/************************************************************************** * 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 "TH2F.h" #include "TH1F.h" #include "TH3F.h" #include "TMath.h" ClassImp(AliUEHistograms) const Int_t AliUEHistograms::fgkUEHists = 3; AliUEHistograms::AliUEHistograms(const char* name, const char* histograms) : TNamed(name, name), fNumberDensitypT(0), fSumpT(0), fNumberDensityPhi(0), fCorrelationpT(0), fCorrelationEta(0), fCorrelationPhi(0), fCorrelationR(0), fCorrelationLeading2Phi(0), fCorrelationMultiplicity(0), fEventCount(0), fEventCountDifferential(0), fVertexContributors(0), fCentralityDistribution(0), fITSClusterMap(0), fSelectCharge(0), fRunNumber(0) { // Constructor // // the string histograms defines which histograms are created: // 1 = NumberDensitypT // 2 = SumpT // 3 = NumberDensityPhi // 4 = NumberDensityPhiCentrality (other multiplicity for Pb) fTwoTrackDistancePt[0] = 0; fTwoTrackDistancePt[1] = 0; TString histogramsStr(histograms); if (histogramsStr.Contains("1")) fNumberDensitypT = new AliUEHist("NumberDensitypT"); if (histogramsStr.Contains("2")) fSumpT = new AliUEHist("SumpT"); if (histogramsStr.Contains("3")) fNumberDensityPhi = new AliUEHist("NumberDensityPhi"); else if (histogramsStr.Contains("4")) fNumberDensityPhi = new AliUEHist("NumberDensityPhiCentrality"); // do not add this hists to the directory Bool_t oldStatus = TH1::AddDirectoryStatus(); TH1::AddDirectory(kFALSE); if (!histogramsStr.Contains("4")) { 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, -1, 1); 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); if (!histogramsStr.Contains("4")) { 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", ";;count", fNumberDensityPhi->GetEventHist()->GetNBins(1), fNumberDensityPhi->GetEventHist()->GetAxis(1, 0)->GetXbins()->GetArray()); fITSClusterMap = new TH3F("fITSClusterMap", "; its cluster map; centrality; pT", 256, -0.5, 255.5, 20, 0, 100.001, 100, 0, 20); 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), fEventCount(0), fEventCountDifferential(0), fVertexContributors(0), fCentralityDistribution(0), fITSClusterMap(0), fSelectCharge(0), fRunNumber(0) { // // AliUEHistograms copy constructor // fTwoTrackDistancePt[0] = 0; fTwoTrackDistancePt[1] = 0; ((AliUEHistograms &) c).Copy(*this); } //____________________________________________________________________ AliUEHistograms::~AliUEHistograms() { // Destructor 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 (fEventCount) { delete fEventCount; fEventCount = 0; } if (fEventCountDifferential) { delete fEventCountDifferential; fEventCountDifferential = 0; } if (fVertexContributors) { delete fVertexContributors; fVertexContributors = 0; } if (fCentralityDistribution) { delete fCentralityDistribution; fCentralityDistribution = 0; } if (fITSClusterMap) { delete fITSClusterMap; fITSClusterMap = 0; } for (Int_t i=0; i<2; i++) if (fTwoTrackDistancePt[i]) { delete fTwoTrackDistancePt[i]; fTwoTrackDistancePt[i] = 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) { // 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; // 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->At(i))->Eta(); // if particles is not set, just fill event statistics if (particles) { Int_t jMax = particles->GetEntriesFast(); if (mixed) jMax = mixed->GetEntriesFast(); for (Int_t i=0; iGetEntriesFast(); i++) { AliVParticle* triggerParticle = (AliVParticle*) particles->At(i); // some optimization Float_t triggerEta = triggerParticle->Eta(); if (!mixed) { // QA fCorrelationpT->Fill(centrality, triggerParticle->Pt()); fCorrelationEta->Fill(centrality, triggerEta); fCorrelationPhi->Fill(centrality, triggerParticle->Phi()); /* if (dynamic_cast(triggerParticle)) fITSClusterMap->Fill(((AliAODTrack*) triggerParticle)->GetITSClusterMap(), centrality, triggerParticle->Pt());*/ } for (Int_t j=0; jAt(j); else particle = (AliVParticle*) mixed->At(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 for cross-checks) if (mixed && triggerParticle == particle) continue; if (particle->Pt() > triggerParticle->Pt()) 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; } 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(); // fill all in toward region and do not use the other regions fNumberDensityPhi->GetTrackHist(AliUEHist::kToward)->Fill(vars, step, weight); } if (firstTime) { // once per trigger particle Double_t vars[3]; vars[0] = triggerParticle->Pt(); vars[1] = centrality; vars[2] = zVtx; fNumberDensityPhi->GetEventHist()->Fill(vars, step); } } } fCentralityDistribution->Fill(centrality); FillEvent(centrality, step); } //____________________________________________________________________ void AliUEHistograms::FillTrackingEfficiency(TObjArray* mc, TObjArray* recoPrim, TObjArray* recoAll, Int_t particleType, Double_t centrality) { // fills the tracking efficiency objects // // mc: all primary MC particles // recoPrim: reconstructed primaries (again MC particles) // recoAll: reconstructed (again MC particles) // particleType is: 0 for pion, 1 for kaon, 2 for proton, 3 for others for (Int_t step=0; step<3; step++) { TObjArray* list = mc; if (step == 1) list = recoPrim; else if (step == 2) list = recoAll; for (Int_t i=0; iGetEntriesFast(); i++) { AliVParticle* particle = (AliVParticle*) list->At(i); Double_t vars[4]; vars[0] = particle->Eta(); vars[1] = particle->Pt(); vars[2] = particleType; vars[3] = centrality; for (Int_t j=0; jGetTrackHistEfficiency()->Fill(vars, step); } } } //____________________________________________________________________ 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::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::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 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 (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 (fITSClusterMap) target.fITSClusterMap = dynamic_cast (fITSClusterMap->Clone()); for (Int_t i=0; i<2; i++) if (fTwoTrackDistancePt[i]) target.fTwoTrackDistancePt[i] = dynamic_cast (fTwoTrackDistancePt[i]->Clone()); target.fSelectCharge = fSelectCharge; target.fRunNumber = fRunNumber; } //____________________________________________________________________ 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 = 16; 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 (fTwoTrackDistancePt[0]) lists[14]->Add(entry->fTwoTrackDistancePt[0]); if (fTwoTrackDistancePt[1]) lists[15]->Add(entry->fTwoTrackDistancePt[1]); 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]) fTwoTrackDistancePt[0]->Merge(lists[14]); if (fTwoTrackDistancePt[1]) fTwoTrackDistancePt[1]->Merge(lists[15]); for (Int_t i=0; iCopyReconstructedData(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(fEventCount); list.Add(fEventCountDifferential); list.Add(fVertexContributors); list.Add(fCentralityDistribution); list.Add(fITSClusterMap); list.Add(fTwoTrackDistancePt[0]); list.Add(fTwoTrackDistancePt[1]); for (Int_t i=0; iScale(factor); } void AliUEHistograms::Reset() { // delegates to AliUEHists for (Int_t i=0; iReset(); } TObjArray* AliUEHistograms::ApplyTwoTrackCut(TObjArray* tracks) { // takes the input list and applies two-track efficiency cuts // returns the tracks which pass the cuts (if a pair fails the cut, both are removed) // while the cut is applied, control histograms are filled: fTwoTrackDistancePt[i] (i = 0 before, i = 1 after) // the cut has been developed by the HBT group and removes tracks which are spatially close inside the TPC volume // see https://indico.cern.ch/materialDisplay.py?contribId=36&sessionId=6&materialId=slides&confId=142700 if (!fTwoTrackDistancePt[0]) { fTwoTrackDistancePt[0] = new TH3F("fTwoTrackDistancePt[0]", ";#Delta#eta;#Delta#varphi^{*}_{min};#Delta p_{T}", 100, -0.05, 0.05, 400, -0.2, 0.2, 20, 0, 10); fTwoTrackDistancePt[1] = (TH3F*) fTwoTrackDistancePt[0]->Clone("fTwoTrackDistancePt[1]"); } TObjArray* accepted = new TObjArray(*tracks); // Eta() is extremely time consuming, therefore cache it for the inner loop here: TArrayF eta(tracks->GetEntriesFast()); for (Int_t i=0; iGetEntriesFast(); i++) eta[i] = ((AliVParticle*) tracks->At(i))->Eta(); for (Int_t i=0; iGetEntriesFast(); i++) { AliVParticle* particle1 = (AliVParticle*) tracks->At(i); Float_t phi1 = particle1->Phi(); Float_t pt1 = particle1->Pt(); Float_t charge1 = particle1->Charge(); // analyze region for IAA paper if (pt1 < 8 || pt1 > 15) continue; for (Int_t j=0; jGetEntriesFast(); j++) { if (i == j) continue; AliVParticle* particle2 = (AliVParticle*) tracks->At(j); Float_t phi2 = particle2->Phi(); Float_t pt2 = particle2->Pt(); Float_t charge2 = particle2->Charge(); if (pt2 > pt1) continue; // Double_t dpt = TMath::Abs(pt1 - pt2); Float_t deta = eta[i] - eta[j]; Float_t detaabs = TMath::Abs(deta); // optimization /* if (detaabs > 0.05) continue;*/ Bool_t cutPassed = kTRUE; Float_t dphistarmin = 1e5; Float_t dphistarminabs = 1e5; for (Double_t rad=0.8; rad<2.51; rad+=0.01) { Float_t dphistar = phi1 - phi2 - TMath::ASin(charge1 * 0.075 * rad / pt1) + TMath::ASin(charge2 * 0.075 * rad / pt2); Float_t dphistarabs = TMath::Abs(dphistar); if (dphistarabs < dphistarminabs) { dphistarmin = dphistar; dphistarminabs = dphistarabs; } } // hardcoded cut values for the moment if (detaabs < 0.011 && dphistarminabs < 0.01) { cutPassed = kFALSE; //Printf("%d %d failed: %.3f %.3f; %.3f %.3f %.4f; %.2f %.2f (%p %p)", i, j, eta[i], eta[j], phi1, phi2, dphistarminabs, pt1, pt2, particle1, particle2); } fTwoTrackDistancePt[0]->Fill(deta, dphistarmin, pt2); if (cutPassed) fTwoTrackDistancePt[1]->Fill(deta, dphistarmin, pt2); else { // remove tracks from list accepted->Remove(particle1); accepted->Remove(particle2); } } } accepted->Compress(); //Printf("AliUEHistograms::ApplyTwoTrackCut: Accepted %d out of %d tracks", accepted->GetEntriesFast(), tracks->GetEntriesFast()); return accepted; }