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73318471 | 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: AliESDtrackCuts.cxx 24534 2008-03-16 22:22:11Z fca $ */ | |
17 | ||
18 | #include "AliESDtrackCuts.h" | |
19 | ||
20 | #include <AliESDtrack.h> | |
21 | #include <AliESD.h> | |
22 | #include <AliESDEvent.h> | |
23 | #include <AliLog.h> | |
24 | ||
25 | #include <TTree.h> | |
26 | #include <TCanvas.h> | |
27 | #include <TDirectory.h> | |
28 | ||
29 | //____________________________________________________________________ | |
30 | ClassImp(AliESDtrackCuts) | |
31 | ||
32 | // Cut names | |
33 | const Char_t* AliESDtrackCuts::fgkCutNames[kNCuts] = { | |
34 | "require TPC refit", | |
35 | "require ITS refit", | |
36 | "n clusters TPC", | |
37 | "n clusters ITS", | |
38 | "#Chi^{2}/clusters TPC", | |
39 | "#Chi^{2}/clusters ITS", | |
40 | "cov 11", | |
41 | "cov 22", | |
42 | "cov 33", | |
43 | "cov 44", | |
44 | "cov 55", | |
45 | "trk-to-vtx", | |
46 | "trk-to-vtx failed", | |
47 | "kink daughters", | |
48 | "p", | |
49 | "p_{T}", | |
50 | "p_{x}", | |
51 | "p_{y}", | |
52 | "p_{z}", | |
53 | "y", | |
54 | "eta" | |
55 | }; | |
56 | ||
57 | //____________________________________________________________________ | |
58 | AliESDtrackCuts::AliESDtrackCuts(const Char_t* name, const Char_t* title) : AliAnalysisCuts(name,title), | |
59 | fCutMinNClusterTPC(0), | |
60 | fCutMinNClusterITS(0), | |
61 | fCutMaxChi2PerClusterTPC(0), | |
62 | fCutMaxChi2PerClusterITS(0), | |
63 | fCutMaxC11(0), | |
64 | fCutMaxC22(0), | |
65 | fCutMaxC33(0), | |
66 | fCutMaxC44(0), | |
67 | fCutMaxC55(0), | |
68 | fCutAcceptKinkDaughters(0), | |
69 | fCutRequireTPCRefit(0), | |
70 | fCutRequireITSRefit(0), | |
71 | fCutNsigmaToVertex(0), | |
72 | fCutSigmaToVertexRequired(0), | |
73 | fPMin(0), | |
74 | fPMax(0), | |
75 | fPtMin(0), | |
76 | fPtMax(0), | |
77 | fPxMin(0), | |
78 | fPxMax(0), | |
79 | fPyMin(0), | |
80 | fPyMax(0), | |
81 | fPzMin(0), | |
82 | fPzMax(0), | |
83 | fEtaMin(0), | |
84 | fEtaMax(0), | |
85 | fRapMin(0), | |
86 | fRapMax(0), | |
87 | fHistogramsOn(0), | |
88 | ffDTheoretical(0), | |
89 | fhCutStatistics(0), | |
90 | fhCutCorrelation(0) | |
91 | { | |
92 | // | |
93 | // constructor | |
94 | // | |
95 | ||
96 | Init(); | |
97 | ||
98 | //############################################################################## | |
99 | // setting default cuts | |
100 | SetMinNClustersTPC(); | |
101 | SetMinNClustersITS(); | |
102 | SetMaxChi2PerClusterTPC(); | |
103 | SetMaxChi2PerClusterITS(); | |
104 | SetMaxCovDiagonalElements(); | |
105 | SetRequireTPCRefit(); | |
106 | SetRequireITSRefit(); | |
107 | SetAcceptKingDaughters(); | |
108 | SetMinNsigmaToVertex(); | |
109 | SetRequireSigmaToVertex(); | |
110 | SetPRange(); | |
111 | SetPtRange(); | |
112 | SetPxRange(); | |
113 | SetPyRange(); | |
114 | SetPzRange(); | |
115 | SetEtaRange(); | |
116 | SetRapRange(); | |
117 | ||
118 | SetHistogramsOn(); | |
119 | } | |
120 | ||
121 | //_____________________________________________________________________________ | |
122 | AliESDtrackCuts::AliESDtrackCuts(const AliESDtrackCuts &c) : AliAnalysisCuts(c), | |
123 | fCutMinNClusterTPC(0), | |
124 | fCutMinNClusterITS(0), | |
125 | fCutMaxChi2PerClusterTPC(0), | |
126 | fCutMaxChi2PerClusterITS(0), | |
127 | fCutMaxC11(0), | |
128 | fCutMaxC22(0), | |
129 | fCutMaxC33(0), | |
130 | fCutMaxC44(0), | |
131 | fCutMaxC55(0), | |
132 | fCutAcceptKinkDaughters(0), | |
133 | fCutRequireTPCRefit(0), | |
134 | fCutRequireITSRefit(0), | |
135 | fCutNsigmaToVertex(0), | |
136 | fCutSigmaToVertexRequired(0), | |
137 | fPMin(0), | |
138 | fPMax(0), | |
139 | fPtMin(0), | |
140 | fPtMax(0), | |
141 | fPxMin(0), | |
142 | fPxMax(0), | |
143 | fPyMin(0), | |
144 | fPyMax(0), | |
145 | fPzMin(0), | |
146 | fPzMax(0), | |
147 | fEtaMin(0), | |
148 | fEtaMax(0), | |
149 | fRapMin(0), | |
150 | fRapMax(0), | |
151 | fHistogramsOn(0), | |
152 | ffDTheoretical(0), | |
153 | fhCutStatistics(0), | |
154 | fhCutCorrelation(0) | |
155 | { | |
156 | // | |
157 | // copy constructor | |
158 | // | |
159 | ||
160 | ((AliESDtrackCuts &) c).Copy(*this); | |
161 | } | |
162 | ||
163 | AliESDtrackCuts::~AliESDtrackCuts() | |
164 | { | |
165 | // | |
166 | // destructor | |
167 | // | |
168 | ||
169 | for (Int_t i=0; i<2; i++) { | |
170 | ||
171 | if (fhNClustersITS[i]) | |
172 | delete fhNClustersITS[i]; | |
173 | if (fhNClustersTPC[i]) | |
174 | delete fhNClustersTPC[i]; | |
175 | if (fhChi2PerClusterITS[i]) | |
176 | delete fhChi2PerClusterITS[i]; | |
177 | if (fhChi2PerClusterTPC[i]) | |
178 | delete fhChi2PerClusterTPC[i]; | |
179 | if (fhC11[i]) | |
180 | delete fhC11[i]; | |
181 | if (fhC22[i]) | |
182 | delete fhC22[i]; | |
183 | if (fhC33[i]) | |
184 | delete fhC33[i]; | |
185 | if (fhC44[i]) | |
186 | delete fhC44[i]; | |
187 | if (fhC55[i]) | |
188 | delete fhC55[i]; | |
189 | ||
190 | if (fhDXY[i]) | |
191 | delete fhDXY[i]; | |
192 | if (fhDZ[i]) | |
193 | delete fhDZ[i]; | |
194 | if (fhDXYvsDZ[i]) | |
195 | delete fhDXYvsDZ[i]; | |
196 | ||
197 | if (fhDXYNormalized[i]) | |
198 | delete fhDXYNormalized[i]; | |
199 | if (fhDZNormalized[i]) | |
200 | delete fhDZNormalized[i]; | |
201 | if (fhDXYvsDZNormalized[i]) | |
202 | delete fhDXYvsDZNormalized[i]; | |
203 | if (fhNSigmaToVertex[i]) | |
204 | delete fhNSigmaToVertex[i]; | |
205 | if (fhPt[i]) | |
206 | delete fhPt[i]; | |
207 | if (fhEta[i]) | |
208 | delete fhEta[i]; | |
209 | } | |
210 | ||
211 | if (ffDTheoretical) | |
212 | delete ffDTheoretical; | |
213 | ||
214 | if (fhCutStatistics) | |
215 | delete fhCutStatistics; | |
216 | if (fhCutCorrelation) | |
217 | delete fhCutCorrelation; | |
218 | } | |
219 | ||
220 | void AliESDtrackCuts::Init() | |
221 | { | |
222 | // | |
223 | // sets everything to zero | |
224 | // | |
225 | ||
226 | fCutMinNClusterTPC = 0; | |
227 | fCutMinNClusterITS = 0; | |
228 | ||
229 | fCutMaxChi2PerClusterTPC = 0; | |
230 | fCutMaxChi2PerClusterITS = 0; | |
231 | ||
232 | fCutMaxC11 = 0; | |
233 | fCutMaxC22 = 0; | |
234 | fCutMaxC33 = 0; | |
235 | fCutMaxC44 = 0; | |
236 | fCutMaxC55 = 0; | |
237 | ||
238 | fCutAcceptKinkDaughters = 0; | |
239 | fCutRequireTPCRefit = 0; | |
240 | fCutRequireITSRefit = 0; | |
241 | ||
242 | fCutNsigmaToVertex = 0; | |
243 | fCutSigmaToVertexRequired = 0; | |
244 | ||
245 | fPMin = 0; | |
246 | fPMax = 0; | |
247 | fPtMin = 0; | |
248 | fPtMax = 0; | |
249 | fPxMin = 0; | |
250 | fPxMax = 0; | |
251 | fPyMin = 0; | |
252 | fPyMax = 0; | |
253 | fPzMin = 0; | |
254 | fPzMax = 0; | |
255 | fEtaMin = 0; | |
256 | fEtaMax = 0; | |
257 | fRapMin = 0; | |
258 | fRapMax = 0; | |
259 | ||
260 | fHistogramsOn = kFALSE; | |
261 | ||
262 | for (Int_t i=0; i<2; ++i) | |
263 | { | |
264 | fhNClustersITS[i] = 0; | |
265 | fhNClustersTPC[i] = 0; | |
266 | ||
267 | fhChi2PerClusterITS[i] = 0; | |
268 | fhChi2PerClusterTPC[i] = 0; | |
269 | ||
270 | fhC11[i] = 0; | |
271 | fhC22[i] = 0; | |
272 | fhC33[i] = 0; | |
273 | fhC44[i] = 0; | |
274 | fhC55[i] = 0; | |
275 | ||
276 | fhDXY[i] = 0; | |
277 | fhDZ[i] = 0; | |
278 | fhDXYvsDZ[i] = 0; | |
279 | ||
280 | fhDXYNormalized[i] = 0; | |
281 | fhDZNormalized[i] = 0; | |
282 | fhDXYvsDZNormalized[i] = 0; | |
283 | fhNSigmaToVertex[i] = 0; | |
284 | ||
285 | fhPt[i] = 0; | |
286 | fhEta[i] = 0; | |
287 | } | |
288 | ffDTheoretical = 0; | |
289 | ||
290 | fhCutStatistics = 0; | |
291 | fhCutCorrelation = 0; | |
292 | } | |
293 | ||
294 | //_____________________________________________________________________________ | |
295 | AliESDtrackCuts &AliESDtrackCuts::operator=(const AliESDtrackCuts &c) | |
296 | { | |
297 | // | |
298 | // Assignment operator | |
299 | // | |
300 | ||
301 | if (this != &c) ((AliESDtrackCuts &) c).Copy(*this); | |
302 | return *this; | |
303 | } | |
304 | ||
305 | //_____________________________________________________________________________ | |
306 | void AliESDtrackCuts::Copy(TObject &c) const | |
307 | { | |
308 | // | |
309 | // Copy function | |
310 | // | |
311 | ||
312 | AliESDtrackCuts& target = (AliESDtrackCuts &) c; | |
313 | ||
314 | target.Init(); | |
315 | ||
316 | target.fCutMinNClusterTPC = fCutMinNClusterTPC; | |
317 | target.fCutMinNClusterITS = fCutMinNClusterITS; | |
318 | ||
319 | target.fCutMaxChi2PerClusterTPC = fCutMaxChi2PerClusterTPC; | |
320 | target.fCutMaxChi2PerClusterITS = fCutMaxChi2PerClusterITS; | |
321 | ||
322 | target.fCutMaxC11 = fCutMaxC11; | |
323 | target.fCutMaxC22 = fCutMaxC22; | |
324 | target.fCutMaxC33 = fCutMaxC33; | |
325 | target.fCutMaxC44 = fCutMaxC44; | |
326 | target.fCutMaxC55 = fCutMaxC55; | |
327 | ||
328 | target.fCutAcceptKinkDaughters = fCutAcceptKinkDaughters; | |
329 | target.fCutRequireTPCRefit = fCutRequireTPCRefit; | |
330 | target.fCutRequireITSRefit = fCutRequireITSRefit; | |
331 | ||
332 | target.fCutNsigmaToVertex = fCutNsigmaToVertex; | |
333 | target.fCutSigmaToVertexRequired = fCutSigmaToVertexRequired; | |
334 | ||
335 | target.fPMin = fPMin; | |
336 | target.fPMax = fPMax; | |
337 | target.fPtMin = fPtMin; | |
338 | target.fPtMax = fPtMax; | |
339 | target.fPxMin = fPxMin; | |
340 | target.fPxMax = fPxMax; | |
341 | target.fPyMin = fPyMin; | |
342 | target.fPyMax = fPyMax; | |
343 | target.fPzMin = fPzMin; | |
344 | target.fPzMax = fPzMax; | |
345 | target.fEtaMin = fEtaMin; | |
346 | target.fEtaMax = fEtaMax; | |
347 | target.fRapMin = fRapMin; | |
348 | target.fRapMax = fRapMax; | |
349 | ||
350 | target.fHistogramsOn = fHistogramsOn; | |
351 | ||
352 | for (Int_t i=0; i<2; ++i) | |
353 | { | |
354 | if (fhNClustersITS[i]) target.fhNClustersITS[i] = (TH1F*) fhNClustersITS[i]->Clone(); | |
355 | if (fhNClustersTPC[i]) target.fhNClustersTPC[i] = (TH1F*) fhNClustersTPC[i]->Clone(); | |
356 | ||
357 | if (fhChi2PerClusterITS[i]) target.fhChi2PerClusterITS[i] = (TH1F*) fhChi2PerClusterITS[i]->Clone(); | |
358 | if (fhChi2PerClusterTPC[i]) target.fhChi2PerClusterTPC[i] = (TH1F*) fhChi2PerClusterTPC[i]->Clone(); | |
359 | ||
360 | if (fhC11[i]) target.fhC11[i] = (TH1F*) fhC11[i]->Clone(); | |
361 | if (fhC22[i]) target.fhC22[i] = (TH1F*) fhC22[i]->Clone(); | |
362 | if (fhC33[i]) target.fhC33[i] = (TH1F*) fhC33[i]->Clone(); | |
363 | if (fhC44[i]) target.fhC44[i] = (TH1F*) fhC44[i]->Clone(); | |
364 | if (fhC55[i]) target.fhC55[i] = (TH1F*) fhC55[i]->Clone(); | |
365 | ||
366 | if (fhDXY[i]) target.fhDXY[i] = (TH1F*) fhDXY[i]->Clone(); | |
367 | if (fhDZ[i]) target.fhDZ[i] = (TH1F*) fhDZ[i]->Clone(); | |
368 | if (fhDXYvsDZ[i]) target.fhDXYvsDZ[i] = (TH2F*) fhDXYvsDZ[i]->Clone(); | |
369 | ||
370 | if (fhDXYNormalized[i]) target.fhDXYNormalized[i] = (TH1F*) fhDXYNormalized[i]->Clone(); | |
371 | if (fhDZNormalized[i]) target.fhDZNormalized[i] = (TH1F*) fhDZNormalized[i]->Clone(); | |
372 | if (fhDXYvsDZNormalized[i]) target.fhDXYvsDZNormalized[i] = (TH2F*) fhDXYvsDZNormalized[i]->Clone(); | |
373 | if (fhNSigmaToVertex[i]) target.fhNSigmaToVertex[i] = (TH1F*) fhNSigmaToVertex[i]->Clone(); | |
374 | ||
375 | if (fhPt[i]) target.fhPt[i] = (TH1F*) fhPt[i]->Clone(); | |
376 | if (fhEta[i]) target.fhEta[i] = (TH1F*) fhEta[i]->Clone(); | |
377 | } | |
378 | if (ffDTheoretical) target.ffDTheoretical = (TF1*) ffDTheoretical->Clone(); | |
379 | ||
380 | if (fhCutStatistics) target.fhCutStatistics = (TH1F*) fhCutStatistics->Clone(); | |
381 | if (fhCutCorrelation) target.fhCutCorrelation = (TH2F*) fhCutCorrelation->Clone(); | |
382 | ||
383 | TNamed::Copy(c); | |
384 | } | |
385 | ||
386 | //_____________________________________________________________________________ | |
387 | Long64_t AliESDtrackCuts::Merge(TCollection* list) { | |
388 | // Merge a list of AliESDtrackCuts objects with this (needed for PROOF) | |
389 | // Returns the number of merged objects (including this) | |
390 | ||
391 | if (!list) | |
392 | return 0; | |
393 | ||
394 | if (list->IsEmpty()) | |
395 | return 1; | |
396 | ||
397 | if (!fHistogramsOn) | |
398 | return 0; | |
399 | ||
400 | TIterator* iter = list->MakeIterator(); | |
401 | TObject* obj; | |
402 | ||
403 | ||
404 | // collection of measured and generated histograms | |
405 | Int_t count = 0; | |
406 | while ((obj = iter->Next())) { | |
407 | ||
408 | AliESDtrackCuts* entry = dynamic_cast<AliESDtrackCuts*>(obj); | |
409 | if (entry == 0) | |
410 | continue; | |
411 | ||
412 | if (!entry->fHistogramsOn) | |
413 | continue; | |
414 | ||
415 | for (Int_t i=0; i<2; i++) { | |
416 | ||
417 | fhNClustersITS[i] ->Add(entry->fhNClustersITS[i] ); | |
418 | fhNClustersTPC[i] ->Add(entry->fhNClustersTPC[i] ); | |
419 | ||
420 | fhChi2PerClusterITS[i] ->Add(entry->fhChi2PerClusterITS[i]); | |
421 | fhChi2PerClusterTPC[i] ->Add(entry->fhChi2PerClusterTPC[i]); | |
422 | ||
423 | fhC11[i] ->Add(entry->fhC11[i] ); | |
424 | fhC22[i] ->Add(entry->fhC22[i] ); | |
425 | fhC33[i] ->Add(entry->fhC33[i] ); | |
426 | fhC44[i] ->Add(entry->fhC44[i] ); | |
427 | fhC55[i] ->Add(entry->fhC55[i] ); | |
428 | ||
429 | fhDXY[i] ->Add(entry->fhDXY[i] ); | |
430 | fhDZ[i] ->Add(entry->fhDZ[i] ); | |
431 | fhDXYvsDZ[i] ->Add(entry->fhDXYvsDZ[i] ); | |
432 | ||
433 | fhDXYNormalized[i] ->Add(entry->fhDXYNormalized[i] ); | |
434 | fhDZNormalized[i] ->Add(entry->fhDZNormalized[i] ); | |
435 | fhDXYvsDZNormalized[i] ->Add(entry->fhDXYvsDZNormalized[i]); | |
436 | fhNSigmaToVertex[i] ->Add(entry->fhNSigmaToVertex[i]); | |
437 | ||
438 | fhPt[i] ->Add(entry->fhPt[i]); | |
439 | fhEta[i] ->Add(entry->fhEta[i]); | |
440 | } | |
441 | ||
442 | fhCutStatistics ->Add(entry->fhCutStatistics); | |
443 | fhCutCorrelation ->Add(entry->fhCutCorrelation); | |
444 | ||
445 | count++; | |
446 | } | |
447 | ||
448 | return count+1; | |
449 | } | |
450 | ||
451 | ||
452 | //____________________________________________________________________ | |
453 | Float_t AliESDtrackCuts::GetSigmaToVertex(AliESDtrack* esdTrack) | |
454 | { | |
455 | // Calculates the number of sigma to the vertex. | |
456 | ||
457 | Float_t b[2]; | |
458 | Float_t bRes[2]; | |
459 | Float_t bCov[3]; | |
460 | esdTrack->GetImpactParameters(b,bCov); | |
461 | if (bCov[0]<=0 || bCov[2]<=0) { | |
462 | AliDebug(1, "Estimated b resolution lower or equal zero!"); | |
463 | bCov[0]=0; bCov[2]=0; | |
464 | } | |
465 | bRes[0] = TMath::Sqrt(bCov[0]); | |
466 | bRes[1] = TMath::Sqrt(bCov[2]); | |
467 | ||
468 | // ----------------------------------- | |
469 | // How to get to a n-sigma cut? | |
470 | // | |
471 | // The accumulated statistics from 0 to d is | |
472 | // | |
473 | // -> Erf(d/Sqrt(2)) for a 1-dim gauss (d = n_sigma) | |
474 | // -> 1 - Exp(-d**2) for a 2-dim gauss (d*d = dx*dx + dy*dy != n_sigma) | |
475 | // | |
476 | // It means that for a 2-dim gauss: n_sigma(d) = Sqrt(2)*ErfInv(1 - Exp((-x**2)/2) | |
477 | // Can this be expressed in a different way? | |
478 | ||
479 | if (bRes[0] == 0 || bRes[1] ==0) | |
480 | return -1; | |
481 | ||
482 | Float_t d = TMath::Sqrt(TMath::Power(b[0]/bRes[0],2) + TMath::Power(b[1]/bRes[1],2)); | |
483 | ||
484 | // stupid rounding problem screws up everything: | |
485 | // if d is too big, TMath::Exp(...) gets 0, and TMath::ErfInverse(1) that should be infinite, gets 0 :( | |
486 | if (TMath::Exp(-d * d / 2) < 1e-10) | |
487 | return 1000; | |
488 | ||
489 | d = TMath::ErfInverse(1 - TMath::Exp(-d * d / 2)) * TMath::Sqrt(2); | |
490 | return d; | |
491 | } | |
492 | ||
493 | void AliESDtrackCuts::EnableNeededBranches(TTree* tree) | |
494 | { | |
495 | // enables the branches needed by AcceptTrack, for a list see comment of AcceptTrack | |
496 | ||
497 | tree->SetBranchStatus("fTracks.fFlags", 1); | |
498 | tree->SetBranchStatus("fTracks.fITSncls", 1); | |
499 | tree->SetBranchStatus("fTracks.fTPCncls", 1); | |
500 | tree->SetBranchStatus("fTracks.fITSchi2", 1); | |
501 | tree->SetBranchStatus("fTracks.fTPCchi2", 1); | |
502 | tree->SetBranchStatus("fTracks.fC*", 1); | |
503 | tree->SetBranchStatus("fTracks.fD", 1); | |
504 | tree->SetBranchStatus("fTracks.fZ", 1); | |
505 | tree->SetBranchStatus("fTracks.fCdd", 1); | |
506 | tree->SetBranchStatus("fTracks.fCdz", 1); | |
507 | tree->SetBranchStatus("fTracks.fCzz", 1); | |
508 | tree->SetBranchStatus("fTracks.fP*", 1); | |
509 | tree->SetBranchStatus("fTracks.fR*", 1); | |
510 | tree->SetBranchStatus("fTracks.fKinkIndexes*", 1); | |
511 | } | |
512 | ||
513 | //____________________________________________________________________ | |
514 | Bool_t | |
515 | AliESDtrackCuts::AcceptTrack(AliESDtrack* esdTrack) { | |
516 | // | |
517 | // figure out if the tracks survives all the track cuts defined | |
518 | // | |
519 | // the different quality parameter and kinematic values are first | |
520 | // retrieved from the track. then it is found out what cuts the | |
521 | // track did not survive and finally the cuts are imposed. | |
522 | ||
523 | // this function needs the following branches: | |
524 | // fTracks.fFlags | |
525 | // fTracks.fITSncls | |
526 | // fTracks.fTPCncls | |
527 | // fTracks.fITSchi2 | |
528 | // fTracks.fTPCchi2 | |
529 | // fTracks.fC //GetExternalCovariance | |
530 | // fTracks.fD //GetImpactParameters | |
531 | // fTracks.fZ //GetImpactParameters | |
532 | // fTracks.fCdd //GetImpactParameters | |
533 | // fTracks.fCdz //GetImpactParameters | |
534 | // fTracks.fCzz //GetImpactParameters | |
535 | // fTracks.fP //GetPxPyPz | |
536 | // fTracks.fR //GetMass | |
537 | // fTracks.fP //GetMass | |
538 | // fTracks.fKinkIndexes | |
539 | ||
540 | UInt_t status = esdTrack->GetStatus(); | |
541 | ||
542 | // dummy array | |
543 | Int_t fIdxInt[200]; | |
544 | ||
545 | // getting quality parameters from the ESD track | |
546 | Int_t nClustersITS = esdTrack->GetITSclusters(fIdxInt); | |
547 | Int_t nClustersTPC = esdTrack->GetTPCclusters(fIdxInt); | |
548 | ||
549 | ||
550 | ||
551 | Float_t chi2PerClusterITS = -1; | |
552 | Float_t chi2PerClusterTPC = -1; | |
553 | if (nClustersITS!=0) | |
554 | chi2PerClusterITS = esdTrack->GetITSchi2()/Float_t(nClustersITS); | |
555 | if (nClustersTPC!=0) | |
556 | chi2PerClusterTPC = esdTrack->GetTPCchi2()/Float_t(nClustersTPC); | |
557 | ||
558 | Double_t extCov[15]; | |
559 | esdTrack->GetExternalCovariance(extCov); | |
560 | ||
561 | // getting the track to vertex parameters | |
562 | Float_t nSigmaToVertex = GetSigmaToVertex(esdTrack); | |
563 | ||
564 | // getting the kinematic variables of the track | |
565 | // (assuming the mass is known) | |
566 | Double_t p[3]; | |
567 | esdTrack->GetPxPyPz(p); | |
568 | Float_t momentum = TMath::Sqrt(TMath::Power(p[0],2) + TMath::Power(p[1],2) + TMath::Power(p[2],2)); | |
569 | Float_t pt = TMath::Sqrt(TMath::Power(p[0],2) + TMath::Power(p[1],2)); | |
570 | Float_t energy = TMath::Sqrt(TMath::Power(esdTrack->GetMass(),2) + TMath::Power(momentum,2)); | |
571 | ||
572 | ||
573 | //y-eta related calculations | |
574 | Float_t eta = -100.; | |
575 | Float_t y = -100.; | |
576 | if((momentum != TMath::Abs(p[2]))&&(momentum != 0)) | |
577 | eta = 0.5*TMath::Log((momentum + p[2])/(momentum - p[2])); | |
578 | if((energy != TMath::Abs(p[2]))&&(momentum != 0)) | |
579 | y = 0.5*TMath::Log((energy + p[2])/(energy - p[2])); | |
580 | ||
581 | ||
582 | //######################################################################## | |
583 | // cut the track? | |
584 | ||
585 | Bool_t cuts[kNCuts]; | |
586 | for (Int_t i=0; i<kNCuts; i++) cuts[i]=kFALSE; | |
587 | ||
588 | // track quality cuts | |
589 | if (fCutRequireTPCRefit && (status&AliESDtrack::kTPCrefit)==0) | |
590 | cuts[0]=kTRUE; | |
591 | if (fCutRequireITSRefit && (status&AliESDtrack::kITSrefit)==0) | |
592 | cuts[1]=kTRUE; | |
593 | if (nClustersTPC<fCutMinNClusterTPC) | |
594 | cuts[2]=kTRUE; | |
595 | if (nClustersITS<fCutMinNClusterITS) | |
596 | cuts[3]=kTRUE; | |
597 | if (chi2PerClusterTPC>fCutMaxChi2PerClusterTPC) | |
598 | cuts[4]=kTRUE; | |
599 | if (chi2PerClusterITS>fCutMaxChi2PerClusterITS) | |
600 | cuts[5]=kTRUE; | |
601 | if (extCov[0] > fCutMaxC11) | |
602 | cuts[6]=kTRUE; | |
603 | if (extCov[2] > fCutMaxC22) | |
604 | cuts[7]=kTRUE; | |
605 | if (extCov[5] > fCutMaxC33) | |
606 | cuts[8]=kTRUE; | |
607 | if (extCov[9] > fCutMaxC44) | |
608 | cuts[9]=kTRUE; | |
609 | if (extCov[14] > fCutMaxC55) | |
610 | cuts[10]=kTRUE; | |
611 | if (nSigmaToVertex > fCutNsigmaToVertex && fCutSigmaToVertexRequired) | |
612 | cuts[11] = kTRUE; | |
613 | // if n sigma could not be calculated | |
614 | if (nSigmaToVertex<0 && fCutSigmaToVertexRequired) | |
615 | cuts[12]=kTRUE; | |
616 | if (!fCutAcceptKinkDaughters && esdTrack->GetKinkIndex(0)>0) | |
617 | cuts[13]=kTRUE; | |
618 | // track kinematics cut | |
619 | if((momentum < fPMin) || (momentum > fPMax)) | |
620 | cuts[14]=kTRUE; | |
621 | if((pt < fPtMin) || (pt > fPtMax)) | |
622 | cuts[15] = kTRUE; | |
623 | if((p[0] < fPxMin) || (p[0] > fPxMax)) | |
624 | cuts[16] = kTRUE; | |
625 | if((p[1] < fPyMin) || (p[1] > fPyMax)) | |
626 | cuts[17] = kTRUE; | |
627 | if((p[2] < fPzMin) || (p[2] > fPzMax)) | |
628 | cuts[18] = kTRUE; | |
629 | if((eta < fEtaMin) || (eta > fEtaMax)) | |
630 | cuts[19] = kTRUE; | |
631 | if((y < fRapMin) || (y > fRapMax)) | |
632 | cuts[20] = kTRUE; | |
633 | ||
634 | Bool_t cut=kFALSE; | |
635 | for (Int_t i=0; i<kNCuts; i++) | |
636 | if (cuts[i]) cut = kTRUE; | |
637 | ||
638 | //######################################################################## | |
639 | // filling histograms | |
640 | if (fHistogramsOn) { | |
641 | fhCutStatistics->Fill(fhCutStatistics->GetBinCenter(fhCutStatistics->GetXaxis()->FindBin("n tracks"))); | |
642 | ||
643 | if (cut) | |
644 | fhCutStatistics->Fill(fhCutStatistics->GetBinCenter(fhCutStatistics->GetXaxis()->FindBin("n cut tracks"))); | |
645 | ||
646 | for (Int_t i=0; i<kNCuts; i++) { | |
647 | if (cuts[i]) | |
648 | fhCutStatistics->Fill(fhCutStatistics->GetBinCenter(fhCutStatistics->GetXaxis()->FindBin(fgkCutNames[i]))); | |
649 | ||
650 | for (Int_t j=i; j<kNCuts; j++) { | |
651 | if (cuts[i] && cuts[j]) { | |
652 | Float_t x = fhCutCorrelation->GetXaxis()->GetBinCenter(fhCutCorrelation->GetXaxis()->FindBin(fgkCutNames[i])); | |
653 | Float_t y = fhCutCorrelation->GetYaxis()->GetBinCenter(fhCutCorrelation->GetYaxis()->FindBin(fgkCutNames[j])); | |
654 | fhCutCorrelation->Fill(x,y); | |
655 | } | |
656 | } | |
657 | } | |
658 | ||
659 | fhNClustersITS[0]->Fill(nClustersITS); | |
660 | fhNClustersTPC[0]->Fill(nClustersTPC); | |
661 | fhChi2PerClusterITS[0]->Fill(chi2PerClusterITS); | |
662 | fhChi2PerClusterTPC[0]->Fill(chi2PerClusterTPC); | |
663 | ||
664 | fhC11[0]->Fill(extCov[0]); | |
665 | fhC22[0]->Fill(extCov[2]); | |
666 | fhC33[0]->Fill(extCov[5]); | |
667 | fhC44[0]->Fill(extCov[9]); | |
668 | fhC55[0]->Fill(extCov[14]); | |
669 | ||
670 | fhPt[0]->Fill(pt); | |
671 | fhEta[0]->Fill(eta); | |
672 | ||
673 | Float_t b[2]; | |
674 | Float_t bRes[2]; | |
675 | Float_t bCov[3]; | |
676 | esdTrack->GetImpactParameters(b,bCov); | |
677 | if (bCov[0]<=0 || bCov[2]<=0) { | |
678 | AliDebug(1, "Estimated b resolution lower or equal zero!"); | |
679 | bCov[0]=0; bCov[2]=0; | |
680 | } | |
681 | bRes[0] = TMath::Sqrt(bCov[0]); | |
682 | bRes[1] = TMath::Sqrt(bCov[2]); | |
683 | ||
684 | fhDZ[0]->Fill(b[1]); | |
685 | fhDXY[0]->Fill(b[0]); | |
686 | fhDXYvsDZ[0]->Fill(b[1],b[0]); | |
687 | ||
688 | if (bRes[0]!=0 && bRes[1]!=0) { | |
689 | fhDZNormalized[0]->Fill(b[1]/bRes[1]); | |
690 | fhDXYNormalized[0]->Fill(b[0]/bRes[0]); | |
691 | fhDXYvsDZNormalized[0]->Fill(b[1]/bRes[1], b[0]/bRes[0]); | |
692 | fhNSigmaToVertex[0]->Fill(nSigmaToVertex); | |
693 | } | |
694 | } | |
695 | ||
696 | //######################################################################## | |
697 | // cut the track! | |
698 | if (cut) return kFALSE; | |
699 | ||
700 | //######################################################################## | |
701 | // filling histograms after cut | |
702 | if (fHistogramsOn) { | |
703 | fhNClustersITS[1]->Fill(nClustersITS); | |
704 | fhNClustersTPC[1]->Fill(nClustersTPC); | |
705 | fhChi2PerClusterITS[1]->Fill(chi2PerClusterITS); | |
706 | fhChi2PerClusterTPC[1]->Fill(chi2PerClusterTPC); | |
707 | ||
708 | fhC11[1]->Fill(extCov[0]); | |
709 | fhC22[1]->Fill(extCov[2]); | |
710 | fhC33[1]->Fill(extCov[5]); | |
711 | fhC44[1]->Fill(extCov[9]); | |
712 | fhC55[1]->Fill(extCov[14]); | |
713 | ||
714 | fhPt[1]->Fill(pt); | |
715 | fhEta[1]->Fill(eta); | |
716 | ||
717 | Float_t b[2]; | |
718 | Float_t bRes[2]; | |
719 | Float_t bCov[3]; | |
720 | esdTrack->GetImpactParameters(b,bCov); | |
721 | if (bCov[0]<=0 || bCov[2]<=0) { | |
722 | AliDebug(1, "Estimated b resolution lower or equal zero!"); | |
723 | bCov[0]=0; bCov[2]=0; | |
724 | } | |
725 | bRes[0] = TMath::Sqrt(bCov[0]); | |
726 | bRes[1] = TMath::Sqrt(bCov[2]); | |
727 | ||
728 | fhDZ[1]->Fill(b[1]); | |
729 | fhDXY[1]->Fill(b[0]); | |
730 | fhDXYvsDZ[1]->Fill(b[1],b[0]); | |
731 | ||
732 | if (bRes[0]!=0 && bRes[1]!=0) | |
733 | { | |
734 | fhDZNormalized[1]->Fill(b[1]/bRes[1]); | |
735 | fhDXYNormalized[1]->Fill(b[0]/bRes[0]); | |
736 | fhDXYvsDZNormalized[1]->Fill(b[1]/bRes[1], b[0]/bRes[0]); | |
737 | fhNSigmaToVertex[1]->Fill(nSigmaToVertex); | |
738 | } | |
739 | } | |
740 | ||
741 | return kTRUE; | |
742 | } | |
743 | ||
744 | //____________________________________________________________________ | |
745 | TObjArray* AliESDtrackCuts::GetAcceptedTracks(AliESD* esd) | |
746 | { | |
747 | // | |
748 | // returns an array of all tracks that pass the cuts | |
749 | // | |
750 | ||
751 | TObjArray* acceptedTracks = new TObjArray(); | |
752 | ||
753 | // loop over esd tracks | |
754 | for (Int_t iTrack = 0; iTrack < esd->GetNumberOfTracks(); iTrack++) { | |
755 | AliESDtrack* track = esd->GetTrack(iTrack); | |
756 | ||
757 | if (AcceptTrack(track)) | |
758 | acceptedTracks->Add(track); | |
759 | } | |
760 | ||
761 | return acceptedTracks; | |
762 | } | |
763 | ||
764 | //____________________________________________________________________ | |
765 | Int_t AliESDtrackCuts::CountAcceptedTracks(AliESD* esd) | |
766 | { | |
767 | // | |
768 | // returns an the number of tracks that pass the cuts | |
769 | // | |
770 | ||
771 | Int_t count = 0; | |
772 | ||
773 | // loop over esd tracks | |
774 | for (Int_t iTrack = 0; iTrack < esd->GetNumberOfTracks(); iTrack++) { | |
775 | AliESDtrack* track = esd->GetTrack(iTrack); | |
776 | ||
777 | if (AcceptTrack(track)) | |
778 | count++; | |
779 | } | |
780 | ||
781 | return count; | |
782 | } | |
783 | ||
784 | //____________________________________________________________________ | |
785 | TObjArray* AliESDtrackCuts::GetAcceptedTracks(AliESDEvent* esd) | |
786 | { | |
787 | // | |
788 | // returns an array of all tracks that pass the cuts | |
789 | // | |
790 | ||
791 | TObjArray* acceptedTracks = new TObjArray(); | |
792 | ||
793 | // loop over esd tracks | |
794 | for (Int_t iTrack = 0; iTrack < esd->GetNumberOfTracks(); iTrack++) { | |
795 | AliESDtrack* track = esd->GetTrack(iTrack); | |
796 | ||
797 | if (AcceptTrack(track)) | |
798 | acceptedTracks->Add(track); | |
799 | } | |
800 | ||
801 | return acceptedTracks; | |
802 | } | |
803 | ||
804 | //____________________________________________________________________ | |
805 | Int_t AliESDtrackCuts::CountAcceptedTracks(AliESDEvent* esd) | |
806 | { | |
807 | // | |
808 | // returns an the number of tracks that pass the cuts | |
809 | // | |
810 | ||
811 | Int_t count = 0; | |
812 | ||
813 | // loop over esd tracks | |
814 | for (Int_t iTrack = 0; iTrack < esd->GetNumberOfTracks(); iTrack++) { | |
815 | AliESDtrack* track = esd->GetTrack(iTrack); | |
816 | ||
817 | if (AcceptTrack(track)) | |
818 | count++; | |
819 | } | |
820 | ||
821 | return count; | |
822 | } | |
823 | ||
824 | //____________________________________________________________________ | |
825 | void AliESDtrackCuts::DefineHistograms(Int_t color) { | |
826 | // | |
827 | // diagnostics histograms are defined | |
828 | // | |
829 | ||
830 | fHistogramsOn=kTRUE; | |
831 | ||
832 | Bool_t oldStatus = TH1::AddDirectoryStatus(); | |
833 | TH1::AddDirectory(kFALSE); | |
834 | ||
835 | //################################################################################### | |
836 | // defining histograms | |
837 | ||
838 | fhCutStatistics = new TH1F("cut_statistics","cut statistics",kNCuts+4,-0.5,kNCuts+3.5); | |
839 | ||
840 | fhCutStatistics->GetXaxis()->SetBinLabel(1,"n tracks"); | |
841 | fhCutStatistics->GetXaxis()->SetBinLabel(2,"n cut tracks"); | |
842 | ||
843 | fhCutCorrelation = new TH2F("cut_correlation","cut correlation",kNCuts,-0.5,kNCuts-0.5,kNCuts,-0.5,kNCuts-0.5);; | |
844 | ||
845 | for (Int_t i=0; i<kNCuts; i++) { | |
846 | fhCutStatistics->GetXaxis()->SetBinLabel(i+4,fgkCutNames[i]); | |
847 | fhCutCorrelation->GetXaxis()->SetBinLabel(i+1,fgkCutNames[i]); | |
848 | fhCutCorrelation->GetYaxis()->SetBinLabel(i+1,fgkCutNames[i]); | |
849 | } | |
850 | ||
851 | fhCutStatistics ->SetLineColor(color); | |
852 | fhCutCorrelation ->SetLineColor(color); | |
853 | fhCutStatistics ->SetLineWidth(2); | |
854 | fhCutCorrelation ->SetLineWidth(2); | |
855 | ||
856 | Char_t str[256]; | |
857 | for (Int_t i=0; i<2; i++) { | |
858 | if (i==0) sprintf(str," "); | |
859 | else sprintf(str,"_cut"); | |
860 | ||
861 | fhNClustersITS[i] = new TH1F(Form("nClustersITS%s",str) ,"",8,-0.5,7.5); | |
862 | fhNClustersTPC[i] = new TH1F(Form("nClustersTPC%s",str) ,"",165,-0.5,164.5); | |
863 | fhChi2PerClusterITS[i] = new TH1F(Form("chi2PerClusterITS%s",str),"",500,0,10); | |
864 | fhChi2PerClusterTPC[i] = new TH1F(Form("chi2PerClusterTPC%s",str),"",500,0,10); | |
865 | ||
866 | fhC11[i] = new TH1F(Form("covMatrixDiagonal11%s",str),"",2000,0,20); | |
867 | fhC22[i] = new TH1F(Form("covMatrixDiagonal22%s",str),"",2000,0,20); | |
868 | fhC33[i] = new TH1F(Form("covMatrixDiagonal33%s",str),"",1000,0,1); | |
869 | fhC44[i] = new TH1F(Form("covMatrixDiagonal44%s",str),"",1000,0,5); | |
870 | fhC55[i] = new TH1F(Form("covMatrixDiagonal55%s",str),"",1000,0,5); | |
871 | ||
872 | fhDXY[i] = new TH1F(Form("dXY%s",str) ,"",500,-10,10); | |
873 | fhDZ[i] = new TH1F(Form("dZ%s",str) ,"",500,-10,10); | |
874 | fhDXYvsDZ[i] = new TH2F(Form("dXYvsDZ%s",str),"",200,-10,10,200,-10,10); | |
875 | ||
876 | fhDXYNormalized[i] = new TH1F(Form("dXYNormalized%s",str) ,"",500,-10,10); | |
877 | fhDZNormalized[i] = new TH1F(Form("dZNormalized%s",str) ,"",500,-10,10); | |
878 | fhDXYvsDZNormalized[i] = new TH2F(Form("dXYvsDZNormalized%s",str),"",200,-10,10,200,-10,10); | |
879 | ||
880 | fhNSigmaToVertex[i] = new TH1F(Form("nSigmaToVertex%s",str),"",500,0,50); | |
881 | ||
882 | fhPt[i] = new TH1F(Form("pt%s",str) ,"p_{T} distribution;p_{T} (GeV/c)",500,0.0,100.0); | |
883 | fhEta[i] = new TH1F(Form("eta%s",str) ,"#eta distribution;#eta",40,-2.0,2.0); | |
884 | ||
885 | fhNClustersITS[i]->SetTitle("n ITS clusters"); | |
886 | fhNClustersTPC[i]->SetTitle("n TPC clusters"); | |
887 | fhChi2PerClusterITS[i]->SetTitle("#Chi^{2} per ITS cluster"); | |
888 | fhChi2PerClusterTPC[i]->SetTitle("#Chi^{2} per TPC cluster"); | |
889 | ||
890 | fhC11[i]->SetTitle("cov 11 : #sigma_{y}^{2} [cm^{2}]"); | |
891 | fhC22[i]->SetTitle("cov 22 : #sigma_{z}^{2} [cm^{2}]"); | |
892 | fhC33[i]->SetTitle("cov 33 : #sigma_{sin(#phi)}^{2}"); | |
893 | fhC44[i]->SetTitle("cov 44 : #sigma_{tan(#theta_{dip})}^{2}"); | |
894 | fhC55[i]->SetTitle("cov 55 : #sigma_{1/p_{T}}^{2} [(c/GeV)^2]"); | |
895 | ||
896 | fhDXY[i]->SetTitle("transverse impact parameter"); | |
897 | fhDZ[i]->SetTitle("longitudinal impact parameter"); | |
898 | fhDXYvsDZ[i]->SetTitle("longitudinal impact parameter"); | |
899 | fhDXYvsDZ[i]->SetYTitle("transverse impact parameter"); | |
900 | ||
901 | fhDXYNormalized[i]->SetTitle("normalized trans impact par"); | |
902 | fhDZNormalized[i]->SetTitle("normalized long impact par"); | |
903 | fhDXYvsDZNormalized[i]->SetTitle("normalized long impact par"); | |
904 | fhDXYvsDZNormalized[i]->SetYTitle("normalized trans impact par"); | |
905 | fhNSigmaToVertex[i]->SetTitle("n #sigma to vertex"); | |
906 | ||
907 | fhNClustersITS[i]->SetLineColor(color); fhNClustersITS[i]->SetLineWidth(2); | |
908 | fhNClustersTPC[i]->SetLineColor(color); fhNClustersTPC[i]->SetLineWidth(2); | |
909 | fhChi2PerClusterITS[i]->SetLineColor(color); fhChi2PerClusterITS[i]->SetLineWidth(2); | |
910 | fhChi2PerClusterTPC[i]->SetLineColor(color); fhChi2PerClusterTPC[i]->SetLineWidth(2); | |
911 | ||
912 | fhC11[i]->SetLineColor(color); fhC11[i]->SetLineWidth(2); | |
913 | fhC22[i]->SetLineColor(color); fhC22[i]->SetLineWidth(2); | |
914 | fhC33[i]->SetLineColor(color); fhC33[i]->SetLineWidth(2); | |
915 | fhC44[i]->SetLineColor(color); fhC44[i]->SetLineWidth(2); | |
916 | fhC55[i]->SetLineColor(color); fhC55[i]->SetLineWidth(2); | |
917 | ||
918 | fhDXY[i]->SetLineColor(color); fhDXY[i]->SetLineWidth(2); | |
919 | fhDZ[i]->SetLineColor(color); fhDZ[i]->SetLineWidth(2); | |
920 | ||
921 | fhDXYNormalized[i]->SetLineColor(color); fhDXYNormalized[i]->SetLineWidth(2); | |
922 | fhDZNormalized[i]->SetLineColor(color); fhDZNormalized[i]->SetLineWidth(2); | |
923 | fhNSigmaToVertex[i]->SetLineColor(color); fhNSigmaToVertex[i]->SetLineWidth(2); | |
924 | } | |
925 | ||
926 | // The number of sigmas to the vertex is per definition gaussian | |
927 | ffDTheoretical = new TF1("nSigmaToVertexTheoretical","([0]/2.506628274)*exp(-(x**2)/2)",0,50); | |
928 | ffDTheoretical->SetParameter(0,1); | |
929 | ||
930 | TH1::AddDirectory(oldStatus); | |
931 | } | |
932 | ||
933 | //____________________________________________________________________ | |
934 | Bool_t AliESDtrackCuts::LoadHistograms(const Char_t* dir) | |
935 | { | |
936 | // | |
937 | // loads the histograms from a file | |
938 | // if dir is empty a directory with the name of this object is taken (like in SaveHistogram) | |
939 | // | |
940 | ||
941 | if (!dir) | |
942 | dir = GetName(); | |
943 | ||
944 | if (!gDirectory->cd(dir)) | |
945 | return kFALSE; | |
946 | ||
947 | ffDTheoretical = dynamic_cast<TF1*> (gDirectory->Get("nSigmaToVertexTheory")); | |
948 | ||
949 | fhCutStatistics = dynamic_cast<TH1F*> (gDirectory->Get("cut_statistics")); | |
950 | fhCutCorrelation = dynamic_cast<TH2F*> (gDirectory->Get("cut_correlation")); | |
951 | ||
952 | Char_t str[5]; | |
953 | for (Int_t i=0; i<2; i++) { | |
954 | if (i==0) | |
955 | { | |
956 | gDirectory->cd("before_cuts"); | |
957 | str[0] = 0; | |
958 | } | |
959 | else | |
960 | { | |
961 | gDirectory->cd("after_cuts"); | |
962 | sprintf(str,"_cut"); | |
963 | } | |
964 | ||
965 | fhNClustersITS[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("nClustersITS%s",str) )); | |
966 | fhNClustersTPC[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("nClustersTPC%s",str) )); | |
967 | fhChi2PerClusterITS[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("chi2PerClusterITS%s",str))); | |
968 | fhChi2PerClusterTPC[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("chi2PerClusterTPC%s",str))); | |
969 | ||
970 | fhC11[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("covMatrixDiagonal11%s",str))); | |
971 | fhC22[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("covMatrixDiagonal22%s",str))); | |
972 | fhC33[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("covMatrixDiagonal33%s",str))); | |
973 | fhC44[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("covMatrixDiagonal44%s",str))); | |
974 | fhC55[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("covMatrixDiagonal55%s",str))); | |
975 | ||
976 | fhDXY[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("dXY%s",str) )); | |
977 | fhDZ[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("dZ%s",str) )); | |
978 | fhDXYvsDZ[i] = dynamic_cast<TH2F*> (gDirectory->Get(Form("dXYvsDZ%s",str))); | |
979 | ||
980 | fhDXYNormalized[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("dXYNormalized%s",str) )); | |
981 | fhDZNormalized[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("dZNormalized%s",str) )); | |
982 | fhDXYvsDZNormalized[i] = dynamic_cast<TH2F*> (gDirectory->Get(Form("dXYvsDZNormalized%s",str))); | |
983 | fhNSigmaToVertex[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("nSigmaToVertex%s",str))); | |
984 | ||
985 | fhPt[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("pt%s",str))); | |
986 | fhEta[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("eta%s",str))); | |
987 | ||
988 | gDirectory->cd("../"); | |
989 | } | |
990 | ||
991 | gDirectory->cd(".."); | |
992 | ||
993 | return kTRUE; | |
994 | } | |
995 | ||
996 | //____________________________________________________________________ | |
997 | void AliESDtrackCuts::SaveHistograms(const Char_t* dir) { | |
998 | // | |
999 | // saves the histograms in a directory (dir) | |
1000 | // | |
1001 | ||
1002 | if (!fHistogramsOn) { | |
1003 | AliDebug(0, "Histograms not on - cannot save histograms!!!"); | |
1004 | return; | |
1005 | } | |
1006 | ||
1007 | if (!dir) | |
1008 | dir = GetName(); | |
1009 | ||
1010 | gDirectory->mkdir(dir); | |
1011 | gDirectory->cd(dir); | |
1012 | ||
1013 | gDirectory->mkdir("before_cuts"); | |
1014 | gDirectory->mkdir("after_cuts"); | |
1015 | ||
1016 | // a factor of 2 is needed since n sigma is positive | |
1017 | ffDTheoretical->SetParameter(0,2*fhNSigmaToVertex[0]->Integral("width")); | |
1018 | ffDTheoretical->Write("nSigmaToVertexTheory"); | |
1019 | ||
1020 | fhCutStatistics->Write(); | |
1021 | fhCutCorrelation->Write(); | |
1022 | ||
1023 | for (Int_t i=0; i<2; i++) { | |
1024 | if (i==0) | |
1025 | gDirectory->cd("before_cuts"); | |
1026 | else | |
1027 | gDirectory->cd("after_cuts"); | |
1028 | ||
1029 | fhNClustersITS[i] ->Write(); | |
1030 | fhNClustersTPC[i] ->Write(); | |
1031 | fhChi2PerClusterITS[i] ->Write(); | |
1032 | fhChi2PerClusterTPC[i] ->Write(); | |
1033 | ||
1034 | fhC11[i] ->Write(); | |
1035 | fhC22[i] ->Write(); | |
1036 | fhC33[i] ->Write(); | |
1037 | fhC44[i] ->Write(); | |
1038 | fhC55[i] ->Write(); | |
1039 | ||
1040 | fhDXY[i] ->Write(); | |
1041 | fhDZ[i] ->Write(); | |
1042 | fhDXYvsDZ[i] ->Write(); | |
1043 | ||
1044 | fhDXYNormalized[i] ->Write(); | |
1045 | fhDZNormalized[i] ->Write(); | |
1046 | fhDXYvsDZNormalized[i] ->Write(); | |
1047 | fhNSigmaToVertex[i] ->Write(); | |
1048 | ||
1049 | fhPt[i] ->Write(); | |
1050 | fhEta[i] ->Write(); | |
1051 | ||
1052 | gDirectory->cd("../"); | |
1053 | } | |
1054 | ||
1055 | gDirectory->cd("../"); | |
1056 | } | |
1057 | ||
1058 | //____________________________________________________________________ | |
1059 | void AliESDtrackCuts::DrawHistograms() | |
1060 | { | |
1061 | // draws some histograms | |
1062 | ||
1063 | TCanvas* canvas1 = new TCanvas(Form("%s_1", GetName()), "Track Quality Results1", 800, 800); | |
1064 | canvas1->Divide(2, 2); | |
1065 | ||
1066 | canvas1->cd(1); | |
1067 | fhNClustersTPC[0]->SetStats(kFALSE); | |
1068 | fhNClustersTPC[0]->Draw(); | |
1069 | ||
1070 | canvas1->cd(2); | |
1071 | fhChi2PerClusterTPC[0]->SetStats(kFALSE); | |
1072 | fhChi2PerClusterTPC[0]->Draw(); | |
1073 | ||
1074 | canvas1->cd(3); | |
1075 | fhNSigmaToVertex[0]->SetStats(kFALSE); | |
1076 | fhNSigmaToVertex[0]->GetXaxis()->SetRangeUser(0, 10); | |
1077 | fhNSigmaToVertex[0]->Draw(); | |
1078 | ||
1079 | canvas1->SaveAs(Form("%s_%s.gif", GetName(), canvas1->GetName())); | |
1080 | ||
1081 | TCanvas* canvas2 = new TCanvas(Form("%s_2", GetName()), "Track Quality Results2", 1200, 800); | |
1082 | canvas2->Divide(3, 2); | |
1083 | ||
1084 | canvas2->cd(1); | |
1085 | fhC11[0]->SetStats(kFALSE); | |
1086 | gPad->SetLogy(); | |
1087 | fhC11[0]->Draw(); | |
1088 | ||
1089 | canvas2->cd(2); | |
1090 | fhC22[0]->SetStats(kFALSE); | |
1091 | gPad->SetLogy(); | |
1092 | fhC22[0]->Draw(); | |
1093 | ||
1094 | canvas2->cd(3); | |
1095 | fhC33[0]->SetStats(kFALSE); | |
1096 | gPad->SetLogy(); | |
1097 | fhC33[0]->Draw(); | |
1098 | ||
1099 | canvas2->cd(4); | |
1100 | fhC44[0]->SetStats(kFALSE); | |
1101 | gPad->SetLogy(); | |
1102 | fhC44[0]->Draw(); | |
1103 | ||
1104 | canvas2->cd(5); | |
1105 | fhC55[0]->SetStats(kFALSE); | |
1106 | gPad->SetLogy(); | |
1107 | fhC55[0]->Draw(); | |
1108 | ||
1109 | canvas2->SaveAs(Form("%s_%s.gif", GetName(), canvas2->GetName())); | |
1110 | ||
1111 | TCanvas* canvas3 = new TCanvas(Form("%s_3", GetName()), "Track Quality Results3", 1200, 800); | |
1112 | canvas3->Divide(3, 2); | |
1113 | ||
1114 | canvas3->cd(1); | |
1115 | fhDXY[0]->SetStats(kFALSE); | |
1116 | gPad->SetLogy(); | |
1117 | fhDXY[0]->Draw(); | |
1118 | ||
1119 | canvas3->cd(2); | |
1120 | fhDZ[0]->SetStats(kFALSE); | |
1121 | gPad->SetLogy(); | |
1122 | fhDZ[0]->Draw(); | |
1123 | ||
1124 | canvas3->cd(3); | |
1125 | fhDXYvsDZ[0]->SetStats(kFALSE); | |
1126 | gPad->SetLogz(); | |
1127 | gPad->SetRightMargin(0.15); | |
1128 | fhDXYvsDZ[0]->Draw("COLZ"); | |
1129 | ||
1130 | canvas3->cd(4); | |
1131 | fhDXYNormalized[0]->SetStats(kFALSE); | |
1132 | gPad->SetLogy(); | |
1133 | fhDXYNormalized[0]->Draw(); | |
1134 | ||
1135 | canvas3->cd(5); | |
1136 | fhDZNormalized[0]->SetStats(kFALSE); | |
1137 | gPad->SetLogy(); | |
1138 | fhDZNormalized[0]->Draw(); | |
1139 | ||
1140 | canvas3->cd(6); | |
1141 | fhDXYvsDZNormalized[0]->SetStats(kFALSE); | |
1142 | gPad->SetLogz(); | |
1143 | gPad->SetRightMargin(0.15); | |
1144 | fhDXYvsDZNormalized[0]->Draw("COLZ"); | |
1145 | ||
1146 | canvas3->SaveAs(Form("%s_%s.gif", GetName(), canvas3->GetName())); | |
1147 | ||
1148 | TCanvas* canvas4 = new TCanvas(Form("%s_4", GetName()), "Track Quality Results4", 800, 500); | |
1149 | canvas4->Divide(2, 1); | |
1150 | ||
1151 | canvas4->cd(1); | |
1152 | fhCutStatistics->SetStats(kFALSE); | |
1153 | fhCutStatistics->LabelsOption("v"); | |
1154 | gPad->SetBottomMargin(0.3); | |
1155 | fhCutStatistics->Draw(); | |
1156 | ||
1157 | canvas4->cd(2); | |
1158 | fhCutCorrelation->SetStats(kFALSE); | |
1159 | fhCutCorrelation->LabelsOption("v"); | |
1160 | gPad->SetBottomMargin(0.3); | |
1161 | gPad->SetLeftMargin(0.3); | |
1162 | fhCutCorrelation->Draw("COLZ"); | |
1163 | ||
1164 | canvas4->SaveAs(Form("%s_%s.gif", GetName(), canvas4->GetName())); | |
1165 | ||
1166 | /*canvas->cd(1); | |
1167 | fhDXYvsDZNormalized[0]->SetStats(kFALSE); | |
1168 | fhDXYvsDZNormalized[0]->DrawCopy("COLZ"); | |
1169 | ||
1170 | canvas->cd(2); | |
1171 | fhNClustersTPC[0]->SetStats(kFALSE); | |
1172 | fhNClustersTPC[0]->DrawCopy(); | |
1173 | ||
1174 | canvas->cd(3); | |
1175 | fhChi2PerClusterITS[0]->SetStats(kFALSE); | |
1176 | fhChi2PerClusterITS[0]->DrawCopy(); | |
1177 | fhChi2PerClusterITS[1]->SetLineColor(2); | |
1178 | fhChi2PerClusterITS[1]->DrawCopy("SAME"); | |
1179 | ||
1180 | canvas->cd(4); | |
1181 | fhChi2PerClusterTPC[0]->SetStats(kFALSE); | |
1182 | fhChi2PerClusterTPC[0]->DrawCopy(); | |
1183 | fhChi2PerClusterTPC[1]->SetLineColor(2); | |
1184 | fhChi2PerClusterTPC[1]->DrawCopy("SAME");*/ | |
1185 | } | |
1186 |