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[u/mrichter/AliRoot.git] / PWG0 / esdTrackCuts / AliESDtrackCuts.cxx
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d560b581 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/* $Id$ */
17
0b75bef2 18#include "AliESDtrackCuts.h"
19
aa93c798 20
21#include <AliESDtrack.h>
22#include <AliESD.h>
23#include <AliLog.h>
3c4b53f0 24
5c495d37 25#include <TTree.h>
3c4b53f0 26#include <TCanvas.h>
d560b581 27#include <TDirectory.h>
aa93c798 28
0b75bef2 29//____________________________________________________________________
f58f1a93 30ClassImp(AliESDtrackCuts)
0b75bef2 31
ebd60d8e 32// Cut names
ab2c1f0d 33const Char_t* AliESDtrackCuts::fgkCutNames[kNCuts] = {
ebd60d8e 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",
ebd60d8e 48 "p",
49 "p_{T}",
50 "p_{x}",
51 "p_{y}",
52 "p_{z}",
53 "y",
54 "eta"
55};
56
0b75bef2 57//____________________________________________________________________
d8594d03 58AliESDtrackCuts::AliESDtrackCuts() : TNamed(),
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),
129a66bb 88 ffDTheoretical(0),
d8594d03 89 fhCutStatistics(0),
90 fhCutCorrelation(0)
91{
92 //
93 // default constructor
94 //
0b8a2421 95
96 Init();
d8594d03 97}
98
99//____________________________________________________________________
100AliESDtrackCuts::AliESDtrackCuts(Char_t* name, Char_t* title) : TNamed(name,title),
aa617804 101 fCutMinNClusterTPC(0),
102 fCutMinNClusterITS(0),
103 fCutMaxChi2PerClusterTPC(0),
104 fCutMaxChi2PerClusterITS(0),
105 fCutMaxC11(0),
106 fCutMaxC22(0),
107 fCutMaxC33(0),
108 fCutMaxC44(0),
109 fCutMaxC55(0),
110 fCutAcceptKinkDaughters(0),
111 fCutRequireTPCRefit(0),
112 fCutRequireITSRefit(0),
113 fCutNsigmaToVertex(0),
114 fCutSigmaToVertexRequired(0),
115 fPMin(0),
116 fPMax(0),
117 fPtMin(0),
118 fPtMax(0),
119 fPxMin(0),
120 fPxMax(0),
121 fPyMin(0),
122 fPyMax(0),
123 fPzMin(0),
124 fPzMax(0),
125 fEtaMin(0),
126 fEtaMax(0),
127 fRapMin(0),
128 fRapMax(0),
129 fHistogramsOn(0),
130 fhCutStatistics(0),
131 fhCutCorrelation(0)
ebd60d8e 132{
133 //
134 // constructor
135 //
136
137 Init();
0b75bef2 138
139 //##############################################################################
140 // setting default cuts
0b75bef2 141 SetMinNClustersTPC();
ebd60d8e 142 SetMinNClustersITS();
0b75bef2 143 SetMaxChi2PerClusterTPC();
144 SetMaxChi2PerClusterITS();
145 SetMaxCovDiagonalElements();
146 SetRequireTPCRefit();
147 SetRequireITSRefit();
148 SetAcceptKingDaughters();
149 SetMinNsigmaToVertex();
150 SetRequireSigmaToVertex();
151 SetPRange();
152 SetPtRange();
153 SetPxRange();
154 SetPyRange();
155 SetPzRange();
156 SetEtaRange();
157 SetRapRange();
158
159 SetHistogramsOn();
ebd60d8e 160}
161
162//_____________________________________________________________________________
3633478d 163AliESDtrackCuts::AliESDtrackCuts(const AliESDtrackCuts &c) : TNamed(c),
aa617804 164 fCutMinNClusterTPC(0),
165 fCutMinNClusterITS(0),
166 fCutMaxChi2PerClusterTPC(0),
167 fCutMaxChi2PerClusterITS(0),
168 fCutMaxC11(0),
169 fCutMaxC22(0),
170 fCutMaxC33(0),
171 fCutMaxC44(0),
172 fCutMaxC55(0),
173 fCutAcceptKinkDaughters(0),
174 fCutRequireTPCRefit(0),
175 fCutRequireITSRefit(0),
176 fCutNsigmaToVertex(0),
177 fCutSigmaToVertexRequired(0),
178 fPMin(0),
179 fPMax(0),
180 fPtMin(0),
181 fPtMax(0),
182 fPxMin(0),
183 fPxMax(0),
184 fPyMin(0),
185 fPyMax(0),
186 fPzMin(0),
187 fPzMax(0),
188 fEtaMin(0),
189 fEtaMax(0),
190 fRapMin(0),
191 fRapMax(0),
192 fHistogramsOn(0),
129a66bb 193 ffDTheoretical(0),
aa617804 194 fhCutStatistics(0),
195 fhCutCorrelation(0)
ebd60d8e 196{
197 //
198 // copy constructor
199 //
200
201 ((AliESDtrackCuts &) c).Copy(*this);
202}
203
204AliESDtrackCuts::~AliESDtrackCuts()
205{
206 //
207 // destructor
208 //
209
927c71e5 210 for (Int_t i=0; i<2; i++) {
211
212 if (fhNClustersITS[i])
213 delete fhNClustersITS[i];
214 if (fhNClustersTPC[i])
215 delete fhNClustersTPC[i];
216 if (fhChi2PerClusterITS[i])
217 delete fhChi2PerClusterITS[i];
218 if (fhChi2PerClusterTPC[i])
219 delete fhChi2PerClusterTPC[i];
220 if (fhC11[i])
221 delete fhC11[i];
222 if (fhC22[i])
223 delete fhC22[i];
224 if (fhC33[i])
225 delete fhC33[i];
226 if (fhC44[i])
227 delete fhC44[i];
228 if (fhC55[i])
229 delete fhC55[i];
230
231 if (fhDXY[i])
232 delete fhDXY[i];
233 if (fhDZ[i])
234 delete fhDZ[i];
235 if (fhDXYvsDZ[i])
236 delete fhDXYvsDZ[i];
237
238 if (fhDXYNormalized[i])
239 delete fhDXYNormalized[i];
240 if (fhDZNormalized[i])
3c4b53f0 241 delete fhDZNormalized[i];
927c71e5 242 if (fhDXYvsDZNormalized[i])
243 delete fhDXYvsDZNormalized[i];
129a66bb 244 if (fhNSigmaToVertex[i])
245 delete fhNSigmaToVertex[i];
927c71e5 246 }
3c4b53f0 247
129a66bb 248 if (ffDTheoretical)
249 delete ffDTheoretical;
927c71e5 250
251 if (fhCutStatistics)
252 delete fhCutStatistics;
253 if (fhCutCorrelation)
254 delete fhCutCorrelation;
ebd60d8e 255}
256
257void AliESDtrackCuts::Init()
258{
259 //
260 // sets everything to zero
261 //
262
ab2c1f0d 263 fCutMinNClusterTPC = 0;
264 fCutMinNClusterITS = 0;
ebd60d8e 265
ab2c1f0d 266 fCutMaxChi2PerClusterTPC = 0;
267 fCutMaxChi2PerClusterITS = 0;
ebd60d8e 268
ab2c1f0d 269 fCutMaxC11 = 0;
270 fCutMaxC22 = 0;
271 fCutMaxC33 = 0;
272 fCutMaxC44 = 0;
273 fCutMaxC55 = 0;
ebd60d8e 274
ab2c1f0d 275 fCutAcceptKinkDaughters = 0;
276 fCutRequireTPCRefit = 0;
277 fCutRequireITSRefit = 0;
ebd60d8e 278
ab2c1f0d 279 fCutNsigmaToVertex = 0;
280 fCutSigmaToVertexRequired = 0;
ebd60d8e 281
282 fPMin = 0;
283 fPMax = 0;
284 fPtMin = 0;
285 fPtMax = 0;
286 fPxMin = 0;
287 fPxMax = 0;
288 fPyMin = 0;
289 fPyMax = 0;
290 fPzMin = 0;
291 fPzMax = 0;
292 fEtaMin = 0;
293 fEtaMax = 0;
294 fRapMin = 0;
295 fRapMax = 0;
296
297 fHistogramsOn = kFALSE;
298
299 for (Int_t i=0; i<2; ++i)
300 {
301 fhNClustersITS[i] = 0;
302 fhNClustersTPC[i] = 0;
303
304 fhChi2PerClusterITS[i] = 0;
305 fhChi2PerClusterTPC[i] = 0;
306
307 fhC11[i] = 0;
308 fhC22[i] = 0;
309 fhC33[i] = 0;
310 fhC44[i] = 0;
311 fhC55[i] = 0;
312
313 fhDXY[i] = 0;
314 fhDZ[i] = 0;
315 fhDXYvsDZ[i] = 0;
316
317 fhDXYNormalized[i] = 0;
318 fhDZNormalized[i] = 0;
319 fhDXYvsDZNormalized[i] = 0;
129a66bb 320 fhNSigmaToVertex[i] = 0;
ebd60d8e 321 }
129a66bb 322 ffDTheoretical = 0;
ebd60d8e 323
324 fhCutStatistics = 0;
325 fhCutCorrelation = 0;
326}
327
328//_____________________________________________________________________________
329AliESDtrackCuts &AliESDtrackCuts::operator=(const AliESDtrackCuts &c)
330{
331 //
332 // Assignment operator
333 //
0b75bef2 334
ebd60d8e 335 if (this != &c) ((AliESDtrackCuts &) c).Copy(*this);
336 return *this;
337}
338
339//_____________________________________________________________________________
340void AliESDtrackCuts::Copy(TObject &c) const
341{
342 //
343 // Copy function
344 //
345
346 AliESDtrackCuts& target = (AliESDtrackCuts &) c;
347
348 target.Init();
349
ab2c1f0d 350 target.fCutMinNClusterTPC = fCutMinNClusterTPC;
351 target.fCutMinNClusterITS = fCutMinNClusterITS;
ebd60d8e 352
ab2c1f0d 353 target.fCutMaxChi2PerClusterTPC = fCutMaxChi2PerClusterTPC;
354 target.fCutMaxChi2PerClusterITS = fCutMaxChi2PerClusterITS;
ebd60d8e 355
ab2c1f0d 356 target.fCutMaxC11 = fCutMaxC11;
357 target.fCutMaxC22 = fCutMaxC22;
358 target.fCutMaxC33 = fCutMaxC33;
359 target.fCutMaxC44 = fCutMaxC44;
360 target.fCutMaxC55 = fCutMaxC55;
ebd60d8e 361
ab2c1f0d 362 target.fCutAcceptKinkDaughters = fCutAcceptKinkDaughters;
363 target.fCutRequireTPCRefit = fCutRequireTPCRefit;
364 target.fCutRequireITSRefit = fCutRequireITSRefit;
ebd60d8e 365
ab2c1f0d 366 target.fCutNsigmaToVertex = fCutNsigmaToVertex;
367 target.fCutSigmaToVertexRequired = fCutSigmaToVertexRequired;
ebd60d8e 368
369 target.fPMin = fPMin;
370 target.fPMax = fPMax;
371 target.fPtMin = fPtMin;
372 target.fPtMax = fPtMax;
373 target.fPxMin = fPxMin;
374 target.fPxMax = fPxMax;
375 target.fPyMin = fPyMin;
376 target.fPyMax = fPyMax;
377 target.fPzMin = fPzMin;
378 target.fPzMax = fPzMax;
379 target.fEtaMin = fEtaMin;
380 target.fEtaMax = fEtaMax;
381 target.fRapMin = fRapMin;
382 target.fRapMax = fRapMax;
383
384 target.fHistogramsOn = fHistogramsOn;
385
386 for (Int_t i=0; i<2; ++i)
387 {
388 if (fhNClustersITS[i]) target.fhNClustersITS[i] = (TH1F*) fhNClustersITS[i]->Clone();
389 if (fhNClustersTPC[i]) target.fhNClustersTPC[i] = (TH1F*) fhNClustersTPC[i]->Clone();
390
391 if (fhChi2PerClusterITS[i]) target.fhChi2PerClusterITS[i] = (TH1F*) fhChi2PerClusterITS[i]->Clone();
392 if (fhChi2PerClusterTPC[i]) target.fhChi2PerClusterTPC[i] = (TH1F*) fhChi2PerClusterTPC[i]->Clone();
393
394 if (fhC11[i]) target.fhC11[i] = (TH1F*) fhC11[i]->Clone();
395 if (fhC22[i]) target.fhC22[i] = (TH1F*) fhC22[i]->Clone();
396 if (fhC33[i]) target.fhC33[i] = (TH1F*) fhC33[i]->Clone();
397 if (fhC44[i]) target.fhC44[i] = (TH1F*) fhC44[i]->Clone();
398 if (fhC55[i]) target.fhC55[i] = (TH1F*) fhC55[i]->Clone();
399
400 if (fhDXY[i]) target.fhDXY[i] = (TH1F*) fhDXY[i]->Clone();
401 if (fhDZ[i]) target.fhDZ[i] = (TH1F*) fhDZ[i]->Clone();
402 if (fhDXYvsDZ[i]) target.fhDXYvsDZ[i] = (TH2F*) fhDXYvsDZ[i]->Clone();
403
404 if (fhDXYNormalized[i]) target.fhDXYNormalized[i] = (TH1F*) fhDXYNormalized[i]->Clone();
405 if (fhDZNormalized[i]) target.fhDZNormalized[i] = (TH1F*) fhDZNormalized[i]->Clone();
406 if (fhDXYvsDZNormalized[i]) target.fhDXYvsDZNormalized[i] = (TH2F*) fhDXYvsDZNormalized[i]->Clone();
129a66bb 407 if (fhNSigmaToVertex[i]) target.fhNSigmaToVertex[i] = (TH1F*) fhNSigmaToVertex[i]->Clone();
ebd60d8e 408 }
129a66bb 409 if (ffDTheoretical) target.ffDTheoretical = (TF1*) ffDTheoretical->Clone();
ebd60d8e 410
411 if (fhCutStatistics) target.fhCutStatistics = (TH1F*) fhCutStatistics->Clone();
412 if (fhCutCorrelation) target.fhCutCorrelation = (TH2F*) fhCutCorrelation->Clone();
0b75bef2 413
0b8a2421 414 TNamed::Copy(c);
0b75bef2 415}
416
927c71e5 417//_____________________________________________________________________________
418Long64_t AliESDtrackCuts::Merge(TCollection* list) {
419 // Merge a list of AliESDtrackCuts objects with this (needed for PROOF)
420 // Returns the number of merged objects (including this)
421
422 if (!list)
423 return 0;
424
425 if (list->IsEmpty())
426 return 1;
427
428 if (!fHistogramsOn)
429 return 0;
430
431 TIterator* iter = list->MakeIterator();
432 TObject* obj;
433
434
435 // collection of measured and generated histograms
436 Int_t count = 0;
437 while ((obj = iter->Next())) {
438
439 AliESDtrackCuts* entry = dynamic_cast<AliESDtrackCuts*>(obj);
440 if (entry == 0)
441 continue;
442
443 if (!entry->fHistogramsOn)
444 continue;
445
446 for (Int_t i=0; i<2; i++) {
447
448 fhNClustersITS[i] ->Add(entry->fhNClustersITS[i] );
449 fhNClustersTPC[i] ->Add(entry->fhNClustersTPC[i] );
450
451 fhChi2PerClusterITS[i] ->Add(entry->fhChi2PerClusterITS[i]);
452 fhChi2PerClusterTPC[i] ->Add(entry->fhChi2PerClusterTPC[i]);
453
454 fhC11[i] ->Add(entry->fhC11[i] );
455 fhC22[i] ->Add(entry->fhC22[i] );
456 fhC33[i] ->Add(entry->fhC33[i] );
457 fhC44[i] ->Add(entry->fhC44[i] );
458 fhC55[i] ->Add(entry->fhC55[i] );
459
460 fhDXY[i] ->Add(entry->fhDXY[i] );
461 fhDZ[i] ->Add(entry->fhDZ[i] );
462 fhDXYvsDZ[i] ->Add(entry->fhDXYvsDZ[i] );
463
464 fhDXYNormalized[i] ->Add(entry->fhDXYNormalized[i] );
3c4b53f0 465 fhDZNormalized[i] ->Add(entry->fhDZNormalized[i] );
927c71e5 466 fhDXYvsDZNormalized[i] ->Add(entry->fhDXYvsDZNormalized[i]);
129a66bb 467 fhNSigmaToVertex[i] ->Add(entry->fhNSigmaToVertex[i]);
468
927c71e5 469 }
470
471 fhCutStatistics ->Add(entry->fhCutStatistics);
472 fhCutCorrelation ->Add(entry->fhCutCorrelation);
473
474 count++;
475 }
476
477 return count+1;
478}
479
480
0b75bef2 481//____________________________________________________________________
2b9019e4 482Float_t AliESDtrackCuts::GetSigmaToVertex(AliESDtrack* esdTrack)
483{
129a66bb 484 // Calculates the number of sigma to the vertex.
2b9019e4 485
486 Float_t b[2];
487 Float_t bRes[2];
488 Float_t bCov[3];
489 esdTrack->GetImpactParameters(b,bCov);
490 if (bCov[0]<=0 || bCov[2]<=0) {
491 AliDebug(1, "Estimated b resolution lower or equal zero!");
492 bCov[0]=0; bCov[2]=0;
493 }
494 bRes[0] = TMath::Sqrt(bCov[0]);
495 bRes[1] = TMath::Sqrt(bCov[2]);
496
497 // -----------------------------------
498 // How to get to a n-sigma cut?
499 //
500 // The accumulated statistics from 0 to d is
501 //
502 // -> Erf(d/Sqrt(2)) for a 1-dim gauss (d = n_sigma)
503 // -> 1 - Exp(-d**2) for a 2-dim gauss (d*d = dx*dx + dy*dy != n_sigma)
504 //
505 // It means that for a 2-dim gauss: n_sigma(d) = Sqrt(2)*ErfInv(1 - Exp((-x**2)/2)
506 // Can this be expressed in a different way?
2b9019e4 507
508 if (bRes[0] == 0 || bRes[1] ==0)
509 return -1;
510
511 Float_t d = TMath::Sqrt(TMath::Power(b[0]/bRes[0],2) + TMath::Power(b[1]/bRes[1],2));
512
513 // stupid rounding problem screws up everything:
514 // if d is too big, TMath::Exp(...) gets 0, and TMath::ErfInverse(1) that should be infinite, gets 0 :(
515 if (TMath::Exp(-d * d / 2) < 1e-10)
516 return 1000;
517
518 d = TMath::ErfInverse(1 - TMath::Exp(-d * d / 2)) * TMath::Sqrt(2);
519 return d;
520}
521
5c495d37 522void AliESDtrackCuts::EnableNeededBranches(TTree* tree)
523{
524 // enables the branches needed by AcceptTrack, for a list see comment of AcceptTrack
525
526 tree->SetBranchStatus("fTracks.fFlags", 1);
527 tree->SetBranchStatus("fTracks.fITSncls", 1);
528 tree->SetBranchStatus("fTracks.fTPCncls", 1);
529 tree->SetBranchStatus("fTracks.fITSchi2", 1);
530 tree->SetBranchStatus("fTracks.fTPCchi2", 1);
531 tree->SetBranchStatus("fTracks.fC*", 1);
532 tree->SetBranchStatus("fTracks.fD", 1);
533 tree->SetBranchStatus("fTracks.fZ", 1);
534 tree->SetBranchStatus("fTracks.fCdd", 1);
535 tree->SetBranchStatus("fTracks.fCdz", 1);
536 tree->SetBranchStatus("fTracks.fCzz", 1);
537 tree->SetBranchStatus("fTracks.fP*", 1);
538 tree->SetBranchStatus("fTracks.fR*", 1);
539 tree->SetBranchStatus("fTracks.fKinkIndexes*", 1);
540}
541
2b9019e4 542//____________________________________________________________________
543Bool_t
0b75bef2 544AliESDtrackCuts::AcceptTrack(AliESDtrack* esdTrack) {
545 //
546 // figure out if the tracks survives all the track cuts defined
547 //
ab2c1f0d 548 // the different quality parameter and kinematic values are first
549 // retrieved from the track. then it is found out what cuts the
550 // track did not survive and finally the cuts are imposed.
0b75bef2 551
5c495d37 552 // this function needs the following branches:
553 // fTracks.fFlags
554 // fTracks.fITSncls
555 // fTracks.fTPCncls
556 // fTracks.fITSchi2
557 // fTracks.fTPCchi2
558 // fTracks.fC //GetExternalCovariance
559 // fTracks.fD //GetImpactParameters
560 // fTracks.fZ //GetImpactParameters
561 // fTracks.fCdd //GetImpactParameters
562 // fTracks.fCdz //GetImpactParameters
563 // fTracks.fCzz //GetImpactParameters
564 // fTracks.fP //GetPxPyPz
565 // fTracks.fR //GetMass
566 // fTracks.fP //GetMass
567 // fTracks.fKinkIndexes
1ae6c515 568
0b75bef2 569 UInt_t status = esdTrack->GetStatus();
ebd60d8e 570
571 // dummy array
572 Int_t fIdxInt[200];
573
0b75bef2 574 // getting quality parameters from the ESD track
575 Int_t nClustersITS = esdTrack->GetITSclusters(fIdxInt);
576 Int_t nClustersTPC = esdTrack->GetTPCclusters(fIdxInt);
577
1ae6c515 578
579
0b75bef2 580 Float_t chi2PerClusterITS = -1;
581 Float_t chi2PerClusterTPC = -1;
582 if (nClustersITS!=0)
583 chi2PerClusterITS = esdTrack->GetITSchi2()/Float_t(nClustersITS);
584 if (nClustersTPC!=0)
5c495d37 585 chi2PerClusterTPC = esdTrack->GetTPCchi2()/Float_t(nClustersTPC);
0b75bef2 586
587 Double_t extCov[15];
ebd60d8e 588 esdTrack->GetExternalCovariance(extCov);
0b75bef2 589
590 // getting the track to vertex parameters
2b9019e4 591 Float_t nSigmaToVertex = GetSigmaToVertex(esdTrack);
0b75bef2 592
2b9019e4 593 // getting the kinematic variables of the track
0b75bef2 594 // (assuming the mass is known)
595 Double_t p[3];
596 esdTrack->GetPxPyPz(p);
597 Float_t momentum = TMath::Sqrt(TMath::Power(p[0],2) + TMath::Power(p[1],2) + TMath::Power(p[2],2));
598 Float_t pt = TMath::Sqrt(TMath::Power(p[0],2) + TMath::Power(p[1],2));
599 Float_t energy = TMath::Sqrt(TMath::Power(esdTrack->GetMass(),2) + TMath::Power(momentum,2));
600
1ae6c515 601
0b75bef2 602 //y-eta related calculations
603 Float_t eta = -100.;
604 Float_t y = -100.;
605 if((momentum != TMath::Abs(p[2]))&&(momentum != 0))
606 eta = 0.5*TMath::Log((momentum + p[2])/(momentum - p[2]));
607 if((energy != TMath::Abs(p[2]))&&(momentum != 0))
608 y = 0.5*TMath::Log((energy + p[2])/(energy - p[2]));
609
610
611 //########################################################################
612 // cut the track?
613
ebd60d8e 614 Bool_t cuts[kNCuts];
615 for (Int_t i=0; i<kNCuts; i++) cuts[i]=kFALSE;
0b75bef2 616
617 // track quality cuts
ab2c1f0d 618 if (fCutRequireTPCRefit && (status&AliESDtrack::kTPCrefit)==0)
0b75bef2 619 cuts[0]=kTRUE;
ab2c1f0d 620 if (fCutRequireITSRefit && (status&AliESDtrack::kITSrefit)==0)
0b75bef2 621 cuts[1]=kTRUE;
2b9019e4 622 if (nClustersTPC<fCutMinNClusterTPC)
0b75bef2 623 cuts[2]=kTRUE;
ab2c1f0d 624 if (nClustersITS<fCutMinNClusterITS)
0b75bef2 625 cuts[3]=kTRUE;
ab2c1f0d 626 if (chi2PerClusterTPC>fCutMaxChi2PerClusterTPC)
0b75bef2 627 cuts[4]=kTRUE;
ab2c1f0d 628 if (chi2PerClusterITS>fCutMaxChi2PerClusterITS)
0b75bef2 629 cuts[5]=kTRUE;
ab2c1f0d 630 if (extCov[0] > fCutMaxC11)
0b75bef2 631 cuts[6]=kTRUE;
ab2c1f0d 632 if (extCov[2] > fCutMaxC22)
0b75bef2 633 cuts[7]=kTRUE;
ab2c1f0d 634 if (extCov[5] > fCutMaxC33)
0b75bef2 635 cuts[8]=kTRUE;
ab2c1f0d 636 if (extCov[9] > fCutMaxC44)
0b75bef2 637 cuts[9]=kTRUE;
ab2c1f0d 638 if (extCov[14] > fCutMaxC55)
0b75bef2 639 cuts[10]=kTRUE;
2b9019e4 640 if (nSigmaToVertex > fCutNsigmaToVertex)
0b75bef2 641 cuts[11] = kTRUE;
642 // if n sigma could not be calculated
10ebe68d 643 if (nSigmaToVertex<0 && fCutSigmaToVertexRequired)
0b75bef2 644 cuts[12]=kTRUE;
5c495d37 645 if (!fCutAcceptKinkDaughters && esdTrack->GetKinkIndex(0)>0)
0b75bef2 646 cuts[13]=kTRUE;
647 // track kinematics cut
648 if((momentum < fPMin) || (momentum > fPMax))
649 cuts[14]=kTRUE;
650 if((pt < fPtMin) || (pt > fPtMax))
651 cuts[15] = kTRUE;
652 if((p[0] < fPxMin) || (p[0] > fPxMax))
653 cuts[16] = kTRUE;
654 if((p[1] < fPyMin) || (p[1] > fPyMax))
655 cuts[17] = kTRUE;
2b9019e4 656 if((p[2] < fPzMin) || (p[2] > fPzMax))
0b75bef2 657 cuts[18] = kTRUE;
658 if((eta < fEtaMin) || (eta > fEtaMax))
659 cuts[19] = kTRUE;
660 if((y < fRapMin) || (y > fRapMax))
661 cuts[20] = kTRUE;
662
663 Bool_t cut=kFALSE;
ebd60d8e 664 for (Int_t i=0; i<kNCuts; i++)
0b75bef2 665 if (cuts[i]) cut = kTRUE;
666
667 //########################################################################
668 // filling histograms
669 if (fHistogramsOn) {
f58f1a93 670 fhCutStatistics->Fill(fhCutStatistics->GetBinCenter(fhCutStatistics->GetXaxis()->FindBin("n tracks")));
0b75bef2 671
672 if (cut)
f58f1a93 673 fhCutStatistics->Fill(fhCutStatistics->GetBinCenter(fhCutStatistics->GetXaxis()->FindBin("n cut tracks")));
0b75bef2 674
ebd60d8e 675 for (Int_t i=0; i<kNCuts; i++) {
0b75bef2 676 if (cuts[i])
ab2c1f0d 677 fhCutStatistics->Fill(fhCutStatistics->GetBinCenter(fhCutStatistics->GetXaxis()->FindBin(fgkCutNames[i])));
0b75bef2 678
ebd60d8e 679 for (Int_t j=i; j<kNCuts; j++) {
0b75bef2 680 if (cuts[i] && cuts[j]) {
ab2c1f0d 681 Float_t x = fhCutCorrelation->GetXaxis()->GetBinCenter(fhCutCorrelation->GetXaxis()->FindBin(fgkCutNames[i]));
682 Float_t y = fhCutCorrelation->GetYaxis()->GetBinCenter(fhCutCorrelation->GetYaxis()->FindBin(fgkCutNames[j]));
f58f1a93 683 fhCutCorrelation->Fill(x,y);
0b75bef2 684 }
685 }
686 }
687
688
2b9019e4 689 fhNClustersITS[0]->Fill(nClustersITS);
690 fhNClustersTPC[0]->Fill(nClustersTPC);
f58f1a93 691 fhChi2PerClusterITS[0]->Fill(chi2PerClusterITS);
2b9019e4 692 fhChi2PerClusterTPC[0]->Fill(chi2PerClusterTPC);
693
694 fhC11[0]->Fill(extCov[0]);
695 fhC22[0]->Fill(extCov[2]);
696 fhC33[0]->Fill(extCov[5]);
697 fhC44[0]->Fill(extCov[9]);
698 fhC55[0]->Fill(extCov[14]);
699
700 Float_t b[2];
701 Float_t bRes[2];
702 Float_t bCov[3];
703 esdTrack->GetImpactParameters(b,bCov);
704 if (bCov[0]<=0 || bCov[2]<=0) {
705 AliDebug(1, "Estimated b resolution lower or equal zero!");
706 bCov[0]=0; bCov[2]=0;
707 }
708 bRes[0] = TMath::Sqrt(bCov[0]);
709 bRes[1] = TMath::Sqrt(bCov[2]);
710
711 fhDZ[0]->Fill(b[1]);
712 fhDXY[0]->Fill(b[0]);
f58f1a93 713 fhDXYvsDZ[0]->Fill(b[1],b[0]);
0b75bef2 714
715 if (bRes[0]!=0 && bRes[1]!=0) {
10ebe68d 716 fhDZNormalized[0]->Fill(b[1]/bRes[1]);
2b9019e4 717 fhDXYNormalized[0]->Fill(b[0]/bRes[0]);
f58f1a93 718 fhDXYvsDZNormalized[0]->Fill(b[1]/bRes[1], b[0]/bRes[0]);
129a66bb 719 fhNSigmaToVertex[0]->Fill(nSigmaToVertex);
0b75bef2 720 }
721 }
722
2b9019e4 723 //########################################################################
0b75bef2 724 // cut the track!
725 if (cut) return kFALSE;
726
2b9019e4 727 //########################################################################
0b75bef2 728 // filling histograms after cut
729 if (fHistogramsOn) {
2b9019e4 730 fhNClustersITS[1]->Fill(nClustersITS);
731 fhNClustersTPC[1]->Fill(nClustersTPC);
f58f1a93 732 fhChi2PerClusterITS[1]->Fill(chi2PerClusterITS);
2b9019e4 733 fhChi2PerClusterTPC[1]->Fill(chi2PerClusterTPC);
734
735 fhC11[1]->Fill(extCov[0]);
736 fhC22[1]->Fill(extCov[2]);
10ebe68d 737 fhC33[1]->Fill(extCov[5]);
2b9019e4 738 fhC44[1]->Fill(extCov[9]);
739 fhC55[1]->Fill(extCov[14]);
740
741 Float_t b[2];
742 Float_t bRes[2];
743 Float_t bCov[3];
744 esdTrack->GetImpactParameters(b,bCov);
745 if (bCov[0]<=0 || bCov[2]<=0) {
746 AliDebug(1, "Estimated b resolution lower or equal zero!");
747 bCov[0]=0; bCov[2]=0;
748 }
749 bRes[0] = TMath::Sqrt(bCov[0]);
750 bRes[1] = TMath::Sqrt(bCov[2]);
751
752 fhDZ[1]->Fill(b[1]);
753 fhDXY[1]->Fill(b[0]);
f58f1a93 754 fhDXYvsDZ[1]->Fill(b[1],b[0]);
0b75bef2 755
10ebe68d 756 if (bRes[0]!=0 && bRes[1]!=0)
757 {
758 fhDZNormalized[1]->Fill(b[1]/bRes[1]);
759 fhDXYNormalized[1]->Fill(b[0]/bRes[0]);
760 fhDXYvsDZNormalized[1]->Fill(b[1]/bRes[1], b[0]/bRes[0]);
129a66bb 761 fhNSigmaToVertex[1]->Fill(nSigmaToVertex);
10ebe68d 762 }
0b75bef2 763 }
2b9019e4 764
0b75bef2 765 return kTRUE;
766}
767
768//____________________________________________________________________
769TObjArray*
ebd60d8e 770AliESDtrackCuts::GetAcceptedTracks(AliESD* esd)
771{
772 //
0b75bef2 773 // returns an array of all tracks that pass the cuts
ebd60d8e 774 //
775
776 TObjArray* acceptedTracks = new TObjArray();
c5858666 777
0b75bef2 778 // loop over esd tracks
779 for (Int_t iTrack = 0; iTrack < esd->GetNumberOfTracks(); iTrack++) {
780 AliESDtrack* track = esd->GetTrack(iTrack);
c5858666 781
ebd60d8e 782 if (AcceptTrack(track))
783 acceptedTracks->Add(track);
0b75bef2 784 }
785
ebd60d8e 786 return acceptedTracks;
0b75bef2 787}
788
c5858666 789//____________________________________________________________________
790Int_t
791AliESDtrackCuts::CountAcceptedTracks(AliESD* esd)
792{
793 //
794 // returns an the number of tracks that pass the cuts
795 //
796
797 Int_t count = 0;
798
799 // loop over esd tracks
800 for (Int_t iTrack = 0; iTrack < esd->GetNumberOfTracks(); iTrack++) {
801 AliESDtrack* track = esd->GetTrack(iTrack);
802
803 if (AcceptTrack(track))
804 count++;
805 }
806
807 return count;
808}
809
0b75bef2 810//____________________________________________________________________
f58f1a93 811 void AliESDtrackCuts::DefineHistograms(Int_t color) {
ab2c1f0d 812 //
813 // diagnostics histograms are defined
814 //
0b75bef2 815
f58f1a93 816 fHistogramsOn=kTRUE;
3c4b53f0 817
818 Bool_t oldStatus = TH1::AddDirectoryStatus();
819 TH1::AddDirectory(kFALSE);
820
ab2c1f0d 821 //###################################################################################
f58f1a93 822 // defining histograms
0b75bef2 823
ebd60d8e 824 fhCutStatistics = new TH1F("cut_statistics","cut statistics",kNCuts+4,-0.5,kNCuts+3.5);
0b75bef2 825
f58f1a93 826 fhCutStatistics->GetXaxis()->SetBinLabel(1,"n tracks");
827 fhCutStatistics->GetXaxis()->SetBinLabel(2,"n cut tracks");
0b75bef2 828
ebd60d8e 829 fhCutCorrelation = new TH2F("cut_correlation","cut correlation",kNCuts,-0.5,kNCuts-0.5,kNCuts,-0.5,kNCuts-0.5);;
0b75bef2 830
ebd60d8e 831 for (Int_t i=0; i<kNCuts; i++) {
ab2c1f0d 832 fhCutStatistics->GetXaxis()->SetBinLabel(i+4,fgkCutNames[i]);
833 fhCutCorrelation->GetXaxis()->SetBinLabel(i+1,fgkCutNames[i]);
834 fhCutCorrelation->GetYaxis()->SetBinLabel(i+1,fgkCutNames[i]);
f58f1a93 835 }
836
837 fhCutStatistics ->SetLineColor(color);
838 fhCutCorrelation ->SetLineColor(color);
839 fhCutStatistics ->SetLineWidth(2);
840 fhCutCorrelation ->SetLineWidth(2);
841
0b75bef2 842 Char_t str[256];
843 for (Int_t i=0; i<2; i++) {
844 if (i==0) sprintf(str," ");
845 else sprintf(str,"_cut");
846
3c4b53f0 847 fhNClustersITS[i] = new TH1F(Form("nClustersITS%s",str) ,"",8,-0.5,7.5);
848 fhNClustersTPC[i] = new TH1F(Form("nClustersTPC%s",str) ,"",165,-0.5,164.5);
ebd60d8e 849 fhChi2PerClusterITS[i] = new TH1F(Form("chi2PerClusterITS%s",str),"",500,0,10);
850 fhChi2PerClusterTPC[i] = new TH1F(Form("chi2PerClusterTPC%s",str),"",500,0,10);
851
3c4b53f0 852 fhC11[i] = new TH1F(Form("covMatrixDiagonal11%s",str),"",2000,0,20);
d8594d03 853 fhC22[i] = new TH1F(Form("covMatrixDiagonal22%s",str),"",2000,0,20);
854 fhC33[i] = new TH1F(Form("covMatrixDiagonal33%s",str),"",1000,0,1);
ebd60d8e 855 fhC44[i] = new TH1F(Form("covMatrixDiagonal44%s",str),"",1000,0,5);
856 fhC55[i] = new TH1F(Form("covMatrixDiagonal55%s",str),"",1000,0,5);
857
3c4b53f0 858 fhDXY[i] = new TH1F(Form("dXY%s",str) ,"",500,-10,10);
859 fhDZ[i] = new TH1F(Form("dZ%s",str) ,"",500,-10,10);
ebd60d8e 860 fhDXYvsDZ[i] = new TH2F(Form("dXYvsDZ%s",str),"",200,-10,10,200,-10,10);
861
3c4b53f0 862 fhDXYNormalized[i] = new TH1F(Form("dXYNormalized%s",str) ,"",500,-10,10);
863 fhDZNormalized[i] = new TH1F(Form("dZNormalized%s",str) ,"",500,-10,10);
ebd60d8e 864 fhDXYvsDZNormalized[i] = new TH2F(Form("dXYvsDZNormalized%s",str),"",200,-10,10,200,-10,10);
865
129a66bb 866 fhNSigmaToVertex[i] = new TH1F(Form("nSigmaToVertex%s",str),"",500,0,50);
ebd60d8e 867
3c4b53f0 868 fhNClustersITS[i]->SetTitle("n ITS clusters");
869 fhNClustersTPC[i]->SetTitle("n TPC clusters");
870 fhChi2PerClusterITS[i]->SetTitle("#Chi^{2} per ITS cluster");
871 fhChi2PerClusterTPC[i]->SetTitle("#Chi^{2} per TPC cluster");
ebd60d8e 872
3c4b53f0 873 fhC11[i]->SetTitle("cov 11 : #sigma_{y}^{2} [cm^{2}]");
874 fhC22[i]->SetTitle("cov 22 : #sigma_{z}^{2} [cm^{2}]");
875 fhC33[i]->SetTitle("cov 33 : #sigma_{sin(#phi)}^{2}");
876 fhC44[i]->SetTitle("cov 44 : #sigma_{tan(#theta_{dip})}^{2}");
877 fhC55[i]->SetTitle("cov 55 : #sigma_{1/p_{T}}^{2} [(c/GeV)^2]");
ebd60d8e 878
3c4b53f0 879 fhDXY[i]->SetTitle("transverse impact parameter");
880 fhDZ[i]->SetTitle("longitudinal impact parameter");
881 fhDXYvsDZ[i]->SetTitle("longitudinal impact parameter");
ebd60d8e 882 fhDXYvsDZ[i]->SetYTitle("transverse impact parameter");
883
3c4b53f0 884 fhDXYNormalized[i]->SetTitle("normalized trans impact par");
885 fhDZNormalized[i]->SetTitle("normalized long impact par");
886 fhDXYvsDZNormalized[i]->SetTitle("normalized long impact par");
ebd60d8e 887 fhDXYvsDZNormalized[i]->SetYTitle("normalized trans impact par");
3c4b53f0 888 fhNSigmaToVertex[i]->SetTitle("n #sigma to vertex");
ebd60d8e 889
890 fhNClustersITS[i]->SetLineColor(color); fhNClustersITS[i]->SetLineWidth(2);
891 fhNClustersTPC[i]->SetLineColor(color); fhNClustersTPC[i]->SetLineWidth(2);
892 fhChi2PerClusterITS[i]->SetLineColor(color); fhChi2PerClusterITS[i]->SetLineWidth(2);
893 fhChi2PerClusterTPC[i]->SetLineColor(color); fhChi2PerClusterTPC[i]->SetLineWidth(2);
894
895 fhC11[i]->SetLineColor(color); fhC11[i]->SetLineWidth(2);
896 fhC22[i]->SetLineColor(color); fhC22[i]->SetLineWidth(2);
897 fhC33[i]->SetLineColor(color); fhC33[i]->SetLineWidth(2);
898 fhC44[i]->SetLineColor(color); fhC44[i]->SetLineWidth(2);
899 fhC55[i]->SetLineColor(color); fhC55[i]->SetLineWidth(2);
900
901 fhDXY[i]->SetLineColor(color); fhDXY[i]->SetLineWidth(2);
902 fhDZ[i]->SetLineColor(color); fhDZ[i]->SetLineWidth(2);
903
904 fhDXYNormalized[i]->SetLineColor(color); fhDXYNormalized[i]->SetLineWidth(2);
129a66bb 905 fhDZNormalized[i]->SetLineColor(color); fhDZNormalized[i]->SetLineWidth(2);
906 fhNSigmaToVertex[i]->SetLineColor(color); fhNSigmaToVertex[i]->SetLineWidth(2);
0b75bef2 907 }
129a66bb 908
909 // The number of sigmas to the vertex is per definition gaussian
910 ffDTheoretical = new TF1("nSigmaToVertexTheoretical","([0]/2.506628274)*exp(-(x**2)/2)",0,50);
911 ffDTheoretical->SetParameter(0,1);
3c4b53f0 912
913 TH1::AddDirectory(oldStatus);
0b75bef2 914}
915
916//____________________________________________________________________
3c4b53f0 917Bool_t AliESDtrackCuts::LoadHistograms(const Char_t* dir)
918{
ab2c1f0d 919 //
3c4b53f0 920 // loads the histograms from a file
921 // if dir is empty a directory with the name of this object is taken (like in SaveHistogram)
ab2c1f0d 922 //
0b75bef2 923
3c4b53f0 924 if (!dir)
925 dir = GetName();
926
927 if (!gDirectory->cd(dir))
928 return kFALSE;
929
930 ffDTheoretical = dynamic_cast<TF1*> (gDirectory->Get("nSigmaToVertexTheory"));
931
932 fhCutStatistics = dynamic_cast<TH1F*> (gDirectory->Get("cut_statistics"));
933 fhCutCorrelation = dynamic_cast<TH2F*> (gDirectory->Get("cut_correlation"));
934
935 Char_t str[5];
936 for (Int_t i=0; i<2; i++) {
937 if (i==0)
938 {
939 gDirectory->cd("before_cuts");
940 str[0] = 0;
941 }
942 else
943 {
944 gDirectory->cd("after_cuts");
945 sprintf(str,"_cut");
946 }
947
948 fhNClustersITS[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("nClustersITS%s",str) ));
949 fhNClustersTPC[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("nClustersTPC%s",str) ));
950 fhChi2PerClusterITS[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("chi2PerClusterITS%s",str)));
951 fhChi2PerClusterTPC[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("chi2PerClusterTPC%s",str)));
952
953 fhC11[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("covMatrixDiagonal11%s",str)));
954 fhC22[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("covMatrixDiagonal22%s",str)));
955 fhC33[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("covMatrixDiagonal33%s",str)));
956 fhC44[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("covMatrixDiagonal44%s",str)));
957 fhC55[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("covMatrixDiagonal55%s",str)));
958
959 fhDXY[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("dXY%s",str) ));
960 fhDZ[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("dZ%s",str) ));
961 fhDXYvsDZ[i] = dynamic_cast<TH2F*> (gDirectory->Get(Form("dXYvsDZ%s",str)));
962
963 fhDXYNormalized[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("dXYNormalized%s",str) ));
964 fhDZNormalized[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("dZNormalized%s",str) ));
965 fhDXYvsDZNormalized[i] = dynamic_cast<TH2F*> (gDirectory->Get(Form("dXYvsDZNormalized%s",str)));
966
967 fhNSigmaToVertex[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("nSigmaToVertex%s",str)));
968
969 // TODO only temporary
970 /*fhNClustersITS[i]->SetTitle("n ITS clusters");
971 fhNClustersTPC[i]->SetTitle("n TPC clusters");
972 fhChi2PerClusterITS[i]->SetTitle("#Chi^{2} per ITS cluster");
973 fhChi2PerClusterTPC[i]->SetTitle("#Chi^{2} per TPC cluster");
974
975 fhC11[i]->SetTitle("cov 11 : #sigma_{y}^{2} [cm^{2}]");
976 fhC22[i]->SetTitle("cov 22 : #sigma_{z}^{2} [cm^{2}]");
977 fhC33[i]->SetTitle("cov 33 : #sigma_{sin(#phi)}^{2}");
978 fhC44[i]->SetTitle("cov 44 : #sigma_{tan(#theta_{dip})}^{2}");
979 fhC55[i]->SetTitle("cov 55 : #sigma_{1/p_{T}}^{2} [(c/GeV)^2]");
980
981 fhDXY[i]->SetTitle("transverse impact parameter");
982 fhDZ[i]->SetTitle("longitudinal impact parameter");
983 fhDXYvsDZ[i]->SetTitle("longitudinal impact parameter");
984 fhDXYvsDZ[i]->SetYTitle("transverse impact parameter");
0b75bef2 985
3c4b53f0 986 fhDXYNormalized[i]->SetTitle("normalized trans impact par");
987 fhDZNormalized[i]->SetTitle("normalized long impact par");
988 fhDXYvsDZNormalized[i]->SetTitle("normalized long impact par");
989 fhDXYvsDZNormalized[i]->SetYTitle("normalized trans impact par");
990 fhNSigmaToVertex[i]->SetTitle("n #sigma to vertex");*/
991
992 gDirectory->cd("../");
993 }
994
995 gDirectory->cd("..");
996
997 return kTRUE;
998}
0b75bef2 999
1000//____________________________________________________________________
3c4b53f0 1001void AliESDtrackCuts::SaveHistograms(const Char_t* dir) {
1002 //
ab2c1f0d 1003 // saves the histograms in a directory (dir)
3c4b53f0 1004 //
ab2c1f0d 1005
0b75bef2 1006 if (!fHistogramsOn) {
1007 AliDebug(0, "Histograms not on - cannot save histograms!!!");
1008 return;
1009 }
1010
3c4b53f0 1011 if (!dir)
1012 dir = GetName();
1013
0b75bef2 1014 gDirectory->mkdir(dir);
1015 gDirectory->cd(dir);
1016
1017 gDirectory->mkdir("before_cuts");
1018 gDirectory->mkdir("after_cuts");
1019
129a66bb 1020 // a factor of 2 is needed since n sigma is positive
1021 ffDTheoretical->SetParameter(0,2*fhNSigmaToVertex[0]->Integral("width"));
1022 ffDTheoretical->Write("nSigmaToVertexTheory");
1023
f58f1a93 1024 fhCutStatistics->Write();
1025 fhCutCorrelation->Write();
0b75bef2 1026
1027 for (Int_t i=0; i<2; i++) {
1028 if (i==0)
1029 gDirectory->cd("before_cuts");
1030 else
1031 gDirectory->cd("after_cuts");
3c4b53f0 1032
f58f1a93 1033 fhNClustersITS[i] ->Write();
1034 fhNClustersTPC[i] ->Write();
1035 fhChi2PerClusterITS[i] ->Write();
1036 fhChi2PerClusterTPC[i] ->Write();
3c4b53f0 1037
f58f1a93 1038 fhC11[i] ->Write();
1039 fhC22[i] ->Write();
1040 fhC33[i] ->Write();
1041 fhC44[i] ->Write();
1042 fhC55[i] ->Write();
1043
1044 fhDXY[i] ->Write();
1045 fhDZ[i] ->Write();
1046 fhDXYvsDZ[i] ->Write();
3c4b53f0 1047
f58f1a93 1048 fhDXYNormalized[i] ->Write();
1049 fhDZNormalized[i] ->Write();
1050 fhDXYvsDZNormalized[i] ->Write();
129a66bb 1051 fhNSigmaToVertex[i] ->Write();
0b75bef2 1052
1053 gDirectory->cd("../");
1054 }
1055
1056 gDirectory->cd("../");
1057}
1058
3c4b53f0 1059//____________________________________________________________________
1060void AliESDtrackCuts::DrawHistograms()
1061{
1062 // draws some histograms
1063
1064 TCanvas* canvas1 = new TCanvas(Form("%s_1", GetName()), "Track Quality Results1", 800, 800);
1065 canvas1->Divide(2, 2);
1066
1067 canvas1->cd(1);
1068 fhNClustersTPC[0]->SetStats(kFALSE);
1069 fhNClustersTPC[0]->Draw();
1070
1071 canvas1->cd(2);
1072 fhChi2PerClusterTPC[0]->SetStats(kFALSE);
1073 fhChi2PerClusterTPC[0]->Draw();
1074
1075 canvas1->cd(3);
1076 fhNSigmaToVertex[0]->SetStats(kFALSE);
1077 fhNSigmaToVertex[0]->GetXaxis()->SetRangeUser(0, 10);
1078 fhNSigmaToVertex[0]->Draw();
1079
1080 canvas1->SaveAs(Form("%s_%s.gif", GetName(), canvas1->GetName()));
1081
1082 TCanvas* canvas2 = new TCanvas(Form("%s_2", GetName()), "Track Quality Results2", 1200, 800);
1083 canvas2->Divide(3, 2);
1084
1085 canvas2->cd(1);
1086 fhC11[0]->SetStats(kFALSE);
1087 gPad->SetLogy();
1088 fhC11[0]->Draw();
1089
1090 canvas2->cd(2);
1091 fhC22[0]->SetStats(kFALSE);
1092 gPad->SetLogy();
1093 fhC22[0]->Draw();
1094
1095 canvas2->cd(3);
1096 fhC33[0]->SetStats(kFALSE);
1097 gPad->SetLogy();
1098 fhC33[0]->Draw();
1099
1100 canvas2->cd(4);
1101 fhC44[0]->SetStats(kFALSE);
1102 gPad->SetLogy();
1103 fhC44[0]->Draw();
1104
1105 canvas2->cd(5);
1106 fhC55[0]->SetStats(kFALSE);
1107 gPad->SetLogy();
1108 fhC55[0]->Draw();
1109
1110 canvas2->SaveAs(Form("%s_%s.gif", GetName(), canvas2->GetName()));
1111
1112 TCanvas* canvas3 = new TCanvas(Form("%s_3", GetName()), "Track Quality Results3", 1200, 800);
1113 canvas3->Divide(3, 2);
1114
1115 canvas3->cd(1);
1116 fhDXY[0]->SetStats(kFALSE);
1117 gPad->SetLogy();
1118 fhDXY[0]->Draw();
1119
1120 canvas3->cd(2);
1121 fhDZ[0]->SetStats(kFALSE);
1122 gPad->SetLogy();
1123 fhDZ[0]->Draw();
1124
1125 canvas3->cd(3);
1126 fhDXYvsDZ[0]->SetStats(kFALSE);
1127 gPad->SetLogz();
1128 gPad->SetRightMargin(0.15);
1129 fhDXYvsDZ[0]->Draw("COLZ");
1130
1131 canvas3->cd(4);
1132 fhDXYNormalized[0]->SetStats(kFALSE);
1133 gPad->SetLogy();
1134 fhDXYNormalized[0]->Draw();
1135
1136 canvas3->cd(5);
1137 fhDZNormalized[0]->SetStats(kFALSE);
1138 gPad->SetLogy();
1139 fhDZNormalized[0]->Draw();
1140
1141 canvas3->cd(6);
1142 fhDXYvsDZNormalized[0]->SetStats(kFALSE);
1143 gPad->SetLogz();
1144 gPad->SetRightMargin(0.15);
1145 fhDXYvsDZNormalized[0]->Draw("COLZ");
1146
1147 canvas3->SaveAs(Form("%s_%s.gif", GetName(), canvas3->GetName()));
1148
1149 TCanvas* canvas4 = new TCanvas(Form("%s_4", GetName()), "Track Quality Results4", 800, 500);
1150 canvas4->Divide(2, 1);
1151
1152 canvas4->cd(1);
1153 fhCutStatistics->SetStats(kFALSE);
1154 fhCutStatistics->LabelsOption("v");
1155 gPad->SetBottomMargin(0.3);
1156 fhCutStatistics->Draw();
1157
1158 canvas4->cd(2);
1159 fhCutCorrelation->SetStats(kFALSE);
1160 fhCutCorrelation->LabelsOption("v");
1161 gPad->SetBottomMargin(0.3);
1162 gPad->SetLeftMargin(0.3);
1163 fhCutCorrelation->Draw("COLZ");
1164
1165 canvas4->SaveAs(Form("%s_%s.gif", GetName(), canvas4->GetName()));
1166
1167 /*canvas->cd(1);
1168 fhDXYvsDZNormalized[0]->SetStats(kFALSE);
1169 fhDXYvsDZNormalized[0]->DrawCopy("COLZ");
1170
1171 canvas->cd(2);
1172 fhNClustersTPC[0]->SetStats(kFALSE);
1173 fhNClustersTPC[0]->DrawCopy();
1174
1175 canvas->cd(3);
1176 fhChi2PerClusterITS[0]->SetStats(kFALSE);
1177 fhChi2PerClusterITS[0]->DrawCopy();
1178 fhChi2PerClusterITS[1]->SetLineColor(2);
1179 fhChi2PerClusterITS[1]->DrawCopy("SAME");
1180
1181 canvas->cd(4);
1182 fhChi2PerClusterTPC[0]->SetStats(kFALSE);
1183 fhChi2PerClusterTPC[0]->DrawCopy();
1184 fhChi2PerClusterTPC[1]->SetLineColor(2);
1185 fhChi2PerClusterTPC[1]->DrawCopy("SAME");*/
1186}
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