); // W_{} Double_t sumOfW2nd26 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(3); // W_{} Double_t sumOfWW26 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(26); // W_{} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator26 = product26 - term1st26*term2nd26; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator26 = 1.-sumOfWW26/(sumOfW1st26*sumOfW2nd26); // covariance: Double_t covariance26 = numerator26/denominator26; // weight dependent prefactor for covariance: Double_t wPrefactor26 = sumOfWW26/(sumOfW1st26*sumOfW2nd26); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(26,wPrefactor26*covariance26); // Cov(,): Double_t product27 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(27); // <> Double_t term1st27 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(2); // <> Double_t term2nd27 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(3); // <> Double_t sumOfW1st27 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(2); // W_{} Double_t sumOfW2nd27 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(3); // W_{} Double_t sumOfWW27 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(27); // W_{} * W_{} // numerator in the expression for the the unbiased estimator for covariance: Double_t numerator27 = product27 - term1st27*term2nd27; // denominator in the expression for the the unbiased estimator for covariance: Double_t denominator27 = 1.-sumOfWW27/(sumOfW1st27*sumOfW2nd27); // covariance: Double_t covariance27 = numerator27/denominator27; // weight dependent prefactor for covariance: Double_t wPrefactor27 = sumOfWW27/(sumOfW1st27*sumOfW2nd27); // finally, store "weighted" covariance: fIntFlowCovariancesNUA->SetBinContent(27,wPrefactor27*covariance27); } // end of AliFlowAnalysisWithQCumulants::CalculateCovariancesNUAIntFlow() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::FinalizeCorrelationsIntFlow() { // From profile fIntFlowCorrelationsPro access measured correlations and spread, // correctly calculate the statistical errors and store the final results and // statistical errors for correlations in histogram fIntFlowCorrelationsHist. // // Remark: Statistical error of correlation is calculated as: // // statistical error = termA * spread * termB: // termA = sqrt{sum_{i=1}^{N} w^2}/(sum_{i=1}^{N} w) // termB = 1/sqrt(1-termA^2) // for(Int_t ci=1;ci<=4;ci++) // correlation index { Double_t correlation = fIntFlowCorrelationsPro->GetBinContent(ci); Double_t spread = fIntFlowCorrelationsPro->GetBinError(ci); Double_t sumOfLinearEventWeights = fIntFlowSumOfEventWeights[0]->GetBinContent(ci); Double_t sumOfQuadraticEventWeights = fIntFlowSumOfEventWeights[1]->GetBinContent(ci); Double_t termA = 0.; Double_t termB = 0.; if(TMath::Abs(sumOfLinearEventWeights) > 0.) // to be improved - shall I omitt here Abs() ? { termA = pow(sumOfQuadraticEventWeights,0.5)/sumOfLinearEventWeights; } else { cout< 0.) { termB = 1./pow(1-pow(termA,2.),0.5); } else { cout<SetBinContent(ci,correlation); fIntFlowCorrelationsHist->SetBinError(ci,statisticalError); } // end of for(Int_t ci=1;ci<=4;ci++) // correlation index // Versus multiplicity: if(!fCalculateCumulantsVsM){return;} for(Int_t ci=0;ci<=3;ci++) // correlation index { Int_t nBins = fIntFlowCorrelationsVsMPro[ci]->GetNbinsX(); for(Int_t b=1;b<=nBins;b++) // looping over multiplicity bins { Double_t correlationVsM = fIntFlowCorrelationsVsMPro[ci]->GetBinContent(b); Double_t spreadVsM = fIntFlowCorrelationsVsMPro[ci]->GetBinError(b); Double_t sumOfLinearEventWeightsVsM = fIntFlowSumOfEventWeightsVsM[ci][0]->GetBinContent(b); Double_t sumOfQuadraticEventWeightsVsM = fIntFlowSumOfEventWeightsVsM[ci][1]->GetBinContent(b); Double_t termAVsM = 0.; Double_t termBVsM = 0.; if(TMath::Abs(sumOfLinearEventWeightsVsM) > 0.) // to be improved - shall I omitt here Abs() ? { termAVsM = pow(sumOfQuadraticEventWeightsVsM,0.5)/sumOfLinearEventWeightsVsM; } if(1.-pow(termAVsM,2.) > 0.) { termBVsM = 1./pow(1-pow(termAVsM,2.),0.5); } Double_t statisticalErrorVsM = termAVsM * spreadVsM * termBVsM; fIntFlowCorrelationsVsMHist[ci]->SetBinContent(b,correlationVsM); fIntFlowCorrelationsVsMHist[ci]->SetBinError(b,statisticalErrorVsM); } // end of for(Int_t b=1;b<=nBins;b++) } // end of for(Int_t ci=1;ci<=4;ci++) // correlation index } // end of AliFlowAnalysisWithQCumulants::FinalizeCorrelationsIntFlow() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::FillAverageMultiplicities(Int_t nRP) { // Fill profile fAverageMultiplicity to hold average multiplicities and number of events for events with nRP>=0, nRP>=1, ... , and nRP>=8 // Binning of fAverageMultiplicity is organized as follows: // 1st bin: all events (including the empty ones) // 2nd bin: event with # of RPs greater or equal to 1 // 3rd bin: event with # of RPs greater or equal to 2 // 4th bin: event with # of RPs greater or equal to 3 // 5th bin: event with # of RPs greater or equal to 4 // 6th bin: event with # of RPs greater or equal to 5 // 7th bin: event with # of RPs greater or equal to 6 // 8th bin: event with # of RPs greater or equal to 7 // 9th bin: event with # of RPs greater or equal to 8 if(!fAvMultiplicity) { cout<<"WARNING: fAvMultiplicity is NULL in AFAWQC::FAM() !!!!"<=i) fAvMultiplicity->Fill(i+0.5,nRP,1); } } // end of AliFlowAnalysisWithQCumulants::FillAverageMultiplicities(nRP) //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CalculateCumulantsIntFlow() { // a) Calculate Q-cumulants from the measured multiparticle correlations. // b) Propagate the statistical errors of measured multiparticle correlations to statistical errors of Q-cumulants. // c) REMARK: Q-cumulants calculated in this method are biased by non-uniform acceptance of detector !!!! // Method ApplyCorrectionForNonUniformAcceptance* (to be improved: finalize the name here) // is called afterwards to correct for this bias. // d) Store the results and statistical error of Q-cumulants in histogram fCumulants. // Binning of fCumulants is organized as follows: // // 1st bin: QC{2} // 2nd bin: QC{4} // 3rd bin: QC{6} // 4th bin: QC{8} // // to be improved: revise the names and check the pointers used in this method // Correlations: Double_t two = fIntFlowCorrelationsHist->GetBinContent(1); // <<2>> Double_t four = fIntFlowCorrelationsHist->GetBinContent(2); // <<4>> Double_t six = fIntFlowCorrelationsHist->GetBinContent(3); // <<6>> Double_t eight = fIntFlowCorrelationsHist->GetBinContent(4); // <<8>> // Statistical errors of average 2-, 4-, 6- and 8-particle azimuthal correlations: Double_t twoError = fIntFlowCorrelationsHist->GetBinError(1); // statistical error of <2> Double_t fourError = fIntFlowCorrelationsHist->GetBinError(2); // statistical error of <4> Double_t sixError = fIntFlowCorrelationsHist->GetBinError(3); // statistical error of <6> Double_t eightError = fIntFlowCorrelationsHist->GetBinError(4); // statistical error of <8> // Covariances (multiplied by prefactor depending on weights - see comments in CalculateCovariancesIntFlow()): Double_t wCov24 = fIntFlowCovariances->GetBinContent(1); // Cov(<2>,<4>) * prefactor(w_<2>,w_<4>) Double_t wCov26 = fIntFlowCovariances->GetBinContent(2); // Cov(<2>,<6>) * prefactor(w_<2>,w_<6>) Double_t wCov28 = fIntFlowCovariances->GetBinContent(3); // Cov(<2>,<8>) * prefactor(w_<2>,w_<8>) Double_t wCov46 = fIntFlowCovariances->GetBinContent(4); // Cov(<4>,<6>) * prefactor(w_<4>,w_<6>) Double_t wCov48 = fIntFlowCovariances->GetBinContent(5); // Cov(<4>,<8>) * prefactor(w_<4>,w_<8>) Double_t wCov68 = fIntFlowCovariances->GetBinContent(6); // Cov(<6>,<8>) * prefactor(w_<6>,w_<8>) // Q-cumulants: Double_t qc2 = 0.; // QC{2} Double_t qc4 = 0.; // QC{4} Double_t qc6 = 0.; // QC{6} Double_t qc8 = 0.; // QC{8} if(TMath::Abs(two) > 0.){qc2 = two;} if(TMath::Abs(four) > 0.){qc4 = four-2.*pow(two,2.);} if(TMath::Abs(six) > 0.){qc6 = six-9.*two*four+12.*pow(two,3.);} if(TMath::Abs(eight) > 0.){qc8 = eight-16.*two*six-18.*pow(four,2.)+144.*pow(two,2.)*four-144.*pow(two,4.);} // Statistical errors of Q-cumulants: Double_t qc2Error = 0.; Double_t qc4Error = 0.; Double_t qc6Error = 0.; Double_t qc8Error = 0.; // Squared statistical errors of Q-cumulants: //Double_t qc2ErrorSquared = 0.; Double_t qc4ErrorSquared = 0.; Double_t qc6ErrorSquared = 0.; Double_t qc8ErrorSquared = 0.; // Statistical error of QC{2}: qc2Error = twoError; // Statistical error of QC{4}: qc4ErrorSquared = 16.*pow(two,2.)*pow(twoError,2)+pow(fourError,2.) - 8.*two*wCov24; if(qc4ErrorSquared>0.) { qc4Error = pow(qc4ErrorSquared,0.5); } else { cout<<" WARNING (QC): Statistical error of QC{4} is imaginary !!!!"<0.) { qc6Error = pow(qc6ErrorSquared,0.5); } else { cout<<" WARNING (QC): Statistical error of QC{6} is imaginary !!!!"<0.) { qc8Error = pow(qc8ErrorSquared,0.5); } else { cout<<"WARNING (QC): Statistical error of QC{8} is imaginary !!!!"<0.) { fIntFlowQcumulants->SetBinContent(1,qc2); fIntFlowQcumulants->SetBinError(1,qc2Error); } if(TMath::Abs(qc4)>0.) { fIntFlowQcumulants->SetBinContent(2,qc4); fIntFlowQcumulants->SetBinError(2,qc4Error); } if(TMath::Abs(qc6)>0.) { fIntFlowQcumulants->SetBinContent(3,qc6); fIntFlowQcumulants->SetBinError(3,qc6Error); } if(TMath::Abs(qc8)>0.) { fIntFlowQcumulants->SetBinContent(4,qc8); fIntFlowQcumulants->SetBinError(4,qc8Error); } // Versus multiplicity: if(!fCalculateCumulantsVsM){return;} Int_t nBins = fIntFlowCorrelationsVsMPro[0]->GetNbinsX(); // to be improved (hardwired 0) Double_t value[4] = {0.}; // QCs vs M Double_t error[4] = {0.}; // error of QCs vs M Double_t dSum1[4] = {0.}; // sum value_i/(error_i)^2 Double_t dSum2[4] = {0.}; // sum 1/(error_i)^2 for(Int_t b=1;b<=nBins;b++) { // Correlations: two = fIntFlowCorrelationsVsMHist[0]->GetBinContent(b); // <<2>> four = fIntFlowCorrelationsVsMHist[1]->GetBinContent(b); // <<4>> six = fIntFlowCorrelationsVsMHist[2]->GetBinContent(b); // <<6>> eight = fIntFlowCorrelationsVsMHist[3]->GetBinContent(b); // <<8>> // Statistical errors of average 2-, 4-, 6- and 8-particle azimuthal correlations: twoError = fIntFlowCorrelationsVsMHist[0]->GetBinError(b); // statistical error of <2> fourError = fIntFlowCorrelationsVsMHist[1]->GetBinError(b); // statistical error of <4> sixError = fIntFlowCorrelationsVsMHist[2]->GetBinError(b); // statistical error of <6> eightError = fIntFlowCorrelationsVsMHist[3]->GetBinError(b); // statistical error of <8> // Covariances (multiplied by prefactor depending on weights - see comments in CalculateCovariancesIntFlow()): wCov24 = fIntFlowCovariancesVsM[0]->GetBinContent(b); // Cov(<2>,<4>) * prefactor(w_<2>,w_<4>) wCov26 = fIntFlowCovariancesVsM[1]->GetBinContent(b); // Cov(<2>,<6>) * prefactor(w_<2>,w_<6>) wCov28 = fIntFlowCovariancesVsM[2]->GetBinContent(b); // Cov(<2>,<8>) * prefactor(w_<2>,w_<8>) wCov46 = fIntFlowCovariancesVsM[3]->GetBinContent(b); // Cov(<4>,<6>) * prefactor(w_<4>,w_<6>) wCov48 = fIntFlowCovariancesVsM[4]->GetBinContent(b); // Cov(<4>,<8>) * prefactor(w_<4>,w_<8>) wCov68 = fIntFlowCovariancesVsM[5]->GetBinContent(b); // Cov(<6>,<8>) * prefactor(w_<6>,w_<8>) // Q-cumulants: qc2 = 0.; // QC{2} qc4 = 0.; // QC{4} qc6 = 0.; // QC{6} qc8 = 0.; // QC{8} if(TMath::Abs(two) > 0.){qc2 = two;} if(TMath::Abs(four) > 0.){qc4 = four-2.*pow(two,2.);} if(TMath::Abs(six) > 0.){qc6 = six-9.*two*four+12.*pow(two,3.);} if(TMath::Abs(eight) > 0.){qc8 = eight-16.*two*six-18.*pow(four,2.)+144.*pow(two,2.)*four-144.*pow(two,4.);} // Statistical errors of Q-cumulants: qc2Error = 0.; qc4Error = 0.; qc6Error = 0.; qc8Error = 0.; // Squared statistical errors of Q-cumulants: //Double_t qc2ErrorSquared = 0.; qc4ErrorSquared = 0.; qc6ErrorSquared = 0.; qc8ErrorSquared = 0.; // Statistical error of QC{2}: qc2Error = twoError; // Statistical error of QC{4}: qc4ErrorSquared = 16.*pow(two,2.)*pow(twoError,2)+pow(fourError,2.) - 8.*two*wCov24; if(qc4ErrorSquared>0.) { qc4Error = pow(qc4ErrorSquared,0.5); } else { // cout<<"WARNING: Statistical error of QC{4} is imaginary in multiplicity bin "<0.) { qc6Error = pow(qc6ErrorSquared,0.5); } else { // cout<<"WARNING: Statistical error of QC{6} is imaginary in multiplicity bin "<0.) { qc8Error = pow(qc8ErrorSquared,0.5); } else { // cout<<"WARNING: Statistical error of QC{8} is imaginary in multiplicity bin "<0.) { fIntFlowQcumulantsVsM[0]->SetBinContent(b,qc2); fIntFlowQcumulantsVsM[0]->SetBinError(b,qc2Error); } if(TMath::Abs(qc4)>0.) { fIntFlowQcumulantsVsM[1]->SetBinContent(b,qc4); fIntFlowQcumulantsVsM[1]->SetBinError(b,qc4Error); } if(TMath::Abs(qc6)>0.) { fIntFlowQcumulantsVsM[2]->SetBinContent(b,qc6); fIntFlowQcumulantsVsM[2]->SetBinError(b,qc6Error); } if(TMath::Abs(qc8)>0.) { fIntFlowQcumulantsVsM[3]->SetBinContent(b,qc8); fIntFlowQcumulantsVsM[3]->SetBinError(b,qc8Error); } // Rebin in M: for(Int_t co=0;co<4;co++) { value[co] = fIntFlowQcumulantsVsM[co]->GetBinContent(b); error[co] = fIntFlowQcumulantsVsM[co]->GetBinError(b); if(error[co]>0.) { dSum1[co]+=value[co]/(error[co]*error[co]); dSum2[co]+=1./(error[co]*error[co]); } } // end of for(Int_t co=0;co<4;co++) } // end of for(Int_t b=1;b<=nBins;b++) // Store rebinned Q-cumulants: for(Int_t co=0;co<4;co++) { if(dSum2[co]>0.) { fIntFlowQcumulantsRebinnedInM->SetBinContent(co+1,dSum1[co]/dSum2[co]); fIntFlowQcumulantsRebinnedInM->SetBinError(co+1,pow(1./dSum2[co],0.5)); } } // end of for(Int_t co=0;co<4;co++) } // end of AliFlowAnalysisWithQCumulants::CalculateCumulantsIntFlow() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CalculateIntFlow() { // a) Calculate the final results for reference flow estimates from Q-cumulants. // b) Propagate the statistical errors to reference flow estimates from // - measured multiparticle correlations (set kTRUE for fPropagateErrorFromCorrelations), or // - cumulants (set kFALSE for fPropagateErrorFromCorrelations). // c) Store the results and statistical errors of reference flow estimates in histogram fIntFlow. // Binning of fIntFlow is organized as follows: // // 1st bin: v{2,QC} // 2nd bin: v{4,QC} // 3rd bin: v{6,QC} // 4th bin: v{8,QC} // // to be improved: revise the names and check the pointers used in this method, add something about calculation vs M if(!(fIntFlowCorrelationsHist && fIntFlowCovariances && fIntFlowQcumulants && fIntFlow)) { cout<<"WARNING: fIntFlowCorrelationsHist && fIntFlowCovariances && fIntFlowQcumulants && fIntFlow is NULL in AFAWQC::CCIF() !!!!"<GetBinContent(1); // QC{2} Double_t qc4 = fIntFlowQcumulants->GetBinContent(2); // QC{4} Double_t qc6 = fIntFlowQcumulants->GetBinContent(3); // QC{6} Double_t qc8 = fIntFlowQcumulants->GetBinContent(4); // QC{8} // Q-cumulants's statistical errors: Double_t qc2Error = fIntFlowQcumulants->GetBinError(1); // QC{2} stat. error Double_t qc4Error = fIntFlowQcumulants->GetBinError(2); // QC{4} stat. error Double_t qc6Error = fIntFlowQcumulants->GetBinError(3); // QC{6} stat. error Double_t qc8Error = fIntFlowQcumulants->GetBinError(4); // QC{8} stat. error // Calculate reference flow estimates from Q-cumulants: if(qc2>=0.){v2 = pow(qc2,1./2.);} if(qc4<=0.){v4 = pow(-1.*qc4,1./4.);} if(qc6>=0.){v6 = pow((1./4.)*qc6,1./6.);} if(qc8<=0.){v8 = pow((-1./33.)*qc8,1./8.);} // Calculate stat. error for reference flow estimates from stat. error of Q-cumulants: if(qc2>0.){v2Error = (1./2.)*pow(qc2,-1./2.)*qc2Error;} if(qc4<0.){v4Error = (1./4.)*pow(-qc4,-3./4.)*qc4Error;} if(qc6>0.){v6Error = (1./6.)*pow(2.,-1./3.)*pow(qc6,-5./6.)*qc6Error;} if(qc8<0.){v8Error = (1./8.)*pow(33.,-1./8.)*pow(-qc8,-7./8.)*qc8Error;} // Print warnings for the 'wrong sign' cumulants: if(TMath::Abs(v2) < 1.e-44) { cout<<" WARNING: Wrong sign QC{2}, couldn't calculate v{2,QC} !!!!"<SetBinContent(1,v2); fIntFlow->SetBinError(1,v2Error); fIntFlow->SetBinContent(2,v4); fIntFlow->SetBinError(2,v4Error); fIntFlow->SetBinContent(3,v6); fIntFlow->SetBinError(3,v6Error); fIntFlow->SetBinContent(4,v8); fIntFlow->SetBinError(4,v8Error); // Versus multiplicity: if(!fCalculateCumulantsVsM){return;} // to be improved - not compatible with if(fPropagateErrorFromCorrelations) bellow Int_t nBins = fIntFlowCorrelationsVsMPro[0]->GetNbinsX(); // to be improved (hardwired 0) for(Int_t b=1;b<=nBins;b++) { // Q-cumulants: Double_t qc2VsM = fIntFlowQcumulantsVsM[0]->GetBinContent(b); // QC{2} Double_t qc4VsM = fIntFlowQcumulantsVsM[1]->GetBinContent(b); // QC{4} Double_t qc6VsM = fIntFlowQcumulantsVsM[2]->GetBinContent(b); // QC{6} Double_t qc8VsM = fIntFlowQcumulantsVsM[3]->GetBinContent(b); // QC{8} // Q-cumulants's statistical errors: Double_t qc2ErrorVsM = fIntFlowQcumulantsVsM[0]->GetBinError(b); // QC{2} stat. error Double_t qc4ErrorVsM = fIntFlowQcumulantsVsM[1]->GetBinError(b); // QC{4} stat. error Double_t qc6ErrorVsM = fIntFlowQcumulantsVsM[2]->GetBinError(b); // QC{6} stat. error Double_t qc8ErrorVsM = fIntFlowQcumulantsVsM[3]->GetBinError(b); // QC{8} stat. error // Reference flow estimates: Double_t v2VsM = 0.; // v{2,QC} Double_t v4VsM = 0.; // v{4,QC} Double_t v6VsM = 0.; // v{6,QC} Double_t v8VsM = 0.; // v{8,QC} // Reference flow estimates errors: Double_t v2ErrorVsM = 0.; // v{2,QC} stat. error Double_t v4ErrorVsM = 0.; // v{4,QC} stat. error Double_t v6ErrorVsM = 0.; // v{6,QC} stat. error Double_t v8ErrorVsM = 0.; // v{8,QC} stat. error // Calculate reference flow estimates from Q-cumulants: if(qc2VsM>=0.){v2VsM = pow(qc2VsM,1./2.);} if(qc4VsM<=0.){v4VsM = pow(-1.*qc4VsM,1./4.);} if(qc6VsM>=0.){v6VsM = pow((1./4.)*qc6VsM,1./6.);} if(qc8VsM<=0.){v8VsM = pow((-1./33.)*qc8VsM,1./8.);} // Calculate stat. error for reference flow estimates from stat. error of Q-cumulants: if(qc2VsM>0.){v2ErrorVsM = (1./2.)*pow(qc2VsM,-1./2.)*qc2ErrorVsM;} if(qc4VsM<0.){v4ErrorVsM = (1./4.)*pow(-qc4VsM,-3./4.)*qc4ErrorVsM;} if(qc6VsM>0.){v6ErrorVsM = (1./6.)*pow(2.,-1./3.)*pow(qc6VsM,-5./6.)*qc6ErrorVsM;} if(qc8VsM<0.){v8ErrorVsM = (1./8.)*pow(33.,-1./8.)*pow(-qc8VsM,-7./8.)*qc8ErrorVsM;} // Store the results and statistical errors of integrated flow estimates: fIntFlowVsM[0]->SetBinContent(b,v2VsM); fIntFlowVsM[0]->SetBinError(b,v2ErrorVsM); fIntFlowVsM[1]->SetBinContent(b,v4VsM); fIntFlowVsM[1]->SetBinError(b,v4ErrorVsM); fIntFlowVsM[2]->SetBinContent(b,v6VsM); fIntFlowVsM[2]->SetBinError(b,v6ErrorVsM); fIntFlowVsM[3]->SetBinContent(b,v8VsM); fIntFlowVsM[3]->SetBinError(b,v8ErrorVsM); } // end of for(Int_t b=1;b<=nBins;b++) // 'Rebinned in M' calculation: // to be improved - this can be implemented better: // Reference flow estimates: Double_t v2RebinnedInM = 0.; // v{2,QC} Double_t v4RebinnedInM = 0.; // v{4,QC} Double_t v6RebinnedInM = 0.; // v{6,QC} Double_t v8RebinnedInM = 0.; // v{8,QC} // Reference flow's statistical errors: Double_t v2ErrorRebinnedInM = 0.; // v{2,QC} stat. error Double_t v4ErrorRebinnedInM = 0.; // v{4,QC} stat. error Double_t v6ErrorRebinnedInM = 0.; // v{6,QC} stat. error Double_t v8ErrorRebinnedInM = 0.; // v{8,QC} stat. error // Q-cumulants: Double_t qc2RebinnedInM = fIntFlowQcumulantsRebinnedInM->GetBinContent(1); // QC{2} Double_t qc4RebinnedInM = fIntFlowQcumulantsRebinnedInM->GetBinContent(2); // QC{4} Double_t qc6RebinnedInM = fIntFlowQcumulantsRebinnedInM->GetBinContent(3); // QC{6} Double_t qc8RebinnedInM = fIntFlowQcumulantsRebinnedInM->GetBinContent(4); // QC{8} // Q-cumulants's statistical errors: Double_t qc2ErrorRebinnedInM = fIntFlowQcumulantsRebinnedInM->GetBinError(1); // QC{2} stat. error Double_t qc4ErrorRebinnedInM = fIntFlowQcumulantsRebinnedInM->GetBinError(2); // QC{4} stat. error Double_t qc6ErrorRebinnedInM = fIntFlowQcumulantsRebinnedInM->GetBinError(3); // QC{6} stat. error Double_t qc8ErrorRebinnedInM = fIntFlowQcumulantsRebinnedInM->GetBinError(4); // QC{8} stat. error // Calculate reference flow estimates from Q-cumulants: if(qc2RebinnedInM>=0.){v2RebinnedInM = pow(qc2RebinnedInM,1./2.);} if(qc4RebinnedInM<=0.){v4RebinnedInM = pow(-1.*qc4RebinnedInM,1./4.);} if(qc6RebinnedInM>=0.){v6RebinnedInM = pow((1./4.)*qc6RebinnedInM,1./6.);} if(qc8RebinnedInM<=0.){v8RebinnedInM = pow((-1./33.)*qc8RebinnedInM,1./8.);} // Calculate stat. error for reference flow estimates from stat. error of Q-cumulants: if(qc2RebinnedInM>0.){v2ErrorRebinnedInM = (1./2.)*pow(qc2RebinnedInM,-1./2.)*qc2ErrorRebinnedInM;} if(qc4RebinnedInM<0.){v4ErrorRebinnedInM = (1./4.)*pow(-qc4RebinnedInM,-3./4.)*qc4ErrorRebinnedInM;} if(qc6RebinnedInM>0.){v6ErrorRebinnedInM = (1./6.)*pow(2.,-1./3.)*pow(qc6RebinnedInM,-5./6.)*qc6ErrorRebinnedInM;} if(qc8RebinnedInM<0.){v8ErrorRebinnedInM = (1./8.)*pow(33.,-1./8.)*pow(-qc8RebinnedInM,-7./8.)*qc8ErrorRebinnedInM;} // Print warnings for the 'wrong sign' cumulants: if(TMath::Abs(v2RebinnedInM) < 1.e-44) { cout<<" WARNING: Wrong sign QC{2} rebinned in M, couldn't calculate v{2,QC} !!!!"<SetBinContent(1,v2RebinnedInM); fIntFlowRebinnedInM->SetBinError(1,v2ErrorRebinnedInM); fIntFlowRebinnedInM->SetBinContent(2,v4RebinnedInM); fIntFlowRebinnedInM->SetBinError(2,v4ErrorRebinnedInM); fIntFlowRebinnedInM->SetBinContent(3,v6RebinnedInM); fIntFlowRebinnedInM->SetBinError(3,v6ErrorRebinnedInM); fIntFlowRebinnedInM->SetBinContent(4,v8RebinnedInM); fIntFlowRebinnedInM->SetBinError(4,v8ErrorRebinnedInM); } // end of if(!fPropagateErrorFromCorrelations) // Used only for debugging/cross-checking: if(fPropagateErrorFromCorrelations) { // Measured azimuthal correlations: Double_t two = fIntFlowCorrelationsHist->GetBinContent(1); // <<2>> Double_t four = fIntFlowCorrelationsHist->GetBinContent(2); // <<4>> Double_t six = fIntFlowCorrelationsHist->GetBinContent(3); // <<6>> Double_t eight = fIntFlowCorrelationsHist->GetBinContent(4); // <<8>> // Statistical errors of average 2-, 4-, 6- and 8-particle azimuthal correlations: Double_t twoError = fIntFlowCorrelationsHist->GetBinError(1); // statistical error of <2> Double_t fourError = fIntFlowCorrelationsHist->GetBinError(2); // statistical error of <4> Double_t sixError = fIntFlowCorrelationsHist->GetBinError(3); // statistical error of <6> Double_t eightError = fIntFlowCorrelationsHist->GetBinError(4); // statistical error of <8> // Covariances (multiplied by prefactor depending on weights - see comments in CalculateCovariancesIntFlow()): Double_t wCov24 = fIntFlowCovariances->GetBinContent(1); // Cov(<2>,<4>) * prefactor(w_<2>,w_<4>) Double_t wCov26 = fIntFlowCovariances->GetBinContent(2); // Cov(<2>,<6>) * prefactor(w_<2>,w_<6>) Double_t wCov28 = fIntFlowCovariances->GetBinContent(3); // Cov(<2>,<8>) * prefactor(w_<2>,w_<8>) Double_t wCov46 = fIntFlowCovariances->GetBinContent(4); // Cov(<4>,<6>) * prefactor(w_<4>,w_<6>) Double_t wCov48 = fIntFlowCovariances->GetBinContent(5); // Cov(<4>,<8>) * prefactor(w_<4>,w_<8>) Double_t wCov68 = fIntFlowCovariances->GetBinContent(6); // Cov(<6>,<8>) * prefactor(w_<6>,w_<8>) // Calculate reference flow estimates: if(two>=0.){v2 = pow(two,1./2.);} if(TMath::Abs(four)>0. && four-2.*pow(two,2.) < 0.){v4 = pow(-1.*(four-2.*pow(two,2.)),1./4.);} if(TMath::Abs(six)>0. && six-9.*two*four+12.*pow(two,3.) > 0.){v6 = pow((1./4.)*(six-9.*two*four+12.*pow(two,3.)),1./6.);} if(TMath::Abs(eight)>0. && eight-16.*two*six-18.*pow(four,2.)+144.*pow(two,2.)*four-144.*pow(two,4.) < 0.) {v8 = pow((-1./33.)*(eight-16.*two*six-18.*pow(four,2.)+144.*pow(two,2.)*four-144.*pow(two,4.)),1./8.);} // Squares of statistical errors of reference flow estimates: Double_t v2ErrorSquared = 0.; // squared statistical error of v{2,QC} Double_t v4ErrorSquared = 0.; // squared statistical error of v{4,QC} Double_t v6ErrorSquared = 0.; // squared statistical error of v{6,QC} Double_t v8ErrorSquared = 0.; // squared statistical error of v{8,QC} // Calculate squared statistical errors of reference flow estimates: if(two > 0.) { v2ErrorSquared = (1./(4.*two))*pow(twoError,2.); } if(2.*pow(two,2.)-four > 0.) { v4ErrorSquared = (1./pow(2.*pow(two,2.)-four,3./2.)) * (pow(two,2.)*pow(twoError,2.)+(1./16.)*pow(fourError,2.)-(1./2.)*two*wCov24); } if(six-9.*four*two+12.*pow(two,3.) > 0.) { v6ErrorSquared = ((1./2.)*(1./pow(2.,2./3.))*(1./pow(six-9.*four*two+12.*pow(two,3.),5./3.))) * ((9./2.)*pow(4.*pow(two,2.)-four,2.)*pow(twoError,2.) + (9./2.)*pow(two,2.)*pow(fourError,2.)+(1./18.)*pow(sixError,2.) - 9.*two*(4.*pow(two,2.)-four)*wCov24+(4.*pow(two,2.)-four)*wCov26-two*wCov46); } if(-1.*eight+16.*six*two+18.*pow(four,2.)-144.*four*pow(two,2.)+144.*pow(two,4.) > 0.) { v8ErrorSquared = (4./pow(33,1./4.)) * (1./pow(-1.*eight+16.*six*two+18.*pow(four,2.)-144.*four*pow(two,2.)+144.*pow(two,4.),7./4.)) * (pow(36.*pow(two,3.)-18.*four*two+six,2.)*pow(twoError,2.) + (81./16.)*pow(4.*pow(two,2.)-four,2.)*pow(fourError,2.) + pow(two,2.)*pow(sixError,2.) + (1./256.)*pow(eightError,2.) - (9./2.)*(36.*pow(two,3.)-18.*four*two+six)*(4.*pow(two,2.)-four)*wCov24 + 2.*two*(36.*pow(two,3.)-18.*four*two+six)*wCov26 - (1./8.)*(36.*pow(two,3.)-18.*four*two+six)*wCov28 - (9./2.)*two*(4.*pow(two,2.)-four)*wCov46 + (9./32.)*(4.*pow(two,2.)-four)*wCov48 - (1./8.)*two*wCov68); } // Calculate statistical errors of reference flow estimates: if(v2ErrorSquared > 0.) { v2Error = pow(v2ErrorSquared,0.5); } if(v4ErrorSquared > 0.) { v4Error = pow(v4ErrorSquared,0.5); } if(v6ErrorSquared > 0.) { v6Error = pow(v6ErrorSquared,0.5); } if(v8ErrorSquared > 0.) { v8Error = pow(v8ErrorSquared,0.5); } // Store the results and statistical errors of integrated flow estimates: fIntFlow->SetBinContent(1,v2); fIntFlow->SetBinError(1,v2Error); fIntFlow->SetBinContent(2,v4); fIntFlow->SetBinError(2,v4Error); fIntFlow->SetBinContent(3,v6); fIntFlow->SetBinError(3,v6Error); fIntFlow->SetBinContent(4,v8); fIntFlow->SetBinError(4,v8Error); } // end of if(fPropagateErrorFromCorrelations) } // end of AliFlowAnalysisWithQCumulants::CalculateIntFlow() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::FillCommonHistResultsIntFlow() { // Fill in AliFlowCommonHistResults histograms relevant for reference flow. // There are two possibilities here: // a) Store minimum bias reference flow - use SetMinimumBiasReferenceFlow(kTRUE). This result is // biased by the interplay between nonflow correlations and multiplicity fluctuations and is // also stored in local histogram fIntFlow; // b) Store reference flow obtained from flow analysis performed at fixed multiplicity and // rebinned only at the end of the day - use SetMinimumBiasReferenceFlow(kFALSE). This result // is also stored in local histogram fIntFlowRebinnedInM. // Reference flow estimates: Double_t v[4] = {0.}; // Statistical errors of reference flow estimates: Double_t vError[4] = {0.}; for(Int_t b=0;b<4;b++) { if(fMinimumBiasReferenceFlow) { v[b] = fIntFlow->GetBinContent(b+1); vError[b] = fIntFlow->GetBinError(b+1); } else { v[b] = fIntFlowRebinnedInM->GetBinContent(b+1); vError[b] = fIntFlowRebinnedInM->GetBinError(b+1); } } // end of for(Int_t b=0;b<4;b++) // Fill AliFlowCommonHistResults histogram: fCommonHistsResults2nd->FillIntegratedFlow(v[0],vError[0]); // to be improved (hardwired 2nd in the name) fCommonHistsResults4th->FillIntegratedFlow(v[1],vError[1]); // to be improved (hardwired 4th in the name) if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) // to be improved (calculate also 6th and 8th order) { fCommonHistsResults6th->FillIntegratedFlow(v[2],vError[2]); // to be improved (hardwired 6th in the name) fCommonHistsResults8th->FillIntegratedFlow(v[3],vError[3]); // to be improved (hardwired 8th in the name) } } // end of AliFlowAnalysisWithQCumulants::FillCommonHistResultsIntFlow() //================================================================================================================================ /* void AliFlowAnalysisWithQCumulants::ApplyCorrectionForNonUniformAcceptanceToCumulantsForIntFlow(Bool_t useParticleWeights, TString eventWeights) { // apply correction for non-uniform acceptance to cumulants for integrated flow // (Remark: non-corrected cumulants are accessed from fCumulants[pW][0], corrected cumulants are stored in fCumulants[pW][1]) // shortcuts for the flags: Int_t pW = (Int_t)(useParticleWeights); // 0=pWeights not used, 1=pWeights used Int_t eW = -1; if(eventWeights == "exact") { eW = 0; } if(!(fCumulants[pW][eW][0] && fCumulants[pW][eW][1] && fCorrections[pW][eW])) { cout<<"WARNING: fCumulants[pW][eW][0] && fCumulants[pW][eW][1] && fCorrections[pW][eW] is NULL in AFAWQC::ACFNUATCFIF() !!!!"<GetBinContent(1)) { cout<<" QC{2,biased}/QC{2,corrected} = "<<(fCumulants[pW][eW][0]->GetBinContent(1))/(fCumulants[pW][eW][1]->GetBinContent(1))<GetBinContent(2)) { cout<<" QC{4,biased}/QC{4,corrected} = "<GetBinContent(2)/fCumulants[pW][eW][1]->GetBinContent(2)<_{1n|1n} = two1n1nW1W1 = // 2nd bin: <2>_{2n|2n} = two2n2nW2W2 = // 3rd bin: <2>_{3n|3n} = two3n3nW3W3 = // 4th bin: <2>_{4n|4n} = two4n4nW4W4 = // 5th bin: ---- EMPTY ---- // 6th bin: <3>_{2n|1n,1n} = three2n1n1nW2W1W1 = // 7th bin: <3>_{3n|2n,1n} = ... // 8th bin: <3>_{4n|2n,2n} = ... // 9th bin: <3>_{4n|3n,1n} = ... // 10th bin: ---- EMPTY ---- // 11th bin: <4>_{1n,1n|1n,1n} = four1n1n1n1nW1W1W1W1 = // 12th bin: <4>_{2n,1n|2n,1n} = ... // 13th bin: <4>_{2n,2n|2n,2n} = ... // 14th bin: <4>_{3n|1n,1n,1n} = ... // 15th bin: <4>_{3n,1n|3n,1n} = ... // 16th bin: <4>_{3n,1n|2n,2n} = ... // 17th bin: <4>_{4n|2n,1n,1n} = ... // 18th bin: ---- EMPTY ---- // 19th bin: <5>_{2n|1n,1n,1n,1n} = ... // 20th bin: <5>_{2n,2n|2n,1n,1n} = ... // 21st bin: <5>_{3n,1n|2n,1n,1n} = ... // 22nd bin: <5>_{4n|1n,1n,1n,1n} = ... // 23rd bin: ---- EMPTY ---- // 24th bin: <6>_{1n,1n,1n|1n,1n,1n} = ... // 25th bin: <6>_{2n,1n,1n|2n,1n,1n} = ... // 26th bin: <6>_{2n,2n|1n,1n,1n,1n} = ... // 27th bin: <6>_{3n,1n|1n,1n,1n,1n} = ... // 28th bin: ---- EMPTY ---- // 29th bin: <7>_{2n,1n,1n|1n,1n,1n,1n} = ... // 30th bin: ---- EMPTY ---- // 31st bin: <8>_{1n,1n,1n,1n|1n,1n,1n,1n} = ... // Remark 2: When particle weights are used there are some extra correlations. They are stored in // fIntFlowExtraCorrelationsPro binning of which is organized as follows: // 1st bin: two1n1nW3W1 = // 2nd bin: two1n1nW1W1W2 = // multiplicity (number of particles used to determine the reaction plane) Double_t dMult = (*fSMpk)(0,0); // real and imaginary parts of weighted Q-vectors evaluated in harmonics n, 2n, 3n and 4n: Double_t dReQ1n1k = (*fReQ)(0,1); Double_t dReQ2n2k = (*fReQ)(1,2); Double_t dReQ3n3k = (*fReQ)(2,3); Double_t dReQ4n4k = (*fReQ)(3,4); Double_t dReQ1n3k = (*fReQ)(0,3); Double_t dImQ1n1k = (*fImQ)(0,1); Double_t dImQ2n2k = (*fImQ)(1,2); Double_t dImQ3n3k = (*fImQ)(2,3); Double_t dImQ4n4k = (*fImQ)(3,4); Double_t dImQ1n3k = (*fImQ)(0,3); // dMs are variables introduced in order to simplify some Eqs. bellow: //.............................................................................................. Double_t dM11 = (*fSMpk)(1,1)-(*fSMpk)(0,2); // dM11 = sum_{i,j=1,i!=j}^M w_i w_j Double_t dM22 = (*fSMpk)(1,2)-(*fSMpk)(0,4); // dM22 = sum_{i,j=1,i!=j}^M w_i^2 w_j^2 Double_t dM33 = (*fSMpk)(1,3)-(*fSMpk)(0,6); // dM33 = sum_{i,j=1,i!=j}^M w_i^3 w_j^3 Double_t dM44 = (*fSMpk)(1,4)-(*fSMpk)(0,8); // dM44 = sum_{i,j=1,i!=j}^M w_i^4 w_j^4 Double_t dM31 = (*fSMpk)(0,3)*(*fSMpk)(0,1)-(*fSMpk)(0,4); // dM31 = sum_{i,j=1,i!=j}^M w_i^3 w_j Double_t dM211 = (*fSMpk)(0,2)*(*fSMpk)(1,1)-2.*(*fSMpk)(0,3)*(*fSMpk)(0,1) - (*fSMpk)(1,2)+2.*(*fSMpk)(0,4); // dM211 = sum_{i,j,k=1,i!=j!=k}^M w_i^2 w_j w_k Double_t dM1111 = (*fSMpk)(3,1)-6.*(*fSMpk)(0,2)*(*fSMpk)(1,1) + 8.*(*fSMpk)(0,3)*(*fSMpk)(0,1) + 3.*(*fSMpk)(1,2)-6.*(*fSMpk)(0,4); // dM1111 = sum_{i,j,k,l=1,i!=j!=k!=l}^M w_i w_j w_k w_l //.............................................................................................. // 2-particle correlations: Double_t two1n1nW1W1 = 0.; // Double_t two2n2nW2W2 = 0.; // Double_t two3n3nW3W3 = 0.; // Double_t two4n4nW4W4 = 0.; // if(dMult>1) { if(dM11) { two1n1nW1W1 = (pow(dReQ1n1k,2)+pow(dImQ1n1k,2)-(*fSMpk)(0,2))/dM11; // average correlation for single event: fIntFlowCorrelationsEBE->SetBinContent(1,two1n1nW1W1); fIntFlowEventWeightsForCorrelationsEBE->SetBinContent(1,dM11); // average correlation for all events: fIntFlowCorrelationsPro->Fill(0.5,two1n1nW1W1,dM11); fIntFlowCorrelationsAllPro->Fill(0.5,two1n1nW1W1,dM11); } if(dM22) { two2n2nW2W2 = (pow(dReQ2n2k,2)+pow(dImQ2n2k,2)-(*fSMpk)(0,4))/dM22; // ... // average correlation for all events: fIntFlowCorrelationsAllPro->Fill(1.5,two2n2nW2W2,dM22); } if(dM33) { two3n3nW3W3 = (pow(dReQ3n3k,2)+pow(dImQ3n3k,2)-(*fSMpk)(0,6))/dM33; // ... // average correlation for all events: fIntFlowCorrelationsAllPro->Fill(2.5,two3n3nW3W3,dM33); } if(dM44) { two4n4nW4W4 = (pow(dReQ4n4k,2)+pow(dImQ4n4k,2)-(*fSMpk)(0,8))/dM44; // ... // average correlation for all events: fIntFlowCorrelationsAllPro->Fill(3.5,two4n4nW4W4,dM44); } } // end of if(dMult>1) // extra 2-particle correlations: Double_t two1n1nW3W1 = 0.; // Double_t two1n1nW1W1W2 = 0.; // if(dMult>1) { if(dM31) { two1n1nW3W1 = (dReQ1n3k*dReQ1n1k+dImQ1n3k*dImQ1n1k-(*fSMpk)(0,4))/dM31; fIntFlowExtraCorrelationsPro->Fill(0.5,two1n1nW3W1,dM31); } if(dM211) { two1n1nW1W1W2 = ((*fSMpk)(0,2)*(pow(dReQ1n1k,2)+pow(dImQ1n1k,2)-(*fSMpk)(0,2)) - 2.*(dReQ1n3k*dReQ1n1k+dImQ1n3k*dImQ1n1k - (*fSMpk)(0,4)))/dM211; fIntFlowExtraCorrelationsPro->Fill(1.5,two1n1nW1W1W2,dM211); } } // end of if(dMult>1) //.............................................................................................. //.............................................................................................. // 3-particle correlations: Double_t three2n1n1nW2W1W1 = 0.; // if(dMult>2) { if(dM211) { three2n1n1nW2W1W1 = (pow(dReQ1n1k,2.)*dReQ2n2k+2.*dReQ1n1k*dImQ1n1k*dImQ2n2k-pow(dImQ1n1k,2.)*dReQ2n2k - 2.*(dReQ1n3k*dReQ1n1k+dImQ1n3k*dImQ1n1k) - pow(dReQ2n2k,2)-pow(dImQ2n2k,2) + 2.*(*fSMpk)(0,4))/dM211; fIntFlowCorrelationsAllPro->Fill(5.5,three2n1n1nW2W1W1,dM211); } } // end of if(dMult>2) //.............................................................................................. //.............................................................................................. // 4-particle correlations: Double_t four1n1n1n1nW1W1W1W1 = 0.; // if(dMult>3) { if(dM1111) { four1n1n1n1nW1W1W1W1 = (pow(pow(dReQ1n1k,2.)+pow(dImQ1n1k,2.),2) - 2.*(pow(dReQ1n1k,2.)*dReQ2n2k+2.*dReQ1n1k*dImQ1n1k*dImQ2n2k-pow(dImQ1n1k,2.)*dReQ2n2k) + 8.*(dReQ1n3k*dReQ1n1k+dImQ1n3k*dImQ1n1k) + (pow(dReQ2n2k,2)+pow(dImQ2n2k,2)) - 4.*(*fSMpk)(0,2)*(pow(dReQ1n1k,2)+pow(dImQ1n1k,2)) - 6.*(*fSMpk)(0,4)+2.*(*fSMpk)(1,2))/dM1111; // average correlation for single event: fIntFlowCorrelationsEBE->SetBinContent(2,four1n1n1n1nW1W1W1W1); fIntFlowEventWeightsForCorrelationsEBE->SetBinContent(2,dM1111); // average correlation for all events: fIntFlowCorrelationsPro->Fill(1.5,four1n1n1n1nW1W1W1W1,dM1111); fIntFlowCorrelationsAllPro->Fill(10.5,four1n1n1n1nW1W1W1W1,dM1111); } } // end of if(dMult>3) //.............................................................................................. } // end of AliFlowAnalysisWithQCumulants::CalculateIntFlowCorrelationsUsingParticleWeights() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CalculateWeightedQProductsForIntFlow() // to be improved (completed) { // calculate averages like <<2><4>>, <<2><6>>, <<4><6>>, etc. which are needed to calculate covariances // Remark: here we take weighted correlations! /* // binning of fQProductsW is organized as follows: // // 1st bin: <2><4> // 2nd bin: <2><6> // 3rd bin: <2><8> // 4th bin: <4><6> // 5th bin: <4><8> // 6th bin: <6><8> Double_t dMult = (*fSMpk)(0,0); // multiplicity (number of particles used to determine the reaction plane) Double_t dM11 = (*fSMpk)(1,1)-(*fSMpk)(0,2); // dM11 = sum_{i,j=1,i!=j}^M w_i w_j Double_t dM1111 = (*fSMpk)(3,1)-6.*(*fSMpk)(0,2)*(*fSMpk)(1,1) + 8.*(*fSMpk)(0,3)*(*fSMpk)(0,1) + 3.*(*fSMpk)(1,2)-6.*(*fSMpk)(0,4); // dM1111 = sum_{i,j,k,l=1,i!=j!=k!=l}^M w_i w_j w_k w_l Double_t twoEBEW = 0.; // <2> Double_t fourEBEW = 0.; // <4> twoEBEW = fQCorrelationsEBE[1]->GetBinContent(1); fourEBEW = fQCorrelationsEBE[1]->GetBinContent(11); // <2><4> if(dMult>3) { fQProducts[1][0]->Fill(0.5,twoEBEW*fourEBEW,dM11*dM1111); } */ } // end of AliFlowAnalysisWithQCumulants::CalculateWeightedQProductsForIntFlow() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::InitializeArraysForIntFlow() { // Initialize all arrays used to calculate integrated flow. for(Int_t sc=0;sc<2;sc++) // sin or cos terms { fIntFlowCorrectionTermsForNUAEBE[sc] = NULL; fIntFlowEventWeightForCorrectionTermsForNUAEBE[sc] = NULL; fIntFlowCorrectionTermsForNUAPro[sc] = NULL; fIntFlowCorrectionTermsForNUAHist[sc] = NULL; for(Int_t ci=0;ci<4;ci++) // correction term index { fIntFlowCorrectionTermsForNUAVsMPro[sc][ci] = NULL; } for(Int_t power=0;power<2;power++) // linear or quadratic { fIntFlowSumOfEventWeightsNUA[sc][power] = NULL; } } for(Int_t power=0;power<2;power++) // linear or quadratic { fIntFlowSumOfEventWeights[power] = NULL; } for(Int_t i=0;i<4;i++) // print on the screen the final results (0=RF, 1=RP, 2=POI, 3=RF (rebbined in M)) { fPrintFinalResults[i] = kTRUE; } for(Int_t ci=0;ci<4;ci++) // correlation index or cumulant order { fIntFlowCorrelationsVsMPro[ci] = NULL; fIntFlowCorrelationsVsMHist[ci] = NULL; fIntFlowQcumulantsVsM[ci] = NULL; fIntFlowVsM[ci] = NULL; fIntFlowDetectorBiasVsM[ci] = NULL; for(Int_t lc=0;lc<2;lc++) { fIntFlowSumOfEventWeightsVsM[ci][lc] = NULL; } } for(Int_t pi=0;pi<6;pi++) // product or covariance index { fIntFlowProductOfCorrelationsVsMPro[pi] = NULL; fIntFlowCovariancesVsM[pi] = NULL; fIntFlowSumOfProductOfEventWeightsVsM[pi] = NULL; } } // end of void AliFlowAnalysisWithQCumulants::InitializeArraysForIntFlow() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::InitializeArraysForDiffFlow() { // Initialize all arrays needed to calculate differential flow. // a) Initialize lists holding profiles; // b) Initialize lists holding histograms; // c) Initialize event-by-event quantities; // d) Initialize profiles; // e) Initialize histograms holding final results. // a) Initialize lists holding profiles; for(Int_t t=0;t<2;t++) // type (RP, POI) { for(Int_t pe=0;pe<2;pe++) // pt or eta { fDiffFlowCorrelationsProList[t][pe] = NULL; fDiffFlowProductOfCorrelationsProList[t][pe] = NULL; fDiffFlowCorrectionsProList[t][pe] = NULL; } } // b) Initialize lists holding histograms; for(Int_t t=0;t<2;t++) // type (RP, POI) { for(Int_t pe=0;pe<2;pe++) // pt or eta { fDiffFlowCorrelationsHistList[t][pe] = NULL; for(Int_t power=0;power<2;power++) { fDiffFlowSumOfEventWeightsHistList[t][pe][power] = NULL; } // end of for(Int_t power=0;power<2;power++) fDiffFlowSumOfProductOfEventWeightsHistList[t][pe] = NULL; fDiffFlowCorrectionsHistList[t][pe] = NULL; fDiffFlowCovariancesHistList[t][pe] = NULL; fDiffFlowCumulantsHistList[t][pe] = NULL; fDiffFlowHistList[t][pe] = NULL; } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta } // enf of for(Int_t t=0;t<2;t++) // type (RP, POI) // c) Initialize event-by-event quantities: // 1D: for(Int_t t=0;t<3;t++) // type (RP, POI, POI&&RP) { for(Int_t pe=0;pe<2;pe++) // pt or eta { for(Int_t m=0;m<4;m++) // multiple of harmonic { for(Int_t k=0;k<9;k++) // power of weight { fReRPQ1dEBE[t][pe][m][k] = NULL; fImRPQ1dEBE[t][pe][m][k] = NULL; fs1dEBE[t][pe][k] = NULL; // to be improved (this doesn't need to be within loop over m) } } } } // 1D: for(Int_t t=0;t<2;t++) // type (RP or POI) { for(Int_t pe=0;pe<2;pe++) // pt or eta { for(Int_t sc=0;sc<2;sc++) // sin or cos terms { for(Int_t cti=0;cti<9;cti++) // correction term index { fDiffFlowCorrectionTermsForNUAEBE[t][pe][sc][cti] = NULL; } } } } // 2D: for(Int_t t=0;t<3;t++) // type (RP, POI, POI&&RP) { for(Int_t m=0;m<4;m++) // multiple of harmonic { for(Int_t k=0;k<9;k++) // power of weight { fReRPQ2dEBE[t][m][k] = NULL; fImRPQ2dEBE[t][m][k] = NULL; fs2dEBE[t][k] = NULL; // to be improved (this doesn't need to be within loop over m) } } } // d) Initialize profiles: for(Int_t t=0;t<2;t++) // type: RP or POI { for(Int_t pe=0;pe<2;pe++) // pt or eta { for(Int_t ci=0;ci<4;ci++) // correlation index { fDiffFlowCorrelationsPro[t][pe][ci] = NULL; } // end of for(Int_t ci=0;ci<4;ci++) for(Int_t mci1=0;mci1<8;mci1++) // mixed correlation index { for(Int_t mci2=0;mci2<8;mci2++) // mixed correlation index { fDiffFlowProductOfCorrelationsPro[t][pe][mci1][mci2] = NULL; } // end of for(Int_t mci2=0;mci2<8;mci2++) // mixed correlation index } // end of for(Int_t mci1=0;mci1<8;mci1++) // mixed correlation index // correction terms for nua: for(Int_t sc=0;sc<2;sc++) // sin or cos terms { for(Int_t cti=0;cti<9;cti++) // correction term index { fDiffFlowCorrectionTermsForNUAPro[t][pe][sc][cti] = NULL; } } } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta } // end of for(Int_t t=0;t<2;t++) // type: RP or POI // e) Initialize histograms holding final results. for(Int_t t=0;t<2;t++) // type: RP or POI { for(Int_t pe=0;pe<2;pe++) // pt or eta { for(Int_t ci=0;ci<4;ci++) // correlation index { fDiffFlowCorrelationsHist[t][pe][ci] = NULL; fDiffFlowCumulants[t][pe][ci] = NULL; fDiffFlow[t][pe][ci] = NULL; } // end of for(Int_t ci=0;ci<4;ci++) for(Int_t covarianceIndex=0;covarianceIndex<5;covarianceIndex++) { fDiffFlowCovariances[t][pe][covarianceIndex] = NULL; } // end of for(Int_t covarianceIndex=0;covarianceIndex<5;covarianceIndex++) // correction terms for nua: for(Int_t sc=0;sc<2;sc++) // sin or cos terms { for(Int_t cti=0;cti<9;cti++) // correction term index { fDiffFlowCorrectionTermsForNUAHist[t][pe][sc][cti] = NULL; } } } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta } // end of for(Int_t t=0;t<2;t++) // type: RP or POI // sum of event weights for reduced correlations: for(Int_t t=0;t<2;t++) // type = RP or POI { for(Int_t pe=0;pe<2;pe++) // pt or eta { for(Int_t p=0;p<2;p++) // power of weight is 1 or 2 { for(Int_t ew=0;ew<4;ew++) // event weight index for reduced correlations { fDiffFlowSumOfEventWeights[t][pe][p][ew] = NULL; } } } } // product of event weights for both types of correlations: for(Int_t t=0;t<2;t++) // type = RP or POI { for(Int_t pe=0;pe<2;pe++) // pt or eta { for(Int_t mci1=0;mci1<8;mci1++) // mixed correlation index { for(Int_t mci2=0;mci2<8;mci2++) // mixed correlation index { fDiffFlowSumOfProductOfEventWeights[t][pe][mci1][mci2] = NULL; } } } } /* // nested lists in fDiffFlowProfiles: for(Int_t t=0;t<2;t++) { fDFPType[t] = NULL; for(Int_t pW=0;pW<2;pW++) // particle weights not used (0) or used (1) { fDFPParticleWeights[t][pW] = NULL; for(Int_t eW=0;eW<2;eW++) { fDFPEventWeights[t][pW][eW] = NULL; fDiffFlowCorrelations[t][pW][eW] = NULL; fDiffFlowProductsOfCorrelations[t][pW][eW] = NULL; for(Int_t sc=0;sc<2;sc++) { fDiffFlowCorrectionTerms[t][pW][eW][sc] = NULL; } } } } */ /* for(Int_t pW=0;pW<2;pW++) // particle weights not used (0) or used (1) { for(Int_t eW=0;eW<2;eW++) { // correlations: for(Int_t correlationIndex=0;correlationIndex<4;correlationIndex++) { fCorrelationsPro[t][pW][eW][correlationIndex] = NULL; } // products of correlations: for(Int_t productOfCorrelationsIndex=0;productOfCorrelationsIndex<6;productOfCorrelationsIndex++) { fProductsOfCorrelationsPro[t][pW][eW][productOfCorrelationsIndex] = NULL; } // correction terms: for(Int_t sc=0;sc<2;sc++) { for(Int_t correctionsIndex=0;correctionsIndex<2;correctionsIndex++) { fCorrectionTermsPro[t][pW][eW][sc][correctionsIndex] = NULL; } } } } */ } // end of AliFlowAnalysisWithQCumulants::InitializeArraysForDiffFlow() //================================================================================================================================ /* void AliFlowAnalysisWithQCumulants::CalculateCorrelationsForDifferentialFlow2D(TString type) { // calculate all reduced correlations needed for differential flow for each (pt,eta) bin: if(type == "RP") // to be improved (removed) { cout< // 1: <4'> // multiplicity: Double_t dMult = (*fSMpk)(0,0); // real and imaginary parts of non-weighted Q-vectors evaluated in harmonics n, 2n, 3n and 4n: Double_t dReQ1n = (*fReQ)(0,0); Double_t dReQ2n = (*fReQ)(1,0); //Double_t dReQ3n = (*fReQ)(2,0); //Double_t dReQ4n = (*fReQ)(3,0); Double_t dImQ1n = (*fImQ)(0,0); Double_t dImQ2n = (*fImQ)(1,0); //Double_t dImQ3n = (*fImQ)(2,0); //Double_t dImQ4n = (*fImQ)(3,0); // looping over all (pt,eta) bins and calculating correlations needed for differential flow: for(Int_t p=1;p<=fnBinsPt;p++) { for(Int_t e=1;e<=fnBinsEta;e++) { // real and imaginary parts of p_{m*n,0} (non-weighted Q-vector evaluated for POIs in particular (pt,eta) bin): Double_t p1n0kRe = 0.; Double_t p1n0kIm = 0.; // number of POIs in particular (pt,eta) bin: Double_t mp = 0.; // real and imaginary parts of q_{m*n,0} (non-weighted Q-vector evaluated for particles which are both RPs and POIs in particular (pt,eta) bin): Double_t q1n0kRe = 0.; Double_t q1n0kIm = 0.; Double_t q2n0kRe = 0.; Double_t q2n0kIm = 0.; // number of particles which are both RPs and POIs in particular (pt,eta) bin: Double_t mq = 0.; // q_{m*n,0}: q1n0kRe = fReEBE2D[2][0][0]->GetBinContent(fReEBE2D[2][0][0]->GetBin(p,e)) * fReEBE2D[2][0][0]->GetBinEntries(fReEBE2D[2][0][0]->GetBin(p,e)); q1n0kIm = fImEBE2D[2][0][0]->GetBinContent(fImEBE2D[2][0][0]->GetBin(p,e)) * fImEBE2D[2][0][0]->GetBinEntries(fImEBE2D[2][0][0]->GetBin(p,e)); q2n0kRe = fReEBE2D[2][1][0]->GetBinContent(fReEBE2D[2][1][0]->GetBin(p,e)) * fReEBE2D[2][1][0]->GetBinEntries(fReEBE2D[2][1][0]->GetBin(p,e)); q2n0kIm = fImEBE2D[2][1][0]->GetBinContent(fImEBE2D[2][1][0]->GetBin(p,e)) * fImEBE2D[2][1][0]->GetBinEntries(fImEBE2D[2][1][0]->GetBin(p,e)); mq = fReEBE2D[2][0][0]->GetBinEntries(fReEBE2D[2][0][0]->GetBin(p,e)); // to be improved (cross-checked by accessing other profiles here) if(type == "POI") { // p_{m*n,0}: p1n0kRe = fReEBE2D[1][0][0]->GetBinContent(fReEBE2D[1][0][0]->GetBin(p,e)) * fReEBE2D[1][0][0]->GetBinEntries(fReEBE2D[1][0][0]->GetBin(p,e)); p1n0kIm = fImEBE2D[1][0][0]->GetBinContent(fImEBE2D[1][0][0]->GetBin(p,e)) * fImEBE2D[1][0][0]->GetBinEntries(fImEBE2D[1][0][0]->GetBin(p,e)); mp = fReEBE2D[1][0][0]->GetBinEntries(fReEBE2D[1][0][0]->GetBin(p,e)); // to be improved (cross-checked by accessing other profiles here) typeFlag = 1; } else if(type == "RP") { // p_{m*n,0} = q_{m*n,0}: p1n0kRe = q1n0kRe; p1n0kIm = q1n0kIm; mp = mq; typeFlag = 0; } // count events with non-empty (pt,eta) bin: if(mp>0) { fNonEmptyBins2D[typeFlag]->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,1); } // 2'-particle correlation for particular (pt,eta) bin: Double_t two1n1nPtEta = 0.; if(mp*dMult-mq) { two1n1nPtEta = (p1n0kRe*dReQ1n+p1n0kIm*dImQ1n-mq) / (mp*dMult-mq); // fill the 2D profile to get the average correlation for each (pt,eta) bin: if(type == "POI") { //f2pPtEtaPOI->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,two1n1nPtEta,mp*dMult-mq); fCorrelationsPro[1][0][0][0]->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,two1n1nPtEta,mp*dMult-mq); } else if(type == "RP") { //f2pPtEtaRP->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,two1n1nPtEta,mp*dMult-mq); fCorrelationsPro[0][0][0][0]->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,two1n1nPtEta,mp*dMult-mq); } } // end of if(mp*dMult-mq) // 4'-particle correlation: Double_t four1n1n1n1nPtEta = 0.; if((mp-mq)*dMult*(dMult-1.)*(dMult-2.) + mq*(dMult-1.)*(dMult-2.)*(dMult-3.)) // to be improved (introduce a new variable for this expression) { four1n1n1n1nPtEta = ((pow(dReQ1n,2.)+pow(dImQ1n,2.))*(p1n0kRe*dReQ1n+p1n0kIm*dImQ1n) - q2n0kRe*(pow(dReQ1n,2.)-pow(dImQ1n,2.)) - 2.*q2n0kIm*dReQ1n*dImQ1n - p1n0kRe*(dReQ1n*dReQ2n+dImQ1n*dImQ2n) + p1n0kIm*(dImQ1n*dReQ2n-dReQ1n*dImQ2n) - 2.*dMult*(p1n0kRe*dReQ1n+p1n0kIm*dImQ1n) - 2.*(pow(dReQ1n,2.)+pow(dImQ1n,2.))*mq + 6.*(q1n0kRe*dReQ1n+q1n0kIm*dImQ1n) + 1.*(q2n0kRe*dReQ2n+q2n0kIm*dImQ2n) + 2.*(p1n0kRe*dReQ1n+p1n0kIm*dImQ1n) + 2.*mq*dMult - 6.*mq) / ((mp-mq)*dMult*(dMult-1.)*(dMult-2.) + mq*(dMult-1.)*(dMult-2.)*(dMult-3.)); // fill the 2D profile to get the average correlation for each (pt, eta) bin: if(type == "POI") { //f4pPtEtaPOI->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,four1n1n1n1nPtEta, // (mp-mq)*dMult*(dMult-1.)*(dMult-2.) // + mq*(dMult-1.)*(dMult-2.)*(dMult-3.)); fCorrelationsPro[1][0][0][1]->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,four1n1n1n1nPtEta, (mp-mq)*dMult*(dMult-1.)*(dMult-2.) + mq*(dMult-1.)*(dMult-2.)*(dMult-3.)); } else if(type == "RP") { //f4pPtEtaRP->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,four1n1n1n1nPtEta, // (mp-mq)*dMult*(dMult-1.)*(dMult-2.) // + mq*(dMult-1.)*(dMult-2.)*(dMult-3.)); fCorrelationsPro[0][0][0][1]->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,four1n1n1n1nPtEta, (mp-mq)*dMult*(dMult-1.)*(dMult-2.) + mq*(dMult-1.)*(dMult-2.)*(dMult-3.)); } } // end of if((mp-mq)*dMult*(dMult-1.)*(dMult-2.) // +mq*(dMult-1.)*(dMult-2.)*(dMult-3.)) } // end of for(Int_t e=1;e<=fnBinsEta;e++) } // end of for(Int_t p=1;p<=fnBinsPt;p++) } // end of AliFlowAnalysisWithQCumulants::CalculateCorrelationsForDifferentialFlow2D() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CalculateWeightedCorrelationsForDifferentialFlow2D(TString type) { // calculate all weighted correlations needed for differential flow if(type == "RP") // to be improved (removed) { cout<GetBinContent(fReEBE2D[1][0][0]->GetBin(p,e)) * fReEBE2D[1][0][0]->GetBinEntries(fReEBE2D[1][0][0]->GetBin(p,e)); p1n0kIm = fImEBE2D[1][0][0]->GetBinContent(fImEBE2D[1][0][0]->GetBin(p,e)) * fImEBE2D[1][0][0]->GetBinEntries(fImEBE2D[1][0][0]->GetBin(p,e)); mp = fReEBE2D[1][0][0]->GetBinEntries(fReEBE2D[1][0][0]->GetBin(p,e)); // q_{m*n,k}: q1n2kRe = fReEBE2D[2][0][2]->GetBinContent(fReEBE2D[2][0][2]->GetBin(p,e)) * fReEBE2D[2][0][2]->GetBinEntries(fReEBE2D[2][0][2]->GetBin(p,e)); q1n2kIm = fImEBE2D[2][0][2]->GetBinContent(fImEBE2D[2][0][2]->GetBin(p,e)) * fImEBE2D[2][0][2]->GetBinEntries(fImEBE2D[2][0][2]->GetBin(p,e)); q2n1kRe = fReEBE2D[2][1][1]->GetBinContent(fReEBE2D[2][1][1]->GetBin(p,e)) * fReEBE2D[2][1][1]->GetBinEntries(fReEBE2D[2][1][1]->GetBin(p,e)); q2n1kIm = fImEBE2D[2][1][1]->GetBinContent(fImEBE2D[2][1][1]->GetBin(p,e)) * fImEBE2D[2][1][1]->GetBinEntries(fImEBE2D[2][1][1]->GetBin(p,e)); // s_{1,1}, s_{1,2} and s_{1,3} // to be improved (add explanation) s1p1k = pow(fs2D[2][1]->GetBinContent(fs2D[2][1]->GetBin(p,e)),1.); s1p2k = pow(fs2D[2][2]->GetBinContent(fs2D[2][2]->GetBin(p,e)),1.); s1p3k = pow(fs2D[2][3]->GetBinContent(fs2D[2][3]->GetBin(p,e)),1.); // M0111 from Eq. (118) in QC2c (to be improved (notation)): dM0111 = mp*(dSM3p1k-3.*dSM1p1k*dSM1p2k+2.*dSM1p3k) - 3.*(s1p1k*(dSM2p1k-dSM1p2k) + 2.*(s1p3k-s1p2k*dSM1p1k)); } else if(type == "RP") { p1n0kRe = fReEBE2D[0][0][0]->GetBinContent(fReEBE2D[0][0][0]->GetBin(p,e)) * fReEBE2D[0][0][0]->GetBinEntries(fReEBE2D[0][0][0]->GetBin(p,e)); p1n0kIm = fImEBE2D[0][0][0]->GetBinContent(fImEBE2D[0][0][0]->GetBin(p,e)) * fImEBE2D[0][0][0]->GetBinEntries(fImEBE2D[0][0][0]->GetBin(p,e)); mp = fReEBE2D[0][0][0]->GetBinEntries(fReEBE2D[0][0][0]->GetBin(p,e)); // q_{m*n,k}: q1n2kRe = fReEBE2D[0][0][2]->GetBinContent(fReEBE2D[0][0][2]->GetBin(p,e)) * fReEBE2D[0][0][2]->GetBinEntries(fReEBE2D[0][0][2]->GetBin(p,e)); q1n2kIm = fImEBE2D[0][0][2]->GetBinContent(fImEBE2D[0][0][2]->GetBin(p,e)) * fImEBE2D[0][0][2]->GetBinEntries(fImEBE2D[0][0][2]->GetBin(p,e)); q2n1kRe = fReEBE2D[0][1][1]->GetBinContent(fReEBE2D[0][1][1]->GetBin(p,e)) * fReEBE2D[0][1][1]->GetBinEntries(fReEBE2D[0][1][1]->GetBin(p,e)); q2n1kIm = fImEBE2D[0][1][1]->GetBinContent(fImEBE2D[0][1][1]->GetBin(p,e)) * fImEBE2D[0][1][1]->GetBinEntries(fImEBE2D[0][1][1]->GetBin(p,e)); // s_{1,1}, s_{1,2} and s_{1,3} // to be improved (add explanation) s1p1k = pow(fs2D[0][1]->GetBinContent(fs2D[0][1]->GetBin(p,e)),1.); s1p2k = pow(fs2D[0][2]->GetBinContent(fs2D[0][2]->GetBin(p,e)),1.); s1p3k = pow(fs2D[0][3]->GetBinContent(fs2D[0][3]->GetBin(p,e)),1.); // M0111 from Eq. (118) in QC2c (to be improved (notation)): dM0111 = mp*(dSM3p1k-3.*dSM1p1k*dSM1p2k+2.*dSM1p3k) - 3.*(s1p1k*(dSM2p1k-dSM1p2k) + 2.*(s1p3k-s1p2k*dSM1p1k)); //............................................................................................... } // 2'-particle correlation: Double_t two1n1nW0W1PtEta = 0.; if(mp*dSM1p1k-s1p1k) { two1n1nW0W1PtEta = (p1n0kRe*dReQ1n1k+p1n0kIm*dImQ1n1k-s1p1k) / (mp*dSM1p1k-s1p1k); // fill the 2D profile to get the average correlation for each (pt, eta) bin: if(type == "POI") { //f2pPtEtaPOIW->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,two1n1nW0W1PtEta, // mp*dSM1p1k-s1p1k); fCorrelationsPro[1][1][0][0]->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,two1n1nW0W1PtEta,mp*dSM1p1k-s1p1k); } else if(type == "RP") { //f2pPtEtaRPW->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,two1n1nW0W1PtEta, // mp*dSM1p1k-s1p1k); fCorrelationsPro[0][1][0][0]->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,two1n1nW0W1PtEta,mp*dSM1p1k-s1p1k); } } // end of if(mp*dMult-dmPrimePrimePtEta) // 4'-particle correlation: Double_t four1n1n1n1nW0W1W1W1PtEta = 0.; if(dM0111) { four1n1n1n1nW0W1W1W1PtEta = ((pow(dReQ1n1k,2.)+pow(dImQ1n1k,2.))*(p1n0kRe*dReQ1n1k+p1n0kIm*dImQ1n1k) - q2n1kRe*(pow(dReQ1n1k,2.)-pow(dImQ1n1k,2.)) - 2.*q2n1kIm*dReQ1n1k*dImQ1n1k - p1n0kRe*(dReQ1n1k*dReQ2n2k+dImQ1n1k*dImQ2n2k) + p1n0kIm*(dImQ1n1k*dReQ2n2k-dReQ1n1k*dImQ2n2k) - 2.*dSM1p2k*(p1n0kRe*dReQ1n1k+p1n0kIm*dImQ1n1k) - 2.*(pow(dReQ1n1k,2.)+pow(dImQ1n1k,2.))*s1p1k + 6.*(q1n2kRe*dReQ1n1k+q1n2kIm*dImQ1n1k) + 1.*(q2n1kRe*dReQ2n2k+q2n1kIm*dImQ2n2k) + 2.*(p1n0kRe*dReQ1n3k+p1n0kIm*dImQ1n3k) + 2.*s1p1k*dSM1p2k - 6.*s1p3k) / dM0111; // to be imropoved (notation of dM0111) // fill the 2D profile to get the average correlation for each (pt, eta) bin: if(type == "POI") { //f4pPtEtaPOIW->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,four1n1n1n1nW0W1W1W1PtEta,dM0111); fCorrelationsPro[1][1][0][1]->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,four1n1n1n1nW0W1W1W1PtEta,dM0111); } else if(type == "RP") { //f4pPtEtaRPW->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,four1n1n1n1nW0W1W1W1PtEta,dM0111); fCorrelationsPro[0][1][0][1]->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,four1n1n1n1nW0W1W1W1PtEta,dM0111); } } // end of if(dM0111) } // end of for(Int_t e=1;e<=fnBinsEta;e++) } // end of for(Int_t p=1;p<=fnBinsPt;p++) } // end of AliFlowAnalysisWithQCumulants::CalculateWeightedCorrelationsForDifferentialFlow2D(TString type) //================================================================================================================================ */ /* void AliFlowAnalysisWithQCumulants::FinalizeCorrelationsForDiffFlow(TString type, Bool_t useParticleWeights, TString eventWeights) { // 1.) Access average for 2D correlations from profiles and store them in 2D final results histograms; // 2.) Access spread for 2D correlations from profiles, calculate error and store it in 2D final results histograms; // 3.) Make projections along pt and eta axis and store results and errors in 1D final results histograms. Int_t typeFlag = -1; Int_t pWeightsFlag = -1; Int_t eWeightsFlag = -1; if(type == "RP") { typeFlag = 0; } else if(type == "POI") { typeFlag = 1; } else { cout<<"WARNING: type must be either RP or POI in AFAWQC::FCFDF() !!!!"<GetBinContent(fNonEmptyBins2D[t]->GetBin(p,e))); } fNonEmptyBins1D[t][0]->SetBinContent(p,contentPt); } // eta: for(Int_t e=1;eGetBinContent(fNonEmptyBins2D[t]->GetBin(p,e))); } fNonEmptyBins1D[t][1]->SetBinContent(e,contentEta); } // from 2D profile in (pt,eta) make two 1D profiles in (pt) and (eta): TProfile *profile[2][4]; // [0=pt,1=eta][correlation index] // to be improved (do not hardwire the correlation index) for(Int_t pe=0;pe<2;pe++) // pt or eta { for(Int_t ci=0;ci<4;ci++) // correlation index { if(pe==0) profile[pe][ci] = this->MakePtProjection(fCorrelationsPro[t][pW][eW][ci]); if(pe==1) profile[pe][ci] = this->MakeEtaProjection(fCorrelationsPro[t][pW][eW][ci]); } } // transfer 2D profile into 2D histogram: // to be improved (see in documentation if there is a method to transfer values from 2D profile into 2D histogram) for(Int_t ci=0;ci<4;ci++) { for(Int_t p=1;p<=fnBinsPt;p++) { for(Int_t e=1;e<=fnBinsEta;e++) { Double_t correlation = fCorrelationsPro[t][pW][eW][ci]->GetBinContent(fCorrelationsPro[t][pW][eW][ci]->GetBin(p,e)); Double_t spread = fCorrelationsPro[t][pW][eW][ci]->GetBinError(fCorrelationsPro[t][pW][eW][ci]->GetBin(p,e)); Double_t nEvts = fNonEmptyBins2D[t]->GetBinContent(fNonEmptyBins2D[t]->GetBin(p,e)); Double_t error = 0.; fFinalCorrelations2D[t][pW][eW][ci]->SetBinContent(fFinalCorrelations2D[t][pW][eW][ci]->GetBin(p,e),correlation); if(nEvts>0) { error = spread/pow(nEvts,0.5); fFinalCorrelations2D[t][pW][eW][ci]->SetBinError(fFinalCorrelations2D[t][pW][eW][ci]->GetBin(p,e),error); } } // end of for(Int_t e=1;e<=fnBinsEta;e++) } // end of for(Int_t p=1;p<=fnBinsPt;p++) } // end of for(Int_t ci=0;ci<4;ci++) // transfer 1D profile into 1D histogram (pt): // to be improved (see in documentation if there is a method to transfer values from 1D profile into 1D histogram) for(Int_t ci=0;ci<4;ci++) { for(Int_t p=1;p<=fnBinsPt;p++) { if(profile[0][ci]) { Double_t correlation = profile[0][ci]->GetBinContent(p); Double_t spread = profile[0][ci]->GetBinError(p); Double_t nEvts = fNonEmptyBins1D[t][0]->GetBinContent(p); Double_t error = 0.; fFinalCorrelations1D[t][pW][eW][0][ci]->SetBinContent(p,correlation); if(nEvts>0) { error = spread/pow(nEvts,0.5); fFinalCorrelations1D[t][pW][eW][0][ci]->SetBinError(p,error); } } } // end of for(Int_t p=1;p<=fnBinsPt;p++) } // end of for(Int_t ci=0;ci<4;ci++) // transfer 1D profile into 1D histogram (eta): // to be improved (see in documentation if there is a method to transfer values from 1D profile into 1D histogram) for(Int_t ci=0;ci<4;ci++) { for(Int_t e=1;e<=fnBinsEta;e++) { if(profile[1][ci]) { Double_t correlation = profile[1][ci]->GetBinContent(e); fFinalCorrelations1D[t][pW][eW][1][ci]->SetBinContent(e,correlation); } } // end of for(Int_t e=1;e<=fnBinsEta;e++) } // end of for(Int_t ci=0;ci<4;ci++) } // end of void AliFlowAnalysisWithQCumulants::FinalizeCorrelationsForDiffFlow(TString type, Bool_t useParticleWeights, TString eventWeights) */ //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCumulants(TString type, TString ptOrEta) { // calcualate cumulants for differential flow from measured correlations // Remark: cumulants calculated here are NOT corrected for non-uniform acceptance. This correction is applied in the method ... // to be improved (description) Int_t typeFlag = -1; Int_t ptEtaFlag = -1; if(type == "RP") { typeFlag = 0; } else if(type == "POI") { typeFlag = 1; } if(ptOrEta == "Pt") { ptEtaFlag = 0; } else if(ptOrEta == "Eta") { ptEtaFlag = 1; } // shortcuts: Int_t t = typeFlag; Int_t pe = ptEtaFlag; // common: Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; // correlation <<2>>: Double_t two = fIntFlowCorrelationsHist->GetBinContent(1); // 1D: for(Int_t b=1;b<=nBinsPtEta[pe];b++) { // reduced correlations: Double_t twoPrime = fDiffFlowCorrelationsHist[t][pe][0]->GetBinContent(b); // <<2'>>(pt) Double_t fourPrime = fDiffFlowCorrelationsHist[t][pe][1]->GetBinContent(b); // <<4'>>(pt) // final statistical error of reduced correlations: //Double_t twoPrimeError = fFinalCorrelations1D[t][pW][eW][0][0]->GetBinError(p); // QC{2'}: Double_t qc2Prime = twoPrime; // QC{2'} //Double_t qc2PrimeError = twoPrimeError; // final stat. error of QC{2'} fDiffFlowCumulants[t][pe][0]->SetBinContent(b,qc2Prime); //fFinalCumulantsPt[t][pW][eW][nua][0]->SetBinError(p,qc2PrimeError); // QC{4'}: Double_t qc4Prime = fourPrime - 2.*twoPrime*two; // QC{4'} = <<4'>> - 2*<<2'>><<2>> fDiffFlowCumulants[t][pe][1]->SetBinContent(b,qc4Prime); } // end of for(Int_t p=1;p<=fnBinsPt;p++) /* // 2D (pt,eta): // to be improved (see documentation if I can do all this without looping) for(Int_t p=1;p<=fnBinsPt;p++) { for(Int_t e=1;e<=fnBinsEta;e++) { // reduced correlations: Double_t twoPrime = fFinalCorrelations2D[t][pW][eW][0]->GetBinContent(fFinalCorrelations2D[t][pW][eW][0]->GetBin(p,e)); // <<2'>>(pt,eta) Double_t fourPrime = fFinalCorrelations2D[t][pW][eW][1]->GetBinContent(fFinalCorrelations2D[t][pW][eW][1]->GetBin(p,e)); // <<4'>>(pt,eta) for(Int_t nua=0;nua<2;nua++) { // QC{2'}: Double_t qc2Prime = twoPrime; // QC{2'} = <<2'>> fFinalCumulants2D[t][pW][eW][nua][0]->SetBinContent(fFinalCumulants2D[t][pW][eW][nua][0]->GetBin(p,e),qc2Prime); // QC{4'}: Double_t qc4Prime = fourPrime - 2.*twoPrime*two; // QC{4'} = <<4'>> - 2*<<2'>><<2>> fFinalCumulants2D[t][pW][eW][nua][1]->SetBinContent(fFinalCumulants2D[t][pW][eW][nua][1]->GetBin(p,e),qc4Prime); } // end of for(Int_t nua=0;nua<2;nua++) } // end of for(Int_t e=1;e<=fnBinsEta;e++) } // end of for(Int_t p=1;p<=fnBinsPt;p++) */ } // end of void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCumulants(TString type, Bool_t useParticleWeights, TString eventWeights); //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CalculateFinalResultsForRPandPOIIntegratedFlow(TString type) { // calculate final results for integrated flow of RPs and POIs Int_t typeFlag = -1; if(type == "RP") { typeFlag = 0; } else if(type == "POI") { typeFlag = 1; } else { cout<<"WARNING: type must be either RP or POI in AFAWQC::CDF() !!!!"<GetHistPtPOI())->Clone(); yield4thPt = (TH1F*)(fCommonHists4th->GetHistPtPOI())->Clone(); yield6thPt = (TH1F*)(fCommonHists6th->GetHistPtPOI())->Clone(); yield8thPt = (TH1F*)(fCommonHists8th->GetHistPtPOI())->Clone(); } else if(type == "RP") { yield2ndPt = (TH1F*)(fCommonHists2nd->GetHistPtRP())->Clone(); yield4thPt = (TH1F*)(fCommonHists4th->GetHistPtRP())->Clone(); yield6thPt = (TH1F*)(fCommonHists6th->GetHistPtRP())->Clone(); yield8thPt = (TH1F*)(fCommonHists8th->GetHistPtRP())->Clone(); } Int_t nBinsPt = yield2ndPt->GetNbinsX(); TH1D *flow2ndPt = NULL; TH1D *flow4thPt = NULL; TH1D *flow6thPt = NULL; TH1D *flow8thPt = NULL; // to be improved (hardwired pt index) flow2ndPt = (TH1D*)fDiffFlow[t][0][0]->Clone(); flow4thPt = (TH1D*)fDiffFlow[t][0][1]->Clone(); flow6thPt = (TH1D*)fDiffFlow[t][0][2]->Clone(); flow8thPt = (TH1D*)fDiffFlow[t][0][3]->Clone(); Double_t dvn2nd = 0., dvn4th = 0., dvn6th = 0., dvn8th = 0.; // differential flow Double_t dErrvn2nd = 0., dErrvn4th = 0., dErrvn6th = 0., dErrvn8th = 0.; // error on differential flow Double_t dVn2nd = 0., dVn4th = 0., dVn6th = 0., dVn8th = 0.; // integrated flow Double_t dErrVn2nd = 0., dErrVn4th = 0., dErrVn6th = 0., dErrVn8th = 0.; // error on integrated flow Double_t dYield2nd = 0., dYield4th = 0., dYield6th = 0., dYield8th = 0.; // pt yield Double_t dSum2nd = 0., dSum4th = 0., dSum6th = 0., dSum8th = 0.; // needed for normalizing integrated flow // looping over pt bins: for(Int_t p=1;pGetBinContent(p); dvn4th = flow4thPt->GetBinContent(p); dvn6th = flow6thPt->GetBinContent(p); dvn8th = flow8thPt->GetBinContent(p); dErrvn2nd = flow2ndPt->GetBinError(p); dErrvn4th = flow4thPt->GetBinError(p); dErrvn6th = flow6thPt->GetBinError(p); dErrvn8th = flow8thPt->GetBinError(p); dYield2nd = yield2ndPt->GetBinContent(p); dYield4th = yield4thPt->GetBinContent(p); dYield6th = yield6thPt->GetBinContent(p); dYield8th = yield8thPt->GetBinContent(p); dVn2nd += dvn2nd*dYield2nd; dVn4th += dvn4th*dYield4th; dVn6th += dvn6th*dYield6th; dVn8th += dvn8th*dYield8th; dSum2nd += dYield2nd; dSum4th += dYield4th; dSum6th += dYield6th; dSum8th += dYield8th; dErrVn2nd += dYield2nd*dYield2nd*dErrvn2nd*dErrvn2nd; // ro be improved (check this relation) dErrVn4th += dYield4th*dYield4th*dErrvn4th*dErrvn4th; dErrVn6th += dYield6th*dYield6th*dErrvn6th*dErrvn6th; dErrVn8th += dYield8th*dYield8th*dErrvn8th*dErrvn8th; } // end of for(Int_t p=1;pFillIntegratedFlowPOI(dVn2nd,dErrVn2nd); fCommonHistsResults4th->FillIntegratedFlowPOI(dVn4th,dErrVn4th); fCommonHistsResults6th->FillIntegratedFlowPOI(dVn6th,0.); // to be improved (errors) fCommonHistsResults8th->FillIntegratedFlowPOI(dVn8th,0.); // to be improved (errors) } else if (type == "RP") { fCommonHistsResults2nd->FillIntegratedFlowRP(dVn2nd,dErrVn2nd); fCommonHistsResults4th->FillIntegratedFlowRP(dVn4th,dErrVn4th); fCommonHistsResults6th->FillIntegratedFlowRP(dVn6th,0.); // to be improved (errors) fCommonHistsResults8th->FillIntegratedFlowRP(dVn8th,0.); // to be improved (errors) } delete flow2ndPt; delete flow4thPt; //delete flow6thPt; //delete flow8thPt; delete yield2ndPt; delete yield4thPt; delete yield6thPt; delete yield8thPt; } // end of AliFlowAnalysisWithQCumulants::CalculateFinalResultsForRPandPOIIntegratedFlow(TString type) //================================================================================================================================ void AliFlowAnalysisWithQCumulants::InitializeArraysForDistributions() { // Initialize all arrays used for distributions. // a) Initialize arrays of histograms used to hold distributions of correlations; // b) Initialize array to hold min and max values of correlations. // a) Initialize arrays of histograms used to hold distributions of correlations: for(Int_t di=0;di<4;di++) // distribution index { fDistributions[di] = NULL; } // b) Initialize default min and max values of correlations: // (Remark: The default values bellow were chosen for v2=5% and M=500) fMinValueOfCorrelation[0] = -0.01; // <2>_min fMaxValueOfCorrelation[0] = 0.04; // <2>_max fMinValueOfCorrelation[1] = -0.00002; // <4>_min fMaxValueOfCorrelation[1] = 0.00015; // <4>_max fMinValueOfCorrelation[2] = -0.0000003; // <6>_min fMaxValueOfCorrelation[2] = 0.0000006; // <6>_max fMinValueOfCorrelation[3] = -0.000000006; // <8>_min fMaxValueOfCorrelation[3] = 0.000000003; // <8>_max } // end of void AliFlowAnalysisWithQCumulants::InitializeArraysForDistributions() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::BookEverythingForDistributions() { // a) Book profile to hold all flags for distributions of correlations; // b) Book all histograms to hold distributions of correlations. TString correlationIndex[4] = {"<2>","<4>","<6>","<8>"}; // to be improved (should I promote this to data members?) // a) Book profile to hold all flags for distributions of correlations: TString distributionsFlagsName = "fDistributionsFlags"; distributionsFlagsName += fAnalysisLabel->Data(); fDistributionsFlags = new TProfile(distributionsFlagsName.Data(),"Flags for Distributions of Correlations",9,0,9); fDistributionsFlags->SetTickLength(-0.01,"Y"); fDistributionsFlags->SetMarkerStyle(25); fDistributionsFlags->SetLabelSize(0.05); fDistributionsFlags->SetLabelOffset(0.02,"Y"); fDistributionsFlags->GetXaxis()->SetBinLabel(1,"Store or not?"); fDistributionsFlags->GetXaxis()->SetBinLabel(2,"<2>_{min}"); fDistributionsFlags->GetXaxis()->SetBinLabel(3,"<2>_{max}"); fDistributionsFlags->GetXaxis()->SetBinLabel(4,"<4>_{min}"); fDistributionsFlags->GetXaxis()->SetBinLabel(5,"<4>_{max}"); fDistributionsFlags->GetXaxis()->SetBinLabel(6,"<6>_{min}"); fDistributionsFlags->GetXaxis()->SetBinLabel(7,"<6>_{max}"); fDistributionsFlags->GetXaxis()->SetBinLabel(8,"<8>_{min}"); fDistributionsFlags->GetXaxis()->SetBinLabel(9,"<8>_{max}"); fDistributionsList->Add(fDistributionsFlags); // b) Book all histograms to hold distributions of correlations. if(fStoreDistributions) { TString distributionsName = "fDistributions"; distributionsName += fAnalysisLabel->Data(); for(Int_t di=0;di<4;di++) // distribution index { fDistributions[di] = new TH1D(Form("Distribution of %s",correlationIndex[di].Data()),Form("Distribution of %s",correlationIndex[di].Data()),10000,fMinValueOfCorrelation[di],fMaxValueOfCorrelation[di]); fDistributions[di]->SetXTitle(correlationIndex[di].Data()); fDistributionsList->Add(fDistributions[di]); } // end of for(Int_t di=0;di<4;di++) // distribution index } // end of if(fStoreDistributions) } // end of void AliFlowAnalysisWithQCumulants::BookEverythingForDistributions() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::StoreFlagsForDistributions() { // Store all flags for distributiuons of correlations in profile fDistributionsFlags. if(!fDistributionsFlags) { cout<<"WARNING: fDistributionsFlags is NULL in AFAWQC::SDF() !!!!"<Fill(0.5,(Int_t)fStoreDistributions); // histos with distributions of correlations stored or not in the output file // store min and max values of correlations: for(Int_t di=0;di<4;di++) // distribution index { fDistributionsFlags->Fill(1.5+2.*(Double_t)di,fMinValueOfCorrelation[di]); fDistributionsFlags->Fill(2.5+2.*(Double_t)di,fMaxValueOfCorrelation[di]); } } // end of void AliFlowAnalysisWithQCumulants::StoreFlagsForDistributions() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::StoreDistributionsOfCorrelations() { // Store distributions of correlations. if(!(fIntFlowCorrelationsEBE && fIntFlowEventWeightsForCorrelationsEBE)) { cout<<"WARNING: fIntFlowCorrelationsEBE && fIntFlowEventWeightsForCorrelationsEBE"<SetOwner(kTRUE); fHistList->Add(fIntFlowList); // list holding profiles: fIntFlowProfiles = new TList(); fIntFlowProfiles->SetName("Profiles"); fIntFlowProfiles->SetOwner(kTRUE); fIntFlowList->Add(fIntFlowProfiles); // list holding histograms with results: fIntFlowResults = new TList(); fIntFlowResults->SetName("Results"); fIntFlowResults->SetOwner(kTRUE); fIntFlowList->Add(fIntFlowResults); // b) Book and nest lists for differential flow; fDiffFlowList = new TList(); fDiffFlowList->SetName("Differential Flow"); fDiffFlowList->SetOwner(kTRUE); fHistList->Add(fDiffFlowList); // list holding profiles: fDiffFlowProfiles = new TList(); fDiffFlowProfiles->SetName("Profiles"); fDiffFlowProfiles->SetOwner(kTRUE); fDiffFlowList->Add(fDiffFlowProfiles); // list holding histograms with results: fDiffFlowResults = new TList(); fDiffFlowResults->SetName("Results"); fDiffFlowResults->SetOwner(kTRUE); fDiffFlowList->Add(fDiffFlowResults); // flags used for naming nested lists in list fDiffFlowProfiles and fDiffFlowResults: TList list; list.SetOwner(kTRUE); TString typeFlag[2] = {"RP","POI"}; TString ptEtaFlag[2] = {"p_{T}","#eta"}; TString powerFlag[2] = {"linear","quadratic"}; // nested lists in fDiffFlowProfiles (~/Differential Flow/Profiles): for(Int_t t=0;t<2;t++) // type: RP or POI { for(Int_t pe=0;pe<2;pe++) // pt or eta { // list holding profiles with correlations: fDiffFlowCorrelationsProList[t][pe] = (TList*)list.Clone(); fDiffFlowCorrelationsProList[t][pe]->SetName(Form("Profiles with correlations (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data())); fDiffFlowProfiles->Add(fDiffFlowCorrelationsProList[t][pe]); // list holding profiles with products of correlations: fDiffFlowProductOfCorrelationsProList[t][pe] = (TList*)list.Clone(); fDiffFlowProductOfCorrelationsProList[t][pe]->SetName(Form("Profiles with products of correlations (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data())); fDiffFlowProfiles->Add(fDiffFlowProductOfCorrelationsProList[t][pe]); // list holding profiles with corrections: fDiffFlowCorrectionsProList[t][pe] = (TList*)list.Clone(); fDiffFlowCorrectionsProList[t][pe]->SetName(Form("Profiles with correction terms for NUA (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data())); fDiffFlowProfiles->Add(fDiffFlowCorrectionsProList[t][pe]); } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta } // end of for(Int_t t=0;t<2;t++) // type: RP or POI // nested lists in fDiffFlowResults (~/Differential Flow/Results): for(Int_t t=0;t<2;t++) // type: RP or POI { for(Int_t pe=0;pe<2;pe++) // pt or eta { // list holding histograms with correlations: fDiffFlowCorrelationsHistList[t][pe] = (TList*)list.Clone(); fDiffFlowCorrelationsHistList[t][pe]->SetName(Form("Correlations (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data())); fDiffFlowResults->Add(fDiffFlowCorrelationsHistList[t][pe]); // list holding histograms with corrections: fDiffFlowCorrectionsHistList[t][pe] = (TList*)list.Clone(); fDiffFlowCorrectionsHistList[t][pe]->SetName(Form("Histograms with correction terms for NUA (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data())); fDiffFlowResults->Add(fDiffFlowCorrectionsHistList[t][pe]); for(Int_t power=0;power<2;power++) { // list holding histograms with sums of event weights: fDiffFlowSumOfEventWeightsHistList[t][pe][power] = (TList*)list.Clone(); fDiffFlowSumOfEventWeightsHistList[t][pe][power]->SetName(Form("Sum of %s event weights (%s, %s)",powerFlag[power].Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data())); fDiffFlowResults->Add(fDiffFlowSumOfEventWeightsHistList[t][pe][power]); } // end of for(Int_t power=0;power<2;power++) // list holding histograms with sums of products of event weights: fDiffFlowSumOfProductOfEventWeightsHistList[t][pe] = (TList*)list.Clone(); fDiffFlowSumOfProductOfEventWeightsHistList[t][pe]->SetName(Form("Sum of products of event weights (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data())); fDiffFlowResults->Add(fDiffFlowSumOfProductOfEventWeightsHistList[t][pe]); // list holding histograms with covariances of correlations: fDiffFlowCovariancesHistList[t][pe] = (TList*)list.Clone(); fDiffFlowCovariancesHistList[t][pe]->SetName(Form("Covariances of correlations (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data())); fDiffFlowResults->Add(fDiffFlowCovariancesHistList[t][pe]); // list holding histograms with differential Q-cumulants: fDiffFlowCumulantsHistList[t][pe] = (TList*)list.Clone(); fDiffFlowCumulantsHistList[t][pe]->SetName(Form("Differential Q-cumulants (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data())); fDiffFlowResults->Add(fDiffFlowCumulantsHistList[t][pe]); // list holding histograms with differential flow estimates from Q-cumulants: fDiffFlowHistList[t][pe] = (TList*)list.Clone(); fDiffFlowHistList[t][pe]->SetName(Form("Differential flow (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data())); fDiffFlowResults->Add(fDiffFlowHistList[t][pe]); } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta } // end of for(Int_t t=0;t<2;t++) // type: RP or POI // c) Book and nest list for particle weights: fWeightsList->SetName("Weights"); fWeightsList->SetOwner(kTRUE); fHistList->Add(fWeightsList); // d) Book and nest list for distributions: fDistributionsList = new TList(); fDistributionsList->SetName("Distributions"); fDistributionsList->SetOwner(kTRUE); fHistList->Add(fDistributionsList); // e) Book and nest list for nested loops: fNestedLoopsList = new TList(); fNestedLoopsList->SetName("Nested Loops"); fNestedLoopsList->SetOwner(kTRUE); fHistList->Add(fNestedLoopsList); } // end of void AliFlowAnalysisWithQCumulants::BookAndNestAllLists() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::FillCommonHistResultsDiffFlow(TString type) { // fill common result histograms for differential flow Int_t typeFlag = -1; //Int_t ptEtaFlag = -1; if(type == "RP") { typeFlag = 0; } else if(type == "POI") { typeFlag = 1; } // shortcuts: Int_t t = typeFlag; //Int_t pe = ptEtaFlag; // to be improved (implement protection here) if(!(fCommonHistsResults2nd && fCommonHistsResults4th && fCommonHistsResults6th && fCommonHistsResults8th)) { cout<<"WARNING: fCommonHistsResults2nd && fCommonHistsResults4th && fCommonHistsResults6th && fCommonHistsResults8th"<GetBinContent(p); Double_t v4 = fDiffFlow[t][0][1]->GetBinContent(p); Double_t v6 = fDiffFlow[t][0][2]->GetBinContent(p); Double_t v8 = fDiffFlow[t][0][3]->GetBinContent(p); Double_t v2Error = fDiffFlow[t][0][0]->GetBinError(p); Double_t v4Error = fDiffFlow[t][0][1]->GetBinError(p); //Double_t v6Error = fFinalFlow1D[t][pW][nua][0][2]->GetBinError(p); //Double_t v8Error = fFinalFlow1D[t][pW][nua][0][3]->GetBinError(p); if(type == "RP") { fCommonHistsResults2nd->FillDifferentialFlowPtRP(p,v2,v2Error); fCommonHistsResults4th->FillDifferentialFlowPtRP(p,v4,v4Error); fCommonHistsResults6th->FillDifferentialFlowPtRP(p,v6,0.); fCommonHistsResults8th->FillDifferentialFlowPtRP(p,v8,0.); } else if(type == "POI") { fCommonHistsResults2nd->FillDifferentialFlowPtPOI(p,v2,v2Error); fCommonHistsResults4th->FillDifferentialFlowPtPOI(p,v4,v4Error); fCommonHistsResults6th->FillDifferentialFlowPtPOI(p,v6,0.); fCommonHistsResults8th->FillDifferentialFlowPtPOI(p,v8,0.); } } // end of for(Int_t p=1;p<=fnBinsPt;p++) // eta: for(Int_t e=1;e<=fnBinsEta;e++) { Double_t v2 = fDiffFlow[t][1][0]->GetBinContent(e); Double_t v4 = fDiffFlow[t][1][1]->GetBinContent(e); Double_t v6 = fDiffFlow[t][1][2]->GetBinContent(e); Double_t v8 = fDiffFlow[t][1][3]->GetBinContent(e); Double_t v2Error = fDiffFlow[t][1][0]->GetBinError(e); Double_t v4Error = fDiffFlow[t][1][1]->GetBinError(e); //Double_t v6Error = fDiffFlow[t][1][2]->GetBinError(e); //Double_t v8Error = fDiffFlow[t][1][3]->GetBinError(e); if(type == "RP") { fCommonHistsResults2nd->FillDifferentialFlowEtaRP(e,v2,v2Error); fCommonHistsResults4th->FillDifferentialFlowEtaRP(e,v4,v4Error); fCommonHistsResults6th->FillDifferentialFlowEtaRP(e,v6,0.); fCommonHistsResults8th->FillDifferentialFlowEtaRP(e,v8,0.); } else if(type == "POI") { fCommonHistsResults2nd->FillDifferentialFlowEtaPOI(e,v2,v2Error); fCommonHistsResults4th->FillDifferentialFlowEtaPOI(e,v4,v4Error); fCommonHistsResults6th->FillDifferentialFlowEtaPOI(e,v6,0.); fCommonHistsResults8th->FillDifferentialFlowEtaPOI(e,v8,0.); } } // end of for(Int_t e=1;e<=fnBinsEta;e++) } // end of void AliFlowAnalysisWithQCumulants::FillCommonHistResultsDiffFlow(TString type, Bool_t useParticleWeights, TString eventWeights, Bool_t correctedForNUA) //================================================================================================================================ void AliFlowAnalysisWithQCumulants::AccessConstants() { // Access needed common constants from AliFlowCommonConstants. fnBinsPhi = AliFlowCommonConstants::GetMaster()->GetNbinsPhi(); fPhiMin = AliFlowCommonConstants::GetMaster()->GetPhiMin(); fPhiMax = AliFlowCommonConstants::GetMaster()->GetPhiMax(); if(fnBinsPhi) fPhiBinWidth = (fPhiMax-fPhiMin)/fnBinsPhi; fnBinsPt = AliFlowCommonConstants::GetMaster()->GetNbinsPt(); fPtMin = AliFlowCommonConstants::GetMaster()->GetPtMin(); fPtMax = AliFlowCommonConstants::GetMaster()->GetPtMax(); if(fnBinsPt) fPtBinWidth = (fPtMax-fPtMin)/fnBinsPt; fnBinsEta = AliFlowCommonConstants::GetMaster()->GetNbinsEta(); fEtaMin = AliFlowCommonConstants::GetMaster()->GetEtaMin(); fEtaMax = AliFlowCommonConstants::GetMaster()->GetEtaMax(); if(fnBinsEta) fEtaBinWidth = (fEtaMax-fEtaMin)/fnBinsEta; } // end of void AliFlowAnalysisWithQCumulants::AccessConstants() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CrossCheckSettings() { // a) Cross check if the choice for multiplicity weights make sense; // a) Cross check if the choice for multiplicity weights make sense: if(strcmp(fMultiplicityWeight->Data(),"combinations") && strcmp(fMultiplicityWeight->Data(),"unit") && strcmp(fMultiplicityWeight->Data(),"multiplicity")) { cout<<"WARNING (QC): Multiplicity weight can be either \"combinations\", \"unit\""<Data()<<"\"."<Fill(ci+0.5,pow(fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(ci+1),p+1)); if(fCalculateCumulantsVsM) { fIntFlowSumOfEventWeightsVsM[ci][p]->Fill(dMult+0.5,pow(fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(ci+1),p+1)); // to be improved: dMult => sum of weights? } } } } // end of void AliFlowAnalysisWithQCumulants::CalculateIntFlowSumOfEventWeights() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CalculateIntFlowSumOfEventWeightsNUA() { // Calculate sum of linear and quadratic event weights for NUA terms. for(Int_t sc=0;sc<2;sc++) // sin or cos terms { for(Int_t p=0;p<2;p++) // power-1 { for(Int_t ci=0;ci<3;ci++) // nua term index { fIntFlowSumOfEventWeightsNUA[sc][p]->Fill(ci+0.5,pow(fIntFlowEventWeightForCorrectionTermsForNUAEBE[sc]->GetBinContent(ci+1),p+1)); } } } } // end of void AliFlowAnalysisWithQCumulants::CalculateIntFlowSumOfEventWeightsNUA() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CalculateIntFlowSumOfProductOfEventWeights() { // Calculate sum of product of event weights for correlations. // multiplicity: Double_t dMult = (*fSMpk)(0,0); Int_t counter = 0; for(Int_t ci1=1;ci1<4;ci1++) { for(Int_t ci2=ci1+1;ci2<=4;ci2++) { fIntFlowSumOfProductOfEventWeights->Fill(0.5+counter, fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(ci1)* fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(ci2)); if(fCalculateCumulantsVsM) { fIntFlowSumOfProductOfEventWeightsVsM[counter]->Fill(dMult+0.5, // to be improved: dMult => sum of weights? fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(ci1)* fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(ci2)); } // end of if(fCalculateCumulantsVsM) counter++; } } } // end of void AliFlowAnalysisWithQCumulants::CalculateIntFlowSumOfProductOfEventWeights() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CalculateIntFlowSumOfProductOfEventWeightsNUA() { // Calculate sum of product of event weights for NUA terms. // w_{<2>} * w_{}: fIntFlowSumOfProductOfEventWeightsNUA->Fill(0.5,fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1)); // w_{<2>} * w_{}: fIntFlowSumOfProductOfEventWeightsNUA->Fill(1.5,fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1)); // w_{ * w_{}: fIntFlowSumOfProductOfEventWeightsNUA->Fill(2.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1)); // w_{<2>} * w{} fIntFlowSumOfProductOfEventWeightsNUA->Fill(3.5,fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2)); // w_{<2>} * w{} fIntFlowSumOfProductOfEventWeightsNUA->Fill(4.5,fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2)); // w_{<2>} * w{} fIntFlowSumOfProductOfEventWeightsNUA->Fill(5.5,fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)); // w_{<2>} * w{} fIntFlowSumOfProductOfEventWeightsNUA->Fill(6.5,fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); // w_{<4>} * w{} fIntFlowSumOfProductOfEventWeightsNUA->Fill(7.5,fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1)); // w_{<4>} * w{} fIntFlowSumOfProductOfEventWeightsNUA->Fill(8.5,fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1)); // w_{<4>} * w{} fIntFlowSumOfProductOfEventWeightsNUA->Fill(9.5,fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2)); // w_{<4>} * w{} fIntFlowSumOfProductOfEventWeightsNUA->Fill(10.5,fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2)); // w_{<4>} * w{} fIntFlowSumOfProductOfEventWeightsNUA->Fill(11.5,fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)); // w_{<4>} * w{} fIntFlowSumOfProductOfEventWeightsNUA->Fill(12.5,fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); // w_{} * w{} fIntFlowSumOfProductOfEventWeightsNUA->Fill(13.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2)); // w_{} * w{} fIntFlowSumOfProductOfEventWeightsNUA->Fill(14.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2)); // w_{} * w{} fIntFlowSumOfProductOfEventWeightsNUA->Fill(15.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)); // w_{} * w{} fIntFlowSumOfProductOfEventWeightsNUA->Fill(16.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); // w_{} * w{} fIntFlowSumOfProductOfEventWeightsNUA->Fill(17.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2)); // w_{} * w{} fIntFlowSumOfProductOfEventWeightsNUA->Fill(18.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2)); // w_{} * w{} fIntFlowSumOfProductOfEventWeightsNUA->Fill(19.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)); // w_{} * w{} fIntFlowSumOfProductOfEventWeightsNUA->Fill(20.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); // w_{} * w{} fIntFlowSumOfProductOfEventWeightsNUA->Fill(21.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2)); // w_{} * w{} fIntFlowSumOfProductOfEventWeightsNUA->Fill(22.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)); // w_{} * w{} fIntFlowSumOfProductOfEventWeightsNUA->Fill(23.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); // w_{} * w{} fIntFlowSumOfProductOfEventWeightsNUA->Fill(24.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)); // w_{} * w{} fIntFlowSumOfProductOfEventWeightsNUA->Fill(25.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); // w_{} * w{} fIntFlowSumOfProductOfEventWeightsNUA->Fill(26.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)* fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); } // end of void AliFlowAnalysisWithQCumulants::CalculateIntFlowIntFlowSumOfProductOfEventWeightsNUA() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrelations(TString type, TString ptOrEta) { // calculate reduced correlations for RPs or POIs in pt or eta bins // multiplicity: Double_t dMult = (*fSMpk)(0,0); // real and imaginary parts of non-weighted Q-vectors evaluated in harmonics n, 2n, 3n and 4n: Double_t dReQ1n = (*fReQ)(0,0); Double_t dReQ2n = (*fReQ)(1,0); //Double_t dReQ3n = (*fReQ)(2,0); //Double_t dReQ4n = (*fReQ)(3,0); Double_t dImQ1n = (*fImQ)(0,0); Double_t dImQ2n = (*fImQ)(1,0); //Double_t dImQ3n = (*fImQ)(2,0); //Double_t dImQ4n = (*fImQ)(3,0); // reduced correlations are stored in fDiffFlowCorrelationsPro[0=RP,1=POI][0=pt,1=eta][correlation index]. Correlation index runs as follows: // // 0: <<2'>> // 1: <<4'>> // 2: <<6'>> // 3: <<8'>> Int_t t = -1; // type flag Int_t pe = -1; // ptEta flag if(type == "RP") { t = 0; } else if(type == "POI") { t = 1; } if(ptOrEta == "Pt") { pe = 0; } else if(ptOrEta == "Eta") { pe = 1; } Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; Double_t minPtEta[2] = {fPtMin,fEtaMin}; //Double_t maxPtEta[2] = {fPtMax,fEtaMax}; Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; // looping over all bins and calculating reduced correlations: for(Int_t b=1;b<=nBinsPtEta[pe];b++) { // real and imaginary parts of p_{m*n,0} (non-weighted Q-vector evaluated for POIs in particular pt or eta bin): Double_t p1n0kRe = 0.; Double_t p1n0kIm = 0.; // number of POIs in particular pt or eta bin: Double_t mp = 0.; // real and imaginary parts of q_{m*n,0} (non-weighted Q-vector evaluated for particles which are both RPs and POIs in particular pt or eta bin): Double_t q1n0kRe = 0.; Double_t q1n0kIm = 0.; Double_t q2n0kRe = 0.; Double_t q2n0kIm = 0.; // number of particles which are both RPs and POIs in particular pt or eta bin: Double_t mq = 0.; if(type == "POI") { // q_{m*n,0}: q1n0kRe = fReRPQ1dEBE[2][pe][0][0]->GetBinContent(fReRPQ1dEBE[2][pe][0][0]->GetBin(b)) * fReRPQ1dEBE[2][pe][0][0]->GetBinEntries(fReRPQ1dEBE[2][pe][0][0]->GetBin(b)); q1n0kIm = fImRPQ1dEBE[2][pe][0][0]->GetBinContent(fImRPQ1dEBE[2][pe][0][0]->GetBin(b)) * fImRPQ1dEBE[2][pe][0][0]->GetBinEntries(fImRPQ1dEBE[2][pe][0][0]->GetBin(b)); q2n0kRe = fReRPQ1dEBE[2][pe][1][0]->GetBinContent(fReRPQ1dEBE[2][pe][1][0]->GetBin(b)) * fReRPQ1dEBE[2][pe][1][0]->GetBinEntries(fReRPQ1dEBE[2][pe][1][0]->GetBin(b)); q2n0kIm = fImRPQ1dEBE[2][pe][1][0]->GetBinContent(fImRPQ1dEBE[2][pe][1][0]->GetBin(b)) * fImRPQ1dEBE[2][pe][1][0]->GetBinEntries(fImRPQ1dEBE[2][pe][1][0]->GetBin(b)); mq = fReRPQ1dEBE[2][pe][0][0]->GetBinEntries(fReRPQ1dEBE[2][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) } else if(type == "RP") { // q_{m*n,0}: q1n0kRe = fReRPQ1dEBE[0][pe][0][0]->GetBinContent(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)) * fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)); q1n0kIm = fImRPQ1dEBE[0][pe][0][0]->GetBinContent(fImRPQ1dEBE[0][pe][0][0]->GetBin(b)) * fImRPQ1dEBE[0][pe][0][0]->GetBinEntries(fImRPQ1dEBE[0][pe][0][0]->GetBin(b)); q2n0kRe = fReRPQ1dEBE[0][pe][1][0]->GetBinContent(fReRPQ1dEBE[0][pe][1][0]->GetBin(b)) * fReRPQ1dEBE[0][pe][1][0]->GetBinEntries(fReRPQ1dEBE[0][pe][1][0]->GetBin(b)); q2n0kIm = fImRPQ1dEBE[0][pe][1][0]->GetBinContent(fImRPQ1dEBE[0][pe][1][0]->GetBin(b)) * fImRPQ1dEBE[0][pe][1][0]->GetBinEntries(fImRPQ1dEBE[0][pe][1][0]->GetBin(b)); mq = fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) } if(type == "POI") { // p_{m*n,0}: p1n0kRe = fReRPQ1dEBE[1][pe][0][0]->GetBinContent(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)) * fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)); p1n0kIm = fImRPQ1dEBE[1][pe][0][0]->GetBinContent(fImRPQ1dEBE[1][pe][0][0]->GetBin(b)) * fImRPQ1dEBE[1][pe][0][0]->GetBinEntries(fImRPQ1dEBE[1][pe][0][0]->GetBin(b)); mp = fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) t = 1; // typeFlag = RP or POI } else if(type == "RP") { // p_{m*n,0} = q_{m*n,0}: p1n0kRe = q1n0kRe; p1n0kIm = q1n0kIm; mp = mq; t = 0; // typeFlag = RP or POI } // 2'-particle correlation for particular (pt,eta) bin: Double_t two1n1nPtEta = 0.; if(mp*dMult-mq) { two1n1nPtEta = (p1n0kRe*dReQ1n+p1n0kIm*dImQ1n-mq) / (mp*dMult-mq); if(type == "POI") // to be improved (I do not this if) { // fill profile to get <<2'>> for POIs fDiffFlowCorrelationsPro[1][pe][0]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],two1n1nPtEta,mp*dMult-mq); // histogram to store <2'> for POIs e-b-e (needed in some other methods): fDiffFlowCorrelationsEBE[1][pe][0]->SetBinContent(b,two1n1nPtEta); fDiffFlowEventWeightsForCorrelationsEBE[1][pe][0]->SetBinContent(b,mp*dMult-mq); } else if(type == "RP") // to be improved (I do not this if) { // profile to get <<2'>> for RPs: fDiffFlowCorrelationsPro[0][pe][0]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],two1n1nPtEta,mp*dMult-mq); // histogram to store <2'> for RPs e-b-e (needed in some other methods): fDiffFlowCorrelationsEBE[0][pe][0]->SetBinContent(b,two1n1nPtEta); fDiffFlowEventWeightsForCorrelationsEBE[0][pe][0]->SetBinContent(b,mp*dMult-mq); } } // end of if(mp*dMult-mq) // 4'-particle correlation: Double_t four1n1n1n1nPtEta = 0.; if((mp-mq)*dMult*(dMult-1.)*(dMult-2.) + mq*(dMult-1.)*(dMult-2.)*(dMult-3.)) // to be improved (introduce a new variable for this expression) { four1n1n1n1nPtEta = ((pow(dReQ1n,2.)+pow(dImQ1n,2.))*(p1n0kRe*dReQ1n+p1n0kIm*dImQ1n) - q2n0kRe*(pow(dReQ1n,2.)-pow(dImQ1n,2.)) - 2.*q2n0kIm*dReQ1n*dImQ1n - p1n0kRe*(dReQ1n*dReQ2n+dImQ1n*dImQ2n) + p1n0kIm*(dImQ1n*dReQ2n-dReQ1n*dImQ2n) - 2.*dMult*(p1n0kRe*dReQ1n+p1n0kIm*dImQ1n) - 2.*(pow(dReQ1n,2.)+pow(dImQ1n,2.))*mq + 6.*(q1n0kRe*dReQ1n+q1n0kIm*dImQ1n) + 1.*(q2n0kRe*dReQ2n+q2n0kIm*dImQ2n) + 2.*(p1n0kRe*dReQ1n+p1n0kIm*dImQ1n) + 2.*mq*dMult - 6.*mq) / ((mp-mq)*dMult*(dMult-1.)*(dMult-2.) + mq*(dMult-1.)*(dMult-2.)*(dMult-3.)); if(type == "POI") { // profile to get <<4'>> for POIs: fDiffFlowCorrelationsPro[1][pe][1]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],four1n1n1n1nPtEta, (mp-mq)*dMult*(dMult-1.)*(dMult-2.) + mq*(dMult-1.)*(dMult-2.)*(dMult-3.)); // histogram to store <4'> for POIs e-b-e (needed in some other methods): fDiffFlowCorrelationsEBE[1][pe][1]->SetBinContent(b,four1n1n1n1nPtEta); fDiffFlowEventWeightsForCorrelationsEBE[1][pe][1]->SetBinContent(b,(mp-mq)*dMult*(dMult-1.)*(dMult-2.) + mq*(dMult-1.)*(dMult-2.)*(dMult-3.)); } else if(type == "RP") { // profile to get <<4'>> for RPs: fDiffFlowCorrelationsPro[0][pe][1]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],four1n1n1n1nPtEta, (mp-mq)*dMult*(dMult-1.)*(dMult-2.) + mq*(dMult-1.)*(dMult-2.)*(dMult-3.)); // histogram to store <4'> for RPs e-b-e (needed in some other methods): fDiffFlowCorrelationsEBE[0][pe][1]->SetBinContent(b,four1n1n1n1nPtEta); fDiffFlowEventWeightsForCorrelationsEBE[0][pe][1]->SetBinContent(b,(mp-mq)*dMult*(dMult-1.)*(dMult-2.) + mq*(dMult-1.)*(dMult-2.)*(dMult-3.)); } } // end of if((mp-mq)*dMult*(dMult-1.)*(dMult-2.) // +mq*(dMult-1.)*(dMult-2.)*(dMult-3.)) } // end of for(Int_t b=1;b<=nBinsPtEta[pe];b++) } // end of void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrelations(TString type, TString ptOrEta); //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CalculateDiffFlowSumOfEventWeights(TString type, TString ptOrEta) { // Calculate sums of various event weights for reduced correlations. // (These quantitites are needed in expressions for unbiased estimators relevant for the statistical errors.) Int_t typeFlag = -1; Int_t ptEtaFlag = -1; if(type == "RP") { typeFlag = 0; } else if(type == "POI") { typeFlag = 1; } if(ptOrEta == "Pt") { ptEtaFlag = 0; } else if(ptOrEta == "Eta") { ptEtaFlag = 1; } // shortcuts: Int_t t = typeFlag; Int_t pe = ptEtaFlag; // binning: Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; Double_t minPtEta[2] = {fPtMin,fEtaMin}; //Double_t maxPtEta[2] = {fPtMax,fEtaMax}; Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; for(Int_t rpq=0;rpq<3;rpq++) { for(Int_t m=0;m<4;m++) { for(Int_t k=0;k<9;k++) { if(!fReRPQ1dEBE[rpq][pe][m][k]) { cout<<"WARNING: fReRPQ1dEBE[rpq][pe][m][k] is NULL in AFAWQC::CSAPOEWFDF() !!!!"<GetBinEntries(b); mp = mq; // trick to use the very same Eqs. bellow both for RP's and POI's diff. flow } else if(type == "POI") { mp = fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(b); mq = fReRPQ1dEBE[2][pe][0][0]->GetBinEntries(b); } // event weight for <2'>: dw2 = mp*dMult-mq; fDiffFlowSumOfEventWeights[t][pe][0][0]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw2); fDiffFlowSumOfEventWeights[t][pe][1][0]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],pow(dw2,2.)); // event weight for <4'>: dw4 = (mp-mq)*dMult*(dMult-1.)*(dMult-2.) + mq*(dMult-1.)*(dMult-2.)*(dMult-3.); fDiffFlowSumOfEventWeights[t][pe][0][1]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw4); fDiffFlowSumOfEventWeights[t][pe][1][1]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],pow(dw4,2.)); // event weight for <6'>: //dw6 = ...; //fDiffFlowSumOfEventWeights[t][pe][0][2]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw6); //fDiffFlowSumOfEventWeights[t][pe][t][1][2]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],pow(dw6,2.)); // event weight for <8'>: //dw8 = ...; //fDiffFlowSumOfEventWeights[t][pe][0][3]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw8); //fDiffFlowSumOfEventWeights[t][pe][1][3]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],pow(dw8,2.)); } // end of for(Int_t b=1;b<=nBinsPtEta[pe];b++) } // end of void AliFlowAnalysisWithQCumulants::CalculateDiffFlowSumOfEventWeights() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CalculateDiffFlowSumOfProductOfEventWeights(TString type, TString ptOrEta) { // Calculate sum of products of various event weights for both types of correlations (the ones for int. and diff. flow). // (These quantitites are needed in expressions for unbiased estimators relevant for the statistical errors.) // // Important: To fill fDiffFlowSumOfProductOfEventWeights[][][][] use bellow table (i,j) with following constraints: // 1.) i,1=<2'>,2=<4>,3=<4'>,4=<6>,5=<6'>,6=<8>,7=<8'>] x [0=<2>,1=<2'>,2=<4>,3=<4'>,4=<6>,5=<6'>,6=<8>,7=<8'>] Int_t typeFlag = -1; Int_t ptEtaFlag = -1; if(type == "RP") { typeFlag = 0; } else if(type == "POI") { typeFlag = 1; } if(ptOrEta == "Pt") { ptEtaFlag = 0; } else if(ptOrEta == "Eta") { ptEtaFlag = 1; } // shortcuts: Int_t t = typeFlag; Int_t pe = ptEtaFlag; // binning: Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; Double_t minPtEta[2] = {fPtMin,fEtaMin}; //Double_t maxPtEta[2] = {fPtMax,fEtaMax}; Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; // protection: for(Int_t rpq=0;rpq<3;rpq++) { for(Int_t m=0;m<4;m++) { for(Int_t k=0;k<9;k++) { if(!fReRPQ1dEBE[rpq][pe][m][k]) { cout<<"WARNING: fReRPQ1dEBE[rpq][pe][m][k] is NULL in AFAWQC::CSAPOEWFDF() !!!!"<GetBinEntries(b); mp = mq; // trick to use the very same Eqs. bellow both for RP's and POI's diff. flow } else if(type == "POI") { mp = fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(b); mq = fReRPQ1dEBE[2][pe][0][0]->GetBinEntries(b); } // event weight for <2'>: dw2 = mp*dMult-mq; fDiffFlowSumOfProductOfEventWeights[t][pe][0][1]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dW2*dw2); // storing product of even weights for <2> and <2'> fDiffFlowSumOfProductOfEventWeights[t][pe][1][2]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw2*dW4); // storing product of even weights for <4> and <2'> fDiffFlowSumOfProductOfEventWeights[t][pe][1][4]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw2*dW6); // storing product of even weights for <6> and <2'> fDiffFlowSumOfProductOfEventWeights[t][pe][1][6]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw2*dW8); // storing product of even weights for <8> and <2'> // event weight for <4'>: dw4 = (mp-mq)*dMult*(dMult-1.)*(dMult-2.) + mq*(dMult-1.)*(dMult-2.)*(dMult-3.); fDiffFlowSumOfProductOfEventWeights[t][pe][0][3]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dW2*dw4); // storing product of even weights for <2> and <4'> fDiffFlowSumOfProductOfEventWeights[t][pe][1][3]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw2*dw4); // storing product of even weights for <2'> and <4'> fDiffFlowSumOfProductOfEventWeights[t][pe][2][3]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dW4*dw4); // storing product of even weights for <4> and <4'> fDiffFlowSumOfProductOfEventWeights[t][pe][3][4]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw4*dW6); // storing product of even weights for <6> and <4'> fDiffFlowSumOfProductOfEventWeights[t][pe][3][6]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw4*dW8); // storing product of even weights for <8> and <4'> // event weight for <6'>: //dw6 = ...; //fDiffFlowSumOfProductOfEventWeights[t][pe][0][5]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dW2*dw6); // storing product of even weights for <2> and <6'> //fDiffFlowSumOfProductOfEventWeights[t][pe][1][5]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw2*dw6); // storing product of even weights for <2'> and <6'> //fDiffFlowSumOfProductOfEventWeights[t][pe][2][5]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dW4*dw6); // storing product of even weights for <4> and <6'> //fDiffFlowSumOfProductOfEventWeights[t][pe][3][5]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw4*dw6); // storing product of even weights for <4'> and <6'> //fDiffFlowSumOfProductOfEventWeights[t][pe][4][5]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dW6*dw6); // storing product of even weights for <6> and <6'> //fDiffFlowSumOfProductOfEventWeights[t][pe][5][6]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw6*dW8); // storing product of even weights for <6'> and <8> //fDiffFlowSumOfProductOfEventWeights[t][pe][5][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw6*dw8); // storing product of even weights for <6'> and <8'> // event weight for <8'>: //dw8 = ...; //fDiffFlowSumOfProductOfEventWeights[t][pe][0][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dW2*dw8); // storing product of even weights for <2> and <8'> //fDiffFlowSumOfProductOfEventWeights[t][pe][1][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw2*dw8); // storing product of even weights for <2'> and <8'> //fDiffFlowSumOfProductOfEventWeights[t][pe][2][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dW4*dw8); // storing product of even weights for <4> and <8'> //fDiffFlowSumOfProductOfEventWeights[t][pe][3][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw4*dw8); // storing product of even weights for <4'> and <8'> //fDiffFlowSumOfProductOfEventWeights[t][pe][4][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dW6*dw8); // storing product of even weights for <6> and <8'> //fDiffFlowSumOfProductOfEventWeights[t][pe][5][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw6*dw8); // storing product of even weights for <6'> and <8'> //fDiffFlowSumOfProductOfEventWeights[t][pe][6][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dW8*dw8); // storing product of even weights for <8> and <8'> // Table: // [0=<2>,1=<2'>,2=<4>,3=<4'>,4=<6>,5=<6'>,6=<8>,7=<8'>] x [0=<2>,1=<2'>,2=<4>,3=<4'>,4=<6>,5=<6'>,6=<8>,7=<8'>] } // end of for(Int_t b=1;b<=nBinsPtEta[pe];b++) } // end of void AliFlowAnalysisWithQCumulants::CalculateDiffFlowSumOfProductOfEventWeights(TString type, TString ptOrEta) //================================================================================================================================ void AliFlowAnalysisWithQCumulants::FinalizeReducedCorrelations(TString type, TString ptOrEta) { // Transfer profiles into histograms and calculate statistical errors correctly. Int_t typeFlag = -1; Int_t ptEtaFlag = -1; if(type == "RP") { typeFlag = 0; } else if(type == "POI") { typeFlag = 1; } if(ptOrEta == "Pt") { ptEtaFlag = 0; } else if(ptOrEta == "Eta") { ptEtaFlag = 1; } // shortcuts: Int_t t = typeFlag; Int_t pe = ptEtaFlag; for(Int_t rci=0;rci<4;rci++) { if(!fDiffFlowCorrelationsPro[t][pe][rci]) { cout<<"WARNING: fDiffFlowCorrelationsPro[t][pe][rci] is NULL in AFAWQC::FRC() !!!!"<GetBinContent(1); // <2> Double_t fourEBE = fIntFlowCorrelationsEBE->GetBinContent(2); // <4> Double_t sixEBE = fIntFlowCorrelationsEBE->GetBinContent(3); // <6> Double_t eightEBE = fIntFlowCorrelationsEBE->GetBinContent(4); // <8> // event weights for correlations: Double_t dW2 = fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1); // event weight for <2> Double_t dW4 = fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2); // event weight for <4> Double_t dW6 = fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(3); // event weight for <6> Double_t dW8 = fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(4); // event weight for <8> // e-b-e reduced correlations: Double_t twoReducedEBE = 0.; // <2'> Double_t fourReducedEBE = 0.; // <4'> Double_t sixReducedEBE = 0.; // <6'> Double_t eightReducedEBE = 0.; // <8'> // event weights for reduced correlations: Double_t dw2 = 0.; // event weight for <2'> Double_t dw4 = 0.; // event weight for <4'> //Double_t dw6 = 0.; // event weight for <6'> //Double_t dw8 = 0.; // event weight for <8'> // looping over bins: for(Int_t b=1;b<=nBinsPtEta[pe];b++) { // e-b-e reduced correlations: twoReducedEBE = fDiffFlowCorrelationsEBE[t][pe][0]->GetBinContent(b); fourReducedEBE = fDiffFlowCorrelationsEBE[t][pe][1]->GetBinContent(b); sixReducedEBE = fDiffFlowCorrelationsEBE[t][pe][2]->GetBinContent(b); eightReducedEBE = fDiffFlowCorrelationsEBE[t][pe][3]->GetBinContent(b); /* // to be improved (I should not do this here again) if(type == "RP") { mq = fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(b); mp = mq; // trick to use the very same Eqs. bellow both for RP's and POI's diff. flow } else if(type == "POI") { mp = fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(b); mq = fReRPQ1dEBE[2][pe][0][0]->GetBinEntries(b); } // event weights for reduced correlations: dw2 = mp*dMult-mq; // weight for <2'> dw4 = (mp-mq)*dMult*(dMult-1.)*(dMult-2.) + mq*(dMult-1.)*(dMult-2.)*(dMult-3.); // weight for <4'> //dw6 = ... //dw8 = ... */ dw2 = fDiffFlowEventWeightsForCorrelationsEBE[t][pe][0]->GetBinContent(b); dw4 = fDiffFlowEventWeightsForCorrelationsEBE[t][pe][1]->GetBinContent(b); // storing all products: fDiffFlowProductOfCorrelationsPro[t][pe][0][1]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],twoEBE*twoReducedEBE,dW2*dw2); // storing <2><2'> fDiffFlowProductOfCorrelationsPro[t][pe][1][2]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],fourEBE*twoReducedEBE,dW4*dw2); // storing <4><2'> fDiffFlowProductOfCorrelationsPro[t][pe][1][4]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sixEBE*twoReducedEBE,dW6*dw2); // storing <6><2'> fDiffFlowProductOfCorrelationsPro[t][pe][1][6]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],eightEBE*twoReducedEBE,dW8*dw2); // storing <8><2'> // event weight for <4'>: fDiffFlowProductOfCorrelationsPro[t][pe][0][3]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],twoEBE*fourReducedEBE,dW2*dw4); // storing <2><4'> fDiffFlowProductOfCorrelationsPro[t][pe][1][3]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],twoReducedEBE*fourReducedEBE,dw2*dw4); // storing <2'><4'> fDiffFlowProductOfCorrelationsPro[t][pe][2][3]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],fourEBE*fourReducedEBE,dW4*dw4); // storing <4><4'> fDiffFlowProductOfCorrelationsPro[t][pe][3][4]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sixEBE*fourReducedEBE,dW6*dw4); // storing <6><4'> fDiffFlowProductOfCorrelationsPro[t][pe][3][6]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],eightEBE*fourReducedEBE,dW8*dw4); // storing <8><4'> // event weight for <6'>: //dw6 = ...; //fDiffFlowProductOfCorrelationsPro[t][pe][0][5]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],twoEBE*sixReducedEBE,dW2*dw6); // storing <2><6'> //fDiffFlowProductOfCorrelationsPro[t][pe][1][5]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],twoReducedEBE*sixReducedEBE,dw2*dw6); // storing <2'><6'> //fDiffFlowProductOfCorrelationsPro[t][pe][2][5]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],fourEBE*sixReducedEBE,dW4*dw6); // storing <4><6'> //fDiffFlowProductOfCorrelationsPro[t][pe][3][5]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],fourReducedEBE*sixReducedEBE,dw4*dw6); // storing <4'><6'> //fDiffFlowProductOfCorrelationsPro[t][pe][4][5]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sixEBE*sixReducedEBE,dW6*dw6); // storing <6><6'> //fDiffFlowProductOfCorrelationsPro[t][pe][5][6]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sixReducedEBE*eightEBE,dw6*dW8); // storing <6'><8> //fDiffFlowProductOfCorrelationsPro[t][pe][5][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sixReducedEBE*eightReducedEBE,dw6*dw8); // storing <6'><8'> // event weight for <8'>: //dw8 = ...; //fDiffFlowProductOfCorrelationsPro[t][pe][0][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],twoEBE*eightReducedEBE,dW2*dw8); // storing <2><8'> //fDiffFlowProductOfCorrelationsPro[t][pe][1][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],twoReducedEBE*eightReducedEBE,dw2*dw8); // storing <2'><8'> //fDiffFlowProductOfCorrelationsPro[t][pe][2][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],fourEBE*eightReducedEBE,dW4*dw8); // storing <4><8'> //fDiffFlowProductOfCorrelationsPro[t][pe][3][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],fourReducedEBE*eightReducedEBE,dw4*dw8); // storing <4'><8'> //fDiffFlowProductOfCorrelationsPro[t][pe][4][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sixEBE*eightReducedEBE,dW6*dw8); // storing <6><8'> //fDiffFlowProductOfCorrelationsPro[t][pe][5][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sixReducedEBE*eightReducedEBE,dw6*dw8); // storing <6'><8'> //fDiffFlowProductOfCorrelationsPro[t][pe][6][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],eightEBE*eightReducedEBE,dW8*dw8); // storing <8><8'> } // end of for(Int_t b=1;b<=nBinsPtEta[pe];b++ } // end of void AliFlowAnalysisWithQCumulants::CalculateDiffFlowProductOfCorrelations(TString type, TString ptOrEta) //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCovariances(TString type, TString ptOrEta) // to be improved (reimplemented) { // a) Calculate unbiased estimators Cov(<2>,<2'>), Cov(<2>,<4'>), Cov(<4>,<2'>), Cov(<4>,<4'>) and Cov(<2'>,<4'>) // for covariances V(<2>,<2'>), V(<2>,<4'>), V(<4>,<2'>), V(<4>,<4'>) and V(<2'>,<4'>). // b) Store in histogram fDiffFlowCovariances[t][pe][index] for instance the following: // // Cov(<2>,<2'>) * (sum_{i=1}^{N} w_{<2>}_i w_{<2'>}_i )/[(sum_{i=1}^{N} w_{<2>}_i) * (sum_{j=1}^{N} w_{<2'>}_j)] // // where N is the number of events, w_{<2>} is event weight for <2> and w_{<2'>} is event weight for <2'>. // c) Binning of fDiffFlowCovariances[t][pe][index] is organized as follows: // // 1st bin: Cov(<2>,<2'>) * (sum_{i=1}^{N} w_{<2>}_i w_{<2'>}_i )/[(sum_{i=1}^{N} w_{<2>}_i) * (sum_{j=1}^{N} w_{<2'>}_j)] // 2nd bin: Cov(<2>,<4'>) * (sum_{i=1}^{N} w_{<2>}_i w_{<4'>}_i )/[(sum_{i=1}^{N} w_{<2>}_i) * (sum_{j=1}^{N} w_{<4'>}_j)] // 3rd bin: Cov(<4>,<2'>) * (sum_{i=1}^{N} w_{<4>}_i w_{<2'>}_i )/[(sum_{i=1}^{N} w_{<4>}_i) * (sum_{j=1}^{N} w_{<2'>}_j)] // 4th bin: Cov(<4>,<4'>) * (sum_{i=1}^{N} w_{<4>}_i w_{<4'>}_i )/[(sum_{i=1}^{N} w_{<4>}_i) * (sum_{j=1}^{N} w_{<4'>}_j)] // 5th bin: Cov(<2'>,<4'>) * (sum_{i=1}^{N} w_{<2'>}_i w_{<4'>}_i )/[(sum_{i=1}^{N} w_{<2'>}_i) * (sum_{j=1}^{N} w_{<4'>}_j)] // ... Int_t typeFlag = -1; Int_t ptEtaFlag = -1; if(type == "RP") { typeFlag = 0; } else if(type == "POI") { typeFlag = 1; } if(ptOrEta == "Pt") { ptEtaFlag = 0; } else if(ptOrEta == "Eta") { ptEtaFlag = 1; } // shortcuts: Int_t t = typeFlag; Int_t pe = ptEtaFlag; // common: Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; //Double_t minPtEta[2] = {fPtMin,fEtaMin}; //Double_t maxPtEta[2] = {fPtMax,fEtaMax}; //Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; // average correlations: Double_t two = fIntFlowCorrelationsHist->GetBinContent(1); // <<2>> Double_t four = fIntFlowCorrelationsHist->GetBinContent(2); // <<4>> //Double_t six = fIntFlowCorrelationsHist->GetBinContent(3); // <<6>> //Double_t eight = fIntFlowCorrelationsHist->GetBinContent(4); // <<8>> // sum of weights for correlation: Double_t sumOfWeightsForTwo = fIntFlowSumOfEventWeights[0]->GetBinContent(1); // sum_{i=1}^{N} w_{<2>} Double_t sumOfWeightsForFour = fIntFlowSumOfEventWeights[0]->GetBinContent(2); // sum_{i=1}^{N} w_{<4>} //Double_t sumOfWeightsForSix = fIntFlowSumOfEventWeights[0]->GetBinContent(3); // sum_{i=1}^{N} w_{<6>} //Double_t sumOfWeightsForEight = fIntFlowSumOfEventWeights[0]->GetBinContent(4); // sum_{i=1}^{N} w_{<8>} // average reduced correlations: Double_t twoReduced = 0.; // <<2'>> Double_t fourReduced = 0.; // <<4'>> //Double_t sixReduced = 0.; // <<6'>> //Double_t eightReduced = 0.; // <<8'>> // sum of weights for reduced correlation: Double_t sumOfWeightsForTwoReduced = 0.; // sum_{i=1}^{N} w_{<2'>} Double_t sumOfWeightsForFourReduced = 0.; // sum_{i=1}^{N} w_{<4'>} //Double_t sumOfWeightsForSixReduced = 0.; // sum_{i=1}^{N} w_{<6'>} //Double_t sumOfWeightsForEightReduced = 0.; // sum_{i=1}^{N} w_{<8'>} // product of weights for reduced correlation: Double_t productOfWeightsForTwoTwoReduced = 0.; // sum_{i=1}^{N} w_{<2>}w_{<2'>} Double_t productOfWeightsForTwoFourReduced = 0.; // sum_{i=1}^{N} w_{<2>}w_{<4'>} Double_t productOfWeightsForFourTwoReduced = 0.; // sum_{i=1}^{N} w_{<4>}w_{<2'>} Double_t productOfWeightsForFourFourReduced = 0.; // sum_{i=1}^{N} w_{<4>}w_{<4'>} Double_t productOfWeightsForTwoReducedFourReduced = 0.; // sum_{i=1}^{N} w_{<2'>}w_{<4'>} // ... // products for differential flow: Double_t twoTwoReduced = 0; // <<2><2'>> Double_t twoFourReduced = 0; // <<2><4'>> Double_t fourTwoReduced = 0; // <<4><2'>> Double_t fourFourReduced = 0; // <<4><4'>> Double_t twoReducedFourReduced = 0; // <<2'><4'>> // denominators in the expressions for the unbiased estimators for covariances: // denominator = 1 - term1/(term2*term3) // prefactor = term1/(term2*term3) Double_t denominator = 0.; Double_t prefactor = 0.; Double_t term1 = 0.; Double_t term2 = 0.; Double_t term3 = 0.; // unbiased estimators for covariances for differential flow: Double_t covTwoTwoReduced = 0.; // Cov(<2>,<2'>) Double_t wCovTwoTwoReduced = 0.; // Cov(<2>,<2'>) * prefactor(w_{<2>},w_{<2'>}) Double_t covTwoFourReduced = 0.; // Cov(<2>,<4'>) Double_t wCovTwoFourReduced = 0.; // Cov(<2>,<4'>) * prefactor(w_{<2>},w_{<4'>}) Double_t covFourTwoReduced = 0.; // Cov(<4>,<2'>) Double_t wCovFourTwoReduced = 0.; // Cov(<4>,<2'>) * prefactor(w_{<4>},w_{<2'>}) Double_t covFourFourReduced = 0.; // Cov(<4>,<4'>) Double_t wCovFourFourReduced = 0.; // Cov(<4>,<4'>) * prefactor(w_{<4>},w_{<4'>}) Double_t covTwoReducedFourReduced = 0.; // Cov(<2'>,<4'>) Double_t wCovTwoReducedFourReduced = 0.; // Cov(<2'>,<4'>) * prefactor(w_{<2'>},w_{<4'>}) for(Int_t b=1;b<=nBinsPtEta[pe];b++) { // average reduced corelations: twoReduced = fDiffFlowCorrelationsHist[t][pe][0]->GetBinContent(b); fourReduced = fDiffFlowCorrelationsHist[t][pe][1]->GetBinContent(b); // average products: twoTwoReduced = fDiffFlowProductOfCorrelationsPro[t][pe][0][1]->GetBinContent(b); twoFourReduced = fDiffFlowProductOfCorrelationsPro[t][pe][0][3]->GetBinContent(b); fourTwoReduced = fDiffFlowProductOfCorrelationsPro[t][pe][1][2]->GetBinContent(b); fourFourReduced = fDiffFlowProductOfCorrelationsPro[t][pe][2][3]->GetBinContent(b); twoReducedFourReduced = fDiffFlowProductOfCorrelationsPro[t][pe][1][3]->GetBinContent(b); // sum of weights for reduced correlations: sumOfWeightsForTwoReduced = fDiffFlowSumOfEventWeights[t][pe][0][0]->GetBinContent(b); sumOfWeightsForFourReduced = fDiffFlowSumOfEventWeights[t][pe][0][1]->GetBinContent(b); // products of weights for correlations: productOfWeightsForTwoTwoReduced = fDiffFlowSumOfProductOfEventWeights[t][pe][0][1]->GetBinContent(b); productOfWeightsForTwoFourReduced = fDiffFlowSumOfProductOfEventWeights[t][pe][0][3]->GetBinContent(b); productOfWeightsForFourTwoReduced = fDiffFlowSumOfProductOfEventWeights[t][pe][1][2]->GetBinContent(b); productOfWeightsForFourFourReduced = fDiffFlowSumOfProductOfEventWeights[t][pe][2][3]->GetBinContent(b); productOfWeightsForTwoReducedFourReduced = fDiffFlowSumOfProductOfEventWeights[t][pe][1][3]->GetBinContent(b); // denominator for the unbiased estimator for covariances: 1 - term1/(term2*term3) // prefactor (multiplies Cov's) = term1/(term2*term3) // <2>,<2'>: term1 = productOfWeightsForTwoTwoReduced; term2 = sumOfWeightsForTwo; term3 = sumOfWeightsForTwoReduced; if(term2*term3>0.) { denominator = 1.-term1/(term2*term3); prefactor = term1/(term2*term3); if(TMath::Abs(denominator)>1e-6) { covTwoTwoReduced = (twoTwoReduced-two*twoReduced)/denominator; wCovTwoTwoReduced = covTwoTwoReduced*prefactor; fDiffFlowCovariances[t][pe][0]->SetBinContent(b,wCovTwoTwoReduced); } } // <2>,<4'>: term1 = productOfWeightsForTwoFourReduced; term2 = sumOfWeightsForTwo; term3 = sumOfWeightsForFourReduced; if(term2*term3>0.) { denominator = 1.-term1/(term2*term3); prefactor = term1/(term2*term3); if(TMath::Abs(denominator)>1e-6) { covTwoFourReduced = (twoFourReduced-two*fourReduced)/denominator; wCovTwoFourReduced = covTwoFourReduced*prefactor; fDiffFlowCovariances[t][pe][1]->SetBinContent(b,wCovTwoFourReduced); } } // <4>,<2'>: term1 = productOfWeightsForFourTwoReduced; term2 = sumOfWeightsForFour; term3 = sumOfWeightsForTwoReduced; if(term2*term3>0.) { denominator = 1.-term1/(term2*term3); prefactor = term1/(term2*term3); if(TMath::Abs(denominator)>1e-6) { covFourTwoReduced = (fourTwoReduced-four*twoReduced)/denominator; wCovFourTwoReduced = covFourTwoReduced*prefactor; fDiffFlowCovariances[t][pe][2]->SetBinContent(b,wCovFourTwoReduced); } } // <4>,<4'>: term1 = productOfWeightsForFourFourReduced; term2 = sumOfWeightsForFour; term3 = sumOfWeightsForFourReduced; if(term2*term3>0.) { denominator = 1.-term1/(term2*term3); prefactor = term1/(term2*term3); if(TMath::Abs(denominator)>1e-6) { covFourFourReduced = (fourFourReduced-four*fourReduced)/denominator; wCovFourFourReduced = covFourFourReduced*prefactor; fDiffFlowCovariances[t][pe][3]->SetBinContent(b,wCovFourFourReduced); } } // <2'>,<4'>: term1 = productOfWeightsForTwoReducedFourReduced; term2 = sumOfWeightsForTwoReduced; term3 = sumOfWeightsForFourReduced; if(term2*term3>0.) { denominator = 1.-term1/(term2*term3); prefactor = term1/(term2*term3); if(TMath::Abs(denominator)>1e-6) { covTwoReducedFourReduced = (twoReducedFourReduced-twoReduced*fourReduced)/denominator; wCovTwoReducedFourReduced = covTwoReducedFourReduced*prefactor; fDiffFlowCovariances[t][pe][4]->SetBinContent(b,wCovTwoReducedFourReduced); } } } // end of for(Int_t b=1;b<=nBinsPtEta[pe];b++) } // end of void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCovariances(TString type, TString ptOrEta) //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CalculateDiffFlow(TString type, TString ptOrEta) { // calculate differential flow from differential cumulants and previously obtained integrated flow: (to be improved: description) Int_t typeFlag = -1; Int_t ptEtaFlag = -1; if(type == "RP") { typeFlag = 0; } else if(type == "POI") { typeFlag = 1; } if(ptOrEta == "Pt") { ptEtaFlag = 0; } else if(ptOrEta == "Eta") { ptEtaFlag = 1; } // shortcuts: Int_t t = typeFlag; Int_t pe = ptEtaFlag; // common: Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; // correlations: Double_t two = fIntFlowCorrelationsHist->GetBinContent(1); // <<2>> Double_t four = fIntFlowCorrelationsHist->GetBinContent(2); // <<4>> // statistical errors of correlations: Double_t twoError = fIntFlowCorrelationsHist->GetBinError(1); Double_t fourError = fIntFlowCorrelationsHist->GetBinError(2); // reduced correlations: Double_t twoReduced = 0.; // <<2'>> Double_t fourReduced = 0.; // <<4'>> // statistical errors of reduced correlations: Double_t twoReducedError = 0.; Double_t fourReducedError = 0.; // covariances: Double_t wCovTwoFour = fIntFlowCovariances->GetBinContent(1);// // Cov(<2>,<4>) * prefactor(<2>,<4>) Double_t wCovTwoTwoReduced = 0.; // Cov(<2>,<2'>) * prefactor(<2>,<2'>) Double_t wCovTwoFourReduced = 0.; // Cov(<2>,<4'>) * prefactor(<2>,<4'>) Double_t wCovFourTwoReduced = 0.; // Cov(<4>,<2'>) * prefactor(<4>,<2'>) Double_t wCovFourFourReduced = 0.; // Cov(<4>,<4'>) * prefactor(<4>,<4'>) Double_t wCovTwoReducedFourReduced = 0.; // Cov(<2'>,<4'>) * prefactor(<2'>,<4'>) // differential flow: Double_t v2Prime = 0.; // v'{2} Double_t v4Prime = 0.; // v'{4} // statistical error of differential flow: Double_t v2PrimeError = 0.; Double_t v4PrimeError = 0.; // squared statistical error of differential flow: Double_t v2PrimeErrorSquared = 0.; Double_t v4PrimeErrorSquared = 0.; // loop over pt or eta bins: for(Int_t b=1;b<=nBinsPtEta[pe];b++) { // reduced correlations and statistical errors: twoReduced = fDiffFlowCorrelationsHist[t][pe][0]->GetBinContent(b); twoReducedError = fDiffFlowCorrelationsHist[t][pe][0]->GetBinError(b); fourReduced = fDiffFlowCorrelationsHist[t][pe][1]->GetBinContent(b); fourReducedError = fDiffFlowCorrelationsHist[t][pe][1]->GetBinError(b); // covariances: wCovTwoTwoReduced = fDiffFlowCovariances[t][pe][0]->GetBinContent(b); wCovTwoFourReduced = fDiffFlowCovariances[t][pe][1]->GetBinContent(b); wCovFourTwoReduced = fDiffFlowCovariances[t][pe][2]->GetBinContent(b); wCovFourFourReduced = fDiffFlowCovariances[t][pe][3]->GetBinContent(b); wCovTwoReducedFourReduced = fDiffFlowCovariances[t][pe][4]->GetBinContent(b); // differential flow: // v'{2}: if(two>0.) { v2Prime = twoReduced/pow(two,0.5); v2PrimeErrorSquared = (1./4.)*pow(two,-3.)* (pow(twoReduced,2.)*pow(twoError,2.) + 4.*pow(two,2.)*pow(twoReducedError,2.) - 4.*two*twoReduced*wCovTwoTwoReduced); if(v2PrimeErrorSquared>0.) v2PrimeError = pow(v2PrimeErrorSquared,0.5); fDiffFlow[t][pe][0]->SetBinContent(b,v2Prime); if(TMath::Abs(v2Prime)>1.e-44)fDiffFlow[t][pe][0]->SetBinError(b,v2PrimeError); } // differential flow: // v'{4} if(2.*pow(two,2.)-four > 0.) { v4Prime = (2.*two*twoReduced-fourReduced)/pow(2.*pow(two,2.)-four,3./4.); v4PrimeErrorSquared = pow(2.*pow(two,2.)-four,-7./2.)* (pow(2.*pow(two,2.)*twoReduced-3.*two*fourReduced+2.*four*twoReduced,2.)*pow(twoError,2.) + (9./16.)*pow(2.*two*twoReduced-fourReduced,2.)*pow(fourError,2.) + 4.*pow(two,2.)*pow(2.*pow(two,2.)-four,2.)*pow(twoReducedError,2.) + pow(2.*pow(two,2.)-four,2.)*pow(fourReducedError,2.) - (3./2.)*(2.*two*twoReduced-fourReduced) * (2.*pow(two,2.)*twoReduced-3.*two*fourReduced+2.*four*twoReduced)*wCovTwoFour - 4.*two*(2.*pow(two,2.)-four) * (2.*pow(two,2.)*twoReduced-3.*two*fourReduced+2.*four*twoReduced)*wCovTwoTwoReduced + 2.*(2.*pow(two,2.)-four) * (2.*pow(two,2.)*twoReduced-3.*two*fourReduced+2.*four*twoReduced)*wCovTwoFourReduced + 3.*two*(2.*pow(two,2.)-four)*(2.*two*twoReduced-fourReduced)*wCovFourTwoReduced - (3./2.)*(2.*pow(two,2.)-four)*(2.*two*twoReduced-fourReduced)*wCovFourFourReduced - 4.*two*pow(2.*pow(two,2.)-four,2.)*wCovTwoReducedFourReduced); if(v4PrimeErrorSquared>0.) v4PrimeError = pow(v4PrimeErrorSquared,0.5); fDiffFlow[t][pe][1]->SetBinContent(b,v4Prime); if(TMath::Abs(v4Prime)>1.e-44)fDiffFlow[t][pe][1]->SetBinError(b,v4PrimeError); } } // end of for(Int_t b=1;b<=fnBinsPtEta[pe];b++) /* // 2D: for(Int_t nua=0;nua<2;nua++) { for(Int_t p=1;p<=fnBinsPt;p++) { for(Int_t e=1;e<=fnBinsEta;e++) { // differential cumulants: Double_t qc2Prime = fFinalCumulants2D[t][pW][eW][nua][0]->GetBinContent(fFinalCumulants2D[t][pW][eW][nua][0]->GetBin(p,e)); // QC{2'} Double_t qc4Prime = fFinalCumulants2D[t][pW][eW][nua][1]->GetBinContent(fFinalCumulants2D[t][pW][eW][nua][1]->GetBin(p,e)); // QC{4'} // differential flow: Double_t v2Prime = 0.; Double_t v4Prime = 0.; if(v2) { v2Prime = qc2Prime/v2; fFinalFlow2D[t][pW][eW][nua][0]->SetBinContent(fFinalFlow2D[t][pW][eW][nua][0]->GetBin(p,e),v2Prime); } if(v4) { v4Prime = -qc4Prime/pow(v4,3.); fFinalFlow2D[t][pW][eW][nua][1]->SetBinContent(fFinalFlow2D[t][pW][eW][nua][1]->GetBin(p,e),v4Prime); } } // end of for(Int_t e=1;e<=fnBinsEta;e++) } // end of for(Int_t p=1;p<=fnBinsPt;p++) } // end of for(Int_t nua=0;nua<2;nua++) */ } // end of AliFlowAnalysisWithQCumulants::CalculateDiffFlow(TString type, Bool_t useParticleWeights) //================================================================================================================================ void AliFlowAnalysisWithQCumulants::StoreIntFlowFlags() { // a) Store all flags for integrated flow in profile fIntFlowFlags. if(!fIntFlowFlags) { cout<<"WARNING: fIntFlowFlags is NULL in AFAWQC::SFFIF() !!!!"<Fill(0.5,(Int_t)fUsePhiWeights||fUsePtWeights||fUseEtaWeights); // which event weights were used: if(strcmp(fMultiplicityWeight->Data(),"combinations")) { fIntFlowFlags->Fill(1.5,0); // 0 = "combinations" (default) } else if(strcmp(fMultiplicityWeight->Data(),"unit")) { fIntFlowFlags->Fill(1.5,1); // 1 = "unit" } else if(strcmp(fMultiplicityWeight->Data(),"multiplicity")) { fIntFlowFlags->Fill(1.5,2); // 2 = "multiplicity" } // corrected for non-uniform acceptance or not: fIntFlowFlags->Fill(2.5,(Int_t)fApplyCorrectionForNUA); fIntFlowFlags->Fill(3.5,(Int_t)fPrintFinalResults[0]); fIntFlowFlags->Fill(4.5,(Int_t)fPrintFinalResults[1]); fIntFlowFlags->Fill(5.5,(Int_t)fPrintFinalResults[2]); fIntFlowFlags->Fill(6.5,(Int_t)fPrintFinalResults[3]); fIntFlowFlags->Fill(7.5,(Int_t)fApplyCorrectionForNUAVsM); fIntFlowFlags->Fill(8.5,(Int_t)fPropagateErrorFromCorrelations); fIntFlowFlags->Fill(9.5,(Int_t)fCalculateCumulantsVsM); fIntFlowFlags->Fill(10.5,(Int_t)fMinimumBiasReferenceFlow); } // end of void AliFlowAnalysisWithQCumulants::StoreIntFlowFlags() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::StoreDiffFlowFlags() { // Store all flags for differential flow in the profile fDiffFlowFlags. if(!fDiffFlowFlags) { cout<<"WARNING: fDiffFlowFlags is NULL in AFAWQC::SFFDF() !!!!"<Fill(0.5,fUsePhiWeights||fUsePtWeights||fUseEtaWeights); // particle weights used or not //fDiffFlowFlags->Fill(1.5,""); // which event weight was used? // to be improved fDiffFlowFlags->Fill(2.5,fApplyCorrectionForNUA); // corrected for non-uniform acceptance or not fDiffFlowFlags->Fill(3.5,fCalculate2DFlow); // calculate also 2D differential flow in (pt,eta) or not } // end of void AliFlowAnalysisWithQCumulants::StoreDiffFlowFlags() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::GetPointersForCommonHistograms() { // Access all pointers to common control and common result histograms and profiles. TString commonHistsName = "AliFlowCommonHistQC"; commonHistsName += fAnalysisLabel->Data(); AliFlowCommonHist *commonHist = dynamic_cast(fHistList->FindObject(commonHistsName.Data())); if(commonHist) this->SetCommonHists(commonHist); TString commonHists2ndOrderName = "AliFlowCommonHist2ndOrderQC"; commonHists2ndOrderName += fAnalysisLabel->Data(); AliFlowCommonHist *commonHist2nd = dynamic_cast(fHistList->FindObject(commonHists2ndOrderName.Data())); if(commonHist2nd) this->SetCommonHists2nd(commonHist2nd); TString commonHists4thOrderName = "AliFlowCommonHist4thOrderQC"; commonHists4thOrderName += fAnalysisLabel->Data(); AliFlowCommonHist *commonHist4th = dynamic_cast(fHistList->FindObject(commonHists4thOrderName.Data())); if(commonHist4th) this->SetCommonHists4th(commonHist4th); TString commonHists6thOrderName = "AliFlowCommonHist6thOrderQC"; commonHists6thOrderName += fAnalysisLabel->Data(); AliFlowCommonHist *commonHist6th = dynamic_cast(fHistList->FindObject(commonHists6thOrderName.Data())); if(commonHist6th) this->SetCommonHists6th(commonHist6th); TString commonHists8thOrderName = "AliFlowCommonHist8thOrderQC"; commonHists8thOrderName += fAnalysisLabel->Data(); AliFlowCommonHist *commonHist8th = dynamic_cast(fHistList->FindObject(commonHists8thOrderName.Data())); if(commonHist8th) this->SetCommonHists8th(commonHist8th); TString commonHistResults2ndOrderName = "AliFlowCommonHistResults2ndOrderQC"; commonHistResults2ndOrderName += fAnalysisLabel->Data(); AliFlowCommonHistResults *commonHistRes2nd = dynamic_cast (fHistList->FindObject(commonHistResults2ndOrderName.Data())); if(commonHistRes2nd) this->SetCommonHistsResults2nd(commonHistRes2nd); TString commonHistResults4thOrderName = "AliFlowCommonHistResults4thOrderQC"; commonHistResults4thOrderName += fAnalysisLabel->Data(); AliFlowCommonHistResults *commonHistRes4th = dynamic_cast (fHistList->FindObject(commonHistResults4thOrderName.Data())); if(commonHistRes4th) this->SetCommonHistsResults4th(commonHistRes4th); TString commonHistResults6thOrderName = "AliFlowCommonHistResults6thOrderQC"; commonHistResults6thOrderName += fAnalysisLabel->Data(); AliFlowCommonHistResults *commonHistRes6th = dynamic_cast (fHistList->FindObject(commonHistResults6thOrderName.Data())); if(commonHistRes6th) this->SetCommonHistsResults6th(commonHistRes6th); TString commonHistResults8thOrderName = "AliFlowCommonHistResults8thOrderQC"; commonHistResults8thOrderName += fAnalysisLabel->Data(); AliFlowCommonHistResults *commonHistRes8th = dynamic_cast (fHistList->FindObject(commonHistResults8thOrderName.Data())); if(commonHistRes8th) this->SetCommonHistsResults8th(commonHistRes8th); } // end of void AliFlowAnalysisWithQCumulants::GetPointersForCommonHistograms() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::GetPointersForParticleWeightsHistograms() { // Get pointers for histograms with particle weights. TList *weightsList = dynamic_cast(fHistList->FindObject("Weights")); if(weightsList) this->SetWeightsList(weightsList); TString fUseParticleWeightsName = "fUseParticleWeightsQC"; // to be improved (hirdwired label QC) fUseParticleWeightsName += fAnalysisLabel->Data(); TProfile *useParticleWeights = dynamic_cast(weightsList->FindObject(fUseParticleWeightsName.Data())); if(useParticleWeights) { this->SetUseParticleWeights(useParticleWeights); fUsePhiWeights = (Int_t)fUseParticleWeights->GetBinContent(1); fUsePtWeights = (Int_t)fUseParticleWeights->GetBinContent(2); fUseEtaWeights = (Int_t)fUseParticleWeights->GetBinContent(3); } } // end of void AliFlowAnalysisWithQCumulants::GetPointersForParticleWeightsHistograms(); //================================================================================================================================ void AliFlowAnalysisWithQCumulants::GetPointersForIntFlowHistograms() { // Get pointers for histograms and profiles relevant for integrated flow: // a) Get pointer to base list for integrated flow holding profile fIntFlowFlags and lists fIntFlowProfiles and fIntFlowResults. // b) Get pointer to profile fIntFlowFlags holding all flags for integrated flow. // c) Get pointer to list fIntFlowProfiles and pointers to all objects that she holds. // d) Get pointer to list fIntFlowResults and pointers to all objects that she holds. TString sinCosFlag[2] = {"sin","cos"}; // to be improved (should I promote this to data member?) TString powerFlag[2] = {"linear","quadratic"}; // to be improved (should I promote this to data member?) TString correlationFlag[4] = {"<<2>>","<<4>>","<<6>>","<<8>>"}; // to be improved (should I promote this to data member?) // a) Get pointer to base list for integrated flow holding profile fIntFlowFlags and lists fIntFlowProfiles and fIntFlowResults: TList *intFlowList = NULL; intFlowList = dynamic_cast(fHistList->FindObject("Integrated Flow")); if(!intFlowList) { cout<<"WARNING: intFlowList is NULL in AFAWQC::GPFIFH() !!!!"<Data(); TProfile *intFlowFlags = dynamic_cast(intFlowList->FindObject(intFlowFlagsName.Data())); if(intFlowFlags) { this->SetIntFlowFlags(intFlowFlags); fApplyCorrectionForNUA = (Bool_t)intFlowFlags->GetBinContent(3); // to be improved (hardwired 3) fCalculateCumulantsVsM = (Bool_t)intFlowFlags->GetBinContent(10); // to be improved (hardwired 9) } else { cout<<"WARNING: intFlowFlags is NULL in FAWQC::GPFIFH() !!!!"<(intFlowList->FindObject("Profiles")); if(intFlowProfiles) { // average multiplicities: TString avMultiplicityName = "fAvMultiplicity"; avMultiplicityName += fAnalysisLabel->Data(); TProfile *avMultiplicity = dynamic_cast(intFlowProfiles->FindObject(avMultiplicityName.Data())); if(avMultiplicity) { this->SetAvMultiplicity(avMultiplicity); } else { cout<<"WARNING: avMultiplicity is NULL in AFAWQC::GPFIFH() !!!!"<>, <<4>>, <<6>> and <<8>> (with wrong errors!): TString intFlowCorrelationsProName = "fIntFlowCorrelationsPro"; intFlowCorrelationsProName += fAnalysisLabel->Data(); TProfile *intFlowCorrelationsPro = dynamic_cast(intFlowProfiles->FindObject(intFlowCorrelationsProName.Data())); if(intFlowCorrelationsPro) { this->SetIntFlowCorrelationsPro(intFlowCorrelationsPro); } else { cout<<"WARNING: intFlowCorrelationsPro is NULL in AFAWQC::GPFIFH() !!!!"<>, <<4>>, <<6>> and <<8>> versus multiplicity for all events (error is wrong here): if(fCalculateCumulantsVsM) { TString intFlowCorrelationsVsMProName = "fIntFlowCorrelationsVsMPro"; intFlowCorrelationsVsMProName += fAnalysisLabel->Data(); for(Int_t ci=0;ci<4;ci++) // correlation index { TProfile *intFlowCorrelationsVsMPro = dynamic_cast (intFlowProfiles->FindObject(Form("%s, %s",intFlowCorrelationsVsMProName.Data(),correlationFlag[ci].Data()))); if(intFlowCorrelationsVsMPro) { this->SetIntFlowCorrelationsVsMPro(intFlowCorrelationsVsMPro,ci); } else { cout<<"WARNING: "<Data(); TProfile *intFlowCorrelationsAllPro = dynamic_cast(intFlowProfiles->FindObject(intFlowCorrelationsAllProName.Data())); if(intFlowCorrelationsAllPro) { this->SetIntFlowCorrelationsAllPro(intFlowCorrelationsAllPro); } else { cout<<"WARNING: intFlowCorrelationsAllPro is NULL in AFAWQC::GPFIFH() !!!!"<Data(); TProfile *intFlowExtraCorrelationsPro = dynamic_cast(intFlowProfiles->FindObject(intFlowExtraCorrelationsProName.Data())); if(intFlowExtraCorrelationsPro) { this->SetIntFlowExtraCorrelationsPro(intFlowExtraCorrelationsPro); } else { cout<<"WARNING: intFlowExtraCorrelationsPro is NULL in AFAWQC::GPFIFH() !!!!"<, <4>, <6> and <8>: TString intFlowProductOfCorrelationsProName = "fIntFlowProductOfCorrelationsPro"; intFlowProductOfCorrelationsProName += fAnalysisLabel->Data(); TProfile *intFlowProductOfCorrelationsPro = dynamic_cast(intFlowProfiles->FindObject(intFlowProductOfCorrelationsProName.Data())); if(intFlowProductOfCorrelationsPro) { this->SetIntFlowProductOfCorrelationsPro(intFlowProductOfCorrelationsPro); } else { cout<<"WARNING: intFlowProductOfCorrelationsPro is NULL in AFAWQC::GPFIFH() !!!!"<, <4>, <6> and <8> versus multiplicity // [0=<<2><4>>,1=<<2><6>>,2=<<2><8>>,3=<<4><6>>,4=<<4><8>>,5=<<6><8>>] if(fCalculateCumulantsVsM) { TString intFlowProductOfCorrelationsVsMProName = "fIntFlowProductOfCorrelationsVsMPro"; intFlowProductOfCorrelationsVsMProName += fAnalysisLabel->Data(); TString productFlag[6] = {"<<2><4>>","<<2><6>>","<<2><8>>","<<4><6>>","<<4><8>>","<<6><8>>"}; for(Int_t pi=0;pi<6;pi++) { TProfile *intFlowProductOfCorrelationsVsMPro = dynamic_cast(intFlowProfiles->FindObject(Form("%s, %s",intFlowProductOfCorrelationsVsMProName.Data(),productFlag[pi].Data()))); if(intFlowProductOfCorrelationsVsMPro) { this->SetIntFlowProductOfCorrelationsVsMPro(intFlowProductOfCorrelationsVsMPro,pi); } else { cout<<"WARNING: "<Data(); TProfile *intFlowCorrectionTermsForNUAPro = dynamic_cast(intFlowProfiles->FindObject((Form("%s: %s terms",intFlowCorrectionTermsForNUAProName.Data(),sinCosFlag[sc].Data())))); if(intFlowCorrectionTermsForNUAPro) { this->SetIntFlowCorrectionTermsForNUAPro(intFlowCorrectionTermsForNUAPro,sc); } else { cout<<"WARNING: intFlowCorrectionTermsForNUAPro is NULL in AFAWQC::GPFIFH() !!!!"<Data(); for(Int_t ci=0;ci<4;ci++) // correction term index (to be improved - hardwired 4) { TProfile *intFlowCorrectionTermsForNUAVsMPro = dynamic_cast(intFlowProfiles->FindObject(Form("%s: #LT#LT%s%s#GT#GT",intFlowCorrectionTermsForNUAVsMProName.Data(),sinCosFlag[sc].Data(),correctionTermFlag[ci].Data()))); if(intFlowCorrectionTermsForNUAVsMPro) { this->SetIntFlowCorrectionTermsForNUAVsMPro(intFlowCorrectionTermsForNUAVsMPro,sc,ci); } else { cout<<"WARNING: intFlowCorrectionTermsForNUAVsMPro is NULL in AFAWQC::GPFIFH() !!!!"<Data(); TProfile *intFlowProductOfCorrectionTermsForNUAPro = dynamic_cast(intFlowProfiles->FindObject(intFlowProductOfCorrectionTermsForNUAProName.Data())); if(intFlowProductOfCorrectionTermsForNUAPro) { this->SetIntFlowProductOfCorrectionTermsForNUAPro(intFlowProductOfCorrectionTermsForNUAPro); } else { cout<<"WARNING: intFlowProductOfCorrectionTermsForNUAPro is NULL in AFAWQC::GPFIFH() !!!!"<(intFlowList->FindObject("Results")); if(intFlowResults) { // average correlations <<2>>, <<4>>, <<6>> and <<8>> (with correct errors!): TString intFlowCorrelationsHistName = "fIntFlowCorrelationsHist"; intFlowCorrelationsHistName += fAnalysisLabel->Data(); TH1D *intFlowCorrelationsHist = dynamic_cast(intFlowResults->FindObject(intFlowCorrelationsHistName.Data())); if(intFlowCorrelationsHist) { this->SetIntFlowCorrelationsHist(intFlowCorrelationsHist); } else { cout<<"WARNING: intFlowCorrelationsHist is NULL in AFAWQC::GPFIFH() !!!!"<>, <<4>>, <<6>> and <<8>> (with correct errors!) vs M: if(fCalculateCumulantsVsM) { TString intFlowCorrelationsVsMHistName = "fIntFlowCorrelationsVsMHist"; intFlowCorrelationsVsMHistName += fAnalysisLabel->Data(); for(Int_t ci=0;ci<4;ci++) // correlation index { TH1D *intFlowCorrelationsVsMHist = dynamic_cast (intFlowResults->FindObject(Form("%s, %s",intFlowCorrelationsVsMHistName.Data(),correlationFlag[ci].Data()))); if(intFlowCorrelationsVsMHist) { this->SetIntFlowCorrelationsVsMHist(intFlowCorrelationsVsMHist,ci); } else { cout<<"WARNING: "<Data(); TH1D *intFlowCorrelationsAllHist = dynamic_cast(intFlowResults->FindObject(intFlowCorrelationsAllHistName.Data())); if(intFlowCorrelationsAllHist) { this->SetIntFlowCorrelationsAllHist(intFlowCorrelationsAllHist); } else { cout<<"WARNING: intFlowCorrelationsAllHist is NULL in AFAWQC::GPFIFH() !!!!"<Data(); for(Int_t sc=0;sc<2;sc++) { TH1D *intFlowCorrectionTermsForNUAHist = dynamic_cast(intFlowResults->FindObject((Form("%s: %s terms",intFlowCorrectionTermsForNUAHistName.Data(),sinCosFlag[sc].Data())))); if(intFlowCorrectionTermsForNUAHist) { this->SetIntFlowCorrectionTermsForNUAHist(intFlowCorrectionTermsForNUAHist,sc); } else { cout<<"WARNING: intFlowCorrectionTermsForNUAHist is NULL in AFAWQC::GPFIFH() !!!!"<Data(); TH1D *intFlowCovariances = dynamic_cast(intFlowResults->FindObject(intFlowCovariancesName.Data())); if(intFlowCovariances) { this->SetIntFlowCovariances(intFlowCovariances); } else { cout<<"WARNING: intFlowCovariances is NULL in AFAWQC::GPFIFH() !!!!"<, <4>, <6> and <8>: TString intFlowSumOfEventWeightsName = "fIntFlowSumOfEventWeights"; intFlowSumOfEventWeightsName += fAnalysisLabel->Data(); for(Int_t power=0;power<2;power++) { TH1D *intFlowSumOfEventWeights = dynamic_cast(intFlowResults->FindObject(Form("%s: %s",intFlowSumOfEventWeightsName.Data(),powerFlag[power].Data()))); if(intFlowSumOfEventWeights) { this->SetIntFlowSumOfEventWeights(intFlowSumOfEventWeights,power); } else { cout<<"WARNING: intFlowSumOfEventWeights is NULL in AFAWQC::GPFIFH() !!!!"<Data(); TH1D *intFlowSumOfProductOfEventWeights = dynamic_cast(intFlowResults->FindObject(intFlowSumOfProductOfEventWeightsName.Data())); if(intFlowSumOfProductOfEventWeights) { this->SetIntFlowSumOfProductOfEventWeights(intFlowSumOfProductOfEventWeights); } else { cout<<"WARNING: intFlowSumOfProductOfEventWeights is NULL in AFAWQC::GPFIFH() !!!!"<Data(); TString covarianceFlag[6] = {"Cov(<2>,<4>)","Cov(<2>,<6>)","Cov(<2>,<8>)","Cov(<4>,<6>)","Cov(<4>,<8>)","Cov(<6>,<8>)"}; for(Int_t ci=0;ci<6;ci++) { TH1D *intFlowCovariancesVsM = dynamic_cast(intFlowResults->FindObject(Form("%s, %s",intFlowCovariancesVsMName.Data(),covarianceFlag[ci].Data()))); if(intFlowCovariancesVsM) { this->SetIntFlowCovariancesVsM(intFlowCovariancesVsM,ci); } else { cout<<"WARNING: "<, <4>, <6> and <8> versus multiplicity // [0=sum{w_{<2>}},1=sum{w_{<4>}},2=sum{w_{<6>}},3=sum{w_{<8>}}][0=linear 1,1=quadratic]: if(fCalculateCumulantsVsM) { TString intFlowSumOfEventWeightsVsMName = "fIntFlowSumOfEventWeightsVsM"; intFlowSumOfEventWeightsVsMName += fAnalysisLabel->Data(); TString sumFlag[2][4] = {{"#sum_{i=1}^{N} w_{<2>}","#sum_{i=1}^{N} w_{<4>}","#sum_{i=1}^{N} w_{<6>}","#sum_{i=1}^{N} w_{<8>}"}, {"#sum_{i=1}^{N} w_{<2>}^{2}","#sum_{i=1}^{N} w_{<4>}^{2}","#sum_{i=1}^{N} w_{<6>}^{2}","#sum_{i=1}^{N} w_{<8>}^{2}"}}; for(Int_t si=0;si<4;si++) { for(Int_t power=0;power<2;power++) { TH1D *intFlowSumOfEventWeightsVsM = dynamic_cast(intFlowResults->FindObject(Form("%s, %s",intFlowSumOfEventWeightsVsMName.Data(),sumFlag[power][si].Data()))); if(intFlowSumOfEventWeightsVsM) { this->SetIntFlowSumOfEventWeightsVsM(intFlowSumOfEventWeightsVsM,si,power); } else { cout<<"WARNING: "<, <4>, <6> and <8> vs M // [0=sum{w_{<2>}w_{<4>}},1=sum{w_{<2>}w_{<6>}},2=sum{w_{<2>}w_{<8>}}, // 3=sum{w_{<4>}w_{<6>}},4=sum{w_{<4>}w_{<8>}},5=sum{w_{<6>}w_{<8>}}]: if(fCalculateCumulantsVsM) { TString intFlowSumOfProductOfEventWeightsVsMName = "fIntFlowSumOfProductOfEventWeightsVsM"; intFlowSumOfProductOfEventWeightsVsMName += fAnalysisLabel->Data(); TString sopowFlag[6] = {"#sum_{i=1}^{N} w_{<2>} w_{<4>}","#sum_{i=1}^{N} w_{<2>} w_{<6>}","#sum_{i=1}^{N} w_{<2>} w_{<8>}", "#sum_{i=1}^{N} w_{<4>} w_{<6>}","#sum_{i=1}^{N} w_{<4>} w_{<8>}","#sum_{i=1}^{N} w_{<6>} w_{<8>}"}; for(Int_t pi=0;pi<6;pi++) { TH1D *intFlowSumOfProductOfEventWeightsVsM = dynamic_cast(intFlowResults->FindObject(Form("%s, %s",intFlowSumOfProductOfEventWeightsVsMName.Data(),sopowFlag[pi].Data()))); if(intFlowSumOfProductOfEventWeightsVsM) { this->SetIntFlowSumOfProductOfEventWeightsVsM(intFlowSumOfProductOfEventWeightsVsM,pi); } else { cout<<"WARNING: "<Data(); TH1D *intFlowCovariancesNUA = dynamic_cast(intFlowResults->FindObject(intFlowCovariancesNUAName.Data())); if(intFlowCovariancesNUA) { this->SetIntFlowCovariancesNUA(intFlowCovariancesNUA); } else { cout<<"WARNING: intFlowCovariancesNUA is NULL in AFAWQC::GPFIFH() !!!!"<Data(); for(Int_t sc=0;sc<2;sc++) { for(Int_t power=0;power<2;power++) { TH1D *intFlowSumOfEventWeightsNUA = dynamic_cast(intFlowResults->FindObject(Form("%s: %s, %s",intFlowSumOfEventWeightsNUAName.Data(),powerFlag[power].Data(),sinCosFlag[sc].Data()))); if(intFlowSumOfEventWeightsNUA) { this->SetIntFlowSumOfEventWeightsNUA(intFlowSumOfEventWeightsNUA,sc,power); } else { cout<<"WARNING: intFlowSumOfEventWeightsNUA is NULL in AFAWQC::GPFIFH() !!!!"<Data(); TH1D *intFlowSumOfProductOfEventWeightsNUA = dynamic_cast(intFlowResults->FindObject(intFlowSumOfProductOfEventWeightsNUAName.Data())); if(intFlowSumOfProductOfEventWeightsNUA) { this->SetIntFlowSumOfProductOfEventWeightsNUA(intFlowSumOfProductOfEventWeightsNUA); } else { cout<<"WARNING: intFlowSumOfProductOfEventWeightsNUA is NULL in AFAWQC::GPFIFH() !!!!"<Data(); TH1D *intFlowQcumulants = dynamic_cast(intFlowResults->FindObject(intFlowQcumulantsName.Data())); if(intFlowQcumulants) { this->SetIntFlowQcumulants(intFlowQcumulants); } else { cout<<"WARNING: intFlowQcumulants is NULL in AFAWQC::GPFIFH() !!!!"<Data(); TH1D *intFlowQcumulantsRebinnedInM = dynamic_cast(intFlowResults->FindObject(intFlowQcumulantsRebinnedInMName.Data())); if(intFlowQcumulantsRebinnedInM) { this->SetIntFlowQcumulantsRebinnedInM(intFlowQcumulantsRebinnedInM); } else { cout<<"WARNING: intFlowQcumulantsRebinnedInM is NULL in AFAWQC::GPFIFH() !!!!"<Data(); for(Int_t co=0;co<4;co++) // cumulant order { TH1D *intFlowQcumulantsVsM = dynamic_cast (intFlowResults->FindObject(Form("%s, %s",intFlowQcumulantsVsMName.Data(),cumulantFlag[co].Data()))); if(intFlowQcumulantsVsM) { this->SetIntFlowQcumulantsVsM(intFlowQcumulantsVsM,co); } else { cout<<"WARNING: "<Data(); TH1D *intFlow = dynamic_cast(intFlowResults->FindObject(intFlowName.Data())); if(intFlow) { this->SetIntFlow(intFlow); } else { cout<<"WARNING: intFlow is NULL in AFAWQC::GPFIFH() !!!!"<Data(); TH1D *intFlowRebinnedInM = dynamic_cast(intFlowResults->FindObject(intFlowRebinnedInMName.Data())); if(intFlowRebinnedInM) { this->SetIntFlowRebinnedInM(intFlowRebinnedInM); } else { cout<<"WARNING: intFlowRebinnedInM is NULL in AFAWQC::GPFIFH() !!!!"<Data(); TString flowFlag[4] = {"v_{2}{2,QC}","v_{2}{4,QC}","v_{2}{6,QC}","v_{2}{8,QC}"}; // to be improved (harwired harmonic) for(Int_t co=0;co<4;co++) // cumulant order { TH1D *intFlowVsM = dynamic_cast (intFlowResults->FindObject(Form("%s, %s",intFlowVsMName.Data(),flowFlag[co].Data()))); if(intFlowVsM) { this->SetIntFlowVsM(intFlowVsM,co); } else { cout<<"WARNING: "<Data(); TH1D *intFlowDetectorBias = dynamic_cast(intFlowResults->FindObject(intFlowDetectorBiasName.Data())); if(intFlowDetectorBias) { this->SetIntFlowDetectorBias(intFlowDetectorBias); } else { cout<<"WARNING: intFlowDetectorBias is NULL in AFAWQC::GPFIFH() !!!!"<Data(); for(Int_t ci=0;ci<4;ci++) // correlation index { TH1D *intFlowDetectorBiasVsM = dynamic_cast (intFlowResults->FindObject(Form("%s for %s",intFlowDetectorBiasVsMName.Data(),cumulantFlag[ci].Data()))); if(intFlowDetectorBiasVsM) { this->SetIntFlowDetectorBiasVsM(intFlowDetectorBiasVsM,ci); } else { cout<<"WARNING: "<","<4'>","<6'>","<8'>"}; TString mixedCorrelationIndex[8] = {"<2>","<2'>","<4>","<4'>","<6>","<6'>","<8>","<8'>"}; TString covarianceName[5] = {"Cov(<2>,<2'>)","Cov(<2>,<4'>)","Cov(<4>,<2'>)","Cov(<4>,<4'>)","Cov(<2'>,<4'>)"}; // b) Get pointer to base list for differential flow fDiffFlowList and nested lists fDiffFlowListProfiles and fDiffFlowListResults: TList *diffFlowList = NULL; diffFlowList = dynamic_cast(fHistList->FindObject("Differential Flow")); if(!diffFlowList) { cout<<"WARNING: diffFlowList is NULL in AFAWQC::GPFDFH() !!!!"<(diffFlowList->FindObject("Profiles")); if(!diffFlowListProfiles) { cout<<"WARNING: diffFlowListProfiles is NULL in AFAWQC::GPFDFH() !!!!"<(diffFlowList->FindObject("Results")); if(!diffFlowListResults) { cout<<"WARNING: diffFlowListResults is NULL in AFAWQC::GPFDFH() !!!!"<Data(); TProfile *diffFlowFlags = dynamic_cast(diffFlowList->FindObject(diffFlowFlagsName.Data())); Bool_t bCalculate2DFlow = kFALSE; if(diffFlowFlags) { this->SetDiffFlowFlags(diffFlowFlags); bCalculate2DFlow = (Int_t)diffFlowFlags->GetBinContent(4); this->SetCalculate2DFlow(bCalculate2DFlow); // to be improved (shoul I call this setter somewhere else?) } // d) Get pointers to all nested lists in fDiffFlowListProfiles and to profiles which they hold; // correlations: TList *diffFlowCorrelationsProList[2][2] = {{NULL}}; TString diffFlowCorrelationsProName = "fDiffFlowCorrelationsPro"; diffFlowCorrelationsProName += fAnalysisLabel->Data(); TProfile *diffFlowCorrelationsPro[2][2][4] = {{{NULL}}}; // products of correlations: TList *diffFlowProductOfCorrelationsProList[2][2] = {{NULL}}; TString diffFlowProductOfCorrelationsProName = "fDiffFlowProductOfCorrelationsPro"; diffFlowProductOfCorrelationsProName += fAnalysisLabel->Data(); TProfile *diffFlowProductOfCorrelationsPro[2][2][8][8] = {{{{NULL}}}}; // corrections: TList *diffFlowCorrectionsProList[2][2] = {{NULL}}; TString diffFlowCorrectionTermsForNUAProName = "fDiffFlowCorrectionTermsForNUAPro"; diffFlowCorrectionTermsForNUAProName += fAnalysisLabel->Data(); TProfile *diffFlowCorrectionTermsForNUAPro[2][2][2][10] = {{{{NULL}}}}; for(Int_t t=0;t<2;t++) { for(Int_t pe=0;pe<2;pe++) { diffFlowCorrelationsProList[t][pe] = dynamic_cast(diffFlowListProfiles->FindObject(Form("Profiles with correlations (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data()))); if(!diffFlowCorrelationsProList[t][pe]) { cout<<"WARNING: diffFlowCorrelationsProList[t][pe] is NULL in AFAWQC::GPFDFH() !!!!"<SetDiffFlowCorrelationsPro(diffFlowCorrelationsPro[t][pe][ci],t,pe,ci); } else { cout<<"WARNING: diffFlowCorrelationsPro[t][pe][ci] is NULL in AFAWQC::GPFDFH() !!!!"<SetDiffFlowProductOfCorrelationsPro(diffFlowProductOfCorrelationsPro[t][pe][mci1][mci2],t,pe,mci1,mci2); } else { cout<<"WARNING: diffFlowCorrelationsPro[t][pe][ci] is NULL in AFAWQC::GPFDFH() !!!!"<SetDiffFlowCorrectionTermsForNUAPro(diffFlowCorrectionTermsForNUAPro[t][pe][sc][cti],t,pe,sc,cti); } else { cout<<"WARNING: diffFlowCorrectionTermsForNUAPro[t][pe][sc][cti] is NULL in AFAWQC::GPFDFH() !!!!"<Data(); TH1D *diffFlowCorrelationsHist[2][2][4] = {{{NULL}}}; // corrections for NUA: TList *diffFlowCorrectionsHistList[2][2] = {{NULL}}; TString diffFlowCorrectionTermsForNUAHistName = "fDiffFlowCorrectionTermsForNUAHist"; diffFlowCorrectionTermsForNUAHistName += fAnalysisLabel->Data(); TH1D *diffFlowCorrectionTermsForNUAHist[2][2][2][10] = {{{{NULL}}}}; // differential Q-cumulants: TList *diffFlowCumulantsHistList[2][2] = {{NULL}}; TString diffFlowCumulantsName = "fDiffFlowCumulants"; diffFlowCumulantsName += fAnalysisLabel->Data(); TH1D *diffFlowCumulants[2][2][4] = {{{NULL}}}; // differential flow estimates from Q-cumulants: TList *diffFlowHistList[2][2] = {{NULL}}; TString diffFlowName = "fDiffFlow"; diffFlowName += fAnalysisLabel->Data(); TH1D *diffFlow[2][2][4] = {{{NULL}}}; // differential covariances: TList *diffFlowCovariancesHistList[2][2] = {{NULL}}; TString diffFlowCovariancesName = "fDiffFlowCovariances"; diffFlowCovariancesName += fAnalysisLabel->Data(); TH1D *diffFlowCovariances[2][2][5] = {{{NULL}}}; for(Int_t t=0;t<2;t++) // type: RP or POI { for(Int_t pe=0;pe<2;pe++) // pt or eta { // reduced correlations: diffFlowCorrelationsHistList[t][pe] = dynamic_cast(diffFlowListResults->FindObject(Form("Correlations (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data()))); if(!diffFlowCorrelationsHistList[t][pe]) { cout<<"WARNING: diffFlowCorrelationsHistList[t][pe] is NULL in AFAWQC::GPFDFH() !!!!"<SetDiffFlowCorrelationsHist(diffFlowCorrelationsHist[t][pe][index],t,pe,index); } else { cout<<"WARNING: diffFlowCorrelationsHist[t][pe][index] is NULL in AFAWQC::GPFDFH() !!!!"<SetDiffFlowCorrectionTermsForNUAHist(diffFlowCorrectionTermsForNUAHist[t][pe][sc][cti],t,pe,sc,cti); } else { cout<<"WARNING: diffFlowCorrectionTermsForNUAHist[t][pe][sc][cti] is NULL in AFAWQC::GPFDFH() !!!!"<SetDiffFlowCumulants(diffFlowCumulants[t][pe][index],t,pe,index); } else { cout<<"WARNING: diffFlowCumulants[t][pe][index] is NULL in AFAWQC::GPFDFH() !!!!"<SetDiffFlow(diffFlow[t][pe][index],t,pe,index); } else { cout<<"WARNING: diffFlow[t][pe][index] is NULL in AFAWQC::GPFDFH() !!!!"<SetDiffFlowCovariances(diffFlowCovariances[t][pe][covIndex],t,pe,covIndex); } else { cout<<"WARNING: diffFlowCovariances[t][pe][covIndex] is NULL in AFAWQC::GPFDFH() !!!!"<Data(); TH1D *diffFlowSumOfEventWeights[2][2][2][4] = {{{{NULL}}}}; for(Int_t t=0;t<2;t++) // type is RP or POI { for(Int_t pe=0;pe<2;pe++) // pt or eta { for(Int_t p=0;p<2;p++) // power of event weights is either 1 or 2 { diffFlowSumOfEventWeightsHistList[t][pe][p] = dynamic_cast(diffFlowListResults->FindObject(Form("Sum of %s event weights (%s, %s)",powerFlag[p].Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data()))); if(!diffFlowSumOfEventWeightsHistList[t][pe][p]) { cout<<"WARNING: diffFlowSumOfEventWeightsHistList[t][pe][p] is NULL in AFAWQC::GPFDFH() !!!!"<SetDiffFlowSumOfEventWeights(diffFlowSumOfEventWeights[t][pe][p][ew],t,pe,p,ew); } else { cout<<"WARNING: diffFlowSumOfEventWeights[t][pe][p][ew] is NULL in AFAWQC::GPFDFH() !!!!"<Data(); TH1D *diffFlowSumOfProductOfEventWeights[2][2][8][8] = {{{{NULL}}}}; for(Int_t t=0;t<2;t++) // type is RP or POI { for(Int_t pe=0;pe<2;pe++) // pt or eta { diffFlowSumOfProductOfEventWeightsHistList[t][pe] = dynamic_cast(diffFlowListResults->FindObject(Form("Sum of products of event weights (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data()))); if(!diffFlowSumOfProductOfEventWeightsHistList[t][pe]) { cout<<"WARNING: diffFlowSumOfProductOfEventWeightsHistList[t][pe] is NULL in AFAWQC::GPFDFH() !!!!"<SetDiffFlowSumOfProductOfEventWeights(diffFlowSumOfProductOfEventWeights[t][pe][mci1][mci2],t,pe,mci1,mci2); } else { cout<<"WARNING: diffFlowSumOfProductOfEventWeights[t][pe][mci1][mci2] is NULL in AFAWQC::GPFDFH() !!!!"<","<4'>","<6'>","<8'>"}; TString mixedCorrelationIndex[8] = {"<2>","<2'>","<4>","<4'>","<6>","<6'>","<8>","<8'>"}; TString covarianceName[5] = {"Cov(<2>,<2'>)","Cov(<2>,<4'>)","Cov(<4>,<2'>)","Cov(<4>,<4'>)","Cov(<2'>,<4'>)"}; Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; Double_t minPtEta[2] = {fPtMin,fEtaMin}; Double_t maxPtEta[2] = {fPtMax,fEtaMax}; // b) Book profile to hold all flags for differential flow: TString diffFlowFlagsName = "fDiffFlowFlags"; diffFlowFlagsName += fAnalysisLabel->Data(); fDiffFlowFlags = new TProfile(diffFlowFlagsName.Data(),"Flags for Differential Flow",4,0,4); fDiffFlowFlags->SetTickLength(-0.01,"Y"); fDiffFlowFlags->SetMarkerStyle(25); fDiffFlowFlags->SetLabelSize(0.05); fDiffFlowFlags->SetLabelOffset(0.02,"Y"); (fDiffFlowFlags->GetXaxis())->SetBinLabel(1,"Particle Weights"); (fDiffFlowFlags->GetXaxis())->SetBinLabel(2,"Event Weights"); (fDiffFlowFlags->GetXaxis())->SetBinLabel(3,"Corrected for NUA?"); (fDiffFlowFlags->GetXaxis())->SetBinLabel(4,"Calculated 2D flow?"); fDiffFlowList->Add(fDiffFlowFlags); // c) Book e-b-e quantities: // Event-by-event r_{m*n,k}(pt,eta), p_{m*n,k}(pt,eta) and q_{m*n,k}(pt,eta) // Explanantion of notation: // 1.) n is harmonic, m is multiple of harmonic; // 2.) k is power of particle weight; // 3.) r_{m*n,k}(pt,eta) = Q-vector evaluated in harmonic m*n for RPs in particular (pt,eta) bin (i-th RP is weighted with w_i^k); // 4.) p_{m*n,k}(pt,eta) = Q-vector evaluated in harmonic m*n for POIs in particular (pt,eta) bin // (if i-th POI is also RP, than it is weighted with w_i^k); // 5.) q_{m*n,k}(pt,eta) = Q-vector evaluated in harmonic m*n for particles which are both RPs and POIs in particular (pt,eta) bin // (i-th RP&&POI is weighted with w_i^k) // 1D: for(Int_t t=0;t<3;t++) // typeFlag (0 = RP, 1 = POI, 2 = RP && POI ) { for(Int_t pe=0;pe<2;pe++) // pt or eta { for(Int_t m=0;m<4;m++) // multiple of harmonic { for(Int_t k=0;k<9;k++) // power of particle weight { fReRPQ1dEBE[t][pe][m][k] = new TProfile(Form("TypeFlag%dpteta%dmultiple%dpower%dRe",t,pe,m,k), Form("TypeFlag%dpteta%dmultiple%dpower%dRe",t,pe,m,k),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); fImRPQ1dEBE[t][pe][m][k] = new TProfile(Form("TypeFlag%dpteta%dmultiple%dpower%dIm",t,pe,m,k), Form("TypeFlag%dpteta%dmultiple%dpower%dIm",t,pe,m,k),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); } } } } // to be improved (add explanation of fs1dEBE[t][pe][k]): for(Int_t t=0;t<3;t++) // typeFlag (0 = RP, 1 = POI, 2 = RP&&POI ) { for(Int_t pe=0;pe<2;pe++) // pt or eta { for(Int_t k=0;k<9;k++) // power of particle weight { fs1dEBE[t][pe][k] = new TProfile(Form("TypeFlag%dpteta%dmultiple%d",t,pe,k), Form("TypeFlag%dpteta%dmultiple%d",t,pe,k),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); } } } // correction terms for nua: for(Int_t t=0;t<2;t++) // typeFlag (0 = RP, 1 = POI) { for(Int_t pe=0;pe<2;pe++) // pt or eta { for(Int_t sc=0;sc<2;sc++) // sin or cos { for(Int_t cti=0;cti<9;cti++) // correction term index { fDiffFlowCorrectionTermsForNUAEBE[t][pe][sc][cti] = new TH1D(Form("typeFlag%d pteta%d sincos%d cti%d",t,pe,sc,cti), Form("typeFlag%d pteta%d sincos%d cti%d",t,pe,sc,cti),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); } } } } // 2D: TProfile2D styleRe("typeMultiplePowerRe","typeMultiplePowerRe",fnBinsPt,fPtMin,fPtMax,fnBinsEta,fEtaMin,fEtaMax); TProfile2D styleIm("typeMultiplePowerIm","typeMultiplePowerIm",fnBinsPt,fPtMin,fPtMax,fnBinsEta,fEtaMin,fEtaMax); for(Int_t t=0;t<3;t++) // typeFlag (0 = RP, 1 = POI, 2 = RP&&POI ) { for(Int_t m=0;m<4;m++) { for(Int_t k=0;k<9;k++) { fReRPQ2dEBE[t][m][k] = (TProfile2D*)styleRe.Clone(Form("typeFlag%dmultiple%dpower%dRe",t,m,k)); fImRPQ2dEBE[t][m][k] = (TProfile2D*)styleIm.Clone(Form("typeFlag%dmultiple%dpower%dIm",t,m,k)); } } } TProfile2D styleS("typePower","typePower",fnBinsPt,fPtMin,fPtMax,fnBinsEta,fEtaMin,fEtaMax); for(Int_t t=0;t<3;t++) // typeFlag (0 = RP, 1 = POI, 2 = RP&&POI ) { for(Int_t k=0;k<9;k++) { fs2dEBE[t][k] = (TProfile2D*)styleS.Clone(Form("typeFlag%dpower%d",t,k)); } } // reduced correlations e-b-e: TString diffFlowCorrelationsEBEName = "fDiffFlowCorrelationsEBE"; diffFlowCorrelationsEBEName += fAnalysisLabel->Data(); for(Int_t t=0;t<2;t++) // type: RP or POI { for(Int_t pe=0;pe<2;pe++) // pt or eta { for(Int_t rci=0;rci<4;rci++) // reduced correlation index { fDiffFlowCorrelationsEBE[t][pe][rci] = new TH1D(Form("%s, %s, %s, %s",diffFlowCorrelationsEBEName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedCorrelationIndex[rci].Data()),Form("%s, %s, %s, %s",diffFlowCorrelationsEBEName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedCorrelationIndex[rci].Data()),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); } // end of for(Int_t ci=0;ci<4;ci++) // correlation index } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta } // end of for(Int_t t=0;t<2;t++) // type: RP or POI // event weights for reduced correlations e-b-e: TString diffFlowEventWeightsForCorrelationsEBEName = "fDiffFlowEventWeightsForCorrelationsEBE"; diffFlowEventWeightsForCorrelationsEBEName += fAnalysisLabel->Data(); for(Int_t t=0;t<2;t++) // type: RP or POI { for(Int_t pe=0;pe<2;pe++) // pt or eta { for(Int_t rci=0;rci<4;rci++) // event weight for reduced correlation index { fDiffFlowEventWeightsForCorrelationsEBE[t][pe][rci] = new TH1D(Form("%s, %s, %s, eW for %s",diffFlowEventWeightsForCorrelationsEBEName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedCorrelationIndex[rci].Data()),Form("%s, %s, %s, eW for %s",diffFlowEventWeightsForCorrelationsEBEName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedCorrelationIndex[rci].Data()),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); } // end of for(Int_t ci=0;ci<4;ci++) // correlation index } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta } // end of for(Int_t t=0;t<2;t++) // type: RP or POI // d) Book profiles; // reduced correlations: TString diffFlowCorrelationsProName = "fDiffFlowCorrelationsPro"; diffFlowCorrelationsProName += fAnalysisLabel->Data(); // corrections terms: TString diffFlowCorrectionTermsForNUAProName = "fDiffFlowCorrectionTermsForNUAPro"; diffFlowCorrectionTermsForNUAProName += fAnalysisLabel->Data(); for(Int_t t=0;t<2;t++) // type: RP or POI { for(Int_t pe=0;pe<2;pe++) // pt or eta { for(Int_t rci=0;rci<4;rci++) // reduced correlation index { // reduced correlations: fDiffFlowCorrelationsPro[t][pe][rci] = new TProfile(Form("%s, %s, %s, %s",diffFlowCorrelationsProName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedCorrelationIndex[rci].Data()),Form("%s, %s, %s, %s",diffFlowCorrelationsProName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedCorrelationIndex[rci].Data()),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe],"s"); fDiffFlowCorrelationsPro[t][pe][rci]->SetXTitle(ptEtaFlag[pe].Data()); fDiffFlowCorrelationsProList[t][pe]->Add(fDiffFlowCorrelationsPro[t][pe][rci]); // to be improved (add dedicated list to hold reduced correlations) } // end of for(Int_t rci=0;rci<4;rci++) // correlation index } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta } // end of for(Int_t t=0;t<2;t++) // type: RP or POI // correction terms for nua: for(Int_t t=0;t<2;t++) // typeFlag (0 = RP, 1 = POI) { for(Int_t pe=0;pe<2;pe++) // pt or eta { for(Int_t sc=0;sc<2;sc++) // sin or cos { for(Int_t cti=0;cti<9;cti++) // correction term index { fDiffFlowCorrectionTermsForNUAPro[t][pe][sc][cti] = new TProfile(Form("%s, %s, %s, %s, cti = %d",diffFlowCorrectionTermsForNUAProName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),sinCosFlag[sc].Data(),cti+1),Form("%s, %s, %s, %s, cti = %d",diffFlowCorrectionTermsForNUAProName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),sinCosFlag[sc].Data(),cti+1),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); fDiffFlowCorrectionsProList[t][pe]->Add(fDiffFlowCorrectionTermsForNUAPro[t][pe][sc][cti]); } } } } // e) Book histograms holding final results. // reduced correlations: TString diffFlowCorrelationsHistName = "fDiffFlowCorrelationsHist"; diffFlowCorrelationsHistName += fAnalysisLabel->Data(); // corrections terms: TString diffFlowCorrectionTermsForNUAHistName = "fDiffFlowCorrectionTermsForNUAHist"; diffFlowCorrectionTermsForNUAHistName += fAnalysisLabel->Data(); // differential covariances: TString diffFlowCovariancesName = "fDiffFlowCovariances"; diffFlowCovariancesName += fAnalysisLabel->Data(); // differential Q-cumulants: TString diffFlowCumulantsName = "fDiffFlowCumulants"; diffFlowCumulantsName += fAnalysisLabel->Data(); // differential flow: TString diffFlowName = "fDiffFlow"; diffFlowName += fAnalysisLabel->Data(); for(Int_t t=0;t<2;t++) // type: RP or POI { for(Int_t pe=0;pe<2;pe++) // pt or eta { for(Int_t index=0;index<4;index++) { // reduced correlations: fDiffFlowCorrelationsHist[t][pe][index] = new TH1D(Form("%s, %s, %s, %s",diffFlowCorrelationsHistName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedCorrelationIndex[index].Data()),Form("%s, %s, %s, %s",diffFlowCorrelationsHistName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedCorrelationIndex[index].Data()),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); fDiffFlowCorrelationsHist[t][pe][index]->SetXTitle(ptEtaFlag[pe].Data()); fDiffFlowCorrelationsHistList[t][pe]->Add(fDiffFlowCorrelationsHist[t][pe][index]); // differential Q-cumulants: fDiffFlowCumulants[t][pe][index] = new TH1D(Form("%s, %s, %s, %s",diffFlowCumulantsName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),differentialCumulantIndex[index].Data()),Form("%s, %s, %s, %s",diffFlowCumulantsName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),differentialCumulantIndex[index].Data()),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); fDiffFlowCumulants[t][pe][index]->SetXTitle(ptEtaFlag[pe].Data()); fDiffFlowCumulantsHistList[t][pe]->Add(fDiffFlowCumulants[t][pe][index]); // differential flow estimates from Q-cumulants: fDiffFlow[t][pe][index] = new TH1D(Form("%s, %s, %s, %s",diffFlowName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),differentialFlowIndex[index].Data()),Form("%s, %s, %s, %s",diffFlowName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),differentialFlowIndex[index].Data()),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); fDiffFlow[t][pe][index]->SetXTitle(ptEtaFlag[pe].Data()); fDiffFlowHistList[t][pe]->Add(fDiffFlow[t][pe][index]); } // end of for(Int_t index=0;index<4;index++) for(Int_t covIndex=0;covIndex<5;covIndex++) // covariance index { // differential covariances: fDiffFlowCovariances[t][pe][covIndex] = new TH1D(Form("%s, %s, %s, %s",diffFlowCovariancesName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),covarianceName[covIndex].Data()),Form("%s, %s, %s, %s",diffFlowCovariancesName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),covarianceName[covIndex].Data()),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); fDiffFlowCovariances[t][pe][covIndex]->SetXTitle(ptEtaFlag[pe].Data()); fDiffFlowCovariancesHistList[t][pe]->Add(fDiffFlowCovariances[t][pe][covIndex]); } // end of for(Int_t covIndex=0;covIndex<5;covIndex++) // covariance index // products of both types of correlations: TString diffFlowProductOfCorrelationsProName = "fDiffFlowProductOfCorrelationsPro"; diffFlowProductOfCorrelationsProName += fAnalysisLabel->Data(); for(Int_t mci1=0;mci1<8;mci1++) // mixed correlation index { for(Int_t mci2=mci1+1;mci2<8;mci2++) // mixed correlation index { fDiffFlowProductOfCorrelationsPro[t][pe][mci1][mci2] = new TProfile(Form("%s, %s, %s, %s, %s",diffFlowProductOfCorrelationsProName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),mixedCorrelationIndex[mci1].Data(),mixedCorrelationIndex[mci2].Data()),Form("%s, %s, %s, %s #times %s",diffFlowProductOfCorrelationsProName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),mixedCorrelationIndex[mci1].Data(),mixedCorrelationIndex[mci2].Data()),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); fDiffFlowProductOfCorrelationsPro[t][pe][mci1][mci2]->SetXTitle(ptEtaFlag[pe].Data()); fDiffFlowProductOfCorrelationsProList[t][pe]->Add(fDiffFlowProductOfCorrelationsPro[t][pe][mci1][mci2]); if(mci1%2 == 0) mci2++; // products which DO NOT include reduced correlations are not stored here } // end of for(Int_t mci2=mci1+1;mci2<8;mci2++) // mixed correlation index } // end of for(Int_t mci1=0;mci1<8;mci1++) // mixed correlation index } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta } // end of for(Int_t t=0;t<2;t++) // type: RP or POI // sums of event weights for reduced correlations: TString diffFlowSumOfEventWeightsName = "fDiffFlowSumOfEventWeights"; diffFlowSumOfEventWeightsName += fAnalysisLabel->Data(); for(Int_t t=0;t<2;t++) // type is RP or POI { for(Int_t pe=0;pe<2;pe++) // pt or eta { for(Int_t p=0;p<2;p++) // power of weights is either 1 or 2 { for(Int_t ew=0;ew<4;ew++) // index of reduced correlation { fDiffFlowSumOfEventWeights[t][pe][p][ew] = new TH1D(Form("%s, %s, %s, %s, %s",diffFlowSumOfEventWeightsName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),powerFlag[p].Data(),reducedCorrelationIndex[ew].Data()),Form("%s, %s, %s, power = %s, %s",diffFlowSumOfEventWeightsName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),powerFlag[p].Data(),reducedCorrelationIndex[ew].Data()),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); fDiffFlowSumOfEventWeights[t][pe][p][ew]->SetXTitle(ptEtaFlag[pe].Data()); fDiffFlowSumOfEventWeightsHistList[t][pe][p]->Add(fDiffFlowSumOfEventWeights[t][pe][p][ew]); // to be improved (add dedicated list to hold all this) } } } } // sum of products of event weights for both types of correlations: TString diffFlowSumOfProductOfEventWeightsName = "fDiffFlowSumOfProductOfEventWeights"; diffFlowSumOfProductOfEventWeightsName += fAnalysisLabel->Data(); for(Int_t t=0;t<2;t++) // type is RP or POI { for(Int_t pe=0;pe<2;pe++) // pt or eta { for(Int_t mci1=0;mci1<8;mci1++) // mixed correlation index { for(Int_t mci2=mci1+1;mci2<8;mci2++) // mixed correlation index { fDiffFlowSumOfProductOfEventWeights[t][pe][mci1][mci2] = new TH1D(Form("%s, %s, %s, %s, %s",diffFlowSumOfProductOfEventWeightsName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),mixedCorrelationIndex[mci1].Data(),mixedCorrelationIndex[mci2].Data()),Form("%s, %s, %s, %s #times %s",diffFlowSumOfProductOfEventWeightsName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),mixedCorrelationIndex[mci1].Data(),mixedCorrelationIndex[mci2].Data()),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); fDiffFlowSumOfProductOfEventWeights[t][pe][mci1][mci2]->SetXTitle(ptEtaFlag[pe].Data()); fDiffFlowSumOfProductOfEventWeightsHistList[t][pe]->Add(fDiffFlowSumOfProductOfEventWeights[t][pe][mci1][mci2]); if(mci1%2 == 0) mci2++; // products which DO NOT include reduced correlations are not stored here } } } } // correction terms for nua: for(Int_t t=0;t<2;t++) // typeFlag (0 = RP, 1 = POI) { for(Int_t pe=0;pe<2;pe++) // pt or eta { for(Int_t sc=0;sc<2;sc++) // sin or cos { for(Int_t cti=0;cti<9;cti++) // correction term index { fDiffFlowCorrectionTermsForNUAHist[t][pe][sc][cti] = new TH1D(Form("%s, %s, %s, %s, cti = %d",diffFlowCorrectionTermsForNUAHistName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),sinCosFlag[sc].Data(),cti+1),Form("%s, %s, %s, %s, cti = %d",diffFlowCorrectionTermsForNUAHistName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),sinCosFlag[sc].Data(),cti+1),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); fDiffFlowCorrectionsHistList[t][pe]->Add(fDiffFlowCorrectionTermsForNUAHist[t][pe][sc][cti]); } } } } } // end of AliFlowAnalysisWithQCumulants::BookEverythingForDifferentialFlow() //================================================================================================================================ /* void AliFlowAnalysisWithQCumulants::CalculateCorrectionsForNUAForIntQcumulants() // to be improved (do I really need this method?) { // Calculate final corrections for non-uniform acceptance for Q-cumulants. // Corrections for non-uniform acceptance are stored in histogram fCorrectionsForNUA, // binning of fCorrectionsForNUA is organized as follows: // // 1st bin: correction to QC{2} // 2nd bin: correction to QC{4} // 3rd bin: correction to QC{6} // 4th bin: correction to QC{8} // shortcuts flags: Int_t pW = (Int_t)(useParticleWeights); Int_t eW = -1; if(eventWeights == "exact") { eW = 0; } for(Int_t sc=0;sc<2;sc++) // sin or cos terms flag { if(!(fQCorrelations[pW][eW] && fQCorrections[pW][eW][sc] && fCorrections[pW][eW])) { cout<<"WARNING: fQCorrelations[pW][eW] && fQCorrections[pW][eW][sc] && fCorrections[pW][eW] is NULL in AFAWQC::CFCFNUAFIF() !!!!"<=0.) { fIntFlow->SetBinError(2,pow(err4thSquared,0.5)); // to be improved (enabled eventually) } else { cout<<"WARNING: Statistical error of v{4,QC} (with non-isotropic terms included) is imaginary !!!! "<GetBinContent(ci); Double_t spread = fIntFlowCorrectionTermsForNUAPro[sc]->GetBinError(ci); Double_t sumOfLinearEventWeights = fIntFlowSumOfEventWeightsNUA[sc][0]->GetBinContent(ci); Double_t sumOfQuadraticEventWeights = fIntFlowSumOfEventWeightsNUA[sc][1]->GetBinContent(ci); Double_t termA = 0.; Double_t termB = 0.; if(sumOfLinearEventWeights) { termA = pow(sumOfQuadraticEventWeights,0.5)/sumOfLinearEventWeights; } else { cout<<"WARNING: sumOfLinearEventWeights == 0 in AFAWQC::FCTFNIF() !!!!"< 0.) { termB = 1./pow(1-pow(termA,2.),0.5); } else { cout<<"WARNING: 1.-pow(termA,2.) <= 0 in AFAWQC::FCTFNIF() !!!!"<SetBinContent(ci,correction); fIntFlowCorrectionTermsForNUAHist[sc]->SetBinError(ci,statisticalError); } // end of for(Int_t ci=1;ci<=10;ci++) // correction term index } // end of for(Int sc=0;sc<2;sc++) // sin or cos correction terms } // end of void AliFlowAnalysisWithQCumulants::FinalizeCorrectionTermsForNUAIntFlow() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::GetPointersForNestedLoopsHistograms() { // Get pointers to all objects relevant for calculations with nested loops. TList *nestedLoopsList = dynamic_cast(fHistList->FindObject("Nested Loops")); if(nestedLoopsList) { this->SetNestedLoopsList(nestedLoopsList); } else { cout<<"WARNING: nestedLoopsList is NULL in AFAWQC::GPFNLH() !!!!"<","<4'>","<6'>","<8'>"}; // to be improved (should I promote this to data members?) TString evaluateNestedLoopsName = "fEvaluateNestedLoops"; evaluateNestedLoopsName += fAnalysisLabel->Data(); TProfile *evaluateNestedLoops = dynamic_cast(nestedLoopsList->FindObject(evaluateNestedLoopsName.Data())); Bool_t bEvaluateIntFlowNestedLoops = kFALSE; Bool_t bEvaluateDiffFlowNestedLoops = kFALSE; if(evaluateNestedLoops) { this->SetEvaluateNestedLoops(evaluateNestedLoops); bEvaluateIntFlowNestedLoops = (Int_t)evaluateNestedLoops->GetBinContent(1); bEvaluateDiffFlowNestedLoops = (Int_t)evaluateNestedLoops->GetBinContent(2); } // nested loops relevant for integrated flow: if(bEvaluateIntFlowNestedLoops) { // correlations: TString intFlowDirectCorrelationsName = "fIntFlowDirectCorrelations"; intFlowDirectCorrelationsName += fAnalysisLabel->Data(); TProfile *intFlowDirectCorrelations = dynamic_cast(nestedLoopsList->FindObject(intFlowDirectCorrelationsName.Data())); if(intFlowDirectCorrelations) { this->SetIntFlowDirectCorrelations(intFlowDirectCorrelations); } else { cout<<"WARNING: intFlowDirectCorrelations is NULL in AFAWQC::GPFNLH() !!!!"<Data(); TProfile *intFlowExtraDirectCorrelations = dynamic_cast(nestedLoopsList->FindObject(intFlowExtraDirectCorrelationsName.Data())); if(intFlowExtraDirectCorrelations) { this->SetIntFlowExtraDirectCorrelations(intFlowExtraDirectCorrelations); } else { cout<<"WARNING: intFlowExtraDirectCorrelations is NULL in AFAWQC::GPFNLH() !!!!"<Data(); TProfile *intFlowDirectCorrectionTermsForNUA[2] = {NULL}; for(Int_t sc=0;sc<2;sc++) // sin or cos terms { intFlowDirectCorrectionTermsForNUA[sc] = dynamic_cast(nestedLoopsList->FindObject(Form("%s: %s terms",intFlowDirectCorrectionTermsForNUAName.Data(),sinCosFlag[sc].Data()))); if(intFlowDirectCorrectionTermsForNUA[sc]) { this->SetIntFlowDirectCorrectionTermsForNUA(intFlowDirectCorrectionTermsForNUA[sc],sc); } else { cout<<"WARNING: intFlowDirectCorrectionTermsForNUA[sc] is NULL in AFAWQC::GPFNLH() !!!!"<Data(); TProfile *diffFlowDirectCorrelations[2][2][4] = {{{NULL}}}; for(Int_t t=0;t<2;t++) { for(Int_t pe=0;pe<2;pe++) { for(Int_t ci=0;ci<4;ci++) // correlation index { diffFlowDirectCorrelations[t][pe][ci] = dynamic_cast(nestedLoopsList->FindObject(Form("%s, %s, %s, %s",diffFlowDirectCorrelationsName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedCorrelationIndex[ci].Data()))); if(diffFlowDirectCorrelations[t][pe][ci]) { this->SetDiffFlowDirectCorrelations(diffFlowDirectCorrelations[t][pe][ci],t,pe,ci); } else { cout<<"WARNING: diffFlowDirectCorrelations[t][pe][ci] is NULL in AFAWQC::GPFDFH() !!!!"<Data(); TProfile *diffFlowDirectCorrectionTermsForNUA[2][2][2][10] = {{{{NULL}}}}; for(Int_t t=0;t<2;t++) { for(Int_t pe=0;pe<2;pe++) { // correction terms for NUA: for(Int_t sc=0;sc<2;sc++) // sin or cos { for(Int_t cti=0;cti<9;cti++) // correction term index { diffFlowDirectCorrectionTermsForNUA[t][pe][sc][cti] = dynamic_cast(nestedLoopsList->FindObject(Form("%s, %s, %s, %s, cti = %d",diffFlowDirectCorrectionTermsForNUAName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),sinCosFlag[sc].Data(),cti+1))); if(diffFlowDirectCorrectionTermsForNUA[t][pe][sc][cti]) { this->SetDiffFlowDirectCorrectionTermsForNUA(diffFlowDirectCorrectionTermsForNUA[t][pe][sc][cti],t,pe,sc,cti); } else { cout<<"WARNING: diffFlowDirectCorrectionTermsForNUA[t][pe][sc][cti] is NULL in AFAWQC::GPFDFH() !!!!"<(nestedLoopsList->FindObject(noOfParticlesInBinName.Data())); if(noOfParticlesInBin) { this->SetNoOfParticlesInBin(noOfParticlesInBin); } else { cout<GetHarmonic())->Fill(0.5,fHarmonic); (fCommonHists2nd->GetHarmonic())->Fill(0.5,fHarmonic); (fCommonHists4th->GetHarmonic())->Fill(0.5,fHarmonic); (fCommonHists6th->GetHarmonic())->Fill(0.5,fHarmonic); (fCommonHists8th->GetHarmonic())->Fill(0.5,fHarmonic); } // end of void AliFlowAnalysisWithQCumulants::StoreHarmonic() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrelationsUsingParticleWeights(TString type, TString ptOrEta) // type = RP or POI { // Calculate all correlations needed for differential flow using particle weights. Int_t t = -1; // type flag Int_t pe = -1; // ptEta flag if(type == "RP") { t = 0; } else if(type == "POI") { t = 1; } if(ptOrEta == "Pt") { pe = 0; } else if(ptOrEta == "Eta") { pe = 1; } Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; Double_t minPtEta[2] = {fPtMin,fEtaMin}; //Double_t maxPtEta[2] = {fPtMax,fEtaMax}; Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; // real and imaginary parts of weighted Q-vectors evaluated in harmonics n, 2n, 3n and 4n: Double_t dReQ1n1k = (*fReQ)(0,1); Double_t dReQ2n2k = (*fReQ)(1,2); Double_t dReQ1n3k = (*fReQ)(0,3); //Double_t dReQ4n4k = (*fReQ)(3,4); Double_t dImQ1n1k = (*fImQ)(0,1); Double_t dImQ2n2k = (*fImQ)(1,2); Double_t dImQ1n3k = (*fImQ)(0,3); //Double_t dImQ4n4k = (*fImQ)(3,4); // S^M_{p,k} (see .h file for the definition of fSMpk): Double_t dSM1p1k = (*fSMpk)(0,1); Double_t dSM1p2k = (*fSMpk)(0,2); Double_t dSM1p3k = (*fSMpk)(0,3); Double_t dSM2p1k = (*fSMpk)(1,1); Double_t dSM3p1k = (*fSMpk)(2,1); // looping over all bins and calculating reduced correlations: for(Int_t b=1;b<=nBinsPtEta[pe];b++) { // real and imaginary parts of p_{m*n,0} (non-weighted Q-vector evaluated for POIs in particular (pt,eta) bin): Double_t p1n0kRe = 0.; Double_t p1n0kIm = 0.; // number of POIs in particular (pt,eta) bin): Double_t mp = 0.; // real and imaginary parts of q_{m*n,k}: // (weighted Q-vector evaluated for particles which are both RPs and POIs in particular (pt,eta) bin) Double_t q1n2kRe = 0.; Double_t q1n2kIm = 0.; Double_t q2n1kRe = 0.; Double_t q2n1kIm = 0.; // s_{1,1}, s_{1,2} and s_{1,3} // to be improved (add explanation) Double_t s1p1k = 0.; Double_t s1p2k = 0.; Double_t s1p3k = 0.; // M0111 from Eq. (118) in QC2c (to be improved (notation)) Double_t dM0111 = 0.; if(type == "POI") { p1n0kRe = fReRPQ1dEBE[1][pe][0][0]->GetBinContent(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)) * fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)); p1n0kIm = fImRPQ1dEBE[1][pe][0][0]->GetBinContent(fImRPQ1dEBE[1][pe][0][0]->GetBin(b)) * fImRPQ1dEBE[1][pe][0][0]->GetBinEntries(fImRPQ1dEBE[1][pe][0][0]->GetBin(b)); mp = fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) t = 1; // typeFlag = RP or POI // q_{m*n,k}: (Remark: m=1 is 0, k=0 iz zero (to be improved!)) q1n2kRe = fReRPQ1dEBE[2][pe][0][2]->GetBinContent(fReRPQ1dEBE[2][pe][0][2]->GetBin(b)) * fReRPQ1dEBE[2][pe][0][2]->GetBinEntries(fReRPQ1dEBE[2][pe][0][2]->GetBin(b)); q1n2kIm = fImRPQ1dEBE[2][pe][0][2]->GetBinContent(fImRPQ1dEBE[2][pe][0][2]->GetBin(b)) * fImRPQ1dEBE[2][pe][0][2]->GetBinEntries(fImRPQ1dEBE[2][pe][0][2]->GetBin(b)); q2n1kRe = fReRPQ1dEBE[2][pe][1][1]->GetBinContent(fReRPQ1dEBE[2][pe][1][1]->GetBin(b)) * fReRPQ1dEBE[2][pe][1][1]->GetBinEntries(fReRPQ1dEBE[2][pe][1][1]->GetBin(b)); q2n1kIm = fImRPQ1dEBE[2][pe][1][1]->GetBinContent(fImRPQ1dEBE[2][pe][1][1]->GetBin(b)) * fImRPQ1dEBE[2][pe][1][1]->GetBinEntries(fImRPQ1dEBE[2][pe][1][1]->GetBin(b)); // s_{1,1}, s_{1,2} and s_{1,3} // to be improved (add explanation) s1p1k = pow(fs1dEBE[2][pe][1]->GetBinContent(b)*fs1dEBE[2][pe][1]->GetBinEntries(b),1.); s1p2k = pow(fs1dEBE[2][pe][2]->GetBinContent(b)*fs1dEBE[2][pe][2]->GetBinEntries(b),1.); s1p3k = pow(fs1dEBE[2][pe][3]->GetBinContent(b)*fs1dEBE[2][pe][3]->GetBinEntries(b),1.); // M0111 from Eq. (118) in QC2c (to be improved (notation)): dM0111 = mp*(dSM3p1k-3.*dSM1p1k*dSM1p2k+2.*dSM1p3k) - 3.*(s1p1k*(dSM2p1k-dSM1p2k) + 2.*(s1p3k-s1p2k*dSM1p1k)); } else if(type == "RP") { // q_{m*n,k}: (Remark: m=1 is 0, k=0 iz zero (to be improved!)) q1n2kRe = fReRPQ1dEBE[0][pe][0][2]->GetBinContent(fReRPQ1dEBE[0][pe][0][2]->GetBin(b)) * fReRPQ1dEBE[0][pe][0][2]->GetBinEntries(fReRPQ1dEBE[0][pe][0][2]->GetBin(b)); q1n2kIm = fImRPQ1dEBE[0][pe][0][2]->GetBinContent(fImRPQ1dEBE[0][pe][0][2]->GetBin(b)) * fImRPQ1dEBE[0][pe][0][2]->GetBinEntries(fImRPQ1dEBE[0][pe][0][2]->GetBin(b)); q2n1kRe = fReRPQ1dEBE[0][pe][1][1]->GetBinContent(fReRPQ1dEBE[0][pe][1][1]->GetBin(b)) * fReRPQ1dEBE[0][pe][1][1]->GetBinEntries(fReRPQ1dEBE[0][pe][1][1]->GetBin(b)); q2n1kIm = fImRPQ1dEBE[0][pe][1][1]->GetBinContent(fImRPQ1dEBE[0][pe][1][1]->GetBin(b)) * fImRPQ1dEBE[0][pe][1][1]->GetBinEntries(fImRPQ1dEBE[0][pe][1][1]->GetBin(b)); // s_{1,1}, s_{1,2} and s_{1,3} // to be improved (add explanation) s1p1k = pow(fs1dEBE[0][pe][1]->GetBinContent(b)*fs1dEBE[0][pe][1]->GetBinEntries(b),1.); s1p2k = pow(fs1dEBE[0][pe][2]->GetBinContent(b)*fs1dEBE[0][pe][2]->GetBinEntries(b),1.); s1p3k = pow(fs1dEBE[0][pe][3]->GetBinContent(b)*fs1dEBE[0][pe][3]->GetBinEntries(b),1.); // to be improved (cross-checked): p1n0kRe = fReRPQ1dEBE[0][pe][0][0]->GetBinContent(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)) * fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)); p1n0kIm = fImRPQ1dEBE[0][pe][0][0]->GetBinContent(fImRPQ1dEBE[0][pe][0][0]->GetBin(b)) * fImRPQ1dEBE[0][pe][0][0]->GetBinEntries(fImRPQ1dEBE[0][pe][0][0]->GetBin(b)); mp = fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) t = 0; // typeFlag = RP or POI // M0111 from Eq. (118) in QC2c (to be improved (notation)): dM0111 = mp*(dSM3p1k-3.*dSM1p1k*dSM1p2k+2.*dSM1p3k) - 3.*(s1p1k*(dSM2p1k-dSM1p2k) + 2.*(s1p3k-s1p2k*dSM1p1k)); //............................................................................................... } // 2'-particle correlation: Double_t two1n1nW0W1 = 0.; if(mp*dSM1p1k-s1p1k) { two1n1nW0W1 = (p1n0kRe*dReQ1n1k+p1n0kIm*dImQ1n1k-s1p1k) / (mp*dSM1p1k-s1p1k); // fill profile to get <<2'>> fDiffFlowCorrelationsPro[t][pe][0]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],two1n1nW0W1,mp*dSM1p1k-s1p1k); // histogram to store <2'> e-b-e (needed in some other methods): fDiffFlowCorrelationsEBE[t][pe][0]->SetBinContent(b,two1n1nW0W1); fDiffFlowEventWeightsForCorrelationsEBE[t][pe][0]->SetBinContent(b,mp*dSM1p1k-s1p1k); } // end of if(mp*dSM1p1k-s1p1k) // 4'-particle correlation: Double_t four1n1n1n1nW0W1W1W1 = 0.; if(dM0111) { four1n1n1n1nW0W1W1W1 = ((pow(dReQ1n1k,2.)+pow(dImQ1n1k,2.))*(p1n0kRe*dReQ1n1k+p1n0kIm*dImQ1n1k) - q2n1kRe*(pow(dReQ1n1k,2.)-pow(dImQ1n1k,2.)) - 2.*q2n1kIm*dReQ1n1k*dImQ1n1k - p1n0kRe*(dReQ1n1k*dReQ2n2k+dImQ1n1k*dImQ2n2k) + p1n0kIm*(dImQ1n1k*dReQ2n2k-dReQ1n1k*dImQ2n2k) - 2.*dSM1p2k*(p1n0kRe*dReQ1n1k+p1n0kIm*dImQ1n1k) - 2.*(pow(dReQ1n1k,2.)+pow(dImQ1n1k,2.))*s1p1k + 6.*(q1n2kRe*dReQ1n1k+q1n2kIm*dImQ1n1k) + 1.*(q2n1kRe*dReQ2n2k+q2n1kIm*dImQ2n2k) + 2.*(p1n0kRe*dReQ1n3k+p1n0kIm*dImQ1n3k) + 2.*s1p1k*dSM1p2k - 6.*s1p3k) / dM0111; // to be improved (notation of dM0111) // fill profile to get <<4'>> fDiffFlowCorrelationsPro[t][pe][1]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],four1n1n1n1nW0W1W1W1,dM0111); // histogram to store <4'> e-b-e (needed in some other methods): fDiffFlowCorrelationsEBE[t][pe][1]->SetBinContent(b,four1n1n1n1nW0W1W1W1); fDiffFlowEventWeightsForCorrelationsEBE[t][pe][1]->SetBinContent(b,dM0111); } // end of if(dM0111) } // end of for(Int_t b=1;b<=nBinsPtEta[pe];b++) } // end of void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrelationsUsingParticleWeights(TString type, TString ptOrEta); // type = RP or POI //================================================================================================================================ void AliFlowAnalysisWithQCumulants::FillCommonControlHistograms(AliFlowEventSimple *anEvent) { // Fill common control histograms. Int_t nRP = anEvent->GetEventNSelTracksRP(); // number of RPs (i.e. number of particles used to determine the reaction plane) fCommonHists->FillControlHistograms(anEvent); if(nRP>1) { fCommonHists2nd->FillControlHistograms(anEvent); if(nRP>3) { fCommonHists4th->FillControlHistograms(anEvent); if(nRP>5) { fCommonHists6th->FillControlHistograms(anEvent); if(nRP>7) { fCommonHists8th->FillControlHistograms(anEvent); } // end of if(nRP>7) } // end of if(nRP>5) } // end of if(nRP>3) } // end of if(nRP>1) } // end of void AliFlowAnalysisWithQCumulants::FillCommonControlHistograms(AliFlowEventSimple *anEvent) //================================================================================================================================ void AliFlowAnalysisWithQCumulants::ResetEventByEventQuantities() { // Reset all event by event quantities. // integrated flow: fReQ->Zero(); fImQ->Zero(); fSMpk->Zero(); fIntFlowCorrelationsEBE->Reset(); fIntFlowEventWeightsForCorrelationsEBE->Reset(); fIntFlowCorrelationsAllEBE->Reset(); if(fApplyCorrectionForNUA) { for(Int_t sc=0;sc<2;sc++) { fIntFlowCorrectionTermsForNUAEBE[sc]->Reset(); fIntFlowEventWeightForCorrectionTermsForNUAEBE[sc]->Reset(); } } // differential flow: // 1D: for(Int_t t=0;t<3;t++) // type (RP, POI, POI&&RP) { for(Int_t pe=0;pe<2;pe++) // 1D in pt or eta { for(Int_t m=0;m<4;m++) // multiple of harmonic { for(Int_t k=0;k<9;k++) // power of weight { if(fReRPQ1dEBE[t][pe][m][k]) fReRPQ1dEBE[t][pe][m][k]->Reset(); if(fImRPQ1dEBE[t][pe][m][k]) fImRPQ1dEBE[t][pe][m][k]->Reset(); } } } } for(Int_t t=0;t<3;t++) // type (0 = RP, 1 = POI, 2 = RP&&POI ) { for(Int_t pe=0;pe<2;pe++) // 1D in pt or eta { for(Int_t k=0;k<9;k++) { if(fs1dEBE[t][pe][k]) fs1dEBE[t][pe][k]->Reset(); } } } // e-b-e reduced correlations: for(Int_t t=0;t<2;t++) // type (0 = RP, 1 = POI) { for(Int_t pe=0;pe<2;pe++) // pt or eta { for(Int_t rci=0;rci<4;rci++) // reduced correlation index { if(fDiffFlowCorrelationsEBE[t][pe][rci]) fDiffFlowCorrelationsEBE[t][pe][rci]->Reset(); if(fDiffFlowEventWeightsForCorrelationsEBE[t][pe][rci]) fDiffFlowEventWeightsForCorrelationsEBE[t][pe][rci]->Reset(); } } } // correction terms for NUA: for(Int_t t=0;t<2;t++) // type (0 = RP, 1 = POI) { for(Int_t pe=0;pe<2;pe++) // pt or eta { for(Int_t sc=0;sc<2;sc++) // sin or cos { for(Int_t cti=0;cti<9;cti++) // correction term index { fDiffFlowCorrectionTermsForNUAEBE[t][pe][sc][cti]->Reset(); } } } } // 2D (pt,eta) if(fCalculate2DFlow) { for(Int_t t=0;t<3;t++) // type (RP, POI, POI&&RP) { for(Int_t m=0;m<4;m++) // multiple of harmonic { for(Int_t k=0;k<9;k++) // power of weight { if(fReRPQ2dEBE[t][m][k]) fReRPQ2dEBE[t][m][k]->Reset(); if(fImRPQ2dEBE[t][m][k]) fImRPQ2dEBE[t][m][k]->Reset(); } } } for(Int_t t=0;t<3;t++) // type (0 = RP, 1 = POI, 2 = RP&&POI ) { for(Int_t k=0;k<9;k++) { if(fs2dEBE[t][k]) fs2dEBE[t][k]->Reset(); } } } // end of if(fCalculate2DFlow) } // end of void AliFlowAnalysisWithQCumulants::ResetEventByEventQuantities(); //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrectionsForNUASinTerms(TString type, TString ptOrEta) { // Calculate correction terms for non-uniform acceptance for differential flow (sin terms). // Results are stored in fDiffFlowCorrectionTermsForNUAPro[t][pe][0][cti], where cti runs as follows: // 0: <> // 1: <> // 2: <> // 3: <>: // 4: // 5: // 6: // multiplicity: Double_t dMult = (*fSMpk)(0,0); // real and imaginary parts of non-weighted Q-vectors evaluated in harmonics n, 2n, 3n and 4n: Double_t dReQ1n = (*fReQ)(0,0); Double_t dReQ2n = (*fReQ)(1,0); //Double_t dReQ3n = (*fReQ)(2,0); //Double_t dReQ4n = (*fReQ)(3,0); Double_t dImQ1n = (*fImQ)(0,0); Double_t dImQ2n = (*fImQ)(1,0); //Double_t dImQ3n = (*fImQ)(2,0); //Double_t dImQ4n = (*fImQ)(3,0); Int_t t = -1; // type flag Int_t pe = -1; // ptEta flag if(type == "RP") { t = 0; } else if(type == "POI") { t = 1; } if(ptOrEta == "Pt") { pe = 0; } else if(ptOrEta == "Eta") { pe = 1; } Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; Double_t minPtEta[2] = {fPtMin,fEtaMin}; //Double_t maxPtEta[2] = {fPtMax,fEtaMax}; Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; // looping over all bins and calculating correction terms: for(Int_t b=1;b<=nBinsPtEta[pe];b++) { // real and imaginary parts of p_{m*n,0} (non-weighted Q-vector evaluated for POIs in particular pt or eta bin): Double_t p1n0kRe = 0.; Double_t p1n0kIm = 0.; // number of POIs in particular pt or eta bin: Double_t mp = 0.; // real and imaginary parts of q_{m*n,0} (non-weighted Q-vector evaluated for particles which are both RPs and POIs in particular pt or eta bin): Double_t q1n0kRe = 0.; Double_t q1n0kIm = 0.; Double_t q2n0kRe = 0.; Double_t q2n0kIm = 0.; // number of particles which are both RPs and POIs in particular pt or eta bin: Double_t mq = 0.; if(type == "POI") { // q_{m*n,0}: q1n0kRe = fReRPQ1dEBE[2][pe][0][0]->GetBinContent(fReRPQ1dEBE[2][pe][0][0]->GetBin(b)) * fReRPQ1dEBE[2][pe][0][0]->GetBinEntries(fReRPQ1dEBE[2][pe][0][0]->GetBin(b)); q1n0kIm = fImRPQ1dEBE[2][pe][0][0]->GetBinContent(fImRPQ1dEBE[2][pe][0][0]->GetBin(b)) * fImRPQ1dEBE[2][pe][0][0]->GetBinEntries(fImRPQ1dEBE[2][pe][0][0]->GetBin(b)); q2n0kRe = fReRPQ1dEBE[2][pe][1][0]->GetBinContent(fReRPQ1dEBE[2][pe][1][0]->GetBin(b)) * fReRPQ1dEBE[2][pe][1][0]->GetBinEntries(fReRPQ1dEBE[2][pe][1][0]->GetBin(b)); q2n0kIm = fImRPQ1dEBE[2][pe][1][0]->GetBinContent(fImRPQ1dEBE[2][pe][1][0]->GetBin(b)) * fImRPQ1dEBE[2][pe][1][0]->GetBinEntries(fImRPQ1dEBE[2][pe][1][0]->GetBin(b)); mq = fReRPQ1dEBE[2][pe][0][0]->GetBinEntries(fReRPQ1dEBE[2][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) } else if(type == "RP") { // q_{m*n,0}: q1n0kRe = fReRPQ1dEBE[0][pe][0][0]->GetBinContent(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)) * fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)); q1n0kIm = fImRPQ1dEBE[0][pe][0][0]->GetBinContent(fImRPQ1dEBE[0][pe][0][0]->GetBin(b)) * fImRPQ1dEBE[0][pe][0][0]->GetBinEntries(fImRPQ1dEBE[0][pe][0][0]->GetBin(b)); q2n0kRe = fReRPQ1dEBE[0][pe][1][0]->GetBinContent(fReRPQ1dEBE[0][pe][1][0]->GetBin(b)) * fReRPQ1dEBE[0][pe][1][0]->GetBinEntries(fReRPQ1dEBE[0][pe][1][0]->GetBin(b)); q2n0kIm = fImRPQ1dEBE[0][pe][1][0]->GetBinContent(fImRPQ1dEBE[0][pe][1][0]->GetBin(b)) * fImRPQ1dEBE[0][pe][1][0]->GetBinEntries(fImRPQ1dEBE[0][pe][1][0]->GetBin(b)); mq = fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) } if(type == "POI") { // p_{m*n,0}: p1n0kRe = fReRPQ1dEBE[1][pe][0][0]->GetBinContent(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)) * fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)); p1n0kIm = fImRPQ1dEBE[1][pe][0][0]->GetBinContent(fImRPQ1dEBE[1][pe][0][0]->GetBin(b)) * fImRPQ1dEBE[1][pe][0][0]->GetBinEntries(fImRPQ1dEBE[1][pe][0][0]->GetBin(b)); mp = fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) t = 1; // typeFlag = RP or POI } else if(type == "RP") { // p_{m*n,0} = q_{m*n,0}: p1n0kRe = q1n0kRe; p1n0kIm = q1n0kIm; mp = mq; t = 0; // typeFlag = RP or POI } // <>: Double_t sinP1nPsi = 0.; if(mp) { sinP1nPsi = p1n0kIm/mp; // fill profile for <>: fDiffFlowCorrectionTermsForNUAPro[t][pe][0][0]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sinP1nPsi,mp); // histogram to store e-b-e (needed in some other methods): fDiffFlowCorrectionTermsForNUAEBE[t][pe][0][0]->SetBinContent(b,sinP1nPsi); } // end of if(mp) // <>: Double_t sinP1nPsiP1nPhi = 0.; if(mp*dMult-mq) { sinP1nPsiP1nPhi = (p1n0kRe*dImQ1n+p1n0kIm*dReQ1n-q2n0kIm)/(mp*dMult-mq); // fill profile for <>: fDiffFlowCorrectionTermsForNUAPro[t][pe][0][1]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sinP1nPsiP1nPhi,mp*dMult-mq); // histogram to store e-b-e (needed in some other methods): fDiffFlowCorrectionTermsForNUAEBE[t][pe][0][1]->SetBinContent(b,sinP1nPsiP1nPhi); } // end of if(mp*dMult-mq) // <>: Double_t sinP1nPsi1P1nPhi2MPhi3 = 0.; if(mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)) { sinP1nPsi1P1nPhi2MPhi3 = (p1n0kIm*(pow(dImQ1n,2.)+pow(dReQ1n,2.)-dMult) - 1.*(q2n0kIm*dReQ1n-q2n0kRe*dImQ1n) - mq*dImQ1n+2.*q1n0kIm) / (mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)); // fill profile for <>: fDiffFlowCorrectionTermsForNUAPro[t][pe][0][2]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sinP1nPsi1P1nPhi2MPhi3,mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)); // histogram to store e-b-e (needed in some other methods): fDiffFlowCorrectionTermsForNUAEBE[t][pe][0][2]->SetBinContent(b,sinP1nPsi1P1nPhi2MPhi3); } // end of if(mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)) // <>: Double_t sinP1nPsi1M1nPhi2MPhi3 = 0.; if(mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)) { sinP1nPsi1M1nPhi2MPhi3 = (p1n0kIm*(pow(dReQ1n,2.)-pow(dImQ1n,2.))-2.*p1n0kRe*dReQ1n*dImQ1n - 1.*(p1n0kIm*dReQ2n-p1n0kRe*dImQ2n) + 2.*mq*dImQ1n-2.*q1n0kIm) / (mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)); // fill profile for <>: fDiffFlowCorrectionTermsForNUAPro[t][pe][0][3]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sinP1nPsi1M1nPhi2MPhi3,mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)); // histogram to store e-b-e (needed in some other methods): fDiffFlowCorrectionTermsForNUAEBE[t][pe][0][3]->SetBinContent(b,sinP1nPsi1M1nPhi2MPhi3); } // end of if(mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)) } // end of for(Int_t b=1;b<=nBinsPtEta[pe];b++) } // end of AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrectionsForNUASinTerms(TString type, TString ptOrEta) //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrectionsForNUACosTerms(TString type, TString ptOrEta) { // Calculate correction terms for non-uniform acceptance for differential flow (cos terms). // Results are stored in fDiffFlowCorrectionTermsForNUAPro[t][pe][1][cti], where cti runs as follows: // 0: <> // 1: <> // 2: <> // 3: <> // 4: // 5: // 6: // multiplicity: Double_t dMult = (*fSMpk)(0,0); // real and imaginary parts of non-weighted Q-vectors evaluated in harmonics n, 2n, 3n and 4n: Double_t dReQ1n = (*fReQ)(0,0); Double_t dReQ2n = (*fReQ)(1,0); //Double_t dReQ3n = (*fReQ)(2,0); //Double_t dReQ4n = (*fReQ)(3,0); Double_t dImQ1n = (*fImQ)(0,0); Double_t dImQ2n = (*fImQ)(1,0); //Double_t dImQ3n = (*fImQ)(2,0); //Double_t dImQ4n = (*fImQ)(3,0); Int_t t = -1; // type flag Int_t pe = -1; // ptEta flag if(type == "RP") { t = 0; } else if(type == "POI") { t = 1; } if(ptOrEta == "Pt") { pe = 0; } else if(ptOrEta == "Eta") { pe = 1; } Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; Double_t minPtEta[2] = {fPtMin,fEtaMin}; //Double_t maxPtEta[2] = {fPtMax,fEtaMax}; Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; // looping over all bins and calculating correction terms: for(Int_t b=1;b<=nBinsPtEta[pe];b++) { // real and imaginary parts of p_{m*n,0} (non-weighted Q-vector evaluated for POIs in particular pt or eta bin): Double_t p1n0kRe = 0.; Double_t p1n0kIm = 0.; // number of POIs in particular pt or eta bin: Double_t mp = 0.; // real and imaginary parts of q_{m*n,0} (non-weighted Q-vector evaluated for particles which are both RPs and POIs in particular pt or eta bin): Double_t q1n0kRe = 0.; Double_t q1n0kIm = 0.; Double_t q2n0kRe = 0.; Double_t q2n0kIm = 0.; // number of particles which are both RPs and POIs in particular pt or eta bin: Double_t mq = 0.; if(type == "POI") { // q_{m*n,0}: q1n0kRe = fReRPQ1dEBE[2][pe][0][0]->GetBinContent(fReRPQ1dEBE[2][pe][0][0]->GetBin(b)) * fReRPQ1dEBE[2][pe][0][0]->GetBinEntries(fReRPQ1dEBE[2][pe][0][0]->GetBin(b)); q1n0kIm = fImRPQ1dEBE[2][pe][0][0]->GetBinContent(fImRPQ1dEBE[2][pe][0][0]->GetBin(b)) * fImRPQ1dEBE[2][pe][0][0]->GetBinEntries(fImRPQ1dEBE[2][pe][0][0]->GetBin(b)); q2n0kRe = fReRPQ1dEBE[2][pe][1][0]->GetBinContent(fReRPQ1dEBE[2][pe][1][0]->GetBin(b)) * fReRPQ1dEBE[2][pe][1][0]->GetBinEntries(fReRPQ1dEBE[2][pe][1][0]->GetBin(b)); q2n0kIm = fImRPQ1dEBE[2][pe][1][0]->GetBinContent(fImRPQ1dEBE[2][pe][1][0]->GetBin(b)) * fImRPQ1dEBE[2][pe][1][0]->GetBinEntries(fImRPQ1dEBE[2][pe][1][0]->GetBin(b)); mq = fReRPQ1dEBE[2][pe][0][0]->GetBinEntries(fReRPQ1dEBE[2][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) } else if(type == "RP") { // q_{m*n,0}: q1n0kRe = fReRPQ1dEBE[0][pe][0][0]->GetBinContent(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)) * fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)); q1n0kIm = fImRPQ1dEBE[0][pe][0][0]->GetBinContent(fImRPQ1dEBE[0][pe][0][0]->GetBin(b)) * fImRPQ1dEBE[0][pe][0][0]->GetBinEntries(fImRPQ1dEBE[0][pe][0][0]->GetBin(b)); q2n0kRe = fReRPQ1dEBE[0][pe][1][0]->GetBinContent(fReRPQ1dEBE[0][pe][1][0]->GetBin(b)) * fReRPQ1dEBE[0][pe][1][0]->GetBinEntries(fReRPQ1dEBE[0][pe][1][0]->GetBin(b)); q2n0kIm = fImRPQ1dEBE[0][pe][1][0]->GetBinContent(fImRPQ1dEBE[0][pe][1][0]->GetBin(b)) * fImRPQ1dEBE[0][pe][1][0]->GetBinEntries(fImRPQ1dEBE[0][pe][1][0]->GetBin(b)); mq = fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) } if(type == "POI") { // p_{m*n,0}: p1n0kRe = fReRPQ1dEBE[1][pe][0][0]->GetBinContent(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)) * fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)); p1n0kIm = fImRPQ1dEBE[1][pe][0][0]->GetBinContent(fImRPQ1dEBE[1][pe][0][0]->GetBin(b)) * fImRPQ1dEBE[1][pe][0][0]->GetBinEntries(fImRPQ1dEBE[1][pe][0][0]->GetBin(b)); mp = fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) t = 1; // typeFlag = RP or POI } else if(type == "RP") { // p_{m*n,0} = q_{m*n,0}: p1n0kRe = q1n0kRe; p1n0kIm = q1n0kIm; mp = mq; t = 0; // typeFlag = RP or POI } // <>: Double_t cosP1nPsi = 0.; if(mp) { cosP1nPsi = p1n0kRe/mp; // fill profile for <>: fDiffFlowCorrectionTermsForNUAPro[t][pe][1][0]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],cosP1nPsi,mp); // histogram to store e-b-e (needed in some other methods): fDiffFlowCorrectionTermsForNUAEBE[t][pe][1][0]->SetBinContent(b,cosP1nPsi); } // end of if(mp) // <>: Double_t cosP1nPsiP1nPhi = 0.; if(mp*dMult-mq) { cosP1nPsiP1nPhi = (p1n0kRe*dReQ1n-p1n0kIm*dImQ1n-q2n0kRe)/(mp*dMult-mq); // fill profile for <>: fDiffFlowCorrectionTermsForNUAPro[t][pe][1][1]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],cosP1nPsiP1nPhi,mp*dMult-mq); // histogram to store e-b-e (needed in some other methods): fDiffFlowCorrectionTermsForNUAEBE[t][pe][1][1]->SetBinContent(b,cosP1nPsiP1nPhi); } // end of if(mp*dMult-mq) // <>: Double_t cosP1nPsi1P1nPhi2MPhi3 = 0.; if(mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)) { cosP1nPsi1P1nPhi2MPhi3 = (p1n0kRe*(pow(dImQ1n,2.)+pow(dReQ1n,2.)-dMult) - 1.*(q2n0kRe*dReQ1n+q2n0kIm*dImQ1n) - mq*dReQ1n+2.*q1n0kRe) / (mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)); // fill profile for <>: fDiffFlowCorrectionTermsForNUAPro[t][pe][1][2]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],cosP1nPsi1P1nPhi2MPhi3,mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)); // histogram to store e-b-e (needed in some other methods): fDiffFlowCorrectionTermsForNUAEBE[t][pe][1][2]->SetBinContent(b,cosP1nPsi1P1nPhi2MPhi3); } // end of if(mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)) // <>: Double_t cosP1nPsi1M1nPhi2MPhi3 = 0.; if(mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)) { cosP1nPsi1M1nPhi2MPhi3 = (p1n0kRe*(pow(dReQ1n,2.)-pow(dImQ1n,2.))+2.*p1n0kIm*dReQ1n*dImQ1n - 1.*(p1n0kRe*dReQ2n+p1n0kIm*dImQ2n) - 2.*mq*dReQ1n+2.*q1n0kRe) / (mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)); // fill profile for <>: fDiffFlowCorrectionTermsForNUAPro[t][pe][1][3]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],cosP1nPsi1M1nPhi2MPhi3,mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)); // histogram to store e-b-e (needed in some other methods): fDiffFlowCorrectionTermsForNUAEBE[t][pe][1][3]->SetBinContent(b,cosP1nPsi1M1nPhi2MPhi3); } // end of if(mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)) } // end of for(Int_t b=1;b<=nBinsPtEta[pe];b++) } // end of AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrectionsForNUACosTerms(TString type, TString ptOrEta) //================================================================================================================================== void AliFlowAnalysisWithQCumulants::FinalizeCorrectionTermsForNUADiffFlow(TString type, TString ptOrEta) { // Transfer prolfiles into histogams and correctly propagate the error (to be improved: description) // to be improved: debugged - I do not correctly transfer all profiles into histos (bug appears only after merging) Int_t t = -1; // type flag Int_t pe = -1; // ptEta flag if(type == "RP") { t = 0; } else if(type == "POI") { t = 1; } if(ptOrEta == "Pt") { pe = 0; } else if(ptOrEta == "Eta") { pe = 1; } Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; //Double_t minPtEta[2] = {fPtMin,fEtaMin}; //Double_t maxPtEta[2] = {fPtMax,fEtaMax}; //Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; for(Int_t sc=0;sc<2;sc++) // sin or cos { for(Int_t cti=0;cti<9;cti++) // correction term index { for(Int_t b=1;b<=nBinsPtEta[pe];b++) { Double_t correctionTerm = fDiffFlowCorrectionTermsForNUAPro[t][pe][sc][cti]->GetBinContent(b); fDiffFlowCorrectionTermsForNUAHist[t][pe][sc][cti]->SetBinContent(b,correctionTerm); // to be improved (propagate error correctly) // ... } // end of for(Int_t b=1;b<=nBinsPtEta[pe];b++) } // correction term index } // end of for(Int_t sc=0;sc<2;sc++) // sin or cos }// end of void AliFlowAnalysisWithQCumulants::FinalizeCorrectionTermsForNUADiffFlow(TString type, TString ptOrEta) //================================================================================================================================== void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCumulantsCorrectedForNUA(TString type, TString ptOrEta) { // Calculate generalized differential flow Q-cumulants (corrected for non-uniform acceptance) Int_t typeFlag = -1; Int_t ptEtaFlag = -1; if(type == "RP") { typeFlag = 0; } else if(type == "POI") { typeFlag = 1; } if(ptOrEta == "Pt") { ptEtaFlag = 0; } else if(ptOrEta == "Eta") { ptEtaFlag = 1; } // shortcuts: Int_t t = typeFlag; Int_t pe = ptEtaFlag; // common: Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; // 2-particle correlation: Double_t two = fIntFlowCorrelationsHist->GetBinContent(1); // <<2>> // sin term coming from integrated flow: Double_t sinP1nPhi = fIntFlowCorrectionTermsForNUAHist[0]->GetBinContent(1); // <> Double_t sinP1nPhi1P1nPhi2 = fIntFlowCorrectionTermsForNUAHist[0]->GetBinContent(2); // <> Double_t sinP1nPhi1M1nPhi2M1nPhi3 = fIntFlowCorrectionTermsForNUAHist[0]->GetBinContent(3); // <> // cos term coming from integrated flow: Double_t cosP1nPhi = fIntFlowCorrectionTermsForNUAHist[1]->GetBinContent(1); // <> Double_t cosP1nPhi1P1nPhi2 = fIntFlowCorrectionTermsForNUAHist[1]->GetBinContent(2); // <> Double_t cosP1nPhi1M1nPhi2M1nPhi3 = fIntFlowCorrectionTermsForNUAHist[1]->GetBinContent(3); // <> for(Int_t b=1;b<=nBinsPtEta[pe];b++) { Double_t twoPrime = fDiffFlowCorrelationsHist[t][pe][0]->GetBinContent(b); // <<2'>> Double_t fourPrime = fDiffFlowCorrelationsHist[t][pe][1]->GetBinContent(b); // <<4'>> Double_t sinP1nPsi = fDiffFlowCorrectionTermsForNUAHist[t][pe][0][0]->GetBinContent(b); // <> Double_t cosP1nPsi = fDiffFlowCorrectionTermsForNUAHist[t][pe][1][0]->GetBinContent(b); // <> Double_t sinP1nPsi1P1nPhi2 = fDiffFlowCorrectionTermsForNUAHist[t][pe][0][1]->GetBinContent(b); // <> Double_t cosP1nPsi1P1nPhi2 = fDiffFlowCorrectionTermsForNUAHist[t][pe][1][1]->GetBinContent(b); // <> Double_t sinP1nPsi1P1nPhi2M1nPhi3 = fDiffFlowCorrectionTermsForNUAHist[t][pe][0][2]->GetBinContent(b); // <> Double_t cosP1nPsi1P1nPhi2M1nPhi3 = fDiffFlowCorrectionTermsForNUAHist[t][pe][1][2]->GetBinContent(b); // <> Double_t sinP1nPsi1M1nPhi2M1nPhi3 = fDiffFlowCorrectionTermsForNUAHist[t][pe][0][3]->GetBinContent(b); // <> Double_t cosP1nPsi1M1nPhi2M1nPhi3 = fDiffFlowCorrectionTermsForNUAHist[t][pe][1][3]->GetBinContent(b); // <> // generalized QC{2'}: Double_t qc2Prime = twoPrime - sinP1nPsi*sinP1nPhi - cosP1nPsi*cosP1nPhi; fDiffFlowCumulants[t][pe][0]->SetBinContent(b,qc2Prime); // generalized QC{4'}: Double_t qc4Prime = fourPrime-2.*twoPrime*two - cosP1nPsi*cosP1nPhi1M1nPhi2M1nPhi3 + sinP1nPsi*sinP1nPhi1M1nPhi2M1nPhi3 - cosP1nPhi*cosP1nPsi1M1nPhi2M1nPhi3 + sinP1nPhi*sinP1nPsi1M1nPhi2M1nPhi3 - 2.*cosP1nPhi*cosP1nPsi1P1nPhi2M1nPhi3 - 2.*sinP1nPhi*sinP1nPsi1P1nPhi2M1nPhi3 - cosP1nPsi1P1nPhi2*cosP1nPhi1P1nPhi2 - sinP1nPsi1P1nPhi2*sinP1nPhi1P1nPhi2 + 2.*cosP1nPhi1P1nPhi2*(cosP1nPsi*cosP1nPhi-sinP1nPsi*sinP1nPhi) + 2.*sinP1nPhi1P1nPhi2*(cosP1nPsi*sinP1nPhi+sinP1nPsi*cosP1nPhi) + 4.*two*(cosP1nPsi*cosP1nPhi+sinP1nPsi*sinP1nPhi) + 2.*cosP1nPsi1P1nPhi2*(pow(cosP1nPhi,2.)-pow(sinP1nPhi,2.)) + 4.*sinP1nPsi1P1nPhi2*cosP1nPhi*sinP1nPhi + 4.*twoPrime*(pow(cosP1nPhi,2.)+pow(sinP1nPhi,2.)) - 6.*(pow(cosP1nPhi,2.)-pow(sinP1nPhi,2.)) * (cosP1nPsi*cosP1nPhi-sinP1nPsi*sinP1nPhi) - 12.*cosP1nPhi*sinP1nPhi * (sinP1nPsi*cosP1nPhi+cosP1nPsi*sinP1nPhi); fDiffFlowCumulants[t][pe][1]->SetBinContent(b,qc4Prime); } // end of for(Int_t p=1;p<=fnBinsPt;p++) } // end of AliFlowAnalysisWithQCumulants::CalculateDiffFlowCumulantsCorrectedForNUA(TString type, TString ptOrEta) //================================================================================================================================== void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrectedForNUA(TString type, TString ptOrEta) { // Calculate differential flow corrected for non-uniform acceptance. // to be improved (rewritten completely) Int_t typeFlag = -1; Int_t ptEtaFlag = -1; if(type == "RP") { typeFlag = 0; } else if(type == "POI") { typeFlag = 1; } if(ptOrEta == "Pt") { ptEtaFlag = 0; } else if(ptOrEta == "Eta") { ptEtaFlag = 1; } // shortcuts: Int_t t = typeFlag; Int_t pe = ptEtaFlag; // common: Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; // to be improved: access here generalized QC{2} and QC{4} instead: Double_t dV2 = fIntFlow->GetBinContent(1); Double_t dV4 = fIntFlow->GetBinContent(2); // loop over pt or eta bins: for(Int_t b=1;b<=nBinsPtEta[pe];b++) { // generalized QC{2'}: Double_t gQC2Prime = fDiffFlowCumulants[t][pe][0]->GetBinContent(b); // v'{2}: if(dV2>0) { Double_t v2Prime = gQC2Prime/dV2; fDiffFlow[t][pe][0]->SetBinContent(b,v2Prime); } // generalized QC{4'}: Double_t gQC4Prime = fDiffFlowCumulants[t][pe][1]->GetBinContent(b); // v'{4}: if(dV4>0) { Double_t v4Prime = -gQC4Prime/pow(dV4,3.); fDiffFlow[t][pe][1]->SetBinContent(b,v4Prime); } } // end of for(Int_t b=1;b<=fnBinsPtEta[pe];b++) } // end of void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrectedForNUA(TString type, TString ptOrEta); //================================================================================================================================== void AliFlowAnalysisWithQCumulants::EvaluateIntFlowCorrelationsWithNestedLoops(AliFlowEventSimple * const anEvent) { // Evaluate with nested loops multiparticle correlations for integrated flow (without using the particle weights). // Remark: Results are stored in profile fIntFlowDirectCorrelations whose binning is organized as follows: // // 1st bin: <2>_{1n|1n} = two1n1n = cos(n*(phi1-phi2))> // 2nd bin: <2>_{2n|2n} = two2n2n = cos(2n*(phi1-phi2))> // 3rd bin: <2>_{3n|3n} = two3n3n = cos(3n*(phi1-phi2))> // 4th bin: <2>_{4n|4n} = two4n4n = cos(4n*(phi1-phi2))> // 5th bin: ---- EMPTY ---- // 6th bin: <3>_{2n|1n,1n} = three2n1n1n = // 7th bin: <3>_{3n|2n,1n} = three3n2n1n = // 8th bin: <3>_{4n|2n,2n} = three4n2n2n = // 9th bin: <3>_{4n|3n,1n} = three4n3n1n = // 10th bin: ---- EMPTY ---- // 11th bin: <4>_{1n,1n|1n,1n} = four1n1n1n1n = // 12th bin: <4>_{2n,1n|2n,1n} = four2n1n2n1n = // 13th bin: <4>_{2n,2n|2n,2n} = four2n2n2n2n = // 14th bin: <4>_{3n|1n,1n,1n} = four3n1n1n1n = // 15th bin: <4>_{3n,1n|3n,1n} = four3n1n3n1n = // 16th bin: <4>_{3n,1n|2n,2n} = four3n1n2n2n = // 17th bin: <4>_{4n|2n,1n,1n} = four4n2n1n1n = // 18th bin: ---- EMPTY ---- // 19th bin: <5>_{2n|1n,1n,1n,1n} = five2n1n1n1n1n = // 20th bin: <5>_{2n,2n|2n,1n,1n} = five2n2n2n1n1n = // 21st bin: <5>_{3n,1n|2n,1n,1n} = five3n1n2n1n1n = // 22nd bin: <5>_{4n|1n,1n,1n,1n} = five4n1n1n1n1n = // 23rd bin: ---- EMPTY ---- // 24th bin: <6>_{1n,1n,1n|1n,1n,1n} = six1n1n1n1n1n1n = // 25th bin: <6>_{2n,1n,1n|2n,1n,1n} = six2n1n1n2n1n1n = // 26th bin: <6>_{2n,2n|1n,1n,1n,1n} = six2n2n1n1n1n1n = // 27th bin: <6>_{3n,1n|1n,1n,1n,1n} = six3n1n1n1n1n1n = // 28th bin: ---- EMPTY ---- // 29th bin: <7>_{2n,1n,1n|1n,1n,1n,1n} = seven2n1n1n1n1n1n1n = // 30th bin: ---- EMPTY ---- // 31st bin: <8>_{1n,1n,1n,1n|1n,1n,1n,1n} = eight1n1n1n1n1n1n1n1n = Int_t nPrim = anEvent->NumberOfTracks(); AliFlowTrackSimple *aftsTrack = NULL; Double_t phi1=0., phi2=0., phi3=0., phi4=0., phi5=0., phi6=0., phi7=0., phi8=0.; Int_t n = fHarmonic; Int_t eventNo = (Int_t)fAvMultiplicity->GetBinEntries(1); // to be improved (is this casting safe in general?) Double_t dMult = (*fSMpk)(0,0); cout<fMaxAllowedMultiplicity) { cout<<"... skipping this event (multiplicity too high) ..."<=2 && nPrim<=fMaxAllowedMultiplicity) { for(Int_t i1=0;i1GetTrack(i1); if(!(aftsTrack->InRPSelection())) continue; phi1=aftsTrack->Phi(); for(Int_t i2=0;i2GetTrack(i2); if(!(aftsTrack->InRPSelection())) continue; phi2=aftsTrack->Phi(); if(nPrim==2) cout<Fill(0.5,cos(n*(phi1-phi2)),1.); // fIntFlowDirectCorrelations->Fill(1.5,cos(2.*n*(phi1-phi2)),1.); // fIntFlowDirectCorrelations->Fill(2.5,cos(3.*n*(phi1-phi2)),1.); // fIntFlowDirectCorrelations->Fill(3.5,cos(4.*n*(phi1-phi2)),1.); // } // end of for(Int_t i2=0;i2=2) // 3-particle correlations: if(nPrim>=3 && nPrim<=fMaxAllowedMultiplicity) { for(Int_t i1=0;i1GetTrack(i1); if(!(aftsTrack->InRPSelection())) continue; phi1=aftsTrack->Phi(); for(Int_t i2=0;i2GetTrack(i2); if(!(aftsTrack->InRPSelection())) continue; phi2=aftsTrack->Phi(); for(Int_t i3=0;i3GetTrack(i3); if(!(aftsTrack->InRPSelection())) continue; phi3=aftsTrack->Phi(); if(nPrim==3) cout<Fill(5.,cos(2.*n*phi1-n*(phi2+phi3)),1.); //<3>_{2n|nn,n} fIntFlowDirectCorrelations->Fill(6.,cos(3.*n*phi1-2.*n*phi2-n*phi3),1.); //<3>_{3n|2n,n} fIntFlowDirectCorrelations->Fill(7.,cos(4.*n*phi1-2.*n*phi2-2.*n*phi3),1.); //<3>_{4n|2n,2n} fIntFlowDirectCorrelations->Fill(8.,cos(4.*n*phi1-3.*n*phi2-n*phi3),1.); //<3>_{4n|3n,n} } // end of for(Int_t i3=0;i3=3) // 4-particle correlations: if(nPrim>=4 && nPrim<=fMaxAllowedMultiplicity) { for(Int_t i1=0;i1GetTrack(i1); if(!(aftsTrack->InRPSelection())) continue; phi1=aftsTrack->Phi(); for(Int_t i2=0;i2GetTrack(i2); if(!(aftsTrack->InRPSelection())) continue; phi2=aftsTrack->Phi(); for(Int_t i3=0;i3GetTrack(i3); if(!(aftsTrack->InRPSelection())) continue; phi3=aftsTrack->Phi(); for(Int_t i4=0;i4GetTrack(i4); if(!(aftsTrack->InRPSelection())) continue; phi4=aftsTrack->Phi(); if(nPrim==4) cout<Fill(10.,cos(n*phi1+n*phi2-n*phi3-n*phi4),1.); // <4>_{n,n|n,n} fIntFlowDirectCorrelations->Fill(11.,cos(2.*n*phi1+n*phi2-2.*n*phi3-n*phi4),1.); // <4>_{2n,n|2n,n} fIntFlowDirectCorrelations->Fill(12.,cos(2.*n*phi1+2*n*phi2-2.*n*phi3-2.*n*phi4),1.); // <4>_{2n,2n|2n,2n} fIntFlowDirectCorrelations->Fill(13.,cos(3.*n*phi1-n*phi2-n*phi3-n*phi4),1.); // <4>_{3n|n,n,n} fIntFlowDirectCorrelations->Fill(14.,cos(3.*n*phi1+n*phi2-3.*n*phi3-n*phi4),1.); // <4>_{3n,n|3n,n} fIntFlowDirectCorrelations->Fill(15.,cos(3.*n*phi1+n*phi2-2.*n*phi3-2.*n*phi4),1.); // <4>_{3n,n|2n,2n} fIntFlowDirectCorrelations->Fill(16.,cos(4.*n*phi1-2.*n*phi2-n*phi3-n*phi4),1.); // <4>_{4n|2n,n,n} } // end of for(Int_t i4=0;i4=) // 5-particle correlations: if(nPrim>=5 && nPrim<=fMaxAllowedMultiplicity) { for(Int_t i1=0;i1GetTrack(i1); if(!(aftsTrack->InRPSelection())) continue; phi1=aftsTrack->Phi(); for(Int_t i2=0;i2GetTrack(i2); if(!(aftsTrack->InRPSelection())) continue; phi2=aftsTrack->Phi(); for(Int_t i3=0;i3GetTrack(i3); if(!(aftsTrack->InRPSelection())) continue; phi3=aftsTrack->Phi(); for(Int_t i4=0;i4GetTrack(i4); if(!(aftsTrack->InRPSelection())) continue; phi4=aftsTrack->Phi(); for(Int_t i5=0;i5GetTrack(i5); if(!(aftsTrack->InRPSelection())) continue; phi5=aftsTrack->Phi(); if(nPrim==5) cout<Fill(18.,cos(2.*n*phi1+n*phi2-n*phi3-n*phi4-n*phi5),1.); //<5>_{2n,n|n,n,n} fIntFlowDirectCorrelations->Fill(19.,cos(2.*n*phi1+2.*n*phi2-2.*n*phi3-n*phi4-n*phi5),1.); //<5>_{2n,2n|2n,n,n} fIntFlowDirectCorrelations->Fill(20.,cos(3.*n*phi1+n*phi2-2.*n*phi3-n*phi4-n*phi5),1.); //<5>_{3n,n|2n,n,n} fIntFlowDirectCorrelations->Fill(21.,cos(4.*n*phi1-n*phi2-n*phi3-n*phi4-n*phi5),1.); //<5>_{4n|n,n,n,n} } // end of for(Int_t i5=0;i5=5) // 6-particle correlations: if(nPrim>=6 && nPrim<=fMaxAllowedMultiplicity) { for(Int_t i1=0;i1GetTrack(i1); if(!(aftsTrack->InRPSelection())) continue; phi1=aftsTrack->Phi(); for(Int_t i2=0;i2GetTrack(i2); if(!(aftsTrack->InRPSelection())) continue; phi2=aftsTrack->Phi(); for(Int_t i3=0;i3GetTrack(i3); if(!(aftsTrack->InRPSelection())) continue; phi3=aftsTrack->Phi(); for(Int_t i4=0;i4GetTrack(i4); if(!(aftsTrack->InRPSelection())) continue; phi4=aftsTrack->Phi(); for(Int_t i5=0;i5GetTrack(i5); if(!(aftsTrack->InRPSelection())) continue; phi5=aftsTrack->Phi(); for(Int_t i6=0;i6GetTrack(i6); if(!(aftsTrack->InRPSelection())) continue; phi6=aftsTrack->Phi(); if(nPrim==6) cout<Fill(23.,cos(n*phi1+n*phi2+n*phi3-n*phi4-n*phi5-n*phi6),1.); //<6>_{n,n,n|n,n,n} fIntFlowDirectCorrelations->Fill(24.,cos(2.*n*phi1+n*phi2+n*phi3-2.*n*phi4-n*phi5-n*phi6),1.); //<6>_{2n,n,n|2n,n,n} fIntFlowDirectCorrelations->Fill(25.,cos(2.*n*phi1+2.*n*phi2-n*phi3-n*phi4-n*phi5-n*phi6),1.); //<6>_{2n,2n|n,n,n,n} fIntFlowDirectCorrelations->Fill(26.,cos(3.*n*phi1+n*phi2-n*phi3-n*phi4-n*phi5-n*phi6),1.); //<6>_{3n,n|n,n,n,n} } // end of for(Int_t i6=0;i6=6) // 7-particle correlations: if(nPrim>=7 && nPrim<=fMaxAllowedMultiplicity) { for(Int_t i1=0;i1GetTrack(i1); if(!(aftsTrack->InRPSelection())) continue; phi1=aftsTrack->Phi(); for(Int_t i2=0;i2GetTrack(i2); if(!(aftsTrack->InRPSelection())) continue; phi2=aftsTrack->Phi(); for(Int_t i3=0;i3GetTrack(i3); if(!(aftsTrack->InRPSelection())) continue; phi3=aftsTrack->Phi(); for(Int_t i4=0;i4GetTrack(i4); if(!(aftsTrack->InRPSelection())) continue; phi4=aftsTrack->Phi(); for(Int_t i5=0;i5GetTrack(i5); if(!(aftsTrack->InRPSelection())) continue; phi5=aftsTrack->Phi(); for(Int_t i6=0;i6GetTrack(i6); if(!(aftsTrack->InRPSelection())) continue; phi6=aftsTrack->Phi(); for(Int_t i7=0;i7GetTrack(i7); if(!(aftsTrack->InRPSelection())) continue; phi7=aftsTrack->Phi(); if(nPrim==7) cout<Fill(28.,cos(2.*n*phi1+n*phi2+n*phi3-n*phi4-n*phi5-n*phi6-n*phi7),1.); // <7>_{2n,n,n|n,n,n,n} } // end of for(Int_t i7=0;i7=7) // 8-particle correlations: if(nPrim>=8 && nPrim<=fMaxAllowedMultiplicity) { for(Int_t i1=0;i1GetTrack(i1); if(!(aftsTrack->InRPSelection())) continue; phi1=aftsTrack->Phi(); for(Int_t i2=0;i2GetTrack(i2); if(!(aftsTrack->InRPSelection())) continue; phi2=aftsTrack->Phi(); for(Int_t i3=0;i3GetTrack(i3); if(!(aftsTrack->InRPSelection())) continue; phi3=aftsTrack->Phi(); for(Int_t i4=0;i4GetTrack(i4); if(!(aftsTrack->InRPSelection())) continue; phi4=aftsTrack->Phi(); for(Int_t i5=0;i5GetTrack(i5); if(!(aftsTrack->InRPSelection())) continue; phi5=aftsTrack->Phi(); for(Int_t i6=0;i6GetTrack(i6); if(!(aftsTrack->InRPSelection())) continue; phi6=aftsTrack->Phi(); for(Int_t i7=0;i7GetTrack(i7); if(!(aftsTrack->InRPSelection())) continue; phi7=aftsTrack->Phi(); for(Int_t i8=0;i8GetTrack(i8); if(!(aftsTrack->InRPSelection())) continue; phi8=aftsTrack->Phi(); cout<Fill(30.,cos(n*phi1+n*phi2+n*phi3+n*phi4-n*phi5-n*phi6-n*phi7-n*phi8),1.); // <8>_{n,n,n,n|n,n,n,n} } // end of for(Int_t i8=0;i8=8) cout<GetXaxis())->GetBinLabel(ci), "") == 0) continue; // to be improved (access finalized histogram here) cout<<(fIntFlowCorrelationsAllPro->GetXaxis())->GetBinLabel(ci)<<":"<GetXaxis())->GetBinLabel(ci), "") == 0) continue; // to be improved (access finalized histogram here) cout<<(fIntFlowCorrectionTermsForNUAPro[sc]->GetXaxis())->GetBinLabel(ci)<<":"<fMaxAllowedMultiplicity) { cout<<"... skipping this event (multiplicity too high) ..."<=2 && nPrim<=fMaxAllowedMultiplicity) { // 2 nested loops multiparticle correlations using particle weights: for(Int_t i1=0;i1GetTrack(i1); if(!(aftsTrack->InRPSelection())) continue; phi1=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi1 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi1*fnBinsPhi/TMath::TwoPi()))); for(Int_t i2=0;i2GetTrack(i2); if(!(aftsTrack->InRPSelection())) continue; phi2=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi2 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi2*fnBinsPhi/TMath::TwoPi()))); if(nPrim==2) cout<Fill(0.5,cos(n*(phi1-phi2)),wPhi1*wPhi2); // if(fUsePhiWeights) fIntFlowDirectCorrelations->Fill(1.5,cos(2.*n*(phi1-phi2)),pow(wPhi1,2)*pow(wPhi2,2)); // if(fUsePhiWeights) fIntFlowDirectCorrelations->Fill(2.5,cos(3.*n*(phi1-phi2)),pow(wPhi1,3)*pow(wPhi2,3)); // if(fUsePhiWeights) fIntFlowDirectCorrelations->Fill(3.5,cos(4.*n*(phi1-phi2)),pow(wPhi1,4)*pow(wPhi2,4)); // // extra correlations: // 2-p extra correlations (do not appear if particle weights are not used): if(fUsePhiWeights) fIntFlowExtraDirectCorrelations->Fill(0.5,cos(n*(phi1-phi2)),pow(wPhi1,3)*wPhi2); // // ... } // end of for(Int_t i2=0;i2=2) if(nPrim>=3 && nPrim<=fMaxAllowedMultiplicity) { // 3 nested loops multiparticle correlations using particle weights: for(Int_t i1=0;i1GetTrack(i1); if(!(aftsTrack->InRPSelection())) continue; phi1=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi1 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi1*fnBinsPhi/TMath::TwoPi()))); for(Int_t i2=0;i2GetTrack(i2); if(!(aftsTrack->InRPSelection())) continue; phi2=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi2 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi2*fnBinsPhi/TMath::TwoPi()))); for(Int_t i3=0;i3GetTrack(i3); if(!(aftsTrack->InRPSelection())) continue; phi3=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi3 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi3*fnBinsPhi/TMath::TwoPi()))); if(nPrim==3) cout<Fill(5.5,cos(2.*n*phi1-n*(phi2+phi3)),pow(wPhi1,2)*wPhi2*wPhi3); // // ... // extra correlations: // 2-p extra correlations (do not appear if particle weights are not used): if(fUsePhiWeights) fIntFlowExtraDirectCorrelations->Fill(1.5,cos(n*(phi1-phi2)),wPhi1*wPhi2*pow(wPhi3,2)); // // ... // 3-p extra correlations (do not appear if particle weights are not used): // ... } // end of for(Int_t i3=0;i3=3) if(nPrim>=4 && nPrim<=fMaxAllowedMultiplicity) { // 4 nested loops multiparticle correlations using particle weights: for(Int_t i1=0;i1GetTrack(i1); if(!(aftsTrack->InRPSelection())) continue; phi1=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi1 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi1*fnBinsPhi/TMath::TwoPi()))); for(Int_t i2=0;i2GetTrack(i2); if(!(aftsTrack->InRPSelection())) continue; phi2=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi2 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi2*fnBinsPhi/TMath::TwoPi()))); for(Int_t i3=0;i3GetTrack(i3); if(!(aftsTrack->InRPSelection())) continue; phi3=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi3 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi3*fnBinsPhi/TMath::TwoPi()))); for(Int_t i4=0;i4GetTrack(i4); if(!(aftsTrack->InRPSelection())) continue; phi4=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi4 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi4*fnBinsPhi/TMath::TwoPi()))); if(nPrim>=4) cout<Fill(10.5,cos(n*phi1+n*phi2-n*phi3-n*phi4),wPhi1*wPhi2*wPhi3*wPhi4); // extra correlations: // 2-p extra correlations (do not appear if particle weights are not used): // ... // 3-p extra correlations (do not appear if particle weights are not used): // ... // 4-p extra correlations (do not appear if particle weights are not used): // ... } // end of for(Int_t i4=0;i4=4) cout<GetXaxis())->GetBinLabel(eci), "") == 0) continue; cout<<(fIntFlowExtraCorrelationsPro->GetXaxis())->GetBinLabel(eci)<<":"<fMaxAllowedMultiplicity) { cout<<"... skipping this event (multiplicity too high) ..."<=1 && nPrim<=fMaxAllowedMultiplicity) { // 1-particle correction terms for non-uniform acceptance: for(Int_t i1=0;i1GetTrack(i1); if(!(aftsTrack->InRPSelection())) continue; phi1=aftsTrack->Phi(); if(nPrim==1) cout<Fill(0.5,sin(n*phi1),1.); // // cos terms: fIntFlowDirectCorrectionTermsForNUA[1]->Fill(0.5,cos(n*phi1),1.); // } // end of for(Int_t i1=0;i1=1) if(nPrim>=2 && nPrim<=fMaxAllowedMultiplicity) { // 2-particle correction terms for non-uniform acceptance: for(Int_t i1=0;i1GetTrack(i1); if(!(aftsTrack->InRPSelection())) continue; phi1=aftsTrack->Phi(); for(Int_t i2=0;i2GetTrack(i2); if(!(aftsTrack->InRPSelection())) continue; phi2=aftsTrack->Phi(); if(nPrim==2) cout<Fill(1.5,sin(n*(phi1+phi2)),1.); // <> fIntFlowDirectCorrectionTermsForNUA[0]->Fill(3.5,sin(n*(2*phi1-phi2)),1.); // <> // cos terms: fIntFlowDirectCorrectionTermsForNUA[1]->Fill(1.5,cos(n*(phi1+phi2)),1.); // <> fIntFlowDirectCorrectionTermsForNUA[1]->Fill(3.5,cos(n*(2*phi1-phi2)),1.); // <> } // end of for(Int_t i2=0;i2=2) if(nPrim>=3 && nPrim<=fMaxAllowedMultiplicity) { // 3-particle correction terms for non-uniform acceptance: for(Int_t i1=0;i1GetTrack(i1); if(!(aftsTrack->InRPSelection())) continue; phi1=aftsTrack->Phi(); for(Int_t i2=0;i2GetTrack(i2); if(!(aftsTrack->InRPSelection())) continue; phi2=aftsTrack->Phi(); for(Int_t i3=0;i3GetTrack(i3); if(!(aftsTrack->InRPSelection())) continue; phi3=aftsTrack->Phi(); if(nPrim>=3) cout<Fill(2.5,sin(n*(phi1-phi2-phi3)),1.); // <> // cos terms: fIntFlowDirectCorrectionTermsForNUA[1]->Fill(2.5,cos(n*(phi1-phi2-phi3)),1.); // <> } // end of for(Int_t i3=0;i3=3) cout<,1=<4'>,2=<6'>,3=<8'>] // Remark 3: <2'> = // <4'> = // ... Int_t typeFlag = -1; Int_t ptEtaFlag = -1; if(type == "RP") { typeFlag = 0; } else if(type == "POI") { typeFlag = 1; } if(ptOrEta == "Pt") { ptEtaFlag = 0; } else if(ptOrEta == "Eta") { ptEtaFlag = 1; } // shortcuts: Int_t t = typeFlag; Int_t pe = ptEtaFlag; Double_t lowerPtEtaEdge[2] = {fPtMin+(fCrossCheckInPtBinNo-1)*fPtBinWidth,fEtaMin+(fCrossCheckInEtaBinNo-1)*fEtaBinWidth}; Double_t upperPtEtaEdge[2] = {fPtMin+fCrossCheckInPtBinNo*fPtBinWidth,fEtaMin+fCrossCheckInEtaBinNo*fEtaBinWidth}; Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; Int_t nPrim = anEvent->NumberOfTracks(); AliFlowTrackSimple *aftsTrack = NULL; Double_t psi1=0., phi2=0., phi3=0., phi4=0.;// phi5=0., phi6=0., phi7=0., phi8=0.; Int_t n = fHarmonic; // 2'-particle correlations: for(Int_t i1=0;i1GetTrack(i1); // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) if(typeFlag==1) // this is diff flow of POIs { if(ptOrEta == "Pt") { if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()InPOISelection())))continue; } else if (ptOrEta == "Eta") { if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()InPOISelection())))continue; } } else // this is diff flow of RPs { if(ptOrEta == "Pt") { if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()InRPSelection())))continue; } else if (ptOrEta == "Eta") { if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()InRPSelection())))continue; } } psi1=aftsTrack->Phi(); for(Int_t i2=0;i2GetTrack(i2); // RP condition (!(first) particle in the correlator must be RP): if(!(aftsTrack->InRPSelection()))continue; phi2=aftsTrack->Phi(); // 2'-particle correlations: fDiffFlowDirectCorrelations[t][pe][0]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(1.*n*(psi1-phi2)),1.); // GetTrack(i1); // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) if(ptOrEta == "Pt") { if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()InPOISelection())))continue; } else if (ptOrEta == "Eta") { if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()InPOISelection())))continue; } psi1=aftsTrack->Phi(); for(Int_t i2=0;i2GetTrack(i2); // RP condition (!(first) particle in the correlator must be RP): if(!(aftsTrack->InRPSelection())) continue; phi2=aftsTrack->Phi(); for(Int_t i3=0;i3GetTrack(i3); // RP condition (!(first) particle in the correlator must be RP): if(!(aftsTrack->InRPSelection())) continue; phi3=aftsTrack->Phi(); // to be improved : where to store it? ->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(n*(2.*phi1-phi2-phi3)),1.); // }//end of for(Int_t i3=0;i3GetTrack(i1); // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) if(typeFlag==1) // this is diff flow of POIs { if(ptOrEta == "Pt") { if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()InPOISelection())))continue; } else if (ptOrEta == "Eta") { if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()InPOISelection())))continue; } } else // this is diff flow of RPs { if(ptOrEta == "Pt") { if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()InRPSelection())))continue; } else if (ptOrEta == "Eta") { if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()InRPSelection())))continue; } } psi1=aftsTrack->Phi(); for(Int_t i2=0;i2GetTrack(i2); // RP condition (!(first) particle in the correlator must be RP): if(!(aftsTrack->InRPSelection())) continue; phi2=aftsTrack->Phi(); for(Int_t i3=0;i3GetTrack(i3); // RP condition (!(first) particle in the correlator must be RP): if(!(aftsTrack->InRPSelection())) continue; phi3=aftsTrack->Phi(); for(Int_t i4=0;i4GetTrack(i4); // RP condition (!(first) particle in the correlator must be RP): if(!(aftsTrack->InRPSelection())) continue; phi4=aftsTrack->Phi(); // 4'-particle correlations: fDiffFlowDirectCorrelations[t][pe][1]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(n*(psi1+phi2-phi3-phi4)),1.); // }//end of for(Int_t i4=0;i4GetTrack(i); // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) if(typeFlag==1) // this is diff flow of POIs { if(ptOrEta == "Pt") { if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()InPOISelection())))continue; } else if (ptOrEta == "Eta") { if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()InPOISelection())))continue; } } else // this is diff flow of RPs { if(ptOrEta == "Pt") { if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()InRPSelection())))continue; } else if (ptOrEta == "Eta") { if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()InRPSelection())))continue; } } if(t==1)t++; fNoOfParticlesInBin->Fill(t+pe+0.5); } } // end of void AliFlowAnalysisWithQCumulants::EvaluateDiffFlowCorrelationsWithNestedLoops(AliFlowEventSimple* anEvent, TString type, TString ptOrEta) //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CrossCheckDiffFlowCorrelations(TString type, TString ptOrEta) { // Compare correlations needed for diff. flow calculated with nested loops and those calculated from Q-vectors Int_t typeFlag = -1; Int_t ptEtaFlag = -1; if(type == "RP") { typeFlag = 0; } else if(type == "POI") { typeFlag = 1; } if(ptOrEta == "Pt") { ptEtaFlag = 0; } else if(ptOrEta == "Eta") { ptEtaFlag = 1; } // shortcuts: Int_t t = typeFlag; Int_t pe = ptEtaFlag; TString rpORpoiString[2] = {"RP ","POI"}; // to be improved (name in the same way as in the other methods, eventually promote to data member) TString ptORetaString[2] = {"pt","eta"}; // to be improved (name in the same way as in the other methods, eventually promote to data member) TString reducedCorrelations[4] = {"<>","<>","",""}; // to be improved (access this from pro or hist) Double_t lowerPtEtaEdge[2] = {fPtMin+(fCrossCheckInPtBinNo-1)*fPtBinWidth,fEtaMin+(fCrossCheckInEtaBinNo-1)*fEtaBinWidth}; Double_t upperPtEtaEdge[2] = {fPtMin+fCrossCheckInPtBinNo*fPtBinWidth,fEtaMin+fCrossCheckInEtaBinNo*fEtaBinWidth}; Int_t crossCheckInPtEtaBinNo[2] = {fCrossCheckInPtBinNo,fCrossCheckInEtaBinNo}; cout<NumberOfTracks(); AliFlowTrackSimple *aftsTrack = NULL; Double_t psi1=0., phi2=0., phi3=0., phi4=0.;// phi5=0., phi6=0., phi7=0., phi8=0.; Double_t wPhi2=1., wPhi3=1., wPhi4=1.;// wPhi5=1., wPhi6=1., wPhi7=1., wPhi8=1.; Int_t n = fHarmonic; // 2'-particle correlations: for(Int_t i1=0;i1GetTrack(i1); // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) if(typeFlag==1) // this is diff flow of POIs { if(ptOrEta == "Pt") { if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()InPOISelection())))continue; } else if (ptOrEta == "Eta") { if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()InPOISelection())))continue; } } else // this is diff flow of RPs { if(ptOrEta == "Pt") { if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()InRPSelection())))continue; } else if (ptOrEta == "Eta") { if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()InRPSelection())))continue; } } psi1=aftsTrack->Phi(); for(Int_t i2=0;i2GetTrack(i2); // RP condition (!(first) particle in the correlator must be RP): if(!(aftsTrack->InRPSelection())) continue; phi2=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi2 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi2*fnBinsPhi/TMath::TwoPi()))); // 2'-particle correlations: fDiffFlowDirectCorrelations[t][pe][0]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(1.*n*(psi1-phi2)),wPhi2); // GetTrack(i1); // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) if(typeFlag==1) // this is diff flow of POIs { if(ptOrEta == "Pt") { if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()InPOISelection())))continue; } else if (ptOrEta == "Eta") { if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()InPOISelection())))continue; } } else // this is diff flow of RPs { if(ptOrEta == "Pt") { if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()InRPSelection())))continue; } else if (ptOrEta == "Eta") { if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()InRPSelection())))continue; } } psi1=aftsTrack->Phi(); for(Int_t i2=0;i2GetTrack(i2); // RP condition (!(first) particle in the correlator must be RP): if(!(aftsTrack->InRPSelection())) continue; phi2=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi2 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi2*fnBinsPhi/TMath::TwoPi()))); for(Int_t i3=0;i3GetTrack(i3); // RP condition (!(first) particle in the correlator must be RP): if(!(aftsTrack->InRPSelection())) continue; phi3=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi3 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi3*fnBinsPhi/TMath::TwoPi()))); for(Int_t i4=0;i4GetTrack(i4); // RP condition (!(first) particle in the correlator must be RP): if(!(aftsTrack->InRPSelection())) continue; phi4=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi4 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi4*fnBinsPhi/TMath::TwoPi()))); // 4'-particle correlations : fDiffFlowDirectCorrelations[t][pe][1]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(n*(psi1+phi2-phi3-phi4)),wPhi2*wPhi3*wPhi4); }//end of for(Int_t i4=0;i4GetTrack(i); // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) if(typeFlag==1) // this is diff flow of POIs { if(ptOrEta == "Pt") { if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()InPOISelection())))continue; } else if (ptOrEta == "Eta") { if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()InPOISelection())))continue; } } else // this is diff flow of RPs { if(ptOrEta == "Pt") { if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()InRPSelection())))continue; } else if (ptOrEta == "Eta") { if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()InRPSelection())))continue; } } if(t==1)t++; fNoOfParticlesInBin->Fill(t+pe+0.5); } } // end of void AliFlowAnalysisWithQCumulants::EvaluateDiffFlowCorrelationsWithNestedLoopsUsingParticleWeights(AliFlowEventSimple* anEvent, TString type, TString ptOrEta) //================================================================================================================================ void AliFlowAnalysisWithQCumulants::EvaluateDiffFlowCorrectionTermsForNUAWithNestedLoops(AliFlowEventSimple * const anEvent, TString type, TString ptOrEta) { // Evaluate with nested loops correction terms for non-uniform acceptance (both sin and cos terms) relevant for differential flow. // Remark 1: Reduced correction terms for non-uniform acceptance are evaluated in pt bin number fCrossCheckInPtBinNo // and eta bin number fCrossCheckInEtaBinNo both for RPs and POIs. // Remark 2: Results are stored in 1 bin profiles fDiffFlowDirectCorrections[t][pe][sc][cti], where first three indices runs as: // [0=RP,1=POI][0=Pt,1=Eta][0=sin terms,1=cos terms], whilst the cti (correction term index) runs as follows: // cti: // 0: <> // 1: <> // 2: <> // 3: <> // 4: // 5: // 6: Int_t typeFlag = -1; Int_t ptEtaFlag = -1; if(type == "RP") { typeFlag = 0; } else if(type == "POI") { typeFlag = 1; } if(ptOrEta == "Pt") { ptEtaFlag = 0; } else if(ptOrEta == "Eta") { ptEtaFlag = 1; } // shortcuts: Int_t t = typeFlag; Int_t pe = ptEtaFlag; Double_t lowerPtEtaEdge[2] = {fPtMin+(fCrossCheckInPtBinNo-1)*fPtBinWidth,fEtaMin+(fCrossCheckInEtaBinNo-1)*fEtaBinWidth}; Double_t upperPtEtaEdge[2] = {fPtMin+fCrossCheckInPtBinNo*fPtBinWidth,fEtaMin+fCrossCheckInEtaBinNo*fEtaBinWidth}; Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; Int_t nPrim = anEvent->NumberOfTracks(); AliFlowTrackSimple *aftsTrack = NULL; Double_t psi1=0., phi2=0., phi3=0.;// phi4=0.;// phi5=0., phi6=0., phi7=0., phi8=0.; Int_t n = fHarmonic; // 1-particle correction terms: for(Int_t i1=0;i1GetTrack(i1); // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) if(typeFlag==1) // this is diff flow of POIs { if(ptOrEta == "Pt") { if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()InPOISelection())))continue; } else if (ptOrEta == "Eta") { if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()InPOISelection())))continue; } } else // this is diff flow of RPs { if(ptOrEta == "Pt") { if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()InRPSelection())))continue; } else if (ptOrEta == "Eta") { if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()InRPSelection())))continue; } } psi1=aftsTrack->Phi(); // sin terms: fDiffFlowDirectCorrectionTermsForNUA[t][pe][0][0]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,sin(n*psi1),1.); // <> // cos terms: fDiffFlowDirectCorrectionTermsForNUA[t][pe][1][0]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(n*psi1),1.); // <> }//end of for(Int_t i1=0;i1GetTrack(i1); // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) if(typeFlag==1) // this is diff flow of POIs { if(ptOrEta == "Pt") { if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()InPOISelection())))continue; } else if (ptOrEta == "Eta") { if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()InPOISelection())))continue; } } else // this is diff flow of RPs { if(ptOrEta == "Pt") { if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()InRPSelection())))continue; } else if (ptOrEta == "Eta") { if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()InRPSelection())))continue; } } psi1=aftsTrack->Phi(); for(Int_t i2=0;i2GetTrack(i2); // RP condition (!(first) particle in the correlator must be RP): if(!(aftsTrack->InRPSelection())) continue; phi2=aftsTrack->Phi(); // sin terms: fDiffFlowDirectCorrectionTermsForNUA[t][pe][0][1]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,sin(n*(psi1+phi2)),1.); // <> // cos terms: fDiffFlowDirectCorrectionTermsForNUA[t][pe][1][1]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(n*(psi1+phi2)),1.); // <> }//end of for(Int_t i2=0;i2GetTrack(i1); // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) if(typeFlag==1) // this is diff flow of POIs { if(ptOrEta == "Pt") { if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()InPOISelection())))continue; } else if (ptOrEta == "Eta") { if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()InPOISelection())))continue; } } else // this is diff flow of RPs { if(ptOrEta == "Pt") { if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()InRPSelection())))continue; } else if (ptOrEta == "Eta") { if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()InRPSelection())))continue; } } psi1=aftsTrack->Phi(); for(Int_t i2=0;i2GetTrack(i2); // RP condition (!(first) particle in the correlator must be RP): if(!(aftsTrack->InRPSelection())) continue; phi2=aftsTrack->Phi(); for(Int_t i3=0;i3GetTrack(i3); // RP condition (!(first) particle in the correlator must be RP): if(!(aftsTrack->InRPSelection())) continue; phi3=aftsTrack->Phi(); // sin terms: fDiffFlowDirectCorrectionTermsForNUA[t][pe][0][2]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,sin(n*(psi1+phi2-phi3)),1.); // <> fDiffFlowDirectCorrectionTermsForNUA[t][pe][0][3]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,sin(n*(psi1-phi2-phi3)),1.); // <> // cos terms: fDiffFlowDirectCorrectionTermsForNUA[t][pe][1][2]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(n*(psi1+phi2-phi3)),1.); // <> fDiffFlowDirectCorrectionTermsForNUA[t][pe][1][3]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(n*(psi1-phi2-phi3)),1.); // <> }//end of for(Int_t i3=0;i3>","<>","<>","<>"}; // to be improved (access this from pro or hist) TString reducedCorrectionCosTerms[4] = {"<>","<>","<>","<>"}; // to be improved (access this from pro or hist) Double_t lowerPtEtaEdge[2] = {fPtMin+(fCrossCheckInPtBinNo-1)*fPtBinWidth,fEtaMin+(fCrossCheckInEtaBinNo-1)*fEtaBinWidth}; Double_t upperPtEtaEdge[2] = {fPtMin+fCrossCheckInPtBinNo*fPtBinWidth,fEtaMin+fCrossCheckInEtaBinNo*fEtaBinWidth}; Int_t crossCheckInPtEtaBinNo[2] = {fCrossCheckInPtBinNo,fCrossCheckInEtaBinNo}; cout<fMaxAllowedMultiplicity) { cout<<"... skipping this event (multiplicity too high) ..."<=1 && nPrim<=fMaxAllowedMultiplicity) { for(Int_t i1=0;i1GetTrack(i1); if(!(aftsTrack->InRPSelection())) continue; phi1=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi1 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi1*fnBinsPhi/TMath::TwoPi()))); // 1-particle correction terms using particle weights: if(fUsePhiWeights) fIntFlowDirectCorrectionTermsForNUA[0]->Fill(0.5,sin(n*phi1),wPhi1); // if(fUsePhiWeights) fIntFlowDirectCorrectionTermsForNUA[1]->Fill(0.5,cos(n*phi1),wPhi1); // } // end of for(Int_t i1=0;i1=1 && nPrim<=fMaxAllowedMultiplicity) // 2-particle correction terms using particle weights: if(nPrim>=2 && nPrim<=fMaxAllowedMultiplicity) { for(Int_t i1=0;i1GetTrack(i1); if(!(aftsTrack->InRPSelection())) continue; phi1=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi1 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi1*fnBinsPhi/TMath::TwoPi()))); for(Int_t i2=0;i2GetTrack(i2); if(!(aftsTrack->InRPSelection())) continue; phi2=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi2 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi2*fnBinsPhi/TMath::TwoPi()))); if(nPrim==2) cout<Fill(1.5,sin(n*(phi1+phi2)),wPhi1*wPhi2); // if(fUsePhiWeights) fIntFlowDirectCorrectionTermsForNUA[1]->Fill(1.5,cos(n*(phi1+phi2)),wPhi1*wPhi2); // } // end of for(Int_t i2=0;i2=2) // 3-particle correction terms using particle weights: if(nPrim>=3 && nPrim<=fMaxAllowedMultiplicity) { for(Int_t i1=0;i1GetTrack(i1); if(!(aftsTrack->InRPSelection())) continue; phi1=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi1 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi1*fnBinsPhi/TMath::TwoPi()))); for(Int_t i2=0;i2GetTrack(i2); if(!(aftsTrack->InRPSelection())) continue; phi2=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi2 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi2*fnBinsPhi/TMath::TwoPi()))); for(Int_t i3=0;i3GetTrack(i3); if(!(aftsTrack->InRPSelection())) continue; phi3=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi3 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi3*fnBinsPhi/TMath::TwoPi()))); if(nPrim==3) cout<Fill(2.5,sin(n*(phi1-phi2-phi3)),wPhi1*wPhi2*wPhi3); // if(fUsePhiWeights) fIntFlowDirectCorrectionTermsForNUA[1]->Fill(2.5,cos(n*(phi1-phi2-phi3)),wPhi1*wPhi2*wPhi3); // } // end of for(Int_t i3=0;i3=3) /* if(nPrim>=4 && nPrim<=fMaxAllowedMultiplicity) { // 4 nested loops multiparticle correlations using particle weights: for(Int_t i1=0;i1GetTrack(i1); if(!(aftsTrack->InRPSelection())) continue; phi1=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi1 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi1*fnBinsPhi/TMath::TwoPi()))); for(Int_t i2=0;i2GetTrack(i2); if(!(aftsTrack->InRPSelection())) continue; phi2=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi2 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi2*fnBinsPhi/TMath::TwoPi()))); for(Int_t i3=0;i3GetTrack(i3); if(!(aftsTrack->InRPSelection())) continue; phi3=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi3 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi3*fnBinsPhi/TMath::TwoPi()))); for(Int_t i4=0;i4GetTrack(i4); if(!(aftsTrack->InRPSelection())) continue; phi4=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi4 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi4*fnBinsPhi/TMath::TwoPi()))); if(nPrim>=4) cout<Fill(10.5,cos(n*phi1+n*phi2-n*phi3-n*phi4),wPhi1*wPhi2*wPhi3*wPhi4); // extra correlations: // 2-p extra correlations (do not appear if particle weights are not used): // ... // 3-p extra correlations (do not appear if particle weights are not used): // ... // 4-p extra correlations (do not appear if particle weights are not used): // ... } // end of for(Int_t i4=0;i4=4) */ cout<> // 1: <> // 2: <> // 3: <> // 4: // 5: // 6: // real and imaginary parts of weighted Q-vectors evaluated in harmonics n, 2n, 3n and 4n: Double_t dReQ1n1k = (*fReQ)(0,1); Double_t dReQ2n2k = (*fReQ)(1,2); //Double_t dReQ1n3k = (*fReQ)(0,3); //Double_t dReQ4n4k = (*fReQ)(3,4); Double_t dImQ1n1k = (*fImQ)(0,1); Double_t dImQ2n2k = (*fImQ)(1,2); //Double_t dImQ1n3k = (*fImQ)(0,3); //Double_t dImQ4n4k = (*fImQ)(3,4); // S^M_{p,k} (see .h file for the definition of fSMpk): Double_t dSM1p1k = (*fSMpk)(0,1); Double_t dSM1p2k = (*fSMpk)(0,2); Double_t dSM2p1k = (*fSMpk)(1,1); Int_t t = -1; // type flag Int_t pe = -1; // ptEta flag if(type == "RP") { t = 0; } else if(type == "POI") { t = 1; } if(ptOrEta == "Pt") { pe = 0; } else if(ptOrEta == "Eta") { pe = 1; } Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; Double_t minPtEta[2] = {fPtMin,fEtaMin}; //Double_t maxPtEta[2] = {fPtMax,fEtaMax}; Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; // looping over all bins and calculating correction terms: for(Int_t b=1;b<=nBinsPtEta[pe];b++) { // real and imaginary parts of p_{m*n,0} (non-weighted Q-vector evaluated for POIs in particular pt or eta bin): Double_t p1n0kRe = 0.; Double_t p1n0kIm = 0.; // number of POIs in particular pt or eta bin: Double_t mp = 0.; // real and imaginary parts of q_{m*n,0} (weighted Q-vector evaluated for particles which are both RPs and POIs in particular pt or eta bin): Double_t q1n2kRe = 0.; Double_t q1n2kIm = 0.; Double_t q2n1kRe = 0.; Double_t q2n1kIm = 0.; // s_{1,1}, s_{1,2} // to be improved (add explanation) Double_t s1p1k = 0.; Double_t s1p2k = 0.; // number of particles which are both RPs and POIs in particular pt or eta bin: Double_t mq = 0.; // M0111 from Eq. (118) in QC2c (to be improved (notation)) Double_t dM01 = 0.; Double_t dM011 = 0.; if(type == "POI") { // q_{m*n,k}: q1n2kRe = fReRPQ1dEBE[2][pe][0][2]->GetBinContent(fReRPQ1dEBE[2][pe][0][2]->GetBin(b)) * fReRPQ1dEBE[2][pe][0][2]->GetBinEntries(fReRPQ1dEBE[2][pe][0][2]->GetBin(b)); q1n2kIm = fImRPQ1dEBE[2][pe][0][2]->GetBinContent(fImRPQ1dEBE[2][pe][0][2]->GetBin(b)) * fImRPQ1dEBE[2][pe][0][2]->GetBinEntries(fImRPQ1dEBE[2][pe][0][2]->GetBin(b)); q2n1kRe = fReRPQ1dEBE[2][pe][1][1]->GetBinContent(fReRPQ1dEBE[2][pe][1][1]->GetBin(b)) * fReRPQ1dEBE[2][pe][1][1]->GetBinEntries(fReRPQ1dEBE[2][pe][1][1]->GetBin(b)); q2n1kIm = fImRPQ1dEBE[2][pe][1][1]->GetBinContent(fImRPQ1dEBE[2][pe][1][1]->GetBin(b)) * fImRPQ1dEBE[2][pe][1][1]->GetBinEntries(fImRPQ1dEBE[2][pe][1][1]->GetBin(b)); mq = fReRPQ1dEBE[2][pe][1][1]->GetBinEntries(fReRPQ1dEBE[2][pe][1][1]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) s1p1k = pow(fs1dEBE[2][pe][1]->GetBinContent(b)*fs1dEBE[2][pe][1]->GetBinEntries(b),1.); s1p2k = pow(fs1dEBE[2][pe][2]->GetBinContent(b)*fs1dEBE[2][pe][2]->GetBinEntries(b),1.); }else if(type == "RP") { // q_{m*n,k}: (Remark: m=1 is 0, k=0 iz zero (to be improved!)) q1n2kRe = fReRPQ1dEBE[0][pe][0][2]->GetBinContent(fReRPQ1dEBE[0][pe][0][2]->GetBin(b)) * fReRPQ1dEBE[0][pe][0][2]->GetBinEntries(fReRPQ1dEBE[0][pe][0][2]->GetBin(b)); q1n2kIm = fImRPQ1dEBE[0][pe][0][2]->GetBinContent(fImRPQ1dEBE[0][pe][0][2]->GetBin(b)) * fImRPQ1dEBE[0][pe][0][2]->GetBinEntries(fImRPQ1dEBE[0][pe][0][2]->GetBin(b)); q2n1kRe = fReRPQ1dEBE[0][pe][1][1]->GetBinContent(fReRPQ1dEBE[0][pe][1][1]->GetBin(b)) * fReRPQ1dEBE[0][pe][1][1]->GetBinEntries(fReRPQ1dEBE[0][pe][1][1]->GetBin(b)); q2n1kIm = fImRPQ1dEBE[0][pe][1][1]->GetBinContent(fImRPQ1dEBE[0][pe][1][1]->GetBin(b)) * fImRPQ1dEBE[0][pe][1][1]->GetBinEntries(fImRPQ1dEBE[0][pe][1][1]->GetBin(b)); // s_{1,1}, s_{1,2} and s_{1,3} // to be improved (add explanation) s1p1k = pow(fs1dEBE[0][pe][1]->GetBinContent(b)*fs1dEBE[0][pe][1]->GetBinEntries(b),1.); s1p2k = pow(fs1dEBE[0][pe][2]->GetBinContent(b)*fs1dEBE[0][pe][2]->GetBinEntries(b),1.); //s1p3k = pow(fs1dEBE[0][pe][3]->GetBinContent(b)*fs1dEBE[0][pe][3]->GetBinEntries(b),1.); mq = fReRPQ1dEBE[0][pe][1][1]->GetBinEntries(fReRPQ1dEBE[0][pe][1][1]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) } if(type == "POI") { // p_{m*n,k}: p1n0kRe = fReRPQ1dEBE[1][pe][0][0]->GetBinContent(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)) * fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)); p1n0kIm = fImRPQ1dEBE[1][pe][0][0]->GetBinContent(fImRPQ1dEBE[1][pe][0][0]->GetBin(b)) * fImRPQ1dEBE[1][pe][0][0]->GetBinEntries(fImRPQ1dEBE[1][pe][0][0]->GetBin(b)); mp = fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) // M01 from Eq. (118) in QC2c (to be improved (notation)): dM01 = mp*dSM1p1k-s1p1k; dM011 = mp*(dSM2p1k-dSM1p2k) - 2.*(s1p1k*dSM1p1k-s1p2k); // typeFlag = RP (0) or POI (1): t = 1; } else if(type == "RP") { // to be improved (cross-checked): p1n0kRe = fReRPQ1dEBE[0][pe][0][0]->GetBinContent(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)) * fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)); p1n0kIm = fImRPQ1dEBE[0][pe][0][0]->GetBinContent(fImRPQ1dEBE[0][pe][0][0]->GetBin(b)) * fImRPQ1dEBE[0][pe][0][0]->GetBinEntries(fImRPQ1dEBE[0][pe][0][0]->GetBin(b)); mp = fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) // M01 from Eq. (118) in QC2c (to be improved (notation)): dM01 = mp*dSM1p1k-s1p1k; dM011 = mp*(dSM2p1k-dSM1p2k) - 2.*(s1p1k*dSM1p1k-s1p2k); // typeFlag = RP (0) or POI (1): t = 0; } // <>: Double_t cosP1nPsi = 0.; if(mp) { cosP1nPsi = p1n0kRe/mp; // fill profile for <>: fDiffFlowCorrectionTermsForNUAPro[t][pe][1][0]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],cosP1nPsi,mp); // histogram to store e-b-e (needed in some other methods): fDiffFlowCorrectionTermsForNUAEBE[t][pe][1][0]->SetBinContent(b,cosP1nPsi); } // end of if(mp) // <>: Double_t cosP1nPsiP1nPhiW2 = 0.; if(dM01) { cosP1nPsiP1nPhiW2 = (p1n0kRe*dReQ1n1k-p1n0kIm*dImQ1n1k-q2n1kRe)/(dM01); // fill profile for <>: fDiffFlowCorrectionTermsForNUAPro[t][pe][1][1]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],cosP1nPsiP1nPhiW2,dM01); // histogram to store e-b-e (needed in some other methods): fDiffFlowCorrectionTermsForNUAEBE[t][pe][1][1]->SetBinContent(b,cosP1nPsiP1nPhiW2); } // end of if(dM01) // <>: Double_t cosP1nPsi1P1nPhi2MPhi3W2W3 = 0.; if(dM011) { cosP1nPsi1P1nPhi2MPhi3W2W3 = (p1n0kRe*(pow(dImQ1n1k,2.)+pow(dReQ1n1k,2.)) - p1n0kRe*dSM1p2k - q2n1kRe*dReQ1n1k-q2n1kIm*dImQ1n1k - s1p1k*dReQ1n1k + 2.*q1n2kRe) / dM011; // fill profile for <>: fDiffFlowCorrectionTermsForNUAPro[t][pe][1][2]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],cosP1nPsi1P1nPhi2MPhi3W2W3,dM011); // histogram to store e-b-e (needed in some other methods): fDiffFlowCorrectionTermsForNUAEBE[t][pe][1][2]->SetBinContent(b,cosP1nPsi1P1nPhi2MPhi3W2W3); } // end of if(dM011) // <>: Double_t cosP1nPsi1M1nPhi2MPhi3W2W3 = 0.; if(dM011) { cosP1nPsi1M1nPhi2MPhi3W2W3 = (p1n0kRe*(pow(dReQ1n1k,2.)-pow(dImQ1n1k,2.))+2.*p1n0kIm*dReQ1n1k*dImQ1n1k - 1.*(p1n0kRe*dReQ2n2k+p1n0kIm*dImQ2n2k) - 2.*s1p1k*dReQ1n1k + 2.*q1n2kRe) / dM011; // fill profile for <>: fDiffFlowCorrectionTermsForNUAPro[t][pe][1][3]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],cosP1nPsi1M1nPhi2MPhi3W2W3,dM011); // histogram to store e-b-e (needed in some other methods): fDiffFlowCorrectionTermsForNUAEBE[t][pe][1][3]->SetBinContent(b,cosP1nPsi1M1nPhi2MPhi3W2W3); } // end of if(dM011) } // end of for(Int_t b=1;b<=nBinsPtEta[pe];b++) } // end of AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrectionsForNUACosTermsUsingParticleWeights(TString type, TString ptOrEta) //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrectionsForNUASinTermsUsingParticleWeights(TString type, TString ptOrEta) { // Calculate correction terms for non-uniform acceptance for differential flow (sin terms). // Results are stored in fDiffFlowCorrectionTermsForNUAPro[t][pe][0][cti], where cti runs as follows: // 0: <> // 1: <> // 2: <> // 3: <>: // 4: // 5: // 6: // real and imaginary parts of weighted Q-vectors evaluated in harmonics n, 2n, 3n and 4n: Double_t dReQ1n1k = (*fReQ)(0,1); Double_t dReQ2n2k = (*fReQ)(1,2); //Double_t dReQ1n3k = (*fReQ)(0,3); //Double_t dReQ4n4k = (*fReQ)(3,4); Double_t dImQ1n1k = (*fImQ)(0,1); Double_t dImQ2n2k = (*fImQ)(1,2); //Double_t dImQ1n3k = (*fImQ)(0,3); //Double_t dImQ4n4k = (*fImQ)(3,4); // S^M_{p,k} (see .h file for the definition of fSMpk): Double_t dSM1p1k = (*fSMpk)(0,1); Double_t dSM1p2k = (*fSMpk)(0,2); Double_t dSM2p1k = (*fSMpk)(1,1); Int_t t = -1; // type flag Int_t pe = -1; // ptEta flag if(type == "RP") { t = 0; } else if(type == "POI") { t = 1; } if(ptOrEta == "Pt") { pe = 0; } else if(ptOrEta == "Eta") { pe = 1; } Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; Double_t minPtEta[2] = {fPtMin,fEtaMin}; //Double_t maxPtEta[2] = {fPtMax,fEtaMax}; Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; // looping over all bins and calculating correction terms: for(Int_t b=1;b<=nBinsPtEta[pe];b++) { // real and imaginary parts of p_{m*n,0} (non-weighted Q-vector evaluated for POIs in particular pt or eta bin): Double_t p1n0kRe = 0.; Double_t p1n0kIm = 0.; // number of POIs in particular pt or eta bin: Double_t mp = 0.; // real and imaginary parts of q_{m*n,0} (weighted Q-vector evaluated for particles which are both RPs and POIs in particular pt or eta bin): Double_t q1n2kRe = 0.; Double_t q1n2kIm = 0.; Double_t q2n1kRe = 0.; Double_t q2n1kIm = 0.; // s_{1,1}, s_{1,2} and s_{1,3} // to be improved (add explanation) Double_t s1p1k = 0.; Double_t s1p2k = 0.; // number of particles which are both RPs and POIs in particular pt or eta bin: Double_t mq = 0.; // M0111 from Eq. (118) in QC2c (to be improved (notation)) Double_t dM01 = 0.; Double_t dM011 = 0.; if(type == "POI") { // q_{m*n,k}: q1n2kRe = fReRPQ1dEBE[2][pe][0][2]->GetBinContent(fReRPQ1dEBE[2][pe][0][2]->GetBin(b)) * fReRPQ1dEBE[2][pe][0][2]->GetBinEntries(fReRPQ1dEBE[2][pe][0][2]->GetBin(b)); q1n2kIm = fImRPQ1dEBE[2][pe][0][2]->GetBinContent(fImRPQ1dEBE[2][pe][0][2]->GetBin(b)) * fImRPQ1dEBE[2][pe][0][2]->GetBinEntries(fImRPQ1dEBE[2][pe][0][2]->GetBin(b)); q2n1kRe = fReRPQ1dEBE[2][pe][1][1]->GetBinContent(fReRPQ1dEBE[2][pe][1][1]->GetBin(b)) * fReRPQ1dEBE[2][pe][1][1]->GetBinEntries(fReRPQ1dEBE[2][pe][1][1]->GetBin(b)); q2n1kIm = fImRPQ1dEBE[2][pe][1][1]->GetBinContent(fImRPQ1dEBE[2][pe][1][1]->GetBin(b)) * fImRPQ1dEBE[2][pe][1][1]->GetBinEntries(fImRPQ1dEBE[2][pe][1][1]->GetBin(b)); mq = fReRPQ1dEBE[2][pe][0][0]->GetBinEntries(fReRPQ1dEBE[2][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) s1p1k = pow(fs1dEBE[2][pe][1]->GetBinContent(b)*fs1dEBE[2][pe][1]->GetBinEntries(b),1.); s1p2k = pow(fs1dEBE[2][pe][2]->GetBinContent(b)*fs1dEBE[2][pe][2]->GetBinEntries(b),1.); }else if(type == "RP") { // q_{m*n,k}: (Remark: m=1 is 0, k=0 iz zero (to be improved!)) q1n2kRe = fReRPQ1dEBE[0][pe][0][2]->GetBinContent(fReRPQ1dEBE[0][pe][0][2]->GetBin(b)) * fReRPQ1dEBE[0][pe][0][2]->GetBinEntries(fReRPQ1dEBE[0][pe][0][2]->GetBin(b)); q1n2kIm = fImRPQ1dEBE[0][pe][0][2]->GetBinContent(fImRPQ1dEBE[0][pe][0][2]->GetBin(b)) * fImRPQ1dEBE[0][pe][0][2]->GetBinEntries(fImRPQ1dEBE[0][pe][0][2]->GetBin(b)); q2n1kRe = fReRPQ1dEBE[0][pe][1][1]->GetBinContent(fReRPQ1dEBE[0][pe][1][1]->GetBin(b)) * fReRPQ1dEBE[0][pe][1][1]->GetBinEntries(fReRPQ1dEBE[0][pe][1][1]->GetBin(b)); q2n1kIm = fImRPQ1dEBE[0][pe][1][1]->GetBinContent(fImRPQ1dEBE[0][pe][1][1]->GetBin(b)) * fImRPQ1dEBE[0][pe][1][1]->GetBinEntries(fImRPQ1dEBE[0][pe][1][1]->GetBin(b)); // s_{1,1}, s_{1,2} and s_{1,3} // to be improved (add explanation) s1p1k = pow(fs1dEBE[0][pe][1]->GetBinContent(b)*fs1dEBE[0][pe][1]->GetBinEntries(b),1.); s1p2k = pow(fs1dEBE[0][pe][2]->GetBinContent(b)*fs1dEBE[0][pe][2]->GetBinEntries(b),1.); //s1p3k = pow(fs1dEBE[0][pe][3]->GetBinContent(b)*fs1dEBE[0][pe][3]->GetBinEntries(b),1.); } if(type == "POI") { // p_{m*n,k}: p1n0kRe = fReRPQ1dEBE[1][pe][0][0]->GetBinContent(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)) * fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)); p1n0kIm = fImRPQ1dEBE[1][pe][0][0]->GetBinContent(fImRPQ1dEBE[1][pe][0][0]->GetBin(b)) * fImRPQ1dEBE[1][pe][0][0]->GetBinEntries(fImRPQ1dEBE[1][pe][0][0]->GetBin(b)); mp = fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) // M01 from Eq. (118) in QC2c (to be improved (notation)): dM01 = mp*dSM1p1k-s1p1k; dM011 = mp*(dSM2p1k-dSM1p2k) - 2.*(s1p1k*dSM1p1k-s1p2k); // typeFlag = RP (0) or POI (1): t = 1; } else if(type == "RP") { // to be improved (cross-checked): p1n0kRe = fReRPQ1dEBE[0][pe][0][0]->GetBinContent(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)) * fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)); p1n0kIm = fImRPQ1dEBE[0][pe][0][0]->GetBinContent(fImRPQ1dEBE[0][pe][0][0]->GetBin(b)) * fImRPQ1dEBE[0][pe][0][0]->GetBinEntries(fImRPQ1dEBE[0][pe][0][0]->GetBin(b)); mp = fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) // M01 from Eq. (118) in QC2c (to be improved (notation)): dM01 = mp*dSM1p1k-s1p1k; dM011 = mp*(dSM2p1k-dSM1p2k) - 2.*(s1p1k*dSM1p1k-s1p2k); // typeFlag = RP (0) or POI (1): t = 0; } // <>: Double_t sinP1nPsi = 0.; if(mp) { sinP1nPsi = p1n0kIm/mp; // fill profile for <>: fDiffFlowCorrectionTermsForNUAPro[t][pe][0][0]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sinP1nPsi,mp); // histogram to store e-b-e (needed in some other methods): fDiffFlowCorrectionTermsForNUAEBE[t][pe][0][0]->SetBinContent(b,sinP1nPsi); } // end of if(mp) // <>: Double_t sinP1nPsiP1nPhiW2 = 0.; if(dM01) { sinP1nPsiP1nPhiW2 = (p1n0kRe*dImQ1n1k+p1n0kIm*dReQ1n1k-q2n1kIm)/(dM01); // fill profile for <>: fDiffFlowCorrectionTermsForNUAPro[t][pe][0][1]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sinP1nPsiP1nPhiW2,dM01); // histogram to store e-b-e (needed in some other methods): fDiffFlowCorrectionTermsForNUAEBE[t][pe][0][1]->SetBinContent(b,sinP1nPsiP1nPhiW2); } // end of if(mp*dMult-mq) // <>: Double_t sinP1nPsi1P1nPhi2MPhi3W2W3 = 0.; if(dM011) { sinP1nPsi1P1nPhi2MPhi3W2W3 = (p1n0kIm*(pow(dImQ1n1k,2.)+pow(dReQ1n1k,2.)) - p1n0kIm*dSM1p2k + q2n1kRe*dImQ1n1k-q2n1kIm*dReQ1n1k - s1p1k*dImQ1n1k + 2.*q1n2kIm) / dM011; // fill profile for <>: fDiffFlowCorrectionTermsForNUAPro[t][pe][0][2]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sinP1nPsi1P1nPhi2MPhi3W2W3,dM011); // histogram to store e-b-e (needed in some other methods): fDiffFlowCorrectionTermsForNUAEBE[t][pe][0][2]->SetBinContent(b,sinP1nPsi1P1nPhi2MPhi3W2W3); } // end of if(dM011) // <>: Double_t sinP1nPsi1M1nPhi2MPhi3W2W3 = 0.; if(dM011) { sinP1nPsi1M1nPhi2MPhi3W2W3 = (p1n0kIm*(pow(dReQ1n1k,2.)-pow(dImQ1n1k,2.))-2.*p1n0kRe*dReQ1n1k*dImQ1n1k + 1.*(p1n0kRe*dImQ2n2k-p1n0kIm*dReQ2n2k) + 2.*s1p1k*dImQ1n1k - 2.*q1n2kIm) / dM011; // fill profile for <>: fDiffFlowCorrectionTermsForNUAPro[t][pe][0][3]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sinP1nPsi1M1nPhi2MPhi3W2W3,dM011); // histogram to store e-b-e (needed in some other methods): fDiffFlowCorrectionTermsForNUAEBE[t][pe][0][3]->SetBinContent(b,sinP1nPsi1M1nPhi2MPhi3W2W3); } // end of if(dM011) } // end of for(Int_t b=1;b<=nBinsPtEta[pe];b++) } // end of AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrectionsForNUASinTermsUsingParticleWeights(TString type, TString ptOrEta) //================================================================================================================================ void AliFlowAnalysisWithQCumulants::EvaluateDiffFlowCorrectionTermsForNUAWithNestedLoopsUsingParticleWeights(AliFlowEventSimple * const anEvent, TString type, TString ptOrEta) { // Evaluate with nested loops correction terms for non-uniform acceptance // with using particle weights (both sin and cos terms) relevant for differential flow. // Remark 1: "w1" in expressions bellow is a particle weight used only for particles which were // flagged both as POI and RP. // Remark 2: Reduced correction terms for non-uniform acceptance are evaluated in pt bin number fCrossCheckInPtBinNo // and eta bin number fCrossCheckInEtaBinNo both for RPs and POIs. // Remark 3: Results are stored in 1 bin profiles fDiffFlowDirectCorrections[t][pe][sc][cti], where first three indices runs as: // [0=RP,1=POI][0=Pt,1=Eta][0=sin terms,1=cos terms], whilst the cti (correction term index) runs as follows: // cti: // 0: <> // 1: <> // 2: <> // 3: <> // 4: // 5: // 6: Int_t typeFlag = -1; Int_t ptEtaFlag = -1; if(type == "RP") { typeFlag = 0; } else if(type == "POI") { typeFlag = 1; } if(ptOrEta == "Pt") { ptEtaFlag = 0; } else if(ptOrEta == "Eta") { ptEtaFlag = 1; } // shortcuts: Int_t t = typeFlag; Int_t pe = ptEtaFlag; Double_t lowerPtEtaEdge[2] = {fPtMin+(fCrossCheckInPtBinNo-1)*fPtBinWidth,fEtaMin+(fCrossCheckInEtaBinNo-1)*fEtaBinWidth}; Double_t upperPtEtaEdge[2] = {fPtMin+fCrossCheckInPtBinNo*fPtBinWidth,fEtaMin+fCrossCheckInEtaBinNo*fEtaBinWidth}; Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; Int_t nPrim = anEvent->NumberOfTracks(); AliFlowTrackSimple *aftsTrack = NULL; Double_t psi1=0., phi2=0., phi3=0.;// phi4=0.;// phi5=0., phi6=0., phi7=0., phi8=0.; Double_t wPhi2=1., wPhi3=1.; Int_t n = fHarmonic; // 1'-particle correction terms: for(Int_t i1=0;i1GetTrack(i1); // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) if(typeFlag==1) // this is diff flow of POIs { if(ptOrEta == "Pt") { if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()InPOISelection())))continue; } else if (ptOrEta == "Eta") { if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()InPOISelection())))continue; } } else // this is diff flow of RPs { if(ptOrEta == "Pt") { if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()InRPSelection())))continue; } else if (ptOrEta == "Eta") { if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()InRPSelection())))continue; } } psi1=aftsTrack->Phi(); // sin terms: fDiffFlowDirectCorrectionTermsForNUA[t][pe][0][0]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,sin(n*psi1),1.); // <> // cos terms: fDiffFlowDirectCorrectionTermsForNUA[t][pe][1][0]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(n*psi1),1.); // <> }//end of for(Int_t i1=0;i1GetTrack(i1); // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) if(typeFlag==1) // this is diff flow of POIs { if(ptOrEta == "Pt") { if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()InPOISelection())))continue; } else if (ptOrEta == "Eta") { if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()InPOISelection())))continue; } } else // this is diff flow of RPs { if(ptOrEta == "Pt") { if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()InRPSelection())))continue; } else if (ptOrEta == "Eta") { if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()InRPSelection())))continue; } } psi1=aftsTrack->Phi(); for(Int_t i2=0;i2GetTrack(i2); // RP condition (!(first) particle in the correlator must be RP): if(!(aftsTrack->InRPSelection())) continue; phi2=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi2 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi2*fnBinsPhi/TMath::TwoPi()))); // sin terms: fDiffFlowDirectCorrectionTermsForNUA[t][pe][0][1]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,sin(n*(psi1+phi2)),wPhi2); // <> // cos terms: fDiffFlowDirectCorrectionTermsForNUA[t][pe][1][1]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(n*(psi1+phi2)),wPhi2); // <> }//end of for(Int_t i2=0;i2GetTrack(i1); // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) if(typeFlag==1) // this is diff flow of POIs { if(ptOrEta == "Pt") { if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()InPOISelection())))continue; } else if (ptOrEta == "Eta") { if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()InPOISelection())))continue; } } else // this is diff flow of RPs { if(ptOrEta == "Pt") { if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()InRPSelection())))continue; } else if (ptOrEta == "Eta") { if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()InRPSelection())))continue; } } psi1=aftsTrack->Phi(); for(Int_t i2=0;i2GetTrack(i2); // RP condition (!(first) particle in the correlator must be RP): if(!(aftsTrack->InRPSelection())) continue; phi2=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi2 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi2*fnBinsPhi/TMath::TwoPi()))); for(Int_t i3=0;i3GetTrack(i3); // RP condition (!(first) particle in the correlator must be RP): if(!(aftsTrack->InRPSelection())) continue; phi3=aftsTrack->Phi(); if(fUsePhiWeights && fPhiWeights) wPhi3 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi3*fnBinsPhi/TMath::TwoPi()))); // sin terms: fDiffFlowDirectCorrectionTermsForNUA[t][pe][0][2]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,sin(n*(psi1+phi2-phi3)),wPhi2*wPhi3); // <> fDiffFlowDirectCorrectionTermsForNUA[t][pe][0][3]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,sin(n*(psi1-phi2-phi3)),wPhi2*wPhi3); // <> // cos terms: fDiffFlowDirectCorrectionTermsForNUA[t][pe][1][2]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(n*(psi1+phi2-phi3)),wPhi2*wPhi3); // <> fDiffFlowDirectCorrectionTermsForNUA[t][pe][1][3]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(n*(psi1-phi2-phi3)),wPhi2*wPhi3); // <> }//end of for(Int_t i3=0;i3GetBinContent(1); // <<2>> Double_t four = fIntFlowCorrelationsHist->GetBinContent(2); // <<4>> Double_t six = fIntFlowCorrelationsHist->GetBinContent(3); // <<6>> Double_t eight = fIntFlowCorrelationsHist->GetBinContent(4); // <<8>> // measured true correlations (a.k.a. cumulants): if(two) measured[0] = two; if(four) measured[1] = four-2.*pow(two,2.); if(six) measured[2] = six-9.*two*four+12.*pow(two,3.); if(eight) measured[3] = eight-16.*two*six-18.*pow(four,2.)+144.*pow(two,2.)*four-144.*pow(two,4.); for(Int_t ci=0;ci<=1;ci++) // correlation index // to be improved (enabled also for QC{6} and QC{8} eventually) { corrected[ci] = fIntFlowQcumulants->GetBinContent(ci+1); if(TMath::Abs(measured[ci])>1.e-44) { fIntFlowDetectorBias->SetBinContent(ci+1,corrected[ci]/measured[ci]); } } // end of for(Int_t ci=1;ci<=4;ci++) // correlation index // Versus multiplicity: if(!fCalculateCumulantsVsM){return;} if(!fApplyCorrectionForNUAVsM){return;} Int_t nBins = fIntFlowCorrelationsVsMPro[0]->GetNbinsX(); // to be improved (hardwired 0) for(Int_t b=1;b<=nBins;b++) { // measured correlations vs M: two = fIntFlowCorrelationsVsMHist[0]->GetBinContent(b); // <<2>> four = fIntFlowCorrelationsVsMHist[1]->GetBinContent(b); // <<4>> six = fIntFlowCorrelationsVsMHist[2]->GetBinContent(b); // <<6>> eight = fIntFlowCorrelationsVsMHist[3]->GetBinContent(b); // <<8>> // measured true correlations (a.k.a. cumulants) vs M: measured[0] = 0.; // QC{2} vs M measured[1] = 0.; // QC{4} vs M measured[2] = 0.; // QC{6} vs M measured[3] = 0.; // QC{8} vs M if(two) measured[0] = two; if(four) measured[1] = four-2.*pow(two,2.); if(six) measured[2] = six-9.*two*four+12.*pow(two,3.); if(eight) measured[3] = eight-16.*two*six-18.*pow(four,2.)+144.*pow(two,2.)*four-144.*pow(two,4.); corrected[0] = 0.; // generalized QC{2} vs M corrected[1] = 0.; // generalized QC{4} vs M corrected[2] = 0.; // generalized QC{6} vs M corrected[3] = 0.; // generalized QC{8} vs M for(Int_t ci=0;ci<=1;ci++) // correlation index // to be improved (enabled also for QC{6} and QC{8} eventually) { corrected[ci] = fIntFlowQcumulantsVsM[ci]->GetBinContent(b); if(TMath::Abs(measured[ci])>1.e-44) { fIntFlowDetectorBiasVsM[ci]->SetBinContent(b,corrected[ci]/measured[ci]); } } // end of for(Int_t ci=1;ci<=4;ci++) // correlation index } // end of for(Int_t b=1;b<=nBins;b++) } // end of AliFlowAnalysisWithQCumulants::CalculateDetectorEffectsForTrueCorrelations() //================================================================================================================================ void AliFlowAnalysisWithQCumulants::CheckPointersUsedInFinish() { // Check all pointers used in method Finish(). if(!fIntFlowCorrelationsPro) { cout<