AliZDCRawStream class updated
[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#include <AliESDtrack.h>
21#include <AliESD.h>
70d782ef 22#include <AliESDEvent.h>
aa93c798 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//____________________________________________________________________
70d782ef 58AliESDtrackCuts::AliESDtrackCuts(const Char_t* name, const Char_t* title) : AliAnalysisCuts(name,title),
aa617804 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 fhCutStatistics(0),
89 fhCutCorrelation(0)
ebd60d8e 90{
91 //
92 // constructor
93 //
94
95 Init();
0b75bef2 96
97 //##############################################################################
98 // setting default cuts
0b75bef2 99 SetMinNClustersTPC();
ebd60d8e 100 SetMinNClustersITS();
0b75bef2 101 SetMaxChi2PerClusterTPC();
102 SetMaxChi2PerClusterITS();
103 SetMaxCovDiagonalElements();
104 SetRequireTPCRefit();
105 SetRequireITSRefit();
106 SetAcceptKingDaughters();
107 SetMinNsigmaToVertex();
108 SetRequireSigmaToVertex();
109 SetPRange();
110 SetPtRange();
111 SetPxRange();
112 SetPyRange();
113 SetPzRange();
114 SetEtaRange();
115 SetRapRange();
116
117 SetHistogramsOn();
ebd60d8e 118}
119
120//_____________________________________________________________________________
88ad8b0a 121AliESDtrackCuts::AliESDtrackCuts(const AliESDtrackCuts &c) : AliAnalysisCuts(c),
aa617804 122 fCutMinNClusterTPC(0),
123 fCutMinNClusterITS(0),
124 fCutMaxChi2PerClusterTPC(0),
125 fCutMaxChi2PerClusterITS(0),
126 fCutMaxC11(0),
127 fCutMaxC22(0),
128 fCutMaxC33(0),
129 fCutMaxC44(0),
130 fCutMaxC55(0),
131 fCutAcceptKinkDaughters(0),
132 fCutRequireTPCRefit(0),
133 fCutRequireITSRefit(0),
134 fCutNsigmaToVertex(0),
135 fCutSigmaToVertexRequired(0),
136 fPMin(0),
137 fPMax(0),
138 fPtMin(0),
139 fPtMax(0),
140 fPxMin(0),
141 fPxMax(0),
142 fPyMin(0),
143 fPyMax(0),
144 fPzMin(0),
145 fPzMax(0),
146 fEtaMin(0),
147 fEtaMax(0),
148 fRapMin(0),
149 fRapMax(0),
150 fHistogramsOn(0),
129a66bb 151 ffDTheoretical(0),
aa617804 152 fhCutStatistics(0),
153 fhCutCorrelation(0)
ebd60d8e 154{
155 //
156 // copy constructor
157 //
158
159 ((AliESDtrackCuts &) c).Copy(*this);
160}
161
162AliESDtrackCuts::~AliESDtrackCuts()
163{
164 //
165 // destructor
166 //
167
927c71e5 168 for (Int_t i=0; i<2; i++) {
169
170 if (fhNClustersITS[i])
171 delete fhNClustersITS[i];
172 if (fhNClustersTPC[i])
173 delete fhNClustersTPC[i];
174 if (fhChi2PerClusterITS[i])
175 delete fhChi2PerClusterITS[i];
176 if (fhChi2PerClusterTPC[i])
177 delete fhChi2PerClusterTPC[i];
178 if (fhC11[i])
179 delete fhC11[i];
180 if (fhC22[i])
181 delete fhC22[i];
182 if (fhC33[i])
183 delete fhC33[i];
184 if (fhC44[i])
185 delete fhC44[i];
186 if (fhC55[i])
187 delete fhC55[i];
188
189 if (fhDXY[i])
190 delete fhDXY[i];
191 if (fhDZ[i])
192 delete fhDZ[i];
193 if (fhDXYvsDZ[i])
194 delete fhDXYvsDZ[i];
195
196 if (fhDXYNormalized[i])
197 delete fhDXYNormalized[i];
198 if (fhDZNormalized[i])
3c4b53f0 199 delete fhDZNormalized[i];
927c71e5 200 if (fhDXYvsDZNormalized[i])
201 delete fhDXYvsDZNormalized[i];
129a66bb 202 if (fhNSigmaToVertex[i])
203 delete fhNSigmaToVertex[i];
927c71e5 204 }
3c4b53f0 205
129a66bb 206 if (ffDTheoretical)
207 delete ffDTheoretical;
927c71e5 208
209 if (fhCutStatistics)
210 delete fhCutStatistics;
211 if (fhCutCorrelation)
212 delete fhCutCorrelation;
ebd60d8e 213}
214
215void AliESDtrackCuts::Init()
216{
217 //
218 // sets everything to zero
219 //
220
ab2c1f0d 221 fCutMinNClusterTPC = 0;
222 fCutMinNClusterITS = 0;
ebd60d8e 223
ab2c1f0d 224 fCutMaxChi2PerClusterTPC = 0;
225 fCutMaxChi2PerClusterITS = 0;
ebd60d8e 226
ab2c1f0d 227 fCutMaxC11 = 0;
228 fCutMaxC22 = 0;
229 fCutMaxC33 = 0;
230 fCutMaxC44 = 0;
231 fCutMaxC55 = 0;
ebd60d8e 232
ab2c1f0d 233 fCutAcceptKinkDaughters = 0;
234 fCutRequireTPCRefit = 0;
235 fCutRequireITSRefit = 0;
ebd60d8e 236
ab2c1f0d 237 fCutNsigmaToVertex = 0;
238 fCutSigmaToVertexRequired = 0;
ebd60d8e 239
240 fPMin = 0;
241 fPMax = 0;
242 fPtMin = 0;
243 fPtMax = 0;
244 fPxMin = 0;
245 fPxMax = 0;
246 fPyMin = 0;
247 fPyMax = 0;
248 fPzMin = 0;
249 fPzMax = 0;
250 fEtaMin = 0;
251 fEtaMax = 0;
252 fRapMin = 0;
253 fRapMax = 0;
254
255 fHistogramsOn = kFALSE;
256
257 for (Int_t i=0; i<2; ++i)
258 {
259 fhNClustersITS[i] = 0;
260 fhNClustersTPC[i] = 0;
261
262 fhChi2PerClusterITS[i] = 0;
263 fhChi2PerClusterTPC[i] = 0;
264
265 fhC11[i] = 0;
266 fhC22[i] = 0;
267 fhC33[i] = 0;
268 fhC44[i] = 0;
269 fhC55[i] = 0;
270
271 fhDXY[i] = 0;
272 fhDZ[i] = 0;
273 fhDXYvsDZ[i] = 0;
274
275 fhDXYNormalized[i] = 0;
276 fhDZNormalized[i] = 0;
277 fhDXYvsDZNormalized[i] = 0;
129a66bb 278 fhNSigmaToVertex[i] = 0;
ebd60d8e 279 }
129a66bb 280 ffDTheoretical = 0;
ebd60d8e 281
282 fhCutStatistics = 0;
283 fhCutCorrelation = 0;
284}
285
286//_____________________________________________________________________________
287AliESDtrackCuts &AliESDtrackCuts::operator=(const AliESDtrackCuts &c)
288{
289 //
290 // Assignment operator
291 //
0b75bef2 292
ebd60d8e 293 if (this != &c) ((AliESDtrackCuts &) c).Copy(*this);
294 return *this;
295}
296
297//_____________________________________________________________________________
298void AliESDtrackCuts::Copy(TObject &c) const
299{
300 //
301 // Copy function
302 //
303
304 AliESDtrackCuts& target = (AliESDtrackCuts &) c;
305
306 target.Init();
307
ab2c1f0d 308 target.fCutMinNClusterTPC = fCutMinNClusterTPC;
309 target.fCutMinNClusterITS = fCutMinNClusterITS;
ebd60d8e 310
ab2c1f0d 311 target.fCutMaxChi2PerClusterTPC = fCutMaxChi2PerClusterTPC;
312 target.fCutMaxChi2PerClusterITS = fCutMaxChi2PerClusterITS;
ebd60d8e 313
ab2c1f0d 314 target.fCutMaxC11 = fCutMaxC11;
315 target.fCutMaxC22 = fCutMaxC22;
316 target.fCutMaxC33 = fCutMaxC33;
317 target.fCutMaxC44 = fCutMaxC44;
318 target.fCutMaxC55 = fCutMaxC55;
ebd60d8e 319
ab2c1f0d 320 target.fCutAcceptKinkDaughters = fCutAcceptKinkDaughters;
321 target.fCutRequireTPCRefit = fCutRequireTPCRefit;
322 target.fCutRequireITSRefit = fCutRequireITSRefit;
ebd60d8e 323
ab2c1f0d 324 target.fCutNsigmaToVertex = fCutNsigmaToVertex;
325 target.fCutSigmaToVertexRequired = fCutSigmaToVertexRequired;
ebd60d8e 326
327 target.fPMin = fPMin;
328 target.fPMax = fPMax;
329 target.fPtMin = fPtMin;
330 target.fPtMax = fPtMax;
331 target.fPxMin = fPxMin;
332 target.fPxMax = fPxMax;
333 target.fPyMin = fPyMin;
334 target.fPyMax = fPyMax;
335 target.fPzMin = fPzMin;
336 target.fPzMax = fPzMax;
337 target.fEtaMin = fEtaMin;
338 target.fEtaMax = fEtaMax;
339 target.fRapMin = fRapMin;
340 target.fRapMax = fRapMax;
341
342 target.fHistogramsOn = fHistogramsOn;
343
344 for (Int_t i=0; i<2; ++i)
345 {
346 if (fhNClustersITS[i]) target.fhNClustersITS[i] = (TH1F*) fhNClustersITS[i]->Clone();
347 if (fhNClustersTPC[i]) target.fhNClustersTPC[i] = (TH1F*) fhNClustersTPC[i]->Clone();
348
349 if (fhChi2PerClusterITS[i]) target.fhChi2PerClusterITS[i] = (TH1F*) fhChi2PerClusterITS[i]->Clone();
350 if (fhChi2PerClusterTPC[i]) target.fhChi2PerClusterTPC[i] = (TH1F*) fhChi2PerClusterTPC[i]->Clone();
351
352 if (fhC11[i]) target.fhC11[i] = (TH1F*) fhC11[i]->Clone();
353 if (fhC22[i]) target.fhC22[i] = (TH1F*) fhC22[i]->Clone();
354 if (fhC33[i]) target.fhC33[i] = (TH1F*) fhC33[i]->Clone();
355 if (fhC44[i]) target.fhC44[i] = (TH1F*) fhC44[i]->Clone();
356 if (fhC55[i]) target.fhC55[i] = (TH1F*) fhC55[i]->Clone();
357
358 if (fhDXY[i]) target.fhDXY[i] = (TH1F*) fhDXY[i]->Clone();
359 if (fhDZ[i]) target.fhDZ[i] = (TH1F*) fhDZ[i]->Clone();
360 if (fhDXYvsDZ[i]) target.fhDXYvsDZ[i] = (TH2F*) fhDXYvsDZ[i]->Clone();
361
362 if (fhDXYNormalized[i]) target.fhDXYNormalized[i] = (TH1F*) fhDXYNormalized[i]->Clone();
363 if (fhDZNormalized[i]) target.fhDZNormalized[i] = (TH1F*) fhDZNormalized[i]->Clone();
364 if (fhDXYvsDZNormalized[i]) target.fhDXYvsDZNormalized[i] = (TH2F*) fhDXYvsDZNormalized[i]->Clone();
129a66bb 365 if (fhNSigmaToVertex[i]) target.fhNSigmaToVertex[i] = (TH1F*) fhNSigmaToVertex[i]->Clone();
ebd60d8e 366 }
129a66bb 367 if (ffDTheoretical) target.ffDTheoretical = (TF1*) ffDTheoretical->Clone();
ebd60d8e 368
369 if (fhCutStatistics) target.fhCutStatistics = (TH1F*) fhCutStatistics->Clone();
370 if (fhCutCorrelation) target.fhCutCorrelation = (TH2F*) fhCutCorrelation->Clone();
0b75bef2 371
0b8a2421 372 TNamed::Copy(c);
0b75bef2 373}
374
927c71e5 375//_____________________________________________________________________________
376Long64_t AliESDtrackCuts::Merge(TCollection* list) {
377 // Merge a list of AliESDtrackCuts objects with this (needed for PROOF)
378 // Returns the number of merged objects (including this)
379
380 if (!list)
381 return 0;
382
383 if (list->IsEmpty())
384 return 1;
385
386 if (!fHistogramsOn)
387 return 0;
388
389 TIterator* iter = list->MakeIterator();
390 TObject* obj;
391
392
393 // collection of measured and generated histograms
394 Int_t count = 0;
395 while ((obj = iter->Next())) {
396
397 AliESDtrackCuts* entry = dynamic_cast<AliESDtrackCuts*>(obj);
398 if (entry == 0)
399 continue;
400
401 if (!entry->fHistogramsOn)
402 continue;
403
404 for (Int_t i=0; i<2; i++) {
405
406 fhNClustersITS[i] ->Add(entry->fhNClustersITS[i] );
407 fhNClustersTPC[i] ->Add(entry->fhNClustersTPC[i] );
408
409 fhChi2PerClusterITS[i] ->Add(entry->fhChi2PerClusterITS[i]);
410 fhChi2PerClusterTPC[i] ->Add(entry->fhChi2PerClusterTPC[i]);
411
412 fhC11[i] ->Add(entry->fhC11[i] );
413 fhC22[i] ->Add(entry->fhC22[i] );
414 fhC33[i] ->Add(entry->fhC33[i] );
415 fhC44[i] ->Add(entry->fhC44[i] );
416 fhC55[i] ->Add(entry->fhC55[i] );
417
418 fhDXY[i] ->Add(entry->fhDXY[i] );
419 fhDZ[i] ->Add(entry->fhDZ[i] );
420 fhDXYvsDZ[i] ->Add(entry->fhDXYvsDZ[i] );
421
422 fhDXYNormalized[i] ->Add(entry->fhDXYNormalized[i] );
3c4b53f0 423 fhDZNormalized[i] ->Add(entry->fhDZNormalized[i] );
927c71e5 424 fhDXYvsDZNormalized[i] ->Add(entry->fhDXYvsDZNormalized[i]);
129a66bb 425 fhNSigmaToVertex[i] ->Add(entry->fhNSigmaToVertex[i]);
426
927c71e5 427 }
428
429 fhCutStatistics ->Add(entry->fhCutStatistics);
430 fhCutCorrelation ->Add(entry->fhCutCorrelation);
431
432 count++;
433 }
434
435 return count+1;
436}
437
438
0b75bef2 439//____________________________________________________________________
2b9019e4 440Float_t AliESDtrackCuts::GetSigmaToVertex(AliESDtrack* esdTrack)
441{
129a66bb 442 // Calculates the number of sigma to the vertex.
2b9019e4 443
444 Float_t b[2];
445 Float_t bRes[2];
446 Float_t bCov[3];
447 esdTrack->GetImpactParameters(b,bCov);
448 if (bCov[0]<=0 || bCov[2]<=0) {
449 AliDebug(1, "Estimated b resolution lower or equal zero!");
450 bCov[0]=0; bCov[2]=0;
451 }
452 bRes[0] = TMath::Sqrt(bCov[0]);
453 bRes[1] = TMath::Sqrt(bCov[2]);
454
455 // -----------------------------------
456 // How to get to a n-sigma cut?
457 //
458 // The accumulated statistics from 0 to d is
459 //
460 // -> Erf(d/Sqrt(2)) for a 1-dim gauss (d = n_sigma)
461 // -> 1 - Exp(-d**2) for a 2-dim gauss (d*d = dx*dx + dy*dy != n_sigma)
462 //
463 // It means that for a 2-dim gauss: n_sigma(d) = Sqrt(2)*ErfInv(1 - Exp((-x**2)/2)
464 // Can this be expressed in a different way?
2b9019e4 465
466 if (bRes[0] == 0 || bRes[1] ==0)
467 return -1;
468
469 Float_t d = TMath::Sqrt(TMath::Power(b[0]/bRes[0],2) + TMath::Power(b[1]/bRes[1],2));
470
471 // stupid rounding problem screws up everything:
472 // if d is too big, TMath::Exp(...) gets 0, and TMath::ErfInverse(1) that should be infinite, gets 0 :(
473 if (TMath::Exp(-d * d / 2) < 1e-10)
474 return 1000;
475
476 d = TMath::ErfInverse(1 - TMath::Exp(-d * d / 2)) * TMath::Sqrt(2);
477 return d;
478}
479
5c495d37 480void AliESDtrackCuts::EnableNeededBranches(TTree* tree)
481{
482 // enables the branches needed by AcceptTrack, for a list see comment of AcceptTrack
483
484 tree->SetBranchStatus("fTracks.fFlags", 1);
485 tree->SetBranchStatus("fTracks.fITSncls", 1);
486 tree->SetBranchStatus("fTracks.fTPCncls", 1);
487 tree->SetBranchStatus("fTracks.fITSchi2", 1);
488 tree->SetBranchStatus("fTracks.fTPCchi2", 1);
489 tree->SetBranchStatus("fTracks.fC*", 1);
490 tree->SetBranchStatus("fTracks.fD", 1);
491 tree->SetBranchStatus("fTracks.fZ", 1);
492 tree->SetBranchStatus("fTracks.fCdd", 1);
493 tree->SetBranchStatus("fTracks.fCdz", 1);
494 tree->SetBranchStatus("fTracks.fCzz", 1);
495 tree->SetBranchStatus("fTracks.fP*", 1);
496 tree->SetBranchStatus("fTracks.fR*", 1);
497 tree->SetBranchStatus("fTracks.fKinkIndexes*", 1);
498}
499
2b9019e4 500//____________________________________________________________________
501Bool_t
0b75bef2 502AliESDtrackCuts::AcceptTrack(AliESDtrack* esdTrack) {
503 //
504 // figure out if the tracks survives all the track cuts defined
505 //
ab2c1f0d 506 // the different quality parameter and kinematic values are first
507 // retrieved from the track. then it is found out what cuts the
508 // track did not survive and finally the cuts are imposed.
0b75bef2 509
5c495d37 510 // this function needs the following branches:
511 // fTracks.fFlags
512 // fTracks.fITSncls
513 // fTracks.fTPCncls
514 // fTracks.fITSchi2
515 // fTracks.fTPCchi2
516 // fTracks.fC //GetExternalCovariance
517 // fTracks.fD //GetImpactParameters
518 // fTracks.fZ //GetImpactParameters
519 // fTracks.fCdd //GetImpactParameters
520 // fTracks.fCdz //GetImpactParameters
521 // fTracks.fCzz //GetImpactParameters
522 // fTracks.fP //GetPxPyPz
523 // fTracks.fR //GetMass
524 // fTracks.fP //GetMass
525 // fTracks.fKinkIndexes
1ae6c515 526
0b75bef2 527 UInt_t status = esdTrack->GetStatus();
ebd60d8e 528
529 // dummy array
530 Int_t fIdxInt[200];
531
0b75bef2 532 // getting quality parameters from the ESD track
533 Int_t nClustersITS = esdTrack->GetITSclusters(fIdxInt);
534 Int_t nClustersTPC = esdTrack->GetTPCclusters(fIdxInt);
535
1ae6c515 536
537
0b75bef2 538 Float_t chi2PerClusterITS = -1;
539 Float_t chi2PerClusterTPC = -1;
540 if (nClustersITS!=0)
541 chi2PerClusterITS = esdTrack->GetITSchi2()/Float_t(nClustersITS);
542 if (nClustersTPC!=0)
5c495d37 543 chi2PerClusterTPC = esdTrack->GetTPCchi2()/Float_t(nClustersTPC);
0b75bef2 544
545 Double_t extCov[15];
ebd60d8e 546 esdTrack->GetExternalCovariance(extCov);
0b75bef2 547
548 // getting the track to vertex parameters
2b9019e4 549 Float_t nSigmaToVertex = GetSigmaToVertex(esdTrack);
0b75bef2 550
2b9019e4 551 // getting the kinematic variables of the track
0b75bef2 552 // (assuming the mass is known)
553 Double_t p[3];
554 esdTrack->GetPxPyPz(p);
555 Float_t momentum = TMath::Sqrt(TMath::Power(p[0],2) + TMath::Power(p[1],2) + TMath::Power(p[2],2));
556 Float_t pt = TMath::Sqrt(TMath::Power(p[0],2) + TMath::Power(p[1],2));
557 Float_t energy = TMath::Sqrt(TMath::Power(esdTrack->GetMass(),2) + TMath::Power(momentum,2));
558
1ae6c515 559
0b75bef2 560 //y-eta related calculations
561 Float_t eta = -100.;
562 Float_t y = -100.;
563 if((momentum != TMath::Abs(p[2]))&&(momentum != 0))
564 eta = 0.5*TMath::Log((momentum + p[2])/(momentum - p[2]));
565 if((energy != TMath::Abs(p[2]))&&(momentum != 0))
566 y = 0.5*TMath::Log((energy + p[2])/(energy - p[2]));
567
568
569 //########################################################################
570 // cut the track?
571
ebd60d8e 572 Bool_t cuts[kNCuts];
573 for (Int_t i=0; i<kNCuts; i++) cuts[i]=kFALSE;
0b75bef2 574
575 // track quality cuts
ab2c1f0d 576 if (fCutRequireTPCRefit && (status&AliESDtrack::kTPCrefit)==0)
0b75bef2 577 cuts[0]=kTRUE;
ab2c1f0d 578 if (fCutRequireITSRefit && (status&AliESDtrack::kITSrefit)==0)
0b75bef2 579 cuts[1]=kTRUE;
2b9019e4 580 if (nClustersTPC<fCutMinNClusterTPC)
0b75bef2 581 cuts[2]=kTRUE;
ab2c1f0d 582 if (nClustersITS<fCutMinNClusterITS)
0b75bef2 583 cuts[3]=kTRUE;
ab2c1f0d 584 if (chi2PerClusterTPC>fCutMaxChi2PerClusterTPC)
0b75bef2 585 cuts[4]=kTRUE;
ab2c1f0d 586 if (chi2PerClusterITS>fCutMaxChi2PerClusterITS)
0b75bef2 587 cuts[5]=kTRUE;
ab2c1f0d 588 if (extCov[0] > fCutMaxC11)
0b75bef2 589 cuts[6]=kTRUE;
ab2c1f0d 590 if (extCov[2] > fCutMaxC22)
0b75bef2 591 cuts[7]=kTRUE;
ab2c1f0d 592 if (extCov[5] > fCutMaxC33)
0b75bef2 593 cuts[8]=kTRUE;
ab2c1f0d 594 if (extCov[9] > fCutMaxC44)
0b75bef2 595 cuts[9]=kTRUE;
ab2c1f0d 596 if (extCov[14] > fCutMaxC55)
0b75bef2 597 cuts[10]=kTRUE;
70d782ef 598 if (nSigmaToVertex > fCutNsigmaToVertex && fCutSigmaToVertexRequired)
0b75bef2 599 cuts[11] = kTRUE;
600 // if n sigma could not be calculated
10ebe68d 601 if (nSigmaToVertex<0 && fCutSigmaToVertexRequired)
0b75bef2 602 cuts[12]=kTRUE;
5c495d37 603 if (!fCutAcceptKinkDaughters && esdTrack->GetKinkIndex(0)>0)
0b75bef2 604 cuts[13]=kTRUE;
605 // track kinematics cut
606 if((momentum < fPMin) || (momentum > fPMax))
607 cuts[14]=kTRUE;
608 if((pt < fPtMin) || (pt > fPtMax))
609 cuts[15] = kTRUE;
610 if((p[0] < fPxMin) || (p[0] > fPxMax))
611 cuts[16] = kTRUE;
612 if((p[1] < fPyMin) || (p[1] > fPyMax))
613 cuts[17] = kTRUE;
2b9019e4 614 if((p[2] < fPzMin) || (p[2] > fPzMax))
0b75bef2 615 cuts[18] = kTRUE;
616 if((eta < fEtaMin) || (eta > fEtaMax))
617 cuts[19] = kTRUE;
618 if((y < fRapMin) || (y > fRapMax))
619 cuts[20] = kTRUE;
620
621 Bool_t cut=kFALSE;
ebd60d8e 622 for (Int_t i=0; i<kNCuts; i++)
0b75bef2 623 if (cuts[i]) cut = kTRUE;
624
625 //########################################################################
626 // filling histograms
627 if (fHistogramsOn) {
f58f1a93 628 fhCutStatistics->Fill(fhCutStatistics->GetBinCenter(fhCutStatistics->GetXaxis()->FindBin("n tracks")));
0b75bef2 629
630 if (cut)
f58f1a93 631 fhCutStatistics->Fill(fhCutStatistics->GetBinCenter(fhCutStatistics->GetXaxis()->FindBin("n cut tracks")));
0b75bef2 632
ebd60d8e 633 for (Int_t i=0; i<kNCuts; i++) {
0b75bef2 634 if (cuts[i])
ab2c1f0d 635 fhCutStatistics->Fill(fhCutStatistics->GetBinCenter(fhCutStatistics->GetXaxis()->FindBin(fgkCutNames[i])));
0b75bef2 636
ebd60d8e 637 for (Int_t j=i; j<kNCuts; j++) {
0b75bef2 638 if (cuts[i] && cuts[j]) {
ab2c1f0d 639 Float_t x = fhCutCorrelation->GetXaxis()->GetBinCenter(fhCutCorrelation->GetXaxis()->FindBin(fgkCutNames[i]));
640 Float_t y = fhCutCorrelation->GetYaxis()->GetBinCenter(fhCutCorrelation->GetYaxis()->FindBin(fgkCutNames[j]));
f58f1a93 641 fhCutCorrelation->Fill(x,y);
0b75bef2 642 }
643 }
644 }
645
646
2b9019e4 647 fhNClustersITS[0]->Fill(nClustersITS);
648 fhNClustersTPC[0]->Fill(nClustersTPC);
f58f1a93 649 fhChi2PerClusterITS[0]->Fill(chi2PerClusterITS);
2b9019e4 650 fhChi2PerClusterTPC[0]->Fill(chi2PerClusterTPC);
651
652 fhC11[0]->Fill(extCov[0]);
653 fhC22[0]->Fill(extCov[2]);
654 fhC33[0]->Fill(extCov[5]);
655 fhC44[0]->Fill(extCov[9]);
656 fhC55[0]->Fill(extCov[14]);
657
658 Float_t b[2];
659 Float_t bRes[2];
660 Float_t bCov[3];
661 esdTrack->GetImpactParameters(b,bCov);
662 if (bCov[0]<=0 || bCov[2]<=0) {
663 AliDebug(1, "Estimated b resolution lower or equal zero!");
664 bCov[0]=0; bCov[2]=0;
665 }
666 bRes[0] = TMath::Sqrt(bCov[0]);
667 bRes[1] = TMath::Sqrt(bCov[2]);
668
669 fhDZ[0]->Fill(b[1]);
670 fhDXY[0]->Fill(b[0]);
f58f1a93 671 fhDXYvsDZ[0]->Fill(b[1],b[0]);
0b75bef2 672
673 if (bRes[0]!=0 && bRes[1]!=0) {
10ebe68d 674 fhDZNormalized[0]->Fill(b[1]/bRes[1]);
2b9019e4 675 fhDXYNormalized[0]->Fill(b[0]/bRes[0]);
f58f1a93 676 fhDXYvsDZNormalized[0]->Fill(b[1]/bRes[1], b[0]/bRes[0]);
129a66bb 677 fhNSigmaToVertex[0]->Fill(nSigmaToVertex);
0b75bef2 678 }
679 }
680
2b9019e4 681 //########################################################################
0b75bef2 682 // cut the track!
683 if (cut) return kFALSE;
684
2b9019e4 685 //########################################################################
0b75bef2 686 // filling histograms after cut
687 if (fHistogramsOn) {
2b9019e4 688 fhNClustersITS[1]->Fill(nClustersITS);
689 fhNClustersTPC[1]->Fill(nClustersTPC);
f58f1a93 690 fhChi2PerClusterITS[1]->Fill(chi2PerClusterITS);
2b9019e4 691 fhChi2PerClusterTPC[1]->Fill(chi2PerClusterTPC);
692
693 fhC11[1]->Fill(extCov[0]);
694 fhC22[1]->Fill(extCov[2]);
10ebe68d 695 fhC33[1]->Fill(extCov[5]);
2b9019e4 696 fhC44[1]->Fill(extCov[9]);
697 fhC55[1]->Fill(extCov[14]);
698
699 Float_t b[2];
700 Float_t bRes[2];
701 Float_t bCov[3];
702 esdTrack->GetImpactParameters(b,bCov);
703 if (bCov[0]<=0 || bCov[2]<=0) {
704 AliDebug(1, "Estimated b resolution lower or equal zero!");
705 bCov[0]=0; bCov[2]=0;
706 }
707 bRes[0] = TMath::Sqrt(bCov[0]);
708 bRes[1] = TMath::Sqrt(bCov[2]);
709
710 fhDZ[1]->Fill(b[1]);
711 fhDXY[1]->Fill(b[0]);
f58f1a93 712 fhDXYvsDZ[1]->Fill(b[1],b[0]);
0b75bef2 713
10ebe68d 714 if (bRes[0]!=0 && bRes[1]!=0)
715 {
716 fhDZNormalized[1]->Fill(b[1]/bRes[1]);
717 fhDXYNormalized[1]->Fill(b[0]/bRes[0]);
718 fhDXYvsDZNormalized[1]->Fill(b[1]/bRes[1], b[0]/bRes[0]);
129a66bb 719 fhNSigmaToVertex[1]->Fill(nSigmaToVertex);
10ebe68d 720 }
0b75bef2 721 }
2b9019e4 722
0b75bef2 723 return kTRUE;
724}
725
726//____________________________________________________________________
70d782ef 727TObjArray* AliESDtrackCuts::GetAcceptedTracks(AliESD* esd)
728{
729 //
730 // returns an array of all tracks that pass the cuts
731 //
732
733 TObjArray* acceptedTracks = new TObjArray();
734
735 // loop over esd tracks
736 for (Int_t iTrack = 0; iTrack < esd->GetNumberOfTracks(); iTrack++) {
737 AliESDtrack* track = esd->GetTrack(iTrack);
738
739 if (AcceptTrack(track))
740 acceptedTracks->Add(track);
741 }
742
743 return acceptedTracks;
744}
745
746//____________________________________________________________________
747Int_t AliESDtrackCuts::CountAcceptedTracks(AliESD* esd)
748{
749 //
750 // returns an the number of tracks that pass the cuts
751 //
752
753 Int_t count = 0;
754
755 // loop over esd tracks
756 for (Int_t iTrack = 0; iTrack < esd->GetNumberOfTracks(); iTrack++) {
757 AliESDtrack* track = esd->GetTrack(iTrack);
758
759 if (AcceptTrack(track))
760 count++;
761 }
762
763 return count;
764}
765
766//____________________________________________________________________
767TObjArray* AliESDtrackCuts::GetAcceptedTracks(AliESDEvent* esd)
ebd60d8e 768{
769 //
0b75bef2 770 // returns an array of all tracks that pass the cuts
ebd60d8e 771 //
772
773 TObjArray* acceptedTracks = new TObjArray();
c5858666 774
0b75bef2 775 // loop over esd tracks
776 for (Int_t iTrack = 0; iTrack < esd->GetNumberOfTracks(); iTrack++) {
777 AliESDtrack* track = esd->GetTrack(iTrack);
c5858666 778
ebd60d8e 779 if (AcceptTrack(track))
780 acceptedTracks->Add(track);
0b75bef2 781 }
782
ebd60d8e 783 return acceptedTracks;
0b75bef2 784}
785
c5858666 786//____________________________________________________________________
70d782ef 787Int_t AliESDtrackCuts::CountAcceptedTracks(AliESDEvent* esd)
c5858666 788{
789 //
790 // returns an the number of tracks that pass the cuts
791 //
792
793 Int_t count = 0;
794
795 // loop over esd tracks
796 for (Int_t iTrack = 0; iTrack < esd->GetNumberOfTracks(); iTrack++) {
797 AliESDtrack* track = esd->GetTrack(iTrack);
798
799 if (AcceptTrack(track))
800 count++;
801 }
802
803 return count;
804}
805
0b75bef2 806//____________________________________________________________________
f58f1a93 807 void AliESDtrackCuts::DefineHistograms(Int_t color) {
ab2c1f0d 808 //
809 // diagnostics histograms are defined
810 //
0b75bef2 811
f58f1a93 812 fHistogramsOn=kTRUE;
3c4b53f0 813
814 Bool_t oldStatus = TH1::AddDirectoryStatus();
815 TH1::AddDirectory(kFALSE);
816
ab2c1f0d 817 //###################################################################################
f58f1a93 818 // defining histograms
0b75bef2 819
ebd60d8e 820 fhCutStatistics = new TH1F("cut_statistics","cut statistics",kNCuts+4,-0.5,kNCuts+3.5);
0b75bef2 821
f58f1a93 822 fhCutStatistics->GetXaxis()->SetBinLabel(1,"n tracks");
823 fhCutStatistics->GetXaxis()->SetBinLabel(2,"n cut tracks");
0b75bef2 824
ebd60d8e 825 fhCutCorrelation = new TH2F("cut_correlation","cut correlation",kNCuts,-0.5,kNCuts-0.5,kNCuts,-0.5,kNCuts-0.5);;
0b75bef2 826
ebd60d8e 827 for (Int_t i=0; i<kNCuts; i++) {
ab2c1f0d 828 fhCutStatistics->GetXaxis()->SetBinLabel(i+4,fgkCutNames[i]);
829 fhCutCorrelation->GetXaxis()->SetBinLabel(i+1,fgkCutNames[i]);
830 fhCutCorrelation->GetYaxis()->SetBinLabel(i+1,fgkCutNames[i]);
f58f1a93 831 }
832
833 fhCutStatistics ->SetLineColor(color);
834 fhCutCorrelation ->SetLineColor(color);
835 fhCutStatistics ->SetLineWidth(2);
836 fhCutCorrelation ->SetLineWidth(2);
837
0b75bef2 838 Char_t str[256];
839 for (Int_t i=0; i<2; i++) {
840 if (i==0) sprintf(str," ");
841 else sprintf(str,"_cut");
842
3c4b53f0 843 fhNClustersITS[i] = new TH1F(Form("nClustersITS%s",str) ,"",8,-0.5,7.5);
844 fhNClustersTPC[i] = new TH1F(Form("nClustersTPC%s",str) ,"",165,-0.5,164.5);
ebd60d8e 845 fhChi2PerClusterITS[i] = new TH1F(Form("chi2PerClusterITS%s",str),"",500,0,10);
846 fhChi2PerClusterTPC[i] = new TH1F(Form("chi2PerClusterTPC%s",str),"",500,0,10);
847
3c4b53f0 848 fhC11[i] = new TH1F(Form("covMatrixDiagonal11%s",str),"",2000,0,20);
d8594d03 849 fhC22[i] = new TH1F(Form("covMatrixDiagonal22%s",str),"",2000,0,20);
850 fhC33[i] = new TH1F(Form("covMatrixDiagonal33%s",str),"",1000,0,1);
ebd60d8e 851 fhC44[i] = new TH1F(Form("covMatrixDiagonal44%s",str),"",1000,0,5);
852 fhC55[i] = new TH1F(Form("covMatrixDiagonal55%s",str),"",1000,0,5);
853
3c4b53f0 854 fhDXY[i] = new TH1F(Form("dXY%s",str) ,"",500,-10,10);
855 fhDZ[i] = new TH1F(Form("dZ%s",str) ,"",500,-10,10);
ebd60d8e 856 fhDXYvsDZ[i] = new TH2F(Form("dXYvsDZ%s",str),"",200,-10,10,200,-10,10);
857
3c4b53f0 858 fhDXYNormalized[i] = new TH1F(Form("dXYNormalized%s",str) ,"",500,-10,10);
859 fhDZNormalized[i] = new TH1F(Form("dZNormalized%s",str) ,"",500,-10,10);
ebd60d8e 860 fhDXYvsDZNormalized[i] = new TH2F(Form("dXYvsDZNormalized%s",str),"",200,-10,10,200,-10,10);
861
129a66bb 862 fhNSigmaToVertex[i] = new TH1F(Form("nSigmaToVertex%s",str),"",500,0,50);
ebd60d8e 863
3c4b53f0 864 fhNClustersITS[i]->SetTitle("n ITS clusters");
865 fhNClustersTPC[i]->SetTitle("n TPC clusters");
866 fhChi2PerClusterITS[i]->SetTitle("#Chi^{2} per ITS cluster");
867 fhChi2PerClusterTPC[i]->SetTitle("#Chi^{2} per TPC cluster");
ebd60d8e 868
3c4b53f0 869 fhC11[i]->SetTitle("cov 11 : #sigma_{y}^{2} [cm^{2}]");
870 fhC22[i]->SetTitle("cov 22 : #sigma_{z}^{2} [cm^{2}]");
871 fhC33[i]->SetTitle("cov 33 : #sigma_{sin(#phi)}^{2}");
872 fhC44[i]->SetTitle("cov 44 : #sigma_{tan(#theta_{dip})}^{2}");
873 fhC55[i]->SetTitle("cov 55 : #sigma_{1/p_{T}}^{2} [(c/GeV)^2]");
ebd60d8e 874
3c4b53f0 875 fhDXY[i]->SetTitle("transverse impact parameter");
876 fhDZ[i]->SetTitle("longitudinal impact parameter");
877 fhDXYvsDZ[i]->SetTitle("longitudinal impact parameter");
ebd60d8e 878 fhDXYvsDZ[i]->SetYTitle("transverse impact parameter");
879
3c4b53f0 880 fhDXYNormalized[i]->SetTitle("normalized trans impact par");
881 fhDZNormalized[i]->SetTitle("normalized long impact par");
882 fhDXYvsDZNormalized[i]->SetTitle("normalized long impact par");
ebd60d8e 883 fhDXYvsDZNormalized[i]->SetYTitle("normalized trans impact par");
3c4b53f0 884 fhNSigmaToVertex[i]->SetTitle("n #sigma to vertex");
ebd60d8e 885
886 fhNClustersITS[i]->SetLineColor(color); fhNClustersITS[i]->SetLineWidth(2);
887 fhNClustersTPC[i]->SetLineColor(color); fhNClustersTPC[i]->SetLineWidth(2);
888 fhChi2PerClusterITS[i]->SetLineColor(color); fhChi2PerClusterITS[i]->SetLineWidth(2);
889 fhChi2PerClusterTPC[i]->SetLineColor(color); fhChi2PerClusterTPC[i]->SetLineWidth(2);
890
891 fhC11[i]->SetLineColor(color); fhC11[i]->SetLineWidth(2);
892 fhC22[i]->SetLineColor(color); fhC22[i]->SetLineWidth(2);
893 fhC33[i]->SetLineColor(color); fhC33[i]->SetLineWidth(2);
894 fhC44[i]->SetLineColor(color); fhC44[i]->SetLineWidth(2);
895 fhC55[i]->SetLineColor(color); fhC55[i]->SetLineWidth(2);
896
897 fhDXY[i]->SetLineColor(color); fhDXY[i]->SetLineWidth(2);
898 fhDZ[i]->SetLineColor(color); fhDZ[i]->SetLineWidth(2);
899
900 fhDXYNormalized[i]->SetLineColor(color); fhDXYNormalized[i]->SetLineWidth(2);
129a66bb 901 fhDZNormalized[i]->SetLineColor(color); fhDZNormalized[i]->SetLineWidth(2);
902 fhNSigmaToVertex[i]->SetLineColor(color); fhNSigmaToVertex[i]->SetLineWidth(2);
0b75bef2 903 }
129a66bb 904
905 // The number of sigmas to the vertex is per definition gaussian
906 ffDTheoretical = new TF1("nSigmaToVertexTheoretical","([0]/2.506628274)*exp(-(x**2)/2)",0,50);
907 ffDTheoretical->SetParameter(0,1);
3c4b53f0 908
909 TH1::AddDirectory(oldStatus);
0b75bef2 910}
911
912//____________________________________________________________________
3c4b53f0 913Bool_t AliESDtrackCuts::LoadHistograms(const Char_t* dir)
914{
ab2c1f0d 915 //
3c4b53f0 916 // loads the histograms from a file
917 // if dir is empty a directory with the name of this object is taken (like in SaveHistogram)
ab2c1f0d 918 //
0b75bef2 919
3c4b53f0 920 if (!dir)
921 dir = GetName();
922
923 if (!gDirectory->cd(dir))
924 return kFALSE;
925
926 ffDTheoretical = dynamic_cast<TF1*> (gDirectory->Get("nSigmaToVertexTheory"));
927
928 fhCutStatistics = dynamic_cast<TH1F*> (gDirectory->Get("cut_statistics"));
929 fhCutCorrelation = dynamic_cast<TH2F*> (gDirectory->Get("cut_correlation"));
930
931 Char_t str[5];
932 for (Int_t i=0; i<2; i++) {
933 if (i==0)
934 {
935 gDirectory->cd("before_cuts");
936 str[0] = 0;
937 }
938 else
939 {
940 gDirectory->cd("after_cuts");
941 sprintf(str,"_cut");
942 }
943
944 fhNClustersITS[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("nClustersITS%s",str) ));
945 fhNClustersTPC[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("nClustersTPC%s",str) ));
946 fhChi2PerClusterITS[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("chi2PerClusterITS%s",str)));
947 fhChi2PerClusterTPC[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("chi2PerClusterTPC%s",str)));
948
949 fhC11[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("covMatrixDiagonal11%s",str)));
950 fhC22[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("covMatrixDiagonal22%s",str)));
951 fhC33[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("covMatrixDiagonal33%s",str)));
952 fhC44[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("covMatrixDiagonal44%s",str)));
953 fhC55[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("covMatrixDiagonal55%s",str)));
954
955 fhDXY[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("dXY%s",str) ));
956 fhDZ[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("dZ%s",str) ));
957 fhDXYvsDZ[i] = dynamic_cast<TH2F*> (gDirectory->Get(Form("dXYvsDZ%s",str)));
958
959 fhDXYNormalized[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("dXYNormalized%s",str) ));
960 fhDZNormalized[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("dZNormalized%s",str) ));
961 fhDXYvsDZNormalized[i] = dynamic_cast<TH2F*> (gDirectory->Get(Form("dXYvsDZNormalized%s",str)));
962
963 fhNSigmaToVertex[i] = dynamic_cast<TH1F*> (gDirectory->Get(Form("nSigmaToVertex%s",str)));
964
965 // TODO only temporary
966 /*fhNClustersITS[i]->SetTitle("n ITS clusters");
967 fhNClustersTPC[i]->SetTitle("n TPC clusters");
968 fhChi2PerClusterITS[i]->SetTitle("#Chi^{2} per ITS cluster");
969 fhChi2PerClusterTPC[i]->SetTitle("#Chi^{2} per TPC cluster");
970
971 fhC11[i]->SetTitle("cov 11 : #sigma_{y}^{2} [cm^{2}]");
972 fhC22[i]->SetTitle("cov 22 : #sigma_{z}^{2} [cm^{2}]");
973 fhC33[i]->SetTitle("cov 33 : #sigma_{sin(#phi)}^{2}");
974 fhC44[i]->SetTitle("cov 44 : #sigma_{tan(#theta_{dip})}^{2}");
975 fhC55[i]->SetTitle("cov 55 : #sigma_{1/p_{T}}^{2} [(c/GeV)^2]");
976
977 fhDXY[i]->SetTitle("transverse impact parameter");
978 fhDZ[i]->SetTitle("longitudinal impact parameter");
979 fhDXYvsDZ[i]->SetTitle("longitudinal impact parameter");
980 fhDXYvsDZ[i]->SetYTitle("transverse impact parameter");
0b75bef2 981
3c4b53f0 982 fhDXYNormalized[i]->SetTitle("normalized trans impact par");
983 fhDZNormalized[i]->SetTitle("normalized long impact par");
984 fhDXYvsDZNormalized[i]->SetTitle("normalized long impact par");
985 fhDXYvsDZNormalized[i]->SetYTitle("normalized trans impact par");
986 fhNSigmaToVertex[i]->SetTitle("n #sigma to vertex");*/
987
988 gDirectory->cd("../");
989 }
990
991 gDirectory->cd("..");
992
993 return kTRUE;
994}
0b75bef2 995
996//____________________________________________________________________
3c4b53f0 997void AliESDtrackCuts::SaveHistograms(const Char_t* dir) {
998 //
ab2c1f0d 999 // saves the histograms in a directory (dir)
3c4b53f0 1000 //
ab2c1f0d 1001
0b75bef2 1002 if (!fHistogramsOn) {
1003 AliDebug(0, "Histograms not on - cannot save histograms!!!");
1004 return;
1005 }
1006
3c4b53f0 1007 if (!dir)
1008 dir = GetName();
1009
0b75bef2 1010 gDirectory->mkdir(dir);
1011 gDirectory->cd(dir);
1012
1013 gDirectory->mkdir("before_cuts");
1014 gDirectory->mkdir("after_cuts");
1015
129a66bb 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
f58f1a93 1020 fhCutStatistics->Write();
1021 fhCutCorrelation->Write();
0b75bef2 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");
3c4b53f0 1028
f58f1a93 1029 fhNClustersITS[i] ->Write();
1030 fhNClustersTPC[i] ->Write();
1031 fhChi2PerClusterITS[i] ->Write();
1032 fhChi2PerClusterTPC[i] ->Write();
3c4b53f0 1033
f58f1a93 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();
3c4b53f0 1043
f58f1a93 1044 fhDXYNormalized[i] ->Write();
1045 fhDZNormalized[i] ->Write();
1046 fhDXYvsDZNormalized[i] ->Write();
129a66bb 1047 fhNSigmaToVertex[i] ->Write();
0b75bef2 1048
1049 gDirectory->cd("../");
1050 }
1051
1052 gDirectory->cd("../");
1053}
1054
3c4b53f0 1055//____________________________________________________________________
1056void AliESDtrackCuts::DrawHistograms()
1057{
1058 // draws some histograms
1059
1060 TCanvas* canvas1 = new TCanvas(Form("%s_1", GetName()), "Track Quality Results1", 800, 800);
1061 canvas1->Divide(2, 2);
1062
1063 canvas1->cd(1);
1064 fhNClustersTPC[0]->SetStats(kFALSE);
1065 fhNClustersTPC[0]->Draw();
1066
1067 canvas1->cd(2);
1068 fhChi2PerClusterTPC[0]->SetStats(kFALSE);
1069 fhChi2PerClusterTPC[0]->Draw();
1070
1071 canvas1->cd(3);
1072 fhNSigmaToVertex[0]->SetStats(kFALSE);
1073 fhNSigmaToVertex[0]->GetXaxis()->SetRangeUser(0, 10);
1074 fhNSigmaToVertex[0]->Draw();
1075
1076 canvas1->SaveAs(Form("%s_%s.gif", GetName(), canvas1->GetName()));
1077
1078 TCanvas* canvas2 = new TCanvas(Form("%s_2", GetName()), "Track Quality Results2", 1200, 800);
1079 canvas2->Divide(3, 2);
1080
1081 canvas2->cd(1);
1082 fhC11[0]->SetStats(kFALSE);
1083 gPad->SetLogy();
1084 fhC11[0]->Draw();
1085
1086 canvas2->cd(2);
1087 fhC22[0]->SetStats(kFALSE);
1088 gPad->SetLogy();
1089 fhC22[0]->Draw();
1090
1091 canvas2->cd(3);
1092 fhC33[0]->SetStats(kFALSE);
1093 gPad->SetLogy();
1094 fhC33[0]->Draw();
1095
1096 canvas2->cd(4);
1097 fhC44[0]->SetStats(kFALSE);
1098 gPad->SetLogy();
1099 fhC44[0]->Draw();
1100
1101 canvas2->cd(5);
1102 fhC55[0]->SetStats(kFALSE);
1103 gPad->SetLogy();
1104 fhC55[0]->Draw();
1105
1106 canvas2->SaveAs(Form("%s_%s.gif", GetName(), canvas2->GetName()));
1107
1108 TCanvas* canvas3 = new TCanvas(Form("%s_3", GetName()), "Track Quality Results3", 1200, 800);
1109 canvas3->Divide(3, 2);
1110
1111 canvas3->cd(1);
1112 fhDXY[0]->SetStats(kFALSE);
1113 gPad->SetLogy();
1114 fhDXY[0]->Draw();
1115
1116 canvas3->cd(2);
1117 fhDZ[0]->SetStats(kFALSE);
1118 gPad->SetLogy();
1119 fhDZ[0]->Draw();
1120
1121 canvas3->cd(3);
1122 fhDXYvsDZ[0]->SetStats(kFALSE);
1123 gPad->SetLogz();
1124 gPad->SetRightMargin(0.15);
1125 fhDXYvsDZ[0]->Draw("COLZ");
1126
1127 canvas3->cd(4);
1128 fhDXYNormalized[0]->SetStats(kFALSE);
1129 gPad->SetLogy();
1130 fhDXYNormalized[0]->Draw();
1131
1132 canvas3->cd(5);
1133 fhDZNormalized[0]->SetStats(kFALSE);
1134 gPad->SetLogy();
1135 fhDZNormalized[0]->Draw();
1136
1137 canvas3->cd(6);
1138 fhDXYvsDZNormalized[0]->SetStats(kFALSE);
1139 gPad->SetLogz();
1140 gPad->SetRightMargin(0.15);
1141 fhDXYvsDZNormalized[0]->Draw("COLZ");
1142
1143 canvas3->SaveAs(Form("%s_%s.gif", GetName(), canvas3->GetName()));
1144
1145 TCanvas* canvas4 = new TCanvas(Form("%s_4", GetName()), "Track Quality Results4", 800, 500);
1146 canvas4->Divide(2, 1);
1147
1148 canvas4->cd(1);
1149 fhCutStatistics->SetStats(kFALSE);
1150 fhCutStatistics->LabelsOption("v");
1151 gPad->SetBottomMargin(0.3);
1152 fhCutStatistics->Draw();
1153
1154 canvas4->cd(2);
1155 fhCutCorrelation->SetStats(kFALSE);
1156 fhCutCorrelation->LabelsOption("v");
1157 gPad->SetBottomMargin(0.3);
1158 gPad->SetLeftMargin(0.3);
1159 fhCutCorrelation->Draw("COLZ");
1160
1161 canvas4->SaveAs(Form("%s_%s.gif", GetName(), canvas4->GetName()));
1162
1163 /*canvas->cd(1);
1164 fhDXYvsDZNormalized[0]->SetStats(kFALSE);
1165 fhDXYvsDZNormalized[0]->DrawCopy("COLZ");
1166
1167 canvas->cd(2);
1168 fhNClustersTPC[0]->SetStats(kFALSE);
1169 fhNClustersTPC[0]->DrawCopy();
1170
1171 canvas->cd(3);
1172 fhChi2PerClusterITS[0]->SetStats(kFALSE);
1173 fhChi2PerClusterITS[0]->DrawCopy();
1174 fhChi2PerClusterITS[1]->SetLineColor(2);
1175 fhChi2PerClusterITS[1]->DrawCopy("SAME");
1176
1177 canvas->cd(4);
1178 fhChi2PerClusterTPC[0]->SetStats(kFALSE);
1179 fhChi2PerClusterTPC[0]->DrawCopy();
1180 fhChi2PerClusterTPC[1]->SetLineColor(2);
1181 fhChi2PerClusterTPC[1]->DrawCopy("SAME");*/
1182}
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