]> git.uio.no Git - u/mrichter/AliRoot.git/blame - PWGJE/EMCALJetTasks/AliAnalysisTaskLocalRhoDev.cxx
git://git.uio.no / u / mrichter / AliRoot.git / blame
? search:
summary | shortlog | log | commit | commitdiff | tree
blob | blame (incremental) | history | HEAD
setter to assume pion mass for clusters
[u/mrichter/AliRoot.git] / PWGJE / EMCALJetTasks / AliAnalysisTaskLocalRhoDev.cxx
CommitLineData
9a902ff9 1// $Id$
2//
3// Analysis task to estimate an event's local energy density
4//
5// This task is part of the emcal jet framework and should be run in the emcaljet train
6// The following extensions to an accepted AliVEvent are expected:
7// - (anti-kt) jets -> necessary if one wants to exclude leading jet contribution to the event plane
8// - background estimate of rho -> this task estimates modulation, not rho itself
9// - pico tracks -> a uniform track selection is necessary to estimate the contribution of v_n harmonics
10// aod's and esd's are handled transparently
11// The task will estimates a phi-dependent background density rho
12// which is added to the event as a AliLocalRhoParamter object
13//
14// Author: Redmer Alexander Bertens, Utrecht Univeristy, Utrecht, Netherlands
15// (rbertens@cern.ch, rbertens@nikhef.nl, r.a.bertens@uu.nl)
16
17// root includes
18#include <TStyle.h>
19#include <TRandom3.h>
20#include <TChain.h>
21#include <TMath.h>
22#include <TF1.h>
23#include <TF2.h>
24#include <TH1F.h>
25#include <TH2F.h>
26#include <TProfile.h>
27#include <TArrayI.h>
28// aliroot includes
29#include <AliAnalysisTask.h>
30#include <AliAnalysisManager.h>
31#include <AliCentrality.h>
32#include <AliVVertex.h>
33#include <AliESDEvent.h>
34#include <AliAODEvent.h>
35#include <AliAODTrack.h>
36// emcal jet framework includes
37#include <AliPicoTrack.h>
38#include <AliEmcalJet.h>
39#include <AliRhoParameter.h>
40#include <AliLocalRhoParameter.h>
41#include <AliAnalysisTaskLocalRhoDev.h>
42
43class AliAnalysisTaskLocalRhoDev;
44using namespace std;
45
46ClassImp(AliAnalysisTaskLocalRhoDev)
47
48//_____________________________________________________________________________
49AliAnalysisTaskLocalRhoDev::AliAnalysisTaskLocalRhoDev() :
50 AliAnalysisTaskEmcalJet("AliAnalysisTaskLocalRhoDev", kTRUE),
51 fDebug(0), fInitialized(0), fAttachToEvent(kTRUE), fFillHistograms(kFALSE), fNoEventWeightsForQC(kTRUE),
52 fUseScaledRho(0), fCentralityClasses(0), fUserSuppliedV2(0), fUserSuppliedV3(0), fUserSuppliedR2(0),
53 fUserSuppliedR3(0), fNAcceptedTracks(0), fNAcceptedTracksQCn(0), fInCentralitySelection(-1), fFitModulationType(kCombined),
54 fFitGoodnessTest(kChi2Poisson), fQCRecovery(kTryFit), fUsePtWeight(kTRUE), fUsePtWeightErrorPropagation(kFALSE), fDetectorType(kTPC),
55 fFitModulationOptions("WLQI"), fRunModeType(kGrid), fFitModulation(0), fFitControl(0x0), fMinPvalue(0.01), fMaxPvalue(1), fExpectedRuns(0x0),
56 fExpectedSemiGoodRuns(0x0), fRunNumber(-1), fCachedRho(0x0), fNameSmallRho(""), fLocalJetMinEta(-10), fLocalJetMaxEta(-10),
57 fLocalJetMinPhi(-10), fLocalJetMaxPhi(-10), fSoftTrackMinPt(0.15),
58 fSoftTrackMaxPt(5.), fSemiGoodJetMinPhi(0.), fSemiGoodJetMaxPhi(4.), fSemiGoodTrackMinPhi(0.), fSemiGoodTrackMaxPhi(4.),
59 fHistPvalueCDFROOT(0x0), fHistPvalueCDFROOTCent(0x0), fHistChi2ROOTCent(0x0), fHistPChi2Root(0x0), fHistPvalueCDF(0x0), fHistPvalueCDFCent(0x0),
60 fHistChi2Cent(0x0), fHistPChi2(0x0), fHistRhoStatusCent(0), fAbsVnHarmonics(kTRUE), fExcludeLeadingJetsFromFit(1.),
61 fRebinSwapHistoOnTheFly(kTRUE), fPercentageOfFits(10.), fUseV0EventPlaneFromHeader(kTRUE), fOutputList(0),
62 fOutputListGood(0), fOutputListBad(0), fHistSwap(0), fHistAnalysisSummary(0), fProfV2(0), fProfV2Cumulant(0),
63 fProfV3(0), fProfV3Cumulant(0)
64{
65 // Default constructor
66
67 for(Int_t i(0); i < 10; i++) {
68 fHistPsi2[i] = 0;
69 fHistPsi3[i] = 0;
70 }
71}
72
73//_____________________________________________________________________________
74AliAnalysisTaskLocalRhoDev::AliAnalysisTaskLocalRhoDev(const char* name, runModeType type) :
75 AliAnalysisTaskEmcalJet(name, kTRUE),
76 fDebug(0), fInitialized(0), fAttachToEvent(kTRUE), fFillHistograms(kFALSE), fNoEventWeightsForQC(kTRUE),
77 fUseScaledRho(0), fCentralityClasses(0), fUserSuppliedV2(0), fUserSuppliedV3(0), fUserSuppliedR2(0),
78 fUserSuppliedR3(0), fNAcceptedTracks(0), fNAcceptedTracksQCn(0), fInCentralitySelection(-1), fFitModulationType(kCombined),
79 fFitGoodnessTest(kChi2Poisson), fQCRecovery(kTryFit), fUsePtWeight(kTRUE), fUsePtWeightErrorPropagation(kFALSE), fDetectorType(kTPC),
80 fFitModulationOptions("WLQI"), fRunModeType(type), fFitModulation(0), fFitControl(0x0), fMinPvalue(0.01), fMaxPvalue(1), fExpectedRuns(0x0),
81 fExpectedSemiGoodRuns(0x0), fRunNumber(-1), fCachedRho(0x0), fNameSmallRho(""), fLocalJetMinEta(-10), fLocalJetMaxEta(-10),
82 fLocalJetMinPhi(-10), fLocalJetMaxPhi(-10), fSoftTrackMinPt(0.15),
83 fSoftTrackMaxPt(5.), fSemiGoodJetMinPhi(0.), fSemiGoodJetMaxPhi(4.), fSemiGoodTrackMinPhi(0.), fSemiGoodTrackMaxPhi(4.),
84 fHistPvalueCDFROOT(0x0), fHistPvalueCDFROOTCent(0x0), fHistChi2ROOTCent(0x0), fHistPChi2Root(0x0), fHistPvalueCDF(0x0), fHistPvalueCDFCent(0x0),
85 fHistChi2Cent(0x0), fHistPChi2(0x0), fHistRhoStatusCent(0), fAbsVnHarmonics(kTRUE), fExcludeLeadingJetsFromFit(1.),
86 fRebinSwapHistoOnTheFly(kTRUE), fPercentageOfFits(10.), fUseV0EventPlaneFromHeader(kTRUE), fOutputList(0),
87 fOutputListGood(0), fOutputListBad(0), fHistSwap(0), fHistAnalysisSummary(0), fProfV2(0), fProfV2Cumulant(0),
88 fProfV3(0), fProfV3Cumulant(0)
89{
90 // Constructor
91 for(Int_t i(0); i < 10; i++) {
92 fHistPsi2[i] = 0;
93 fHistPsi3[i] = 0;
94 }
95
96 DefineInput(0, TChain::Class());
97 DefineOutput(1, TList::Class());
98 switch (fRunModeType) {
99 case kLocal : {
100 gStyle->SetOptFit(1);
101 DefineOutput(2, TList::Class());
102 DefineOutput(3, TList::Class());
103 } break;
104 default: fDebug = -1; // suppress debug info explicitely when not running locally
105 }
106}
107
108//_____________________________________________________________________________
109AliAnalysisTaskLocalRhoDev::~AliAnalysisTaskLocalRhoDev()
110{
111 // destructor
112 if(fOutputList) delete fOutputList;
113 if(fOutputListGood) delete fOutputListGood;
114 if(fOutputListBad) delete fOutputListBad;
115 if(fFitModulation) delete fFitModulation;
116 if(fHistSwap) delete fHistSwap;
117}
118
119//_____________________________________________________________________________
120void AliAnalysisTaskLocalRhoDev::ExecOnce()
121{
122 // Init the analysis
123 if(fLocalRhoName=="") fLocalRhoName = Form("LocalRhoFrom_%s", GetName());
124 fLocalRho = new AliLocalRhoParameter(fLocalRhoName.Data(), 0);
125 // add the local rho to the event if necessary
126 if(fAttachToEvent) {
127 if(!(InputEvent()->FindListObject(fLocalRho->GetName()))) {
128 InputEvent()->AddObject(fLocalRho);
129 } else {
130 AliFatal(Form("%s: Container with same name %s already present. Aborting", GetName(), fLocalRho->GetName()));
131 }
132 }
133 AliAnalysisTaskEmcalJet::ExecOnce(); // init the base clas
134 if(fUseScaledRho) {
135 // unscaled rho has been retrieved by the parent class, now we retrieve rho scaled
136 fRho = dynamic_cast<AliRhoParameter*>(InputEvent()->FindListObject(Form("%s_Scaled", fRho->GetName())));
137 if(!fRho) {
138 AliFatal(Form("%s: Couldn't find container for scaled rho. Aborting !", GetName()));
139 }
140 }
141 if(!GetJetContainer()) AliFatal(Form("%s: Couldn't get jet container. Aborting !", GetName()));
142}
143
144//_____________________________________________________________________________
145Bool_t AliAnalysisTaskLocalRhoDev::InitializeAnalysis()
146{
147 // Initialize the anaysis
148
149 if(fDebug > 0) printf("__FILE__ = %s \n __LINE __ %i , __FUNC__ %s \n ", __FILE__, __LINE__, __func__);
150 if(fLocalJetMinEta > -10 && fLocalJetMaxEta > -10) SetJetEtaLimits(fLocalJetMinEta, fLocalJetMaxEta);
151 if(fLocalJetMinPhi > -10 && fLocalJetMaxPhi > -10) SetJetPhiLimits(fLocalJetMinPhi, fLocalJetMaxPhi);
152 switch (fFitModulationType) {
153 case kNoFit : { SetModulationFit(new TF1("fit_kNoFit", "[0]", 0, TMath::TwoPi())); } break;
154 case kV2 : {
155 SetModulationFit(new TF1("fit_kV2", "[0]*([1]+[2]*[3]*TMath::Cos([2]*(x-[4])))", 0, TMath::TwoPi()));
156 fFitModulation->SetParameter(0, 0.); // normalization
157 fFitModulation->SetParameter(3, 0.2); // v2
158 fFitModulation->FixParameter(1, 1.); // constant
159 fFitModulation->FixParameter(2, 2.); // constant
160 } break;
161 case kV3: {
162 SetModulationFit(new TF1("fit_kV3", "[0]*([1]+[2]*[3]*TMath::Cos([2]*(x-[4])))", 0, TMath::TwoPi()));
163 fFitModulation->SetParameter(0, 0.); // normalization
164 fFitModulation->SetParameter(3, 0.2); // v3
165 fFitModulation->FixParameter(1, 1.); // constant
166 fFitModulation->FixParameter(2, 3.); // constant
167 } break;
168 default : { // for the combined fit, the 'direct fourier series' or the user supplied vn values we use v2 and v3
169 SetModulationFit(new TF1("fit_kCombined", "[0]*([1]+[2]*([3]*TMath::Cos([2]*(x-[4]))+[7]*TMath::Cos([5]*(x-[6]))))", 0, TMath::TwoPi()));
170 fFitModulation->SetParameter(0, 0.); // normalization
171 fFitModulation->SetParameter(3, 0.2); // v2
172 fFitModulation->FixParameter(1, 1.); // constant
173 fFitModulation->FixParameter(2, 2.); // constant
174 fFitModulation->FixParameter(5, 3.); // constant
175 fFitModulation->SetParameter(7, 0.2); // v3
176 } break;
177 }
178 switch (fRunModeType) {
179 case kGrid : { fFitModulationOptions += "N0"; } break;
180 default : break;
181 }
182 FillAnalysisSummaryHistogram();
183 return kTRUE;
184}
185
186//_____________________________________________________________________________
187void AliAnalysisTaskLocalRhoDev::UserCreateOutputObjects()
188{
189 // create output objects
190 if(fDebug > 0) printf("__FILE__ = %s \n __LINE __ %i , __FUNC__ %s \n ", __FILE__, __LINE__, __func__);
191 fHistSwap = new TH1F("fHistSwap", "fHistSwap", 20, 0, TMath::TwoPi());
192 if(!fCentralityClasses) { // classes must be defined at this point
193 Double_t c[] = {0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100};
194 fCentralityClasses = new TArrayD(sizeof(c)/sizeof(c[0]), c);
195 }
196 if(!fExpectedRuns) { // expected runs must be defined at this point
197 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 */};
198 fExpectedRuns = new TArrayI(sizeof(r)/sizeof(r[0]), r);
199 }
200 if(!fExpectedSemiGoodRuns) {
201 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};
202 fExpectedSemiGoodRuns = new TArrayI(sizeof(r)/sizeof(r[0]), r);
203 }
204 fOutputList = new TList();
205 fOutputList->SetOwner(kTRUE);
206 // the analysis summary histo which stores all the analysis flags is always written to file
207 fHistAnalysisSummary = BookTH1F("fHistAnalysisSummary", "flag", 54, -0.5, 54.5);
208 if(!fFillHistograms) {
209 PostData(1, fOutputList);
210 return;
211 }
212 for(Int_t i(0); i < fCentralityClasses->GetSize()-1; i++) {
213 fHistPsi2[i] = BookTH1F("fHistPsi2", "#Psi_{2}", 100, -.5*TMath::Pi(), .5*TMath::Pi(), i);
214 fHistPsi3[i] = BookTH1F("fHistPsi3", "#Psi_{3}", 100, -1.*TMath::Pi()/3., TMath::Pi()/3., i);
215 }
216 // cdf of chisquare distribution
217 fHistPvalueCDF = BookTH1F("fHistPvalueCDF", "CDF #chi^{2}", 500, 0, 1);
218 fHistRhoStatusCent = BookTH2F("fHistRhoStatusCent", "centrality", "status [0=ok, 1=failed]", 101, -1, 100, 2, -.5, 1.5);
219 // vn profiles
220 Float_t temp[fCentralityClasses->GetSize()];
221 for(Int_t i(0); i < fCentralityClasses->GetSize(); i++) temp[i] = fCentralityClasses->At(i);
222 fProfV2 = new TProfile("fProfV2", "fProfV2", fCentralityClasses->GetSize()-1, temp);
223 fProfV3 = new TProfile("fProfV3", "fProfV3", fCentralityClasses->GetSize()-1, temp);
224 fOutputList->Add(fProfV2);
225 fOutputList->Add(fProfV3);
226 switch (fFitModulationType) {
227 case kQC2 : {
228 fProfV2Cumulant = new TProfile("fProfV2Cumulant", "fProfV2Cumulant", fCentralityClasses->GetSize()-1, temp);
229 fProfV3Cumulant = new TProfile("fProfV3Cumulant", "fProfV3Cumulant", fCentralityClasses->GetSize()-1, temp);
230 fOutputList->Add(fProfV2Cumulant);
231 fOutputList->Add(fProfV3Cumulant);
232 } break;
233 case kQC4 : {
234 fProfV2Cumulant = new TProfile("fProfV2Cumulant", "fProfV2Cumulant", fCentralityClasses->GetSize()-1, temp);
235 fProfV3Cumulant = new TProfile("fProfV3Cumulant", "fProfV3Cumulant", fCentralityClasses->GetSize()-1, temp);
236 fOutputList->Add(fProfV2Cumulant);
237 fOutputList->Add(fProfV3Cumulant);
238 } break;
239 default : break;
240 }
241 if(fUsePtWeight) fHistSwap->Sumw2();
242 if(fUserSuppliedV2) fOutputList->Add(fUserSuppliedV2);
243 if(fUserSuppliedV3) fOutputList->Add(fUserSuppliedV3);
244 if(fUserSuppliedR2) fOutputList->Add(fUserSuppliedR2);
245 if(fUserSuppliedR3) fOutputList->Add(fUserSuppliedR3);
246
247 // increase readability of output list
248 fOutputList->Sort();
249
250 // cdf and pdf of chisquare distribution
251 fHistPvalueCDF = BookTH1F("fHistPvalueCDF", "CDF #chi^{2}", 50, 0, 1);
252 fHistPvalueCDFCent = BookTH2F("fHistPvalueCDFCent", "centrality", "p-value", 40, 0, 100, 40, 0, 1);
253 fHistChi2Cent = BookTH2F("fHistChi2Cent", "centrality", "#tilde{#chi^{2}}", 100, 0, 100, 100, 0, 5);
254 fHistPChi2 = BookTH2F("fHistPChi2", "p-value", "#tilde{#chi^{2}}", 1000, 0, 1, 100, 0, 5);
255 fHistPvalueCDFROOT = BookTH1F("fHistPvalueCDFROOT", "CDF #chi^{2} ROOT", 50, 0, 1);
256 fHistPvalueCDFROOTCent = BookTH2F("fHistPvalueCDFROOTCent", "centrality", "p-value ROOT", 40, 0, 100, 45, 0, 1);
257 fHistChi2ROOTCent = BookTH2F("fHistChi2ROOTCent", "centrality", "#tilde{#chi^{2}}", 40, 0, 100, 45, 0, 5);
258 fHistPChi2Root = BookTH2F("fHistPChi2Root", "p-value", "#tilde{#chi^{2}} ROOT", 1000, 0, 1, 100, 0, 5);
259 fHistRhoStatusCent = BookTH2F("fHistRhoStatusCent", "centrality", "status [-1=lin was better, 0=ok, 1 = failed]", 101, -1, 100, 3, -1.5, 1.5);
260
261 PostData(1, fOutputList);
262 switch (fRunModeType) {
263 case kLocal : {
264 fOutputListGood = new TList();
265 fOutputListGood->SetOwner(kTRUE);
266 fOutputListBad = new TList();
267 fOutputListBad->SetOwner(kTRUE);
268 PostData(2, fOutputListGood);
269 PostData(3, fOutputListBad);
270 } break;
271 default: break;
272 }
273}
274
275//_____________________________________________________________________________
276TH1F* AliAnalysisTaskLocalRhoDev::BookTH1F(const char* name, const char* x, Int_t bins, Double_t min, Double_t max, Int_t c, Bool_t append)
277{
278 // Book a TH1F and connect it to the output container
279
280 if(fDebug > 0) printf("__FILE__ = %s \n __LINE __ %i , __FUNC__ %s \n ", __FILE__, __LINE__, __func__);
281 if(!fOutputList) return 0x0;
282 TString title(name);
283 if(c!=-1) { // format centrality dependent histograms accordingly
284 name = Form("%s_%i", name, c);
285 title += Form("_%i-%i", (int)fCentralityClasses->At(c), (int)fCentralityClasses->At(1+c));
286 }
287 title += Form(";%s;[counts]", x);
288 TH1F* histogram = new TH1F(name, title.Data(), bins, min, max);
289 histogram->Sumw2();
290 if(append) fOutputList->Add(histogram);
291 return histogram;
292}
293
294//_____________________________________________________________________________
295TH2F* AliAnalysisTaskLocalRhoDev::BookTH2F(const char* name, const char* x, const char*y, Int_t binsx, Double_t minx, Double_t maxx,
296 Int_t binsy, Double_t miny, Double_t maxy, Int_t c, Bool_t append)
297{
298 // Book a TH2F and connect it to the output container
299
300 if(fDebug > 0) printf("__FILE__ = %s \n __LINE __ %i , __FUNC__ %s \n ", __FILE__, __LINE__, __func__);
301 if(!fOutputList) return 0x0;
302 TString title(name);
303 if(c!=-1) { // format centrality dependent histograms accordingly
304 name = Form("%s_%i", name, c);
305 title += Form("_%i-%i", (int)fCentralityClasses->At(c), (int)fCentralityClasses->At(1+c));
306 }
307 title += Form(";%s;%s", x, y);
308 TH2F* histogram = new TH2F(name, title.Data(), binsx, minx, maxx, binsy, miny, maxy);
309 histogram->Sumw2();
310 if(append) fOutputList->Add(histogram);
311 return histogram;
312}
313
314//_____________________________________________________________________________
315Bool_t AliAnalysisTaskLocalRhoDev::Run()
316{
317 // Execute once for each event
318
319 if(fDebug > 0) printf("__FILE__ = %s \n __LINE __ %i , __FUNC__ %s \n ", __FILE__, __LINE__, __func__);
320 if(!(PassesCuts(InputEvent())||fTracks||fJets||fRho)) return kFALSE;
321 if(!fInitialized) fInitialized = InitializeAnalysis();
322 // get the centrality bin (necessary for some control histograms
323 fInCentralitySelection = -1;
324 Double_t cent(InputEvent()->GetCentrality()->GetCentralityPercentile("V0M"));
325 for(Int_t i(0); i < fCentralityClasses->GetSize()-1; i++) {
326 if(cent >= fCentralityClasses->At(i) && cent <= fCentralityClasses->At(1+i)) {
327 fInCentralitySelection = i;
328 break; }
329 }
330 if(fInCentralitySelection < 0) return kFALSE;
331 // set the rho value
332 fLocalRho->SetVal(fRho->GetVal());
333 // set the correct event plane accordign to the requested reference detector
334 Double_t psi2(-1), psi3(-1);
335 switch (fDetectorType) { // determine the detector type for the rho fit
336 case kTPC : {
337 // [0] psi2 [1] psi3
338 Double_t tpc[2];
339 CalculateEventPlaneTPC(tpc);
340 psi2 = tpc[0]; psi3 = tpc[1];
341 } break;
342 case kVZEROA : {
343 // [0][0] psi2a [1,0] psi2c
344 // [0][1] psi3a [1,1] psi3c
345 Double_t vzero[2][2];
346 CalculateEventPlaneVZERO(vzero);
347 psi2 = vzero[0][0]; psi3 = vzero[0][1];
348 } break;
349 case kVZEROC : {
350 // [0][0] psi2a [1,0] psi2c
351 // [0][1] psi3a [1,1] psi3c
352 Double_t vzero[2][2];
353 CalculateEventPlaneVZERO(vzero);
354 psi2 = vzero[1][0]; psi3 = vzero[1][1];
355 } break;
356 case kVZEROComb : {
357 /* for the combined vzero event plane
358 * [0] psi2 [1] psi3
359 * not fully implmemented yet, use with caution ! */
360 Double_t vzeroComb[2];
361 CalculateEventPlaneCombinedVZERO(vzeroComb);
362 psi2 = vzeroComb[0]; psi3 = vzeroComb[1];
363 } break;
364 default : break;
365 }
366 if(fFillHistograms) FillEventPlaneHistograms(psi2, psi3);
367 switch (fFitModulationType) { // do the fits
368 case kNoFit : { fFitModulation->FixParameter(0, fLocalRho->GetVal()); } break;
369 case kV2 : { // only v2
370 if(CorrectRho(psi2, psi3)) {
371 if(fFillHistograms) fProfV2->Fill(fCent, fFitModulation->GetParameter(3));
372 if(fUserSuppliedR2) {
373 Double_t r(fUserSuppliedR2->GetBinContent(fUserSuppliedR2->GetXaxis()->FindBin(fCent)));
374 if(r > 0) fFitModulation->SetParameter(3, fFitModulation->GetParameter(3)/r);
375 }
376 }
377 } break;
378 case kV3 : { // only v3
379 if(CorrectRho(psi2, psi3)) {
380 if(fUserSuppliedR3) {
381 Double_t r(fUserSuppliedR3->GetBinContent(fUserSuppliedR3->GetXaxis()->FindBin(fCent)));
382 if(r > 0) fFitModulation->SetParameter(3, fFitModulation->GetParameter(3)/r);
383 }
384 if(fFillHistograms) fProfV3->Fill(fCent, fFitModulation->GetParameter(3));
385 }
386 } break;
387 case kQC2 : { // qc2 analysis - NOTE: not a wise idea to use this !
388 if(CorrectRho(psi2, psi3)) {
389 if(fUserSuppliedR2 && fUserSuppliedR3) {
390 // note for the qc method, resolution is REVERSED to go back to v2obs
391 Double_t r2(fUserSuppliedR2->GetBinContent(fUserSuppliedR2->GetXaxis()->FindBin(fCent)));
392 Double_t r3(fUserSuppliedR3->GetBinContent(fUserSuppliedR3->GetXaxis()->FindBin(fCent)));
393 if(r2 > 0) fFitModulation->SetParameter(3, fFitModulation->GetParameter(3)*r2);
394 if(r3 > 0) fFitModulation->SetParameter(7, fFitModulation->GetParameter(7)*r3);
395 }
396 if (fUsePtWeight) { // use weighted weights
397 Double_t dQCnM11 = (fNoEventWeightsForQC) ? 1. : QCnM11();
398 if(fFillHistograms) {
399 fProfV2->Fill(fCent, fFitModulation->GetParameter(3), dQCnM11);
400 fProfV3->Fill(fCent, fFitModulation->GetParameter(7), dQCnM11);
401 }
402 } else {
403 Double_t dQCnM = (fNoEventWeightsForQC) ? 2. : QCnM();
404 if(fFillHistograms) {
405 fProfV2->Fill(fCent, fFitModulation->GetParameter(3), dQCnM*(dQCnM-1));
406 fProfV3->Fill(fCent, fFitModulation->GetParameter(7), dQCnM*(dQCnM-1));
407 }
408 }
409 }
410 } break;
411 case kQC4 : { // NOTE: see comment at kQC2
412 if(CorrectRho(psi2, psi3)) {
413 if(fUserSuppliedR2 && fUserSuppliedR3) {
414 // note for the qc method, resolution is REVERSED to go back to v2obs
415 Double_t r2(fUserSuppliedR2->GetBinContent(fUserSuppliedR2->GetXaxis()->FindBin(fCent)));
416 Double_t r3(fUserSuppliedR3->GetBinContent(fUserSuppliedR3->GetXaxis()->FindBin(fCent)));
417 if(r2 > 0) fFitModulation->SetParameter(3, fFitModulation->GetParameter(3)*r2);
418 if(r3 > 0) fFitModulation->SetParameter(7, fFitModulation->GetParameter(7)*r3);
419 }
420 if (fUsePtWeight) { // use weighted weights
421 if(fFillHistograms) {
422 fProfV2->Fill(fCent, TMath::Power(fFitModulation->GetParameter(3),0.5)/*, QCnM1111()*/);
423 fProfV3->Fill(fCent, TMath::Power(fFitModulation->GetParameter(7),0.5)/*, QCnM1111()*/);
424 }
425 } else {
426 if(fFillHistograms) {
427 fProfV2->Fill(fCent, TMath::Power(fFitModulation->GetParameter(3),0.5)/*, QCnM()*(QCnM()-1)*(QCnM()-2)*(QCnM()-3)*/);
428 fProfV3->Fill(fCent, TMath::Power(fFitModulation->GetParameter(7),0.5)/*, QCnM()*(QCnM()-1)*(QCnM()-2)*(QCnM()-3)*/);
429 }
430 }
431 }
432 } break;
433 default : {
434 if(CorrectRho(psi2, psi3)) {
435 if(fUserSuppliedR2 && fUserSuppliedR3) {
436 Double_t r2(fUserSuppliedR2->GetBinContent(fUserSuppliedR2->GetXaxis()->FindBin(fCent)));
437 Double_t r3(fUserSuppliedR3->GetBinContent(fUserSuppliedR3->GetXaxis()->FindBin(fCent)));
438 if(r2 > 0) fFitModulation->SetParameter(3, fFitModulation->GetParameter(3)/r2);
439 if(r3 > 0) fFitModulation->SetParameter(7, fFitModulation->GetParameter(7)/r3);
440 }
441 if(fFillHistograms) {
442 fProfV2->Fill(fCent, fFitModulation->GetParameter(3));
443 fProfV3->Fill(fCent, fFitModulation->GetParameter(7));
444 }
445 }
446 } break;
447 }
448 // if all went well, add local rho
449 fLocalRho->SetLocalRho(fFitModulation);
450 PostData(1, fOutputList);
451 return kTRUE;
452}
453
454//_____________________________________________________________________________
455void AliAnalysisTaskLocalRhoDev::CalculateEventPlaneVZERO(Double_t vzero[2][2]) const
456{
457 // Get the vzero event plane
458 if(fUseV0EventPlaneFromHeader) {
459 // use the vzero event plane from the event header
460 // note: to use the calibrated vzero event plane, run
461 // $ALICE_ROOT/ANALYSIS/macros/AddTaskVZEROEPSelection.C
462 // prior to this task (make sure the calibration is available for the dataset
463 // you want to use)
464 Double_t a(0), b(0), c(0), d(0), e(0), f(0), g(0), h(0);
465 vzero[0][0] = InputEvent()->GetEventplane()->CalculateVZEROEventPlane(InputEvent(), 8, 2, a, b);
466 vzero[1][0] = InputEvent()->GetEventplane()->CalculateVZEROEventPlane(InputEvent(), 9, 2, c, d);
467 vzero[0][1] = InputEvent()->GetEventplane()->CalculateVZEROEventPlane(InputEvent(), 8, 3, e, f);
468 vzero[1][1] = InputEvent()->GetEventplane()->CalculateVZEROEventPlane(InputEvent(), 9, 3, g, h);
469 return;
470 }
471 // grab the vzero event plane without recentering
472 if(fDebug > 0) printf("__FILE__ = %s \n __LINE __ %i , __FUNC__ %s \n ", __FILE__, __LINE__, __func__);
473 Double_t qxa2(0), qya2(0), qxc2(0), qyc2(0); // for psi2
474 Double_t qxa3(0), qya3(0), qxc3(0), qyc3(0); // for psi3
475 for(Int_t iVZERO(0); iVZERO < 64; iVZERO++) {
476 Double_t phi(TMath::PiOver4()*(.5+iVZERO%8)), /* eta(0), */ weight(InputEvent()->GetVZEROEqMultiplicity(iVZERO));
477 // (iVZERO<32) ? eta = -3.45+.5*(iVZERO/8) : eta = 4.8-.6*((iVZERO/8)-4);
478 if(iVZERO<32) {
479 qxa2 += weight*TMath::Cos(2.*phi);
480 qya2 += weight*TMath::Sin(2.*phi);
481 qxa3 += weight*TMath::Cos(3.*phi);
482 qya3 += weight*TMath::Sin(3.*phi);
483 }
484 else {
485 qxc2 += weight*TMath::Cos(2.*phi);
486 qyc2 += weight*TMath::Sin(2.*phi);
487 qxc3 += weight*TMath::Cos(3.*phi);
488 qyc3 += weight*TMath::Sin(3.*phi);
489 }
490 }
491 vzero[0][0] = .5*TMath::ATan2(qya2, qxa2);
492 vzero[1][0] = .5*TMath::ATan2(qyc2, qxc2);
493 vzero[0][1] = (1./3.)*TMath::ATan2(qya3, qxa3);
494 vzero[1][1] = (1./3.)*TMath::ATan2(qyc3, qxc3);
495}
496
497//_____________________________________________________________________________
498void AliAnalysisTaskLocalRhoDev::CalculateEventPlaneTPC(Double_t* tpc)
499{
500 // Grab the TPC event plane. if parameter fExcludeLeadingJetsFromFit is larger than 0,
501 // strip in eta of width fExcludeLeadingJetsFromFit * GetJetContainer()->GetJetRadius() around the leading jet (before
502 // subtraction of rho) will be exluded from the event plane estimate
503
504 if(fDebug > 0) printf("__FILE__ = %s \n __LINE __ %i , __FUNC__ %s \n ", __FILE__, __LINE__, __func__);
505 fNAcceptedTracks = 0; // reset the track counter
506 Double_t qx2(0), qy2(0); // for psi2
507 Double_t qx3(0), qy3(0); // for psi3
508 if(fTracks) {
509 Float_t excludeInEta = -999;
510 if(fExcludeLeadingJetsFromFit > 0 ) { // remove the leading jet from ep estimate
511 AliEmcalJet* leadingJet(GetJetContainer()->GetLeadingJet());
512 if(leadingJet) excludeInEta = leadingJet->Eta();
513 }
514 Int_t iTracks(fTracks->GetEntriesFast());
515 for(Int_t iTPC(0); iTPC < iTracks; iTPC++) {
516 AliVTrack* track = static_cast<AliVTrack*>(fTracks->At(iTPC));
517 if(!PassesCuts(track) || track->Pt() < fSoftTrackMinPt || track->Pt() > fSoftTrackMaxPt) continue;
518 if(fExcludeLeadingJetsFromFit > 0 &&( (TMath::Abs(track->Eta() - excludeInEta) < GetJetContainer()->GetJetRadius()*fExcludeLeadingJetsFromFit ) || (TMath::Abs(track->Eta()) - GetJetContainer()->GetJetRadius() - GetJetContainer()->GetJetEtaMax() ) > 0 )) continue;
519 fNAcceptedTracks++;
520 qx2+= TMath::Cos(2.*track->Phi());
521 qy2+= TMath::Sin(2.*track->Phi());
522 qx3+= TMath::Cos(3.*track->Phi());
523 qy3+= TMath::Sin(3.*track->Phi());
524 }
525 }
526 tpc[0] = .5*TMath::ATan2(qy2, qx2);
527 tpc[1] = (1./3.)*TMath::ATan2(qy3, qx3);
528}
529
530//_____________________________________________________________________________
531void AliAnalysisTaskLocalRhoDev::CalculateEventPlaneCombinedVZERO(Double_t* comb) const
532{
533 // Grab the combined vzero event plane
534
535 // if(fUseV0EventPlaneFromHeader) { // use the vzero from the header
536 Double_t a(0), b(0), c(0), d(0);
537 comb[0] = InputEvent()->GetEventplane()->CalculateVZEROEventPlane(InputEvent(), 10, 2, a, b);
538 comb[1] = InputEvent()->GetEventplane()->CalculateVZEROEventPlane(InputEvent(), 10, 3, c, d);
539 // FIXME the rest of this function isn't impelmented yet (as of 01-07-2013)
540 // this means a default the combined vzero event plane from the header is used
541 // to get this value 'by hand', vzeroa and vzeroc event planes have to be combined
542 // according to their resolution - this will be added ...
543 //
544 // } else {
545 // Double_t qx2a(0), qy2a(0), qx2c(0), qy2c(0), qx3a(0), qy3a(0), qx3c(0), qy3c(0);
546 // InputEvent()->GetEventplane()->CalculateVZEROEventPlane(InputEvent(), 8, 2, qx2a, qy2a);
547 // InputEvent()->GetEventplane()->CalculateVZEROEventPlane(InputEvent(), 9, 2, qx2c, qy2c);
548 // InputEvent()->GetEventplane()->CalculateVZEROEventPlane(InputEvent(), 8, 3, qx3a, qy3a);
549 // InputEvent()->GetEventplane()->CalculateVZEROEventPlane(InputEvent(), 9, 3, qx3c, qy3c);
550 // Double_t chi2A(-1), chi2C(-1), chi3A(-1), chi3C(-1); // get chi from the resolution
551 // Double_t qx2(chi2A*chi2A*qx2a+chi2C*chi2C*qx2c);
552 // Double_t qy2(chi2A*chi2A*qy2a+chi2C*chi2C*qy2c);
553 // Double_t qx3(chi3A*chi3A*qx3a+chi3C*chi3C*qx3c);
554 // Double_t qy3(chi3A*chi3A*qy3a+chi3C*chi3C*qy3c);
555 // comb[0] = .5*TMath::ATan2(qy2, qx2);
556 // comb[1] = (1./3.)*TMath::ATan2(qy3, qx3);
557 // }
558}
559
560//_____________________________________________________________________________
561Double_t AliAnalysisTaskLocalRhoDev::CalculateQC2(Int_t harm)
562{
563 // Get the second order q-cumulant, a -999 return will be caught in the qa routine of CorrectRho
564
565 if(fDebug > 0) printf("__FILE__ = %s \n __LINE __ %i , __FUNC__ %s \n ", __FILE__, __LINE__, __func__);
566 Double_t reQ(0), imQ(0), modQ(0), M11(0), M(0);
567 if(fUsePtWeight) { // for the weighted 2-nd order q-cumulant
568 QCnQnk(harm, 1, reQ, imQ); // get the weighted 2-nd order q-vectors
569 modQ = reQ*reQ+imQ*imQ; // get abs Q-squared
570 M11 = QCnM11(); // equals S2,1 - S1,2
571 return (M11 > 0) ? ((modQ - QCnS(1,2))/M11) : -999;
572 } // else return the non-weighted 2-nd order q-cumulant
573 QCnQnk(harm, 0, reQ, imQ); // get the non-weighted 2-nd order q-vectors
574 modQ = reQ*reQ+imQ*imQ; // get abs Q-squared
575 M = QCnM();
576 return (M > 1) ? (modQ - M)/(M*(M-1)) : -999;
577}
578
579//_____________________________________________________________________________
580Double_t AliAnalysisTaskLocalRhoDev::CalculateQC4(Int_t harm)
581{
582 // Get the fourth order q-cumulant, a -999 return will be caught in the qa routine of CorrectRho
583
584 if(fDebug > 0) printf("__FILE__ = %s \n __LINE __ %i , __FUNC__ %s \n ", __FILE__, __LINE__, __func__);
585 Double_t reQn1(0), imQn1(0), reQ2n2(0), imQ2n2(0), reQn3(0), imQn3(0), M1111(0), M(0);
586 Double_t a(0), b(0), c(0), d(0), e(0), f(0), g(0); // terms of the calculation
587 if(fUsePtWeight) { // for the weighted 4-th order q-cumulant
588 QCnQnk(harm, 1, reQn1, imQn1);
589 QCnQnk(harm*2, 2, reQ2n2, imQ2n2);
590 QCnQnk(harm, 3, reQn3, imQn3);
591 // fill in the terms ...
592 a = (reQn1*reQn1+imQn1*imQn1)*(reQn1*reQn1+imQn1*imQn1);
593 b = reQ2n2*reQ2n2 + imQ2n2*imQ2n2;
594 c = -2.*(reQ2n2*reQn1*reQn1-reQ2n2*imQn1*imQn1+2.*imQ2n2*reQn1*imQn1);
595 d = 8.*(reQn3*reQn1+imQn3*imQn1);
596 e = -4.*QCnS(1,2)*(reQn1*reQn1+imQn1*imQn1);
597 f = -6.*QCnS(1,4);
598 g = 2.*QCnS(2,2);
599 M1111 = QCnM1111();
600 return (M1111 > 0) ? (a+b+c+d+e+f+g)/M1111 : -999;
601 } // else return the unweighted case
602 Double_t reQn(0), imQn(0), reQ2n(0), imQ2n(0);
603 QCnQnk(harm, 0, reQn, imQn);
604 QCnQnk(harm*2, 0, reQ2n, imQ2n);
605 // fill in the terms ...
606 M = QCnM();
607 if(M < 4) return -999;
608 a = (reQn*reQn+imQn*imQn)*(reQn*reQn+imQn*imQn);
609 b = reQ2n*reQ2n + imQ2n*imQ2n;
610 c = -2.*(reQ2n*reQn*reQn-reQ2n*imQn*imQn+2.*imQ2n*reQn*imQn);
611 e = -4.*(M-2)*(reQn*reQn+imQn*imQn);
612 f = 2.*M*(M-3);
613 return (a+b+c+e+f)/(M*(M-1)*(M-2)*(M-3));
614}
615
616//_____________________________________________________________________________
617void AliAnalysisTaskLocalRhoDev::QCnQnk(Int_t n, Int_t k, Double_t &reQ, Double_t &imQ)
618{
619 // Get the weighted n-th order q-vector, pass real and imaginary part as reference
620
621 if(fDebug > 0) printf("__FILE__ = %s \n __LINE __ %i , __FUNC__ %s \n ", __FILE__, __LINE__, __func__);
622 if(!fTracks) return;
623 fNAcceptedTracksQCn = 0;
624 Int_t iTracks(fTracks->GetEntriesFast());
625 for(Int_t iTPC(0); iTPC < iTracks; iTPC++) {
626 AliVTrack* track = static_cast<AliVTrack*>(fTracks->At(iTPC));
627 if(!PassesCuts(track) || track->Pt() < fSoftTrackMinPt || track->Pt() > fSoftTrackMaxPt) continue;
628 fNAcceptedTracksQCn++;
629 // for the unweighted case, k equals zero and the weight doesn't contribute to the equation below
630 reQ += TMath::Power(track->Pt(), k) * TMath::Cos(((double)n)*track->Phi());
631 imQ += TMath::Power(track->Pt(), k) * TMath::Sin(((double)n)*track->Phi());
632 }
633}
634
635//_____________________________________________________________________________
636Double_t AliAnalysisTaskLocalRhoDev::QCnS(Int_t i, Int_t j)
637{
638 // Get the weighted ij-th order autocorrelation correction
639
640 if(fDebug > 0) printf("__FILE__ = %s \n __LINE __ %i , __FUNC__ %s \n ", __FILE__, __LINE__, __func__);
641 if(!fTracks || i <= 0 || j <= 0) return -999;
642 Int_t iTracks(fTracks->GetEntriesFast());
643 Double_t Sij(0);
644 for(Int_t iTPC(0); iTPC < iTracks; iTPC++) {
645 AliVTrack* track = static_cast<AliVTrack*>(fTracks->At(iTPC));
646 if(!PassesCuts(track) || track->Pt() < fSoftTrackMinPt || track->Pt() > fSoftTrackMaxPt) continue;
647 Sij+=TMath::Power(track->Pt(), j);
648 }
649 return TMath::Power(Sij, i);
650}
651
652//_____________________________________________________________________________
653Double_t AliAnalysisTaskLocalRhoDev::QCnM()
654{
655 // Get multiplicity for unweighted q-cumulants. function QCnQnk should be called first
656
657 if(fDebug > 0) printf("__FILE__ = %s \n __LINE __ %i , __FUNC__ %s \n ", __FILE__, __LINE__, __func__);
658 return (Double_t) fNAcceptedTracksQCn;
659}
660
661//_____________________________________________________________________________
662Double_t AliAnalysisTaskLocalRhoDev::QCnM11()
663{
664 // Get multiplicity weights for the weighted two particle cumulant
665
666 if(fDebug > 0) printf("__FILE__ = %s \n __LINE __ %i , __FUNC__ %s \n ", __FILE__, __LINE__, __func__);
667 return (QCnS(2,1) - QCnS(1,2));
668}
669
670//_____________________________________________________________________________
671Double_t AliAnalysisTaskLocalRhoDev::QCnM1111()
672{
673 // Get multiplicity weights for the weighted four particle cumulant
674
675 if(fDebug > 0) printf("__FILE__ = %s \n __LINE __ %i , __FUNC__ %s \n ", __FILE__, __LINE__, __func__);
676 return (QCnS(4,1)-6*QCnS(1,2)*QCnS(2,1)+8*QCnS(1,3)*QCnS(1,1)+3*QCnS(2,2)-6*QCnS(1,4));
677}
678
679//_____________________________________________________________________________
680Bool_t AliAnalysisTaskLocalRhoDev::QCnRecovery(Double_t psi2, Double_t psi3)
681{
682 // Decides how to deal with the situation where c2 or c3 is negative
683 // Returns kTRUE depending on whether or not a modulated rho is used for the jet background
684
685 if(fDebug > 0) printf("__FILE__ = %s \n __LINE __ %i , __FUNC__ %s \n ", __FILE__, __LINE__, __func__);
686 if(TMath::AreEqualAbs(fFitModulation->GetParameter(3), .0, 1e-10) && TMath::AreEqualAbs(fFitModulation->GetParameter(7), .0,1e-10)) {
687 fFitModulation->SetParameter(7, 0);
688 fFitModulation->SetParameter(3, 0);
689 fFitModulation->SetParameter(0, fLocalRho->GetVal());
690 return kTRUE; // v2 and v3 have physical null values
691 }
692 switch (fQCRecovery) {
693 case kFixedRho : { // roll back to the original rho
694 fFitModulation->SetParameter(7, 0);
695 fFitModulation->SetParameter(3, 0);
696 fFitModulation->SetParameter(0, fLocalRho->GetVal());
697 return kFALSE; // rho is forced to be fixed
698 }
699 case kNegativeVn : {
700 Double_t c2(fFitModulation->GetParameter(3));
701 Double_t c3(fFitModulation->GetParameter(7));
702 if( c2 < 0 ) c2 = -1.*TMath::Sqrt(-1.*c2);
703 if( c3 < 0 ) c3 = -1.*TMath::Sqrt(-1.*c3);
704 fFitModulation->SetParameter(3, c2);
705 fFitModulation->SetParameter(7, c3);
706 return kTRUE; // is this a physical quantity ?
707 }
708 case kTryFit : {
709 fitModulationType tempType(fFitModulationType); // store temporarily
710 fFitModulationType = kCombined;
711 fFitModulation->SetParameter(7, 0);
712 fFitModulation->SetParameter(3, 0);
713 Bool_t pass(CorrectRho(psi2, psi3)); // do the fit and all quality checks
714 fFitModulationType = tempType; // roll back for next event
715 return pass;
716 }
717 default : return kFALSE;
718 }
719 return kFALSE;
720}
721
722//_____________________________________________________________________________
723Bool_t AliAnalysisTaskLocalRhoDev::CorrectRho(Double_t psi2, Double_t psi3)
724{
725 // Get rho' -> rho(phi)
726 // three routines are available, 1 and 2 can be used with or without pt weights
727 // [1] get vn from q-cumulants
728 // in case of cumulants, both cumulants and vn values are stored. in both cases, v2 and v3
729 // are expected. a check is performed to see if rho has no negative local minimum
730 // for full description, see Phys. Rev. C 83, 044913
731 // since the cn distribution has negative values, vn = sqrt(cn) can be imaginary sometimes
732 // in this case one can either roll back to the 'original' fixed rho, do a fit for vn or take use
733 // vn = - sqrt(|cn|) note that because of this, use of q-cumulants is not safe !
734 // [2] fitting a fourier expansion to the de/dphi distribution
735 // the fit can be done with either v2, v3 or a combination.
736 // in all cases, a cut can be made on the p-value of the chi-squared value of the fit
737 // and a check can be performed to see if rho has no negative local minimum
738 // [3] get v2 and v3 from user supplied histograms
739 // in this way, a fixed value of v2 and v3 is subtracted w.r.t. whichever event plane is requested
740
741 if(fDebug > 0) printf("__FILE__ = %s \n __LINE __ %i , __FUNC__ %s \n ", __FILE__, __LINE__, __func__);
742 Int_t freeParams(2); // free parameters of the fit (for NDF)
743 switch (fFitModulationType) { // for approaches where no fitting is required
744 case kQC2 : {
745 fFitModulation->FixParameter(4, psi2);
746 fFitModulation->FixParameter(6, psi3);
747 fFitModulation->FixParameter(3, CalculateQC2(2)); // set here with cn, vn = sqrt(cn)
748 fFitModulation->FixParameter(7, CalculateQC2(3));
749 // first fill the histos of the raw cumulant distribution
750 if (fUsePtWeight) { // use weighted weights
751 Double_t dQCnM11 = (fNoEventWeightsForQC) ? 1. : QCnM11();
752 fProfV2Cumulant->Fill(fCent, fFitModulation->GetParameter(3), dQCnM11);
753 fProfV3Cumulant->Fill(fCent, fFitModulation->GetParameter(7), dQCnM11);
754 } else {
755 Double_t dQCnM = (fNoEventWeightsForQC) ? 2. : QCnM();
756 fProfV2Cumulant->Fill(fCent, fFitModulation->GetParameter(3), dQCnM*(dQCnM-1));
757 fProfV3Cumulant->Fill(fCent, fFitModulation->GetParameter(7), dQCnM*(dQCnM-1));
758 }
759 // then see if one of the cn value is larger than zero and vn is readily available
760 if(fFitModulation->GetParameter(3) > 0 && fFitModulation->GetParameter(7) > 0) {
761 fFitModulation->FixParameter(3, TMath::Sqrt(fFitModulation->GetParameter(3)));
762 fFitModulation->FixParameter(7, TMath::Sqrt(fFitModulation->GetParameter(7)));
763 } else if (!QCnRecovery(psi2, psi3)) return kFALSE; // try to recover the cumulant, this will set v2 and v3
764 if(fAbsVnHarmonics && fFitModulation->GetMinimum(0, TMath::TwoPi()) < 0) { // general check
765 fFitModulation->SetParameter(7, 0);
766 fFitModulation->SetParameter(3, 0);
767 fFitModulation->SetParameter(0, fLocalRho->GetVal());
768 return kFALSE;
769 }
770 return kTRUE;
771 } break;
772 case kQC4 : {
773 fFitModulation->FixParameter(4, psi2);
774 fFitModulation->FixParameter(6, psi3);
775 fFitModulation->FixParameter(3, CalculateQC4(2)); // set here with cn, vn = sqrt(cn)
776 fFitModulation->FixParameter(7, CalculateQC4(3));
777 // first fill the histos of the raw cumulant distribution
778 if (fUsePtWeight) { // use weighted weights
779 fProfV2Cumulant->Fill(fCent, fFitModulation->GetParameter(3)/*, QCnM1111()*/);
780 fProfV3Cumulant->Fill(fCent, fFitModulation->GetParameter(7)/*, QCnM1111()*/);
781 } else {
782 fProfV2Cumulant->Fill(fCent, fFitModulation->GetParameter(3)/*, QCnM1111()*/);
783 fProfV3Cumulant->Fill(fCent, fFitModulation->GetParameter(7)/*, QCnM1111()*/);
784 }
785 // then see if one of the cn value is larger than zero and vn is readily available
786 if(fFitModulation->GetParameter(3) > 0 && fFitModulation->GetParameter(7) > 0) {
787 fFitModulation->FixParameter(3, TMath::Sqrt(fFitModulation->GetParameter(3)));
788 fFitModulation->FixParameter(7, TMath::Sqrt(fFitModulation->GetParameter(7)));
789 } else if (!QCnRecovery(psi2, psi3)) return kFALSE; // try to recover the cumulant, this will set v2 and v3
790 if(fAbsVnHarmonics && fFitModulation->GetMinimum(0, TMath::TwoPi()) < 0) { // general check
791 fFitModulation->SetParameter(7, 0);
792 fFitModulation->SetParameter(3, 0);
793 fFitModulation->SetParameter(0, fLocalRho->GetVal());
794 return kFALSE;
795 }
796 } break;
797 case kIntegratedFlow : {
798 // use v2 and v3 values from an earlier iteration over the data
799 fFitModulation->FixParameter(3, fUserSuppliedV2->GetBinContent(fUserSuppliedV2->GetXaxis()->FindBin(fCent)));
800 fFitModulation->FixParameter(4, psi2);
801 fFitModulation->FixParameter(6, psi3);
802 fFitModulation->FixParameter(7, fUserSuppliedV3->GetBinContent(fUserSuppliedV3->GetXaxis()->FindBin(fCent)));
803 if(fAbsVnHarmonics && fFitModulation->GetMinimum(0, TMath::TwoPi()) < 0) {
804 fFitModulation->SetParameter(7, 0);
805 fFitModulation->SetParameter(3, 0);
806 fFitModulation->SetParameter(0, fLocalRho->GetVal());
807 return kFALSE;
808 }
809 return kTRUE;
810 }
811 default : break;
812 }
813 TString detector("");
814 switch (fDetectorType) {
815 case kTPC : detector+="TPC";
816 break;
817 case kVZEROA : detector+="VZEROA";
818 break;
819 case kVZEROC : detector+="VZEROC";
820 break;
821 case kVZEROComb : detector+="VZEROComb";
822 break;
823 default: break;
824 }
825 Int_t iTracks(fTracks->GetEntriesFast());
826 Double_t excludeInEta = -999;
827 Double_t excludeInPhi = -999;
828 Double_t excludeInPt = -999;
829 if(iTracks <= 0 || fLocalRho->GetVal() <= 0 ) return kFALSE; // no use fitting an empty event ...
830 if(fExcludeLeadingJetsFromFit > 0 ) {
831 AliEmcalJet* leadingJet(GetJetContainer()->GetLeadingJet());
832 if(PassesCuts(leadingJet)) {
833 excludeInEta = leadingJet->Eta();
834 excludeInPhi = leadingJet->Phi();
835 excludeInPt = leadingJet->Pt();
836 }
837 }
838 // check the acceptance of the track selection that will be used
839 // if one uses e.g. semi-good tpc tracks, accepance in phi is reduced to 0 < phi < 4
840 // the defaults (-10 < phi < 10) which accept all, are then overwritten
841 Double_t lowBound(0.), upBound(TMath::TwoPi()); // bounds for fit
842 if(GetParticleContainer()->GetParticlePhiMin() > lowBound) lowBound = GetParticleContainer()->GetParticlePhiMin();
843 if(GetParticleContainer()->GetParticlePhiMax() < upBound) upBound = GetParticleContainer()->GetParticlePhiMax();
844
845 fHistSwap->Reset(); // clear the histogram
846 TH1F _tempSwap; // on stack for quick access
847 TH1F _tempSwapN; // on stack for quick access, bookkeeping histogram
848 if(fRebinSwapHistoOnTheFly) {
849 if(fNAcceptedTracks < 49) fNAcceptedTracks = 49; // avoid aliasing effects
850 _tempSwap = TH1F("_tempSwap", "_tempSwap", TMath::CeilNint(TMath::Sqrt(fNAcceptedTracks)), lowBound, upBound);
851 if(fUsePtWeightErrorPropagation) _tempSwapN = TH1F("_tempSwapN", "_tempSwapN", TMath::CeilNint(TMath::Sqrt(fNAcceptedTracks)), lowBound, upBound);
852 if(fUsePtWeight) _tempSwap.Sumw2();
853 }
854 else _tempSwap = *fHistSwap; // now _tempSwap holds the desired histo
855 // non poissonian error when using pt weights
856 Double_t totalpts(0.), totalptsquares(0.), totalns(0.);
857 for(Int_t i(0); i < iTracks; i++) {
858 AliVTrack* track = static_cast<AliVTrack*>(fTracks->At(i));
859 if(fExcludeLeadingJetsFromFit > 0 &&( (TMath::Abs(track->Eta() - excludeInEta) < GetJetContainer()->GetJetRadius()*fExcludeLeadingJetsFromFit ) || (TMath::Abs(track->Eta()) - GetJetContainer()->GetJetRadius() - GetJetContainer()->GetJetEtaMax() ) > 0 )) continue;
860 if(!PassesCuts(track) || track->Pt() > fSoftTrackMaxPt || track->Pt() < fSoftTrackMinPt) continue;
861 if(fUsePtWeight) {
862 _tempSwap.Fill(track->Phi(), track->Pt());
863 if(fUsePtWeightErrorPropagation) {
864 totalpts += track->Pt();
865 totalptsquares += track->Pt()*track->Pt();
866 totalns += 1;
867 _tempSwapN.Fill(track->Phi());
868 }
869 }
870 else _tempSwap.Fill(track->Phi());
871 }
872 if(fUsePtWeight && fUsePtWeightErrorPropagation) {
873 // in the case of pt weights overwrite the poissonian error estimate which is assigned by root by a more sophisticated appraoch
874 // the assumption here is that the bin error will be dominated by the uncertainty in the mean pt in a bin and in the uncertainty
875 // of the number of tracks in a bin, the first of which will be estimated from the sample standard deviation of all tracks in the
876 // event, for the latter use a poissonian estimate. the two contrubitions are assumed to be uncorrelated
877 if(totalns < 1) return kFALSE; // not one track passes the cuts
878 for(Int_t l = 0; l < _tempSwap.GetNbinsX(); l++) {
879 if(_tempSwapN.GetBinContent(l+1) == 0) {
880 _tempSwap.SetBinContent(l+1,0);
881 _tempSwap.SetBinError(l+1,0);
882 }
883 else {
884 Double_t vartimesnsq = totalptsquares*totalns - totalpts*totalpts;
885 Double_t variance = vartimesnsq/(totalns*(totalns-1.));
886 Double_t SDOMSq = variance / _tempSwapN.GetBinContent(l+1);
887 Double_t SDOMSqOverMeanSq = SDOMSq * _tempSwapN.GetBinContent(l+1) * _tempSwapN.GetBinContent(l+1) / (_tempSwapN.GetBinContent(l+1) * _tempSwapN.GetBinContent(l+1));
888 Double_t poissonfrac = 1./_tempSwapN.GetBinContent(l+1);
889 Double_t vartotalfrac = SDOMSqOverMeanSq + poissonfrac;
890 Double_t vartotal = vartotalfrac * _tempSwap.GetBinContent(l+1) * _tempSwap.GetBinContent(l+1);
891 if(vartotal > 0.0001) _tempSwap.SetBinError(l+1,TMath::Sqrt(vartotal));
892 else {
893 _tempSwap.SetBinContent(l+1,0);
894 _tempSwap.SetBinError(l+1,0);
895 }
896 }
897 }
898 }
899
900 fFitModulation->SetParameter(0, fLocalRho->GetVal());
901 switch (fFitModulationType) {
902 case kNoFit : {
903 fFitModulation->FixParameter(0, fLocalRho->GetVal() );
904 freeParams = 0;
905 } break;
906 case kV2 : {
907 fFitModulation->FixParameter(4, psi2);
908 freeParams = 1;
909 } break;
910 case kV3 : {
911 fFitModulation->FixParameter(4, psi3);
912 freeParams = 1;
913 } break;
914 case kCombined : {
915 fFitModulation->FixParameter(4, psi2);
916 fFitModulation->FixParameter(6, psi3);
917 freeParams = 2;
918 } break;
919 case kFourierSeries : {
920 // in this approach, an explicit calculation will be made of vn = sqrt(xn^2+yn^2)
921 // where x[y] = Integrate[r(phi)cos[sin](n phi)dphi, 0, 2pi]
922 Double_t cos2(0), sin2(0), cos3(0), sin3(0), sumPt(0);
923 for(Int_t i(0); i < iTracks; i++) {
924 AliVTrack* track = static_cast<AliVTrack*>(fTracks->At(i));
925 if(!PassesCuts(track) || track->Pt() > fSoftTrackMaxPt || track->Pt() < fSoftTrackMinPt) continue;
926 sumPt += track->Pt();
927 cos2 += track->Pt()*TMath::Cos(2*PhaseShift(track->Phi()-psi2));
928 sin2 += track->Pt()*TMath::Sin(2*PhaseShift(track->Phi()-psi2));
929 cos3 += track->Pt()*TMath::Cos(3*PhaseShift(track->Phi()-psi3));
930 sin3 += track->Pt()*TMath::Sin(3*PhaseShift(track->Phi()-psi3));
931 }
932 fFitModulation->SetParameter(3, TMath::Sqrt(cos2*cos2+sin2*sin2)/fLocalRho->GetVal());
933 fFitModulation->SetParameter(4, psi2);
934 fFitModulation->SetParameter(6, psi3);
935 fFitModulation->SetParameter(7, TMath::Sqrt(cos3*cos3+sin3*sin3)/fLocalRho->GetVal());
936 } break;
937 default : break;
938 }
939 _tempSwap.Fit(fFitModulation, fFitModulationOptions.Data(), "", lowBound, upBound);
940 // the quality of the fit is evaluated from 1 - the cdf of the chi square distribution
941 // three methods are available, all with their drawbacks. all are stored, one is selected to do the cut
942 Int_t NDF(_tempSwap.GetXaxis()->GetNbins()-freeParams);
943 if(NDF == 0) return kFALSE;
944 Double_t CDF(1.-ChiSquareCDF(NDF, ChiSquare(_tempSwap, fFitModulation)));
945 Double_t CDFROOT(1.-ChiSquareCDF(NDF, fFitModulation->GetChisquare()));
946 // fill the values and centrality correlation (redundant but easy on the eyes)
947 fHistPvalueCDF->Fill(CDF);
948 fHistPvalueCDFCent->Fill(fCent, CDF);
949 fHistPvalueCDFROOT->Fill(CDFROOT);
950 fHistPvalueCDFROOTCent->Fill(fCent, CDFROOT);
951 fHistChi2ROOTCent->Fill(fCent, fFitModulation->GetChisquare()/((float)NDF));
952 fHistChi2Cent->Fill(fCent, ChiSquare(_tempSwap, fFitModulation)/((float)NDF));
953 fHistPChi2Root->Fill(CDFROOT, fFitModulation->GetChisquare()/((float)NDF));
954 fHistPChi2->Fill(CDF, ChiSquare(_tempSwap, fFitModulation)/((float)NDF));
955
956 // variable CDF is used for making cuts, so we fill it with the selected p-value
957 switch (fFitGoodnessTest) {
958 case kChi2ROOT : {
959 CDF = CDFROOT;
960 } break;
961 case kChi2Poisson : break; // CDF is already CDF
962 default: break;
963 }
964
965 if(fFitControl) {
966 // as an additional quality check, see if fitting a control fit has a higher significance
967 _tempSwap.Fit(fFitControl, fFitModulationOptions.Data(), "", lowBound, upBound);
968 Double_t CDFControl(-1.);
969 switch (fFitGoodnessTest) {
970 case kChi2ROOT : {
971 CDFControl = 1.-ChiSquareCDF(fFitControl->GetNDF(), fFitModulation->GetChisquare());
972 } break;
973 case kChi2Poisson : {
974 CDFControl = 1.-ChiSquareCDF(fFitControl->GetNDF(), ChiSquare(_tempSwap, fFitModulation));
975 } break;
976 default: break;
977 }
978 if(CDFControl > CDF) {
979 CDF = -1.; // control fit is more significant, so throw out the 'old' fit
980 fHistRhoStatusCent->Fill(fCent, -1);
981 }
982 }
983 if(CDF >= fMinPvalue && CDF <= fMaxPvalue && ( fAbsVnHarmonics && fFitModulation->GetMinimum(0, TMath::TwoPi()) > 0)) { // fit quality. not that although with limited acceptance the fit is performed on just
984 // part of phase space, the requirement that energy desntiy is larger than zero is applied
985 // to the FULL spectrum
986 fHistRhoStatusCent->Fill(fCent, 0.);
987 // for LOCAL didactic purposes, save the best and the worst fits
988 // this routine can produce a lot of output histograms (it's not memory 'safe') and will not work on GRID
989 // since the output will become unmergeable (i.e. different nodes may produce conflicting output)
990 switch (fRunModeType) {
991 case kLocal : {
992 if(gRandom->Uniform(0, 100) > fPercentageOfFits) break;
993 static Int_t didacticCounterBest(0);
994 TProfile* didacticProfile = (TProfile*)_tempSwap.Clone(Form("Fit_%i_1-CDF_%.3f_cen_%i_%s", didacticCounterBest, CDF, fInCentralitySelection, detector.Data()));
995 TF1* didacticFit = (TF1*)fFitModulation->Clone(Form("fit_%i_CDF_%.3f_cen_%i_%s", didacticCounterBest, CDF, fInCentralitySelection, detector.Data()));
996 switch(fFitModulationType) {
997 case kCombined : {
998 // to make a nice picture also plot the separate components (v2 and v3) of the fit
999 // only done for cobined fit where there are actually components to split ...
1000 TF1* v0(new TF1("dfit_kV2", "[0]", 0, TMath::TwoPi()));
1001 v0->SetParameter(0, didacticFit->GetParameter(0)); // normalization
1002 v0->SetLineColor(kMagenta);
1003 v0->SetLineStyle(7);
1004 didacticProfile->GetListOfFunctions()->Add(v0);
1005 TF1* v2(new TF1("dfit_kV2", "[0]*([1]+[2]*[3]*TMath::Cos([2]*(x-[4])))", 0, TMath::TwoPi()));
1006 v2->SetParameter(0, didacticFit->GetParameter(0)); // normalization
1007 v2->SetParameter(3, didacticFit->GetParameter(3)); // v2
1008 v2->FixParameter(1, 1.); // constant
1009 v2->FixParameter(2, 2.); // constant
1010 v2->FixParameter(4, didacticFit->GetParameter(4)); // psi2
1011 v2->SetLineColor(kGreen);
1012 didacticProfile->GetListOfFunctions()->Add(v2);
1013 TF1* v3(new TF1("dfit_kV3", "[0]*([1]+[2]*[3]*TMath::Cos([5]*(x-[4])))", 0, TMath::TwoPi()));
1014 v3->SetParameter(0, didacticFit->GetParameter(0)); // normalization
1015 v3->SetParameter(3, didacticFit->GetParameter(7)); // v3
1016 v3->FixParameter(1, 1.); // constant
1017 v3->FixParameter(2, 2.); // constant
1018 v3->FixParameter(4, didacticFit->GetParameter(6)); // psi3
1019 v3->FixParameter(5, 3.); // constant
1020 v3->SetLineColor(kCyan);
1021 didacticProfile->GetListOfFunctions()->Add(v3);
1022 }
1023 default : break;
1024 }
1025 didacticProfile->GetListOfFunctions()->Add(didacticFit);
1026 didacticProfile->GetYaxis()->SetTitle("#frac{d #sum #it{p}_{T}}{d #varphi} [GeV/#it{c}]");
1027 didacticProfile->GetXaxis()->SetTitle("#varphi");
1028 fOutputListGood->Add(didacticProfile);
1029 didacticCounterBest++;
1030 TH2F* didacticSurface = BookTH2F(Form("surface_%s", didacticProfile->GetName()), "#phi", "#eta", 50, 0, TMath::TwoPi(), 50, -1, 1, -1, kFALSE);
1031 for(Int_t i(0); i < iTracks; i++) {
1032 AliVTrack* track = static_cast<AliVTrack*>(fTracks->At(i));
1033 if(PassesCuts(track)) {
1034 if(fUsePtWeight) didacticSurface->Fill(track->Phi(), track->Eta(), track->Pt());
1035 else didacticSurface->Fill(track->Phi(), track->Eta());
1036 }
1037 }
1038 if(fExcludeLeadingJetsFromFit) { // visualize the excluded region
1039 TF2 *f2 = new TF2(Form("%s_LJ", didacticSurface->GetName()),"[0]*TMath::Gaus(x,[1],[2])*TMath::Gaus(y,[3],[4])", 0, TMath::TwoPi(), -1, 1);
1040 f2->SetParameters(excludeInPt/3.,excludeInPhi,.1,excludeInEta,.1);
1041 didacticSurface->GetListOfFunctions()->Add(f2);
1042 }
1043 fOutputListGood->Add(didacticSurface);
1044 } break;
1045 default : break;
1046 }
1047 } else { // if the fit is of poor quality revert to the original rho estimate
1048 switch (fRunModeType) { // again see if we want to save the fit
1049 case kLocal : {
1050 static Int_t didacticCounterWorst(0);
1051 if(gRandom->Uniform(0, 100) > fPercentageOfFits) break;
1052 TProfile* didacticProfile = (TProfile*)_tempSwap.Clone(Form("Fit_%i_1-CDF_%.3f_cen_%i_%s", didacticCounterWorst, CDF, fInCentralitySelection, detector.Data() ));
1053 TF1* didacticFit = (TF1*)fFitModulation->Clone(Form("fit_%i_p_%.3f_cen_%i_%s", didacticCounterWorst, CDF, fInCentralitySelection, detector.Data()));
1054 didacticProfile->GetListOfFunctions()->Add(didacticFit);
1055 fOutputListBad->Add(didacticProfile);
1056 didacticCounterWorst++;
1057 } break;
1058 default : break;
1059 }
1060 switch (fFitModulationType) {
1061 case kNoFit : break; // nothing to do
1062 case kCombined : fFitModulation->SetParameter(7, 0); // no break
1063 case kFourierSeries : fFitModulation->SetParameter(7, 0); // no break
1064 default : { // needs to be done if there was a poor fit
1065 fFitModulation->SetParameter(3, 0);
1066 fFitModulation->SetParameter(0, fLocalRho->GetVal());
1067 } break;
1068 }
1069 if(CDF > -.5) fHistRhoStatusCent->Fill(fCent, 1.);
1070 return kFALSE; // return false if the fit is rejected
1071 }
1072 return kTRUE;
1073}
1074//_____________________________________________________________________________
1075void AliAnalysisTaskLocalRhoDev::FillAnalysisSummaryHistogram() const
1076{
1077 // Fill the analysis summary histrogram, saves all relevant analysis settigns
1078
1079 if(fDebug > 0) printf("__FILE__ = %s \n __LINE __ %i , __FUNC__ %s \n ", __FILE__, __LINE__, __func__);
1080 fHistAnalysisSummary->GetXaxis()->SetBinLabel(2, "fJetRadius");
1081 fHistAnalysisSummary->SetBinContent(2, GetJetContainer()->GetJetRadius());
1082 fHistAnalysisSummary->GetXaxis()->SetBinLabel(3, "fJetEtaMin");
1083 fHistAnalysisSummary->SetBinContent(3, GetJetContainer()->GetJetEtaMin());
1084 fHistAnalysisSummary->GetXaxis()->SetBinLabel(4, "fJetEtaMax");
1085 fHistAnalysisSummary->SetBinContent(4, GetJetContainer()->GetJetEtaMax());
1086 fHistAnalysisSummary->GetXaxis()->SetBinLabel(5, "fJetPhiMin");
1087 fHistAnalysisSummary->SetBinContent(5, GetJetContainer()->GetJetPhiMin());
1088 fHistAnalysisSummary->GetXaxis()->SetBinLabel(6, "fJetPhiMax");
1089 fHistAnalysisSummary->SetBinContent(6, GetJetContainer()->GetJetPhiMin());
1090 fHistAnalysisSummary->GetXaxis()->SetBinLabel(34, "fitModulationType");
1091 fHistAnalysisSummary->SetBinContent(34, (int)fFitModulationType);
1092 fHistAnalysisSummary->GetXaxis()->SetBinLabel(35, "runModeType");
1093 fHistAnalysisSummary->SetBinContent(35, (int)fRunModeType);
1094 fHistAnalysisSummary->GetXaxis()->SetBinLabel(37, "iterator");
1095 fHistAnalysisSummary->SetBinContent(37, 1.);
1096 fHistAnalysisSummary->GetXaxis()->SetBinLabel(38, "fMinPvalue");
1097 fHistAnalysisSummary->SetBinContent(38, fMinPvalue);
1098 fHistAnalysisSummary->GetXaxis()->SetBinLabel(39, "fMaxPvalue");
1099 fHistAnalysisSummary->SetBinContent(39, fMaxPvalue);
1100 fHistAnalysisSummary->GetXaxis()->SetBinLabel(40, "fExcludeLeadingJetsFromFit");
1101 fHistAnalysisSummary->SetBinContent(40, fExcludeLeadingJetsFromFit);
1102 fHistAnalysisSummary->GetXaxis()->SetBinLabel(41, "fRebinSwapHistoOnTheFly");
1103 fHistAnalysisSummary->SetBinContent(41, (int)fRebinSwapHistoOnTheFly);
1104 fHistAnalysisSummary->GetXaxis()->SetBinLabel(42, "fUsePtWeight");
1105 fHistAnalysisSummary->SetBinContent(42, (int)fUsePtWeight);
1106 fHistAnalysisSummary->GetXaxis()->SetBinLabel(45, "fLocalJetMinEta");
1107 fHistAnalysisSummary->SetBinContent(45,fLocalJetMinEta );
1108 fHistAnalysisSummary->GetXaxis()->SetBinLabel(46, "fLocalJetMaxEta");
1109 fHistAnalysisSummary->SetBinContent(46, fLocalJetMaxEta);
1110 fHistAnalysisSummary->GetXaxis()->SetBinLabel(47, "fLocalJetMinPhi");
1111 fHistAnalysisSummary->SetBinContent(47, fLocalJetMinPhi);
1112 fHistAnalysisSummary->GetXaxis()->SetBinLabel(48, "fLocalJetMaxPhi");
1113 fHistAnalysisSummary->SetBinContent(48, fLocalJetMaxPhi);
1114 fHistAnalysisSummary->GetXaxis()->SetBinLabel(49, "fSoftTrackMinPt");
1115 fHistAnalysisSummary->SetBinContent(49, fSoftTrackMinPt);
1116 fHistAnalysisSummary->GetXaxis()->SetBinLabel(50, "fSoftTrackMaxPt");
1117 fHistAnalysisSummary->SetBinContent(50, fSoftTrackMaxPt);
1118 fHistAnalysisSummary->GetXaxis()->SetBinLabel(51, "fUseScaledRho");
1119 fHistAnalysisSummary->SetBinContent(51, fUseScaledRho);
1120 fHistAnalysisSummary->GetXaxis()->SetBinLabel(53, "used rho");
1121 fHistAnalysisSummary->GetXaxis()->SetBinLabel(54, "used small rho");
1122}
1123
1124//_____________________________________________________________________________
1125void AliAnalysisTaskLocalRhoDev::FillEventPlaneHistograms(Double_t psi2, Double_t psi3) const
1126{
1127 // Fill event plane histograms
1128
1129 if(fDebug > 0) printf("__FILE__ = %s \n __LINE __ %i , __FUNC__ %s \n ", __FILE__, __LINE__, __func__);
1130 fHistPsi2[fInCentralitySelection]->Fill(psi2);
1131 fHistPsi3[fInCentralitySelection]->Fill(psi3);
1132}
1133//_____________________________________________________________________________
1134Bool_t AliAnalysisTaskLocalRhoDev::PassesCuts(AliVEvent* event)
1135{
1136 // event cuts
1137 if(fDebug > 0) printf("__FILE__ = %s \n __LINE __ %i , __FUNC__ %s \n ", __FILE__, __LINE__, __func__);
1138 if(!event) return kFALSE;
1139 // determine the run number to see if the track and jet cuts should be refreshed for semi-good TPC runs
1140 // only done if the runnumber changes, could be moved to a call to AliAnalysisTaskSE::Notify()
1141 if(fRunNumber != InputEvent()->GetRunNumber()) {
1142 fRunNumber = InputEvent()->GetRunNumber(); // set the current run number
1143 if(fDebug > 0) printf("__FUNC__ %s > NEW RUNNUMBER DETECTED \n ", __func__);
1144 // reset the cuts. should be a pointless operation except for the case where the run number changes
1145 // from semi-good back to good on one node, which is not a likely scenario
1146 AliAnalysisTaskEmcal::SetTrackPhiLimits(-10., 10.);
1147 AliAnalysisTaskEmcalJet::SetJetPhiLimits(-10., 10.);
1148 if(fCachedRho) { // if there's a cached rho, it's the default, so switch back
1149 if(fDebug > 0) printf("__FUNC__ %s > replacing rho with cached rho \n ", __func__);
1150 fRho = fCachedRho; // reset rho back to cached value. again, should be pointless
1151 }
1152 Bool_t flaggedAsSemiGood(kFALSE); // not flagged as anything
1153 for(Int_t i(0); i < fExpectedSemiGoodRuns->GetSize(); i++) {
1154 if(fExpectedSemiGoodRuns->At(i) == fRunNumber) { // run is semi-good
1155 if(fDebug > 0) printf("__FUNC__ %s > semi-good tpc run detected, adjusting acceptance \n ", __func__);
1156 flaggedAsSemiGood = kTRUE;
1157 AliAnalysisTaskEmcalJet::SetJetPhiLimits(fSemiGoodJetMinPhi, fSemiGoodJetMaxPhi); // just an acceptance cut, jets are obtained from full azimuth, so no edge effects
1158 AliAnalysisTaskEmcal::SetTrackPhiLimits(fSemiGoodTrackMinPhi, fSemiGoodTrackMaxPhi); // only affects vn extraction, NOT jet finding
1159 // for semi-good runs, also try to get the 'small rho' estimate, if it is available
1160 AliRhoParameter* tempRho(dynamic_cast<AliRhoParameter*>(InputEvent()->FindListObject(fNameSmallRho.Data())));
1161 if(tempRho) {
1162 if(fDebug > 0) printf("__FUNC__ %s > switching to small rho, caching normal rho \n ", __func__);
1163 fHistAnalysisSummary->SetBinContent(54, 1.); // bookkeep the fact that small rho is used
1164 fCachedRho = fRho; // cache the original rho ...
1165 fRho = tempRho; // ... and use the small rho
1166 }
1167 }
1168 }
1169 if(!flaggedAsSemiGood) fHistAnalysisSummary->SetBinContent(53, 1.); // bookkeep which rho estimate is used
1170 }
1171 return kTRUE;
1172}
1173
1174//_____________________________________________________________________________
1175void AliAnalysisTaskLocalRhoDev::Terminate(Option_t *)
1176{
1177 // Terminate
1178}
1179
1180//_____________________________________________________________________________
1181void AliAnalysisTaskLocalRhoDev::SetModulationFit(TF1* fit)
1182{
1183 // Set function to fit modulation
1184
1185 if (fFitModulation) delete fFitModulation;
1186 fFitModulation = fit;
1187}