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489d5531 | 1 | /************************************************************************* |
2 | * Copyright(c) 1998-2008, ALICE Experiment at CERN, All rights reserved. * | |
3 | * * | |
4 | * Author: The ALICE Off-line Project. * | |
5 | * Contributors are mentioned in the code where appropriate. * | |
6 | * * | |
7 | * Permission to use, copy, modify and distribute this software and its * | |
8 | * documentation strictly for non-commercial purposes is hereby granted * | |
9 | * without fee, provided that the above copyright notice appears in all * | |
10 | * copies and that both the copyright notice and this permission notice * | |
11 | * appear in the supporting documentation. The authors make no claims * | |
12 | * about the suitability of this software for any purpose. It is * | |
13 | * provided "as is" without express or implied warranty. * | |
14 | **************************************************************************/ | |
15 | ||
16 | /********************************** | |
17 | * flow analysis with Q-cumulants * | |
18 | * * | |
ff70ca91 | 19 | * author: Ante Bilandzic * |
20 | * (abilandzic@gmail.com) * | |
489d5531 | 21 | *********************************/ |
22 | ||
23 | #define AliFlowAnalysisWithQCumulants_cxx | |
24 | ||
25 | #include "Riostream.h" | |
26 | #include "AliFlowCommonConstants.h" | |
27 | #include "AliFlowCommonHist.h" | |
28 | #include "AliFlowCommonHistResults.h" | |
29 | #include "TChain.h" | |
30 | ||
31 | #include "TFile.h" | |
32 | #include "TList.h" | |
33 | #include "TGraph.h" | |
34 | #include "TParticle.h" | |
35 | #include "TRandom3.h" | |
36 | #include "TStyle.h" | |
37 | #include "TProfile.h" | |
38 | #include "TProfile2D.h" | |
39 | #include "TProfile3D.h" | |
40 | #include "TMath.h" | |
41 | #include "TArrow.h" | |
42 | #include "TPaveLabel.h" | |
43 | #include "TCanvas.h" | |
44 | #include "AliFlowEventSimple.h" | |
45 | #include "AliFlowTrackSimple.h" | |
46 | #include "AliFlowAnalysisWithQCumulants.h" | |
47 | #include "TArrayD.h" | |
48 | #include "TRandom.h" | |
49 | #include "TF1.h" | |
50 | ||
51 | class TH1; | |
52 | class TH2; | |
53 | class TGraph; | |
54 | class TPave; | |
55 | class TLatex; | |
56 | class TMarker; | |
57 | class TRandom3; | |
58 | class TObjArray; | |
59 | class TList; | |
60 | class TCanvas; | |
61 | class TSystem; | |
62 | class TROOT; | |
63 | class AliFlowVector; | |
64 | class TVector; | |
65 | ||
489d5531 | 66 | //================================================================================================================ |
67 | ||
489d5531 | 68 | ClassImp(AliFlowAnalysisWithQCumulants) |
69 | ||
70 | AliFlowAnalysisWithQCumulants::AliFlowAnalysisWithQCumulants(): | |
71 | // 0.) base: | |
72 | fHistList(NULL), | |
73 | // 1.) common: | |
74 | fCommonHists(NULL), | |
75 | fCommonHists2nd(NULL), | |
76 | fCommonHists4th(NULL), | |
77 | fCommonHists6th(NULL), | |
78 | fCommonHists8th(NULL), | |
79 | fCommonHistsResults2nd(NULL), | |
80 | fCommonHistsResults4th(NULL), | |
81 | fCommonHistsResults6th(NULL), | |
82 | fCommonHistsResults8th(NULL), | |
83 | fnBinsPhi(0), | |
84 | fPhiMin(0), | |
85 | fPhiMax(0), | |
86 | fPhiBinWidth(0), | |
87 | fnBinsPt(0), | |
88 | fPtMin(0), | |
89 | fPtMax(0), | |
90 | fPtBinWidth(0), | |
91 | fnBinsEta(0), | |
92 | fEtaMin(0), | |
93 | fEtaMax(0), | |
94 | fEtaBinWidth(0), | |
dd442cd2 | 95 | fFillMultipleControlHistograms(kFALSE), |
489d5531 | 96 | fHarmonic(2), |
97 | fAnalysisLabel(NULL), | |
98 | // 2a.) particle weights: | |
99 | fWeightsList(NULL), | |
100 | fUsePhiWeights(kFALSE), | |
101 | fUsePtWeights(kFALSE), | |
102 | fUseEtaWeights(kFALSE), | |
103 | fUseParticleWeights(NULL), | |
104 | fPhiWeights(NULL), | |
105 | fPtWeights(NULL), | |
106 | fEtaWeights(NULL), | |
107 | // 2b.) event weights: | |
108 | fMultiplicityWeight(NULL), | |
109 | // 3.) integrated flow: | |
110 | fIntFlowList(NULL), | |
111 | fIntFlowProfiles(NULL), | |
112 | fIntFlowResults(NULL), | |
113 | fIntFlowFlags(NULL), | |
b92ea2b9 | 114 | fApplyCorrectionForNUA(kFALSE), |
2001bc3a | 115 | fApplyCorrectionForNUAVsM(kFALSE), |
9da1a4f3 | 116 | fnBinsMult(10000), |
067e9bc8 | 117 | fMinMult(0.), |
118 | fMaxMult(10000.), | |
b77b6434 | 119 | fPropagateErrorAlsoFromNIT(kFALSE), |
8ed4edc7 | 120 | fCalculateCumulantsVsM(kFALSE), |
0dd3b008 | 121 | fMinimumBiasReferenceFlow(kTRUE), |
e5834fcb | 122 | fForgetAboutCovariances(kFALSE), |
123 | fStorePhiDistributionForOneEvent(kFALSE), | |
489d5531 | 124 | fReQ(NULL), |
125 | fImQ(NULL), | |
126 | fSMpk(NULL), | |
127 | fIntFlowCorrelationsEBE(NULL), | |
128 | fIntFlowEventWeightsForCorrelationsEBE(NULL), | |
129 | fIntFlowCorrelationsAllEBE(NULL), | |
e5834fcb | 130 | fReferenceMultiplicityEBE(0.), |
489d5531 | 131 | fAvMultiplicity(NULL), |
132 | fIntFlowCorrelationsPro(NULL), | |
b40a910e | 133 | fIntFlowSquaredCorrelationsPro(NULL), |
489d5531 | 134 | fIntFlowCorrelationsAllPro(NULL), |
135 | fIntFlowExtraCorrelationsPro(NULL), | |
136 | fIntFlowProductOfCorrelationsPro(NULL), | |
0328db2d | 137 | fIntFlowProductOfCorrectionTermsForNUAPro(NULL), |
489d5531 | 138 | fIntFlowCorrelationsHist(NULL), |
139 | fIntFlowCorrelationsAllHist(NULL), | |
140 | fIntFlowCovariances(NULL), | |
141 | fIntFlowSumOfProductOfEventWeights(NULL), | |
0328db2d | 142 | fIntFlowCovariancesNUA(NULL), |
143 | fIntFlowSumOfProductOfEventWeightsNUA(NULL), | |
489d5531 | 144 | fIntFlowQcumulants(NULL), |
b92ea2b9 | 145 | fIntFlowQcumulantsRebinnedInM(NULL), |
146 | fIntFlowQcumulantsErrorSquaredRatio(NULL), | |
489d5531 | 147 | fIntFlow(NULL), |
b3dacf6b | 148 | fIntFlowRebinnedInM(NULL), |
2001bc3a | 149 | fIntFlowDetectorBias(NULL), |
489d5531 | 150 | // 4.) differential flow: |
151 | fDiffFlowList(NULL), | |
152 | fDiffFlowProfiles(NULL), | |
153 | fDiffFlowResults(NULL), | |
154 | fDiffFlowFlags(NULL), | |
155 | fCalculate2DFlow(kFALSE), | |
156 | // 5.) distributions: | |
57340a27 | 157 | fDistributionsList(NULL), |
158 | fDistributionsFlags(NULL), | |
489d5531 | 159 | fStoreDistributions(kFALSE), |
e5834fcb | 160 | // 6.) various: |
161 | fVariousList(NULL), | |
162 | fPhiDistributionForOneEvent(NULL), | |
489d5531 | 163 | // x.) debugging and cross-checking: |
164 | fNestedLoopsList(NULL), | |
165 | fEvaluateIntFlowNestedLoops(kFALSE), | |
166 | fEvaluateDiffFlowNestedLoops(kFALSE), | |
167 | fMaxAllowedMultiplicity(10), | |
168 | fEvaluateNestedLoops(NULL), | |
169 | fIntFlowDirectCorrelations(NULL), | |
170 | fIntFlowExtraDirectCorrelations(NULL), | |
171 | fCrossCheckInPtBinNo(10), | |
3b552efe | 172 | fCrossCheckInEtaBinNo(20), |
489d5531 | 173 | fNoOfParticlesInBin(NULL) |
174 | { | |
175 | // constructor | |
176 | ||
177 | // base list to hold all output objects: | |
178 | fHistList = new TList(); | |
179 | fHistList->SetName("cobjQC"); | |
180 | fHistList->SetOwner(kTRUE); | |
181 | ||
182 | // list to hold histograms with phi, pt and eta weights: | |
183 | fWeightsList = new TList(); | |
184 | ||
185 | // multiplicity weight: | |
186 | fMultiplicityWeight = new TString("combinations"); | |
187 | ||
188 | // analysis label; | |
189 | fAnalysisLabel = new TString(); | |
190 | ||
191 | // initialize all arrays: | |
192 | this->InitializeArraysForIntFlow(); | |
193 | this->InitializeArraysForDiffFlow(); | |
194 | this->InitializeArraysForDistributions(); | |
e5834fcb | 195 | this->InitializeArraysForVarious(); |
489d5531 | 196 | this->InitializeArraysForNestedLoops(); |
197 | ||
198 | } // end of constructor | |
199 | ||
200 | ||
201 | //================================================================================================================ | |
202 | ||
203 | ||
204 | AliFlowAnalysisWithQCumulants::~AliFlowAnalysisWithQCumulants() | |
205 | { | |
206 | // destructor | |
207 | ||
208 | delete fHistList; | |
209 | ||
210 | } // end of AliFlowAnalysisWithQCumulants::~AliFlowAnalysisWithQCumulants() | |
211 | ||
212 | ||
213 | //================================================================================================================ | |
214 | ||
215 | ||
216 | void AliFlowAnalysisWithQCumulants::Init() | |
217 | { | |
3b552efe | 218 | // a) Cross check if the settings make sense before starting the QC adventure; |
489d5531 | 219 | // b) Access all common constants; |
220 | // c) Book all objects; | |
3b552efe | 221 | // d) Store flags for integrated and differential flow; |
489d5531 | 222 | // e) Store flags for distributions of corelations; |
223 | // f) Store harmonic which will be estimated. | |
3b552efe | 224 | |
489d5531 | 225 | //save old value and prevent histograms from being added to directory |
226 | //to avoid name clashes in case multiple analaysis objects are used | |
227 | //in an analysis | |
228 | Bool_t oldHistAddStatus = TH1::AddDirectoryStatus(); | |
229 | TH1::AddDirectory(kFALSE); | |
230 | ||
3b552efe | 231 | // a) Cross check if the settings make sense before starting the QC adventure; |
489d5531 | 232 | this->CrossCheckSettings(); |
233 | // b) Access all common constants: | |
234 | this->AccessConstants(); | |
235 | // c) Book all objects: | |
236 | this->BookAndFillWeightsHistograms(); | |
237 | this->BookAndNestAllLists(); | |
238 | this->BookCommonHistograms(); | |
239 | this->BookEverythingForIntegratedFlow(); | |
240 | this->BookEverythingForDifferentialFlow(); | |
241 | this->BookEverythingForDistributions(); | |
e5834fcb | 242 | this->BookEverythingForVarious(); |
489d5531 | 243 | this->BookEverythingForNestedLoops(); |
244 | // d) Store flags for integrated and differential flow: | |
245 | this->StoreIntFlowFlags(); | |
3b552efe | 246 | this->StoreDiffFlowFlags(); |
489d5531 | 247 | // e) Store flags for distributions of corelations: |
248 | this->StoreFlagsForDistributions(); | |
249 | // f) Store harmonic which will be estimated: | |
250 | this->StoreHarmonic(); | |
251 | ||
252 | TH1::AddDirectory(oldHistAddStatus); | |
253 | } // end of void AliFlowAnalysisWithQCumulants::Init() | |
254 | ||
255 | ||
256 | //================================================================================================================ | |
257 | ||
258 | ||
259 | void AliFlowAnalysisWithQCumulants::Make(AliFlowEventSimple* anEvent) | |
260 | { | |
261 | // Running over data only in this method. | |
262 | ||
b3dacf6b | 263 | // a) Check all pointers used in this method; |
264 | // b) Define local variables; | |
265 | // c) Fill the common control histograms and call the method to fill fAvMultiplicity; | |
266 | // d) Loop over data and calculate e-b-e quantities; | |
267 | // e) Call all the methods which calculate correlations for reference flow; | |
268 | // f) Call all the methods which calculate correlations for differential flow; | |
269 | // g) Distributions of correlations; | |
e5834fcb | 270 | // h) Store phi distribution for one event to illustrate flow; |
271 | // i) Debugging and cross-checking (evaluate nested loops); | |
272 | // j) Reset all event-by-event quantities. | |
489d5531 | 273 | |
b3dacf6b | 274 | // a) Check all pointers used in this method: |
275 | this->CheckPointersUsedInMake(); | |
276 | ||
277 | // b) Define local variables: | |
489d5531 | 278 | Double_t dPhi = 0.; // azimuthal angle in the laboratory frame |
279 | Double_t dPt = 0.; // transverse momentum | |
280 | Double_t dEta = 0.; // pseudorapidity | |
489d5531 | 281 | Double_t wPhi = 1.; // phi weight |
282 | Double_t wPt = 1.; // pt weight | |
283 | Double_t wEta = 1.; // eta weight | |
489d5531 | 284 | Int_t nRP = anEvent->GetEventNSelTracksRP(); // number of RPs (i.e. number of particles used to determine the reaction plane) |
e5834fcb | 285 | fReferenceMultiplicityEBE = anEvent->GetReferenceMultiplicity(); // reference multiplicity for current event |
9f33751d | 286 | |
b3dacf6b | 287 | // c) Fill the common control histograms and call the method to fill fAvMultiplicity: |
489d5531 | 288 | this->FillCommonControlHistograms(anEvent); |
289 | this->FillAverageMultiplicities(nRP); | |
290 | ||
b3dacf6b | 291 | // d) Loop over data and calculate e-b-e quantities: |
9f33751d | 292 | Int_t nPrim = anEvent->NumberOfTracks(); // nPrim = total number of primary tracks, i.e. nPrim = nRP + nPOI where: |
489d5531 | 293 | // nRP = # of particles used to determine the reaction plane; |
294 | // nPOI = # of particles of interest for a detailed flow analysis; | |
489d5531 | 295 | |
296 | AliFlowTrackSimple *aftsTrack = NULL; | |
297 | ||
298 | for(Int_t i=0;i<nPrim;i++) | |
299 | { | |
300 | aftsTrack=anEvent->GetTrack(i); | |
301 | if(aftsTrack) | |
302 | { | |
303 | if(!(aftsTrack->InRPSelection() || aftsTrack->InPOISelection())) continue; // consider only tracks which are RPs or POIs | |
304 | Int_t n = fHarmonic; // shortcut for the harmonic | |
305 | if(aftsTrack->InRPSelection()) // RP condition: | |
306 | { | |
307 | dPhi = aftsTrack->Phi(); | |
308 | dPt = aftsTrack->Pt(); | |
309 | dEta = aftsTrack->Eta(); | |
310 | if(fUsePhiWeights && fPhiWeights && fnBinsPhi) // determine phi weight for this particle: | |
311 | { | |
312 | wPhi = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(dPhi*fnBinsPhi/TMath::TwoPi()))); | |
313 | } | |
314 | if(fUsePtWeights && fPtWeights && fnBinsPt) // determine pt weight for this particle: | |
315 | { | |
316 | wPt = fPtWeights->GetBinContent(1+(Int_t)(TMath::Floor((dPt-fPtMin)/fPtBinWidth))); | |
317 | } | |
318 | if(fUseEtaWeights && fEtaWeights && fEtaBinWidth) // determine eta weight for this particle: | |
319 | { | |
320 | wEta = fEtaWeights->GetBinContent(1+(Int_t)(TMath::Floor((dEta-fEtaMin)/fEtaBinWidth))); | |
321 | } | |
322 | ||
323 | // integrated flow: | |
8ed4edc7 | 324 | // calculate Re[Q_{m*n,k}] and Im[Q_{m*n,k}], m = 1,2,3,4,5,6 for this event: |
325 | for(Int_t m=0;m<6;m++) | |
489d5531 | 326 | { |
327 | for(Int_t k=0;k<9;k++) | |
328 | { | |
329 | (*fReQ)(m,k)+=pow(wPhi*wPt*wEta,k)*TMath::Cos((m+1)*n*dPhi); | |
330 | (*fImQ)(m,k)+=pow(wPhi*wPt*wEta,k)*TMath::Sin((m+1)*n*dPhi); | |
331 | } | |
332 | } | |
333 | // calculate S^{M}_{p,k} for this event | |
334 | // Remark: final calculation of S^{M}_{p,k} follows after the loop over data bellow: | |
335 | for(Int_t p=0;p<8;p++) | |
336 | { | |
337 | for(Int_t k=0;k<9;k++) | |
338 | { | |
339 | (*fSMpk)(p,k)+=pow(wPhi*wPt*wEta,k); | |
340 | } | |
341 | } | |
342 | ||
343 | // differential flow: | |
344 | // 1D (pt): | |
345 | // (r_{m*m,k}(pt)): | |
346 | for(Int_t m=0;m<4;m++) | |
347 | { | |
348 | for(Int_t k=0;k<9;k++) | |
349 | { | |
350 | fReRPQ1dEBE[0][0][m][k]->Fill(dPt,pow(wPhi*wPt*wEta,k)*TMath::Cos((m+1.)*n*dPhi),1.); | |
351 | fImRPQ1dEBE[0][0][m][k]->Fill(dPt,pow(wPhi*wPt*wEta,k)*TMath::Sin((m+1.)*n*dPhi),1.); | |
352 | } | |
353 | } | |
354 | ||
355 | // s_{k}(pt) for RPs // to be improved (clarified) | |
356 | // Remark: final calculation of s_{p,k}(pt) follows after the loop over data bellow: | |
357 | for(Int_t k=0;k<9;k++) | |
358 | { | |
359 | fs1dEBE[0][0][k]->Fill(dPt,pow(wPhi*wPt*wEta,k),1.); | |
360 | } | |
361 | // 1D (eta): | |
362 | // (r_{m*m,k}(eta)): | |
363 | for(Int_t m=0;m<4;m++) | |
364 | { | |
365 | for(Int_t k=0;k<9;k++) | |
366 | { | |
367 | fReRPQ1dEBE[0][1][m][k]->Fill(dEta,pow(wPhi*wPt*wEta,k)*TMath::Cos((m+1.)*n*dPhi),1.); | |
368 | fImRPQ1dEBE[0][1][m][k]->Fill(dEta,pow(wPhi*wPt*wEta,k)*TMath::Sin((m+1.)*n*dPhi),1.); | |
369 | } | |
370 | } | |
371 | // s_{k}(eta) for RPs // to be improved (clarified) | |
372 | // Remark: final calculation of s_{p,k}(eta) follows after the loop over data bellow: | |
373 | for(Int_t k=0;k<9;k++) | |
374 | { | |
375 | fs1dEBE[0][1][k]->Fill(dEta,pow(wPhi*wPt*wEta,k),1.); | |
376 | } | |
489d5531 | 377 | // 2D (pt,eta): |
378 | if(fCalculate2DFlow) | |
379 | { | |
380 | // (r_{m*m,k}(pt,eta)): | |
381 | for(Int_t m=0;m<4;m++) | |
382 | { | |
383 | for(Int_t k=0;k<9;k++) | |
384 | { | |
385 | fReRPQ2dEBE[0][m][k]->Fill(dPt,dEta,pow(wPhi*wPt*wEta,k)*TMath::Cos((m+1.)*n*dPhi),1.); | |
386 | fImRPQ2dEBE[0][m][k]->Fill(dPt,dEta,pow(wPhi*wPt*wEta,k)*TMath::Sin((m+1.)*n*dPhi),1.); | |
387 | } | |
388 | } | |
389 | // s_{k}(pt,eta) for RPs // to be improved (clarified) | |
390 | // Remark: final calculation of s_{p,k}(pt,eta) follows after the loop over data bellow: | |
391 | for(Int_t k=0;k<9;k++) | |
392 | { | |
393 | fs2dEBE[0][k]->Fill(dPt,dEta,pow(wPhi*wPt*wEta,k),1.); | |
394 | } | |
395 | } // end of if(fCalculate2DFlow) | |
489d5531 | 396 | |
397 | if(aftsTrack->InPOISelection()) | |
398 | { | |
399 | // 1D (pt): | |
400 | // (q_{m*m,k}(pt)): | |
401 | for(Int_t m=0;m<4;m++) | |
402 | { | |
403 | for(Int_t k=0;k<9;k++) | |
404 | { | |
405 | fReRPQ1dEBE[2][0][m][k]->Fill(dPt,pow(wPhi*wPt*wEta,k)*TMath::Cos((m+1.)*n*dPhi),1.); | |
406 | fImRPQ1dEBE[2][0][m][k]->Fill(dPt,pow(wPhi*wPt*wEta,k)*TMath::Sin((m+1.)*n*dPhi),1.); | |
407 | } | |
408 | } | |
409 | // s_{k}(pt) for RP&&POIs // to be improved (clarified) | |
410 | // Remark: final calculation of s_{p,k}(pt,eta) follows after the loop over data bellow: | |
411 | for(Int_t k=0;k<9;k++) | |
412 | { | |
413 | fs1dEBE[2][0][k]->Fill(dPt,pow(wPhi*wPt*wEta,k),1.); | |
414 | } | |
415 | // 1D (eta): | |
416 | // (q_{m*m,k}(eta)): | |
417 | for(Int_t m=0;m<4;m++) | |
418 | { | |
419 | for(Int_t k=0;k<9;k++) | |
420 | { | |
421 | fReRPQ1dEBE[2][1][m][k]->Fill(dEta,pow(wPhi*wPt*wEta,k)*TMath::Cos((m+1.)*n*dPhi),1.); | |
422 | fImRPQ1dEBE[2][1][m][k]->Fill(dEta,pow(wPhi*wPt*wEta,k)*TMath::Sin((m+1.)*n*dPhi),1.); | |
423 | } | |
424 | } | |
425 | // s_{k}(eta) for RP&&POIs // to be improved (clarified) | |
426 | // Remark: final calculation of s_{p,k}(pt,eta) follows after the loop over data bellow: | |
427 | for(Int_t k=0;k<9;k++) | |
428 | { | |
429 | fs1dEBE[2][1][k]->Fill(dEta,pow(wPhi*wPt*wEta,k),1.); | |
b77b6434 | 430 | } |
489d5531 | 431 | // 2D (pt,eta) |
432 | if(fCalculate2DFlow) | |
433 | { | |
434 | // (q_{m*m,k}(pt,eta)): | |
435 | for(Int_t m=0;m<4;m++) | |
436 | { | |
437 | for(Int_t k=0;k<9;k++) | |
438 | { | |
439 | fReRPQ2dEBE[2][m][k]->Fill(dPt,dEta,pow(wPhi*wPt*wEta,k)*TMath::Cos((m+1.)*n*dPhi),1.); | |
440 | fImRPQ2dEBE[2][m][k]->Fill(dPt,dEta,pow(wPhi*wPt*wEta,k)*TMath::Sin((m+1.)*n*dPhi),1.); | |
441 | } | |
442 | } | |
443 | // s_{k}(pt,eta) for RP&&POIs // to be improved (clarified) | |
444 | // Remark: final calculation of s_{p,k}(pt,eta) follows after the loop over data bellow: | |
445 | for(Int_t k=0;k<9;k++) | |
446 | { | |
447 | fs2dEBE[2][k]->Fill(dPt,dEta,pow(wPhi*wPt*wEta,k),1.); | |
448 | } | |
449 | } // end of if(fCalculate2DFlow) | |
489d5531 | 450 | |
b77b6434 | 451 | } // end of if(aftsTrack->InPOISelection()) |
489d5531 | 452 | } // end of if(pTrack->InRPSelection()) |
453 | ||
489d5531 | 454 | if(aftsTrack->InPOISelection()) |
455 | { | |
456 | dPhi = aftsTrack->Phi(); | |
457 | dPt = aftsTrack->Pt(); | |
458 | dEta = aftsTrack->Eta(); | |
459 | ||
460 | // 1D (pt) | |
461 | // p_n(m*n,0): | |
462 | for(Int_t m=0;m<4;m++) | |
463 | { | |
464 | fReRPQ1dEBE[1][0][m][0]->Fill(dPt,TMath::Cos((m+1.)*n*dPhi),1.); | |
465 | fImRPQ1dEBE[1][0][m][0]->Fill(dPt,TMath::Sin((m+1.)*n*dPhi),1.); | |
466 | } | |
467 | // 1D (eta) | |
468 | // p_n(m*n,0): | |
469 | for(Int_t m=0;m<4;m++) | |
470 | { | |
471 | fReRPQ1dEBE[1][1][m][0]->Fill(dEta,TMath::Cos((m+1.)*n*dPhi),1.); | |
472 | fImRPQ1dEBE[1][1][m][0]->Fill(dEta,TMath::Sin((m+1.)*n*dPhi),1.); | |
473 | } | |
489d5531 | 474 | // 2D (pt,eta): |
475 | if(fCalculate2DFlow) | |
476 | { | |
477 | // p_n(m*n,0): | |
478 | for(Int_t m=0;m<4;m++) | |
479 | { | |
480 | fReRPQ2dEBE[1][m][0]->Fill(dPt,dEta,TMath::Cos((m+1.)*n*dPhi),1.); | |
481 | fImRPQ2dEBE[1][m][0]->Fill(dPt,dEta,TMath::Sin((m+1.)*n*dPhi),1.); | |
482 | } | |
483 | } // end of if(fCalculate2DFlow) | |
b77b6434 | 484 | } // end of if(pTrack->InPOISelection()) |
485 | ||
489d5531 | 486 | } else // to if(aftsTrack) |
487 | { | |
488 | cout<<endl; | |
489 | cout<<" WARNING: no particle! (i.e. aftsTrack is a NULL pointer in AFAWQC::Make().)"<<endl; | |
490 | cout<<endl; | |
491 | } | |
492 | } // end of for(Int_t i=0;i<nPrim;i++) | |
493 | ||
494 | // calculate the final expressions for S^{M}_{p,k}: | |
495 | for(Int_t p=0;p<8;p++) | |
496 | { | |
497 | for(Int_t k=0;k<9;k++) | |
498 | { | |
499 | (*fSMpk)(p,k)=pow((*fSMpk)(p,k),p+1); | |
500 | } | |
501 | } | |
502 | ||
b3dacf6b | 503 | // e) Call all the methods which calculate correlations for reference flow: |
489d5531 | 504 | if(!fEvaluateIntFlowNestedLoops) |
505 | { | |
506 | if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) | |
507 | { | |
508 | if(nRP>1) this->CalculateIntFlowCorrelations(); // without using particle weights | |
0328db2d | 509 | } else // to if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) |
489d5531 | 510 | { |
511 | if(nRP>1) this->CalculateIntFlowCorrelationsUsingParticleWeights(); // with using particle weights | |
512 | } | |
513 | ||
514 | if(nRP>3) this->CalculateIntFlowProductOfCorrelations(); | |
515 | if(nRP>1) this->CalculateIntFlowSumOfEventWeights(); | |
516 | if(nRP>1) this->CalculateIntFlowSumOfProductOfEventWeights(); | |
b92ea2b9 | 517 | |
518 | // non-isotropic terms: | |
519 | if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) | |
489d5531 | 520 | { |
b92ea2b9 | 521 | if(nRP>0) this->CalculateIntFlowCorrectionsForNUASinTerms(); |
522 | if(nRP>0) this->CalculateIntFlowCorrectionsForNUACosTerms(); | |
523 | } else // to if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) | |
524 | { | |
525 | if(nRP>0) this->CalculateIntFlowCorrectionsForNUASinTermsUsingParticleWeights(); | |
526 | if(nRP>0) this->CalculateIntFlowCorrectionsForNUACosTermsUsingParticleWeights(); | |
527 | } | |
0328db2d | 528 | |
b92ea2b9 | 529 | if(nRP>0) this->CalculateIntFlowProductOfCorrectionTermsForNUA(); |
530 | if(nRP>0) this->CalculateIntFlowSumOfEventWeightsNUA(); | |
531 | if(nRP>0) this->CalculateIntFlowSumOfProductOfEventWeightsNUA(); | |
489d5531 | 532 | } // end of if(!fEvaluateIntFlowNestedLoops) |
533 | ||
b3dacf6b | 534 | // f) Call all the methods which calculate correlations for differential flow: |
489d5531 | 535 | if(!fEvaluateDiffFlowNestedLoops) |
536 | { | |
537 | if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) | |
538 | { | |
539 | // without using particle weights: | |
540 | this->CalculateDiffFlowCorrelations("RP","Pt"); | |
541 | this->CalculateDiffFlowCorrelations("RP","Eta"); | |
542 | this->CalculateDiffFlowCorrelations("POI","Pt"); | |
57340a27 | 543 | this->CalculateDiffFlowCorrelations("POI","Eta"); |
b92ea2b9 | 544 | // non-isotropic terms: |
545 | this->CalculateDiffFlowCorrectionsForNUASinTerms("RP","Pt"); | |
546 | this->CalculateDiffFlowCorrectionsForNUASinTerms("RP","Eta"); | |
547 | this->CalculateDiffFlowCorrectionsForNUASinTerms("POI","Pt"); | |
548 | this->CalculateDiffFlowCorrectionsForNUASinTerms("POI","Eta"); | |
549 | this->CalculateDiffFlowCorrectionsForNUACosTerms("RP","Pt"); | |
550 | this->CalculateDiffFlowCorrectionsForNUACosTerms("RP","Eta"); | |
551 | this->CalculateDiffFlowCorrectionsForNUACosTerms("POI","Pt"); | |
552 | this->CalculateDiffFlowCorrectionsForNUACosTerms("POI","Eta"); | |
489d5531 | 553 | } else // to if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) |
554 | { | |
555 | // with using particle weights: | |
556 | this->CalculateDiffFlowCorrelationsUsingParticleWeights("RP","Pt"); | |
557 | this->CalculateDiffFlowCorrelationsUsingParticleWeights("RP","Eta"); | |
558 | this->CalculateDiffFlowCorrelationsUsingParticleWeights("POI","Pt"); | |
559 | this->CalculateDiffFlowCorrelationsUsingParticleWeights("POI","Eta"); | |
b92ea2b9 | 560 | // non-isotropic terms: |
561 | this->CalculateDiffFlowCorrectionsForNUASinTermsUsingParticleWeights("RP","Pt"); | |
562 | this->CalculateDiffFlowCorrectionsForNUASinTermsUsingParticleWeights("RP","Eta"); | |
563 | this->CalculateDiffFlowCorrectionsForNUASinTermsUsingParticleWeights("POI","Pt"); | |
564 | this->CalculateDiffFlowCorrectionsForNUASinTermsUsingParticleWeights("POI","Eta"); | |
565 | this->CalculateDiffFlowCorrectionsForNUACosTermsUsingParticleWeights("RP","Pt"); | |
566 | this->CalculateDiffFlowCorrectionsForNUACosTermsUsingParticleWeights("RP","Eta"); | |
567 | this->CalculateDiffFlowCorrectionsForNUACosTermsUsingParticleWeights("POI","Pt"); | |
568 | this->CalculateDiffFlowCorrectionsForNUACosTermsUsingParticleWeights("POI","Eta"); | |
489d5531 | 569 | } |
57340a27 | 570 | |
489d5531 | 571 | // whether or not using particle weights the following is calculated in the same way: |
572 | this->CalculateDiffFlowProductOfCorrelations("RP","Pt"); | |
573 | this->CalculateDiffFlowProductOfCorrelations("RP","Eta"); | |
574 | this->CalculateDiffFlowProductOfCorrelations("POI","Pt"); | |
575 | this->CalculateDiffFlowProductOfCorrelations("POI","Eta"); | |
576 | this->CalculateDiffFlowSumOfEventWeights("RP","Pt"); | |
577 | this->CalculateDiffFlowSumOfEventWeights("RP","Eta"); | |
578 | this->CalculateDiffFlowSumOfEventWeights("POI","Pt"); | |
579 | this->CalculateDiffFlowSumOfEventWeights("POI","Eta"); | |
580 | this->CalculateDiffFlowSumOfProductOfEventWeights("RP","Pt"); | |
581 | this->CalculateDiffFlowSumOfProductOfEventWeights("RP","Eta"); | |
582 | this->CalculateDiffFlowSumOfProductOfEventWeights("POI","Pt"); | |
583 | this->CalculateDiffFlowSumOfProductOfEventWeights("POI","Eta"); | |
584 | } // end of if(!fEvaluateDiffFlowNestedLoops) | |
585 | ||
586 | ||
587 | ||
588 | // with weights: | |
589 | // ... | |
590 | ||
591 | /* | |
592 | // 2D differential flow | |
593 | if(fCalculate2DFlow) | |
594 | { | |
595 | // without weights: | |
596 | if(nRP>1) this->CalculateCorrelationsForDifferentialFlow2D("RP"); | |
597 | if(nRP>1) this->CalculateCorrelationsForDifferentialFlow2D("POI"); | |
598 | ||
599 | // with weights: | |
600 | if(fUsePhiWeights||fUsePtWeights||fUseEtaWeights) | |
601 | { | |
602 | if(nRP>1) this->CalculateWeightedCorrelationsForDifferentialFlow2D("RP"); | |
603 | if(nRP>1) this->CalculateWeightedCorrelationsForDifferentialFlow2D("POI"); | |
604 | } | |
605 | } // end of if(fCalculate2DFlow) | |
606 | */ | |
57340a27 | 607 | |
e5834fcb | 608 | // g) Distributions of correlations: |
609 | if(fStoreDistributions){this->StoreDistributionsOfCorrelations();} | |
610 | ||
611 | // h) Store phi distribution for one event to illustrate flow: | |
612 | if(fStorePhiDistributionForOneEvent){this->StorePhiDistributionForOneEvent(anEvent);} | |
489d5531 | 613 | |
b3dacf6b | 614 | // h) Debugging and cross-checking (evaluate nested loops): |
615 | // h1) cross-checking results for integrated flow: | |
489d5531 | 616 | if(fEvaluateIntFlowNestedLoops) |
617 | { | |
618 | if(nPrim>0 && nPrim<=fMaxAllowedMultiplicity) // by default fMaxAllowedMultiplicity = 10 | |
619 | { | |
620 | // without using particle weights: | |
621 | if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) | |
622 | { | |
623 | // correlations: | |
624 | this->CalculateIntFlowCorrelations(); // from Q-vectors | |
625 | this->EvaluateIntFlowCorrelationsWithNestedLoops(anEvent); // from nested loops (to be improved: do I have to pass here anEvent or not?) | |
626 | // correction for non-uniform acceptance: | |
627 | this->CalculateIntFlowCorrectionsForNUASinTerms(); // from Q-vectors (sin terms) | |
628 | this->CalculateIntFlowCorrectionsForNUACosTerms(); // from Q-vectors (cos terms) | |
629 | this->EvaluateIntFlowCorrectionsForNUAWithNestedLoops(anEvent); // from nested loops (both sin and cos terms) | |
630 | } | |
631 | // using particle weights: | |
632 | if(fUsePhiWeights||fUsePtWeights||fUseEtaWeights) | |
633 | { | |
634 | // correlations: | |
635 | this->CalculateIntFlowCorrelationsUsingParticleWeights(); // from Q-vectors | |
636 | this->EvaluateIntFlowCorrelationsWithNestedLoopsUsingParticleWeights(anEvent); // from nested loops (to be improved: do I have to pass here anEvent or not?) | |
637 | // correction for non-uniform acceptance: | |
638 | this->CalculateIntFlowCorrectionsForNUASinTermsUsingParticleWeights(); // from Q-vectors (sin terms) | |
639 | this->CalculateIntFlowCorrectionsForNUACosTermsUsingParticleWeights(); // from Q-vectors (cos terms) | |
57340a27 | 640 | this->EvaluateIntFlowCorrectionsForNUAWithNestedLoopsUsingParticleWeights(anEvent); // from nested loops (both sin and cos terms) |
489d5531 | 641 | } |
642 | } else if (nPrim>fMaxAllowedMultiplicity) // to if(nPrim>0 && nPrim<=fMaxAllowedMultiplicity) | |
643 | { | |
644 | cout<<endl; | |
645 | cout<<"Skipping the event because multiplicity is "<<nPrim<<". Too high to evaluate nested loops!"<<endl; | |
646 | } else | |
647 | { | |
648 | cout<<endl; | |
649 | cout<<"Skipping the event because multiplicity is "<<nPrim<<"."<<endl; | |
650 | } | |
651 | } // end of if(fEvaluateIntFlowNestedLoops) | |
652 | ||
b3dacf6b | 653 | // h2) cross-checking results for differential flow: |
489d5531 | 654 | if(fEvaluateDiffFlowNestedLoops) |
655 | { | |
656 | if(nPrim>0 && nPrim<=fMaxAllowedMultiplicity) // by default fMaxAllowedMultiplicity = 10 | |
657 | { | |
658 | // without using particle weights: | |
659 | if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) | |
660 | { | |
661 | // reduced correlations: | |
662 | // Q-vectors: | |
663 | this->CalculateDiffFlowCorrelations("RP","Pt"); | |
664 | this->CalculateDiffFlowCorrelations("RP","Eta"); | |
665 | this->CalculateDiffFlowCorrelations("POI","Pt"); | |
666 | this->CalculateDiffFlowCorrelations("POI","Eta"); | |
667 | // nested loops: | |
668 | this->EvaluateDiffFlowCorrelationsWithNestedLoops(anEvent,"RP","Pt"); | |
669 | this->EvaluateDiffFlowCorrelationsWithNestedLoops(anEvent,"RP","Eta"); | |
670 | this->EvaluateDiffFlowCorrelationsWithNestedLoops(anEvent,"POI","Pt"); | |
671 | this->EvaluateDiffFlowCorrelationsWithNestedLoops(anEvent,"POI","Eta"); | |
672 | // reduced corrections for non-uniform acceptance: | |
673 | // Q-vectors: | |
674 | this->CalculateDiffFlowCorrectionsForNUASinTerms("RP","Pt"); | |
675 | this->CalculateDiffFlowCorrectionsForNUASinTerms("RP","Eta"); | |
676 | this->CalculateDiffFlowCorrectionsForNUASinTerms("POI","Pt"); | |
677 | this->CalculateDiffFlowCorrectionsForNUASinTerms("POI","Eta"); | |
678 | this->CalculateDiffFlowCorrectionsForNUACosTerms("RP","Pt"); | |
679 | this->CalculateDiffFlowCorrectionsForNUACosTerms("RP","Eta"); | |
680 | this->CalculateDiffFlowCorrectionsForNUACosTerms("POI","Pt"); | |
681 | this->CalculateDiffFlowCorrectionsForNUACosTerms("POI","Eta"); | |
682 | // nested loops: | |
683 | this->EvaluateDiffFlowCorrectionTermsForNUAWithNestedLoops(anEvent,"RP","Pt"); | |
684 | this->EvaluateDiffFlowCorrectionTermsForNUAWithNestedLoops(anEvent,"RP","Eta"); | |
685 | this->EvaluateDiffFlowCorrectionTermsForNUAWithNestedLoops(anEvent,"POI","Pt"); | |
686 | this->EvaluateDiffFlowCorrectionTermsForNUAWithNestedLoops(anEvent,"POI","Eta"); | |
687 | } // end of if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) | |
688 | // using particle weights: | |
689 | if(fUsePhiWeights||fUsePtWeights||fUseEtaWeights) | |
690 | { | |
691 | this->CalculateDiffFlowCorrelationsUsingParticleWeights("RP","Pt"); | |
692 | this->CalculateDiffFlowCorrelationsUsingParticleWeights("RP","Eta"); | |
693 | this->CalculateDiffFlowCorrelationsUsingParticleWeights("POI","Pt"); | |
694 | this->CalculateDiffFlowCorrelationsUsingParticleWeights("POI","Eta"); | |
695 | this->CalculateDiffFlowCorrectionsForNUASinTermsUsingParticleWeights("RP","Pt"); | |
696 | this->CalculateDiffFlowCorrectionsForNUASinTermsUsingParticleWeights("RP","Eta"); | |
697 | this->CalculateDiffFlowCorrectionsForNUASinTermsUsingParticleWeights("POI","Pt"); | |
698 | this->CalculateDiffFlowCorrectionsForNUASinTermsUsingParticleWeights("POI","Eta"); | |
699 | this->CalculateDiffFlowCorrectionsForNUACosTermsUsingParticleWeights("RP","Pt"); | |
700 | this->CalculateDiffFlowCorrectionsForNUACosTermsUsingParticleWeights("RP","Eta"); | |
701 | this->CalculateDiffFlowCorrectionsForNUACosTermsUsingParticleWeights("POI","Pt"); | |
702 | this->CalculateDiffFlowCorrectionsForNUACosTermsUsingParticleWeights("POI","Eta"); | |
703 | this->EvaluateDiffFlowCorrelationsWithNestedLoopsUsingParticleWeights(anEvent,"RP","Pt"); | |
704 | this->EvaluateDiffFlowCorrelationsWithNestedLoopsUsingParticleWeights(anEvent,"RP","Eta"); | |
705 | this->EvaluateDiffFlowCorrelationsWithNestedLoopsUsingParticleWeights(anEvent,"POI","Pt"); | |
3b552efe | 706 | this->EvaluateDiffFlowCorrelationsWithNestedLoopsUsingParticleWeights(anEvent,"POI","Eta"); |
489d5531 | 707 | this->EvaluateDiffFlowCorrectionTermsForNUAWithNestedLoopsUsingParticleWeights(anEvent,"RP","Pt"); |
708 | this->EvaluateDiffFlowCorrectionTermsForNUAWithNestedLoopsUsingParticleWeights(anEvent,"RP","Eta"); | |
709 | this->EvaluateDiffFlowCorrectionTermsForNUAWithNestedLoopsUsingParticleWeights(anEvent,"POI","Pt"); | |
710 | this->EvaluateDiffFlowCorrectionTermsForNUAWithNestedLoopsUsingParticleWeights(anEvent,"POI","Eta"); | |
711 | } // end of if(fUsePhiWeights||fUsePtWeights||fUseEtaWeights) | |
712 | } // end of if(nPrim>0 && nPrim<=fMaxAllowedMultiplicity) // by default fMaxAllowedMultiplicity = 10 | |
713 | } // end of if(fEvaluateDiffFlowNestedLoops) | |
714 | ||
b3dacf6b | 715 | // i) Reset all event-by-event quantities. |
489d5531 | 716 | this->ResetEventByEventQuantities(); |
717 | ||
718 | } // end of AliFlowAnalysisWithQCumulants::Make(AliFlowEventSimple* anEvent) | |
719 | ||
489d5531 | 720 | //================================================================================================================================ |
721 | ||
489d5531 | 722 | void AliFlowAnalysisWithQCumulants::Finish() |
723 | { | |
724 | // Calculate the final results. | |
489d5531 | 725 | |
b3dacf6b | 726 | // a) Check all pointers used in this method; |
727 | // b) Acces the constants; | |
728 | // c) Access the flags; | |
b92ea2b9 | 729 | // d) Calculate reference cumulants (not corrected for detector effects); |
730 | // e) Correct reference cumulants for detector effects; | |
731 | // f) Calculate reference flow; | |
b77b6434 | 732 | // g) Store results for reference flow in AliFlowCommonHistResults and print them on the screen; |
733 | ||
b92ea2b9 | 734 | |
735 | ||
b92ea2b9 | 736 | // h) Calculate the final results for differential flow (without/with weights); |
737 | // i) Correct the results for differential flow (without/with weights) for effects of non-uniform acceptance (NUA); | |
738 | // j) Calculate the final results for integrated flow (RP/POI) and store in AliFlowCommonHistResults; | |
739 | // k) Store results for differential flow in AliFlowCommonHistResults; | |
740 | // l) Print the final results for integrated flow (RP/POI) on the screen; | |
741 | // m) Cross-checking: Results from Q-vectors vs results from nested loops. | |
b3dacf6b | 742 | |
743 | // a) Check all pointers used in this method: | |
744 | this->CheckPointersUsedInFinish(); | |
745 | ||
746 | // b) Acces the constants: | |
489d5531 | 747 | this->AccessConstants(); |
748 | ||
b3dacf6b | 749 | if(fCommonHists && fCommonHists->GetHarmonic()) // to be improved (moved somewhere else) |
489d5531 | 750 | { |
b3dacf6b | 751 | fHarmonic = (Int_t)(fCommonHists->GetHarmonic())->GetBinContent(1); |
489d5531 | 752 | } |
b3dacf6b | 753 | |
754 | // c) Access the flags: // to be improved (implement a method for this) | |
755 | fUsePhiWeights = (Bool_t)fUseParticleWeights->GetBinContent(1); | |
756 | fUsePtWeights = (Bool_t)fUseParticleWeights->GetBinContent(2); | |
757 | fUseEtaWeights = (Bool_t)fUseParticleWeights->GetBinContent(3); | |
758 | fApplyCorrectionForNUA = (Bool_t)fIntFlowFlags->GetBinContent(3); | |
759 | fPrintFinalResults[0] = (Bool_t)fIntFlowFlags->GetBinContent(4); | |
760 | fPrintFinalResults[1] = (Bool_t)fIntFlowFlags->GetBinContent(5); | |
761 | fPrintFinalResults[2] = (Bool_t)fIntFlowFlags->GetBinContent(6); | |
762 | fPrintFinalResults[3] = (Bool_t)fIntFlowFlags->GetBinContent(7); | |
763 | fApplyCorrectionForNUAVsM = (Bool_t)fIntFlowFlags->GetBinContent(8); | |
b77b6434 | 764 | fPropagateErrorAlsoFromNIT = (Bool_t)fIntFlowFlags->GetBinContent(9); |
0dd3b008 | 765 | fCalculateCumulantsVsM = (Bool_t)fIntFlowFlags->GetBinContent(10); |
766 | fMinimumBiasReferenceFlow = (Bool_t)fIntFlowFlags->GetBinContent(11); | |
e5834fcb | 767 | fForgetAboutCovariances = (Bool_t)fIntFlowFlags->GetBinContent(12); |
768 | fStorePhiDistributionForOneEvent = (Bool_t)fIntFlowFlags->GetBinContent(13); | |
dd442cd2 | 769 | fFillMultipleControlHistograms = (Bool_t)fIntFlowFlags->GetBinContent(14); |
b3dacf6b | 770 | fEvaluateIntFlowNestedLoops = (Bool_t)fEvaluateNestedLoops->GetBinContent(1); |
771 | fEvaluateDiffFlowNestedLoops = (Bool_t)fEvaluateNestedLoops->GetBinContent(2); | |
489d5531 | 772 | fCrossCheckInPtBinNo = (Int_t)fEvaluateNestedLoops->GetBinContent(3); |
773 | fCrossCheckInEtaBinNo = (Int_t)fEvaluateNestedLoops->GetBinContent(4); | |
8e1cefdd | 774 | |
b92ea2b9 | 775 | // d) Calculate reference cumulants (not corrected for detector effects): |
489d5531 | 776 | this->FinalizeCorrelationsIntFlow(); |
777 | this->CalculateCovariancesIntFlow(); | |
778 | this->CalculateCumulantsIntFlow(); | |
489d5531 | 779 | |
b92ea2b9 | 780 | // e) Correct reference cumulants for detector effects: |
781 | this->FinalizeCorrectionTermsForNUAIntFlow(); | |
782 | this->CalculateCovariancesNUAIntFlow(); | |
783 | this->CalculateQcumulantsCorrectedForNUAIntFlow(); | |
784 | ||
785 | // f) Calculate reference flow: | |
786 | this->CalculateReferenceFlow(); | |
489d5531 | 787 | |
b77b6434 | 788 | // g) Store results for reference flow in AliFlowCommonHistResults and print them on the screen: |
489d5531 | 789 | this->FillCommonHistResultsIntFlow(); |
b3dacf6b | 790 | if(fPrintFinalResults[0]){this->PrintFinalResultsForIntegratedFlow("RF");} |
791 | if(fPrintFinalResults[3] && fCalculateCumulantsVsM){this->PrintFinalResultsForIntegratedFlow("RF, rebinned in M");} | |
489d5531 | 792 | |
b77b6434 | 793 | |
794 | ||
795 | ||
796 | ||
797 | ||
798 | ||
799 | ||
800 | ||
b3dacf6b | 801 | // g) Calculate the final results for differential flow (without/with weights): |
489d5531 | 802 | this->FinalizeReducedCorrelations("RP","Pt"); |
803 | this->FinalizeReducedCorrelations("RP","Eta"); | |
804 | this->FinalizeReducedCorrelations("POI","Pt"); | |
805 | this->FinalizeReducedCorrelations("POI","Eta"); | |
806 | this->CalculateDiffFlowCovariances("RP","Pt"); | |
807 | this->CalculateDiffFlowCovariances("RP","Eta"); | |
808 | this->CalculateDiffFlowCovariances("POI","Pt"); | |
809 | this->CalculateDiffFlowCovariances("POI","Eta"); | |
810 | this->CalculateDiffFlowCumulants("RP","Pt"); | |
811 | this->CalculateDiffFlowCumulants("RP","Eta"); | |
812 | this->CalculateDiffFlowCumulants("POI","Pt"); | |
813 | this->CalculateDiffFlowCumulants("POI","Eta"); | |
814 | this->CalculateDiffFlow("RP","Pt"); | |
815 | this->CalculateDiffFlow("RP","Eta"); | |
816 | this->CalculateDiffFlow("POI","Pt"); | |
817 | this->CalculateDiffFlow("POI","Eta"); | |
818 | ||
b3dacf6b | 819 | // h) Correct the results for differential flow (without/with weights) for effects of non-uniform acceptance (NUA): |
820 | if(fApplyCorrectionForNUA) | |
489d5531 | 821 | { |
822 | this->FinalizeCorrectionTermsForNUADiffFlow("RP","Pt"); | |
823 | this->FinalizeCorrectionTermsForNUADiffFlow("RP","Eta"); | |
824 | this->FinalizeCorrectionTermsForNUADiffFlow("POI","Pt"); | |
825 | this->FinalizeCorrectionTermsForNUADiffFlow("POI","Eta"); | |
826 | this->CalculateDiffFlowCumulantsCorrectedForNUA("RP","Pt"); | |
827 | this->CalculateDiffFlowCumulantsCorrectedForNUA("RP","Eta"); | |
828 | this->CalculateDiffFlowCumulantsCorrectedForNUA("POI","Pt"); | |
829 | this->CalculateDiffFlowCumulantsCorrectedForNUA("POI","Eta"); | |
830 | this->CalculateDiffFlowCorrectedForNUA("RP","Pt"); | |
831 | this->CalculateDiffFlowCorrectedForNUA("RP","Eta"); | |
832 | this->CalculateDiffFlowCorrectedForNUA("POI","Pt"); | |
833 | this->CalculateDiffFlowCorrectedForNUA("POI","Eta"); | |
3b552efe | 834 | } |
489d5531 | 835 | |
b3dacf6b | 836 | // i) Calculate the final results for integrated flow (RP/POI) and store in AliFlowCommonHistResults: |
489d5531 | 837 | this->CalculateFinalResultsForRPandPOIIntegratedFlow("RP"); |
838 | this->CalculateFinalResultsForRPandPOIIntegratedFlow("POI"); | |
839 | ||
b3dacf6b | 840 | // j) Store results for differential flow in AliFlowCommonHistResults: |
489d5531 | 841 | this->FillCommonHistResultsDiffFlow("RP"); |
842 | this->FillCommonHistResultsDiffFlow("POI"); | |
843 | ||
b3dacf6b | 844 | // k) Print the final results for integrated flow (RP/POI) on the screen: |
845 | if(fPrintFinalResults[1]){this->PrintFinalResultsForIntegratedFlow("RP");} | |
846 | if(fPrintFinalResults[2]){this->PrintFinalResultsForIntegratedFlow("POI");} | |
847 | ||
848 | // l) Cross-checking: Results from Q-vectors vs results from nested loops: | |
849 | // l1) Reference flow: | |
489d5531 | 850 | if(fEvaluateIntFlowNestedLoops) |
851 | { | |
852 | this->CrossCheckIntFlowCorrelations(); | |
853 | this->CrossCheckIntFlowCorrectionTermsForNUA(); | |
854 | if(fUsePhiWeights||fUsePtWeights||fUseEtaWeights) this->CrossCheckIntFlowExtraCorrelations(); | |
855 | } // end of if(fEvaluateIntFlowNestedLoops) | |
856 | ||
b3dacf6b | 857 | // l2) Differential flow: |
489d5531 | 858 | if(fEvaluateDiffFlowNestedLoops) |
859 | { | |
b3dacf6b | 860 | // Correlations: |
489d5531 | 861 | this->PrintNumberOfParticlesInSelectedBin(); |
862 | this->CrossCheckDiffFlowCorrelations("RP","Pt"); | |
863 | this->CrossCheckDiffFlowCorrelations("RP","Eta"); | |
864 | this->CrossCheckDiffFlowCorrelations("POI","Pt"); | |
865 | this->CrossCheckDiffFlowCorrelations("POI","Eta"); | |
b3dacf6b | 866 | // Correction terms for non-uniform acceptance: |
489d5531 | 867 | this->CrossCheckDiffFlowCorrectionTermsForNUA("RP","Pt"); |
868 | this->CrossCheckDiffFlowCorrectionTermsForNUA("RP","Eta"); | |
869 | this->CrossCheckDiffFlowCorrectionTermsForNUA("POI","Pt"); | |
870 | this->CrossCheckDiffFlowCorrectionTermsForNUA("POI","Eta"); | |
871 | } // end of if(fEvaluateDiffFlowNestedLoops) | |
872 | ||
873 | } // end of AliFlowAnalysisWithQCumulants::Finish() | |
874 | ||
489d5531 | 875 | //================================================================================================================================ |
876 | ||
489d5531 | 877 | void AliFlowAnalysisWithQCumulants::CalculateIntFlowCorrectionsForNUACosTerms() |
878 | { | |
b92ea2b9 | 879 | // Calculate correction terms for non-uniform acceptance of the detector for reference flow (cos terms). |
489d5531 | 880 | |
881 | // multiplicity: | |
882 | Double_t dMult = (*fSMpk)(0,0); | |
883 | ||
884 | // real and imaginary parts of non-weighted Q-vectors evaluated in harmonics n, 2n, 3n and 4n: | |
885 | Double_t dReQ1n = (*fReQ)(0,0); | |
886 | Double_t dReQ2n = (*fReQ)(1,0); | |
887 | //Double_t dReQ3n = (*fReQ)(2,0); | |
888 | //Double_t dReQ4n = (*fReQ)(3,0); | |
889 | Double_t dImQ1n = (*fImQ)(0,0); | |
890 | Double_t dImQ2n = (*fImQ)(1,0); | |
891 | //Double_t dImQ3n = (*fImQ)(2,0); | |
892 | //Double_t dImQ4n = (*fImQ)(3,0); | |
893 | ||
894 | // ************************************************************* | |
895 | // **** corrections for non-uniform acceptance (cos terms): **** | |
896 | // ************************************************************* | |
897 | // | |
898 | // Remark 1: corrections for non-uniform acceptance (cos terms) calculated with non-weighted Q-vectors | |
899 | // are stored in 1D profile fQCorrectionsCos. | |
900 | // Remark 2: binning of fIntFlowCorrectionTermsForNUAPro[1] is organized as follows: | |
901 | // -------------------------------------------------------------------------------------------------------------------- | |
902 | // 1st bin: <<cos(n*(phi1))>> = cosP1n | |
903 | // 2nd bin: <<cos(n*(phi1+phi2))>> = cosP1nP1n | |
904 | // 3rd bin: <<cos(n*(phi1-phi2-phi3))>> = cosP1nM1nM1n | |
905 | // 4th bin: <<cos(n*(2phi1-phi2))>> = cosP2nM1n | |
906 | // -------------------------------------------------------------------------------------------------------------------- | |
907 | ||
908 | // 1-particle: | |
909 | Double_t cosP1n = 0.; // <<cos(n*(phi1))>> | |
910 | ||
911 | if(dMult>0) | |
912 | { | |
913 | cosP1n = dReQ1n/dMult; | |
914 | ||
915 | // average non-weighted 1-particle correction (cos terms) for non-uniform acceptance for single event: | |
916 | fIntFlowCorrectionTermsForNUAEBE[1]->SetBinContent(1,cosP1n); | |
0328db2d | 917 | // event weights for NUA terms: |
918 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->SetBinContent(1,dMult); | |
489d5531 | 919 | |
920 | // final average non-weighted 1-particle correction (cos terms) for non-uniform acceptance for all events: | |
921 | fIntFlowCorrectionTermsForNUAPro[1]->Fill(0.5,cosP1n,dMult); | |
b3dacf6b | 922 | if(fCalculateCumulantsVsM){fIntFlowCorrectionTermsForNUAVsMPro[1][0]->Fill(dMult+0.5,cosP1n,dMult);} |
489d5531 | 923 | } |
924 | ||
925 | // 2-particle: | |
3b552efe | 926 | Double_t cosP1nP1n = 0.; // <<cos(n*(phi1+phi2))>> |
489d5531 | 927 | Double_t cosP2nM1n = 0.; // <<cos(n*(2phi1-phi2))>> |
928 | ||
929 | if(dMult>1) | |
930 | { | |
931 | cosP1nP1n = (pow(dReQ1n,2)-pow(dImQ1n,2)-dReQ2n)/(dMult*(dMult-1)); | |
932 | cosP2nM1n = (dReQ2n*dReQ1n+dImQ2n*dImQ1n-dReQ1n)/(dMult*(dMult-1)); | |
933 | ||
934 | // average non-weighted 2-particle correction (cos terms) for non-uniform acceptance for single event: | |
3b552efe | 935 | fIntFlowCorrectionTermsForNUAEBE[1]->SetBinContent(2,cosP1nP1n); |
489d5531 | 936 | fIntFlowCorrectionTermsForNUAEBE[1]->SetBinContent(4,cosP2nM1n); |
0328db2d | 937 | // event weights for NUA terms: |
938 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->SetBinContent(2,dMult*(dMult-1)); | |
939 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->SetBinContent(4,dMult*(dMult-1)); | |
940 | ||
489d5531 | 941 | // final average non-weighted 2-particle correction (cos terms) for non-uniform acceptance for all events: |
3b552efe | 942 | fIntFlowCorrectionTermsForNUAPro[1]->Fill(1.5,cosP1nP1n,dMult*(dMult-1)); |
489d5531 | 943 | fIntFlowCorrectionTermsForNUAPro[1]->Fill(3.5,cosP2nM1n,dMult*(dMult-1)); |
b3dacf6b | 944 | if(fCalculateCumulantsVsM) |
945 | { | |
946 | fIntFlowCorrectionTermsForNUAVsMPro[1][1]->Fill(dMult+0.5,cosP1nP1n,dMult*(dMult-1)); | |
947 | fIntFlowCorrectionTermsForNUAVsMPro[1][3]->Fill(dMult+0.5,cosP2nM1n,dMult*(dMult-1)); | |
948 | } | |
489d5531 | 949 | } |
950 | ||
951 | // 3-particle: | |
952 | Double_t cosP1nM1nM1n = 0.; // <<cos(n*(phi1-phi2-phi3))>> | |
953 | ||
954 | if(dMult>2) | |
955 | { | |
956 | cosP1nM1nM1n = (dReQ1n*(pow(dReQ1n,2)+pow(dImQ1n,2))-dReQ1n*dReQ2n-dImQ1n*dImQ2n-2.*(dMult-1)*dReQ1n) | |
957 | / (dMult*(dMult-1)*(dMult-2)); | |
958 | ||
959 | // average non-weighted 3-particle correction (cos terms) for non-uniform acceptance for single event: | |
960 | fIntFlowCorrectionTermsForNUAEBE[1]->SetBinContent(3,cosP1nM1nM1n); | |
0328db2d | 961 | // event weights for NUA terms: |
962 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->SetBinContent(3,dMult*(dMult-1)*(dMult-2)); | |
489d5531 | 963 | |
964 | // final average non-weighted 3-particle correction (cos terms) for non-uniform acceptance for all events: | |
2001bc3a | 965 | fIntFlowCorrectionTermsForNUAPro[1]->Fill(2.5,cosP1nM1nM1n,dMult*(dMult-1)*(dMult-2)); |
b3dacf6b | 966 | if(fCalculateCumulantsVsM){fIntFlowCorrectionTermsForNUAVsMPro[1][2]->Fill(dMult+0.5,cosP1nM1nM1n,dMult*(dMult-1)*(dMult-2));} |
489d5531 | 967 | } |
968 | ||
969 | } // end of AliFlowAnalysisWithQCumulants::CalculateIntFlowCorrectionsForNUACosTerms() | |
970 | ||
971 | ||
972 | //================================================================================================================================ | |
973 | ||
974 | ||
975 | void AliFlowAnalysisWithQCumulants::CalculateIntFlowCorrectionsForNUASinTerms() | |
976 | { | |
977 | // calculate corrections for non-uniform acceptance of the detector for no-name integrated flow (sin terms) | |
978 | ||
979 | // multiplicity: | |
980 | Double_t dMult = (*fSMpk)(0,0); | |
981 | ||
982 | // real and imaginary parts of non-weighted Q-vectors evaluated in harmonics n, 2n, 3n and 4n: | |
983 | Double_t dReQ1n = (*fReQ)(0,0); | |
984 | Double_t dReQ2n = (*fReQ)(1,0); | |
985 | //Double_t dReQ3n = (*fReQ)(2,0); | |
986 | //Double_t dReQ4n = (*fReQ)(3,0); | |
987 | Double_t dImQ1n = (*fImQ)(0,0); | |
988 | Double_t dImQ2n = (*fImQ)(1,0); | |
989 | //Double_t dImQ3n = (*fImQ)(2,0); | |
990 | //Double_t dImQ4n = (*fImQ)(3,0); | |
991 | ||
992 | // ************************************************************* | |
993 | // **** corrections for non-uniform acceptance (sin terms): **** | |
994 | // ************************************************************* | |
995 | // | |
996 | // Remark 1: corrections for non-uniform acceptance (sin terms) calculated with non-weighted Q-vectors | |
997 | // are stored in 1D profile fQCorrectionsSin. | |
998 | // Remark 2: binning of fIntFlowCorrectionTermsForNUAPro[0] is organized as follows: | |
999 | // -------------------------------------------------------------------------------------------------------------------- | |
1000 | // 1st bin: <<sin(n*(phi1))>> = sinP1n | |
1001 | // 2nd bin: <<sin(n*(phi1+phi2))>> = sinP1nP1n | |
1002 | // 3rd bin: <<sin(n*(phi1-phi2-phi3))>> = sinP1nM1nM1n | |
1003 | // 4th bin: <<sin(n*(2phi1-phi2))>> = sinP2nM1n | |
1004 | // -------------------------------------------------------------------------------------------------------------------- | |
1005 | ||
1006 | // 1-particle: | |
1007 | Double_t sinP1n = 0.; // <sin(n*(phi1))> | |
1008 | ||
1009 | if(dMult>0) | |
1010 | { | |
1011 | sinP1n = dImQ1n/dMult; | |
1012 | ||
1013 | // average non-weighted 1-particle correction (sin terms) for non-uniform acceptance for single event: | |
0328db2d | 1014 | fIntFlowCorrectionTermsForNUAEBE[0]->SetBinContent(1,sinP1n); |
1015 | // event weights for NUA terms: | |
1016 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->SetBinContent(1,dMult); | |
489d5531 | 1017 | |
1018 | // final average non-weighted 1-particle correction (sin terms) for non-uniform acceptance for all events: | |
1019 | fIntFlowCorrectionTermsForNUAPro[0]->Fill(0.5,sinP1n,dMult); | |
b3dacf6b | 1020 | if(fCalculateCumulantsVsM){fIntFlowCorrectionTermsForNUAVsMPro[0][0]->Fill(dMult+0.5,sinP1n,dMult);} |
489d5531 | 1021 | } |
1022 | ||
1023 | // 2-particle: | |
1024 | Double_t sinP1nP1n = 0.; // <<sin(n*(phi1+phi2))>> | |
1025 | Double_t sinP2nM1n = 0.; // <<sin(n*(2phi1-phi2))>> | |
1026 | if(dMult>1) | |
1027 | { | |
3b552efe | 1028 | sinP1nP1n = (2.*dReQ1n*dImQ1n-dImQ2n)/(dMult*(dMult-1)); |
489d5531 | 1029 | sinP2nM1n = (dImQ2n*dReQ1n-dReQ2n*dImQ1n-dImQ1n)/(dMult*(dMult-1)); |
1030 | ||
1031 | // average non-weighted 2-particle correction (sin terms) for non-uniform acceptance for single event: | |
1032 | fIntFlowCorrectionTermsForNUAEBE[0]->SetBinContent(2,sinP1nP1n); | |
3b552efe | 1033 | fIntFlowCorrectionTermsForNUAEBE[0]->SetBinContent(4,sinP2nM1n); |
0328db2d | 1034 | // event weights for NUA terms: |
1035 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->SetBinContent(2,dMult*(dMult-1)); | |
1036 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->SetBinContent(4,dMult*(dMult-1)); | |
489d5531 | 1037 | |
1038 | // final average non-weighted 1-particle correction (sin terms) for non-uniform acceptance for all events: | |
1039 | fIntFlowCorrectionTermsForNUAPro[0]->Fill(1.5,sinP1nP1n,dMult*(dMult-1)); | |
1040 | fIntFlowCorrectionTermsForNUAPro[0]->Fill(3.5,sinP2nM1n,dMult*(dMult-1)); | |
b3dacf6b | 1041 | if(fCalculateCumulantsVsM) |
1042 | { | |
1043 | fIntFlowCorrectionTermsForNUAVsMPro[0][1]->Fill(dMult+0.5,sinP1nP1n,dMult*(dMult-1)); | |
1044 | fIntFlowCorrectionTermsForNUAVsMPro[0][3]->Fill(dMult+0.5,sinP2nM1n,dMult*(dMult-1)); | |
1045 | } | |
489d5531 | 1046 | } |
1047 | ||
1048 | // 3-particle: | |
1049 | Double_t sinP1nM1nM1n = 0.; // <<sin(n*(phi1-phi2-phi3))>> | |
1050 | ||
1051 | if(dMult>2) | |
1052 | { | |
1053 | sinP1nM1nM1n = (-dImQ1n*(pow(dReQ1n,2)+pow(dImQ1n,2))+dReQ1n*dImQ2n-dImQ1n*dReQ2n+2.*(dMult-1)*dImQ1n) | |
1054 | / (dMult*(dMult-1)*(dMult-2)); | |
1055 | ||
1056 | // average non-weighted 3-particle correction (sin terms) for non-uniform acceptance for single event: | |
1057 | fIntFlowCorrectionTermsForNUAEBE[0]->SetBinContent(3,sinP1nM1nM1n); | |
0328db2d | 1058 | // event weights for NUA terms: |
1059 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->SetBinContent(3,dMult*(dMult-1)*(dMult-2)); | |
489d5531 | 1060 | |
1061 | // final average non-weighted 3-particle correction (sin terms) for non-uniform acceptance for all events: | |
2001bc3a | 1062 | fIntFlowCorrectionTermsForNUAPro[0]->Fill(2.5,sinP1nM1nM1n,dMult*(dMult-1)*(dMult-2)); |
b3dacf6b | 1063 | if(fCalculateCumulantsVsM){fIntFlowCorrectionTermsForNUAVsMPro[0][2]->Fill(dMult+0.5,sinP1nM1nM1n,dMult*(dMult-1)*(dMult-2));} |
489d5531 | 1064 | } |
1065 | ||
1066 | } // end of AliFlowAnalysisWithQCumulants::CalculateIntFlowCorrectionsForNUASinTerms() | |
1067 | ||
489d5531 | 1068 | //================================================================================================================================ |
1069 | ||
489d5531 | 1070 | void AliFlowAnalysisWithQCumulants::GetOutputHistograms(TList *outputListHistos) |
1071 | { | |
1072 | // a) Get pointers for common control and common result histograms and profiles. | |
1073 | // b) Get pointers for histograms with particle weights. | |
1074 | // c) Get pointers for histograms and profiles relevant for integrated flow. | |
1075 | // d) Get pointers for histograms and profiles relevant for differental flow. | |
1076 | // e) Get pointers for histograms and profiles holding results obtained with nested loops. | |
1077 | ||
1078 | if(outputListHistos) | |
3b552efe | 1079 | { |
1080 | this->SetHistList(outputListHistos); | |
1081 | if(!fHistList) | |
1082 | { | |
1083 | cout<<endl; | |
1084 | cout<<" WARNING (QC): fHistList is NULL in AFAWQC::GOH() !!!!"<<endl; | |
1085 | cout<<endl; | |
1086 | exit(0); | |
489d5531 | 1087 | } |
1088 | this->GetPointersForCommonHistograms(); | |
1089 | this->GetPointersForParticleWeightsHistograms(); | |
1090 | this->GetPointersForIntFlowHistograms(); | |
1091 | this->GetPointersForDiffFlowHistograms(); | |
1092 | this->GetPointersForNestedLoopsHistograms(); | |
3b552efe | 1093 | } else |
1094 | { | |
1095 | cout<<endl; | |
1096 | cout<<" WARNING (QC): outputListHistos is NULL in AFAWQC::GOH() !!!!"<<endl; | |
1097 | cout<<endl; | |
1098 | exit(0); | |
489d5531 | 1099 | } |
1100 | ||
1101 | } // end of void AliFlowAnalysisWithQCumulants::GetOutputHistograms(TList *outputListHistos) | |
ad87ae62 | 1102 | |
489d5531 | 1103 | //================================================================================================================================ |
1104 | ||
489d5531 | 1105 | TProfile* AliFlowAnalysisWithQCumulants::MakePtProjection(TProfile2D *profilePtEta) const |
ad87ae62 | 1106 | { |
489d5531 | 1107 | // project 2D profile onto pt axis to get 1D profile |
1108 | ||
1109 | Int_t nBinsPt = profilePtEta->GetNbinsX(); | |
1110 | Double_t dPtMin = (profilePtEta->GetXaxis())->GetXmin(); | |
1111 | Double_t dPtMax = (profilePtEta->GetXaxis())->GetXmax(); | |
1112 | ||
1113 | Int_t nBinsEta = profilePtEta->GetNbinsY(); | |
1114 | ||
1115 | TProfile *profilePt = new TProfile("","",nBinsPt,dPtMin,dPtMax); | |
1116 | ||
1117 | for(Int_t p=1;p<=nBinsPt;p++) | |
1118 | { | |
1119 | Double_t contentPt = 0.; | |
1120 | Double_t entryPt = 0.; | |
1121 | Double_t spreadPt = 0.; | |
1122 | Double_t sum1 = 0.; | |
1123 | Double_t sum2 = 0.; | |
1124 | Double_t sum3 = 0.; | |
1125 | for(Int_t e=1;e<=nBinsEta;e++) | |
1126 | { | |
1127 | contentPt += (profilePtEta->GetBinContent(profilePtEta->GetBin(p,e))) | |
1128 | * (profilePtEta->GetBinEntries(profilePtEta->GetBin(p,e))); | |
1129 | entryPt += (profilePtEta->GetBinEntries(profilePtEta->GetBin(p,e))); | |
1130 | ||
1131 | sum1 += (profilePtEta->GetBinEntries(profilePtEta->GetBin(p,e))) | |
1132 | * (pow(profilePtEta->GetBinError(profilePtEta->GetBin(p,e)),2.) | |
1133 | + pow(profilePtEta->GetBinContent(profilePtEta->GetBin(p,e)),2.)); | |
1134 | sum2 += (profilePtEta->GetBinEntries(profilePtEta->GetBin(p,e))); | |
1135 | sum3 += (profilePtEta->GetBinEntries(profilePtEta->GetBin(p,e))) | |
1136 | * (profilePtEta->GetBinContent(profilePtEta->GetBin(p,e))); | |
1137 | } | |
1138 | if(sum2>0. && sum1/sum2-pow(sum3/sum2,2.) > 0.) | |
1139 | { | |
1140 | spreadPt = pow(sum1/sum2-pow(sum3/sum2,2.),0.5); | |
1141 | } | |
1142 | profilePt->SetBinContent(p,contentPt); | |
1143 | profilePt->SetBinEntries(p,entryPt); | |
1144 | { | |
1145 | profilePt->SetBinError(p,spreadPt); | |
1146 | } | |
1147 | ||
1148 | } | |
1149 | ||
1150 | return profilePt; | |
1151 | ||
1152 | } // end of TProfile* AliFlowAnalysisWithQCumulants::MakePtProjection(TProfile2D *profilePtEta) | |
1153 | ||
1154 | ||
1155 | //================================================================================================================================ | |
1156 | ||
1157 | ||
1158 | TProfile* AliFlowAnalysisWithQCumulants::MakeEtaProjection(TProfile2D *profilePtEta) const | |
1159 | { | |
1160 | // project 2D profile onto eta axis to get 1D profile | |
1161 | ||
1162 | Int_t nBinsEta = profilePtEta->GetNbinsY(); | |
1163 | Double_t dEtaMin = (profilePtEta->GetYaxis())->GetXmin(); | |
1164 | Double_t dEtaMax = (profilePtEta->GetYaxis())->GetXmax(); | |
1165 | ||
1166 | Int_t nBinsPt = profilePtEta->GetNbinsX(); | |
1167 | ||
1168 | TProfile *profileEta = new TProfile("","",nBinsEta,dEtaMin,dEtaMax); | |
1169 | ||
1170 | for(Int_t e=1;e<=nBinsEta;e++) | |
1171 | { | |
1172 | Double_t contentEta = 0.; | |
1173 | Double_t entryEta = 0.; | |
1174 | for(Int_t p=1;p<=nBinsPt;p++) | |
1175 | { | |
1176 | contentEta += (profilePtEta->GetBinContent(profilePtEta->GetBin(p,e))) | |
1177 | * (profilePtEta->GetBinEntries(profilePtEta->GetBin(p,e))); | |
1178 | entryEta += (profilePtEta->GetBinEntries(profilePtEta->GetBin(p,e))); | |
1179 | } | |
1180 | profileEta->SetBinContent(e,contentEta); | |
1181 | profileEta->SetBinEntries(e,entryEta); | |
1182 | } | |
1183 | ||
1184 | return profileEta; | |
1185 | ||
1186 | } // end of TProfile* AliFlowAnalysisWithQCumulants::MakeEtaProjection(TProfile2D *profilePtEta) | |
1187 | ||
489d5531 | 1188 | //================================================================================================================================ |
1189 | ||
489d5531 | 1190 | void AliFlowAnalysisWithQCumulants::PrintFinalResultsForIntegratedFlow(TString type) |
1191 | { | |
2001bc3a | 1192 | // Printing on the screen the final results for integrated flow (RF, POI and RP). |
489d5531 | 1193 | |
1194 | Int_t n = fHarmonic; | |
1195 | ||
489d5531 | 1196 | Double_t dVn[4] = {0.}; // array to hold Vn{2}, Vn{4}, Vn{6} and Vn{8} |
1197 | Double_t dVnErr[4] = {0.}; // array to hold errors of Vn{2}, Vn{4}, Vn{6} and Vn{8} | |
1198 | ||
2001bc3a | 1199 | if(type == "RF") |
489d5531 | 1200 | { |
0dd3b008 | 1201 | for(Int_t b=0;b<4;b++) |
1202 | { | |
b77b6434 | 1203 | dVn[0] = (fCommonHistsResults2nd->GetHistIntFlow())->GetBinContent(1); |
1204 | dVnErr[0] = (fCommonHistsResults2nd->GetHistIntFlow())->GetBinError(1); | |
1205 | dVn[1] = (fCommonHistsResults4th->GetHistIntFlow())->GetBinContent(1); | |
1206 | dVnErr[1] = (fCommonHistsResults4th->GetHistIntFlow())->GetBinError(1); | |
1207 | dVn[2] = (fCommonHistsResults6th->GetHistIntFlow())->GetBinContent(1); | |
1208 | dVnErr[2] = (fCommonHistsResults6th->GetHistIntFlow())->GetBinError(1); | |
1209 | dVn[3] = (fCommonHistsResults8th->GetHistIntFlow())->GetBinContent(1); | |
1210 | dVnErr[3] = (fCommonHistsResults8th->GetHistIntFlow())->GetBinError(1); | |
0dd3b008 | 1211 | } |
489d5531 | 1212 | } else if(type == "RP") |
1213 | { | |
1214 | dVn[0] = (fCommonHistsResults2nd->GetHistIntFlowRP())->GetBinContent(1); | |
1215 | dVnErr[0] = (fCommonHistsResults2nd->GetHistIntFlowRP())->GetBinError(1); | |
1216 | dVn[1] = (fCommonHistsResults4th->GetHistIntFlowRP())->GetBinContent(1); | |
1217 | dVnErr[1] = (fCommonHistsResults4th->GetHistIntFlowRP())->GetBinError(1); | |
1218 | dVn[2] = (fCommonHistsResults6th->GetHistIntFlowRP())->GetBinContent(1); | |
1219 | dVnErr[2] = (fCommonHistsResults6th->GetHistIntFlowRP())->GetBinError(1); | |
1220 | dVn[3] = (fCommonHistsResults8th->GetHistIntFlowRP())->GetBinContent(1); | |
1221 | dVnErr[3] = (fCommonHistsResults8th->GetHistIntFlowRP())->GetBinError(1); | |
1222 | } else if(type == "POI") | |
1223 | { | |
1224 | dVn[0] = (fCommonHistsResults2nd->GetHistIntFlowPOI())->GetBinContent(1); | |
1225 | dVnErr[0] = (fCommonHistsResults2nd->GetHistIntFlowPOI())->GetBinError(1); | |
1226 | dVn[1] = (fCommonHistsResults4th->GetHistIntFlowPOI())->GetBinContent(1); | |
1227 | dVnErr[1] = (fCommonHistsResults4th->GetHistIntFlowPOI())->GetBinError(1); | |
1228 | dVn[2] = (fCommonHistsResults6th->GetHistIntFlowPOI())->GetBinContent(1); | |
1229 | dVnErr[2] = (fCommonHistsResults6th->GetHistIntFlowPOI())->GetBinError(1); | |
1230 | dVn[3] = (fCommonHistsResults8th->GetHistIntFlowPOI())->GetBinContent(1); | |
1231 | dVnErr[3] = (fCommonHistsResults8th->GetHistIntFlowPOI())->GetBinError(1); | |
b77b6434 | 1232 | } else if(type == "RF, rebinned in M" && fCalculateCumulantsVsM) |
b3dacf6b | 1233 | { |
0dd3b008 | 1234 | for(Int_t b=0;b<4;b++) |
1235 | { | |
1236 | dVn[b] = fIntFlowRebinnedInM->GetBinContent(b+1); | |
1237 | dVnErr[b] = fIntFlowRebinnedInM->GetBinError(b+1); | |
1238 | } | |
b3dacf6b | 1239 | } |
489d5531 | 1240 | |
1241 | TString title = " flow estimates from Q-cumulants"; | |
1242 | TString subtitle = " ("; | |
b3dacf6b | 1243 | TString subtitle2 = " (rebinned in M)"; |
489d5531 | 1244 | |
b3dacf6b | 1245 | if(type != "RF, rebinned in M") |
489d5531 | 1246 | { |
b3dacf6b | 1247 | if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) |
1248 | { | |
1249 | subtitle.Append(type); | |
1250 | subtitle.Append(", without weights)"); | |
1251 | } else | |
1252 | { | |
1253 | subtitle.Append(type); | |
1254 | subtitle.Append(", with weights)"); | |
1255 | } | |
1256 | } else | |
489d5531 | 1257 | { |
b3dacf6b | 1258 | if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) |
1259 | { | |
1260 | subtitle.Append("RF"); | |
1261 | subtitle.Append(", without weights)"); | |
1262 | } else | |
1263 | { | |
1264 | subtitle.Append("RF"); | |
1265 | subtitle.Append(", with weights)"); | |
1266 | } | |
1267 | } | |
1268 | ||
489d5531 | 1269 | cout<<endl; |
1270 | cout<<"*************************************"<<endl; | |
1271 | cout<<"*************************************"<<endl; | |
1272 | cout<<title.Data()<<endl; | |
1273 | cout<<subtitle.Data()<<endl; | |
b3dacf6b | 1274 | if(type == "RF, rebinned in M"){cout<<subtitle2.Data()<<endl;} |
489d5531 | 1275 | cout<<endl; |
1276 | ||
1277 | for(Int_t i=0;i<4;i++) | |
1278 | { | |
2001bc3a | 1279 | cout<<" v_"<<n<<"{"<<2*(i+1)<<"} = "<<dVn[i]<<" +/- "<<dVnErr[i]<<endl; |
489d5531 | 1280 | } |
2001bc3a | 1281 | |
489d5531 | 1282 | cout<<endl; |
b92ea2b9 | 1283 | if(type == "RF") |
1284 | { | |
b77b6434 | 1285 | if(fApplyCorrectionForNUA) |
1286 | { | |
1287 | cout<<" detector bias (corrected for): "<<endl; | |
1288 | } else | |
1289 | { | |
1290 | cout<<" detector bias (not corrected for):"<<endl; | |
1291 | } | |
b92ea2b9 | 1292 | cout<<" to QC{2}: "<<fIntFlowDetectorBias->GetBinContent(1)<<" +/- "<<fIntFlowDetectorBias->GetBinError(1)<<endl; |
1293 | cout<<" to QC{4}: "<<fIntFlowDetectorBias->GetBinContent(2)<<" +/- "<<fIntFlowDetectorBias->GetBinError(2)<<endl; | |
1294 | cout<<endl; | |
1295 | } | |
b3dacf6b | 1296 | if(type == "RF" || type == "RF, rebinned in M") |
489d5531 | 1297 | { |
2001bc3a | 1298 | cout<<" nEvts = "<<(Int_t)fCommonHists->GetHistMultRP()->GetEntries()<<", <M> = "<<(Double_t)fCommonHists->GetHistMultRP()->GetMean()<<endl; |
489d5531 | 1299 | } |
1300 | else if (type == "RP") | |
1301 | { | |
2001bc3a | 1302 | cout<<" nEvts = "<<(Int_t)fCommonHists->GetHistMultRP()->GetEntries()<<", <M> = "<<(Double_t)fCommonHists->GetHistMultRP()->GetMean()<<endl; |
489d5531 | 1303 | } |
1304 | else if (type == "POI") | |
1305 | { | |
2001bc3a | 1306 | cout<<" nEvts = "<<(Int_t)fCommonHists->GetHistMultPOI()->GetEntries()<<", <M> = "<<(Double_t)fCommonHists->GetHistMultPOI()->GetMean()<<endl; |
1307 | } | |
1308 | ||
489d5531 | 1309 | cout<<"*************************************"<<endl; |
1310 | cout<<"*************************************"<<endl; | |
1311 | cout<<endl; | |
1312 | ||
2001bc3a | 1313 | }// end of AliFlowAnalysisWithQCumulants::PrintFinalResultsForIntegratedFlow(TString type="RF"); |
489d5531 | 1314 | |
1315 | //================================================================================================================================ | |
1316 | ||
489d5531 | 1317 | void AliFlowAnalysisWithQCumulants::WriteHistograms(TString outputFileName) |
1318 | { | |
1319 | //store the final results in output .root file | |
1320 | TFile *output = new TFile(outputFileName.Data(),"RECREATE"); | |
1321 | //output->WriteObject(fHistList, "cobjQC","SingleKey"); | |
1322 | fHistList->Write(fHistList->GetName(), TObject::kSingleKey); | |
1323 | delete output; | |
1324 | } | |
1325 | ||
1326 | ||
1327 | //================================================================================================================================ | |
1328 | ||
1329 | ||
1330 | void AliFlowAnalysisWithQCumulants::WriteHistograms(TDirectoryFile *outputFileName) | |
1331 | { | |
1332 | //store the final results in output .root file | |
1333 | fHistList->SetName("cobjQC"); | |
1334 | fHistList->SetOwner(kTRUE); | |
1335 | outputFileName->Add(fHistList); | |
1336 | outputFileName->Write(outputFileName->GetName(), TObject::kSingleKey); | |
1337 | } | |
1338 | ||
489d5531 | 1339 | //================================================================================================================================ |
1340 | ||
489d5531 | 1341 | void AliFlowAnalysisWithQCumulants::BookCommonHistograms() |
1342 | { | |
1343 | // Book common control histograms and common histograms for final results. | |
1344 | // common control histogram (ALL events) | |
1345 | TString commonHistsName = "AliFlowCommonHistQC"; | |
1346 | commonHistsName += fAnalysisLabel->Data(); | |
1347 | fCommonHists = new AliFlowCommonHist(commonHistsName.Data()); | |
1348 | fHistList->Add(fCommonHists); | |
dd442cd2 | 1349 | if(fFillMultipleControlHistograms) |
1350 | { | |
1351 | // common control histogram (for events with 2 and more particles) | |
1352 | TString commonHists2ndOrderName = "AliFlowCommonHist2ndOrderQC"; | |
1353 | commonHists2ndOrderName += fAnalysisLabel->Data(); | |
1354 | fCommonHists2nd = new AliFlowCommonHist(commonHists2ndOrderName.Data()); | |
1355 | fHistList->Add(fCommonHists2nd); | |
1356 | // common control histogram (for events with 4 and more particles) | |
1357 | TString commonHists4thOrderName = "AliFlowCommonHist4thOrderQC"; | |
1358 | commonHists4thOrderName += fAnalysisLabel->Data(); | |
1359 | fCommonHists4th = new AliFlowCommonHist(commonHists4thOrderName.Data()); | |
1360 | fHistList->Add(fCommonHists4th); | |
1361 | // common control histogram (for events with 6 and more particles) | |
1362 | TString commonHists6thOrderName = "AliFlowCommonHist6thOrderQC"; | |
1363 | commonHists6thOrderName += fAnalysisLabel->Data(); | |
1364 | fCommonHists6th = new AliFlowCommonHist(commonHists6thOrderName.Data()); | |
1365 | fHistList->Add(fCommonHists6th); | |
1366 | // common control histogram (for events with 8 and more particles) | |
1367 | TString commonHists8thOrderName = "AliFlowCommonHist8thOrderQC"; | |
1368 | commonHists8thOrderName += fAnalysisLabel->Data(); | |
1369 | fCommonHists8th = new AliFlowCommonHist(commonHists8thOrderName.Data()); | |
1370 | fHistList->Add(fCommonHists8th); | |
1371 | } // end of if(fFillMultipleControlHistograms) | |
1372 | ||
1373 | // common histograms for final results for QC{2}: | |
489d5531 | 1374 | TString commonHistResults2ndOrderName = "AliFlowCommonHistResults2ndOrderQC"; |
1375 | commonHistResults2ndOrderName += fAnalysisLabel->Data(); | |
1376 | fCommonHistsResults2nd = new AliFlowCommonHistResults(commonHistResults2ndOrderName.Data()); | |
1377 | fHistList->Add(fCommonHistsResults2nd); | |
dd442cd2 | 1378 | // common histograms for final results for QC{4}: |
489d5531 | 1379 | TString commonHistResults4thOrderName = "AliFlowCommonHistResults4thOrderQC"; |
1380 | commonHistResults4thOrderName += fAnalysisLabel->Data(); | |
1381 | fCommonHistsResults4th = new AliFlowCommonHistResults(commonHistResults4thOrderName.Data()); | |
1382 | fHistList->Add(fCommonHistsResults4th); | |
dd442cd2 | 1383 | // common histograms for final results for QC{6}: |
489d5531 | 1384 | TString commonHistResults6thOrderName = "AliFlowCommonHistResults6thOrderQC"; |
1385 | commonHistResults6thOrderName += fAnalysisLabel->Data(); | |
1386 | fCommonHistsResults6th = new AliFlowCommonHistResults(commonHistResults6thOrderName.Data()); | |
1387 | fHistList->Add(fCommonHistsResults6th); | |
dd442cd2 | 1388 | // common histograms for final results for QC{8}: |
489d5531 | 1389 | TString commonHistResults8thOrderName = "AliFlowCommonHistResults8thOrderQC"; |
1390 | commonHistResults8thOrderName += fAnalysisLabel->Data(); | |
1391 | fCommonHistsResults8th = new AliFlowCommonHistResults(commonHistResults8thOrderName.Data()); | |
1392 | fHistList->Add(fCommonHistsResults8th); | |
1393 | ||
1394 | } // end of void AliFlowAnalysisWithQCumulants::BookCommonHistograms() | |
1395 | ||
1396 | ||
1397 | //================================================================================================================================ | |
1398 | ||
1399 | ||
1400 | void AliFlowAnalysisWithQCumulants::BookAndFillWeightsHistograms() | |
1401 | { | |
1402 | // book and fill histograms which hold phi, pt and eta weights | |
1403 | ||
1404 | if(!fWeightsList) | |
1405 | { | |
1406 | cout<<"WARNING: fWeightsList is NULL in AFAWQC::BAFWH() !!!!"<<endl; | |
1407 | exit(0); | |
1408 | } | |
1409 | ||
1410 | TString fUseParticleWeightsName = "fUseParticleWeightsQC"; | |
1411 | fUseParticleWeightsName += fAnalysisLabel->Data(); | |
1412 | fUseParticleWeights = new TProfile(fUseParticleWeightsName.Data(),"0 = particle weight not used, 1 = particle weight used ",3,0,3); | |
1413 | fUseParticleWeights->SetLabelSize(0.06); | |
1414 | (fUseParticleWeights->GetXaxis())->SetBinLabel(1,"w_{#phi}"); | |
1415 | (fUseParticleWeights->GetXaxis())->SetBinLabel(2,"w_{p_{T}}"); | |
1416 | (fUseParticleWeights->GetXaxis())->SetBinLabel(3,"w_{#eta}"); | |
1417 | fUseParticleWeights->Fill(0.5,(Int_t)fUsePhiWeights); | |
1418 | fUseParticleWeights->Fill(1.5,(Int_t)fUsePtWeights); | |
1419 | fUseParticleWeights->Fill(2.5,(Int_t)fUseEtaWeights); | |
1420 | fWeightsList->Add(fUseParticleWeights); | |
1421 | ||
1422 | if(fUsePhiWeights) | |
1423 | { | |
1424 | if(fWeightsList->FindObject("phi_weights")) | |
1425 | { | |
1426 | fPhiWeights = dynamic_cast<TH1F*>(fWeightsList->FindObject("phi_weights")); | |
1427 | if(TMath::Abs(fPhiWeights->GetBinWidth(1)-fPhiBinWidth)>pow(10.,-6.)) | |
1428 | { | |
1429 | cout<<endl; | |
1430 | cout<<"WARNING (QC): Inconsistent binning in histograms for phi-weights throughout the code."<<endl; | |
1431 | cout<<endl; | |
6fbbbbf1 | 1432 | //exit(0); |
489d5531 | 1433 | } |
1434 | } else | |
1435 | { | |
1436 | cout<<"WARNING: fWeightsList->FindObject(\"phi_weights\") is NULL in AFAWQC::BAFWH() !!!!"<<endl; | |
1437 | exit(0); | |
1438 | } | |
1439 | } // end of if(fUsePhiWeights) | |
1440 | ||
1441 | if(fUsePtWeights) | |
1442 | { | |
1443 | if(fWeightsList->FindObject("pt_weights")) | |
1444 | { | |
1445 | fPtWeights = dynamic_cast<TH1D*>(fWeightsList->FindObject("pt_weights")); | |
1446 | if(TMath::Abs(fPtWeights->GetBinWidth(1)-fPtBinWidth)>pow(10.,-6.)) | |
1447 | { | |
1448 | cout<<endl; | |
1449 | cout<<"WARNING (QC): Inconsistent binning in histograms for pt-weights throughout the code."<<endl; | |
1450 | cout<<endl; | |
6fbbbbf1 | 1451 | //exit(0); |
489d5531 | 1452 | } |
1453 | } else | |
1454 | { | |
1455 | cout<<"WARNING: fWeightsList->FindObject(\"pt_weights\") is NULL in AFAWQC::BAFWH() !!!!"<<endl; | |
1456 | exit(0); | |
1457 | } | |
1458 | } // end of if(fUsePtWeights) | |
1459 | ||
1460 | if(fUseEtaWeights) | |
1461 | { | |
1462 | if(fWeightsList->FindObject("eta_weights")) | |
1463 | { | |
1464 | fEtaWeights = dynamic_cast<TH1D*>(fWeightsList->FindObject("eta_weights")); | |
1465 | if(TMath::Abs(fEtaWeights->GetBinWidth(1)-fEtaBinWidth)>pow(10.,-6.)) | |
1466 | { | |
1467 | cout<<endl; | |
1468 | cout<<"WARNING (QC): Inconsistent binning in histograms for eta-weights throughout the code."<<endl; | |
1469 | cout<<endl; | |
6fbbbbf1 | 1470 | //exit(0); |
489d5531 | 1471 | } |
1472 | } else | |
1473 | { | |
1474 | cout<<"WARNING: fUseEtaWeights && fWeightsList->FindObject(\"eta_weights\") is NULL in AFAWQC::BAFWH() !!!!"<<endl; | |
1475 | exit(0); | |
1476 | } | |
1477 | } // end of if(fUseEtaWeights) | |
1478 | ||
1479 | } // end of AliFlowAnalysisWithQCumulants::BookAndFillWeightsHistograms() | |
1480 | ||
1481 | ||
1482 | //================================================================================================================================ | |
1483 | ||
1484 | ||
1485 | void AliFlowAnalysisWithQCumulants::BookEverythingForIntegratedFlow() | |
1486 | { | |
1487 | // Book all objects for integrated flow: | |
e5834fcb | 1488 | // a) Book profile to hold all flags for integrated flow; |
1489 | // b) Book event-by-event quantities; | |
1490 | // c) Book profiles; // to be improved (comment) | |
489d5531 | 1491 | // d) Book histograms holding the final results. |
1492 | ||
1493 | TString sinCosFlag[2] = {"sin","cos"}; // to be improved (should I promote this to data members?) | |
1494 | TString powerFlag[2] = {"linear","quadratic"}; // to be improved (should I promote this to data members?) | |
1495 | ||
1496 | // a) Book profile to hold all flags for integrated flow: | |
1497 | TString intFlowFlagsName = "fIntFlowFlags"; | |
1498 | intFlowFlagsName += fAnalysisLabel->Data(); | |
dd442cd2 | 1499 | fIntFlowFlags = new TProfile(intFlowFlagsName.Data(),"Flags for Integrated Flow",14,0,14); |
489d5531 | 1500 | fIntFlowFlags->SetTickLength(-0.01,"Y"); |
1501 | fIntFlowFlags->SetMarkerStyle(25); | |
1502 | fIntFlowFlags->SetLabelSize(0.05); | |
1503 | fIntFlowFlags->SetLabelOffset(0.02,"Y"); | |
1504 | fIntFlowFlags->GetXaxis()->SetBinLabel(1,"Particle Weights"); | |
1505 | fIntFlowFlags->GetXaxis()->SetBinLabel(2,"Event Weights"); | |
1506 | fIntFlowFlags->GetXaxis()->SetBinLabel(3,"Corrected for NUA?"); | |
b3dacf6b | 1507 | fIntFlowFlags->GetXaxis()->SetBinLabel(4,"Print RF results"); |
489d5531 | 1508 | fIntFlowFlags->GetXaxis()->SetBinLabel(5,"Print RP results"); |
3b552efe | 1509 | fIntFlowFlags->GetXaxis()->SetBinLabel(6,"Print POI results"); |
b3dacf6b | 1510 | fIntFlowFlags->GetXaxis()->SetBinLabel(7,"Print RF (rebinned in M) results"); |
1511 | fIntFlowFlags->GetXaxis()->SetBinLabel(8,"Corrected for NUA vs M?"); | |
1512 | fIntFlowFlags->GetXaxis()->SetBinLabel(9,"Propagate errors to v_{n} from correlations?"); | |
1513 | fIntFlowFlags->GetXaxis()->SetBinLabel(10,"Calculate cumulants vs M"); | |
0dd3b008 | 1514 | fIntFlowFlags->GetXaxis()->SetBinLabel(11,"fMinimumBiasReferenceFlow"); |
8e1cefdd | 1515 | fIntFlowFlags->GetXaxis()->SetBinLabel(12,"fForgetAboutCovariances"); |
e5834fcb | 1516 | fIntFlowFlags->GetXaxis()->SetBinLabel(13,"fStorePhiDistributionForOneEvent"); |
dd442cd2 | 1517 | fIntFlowFlags->GetXaxis()->SetBinLabel(14,"fFillMultipleControlHistograms"); |
489d5531 | 1518 | fIntFlowList->Add(fIntFlowFlags); |
1519 | ||
1520 | // b) Book event-by-event quantities: | |
1521 | // Re[Q_{m*n,k}], Im[Q_{m*n,k}] and S_{p,k}^M: | |
8ed4edc7 | 1522 | fReQ = new TMatrixD(6,9); |
1523 | fImQ = new TMatrixD(6,9); | |
489d5531 | 1524 | fSMpk = new TMatrixD(8,9); |
1525 | // average correlations <2>, <4>, <6> and <8> for single event (bining is the same as in fIntFlowCorrelationsPro and fIntFlowCorrelationsHist): | |
1526 | TString intFlowCorrelationsEBEName = "fIntFlowCorrelationsEBE"; | |
1527 | intFlowCorrelationsEBEName += fAnalysisLabel->Data(); | |
1528 | fIntFlowCorrelationsEBE = new TH1D(intFlowCorrelationsEBEName.Data(),intFlowCorrelationsEBEName.Data(),4,0,4); | |
1529 | // weights for average correlations <2>, <4>, <6> and <8> for single event: | |
1530 | TString intFlowEventWeightsForCorrelationsEBEName = "fIntFlowEventWeightsForCorrelationsEBE"; | |
1531 | intFlowEventWeightsForCorrelationsEBEName += fAnalysisLabel->Data(); | |
1532 | fIntFlowEventWeightsForCorrelationsEBE = new TH1D(intFlowEventWeightsForCorrelationsEBEName.Data(),intFlowEventWeightsForCorrelationsEBEName.Data(),4,0,4); | |
1533 | // average all correlations for single event (bining is the same as in fIntFlowCorrelationsAllPro and fIntFlowCorrelationsAllHist): | |
1534 | TString intFlowCorrelationsAllEBEName = "fIntFlowCorrelationsAllEBE"; | |
1535 | intFlowCorrelationsAllEBEName += fAnalysisLabel->Data(); | |
8ed4edc7 | 1536 | fIntFlowCorrelationsAllEBE = new TH1D(intFlowCorrelationsAllEBEName.Data(),intFlowCorrelationsAllEBEName.Data(),34,0,34); |
489d5531 | 1537 | // average correction terms for non-uniform acceptance for single event |
1538 | // (binning is the same as in fIntFlowCorrectionTermsForNUAPro[2] and fIntFlowCorrectionTermsForNUAHist[2]): | |
1539 | TString fIntFlowCorrectionTermsForNUAEBEName = "fIntFlowCorrectionTermsForNUAEBE"; | |
1540 | fIntFlowCorrectionTermsForNUAEBEName += fAnalysisLabel->Data(); | |
1541 | for(Int_t sc=0;sc<2;sc++) // sin or cos terms | |
1542 | { | |
b92ea2b9 | 1543 | fIntFlowCorrectionTermsForNUAEBE[sc] = new TH1D(Form("%s: %s terms",fIntFlowCorrectionTermsForNUAEBEName.Data(),sinCosFlag[sc].Data()),Form("Correction terms for non-uniform acceptance (%s terms)",sinCosFlag[sc].Data()),4,0,4); |
489d5531 | 1544 | } |
0328db2d | 1545 | // event weights for terms for non-uniform acceptance: |
1546 | TString fIntFlowEventWeightForCorrectionTermsForNUAEBEName = "fIntFlowEventWeightForCorrectionTermsForNUAEBE"; | |
1547 | fIntFlowEventWeightForCorrectionTermsForNUAEBEName += fAnalysisLabel->Data(); | |
1548 | for(Int_t sc=0;sc<2;sc++) // sin or cos terms | |
1549 | { | |
b92ea2b9 | 1550 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[sc] = new TH1D(Form("%s: %s terms",fIntFlowEventWeightForCorrectionTermsForNUAEBEName.Data(),sinCosFlag[sc].Data()),Form("Event weights for terms for non-uniform acceptance (%s terms)",sinCosFlag[sc].Data()),4,0,4); // to be improved - 4 |
0328db2d | 1551 | } |
489d5531 | 1552 | // c) Book profiles: // to be improved (comment) |
1553 | // profile to hold average multiplicities and number of events for events with nRP>=0, nRP>=1, ... , and nRP>=8: | |
1554 | TString avMultiplicityName = "fAvMultiplicity"; | |
1555 | avMultiplicityName += fAnalysisLabel->Data(); | |
1556 | fAvMultiplicity = new TProfile(avMultiplicityName.Data(),"Average Multiplicities of RPs",9,0,9); | |
1557 | fAvMultiplicity->SetTickLength(-0.01,"Y"); | |
1558 | fAvMultiplicity->SetMarkerStyle(25); | |
1559 | fAvMultiplicity->SetLabelSize(0.05); | |
1560 | fAvMultiplicity->SetLabelOffset(0.02,"Y"); | |
1561 | fAvMultiplicity->SetYTitle("Average Multiplicity"); | |
1562 | (fAvMultiplicity->GetXaxis())->SetBinLabel(1,"all evts"); | |
1563 | (fAvMultiplicity->GetXaxis())->SetBinLabel(2,"n_{RP} #geq 1"); | |
1564 | (fAvMultiplicity->GetXaxis())->SetBinLabel(3,"n_{RP} #geq 2"); | |
1565 | (fAvMultiplicity->GetXaxis())->SetBinLabel(4,"n_{RP} #geq 3"); | |
1566 | (fAvMultiplicity->GetXaxis())->SetBinLabel(5,"n_{RP} #geq 4"); | |
1567 | (fAvMultiplicity->GetXaxis())->SetBinLabel(6,"n_{RP} #geq 5"); | |
1568 | (fAvMultiplicity->GetXaxis())->SetBinLabel(7,"n_{RP} #geq 6"); | |
1569 | (fAvMultiplicity->GetXaxis())->SetBinLabel(8,"n_{RP} #geq 7"); | |
1570 | (fAvMultiplicity->GetXaxis())->SetBinLabel(9,"n_{RP} #geq 8"); | |
1571 | fIntFlowProfiles->Add(fAvMultiplicity); | |
b40a910e | 1572 | // Average correlations <<2>>, <<4>>, <<6>> and <<8>> for all events (with wrong errors!): |
1573 | TString correlationFlag[4] = {"#LT#LT2#GT#GT","#LT#LT4#GT#GT","#LT#LT6#GT#GT","#LT#LT8#GT#GT"}; | |
489d5531 | 1574 | TString intFlowCorrelationsProName = "fIntFlowCorrelationsPro"; |
1575 | intFlowCorrelationsProName += fAnalysisLabel->Data(); | |
1576 | fIntFlowCorrelationsPro = new TProfile(intFlowCorrelationsProName.Data(),"Average correlations for all events",4,0,4,"s"); | |
b40a910e | 1577 | fIntFlowCorrelationsPro->Sumw2(); |
489d5531 | 1578 | fIntFlowCorrelationsPro->SetTickLength(-0.01,"Y"); |
1579 | fIntFlowCorrelationsPro->SetMarkerStyle(25); | |
1580 | fIntFlowCorrelationsPro->SetLabelSize(0.06); | |
1581 | fIntFlowCorrelationsPro->SetLabelOffset(0.01,"Y"); | |
68a3b4b1 | 1582 | for(Int_t b=0;b<4;b++) |
b3dacf6b | 1583 | { |
68a3b4b1 | 1584 | (fIntFlowCorrelationsPro->GetXaxis())->SetBinLabel(b+1,correlationFlag[b].Data()); |
b3dacf6b | 1585 | } |
489d5531 | 1586 | fIntFlowProfiles->Add(fIntFlowCorrelationsPro); |
b40a910e | 1587 | // Average correlations squared <<2>^2>, <<4>^2>, <<6>^2> and <<8>^2> for all events: |
1588 | TString squaredCorrelationFlag[4] = {"#LT#LT2#GT^{2}#GT","#LT#LT4#GT^{2}#GT","#LT#LT6#GT^{2}#GT","#LT#LT8#GT^{2}#GT"}; | |
1589 | TString intFlowSquaredCorrelationsProName = "fIntFlowSquaredCorrelationsPro"; | |
1590 | intFlowSquaredCorrelationsProName += fAnalysisLabel->Data(); | |
1591 | fIntFlowSquaredCorrelationsPro = new TProfile(intFlowSquaredCorrelationsProName.Data(),"Average squared correlations for all events",4,0,4,"s"); | |
1592 | fIntFlowSquaredCorrelationsPro->Sumw2(); | |
1593 | fIntFlowSquaredCorrelationsPro->SetTickLength(-0.01,"Y"); | |
1594 | fIntFlowSquaredCorrelationsPro->SetMarkerStyle(25); | |
1595 | fIntFlowSquaredCorrelationsPro->SetLabelSize(0.06); | |
1596 | fIntFlowSquaredCorrelationsPro->SetLabelOffset(0.01,"Y"); | |
1597 | for(Int_t b=0;b<4;b++) | |
1598 | { | |
1599 | (fIntFlowSquaredCorrelationsPro->GetXaxis())->SetBinLabel(b+1,squaredCorrelationFlag[b].Data()); | |
1600 | } | |
1601 | fIntFlowProfiles->Add(fIntFlowSquaredCorrelationsPro); | |
b3dacf6b | 1602 | if(fCalculateCumulantsVsM) |
1603 | { | |
1604 | for(Int_t ci=0;ci<4;ci++) // correlation index | |
1605 | { | |
b40a910e | 1606 | // average correlations <<2>>, <<4>>, <<6>> and <<8>> versus multiplicity for all events (with wrong errors): |
b3dacf6b | 1607 | TString intFlowCorrelationsVsMProName = "fIntFlowCorrelationsVsMPro"; |
1608 | intFlowCorrelationsVsMProName += fAnalysisLabel->Data(); | |
1609 | fIntFlowCorrelationsVsMPro[ci] = new TProfile(Form("%s, %s",intFlowCorrelationsVsMProName.Data(),correlationFlag[ci].Data()), | |
1610 | Form("%s vs multiplicity",correlationFlag[ci].Data()), | |
b40a910e | 1611 | fnBinsMult,fMinMult,fMaxMult,"s"); |
1612 | fIntFlowCorrelationsVsMPro[ci]->Sumw2(); | |
b3dacf6b | 1613 | fIntFlowCorrelationsVsMPro[ci]->GetYaxis()->SetTitle(correlationFlag[ci].Data()); |
1614 | fIntFlowCorrelationsVsMPro[ci]->GetXaxis()->SetTitle("M"); | |
1615 | fIntFlowProfiles->Add(fIntFlowCorrelationsVsMPro[ci]); | |
b40a910e | 1616 | // average squared correlations <<2>^2>, <<4>^2>, <<6>^2> and <<8>^2> versus multiplicity for all events: |
1617 | TString intFlowSquaredCorrelationsVsMProName = "fIntFlowSquaredCorrelationsVsMPro"; | |
1618 | intFlowSquaredCorrelationsVsMProName += fAnalysisLabel->Data(); | |
1619 | fIntFlowSquaredCorrelationsVsMPro[ci] = new TProfile(Form("%s, %s",intFlowSquaredCorrelationsVsMProName.Data(),squaredCorrelationFlag[ci].Data()), | |
1620 | Form("%s vs multiplicity",squaredCorrelationFlag[ci].Data()), | |
1621 | fnBinsMult,fMinMult,fMaxMult,"s"); | |
1622 | fIntFlowSquaredCorrelationsVsMPro[ci]->Sumw2(); | |
1623 | fIntFlowSquaredCorrelationsVsMPro[ci]->GetYaxis()->SetTitle(squaredCorrelationFlag[ci].Data()); | |
1624 | fIntFlowSquaredCorrelationsVsMPro[ci]->GetXaxis()->SetTitle("M"); | |
1625 | fIntFlowProfiles->Add(fIntFlowSquaredCorrelationsVsMPro[ci]); | |
b3dacf6b | 1626 | } // end of for(Int_t ci=0;ci<4;ci++) // correlation index |
1627 | } // end of if(fCalculateCumulantsVsM) | |
489d5531 | 1628 | // averaged all correlations for all events (with wrong errors!): |
1629 | TString intFlowCorrelationsAllProName = "fIntFlowCorrelationsAllPro"; | |
1630 | intFlowCorrelationsAllProName += fAnalysisLabel->Data(); | |
8ed4edc7 | 1631 | fIntFlowCorrelationsAllPro = new TProfile(intFlowCorrelationsAllProName.Data(),"Average correlations for all events",34,0,34,"s"); |
489d5531 | 1632 | fIntFlowCorrelationsAllPro->SetTickLength(-0.01,"Y"); |
1633 | fIntFlowCorrelationsAllPro->SetMarkerStyle(25); | |
1634 | fIntFlowCorrelationsAllPro->SetLabelSize(0.03); | |
1635 | fIntFlowCorrelationsAllPro->SetLabelOffset(0.01,"Y"); | |
1636 | // 2-p correlations: | |
1637 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(1,"<<2>>_{n|n}"); | |
1638 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(2,"<<2>>_{2n|2n}"); | |
1639 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(3,"<<2>>_{3n|3n}"); | |
1640 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(4,"<<2>>_{4n|4n}"); | |
1641 | // 3-p correlations: | |
1642 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(6,"<<3>>_{2n|n,n}"); | |
1643 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(7,"<<3>>_{3n|2n,n}"); | |
1644 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(8,"<<3>>_{4n|2n,2n}"); | |
1645 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(9,"<<3>>_{4n|3n,n}"); | |
1646 | // 4-p correlations: | |
1647 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(11,"<<4>>_{n,n|n,n}"); | |
1648 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(12,"<<4>>_{2n,n|2n,n}"); | |
1649 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(13,"<<4>>_{2n,2n|2n,2n}"); | |
1650 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(14,"<<4>>_{3n|n,n,n}"); | |
1651 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(15,"<<4>>_{3n,n|3n,n}"); | |
1652 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(16,"<<4>>_{3n,n|2n,2n}"); | |
1653 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(17,"<<4>>_{4n|2n,n,n}"); | |
1654 | // 5-p correlations: | |
1655 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(19,"<<5>>_{2n|n,n,n,n}"); | |
1656 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(20,"<<5>>_{2n,2n|2n,n,n}"); | |
1657 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(21,"<<5>>_{3n,n|2n,n,n}"); | |
1658 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(22,"<<5>>_{4n|n,n,n,n}"); | |
1659 | // 6-p correlations: | |
1660 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(24,"<<6>>_{n,n,n|n,n,n}"); | |
1661 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(25,"<<6>>_{2n,n,n|2n,n,n}"); | |
1662 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(26,"<<6>>_{2n,2n|n,n,n,n}"); | |
1663 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(27,"<<6>>_{3n,n|n,n,n,n}"); | |
1664 | // 7-p correlations: | |
1665 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(29,"<<7>>_{2n,n,n|n,n,n,n}"); | |
1666 | // 8-p correlations: | |
1667 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(31,"<<8>>_{n,n,n,n|n,n,n,n}"); | |
8ed4edc7 | 1668 | // EXTRA correlations: |
1669 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(33,"<<4>>_{4n,2n|3n,3n}"); | |
1670 | (fIntFlowCorrelationsAllPro->GetXaxis())->SetBinLabel(34,"<<5>>_{2n,2n,2n|3n,3n}"); | |
489d5531 | 1671 | fIntFlowProfiles->Add(fIntFlowCorrelationsAllPro); |
1672 | // when particle weights are used some extra correlations appear: | |
1673 | if(fUsePhiWeights||fUsePtWeights||fUseEtaWeights) | |
1674 | { | |
1675 | TString intFlowExtraCorrelationsProName = "fIntFlowExtraCorrelationsPro"; | |
1676 | intFlowExtraCorrelationsProName += fAnalysisLabel->Data(); | |
1677 | fIntFlowExtraCorrelationsPro = new TProfile(intFlowExtraCorrelationsProName.Data(),"Average extra correlations for all events",100,0,100,"s"); | |
1678 | fIntFlowExtraCorrelationsPro->SetTickLength(-0.01,"Y"); | |
1679 | fIntFlowExtraCorrelationsPro->SetMarkerStyle(25); | |
1680 | fIntFlowExtraCorrelationsPro->SetLabelSize(0.03); | |
1681 | fIntFlowExtraCorrelationsPro->SetLabelOffset(0.01,"Y"); | |
1682 | // extra 2-p correlations: | |
1683 | (fIntFlowExtraCorrelationsPro->GetXaxis())->SetBinLabel(1,"<<w1^3 w2 cos(n*(phi1-phi2))>>"); | |
1684 | (fIntFlowExtraCorrelationsPro->GetXaxis())->SetBinLabel(2,"<<w1 w2 w3^2 cos(n*(phi1-phi2))>>"); | |
1685 | fIntFlowProfiles->Add(fIntFlowExtraCorrelationsPro); | |
1686 | } // end of if(fUsePhiWeights||fUsePtWeights||fUseEtaWeights) | |
1687 | // average product of correlations <2>, <4>, <6> and <8>: | |
b3dacf6b | 1688 | TString productFlag[6] = {"<<2><4>>","<<2><6>>","<<2><8>>","<<4><6>>","<<4><8>>","<<6><8>>"}; |
489d5531 | 1689 | TString intFlowProductOfCorrelationsProName = "fIntFlowProductOfCorrelationsPro"; |
1690 | intFlowProductOfCorrelationsProName += fAnalysisLabel->Data(); | |
1691 | fIntFlowProductOfCorrelationsPro = new TProfile(intFlowProductOfCorrelationsProName.Data(),"Average products of correlations",6,0,6); | |
1692 | fIntFlowProductOfCorrelationsPro->SetTickLength(-0.01,"Y"); | |
1693 | fIntFlowProductOfCorrelationsPro->SetMarkerStyle(25); | |
1694 | fIntFlowProductOfCorrelationsPro->SetLabelSize(0.05); | |
1695 | fIntFlowProductOfCorrelationsPro->SetLabelOffset(0.01,"Y"); | |
68a3b4b1 | 1696 | for(Int_t b=0;b<6;b++) |
b3dacf6b | 1697 | { |
68a3b4b1 | 1698 | (fIntFlowProductOfCorrelationsPro->GetXaxis())->SetBinLabel(b+1,productFlag[b].Data()); |
b3dacf6b | 1699 | } |
1700 | fIntFlowProfiles->Add(fIntFlowProductOfCorrelationsPro); | |
ff70ca91 | 1701 | // average product of correlations <2>, <4>, <6> and <8> versus multiplicity |
1702 | // [0=<<2><4>>,1=<<2><6>>,2=<<2><8>>,3=<<4><6>>,4=<<4><8>>,5=<<6><8>>] | |
b3dacf6b | 1703 | if(fCalculateCumulantsVsM) |
1704 | { | |
1705 | TString intFlowProductOfCorrelationsVsMProName = "fIntFlowProductOfCorrelationsVsMPro"; | |
1706 | intFlowProductOfCorrelationsVsMProName += fAnalysisLabel->Data(); | |
1707 | for(Int_t pi=0;pi<6;pi++) | |
1708 | { | |
1709 | fIntFlowProductOfCorrelationsVsMPro[pi] = new TProfile(Form("%s, %s",intFlowProductOfCorrelationsVsMProName.Data(),productFlag[pi].Data()), | |
1710 | Form("%s versus multiplicity",productFlag[pi].Data()), | |
1711 | fnBinsMult,fMinMult,fMaxMult); | |
1712 | fIntFlowProductOfCorrelationsVsMPro[pi]->GetXaxis()->SetTitle("M"); | |
1713 | fIntFlowProfiles->Add(fIntFlowProductOfCorrelationsVsMPro[pi]); | |
1714 | } // end of for(Int_t pi=0;pi<6;pi++) | |
1715 | } // end of if(fCalculateCumulantsVsM) | |
0328db2d | 1716 | // average product of correction terms for NUA: |
1717 | TString intFlowProductOfCorrectionTermsForNUAProName = "fIntFlowProductOfCorrectionTermsForNUAPro"; | |
1718 | intFlowProductOfCorrectionTermsForNUAProName += fAnalysisLabel->Data(); | |
1719 | fIntFlowProductOfCorrectionTermsForNUAPro = new TProfile(intFlowProductOfCorrectionTermsForNUAProName.Data(),"Average products of correction terms for NUA",27,0,27); | |
1720 | fIntFlowProductOfCorrectionTermsForNUAPro->SetTickLength(-0.01,"Y"); | |
1721 | fIntFlowProductOfCorrectionTermsForNUAPro->SetMarkerStyle(25); | |
1722 | fIntFlowProductOfCorrectionTermsForNUAPro->SetLabelSize(0.05); | |
1723 | fIntFlowProductOfCorrectionTermsForNUAPro->SetLabelOffset(0.01,"Y"); | |
1724 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(1,"<<2><cos(#phi)>>"); | |
1725 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(2,"<<2><sin(#phi)>>"); | |
1726 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(3,"<<cos(#phi)><sin(#phi)>>"); | |
1727 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(4,"Cov(<2>,<cos(#phi_{1}+#phi_{2})>)"); | |
1728 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(5,"Cov(<2>,<sin(#phi_{1}+#phi_{2})>)"); | |
1729 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(6,"Cov(<2>,<cos(#phi_{1}-#phi_{2}-#phi_{3})>)"); | |
1730 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(7,"Cov(<2>,<sin(#phi_{1}-#phi_{2}-#phi_{3})>)"); | |
1731 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(8,"Cov(<4>,<cos(#phi)>)"); | |
1732 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(9,"Cov(<4>,<sin(#phi)>)"); | |
1733 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(10,"Cov(<4>,<cos(#phi_{1}+#phi_{2})>)"); | |
1734 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(11,"Cov(<4>,<sin(#phi_{1}+#phi_{2})>)"); | |
1735 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(12,"Cov(<4>,<cos(#phi_{1}-#phi_{2}-#phi_{3})>>)"); | |
1736 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(13,"Cov(<4>,<sin(#phi_{1}-#phi_{2}-#phi_{3})>>)"); | |
1737 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(14,"Cov(<cos(#phi)>,<cos(#phi_{1}+#phi_{2})>)"); | |
1738 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(15,"Cov(<cos(#phi)>,<sin(#phi_{1}+#phi_{2})>)"); | |
1739 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(16,"Cov(<cos(#phi)>,<cos(#phi_{1}-#phi_{2}-#phi_{3})>)"); | |
1740 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(17,"Cov(<cos(#phi)>,<sin(#phi_{1}-#phi_{2}-#phi_{3})>)"); | |
1741 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(18,"Cov(<sin(#phi)>,<cos(#phi_{1}+#phi_{2})>)"); | |
1742 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(19,"Cov(<sin(#phi)>,<sin(#phi_{1}+#phi_{2})>)"); | |
1743 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(20,"Cov(<sin(#phi)>,<cos(#phi_{1}-#phi_{2}-#phi_{3})>)"); | |
1744 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(21,"Cov(<sin(#phi)>,<sin(#phi_{1}-#phi_{2}-#phi_{3})>)"); | |
1745 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(22,"Cov(<cos(#phi_{1}+#phi_{2})>,<sin(#phi_{1}+#phi_{2})>)"); | |
1746 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(23,"Cov(<cos(#phi_{1}+#phi_{2})>,<cos(#phi_{1}-#phi_{2}-#phi_{3})>)"); | |
1747 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(24,"Cov(<cos(#phi_{1}+#phi_{2})>,<sin(#phi_{1}-#phi_{2}-#phi_{3})>)"); | |
1748 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(25,"Cov(<sin(#phi_{1}+#phi_{2})>,<cos(#phi_{1}-#phi_{2}-#phi_{3})>)"); | |
1749 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(26,"Cov(<sin(#phi_{1}+#phi_{2})>,<sin(#phi_{1}-#phi_{2}-#phi_{3})>)"); | |
1750 | (fIntFlowProductOfCorrectionTermsForNUAPro->GetXaxis())->SetBinLabel(27,"Cov(<cos(#phi_{1}-#phi_{2}-#phi_{3}>,<sin(#phi_{1}-#phi_{2}-#phi_{3}>)"); | |
1751 | fIntFlowProfiles->Add(fIntFlowProductOfCorrectionTermsForNUAPro); | |
489d5531 | 1752 | // average correction terms for non-uniform acceptance (with wrong errors!): |
1753 | for(Int_t sc=0;sc<2;sc++) // sin or cos terms | |
1754 | { | |
1755 | TString intFlowCorrectionTermsForNUAProName = "fIntFlowCorrectionTermsForNUAPro"; | |
1756 | intFlowCorrectionTermsForNUAProName += fAnalysisLabel->Data(); | |
b92ea2b9 | 1757 | fIntFlowCorrectionTermsForNUAPro[sc] = new TProfile(Form("%s: %s terms",intFlowCorrectionTermsForNUAProName.Data(),sinCosFlag[sc].Data()),Form("Correction terms for non-uniform acceptance (%s terms)",sinCosFlag[sc].Data()),4,0,4,"s"); |
489d5531 | 1758 | fIntFlowCorrectionTermsForNUAPro[sc]->SetTickLength(-0.01,"Y"); |
1759 | fIntFlowCorrectionTermsForNUAPro[sc]->SetMarkerStyle(25); | |
1760 | fIntFlowCorrectionTermsForNUAPro[sc]->SetLabelSize(0.03); | |
1761 | fIntFlowCorrectionTermsForNUAPro[sc]->SetLabelOffset(0.01,"Y"); | |
b92ea2b9 | 1762 | (fIntFlowCorrectionTermsForNUAPro[sc]->GetXaxis())->SetBinLabel(1,Form("#LT#LT%s(n(phi1))#GT#GT",sinCosFlag[sc].Data())); |
1763 | (fIntFlowCorrectionTermsForNUAPro[sc]->GetXaxis())->SetBinLabel(2,Form("#LT#LT%s(n(phi1+phi2))#GT#GT",sinCosFlag[sc].Data())); | |
1764 | (fIntFlowCorrectionTermsForNUAPro[sc]->GetXaxis())->SetBinLabel(3,Form("#LT#LT%s(n(phi1-phi2-phi3))#GT#GT",sinCosFlag[sc].Data())); | |
1765 | (fIntFlowCorrectionTermsForNUAPro[sc]->GetXaxis())->SetBinLabel(4,Form("#LT#LT%s(n(2phi1-phi2))#GT#GT",sinCosFlag[sc].Data())); | |
489d5531 | 1766 | fIntFlowProfiles->Add(fIntFlowCorrectionTermsForNUAPro[sc]); |
2001bc3a | 1767 | // versus multiplicity: |
b3dacf6b | 1768 | if(fCalculateCumulantsVsM) |
1769 | { | |
1770 | TString correctionTermFlag[4] = {"(n(phi1))","(n(phi1+phi2))","(n(phi1-phi2-phi3))","(n(2phi1-phi2))"}; // to be improved - hardwired 4 | |
1771 | for(Int_t ci=0;ci<4;ci++) // correction term index (to be improved - hardwired 4) | |
1772 | { | |
1773 | TString intFlowCorrectionTermsForNUAVsMProName = "fIntFlowCorrectionTermsForNUAVsMPro"; | |
1774 | intFlowCorrectionTermsForNUAVsMProName += fAnalysisLabel->Data(); | |
1775 | fIntFlowCorrectionTermsForNUAVsMPro[sc][ci] = new TProfile(Form("%s: #LT#LT%s%s#GT#GT",intFlowCorrectionTermsForNUAVsMProName.Data(),sinCosFlag[sc].Data(),correctionTermFlag[ci].Data()),Form("#LT#LT%s%s#GT#GT vs M",sinCosFlag[sc].Data(),correctionTermFlag[ci].Data()),fnBinsMult,fMinMult,fMaxMult,"s"); | |
1776 | fIntFlowProfiles->Add(fIntFlowCorrectionTermsForNUAVsMPro[sc][ci]); | |
1777 | } | |
1778 | } // end of if(fCalculateCumulantsVsM) | |
489d5531 | 1779 | } // end of for(Int_t sc=0;sc<2;sc++) |
1780 | ||
1781 | // d) Book histograms holding the final results: | |
1782 | // average correlations <<2>>, <<4>>, <<6>> and <<8>> for all events (with correct errors!): | |
1783 | TString intFlowCorrelationsHistName = "fIntFlowCorrelationsHist"; | |
1784 | intFlowCorrelationsHistName += fAnalysisLabel->Data(); | |
1785 | fIntFlowCorrelationsHist = new TH1D(intFlowCorrelationsHistName.Data(),"Average correlations for all events",4,0,4); | |
1786 | fIntFlowCorrelationsHist->SetTickLength(-0.01,"Y"); | |
1787 | fIntFlowCorrelationsHist->SetMarkerStyle(25); | |
1788 | fIntFlowCorrelationsHist->SetLabelSize(0.06); | |
1789 | fIntFlowCorrelationsHist->SetLabelOffset(0.01,"Y"); | |
1790 | (fIntFlowCorrelationsHist->GetXaxis())->SetBinLabel(1,"<<2>>"); | |
1791 | (fIntFlowCorrelationsHist->GetXaxis())->SetBinLabel(2,"<<4>>"); | |
1792 | (fIntFlowCorrelationsHist->GetXaxis())->SetBinLabel(3,"<<6>>"); | |
1793 | (fIntFlowCorrelationsHist->GetXaxis())->SetBinLabel(4,"<<8>>"); | |
1794 | fIntFlowResults->Add(fIntFlowCorrelationsHist); | |
ff70ca91 | 1795 | // average correlations <<2>>, <<4>>, <<6>> and <<8>> for all events (with correct errors!) vs M: |
b3dacf6b | 1796 | if(fCalculateCumulantsVsM) |
1797 | { | |
1798 | for(Int_t ci=0;ci<4;ci++) // correlation index | |
1799 | { | |
1800 | TString intFlowCorrelationsVsMHistName = "fIntFlowCorrelationsVsMHist"; | |
1801 | intFlowCorrelationsVsMHistName += fAnalysisLabel->Data(); | |
1802 | fIntFlowCorrelationsVsMHist[ci] = new TH1D(Form("%s, %s",intFlowCorrelationsVsMHistName.Data(),correlationFlag[ci].Data()), | |
1803 | Form("%s vs multiplicity",correlationFlag[ci].Data()), | |
1804 | fnBinsMult,fMinMult,fMaxMult); | |
1805 | fIntFlowCorrelationsVsMHist[ci]->GetYaxis()->SetTitle(correlationFlag[ci].Data()); | |
1806 | fIntFlowCorrelationsVsMHist[ci]->GetXaxis()->SetTitle("M"); | |
1807 | fIntFlowResults->Add(fIntFlowCorrelationsVsMHist[ci]); | |
1808 | } // end of for(Int_t ci=0;ci<4;ci++) // correlation index | |
1809 | } // end of if(fCalculateCumulantsVsM) | |
489d5531 | 1810 | // average all correlations for all events (with correct errors!): |
1811 | TString intFlowCorrelationsAllHistName = "fIntFlowCorrelationsAllHist"; | |
1812 | intFlowCorrelationsAllHistName += fAnalysisLabel->Data(); | |
8ed4edc7 | 1813 | fIntFlowCorrelationsAllHist = new TH1D(intFlowCorrelationsAllHistName.Data(),"Average correlations for all events",34,0,34); |
489d5531 | 1814 | fIntFlowCorrelationsAllHist->SetTickLength(-0.01,"Y"); |
1815 | fIntFlowCorrelationsAllHist->SetMarkerStyle(25); | |
1816 | fIntFlowCorrelationsAllHist->SetLabelSize(0.03); | |
1817 | fIntFlowCorrelationsAllHist->SetLabelOffset(0.01,"Y"); | |
1818 | // 2-p correlations: | |
1819 | (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(1,"<<2>>_{n|n}"); | |
1820 | (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(2,"<<2>>_{2n|2n}"); | |
1821 | (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(3,"<<2>>_{3n|3n}"); | |
1822 | (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(4,"<<2>>_{4n|4n}"); | |
1823 | // 3-p correlations: | |
1824 | (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(6,"<<3>>_{2n|n,n}"); | |
1825 | (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(7,"<<3>>_{3n|2n,n}"); | |
1826 | (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(8,"<<3>>_{4n|2n,2n}"); | |
1827 | (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(9,"<<3>>_{4n|3n,n}"); | |
1828 | // 4-p correlations: | |
1829 | (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(11,"<<4>>_{n,n|n,n}"); | |
1830 | (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(12,"<<4>>_{2n,n|2n,n}"); | |
1831 | (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(13,"<<4>>_{2n,2n|2n,2n}"); | |
1832 | (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(14,"<<4>>_{3n|n,n,n}"); | |
1833 | (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(15,"<<4>>_{3n,n|3n,n}"); | |
1834 | (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(16,"<<4>>_{3n,n|2n,2n}"); | |
1835 | (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(17,"<<4>>_{4n|2n,n,n}"); | |
1836 | // 5-p correlations: | |
1837 | (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(19,"<<5>>_{2n|n,n,n,n}"); | |
1838 | (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(20,"<<5>>_{2n,2n|2n,n,n}"); | |
1839 | (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(21,"<<5>>_{3n,n|2n,n,n}"); | |
1840 | (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(22,"<<5>>_{4n|n,n,n,n}"); | |
1841 | // 6-p correlations: | |
1842 | (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(24,"<<6>>_{n,n,n|n,n,n}"); | |
1843 | (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(25,"<<6>>_{2n,n,n|2n,n,n}"); | |
1844 | (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(26,"<<6>>_{2n,2n|n,n,n,n}"); | |
1845 | (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(27,"<<6>>_{3n,n|n,n,n,n}"); | |
1846 | // 7-p correlations: | |
1847 | (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(29,"<<7>>_{2n,n,n|n,n,n,n}"); | |
1848 | // 8-p correlations: | |
1849 | (fIntFlowCorrelationsAllHist->GetXaxis())->SetBinLabel(31,"<<8>>_{n,n,n,n|n,n,n,n}"); | |
1850 | fIntFlowResults->Add(fIntFlowCorrelationsAllHist); | |
1851 | // average correction terms for non-uniform acceptance (with correct errors!): | |
1852 | for(Int_t sc=0;sc<2;sc++) // sin or cos terms | |
1853 | { | |
1854 | TString intFlowCorrectionTermsForNUAHistName = "fIntFlowCorrectionTermsForNUAHist"; | |
1855 | intFlowCorrectionTermsForNUAHistName += fAnalysisLabel->Data(); | |
b92ea2b9 | 1856 | fIntFlowCorrectionTermsForNUAHist[sc] = new TH1D(Form("%s: %s terms",intFlowCorrectionTermsForNUAHistName.Data(),sinCosFlag[sc].Data()),Form("Correction terms for non-uniform acceptance (%s terms)",sinCosFlag[sc].Data()),4,0,4); |
489d5531 | 1857 | fIntFlowCorrectionTermsForNUAHist[sc]->SetTickLength(-0.01,"Y"); |
1858 | fIntFlowCorrectionTermsForNUAHist[sc]->SetMarkerStyle(25); | |
1859 | fIntFlowCorrectionTermsForNUAHist[sc]->SetLabelSize(0.03); | |
1860 | fIntFlowCorrectionTermsForNUAHist[sc]->SetLabelOffset(0.01,"Y"); | |
b92ea2b9 | 1861 | (fIntFlowCorrectionTermsForNUAHist[sc]->GetXaxis())->SetBinLabel(1,Form("#LT#LT%s(n(#phi_{1}))#GT#GT",sinCosFlag[sc].Data())); |
1862 | (fIntFlowCorrectionTermsForNUAHist[sc]->GetXaxis())->SetBinLabel(2,Form("#LT#LT%s(n(phi1+phi2))#GT#GT",sinCosFlag[sc].Data())); | |
1863 | (fIntFlowCorrectionTermsForNUAHist[sc]->GetXaxis())->SetBinLabel(3,Form("#LT#LT%s(n(phi1-phi2-phi3))#GT#GT",sinCosFlag[sc].Data())); | |
1864 | (fIntFlowCorrectionTermsForNUAHist[sc]->GetXaxis())->SetBinLabel(4,Form("#LT#LT%s(n(2phi1-phi2))#GT#GT",sinCosFlag[sc].Data())); | |
489d5531 | 1865 | fIntFlowResults->Add(fIntFlowCorrectionTermsForNUAHist[sc]); |
1866 | } // end of for(Int_t sc=0;sc<2;sc++) | |
1867 | // covariances (multiplied with weight dependent prefactor): | |
1868 | TString intFlowCovariancesName = "fIntFlowCovariances"; | |
1869 | intFlowCovariancesName += fAnalysisLabel->Data(); | |
1870 | fIntFlowCovariances = new TH1D(intFlowCovariancesName.Data(),"Covariances (multiplied with weight dependent prefactor)",6,0,6); | |
1871 | fIntFlowCovariances->SetLabelSize(0.04); | |
1872 | fIntFlowCovariances->SetMarkerStyle(25); | |
1873 | (fIntFlowCovariances->GetXaxis())->SetBinLabel(1,"Cov(<2>,<4>)"); | |
1874 | (fIntFlowCovariances->GetXaxis())->SetBinLabel(2,"Cov(<2>,<6>)"); | |
1875 | (fIntFlowCovariances->GetXaxis())->SetBinLabel(3,"Cov(<2>,<8>)"); | |
1876 | (fIntFlowCovariances->GetXaxis())->SetBinLabel(4,"Cov(<4>,<6>)"); | |
1877 | (fIntFlowCovariances->GetXaxis())->SetBinLabel(5,"Cov(<4>,<8>)"); | |
1878 | (fIntFlowCovariances->GetXaxis())->SetBinLabel(6,"Cov(<6>,<8>)"); | |
1879 | fIntFlowResults->Add(fIntFlowCovariances); | |
1880 | // sum of linear and quadratic event weights for <2>, <4>, <6> and <8>: | |
1881 | TString intFlowSumOfEventWeightsName = "fIntFlowSumOfEventWeights"; | |
1882 | intFlowSumOfEventWeightsName += fAnalysisLabel->Data(); | |
1883 | for(Int_t power=0;power<2;power++) | |
1884 | { | |
1885 | fIntFlowSumOfEventWeights[power] = new TH1D(Form("%s: %s",intFlowSumOfEventWeightsName.Data(),powerFlag[power].Data()),Form("Sum of %s event weights for correlations",powerFlag[power].Data()),4,0,4); | |
1886 | fIntFlowSumOfEventWeights[power]->SetLabelSize(0.05); | |
1887 | fIntFlowSumOfEventWeights[power]->SetMarkerStyle(25); | |
1888 | if(power == 0) | |
1889 | { | |
1890 | (fIntFlowSumOfEventWeights[power]->GetXaxis())->SetBinLabel(1,"#sum_{i=1}^{N} w_{<2>}"); | |
1891 | (fIntFlowSumOfEventWeights[power]->GetXaxis())->SetBinLabel(2,"#sum_{i=1}^{N} w_{<4>}"); | |
1892 | (fIntFlowSumOfEventWeights[power]->GetXaxis())->SetBinLabel(3,"#sum_{i=1}^{N} w_{<6>}"); | |
1893 | (fIntFlowSumOfEventWeights[power]->GetXaxis())->SetBinLabel(4,"#sum_{i=1}^{N} w_{<8>}"); | |
1894 | } else if (power == 1) | |
1895 | { | |
1896 | (fIntFlowSumOfEventWeights[power]->GetXaxis())->SetBinLabel(1,"#sum_{i=1}^{N} w_{<2>}^{2}"); | |
1897 | (fIntFlowSumOfEventWeights[power]->GetXaxis())->SetBinLabel(2,"#sum_{i=1}^{N} w_{<4>}^{2}"); | |
1898 | (fIntFlowSumOfEventWeights[power]->GetXaxis())->SetBinLabel(3,"#sum_{i=1}^{N} w_{<6>}^{2}"); | |
1899 | (fIntFlowSumOfEventWeights[power]->GetXaxis())->SetBinLabel(4,"#sum_{i=1}^{N} w_{<8>}^{2}"); | |
1900 | } | |
1901 | fIntFlowResults->Add(fIntFlowSumOfEventWeights[power]); | |
1902 | } | |
1903 | // sum of products of event weights for correlations <2>, <4>, <6> and <8>: | |
1904 | TString intFlowSumOfProductOfEventWeightsName = "fIntFlowSumOfProductOfEventWeights"; | |
1905 | intFlowSumOfProductOfEventWeightsName += fAnalysisLabel->Data(); | |
1906 | fIntFlowSumOfProductOfEventWeights = new TH1D(intFlowSumOfProductOfEventWeightsName.Data(),"Sum of product of event weights for correlations",6,0,6); | |
1907 | fIntFlowSumOfProductOfEventWeights->SetLabelSize(0.05); | |
1908 | fIntFlowSumOfProductOfEventWeights->SetMarkerStyle(25); | |
1909 | (fIntFlowSumOfProductOfEventWeights->GetXaxis())->SetBinLabel(1,"#sum_{i=1}^{N} w_{<2>} w_{<4>}"); | |
1910 | (fIntFlowSumOfProductOfEventWeights->GetXaxis())->SetBinLabel(2,"#sum_{i=1}^{N} w_{<2>} w_{<6>}"); | |
1911 | (fIntFlowSumOfProductOfEventWeights->GetXaxis())->SetBinLabel(3,"#sum_{i=1}^{N} w_{<2>} w_{<8>}"); | |
1912 | (fIntFlowSumOfProductOfEventWeights->GetXaxis())->SetBinLabel(4,"#sum_{i=1}^{N} w_{<4>} w_{<6>}"); | |
1913 | (fIntFlowSumOfProductOfEventWeights->GetXaxis())->SetBinLabel(5,"#sum_{i=1}^{N} w_{<4>} w_{<8>}"); | |
1914 | (fIntFlowSumOfProductOfEventWeights->GetXaxis())->SetBinLabel(6,"#sum_{i=1}^{N} w_{<6>} w_{<8>}"); | |
1915 | fIntFlowResults->Add(fIntFlowSumOfProductOfEventWeights); | |
ff70ca91 | 1916 | // final result for covariances of correlations (multiplied with weight dependent prefactor) versus M |
1917 | // [0=Cov(2,4),1=Cov(2,6),2=Cov(2,8),3=Cov(4,6),4=Cov(4,8),5=Cov(6,8)]: | |
b3dacf6b | 1918 | if(fCalculateCumulantsVsM) |
ff70ca91 | 1919 | { |
b3dacf6b | 1920 | TString intFlowCovariancesVsMName = "fIntFlowCovariancesVsM"; |
1921 | intFlowCovariancesVsMName += fAnalysisLabel->Data(); | |
1922 | TString covarianceFlag[6] = {"Cov(<2>,<4>)","Cov(<2>,<6>)","Cov(<2>,<8>)","Cov(<4>,<6>)","Cov(<4>,<8>)","Cov(<6>,<8>)"}; | |
1923 | for(Int_t ci=0;ci<6;ci++) | |
1924 | { | |
1925 | fIntFlowCovariancesVsM[ci] = new TH1D(Form("%s, %s",intFlowCovariancesVsMName.Data(),covarianceFlag[ci].Data()), | |
1926 | Form("%s vs multiplicity",covarianceFlag[ci].Data()), | |
1927 | fnBinsMult,fMinMult,fMaxMult); | |
1928 | fIntFlowCovariancesVsM[ci]->GetYaxis()->SetTitle(covarianceFlag[ci].Data()); | |
1929 | fIntFlowCovariancesVsM[ci]->GetXaxis()->SetTitle("M"); | |
1930 | fIntFlowResults->Add(fIntFlowCovariancesVsM[ci]); | |
1931 | } | |
1932 | } // end of if(fCalculateCumulantsVsM) | |
ff70ca91 | 1933 | // sum of linear and quadratic event weights for <2>, <4>, <6> and <8> versus multiplicity |
1934 | // [0=sum{w_{<2>}},1=sum{w_{<4>}},2=sum{w_{<6>}},3=sum{w_{<8>}}][0=linear 1,1=quadratic]: | |
b3dacf6b | 1935 | if(fCalculateCumulantsVsM) |
ff70ca91 | 1936 | { |
b3dacf6b | 1937 | TString intFlowSumOfEventWeightsVsMName = "fIntFlowSumOfEventWeightsVsM"; |
1938 | intFlowSumOfEventWeightsVsMName += fAnalysisLabel->Data(); | |
1939 | TString sumFlag[2][4] = {{"#sum_{i=1}^{N} w_{<2>}","#sum_{i=1}^{N} w_{<4>}","#sum_{i=1}^{N} w_{<6>}","#sum_{i=1}^{N} w_{<8>}"}, | |
1940 | {"#sum_{i=1}^{N} w_{<2>}^{2}","#sum_{i=1}^{N} w_{<4>}^{2}","#sum_{i=1}^{N} w_{<6>}^{2}","#sum_{i=1}^{N} w_{<8>}^{2}"}}; | |
1941 | for(Int_t si=0;si<4;si++) | |
ff70ca91 | 1942 | { |
b3dacf6b | 1943 | for(Int_t power=0;power<2;power++) |
1944 | { | |
1945 | fIntFlowSumOfEventWeightsVsM[si][power] = new TH1D(Form("%s, %s",intFlowSumOfEventWeightsVsMName.Data(),sumFlag[power][si].Data()), | |
1946 | Form("%s vs multiplicity",sumFlag[power][si].Data()), | |
1947 | fnBinsMult,fMinMult,fMaxMult); | |
1948 | fIntFlowSumOfEventWeightsVsM[si][power]->GetYaxis()->SetTitle(sumFlag[power][si].Data()); | |
1949 | fIntFlowSumOfEventWeightsVsM[si][power]->GetXaxis()->SetTitle("M"); | |
1950 | fIntFlowResults->Add(fIntFlowSumOfEventWeightsVsM[si][power]); | |
1951 | } // end of for(Int_t power=0;power<2;power++) | |
1952 | } // end of for(Int_t si=0;si<4;si++) | |
1953 | } // end of if(fCalculateCumulantsVsM) | |
ff70ca91 | 1954 | // sum of products of event weights for correlations <2>, <4>, <6> and <8> vs M |
1955 | // [0=sum{w_{<2>}w_{<4>}},1=sum{w_{<2>}w_{<6>}},2=sum{w_{<2>}w_{<8>}}, | |
1956 | // 3=sum{w_{<4>}w_{<6>}},4=sum{w_{<4>}w_{<8>}},5=sum{w_{<6>}w_{<8>}}]: | |
b3dacf6b | 1957 | if(fCalculateCumulantsVsM) |
1958 | { | |
1959 | TString intFlowSumOfProductOfEventWeightsVsMName = "fIntFlowSumOfProductOfEventWeightsVsM"; | |
1960 | intFlowSumOfProductOfEventWeightsVsMName += fAnalysisLabel->Data(); | |
1961 | TString sopowFlag[6] = {"#sum_{i=1}^{N} w_{<2>} w_{<4>}","#sum_{i=1}^{N} w_{<2>} w_{<6>}","#sum_{i=1}^{N} w_{<2>} w_{<8>}", | |
1962 | "#sum_{i=1}^{N} w_{<4>} w_{<6>}","#sum_{i=1}^{N} w_{<4>} w_{<8>}","#sum_{i=1}^{N} w_{<6>} w_{<8>}"}; | |
1963 | for(Int_t pi=0;pi<6;pi++) | |
1964 | { | |
1965 | fIntFlowSumOfProductOfEventWeightsVsM[pi] = new TH1D(Form("%s, %s",intFlowSumOfProductOfEventWeightsVsMName.Data(),sopowFlag[pi].Data()), | |
1966 | Form("%s versus multiplicity",sopowFlag[pi].Data()), | |
1967 | fnBinsMult,fMinMult,fMaxMult); | |
1968 | fIntFlowSumOfProductOfEventWeightsVsM[pi]->GetXaxis()->SetTitle("M"); | |
1969 | fIntFlowSumOfProductOfEventWeightsVsM[pi]->GetYaxis()->SetTitle(sopowFlag[pi].Data()); | |
1970 | fIntFlowResults->Add(fIntFlowSumOfProductOfEventWeightsVsM[pi]); | |
1971 | } // end of for(Int_t pi=0;pi<6;pi++) | |
1972 | } // end of if(fCalculateCumulantsVsM) | |
0328db2d | 1973 | // covariances of NUA terms (multiplied with weight dependent prefactor): |
1974 | TString intFlowCovariancesNUAName = "fIntFlowCovariancesNUA"; | |
1975 | intFlowCovariancesNUAName += fAnalysisLabel->Data(); | |
1976 | fIntFlowCovariancesNUA = new TH1D(intFlowCovariancesNUAName.Data(),"Covariances for NUA (multiplied with weight dependent prefactor)",27,0,27); | |
1977 | fIntFlowCovariancesNUA->SetLabelSize(0.04); | |
1978 | fIntFlowCovariancesNUA->SetMarkerStyle(25); | |
1979 | fIntFlowCovariancesNUA->GetXaxis()->SetLabelSize(0.02); | |
1980 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(1,"Cov(<2>,<cos(#phi)>"); | |
1981 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(2,"Cov(<2>,<sin(#phi)>)"); | |
1982 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(3,"Cov(<cos(#phi)>,<sin(#phi)>)"); | |
1983 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(4,"Cov(<2>,<cos(#phi_{1}+#phi_{2})>)"); | |
1984 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(5,"Cov(<2>,<sin(#phi_{1}+#phi_{2})>)"); | |
1985 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(6,"Cov(<2>,<cos(#phi_{1}-#phi_{2}-#phi_{3})>)"); | |
1986 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(7,"Cov(<2>,<sin(#phi_{1}-#phi_{2}-#phi_{3})>)"); | |
1987 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(8,"Cov(<4>,<cos(#phi)>)"); | |
1988 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(9,"Cov(<4>,<sin(#phi)>)"); | |
1989 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(10,"Cov(<4>,<cos(#phi_{1}+#phi_{2})>)"); | |
1990 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(11,"Cov(<4>,<sin(#phi_{1}+#phi_{2})>)"); | |
1991 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(12,"Cov(<4>,<cos(#phi_{1}-#phi_{2}-#phi_{3})>>)"); | |
1992 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(13,"Cov(<4>,<sin(#phi_{1}-#phi_{2}-#phi_{3})>>)"); | |
1993 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(14,"Cov(<cos(#phi)>,<cos(#phi_{1}+#phi_{2})>)"); | |
1994 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(15,"Cov(<cos(#phi)>,<sin(#phi_{1}+#phi_{2})>)"); | |
1995 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(16,"Cov(<cos(#phi)>,<cos(#phi_{1}-#phi_{2}-#phi_{3})>)"); | |
1996 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(17,"Cov(<cos(#phi)>,<sin(#phi_{1}-#phi_{2}-#phi_{3})>)"); | |
1997 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(18,"Cov(<sin(#phi)>,<cos(#phi_{1}+#phi_{2})>)"); | |
1998 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(19,"Cov(<sin(#phi)>,<sin(#phi_{1}+#phi_{2})>)"); | |
1999 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(20,"Cov(<sin(#phi)>,<cos(#phi_{1}-#phi_{2}-#phi_{3})>)"); | |
2000 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(21,"Cov(<sin(#phi)>,<sin(#phi_{1}-#phi_{2}-#phi_{3})>)"); | |
2001 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(22,"Cov(<cos(#phi_{1}+#phi_{2})>,<sin(#phi_{1}+#phi_{2})>)"); | |
2002 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(23,"Cov(<cos(#phi_{1}+#phi_{2})>,<cos(#phi_{1}-#phi_{2}-#phi_{3})>)"); | |
2003 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(24,"Cov(<cos(#phi_{1}+#phi_{2})>,<sin(#phi_{1}-#phi_{2}-#phi_{3})>)"); | |
2004 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(25,"Cov(<sin(#phi_{1}+#phi_{2})>,<cos(#phi_{1}-#phi_{2}-#phi_{3})>)"); | |
2005 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(26,"Cov(<sin(#phi_{1}+#phi_{2})>,<sin(#phi_{1}-#phi_{2}-#phi_{3})>)"); | |
2006 | (fIntFlowCovariancesNUA->GetXaxis())->SetBinLabel(27,"Cov(<cos(#phi_{1}-#phi_{2}-#phi_{3}>,<sin(#phi_{1}-#phi_{2}-#phi_{3}>)"); | |
2007 | fIntFlowResults->Add(fIntFlowCovariancesNUA); | |
2008 | // sum of linear and quadratic event weights for NUA terms: | |
2009 | TString intFlowSumOfEventWeightsNUAName = "fIntFlowSumOfEventWeightsNUA"; | |
2010 | intFlowSumOfEventWeightsNUAName += fAnalysisLabel->Data(); | |
2011 | for(Int_t sc=0;sc<2;sc++) | |
2012 | { | |
2013 | for(Int_t power=0;power<2;power++) | |
2014 | { | |
b92ea2b9 | 2015 | fIntFlowSumOfEventWeightsNUA[sc][power] = new TH1D(Form("%s: %s, %s",intFlowSumOfEventWeightsNUAName.Data(),powerFlag[power].Data(),sinCosFlag[sc].Data()),Form("Sum of %s event weights for NUA %s terms",powerFlag[power].Data(),sinCosFlag[sc].Data()),4,0,4); // to be improved - 4 |
0328db2d | 2016 | fIntFlowSumOfEventWeightsNUA[sc][power]->SetLabelSize(0.05); |
2017 | fIntFlowSumOfEventWeightsNUA[sc][power]->SetMarkerStyle(25); | |
2018 | if(power == 0) | |
2019 | { | |
2020 | (fIntFlowSumOfEventWeightsNUA[sc][power]->GetXaxis())->SetBinLabel(1,Form("#sum_{i=1}^{N} w_{<%s(#phi)>}",sinCosFlag[sc].Data())); | |
2021 | (fIntFlowSumOfEventWeightsNUA[sc][power]->GetXaxis())->SetBinLabel(2,Form("#sum_{i=1}^{N} w_{<%s(#phi_{1}+#phi_{2})>}",sinCosFlag[sc].Data())); | |
b92ea2b9 | 2022 | (fIntFlowSumOfEventWeightsNUA[sc][power]->GetXaxis())->SetBinLabel(3,Form("#sum_{i=1}^{N} w_{<%s(#phi_{1}-#phi_{2}-#phi_{3})>}",sinCosFlag[sc].Data())); |
2023 | (fIntFlowSumOfEventWeightsNUA[sc][power]->GetXaxis())->SetBinLabel(4,Form("#sum_{i=1}^{N} w_{<%s(2#phi_{1}-#phi_{2})>}",sinCosFlag[sc].Data())); | |
0328db2d | 2024 | } else if(power == 1) |
2025 | { | |
2026 | (fIntFlowSumOfEventWeightsNUA[sc][power]->GetXaxis())->SetBinLabel(1,Form("#sum_{i=1}^{N} w_{<%s(#phi)>}^{2}",sinCosFlag[sc].Data())); | |
2027 | (fIntFlowSumOfEventWeightsNUA[sc][power]->GetXaxis())->SetBinLabel(2,Form("#sum_{i=1}^{N} w_{<%s(#phi_{1}+#phi_{2})>}^{2}",sinCosFlag[sc].Data())); | |
2028 | (fIntFlowSumOfEventWeightsNUA[sc][power]->GetXaxis())->SetBinLabel(3,Form("#sum_{i=1}^{N} w_{<%s(#phi_{1}-#phi_{2}-#phi_{3})>}^{2}",sinCosFlag[sc].Data())); | |
b92ea2b9 | 2029 | (fIntFlowSumOfEventWeightsNUA[sc][power]->GetXaxis())->SetBinLabel(4,Form("#sum_{i=1}^{N} w_{<%s(2#phi_{1}-#phi_{2})>}^{2}",sinCosFlag[sc].Data())); |
0328db2d | 2030 | } |
2031 | fIntFlowResults->Add(fIntFlowSumOfEventWeightsNUA[sc][power]); | |
2032 | } | |
2033 | } | |
2034 | // sum of products of event weights for NUA terms: | |
2035 | TString intFlowSumOfProductOfEventWeightsNUAName = "fIntFlowSumOfProductOfEventWeightsNUA"; | |
2036 | intFlowSumOfProductOfEventWeightsNUAName += fAnalysisLabel->Data(); | |
2037 | fIntFlowSumOfProductOfEventWeightsNUA = new TH1D(intFlowSumOfProductOfEventWeightsNUAName.Data(),"Sum of product of event weights for NUA terms",27,0,27); | |
2038 | fIntFlowSumOfProductOfEventWeightsNUA->SetLabelSize(0.05); | |
2039 | fIntFlowSumOfProductOfEventWeightsNUA->SetMarkerStyle(25); | |
2040 | (fIntFlowSumOfProductOfEventWeightsNUA->GetXaxis())->SetBinLabel(1,"#sum_{i=1}^{N} w_{<2>} w_{<cos(#phi)>}"); | |
2041 | (fIntFlowSumOfProductOfEventWeightsNUA->GetXaxis())->SetBinLabel(2,"#sum_{i=1}^{N} w_{<2>} w_{<sin(#phi)>}"); | |
2042 | (fIntFlowSumOfProductOfEventWeightsNUA->GetXaxis())->SetBinLabel(3,"#sum_{i=1}^{N} w_{<cos(#phi)>} w_{<sin(#phi)>}"); | |
2043 | // .... | |
2044 | // to be improved - add labels for remaining bins | |
2045 | // .... | |
2046 | fIntFlowResults->Add(fIntFlowSumOfProductOfEventWeightsNUA); | |
b3dacf6b | 2047 | // Final results for reference Q-cumulants: |
2048 | TString cumulantFlag[4] = {"QC{2}","QC{4}","QC{6}","QC{8}"}; | |
489d5531 | 2049 | TString intFlowQcumulantsName = "fIntFlowQcumulants"; |
2050 | intFlowQcumulantsName += fAnalysisLabel->Data(); | |
b92ea2b9 | 2051 | fIntFlowQcumulants = new TH1D(intFlowQcumulantsName.Data(),"Reference Q-cumulants",4,0,4); |
b77b6434 | 2052 | if(fPropagateErrorAlsoFromNIT) |
b92ea2b9 | 2053 | { |
b77b6434 | 2054 | fIntFlowQcumulants->SetTitle("Reference Q-cumulants (error from non-isotropic terms also propagated)"); |
b92ea2b9 | 2055 | } |
489d5531 | 2056 | fIntFlowQcumulants->SetLabelSize(0.05); |
2057 | fIntFlowQcumulants->SetMarkerStyle(25); | |
68a3b4b1 | 2058 | for(Int_t b=0;b<4;b++) |
b3dacf6b | 2059 | { |
68a3b4b1 | 2060 | (fIntFlowQcumulants->GetXaxis())->SetBinLabel(b+1,cumulantFlag[b].Data()); |
b3dacf6b | 2061 | } |
489d5531 | 2062 | fIntFlowResults->Add(fIntFlowQcumulants); |
b3dacf6b | 2063 | // Final results for reference Q-cumulants rebinned in M: |
2064 | if(fCalculateCumulantsVsM) | |
2065 | { | |
2066 | TString intFlowQcumulantsRebinnedInMName = "fIntFlowQcumulantsRebinnedInM"; | |
2067 | intFlowQcumulantsRebinnedInMName += fAnalysisLabel->Data(); | |
2068 | fIntFlowQcumulantsRebinnedInM = new TH1D(intFlowQcumulantsRebinnedInMName.Data(),"Reference Q-cumulants rebinned in M",4,0,4); | |
2069 | fIntFlowQcumulantsRebinnedInM->SetLabelSize(0.05); | |
2070 | fIntFlowQcumulantsRebinnedInM->SetMarkerStyle(25); | |
68a3b4b1 | 2071 | for(Int_t b=0;b<4;b++) |
b3dacf6b | 2072 | { |
68a3b4b1 | 2073 | (fIntFlowQcumulantsRebinnedInM->GetXaxis())->SetBinLabel(b+1,cumulantFlag[b].Data()); |
b3dacf6b | 2074 | } |
2075 | fIntFlowResults->Add(fIntFlowQcumulantsRebinnedInM); | |
2076 | } // end of if(fCalculateCumulantsVsM) | |
b92ea2b9 | 2077 | // Ratio between error squared: with/without non-isotropic terms: |
2078 | TString intFlowQcumulantsErrorSquaredRatioName = "fIntFlowQcumulantsErrorSquaredRatio"; | |
2079 | intFlowQcumulantsErrorSquaredRatioName += fAnalysisLabel->Data(); | |
2080 | fIntFlowQcumulantsErrorSquaredRatio = new TH1D(intFlowQcumulantsErrorSquaredRatioName.Data(),"Error squared of reference Q-cumulants: #frac{with NUA terms}{without NUA terms}",4,0,4); | |
2081 | fIntFlowQcumulantsErrorSquaredRatio->SetLabelSize(0.05); | |
2082 | fIntFlowQcumulantsErrorSquaredRatio->SetMarkerStyle(25); | |
2083 | for(Int_t b=0;b<4;b++) | |
2084 | { | |
2085 | (fIntFlowQcumulantsErrorSquaredRatio->GetXaxis())->SetBinLabel(b+1,cumulantFlag[b].Data()); | |
2086 | } | |
2087 | fIntFlowResults->Add(fIntFlowQcumulantsErrorSquaredRatio); | |
ff70ca91 | 2088 | // final results for integrated Q-cumulants versus multiplicity: |
b3dacf6b | 2089 | if(fCalculateCumulantsVsM) |
2090 | { | |
2091 | TString intFlowQcumulantsVsMName = "fIntFlowQcumulantsVsM"; | |
2092 | intFlowQcumulantsVsMName += fAnalysisLabel->Data(); | |
2093 | for(Int_t co=0;co<4;co++) // cumulant order | |
2094 | { | |
2095 | fIntFlowQcumulantsVsM[co] = new TH1D(Form("%s, %s",intFlowQcumulantsVsMName.Data(),cumulantFlag[co].Data()), | |
2096 | Form("%s vs multipicity",cumulantFlag[co].Data()), | |
2097 | fnBinsMult,fMinMult,fMaxMult); | |
2098 | fIntFlowQcumulantsVsM[co]->GetXaxis()->SetTitle("M"); | |
2099 | fIntFlowQcumulantsVsM[co]->GetYaxis()->SetTitle(cumulantFlag[co].Data()); | |
2100 | fIntFlowResults->Add(fIntFlowQcumulantsVsM[co]); | |
2101 | } // end of for(Int_t co=0;co<4;co++) // cumulant order | |
2102 | } // end of if(fCalculateCumulantsVsM) | |
489d5531 | 2103 | // final integrated flow estimates from Q-cumulants: |
b3dacf6b | 2104 | TString flowFlag[4] = {Form("v_{%d}{2,QC}",fHarmonic),Form("v_{%d}{4,QC}",fHarmonic),Form("v_{%d}{6,QC}",fHarmonic),Form("v_{%d}{8,QC}",fHarmonic)}; |
489d5531 | 2105 | TString intFlowName = "fIntFlow"; |
2106 | intFlowName += fAnalysisLabel->Data(); | |
2107 | // integrated flow from Q-cumulants: | |
b3dacf6b | 2108 | fIntFlow = new TH1D(intFlowName.Data(),"Reference flow estimates from Q-cumulants",4,0,4); |
489d5531 | 2109 | fIntFlow->SetLabelSize(0.05); |
2110 | fIntFlow->SetMarkerStyle(25); | |
68a3b4b1 | 2111 | for(Int_t b=0;b<4;b++) |
b3dacf6b | 2112 | { |
68a3b4b1 | 2113 | (fIntFlow->GetXaxis())->SetBinLabel(b+1,flowFlag[b].Data()); |
b3dacf6b | 2114 | } |
ff70ca91 | 2115 | fIntFlowResults->Add(fIntFlow); |
b3dacf6b | 2116 | // Reference flow vs M rebinned in one huge bin: |
2117 | if(fCalculateCumulantsVsM) | |
2118 | { | |
2119 | TString intFlowRebinnedInMName = "fIntFlowRebinnedInM"; | |
2120 | intFlowRebinnedInMName += fAnalysisLabel->Data(); | |
2121 | fIntFlowRebinnedInM = new TH1D(intFlowRebinnedInMName.Data(),"Reference flow estimates from Q-cumulants (rebinned in M)",4,0,4); | |
2122 | fIntFlowRebinnedInM->SetLabelSize(0.05); | |
2123 | fIntFlowRebinnedInM->SetMarkerStyle(25); | |
68a3b4b1 | 2124 | for(Int_t b=0;b<4;b++) |
b3dacf6b | 2125 | { |
68a3b4b1 | 2126 | (fIntFlowRebinnedInM->GetXaxis())->SetBinLabel(b+1,flowFlag[b].Data()); |
b3dacf6b | 2127 | } |
2128 | fIntFlowResults->Add(fIntFlowRebinnedInM); | |
2129 | } | |
ff70ca91 | 2130 | // integrated flow from Q-cumulants: versus multiplicity: |
b3dacf6b | 2131 | if(fCalculateCumulantsVsM) |
2132 | { | |
2133 | TString intFlowVsMName = "fIntFlowVsM"; | |
2134 | intFlowVsMName += fAnalysisLabel->Data(); | |
2135 | for(Int_t co=0;co<4;co++) // cumulant order | |
2136 | { | |
2137 | fIntFlowVsM[co] = new TH1D(Form("%s, %s",intFlowVsMName.Data(),flowFlag[co].Data()), | |
2138 | Form("%s vs multipicity",flowFlag[co].Data()), | |
2139 | fnBinsMult,fMinMult,fMaxMult); | |
2140 | fIntFlowVsM[co]->GetXaxis()->SetTitle("M"); | |
2141 | fIntFlowVsM[co]->GetYaxis()->SetTitle(flowFlag[co].Data()); | |
2142 | fIntFlowResults->Add(fIntFlowVsM[co]); | |
2143 | } // end of for(Int_t co=0;co<4;co++) // cumulant order | |
2144 | } // end of if(fCalculateCumulantsVsM) | |
2001bc3a | 2145 | // quantifying detector effects effects to correlations: |
2146 | TString intFlowDetectorBiasName = "fIntFlowDetectorBias"; | |
2147 | intFlowDetectorBiasName += fAnalysisLabel->Data(); | |
2148 | fIntFlowDetectorBias = new TH1D(intFlowDetectorBiasName.Data(),"Quantifying detector bias",4,0,4); | |
2149 | fIntFlowDetectorBias->SetLabelSize(0.05); | |
2150 | fIntFlowDetectorBias->SetMarkerStyle(25); | |
2151 | for(Int_t ci=0;ci<4;ci++) | |
2152 | { | |
2153 | (fIntFlowDetectorBias->GetXaxis())->SetBinLabel(ci+1,Form("#frac{corrected}{measured} %s",cumulantFlag[ci].Data())); | |
2154 | } | |
2155 | fIntFlowResults->Add(fIntFlowDetectorBias); | |
2156 | // quantifying detector effects to correlations versus multiplicity: | |
b3dacf6b | 2157 | if(fCalculateCumulantsVsM) |
2001bc3a | 2158 | { |
b3dacf6b | 2159 | TString intFlowDetectorBiasVsMName = "fIntFlowDetectorBiasVsM"; |
2160 | intFlowDetectorBiasVsMName += fAnalysisLabel->Data(); | |
2161 | for(Int_t ci=0;ci<4;ci++) // correlation index | |
2162 | { | |
2163 | fIntFlowDetectorBiasVsM[ci] = new TH1D(Form("%s for %s",intFlowDetectorBiasVsMName.Data(),cumulantFlag[ci].Data()), | |
2164 | Form("Quantifying detector bias for %s vs multipicity",cumulantFlag[ci].Data()), | |
2165 | fnBinsMult,fMinMult,fMaxMult); | |
2166 | fIntFlowDetectorBiasVsM[ci]->GetXaxis()->SetTitle("M"); | |
2167 | fIntFlowDetectorBiasVsM[ci]->GetYaxis()->SetTitle("#frac{corrected}{measured}"); | |
b77b6434 | 2168 | fIntFlowResults->Add(fIntFlowDetectorBiasVsM[ci]); |
b3dacf6b | 2169 | } // end of for(Int_t co=0;co<4;co++) // cumulant order |
2170 | } // end of if(fCalculateCumulantsVsM) | |
2171 | ||
489d5531 | 2172 | /* // to be improved (removed): |
2173 | // final average weighted multi-particle correlations for all events calculated from Q-vectors | |
2174 | fQCorrelations[1] = new TProfile("Weighted correlations","final average multi-particle correlations from weighted Q-vectors",200,0,200,"s"); | |
2175 | fQCorrelations[1]->SetTickLength(-0.01,"Y"); | |
2176 | fQCorrelations[1]->SetMarkerStyle(25); | |
2177 | fQCorrelations[1]->SetLabelSize(0.03); | |
2178 | fQCorrelations[1]->SetLabelOffset(0.01,"Y"); | |
2179 | // 2-particle correlations: | |
2180 | (fQCorrelations[1]->GetXaxis())->SetBinLabel(1,"<w_{1}w_{2}cos(n(#phi_{1}-#phi_{2}))>"); | |
2181 | (fQCorrelations[1]->GetXaxis())->SetBinLabel(2,"<w_{1}^{2}w_{2}^{2}cos(2n(#phi_{1}-#phi_{2}))>"); | |
2182 | (fQCorrelations[1]->GetXaxis())->SetBinLabel(3,"<w_{1}^{3}w_{2}^{3}cos(3n(#phi_{1}-#phi_{2}))>"); | |
2183 | (fQCorrelations[1]->GetXaxis())->SetBinLabel(4,"<w_{1}^{4}w_{2}^{4}cos(4n(#phi_{1}-#phi_{2}))>"); | |
2184 | (fQCorrelations[1]->GetXaxis())->SetBinLabel(5,"<w_{1}^{3}w_{2}cos(n(#phi_{1}-#phi_{2}))>"); | |
2185 | (fQCorrelations[1]->GetXaxis())->SetBinLabel(6,"<w_{1}^{2}w_{2}w_{3}cos(n(#phi_{1}-#phi_{2}))>"); | |
2186 | // 3-particle correlations: | |
2187 | (fQCorrelations[1]->GetXaxis())->SetBinLabel(21,"<w_{1}w_{2}w_{3}^{2}cos(n(2#phi_{1}-#phi_{2}-#phi_{3}))>"); | |
2188 | // 4-particle correlations: | |
2189 | (fQCorrelations[1]->GetXaxis())->SetBinLabel(41,"<w_{1}w_{2}w_{3}w_{4}cos(n(#phi_{1}+#phi_{2}-#phi_{3}-#phi_{4}))>"); | |
2190 | // add fQCorrelations[1] to the list fIntFlowList: | |
2191 | fIntFlowList->Add(fQCorrelations[1]); | |
2192 | */ | |
2193 | ||
2194 | } // end of AliFlowAnalysisWithQCumulants::BookEverythingForIntegratedFlow() | |
2195 | ||
2196 | ||
2197 | //================================================================================================================================ | |
2198 | ||
2199 | ||
2200 | void AliFlowAnalysisWithQCumulants::InitializeArraysForNestedLoops() | |
2201 | { | |
2202 | // Initialize arrays of all objects relevant for calculations with nested loops. | |
2203 | ||
2204 | // integrated flow: | |
2205 | for(Int_t sc=0;sc<2;sc++) // sin or cos terms | |
2206 | { | |
2207 | fIntFlowDirectCorrectionTermsForNUA[sc] = NULL; | |
2208 | } | |
2209 | ||
2210 | // differential flow: | |
2211 | // correlations: | |
2212 | for(Int_t t=0;t<2;t++) // type: RP or POI | |
2213 | { | |
2214 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
2215 | { | |
2216 | for(Int_t ci=0;ci<4;ci++) // correlation index | |
2217 | { | |
2218 | fDiffFlowDirectCorrelations[t][pe][ci] = NULL; | |
2219 | } // end of for(Int_t ci=0;ci<4;ci++) // correlation index | |
2220 | } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta | |
2221 | } // end of for(Int_t t=0;t<2;t++) // type: RP or POI | |
2222 | // correction terms for non-uniform acceptance: | |
2223 | for(Int_t t=0;t<2;t++) // type: RP or POI | |
2224 | { | |
2225 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
2226 | { | |
2227 | for(Int_t sc=0;sc<2;sc++) // sin or cos terms | |
2228 | { | |
2229 | for(Int_t cti=0;cti<9;cti++) // correction term index | |
2230 | { | |
2231 | fDiffFlowDirectCorrectionTermsForNUA[t][pe][sc][cti] = NULL; | |
2232 | } | |
2233 | } | |
2234 | } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta | |
2235 | } // end of for(Int_t t=0;t<2;t++) // type: RP or POI | |
2236 | ||
2237 | ||
2238 | } // end of void AliFlowAnalysisWithQCumulants::InitializeArraysForNestedLoops() | |
2239 | ||
2240 | ||
2241 | //================================================================================================================================ | |
2242 | ||
2243 | ||
2244 | void AliFlowAnalysisWithQCumulants::BookEverythingForNestedLoops() | |
2245 | { | |
2246 | // Book all objects relevant for calculations with nested loops. | |
2247 | ||
2248 | TString sinCosFlag[2] = {"sin","cos"}; // to be improved (should I promote this to data members?) | |
2249 | TString typeFlag[2] = {"RP","POI"}; // to be improved (should I promote this to data members?) | |
2250 | TString ptEtaFlag[2] = {"p_{T}","#eta"}; // to be improved (should I promote this to data members?) | |
2251 | TString reducedCorrelationIndex[4] = {"<2'>","<4'>","<6'>","<8'>"}; // to be improved (should I promote this to data members?) | |
2252 | Double_t lowerPtEtaEdge[2] = {fPtMin+(fCrossCheckInPtBinNo-1)*fPtBinWidth,fEtaMin+(fCrossCheckInEtaBinNo-1)*fEtaBinWidth}; | |
2253 | Double_t upperPtEtaEdge[2] = {fPtMin+fCrossCheckInPtBinNo*fPtBinWidth,fEtaMin+fCrossCheckInEtaBinNo*fEtaBinWidth}; | |
2254 | ||
2255 | TString evaluateNestedLoopsName = "fEvaluateNestedLoops"; | |
2256 | evaluateNestedLoopsName += fAnalysisLabel->Data(); | |
2257 | fEvaluateNestedLoops = new TProfile(evaluateNestedLoopsName.Data(),"Flags for nested loops",4,0,4); | |
2258 | fEvaluateNestedLoops->SetLabelSize(0.03); | |
2259 | (fEvaluateNestedLoops->GetXaxis())->SetBinLabel(1,"fEvaluateIntFlowNestedLoops"); | |
2260 | (fEvaluateNestedLoops->GetXaxis())->SetBinLabel(2,"fEvaluateDiffFlowNestedLoops"); | |
2261 | (fEvaluateNestedLoops->GetXaxis())->SetBinLabel(3,"fCrossCheckInPtBinNo"); | |
2262 | (fEvaluateNestedLoops->GetXaxis())->SetBinLabel(4,"fCrossCheckInEtaBinNo"); | |
2263 | fEvaluateNestedLoops->Fill(0.5,(Int_t)fEvaluateIntFlowNestedLoops); | |
2264 | fEvaluateNestedLoops->Fill(1.5,(Int_t)fEvaluateDiffFlowNestedLoops); | |
2265 | fEvaluateNestedLoops->Fill(2.5,fCrossCheckInPtBinNo); | |
2266 | fEvaluateNestedLoops->Fill(3.5,fCrossCheckInEtaBinNo); | |
2267 | fNestedLoopsList->Add(fEvaluateNestedLoops); | |
2268 | // nested loops for integrated flow: | |
2269 | if(fEvaluateIntFlowNestedLoops) | |
2270 | { | |
2271 | // correlations: | |
2272 | TString intFlowDirectCorrelationsName = "fIntFlowDirectCorrelations"; | |
2273 | intFlowDirectCorrelationsName += fAnalysisLabel->Data(); | |
8ed4edc7 | 2274 | fIntFlowDirectCorrelations = new TProfile(intFlowDirectCorrelationsName.Data(),"Multiparticle correlations calculated with nested loops (for int. flow)",34,0,34,"s"); |
489d5531 | 2275 | fNestedLoopsList->Add(fIntFlowDirectCorrelations); |
2276 | if(fUsePhiWeights||fUsePtWeights||fUseEtaWeights) | |
2277 | { | |
2278 | TString intFlowExtraDirectCorrelationsName = "fIntFlowExtraDirectCorrelations"; | |
2279 | intFlowExtraDirectCorrelationsName += fAnalysisLabel->Data(); | |
2280 | fIntFlowExtraDirectCorrelations = new TProfile(intFlowExtraDirectCorrelationsName.Data(),"Extra multiparticle correlations calculated with nested loops (for int. flow)",100,0,100,"s"); | |
2281 | fNestedLoopsList->Add(fIntFlowExtraDirectCorrelations); | |
2282 | } // end of if(fUsePhiWeights||fUsePtWeights||fUseEtaWeights) | |
2283 | // correction terms for non-uniform acceptance: | |
2284 | for(Int_t sc=0;sc<2;sc++) // sin or cos terms | |
2285 | { | |
2286 | TString intFlowDirectCorrectionTermsForNUAName = "fIntFlowDirectCorrectionTermsForNUA"; | |
2287 | intFlowDirectCorrectionTermsForNUAName += fAnalysisLabel->Data(); | |
2288 | fIntFlowDirectCorrectionTermsForNUA[sc] = new TProfile(Form("%s: %s terms",intFlowDirectCorrectionTermsForNUAName.Data(),sinCosFlag[sc].Data()),Form("Correction terms for non-uniform acceptance (%s terms)",sinCosFlag[sc].Data()),10,0,10,"s"); | |
2289 | fNestedLoopsList->Add(fIntFlowDirectCorrectionTermsForNUA[sc]); | |
2290 | } // end of for(Int_t sc=0;sc<2;sc++) | |
2291 | } // end of if(fEvaluateIntFlowNestedLoops) | |
2292 | ||
2293 | // nested loops for differential flow: | |
2294 | if(fEvaluateDiffFlowNestedLoops) | |
2295 | { | |
2296 | // reduced correlations: | |
2297 | TString diffFlowDirectCorrelationsName = "fDiffFlowDirectCorrelations"; | |
2298 | diffFlowDirectCorrelationsName += fAnalysisLabel->Data(); | |
2299 | for(Int_t t=0;t<2;t++) // type: RP or POI | |
2300 | { | |
2301 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
2302 | { | |
2303 | for(Int_t rci=0;rci<4;rci++) // reduced correlation index | |
2304 | { | |
2305 | // reduced correlations: | |
2306 | fDiffFlowDirectCorrelations[t][pe][rci] = new TProfile(Form("%s, %s, %s, %s",diffFlowDirectCorrelationsName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedCorrelationIndex[rci].Data()),Form("%s, %s, %s, %s",diffFlowDirectCorrelationsName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedCorrelationIndex[rci].Data()),1,lowerPtEtaEdge[pe],upperPtEtaEdge[pe],"s"); | |
2307 | fDiffFlowDirectCorrelations[t][pe][rci]->SetXTitle(ptEtaFlag[pe].Data()); | |
2308 | fNestedLoopsList->Add(fDiffFlowDirectCorrelations[t][pe][rci]); // to be improved (add dedicated list to hold reduced correlations) | |
2309 | } // end of for(Int_t rci=0;rci<4;rci++) // correlation index | |
2310 | } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta | |
2311 | } // end of for(Int_t t=0;t<2;t++) // type: RP or POI | |
2312 | // correction terms for non-uniform acceptance: | |
2313 | TString diffFlowDirectCorrectionTermsForNUAName = "fDiffFlowDirectCorrectionTermsForNUA"; | |
2314 | diffFlowDirectCorrectionTermsForNUAName += fAnalysisLabel->Data(); | |
2315 | for(Int_t t=0;t<2;t++) // typeFlag (0 = RP, 1 = POI) | |
2316 | { | |
2317 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
2318 | { | |
2319 | for(Int_t sc=0;sc<2;sc++) // sin or cos | |
2320 | { | |
2321 | for(Int_t cti=0;cti<9;cti++) // correction term index | |
2322 | { | |
2323 | fDiffFlowDirectCorrectionTermsForNUA[t][pe][sc][cti] = new TProfile(Form("%s, %s, %s, %s, cti = %d",diffFlowDirectCorrectionTermsForNUAName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),sinCosFlag[sc].Data(),cti+1),Form("%s, %s, %s, %s, cti = %d",diffFlowDirectCorrectionTermsForNUAName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),sinCosFlag[sc].Data(),cti+1),1,lowerPtEtaEdge[pe],upperPtEtaEdge[pe],"s"); | |
2324 | fNestedLoopsList->Add(fDiffFlowDirectCorrectionTermsForNUA[t][pe][sc][cti]); | |
2325 | } | |
2326 | } | |
2327 | } | |
3b552efe | 2328 | } |
2329 | // number of RPs and POIs in selected pt and eta bins for cross-checkings: | |
2330 | TString noOfParticlesInBinName = "fNoOfParticlesInBin"; | |
2331 | fNoOfParticlesInBin = new TH1D(noOfParticlesInBinName.Data(),"Number of RPs and POIs in selected p_{T} and #eta bin",4,0,4); | |
489d5531 | 2332 | fNoOfParticlesInBin->GetXaxis()->SetBinLabel(1,"# of RPs in p_{T} bin"); |
2333 | fNoOfParticlesInBin->GetXaxis()->SetBinLabel(2,"# of RPs in #eta bin"); | |
2334 | fNoOfParticlesInBin->GetXaxis()->SetBinLabel(3,"# of POIs in p_{T} bin"); | |
3b552efe | 2335 | fNoOfParticlesInBin->GetXaxis()->SetBinLabel(4,"# of POIs in #eta bin"); |
489d5531 | 2336 | fNestedLoopsList->Add(fNoOfParticlesInBin); |
2337 | } // end of if(fEvaluateDiffFlowNestedLoops) | |
2338 | ||
2339 | } // end of AliFlowAnalysisWithQCumulants::BookEverythingForNestedLoops() | |
2340 | ||
2341 | ||
2342 | //================================================================================================================================ | |
2343 | ||
2344 | ||
2345 | void AliFlowAnalysisWithQCumulants::CalculateIntFlowCorrelations() | |
2346 | { | |
2347 | // calculate all correlations needed for integrated flow | |
57340a27 | 2348 | |
489d5531 | 2349 | // multiplicity: |
2350 | Double_t dMult = (*fSMpk)(0,0); | |
57340a27 | 2351 | |
489d5531 | 2352 | // real and imaginary parts of non-weighted Q-vectors evaluated in harmonics n, 2n, 3n and 4n: |
2353 | Double_t dReQ1n = (*fReQ)(0,0); | |
2354 | Double_t dReQ2n = (*fReQ)(1,0); | |
2355 | Double_t dReQ3n = (*fReQ)(2,0); | |
2356 | Double_t dReQ4n = (*fReQ)(3,0); | |
8ed4edc7 | 2357 | //Double_t dReQ5n = (*fReQ)(4,0); |
2358 | Double_t dReQ6n = (*fReQ)(5,0); | |
489d5531 | 2359 | Double_t dImQ1n = (*fImQ)(0,0); |
2360 | Double_t dImQ2n = (*fImQ)(1,0); | |
2361 | Double_t dImQ3n = (*fImQ)(2,0); | |
2362 | Double_t dImQ4n = (*fImQ)(3,0); | |
8ed4edc7 | 2363 | //Double_t dImQ5n = (*fImQ)(4,0); |
2364 | Double_t dImQ6n = (*fImQ)(5,0); | |
489d5531 | 2365 | |
2366 | // real and imaginary parts of some expressions involving various combinations of Q-vectors evaluated in harmonics n, 2n, 3n and 4n: | |
2367 | // (these expression appear in the Eqs. for the multi-particle correlations bellow) | |
2368 | ||
2369 | // Re[Q_{2n} Q_{n}^* Q_{n}^*] | |
2370 | Double_t reQ2nQ1nstarQ1nstar = pow(dReQ1n,2.)*dReQ2n + 2.*dReQ1n*dImQ1n*dImQ2n - pow(dImQ1n,2.)*dReQ2n; | |
2371 | ||
2372 | // Im[Q_{2n} Q_{n}^* Q_{n}^*] | |
2373 | //Double_t imQ2nQ1nstarQ1nstar = pow(dReQ1n,2.)*dImQ2n-2.*dReQ1n*dImQ1n*dReQ2n-pow(dImQ1n,2.)*dImQ2n; | |
2374 | ||
2375 | // Re[Q_{n} Q_{n} Q_{2n}^*] = Re[Q_{2n} Q_{n}^* Q_{n}^*] | |
2376 | Double_t reQ1nQ1nQ2nstar = reQ2nQ1nstarQ1nstar; | |
2377 | ||
2378 | // Re[Q_{3n} Q_{n} Q_{2n}^* Q_{2n}^*] | |
2379 | Double_t reQ3nQ1nQ2nstarQ2nstar = (pow(dReQ2n,2.)-pow(dImQ2n,2.))*(dReQ3n*dReQ1n-dImQ3n*dImQ1n) | |
2380 | + 2.*dReQ2n*dImQ2n*(dReQ3n*dImQ1n+dImQ3n*dReQ1n); | |
2381 | ||
2382 | // Im[Q_{3n} Q_{n} Q_{2n}^* Q_{2n}^*] | |
2383 | //Double_t imQ3nQ1nQ2nstarQ2nstar = calculate and implement this (deleteMe) | |
2384 | ||
2385 | // Re[Q_{2n} Q_{2n} Q_{3n}^* Q_{1n}^*] = Re[Q_{3n} Q_{n} Q_{2n}^* Q_{2n}^*] | |
2386 | Double_t reQ2nQ2nQ3nstarQ1nstar = reQ3nQ1nQ2nstarQ2nstar; | |
2387 | ||
2388 | // Re[Q_{4n} Q_{2n}^* Q_{2n}^*] | |
2389 | Double_t reQ4nQ2nstarQ2nstar = pow(dReQ2n,2.)*dReQ4n+2.*dReQ2n*dImQ2n*dImQ4n-pow(dImQ2n,2.)*dReQ4n; | |
2390 | ||
2391 | // Im[Q_{4n} Q_{2n}^* Q_{2n}^*] | |
2392 | //Double_t imQ4nQ2nstarQ2nstar = calculate and implement this (deleteMe) | |
2393 | ||
2394 | // Re[Q_{2n} Q_{2n} Q_{4n}^*] = Re[Q_{4n} Q_{2n}^* Q_{2n}^*] | |
2395 | Double_t reQ2nQ2nQ4nstar = reQ4nQ2nstarQ2nstar; | |
2396 | ||
2397 | // Re[Q_{4n} Q_{3n}^* Q_{n}^*] | |
2398 | Double_t reQ4nQ3nstarQ1nstar = dReQ4n*(dReQ3n*dReQ1n-dImQ3n*dImQ1n)+dImQ4n*(dReQ3n*dImQ1n+dImQ3n*dReQ1n); | |
2399 | ||
2400 | // Re[Q_{3n} Q_{n} Q_{4n}^*] = Re[Q_{4n} Q_{3n}^* Q_{n}^*] | |
2401 | Double_t reQ3nQ1nQ4nstar = reQ4nQ3nstarQ1nstar; | |
2402 | ||
2403 | // Im[Q_{4n} Q_{3n}^* Q_{n}^*] | |
2404 | //Double_t imQ4nQ3nstarQ1nstar = calculate and implement this (deleteMe) | |
2405 | ||
2406 | // Re[Q_{3n} Q_{2n}^* Q_{n}^*] | |
2407 | Double_t reQ3nQ2nstarQ1nstar = dReQ3n*dReQ2n*dReQ1n-dReQ3n*dImQ2n*dImQ1n+dImQ3n*dReQ2n*dImQ1n | |
2408 | + dImQ3n*dImQ2n*dReQ1n; | |
2409 | ||
2410 | // Re[Q_{2n} Q_{n} Q_{3n}^*] = Re[Q_{3n} Q_{2n}^* Q_{n}^*] | |
2411 | Double_t reQ2nQ1nQ3nstar = reQ3nQ2nstarQ1nstar; | |
2412 | ||
2413 | // Im[Q_{3n} Q_{2n}^* Q_{n}^*] | |
2414 | //Double_t imQ3nQ2nstarQ1nstar; //calculate and implement this (deleteMe) | |
2415 | ||
2416 | // Re[Q_{3n} Q_{n}^* Q_{n}^* Q_{n}^*] | |
2417 | Double_t reQ3nQ1nstarQ1nstarQ1nstar = dReQ3n*pow(dReQ1n,3)-3.*dReQ1n*dReQ3n*pow(dImQ1n,2) | |
2418 | + 3.*dImQ1n*dImQ3n*pow(dReQ1n,2)-dImQ3n*pow(dImQ1n,3); | |
2419 | ||
2420 | // Im[Q_{3n} Q_{n}^* Q_{n}^* Q_{n}^*] | |
2421 | //Double_t imQ3nQ1nstarQ1nstarQ1nstar; //calculate and implement this (deleteMe) | |
2422 | ||
2423 | // |Q_{2n}|^2 |Q_{n}|^2 | |
2424 | Double_t dQ2nQ1nQ2nstarQ1nstar = (pow(dReQ2n,2.)+pow(dImQ2n,2.))*(pow(dReQ1n,2.)+pow(dImQ1n,2.)); | |
2425 | ||
2426 | // Re[Q_{4n} Q_{2n}^* Q_{n}^* Q_{n}^*] | |
2427 | Double_t reQ4nQ2nstarQ1nstarQ1nstar = (dReQ4n*dReQ2n+dImQ4n*dImQ2n)*(pow(dReQ1n,2)-pow(dImQ1n,2)) | |
2428 | + 2.*dReQ1n*dImQ1n*(dImQ4n*dReQ2n-dReQ4n*dImQ2n); | |
2429 | ||
2430 | // Im[Q_{4n} Q_{2n}^* Q_{n}^* Q_{n}^*] | |
2431 | //Double_t imQ4nQ2nstarQ1nstarQ1nstar; //calculate and implement this (deleteMe) | |
2432 | ||
2433 | // Re[Q_{2n} Q_{n} Q_{n}^* Q_{n}^* Q_{n}^*] | |
2434 | Double_t reQ2nQ1nQ1nstarQ1nstarQ1nstar = (dReQ2n*dReQ1n-dImQ2n*dImQ1n)*(pow(dReQ1n,3)-3.*dReQ1n*pow(dImQ1n,2)) | |
2435 | + (dReQ2n*dImQ1n+dReQ1n*dImQ2n)*(3.*dImQ1n*pow(dReQ1n,2)-pow(dImQ1n,3)); | |
2436 | ||
2437 | // Im[Q_{2n} Q_{n} Q_{n}^* Q_{n}^* Q_{n}^*] | |
2438 | //Double_t imQ2nQ1nQ1nstarQ1nstarQ1nstar; //calculate and implement this (deleteMe) | |
2439 | ||
2440 | // Re[Q_{2n} Q_{2n} Q_{2n}^* Q_{n}^* Q_{n}^*] | |
2441 | Double_t reQ2nQ2nQ2nstarQ1nstarQ1nstar = (pow(dReQ2n,2.)+pow(dImQ2n,2.)) | |
2442 | * (dReQ2n*(pow(dReQ1n,2.)-pow(dImQ1n,2.)) + 2.*dImQ2n*dReQ1n*dImQ1n); | |
2443 | ||
2444 | // Im[Q_{2n} Q_{2n} Q_{2n}^* Q_{n}^* Q_{n}^*] | |
2445 | //Double_t imQ2nQ2nQ2nstarQ1nstarQ1nstar = (pow(dReQ2n,2.)+pow(dImQ2n,2.)) | |
2446 | // * (dImQ2n*(pow(dReQ1n,2.)-pow(dImQ1n,2.)) - 2.*dReQ2n*dReQ1n*dImQ1n); | |
2447 | ||
2448 | // Re[Q_{4n} Q_{n}^* Q_{n}^* Q_{n}^* Q_{n}^*] | |
2449 | Double_t reQ4nQ1nstarQ1nstarQ1nstarQ1nstar = pow(dReQ1n,4.)*dReQ4n-6.*pow(dReQ1n,2.)*dReQ4n*pow(dImQ1n,2.) | |
2450 | + pow(dImQ1n,4.)*dReQ4n+4.*pow(dReQ1n,3.)*dImQ1n*dImQ4n | |
2451 | - 4.*pow(dImQ1n,3.)*dReQ1n*dImQ4n; | |
2452 | ||
2453 | // Im[Q_{4n} Q_{n}^* Q_{n}^* Q_{n}^* Q_{n}^*] | |
2454 | //Double_t imQ4nQ1nstarQ1nstarQ1nstarQ1nstar = pow(dReQ1n,4.)*dImQ4n-6.*pow(dReQ1n,2.)*dImQ4n*pow(dImQ1n,2.) | |
2455 | // + pow(dImQ1n,4.)*dImQ4n+4.*pow(dImQ1n,3.)*dReQ1n*dReQ4n | |
2456 | // - 4.*pow(dReQ1n,3.)*dImQ1n*dReQ4n; | |
2457 | ||
2458 | // Re[Q_{3n} Q_{n} Q_{2n}^* Q_{n}^* Q_{n}^*] | |
2459 | Double_t reQ3nQ1nQ2nstarQ1nstarQ1nstar = (pow(dReQ1n,2.)+pow(dImQ1n,2.)) | |
2460 | * (dReQ1n*dReQ2n*dReQ3n-dReQ3n*dImQ1n*dImQ2n+dReQ2n*dImQ1n*dImQ3n+dReQ1n*dImQ2n*dImQ3n); | |
2461 | ||
2462 | // Im[Q_{3n} Q_{n} Q_{2n}^* Q_{n}^* Q_{n}^*] | |
2463 | //Double_t imQ3nQ1nQ2nstarQ1nstarQ1nstar = (pow(dReQ1n,2.)+pow(dImQ1n,2.)) | |
2464 | // * (-dReQ2n*dReQ3n*dImQ1n-dReQ1n*dReQ3n*dImQ2n+dReQ1n*dReQ2n*dImQ3n-dImQ1n*dImQ2n*dImQ3n); | |
2465 | ||
2466 | ||
2467 | // Re[Q_{2n} Q_{2n} Q_{n}^* Q_{n}^* Q_{n}^* Q_{n}^*] | |
2468 | Double_t reQ2nQ2nQ1nstarQ1nstarQ1nstarQ1nstar = (pow(dReQ1n,2.)*dReQ2n-2.*dReQ1n*dReQ2n*dImQ1n-dReQ2n*pow(dImQ1n,2.) | |
2469 | + dImQ2n*pow(dReQ1n,2.)+2.*dReQ1n*dImQ1n*dImQ2n-pow(dImQ1n,2.)*dImQ2n) | |
2470 | * (pow(dReQ1n,2.)*dReQ2n+2.*dReQ1n*dReQ2n*dImQ1n-dReQ2n*pow(dImQ1n,2.) | |
2471 | - dImQ2n*pow(dReQ1n,2.)+2.*dReQ1n*dImQ1n*dImQ2n+pow(dImQ1n,2.)*dImQ2n); | |
2472 | ||
2473 | // Im[Q_{2n} Q_{2n} Q_{n}^* Q_{n}^* Q_{n}^* Q_{n}^*] | |
2474 | //Double_t imQ2nQ2nQ1nstarQ1nstarQ1nstarQ1nstar = 2.*(pow(dReQ1n,2.)*dReQ2n-dReQ2n*pow(dImQ1n,2.) | |
2475 | // + 2.*dReQ1n*dImQ1n*dImQ2n)*(pow(dReQ1n,2.)*dImQ2n | |
2476 | // - 2.*dReQ1n*dImQ1n*dReQ2n-pow(dImQ1n,2.)*dImQ2n); | |
2477 | ||
2478 | // Re[Q_{3n} Q_{n} Q_{n}^* Q_{n}^* Q_{n}^* Q_{n}^*] | |
2479 | Double_t reQ3nQ1nQ1nstarQ1nstarQ1nstarQ1nstar = (pow(dReQ1n,2.)+pow(dImQ1n,2.)) | |
2480 | * (pow(dReQ1n,3.)*dReQ3n-3.*dReQ1n*dReQ3n*pow(dImQ1n,2.) | |
2481 | + 3.*pow(dReQ1n,2.)*dImQ1n*dImQ3n-pow(dImQ1n,3.)*dImQ3n); | |
2482 | ||
2483 | // Im[Q_{3n} Q_{n} Q_{n}^* Q_{n}^* Q_{n}^* Q_{n}^*] | |
2484 | //Double_t imQ3nQ1nQ1nstarQ1nstarQ1nstarQ1nstar = (pow(dReQ1n,2.)+pow(dImQ1n,2.)) | |
2485 | // * (pow(dImQ1n,3.)*dReQ3n-3.*dImQ1n*dReQ3n*pow(dReQ1n,2.) | |
2486 | // - 3.*pow(dImQ1n,2.)*dReQ1n*dImQ3n+pow(dReQ1n,3.)*dImQ3n); | |
2487 | ||
2488 | // |Q_{2n}|^2 |Q_{n}|^4 | |
2489 | Double_t dQ2nQ1nQ1nQ2nstarQ1nstarQ1nstar = (pow(dReQ2n,2.)+pow(dImQ2n,2.))*pow((pow(dReQ1n,2.)+pow(dImQ1n,2.)),2.); | |
2490 | ||
2491 | // Re[Q_{2n} Q_{n} Q_{n} Q_{n}^* Q_{n}^* Q_{n}^* Q_{n}^*] | |
2492 | Double_t reQ2nQ1nQ1nQ1nstarQ1nstarQ1nstarQ1nstar = pow((pow(dReQ1n,2.)+pow(dImQ1n,2.)),2.) | |
2493 | * (pow(dReQ1n,2.)*dReQ2n-dReQ2n*pow(dImQ1n,2.) | |
2494 | + 2.*dReQ1n*dImQ1n*dImQ2n); | |
2495 | ||
2496 | // Im[Q_{2n} Q_{n} Q_{n} Q_{n}^* Q_{n}^* Q_{n}^* Q_{n}^*] | |
2497 | //Double_t imQ2nQ1nQ1nQ1nstarQ1nstarQ1nstarQ1nstar = pow((pow(dReQ1n,2.)+pow(dImQ1n,2.)),2.) | |
2498 | // * (pow(dReQ1n,2.)*dImQ2n-dImQ2n*pow(dImQ1n,2.) | |
2499 | // - 2.*dReQ1n*dReQ2n*dImQ1n); | |
2500 | ||
2501 | ||
2502 | ||
2503 | ||
2504 | // ************************************** | |
2505 | // **** multi-particle correlations: **** | |
2506 | // ************************************** | |
2507 | // | |
8ed4edc7 | 2508 | // Remark 1: All multi-particle correlations calculated with non-weighted Q-vectors are stored in 1D profile fIntFlowCorrelationsAllPro; |
2509 | // Remark 2: There is a special profile fIntFlowCorrelationsPro holding results ONLY for same harmonic's <<2>>, <<4>>, <<6>> and <<8>>; | |
2510 | // Remark 3: Binning of fIntFlowCorrelationsAllPro is organized as follows: | |
489d5531 | 2511 | // -------------------------------------------------------------------------------------------------------------------- |
2512 | // 1st bin: <2>_{1n|1n} = two1n1n = cos(n*(phi1-phi2))> | |
2513 | // 2nd bin: <2>_{2n|2n} = two2n2n = cos(2n*(phi1-phi2))> | |
2514 | // 3rd bin: <2>_{3n|3n} = two3n3n = cos(3n*(phi1-phi2))> | |
2515 | // 4th bin: <2>_{4n|4n} = two4n4n = cos(4n*(phi1-phi2))> | |
2516 | // 5th bin: ---- EMPTY ---- | |
2517 | // 6th bin: <3>_{2n|1n,1n} = three2n1n1n = <cos(n*(2.*phi1-phi2-phi3))> | |
2518 | // 7th bin: <3>_{3n|2n,1n} = three3n2n1n = <cos(n*(3.*phi1-2.*phi2-phi3))> | |
2519 | // 8th bin: <3>_{4n|2n,2n} = three4n2n2n = <cos(n*(4.*phi1-2.*phi2-2.*phi3))> | |
2520 | // 9th bin: <3>_{4n|3n,1n} = three4n3n1n = <cos(n*(4.*phi1-3.*phi2-phi3))> | |
2521 | // 10th bin: ---- EMPTY ---- | |
2522 | // 11th bin: <4>_{1n,1n|1n,1n} = four1n1n1n1n = <cos(n*(phi1+phi2-phi3-phi4))> | |
2523 | // 12th bin: <4>_{2n,1n|2n,1n} = four2n1n2n1n = <cos(2.*n*(phi1+phi2-phi3-phi4))> | |
2524 | // 13th bin: <4>_{2n,2n|2n,2n} = four2n2n2n2n = <cos(n*(2.*phi1+phi2-2.*phi3-phi4))> | |
2525 | // 14th bin: <4>_{3n|1n,1n,1n} = four3n1n1n1n = <cos(n*(3.*phi1-phi2-phi3-phi4))> | |
2526 | // 15th bin: <4>_{3n,1n|3n,1n} = four3n1n3n1n = <cos(n*(4.*phi1-2.*phi2-phi3-phi4))> | |
2527 | // 16th bin: <4>_{3n,1n|2n,2n} = four3n1n2n2n = <cos(n*(3.*phi1+phi2-2.*phi3-2.*phi4))> | |
2528 | // 17th bin: <4>_{4n|2n,1n,1n} = four4n2n1n1n = <cos(n*(3.*phi1+phi2-3.*phi3-phi4))> | |
2529 | // 18th bin: ---- EMPTY ---- | |
2530 | // 19th bin: <5>_{2n|1n,1n,1n,1n} = five2n1n1n1n1n = <cos(n*(2.*phi1+phi2-phi3-phi4-phi5))> | |
2531 | // 20th bin: <5>_{2n,2n|2n,1n,1n} = five2n2n2n1n1n = <cos(n*(2.*phi1+2.*phi2-2.*phi3-phi4-phi5))> | |
2532 | // 21st bin: <5>_{3n,1n|2n,1n,1n} = five3n1n2n1n1n = <cos(n*(3.*phi1+phi2-2.*phi3-phi4-phi5))> | |
2533 | // 22nd bin: <5>_{4n|1n,1n,1n,1n} = five4n1n1n1n1n = <cos(n*(4.*phi1-phi2-phi3-phi4-phi5))> | |
2534 | // 23rd bin: ---- EMPTY ---- | |
2535 | // 24th bin: <6>_{1n,1n,1n|1n,1n,1n} = six1n1n1n1n1n1n = <cos(n*(phi1+phi2+phi3-phi4-phi5-phi6))> | |
2536 | // 25th bin: <6>_{2n,1n,1n|2n,1n,1n} = six2n1n1n2n1n1n = <cos(n*(2.*phi1+2.*phi2-phi3-phi4-phi5-phi6))> | |
2537 | // 26th bin: <6>_{2n,2n|1n,1n,1n,1n} = six2n2n1n1n1n1n = <cos(n*(3.*phi1+phi2-phi3-phi4-phi5-phi6))> | |
2538 | // 27th bin: <6>_{3n,1n|1n,1n,1n,1n} = six3n1n1n1n1n1n = <cos(n*(2.*phi1+phi2+phi3-2.*phi4-phi5-phi6))> | |
2539 | // 28th bin: ---- EMPTY ---- | |
2540 | // 29th bin: <7>_{2n,1n,1n|1n,1n,1n,1n} = seven2n1n1n1n1n1n1n = <cos(n*(2.*phi1+phi2+phi3-phi4-phi5-phi6-phi7))> | |
2541 | // 30th bin: ---- EMPTY ---- | |
2542 | // 31st bin: <8>_{1n,1n,1n,1n|1n,1n,1n,1n} = eight1n1n1n1n1n1n1n1n = <cos(n*(phi1+phi2+phi3+phi4-phi5-phi6-phi7-phi8))> | |
8ed4edc7 | 2543 | // 32nd bin: ---- EMPTY ---- |
2544 | // 33rd bin: <4>_{4n,2n|3n,3n}= four4n2n3n3n = <cos(n*(4.*phi1+2.*phi2-3.*phi3-3.*phi4))> | |
2545 | // 34th bin: <5>_{2n,2n,2n|3n,3n} = five2n2n2n3n3n = <cos(n*(2.*phi1+2.*phi2+2.*phi3-3.*phi4-3.*phi5))> | |
489d5531 | 2546 | // -------------------------------------------------------------------------------------------------------------------- |
2547 | ||
2548 | // 2-particle: | |
2549 | Double_t two1n1n = 0.; // <cos(n*(phi1-phi2))> | |
2550 | Double_t two2n2n = 0.; // <cos(2n*(phi1-phi2))> | |
2551 | Double_t two3n3n = 0.; // <cos(3n*(phi1-phi2))> | |
2552 | Double_t two4n4n = 0.; // <cos(4n*(phi1-phi2))> | |
2553 | ||
2554 | if(dMult>1) | |
2555 | { | |
2556 | two1n1n = (pow(dReQ1n,2.)+pow(dImQ1n,2.)-dMult)/(dMult*(dMult-1.)); | |
2557 | two2n2n = (pow(dReQ2n,2.)+pow(dImQ2n,2.)-dMult)/(dMult*(dMult-1.)); | |
2558 | two3n3n = (pow(dReQ3n,2.)+pow(dImQ3n,2.)-dMult)/(dMult*(dMult-1.)); | |
2559 | two4n4n = (pow(dReQ4n,2.)+pow(dImQ4n,2.)-dMult)/(dMult*(dMult-1.)); | |
2560 | ||
2561 | // average 2-particle correlations for single event: | |
2562 | fIntFlowCorrelationsAllEBE->SetBinContent(1,two1n1n); | |
2563 | fIntFlowCorrelationsAllEBE->SetBinContent(2,two2n2n); | |
2564 | fIntFlowCorrelationsAllEBE->SetBinContent(3,two3n3n); | |
2565 | fIntFlowCorrelationsAllEBE->SetBinContent(4,two4n4n); | |
2566 | ||
2567 | // average 2-particle correlations for all events: | |
2568 | fIntFlowCorrelationsAllPro->Fill(0.5,two1n1n,dMult*(dMult-1.)); | |
2569 | fIntFlowCorrelationsAllPro->Fill(1.5,two2n2n,dMult*(dMult-1.)); | |
2570 | fIntFlowCorrelationsAllPro->Fill(2.5,two3n3n,dMult*(dMult-1.)); | |
2571 | fIntFlowCorrelationsAllPro->Fill(3.5,two4n4n,dMult*(dMult-1.)); | |
2572 | ||
2573 | // store separetately <2> (to be improved: do I really need this?) | |
2574 | fIntFlowCorrelationsEBE->SetBinContent(1,two1n1n); // <2> | |
2575 | ||
2576 | // to be improved (this can be implemented better): | |
2577 | Double_t mWeight2p = 0.; | |
2578 | if(!strcmp(fMultiplicityWeight->Data(),"combinations")) | |
2579 | { | |
2580 | mWeight2p = dMult*(dMult-1.); | |
2581 | } else if(!strcmp(fMultiplicityWeight->Data(),"unit")) | |
2582 | { | |
2583 | mWeight2p = 1.; | |
2584 | } else if(!strcmp(fMultiplicityWeight->Data(),"multiplicity")) | |
2585 | { | |
2586 | mWeight2p = dMult; | |
2587 | } | |
2588 | ||
2589 | fIntFlowEventWeightsForCorrelationsEBE->SetBinContent(1,mWeight2p); // eW_<2> | |
2590 | fIntFlowCorrelationsPro->Fill(0.5,two1n1n,mWeight2p); | |
b40a910e | 2591 | fIntFlowSquaredCorrelationsPro->Fill(0.5,two1n1n*two1n1n,mWeight2p); |
2592 | if(fCalculateCumulantsVsM) | |
2593 | { | |
2594 | fIntFlowCorrelationsVsMPro[0]->Fill(dMult+0.5,two1n1n,mWeight2p); | |
2595 | fIntFlowSquaredCorrelationsVsMPro[0]->Fill(dMult+0.5,two1n1n*two1n1n,mWeight2p); | |
2596 | } | |
489d5531 | 2597 | // distribution of <cos(n*(phi1-phi2))>: |
2598 | //f2pDistribution->Fill(two1n1n,dMult*(dMult-1.)); | |
2599 | } // end of if(dMult>1) | |
2600 | ||
2601 | // 3-particle: | |
2602 | Double_t three2n1n1n = 0.; // <cos(n*(2.*phi1-phi2-phi3))> | |
2603 | Double_t three3n2n1n = 0.; // <cos(n*(3.*phi1-2.*phi2-phi3))> | |
2604 | Double_t three4n2n2n = 0.; // <cos(n*(4.*phi1-2.*phi2-2.*phi3))> | |
2605 | Double_t three4n3n1n = 0.; // <cos(n*(4.*phi1-3.*phi2-phi3))> | |
2606 | ||
2607 | if(dMult>2) | |
2608 | { | |
2609 | three2n1n1n = (reQ2nQ1nstarQ1nstar-2.*(pow(dReQ1n,2.)+pow(dImQ1n,2.)) | |
2610 | - (pow(dReQ2n,2.)+pow(dImQ2n,2.))+2.*dMult) | |
2611 | / (dMult*(dMult-1.)*(dMult-2.)); | |
2612 | three3n2n1n = (reQ3nQ2nstarQ1nstar-(pow(dReQ3n,2.)+pow(dImQ3n,2.)) | |
2613 | - (pow(dReQ2n,2.)+pow(dImQ2n,2.)) | |
2614 | - (pow(dReQ1n,2.)+pow(dImQ1n,2.))+2.*dMult) | |
2615 | / (dMult*(dMult-1.)*(dMult-2.)); | |
2616 | three4n2n2n = (reQ4nQ2nstarQ2nstar-2.*(pow(dReQ2n,2.)+pow(dImQ2n,2.)) | |
2617 | - (pow(dReQ4n,2.)+pow(dImQ4n,2.))+2.*dMult) | |
2618 | / (dMult*(dMult-1.)*(dMult-2.)); | |
2619 | three4n3n1n = (reQ4nQ3nstarQ1nstar-(pow(dReQ4n,2.)+pow(dImQ4n,2.)) | |
2620 | - (pow(dReQ3n,2.)+pow(dImQ3n,2.)) | |
2621 | - (pow(dReQ1n,2.)+pow(dImQ1n,2.))+2.*dMult) | |
2622 | / (dMult*(dMult-1.)*(dMult-2.)); | |
2623 | ||
2624 | // average 3-particle correlations for single event: | |
2625 | fIntFlowCorrelationsAllEBE->SetBinContent(6,three2n1n1n); | |
2626 | fIntFlowCorrelationsAllEBE->SetBinContent(7,three3n2n1n); | |
2627 | fIntFlowCorrelationsAllEBE->SetBinContent(8,three4n2n2n); | |
2628 | fIntFlowCorrelationsAllEBE->SetBinContent(9,three4n3n1n); | |
2629 | ||
2630 | // average 3-particle correlations for all events: | |
2631 | fIntFlowCorrelationsAllPro->Fill(5.5,three2n1n1n,dMult*(dMult-1.)*(dMult-2.)); | |
2632 | fIntFlowCorrelationsAllPro->Fill(6.5,three3n2n1n,dMult*(dMult-1.)*(dMult-2.)); | |
2633 | fIntFlowCorrelationsAllPro->Fill(7.5,three4n2n2n,dMult*(dMult-1.)*(dMult-2.)); | |
2634 | fIntFlowCorrelationsAllPro->Fill(8.5,three4n3n1n,dMult*(dMult-1.)*(dMult-2.)); | |
2635 | } // end of if(dMult>2) | |
2636 | ||
2637 | // 4-particle: | |
2638 | Double_t four1n1n1n1n = 0.; // <cos(n*(phi1+phi2-phi3-phi4))> | |
2639 | Double_t four2n2n2n2n = 0.; // <cos(2.*n*(phi1+phi2-phi3-phi4))> | |
2640 | Double_t four2n1n2n1n = 0.; // <cos(n*(2.*phi1+phi2-2.*phi3-phi4))> | |
2641 | Double_t four3n1n1n1n = 0.; // <cos(n*(3.*phi1-phi2-phi3-phi4))> | |
2642 | Double_t four4n2n1n1n = 0.; // <cos(n*(4.*phi1-2.*phi2-phi3-phi4))> | |
2643 | Double_t four3n1n2n2n = 0.; // <cos(n*(3.*phi1+phi2-2.*phi3-2.*phi4))> | |
2644 | Double_t four3n1n3n1n = 0.; // <cos(n*(3.*phi1+phi2-3.*phi3-phi4))> | |
2645 | ||
2646 | if(dMult>3) | |
2647 | { | |
2648 | four1n1n1n1n = (2.*dMult*(dMult-3.)+pow((pow(dReQ1n,2.)+pow(dImQ1n,2.)),2.)-4.*(dMult-2.)*(pow(dReQ1n,2.) | |
2649 | + pow(dImQ1n,2.))-2.*reQ2nQ1nstarQ1nstar+(pow(dReQ2n,2.)+pow(dImQ2n,2.))) | |
2650 | / (dMult*(dMult-1)*(dMult-2.)*(dMult-3.)); | |
2651 | four2n2n2n2n = (2.*dMult*(dMult-3.)+pow((pow(dReQ2n,2.)+pow(dImQ2n,2.)),2.)-4.*(dMult-2.)*(pow(dReQ2n,2.) | |
2652 | + pow(dImQ2n,2.))-2.*reQ4nQ2nstarQ2nstar+(pow(dReQ4n,2.)+pow(dImQ4n,2.))) | |
2653 | / (dMult*(dMult-1)*(dMult-2.)*(dMult-3.)); | |
2654 | four2n1n2n1n = (dQ2nQ1nQ2nstarQ1nstar-2.*reQ3nQ2nstarQ1nstar-2.*reQ2nQ1nstarQ1nstar) | |
2655 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)) | |
2656 | - ((dMult-5.)*(pow(dReQ1n,2.)+pow(dImQ1n,2.)) | |
2657 | + (dMult-4.)*(pow(dReQ2n,2.)+pow(dImQ2n,2.))-(pow(dReQ3n,2.)+pow(dImQ3n,2.))) | |
2658 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)) | |
2659 | + (dMult-6.)/((dMult-1.)*(dMult-2.)*(dMult-3.)); | |
2660 | four3n1n1n1n = (reQ3nQ1nstarQ1nstarQ1nstar-3.*reQ3nQ2nstarQ1nstar-3.*reQ2nQ1nstarQ1nstar) | |
2661 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)) | |
2662 | + (2.*(pow(dReQ3n,2.)+pow(dImQ3n,2.))+3.*(pow(dReQ2n,2.)+pow(dImQ2n,2.)) | |
2663 | + 6.*(pow(dReQ1n,2.)+pow(dImQ1n,2.))-6.*dMult) | |
2664 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)); | |
2665 | four4n2n1n1n = (reQ4nQ2nstarQ1nstarQ1nstar-2.*reQ4nQ3nstarQ1nstar-reQ4nQ2nstarQ2nstar-2.*reQ3nQ2nstarQ1nstar) | |
2666 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)) | |
2667 | - (reQ2nQ1nstarQ1nstar-2.*(pow(dReQ4n,2.)+pow(dImQ4n,2.))-2.*(pow(dReQ3n,2.)+pow(dImQ3n,2.)) | |
2668 | - 3.*(pow(dReQ2n,2.)+pow(dImQ2n,2.))-4.*(pow(dReQ1n,2.)+pow(dImQ1n,2.))) | |
2669 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)) | |
2670 | - 6./((dMult-1.)*(dMult-2.)*(dMult-3.)); | |
2671 | four3n1n2n2n = (reQ3nQ1nQ2nstarQ2nstar-reQ4nQ2nstarQ2nstar-reQ3nQ1nQ4nstar-2.*reQ3nQ2nstarQ1nstar) | |
2672 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)) | |
2673 | - (2.*reQ1nQ1nQ2nstar-(pow(dReQ4n,2.)+pow(dImQ4n,2.))-2.*(pow(dReQ3n,2.)+pow(dImQ3n,2.)) | |
2674 | - 4.*(pow(dReQ2n,2.)+pow(dImQ2n,2.))-4.*(pow(dReQ1n,2.)+pow(dImQ1n,2.))) | |
2675 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)) | |
2676 | - 6./((dMult-1.)*(dMult-2.)*(dMult-3.)); | |
2677 | four3n1n3n1n = ((pow(dReQ3n,2.)+pow(dImQ3n,2.))*(pow(dReQ1n,2.)+pow(dImQ1n,2.)) | |
2678 | - 2.*reQ4nQ3nstarQ1nstar-2.*reQ3nQ2nstarQ1nstar) | |
2679 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)) | |
2680 | + ((pow(dReQ4n,2.)+pow(dImQ4n,2.))-(dMult-4.)*(pow(dReQ3n,2.)+pow(dImQ3n,2.)) | |
2681 | + (pow(dReQ2n,2.)+pow(dImQ2n,2.))-(dMult-4.)*(pow(dReQ1n,2.)+pow(dImQ1n,2.))) | |
2682 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)) | |
2683 | + (dMult-6.)/((dMult-1.)*(dMult-2.)*(dMult-3.)); | |
2684 | ||
2685 | // average 4-particle correlations for single event: | |
2686 | fIntFlowCorrelationsAllEBE->SetBinContent(11,four1n1n1n1n); | |
2687 | fIntFlowCorrelationsAllEBE->SetBinContent(12,four2n1n2n1n); | |
2688 | fIntFlowCorrelationsAllEBE->SetBinContent(13,four2n2n2n2n); | |
2689 | fIntFlowCorrelationsAllEBE->SetBinContent(14,four3n1n1n1n); | |
2690 | fIntFlowCorrelationsAllEBE->SetBinContent(15,four3n1n3n1n); | |
2691 | fIntFlowCorrelationsAllEBE->SetBinContent(16,four3n1n2n2n); | |
2692 | fIntFlowCorrelationsAllEBE->SetBinContent(17,four4n2n1n1n); | |
2693 | ||
2694 | // average 4-particle correlations for all events: | |
2695 | fIntFlowCorrelationsAllPro->Fill(10.5,four1n1n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)); | |
2696 | fIntFlowCorrelationsAllPro->Fill(11.5,four2n1n2n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)); | |
2697 | fIntFlowCorrelationsAllPro->Fill(12.5,four2n2n2n2n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)); | |
2698 | fIntFlowCorrelationsAllPro->Fill(13.5,four3n1n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)); | |
2699 | fIntFlowCorrelationsAllPro->Fill(14.5,four3n1n3n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)); | |
2700 | fIntFlowCorrelationsAllPro->Fill(15.5,four3n1n2n2n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)); | |
2701 | fIntFlowCorrelationsAllPro->Fill(16.5,four4n2n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)); | |
2702 | ||
2703 | // store separetately <4> (to be improved: do I really need this?) | |
2704 | fIntFlowCorrelationsEBE->SetBinContent(2,four1n1n1n1n); // <4> | |
2705 | ||
2706 | // to be improved (this can be implemented better): | |
2707 | Double_t mWeight4p = 0.; | |
2708 | if(!strcmp(fMultiplicityWeight->Data(),"combinations")) | |
2709 | { | |
2710 | mWeight4p = dMult*(dMult-1.)*(dMult-2.)*(dMult-3.); | |
2711 | } else if(!strcmp(fMultiplicityWeight->Data(),"unit")) | |
2712 | { | |
2713 | mWeight4p = 1.; | |
2714 | } else if(!strcmp(fMultiplicityWeight->Data(),"multiplicity")) | |
2715 | { | |
2716 | mWeight4p = dMult; | |
2717 | } | |
2718 | ||
2719 | fIntFlowEventWeightsForCorrelationsEBE->SetBinContent(2,mWeight4p); // eW_<4> | |
2720 | fIntFlowCorrelationsPro->Fill(1.5,four1n1n1n1n,mWeight4p); | |
b40a910e | 2721 | fIntFlowSquaredCorrelationsPro->Fill(1.5,four1n1n1n1n*four1n1n1n1n,mWeight4p); |
2722 | if(fCalculateCumulantsVsM) | |
2723 | { | |
2724 | fIntFlowCorrelationsVsMPro[1]->Fill(dMult+0.5,four1n1n1n1n,mWeight4p); | |
2725 | fIntFlowSquaredCorrelationsVsMPro[1]->Fill(dMult+0.5,four1n1n1n1n*four1n1n1n1n,mWeight4p); | |
2726 | } | |
489d5531 | 2727 | // distribution of <cos(n*(phi1+phi2-phi3-phi4))> |
2728 | //f4pDistribution->Fill(four1n1n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)); | |
2729 | ||
2730 | } // end of if(dMult>3) | |
2731 | ||
2732 | // 5-particle: | |
2733 | Double_t five2n1n1n1n1n = 0.; // <cos(n*(2.*phi1+phi2-phi3-phi4-phi5))> | |
2734 | Double_t five2n2n2n1n1n = 0.; // <cos(n*(2.*phi1+2.*phi2-2.*phi3-phi4-phi5))> | |
2735 | Double_t five3n1n2n1n1n = 0.; // <cos(n*(3.*phi1+phi2-2.*phi3-phi4-phi5))> | |
2736 | Double_t five4n1n1n1n1n = 0.; // <cos(n*(4.*phi1-phi2-phi3-phi4-phi5))> | |
2737 | ||
2738 | if(dMult>4) | |
2739 | { | |
2740 | five2n1n1n1n1n = (reQ2nQ1nQ1nstarQ1nstarQ1nstar-reQ3nQ1nstarQ1nstarQ1nstar+6.*reQ3nQ2nstarQ1nstar) | |
2741 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) | |
2742 | - (reQ2nQ1nQ3nstar+3.*(dMult-6.)*reQ2nQ1nstarQ1nstar+3.*reQ1nQ1nQ2nstar) | |
2743 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) | |
2744 | - (2.*(pow(dReQ3n,2.)+pow(dImQ3n,2.)) | |
2745 | + 3.*(pow(dReQ1n,2.)+pow(dImQ1n,2.))*(pow(dReQ2n,2.)+pow(dImQ2n,2.)) | |
2746 | - 3.*(dMult-4.)*(pow(dReQ2n,2.)+pow(dImQ2n,2.))) | |
2747 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) | |
2748 | - 3.*(pow((pow(dReQ1n,2.)+pow(dImQ1n,2.)),2.) | |
2749 | - 2.*(2*dMult-5.)*(pow(dReQ1n,2.)+pow(dImQ1n,2.))+2.*dMult*(dMult-4.)) | |
2750 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)); | |
2751 | ||
2752 | five2n2n2n1n1n = (reQ2nQ2nQ2nstarQ1nstarQ1nstar-reQ4nQ2nstarQ1nstarQ1nstar-2.*reQ2nQ2nQ3nstarQ1nstar) | |
2753 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) | |
2754 | + 2.*(reQ4nQ2nstarQ2nstar+4.*reQ3nQ2nstarQ1nstar+reQ3nQ1nQ4nstar) | |
2755 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) | |
2756 | + (reQ2nQ2nQ4nstar-2.*(dMult-5.)*reQ2nQ1nstarQ1nstar+2.*reQ1nQ1nQ2nstar) | |
2757 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) | |
2758 | - (2.*(pow(dReQ4n,2.)+pow(dImQ4n,2.))+4.*(pow(dReQ3n,2.)+pow(dImQ3n,2.)) | |
2759 | + 1.*pow((pow(dReQ2n,2.)+pow(dImQ2n,2.)),2.) | |
2760 | - 2.*(3.*dMult-10.)*(pow(dReQ2n,2.)+pow(dImQ2n,2.))) | |
2761 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) | |
2762 | - (4.*(pow(dReQ1n,2.)+pow(dImQ1n,2.))*(pow(dReQ2n,2.)+pow(dImQ2n,2.)) | |
2763 | - 4.*(dMult-5.)*(pow(dReQ1n,2.)+pow(dImQ1n,2.))+4.*dMult*(dMult-6.)) | |
2764 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)); | |
2765 | ||
2766 | five4n1n1n1n1n = (reQ4nQ1nstarQ1nstarQ1nstarQ1nstar-6.*reQ4nQ2nstarQ1nstarQ1nstar-4.*reQ3nQ1nstarQ1nstarQ1nstar) | |
2767 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) | |
2768 | + (8.*reQ4nQ3nstarQ1nstar+3.*reQ4nQ2nstarQ2nstar+12.*reQ3nQ2nstarQ1nstar+12.*reQ2nQ1nstarQ1nstar) | |
2769 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) | |
2770 | - (6.*(pow(dReQ4n,2.)+pow(dImQ4n,2.))+8.*(pow(dReQ3n,2.)+pow(dImQ3n,2.)) | |
2771 | + 12.*(pow(dReQ2n,2.)+pow(dImQ2n,2.))+24.*(pow(dReQ1n,2.)+pow(dImQ1n,2.))-24.*dMult) | |
2772 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)); | |
2773 | ||
2774 | five3n1n2n1n1n = (reQ3nQ1nQ2nstarQ1nstarQ1nstar-reQ4nQ2nstarQ1nstarQ1nstar-reQ3nQ1nstarQ1nstarQ1nstar) | |
2775 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) | |
2776 | - (reQ3nQ1nQ2nstarQ2nstar-3.*reQ4nQ3nstarQ1nstar-reQ4nQ2nstarQ2nstar) | |
2777 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) | |
2778 | - ((2.*dMult-13.)*reQ3nQ2nstarQ1nstar-reQ3nQ1nQ4nstar-9.*reQ2nQ1nstarQ1nstar) | |
2779 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) | |
2780 | - (2.*reQ1nQ1nQ2nstar+2.*(pow(dReQ4n,2.)+pow(dImQ4n,2.)) | |
2781 | - 2.*(dMult-5.)*(pow(dReQ3n,2.)+pow(dImQ3n,2.))+2.*(pow(dReQ3n,2.) | |
2782 | + pow(dImQ3n,2.))*(pow(dReQ1n,2.)+pow(dImQ1n,2.))) | |
2783 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) | |
2784 | + (2.*(dMult-6.)*(pow(dReQ2n,2.)+pow(dImQ2n,2.)) | |
2785 | - 2.*(pow(dReQ2n,2.)+pow(dImQ2n,2.))*(pow(dReQ1n,2.)+pow(dImQ1n,2.)) | |
2786 | - pow((pow(dReQ1n,2.)+pow(dImQ1n,2.)),2.) | |
2787 | + 2.*(3.*dMult-11.)*(pow(dReQ1n,2.)+pow(dImQ1n,2.))) | |
2788 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) | |
2789 | - 4.*(dMult-6.)/((dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)); | |
2790 | ||
2791 | // average 5-particle correlations for single event: | |
2792 | fIntFlowCorrelationsAllEBE->SetBinContent(19,five2n1n1n1n1n); | |
2793 | fIntFlowCorrelationsAllEBE->SetBinContent(20,five2n2n2n1n1n); | |
2794 | fIntFlowCorrelationsAllEBE->SetBinContent(21,five3n1n2n1n1n); | |
2795 | fIntFlowCorrelationsAllEBE->SetBinContent(22,five4n1n1n1n1n); | |
2796 | ||
2797 | // average 5-particle correlations for all events: | |
2798 | fIntFlowCorrelationsAllPro->Fill(18.5,five2n1n1n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)); | |
2799 | fIntFlowCorrelationsAllPro->Fill(19.5,five2n2n2n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)); | |
2800 | fIntFlowCorrelationsAllPro->Fill(20.5,five3n1n2n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)); | |
2801 | fIntFlowCorrelationsAllPro->Fill(21.5,five4n1n1n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)); | |
2802 | } // end of if(dMult>4) | |
2803 | ||
2804 | // 6-particle: | |
2805 | Double_t six1n1n1n1n1n1n = 0.; // <cos(n*(phi1+phi2+phi3-phi4-phi5-phi6))> | |
2806 | Double_t six2n2n1n1n1n1n = 0.; // <cos(n*(2.*phi1+2.*phi2-phi3-phi4-phi5-phi6))> | |
2807 | Double_t six3n1n1n1n1n1n = 0.; // <cos(n*(3.*phi1+phi2-phi3-phi4-phi5-phi6))> | |
2808 | Double_t six2n1n1n2n1n1n = 0.; // <cos(n*(2.*phi1+phi2+phi3-2.*phi4-phi5-phi6))> | |
2809 | ||
2810 | if(dMult>5) | |
2811 | { | |
2812 | six1n1n1n1n1n1n = (pow(pow(dReQ1n,2.)+pow(dImQ1n,2.),3.)+9.*dQ2nQ1nQ2nstarQ1nstar-6.*reQ2nQ1nQ1nstarQ1nstarQ1nstar) | |
2813 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)) | |
2814 | + 4.*(reQ3nQ1nstarQ1nstarQ1nstar-3.*reQ3nQ2nstarQ1nstar) | |
2815 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)) | |
2816 | + 2.*(9.*(dMult-4.)*reQ2nQ1nstarQ1nstar+2.*(pow(dReQ3n,2.)+pow(dImQ3n,2.))) | |
2817 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)) | |
2818 | - 9.*(pow((pow(dReQ1n,2.)+pow(dImQ1n,2.)),2.)+(pow(dReQ2n,2.)+pow(dImQ2n,2.))) | |
2819 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-5.)) | |
2820 | + (18.*(pow(dReQ1n,2.)+pow(dImQ1n,2.))) | |
2821 | / (dMult*(dMult-1)*(dMult-3)*(dMult-4)) | |
2822 | - 6./((dMult-1.)*(dMult-2.)*(dMult-3.)); | |
2823 | ||
2824 | six2n1n1n2n1n1n = (dQ2nQ1nQ1nQ2nstarQ1nstarQ1nstar-dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.) | |
2825 | * (2.*five2n2n2n1n1n+4.*five2n1n1n1n1n+4.*five3n1n2n1n1n+4.*four2n1n2n1n+1.*four1n1n1n1n) | |
2826 | - dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(4.*four1n1n1n1n+4.*two1n1n | |
2827 | + 2.*three2n1n1n+2.*three2n1n1n+4.*four3n1n1n1n+8.*three2n1n1n+2.*four4n2n1n1n | |
2828 | + 4.*four2n1n2n1n+2.*two2n2n+8.*four2n1n2n1n+4.*four3n1n3n1n+8.*three3n2n1n | |
2829 | + 4.*four3n1n2n2n+4.*four1n1n1n1n+4.*four2n1n2n1n+1.*four2n2n2n2n) | |
2830 | - dMult*(dMult-1.)*(dMult-2.)*(2.*three2n1n1n+8.*two1n1n+4.*two1n1n+2. | |
2831 | + 4.*two1n1n+4.*three2n1n1n+2.*two2n2n+4.*three2n1n1n+8.*three3n2n1n | |
2832 | + 8.*two2n2n+4.*three4n3n1n+4.*two3n3n+4.*three3n2n1n+4.*two1n1n | |
2833 | + 8.*three2n1n1n+4.*two1n1n+4.*three3n2n1n+4.*three2n1n1n+2.*two2n2n | |
2834 | + 4.*three3n2n1n+2.*three4n2n2n)-dMult*(dMult-1.) | |
2835 | * (4.*two1n1n+4.+4.*two1n1n+2.*two2n2n+1.+4.*two1n1n+4.*two2n2n+4.*two3n3n | |
2836 | + 1.+2.*two2n2n+1.*two4n4n)-dMult) | |
2837 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)); // to be improved (direct formula needed) | |
2838 | ||
2839 | six2n2n1n1n1n1n = (reQ2nQ2nQ1nstarQ1nstarQ1nstarQ1nstar-dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.) | |
2840 | * (five4n1n1n1n1n+8.*five2n1n1n1n1n+6.*five2n2n2n1n1n)-dMult*(dMult-1.)*(dMult-2.)*(dMult-3.) | |
2841 | * (4.*four3n1n1n1n+6.*four4n2n1n1n+12.*three2n1n1n+12.*four1n1n1n1n+24.*four2n1n2n1n | |
2842 | + 4.*four3n1n2n2n+3.*four2n2n2n2n)-dMult*(dMult-1.)*(dMult-2.)*(6.*three2n1n1n+12.*three3n2n1n | |
2843 | + 4.*three4n3n1n+3.*three4n2n2n+8.*three2n1n1n+24.*two1n1n+12.*two2n2n+12.*three2n1n1n+8.*three3n2n1n | |
2844 | + 1.*three4n2n2n)-dMult*(dMult-1.)*(4.*two1n1n+6.*two2n2n+4.*two3n3n+1.*two4n4n+2.*two2n2n+8.*two1n1n+6.)-dMult) | |
2845 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)); // to be improved (direct formula needed) | |
2846 | ||
2847 | six3n1n1n1n1n1n = (reQ3nQ1nQ1nstarQ1nstarQ1nstarQ1nstar-dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.) | |
2848 | * (five4n1n1n1n1n+4.*five2n1n1n1n1n+6.*five3n1n2n1n1n+4.*four3n1n1n1n) | |
2849 | - dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(4.*four3n1n1n1n+6.*four4n2n1n1n+6.*four1n1n1n1n | |
2850 | + 12.*three2n1n1n+12.*four2n1n2n1n+6.*four3n1n1n1n+12.*three3n2n1n+4.*four3n1n3n1n+3.*four3n1n2n2n) | |
2851 | - dMult*(dMult-1.)*(dMult-2.)*(6.*three2n1n1n+12.*three3n2n1n+4.*three4n3n1n+3.*three4n2n2n+4.*two1n1n | |
2852 | + 12.*two1n1n+6.*three2n1n1n+12.*three2n1n1n+4.*three3n2n1n+12.*two2n2n+4.*three3n2n1n+4.*two3n3n+1.*three4n3n1n | |
2853 | + 6.*three3n2n1n)-dMult*(dMult-1.)*(4.*two1n1n+6.*two2n2n+4.*two3n3n+1.*two4n4n+1.*two1n1n+4.+6.*two1n1n+4.*two2n2n | |
2854 | + 1.*two3n3n)-dMult)/(dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)); // to be improved (direct formula needed) | |
2855 | ||
2856 | // average 6-particle correlations for single event: | |
2857 | fIntFlowCorrelationsAllEBE->SetBinContent(24,six1n1n1n1n1n1n); | |
2858 | fIntFlowCorrelationsAllEBE->SetBinContent(25,six2n1n1n2n1n1n); | |
2859 | fIntFlowCorrelationsAllEBE->SetBinContent(26,six2n2n1n1n1n1n); | |
2860 | fIntFlowCorrelationsAllEBE->SetBinContent(27,six3n1n1n1n1n1n); | |
2861 | ||
2862 | // average 6-particle correlations for all events: | |
2863 | fIntFlowCorrelationsAllPro->Fill(23.5,six1n1n1n1n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)); | |
2864 | fIntFlowCorrelationsAllPro->Fill(24.5,six2n1n1n2n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)); | |
2865 | fIntFlowCorrelationsAllPro->Fill(25.5,six2n2n1n1n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)); | |
2866 | fIntFlowCorrelationsAllPro->Fill(26.5,six3n1n1n1n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)); | |
2867 | ||
2868 | // store separetately <6> (to be improved: do I really need this?) | |
2869 | fIntFlowCorrelationsEBE->SetBinContent(3,six1n1n1n1n1n1n); // <6> | |
2870 | ||
2871 | // to be improved (this can be implemented better): | |
2872 | Double_t mWeight6p = 0.; | |
2873 | if(!strcmp(fMultiplicityWeight->Data(),"combinations")) | |
2874 | { | |
2875 | mWeight6p = dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.); | |
2876 | } else if(!strcmp(fMultiplicityWeight->Data(),"unit")) | |
2877 | { | |
2878 | mWeight6p = 1.; | |
2879 | } else if(!strcmp(fMultiplicityWeight->Data(),"multiplicity")) | |
2880 | { | |
2881 | mWeight6p = dMult; | |
2882 | } | |
2883 | ||
2884 | fIntFlowEventWeightsForCorrelationsEBE->SetBinContent(3,mWeight6p); // eW_<6> | |
2885 | fIntFlowCorrelationsPro->Fill(2.5,six1n1n1n1n1n1n,mWeight6p); | |
b40a910e | 2886 | fIntFlowSquaredCorrelationsPro->Fill(2.5,six1n1n1n1n1n1n*six1n1n1n1n1n1n,mWeight6p); |
2887 | if(fCalculateCumulantsVsM) | |
2888 | { | |
2889 | fIntFlowCorrelationsVsMPro[2]->Fill(dMult+0.5,six1n1n1n1n1n1n,mWeight6p); | |
2890 | fIntFlowSquaredCorrelationsVsMPro[2]->Fill(dMult+0.5,six1n1n1n1n1n1n*six1n1n1n1n1n1n,mWeight6p); | |
2891 | } | |
489d5531 | 2892 | // distribution of <cos(n*(phi1+phi2+phi3-phi4-phi5-phi6))> |
2893 | //f6pDistribution->Fill(six1n1n1n1n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)); | |
2894 | } // end of if(dMult>5) | |
2895 | ||
2896 | // 7-particle: | |
2897 | Double_t seven2n1n1n1n1n1n1n = 0.; // <cos(n*(2.*phi1+phi2+phi3-phi4-phi5-phi6-phi7))> | |
2898 | ||
2899 | if(dMult>6) | |
2900 | { | |
2901 | seven2n1n1n1n1n1n1n = (reQ2nQ1nQ1nQ1nstarQ1nstarQ1nstarQ1nstar-dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.) | |
2902 | * (2.*six3n1n1n1n1n1n+4.*six1n1n1n1n1n1n+1.*six2n2n1n1n1n1n+6.*six2n1n1n2n1n1n+8.*five2n1n1n1n1n) | |
2903 | - dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(1.*five4n1n1n1n1n +8.*five2n1n1n1n1n+8.*four3n1n1n1n | |
2904 | + 12.*five3n1n2n1n1n+4.*five2n1n1n1n1n+3.*five2n2n2n1n1n+6.*five2n2n2n1n1n+6.*four1n1n1n1n+24.*four1n1n1n1n | |
2905 | + 12.*five2n1n1n1n1n+12.*five2n1n1n1n1n+12.*three2n1n1n+24.*four2n1n2n1n+4.*five3n1n2n1n1n+4.*five2n1n1n1n1n) | |
2906 | - dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(4.*four3n1n1n1n+6.*four4n2n1n1n+12.*four1n1n1n1n+24.*three2n1n1n | |
2907 | + 24.*four2n1n2n1n+12.*four3n1n1n1n+24.*three3n2n1n+8.*four3n1n3n1n+6.*four3n1n2n2n+6.*three2n1n1n+12.*four1n1n1n1n | |
2908 | + 12.*four2n1n2n1n+6.*three2n1n1n+12.*four2n1n2n1n+4.*four3n1n2n2n+3.*four2n2n2n2n+4.*four1n1n1n1n+6.*three2n1n1n | |
2909 | + 24.*two1n1n+24.*four1n1n1n1n+4.*four3n1n1n1n+24.*two1n1n+24.*three2n1n1n+12.*two2n2n+24.*three2n1n1n+12.*four2n1n2n1n | |
2910 | + 8.*three3n2n1n+8.*four2n1n2n1n+1.*four4n2n1n1n)-dMult*(dMult-1.)*(dMult-2.)*(6.*three2n1n1n+1.*three2n1n1n+8.*two1n1n | |
2911 | + 12.*three3n2n1n+24.*two1n1n+12.*three2n1n1n+4.*three2n1n1n+8.*two1n1n+4.*three4n3n1n+24.*three2n1n1n+8.*three3n2n1n | |
2912 | + 12.*two1n1n+12.*two1n1n+3.*three4n2n2n+24.*two2n2n+6.*two2n2n+12.+12.*three3n2n1n+8.*two3n3n+12.*three2n1n1n+24.*two1n1n | |
2913 | + 4.*three3n2n1n+8.*three3n2n1n+2.*three4n3n1n+12.*two1n1n+8.*three2n1n1n+4.*three2n1n1n+2.*three3n2n1n+6.*two2n2n+8.*two2n2n | |
2914 | + 1.*three4n2n2n+4.*three3n2n1n+6.*three2n1n1n)-dMult*(dMult-1.)*(4.*two1n1n+2.*two1n1n+6.*two2n2n+8.+1.*two2n2n+4.*two3n3n | |
2915 | + 12.*two1n1n+4.*two1n1n+1.*two4n4n+8.*two2n2n+6.+2.*two3n3n+4.*two1n1n+1.*two2n2n)-dMult) | |
2916 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)*(dMult-6.)); // to be improved (direct formula needed) | |
2917 | ||
2918 | // average 7-particle correlations for single event: | |
2919 | fIntFlowCorrelationsAllEBE->SetBinContent(29,seven2n1n1n1n1n1n1n); | |
2920 | ||
2921 | // average 7-particle correlations for all events: | |
2922 | fIntFlowCorrelationsAllPro->Fill(28.5,seven2n1n1n1n1n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)*(dMult-6.)); | |
2923 | } // end of if(dMult>6) | |
2924 | ||
2925 | // 8-particle: | |
2926 | Double_t eight1n1n1n1n1n1n1n1n = 0.; // <cos(n*(phi1+phi2+phi3+phi4-phi5-phi6-phi7-phi8))> | |
2927 | if(dMult>7) | |
2928 | { | |
2929 | eight1n1n1n1n1n1n1n1n = (pow(pow(dReQ1n,2.)+pow(dImQ1n,2.),4.)-dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)*(dMult-6.) | |
2930 | * (12.*seven2n1n1n1n1n1n1n+16.*six1n1n1n1n1n1n)-dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.) | |
2931 | * (8.*six3n1n1n1n1n1n+48.*six1n1n1n1n1n1n+6.*six2n2n1n1n1n1n+96.*five2n1n1n1n1n+72.*four1n1n1n1n+36.*six2n1n1n2n1n1n) | |
2932 | - dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(2.*five4n1n1n1n1n+32.*five2n1n1n1n1n+36.*four1n1n1n1n | |
2933 | + 32.*four3n1n1n1n+48.*five2n1n1n1n1n+48.*five3n1n2n1n1n+144.*five2n1n1n1n1n+288.*four1n1n1n1n+36.*five2n2n2n1n1n | |
2934 | + 144.*three2n1n1n+96.*two1n1n+144.*four2n1n2n1n)-dMult*(dMult-1.)*(dMult-2.)*(dMult-3.) | |
2935 | * (8.*four3n1n1n1n+48.*four1n1n1n1n+12.*four4n2n1n1n+96.*four2n1n2n1n+96.*three2n1n1n+72.*three2n1n1n+144.*two1n1n | |
2936 | + 16.*four3n1n3n1n+48.*four3n1n1n1n+144.*four1n1n1n1n+72.*four1n1n1n1n+96.*three3n2n1n+24.*four3n1n2n2n+144.*four2n1n2n1n | |
2937 | + 288.*two1n1n+288.*three2n1n1n+9.*four2n2n2n2n+72.*two2n2n+24.)-dMult*(dMult-1.)*(dMult-2.)*(12.*three2n1n1n+16.*two1n1n | |
2938 | + 24.*three3n2n1n+48.*three2n1n1n+96.*two1n1n+8.*three4n3n1n+32.*three3n2n1n+96.*three2n1n1n+144.*two1n1n+6.*three4n2n2n | |
2939 | + 96.*two2n2n+36.*two2n2n+72.+48.*three3n2n1n+16.*two3n3n+72.*three2n1n1n+144.*two1n1n)-dMult*(dMult-1.)*(8.*two1n1n | |
2940 | + 12.*two2n2n+16.+8.*two3n3n+48.*two1n1n+1.*two4n4n+16.*two2n2n+18.)-dMult) | |
2941 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)*(dMult-6.)*(dMult-7.)); // to be improved (direct formula needed) | |
2942 | ||
2943 | // average 8-particle correlations for single event: | |
2944 | fIntFlowCorrelationsAllEBE->SetBinContent(31,eight1n1n1n1n1n1n1n1n); | |
2945 | ||
2946 | // average 8-particle correlations for all events: | |
2947 | fIntFlowCorrelationsAllPro->Fill(30.5,eight1n1n1n1n1n1n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)*(dMult-6.)*(dMult-7.)); | |
2948 | ||
2949 | // store separetately <8> (to be improved: do I really need this?) | |
2950 | fIntFlowCorrelationsEBE->SetBinContent(4,eight1n1n1n1n1n1n1n1n); // <8> | |
2951 | ||
2952 | // to be improved (this can be implemented better): | |
2953 | Double_t mWeight8p = 0.; | |
2954 | if(!strcmp(fMultiplicityWeight->Data(),"combinations")) | |
2955 | { | |
2956 | mWeight8p = dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)*(dMult-6.)*(dMult-7.); | |
2957 | } else if(!strcmp(fMultiplicityWeight->Data(),"unit")) | |
2958 | { | |
2959 | mWeight8p = 1.; | |
2960 | } else if(!strcmp(fMultiplicityWeight->Data(),"multiplicity")) | |
2961 | { | |
2962 | mWeight8p = dMult; | |
2963 | } | |
2964 | ||
2965 | fIntFlowEventWeightsForCorrelationsEBE->SetBinContent(4,mWeight8p); // eW_<8> | |
b40a910e | 2966 | fIntFlowCorrelationsPro->Fill(3.5,eight1n1n1n1n1n1n1n1n,mWeight8p); |
2967 | fIntFlowSquaredCorrelationsPro->Fill(3.5,eight1n1n1n1n1n1n1n1n*eight1n1n1n1n1n1n1n1n,mWeight8p); | |
2968 | if(fCalculateCumulantsVsM) | |
2969 | { | |
2970 | fIntFlowCorrelationsVsMPro[3]->Fill(dMult+0.5,eight1n1n1n1n1n1n1n1n,mWeight8p); | |
2971 | fIntFlowSquaredCorrelationsVsMPro[3]->Fill(dMult+0.5,eight1n1n1n1n1n1n1n1n*eight1n1n1n1n1n1n1n1n,mWeight8p); | |
2972 | } | |
489d5531 | 2973 | // distribution of <cos(n*(phi1+phi2+phi3+phi4-phi5-phi6-phi7-phi8))> |
2974 | //f8pDistribution->Fill(eight1n1n1n1n1n1n1n1n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)*(dMult-5.)*(dMult-6.)*(dMult-7.)); | |
2975 | } // end of if(dMult>7) | |
2976 | ||
8ed4edc7 | 2977 | // EXTRA: |
2978 | ||
2979 | // 33rd bin: <4>_{4n,2n|3n,3n}= four4n2n3n3n = <cos(n*(4.*phi1+2.*phi2-3.*phi3-3.*phi4))> | |
2980 | // 34th bin: <5>_{2n,2n,2n|3n,3n} = five2n2n2n3n3n = <cos(n*(2.*phi1+2.*phi2+2.*phi3-3.*phi4-3.*phi5))> | |
2981 | ||
2982 | // 4-particle: | |
2983 | Double_t four4n2n3n3n = 0.; // <cos(n*(4.*phi1+2.*phi2-3.*phi3-3.*phi4))> | |
2984 | Double_t reQ4nQ2nQ3nstarQ3nstar = (dReQ4n*dReQ2n-dImQ4n*dImQ2n)*(dReQ3n*dReQ3n-dImQ3n*dImQ3n) | |
2985 | + 2.*(dReQ4n*dImQ2n+dImQ4n*dReQ2n)*dReQ3n*dImQ3n; | |
2986 | Double_t three1n2n3n = three3n2n1n; | |
2987 | // <3>_{6n|3n,3n}: | |
2988 | Double_t reQ6nQ3nstarQ3nstar = pow(dReQ3n,2.)*dReQ6n + 2.*dReQ3n*dImQ3n*dImQ6n - pow(dImQ3n,2.)*dReQ6n; | |
2989 | Double_t three6n3n3n = 0.; | |
2990 | if(dMult>2.) | |
2991 | { | |
2992 | three6n3n3n = (reQ6nQ3nstarQ3nstar-2.*(pow(dReQ3n,2.)+pow(dImQ3n,2.)) | |
2993 | - (pow(dReQ6n,2.)+pow(dImQ6n,2.))+2.*dMult) | |
2994 | / (dMult*(dMult-1.)*(dMult-2.)); | |
2995 | } | |
2996 | ||
2997 | // <3>_{4n,2n|6n}: | |
2998 | Double_t reQ6nQ4nstarQ2nstar = dReQ6n*dReQ4n*dReQ2n-dReQ6n*dImQ4n*dImQ2n+dImQ6n*dReQ4n*dImQ2n | |
2999 | + dImQ6n*dImQ4n*dReQ2n; | |
3000 | Double_t three4n2n6n = 0.; | |
3001 | if(dMult>2.) | |
3002 | { | |
3003 | three4n2n6n = (reQ6nQ4nstarQ2nstar-(pow(dReQ6n,2.)+pow(dImQ6n,2.)) | |
3004 | - (pow(dReQ4n,2.)+pow(dImQ4n,2.)) | |
3005 | - (pow(dReQ2n,2.)+pow(dImQ2n,2.))+2.*dMult) | |
3006 | / (dMult*(dMult-1.)*(dMult-2.)); | |
3007 | } | |
3008 | Double_t two6n6n = 0.; | |
3009 | if(dMult>1.) | |
3010 | { | |
3011 | two6n6n = (pow(dReQ6n,2.)+pow(dImQ6n,2.)-dMult)/(dMult*(dMult-1.)); | |
3012 | } | |
3013 | if(dMult>3.) | |
3014 | { | |
3015 | four4n2n3n3n = reQ4nQ2nQ3nstarQ3nstar/(dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)) | |
3016 | - (2.*three1n2n3n+three6n3n3n+2.*three4n3n1n+three4n2n6n)/(dMult-3.) | |
3017 | - (2.*two3n3n+two2n2n+two4n4n+two6n6n+2.*two1n1n)/((dMult-2.)*(dMult-3.)) | |
3018 | - 1./((dMult-1.)*(dMult-2.)*(dMult-3.)); | |
3019 | fIntFlowCorrelationsAllPro->Fill(32.5,four4n2n3n3n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)); | |
3020 | } // end of if(dMult>3) | |
3021 | ||
3022 | // 5-particle: | |
3023 | Double_t five2n2n2n3n3n = 0.; // <cos(n*(2.*phi1+2.*phi2+2.*phi3-3.*phi4-3.*phi5))> | |
3024 | Double_t reQ2nQ2nQ2nQ3nstarQ3nstar = pow(dReQ2n,3.)*pow(dReQ3n,2.) | |
3025 | - 3.*dReQ2n*pow(dReQ3n,2.)*pow(dImQ2n,2.) + 6.*pow(dReQ2n,2.)*dReQ3n*dImQ2n*dImQ3n | |
3026 | - 2.*dReQ3n*pow(dImQ2n,3.)*dImQ3n - pow(dReQ2n,3.)*pow(dImQ3n,2.) + 3.*dReQ2n*pow(dImQ2n,2.)*pow(dImQ3n,2.); | |
3027 | //Double_t reQ2nQ2nQ2nQ3nstarQ3nstar = (pow(dReQ2n,3.)-3.*dReQ2n*dImQ2n*dImQ2n)*(dReQ3n*dReQ3n-dImQ3n*dImQ3n) | |
3028 | // + 2.*dReQ3n*dImQ3n*(3.*dReQ2n*dReQ2n*dImQ2n-pow(dImQ3n,3.)); | |
3029 | Double_t four2n2n1n3n = four3n1n2n2n; | |
3030 | // <4>_{2n,2n,2n|6n}: | |
3031 | Double_t reQ6nQ2nstarQ2nstarQ2nstar = dReQ6n*pow(dReQ2n,3)-3.*dReQ2n*dReQ6n*pow(dImQ2n,2) | |
3032 | + 3.*dImQ2n*dImQ6n*pow(dReQ2n,2)-dImQ6n*pow(dImQ2n,3); | |
3033 | Double_t four2n2n2n6n = 0.; | |
3034 | if(dMult>3.) | |
3035 | { | |
3036 | four2n2n2n6n = (reQ6nQ2nstarQ2nstarQ2nstar-3.*reQ6nQ4nstarQ2nstar-3.*reQ4nQ2nstarQ2nstar) | |
3037 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)) | |
3038 | + (2.*(pow(dReQ6n,2.)+pow(dImQ6n,2.))+3.*(pow(dReQ4n,2.)+pow(dImQ4n,2.)) | |
3039 | + 6.*(pow(dReQ2n,2.)+pow(dImQ2n,2.))-6.*dMult) | |
3040 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)); | |
3041 | } | |
3042 | Double_t three2n2n4n = three4n2n2n; | |
3043 | Double_t three4n1n3n = three4n3n1n; | |
3044 | ||
3045 | if(dMult>4.) | |
3046 | { | |
3047 | five2n2n2n3n3n = reQ2nQ2nQ2nQ3nstarQ3nstar | |
3048 | / (dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)) | |
3049 | - (6.*four2n2n1n3n+3.*four4n2n3n3n+1.*four2n2n2n6n)/(dMult-4.) | |
3050 | - (3.*three2n2n4n+6.*three1n2n3n+1.*three6n3n3n+3.*three4n2n6n+6.*three2n1n1n+6.*three4n1n3n)/((dMult-3.)*(dMult-4.)) | |
3051 | - (2.*two3n3n+3.*two2n2n+1.*two6n6n+6.*two1n1n+3.*two4n4n)/((dMult-2.)*(dMult-3.)*(dMult-4.)) | |
3052 | - 1./((dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)); | |
3053 | fIntFlowCorrelationsAllPro->Fill(33.5,five2n2n2n3n3n,dMult*(dMult-1.)*(dMult-2.)*(dMult-3.)*(dMult-4.)); | |
3054 | } // end of if(dMult>4) | |
3055 | ||
489d5531 | 3056 | } // end of AliFlowAnalysisWithQCumulants::CalculateIntFlowCorrelations() |
3057 | ||
489d5531 | 3058 | //================================================================================================================================ |
3059 | ||
e5834fcb | 3060 | void AliFlowAnalysisWithQCumulants::StorePhiDistributionForOneEvent(AliFlowEventSimple *anEvent) |
3061 | { | |
3062 | // Store phi distribution for one event to illustrate flow. | |
3063 | ||
3064 | if(fPhiDistributionForOneEvent->GetEntries()>0){return;} // store only phi distribution for one event | |
3065 | ||
3066 | Double_t vMin = fPhiDistributionForOneEventSettings[0]; | |
3067 | Double_t vMax = fPhiDistributionForOneEventSettings[1]; | |
3068 | Double_t refMultMin = fPhiDistributionForOneEventSettings[2]; | |
3069 | Double_t refMultMax = fPhiDistributionForOneEventSettings[3]; | |
3070 | ||
3071 | Double_t vEBE = 0.; | |
3072 | Double_t cumulant4thEBE = fIntFlowCorrelationsEBE->GetBinContent(2)-2.*pow(fIntFlowCorrelationsEBE->GetBinContent(1),2.); | |
3073 | if(cumulant4thEBE<0.) | |
3074 | { | |
3075 | vEBE = pow(-1.*cumulant4thEBE,0.25); | |
3076 | if((vEBE>vMin && vEBE<vMax) && (fReferenceMultiplicityEBE>refMultMin && fReferenceMultiplicityEBE<refMultMax)) | |
3077 | { | |
3958eee6 | 3078 | fPhiDistributionForOneEvent->SetTitle(Form("v_{%i} = %f",fHarmonic,vEBE)); |
e5834fcb | 3079 | for(Int_t p=0;p<anEvent->NumberOfTracks();p++) |
3080 | { | |
3081 | if(anEvent->GetTrack(p)->InRPSelection()) | |
3082 | { | |
3083 | fPhiDistributionForOneEvent->Fill(anEvent->GetTrack(p)->Phi()); | |
3084 | } | |
3085 | } // end of for(Int_t p=0;p<anEvent->NumberOfTracks();p++) | |
3958eee6 | 3086 | } else |
3087 | { | |
3088 | fPhiDistributionForOneEvent->SetTitle(Form("v_{%i} = %f, out of specified boundaries",fHarmonic,vEBE)); | |
3089 | } | |
3090 | ||
e5834fcb | 3091 | } // end of if(cumulant4thEBE<0.) |
3092 | ||
3093 | } // end of void AliFlowAnalysisWithQCumulants::StorePhiDistributionForOneEvent(AliFlowEventSimple *anEvent) | |
3094 | ||
3095 | //================================================================================================================================ | |
489d5531 | 3096 | |
3097 | void AliFlowAnalysisWithQCumulants::CalculateIntFlowProductOfCorrelations() | |
3098 | { | |
0328db2d | 3099 | // Calculate averages of products of correlations for integrated flow. |
489d5531 | 3100 | |
2001bc3a | 3101 | // multiplicity: |
3102 | Double_t dMult = (*fSMpk)(0,0); | |
3103 | ||
489d5531 | 3104 | Int_t counter = 0; |
3105 | ||
3106 | for(Int_t ci1=1;ci1<4;ci1++) | |
3107 | { | |
3108 | for(Int_t ci2=ci1+1;ci2<=4;ci2++) | |
3109 | { | |
ff70ca91 | 3110 | fIntFlowProductOfCorrelationsPro->Fill(0.5+counter, |
3111 | fIntFlowCorrelationsEBE->GetBinContent(ci1)* | |
3112 | fIntFlowCorrelationsEBE->GetBinContent(ci2), | |
3113 | fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(ci1)* | |
3114 | fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(ci2)); | |
3115 | // products versus multiplicity: // [0=<<2><4>>,1=<<2><6>>,2=<<2><8>>,3=<<4><6>>,4=<<4><8>>,5=<<6><8>>] | |
b3dacf6b | 3116 | if(fCalculateCumulantsVsM) |
3117 | { | |
3118 | fIntFlowProductOfCorrelationsVsMPro[counter]->Fill(dMult+0.5, // to be improved: dMult => sum of weights ? | |
3119 | fIntFlowCorrelationsEBE->GetBinContent(ci1)* | |
3120 | fIntFlowCorrelationsEBE->GetBinContent(ci2), | |
3121 | fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(ci1)* | |
3122 | fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(ci2)); | |
3123 | } // end of if(fCalculateCumulantsVsM) | |
ff70ca91 | 3124 | counter++; |
489d5531 | 3125 | } |
3126 | } | |
3127 | ||
3128 | } // end of AliFlowAnalysisWithQCumulants::CalculateIntFlowProductOfCorrelations() | |
3129 | ||
3130 | ||
3131 | //================================================================================================================================ | |
3132 | ||
3133 | ||
0328db2d | 3134 | void AliFlowAnalysisWithQCumulants::CalculateIntFlowProductOfCorrectionTermsForNUA() |
3135 | { | |
3136 | // Calculate averages of products of correction terms for NUA. | |
3137 | ||
3138 | // a) Binning of fIntFlowProductOfCorrectionTermsForNUAPro is organized as follows: | |
3139 | // 1st bin: <<2><cos(phi)>> | |
3140 | // 2nd bin: <<2><sin(phi)>> | |
3141 | // 3rd bin: <<cos(phi)><sin(phi)>> | |
3142 | // 4th bin: <<2><cos(phi1+phi2)>> | |
3143 | // 5th bin: <<2><sin(phi1+phi2)>> | |
3144 | // 6th bin: <<2><cos(phi1-phi2-phi3)>> | |
3145 | // 7th bin: <<2><sin(phi1-phi2-phi3)>> | |
3146 | // 8th bin: <<4><cos(phi1)>> | |
3147 | // 9th bin: <<4><sin(phi1)>> | |
3148 | // 10th bin: <<4><cos(phi1+phi2)>> | |
3149 | // 11th bin: <<4><sin(phi1+phi2)>> | |
3150 | // 12th bin: <<4><cos(phi1-phi2-phi3)>> | |
3151 | // 13th bin: <<4><sin(phi1-phi2-phi3)>> | |
3152 | // 14th bin: <<cos(phi1)><cos(phi1+phi2)>> | |
3153 | // 15th bin: <<cos(phi1)><sin(phi1+phi2)>> | |
3154 | // 16th bin: <<cos(phi1)><cos(phi1-phi2-phi3)>> | |
3155 | // 17th bin: <<cos(phi1)><sin(phi1-phi2-phi3)>> | |
3156 | // 18th bin: <<sin(phi1)><cos(phi1+phi2)>> | |
3157 | // 19th bin: <<sin(phi1)><sin(phi1+phi2)>> | |
3158 | // 20th bin: <<sin(phi1)><cos(phi1-phi2-phi3)>> | |
3159 | // 21st bin: <<sin(phi1)><sin(phi1-phi2-phi3)>> | |
3160 | // 22nd bin: <<cos(phi1+phi2)><sin(phi1+phi2)>> | |
3161 | // 23rd bin: <<cos(phi1+phi2)><cos(phi1-phi2-phi3)>> | |
3162 | // 24th bin: <<cos(phi1+phi2)><sin(phi1-phi2-phi3)>> | |
3163 | // 25th bin: <<sin(phi1+phi2)><cos(phi1-phi2-phi3)>> | |
3164 | // 26th bin: <<sin(phi1+phi2)><sin(phi1-phi2-phi3)>> | |
3165 | // 27th bin: <<cos(phi1-phi2-phi3)><sin(phi1-phi2-phi3)>> | |
3166 | ||
3167 | // <<2><cos(phi)>>: | |
3168 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(0.5, | |
3169 | fIntFlowCorrelationsEBE->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(1), | |
3170 | fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1) | |
3171 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1)); | |
3172 | // <<2><sin(phi)>>: | |
3173 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(1.5, | |
3174 | fIntFlowCorrelationsEBE->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(1), | |
3175 | fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1) | |
3176 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1)); | |
3177 | // <<cos(phi)><sin(phi)>>: | |
3178 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(2.5, | |
3179 | fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(1), | |
3180 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1) | |
3181 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1)); | |
3182 | // <<2><cos(phi1+phi2)>>: | |
3183 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(3.5, | |
3184 | fIntFlowCorrelationsEBE->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(2), | |
3185 | fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1) | |
3186 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2)); | |
3187 | // <<2><sin(phi1+phi2)>>: | |
3188 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(4.5, | |
3189 | fIntFlowCorrelationsEBE->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(2), | |
3190 | fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1) | |
3191 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2)); | |
3192 | // <<2><cos(phi1-phi2-phi3)>>: | |
3193 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(5.5, | |
3194 | fIntFlowCorrelationsEBE->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(3), | |
3195 | fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1) | |
3196 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)); | |
3197 | // <<2><sin(phi1-phi2-phi3)>>: | |
3198 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(6.5, | |
3199 | fIntFlowCorrelationsEBE->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(3), | |
3200 | fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1) | |
3201 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); | |
3202 | // <<4><cos(phi1)>>: | |
3203 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(7.5, | |
3204 | fIntFlowCorrelationsEBE->GetBinContent(2)*fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(1), | |
3205 | fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2) | |
3206 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1)); | |
3207 | // <<4><sin(phi1)>>: | |
3208 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(8.5, | |
3209 | fIntFlowCorrelationsEBE->GetBinContent(2)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(1), | |
3210 | fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2) | |
3211 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1)); | |
3212 | // <<4><cos(phi1+phi2)>>: | |
3213 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(9.5, | |
3214 | fIntFlowCorrelationsEBE->GetBinContent(2)*fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(2), | |
3215 | fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2) | |
3216 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2)); | |
3217 | // <<4><sin(phi1+phi2)>>: | |
3218 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(10.5, | |
3219 | fIntFlowCorrelationsEBE->GetBinContent(2)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(2), | |
3220 | fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2) | |
3221 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2)); | |
3222 | // <<4><cos(phi1-phi2-phi3)>>: | |
3223 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(11.5, | |
3224 | fIntFlowCorrelationsEBE->GetBinContent(2)*fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(3), | |
3225 | fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2) | |
3226 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)); | |
3227 | // <<4><sin(phi1-phi2-phi3)>>: | |
3228 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(12.5, | |
3229 | fIntFlowCorrelationsEBE->GetBinContent(2)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(3), | |
3230 | fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2) | |
3231 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); | |
3232 | // <<cos(phi1)><cos(phi1+phi2)>>: | |
3233 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(13.5, | |
3234 | fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(2), | |
3235 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1) | |
3236 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2)); | |
3237 | // <<cos(phi1)><sin(phi1+phi2)>>: | |
3238 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(14.5, | |
3239 | fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(2), | |
3240 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1) | |
3241 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2)); | |
3242 | // <<cos(phi1)><cos(phi1-phi2-phi3)>>: | |
3243 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(15.5, | |
3244 | fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(3), | |
3245 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1) | |
3246 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)); | |
3247 | // <<cos(phi1)><sin(phi1-phi2-phi3)>>: | |
3248 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(16.5, | |
3249 | fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(3), | |
3250 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1) | |
3251 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); | |
3252 | // <<sin(phi1)><cos(phi1+phi2)>>: | |
3253 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(17.5, | |
3254 | fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(2), | |
3255 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1) | |
3256 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2)); | |
3257 | // <<sin(phi1)><sin(phi1+phi2)>>: | |
3258 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(18.5, | |
3259 | fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(2), | |
3260 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1) | |
3261 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2)); | |
3262 | // <<sin(phi1)><cos(phi1-phi2-phi3)>>: | |
3263 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(19.5, | |
3264 | fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(3), | |
3265 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1) | |
3266 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)); | |
3267 | // <<sin(phi1)><sin(phi1-phi2-phi3)>>: | |
3268 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(20.5, | |
3269 | fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(1)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(3), | |
3270 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1) | |
3271 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); | |
3272 | // <<cos(phi1+phi2)><sin(phi1+phi2)>>: | |
3273 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(21.5, | |
3274 | fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(2)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(2), | |
3275 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2) | |
3276 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2)); | |
3277 | // <<cos(phi1+phi2)><cos(phi1-phi2-phi3)>>: | |
3278 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(22.5, | |
3279 | fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(2)*fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(3), | |
3280 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2) | |
3281 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)); | |
3282 | // <<cos(phi1+phi2)><sin(phi1-phi2-phi3)>>: | |
3283 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(23.5, | |
3284 | fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(2)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(3), | |
3285 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2) | |
3286 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); | |
3287 | // <<sin(phi1+phi2)><cos(phi1-phi2-phi3)>>: | |
3288 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(24.5, | |
3289 | fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(2)*fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(3), | |
3290 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2) | |
3291 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)); | |
3292 | // <<sin(phi1+phi2)><sin(phi1-phi2-phi3)>>: | |
3293 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(25.5, | |
3294 | fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(2)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(3), | |
3295 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2) | |
3296 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); | |
3297 | // <<cos(phi1-phi2-phi3)><sin(phi1-phi2-phi3)>>: | |
3298 | fIntFlowProductOfCorrectionTermsForNUAPro->Fill(26.5, | |
3299 | fIntFlowCorrectionTermsForNUAEBE[1]->GetBinContent(3)*fIntFlowCorrectionTermsForNUAEBE[0]->GetBinContent(3), | |
3300 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3) | |
3301 | *fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); | |
3302 | ||
3303 | } // end of AliFlowAnalysisWithQCumulants::CalculateIntFlowProductOfCorrectionTermsForNUA() | |
3304 | ||
0328db2d | 3305 | //================================================================================================================================ |
3306 | ||
489d5531 | 3307 | void AliFlowAnalysisWithQCumulants::CalculateCovariancesIntFlow() |
3308 | { | |
3309 | // a) Calculate unbiased estimators Cov(<2>,<4>), Cov(<2>,<6>), Cov(<2>,<8>), Cov(<4>,<6>), Cov(<4>,<8>) and Cov(<6>,<8>) | |
3310 | // for covariances V_(<2>,<4>), V_(<2>,<6>), V_(<2>,<8>), V_(<4>,<6>), V_(<4>,<8>) and V_(<6>,<8>). | |
3311 | // b) Store in histogram fIntFlowCovariances for instance the following: | |
3312 | // | |
3313 | // Cov(<2>,<4>) * (sum_{i=1}^{N} w_{<2>}_i w_{<4>}_i )/[(sum_{i=1}^{N} w_{<2>}_i) * (sum_{j=1}^{N} w_{<4>}_j)] | |
3314 | // | |
3315 | // where N is the number of events, w_{<2>} is event weight for <2> and w_{<4>} is event weight for <4>. | |
3316 | // c) Binning of fIntFlowCovariances is organized as follows: | |
3317 | // | |
3318 | // 1st bin: Cov(<2>,<4>) * (sum_{i=1}^{N} w_{<2>}_i w_{<4>}_i )/[(sum_{i=1}^{N} w_{<2>}_i) * (sum_{j=1}^{N} w_{<4>}_j)] | |
3319 | // 2nd bin: Cov(<2>,<6>) * (sum_{i=1}^{N} w_{<2>}_i w_{<6>}_i )/[(sum_{i=1}^{N} w_{<2>}_i) * (sum_{j=1}^{N} w_{<6>}_j)] | |
3320 | // 3rd bin: Cov(<2>,<8>) * (sum_{i=1}^{N} w_{<2>}_i w_{<8>}_i )/[(sum_{i=1}^{N} w_{<2>}_i) * (sum_{j=1}^{N} w_{<8>}_j)] | |
3321 | // 4th bin: Cov(<4>,<6>) * (sum_{i=1}^{N} w_{<4>}_i w_{<6>}_i )/[(sum_{i=1}^{N} w_{<4>}_i) * (sum_{j=1}^{N} w_{<6>}_j)] | |
3322 | // 5th bin: Cov(<4>,<8>) * (sum_{i=1}^{N} w_{<4>}_i w_{<8>}_i )/[(sum_{i=1}^{N} w_{<4>}_i) * (sum_{j=1}^{N} w_{<8>}_j)] | |
3323 | // 6th bin: Cov(<6>,<8>) * (sum_{i=1}^{N} w_{<6>}_i w_{<8>}_i )/[(sum_{i=1}^{N} w_{<6>}_i) * (sum_{j=1}^{N} w_{<8>}_j)] | |
b3dacf6b | 3324 | // |
489d5531 | 3325 | |
b3dacf6b | 3326 | // Average 2-, 4-, 6- and 8-particle correlations for all events: |
489d5531 | 3327 | Double_t correlation[4] = {0.}; |
3328 | for(Int_t ci=0;ci<4;ci++) | |
3329 | { | |
3330 | correlation[ci] = fIntFlowCorrelationsPro->GetBinContent(ci+1); | |
3331 | } | |
b3dacf6b | 3332 | // Average products of 2-, 4-, 6- and 8-particle correlations: |
489d5531 | 3333 | Double_t productOfCorrelations[4][4] = {{0.}}; |
3334 | Int_t productOfCorrelationsLabel = 1; | |
b3dacf6b | 3335 | // Denominators in the expressions for the unbiased estimator for covariance: |
489d5531 | 3336 | Double_t denominator[4][4] = {{0.}}; |
3337 | Int_t sumOfProductOfEventWeightsLabel1 = 1; | |
b3dacf6b | 3338 | // Weight dependent prefactor which multiply unbiased estimators for covariances: |
489d5531 | 3339 | Double_t wPrefactor[4][4] = {{0.}}; |
3340 | Int_t sumOfProductOfEventWeightsLabel2 = 1; | |
3341 | for(Int_t c1=0;c1<4;c1++) | |
3342 | { | |
3343 | for(Int_t c2=c1+1;c2<4;c2++) | |
3344 | { | |
3345 | productOfCorrelations[c1][c2] = fIntFlowProductOfCorrelationsPro->GetBinContent(productOfCorrelationsLabel); | |
b3dacf6b | 3346 | if(TMath::Abs(fIntFlowSumOfEventWeights[0]->GetBinContent(c1+1)) > 1.e-44 && TMath::Abs(fIntFlowSumOfEventWeights[0]->GetBinContent(c2+1)) > 1.e-44) |
3347 | { | |
3348 | denominator[c1][c2] = 1.-(fIntFlowSumOfProductOfEventWeights->GetBinContent(sumOfProductOfEventWeightsLabel1)) | |
3349 | / (fIntFlowSumOfEventWeights[0]->GetBinContent(c1+1) | |
3350 | * fIntFlowSumOfEventWeights[0]->GetBinContent(c2+1)); | |
3351 | wPrefactor[c1][c2] = fIntFlowSumOfProductOfEventWeights->GetBinContent(sumOfProductOfEventWeightsLabel2) | |
3352 | / (fIntFlowSumOfEventWeights[0]->GetBinContent(c1+1) | |
3353 | * fIntFlowSumOfEventWeights[0]->GetBinContent(c2+1)); | |
489d5531 | 3354 | } |
b3dacf6b | 3355 | productOfCorrelationsLabel++; // to be improved - do I need here all 3 counters? |
489d5531 | 3356 | sumOfProductOfEventWeightsLabel1++; |
3357 | sumOfProductOfEventWeightsLabel2++; | |
b3dacf6b | 3358 | } // end of for(Int_t c2=c1+1;c2<4;c2++) |
3359 | } // end of for(Int_t c1=0;c1<4;c1++) | |
489d5531 | 3360 | |
489d5531 | 3361 | Int_t covarianceLabel = 1; |
3362 | for(Int_t c1=0;c1<4;c1++) | |
3363 | { | |
3364 | for(Int_t c2=c1+1;c2<4;c2++) | |
3365 | { | |
b3dacf6b | 3366 | if(TMath::Abs(denominator[c1][c2]) > 1.e-44) |
489d5531 | 3367 | { |
b3dacf6b | 3368 | // Covariances: |
489d5531 | 3369 | Double_t cov = (productOfCorrelations[c1][c2]-correlation[c1]*correlation[c2])/denominator[c1][c2]; |
b3dacf6b | 3370 | // Covariances multiplied with weight dependent prefactor: |
489d5531 | 3371 | Double_t wCov = cov * wPrefactor[c1][c2]; |
3372 | fIntFlowCovariances->SetBinContent(covarianceLabel,wCov); | |
3373 | } | |
3374 | covarianceLabel++; | |
b3dacf6b | 3375 | } // end of for(Int_t c2=c1+1;c2<4;c2++) |
3376 | } // end of for(Int_t c1=0;c1<4;c1++) | |
489d5531 | 3377 | |
b3dacf6b | 3378 | // Versus multiplicity: |
3379 | if(!fCalculateCumulantsVsM){return;} | |
9da1a4f3 | 3380 | Int_t nBins = fIntFlowCorrelationsVsMPro[0]->GetNbinsX(); // to be improved (hardwired 0) |
3381 | for(Int_t b=1;b<=nBins;b++) | |
3382 | { | |
b3dacf6b | 3383 | // Average 2-, 4-, 6- and 8-particle correlations for all events: |
9da1a4f3 | 3384 | Double_t correlationVsM[4] = {0.}; |
3385 | for(Int_t ci=0;ci<4;ci++) | |
3386 | { | |
3387 | correlationVsM[ci] = fIntFlowCorrelationsVsMPro[ci]->GetBinContent(b); | |
3388 | } // end of for(Int_t ci=0;ci<4;ci++) | |
b3dacf6b | 3389 | // Average products of 2-, 4-, 6- and 8-particle correlations: |
9da1a4f3 | 3390 | Double_t productOfCorrelationsVsM[4][4] = {{0.}}; |
3391 | Int_t productOfCorrelationsLabelVsM = 1; | |
b3dacf6b | 3392 | // Denominators in the expressions for the unbiased estimator for covariance: |
9da1a4f3 | 3393 | Double_t denominatorVsM[4][4] = {{0.}}; |
3394 | Int_t sumOfProductOfEventWeightsLabel1VsM = 1; | |
b3dacf6b | 3395 | // Weight dependent prefactor which multiply unbiased estimators for covariances: |
9da1a4f3 | 3396 | Double_t wPrefactorVsM[4][4] = {{0.}}; |
3397 | Int_t sumOfProductOfEventWeightsLabel2VsM = 1; | |
3398 | for(Int_t c1=0;c1<4;c1++) | |
3399 | { | |
3400 | for(Int_t c2=c1+1;c2<4;c2++) | |
3401 | { | |
3402 | productOfCorrelationsVsM[c1][c2] = fIntFlowProductOfCorrelationsVsMPro[productOfCorrelationsLabelVsM-1]->GetBinContent(b); | |
b3dacf6b | 3403 | if(TMath::Abs(fIntFlowSumOfEventWeightsVsM[c1][0]->GetBinContent(b)) > 1.e-44 && TMath::Abs(fIntFlowSumOfEventWeightsVsM[c2][0]->GetBinContent(b)) > 1.e-44) |
3404 | { | |
3405 | denominatorVsM[c1][c2] = 1.-(fIntFlowSumOfProductOfEventWeightsVsM[sumOfProductOfEventWeightsLabel1VsM-1]->GetBinContent(b)) | |
3406 | / (fIntFlowSumOfEventWeightsVsM[c1][0]->GetBinContent(b) | |
3407 | * fIntFlowSumOfEventWeightsVsM[c2][0]->GetBinContent(b)); | |
3408 | wPrefactorVsM[c1][c2] = fIntFlowSumOfProductOfEventWeightsVsM[sumOfProductOfEventWeightsLabel2VsM-1]->GetBinContent(b) | |
3409 | / (fIntFlowSumOfEventWeightsVsM[c1][0]->GetBinContent(b) | |
3410 | * fIntFlowSumOfEventWeightsVsM[c2][0]->GetBinContent(b)); | |
9da1a4f3 | 3411 | } |
3412 | productOfCorrelationsLabelVsM++; | |
3413 | sumOfProductOfEventWeightsLabel1VsM++; | |
3414 | sumOfProductOfEventWeightsLabel2VsM++; | |
3415 | } // end of for(Int_t c1=0;c1<4;c1++) | |
3416 | } // end of for(Int_t c2=c1+1;c2<4;c2++) | |
b3dacf6b | 3417 | |
9da1a4f3 | 3418 | Int_t covarianceLabelVsM = 1; |
3419 | for(Int_t c1=0;c1<4;c1++) | |
3420 | { | |
3421 | for(Int_t c2=c1+1;c2<4;c2++) | |
3422 | { | |
b3dacf6b | 3423 | if(TMath::Abs(denominatorVsM[c1][c2]) > 1.e-44) |
9da1a4f3 | 3424 | { |
b3dacf6b | 3425 | // Covariances: |
9da1a4f3 | 3426 | Double_t covVsM = (productOfCorrelationsVsM[c1][c2]-correlationVsM[c1]*correlationVsM[c2])/denominatorVsM[c1][c2]; |
b3dacf6b | 3427 | // Covariances multiplied with weight dependent prefactor: |
9da1a4f3 | 3428 | Double_t wCovVsM = covVsM * wPrefactorVsM[c1][c2]; |
3429 | fIntFlowCovariancesVsM[covarianceLabelVsM-1]->SetBinContent(b,wCovVsM); | |
3430 | } | |
3431 | covarianceLabelVsM++; | |
b3dacf6b | 3432 | } // end of for(Int_t c2=c1+1;c2<4;c2++) |
3433 | } // end of for(Int_t c1=0;c1<4;c1++) | |
9da1a4f3 | 3434 | } // end of for(Int_t b=1;b<=nBins;b++) |
3435 | ||
489d5531 | 3436 | } // end of AliFlowAnalysisWithQCumulants::CalculateCovariancesIntFlow() |
3437 | ||
489d5531 | 3438 | //================================================================================================================================ |
3439 | ||
0328db2d | 3440 | void AliFlowAnalysisWithQCumulants::CalculateCovariancesNUAIntFlow() |
3441 | { | |
3442 | // a) Calculate unbiased estimators Cov(*,*) for true covariances V_(*,*) for NUA terms. | |
3443 | // b) Store in histogram fIntFlowCovariancesNUA for instance the following: | |
3444 | // | |
3445 | // Cov(<2>,<cos(phi)>) * (sum_{i=1}^{N} w_{<2>}_i w_{<cos(phi)>}_i )/[(sum_{i=1}^{N} w_{<2>}_i) * (sum_{j=1}^{N} w_{<cos(phi)>}_j)] | |
3446 | // | |
3447 | // where N is the number of events, w_{<2>} is event weight for <2> and w_{<cos(phi)>} is event weight for <cos(phi)>. | |
3448 | // c) Binning of fIntFlowCovariancesNUA is organized as follows: | |
3449 | // | |
3450 | // 1st bin: Cov(<2>,<cos(phi)>) * (sum_{i=1}^{N} w_{<2>}_i w_{<cos(phi)>}_i )/[(sum_{i=1}^{N} w_{<2>}_i) * (sum_{j=1}^{N} w_{<cos(phi)>}_j)] | |
3451 | // 2nd bin: Cov(<2>,<sin(phi)>) * (sum_{i=1}^{N} w_{<2>}_i w_{<sin(phi)>}_i )/[(sum_{i=1}^{N} w_{<2>}_i) * (sum_{j=1}^{N} w_{<sin(phi)>}_j)] | |
3452 | // 3rd bin: Cov(<cos(phi)>,<sin(phi)>) * (sum_{i=1}^{N} w_{<cos(phi)>}_i w_{<sin(phi)>}_i )/[(sum_{i=1}^{N} w_{<cos(phi)>}_i) * (sum_{j=1}^{N} w_{<sin(phi)>}_j)] | |
3453 | // ... | |
3454 | ||
3455 | // Cov(<2>,<cos(phi)>): | |
3456 | Double_t product1 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(1); // <<2><cos(phi)>> | |
3457 | Double_t term1st1 = fIntFlowCorrelationsPro->GetBinContent(1); // <<2>> | |
3458 | Double_t term2nd1 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(1); // <<cos(phi)>> | |
3459 | Double_t sumOfW1st1 = fIntFlowSumOfEventWeights[0]->GetBinContent(1); // W_{<2>} | |
3460 | Double_t sumOfW2nd1 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(1); // W_{<cos(phi)>} | |
3461 | Double_t sumOfWW1 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(1); // W_{<2>} * W_{<cos(phi)>} | |
3462 | // numerator in the expression for the the unbiased estimator for covariance: | |
3463 | Double_t numerator1 = product1 - term1st1*term2nd1; | |
3464 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 3465 | Double_t denominator1 = 0.; |
3466 | if(TMath::Abs(sumOfW1st1*sumOfW2nd1)>0.) | |
3467 | { | |
3468 | denominator1 = 1.-sumOfWW1/(sumOfW1st1*sumOfW2nd1); | |
3469 | if(TMath::Abs(denominator1)>0.) | |
3470 | { | |
3471 | // covariance: | |
3472 | Double_t covariance1 = numerator1/denominator1; | |
3473 | // weight dependent prefactor for covariance: | |
3474 | Double_t wPrefactor1 = sumOfWW1/(sumOfW1st1*sumOfW2nd1); | |
3475 | // finally, store "weighted" covariance: | |
3476 | fIntFlowCovariancesNUA->SetBinContent(1,wPrefactor1*covariance1); | |
3477 | } // end of if(TMath::Abs(denominator)>0.) | |
3478 | } // end of if(TMath::Abs(sumOfW1st1*sumOfW2nd1)>0.) | |
3479 | ||
0328db2d | 3480 | // Cov(<2>,<sin(phi)>): |
3481 | Double_t product2 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(2); // <<2><sin(phi)>> | |
3482 | Double_t term1st2 = fIntFlowCorrelationsPro->GetBinContent(1); // <<2>> | |
3483 | Double_t term2nd2 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(1); // <<sin(phi)>> | |
3484 | Double_t sumOfW1st2 = fIntFlowSumOfEventWeights[0]->GetBinContent(1); // W_{<2>} | |
3485 | Double_t sumOfW2nd2 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(1); // W_{<sin(phi)>} | |
3486 | Double_t sumOfWW2 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(2); // W_{<2>} * W_{<sin(phi)>} | |
3487 | // numerator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 3488 | Double_t numerator2 = product2 - term1st2*term2nd2; |
0328db2d | 3489 | // denominator in the expression for the the unbiased estimator for covariance: |
b92ea2b9 | 3490 | Double_t denominator2 = 0.; |
3491 | if(TMath::Abs(sumOfW1st2*sumOfW2nd2)>0.) | |
3492 | { | |
3493 | denominator2 = 1.-sumOfWW2/(sumOfW1st2*sumOfW2nd2); | |
3494 | if(TMath::Abs(denominator2)>0.) | |
3495 | { | |
3496 | // covariance: | |
3497 | Double_t covariance2 = numerator2/denominator2; | |
3498 | // weight dependent prefactor for covariance: | |
3499 | Double_t wPrefactor2 = sumOfWW2/(sumOfW1st2*sumOfW2nd2); | |
3500 | // finally, store "weighted" covariance: | |
3501 | fIntFlowCovariancesNUA->SetBinContent(2,wPrefactor2*covariance2); | |
3502 | } // end of if(TMath::Abs(denominator2)>0.) | |
3503 | } // end of if(TMath::Abs(sumOfW1st2*sumOfW2nd2)>0.) | |
0328db2d | 3504 | |
3505 | // Cov(<cos(phi)>,<sin(phi)>): | |
3506 | Double_t product3 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(3); // <<cos(phi)><sin(phi)>> | |
3507 | Double_t term1st3 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(1); // <<cos(phi)>> | |
3508 | Double_t term2nd3 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(1); // <<sin(phi)>> | |
3509 | Double_t sumOfW1st3 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(1); // W_{<cos(phi)>} | |
3510 | Double_t sumOfW2nd3 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(1); // W_{<sin(phi)>} | |
3511 | Double_t sumOfWW3 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(3); // W_{<cos(phi)>} * W_{<sin(phi)>} | |
3512 | // numerator in the expression for the the unbiased estimator for covariance: | |
3513 | Double_t numerator3 = product3 - term1st3*term2nd3; | |
3514 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 3515 | Double_t denominator3 = 0; |
3516 | if(TMath::Abs(sumOfW1st3*sumOfW2nd3)>0.) | |
3517 | { | |
3518 | denominator3 = 1.-sumOfWW3/(sumOfW1st3*sumOfW2nd3); | |
3519 | if(TMath::Abs(denominator3)>0.) | |
3520 | { | |
3521 | // covariance: | |
3522 | Double_t covariance3 = numerator3/denominator3; | |
3523 | // weight dependent prefactor for covariance: | |
3524 | Double_t wPrefactor3 = sumOfWW3/(sumOfW1st3*sumOfW2nd3); | |
3525 | // finally, store "weighted" covariance: | |
3526 | fIntFlowCovariancesNUA->SetBinContent(3,wPrefactor3*covariance3); | |
3527 | } // end of if(TMath::Abs(denominator3)>0.) | |
3528 | } // end of if(TMath::Abs(sumOfW1st3*sumOfW2nd3)>0.) | |
0328db2d | 3529 | |
3530 | // Cov(<2>,<cos(phi1+phi2)>): | |
3531 | Double_t product4 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(4); // <<2><cos(phi1+phi2)>> | |
3532 | Double_t term1st4 = fIntFlowCorrelationsPro->GetBinContent(1); // <<2>> | |
3533 | Double_t term2nd4 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(2); // <<cos(phi1+phi2)>> | |
3534 | Double_t sumOfW1st4 = fIntFlowSumOfEventWeights[0]->GetBinContent(1); // W_{<2>} | |
3535 | Double_t sumOfW2nd4 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(2); // W_{<cos(phi1+phi2)>} | |
3536 | Double_t sumOfWW4 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(4); // W_{<2>} * W_{<cos(phi1+phi2)>} | |
3537 | // numerator in the expression for the the unbiased estimator for covariance: | |
3538 | Double_t numerator4 = product4 - term1st4*term2nd4; | |
3539 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 3540 | Double_t denominator4 = 0.; |
3541 | if(TMath::Abs(sumOfW1st4*sumOfW2nd4)>0.) | |
3542 | { | |
3543 | denominator4 = 1.-sumOfWW4/(sumOfW1st4*sumOfW2nd4); | |
3544 | if(TMath::Abs(denominator4)>0.) | |
3545 | { | |
3546 | // covariance: | |
3547 | Double_t covariance4 = numerator4/denominator4; | |
3548 | // weight dependent prefactor for covariance: | |
3549 | Double_t wPrefactor4 = sumOfWW4/(sumOfW1st4*sumOfW2nd4); | |
3550 | // finally, store "weighted" covariance: | |
3551 | fIntFlowCovariancesNUA->SetBinContent(4,wPrefactor4*covariance4); | |
3552 | } // end of if(TMath::Abs(denominator4)>0.) | |
3553 | } // end of if(TMath::Abs(sumOfW1st4*sumOfW2nd4)>0.) | |
3554 | ||
0328db2d | 3555 | // Cov(<2>,<sin(phi1+phi2)>): |
3556 | Double_t product5 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(5); // <<2><sin(phi1+phi2)>> | |
3557 | Double_t term1st5 = fIntFlowCorrelationsPro->GetBinContent(1); // <<2>> | |
3558 | Double_t term2nd5 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(2); // <<sin(phi1+phi2)>> | |
3559 | Double_t sumOfW1st5 = fIntFlowSumOfEventWeights[0]->GetBinContent(1); // W_{<2>} | |
3560 | Double_t sumOfW2nd5 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(2); // W_{<sin(phi1+phi2)>} | |
3561 | Double_t sumOfWW5 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(5); // W_{<2>} * W_{<sin(phi1+phi2)>} | |
3562 | // numerator in the expression for the the unbiased estimator for covariance: | |
3563 | Double_t numerator5 = product5 - term1st5*term2nd5; | |
3564 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 3565 | Double_t denominator5 = 0.; |
3566 | if(TMath::Abs(sumOfW1st5*sumOfW2nd5)>0.) | |
3567 | { | |
3568 | denominator5 = 1.-sumOfWW5/(sumOfW1st5*sumOfW2nd5); | |
3569 | if(TMath::Abs(denominator5)>0.) | |
3570 | { | |
3571 | // covariance: | |
3572 | Double_t covariance5 = numerator5/denominator5; | |
3573 | // weight dependent prefactor for covariance: | |
3574 | Double_t wPrefactor5 = sumOfWW5/(sumOfW1st5*sumOfW2nd5); | |
3575 | // finally, store "weighted" covariance: | |
3576 | fIntFlowCovariancesNUA->SetBinContent(5,wPrefactor5*covariance5); | |
3577 | } // end of if(TMath::Abs(denominator5)>0.) | |
3578 | } // end of if(TMath::Abs(sumOfW1st5*sumOfW2nd5)>0.) | |
3579 | ||
0328db2d | 3580 | // Cov(<2>,<cos(phi1-phi2-phi3)>): |
3581 | Double_t product6 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(6); // <<2><cos(phi1-phi2-phi3)>> | |
3582 | Double_t term1st6 = fIntFlowCorrelationsPro->GetBinContent(1); // <<2>> | |
3583 | Double_t term2nd6 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(3); // <<cos(phi1-phi2-phi3)>> | |
3584 | Double_t sumOfW1st6 = fIntFlowSumOfEventWeights[0]->GetBinContent(1); // W_{<2>} | |
3585 | Double_t sumOfW2nd6 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(3); // W_{<cos(phi1-phi2-phi3)>} | |
3586 | Double_t sumOfWW6 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(6); // W_{<2>} * W_{<cos(phi1-phi2-phi3)>} | |
3587 | // numerator in the expression for the the unbiased estimator for covariance: | |
3588 | Double_t numerator6 = product6 - term1st6*term2nd6; | |
3589 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 3590 | Double_t denominator6 = 0.; |
3591 | if(TMath::Abs(sumOfW1st6*sumOfW2nd6)>0.) | |
3592 | { | |
3593 | denominator6 = 1.-sumOfWW6/(sumOfW1st6*sumOfW2nd6); | |
3594 | if(TMath::Abs(denominator6)>0.) | |
3595 | { | |
3596 | // covariance: | |
3597 | Double_t covariance6 = numerator6/denominator6; | |
3598 | // weight dependent prefactor for covariance: | |
3599 | Double_t wPrefactor6 = sumOfWW6/(sumOfW1st6*sumOfW2nd6); | |
3600 | // finally, store "weighted" covariance: | |
3601 | fIntFlowCovariancesNUA->SetBinContent(6,wPrefactor6*covariance6); | |
3602 | } // end of if(TMath::Abs(denominator6)>0.) | |
3603 | } // end of if(TMath::Abs(sumOfW1st6*sumOfW2nd6)>0.) | |
3604 | ||
0328db2d | 3605 | // Cov(<2>,<sin(phi1-phi2-phi3)>): |
3606 | Double_t product7 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(7); // <<2><sin(phi1-phi2-phi3)>> | |
3607 | Double_t term1st7 = fIntFlowCorrelationsPro->GetBinContent(1); // <<2>> | |
3608 | Double_t term2nd7 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(3); // <<sin(phi1-phi2-phi3)>> | |
3609 | Double_t sumOfW1st7 = fIntFlowSumOfEventWeights[0]->GetBinContent(1); // W_{<2>} | |
3610 | Double_t sumOfW2nd7 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(3); // W_{<sin(phi1-phi2-phi3)>} | |
3611 | Double_t sumOfWW7 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(7); // W_{<2>} * W_{<sin(phi1-phi2-phi3)>} | |
3612 | // numerator in the expression for the the unbiased estimator for covariance: | |
3613 | Double_t numerator7 = product7 - term1st7*term2nd7; | |
3614 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 3615 | Double_t denominator7 = 0.; |
3616 | if(TMath::Abs(sumOfW1st7*sumOfW2nd7)>0.) | |
3617 | { | |
3618 | denominator7 = 1.-sumOfWW7/(sumOfW1st7*sumOfW2nd7); | |
3619 | if(TMath::Abs(denominator7)>0.) | |
3620 | { | |
3621 | // covariance: | |
3622 | Double_t covariance7 = numerator7/denominator7; | |
3623 | // weight dependent prefactor for covariance: | |
3624 | Double_t wPrefactor7 = sumOfWW7/(sumOfW1st7*sumOfW2nd7); | |
3625 | // finally, store "weighted" covariance: | |
3626 | fIntFlowCovariancesNUA->SetBinContent(7,wPrefactor7*covariance7); | |
3627 | } // end of if(TMath::Abs(denominator7)>0.) | |
3628 | } // end of if(TMath::Abs(sumOfW1st7*sumOfW2nd7)>0.) | |
3629 | ||
0328db2d | 3630 | // Cov(<4>,<cos(phi1>): |
3631 | Double_t product8 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(8); // <<4><cos(phi1)>> | |
3632 | Double_t term1st8 = fIntFlowCorrelationsPro->GetBinContent(2); // <<4>> | |
3633 | Double_t term2nd8 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(1); // <<cos(phi1)>> | |
3634 | Double_t sumOfW1st8 = fIntFlowSumOfEventWeights[0]->GetBinContent(2); // W_{<4>} | |
3635 | Double_t sumOfW2nd8 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(1); // W_{<cos(phi1)>} | |
3636 | Double_t sumOfWW8 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(8); // W_{<4>} * W_{<cos(phi1)>} | |
3637 | // numerator in the expression for the the unbiased estimator for covariance: | |
3638 | Double_t numerator8 = product8 - term1st8*term2nd8; | |
3639 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 3640 | Double_t denominator8 = 0.; |
3641 | if(TMath::Abs(sumOfW1st8*sumOfW2nd8)>0.) | |
3642 | { | |
3643 | denominator8 = 1.-sumOfWW8/(sumOfW1st8*sumOfW2nd8); | |
3644 | if(TMath::Abs(denominator8)>0.) | |
3645 | { | |
3646 | // covariance: | |
3647 | Double_t covariance8 = numerator8/denominator8; | |
3648 | // weight dependent prefactor for covariance: | |
3649 | Double_t wPrefactor8 = sumOfWW8/(sumOfW1st8*sumOfW2nd8); | |
3650 | // finally, store "weighted" covariance: | |
3651 | fIntFlowCovariancesNUA->SetBinContent(8,wPrefactor8*covariance8); | |
3652 | } // end of if(TMath::Abs(denominator8)>0.) | |
3653 | } // end of if(TMath::Abs(sumOfW1st8*sumOfW2nd8)>0.) | |
3654 | ||
0328db2d | 3655 | // Cov(<4>,<sin(phi1)>): |
3656 | Double_t product9 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(9); // <<4><sin(phi1)>> | |
3657 | Double_t term1st9 = fIntFlowCorrelationsPro->GetBinContent(2); // <<4>> | |
3658 | Double_t term2nd9 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(1); // <<sin(phi1)>> | |
3659 | Double_t sumOfW1st9 = fIntFlowSumOfEventWeights[0]->GetBinContent(2); // W_{<4>} | |
3660 | Double_t sumOfW2nd9 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(1); // W_{<sin(phi1)>} | |
3661 | Double_t sumOfWW9 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(9); // W_{<4>} * W_{<sin(phi1)>} | |
3662 | // numerator in the expression for the the unbiased estimator for covariance: | |
3663 | Double_t numerator9 = product9 - term1st9*term2nd9; | |
3664 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 3665 | Double_t denominator9 = 0.; |
3666 | if(TMath::Abs(sumOfW1st9*sumOfW2nd9)>0.) | |
3667 | { | |
3668 | denominator9 = 1.-sumOfWW9/(sumOfW1st9*sumOfW2nd9); | |
3669 | if(TMath::Abs(denominator9)>0.) | |
3670 | { | |
3671 | // covariance: | |
3672 | Double_t covariance9 = numerator9/denominator9; | |
3673 | // weight dependent prefactor for covariance: | |
3674 | Double_t wPrefactor9 = sumOfWW9/(sumOfW1st9*sumOfW2nd9); | |
3675 | // finally, store "weighted" covariance: | |
3676 | fIntFlowCovariancesNUA->SetBinContent(9,wPrefactor9*covariance9); | |
3677 | } | |
3678 | } // end of if(TMath::Abs(sumOfW1st9*sumOfW2nd9)>0.) | |
3679 | ||
0328db2d | 3680 | // Cov(<4>,<cos(phi1+phi2)>): |
3681 | Double_t product10 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(10); // <<4><cos(phi1+phi2)>> | |
3682 | Double_t term1st10 = fIntFlowCorrelationsPro->GetBinContent(2); // <<4>> | |
3683 | Double_t term2nd10 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(2); // <<cos(phi1+phi2)>> | |
3684 | Double_t sumOfW1st10 = fIntFlowSumOfEventWeights[0]->GetBinContent(2); // W_{<4>} | |
3685 | Double_t sumOfW2nd10 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(2); // W_{<cos(phi1+phi2)>} | |
3686 | Double_t sumOfWW10 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(10); // W_{<4>} * W_{<cos(phi1+phi2)>} | |
3687 | // numerator in the expression for the the unbiased estimator for covariance: | |
3688 | Double_t numerator10 = product10 - term1st10*term2nd10; | |
3689 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 3690 | Double_t denominator10 = 0.; |
3691 | if(TMath::Abs(sumOfW1st10*sumOfW2nd10)>0.) | |
3692 | { | |
3693 | denominator10 = 1.-sumOfWW10/(sumOfW1st10*sumOfW2nd10); | |
3694 | if(TMath::Abs(denominator10)>0.) | |
3695 | { | |
3696 | // covariance: | |
3697 | Double_t covariance10 = numerator10/denominator10; | |
3698 | // weight dependent prefactor for covariance: | |
3699 | Double_t wPrefactor10 = sumOfWW10/(sumOfW1st10*sumOfW2nd10); | |
3700 | // finally, store "weighted" covariance: | |
3701 | fIntFlowCovariancesNUA->SetBinContent(10,wPrefactor10*covariance10); | |
3702 | } // end of if(TMath::Abs(denominator10)>0.) | |
3703 | } // end of if(TMath::Abs(sumOfW1st10*sumOfW2nd10)>0.) | |
3704 | ||
0328db2d | 3705 | // Cov(<4>,<sin(phi1+phi2)>): |
3706 | Double_t product11 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(11); // <<4><sin(phi1+phi2)>> | |
3707 | Double_t term1st11 = fIntFlowCorrelationsPro->GetBinContent(2); // <<4>> | |
3708 | Double_t term2nd11 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(2); // <<sin(phi1+phi2)>> | |
3709 | Double_t sumOfW1st11 = fIntFlowSumOfEventWeights[0]->GetBinContent(2); // W_{<4>} | |
3710 | Double_t sumOfW2nd11 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(2); // W_{<sin(phi1+phi2)>} | |
3711 | Double_t sumOfWW11 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(11); // W_{<4>} * W_{<sin(phi1+phi2)>} | |
3712 | // numerator in the expression for the the unbiased estimator for covariance: | |
3713 | Double_t numerator11 = product11 - term1st11*term2nd11; | |
3714 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 3715 | Double_t denominator11 = 0.; |
3716 | if(TMath::Abs(sumOfW1st11*sumOfW2nd11)>0.) | |
3717 | { | |
3718 | denominator11 = 1.-sumOfWW11/(sumOfW1st11*sumOfW2nd11); | |
3719 | if(TMath::Abs(denominator11)>0.) | |
3720 | { | |
3721 | // covariance: | |
3722 | Double_t covariance11 = numerator11/denominator11; | |
3723 | // weight dependent prefactor for covariance: | |
3724 | Double_t wPrefactor11 = sumOfWW11/(sumOfW1st11*sumOfW2nd11); | |
3725 | // finally, store "weighted" covariance: | |
3726 | fIntFlowCovariancesNUA->SetBinContent(11,wPrefactor11*covariance11); | |
3727 | } // end of if(TMath::Abs(denominator11)>0.) | |
3728 | } // end of if(TMath::Abs(sumOfW1st11*sumOfW2nd11)>0.) | |
0328db2d | 3729 | |
3730 | // Cov(<4>,<cos(phi1-phi2-phi3)>): | |
3731 | Double_t product12 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(12); // <<4><cos(phi1-phi2-phi3)>> | |
3732 | Double_t term1st12 = fIntFlowCorrelationsPro->GetBinContent(2); // <<4>> | |
3733 | Double_t term2nd12 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(3); // <<cos(phi1-phi2-phi3)>> | |
3734 | Double_t sumOfW1st12 = fIntFlowSumOfEventWeights[0]->GetBinContent(2); // W_{<4>} | |
3735 | Double_t sumOfW2nd12 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(3); // W_{<cos(phi1-phi2-phi3)>} | |
3736 | Double_t sumOfWW12 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(12); // W_{<4>} * W_{<cos(phi1-phi2-phi3)>} | |
3737 | // numerator in the expression for the the unbiased estimator for covariance: | |
3738 | Double_t numerator12 = product12 - term1st12*term2nd12; | |
3739 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 3740 | Double_t denominator12 = 0.; |
3741 | if(TMath::Abs(sumOfW1st12*sumOfW2nd12)>0.) | |
3742 | { | |
3743 | denominator12 = 1.-sumOfWW12/(sumOfW1st12*sumOfW2nd12); | |
3744 | if(TMath::Abs(denominator12)>0.) | |
3745 | { | |
3746 | // covariance: | |
3747 | Double_t covariance12 = numerator12/denominator12; | |
3748 | // weight dependent prefactor for covariance: | |
3749 | Double_t wPrefactor12 = sumOfWW12/(sumOfW1st12*sumOfW2nd12); | |
3750 | // finally, store "weighted" covariance: | |
3751 | fIntFlowCovariancesNUA->SetBinContent(12,wPrefactor12*covariance12); | |
3752 | } // end of if(TMath::Abs(denominator12)>0.) | |
3753 | } // end of if(TMath::Abs(sumOfW1st12*sumOfW2nd12)>0.) | |
0328db2d | 3754 | |
3755 | // Cov(<4>,<sin(phi1-phi2-phi3)>): | |
3756 | Double_t product13 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(13); // <<4><sin(phi1-phi2-phi3)>> | |
3757 | Double_t term1st13 = fIntFlowCorrelationsPro->GetBinContent(2); // <<4>> | |
3758 | Double_t term2nd13 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(3); // <<sin(phi1-phi2-phi3)>> | |
3759 | Double_t sumOfW1st13 = fIntFlowSumOfEventWeights[0]->GetBinContent(2); // W_{<4>} | |
3760 | Double_t sumOfW2nd13 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(3); // W_{<sin(phi1-phi2-phi3)>} | |
3761 | Double_t sumOfWW13 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(13); // W_{<4>} * W_{<sin(phi1-phi2-phi3)>} | |
3762 | // numerator in the expression for the the unbiased estimator for covariance: | |
3763 | Double_t numerator13 = product13 - term1st13*term2nd13; | |
3764 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 3765 | Double_t denominator13 = 0.; |
3766 | if(TMath::Abs(sumOfW1st13*sumOfW2nd13)>0.) | |
3767 | { | |
3768 | denominator13 = 1.-sumOfWW13/(sumOfW1st13*sumOfW2nd13); | |
3769 | if(TMath::Abs(denominator13)>0.) | |
3770 | { | |
3771 | // covariance: | |
3772 | Double_t covariance13 = numerator13/denominator13; | |
3773 | // weight dependent prefactor for covariance: | |
3774 | Double_t wPrefactor13 = sumOfWW13/(sumOfW1st13*sumOfW2nd13); | |
3775 | // finally, store "weighted" covariance: | |
3776 | fIntFlowCovariancesNUA->SetBinContent(13,wPrefactor13*covariance13); | |
3777 | } // end of if(TMath::Abs(denominator13)>0.) | |
3778 | } // end of if(TMath::Abs(sumOfW1st13*sumOfW2nd13)>0.) | |
0328db2d | 3779 | |
3780 | // Cov(<cos(phi1)>,<cos(phi1+phi2)>): | |
3781 | Double_t product14 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(14); // <<cos(phi1)><cos(phi1+phi2)>> | |
3782 | Double_t term1st14 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(1); // <<cos(phi1)>> | |
3783 | Double_t term2nd14 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(2); // <<cos(phi1+phi2)>> | |
3784 | Double_t sumOfW1st14 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(1); // W_{<cos(phi1)>} | |
3785 | Double_t sumOfW2nd14 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(2); // W_{<cos(phi1+phi2)>} | |
3786 | Double_t sumOfWW14 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(14); // W_{<cos(phi1)>} * W_{<cos(phi1+phi2)>} | |
3787 | // numerator in the expression for the the unbiased estimator for covariance: | |
3788 | Double_t numerator14 = product14 - term1st14*term2nd14; | |
3789 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 3790 | Double_t denominator14 = 0.; |
3791 | if(TMath::Abs(sumOfW1st14*sumOfW2nd14)>0.) | |
3792 | { | |
3793 | denominator14 = 1.-sumOfWW14/(sumOfW1st14*sumOfW2nd14); | |
3794 | if(TMath::Abs(denominator14)>0.) | |
3795 | { | |
3796 | // covariance: | |
3797 | Double_t covariance14 = numerator14/denominator14; | |
3798 | // weight dependent prefactor for covariance: | |
3799 | Double_t wPrefactor14 = sumOfWW14/(sumOfW1st14*sumOfW2nd14); | |
3800 | // finally, store "weighted" covariance: | |
3801 | fIntFlowCovariancesNUA->SetBinContent(14,wPrefactor14*covariance14); | |
3802 | } // end of if(TMath::Abs(denominator14)>0.) | |
3803 | } // end of if(TMath::Abs(sumOfW1st14*sumOfW2nd14)>0.) | |
0328db2d | 3804 | |
3805 | // Cov(<cos(phi1)>,<sin(phi1+phi2)>): | |
3806 | Double_t product15 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(15); // <<cos(phi1)><sin(phi1+phi2)>> | |
3807 | Double_t term1st15 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(1); // <<cos(phi1)>> | |
3808 | Double_t term2nd15 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(2); // <<sin(phi1+phi2)>> | |
3809 | Double_t sumOfW1st15 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(1); // W_{<cos(phi1)>} | |
3810 | Double_t sumOfW2nd15 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(2); // W_{<sin(phi1+phi2)>} | |
3811 | Double_t sumOfWW15 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(15); // W_{<cos(phi1)>} * W_{<sin(phi1+phi2)>} | |
3812 | // numerator in the expression for the the unbiased estimator for covariance: | |
3813 | Double_t numerator15 = product15 - term1st15*term2nd15; | |
3814 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 3815 | Double_t denominator15 = 0.; |
3816 | if(TMath::Abs(sumOfW1st15*sumOfW2nd15)>0.) | |
3817 | { | |
3818 | denominator15 = 1.-sumOfWW15/(sumOfW1st15*sumOfW2nd15); | |
3819 | if(TMath::Abs(denominator15)>0.) | |
3820 | { | |
3821 | // covariance: | |
3822 | Double_t covariance15 = numerator15/denominator15; | |
3823 | // weight dependent prefactor for covariance: | |
3824 | Double_t wPrefactor15 = sumOfWW15/(sumOfW1st15*sumOfW2nd15); | |
3825 | // finally, store "weighted" covariance: | |
3826 | fIntFlowCovariancesNUA->SetBinContent(15,wPrefactor15*covariance15); | |
3827 | } // end of if(TMath::Abs(denominator15)>0.) | |
3828 | } // end of if(TMath::Abs(sumOfW1st15*sumOfW2nd15)>0.) | |
3829 | ||
0328db2d | 3830 | // Cov(<cos(phi1)>,<cos(phi1-phi2-phi3)>): |
3831 | Double_t product16 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(16); // <<cos(phi1)><cos(phi1-phi2-phi3)>> | |
3832 | Double_t term1st16 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(1); // <<cos(phi1)>> | |
3833 | Double_t term2nd16 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(3); // <<cos(phi1-phi2-phi3)>> | |
3834 | Double_t sumOfW1st16 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(1); // W_{<cos(phi1)>} | |
3835 | Double_t sumOfW2nd16 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(3); // W_{<cos(phi1-phi2-phi3)>} | |
3836 | Double_t sumOfWW16 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(16); // W_{<cos(phi1)>} * W_{<cos(phi1-phi2-phi3)>} | |
3837 | // numerator in the expression for the the unbiased estimator for covariance: | |
3838 | Double_t numerator16 = product16 - term1st16*term2nd16; | |
3839 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 3840 | Double_t denominator16 = 0.; |
3841 | if(TMath::Abs(sumOfW1st16*sumOfW2nd16)>0.) | |
3842 | { | |
3843 | denominator16 = 1.-sumOfWW16/(sumOfW1st16*sumOfW2nd16); | |
3844 | if(TMath::Abs(denominator16)>0.) | |
3845 | { | |
3846 | // covariance: | |
3847 | Double_t covariance16 = numerator16/denominator16; | |
3848 | // weight dependent prefactor for covariance: | |
3849 | Double_t wPrefactor16 = sumOfWW16/(sumOfW1st16*sumOfW2nd16); | |
3850 | // finally, store "weighted" covariance: | |
3851 | fIntFlowCovariancesNUA->SetBinContent(16,wPrefactor16*covariance16); | |
3852 | } // end of if(TMath::Abs(denominator16)>0.) | |
3853 | } // end ofif(TMath::Abs(sumOfW1st16*sumOfW2nd16)>0.) | |
3854 | ||
0328db2d | 3855 | // Cov(<cos(phi1)>,<sin(phi1-phi2-phi3)>): |
3856 | Double_t product17 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(17); // <<cos(phi1)><sin(phi1-phi2-phi3)>> | |
3857 | Double_t term1st17 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(1); // <<cos(phi1)>> | |
3858 | Double_t term2nd17 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(3); // <<sin(phi1-phi2-phi3)>> | |
3859 | Double_t sumOfW1st17 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(1); // W_{<cos(phi1)>} | |
3860 | Double_t sumOfW2nd17 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(3); // W_{<sin(phi1-phi2-phi3)>} | |
3861 | Double_t sumOfWW17 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(17); // W_{<cos(phi1)>} * W_{<sin(phi1-phi2-phi3)>} | |
3862 | // numerator in the expression for the the unbiased estimator for covariance: | |
3863 | Double_t numerator17 = product17 - term1st17*term2nd17; | |
3864 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 3865 | Double_t denominator17 = 0.; |
3866 | if(TMath::Abs(sumOfW1st17*sumOfW2nd17)>0.) | |
3867 | { | |
3868 | denominator17 = 1.-sumOfWW17/(sumOfW1st17*sumOfW2nd17); | |
3869 | if(TMath::Abs(denominator17)>0.) | |
3870 | { | |
3871 | // covariance: | |
3872 | Double_t covariance17 = numerator17/denominator17; | |
3873 | // weight dependent prefactor for covariance: | |
3874 | Double_t wPrefactor17 = sumOfWW17/(sumOfW1st17*sumOfW2nd17); | |
3875 | // finally, store "weighted" covariance: | |
3876 | fIntFlowCovariancesNUA->SetBinContent(17,wPrefactor17*covariance17); | |
3877 | } // end of if(TMath::Abs(denominator17)>0.) | |
3878 | } // end of if(TMath::Abs(sumOfW1st17*sumOfW2nd17)>0.) | |
0328db2d | 3879 | |
3880 | // Cov(<sin(phi1)>,<cos(phi1+phi2)>): | |
3881 | Double_t product18 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(18); // <<sin(phi1)><cos(phi1+phi2)>> | |
3882 | Double_t term1st18 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(1); // <<sin(phi1)>> | |
3883 | Double_t term2nd18 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(2); // <<cos(phi1+phi2)>> | |
3884 | Double_t sumOfW1st18 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(1); // W_{<sin(phi1)>} | |
3885 | Double_t sumOfW2nd18 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(2); // W_{<cos(phi1+phi2)>} | |
3886 | Double_t sumOfWW18 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(18); // W_{<sin(phi1)>} * W_{<cos(phi1+phi2)>} | |
3887 | // numerator in the expression for the the unbiased estimator for covariance: | |
3888 | Double_t numerator18 = product18 - term1st18*term2nd18; | |
3889 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 3890 | Double_t denominator18 = 0.; |
3891 | if(TMath::Abs(sumOfW1st18*sumOfW2nd18)>0.) | |
3892 | { | |
3893 | denominator18 = 1.-sumOfWW18/(sumOfW1st18*sumOfW2nd18); | |
3894 | if(TMath::Abs(denominator18)>0.) | |
3895 | { | |
3896 | // covariance: | |
3897 | Double_t covariance18 = numerator18/denominator18; | |
3898 | // weight dependent prefactor for covariance: | |
3899 | Double_t wPrefactor18 = sumOfWW18/(sumOfW1st18*sumOfW2nd18); | |
3900 | // finally, store "weighted" covariance: | |
3901 | fIntFlowCovariancesNUA->SetBinContent(18,wPrefactor18*covariance18); | |
3902 | } // end of if(TMath::Abs(denominator18)>0.) | |
3903 | } // end of if(TMath::Abs(sumOfW1st18*sumOfW2nd18)>0.) | |
0328db2d | 3904 | |
3905 | // Cov(<sin(phi1)>,<sin(phi1+phi2)>): | |
3906 | Double_t product19 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(19); // <<sin(phi1)><sin(phi1+phi2)>> | |
3907 | Double_t term1st19 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(1); // <<sin(phi1)>> | |
3908 | Double_t term2nd19 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(2); // <<sin(phi1+phi2)>> | |
3909 | Double_t sumOfW1st19 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(1); // W_{<sin(phi1)>} | |
3910 | Double_t sumOfW2nd19 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(2); // W_{<sin(phi1+phi2)>} | |
3911 | Double_t sumOfWW19 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(19); // W_{<sin(phi1)>} * W_{<sin(phi1+phi2)>} | |
3912 | // numerator in the expression for the the unbiased estimator for covariance: | |
3913 | Double_t numerator19 = product19 - term1st19*term2nd19; | |
3914 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 3915 | Double_t denominator19 = 0.; |
3916 | if(TMath::Abs(sumOfW1st19*sumOfW2nd19)>0.) | |
3917 | { | |
3918 | denominator19 = 1.-sumOfWW19/(sumOfW1st19*sumOfW2nd19); | |
3919 | if(TMath::Abs(denominator19)>0.) | |
3920 | { | |
3921 | // covariance: | |
3922 | Double_t covariance19 = numerator19/denominator19; | |
3923 | // weight dependent prefactor for covariance: | |
3924 | Double_t wPrefactor19 = sumOfWW19/(sumOfW1st19*sumOfW2nd19); | |
3925 | // finally, store "weighted" covariance: | |
3926 | fIntFlowCovariancesNUA->SetBinContent(19,wPrefactor19*covariance19); | |
3927 | } // end of if(TMath::Abs(denominator19)>0.) | |
3928 | } // end of if(TMath::Abs(sumOfW1st19*sumOfW2nd19)>0.) | |
3929 | ||
0328db2d | 3930 | // Cov(<sin(phi1)>,<cos(phi1-phi2-phi3)>): |
3931 | Double_t product20 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(20); // <<sin(phi1)><cos(phi1-phi2-phi3)>> | |
3932 | Double_t term1st20 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(1); // <<sin(phi1)>> | |
3933 | Double_t term2nd20 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(3); // <<cos(phi1-phi2-phi3)>> | |
3934 | Double_t sumOfW1st20 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(1); // W_{<sin(phi1)>} | |
3935 | Double_t sumOfW2nd20 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(3); // W_{<cos(phi1-phi2-phi3)>} | |
3936 | Double_t sumOfWW20 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(20); // W_{<sin(phi1)>} * W_{<cos(phi1-phi2-phi3)>} | |
3937 | // numerator in the expression for the the unbiased estimator for covariance: | |
3938 | Double_t numerator20 = product20 - term1st20*term2nd20; | |
3939 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 3940 | Double_t denominator20 = 0.; |
3941 | if(TMath::Abs(sumOfW1st20*sumOfW2nd20)>0.) | |
3942 | { | |
3943 | denominator20 = 1.-sumOfWW20/(sumOfW1st20*sumOfW2nd20); | |
3944 | if(TMath::Abs(denominator20)>0.) | |
3945 | { | |
3946 | // covariance: | |
3947 | Double_t covariance20 = numerator20/denominator20; | |
3948 | // weight dependent prefactor for covariance: | |
3949 | Double_t wPrefactor20 = sumOfWW20/(sumOfW1st20*sumOfW2nd20); | |
3950 | // finally, store "weighted" covariance: | |
3951 | fIntFlowCovariancesNUA->SetBinContent(20,wPrefactor20*covariance20); | |
3952 | } // end of if(TMath::Abs(denominator20)>0.) | |
3953 | } // end of if(TMath::Abs(sumOfW1st20*sumOfW2nd20)>0.) | |
0328db2d | 3954 | |
3955 | // Cov(<sin(phi1)>,<sin(phi1-phi2-phi3)>): | |
3956 | Double_t product21 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(21); // <<sin(phi1)><sin(phi1-phi2-phi3)>> | |
3957 | Double_t term1st21 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(1); // <<sin(phi1)>> | |
3958 | Double_t term2nd21 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(3); // <<sin(phi1-phi2-phi3)>> | |
3959 | Double_t sumOfW1st21 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(1); // W_{<sin(phi1)>} | |
3960 | Double_t sumOfW2nd21 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(3); // W_{<sin(phi1-phi2-phi3)>} | |
3961 | Double_t sumOfWW21 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(21); // W_{<sin(phi1)>} * W_{<sin(phi1-phi2-phi3)>} | |
3962 | // numerator in the expression for the the unbiased estimator for covariance: | |
3963 | Double_t numerator21 = product21 - term1st21*term2nd21; | |
3964 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 3965 | Double_t denominator21 = 0.; |
3966 | if(TMath::Abs(sumOfW1st21*sumOfW2nd21)>0.) | |
3967 | { | |
3968 | denominator21 = 1.-sumOfWW21/(sumOfW1st21*sumOfW2nd21); | |
3969 | if(TMath::Abs(denominator21)>0.) | |
3970 | { | |
3971 | // covariance: | |
3972 | Double_t covariance21 = numerator21/denominator21; | |
3973 | // weight dependent prefactor for covariance: | |
3974 | Double_t wPrefactor21 = sumOfWW21/(sumOfW1st21*sumOfW2nd21); | |
3975 | // finally, store "weighted" covariance: | |
3976 | fIntFlowCovariancesNUA->SetBinContent(21,wPrefactor21*covariance21); | |
3977 | } // end of if(TMath::Abs(denominator21)>0.) | |
3978 | } // end of if(TMath::Abs(sumOfW1st21*sumOfW2nd21)>0.) | |
0328db2d | 3979 | |
3980 | // Cov(<cos(phi1+phi2)>,<sin(phi1+phi2)>): | |
3981 | Double_t product22 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(22); // <<cos(phi1+phi2)><sin(phi1+phi2)>> | |
3982 | Double_t term1st22 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(2); // <<cos(phi1+phi2)>> | |
3983 | Double_t term2nd22 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(2); // <<sin(phi1+phi2)>> | |
3984 | Double_t sumOfW1st22 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(2); // W_{<cos(phi1+phi2)>} | |
3985 | Double_t sumOfW2nd22 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(2); // W_{<sin(phi1+phi2)>} | |
3986 | Double_t sumOfWW22 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(22); // W_{<cos(phi1+phi2)>} * W_{<sin(phi1+phi2)>} | |
3987 | // numerator in the expression for the the unbiased estimator for covariance: | |
3988 | Double_t numerator22 = product22 - term1st22*term2nd22; | |
3989 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 3990 | Double_t denominator22 = 0.; |
3991 | if(TMath::Abs(sumOfW1st22*sumOfW2nd22)>0.) | |
3992 | { | |
3993 | denominator22 = 1.-sumOfWW22/(sumOfW1st22*sumOfW2nd22); | |
3994 | if(TMath::Abs(denominator22)>0.) | |
3995 | { | |
3996 | // covariance: | |
3997 | Double_t covariance22 = numerator22/denominator22; | |
3998 | // weight dependent prefactor for covariance: | |
3999 | Double_t wPrefactor22 = sumOfWW22/(sumOfW1st22*sumOfW2nd22); | |
4000 | // finally, store "weighted" covariance: | |
4001 | fIntFlowCovariancesNUA->SetBinContent(22,wPrefactor22*covariance22); | |
4002 | } // end of if(TMath::Abs(denominator22)>0.) | |
4003 | } // end of if(TMath::Abs(sumOfW1st22*sumOfW2nd22)>0.) | |
0328db2d | 4004 | |
4005 | // Cov(<cos(phi1+phi2)>,<cos(phi1-phi2-phi3)>): | |
4006 | Double_t product23 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(23); // <<cos(phi1+phi2)><cos(phi1-phi2-phi3)>> | |
4007 | Double_t term1st23 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(2); // <<cos(phi1+phi2)>> | |
4008 | Double_t term2nd23 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(3); // <<cos(phi1-phi2-phi3)>> | |
4009 | Double_t sumOfW1st23 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(2); // W_{<cos(phi1+phi2)>} | |
4010 | Double_t sumOfW2nd23 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(3); // W_{<cos(phi1-phi2-phi3)>} | |
4011 | Double_t sumOfWW23 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(23); // W_{<cos(phi1+phi2)>} * W_{<cos(phi1-phi2-phi3)>} | |
4012 | // numerator in the expression for the the unbiased estimator for covariance: | |
4013 | Double_t numerator23 = product23 - term1st23*term2nd23; | |
4014 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 4015 | Double_t denominator23 = 0.; |
4016 | if(TMath::Abs(sumOfW1st23*sumOfW2nd23)>0.) | |
4017 | { | |
4018 | denominator23 = 1.-sumOfWW23/(sumOfW1st23*sumOfW2nd23); | |
4019 | if(TMath::Abs(denominator23)>0.) | |
4020 | { | |
4021 | // covariance: | |
4022 | Double_t covariance23 = numerator23/denominator23; | |
4023 | // weight dependent prefactor for covariance: | |
4024 | Double_t wPrefactor23 = sumOfWW23/(sumOfW1st23*sumOfW2nd23); | |
4025 | // finally, store "weighted" covariance: | |
4026 | fIntFlowCovariancesNUA->SetBinContent(23,wPrefactor23*covariance23); | |
4027 | } // end of if(TMath::Abs(denominator23)>0.) | |
4028 | } // end of if(TMath::Abs(sumOfW1st23*sumOfW2nd23)>0.) | |
4029 | ||
0328db2d | 4030 | // Cov(<cos(phi1+phi2)>,<sin(phi1-phi2-phi3)>): |
4031 | Double_t product24 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(24); // <<cos(phi1+phi2)><sin(phi1-phi2-phi3)>> | |
4032 | Double_t term1st24 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(2); // <<cos(phi1+phi2)>> | |
4033 | Double_t term2nd24 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(3); // <<sin(phi1-phi2-phi3)>> | |
4034 | Double_t sumOfW1st24 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(2); // W_{<cos(phi1+phi2)>} | |
4035 | Double_t sumOfW2nd24 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(3); // W_{<sin(phi1-phi2-phi3)>} | |
4036 | Double_t sumOfWW24 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(24); // W_{<cos(phi1+phi2)>} * W_{<sin(phi1-phi2-phi3)>} | |
4037 | // numerator in the expression for the the unbiased estimator for covariance: | |
4038 | Double_t numerator24 = product24 - term1st24*term2nd24; | |
4039 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 4040 | Double_t denominator24 = 0.; |
4041 | if(TMath::Abs(sumOfW1st24*sumOfW2nd24)>0.) | |
4042 | { | |
4043 | denominator24 = 1.-sumOfWW24/(sumOfW1st24*sumOfW2nd24); | |
4044 | if(TMath::Abs(denominator24)>0.) | |
4045 | { | |
4046 | // covariance: | |
4047 | Double_t covariance24 = numerator24/denominator24; | |
4048 | // weight dependent prefactor for covariance: | |
4049 | Double_t wPrefactor24 = sumOfWW24/(sumOfW1st24*sumOfW2nd24); | |
4050 | // finally, store "weighted" covariance: | |
4051 | fIntFlowCovariancesNUA->SetBinContent(24,wPrefactor24*covariance24); | |
4052 | } // end of if(TMath::Abs(denominator24)>0.) | |
4053 | } // end of if(TMath::Abs(sumOfW1st24*sumOfW2nd24)>0.) | |
0328db2d | 4054 | |
4055 | // Cov(<sin(phi1+phi2)>,<cos(phi1-phi2-phi3)>): | |
4056 | Double_t product25 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(25); // <<sin(phi1+phi2)><cos(phi1-phi2-phi3)>> | |
4057 | Double_t term1st25 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(2); // <<sin(phi1+phi2)>> | |
4058 | Double_t term2nd25 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(3); // <<cos(phi1-phi2-phi3)>> | |
4059 | Double_t sumOfW1st25 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(2); // W_{<sin(phi1+phi2)>} | |
4060 | Double_t sumOfW2nd25 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(3); // W_{<cos(phi1-phi2-phi3)>} | |
4061 | Double_t sumOfWW25 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(25); // W_{<sin(phi1+phi2)>} * W_{<cos(phi1-phi2-phi3)>} | |
4062 | // numerator in the expression for the the unbiased estimator for covariance: | |
4063 | Double_t numerator25 = product25 - term1st25*term2nd25; | |
4064 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 4065 | Double_t denominator25 = 0.; |
4066 | if(TMath::Abs(sumOfW1st25*sumOfW2nd25)>0.) | |
4067 | { | |
4068 | denominator25 = 1.-sumOfWW25/(sumOfW1st25*sumOfW2nd25); | |
4069 | if(TMath::Abs(denominator25)>0.) | |
4070 | { | |
4071 | // covariance: | |
4072 | Double_t covariance25 = numerator25/denominator25; | |
4073 | // weight dependent prefactor for covariance: | |
4074 | Double_t wPrefactor25 = sumOfWW25/(sumOfW1st25*sumOfW2nd25); | |
4075 | // finally, store "weighted" covariance: | |
4076 | fIntFlowCovariancesNUA->SetBinContent(25,wPrefactor25*covariance25); | |
4077 | } // end of if(TMath::Abs(denominator25)>0.) | |
4078 | } // end of if(TMath::Abs(sumOfW1st25*sumOfW2nd25)>0.) | |
4079 | ||
0328db2d | 4080 | // Cov(<sin(phi1+phi2)>,<sin(phi1-phi2-phi3)>): |
4081 | Double_t product26 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(26); // <<sin(phi1+phi2)><sin(phi1-phi2-phi3)>> | |
4082 | Double_t term1st26 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(2); // <<sin(phi1+phi2)>> | |
4083 | Double_t term2nd26 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(3); // <<sin(phi1-phi2-phi3)>> | |
4084 | Double_t sumOfW1st26 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(2); // W_{<sin(phi1+phi2)>} | |
4085 | Double_t sumOfW2nd26 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(3); // W_{<sin(phi1-phi2-phi3)>} | |
4086 | Double_t sumOfWW26 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(26); // W_{<sin(phi1+phi2)>} * W_{<sin(phi1-phi2-phi3)>} | |
4087 | // numerator in the expression for the the unbiased estimator for covariance: | |
4088 | Double_t numerator26 = product26 - term1st26*term2nd26; | |
4089 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 4090 | Double_t denominator26 = 0.; |
4091 | if(TMath::Abs(sumOfW1st26*sumOfW2nd26)>0.) | |
4092 | { | |
4093 | denominator26 = 1.-sumOfWW26/(sumOfW1st26*sumOfW2nd26); | |
4094 | if(TMath::Abs(denominator26)>0.) | |
4095 | { | |
4096 | // covariance: | |
4097 | Double_t covariance26 = numerator26/denominator26; | |
4098 | // weight dependent prefactor for covariance: | |
4099 | Double_t wPrefactor26 = sumOfWW26/(sumOfW1st26*sumOfW2nd26); | |
4100 | // finally, store "weighted" covariance: | |
4101 | fIntFlowCovariancesNUA->SetBinContent(26,wPrefactor26*covariance26); | |
4102 | } // end of if(TMath::Abs(denominator26)>0.) | |
4103 | } // end of if(TMath::Abs(sumOfW1st26*sumOfW2nd26)>0.) | |
4104 | ||
0328db2d | 4105 | // Cov(<cos(phi1-phi2-phi3)>,<sin(phi1-phi2-phi3)>): |
4106 | Double_t product27 = fIntFlowProductOfCorrectionTermsForNUAPro->GetBinContent(27); // <<cos(phi1-phi2-phi3)><sin(phi1-phi2-phi3)>> | |
b92ea2b9 | 4107 | Double_t term1st27 = fIntFlowCorrectionTermsForNUAPro[1]->GetBinContent(3); // <<cos(phi1-phi2-phi3)>> |
0328db2d | 4108 | Double_t term2nd27 = fIntFlowCorrectionTermsForNUAPro[0]->GetBinContent(3); // <<sin(phi1-phi2-phi3)>> |
b92ea2b9 | 4109 | Double_t sumOfW1st27 = fIntFlowSumOfEventWeightsNUA[1][0]->GetBinContent(3); // W_{<cos(phi1-phi2-phi3)>} |
0328db2d | 4110 | Double_t sumOfW2nd27 = fIntFlowSumOfEventWeightsNUA[0][0]->GetBinContent(3); // W_{<sin(phi1-phi2-phi3)>} |
4111 | Double_t sumOfWW27 = fIntFlowSumOfProductOfEventWeightsNUA->GetBinContent(27); // W_{<cos(phi1-phi2-phi3)>} * W_{<sin(phi1-phi2-phi3)>} | |
4112 | // numerator in the expression for the the unbiased estimator for covariance: | |
4113 | Double_t numerator27 = product27 - term1st27*term2nd27; | |
4114 | // denominator in the expression for the the unbiased estimator for covariance: | |
b92ea2b9 | 4115 | Double_t denominator27 = 0.; |
4116 | if(TMath::Abs(sumOfW1st27*sumOfW2nd27)>0.) | |
4117 | { | |
4118 | denominator27 = 1.-sumOfWW27/(sumOfW1st27*sumOfW2nd27); | |
4119 | if(TMath::Abs(denominator27)>0.) | |
4120 | { | |
4121 | // covariance: | |
4122 | Double_t covariance27 = numerator27/denominator27; | |
4123 | // weight dependent prefactor for covariance: | |
4124 | Double_t wPrefactor27 = sumOfWW27/(sumOfW1st27*sumOfW2nd27); | |
4125 | // finally, store "weighted" covariance: | |
4126 | fIntFlowCovariancesNUA->SetBinContent(27,wPrefactor27*covariance27); | |
4127 | } // end of if(TMath::Abs(denominator27)>0.) | |
4128 | } // end of if(TMath::Abs(sumOfW1st27*sumOfW2nd27)>0.) | |
4129 | ||
0328db2d | 4130 | } // end of AliFlowAnalysisWithQCumulants::CalculateCovariancesNUAIntFlow() |
4131 | ||
0328db2d | 4132 | //================================================================================================================================ |
4133 | ||
489d5531 | 4134 | void AliFlowAnalysisWithQCumulants::FinalizeCorrelationsIntFlow() |
4135 | { | |
4136 | // From profile fIntFlowCorrelationsPro access measured correlations and spread, | |
4137 | // correctly calculate the statistical errors and store the final results and | |
4138 | // statistical errors for correlations in histogram fIntFlowCorrelationsHist. | |
4139 | // | |
4140 | // Remark: Statistical error of correlation is calculated as: | |
4141 | // | |
4142 | // statistical error = termA * spread * termB: | |
4143 | // termA = sqrt{sum_{i=1}^{N} w^2}/(sum_{i=1}^{N} w) | |
4144 | // termB = 1/sqrt(1-termA^2) | |
b3dacf6b | 4145 | // |
4146 | ||
489d5531 | 4147 | for(Int_t ci=1;ci<=4;ci++) // correlation index |
4148 | { | |
b40a910e | 4149 | if(fIntFlowCorrelationsPro->GetBinEffectiveEntries(ci) < 2 || fIntFlowSquaredCorrelationsPro->GetBinEffectiveEntries(ci) < 2) |
4150 | { | |
4151 | fIntFlowCorrelationsPro->SetBinError(ci,0.); | |
4152 | fIntFlowSquaredCorrelationsPro->SetBinError(ci,0.); | |
4153 | continue; | |
4154 | } | |
489d5531 | 4155 | Double_t correlation = fIntFlowCorrelationsPro->GetBinContent(ci); |
b40a910e | 4156 | Double_t squaredCorrelation = fIntFlowSquaredCorrelationsPro->GetBinContent(ci); |
4157 | Double_t spread = 0.; | |
4158 | if(squaredCorrelation-correlation*correlation >= 0.) | |
4159 | { | |
4160 | spread = pow(squaredCorrelation-correlation*correlation,0.5); | |
4161 | } else | |
4162 | { | |
4163 | cout<<endl; | |
4164 | cout<<Form(" WARNING: Imaginary 'spread' for %d-particle correlation!!!! ",2*ci)<<endl; | |
4165 | cout<<endl; | |
4166 | } | |
489d5531 | 4167 | Double_t sumOfLinearEventWeights = fIntFlowSumOfEventWeights[0]->GetBinContent(ci); |
4168 | Double_t sumOfQuadraticEventWeights = fIntFlowSumOfEventWeights[1]->GetBinContent(ci); | |
4169 | Double_t termA = 0.; | |
4170 | Double_t termB = 0.; | |
b3dacf6b | 4171 | if(TMath::Abs(sumOfLinearEventWeights) > 0.) // to be improved - shall I omitt here Abs() ? |
489d5531 | 4172 | { |
4173 | termA = pow(sumOfQuadraticEventWeights,0.5)/sumOfLinearEventWeights; | |
4174 | } else | |
4175 | { | |
b3dacf6b | 4176 | cout<<endl; |
4177 | cout<<" WARNING (QC): sumOfLinearEventWeights == 0 in method FinalizeCorrelationsIntFlow() !!!!"<<endl; | |
4178 | cout<<" (for "<<2*ci<<"-particle correlation)"<<endl; | |
4179 | cout<<endl; | |
489d5531 | 4180 | } |
4181 | if(1.-pow(termA,2.) > 0.) | |
4182 | { | |
4183 | termB = 1./pow(1-pow(termA,2.),0.5); | |
4184 | } else | |
4185 | { | |
b3dacf6b | 4186 | cout<<endl; |
4187 | cout<<" WARNING (QC): 1.-pow(termA,2.) <= 0 in method FinalizeCorrelationsIntFlow() !!!!"<<endl; | |
4188 | cout<<" (for "<<2*ci<<"-particle correlation)"<<endl; | |
4189 | cout<<endl; | |
489d5531 | 4190 | } |
4191 | Double_t statisticalError = termA * spread * termB; | |
4192 | fIntFlowCorrelationsHist->SetBinContent(ci,correlation); | |
4193 | fIntFlowCorrelationsHist->SetBinError(ci,statisticalError); | |
ff70ca91 | 4194 | } // end of for(Int_t ci=1;ci<=4;ci++) // correlation index |
4195 | ||
b3dacf6b | 4196 | // Versus multiplicity: |
4197 | if(!fCalculateCumulantsVsM){return;} | |
ff70ca91 | 4198 | for(Int_t ci=0;ci<=3;ci++) // correlation index |
4199 | { | |
4200 | Int_t nBins = fIntFlowCorrelationsVsMPro[ci]->GetNbinsX(); | |
4201 | for(Int_t b=1;b<=nBins;b++) // looping over multiplicity bins | |
4202 | { | |
b40a910e | 4203 | if(fIntFlowCorrelationsVsMPro[ci]->GetBinEffectiveEntries(b) < 2 || fIntFlowSquaredCorrelationsVsMPro[ci]->GetBinEffectiveEntries(b) < 2) |
4204 | { | |
4205 | fIntFlowCorrelationsVsMPro[ci]->SetBinError(b,0.); | |
4206 | fIntFlowSquaredCorrelationsVsMPro[ci]->SetBinError(b,0.); | |
4207 | continue; | |
4208 | } | |
ff70ca91 | 4209 | Double_t correlationVsM = fIntFlowCorrelationsVsMPro[ci]->GetBinContent(b); |
b40a910e | 4210 | Double_t squaredCorrelationVsM = fIntFlowSquaredCorrelationsVsMPro[ci]->GetBinContent(b); |
4211 | Double_t spreadVsM = 0.; | |
4212 | if(squaredCorrelationVsM-correlationVsM*correlationVsM >= 0.) | |
4213 | { | |
4214 | spreadVsM = pow(squaredCorrelationVsM-correlationVsM*correlationVsM,0.5); | |
4215 | } else | |
4216 | { | |
4217 | cout<<endl; | |
4218 | cout<<Form(" WARNING (QC): Imaginary 'spreadVsM' for ci = %d, bin = %d, entries = %f !!!!", | |
4219 | ci,b,fIntFlowCorrelationsVsMPro[ci]->GetBinEffectiveEntries(b))<<endl; | |
4220 | cout<<endl; | |
4221 | } | |
ff70ca91 | 4222 | Double_t sumOfLinearEventWeightsVsM = fIntFlowSumOfEventWeightsVsM[ci][0]->GetBinContent(b); |
4223 | Double_t sumOfQuadraticEventWeightsVsM = fIntFlowSumOfEventWeightsVsM[ci][1]->GetBinContent(b); | |
4224 | Double_t termAVsM = 0.; | |
4225 | Double_t termBVsM = 0.; | |
b40a910e | 4226 | if(sumOfLinearEventWeightsVsM > 0.) |
ff70ca91 | 4227 | { |
4228 | termAVsM = pow(sumOfQuadraticEventWeightsVsM,0.5)/sumOfLinearEventWeightsVsM; | |
b3dacf6b | 4229 | } |
ff70ca91 | 4230 | if(1.-pow(termAVsM,2.) > 0.) |
4231 | { | |
4232 | termBVsM = 1./pow(1-pow(termAVsM,2.),0.5); | |
b3dacf6b | 4233 | } |
ff70ca91 | 4234 | Double_t statisticalErrorVsM = termAVsM * spreadVsM * termBVsM; |
4235 | fIntFlowCorrelationsVsMHist[ci]->SetBinContent(b,correlationVsM); | |
4236 | fIntFlowCorrelationsVsMHist[ci]->SetBinError(b,statisticalErrorVsM); | |
4237 | } // end of for(Int_t b=1;b<=nBins;b++) | |
4238 | } // end of for(Int_t ci=1;ci<=4;ci++) // correlation index | |
4239 | ||
489d5531 | 4240 | } // end of AliFlowAnalysisWithQCumulants::FinalizeCorrelationsIntFlow() |
4241 | ||
489d5531 | 4242 | //================================================================================================================================ |
4243 | ||
489d5531 | 4244 | void AliFlowAnalysisWithQCumulants::FillAverageMultiplicities(Int_t nRP) |
4245 | { | |
b77b6434 | 4246 | // Fill profile fAverageMultiplicity to hold average multiplicities and |
4247 | // number of events for events with nRP>=0, nRP>=1, ... , and nRP>=8 | |
489d5531 | 4248 | |
4249 | // Binning of fAverageMultiplicity is organized as follows: | |
4250 | // 1st bin: all events (including the empty ones) | |
4251 | // 2nd bin: event with # of RPs greater or equal to 1 | |
4252 | // 3rd bin: event with # of RPs greater or equal to 2 | |
4253 | // 4th bin: event with # of RPs greater or equal to 3 | |
4254 | // 5th bin: event with # of RPs greater or equal to 4 | |
4255 | // 6th bin: event with # of RPs greater or equal to 5 | |
4256 | // 7th bin: event with # of RPs greater or equal to 6 | |
4257 | // 8th bin: event with # of RPs greater or equal to 7 | |
4258 | // 9th bin: event with # of RPs greater or equal to 8 | |
4259 | ||
489d5531 | 4260 | if(nRP<0) |
4261 | { | |
b77b6434 | 4262 | cout<<endl; |
4263 | cout<<" WARNING (QC): nRP<0 in in AFAWQC::FAM() !!!!"<<endl; | |
4264 | cout<<endl; | |
489d5531 | 4265 | exit(0); |
4266 | } | |
4267 | ||
4268 | for(Int_t i=0;i<9;i++) | |
4269 | { | |
b77b6434 | 4270 | if(nRP>=i){fAvMultiplicity->Fill(i+0.5,nRP,1);} |
489d5531 | 4271 | } |
4272 | ||
4273 | } // end of AliFlowAnalysisWithQCumulants::FillAverageMultiplicities(nRP) | |
4274 | ||
489d5531 | 4275 | //================================================================================================================================ |
4276 | ||
489d5531 | 4277 | void AliFlowAnalysisWithQCumulants::CalculateCumulantsIntFlow() |
b3dacf6b | 4278 | { |
b92ea2b9 | 4279 | // a) Calculate Q-cumulants from the measured multiparticle correlations; |
4280 | // b) Propagate the statistical errors from measured multiparticle correlations to statistical errors of Q-cumulants; | |
4281 | // c) Remark: Q-cumulants calculated in this method are biased by non-uniform acceptance of detector !!!! | |
4282 | // Method CalculateQcumulantsCorrectedForNUAIntFlow() is called afterwards to correct for this bias; | |
4283 | // d) Store the results and statistical error of Q-cumulants in histogram fIntFlowQcumulants. | |
4284 | // Binning of fIntFlowQcumulants is organized as follows: | |
489d5531 | 4285 | // |
b3dacf6b | 4286 | // 1st bin: QC{2} |
4287 | // 2nd bin: QC{4} | |
4288 | // 3rd bin: QC{6} | |
4289 | // 4th bin: QC{8} | |
4290 | // | |
489d5531 | 4291 | |
b3dacf6b | 4292 | // Correlations: |
489d5531 | 4293 | Double_t two = fIntFlowCorrelationsHist->GetBinContent(1); // <<2>> |
4294 | Double_t four = fIntFlowCorrelationsHist->GetBinContent(2); // <<4>> | |
4295 | Double_t six = fIntFlowCorrelationsHist->GetBinContent(3); // <<6>> | |
4296 | Double_t eight = fIntFlowCorrelationsHist->GetBinContent(4); // <<8>> | |
b3dacf6b | 4297 | // Statistical errors of average 2-, 4-, 6- and 8-particle azimuthal correlations: |
489d5531 | 4298 | Double_t twoError = fIntFlowCorrelationsHist->GetBinError(1); // statistical error of <2> |
4299 | Double_t fourError = fIntFlowCorrelationsHist->GetBinError(2); // statistical error of <4> | |
4300 | Double_t sixError = fIntFlowCorrelationsHist->GetBinError(3); // statistical error of <6> | |
4301 | Double_t eightError = fIntFlowCorrelationsHist->GetBinError(4); // statistical error of <8> | |
b3dacf6b | 4302 | // Covariances (multiplied by prefactor depending on weights - see comments in CalculateCovariancesIntFlow()): |
8e1cefdd | 4303 | Double_t wCov24 = 0.; // Cov(<2>,<4>) * prefactor(w_<2>,w_<4>) |
4304 | Double_t wCov26 = 0.; // Cov(<2>,<6>) * prefactor(w_<2>,w_<6>) | |
4305 | Double_t wCov28 = 0.; // Cov(<2>,<8>) * prefactor(w_<2>,w_<8>) | |
4306 | Double_t wCov46 = 0.; // Cov(<4>,<6>) * prefactor(w_<4>,w_<6>) | |
4307 | Double_t wCov48 = 0.; // Cov(<4>,<8>) * prefactor(w_<4>,w_<8>) | |
4308 | Double_t wCov68 = 0.; // Cov(<6>,<8>) * prefactor(w_<6>,w_<8>) | |
4309 | if(!fForgetAboutCovariances) | |
4310 | { | |
4311 | wCov24 = fIntFlowCovariances->GetBinContent(1); // Cov(<2>,<4>) * prefactor(w_<2>,w_<4>) | |
4312 | wCov26 = fIntFlowCovariances->GetBinContent(2); // Cov(<2>,<6>) * prefactor(w_<2>,w_<6>) | |
4313 | wCov28 = fIntFlowCovariances->GetBinContent(3); // Cov(<2>,<8>) * prefactor(w_<2>,w_<8>) | |
4314 | wCov46 = fIntFlowCovariances->GetBinContent(4); // Cov(<4>,<6>) * prefactor(w_<4>,w_<6>) | |
4315 | wCov48 = fIntFlowCovariances->GetBinContent(5); // Cov(<4>,<8>) * prefactor(w_<4>,w_<8>) | |
4316 | wCov68 = fIntFlowCovariances->GetBinContent(6); // Cov(<6>,<8>) * prefactor(w_<6>,w_<8>) | |
4317 | } | |
489d5531 | 4318 | // Q-cumulants: |
4319 | Double_t qc2 = 0.; // QC{2} | |
4320 | Double_t qc4 = 0.; // QC{4} | |
4321 | Double_t qc6 = 0.; // QC{6} | |
4322 | Double_t qc8 = 0.; // QC{8} | |
b3dacf6b | 4323 | if(TMath::Abs(two) > 0.){qc2 = two;} |
4324 | if(TMath::Abs(four) > 0.){qc4 = four-2.*pow(two,2.);} | |
4325 | if(TMath::Abs(six) > 0.){qc6 = six-9.*two*four+12.*pow(two,3.);} | |
4326 | if(TMath::Abs(eight) > 0.){qc8 = eight-16.*two*six-18.*pow(four,2.)+144.*pow(two,2.)*four-144.*pow(two,4.);} | |
4327 | // Statistical errors of Q-cumulants: | |
489d5531 | 4328 | Double_t qc2Error = 0.; |
4329 | Double_t qc4Error = 0.; | |
4330 | Double_t qc6Error = 0.; | |
b3dacf6b | 4331 | Double_t qc8Error = 0.; |
4332 | // Squared statistical errors of Q-cumulants: | |
489d5531 | 4333 | //Double_t qc2ErrorSquared = 0.; |
4334 | Double_t qc4ErrorSquared = 0.; | |
4335 | Double_t qc6ErrorSquared = 0.; | |
b3dacf6b | 4336 | Double_t qc8ErrorSquared = 0.; |
4337 | // Statistical error of QC{2}: | |
4338 | qc2Error = twoError; | |
4339 | // Statistical error of QC{4}: | |
489d5531 | 4340 | qc4ErrorSquared = 16.*pow(two,2.)*pow(twoError,2)+pow(fourError,2.) |
4341 | - 8.*two*wCov24; | |
4342 | if(qc4ErrorSquared>0.) | |
4343 | { | |
4344 | qc4Error = pow(qc4ErrorSquared,0.5); | |
4345 | } else | |
4346 | { | |
b3dacf6b | 4347 | cout<<" WARNING (QC): Statistical error of QC{4} is imaginary !!!!"<<endl; |
4348 | } | |
4349 | // Statistical error of QC{6}: | |
489d5531 | 4350 | qc6ErrorSquared = 81.*pow(4.*pow(two,2.)-four,2.)*pow(twoError,2.) |
4351 | + 81.*pow(two,2.)*pow(fourError,2.) | |
4352 | + pow(sixError,2.) | |
4353 | - 162.*two*(4.*pow(two,2.)-four)*wCov24 | |
4354 | + 18.*(4.*pow(two,2.)-four)*wCov26 | |
b3dacf6b | 4355 | - 18.*two*wCov46; |
489d5531 | 4356 | if(qc6ErrorSquared>0.) |
4357 | { | |
4358 | qc6Error = pow(qc6ErrorSquared,0.5); | |
4359 | } else | |
4360 | { | |
b3dacf6b | 4361 | cout<<" WARNING (QC): Statistical error of QC{6} is imaginary !!!!"<<endl; |
4362 | } | |
4363 | // Statistical error of QC{8}: | |
489d5531 | 4364 | qc8ErrorSquared = 256.*pow(36.*pow(two,3.)-18.*four*two+six,2.)*pow(twoError,2.) |
4365 | + 1296.*pow(4.*pow(two,2.)-four,2.)*pow(fourError,2.) | |
4366 | + 256.*pow(two,2.)*pow(sixError,2.) | |
4367 | + pow(eightError,2.) | |
4368 | - 1152.*(36.*pow(two,3.)-18.*four*two+six)*(4.*pow(two,2.)-four)*wCov24 | |
4369 | + 512.*two*(36.*pow(two,3.)-18.*four*two+six)*wCov26 | |
4370 | - 32.*(36.*pow(two,3.)-18.*four*two+six)*wCov28 | |
4371 | - 1152.*two*(4.*pow(two,2.)-four)*wCov46 | |
4372 | + 72.*(4.*pow(two,2.)-four)*wCov48 | |
4373 | - 32.*two*wCov68; | |
4374 | if(qc8ErrorSquared>0.) | |
4375 | { | |
4376 | qc8Error = pow(qc8ErrorSquared,0.5); | |
4377 | } else | |
4378 | { | |
b3dacf6b | 4379 | cout<<"WARNING (QC): Statistical error of QC{8} is imaginary !!!!"<<endl; |
489d5531 | 4380 | } |
b3dacf6b | 4381 | // Store the results and statistical errors for Q-cumulants: |
4382 | if(TMath::Abs(qc2)>0.) | |
4383 | { | |
4384 | fIntFlowQcumulants->SetBinContent(1,qc2); | |
4385 | fIntFlowQcumulants->SetBinError(1,qc2Error); | |
4386 | } | |
4387 | if(TMath::Abs(qc4)>0.) | |
4388 | { | |
4389 | fIntFlowQcumulants->SetBinContent(2,qc4); | |
4390 | fIntFlowQcumulants->SetBinError(2,qc4Error); | |
4391 | } | |
4392 | if(TMath::Abs(qc6)>0.) | |
4393 | { | |
4394 | fIntFlowQcumulants->SetBinContent(3,qc6); | |
4395 | fIntFlowQcumulants->SetBinError(3,qc6Error); | |
4396 | } | |
4397 | if(TMath::Abs(qc8)>0.) | |
4398 | { | |
4399 | fIntFlowQcumulants->SetBinContent(4,qc8); | |
4400 | fIntFlowQcumulants->SetBinError(4,qc8Error); | |
4401 | } | |
4402 | ||
4403 | // Versus multiplicity: | |
4404 | if(!fCalculateCumulantsVsM){return;} | |
9da1a4f3 | 4405 | Int_t nBins = fIntFlowCorrelationsVsMPro[0]->GetNbinsX(); // to be improved (hardwired 0) |
b3dacf6b | 4406 | Double_t value[4] = {0.}; // QCs vs M |
4407 | Double_t error[4] = {0.}; // error of QCs vs M | |
4408 | Double_t dSum1[4] = {0.}; // sum value_i/(error_i)^2 | |
4409 | Double_t dSum2[4] = {0.}; // sum 1/(error_i)^2 | |
9da1a4f3 | 4410 | for(Int_t b=1;b<=nBins;b++) |
4411 | { | |
b3dacf6b | 4412 | // Correlations: |
9da1a4f3 | 4413 | two = fIntFlowCorrelationsVsMHist[0]->GetBinContent(b); // <<2>> |
4414 | four = fIntFlowCorrelationsVsMHist[1]->GetBinContent(b); // <<4>> | |
4415 | six = fIntFlowCorrelationsVsMHist[2]->GetBinContent(b); // <<6>> | |
4416 | eight = fIntFlowCorrelationsVsMHist[3]->GetBinContent(b); // <<8>> | |
b3dacf6b | 4417 | // Statistical errors of average 2-, 4-, 6- and 8-particle azimuthal correlations: |
9da1a4f3 | 4418 | twoError = fIntFlowCorrelationsVsMHist[0]->GetBinError(b); // statistical error of <2> |
4419 | fourError = fIntFlowCorrelationsVsMHist[1]->GetBinError(b); // statistical error of <4> | |
4420 | sixError = fIntFlowCorrelationsVsMHist[2]->GetBinError(b); // statistical error of <6> | |
4421 | eightError = fIntFlowCorrelationsVsMHist[3]->GetBinError(b); // statistical error of <8> | |
b3dacf6b | 4422 | // Covariances (multiplied by prefactor depending on weights - see comments in CalculateCovariancesIntFlow()): |
8e1cefdd | 4423 | if(!fForgetAboutCovariances) |
4424 | { | |
4425 | wCov24 = fIntFlowCovariancesVsM[0]->GetBinContent(b); // Cov(<2>,<4>) * prefactor(w_<2>,w_<4>) | |
4426 | wCov26 = fIntFlowCovariancesVsM[1]->GetBinContent(b); // Cov(<2>,<6>) * prefactor(w_<2>,w_<6>) | |
4427 | wCov28 = fIntFlowCovariancesVsM[2]->GetBinContent(b); // Cov(<2>,<8>) * prefactor(w_<2>,w_<8>) | |
4428 | wCov46 = fIntFlowCovariancesVsM[3]->GetBinContent(b); // Cov(<4>,<6>) * prefactor(w_<4>,w_<6>) | |
4429 | wCov48 = fIntFlowCovariancesVsM[4]->GetBinContent(b); // Cov(<4>,<8>) * prefactor(w_<4>,w_<8>) | |
4430 | wCov68 = fIntFlowCovariancesVsM[5]->GetBinContent(b); // Cov(<6>,<8>) * prefactor(w_<6>,w_<8>) | |
4431 | } | |
9da1a4f3 | 4432 | // Q-cumulants: |
4433 | qc2 = 0.; // QC{2} | |
4434 | qc4 = 0.; // QC{4} | |
4435 | qc6 = 0.; // QC{6} | |
4436 | qc8 = 0.; // QC{8} | |
b3dacf6b | 4437 | if(TMath::Abs(two) > 0.){qc2 = two;} |
4438 | if(TMath::Abs(four) > 0.){qc4 = four-2.*pow(two,2.);} | |
4439 | if(TMath::Abs(six) > 0.){qc6 = six-9.*two*four+12.*pow(two,3.);} | |
4440 | if(TMath::Abs(eight) > 0.){qc8 = eight-16.*two*six-18.*pow(four,2.)+144.*pow(two,2.)*four-144.*pow(two,4.);} | |
4441 | // Statistical errors of Q-cumulants: | |
9da1a4f3 | 4442 | qc2Error = 0.; |
4443 | qc4Error = 0.; | |
4444 | qc6Error = 0.; | |
b3dacf6b | 4445 | qc8Error = 0.; |
4446 | // Squared statistical errors of Q-cumulants: | |
9da1a4f3 | 4447 | //Double_t qc2ErrorSquared = 0.; |
4448 | qc4ErrorSquared = 0.; | |
4449 | qc6ErrorSquared = 0.; | |
b3dacf6b | 4450 | qc8ErrorSquared = 0.; |
4451 | // Statistical error of QC{2}: | |
4452 | qc2Error = twoError; | |
4453 | // Statistical error of QC{4}: | |
9da1a4f3 | 4454 | qc4ErrorSquared = 16.*pow(two,2.)*pow(twoError,2)+pow(fourError,2.) |
4455 | - 8.*two*wCov24; | |
4456 | if(qc4ErrorSquared>0.) | |
4457 | { | |
4458 | qc4Error = pow(qc4ErrorSquared,0.5); | |
4459 | } else | |
4460 | { | |
4461 | // cout<<"WARNING: Statistical error of QC{4} is imaginary in multiplicity bin "<<b<<" !!!!"<<endl; | |
b3dacf6b | 4462 | } |
4463 | // Statistical error of QC{6}: | |
9da1a4f3 | 4464 | qc6ErrorSquared = 81.*pow(4.*pow(two,2.)-four,2.)*pow(twoError,2.) |
4465 | + 81.*pow(two,2.)*pow(fourError,2.) | |
4466 | + pow(sixError,2.) | |
4467 | - 162.*two*(4.*pow(two,2.)-four)*wCov24 | |
4468 | + 18.*(4.*pow(two,2.)-four)*wCov26 | |
b3dacf6b | 4469 | - 18.*two*wCov46; |
9da1a4f3 | 4470 | if(qc6ErrorSquared>0.) |
4471 | { | |
4472 | qc6Error = pow(qc6ErrorSquared,0.5); | |
4473 | } else | |
4474 | { | |
4475 | // cout<<"WARNING: Statistical error of QC{6} is imaginary in multiplicity bin "<<b<<" !!!!"<<endl; | |
b3dacf6b | 4476 | } |
4477 | // Statistical error of QC{8}: | |
9da1a4f3 | 4478 | qc8ErrorSquared = 256.*pow(36.*pow(two,3.)-18.*four*two+six,2.)*pow(twoError,2.) |
4479 | + 1296.*pow(4.*pow(two,2.)-four,2.)*pow(fourError,2.) | |
4480 | + 256.*pow(two,2.)*pow(sixError,2.) | |
4481 | + pow(eightError,2.) | |
4482 | - 1152.*(36.*pow(two,3.)-18.*four*two+six)*(4.*pow(two,2.)-four)*wCov24 | |
4483 | + 512.*two*(36.*pow(two,3.)-18.*four*two+six)*wCov26 | |
4484 | - 32.*(36.*pow(two,3.)-18.*four*two+six)*wCov28 | |
4485 | - 1152.*two*(4.*pow(two,2.)-four)*wCov46 | |
4486 | + 72.*(4.*pow(two,2.)-four)*wCov48 | |
4487 | - 32.*two*wCov68; | |
4488 | if(qc8ErrorSquared>0.) | |
4489 | { | |
4490 | qc8Error = pow(qc8ErrorSquared,0.5); | |
4491 | } else | |
4492 | { | |
4493 | // cout<<"WARNING: Statistical error of QC{8} is imaginary in multiplicity bin "<<b<<" !!!!"<<endl; | |
4494 | } | |
b3dacf6b | 4495 | // Store the results and statistical errors for Q-cumulants: |
4496 | if(TMath::Abs(qc2)>0.) | |
4497 | { | |
4498 | fIntFlowQcumulantsVsM[0]->SetBinContent(b,qc2); | |
4499 | fIntFlowQcumulantsVsM[0]->SetBinError(b,qc2Error); | |
4500 | } | |
4501 | if(TMath::Abs(qc4)>0.) | |
4502 | { | |
4503 | fIntFlowQcumulantsVsM[1]->SetBinContent(b,qc4); | |
4504 | fIntFlowQcumulantsVsM[1]->SetBinError(b,qc4Error); | |
4505 | } | |
4506 | if(TMath::Abs(qc6)>0.) | |
4507 | { | |
4508 | fIntFlowQcumulantsVsM[2]->SetBinContent(b,qc6); | |
4509 | fIntFlowQcumulantsVsM[2]->SetBinError(b,qc6Error); | |
4510 | } | |
4511 | if(TMath::Abs(qc8)>0.) | |
4512 | { | |
4513 | fIntFlowQcumulantsVsM[3]->SetBinContent(b,qc8); | |
4514 | fIntFlowQcumulantsVsM[3]->SetBinError(b,qc8Error); | |
4515 | } | |
4516 | // Rebin in M: | |
4517 | for(Int_t co=0;co<4;co++) | |
4518 | { | |
b40a910e | 4519 | if(fIntFlowCorrelationsVsMPro[co]->GetBinEffectiveEntries(b)<2){continue;} |
b3dacf6b | 4520 | value[co] = fIntFlowQcumulantsVsM[co]->GetBinContent(b); |
4521 | error[co] = fIntFlowQcumulantsVsM[co]->GetBinError(b); | |
4522 | if(error[co]>0.) | |
4523 | { | |
4524 | dSum1[co]+=value[co]/(error[co]*error[co]); | |
4525 | dSum2[co]+=1./(error[co]*error[co]); | |
4526 | } | |
4527 | } // end of for(Int_t co=0;co<4;co++) | |
9da1a4f3 | 4528 | } // end of for(Int_t b=1;b<=nBins;b++) |
b3dacf6b | 4529 | // Store rebinned Q-cumulants: |
4530 | for(Int_t co=0;co<4;co++) | |
4531 | { | |
4532 | if(dSum2[co]>0.) | |
4533 | { | |
4534 | fIntFlowQcumulantsRebinnedInM->SetBinContent(co+1,dSum1[co]/dSum2[co]); | |
4535 | fIntFlowQcumulantsRebinnedInM->SetBinError(co+1,pow(1./dSum2[co],0.5)); | |
4536 | } | |
4537 | } // end of for(Int_t co=0;co<4;co++) | |
4538 | ||
489d5531 | 4539 | } // end of AliFlowAnalysisWithQCumulants::CalculateCumulantsIntFlow() |
4540 | ||
489d5531 | 4541 | //================================================================================================================================ |
4542 | ||
b92ea2b9 | 4543 | void AliFlowAnalysisWithQCumulants::CalculateReferenceFlow() |
489d5531 | 4544 | { |
b92ea2b9 | 4545 | // a) Calculate the final results for reference flow estimates from Q-cumulants; |
4546 | // b) Propagate the statistical errors to reference flow estimates from statistical error of Q-cumulants; | |
0328db2d | 4547 | // c) Store the results and statistical errors of reference flow estimates in histogram fIntFlow. |
489d5531 | 4548 | // Binning of fIntFlow is organized as follows: |
4549 | // | |
b3dacf6b | 4550 | // 1st bin: v{2,QC} |
4551 | // 2nd bin: v{4,QC} | |
4552 | // 3rd bin: v{6,QC} | |
4553 | // 4th bin: v{8,QC} | |
4554 | // | |
489d5531 | 4555 | |
b3dacf6b | 4556 | // Reference flow estimates: |
489d5531 | 4557 | Double_t v2 = 0.; // v{2,QC} |
4558 | Double_t v4 = 0.; // v{4,QC} | |
4559 | Double_t v6 = 0.; // v{6,QC} | |
4560 | Double_t v8 = 0.; // v{8,QC} | |
b3dacf6b | 4561 | // Reference flow's statistical errors: |
4562 | Double_t v2Error = 0.; // v{2,QC} stat. error | |
4563 | Double_t v4Error = 0.; // v{4,QC} stat. error | |
4564 | Double_t v6Error = 0.; // v{6,QC} stat. error | |
4565 | Double_t v8Error = 0.; // v{8,QC} stat. error | |
4566 | ||
b92ea2b9 | 4567 | // Q-cumulants: |
4568 | Double_t qc2 = fIntFlowQcumulants->GetBinContent(1); // QC{2} | |
4569 | Double_t qc4 = fIntFlowQcumulants->GetBinContent(2); // QC{4} | |
4570 | Double_t qc6 = fIntFlowQcumulants->GetBinContent(3); // QC{6} | |
4571 | Double_t qc8 = fIntFlowQcumulants->GetBinContent(4); // QC{8} | |
4572 | // Q-cumulants's statistical errors: | |
4573 | Double_t qc2Error = fIntFlowQcumulants->GetBinError(1); // QC{2} stat. error | |
4574 | Double_t qc4Error = fIntFlowQcumulants->GetBinError(2); // QC{4} stat. error | |
4575 | Double_t qc6Error = fIntFlowQcumulants->GetBinError(3); // QC{6} stat. error | |
4576 | Double_t qc8Error = fIntFlowQcumulants->GetBinError(4); // QC{8} stat. error | |
4577 | // Calculate reference flow estimates from Q-cumulants: | |
4578 | if(qc2>=0.){v2 = pow(qc2,1./2.);} | |
4579 | if(qc4<=0.){v4 = pow(-1.*qc4,1./4.);} | |
4580 | if(qc6>=0.){v6 = pow((1./4.)*qc6,1./6.);} | |
4581 | if(qc8<=0.){v8 = pow((-1./33.)*qc8,1./8.);} | |
4582 | // Calculate stat. error for reference flow estimates from stat. error of Q-cumulants: | |
4583 | if(qc2>0.){v2Error = (1./2.)*pow(qc2,-1./2.)*qc2Error;} | |
4584 | if(qc4<0.){v4Error = (1./4.)*pow(-qc4,-3./4.)*qc4Error;} | |
4585 | if(qc6>0.){v6Error = (1./6.)*pow(2.,-1./3.)*pow(qc6,-5./6.)*qc6Error;} | |
4586 | if(qc8<0.){v8Error = (1./8.)*pow(33.,-1./8.)*pow(-qc8,-7./8.)*qc8Error;} | |
4587 | // Print warnings for the 'wrong sign' cumulants: | |
4588 | if(TMath::Abs(v2) < 1.e-44) | |
4589 | { | |
4590 | cout<<" WARNING: Wrong sign QC{2}, couldn't calculate v{2,QC} !!!!"<<endl; | |
4591 | } | |
4592 | if(TMath::Abs(v4) < 1.e-44) | |
4593 | { | |
4594 | cout<<" WARNING: Wrong sign QC{4}, couldn't calculate v{4,QC} !!!!"<<endl; | |
4595 | } | |
4596 | if(TMath::Abs(v6) < 1.e-44) | |
4597 | { | |
4598 | cout<<" WARNING: Wrong sign QC{6}, couldn't calculate v{6,QC} !!!!"<<endl; | |
4599 | } | |
4600 | if(TMath::Abs(v8) < 1.e-44) | |
4601 | { | |
4602 | cout<<" WARNING: Wrong sign QC{8}, couldn't calculate v{8,QC} !!!!"<<endl; | |
4603 | } | |
4604 | // Store the results and statistical errors of integrated flow estimates: | |
4605 | fIntFlow->SetBinContent(1,v2); | |
4606 | fIntFlow->SetBinError(1,v2Error); | |
4607 | fIntFlow->SetBinContent(2,v4); | |
4608 | fIntFlow->SetBinError(2,v4Error); | |
4609 | fIntFlow->SetBinContent(3,v6); | |
4610 | fIntFlow->SetBinError(3,v6Error); | |
4611 | fIntFlow->SetBinContent(4,v8); | |
4612 | fIntFlow->SetBinError(4,v8Error); | |
4613 | ||
4614 | // Versus multiplicity: | |
4615 | if(!fCalculateCumulantsVsM){return;} | |
4616 | Int_t nBins = fIntFlowCorrelationsVsMPro[0]->GetNbinsX(); // to be improved (hardwired 0) | |
4617 | for(Int_t b=1;b<=nBins;b++) | |
9da1a4f3 | 4618 | { |
4619 | // Q-cumulants: | |
b92ea2b9 | 4620 | Double_t qc2VsM = fIntFlowQcumulantsVsM[0]->GetBinContent(b); // QC{2} |
4621 | Double_t qc4VsM = fIntFlowQcumulantsVsM[1]->GetBinContent(b); // QC{4} | |
4622 | Double_t qc6VsM = fIntFlowQcumulantsVsM[2]->GetBinContent(b); // QC{6} | |
4623 | Double_t qc8VsM = fIntFlowQcumulantsVsM[3]->GetBinContent(b); // QC{8} | |
b3dacf6b | 4624 | // Q-cumulants's statistical errors: |
b92ea2b9 | 4625 | Double_t qc2ErrorVsM = fIntFlowQcumulantsVsM[0]->GetBinError(b); // QC{2} stat. error |
4626 | Double_t qc4ErrorVsM = fIntFlowQcumulantsVsM[1]->GetBinError(b); // QC{4} stat. error | |
4627 | Double_t qc6ErrorVsM = fIntFlowQcumulantsVsM[2]->GetBinError(b); // QC{6} stat. error | |
4628 | Double_t qc8ErrorVsM = fIntFlowQcumulantsVsM[3]->GetBinError(b); // QC{8} stat. error | |
b3dacf6b | 4629 | // Reference flow estimates: |
b92ea2b9 | 4630 | Double_t v2VsM = 0.; // v{2,QC} |
4631 | Double_t v4VsM = 0.; // v{4,QC} | |
4632 | Double_t v6VsM = 0.; // v{6,QC} | |
4633 | Double_t v8VsM = 0.; // v{8,QC} | |
4634 | // Reference flow estimates errors: | |
4635 | Double_t v2ErrorVsM = 0.; // v{2,QC} stat. error | |
4636 | Double_t v4ErrorVsM = 0.; // v{4,QC} stat. error | |
4637 | Double_t v6ErrorVsM = 0.; // v{6,QC} stat. error | |
4638 | Double_t v8ErrorVsM = 0.; // v{8,QC} stat. error | |
b3dacf6b | 4639 | // Calculate reference flow estimates from Q-cumulants: |
b92ea2b9 | 4640 | if(qc2VsM>=0.){v2VsM = pow(qc2VsM,1./2.);} |
4641 | if(qc4VsM<=0.){v4VsM = pow(-1.*qc4VsM,1./4.);} | |
4642 | if(qc6VsM>=0.){v6VsM = pow((1./4.)*qc6VsM,1./6.);} | |
4643 | if(qc8VsM<=0.){v8VsM = pow((-1./33.)*qc8VsM,1./8.);} | |
b3dacf6b | 4644 | // Calculate stat. error for reference flow estimates from stat. error of Q-cumulants: |
b92ea2b9 | 4645 | if(qc2VsM>0.){v2ErrorVsM = (1./2.)*pow(qc2VsM,-1./2.)*qc2ErrorVsM;} |
4646 | if(qc4VsM<0.){v4ErrorVsM = (1./4.)*pow(-qc4VsM,-3./4.)*qc4ErrorVsM;} | |
4647 | if(qc6VsM>0.){v6ErrorVsM = (1./6.)*pow(2.,-1./3.)*pow(qc6VsM,-5./6.)*qc6ErrorVsM;} | |
4648 | if(qc8VsM<0.){v8ErrorVsM = (1./8.)*pow(33.,-1./8.)*pow(-qc8VsM,-7./8.)*qc8ErrorVsM;} | |
b3dacf6b | 4649 | // Store the results and statistical errors of integrated flow estimates: |
b92ea2b9 | 4650 | fIntFlowVsM[0]->SetBinContent(b,v2VsM); |
4651 | fIntFlowVsM[0]->SetBinError(b,v2ErrorVsM); | |
4652 | fIntFlowVsM[1]->SetBinContent(b,v4VsM); | |
4653 | fIntFlowVsM[1]->SetBinError(b,v4ErrorVsM); | |
4654 | fIntFlowVsM[2]->SetBinContent(b,v6VsM); | |
4655 | fIntFlowVsM[2]->SetBinError(b,v6ErrorVsM); | |
4656 | fIntFlowVsM[3]->SetBinContent(b,v8VsM); | |
4657 | fIntFlowVsM[3]->SetBinError(b,v8ErrorVsM); | |
4658 | } // end of for(Int_t b=1;b<=nBins;b++) | |
4659 | ||
4660 | // 'Rebinned in M' calculation: // to be improved - this can be implemented better: | |
4661 | // Reference flow estimates: | |
4662 | Double_t v2RebinnedInM = 0.; // v{2,QC} | |
4663 | Double_t v4RebinnedInM = 0.; // v{4,QC} | |
4664 | Double_t v6RebinnedInM = 0.; // v{6,QC} | |
4665 | Double_t v8RebinnedInM = 0.; // v{8,QC} | |
4666 | // Reference flow's statistical errors: | |
4667 | Double_t v2ErrorRebinnedInM = 0.; // v{2,QC} stat. error | |
4668 | Double_t v4ErrorRebinnedInM = 0.; // v{4,QC} stat. error | |
4669 | Double_t v6ErrorRebinnedInM = 0.; // v{6,QC} stat. error | |
4670 | Double_t v8ErrorRebinnedInM = 0.; // v{8,QC} stat. error | |
4671 | // Q-cumulants: | |
4672 | Double_t qc2RebinnedInM = fIntFlowQcumulantsRebinnedInM->GetBinContent(1); // QC{2} | |
4673 | Double_t qc4RebinnedInM = fIntFlowQcumulantsRebinnedInM->GetBinContent(2); // QC{4} | |
4674 | Double_t qc6RebinnedInM = fIntFlowQcumulantsRebinnedInM->GetBinContent(3); // QC{6} | |
4675 | Double_t qc8RebinnedInM = fIntFlowQcumulantsRebinnedInM->GetBinContent(4); // QC{8} | |
4676 | // Q-cumulants's statistical errors: | |
4677 | Double_t qc2ErrorRebinnedInM = fIntFlowQcumulantsRebinnedInM->GetBinError(1); // QC{2} stat. error | |
4678 | Double_t qc4ErrorRebinnedInM = fIntFlowQcumulantsRebinnedInM->GetBinError(2); // QC{4} stat. error | |
4679 | Double_t qc6ErrorRebinnedInM = fIntFlowQcumulantsRebinnedInM->GetBinError(3); // QC{6} stat. error | |
4680 | Double_t qc8ErrorRebinnedInM = fIntFlowQcumulantsRebinnedInM->GetBinError(4); // QC{8} stat. error | |
4681 | // Calculate reference flow estimates from Q-cumulants: | |
4682 | if(qc2RebinnedInM>=0.){v2RebinnedInM = pow(qc2RebinnedInM,1./2.);} | |
4683 | if(qc4RebinnedInM<=0.){v4RebinnedInM = pow(-1.*qc4RebinnedInM,1./4.);} | |
4684 | if(qc6RebinnedInM>=0.){v6RebinnedInM = pow((1./4.)*qc6RebinnedInM,1./6.);} | |
4685 | if(qc8RebinnedInM<=0.){v8RebinnedInM = pow((-1./33.)*qc8RebinnedInM,1./8.);} | |
4686 | // Calculate stat. error for reference flow estimates from stat. error of Q-cumulants: | |
4687 | if(qc2RebinnedInM>0.){v2ErrorRebinnedInM = (1./2.)*pow(qc2RebinnedInM,-1./2.)*qc2ErrorRebinnedInM;} | |
4688 | if(qc4RebinnedInM<0.){v4ErrorRebinnedInM = (1./4.)*pow(-qc4RebinnedInM,-3./4.)*qc4ErrorRebinnedInM;} | |
4689 | if(qc6RebinnedInM>0.){v6ErrorRebinnedInM = (1./6.)*pow(2.,-1./3.)*pow(qc6RebinnedInM,-5./6.)*qc6ErrorRebinnedInM;} | |
4690 | if(qc8RebinnedInM<0.){v8ErrorRebinnedInM = (1./8.)*pow(33.,-1./8.)*pow(-qc8RebinnedInM,-7./8.)*qc8ErrorRebinnedInM;} | |
4691 | // Print warnings for the 'wrong sign' cumulants: | |
4692 | if(TMath::Abs(v2RebinnedInM) < 1.e-44) | |
4693 | { | |
4694 | cout<<" WARNING: Wrong sign QC{2} rebinned in M, couldn't calculate v{2,QC} !!!!"<<endl; | |
4695 | } | |
4696 | if(TMath::Abs(v4RebinnedInM) < 1.e-44) | |
4697 | { | |
4698 | cout<<" WARNING: Wrong sign QC{4} rebinned in M, couldn't calculate v{4,QC} !!!!"<<endl; | |
4699 | } | |
4700 | if(TMath::Abs(v6RebinnedInM) < 1.e-44) | |
4701 | { | |
4702 | cout<<" WARNING: Wrong sign QC{6} rebinned in M, couldn't calculate v{6,QC} !!!!"<<endl; | |
4703 | } | |
4704 | if(TMath::Abs(v8RebinnedInM) < 1.e-44) | |
4705 | { | |
4706 | cout<<" WARNING: Wrong sign QC{8} rebinned in M, couldn't calculate v{8,QC} !!!!"<<endl; | |
4707 | } | |
4708 | // Store the results and statistical errors of integrated flow estimates: | |
4709 | fIntFlowRebinnedInM->SetBinContent(1,v2RebinnedInM); | |
4710 | fIntFlowRebinnedInM->SetBinError(1,v2ErrorRebinnedInM); | |
4711 | fIntFlowRebinnedInM->SetBinContent(2,v4RebinnedInM); | |
4712 | fIntFlowRebinnedInM->SetBinError(2,v4ErrorRebinnedInM); | |
4713 | fIntFlowRebinnedInM->SetBinContent(3,v6RebinnedInM); | |
4714 | fIntFlowRebinnedInM->SetBinError(3,v6ErrorRebinnedInM); | |
4715 | fIntFlowRebinnedInM->SetBinContent(4,v8RebinnedInM); | |
4716 | fIntFlowRebinnedInM->SetBinError(4,v8ErrorRebinnedInM); | |
4717 | ||
4718 | } // end of AliFlowAnalysisWithQCumulants::CalculateReferenceFlow() | |
489d5531 | 4719 | |
489d5531 | 4720 | //================================================================================================================================ |
4721 | ||
489d5531 | 4722 | void AliFlowAnalysisWithQCumulants::FillCommonHistResultsIntFlow() |
4723 | { | |
0dd3b008 | 4724 | // Fill in AliFlowCommonHistResults histograms relevant for reference flow. |
489d5531 | 4725 | |
0dd3b008 | 4726 | // There are two possibilities here: |
4727 | // a) Store minimum bias reference flow - use SetMinimumBiasReferenceFlow(kTRUE). This result is | |
4728 | // biased by the interplay between nonflow correlations and multiplicity fluctuations and is | |
4729 | // also stored in local histogram fIntFlow; | |
4730 | // b) Store reference flow obtained from flow analysis performed at fixed multiplicity and | |
4731 | // rebinned only at the end of the day - use SetMinimumBiasReferenceFlow(kFALSE). This result | |
4732 | // is also stored in local histogram fIntFlowRebinnedInM. | |
489d5531 | 4733 | |
0dd3b008 | 4734 | // Reference flow estimates: |
4735 | Double_t v[4] = {0.}; | |
4736 | // Statistical errors of reference flow estimates: | |
4737 | Double_t vError[4] = {0.}; | |
489d5531 | 4738 | |
0dd3b008 | 4739 | for(Int_t b=0;b<4;b++) |
4740 | { | |
4741 | if(fMinimumBiasReferenceFlow) | |
4742 | { | |
4743 | v[b] = fIntFlow->GetBinContent(b+1); | |
4744 | vError[b] = fIntFlow->GetBinError(b+1); | |
4745 | } else | |
4746 | { | |
4747 | v[b] = fIntFlowRebinnedInM->GetBinContent(b+1); | |
4748 | vError[b] = fIntFlowRebinnedInM->GetBinError(b+1); | |
4749 | } | |
4750 | } // end of for(Int_t b=0;b<4;b++) | |
4751 | ||
4752 | // Fill AliFlowCommonHistResults histogram: | |
4753 | fCommonHistsResults2nd->FillIntegratedFlow(v[0],vError[0]); // to be improved (hardwired 2nd in the name) | |
4754 | fCommonHistsResults4th->FillIntegratedFlow(v[1],vError[1]); // to be improved (hardwired 4th in the name) | |
489d5531 | 4755 | if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) // to be improved (calculate also 6th and 8th order) |
4756 | { | |
0dd3b008 | 4757 | fCommonHistsResults6th->FillIntegratedFlow(v[2],vError[2]); // to be improved (hardwired 6th in the name) |
4758 | fCommonHistsResults8th->FillIntegratedFlow(v[3],vError[3]); // to be improved (hardwired 8th in the name) | |
489d5531 | 4759 | } |
4760 | ||
4761 | } // end of AliFlowAnalysisWithQCumulants::FillCommonHistResultsIntFlow() | |
4762 | ||
489d5531 | 4763 | //================================================================================================================================ |
4764 | ||
489d5531 | 4765 | void AliFlowAnalysisWithQCumulants::CalculateIntFlowCorrelationsUsingParticleWeights() |
4766 | { | |
4767 | // Calculate all correlations needed for integrated flow using particle weights. | |
4768 | ||
4769 | // Remark 1: When particle weights are used the binning of fIntFlowCorrelationAllPro is organized as follows: | |
4770 | // | |
4771 | // 1st bin: <2>_{1n|1n} = two1n1nW1W1 = <w1 w2 cos(n*(phi1-phi2))> | |
4772 | // 2nd bin: <2>_{2n|2n} = two2n2nW2W2 = <w1^2 w2^2 cos(2n*(phi1-phi2))> | |
4773 | // 3rd bin: <2>_{3n|3n} = two3n3nW3W3 = <w1^3 w2^3 cos(3n*(phi1-phi2))> | |
4774 | // 4th bin: <2>_{4n|4n} = two4n4nW4W4 = <w1^4 w2^4 cos(4n*(phi1-phi2))> | |
4775 | // 5th bin: ---- EMPTY ---- | |
4776 | // 6th bin: <3>_{2n|1n,1n} = three2n1n1nW2W1W1 = <w1^2 w2 w3 cos(n*(2phi1-phi2-phi3))> | |
4777 | // 7th bin: <3>_{3n|2n,1n} = ... | |
4778 | // 8th bin: <3>_{4n|2n,2n} = ... | |
4779 | // 9th bin: <3>_{4n|3n,1n} = ... | |
4780 | // 10th bin: ---- EMPTY ---- | |
4781 | // 11th bin: <4>_{1n,1n|1n,1n} = four1n1n1n1nW1W1W1W1 = <w1 w2 w3 w4 cos(n*(phi1+phi2-phi3-phi4))> | |
4782 | // 12th bin: <4>_{2n,1n|2n,1n} = ... | |
4783 | // 13th bin: <4>_{2n,2n|2n,2n} = ... | |
4784 | // 14th bin: <4>_{3n|1n,1n,1n} = ... | |
4785 | // 15th bin: <4>_{3n,1n|3n,1n} = ... | |
4786 | // 16th bin: <4>_{3n,1n|2n,2n} = ... | |
4787 | // 17th bin: <4>_{4n|2n,1n,1n} = ... | |
4788 | // 18th bin: ---- EMPTY ---- | |
4789 | // 19th bin: <5>_{2n|1n,1n,1n,1n} = ... | |
4790 | // 20th bin: <5>_{2n,2n|2n,1n,1n} = ... | |
4791 | // 21st bin: <5>_{3n,1n|2n,1n,1n} = ... | |
4792 | // 22nd bin: <5>_{4n|1n,1n,1n,1n} = ... | |
4793 | // 23rd bin: ---- EMPTY ---- | |
4794 | // 24th bin: <6>_{1n,1n,1n|1n,1n,1n} = ... | |
4795 | // 25th bin: <6>_{2n,1n,1n|2n,1n,1n} = ... | |
4796 | // 26th bin: <6>_{2n,2n|1n,1n,1n,1n} = ... | |
4797 | // 27th bin: <6>_{3n,1n|1n,1n,1n,1n} = ... | |
4798 | // 28th bin: ---- EMPTY ---- | |
4799 | // 29th bin: <7>_{2n,1n,1n|1n,1n,1n,1n} = ... | |
4800 | // 30th bin: ---- EMPTY ---- | |
4801 | // 31st bin: <8>_{1n,1n,1n,1n|1n,1n,1n,1n} = ... | |
4802 | ||
4803 | // Remark 2: When particle weights are used there are some extra correlations. They are stored in | |
4804 | // fIntFlowExtraCorrelationsPro binning of which is organized as follows: | |
4805 | ||
4806 | // 1st bin: two1n1nW3W1 = <w1^3 w2 cos(n*(phi1-phi2))> | |
4807 | // 2nd bin: two1n1nW1W1W2 = <w1 w2 w3^2 cos(n*(phi1-phi2))> | |
4808 | ||
4809 | // multiplicity (number of particles used to determine the reaction plane) | |
4810 | Double_t dMult = (*fSMpk)(0,0); | |
4811 | ||
4812 | // real and imaginary parts of weighted Q-vectors evaluated in harmonics n, 2n, 3n and 4n: | |
4813 | Double_t dReQ1n1k = (*fReQ)(0,1); | |
4814 | Double_t dReQ2n2k = (*fReQ)(1,2); | |
4815 | Double_t dReQ3n3k = (*fReQ)(2,3); | |
4816 | Double_t dReQ4n4k = (*fReQ)(3,4); | |
4817 | Double_t dReQ1n3k = (*fReQ)(0,3); | |
4818 | Double_t dImQ1n1k = (*fImQ)(0,1); | |
4819 | Double_t dImQ2n2k = (*fImQ)(1,2); | |
4820 | Double_t dImQ3n3k = (*fImQ)(2,3); | |
4821 | Double_t dImQ4n4k = (*fImQ)(3,4); | |
4822 | Double_t dImQ1n3k = (*fImQ)(0,3); | |
4823 | ||
4824 | // dMs are variables introduced in order to simplify some Eqs. bellow: | |
4825 | //.............................................................................................. | |
4826 | Double_t dM11 = (*fSMpk)(1,1)-(*fSMpk)(0,2); // dM11 = sum_{i,j=1,i!=j}^M w_i w_j | |
4827 | Double_t dM22 = (*fSMpk)(1,2)-(*fSMpk)(0,4); // dM22 = sum_{i,j=1,i!=j}^M w_i^2 w_j^2 | |
4828 | Double_t dM33 = (*fSMpk)(1,3)-(*fSMpk)(0,6); // dM33 = sum_{i,j=1,i!=j}^M w_i^3 w_j^3 | |
4829 | Double_t dM44 = (*fSMpk)(1,4)-(*fSMpk)(0,8); // dM44 = sum_{i,j=1,i!=j}^M w_i^4 w_j^4 | |
4830 | Double_t dM31 = (*fSMpk)(0,3)*(*fSMpk)(0,1)-(*fSMpk)(0,4); // dM31 = sum_{i,j=1,i!=j}^M w_i^3 w_j | |
4831 | Double_t dM211 = (*fSMpk)(0,2)*(*fSMpk)(1,1)-2.*(*fSMpk)(0,3)*(*fSMpk)(0,1) | |
4832 | - (*fSMpk)(1,2)+2.*(*fSMpk)(0,4); // dM211 = sum_{i,j,k=1,i!=j!=k}^M w_i^2 w_j w_k | |
4833 | Double_t dM1111 = (*fSMpk)(3,1)-6.*(*fSMpk)(0,2)*(*fSMpk)(1,1) | |
4834 | + 8.*(*fSMpk)(0,3)*(*fSMpk)(0,1) | |
4835 | + 3.*(*fSMpk)(1,2)-6.*(*fSMpk)(0,4); // dM1111 = sum_{i,j,k,l=1,i!=j!=k!=l}^M w_i w_j w_k w_l | |
4836 | //.............................................................................................. | |
4837 | ||
4838 | // 2-particle correlations: | |
4839 | Double_t two1n1nW1W1 = 0.; // <w1 w2 cos(n*(phi1-phi2))> | |
4840 | Double_t two2n2nW2W2 = 0.; // <w1^2 w2^2 cos(2n*(phi1-phi2))> | |
4841 | Double_t two3n3nW3W3 = 0.; // <w1^3 w2^3 cos(3n*(phi1-phi2))> | |
4842 | Double_t two4n4nW4W4 = 0.; // <w1^4 w2^4 cos(4n*(phi1-phi2))> | |
4843 | if(dMult>1) | |
4844 | { | |
4845 | if(dM11) | |
4846 | { | |
4847 | two1n1nW1W1 = (pow(dReQ1n1k,2)+pow(dImQ1n1k,2)-(*fSMpk)(0,2))/dM11; | |
4848 | // average correlation <w1 w2 cos(n*(phi1-phi2))> for single event: | |
4849 | fIntFlowCorrelationsEBE->SetBinContent(1,two1n1nW1W1); | |
4850 | fIntFlowEventWeightsForCorrelationsEBE->SetBinContent(1,dM11); | |
4851 | // average correlation <w1 w2 cos(n*(phi1-phi2))> for all events: | |
b40a910e | 4852 | fIntFlowCorrelationsPro->Fill(0.5,two1n1nW1W1,dM11); |
4853 | // average squared correlation <w1 w2 cos(n*(phi1-phi2))> for all events: | |
4854 | fIntFlowSquaredCorrelationsPro->Fill(0.5,two1n1nW1W1*two1n1nW1W1,dM11); | |
489d5531 | 4855 | fIntFlowCorrelationsAllPro->Fill(0.5,two1n1nW1W1,dM11); |
4856 | } | |
4857 | if(dM22) | |
4858 | { | |
4859 | two2n2nW2W2 = (pow(dReQ2n2k,2)+pow(dImQ2n2k,2)-(*fSMpk)(0,4))/dM22; | |
4860 | // ... | |
4861 | // average correlation <w1^2 w2^2 cos(2n*(phi1-phi2))> for all events: | |
4862 | fIntFlowCorrelationsAllPro->Fill(1.5,two2n2nW2W2,dM22); | |
4863 | } | |
4864 | if(dM33) | |
4865 | { | |
4866 | two3n3nW3W3 = (pow(dReQ3n3k,2)+pow(dImQ3n3k,2)-(*fSMpk)(0,6))/dM33; | |
4867 | // ... | |
4868 | // average correlation <w1^3 w2^3 cos(3n*(phi1-phi2))> for all events: | |
4869 | fIntFlowCorrelationsAllPro->Fill(2.5,two3n3nW3W3,dM33); | |
4870 | } | |
4871 | if(dM44) | |
4872 | { | |
4873 | two4n4nW4W4 = (pow(dReQ4n4k,2)+pow(dImQ4n4k,2)-(*fSMpk)(0,8))/dM44; | |
4874 | // ... | |
4875 | // average correlation <w1^4 w2^4 cos(4n*(phi1-phi2))> for all events: | |
4876 | fIntFlowCorrelationsAllPro->Fill(3.5,two4n4nW4W4,dM44); | |
4877 | } | |
4878 | } // end of if(dMult>1) | |
4879 | ||
4880 | // extra 2-particle correlations: | |
4881 | Double_t two1n1nW3W1 = 0.; // <w1^3 w2 cos(n*(phi1-phi2))> | |
4882 | Double_t two1n1nW1W1W2 = 0.; // <w1 w2 w3^2 cos(n*(phi1-phi2))> | |
4883 | if(dMult>1) | |
4884 | { | |
4885 | if(dM31) | |
4886 | { | |
4887 | two1n1nW3W1 = (dReQ1n3k*dReQ1n1k+dImQ1n3k*dImQ1n1k-(*fSMpk)(0,4))/dM31; | |
4888 | fIntFlowExtraCorrelationsPro->Fill(0.5,two1n1nW3W1,dM31); | |
4889 | } | |
4890 | if(dM211) | |
4891 | { | |
4892 | two1n1nW1W1W2 = ((*fSMpk)(0,2)*(pow(dReQ1n1k,2)+pow(dImQ1n1k,2)-(*fSMpk)(0,2)) | |
4893 | - 2.*(dReQ1n3k*dReQ1n1k+dImQ1n3k*dImQ1n1k | |
4894 | - (*fSMpk)(0,4)))/dM211; | |
4895 | fIntFlowExtraCorrelationsPro->Fill(1.5,two1n1nW1W1W2,dM211); | |
4896 | } | |
4897 | } // end of if(dMult>1) | |
4898 | //.............................................................................................. | |
4899 | ||
4900 | //.............................................................................................. | |
4901 | // 3-particle correlations: | |
4902 | Double_t three2n1n1nW2W1W1 = 0.; // <w1^2 w2 w3 cos(n*(2phi1-phi2-phi3))> | |
4903 | ||
4904 | if(dMult>2) | |
4905 | { | |
4906 | if(dM211) | |
4907 | { | |
4908 | three2n1n1nW2W1W1 = (pow(dReQ1n1k,2.)*dReQ2n2k+2.*dReQ1n1k*dImQ1n1k*dImQ2n2k-pow(dImQ1n1k,2.)*dReQ2n2k | |
4909 | - 2.*(dReQ1n3k*dReQ1n1k+dImQ1n3k*dImQ1n1k) | |
4910 | - pow(dReQ2n2k,2)-pow(dImQ2n2k,2) | |
4911 | + 2.*(*fSMpk)(0,4))/dM211; | |
4912 | fIntFlowCorrelationsAllPro->Fill(5.5,three2n1n1nW2W1W1,dM211); | |
4913 | } | |
4914 | } // end of if(dMult>2) | |
4915 | //.............................................................................................. | |
4916 | ||
4917 | //.............................................................................................. | |
4918 | // 4-particle correlations: | |
4919 | Double_t four1n1n1n1nW1W1W1W1 = 0.; // <w1 w2 w3 w4 cos(n*(phi1+phi2-phi3-phi4))> | |
4920 | if(dMult>3) | |
4921 | { | |
4922 | if(dM1111) | |
4923 | { | |
4924 | four1n1n1n1nW1W1W1W1 = (pow(pow(dReQ1n1k,2.)+pow(dImQ1n1k,2.),2) | |
4925 | - 2.*(pow(dReQ1n1k,2.)*dReQ2n2k+2.*dReQ1n1k*dImQ1n1k*dImQ2n2k-pow(dImQ1n1k,2.)*dReQ2n2k) | |
4926 | + 8.*(dReQ1n3k*dReQ1n1k+dImQ1n3k*dImQ1n1k) | |
4927 | + (pow(dReQ2n2k,2)+pow(dImQ2n2k,2)) | |
4928 | - 4.*(*fSMpk)(0,2)*(pow(dReQ1n1k,2)+pow(dImQ1n1k,2)) | |
4929 | - 6.*(*fSMpk)(0,4)+2.*(*fSMpk)(1,2))/dM1111; | |
4930 | ||
4931 | // average correlation <w1 w2 w3 w4 cos(n*(phi1+phi2-phi3-phi4))> for single event: | |
4932 | fIntFlowCorrelationsEBE->SetBinContent(2,four1n1n1n1nW1W1W1W1); | |
4933 | fIntFlowEventWeightsForCorrelationsEBE->SetBinContent(2,dM1111); | |
4934 | // average correlation <w1 w2 w3 w4 cos(n*(phi1+phi2-phi3-phi4))> for all events: | |
4935 | fIntFlowCorrelationsPro->Fill(1.5,four1n1n1n1nW1W1W1W1,dM1111); | |
b40a910e | 4936 | // average squared correlation <w1 w2 w3 w4 cos(n*(phi1+phi2-phi3-phi4))> for all events: |
4937 | fIntFlowSquaredCorrelationsPro->Fill(1.5,four1n1n1n1nW1W1W1W1*four1n1n1n1nW1W1W1W1,dM1111); | |
489d5531 | 4938 | fIntFlowCorrelationsAllPro->Fill(10.5,four1n1n1n1nW1W1W1W1,dM1111); |
4939 | } | |
4940 | } // end of if(dMult>3) | |
4941 | //.............................................................................................. | |
4942 | ||
4943 | } // end of AliFlowAnalysisWithQCumulants::CalculateIntFlowCorrelationsUsingParticleWeights() | |
4944 | ||
489d5531 | 4945 | //================================================================================================================================ |
4946 | ||
489d5531 | 4947 | void AliFlowAnalysisWithQCumulants::InitializeArraysForIntFlow() |
4948 | { | |
4949 | // Initialize all arrays used to calculate integrated flow. | |
4950 | ||
4951 | for(Int_t sc=0;sc<2;sc++) // sin or cos terms | |
4952 | { | |
4953 | fIntFlowCorrectionTermsForNUAEBE[sc] = NULL; | |
0328db2d | 4954 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[sc] = NULL; |
489d5531 | 4955 | fIntFlowCorrectionTermsForNUAPro[sc] = NULL; |
4956 | fIntFlowCorrectionTermsForNUAHist[sc] = NULL; | |
b92ea2b9 | 4957 | for(Int_t ci=0;ci<4;ci++) // correction term index (to be improved - hardwired 4) |
2001bc3a | 4958 | { |
4959 | fIntFlowCorrectionTermsForNUAVsMPro[sc][ci] = NULL; | |
4960 | } | |
0328db2d | 4961 | for(Int_t power=0;power<2;power++) // linear or quadratic |
4962 | { | |
4963 | fIntFlowSumOfEventWeightsNUA[sc][power] = NULL; | |
4964 | } | |
489d5531 | 4965 | } |
4966 | for(Int_t power=0;power<2;power++) // linear or quadratic | |
4967 | { | |
4968 | fIntFlowSumOfEventWeights[power] = NULL; | |
4969 | } | |
b3dacf6b | 4970 | for(Int_t i=0;i<4;i++) // print on the screen the final results (0=RF, 1=RP, 2=POI, 3=RF (rebbined in M)) |
489d5531 | 4971 | { |
4972 | fPrintFinalResults[i] = kTRUE; | |
4973 | } | |
ff70ca91 | 4974 | for(Int_t ci=0;ci<4;ci++) // correlation index or cumulant order |
4975 | { | |
4976 | fIntFlowCorrelationsVsMPro[ci] = NULL; | |
b40a910e | 4977 | fIntFlowSquaredCorrelationsVsMPro[ci] = NULL; |
ff70ca91 | 4978 | fIntFlowCorrelationsVsMHist[ci] = NULL; |
4979 | fIntFlowQcumulantsVsM[ci] = NULL; | |
4980 | fIntFlowVsM[ci] = NULL; | |
2001bc3a | 4981 | fIntFlowDetectorBiasVsM[ci] = NULL; |
ff70ca91 | 4982 | for(Int_t lc=0;lc<2;lc++) |
4983 | { | |
4984 | fIntFlowSumOfEventWeightsVsM[ci][lc] = NULL; | |
4985 | } | |
4986 | } | |
4987 | for(Int_t pi=0;pi<6;pi++) // product or covariance index | |
4988 | { | |
4989 | fIntFlowProductOfCorrelationsVsMPro[pi] = NULL; | |
4990 | fIntFlowCovariancesVsM[pi] = NULL; | |
4991 | fIntFlowSumOfProductOfEventWeightsVsM[pi] = NULL; | |
4992 | } | |
e5834fcb | 4993 | |
489d5531 | 4994 | } // end of void AliFlowAnalysisWithQCumulants::InitializeArraysForIntFlow() |
4995 | ||
489d5531 | 4996 | //================================================================================================================================ |
4997 | ||
489d5531 | 4998 | void AliFlowAnalysisWithQCumulants::InitializeArraysForDiffFlow() |
4999 | { | |
5000 | // Initialize all arrays needed to calculate differential flow. | |
5001 | // a) Initialize lists holding profiles; | |
5002 | // b) Initialize lists holding histograms; | |
5003 | // c) Initialize event-by-event quantities; | |
5004 | // d) Initialize profiles; | |
5005 | // e) Initialize histograms holding final results. | |
5006 | ||
5007 | // a) Initialize lists holding profiles; | |
5008 | for(Int_t t=0;t<2;t++) // type (RP, POI) | |
5009 | { | |
5010 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
5011 | { | |
5012 | fDiffFlowCorrelationsProList[t][pe] = NULL; | |
5013 | fDiffFlowProductOfCorrelationsProList[t][pe] = NULL; | |
5014 | fDiffFlowCorrectionsProList[t][pe] = NULL; | |
5015 | } | |
5016 | } | |
5017 | ||
5018 | // b) Initialize lists holding histograms; | |
5019 | for(Int_t t=0;t<2;t++) // type (RP, POI) | |
5020 | { | |
5021 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
5022 | { | |
5023 | fDiffFlowCorrelationsHistList[t][pe] = NULL; | |
5024 | for(Int_t power=0;power<2;power++) | |
5025 | { | |
5026 | fDiffFlowSumOfEventWeightsHistList[t][pe][power] = NULL; | |
5027 | } // end of for(Int_t power=0;power<2;power++) | |
5028 | fDiffFlowSumOfProductOfEventWeightsHistList[t][pe] = NULL; | |
5029 | fDiffFlowCorrectionsHistList[t][pe] = NULL; | |
5030 | fDiffFlowCovariancesHistList[t][pe] = NULL; | |
5031 | fDiffFlowCumulantsHistList[t][pe] = NULL; | |
5032 | fDiffFlowHistList[t][pe] = NULL; | |
5033 | } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta | |
5034 | } // enf of for(Int_t t=0;t<2;t++) // type (RP, POI) | |
5035 | ||
5036 | // c) Initialize event-by-event quantities: | |
5037 | // 1D: | |
5038 | for(Int_t t=0;t<3;t++) // type (RP, POI, POI&&RP) | |
5039 | { | |
5040 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
5041 | { | |
5042 | for(Int_t m=0;m<4;m++) // multiple of harmonic | |
5043 | { | |
5044 | for(Int_t k=0;k<9;k++) // power of weight | |
5045 | { | |
5046 | fReRPQ1dEBE[t][pe][m][k] = NULL; | |
5047 | fImRPQ1dEBE[t][pe][m][k] = NULL; | |
5048 | fs1dEBE[t][pe][k] = NULL; // to be improved (this doesn't need to be within loop over m) | |
5049 | } | |
5050 | } | |
5051 | } | |
5052 | } | |
5053 | // 1D: | |
5054 | for(Int_t t=0;t<2;t++) // type (RP or POI) | |
5055 | { | |
5056 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
5057 | { | |
5058 | for(Int_t sc=0;sc<2;sc++) // sin or cos terms | |
5059 | { | |
5060 | for(Int_t cti=0;cti<9;cti++) // correction term index | |
5061 | { | |
5062 | fDiffFlowCorrectionTermsForNUAEBE[t][pe][sc][cti] = NULL; | |
5063 | } | |
5064 | } | |
5065 | } | |
5066 | } | |
5067 | // 2D: | |
5068 | for(Int_t t=0;t<3;t++) // type (RP, POI, POI&&RP) | |
5069 | { | |
5070 | for(Int_t m=0;m<4;m++) // multiple of harmonic | |
5071 | { | |
5072 | for(Int_t k=0;k<9;k++) // power of weight | |
5073 | { | |
5074 | fReRPQ2dEBE[t][m][k] = NULL; | |
5075 | fImRPQ2dEBE[t][m][k] = NULL; | |
5076 | fs2dEBE[t][k] = NULL; // to be improved (this doesn't need to be within loop over m) | |
5077 | } | |
5078 | } | |
5079 | } | |
5080 | ||
5081 | // d) Initialize profiles: | |
5082 | for(Int_t t=0;t<2;t++) // type: RP or POI | |
5083 | { | |
5084 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
5085 | { | |
5086 | for(Int_t ci=0;ci<4;ci++) // correlation index | |
5087 | { | |
5088 | fDiffFlowCorrelationsPro[t][pe][ci] = NULL; | |
b40a910e | 5089 | fDiffFlowSquaredCorrelationsPro[t][pe][ci] = NULL; |
489d5531 | 5090 | } // end of for(Int_t ci=0;ci<4;ci++) |
5091 | for(Int_t mci1=0;mci1<8;mci1++) // mixed correlation index | |
5092 | { | |
5093 | for(Int_t mci2=0;mci2<8;mci2++) // mixed correlation index | |
5094 | { | |
5095 | fDiffFlowProductOfCorrelationsPro[t][pe][mci1][mci2] = NULL; | |
5096 | } // end of for(Int_t mci2=0;mci2<8;mci2++) // mixed correlation index | |
5097 | } // end of for(Int_t mci1=0;mci1<8;mci1++) // mixed correlation index | |
5098 | // correction terms for nua: | |
5099 | for(Int_t sc=0;sc<2;sc++) // sin or cos terms | |
5100 | { | |
5101 | for(Int_t cti=0;cti<9;cti++) // correction term index | |
5102 | { | |
5103 | fDiffFlowCorrectionTermsForNUAPro[t][pe][sc][cti] = NULL; | |
5104 | } | |
5105 | } | |
5106 | } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta | |
5107 | } // end of for(Int_t t=0;t<2;t++) // type: RP or POI | |
5108 | ||
5109 | // e) Initialize histograms holding final results. | |
5110 | for(Int_t t=0;t<2;t++) // type: RP or POI | |
5111 | { | |
5112 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
5113 | { | |
5114 | for(Int_t ci=0;ci<4;ci++) // correlation index | |
5115 | { | |
5116 | fDiffFlowCorrelationsHist[t][pe][ci] = NULL; | |
5117 | fDiffFlowCumulants[t][pe][ci] = NULL; | |
5118 | fDiffFlow[t][pe][ci] = NULL; | |
5119 | } // end of for(Int_t ci=0;ci<4;ci++) | |
5120 | for(Int_t covarianceIndex=0;covarianceIndex<5;covarianceIndex++) | |
5121 | { | |
5122 | fDiffFlowCovariances[t][pe][covarianceIndex] = NULL; | |
5123 | } // end of for(Int_t covarianceIndex=0;covarianceIndex<5;covarianceIndex++) | |
5124 | // correction terms for nua: | |
5125 | for(Int_t sc=0;sc<2;sc++) // sin or cos terms | |
5126 | { | |
5127 | for(Int_t cti=0;cti<9;cti++) // correction term index | |
5128 | { | |
5129 | fDiffFlowCorrectionTermsForNUAHist[t][pe][sc][cti] = NULL; | |
5130 | } | |
5131 | } | |
5132 | } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta | |
5133 | } // end of for(Int_t t=0;t<2;t++) // type: RP or POI | |
5134 | ||
5135 | // sum of event weights for reduced correlations: | |
5136 | for(Int_t t=0;t<2;t++) // type = RP or POI | |
5137 | { | |
5138 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
5139 | { | |
5140 | for(Int_t p=0;p<2;p++) // power of weight is 1 or 2 | |
5141 | { | |
5142 | for(Int_t ew=0;ew<4;ew++) // event weight index for reduced correlations | |
5143 | { | |
5144 | fDiffFlowSumOfEventWeights[t][pe][p][ew] = NULL; | |
5145 | } | |
5146 | } | |
5147 | } | |
5148 | } | |
5149 | // product of event weights for both types of correlations: | |
5150 | for(Int_t t=0;t<2;t++) // type = RP or POI | |
5151 | { | |
5152 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
5153 | { | |
5154 | for(Int_t mci1=0;mci1<8;mci1++) // mixed correlation index | |
5155 | { | |
5156 | for(Int_t mci2=0;mci2<8;mci2++) // mixed correlation index | |
5157 | { | |
5158 | fDiffFlowSumOfProductOfEventWeights[t][pe][mci1][mci2] = NULL; | |
5159 | } | |
5160 | } | |
5161 | } | |
5162 | } | |
5163 | ||
5164 | ||
5165 | ||
5166 | ||
5167 | /* | |
5168 | ||
5169 | // nested lists in fDiffFlowProfiles: | |
5170 | for(Int_t t=0;t<2;t++) | |
5171 | { | |
5172 | fDFPType[t] = NULL; | |
5173 | for(Int_t pW=0;pW<2;pW++) // particle weights not used (0) or used (1) | |
5174 | { | |
5175 | fDFPParticleWeights[t][pW] = NULL; | |
5176 | for(Int_t eW=0;eW<2;eW++) | |
5177 | { | |
5178 | fDFPEventWeights[t][pW][eW] = NULL; | |
5179 | fDiffFlowCorrelations[t][pW][eW] = NULL; | |
5180 | fDiffFlowProductsOfCorrelations[t][pW][eW] = NULL; | |
5181 | for(Int_t sc=0;sc<2;sc++) | |
5182 | { | |
5183 | fDiffFlowCorrectionTerms[t][pW][eW][sc] = NULL; | |
5184 | } | |
5185 | } | |
5186 | } | |
5187 | } | |
5188 | ||
5189 | ||
5190 | */ | |
5191 | ||
5192 | ||
5193 | ||
5194 | /* | |
5195 | for(Int_t pW=0;pW<2;pW++) // particle weights not used (0) or used (1) | |
5196 | { | |
5197 | for(Int_t eW=0;eW<2;eW++) | |
5198 | { | |
5199 | // correlations: | |
5200 | for(Int_t correlationIndex=0;correlationIndex<4;correlationIndex++) | |
5201 | { | |
5202 | fCorrelationsPro[t][pW][eW][correlationIndex] = NULL; | |
5203 | } | |
5204 | // products of correlations: | |
5205 | for(Int_t productOfCorrelationsIndex=0;productOfCorrelationsIndex<6;productOfCorrelationsIndex++) | |
5206 | { | |
5207 | fProductsOfCorrelationsPro[t][pW][eW][productOfCorrelationsIndex] = NULL; | |
5208 | } | |
5209 | // correction terms: | |
5210 | for(Int_t sc=0;sc<2;sc++) | |
5211 | { | |
5212 | for(Int_t correctionsIndex=0;correctionsIndex<2;correctionsIndex++) | |
5213 | { | |
5214 | fCorrectionTermsPro[t][pW][eW][sc][correctionsIndex] = NULL; | |
5215 | } | |
5216 | } | |
5217 | } | |
5218 | } | |
5219 | */ | |
5220 | ||
5221 | } // end of AliFlowAnalysisWithQCumulants::InitializeArraysForDiffFlow() | |
5222 | ||
5223 | ||
5224 | //================================================================================================================================ | |
5225 | /* | |
5226 | ||
5227 | ||
5228 | void AliFlowAnalysisWithQCumulants::CalculateCorrelationsForDifferentialFlow2D(TString type) | |
5229 | { | |
5230 | // calculate all reduced correlations needed for differential flow for each (pt,eta) bin: | |
5231 | ||
5232 | if(type == "RP") // to be improved (removed) | |
5233 | { | |
5234 | cout<<endl; | |
5235 | } | |
5236 | // ... | |
5237 | ||
5238 | ||
5239 | Int_t typeFlag = -1; | |
5240 | ||
5241 | // reduced correlations ares stored in fCorrelationsPro[t][pW][index] and are indexed as follows: | |
5242 | // index: | |
5243 | // 0: <2'> | |
5244 | // 1: <4'> | |
5245 | ||
5246 | // multiplicity: | |
5247 | Double_t dMult = (*fSMpk)(0,0); | |
5248 | ||
5249 | // real and imaginary parts of non-weighted Q-vectors evaluated in harmonics n, 2n, 3n and 4n: | |
5250 | Double_t dReQ1n = (*fReQ)(0,0); | |
5251 | Double_t dReQ2n = (*fReQ)(1,0); | |
5252 | //Double_t dReQ3n = (*fReQ)(2,0); | |
5253 | //Double_t dReQ4n = (*fReQ)(3,0); | |
5254 | Double_t dImQ1n = (*fImQ)(0,0); | |
5255 | Double_t dImQ2n = (*fImQ)(1,0); | |
5256 | //Double_t dImQ3n = (*fImQ)(2,0); | |
5257 | //Double_t dImQ4n = (*fImQ)(3,0); | |
5258 | ||
5259 | // looping over all (pt,eta) bins and calculating correlations needed for differential flow: | |
5260 | for(Int_t p=1;p<=fnBinsPt;p++) | |
5261 | { | |
5262 | for(Int_t e=1;e<=fnBinsEta;e++) | |
5263 | { | |
5264 | // real and imaginary parts of p_{m*n,0} (non-weighted Q-vector evaluated for POIs in particular (pt,eta) bin): | |
5265 | Double_t p1n0kRe = 0.; | |
5266 | Double_t p1n0kIm = 0.; | |
5267 | ||
5268 | // number of POIs in particular (pt,eta) bin: | |
5269 | Double_t mp = 0.; | |
5270 | ||
5271 | // real and imaginary parts of q_{m*n,0} (non-weighted Q-vector evaluated for particles which are both RPs and POIs in particular (pt,eta) bin): | |
5272 | Double_t q1n0kRe = 0.; | |
5273 | Double_t q1n0kIm = 0.; | |
5274 | Double_t q2n0kRe = 0.; | |
5275 | Double_t q2n0kIm = 0.; | |
5276 | ||
5277 | // number of particles which are both RPs and POIs in particular (pt,eta) bin: | |
5278 | Double_t mq = 0.; | |
5279 | ||
5280 | // q_{m*n,0}: | |
5281 | q1n0kRe = fReEBE2D[2][0][0]->GetBinContent(fReEBE2D[2][0][0]->GetBin(p,e)) | |
5282 | * fReEBE2D[2][0][0]->GetBinEntries(fReEBE2D[2][0][0]->GetBin(p,e)); | |
5283 | q1n0kIm = fImEBE2D[2][0][0]->GetBinContent(fImEBE2D[2][0][0]->GetBin(p,e)) | |
5284 | * fImEBE2D[2][0][0]->GetBinEntries(fImEBE2D[2][0][0]->GetBin(p,e)); | |
5285 | q2n0kRe = fReEBE2D[2][1][0]->GetBinContent(fReEBE2D[2][1][0]->GetBin(p,e)) | |
5286 | * fReEBE2D[2][1][0]->GetBinEntries(fReEBE2D[2][1][0]->GetBin(p,e)); | |
5287 | q2n0kIm = fImEBE2D[2][1][0]->GetBinContent(fImEBE2D[2][1][0]->GetBin(p,e)) | |
5288 | * fImEBE2D[2][1][0]->GetBinEntries(fImEBE2D[2][1][0]->GetBin(p,e)); | |
5289 | ||
5290 | mq = fReEBE2D[2][0][0]->GetBinEntries(fReEBE2D[2][0][0]->GetBin(p,e)); // to be improved (cross-checked by accessing other profiles here) | |
5291 | ||
5292 | if(type == "POI") | |
5293 | { | |
5294 | // p_{m*n,0}: | |
5295 | p1n0kRe = fReEBE2D[1][0][0]->GetBinContent(fReEBE2D[1][0][0]->GetBin(p,e)) | |
5296 | * fReEBE2D[1][0][0]->GetBinEntries(fReEBE2D[1][0][0]->GetBin(p,e)); | |
5297 | p1n0kIm = fImEBE2D[1][0][0]->GetBinContent(fImEBE2D[1][0][0]->GetBin(p,e)) | |
5298 | * fImEBE2D[1][0][0]->GetBinEntries(fImEBE2D[1][0][0]->GetBin(p,e)); | |
5299 | ||
5300 | mp = fReEBE2D[1][0][0]->GetBinEntries(fReEBE2D[1][0][0]->GetBin(p,e)); // to be improved (cross-checked by accessing other profiles here) | |
5301 | ||
5302 | typeFlag = 1; | |
5303 | } | |
5304 | else if(type == "RP") | |
5305 | { | |
5306 | // p_{m*n,0} = q_{m*n,0}: | |
5307 | p1n0kRe = q1n0kRe; | |
5308 | p1n0kIm = q1n0kIm; | |
5309 | mp = mq; | |
5310 | ||
5311 | typeFlag = 0; | |
5312 | } | |
5313 | ||
5314 | // count events with non-empty (pt,eta) bin: | |
5315 | if(mp>0) | |
5316 | { | |
5317 | fNonEmptyBins2D[typeFlag]->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,1); | |
5318 | } | |
5319 | ||
5320 | // 2'-particle correlation for particular (pt,eta) bin: | |
5321 | Double_t two1n1nPtEta = 0.; | |
5322 | if(mp*dMult-mq) | |
5323 | { | |
5324 | two1n1nPtEta = (p1n0kRe*dReQ1n+p1n0kIm*dImQ1n-mq) | |
5325 | / (mp*dMult-mq); | |
5326 | ||
5327 | // fill the 2D profile to get the average correlation for each (pt,eta) bin: | |
5328 | if(type == "POI") | |
5329 | { | |
5330 | //f2pPtEtaPOI->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,two1n1nPtEta,mp*dMult-mq); | |
5331 | ||
5332 | fCorrelationsPro[1][0][0][0]->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,two1n1nPtEta,mp*dMult-mq); | |
5333 | } | |
5334 | else if(type == "RP") | |
5335 | { | |
5336 | //f2pPtEtaRP->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,two1n1nPtEta,mp*dMult-mq); | |
5337 | fCorrelationsPro[0][0][0][0]->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,two1n1nPtEta,mp*dMult-mq); | |
5338 | } | |
5339 | } // end of if(mp*dMult-mq) | |
5340 | ||
5341 | // 4'-particle correlation: | |
5342 | Double_t four1n1n1n1nPtEta = 0.; | |
5343 | if((mp-mq)*dMult*(dMult-1.)*(dMult-2.) | |
5344 | + mq*(dMult-1.)*(dMult-2.)*(dMult-3.)) // to be improved (introduce a new variable for this expression) | |
5345 | { | |
5346 | four1n1n1n1nPtEta = ((pow(dReQ1n,2.)+pow(dImQ1n,2.))*(p1n0kRe*dReQ1n+p1n0kIm*dImQ1n) | |
5347 | - q2n0kRe*(pow(dReQ1n,2.)-pow(dImQ1n,2.)) | |
5348 | - 2.*q2n0kIm*dReQ1n*dImQ1n | |
5349 | - p1n0kRe*(dReQ1n*dReQ2n+dImQ1n*dImQ2n) | |
5350 | + p1n0kIm*(dImQ1n*dReQ2n-dReQ1n*dImQ2n) | |
5351 | - 2.*dMult*(p1n0kRe*dReQ1n+p1n0kIm*dImQ1n) | |
5352 | - 2.*(pow(dReQ1n,2.)+pow(dImQ1n,2.))*mq | |
5353 | + 6.*(q1n0kRe*dReQ1n+q1n0kIm*dImQ1n) | |
5354 | + 1.*(q2n0kRe*dReQ2n+q2n0kIm*dImQ2n) | |
5355 | + 2.*(p1n0kRe*dReQ1n+p1n0kIm*dImQ1n) | |
5356 | + 2.*mq*dMult | |
5357 | - 6.*mq) | |
5358 | / ((mp-mq)*dMult*(dMult-1.)*(dMult-2.) | |
5359 | + mq*(dMult-1.)*(dMult-2.)*(dMult-3.)); | |
5360 | ||
5361 | // fill the 2D profile to get the average correlation for each (pt, eta) bin: | |
5362 | if(type == "POI") | |
5363 | { | |
5364 | //f4pPtEtaPOI->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,four1n1n1n1nPtEta, | |
5365 | // (mp-mq)*dMult*(dMult-1.)*(dMult-2.) | |
5366 | // + mq*(dMult-1.)*(dMult-2.)*(dMult-3.)); | |
5367 | ||
5368 | fCorrelationsPro[1][0][0][1]->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,four1n1n1n1nPtEta, | |
5369 | (mp-mq)*dMult*(dMult-1.)*(dMult-2.) | |
5370 | + mq*(dMult-1.)*(dMult-2.)*(dMult-3.)); | |
5371 | } | |
5372 | else if(type == "RP") | |
5373 | { | |
5374 | //f4pPtEtaRP->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,four1n1n1n1nPtEta, | |
5375 | // (mp-mq)*dMult*(dMult-1.)*(dMult-2.) | |
5376 | // + mq*(dMult-1.)*(dMult-2.)*(dMult-3.)); | |
5377 | ||
5378 | fCorrelationsPro[0][0][0][1]->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,four1n1n1n1nPtEta, | |
5379 | (mp-mq)*dMult*(dMult-1.)*(dMult-2.) | |
5380 | + mq*(dMult-1.)*(dMult-2.)*(dMult-3.)); | |
5381 | } | |
5382 | } // end of if((mp-mq)*dMult*(dMult-1.)*(dMult-2.) | |
5383 | // +mq*(dMult-1.)*(dMult-2.)*(dMult-3.)) | |
5384 | ||
5385 | } // end of for(Int_t e=1;e<=fnBinsEta;e++) | |
5386 | } // end of for(Int_t p=1;p<=fnBinsPt;p++) | |
5387 | ||
5388 | ||
5389 | ||
5390 | ||
5391 | ||
5392 | } // end of AliFlowAnalysisWithQCumulants::CalculateCorrelationsForDifferentialFlow2D() | |
5393 | ||
5394 | ||
5395 | ||
5396 | ||
5397 | ||
5398 | ||
5399 | //================================================================================================================================ | |
5400 | ||
5401 | ||
5402 | void AliFlowAnalysisWithQCumulants::CalculateWeightedCorrelationsForDifferentialFlow2D(TString type) | |
5403 | { | |
5404 | // calculate all weighted correlations needed for differential flow | |
5405 | ||
5406 | if(type == "RP") // to be improved (removed) | |
5407 | { | |
5408 | cout<<endl; | |
5409 | } | |
5410 | // ... | |
5411 | ||
5412 | ||
5413 | ||
5414 | ||
5415 | // real and imaginary parts of weighted Q-vectors evaluated in harmonics n, 2n, 3n and 4n: | |
5416 | Double_t dReQ1n1k = (*fReQ)(0,1); | |
5417 | Double_t dReQ2n2k = (*fReQ)(1,2); | |
5418 | Double_t dReQ1n3k = (*fReQ)(0,3); | |
5419 | //Double_t dReQ4n4k = (*fReQ)(3,4); | |
5420 | Double_t dImQ1n1k = (*fImQ)(0,1); | |
5421 | Double_t dImQ2n2k = (*fImQ)(1,2); | |
5422 | Double_t dImQ1n3k = (*fImQ)(0,3); | |
5423 | //Double_t dImQ4n4k = (*fImQ)(3,4); | |
5424 | ||
5425 | // S^M_{p,k} (see .h file for the definition of fSMpk): | |
5426 | Double_t dSM1p1k = (*fSMpk)(0,1); | |
5427 | Double_t dSM1p2k = (*fSMpk)(0,2); | |
5428 | Double_t dSM1p3k = (*fSMpk)(0,3); | |
5429 | Double_t dSM2p1k = (*fSMpk)(1,1); | |
5430 | Double_t dSM3p1k = (*fSMpk)(2,1); | |
5431 | ||
5432 | // looping over all (pt,eta) bins and calculating weighted correlations needed for differential flow: | |
5433 | for(Int_t p=1;p<=fnBinsPt;p++) | |
5434 | { | |
5435 | for(Int_t e=1;e<=fnBinsEta;e++) | |
5436 | { | |
5437 | // real and imaginary parts of p_{m*n,0} (non-weighted Q-vector evaluated for POIs in particular (pt,eta) bin): | |
5438 | Double_t p1n0kRe = 0.; | |
5439 | Double_t p1n0kIm = 0.; | |
5440 | ||
5441 | // number of POIs in particular (pt,eta) bin): | |
5442 | Double_t mp = 0.; | |
5443 | ||
5444 | // real and imaginary parts of q_{m*n,k}: | |
5445 | // (weighted Q-vector evaluated for particles which are both RPs and POIs in particular (pt,eta) bin) | |
5446 | Double_t q1n2kRe = 0.; | |
5447 | Double_t q1n2kIm = 0.; | |
5448 | Double_t q2n1kRe = 0.; | |
5449 | Double_t q2n1kIm = 0.; | |
5450 | ||
5451 | // s_{1,1}, s_{1,2} and s_{1,3} // to be improved (add explanation) | |
5452 | Double_t s1p1k = 0.; | |
5453 | Double_t s1p2k = 0.; | |
5454 | Double_t s1p3k = 0.; | |
5455 | ||
5456 | // M0111 from Eq. (118) in QC2c (to be improved (notation)) | |
5457 | Double_t dM0111 = 0.; | |
5458 | ||
5459 | if(type == "POI") | |
5460 | { | |
5461 | // p_{m*n,0}: | |
5462 | p1n0kRe = fReEBE2D[1][0][0]->GetBinContent(fReEBE2D[1][0][0]->GetBin(p,e)) | |
5463 | * fReEBE2D[1][0][0]->GetBinEntries(fReEBE2D[1][0][0]->GetBin(p,e)); | |
5464 | p1n0kIm = fImEBE2D[1][0][0]->GetBinContent(fImEBE2D[1][0][0]->GetBin(p,e)) | |
5465 | * fImEBE2D[1][0][0]->GetBinEntries(fImEBE2D[1][0][0]->GetBin(p,e)); | |
5466 | ||
5467 | mp = fReEBE2D[1][0][0]->GetBinEntries(fReEBE2D[1][0][0]->GetBin(p,e)); | |
5468 | ||
5469 | // q_{m*n,k}: | |
5470 | q1n2kRe = fReEBE2D[2][0][2]->GetBinContent(fReEBE2D[2][0][2]->GetBin(p,e)) | |
5471 | * fReEBE2D[2][0][2]->GetBinEntries(fReEBE2D[2][0][2]->GetBin(p,e)); | |
5472 | q1n2kIm = fImEBE2D[2][0][2]->GetBinContent(fImEBE2D[2][0][2]->GetBin(p,e)) | |
5473 | * fImEBE2D[2][0][2]->GetBinEntries(fImEBE2D[2][0][2]->GetBin(p,e)); | |
5474 | q2n1kRe = fReEBE2D[2][1][1]->GetBinContent(fReEBE2D[2][1][1]->GetBin(p,e)) | |
5475 | * fReEBE2D[2][1][1]->GetBinEntries(fReEBE2D[2][1][1]->GetBin(p,e)); | |
5476 | q2n1kIm = fImEBE2D[2][1][1]->GetBinContent(fImEBE2D[2][1][1]->GetBin(p,e)) | |
5477 | * fImEBE2D[2][1][1]->GetBinEntries(fImEBE2D[2][1][1]->GetBin(p,e)); | |
5478 | ||
5479 | // s_{1,1}, s_{1,2} and s_{1,3} // to be improved (add explanation) | |
5480 | s1p1k = pow(fs2D[2][1]->GetBinContent(fs2D[2][1]->GetBin(p,e)),1.); | |
5481 | s1p2k = pow(fs2D[2][2]->GetBinContent(fs2D[2][2]->GetBin(p,e)),1.); | |
5482 | s1p3k = pow(fs2D[2][3]->GetBinContent(fs2D[2][3]->GetBin(p,e)),1.); | |
5483 | ||
5484 | // M0111 from Eq. (118) in QC2c (to be improved (notation)): | |
5485 | dM0111 = mp*(dSM3p1k-3.*dSM1p1k*dSM1p2k+2.*dSM1p3k) | |
5486 | - 3.*(s1p1k*(dSM2p1k-dSM1p2k) | |
5487 | + 2.*(s1p3k-s1p2k*dSM1p1k)); | |
5488 | } | |
5489 | else if(type == "RP") | |
5490 | { | |
5491 | p1n0kRe = fReEBE2D[0][0][0]->GetBinContent(fReEBE2D[0][0][0]->GetBin(p,e)) | |
5492 | * fReEBE2D[0][0][0]->GetBinEntries(fReEBE2D[0][0][0]->GetBin(p,e)); | |
5493 | p1n0kIm = fImEBE2D[0][0][0]->GetBinContent(fImEBE2D[0][0][0]->GetBin(p,e)) | |
5494 | * fImEBE2D[0][0][0]->GetBinEntries(fImEBE2D[0][0][0]->GetBin(p,e)); | |
5495 | ||
5496 | mp = fReEBE2D[0][0][0]->GetBinEntries(fReEBE2D[0][0][0]->GetBin(p,e)); | |
5497 | ||
5498 | // q_{m*n,k}: | |
5499 | q1n2kRe = fReEBE2D[0][0][2]->GetBinContent(fReEBE2D[0][0][2]->GetBin(p,e)) | |
5500 | * fReEBE2D[0][0][2]->GetBinEntries(fReEBE2D[0][0][2]->GetBin(p,e)); | |
5501 | q1n2kIm = fImEBE2D[0][0][2]->GetBinContent(fImEBE2D[0][0][2]->GetBin(p,e)) | |
5502 | * fImEBE2D[0][0][2]->GetBinEntries(fImEBE2D[0][0][2]->GetBin(p,e)); | |
5503 | q2n1kRe = fReEBE2D[0][1][1]->GetBinContent(fReEBE2D[0][1][1]->GetBin(p,e)) | |
5504 | * fReEBE2D[0][1][1]->GetBinEntries(fReEBE2D[0][1][1]->GetBin(p,e)); | |
5505 | q2n1kIm = fImEBE2D[0][1][1]->GetBinContent(fImEBE2D[0][1][1]->GetBin(p,e)) | |
5506 | * fImEBE2D[0][1][1]->GetBinEntries(fImEBE2D[0][1][1]->GetBin(p,e)); | |
5507 | ||
5508 | // s_{1,1}, s_{1,2} and s_{1,3} // to be improved (add explanation) | |
5509 | s1p1k = pow(fs2D[0][1]->GetBinContent(fs2D[0][1]->GetBin(p,e)),1.); | |
5510 | s1p2k = pow(fs2D[0][2]->GetBinContent(fs2D[0][2]->GetBin(p,e)),1.); | |
5511 | s1p3k = pow(fs2D[0][3]->GetBinContent(fs2D[0][3]->GetBin(p,e)),1.); | |
5512 | ||
5513 | // M0111 from Eq. (118) in QC2c (to be improved (notation)): | |
5514 | dM0111 = mp*(dSM3p1k-3.*dSM1p1k*dSM1p2k+2.*dSM1p3k) | |
5515 | - 3.*(s1p1k*(dSM2p1k-dSM1p2k) | |
5516 | + 2.*(s1p3k-s1p2k*dSM1p1k)); | |
5517 | //............................................................................................... | |
5518 | } | |
5519 | ||
5520 | // 2'-particle correlation: | |
5521 | Double_t two1n1nW0W1PtEta = 0.; | |
5522 | if(mp*dSM1p1k-s1p1k) | |
5523 | { | |
5524 | two1n1nW0W1PtEta = (p1n0kRe*dReQ1n1k+p1n0kIm*dImQ1n1k-s1p1k) | |
5525 | / (mp*dSM1p1k-s1p1k); | |
5526 | ||
5527 | // fill the 2D profile to get the average correlation for each (pt, eta) bin: | |
5528 | if(type == "POI") | |
5529 | { | |
5530 | //f2pPtEtaPOIW->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,two1n1nW0W1PtEta, | |
5531 | // mp*dSM1p1k-s1p1k); | |
5532 | fCorrelationsPro[1][1][0][0]->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,two1n1nW0W1PtEta,mp*dSM1p1k-s1p1k); | |
5533 | } | |
5534 | else if(type == "RP") | |
5535 | { | |
5536 | //f2pPtEtaRPW->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,two1n1nW0W1PtEta, | |
5537 | // mp*dSM1p1k-s1p1k); | |
5538 | fCorrelationsPro[0][1][0][0]->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,two1n1nW0W1PtEta,mp*dSM1p1k-s1p1k); | |
5539 | } | |
5540 | } // end of if(mp*dMult-dmPrimePrimePtEta) | |
5541 | ||
5542 | // 4'-particle correlation: | |
5543 | Double_t four1n1n1n1nW0W1W1W1PtEta = 0.; | |
5544 | if(dM0111) | |
5545 | { | |
5546 | four1n1n1n1nW0W1W1W1PtEta = ((pow(dReQ1n1k,2.)+pow(dImQ1n1k,2.))*(p1n0kRe*dReQ1n1k+p1n0kIm*dImQ1n1k) | |
5547 | - q2n1kRe*(pow(dReQ1n1k,2.)-pow(dImQ1n1k,2.)) | |
5548 | - 2.*q2n1kIm*dReQ1n1k*dImQ1n1k | |
5549 | - p1n0kRe*(dReQ1n1k*dReQ2n2k+dImQ1n1k*dImQ2n2k) | |
5550 | + p1n0kIm*(dImQ1n1k*dReQ2n2k-dReQ1n1k*dImQ2n2k) | |
5551 | - 2.*dSM1p2k*(p1n0kRe*dReQ1n1k+p1n0kIm*dImQ1n1k) | |
5552 | - 2.*(pow(dReQ1n1k,2.)+pow(dImQ1n1k,2.))*s1p1k | |
5553 | + 6.*(q1n2kRe*dReQ1n1k+q1n2kIm*dImQ1n1k) | |
5554 | + 1.*(q2n1kRe*dReQ2n2k+q2n1kIm*dImQ2n2k) | |
5555 | + 2.*(p1n0kRe*dReQ1n3k+p1n0kIm*dImQ1n3k) | |
5556 | + 2.*s1p1k*dSM1p2k | |
5557 | - 6.*s1p3k) | |
5558 | / dM0111; // to be imropoved (notation of dM0111) | |
5559 | ||
5560 | // fill the 2D profile to get the average correlation for each (pt, eta) bin: | |
5561 | if(type == "POI") | |
5562 | { | |
5563 | //f4pPtEtaPOIW->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,four1n1n1n1nW0W1W1W1PtEta,dM0111); | |
5564 | fCorrelationsPro[1][1][0][1]->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,four1n1n1n1nW0W1W1W1PtEta,dM0111); | |
5565 | } | |
5566 | else if(type == "RP") | |
5567 | { | |
5568 | //f4pPtEtaRPW->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,four1n1n1n1nW0W1W1W1PtEta,dM0111); | |
5569 | fCorrelationsPro[0][1][0][1]->Fill(fPtMin+(p-1)*fPtBinWidth,fEtaMin+(e-1)*fEtaBinWidth,four1n1n1n1nW0W1W1W1PtEta,dM0111); | |
5570 | } | |
5571 | } // end of if(dM0111) | |
5572 | ||
5573 | } // end of for(Int_t e=1;e<=fnBinsEta;e++) | |
5574 | } // end of for(Int_t p=1;p<=fnBinsPt;p++) | |
5575 | ||
5576 | ||
5577 | ||
5578 | ||
5579 | } // end of AliFlowAnalysisWithQCumulants::CalculateWeightedCorrelationsForDifferentialFlow2D(TString type) | |
5580 | ||
5581 | ||
5582 | //================================================================================================================================ | |
5583 | ||
5584 | */ | |
5585 | ||
5586 | /* | |
5587 | void AliFlowAnalysisWithQCumulants::FinalizeCorrelationsForDiffFlow(TString type, Bool_t useParticleWeights, TString eventWeights) | |
5588 | { | |
5589 | // 1.) Access average for 2D correlations from profiles and store them in 2D final results histograms; | |
5590 | // 2.) Access spread for 2D correlations from profiles, calculate error and store it in 2D final results histograms; | |
5591 | // 3.) Make projections along pt and eta axis and store results and errors in 1D final results histograms. | |
5592 | ||
5593 | Int_t typeFlag = -1; | |
5594 | Int_t pWeightsFlag = -1; | |
5595 | Int_t eWeightsFlag = -1; | |
5596 | ||
5597 | if(type == "RP") | |
5598 | { | |
5599 | typeFlag = 0; | |
5600 | } else if(type == "POI") | |
5601 | { | |
5602 | typeFlag = 1; | |
5603 | } else | |
5604 | { | |
5605 | cout<<"WARNING: type must be either RP or POI in AFAWQC::FCFDF() !!!!"<<endl; | |
5606 | exit(0); | |
5607 | } | |
5608 | ||
5609 | if(!useParticleWeights) | |
5610 | { | |
5611 | pWeightsFlag = 0; | |
5612 | } else | |
5613 | { | |
5614 | pWeightsFlag = 1; | |
5615 | } | |
5616 | ||
5617 | if(eventWeights == "exact") | |
5618 | { | |
5619 | eWeightsFlag = 0; | |
5620 | } | |
5621 | ||
5622 | // shortcuts: | |
5623 | Int_t t = typeFlag; | |
5624 | Int_t pW = pWeightsFlag; | |
5625 | Int_t eW = eWeightsFlag; | |
5626 | ||
5627 | // from 2D histogram fNonEmptyBins2D make two 1D histograms fNonEmptyBins1D in pt and eta (to be improved (i.e. moved somewhere else)) | |
5628 | // pt: | |
5629 | for(Int_t p=1;p<fnBinsPt;p++) | |
5630 | { | |
5631 | Double_t contentPt = 0.; | |
5632 | for(Int_t e=1;e<=fnBinsEta;e++) | |
5633 | { | |
5634 | contentPt += (fNonEmptyBins2D[t]->GetBinContent(fNonEmptyBins2D[t]->GetBin(p,e))); | |
5635 | } | |
5636 | fNonEmptyBins1D[t][0]->SetBinContent(p,contentPt); | |
5637 | } | |
5638 | // eta: | |
5639 | for(Int_t e=1;e<fnBinsEta;e++) | |
5640 | { | |
5641 | Double_t contentEta = 0.; | |
5642 | for(Int_t p=1;p<=fnBinsPt;p++) | |
5643 | { | |
5644 | contentEta += (fNonEmptyBins2D[t]->GetBinContent(fNonEmptyBins2D[t]->GetBin(p,e))); | |
5645 | } | |
5646 | fNonEmptyBins1D[t][1]->SetBinContent(e,contentEta); | |
5647 | } | |
5648 | ||
5649 | // from 2D profile in (pt,eta) make two 1D profiles in (pt) and (eta): | |
5650 | TProfile *profile[2][4]; // [0=pt,1=eta][correlation index] // to be improved (do not hardwire the correlation index) | |
5651 | ||
5652 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
5653 | { | |
5654 | for(Int_t ci=0;ci<4;ci++) // correlation index | |
5655 | { | |
5656 | if(pe==0) profile[pe][ci] = this->MakePtProjection(fCorrelationsPro[t][pW][eW][ci]); | |
5657 | if(pe==1) profile[pe][ci] = this->MakeEtaProjection(fCorrelationsPro[t][pW][eW][ci]); | |
5658 | } | |
5659 | } | |
5660 | ||
5661 | // transfer 2D profile into 2D histogram: | |
5662 | // to be improved (see in documentation if there is a method to transfer values from 2D profile into 2D histogram) | |
5663 | for(Int_t ci=0;ci<4;ci++) | |
5664 | { | |
5665 | for(Int_t p=1;p<=fnBinsPt;p++) | |
5666 | { | |
5667 | for(Int_t e=1;e<=fnBinsEta;e++) | |
5668 | { | |
5669 | Double_t correlation = fCorrelationsPro[t][pW][eW][ci]->GetBinContent(fCorrelationsPro[t][pW][eW][ci]->GetBin(p,e)); | |
5670 | Double_t spread = fCorrelationsPro[t][pW][eW][ci]->GetBinError(fCorrelationsPro[t][pW][eW][ci]->GetBin(p,e)); | |
5671 | Double_t nEvts = fNonEmptyBins2D[t]->GetBinContent(fNonEmptyBins2D[t]->GetBin(p,e)); | |
5672 | Double_t error = 0.; | |
5673 | fFinalCorrelations2D[t][pW][eW][ci]->SetBinContent(fFinalCorrelations2D[t][pW][eW][ci]->GetBin(p,e),correlation); | |
5674 | if(nEvts>0) | |
5675 | { | |
5676 | error = spread/pow(nEvts,0.5); | |
5677 | fFinalCorrelations2D[t][pW][eW][ci]->SetBinError(fFinalCorrelations2D[t][pW][eW][ci]->GetBin(p,e),error); | |
5678 | } | |
5679 | } // end of for(Int_t e=1;e<=fnBinsEta;e++) | |
5680 | } // end of for(Int_t p=1;p<=fnBinsPt;p++) | |
5681 | } // end of for(Int_t ci=0;ci<4;ci++) | |
5682 | ||
5683 | // transfer 1D profile into 1D histogram (pt): | |
5684 | // to be improved (see in documentation if there is a method to transfer values from 1D profile into 1D histogram) | |
5685 | for(Int_t ci=0;ci<4;ci++) | |
5686 | { | |
5687 | for(Int_t p=1;p<=fnBinsPt;p++) | |
5688 | { | |
5689 | if(profile[0][ci]) | |
5690 | { | |
5691 | Double_t correlation = profile[0][ci]->GetBinContent(p); | |
5692 | Double_t spread = profile[0][ci]->GetBinError(p); | |
5693 | Double_t nEvts = fNonEmptyBins1D[t][0]->GetBinContent(p); | |
5694 | Double_t error = 0.; | |
5695 | fFinalCorrelations1D[t][pW][eW][0][ci]->SetBinContent(p,correlation); | |
5696 | if(nEvts>0) | |
5697 | { | |
5698 | error = spread/pow(nEvts,0.5); | |
5699 | fFinalCorrelations1D[t][pW][eW][0][ci]->SetBinError(p,error); | |
5700 | } | |
5701 | } | |
5702 | } // end of for(Int_t p=1;p<=fnBinsPt;p++) | |
5703 | } // end of for(Int_t ci=0;ci<4;ci++) | |
5704 | ||
5705 | // transfer 1D profile into 1D histogram (eta): | |
5706 | // to be improved (see in documentation if there is a method to transfer values from 1D profile into 1D histogram) | |
5707 | for(Int_t ci=0;ci<4;ci++) | |
5708 | { | |
5709 | for(Int_t e=1;e<=fnBinsEta;e++) | |
5710 | { | |
5711 | if(profile[1][ci]) | |
5712 | { | |
5713 | Double_t correlation = profile[1][ci]->GetBinContent(e); | |
5714 | fFinalCorrelations1D[t][pW][eW][1][ci]->SetBinContent(e,correlation); | |
5715 | } | |
5716 | } // end of for(Int_t e=1;e<=fnBinsEta;e++) | |
5717 | } // end of for(Int_t ci=0;ci<4;ci++) | |
5718 | ||
5719 | } // end of void AliFlowAnalysisWithQCumulants::FinalizeCorrelationsForDiffFlow(TString type, Bool_t useParticleWeights, TString eventWeights) | |
5720 | */ | |
5721 | ||
5722 | ||
5723 | //================================================================================================================================ | |
5724 | ||
5725 | ||
5726 | void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCumulants(TString type, TString ptOrEta) | |
5727 | { | |
5728 | // calcualate cumulants for differential flow from measured correlations | |
5729 | // Remark: cumulants calculated here are NOT corrected for non-uniform acceptance. This correction is applied in the method ... | |
5730 | // to be improved (description) | |
5731 | ||
2a98ceb8 | 5732 | Int_t typeFlag = 0; |
5733 | Int_t ptEtaFlag = 0; | |
489d5531 | 5734 | |
5735 | if(type == "RP") | |
5736 | { | |
5737 | typeFlag = 0; | |
5738 | } else if(type == "POI") | |
5739 | { | |
5740 | typeFlag = 1; | |
5741 | } | |
5742 | ||
5743 | if(ptOrEta == "Pt") | |
5744 | { | |
5745 | ptEtaFlag = 0; | |
5746 | } else if(ptOrEta == "Eta") | |
5747 | { | |
5748 | ptEtaFlag = 1; | |
5749 | } | |
5750 | ||
5751 | // shortcuts: | |
5752 | Int_t t = typeFlag; | |
5753 | Int_t pe = ptEtaFlag; | |
5754 | ||
5755 | // common: | |
5756 | Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; | |
5757 | ||
5758 | // correlation <<2>>: | |
5759 | Double_t two = fIntFlowCorrelationsHist->GetBinContent(1); | |
5760 | ||
5761 | // 1D: | |
5762 | for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
5763 | { | |
5764 | // reduced correlations: | |
5765 | Double_t twoPrime = fDiffFlowCorrelationsHist[t][pe][0]->GetBinContent(b); // <<2'>>(pt) | |
5766 | Double_t fourPrime = fDiffFlowCorrelationsHist[t][pe][1]->GetBinContent(b); // <<4'>>(pt) | |
5767 | // final statistical error of reduced correlations: | |
5768 | //Double_t twoPrimeError = fFinalCorrelations1D[t][pW][eW][0][0]->GetBinError(p); | |
5769 | // QC{2'}: | |
5770 | Double_t qc2Prime = twoPrime; // QC{2'} | |
5771 | //Double_t qc2PrimeError = twoPrimeError; // final stat. error of QC{2'} | |
5772 | fDiffFlowCumulants[t][pe][0]->SetBinContent(b,qc2Prime); | |
5773 | //fFinalCumulantsPt[t][pW][eW][nua][0]->SetBinError(p,qc2PrimeError); | |
5774 | // QC{4'}: | |
5775 | Double_t qc4Prime = fourPrime - 2.*twoPrime*two; // QC{4'} = <<4'>> - 2*<<2'>><<2>> | |
5776 | fDiffFlowCumulants[t][pe][1]->SetBinContent(b,qc4Prime); | |
5777 | } // end of for(Int_t p=1;p<=fnBinsPt;p++) | |
5778 | ||
5779 | ||
5780 | /* | |
5781 | // 2D (pt,eta): | |
5782 | // to be improved (see documentation if I can do all this without looping) | |
5783 | for(Int_t p=1;p<=fnBinsPt;p++) | |
5784 | { | |
5785 | for(Int_t e=1;e<=fnBinsEta;e++) | |
5786 | { | |
5787 | // reduced correlations: | |
5788 | Double_t twoPrime = fFinalCorrelations2D[t][pW][eW][0]->GetBinContent(fFinalCorrelations2D[t][pW][eW][0]->GetBin(p,e)); // <<2'>>(pt,eta) | |
5789 | Double_t fourPrime = fFinalCorrelations2D[t][pW][eW][1]->GetBinContent(fFinalCorrelations2D[t][pW][eW][1]->GetBin(p,e)); // <<4'>>(pt,eta) | |
5790 | for(Int_t nua=0;nua<2;nua++) | |
5791 | { | |
5792 | // QC{2'}: | |
5793 | Double_t qc2Prime = twoPrime; // QC{2'} = <<2'>> | |
5794 | fFinalCumulants2D[t][pW][eW][nua][0]->SetBinContent(fFinalCumulants2D[t][pW][eW][nua][0]->GetBin(p,e),qc2Prime); | |
5795 | // QC{4'}: | |
5796 | Double_t qc4Prime = fourPrime - 2.*twoPrime*two; // QC{4'} = <<4'>> - 2*<<2'>><<2>> | |
5797 | fFinalCumulants2D[t][pW][eW][nua][1]->SetBinContent(fFinalCumulants2D[t][pW][eW][nua][1]->GetBin(p,e),qc4Prime); | |
5798 | } // end of for(Int_t nua=0;nua<2;nua++) | |
5799 | } // end of for(Int_t e=1;e<=fnBinsEta;e++) | |
5800 | } // end of for(Int_t p=1;p<=fnBinsPt;p++) | |
5801 | */ | |
5802 | ||
5803 | } // end of void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCumulants(TString type, Bool_t useParticleWeights, TString eventWeights); | |
5804 | ||
489d5531 | 5805 | //================================================================================================================================ |
5806 | ||
489d5531 | 5807 | void AliFlowAnalysisWithQCumulants::CalculateFinalResultsForRPandPOIIntegratedFlow(TString type) |
5808 | { | |
5809 | // calculate final results for integrated flow of RPs and POIs | |
5810 | ||
2a98ceb8 | 5811 | Int_t typeFlag = 0; |
489d5531 | 5812 | |
5813 | if(type == "RP") | |
5814 | { | |
5815 | typeFlag = 0; | |
5816 | } else if(type == "POI") | |
5817 | { | |
5818 | typeFlag = 1; | |
5819 | } else | |
5820 | { | |
5821 | cout<<"WARNING: type must be either RP or POI in AFAWQC::CDF() !!!!"<<endl; | |
5822 | exit(0); | |
5823 | } | |
5824 | ||
5825 | // shortcuts: | |
5826 | Int_t t = typeFlag; | |
5827 | ||
5828 | // pt yield: | |
5829 | TH1F *yield2ndPt = NULL; | |
5830 | TH1F *yield4thPt = NULL; | |
5831 | TH1F *yield6thPt = NULL; | |
5832 | TH1F *yield8thPt = NULL; | |
5833 | ||
5834 | if(type == "POI") | |
5835 | { | |
dd442cd2 | 5836 | if(fFillMultipleControlHistograms) |
5837 | { | |
5838 | yield2ndPt = (TH1F*)(fCommonHists2nd->GetHistPtPOI())->Clone(); | |
5839 | yield4thPt = (TH1F*)(fCommonHists4th->GetHistPtPOI())->Clone(); | |
5840 | yield6thPt = (TH1F*)(fCommonHists6th->GetHistPtPOI())->Clone(); | |
5841 | yield8thPt = (TH1F*)(fCommonHists8th->GetHistPtPOI())->Clone(); | |
5842 | } else | |
5843 | { | |
5844 | yield2ndPt = (TH1F*)(fCommonHists->GetHistPtPOI())->Clone(); | |
5845 | yield4thPt = (TH1F*)(fCommonHists->GetHistPtPOI())->Clone(); | |
5846 | yield6thPt = (TH1F*)(fCommonHists->GetHistPtPOI())->Clone(); | |
5847 | yield8thPt = (TH1F*)(fCommonHists->GetHistPtPOI())->Clone(); | |
5848 | } | |
489d5531 | 5849 | } |
5850 | else if(type == "RP") | |
5851 | { | |
dd442cd2 | 5852 | if(fFillMultipleControlHistograms) |
5853 | { | |
5854 | yield2ndPt = (TH1F*)(fCommonHists2nd->GetHistPtRP())->Clone(); | |
5855 | yield4thPt = (TH1F*)(fCommonHists4th->GetHistPtRP())->Clone(); | |
5856 | yield6thPt = (TH1F*)(fCommonHists6th->GetHistPtRP())->Clone(); | |
5857 | yield8thPt = (TH1F*)(fCommonHists8th->GetHistPtRP())->Clone(); | |
5858 | } else | |
5859 | { | |
5860 | yield2ndPt = (TH1F*)(fCommonHists->GetHistPtRP())->Clone(); | |
5861 | yield4thPt = (TH1F*)(fCommonHists->GetHistPtRP())->Clone(); | |
5862 | yield6thPt = (TH1F*)(fCommonHists->GetHistPtRP())->Clone(); | |
5863 | yield8thPt = (TH1F*)(fCommonHists->GetHistPtRP())->Clone(); | |
5864 | } | |
489d5531 | 5865 | } |
5866 | ||
5867 | Int_t nBinsPt = yield2ndPt->GetNbinsX(); | |
5868 | ||
5869 | TH1D *flow2ndPt = NULL; | |
5870 | TH1D *flow4thPt = NULL; | |
5871 | TH1D *flow6thPt = NULL; | |
5872 | TH1D *flow8thPt = NULL; | |
5873 | ||
5874 | // to be improved (hardwired pt index) | |
5875 | flow2ndPt = (TH1D*)fDiffFlow[t][0][0]->Clone(); | |
5876 | flow4thPt = (TH1D*)fDiffFlow[t][0][1]->Clone(); | |
5877 | flow6thPt = (TH1D*)fDiffFlow[t][0][2]->Clone(); | |
5878 | flow8thPt = (TH1D*)fDiffFlow[t][0][3]->Clone(); | |
5879 | ||
5880 | Double_t dvn2nd = 0., dvn4th = 0., dvn6th = 0., dvn8th = 0.; // differential flow | |
5881 | Double_t dErrvn2nd = 0., dErrvn4th = 0., dErrvn6th = 0., dErrvn8th = 0.; // error on differential flow | |
5882 | ||
5883 | Double_t dVn2nd = 0., dVn4th = 0., dVn6th = 0., dVn8th = 0.; // integrated flow | |
5884 | Double_t dErrVn2nd = 0., dErrVn4th = 0., dErrVn6th = 0., dErrVn8th = 0.; // error on integrated flow | |
5885 | ||
5886 | Double_t dYield2nd = 0., dYield4th = 0., dYield6th = 0., dYield8th = 0.; // pt yield | |
5887 | Double_t dSum2nd = 0., dSum4th = 0., dSum6th = 0., dSum8th = 0.; // needed for normalizing integrated flow | |
5888 | ||
5889 | // looping over pt bins: | |
5890 | for(Int_t p=1;p<nBinsPt+1;p++) | |
5891 | { | |
5892 | dvn2nd = flow2ndPt->GetBinContent(p); | |
5893 | dvn4th = flow4thPt->GetBinContent(p); | |
5894 | dvn6th = flow6thPt->GetBinContent(p); | |
5895 | dvn8th = flow8thPt->GetBinContent(p); | |
5896 | ||
5897 | dErrvn2nd = flow2ndPt->GetBinError(p); | |
5898 | dErrvn4th = flow4thPt->GetBinError(p); | |
5899 | dErrvn6th = flow6thPt->GetBinError(p); | |
5900 | dErrvn8th = flow8thPt->GetBinError(p); | |
5901 | ||
5902 | dYield2nd = yield2ndPt->GetBinContent(p); | |
5903 | dYield4th = yield4thPt->GetBinContent(p); | |
5904 | dYield6th = yield6thPt->GetBinContent(p); | |
5905 | dYield8th = yield8thPt->GetBinContent(p); | |
5906 | ||
5907 | dVn2nd += dvn2nd*dYield2nd; | |
5908 | dVn4th += dvn4th*dYield4th; | |
5909 | dVn6th += dvn6th*dYield6th; | |
5910 | dVn8th += dvn8th*dYield8th; | |
5911 | ||
5912 | dSum2nd += dYield2nd; | |
5913 | dSum4th += dYield4th; | |
5914 | dSum6th += dYield6th; | |
5915 | dSum8th += dYield8th; | |
5916 | ||
5917 | dErrVn2nd += dYield2nd*dYield2nd*dErrvn2nd*dErrvn2nd; // ro be improved (check this relation) | |
5918 | dErrVn4th += dYield4th*dYield4th*dErrvn4th*dErrvn4th; | |
5919 | dErrVn6th += dYield6th*dYield6th*dErrvn6th*dErrvn6th; | |
5920 | dErrVn8th += dYield8th*dYield8th*dErrvn8th*dErrvn8th; | |
5921 | ||
5922 | } // end of for(Int_t p=1;p<nBinsPt+1;p++) | |
5923 | ||
5924 | // normalizing the results for integrated flow: | |
5925 | if(dSum2nd) | |
5926 | { | |
5927 | dVn2nd /= dSum2nd; | |
5928 | dErrVn2nd /= (dSum2nd*dSum2nd); | |
5929 | dErrVn2nd = TMath::Sqrt(dErrVn2nd); | |
5930 | } | |
5931 | if(dSum4th) | |
5932 | { | |
5933 | dVn4th /= dSum4th; | |
5934 | dErrVn4th /= (dSum4th*dSum4th); | |
5935 | dErrVn4th = TMath::Sqrt(dErrVn4th); | |
5936 | } | |
5937 | //if(dSum6th) dVn6th/=dSum6th; | |
5938 | //if(dSum8th) dVn8th/=dSum8th; | |
5939 | ||
5940 | // storing the results for integrated flow in common histos: (to be improved: new method for this?) | |
5941 | if(type == "POI") | |
5942 | { | |
5943 | fCommonHistsResults2nd->FillIntegratedFlowPOI(dVn2nd,dErrVn2nd); | |
5944 | fCommonHistsResults4th->FillIntegratedFlowPOI(dVn4th,dErrVn4th); | |
5945 | fCommonHistsResults6th->FillIntegratedFlowPOI(dVn6th,0.); // to be improved (errors) | |
5946 | fCommonHistsResults8th->FillIntegratedFlowPOI(dVn8th,0.); // to be improved (errors) | |
5947 | } | |
5948 | else if (type == "RP") | |
5949 | { | |
5950 | fCommonHistsResults2nd->FillIntegratedFlowRP(dVn2nd,dErrVn2nd); | |
5951 | fCommonHistsResults4th->FillIntegratedFlowRP(dVn4th,dErrVn4th); | |
5952 | fCommonHistsResults6th->FillIntegratedFlowRP(dVn6th,0.); // to be improved (errors) | |
5953 | fCommonHistsResults8th->FillIntegratedFlowRP(dVn8th,0.); // to be improved (errors) | |
5954 | } | |
5955 | ||
5956 | delete flow2ndPt; | |
5957 | delete flow4thPt; | |
5958 | //delete flow6thPt; | |
5959 | //delete flow8thPt; | |
5960 | ||
5961 | delete yield2ndPt; | |
5962 | delete yield4thPt; | |
5963 | delete yield6thPt; | |
5964 | delete yield8thPt; | |
5965 | ||
5966 | } // end of AliFlowAnalysisWithQCumulants::CalculateFinalResultsForRPandPOIIntegratedFlow(TString type) | |
5967 | ||
489d5531 | 5968 | //================================================================================================================================ |
5969 | ||
489d5531 | 5970 | void AliFlowAnalysisWithQCumulants::InitializeArraysForDistributions() |
5971 | { | |
5972 | // Initialize all arrays used for distributions. | |
5973 | ||
5974 | // a) Initialize arrays of histograms used to hold distributions of correlations; | |
5975 | // b) Initialize array to hold min and max values of correlations. | |
5976 | ||
5977 | // a) Initialize arrays of histograms used to hold distributions of correlations: | |
5978 | for(Int_t di=0;di<4;di++) // distribution index | |
5979 | { | |
5980 | fDistributions[di] = NULL; | |
5981 | } | |
5982 | ||
5983 | // b) Initialize default min and max values of correlations: | |
5984 | // (Remark: The default values bellow were chosen for v2=5% and M=500) | |
5985 | fMinValueOfCorrelation[0] = -0.01; // <2>_min | |
5986 | fMaxValueOfCorrelation[0] = 0.04; // <2>_max | |
5987 | fMinValueOfCorrelation[1] = -0.00002; // <4>_min | |
5988 | fMaxValueOfCorrelation[1] = 0.00015; // <4>_max | |
5989 | fMinValueOfCorrelation[2] = -0.0000003; // <6>_min | |
5990 | fMaxValueOfCorrelation[2] = 0.0000006; // <6>_max | |
5991 | fMinValueOfCorrelation[3] = -0.000000006; // <8>_min | |
5992 | fMaxValueOfCorrelation[3] = 0.000000003; // <8>_max | |
5993 | ||
5994 | } // end of void AliFlowAnalysisWithQCumulants::InitializeArraysForDistributions() | |
5995 | ||
489d5531 | 5996 | //================================================================================================================================ |
5997 | ||
e5834fcb | 5998 | void AliFlowAnalysisWithQCumulants::InitializeArraysForVarious() |
5999 | { | |
6000 | // Initialize all arrays used for various unclassified objects. | |
6001 | ||
6002 | for(Int_t p=0;p<4;p++) // [v_min,v_max,refMult_min,refMult_max] | |
6003 | { | |
6004 | fPhiDistributionForOneEventSettings[p] = 0.; | |
6005 | } | |
6006 | ||
6007 | } // end of void AliFlowAnalysisWithQCumulants::InitializeArraysForVarious() | |
6008 | ||
6009 | //================================================================================================================================ | |
489d5531 | 6010 | |
6011 | void AliFlowAnalysisWithQCumulants::BookEverythingForDistributions() | |
6012 | { | |
6013 | // a) Book profile to hold all flags for distributions of correlations; | |
6014 | // b) Book all histograms to hold distributions of correlations. | |
6015 | ||
6016 | TString correlationIndex[4] = {"<2>","<4>","<6>","<8>"}; // to be improved (should I promote this to data members?) | |
6017 | ||
6018 | // a) Book profile to hold all flags for distributions of correlations: | |
6019 | TString distributionsFlagsName = "fDistributionsFlags"; | |
6020 | distributionsFlagsName += fAnalysisLabel->Data(); | |
6021 | fDistributionsFlags = new TProfile(distributionsFlagsName.Data(),"Flags for Distributions of Correlations",9,0,9); | |
6022 | fDistributionsFlags->SetTickLength(-0.01,"Y"); | |
6023 | fDistributionsFlags->SetMarkerStyle(25); | |
6024 | fDistributionsFlags->SetLabelSize(0.05); | |
6025 | fDistributionsFlags->SetLabelOffset(0.02,"Y"); | |
6026 | fDistributionsFlags->GetXaxis()->SetBinLabel(1,"Store or not?"); | |
6027 | fDistributionsFlags->GetXaxis()->SetBinLabel(2,"<2>_{min}"); | |
6028 | fDistributionsFlags->GetXaxis()->SetBinLabel(3,"<2>_{max}"); | |
6029 | fDistributionsFlags->GetXaxis()->SetBinLabel(4,"<4>_{min}"); | |
6030 | fDistributionsFlags->GetXaxis()->SetBinLabel(5,"<4>_{max}"); | |
6031 | fDistributionsFlags->GetXaxis()->SetBinLabel(6,"<6>_{min}"); | |
6032 | fDistributionsFlags->GetXaxis()->SetBinLabel(7,"<6>_{max}"); | |
6033 | fDistributionsFlags->GetXaxis()->SetBinLabel(8,"<8>_{min}"); | |
6034 | fDistributionsFlags->GetXaxis()->SetBinLabel(9,"<8>_{max}"); | |
6035 | fDistributionsList->Add(fDistributionsFlags); | |
6036 | ||
6037 | // b) Book all histograms to hold distributions of correlations. | |
6038 | if(fStoreDistributions) | |
6039 | { | |
6040 | TString distributionsName = "fDistributions"; | |
6041 | distributionsName += fAnalysisLabel->Data(); | |
6042 | for(Int_t di=0;di<4;di++) // distribution index | |
6043 | { | |
6044 | fDistributions[di] = new TH1D(Form("Distribution of %s",correlationIndex[di].Data()),Form("Distribution of %s",correlationIndex[di].Data()),10000,fMinValueOfCorrelation[di],fMaxValueOfCorrelation[di]); | |
6045 | fDistributions[di]->SetXTitle(correlationIndex[di].Data()); | |
6046 | fDistributionsList->Add(fDistributions[di]); | |
6047 | } // end of for(Int_t di=0;di<4;di++) // distribution index | |
6048 | } // end of if(fStoreDistributions) | |
6049 | ||
6050 | } // end of void AliFlowAnalysisWithQCumulants::BookEverythingForDistributions() | |
6051 | ||
489d5531 | 6052 | //================================================================================================================================ |
6053 | ||
e5834fcb | 6054 | void AliFlowAnalysisWithQCumulants::BookEverythingForVarious() |
6055 | { | |
6056 | // Book all objects for various unclassified quantities. | |
6057 | ||
6058 | if(!fStorePhiDistributionForOneEvent){return;} | |
6059 | ||
6060 | // a) Book histogram holding phi distribution for single event to illustrate flow. | |
6061 | ||
6062 | // a) Book histogram holding phi distribution for single event to illustrate flow: | |
6063 | fPhiDistributionForOneEvent = new TH1D("fPhiDistributionForOneEvent","",360,0.,TMath::TwoPi()); | |
6064 | fPhiDistributionForOneEvent->GetXaxis()->SetTitle("#phi"); | |
6065 | fVariousList->Add(fPhiDistributionForOneEvent); | |
6066 | ||
6067 | } // end of void AliFlowAnalysisWithQCumulants::BookEverythingForVarious() | |
6068 | ||
6069 | //================================================================================================================================ | |
489d5531 | 6070 | |
6071 | void AliFlowAnalysisWithQCumulants::StoreFlagsForDistributions() | |
6072 | { | |
6073 | // Store all flags for distributiuons of correlations in profile fDistributionsFlags. | |
6074 | ||
6075 | if(!fDistributionsFlags) | |
6076 | { | |
6077 | cout<<"WARNING: fDistributionsFlags is NULL in AFAWQC::SDF() !!!!"<<endl; | |
6078 | exit(0); | |
6079 | } | |
6080 | ||
6081 | fDistributionsFlags->Fill(0.5,(Int_t)fStoreDistributions); // histos with distributions of correlations stored or not in the output file | |
6082 | // store min and max values of correlations: | |
6083 | for(Int_t di=0;di<4;di++) // distribution index | |
6084 | { | |
6085 | fDistributionsFlags->Fill(1.5+2.*(Double_t)di,fMinValueOfCorrelation[di]); | |
6086 | fDistributionsFlags->Fill(2.5+2.*(Double_t)di,fMaxValueOfCorrelation[di]); | |
6087 | } | |
6088 | ||
6089 | } // end of void AliFlowAnalysisWithQCumulants::StoreFlagsForDistributions() | |
6090 | ||
6091 | ||
6092 | //================================================================================================================================ | |
6093 | ||
6094 | ||
6095 | void AliFlowAnalysisWithQCumulants::StoreDistributionsOfCorrelations() | |
6096 | { | |
6097 | // Store distributions of correlations. | |
6098 | ||
6099 | if(!(fIntFlowCorrelationsEBE && fIntFlowEventWeightsForCorrelationsEBE)) | |
6100 | { | |
6101 | cout<<"WARNING: fIntFlowCorrelationsEBE && fIntFlowEventWeightsForCorrelationsEBE"<<endl; | |
6102 | cout<<" is NULL in AFAWQC::SDOC() !!!!"<<endl; | |
6103 | exit(0); | |
6104 | } | |
6105 | ||
6106 | for(Int_t di=0;di<4;di++) // distribution index | |
6107 | { | |
6108 | if(!fDistributions[di]) | |
6109 | { | |
6110 | cout<<"WARNING: fDistributions[di] is NULL in AFAWQC::SDOC() !!!!"<<endl; | |
6111 | cout<<"di = "<<di<<endl; | |
6112 | exit(0); | |
6113 | } else | |
6114 | { | |
6115 | fDistributions[di]->Fill(fIntFlowCorrelationsEBE->GetBinContent(di+1),fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(di+1)); | |
6116 | } | |
6117 | } // end of for(Int_t di=0;di<4;di++) // distribution index | |
6118 | ||
6119 | } // end of void AliFlowAnalysisWithQCumulants::StoreDistributionsOfCorrelations() | |
6120 | ||
489d5531 | 6121 | //================================================================================================================================ |
6122 | ||
489d5531 | 6123 | void AliFlowAnalysisWithQCumulants::BookAndNestAllLists() |
6124 | { | |
6125 | // Book and nest all lists nested in the base list fHistList. | |
6126 | // a) Book and nest lists for integrated flow; | |
6127 | // b) Book and nest lists for differential flow; | |
6128 | // c) Book and nest list for particle weights; | |
6129 | // d) Book and nest list for distributions; | |
e5834fcb | 6130 | // e) Book and nest list for various unclassified objects; |
6131 | // f) Book and nest list for nested loops. | |
489d5531 | 6132 | |
6133 | // a) Book and nest all lists for integrated flow: | |
6134 | // base list for integrated flow: | |
6135 | fIntFlowList = new TList(); | |
6136 | fIntFlowList->SetName("Integrated Flow"); | |
6137 | fIntFlowList->SetOwner(kTRUE); | |
6138 | fHistList->Add(fIntFlowList); | |
6139 | // list holding profiles: | |
6140 | fIntFlowProfiles = new TList(); | |
6141 | fIntFlowProfiles->SetName("Profiles"); | |
6142 | fIntFlowProfiles->SetOwner(kTRUE); | |
6143 | fIntFlowList->Add(fIntFlowProfiles); | |
6144 | // list holding histograms with results: | |
6145 | fIntFlowResults = new TList(); | |
6146 | fIntFlowResults->SetName("Results"); | |
6147 | fIntFlowResults->SetOwner(kTRUE); | |
6148 | fIntFlowList->Add(fIntFlowResults); | |
6149 | ||
6150 | // b) Book and nest lists for differential flow; | |
6151 | fDiffFlowList = new TList(); | |
6152 | fDiffFlowList->SetName("Differential Flow"); | |
6153 | fDiffFlowList->SetOwner(kTRUE); | |
6154 | fHistList->Add(fDiffFlowList); | |
6155 | // list holding profiles: | |
6156 | fDiffFlowProfiles = new TList(); | |
6157 | fDiffFlowProfiles->SetName("Profiles"); | |
6158 | fDiffFlowProfiles->SetOwner(kTRUE); | |
6159 | fDiffFlowList->Add(fDiffFlowProfiles); | |
6160 | // list holding histograms with results: | |
6161 | fDiffFlowResults = new TList(); | |
6162 | fDiffFlowResults->SetName("Results"); | |
6163 | fDiffFlowResults->SetOwner(kTRUE); | |
6164 | fDiffFlowList->Add(fDiffFlowResults); | |
6165 | // flags used for naming nested lists in list fDiffFlowProfiles and fDiffFlowResults: | |
6166 | TList list; | |
6167 | list.SetOwner(kTRUE); | |
6168 | TString typeFlag[2] = {"RP","POI"}; | |
6169 | TString ptEtaFlag[2] = {"p_{T}","#eta"}; | |
6170 | TString powerFlag[2] = {"linear","quadratic"}; | |
6171 | // nested lists in fDiffFlowProfiles (~/Differential Flow/Profiles): | |
6172 | for(Int_t t=0;t<2;t++) // type: RP or POI | |
6173 | { | |
6174 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
6175 | { | |
6176 | // list holding profiles with correlations: | |
6177 | fDiffFlowCorrelationsProList[t][pe] = (TList*)list.Clone(); | |
6178 | fDiffFlowCorrelationsProList[t][pe]->SetName(Form("Profiles with correlations (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data())); | |
6179 | fDiffFlowProfiles->Add(fDiffFlowCorrelationsProList[t][pe]); | |
6180 | // list holding profiles with products of correlations: | |
6181 | fDiffFlowProductOfCorrelationsProList[t][pe] = (TList*)list.Clone(); | |
6182 | fDiffFlowProductOfCorrelationsProList[t][pe]->SetName(Form("Profiles with products of correlations (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data())); | |
6183 | fDiffFlowProfiles->Add(fDiffFlowProductOfCorrelationsProList[t][pe]); | |
6184 | // list holding profiles with corrections: | |
6185 | fDiffFlowCorrectionsProList[t][pe] = (TList*)list.Clone(); | |
6186 | fDiffFlowCorrectionsProList[t][pe]->SetName(Form("Profiles with correction terms for NUA (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data())); | |
6187 | fDiffFlowProfiles->Add(fDiffFlowCorrectionsProList[t][pe]); | |
6188 | } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta | |
6189 | } // end of for(Int_t t=0;t<2;t++) // type: RP or POI | |
6190 | // nested lists in fDiffFlowResults (~/Differential Flow/Results): | |
6191 | for(Int_t t=0;t<2;t++) // type: RP or POI | |
6192 | { | |
6193 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
6194 | { | |
6195 | // list holding histograms with correlations: | |
6196 | fDiffFlowCorrelationsHistList[t][pe] = (TList*)list.Clone(); | |
6197 | fDiffFlowCorrelationsHistList[t][pe]->SetName(Form("Correlations (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data())); | |
6198 | fDiffFlowResults->Add(fDiffFlowCorrelationsHistList[t][pe]); | |
6199 | // list holding histograms with corrections: | |
6200 | fDiffFlowCorrectionsHistList[t][pe] = (TList*)list.Clone(); | |
6201 | fDiffFlowCorrectionsHistList[t][pe]->SetName(Form("Histograms with correction terms for NUA (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data())); | |
6202 | fDiffFlowResults->Add(fDiffFlowCorrectionsHistList[t][pe]); | |
6203 | for(Int_t power=0;power<2;power++) | |
6204 | { | |
6205 | // list holding histograms with sums of event weights: | |
6206 | fDiffFlowSumOfEventWeightsHistList[t][pe][power] = (TList*)list.Clone(); | |
6207 | fDiffFlowSumOfEventWeightsHistList[t][pe][power]->SetName(Form("Sum of %s event weights (%s, %s)",powerFlag[power].Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data())); | |
6208 | fDiffFlowResults->Add(fDiffFlowSumOfEventWeightsHistList[t][pe][power]); | |
6209 | } // end of for(Int_t power=0;power<2;power++) | |
6210 | // list holding histograms with sums of products of event weights: | |
6211 | fDiffFlowSumOfProductOfEventWeightsHistList[t][pe] = (TList*)list.Clone(); | |
6212 | fDiffFlowSumOfProductOfEventWeightsHistList[t][pe]->SetName(Form("Sum of products of event weights (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data())); | |
6213 | fDiffFlowResults->Add(fDiffFlowSumOfProductOfEventWeightsHistList[t][pe]); | |
6214 | // list holding histograms with covariances of correlations: | |
6215 | fDiffFlowCovariancesHistList[t][pe] = (TList*)list.Clone(); | |
6216 | fDiffFlowCovariancesHistList[t][pe]->SetName(Form("Covariances of correlations (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data())); | |
6217 | fDiffFlowResults->Add(fDiffFlowCovariancesHistList[t][pe]); | |
6218 | // list holding histograms with differential Q-cumulants: | |
6219 | fDiffFlowCumulantsHistList[t][pe] = (TList*)list.Clone(); | |
6220 | fDiffFlowCumulantsHistList[t][pe]->SetName(Form("Differential Q-cumulants (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data())); | |
6221 | fDiffFlowResults->Add(fDiffFlowCumulantsHistList[t][pe]); | |
6222 | // list holding histograms with differential flow estimates from Q-cumulants: | |
6223 | fDiffFlowHistList[t][pe] = (TList*)list.Clone(); | |
6224 | fDiffFlowHistList[t][pe]->SetName(Form("Differential flow (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data())); | |
6225 | fDiffFlowResults->Add(fDiffFlowHistList[t][pe]); | |
6226 | } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta | |
6227 | } // end of for(Int_t t=0;t<2;t++) // type: RP or POI | |
6228 | ||
6229 | // c) Book and nest list for particle weights: | |
6230 | fWeightsList->SetName("Weights"); | |
6231 | fWeightsList->SetOwner(kTRUE); | |
6232 | fHistList->Add(fWeightsList); | |
6233 | ||
6234 | // d) Book and nest list for distributions: | |
6235 | fDistributionsList = new TList(); | |
6236 | fDistributionsList->SetName("Distributions"); | |
6237 | fDistributionsList->SetOwner(kTRUE); | |
6238 | fHistList->Add(fDistributionsList); | |
6239 | ||
e5834fcb | 6240 | // e) Book and nest list for various unclassified objects: |
6241 | if(fStorePhiDistributionForOneEvent) | |
6242 | { | |
6243 | fVariousList = new TList(); | |
6244 | fVariousList->SetName("Various"); | |
6245 | fVariousList->SetOwner(kTRUE); | |
6246 | fHistList->Add(fVariousList); | |
6247 | } | |
6248 | ||
6249 | // f) Book and nest list for nested loops: | |
489d5531 | 6250 | fNestedLoopsList = new TList(); |
6251 | fNestedLoopsList->SetName("Nested Loops"); | |
6252 | fNestedLoopsList->SetOwner(kTRUE); | |
6253 | fHistList->Add(fNestedLoopsList); | |
6254 | ||
6255 | } // end of void AliFlowAnalysisWithQCumulants::BookAndNestAllLists() | |
6256 | ||
6257 | ||
6258 | //================================================================================================================================ | |
6259 | ||
6260 | ||
6261 | void AliFlowAnalysisWithQCumulants::FillCommonHistResultsDiffFlow(TString type) | |
6262 | { | |
6263 | // fill common result histograms for differential flow | |
6264 | ||
2a98ceb8 | 6265 | Int_t typeFlag = 0; |
6266 | //Int_t ptEtaFlag = 0; | |
489d5531 | 6267 | |
6268 | if(type == "RP") | |
6269 | { | |
6270 | typeFlag = 0; | |
6271 | } else if(type == "POI") | |
6272 | { | |
6273 | typeFlag = 1; | |
6274 | } | |
6275 | ||
6276 | // shortcuts: | |
6277 | Int_t t = typeFlag; | |
6278 | //Int_t pe = ptEtaFlag; | |
6279 | ||
6280 | // to be improved (implement protection here) | |
6281 | ||
6282 | if(!(fCommonHistsResults2nd && fCommonHistsResults4th && fCommonHistsResults6th && fCommonHistsResults8th)) | |
6283 | { | |
6284 | cout<<"WARNING: fCommonHistsResults2nd && fCommonHistsResults4th && fCommonHistsResults6th && fCommonHistsResults8th"<<endl; | |
6285 | cout<<" is NULL in AFAWQC::FCHRIF() !!!!"<<endl; | |
6286 | exit(0); | |
6287 | } | |
6288 | ||
6289 | // pt: | |
6290 | for(Int_t p=1;p<=fnBinsPt;p++) | |
6291 | { | |
6292 | Double_t v2 = fDiffFlow[t][0][0]->GetBinContent(p); | |
6293 | Double_t v4 = fDiffFlow[t][0][1]->GetBinContent(p); | |
6294 | Double_t v6 = fDiffFlow[t][0][2]->GetBinContent(p); | |
6295 | Double_t v8 = fDiffFlow[t][0][3]->GetBinContent(p); | |
6296 | ||
6297 | Double_t v2Error = fDiffFlow[t][0][0]->GetBinError(p); | |
6298 | Double_t v4Error = fDiffFlow[t][0][1]->GetBinError(p); | |
6299 | //Double_t v6Error = fFinalFlow1D[t][pW][nua][0][2]->GetBinError(p); | |
6300 | //Double_t v8Error = fFinalFlow1D[t][pW][nua][0][3]->GetBinError(p); | |
6301 | ||
6302 | if(type == "RP") | |
6303 | { | |
6304 | fCommonHistsResults2nd->FillDifferentialFlowPtRP(p,v2,v2Error); | |
6305 | fCommonHistsResults4th->FillDifferentialFlowPtRP(p,v4,v4Error); | |
6306 | fCommonHistsResults6th->FillDifferentialFlowPtRP(p,v6,0.); | |
6307 | fCommonHistsResults8th->FillDifferentialFlowPtRP(p,v8,0.); | |
6308 | } else if(type == "POI") | |
6309 | { | |
6310 | fCommonHistsResults2nd->FillDifferentialFlowPtPOI(p,v2,v2Error); | |
6311 | fCommonHistsResults4th->FillDifferentialFlowPtPOI(p,v4,v4Error); | |
6312 | fCommonHistsResults6th->FillDifferentialFlowPtPOI(p,v6,0.); | |
6313 | fCommonHistsResults8th->FillDifferentialFlowPtPOI(p,v8,0.); | |
6314 | } | |
6315 | } // end of for(Int_t p=1;p<=fnBinsPt;p++) | |
6316 | ||
6317 | // eta: | |
6318 | for(Int_t e=1;e<=fnBinsEta;e++) | |
6319 | { | |
6320 | Double_t v2 = fDiffFlow[t][1][0]->GetBinContent(e); | |
6321 | Double_t v4 = fDiffFlow[t][1][1]->GetBinContent(e); | |
6322 | Double_t v6 = fDiffFlow[t][1][2]->GetBinContent(e); | |
6323 | Double_t v8 = fDiffFlow[t][1][3]->GetBinContent(e); | |
6324 | ||
6325 | Double_t v2Error = fDiffFlow[t][1][0]->GetBinError(e); | |
6326 | Double_t v4Error = fDiffFlow[t][1][1]->GetBinError(e); | |
6327 | //Double_t v6Error = fDiffFlow[t][1][2]->GetBinError(e); | |
6328 | //Double_t v8Error = fDiffFlow[t][1][3]->GetBinError(e); | |
6329 | ||
6330 | if(type == "RP") | |
6331 | { | |
6332 | fCommonHistsResults2nd->FillDifferentialFlowEtaRP(e,v2,v2Error); | |
6333 | fCommonHistsResults4th->FillDifferentialFlowEtaRP(e,v4,v4Error); | |
6334 | fCommonHistsResults6th->FillDifferentialFlowEtaRP(e,v6,0.); | |
6335 | fCommonHistsResults8th->FillDifferentialFlowEtaRP(e,v8,0.); | |
6336 | } else if(type == "POI") | |
6337 | { | |
6338 | fCommonHistsResults2nd->FillDifferentialFlowEtaPOI(e,v2,v2Error); | |
6339 | fCommonHistsResults4th->FillDifferentialFlowEtaPOI(e,v4,v4Error); | |
6340 | fCommonHistsResults6th->FillDifferentialFlowEtaPOI(e,v6,0.); | |
6341 | fCommonHistsResults8th->FillDifferentialFlowEtaPOI(e,v8,0.); | |
6342 | } | |
6343 | } // end of for(Int_t e=1;e<=fnBinsEta;e++) | |
6344 | ||
6345 | } // end of void AliFlowAnalysisWithQCumulants::FillCommonHistResultsDiffFlow(TString type, Bool_t useParticleWeights, TString eventWeights, Bool_t correctedForNUA) | |
6346 | ||
489d5531 | 6347 | //================================================================================================================================ |
6348 | ||
489d5531 | 6349 | void AliFlowAnalysisWithQCumulants::AccessConstants() |
6350 | { | |
b3dacf6b | 6351 | // Access needed common constants from AliFlowCommonConstants. |
489d5531 | 6352 | |
6353 | fnBinsPhi = AliFlowCommonConstants::GetMaster()->GetNbinsPhi(); | |
6354 | fPhiMin = AliFlowCommonConstants::GetMaster()->GetPhiMin(); | |
6355 | fPhiMax = AliFlowCommonConstants::GetMaster()->GetPhiMax(); | |
6356 | if(fnBinsPhi) fPhiBinWidth = (fPhiMax-fPhiMin)/fnBinsPhi; | |
6357 | fnBinsPt = AliFlowCommonConstants::GetMaster()->GetNbinsPt(); | |
6358 | fPtMin = AliFlowCommonConstants::GetMaster()->GetPtMin(); | |
6359 | fPtMax = AliFlowCommonConstants::GetMaster()->GetPtMax(); | |
6360 | if(fnBinsPt) fPtBinWidth = (fPtMax-fPtMin)/fnBinsPt; | |
6361 | fnBinsEta = AliFlowCommonConstants::GetMaster()->GetNbinsEta(); | |
6362 | fEtaMin = AliFlowCommonConstants::GetMaster()->GetEtaMin(); | |
6363 | fEtaMax = AliFlowCommonConstants::GetMaster()->GetEtaMax(); | |
6364 | if(fnBinsEta) fEtaBinWidth = (fEtaMax-fEtaMin)/fnBinsEta; | |
6365 | ||
6366 | } // end of void AliFlowAnalysisWithQCumulants::AccessConstants() | |
6367 | ||
489d5531 | 6368 | //================================================================================================================================ |
6369 | ||
489d5531 | 6370 | void AliFlowAnalysisWithQCumulants::CrossCheckSettings() |
6371 | { | |
6372 | // a) Cross check if the choice for multiplicity weights make sense; | |
6373 | ||
6374 | // a) Cross check if the choice for multiplicity weights make sense: | |
6375 | if(strcmp(fMultiplicityWeight->Data(),"combinations") && | |
6376 | strcmp(fMultiplicityWeight->Data(),"unit") && | |
6377 | strcmp(fMultiplicityWeight->Data(),"multiplicity")) | |
6378 | { | |
6379 | cout<<"WARNING (QC): Multiplicity weight can be either \"combinations\", \"unit\""<<endl; | |
6380 | cout<<" or \"multiplicity\". Certainly not \""<<fMultiplicityWeight->Data()<<"\"."<<endl; | |
6381 | exit(0); | |
6382 | } | |
6383 | ||
6384 | } // end of void AliFlowAnalysisWithQCumulants::CrossCheckSettings() | |
6385 | ||
489d5531 | 6386 | //================================================================================================================================ |
6387 | ||
489d5531 | 6388 | void AliFlowAnalysisWithQCumulants::CalculateIntFlowSumOfEventWeights() |
6389 | { | |
0328db2d | 6390 | // Calculate sum of linear and quadratic event weights for correlations. |
2001bc3a | 6391 | |
6392 | // multiplicity: | |
6393 | Double_t dMult = (*fSMpk)(0,0); | |
9f33751d | 6394 | |
489d5531 | 6395 | for(Int_t p=0;p<2;p++) // power-1 |
6396 | { | |
6397 | for(Int_t ci=0;ci<4;ci++) // correlation index | |
6398 | { | |
6399 | fIntFlowSumOfEventWeights[p]->Fill(ci+0.5,pow(fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(ci+1),p+1)); | |
b3dacf6b | 6400 | if(fCalculateCumulantsVsM) |
6401 | { | |
6402 | fIntFlowSumOfEventWeightsVsM[ci][p]->Fill(dMult+0.5,pow(fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(ci+1),p+1)); // to be improved: dMult => sum of weights? | |
6403 | } | |
489d5531 | 6404 | } |
6405 | } | |
6406 | ||
6407 | } // end of void AliFlowAnalysisWithQCumulants::CalculateIntFlowSumOfEventWeights() | |
6408 | ||
489d5531 | 6409 | //================================================================================================================================ |
6410 | ||
0328db2d | 6411 | void AliFlowAnalysisWithQCumulants::CalculateIntFlowSumOfEventWeightsNUA() |
489d5531 | 6412 | { |
0328db2d | 6413 | // Calculate sum of linear and quadratic event weights for NUA terms. |
6414 | ||
6415 | for(Int_t sc=0;sc<2;sc++) // sin or cos terms | |
489d5531 | 6416 | { |
0328db2d | 6417 | for(Int_t p=0;p<2;p++) // power-1 |
6418 | { | |
b92ea2b9 | 6419 | for(Int_t ci=0;ci<4;ci++) // nua term index |
0328db2d | 6420 | { |
6421 | fIntFlowSumOfEventWeightsNUA[sc][p]->Fill(ci+0.5,pow(fIntFlowEventWeightForCorrectionTermsForNUAEBE[sc]->GetBinContent(ci+1),p+1)); | |
489d5531 | 6422 | } |
0328db2d | 6423 | } |
6424 | } | |
6425 | ||
6426 | } // end of void AliFlowAnalysisWithQCumulants::CalculateIntFlowSumOfEventWeightsNUA() | |
489d5531 | 6427 | |
0328db2d | 6428 | //================================================================================================================================ |
6429 | ||
0328db2d | 6430 | void AliFlowAnalysisWithQCumulants::CalculateIntFlowSumOfProductOfEventWeights() |
6431 | { | |
ff70ca91 | 6432 | // Calculate sum of product of event weights for correlations. |
2001bc3a | 6433 | |
6434 | // multiplicity: | |
6435 | Double_t dMult = (*fSMpk)(0,0); | |
6436 | ||
489d5531 | 6437 | Int_t counter = 0; |
6438 | ||
6439 | for(Int_t ci1=1;ci1<4;ci1++) | |
6440 | { | |
6441 | for(Int_t ci2=ci1+1;ci2<=4;ci2++) | |
6442 | { | |
ff70ca91 | 6443 | fIntFlowSumOfProductOfEventWeights->Fill(0.5+counter, |
6444 | fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(ci1)* | |
b3dacf6b | 6445 | fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(ci2)); |
6446 | if(fCalculateCumulantsVsM) | |
6447 | { | |
6448 | fIntFlowSumOfProductOfEventWeightsVsM[counter]->Fill(dMult+0.5, // to be improved: dMult => sum of weights? | |
6449 | fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(ci1)* | |
6450 | fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(ci2)); | |
6451 | } // end of if(fCalculateCumulantsVsM) | |
ff70ca91 | 6452 | counter++; |
489d5531 | 6453 | } |
6454 | } | |
6455 | ||
0328db2d | 6456 | } // end of void AliFlowAnalysisWithQCumulants::CalculateIntFlowSumOfProductOfEventWeights() |
6457 | ||
0328db2d | 6458 | //================================================================================================================================ |
6459 | ||
0328db2d | 6460 | void AliFlowAnalysisWithQCumulants::CalculateIntFlowSumOfProductOfEventWeightsNUA() |
6461 | { | |
6462 | // Calculate sum of product of event weights for NUA terms. | |
6463 | ||
6464 | // w_{<2>} * w_{<cos(#phi)>}: | |
6465 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(0.5,fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1)* | |
6466 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1)); | |
6467 | // w_{<2>} * w_{<sin(#phi)>}: | |
6468 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(1.5,fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1)* | |
6469 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1)); | |
6470 | // w_{<cos(#phi)> * w_{<sin(#phi)>}: | |
6471 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(2.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1)* | |
6472 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1)); | |
6473 | // w_{<2>} * w{<cos(phi1+phi2)>} | |
6474 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(3.5,fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1)* | |
6475 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2)); | |
6476 | // w_{<2>} * w{<sin(phi1+phi2)>} | |
6477 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(4.5,fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1)* | |
6478 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2)); | |
6479 | // w_{<2>} * w{<cos(phi1-phi2-phi3)>} | |
6480 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(5.5,fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1)* | |
6481 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)); | |
6482 | // w_{<2>} * w{<sin(phi1-phi2-phi3)>} | |
6483 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(6.5,fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1)* | |
6484 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); | |
6485 | // w_{<4>} * w{<cos(phi1)>} | |
6486 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(7.5,fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2)* | |
6487 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1)); | |
6488 | // w_{<4>} * w{<sin(phi1)>} | |
6489 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(8.5,fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2)* | |
6490 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1)); | |
6491 | // w_{<4>} * w{<cos(phi1+phi2)>} | |
6492 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(9.5,fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2)* | |
6493 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2)); | |
6494 | // w_{<4>} * w{<sin(phi1+phi2)>} | |
6495 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(10.5,fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2)* | |
6496 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2)); | |
6497 | // w_{<4>} * w{<cos(phi1-phi2-phi3)>} | |
6498 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(11.5,fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2)* | |
6499 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)); | |
6500 | // w_{<4>} * w{<sin(phi1-phi2-phi3)>} | |
6501 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(12.5,fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2)* | |
6502 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); | |
6503 | // w_{<cos(phi1)>} * w{<cos(phi1+phi2)>} | |
6504 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(13.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1)* | |
6505 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2)); | |
6506 | // w_{<cos(phi1)>} * w{<sin(phi1+phi2)>} | |
6507 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(14.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1)* | |
6508 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2)); | |
6509 | // w_{<cos(phi1)>} * w{<cos(phi1-phi2-phi3)>} | |
6510 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(15.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1)* | |
6511 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)); | |
6512 | // w_{<cos(phi1)>} * w{<sin(phi1-phi2-phi3)>} | |
6513 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(16.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(1)* | |
6514 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); | |
6515 | // w_{<sin(phi1)>} * w{<cos(phi1+phi2)>} | |
6516 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(17.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1)* | |
6517 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2)); | |
6518 | // w_{<sin(phi1)>} * w{<sin(phi1+phi2)>} | |
6519 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(18.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1)* | |
6520 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2)); | |
6521 | // w_{<sin(phi1)>} * w{<cos(phi1-phi2-phi3)>} | |
6522 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(19.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1)* | |
6523 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)); | |
6524 | // w_{<sin(phi1)>} * w{<sin(phi1-phi2-phi3)>} | |
6525 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(20.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(1)* | |
6526 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); | |
6527 | // w_{<cos(phi1+phi2)>} * w{<sin(phi1+phi2))>} | |
6528 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(21.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2)* | |
6529 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2)); | |
6530 | // w_{<cos(phi1+phi2)>} * w{<cos(phi1-phi2-phi3)>} | |
6531 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(22.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2)* | |
6532 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)); | |
6533 | // w_{<cos(phi1+phi2)>} * w{<sin(phi1-phi2-phi3)>} | |
6534 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(23.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(2)* | |
6535 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); | |
6536 | // w_{<sin(phi1+phi2)>} * w{<cos(phi1-phi2-phi3)>} | |
6537 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(24.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2)* | |
6538 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)); | |
6539 | // w_{<sin(phi1+phi2)>} * w{<sin(phi1-phi2-phi3)>} | |
6540 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(25.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(2)* | |
6541 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); | |
6542 | // w_{<cos(phi1-phi2-phi3)>} * w{<sin(phi1-phi2-phi3)>} | |
6543 | fIntFlowSumOfProductOfEventWeightsNUA->Fill(26.5,fIntFlowEventWeightForCorrectionTermsForNUAEBE[1]->GetBinContent(3)* | |
6544 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[0]->GetBinContent(3)); | |
6545 | ||
6546 | } // end of void AliFlowAnalysisWithQCumulants::CalculateIntFlowIntFlowSumOfProductOfEventWeightsNUA() | |
489d5531 | 6547 | |
6548 | ||
6549 | //================================================================================================================================ | |
6550 | ||
6551 | ||
6552 | void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrelations(TString type, TString ptOrEta) | |
6553 | { | |
6554 | // calculate reduced correlations for RPs or POIs in pt or eta bins | |
6555 | ||
6556 | // multiplicity: | |
6557 | Double_t dMult = (*fSMpk)(0,0); | |
6558 | ||
6559 | // real and imaginary parts of non-weighted Q-vectors evaluated in harmonics n, 2n, 3n and 4n: | |
6560 | Double_t dReQ1n = (*fReQ)(0,0); | |
6561 | Double_t dReQ2n = (*fReQ)(1,0); | |
6562 | //Double_t dReQ3n = (*fReQ)(2,0); | |
6563 | //Double_t dReQ4n = (*fReQ)(3,0); | |
6564 | Double_t dImQ1n = (*fImQ)(0,0); | |
6565 | Double_t dImQ2n = (*fImQ)(1,0); | |
6566 | //Double_t dImQ3n = (*fImQ)(2,0); | |
6567 | //Double_t dImQ4n = (*fImQ)(3,0); | |
6568 | ||
6569 | // reduced correlations are stored in fDiffFlowCorrelationsPro[0=RP,1=POI][0=pt,1=eta][correlation index]. Correlation index runs as follows: | |
6570 | // | |
6571 | // 0: <<2'>> | |
6572 | // 1: <<4'>> | |
6573 | // 2: <<6'>> | |
6574 | // 3: <<8'>> | |
6575 | ||
2a98ceb8 | 6576 | Int_t t = 0; // type flag |
6577 | Int_t pe = 0; // ptEta flag | |
489d5531 | 6578 | |
6579 | if(type == "RP") | |
6580 | { | |
6581 | t = 0; | |
6582 | } else if(type == "POI") | |
6583 | { | |
6584 | t = 1; | |
6585 | } | |
6586 | ||
6587 | if(ptOrEta == "Pt") | |
6588 | { | |
6589 | pe = 0; | |
6590 | } else if(ptOrEta == "Eta") | |
6591 | { | |
6592 | pe = 1; | |
6593 | } | |
6594 | ||
6595 | Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; | |
6596 | Double_t minPtEta[2] = {fPtMin,fEtaMin}; | |
6597 | //Double_t maxPtEta[2] = {fPtMax,fEtaMax}; | |
6598 | Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; | |
6599 | ||
6600 | // looping over all bins and calculating reduced correlations: | |
6601 | for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
6602 | { | |
6603 | // real and imaginary parts of p_{m*n,0} (non-weighted Q-vector evaluated for POIs in particular pt or eta bin): | |
6604 | Double_t p1n0kRe = 0.; | |
6605 | Double_t p1n0kIm = 0.; | |
6606 | ||
6607 | // number of POIs in particular pt or eta bin: | |
6608 | Double_t mp = 0.; | |
6609 | ||
6610 | // real and imaginary parts of q_{m*n,0} (non-weighted Q-vector evaluated for particles which are both RPs and POIs in particular pt or eta bin): | |
6611 | Double_t q1n0kRe = 0.; | |
6612 | Double_t q1n0kIm = 0.; | |
6613 | Double_t q2n0kRe = 0.; | |
6614 | Double_t q2n0kIm = 0.; | |
6615 | ||
6616 | // number of particles which are both RPs and POIs in particular pt or eta bin: | |
6617 | Double_t mq = 0.; | |
6618 | ||
6619 | if(type == "POI") | |
6620 | { | |
6621 | // q_{m*n,0}: | |
6622 | q1n0kRe = fReRPQ1dEBE[2][pe][0][0]->GetBinContent(fReRPQ1dEBE[2][pe][0][0]->GetBin(b)) | |
6623 | * fReRPQ1dEBE[2][pe][0][0]->GetBinEntries(fReRPQ1dEBE[2][pe][0][0]->GetBin(b)); | |
6624 | q1n0kIm = fImRPQ1dEBE[2][pe][0][0]->GetBinContent(fImRPQ1dEBE[2][pe][0][0]->GetBin(b)) | |
6625 | * fImRPQ1dEBE[2][pe][0][0]->GetBinEntries(fImRPQ1dEBE[2][pe][0][0]->GetBin(b)); | |
6626 | q2n0kRe = fReRPQ1dEBE[2][pe][1][0]->GetBinContent(fReRPQ1dEBE[2][pe][1][0]->GetBin(b)) | |
6627 | * fReRPQ1dEBE[2][pe][1][0]->GetBinEntries(fReRPQ1dEBE[2][pe][1][0]->GetBin(b)); | |
6628 | q2n0kIm = fImRPQ1dEBE[2][pe][1][0]->GetBinContent(fImRPQ1dEBE[2][pe][1][0]->GetBin(b)) | |
6629 | * fImRPQ1dEBE[2][pe][1][0]->GetBinEntries(fImRPQ1dEBE[2][pe][1][0]->GetBin(b)); | |
6630 | ||
6631 | mq = fReRPQ1dEBE[2][pe][0][0]->GetBinEntries(fReRPQ1dEBE[2][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) | |
6632 | } | |
6633 | else if(type == "RP") | |
6634 | { | |
6635 | // q_{m*n,0}: | |
6636 | q1n0kRe = fReRPQ1dEBE[0][pe][0][0]->GetBinContent(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)) | |
6637 | * fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)); | |
6638 | q1n0kIm = fImRPQ1dEBE[0][pe][0][0]->GetBinContent(fImRPQ1dEBE[0][pe][0][0]->GetBin(b)) | |
6639 | * fImRPQ1dEBE[0][pe][0][0]->GetBinEntries(fImRPQ1dEBE[0][pe][0][0]->GetBin(b)); | |
6640 | q2n0kRe = fReRPQ1dEBE[0][pe][1][0]->GetBinContent(fReRPQ1dEBE[0][pe][1][0]->GetBin(b)) | |
6641 | * fReRPQ1dEBE[0][pe][1][0]->GetBinEntries(fReRPQ1dEBE[0][pe][1][0]->GetBin(b)); | |
6642 | q2n0kIm = fImRPQ1dEBE[0][pe][1][0]->GetBinContent(fImRPQ1dEBE[0][pe][1][0]->GetBin(b)) | |
6643 | * fImRPQ1dEBE[0][pe][1][0]->GetBinEntries(fImRPQ1dEBE[0][pe][1][0]->GetBin(b)); | |
6644 | ||
6645 | mq = fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) | |
6646 | } | |
6647 | ||
6648 | if(type == "POI") | |
6649 | { | |
6650 | // p_{m*n,0}: | |
6651 | p1n0kRe = fReRPQ1dEBE[1][pe][0][0]->GetBinContent(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)) | |
6652 | * fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)); | |
6653 | p1n0kIm = fImRPQ1dEBE[1][pe][0][0]->GetBinContent(fImRPQ1dEBE[1][pe][0][0]->GetBin(b)) | |
6654 | * fImRPQ1dEBE[1][pe][0][0]->GetBinEntries(fImRPQ1dEBE[1][pe][0][0]->GetBin(b)); | |
6655 | ||
6656 | mp = fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) | |
6657 | ||
6658 | t = 1; // typeFlag = RP or POI | |
6659 | } | |
6660 | else if(type == "RP") | |
6661 | { | |
6662 | // p_{m*n,0} = q_{m*n,0}: | |
6663 | p1n0kRe = q1n0kRe; | |
6664 | p1n0kIm = q1n0kIm; | |
6665 | ||
6666 | mp = mq; | |
6667 | ||
6668 | t = 0; // typeFlag = RP or POI | |
6669 | } | |
6670 | ||
6671 | // 2'-particle correlation for particular (pt,eta) bin: | |
6672 | Double_t two1n1nPtEta = 0.; | |
b40a910e | 6673 | Double_t mWeight2pPrime = 0.; // multiplicity weight for <2'> |
489d5531 | 6674 | if(mp*dMult-mq) |
6675 | { | |
6676 | two1n1nPtEta = (p1n0kRe*dReQ1n+p1n0kIm*dImQ1n-mq) | |
6677 | / (mp*dMult-mq); | |
b40a910e | 6678 | // determine multiplicity weight: |
6679 | if(!strcmp(fMultiplicityWeight->Data(),"combinations")) | |
6680 | { | |
6681 | mWeight2pPrime = mp*dMult-mq; | |
6682 | } else if(!strcmp(fMultiplicityWeight->Data(),"unit")) | |
6683 | { | |
6684 | mWeight2pPrime = 1.; | |
6685 | } | |
489d5531 | 6686 | if(type == "POI") // to be improved (I do not this if) |
6687 | { | |
6688 | // fill profile to get <<2'>> for POIs | |
b40a910e | 6689 | fDiffFlowCorrelationsPro[1][pe][0]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],two1n1nPtEta,mWeight2pPrime); |
6690 | // fill profile to get <<2'>^2> for POIs | |
6691 | fDiffFlowSquaredCorrelationsPro[1][pe][0]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],two1n1nPtEta*two1n1nPtEta,mWeight2pPrime); | |
489d5531 | 6692 | // histogram to store <2'> for POIs e-b-e (needed in some other methods): |
6693 | fDiffFlowCorrelationsEBE[1][pe][0]->SetBinContent(b,two1n1nPtEta); | |
b40a910e | 6694 | fDiffFlowEventWeightsForCorrelationsEBE[1][pe][0]->SetBinContent(b,mWeight2pPrime); |
489d5531 | 6695 | } |
6696 | else if(type == "RP") // to be improved (I do not this if) | |
6697 | { | |
6698 | // profile to get <<2'>> for RPs: | |
b40a910e | 6699 | fDiffFlowCorrelationsPro[0][pe][0]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],two1n1nPtEta,mWeight2pPrime); |
6700 | // profile to get <<2'>^2> for RPs: | |
6701 | fDiffFlowSquaredCorrelationsPro[0][pe][0]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],two1n1nPtEta*two1n1nPtEta,mWeight2pPrime); | |
489d5531 | 6702 | // histogram to store <2'> for RPs e-b-e (needed in some other methods): |
6703 | fDiffFlowCorrelationsEBE[0][pe][0]->SetBinContent(b,two1n1nPtEta); | |
b40a910e | 6704 | fDiffFlowEventWeightsForCorrelationsEBE[0][pe][0]->SetBinContent(b,mWeight2pPrime); |
489d5531 | 6705 | } |
6706 | } // end of if(mp*dMult-mq) | |
6707 | ||
6708 | // 4'-particle correlation: | |
6709 | Double_t four1n1n1n1nPtEta = 0.; | |
b40a910e | 6710 | Double_t mWeight4pPrime = 0.; // multiplicity weight for <4'> |
489d5531 | 6711 | if((mp-mq)*dMult*(dMult-1.)*(dMult-2.) |
6712 | + mq*(dMult-1.)*(dMult-2.)*(dMult-3.)) // to be improved (introduce a new variable for this expression) | |
6713 | { | |
6714 | four1n1n1n1nPtEta = ((pow(dReQ1n,2.)+pow(dImQ1n,2.))*(p1n0kRe*dReQ1n+p1n0kIm*dImQ1n) | |
6715 | - q2n0kRe*(pow(dReQ1n,2.)-pow(dImQ1n,2.)) | |
6716 | - 2.*q2n0kIm*dReQ1n*dImQ1n | |
6717 | - p1n0kRe*(dReQ1n*dReQ2n+dImQ1n*dImQ2n) | |
6718 | + p1n0kIm*(dImQ1n*dReQ2n-dReQ1n*dImQ2n) | |
6719 | - 2.*dMult*(p1n0kRe*dReQ1n+p1n0kIm*dImQ1n) | |
6720 | - 2.*(pow(dReQ1n,2.)+pow(dImQ1n,2.))*mq | |
6721 | + 6.*(q1n0kRe*dReQ1n+q1n0kIm*dImQ1n) | |
6722 | + 1.*(q2n0kRe*dReQ2n+q2n0kIm*dImQ2n) | |
6723 | + 2.*(p1n0kRe*dReQ1n+p1n0kIm*dImQ1n) | |
6724 | + 2.*mq*dMult | |
6725 | - 6.*mq) | |
6726 | / ((mp-mq)*dMult*(dMult-1.)*(dMult-2.) | |
6727 | + mq*(dMult-1.)*(dMult-2.)*(dMult-3.)); | |
b40a910e | 6728 | // determine multiplicity weight: |
6729 | if(!strcmp(fMultiplicityWeight->Data(),"combinations")) | |
6730 | { | |
6731 | mWeight4pPrime = (mp-mq)*dMult*(dMult-1.)*(dMult-2.) + mq*(dMult-1.)*(dMult-2.)*(dMult-3.); | |
6732 | } else if(!strcmp(fMultiplicityWeight->Data(),"unit")) | |
6733 | { | |
6734 | mWeight4pPrime = 1.; | |
6735 | } | |
489d5531 | 6736 | if(type == "POI") |
6737 | { | |
6738 | // profile to get <<4'>> for POIs: | |
b40a910e | 6739 | fDiffFlowCorrelationsPro[1][pe][1]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],four1n1n1n1nPtEta,mWeight4pPrime); |
6740 | // profile to get <<4'>^2> for POIs: | |
6741 | fDiffFlowSquaredCorrelationsPro[1][pe][1]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],four1n1n1n1nPtEta*four1n1n1n1nPtEta,mWeight4pPrime); | |
489d5531 | 6742 | // histogram to store <4'> for POIs e-b-e (needed in some other methods): |
6743 | fDiffFlowCorrelationsEBE[1][pe][1]->SetBinContent(b,four1n1n1n1nPtEta); | |
b40a910e | 6744 | fDiffFlowEventWeightsForCorrelationsEBE[1][pe][1]->SetBinContent(b,mWeight4pPrime); |
489d5531 | 6745 | } |
6746 | else if(type == "RP") | |
6747 | { | |
6748 | // profile to get <<4'>> for RPs: | |
b40a910e | 6749 | fDiffFlowCorrelationsPro[0][pe][1]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],four1n1n1n1nPtEta,mWeight4pPrime); |
6750 | // profile to get <<4'>^2> for RPs: | |
6751 | fDiffFlowSquaredCorrelationsPro[0][pe][1]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],four1n1n1n1nPtEta*four1n1n1n1nPtEta,mWeight4pPrime); | |
489d5531 | 6752 | // histogram to store <4'> for RPs e-b-e (needed in some other methods): |
6753 | fDiffFlowCorrelationsEBE[0][pe][1]->SetBinContent(b,four1n1n1n1nPtEta); | |
b40a910e | 6754 | fDiffFlowEventWeightsForCorrelationsEBE[0][pe][1]->SetBinContent(b,mWeight4pPrime); |
489d5531 | 6755 | } |
6756 | } // end of if((mp-mq)*dMult*(dMult-1.)*(dMult-2.) | |
6757 | // +mq*(dMult-1.)*(dMult-2.)*(dMult-3.)) | |
6758 | ||
6759 | } // end of for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
6760 | ||
6761 | ||
6762 | } // end of void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrelations(TString type, TString ptOrEta); | |
6763 | ||
489d5531 | 6764 | //================================================================================================================================ |
6765 | ||
489d5531 | 6766 | void AliFlowAnalysisWithQCumulants::CalculateDiffFlowSumOfEventWeights(TString type, TString ptOrEta) |
6767 | { | |
6768 | // Calculate sums of various event weights for reduced correlations. | |
6769 | // (These quantitites are needed in expressions for unbiased estimators relevant for the statistical errors.) | |
6770 | ||
2a98ceb8 | 6771 | Int_t typeFlag = 0; |
6772 | Int_t ptEtaFlag = 0; | |
489d5531 | 6773 | |
6774 | if(type == "RP") | |
6775 | { | |
6776 | typeFlag = 0; | |
6777 | } else if(type == "POI") | |
6778 | { | |
6779 | typeFlag = 1; | |
6780 | } | |
6781 | ||
6782 | if(ptOrEta == "Pt") | |
6783 | { | |
6784 | ptEtaFlag = 0; | |
6785 | } else if(ptOrEta == "Eta") | |
6786 | { | |
6787 | ptEtaFlag = 1; | |
6788 | } | |
6789 | ||
6790 | // shortcuts: | |
6791 | Int_t t = typeFlag; | |
6792 | Int_t pe = ptEtaFlag; | |
6793 | ||
6794 | // binning: | |
6795 | Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; | |
6796 | Double_t minPtEta[2] = {fPtMin,fEtaMin}; | |
6797 | //Double_t maxPtEta[2] = {fPtMax,fEtaMax}; | |
6798 | Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; | |
6799 | ||
6800 | for(Int_t rpq=0;rpq<3;rpq++) | |
6801 | { | |
6802 | for(Int_t m=0;m<4;m++) | |
6803 | { | |
6804 | for(Int_t k=0;k<9;k++) | |
6805 | { | |
6806 | if(!fReRPQ1dEBE[rpq][pe][m][k]) | |
6807 | { | |
6808 | cout<<"WARNING: fReRPQ1dEBE[rpq][pe][m][k] is NULL in AFAWQC::CSAPOEWFDF() !!!!"<<endl; | |
6809 | cout<<"pe = "<<pe<<endl; | |
6810 | cout<<"rpq = "<<rpq<<endl; | |
6811 | cout<<"m = "<<m<<endl; | |
6812 | cout<<"k = "<<k<<endl; | |
6813 | exit(0); | |
6814 | } | |
6815 | } | |
6816 | } | |
6817 | } | |
6818 | ||
6819 | // multiplicities: | |
6820 | Double_t dMult = (*fSMpk)(0,0); // total event multiplicity | |
6821 | //Double_t mr = 0.; // number of RPs in particular pt or eta bin | |
6822 | Double_t mp = 0.; // number of POIs in particular pt or eta bin | |
6823 | Double_t mq = 0.; // number of particles which are both RPs and POIs in particular pt or eta bin | |
6824 | ||
6825 | // event weights for reduced correlations: | |
6826 | Double_t dw2 = 0.; // event weight for <2'> | |
6827 | Double_t dw4 = 0.; // event weight for <4'> | |
6828 | //Double_t dw6 = 0.; // event weight for <6'> | |
6829 | //Double_t dw8 = 0.; // event weight for <8'> | |
6830 | ||
6831 | // looping over bins: | |
6832 | for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
6833 | { | |
6834 | if(type == "RP") | |
6835 | { | |
6836 | mq = fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(b); | |
6837 | mp = mq; // trick to use the very same Eqs. bellow both for RP's and POI's diff. flow | |
6838 | } else if(type == "POI") | |
6839 | { | |
6840 | mp = fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(b); | |
6841 | mq = fReRPQ1dEBE[2][pe][0][0]->GetBinEntries(b); | |
6842 | } | |
6843 | ||
6844 | // event weight for <2'>: | |
6845 | dw2 = mp*dMult-mq; | |
6846 | fDiffFlowSumOfEventWeights[t][pe][0][0]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw2); | |
6847 | fDiffFlowSumOfEventWeights[t][pe][1][0]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],pow(dw2,2.)); | |
6848 | ||
6849 | // event weight for <4'>: | |
6850 | dw4 = (mp-mq)*dMult*(dMult-1.)*(dMult-2.) | |
6851 | + mq*(dMult-1.)*(dMult-2.)*(dMult-3.); | |
6852 | fDiffFlowSumOfEventWeights[t][pe][0][1]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw4); | |
6853 | fDiffFlowSumOfEventWeights[t][pe][1][1]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],pow(dw4,2.)); | |
6854 | ||
6855 | // event weight for <6'>: | |
6856 | //dw6 = ...; | |
6857 | //fDiffFlowSumOfEventWeights[t][pe][0][2]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw6); | |
6858 | //fDiffFlowSumOfEventWeights[t][pe][t][1][2]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],pow(dw6,2.)); | |
6859 | ||
6860 | // event weight for <8'>: | |
6861 | //dw8 = ...; | |
6862 | //fDiffFlowSumOfEventWeights[t][pe][0][3]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw8); | |
6863 | //fDiffFlowSumOfEventWeights[t][pe][1][3]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],pow(dw8,2.)); | |
6864 | } // end of for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
6865 | ||
6866 | } // end of void AliFlowAnalysisWithQCumulants::CalculateDiffFlowSumOfEventWeights() | |
6867 | ||
6868 | ||
6869 | //================================================================================================================================ | |
6870 | ||
6871 | ||
6872 | void AliFlowAnalysisWithQCumulants::CalculateDiffFlowSumOfProductOfEventWeights(TString type, TString ptOrEta) | |
6873 | { | |
6874 | // Calculate sum of products of various event weights for both types of correlations (the ones for int. and diff. flow). | |
6875 | // (These quantitites are needed in expressions for unbiased estimators relevant for the statistical errors.) | |
6876 | // | |
6877 | // Important: To fill fDiffFlowSumOfProductOfEventWeights[][][][] use bellow table (i,j) with following constraints: | |
6878 | // 1.) i<j | |
6879 | // 2.) do not store terms which DO NOT include reduced correlations; | |
6880 | // Table: | |
6881 | // [0=<2>,1=<2'>,2=<4>,3=<4'>,4=<6>,5=<6'>,6=<8>,7=<8'>] x [0=<2>,1=<2'>,2=<4>,3=<4'>,4=<6>,5=<6'>,6=<8>,7=<8'>] | |
6882 | ||
2a98ceb8 | 6883 | Int_t typeFlag = 0; |
6884 | Int_t ptEtaFlag = 0; | |
489d5531 | 6885 | |
6886 | if(type == "RP") | |
6887 | { | |
6888 | typeFlag = 0; | |
6889 | } else if(type == "POI") | |
6890 | { | |
6891 | typeFlag = 1; | |
6892 | } | |
6893 | ||
6894 | if(ptOrEta == "Pt") | |
6895 | { | |
6896 | ptEtaFlag = 0; | |
6897 | } else if(ptOrEta == "Eta") | |
6898 | { | |
6899 | ptEtaFlag = 1; | |
6900 | } | |
6901 | ||
6902 | // shortcuts: | |
6903 | Int_t t = typeFlag; | |
6904 | Int_t pe = ptEtaFlag; | |
6905 | ||
6906 | // binning: | |
6907 | Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; | |
6908 | Double_t minPtEta[2] = {fPtMin,fEtaMin}; | |
6909 | //Double_t maxPtEta[2] = {fPtMax,fEtaMax}; | |
6910 | Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; | |
6911 | ||
6912 | // protection: | |
6913 | for(Int_t rpq=0;rpq<3;rpq++) | |
6914 | { | |
6915 | for(Int_t m=0;m<4;m++) | |
6916 | { | |
6917 | for(Int_t k=0;k<9;k++) | |
6918 | { | |
6919 | if(!fReRPQ1dEBE[rpq][pe][m][k]) | |
6920 | { | |
6921 | cout<<"WARNING: fReRPQ1dEBE[rpq][pe][m][k] is NULL in AFAWQC::CSAPOEWFDF() !!!!"<<endl; | |
6922 | cout<<"pe = "<<pe<<endl; | |
6923 | cout<<"rpq = "<<rpq<<endl; | |
6924 | cout<<"m = "<<m<<endl; | |
6925 | cout<<"k = "<<k<<endl; | |
6926 | exit(0); | |
6927 | } | |
6928 | } | |
6929 | } | |
6930 | } | |
6931 | ||
6932 | // multiplicities: | |
6933 | Double_t dMult = (*fSMpk)(0,0); // total event multiplicity | |
6934 | //Double_t mr = 0.; // number of RPs in particular pt or eta bin | |
6935 | Double_t mp = 0.; // number of POIs in particular pt or eta bin | |
6936 | Double_t mq = 0.; // number of particles which are both RPs and POIs in particular pt or eta bin | |
6937 | ||
6938 | // event weights for correlations: | |
6939 | Double_t dW2 = dMult*(dMult-1); // event weight for <2> | |
6940 | Double_t dW4 = dMult*(dMult-1)*(dMult-2)*(dMult-3); // event weight for <4> | |
6941 | Double_t dW6 = dMult*(dMult-1)*(dMult-2)*(dMult-3)*(dMult-4)*(dMult-5); // event weight for <6> | |
6942 | Double_t dW8 = dMult*(dMult-1)*(dMult-2)*(dMult-3)*(dMult-4)*(dMult-5)*(dMult-6)*(dMult-7); // event weight for <8> | |
6943 | ||
6944 | // event weights for reduced correlations: | |
6945 | Double_t dw2 = 0.; // event weight for <2'> | |
6946 | Double_t dw4 = 0.; // event weight for <4'> | |
6947 | //Double_t dw6 = 0.; // event weight for <6'> | |
6948 | //Double_t dw8 = 0.; // event weight for <8'> | |
6949 | ||
6950 | // looping over bins: | |
6951 | for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
6952 | { | |
6953 | if(type == "RP") | |
6954 | { | |
6955 | mq = fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(b); | |
6956 | mp = mq; // trick to use the very same Eqs. bellow both for RP's and POI's diff. flow | |
6957 | } else if(type == "POI") | |
6958 | { | |
6959 | mp = fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(b); | |
6960 | mq = fReRPQ1dEBE[2][pe][0][0]->GetBinEntries(b); | |
6961 | } | |
6962 | ||
6963 | // event weight for <2'>: | |
6964 | dw2 = mp*dMult-mq; | |
6965 | fDiffFlowSumOfProductOfEventWeights[t][pe][0][1]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dW2*dw2); // storing product of even weights for <2> and <2'> | |
6966 | fDiffFlowSumOfProductOfEventWeights[t][pe][1][2]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw2*dW4); // storing product of even weights for <4> and <2'> | |
6967 | fDiffFlowSumOfProductOfEventWeights[t][pe][1][4]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw2*dW6); // storing product of even weights for <6> and <2'> | |
6968 | fDiffFlowSumOfProductOfEventWeights[t][pe][1][6]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw2*dW8); // storing product of even weights for <8> and <2'> | |
6969 | ||
6970 | // event weight for <4'>: | |
6971 | dw4 = (mp-mq)*dMult*(dMult-1.)*(dMult-2.) | |
6972 | + mq*(dMult-1.)*(dMult-2.)*(dMult-3.); | |
6973 | fDiffFlowSumOfProductOfEventWeights[t][pe][0][3]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dW2*dw4); // storing product of even weights for <2> and <4'> | |
6974 | fDiffFlowSumOfProductOfEventWeights[t][pe][1][3]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw2*dw4); // storing product of even weights for <2'> and <4'> | |
6975 | fDiffFlowSumOfProductOfEventWeights[t][pe][2][3]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dW4*dw4); // storing product of even weights for <4> and <4'> | |
6976 | fDiffFlowSumOfProductOfEventWeights[t][pe][3][4]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw4*dW6); // storing product of even weights for <6> and <4'> | |
6977 | fDiffFlowSumOfProductOfEventWeights[t][pe][3][6]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw4*dW8); // storing product of even weights for <8> and <4'> | |
6978 | ||
6979 | // event weight for <6'>: | |
6980 | //dw6 = ...; | |
6981 | //fDiffFlowSumOfProductOfEventWeights[t][pe][0][5]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dW2*dw6); // storing product of even weights for <2> and <6'> | |
6982 | //fDiffFlowSumOfProductOfEventWeights[t][pe][1][5]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw2*dw6); // storing product of even weights for <2'> and <6'> | |
6983 | //fDiffFlowSumOfProductOfEventWeights[t][pe][2][5]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dW4*dw6); // storing product of even weights for <4> and <6'> | |
6984 | //fDiffFlowSumOfProductOfEventWeights[t][pe][3][5]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw4*dw6); // storing product of even weights for <4'> and <6'> | |
6985 | //fDiffFlowSumOfProductOfEventWeights[t][pe][4][5]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dW6*dw6); // storing product of even weights for <6> and <6'> | |
6986 | //fDiffFlowSumOfProductOfEventWeights[t][pe][5][6]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw6*dW8); // storing product of even weights for <6'> and <8> | |
6987 | //fDiffFlowSumOfProductOfEventWeights[t][pe][5][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw6*dw8); // storing product of even weights for <6'> and <8'> | |
6988 | ||
6989 | // event weight for <8'>: | |
6990 | //dw8 = ...; | |
6991 | //fDiffFlowSumOfProductOfEventWeights[t][pe][0][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dW2*dw8); // storing product of even weights for <2> and <8'> | |
6992 | //fDiffFlowSumOfProductOfEventWeights[t][pe][1][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw2*dw8); // storing product of even weights for <2'> and <8'> | |
6993 | //fDiffFlowSumOfProductOfEventWeights[t][pe][2][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dW4*dw8); // storing product of even weights for <4> and <8'> | |
6994 | //fDiffFlowSumOfProductOfEventWeights[t][pe][3][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw4*dw8); // storing product of even weights for <4'> and <8'> | |
6995 | //fDiffFlowSumOfProductOfEventWeights[t][pe][4][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dW6*dw8); // storing product of even weights for <6> and <8'> | |
6996 | //fDiffFlowSumOfProductOfEventWeights[t][pe][5][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dw6*dw8); // storing product of even weights for <6'> and <8'> | |
6997 | //fDiffFlowSumOfProductOfEventWeights[t][pe][6][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],dW8*dw8); // storing product of even weights for <8> and <8'> | |
6998 | ||
6999 | // Table: | |
7000 | // [0=<2>,1=<2'>,2=<4>,3=<4'>,4=<6>,5=<6'>,6=<8>,7=<8'>] x [0=<2>,1=<2'>,2=<4>,3=<4'>,4=<6>,5=<6'>,6=<8>,7=<8'>] | |
7001 | ||
7002 | } // end of for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
7003 | ||
7004 | ||
7005 | ||
7006 | } // end of void AliFlowAnalysisWithQCumulants::CalculateDiffFlowSumOfProductOfEventWeights(TString type, TString ptOrEta) | |
7007 | ||
7008 | ||
7009 | //================================================================================================================================ | |
7010 | ||
7011 | ||
7012 | void AliFlowAnalysisWithQCumulants::FinalizeReducedCorrelations(TString type, TString ptOrEta) | |
7013 | { | |
7014 | // Transfer profiles into histograms and calculate statistical errors correctly. | |
7015 | ||
2a98ceb8 | 7016 | Int_t typeFlag = 0; |
7017 | Int_t ptEtaFlag = 0; | |
489d5531 | 7018 | |
7019 | if(type == "RP") | |
7020 | { | |
7021 | typeFlag = 0; | |
7022 | } else if(type == "POI") | |
7023 | { | |
7024 | typeFlag = 1; | |
7025 | } | |
7026 | ||
7027 | if(ptOrEta == "Pt") | |
7028 | { | |
7029 | ptEtaFlag = 0; | |
7030 | } else if(ptOrEta == "Eta") | |
7031 | { | |
7032 | ptEtaFlag = 1; | |
7033 | } | |
7034 | ||
7035 | // shortcuts: | |
7036 | Int_t t = typeFlag; | |
7037 | Int_t pe = ptEtaFlag; | |
7038 | ||
7039 | for(Int_t rci=0;rci<4;rci++) | |
7040 | { | |
7041 | if(!fDiffFlowCorrelationsPro[t][pe][rci]) | |
7042 | { | |
7043 | cout<<"WARNING: fDiffFlowCorrelationsPro[t][pe][rci] is NULL in AFAWQC::FRC() !!!!"<<endl; | |
7044 | cout<<"t = "<<t<<endl; | |
7045 | cout<<"pe = "<<pe<<endl; | |
7046 | cout<<"rci = "<<rci<<endl; | |
7047 | exit(0); | |
7048 | } | |
b40a910e | 7049 | if(!fDiffFlowSquaredCorrelationsPro[t][pe][rci]) |
7050 | { | |
7051 | cout<<"WARNING: fDiffFlowSquaredCorrelationsPro[t][pe][rci] is NULL in AFAWQC::FRC() !!!!"<<endl; | |
7052 | cout<<"t = "<<t<<endl; | |
7053 | cout<<"pe = "<<pe<<endl; | |
7054 | cout<<"rci = "<<rci<<endl; | |
7055 | exit(0); | |
7056 | } | |
489d5531 | 7057 | for(Int_t power=0;power<2;power++) |
7058 | { | |
7059 | if(!fDiffFlowSumOfEventWeights[t][pe][power][rci]) | |
7060 | { | |
7061 | cout<<"WARNING: fDiffFlowSumOfEventWeights[t][pe][power][rci] is NULL in AFAWQC::FRC() !!!!"<<endl; | |
7062 | cout<<"t = "<<t<<endl; | |
7063 | cout<<"pe = "<<pe<<endl; | |
7064 | cout<<"power = "<<power<<endl; | |
7065 | cout<<"rci = "<<rci<<endl; | |
7066 | exit(0); | |
7067 | } | |
7068 | } // end of for(Int_t power=0;power<2;power++) | |
7069 | } // end of for(Int_t rci=0;rci<4;rci++) | |
7070 | ||
7071 | // common: | |
b40a910e | 7072 | Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; |
489d5531 | 7073 | // transfer 1D profile into 1D histogram: |
7074 | Double_t correlation = 0.; | |
b40a910e | 7075 | Double_t squaredCorrelation = 0.; |
489d5531 | 7076 | Double_t spread = 0.; |
7077 | Double_t sumOfWeights = 0.; // sum of weights for particular reduced correlations for particular pt or eta bin | |
7078 | Double_t sumOfSquaredWeights = 0.; // sum of squared weights for particular reduced correlations for particular pt or eta bin | |
7079 | Double_t error = 0.; // error = termA * spread * termB | |
7080 | // termA = (sqrt(sumOfSquaredWeights)/sumOfWeights) | |
7081 | // termB = 1/pow(1-termA^2,0.5) | |
7082 | Double_t termA = 0.; | |
7083 | Double_t termB = 0.; | |
7084 | for(Int_t rci=0;rci<4;rci++) // index of reduced correlation | |
7085 | { | |
7086 | for(Int_t b=1;b<=nBinsPtEta[pe];b++) // number of pt or eta bins | |
7087 | { | |
b40a910e | 7088 | if(fDiffFlowCorrelationsPro[t][pe][rci]->GetBinEffectiveEntries(b) < 2 || |
7089 | fDiffFlowSquaredCorrelationsPro[t][pe][rci]->GetBinEffectiveEntries(b) < 2) | |
7090 | { | |
7091 | fDiffFlowCorrelationsPro[t][pe][rci]->SetBinError(b,0.); | |
7092 | fDiffFlowSquaredCorrelationsPro[t][pe][rci]->SetBinError(b,0.); | |
7093 | continue; // to be improved - should I ignore results in pt bins with one entry for reduced correlations or not? | |
7094 | } | |
489d5531 | 7095 | correlation = fDiffFlowCorrelationsPro[t][pe][rci]->GetBinContent(b); |
b40a910e | 7096 | squaredCorrelation = fDiffFlowSquaredCorrelationsPro[t][pe][rci]->GetBinContent(b); |
7097 | if(squaredCorrelation-correlation*correlation >= 0.) | |
7098 | { | |
7099 | spread = pow(squaredCorrelation-correlation*correlation,0.5); | |
7100 | } else | |
7101 | { | |
7102 | cout<<endl; | |
7103 | cout<<Form(" WARNING: Imaginary 'spread' for rci = %d, pe = %d, bin = %d !!!!",rci,pe,b)<<endl; | |
7104 | cout<<endl; | |
7105 | } | |
489d5531 | 7106 | sumOfWeights = fDiffFlowSumOfEventWeights[t][pe][0][rci]->GetBinContent(b); |
7107 | sumOfSquaredWeights = fDiffFlowSumOfEventWeights[t][pe][1][rci]->GetBinContent(b); | |
7108 | if(sumOfWeights) termA = (pow(sumOfSquaredWeights,0.5)/sumOfWeights); | |
7109 | if(1.-pow(termA,2.)>0.) termB = 1./pow(1.-pow(termA,2.),0.5); | |
7110 | error = termA*spread*termB; // final error (unbiased estimator for standard deviation) | |
7111 | fDiffFlowCorrelationsHist[t][pe][rci]->SetBinContent(b,correlation); | |
7112 | fDiffFlowCorrelationsHist[t][pe][rci]->SetBinError(b,error); | |
7113 | } // end of for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
7114 | } // end of for(Int_t rci=0;rci<4;rci++) | |
7115 | ||
7116 | } // end of void AliFlowAnalysisWithQCumulants::FinalizeReducedCorrelations(TString type, TString ptOrEta) | |
7117 | ||
7118 | ||
7119 | //================================================================================================================================ | |
7120 | ||
7121 | ||
7122 | void AliFlowAnalysisWithQCumulants::CalculateDiffFlowProductOfCorrelations(TString type, TString ptOrEta) | |
7123 | { | |
7124 | // store products: <2><2'>, <2><4'>, <2><6'>, <2><8'>, <2'><4>, | |
7125 | // <2'><4'>, <2'><6>, <2'><6'>, <2'><8>, <2'><8'>, | |
7126 | // <4><4'>, <4><6'>, <4><8'>, <4'><6>, <4'><6'>, | |
7127 | // <4'><8>, <4'><8'>, <6><6'>, <6><8'>, <6'><8>, | |
7128 | // <6'><8'>, <8><8'>. | |
7129 | ||
2a98ceb8 | 7130 | Int_t typeFlag = 0; |
7131 | Int_t ptEtaFlag = 0; | |
489d5531 | 7132 | |
7133 | if(type == "RP") | |
7134 | { | |
7135 | typeFlag = 0; | |
7136 | } else if(type == "POI") | |
7137 | { | |
7138 | typeFlag = 1; | |
7139 | } | |
7140 | ||
7141 | if(ptOrEta == "Pt") | |
7142 | { | |
7143 | ptEtaFlag = 0; | |
7144 | } else if(ptOrEta == "Eta") | |
7145 | { | |
7146 | ptEtaFlag = 1; | |
7147 | } | |
7148 | ||
7149 | // shortcuts: | |
7150 | Int_t t = typeFlag; | |
7151 | Int_t pe = ptEtaFlag; | |
7152 | ||
7153 | // common: | |
7154 | Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; | |
7155 | Double_t minPtEta[2] = {fPtMin,fEtaMin}; | |
7156 | Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; | |
7157 | ||
7158 | // protections // to be improved (add protection for all pointers in this method) | |
7159 | if(!fIntFlowCorrelationsEBE) | |
7160 | { | |
7161 | cout<<"WARNING: fIntFlowCorrelationsEBE is NULL in AFAWQC::CDFPOC() !!!!"<<endl; | |
7162 | exit(0); | |
7163 | } | |
7164 | ||
7165 | /* | |
7166 | Double_t dMult = (*fSMpk)(0,0); // multiplicity (number of particles used to determine the reaction plane) | |
7167 | //Double_t mr = 0.; // number of RPs in particular pt or eta bin | |
7168 | Double_t mp = 0.; // number of POIs in particular pt or eta bin | |
7169 | Double_t mq = 0.; // number of particles which are both RPs and POIs in particular pt or eta bin | |
7170 | */ | |
7171 | ||
7172 | // e-b-e correlations: | |
7173 | Double_t twoEBE = fIntFlowCorrelationsEBE->GetBinContent(1); // <2> | |
7174 | Double_t fourEBE = fIntFlowCorrelationsEBE->GetBinContent(2); // <4> | |
7175 | Double_t sixEBE = fIntFlowCorrelationsEBE->GetBinContent(3); // <6> | |
7176 | Double_t eightEBE = fIntFlowCorrelationsEBE->GetBinContent(4); // <8> | |
7177 | ||
7178 | // event weights for correlations: | |
7179 | Double_t dW2 = fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(1); // event weight for <2> | |
7180 | Double_t dW4 = fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(2); // event weight for <4> | |
7181 | Double_t dW6 = fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(3); // event weight for <6> | |
7182 | Double_t dW8 = fIntFlowEventWeightsForCorrelationsEBE->GetBinContent(4); // event weight for <8> | |
7183 | ||
7184 | // e-b-e reduced correlations: | |
7185 | Double_t twoReducedEBE = 0.; // <2'> | |
7186 | Double_t fourReducedEBE = 0.; // <4'> | |
7187 | Double_t sixReducedEBE = 0.; // <6'> | |
7188 | Double_t eightReducedEBE = 0.; // <8'> | |
7189 | ||
7190 | // event weights for reduced correlations: | |
7191 | Double_t dw2 = 0.; // event weight for <2'> | |
7192 | Double_t dw4 = 0.; // event weight for <4'> | |
7193 | //Double_t dw6 = 0.; // event weight for <6'> | |
7194 | //Double_t dw8 = 0.; // event weight for <8'> | |
7195 | ||
7196 | // looping over bins: | |
7197 | for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
7198 | { | |
7199 | // e-b-e reduced correlations: | |
7200 | twoReducedEBE = fDiffFlowCorrelationsEBE[t][pe][0]->GetBinContent(b); | |
7201 | fourReducedEBE = fDiffFlowCorrelationsEBE[t][pe][1]->GetBinContent(b); | |
7202 | sixReducedEBE = fDiffFlowCorrelationsEBE[t][pe][2]->GetBinContent(b); | |
7203 | eightReducedEBE = fDiffFlowCorrelationsEBE[t][pe][3]->GetBinContent(b); | |
7204 | ||
7205 | /* | |
7206 | // to be improved (I should not do this here again) | |
7207 | if(type == "RP") | |
7208 | { | |
7209 | mq = fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(b); | |
7210 | mp = mq; // trick to use the very same Eqs. bellow both for RP's and POI's diff. flow | |
7211 | } else if(type == "POI") | |
7212 | { | |
7213 | mp = fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(b); | |
7214 | mq = fReRPQ1dEBE[2][pe][0][0]->GetBinEntries(b); | |
7215 | } | |
7216 | ||
7217 | // event weights for reduced correlations: | |
7218 | dw2 = mp*dMult-mq; // weight for <2'> | |
7219 | dw4 = (mp-mq)*dMult*(dMult-1.)*(dMult-2.) | |
7220 | + mq*(dMult-1.)*(dMult-2.)*(dMult-3.); // weight for <4'> | |
7221 | //dw6 = ... | |
7222 | //dw8 = ... | |
7223 | ||
7224 | */ | |
7225 | ||
7226 | dw2 = fDiffFlowEventWeightsForCorrelationsEBE[t][pe][0]->GetBinContent(b); | |
7227 | dw4 = fDiffFlowEventWeightsForCorrelationsEBE[t][pe][1]->GetBinContent(b); | |
7228 | ||
7229 | // storing all products: | |
7230 | fDiffFlowProductOfCorrelationsPro[t][pe][0][1]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],twoEBE*twoReducedEBE,dW2*dw2); // storing <2><2'> | |
7231 | fDiffFlowProductOfCorrelationsPro[t][pe][1][2]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],fourEBE*twoReducedEBE,dW4*dw2); // storing <4><2'> | |
7232 | fDiffFlowProductOfCorrelationsPro[t][pe][1][4]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sixEBE*twoReducedEBE,dW6*dw2); // storing <6><2'> | |
7233 | fDiffFlowProductOfCorrelationsPro[t][pe][1][6]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],eightEBE*twoReducedEBE,dW8*dw2); // storing <8><2'> | |
7234 | ||
7235 | // event weight for <4'>: | |
7236 | fDiffFlowProductOfCorrelationsPro[t][pe][0][3]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],twoEBE*fourReducedEBE,dW2*dw4); // storing <2><4'> | |
7237 | fDiffFlowProductOfCorrelationsPro[t][pe][1][3]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],twoReducedEBE*fourReducedEBE,dw2*dw4); // storing <2'><4'> | |
7238 | fDiffFlowProductOfCorrelationsPro[t][pe][2][3]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],fourEBE*fourReducedEBE,dW4*dw4); // storing <4><4'> | |
7239 | fDiffFlowProductOfCorrelationsPro[t][pe][3][4]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sixEBE*fourReducedEBE,dW6*dw4); // storing <6><4'> | |
7240 | fDiffFlowProductOfCorrelationsPro[t][pe][3][6]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],eightEBE*fourReducedEBE,dW8*dw4); // storing <8><4'> | |
7241 | ||
7242 | // event weight for <6'>: | |
7243 | //dw6 = ...; | |
7244 | //fDiffFlowProductOfCorrelationsPro[t][pe][0][5]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],twoEBE*sixReducedEBE,dW2*dw6); // storing <2><6'> | |
7245 | //fDiffFlowProductOfCorrelationsPro[t][pe][1][5]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],twoReducedEBE*sixReducedEBE,dw2*dw6); // storing <2'><6'> | |
7246 | //fDiffFlowProductOfCorrelationsPro[t][pe][2][5]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],fourEBE*sixReducedEBE,dW4*dw6); // storing <4><6'> | |
7247 | //fDiffFlowProductOfCorrelationsPro[t][pe][3][5]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],fourReducedEBE*sixReducedEBE,dw4*dw6); // storing <4'><6'> | |
7248 | //fDiffFlowProductOfCorrelationsPro[t][pe][4][5]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sixEBE*sixReducedEBE,dW6*dw6); // storing <6><6'> | |
7249 | //fDiffFlowProductOfCorrelationsPro[t][pe][5][6]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sixReducedEBE*eightEBE,dw6*dW8); // storing <6'><8> | |
7250 | //fDiffFlowProductOfCorrelationsPro[t][pe][5][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sixReducedEBE*eightReducedEBE,dw6*dw8); // storing <6'><8'> | |
7251 | ||
7252 | // event weight for <8'>: | |
7253 | //dw8 = ...; | |
7254 | //fDiffFlowProductOfCorrelationsPro[t][pe][0][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],twoEBE*eightReducedEBE,dW2*dw8); // storing <2><8'> | |
7255 | //fDiffFlowProductOfCorrelationsPro[t][pe][1][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],twoReducedEBE*eightReducedEBE,dw2*dw8); // storing <2'><8'> | |
7256 | //fDiffFlowProductOfCorrelationsPro[t][pe][2][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],fourEBE*eightReducedEBE,dW4*dw8); // storing <4><8'> | |
7257 | //fDiffFlowProductOfCorrelationsPro[t][pe][3][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],fourReducedEBE*eightReducedEBE,dw4*dw8); // storing <4'><8'> | |
7258 | //fDiffFlowProductOfCorrelationsPro[t][pe][4][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sixEBE*eightReducedEBE,dW6*dw8); // storing <6><8'> | |
7259 | //fDiffFlowProductOfCorrelationsPro[t][pe][5][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sixReducedEBE*eightReducedEBE,dw6*dw8); // storing <6'><8'> | |
7260 | //fDiffFlowProductOfCorrelationsPro[t][pe][6][7]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],eightEBE*eightReducedEBE,dW8*dw8); // storing <8><8'> | |
7261 | } // end of for(Int_t b=1;b<=nBinsPtEta[pe];b++ | |
7262 | ||
7263 | } // end of void AliFlowAnalysisWithQCumulants::CalculateDiffFlowProductOfCorrelations(TString type, TString ptOrEta) | |
7264 | ||
7265 | ||
7266 | //================================================================================================================================ | |
7267 | ||
7268 | ||
7269 | void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCovariances(TString type, TString ptOrEta) // to be improved (reimplemented) | |
7270 | { | |
7271 | // a) Calculate unbiased estimators Cov(<2>,<2'>), Cov(<2>,<4'>), Cov(<4>,<2'>), Cov(<4>,<4'>) and Cov(<2'>,<4'>) | |
7272 | // for covariances V(<2>,<2'>), V(<2>,<4'>), V(<4>,<2'>), V(<4>,<4'>) and V(<2'>,<4'>). | |
7273 | // b) Store in histogram fDiffFlowCovariances[t][pe][index] for instance the following: | |
7274 | // | |
7275 | // Cov(<2>,<2'>) * (sum_{i=1}^{N} w_{<2>}_i w_{<2'>}_i )/[(sum_{i=1}^{N} w_{<2>}_i) * (sum_{j=1}^{N} w_{<2'>}_j)] | |
7276 | // | |
7277 | // where N is the number of events, w_{<2>} is event weight for <2> and w_{<2'>} is event weight for <2'>. | |
7278 | // c) Binning of fDiffFlowCovariances[t][pe][index] is organized as follows: | |
7279 | // | |
7280 | // 1st bin: Cov(<2>,<2'>) * (sum_{i=1}^{N} w_{<2>}_i w_{<2'>}_i )/[(sum_{i=1}^{N} w_{<2>}_i) * (sum_{j=1}^{N} w_{<2'>}_j)] | |
7281 | // 2nd bin: Cov(<2>,<4'>) * (sum_{i=1}^{N} w_{<2>}_i w_{<4'>}_i )/[(sum_{i=1}^{N} w_{<2>}_i) * (sum_{j=1}^{N} w_{<4'>}_j)] | |
7282 | // 3rd bin: Cov(<4>,<2'>) * (sum_{i=1}^{N} w_{<4>}_i w_{<2'>}_i )/[(sum_{i=1}^{N} w_{<4>}_i) * (sum_{j=1}^{N} w_{<2'>}_j)] | |
7283 | // 4th bin: Cov(<4>,<4'>) * (sum_{i=1}^{N} w_{<4>}_i w_{<4'>}_i )/[(sum_{i=1}^{N} w_{<4>}_i) * (sum_{j=1}^{N} w_{<4'>}_j)] | |
7284 | // 5th bin: Cov(<2'>,<4'>) * (sum_{i=1}^{N} w_{<2'>}_i w_{<4'>}_i )/[(sum_{i=1}^{N} w_{<2'>}_i) * (sum_{j=1}^{N} w_{<4'>}_j)] | |
7285 | // ... | |
7286 | ||
2a98ceb8 | 7287 | Int_t typeFlag = 0; |
7288 | Int_t ptEtaFlag = 0; | |
489d5531 | 7289 | |
7290 | if(type == "RP") | |
7291 | { | |
7292 | typeFlag = 0; | |
7293 | } else if(type == "POI") | |
7294 | { | |
7295 | typeFlag = 1; | |
7296 | } | |
7297 | ||
7298 | if(ptOrEta == "Pt") | |
7299 | { | |
7300 | ptEtaFlag = 0; | |
7301 | } else if(ptOrEta == "Eta") | |
7302 | { | |
7303 | ptEtaFlag = 1; | |
7304 | } | |
7305 | ||
7306 | // shortcuts: | |
7307 | Int_t t = typeFlag; | |
7308 | Int_t pe = ptEtaFlag; | |
7309 | ||
7310 | // common: | |
7311 | Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; | |
7312 | //Double_t minPtEta[2] = {fPtMin,fEtaMin}; | |
7313 | //Double_t maxPtEta[2] = {fPtMax,fEtaMax}; | |
7314 | //Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; | |
7315 | ||
7316 | // average correlations: | |
7317 | Double_t two = fIntFlowCorrelationsHist->GetBinContent(1); // <<2>> | |
7318 | Double_t four = fIntFlowCorrelationsHist->GetBinContent(2); // <<4>> | |
7319 | //Double_t six = fIntFlowCorrelationsHist->GetBinContent(3); // <<6>> | |
7320 | //Double_t eight = fIntFlowCorrelationsHist->GetBinContent(4); // <<8>> | |
7321 | ||
7322 | // sum of weights for correlation: | |
7323 | Double_t sumOfWeightsForTwo = fIntFlowSumOfEventWeights[0]->GetBinContent(1); // sum_{i=1}^{N} w_{<2>} | |
7324 | Double_t sumOfWeightsForFour = fIntFlowSumOfEventWeights[0]->GetBinContent(2); // sum_{i=1}^{N} w_{<4>} | |
7325 | //Double_t sumOfWeightsForSix = fIntFlowSumOfEventWeights[0]->GetBinContent(3); // sum_{i=1}^{N} w_{<6>} | |
7326 | //Double_t sumOfWeightsForEight = fIntFlowSumOfEventWeights[0]->GetBinContent(4); // sum_{i=1}^{N} w_{<8>} | |
7327 | ||
7328 | // average reduced correlations: | |
7329 | Double_t twoReduced = 0.; // <<2'>> | |
7330 | Double_t fourReduced = 0.; // <<4'>> | |
7331 | //Double_t sixReduced = 0.; // <<6'>> | |
7332 | //Double_t eightReduced = 0.; // <<8'>> | |
7333 | ||
7334 | // sum of weights for reduced correlation: | |
7335 | Double_t sumOfWeightsForTwoReduced = 0.; // sum_{i=1}^{N} w_{<2'>} | |
7336 | Double_t sumOfWeightsForFourReduced = 0.; // sum_{i=1}^{N} w_{<4'>} | |
7337 | //Double_t sumOfWeightsForSixReduced = 0.; // sum_{i=1}^{N} w_{<6'>} | |
7338 | //Double_t sumOfWeightsForEightReduced = 0.; // sum_{i=1}^{N} w_{<8'>} | |
7339 | ||
7340 | // product of weights for reduced correlation: | |
7341 | Double_t productOfWeightsForTwoTwoReduced = 0.; // sum_{i=1}^{N} w_{<2>}w_{<2'>} | |
7342 | Double_t productOfWeightsForTwoFourReduced = 0.; // sum_{i=1}^{N} w_{<2>}w_{<4'>} | |
7343 | Double_t productOfWeightsForFourTwoReduced = 0.; // sum_{i=1}^{N} w_{<4>}w_{<2'>} | |
7344 | Double_t productOfWeightsForFourFourReduced = 0.; // sum_{i=1}^{N} w_{<4>}w_{<4'>} | |
7345 | Double_t productOfWeightsForTwoReducedFourReduced = 0.; // sum_{i=1}^{N} w_{<2'>}w_{<4'>} | |
7346 | // ... | |
7347 | ||
7348 | // products for differential flow: | |
7349 | Double_t twoTwoReduced = 0; // <<2><2'>> | |
7350 | Double_t twoFourReduced = 0; // <<2><4'>> | |
7351 | Double_t fourTwoReduced = 0; // <<4><2'>> | |
7352 | Double_t fourFourReduced = 0; // <<4><4'>> | |
7353 | Double_t twoReducedFourReduced = 0; // <<2'><4'>> | |
7354 | ||
7355 | // denominators in the expressions for the unbiased estimators for covariances: | |
7356 | // denominator = 1 - term1/(term2*term3) | |
7357 | // prefactor = term1/(term2*term3) | |
7358 | Double_t denominator = 0.; | |
7359 | Double_t prefactor = 0.; | |
7360 | Double_t term1 = 0.; | |
7361 | Double_t term2 = 0.; | |
7362 | Double_t term3 = 0.; | |
7363 | ||
7364 | // unbiased estimators for covariances for differential flow: | |
7365 | Double_t covTwoTwoReduced = 0.; // Cov(<2>,<2'>) | |
7366 | Double_t wCovTwoTwoReduced = 0.; // Cov(<2>,<2'>) * prefactor(w_{<2>},w_{<2'>}) | |
7367 | Double_t covTwoFourReduced = 0.; // Cov(<2>,<4'>) | |
7368 | Double_t wCovTwoFourReduced = 0.; // Cov(<2>,<4'>) * prefactor(w_{<2>},w_{<4'>}) | |
7369 | Double_t covFourTwoReduced = 0.; // Cov(<4>,<2'>) | |
7370 | Double_t wCovFourTwoReduced = 0.; // Cov(<4>,<2'>) * prefactor(w_{<4>},w_{<2'>}) | |
7371 | Double_t covFourFourReduced = 0.; // Cov(<4>,<4'>) | |
7372 | Double_t wCovFourFourReduced = 0.; // Cov(<4>,<4'>) * prefactor(w_{<4>},w_{<4'>}) | |
7373 | Double_t covTwoReducedFourReduced = 0.; // Cov(<2'>,<4'>) | |
7374 | Double_t wCovTwoReducedFourReduced = 0.; // Cov(<2'>,<4'>) * prefactor(w_{<2'>},w_{<4'>}) | |
7375 | ||
7376 | for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
7377 | { | |
7378 | // average reduced corelations: | |
7379 | twoReduced = fDiffFlowCorrelationsHist[t][pe][0]->GetBinContent(b); | |
7380 | fourReduced = fDiffFlowCorrelationsHist[t][pe][1]->GetBinContent(b); | |
7381 | // average products: | |
7382 | twoTwoReduced = fDiffFlowProductOfCorrelationsPro[t][pe][0][1]->GetBinContent(b); | |
7383 | twoFourReduced = fDiffFlowProductOfCorrelationsPro[t][pe][0][3]->GetBinContent(b); | |
7384 | fourTwoReduced = fDiffFlowProductOfCorrelationsPro[t][pe][1][2]->GetBinContent(b); | |
7385 | fourFourReduced = fDiffFlowProductOfCorrelationsPro[t][pe][2][3]->GetBinContent(b); | |
7386 | twoReducedFourReduced = fDiffFlowProductOfCorrelationsPro[t][pe][1][3]->GetBinContent(b); | |
7387 | // sum of weights for reduced correlations: | |
7388 | sumOfWeightsForTwoReduced = fDiffFlowSumOfEventWeights[t][pe][0][0]->GetBinContent(b); | |
7389 | sumOfWeightsForFourReduced = fDiffFlowSumOfEventWeights[t][pe][0][1]->GetBinContent(b); | |
7390 | // products of weights for correlations: | |
7391 | productOfWeightsForTwoTwoReduced = fDiffFlowSumOfProductOfEventWeights[t][pe][0][1]->GetBinContent(b); | |
7392 | productOfWeightsForTwoFourReduced = fDiffFlowSumOfProductOfEventWeights[t][pe][0][3]->GetBinContent(b); | |
7393 | productOfWeightsForFourTwoReduced = fDiffFlowSumOfProductOfEventWeights[t][pe][1][2]->GetBinContent(b); | |
7394 | productOfWeightsForFourFourReduced = fDiffFlowSumOfProductOfEventWeights[t][pe][2][3]->GetBinContent(b); | |
7395 | productOfWeightsForTwoReducedFourReduced = fDiffFlowSumOfProductOfEventWeights[t][pe][1][3]->GetBinContent(b); | |
7396 | // denominator for the unbiased estimator for covariances: 1 - term1/(term2*term3) | |
7397 | // prefactor (multiplies Cov's) = term1/(term2*term3) | |
7398 | // <2>,<2'>: | |
7399 | term1 = productOfWeightsForTwoTwoReduced; | |
7400 | term2 = sumOfWeightsForTwo; | |
7401 | term3 = sumOfWeightsForTwoReduced; | |
7402 | if(term2*term3>0.) | |
7403 | { | |
7404 | denominator = 1.-term1/(term2*term3); | |
7405 | prefactor = term1/(term2*term3); | |
0328db2d | 7406 | if(TMath::Abs(denominator)>1e-6) |
489d5531 | 7407 | { |
7408 | covTwoTwoReduced = (twoTwoReduced-two*twoReduced)/denominator; | |
7409 | wCovTwoTwoReduced = covTwoTwoReduced*prefactor; | |
7410 | fDiffFlowCovariances[t][pe][0]->SetBinContent(b,wCovTwoTwoReduced); | |
7411 | } | |
7412 | } | |
7413 | // <2>,<4'>: | |
7414 | term1 = productOfWeightsForTwoFourReduced; | |
7415 | term2 = sumOfWeightsForTwo; | |
7416 | term3 = sumOfWeightsForFourReduced; | |
7417 | if(term2*term3>0.) | |
7418 | { | |
7419 | denominator = 1.-term1/(term2*term3); | |
7420 | prefactor = term1/(term2*term3); | |
0328db2d | 7421 | if(TMath::Abs(denominator)>1e-6) |
489d5531 | 7422 | { |
7423 | covTwoFourReduced = (twoFourReduced-two*fourReduced)/denominator; | |
7424 | wCovTwoFourReduced = covTwoFourReduced*prefactor; | |
7425 | fDiffFlowCovariances[t][pe][1]->SetBinContent(b,wCovTwoFourReduced); | |
7426 | } | |
7427 | } | |
7428 | // <4>,<2'>: | |
7429 | term1 = productOfWeightsForFourTwoReduced; | |
7430 | term2 = sumOfWeightsForFour; | |
7431 | term3 = sumOfWeightsForTwoReduced; | |
7432 | if(term2*term3>0.) | |
7433 | { | |
7434 | denominator = 1.-term1/(term2*term3); | |
7435 | prefactor = term1/(term2*term3); | |
0328db2d | 7436 | if(TMath::Abs(denominator)>1e-6) |
489d5531 | 7437 | { |
7438 | covFourTwoReduced = (fourTwoReduced-four*twoReduced)/denominator; | |
7439 | wCovFourTwoReduced = covFourTwoReduced*prefactor; | |
7440 | fDiffFlowCovariances[t][pe][2]->SetBinContent(b,wCovFourTwoReduced); | |
7441 | } | |
7442 | } | |
7443 | // <4>,<4'>: | |
7444 | term1 = productOfWeightsForFourFourReduced; | |
7445 | term2 = sumOfWeightsForFour; | |
7446 | term3 = sumOfWeightsForFourReduced; | |
7447 | if(term2*term3>0.) | |
7448 | { | |
7449 | denominator = 1.-term1/(term2*term3); | |
7450 | prefactor = term1/(term2*term3); | |
0328db2d | 7451 | if(TMath::Abs(denominator)>1e-6) |
489d5531 | 7452 | { |
7453 | covFourFourReduced = (fourFourReduced-four*fourReduced)/denominator; | |
7454 | wCovFourFourReduced = covFourFourReduced*prefactor; | |
7455 | fDiffFlowCovariances[t][pe][3]->SetBinContent(b,wCovFourFourReduced); | |
7456 | } | |
7457 | } | |
7458 | // <2'>,<4'>: | |
7459 | term1 = productOfWeightsForTwoReducedFourReduced; | |
7460 | term2 = sumOfWeightsForTwoReduced; | |
7461 | term3 = sumOfWeightsForFourReduced; | |
7462 | if(term2*term3>0.) | |
7463 | { | |
7464 | denominator = 1.-term1/(term2*term3); | |
7465 | prefactor = term1/(term2*term3); | |
0328db2d | 7466 | if(TMath::Abs(denominator)>1e-6) |
489d5531 | 7467 | { |
7468 | covTwoReducedFourReduced = (twoReducedFourReduced-twoReduced*fourReduced)/denominator; | |
7469 | wCovTwoReducedFourReduced = covTwoReducedFourReduced*prefactor; | |
7470 | fDiffFlowCovariances[t][pe][4]->SetBinContent(b,wCovTwoReducedFourReduced); | |
7471 | } | |
7472 | } | |
7473 | } // end of for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
7474 | ||
7475 | } // end of void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCovariances(TString type, TString ptOrEta) | |
7476 | ||
7477 | ||
7478 | //================================================================================================================================ | |
7479 | ||
7480 | ||
7481 | void AliFlowAnalysisWithQCumulants::CalculateDiffFlow(TString type, TString ptOrEta) | |
7482 | { | |
7483 | // calculate differential flow from differential cumulants and previously obtained integrated flow: (to be improved: description) | |
7484 | ||
2a98ceb8 | 7485 | Int_t typeFlag = 0; |
7486 | Int_t ptEtaFlag = 0; | |
489d5531 | 7487 | |
7488 | if(type == "RP") | |
7489 | { | |
7490 | typeFlag = 0; | |
7491 | } else if(type == "POI") | |
7492 | { | |
7493 | typeFlag = 1; | |
7494 | } | |
7495 | ||
7496 | if(ptOrEta == "Pt") | |
7497 | { | |
7498 | ptEtaFlag = 0; | |
7499 | } else if(ptOrEta == "Eta") | |
7500 | { | |
7501 | ptEtaFlag = 1; | |
7502 | } | |
7503 | ||
7504 | // shortcuts: | |
7505 | Int_t t = typeFlag; | |
7506 | Int_t pe = ptEtaFlag; | |
7507 | ||
7508 | // common: | |
7509 | Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; | |
7510 | ||
7511 | // correlations: | |
7512 | Double_t two = fIntFlowCorrelationsHist->GetBinContent(1); // <<2>> | |
7513 | Double_t four = fIntFlowCorrelationsHist->GetBinContent(2); // <<4>> | |
7514 | ||
7515 | // statistical errors of correlations: | |
7516 | Double_t twoError = fIntFlowCorrelationsHist->GetBinError(1); | |
7517 | Double_t fourError = fIntFlowCorrelationsHist->GetBinError(2); | |
7518 | ||
7519 | // reduced correlations: | |
7520 | Double_t twoReduced = 0.; // <<2'>> | |
7521 | Double_t fourReduced = 0.; // <<4'>> | |
7522 | ||
7523 | // statistical errors of reduced correlations: | |
7524 | Double_t twoReducedError = 0.; | |
7525 | Double_t fourReducedError = 0.; | |
7526 | ||
7527 | // covariances: | |
8e1cefdd | 7528 | Double_t wCovTwoFour = 0.; // Cov(<2>,<4>) * prefactor(<2>,<4>) |
7529 | if(!fForgetAboutCovariances) | |
7530 | { | |
7531 | wCovTwoFour = fIntFlowCovariances->GetBinContent(1); // Cov(<2>,<4>) * prefactor(<2>,<4>) | |
7532 | } | |
489d5531 | 7533 | Double_t wCovTwoTwoReduced = 0.; // Cov(<2>,<2'>) * prefactor(<2>,<2'>) |
7534 | Double_t wCovTwoFourReduced = 0.; // Cov(<2>,<4'>) * prefactor(<2>,<4'>) | |
7535 | Double_t wCovFourTwoReduced = 0.; // Cov(<4>,<2'>) * prefactor(<4>,<2'>) | |
7536 | Double_t wCovFourFourReduced = 0.; // Cov(<4>,<4'>) * prefactor(<4>,<4'>) | |
7537 | Double_t wCovTwoReducedFourReduced = 0.; // Cov(<2'>,<4'>) * prefactor(<2'>,<4'>) | |
7538 | ||
7539 | // differential flow: | |
7540 | Double_t v2Prime = 0.; // v'{2} | |
7541 | Double_t v4Prime = 0.; // v'{4} | |
7542 | ||
7543 | // statistical error of differential flow: | |
7544 | Double_t v2PrimeError = 0.; | |
7545 | Double_t v4PrimeError = 0.; | |
7546 | ||
7547 | // squared statistical error of differential flow: | |
7548 | Double_t v2PrimeErrorSquared = 0.; | |
7549 | Double_t v4PrimeErrorSquared = 0.; | |
7550 | ||
7551 | // loop over pt or eta bins: | |
7552 | for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
7553 | { | |
7554 | // reduced correlations and statistical errors: | |
7555 | twoReduced = fDiffFlowCorrelationsHist[t][pe][0]->GetBinContent(b); | |
7556 | twoReducedError = fDiffFlowCorrelationsHist[t][pe][0]->GetBinError(b); | |
7557 | fourReduced = fDiffFlowCorrelationsHist[t][pe][1]->GetBinContent(b); | |
7558 | fourReducedError = fDiffFlowCorrelationsHist[t][pe][1]->GetBinError(b); | |
7559 | // covariances: | |
8e1cefdd | 7560 | if(!fForgetAboutCovariances) |
7561 | { | |
7562 | wCovTwoTwoReduced = fDiffFlowCovariances[t][pe][0]->GetBinContent(b); | |
7563 | wCovTwoFourReduced = fDiffFlowCovariances[t][pe][1]->GetBinContent(b); | |
7564 | wCovFourTwoReduced = fDiffFlowCovariances[t][pe][2]->GetBinContent(b); | |
7565 | wCovFourFourReduced = fDiffFlowCovariances[t][pe][3]->GetBinContent(b); | |
7566 | wCovTwoReducedFourReduced = fDiffFlowCovariances[t][pe][4]->GetBinContent(b); | |
7567 | } | |
489d5531 | 7568 | // differential flow: |
7569 | // v'{2}: | |
7570 | if(two>0.) | |
7571 | { | |
7572 | v2Prime = twoReduced/pow(two,0.5); | |
7573 | v2PrimeErrorSquared = (1./4.)*pow(two,-3.)* | |
7574 | (pow(twoReduced,2.)*pow(twoError,2.) | |
7575 | + 4.*pow(two,2.)*pow(twoReducedError,2.) | |
7576 | - 4.*two*twoReduced*wCovTwoTwoReduced); | |
7577 | ||
7578 | ||
7579 | if(v2PrimeErrorSquared>0.) v2PrimeError = pow(v2PrimeErrorSquared,0.5); | |
7580 | fDiffFlow[t][pe][0]->SetBinContent(b,v2Prime); | |
60694576 | 7581 | if(TMath::Abs(v2Prime)>1.e-44)fDiffFlow[t][pe][0]->SetBinError(b,v2PrimeError); |
489d5531 | 7582 | } |
7583 | // differential flow: | |
7584 | // v'{4} | |
7585 | if(2.*pow(two,2.)-four > 0.) | |
7586 | { | |
7587 | v4Prime = (2.*two*twoReduced-fourReduced)/pow(2.*pow(two,2.)-four,3./4.); | |
7588 | v4PrimeErrorSquared = pow(2.*pow(two,2.)-four,-7./2.)* | |
7589 | (pow(2.*pow(two,2.)*twoReduced-3.*two*fourReduced+2.*four*twoReduced,2.)*pow(twoError,2.) | |
7590 | + (9./16.)*pow(2.*two*twoReduced-fourReduced,2.)*pow(fourError,2.) | |
7591 | + 4.*pow(two,2.)*pow(2.*pow(two,2.)-four,2.)*pow(twoReducedError,2.) | |
7592 | + pow(2.*pow(two,2.)-four,2.)*pow(fourReducedError,2.) | |
7593 | - (3./2.)*(2.*two*twoReduced-fourReduced) | |
7594 | * (2.*pow(two,2.)*twoReduced-3.*two*fourReduced+2.*four*twoReduced)*wCovTwoFour | |
7595 | - 4.*two*(2.*pow(two,2.)-four) | |
7596 | * (2.*pow(two,2.)*twoReduced-3.*two*fourReduced+2.*four*twoReduced)*wCovTwoTwoReduced | |
7597 | + 2.*(2.*pow(two,2.)-four) | |
7598 | * (2.*pow(two,2.)*twoReduced-3.*two*fourReduced+2.*four*twoReduced)*wCovTwoFourReduced | |
7599 | + 3.*two*(2.*pow(two,2.)-four)*(2.*two*twoReduced-fourReduced)*wCovFourTwoReduced | |
7600 | - (3./2.)*(2.*pow(two,2.)-four)*(2.*two*twoReduced-fourReduced)*wCovFourFourReduced | |
7601 | - 4.*two*pow(2.*pow(two,2.)-four,2.)*wCovTwoReducedFourReduced); | |
7602 | if(v4PrimeErrorSquared>0.) v4PrimeError = pow(v4PrimeErrorSquared,0.5); | |
7603 | fDiffFlow[t][pe][1]->SetBinContent(b,v4Prime); | |
60694576 | 7604 | if(TMath::Abs(v4Prime)>1.e-44)fDiffFlow[t][pe][1]->SetBinError(b,v4PrimeError); |
489d5531 | 7605 | } |
7606 | ||
7607 | } // end of for(Int_t b=1;b<=fnBinsPtEta[pe];b++) | |
7608 | ||
7609 | ||
7610 | ||
7611 | ||
7612 | /* | |
7613 | // 2D: | |
7614 | for(Int_t nua=0;nua<2;nua++) | |
7615 | { | |
7616 | for(Int_t p=1;p<=fnBinsPt;p++) | |
7617 | { | |
7618 | for(Int_t e=1;e<=fnBinsEta;e++) | |
7619 | { | |
7620 | // differential cumulants: | |
7621 | Double_t qc2Prime = fFinalCumulants2D[t][pW][eW][nua][0]->GetBinContent(fFinalCumulants2D[t][pW][eW][nua][0]->GetBin(p,e)); // QC{2'} | |
7622 | Double_t qc4Prime = fFinalCumulants2D[t][pW][eW][nua][1]->GetBinContent(fFinalCumulants2D[t][pW][eW][nua][1]->GetBin(p,e)); // QC{4'} | |
7623 | // differential flow: | |
7624 | Double_t v2Prime = 0.; | |
7625 | Double_t v4Prime = 0.; | |
7626 | if(v2) | |
7627 | { | |
7628 | v2Prime = qc2Prime/v2; | |
7629 | fFinalFlow2D[t][pW][eW][nua][0]->SetBinContent(fFinalFlow2D[t][pW][eW][nua][0]->GetBin(p,e),v2Prime); | |
7630 | } | |
7631 | if(v4) | |
7632 | { | |
7633 | v4Prime = -qc4Prime/pow(v4,3.); | |
7634 | fFinalFlow2D[t][pW][eW][nua][1]->SetBinContent(fFinalFlow2D[t][pW][eW][nua][1]->GetBin(p,e),v4Prime); | |
7635 | } | |
7636 | } // end of for(Int_t e=1;e<=fnBinsEta;e++) | |
7637 | } // end of for(Int_t p=1;p<=fnBinsPt;p++) | |
7638 | } // end of for(Int_t nua=0;nua<2;nua++) | |
7639 | */ | |
7640 | ||
7641 | } // end of AliFlowAnalysisWithQCumulants::CalculateDiffFlow(TString type, Bool_t useParticleWeights) | |
7642 | ||
489d5531 | 7643 | //================================================================================================================================ |
7644 | ||
489d5531 | 7645 | void AliFlowAnalysisWithQCumulants::StoreIntFlowFlags() |
7646 | { | |
7647 | // a) Store all flags for integrated flow in profile fIntFlowFlags. | |
7648 | ||
7649 | if(!fIntFlowFlags) | |
7650 | { | |
7651 | cout<<"WARNING: fIntFlowFlags is NULL in AFAWQC::SFFIF() !!!!"<<endl; | |
7652 | exit(0); | |
7653 | } | |
7654 | ||
7655 | // particle weights used or not: | |
7656 | fIntFlowFlags->Fill(0.5,(Int_t)fUsePhiWeights||fUsePtWeights||fUseEtaWeights); | |
7657 | // which event weights were used: | |
7658 | if(strcmp(fMultiplicityWeight->Data(),"combinations")) | |
7659 | { | |
7660 | fIntFlowFlags->Fill(1.5,0); // 0 = "combinations" (default) | |
7661 | } else if(strcmp(fMultiplicityWeight->Data(),"unit")) | |
7662 | { | |
7663 | fIntFlowFlags->Fill(1.5,1); // 1 = "unit" | |
7664 | } else if(strcmp(fMultiplicityWeight->Data(),"multiplicity")) | |
7665 | { | |
7666 | fIntFlowFlags->Fill(1.5,2); // 2 = "multiplicity" | |
7667 | } | |
489d5531 | 7668 | fIntFlowFlags->Fill(2.5,(Int_t)fApplyCorrectionForNUA); |
7669 | fIntFlowFlags->Fill(3.5,(Int_t)fPrintFinalResults[0]); | |
7670 | fIntFlowFlags->Fill(4.5,(Int_t)fPrintFinalResults[1]); | |
7671 | fIntFlowFlags->Fill(5.5,(Int_t)fPrintFinalResults[2]); | |
b3dacf6b | 7672 | fIntFlowFlags->Fill(6.5,(Int_t)fPrintFinalResults[3]); |
7673 | fIntFlowFlags->Fill(7.5,(Int_t)fApplyCorrectionForNUAVsM); | |
b77b6434 | 7674 | fIntFlowFlags->Fill(8.5,(Int_t)fPropagateErrorAlsoFromNIT); |
b3dacf6b | 7675 | fIntFlowFlags->Fill(9.5,(Int_t)fCalculateCumulantsVsM); |
0dd3b008 | 7676 | fIntFlowFlags->Fill(10.5,(Int_t)fMinimumBiasReferenceFlow); |
8e1cefdd | 7677 | fIntFlowFlags->Fill(11.5,(Int_t)fForgetAboutCovariances); |
e5834fcb | 7678 | fIntFlowFlags->Fill(12.5,(Int_t)fStorePhiDistributionForOneEvent); |
dd442cd2 | 7679 | fIntFlowFlags->Fill(13.5,(Int_t)fFillMultipleControlHistograms); |
489d5531 | 7680 | } // end of void AliFlowAnalysisWithQCumulants::StoreIntFlowFlags() |
7681 | ||
489d5531 | 7682 | //================================================================================================================================ |
7683 | ||
489d5531 | 7684 | void AliFlowAnalysisWithQCumulants::StoreDiffFlowFlags() |
7685 | { | |
7686 | // Store all flags for differential flow in the profile fDiffFlowFlags. | |
7687 | ||
7688 | if(!fDiffFlowFlags) | |
7689 | { | |
7690 | cout<<"WARNING: fDiffFlowFlags is NULL in AFAWQC::SFFDF() !!!!"<<endl; | |
7691 | exit(0); | |
7692 | } | |
7693 | ||
7694 | fDiffFlowFlags->Fill(0.5,fUsePhiWeights||fUsePtWeights||fUseEtaWeights); // particle weights used or not | |
7695 | //fDiffFlowFlags->Fill(1.5,""); // which event weight was used? // to be improved | |
7696 | fDiffFlowFlags->Fill(2.5,fApplyCorrectionForNUA); // corrected for non-uniform acceptance or not | |
7697 | fDiffFlowFlags->Fill(3.5,fCalculate2DFlow); // calculate also 2D differential flow in (pt,eta) or not | |
7698 | ||
7699 | } // end of void AliFlowAnalysisWithQCumulants::StoreDiffFlowFlags() | |
7700 | ||
489d5531 | 7701 | //================================================================================================================================ |
7702 | ||
489d5531 | 7703 | void AliFlowAnalysisWithQCumulants::GetPointersForCommonHistograms() |
7704 | { | |
7705 | // Access all pointers to common control and common result histograms and profiles. | |
7706 | ||
7707 | TString commonHistsName = "AliFlowCommonHistQC"; | |
7708 | commonHistsName += fAnalysisLabel->Data(); | |
7709 | AliFlowCommonHist *commonHist = dynamic_cast<AliFlowCommonHist*>(fHistList->FindObject(commonHistsName.Data())); | |
b77b6434 | 7710 | if(commonHist) |
7711 | { | |
7712 | this->SetCommonHists(commonHist); | |
7713 | if(fCommonHists->GetHarmonic()) | |
7714 | { | |
7715 | fHarmonic = (Int_t)(fCommonHists->GetHarmonic())->GetBinContent(1); | |
7716 | } | |
7717 | } // end of if(commonHist) | |
489d5531 | 7718 | TString commonHists2ndOrderName = "AliFlowCommonHist2ndOrderQC"; |
7719 | commonHists2ndOrderName += fAnalysisLabel->Data(); | |
7720 | AliFlowCommonHist *commonHist2nd = dynamic_cast<AliFlowCommonHist*>(fHistList->FindObject(commonHists2ndOrderName.Data())); | |
7721 | if(commonHist2nd) this->SetCommonHists2nd(commonHist2nd); | |
7722 | TString commonHists4thOrderName = "AliFlowCommonHist4thOrderQC"; | |
7723 | commonHists4thOrderName += fAnalysisLabel->Data(); | |
7724 | AliFlowCommonHist *commonHist4th = dynamic_cast<AliFlowCommonHist*>(fHistList->FindObject(commonHists4thOrderName.Data())); | |
7725 | if(commonHist4th) this->SetCommonHists4th(commonHist4th); | |
7726 | TString commonHists6thOrderName = "AliFlowCommonHist6thOrderQC"; | |
7727 | commonHists6thOrderName += fAnalysisLabel->Data(); | |
7728 | AliFlowCommonHist *commonHist6th = dynamic_cast<AliFlowCommonHist*>(fHistList->FindObject(commonHists6thOrderName.Data())); | |
7729 | if(commonHist6th) this->SetCommonHists6th(commonHist6th); | |
7730 | TString commonHists8thOrderName = "AliFlowCommonHist8thOrderQC"; | |
7731 | commonHists8thOrderName += fAnalysisLabel->Data(); | |
7732 | AliFlowCommonHist *commonHist8th = dynamic_cast<AliFlowCommonHist*>(fHistList->FindObject(commonHists8thOrderName.Data())); | |
dd442cd2 | 7733 | if(commonHist8th) this->SetCommonHists8th(commonHist8th); |
7734 | ||
489d5531 | 7735 | TString commonHistResults2ndOrderName = "AliFlowCommonHistResults2ndOrderQC"; |
7736 | commonHistResults2ndOrderName += fAnalysisLabel->Data(); | |
b77b6434 | 7737 | AliFlowCommonHistResults *commonHistRes2nd = dynamic_cast<AliFlowCommonHistResults*> |
7738 | (fHistList->FindObject(commonHistResults2ndOrderName.Data())); | |
489d5531 | 7739 | if(commonHistRes2nd) this->SetCommonHistsResults2nd(commonHistRes2nd); |
7740 | TString commonHistResults4thOrderName = "AliFlowCommonHistResults4thOrderQC"; | |
7741 | commonHistResults4thOrderName += fAnalysisLabel->Data(); | |
7742 | AliFlowCommonHistResults *commonHistRes4th = dynamic_cast<AliFlowCommonHistResults*> | |
7743 | (fHistList->FindObject(commonHistResults4thOrderName.Data())); | |
7744 | if(commonHistRes4th) this->SetCommonHistsResults4th(commonHistRes4th); | |
7745 | TString commonHistResults6thOrderName = "AliFlowCommonHistResults6thOrderQC"; | |
7746 | commonHistResults6thOrderName += fAnalysisLabel->Data(); | |
7747 | AliFlowCommonHistResults *commonHistRes6th = dynamic_cast<AliFlowCommonHistResults*> | |
7748 | (fHistList->FindObject(commonHistResults6thOrderName.Data())); | |
7749 | if(commonHistRes6th) this->SetCommonHistsResults6th(commonHistRes6th); | |
7750 | TString commonHistResults8thOrderName = "AliFlowCommonHistResults8thOrderQC"; | |
7751 | commonHistResults8thOrderName += fAnalysisLabel->Data(); | |
7752 | AliFlowCommonHistResults *commonHistRes8th = dynamic_cast<AliFlowCommonHistResults*> | |
7753 | (fHistList->FindObject(commonHistResults8thOrderName.Data())); | |
7754 | if(commonHistRes8th) this->SetCommonHistsResults8th(commonHistRes8th); | |
7755 | ||
7756 | } // end of void AliFlowAnalysisWithQCumulants::GetPointersForCommonHistograms() | |
7757 | ||
7758 | ||
7759 | //================================================================================================================================ | |
7760 | ||
7761 | ||
7762 | void AliFlowAnalysisWithQCumulants::GetPointersForParticleWeightsHistograms() | |
7763 | { | |
7764 | // Get pointers for histograms with particle weights. | |
7765 | ||
7766 | TList *weightsList = dynamic_cast<TList*>(fHistList->FindObject("Weights")); | |
7767 | if(weightsList) this->SetWeightsList(weightsList); | |
7768 | TString fUseParticleWeightsName = "fUseParticleWeightsQC"; // to be improved (hirdwired label QC) | |
7769 | fUseParticleWeightsName += fAnalysisLabel->Data(); | |
7770 | TProfile *useParticleWeights = dynamic_cast<TProfile*>(weightsList->FindObject(fUseParticleWeightsName.Data())); | |
7771 | if(useParticleWeights) | |
7772 | { | |
7773 | this->SetUseParticleWeights(useParticleWeights); | |
7774 | fUsePhiWeights = (Int_t)fUseParticleWeights->GetBinContent(1); | |
7775 | fUsePtWeights = (Int_t)fUseParticleWeights->GetBinContent(2); | |
7776 | fUseEtaWeights = (Int_t)fUseParticleWeights->GetBinContent(3); | |
7777 | } | |
7778 | } // end of void AliFlowAnalysisWithQCumulants::GetPointersForParticleWeightsHistograms(); | |
7779 | ||
7780 | ||
7781 | //================================================================================================================================ | |
7782 | ||
7783 | ||
7784 | void AliFlowAnalysisWithQCumulants::GetPointersForIntFlowHistograms() | |
7785 | { | |
7786 | // Get pointers for histograms and profiles relevant for integrated flow: | |
7787 | // a) Get pointer to base list for integrated flow holding profile fIntFlowFlags and lists fIntFlowProfiles and fIntFlowResults. | |
7788 | // b) Get pointer to profile fIntFlowFlags holding all flags for integrated flow. | |
7789 | // c) Get pointer to list fIntFlowProfiles and pointers to all objects that she holds. | |
7790 | // d) Get pointer to list fIntFlowResults and pointers to all objects that she holds. | |
7791 | ||
7792 | TString sinCosFlag[2] = {"sin","cos"}; // to be improved (should I promote this to data member?) | |
7793 | TString powerFlag[2] = {"linear","quadratic"}; // to be improved (should I promote this to data member?) | |
b40a910e | 7794 | TString correlationFlag[4] = {"#LT#LT2#GT#GT","#LT#LT4#GT#GT","#LT#LT6#GT#GT","#LT#LT8#GT#GT"}; // to be improved (should I promote this to data member?) |
7795 | TString squaredCorrelationFlag[4] = {"#LT#LT2#GT^{2}#GT","#LT#LT4#GT^{2}#GT","#LT#LT6#GT^{2}#GT","#LT#LT8#GT^{2}#GT"}; // to be improved (should I promote this to data member?) | |
489d5531 | 7796 | |
7797 | // a) Get pointer to base list for integrated flow holding profile fIntFlowFlags and lists fIntFlowProfiles and fIntFlowResults: | |
7798 | TList *intFlowList = NULL; | |
7799 | intFlowList = dynamic_cast<TList*>(fHistList->FindObject("Integrated Flow")); | |
7800 | if(!intFlowList) | |
7801 | { | |
7802 | cout<<"WARNING: intFlowList is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
7803 | exit(0); | |
7804 | } | |
7805 | ||
b92ea2b9 | 7806 | // b) Get pointer to profile fIntFlowFlags holding all flags for integrated flow: |
7807 | TString intFlowFlagsName = "fIntFlowFlags"; | |
7808 | intFlowFlagsName += fAnalysisLabel->Data(); | |
7809 | TProfile *intFlowFlags = dynamic_cast<TProfile*>(intFlowList->FindObject(intFlowFlagsName.Data())); | |
7810 | if(intFlowFlags) | |
7811 | { | |
7812 | this->SetIntFlowFlags(intFlowFlags); | |
7813 | fApplyCorrectionForNUA = (Bool_t)intFlowFlags->GetBinContent(3); | |
7814 | fApplyCorrectionForNUAVsM = (Bool_t)intFlowFlags->GetBinContent(8); | |
7815 | fCalculateCumulantsVsM = (Bool_t)intFlowFlags->GetBinContent(10); | |
7816 | } else | |
7817 | { | |
7818 | cout<<"WARNING: intFlowFlags is NULL in FAWQC::GPFIFH() !!!!"<<endl; | |
7819 | } | |
489d5531 | 7820 | |
7821 | // c) Get pointer to list fIntFlowProfiles and pointers to all objects that she holds: | |
7822 | TList *intFlowProfiles = NULL; | |
7823 | intFlowProfiles = dynamic_cast<TList*>(intFlowList->FindObject("Profiles")); | |
7824 | if(intFlowProfiles) | |
7825 | { | |
7826 | // average multiplicities: | |
7827 | TString avMultiplicityName = "fAvMultiplicity"; | |
7828 | avMultiplicityName += fAnalysisLabel->Data(); | |
7829 | TProfile *avMultiplicity = dynamic_cast<TProfile*>(intFlowProfiles->FindObject(avMultiplicityName.Data())); | |
7830 | if(avMultiplicity) | |
7831 | { | |
7832 | this->SetAvMultiplicity(avMultiplicity); | |
7833 | } else | |
7834 | { | |
7835 | cout<<"WARNING: avMultiplicity is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
7836 | } | |
7837 | // average correlations <<2>>, <<4>>, <<6>> and <<8>> (with wrong errors!): | |
7838 | TString intFlowCorrelationsProName = "fIntFlowCorrelationsPro"; | |
7839 | intFlowCorrelationsProName += fAnalysisLabel->Data(); | |
7840 | TProfile *intFlowCorrelationsPro = dynamic_cast<TProfile*>(intFlowProfiles->FindObject(intFlowCorrelationsProName.Data())); | |
7841 | if(intFlowCorrelationsPro) | |
7842 | { | |
7843 | this->SetIntFlowCorrelationsPro(intFlowCorrelationsPro); | |
7844 | } else | |
7845 | { | |
7846 | cout<<"WARNING: intFlowCorrelationsPro is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
ff70ca91 | 7847 | } |
b40a910e | 7848 | // average squared correlations <<2>^2>, <<4>^2>, <<6>^2> and <<8^2>>: |
7849 | TString intFlowSquaredCorrelationsProName = "fIntFlowSquaredCorrelationsPro"; | |
7850 | intFlowSquaredCorrelationsProName += fAnalysisLabel->Data(); | |
7851 | TProfile *intFlowSquaredCorrelationsPro = dynamic_cast<TProfile*>(intFlowProfiles->FindObject(intFlowSquaredCorrelationsProName.Data())); | |
7852 | if(intFlowSquaredCorrelationsPro) | |
7853 | { | |
7854 | this->SetIntFlowSquaredCorrelationsPro(intFlowSquaredCorrelationsPro); | |
7855 | } else | |
7856 | { | |
7857 | cout<<"WARNING: intFlowSquaredCorrelationsPro is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
7858 | } | |
b3dacf6b | 7859 | if(fCalculateCumulantsVsM) |
ff70ca91 | 7860 | { |
b40a910e | 7861 | // Average correlations <<2>>, <<4>>, <<6>> and <<8>> versus multiplicity for all events (error is wrong here): |
b3dacf6b | 7862 | TString intFlowCorrelationsVsMProName = "fIntFlowCorrelationsVsMPro"; |
7863 | intFlowCorrelationsVsMProName += fAnalysisLabel->Data(); | |
7864 | for(Int_t ci=0;ci<4;ci++) // correlation index | |
ff70ca91 | 7865 | { |
b3dacf6b | 7866 | TProfile *intFlowCorrelationsVsMPro = dynamic_cast<TProfile*> |
7867 | (intFlowProfiles->FindObject(Form("%s, %s",intFlowCorrelationsVsMProName.Data(),correlationFlag[ci].Data()))); | |
7868 | if(intFlowCorrelationsVsMPro) | |
7869 | { | |
7870 | this->SetIntFlowCorrelationsVsMPro(intFlowCorrelationsVsMPro,ci); | |
7871 | } else | |
7872 | { | |
7873 | cout<<"WARNING: "<<Form("intFlowCorrelationsVsMPro[%d]",ci)<<" is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
7874 | } | |
7875 | } // end of for(Int_t ci=0;ci<4;ci++) // correlation index | |
b40a910e | 7876 | // Average squared correlations <<2>^2>, <<4>^2>, <<6>^2> and <<8>^2> versus multiplicity for all events: |
7877 | TString intFlowSquaredCorrelationsVsMProName = "fIntFlowSquaredCorrelationsVsMPro"; | |
7878 | intFlowSquaredCorrelationsVsMProName += fAnalysisLabel->Data(); | |
7879 | for(Int_t ci=0;ci<4;ci++) // correlation index | |
7880 | { | |
7881 | TProfile *intFlowSquaredCorrelationsVsMPro = dynamic_cast<TProfile*> | |
7882 | (intFlowProfiles->FindObject(Form("%s, %s",intFlowSquaredCorrelationsVsMProName.Data(),squaredCorrelationFlag[ci].Data()))); | |
7883 | if(intFlowSquaredCorrelationsVsMPro) | |
7884 | { | |
7885 | this->SetIntFlowSquaredCorrelationsVsMPro(intFlowSquaredCorrelationsVsMPro,ci); | |
7886 | } else | |
7887 | { | |
7888 | cout<<"WARNING: "<<Form("intFlowSquaredCorrelationsVsMPro[%d]",ci)<<" is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
7889 | } | |
7890 | } // end of for(Int_t ci=0;ci<4;ci++) // correlation index | |
b3dacf6b | 7891 | } // end of if(fCalculateCumulantsVsM) |
489d5531 | 7892 | // average all correlations for integrated flow (with wrong errors!): |
7893 | TString intFlowCorrelationsAllProName = "fIntFlowCorrelationsAllPro"; | |
7894 | intFlowCorrelationsAllProName += fAnalysisLabel->Data(); | |
7895 | TProfile *intFlowCorrelationsAllPro = dynamic_cast<TProfile*>(intFlowProfiles->FindObject(intFlowCorrelationsAllProName.Data())); | |
7896 | if(intFlowCorrelationsAllPro) | |
7897 | { | |
7898 | this->SetIntFlowCorrelationsAllPro(intFlowCorrelationsAllPro); | |
7899 | } else | |
7900 | { | |
7901 | cout<<"WARNING: intFlowCorrelationsAllPro is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
7902 | } | |
7903 | // average extra correlations for integrated flow (which appear only when particle weights are used): | |
7904 | // (to be improved: Weak point in implementation, I am assuming here that method GetPointersForParticleWeightsHistograms() was called) | |
7905 | if(fUsePhiWeights||fUsePtWeights||fUseEtaWeights) | |
7906 | { | |
7907 | TString intFlowExtraCorrelationsProName = "fIntFlowExtraCorrelationsPro"; | |
7908 | intFlowExtraCorrelationsProName += fAnalysisLabel->Data(); | |
7909 | TProfile *intFlowExtraCorrelationsPro = dynamic_cast<TProfile*>(intFlowProfiles->FindObject(intFlowExtraCorrelationsProName.Data())); | |
7910 | if(intFlowExtraCorrelationsPro) | |
7911 | { | |
7912 | this->SetIntFlowExtraCorrelationsPro(intFlowExtraCorrelationsPro); | |
7913 | } else | |
7914 | { | |
7915 | cout<<"WARNING: intFlowExtraCorrelationsPro is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
7916 | } | |
7917 | } // end of if(fUsePhiWeights||fUsePtWeights||fUseEtaWeights) | |
7918 | // average products of correlations <2>, <4>, <6> and <8>: | |
7919 | TString intFlowProductOfCorrelationsProName = "fIntFlowProductOfCorrelationsPro"; | |
7920 | intFlowProductOfCorrelationsProName += fAnalysisLabel->Data(); | |
7921 | TProfile *intFlowProductOfCorrelationsPro = dynamic_cast<TProfile*>(intFlowProfiles->FindObject(intFlowProductOfCorrelationsProName.Data())); | |
7922 | if(intFlowProductOfCorrelationsPro) | |
7923 | { | |
7924 | this->SetIntFlowProductOfCorrelationsPro(intFlowProductOfCorrelationsPro); | |
7925 | } else | |
7926 | { | |
7927 | cout<<"WARNING: intFlowProductOfCorrelationsPro is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
ff70ca91 | 7928 | } |
7929 | // average product of correlations <2>, <4>, <6> and <8> versus multiplicity | |
7930 | // [0=<<2><4>>,1=<<2><6>>,2=<<2><8>>,3=<<4><6>>,4=<<4><8>>,5=<<6><8>>] | |
b3dacf6b | 7931 | if(fCalculateCumulantsVsM) |
7932 | { | |
7933 | TString intFlowProductOfCorrelationsVsMProName = "fIntFlowProductOfCorrelationsVsMPro"; | |
7934 | intFlowProductOfCorrelationsVsMProName += fAnalysisLabel->Data(); | |
7935 | TString productFlag[6] = {"<<2><4>>","<<2><6>>","<<2><8>>","<<4><6>>","<<4><8>>","<<6><8>>"}; | |
7936 | for(Int_t pi=0;pi<6;pi++) | |
7937 | { | |
7938 | TProfile *intFlowProductOfCorrelationsVsMPro = dynamic_cast<TProfile*>(intFlowProfiles->FindObject(Form("%s, %s",intFlowProductOfCorrelationsVsMProName.Data(),productFlag[pi].Data()))); | |
7939 | if(intFlowProductOfCorrelationsVsMPro) | |
7940 | { | |
7941 | this->SetIntFlowProductOfCorrelationsVsMPro(intFlowProductOfCorrelationsVsMPro,pi); | |
7942 | } else | |
7943 | { | |
7944 | cout<<"WARNING: "<<Form("intFlowProductOfCorrelationsVsMPro[%d]",pi)<<" is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
7945 | } | |
7946 | } // end of for(Int_t pi=0;pi<6;pi++) | |
7947 | } // end of if(fCalculateCumulantsVsM) | |
489d5531 | 7948 | // average correction terms for non-uniform acceptance (with wrong errors!): |
7949 | for(Int_t sc=0;sc<2;sc++) | |
7950 | { | |
7951 | TString intFlowCorrectionTermsForNUAProName = "fIntFlowCorrectionTermsForNUAPro"; | |
7952 | intFlowCorrectionTermsForNUAProName += fAnalysisLabel->Data(); | |
7953 | TProfile *intFlowCorrectionTermsForNUAPro = dynamic_cast<TProfile*>(intFlowProfiles->FindObject((Form("%s: %s terms",intFlowCorrectionTermsForNUAProName.Data(),sinCosFlag[sc].Data())))); | |
7954 | if(intFlowCorrectionTermsForNUAPro) | |
7955 | { | |
7956 | this->SetIntFlowCorrectionTermsForNUAPro(intFlowCorrectionTermsForNUAPro,sc); | |
7957 | } else | |
7958 | { | |
7959 | cout<<"WARNING: intFlowCorrectionTermsForNUAPro is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
7960 | cout<<"sc = "<<sc<<endl; | |
7961 | } | |
2001bc3a | 7962 | // versus multiplicity: |
b3dacf6b | 7963 | if(fCalculateCumulantsVsM) |
2001bc3a | 7964 | { |
b3dacf6b | 7965 | TString correctionTermFlag[4] = {"(n(phi1))","(n(phi1+phi2))","(n(phi1-phi2-phi3))","(n(2phi1-phi2))"}; // to be improved - hardwired 4 |
7966 | TString intFlowCorrectionTermsForNUAVsMProName = "fIntFlowCorrectionTermsForNUAVsMPro"; | |
7967 | intFlowCorrectionTermsForNUAVsMProName += fAnalysisLabel->Data(); | |
7968 | for(Int_t ci=0;ci<4;ci++) // correction term index (to be improved - hardwired 4) | |
2001bc3a | 7969 | { |
b3dacf6b | 7970 | TProfile *intFlowCorrectionTermsForNUAVsMPro = dynamic_cast<TProfile*>(intFlowProfiles->FindObject(Form("%s: #LT#LT%s%s#GT#GT",intFlowCorrectionTermsForNUAVsMProName.Data(),sinCosFlag[sc].Data(),correctionTermFlag[ci].Data()))); |
7971 | if(intFlowCorrectionTermsForNUAVsMPro) | |
7972 | { | |
7973 | this->SetIntFlowCorrectionTermsForNUAVsMPro(intFlowCorrectionTermsForNUAVsMPro,sc,ci); | |
7974 | } else | |
7975 | { | |
7976 | cout<<"WARNING: intFlowCorrectionTermsForNUAVsMPro is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
7977 | cout<<"sc = "<<sc<<endl; | |
7978 | cout<<"ci = "<<ci<<endl; | |
7979 | } | |
7980 | } // end of for(Int_t ci=0;ci<4;ci++) // correction term index (to be improved - hardwired 4) | |
7981 | } // end of if(fCalculateCumulantsVsM) | |
489d5531 | 7982 | } // end of for(Int_t sc=0;sc<2;sc++) |
0328db2d | 7983 | // average products of correction terms for NUA: |
7984 | TString intFlowProductOfCorrectionTermsForNUAProName = "fIntFlowProductOfCorrectionTermsForNUAPro"; | |
7985 | intFlowProductOfCorrectionTermsForNUAProName += fAnalysisLabel->Data(); | |
7986 | TProfile *intFlowProductOfCorrectionTermsForNUAPro = dynamic_cast<TProfile*>(intFlowProfiles->FindObject(intFlowProductOfCorrectionTermsForNUAProName.Data())); | |
7987 | if(intFlowProductOfCorrectionTermsForNUAPro) | |
7988 | { | |
7989 | this->SetIntFlowProductOfCorrectionTermsForNUAPro(intFlowProductOfCorrectionTermsForNUAPro); | |
7990 | } else | |
7991 | { | |
7992 | cout<<"WARNING: intFlowProductOfCorrectionTermsForNUAPro is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
7993 | } | |
489d5531 | 7994 | } else // to if(intFlowProfiles) |
7995 | { | |
7996 | cout<<"WARNING: intFlowProfiles is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
7997 | } | |
7998 | ||
7999 | // d) Get pointer to list fIntFlowResults and pointers to all objects that she holds. | |
8000 | TList *intFlowResults = NULL; | |
8001 | intFlowResults = dynamic_cast<TList*>(intFlowList->FindObject("Results")); | |
8002 | if(intFlowResults) | |
8003 | { | |
8004 | // average correlations <<2>>, <<4>>, <<6>> and <<8>> (with correct errors!): | |
8005 | TString intFlowCorrelationsHistName = "fIntFlowCorrelationsHist"; | |
8006 | intFlowCorrelationsHistName += fAnalysisLabel->Data(); | |
8007 | TH1D *intFlowCorrelationsHist = dynamic_cast<TH1D*>(intFlowResults->FindObject(intFlowCorrelationsHistName.Data())); | |
8008 | if(intFlowCorrelationsHist) | |
8009 | { | |
8010 | this->SetIntFlowCorrelationsHist(intFlowCorrelationsHist); | |
8011 | } else | |
8012 | { | |
8013 | cout<<"WARNING: intFlowCorrelationsHist is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
8014 | } | |
ff70ca91 | 8015 | // average correlations <<2>>, <<4>>, <<6>> and <<8>> (with correct errors!) vs M: |
b3dacf6b | 8016 | if(fCalculateCumulantsVsM) |
ff70ca91 | 8017 | { |
b3dacf6b | 8018 | TString intFlowCorrelationsVsMHistName = "fIntFlowCorrelationsVsMHist"; |
8019 | intFlowCorrelationsVsMHistName += fAnalysisLabel->Data(); | |
8020 | for(Int_t ci=0;ci<4;ci++) // correlation index | |
ff70ca91 | 8021 | { |
b3dacf6b | 8022 | TH1D *intFlowCorrelationsVsMHist = dynamic_cast<TH1D*> |
8023 | (intFlowResults->FindObject(Form("%s, %s",intFlowCorrelationsVsMHistName.Data(),correlationFlag[ci].Data()))); | |
8024 | if(intFlowCorrelationsVsMHist) | |
8025 | { | |
8026 | this->SetIntFlowCorrelationsVsMHist(intFlowCorrelationsVsMHist,ci); | |
8027 | } else | |
8028 | { | |
8029 | cout<<"WARNING: "<<Form("intFlowCorrelationsVsMHist[%d]",ci)<<" is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
8030 | } | |
8031 | } // end of for(Int_t ci=0;ci<4;ci++) // correlation index | |
8032 | } // end of if(fCalculateCumulantsVsM) | |
489d5531 | 8033 | // average all correlations for integrated flow (with correct errors!): |
8034 | TString intFlowCorrelationsAllHistName = "fIntFlowCorrelationsAllHist"; | |
8035 | intFlowCorrelationsAllHistName += fAnalysisLabel->Data(); | |
8036 | TH1D *intFlowCorrelationsAllHist = dynamic_cast<TH1D*>(intFlowResults->FindObject(intFlowCorrelationsAllHistName.Data())); | |
8037 | if(intFlowCorrelationsAllHist) | |
8038 | { | |
8039 | this->SetIntFlowCorrelationsAllHist(intFlowCorrelationsAllHist); | |
8040 | } else | |
8041 | { | |
8042 | cout<<"WARNING: intFlowCorrelationsAllHist is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
8043 | } | |
8044 | // average correction terms for non-uniform acceptance (with correct errors!): | |
8045 | TString intFlowCorrectionTermsForNUAHistName = "fIntFlowCorrectionTermsForNUAHist"; | |
8046 | intFlowCorrectionTermsForNUAHistName += fAnalysisLabel->Data(); | |
8047 | for(Int_t sc=0;sc<2;sc++) | |
8048 | { | |
8049 | TH1D *intFlowCorrectionTermsForNUAHist = dynamic_cast<TH1D*>(intFlowResults->FindObject((Form("%s: %s terms",intFlowCorrectionTermsForNUAHistName.Data(),sinCosFlag[sc].Data())))); | |
8050 | if(intFlowCorrectionTermsForNUAHist) | |
8051 | { | |
8052 | this->SetIntFlowCorrectionTermsForNUAHist(intFlowCorrectionTermsForNUAHist,sc); | |
8053 | } else | |
8054 | { | |
8055 | cout<<"WARNING: intFlowCorrectionTermsForNUAHist is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
8056 | cout<<"sc = "<<sc<<endl; | |
8057 | } | |
8058 | } // end of for(Int_t sc=0;sc<2;sc++) | |
8059 | // covariances (multiplied with weight dependent prefactor): | |
8060 | TString intFlowCovariancesName = "fIntFlowCovariances"; | |
8061 | intFlowCovariancesName += fAnalysisLabel->Data(); | |
8062 | TH1D *intFlowCovariances = dynamic_cast<TH1D*>(intFlowResults->FindObject(intFlowCovariancesName.Data())); | |
8063 | if(intFlowCovariances) | |
8064 | { | |
8065 | this->SetIntFlowCovariances(intFlowCovariances); | |
8066 | } else | |
8067 | { | |
8068 | cout<<"WARNING: intFlowCovariances is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
8069 | } | |
8070 | // sum of linear and quadratic event weights for <2>, <4>, <6> and <8>: | |
8071 | TString intFlowSumOfEventWeightsName = "fIntFlowSumOfEventWeights"; | |
8072 | intFlowSumOfEventWeightsName += fAnalysisLabel->Data(); | |
8073 | for(Int_t power=0;power<2;power++) | |
8074 | { | |
8075 | TH1D *intFlowSumOfEventWeights = dynamic_cast<TH1D*>(intFlowResults->FindObject(Form("%s: %s",intFlowSumOfEventWeightsName.Data(),powerFlag[power].Data()))); | |
8076 | if(intFlowSumOfEventWeights) | |
8077 | { | |
8078 | this->SetIntFlowSumOfEventWeights(intFlowSumOfEventWeights,power); | |
8079 | } else | |
8080 | { | |
8081 | cout<<"WARNING: intFlowSumOfEventWeights is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
8082 | cout<<"power = "<<power<<endl; | |
8083 | } | |
8084 | } // end of for(Int_t power=0;power<2;power++) | |
8085 | // sum of products of event weights for correlations <2>, <4>, <6> and <8>: | |
8086 | TString intFlowSumOfProductOfEventWeightsName = "fIntFlowSumOfProductOfEventWeights"; | |
8087 | intFlowSumOfProductOfEventWeightsName += fAnalysisLabel->Data(); | |
8088 | TH1D *intFlowSumOfProductOfEventWeights = dynamic_cast<TH1D*>(intFlowResults->FindObject(intFlowSumOfProductOfEventWeightsName.Data())); | |
8089 | if(intFlowSumOfProductOfEventWeights) | |
8090 | { | |
8091 | this->SetIntFlowSumOfProductOfEventWeights(intFlowSumOfProductOfEventWeights); | |
8092 | } else | |
8093 | { | |
8094 | cout<<"WARNING: intFlowSumOfProductOfEventWeights is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
8095 | } | |
ff70ca91 | 8096 | // final result for covariances of correlations (multiplied with weight dependent prefactor) versus M |
8097 | // [0=Cov(2,4),1=Cov(2,6),2=Cov(2,8),3=Cov(4,6),4=Cov(4,8),5=Cov(6,8)]: | |
b3dacf6b | 8098 | if(fCalculateCumulantsVsM) |
ff70ca91 | 8099 | { |
b3dacf6b | 8100 | TString intFlowCovariancesVsMName = "fIntFlowCovariancesVsM"; |
8101 | intFlowCovariancesVsMName += fAnalysisLabel->Data(); | |
8102 | TString covarianceFlag[6] = {"Cov(<2>,<4>)","Cov(<2>,<6>)","Cov(<2>,<8>)","Cov(<4>,<6>)","Cov(<4>,<8>)","Cov(<6>,<8>)"}; | |
8103 | for(Int_t ci=0;ci<6;ci++) | |
8104 | { | |
8105 | TH1D *intFlowCovariancesVsM = dynamic_cast<TH1D*>(intFlowResults->FindObject(Form("%s, %s",intFlowCovariancesVsMName.Data(),covarianceFlag[ci].Data()))); | |
8106 | if(intFlowCovariancesVsM) | |
ff70ca91 | 8107 | { |
b3dacf6b | 8108 | this->SetIntFlowCovariancesVsM(intFlowCovariancesVsM,ci); |
ff70ca91 | 8109 | } else |
8110 | { | |
b3dacf6b | 8111 | cout<<"WARNING: "<<Form("intFlowCovariancesVsM[%d]",ci)<<" is NULL in AFAWQC::GPFIFH() !!!!"<<endl; |
ff70ca91 | 8112 | } |
b3dacf6b | 8113 | } // end of for(Int_t ci=0;ci<6;ci++) |
8114 | } // end of if(fCalculateCumulantsVsM) | |
8115 | // sum of linear and quadratic event weights for <2>, <4>, <6> and <8> versus multiplicity | |
8116 | // [0=sum{w_{<2>}},1=sum{w_{<4>}},2=sum{w_{<6>}},3=sum{w_{<8>}}][0=linear 1,1=quadratic]: | |
8117 | if(fCalculateCumulantsVsM) | |
8118 | { | |
8119 | TString intFlowSumOfEventWeightsVsMName = "fIntFlowSumOfEventWeightsVsM"; | |
8120 | intFlowSumOfEventWeightsVsMName += fAnalysisLabel->Data(); | |
8121 | TString sumFlag[2][4] = {{"#sum_{i=1}^{N} w_{<2>}","#sum_{i=1}^{N} w_{<4>}","#sum_{i=1}^{N} w_{<6>}","#sum_{i=1}^{N} w_{<8>}"}, | |
8122 | {"#sum_{i=1}^{N} w_{<2>}^{2}","#sum_{i=1}^{N} w_{<4>}^{2}","#sum_{i=1}^{N} w_{<6>}^{2}","#sum_{i=1}^{N} w_{<8>}^{2}"}}; | |
8123 | for(Int_t si=0;si<4;si++) | |
8124 | { | |
8125 | for(Int_t power=0;power<2;power++) | |
8126 | { | |
8127 | TH1D *intFlowSumOfEventWeightsVsM = dynamic_cast<TH1D*>(intFlowResults->FindObject(Form("%s, %s",intFlowSumOfEventWeightsVsMName.Data(),sumFlag[power][si].Data()))); | |
8128 | if(intFlowSumOfEventWeightsVsM) | |
8129 | { | |
8130 | this->SetIntFlowSumOfEventWeightsVsM(intFlowSumOfEventWeightsVsM,si,power); | |
8131 | } else | |
8132 | { | |
8133 | cout<<"WARNING: "<<Form("intFlowSumOfEventWeightsVsM[%d][%d]",si,power)<<" is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
8134 | } | |
8135 | } // end of for(Int_t power=0;power<2;power++) | |
8136 | } // end of for(Int_t si=0;si<4;si++) | |
8137 | } // end of if(fCalculateCumulantsVsM) | |
ff70ca91 | 8138 | // sum of products of event weights for correlations <2>, <4>, <6> and <8> vs M |
8139 | // [0=sum{w_{<2>}w_{<4>}},1=sum{w_{<2>}w_{<6>}},2=sum{w_{<2>}w_{<8>}}, | |
8140 | // 3=sum{w_{<4>}w_{<6>}},4=sum{w_{<4>}w_{<8>}},5=sum{w_{<6>}w_{<8>}}]: | |
b3dacf6b | 8141 | if(fCalculateCumulantsVsM) |
ff70ca91 | 8142 | { |
b3dacf6b | 8143 | TString intFlowSumOfProductOfEventWeightsVsMName = "fIntFlowSumOfProductOfEventWeightsVsM"; |
8144 | intFlowSumOfProductOfEventWeightsVsMName += fAnalysisLabel->Data(); | |
8145 | TString sopowFlag[6] = {"#sum_{i=1}^{N} w_{<2>} w_{<4>}","#sum_{i=1}^{N} w_{<2>} w_{<6>}","#sum_{i=1}^{N} w_{<2>} w_{<8>}", | |
8146 | "#sum_{i=1}^{N} w_{<4>} w_{<6>}","#sum_{i=1}^{N} w_{<4>} w_{<8>}","#sum_{i=1}^{N} w_{<6>} w_{<8>}"}; | |
8147 | for(Int_t pi=0;pi<6;pi++) | |
ff70ca91 | 8148 | { |
b3dacf6b | 8149 | TH1D *intFlowSumOfProductOfEventWeightsVsM = dynamic_cast<TH1D*>(intFlowResults->FindObject(Form("%s, %s",intFlowSumOfProductOfEventWeightsVsMName.Data(),sopowFlag[pi].Data()))); |
8150 | if(intFlowSumOfProductOfEventWeightsVsM) | |
8151 | { | |
8152 | this->SetIntFlowSumOfProductOfEventWeightsVsM(intFlowSumOfProductOfEventWeightsVsM,pi); | |
8153 | } else | |
8154 | { | |
8155 | cout<<"WARNING: "<<Form("intFlowSumOfProductOfEventWeightsVsM[%d]",pi)<<" is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
8156 | } | |
8157 | } // end of for(Int_t pi=0;pi<6;pi++) | |
8158 | } // end of if(fCalculateCumulantsVsM) | |
0328db2d | 8159 | // covariances for NUA (multiplied with weight dependent prefactor): |
8160 | TString intFlowCovariancesNUAName = "fIntFlowCovariancesNUA"; | |
8161 | intFlowCovariancesNUAName += fAnalysisLabel->Data(); | |
8162 | TH1D *intFlowCovariancesNUA = dynamic_cast<TH1D*>(intFlowResults->FindObject(intFlowCovariancesNUAName.Data())); | |
8163 | if(intFlowCovariancesNUA) | |
8164 | { | |
8165 | this->SetIntFlowCovariancesNUA(intFlowCovariancesNUA); | |
8166 | } else | |
8167 | { | |
8168 | cout<<"WARNING: intFlowCovariancesNUA is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
8169 | } | |
8170 | // sum of linear and quadratic event weights NUA terms: | |
8171 | TString intFlowSumOfEventWeightsNUAName = "fIntFlowSumOfEventWeightsNUA"; | |
8172 | intFlowSumOfEventWeightsNUAName += fAnalysisLabel->Data(); | |
8173 | for(Int_t sc=0;sc<2;sc++) | |
8174 | { | |
8175 | for(Int_t power=0;power<2;power++) | |
8176 | { | |
8177 | TH1D *intFlowSumOfEventWeightsNUA = dynamic_cast<TH1D*>(intFlowResults->FindObject(Form("%s: %s, %s",intFlowSumOfEventWeightsNUAName.Data(),powerFlag[power].Data(),sinCosFlag[sc].Data()))); | |
8178 | if(intFlowSumOfEventWeightsNUA) | |
8179 | { | |
8180 | this->SetIntFlowSumOfEventWeightsNUA(intFlowSumOfEventWeightsNUA,sc,power); | |
8181 | } else | |
8182 | { | |
8183 | cout<<"WARNING: intFlowSumOfEventWeightsNUA is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
8184 | cout<<"sc = "<<sc<<endl; | |
8185 | cout<<"power = "<<power<<endl; | |
8186 | } | |
8187 | } // end of for(Int_t power=0;power<2;power++) | |
8188 | } // end of for(Int_t sc=0;sc<2;sc++) | |
8189 | // sum of products of event weights for NUA terms: | |
8190 | TString intFlowSumOfProductOfEventWeightsNUAName = "fIntFlowSumOfProductOfEventWeightsNUA"; | |
8191 | intFlowSumOfProductOfEventWeightsNUAName += fAnalysisLabel->Data(); | |
8192 | TH1D *intFlowSumOfProductOfEventWeightsNUA = dynamic_cast<TH1D*>(intFlowResults->FindObject(intFlowSumOfProductOfEventWeightsNUAName.Data())); | |
8193 | if(intFlowSumOfProductOfEventWeightsNUA) | |
8194 | { | |
8195 | this->SetIntFlowSumOfProductOfEventWeightsNUA(intFlowSumOfProductOfEventWeightsNUA); | |
8196 | } else | |
8197 | { | |
8198 | cout<<"WARNING: intFlowSumOfProductOfEventWeightsNUA is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
8199 | } | |
b3dacf6b | 8200 | // Final results for reference Q-cumulants: |
489d5531 | 8201 | TString intFlowQcumulantsName = "fIntFlowQcumulants"; |
8202 | intFlowQcumulantsName += fAnalysisLabel->Data(); | |
8203 | TH1D *intFlowQcumulants = dynamic_cast<TH1D*>(intFlowResults->FindObject(intFlowQcumulantsName.Data())); | |
8204 | if(intFlowQcumulants) | |
8205 | { | |
8206 | this->SetIntFlowQcumulants(intFlowQcumulants); | |
8207 | } else | |
8208 | { | |
8209 | cout<<"WARNING: intFlowQcumulants is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
8210 | } | |
b3dacf6b | 8211 | // Final results for reference Q-cumulants rebinned in M: |
8212 | if(fCalculateCumulantsVsM) | |
8213 | { | |
8214 | TString intFlowQcumulantsRebinnedInMName = "fIntFlowQcumulantsRebinnedInM"; | |
8215 | intFlowQcumulantsRebinnedInMName += fAnalysisLabel->Data(); | |
8216 | TH1D *intFlowQcumulantsRebinnedInM = dynamic_cast<TH1D*>(intFlowResults->FindObject(intFlowQcumulantsRebinnedInMName.Data())); | |
8217 | if(intFlowQcumulantsRebinnedInM) | |
8218 | { | |
8219 | this->SetIntFlowQcumulantsRebinnedInM(intFlowQcumulantsRebinnedInM); | |
8220 | } else | |
8221 | { | |
8222 | cout<<"WARNING: intFlowQcumulantsRebinnedInM is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
8223 | } | |
8224 | } // end of if(fCalculateCumulantsVsM) | |
b92ea2b9 | 8225 | // Ratio between error squared: with/without non-isotropic terms: |
8226 | TString intFlowQcumulantsErrorSquaredRatioName = "fIntFlowQcumulantsErrorSquaredRatio"; | |
8227 | intFlowQcumulantsErrorSquaredRatioName += fAnalysisLabel->Data(); | |
8228 | TH1D *intFlowQcumulantsErrorSquaredRatio = dynamic_cast<TH1D*>(intFlowResults->FindObject(intFlowQcumulantsErrorSquaredRatioName.Data())); | |
8229 | if(intFlowQcumulantsErrorSquaredRatio) | |
8230 | { | |
8231 | this->SetIntFlowQcumulantsErrorSquaredRatio(intFlowQcumulantsErrorSquaredRatio); | |
8232 | } else | |
8233 | { | |
8234 | cout<<" WARNING: intntFlowQcumulantsErrorSquaredRatio is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
8235 | } | |
ff70ca91 | 8236 | // final results for integrated Q-cumulants versus multiplicity: |
ff70ca91 | 8237 | TString cumulantFlag[4] = {"QC{2}","QC{4}","QC{6}","QC{8}"}; |
b3dacf6b | 8238 | if(fCalculateCumulantsVsM) |
ff70ca91 | 8239 | { |
b3dacf6b | 8240 | TString intFlowQcumulantsVsMName = "fIntFlowQcumulantsVsM"; |
8241 | intFlowQcumulantsVsMName += fAnalysisLabel->Data(); | |
8242 | for(Int_t co=0;co<4;co++) // cumulant order | |
ff70ca91 | 8243 | { |
b3dacf6b | 8244 | TH1D *intFlowQcumulantsVsM = dynamic_cast<TH1D*> |
8245 | (intFlowResults->FindObject(Form("%s, %s",intFlowQcumulantsVsMName.Data(),cumulantFlag[co].Data()))); | |
8246 | if(intFlowQcumulantsVsM) | |
8247 | { | |
8248 | this->SetIntFlowQcumulantsVsM(intFlowQcumulantsVsM,co); | |
8249 | } else | |
8250 | { | |
8251 | cout<<"WARNING: "<<Form("intFlowQcumulantsVsM[%d]",co)<<" is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
8252 | } | |
8253 | } // end of for(Int_t co=0;co<4;co++) // cumulant order | |
8254 | } // end of if(fCalculateCumulantsVsM) | |
8255 | // Final reference flow estimates from Q-cumulants: | |
489d5531 | 8256 | TString intFlowName = "fIntFlow"; |
8257 | intFlowName += fAnalysisLabel->Data(); | |
8258 | TH1D *intFlow = dynamic_cast<TH1D*>(intFlowResults->FindObject(intFlowName.Data())); | |
8259 | if(intFlow) | |
8260 | { | |
8261 | this->SetIntFlow(intFlow); | |
8262 | } else | |
8263 | { | |
8264 | cout<<"WARNING: intFlow is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
ff70ca91 | 8265 | } |
b3dacf6b | 8266 | // Final reference flow estimates from Q-cumulants vs M rebinned in M: |
8267 | if(fCalculateCumulantsVsM) | |
ff70ca91 | 8268 | { |
b3dacf6b | 8269 | TString intFlowRebinnedInMName = "fIntFlowRebinnedInM"; |
8270 | intFlowRebinnedInMName += fAnalysisLabel->Data(); | |
8271 | TH1D *intFlowRebinnedInM = dynamic_cast<TH1D*>(intFlowResults->FindObject(intFlowRebinnedInMName.Data())); | |
8272 | if(intFlowRebinnedInM) | |
ff70ca91 | 8273 | { |
b3dacf6b | 8274 | this->SetIntFlowRebinnedInM(intFlowRebinnedInM); |
8275 | } else | |
ff70ca91 | 8276 | { |
b3dacf6b | 8277 | cout<<"WARNING: intFlowRebinnedInM is NULL in AFAWQC::GPFIFH() !!!!"<<endl; |
8278 | } | |
8279 | } // end of if(fCalculateCumulantsVsM) | |
8280 | // integrated flow from Q-cumulants versus multiplicity: | |
8281 | if(fCalculateCumulantsVsM) | |
8282 | { | |
8283 | TString intFlowVsMName = "fIntFlowVsM"; | |
8284 | intFlowVsMName += fAnalysisLabel->Data(); | |
b77b6434 | 8285 | TString flowFlag[4] = {Form("v_{%d}{2,QC}",fHarmonic),Form("v_{%d}{4,QC}",fHarmonic),Form("v_{%d}{6,QC}",fHarmonic),Form("v_{%d}{8,QC}",fHarmonic)}; |
b3dacf6b | 8286 | for(Int_t co=0;co<4;co++) // cumulant order |
8287 | { | |
8288 | TH1D *intFlowVsM = dynamic_cast<TH1D*> | |
b77b6434 | 8289 | (intFlowResults->FindObject(Form("%s, %s",intFlowVsMName.Data(),flowFlag[co].Data()))); |
b3dacf6b | 8290 | if(intFlowVsM) |
8291 | { | |
8292 | this->SetIntFlowVsM(intFlowVsM,co); | |
8293 | } else | |
8294 | { | |
8295 | cout<<"WARNING: "<<Form("intFlowVsM[%d]",co)<<" is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
8296 | } | |
8297 | } // end of for(Int_t co=0;co<4;co++) // cumulant order | |
8298 | } // end of if(fCalculateCumulantsVsM) | |
2001bc3a | 8299 | // quantifying detector effects effects to correlations: |
8300 | TString intFlowDetectorBiasName = "fIntFlowDetectorBias"; | |
8301 | intFlowDetectorBiasName += fAnalysisLabel->Data(); | |
8302 | TH1D *intFlowDetectorBias = dynamic_cast<TH1D*>(intFlowResults->FindObject(intFlowDetectorBiasName.Data())); | |
8303 | if(intFlowDetectorBias) | |
8304 | { | |
8305 | this->SetIntFlowDetectorBias(intFlowDetectorBias); | |
8306 | } else | |
8307 | { | |
8308 | cout<<"WARNING: intFlowDetectorBias is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
8309 | } | |
8310 | // quantifying detector effects effects to correlations vs multiplicity: | |
b77b6434 | 8311 | if(fCalculateCumulantsVsM) |
2001bc3a | 8312 | { |
3c5d5752 | 8313 | TString intFlowDetectorBiasVsMName = "fIntFlowDetectorBiasVsM"; |
8314 | intFlowDetectorBiasVsMName += fAnalysisLabel->Data(); | |
8315 | for(Int_t ci=0;ci<4;ci++) // correlation index | |
2001bc3a | 8316 | { |
3c5d5752 | 8317 | TH1D *intFlowDetectorBiasVsM = dynamic_cast<TH1D*> |
8318 | (intFlowResults->FindObject(Form("%s for %s",intFlowDetectorBiasVsMName.Data(),cumulantFlag[ci].Data()))); | |
8319 | if(intFlowDetectorBiasVsM) | |
8320 | { | |
8321 | this->SetIntFlowDetectorBiasVsM(intFlowDetectorBiasVsM,ci); | |
8322 | } else | |
8323 | { | |
8324 | cout<<"WARNING: "<<Form("intFlowDetectorBiasVsM[%d]",ci)<<" is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
8325 | } | |
8326 | } // end of for(Int_t ci=0;ci<4;ci++) // correlation index | |
b77b6434 | 8327 | } // end of if(fCalculateCumulantsVsM) |
489d5531 | 8328 | } else // to if(intFlowResults) |
8329 | { | |
8330 | cout<<"WARNING: intFlowResults is NULL in AFAWQC::GPFIFH() !!!!"<<endl; | |
8331 | } | |
ff70ca91 | 8332 | |
489d5531 | 8333 | } // end of void AliFlowAnalysisWithQCumulants::GetPointersForIntFlowHistograms() |
8334 | ||
489d5531 | 8335 | //================================================================================================================================ |
8336 | ||
489d5531 | 8337 | void AliFlowAnalysisWithQCumulants::GetPointersForDiffFlowHistograms() |
8338 | { | |
8339 | // Get pointer to all objects relevant for differential flow. | |
8340 | // a) Define flags locally (to be improved: should I promote flags to data members?); | |
8341 | // b) Get pointer to base list for differential flow fDiffFlowList and nested lists fDiffFlowListProfiles and fDiffFlowListResults; | |
8342 | // c) Get pointer to profile fDiffFlowFlags holding all flags for differential flow; | |
8343 | // d) Get pointers to all nested lists in fDiffFlowListProfiles and to profiles which they hold; | |
8344 | // e) Get pointers to all nested lists in fDiffFlowListResults and to histograms which they hold. | |
8345 | ||
8346 | // a) Define flags locally (to be improved: should I promote flags to data members?): | |
8347 | TString typeFlag[2] = {"RP","POI"}; | |
8348 | TString ptEtaFlag[2] = {"p_{T}","#eta"}; | |
8349 | TString powerFlag[2] = {"linear","quadratic"}; | |
8350 | TString sinCosFlag[2] = {"sin","cos"}; | |
8351 | TString differentialCumulantIndex[4] = {"QC{2'}","QC{4'}","QC{6'}","QC{8'}"}; | |
8352 | TString differentialFlowIndex[4] = {"v'{2}","v'{4}","v'{6}","v'{8}"}; | |
8353 | TString reducedCorrelationIndex[4] = {"<2'>","<4'>","<6'>","<8'>"}; | |
b40a910e | 8354 | TString reducedSquaredCorrelationIndex[4] = {"<2'>^{2}","<4'>^{2}","<6'>^{2}","<8'>^{2}"}; |
489d5531 | 8355 | TString mixedCorrelationIndex[8] = {"<2>","<2'>","<4>","<4'>","<6>","<6'>","<8>","<8'>"}; |
8356 | TString covarianceName[5] = {"Cov(<2>,<2'>)","Cov(<2>,<4'>)","Cov(<4>,<2'>)","Cov(<4>,<4'>)","Cov(<2'>,<4'>)"}; | |
8357 | ||
8358 | // b) Get pointer to base list for differential flow fDiffFlowList and nested lists fDiffFlowListProfiles and fDiffFlowListResults: | |
8359 | TList *diffFlowList = NULL; | |
8360 | diffFlowList = dynamic_cast<TList*>(fHistList->FindObject("Differential Flow")); | |
8361 | if(!diffFlowList) | |
8362 | { | |
8363 | cout<<"WARNING: diffFlowList is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
8364 | exit(0); | |
8365 | } | |
8366 | // list holding nested lists containing profiles: | |
8367 | TList *diffFlowListProfiles = NULL; | |
8368 | diffFlowListProfiles = dynamic_cast<TList*>(diffFlowList->FindObject("Profiles")); | |
8369 | if(!diffFlowListProfiles) | |
8370 | { | |
8371 | cout<<"WARNING: diffFlowListProfiles is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
8372 | exit(0); | |
8373 | } | |
8374 | // list holding nested lists containing 2D and 1D histograms with final results: | |
8375 | TList *diffFlowListResults = NULL; | |
8376 | diffFlowListResults = dynamic_cast<TList*>(diffFlowList->FindObject("Results")); | |
8377 | if(!diffFlowListResults) | |
8378 | { | |
8379 | cout<<"WARNING: diffFlowListResults is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
8380 | exit(0); | |
8381 | } | |
8382 | ||
8383 | // c) Get pointer to profile holding all flags for differential flow; | |
8384 | TString diffFlowFlagsName = "fDiffFlowFlags"; | |
8385 | diffFlowFlagsName += fAnalysisLabel->Data(); | |
8386 | TProfile *diffFlowFlags = dynamic_cast<TProfile*>(diffFlowList->FindObject(diffFlowFlagsName.Data())); | |
8387 | Bool_t bCalculate2DFlow = kFALSE; | |
8388 | if(diffFlowFlags) | |
8389 | { | |
8390 | this->SetDiffFlowFlags(diffFlowFlags); | |
8391 | bCalculate2DFlow = (Int_t)diffFlowFlags->GetBinContent(4); | |
8392 | this->SetCalculate2DFlow(bCalculate2DFlow); // to be improved (shoul I call this setter somewhere else?) | |
8393 | } | |
8394 | ||
8395 | // d) Get pointers to all nested lists in fDiffFlowListProfiles and to profiles which they hold; | |
8396 | // correlations: | |
8397 | TList *diffFlowCorrelationsProList[2][2] = {{NULL}}; | |
8398 | TString diffFlowCorrelationsProName = "fDiffFlowCorrelationsPro"; | |
8399 | diffFlowCorrelationsProName += fAnalysisLabel->Data(); | |
b40a910e | 8400 | TProfile *diffFlowCorrelationsPro[2][2][4] = {{{NULL}}}; |
8401 | // squared correlations: | |
8402 | TString diffFlowSquaredCorrelationsProName = "fDiffFlowSquaredCorrelationsPro"; | |
8403 | diffFlowSquaredCorrelationsProName += fAnalysisLabel->Data(); | |
8404 | TProfile *diffFlowSquaredCorrelationsPro[2][2][4] = {{{NULL}}}; | |
489d5531 | 8405 | // products of correlations: |
8406 | TList *diffFlowProductOfCorrelationsProList[2][2] = {{NULL}}; | |
8407 | TString diffFlowProductOfCorrelationsProName = "fDiffFlowProductOfCorrelationsPro"; | |
8408 | diffFlowProductOfCorrelationsProName += fAnalysisLabel->Data(); | |
8409 | TProfile *diffFlowProductOfCorrelationsPro[2][2][8][8] = {{{{NULL}}}}; | |
8410 | // corrections: | |
8411 | TList *diffFlowCorrectionsProList[2][2] = {{NULL}}; | |
8412 | TString diffFlowCorrectionTermsForNUAProName = "fDiffFlowCorrectionTermsForNUAPro"; | |
8413 | diffFlowCorrectionTermsForNUAProName += fAnalysisLabel->Data(); | |
8414 | TProfile *diffFlowCorrectionTermsForNUAPro[2][2][2][10] = {{{{NULL}}}}; | |
8415 | for(Int_t t=0;t<2;t++) | |
8416 | { | |
8417 | for(Int_t pe=0;pe<2;pe++) | |
8418 | { | |
8419 | diffFlowCorrelationsProList[t][pe] = dynamic_cast<TList*>(diffFlowListProfiles->FindObject(Form("Profiles with correlations (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data()))); | |
8420 | if(!diffFlowCorrelationsProList[t][pe]) | |
8421 | { | |
8422 | cout<<"WARNING: diffFlowCorrelationsProList[t][pe] is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
8423 | cout<<"t = "<<t<<endl; | |
8424 | cout<<"pe = "<<pe<<endl; | |
8425 | exit(0); | |
8426 | } | |
8427 | for(Int_t ci=0;ci<4;ci++) // correlation index | |
8428 | { | |
b40a910e | 8429 | // reduced correlations: |
489d5531 | 8430 | diffFlowCorrelationsPro[t][pe][ci] = dynamic_cast<TProfile*>(diffFlowCorrelationsProList[t][pe]->FindObject(Form("%s, %s, %s, %s",diffFlowCorrelationsProName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedCorrelationIndex[ci].Data()))); |
8431 | if(diffFlowCorrelationsPro[t][pe][ci]) | |
8432 | { | |
8433 | this->SetDiffFlowCorrelationsPro(diffFlowCorrelationsPro[t][pe][ci],t,pe,ci); | |
8434 | } else | |
8435 | { | |
8436 | cout<<"WARNING: diffFlowCorrelationsPro[t][pe][ci] is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
8437 | cout<<"t = "<<t<<endl; | |
8438 | cout<<"pe = "<<pe<<endl; | |
8439 | cout<<"ci = "<<ci<<endl; | |
8440 | } | |
b40a910e | 8441 | // reduced squared correlations: |
8442 | diffFlowSquaredCorrelationsPro[t][pe][ci] = dynamic_cast<TProfile*>(diffFlowCorrelationsProList[t][pe]->FindObject(Form("%s, %s, %s, %s",diffFlowSquaredCorrelationsProName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedSquaredCorrelationIndex[ci].Data()))); | |
8443 | if(diffFlowSquaredCorrelationsPro[t][pe][ci]) | |
8444 | { | |
8445 | this->SetDiffFlowSquaredCorrelationsPro(diffFlowSquaredCorrelationsPro[t][pe][ci],t,pe,ci); | |
8446 | } else | |
8447 | { | |
8448 | cout<<"WARNING: diffFlowSquaredCorrelationsPro[t][pe][ci] is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
8449 | cout<<"t = "<<t<<endl; | |
8450 | cout<<"pe = "<<pe<<endl; | |
8451 | cout<<"ci = "<<ci<<endl; | |
8452 | } | |
489d5531 | 8453 | } // end of for(Int_t ci=0;ci<4;ci++) // correlation index |
8454 | // products of correlations: | |
8455 | diffFlowProductOfCorrelationsProList[t][pe] = dynamic_cast<TList*>(diffFlowListProfiles->FindObject(Form("Profiles with products of correlations (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data()))); | |
8456 | if(!diffFlowProductOfCorrelationsProList[t][pe]) | |
8457 | { | |
8458 | cout<<"WARNING: ddiffFlowProductOfCorrelationsProList[t][pe] is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
8459 | cout<<"t = "<<t<<endl; | |
8460 | cout<<"pe = "<<pe<<endl; | |
8461 | exit(0); | |
8462 | } | |
8463 | for(Int_t mci1=0;mci1<8;mci1++) // mixed correlation index | |
8464 | { | |
8465 | for(Int_t mci2=mci1+1;mci2<8;mci2++) // mixed correlation index | |
8466 | { | |
8467 | diffFlowProductOfCorrelationsPro[t][pe][mci1][mci2] = dynamic_cast<TProfile*>(diffFlowProductOfCorrelationsProList[t][pe]->FindObject(Form("%s, %s, %s, %s, %s",diffFlowProductOfCorrelationsProName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),mixedCorrelationIndex[mci1].Data(),mixedCorrelationIndex[mci2].Data()))); | |
8468 | if(diffFlowProductOfCorrelationsPro[t][pe][mci1][mci2]) | |
8469 | { | |
8470 | this->SetDiffFlowProductOfCorrelationsPro(diffFlowProductOfCorrelationsPro[t][pe][mci1][mci2],t,pe,mci1,mci2); | |
8471 | } else | |
8472 | { | |
b40a910e | 8473 | cout<<"WARNING: diffFlowProductOfCorrelationsPro[t][pe][ci] is NULL in AFAWQC::GPFDFH() !!!!"<<endl; |
489d5531 | 8474 | cout<<"t = "<<t<<endl; |
8475 | cout<<"pe = "<<pe<<endl; | |
8476 | cout<<"mci1 = "<<mci1<<endl; | |
8477 | cout<<"mci2 = "<<mci2<<endl; | |
8478 | } | |
8479 | if(mci1%2 == 0) mci2++; // products which DO NOT include reduced correlations are not stored here | |
8480 | } // end of for(Int_t mci2=mci1+1;mci2<8;mci2++) // mixed correlation index | |
8481 | } // end of for(Int_t mci1=0;mci1<8;mci1++) // mixed correlation index | |
8482 | // corrections: | |
8483 | diffFlowCorrectionsProList[t][pe] = dynamic_cast<TList*>(diffFlowListProfiles->FindObject(Form("Profiles with correction terms for NUA (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data()))); | |
8484 | if(!diffFlowCorrectionsProList[t][pe]) | |
8485 | { | |
8486 | cout<<"WARNING: diffFlowCorrectionsProList[t][pe] is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
8487 | cout<<"t = "<<t<<endl; | |
8488 | cout<<"pe = "<<pe<<endl; | |
8489 | exit(0); | |
8490 | } | |
8491 | // correction terms for NUA: | |
8492 | for(Int_t sc=0;sc<2;sc++) // sin or cos | |
8493 | { | |
8494 | for(Int_t cti=0;cti<9;cti++) // correction term index | |
8495 | { | |
8496 | diffFlowCorrectionTermsForNUAPro[t][pe][sc][cti] = dynamic_cast<TProfile*>(diffFlowCorrectionsProList[t][pe]->FindObject(Form("%s, %s, %s, %s, cti = %d",diffFlowCorrectionTermsForNUAProName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),sinCosFlag[sc].Data(),cti+1))); | |
8497 | if(diffFlowCorrectionTermsForNUAPro[t][pe][sc][cti]) | |
8498 | { | |
8499 | this->SetDiffFlowCorrectionTermsForNUAPro(diffFlowCorrectionTermsForNUAPro[t][pe][sc][cti],t,pe,sc,cti); | |
8500 | } else | |
8501 | { | |
8502 | cout<<"WARNING: diffFlowCorrectionTermsForNUAPro[t][pe][sc][cti] is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
8503 | cout<<"t = "<<t<<endl; | |
8504 | cout<<"pe = "<<pe<<endl; | |
8505 | cout<<"sc = "<<sc<<endl; | |
8506 | cout<<"cti = "<<cti<<endl; | |
8507 | } | |
8508 | } // end of for(Int_t cti=0;cti<9;cti++) // correction term index | |
8509 | } // end of for(Int_t sc=0;sc<2;sc++) // sin or cos | |
8510 | // ... | |
8511 | } // end of for(Int_t pe=0;pe<2;pe++) | |
8512 | } // end of for(Int_t t=0;t<2;t++) | |
8513 | ||
8514 | // e) Get pointers to all nested lists in fDiffFlowListResults and to histograms which they hold. | |
8515 | // reduced correlations: | |
8516 | TList *diffFlowCorrelationsHistList[2][2] = {{NULL}}; | |
8517 | TString diffFlowCorrelationsHistName = "fDiffFlowCorrelationsHist"; | |
8518 | diffFlowCorrelationsHistName += fAnalysisLabel->Data(); | |
8519 | TH1D *diffFlowCorrelationsHist[2][2][4] = {{{NULL}}}; | |
8520 | // corrections for NUA: | |
8521 | TList *diffFlowCorrectionsHistList[2][2] = {{NULL}}; | |
8522 | TString diffFlowCorrectionTermsForNUAHistName = "fDiffFlowCorrectionTermsForNUAHist"; | |
8523 | diffFlowCorrectionTermsForNUAHistName += fAnalysisLabel->Data(); | |
8524 | TH1D *diffFlowCorrectionTermsForNUAHist[2][2][2][10] = {{{{NULL}}}}; | |
8525 | // differential Q-cumulants: | |
8526 | TList *diffFlowCumulantsHistList[2][2] = {{NULL}}; | |
8527 | TString diffFlowCumulantsName = "fDiffFlowCumulants"; | |
8528 | diffFlowCumulantsName += fAnalysisLabel->Data(); | |
8529 | TH1D *diffFlowCumulants[2][2][4] = {{{NULL}}}; | |
8530 | // differential flow estimates from Q-cumulants: | |
8531 | TList *diffFlowHistList[2][2] = {{NULL}}; | |
8532 | TString diffFlowName = "fDiffFlow"; | |
8533 | diffFlowName += fAnalysisLabel->Data(); | |
8534 | TH1D *diffFlow[2][2][4] = {{{NULL}}}; | |
8535 | // differential covariances: | |
8536 | TList *diffFlowCovariancesHistList[2][2] = {{NULL}}; | |
8537 | TString diffFlowCovariancesName = "fDiffFlowCovariances"; | |
8538 | diffFlowCovariancesName += fAnalysisLabel->Data(); | |
8539 | TH1D *diffFlowCovariances[2][2][5] = {{{NULL}}}; | |
8540 | for(Int_t t=0;t<2;t++) // type: RP or POI | |
8541 | { | |
8542 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
8543 | { | |
8544 | // reduced correlations: | |
8545 | diffFlowCorrelationsHistList[t][pe] = dynamic_cast<TList*>(diffFlowListResults->FindObject(Form("Correlations (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data()))); | |
8546 | if(!diffFlowCorrelationsHistList[t][pe]) | |
8547 | { | |
8548 | cout<<"WARNING: diffFlowCorrelationsHistList[t][pe] is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
8549 | cout<<"t = "<<t<<endl; | |
8550 | cout<<"pe = "<<pe<<endl; | |
8551 | exit(0); | |
8552 | } | |
8553 | for(Int_t index=0;index<4;index++) | |
8554 | { | |
8555 | diffFlowCorrelationsHist[t][pe][index] = dynamic_cast<TH1D*>(diffFlowCorrelationsHistList[t][pe]->FindObject(Form("%s, %s, %s, %s",diffFlowCorrelationsHistName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedCorrelationIndex[index].Data()))); | |
8556 | if(diffFlowCorrelationsHist[t][pe][index]) | |
8557 | { | |
8558 | this->SetDiffFlowCorrelationsHist(diffFlowCorrelationsHist[t][pe][index],t,pe,index); | |
8559 | } else | |
8560 | { | |
8561 | cout<<"WARNING: diffFlowCorrelationsHist[t][pe][index] is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
8562 | cout<<"t = "<<t<<endl; | |
8563 | cout<<"pe = "<<pe<<endl; | |
8564 | cout<<"index = "<<index<<endl; | |
8565 | exit(0); | |
8566 | } | |
8567 | } // end of for(Int_t index=0;index<4;index++) | |
8568 | // corrections: | |
8569 | diffFlowCorrectionsHistList[t][pe] = dynamic_cast<TList*>(diffFlowListResults->FindObject(Form("Histograms with correction terms for NUA (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data()))); | |
8570 | if(!diffFlowCorrectionsHistList[t][pe]) | |
8571 | { | |
8572 | cout<<"WARNING: diffFlowCorrectionsHistList[t][pe] is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
8573 | cout<<"t = "<<t<<endl; | |
8574 | cout<<"pe = "<<pe<<endl; | |
8575 | exit(0); | |
8576 | } | |
8577 | // correction terms for NUA: | |
8578 | for(Int_t sc=0;sc<2;sc++) // sin or cos | |
8579 | { | |
8580 | for(Int_t cti=0;cti<9;cti++) // correction term index | |
8581 | { | |
8582 | diffFlowCorrectionTermsForNUAHist[t][pe][sc][cti] = dynamic_cast<TH1D*>(diffFlowCorrectionsHistList[t][pe]->FindObject(Form("%s, %s, %s, %s, cti = %d",diffFlowCorrectionTermsForNUAHistName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),sinCosFlag[sc].Data(),cti+1))); | |
8583 | if(diffFlowCorrectionTermsForNUAHist[t][pe][sc][cti]) | |
8584 | { | |
8585 | this->SetDiffFlowCorrectionTermsForNUAHist(diffFlowCorrectionTermsForNUAHist[t][pe][sc][cti],t,pe,sc,cti); | |
8586 | } else | |
8587 | { | |
8588 | cout<<"WARNING: diffFlowCorrectionTermsForNUAHist[t][pe][sc][cti] is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
8589 | cout<<"t = "<<t<<endl; | |
8590 | cout<<"pe = "<<pe<<endl; | |
8591 | cout<<"sc = "<<sc<<endl; | |
8592 | cout<<"cti = "<<cti<<endl; | |
8593 | } | |
8594 | } // end of for(Int_t cti=0;cti<9;cti++) // correction term index | |
8595 | } // end of for(Int_t sc=0;sc<2;sc++) // sin or cos | |
8596 | // ... | |
8597 | // differential Q-cumulants: | |
8598 | diffFlowCumulantsHistList[t][pe] = dynamic_cast<TList*>(diffFlowListResults->FindObject(Form("Differential Q-cumulants (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data()))); | |
8599 | if(!diffFlowCumulantsHistList[t][pe]) | |
8600 | { | |
8601 | cout<<"WARNING: diffFlowCumulantsHistList[t][pe] is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
8602 | cout<<"t = "<<t<<endl; | |
8603 | cout<<"pe = "<<pe<<endl; | |
8604 | exit(0); | |
8605 | } | |
8606 | for(Int_t index=0;index<4;index++) | |
8607 | { | |
8608 | diffFlowCumulants[t][pe][index] = dynamic_cast<TH1D*>(diffFlowCumulantsHistList[t][pe]->FindObject(Form("%s, %s, %s, %s",diffFlowCumulantsName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),differentialCumulantIndex[index].Data()))); | |
8609 | if(diffFlowCumulants[t][pe][index]) | |
8610 | { | |
8611 | this->SetDiffFlowCumulants(diffFlowCumulants[t][pe][index],t,pe,index); | |
8612 | } else | |
8613 | { | |
8614 | cout<<"WARNING: diffFlowCumulants[t][pe][index] is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
8615 | cout<<"t = "<<t<<endl; | |
8616 | cout<<"pe = "<<pe<<endl; | |
8617 | cout<<"index = "<<index<<endl; | |
8618 | exit(0); | |
8619 | } | |
8620 | } // end of for(Int_t index=0;index<4;index++) | |
8621 | // differential flow estimates from Q-cumulants: | |
8622 | diffFlowHistList[t][pe] = dynamic_cast<TList*>(diffFlowListResults->FindObject(Form("Differential flow (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data()))); | |
8623 | if(!diffFlowHistList[t][pe]) | |
8624 | { | |
8625 | cout<<"WARNING: diffFlowHistList[t][pe] is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
8626 | cout<<"t = "<<t<<endl; | |
8627 | cout<<"pe = "<<pe<<endl; | |
8628 | exit(0); | |
8629 | } | |
8630 | for(Int_t index=0;index<4;index++) | |
8631 | { | |
8632 | diffFlow[t][pe][index] = dynamic_cast<TH1D*>(diffFlowHistList[t][pe]->FindObject(Form("%s, %s, %s, %s",diffFlowName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),differentialFlowIndex[index].Data()))); | |
8633 | if(diffFlow[t][pe][index]) | |
8634 | { | |
8635 | this->SetDiffFlow(diffFlow[t][pe][index],t,pe,index); | |
8636 | } else | |
8637 | { | |
8638 | cout<<"WARNING: diffFlow[t][pe][index] is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
8639 | cout<<"t = "<<t<<endl; | |
8640 | cout<<"pe = "<<pe<<endl; | |
8641 | cout<<"index = "<<index<<endl; | |
8642 | exit(0); | |
8643 | } | |
8644 | } // end of for(Int_t index=0;index<4;index++) | |
8645 | // differential covariances: | |
8646 | diffFlowCovariancesHistList[t][pe] = dynamic_cast<TList*>(diffFlowListResults->FindObject(Form("Covariances of correlations (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data()))); | |
8647 | if(!diffFlowCovariancesHistList[t][pe]) | |
8648 | { | |
8649 | cout<<"WARNING: diffFlowCovariancesHistList[t][pe] is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
8650 | cout<<"t = "<<t<<endl; | |
8651 | cout<<"pe = "<<pe<<endl; | |
8652 | exit(0); | |
8653 | } | |
8654 | for(Int_t covIndex=0;covIndex<5;covIndex++) | |
8655 | { | |
8656 | diffFlowCovariances[t][pe][covIndex] = dynamic_cast<TH1D*>(diffFlowCovariancesHistList[t][pe]->FindObject(Form("%s, %s, %s, %s",diffFlowCovariancesName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),covarianceName[covIndex].Data()))); | |
8657 | if(diffFlowCovariances[t][pe][covIndex]) | |
8658 | { | |
8659 | this->SetDiffFlowCovariances(diffFlowCovariances[t][pe][covIndex],t,pe,covIndex); | |
8660 | } else | |
8661 | { | |
8662 | cout<<"WARNING: diffFlowCovariances[t][pe][covIndex] is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
8663 | cout<<"t = "<<t<<endl; | |
8664 | cout<<"pe = "<<pe<<endl; | |
8665 | cout<<"covIndex = "<<covIndex<<endl; | |
8666 | exit(0); | |
8667 | } | |
8668 | } // end of for(Int_t covIndex=0;covIndex<5;covIndex++) // covariance index | |
8669 | } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta | |
8670 | } // end of for(Int_t t=0;t<2;t++) // type: RP or POI | |
8671 | // sum of event weights for reduced correlations: | |
8672 | TList *diffFlowSumOfEventWeightsHistList[2][2][2] = {{{NULL}}}; | |
8673 | TString diffFlowSumOfEventWeightsName = "fDiffFlowSumOfEventWeights"; | |
8674 | diffFlowSumOfEventWeightsName += fAnalysisLabel->Data(); | |
8675 | TH1D *diffFlowSumOfEventWeights[2][2][2][4] = {{{{NULL}}}}; | |
8676 | for(Int_t t=0;t<2;t++) // type is RP or POI | |
8677 | { | |
8678 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
8679 | { | |
8680 | for(Int_t p=0;p<2;p++) // power of event weights is either 1 or 2 | |
8681 | { | |
8682 | diffFlowSumOfEventWeightsHistList[t][pe][p] = dynamic_cast<TList*>(diffFlowListResults->FindObject(Form("Sum of %s event weights (%s, %s)",powerFlag[p].Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data()))); | |
8683 | if(!diffFlowSumOfEventWeightsHistList[t][pe][p]) | |
8684 | { | |
8685 | cout<<"WARNING: diffFlowSumOfEventWeightsHistList[t][pe][p] is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
8686 | cout<<"t = "<<t<<endl; | |
8687 | cout<<"pe = "<<pe<<endl; | |
8688 | cout<<"power = "<<p<<endl; | |
8689 | exit(0); | |
8690 | } | |
8691 | for(Int_t ew=0;ew<4;ew++) // index of reduced correlation | |
8692 | { | |
8693 | diffFlowSumOfEventWeights[t][pe][p][ew] = dynamic_cast<TH1D*>(diffFlowSumOfEventWeightsHistList[t][pe][p]->FindObject(Form("%s, %s, %s, %s, %s",diffFlowSumOfEventWeightsName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),powerFlag[p].Data(),reducedCorrelationIndex[ew].Data()))); | |
8694 | if(diffFlowSumOfEventWeights[t][pe][p][ew]) | |
8695 | { | |
8696 | this->SetDiffFlowSumOfEventWeights(diffFlowSumOfEventWeights[t][pe][p][ew],t,pe,p,ew); | |
8697 | } else | |
8698 | { | |
8699 | cout<<"WARNING: diffFlowSumOfEventWeights[t][pe][p][ew] is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
8700 | cout<<"t = "<<t<<endl; | |
8701 | cout<<"pe = "<<pe<<endl; | |
8702 | cout<<"power = "<<p<<endl; | |
8703 | cout<<"ew = "<<ew<<endl; | |
8704 | exit(0); | |
8705 | } | |
8706 | } | |
8707 | } // end of for(Int_t p=0;p<2;p++) // power of event weights is either 1 or 2 | |
8708 | } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta | |
8709 | } // end of for(Int_t t=0;t<2;t++) // type is RP or POI | |
8710 | // | |
8711 | TList *diffFlowSumOfProductOfEventWeightsHistList[2][2] = {{NULL}}; | |
8712 | TString diffFlowSumOfProductOfEventWeightsName = "fDiffFlowSumOfProductOfEventWeights"; | |
8713 | diffFlowSumOfProductOfEventWeightsName += fAnalysisLabel->Data(); | |
8714 | TH1D *diffFlowSumOfProductOfEventWeights[2][2][8][8] = {{{{NULL}}}}; | |
8715 | for(Int_t t=0;t<2;t++) // type is RP or POI | |
8716 | { | |
8717 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
8718 | { | |
8719 | diffFlowSumOfProductOfEventWeightsHistList[t][pe] = dynamic_cast<TList*>(diffFlowListResults->FindObject(Form("Sum of products of event weights (%s, %s)",typeFlag[t].Data(),ptEtaFlag[pe].Data()))); | |
8720 | if(!diffFlowSumOfProductOfEventWeightsHistList[t][pe]) | |
8721 | { | |
8722 | cout<<"WARNING: diffFlowSumOfProductOfEventWeightsHistList[t][pe] is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
8723 | cout<<"t = "<<t<<endl; | |
8724 | cout<<"pe = "<<pe<<endl; | |
8725 | exit(0); | |
8726 | } | |
8727 | for(Int_t mci1=0;mci1<8;mci1++) // mixed correlation index | |
8728 | { | |
8729 | for(Int_t mci2=mci1+1;mci2<8;mci2++) // mixed correlation index | |
8730 | { | |
8731 | diffFlowSumOfProductOfEventWeights[t][pe][mci1][mci2] = dynamic_cast<TH1D*>(diffFlowSumOfProductOfEventWeightsHistList[t][pe]->FindObject(Form("%s, %s, %s, %s, %s",diffFlowSumOfProductOfEventWeightsName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),mixedCorrelationIndex[mci1].Data(),mixedCorrelationIndex[mci2].Data()))); | |
8732 | if(diffFlowSumOfProductOfEventWeights[t][pe][mci1][mci2]) | |
8733 | { | |
8734 | this->SetDiffFlowSumOfProductOfEventWeights(diffFlowSumOfProductOfEventWeights[t][pe][mci1][mci2],t,pe,mci1,mci2); | |
8735 | } else | |
8736 | { | |
8737 | cout<<"WARNING: diffFlowSumOfProductOfEventWeights[t][pe][mci1][mci2] is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
8738 | cout<<"t = "<<t<<endl; | |
8739 | cout<<"pe = "<<pe<<endl; | |
8740 | cout<<"mci1 = "<<mci1<<endl; | |
8741 | cout<<"mci2 = "<<mci2<<endl; | |
8742 | exit(0); | |
8743 | } | |
8744 | if(mci1%2 == 0) mci2++; // products which DO NOT include reduced correlations are not stored here | |
8745 | } // end of for(Int_t mci2=mci1+1;mci2<8;mci2++) // mixed correlation index | |
8746 | } // end of for(Int_t mci1=0;mci1<8;mci1++) // mixed correlation index | |
8747 | } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta | |
8748 | } // end of for(Int_t t=0;t<2;t++) // type is RP or POI | |
8749 | ||
8750 | } // end void AliFlowAnalysisWithQCumulants::GetPointersForDiffFlowHistograms() | |
8751 | ||
8752 | ||
8753 | //================================================================================================================================ | |
8754 | ||
8755 | ||
8756 | void AliFlowAnalysisWithQCumulants::BookEverythingForDifferentialFlow() | |
8757 | { | |
8758 | // Book all histograms and profiles needed for differential flow. | |
8759 | // a) Define flags locally (to be improved: should I promote flags to data members?); | |
8760 | // b) Book profile to hold all flags for differential flow; | |
8761 | // c) Book e-b-e quantities; | |
8762 | // d) Book profiles; | |
8763 | // e) Book histograms holding final results. | |
8764 | ||
8765 | // a) Define flags locally (to be improved: should I promote flags to data members?): | |
8766 | TString typeFlag[2] = {"RP","POI"}; | |
8767 | TString ptEtaFlag[2] = {"p_{T}","#eta"}; | |
8768 | TString powerFlag[2] = {"linear","quadratic"}; | |
8769 | TString sinCosFlag[2] = {"sin","cos"}; | |
8770 | TString differentialCumulantIndex[4] = {"QC{2'}","QC{4'}","QC{6'}","QC{8'}"}; | |
8771 | TString differentialFlowIndex[4] = {"v'{2}","v'{4}","v'{6}","v'{8}"}; | |
8772 | TString reducedCorrelationIndex[4] = {"<2'>","<4'>","<6'>","<8'>"}; | |
b40a910e | 8773 | TString reducedSquaredCorrelationIndex[4] = {"<2'>^{2}","<4'>^{2}","<6'>^{2}","<8'>^{2}"}; |
489d5531 | 8774 | TString mixedCorrelationIndex[8] = {"<2>","<2'>","<4>","<4'>","<6>","<6'>","<8>","<8'>"}; |
8775 | TString covarianceName[5] = {"Cov(<2>,<2'>)","Cov(<2>,<4'>)","Cov(<4>,<2'>)","Cov(<4>,<4'>)","Cov(<2'>,<4'>)"}; | |
8776 | Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; | |
8777 | Double_t minPtEta[2] = {fPtMin,fEtaMin}; | |
8778 | Double_t maxPtEta[2] = {fPtMax,fEtaMax}; | |
8779 | ||
8780 | // b) Book profile to hold all flags for differential flow: | |
8781 | TString diffFlowFlagsName = "fDiffFlowFlags"; | |
8782 | diffFlowFlagsName += fAnalysisLabel->Data(); | |
8783 | fDiffFlowFlags = new TProfile(diffFlowFlagsName.Data(),"Flags for Differential Flow",4,0,4); | |
8784 | fDiffFlowFlags->SetTickLength(-0.01,"Y"); | |
8785 | fDiffFlowFlags->SetMarkerStyle(25); | |
8786 | fDiffFlowFlags->SetLabelSize(0.05); | |
8787 | fDiffFlowFlags->SetLabelOffset(0.02,"Y"); | |
8788 | (fDiffFlowFlags->GetXaxis())->SetBinLabel(1,"Particle Weights"); | |
8789 | (fDiffFlowFlags->GetXaxis())->SetBinLabel(2,"Event Weights"); | |
8790 | (fDiffFlowFlags->GetXaxis())->SetBinLabel(3,"Corrected for NUA?"); | |
8791 | (fDiffFlowFlags->GetXaxis())->SetBinLabel(4,"Calculated 2D flow?"); | |
8792 | fDiffFlowList->Add(fDiffFlowFlags); | |
8793 | ||
8794 | // c) Book e-b-e quantities: | |
8795 | // Event-by-event r_{m*n,k}(pt,eta), p_{m*n,k}(pt,eta) and q_{m*n,k}(pt,eta) | |
8796 | // Explanantion of notation: | |
8797 | // 1.) n is harmonic, m is multiple of harmonic; | |
8798 | // 2.) k is power of particle weight; | |
8799 | // 3.) r_{m*n,k}(pt,eta) = Q-vector evaluated in harmonic m*n for RPs in particular (pt,eta) bin (i-th RP is weighted with w_i^k); | |
8800 | // 4.) p_{m*n,k}(pt,eta) = Q-vector evaluated in harmonic m*n for POIs in particular (pt,eta) bin | |
8801 | // (if i-th POI is also RP, than it is weighted with w_i^k); | |
8802 | // 5.) q_{m*n,k}(pt,eta) = Q-vector evaluated in harmonic m*n for particles which are both RPs and POIs in particular (pt,eta) bin | |
8803 | // (i-th RP&&POI is weighted with w_i^k) | |
8804 | ||
8805 | // 1D: | |
8806 | for(Int_t t=0;t<3;t++) // typeFlag (0 = RP, 1 = POI, 2 = RP && POI ) | |
8807 | { | |
8808 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
8809 | { | |
8810 | for(Int_t m=0;m<4;m++) // multiple of harmonic | |
8811 | { | |
8812 | for(Int_t k=0;k<9;k++) // power of particle weight | |
8813 | { | |
8814 | fReRPQ1dEBE[t][pe][m][k] = new TProfile(Form("TypeFlag%dpteta%dmultiple%dpower%dRe",t,pe,m,k), | |
8815 | Form("TypeFlag%dpteta%dmultiple%dpower%dRe",t,pe,m,k),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); | |
8816 | fImRPQ1dEBE[t][pe][m][k] = new TProfile(Form("TypeFlag%dpteta%dmultiple%dpower%dIm",t,pe,m,k), | |
8817 | Form("TypeFlag%dpteta%dmultiple%dpower%dIm",t,pe,m,k),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); | |
8818 | } | |
8819 | } | |
8820 | } | |
8821 | } | |
8822 | // to be improved (add explanation of fs1dEBE[t][pe][k]): | |
8823 | for(Int_t t=0;t<3;t++) // typeFlag (0 = RP, 1 = POI, 2 = RP&&POI ) | |
8824 | { | |
8825 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
8826 | { | |
8827 | for(Int_t k=0;k<9;k++) // power of particle weight | |
8828 | { | |
8829 | fs1dEBE[t][pe][k] = new TProfile(Form("TypeFlag%dpteta%dmultiple%d",t,pe,k), | |
8830 | Form("TypeFlag%dpteta%dmultiple%d",t,pe,k),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); | |
8831 | } | |
8832 | } | |
8833 | } | |
8834 | // correction terms for nua: | |
8835 | for(Int_t t=0;t<2;t++) // typeFlag (0 = RP, 1 = POI) | |
8836 | { | |
8837 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
8838 | { | |
8839 | for(Int_t sc=0;sc<2;sc++) // sin or cos | |
8840 | { | |
8841 | for(Int_t cti=0;cti<9;cti++) // correction term index | |
8842 | { | |
8843 | fDiffFlowCorrectionTermsForNUAEBE[t][pe][sc][cti] = new TH1D(Form("typeFlag%d pteta%d sincos%d cti%d",t,pe,sc,cti), | |
8844 | Form("typeFlag%d pteta%d sincos%d cti%d",t,pe,sc,cti),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); | |
8845 | } | |
8846 | } | |
8847 | } | |
8848 | } | |
8849 | // 2D: | |
b77b6434 | 8850 | if(fCalculate2DFlow) |
8851 | { | |
8852 | TProfile2D styleRe("typeMultiplePowerRe","typeMultiplePowerRe",fnBinsPt,fPtMin,fPtMax,fnBinsEta,fEtaMin,fEtaMax); | |
8853 | TProfile2D styleIm("typeMultiplePowerIm","typeMultiplePowerIm",fnBinsPt,fPtMin,fPtMax,fnBinsEta,fEtaMin,fEtaMax); | |
8854 | for(Int_t t=0;t<3;t++) // typeFlag (0 = RP, 1 = POI, 2 = RP&&POI ) | |
8855 | { | |
8856 | for(Int_t m=0;m<4;m++) | |
8857 | { | |
8858 | for(Int_t k=0;k<9;k++) | |
8859 | { | |
8860 | fReRPQ2dEBE[t][m][k] = (TProfile2D*)styleRe.Clone(Form("typeFlag%dmultiple%dpower%dRe",t,m,k)); | |
8861 | fImRPQ2dEBE[t][m][k] = (TProfile2D*)styleIm.Clone(Form("typeFlag%dmultiple%dpower%dIm",t,m,k)); | |
8862 | } | |
8863 | } | |
8864 | } | |
8865 | TProfile2D styleS("typePower","typePower",fnBinsPt,fPtMin,fPtMax,fnBinsEta,fEtaMin,fEtaMax); | |
8866 | for(Int_t t=0;t<3;t++) // typeFlag (0 = RP, 1 = POI, 2 = RP&&POI ) | |
8867 | { | |
489d5531 | 8868 | for(Int_t k=0;k<9;k++) |
8869 | { | |
b77b6434 | 8870 | fs2dEBE[t][k] = (TProfile2D*)styleS.Clone(Form("typeFlag%dpower%d",t,k)); |
489d5531 | 8871 | } |
489d5531 | 8872 | } |
b77b6434 | 8873 | } // end of if(fCalculate2DFlow) |
489d5531 | 8874 | // reduced correlations e-b-e: |
8875 | TString diffFlowCorrelationsEBEName = "fDiffFlowCorrelationsEBE"; | |
8876 | diffFlowCorrelationsEBEName += fAnalysisLabel->Data(); | |
8877 | for(Int_t t=0;t<2;t++) // type: RP or POI | |
8878 | { | |
8879 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
8880 | { | |
8881 | for(Int_t rci=0;rci<4;rci++) // reduced correlation index | |
8882 | { | |
8883 | fDiffFlowCorrelationsEBE[t][pe][rci] = new TH1D(Form("%s, %s, %s, %s",diffFlowCorrelationsEBEName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedCorrelationIndex[rci].Data()),Form("%s, %s, %s, %s",diffFlowCorrelationsEBEName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedCorrelationIndex[rci].Data()),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); | |
8884 | } // end of for(Int_t ci=0;ci<4;ci++) // correlation index | |
8885 | } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta | |
8886 | } // end of for(Int_t t=0;t<2;t++) // type: RP or POI | |
8887 | // event weights for reduced correlations e-b-e: | |
8888 | TString diffFlowEventWeightsForCorrelationsEBEName = "fDiffFlowEventWeightsForCorrelationsEBE"; | |
8889 | diffFlowEventWeightsForCorrelationsEBEName += fAnalysisLabel->Data(); | |
8890 | for(Int_t t=0;t<2;t++) // type: RP or POI | |
8891 | { | |
8892 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
8893 | { | |
8894 | for(Int_t rci=0;rci<4;rci++) // event weight for reduced correlation index | |
8895 | { | |
8896 | fDiffFlowEventWeightsForCorrelationsEBE[t][pe][rci] = new TH1D(Form("%s, %s, %s, eW for %s",diffFlowEventWeightsForCorrelationsEBEName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedCorrelationIndex[rci].Data()),Form("%s, %s, %s, eW for %s",diffFlowEventWeightsForCorrelationsEBEName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedCorrelationIndex[rci].Data()),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); | |
8897 | } // end of for(Int_t ci=0;ci<4;ci++) // correlation index | |
8898 | } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta | |
8899 | } // end of for(Int_t t=0;t<2;t++) // type: RP or POI | |
8900 | ||
8901 | // d) Book profiles; | |
8902 | // reduced correlations: | |
8903 | TString diffFlowCorrelationsProName = "fDiffFlowCorrelationsPro"; | |
8904 | diffFlowCorrelationsProName += fAnalysisLabel->Data(); | |
b40a910e | 8905 | // reduced squared correlations: |
8906 | TString diffFlowSquaredCorrelationsProName = "fDiffFlowSquaredCorrelationsPro"; | |
8907 | diffFlowSquaredCorrelationsProName += fAnalysisLabel->Data(); | |
489d5531 | 8908 | // corrections terms: |
8909 | TString diffFlowCorrectionTermsForNUAProName = "fDiffFlowCorrectionTermsForNUAPro"; | |
8910 | diffFlowCorrectionTermsForNUAProName += fAnalysisLabel->Data(); | |
b40a910e | 8911 | // reduced correlations: |
489d5531 | 8912 | for(Int_t t=0;t<2;t++) // type: RP or POI |
8913 | { | |
8914 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
8915 | { | |
8916 | for(Int_t rci=0;rci<4;rci++) // reduced correlation index | |
8917 | { | |
489d5531 | 8918 | fDiffFlowCorrelationsPro[t][pe][rci] = new TProfile(Form("%s, %s, %s, %s",diffFlowCorrelationsProName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedCorrelationIndex[rci].Data()),Form("%s, %s, %s, %s",diffFlowCorrelationsProName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedCorrelationIndex[rci].Data()),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe],"s"); |
b40a910e | 8919 | fDiffFlowCorrelationsPro[t][pe][rci]->Sumw2(); |
489d5531 | 8920 | fDiffFlowCorrelationsPro[t][pe][rci]->SetXTitle(ptEtaFlag[pe].Data()); |
8921 | fDiffFlowCorrelationsProList[t][pe]->Add(fDiffFlowCorrelationsPro[t][pe][rci]); // to be improved (add dedicated list to hold reduced correlations) | |
8922 | } // end of for(Int_t rci=0;rci<4;rci++) // correlation index | |
8923 | } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta | |
8924 | } // end of for(Int_t t=0;t<2;t++) // type: RP or POI | |
b40a910e | 8925 | // reduced squared correlations: |
8926 | for(Int_t t=0;t<2;t++) // type: RP or POI | |
8927 | { | |
8928 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
8929 | { | |
8930 | for(Int_t rci=0;rci<4;rci++) // reduced correlation index | |
8931 | { | |
8932 | fDiffFlowSquaredCorrelationsPro[t][pe][rci] = new TProfile(Form("%s, %s, %s, %s",diffFlowSquaredCorrelationsProName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedSquaredCorrelationIndex[rci].Data()),Form("%s, %s, %s, %s",diffFlowSquaredCorrelationsProName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedSquaredCorrelationIndex[rci].Data()),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe],"s"); | |
8933 | fDiffFlowSquaredCorrelationsPro[t][pe][rci]->Sumw2(); | |
8934 | fDiffFlowSquaredCorrelationsPro[t][pe][rci]->SetXTitle(ptEtaFlag[pe].Data()); | |
8935 | fDiffFlowCorrelationsProList[t][pe]->Add(fDiffFlowSquaredCorrelationsPro[t][pe][rci]); // to be improved (add dedicated list to hold reduced correlations) | |
8936 | } // end of for(Int_t rci=0;rci<4;rci++) // correlation index | |
8937 | } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta | |
8938 | } // end of for(Int_t t=0;t<2;t++) // type: RP or POI | |
489d5531 | 8939 | // correction terms for nua: |
8940 | for(Int_t t=0;t<2;t++) // typeFlag (0 = RP, 1 = POI) | |
8941 | { | |
8942 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
8943 | { | |
8944 | for(Int_t sc=0;sc<2;sc++) // sin or cos | |
8945 | { | |
8946 | for(Int_t cti=0;cti<9;cti++) // correction term index | |
8947 | { | |
8948 | fDiffFlowCorrectionTermsForNUAPro[t][pe][sc][cti] = new TProfile(Form("%s, %s, %s, %s, cti = %d",diffFlowCorrectionTermsForNUAProName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),sinCosFlag[sc].Data(),cti+1),Form("%s, %s, %s, %s, cti = %d",diffFlowCorrectionTermsForNUAProName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),sinCosFlag[sc].Data(),cti+1),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); | |
8949 | fDiffFlowCorrectionsProList[t][pe]->Add(fDiffFlowCorrectionTermsForNUAPro[t][pe][sc][cti]); | |
8950 | } | |
8951 | } | |
8952 | } | |
8953 | } | |
8954 | // e) Book histograms holding final results. | |
8955 | // reduced correlations: | |
8956 | TString diffFlowCorrelationsHistName = "fDiffFlowCorrelationsHist"; | |
8957 | diffFlowCorrelationsHistName += fAnalysisLabel->Data(); | |
8958 | // corrections terms: | |
8959 | TString diffFlowCorrectionTermsForNUAHistName = "fDiffFlowCorrectionTermsForNUAHist"; | |
8960 | diffFlowCorrectionTermsForNUAHistName += fAnalysisLabel->Data(); | |
8961 | // differential covariances: | |
8962 | TString diffFlowCovariancesName = "fDiffFlowCovariances"; | |
8963 | diffFlowCovariancesName += fAnalysisLabel->Data(); | |
8964 | // differential Q-cumulants: | |
8965 | TString diffFlowCumulantsName = "fDiffFlowCumulants"; | |
8966 | diffFlowCumulantsName += fAnalysisLabel->Data(); | |
8967 | // differential flow: | |
8968 | TString diffFlowName = "fDiffFlow"; | |
8969 | diffFlowName += fAnalysisLabel->Data(); | |
8970 | for(Int_t t=0;t<2;t++) // type: RP or POI | |
8971 | { | |
8972 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
8973 | { | |
8974 | for(Int_t index=0;index<4;index++) | |
8975 | { | |
8976 | // reduced correlations: | |
8977 | fDiffFlowCorrelationsHist[t][pe][index] = new TH1D(Form("%s, %s, %s, %s",diffFlowCorrelationsHistName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedCorrelationIndex[index].Data()),Form("%s, %s, %s, %s",diffFlowCorrelationsHistName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedCorrelationIndex[index].Data()),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); | |
8978 | fDiffFlowCorrelationsHist[t][pe][index]->SetXTitle(ptEtaFlag[pe].Data()); | |
8979 | fDiffFlowCorrelationsHistList[t][pe]->Add(fDiffFlowCorrelationsHist[t][pe][index]); | |
8980 | // differential Q-cumulants: | |
8981 | fDiffFlowCumulants[t][pe][index] = new TH1D(Form("%s, %s, %s, %s",diffFlowCumulantsName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),differentialCumulantIndex[index].Data()),Form("%s, %s, %s, %s",diffFlowCumulantsName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),differentialCumulantIndex[index].Data()),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); | |
8982 | fDiffFlowCumulants[t][pe][index]->SetXTitle(ptEtaFlag[pe].Data()); | |
8983 | fDiffFlowCumulantsHistList[t][pe]->Add(fDiffFlowCumulants[t][pe][index]); | |
8984 | // differential flow estimates from Q-cumulants: | |
8985 | fDiffFlow[t][pe][index] = new TH1D(Form("%s, %s, %s, %s",diffFlowName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),differentialFlowIndex[index].Data()),Form("%s, %s, %s, %s",diffFlowName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),differentialFlowIndex[index].Data()),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); | |
8986 | fDiffFlow[t][pe][index]->SetXTitle(ptEtaFlag[pe].Data()); | |
8987 | fDiffFlowHistList[t][pe]->Add(fDiffFlow[t][pe][index]); | |
8988 | } // end of for(Int_t index=0;index<4;index++) | |
8989 | for(Int_t covIndex=0;covIndex<5;covIndex++) // covariance index | |
8990 | { | |
8991 | // differential covariances: | |
8992 | fDiffFlowCovariances[t][pe][covIndex] = new TH1D(Form("%s, %s, %s, %s",diffFlowCovariancesName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),covarianceName[covIndex].Data()),Form("%s, %s, %s, %s",diffFlowCovariancesName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),covarianceName[covIndex].Data()),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); | |
8993 | fDiffFlowCovariances[t][pe][covIndex]->SetXTitle(ptEtaFlag[pe].Data()); | |
8994 | fDiffFlowCovariancesHistList[t][pe]->Add(fDiffFlowCovariances[t][pe][covIndex]); | |
8995 | } // end of for(Int_t covIndex=0;covIndex<5;covIndex++) // covariance index | |
8996 | // products of both types of correlations: | |
8997 | TString diffFlowProductOfCorrelationsProName = "fDiffFlowProductOfCorrelationsPro"; | |
8998 | diffFlowProductOfCorrelationsProName += fAnalysisLabel->Data(); | |
8999 | for(Int_t mci1=0;mci1<8;mci1++) // mixed correlation index | |
9000 | { | |
9001 | for(Int_t mci2=mci1+1;mci2<8;mci2++) // mixed correlation index | |
9002 | { | |
9003 | fDiffFlowProductOfCorrelationsPro[t][pe][mci1][mci2] = new TProfile(Form("%s, %s, %s, %s, %s",diffFlowProductOfCorrelationsProName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),mixedCorrelationIndex[mci1].Data(),mixedCorrelationIndex[mci2].Data()),Form("%s, %s, %s, %s #times %s",diffFlowProductOfCorrelationsProName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),mixedCorrelationIndex[mci1].Data(),mixedCorrelationIndex[mci2].Data()),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); | |
9004 | fDiffFlowProductOfCorrelationsPro[t][pe][mci1][mci2]->SetXTitle(ptEtaFlag[pe].Data()); | |
9005 | fDiffFlowProductOfCorrelationsProList[t][pe]->Add(fDiffFlowProductOfCorrelationsPro[t][pe][mci1][mci2]); | |
9006 | if(mci1%2 == 0) mci2++; // products which DO NOT include reduced correlations are not stored here | |
9007 | } // end of for(Int_t mci2=mci1+1;mci2<8;mci2++) // mixed correlation index | |
9008 | } // end of for(Int_t mci1=0;mci1<8;mci1++) // mixed correlation index | |
9009 | } // end of for(Int_t pe=0;pe<2;pe++) // pt or eta | |
9010 | } // end of for(Int_t t=0;t<2;t++) // type: RP or POI | |
9011 | // sums of event weights for reduced correlations: | |
9012 | TString diffFlowSumOfEventWeightsName = "fDiffFlowSumOfEventWeights"; | |
9013 | diffFlowSumOfEventWeightsName += fAnalysisLabel->Data(); | |
9014 | for(Int_t t=0;t<2;t++) // type is RP or POI | |
9015 | { | |
9016 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
9017 | { | |
9018 | for(Int_t p=0;p<2;p++) // power of weights is either 1 or 2 | |
9019 | { | |
9020 | for(Int_t ew=0;ew<4;ew++) // index of reduced correlation | |
9021 | { | |
9022 | fDiffFlowSumOfEventWeights[t][pe][p][ew] = new TH1D(Form("%s, %s, %s, %s, %s",diffFlowSumOfEventWeightsName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),powerFlag[p].Data(),reducedCorrelationIndex[ew].Data()),Form("%s, %s, %s, power = %s, %s",diffFlowSumOfEventWeightsName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),powerFlag[p].Data(),reducedCorrelationIndex[ew].Data()),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); | |
9023 | fDiffFlowSumOfEventWeights[t][pe][p][ew]->SetXTitle(ptEtaFlag[pe].Data()); | |
9024 | fDiffFlowSumOfEventWeightsHistList[t][pe][p]->Add(fDiffFlowSumOfEventWeights[t][pe][p][ew]); // to be improved (add dedicated list to hold all this) | |
9025 | } | |
9026 | } | |
9027 | } | |
9028 | } | |
9029 | // sum of products of event weights for both types of correlations: | |
9030 | TString diffFlowSumOfProductOfEventWeightsName = "fDiffFlowSumOfProductOfEventWeights"; | |
9031 | diffFlowSumOfProductOfEventWeightsName += fAnalysisLabel->Data(); | |
9032 | for(Int_t t=0;t<2;t++) // type is RP or POI | |
9033 | { | |
9034 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
9035 | { | |
9036 | for(Int_t mci1=0;mci1<8;mci1++) // mixed correlation index | |
9037 | { | |
9038 | for(Int_t mci2=mci1+1;mci2<8;mci2++) // mixed correlation index | |
9039 | { | |
9040 | fDiffFlowSumOfProductOfEventWeights[t][pe][mci1][mci2] = new TH1D(Form("%s, %s, %s, %s, %s",diffFlowSumOfProductOfEventWeightsName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),mixedCorrelationIndex[mci1].Data(),mixedCorrelationIndex[mci2].Data()),Form("%s, %s, %s, %s #times %s",diffFlowSumOfProductOfEventWeightsName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),mixedCorrelationIndex[mci1].Data(),mixedCorrelationIndex[mci2].Data()),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); | |
9041 | fDiffFlowSumOfProductOfEventWeights[t][pe][mci1][mci2]->SetXTitle(ptEtaFlag[pe].Data()); | |
9042 | fDiffFlowSumOfProductOfEventWeightsHistList[t][pe]->Add(fDiffFlowSumOfProductOfEventWeights[t][pe][mci1][mci2]); | |
9043 | if(mci1%2 == 0) mci2++; // products which DO NOT include reduced correlations are not stored here | |
9044 | } | |
9045 | } | |
9046 | } | |
9047 | } | |
9048 | // correction terms for nua: | |
9049 | for(Int_t t=0;t<2;t++) // typeFlag (0 = RP, 1 = POI) | |
9050 | { | |
9051 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
9052 | { | |
9053 | for(Int_t sc=0;sc<2;sc++) // sin or cos | |
9054 | { | |
9055 | for(Int_t cti=0;cti<9;cti++) // correction term index | |
9056 | { | |
9057 | fDiffFlowCorrectionTermsForNUAHist[t][pe][sc][cti] = new TH1D(Form("%s, %s, %s, %s, cti = %d",diffFlowCorrectionTermsForNUAHistName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),sinCosFlag[sc].Data(),cti+1),Form("%s, %s, %s, %s, cti = %d",diffFlowCorrectionTermsForNUAHistName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),sinCosFlag[sc].Data(),cti+1),nBinsPtEta[pe],minPtEta[pe],maxPtEta[pe]); | |
9058 | fDiffFlowCorrectionsHistList[t][pe]->Add(fDiffFlowCorrectionTermsForNUAHist[t][pe][sc][cti]); | |
9059 | } | |
9060 | } | |
9061 | } | |
9062 | } | |
9063 | ||
9064 | } // end of AliFlowAnalysisWithQCumulants::BookEverythingForDifferentialFlow() | |
9065 | ||
489d5531 | 9066 | //================================================================================================================================ |
9067 | ||
489d5531 | 9068 | void AliFlowAnalysisWithQCumulants::CalculateQcumulantsCorrectedForNUAIntFlow() |
9069 | { | |
9070 | // Calculate generalized Q-cumulants (cumulants corrected for non-unifom acceptance). | |
9071 | ||
b92ea2b9 | 9072 | // Isotropic cumulants: |
9073 | Double_t QC2 = fIntFlowQcumulants->GetBinContent(1); | |
9074 | Double_t QC2Error = fIntFlowQcumulants->GetBinError(1); | |
9075 | Double_t QC4 = fIntFlowQcumulants->GetBinContent(2); | |
9076 | Double_t QC4Error = fIntFlowQcumulants->GetBinError(2); | |
9077 | //Double_t QC6 = fIntFlowQcumulants->GetBinContent(3); | |
9078 | //Double_t QC6Error = fIntFlowQcumulants->GetBinError(3); | |
9079 | //Double_t QC8 = fIntFlowQcumulants->GetBinContent(4); | |
9080 | //Double_t QC8Error = fIntFlowQcumulants->GetBinError(4); | |
9081 | ||
9082 | // Measured 2-, 4-, 6- and 8-particle correlations: | |
489d5531 | 9083 | Double_t two = fIntFlowCorrelationsHist->GetBinContent(1); // <<2>> |
b92ea2b9 | 9084 | Double_t twoError = fIntFlowCorrelationsHist->GetBinError(1); // statistical error of <<2>> |
489d5531 | 9085 | Double_t four = fIntFlowCorrelationsHist->GetBinContent(2); // <<4>> |
b92ea2b9 | 9086 | Double_t fourError = fIntFlowCorrelationsHist->GetBinError(2); // statistical error of <<4>> |
489d5531 | 9087 | //Double_t six = fIntFlowCorrelationsHist->GetBinContent(3); // <<6>> |
489d5531 | 9088 | //Double_t sixError = fIntFlowCorrelationsHist->GetBinError(3); // statistical error of <<6>> |
b92ea2b9 | 9089 | //Double_t eight = fIntFlowCorrelationsHist->GetBinContent(4); // <<8>> |
489d5531 | 9090 | //Double_t eightError = fIntFlowCorrelationsHist->GetBinError(4); // statistical error of <<8>> |
b92ea2b9 | 9091 | |
9092 | // Non-isotropic terms: | |
9093 | Double_t c1 = fIntFlowCorrectionTermsForNUAHist[1]->GetBinContent(1); // <<cos(n*phi1)>> | |
9094 | Double_t c1Error = fIntFlowCorrectionTermsForNUAHist[1]->GetBinError(1); // statistical error of <<cos(n*phi1)>> | |
9095 | Double_t c2 = fIntFlowCorrectionTermsForNUAHist[1]->GetBinContent(2); // <<cos(n*(phi1+phi2))>> | |
9096 | Double_t c2Error = fIntFlowCorrectionTermsForNUAHist[1]->GetBinError(2); // statistical error of <<cos(n*(phi1+phi2))>> | |
9097 | Double_t c3 = fIntFlowCorrectionTermsForNUAHist[1]->GetBinContent(3); // <<cos(n*(phi1-phi2-phi3))>> | |
9098 | Double_t c3Error = fIntFlowCorrectionTermsForNUAHist[1]->GetBinError(3); // statistical error of <<cos(n*(phi1-phi2-phi3))>> | |
9099 | Double_t s1 = fIntFlowCorrectionTermsForNUAHist[0]->GetBinContent(1); // <<sin(n*phi1)>> | |
9100 | Double_t s1Error = fIntFlowCorrectionTermsForNUAHist[0]->GetBinError(1); // statistical error of <<sin(n*phi1)>> | |
9101 | Double_t s2 = fIntFlowCorrectionTermsForNUAHist[0]->GetBinContent(2); // <<sin(n*(phi1+phi2))>> | |
9102 | Double_t s2Error = fIntFlowCorrectionTermsForNUAHist[0]->GetBinError(2); // statistical error of <<sin(n*(phi1+phi2))>> | |
9103 | Double_t s3 = fIntFlowCorrectionTermsForNUAHist[0]->GetBinContent(3); // <<sin(n*(phi1-phi2-phi3))>> | |
9104 | Double_t s3Error = fIntFlowCorrectionTermsForNUAHist[0]->GetBinError(3); // statistical error of <<sin(n*(phi1-phi2-phi3))>> | |
9105 | ||
9106 | // Shortcuts: | |
9107 | Double_t a1 = 2.*pow(c1,2.)+2.*pow(s1,2.)-two; | |
9108 | Double_t a2 = 6.*pow(c1,3.)-2.*c1*c2+c3+6.*c1*pow(s1,2.)-2.*s1*s2-4.*c1*two; | |
9109 | Double_t a3 = 2.*pow(s1,2.)-2.*pow(c1,2.)+c2; | |
9110 | Double_t a4 = 6.*pow(s1,3.)+6.*pow(c1,2.)*s1+2.*c2*s1-2.*c1*s2-s3-4.*s1*two; | |
9111 | Double_t a5 = 4.*c1*s1-s2; | |
9112 | ||
9113 | // Covariances (including weight dependent prefactor): | |
8e1cefdd | 9114 | Double_t wCov1 = 0.; // w*Cov(<2>,<cos(phi)) |
9115 | Double_t wCov2 = 0.; // w*Cov(<2>,<sin(phi)) | |
9116 | Double_t wCov3 = 0.; // w*Cov(<cos(phi),<sin(phi)) | |
9117 | Double_t wCov4 = 0.; // w*Cov(<2>,<4>) | |
9118 | Double_t wCov5 = 0.; // w*Cov(<2>,<cos(#phi_{1}+#phi_{2})>) | |
9119 | Double_t wCov6 = 0.; // w*Cov(<2>,<cos(#phi_{1}-#phi_{2}-#phi_{3})>) | |
9120 | Double_t wCov7 = 0.; // w*Cov(<2>,<sin(#phi_{1}+#phi_{2})>) | |
9121 | Double_t wCov8 = 0.; // w*Cov(<2>,<sin(#phi_{1}-#phi_{2}-#phi_{3})>) | |
9122 | Double_t wCov9 = 0.; // w*Cov(<4>,<cos(#phi)> | |
9123 | Double_t wCov10 = 0.; // w*Cov(<4>,<cos(#phi_{1}+#phi_{2})>) | |
9124 | Double_t wCov11 = 0.; // w*Cov(<4>,<cos(#phi_{1}-#phi_{2}-#phi_{3})>) | |
9125 | Double_t wCov12 = 0.; // w*Cov(<4>,<sin(#phi)> | |
9126 | Double_t wCov13 = 0.; // w*Cov(<4>,<sin(#phi_{1}+#phi_{2})>) | |
9127 | Double_t wCov14 = 0.; // w*Cov(<4>,<sin(#phi_{1}-#phi_{2}-#phi_{3})>) | |
9128 | Double_t wCov15 = 0.; // w*Cov(<cos(#phi)>,<cos(#phi_{1}+#phi_{2})>) | |
9129 | Double_t wCov16 = 0.; // w*Cov(<cos(#phi)>,<cos(#phi_{1}-#phi_{2}-#phi_{3})>) | |
9130 | Double_t wCov17 = 0.; // w*Cov(<cos(#phi)>,<sin(#phi_{1}+#phi_{2})>) | |
9131 | Double_t wCov18 = 0.; // w*Cov(<cos(#phi)>,<sin(#phi_{1}-#phi_{2}-#phi_{3})>) | |
9132 | Double_t wCov19 = 0.; // w*Cov(<cos(#phi_{1}+#phi_{2})>,<cos(#phi_{1}-#phi_{2}-#phi_{3})>) | |
9133 | Double_t wCov20 = 0.; // w*Cov(<sin(#phi)>,<cos(#phi_{1}+#phi_{2})>) | |
9134 | Double_t wCov21 = 0.; // w*Cov(<cos(#phi_{1}+#phi_{2})>,<sin(#phi_{1}+#phi_{2})>) | |
9135 | Double_t wCov22 = 0.; // w*Cov(<cos(#phi_{1}+#phi_{2})>,<sin(#phi_{1}-#phi_{2}-#phi_{3})>) | |
9136 | Double_t wCov23 = 0.; // w*Cov(<sin(#phi)>,<cos(#phi_{1}-#phi_{2}-#phi_{3})>) | |
9137 | Double_t wCov24 = 0.; // w*Cov(<sin(#phi_{1}+#phi_{2})>,<cos(#phi_{1}-#phi_{2}-#phi_{3})>) | |
9138 | Double_t wCov25 = 0.; // w*Cov(<cos(#phi_{1}-#phi_{2}-#phi_{3}>,<sin(#phi_{1}-#phi_{2}-#phi_{3}>) | |
9139 | Double_t wCov26 = 0.; // w*Cov(<sin(#phi)>,<sin(#phi_{1}+#phi_{2})>) | |
9140 | Double_t wCov27 = 0.; // w*Cov(<sin(#phi)>,<sin(#phi_{1}-#phi_{2}-#phi_{3})>) | |
9141 | Double_t wCov28 = 0.; // w*Cov(<sin(#phi_{1}+#phi_{2})>,<sin(#phi_{1}-#phi_{2}-#phi_{3})>) | |
9142 | if(!fForgetAboutCovariances) | |
9143 | { | |
9144 | wCov1 = fIntFlowCovariancesNUA->GetBinContent(1); // w*Cov(<2>,<cos(phi)) | |
9145 | wCov2 = fIntFlowCovariancesNUA->GetBinContent(2); // w*Cov(<2>,<sin(phi)) | |
9146 | wCov3 = fIntFlowCovariancesNUA->GetBinContent(3); // w*Cov(<cos(phi),<sin(phi)) | |
9147 | wCov4 = fIntFlowCovariances->GetBinContent(1); // w*Cov(<2>,<4>) | |
9148 | wCov5 = fIntFlowCovariancesNUA->GetBinContent(4); // w*Cov(<2>,<cos(#phi_{1}+#phi_{2})>) | |
9149 | wCov6 = fIntFlowCovariancesNUA->GetBinContent(6); // w*Cov(<2>,<cos(#phi_{1}-#phi_{2}-#phi_{3})>) | |
9150 | wCov7 = fIntFlowCovariancesNUA->GetBinContent(5); // w*Cov(<2>,<sin(#phi_{1}+#phi_{2})>) | |
9151 | wCov8 = fIntFlowCovariancesNUA->GetBinContent(7); // w*Cov(<2>,<sin(#phi_{1}-#phi_{2}-#phi_{3})>) | |
9152 | wCov9 = fIntFlowCovariancesNUA->GetBinContent(8); // w*Cov(<4>,<cos(#phi)> | |
9153 | wCov10 = fIntFlowCovariancesNUA->GetBinContent(10); // w*Cov(<4>,<cos(#phi_{1}+#phi_{2})>) | |
9154 | wCov11 = fIntFlowCovariancesNUA->GetBinContent(12); // w*Cov(<4>,<cos(#phi_{1}-#phi_{2}-#phi_{3})>) | |
9155 | wCov12 = fIntFlowCovariancesNUA->GetBinContent(9); // w*Cov(<4>,<sin(#phi)> | |
9156 | wCov13 = fIntFlowCovariancesNUA->GetBinContent(11); // w*Cov(<4>,<sin(#phi_{1}+#phi_{2})>) | |
9157 | wCov14 = fIntFlowCovariancesNUA->GetBinContent(13); // w*Cov(<4>,<sin(#phi_{1}-#phi_{2}-#phi_{3})>) | |
9158 | wCov15 = fIntFlowCovariancesNUA->GetBinContent(14); // w*Cov(<cos(#phi)>,<cos(#phi_{1}+#phi_{2})>) | |
9159 | wCov16 = fIntFlowCovariancesNUA->GetBinContent(16); // w*Cov(<cos(#phi)>,<cos(#phi_{1}-#phi_{2}-#phi_{3})>) | |
9160 | wCov17 = fIntFlowCovariancesNUA->GetBinContent(15); // w*Cov(<cos(#phi)>,<sin(#phi_{1}+#phi_{2})>) | |
9161 | wCov18 = fIntFlowCovariancesNUA->GetBinContent(17); // w*Cov(<cos(#phi)>,<sin(#phi_{1}-#phi_{2}-#phi_{3})>) | |
9162 | wCov19 = fIntFlowCovariancesNUA->GetBinContent(23); // w*Cov(<cos(#phi_{1}+#phi_{2})>,<cos(#phi_{1}-#phi_{2}-#phi_{3})>) | |
9163 | wCov20 = fIntFlowCovariancesNUA->GetBinContent(18); // w*Cov(<sin(#phi)>,<cos(#phi_{1}+#phi_{2})>) | |
9164 | wCov21 = fIntFlowCovariancesNUA->GetBinContent(22); // w*Cov(<cos(#phi_{1}+#phi_{2})>,<sin(#phi_{1}+#phi_{2})>) | |
9165 | wCov22 = fIntFlowCovariancesNUA->GetBinContent(24); // w*Cov(<cos(#phi_{1}+#phi_{2})>,<sin(#phi_{1}-#phi_{2}-#phi_{3})>) | |
9166 | wCov23 = fIntFlowCovariancesNUA->GetBinContent(20); // w*Cov(<sin(#phi)>,<cos(#phi_{1}-#phi_{2}-#phi_{3})>) | |
9167 | wCov24 = fIntFlowCovariancesNUA->GetBinContent(25); // w*Cov(<sin(#phi_{1}+#phi_{2})>,<cos(#phi_{1}-#phi_{2}-#phi_{3})>) | |
9168 | wCov25 = fIntFlowCovariancesNUA->GetBinContent(27); // w*Cov(<cos(#phi_{1}-#phi_{2}-#phi_{3}>,<sin(#phi_{1}-#phi_{2}-#phi_{3}>) | |
9169 | wCov26 = fIntFlowCovariancesNUA->GetBinContent(19); // w*Cov(<sin(#phi)>,<sin(#phi_{1}+#phi_{2})>) | |
9170 | wCov27 = fIntFlowCovariancesNUA->GetBinContent(21); // w*Cov(<sin(#phi)>,<sin(#phi_{1}-#phi_{2}-#phi_{3})>) | |
9171 | wCov28 = fIntFlowCovariancesNUA->GetBinContent(26); // w*Cov(<sin(#phi_{1}+#phi_{2})>,<sin(#phi_{1}-#phi_{2}-#phi_{3})>) | |
9172 | } // end of if(!fForgetAboutCovariances) | |
9173 | ||
b92ea2b9 | 9174 | // Calculating generalized QC{2}: |
9175 | // Generalized QC{2}: | |
9176 | Double_t gQC2 = two - pow(c1,2.) - pow(s1,2.); | |
9177 | if(fApplyCorrectionForNUA){fIntFlowQcumulants->SetBinContent(1,gQC2);} | |
9178 | // Statistical error of generalized QC{2}: | |
9179 | Double_t gQC2ErrorSquared = pow(twoError,2.)+4.*pow(c1,2.)*pow(c1Error,2.) | |
9180 | + 4.*pow(s1,2.)*pow(s1Error,2.) | |
9181 | - 4*c1*wCov1-4*s1*wCov2 | |
9182 | + 8.*c1*s1*wCov3; | |
9183 | // Store ratio of error squared - with/without NUA terms: | |
9184 | Double_t ratioErrorSquaredQC2 = 0.; | |
9185 | if(fIntFlowQcumulants->GetBinError(1)>0.) | |
9186 | { | |
9187 | ratioErrorSquaredQC2 = (gQC2ErrorSquared/pow(fIntFlowQcumulants->GetBinError(1),2.)); | |
9188 | fIntFlowQcumulantsErrorSquaredRatio->SetBinContent(1,ratioErrorSquaredQC2); | |
9189 | } | |
9190 | // If enabled, store error by including non-isotropic terms: | |
b77b6434 | 9191 | if(fApplyCorrectionForNUA && fPropagateErrorAlsoFromNIT) |
b92ea2b9 | 9192 | { |
9193 | if(gQC2ErrorSquared>=0.) | |
9194 | { | |
9195 | fIntFlowQcumulants->SetBinError(1,pow(gQC2ErrorSquared,0.5)); | |
9196 | } else | |
9197 | { | |
9198 | fIntFlowQcumulants->SetBinError(1,0.); | |
9199 | cout<<endl; | |
9200 | cout<<" WARNING (QC): Statistical error of generalized QC{2} is imaginary !!!!"<<endl; | |
9201 | cout<<endl; | |
9202 | } | |
b77b6434 | 9203 | } // end of if(fApplyCorrectionForNUA && fPropagateErrorAlsoFromNIT) |
b92ea2b9 | 9204 | // Quantify detector bias to QC{2}: |
9205 | if(TMath::Abs(QC2)>0.) | |
9206 | { | |
9207 | fIntFlowDetectorBias->SetBinContent(1,gQC2/QC2); | |
9208 | if(QC2Error>0.) | |
9209 | { | |
9210 | Double_t errorSquared = gQC2ErrorSquared/pow(QC2,2.)+pow(gQC2,2.)*pow(QC2Error,2.)/pow(QC2,4.); | |
9211 | if(errorSquared>0.) | |
9212 | { | |
9213 | fIntFlowDetectorBias->SetBinError(1,pow(errorSquared,0.5)); | |
9214 | } | |
9215 | } | |
9216 | } // end of if(TMath::Abs(QC2)>0.) | |
9217 | ||
9218 | // Calculating generalized QC{4}: | |
9219 | // Generalized QC{4}: | |
9220 | Double_t gQC4 = four-2.*pow(two,2.) | |
9221 | - 4.*c1*c3+4.*s1*s3-pow(c2,2.)-pow(s2,2.) | |
9222 | + 4.*c2*(pow(c1,2.)-pow(s1,2.))+8.*s2*s1*c1 | |
9223 | + 8.*two*(pow(c1,2.)+pow(s1,2.))-6.*pow((pow(c1,2.)+pow(s1,2.)),2.); | |
9224 | if(fApplyCorrectionForNUA){fIntFlowQcumulants->SetBinContent(2,gQC4);} | |
9225 | // Statistical error of generalized QC{4}: | |
9226 | Double_t gQC4ErrorSquared = 16.*pow(a1,2.)*pow(twoError,2.)+pow(fourError,2.)+16.*pow(a2,2.)*pow(c1Error,2.) | |
9227 | + 4.*pow(a3,2.)*pow(c2Error,2.)+16.*pow(c1,2.)*pow(c3Error,2.) | |
9228 | + 16.*pow(a4,2.)*pow(s1Error,2.)+4.*pow(a5,2.)*pow(s2Error,2.) | |
9229 | + 16.*pow(s1,2.)*pow(s3Error,2.)+8.*a1*wCov4-32.*a1*a2*wCov1 | |
9230 | - 16.*a3*a1*wCov5-32.*c1*a1*wCov6-32.*a1*a4*wCov2+16.*a5*a1*wCov7 | |
9231 | + 32.*s1*a1*wCov8-8.*a2*wCov9-4.*a3*wCov10-8.*c1*wCov11-8.*a4*wCov12 | |
9232 | + 4.*a5*wCov13+8.*s1*wCov14+16.*a3*a2*wCov15+32.*c1*a2*wCov16+32.*a2*a4*wCov3 | |
9233 | - 16.*a5*a2*wCov17-32.*s1*a2*wCov18+16.*c1*a3*wCov19+16.*a3*a4*wCov20 | |
9234 | - 8.*a3*a5*wCov21-16.*s1*a3*wCov22+32.*c1*a4*wCov23-16.*c1*a5*wCov24 | |
9235 | - 32.*c1*s1*wCov25-16.*a5*a4*wCov26-32.*s1*a4*wCov27+16.*s1*a5*wCov28; | |
9236 | // Store ratio of error squared - with/without NUA terms: | |
9237 | Double_t ratioErrorSquaredQC4 = 0.; | |
9238 | if(fIntFlowQcumulants->GetBinError(2)>0.) | |
9239 | { | |
9240 | ratioErrorSquaredQC4 = (gQC4ErrorSquared/pow(fIntFlowQcumulants->GetBinError(2),2.)); | |
9241 | fIntFlowQcumulantsErrorSquaredRatio->SetBinContent(2,ratioErrorSquaredQC4); | |
9242 | } | |
b77b6434 | 9243 | if(fApplyCorrectionForNUA && fPropagateErrorAlsoFromNIT) |
b92ea2b9 | 9244 | { |
9245 | if(gQC4ErrorSquared>=0.) | |
9246 | { | |
9247 | fIntFlowQcumulants->SetBinError(2,pow(gQC4ErrorSquared,0.5)); | |
9248 | } else | |
9249 | { | |
9250 | fIntFlowQcumulants->SetBinError(2,0.); | |
9251 | cout<<endl; | |
9252 | cout<<" WARNING (QC): Statistical error of generalized QC{4} is imaginary !!!!"<<endl; | |
9253 | cout<<endl; | |
9254 | } | |
b77b6434 | 9255 | } // end of if(fApplyCorrectionForNUA && fPropagateErrorAlsoFromNIT) |
b92ea2b9 | 9256 | // Quantify detector bias to QC{4}: |
9257 | if(TMath::Abs(QC4)>0.) | |
9258 | { | |
9259 | fIntFlowDetectorBias->SetBinContent(2,gQC4/QC4); | |
9260 | if(QC4Error>0.) | |
9261 | { | |
9262 | Double_t errorSquared = gQC4ErrorSquared/pow(QC4,2.)+pow(gQC4,2.)*pow(QC4Error,2.)/pow(QC4,4.); | |
9263 | if(errorSquared>0.) | |
9264 | { | |
9265 | fIntFlowDetectorBias->SetBinError(2,pow(errorSquared,0.5)); | |
9266 | } | |
9267 | } | |
9268 | } // end of if(TMath::Abs(QC4)>0.) | |
489d5531 | 9269 | |
b92ea2b9 | 9270 | |
9271 | // .... to be improved (continued for 6th and 8th order) .... | |
9272 | ||
9273 | ||
2001bc3a | 9274 | // versus multiplicity: |
b77b6434 | 9275 | if(fCalculateCumulantsVsM) // to be improved - propagate error for nua terms vs M |
2001bc3a | 9276 | { |
9277 | Int_t nBins = fIntFlowCorrelationsVsMPro[0]->GetNbinsX(); // to be improved (hardwired 0) | |
b77b6434 | 9278 | Double_t value[4] = {0.}; // QCs vs M |
9279 | Double_t error[4] = {0.}; // error of QCs vs M | |
9280 | Double_t dSum1[4] = {0.}; // sum value_i/(error_i)^2 | |
9281 | Double_t dSum2[4] = {0.}; // sum 1/(error_i)^2 | |
2001bc3a | 9282 | for(Int_t b=1;b<=nBins;b++) |
9283 | { | |
b92ea2b9 | 9284 | // Measured correlations: |
2001bc3a | 9285 | two = fIntFlowCorrelationsVsMHist[0]->GetBinContent(b); // <<2>> vs M |
9286 | four = fIntFlowCorrelationsVsMHist[1]->GetBinContent(b); // <<4>> vs M | |
b92ea2b9 | 9287 | // Isotropic cumulants: |
9288 | QC2 = two; | |
9289 | QC4 = four-2.*pow(two,2.); | |
9290 | // Non-isotropic terms: | |
9291 | c1 = fIntFlowCorrectionTermsForNUAVsMPro[1][0]->GetBinContent(b); // <<cos(n*phi1)>> | |
9292 | c2 = fIntFlowCorrectionTermsForNUAVsMPro[1][1]->GetBinContent(b); // <<cos(n*(phi1+phi2))>> | |
9293 | c3 = fIntFlowCorrectionTermsForNUAVsMPro[1][2]->GetBinContent(b); // <<cos(n*(phi1-phi2-phi3))>> | |
9294 | s1 = fIntFlowCorrectionTermsForNUAVsMPro[0][0]->GetBinContent(b); // <<sin(n*phi1)>> | |
9295 | s2 = fIntFlowCorrectionTermsForNUAVsMPro[0][1]->GetBinContent(b); // <<sin(n*(phi1+phi2))>> | |
9296 | s3 = fIntFlowCorrectionTermsForNUAVsMPro[0][2]->GetBinContent(b); // <<sin(n*(phi1-phi2-phi3))>> | |
9297 | // Generalized QC{2} vs M: | |
9298 | gQC2 = two - pow(c1,2.) - pow(s1,2.); | |
b77b6434 | 9299 | if(fApplyCorrectionForNUAVsM){fIntFlowQcumulantsVsM[0]->SetBinContent(b,gQC2);} |
b92ea2b9 | 9300 | // Generalized QC{4} vs M: |
9301 | gQC4 = four-2.*pow(two,2.) | |
9302 | - 4.*c1*c3+4.*s1*s3-pow(c2,2.)-pow(s2,2.) | |
9303 | + 4.*c2*(pow(c1,2.)-pow(s1,2.))+8.*s2*s1*c1 | |
9304 | + 8.*two*(pow(c1,2.)+pow(s1,2.))-6.*pow((pow(c1,2.)+pow(s1,2.)),2.); | |
b77b6434 | 9305 | if(fApplyCorrectionForNUAVsM){fIntFlowQcumulantsVsM[1]->SetBinContent(b,gQC4);} |
b92ea2b9 | 9306 | // Detector bias vs M: |
9307 | if(TMath::Abs(QC2)>0.) | |
9308 | { | |
9309 | fIntFlowDetectorBiasVsM[0]->SetBinContent(b,gQC2/QC2); | |
9310 | } // end of if(TMath::Abs(QC2)>0.) | |
9311 | if(TMath::Abs(QC4)>0.) | |
9312 | { | |
9313 | fIntFlowDetectorBiasVsM[1]->SetBinContent(b,gQC4/QC4); | |
b77b6434 | 9314 | } // end of if(TMath::Abs(QC4)>0.) |
9315 | // Rebin in M: | |
9316 | for(Int_t co=0;co<4;co++) | |
9317 | { | |
9318 | value[co] = fIntFlowQcumulantsVsM[co]->GetBinContent(b); | |
9319 | error[co] = fIntFlowQcumulantsVsM[co]->GetBinError(b); | |
9320 | if(error[co]>0.) | |
9321 | { | |
9322 | dSum1[co]+=value[co]/(error[co]*error[co]); | |
9323 | dSum2[co]+=1./(error[co]*error[co]); | |
9324 | } | |
9325 | } // end of for(Int_t co=0;co<4;co++) | |
9326 | } // end of for(Int_t b=1;b<=nBins;b++) | |
9327 | // Store rebinned Q-cumulants: | |
9328 | if(fApplyCorrectionForNUAVsM) | |
9329 | { | |
9330 | for(Int_t co=0;co<4;co++) | |
9331 | { | |
9332 | if(dSum2[co]>0.) | |
9333 | { | |
9334 | fIntFlowQcumulantsRebinnedInM->SetBinContent(co+1,dSum1[co]/dSum2[co]); | |
9335 | fIntFlowQcumulantsRebinnedInM->SetBinError(co+1,pow(1./dSum2[co],0.5)); | |
9336 | } | |
9337 | } // end of for(Int_t co=0;co<4;co++) | |
9338 | } // end of if(fApplyCorrectionForNUAVsM) | |
9339 | } // end of if(fCalculateCumulantsVsM) | |
2001bc3a | 9340 | |
489d5531 | 9341 | } // end of void AliFlowAnalysisWithQCumulants::CalculateQcumulantsCorrectedForNUAIntFlow() |
0328db2d | 9342 | |
489d5531 | 9343 | //================================================================================================================================ |
9344 | ||
489d5531 | 9345 | void AliFlowAnalysisWithQCumulants::FinalizeCorrectionTermsForNUAIntFlow() |
9346 | { | |
0328db2d | 9347 | // From profile fIntFlowCorrectionTermsForNUAPro[sc] access measured correction terms for NUA |
489d5531 | 9348 | // and their spread, correctly calculate the statistical errors and store the final |
0328db2d | 9349 | // results and statistical errors for correction terms for NUA in histogram fIntFlowCorrectionTermsForNUAHist[sc]. |
489d5531 | 9350 | // |
9351 | // Remark: Statistical error of correction temrs is calculated as: | |
9352 | // | |
9353 | // statistical error = termA * spread * termB: | |
9354 | // termA = sqrt{sum_{i=1}^{N} w^2}/(sum_{i=1}^{N} w) | |
9355 | // termB = 1/sqrt(1-termA^2) | |
9356 | ||
b92ea2b9 | 9357 | TString sinCosFlag[2] = {"sin","cos"}; // to be improved - promore this to data member? |
9358 | TString nonisotropicTermFlag[4] = {"(n(phi1))","(n(phi1+phi2))","(n(phi1-phi2-phi3))","(n(2phi1-phi2))"}; // to be improved - hardwired 4 | |
9359 | ||
489d5531 | 9360 | for(Int_t sc=0;sc<2;sc++) // sin or cos correction terms |
9361 | { | |
b92ea2b9 | 9362 | for(Int_t ci=1;ci<=4;ci++) // correction term index (to be improved - hardwired 4) |
489d5531 | 9363 | { |
9364 | Double_t correction = fIntFlowCorrectionTermsForNUAPro[sc]->GetBinContent(ci); | |
0328db2d | 9365 | Double_t spread = fIntFlowCorrectionTermsForNUAPro[sc]->GetBinError(ci); |
9366 | Double_t sumOfLinearEventWeights = fIntFlowSumOfEventWeightsNUA[sc][0]->GetBinContent(ci); | |
9367 | Double_t sumOfQuadraticEventWeights = fIntFlowSumOfEventWeightsNUA[sc][1]->GetBinContent(ci); | |
9368 | Double_t termA = 0.; | |
9369 | Double_t termB = 0.; | |
b92ea2b9 | 9370 | if(TMath::Abs(sumOfLinearEventWeights)>1.e-44) |
0328db2d | 9371 | { |
9372 | termA = pow(sumOfQuadraticEventWeights,0.5)/sumOfLinearEventWeights; | |
9373 | } else | |
9374 | { | |
b92ea2b9 | 9375 | cout<<" WARNING (QC): sumOfLinearEventWeights == 0 in AFAWQC::FCTFNIF() !!!!"<<endl; |
9376 | cout<<Form(" (for <<%s[%s]>> non-isotropic term)",sinCosFlag[sc].Data(),nonisotropicTermFlag[ci-1].Data())<<endl; | |
0328db2d | 9377 | } |
489d5531 | 9378 | if(1.-pow(termA,2.) > 0.) |
9379 | { | |
9380 | termB = 1./pow(1-pow(termA,2.),0.5); | |
9381 | } else | |
9382 | { | |
b92ea2b9 | 9383 | cout<<" WARNING (QC): 1.-pow(termA,2.) <= 0 in AFAWQC::FCTFNIF() !!!!"<<endl; |
9384 | cout<<Form(" (for <<%s[%s]>> non-isotropic term)",sinCosFlag[sc].Data(),nonisotropicTermFlag[ci-1].Data())<<endl; | |
489d5531 | 9385 | } |
9386 | Double_t statisticalError = termA * spread * termB; | |
489d5531 | 9387 | fIntFlowCorrectionTermsForNUAHist[sc]->SetBinContent(ci,correction); |
0328db2d | 9388 | fIntFlowCorrectionTermsForNUAHist[sc]->SetBinError(ci,statisticalError); |
b92ea2b9 | 9389 | } // end of for(Int_t ci=1;ci<=4;ci++) // correction term index |
489d5531 | 9390 | } // end of for(Int sc=0;sc<2;sc++) // sin or cos correction terms |
9391 | ||
9392 | } // end of void AliFlowAnalysisWithQCumulants::FinalizeCorrectionTermsForNUAIntFlow() | |
9393 | ||
489d5531 | 9394 | //================================================================================================================================ |
9395 | ||
489d5531 | 9396 | void AliFlowAnalysisWithQCumulants::GetPointersForNestedLoopsHistograms() |
9397 | { | |
9398 | // Get pointers to all objects relevant for calculations with nested loops. | |
9399 | ||
9400 | TList *nestedLoopsList = dynamic_cast<TList*>(fHistList->FindObject("Nested Loops")); | |
9401 | if(nestedLoopsList) | |
9402 | { | |
9403 | this->SetNestedLoopsList(nestedLoopsList); | |
9404 | } else | |
9405 | { | |
9406 | cout<<"WARNING: nestedLoopsList is NULL in AFAWQC::GPFNLH() !!!!"<<endl; | |
9407 | exit(0); | |
9408 | } | |
9409 | ||
9410 | TString sinCosFlag[2] = {"sin","cos"}; // to be improved (should I promote this to data members?) | |
9411 | TString typeFlag[2] = {"RP","POI"}; // to be improved (should I promote this to data members?) | |
9412 | TString ptEtaFlag[2] = {"p_{T}","#eta"}; // to be improved (should I promote this to data members?) | |
9413 | TString reducedCorrelationIndex[4] = {"<2'>","<4'>","<6'>","<8'>"}; // to be improved (should I promote this to data members?) | |
9414 | ||
9415 | TString evaluateNestedLoopsName = "fEvaluateNestedLoops"; | |
9416 | evaluateNestedLoopsName += fAnalysisLabel->Data(); | |
9417 | TProfile *evaluateNestedLoops = dynamic_cast<TProfile*>(nestedLoopsList->FindObject(evaluateNestedLoopsName.Data())); | |
9418 | Bool_t bEvaluateIntFlowNestedLoops = kFALSE; | |
9419 | Bool_t bEvaluateDiffFlowNestedLoops = kFALSE; | |
9420 | if(evaluateNestedLoops) | |
9421 | { | |
9422 | this->SetEvaluateNestedLoops(evaluateNestedLoops); | |
9423 | bEvaluateIntFlowNestedLoops = (Int_t)evaluateNestedLoops->GetBinContent(1); | |
9424 | bEvaluateDiffFlowNestedLoops = (Int_t)evaluateNestedLoops->GetBinContent(2); | |
9425 | } | |
9426 | // nested loops relevant for integrated flow: | |
9427 | if(bEvaluateIntFlowNestedLoops) | |
9428 | { | |
9429 | // correlations: | |
9430 | TString intFlowDirectCorrelationsName = "fIntFlowDirectCorrelations"; | |
9431 | intFlowDirectCorrelationsName += fAnalysisLabel->Data(); | |
9432 | TProfile *intFlowDirectCorrelations = dynamic_cast<TProfile*>(nestedLoopsList->FindObject(intFlowDirectCorrelationsName.Data())); | |
9433 | if(intFlowDirectCorrelations) | |
9434 | { | |
9435 | this->SetIntFlowDirectCorrelations(intFlowDirectCorrelations); | |
9436 | } else | |
9437 | { | |
9438 | cout<<"WARNING: intFlowDirectCorrelations is NULL in AFAWQC::GPFNLH() !!!!"<<endl; | |
9439 | exit(0); | |
9440 | } | |
9441 | if(fUsePhiWeights||fUsePtWeights||fUseEtaWeights) | |
9442 | { | |
9443 | TString intFlowExtraDirectCorrelationsName = "fIntFlowExtraDirectCorrelations"; | |
9444 | intFlowExtraDirectCorrelationsName += fAnalysisLabel->Data(); | |
9445 | TProfile *intFlowExtraDirectCorrelations = dynamic_cast<TProfile*>(nestedLoopsList->FindObject(intFlowExtraDirectCorrelationsName.Data())); | |
9446 | if(intFlowExtraDirectCorrelations) | |
9447 | { | |
9448 | this->SetIntFlowExtraDirectCorrelations(intFlowExtraDirectCorrelations); | |
9449 | } else | |
9450 | { | |
9451 | cout<<"WARNING: intFlowExtraDirectCorrelations is NULL in AFAWQC::GPFNLH() !!!!"<<endl; | |
9452 | exit(0); | |
9453 | } | |
9454 | } // end of if(fUsePhiWeights||fUsePtWeights||fUseEtaWeights) | |
9455 | // correction terms for non-uniform acceptance: | |
9456 | TString intFlowDirectCorrectionTermsForNUAName = "fIntFlowDirectCorrectionTermsForNUA"; | |
9457 | intFlowDirectCorrectionTermsForNUAName += fAnalysisLabel->Data(); | |
9458 | TProfile *intFlowDirectCorrectionTermsForNUA[2] = {NULL}; | |
9459 | for(Int_t sc=0;sc<2;sc++) // sin or cos terms | |
9460 | { | |
9461 | intFlowDirectCorrectionTermsForNUA[sc] = dynamic_cast<TProfile*>(nestedLoopsList->FindObject(Form("%s: %s terms",intFlowDirectCorrectionTermsForNUAName.Data(),sinCosFlag[sc].Data()))); | |
9462 | if(intFlowDirectCorrectionTermsForNUA[sc]) | |
9463 | { | |
9464 | this->SetIntFlowDirectCorrectionTermsForNUA(intFlowDirectCorrectionTermsForNUA[sc],sc); | |
9465 | } else | |
9466 | { | |
9467 | cout<<"WARNING: intFlowDirectCorrectionTermsForNUA[sc] is NULL in AFAWQC::GPFNLH() !!!!"<<endl; | |
9468 | cout<<"sc = "<<sc<<endl; | |
9469 | exit(0); | |
9470 | } | |
9471 | } // end of for(Int_t sc=0;sc<2;sc++) | |
9472 | } // end of if(bEvaluateIntFlowNestedLoops) | |
9473 | ||
9474 | // nested loops relevant for differential flow: | |
9475 | if(bEvaluateDiffFlowNestedLoops) | |
9476 | { | |
9477 | // correlations: | |
9478 | TString diffFlowDirectCorrelationsName = "fDiffFlowDirectCorrelations"; | |
9479 | diffFlowDirectCorrelationsName += fAnalysisLabel->Data(); | |
9480 | TProfile *diffFlowDirectCorrelations[2][2][4] = {{{NULL}}}; | |
9481 | for(Int_t t=0;t<2;t++) | |
9482 | { | |
9483 | for(Int_t pe=0;pe<2;pe++) | |
9484 | { | |
9485 | for(Int_t ci=0;ci<4;ci++) // correlation index | |
9486 | { | |
9487 | diffFlowDirectCorrelations[t][pe][ci] = dynamic_cast<TProfile*>(nestedLoopsList->FindObject(Form("%s, %s, %s, %s",diffFlowDirectCorrelationsName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),reducedCorrelationIndex[ci].Data()))); | |
9488 | if(diffFlowDirectCorrelations[t][pe][ci]) | |
9489 | { | |
9490 | this->SetDiffFlowDirectCorrelations(diffFlowDirectCorrelations[t][pe][ci],t,pe,ci); | |
9491 | } else | |
9492 | { | |
9493 | cout<<"WARNING: diffFlowDirectCorrelations[t][pe][ci] is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
9494 | cout<<"t = "<<t<<endl; | |
9495 | cout<<"pe = "<<pe<<endl; | |
9496 | cout<<"ci = "<<ci<<endl; | |
9497 | } | |
9498 | } // end of for(Int_t ci=0;ci<4;ci++) // correlation index | |
9499 | } // end of for(Int_t pe=0;pe<2;pe++) | |
9500 | } // end of for(Int_t t=0;t<2;t++) | |
9501 | // correction terms for non-uniform acceptance: | |
9502 | TString diffFlowDirectCorrectionTermsForNUAName = "fDiffFlowDirectCorrectionTermsForNUA"; | |
9503 | diffFlowDirectCorrectionTermsForNUAName += fAnalysisLabel->Data(); | |
9504 | TProfile *diffFlowDirectCorrectionTermsForNUA[2][2][2][10] = {{{{NULL}}}}; | |
9505 | for(Int_t t=0;t<2;t++) | |
9506 | { | |
9507 | for(Int_t pe=0;pe<2;pe++) | |
9508 | { | |
9509 | // correction terms for NUA: | |
9510 | for(Int_t sc=0;sc<2;sc++) // sin or cos | |
9511 | { | |
9512 | for(Int_t cti=0;cti<9;cti++) // correction term index | |
9513 | { | |
9514 | diffFlowDirectCorrectionTermsForNUA[t][pe][sc][cti] = dynamic_cast<TProfile*>(nestedLoopsList->FindObject(Form("%s, %s, %s, %s, cti = %d",diffFlowDirectCorrectionTermsForNUAName.Data(),typeFlag[t].Data(),ptEtaFlag[pe].Data(),sinCosFlag[sc].Data(),cti+1))); | |
9515 | if(diffFlowDirectCorrectionTermsForNUA[t][pe][sc][cti]) | |
9516 | { | |
9517 | this->SetDiffFlowDirectCorrectionTermsForNUA(diffFlowDirectCorrectionTermsForNUA[t][pe][sc][cti],t,pe,sc,cti); | |
9518 | } else | |
9519 | { | |
9520 | cout<<"WARNING: diffFlowDirectCorrectionTermsForNUA[t][pe][sc][cti] is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
9521 | cout<<"t = "<<t<<endl; | |
9522 | cout<<"pe = "<<pe<<endl; | |
9523 | cout<<"sc = "<<sc<<endl; | |
9524 | cout<<"cti = "<<cti<<endl; | |
9525 | } | |
9526 | } // end of for(Int_t cti=0;cti<9;cti++) // correction term index | |
9527 | } // end of for(Int_t sc=0;sc<2;sc++) // sin or cos | |
9528 | } // end of for(Int_t pe=0;pe<2;pe++) | |
9529 | } // end of for(Int_t t=0;t<2;t++) | |
9530 | // number of RPs and POIs in selected pt and eta bins for cross-checkings: | |
9531 | TString noOfParticlesInBinName = "fNoOfParticlesInBin"; | |
9532 | TH1D *noOfParticlesInBin = NULL; | |
9533 | noOfParticlesInBin = dynamic_cast<TH1D*>(nestedLoopsList->FindObject(noOfParticlesInBinName.Data())); | |
9534 | if(noOfParticlesInBin) | |
9535 | { | |
9536 | this->SetNoOfParticlesInBin(noOfParticlesInBin); | |
9537 | } else | |
9538 | { | |
9539 | cout<<endl; | |
9540 | cout<<" WARNING (QC): noOfParticlesInBin is NULL in AFAWQC::GPFDFH() !!!!"<<endl; | |
9541 | cout<<endl; | |
9542 | } | |
9543 | } // end of if(bEvaluateDiffFlowNestedLoops) | |
9544 | ||
9545 | } // end of void AliFlowAnalysisWithQCumulants::GetPointersForNestedLoopsHistograms() | |
9546 | ||
489d5531 | 9547 | //================================================================================================================================ |
9548 | ||
489d5531 | 9549 | void AliFlowAnalysisWithQCumulants::StoreHarmonic() |
9550 | { | |
9551 | // Store flow harmonic in common control histograms. | |
9552 | ||
9553 | (fCommonHists->GetHarmonic())->Fill(0.5,fHarmonic); | |
dd442cd2 | 9554 | if(fFillMultipleControlHistograms) |
9555 | { | |
9556 | (fCommonHists2nd->GetHarmonic())->Fill(0.5,fHarmonic); | |
9557 | (fCommonHists4th->GetHarmonic())->Fill(0.5,fHarmonic); | |
9558 | (fCommonHists6th->GetHarmonic())->Fill(0.5,fHarmonic); | |
9559 | (fCommonHists8th->GetHarmonic())->Fill(0.5,fHarmonic); | |
9560 | } | |
9561 | ||
489d5531 | 9562 | } // end of void AliFlowAnalysisWithQCumulants::StoreHarmonic() |
9563 | ||
489d5531 | 9564 | //================================================================================================================================ |
9565 | ||
489d5531 | 9566 | void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrelationsUsingParticleWeights(TString type, TString ptOrEta) // type = RP or POI |
9567 | { | |
9568 | // Calculate all correlations needed for differential flow using particle weights. | |
9569 | ||
2a98ceb8 | 9570 | Int_t t = 0; // type flag |
9571 | Int_t pe = 0; // ptEta flag | |
489d5531 | 9572 | |
9573 | if(type == "RP") | |
9574 | { | |
9575 | t = 0; | |
9576 | } else if(type == "POI") | |
9577 | { | |
9578 | t = 1; | |
9579 | } | |
9580 | ||
9581 | if(ptOrEta == "Pt") | |
9582 | { | |
9583 | pe = 0; | |
9584 | } else if(ptOrEta == "Eta") | |
9585 | { | |
9586 | pe = 1; | |
9587 | } | |
9588 | ||
9589 | Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; | |
9590 | Double_t minPtEta[2] = {fPtMin,fEtaMin}; | |
9591 | //Double_t maxPtEta[2] = {fPtMax,fEtaMax}; | |
9592 | Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; | |
9593 | ||
9594 | // real and imaginary parts of weighted Q-vectors evaluated in harmonics n, 2n, 3n and 4n: | |
9595 | Double_t dReQ1n1k = (*fReQ)(0,1); | |
9596 | Double_t dReQ2n2k = (*fReQ)(1,2); | |
9597 | Double_t dReQ1n3k = (*fReQ)(0,3); | |
9598 | //Double_t dReQ4n4k = (*fReQ)(3,4); | |
9599 | Double_t dImQ1n1k = (*fImQ)(0,1); | |
9600 | Double_t dImQ2n2k = (*fImQ)(1,2); | |
9601 | Double_t dImQ1n3k = (*fImQ)(0,3); | |
9602 | //Double_t dImQ4n4k = (*fImQ)(3,4); | |
9603 | ||
9604 | // S^M_{p,k} (see .h file for the definition of fSMpk): | |
9605 | Double_t dSM1p1k = (*fSMpk)(0,1); | |
9606 | Double_t dSM1p2k = (*fSMpk)(0,2); | |
9607 | Double_t dSM1p3k = (*fSMpk)(0,3); | |
9608 | Double_t dSM2p1k = (*fSMpk)(1,1); | |
9609 | Double_t dSM3p1k = (*fSMpk)(2,1); | |
9610 | ||
9611 | // looping over all bins and calculating reduced correlations: | |
9612 | for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
9613 | { | |
9614 | // real and imaginary parts of p_{m*n,0} (non-weighted Q-vector evaluated for POIs in particular (pt,eta) bin): | |
9615 | Double_t p1n0kRe = 0.; | |
9616 | Double_t p1n0kIm = 0.; | |
9617 | ||
9618 | // number of POIs in particular (pt,eta) bin): | |
9619 | Double_t mp = 0.; | |
9620 | ||
9621 | // real and imaginary parts of q_{m*n,k}: | |
9622 | // (weighted Q-vector evaluated for particles which are both RPs and POIs in particular (pt,eta) bin) | |
9623 | Double_t q1n2kRe = 0.; | |
9624 | Double_t q1n2kIm = 0.; | |
9625 | Double_t q2n1kRe = 0.; | |
9626 | Double_t q2n1kIm = 0.; | |
9627 | ||
9628 | // s_{1,1}, s_{1,2} and s_{1,3} // to be improved (add explanation) | |
9629 | Double_t s1p1k = 0.; | |
9630 | Double_t s1p2k = 0.; | |
9631 | Double_t s1p3k = 0.; | |
9632 | ||
9633 | // M0111 from Eq. (118) in QC2c (to be improved (notation)) | |
9634 | Double_t dM0111 = 0.; | |
9635 | ||
9636 | if(type == "POI") | |
9637 | { | |
9638 | p1n0kRe = fReRPQ1dEBE[1][pe][0][0]->GetBinContent(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)) | |
9639 | * fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)); | |
9640 | p1n0kIm = fImRPQ1dEBE[1][pe][0][0]->GetBinContent(fImRPQ1dEBE[1][pe][0][0]->GetBin(b)) | |
9641 | * fImRPQ1dEBE[1][pe][0][0]->GetBinEntries(fImRPQ1dEBE[1][pe][0][0]->GetBin(b)); | |
9642 | ||
9643 | mp = fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) | |
9644 | ||
9645 | t = 1; // typeFlag = RP or POI | |
9646 | ||
9647 | // q_{m*n,k}: (Remark: m=1 is 0, k=0 iz zero (to be improved!)) | |
9648 | q1n2kRe = fReRPQ1dEBE[2][pe][0][2]->GetBinContent(fReRPQ1dEBE[2][pe][0][2]->GetBin(b)) | |
9649 | * fReRPQ1dEBE[2][pe][0][2]->GetBinEntries(fReRPQ1dEBE[2][pe][0][2]->GetBin(b)); | |
9650 | q1n2kIm = fImRPQ1dEBE[2][pe][0][2]->GetBinContent(fImRPQ1dEBE[2][pe][0][2]->GetBin(b)) | |
9651 | * fImRPQ1dEBE[2][pe][0][2]->GetBinEntries(fImRPQ1dEBE[2][pe][0][2]->GetBin(b)); | |
9652 | q2n1kRe = fReRPQ1dEBE[2][pe][1][1]->GetBinContent(fReRPQ1dEBE[2][pe][1][1]->GetBin(b)) | |
9653 | * fReRPQ1dEBE[2][pe][1][1]->GetBinEntries(fReRPQ1dEBE[2][pe][1][1]->GetBin(b)); | |
9654 | q2n1kIm = fImRPQ1dEBE[2][pe][1][1]->GetBinContent(fImRPQ1dEBE[2][pe][1][1]->GetBin(b)) | |
9655 | * fImRPQ1dEBE[2][pe][1][1]->GetBinEntries(fImRPQ1dEBE[2][pe][1][1]->GetBin(b)); | |
9656 | ||
9657 | // s_{1,1}, s_{1,2} and s_{1,3} // to be improved (add explanation) | |
9658 | s1p1k = pow(fs1dEBE[2][pe][1]->GetBinContent(b)*fs1dEBE[2][pe][1]->GetBinEntries(b),1.); | |
9659 | s1p2k = pow(fs1dEBE[2][pe][2]->GetBinContent(b)*fs1dEBE[2][pe][2]->GetBinEntries(b),1.); | |
9660 | s1p3k = pow(fs1dEBE[2][pe][3]->GetBinContent(b)*fs1dEBE[2][pe][3]->GetBinEntries(b),1.); | |
9661 | ||
9662 | // M0111 from Eq. (118) in QC2c (to be improved (notation)): | |
9663 | dM0111 = mp*(dSM3p1k-3.*dSM1p1k*dSM1p2k+2.*dSM1p3k) | |
9664 | - 3.*(s1p1k*(dSM2p1k-dSM1p2k) | |
9665 | + 2.*(s1p3k-s1p2k*dSM1p1k)); | |
9666 | } | |
9667 | else if(type == "RP") | |
9668 | { | |
9669 | // q_{m*n,k}: (Remark: m=1 is 0, k=0 iz zero (to be improved!)) | |
9670 | q1n2kRe = fReRPQ1dEBE[0][pe][0][2]->GetBinContent(fReRPQ1dEBE[0][pe][0][2]->GetBin(b)) | |
9671 | * fReRPQ1dEBE[0][pe][0][2]->GetBinEntries(fReRPQ1dEBE[0][pe][0][2]->GetBin(b)); | |
9672 | q1n2kIm = fImRPQ1dEBE[0][pe][0][2]->GetBinContent(fImRPQ1dEBE[0][pe][0][2]->GetBin(b)) | |
9673 | * fImRPQ1dEBE[0][pe][0][2]->GetBinEntries(fImRPQ1dEBE[0][pe][0][2]->GetBin(b)); | |
9674 | q2n1kRe = fReRPQ1dEBE[0][pe][1][1]->GetBinContent(fReRPQ1dEBE[0][pe][1][1]->GetBin(b)) | |
9675 | * fReRPQ1dEBE[0][pe][1][1]->GetBinEntries(fReRPQ1dEBE[0][pe][1][1]->GetBin(b)); | |
9676 | q2n1kIm = fImRPQ1dEBE[0][pe][1][1]->GetBinContent(fImRPQ1dEBE[0][pe][1][1]->GetBin(b)) | |
9677 | * fImRPQ1dEBE[0][pe][1][1]->GetBinEntries(fImRPQ1dEBE[0][pe][1][1]->GetBin(b)); | |
9678 | ||
9679 | // s_{1,1}, s_{1,2} and s_{1,3} // to be improved (add explanation) | |
9680 | s1p1k = pow(fs1dEBE[0][pe][1]->GetBinContent(b)*fs1dEBE[0][pe][1]->GetBinEntries(b),1.); | |
9681 | s1p2k = pow(fs1dEBE[0][pe][2]->GetBinContent(b)*fs1dEBE[0][pe][2]->GetBinEntries(b),1.); | |
9682 | s1p3k = pow(fs1dEBE[0][pe][3]->GetBinContent(b)*fs1dEBE[0][pe][3]->GetBinEntries(b),1.); | |
9683 | ||
9684 | // to be improved (cross-checked): | |
9685 | p1n0kRe = fReRPQ1dEBE[0][pe][0][0]->GetBinContent(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)) | |
9686 | * fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)); | |
9687 | p1n0kIm = fImRPQ1dEBE[0][pe][0][0]->GetBinContent(fImRPQ1dEBE[0][pe][0][0]->GetBin(b)) | |
9688 | * fImRPQ1dEBE[0][pe][0][0]->GetBinEntries(fImRPQ1dEBE[0][pe][0][0]->GetBin(b)); | |
9689 | ||
9690 | mp = fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) | |
9691 | ||
9692 | t = 0; // typeFlag = RP or POI | |
9693 | ||
9694 | // M0111 from Eq. (118) in QC2c (to be improved (notation)): | |
9695 | dM0111 = mp*(dSM3p1k-3.*dSM1p1k*dSM1p2k+2.*dSM1p3k) | |
9696 | - 3.*(s1p1k*(dSM2p1k-dSM1p2k) | |
9697 | + 2.*(s1p3k-s1p2k*dSM1p1k)); | |
9698 | //............................................................................................... | |
9699 | } | |
9700 | ||
9701 | // 2'-particle correlation: | |
9702 | Double_t two1n1nW0W1 = 0.; | |
9703 | if(mp*dSM1p1k-s1p1k) | |
9704 | { | |
9705 | two1n1nW0W1 = (p1n0kRe*dReQ1n1k+p1n0kIm*dImQ1n1k-s1p1k) | |
9706 | / (mp*dSM1p1k-s1p1k); | |
9707 | ||
9708 | // fill profile to get <<2'>> | |
b40a910e | 9709 | fDiffFlowCorrelationsPro[t][pe][0]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],two1n1nW0W1,mp*dSM1p1k-s1p1k); |
9710 | // fill profile to get <<2'>^2> | |
9711 | fDiffFlowSquaredCorrelationsPro[t][pe][0]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],two1n1nW0W1*two1n1nW0W1,mp*dSM1p1k-s1p1k); | |
489d5531 | 9712 | // histogram to store <2'> e-b-e (needed in some other methods): |
9713 | fDiffFlowCorrelationsEBE[t][pe][0]->SetBinContent(b,two1n1nW0W1); | |
9714 | fDiffFlowEventWeightsForCorrelationsEBE[t][pe][0]->SetBinContent(b,mp*dSM1p1k-s1p1k); | |
9715 | } // end of if(mp*dSM1p1k-s1p1k) | |
9716 | ||
9717 | // 4'-particle correlation: | |
9718 | Double_t four1n1n1n1nW0W1W1W1 = 0.; | |
9719 | if(dM0111) | |
9720 | { | |
9721 | four1n1n1n1nW0W1W1W1 = ((pow(dReQ1n1k,2.)+pow(dImQ1n1k,2.))*(p1n0kRe*dReQ1n1k+p1n0kIm*dImQ1n1k) | |
9722 | - q2n1kRe*(pow(dReQ1n1k,2.)-pow(dImQ1n1k,2.)) | |
9723 | - 2.*q2n1kIm*dReQ1n1k*dImQ1n1k | |
9724 | - p1n0kRe*(dReQ1n1k*dReQ2n2k+dImQ1n1k*dImQ2n2k) | |
9725 | + p1n0kIm*(dImQ1n1k*dReQ2n2k-dReQ1n1k*dImQ2n2k) | |
9726 | - 2.*dSM1p2k*(p1n0kRe*dReQ1n1k+p1n0kIm*dImQ1n1k) | |
9727 | - 2.*(pow(dReQ1n1k,2.)+pow(dImQ1n1k,2.))*s1p1k | |
9728 | + 6.*(q1n2kRe*dReQ1n1k+q1n2kIm*dImQ1n1k) | |
9729 | + 1.*(q2n1kRe*dReQ2n2k+q2n1kIm*dImQ2n2k) | |
9730 | + 2.*(p1n0kRe*dReQ1n3k+p1n0kIm*dImQ1n3k) | |
9731 | + 2.*s1p1k*dSM1p2k | |
9732 | - 6.*s1p3k) | |
9733 | / dM0111; // to be improved (notation of dM0111) | |
9734 | ||
9735 | // fill profile to get <<4'>> | |
b40a910e | 9736 | fDiffFlowCorrelationsPro[t][pe][1]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],four1n1n1n1nW0W1W1W1,dM0111); |
9737 | // fill profile to get <<4'>^2> | |
9738 | fDiffFlowSquaredCorrelationsPro[t][pe][1]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],four1n1n1n1nW0W1W1W1*four1n1n1n1nW0W1W1W1,dM0111); | |
489d5531 | 9739 | // histogram to store <4'> e-b-e (needed in some other methods): |
9740 | fDiffFlowCorrelationsEBE[t][pe][1]->SetBinContent(b,four1n1n1n1nW0W1W1W1); | |
9741 | fDiffFlowEventWeightsForCorrelationsEBE[t][pe][1]->SetBinContent(b,dM0111); | |
9742 | } // end of if(dM0111) | |
9743 | } // end of for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
9744 | ||
9745 | } // end of void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrelationsUsingParticleWeights(TString type, TString ptOrEta); // type = RP or POI | |
9746 | ||
489d5531 | 9747 | //================================================================================================================================ |
9748 | ||
489d5531 | 9749 | void AliFlowAnalysisWithQCumulants::FillCommonControlHistograms(AliFlowEventSimple *anEvent) |
9750 | { | |
9751 | // Fill common control histograms. | |
9752 | ||
9753 | Int_t nRP = anEvent->GetEventNSelTracksRP(); // number of RPs (i.e. number of particles used to determine the reaction plane) | |
9754 | fCommonHists->FillControlHistograms(anEvent); | |
dd442cd2 | 9755 | if(fFillMultipleControlHistograms) |
489d5531 | 9756 | { |
dd442cd2 | 9757 | if(nRP>1) |
489d5531 | 9758 | { |
dd442cd2 | 9759 | fCommonHists2nd->FillControlHistograms(anEvent); |
9760 | if(nRP>3) | |
489d5531 | 9761 | { |
dd442cd2 | 9762 | fCommonHists4th->FillControlHistograms(anEvent); |
9763 | if(nRP>5) | |
489d5531 | 9764 | { |
dd442cd2 | 9765 | fCommonHists6th->FillControlHistograms(anEvent); |
9766 | if(nRP>7) | |
9767 | { | |
9768 | fCommonHists8th->FillControlHistograms(anEvent); | |
9769 | } // end of if(nRP>7) | |
9770 | } // end of if(nRP>5) | |
9771 | } // end of if(nRP>3) | |
9772 | } // end of if(nRP>1) | |
9773 | } // end of if(fFillMultipleControlHistograms) | |
489d5531 | 9774 | |
9775 | } // end of void AliFlowAnalysisWithQCumulants::FillCommonControlHistograms(AliFlowEventSimple *anEvent) | |
9776 | ||
489d5531 | 9777 | //================================================================================================================================ |
9778 | ||
489d5531 | 9779 | void AliFlowAnalysisWithQCumulants::ResetEventByEventQuantities() |
9780 | { | |
9781 | // Reset all event by event quantities. | |
9782 | ||
9783 | // integrated flow: | |
9784 | fReQ->Zero(); | |
9785 | fImQ->Zero(); | |
9786 | fSMpk->Zero(); | |
9787 | fIntFlowCorrelationsEBE->Reset(); | |
9788 | fIntFlowEventWeightsForCorrelationsEBE->Reset(); | |
9789 | fIntFlowCorrelationsAllEBE->Reset(); | |
9790 | ||
b92ea2b9 | 9791 | for(Int_t sc=0;sc<2;sc++) |
489d5531 | 9792 | { |
b92ea2b9 | 9793 | fIntFlowCorrectionTermsForNUAEBE[sc]->Reset(); |
9794 | fIntFlowEventWeightForCorrectionTermsForNUAEBE[sc]->Reset(); | |
489d5531 | 9795 | } |
9796 | ||
9797 | // differential flow: | |
9798 | // 1D: | |
9799 | for(Int_t t=0;t<3;t++) // type (RP, POI, POI&&RP) | |
9800 | { | |
9801 | for(Int_t pe=0;pe<2;pe++) // 1D in pt or eta | |
9802 | { | |
9803 | for(Int_t m=0;m<4;m++) // multiple of harmonic | |
9804 | { | |
9805 | for(Int_t k=0;k<9;k++) // power of weight | |
9806 | { | |
9807 | if(fReRPQ1dEBE[t][pe][m][k]) fReRPQ1dEBE[t][pe][m][k]->Reset(); | |
9808 | if(fImRPQ1dEBE[t][pe][m][k]) fImRPQ1dEBE[t][pe][m][k]->Reset(); | |
9809 | } | |
9810 | } | |
9811 | } | |
9812 | } | |
9813 | ||
9814 | for(Int_t t=0;t<3;t++) // type (0 = RP, 1 = POI, 2 = RP&&POI ) | |
9815 | { | |
9816 | for(Int_t pe=0;pe<2;pe++) // 1D in pt or eta | |
9817 | { | |
9818 | for(Int_t k=0;k<9;k++) | |
9819 | { | |
9820 | if(fs1dEBE[t][pe][k]) fs1dEBE[t][pe][k]->Reset(); | |
9821 | } | |
9822 | } | |
9823 | } | |
9824 | ||
9825 | // e-b-e reduced correlations: | |
9826 | for(Int_t t=0;t<2;t++) // type (0 = RP, 1 = POI) | |
9827 | { | |
9828 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
9829 | { | |
9830 | for(Int_t rci=0;rci<4;rci++) // reduced correlation index | |
9831 | { | |
9832 | if(fDiffFlowCorrelationsEBE[t][pe][rci]) fDiffFlowCorrelationsEBE[t][pe][rci]->Reset(); | |
9833 | if(fDiffFlowEventWeightsForCorrelationsEBE[t][pe][rci]) fDiffFlowEventWeightsForCorrelationsEBE[t][pe][rci]->Reset(); | |
9834 | } | |
9835 | } | |
9836 | } | |
9837 | ||
9838 | // correction terms for NUA: | |
9839 | for(Int_t t=0;t<2;t++) // type (0 = RP, 1 = POI) | |
9840 | { | |
9841 | for(Int_t pe=0;pe<2;pe++) // pt or eta | |
9842 | { | |
9843 | for(Int_t sc=0;sc<2;sc++) // sin or cos | |
9844 | { | |
9845 | for(Int_t cti=0;cti<9;cti++) // correction term index | |
9846 | { | |
9847 | fDiffFlowCorrectionTermsForNUAEBE[t][pe][sc][cti]->Reset(); | |
9848 | } | |
9849 | } | |
9850 | } | |
9851 | } | |
9852 | ||
9853 | // 2D (pt,eta) | |
9854 | if(fCalculate2DFlow) | |
9855 | { | |
9856 | for(Int_t t=0;t<3;t++) // type (RP, POI, POI&&RP) | |
9857 | { | |
9858 | for(Int_t m=0;m<4;m++) // multiple of harmonic | |
9859 | { | |
9860 | for(Int_t k=0;k<9;k++) // power of weight | |
9861 | { | |
b77b6434 | 9862 | if(fReRPQ2dEBE[t][m][k]){fReRPQ2dEBE[t][m][k]->Reset();} |
9863 | if(fImRPQ2dEBE[t][m][k]){fImRPQ2dEBE[t][m][k]->Reset();} | |
489d5531 | 9864 | } |
9865 | } | |
9866 | } | |
9867 | for(Int_t t=0;t<3;t++) // type (0 = RP, 1 = POI, 2 = RP&&POI ) | |
9868 | { | |
9869 | for(Int_t k=0;k<9;k++) | |
9870 | { | |
b77b6434 | 9871 | if(fs2dEBE[t][k]){fs2dEBE[t][k]->Reset();} |
489d5531 | 9872 | } |
9873 | } | |
9874 | } // end of if(fCalculate2DFlow) | |
9875 | ||
9876 | } // end of void AliFlowAnalysisWithQCumulants::ResetEventByEventQuantities(); | |
9877 | ||
9878 | ||
9879 | //================================================================================================================================ | |
9880 | ||
9881 | ||
9882 | void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrectionsForNUASinTerms(TString type, TString ptOrEta) | |
9883 | { | |
9884 | // Calculate correction terms for non-uniform acceptance for differential flow (sin terms). | |
9885 | ||
9886 | // Results are stored in fDiffFlowCorrectionTermsForNUAPro[t][pe][0][cti], where cti runs as follows: | |
9887 | // 0: <<sin n(psi1)>> | |
9888 | // 1: <<sin n(psi1+phi2)>> | |
9889 | // 2: <<sin n(psi1+phi2-phi3)>> | |
9890 | // 3: <<sin n(psi1-phi2-phi3)>>: | |
9891 | // 4: | |
9892 | // 5: | |
9893 | // 6: | |
9894 | ||
9895 | // multiplicity: | |
9896 | Double_t dMult = (*fSMpk)(0,0); | |
9897 | ||
9898 | // real and imaginary parts of non-weighted Q-vectors evaluated in harmonics n, 2n, 3n and 4n: | |
9899 | Double_t dReQ1n = (*fReQ)(0,0); | |
9900 | Double_t dReQ2n = (*fReQ)(1,0); | |
9901 | //Double_t dReQ3n = (*fReQ)(2,0); | |
9902 | //Double_t dReQ4n = (*fReQ)(3,0); | |
9903 | Double_t dImQ1n = (*fImQ)(0,0); | |
9904 | Double_t dImQ2n = (*fImQ)(1,0); | |
9905 | //Double_t dImQ3n = (*fImQ)(2,0); | |
9906 | //Double_t dImQ4n = (*fImQ)(3,0); | |
9907 | ||
2a98ceb8 | 9908 | Int_t t = 0; // type flag |
9909 | Int_t pe = 0; // ptEta flag | |
489d5531 | 9910 | |
9911 | if(type == "RP") | |
9912 | { | |
9913 | t = 0; | |
9914 | } else if(type == "POI") | |
9915 | { | |
9916 | t = 1; | |
9917 | } | |
9918 | ||
9919 | if(ptOrEta == "Pt") | |
9920 | { | |
9921 | pe = 0; | |
9922 | } else if(ptOrEta == "Eta") | |
9923 | { | |
9924 | pe = 1; | |
9925 | } | |
9926 | ||
9927 | Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; | |
9928 | Double_t minPtEta[2] = {fPtMin,fEtaMin}; | |
9929 | //Double_t maxPtEta[2] = {fPtMax,fEtaMax}; | |
9930 | Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; | |
9931 | ||
9932 | // looping over all bins and calculating correction terms: | |
9933 | for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
9934 | { | |
9935 | // real and imaginary parts of p_{m*n,0} (non-weighted Q-vector evaluated for POIs in particular pt or eta bin): | |
9936 | Double_t p1n0kRe = 0.; | |
9937 | Double_t p1n0kIm = 0.; | |
9938 | ||
9939 | // number of POIs in particular pt or eta bin: | |
9940 | Double_t mp = 0.; | |
9941 | ||
9942 | // real and imaginary parts of q_{m*n,0} (non-weighted Q-vector evaluated for particles which are both RPs and POIs in particular pt or eta bin): | |
9943 | Double_t q1n0kRe = 0.; | |
9944 | Double_t q1n0kIm = 0.; | |
9945 | Double_t q2n0kRe = 0.; | |
9946 | Double_t q2n0kIm = 0.; | |
9947 | ||
9948 | // number of particles which are both RPs and POIs in particular pt or eta bin: | |
9949 | Double_t mq = 0.; | |
9950 | ||
9951 | if(type == "POI") | |
9952 | { | |
9953 | // q_{m*n,0}: | |
9954 | q1n0kRe = fReRPQ1dEBE[2][pe][0][0]->GetBinContent(fReRPQ1dEBE[2][pe][0][0]->GetBin(b)) | |
9955 | * fReRPQ1dEBE[2][pe][0][0]->GetBinEntries(fReRPQ1dEBE[2][pe][0][0]->GetBin(b)); | |
9956 | q1n0kIm = fImRPQ1dEBE[2][pe][0][0]->GetBinContent(fImRPQ1dEBE[2][pe][0][0]->GetBin(b)) | |
9957 | * fImRPQ1dEBE[2][pe][0][0]->GetBinEntries(fImRPQ1dEBE[2][pe][0][0]->GetBin(b)); | |
9958 | q2n0kRe = fReRPQ1dEBE[2][pe][1][0]->GetBinContent(fReRPQ1dEBE[2][pe][1][0]->GetBin(b)) | |
9959 | * fReRPQ1dEBE[2][pe][1][0]->GetBinEntries(fReRPQ1dEBE[2][pe][1][0]->GetBin(b)); | |
9960 | q2n0kIm = fImRPQ1dEBE[2][pe][1][0]->GetBinContent(fImRPQ1dEBE[2][pe][1][0]->GetBin(b)) | |
9961 | * fImRPQ1dEBE[2][pe][1][0]->GetBinEntries(fImRPQ1dEBE[2][pe][1][0]->GetBin(b)); | |
9962 | ||
9963 | mq = fReRPQ1dEBE[2][pe][0][0]->GetBinEntries(fReRPQ1dEBE[2][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) | |
9964 | } | |
9965 | else if(type == "RP") | |
9966 | { | |
9967 | // q_{m*n,0}: | |
9968 | q1n0kRe = fReRPQ1dEBE[0][pe][0][0]->GetBinContent(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)) | |
9969 | * fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)); | |
9970 | q1n0kIm = fImRPQ1dEBE[0][pe][0][0]->GetBinContent(fImRPQ1dEBE[0][pe][0][0]->GetBin(b)) | |
9971 | * fImRPQ1dEBE[0][pe][0][0]->GetBinEntries(fImRPQ1dEBE[0][pe][0][0]->GetBin(b)); | |
9972 | q2n0kRe = fReRPQ1dEBE[0][pe][1][0]->GetBinContent(fReRPQ1dEBE[0][pe][1][0]->GetBin(b)) | |
9973 | * fReRPQ1dEBE[0][pe][1][0]->GetBinEntries(fReRPQ1dEBE[0][pe][1][0]->GetBin(b)); | |
9974 | q2n0kIm = fImRPQ1dEBE[0][pe][1][0]->GetBinContent(fImRPQ1dEBE[0][pe][1][0]->GetBin(b)) | |
9975 | * fImRPQ1dEBE[0][pe][1][0]->GetBinEntries(fImRPQ1dEBE[0][pe][1][0]->GetBin(b)); | |
9976 | ||
9977 | mq = fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) | |
9978 | } | |
9979 | if(type == "POI") | |
9980 | { | |
9981 | // p_{m*n,0}: | |
9982 | p1n0kRe = fReRPQ1dEBE[1][pe][0][0]->GetBinContent(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)) | |
9983 | * fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)); | |
9984 | p1n0kIm = fImRPQ1dEBE[1][pe][0][0]->GetBinContent(fImRPQ1dEBE[1][pe][0][0]->GetBin(b)) | |
9985 | * fImRPQ1dEBE[1][pe][0][0]->GetBinEntries(fImRPQ1dEBE[1][pe][0][0]->GetBin(b)); | |
9986 | ||
9987 | mp = fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) | |
9988 | ||
9989 | t = 1; // typeFlag = RP or POI | |
9990 | } | |
9991 | else if(type == "RP") | |
9992 | { | |
9993 | // p_{m*n,0} = q_{m*n,0}: | |
9994 | p1n0kRe = q1n0kRe; | |
9995 | p1n0kIm = q1n0kIm; | |
9996 | ||
9997 | mp = mq; | |
9998 | ||
9999 | t = 0; // typeFlag = RP or POI | |
10000 | } | |
10001 | ||
10002 | // <<sin n(psi1)>>: | |
10003 | Double_t sinP1nPsi = 0.; | |
10004 | if(mp) | |
10005 | { | |
10006 | sinP1nPsi = p1n0kIm/mp; | |
10007 | // fill profile for <<sin n(psi1)>>: | |
10008 | fDiffFlowCorrectionTermsForNUAPro[t][pe][0][0]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sinP1nPsi,mp); | |
10009 | // histogram to store <sin n(psi1)> e-b-e (needed in some other methods): | |
10010 | fDiffFlowCorrectionTermsForNUAEBE[t][pe][0][0]->SetBinContent(b,sinP1nPsi); | |
10011 | } // end of if(mp) | |
10012 | ||
10013 | // <<sin n(psi1+phi2)>>: | |
10014 | Double_t sinP1nPsiP1nPhi = 0.; | |
10015 | if(mp*dMult-mq) | |
10016 | { | |
10017 | sinP1nPsiP1nPhi = (p1n0kRe*dImQ1n+p1n0kIm*dReQ1n-q2n0kIm)/(mp*dMult-mq); | |
10018 | // fill profile for <<sin n(psi1+phi2)>>: | |
10019 | fDiffFlowCorrectionTermsForNUAPro[t][pe][0][1]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sinP1nPsiP1nPhi,mp*dMult-mq); | |
10020 | // histogram to store <sin n(psi1+phi2)> e-b-e (needed in some other methods): | |
10021 | fDiffFlowCorrectionTermsForNUAEBE[t][pe][0][1]->SetBinContent(b,sinP1nPsiP1nPhi); | |
10022 | } // end of if(mp*dMult-mq) | |
10023 | ||
10024 | // <<sin n(psi1+phi2-phi3)>>: | |
10025 | Double_t sinP1nPsi1P1nPhi2MPhi3 = 0.; | |
10026 | if(mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)) | |
10027 | { | |
10028 | sinP1nPsi1P1nPhi2MPhi3 = (p1n0kIm*(pow(dImQ1n,2.)+pow(dReQ1n,2.)-dMult) | |
10029 | - 1.*(q2n0kIm*dReQ1n-q2n0kRe*dImQ1n) | |
10030 | - mq*dImQ1n+2.*q1n0kIm) | |
10031 | / (mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)); | |
10032 | // fill profile for <<sin n(psi1+phi2)>>: | |
10033 | fDiffFlowCorrectionTermsForNUAPro[t][pe][0][2]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sinP1nPsi1P1nPhi2MPhi3,mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)); | |
10034 | // histogram to store <sin n(psi1+phi2)> e-b-e (needed in some other methods): | |
10035 | fDiffFlowCorrectionTermsForNUAEBE[t][pe][0][2]->SetBinContent(b,sinP1nPsi1P1nPhi2MPhi3); | |
10036 | } // end of if(mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)) | |
10037 | ||
10038 | // <<sin n(psi1-phi2-phi3)>>: | |
10039 | Double_t sinP1nPsi1M1nPhi2MPhi3 = 0.; | |
10040 | if(mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)) | |
10041 | { | |
10042 | sinP1nPsi1M1nPhi2MPhi3 = (p1n0kIm*(pow(dReQ1n,2.)-pow(dImQ1n,2.))-2.*p1n0kRe*dReQ1n*dImQ1n | |
10043 | - 1.*(p1n0kIm*dReQ2n-p1n0kRe*dImQ2n) | |
10044 | + 2.*mq*dImQ1n-2.*q1n0kIm) | |
10045 | / (mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)); | |
10046 | // fill profile for <<sin n(psi1+phi2)>>: | |
10047 | fDiffFlowCorrectionTermsForNUAPro[t][pe][0][3]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sinP1nPsi1M1nPhi2MPhi3,mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)); | |
10048 | // histogram to store <sin n(psi1+phi2)> e-b-e (needed in some other methods): | |
10049 | fDiffFlowCorrectionTermsForNUAEBE[t][pe][0][3]->SetBinContent(b,sinP1nPsi1M1nPhi2MPhi3); | |
10050 | } // end of if(mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)) | |
10051 | } // end of for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
10052 | ||
10053 | } // end of AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrectionsForNUASinTerms(TString type, TString ptOrEta) | |
10054 | ||
10055 | ||
10056 | //================================================================================================================================ | |
10057 | ||
10058 | ||
10059 | void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrectionsForNUACosTerms(TString type, TString ptOrEta) | |
10060 | { | |
10061 | // Calculate correction terms for non-uniform acceptance for differential flow (cos terms). | |
10062 | ||
10063 | // Results are stored in fDiffFlowCorrectionTermsForNUAPro[t][pe][1][cti], where cti runs as follows: | |
10064 | // 0: <<cos n(psi)>> | |
10065 | // 1: <<cos n(psi1+phi2)>> | |
10066 | // 2: <<cos n(psi1+phi2-phi3)>> | |
10067 | // 3: <<cos n(psi1-phi2-phi3)>> | |
10068 | // 4: | |
10069 | // 5: | |
10070 | // 6: | |
10071 | ||
10072 | // multiplicity: | |
10073 | Double_t dMult = (*fSMpk)(0,0); | |
10074 | ||
10075 | // real and imaginary parts of non-weighted Q-vectors evaluated in harmonics n, 2n, 3n and 4n: | |
10076 | Double_t dReQ1n = (*fReQ)(0,0); | |
10077 | Double_t dReQ2n = (*fReQ)(1,0); | |
10078 | //Double_t dReQ3n = (*fReQ)(2,0); | |
10079 | //Double_t dReQ4n = (*fReQ)(3,0); | |
10080 | Double_t dImQ1n = (*fImQ)(0,0); | |
10081 | Double_t dImQ2n = (*fImQ)(1,0); | |
10082 | //Double_t dImQ3n = (*fImQ)(2,0); | |
10083 | //Double_t dImQ4n = (*fImQ)(3,0); | |
10084 | ||
2a98ceb8 | 10085 | Int_t t = 0; // type flag |
10086 | Int_t pe = 0; // ptEta flag | |
489d5531 | 10087 | |
10088 | if(type == "RP") | |
10089 | { | |
10090 | t = 0; | |
10091 | } else if(type == "POI") | |
10092 | { | |
10093 | t = 1; | |
10094 | } | |
10095 | ||
10096 | if(ptOrEta == "Pt") | |
10097 | { | |
10098 | pe = 0; | |
10099 | } else if(ptOrEta == "Eta") | |
10100 | { | |
10101 | pe = 1; | |
10102 | } | |
10103 | ||
10104 | Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; | |
10105 | Double_t minPtEta[2] = {fPtMin,fEtaMin}; | |
10106 | //Double_t maxPtEta[2] = {fPtMax,fEtaMax}; | |
10107 | Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; | |
10108 | ||
10109 | // looping over all bins and calculating correction terms: | |
10110 | for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
10111 | { | |
10112 | // real and imaginary parts of p_{m*n,0} (non-weighted Q-vector evaluated for POIs in particular pt or eta bin): | |
10113 | Double_t p1n0kRe = 0.; | |
10114 | Double_t p1n0kIm = 0.; | |
10115 | ||
10116 | // number of POIs in particular pt or eta bin: | |
10117 | Double_t mp = 0.; | |
10118 | ||
10119 | // real and imaginary parts of q_{m*n,0} (non-weighted Q-vector evaluated for particles which are both RPs and POIs in particular pt or eta bin): | |
10120 | Double_t q1n0kRe = 0.; | |
10121 | Double_t q1n0kIm = 0.; | |
10122 | Double_t q2n0kRe = 0.; | |
10123 | Double_t q2n0kIm = 0.; | |
10124 | ||
10125 | // number of particles which are both RPs and POIs in particular pt or eta bin: | |
10126 | Double_t mq = 0.; | |
10127 | ||
10128 | if(type == "POI") | |
10129 | { | |
10130 | // q_{m*n,0}: | |
10131 | q1n0kRe = fReRPQ1dEBE[2][pe][0][0]->GetBinContent(fReRPQ1dEBE[2][pe][0][0]->GetBin(b)) | |
10132 | * fReRPQ1dEBE[2][pe][0][0]->GetBinEntries(fReRPQ1dEBE[2][pe][0][0]->GetBin(b)); | |
10133 | q1n0kIm = fImRPQ1dEBE[2][pe][0][0]->GetBinContent(fImRPQ1dEBE[2][pe][0][0]->GetBin(b)) | |
10134 | * fImRPQ1dEBE[2][pe][0][0]->GetBinEntries(fImRPQ1dEBE[2][pe][0][0]->GetBin(b)); | |
10135 | q2n0kRe = fReRPQ1dEBE[2][pe][1][0]->GetBinContent(fReRPQ1dEBE[2][pe][1][0]->GetBin(b)) | |
10136 | * fReRPQ1dEBE[2][pe][1][0]->GetBinEntries(fReRPQ1dEBE[2][pe][1][0]->GetBin(b)); | |
10137 | q2n0kIm = fImRPQ1dEBE[2][pe][1][0]->GetBinContent(fImRPQ1dEBE[2][pe][1][0]->GetBin(b)) | |
10138 | * fImRPQ1dEBE[2][pe][1][0]->GetBinEntries(fImRPQ1dEBE[2][pe][1][0]->GetBin(b)); | |
10139 | ||
10140 | mq = fReRPQ1dEBE[2][pe][0][0]->GetBinEntries(fReRPQ1dEBE[2][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) | |
10141 | } | |
10142 | else if(type == "RP") | |
10143 | { | |
10144 | // q_{m*n,0}: | |
10145 | q1n0kRe = fReRPQ1dEBE[0][pe][0][0]->GetBinContent(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)) | |
10146 | * fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)); | |
10147 | q1n0kIm = fImRPQ1dEBE[0][pe][0][0]->GetBinContent(fImRPQ1dEBE[0][pe][0][0]->GetBin(b)) | |
10148 | * fImRPQ1dEBE[0][pe][0][0]->GetBinEntries(fImRPQ1dEBE[0][pe][0][0]->GetBin(b)); | |
10149 | q2n0kRe = fReRPQ1dEBE[0][pe][1][0]->GetBinContent(fReRPQ1dEBE[0][pe][1][0]->GetBin(b)) | |
10150 | * fReRPQ1dEBE[0][pe][1][0]->GetBinEntries(fReRPQ1dEBE[0][pe][1][0]->GetBin(b)); | |
10151 | q2n0kIm = fImRPQ1dEBE[0][pe][1][0]->GetBinContent(fImRPQ1dEBE[0][pe][1][0]->GetBin(b)) | |
10152 | * fImRPQ1dEBE[0][pe][1][0]->GetBinEntries(fImRPQ1dEBE[0][pe][1][0]->GetBin(b)); | |
10153 | ||
10154 | mq = fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) | |
10155 | } | |
10156 | if(type == "POI") | |
10157 | { | |
10158 | // p_{m*n,0}: | |
10159 | p1n0kRe = fReRPQ1dEBE[1][pe][0][0]->GetBinContent(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)) | |
10160 | * fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)); | |
10161 | p1n0kIm = fImRPQ1dEBE[1][pe][0][0]->GetBinContent(fImRPQ1dEBE[1][pe][0][0]->GetBin(b)) | |
10162 | * fImRPQ1dEBE[1][pe][0][0]->GetBinEntries(fImRPQ1dEBE[1][pe][0][0]->GetBin(b)); | |
10163 | ||
10164 | mp = fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) | |
10165 | ||
10166 | t = 1; // typeFlag = RP or POI | |
10167 | } | |
10168 | else if(type == "RP") | |
10169 | { | |
10170 | // p_{m*n,0} = q_{m*n,0}: | |
10171 | p1n0kRe = q1n0kRe; | |
10172 | p1n0kIm = q1n0kIm; | |
10173 | ||
10174 | mp = mq; | |
10175 | ||
10176 | t = 0; // typeFlag = RP or POI | |
10177 | } | |
10178 | ||
10179 | // <<cos n(psi1)>>: | |
10180 | Double_t cosP1nPsi = 0.; | |
10181 | if(mp) | |
10182 | { | |
10183 | cosP1nPsi = p1n0kRe/mp; | |
10184 | ||
10185 | // fill profile for <<cos n(psi1)>>: | |
10186 | fDiffFlowCorrectionTermsForNUAPro[t][pe][1][0]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],cosP1nPsi,mp); | |
10187 | // histogram to store <cos n(psi1)> e-b-e (needed in some other methods): | |
10188 | fDiffFlowCorrectionTermsForNUAEBE[t][pe][1][0]->SetBinContent(b,cosP1nPsi); | |
10189 | } // end of if(mp) | |
10190 | ||
10191 | // <<cos n(psi1+phi2)>>: | |
10192 | Double_t cosP1nPsiP1nPhi = 0.; | |
10193 | if(mp*dMult-mq) | |
10194 | { | |
10195 | cosP1nPsiP1nPhi = (p1n0kRe*dReQ1n-p1n0kIm*dImQ1n-q2n0kRe)/(mp*dMult-mq); | |
10196 | // fill profile for <<sin n(psi1+phi2)>>: | |
10197 | fDiffFlowCorrectionTermsForNUAPro[t][pe][1][1]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],cosP1nPsiP1nPhi,mp*dMult-mq); | |
10198 | // histogram to store <sin n(psi1+phi2)> e-b-e (needed in some other methods): | |
10199 | fDiffFlowCorrectionTermsForNUAEBE[t][pe][1][1]->SetBinContent(b,cosP1nPsiP1nPhi); | |
10200 | } // end of if(mp*dMult-mq) | |
10201 | ||
10202 | // <<cos n(psi1+phi2-phi3)>>: | |
10203 | Double_t cosP1nPsi1P1nPhi2MPhi3 = 0.; | |
10204 | if(mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)) | |
10205 | { | |
10206 | cosP1nPsi1P1nPhi2MPhi3 = (p1n0kRe*(pow(dImQ1n,2.)+pow(dReQ1n,2.)-dMult) | |
10207 | - 1.*(q2n0kRe*dReQ1n+q2n0kIm*dImQ1n) | |
10208 | - mq*dReQ1n+2.*q1n0kRe) | |
10209 | / (mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)); | |
10210 | // fill profile for <<sin n(psi1+phi2)>>: | |
10211 | fDiffFlowCorrectionTermsForNUAPro[t][pe][1][2]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],cosP1nPsi1P1nPhi2MPhi3,mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)); | |
10212 | // histogram to store <sin n(psi1+phi2)> e-b-e (needed in some other methods): | |
10213 | fDiffFlowCorrectionTermsForNUAEBE[t][pe][1][2]->SetBinContent(b,cosP1nPsi1P1nPhi2MPhi3); | |
10214 | } // end of if(mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)) | |
10215 | ||
10216 | // <<cos n(psi1-phi2-phi3)>>: | |
10217 | Double_t cosP1nPsi1M1nPhi2MPhi3 = 0.; | |
10218 | if(mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)) | |
10219 | { | |
10220 | cosP1nPsi1M1nPhi2MPhi3 = (p1n0kRe*(pow(dReQ1n,2.)-pow(dImQ1n,2.))+2.*p1n0kIm*dReQ1n*dImQ1n | |
10221 | - 1.*(p1n0kRe*dReQ2n+p1n0kIm*dImQ2n) | |
10222 | - 2.*mq*dReQ1n+2.*q1n0kRe) | |
10223 | / (mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)); | |
10224 | // fill profile for <<sin n(psi1+phi2)>>: | |
10225 | fDiffFlowCorrectionTermsForNUAPro[t][pe][1][3]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],cosP1nPsi1M1nPhi2MPhi3,mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)); | |
10226 | // histogram to store <sin n(psi1+phi2)> e-b-e (needed in some other methods): | |
10227 | fDiffFlowCorrectionTermsForNUAEBE[t][pe][1][3]->SetBinContent(b,cosP1nPsi1M1nPhi2MPhi3); | |
10228 | } // end of if(mq*(dMult-1.)*(dMult-2.)+(mp-mq)*dMult*(dMult-1.)) | |
10229 | } // end of for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
10230 | ||
10231 | } // end of AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrectionsForNUACosTerms(TString type, TString ptOrEta) | |
10232 | ||
10233 | ||
10234 | //================================================================================================================================== | |
10235 | ||
10236 | ||
10237 | void AliFlowAnalysisWithQCumulants::FinalizeCorrectionTermsForNUADiffFlow(TString type, TString ptOrEta) | |
10238 | { | |
10239 | // Transfer prolfiles into histogams and correctly propagate the error (to be improved: description) | |
10240 | ||
10241 | // to be improved: debugged - I do not correctly transfer all profiles into histos (bug appears only after merging) | |
10242 | ||
2a98ceb8 | 10243 | Int_t t = 0; // type flag |
10244 | Int_t pe = 0; // ptEta flag | |
489d5531 | 10245 | |
10246 | if(type == "RP") | |
10247 | { | |
10248 | t = 0; | |
10249 | } else if(type == "POI") | |
10250 | { | |
10251 | t = 1; | |
10252 | } | |
10253 | ||
10254 | if(ptOrEta == "Pt") | |
10255 | { | |
10256 | pe = 0; | |
10257 | } else if(ptOrEta == "Eta") | |
10258 | { | |
10259 | pe = 1; | |
10260 | } | |
10261 | ||
10262 | Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; | |
10263 | //Double_t minPtEta[2] = {fPtMin,fEtaMin}; | |
10264 | //Double_t maxPtEta[2] = {fPtMax,fEtaMax}; | |
10265 | //Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; | |
10266 | ||
10267 | for(Int_t sc=0;sc<2;sc++) // sin or cos | |
10268 | { | |
10269 | for(Int_t cti=0;cti<9;cti++) // correction term index | |
10270 | { | |
10271 | for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
10272 | { | |
10273 | Double_t correctionTerm = fDiffFlowCorrectionTermsForNUAPro[t][pe][sc][cti]->GetBinContent(b); | |
10274 | fDiffFlowCorrectionTermsForNUAHist[t][pe][sc][cti]->SetBinContent(b,correctionTerm); | |
10275 | // to be improved (propagate error correctly) | |
10276 | // ... | |
10277 | } // end of for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
10278 | } // correction term index | |
10279 | } // end of for(Int_t sc=0;sc<2;sc++) // sin or cos | |
10280 | ||
10281 | }// end of void AliFlowAnalysisWithQCumulants::FinalizeCorrectionTermsForNUADiffFlow(TString type, TString ptOrEta) | |
10282 | ||
10283 | ||
10284 | //================================================================================================================================== | |
10285 | ||
10286 | ||
10287 | void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCumulantsCorrectedForNUA(TString type, TString ptOrEta) | |
10288 | { | |
10289 | // Calculate generalized differential flow Q-cumulants (corrected for non-uniform acceptance) | |
10290 | ||
2a98ceb8 | 10291 | Int_t typeFlag = 0; |
10292 | Int_t ptEtaFlag = 0; | |
489d5531 | 10293 | |
10294 | if(type == "RP") | |
10295 | { | |
10296 | typeFlag = 0; | |
10297 | } else if(type == "POI") | |
10298 | { | |
10299 | typeFlag = 1; | |
10300 | } | |
10301 | ||
10302 | if(ptOrEta == "Pt") | |
10303 | { | |
10304 | ptEtaFlag = 0; | |
10305 | } else if(ptOrEta == "Eta") | |
10306 | { | |
10307 | ptEtaFlag = 1; | |
10308 | } | |
10309 | ||
10310 | // shortcuts: | |
10311 | Int_t t = typeFlag; | |
10312 | Int_t pe = ptEtaFlag; | |
10313 | ||
10314 | // common: | |
10315 | Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; | |
10316 | ||
10317 | // 2-particle correlation: | |
10318 | Double_t two = fIntFlowCorrelationsHist->GetBinContent(1); // <<2>> | |
10319 | // sin term coming from integrated flow: | |
10320 | Double_t sinP1nPhi = fIntFlowCorrectionTermsForNUAHist[0]->GetBinContent(1); // <<sin(n*phi1)>> | |
10321 | Double_t sinP1nPhi1P1nPhi2 = fIntFlowCorrectionTermsForNUAHist[0]->GetBinContent(2); // <<sin(n*(phi1+phi2))>> | |
10322 | Double_t sinP1nPhi1M1nPhi2M1nPhi3 = fIntFlowCorrectionTermsForNUAHist[0]->GetBinContent(3); // <<sin(n*(phi1-phi2-phi3))>> | |
10323 | // cos term coming from integrated flow: | |
10324 | Double_t cosP1nPhi = fIntFlowCorrectionTermsForNUAHist[1]->GetBinContent(1); // <<cos(n*phi1)>> | |
10325 | Double_t cosP1nPhi1P1nPhi2 = fIntFlowCorrectionTermsForNUAHist[1]->GetBinContent(2); // <<cos(n*(phi1+phi2))>> | |
10326 | Double_t cosP1nPhi1M1nPhi2M1nPhi3 = fIntFlowCorrectionTermsForNUAHist[1]->GetBinContent(3); // <<cos(n*(phi1-phi2-phi3))>> | |
10327 | ||
10328 | for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
10329 | { | |
10330 | Double_t twoPrime = fDiffFlowCorrelationsHist[t][pe][0]->GetBinContent(b); // <<2'>> | |
10331 | Double_t fourPrime = fDiffFlowCorrelationsHist[t][pe][1]->GetBinContent(b); // <<4'>> | |
10332 | Double_t sinP1nPsi = fDiffFlowCorrectionTermsForNUAHist[t][pe][0][0]->GetBinContent(b); // <<sin n(Psi)>> | |
10333 | Double_t cosP1nPsi = fDiffFlowCorrectionTermsForNUAHist[t][pe][1][0]->GetBinContent(b); // <<cos n(Psi)>> | |
10334 | Double_t sinP1nPsi1P1nPhi2 = fDiffFlowCorrectionTermsForNUAHist[t][pe][0][1]->GetBinContent(b); // <<sin n(psi1+phi2)>> | |
10335 | Double_t cosP1nPsi1P1nPhi2 = fDiffFlowCorrectionTermsForNUAHist[t][pe][1][1]->GetBinContent(b); // <<cos n(psi1+phi2)>> | |
10336 | Double_t sinP1nPsi1P1nPhi2M1nPhi3 = fDiffFlowCorrectionTermsForNUAHist[t][pe][0][2]->GetBinContent(b); // <<sin n(psi1+phi2-phi3)>> | |
10337 | Double_t cosP1nPsi1P1nPhi2M1nPhi3 = fDiffFlowCorrectionTermsForNUAHist[t][pe][1][2]->GetBinContent(b); // <<cos n(psi1+phi2-phi3)>> | |
10338 | Double_t sinP1nPsi1M1nPhi2M1nPhi3 = fDiffFlowCorrectionTermsForNUAHist[t][pe][0][3]->GetBinContent(b); // <<sin n(psi1-phi2-phi3)>> | |
10339 | Double_t cosP1nPsi1M1nPhi2M1nPhi3 = fDiffFlowCorrectionTermsForNUAHist[t][pe][1][3]->GetBinContent(b); // <<cos n(psi1-phi2-phi3)>> | |
10340 | // generalized QC{2'}: | |
10341 | Double_t qc2Prime = twoPrime - sinP1nPsi*sinP1nPhi - cosP1nPsi*cosP1nPhi; | |
10342 | fDiffFlowCumulants[t][pe][0]->SetBinContent(b,qc2Prime); | |
10343 | // generalized QC{4'}: | |
10344 | Double_t qc4Prime = fourPrime-2.*twoPrime*two | |
10345 | - cosP1nPsi*cosP1nPhi1M1nPhi2M1nPhi3 | |
10346 | + sinP1nPsi*sinP1nPhi1M1nPhi2M1nPhi3 | |
10347 | - cosP1nPhi*cosP1nPsi1M1nPhi2M1nPhi3 | |
10348 | + sinP1nPhi*sinP1nPsi1M1nPhi2M1nPhi3 | |
10349 | - 2.*cosP1nPhi*cosP1nPsi1P1nPhi2M1nPhi3 | |
10350 | - 2.*sinP1nPhi*sinP1nPsi1P1nPhi2M1nPhi3 | |
10351 | - cosP1nPsi1P1nPhi2*cosP1nPhi1P1nPhi2 | |
10352 | - sinP1nPsi1P1nPhi2*sinP1nPhi1P1nPhi2 | |
10353 | + 2.*cosP1nPhi1P1nPhi2*(cosP1nPsi*cosP1nPhi-sinP1nPsi*sinP1nPhi) | |
10354 | + 2.*sinP1nPhi1P1nPhi2*(cosP1nPsi*sinP1nPhi+sinP1nPsi*cosP1nPhi) | |
10355 | + 4.*two*(cosP1nPsi*cosP1nPhi+sinP1nPsi*sinP1nPhi) | |
10356 | + 2.*cosP1nPsi1P1nPhi2*(pow(cosP1nPhi,2.)-pow(sinP1nPhi,2.)) | |
10357 | + 4.*sinP1nPsi1P1nPhi2*cosP1nPhi*sinP1nPhi | |
10358 | + 4.*twoPrime*(pow(cosP1nPhi,2.)+pow(sinP1nPhi,2.)) | |
10359 | - 6.*(pow(cosP1nPhi,2.)-pow(sinP1nPhi,2.)) | |
10360 | * (cosP1nPsi*cosP1nPhi-sinP1nPsi*sinP1nPhi) | |
10361 | - 12.*cosP1nPhi*sinP1nPhi | |
10362 | * (sinP1nPsi*cosP1nPhi+cosP1nPsi*sinP1nPhi); | |
10363 | fDiffFlowCumulants[t][pe][1]->SetBinContent(b,qc4Prime); | |
10364 | } // end of for(Int_t p=1;p<=fnBinsPt;p++) | |
10365 | ||
10366 | } // end of AliFlowAnalysisWithQCumulants::CalculateDiffFlowCumulantsCorrectedForNUA(TString type, TString ptOrEta) | |
10367 | ||
10368 | ||
10369 | //================================================================================================================================== | |
10370 | ||
10371 | ||
10372 | void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrectedForNUA(TString type, TString ptOrEta) | |
10373 | { | |
10374 | // Calculate differential flow corrected for non-uniform acceptance. | |
10375 | ||
10376 | // to be improved (rewritten completely) | |
10377 | ||
2a98ceb8 | 10378 | Int_t typeFlag = 0; |
10379 | Int_t ptEtaFlag = 0; | |
489d5531 | 10380 | |
10381 | if(type == "RP") | |
10382 | { | |
10383 | typeFlag = 0; | |
10384 | } else if(type == "POI") | |
10385 | { | |
10386 | typeFlag = 1; | |
10387 | } | |
10388 | ||
10389 | if(ptOrEta == "Pt") | |
10390 | { | |
10391 | ptEtaFlag = 0; | |
10392 | } else if(ptOrEta == "Eta") | |
10393 | { | |
10394 | ptEtaFlag = 1; | |
10395 | } | |
10396 | ||
10397 | // shortcuts: | |
10398 | Int_t t = typeFlag; | |
10399 | Int_t pe = ptEtaFlag; | |
10400 | ||
10401 | // common: | |
10402 | Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; | |
10403 | ||
10404 | // to be improved: access here generalized QC{2} and QC{4} instead: | |
10405 | Double_t dV2 = fIntFlow->GetBinContent(1); | |
10406 | Double_t dV4 = fIntFlow->GetBinContent(2); | |
10407 | ||
10408 | // loop over pt or eta bins: | |
10409 | for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
10410 | { | |
10411 | // generalized QC{2'}: | |
10412 | Double_t gQC2Prime = fDiffFlowCumulants[t][pe][0]->GetBinContent(b); | |
10413 | // v'{2}: | |
10414 | if(dV2>0) | |
10415 | { | |
10416 | Double_t v2Prime = gQC2Prime/dV2; | |
10417 | fDiffFlow[t][pe][0]->SetBinContent(b,v2Prime); | |
10418 | } | |
10419 | // generalized QC{4'}: | |
10420 | Double_t gQC4Prime = fDiffFlowCumulants[t][pe][1]->GetBinContent(b); | |
10421 | // v'{4}: | |
10422 | if(dV4>0) | |
10423 | { | |
10424 | Double_t v4Prime = -gQC4Prime/pow(dV4,3.); | |
10425 | fDiffFlow[t][pe][1]->SetBinContent(b,v4Prime); | |
10426 | } | |
10427 | } // end of for(Int_t b=1;b<=fnBinsPtEta[pe];b++) | |
10428 | ||
10429 | } // end of void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrectedForNUA(TString type, TString ptOrEta); | |
10430 | ||
10431 | ||
10432 | //================================================================================================================================== | |
10433 | ||
10434 | ||
0328db2d | 10435 | void AliFlowAnalysisWithQCumulants::EvaluateIntFlowCorrelationsWithNestedLoops(AliFlowEventSimple * const anEvent) |
489d5531 | 10436 | { |
10437 | // Evaluate with nested loops multiparticle correlations for integrated flow (without using the particle weights). | |
10438 | ||
10439 | // Remark: Results are stored in profile fIntFlowDirectCorrelations whose binning is organized as follows: | |
10440 | // | |
10441 | // 1st bin: <2>_{1n|1n} = two1n1n = cos(n*(phi1-phi2))> | |
10442 | // 2nd bin: <2>_{2n|2n} = two2n2n = cos(2n*(phi1-phi2))> | |
10443 | // 3rd bin: <2>_{3n|3n} = two3n3n = cos(3n*(phi1-phi2))> | |
10444 | // 4th bin: <2>_{4n|4n} = two4n4n = cos(4n*(phi1-phi2))> | |
10445 | // 5th bin: ---- EMPTY ---- | |
10446 | // 6th bin: <3>_{2n|1n,1n} = three2n1n1n = <cos(n*(2.*phi1-phi2-phi3))> | |
10447 | // 7th bin: <3>_{3n|2n,1n} = three3n2n1n = <cos(n*(3.*phi1-2.*phi2-phi3))> | |
10448 | // 8th bin: <3>_{4n|2n,2n} = three4n2n2n = <cos(n*(4.*phi1-2.*phi2-2.*phi3))> | |
10449 | // 9th bin: <3>_{4n|3n,1n} = three4n3n1n = <cos(n*(4.*phi1-3.*phi2-phi3))> | |
10450 | // 10th bin: ---- EMPTY ---- | |
10451 | // 11th bin: <4>_{1n,1n|1n,1n} = four1n1n1n1n = <cos(n*(phi1+phi2-phi3-phi4))> | |
10452 | // 12th bin: <4>_{2n,1n|2n,1n} = four2n1n2n1n = <cos(2.*n*(phi1+phi2-phi3-phi4))> | |
10453 | // 13th bin: <4>_{2n,2n|2n,2n} = four2n2n2n2n = <cos(n*(2.*phi1+phi2-2.*phi3-phi4))> | |
10454 | // 14th bin: <4>_{3n|1n,1n,1n} = four3n1n1n1n = <cos(n*(3.*phi1-phi2-phi3-phi4))> | |
10455 | // 15th bin: <4>_{3n,1n|3n,1n} = four3n1n3n1n = <cos(n*(4.*phi1-2.*phi2-phi3-phi4))> | |
10456 | // 16th bin: <4>_{3n,1n|2n,2n} = four3n1n2n2n = <cos(n*(3.*phi1+phi2-2.*phi3-2.*phi4))> | |
10457 | // 17th bin: <4>_{4n|2n,1n,1n} = four4n2n1n1n = <cos(n*(3.*phi1+phi2-3.*phi3-phi4))> | |
10458 | // 18th bin: ---- EMPTY ---- | |
10459 | // 19th bin: <5>_{2n|1n,1n,1n,1n} = five2n1n1n1n1n = <cos(n*(2.*phi1+phi2-phi3-phi4-phi5))> | |
10460 | // 20th bin: <5>_{2n,2n|2n,1n,1n} = five2n2n2n1n1n = <cos(n*(2.*phi1+2.*phi2-2.*phi3-phi4-phi5))> | |
10461 | // 21st bin: <5>_{3n,1n|2n,1n,1n} = five3n1n2n1n1n = <cos(n*(3.*phi1+phi2-2.*phi3-phi4-phi5))> | |
10462 | // 22nd bin: <5>_{4n|1n,1n,1n,1n} = five4n1n1n1n1n = <cos(n*(4.*phi1-phi2-phi3-phi4-phi5))> | |
10463 | // 23rd bin: ---- EMPTY ---- | |
10464 | // 24th bin: <6>_{1n,1n,1n|1n,1n,1n} = six1n1n1n1n1n1n = <cos(n*(phi1+phi2+phi3-phi4-phi5-phi6))> | |
10465 | // 25th bin: <6>_{2n,1n,1n|2n,1n,1n} = six2n1n1n2n1n1n = <cos(n*(2.*phi1+2.*phi2-phi3-phi4-phi5-phi6))> | |
10466 | // 26th bin: <6>_{2n,2n|1n,1n,1n,1n} = six2n2n1n1n1n1n = <cos(n*(3.*phi1+phi2-phi3-phi4-phi5-phi6))> | |
10467 | // 27th bin: <6>_{3n,1n|1n,1n,1n,1n} = six3n1n1n1n1n1n = <cos(n*(2.*phi1+phi2+phi3-2.*phi4-phi5-phi6))> | |
10468 | // 28th bin: ---- EMPTY ---- | |
10469 | // 29th bin: <7>_{2n,1n,1n|1n,1n,1n,1n} = seven2n1n1n1n1n1n1n = <cos(n*(2.*phi1+phi2+phi3-phi4-phi5-phi6-phi7))> | |
10470 | // 30th bin: ---- EMPTY ---- | |
10471 | // 31st bin: <8>_{1n,1n,1n,1n|1n,1n,1n,1n} = eight1n1n1n1n1n1n1n1n = <cos(n*(phi1+phi2+phi3+phi4-phi5-phi6-phi7-phi8))> | |
8ed4edc7 | 10472 | // 32nd bin: ---- EMPTY ---- |
10473 | // 33rd bin: <4>_{4n,2n|3n,3n}= four4n2n3n3n = <cos(n*(4.*phi1+2.*phi2-3.*phi3-3.*phi4))> | |
10474 | // 34th bin: <5>_{2n,2n,2n|3n,3n} = five2n2n2n3n3n = <cos(n*(2.*phi1+2.*phi2+2.*phi3-3.*phi4-3.*phi5))> | |
10475 | ||
489d5531 | 10476 | Int_t nPrim = anEvent->NumberOfTracks(); |
10477 | AliFlowTrackSimple *aftsTrack = NULL; | |
10478 | Double_t phi1=0., phi2=0., phi3=0., phi4=0., phi5=0., phi6=0., phi7=0., phi8=0.; | |
10479 | Int_t n = fHarmonic; | |
10480 | Int_t eventNo = (Int_t)fAvMultiplicity->GetBinEntries(1); // to be improved (is this casting safe in general?) | |
10481 | Double_t dMult = (*fSMpk)(0,0); | |
10482 | cout<<endl; | |
10483 | cout<<"Multiparticle correlations: Event number: "<<eventNo<<", multiplicity is "<<dMult<<endl; | |
10484 | if(dMult<2) | |
10485 | { | |
10486 | cout<<"... skipping this event (multiplicity too low) ..."<<endl; | |
10487 | } else if (dMult>fMaxAllowedMultiplicity) | |
10488 | { | |
10489 | cout<<"... skipping this event (multiplicity too high) ..."<<endl; | |
10490 | } else | |
10491 | { | |
10492 | cout<<"... evaluating nested loops (without using particle weights)..."<<endl; | |
10493 | } | |
10494 | ||
10495 | // 2-particle correlations: | |
10496 | if(nPrim>=2 && nPrim<=fMaxAllowedMultiplicity) | |
10497 | { | |
10498 | for(Int_t i1=0;i1<nPrim;i1++) | |
10499 | { | |
10500 | aftsTrack=anEvent->GetTrack(i1); | |
10501 | if(!(aftsTrack->InRPSelection())) continue; | |
10502 | phi1=aftsTrack->Phi(); | |
10503 | for(Int_t i2=0;i2<nPrim;i2++) | |
10504 | { | |
10505 | if(i2==i1)continue; | |
10506 | aftsTrack=anEvent->GetTrack(i2); | |
10507 | if(!(aftsTrack->InRPSelection())) continue; | |
10508 | phi2=aftsTrack->Phi(); | |
10509 | if(nPrim==2) cout<<i1<<" "<<i2<<"\r"<<flush; | |
10510 | // fill the profile with 2-p correlations: | |
10511 | fIntFlowDirectCorrelations->Fill(0.5,cos(n*(phi1-phi2)),1.); // <cos(n*(phi1-phi2))> | |
10512 | fIntFlowDirectCorrelations->Fill(1.5,cos(2.*n*(phi1-phi2)),1.); // <cos(2n*(phi1-phi2))> | |
10513 | fIntFlowDirectCorrelations->Fill(2.5,cos(3.*n*(phi1-phi2)),1.); // <cos(3n*(phi1-phi2))> | |
10514 | fIntFlowDirectCorrelations->Fill(3.5,cos(4.*n*(phi1-phi2)),1.); // <cos(4n*(phi1-phi2))> | |
10515 | } // end of for(Int_t i2=0;i2<nPrim;i2++) | |
10516 | } // end of for(Int_t i1=0;i1<nPrim;i1++) | |
10517 | } // end of if(nPrim>=2) | |
10518 | ||
10519 | // 3-particle correlations: | |
10520 | if(nPrim>=3 && nPrim<=fMaxAllowedMultiplicity) | |
10521 | { | |
10522 | for(Int_t i1=0;i1<nPrim;i1++) | |
10523 | { | |
10524 | aftsTrack=anEvent->GetTrack(i1); | |
10525 | if(!(aftsTrack->InRPSelection())) continue; | |
10526 | phi1=aftsTrack->Phi(); | |
10527 | for(Int_t i2=0;i2<nPrim;i2++) | |
10528 | { | |
10529 | if(i2==i1)continue; | |
10530 | aftsTrack=anEvent->GetTrack(i2); | |
10531 | if(!(aftsTrack->InRPSelection())) continue; | |
10532 | phi2=aftsTrack->Phi(); | |
10533 | for(Int_t i3=0;i3<nPrim;i3++) | |
10534 | { | |
10535 | if(i3==i1||i3==i2)continue; | |
10536 | aftsTrack=anEvent->GetTrack(i3); | |
10537 | if(!(aftsTrack->InRPSelection())) continue; | |
10538 | phi3=aftsTrack->Phi(); | |
10539 | if(nPrim==3) cout<<i1<<" "<<i2<<" "<<i3<<"\r"<<flush; | |
10540 | // fill the profile with 3-p correlations: | |
10541 | fIntFlowDirectCorrelations->Fill(5.,cos(2.*n*phi1-n*(phi2+phi3)),1.); //<3>_{2n|nn,n} | |
10542 | fIntFlowDirectCorrelations->Fill(6.,cos(3.*n*phi1-2.*n*phi2-n*phi3),1.); //<3>_{3n|2n,n} | |
10543 | fIntFlowDirectCorrelations->Fill(7.,cos(4.*n*phi1-2.*n*phi2-2.*n*phi3),1.); //<3>_{4n|2n,2n} | |
10544 | fIntFlowDirectCorrelations->Fill(8.,cos(4.*n*phi1-3.*n*phi2-n*phi3),1.); //<3>_{4n|3n,n} | |
10545 | } // end of for(Int_t i3=0;i3<nPrim;i3++) | |
10546 | } // end of for(Int_t i2=0;i2<nPrim;i2++) | |
10547 | } // end of for(Int_t i1=0;i1<nPrim;i1++) | |
10548 | } // end of if(nPrim>=3) | |
10549 | ||
10550 | // 4-particle correlations: | |
10551 | if(nPrim>=4 && nPrim<=fMaxAllowedMultiplicity) | |
10552 | { | |
10553 | for(Int_t i1=0;i1<nPrim;i1++) | |
10554 | { | |
10555 | aftsTrack=anEvent->GetTrack(i1); | |
10556 | if(!(aftsTrack->InRPSelection())) continue; | |
10557 | phi1=aftsTrack->Phi(); | |
10558 | for(Int_t i2=0;i2<nPrim;i2++) | |
10559 | { | |
10560 | if(i2==i1)continue; | |
10561 | aftsTrack=anEvent->GetTrack(i2); | |
10562 | if(!(aftsTrack->InRPSelection())) continue; | |
10563 | phi2=aftsTrack->Phi(); | |
10564 | for(Int_t i3=0;i3<nPrim;i3++) | |
10565 | { | |
10566 | if(i3==i1||i3==i2)continue; | |
10567 | aftsTrack=anEvent->GetTrack(i3); | |
10568 | if(!(aftsTrack->InRPSelection())) continue; | |
10569 | phi3=aftsTrack->Phi(); | |
10570 | for(Int_t i4=0;i4<nPrim;i4++) | |
10571 | { | |
10572 | if(i4==i1||i4==i2||i4==i3)continue; | |
10573 | aftsTrack=anEvent->GetTrack(i4); | |
10574 | if(!(aftsTrack->InRPSelection())) continue; | |
10575 | phi4=aftsTrack->Phi(); | |
10576 | if(nPrim==4) cout<<i1<<" "<<i2<<" "<<i3<<" "<<i4<<"\r"<<flush; | |
10577 | // fill the profile with 4-p correlations: | |
10578 | fIntFlowDirectCorrelations->Fill(10.,cos(n*phi1+n*phi2-n*phi3-n*phi4),1.); // <4>_{n,n|n,n} | |
10579 | fIntFlowDirectCorrelations->Fill(11.,cos(2.*n*phi1+n*phi2-2.*n*phi3-n*phi4),1.); // <4>_{2n,n|2n,n} | |
10580 | fIntFlowDirectCorrelations->Fill(12.,cos(2.*n*phi1+2*n*phi2-2.*n*phi3-2.*n*phi4),1.); // <4>_{2n,2n|2n,2n} | |
10581 | fIntFlowDirectCorrelations->Fill(13.,cos(3.*n*phi1-n*phi2-n*phi3-n*phi4),1.); // <4>_{3n|n,n,n} | |
10582 | fIntFlowDirectCorrelations->Fill(14.,cos(3.*n*phi1+n*phi2-3.*n*phi3-n*phi4),1.); // <4>_{3n,n|3n,n} | |
10583 | fIntFlowDirectCorrelations->Fill(15.,cos(3.*n*phi1+n*phi2-2.*n*phi3-2.*n*phi4),1.); // <4>_{3n,n|2n,2n} | |
10584 | fIntFlowDirectCorrelations->Fill(16.,cos(4.*n*phi1-2.*n*phi2-n*phi3-n*phi4),1.); // <4>_{4n|2n,n,n} | |
8ed4edc7 | 10585 | fIntFlowDirectCorrelations->Fill(32.,cos(n*(4.*phi1+2.*phi2-3.*phi3-3.*phi4)),1.); // <4>_{4n,2n|3n,3n} |
489d5531 | 10586 | } // end of for(Int_t i4=0;i4<nPrim;i4++) |
10587 | } // end of for(Int_t i3=0;i3<nPrim;i3++) | |
10588 | } // end of for(Int_t i2=0;i2<nPrim;i2++) | |
10589 | } // end of for(Int_t i1=0;i1<nPrim;i1++) | |
10590 | } // end of if(nPrim>=) | |
10591 | ||
10592 | // 5-particle correlations: | |
10593 | if(nPrim>=5 && nPrim<=fMaxAllowedMultiplicity) | |
10594 | { | |
10595 | for(Int_t i1=0;i1<nPrim;i1++) | |
10596 | { | |
10597 | aftsTrack=anEvent->GetTrack(i1); | |
10598 | if(!(aftsTrack->InRPSelection())) continue; | |
10599 | phi1=aftsTrack->Phi(); | |
10600 | for(Int_t i2=0;i2<nPrim;i2++) | |
10601 | { | |
10602 | if(i2==i1)continue; | |
10603 | aftsTrack=anEvent->GetTrack(i2); | |
10604 | if(!(aftsTrack->InRPSelection())) continue; | |
10605 | phi2=aftsTrack->Phi(); | |
10606 | for(Int_t i3=0;i3<nPrim;i3++) | |
10607 | { | |
10608 | if(i3==i1||i3==i2)continue; | |
10609 | aftsTrack=anEvent->GetTrack(i3); | |
10610 | if(!(aftsTrack->InRPSelection())) continue; | |
10611 | phi3=aftsTrack->Phi(); | |
10612 | for(Int_t i4=0;i4<nPrim;i4++) | |
10613 | { | |
10614 | if(i4==i1||i4==i2||i4==i3)continue; | |
10615 | aftsTrack=anEvent->GetTrack(i4); | |
10616 | if(!(aftsTrack->InRPSelection())) continue; | |
10617 | phi4=aftsTrack->Phi(); | |
10618 | for(Int_t i5=0;i5<nPrim;i5++) | |
10619 | { | |
10620 | if(i5==i1||i5==i2||i5==i3||i5==i4)continue; | |
10621 | aftsTrack=anEvent->GetTrack(i5); | |
10622 | if(!(aftsTrack->InRPSelection())) continue; | |
10623 | phi5=aftsTrack->Phi(); | |
10624 | if(nPrim==5) cout<<i1<<" "<<i2<<" "<<i3<<" "<<i4<<" "<<i5<<"\r"<<flush; | |
10625 | // fill the profile with 5-p correlations: | |
10626 | fIntFlowDirectCorrelations->Fill(18.,cos(2.*n*phi1+n*phi2-n*phi3-n*phi4-n*phi5),1.); //<5>_{2n,n|n,n,n} | |
10627 | fIntFlowDirectCorrelations->Fill(19.,cos(2.*n*phi1+2.*n*phi2-2.*n*phi3-n*phi4-n*phi5),1.); //<5>_{2n,2n|2n,n,n} | |
10628 | fIntFlowDirectCorrelations->Fill(20.,cos(3.*n*phi1+n*phi2-2.*n*phi3-n*phi4-n*phi5),1.); //<5>_{3n,n|2n,n,n} | |
10629 | fIntFlowDirectCorrelations->Fill(21.,cos(4.*n*phi1-n*phi2-n*phi3-n*phi4-n*phi5),1.); //<5>_{4n|n,n,n,n} | |
8ed4edc7 | 10630 | fIntFlowDirectCorrelations->Fill(33.,cos(2.*n*phi1+2.*n*phi2+2.*n*phi3-3.*n*phi4-3.*n*phi5),1.); |
489d5531 | 10631 | } // end of for(Int_t i5=0;i5<nPrim;i5++) |
10632 | } // end of for(Int_t i4=0;i4<nPrim;i4++) | |
10633 | } // end of for(Int_t i3=0;i3<nPrim;i3++) | |
10634 | } // end of for(Int_t i2=0;i2<nPrim;i2++) | |
10635 | } // end of for(Int_t i1=0;i1<nPrim;i1++) | |
10636 | } // end of if(nPrim>=5) | |
10637 | ||
10638 | // 6-particle correlations: | |
10639 | if(nPrim>=6 && nPrim<=fMaxAllowedMultiplicity) | |
10640 | { | |
10641 | for(Int_t i1=0;i1<nPrim;i1++) | |
10642 | { | |
10643 | aftsTrack=anEvent->GetTrack(i1); | |
10644 | if(!(aftsTrack->InRPSelection())) continue; | |
10645 | phi1=aftsTrack->Phi(); | |
10646 | for(Int_t i2=0;i2<nPrim;i2++) | |
10647 | { | |
10648 | if(i2==i1)continue; | |
10649 | aftsTrack=anEvent->GetTrack(i2); | |
10650 | if(!(aftsTrack->InRPSelection())) continue; | |
10651 | phi2=aftsTrack->Phi(); | |
10652 | for(Int_t i3=0;i3<nPrim;i3++) | |
10653 | { | |
10654 | if(i3==i1||i3==i2)continue; | |
10655 | aftsTrack=anEvent->GetTrack(i3); | |
10656 | if(!(aftsTrack->InRPSelection())) continue; | |
10657 | phi3=aftsTrack->Phi(); | |
10658 | for(Int_t i4=0;i4<nPrim;i4++) | |
10659 | { | |
10660 | if(i4==i1||i4==i2||i4==i3)continue; | |
10661 | aftsTrack=anEvent->GetTrack(i4); | |
10662 | if(!(aftsTrack->InRPSelection())) continue; | |
10663 | phi4=aftsTrack->Phi(); | |
10664 | for(Int_t i5=0;i5<nPrim;i5++) | |
10665 | { | |
10666 | if(i5==i1||i5==i2||i5==i3||i5==i4)continue; | |
10667 | aftsTrack=anEvent->GetTrack(i5); | |
10668 | if(!(aftsTrack->InRPSelection())) continue; | |
10669 | phi5=aftsTrack->Phi(); | |
10670 | for(Int_t i6=0;i6<nPrim;i6++) | |
10671 | { | |
10672 | if(i6==i1||i6==i2||i6==i3||i6==i4||i6==i5)continue; | |
10673 | aftsTrack=anEvent->GetTrack(i6); | |
10674 | if(!(aftsTrack->InRPSelection())) continue; | |
10675 | phi6=aftsTrack->Phi(); | |
10676 | if(nPrim==6) cout<<i1<<" "<<i2<<" "<<i3<<" "<<i4<<" "<<i5<<" "<<i6<<"\r"<<flush; | |
10677 | // fill the profile with 6-p correlations: | |
10678 | fIntFlowDirectCorrelations->Fill(23.,cos(n*phi1+n*phi2+n*phi3-n*phi4-n*phi5-n*phi6),1.); //<6>_{n,n,n|n,n,n} | |
10679 | fIntFlowDirectCorrelations->Fill(24.,cos(2.*n*phi1+n*phi2+n*phi3-2.*n*phi4-n*phi5-n*phi6),1.); //<6>_{2n,n,n|2n,n,n} | |
10680 | fIntFlowDirectCorrelations->Fill(25.,cos(2.*n*phi1+2.*n*phi2-n*phi3-n*phi4-n*phi5-n*phi6),1.); //<6>_{2n,2n|n,n,n,n} | |
10681 | fIntFlowDirectCorrelations->Fill(26.,cos(3.*n*phi1+n*phi2-n*phi3-n*phi4-n*phi5-n*phi6),1.); //<6>_{3n,n|n,n,n,n} | |
10682 | } // end of for(Int_t i6=0;i6<nPrim;i6++) | |
10683 | } // end of for(Int_t i5=0;i5<nPrim;i5++) | |
10684 | } // end of for(Int_t i4=0;i4<nPrim;i4++) | |
10685 | } // end of for(Int_t i3=0;i3<nPrim;i3++) | |
10686 | } // end of for(Int_t i2=0;i2<nPrim;i2++) | |
10687 | } // end of for(Int_t i1=0;i1<nPrim;i1++) | |
10688 | } // end of if(nPrim>=6) | |
10689 | ||
10690 | // 7-particle correlations: | |
10691 | if(nPrim>=7 && nPrim<=fMaxAllowedMultiplicity) | |
10692 | { | |
10693 | for(Int_t i1=0;i1<nPrim;i1++) | |
10694 | { | |
10695 | aftsTrack=anEvent->GetTrack(i1); | |
10696 | if(!(aftsTrack->InRPSelection())) continue; | |
10697 | phi1=aftsTrack->Phi(); | |
10698 | for(Int_t i2=0;i2<nPrim;i2++) | |
10699 | { | |
10700 | if(i2==i1)continue; | |
10701 | aftsTrack=anEvent->GetTrack(i2); | |
10702 | if(!(aftsTrack->InRPSelection())) continue; | |
10703 | phi2=aftsTrack->Phi(); | |
10704 | for(Int_t i3=0;i3<nPrim;i3++) | |
10705 | { | |
10706 | if(i3==i1||i3==i2)continue; | |
10707 | aftsTrack=anEvent->GetTrack(i3); | |
10708 | if(!(aftsTrack->InRPSelection())) continue; | |
10709 | phi3=aftsTrack->Phi(); | |
10710 | for(Int_t i4=0;i4<nPrim;i4++) | |
10711 | { | |
10712 | if(i4==i1||i4==i2||i4==i3)continue; | |
10713 | aftsTrack=anEvent->GetTrack(i4); | |
10714 | if(!(aftsTrack->InRPSelection())) continue; | |
10715 | phi4=aftsTrack->Phi(); | |
10716 | for(Int_t i5=0;i5<nPrim;i5++) | |
10717 | { | |
10718 | if(i5==i1||i5==i2||i5==i3||i5==i4)continue; | |
10719 | aftsTrack=anEvent->GetTrack(i5); | |
10720 | if(!(aftsTrack->InRPSelection())) continue; | |
10721 | phi5=aftsTrack->Phi(); | |
10722 | for(Int_t i6=0;i6<nPrim;i6++) | |
10723 | { | |
10724 | if(i6==i1||i6==i2||i6==i3||i6==i4||i6==i5)continue; | |
10725 | aftsTrack=anEvent->GetTrack(i6); | |
10726 | if(!(aftsTrack->InRPSelection())) continue; | |
10727 | phi6=aftsTrack->Phi(); | |
10728 | for(Int_t i7=0;i7<nPrim;i7++) | |
10729 | { | |
10730 | if(i7==i1||i7==i2||i7==i3||i7==i4||i7==i5||i7==i6)continue; | |
10731 | aftsTrack=anEvent->GetTrack(i7); | |
10732 | if(!(aftsTrack->InRPSelection())) continue; | |
10733 | phi7=aftsTrack->Phi(); | |
10734 | if(nPrim==7) cout<<i1<<" "<<i2<<" "<<i3<<" "<<i4<<" "<<i5<<" "<<i6<<" "<<i7<<"\r"<<flush; | |
10735 | // fill the profile with 7-p correlation: | |
10736 | fIntFlowDirectCorrelations->Fill(28.,cos(2.*n*phi1+n*phi2+n*phi3-n*phi4-n*phi5-n*phi6-n*phi7),1.); // <7>_{2n,n,n|n,n,n,n} | |
10737 | } // end of for(Int_t i7=0;i7<nPrim;i7++) | |
10738 | } // end of for(Int_t i6=0;i6<nPrim;i6++) | |
10739 | } // end of for(Int_t i5=0;i5<nPrim;i5++) | |
10740 | } // end of for(Int_t i4=0;i4<nPrim;i4++) | |
10741 | } // end of for(Int_t i3=0;i3<nPrim;i3++) | |
10742 | } // end of for(Int_t i2=0;i2<nPrim;i2++) | |
10743 | } // end of for(Int_t i1=0;i1<nPrim;i1++) | |
10744 | } // end of if(nPrim>=7) | |
10745 | ||
10746 | // 8-particle correlations: | |
10747 | if(nPrim>=8 && nPrim<=fMaxAllowedMultiplicity) | |
10748 | { | |
10749 | for(Int_t i1=0;i1<nPrim;i1++) | |
10750 | { | |
10751 | aftsTrack=anEvent->GetTrack(i1); | |
10752 | if(!(aftsTrack->InRPSelection())) continue; | |
10753 | phi1=aftsTrack->Phi(); | |
10754 | for(Int_t i2=0;i2<nPrim;i2++) | |
10755 | { | |
10756 | if(i2==i1)continue; | |
10757 | aftsTrack=anEvent->GetTrack(i2); | |
10758 | if(!(aftsTrack->InRPSelection())) continue; | |
10759 | phi2=aftsTrack->Phi(); | |
10760 | for(Int_t i3=0;i3<nPrim;i3++) | |
10761 | { | |
10762 | if(i3==i1||i3==i2)continue; | |
10763 | aftsTrack=anEvent->GetTrack(i3); | |
10764 | if(!(aftsTrack->InRPSelection())) continue; | |
10765 | phi3=aftsTrack->Phi(); | |
10766 | for(Int_t i4=0;i4<nPrim;i4++) | |
10767 | { | |
10768 | if(i4==i1||i4==i2||i4==i3)continue; | |
10769 | aftsTrack=anEvent->GetTrack(i4); | |
10770 | if(!(aftsTrack->InRPSelection())) continue; | |
10771 | phi4=aftsTrack->Phi(); | |
10772 | for(Int_t i5=0;i5<nPrim;i5++) | |
10773 | { | |
10774 | if(i5==i1||i5==i2||i5==i3||i5==i4)continue; | |
10775 | aftsTrack=anEvent->GetTrack(i5); | |
10776 | if(!(aftsTrack->InRPSelection())) continue; | |
10777 | phi5=aftsTrack->Phi(); | |
10778 | for(Int_t i6=0;i6<nPrim;i6++) | |
10779 | { | |
10780 | if(i6==i1||i6==i2||i6==i3||i6==i4||i6==i5)continue; | |
10781 | aftsTrack=anEvent->GetTrack(i6); | |
10782 | if(!(aftsTrack->InRPSelection())) continue; | |
10783 | phi6=aftsTrack->Phi(); | |
10784 | for(Int_t i7=0;i7<nPrim;i7++) | |
10785 | { | |
10786 | if(i7==i1||i7==i2||i7==i3||i7==i4||i7==i5||i7==i6)continue; | |
10787 | aftsTrack=anEvent->GetTrack(i7); | |
10788 | if(!(aftsTrack->InRPSelection())) continue; | |
10789 | phi7=aftsTrack->Phi(); | |
10790 | for(Int_t i8=0;i8<nPrim;i8++) | |
10791 | { | |
10792 | if(i8==i1||i8==i2||i8==i3||i8==i4||i8==i5||i8==i6||i8==i7)continue; | |
10793 | aftsTrack=anEvent->GetTrack(i8); | |
10794 | if(!(aftsTrack->InRPSelection())) continue; | |
10795 | phi8=aftsTrack->Phi(); | |
10796 | cout<<i1<<" "<<i2<<" "<<i3<<" "<<i4<<" "<<i5<<" "<<i6<<" "<<i7<<" "<<i8<<"\r"<<flush; | |
10797 | // fill the profile with 8-p correlation: | |
10798 | fIntFlowDirectCorrelations->Fill(30.,cos(n*phi1+n*phi2+n*phi3+n*phi4-n*phi5-n*phi6-n*phi7-n*phi8),1.); // <8>_{n,n,n,n|n,n,n,n} | |
10799 | } // end of for(Int_t i8=0;i8<nPrim;i8++) | |
10800 | } // end of for(Int_t i7=0;i7<nPrim;i7++) | |
10801 | } // end of for(Int_t i6=0;i6<nPrim;i6++) | |
10802 | } // end of for(Int_t i5=0;i5<nPrim;i5++) | |
10803 | } // end of for(Int_t i4=0;i4<nPrim;i4++) | |
10804 | } // end of for(Int_t i3=0;i3<nPrim;i3++) | |
10805 | } // end of for(Int_t i2=0;i2<nPrim;i2++) | |
10806 | } // end of for(Int_t i1=0;i1<nPrim;i1++) | |
10807 | } // end of if(nPrim>=8) | |
10808 | ||
10809 | cout<<endl; | |
10810 | ||
10811 | } // end of AliFlowAnalysisWithQCumulants::EvaluateIntFlowCorrelationsWithNestedLoops(AliFlowEventSimple* anEvent) | |
10812 | ||
10813 | ||
10814 | //================================================================================================================================== | |
10815 | ||
10816 | ||
10817 | void AliFlowAnalysisWithQCumulants::CrossCheckIntFlowCorrelations() | |
10818 | { | |
10819 | // Cross-check results for multiparticle correlations needed for int. flow: results from Q-vectors vs results from nested loops. | |
10820 | ||
10821 | cout<<endl; | |
10822 | cout<<endl; | |
10823 | cout<<" *****************************************"<<endl; | |
10824 | cout<<" **** cross-checking the correlations ****"<<endl; | |
10825 | cout<<" **** for integrated flow ****"<<endl; | |
10826 | if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) | |
10827 | { | |
10828 | cout<<" **** (particle weights not used) ****"<<endl; | |
10829 | } else | |
10830 | { | |
10831 | cout<<" **** (particle weights used) ****"<<endl; | |
10832 | } | |
10833 | cout<<" *****************************************"<<endl; | |
10834 | cout<<endl; | |
10835 | cout<<endl; | |
10836 | ||
8ed4edc7 | 10837 | Int_t ciMax = 34; // to be improved (removed eventually when I calculate 6th and 8th order with particle weights) |
489d5531 | 10838 | |
10839 | if(fUsePhiWeights||fUsePtWeights||fUseEtaWeights) | |
10840 | { | |
10841 | ciMax = 11; | |
10842 | } | |
10843 | ||
10844 | for(Int_t ci=1;ci<=ciMax;ci++) | |
10845 | { | |
10846 | if(strcmp((fIntFlowCorrelationsAllPro->GetXaxis())->GetBinLabel(ci), "") == 0) continue; // to be improved (access finalized histogram here) | |
10847 | cout<<(fIntFlowCorrelationsAllPro->GetXaxis())->GetBinLabel(ci)<<":"<<endl; // to be improved (access finalized histogram here) | |
10848 | cout<<"from Q-vectors = "<<fIntFlowCorrelationsAllPro->GetBinContent(ci)<<endl; // to be improved (access finalized histogram here) | |
10849 | cout<<"from nested loops = "<<fIntFlowDirectCorrelations->GetBinContent(ci)<<endl; | |
10850 | cout<<endl; | |
10851 | } | |
10852 | ||
10853 | } // end of void AliFlowAnalysisWithQCumulants::CrossCheckIntFlowCorrelations() | |
10854 | ||
10855 | ||
10856 | //================================================================================================================================ | |
10857 | ||
10858 | ||
10859 | void AliFlowAnalysisWithQCumulants::CrossCheckIntFlowCorrectionTermsForNUA() | |
10860 | { | |
10861 | // Cross-check results for corrections terms for non-uniform acceptance needed for int. flow: results from Q-vectors vs results from nested loops. | |
10862 | ||
10863 | cout<<endl; | |
10864 | cout<<endl; | |
10865 | cout<<" *********************************************"<<endl; | |
10866 | cout<<" **** cross-checking the correction terms ****"<<endl; | |
10867 | cout<<" **** for non-uniform acceptance relevant ****"<<endl; | |
10868 | cout<<" **** for integrated flow ****"<<endl; | |
10869 | if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) | |
10870 | { | |
10871 | cout<<" **** (particle weights not used) ****"<<endl; | |
10872 | } else | |
10873 | { | |
10874 | cout<<" **** (particle weights used) ****"<<endl; | |
10875 | } | |
10876 | cout<<" *********************************************"<<endl; | |
10877 | cout<<endl; | |
10878 | cout<<endl; | |
10879 | ||
b92ea2b9 | 10880 | for(Int_t ci=1;ci<=4;ci++) // correction term index (to be improved - hardwired 4) |
489d5531 | 10881 | { |
10882 | for(Int_t sc=0;sc<2;sc++) // sin or cos term | |
10883 | { | |
10884 | if(strcmp((fIntFlowCorrectionTermsForNUAPro[sc]->GetXaxis())->GetBinLabel(ci), "") == 0) continue; // to be improved (access finalized histogram here) | |
10885 | cout<<(fIntFlowCorrectionTermsForNUAPro[sc]->GetXaxis())->GetBinLabel(ci)<<":"<<endl; // to be improved (access finalized histogram here) | |
10886 | cout<<"from Q-vectors = "<<fIntFlowCorrectionTermsForNUAPro[sc]->GetBinContent(ci)<<endl; // to be improved (access finalized histogram here) | |
10887 | cout<<"from nested loops = "<<fIntFlowDirectCorrectionTermsForNUA[sc]->GetBinContent(ci)<<endl; | |
10888 | cout<<endl; | |
10889 | } // end of for(Int_t sc=0;sc<2;sc++) // sin or cos term | |
10890 | } // end of for(Int_t ci=1;ci<=10;ci++) // correction term index | |
10891 | ||
10892 | } // end of void AliFlowAnalysisWithQCumulants::CrossCheckIntFlowCorrectionTermsForNUA() | |
10893 | ||
10894 | ||
10895 | //================================================================================================================================ | |
10896 | ||
10897 | ||
0328db2d | 10898 | void AliFlowAnalysisWithQCumulants::EvaluateIntFlowCorrelationsWithNestedLoopsUsingParticleWeights(AliFlowEventSimple * const anEvent) |
489d5531 | 10899 | { |
10900 | // Evaluate with nested loops multiparticle correlations for integrated flow (using the particle weights). | |
10901 | ||
10902 | // Results are stored in profile fIntFlowDirectCorrelations. | |
10903 | // Remark 1: When particle weights are used the binning of fIntFlowDirectCorrelations is organized as follows: | |
10904 | // | |
10905 | // 1st bin: <2>_{1n|1n} = two1n1nW1W1 = <w1 w2 cos(n*(phi1-phi2))> | |
10906 | // 2nd bin: <2>_{2n|2n} = two2n2nW2W2 = <w1^2 w2^2 cos(2n*(phi1-phi2))> | |
10907 | // 3rd bin: <2>_{3n|3n} = two3n3nW3W3 = <w1^3 w2^3 cos(3n*(phi1-phi2))> | |
10908 | // 4th bin: <2>_{4n|4n} = two4n4nW4W4 = <w1^4 w2^4 cos(4n*(phi1-phi2))> | |
10909 | // 5th bin: ---- EMPTY ---- | |
10910 | // 6th bin: <3>_{2n|1n,1n} = three2n1n1nW2W1W1 = <w1^2 w2 w3 cos(n*(2phi1-phi2-phi3))> | |
10911 | // 7th bin: <3>_{3n|2n,1n} = ... | |
10912 | // 8th bin: <3>_{4n|2n,2n} = ... | |
10913 | // 9th bin: <3>_{4n|3n,1n} = ... | |
10914 | // 10th bin: ---- EMPTY ---- | |
10915 | // 11th bin: <4>_{1n,1n|1n,1n} = four1n1n1n1nW1W1W1W1 = <w1 w2 w3 w4 cos(n*(phi1+phi2-phi3-phi4))> | |
10916 | // 12th bin: <4>_{2n,1n|2n,1n} = ... | |
10917 | // 13th bin: <4>_{2n,2n|2n,2n} = ... | |
10918 | // 14th bin: <4>_{3n|1n,1n,1n} = ... | |
10919 | // 15th bin: <4>_{3n,1n|3n,1n} = ... | |
10920 | // 16th bin: <4>_{3n,1n|2n,2n} = ... | |
10921 | // 17th bin: <4>_{4n|2n,1n,1n} = ... | |
10922 | // 18th bin: ---- EMPTY ---- | |
10923 | // 19th bin: <5>_{2n|1n,1n,1n,1n} = ... | |
10924 | // 20th bin: <5>_{2n,2n|2n,1n,1n} = ... | |
10925 | // 21st bin: <5>_{3n,1n|2n,1n,1n} = ... | |
10926 | // 22nd bin: <5>_{4n|1n,1n,1n,1n} = ... | |
10927 | // 23rd bin: ---- EMPTY ---- | |
10928 | // 24th bin: <6>_{1n,1n,1n|1n,1n,1n} = ... | |
10929 | // 25th bin: <6>_{2n,1n,1n|2n,1n,1n} = ... | |
10930 | // 26th bin: <6>_{2n,2n|1n,1n,1n,1n} = ... | |
10931 | // 27th bin: <6>_{3n,1n|1n,1n,1n,1n} = ... | |
10932 | // 28th bin: ---- EMPTY ---- | |
10933 | // 29th bin: <7>_{2n,1n,1n|1n,1n,1n,1n} = ... | |
10934 | // 30th bin: ---- EMPTY ---- | |
10935 | // 31st bin: <8>_{1n,1n,1n,1n|1n,1n,1n,1n} = ... | |
57340a27 | 10936 | |
489d5531 | 10937 | // Remark 2: When particle weights are used there are some extra correlations. They are stored in |
10938 | // fIntFlowExtraDirectCorrelations binning of which is organized as follows: | |
57340a27 | 10939 | |
489d5531 | 10940 | // 1st bin: two1n1nW3W1 = <w1^3 w2 cos(n*(phi1-phi2))> |
10941 | // 2nd bin: two1n1nW1W1W2 = <w1 w2 w3^2 cos(n*(phi1-phi2))> | |
10942 | // ... | |
57340a27 | 10943 | |
489d5531 | 10944 | Int_t nPrim = anEvent->NumberOfTracks(); |
10945 | AliFlowTrackSimple *aftsTrack = NULL; | |
10946 | //Double_t phi1=0., phi2=0., phi3=0., phi4=0., phi5=0., phi6=0., phi7=0., phi8=0.; | |
10947 | //Double_t wPhi1=1., wPhi2=1., wPhi3=1., wPhi4=1., wPhi5=1., wPhi6=1., wPhi7=1., wPhi8=1.; | |
10948 | Double_t phi1=0., phi2=0., phi3=0., phi4=0.; | |
10949 | Double_t wPhi1=1., wPhi2=1., wPhi3=1., wPhi4=1.; | |
10950 | Int_t n = fHarmonic; | |
10951 | Int_t eventNo = (Int_t)fAvMultiplicity->GetBinEntries(1); // to be improved (is this casting safe in general?) | |
10952 | Double_t dMult = (*fSMpk)(0,0); | |
10953 | cout<<endl; | |
10954 | cout<<"Multiparticle correlations: Event number: "<<eventNo<<", multiplicity is "<<dMult<<endl; | |
10955 | if(dMult<2) | |
10956 | { | |
10957 | cout<<"... skipping this event (multiplicity too low) ..."<<endl; | |
10958 | } else if (dMult>fMaxAllowedMultiplicity) | |
10959 | { | |
10960 | cout<<"... skipping this event (multiplicity too high) ..."<<endl; | |
10961 | } else | |
10962 | { | |
10963 | cout<<"... evaluating nested loops (using particle weights) ..."<<endl; | |
10964 | } | |
10965 | ||
10966 | // 2-particle correlations: | |
10967 | if(nPrim>=2 && nPrim<=fMaxAllowedMultiplicity) | |
10968 | { | |
10969 | // 2 nested loops multiparticle correlations using particle weights: | |
10970 | for(Int_t i1=0;i1<nPrim;i1++) | |
10971 | { | |
10972 | aftsTrack=anEvent->GetTrack(i1); | |
10973 | if(!(aftsTrack->InRPSelection())) continue; | |
10974 | phi1=aftsTrack->Phi(); | |
10975 | if(fUsePhiWeights && fPhiWeights) wPhi1 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi1*fnBinsPhi/TMath::TwoPi()))); | |
10976 | for(Int_t i2=0;i2<nPrim;i2++) | |
10977 | { | |
10978 | if(i2==i1)continue; | |
10979 | aftsTrack=anEvent->GetTrack(i2); | |
10980 | if(!(aftsTrack->InRPSelection())) continue; | |
10981 | phi2=aftsTrack->Phi(); | |
10982 | if(fUsePhiWeights && fPhiWeights) wPhi2 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi2*fnBinsPhi/TMath::TwoPi()))); | |
10983 | if(nPrim==2) cout<<i1<<" "<<i2<<"\r"<<flush; | |
10984 | // 2-p correlations using particle weights: | |
10985 | if(fUsePhiWeights) fIntFlowDirectCorrelations->Fill(0.5,cos(n*(phi1-phi2)),wPhi1*wPhi2); // <w1 w2 cos( n*(phi1-phi2))> | |
10986 | if(fUsePhiWeights) fIntFlowDirectCorrelations->Fill(1.5,cos(2.*n*(phi1-phi2)),pow(wPhi1,2)*pow(wPhi2,2)); // <w1^2 w2^2 cos(2n*(phi1-phi2))> | |
10987 | if(fUsePhiWeights) fIntFlowDirectCorrelations->Fill(2.5,cos(3.*n*(phi1-phi2)),pow(wPhi1,3)*pow(wPhi2,3)); // <w1^3 w2^3 cos(3n*(phi1-phi2))> | |
10988 | if(fUsePhiWeights) fIntFlowDirectCorrelations->Fill(3.5,cos(4.*n*(phi1-phi2)),pow(wPhi1,4)*pow(wPhi2,4)); // <w1^4 w2^4 cos(4n*(phi1-phi2))> | |
10989 | // extra correlations: | |
10990 | // 2-p extra correlations (do not appear if particle weights are not used): | |
10991 | if(fUsePhiWeights) fIntFlowExtraDirectCorrelations->Fill(0.5,cos(n*(phi1-phi2)),pow(wPhi1,3)*wPhi2); // <w1^3 w2 cos(n*(phi1-phi2))> | |
10992 | // ... | |
10993 | } // end of for(Int_t i2=0;i2<nPrim;i2++) | |
10994 | } // end of for(Int_t i1=0;i1<nPrim;i1++) | |
10995 | } // end of if(nPrim>=2) | |
10996 | ||
10997 | if(nPrim>=3 && nPrim<=fMaxAllowedMultiplicity) | |
57340a27 | 10998 | { |
489d5531 | 10999 | // 3 nested loops multiparticle correlations using particle weights: |
11000 | for(Int_t i1=0;i1<nPrim;i1++) | |
57340a27 | 11001 | { |
489d5531 | 11002 | aftsTrack=anEvent->GetTrack(i1); |
11003 | if(!(aftsTrack->InRPSelection())) continue; | |
11004 | phi1=aftsTrack->Phi(); | |
11005 | if(fUsePhiWeights && fPhiWeights) wPhi1 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi1*fnBinsPhi/TMath::TwoPi()))); | |
11006 | for(Int_t i2=0;i2<nPrim;i2++) | |
11007 | { | |
11008 | if(i2==i1)continue; | |
11009 | aftsTrack=anEvent->GetTrack(i2); | |
11010 | if(!(aftsTrack->InRPSelection())) continue; | |
11011 | phi2=aftsTrack->Phi(); | |
11012 | if(fUsePhiWeights && fPhiWeights) wPhi2 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi2*fnBinsPhi/TMath::TwoPi()))); | |
11013 | for(Int_t i3=0;i3<nPrim;i3++) | |
11014 | { | |
11015 | if(i3==i1||i3==i2)continue; | |
11016 | aftsTrack=anEvent->GetTrack(i3); | |
11017 | if(!(aftsTrack->InRPSelection())) continue; | |
11018 | phi3=aftsTrack->Phi(); | |
11019 | if(fUsePhiWeights && fPhiWeights) wPhi3 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi3*fnBinsPhi/TMath::TwoPi()))); | |
11020 | if(nPrim==3) cout<<i1<<" "<<i2<<" "<<i3<<"\r"<<flush; | |
11021 | // 3-p correlations using particle weights: | |
11022 | if(fUsePhiWeights) fIntFlowDirectCorrelations->Fill(5.5,cos(2.*n*phi1-n*(phi2+phi3)),pow(wPhi1,2)*wPhi2*wPhi3); // <w1^2 w2 w3 cos(n*(2phi1-phi2-phi3))> | |
11023 | // ... | |
11024 | // extra correlations: | |
11025 | // 2-p extra correlations (do not appear if particle weights are not used): | |
11026 | if(fUsePhiWeights) fIntFlowExtraDirectCorrelations->Fill(1.5,cos(n*(phi1-phi2)),wPhi1*wPhi2*pow(wPhi3,2)); // <w1 w2 w3^2 cos(n*(phi1-phi2))> | |
11027 | // ... | |
11028 | // 3-p extra correlations (do not appear if particle weights are not used): | |
11029 | // ... | |
11030 | } // end of for(Int_t i3=0;i3<nPrim;i3++) | |
11031 | } // end of for(Int_t i2=0;i2<nPrim;i2++) | |
11032 | } // end of for(Int_t i1=0;i1<nPrim;i1++) | |
11033 | } // end of if(nPrim>=3) | |
57340a27 | 11034 | |
489d5531 | 11035 | if(nPrim>=4 && nPrim<=fMaxAllowedMultiplicity) |
11036 | { | |
11037 | // 4 nested loops multiparticle correlations using particle weights: | |
11038 | for(Int_t i1=0;i1<nPrim;i1++) | |
11039 | { | |
11040 | aftsTrack=anEvent->GetTrack(i1); | |
11041 | if(!(aftsTrack->InRPSelection())) continue; | |
11042 | phi1=aftsTrack->Phi(); | |
11043 | if(fUsePhiWeights && fPhiWeights) wPhi1 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi1*fnBinsPhi/TMath::TwoPi()))); | |
11044 | for(Int_t i2=0;i2<nPrim;i2++) | |
11045 | { | |
11046 | if(i2==i1)continue; | |
11047 | aftsTrack=anEvent->GetTrack(i2); | |
11048 | if(!(aftsTrack->InRPSelection())) continue; | |
11049 | phi2=aftsTrack->Phi(); | |
11050 | if(fUsePhiWeights && fPhiWeights) wPhi2 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi2*fnBinsPhi/TMath::TwoPi()))); | |
11051 | for(Int_t i3=0;i3<nPrim;i3++) | |
11052 | { | |
11053 | if(i3==i1||i3==i2)continue; | |
11054 | aftsTrack=anEvent->GetTrack(i3); | |
11055 | if(!(aftsTrack->InRPSelection())) continue; | |
11056 | phi3=aftsTrack->Phi(); | |
11057 | if(fUsePhiWeights && fPhiWeights) wPhi3 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi3*fnBinsPhi/TMath::TwoPi()))); | |
11058 | for(Int_t i4=0;i4<nPrim;i4++) | |
11059 | { | |
11060 | if(i4==i1||i4==i2||i4==i3)continue; | |
11061 | aftsTrack=anEvent->GetTrack(i4); | |
11062 | if(!(aftsTrack->InRPSelection())) continue; | |
11063 | phi4=aftsTrack->Phi(); | |
11064 | if(fUsePhiWeights && fPhiWeights) wPhi4 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi4*fnBinsPhi/TMath::TwoPi()))); | |
11065 | if(nPrim>=4) cout<<i1<<" "<<i2<<" "<<i3<<" "<<i4<<"\r"<<flush; // to be improved (replace eventually this if statement with if(nPrim==4)) | |
11066 | // 4-p correlations using particle weights: | |
11067 | if(fUsePhiWeights) fIntFlowDirectCorrelations->Fill(10.5,cos(n*phi1+n*phi2-n*phi3-n*phi4),wPhi1*wPhi2*wPhi3*wPhi4); | |
11068 | // extra correlations: | |
11069 | // 2-p extra correlations (do not appear if particle weights are not used): | |
11070 | // ... | |
11071 | // 3-p extra correlations (do not appear if particle weights are not used): | |
11072 | // ... | |
11073 | // 4-p extra correlations (do not appear if particle weights are not used): | |
11074 | // ... | |
11075 | } // end of for(Int_t i4=0;i4<nPrim;i4++) | |
11076 | } // end of for(Int_t i3=0;i3<nPrim;i3++) | |
11077 | } // end of for(Int_t i2=0;i2<nPrim;i2++) | |
11078 | } // end of for(Int_t i1=0;i1<nPrim;i1++) | |
11079 | } // end of if(nPrim>=4) | |
57340a27 | 11080 | |
489d5531 | 11081 | cout<<endl; |
57340a27 | 11082 | |
489d5531 | 11083 | } // end of void AliFlowAnalysisWithQCumulants::EvaluateIntFlowCorrelationsWithNestedLoopsUsingParticleWeights(AliFlowEventSimple* anEvent) |
57340a27 | 11084 | |
489d5531 | 11085 | |
11086 | //================================================================================================================================ | |
11087 | ||
11088 | ||
11089 | void AliFlowAnalysisWithQCumulants::CrossCheckIntFlowExtraCorrelations() | |
57340a27 | 11090 | { |
489d5531 | 11091 | // Cross-check results for extra multiparticle correlations needed for int. flow |
11092 | // which appear only when particle weights are used: results from Q-vectors vs results from nested loops. | |
57340a27 | 11093 | |
489d5531 | 11094 | cout<<endl; |
11095 | cout<<endl; | |
11096 | cout<<" ***********************************************"<<endl; | |
11097 | cout<<" **** cross-checking the extra correlations ****"<<endl; | |
11098 | cout<<" **** for integrated flow ****"<<endl; | |
11099 | cout<<" ***********************************************"<<endl; | |
11100 | cout<<endl; | |
11101 | cout<<endl; | |
11102 | ||
11103 | for(Int_t eci=1;eci<=2;eci++) // to be improved (increased eciMax eventually when I calculate 6th and 8th) | |
57340a27 | 11104 | { |
489d5531 | 11105 | if(strcmp((fIntFlowExtraCorrelationsPro->GetXaxis())->GetBinLabel(eci), "") == 0) continue; |
11106 | cout<<(fIntFlowExtraCorrelationsPro->GetXaxis())->GetBinLabel(eci)<<":"<<endl; | |
11107 | cout<<"from Q-vectors = "<<fIntFlowExtraCorrelationsPro->GetBinContent(eci)<<endl; | |
11108 | cout<<"from nested loops = "<<fIntFlowExtraDirectCorrelations->GetBinContent(eci)<<endl; | |
11109 | cout<<endl; | |
11110 | } | |
57340a27 | 11111 | |
489d5531 | 11112 | } // end of void AliFlowAnalysisWithQCumulants::CrossCheckIntFlowExtraCorrelations() |
57340a27 | 11113 | |
11114 | ||
489d5531 | 11115 | //================================================================================================================================ |
3b552efe | 11116 | |
11117 | ||
0328db2d | 11118 | void AliFlowAnalysisWithQCumulants::EvaluateIntFlowCorrectionsForNUAWithNestedLoops(AliFlowEventSimple * const anEvent) |
489d5531 | 11119 | { |
11120 | // Evaluate with nested loops correction terms for non-uniform acceptance relevant for NONAME integrated flow (to be improved (name)). | |
11121 | // | |
11122 | // Remark: Both sin and cos correction terms are calculated in this method. Sin terms are stored in fIntFlowDirectCorrectionTermsForNUA[0], | |
11123 | // and cos terms in fIntFlowDirectCorrectionTermsForNUA[1]. Binning of fIntFlowDirectCorrectionTermsForNUA[sc] is organized as follows | |
11124 | // (sc stands for either sin or cos): | |
11125 | ||
11126 | // 1st bin: <<sc(n*(phi1))>> | |
11127 | // 2nd bin: <<sc(n*(phi1+phi2))>> | |
11128 | // 3rd bin: <<sc(n*(phi1-phi2-phi3))>> | |
11129 | // 4th bin: <<sc(n*(2phi1-phi2))>> | |
11130 | ||
11131 | Int_t nPrim = anEvent->NumberOfTracks(); | |
11132 | AliFlowTrackSimple *aftsTrack = NULL; | |
11133 | Double_t phi1=0., phi2=0., phi3=0.; | |
11134 | Int_t n = fHarmonic; | |
11135 | Int_t eventNo = (Int_t)fAvMultiplicity->GetBinEntries(1); // to be improved (is this casting safe in general?) | |
11136 | Double_t dMult = (*fSMpk)(0,0); | |
11137 | cout<<endl; | |
11138 | cout<<"Correction terms for non-uniform acceptance: Event number: "<<eventNo<<", multiplicity is "<<dMult<<endl; | |
11139 | if(dMult<1) | |
3b552efe | 11140 | { |
489d5531 | 11141 | cout<<"... skipping this event (multiplicity too low) ..."<<endl; |
11142 | } else if (dMult>fMaxAllowedMultiplicity) | |
3b552efe | 11143 | { |
489d5531 | 11144 | cout<<"... skipping this event (multiplicity too high) ..."<<endl; |
11145 | } else | |
11146 | { | |
11147 | cout<<"... evaluating nested loops (without using particle weights)..."<<endl; | |
11148 | } | |
11149 | ||
11150 | if(nPrim>=1 && nPrim<=fMaxAllowedMultiplicity) | |
11151 | { | |
11152 | // 1-particle correction terms for non-uniform acceptance: | |
11153 | for(Int_t i1=0;i1<nPrim;i1++) | |
11154 | { | |
11155 | aftsTrack=anEvent->GetTrack(i1); | |
11156 | if(!(aftsTrack->InRPSelection())) continue; | |
11157 | phi1=aftsTrack->Phi(); | |
11158 | if(nPrim==1) cout<<i1<<"\r"<<flush; | |
11159 | // sin terms: | |
11160 | fIntFlowDirectCorrectionTermsForNUA[0]->Fill(0.5,sin(n*phi1),1.); // <sin(n*phi1)> | |
11161 | // cos terms: | |
11162 | fIntFlowDirectCorrectionTermsForNUA[1]->Fill(0.5,cos(n*phi1),1.); // <cos(n*phi1)> | |
11163 | } // end of for(Int_t i1=0;i1<nPrim;i1++) | |
11164 | } // end of if(nPrim>=1) | |
11165 | ||
11166 | if(nPrim>=2 && nPrim<=fMaxAllowedMultiplicity) | |
11167 | { | |
11168 | // 2-particle correction terms for non-uniform acceptance: | |
11169 | for(Int_t i1=0;i1<nPrim;i1++) | |
11170 | { | |
11171 | aftsTrack=anEvent->GetTrack(i1); | |
11172 | if(!(aftsTrack->InRPSelection())) continue; | |
11173 | phi1=aftsTrack->Phi(); | |
11174 | for(Int_t i2=0;i2<nPrim;i2++) | |
3b552efe | 11175 | { |
489d5531 | 11176 | if(i2==i1)continue; |
11177 | aftsTrack=anEvent->GetTrack(i2); | |
11178 | if(!(aftsTrack->InRPSelection())) continue; | |
11179 | phi2=aftsTrack->Phi(); | |
11180 | if(nPrim==2) cout<<i1<<" "<<i2<<"\r"<<flush; | |
11181 | // sin terms: | |
3b552efe | 11182 | fIntFlowDirectCorrectionTermsForNUA[0]->Fill(1.5,sin(n*(phi1+phi2)),1.); // <<sin(n*(phi1+phi2))>> |
489d5531 | 11183 | fIntFlowDirectCorrectionTermsForNUA[0]->Fill(3.5,sin(n*(2*phi1-phi2)),1.); // <<sin(n*(2*phi1-phi2))>> |
11184 | // cos terms: | |
3b552efe | 11185 | fIntFlowDirectCorrectionTermsForNUA[1]->Fill(1.5,cos(n*(phi1+phi2)),1.); // <<cos(n*(phi1+phi2))>> |
489d5531 | 11186 | fIntFlowDirectCorrectionTermsForNUA[1]->Fill(3.5,cos(n*(2*phi1-phi2)),1.); // <<cos(n*(2*phi1-phi2))>> |
11187 | } // end of for(Int_t i2=0;i2<nPrim;i2++) | |
11188 | } // end of for(Int_t i1=0;i1<nPrim;i1++) | |
11189 | } // end of if(nPrim>=2) | |
11190 | ||
11191 | if(nPrim>=3 && nPrim<=fMaxAllowedMultiplicity) | |
11192 | { | |
11193 | // 3-particle correction terms for non-uniform acceptance: | |
11194 | for(Int_t i1=0;i1<nPrim;i1++) | |
11195 | { | |
11196 | aftsTrack=anEvent->GetTrack(i1); | |
11197 | if(!(aftsTrack->InRPSelection())) continue; | |
11198 | phi1=aftsTrack->Phi(); | |
11199 | for(Int_t i2=0;i2<nPrim;i2++) | |
11200 | { | |
11201 | if(i2==i1)continue; | |
11202 | aftsTrack=anEvent->GetTrack(i2); | |
11203 | if(!(aftsTrack->InRPSelection())) continue; | |
11204 | phi2=aftsTrack->Phi(); | |
11205 | for(Int_t i3=0;i3<nPrim;i3++) | |
11206 | { | |
11207 | if(i3==i1||i3==i2)continue; | |
11208 | aftsTrack=anEvent->GetTrack(i3); | |
11209 | if(!(aftsTrack->InRPSelection())) continue; | |
11210 | phi3=aftsTrack->Phi(); | |
11211 | if(nPrim>=3) cout<<i1<<" "<<i2<<" "<<i3<<"\r"<<flush; // to be improved (eventually I will change this if statement) | |
11212 | // sin terms: | |
11213 | fIntFlowDirectCorrectionTermsForNUA[0]->Fill(2.5,sin(n*(phi1-phi2-phi3)),1.); // <<sin(n*(phi1-phi2-phi3))>> | |
11214 | // cos terms: | |
11215 | fIntFlowDirectCorrectionTermsForNUA[1]->Fill(2.5,cos(n*(phi1-phi2-phi3)),1.); // <<cos(n*(phi1-phi2-phi3))>> | |
11216 | } // end of for(Int_t i3=0;i3<nPrim;i3++) | |
11217 | } // end of for(Int_t i2=0;i2<nPrim;i2++) | |
11218 | } // end of for(Int_t i1=0;i1<nPrim;i1++) | |
11219 | } // end of if(nPrim>=3) | |
11220 | ||
11221 | cout<<endl; | |
11222 | } | |
11223 | //================================================================================================================================ | |
0328db2d | 11224 | void AliFlowAnalysisWithQCumulants::EvaluateDiffFlowCorrelationsWithNestedLoops(AliFlowEventSimple * const anEvent, TString type, TString ptOrEta) |
489d5531 | 11225 | { |
11226 | // Evaluate reduced correlations with nested loops without using the particle weights. | |
11227 | ||
11228 | // Remark 1: Reduced correlations are evaluated in pt bin number fCrossCheckInPtBinNo and eta bin number fCrossCheckInEtaBinNo both for RPs and POIs. | |
11229 | // Remark 2: Results are stored in 1 bin profiles fDiffFlowDirectCorrelations[t][pe][ci], where indices runs as follows: | |
11230 | // [0=RP,1=POI][0=Pt,1=Eta][0=<2'>,1=<4'>,2=<6'>,3=<8'>] | |
11231 | // Remark 3: <2'> = <cos(n*(psi1-phi2))> | |
11232 | // <4'> = <cos(n*(psi1+phi2-phi3-phi4))> | |
11233 | // ... | |
11234 | ||
2a98ceb8 | 11235 | Int_t typeFlag = 0; |
11236 | Int_t ptEtaFlag = 0; | |
489d5531 | 11237 | if(type == "RP") |
11238 | { | |
11239 | typeFlag = 0; | |
11240 | } else if(type == "POI") | |
11241 | { | |
11242 | typeFlag = 1; | |
11243 | } | |
11244 | if(ptOrEta == "Pt") | |
11245 | { | |
11246 | ptEtaFlag = 0; | |
11247 | } else if(ptOrEta == "Eta") | |
11248 | { | |
11249 | ptEtaFlag = 1; | |
11250 | } | |
11251 | // shortcuts: | |
11252 | Int_t t = typeFlag; | |
11253 | Int_t pe = ptEtaFlag; | |
11254 | ||
11255 | Double_t lowerPtEtaEdge[2] = {fPtMin+(fCrossCheckInPtBinNo-1)*fPtBinWidth,fEtaMin+(fCrossCheckInEtaBinNo-1)*fEtaBinWidth}; | |
11256 | Double_t upperPtEtaEdge[2] = {fPtMin+fCrossCheckInPtBinNo*fPtBinWidth,fEtaMin+fCrossCheckInEtaBinNo*fEtaBinWidth}; | |
11257 | Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; | |
11258 | ||
11259 | Int_t nPrim = anEvent->NumberOfTracks(); | |
11260 | AliFlowTrackSimple *aftsTrack = NULL; | |
11261 | ||
11262 | Double_t psi1=0., phi2=0., phi3=0., phi4=0.;// phi5=0., phi6=0., phi7=0., phi8=0.; | |
11263 | ||
3b552efe | 11264 | Int_t n = fHarmonic; |
489d5531 | 11265 | |
11266 | // 2'-particle correlations: | |
11267 | for(Int_t i1=0;i1<nPrim;i1++) | |
11268 | { | |
11269 | aftsTrack=anEvent->GetTrack(i1); | |
3b552efe | 11270 | // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) |
11271 | if(typeFlag==1) // this is diff flow of POIs | |
489d5531 | 11272 | { |
11273 | if(ptOrEta == "Pt") | |
11274 | { | |
11275 | if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
11276 | } else if (ptOrEta == "Eta") | |
11277 | { | |
11278 | if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
3b552efe | 11279 | } |
11280 | } else // this is diff flow of RPs | |
11281 | { | |
489d5531 | 11282 | if(ptOrEta == "Pt") |
11283 | { | |
11284 | if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()<upperPtEtaEdge[pe]) && (aftsTrack->InRPSelection())))continue; | |
11285 | } else if (ptOrEta == "Eta") | |
11286 | { | |
11287 | if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()<upperPtEtaEdge[pe]) && (aftsTrack->InRPSelection())))continue; | |
3b552efe | 11288 | } |
11289 | } | |
489d5531 | 11290 | |
11291 | psi1=aftsTrack->Phi(); | |
11292 | for(Int_t i2=0;i2<nPrim;i2++) | |
11293 | { | |
11294 | if(i2==i1)continue; | |
11295 | aftsTrack=anEvent->GetTrack(i2); | |
11296 | // RP condition (!(first) particle in the correlator must be RP): | |
11297 | if(!(aftsTrack->InRPSelection()))continue; | |
11298 | phi2=aftsTrack->Phi(); | |
11299 | // 2'-particle correlations: | |
11300 | fDiffFlowDirectCorrelations[t][pe][0]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(1.*n*(psi1-phi2)),1.); // <cos(n*(psi1-phi2)) | |
11301 | }//end of for(Int_t i2=0;i2<nPrim;i2++) | |
11302 | }//end of for(Int_t i1=0;i1<nPrim;i1++) | |
11303 | ||
11304 | /* | |
11305 | ||
11306 | // 3'-particle correlations: | |
11307 | for(Int_t i1=0;i1<nPrim;i1++) | |
11308 | { | |
11309 | aftsTrack=anEvent->GetTrack(i1); | |
11310 | // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) | |
11311 | if(ptOrEta == "Pt") | |
11312 | { | |
11313 | if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
11314 | } else if (ptOrEta == "Eta") | |
11315 | { | |
11316 | if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
11317 | } | |
11318 | psi1=aftsTrack->Phi(); | |
11319 | for(Int_t i2=0;i2<nPrim;i2++) | |
11320 | { | |
11321 | if(i2==i1)continue; | |
11322 | aftsTrack=anEvent->GetTrack(i2); | |
11323 | // RP condition (!(first) particle in the correlator must be RP): | |
11324 | if(!(aftsTrack->InRPSelection())) continue; | |
11325 | phi2=aftsTrack->Phi(); | |
11326 | for(Int_t i3=0;i3<nPrim;i3++) | |
11327 | { | |
11328 | if(i3==i1||i3==i2)continue; | |
11329 | aftsTrack=anEvent->GetTrack(i3); | |
11330 | // RP condition (!(first) particle in the correlator must be RP): | |
11331 | if(!(aftsTrack->InRPSelection())) continue; | |
11332 | phi3=aftsTrack->Phi(); | |
11333 | // to be improved : where to store it? ->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(n*(2.*phi1-phi2-phi3)),1.); // <w1 w2 w3 cos(n(2psi1-phi2-phi3))> | |
11334 | }//end of for(Int_t i3=0;i3<nPrim;i3++) | |
11335 | }//end of for(Int_t i2=0;i2<nPrim;i2++) | |
11336 | }//end of for(Int_t i1=0;i1<nPrim;i1++) | |
11337 | ||
11338 | */ | |
11339 | ||
11340 | // 4'-particle correlations: | |
11341 | for(Int_t i1=0;i1<nPrim;i1++) | |
11342 | { | |
11343 | aftsTrack=anEvent->GetTrack(i1); | |
3b552efe | 11344 | // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) |
11345 | if(typeFlag==1) // this is diff flow of POIs | |
489d5531 | 11346 | { |
11347 | if(ptOrEta == "Pt") | |
11348 | { | |
11349 | if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
11350 | } else if (ptOrEta == "Eta") | |
11351 | { | |
11352 | if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
3b552efe | 11353 | } |
11354 | } else // this is diff flow of RPs | |
11355 | { | |
489d5531 | 11356 | if(ptOrEta == "Pt") |
11357 | { | |
11358 | if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()<upperPtEtaEdge[pe]) && (aftsTrack->InRPSelection())))continue; | |
11359 | } else if (ptOrEta == "Eta") | |
11360 | { | |
11361 | if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()<upperPtEtaEdge[pe]) && (aftsTrack->InRPSelection())))continue; | |
3b552efe | 11362 | } |
11363 | } | |
489d5531 | 11364 | |
11365 | psi1=aftsTrack->Phi(); | |
11366 | for(Int_t i2=0;i2<nPrim;i2++) | |
11367 | { | |
11368 | if(i2==i1) continue; | |
11369 | aftsTrack=anEvent->GetTrack(i2); | |
11370 | // RP condition (!(first) particle in the correlator must be RP): | |
11371 | if(!(aftsTrack->InRPSelection())) continue; | |
11372 | phi2=aftsTrack->Phi(); | |
11373 | for(Int_t i3=0;i3<nPrim;i3++) | |
11374 | { | |
11375 | if(i3==i1||i3==i2) continue; | |
11376 | aftsTrack=anEvent->GetTrack(i3); | |
11377 | // RP condition (!(first) particle in the correlator must be RP): | |
11378 | if(!(aftsTrack->InRPSelection())) continue; | |
11379 | phi3=aftsTrack->Phi(); | |
11380 | for(Int_t i4=0;i4<nPrim;i4++) | |
11381 | { | |
11382 | if(i4==i1||i4==i2||i4==i3) continue; | |
11383 | aftsTrack=anEvent->GetTrack(i4); | |
11384 | // RP condition (!(first) particle in the correlator must be RP): | |
11385 | if(!(aftsTrack->InRPSelection())) continue; | |
11386 | phi4=aftsTrack->Phi(); | |
11387 | // 4'-particle correlations: | |
11388 | fDiffFlowDirectCorrelations[t][pe][1]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(n*(psi1+phi2-phi3-phi4)),1.); // <cos(n(psi1+phi2-phi3-phi4))> | |
11389 | }//end of for(Int_t i4=0;i4<nPrim;i4++) | |
11390 | }//end of for(Int_t i3=0;i3<nPrim;i3++) | |
11391 | }//end of for(Int_t i2=0;i2<nPrim;i2++) | |
11392 | }//end of for(Int_t i1=0;i1<nPrim;i1++) | |
11393 | ||
11394 | // count # of RPs and POIs in selected pt and eta bins for cross-checkings: | |
3b552efe | 11395 | for(Int_t i=0;i<nPrim;i++) |
11396 | { | |
11397 | aftsTrack=anEvent->GetTrack(i); | |
11398 | // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) | |
11399 | if(typeFlag==1) // this is diff flow of POIs | |
489d5531 | 11400 | { |
11401 | if(ptOrEta == "Pt") | |
11402 | { | |
11403 | if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
11404 | } else if (ptOrEta == "Eta") | |
11405 | { | |
11406 | if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
3b552efe | 11407 | } |
11408 | } else // this is diff flow of RPs | |
11409 | { | |
489d5531 | 11410 | if(ptOrEta == "Pt") |
11411 | { | |
11412 | if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()<upperPtEtaEdge[pe]) && (aftsTrack->InRPSelection())))continue; | |
11413 | } else if (ptOrEta == "Eta") | |
11414 | { | |
11415 | if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()<upperPtEtaEdge[pe]) && (aftsTrack->InRPSelection())))continue; | |
3b552efe | 11416 | } |
11417 | } | |
11418 | if(t==1)t++; | |
11419 | fNoOfParticlesInBin->Fill(t+pe+0.5); | |
489d5531 | 11420 | } |
11421 | ||
11422 | } // end of void AliFlowAnalysisWithQCumulants::EvaluateDiffFlowCorrelationsWithNestedLoops(AliFlowEventSimple* anEvent, TString type, TString ptOrEta) | |
11423 | ||
11424 | ||
11425 | //================================================================================================================================ | |
11426 | ||
11427 | ||
11428 | void AliFlowAnalysisWithQCumulants::CrossCheckDiffFlowCorrelations(TString type, TString ptOrEta) | |
11429 | { | |
11430 | // Compare correlations needed for diff. flow calculated with nested loops and those calculated from Q-vectors | |
11431 | ||
2a98ceb8 | 11432 | Int_t typeFlag = 0; |
11433 | Int_t ptEtaFlag = 0; | |
489d5531 | 11434 | if(type == "RP") |
11435 | { | |
11436 | typeFlag = 0; | |
11437 | } else if(type == "POI") | |
11438 | { | |
11439 | typeFlag = 1; | |
11440 | } | |
11441 | if(ptOrEta == "Pt") | |
11442 | { | |
11443 | ptEtaFlag = 0; | |
11444 | } else if(ptOrEta == "Eta") | |
11445 | { | |
11446 | ptEtaFlag = 1; | |
11447 | } | |
11448 | // shortcuts: | |
11449 | Int_t t = typeFlag; | |
11450 | Int_t pe = ptEtaFlag; | |
11451 | ||
11452 | TString rpORpoiString[2] = {"RP ","POI"}; // to be improved (name in the same way as in the other methods, eventually promote to data member) | |
11453 | TString ptORetaString[2] = {"pt","eta"}; // to be improved (name in the same way as in the other methods, eventually promote to data member) | |
11454 | TString reducedCorrelations[4] = {"<<cos(n(psi1-phi2))>>","<<cos(n(psi1+phi2-phi3-phi4))>>","",""}; // to be improved (access this from pro or hist) | |
11455 | Double_t lowerPtEtaEdge[2] = {fPtMin+(fCrossCheckInPtBinNo-1)*fPtBinWidth,fEtaMin+(fCrossCheckInEtaBinNo-1)*fEtaBinWidth}; | |
11456 | Double_t upperPtEtaEdge[2] = {fPtMin+fCrossCheckInPtBinNo*fPtBinWidth,fEtaMin+fCrossCheckInEtaBinNo*fEtaBinWidth}; | |
11457 | ||
11458 | Int_t crossCheckInPtEtaBinNo[2] = {fCrossCheckInPtBinNo,fCrossCheckInEtaBinNo}; | |
11459 | ||
11460 | ||
11461 | cout<<endl; | |
11462 | cout<<" *****************************************"<<endl; | |
11463 | cout<<" **** cross-checking the correlations ****"<<endl; | |
11464 | cout<<" **** for differential flow ("<<rpORpoiString[t]<<") ****"<<endl; | |
11465 | if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) | |
11466 | { | |
11467 | cout<<" **** (particle weights not used) ****"<<endl; | |
11468 | } else | |
11469 | { | |
11470 | cout<<" **** (particle weights used) ****"<<endl; | |
11471 | } | |
11472 | cout<<" *****************************************"<<endl; | |
11473 | cout<<endl; | |
11474 | cout<<" "<<ptORetaString[pe]<<" bin: "<<lowerPtEtaEdge[pe]<<" <= "<<ptORetaString[pe]<<" < "<<upperPtEtaEdge[pe]<<endl; | |
11475 | cout<<endl; | |
11476 | ||
11477 | for(Int_t rci=0;rci<2;rci++) // to be improved (calculate 6th and 8th order) | |
11478 | { | |
11479 | cout<<" "<<reducedCorrelations[rci].Data()<<":"<<endl; | |
11480 | cout<<" from Q-vectors = "<<fDiffFlowCorrelationsPro[t][pe][rci]->GetBinContent(crossCheckInPtEtaBinNo[pe])<<endl; | |
11481 | cout<<" from nested loops = "<<fDiffFlowDirectCorrelations[t][pe][rci]->GetBinContent(1)<<endl; | |
11482 | cout<<endl; | |
11483 | } // end of for(Int_t rci=0;rci<4;rci++) | |
11484 | ||
11485 | } // end of void AliFlowAnalysisWithQCumulants::CrossCheckDiffFlowCorrelations(TString type, TString ptOrEta) | |
11486 | ||
3b552efe | 11487 | //================================================================================================================================ |
11488 | ||
489d5531 | 11489 | void AliFlowAnalysisWithQCumulants::PrintNumberOfParticlesInSelectedBin() |
3b552efe | 11490 | { |
11491 | // Print on the screen number of RPs and POIs in selected pt and eta bin for cross checkings. | |
11492 | ||
11493 | cout<<endl; | |
11494 | cout<<"Number of RPs in selected pt bin = "<<fNoOfParticlesInBin->GetBinContent(1)<<endl; | |
11495 | cout<<"Number of RPs in selected eta bin = "<<fNoOfParticlesInBin->GetBinContent(2)<<endl; | |
11496 | cout<<"Number of POIs in selected pt bin = "<<fNoOfParticlesInBin->GetBinContent(3)<<endl; | |
11497 | cout<<"Number of POIs in selected eta bin = "<<fNoOfParticlesInBin->GetBinContent(4)<<endl; | |
11498 | ||
489d5531 | 11499 | } // end of void AliFlowAnalysisWithQCumulants::PrintNumberOfParticlesInSelectedBin() |
11500 | ||
3b552efe | 11501 | //================================================================================================================================ |
11502 | ||
0328db2d | 11503 | void AliFlowAnalysisWithQCumulants::EvaluateDiffFlowCorrelationsWithNestedLoopsUsingParticleWeights(AliFlowEventSimple * const anEvent, TString type, TString ptOrEta) |
489d5531 | 11504 | { |
11505 | // Evaluate reduced correlations with nested loops without using the particle weights. | |
11506 | ||
11507 | // Remark 1: Reduced correlations are evaluated in pt bin number fCrossCheckInPtBinNo and eta bin number fCrossCheckInEtaBinNo both for RPs and POIs. | |
11508 | // Remark 2: Results are stored in 1 bin profiles fDiffFlowDirectCorrelations[t][pe][ci], where indices runs as follows: | |
11509 | // [0=RP,1=POI][0=Pt,1=Eta][0=<2'>,1=<4'>,2=<6'>,3=<8'>] | |
11510 | // Remark 3: <2'> = <w2 cos(n*(psi1-phi2))> | |
11511 | // <4'> = <w2 w3 w4 cos(n*(psi1+phi2-phi3-phi4))> | |
11512 | // ... | |
11513 | ||
2a98ceb8 | 11514 | Int_t typeFlag = 0; |
11515 | Int_t ptEtaFlag = 0; | |
489d5531 | 11516 | if(type == "RP") |
11517 | { | |
11518 | typeFlag = 0; | |
11519 | } else if(type == "POI") | |
11520 | { | |
11521 | typeFlag = 1; | |
11522 | } | |
11523 | if(ptOrEta == "Pt") | |
11524 | { | |
11525 | ptEtaFlag = 0; | |
11526 | } else if(ptOrEta == "Eta") | |
11527 | { | |
11528 | ptEtaFlag = 1; | |
11529 | } | |
11530 | // shortcuts: | |
11531 | Int_t t = typeFlag; | |
11532 | Int_t pe = ptEtaFlag; | |
11533 | ||
11534 | Double_t lowerPtEtaEdge[2] = {fPtMin+(fCrossCheckInPtBinNo-1)*fPtBinWidth,fEtaMin+(fCrossCheckInEtaBinNo-1)*fEtaBinWidth}; | |
11535 | Double_t upperPtEtaEdge[2] = {fPtMin+fCrossCheckInPtBinNo*fPtBinWidth,fEtaMin+fCrossCheckInEtaBinNo*fEtaBinWidth}; | |
11536 | Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; | |
11537 | ||
11538 | Int_t nPrim = anEvent->NumberOfTracks(); | |
11539 | AliFlowTrackSimple *aftsTrack = NULL; | |
11540 | ||
11541 | Double_t psi1=0., phi2=0., phi3=0., phi4=0.;// phi5=0., phi6=0., phi7=0., phi8=0.; | |
11542 | Double_t wPhi2=1., wPhi3=1., wPhi4=1.;// wPhi5=1., wPhi6=1., wPhi7=1., wPhi8=1.; | |
11543 | ||
11544 | Int_t n = fHarmonic; | |
11545 | ||
11546 | // 2'-particle correlations: | |
11547 | for(Int_t i1=0;i1<nPrim;i1++) | |
11548 | { | |
11549 | aftsTrack=anEvent->GetTrack(i1); | |
3b552efe | 11550 | // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) |
11551 | if(typeFlag==1) // this is diff flow of POIs | |
489d5531 | 11552 | { |
11553 | if(ptOrEta == "Pt") | |
11554 | { | |
11555 | if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
11556 | } else if (ptOrEta == "Eta") | |
11557 | { | |
11558 | if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
3b552efe | 11559 | } |
11560 | } else // this is diff flow of RPs | |
11561 | { | |
489d5531 | 11562 | if(ptOrEta == "Pt") |
11563 | { | |
11564 | if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()<upperPtEtaEdge[pe]) && (aftsTrack->InRPSelection())))continue; | |
11565 | } else if (ptOrEta == "Eta") | |
11566 | { | |
11567 | if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()<upperPtEtaEdge[pe]) && (aftsTrack->InRPSelection())))continue; | |
3b552efe | 11568 | } |
489d5531 | 11569 | } |
11570 | psi1=aftsTrack->Phi(); | |
11571 | for(Int_t i2=0;i2<nPrim;i2++) | |
11572 | { | |
11573 | if(i2==i1) continue; | |
11574 | aftsTrack=anEvent->GetTrack(i2); | |
11575 | // RP condition (!(first) particle in the correlator must be RP): | |
11576 | if(!(aftsTrack->InRPSelection())) continue; | |
11577 | phi2=aftsTrack->Phi(); | |
11578 | if(fUsePhiWeights && fPhiWeights) wPhi2 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi2*fnBinsPhi/TMath::TwoPi()))); | |
11579 | // 2'-particle correlations: | |
11580 | fDiffFlowDirectCorrelations[t][pe][0]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(1.*n*(psi1-phi2)),wPhi2); // <w2 cos(n*(psi1-phi2)) | |
11581 | }//end of for(Int_t i2=0;i2<nPrim;i2++) | |
11582 | }//end of for(Int_t i1=0;i1<nPrim;i1++) | |
11583 | ||
11584 | // 4'-particle correlations: | |
11585 | for(Int_t i1=0;i1<nPrim;i1++) | |
11586 | { | |
11587 | aftsTrack=anEvent->GetTrack(i1); | |
3b552efe | 11588 | // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) |
11589 | if(typeFlag==1) // this is diff flow of POIs | |
489d5531 | 11590 | { |
11591 | if(ptOrEta == "Pt") | |
11592 | { | |
11593 | if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
11594 | } else if (ptOrEta == "Eta") | |
11595 | { | |
11596 | if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
3b552efe | 11597 | } |
11598 | } else // this is diff flow of RPs | |
11599 | { | |
489d5531 | 11600 | if(ptOrEta == "Pt") |
11601 | { | |
11602 | if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()<upperPtEtaEdge[pe]) && (aftsTrack->InRPSelection())))continue; | |
11603 | } else if (ptOrEta == "Eta") | |
11604 | { | |
11605 | if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()<upperPtEtaEdge[pe]) && (aftsTrack->InRPSelection())))continue; | |
3b552efe | 11606 | } |
489d5531 | 11607 | } |
11608 | psi1=aftsTrack->Phi(); | |
11609 | for(Int_t i2=0;i2<nPrim;i2++) | |
11610 | { | |
11611 | if(i2==i1) continue; | |
11612 | aftsTrack=anEvent->GetTrack(i2); | |
11613 | // RP condition (!(first) particle in the correlator must be RP): | |
11614 | if(!(aftsTrack->InRPSelection())) continue; | |
11615 | phi2=aftsTrack->Phi(); | |
11616 | if(fUsePhiWeights && fPhiWeights) wPhi2 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi2*fnBinsPhi/TMath::TwoPi()))); | |
11617 | for(Int_t i3=0;i3<nPrim;i3++) | |
11618 | { | |
11619 | if(i3==i1||i3==i2) continue; | |
11620 | aftsTrack=anEvent->GetTrack(i3); | |
11621 | // RP condition (!(first) particle in the correlator must be RP): | |
11622 | if(!(aftsTrack->InRPSelection())) continue; | |
11623 | phi3=aftsTrack->Phi(); | |
11624 | if(fUsePhiWeights && fPhiWeights) wPhi3 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi3*fnBinsPhi/TMath::TwoPi()))); | |
11625 | for(Int_t i4=0;i4<nPrim;i4++) | |
11626 | { | |
11627 | if(i4==i1||i4==i2||i4==i3) continue; | |
11628 | aftsTrack=anEvent->GetTrack(i4); | |
11629 | // RP condition (!(first) particle in the correlator must be RP): | |
11630 | if(!(aftsTrack->InRPSelection())) continue; | |
11631 | phi4=aftsTrack->Phi(); | |
11632 | if(fUsePhiWeights && fPhiWeights) wPhi4 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi4*fnBinsPhi/TMath::TwoPi()))); | |
11633 | // 4'-particle correlations <w2 w3 w4 cos(n(psi1+phi2-phi3-phi4))>: | |
11634 | fDiffFlowDirectCorrelations[t][pe][1]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(n*(psi1+phi2-phi3-phi4)),wPhi2*wPhi3*wPhi4); | |
11635 | }//end of for(Int_t i4=0;i4<nPrim;i4++) | |
11636 | }//end of for(Int_t i3=0;i3<nPrim;i3++) | |
11637 | }//end of for(Int_t i2=0;i2<nPrim;i2++) | |
11638 | }//end of for(Int_t i1=0;i1<nPrim;i1++) | |
11639 | ||
11640 | // count # of RPs and POIs in selected pt and eta bins for cross-checkings: (to be improved - moved to dedicated method) | |
3b552efe | 11641 | for(Int_t i=0;i<nPrim;i++) |
11642 | { | |
489d5531 | 11643 | aftsTrack=anEvent->GetTrack(i); |
11644 | // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) | |
11645 | if(typeFlag==1) // this is diff flow of POIs | |
11646 | { | |
11647 | if(ptOrEta == "Pt") | |
11648 | { | |
11649 | if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
11650 | } else if (ptOrEta == "Eta") | |
11651 | { | |
11652 | if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
11653 | } | |
11654 | } else // this is diff flow of RPs | |
11655 | { | |
11656 | if(ptOrEta == "Pt") | |
11657 | { | |
11658 | if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()<upperPtEtaEdge[pe]) && (aftsTrack->InRPSelection())))continue; | |
11659 | } else if (ptOrEta == "Eta") | |
11660 | { | |
11661 | if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()<upperPtEtaEdge[pe]) && (aftsTrack->InRPSelection())))continue; | |
11662 | } | |
11663 | } | |
11664 | if(t==1)t++; | |
11665 | fNoOfParticlesInBin->Fill(t+pe+0.5); | |
11666 | } | |
11667 | ||
11668 | } // end of void AliFlowAnalysisWithQCumulants::EvaluateDiffFlowCorrelationsWithNestedLoopsUsingParticleWeights(AliFlowEventSimple* anEvent, TString type, TString ptOrEta) | |
11669 | ||
11670 | ||
11671 | //================================================================================================================================ | |
11672 | ||
11673 | ||
0328db2d | 11674 | void AliFlowAnalysisWithQCumulants::EvaluateDiffFlowCorrectionTermsForNUAWithNestedLoops(AliFlowEventSimple * const anEvent, TString type, TString ptOrEta) |
489d5531 | 11675 | { |
11676 | // Evaluate with nested loops correction terms for non-uniform acceptance (both sin and cos terms) relevant for differential flow. | |
11677 | ||
11678 | // Remark 1: Reduced correction terms for non-uniform acceptance are evaluated in pt bin number fCrossCheckInPtBinNo | |
11679 | // and eta bin number fCrossCheckInEtaBinNo both for RPs and POIs. | |
11680 | // Remark 2: Results are stored in 1 bin profiles fDiffFlowDirectCorrections[t][pe][sc][cti], where first three indices runs as: | |
11681 | // [0=RP,1=POI][0=Pt,1=Eta][0=sin terms,1=cos terms], whilst the cti (correction term index) runs as follows: | |
11682 | // cti: | |
11683 | // 0: <<sc n(psi1)>> | |
11684 | // 1: <<sc n(psi1+phi2)>> | |
11685 | // 2: <<sc n(psi1+phi2-phi3)>> | |
11686 | // 3: <<sc n(psi1-phi2-phi3)>> | |
11687 | // 4: | |
11688 | // 5: | |
11689 | // 6: | |
11690 | ||
2a98ceb8 | 11691 | Int_t typeFlag = 0; |
11692 | Int_t ptEtaFlag = 0; | |
489d5531 | 11693 | if(type == "RP") |
11694 | { | |
11695 | typeFlag = 0; | |
11696 | } else if(type == "POI") | |
11697 | { | |
11698 | typeFlag = 1; | |
11699 | } | |
11700 | if(ptOrEta == "Pt") | |
11701 | { | |
11702 | ptEtaFlag = 0; | |
11703 | } else if(ptOrEta == "Eta") | |
11704 | { | |
11705 | ptEtaFlag = 1; | |
11706 | } | |
11707 | // shortcuts: | |
11708 | Int_t t = typeFlag; | |
11709 | Int_t pe = ptEtaFlag; | |
11710 | ||
11711 | Double_t lowerPtEtaEdge[2] = {fPtMin+(fCrossCheckInPtBinNo-1)*fPtBinWidth,fEtaMin+(fCrossCheckInEtaBinNo-1)*fEtaBinWidth}; | |
11712 | Double_t upperPtEtaEdge[2] = {fPtMin+fCrossCheckInPtBinNo*fPtBinWidth,fEtaMin+fCrossCheckInEtaBinNo*fEtaBinWidth}; | |
11713 | Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; | |
11714 | ||
11715 | Int_t nPrim = anEvent->NumberOfTracks(); | |
11716 | AliFlowTrackSimple *aftsTrack = NULL; | |
11717 | ||
11718 | Double_t psi1=0., phi2=0., phi3=0.;// phi4=0.;// phi5=0., phi6=0., phi7=0., phi8=0.; | |
11719 | ||
11720 | Int_t n = fHarmonic; | |
11721 | ||
11722 | // 1-particle correction terms: | |
11723 | for(Int_t i1=0;i1<nPrim;i1++) | |
11724 | { | |
11725 | aftsTrack=anEvent->GetTrack(i1); | |
3b552efe | 11726 | // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) |
11727 | if(typeFlag==1) // this is diff flow of POIs | |
489d5531 | 11728 | { |
11729 | if(ptOrEta == "Pt") | |
11730 | { | |
11731 | if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
11732 | } else if (ptOrEta == "Eta") | |
11733 | { | |
11734 | if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
3b552efe | 11735 | } |
11736 | } else // this is diff flow of RPs | |
11737 | { | |
489d5531 | 11738 | if(ptOrEta == "Pt") |
11739 | { | |
11740 | if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()<upperPtEtaEdge[pe]) && (aftsTrack->InRPSelection())))continue; | |
11741 | } else if (ptOrEta == "Eta") | |
11742 | { | |
11743 | if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()<upperPtEtaEdge[pe]) && (aftsTrack->InRPSelection())))continue; | |
3b552efe | 11744 | } |
11745 | } | |
489d5531 | 11746 | psi1=aftsTrack->Phi(); |
11747 | // sin terms: | |
11748 | fDiffFlowDirectCorrectionTermsForNUA[t][pe][0][0]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,sin(n*psi1),1.); // <<sin(n*(psi1))>> | |
11749 | // cos terms: | |
11750 | fDiffFlowDirectCorrectionTermsForNUA[t][pe][1][0]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(n*psi1),1.); // <<cos(n*(psi1))>> | |
11751 | }//end of for(Int_t i1=0;i1<nPrim;i1++) | |
11752 | ||
11753 | // 2-particle correction terms: | |
11754 | for(Int_t i1=0;i1<nPrim;i1++) | |
11755 | { | |
11756 | aftsTrack=anEvent->GetTrack(i1); | |
3b552efe | 11757 | // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) |
11758 | if(typeFlag==1) // this is diff flow of POIs | |
489d5531 | 11759 | { |
11760 | if(ptOrEta == "Pt") | |
11761 | { | |
11762 | if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
11763 | } else if (ptOrEta == "Eta") | |
11764 | { | |
11765 | if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
3b552efe | 11766 | } |
11767 | } else // this is diff flow of RPs | |
11768 | { | |
489d5531 | 11769 | if(ptOrEta == "Pt") |
11770 | { | |
11771 | if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()<upperPtEtaEdge[pe]) && (aftsTrack->InRPSelection())))continue; | |
11772 | } else if (ptOrEta == "Eta") | |
11773 | { | |
11774 | if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()<upperPtEtaEdge[pe]) && (aftsTrack->InRPSelection())))continue; | |
3b552efe | 11775 | } |
489d5531 | 11776 | } |
11777 | psi1=aftsTrack->Phi(); | |
11778 | for(Int_t i2=0;i2<nPrim;i2++) | |
11779 | { | |
11780 | if(i2==i1) continue; | |
11781 | aftsTrack=anEvent->GetTrack(i2); | |
11782 | // RP condition (!(first) particle in the correlator must be RP): | |
11783 | if(!(aftsTrack->InRPSelection())) continue; | |
11784 | phi2=aftsTrack->Phi(); | |
11785 | // sin terms: | |
11786 | fDiffFlowDirectCorrectionTermsForNUA[t][pe][0][1]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,sin(n*(psi1+phi2)),1.); // <<sin(n*(psi1+phi2))>> | |
11787 | // cos terms: | |
11788 | fDiffFlowDirectCorrectionTermsForNUA[t][pe][1][1]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(n*(psi1+phi2)),1.); // <<cos(n*(psi1+phi2))>> | |
11789 | }//end of for(Int_t i2=0;i2<nPrim;i2++) | |
11790 | }//end of for(Int_t i1=0;i1<nPrim;i1++) | |
11791 | ||
11792 | // 3-particle correction terms: | |
11793 | for(Int_t i1=0;i1<nPrim;i1++) | |
11794 | { | |
11795 | aftsTrack=anEvent->GetTrack(i1); | |
3b552efe | 11796 | // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) |
11797 | if(typeFlag==1) // this is diff flow of POIs | |
489d5531 | 11798 | { |
11799 | if(ptOrEta == "Pt") | |
11800 | { | |
11801 | if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
11802 | } else if (ptOrEta == "Eta") | |
11803 | { | |
11804 | if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
3b552efe | 11805 | } |
11806 | } else // this is diff flow of RPs | |
11807 | { | |
489d5531 | 11808 | if(ptOrEta == "Pt") |
11809 | { | |
11810 | if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()<upperPtEtaEdge[pe]) && (aftsTrack->InRPSelection())))continue; | |
11811 | } else if (ptOrEta == "Eta") | |
11812 | { | |
11813 | if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()<upperPtEtaEdge[pe]) && (aftsTrack->InRPSelection())))continue; | |
3b552efe | 11814 | } |
489d5531 | 11815 | } |
11816 | psi1=aftsTrack->Phi(); | |
11817 | for(Int_t i2=0;i2<nPrim;i2++) | |
11818 | { | |
11819 | if(i2==i1) continue; | |
11820 | aftsTrack=anEvent->GetTrack(i2); | |
11821 | // RP condition (!(first) particle in the correlator must be RP): | |
11822 | if(!(aftsTrack->InRPSelection())) continue; | |
11823 | phi2=aftsTrack->Phi(); | |
11824 | for(Int_t i3=0;i3<nPrim;i3++) | |
11825 | { | |
11826 | if(i3==i1||i3==i2) continue; | |
11827 | aftsTrack=anEvent->GetTrack(i3); | |
11828 | // RP condition (!(first) particle in the correlator must be RP): | |
11829 | if(!(aftsTrack->InRPSelection())) continue; | |
11830 | phi3=aftsTrack->Phi(); | |
11831 | // sin terms: | |
11832 | fDiffFlowDirectCorrectionTermsForNUA[t][pe][0][2]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,sin(n*(psi1+phi2-phi3)),1.); // <<sin(n*(psi1+phi2-phi3))>> | |
11833 | fDiffFlowDirectCorrectionTermsForNUA[t][pe][0][3]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,sin(n*(psi1-phi2-phi3)),1.); // <<sin(n*(psi1-phi2-phi3))>> | |
11834 | // cos terms: | |
11835 | fDiffFlowDirectCorrectionTermsForNUA[t][pe][1][2]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(n*(psi1+phi2-phi3)),1.); // <<cos(n*(psi1+phi2-phi3))>> | |
11836 | fDiffFlowDirectCorrectionTermsForNUA[t][pe][1][3]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(n*(psi1-phi2-phi3)),1.); // <<cos(n*(psi1-phi2-phi3))>> | |
11837 | }//end of for(Int_t i3=0;i3<nPrim;i3++) | |
11838 | }//end of for(Int_t i2=0;i2<nPrim;i2++) | |
11839 | }//end of for(Int_t i1=0;i1<nPrim;i1++) | |
11840 | ||
11841 | } // end of void AliFlowAnalysisWithQCumulants::EvaluateDiffFlowCorrectionTermsForNUAWithNestedLoops(AliFlowEventSimple* anEvent, TString type, TString ptOrEta) | |
11842 | ||
11843 | ||
11844 | //================================================================================================================================ | |
11845 | ||
11846 | ||
11847 | void AliFlowAnalysisWithQCumulants::CrossCheckDiffFlowCorrectionTermsForNUA(TString type, TString ptOrEta) | |
11848 | { | |
11849 | // Compare corrections temrs for non-uniform acceptance needed for diff. flow calculated with nested loops and those calculated from Q-vectors | |
11850 | ||
2a98ceb8 | 11851 | Int_t typeFlag = 0; |
11852 | Int_t ptEtaFlag = 0; | |
489d5531 | 11853 | if(type == "RP") |
11854 | { | |
11855 | typeFlag = 0; | |
11856 | } else if(type == "POI") | |
11857 | { | |
11858 | typeFlag = 1; | |
11859 | } | |
11860 | if(ptOrEta == "Pt") | |
11861 | { | |
11862 | ptEtaFlag = 0; | |
11863 | } else if(ptOrEta == "Eta") | |
11864 | { | |
11865 | ptEtaFlag = 1; | |
11866 | } | |
11867 | // shortcuts: | |
11868 | Int_t t = typeFlag; | |
11869 | Int_t pe = ptEtaFlag; | |
11870 | ||
11871 | TString rpORpoiString[2] = {"RP ","POI"}; // to be improved (name in the same way as in the other methods, eventually promote to data member) | |
11872 | TString ptORetaString[2] = {"pt","eta"}; // to be improved (name in the same way as in the other methods, eventually promote to data member) | |
11873 | //TString sinCosFlag[2] = {"sin","cos"}; // to be improved (eventually promote to data member) | |
11874 | TString reducedCorrectionSinTerms[4] = {"<<sin(n(psi1))>>","<<sin(n(psi1+phi2))>>","<<sin(n*(psi1+phi2-phi3))>>","<<sin(n*(psi1-phi2-phi3))>>"}; // to be improved (access this from pro or hist) | |
11875 | TString reducedCorrectionCosTerms[4] = {"<<cos(n(psi1))>>","<<cos(n(psi1+phi2))>>","<<cos(n*(psi1+phi2-phi3))>>","<<cos(n*(psi1-phi2-phi3))>>"}; // to be improved (access this from pro or hist) | |
11876 | Double_t lowerPtEtaEdge[2] = {fPtMin+(fCrossCheckInPtBinNo-1)*fPtBinWidth,fEtaMin+(fCrossCheckInEtaBinNo-1)*fEtaBinWidth}; | |
11877 | Double_t upperPtEtaEdge[2] = {fPtMin+fCrossCheckInPtBinNo*fPtBinWidth,fEtaMin+fCrossCheckInEtaBinNo*fEtaBinWidth}; | |
11878 | ||
11879 | Int_t crossCheckInPtEtaBinNo[2] = {fCrossCheckInPtBinNo,fCrossCheckInEtaBinNo}; | |
11880 | ||
11881 | cout<<endl; | |
11882 | cout<<" ******************************************"<<endl; | |
11883 | cout<<" **** cross-checking the correction ****"<<endl; | |
46b94261 | 11884 | cout<<" **** terms for non-uniform acceptance ****"<<endl; |
489d5531 | 11885 | cout<<" **** for differential flow ("<<rpORpoiString[t]<<") ****"<<endl; |
11886 | if(!(fUsePhiWeights||fUsePtWeights||fUseEtaWeights)) | |
11887 | { | |
11888 | cout<<" **** (particle weights not used) ****"<<endl; | |
11889 | } else | |
11890 | { | |
11891 | cout<<" **** (particle weights used) ****"<<endl; | |
11892 | } | |
11893 | cout<<" ******************************************"<<endl; | |
11894 | cout<<endl; | |
11895 | cout<<" "<<ptORetaString[pe]<<" bin: "<<lowerPtEtaEdge[pe]<<" <= "<<ptORetaString[pe]<<" < "<<upperPtEtaEdge[pe]<<endl; | |
11896 | cout<<endl; | |
11897 | ||
11898 | for(Int_t cti=0;cti<4;cti++) // correction term index | |
11899 | { | |
11900 | for(Int_t sc=0;sc<2;sc++) // sin or cos terms | |
11901 | { | |
11902 | if(sc==0) // to be improved (this can be implemented better) | |
11903 | { | |
11904 | cout<<" "<<reducedCorrectionSinTerms[cti].Data()<<":"<<endl; | |
11905 | } else | |
11906 | { | |
11907 | cout<<" "<<reducedCorrectionCosTerms[cti].Data()<<":"<<endl; | |
11908 | } | |
11909 | cout<<" from Q-vectors = "<<fDiffFlowCorrectionTermsForNUAPro[t][pe][sc][cti]->GetBinContent(crossCheckInPtEtaBinNo[pe])<<endl; | |
11910 | cout<<" from nested loops = "<<fDiffFlowDirectCorrectionTermsForNUA[t][pe][sc][cti]->GetBinContent(1)<<endl; | |
11911 | cout<<endl; | |
11912 | } | |
11913 | } // end of for(Int_t rci=0;rci<4;rci++) | |
11914 | ||
11915 | } // end of void AliFlowAnalysisWithQCumulants::CrossCheckDiffFlowCorrectionTermsForNUA(TString type, TString ptOrEta) | |
11916 | ||
11917 | ||
57340a27 | 11918 | //================================================================================================================================ |
11919 | ||
489d5531 | 11920 | |
11921 | void AliFlowAnalysisWithQCumulants::CalculateIntFlowCorrectionsForNUACosTermsUsingParticleWeights() | |
11922 | { | |
11923 | // Calculate corrections using particle weights for non-uniform acceptance of the detector for no-name integrated flow (cos terms). | |
11924 | ||
11925 | // ********************************************************************** | |
11926 | // **** weighted corrections for non-uniform acceptance (cos terms): **** | |
11927 | // ********************************************************************** | |
57340a27 | 11928 | |
489d5531 | 11929 | // Remark 1: When particle weights are used the binning of fIntFlowCorrectionTermsForNUAPro[1] is organized as follows: |
57340a27 | 11930 | // |
489d5531 | 11931 | // 1st bin: <<w1 cos(n*(phi1))>> = cosP1nW1 |
11932 | // 2nd bin: <<w1 w2 cos(n*(phi1+phi2))>> = cosP1nP1nW1W1 | |
11933 | // 3rd bin: <<w1 w2 w3 cos(n*(phi1-phi2-phi3))>> = cosP1nM1nM1nW1W1W1 | |
11934 | // ... | |
11935 | ||
11936 | // multiplicity (number of particles used to determine the reaction plane) | |
11937 | Double_t dMult = (*fSMpk)(0,0); | |
11938 | ||
11939 | // real and imaginary parts of weighted Q-vectors evaluated in harmonics n, 2n, 3n and 4n: | |
11940 | Double_t dReQ1n1k = (*fReQ)(0,1); | |
11941 | Double_t dReQ2n2k = (*fReQ)(1,2); | |
11942 | //Double_t dReQ3n3k = (*fReQ)(2,3); | |
11943 | //Double_t dReQ4n4k = (*fReQ)(3,4); | |
11944 | Double_t dReQ1n3k = (*fReQ)(0,3); | |
11945 | Double_t dImQ1n1k = (*fImQ)(0,1); | |
11946 | Double_t dImQ2n2k = (*fImQ)(1,2); | |
11947 | //Double_t dImQ3n3k = (*fImQ)(2,3); | |
11948 | //Double_t dImQ4n4k = (*fImQ)(3,4); | |
11949 | //Double_t dImQ1n3k = (*fImQ)(0,3); | |
11950 | ||
11951 | // dMs are variables introduced in order to simplify some Eqs. bellow: | |
11952 | //.............................................................................................. | |
11953 | Double_t dM11 = (*fSMpk)(1,1)-(*fSMpk)(0,2); // dM11 = sum_{i,j=1,i!=j}^M w_i w_j | |
57340a27 | 11954 | Double_t dM111 = (*fSMpk)(2,1)-3.*(*fSMpk)(0,2)*(*fSMpk)(0,1) |
489d5531 | 11955 | + 2.*(*fSMpk)(0,3); // dM111 = sum_{i,j,k=1,i!=j!=k}^M w_i w_j w_k |
11956 | //.............................................................................................. | |
ecac11c2 | 11957 | // 1-particle: |
489d5531 | 11958 | Double_t cosP1nW1 = 0.; // <<w1 cos(n*(phi1))>> |
11959 | ||
0328db2d | 11960 | if(dMult>0 && TMath::Abs((*fSMpk)(0,1))>1e-6) |
489d5531 | 11961 | { |
11962 | cosP1nW1 = dReQ1n1k/(*fSMpk)(0,1); | |
11963 | ||
11964 | // average weighted 1-particle correction (cos terms) for non-uniform acceptance for single event: | |
11965 | fIntFlowCorrectionTermsForNUAEBE[1]->SetBinContent(1,cosP1nW1); | |
11966 | ||
11967 | // final average weighted 1-particle correction (cos terms) for non-uniform acceptance for all events: | |
11968 | fIntFlowCorrectionTermsForNUAPro[1]->Fill(0.5,cosP1nW1,(*fSMpk)(0,1)); | |
11969 | } | |
11970 | ||
11971 | // 2-particle: | |
11972 | Double_t cosP1nP1nW1W1 = 0.; // <<w1 w2 cos(n*(phi1+phi2))>> | |
11973 | ||
0328db2d | 11974 | if(dMult>1 && TMath::Abs(dM11)>1e-6) |
489d5531 | 11975 | { |
11976 | cosP1nP1nW1W1 = (pow(dReQ1n1k,2)-pow(dImQ1n1k,2)-dReQ2n2k)/dM11; | |
11977 | ||
11978 | // average weighted 2-particle correction (cos terms) for non-uniform acceptance for single event: | |
11979 | fIntFlowCorrectionTermsForNUAEBE[1]->SetBinContent(2,cosP1nP1nW1W1); | |
11980 | ||
11981 | // final average weighted 2-particle correction (cos terms) for non-uniform acceptance for all events: | |
11982 | fIntFlowCorrectionTermsForNUAPro[1]->Fill(1.5,cosP1nP1nW1W1,dM11); | |
11983 | } | |
11984 | ||
11985 | // 3-particle: | |
11986 | Double_t cosP1nM1nM1nW1W1W1 = 0.; // <<w1 w2 w3 cos(n*(phi1-phi2-phi3))>> | |
11987 | ||
0328db2d | 11988 | if(dMult>2 && TMath::Abs(dM111)>1e-6) |
489d5531 | 11989 | { |
57340a27 | 11990 | cosP1nM1nM1nW1W1W1 = (dReQ1n1k*(pow(dReQ1n1k,2)+pow(dImQ1n1k,2)) |
11991 | - dReQ1n1k*dReQ2n2k-dImQ1n1k*dImQ2n2k | |
11992 | - 2.*((*fSMpk)(0,2))*dReQ1n1k | |
489d5531 | 11993 | + 2.*dReQ1n3k) |
11994 | / dM111; | |
11995 | ||
11996 | // average non-weighted 3-particle correction (cos terms) for non-uniform acceptance for single event: | |
11997 | fIntFlowCorrectionTermsForNUAEBE[1]->SetBinContent(3,cosP1nM1nM1nW1W1W1); | |
11998 | ||
11999 | // final average non-weighted 3-particle correction (cos terms) for non-uniform acceptance for all events: | |
12000 | fIntFlowCorrectionTermsForNUAPro[1]->Fill(2.5,cosP1nM1nM1nW1W1W1,dM111); | |
12001 | } | |
12002 | ||
12003 | } // end of AliFlowAnalysisWithQCumulants::CalculateIntFlowCorrectionsForNUACosTermsUsingParticleWeights() | |
12004 | ||
12005 | ||
12006 | //================================================================================================================================ | |
12007 | ||
12008 | ||
12009 | void AliFlowAnalysisWithQCumulants::CalculateIntFlowCorrectionsForNUASinTermsUsingParticleWeights() | |
12010 | { | |
12011 | // calculate corrections using particle weights for non-uniform acceptance of the detector for no-name integrated flow (sin terms) | |
12012 | ||
12013 | // ********************************************************************** | |
12014 | // **** weighted corrections for non-uniform acceptance (sin terms): **** | |
12015 | // ********************************************************************** | |
12016 | ||
12017 | // Remark 1: When particle weights are used the binning of fIntFlowCorrectionTermsForNUAPro[0] is organized as follows: | |
57340a27 | 12018 | // |
489d5531 | 12019 | // 1st bin: <<w1 sin(n*(phi1))>> = sinP1nW1 |
12020 | // 2nd bin: <<w1 w2 sin(n*(phi1+phi2))>> = sinP1nP1nW1W1 | |
12021 | // 3rd bin: <<w1 w2 w3 sin(n*(phi1-phi2-phi3))>> = sinP1nM1nM1nW1W1W1 | |
12022 | // ... | |
12023 | ||
12024 | // multiplicity (number of particles used to determine the reaction plane) | |
12025 | Double_t dMult = (*fSMpk)(0,0); | |
12026 | ||
12027 | // real and imaginary parts of weighted Q-vectors evaluated in harmonics n, 2n, 3n and 4n: | |
12028 | Double_t dReQ1n1k = (*fReQ)(0,1); | |
12029 | Double_t dReQ2n2k = (*fReQ)(1,2); | |
12030 | //Double_t dReQ3n3k = (*fReQ)(2,3); | |
12031 | //Double_t dReQ4n4k = (*fReQ)(3,4); | |
12032 | //Double_t dReQ1n3k = (*fReQ)(0,3); | |
12033 | Double_t dImQ1n1k = (*fImQ)(0,1); | |
12034 | Double_t dImQ2n2k = (*fImQ)(1,2); | |
12035 | //Double_t dImQ3n3k = (*fImQ)(2,3); | |
12036 | //Double_t dImQ4n4k = (*fImQ)(3,4); | |
12037 | Double_t dImQ1n3k = (*fImQ)(0,3); | |
12038 | ||
12039 | // dMs are variables introduced in order to simplify some Eqs. bellow: | |
12040 | //.............................................................................................. | |
12041 | Double_t dM11 = (*fSMpk)(1,1)-(*fSMpk)(0,2); // dM11 = sum_{i,j=1,i!=j}^M w_i w_j | |
57340a27 | 12042 | Double_t dM111 = (*fSMpk)(2,1)-3.*(*fSMpk)(0,2)*(*fSMpk)(0,1) |
489d5531 | 12043 | + 2.*(*fSMpk)(0,3); // dM111 = sum_{i,j,k=1,i!=j!=k}^M w_i w_j w_k |
12044 | //.............................................................................................. | |
12045 | ||
12046 | // 1-particle: | |
12047 | Double_t sinP1nW1 = 0.; // <<w1 sin(n*(phi1))>> | |
12048 | ||
0328db2d | 12049 | if(dMult>0 && TMath::Abs((*fSMpk)(0,1))>1e-6) |
489d5531 | 12050 | { |
12051 | sinP1nW1 = dImQ1n1k/((*fSMpk)(0,1)); | |
12052 | ||
12053 | // average weighted 1-particle correction (sin terms) for non-uniform acceptance for single event: | |
12054 | fIntFlowCorrectionTermsForNUAEBE[0]->SetBinContent(1,sinP1nW1); | |
12055 | ||
12056 | // final average weighted 1-particle correction (sin terms) for non-uniform acceptance for all events: | |
12057 | fIntFlowCorrectionTermsForNUAPro[0]->Fill(0.5,sinP1nW1,(*fSMpk)(0,1)); | |
12058 | } | |
12059 | ||
12060 | // 2-particle: | |
12061 | Double_t sinP1nP1nW1W1 = 0.; // <<w1 w2 sin(n*(phi1+phi2))>> | |
12062 | ||
0328db2d | 12063 | if(dMult>1 && TMath::Abs(dM11)>1e-6) |
489d5531 | 12064 | { |
12065 | sinP1nP1nW1W1 = (2.*dReQ1n1k*dImQ1n1k-dImQ2n2k)/dM11; | |
12066 | ||
12067 | // average weighted 2-particle correction (sin terms) for non-uniform acceptance for single event: | |
12068 | fIntFlowCorrectionTermsForNUAEBE[0]->SetBinContent(2,sinP1nP1nW1W1); | |
12069 | ||
12070 | // final average weighted 1-particle correction (sin terms) for non-uniform acceptance for all events: | |
12071 | fIntFlowCorrectionTermsForNUAPro[0]->Fill(1.5,sinP1nP1nW1W1,dM11); | |
12072 | } | |
12073 | ||
12074 | // 3-particle: | |
12075 | Double_t sinP1nM1nM1nW1W1W1 = 0.; // <<w1 w2 w3 sin(n*(phi1-phi2-phi3))>> | |
12076 | ||
0328db2d | 12077 | if(dMult>2 && TMath::Abs(dM111)>1e-6) |
489d5531 | 12078 | { |
57340a27 | 12079 | sinP1nM1nM1nW1W1W1 = (-dImQ1n1k*(pow(dReQ1n1k,2)+pow(dImQ1n1k,2)) |
12080 | + dReQ1n1k*dImQ2n2k-dImQ1n1k*dReQ2n2k | |
12081 | + 2.*((*fSMpk)(0,2))*dImQ1n1k | |
489d5531 | 12082 | - 2.*dImQ1n3k) |
12083 | / dM111; | |
12084 | ||
12085 | // average weighted 3-particle correction (sin terms) for non-uniform acceptance for single event: | |
12086 | fIntFlowCorrectionTermsForNUAEBE[0]->SetBinContent(3,sinP1nM1nM1nW1W1W1); | |
12087 | ||
12088 | // final average weighted 3-particle correction (sin terms) for non-uniform acceptance for all events: | |
12089 | fIntFlowCorrectionTermsForNUAPro[0]->Fill(2.5,sinP1nM1nM1nW1W1W1,dM111); | |
12090 | } | |
12091 | ||
12092 | } // end of AliFlowAnalysisWithQCumulants::CalculateIntFlowCorrectionsForNUASinTermsUsingParticleWeights() | |
12093 | ||
12094 | ||
57340a27 | 12095 | //================================================================================================================================ |
489d5531 | 12096 | |
12097 | ||
0328db2d | 12098 | void AliFlowAnalysisWithQCumulants::EvaluateIntFlowCorrectionsForNUAWithNestedLoopsUsingParticleWeights(AliFlowEventSimple * const anEvent) |
489d5531 | 12099 | { |
12100 | // Evaluate with nested loops correction terms for non-uniform acceptance for integrated flow (using the particle weights). | |
12101 | ||
57340a27 | 12102 | // Results are stored in profiles fIntFlowDirectCorrectionTermsForNUA[0] (sin terms) and |
12103 | // fIntFlowDirectCorrectionTermsForNUA[1] (cos terms). | |
489d5531 | 12104 | |
57340a27 | 12105 | // Remark 1: When particle weights are used the binning of fIntFlowDirectCorrectionTermsForNUA[sc] is |
489d5531 | 12106 | // organized as follows (sc stands for either sin or cos): |
12107 | // | |
12108 | // 1st bin: <<w1 sc(n*(phi1))>> = scP1nW1 | |
12109 | // 2nd bin: <<w1 w2 sc(n*(phi1+phi2))>> = scP1nP1nW1W1 | |
12110 | // 3rd bin: <<w1 w2 w3 sc(n*(phi1-phi2-phi3))>> = scP1nM1nM1nW1W1W1 | |
3b552efe | 12111 | // ... |
489d5531 | 12112 | |
12113 | Int_t nPrim = anEvent->NumberOfTracks(); | |
12114 | AliFlowTrackSimple *aftsTrack = NULL; | |
12115 | //Double_t phi1=0., phi2=0., phi3=0., phi4=0., phi5=0., phi6=0., phi7=0., phi8=0.; | |
12116 | //Double_t wPhi1=1., wPhi2=1., wPhi3=1., wPhi4=1., wPhi5=1., wPhi6=1., wPhi7=1., wPhi8=1.; | |
12117 | Double_t phi1=0., phi2=0., phi3=0.; | |
12118 | Double_t wPhi1=1., wPhi2=1., wPhi3=1.; | |
12119 | Int_t n = fHarmonic; | |
12120 | Int_t eventNo = (Int_t)fAvMultiplicity->GetBinEntries(1); // to be improved (is this casting safe in general?) | |
12121 | Double_t dMult = (*fSMpk)(0,0); | |
12122 | cout<<endl; | |
12123 | cout<<"Correction terms for non-uniform acceptance: Event number: "<<eventNo<<", multiplicity is "<<dMult<<endl; | |
12124 | if(dMult<1) | |
12125 | { | |
12126 | cout<<"... skipping this event (multiplicity too low) ..."<<endl; | |
12127 | } else if (dMult>fMaxAllowedMultiplicity) | |
12128 | { | |
12129 | cout<<"... skipping this event (multiplicity too high) ..."<<endl; | |
12130 | } else | |
12131 | { | |
12132 | cout<<"... evaluating nested loops (using particle weights) ..."<<endl; | |
12133 | } | |
12134 | ||
12135 | // 1-particle correction terms using particle weights: | |
12136 | if(nPrim>=1 && nPrim<=fMaxAllowedMultiplicity) | |
12137 | { | |
12138 | for(Int_t i1=0;i1<nPrim;i1++) | |
12139 | { | |
12140 | aftsTrack=anEvent->GetTrack(i1); | |
12141 | if(!(aftsTrack->InRPSelection())) continue; | |
12142 | phi1=aftsTrack->Phi(); | |
12143 | if(fUsePhiWeights && fPhiWeights) wPhi1 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi1*fnBinsPhi/TMath::TwoPi()))); | |
57340a27 | 12144 | // 1-particle correction terms using particle weights: |
489d5531 | 12145 | if(fUsePhiWeights) fIntFlowDirectCorrectionTermsForNUA[0]->Fill(0.5,sin(n*phi1),wPhi1); // <w1 sin(n*phi1)> |
12146 | if(fUsePhiWeights) fIntFlowDirectCorrectionTermsForNUA[1]->Fill(0.5,cos(n*phi1),wPhi1); // <w1 cos(n*phi1)> | |
57340a27 | 12147 | } // end of for(Int_t i1=0;i1<nPrim;i1++) |
12148 | } // end of if(nPrim>=1 && nPrim<=fMaxAllowedMultiplicity) | |
12149 | ||
489d5531 | 12150 | // 2-particle correction terms using particle weights: |
12151 | if(nPrim>=2 && nPrim<=fMaxAllowedMultiplicity) | |
12152 | { | |
12153 | for(Int_t i1=0;i1<nPrim;i1++) | |
12154 | { | |
12155 | aftsTrack=anEvent->GetTrack(i1); | |
12156 | if(!(aftsTrack->InRPSelection())) continue; | |
12157 | phi1=aftsTrack->Phi(); | |
12158 | if(fUsePhiWeights && fPhiWeights) wPhi1 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi1*fnBinsPhi/TMath::TwoPi()))); | |
12159 | for(Int_t i2=0;i2<nPrim;i2++) | |
12160 | { | |
12161 | if(i2==i1)continue; | |
12162 | aftsTrack=anEvent->GetTrack(i2); | |
12163 | if(!(aftsTrack->InRPSelection())) continue; | |
12164 | phi2=aftsTrack->Phi(); | |
12165 | if(fUsePhiWeights && fPhiWeights) wPhi2 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi2*fnBinsPhi/TMath::TwoPi()))); | |
12166 | if(nPrim==2) cout<<i1<<" "<<i2<<"\r"<<flush; | |
57340a27 | 12167 | // 2-p correction terms using particle weights: |
489d5531 | 12168 | if(fUsePhiWeights) fIntFlowDirectCorrectionTermsForNUA[0]->Fill(1.5,sin(n*(phi1+phi2)),wPhi1*wPhi2); // <w1 w2 sin(n*(phi1+phi2))> |
12169 | if(fUsePhiWeights) fIntFlowDirectCorrectionTermsForNUA[1]->Fill(1.5,cos(n*(phi1+phi2)),wPhi1*wPhi2); // <w1 w2 cos(n*(phi1+phi2))> | |
12170 | } // end of for(Int_t i2=0;i2<nPrim;i2++) | |
12171 | } // end of for(Int_t i1=0;i1<nPrim;i1++) | |
12172 | } // end of if(nPrim>=2) | |
12173 | ||
12174 | // 3-particle correction terms using particle weights: | |
12175 | if(nPrim>=3 && nPrim<=fMaxAllowedMultiplicity) | |
12176 | { | |
12177 | for(Int_t i1=0;i1<nPrim;i1++) | |
12178 | { | |
12179 | aftsTrack=anEvent->GetTrack(i1); | |
12180 | if(!(aftsTrack->InRPSelection())) continue; | |
12181 | phi1=aftsTrack->Phi(); | |
12182 | if(fUsePhiWeights && fPhiWeights) wPhi1 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi1*fnBinsPhi/TMath::TwoPi()))); | |
12183 | for(Int_t i2=0;i2<nPrim;i2++) | |
12184 | { | |
12185 | if(i2==i1)continue; | |
12186 | aftsTrack=anEvent->GetTrack(i2); | |
12187 | if(!(aftsTrack->InRPSelection())) continue; | |
12188 | phi2=aftsTrack->Phi(); | |
12189 | if(fUsePhiWeights && fPhiWeights) wPhi2 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi2*fnBinsPhi/TMath::TwoPi()))); | |
12190 | for(Int_t i3=0;i3<nPrim;i3++) | |
12191 | { | |
12192 | if(i3==i1||i3==i2)continue; | |
12193 | aftsTrack=anEvent->GetTrack(i3); | |
12194 | if(!(aftsTrack->InRPSelection())) continue; | |
12195 | phi3=aftsTrack->Phi(); | |
12196 | if(fUsePhiWeights && fPhiWeights) wPhi3 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi3*fnBinsPhi/TMath::TwoPi()))); | |
12197 | if(nPrim==3) cout<<i1<<" "<<i2<<" "<<i3<<"\r"<<flush; | |
57340a27 | 12198 | // 3-p correction terms using particle weights: |
489d5531 | 12199 | if(fUsePhiWeights) fIntFlowDirectCorrectionTermsForNUA[0]->Fill(2.5,sin(n*(phi1-phi2-phi3)),wPhi1*wPhi2*wPhi3); // <w1 w2 w3 sin(n*(phi1-phi2-phi3))> |
12200 | if(fUsePhiWeights) fIntFlowDirectCorrectionTermsForNUA[1]->Fill(2.5,cos(n*(phi1-phi2-phi3)),wPhi1*wPhi2*wPhi3); // <w1 w2 w3 cos(n*(phi1-phi2-phi3))> | |
12201 | } // end of for(Int_t i3=0;i3<nPrim;i3++) | |
12202 | } // end of for(Int_t i2=0;i2<nPrim;i2++) | |
12203 | } // end of for(Int_t i1=0;i1<nPrim;i1++) | |
12204 | } // end of if(nPrim>=3) | |
12205 | ||
57340a27 | 12206 | /* |
12207 | ||
489d5531 | 12208 | if(nPrim>=4 && nPrim<=fMaxAllowedMultiplicity) |
12209 | { | |
12210 | // 4 nested loops multiparticle correlations using particle weights: | |
12211 | for(Int_t i1=0;i1<nPrim;i1++) | |
12212 | { | |
12213 | aftsTrack=anEvent->GetTrack(i1); | |
12214 | if(!(aftsTrack->InRPSelection())) continue; | |
12215 | phi1=aftsTrack->Phi(); | |
12216 | if(fUsePhiWeights && fPhiWeights) wPhi1 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi1*fnBinsPhi/TMath::TwoPi()))); | |
12217 | for(Int_t i2=0;i2<nPrim;i2++) | |
12218 | { | |
12219 | if(i2==i1)continue; | |
12220 | aftsTrack=anEvent->GetTrack(i2); | |
12221 | if(!(aftsTrack->InRPSelection())) continue; | |
12222 | phi2=aftsTrack->Phi(); | |
12223 | if(fUsePhiWeights && fPhiWeights) wPhi2 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi2*fnBinsPhi/TMath::TwoPi()))); | |
12224 | for(Int_t i3=0;i3<nPrim;i3++) | |
12225 | { | |
12226 | if(i3==i1||i3==i2)continue; | |
12227 | aftsTrack=anEvent->GetTrack(i3); | |
12228 | if(!(aftsTrack->InRPSelection())) continue; | |
12229 | phi3=aftsTrack->Phi(); | |
12230 | if(fUsePhiWeights && fPhiWeights) wPhi3 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi3*fnBinsPhi/TMath::TwoPi()))); | |
12231 | for(Int_t i4=0;i4<nPrim;i4++) | |
12232 | { | |
12233 | if(i4==i1||i4==i2||i4==i3)continue; | |
12234 | aftsTrack=anEvent->GetTrack(i4); | |
12235 | if(!(aftsTrack->InRPSelection())) continue; | |
12236 | phi4=aftsTrack->Phi(); | |
12237 | if(fUsePhiWeights && fPhiWeights) wPhi4 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi4*fnBinsPhi/TMath::TwoPi()))); | |
12238 | if(nPrim>=4) cout<<i1<<" "<<i2<<" "<<i3<<" "<<i4<<"\r"<<flush; // to be improved (replace eventually this if statement with if(nPrim==4)) | |
12239 | // 4-p correlations using particle weights: | |
12240 | if(fUsePhiWeights) fIntFlowDirectCorrelations->Fill(10.5,cos(n*phi1+n*phi2-n*phi3-n*phi4),wPhi1*wPhi2*wPhi3*wPhi4); | |
12241 | // extra correlations: | |
12242 | // 2-p extra correlations (do not appear if particle weights are not used): | |
12243 | // ... | |
12244 | // 3-p extra correlations (do not appear if particle weights are not used): | |
12245 | // ... | |
12246 | // 4-p extra correlations (do not appear if particle weights are not used): | |
12247 | // ... | |
12248 | } // end of for(Int_t i4=0;i4<nPrim;i4++) | |
12249 | } // end of for(Int_t i3=0;i3<nPrim;i3++) | |
12250 | } // end of for(Int_t i2=0;i2<nPrim;i2++) | |
12251 | } // end of for(Int_t i1=0;i1<nPrim;i1++) | |
12252 | } // end of if(nPrim>=4) | |
12253 | ||
12254 | */ | |
12255 | ||
12256 | cout<<endl; | |
12257 | ||
12258 | } // end of void AliFlowAnalysisWithQCumulants::EvaluateIntFlowCorrectionsForNUAWithNestedLoopsUsingParticleWeights(AliFlowEventSimple* anEvent) | |
12259 | ||
12260 | ||
57340a27 | 12261 | //================================================================================================================================ |
489d5531 | 12262 | |
12263 | ||
12264 | void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrectionsForNUACosTermsUsingParticleWeights(TString type, TString ptOrEta) | |
12265 | { | |
12266 | // Calculate correction terms for non-uniform acceptance for differential flow (cos terms) using particle weights. | |
57340a27 | 12267 | |
489d5531 | 12268 | // Results are stored in fDiffFlowCorrectionTermsForNUAPro[t][pe][1][cti], where cti runs as follows: |
57340a27 | 12269 | // |
489d5531 | 12270 | // 0: <<cos n(psi)>> |
12271 | // 1: <<w2 cos n(psi1+phi2)>> | |
12272 | // 2: <<w2 w3 cos n(psi1+phi2-phi3)>> | |
12273 | // 3: <<w2 w3 cos n(psi1-phi2-phi3)>> | |
12274 | // 4: | |
12275 | // 5: | |
12276 | // 6: | |
12277 | ||
12278 | // real and imaginary parts of weighted Q-vectors evaluated in harmonics n, 2n, 3n and 4n: | |
12279 | Double_t dReQ1n1k = (*fReQ)(0,1); | |
12280 | Double_t dReQ2n2k = (*fReQ)(1,2); | |
12281 | //Double_t dReQ1n3k = (*fReQ)(0,3); | |
12282 | //Double_t dReQ4n4k = (*fReQ)(3,4); | |
12283 | Double_t dImQ1n1k = (*fImQ)(0,1); | |
12284 | Double_t dImQ2n2k = (*fImQ)(1,2); | |
12285 | //Double_t dImQ1n3k = (*fImQ)(0,3); | |
12286 | //Double_t dImQ4n4k = (*fImQ)(3,4); | |
12287 | ||
12288 | // S^M_{p,k} (see .h file for the definition of fSMpk): | |
12289 | Double_t dSM1p1k = (*fSMpk)(0,1); | |
12290 | Double_t dSM1p2k = (*fSMpk)(0,2); | |
12291 | Double_t dSM2p1k = (*fSMpk)(1,1); | |
12292 | ||
2a98ceb8 | 12293 | Int_t t = 0; // type flag |
12294 | Int_t pe = 0; // ptEta flag | |
489d5531 | 12295 | |
12296 | if(type == "RP") | |
12297 | { | |
12298 | t = 0; | |
12299 | } else if(type == "POI") | |
12300 | { | |
12301 | t = 1; | |
12302 | } | |
12303 | ||
12304 | if(ptOrEta == "Pt") | |
12305 | { | |
12306 | pe = 0; | |
12307 | } else if(ptOrEta == "Eta") | |
12308 | { | |
12309 | pe = 1; | |
12310 | } | |
12311 | ||
12312 | Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; | |
12313 | Double_t minPtEta[2] = {fPtMin,fEtaMin}; | |
12314 | //Double_t maxPtEta[2] = {fPtMax,fEtaMax}; | |
12315 | Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; | |
12316 | ||
12317 | // looping over all bins and calculating correction terms: | |
12318 | for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
12319 | { | |
12320 | // real and imaginary parts of p_{m*n,0} (non-weighted Q-vector evaluated for POIs in particular pt or eta bin): | |
12321 | Double_t p1n0kRe = 0.; | |
12322 | Double_t p1n0kIm = 0.; | |
12323 | ||
12324 | // number of POIs in particular pt or eta bin: | |
12325 | Double_t mp = 0.; | |
12326 | ||
12327 | // real and imaginary parts of q_{m*n,0} (weighted Q-vector evaluated for particles which are both RPs and POIs in particular pt or eta bin): | |
12328 | Double_t q1n2kRe = 0.; | |
12329 | Double_t q1n2kIm = 0.; | |
12330 | Double_t q2n1kRe = 0.; | |
12331 | Double_t q2n1kIm = 0.; | |
46b94261 | 12332 | |
489d5531 | 12333 | // s_{1,1}, s_{1,2} // to be improved (add explanation) |
12334 | Double_t s1p1k = 0.; | |
12335 | Double_t s1p2k = 0.; | |
46b94261 | 12336 | |
489d5531 | 12337 | // number of particles which are both RPs and POIs in particular pt or eta bin: |
46b94261 | 12338 | Double_t mq = 0.; |
489d5531 | 12339 | |
12340 | // M0111 from Eq. (118) in QC2c (to be improved (notation)) | |
12341 | Double_t dM01 = 0.; | |
12342 | Double_t dM011 = 0.; | |
12343 | ||
12344 | if(type == "POI") | |
12345 | { | |
12346 | // q_{m*n,k}: | |
12347 | q1n2kRe = fReRPQ1dEBE[2][pe][0][2]->GetBinContent(fReRPQ1dEBE[2][pe][0][2]->GetBin(b)) | |
12348 | * fReRPQ1dEBE[2][pe][0][2]->GetBinEntries(fReRPQ1dEBE[2][pe][0][2]->GetBin(b)); | |
12349 | q1n2kIm = fImRPQ1dEBE[2][pe][0][2]->GetBinContent(fImRPQ1dEBE[2][pe][0][2]->GetBin(b)) | |
12350 | * fImRPQ1dEBE[2][pe][0][2]->GetBinEntries(fImRPQ1dEBE[2][pe][0][2]->GetBin(b)); | |
12351 | q2n1kRe = fReRPQ1dEBE[2][pe][1][1]->GetBinContent(fReRPQ1dEBE[2][pe][1][1]->GetBin(b)) | |
12352 | * fReRPQ1dEBE[2][pe][1][1]->GetBinEntries(fReRPQ1dEBE[2][pe][1][1]->GetBin(b)); | |
12353 | q2n1kIm = fImRPQ1dEBE[2][pe][1][1]->GetBinContent(fImRPQ1dEBE[2][pe][1][1]->GetBin(b)) | |
12354 | * fImRPQ1dEBE[2][pe][1][1]->GetBinEntries(fImRPQ1dEBE[2][pe][1][1]->GetBin(b)); | |
12355 | mq = fReRPQ1dEBE[2][pe][1][1]->GetBinEntries(fReRPQ1dEBE[2][pe][1][1]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) | |
46b94261 | 12356 | |
489d5531 | 12357 | s1p1k = pow(fs1dEBE[2][pe][1]->GetBinContent(b)*fs1dEBE[2][pe][1]->GetBinEntries(b),1.); |
12358 | s1p2k = pow(fs1dEBE[2][pe][2]->GetBinContent(b)*fs1dEBE[2][pe][2]->GetBinEntries(b),1.); | |
12359 | }else if(type == "RP") | |
12360 | { | |
12361 | // q_{m*n,k}: (Remark: m=1 is 0, k=0 iz zero (to be improved!)) | |
12362 | q1n2kRe = fReRPQ1dEBE[0][pe][0][2]->GetBinContent(fReRPQ1dEBE[0][pe][0][2]->GetBin(b)) | |
12363 | * fReRPQ1dEBE[0][pe][0][2]->GetBinEntries(fReRPQ1dEBE[0][pe][0][2]->GetBin(b)); | |
12364 | q1n2kIm = fImRPQ1dEBE[0][pe][0][2]->GetBinContent(fImRPQ1dEBE[0][pe][0][2]->GetBin(b)) | |
12365 | * fImRPQ1dEBE[0][pe][0][2]->GetBinEntries(fImRPQ1dEBE[0][pe][0][2]->GetBin(b)); | |
12366 | q2n1kRe = fReRPQ1dEBE[0][pe][1][1]->GetBinContent(fReRPQ1dEBE[0][pe][1][1]->GetBin(b)) | |
12367 | * fReRPQ1dEBE[0][pe][1][1]->GetBinEntries(fReRPQ1dEBE[0][pe][1][1]->GetBin(b)); | |
12368 | q2n1kIm = fImRPQ1dEBE[0][pe][1][1]->GetBinContent(fImRPQ1dEBE[0][pe][1][1]->GetBin(b)) | |
12369 | * fImRPQ1dEBE[0][pe][1][1]->GetBinEntries(fImRPQ1dEBE[0][pe][1][1]->GetBin(b)); | |
12370 | // s_{1,1}, s_{1,2} and s_{1,3} // to be improved (add explanation) | |
12371 | s1p1k = pow(fs1dEBE[0][pe][1]->GetBinContent(b)*fs1dEBE[0][pe][1]->GetBinEntries(b),1.); | |
12372 | s1p2k = pow(fs1dEBE[0][pe][2]->GetBinContent(b)*fs1dEBE[0][pe][2]->GetBinEntries(b),1.); | |
3b552efe | 12373 | //s1p3k = pow(fs1dEBE[0][pe][3]->GetBinContent(b)*fs1dEBE[0][pe][3]->GetBinEntries(b),1.); |
12374 | ||
489d5531 | 12375 | mq = fReRPQ1dEBE[0][pe][1][1]->GetBinEntries(fReRPQ1dEBE[0][pe][1][1]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) |
12376 | } | |
3b552efe | 12377 | |
489d5531 | 12378 | if(type == "POI") |
3b552efe | 12379 | { |
12380 | // p_{m*n,k}: | |
489d5531 | 12381 | p1n0kRe = fReRPQ1dEBE[1][pe][0][0]->GetBinContent(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)) |
12382 | * fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)); | |
12383 | p1n0kIm = fImRPQ1dEBE[1][pe][0][0]->GetBinContent(fImRPQ1dEBE[1][pe][0][0]->GetBin(b)) | |
3b552efe | 12384 | * fImRPQ1dEBE[1][pe][0][0]->GetBinEntries(fImRPQ1dEBE[1][pe][0][0]->GetBin(b)); |
12385 | mp = fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) | |
489d5531 | 12386 | // M01 from Eq. (118) in QC2c (to be improved (notation)): |
3b552efe | 12387 | dM01 = mp*dSM1p1k-s1p1k; |
12388 | dM011 = mp*(dSM2p1k-dSM1p2k) | |
12389 | - 2.*(s1p1k*dSM1p1k-s1p2k); | |
12390 | ||
12391 | // typeFlag = RP (0) or POI (1): | |
12392 | t = 1; | |
12393 | } else if(type == "RP") | |
489d5531 | 12394 | { |
12395 | // to be improved (cross-checked): | |
12396 | p1n0kRe = fReRPQ1dEBE[0][pe][0][0]->GetBinContent(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)) | |
12397 | * fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)); | |
12398 | p1n0kIm = fImRPQ1dEBE[0][pe][0][0]->GetBinContent(fImRPQ1dEBE[0][pe][0][0]->GetBin(b)) | |
12399 | * fImRPQ1dEBE[0][pe][0][0]->GetBinEntries(fImRPQ1dEBE[0][pe][0][0]->GetBin(b)); | |
12400 | mp = fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) | |
12401 | // M01 from Eq. (118) in QC2c (to be improved (notation)): | |
3b552efe | 12402 | dM01 = mp*dSM1p1k-s1p1k; |
12403 | dM011 = mp*(dSM2p1k-dSM1p2k) | |
12404 | - 2.*(s1p1k*dSM1p1k-s1p2k); | |
489d5531 | 12405 | // typeFlag = RP (0) or POI (1): |
3b552efe | 12406 | t = 0; |
12407 | } | |
489d5531 | 12408 | |
12409 | // <<cos n(psi1)>>: | |
12410 | Double_t cosP1nPsi = 0.; | |
12411 | if(mp) | |
12412 | { | |
12413 | cosP1nPsi = p1n0kRe/mp; | |
12414 | ||
12415 | // fill profile for <<cos n(psi1)>>: | |
12416 | fDiffFlowCorrectionTermsForNUAPro[t][pe][1][0]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],cosP1nPsi,mp); | |
12417 | // histogram to store <cos n(psi1)> e-b-e (needed in some other methods): | |
12418 | fDiffFlowCorrectionTermsForNUAEBE[t][pe][1][0]->SetBinContent(b,cosP1nPsi); | |
46b94261 | 12419 | } // end of if(mp) |
57340a27 | 12420 | |
489d5531 | 12421 | // <<w2 cos n(psi1+phi2)>>: |
12422 | Double_t cosP1nPsiP1nPhiW2 = 0.; | |
12423 | if(dM01) | |
12424 | { | |
12425 | cosP1nPsiP1nPhiW2 = (p1n0kRe*dReQ1n1k-p1n0kIm*dImQ1n1k-q2n1kRe)/(dM01); | |
12426 | // fill profile for <<w2 cos n(psi1+phi2)>>: | |
12427 | fDiffFlowCorrectionTermsForNUAPro[t][pe][1][1]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],cosP1nPsiP1nPhiW2,dM01); | |
12428 | // histogram to store <w2 cos n(psi1+phi2)> e-b-e (needed in some other methods): | |
12429 | fDiffFlowCorrectionTermsForNUAEBE[t][pe][1][1]->SetBinContent(b,cosP1nPsiP1nPhiW2); | |
12430 | } // end of if(dM01) | |
12431 | ||
12432 | // <<w2 w3 cos n(psi1+phi2-phi3)>>: | |
12433 | Double_t cosP1nPsi1P1nPhi2MPhi3W2W3 = 0.; | |
12434 | if(dM011) | |
12435 | { | |
46b94261 | 12436 | cosP1nPsi1P1nPhi2MPhi3W2W3 = (p1n0kRe*(pow(dImQ1n1k,2.)+pow(dReQ1n1k,2.)) |
12437 | - p1n0kRe*dSM1p2k | |
12438 | - q2n1kRe*dReQ1n1k-q2n1kIm*dImQ1n1k | |
12439 | - s1p1k*dReQ1n1k | |
12440 | + 2.*q1n2kRe) | |
12441 | / dM011; | |
489d5531 | 12442 | // fill profile for <<w1 w2 w3 cos n(psi1+phi2)>>: |
12443 | fDiffFlowCorrectionTermsForNUAPro[t][pe][1][2]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],cosP1nPsi1P1nPhi2MPhi3W2W3,dM011); | |
12444 | // histogram to store <w1 w2 w3 cos n(psi1+phi2)> e-b-e (needed in some other methods): | |
12445 | fDiffFlowCorrectionTermsForNUAEBE[t][pe][1][2]->SetBinContent(b,cosP1nPsi1P1nPhi2MPhi3W2W3); | |
12446 | } // end of if(dM011) | |
12447 | ||
12448 | // <<w2 w3 cos n(psi1-phi2-phi3)>>: | |
12449 | Double_t cosP1nPsi1M1nPhi2MPhi3W2W3 = 0.; | |
12450 | if(dM011) | |
12451 | { | |
12452 | cosP1nPsi1M1nPhi2MPhi3W2W3 = (p1n0kRe*(pow(dReQ1n1k,2.)-pow(dImQ1n1k,2.))+2.*p1n0kIm*dReQ1n1k*dImQ1n1k | |
12453 | - 1.*(p1n0kRe*dReQ2n2k+p1n0kIm*dImQ2n2k) | |
46b94261 | 12454 | - 2.*s1p1k*dReQ1n1k |
489d5531 | 12455 | + 2.*q1n2kRe) |
12456 | / dM011; | |
12457 | // fill profile for <<w1 w2 w3 cos n(psi1+phi2)>>: | |
12458 | fDiffFlowCorrectionTermsForNUAPro[t][pe][1][3]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],cosP1nPsi1M1nPhi2MPhi3W2W3,dM011); | |
12459 | // histogram to store <w1 w2 w3 cos n(psi1+phi2)> e-b-e (needed in some other methods): | |
12460 | fDiffFlowCorrectionTermsForNUAEBE[t][pe][1][3]->SetBinContent(b,cosP1nPsi1M1nPhi2MPhi3W2W3); | |
12461 | } // end of if(dM011) | |
12462 | ||
12463 | } // end of for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
46b94261 | 12464 | |
57340a27 | 12465 | } // end of AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrectionsForNUACosTermsUsingParticleWeights(TString type, TString ptOrEta) |
12466 | ||
489d5531 | 12467 | |
12468 | //================================================================================================================================ | |
12469 | ||
12470 | ||
12471 | void AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrectionsForNUASinTermsUsingParticleWeights(TString type, TString ptOrEta) | |
12472 | { | |
12473 | // Calculate correction terms for non-uniform acceptance for differential flow (sin terms). | |
12474 | ||
12475 | // Results are stored in fDiffFlowCorrectionTermsForNUAPro[t][pe][0][cti], where cti runs as follows: | |
12476 | // 0: <<sin n(psi1)>> | |
12477 | // 1: <<w2 sin n(psi1+phi2)>> | |
12478 | // 2: <<w2 w3 sin n(psi1+phi2-phi3)>> | |
12479 | // 3: <<w2 w3 sin n(psi1-phi2-phi3)>>: | |
12480 | // 4: | |
12481 | // 5: | |
12482 | // 6: | |
12483 | ||
12484 | // real and imaginary parts of weighted Q-vectors evaluated in harmonics n, 2n, 3n and 4n: | |
12485 | Double_t dReQ1n1k = (*fReQ)(0,1); | |
12486 | Double_t dReQ2n2k = (*fReQ)(1,2); | |
12487 | //Double_t dReQ1n3k = (*fReQ)(0,3); | |
12488 | //Double_t dReQ4n4k = (*fReQ)(3,4); | |
12489 | Double_t dImQ1n1k = (*fImQ)(0,1); | |
12490 | Double_t dImQ2n2k = (*fImQ)(1,2); | |
12491 | //Double_t dImQ1n3k = (*fImQ)(0,3); | |
12492 | //Double_t dImQ4n4k = (*fImQ)(3,4); | |
12493 | ||
12494 | // S^M_{p,k} (see .h file for the definition of fSMpk): | |
12495 | Double_t dSM1p1k = (*fSMpk)(0,1); | |
12496 | Double_t dSM1p2k = (*fSMpk)(0,2); | |
12497 | Double_t dSM2p1k = (*fSMpk)(1,1); | |
12498 | ||
2a98ceb8 | 12499 | Int_t t = 0; // type flag |
12500 | Int_t pe = 0; // ptEta flag | |
489d5531 | 12501 | |
12502 | if(type == "RP") | |
12503 | { | |
12504 | t = 0; | |
12505 | } else if(type == "POI") | |
12506 | { | |
12507 | t = 1; | |
12508 | } | |
12509 | ||
12510 | if(ptOrEta == "Pt") | |
12511 | { | |
12512 | pe = 0; | |
12513 | } else if(ptOrEta == "Eta") | |
12514 | { | |
12515 | pe = 1; | |
12516 | } | |
12517 | ||
12518 | Int_t nBinsPtEta[2] = {fnBinsPt,fnBinsEta}; | |
12519 | Double_t minPtEta[2] = {fPtMin,fEtaMin}; | |
12520 | //Double_t maxPtEta[2] = {fPtMax,fEtaMax}; | |
12521 | Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; | |
12522 | ||
12523 | // looping over all bins and calculating correction terms: | |
12524 | for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
12525 | { | |
12526 | // real and imaginary parts of p_{m*n,0} (non-weighted Q-vector evaluated for POIs in particular pt or eta bin): | |
12527 | Double_t p1n0kRe = 0.; | |
12528 | Double_t p1n0kIm = 0.; | |
12529 | ||
12530 | // number of POIs in particular pt or eta bin: | |
12531 | Double_t mp = 0.; | |
12532 | ||
12533 | // real and imaginary parts of q_{m*n,0} (weighted Q-vector evaluated for particles which are both RPs and POIs in particular pt or eta bin): | |
12534 | Double_t q1n2kRe = 0.; | |
12535 | Double_t q1n2kIm = 0.; | |
12536 | Double_t q2n1kRe = 0.; | |
12537 | Double_t q2n1kIm = 0.; | |
46b94261 | 12538 | |
489d5531 | 12539 | // s_{1,1}, s_{1,2} and s_{1,3} // to be improved (add explanation) |
12540 | Double_t s1p1k = 0.; | |
12541 | Double_t s1p2k = 0.; | |
46b94261 | 12542 | |
489d5531 | 12543 | // number of particles which are both RPs and POIs in particular pt or eta bin: |
46b94261 | 12544 | Double_t mq = 0.; |
489d5531 | 12545 | |
12546 | // M0111 from Eq. (118) in QC2c (to be improved (notation)) | |
12547 | Double_t dM01 = 0.; | |
12548 | Double_t dM011 = 0.; | |
12549 | ||
12550 | if(type == "POI") | |
12551 | { | |
12552 | // q_{m*n,k}: | |
12553 | q1n2kRe = fReRPQ1dEBE[2][pe][0][2]->GetBinContent(fReRPQ1dEBE[2][pe][0][2]->GetBin(b)) | |
12554 | * fReRPQ1dEBE[2][pe][0][2]->GetBinEntries(fReRPQ1dEBE[2][pe][0][2]->GetBin(b)); | |
12555 | q1n2kIm = fImRPQ1dEBE[2][pe][0][2]->GetBinContent(fImRPQ1dEBE[2][pe][0][2]->GetBin(b)) | |
12556 | * fImRPQ1dEBE[2][pe][0][2]->GetBinEntries(fImRPQ1dEBE[2][pe][0][2]->GetBin(b)); | |
12557 | q2n1kRe = fReRPQ1dEBE[2][pe][1][1]->GetBinContent(fReRPQ1dEBE[2][pe][1][1]->GetBin(b)) | |
12558 | * fReRPQ1dEBE[2][pe][1][1]->GetBinEntries(fReRPQ1dEBE[2][pe][1][1]->GetBin(b)); | |
12559 | q2n1kIm = fImRPQ1dEBE[2][pe][1][1]->GetBinContent(fImRPQ1dEBE[2][pe][1][1]->GetBin(b)) | |
12560 | * fImRPQ1dEBE[2][pe][1][1]->GetBinEntries(fImRPQ1dEBE[2][pe][1][1]->GetBin(b)); | |
12561 | mq = fReRPQ1dEBE[2][pe][0][0]->GetBinEntries(fReRPQ1dEBE[2][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) | |
46b94261 | 12562 | |
489d5531 | 12563 | s1p1k = pow(fs1dEBE[2][pe][1]->GetBinContent(b)*fs1dEBE[2][pe][1]->GetBinEntries(b),1.); |
12564 | s1p2k = pow(fs1dEBE[2][pe][2]->GetBinContent(b)*fs1dEBE[2][pe][2]->GetBinEntries(b),1.); | |
12565 | }else if(type == "RP") | |
12566 | { | |
12567 | // q_{m*n,k}: (Remark: m=1 is 0, k=0 iz zero (to be improved!)) | |
12568 | q1n2kRe = fReRPQ1dEBE[0][pe][0][2]->GetBinContent(fReRPQ1dEBE[0][pe][0][2]->GetBin(b)) | |
12569 | * fReRPQ1dEBE[0][pe][0][2]->GetBinEntries(fReRPQ1dEBE[0][pe][0][2]->GetBin(b)); | |
12570 | q1n2kIm = fImRPQ1dEBE[0][pe][0][2]->GetBinContent(fImRPQ1dEBE[0][pe][0][2]->GetBin(b)) | |
12571 | * fImRPQ1dEBE[0][pe][0][2]->GetBinEntries(fImRPQ1dEBE[0][pe][0][2]->GetBin(b)); | |
12572 | q2n1kRe = fReRPQ1dEBE[0][pe][1][1]->GetBinContent(fReRPQ1dEBE[0][pe][1][1]->GetBin(b)) | |
12573 | * fReRPQ1dEBE[0][pe][1][1]->GetBinEntries(fReRPQ1dEBE[0][pe][1][1]->GetBin(b)); | |
12574 | q2n1kIm = fImRPQ1dEBE[0][pe][1][1]->GetBinContent(fImRPQ1dEBE[0][pe][1][1]->GetBin(b)) | |
12575 | * fImRPQ1dEBE[0][pe][1][1]->GetBinEntries(fImRPQ1dEBE[0][pe][1][1]->GetBin(b)); | |
12576 | // s_{1,1}, s_{1,2} and s_{1,3} // to be improved (add explanation) | |
12577 | s1p1k = pow(fs1dEBE[0][pe][1]->GetBinContent(b)*fs1dEBE[0][pe][1]->GetBinEntries(b),1.); | |
12578 | s1p2k = pow(fs1dEBE[0][pe][2]->GetBinContent(b)*fs1dEBE[0][pe][2]->GetBinEntries(b),1.); | |
12579 | //s1p3k = pow(fs1dEBE[0][pe][3]->GetBinContent(b)*fs1dEBE[0][pe][3]->GetBinEntries(b),1.); | |
3b552efe | 12580 | } |
12581 | ||
12582 | if(type == "POI") | |
12583 | { | |
12584 | // p_{m*n,k}: | |
489d5531 | 12585 | p1n0kRe = fReRPQ1dEBE[1][pe][0][0]->GetBinContent(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)) |
12586 | * fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)); | |
12587 | p1n0kIm = fImRPQ1dEBE[1][pe][0][0]->GetBinContent(fImRPQ1dEBE[1][pe][0][0]->GetBin(b)) | |
3b552efe | 12588 | * fImRPQ1dEBE[1][pe][0][0]->GetBinEntries(fImRPQ1dEBE[1][pe][0][0]->GetBin(b)); |
12589 | mp = fReRPQ1dEBE[1][pe][0][0]->GetBinEntries(fReRPQ1dEBE[1][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) | |
489d5531 | 12590 | // M01 from Eq. (118) in QC2c (to be improved (notation)): |
3b552efe | 12591 | dM01 = mp*dSM1p1k-s1p1k; |
12592 | dM011 = mp*(dSM2p1k-dSM1p2k) | |
12593 | - 2.*(s1p1k*dSM1p1k-s1p2k); | |
12594 | // typeFlag = RP (0) or POI (1): | |
12595 | t = 1; | |
489d5531 | 12596 | } else if(type == "RP") |
3b552efe | 12597 | { |
489d5531 | 12598 | // to be improved (cross-checked): |
12599 | p1n0kRe = fReRPQ1dEBE[0][pe][0][0]->GetBinContent(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)) | |
12600 | * fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)); | |
12601 | p1n0kIm = fImRPQ1dEBE[0][pe][0][0]->GetBinContent(fImRPQ1dEBE[0][pe][0][0]->GetBin(b)) | |
12602 | * fImRPQ1dEBE[0][pe][0][0]->GetBinEntries(fImRPQ1dEBE[0][pe][0][0]->GetBin(b)); | |
12603 | mp = fReRPQ1dEBE[0][pe][0][0]->GetBinEntries(fReRPQ1dEBE[0][pe][0][0]->GetBin(b)); // to be improved (cross-checked by accessing other profiles here) | |
12604 | // M01 from Eq. (118) in QC2c (to be improved (notation)): | |
3b552efe | 12605 | dM01 = mp*dSM1p1k-s1p1k; |
12606 | dM011 = mp*(dSM2p1k-dSM1p2k) | |
489d5531 | 12607 | - 2.*(s1p1k*dSM1p1k-s1p2k); |
12608 | // typeFlag = RP (0) or POI (1): | |
3b552efe | 12609 | t = 0; |
12610 | } | |
12611 | ||
489d5531 | 12612 | // <<sin n(psi1)>>: |
12613 | Double_t sinP1nPsi = 0.; | |
12614 | if(mp) | |
12615 | { | |
12616 | sinP1nPsi = p1n0kIm/mp; | |
12617 | ||
12618 | // fill profile for <<sin n(psi1)>>: | |
12619 | fDiffFlowCorrectionTermsForNUAPro[t][pe][0][0]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sinP1nPsi,mp); | |
12620 | // histogram to store <sin n(psi1)> e-b-e (needed in some other methods): | |
12621 | fDiffFlowCorrectionTermsForNUAEBE[t][pe][0][0]->SetBinContent(b,sinP1nPsi); | |
46b94261 | 12622 | } // end of if(mp) |
12623 | ||
489d5531 | 12624 | // <<w2 sin n(psi1+phi2)>>: |
12625 | Double_t sinP1nPsiP1nPhiW2 = 0.; | |
12626 | if(dM01) | |
12627 | { | |
12628 | sinP1nPsiP1nPhiW2 = (p1n0kRe*dImQ1n1k+p1n0kIm*dReQ1n1k-q2n1kIm)/(dM01); | |
12629 | // fill profile for <<w2 sin n(psi1+phi2)>>: | |
12630 | fDiffFlowCorrectionTermsForNUAPro[t][pe][0][1]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sinP1nPsiP1nPhiW2,dM01); | |
12631 | // histogram to store <w2 sin n(psi1+phi2)> e-b-e (needed in some other methods): | |
12632 | fDiffFlowCorrectionTermsForNUAEBE[t][pe][0][1]->SetBinContent(b,sinP1nPsiP1nPhiW2); | |
12633 | } // end of if(mp*dMult-mq) | |
12634 | ||
12635 | // <<w2 w3 sin n(psi1+phi2-phi3)>>: | |
12636 | Double_t sinP1nPsi1P1nPhi2MPhi3W2W3 = 0.; | |
12637 | if(dM011) | |
12638 | { | |
46b94261 | 12639 | sinP1nPsi1P1nPhi2MPhi3W2W3 = (p1n0kIm*(pow(dImQ1n1k,2.)+pow(dReQ1n1k,2.)) |
12640 | - p1n0kIm*dSM1p2k | |
12641 | + q2n1kRe*dImQ1n1k-q2n1kIm*dReQ1n1k | |
12642 | - s1p1k*dImQ1n1k | |
12643 | + 2.*q1n2kIm) | |
12644 | / dM011; | |
489d5531 | 12645 | // fill profile for <<w2 w3 sin n(psi1+phi2-phi3)>>: |
12646 | fDiffFlowCorrectionTermsForNUAPro[t][pe][0][2]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sinP1nPsi1P1nPhi2MPhi3W2W3,dM011); | |
12647 | // histogram to store <w2 w3 sin n(psi1+phi2-phi3)> e-b-e (needed in some other methods): | |
12648 | fDiffFlowCorrectionTermsForNUAEBE[t][pe][0][2]->SetBinContent(b,sinP1nPsi1P1nPhi2MPhi3W2W3); | |
12649 | } // end of if(dM011) | |
12650 | ||
12651 | // <<w2 w3 sin n(psi1-phi2-phi3)>>: | |
12652 | Double_t sinP1nPsi1M1nPhi2MPhi3W2W3 = 0.; | |
12653 | if(dM011) | |
12654 | { | |
12655 | sinP1nPsi1M1nPhi2MPhi3W2W3 = (p1n0kIm*(pow(dReQ1n1k,2.)-pow(dImQ1n1k,2.))-2.*p1n0kRe*dReQ1n1k*dImQ1n1k | |
12656 | + 1.*(p1n0kRe*dImQ2n2k-p1n0kIm*dReQ2n2k) | |
46b94261 | 12657 | + 2.*s1p1k*dImQ1n1k |
489d5531 | 12658 | - 2.*q1n2kIm) |
12659 | / dM011; | |
12660 | // fill profile for <<w2 w3 sin n(psi1-phi2-phi3)>>: | |
12661 | fDiffFlowCorrectionTermsForNUAPro[t][pe][0][3]->Fill(minPtEta[pe]+(b-1)*binWidthPtEta[pe],sinP1nPsi1M1nPhi2MPhi3W2W3,dM011); | |
12662 | // histogram to store <w2 w3 sin n(psi1-phi2-phi3)> e-b-e (needed in some other methods): | |
12663 | fDiffFlowCorrectionTermsForNUAEBE[t][pe][0][3]->SetBinContent(b,sinP1nPsi1M1nPhi2MPhi3W2W3); | |
12664 | } // end of if(dM011) | |
12665 | ||
12666 | } // end of for(Int_t b=1;b<=nBinsPtEta[pe];b++) | |
12667 | ||
12668 | } // end of AliFlowAnalysisWithQCumulants::CalculateDiffFlowCorrectionsForNUASinTermsUsingParticleWeights(TString type, TString ptOrEta) | |
12669 | ||
12670 | ||
12671 | //================================================================================================================================ | |
12672 | ||
12673 | ||
0328db2d | 12674 | void AliFlowAnalysisWithQCumulants::EvaluateDiffFlowCorrectionTermsForNUAWithNestedLoopsUsingParticleWeights(AliFlowEventSimple * const anEvent, TString type, TString ptOrEta) |
489d5531 | 12675 | { |
57340a27 | 12676 | // Evaluate with nested loops correction terms for non-uniform acceptance |
489d5531 | 12677 | // with using particle weights (both sin and cos terms) relevant for differential flow. |
12678 | ||
57340a27 | 12679 | // Remark 1: "w1" in expressions bellow is a particle weight used only for particles which were |
12680 | // flagged both as POI and RP. | |
489d5531 | 12681 | // Remark 2: Reduced correction terms for non-uniform acceptance are evaluated in pt bin number fCrossCheckInPtBinNo |
12682 | // and eta bin number fCrossCheckInEtaBinNo both for RPs and POIs. | |
12683 | // Remark 3: Results are stored in 1 bin profiles fDiffFlowDirectCorrections[t][pe][sc][cti], where first three indices runs as: | |
12684 | // [0=RP,1=POI][0=Pt,1=Eta][0=sin terms,1=cos terms], whilst the cti (correction term index) runs as follows: | |
12685 | // cti: | |
12686 | // 0: <<sc n(psi1)>> | |
12687 | // 1: <<w2 sc n(psi1+phi2)>> | |
12688 | // 2: <<w2 w3 sc n(psi1+phi2-phi3)>> | |
12689 | // 3: <<w2 w3 sc n(psi1-phi2-phi3)>> | |
12690 | // 4: | |
12691 | // 5: | |
12692 | // 6: | |
46b94261 | 12693 | |
2a98ceb8 | 12694 | Int_t typeFlag = 0; |
12695 | Int_t ptEtaFlag = 0; | |
489d5531 | 12696 | if(type == "RP") |
12697 | { | |
12698 | typeFlag = 0; | |
12699 | } else if(type == "POI") | |
12700 | { | |
12701 | typeFlag = 1; | |
12702 | } | |
12703 | if(ptOrEta == "Pt") | |
12704 | { | |
12705 | ptEtaFlag = 0; | |
12706 | } else if(ptOrEta == "Eta") | |
12707 | { | |
12708 | ptEtaFlag = 1; | |
12709 | } | |
12710 | // shortcuts: | |
12711 | Int_t t = typeFlag; | |
12712 | Int_t pe = ptEtaFlag; | |
12713 | ||
12714 | Double_t lowerPtEtaEdge[2] = {fPtMin+(fCrossCheckInPtBinNo-1)*fPtBinWidth,fEtaMin+(fCrossCheckInEtaBinNo-1)*fEtaBinWidth}; | |
12715 | Double_t upperPtEtaEdge[2] = {fPtMin+fCrossCheckInPtBinNo*fPtBinWidth,fEtaMin+fCrossCheckInEtaBinNo*fEtaBinWidth}; | |
12716 | Double_t binWidthPtEta[2] = {fPtBinWidth,fEtaBinWidth}; | |
12717 | ||
12718 | Int_t nPrim = anEvent->NumberOfTracks(); | |
12719 | AliFlowTrackSimple *aftsTrack = NULL; | |
12720 | ||
12721 | Double_t psi1=0., phi2=0., phi3=0.;// phi4=0.;// phi5=0., phi6=0., phi7=0., phi8=0.; | |
12722 | Double_t wPhi2=1., wPhi3=1.; | |
12723 | ||
12724 | Int_t n = fHarmonic; | |
12725 | ||
12726 | // 1'-particle correction terms: | |
12727 | for(Int_t i1=0;i1<nPrim;i1++) | |
12728 | { | |
12729 | aftsTrack=anEvent->GetTrack(i1); | |
3b552efe | 12730 | // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) |
12731 | if(typeFlag==1) // this is diff flow of POIs | |
489d5531 | 12732 | { |
12733 | if(ptOrEta == "Pt") | |
12734 | { | |
12735 | if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
12736 | } else if (ptOrEta == "Eta") | |
12737 | { | |
12738 | if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
3b552efe | 12739 | } |
12740 | } else // this is diff flow of RPs | |
12741 | { | |
489d5531 | 12742 | if(ptOrEta == "Pt") |
12743 | { | |
12744 | if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()<upperPtEtaEdge[pe]) && (aftsTrack->InRPSelection())))continue; | |
12745 | } else if (ptOrEta == "Eta") | |
12746 | { | |
12747 | if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()<upperPtEtaEdge[pe]) && (aftsTrack->InRPSelection())))continue; | |
3b552efe | 12748 | } |
489d5531 | 12749 | } |
12750 | psi1=aftsTrack->Phi(); | |
12751 | // sin terms: | |
12752 | fDiffFlowDirectCorrectionTermsForNUA[t][pe][0][0]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,sin(n*psi1),1.); // <<sin(n*(psi1))>> | |
12753 | // cos terms: | |
12754 | fDiffFlowDirectCorrectionTermsForNUA[t][pe][1][0]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(n*psi1),1.); // <<cos(n*(psi1))>> | |
12755 | }//end of for(Int_t i1=0;i1<nPrim;i1++) | |
12756 | ||
12757 | // 2'-particle correction terms: | |
12758 | for(Int_t i1=0;i1<nPrim;i1++) | |
12759 | { | |
12760 | aftsTrack=anEvent->GetTrack(i1); | |
3b552efe | 12761 | // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) |
12762 | if(typeFlag==1) // this is diff flow of POIs | |
489d5531 | 12763 | { |
12764 | if(ptOrEta == "Pt") | |
12765 | { | |
12766 | if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
12767 | } else if (ptOrEta == "Eta") | |
12768 | { | |
12769 | if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
3b552efe | 12770 | } |
12771 | } else // this is diff flow of RPs | |
12772 | { | |
489d5531 | 12773 | if(ptOrEta == "Pt") |
12774 | { | |
12775 | if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()<upperPtEtaEdge[pe]) && (aftsTrack->InRPSelection())))continue; | |
12776 | } else if (ptOrEta == "Eta") | |
12777 | { | |
12778 | if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()<upperPtEtaEdge[pe]) && (aftsTrack->InRPSelection())))continue; | |
3b552efe | 12779 | } |
489d5531 | 12780 | } |
12781 | psi1=aftsTrack->Phi(); | |
12782 | for(Int_t i2=0;i2<nPrim;i2++) | |
12783 | { | |
12784 | if(i2==i1) continue; | |
12785 | aftsTrack=anEvent->GetTrack(i2); | |
12786 | // RP condition (!(first) particle in the correlator must be RP): | |
12787 | if(!(aftsTrack->InRPSelection())) continue; | |
46b94261 | 12788 | phi2=aftsTrack->Phi(); |
489d5531 | 12789 | if(fUsePhiWeights && fPhiWeights) wPhi2 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi2*fnBinsPhi/TMath::TwoPi()))); |
12790 | // sin terms: | |
12791 | fDiffFlowDirectCorrectionTermsForNUA[t][pe][0][1]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,sin(n*(psi1+phi2)),wPhi2); // <<w2 sin(n*(psi1+phi2))>> | |
12792 | // cos terms: | |
12793 | fDiffFlowDirectCorrectionTermsForNUA[t][pe][1][1]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(n*(psi1+phi2)),wPhi2); // <<w2 cos(n*(psi1+phi2))>> | |
12794 | }//end of for(Int_t i2=0;i2<nPrim;i2++) | |
12795 | }//end of for(Int_t i1=0;i1<nPrim;i1++) | |
12796 | ||
12797 | // 3'-particle correction terms: | |
12798 | for(Int_t i1=0;i1<nPrim;i1++) | |
12799 | { | |
12800 | aftsTrack=anEvent->GetTrack(i1); | |
3b552efe | 12801 | // POI condition (first particle in the correlator must be POI): // to be improved (this can be implemented much better) |
12802 | if(typeFlag==1) // this is diff flow of POIs | |
489d5531 | 12803 | { |
12804 | if(ptOrEta == "Pt") | |
12805 | { | |
12806 | if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
12807 | } else if (ptOrEta == "Eta") | |
12808 | { | |
12809 | if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()<upperPtEtaEdge[pe]) && (aftsTrack->InPOISelection())))continue; | |
3b552efe | 12810 | } |
12811 | } else // this is diff flow of RPs | |
12812 | { | |
489d5531 | 12813 | if(ptOrEta == "Pt") |
12814 | { | |
12815 | if(!((aftsTrack->Pt()>=lowerPtEtaEdge[pe] && aftsTrack->Pt()<upperPtEtaEdge[pe]) && (aftsTrack->InRPSelection())))continue; | |
12816 | } else if (ptOrEta == "Eta") | |
12817 | { | |
12818 | if(!((aftsTrack->Eta()>=lowerPtEtaEdge[pe] && aftsTrack->Eta()<upperPtEtaEdge[pe]) && (aftsTrack->InRPSelection())))continue; | |
3b552efe | 12819 | } |
489d5531 | 12820 | } |
12821 | psi1=aftsTrack->Phi(); | |
12822 | for(Int_t i2=0;i2<nPrim;i2++) | |
12823 | { | |
12824 | if(i2==i1) continue; | |
12825 | aftsTrack=anEvent->GetTrack(i2); | |
12826 | // RP condition (!(first) particle in the correlator must be RP): | |
12827 | if(!(aftsTrack->InRPSelection())) continue; | |
12828 | phi2=aftsTrack->Phi(); | |
12829 | if(fUsePhiWeights && fPhiWeights) wPhi2 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi2*fnBinsPhi/TMath::TwoPi()))); | |
12830 | for(Int_t i3=0;i3<nPrim;i3++) | |
12831 | { | |
12832 | if(i3==i1||i3==i2) continue; | |
12833 | aftsTrack=anEvent->GetTrack(i3); | |
12834 | // RP condition (!(first) particle in the correlator must be RP): | |
12835 | if(!(aftsTrack->InRPSelection())) continue; | |
12836 | phi3=aftsTrack->Phi(); | |
12837 | if(fUsePhiWeights && fPhiWeights) wPhi3 = fPhiWeights->GetBinContent(1+(Int_t)(TMath::Floor(phi3*fnBinsPhi/TMath::TwoPi()))); | |
12838 | // sin terms: | |
12839 | fDiffFlowDirectCorrectionTermsForNUA[t][pe][0][2]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,sin(n*(psi1+phi2-phi3)),wPhi2*wPhi3); // <<wPhi2*wPhi3 sin(n*(psi1+phi2-phi3))>> | |
12840 | fDiffFlowDirectCorrectionTermsForNUA[t][pe][0][3]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,sin(n*(psi1-phi2-phi3)),wPhi2*wPhi3); // <<wPhi2*wPhi3 sin(n*(psi1-phi2-phi3))>> | |
12841 | // cos terms: | |
12842 | fDiffFlowDirectCorrectionTermsForNUA[t][pe][1][2]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(n*(psi1+phi2-phi3)),wPhi2*wPhi3); // <<wPhi2*wPhi3 cos(n*(psi1+phi2-phi3))>> | |
12843 | fDiffFlowDirectCorrectionTermsForNUA[t][pe][1][3]->Fill(lowerPtEtaEdge[pe]+binWidthPtEta[pe]/2.,cos(n*(psi1-phi2-phi3)),wPhi2*wPhi3); // <<wPhi2*wPhi3 cos(n*(psi1-phi2-phi3))>> | |
12844 | }//end of for(Int_t i3=0;i3<nPrim;i3++) | |
12845 | }//end of for(Int_t i2=0;i2<nPrim;i2++) | |
46b94261 | 12846 | }//end of for(Int_t i1=0;i1<nPrim;i1++) |
489d5531 | 12847 | |
12848 | } // end of void AliFlowAnalysisWithQCumulants::EvaluateDiffFlowCorrectionTermsForNUAWithNestedLoopsUsingParticleWeights(AliFlowEventSimple* anEvent, TString type, TString ptOrEta) | |
12849 | ||
2001bc3a | 12850 | //================================================================================================================================ |
12851 | ||
b3dacf6b | 12852 | void AliFlowAnalysisWithQCumulants::CheckPointersUsedInFinish() |
12853 | { | |
12854 | // Check all pointers used in method Finish(). | |
12855 | ||
b77b6434 | 12856 | if(!fAvMultiplicity) |
12857 | { | |
12858 | cout<<endl; | |
12859 | cout<<" WARNING (QC): fAvMultiplicity is NULL in CheckPointersUsedInFinish() !!!!"<<endl; | |
12860 | cout<<endl; | |
12861 | exit(0); | |
12862 | } | |
b3dacf6b | 12863 | if(!fIntFlowCorrelationsPro) |
12864 | { | |
12865 | cout<<endl; | |
12866 | cout<<" WARNING (QC): fIntFlowCorrelationsPro is NULL in CheckPointersUsedInFinish() !!!!"<<endl; | |
12867 | cout<<endl; | |
12868 | exit(0); | |
12869 | } | |
b40a910e | 12870 | if(!fIntFlowSquaredCorrelationsPro) |
12871 | { | |
12872 | cout<<endl; | |
12873 | cout<<" WARNING (QC): fIntFlowSquaredCorrelationsPro is NULL in CheckPointersUsedInFinish() !!!!"<<endl; | |
12874 | cout<<endl; | |
12875 | exit(0); | |
12876 | } | |
b3dacf6b | 12877 | if(!fIntFlowCorrelationsHist) |
12878 | { | |
12879 | cout<<endl; | |
12880 | cout<<" WARNING (QC): fIntFlowCorrelationsHist is NULL in CheckPointersUsedInFinish() !!!!"<<endl; | |
12881 | cout<<endl; | |
12882 | exit(0); | |
12883 | } | |
b77b6434 | 12884 | if((fUsePhiWeights||fUsePtWeights||fUseEtaWeights) && !fIntFlowExtraCorrelationsPro) |
12885 | { | |
12886 | cout<<endl; | |
12887 | cout<<" WARNING (QC): fIntFlowExtraCorrelationsPro is NULL in CheckPointersUsedInFinish() !!!!"<<endl; | |
12888 | cout<<endl; | |
12889 | exit(0); | |
12890 | } | |
b3dacf6b | 12891 | for(Int_t power=0;power<2;power++) |
12892 | { | |
12893 | if(!fIntFlowSumOfEventWeights[power]) | |
12894 | { | |
12895 | cout<<endl; | |
12896 | cout<<Form(" WARNING (QC): fIntFlowSumOfEventWeights[%d] is NULL in CheckPointersUsedInFinish() !!!!",power)<<endl; | |
12897 | cout<<endl; | |
12898 | exit(0); | |
12899 | } | |
12900 | } // end of for(Int_t power=0;power<2;power++) | |
12901 | if(!fIntFlowProductOfCorrelationsPro) | |
12902 | { | |
12903 | cout<<endl; | |
12904 | cout<<" WARNING (QC): fIntFlowProductOfCorrelationsPro is NULL in CheckPointersUsedInFinish() !!!!"<<endl; | |
12905 | cout<<endl; | |
12906 | exit(0); | |
12907 | } | |
12908 | if(!fIntFlowSumOfProductOfEventWeights) | |
12909 | { | |
12910 | cout<<endl; | |
12911 | cout<<" WARNING (QC): fIntFlowSumOfProductOfEventWeights is NULL in CheckPointersUsedInFinish() !!!!"<<endl; | |
12912 | cout<<endl; | |
12913 | exit(0); | |
12914 | } | |
12915 | if(!fIntFlowCovariances) | |
12916 | { | |
12917 | cout<<endl; | |
12918 | cout<<" WARNING (QC): fIntFlowCovariances is NULL in CheckPointersUsedInFinish() !!!!"<<endl; | |
12919 | cout<<endl; | |
12920 | exit(0); | |
12921 | } | |
12922 | if(!fIntFlowQcumulants) | |
12923 | { | |
12924 | cout<<endl; | |
12925 | cout<<" WARNING (QC): fIntFlowQcumulants is NULL in CheckPointersUsedInFinish() !!!!"<<endl; | |
12926 | cout<<endl; | |
12927 | exit(0); | |
12928 | } | |
0dd3b008 | 12929 | if(!fIntFlow) |
12930 | { | |
12931 | cout<<endl; | |
12932 | cout<<" WARNING (QC): fIntFlow is NULL in CheckPointersUsedInFinish() !!!!"<<endl; | |
12933 | cout<<endl; | |
12934 | exit(0); | |
12935 | } | |
12936 | if(!fCommonHists) | |
12937 | { | |
12938 | cout<<endl; | |
12939 | cout<<" WARNING (QC): fCommonHists is NULL in CheckPointersUsedInFinish() !!!!"<<endl; | |
12940 | cout<<endl; | |
12941 | exit(0); | |
12942 | } | |
12943 | if(!(fCommonHistsResults2nd && fCommonHistsResults4th && fCommonHistsResults6th && fCommonHistsResults8th)) | |
12944 | { | |
12945 | cout<<endl; | |
12946 | cout<<" WARNING (QC): fCommonHistsResults2nd && fCommonHistsResults4th && fCommonHistsResults6th"<<endl; | |
12947 | cout<<" && fCommonHistsResults8th is NULL in CheckPointersUsedInFinish() !!!!"<<endl; | |
12948 | cout<<endl; | |
12949 | exit(0); | |
12950 | } | |
b3dacf6b | 12951 | |
b92ea2b9 | 12952 | // NUA stuff: |
12953 | for(Int_t sc=0;sc<2;sc++) // sin/cos | |
12954 | { | |
12955 | if(!fIntFlowCorrectionTermsForNUAPro[sc]) | |
12956 | { | |
12957 | cout<<endl; | |
12958 | cout<<Form(" WARNING (QC): fIntFlowCorrectionTermsForNUAPro[%d] is NULL in CheckPointersUsedInFinish() !!!!",sc)<<endl; | |
12959 | cout<<endl; | |
12960 | exit(0); | |
12961 | } | |
12962 | if(!fIntFlowCorrectionTermsForNUAHist[sc]) | |
12963 | { | |
12964 | cout<<endl; | |
12965 | cout<<Form(" WARNING (QC): fIntFlowCorrectionTermsForNUAHist[%d] is NULL in CheckPointersUsedInFinish() !!!!",sc)<<endl; | |
12966 | cout<<endl; | |
12967 | exit(0); | |
12968 | } | |
12969 | for(Int_t lq=0;lq<2;lq++) // linear/quadratic | |
12970 | { | |
12971 | if(!fIntFlowSumOfEventWeightsNUA[sc][lq]) | |
12972 | { | |
12973 | cout<<endl; | |
12974 | cout<<Form(" WARNING (QC): fIntFlowSumOfEventWeightsNUA[%d][%d] is NULL in CheckPointersUsedInFinish() !!!!",sc,lq)<<endl; | |
12975 | cout<<endl; | |
12976 | exit(0); | |
12977 | } | |
12978 | } // end of for(Int_t lq=0;lq<2;lq++) // linear/quadratic | |
12979 | } // end of for(Int_t power=0;power<2;power++) | |
12980 | if(!fIntFlowProductOfCorrectionTermsForNUAPro) | |
12981 | { | |
12982 | cout<<endl; | |
12983 | cout<<" WARNING (QC): fIntFlowProductOfCorrectionTermsForNUAPro is NULL in CheckPointersUsedInFinish() !!!!"<<endl; | |
12984 | cout<<endl; | |
12985 | exit(0); | |
12986 | } | |
12987 | if(!fIntFlowSumOfProductOfEventWeightsNUA) | |
12988 | { | |
12989 | cout<<endl; | |
12990 | cout<<" WARNING (QC): fIntFlowSumOfProductOfEventWeightsNUA is NULL in CheckPointersUsedInFinish() !!!!"<<endl; | |
12991 | cout<<endl; | |
12992 | exit(0); | |
12993 | } | |
12994 | if(!fIntFlowCovariancesNUA) | |
12995 | { | |
12996 | cout<<endl; | |
12997 | cout<<" WARNING (QC): fIntFlowCovariancesNUA is NULL in CheckPointersUsedInFinish() !!!!"<<endl; | |
12998 | cout<<endl; | |
12999 | exit(0); | |
13000 | } | |
13001 | if(!fIntFlowQcumulantsErrorSquaredRatio) | |
13002 | { | |
13003 | cout<<endl; | |
13004 | cout<<" WARNING (QC): fIntFlowQcumulantsErrorSquaredRatio is NULL in CheckPointersUsedInFinish() !!!!"<<endl; | |
13005 | cout<<endl; | |
13006 | exit(0); | |
13007 | } | |
13008 | if(!fIntFlowDetectorBias) | |
13009 | { | |
13010 | cout<<endl; | |
13011 | cout<<" WARNING (QC): fIntFlowDetectorBias is NULL in CheckPointersUsedInFinish() !!!!"<<endl; | |
13012 | cout<<endl; | |
13013 | exit(0); | |
13014 | } | |
13015 | ||
b3dacf6b | 13016 | // Versus multiplicity: |
13017 | if(!fCalculateCumulantsVsM){return;} | |
b77b6434 | 13018 | for(Int_t co=0;co<=3;co++) // cumulant order |
b3dacf6b | 13019 | { |
b77b6434 | 13020 | if(!fIntFlowQcumulantsVsM[co]) |
b3dacf6b | 13021 | { |
13022 | cout<<endl; | |
b77b6434 | 13023 | cout<<Form(" WARNING (QC): fIntFlowQcumulantsVsM[%d] is NULL in CheckPointersUsedInFinish() !!!!",co)<<endl; |
b3dacf6b | 13024 | cout<<endl; |
13025 | exit(0); | |
13026 | } | |
b77b6434 | 13027 | if(!fIntFlowVsM[co]) |
b3dacf6b | 13028 | { |
13029 | cout<<endl; | |
b77b6434 | 13030 | cout<<Form(" WARNING (QC): fIntFlowVsM[%d] is NULL in CheckPointersUsedInFinish() !!!!",co)<<endl; |
13031 | cout<<endl; | |
13032 | exit(0); | |
13033 | } | |
13034 | if(!fIntFlowDetectorBiasVsM[co]) | |
13035 | { | |
13036 | cout<<endl; | |
13037 | cout<<Form(" WARNING (QC): fIntFlowDetectorBiasVsM[%d] is NULL in CheckPointersUsedInFinish() !!!!",co)<<endl; | |
13038 | cout<<endl; | |
13039 | exit(0); | |
13040 | } | |
13041 | } // end of for(Int_t c0=0;c0<=3;c0++) // cumulant order | |
13042 | for(Int_t ci=0;ci<=3;ci++) // correlation index | |
13043 | { | |
13044 | if(!fIntFlowCorrelationsVsMPro[ci]) | |
13045 | { | |
13046 | cout<<endl; | |
13047 | cout<<Form(" WARNING (QC): fIntFlowCorrelationsVsMPro[%d] is NULL in CheckPointersUsedInFinish() !!!!",ci)<<endl; | |
b3dacf6b | 13048 | cout<<endl; |
13049 | exit(0); | |
13050 | } | |
b40a910e | 13051 | if(!fIntFlowSquaredCorrelationsVsMPro[ci]) |
13052 | { | |
13053 | cout<<endl; | |
13054 | cout<<Form(" WARNING (QC): fIntFlowSquaredCorrelationsVsMPro[%d] is NULL in CheckPointersUsedInFinish() !!!!",ci)<<endl; | |
13055 | cout<<endl; | |
13056 | exit(0); | |
13057 | } | |
b77b6434 | 13058 | if(!fIntFlowCorrelationsVsMHist[ci]) |
b92ea2b9 | 13059 | { |
13060 | cout<<endl; | |
b77b6434 | 13061 | cout<<Form(" WARNING (QC): fIntFlowCorrelationsVsMHist[%d] is NULL in CheckPointersUsedInFinish() !!!!",ci)<<endl; |
b92ea2b9 | 13062 | cout<<endl; |
13063 | exit(0); | |
13064 | } | |
b3dacf6b | 13065 | for(Int_t power=0;power<2;power++) |
13066 | { | |
13067 | if(!fIntFlowSumOfEventWeightsVsM[ci][power]) | |
13068 | { | |
13069 | cout<<endl; | |
13070 | cout<<Form(" WARNING (QC): fIntFlowSumOfEventWeightsVsM[%d][%d] is NULL in CheckPointersUsedInFinish() !!!!",ci,power)<<endl; | |
13071 | cout<<endl; | |
13072 | exit(0); | |
13073 | } | |
13074 | } // end of for(Int_t power=0;power<2;power++) | |
13075 | } // end of for(Int_t ci=0;ci<=3;ci++) // correlation index | |
13076 | for(Int_t i=0;i<6;i++) | |
13077 | { | |
13078 | if(!fIntFlowProductOfCorrelationsVsMPro[i]) | |
13079 | { | |
13080 | cout<<endl; | |
13081 | cout<<Form(" WARNING (QC): fIntFlowProductOfCorrelationsVsMPro[%d] is NULL in CheckPointersUsedInFinish() !!!!",i)<<endl; | |
13082 | cout<<endl; | |
13083 | exit(0); | |
13084 | } | |
13085 | if(!fIntFlowSumOfProductOfEventWeightsVsM[i]) | |
13086 | { | |
13087 | cout<<endl; | |
13088 | cout<<Form(" WARNING (QC): fIntFlowSumOfProductOfEventWeightsVsM[%d] is NULL in CheckPointersUsedInFinish() !!!!",i)<<endl; | |
13089 | cout<<endl; | |
13090 | exit(0); | |
13091 | } | |
13092 | if(!fIntFlowCovariancesVsM[i]) | |
13093 | { | |
13094 | cout<<endl; | |
13095 | cout<<Form(" WARNING (QC): fIntFlowCovariancesVsM[%d] is NULL in CheckPointersUsedInFinish() !!!!",i)<<endl; | |
13096 | cout<<endl; | |
13097 | exit(0); | |
13098 | } | |
13099 | } // end of for(Int_t i=0;i<6;i++) | |
13100 | if(!fIntFlowRebinnedInM) | |
13101 | { | |
13102 | cout<<endl; | |
13103 | cout<<" WARNING (QC): fIntFlowRebinnedInM is NULL in CheckPointersUsedInFinish() !!!!"<<endl; | |
13104 | cout<<endl; | |
13105 | exit(0); | |
13106 | } | |
13107 | if(!fIntFlowQcumulantsRebinnedInM) | |
13108 | { | |
13109 | cout<<endl; | |
13110 | cout<<" WARNING (QC): fIntFlowQcumulantsRebinnedInM is NULL in CheckPointersUsedInFinish() !!!!"<<endl; | |
13111 | cout<<endl; | |
13112 | exit(0); | |
13113 | } | |
13114 | ||
13115 | } // end of void AliFlowAnalysisWithQCumulants::CheckPointersUsedInFinish() | |
13116 | ||
13117 | //================================================================================================================================ | |
13118 | ||
13119 | void AliFlowAnalysisWithQCumulants::CheckPointersUsedInMake() | |
13120 | { | |
13121 | // Check all pointers used in method Make(). | |
13122 | ||
b77b6434 | 13123 | if(!fAvMultiplicity) |
13124 | { | |
13125 | cout<<endl; | |
13126 | cout<<" WARNING (QC): fAvMultiplicity is NULL in CheckPointersUsedInMake() !!!!"<<endl; | |
13127 | cout<<endl; | |
13128 | exit(0); | |
13129 | } | |
13130 | if((fUsePhiWeights||fUsePtWeights||fUseEtaWeights) && !fIntFlowExtraCorrelationsPro) | |
13131 | { | |
13132 | cout<<endl; | |
13133 | cout<<" WARNING (QC): fIntFlowExtraCorrelationsPro is NULL in CheckPointersUsedInMake() !!!!"<<endl; | |
13134 | cout<<endl; | |
13135 | exit(0); | |
13136 | } | |
b3dacf6b | 13137 | |
13138 | } // end of void AliFlowAnalysisWithQCumulants::CheckPointersUsedInMake() | |
13139 | ||
57340a27 | 13140 |