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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 | // The class AliCFTrackQualityCuts is designed to select reconstructed tracks | |
17 | // of high quality and to provide corresponding QA histograms. | |
18 | // This class inherits from the Analysis' Framework abstract base class | |
19 | // AliAnalysisCuts and is a part of the Correction Framework. | |
20 | // This class acts on single, reconstructed tracks, it is applicable on | |
21 | // ESD and AOD data. | |
22 | // It mainly consists of a IsSelected function that returns a boolean. | |
23 | // This function checks whether the considered track passes a set of cuts: | |
24 | // - number of clusters in the TPC | |
25 | // - number of clusters in the ITS | |
26 | // - chi2 / cluster in the TPC | |
27 | // - chi2 / cluster in the ITS | |
28 | // - covariance matrix diagonal elements | |
29 | // - track status (cf AliESDtrack.h) | |
30 | // | |
31 | // The cut values for these cuts are set with the corresponding set functions. | |
32 | // All cut classes provided by the correction framework are supposed to be | |
33 | // added in the Analysis Framwork's class AliAnalysisFilter and applied by | |
34 | // the filter via a loop. | |
35 | // | |
36 | // author: I. Kraus (Ingrid.Kraus@cern.ch) | |
37 | // idea taken form | |
38 | // AliESDtrackCuts writte by Jan Fiete Grosse-Oetringhaus and | |
39 | // AliRsnDaughterCut class written by A. Pulvirenti. | |
40 | ||
41 | #ifndef ALICFTRACKQUALITYCUTS_H | |
42 | #define ALICFTRACKQUALITYCUTS_H | |
43 | ||
44 | #include "AliCFCutBase.h" | |
45 | ||
46 | class TH2F ; | |
47 | class TH1F ; | |
48 | class TBits; | |
49 | class AliESDtrack ; | |
50 | ||
51 | class AliCFTrackQualityCuts : public AliCFCutBase | |
52 | { | |
53 | public : | |
54 | AliCFTrackQualityCuts() ; | |
55 | AliCFTrackQualityCuts(Char_t* name, Char_t* title) ; | |
56 | AliCFTrackQualityCuts(const AliCFTrackQualityCuts& c) ; | |
57 | AliCFTrackQualityCuts& operator=(const AliCFTrackQualityCuts& c) ; | |
58 | ~AliCFTrackQualityCuts(); | |
59 | void Copy(TObject &c) const; | |
60 | ||
61 | Bool_t IsSelected(TObject* obj); | |
62 | Bool_t IsSelected(TList* /*list*/) {return kTRUE;} | |
63 | ||
64 | // cut value setter | |
65 | void SetMinNClusterTPC(Int_t cluster=-1) {fMinNClusterTPC = cluster;} | |
66 | void SetMinNClusterITS(Int_t cluster=-1) {fMinNClusterITS = cluster;} | |
67 | void SetMaxChi2PerClusterTPC(Double_t chi=1e99) {fMaxChi2PerClusterTPC = chi;} | |
68 | void SetMaxChi2PerClusterITS(Double_t chi=1e99) {fMaxChi2PerClusterITS = chi;} | |
69 | void SetMaxCovDiagonalElements(Float_t c1=1e99, Float_t c2=1e99, Float_t c3=1e99, Float_t c4=1e99, Float_t c5=1e99) | |
70 | {fCovariance11Max=c1;fCovariance22Max=c2;fCovariance33Max=c3;fCovariance44Max=c4;fCovariance55Max=c5;} | |
71 | void SetStatus(ULong_t status=0) {fStatus = status ;} | |
72 | ||
73 | // QA histograms | |
74 | void DrawHistograms(Bool_t drawLogScale=kTRUE); | |
75 | void SaveHistograms(const Char_t* dir = 0); | |
76 | void AddQAHistograms(TList *qaList); | |
77 | // QA histogram setter | |
78 | // please use indices from the enumeration below | |
79 | void SetHistogramBins(Int_t index, Int_t nbins, Double_t *bins); | |
80 | void SetHistogramBins(Int_t index, Int_t nbins, Double_t xmin, Double_t xmax); | |
81 | ||
82 | // indeces/counters for single selections | |
83 | enum { | |
84 | kCutClusterTPC=0, // number of clusters in TPC | |
85 | kCutClusterITS, // number of clusters in ITS | |
86 | kCutChi2TPC, // chi2 per cluster in TPC | |
87 | kCutChi2ITS, // chi2 per cluster in ITS | |
88 | kCutCovElement11, // diagonal element 11 of covariance matrix | |
89 | kCutCovElement22, // diagonal element 22 of covariance matrix | |
90 | kCutCovElement33, // diagonal element 33 of covariance matrix | |
91 | kCutCovElement44, // diagonal element 44 of covariance matrix | |
92 | kCutCovElement55, // diagonal element 55 of covariance matrix | |
93 | kCutStatus, // track status | |
94 | kNCuts=10, // number of single selections | |
95 | kNStepQA=2, // number of QA steps (before/after the cuts) | |
96 | kNHist=9 // number of QA histograms | |
97 | }; | |
98 | ||
99 | private: | |
100 | void SelectionBitMap(TObject* obj); | |
101 | void DefineHistograms(); // books histograms and TList | |
102 | void Initialise(); // sets everything to 0 | |
103 | void FillHistograms(TObject* obj, Bool_t b); | |
104 | // Fills histograms before and after cuts | |
105 | Double_t fMinNClusterTPC; // min number of clusters in TPC | |
106 | Double_t fMinNClusterITS; // min number of clusters in ITS | |
107 | Double_t fMaxChi2PerClusterTPC; // max chi2 per clusters in TPC | |
108 | Double_t fMaxChi2PerClusterITS; // max chi2 per clusters in ITS | |
109 | ||
110 | Double_t fCovariance11Max ; // max covariance matrix element 11 | |
111 | Double_t fCovariance22Max ; // max covariance matrix element 22 | |
112 | Double_t fCovariance33Max ; // max covariance matrix element 33 | |
113 | Double_t fCovariance44Max ; // max covariance matrix element 44 | |
114 | Double_t fCovariance55Max ; // max covariance matrix element 55 | |
115 | ||
116 | ULong_t fStatus; // track status | |
117 | ||
118 | TH1F* fhCutStatistics; // Histogram: statistics of what cuts the tracks did not survive | |
119 | TH2F* fhCutCorrelation; // Histogram: 2d statistics plot | |
120 | ||
121 | TH1F* fhQA[kNHist][kNStepQA]; // QA Histograms | |
122 | TBits *fBitmap ; // stores single selection decisions | |
123 | ||
124 | // QA histogram setters | |
125 | Int_t fhNBinsClusterTPC; // number of bins+1: cluster TPC | |
126 | Int_t fhNBinsClusterITS; // number of bins+1: cluster ITS | |
127 | Int_t fhNBinsChi2TPC; // number of bins+1: chi2 per cluster TPC | |
128 | Int_t fhNBinsChi2ITS; // number of bins+1: chi2 per cluster ITS | |
129 | Int_t fhNBinsCovariance11; // number of bins+1: covariance matrix element 11 | |
130 | Int_t fhNBinsCovariance22; // number of bins+1: covariance matrix element 22 | |
131 | Int_t fhNBinsCovariance33; // number of bins+1: covariance matrix element 33 | |
132 | Int_t fhNBinsCovariance44; // number of bins+1: covariance matrix element 44 | |
133 | Int_t fhNBinsCovariance55; // number of bins+1: covariance matrix element 55 | |
134 | ||
135 | Double_t *fhBinLimClusterTPC; //[fhNBinsClusterTPC] bin limits: cluster TPC | |
136 | Double_t *fhBinLimClusterITS; //[fhNBinsClusterITS] bin limits: cluster ITS | |
137 | Double_t *fhBinLimChi2TPC; //[fhNBinsChi2TPC] bin limits: chi2 per cluster TPC | |
138 | Double_t *fhBinLimChi2ITS; //[fhNBinsChi2ITS] bin limits: chi2 per cluster ITS | |
139 | Double_t *fhBinLimCovariance11;//[fhNBinsCovariance11] bin limits: covariance matrix element 11 | |
140 | Double_t *fhBinLimCovariance22;//[fhNBinsCovariance22] bin limits: covariance matrix element 22 | |
141 | Double_t *fhBinLimCovariance33;//[fhNBinsCovariance33] bin limits: covariance matrix element 33 | |
142 | Double_t *fhBinLimCovariance44;//[fhNBinsCovariance44] bin limits: covariance matrix element 44 | |
143 | Double_t *fhBinLimCovariance55;//[fhNBinsCovariance55] bin limits: covariance matrix element 55 | |
144 | ||
145 | ClassDef(AliCFTrackQualityCuts,3); | |
146 | }; | |
147 | ||
148 | #endif |