ClassImp(AliAnalysisTaskRhoVnModulation)
AliAnalysisTaskRhoVnModulation::AliAnalysisTaskRhoVnModulation() : AliAnalysisTaskEmcalJet("AliAnalysisTaskRhoVnModulation", kTRUE),
- fDebug(0), fRunToyMC(kFALSE), fLocalInit(0), fAttachToEvent(kTRUE), fSemiCentralInclusive(kFALSE), fFillHistograms(kTRUE), fFillQAHistograms(kTRUE), fReduceBinsXByFactor(-1.), fReduceBinsYByFactor(-1.), fNoEventWeightsForQC(kTRUE), fCentralityClasses(0), fPtBinsHybrids(0), fPtBinsJets(0), fUserSuppliedV2(0), fUserSuppliedV3(0), fUserSuppliedR2(0), fUserSuppliedR3(0), fTracksCont(0), fJetsCont(0), fUseScaledRho(0), fNAcceptedTracks(0), fNAcceptedTracksQCn(0), fFitModulationType(kNoFit), fFitGoodnessTest(kChi2Poisson), fQCRecovery(kTryFit), fUsePtWeight(kTRUE), fUsePtWeightErrorPropagation(kTRUE), fDetectorType(kTPC), fFitModulationOptions("QWLI"), fRunModeType(kGrid), fDataType(kESD), fCollisionType(kPbPb), fRandom(0), fRunNumber(-1), fMappedRunNumber(0), fInCentralitySelection(-1), fFitModulation(0), fFitControl(0), fMinPvalue(0.01), fMaxPvalue(1), fNameJetClones(0), fNamePicoTrackClones(0), fNameRho(0), fLocalJetMinEta(-10), fLocalJetMaxEta(-10), fLocalJetMinPhi(-10), fLocalJetMaxPhi(-10), fSoftTrackMinPt(0.15), fSoftTrackMaxPt(5.), fSemiGoodJetMinPhi(0.), fSemiGoodJetMaxPhi(4.), fSemiGoodTrackMinPhi(0.), fSemiGoodTrackMaxPhi(4.), fAbsVertexZ(10), fHistCentrality(0), fHistVertexz(0), fHistRunnumbersPhi(0), fHistRunnumbersEta(0), fHistPvalueCDFROOT(0), fHistPvalueCDFROOTCent(0), fHistChi2ROOTCent(0), fHistPChi2Root(0), fHistPvalueCDF(0), fHistPvalueCDFCent(0), fHistChi2Cent(0), fHistPChi2(0), fHistKolmogorovTest(0), fHistKolmogorovTestCent(0), fHistPKolmogorov(0), fHistRhoStatusCent(0), fMinDisanceRCtoLJ(0), fRandomConeRadius(-1.), fMaxCones(-1), fAbsVnHarmonics(kTRUE), fExcludeLeadingJetsFromFit(1.), fRebinSwapHistoOnTheFly(kTRUE), fPercentageOfFits(10.), fUseV0EventPlaneFromHeader(kTRUE), fExplicitOutlierCut(-1), fMinLeadingHadronPt(0), fSubtractJetPt(kFALSE), fOutputList(0), fOutputListGood(0), fOutputListBad(0), fHistAnalysisSummary(0), fHistSwap(0), fProfV2(0), fProfV2Cumulant(0), fProfV3(0), fProfV3Cumulant(0), fHistPsiControl(0), fHistPsiSpread(0), fHistPsiVZEROA(0), fHistPsiVZEROC(0), fHistPsiVZERO(0), fHistPsiTPC(0), fHistPsiVZEROAV0M(0), fHistPsiVZEROCV0M(0), fHistPsiVZEROVV0M(0), fHistPsiTPCiV0M(0), fHistPsiVZEROATRK(0), fHistPsiVZEROCTRK(0), fHistPsiVZEROTRK(0), fHistPsiTPCTRK(0), fHistRhoVsMult(0), fHistRhoVsCent(0), fHistRhoAVsMult(0), fHistRhoAVsCent(0) {
+ fDebug(0), fRunToyMC(kFALSE), fLocalInit(0), fAttachToEvent(kTRUE), fSemiCentralInclusive(kFALSE), fFillHistograms(kTRUE), fFillQAHistograms(kTRUE), fReduceBinsXByFactor(-1.), fReduceBinsYByFactor(-1.), fNoEventWeightsForQC(kTRUE), fCentralityClasses(0), fPtBinsHybrids(0), fPtBinsJets(0), fExpectedRuns(0), fExpectedSemiGoodRuns(0), fUserSuppliedV2(0), fUserSuppliedV3(0), fUserSuppliedR2(0), fUserSuppliedR3(0), fTracksCont(0), fJetsCont(0), fLeadingJet(0), fUseScaledRho(0), fNAcceptedTracks(0), fNAcceptedTracksQCn(0), fFitModulationType(kNoFit), fFitGoodnessTest(kChi2Poisson), fQCRecovery(kTryFit), fUsePtWeight(kTRUE), fUsePtWeightErrorPropagation(kTRUE), fDetectorType(kTPC), fFitModulationOptions("QWLI"), fRunModeType(kGrid), fDataType(kESD), fCollisionType(kPbPb), fRandom(0), fRunNumber(-1), fMappedRunNumber(0), fInCentralitySelection(-1), fFitModulation(0), fFitControl(0), fMinPvalue(0.01), fMaxPvalue(1), fNameJetClones(0), fNamePicoTrackClones(0), fNameRho(0), fNameSmallRho(""), fCachedRho(0), fLocalJetMinEta(-10), fLocalJetMaxEta(-10), fLocalJetMinPhi(-10), fLocalJetMaxPhi(-10), fSoftTrackMinPt(0.15), fSoftTrackMaxPt(5.), fSemiGoodJetMinPhi(0.), fSemiGoodJetMaxPhi(4.), fSemiGoodTrackMinPhi(0.), fSemiGoodTrackMaxPhi(4.), fAbsVertexZ(10), fHistCentrality(0), fHistVertexz(0), fHistRunnumbersPhi(0), fHistRunnumbersEta(0), fHistPvalueCDFROOT(0), fHistPvalueCDFROOTCent(0), fHistChi2ROOTCent(0), fHistPChi2Root(0), fHistPvalueCDF(0), fHistPvalueCDFCent(0), fHistChi2Cent(0), fHistPChi2(0), fHistKolmogorovTest(0), fHistKolmogorovTestCent(0), fHistPKolmogorov(0), fHistRhoStatusCent(0), fHistUndeterminedRunQA(0), fMinDisanceRCtoLJ(0), fRandomConeRadius(-1.), fMaxCones(-1), fAbsVnHarmonics(kTRUE), fExcludeLeadingJetsFromFit(1.), fRebinSwapHistoOnTheFly(kTRUE), fPercentageOfFits(10.), fUseV0EventPlaneFromHeader(kTRUE), fExplicitOutlierCut(-1), fMinLeadingHadronPt(0), fSubtractJetPt(kFALSE), fOutputList(0), fOutputListGood(0), fOutputListBad(0), fHistAnalysisSummary(0), fHistSwap(0), fProfV2(0), fProfV2Cumulant(0), fProfV3(0), fProfV3Cumulant(0), fHistPsiControl(0), fHistPsiSpread(0), fHistPsiVZEROA(0), fHistPsiVZEROC(0), fHistPsiVZERO(0), fHistPsiTPC(0), fHistPsiVZEROAV0M(0), fHistPsiVZEROCV0M(0), fHistPsiVZEROVV0M(0), fHistPsiTPCiV0M(0), fHistPsiVZEROATRK(0), fHistPsiVZEROCTRK(0), fHistPsiVZEROTRK(0), fHistPsiTPCTRK(0), fHistRhoVsMult(0), fHistRhoVsCent(0), fHistRhoAVsMult(0), fHistRhoAVsCent(0) {
for(Int_t i(0); i < 10; i++) {
fProfV2Resolution[i] = 0;
fProfV3Resolution[i] = 0;
}
//_____________________________________________________________________________
AliAnalysisTaskRhoVnModulation::AliAnalysisTaskRhoVnModulation(const char* name, runModeType type) : AliAnalysisTaskEmcalJet(name, kTRUE),
- fDebug(0), fRunToyMC(kFALSE), fLocalInit(0), fAttachToEvent(kTRUE), fSemiCentralInclusive(kFALSE), fFillHistograms(kTRUE), fFillQAHistograms(kTRUE), fReduceBinsXByFactor(-1.), fReduceBinsYByFactor(-1.), fNoEventWeightsForQC(kTRUE), fCentralityClasses(0), fPtBinsHybrids(0), fPtBinsJets(0), fUserSuppliedV2(0), fUserSuppliedV3(0), fUserSuppliedR2(0), fUserSuppliedR3(0), fTracksCont(0), fJetsCont(0), fUseScaledRho(0), fNAcceptedTracks(0), fNAcceptedTracksQCn(0), fFitModulationType(kNoFit), fFitGoodnessTest(kChi2Poisson), fQCRecovery(kTryFit), fUsePtWeight(kTRUE), fUsePtWeightErrorPropagation(kTRUE), fDetectorType(kTPC), fFitModulationOptions("QWLI"), fRunModeType(type), fDataType(kESD), fCollisionType(kPbPb), fRandom(0), fRunNumber(-1), fMappedRunNumber(0), fInCentralitySelection(-1), fFitModulation(0), fFitControl(0), fMinPvalue(0.01), fMaxPvalue(1), fNameJetClones(0), fNamePicoTrackClones(0), fNameRho(0), fLocalJetMinEta(-10), fLocalJetMaxEta(-10), fLocalJetMinPhi(-10), fLocalJetMaxPhi(-10), fSoftTrackMinPt(0.15), fSoftTrackMaxPt(5.), fSemiGoodJetMinPhi(0.), fSemiGoodJetMaxPhi(4.), fSemiGoodTrackMinPhi(0.), fSemiGoodTrackMaxPhi(4.), fAbsVertexZ(10), fHistCentrality(0), fHistVertexz(0), fHistRunnumbersPhi(0), fHistRunnumbersEta(0), fHistPvalueCDFROOT(0), fHistPvalueCDFROOTCent(0), fHistChi2ROOTCent(0), fHistPChi2Root(0), fHistPvalueCDF(0), fHistPvalueCDFCent(0), fHistChi2Cent(0), fHistPChi2(0), fHistKolmogorovTest(0), fHistKolmogorovTestCent(0), fHistPKolmogorov(0), fHistRhoStatusCent(0), fMinDisanceRCtoLJ(0), fRandomConeRadius(-1.), fMaxCones(-1), fAbsVnHarmonics(kTRUE), fExcludeLeadingJetsFromFit(1.), fRebinSwapHistoOnTheFly(kTRUE), fPercentageOfFits(10.), fUseV0EventPlaneFromHeader(kTRUE), fExplicitOutlierCut(-1), fMinLeadingHadronPt(0), fSubtractJetPt(kFALSE), fOutputList(0), fOutputListGood(0), fOutputListBad(0), fHistAnalysisSummary(0), fHistSwap(0), fProfV2(0), fProfV2Cumulant(0), fProfV3(0), fProfV3Cumulant(0), fHistPsiControl(0), fHistPsiSpread(0), fHistPsiVZEROA(0), fHistPsiVZEROC(0), fHistPsiVZERO(0), fHistPsiTPC(0), fHistPsiVZEROAV0M(0), fHistPsiVZEROCV0M(0), fHistPsiVZEROVV0M(0), fHistPsiTPCiV0M(0), fHistPsiVZEROATRK(0), fHistPsiVZEROCTRK(0), fHistPsiVZEROTRK(0), fHistPsiTPCTRK(0), fHistRhoVsMult(0), fHistRhoVsCent(0), fHistRhoAVsMult(0), fHistRhoAVsCent(0) {
+ fDebug(0), fRunToyMC(kFALSE), fLocalInit(0), fAttachToEvent(kTRUE), fSemiCentralInclusive(kFALSE), fFillHistograms(kTRUE), fFillQAHistograms(kTRUE), fReduceBinsXByFactor(-1.), fReduceBinsYByFactor(-1.), fNoEventWeightsForQC(kTRUE), fCentralityClasses(0), fPtBinsHybrids(0), fPtBinsJets(0), fExpectedRuns(0), fExpectedSemiGoodRuns(0), fUserSuppliedV2(0), fUserSuppliedV3(0), fUserSuppliedR2(0), fUserSuppliedR3(0), fTracksCont(0), fJetsCont(0), fLeadingJet(0), fUseScaledRho(0), fNAcceptedTracks(0), fNAcceptedTracksQCn(0), fFitModulationType(kNoFit), fFitGoodnessTest(kChi2Poisson), fQCRecovery(kTryFit), fUsePtWeight(kTRUE), fUsePtWeightErrorPropagation(kTRUE), fDetectorType(kTPC), fFitModulationOptions("QWLI"), fRunModeType(type), fDataType(kESD), fCollisionType(kPbPb), fRandom(0), fRunNumber(-1), fMappedRunNumber(0), fInCentralitySelection(-1), fFitModulation(0), fFitControl(0), fMinPvalue(0.01), fMaxPvalue(1), fNameJetClones(0), fNamePicoTrackClones(0), fNameRho(0), fNameSmallRho(""), fCachedRho(0), fLocalJetMinEta(-10), fLocalJetMaxEta(-10), fLocalJetMinPhi(-10), fLocalJetMaxPhi(-10), fSoftTrackMinPt(0.15), fSoftTrackMaxPt(5.), fSemiGoodJetMinPhi(0.), fSemiGoodJetMaxPhi(4.), fSemiGoodTrackMinPhi(0.), fSemiGoodTrackMaxPhi(4.), fAbsVertexZ(10), fHistCentrality(0), fHistVertexz(0), fHistRunnumbersPhi(0), fHistRunnumbersEta(0), fHistPvalueCDFROOT(0), fHistPvalueCDFROOTCent(0), fHistChi2ROOTCent(0), fHistPChi2Root(0), fHistPvalueCDF(0), fHistPvalueCDFCent(0), fHistChi2Cent(0), fHistPChi2(0), fHistKolmogorovTest(0), fHistKolmogorovTestCent(0), fHistPKolmogorov(0), fHistRhoStatusCent(0), fHistUndeterminedRunQA(0), fMinDisanceRCtoLJ(0), fRandomConeRadius(-1.), fMaxCones(-1), fAbsVnHarmonics(kTRUE), fExcludeLeadingJetsFromFit(1.), fRebinSwapHistoOnTheFly(kTRUE), fPercentageOfFits(10.), fUseV0EventPlaneFromHeader(kTRUE), fExplicitOutlierCut(-1), fMinLeadingHadronPt(0), fSubtractJetPt(kFALSE), fOutputList(0), fOutputListGood(0), fOutputListBad(0), fHistAnalysisSummary(0), fHistSwap(0), fProfV2(0), fProfV2Cumulant(0), fProfV3(0), fProfV3Cumulant(0), fHistPsiControl(0), fHistPsiSpread(0), fHistPsiVZEROA(0), fHistPsiVZEROC(0), fHistPsiVZERO(0), fHistPsiTPC(0), fHistPsiVZEROAV0M(0), fHistPsiVZEROCV0M(0), fHistPsiVZEROVV0M(0), fHistPsiTPCiV0M(0), fHistPsiVZEROATRK(0), fHistPsiVZEROCTRK(0), fHistPsiVZEROTRK(0), fHistPsiTPCTRK(0), fHistRhoVsMult(0), fHistRhoVsCent(0), fHistRhoAVsMult(0), fHistRhoAVsCent(0) {
for(Int_t i(0); i < 10; i++) {
fProfV2Resolution[i] = 0;
fProfV3Resolution[i] = 0;
if(fFitModulation) delete fFitModulation;
if(fHistSwap) delete fHistSwap;
if(fCentralityClasses) delete fCentralityClasses;
+ if(fExpectedRuns) delete fExpectedRuns;
+ if(fExpectedSemiGoodRuns) delete fExpectedSemiGoodRuns;
if(fFitControl) delete fFitControl;
}
//_____________________________________________________________________________
Double_t c[] = {0., 20., 40., 60., 80., 100.};
fCentralityClasses = new TArrayD(sizeof(c)/sizeof(c[0]), c);
}
+ if(!fExpectedRuns) { // expected runs must be defined at this point
+ Int_t r[] = {167813, 167988, 168066, 168068, 168069, 168076, 168104, 168212, 168311, 168322, 168325, 168341, 168361, 168362, 168458, 168460, 168461, 168992, 169091, 169094, 169138, 169143, 169167, 169417, 169835, 169837, 169838, 169846, 169855, 169858, 169859, 169923, 169956, 170027, 170036, 170081, /* up till here original good TPC list */169975, 169981, 170038, 170040, 170083, 170084, 170085, 170088, 170089, 170091, 170152, 170155, 170159, 170163, 170193, 170195, 170203, 170204, 170205, 170228, 170230, 170264, 170268, 170269, 170270, 170306, 170308, 170309, /* original semi-good tpc list */169415, 169411, 169035, 168988, 168984, 168826, 168777, 168512, 168511, 168467, 168464, 168342, 168310, 168115, 168108, 168107, 167987, 167915, 167903, /*new runs, good according to RCT */ 169238, 169160, 169156, 169148, 169145, 169144 /* run swith missing OROC 8 but seem ok in QA */};
+ fExpectedRuns = new TArrayI(sizeof(r)/sizeof(r[0]), r);
+ }
+ if(!fExpectedSemiGoodRuns) {
+ Int_t r[] = {169975, 169981, 170038, 170040, 170083, 170084, 170085, 170088, 170089, 170091, 170152, 170155, 170159, 170163, 170193, 170195, 170203, 170204, 170205, 170228, 170230, 170264, 170268, 170269, 170270, 170306, 170308, 170309};
+ fExpectedSemiGoodRuns = new TArrayI(sizeof(r)/sizeof(r[0]), r);
+ }
// global QA
fHistCentrality = BookTH1F("fHistCentrality", "centrality", 102, -2, 100);
fHistVertexz = BookTH1F("fHistVertexz", "vertex z (cm)", 100, -12, 12);
// pico track kinematics
for(Int_t i(0); i < fCentralityClasses->GetSize()-1; i++) {
- fHistPicoTrackPt[i] = BookTH1F("fHistPicoTrackPt", "p_{t} [GeV/c]", 100, 0, 50, i);
+ fHistPicoTrackPt[i] = BookTH1F("fHistPicoTrackPt", "p_{t} [GeV/c]", 100, 0, 100, i);
fHistPicoTrackMult[i] = BookTH1F("fHistPicoTrackMult", "multiplicity", 100, 0, 5000, i);
if(fFillQAHistograms) {
fHistPicoCat1[i] = BookTH2F("fHistPicoCat1", "#eta", "#phi", 50, -1, 1, 50, 0, TMath::TwoPi(), i);
fReduceBinsXByFactor = 1;
fReduceBinsYByFactor = 1;
if(fFillQAHistograms) {
- fHistRunnumbersEta = new TH2F("fHistRunnumbersEta", "fHistRunnumbersEta", 100, -.5, 99.5, 100, -1.1, 1.1);
+ fHistRunnumbersEta = new TH2F("fHistRunnumbersEta", "fHistRunnumbersEta", fExpectedRuns->GetSize()+1, -.5, fExpectedRuns->GetSize()+.5, 100, -1.1, 1.1);
fHistRunnumbersEta->Sumw2();
fOutputList->Add(fHistRunnumbersEta);
- fHistRunnumbersPhi = new TH2F("fHistRunnumbersPhi", "fHistRunnumbersPhi", 100, -.5, 99.5, 100, -0.2, TMath::TwoPi()+0.2);
+ fHistRunnumbersPhi = new TH2F("fHistRunnumbersPhi", "fHistRunnumbersPhi", fExpectedRuns->GetSize()+1, -.5, fExpectedRuns->GetSize()+.5, 100, -0.2, TMath::TwoPi()+0.2);
fHistRunnumbersPhi->Sumw2();
fOutputList->Add(fHistRunnumbersPhi);
+ for(Int_t i(0); i < fExpectedRuns->GetSize(); i++) {
+ fHistRunnumbersPhi->GetXaxis()->SetBinLabel(i+1, Form("%i", fExpectedRuns->At(i)));
+ fHistRunnumbersEta->GetXaxis()->SetBinLabel(i+1, Form("%i", fExpectedRuns->At(i)));
+ }
+ fHistRunnumbersPhi->GetXaxis()->SetBinLabel(fExpectedRuns->GetSize()+1, "undetermined");
+ fHistRunnumbersEta->GetXaxis()->SetBinLabel(fExpectedRuns->GetSize()+1, "undetermined");
}
- fHistAnalysisSummary = BookTH1F("fHistAnalysisSummary", "flag", 52, -0.5, 52.5);
+ fHistAnalysisSummary = BookTH1F("fHistAnalysisSummary", "flag", 54, -0.5, 54.5);
fHistSwap = new TH1F("fHistSwap", "fHistSwap", 20, 0, TMath::TwoPi());
if(fUsePtWeight) fHistSwap->Sumw2();
fHistPChi2Root = BookTH2F("fHistPChi2Root", "p-value", "#tilde{#chi^{2}} ROOT", 1000, 0, 1, 100, 0, 5);
fHistPKolmogorov = BookTH2F("fHistPKolmogorov", "p-value", "kolmogorov p",40, 0, 1, 40, 0, 1);
fHistRhoStatusCent = BookTH2F("fHistRhoStatusCent", "centrality", "status [-1=lin was better, 0=ok, 1 = failed]", 101, -1, 100, 3, -1.5, 1.5);
+ fHistUndeterminedRunQA = BookTH1F("fHistUndeterminedRunQA", "runnumber", 10, 0, 10);
PostData(1, fOutputList);
if(!fLocalInit) fLocalInit = InitializeAnalysis();
// reject the event if expected data is missing
if(!PassesCuts(InputEvent())) return kFALSE;
- if(!fCaloClusters && fDebug > 0) printf(" > Warning: couldn't retreive calo clusters! < \n");
+ fLeadingJet = GetLeadingJet(); // store the leading jet
// set the rho value
fLocalRho->SetVal(fRho->GetVal());
// [0][0] psi2a [1,0] psi2c
}
// if all went well, update the local rho parameter
fLocalRho->SetLocalRho(fFitModulation);
- // fill a number of histograms
- if(fFillHistograms) FillHistogramsAfterSubtraction(psi2, psi3, vzero, vzeroComb, tpc);
+ // fill a number of histograms. event qa needs to be filled first as it also determines the runnumber for the track qa
if(fFillQAHistograms) FillQAHistograms(InputEvent());
+ if(fFillHistograms) FillHistogramsAfterSubtraction(psi2, psi3, vzero, vzeroComb, tpc);
// send the output to the connected output container
PostData(1, fOutputList);
switch (fRunModeType) {
if(fTracks) {
Float_t excludeInEta = -999;
if(fExcludeLeadingJetsFromFit > 0 ) { // remove the leading jet from ep estimate
- AliEmcalJet* leadingJet(GetJetContainer()->GetLeadingJet());
- if(leadingJet) excludeInEta = leadingJet->Eta();
+ if(fLeadingJet) excludeInEta = fLeadingJet->Eta();
}
Int_t iTracks(fTracks->GetEntriesFast());
for(Int_t iTPC(0); iTPC < iTracks; iTPC++) {
// in all cases, a cut can be made on the p-value of the chi-squared value of the fit
// and a check can be performed to see if rho has no negative local minimum
if(fDebug > 0) printf("__FILE__ = %s \n __LINE __ %i , __FUNC__ %s \n ", __FILE__, __LINE__, __func__);
+ Int_t freeParams(2); // free parameters of the fit (for NDF)
switch (fFitModulationType) { // for approaches where no fitting is required
case kQC2 : {
fFitModulation->FixParameter(4, psi2);
Double_t excludeInPt = -999;
if(iTracks <= 0 || fLocalRho->GetVal() <= 0 ) return kFALSE; // no use fitting an empty event ...
if(fExcludeLeadingJetsFromFit > 0 ) {
- AliEmcalJet* leadingJet(GetJetContainer()->GetLeadingJet());
- if(leadingJet) {
- excludeInEta = leadingJet->Eta();
- excludeInPhi = leadingJet->Phi();
- excludeInPt = leadingJet->Pt();
+ if(fLeadingJet) {
+ excludeInEta = fLeadingJet->Eta();
+ excludeInPhi = fLeadingJet->Phi();
+ excludeInPt = fLeadingJet->Pt();
}
}
// check the acceptance of the track selection that will be used
fFitModulation->SetParameter(0, fLocalRho->GetVal());
switch (fFitModulationType) {
- case kNoFit : { fFitModulation->FixParameter(0, fLocalRho->GetVal() );
+ case kNoFit : {
+ fFitModulation->FixParameter(0, fLocalRho->GetVal() );
+ freeParams = 0;
} break;
case kV2 : {
fFitModulation->FixParameter(4, psi2);
+ freeParams = 1;
} break;
case kV3 : {
fFitModulation->FixParameter(4, psi3);
+ freeParams = 1;
} break;
case kCombined : {
fFitModulation->FixParameter(4, psi2);
fFitModulation->FixParameter(6, psi3);
+ freeParams = 2;
} break;
case kFourierSeries : {
// in this approach, an explicit calculation will be made of vn = sqrt(xn^2+yn^2)
_tempSwap.Fit(fFitModulation, fFitModulationOptions.Data(), "", lowBound, upBound);
// the quality of the fit is evaluated from 1 - the cdf of the chi square distribution
// three methods are available, all with their drawbacks. all are stored, one is selected to do the cut
- Double_t CDF(1.-ChiSquareCDF(fFitModulation->GetNDF(), ChiSquare(_tempSwap, fFitModulation)));
- Double_t CDFROOT(1.-ChiSquareCDF(fFitModulation->GetNDF(), fFitModulation->GetChisquare()));
+ Int_t NDF(_tempSwap.GetXaxis()->GetNbins()-freeParams);
+ if(NDF == 0) return kFALSE;
+ Double_t CDF(1.-ChiSquareCDF(NDF, ChiSquare(_tempSwap, fFitModulation)));
+ Double_t CDFROOT(1.-ChiSquareCDF(NDF, fFitModulation->GetChisquare()));
Double_t CDFKolmogorov(KolmogorovTest(_tempSwap, fFitModulation));
// fill the values and centrality correlation (redundant but easy on the eyes)
fHistPvalueCDF->Fill(CDF);
fHistPvalueCDFROOT->Fill(CDFROOT);
fHistPvalueCDFROOTCent->Fill(fCent, CDFROOT);
fHistKolmogorovTest->Fill(CDFKolmogorov);
- fHistChi2ROOTCent->Fill(fCent, fFitModulation->GetChisquare()/((float)fFitModulation->GetNDF()));
- fHistChi2Cent->Fill(fCent, ChiSquare(_tempSwap, fFitModulation)/((float)fFitModulation->GetNDF()));
+ fHistChi2ROOTCent->Fill(fCent, fFitModulation->GetChisquare()/((float)NDF));
+ fHistChi2Cent->Fill(fCent, ChiSquare(_tempSwap, fFitModulation)/((float)NDF));
fHistKolmogorovTestCent->Fill(fCent, CDFKolmogorov);
- fHistPChi2Root->Fill(CDFROOT, fFitModulation->GetChisquare()/((float)fFitModulation->GetNDF()));
- fHistPChi2->Fill(CDF, ChiSquare(_tempSwap, fFitModulation)/((float)fFitModulation->GetNDF()));
+ fHistPChi2Root->Fill(CDFROOT, fFitModulation->GetChisquare()/((float)NDF));
+ fHistPChi2->Fill(CDF, ChiSquare(_tempSwap, fFitModulation)/((float)NDF));
fHistPKolmogorov->Fill(CDF, CDFKolmogorov);
// variable CDF is used for making cuts, so we fill it with the selected p-value
v2->SetParameter(3, didacticFit->GetParameter(3)); // v2
v2->FixParameter(1, 1.); // constant
v2->FixParameter(2, 2.); // constant
+ v2->FixParameter(4, didacticFit->GetParameter(4)); // psi2
v2->SetLineColor(kGreen);
didacticProfile->GetListOfFunctions()->Add(v2);
- TF1* v3(new TF1("dfit_kV3", "[0]*([1]+[2]*[3]*TMath::Cos([2]*(x-[4])))", 0, TMath::TwoPi()));
+ TF1* v3(new TF1("dfit_kV3", "[0]*([1]+[2]*[3]*TMath::Cos([5]*(x-[4])))", 0, TMath::TwoPi()));
v3->SetParameter(0, didacticFit->GetParameter(0)); // normalization
v3->SetParameter(3, didacticFit->GetParameter(7)); // v3
v3->FixParameter(1, 1.); // constant
- v3->FixParameter(2, 3.); // constant
+ v3->FixParameter(2, 2.); // constant
+ v3->FixParameter(4, didacticFit->GetParameter(6)); // psi3
+ v3->FixParameter(5, 3.); // constant
v3->SetLineColor(kYellow);
didacticProfile->GetListOfFunctions()->Add(v3);
}
{
// event cuts
if(fDebug > 0) printf("__FILE__ = %s \n __LINE __ %i , __FUNC__ %s \n ", __FILE__, __LINE__, __func__);
+ // determine the run number to see if the track and jet cuts should be refreshed for semi-good TPC runs
+ // only done if the runnumber changes, could be moved to a call to AliAnalysisTaskSE::Notify()
+ if(fRunNumber != InputEvent()->GetRunNumber()) {
+ fRunNumber = InputEvent()->GetRunNumber(); // set the current run number
+ if(fDebug > 0) printf("__FUNC__ %s > NEW RUNNUMBER DETECTED \n ", __func__);
+ // reset the cuts. should be a pointless operation except for the case where the run number changes
+ // from semi-good back to good on one node, which is not a likely scenario
+ AliAnalysisTaskEmcal::SetTrackPhiLimits(-10., 10.);
+ AliAnalysisTaskEmcalJet::SetJetPhiLimits(-10., 10.);
+ if(fCachedRho) { // if there's a cached rho, it's the default, so switch back
+ if(fDebug > 0) printf("__FUNC__ %s > replacing rho with cached rho \n ", __func__);
+ fRho = fCachedRho; // reset rho back to cached value. again, should be pointless
+ }
+ Bool_t flaggedAsSemiGood(kFALSE); // not flagged as anything
+ for(Int_t i(0); i < fExpectedSemiGoodRuns->GetSize(); i++) {
+ if(fExpectedSemiGoodRuns->At(i) == fRunNumber) { // run is semi-good
+ if(fDebug > 0) printf("__FUNC__ %s > semi-good tpc run detected, adjusting acceptance \n ", __func__);
+ flaggedAsSemiGood = kTRUE;
+ AliAnalysisTaskEmcalJet::SetJetPhiLimits(fSemiGoodJetMinPhi, fSemiGoodJetMaxPhi); // just an acceptance cut, jets are obtained from full azimuth, so no edge effects
+ AliAnalysisTaskEmcal::SetTrackPhiLimits(fSemiGoodTrackMinPhi, fSemiGoodTrackMaxPhi); // only affects vn extraction, NOT jet finding
+ // for semi-good runs, also try to get the 'small rho' estimate, if it is available
+ AliRhoParameter* tempRho(dynamic_cast<AliRhoParameter*>(InputEvent()->FindListObject(fNameSmallRho.Data())));
+ if(tempRho) {
+ if(fDebug > 0) printf("__FUNC__ %s > switching to small rho, caching normal rho \n ", __func__);
+ fHistAnalysisSummary->SetBinContent(54, 1.); // bookkeep the fact that small rho is used
+ fCachedRho = fRho; // cache the original rho ...
+ fRho = tempRho; // ... and use the small rho
+ }
+ }
+ }
+ if(!flaggedAsSemiGood) {
+ // in case the run is not a semi-good run, check if it is recognized as another run
+ // only done to catch unexpected runs
+ for(Int_t i(0); i < fExpectedRuns->GetSize(); i++) {
+ if(fExpectedRuns->At(i) == fRunNumber) break; // run is known, break the loop else store the number in a random bin
+ fHistUndeterminedRunQA->SetBinContent(TMath::Nint(10.*gRandom->Uniform(0.,.9))+1, fRunNumber);
+ }
+ fHistAnalysisSummary->SetBinContent(53, 1.); // bookkeep which rho estimate is used
+ }
+ }
+ // continue with event selection
if(!event || !AliAnalysisTaskEmcal::IsEventSelected()) return kFALSE;
if(fSemiCentralInclusive && ! (event->GetTriggerMask() & (ULong64_t(1)<<7))) return kFALSE;
if(TMath::Abs(InputEvent()->GetPrimaryVertex()->GetZ()) > 10.) return kFALSE;
if(fExplicitOutlierCut == 2010 || fExplicitOutlierCut == 2011) {
if(!PassesCuts(fExplicitOutlierCut)) return kFALSE;
}
- if(fRho->GetVal() <= 0 ) return kFALSE;
if(fTracks->GetEntries() < 1) return kFALSE;
- if(fRunNumber != InputEvent()->GetRunNumber()) {
- fRunNumber = InputEvent()->GetRunNumber(); // set the current run number
- if(fDebug > 0 ) printf("> NEW RUNNNUMBER DETECTED: %i <\n", fRunNumber);
- // determine the run number to see if the track and jet cuts should be refreshed for semi-good TPC runs
- Int_t semiGoodTPCruns[] = {169975, 169981, 170038, 170040, 170083, 170084, 170085, 170088, 170089, 170091, 170152, 170155, 170159, 170163, 170193, 170195, 170203, 170204, 170205, 170228, 170230, 170264, 170268, 170269, 170270, 170306, 170308, 170309};
- for(Int_t i(0); i < (int)(sizeof(semiGoodTPCruns)/sizeof(semiGoodTPCruns[0])); i++) {
- if(semiGoodTPCruns[i] == fRunNumber) { // run is semi-good
- if(fDebug > 0) printf(" > SEMI-GOOD TPC DETECTED, adjusting acceptance accordingly ... <\n");
- AliAnalysisTaskEmcalJet::SetJetPhiLimits(fSemiGoodJetMinPhi, fSemiGoodJetMaxPhi);
- AliAnalysisTaskEmcal::SetTrackPhiLimits(fSemiGoodTrackMinPhi, fSemiGoodTrackMaxPhi);
- }
- }
- }
+ if(fRho->GetVal() <= 0 ) return kFALSE;
return kTRUE;
}
//_____________________________________________________________________________
// fill delta pt histograms
if(fDebug > 0) printf("__FILE__ = %s \n __LINE __ %i , __FUNC__ %s \n ", __FILE__, __LINE__, __func__);
Int_t i(0);
- AliEmcalJet* leadingJet(GetJetContainer()->GetLeadingJet());
- if(!leadingJet && fDebug > 0) printf(" > failed to retrieve leading jet ! < \n");
const Float_t areaRC = fRandomConeRadius*fRandomConeRadius*TMath::Pi();
// we're retrieved the leading jet, now get a random cone
for(i = 0; i < fMaxCones; i++) {
fHistDeltaPtDeltaPhi3[fInCentralitySelection]->Fill(PhaseShift(phi-psi3, 3.), pt - areaRC*fLocalRho->GetLocalVal(phi, GetJetContainer()->GetJetRadius(), fLocalRho->GetVal()));
}
// get a random cone excluding leading jet area
- CalculateRandomCone(pt, eta, phi, leadingJet);
+ CalculateRandomCone(pt, eta, phi, fLeadingJet);
if(pt > 0) {
if(fFillQAHistograms) fHistRCPhiEtaExLJ[fInCentralitySelection]->Fill(phi, eta);
fHistRhoVsRCPtExLJ[fInCentralitySelection]->Fill(pt, fLocalRho->GetLocalVal(phi, GetJetContainer()->GetJetRadius(), fLocalRho->GetVal())*areaRC);
fHistVertexz->Fill(vevent->GetPrimaryVertex()->GetZ());
fHistCentrality->Fill(fCent);
Int_t runNumber(InputEvent()->GetRunNumber());
- Int_t runs[] = {167813, 167988, 168066, 168068, 168069, 168076, 168104, 168212, 168311, 168322, 168325, 168341, 168361, 168362, 168458, 168460, 168461, 168992, 169091, 169094, 169138, 169143, 169167, 169417, 169835, 169837, 169838, 169846, 169855, 169858, 169859, 169923, 169956, 170027, 170036, 170081, 169975, 169981, 170038, 170040, 170083, 170084, 170085, 170088, 170089, 170091, 170152, 170155, 170159, 170163, 170193, 170195, 170203, 170204, 170205, 170228, 170230, 170264, 170268, 170269, 170270, 170306, 170308, 170309};
- for(fMappedRunNumber = 0; fMappedRunNumber < 64; fMappedRunNumber++) {
- if(runs[fMappedRunNumber]==runNumber) break;
+ for(fMappedRunNumber = 0; fExpectedRuns->GetSize()+1; fMappedRunNumber++) {
+ if(fExpectedRuns->At(fMappedRunNumber) == runNumber) break;
}
}
//_____________________________________________________________________________
fHistAnalysisSummary->SetBinContent(51, fMaxCones);
fHistAnalysisSummary->GetXaxis()->SetBinLabel(52, "fUseScaledRho");
fHistAnalysisSummary->SetBinContent(52, fUseScaledRho);
+ fHistAnalysisSummary->GetXaxis()->SetBinLabel(53, "used rho");
+ fHistAnalysisSummary->GetXaxis()->SetBinLabel(54, "used small rho");
}
//_____________________________________________________________________________
void AliAnalysisTaskRhoVnModulation::Terminate(Option_t *)
switch (fRunModeType) {
case kLocal : {
printf("__FILE__ = %s \n __LINE __ %i , __FUNC__ %s \n ", __FILE__, __LINE__, __func__);
- if(fFillQAHistograms) {
- Int_t runs[] = {167813, 167988, 168066, 168068, 168069, 168076, 168104, 168212, 168311, 168322, 168325, 168341, 168361, 168362, 168458, 168460, 168461, 168992, 169091, 169094, 169138, 169143, 169167, 169417, 169835, 169837, 169838, 169846, 169855, 169858, 169859, 169923, 169956, 170027, 170036, 170081, 169975, 169981, 170038, 170040, 170083, 170084, 170085, 170088, 170089, 170091, 170152, 170155, 170159, 170163, 170193, 170195, 170203, 170204, 170205, 170228, 170230, 170264, 170268, 170269, 170270, 170306, 170308, 170309};
- for(Int_t i(0); i < 64; i++) {
- fHistRunnumbersPhi->GetXaxis()->SetBinLabel(i+1, Form("%i", runs[i]));
- fHistRunnumbersEta->GetXaxis()->SetBinLabel(i+1, Form("%i", runs[i]));
- }
- fHistRunnumbersPhi->GetXaxis()->SetBinLabel(65, "undetermined");
- fHistRunnumbersEta->GetXaxis()->SetBinLabel(65, "undetermined");
- }
AliAnalysisTaskRhoVnModulation::Dump();
for(Int_t i(0); i < fHistAnalysisSummary->GetXaxis()->GetNbins(); i++) printf( " > flag: %s \t content %.2f \n", fHistAnalysisSummary->GetXaxis()->GetBinLabel(1+i), fHistAnalysisSummary->GetBinContent(1+i));
} break;
git://git.uio.no / u / mrichter / AliRoot.git / blobdiff