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a75aacd6 | 1 | /************************************************************************** |
2 | * Copyright(c) 1998-1999, 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 | /* $Id: AliUEHistograms.cxx 20164 2007-08-14 15:31:50Z morsch $ */ | |
17 | ||
18 | // | |
19 | // | |
20 | // encapsulates several AliUEHist objects for a full UE analysis plus additional control histograms | |
21 | // | |
22 | // | |
23 | // Author: Jan Fiete Grosse-Oetringhaus, Sara Vallero | |
24 | ||
25 | #include "AliUEHistograms.h" | |
26 | ||
27 | #include "AliCFContainer.h" | |
28 | #include "AliVParticle.h" | |
2a910c25 | 29 | #include "AliAODTrack.h" |
a75aacd6 | 30 | |
31 | #include "TList.h" | |
32 | #include "TH2F.h" | |
33 | #include "TH1F.h" | |
34 | #include "TH3F.h" | |
35 | #include "TMath.h" | |
b0d56b29 | 36 | #include "TLorentzVector.h" |
a75aacd6 | 37 | |
38 | ClassImp(AliUEHistograms) | |
39 | ||
bf58cbde | 40 | const Int_t AliUEHistograms::fgkUEHists = 3; |
41 | ||
e0331fd9 | 42 | AliUEHistograms::AliUEHistograms(const char* name, const char* histograms) : |
43 | TNamed(name, name), | |
a75aacd6 | 44 | fNumberDensitypT(0), |
45 | fSumpT(0), | |
46 | fNumberDensityPhi(0), | |
47 | fCorrelationpT(0), | |
48 | fCorrelationEta(0), | |
49 | fCorrelationPhi(0), | |
50 | fCorrelationR(0), | |
51 | fCorrelationLeading2Phi(0), | |
52 | fCorrelationMultiplicity(0), | |
53 | fEventCount(0), | |
54 | fEventCountDifferential(0), | |
bf58cbde | 55 | fVertexContributors(0), |
c7245604 | 56 | fCentralityDistribution(0), |
447d47d8 | 57 | fCentralityCorrelation(0), |
2a910c25 | 58 | fITSClusterMap(0), |
85bfac17 | 59 | fSelectCharge(0), |
d38fa455 | 60 | fTriggerRestrictEta(-1), |
b0d56b29 | 61 | fCutConversions(kFALSE), |
62 | fCutResonances(kFALSE), | |
85bfac17 | 63 | fRunNumber(0) |
a75aacd6 | 64 | { |
65 | // Constructor | |
bf58cbde | 66 | // |
67 | // the string histograms defines which histograms are created: | |
68 | // 1 = NumberDensitypT | |
69 | // 2 = SumpT | |
70 | // 3 = NumberDensityPhi | |
71 | // 4 = NumberDensityPhiCentrality (other multiplicity for Pb) | |
72 | ||
670e1d49 | 73 | fTwoTrackDistancePt[0] = 0; |
74 | fTwoTrackDistancePt[1] = 0; | |
1bba939a | 75 | |
bf58cbde | 76 | TString histogramsStr(histograms); |
77 | ||
78 | if (histogramsStr.Contains("1")) | |
79 | fNumberDensitypT = new AliUEHist("NumberDensitypT"); | |
80 | if (histogramsStr.Contains("2")) | |
81 | fSumpT = new AliUEHist("SumpT"); | |
a75aacd6 | 82 | |
bf58cbde | 83 | if (histogramsStr.Contains("3")) |
84 | fNumberDensityPhi = new AliUEHist("NumberDensityPhi"); | |
85 | else if (histogramsStr.Contains("4")) | |
86 | fNumberDensityPhi = new AliUEHist("NumberDensityPhiCentrality"); | |
44af28f9 | 87 | else if (histogramsStr.Contains("5")) |
88 | fNumberDensityPhi = new AliUEHist("NumberDensityPhiCentralityVtx"); | |
a75aacd6 | 89 | |
90 | // do not add this hists to the directory | |
91 | Bool_t oldStatus = TH1::AddDirectoryStatus(); | |
92 | TH1::AddDirectory(kFALSE); | |
93 | ||
44af28f9 | 94 | if (!histogramsStr.Contains("4") && !histogramsStr.Contains("5")) |
c7245604 | 95 | { |
96 | fCorrelationpT = new TH2F("fCorrelationpT", ";p_{T,lead} (MC);p_{T,lead} (RECO)", 200, 0, 50, 200, 0, 50); | |
2a910c25 | 97 | fCorrelationEta = new TH2F("fCorrelationEta", ";#eta_{lead} (MC);#eta_{T,lead} (RECO)", 200, -1, 1, 200, -1, 1); |
a4a4d54e | 98 | fCorrelationPhi = new TH2F("fCorrelationPhi", ";#varphi_{lead} (MC);#varphi_{T,lead} (RECO)", 200, 0, TMath::TwoPi(), 200, 0, TMath::TwoPi()); |
c7245604 | 99 | } |
100 | else | |
101 | { | |
2a910c25 | 102 | fCorrelationpT = new TH2F("fCorrelationpT", ";Centrality;p_{T} (RECO)", 100, 0, 100.001, 200, 0, 50); |
103 | fCorrelationEta = new TH2F("fCorrelationEta", ";Centrality;#eta (RECO)", 100, 0, 100.001, 200, -1, 1); | |
a4a4d54e | 104 | fCorrelationPhi = new TH2F("fCorrelationPhi", ";Centrality;#varphi (RECO)", 100, 0, 100.001, 200, 0, TMath::TwoPi()); |
c7245604 | 105 | } |
106 | ||
a75aacd6 | 107 | fCorrelationR = new TH2F("fCorrelationR", ";R;p_{T,lead} (MC)", 200, 0, 2, 200, 0, 50); |
a4a4d54e | 108 | fCorrelationLeading2Phi = new TH2F("fCorrelationLeading2Phi", ";#Delta #varphi;p_{T,lead} (MC)", 200, -TMath::Pi(), TMath::Pi(), 200, 0, 50); |
a75aacd6 | 109 | fCorrelationMultiplicity = new TH2F("fCorrelationMultiplicity", ";MC tracks;Reco tracks", 100, -0.5, 99.5, 100, -0.5, 99.5); |
110 | ||
44af28f9 | 111 | if (!histogramsStr.Contains("4") && !histogramsStr.Contains("5")) |
2a910c25 | 112 | { |
113 | fEventCount = new TH2F("fEventCount", ";step;event type;count", AliUEHist::fgkCFSteps+2, -2.5, -0.5 + AliUEHist::fgkCFSteps, 3, -0.5, 2.5); | |
114 | fEventCount->GetYaxis()->SetBinLabel(1, "ND"); | |
115 | fEventCount->GetYaxis()->SetBinLabel(2, "SD"); | |
116 | fEventCount->GetYaxis()->SetBinLabel(3, "DD"); | |
117 | } | |
118 | else | |
119 | { | |
120 | fEventCount = new TH2F("fEventCount", ";step;centrality;count", AliUEHist::fgkCFSteps+2, -2.5, -0.5 + AliUEHist::fgkCFSteps, fNumberDensityPhi->GetEventHist()->GetNBins(1), fNumberDensityPhi->GetEventHist()->GetAxis(1, 0)->GetXbins()->GetArray()); | |
121 | } | |
a75aacd6 | 122 | |
123 | fEventCountDifferential = new TH3F("fEventCountDifferential", ";p_{T,lead};step;event type", 100, 0, 50, AliUEHist::fgkCFSteps, -0.5, -0.5 + AliUEHist::fgkCFSteps, 3, -0.5, 2.5); | |
124 | fEventCountDifferential->GetZaxis()->SetBinLabel(1, "ND"); | |
125 | fEventCountDifferential->GetZaxis()->SetBinLabel(2, "SD"); | |
126 | fEventCountDifferential->GetZaxis()->SetBinLabel(3, "DD"); | |
127 | ||
128 | fVertexContributors = new TH1F("fVertexContributors", ";contributors;count", 100, -0.5, 99.5); | |
129 | ||
664d6288 | 130 | if (fNumberDensityPhi) |
447d47d8 | 131 | { |
132 | fCentralityDistribution = new TH1F("fCentralityDistribution", ";centrality;count", fNumberDensityPhi->GetEventHist()->GetNBins(1), fNumberDensityPhi->GetEventHist()->GetAxis(1, 0)->GetXbins()->GetArray()); | |
133 | fCentralityCorrelation = new TH2F("fCentralityCorrelation", ";centrality;multiplicity", fNumberDensityPhi->GetEventHist()->GetNBins(1), fNumberDensityPhi->GetEventHist()->GetAxis(1, 0)->GetXbins()->GetArray(), 200, 0, 4000); | |
134 | } | |
bf58cbde | 135 | |
2a910c25 | 136 | fITSClusterMap = new TH3F("fITSClusterMap", "; its cluster map; centrality; pT", 256, -0.5, 255.5, 20, 0, 100.001, 100, 0, 20); |
137 | ||
a75aacd6 | 138 | TH1::AddDirectory(oldStatus); |
139 | } | |
140 | ||
d1c75d06 | 141 | //_____________________________________________________________________________ |
142 | AliUEHistograms::AliUEHistograms(const AliUEHistograms &c) : | |
e0331fd9 | 143 | TNamed(fName, fTitle), |
d1c75d06 | 144 | fNumberDensitypT(0), |
145 | fSumpT(0), | |
146 | fNumberDensityPhi(0), | |
147 | fCorrelationpT(0), | |
148 | fCorrelationEta(0), | |
149 | fCorrelationPhi(0), | |
150 | fCorrelationR(0), | |
151 | fCorrelationLeading2Phi(0), | |
152 | fCorrelationMultiplicity(0), | |
153 | fEventCount(0), | |
154 | fEventCountDifferential(0), | |
bf58cbde | 155 | fVertexContributors(0), |
c7245604 | 156 | fCentralityDistribution(0), |
447d47d8 | 157 | fCentralityCorrelation(0), |
2a910c25 | 158 | fITSClusterMap(0), |
85bfac17 | 159 | fSelectCharge(0), |
d38fa455 | 160 | fTriggerRestrictEta(-1), |
b0d56b29 | 161 | fCutConversions(kFALSE), |
162 | fCutResonances(kFALSE), | |
85bfac17 | 163 | fRunNumber(0) |
d1c75d06 | 164 | { |
165 | // | |
166 | // AliUEHistograms copy constructor | |
167 | // | |
168 | ||
670e1d49 | 169 | fTwoTrackDistancePt[0] = 0; |
170 | fTwoTrackDistancePt[1] = 0; | |
1bba939a | 171 | |
d1c75d06 | 172 | ((AliUEHistograms &) c).Copy(*this); |
173 | } | |
174 | ||
a75aacd6 | 175 | //____________________________________________________________________ |
176 | AliUEHistograms::~AliUEHistograms() | |
177 | { | |
178 | // Destructor | |
179 | ||
b0d56b29 | 180 | DeleteContainers(); |
181 | } | |
182 | ||
183 | void AliUEHistograms::DeleteContainers() | |
184 | { | |
a75aacd6 | 185 | if (fNumberDensitypT) |
186 | { | |
187 | delete fNumberDensitypT; | |
188 | fNumberDensitypT = 0; | |
189 | } | |
190 | ||
191 | if (fSumpT) | |
192 | { | |
193 | delete fSumpT; | |
194 | fSumpT = 0; | |
195 | } | |
196 | ||
197 | if (fNumberDensityPhi) | |
198 | { | |
199 | delete fNumberDensityPhi; | |
200 | fNumberDensityPhi = 0; | |
201 | } | |
202 | ||
203 | if (fCorrelationpT) | |
204 | { | |
205 | delete fCorrelationpT; | |
206 | fCorrelationpT = 0; | |
207 | } | |
208 | ||
209 | if (fCorrelationEta) | |
210 | { | |
211 | delete fCorrelationEta; | |
212 | fCorrelationEta = 0; | |
213 | } | |
214 | ||
215 | if (fCorrelationPhi) | |
216 | { | |
217 | delete fCorrelationPhi; | |
218 | fCorrelationPhi = 0; | |
219 | } | |
220 | ||
221 | if (fCorrelationR) | |
222 | { | |
223 | delete fCorrelationR; | |
224 | fCorrelationR = 0; | |
225 | } | |
226 | ||
227 | if (fCorrelationLeading2Phi) | |
228 | { | |
229 | delete fCorrelationLeading2Phi; | |
230 | fCorrelationLeading2Phi = 0; | |
231 | } | |
232 | ||
233 | if (fCorrelationMultiplicity) | |
234 | { | |
235 | delete fCorrelationMultiplicity; | |
236 | fCorrelationMultiplicity = 0; | |
237 | } | |
238 | ||
239 | if (fEventCount) | |
240 | { | |
241 | delete fEventCount; | |
242 | fEventCount = 0; | |
243 | } | |
244 | ||
245 | if (fEventCountDifferential) | |
246 | { | |
247 | delete fEventCountDifferential; | |
248 | fEventCountDifferential = 0; | |
249 | } | |
250 | ||
251 | if (fVertexContributors) | |
252 | { | |
253 | delete fVertexContributors; | |
254 | fVertexContributors = 0; | |
255 | } | |
bf58cbde | 256 | |
257 | if (fCentralityDistribution) | |
258 | { | |
259 | delete fCentralityDistribution; | |
260 | fCentralityDistribution = 0; | |
261 | } | |
2a910c25 | 262 | |
447d47d8 | 263 | if (fCentralityCorrelation) |
264 | { | |
265 | delete fCentralityCorrelation; | |
266 | fCentralityCorrelation = 0; | |
267 | } | |
268 | ||
2a910c25 | 269 | if (fITSClusterMap) |
270 | { | |
271 | delete fITSClusterMap; | |
272 | fITSClusterMap = 0; | |
273 | } | |
1bba939a | 274 | |
275 | for (Int_t i=0; i<2; i++) | |
670e1d49 | 276 | if (fTwoTrackDistancePt[i]) |
1bba939a | 277 | { |
670e1d49 | 278 | delete fTwoTrackDistancePt[i]; |
279 | fTwoTrackDistancePt[i] = 0; | |
1bba939a | 280 | } |
a75aacd6 | 281 | } |
282 | ||
ada1a03f | 283 | AliUEHist* AliUEHistograms::GetUEHist(Int_t id) |
284 | { | |
285 | // returns AliUEHist object, useful for loops | |
286 | ||
287 | switch (id) | |
288 | { | |
289 | case 0: return fNumberDensitypT; break; | |
290 | case 1: return fSumpT; break; | |
291 | case 2: return fNumberDensityPhi; break; | |
292 | } | |
293 | ||
294 | return 0; | |
295 | } | |
296 | ||
a75aacd6 | 297 | //____________________________________________________________________ |
298 | Int_t AliUEHistograms::CountParticles(TList* list, Float_t ptMin) | |
299 | { | |
300 | // counts the number of particles in the list with a pT above ptMin | |
301 | // TODO eta cut needed here? | |
302 | ||
303 | Int_t count = 0; | |
304 | for (Int_t j=0; j<list->GetEntries(); j++) | |
305 | if (((AliVParticle*) list->At(j))->Pt() > ptMin) | |
306 | count++; | |
307 | ||
308 | return count; | |
309 | } | |
310 | ||
311 | //____________________________________________________________________ | |
85bfac17 | 312 | void AliUEHistograms::Fill(Int_t eventType, Float_t zVtx, AliUEHist::CFStep step, AliVParticle* leading, TList* toward, TList* away, TList* min, TList* max) |
a75aacd6 | 313 | { |
314 | // fills the UE event histograms | |
315 | // | |
316 | // this function needs the leading (track or jet or ...) and four lists of AliVParticles which contain the particles/tracks to be filled in the four regions | |
317 | ||
318 | // if leading is not set, just fill event statistics | |
319 | if (leading) | |
320 | { | |
321 | Int_t multiplicity = 0; | |
322 | ||
323 | // TODO configurable? | |
324 | Float_t ptMin = 0.15; | |
325 | if (leading->Pt() > ptMin) | |
326 | multiplicity++; | |
327 | ||
328 | multiplicity += CountParticles(toward, ptMin); | |
329 | multiplicity += CountParticles(away, ptMin); | |
330 | multiplicity += CountParticles(min, ptMin); | |
331 | multiplicity += CountParticles(max, ptMin); | |
332 | ||
85bfac17 | 333 | FillRegion(AliUEHist::kToward, zVtx, step, leading, toward, multiplicity); |
334 | FillRegion(AliUEHist::kAway, zVtx, step, leading, away, multiplicity); | |
335 | FillRegion(AliUEHist::kMin, zVtx, step, leading, min, multiplicity); | |
336 | FillRegion(AliUEHist::kMax, zVtx, step, leading, max, multiplicity); | |
b1831bcb | 337 | |
85bfac17 | 338 | Double_t vars[3]; |
a75aacd6 | 339 | vars[0] = leading->Pt(); |
340 | vars[1] = multiplicity; | |
85bfac17 | 341 | vars[2] = zVtx; |
bf58cbde | 342 | for (Int_t i=0; i<fgkUEHists; i++) |
343 | if (GetUEHist(i)) | |
344 | GetUEHist(i)->GetEventHist()->Fill(vars, step); | |
a75aacd6 | 345 | |
346 | fEventCountDifferential->Fill(leading->Pt(), step, eventType); | |
347 | } | |
348 | ||
349 | FillEvent(eventType, step); | |
350 | } | |
351 | ||
352 | //____________________________________________________________________ | |
85bfac17 | 353 | void AliUEHistograms::FillRegion(AliUEHist::Region region, Float_t zVtx, AliUEHist::CFStep step, AliVParticle* leading, TList* list, Int_t multiplicity) |
a75aacd6 | 354 | { |
355 | // loops over AliVParticles in list and fills the given region at the given step | |
356 | // | |
357 | // See also Fill(...) | |
358 | ||
359 | for (Int_t i=0; i<list->GetEntries(); i++) | |
360 | { | |
361 | AliVParticle* particle = (AliVParticle*) list->At(i); | |
362 | ||
85bfac17 | 363 | Double_t vars[6]; |
a75aacd6 | 364 | vars[0] = particle->Eta(); |
365 | vars[1] = particle->Pt(); | |
366 | vars[2] = leading->Pt(); | |
367 | vars[3] = multiplicity; | |
368 | vars[4] = leading->Phi() - particle->Phi(); | |
2ac8dc5c | 369 | if (vars[4] > 1.5 * TMath::Pi()) |
370 | vars[4] -= TMath::TwoPi(); | |
371 | if (vars[4] < -0.5 * TMath::Pi()) | |
372 | vars[4] += TMath::TwoPi(); | |
85bfac17 | 373 | vars[5] = zVtx; |
374 | ||
bf58cbde | 375 | if (fNumberDensitypT) |
376 | fNumberDensitypT->GetTrackHist(region)->Fill(vars, step); | |
377 | ||
378 | if (fSumpT) | |
379 | fSumpT->GetTrackHist(region)->Fill(vars, step, particle->Pt()); | |
a75aacd6 | 380 | |
381 | // fill all in toward region (is anyway as function of delta phi!) | |
bf58cbde | 382 | if (fNumberDensityPhi) |
383 | fNumberDensityPhi->GetTrackHist(AliUEHist::kToward)->Fill(vars, step); | |
a75aacd6 | 384 | } |
385 | } | |
386 | ||
387 | //____________________________________________________________________ | |
388 | void AliUEHistograms::Fill(AliVParticle* leadingMC, AliVParticle* leadingReco) | |
389 | { | |
390 | // fills the correlation histograms | |
391 | ||
392 | if (leadingMC) | |
393 | { | |
394 | fCorrelationpT->Fill(leadingMC->Pt(), leadingReco->Pt()); | |
395 | if (leadingMC->Pt() > 0.5) | |
396 | { | |
397 | fCorrelationEta->Fill(leadingMC->Eta(), leadingReco->Eta()); | |
398 | fCorrelationPhi->Fill(leadingMC->Phi(), leadingReco->Phi()); | |
399 | } | |
400 | ||
401 | Float_t phiDiff = leadingMC->Phi() - leadingReco->Phi(); | |
402 | if (phiDiff > TMath::Pi()) | |
403 | phiDiff -= TMath::TwoPi(); | |
404 | if (phiDiff < -TMath::Pi()) | |
405 | phiDiff += TMath::TwoPi(); | |
406 | ||
407 | Float_t etaDiff = leadingMC->Eta() - leadingReco->Eta(); | |
408 | ||
409 | fCorrelationR->Fill(TMath::Sqrt(phiDiff * phiDiff + etaDiff * etaDiff), leadingMC->Pt()); | |
410 | fCorrelationLeading2Phi->Fill(phiDiff, leadingMC->Pt()); | |
411 | } | |
412 | else | |
413 | { | |
414 | fCorrelationpT->Fill(1.0, leadingReco->Pt()); | |
415 | if (leadingReco->Pt() > 0.5) | |
416 | { | |
417 | fCorrelationEta->Fill(0.0, leadingReco->Eta()); | |
418 | fCorrelationPhi->Fill(0.0, leadingReco->Phi()); | |
419 | } | |
420 | } | |
421 | } | |
bf58cbde | 422 | |
423 | //____________________________________________________________________ | |
eed401dc | 424 | void AliUEHistograms::FillCorrelations(Double_t centrality, Float_t zVtx, AliUEHist::CFStep step, TObjArray* particles, TObjArray* mixed, Float_t weight, Bool_t firstTime) |
bf58cbde | 425 | { |
426 | // fills the fNumberDensityPhi histogram | |
427 | // | |
428 | // this function need a list of AliVParticles which contain the particles/tracks to be filled | |
e0331fd9 | 429 | // |
430 | // if mixed is non-0, mixed events are filled, the trigger particle is from particles, the associated from mixed | |
c05ff6be | 431 | // if weight < 0, then the pt of the associated particle is filled as weight |
432 | ||
433 | Bool_t fillpT = kFALSE; | |
434 | if (weight < 0) | |
435 | fillpT = kTRUE; | |
bf58cbde | 436 | |
eed401dc | 437 | // Eta() is extremely time consuming, therefore cache it for the inner loop here: |
438 | TObjArray* input = (mixed) ? mixed : particles; | |
439 | TArrayF eta(input->GetEntriesFast()); | |
440 | for (Int_t i=0; i<input->GetEntriesFast(); i++) | |
441 | eta[i] = ((AliVParticle*) input->At(i))->Eta(); | |
442 | ||
bf58cbde | 443 | // if particles is not set, just fill event statistics |
444 | if (particles) | |
445 | { | |
eed401dc | 446 | Int_t jMax = particles->GetEntriesFast(); |
447 | if (mixed) | |
448 | jMax = mixed->GetEntriesFast(); | |
449 | ||
450 | for (Int_t i=0; i<particles->GetEntriesFast(); i++) | |
bf58cbde | 451 | { |
452 | AliVParticle* triggerParticle = (AliVParticle*) particles->At(i); | |
eed401dc | 453 | |
454 | // some optimization | |
455 | Float_t triggerEta = triggerParticle->Eta(); | |
e0331fd9 | 456 | |
c7245604 | 457 | if (!mixed) |
458 | { | |
459 | // QA | |
460 | fCorrelationpT->Fill(centrality, triggerParticle->Pt()); | |
eed401dc | 461 | fCorrelationEta->Fill(centrality, triggerEta); |
c7245604 | 462 | fCorrelationPhi->Fill(centrality, triggerParticle->Phi()); |
85bfac17 | 463 | /* if (dynamic_cast<AliAODTrack*>(triggerParticle)) |
464 | fITSClusterMap->Fill(((AliAODTrack*) triggerParticle)->GetITSClusterMap(), centrality, triggerParticle->Pt());*/ | |
c7245604 | 465 | } |
466 | ||
d38fa455 | 467 | if (fTriggerRestrictEta > 0 && TMath::Abs(triggerEta) > fTriggerRestrictEta) |
468 | continue; | |
469 | ||
e0331fd9 | 470 | for (Int_t j=0; j<jMax; j++) |
bf58cbde | 471 | { |
e0331fd9 | 472 | if (!mixed && i == j) |
bf58cbde | 473 | continue; |
474 | ||
e0331fd9 | 475 | AliVParticle* particle = 0; |
476 | if (!mixed) | |
477 | particle = (AliVParticle*) particles->At(j); | |
478 | else | |
479 | particle = (AliVParticle*) mixed->At(j); | |
bf58cbde | 480 | |
2a910c25 | 481 | // check if both particles point to the same element (does not occur for mixed events, but if subsets are mixed within the same event for cross-checks) |
482 | if (mixed && triggerParticle == particle) | |
483 | continue; | |
484 | ||
c7245604 | 485 | if (particle->Pt() > triggerParticle->Pt()) |
486 | continue; | |
487 | ||
488 | if (fSelectCharge > 0) | |
489 | { | |
490 | // skip like sign | |
491 | if (fSelectCharge == 1 && particle->Charge() * triggerParticle->Charge() > 0) | |
492 | continue; | |
493 | ||
494 | // skip unlike sign | |
495 | if (fSelectCharge == 2 && particle->Charge() * triggerParticle->Charge() < 0) | |
496 | continue; | |
497 | } | |
498 | ||
b0d56b29 | 499 | // conversions |
500 | if (fCutConversions && particle->Charge() * triggerParticle->Charge() < 0) | |
501 | { | |
502 | Float_t mass = GetInvMassSquared(triggerParticle->Pt(), triggerEta, triggerParticle->Phi(), particle->Pt(), eta[j], particle->Phi(), 0.510e-3); | |
503 | ||
504 | if (mass < 0.04*0.04) | |
505 | continue; | |
506 | } | |
507 | ||
508 | // K0s, rhos | |
509 | if (fCutResonances && particle->Charge() * triggerParticle->Charge() < 0) | |
510 | { | |
511 | Float_t mass = GetInvMassSquared(triggerParticle->Pt(), triggerEta, triggerParticle->Phi(), particle->Pt(), eta[j], particle->Phi(), 0.1396); | |
512 | ||
513 | if ((mass > 0.49*0.49 && mass < 0.51*0.51) || (mass > 0.765*0.765 && mass < 0.785*0.785)) | |
514 | continue; | |
515 | } | |
516 | ||
85bfac17 | 517 | Double_t vars[6]; |
eed401dc | 518 | vars[0] = triggerEta - eta[j]; |
bf58cbde | 519 | vars[1] = particle->Pt(); |
520 | vars[2] = triggerParticle->Pt(); | |
521 | vars[3] = centrality; | |
522 | vars[4] = triggerParticle->Phi() - particle->Phi(); | |
523 | if (vars[4] > 1.5 * TMath::Pi()) | |
524 | vars[4] -= TMath::TwoPi(); | |
525 | if (vars[4] < -0.5 * TMath::Pi()) | |
526 | vars[4] += TMath::TwoPi(); | |
85bfac17 | 527 | vars[5] = zVtx; |
c05ff6be | 528 | |
529 | if (fillpT) | |
530 | weight = particle->Pt(); | |
bf58cbde | 531 | |
c7245604 | 532 | // fill all in toward region and do not use the other regions |
533 | fNumberDensityPhi->GetTrackHist(AliUEHist::kToward)->Fill(vars, step, weight); | |
d38fa455 | 534 | |
535 | // Printf("%.2f %.2f --> %.2f", triggerEta, eta[j], vars[0]); | |
c7245604 | 536 | } |
bf58cbde | 537 | |
c7245604 | 538 | if (firstTime) |
539 | { | |
540 | // once per trigger particle | |
85bfac17 | 541 | Double_t vars[3]; |
c7245604 | 542 | vars[0] = triggerParticle->Pt(); |
543 | vars[1] = centrality; | |
85bfac17 | 544 | vars[2] = zVtx; |
c7245604 | 545 | fNumberDensityPhi->GetEventHist()->Fill(vars, step); |
c7245604 | 546 | } |
bf58cbde | 547 | } |
548 | } | |
549 | ||
550 | fCentralityDistribution->Fill(centrality); | |
447d47d8 | 551 | fCentralityCorrelation->Fill(centrality, particles->GetEntriesFast()); |
2a910c25 | 552 | FillEvent(centrality, step); |
bf58cbde | 553 | } |
a75aacd6 | 554 | |
b1831bcb | 555 | //____________________________________________________________________ |
c7245604 | 556 | void AliUEHistograms::FillTrackingEfficiency(TObjArray* mc, TObjArray* recoPrim, TObjArray* recoAll, Int_t particleType, Double_t centrality) |
b1831bcb | 557 | { |
558 | // fills the tracking efficiency objects | |
559 | // | |
560 | // mc: all primary MC particles | |
561 | // recoPrim: reconstructed primaries (again MC particles) | |
562 | // recoAll: reconstructed (again MC particles) | |
563 | // particleType is: 0 for pion, 1 for kaon, 2 for proton, 3 for others | |
564 | ||
565 | for (Int_t step=0; step<3; step++) | |
566 | { | |
567 | TObjArray* list = mc; | |
568 | if (step == 1) | |
569 | list = recoPrim; | |
570 | else if (step == 2) | |
571 | list = recoAll; | |
572 | ||
eed401dc | 573 | for (Int_t i=0; i<list->GetEntriesFast(); i++) |
b1831bcb | 574 | { |
575 | AliVParticle* particle = (AliVParticle*) list->At(i); | |
c7245604 | 576 | Double_t vars[4]; |
b1831bcb | 577 | vars[0] = particle->Eta(); |
578 | vars[1] = particle->Pt(); | |
579 | vars[2] = particleType; | |
c7245604 | 580 | vars[3] = centrality; |
b1831bcb | 581 | |
bf58cbde | 582 | for (Int_t j=0; j<fgkUEHists; j++) |
583 | if (GetUEHist(j)) | |
584 | GetUEHist(j)->GetTrackHistEfficiency()->Fill(vars, step); | |
b1831bcb | 585 | } |
586 | } | |
587 | } | |
588 | ||
a75aacd6 | 589 | //____________________________________________________________________ |
590 | void AliUEHistograms::FillEvent(Int_t eventType, Int_t step) | |
591 | { | |
592 | // fills the number of events at the given step and the given enty type | |
593 | // | |
594 | // WARNING: This function is called from Fill, so only call it for steps where Fill is not called | |
595 | ||
596 | fEventCount->Fill(step, eventType); | |
597 | } | |
598 | ||
2a910c25 | 599 | //____________________________________________________________________ |
600 | void AliUEHistograms::FillEvent(Double_t centrality, Int_t step) | |
601 | { | |
602 | // fills the number of events at the given step and the given centrality | |
603 | // | |
604 | // WARNING: This function is called from Fill, so only call it for steps where Fill is not called | |
605 | ||
606 | fEventCount->Fill(step, centrality); | |
607 | } | |
608 | ||
a75aacd6 | 609 | //____________________________________________________________________ |
610 | void AliUEHistograms::SetEtaRange(Float_t etaMin, Float_t etaMax) | |
611 | { | |
612 | // sets eta min and max for all contained AliUEHist classes | |
613 | ||
bf58cbde | 614 | for (Int_t i=0; i<fgkUEHists; i++) |
615 | if (GetUEHist(i)) | |
616 | GetUEHist(i)->SetEtaRange(etaMin, etaMax); | |
a75aacd6 | 617 | } |
618 | ||
619 | //____________________________________________________________________ | |
620 | void AliUEHistograms::SetPtRange(Float_t ptMin, Float_t ptMax) | |
621 | { | |
622 | // sets pT min and max for all contained AliUEHist classes | |
623 | ||
bf58cbde | 624 | for (Int_t i=0; i<fgkUEHists; i++) |
625 | if (GetUEHist(i)) | |
626 | GetUEHist(i)->SetPtRange(ptMin, ptMax); | |
a75aacd6 | 627 | } |
628 | ||
85bfac17 | 629 | //____________________________________________________________________ |
630 | void AliUEHistograms::SetZVtxRange(Float_t min, Float_t max) | |
631 | { | |
632 | // sets pT min and max for all contained AliUEHist classes | |
633 | ||
634 | for (Int_t i=0; i<fgkUEHists; i++) | |
635 | if (GetUEHist(i)) | |
636 | GetUEHist(i)->SetZVtxRange(min, max); | |
637 | } | |
638 | ||
144bd037 | 639 | //____________________________________________________________________ |
640 | void AliUEHistograms::SetContaminationEnhancement(TH1F* hist) | |
641 | { | |
642 | // sets the contamination enhancement histogram in all contained AliUEHist classes | |
643 | ||
bf58cbde | 644 | for (Int_t i=0; i<fgkUEHists; i++) |
645 | if (GetUEHist(i)) | |
646 | GetUEHist(i)->SetContaminationEnhancement(hist); | |
144bd037 | 647 | } |
648 | ||
a75aacd6 | 649 | //____________________________________________________________________ |
650 | void AliUEHistograms::SetCombineMinMax(Bool_t flag) | |
651 | { | |
652 | // sets pT min and max for all contained AliUEHist classes | |
653 | ||
bf58cbde | 654 | for (Int_t i=0; i<fgkUEHists; i++) |
655 | if (GetUEHist(i)) | |
656 | GetUEHist(i)->SetCombineMinMax(flag); | |
a75aacd6 | 657 | } |
658 | ||
659 | //____________________________________________________________________ | |
660 | void AliUEHistograms::Correct(AliUEHistograms* corrections) | |
661 | { | |
662 | // corrects the contained histograms by calling AliUEHist::Correct | |
663 | ||
bf58cbde | 664 | for (Int_t i=0; i<fgkUEHists; i++) |
665 | if (GetUEHist(i)) | |
666 | GetUEHist(i)->Correct(corrections->GetUEHist(i)); | |
a75aacd6 | 667 | } |
668 | ||
669 | //____________________________________________________________________ | |
670 | AliUEHistograms &AliUEHistograms::operator=(const AliUEHistograms &c) | |
671 | { | |
672 | // assigment operator | |
673 | ||
b0d56b29 | 674 | DeleteContainers(); |
675 | ||
a75aacd6 | 676 | if (this != &c) |
677 | ((AliUEHistograms &) c).Copy(*this); | |
678 | ||
679 | return *this; | |
680 | } | |
681 | ||
682 | //____________________________________________________________________ | |
683 | void AliUEHistograms::Copy(TObject& c) const | |
684 | { | |
685 | // copy function | |
686 | ||
687 | AliUEHistograms& target = (AliUEHistograms &) c; | |
688 | ||
689 | if (fNumberDensitypT) | |
690 | target.fNumberDensitypT = dynamic_cast<AliUEHist*> (fNumberDensitypT->Clone()); | |
691 | ||
692 | if (fSumpT) | |
693 | target.fSumpT = dynamic_cast<AliUEHist*> (fSumpT->Clone()); | |
694 | ||
695 | if (fNumberDensityPhi) | |
696 | target.fNumberDensityPhi = dynamic_cast<AliUEHist*> (fNumberDensityPhi->Clone()); | |
697 | ||
698 | if (fCorrelationpT) | |
699 | target.fCorrelationpT = dynamic_cast<TH2F*> (fCorrelationpT->Clone()); | |
700 | ||
701 | if (fCorrelationEta) | |
702 | target.fCorrelationEta = dynamic_cast<TH2F*> (fCorrelationEta->Clone()); | |
703 | ||
704 | if (fCorrelationPhi) | |
705 | target.fCorrelationPhi = dynamic_cast<TH2F*> (fCorrelationPhi->Clone()); | |
706 | ||
707 | if (fCorrelationR) | |
708 | target.fCorrelationR = dynamic_cast<TH2F*> (fCorrelationR->Clone()); | |
709 | ||
710 | if (fCorrelationLeading2Phi) | |
711 | target.fCorrelationLeading2Phi = dynamic_cast<TH2F*> (fCorrelationLeading2Phi->Clone()); | |
712 | ||
713 | if (fCorrelationMultiplicity) | |
714 | target.fCorrelationMultiplicity = dynamic_cast<TH2F*> (fCorrelationMultiplicity->Clone()); | |
715 | ||
716 | if (fEventCount) | |
717 | target.fEventCount = dynamic_cast<TH2F*> (fEventCount->Clone()); | |
718 | ||
719 | if (fEventCountDifferential) | |
720 | target.fEventCountDifferential = dynamic_cast<TH3F*> (fEventCountDifferential->Clone()); | |
721 | ||
722 | if (fVertexContributors) | |
723 | target.fVertexContributors = dynamic_cast<TH1F*> (fVertexContributors->Clone()); | |
bf58cbde | 724 | |
725 | if (fCentralityDistribution) | |
726 | target.fCentralityDistribution = dynamic_cast<TH1F*> (fCentralityDistribution->Clone()); | |
c7245604 | 727 | |
447d47d8 | 728 | if (fCentralityCorrelation) |
729 | target.fCentralityCorrelation = dynamic_cast<TH2F*> (fCentralityCorrelation->Clone()); | |
730 | ||
2a910c25 | 731 | if (fITSClusterMap) |
732 | target.fITSClusterMap = dynamic_cast<TH3F*> (fITSClusterMap->Clone()); | |
733 | ||
1bba939a | 734 | for (Int_t i=0; i<2; i++) |
670e1d49 | 735 | if (fTwoTrackDistancePt[i]) |
736 | target.fTwoTrackDistancePt[i] = dynamic_cast<TH3F*> (fTwoTrackDistancePt[i]->Clone()); | |
1bba939a | 737 | |
c7245604 | 738 | target.fSelectCharge = fSelectCharge; |
d38fa455 | 739 | target.fTriggerRestrictEta = fTriggerRestrictEta; |
b0d56b29 | 740 | target.fCutConversions = fCutConversions; |
741 | target.fCutResonances = fCutResonances; | |
85bfac17 | 742 | target.fRunNumber = fRunNumber; |
a75aacd6 | 743 | } |
744 | ||
745 | //____________________________________________________________________ | |
746 | Long64_t AliUEHistograms::Merge(TCollection* list) | |
747 | { | |
748 | // Merge a list of AliUEHistograms objects with this (needed for | |
749 | // PROOF). | |
750 | // Returns the number of merged objects (including this). | |
751 | ||
752 | if (!list) | |
753 | return 0; | |
754 | ||
755 | if (list->IsEmpty()) | |
756 | return 1; | |
757 | ||
758 | TIterator* iter = list->MakeIterator(); | |
759 | TObject* obj; | |
760 | ||
761 | // collections of objects | |
447d47d8 | 762 | const Int_t kMaxLists = 17; |
a75aacd6 | 763 | TList* lists[kMaxLists]; |
764 | ||
765 | for (Int_t i=0; i<kMaxLists; i++) | |
766 | lists[i] = new TList; | |
767 | ||
768 | Int_t count = 0; | |
769 | while ((obj = iter->Next())) { | |
770 | ||
771 | AliUEHistograms* entry = dynamic_cast<AliUEHistograms*> (obj); | |
772 | if (entry == 0) | |
773 | continue; | |
774 | ||
bf58cbde | 775 | if (entry->fNumberDensitypT) |
776 | lists[0]->Add(entry->fNumberDensitypT); | |
777 | if (entry->fSumpT) | |
778 | lists[1]->Add(entry->fSumpT); | |
779 | if (entry->fNumberDensityPhi) | |
780 | lists[2]->Add(entry->fNumberDensityPhi); | |
a75aacd6 | 781 | lists[3]->Add(entry->fCorrelationpT); |
782 | lists[4]->Add(entry->fCorrelationEta); | |
783 | lists[5]->Add(entry->fCorrelationPhi); | |
784 | lists[6]->Add(entry->fCorrelationR); | |
785 | lists[7]->Add(entry->fCorrelationLeading2Phi); | |
786 | lists[8]->Add(entry->fCorrelationMultiplicity); | |
787 | lists[9]->Add(entry->fEventCount); | |
788 | lists[10]->Add(entry->fEventCountDifferential); | |
789 | lists[11]->Add(entry->fVertexContributors); | |
bf58cbde | 790 | lists[12]->Add(entry->fCentralityDistribution); |
2a910c25 | 791 | lists[13]->Add(entry->fITSClusterMap); |
670e1d49 | 792 | if (fTwoTrackDistancePt[0]) |
793 | lists[14]->Add(entry->fTwoTrackDistancePt[0]); | |
794 | if (fTwoTrackDistancePt[1]) | |
795 | lists[15]->Add(entry->fTwoTrackDistancePt[1]); | |
447d47d8 | 796 | if (fCentralityCorrelation) |
797 | lists[16]->Add(entry->fCentralityCorrelation); | |
a75aacd6 | 798 | count++; |
799 | } | |
800 | ||
bf58cbde | 801 | if (fNumberDensitypT) |
802 | fNumberDensitypT->Merge(lists[0]); | |
803 | if (fSumpT) | |
804 | fSumpT->Merge(lists[1]); | |
805 | if (fNumberDensityPhi) | |
806 | fNumberDensityPhi->Merge(lists[2]); | |
a75aacd6 | 807 | fCorrelationpT->Merge(lists[3]); |
808 | fCorrelationEta->Merge(lists[4]); | |
809 | fCorrelationPhi->Merge(lists[5]); | |
810 | fCorrelationR->Merge(lists[6]); | |
811 | fCorrelationLeading2Phi->Merge(lists[7]); | |
812 | fCorrelationMultiplicity->Merge(lists[8]); | |
813 | fEventCount->Merge(lists[9]); | |
814 | fEventCountDifferential->Merge(lists[10]); | |
815 | fVertexContributors->Merge(lists[11]); | |
bf58cbde | 816 | fCentralityDistribution->Merge(lists[12]); |
2a910c25 | 817 | fITSClusterMap->Merge(lists[13]); |
670e1d49 | 818 | if (fTwoTrackDistancePt[0]) |
819 | fTwoTrackDistancePt[0]->Merge(lists[14]); | |
820 | if (fTwoTrackDistancePt[1]) | |
821 | fTwoTrackDistancePt[1]->Merge(lists[15]); | |
447d47d8 | 822 | if (fCentralityCorrelation) |
823 | fCentralityCorrelation->Merge(lists[16]); | |
a75aacd6 | 824 | |
825 | for (Int_t i=0; i<kMaxLists; i++) | |
826 | delete lists[i]; | |
827 | ||
828 | return count+1; | |
829 | } | |
b1831bcb | 830 | |
831 | void AliUEHistograms::CopyReconstructedData(AliUEHistograms* from) | |
832 | { | |
833 | // copies those histograms extracted from ESD to this object | |
834 | ||
bf58cbde | 835 | for (Int_t i=0; i<fgkUEHists; i++) |
836 | if (GetUEHist(i)) | |
837 | GetUEHist(i)->CopyReconstructedData(from->GetUEHist(i)); | |
b1831bcb | 838 | } |
6f803f6c | 839 | |
2a910c25 | 840 | void AliUEHistograms::ExtendTrackingEfficiency(Bool_t verbose) |
6f803f6c | 841 | { |
842 | // delegates to AliUEHists | |
843 | ||
bf58cbde | 844 | for (Int_t i=0; i<fgkUEHists; i++) |
845 | if (GetUEHist(i)) | |
2a910c25 | 846 | GetUEHist(i)->ExtendTrackingEfficiency(verbose); |
6f803f6c | 847 | } |
848 | ||
c7245604 | 849 | void AliUEHistograms::Scale(Double_t factor) |
850 | { | |
851 | // scales all contained histograms by the given factor | |
852 | ||
853 | for (Int_t i=0; i<fgkUEHists; i++) | |
854 | if (GetUEHist(i)) | |
855 | GetUEHist(i)->Scale(factor); | |
856 | ||
857 | TList list; | |
858 | list.Add(fCorrelationpT); | |
859 | list.Add(fCorrelationEta); | |
860 | list.Add(fCorrelationPhi); | |
861 | list.Add(fCorrelationR); | |
862 | list.Add(fCorrelationLeading2Phi); | |
863 | list.Add(fCorrelationMultiplicity); | |
864 | list.Add(fEventCount); | |
865 | list.Add(fEventCountDifferential); | |
866 | list.Add(fVertexContributors); | |
867 | list.Add(fCentralityDistribution); | |
447d47d8 | 868 | list.Add(fCentralityCorrelation); |
2a910c25 | 869 | list.Add(fITSClusterMap); |
670e1d49 | 870 | list.Add(fTwoTrackDistancePt[0]); |
871 | list.Add(fTwoTrackDistancePt[1]); | |
c7245604 | 872 | |
873 | for (Int_t i=0; i<list.GetEntries(); i++) | |
874 | ((TH1*) list.At(i))->Scale(factor); | |
875 | } | |
876 | ||
877 | void AliUEHistograms::Reset() | |
878 | { | |
879 | // delegates to AliUEHists | |
880 | ||
881 | for (Int_t i=0; i<fgkUEHists; i++) | |
882 | if (GetUEHist(i)) | |
883 | GetUEHist(i)->Reset(); | |
884 | } | |
1bba939a | 885 | |
c5c840c5 | 886 | void AliUEHistograms::TwoTrackEfficiency(TObjArray* tracks, TObjArray* mixed, Float_t bSign) |
1bba939a | 887 | { |
c5c840c5 | 888 | // takes the input list <tracks> and fills histograms to study two two-track efficiency effects |
889 | // fTwoTrackDistancePt[i] (i = 0 same, i = 1 mixed) | |
890 | // | |
891 | // the variables have been developed by the HBT group | |
892 | // see e.g. https://indico.cern.ch/materialDisplay.py?contribId=36&sessionId=6&materialId=slides&confId=142700 | |
1bba939a | 893 | |
670e1d49 | 894 | if (!fTwoTrackDistancePt[0]) |
1bba939a | 895 | { |
b8abd4b7 | 896 | fTwoTrackDistancePt[0] = new TH3F("fTwoTrackDistancePt[0]", ";#Delta#eta;#Delta#varphi^{*}_{min};#Delta p_{T}", 100, -0.05, 0.05, 400, -0.2, 0.2, 20, 0, 10); |
670e1d49 | 897 | fTwoTrackDistancePt[1] = (TH3F*) fTwoTrackDistancePt[0]->Clone("fTwoTrackDistancePt[1]"); |
1bba939a | 898 | } |
6840ec31 | 899 | |
1bba939a | 900 | // Eta() is extremely time consuming, therefore cache it for the inner loop here: |
c5c840c5 | 901 | TArrayF eta1(tracks->GetEntriesFast()); |
1bba939a | 902 | for (Int_t i=0; i<tracks->GetEntriesFast(); i++) |
c5c840c5 | 903 | eta1[i] = ((AliVParticle*) tracks->At(i))->Eta(); |
904 | ||
905 | Int_t jMax = tracks->GetEntriesFast(); | |
906 | if (mixed) | |
907 | jMax = mixed->GetEntriesFast(); | |
908 | ||
909 | TArrayF eta2(jMax); | |
910 | if (!mixed) | |
911 | eta2 = eta1; | |
912 | else | |
913 | for (Int_t i=0; i<mixed->GetEntriesFast(); i++) | |
914 | eta2[i] = ((AliVParticle*) mixed->At(i))->Eta(); | |
1bba939a | 915 | |
916 | for (Int_t i=0; i<tracks->GetEntriesFast(); i++) | |
917 | { | |
918 | AliVParticle* particle1 = (AliVParticle*) tracks->At(i); | |
f11dcf7d | 919 | Float_t phi1 = particle1->Phi(); |
920 | Float_t pt1 = particle1->Pt(); | |
921 | Float_t charge1 = particle1->Charge(); | |
0a439e96 | 922 | |
c5c840c5 | 923 | for (Int_t j=0; j<jMax; j++) |
1bba939a | 924 | { |
c5c840c5 | 925 | if (!mixed && i == j) |
0a439e96 | 926 | continue; |
927 | ||
c5c840c5 | 928 | AliVParticle* particle2 = 0; |
929 | if (mixed) | |
930 | particle2 = (AliVParticle*) mixed->At(j); | |
931 | else | |
932 | particle2 = (AliVParticle*) tracks->At(j); | |
f11dcf7d | 933 | Float_t phi2 = particle2->Phi(); |
934 | Float_t pt2 = particle2->Pt(); | |
935 | Float_t charge2 = particle2->Charge(); | |
1bba939a | 936 | |
0a439e96 | 937 | if (pt2 > pt1) |
938 | continue; | |
939 | ||
940 | // Double_t dpt = TMath::Abs(pt1 - pt2); | |
c5c840c5 | 941 | Float_t deta = eta1[i] - eta2[j]; |
f11dcf7d | 942 | Float_t detaabs = TMath::Abs(deta); |
1bba939a | 943 | |
944 | // optimization | |
6840ec31 | 945 | if (detaabs > 0.05 && (pt1 < 8 || pt1 > 15)) |
946 | continue; | |
1bba939a | 947 | |
f11dcf7d | 948 | Float_t dphistarmin = 1e5; |
949 | Float_t dphistarminabs = 1e5; | |
1bba939a | 950 | |
951 | for (Double_t rad=0.8; rad<2.51; rad+=0.01) | |
952 | { | |
6840ec31 | 953 | Float_t dphistar = phi1 - phi2 - TMath::ASin(charge1 * 0.075 * bSign * rad / pt1) + TMath::ASin(charge2 * 0.075 * bSign * rad / pt2); |
f11dcf7d | 954 | Float_t dphistarabs = TMath::Abs(dphistar); |
1bba939a | 955 | |
956 | if (dphistarabs < dphistarminabs) | |
957 | { | |
958 | dphistarmin = dphistar; | |
959 | dphistarminabs = dphistarabs; | |
960 | } | |
1bba939a | 961 | } |
a4a4d54e | 962 | |
6840ec31 | 963 | Float_t fillPt = pt2; |
964 | ||
965 | // analyze region for IAA paper | |
966 | if (pt1 < 8 || pt1 > 15) | |
967 | fillPt = 0.25; | |
968 | ||
c5c840c5 | 969 | if (!mixed) |
970 | fTwoTrackDistancePt[0]->Fill(deta, dphistarmin, fillPt); | |
1bba939a | 971 | else |
c5c840c5 | 972 | fTwoTrackDistancePt[1]->Fill(deta, dphistarmin, fillPt); |
1bba939a | 973 | } |
974 | } | |
1bba939a | 975 | } |
b0d56b29 | 976 | |
977 | Float_t AliUEHistograms::GetInvMassSquared(Float_t pt1, Float_t eta1, Float_t phi1, Float_t pt2, Float_t eta2, Float_t phi2, Float_t m0) | |
978 | { | |
979 | // calculate inv mass squared | |
980 | // same can be achieved, but with more computing time with | |
981 | /*TLorentzVector photon, p1, p2; | |
982 | p1.SetPtEtaPhiM(triggerParticle->Pt(), triggerEta, triggerParticle->Phi(), 0.510e-3); | |
983 | p2.SetPtEtaPhiM(particle->Pt(), eta[j], particle->Phi(), 0.510e-3); | |
984 | photon = p1+p2; | |
985 | photon.M()*/ | |
986 | ||
987 | Float_t tantheta1 = 1e10; | |
988 | ||
989 | if (eta1 < -1e-10 || eta1 > 1e-10) | |
990 | tantheta1 = 2 * TMath::Exp(-eta1) / ( 1 - TMath::Exp(-2*eta1)); | |
991 | ||
992 | Float_t tantheta2 = 1e10; | |
993 | if (eta2 < -1e-10 || eta2 > 1e-10) | |
994 | tantheta2 = 2 * TMath::Exp(-eta2) / ( 1 - TMath::Exp(-2*eta2)); | |
995 | ||
996 | Float_t e1squ = m0 * m0 + pt1 * pt1 * (1.0 + 1.0 / tantheta1 / tantheta1); | |
997 | Float_t e2squ = m0 * m0 + pt2 * pt2 * (1.0 + 1.0 / tantheta2 / tantheta2); | |
998 | ||
999 | Float_t mass2 = 2 * m0 * m0 + 2 * ( TMath::Sqrt(e1squ * e2squ) - ( pt1 * pt2 * ( TMath::Cos(phi1 - phi2) + 1.0 / tantheta1 / tantheta2 ) ) ); | |
1000 | ||
1001 | return mass2; | |
1002 | } |