/************************************************************************** * Copyright(c) 1998-1999, 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. * **************************************************************************/ /* $Id: AliUEHistograms.cxx 20164 2007-08-14 15:31:50Z morsch $ */ // // // encapsulates several AliUEHist objects for a full UE analysis plus additional control histograms // // // Author: Jan Fiete Grosse-Oetringhaus, Sara Vallero #include "AliUEHistograms.h" #include "AliCFContainer.h" #include "AliVParticle.h" #include "AliAODTrack.h" #include "TList.h" #include "TCanvas.h" #include "TH2F.h" #include "TH1F.h" #include "TH3F.h" #include "TMath.h" #include "TLorentzVector.h" ClassImp(AliUEHistograms) const Int_t AliUEHistograms::fgkUEHists = 3; AliUEHistograms::AliUEHistograms(const char* name, const char* histograms, const char* binning) : TNamed(name, name), fNumberDensitypT(0), fSumpT(0), fNumberDensityPhi(0), fCorrelationpT(0), fCorrelationEta(0), fCorrelationPhi(0), fCorrelationR(0), fCorrelationLeading2Phi(0), fCorrelationMultiplicity(0), fYields(0), fInvYield2(0), fEventCount(0), fEventCountDifferential(0), fVertexContributors(0), fCentralityDistribution(0), fCentralityCorrelation(0), fITSClusterMap(0), fControlConvResoncances(0), fEfficiencyCorrectionTriggers(0), fEfficiencyCorrectionAssociated(0), fSelectCharge(0), fTriggerSelectCharge(0), fAssociatedSelectCharge(0), fTriggerRestrictEta(-1), fEtaOrdering(kFALSE), fCutConversions(kFALSE), fCutResonances(kFALSE), fRejectResonanceDaughters(-1), fOnlyOneEtaSide(0), fWeightPerEvent(kFALSE), fPtOrder(kTRUE), fTwoTrackCutMinRadius(0.8), fRunNumber(0), fMergeCount(1) { // Constructor // // the string histograms defines which histograms are created: // 1 = NumberDensitypT // 2 = SumpT // 3 = NumberDensityPhi // 4 = NumberDensityPhiCentrality (other multiplicity for Pb) AliLog::SetClassDebugLevel("AliCFContainer", -1); AliLog::SetClassDebugLevel("AliCFGridSparse", -3); fTwoTrackDistancePt[0] = 0; fTwoTrackDistancePt[1] = 0; TString histogramsStr(histograms); TString defaultBinningStr; defaultBinningStr = "eta: -1.0, -0.9, -0.8, -0.7, -0.6, -0.5, -0.4, -0.3, -0.2, -0.1, 0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0\n" "p_t_assoc: 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 8.0\n" "p_t_leading: 0.0, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0, 5.5, 6.0, 6.5, 7.0, 7.5, 8.0, 8.5, 9.0, 9.5, 10.0, 10.5, 11.0, 11.5, 12.0, 12.5, 13.0, 13.5, 14.0, 14.5, 15.0, 15.5, 16.0, 16.5, 17.0, 17.5, 18.0, 18.5, 19.0, 19.5, 20.0, 20.5, 21.0, 21.5, 22.0, 22.5, 23.0, 23.5, 24.0, 24.5, 25.0, 25.5, 26.0, 26.5, 27.0, 27.5, 28.0, 28.5, 29.0, 29.5, 30.0, 30.5, 31.0, 31.5, 32.0, 32.5, 33.0, 33.5, 34.0, 34.5, 35.0, 35.5, 36.0, 36.5, 37.0, 37.5, 38.0, 38.5, 39.0, 39.5, 40.0, 40.5, 41.0, 41.5, 42.0, 42.5, 43.0, 43.5, 44.0, 44.5, 45.0, 45.5, 46.0, 46.5, 47.0, 47.5, 48.0, 48.5, 49.0, 49.5, 50.0\n" "p_t_leading_course: 0.5, 1.0, 2.0, 3.0, 4.0, 6.0, 8.0\n" "p_t_eff: 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.25, 1.5, 1.75, 2.0, 2.25, 2.5, 2.75, 3.0, 3.25, 3.5, 3.75, 4.0, 4.5, 5.0, 6.0, 7.0, 8.0\n" "vertex_eff: -10, -8, -6, -4, -2, 0, 2, 4, 6, 8, 10\n" ; if (histogramsStr.Contains("4") || histogramsStr.Contains("5") || histogramsStr.Contains("6")) // Dphi Corr { if (histogramsStr.Contains("C")) defaultBinningStr += "multiplicity: 0, 20, 40, 60, 80, 100.1\n"; // course else defaultBinningStr += "multiplicity: 0, 1, 2, 3, 4, 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100.1\n"; if (histogramsStr.Contains("5")) defaultBinningStr += "vertex: -7, -5, -3, -1, 1, 3, 5, 7\n"; else defaultBinningStr += "vertex: -10, -8, -6, -4, -2, 0, 2, 4, 6, 8, 10\n"; if (histogramsStr.Contains("R")) defaultBinningStr += "delta_phi: -1.570796, -1.483530, -1.396263, -1.308997, -1.221730, -1.134464, -1.047198, -0.959931, -0.872665, -0.785398, -0.698132, -0.610865, -0.523599, -0.436332, -0.349066, -0.261799, -0.174533, -0.087266, 0.0, 0.087266, 0.174533, 0.261799, 0.349066, 0.436332, 0.523599, 0.610865, 0.698132, 0.785398, 0.872665, 0.959931, 1.047198, 1.134464, 1.221730, 1.308997, 1.396263, 1.483530, 1.570796, 1.658063, 1.745329, 1.832596, 1.919862, 2.007129, 2.094395, 2.181662, 2.268928, 2.356194, 2.443461, 2.530727, 2.617994, 2.705260, 2.792527, 2.879793, 2.967060, 3.054326, 3.141593, 3.228859, 3.316126, 3.403392, 3.490659, 3.577925, 3.665191, 3.752458, 3.839724, 3.926991, 4.014257, 4.101524, 4.188790, 4.276057, 4.363323, 4.450590, 4.537856, 4.625123, 4.712389\n" // this binning starts at -pi/2 and is modulo 3 "delta_eta: -2.4, -2.3, -2.2, -2.1, -2.0, -1.9, -1.8, -1.7, -1.6, -1.5, -1.4, -1.3, -1.2, -1.1, -1.0, -0.9, -0.8, -0.7, -0.6, -0.5, -0.4, -0.3, -0.2, -0.1, 0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0,2.1, 2.2, 2.3, 2.4\n" ; else // for TTR studies defaultBinningStr += "delta_phi: -1.570796, -1.483530, -1.396263, -1.308997, -1.221730, -1.134464, -1.047198, -0.959931, -0.872665, -0.785398, -0.698132, -0.610865, -0.523599, -0.436332, -0.349066, -0.261799, -0.174533, -0.087266, -0.043633, -0.021817, 0.0, 0.021817, 0.043633, 0.087266, 0.174533, 0.261799, 0.349066, 0.436332, 0.523599, 0.610865, 0.698132, 0.785398, 0.872665, 0.959931, 1.047198, 1.134464, 1.221730, 1.308997, 1.396263, 1.483530, 1.570796, 1.658063, 1.745329, 1.832596, 1.919862, 2.007129, 2.094395, 2.181662, 2.268928, 2.356194, 2.443461, 2.530727, 2.617994, 2.705260, 2.792527, 2.879793, 2.967060, 3.054326, 3.141593, 3.228859, 3.316126, 3.403392, 3.490659, 3.577925, 3.665191, 3.752458, 3.839724, 3.926991, 4.014257, 4.101524, 4.188790, 4.276057, 4.363323, 4.450590, 4.537856, 4.625123, 4.712389\n" "delta_eta: -2.0, -1.9, -1.8, -1.7, -1.6, -1.5, -1.4, -1.3, -1.2, -1.1, -1.0, -0.9, -0.8, -0.7, -0.6, -0.5, -0.4, -0.3, -0.2, -0.1, -0.05, -0.025, 0, 0.025, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0\n" ; } else // UE defaultBinningStr += "multiplicity: -0.5, 0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5, 9.5, 10.5, 11.5, 12.5, 13.5, 200.0\n" "delta_phi: -1.570796, -1.483530, -1.396263, -1.308997, -1.221730, -1.134464, -1.047198, -0.959931, -0.872665, -0.785398, -0.698132, -0.610865, -0.523599, -0.436332, -0.349066, -0.261799, -0.174533, -0.087266, 0.0, 0.087266, 0.174533, 0.261799, 0.349066, 0.436332, 0.523599, 0.610865, 0.698132, 0.785398, 0.872665, 0.959931, 1.047198, 1.134464, 1.221730, 1.308997, 1.396263, 1.483530, 1.570796, 1.658063, 1.745329, 1.832596, 1.919862, 2.007129, 2.094395, 2.181662, 2.268928, 2.356194, 2.443461, 2.530727, 2.617994, 2.705260, 2.792527, 2.879793, 2.967060, 3.054326, 3.141593, 3.228859, 3.316126, 3.403392, 3.490659, 3.577925, 3.665191, 3.752458, 3.839724, 3.926991, 4.014257, 4.101524, 4.188790, 4.276057, 4.363323, 4.450590, 4.537856, 4.625123, 4.712389\n" "vertex: -10, -8, -6, -4, -2, 0, 2, 4, 6, 8, 10\n" ; // combine customBinning with defaultBinningStr -> use customBinning where available and otherwise defaultBinningStr TString customBinning(binning); TString binningStr; TObjArray* lines = defaultBinningStr.Tokenize("\n"); for (Int_t i=0; iGetEntriesFast(); i++) { TString line(lines->At(i)->GetName()); TString tag = line(0, line.Index(":")+1); if (!customBinning.BeginsWith(tag) && !customBinning.Contains(TString("\n") + tag)) binningStr += line + "\n"; else Printf("Using custom binning for %s", tag.Data()); } delete lines; binningStr += customBinning; if (histogramsStr.Contains("1")) fNumberDensitypT = new AliUEHist("NumberDensitypT", binningStr); if (histogramsStr.Contains("2")) fSumpT = new AliUEHist("SumpT", binningStr); if (histogramsStr.Contains("3")) fNumberDensityPhi = new AliUEHist("NumberDensityPhi", binningStr); else if (histogramsStr.Contains("4")) fNumberDensityPhi = new AliUEHist("NumberDensityPhiCentrality", binningStr); else if (histogramsStr.Contains("5") || histogramsStr.Contains("6")) fNumberDensityPhi = new AliUEHist("NumberDensityPhiCentralityVtx", binningStr); // do not add this hists to the directory Bool_t oldStatus = TH1::AddDirectoryStatus(); TH1::AddDirectory(kFALSE); if (!histogramsStr.Contains("4") && !histogramsStr.Contains("5") && !histogramsStr.Contains("6")) { fCorrelationpT = new TH2F("fCorrelationpT", ";p_{T,lead} (MC);p_{T,lead} (RECO)", 200, 0, 50, 200, 0, 50); fCorrelationEta = new TH2F("fCorrelationEta", ";#eta_{lead} (MC);#eta_{T,lead} (RECO)", 200, -1, 1, 200, -1, 1); fCorrelationPhi = new TH2F("fCorrelationPhi", ";#varphi_{lead} (MC);#varphi_{T,lead} (RECO)", 200, 0, TMath::TwoPi(), 200, 0, TMath::TwoPi()); } else { fCorrelationpT = new TH2F("fCorrelationpT", ";Centrality;p_{T} (RECO)", 100, 0, 100.001, 200, 0, 50); fCorrelationEta = new TH2F("fCorrelationEta", ";Centrality;#eta (RECO)", 100, 0, 100.001, 200, -5, 5); fCorrelationPhi = new TH2F("fCorrelationPhi", ";Centrality;#varphi (RECO)", 100, 0, 100.001, 200, 0, TMath::TwoPi()); } fCorrelationR = new TH2F("fCorrelationR", ";R;p_{T,lead} (MC)", 200, 0, 2, 200, 0, 50); fCorrelationLeading2Phi = new TH2F("fCorrelationLeading2Phi", ";#Delta #varphi;p_{T,lead} (MC)", 200, -TMath::Pi(), TMath::Pi(), 200, 0, 50); fCorrelationMultiplicity = new TH2F("fCorrelationMultiplicity", ";MC tracks;Reco tracks", 100, -0.5, 99.5, 100, -0.5, 99.5); fYields = new TH3F("fYields", ";centrality;pT;eta", 100, 0, 100, 40, 0, 20, 100, -1, 1); fInvYield2 = new TH2F("fInvYield2", ";centrality;pT;1/pT dNch/dpT", 100, 0, 100, 80, 0, 20); if (!histogramsStr.Contains("4") && !histogramsStr.Contains("5") && !histogramsStr.Contains("6")) { fEventCount = new TH2F("fEventCount", ";step;event type;count", AliUEHist::fgkCFSteps+2, -2.5, -0.5 + AliUEHist::fgkCFSteps, 3, -0.5, 2.5); fEventCount->GetYaxis()->SetBinLabel(1, "ND"); fEventCount->GetYaxis()->SetBinLabel(2, "SD"); fEventCount->GetYaxis()->SetBinLabel(3, "DD"); } else { fEventCount = new TH2F("fEventCount", ";step;centrality;count", AliUEHist::fgkCFSteps+2, -2.5, -0.5 + AliUEHist::fgkCFSteps, fNumberDensityPhi->GetEventHist()->GetNBins(1), fNumberDensityPhi->GetEventHist()->GetAxis(1, 0)->GetXbins()->GetArray()); } fEventCountDifferential = new TH3F("fEventCountDifferential", ";p_{T,lead};step;event type", 100, 0, 50, AliUEHist::fgkCFSteps, -0.5, -0.5 + AliUEHist::fgkCFSteps, 3, -0.5, 2.5); fEventCountDifferential->GetZaxis()->SetBinLabel(1, "ND"); fEventCountDifferential->GetZaxis()->SetBinLabel(2, "SD"); fEventCountDifferential->GetZaxis()->SetBinLabel(3, "DD"); fVertexContributors = new TH1F("fVertexContributors", ";contributors;count", 100, -0.5, 99.5); if (fNumberDensityPhi) { fCentralityDistribution = new TH1F("fCentralityDistribution", ";centrality;count", fNumberDensityPhi->GetEventHist()->GetNBins(1), fNumberDensityPhi->GetEventHist()->GetAxis(1, 0)->GetXbins()->GetArray()); fCentralityCorrelation = new TH2F("fCentralityCorrelation", ";centrality;multiplicity", 404, 0, 101, 200, 0, 4000); } fITSClusterMap = new TH3F("fITSClusterMap", "; its cluster map; centrality; pT", 256, -0.5, 255.5, 20, 0, 100.001, 100, 0, 20); fControlConvResoncances = new TH2F("fControlConvResoncances", ";id;delta mass", 3, -0.5, 2.5, 100, -0.1, 0.1); TH1::AddDirectory(oldStatus); } //_____________________________________________________________________________ AliUEHistograms::AliUEHistograms(const AliUEHistograms &c) : TNamed(fName, fTitle), fNumberDensitypT(0), fSumpT(0), fNumberDensityPhi(0), fCorrelationpT(0), fCorrelationEta(0), fCorrelationPhi(0), fCorrelationR(0), fCorrelationLeading2Phi(0), fCorrelationMultiplicity(0), fYields(0), fInvYield2(0), fEventCount(0), fEventCountDifferential(0), fVertexContributors(0), fCentralityDistribution(0), fCentralityCorrelation(0), fITSClusterMap(0), fControlConvResoncances(0), fEfficiencyCorrectionTriggers(0), fEfficiencyCorrectionAssociated(0), fSelectCharge(0), fTriggerSelectCharge(0), fAssociatedSelectCharge(0), fTriggerRestrictEta(-1), fEtaOrdering(kFALSE), fCutConversions(kFALSE), fCutResonances(kFALSE), fRejectResonanceDaughters(-1), fOnlyOneEtaSide(0), fWeightPerEvent(kFALSE), fPtOrder(kTRUE), fTwoTrackCutMinRadius(0.8), fRunNumber(0), fMergeCount(1) { // // AliUEHistograms copy constructor // fTwoTrackDistancePt[0] = 0; fTwoTrackDistancePt[1] = 0; ((AliUEHistograms &) c).Copy(*this); } //____________________________________________________________________ AliUEHistograms::~AliUEHistograms() { // Destructor DeleteContainers(); } void AliUEHistograms::DeleteContainers() { if (fNumberDensitypT) { delete fNumberDensitypT; fNumberDensitypT = 0; } if (fSumpT) { delete fSumpT; fSumpT = 0; } if (fNumberDensityPhi) { delete fNumberDensityPhi; fNumberDensityPhi = 0; } if (fCorrelationpT) { delete fCorrelationpT; fCorrelationpT = 0; } if (fCorrelationEta) { delete fCorrelationEta; fCorrelationEta = 0; } if (fCorrelationPhi) { delete fCorrelationPhi; fCorrelationPhi = 0; } if (fCorrelationR) { delete fCorrelationR; fCorrelationR = 0; } if (fCorrelationLeading2Phi) { delete fCorrelationLeading2Phi; fCorrelationLeading2Phi = 0; } if (fCorrelationMultiplicity) { delete fCorrelationMultiplicity; fCorrelationMultiplicity = 0; } if (fYields) { delete fYields; fYields = 0; } if (fInvYield2) { delete fInvYield2; fInvYield2 = 0; } if (fEventCount) { delete fEventCount; fEventCount = 0; } if (fEventCountDifferential) { delete fEventCountDifferential; fEventCountDifferential = 0; } if (fVertexContributors) { delete fVertexContributors; fVertexContributors = 0; } if (fCentralityDistribution) { delete fCentralityDistribution; fCentralityDistribution = 0; } if (fCentralityCorrelation) { delete fCentralityCorrelation; fCentralityCorrelation = 0; } if (fITSClusterMap) { delete fITSClusterMap; fITSClusterMap = 0; } for (Int_t i=0; i<2; i++) if (fTwoTrackDistancePt[i]) { delete fTwoTrackDistancePt[i]; fTwoTrackDistancePt[i] = 0; } if (fControlConvResoncances) { delete fControlConvResoncances; fControlConvResoncances = 0; } if (fEfficiencyCorrectionTriggers) { delete fEfficiencyCorrectionTriggers; fEfficiencyCorrectionTriggers = 0; } if (fEfficiencyCorrectionAssociated) { delete fEfficiencyCorrectionAssociated; fEfficiencyCorrectionAssociated = 0; } } AliUEHist* AliUEHistograms::GetUEHist(Int_t id) { // returns AliUEHist object, useful for loops switch (id) { case 0: return fNumberDensitypT; break; case 1: return fSumpT; break; case 2: return fNumberDensityPhi; break; } return 0; } //____________________________________________________________________ Int_t AliUEHistograms::CountParticles(TList* list, Float_t ptMin) { // counts the number of particles in the list with a pT above ptMin // TODO eta cut needed here? Int_t count = 0; for (Int_t j=0; jGetEntries(); j++) if (((AliVParticle*) list->At(j))->Pt() > ptMin) count++; return count; } //____________________________________________________________________ void AliUEHistograms::Fill(Int_t eventType, Float_t zVtx, AliUEHist::CFStep step, AliVParticle* leading, TList* toward, TList* away, TList* min, TList* max) { // fills the UE event histograms // // this function needs the leading (track or jet or ...) and four lists of AliVParticles which contain the particles/tracks to be filled in the four regions // if leading is not set, just fill event statistics if (leading) { Int_t multiplicity = 0; // TODO configurable? Float_t ptMin = 0.15; if (leading->Pt() > ptMin) multiplicity++; multiplicity += CountParticles(toward, ptMin); multiplicity += CountParticles(away, ptMin); multiplicity += CountParticles(min, ptMin); multiplicity += CountParticles(max, ptMin); FillRegion(AliUEHist::kToward, zVtx, step, leading, toward, multiplicity); FillRegion(AliUEHist::kAway, zVtx, step, leading, away, multiplicity); FillRegion(AliUEHist::kMin, zVtx, step, leading, min, multiplicity); FillRegion(AliUEHist::kMax, zVtx, step, leading, max, multiplicity); Double_t vars[3]; vars[0] = leading->Pt(); vars[1] = multiplicity; vars[2] = zVtx; for (Int_t i=0; iGetEventHist()->Fill(vars, step); fEventCountDifferential->Fill(leading->Pt(), step, eventType); } FillEvent(eventType, step); } //____________________________________________________________________ void AliUEHistograms::FillRegion(AliUEHist::Region region, Float_t zVtx, AliUEHist::CFStep step, AliVParticle* leading, TList* list, Int_t multiplicity) { // loops over AliVParticles in list and fills the given region at the given step // // See also Fill(...) for (Int_t i=0; iGetEntries(); i++) { AliVParticle* particle = (AliVParticle*) list->At(i); Double_t vars[6]; vars[0] = particle->Eta(); vars[1] = particle->Pt(); vars[2] = leading->Pt(); vars[3] = multiplicity; vars[4] = leading->Phi() - particle->Phi(); if (vars[4] > 1.5 * TMath::Pi()) vars[4] -= TMath::TwoPi(); if (vars[4] < -0.5 * TMath::Pi()) vars[4] += TMath::TwoPi(); vars[5] = zVtx; if (fNumberDensitypT) fNumberDensitypT->GetTrackHist(region)->Fill(vars, step); if (fSumpT) fSumpT->GetTrackHist(region)->Fill(vars, step, particle->Pt()); // fill all in toward region (is anyway as function of delta phi!) if (fNumberDensityPhi) fNumberDensityPhi->GetTrackHist(AliUEHist::kToward)->Fill(vars, step); } } //____________________________________________________________________ void AliUEHistograms::Fill(AliVParticle* leadingMC, AliVParticle* leadingReco) { // fills the correlation histograms if (leadingMC) { fCorrelationpT->Fill(leadingMC->Pt(), leadingReco->Pt()); if (leadingMC->Pt() > 0.5) { fCorrelationEta->Fill(leadingMC->Eta(), leadingReco->Eta()); fCorrelationPhi->Fill(leadingMC->Phi(), leadingReco->Phi()); } Float_t phiDiff = leadingMC->Phi() - leadingReco->Phi(); if (phiDiff > TMath::Pi()) phiDiff -= TMath::TwoPi(); if (phiDiff < -TMath::Pi()) phiDiff += TMath::TwoPi(); Float_t etaDiff = leadingMC->Eta() - leadingReco->Eta(); fCorrelationR->Fill(TMath::Sqrt(phiDiff * phiDiff + etaDiff * etaDiff), leadingMC->Pt()); fCorrelationLeading2Phi->Fill(phiDiff, leadingMC->Pt()); } else { fCorrelationpT->Fill(1.0, leadingReco->Pt()); if (leadingReco->Pt() > 0.5) { fCorrelationEta->Fill(0.0, leadingReco->Eta()); fCorrelationPhi->Fill(0.0, leadingReco->Phi()); } } } //____________________________________________________________________ void AliUEHistograms::FillCorrelations(Double_t centrality, Float_t zVtx, AliUEHist::CFStep step, TObjArray* particles, TObjArray* mixed, Float_t weight, Bool_t firstTime, Bool_t twoTrackEfficiencyCut, Float_t bSign, Float_t twoTrackEfficiencyCutValue, Bool_t applyEfficiency) { // fills the fNumberDensityPhi histogram // // this function need a list of AliVParticles which contain the particles/tracks to be filled // // if mixed is non-0, mixed events are filled, the trigger particle is from particles, the associated from mixed // if weight < 0, then the pt of the associated particle is filled as weight Bool_t fillpT = kFALSE; if (weight < 0) fillpT = kTRUE; if (twoTrackEfficiencyCut && !fTwoTrackDistancePt[0]) { // do not add this hists to the directory Bool_t oldStatus = TH1::AddDirectoryStatus(); TH1::AddDirectory(kFALSE); fTwoTrackDistancePt[0] = new TH3F("fTwoTrackDistancePt[0]", ";#Delta#eta;#Delta#varphi^{*}_{min};#Delta p_{T}", 100, -0.15, 0.15, 100, -0.05, 0.05, 20, 0, 10); fTwoTrackDistancePt[1] = (TH3F*) fTwoTrackDistancePt[0]->Clone("fTwoTrackDistancePt[1]"); TH1::AddDirectory(oldStatus); } // Eta() is extremely time consuming, therefore cache it for the inner loop here: TObjArray* input = (mixed) ? mixed : particles; TArrayF eta(input->GetEntriesFast()); for (Int_t i=0; iGetEntriesFast(); i++) eta[i] = ((AliVParticle*) input->UncheckedAt(i))->Eta(); // if particles is not set, just fill event statistics if (particles) { Int_t jMax = particles->GetEntriesFast(); if (mixed) jMax = mixed->GetEntriesFast(); TH1* triggerWeighting = 0; if (fWeightPerEvent) { TAxis* axis = fNumberDensityPhi->GetTrackHist(AliUEHist::kToward)->GetGrid(0)->GetGrid()->GetAxis(2); triggerWeighting = new TH1F("triggerWeighting", "", axis->GetNbins(), axis->GetXbins()->GetArray()); for (Int_t i=0; iGetEntriesFast(); i++) { AliVParticle* triggerParticle = (AliVParticle*) particles->UncheckedAt(i); // some optimization Float_t triggerEta = triggerParticle->Eta(); if (fTriggerRestrictEta > 0 && TMath::Abs(triggerEta) > fTriggerRestrictEta) continue; if (fOnlyOneEtaSide != 0) { if (fOnlyOneEtaSide * triggerEta < 0) continue; } if (fTriggerSelectCharge != 0) if (triggerParticle->Charge() * fTriggerSelectCharge < 0) continue; triggerWeighting->Fill(triggerParticle->Pt()); } } // identify K, Lambda candidates and flag those particles // a TObject bit is used for this const UInt_t kResonanceDaughterFlag = 1 << 14; if (fRejectResonanceDaughters > 0) { Double_t resonanceMass = -1; Double_t massDaughter1 = -1; Double_t massDaughter2 = -1; const Double_t interval = 0.02; switch (fRejectResonanceDaughters) { case 1: resonanceMass = 1.2; massDaughter1 = 0.1396; massDaughter2 = 0.9383; break; // method test case 2: resonanceMass = 0.4976; massDaughter1 = 0.1396; massDaughter2 = massDaughter1; break; // k0 case 3: resonanceMass = 1.115; massDaughter1 = 0.1396; massDaughter2 = 0.9383; break; // lambda default: AliFatal(Form("Invalid setting %d", fRejectResonanceDaughters)); } for (Int_t i=0; iGetEntriesFast(); i++) particles->UncheckedAt(i)->ResetBit(kResonanceDaughterFlag); if (mixed) for (Int_t i=0; iUncheckedAt(i)->ResetBit(kResonanceDaughterFlag); for (Int_t i=0; iGetEntriesFast(); i++) { AliVParticle* triggerParticle = (AliVParticle*) particles->UncheckedAt(i); for (Int_t j=0; jUncheckedAt(j); else particle = (AliVParticle*) mixed->UncheckedAt(j); // check if both particles point to the same element (does not occur for mixed events, but if subsets are mixed within the same event) if (mixed && triggerParticle->IsEqual(particle)) continue; if (triggerParticle->Charge() * particle->Charge() > 0) continue; Float_t mass = GetInvMassSquaredCheap(triggerParticle->Pt(), triggerParticle->Eta(), triggerParticle->Phi(), particle->Pt(), particle->Eta(), particle->Phi(), massDaughter1, massDaughter2); if (TMath::Abs(mass - resonanceMass*resonanceMass) < interval*5) { mass = GetInvMassSquared(triggerParticle->Pt(), triggerParticle->Eta(), triggerParticle->Phi(), particle->Pt(), particle->Eta(), particle->Phi(), massDaughter1, massDaughter2); if (mass > (resonanceMass-interval)*(resonanceMass-interval) && mass < (resonanceMass+interval)*(resonanceMass+interval)) { triggerParticle->SetBit(kResonanceDaughterFlag); particle->SetBit(kResonanceDaughterFlag); // Printf("Flagged %d %d %f", i, j, TMath::Sqrt(mass)); } } } } } for (Int_t i=0; iGetEntriesFast(); i++) { AliVParticle* triggerParticle = (AliVParticle*) particles->UncheckedAt(i); // some optimization Float_t triggerEta = triggerParticle->Eta(); if (fTriggerRestrictEta > 0 && TMath::Abs(triggerEta) > fTriggerRestrictEta) continue; if (fOnlyOneEtaSide != 0) { if (fOnlyOneEtaSide * triggerEta < 0) continue; } if (fTriggerSelectCharge != 0) if (triggerParticle->Charge() * fTriggerSelectCharge < 0) continue; if (fRejectResonanceDaughters > 0) if (triggerParticle->TestBit(kResonanceDaughterFlag)) { // Printf("Skipped i=%d", i); continue; } for (Int_t j=0; jUncheckedAt(j); else particle = (AliVParticle*) mixed->UncheckedAt(j); // check if both particles point to the same element (does not occur for mixed events, but if subsets are mixed within the same event) if (mixed && triggerParticle->IsEqual(particle)) continue; if (fPtOrder) if (particle->Pt() >= triggerParticle->Pt()) continue; if (fAssociatedSelectCharge != 0) if (particle->Charge() * fAssociatedSelectCharge < 0) continue; if (fSelectCharge > 0) { // skip like sign if (fSelectCharge == 1 && particle->Charge() * triggerParticle->Charge() > 0) continue; // skip unlike sign if (fSelectCharge == 2 && particle->Charge() * triggerParticle->Charge() < 0) continue; } if (fEtaOrdering) { if (triggerEta < 0 && eta[j] < triggerEta) continue; if (triggerEta > 0 && eta[j] > triggerEta) continue; } if (fRejectResonanceDaughters > 0) if (particle->TestBit(kResonanceDaughterFlag)) { // Printf("Skipped j=%d", j); continue; } // conversions if (fCutConversions && particle->Charge() * triggerParticle->Charge() < 0) { Float_t mass = GetInvMassSquaredCheap(triggerParticle->Pt(), triggerEta, triggerParticle->Phi(), particle->Pt(), eta[j], particle->Phi(), 0.510e-3, 0.510e-3); if (mass < 0.1) { mass = GetInvMassSquared(triggerParticle->Pt(), triggerEta, triggerParticle->Phi(), particle->Pt(), eta[j], particle->Phi(), 0.510e-3, 0.510e-3); fControlConvResoncances->Fill(0.0, mass); if (mass < 0.04*0.04) continue; } } // K0s if (fCutResonances && particle->Charge() * triggerParticle->Charge() < 0) { Float_t mass = GetInvMassSquaredCheap(triggerParticle->Pt(), triggerEta, triggerParticle->Phi(), particle->Pt(), eta[j], particle->Phi(), 0.1396, 0.1396); const Float_t kK0smass = 0.4976; if (TMath::Abs(mass - kK0smass*kK0smass) < 0.1) { mass = GetInvMassSquared(triggerParticle->Pt(), triggerEta, triggerParticle->Phi(), particle->Pt(), eta[j], particle->Phi(), 0.1396, 0.1396); fControlConvResoncances->Fill(1, mass - kK0smass*kK0smass); if (mass > (kK0smass-0.02)*(kK0smass-0.02) && mass < (kK0smass+0.02)*(kK0smass+0.02)) continue; } } // Lambda if (fCutResonances && particle->Charge() * triggerParticle->Charge() < 0) { Float_t mass1 = GetInvMassSquaredCheap(triggerParticle->Pt(), triggerEta, triggerParticle->Phi(), particle->Pt(), eta[j], particle->Phi(), 0.1396, 0.9383); Float_t mass2 = GetInvMassSquaredCheap(triggerParticle->Pt(), triggerEta, triggerParticle->Phi(), particle->Pt(), eta[j], particle->Phi(), 0.9383, 0.1396); const Float_t kLambdaMass = 1.115; if (TMath::Abs(mass1 - kLambdaMass*kLambdaMass) < 0.1) { mass1 = GetInvMassSquared(triggerParticle->Pt(), triggerEta, triggerParticle->Phi(), particle->Pt(), eta[j], particle->Phi(), 0.1396, 0.9383); fControlConvResoncances->Fill(2, mass1 - kLambdaMass*kLambdaMass); if (mass1 > (kLambdaMass-0.02)*(kLambdaMass-0.02) && mass1 < (kLambdaMass+0.02)*(kLambdaMass+0.02)) continue; } if (TMath::Abs(mass2 - kLambdaMass*kLambdaMass) < 0.1) { mass2 = GetInvMassSquared(triggerParticle->Pt(), triggerEta, triggerParticle->Phi(), particle->Pt(), eta[j], particle->Phi(), 0.9383, 0.1396); fControlConvResoncances->Fill(2, mass2 - kLambdaMass*kLambdaMass); if (mass2 > (kLambdaMass-0.02)*(kLambdaMass-0.02) && mass2 < (kLambdaMass+0.02)*(kLambdaMass+0.02)) continue; } } if (twoTrackEfficiencyCut) { // the variables & cuthave been developed by the HBT group // see e.g. https://indico.cern.ch/materialDisplay.py?contribId=36&sessionId=6&materialId=slides&confId=142700 Float_t phi1 = triggerParticle->Phi(); Float_t pt1 = triggerParticle->Pt(); Float_t charge1 = triggerParticle->Charge(); Float_t phi2 = particle->Phi(); Float_t pt2 = particle->Pt(); Float_t charge2 = particle->Charge(); Float_t deta = triggerEta - eta[j]; // optimization if (TMath::Abs(deta) < twoTrackEfficiencyCutValue * 2.5 * 3) { // check first boundaries to see if is worth to loop and find the minimum Float_t dphistar1 = GetDPhiStar(phi1, pt1, charge1, phi2, pt2, charge2, fTwoTrackCutMinRadius, bSign); Float_t dphistar2 = GetDPhiStar(phi1, pt1, charge1, phi2, pt2, charge2, 2.5, bSign); const Float_t kLimit = twoTrackEfficiencyCutValue * 3; Float_t dphistarminabs = 1e5; Float_t dphistarmin = 1e5; if (TMath::Abs(dphistar1) < kLimit || TMath::Abs(dphistar2) < kLimit || dphistar1 * dphistar2 < 0) { for (Double_t rad=fTwoTrackCutMinRadius; rad<2.51; rad+=0.01) { Float_t dphistar = GetDPhiStar(phi1, pt1, charge1, phi2, pt2, charge2, rad, bSign); Float_t dphistarabs = TMath::Abs(dphistar); if (dphistarabs < dphistarminabs) { dphistarmin = dphistar; dphistarminabs = dphistarabs; } } fTwoTrackDistancePt[0]->Fill(deta, dphistarmin, TMath::Abs(pt1 - pt2)); if (dphistarminabs < twoTrackEfficiencyCutValue && TMath::Abs(deta) < twoTrackEfficiencyCutValue) { // Printf("Removed track pair %d %d with %f %f %f %f %f %f %f %f %f", i, j, deta, dphistarminabs, phi1, pt1, charge1, phi2, pt2, charge2, bSign); continue; } fTwoTrackDistancePt[1]->Fill(deta, dphistarmin, TMath::Abs(pt1 - pt2)); } } } Double_t vars[6]; vars[0] = triggerEta - eta[j]; vars[1] = particle->Pt(); vars[2] = triggerParticle->Pt(); vars[3] = centrality; vars[4] = triggerParticle->Phi() - particle->Phi(); if (vars[4] > 1.5 * TMath::Pi()) vars[4] -= TMath::TwoPi(); if (vars[4] < -0.5 * TMath::Pi()) vars[4] += TMath::TwoPi(); vars[5] = zVtx; if (fillpT) weight = particle->Pt(); Double_t useWeight = weight; if (applyEfficiency) { if (fEfficiencyCorrectionAssociated) { Int_t effVars[4]; // associated particle effVars[0] = fEfficiencyCorrectionAssociated->GetAxis(0)->FindBin(eta[j]); effVars[1] = fEfficiencyCorrectionAssociated->GetAxis(1)->FindBin(vars[1]); //pt effVars[2] = fEfficiencyCorrectionAssociated->GetAxis(2)->FindBin(vars[3]); //centrality effVars[3] = fEfficiencyCorrectionAssociated->GetAxis(3)->FindBin(vars[5]); //zVtx // Printf("%d %d %d %d %f", effVars[0], effVars[1], effVars[2], effVars[3], fEfficiencyCorrectionAssociated->GetBinContent(effVars)); useWeight *= fEfficiencyCorrectionAssociated->GetBinContent(effVars); } if (fEfficiencyCorrectionTriggers) { Int_t effVars[4]; effVars[0] = fEfficiencyCorrectionTriggers->GetAxis(0)->FindBin(triggerEta); effVars[1] = fEfficiencyCorrectionTriggers->GetAxis(1)->FindBin(vars[2]); //pt effVars[2] = fEfficiencyCorrectionTriggers->GetAxis(2)->FindBin(vars[3]); //centrality effVars[3] = fEfficiencyCorrectionTriggers->GetAxis(3)->FindBin(vars[5]); //zVtx useWeight *= fEfficiencyCorrectionTriggers->GetBinContent(effVars); } } if (fWeightPerEvent) { Int_t weightBin = triggerWeighting->GetXaxis()->FindBin(vars[2]); // Printf("Using weight %f", triggerWeighting->GetBinContent(weightBin)); useWeight /= triggerWeighting->GetBinContent(weightBin); } // fill all in toward region and do not use the other regions fNumberDensityPhi->GetTrackHist(AliUEHist::kToward)->Fill(vars, step, useWeight); // Printf("%.2f %.2f --> %.2f", triggerEta, eta[j], vars[0]); } if (firstTime) { // once per trigger particle Double_t vars[3]; vars[0] = triggerParticle->Pt(); vars[1] = centrality; vars[2] = zVtx; Double_t useWeight = 1; if (fEfficiencyCorrectionTriggers && applyEfficiency) { Int_t effVars[4]; // trigger particle effVars[0] = fEfficiencyCorrectionTriggers->GetAxis(0)->FindBin(triggerEta); effVars[1] = fEfficiencyCorrectionTriggers->GetAxis(1)->FindBin(vars[0]); //pt effVars[2] = fEfficiencyCorrectionTriggers->GetAxis(2)->FindBin(vars[1]); //centrality effVars[3] = fEfficiencyCorrectionTriggers->GetAxis(3)->FindBin(vars[2]); //zVtx useWeight *= fEfficiencyCorrectionTriggers->GetBinContent(effVars); } if (TMath::Abs(triggerEta) < 0.8 && triggerParticle->Pt() > 0) fInvYield2->Fill(centrality, triggerParticle->Pt(), useWeight / triggerParticle->Pt()); if (fWeightPerEvent) { // leads effectively to a filling of one entry per filled trigger particle pT bin Int_t weightBin = triggerWeighting->GetXaxis()->FindBin(vars[0]); // Printf("Using weight %f", triggerWeighting->GetBinContent(weightBin)); useWeight /= triggerWeighting->GetBinContent(weightBin); } fNumberDensityPhi->GetEventHist()->Fill(vars, step, useWeight); // QA fCorrelationpT->Fill(centrality, triggerParticle->Pt()); fCorrelationEta->Fill(centrality, triggerEta); fCorrelationPhi->Fill(centrality, triggerParticle->Phi()); fYields->Fill(centrality, triggerParticle->Pt(), triggerEta); /* if (dynamic_cast(triggerParticle)) fITSClusterMap->Fill(((AliAODTrack*) triggerParticle)->GetITSClusterMap(), centrality, triggerParticle->Pt());*/ } } if (triggerWeighting) { delete triggerWeighting; triggerWeighting = 0; } } fCentralityDistribution->Fill(centrality); fCentralityCorrelation->Fill(centrality, particles->GetEntriesFast()); FillEvent(centrality, step); } //____________________________________________________________________ void AliUEHistograms::FillTrackingEfficiency(TObjArray* mc, TObjArray* recoPrim, TObjArray* recoAll, TObjArray* recoPrimPID, TObjArray* recoAllPID, TObjArray* fake, Int_t particleType, Double_t centrality, Double_t zVtx) { // fills the tracking efficiency objects // // mc: all primary MC particles // recoPrim: reconstructed primaries (again MC particles) // recoAll: reconstructed (again MC particles) // recoPrim: reconstructed primaries with checks on PID (again MC particles) // recoAll: reconstructed with checks on PID (again MC particles) // particleType is: 0 for pion, 1 for kaon, 2 for proton, 3 for others for (Int_t step=0; step<6; step++) { TObjArray* list = mc; if (step == 1) list = recoPrim; else if (step == 2) list = recoAll; else if (step == 3) list = recoPrimPID; else if (step == 4) list = recoAllPID; else if (step == 5) list = fake; if (!list) continue; for (Int_t i=0; iGetEntriesFast(); i++) { AliVParticle* particle = (AliVParticle*) list->UncheckedAt(i); Double_t vars[5]; vars[0] = particle->Eta(); vars[1] = particle->Pt(); vars[2] = particleType; vars[3] = centrality; vars[4] = zVtx; for (Int_t j=0; jGetTrackHistEfficiency()->Fill(vars, step); } } } //____________________________________________________________________ void AliUEHistograms::FillFakePt(TObjArray* fake, Double_t centrality) { TObjArray* tracksReco = (TObjArray*) fake->At(0); TObjArray* tracksMC = (TObjArray*) fake->At(1); if (tracksReco->GetEntriesFast() != tracksMC->GetEntriesFast()) AliFatal(Form("Inconsistent arrays: %d vs %d", tracksReco->GetEntriesFast(), tracksMC->GetEntriesFast())); for (Int_t i=0; iGetEntriesFast(); i++) { AliVParticle* particle1 = (AliVParticle*) tracksReco->At(i); AliVParticle* particle2 = (AliVParticle*) tracksMC->At(i); Double_t vars[3]; vars[0] = particle1->Pt(); vars[1] = particle2->Pt(); vars[2] = centrality; for (Int_t j=0; jGetMCRecoPtCorrelation()->Fill(vars[0],vars[1],vars[2]); } } //____________________________________________________________________ void AliUEHistograms::FillEvent(Int_t eventType, Int_t step) { // fills the number of events at the given step and the given enty type // // WARNING: This function is called from Fill, so only call it for steps where Fill is not called fEventCount->Fill(step, eventType); } //____________________________________________________________________ void AliUEHistograms::FillEvent(Double_t centrality, Int_t step) { // fills the number of events at the given step and the given centrality // // WARNING: This function is called from Fill, so only call it for steps where Fill is not called fEventCount->Fill(step, centrality); } //____________________________________________________________________ void AliUEHistograms::SetEtaRange(Float_t etaMin, Float_t etaMax) { // sets eta min and max for all contained AliUEHist classes for (Int_t i=0; iSetEtaRange(etaMin, etaMax); } //____________________________________________________________________ void AliUEHistograms::SetPtRange(Float_t ptMin, Float_t ptMax) { // sets pT min and max for all contained AliUEHist classes for (Int_t i=0; iSetPtRange(ptMin, ptMax); } //____________________________________________________________________ void AliUEHistograms::SetPartSpecies(Int_t species) { // sets PartSpecie for all contained AliUEHist classes for (Int_t i=0; iSetPartSpecies(species); } //____________________________________________________________________ void AliUEHistograms::SetZVtxRange(Float_t min, Float_t max) { // sets pT min and max for all contained AliUEHist classes for (Int_t i=0; iSetZVtxRange(min, max); } //____________________________________________________________________ void AliUEHistograms::SetContaminationEnhancement(TH1F* hist) { // sets the contamination enhancement histogram in all contained AliUEHist classes for (Int_t i=0; iSetContaminationEnhancement(hist); } //____________________________________________________________________ void AliUEHistograms::SetCombineMinMax(Bool_t flag) { // sets pT min and max for all contained AliUEHist classes for (Int_t i=0; iSetCombineMinMax(flag); } //____________________________________________________________________ void AliUEHistograms::SetTrackEtaCut(Float_t value) { // sets track eta cut for all contained AliUEHist classes for (Int_t i=0; iSetTrackEtaCut(value); } //____________________________________________________________________ void AliUEHistograms::SetWeightPerEvent(Bool_t flag) { // sets fWeightPerEvent for all contained AliUEHist classes fWeightPerEvent = flag; for (Int_t i=0; iSetWeightPerEvent(fWeightPerEvent); } //____________________________________________________________________ void AliUEHistograms::Correct(AliUEHistograms* corrections) { // corrects the contained histograms by calling AliUEHist::Correct for (Int_t i=0; iCorrect(corrections->GetUEHist(i)); } //____________________________________________________________________ AliUEHistograms &AliUEHistograms::operator=(const AliUEHistograms &c) { // assigment operator DeleteContainers(); if (this != &c) ((AliUEHistograms &) c).Copy(*this); return *this; } //____________________________________________________________________ void AliUEHistograms::Copy(TObject& c) const { // copy function AliUEHistograms& target = (AliUEHistograms &) c; if (fNumberDensitypT) target.fNumberDensitypT = dynamic_cast (fNumberDensitypT->Clone()); if (fSumpT) target.fSumpT = dynamic_cast (fSumpT->Clone()); if (fNumberDensityPhi) target.fNumberDensityPhi = dynamic_cast (fNumberDensityPhi->Clone()); if (fCorrelationpT) target.fCorrelationpT = dynamic_cast (fCorrelationpT->Clone()); if (fCorrelationEta) target.fCorrelationEta = dynamic_cast (fCorrelationEta->Clone()); if (fCorrelationPhi) target.fCorrelationPhi = dynamic_cast (fCorrelationPhi->Clone()); if (fCorrelationR) target.fCorrelationR = dynamic_cast (fCorrelationR->Clone()); if (fCorrelationLeading2Phi) target.fCorrelationLeading2Phi = dynamic_cast (fCorrelationLeading2Phi->Clone()); if (fCorrelationMultiplicity) target.fCorrelationMultiplicity = dynamic_cast (fCorrelationMultiplicity->Clone()); if (fYields) target.fYields = dynamic_cast (fYields->Clone()); if (fInvYield2) target.fInvYield2 = dynamic_cast (fInvYield2->Clone()); if (fEventCount) target.fEventCount = dynamic_cast (fEventCount->Clone()); if (fEventCountDifferential) target.fEventCountDifferential = dynamic_cast (fEventCountDifferential->Clone()); if (fVertexContributors) target.fVertexContributors = dynamic_cast (fVertexContributors->Clone()); if (fCentralityDistribution) target.fCentralityDistribution = dynamic_cast (fCentralityDistribution->Clone()); if (fCentralityCorrelation) target.fCentralityCorrelation = dynamic_cast (fCentralityCorrelation->Clone()); if (fITSClusterMap) target.fITSClusterMap = dynamic_cast (fITSClusterMap->Clone()); if (fControlConvResoncances) target.fControlConvResoncances = dynamic_cast (fControlConvResoncances->Clone()); for (Int_t i=0; i<2; i++) if (fTwoTrackDistancePt[i]) target.fTwoTrackDistancePt[i] = dynamic_cast (fTwoTrackDistancePt[i]->Clone()); if (fEfficiencyCorrectionTriggers) target.fEfficiencyCorrectionTriggers = dynamic_cast (fEfficiencyCorrectionTriggers->Clone()); if (fEfficiencyCorrectionAssociated) target.fEfficiencyCorrectionAssociated = dynamic_cast (fEfficiencyCorrectionAssociated->Clone()); target.fSelectCharge = fSelectCharge; target.fTriggerSelectCharge = fTriggerSelectCharge; target.fAssociatedSelectCharge = fAssociatedSelectCharge; target.fTriggerRestrictEta = fTriggerRestrictEta; target.fEtaOrdering = fEtaOrdering; target.fCutConversions = fCutConversions; target.fCutResonances = fCutResonances; target.fOnlyOneEtaSide = fOnlyOneEtaSide; target.fWeightPerEvent = fWeightPerEvent; target.fRunNumber = fRunNumber; target.fMergeCount = fMergeCount; target.fWeightPerEvent = fWeightPerEvent; target.fPtOrder = fPtOrder; target.fTwoTrackCutMinRadius = fTwoTrackCutMinRadius; } //____________________________________________________________________ Long64_t AliUEHistograms::Merge(TCollection* list) { // Merge a list of AliUEHistograms objects with this (needed for // PROOF). // Returns the number of merged objects (including this). if (!list) return 0; if (list->IsEmpty()) return 1; TIterator* iter = list->MakeIterator(); TObject* obj; // collections of objects const Int_t kMaxLists = 20; TList* lists[kMaxLists]; for (Int_t i=0; iNext())) { AliUEHistograms* entry = dynamic_cast (obj); if (entry == 0) continue; if (entry->fNumberDensitypT) lists[0]->Add(entry->fNumberDensitypT); if (entry->fSumpT) lists[1]->Add(entry->fSumpT); if (entry->fNumberDensityPhi) lists[2]->Add(entry->fNumberDensityPhi); lists[3]->Add(entry->fCorrelationpT); lists[4]->Add(entry->fCorrelationEta); lists[5]->Add(entry->fCorrelationPhi); lists[6]->Add(entry->fCorrelationR); lists[7]->Add(entry->fCorrelationLeading2Phi); lists[8]->Add(entry->fCorrelationMultiplicity); lists[9]->Add(entry->fEventCount); lists[10]->Add(entry->fEventCountDifferential); lists[11]->Add(entry->fVertexContributors); lists[12]->Add(entry->fCentralityDistribution); lists[13]->Add(entry->fITSClusterMap); if (entry->fTwoTrackDistancePt[0]) lists[14]->Add(entry->fTwoTrackDistancePt[0]); if (entry->fTwoTrackDistancePt[1]) lists[15]->Add(entry->fTwoTrackDistancePt[1]); if (entry->fCentralityCorrelation) lists[16]->Add(entry->fCentralityCorrelation); if (entry->fYields) lists[17]->Add(entry->fYields); if (entry->fInvYield2) lists[18]->Add(entry->fInvYield2); if (entry->fControlConvResoncances) lists[19]->Add(entry->fControlConvResoncances); fMergeCount += entry->fMergeCount; count++; } if (fNumberDensitypT) fNumberDensitypT->Merge(lists[0]); if (fSumpT) fSumpT->Merge(lists[1]); if (fNumberDensityPhi) fNumberDensityPhi->Merge(lists[2]); fCorrelationpT->Merge(lists[3]); fCorrelationEta->Merge(lists[4]); fCorrelationPhi->Merge(lists[5]); fCorrelationR->Merge(lists[6]); fCorrelationLeading2Phi->Merge(lists[7]); fCorrelationMultiplicity->Merge(lists[8]); fEventCount->Merge(lists[9]); fEventCountDifferential->Merge(lists[10]); fVertexContributors->Merge(lists[11]); fCentralityDistribution->Merge(lists[12]); fITSClusterMap->Merge(lists[13]); if (fTwoTrackDistancePt[0] && lists[14]->GetEntries() > 0) fTwoTrackDistancePt[0]->Merge(lists[14]); if (fTwoTrackDistancePt[1] && lists[15]->GetEntries() > 0) fTwoTrackDistancePt[1]->Merge(lists[15]); if (fCentralityCorrelation) fCentralityCorrelation->Merge(lists[16]); if (fYields && lists[17]->GetEntries() > 0) fYields->Merge(lists[17]); if (fInvYield2 && lists[18]->GetEntries() > 0) fInvYield2->Merge(lists[18]); if (fControlConvResoncances && lists[19]->GetEntries() > 0) fControlConvResoncances->Merge(lists[19]); for (Int_t i=0; iCopyReconstructedData(from->GetUEHist(i)); } void AliUEHistograms::DeepCopy(AliUEHistograms* from) { // copies the entries of this object's members from the object to this object for (Int_t i=0; iGetUEHist(i)) GetUEHist(i)->DeepCopy(from->GetUEHist(i)); } void AliUEHistograms::ExtendTrackingEfficiency(Bool_t verbose) { // delegates to AliUEHists for (Int_t i=0; iExtendTrackingEfficiency(verbose); } void AliUEHistograms::Scale(Double_t factor) { // scales all contained histograms by the given factor for (Int_t i=0; iScale(factor); TList list; list.Add(fCorrelationpT); list.Add(fCorrelationEta); list.Add(fCorrelationPhi); list.Add(fCorrelationR); list.Add(fCorrelationLeading2Phi); list.Add(fCorrelationMultiplicity); list.Add(fYields); list.Add(fInvYield2); list.Add(fEventCount); list.Add(fEventCountDifferential); list.Add(fVertexContributors); list.Add(fCentralityDistribution); list.Add(fCentralityCorrelation); list.Add(fITSClusterMap); list.Add(fTwoTrackDistancePt[0]); list.Add(fTwoTrackDistancePt[1]); list.Add(fControlConvResoncances); for (Int_t i=0; iScale(factor); } void AliUEHistograms::Reset() { // delegates to AliUEHists for (Int_t i=0; iReset(); }