source: trunk/MagicSoft/Mars/mhcalib/MHGausEvents.h@ 4964

Last change on this file since 4964 was 4962, checked in by gaug, 20 years ago
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1#ifndef MARS_MHGausEvents
2#define MARS_MHGausEvents
3
4#ifndef ROOT_TH1
5#include <TH1.h>
6#endif
7
8#ifndef MARS_MH
9#include "MH.h"
10#endif
11
12#ifndef MARS_MArrayF
13#include "MArrayF.h"
14#endif
15
16class TVirtualPad;
17class TGraph;
18class MArrayF;
19class TH1F;
20class TH1I;
21class TF1;
22class MHGausEvents : public MH
23{
24private:
25
26 const static Int_t fgNDFLimit; //! Default for fNDFLimit (now set to: 2)
27 const static Float_t fgProbLimit; //! Default for fProbLimit (now set to: 0.001)
28 const static Int_t fgPowerProbabilityBins; //! Default for fPowerProbabilityBins (now set to: 20)
29
30protected:
31
32 Int_t fBinsAfterStripping; // Bins for the Gauss Histogram after stripping off the zeros at both ends
33 UInt_t fCurrentSize; // Current size of the array fEvents
34 Byte_t fFlags; // Bit field for the fit result bits
35 Int_t fPowerProbabilityBins; // Bins for the projected power spectrum
36
37 TH1I *fHPowerProbability; // Fourier transform of fEvents projected on y-axis
38 MArrayF *fPowerSpectrum; // Fourier transform of fEvents
39
40 enum { kGausFitOK,
41 kExpFitOK,
42 kFourierSpectrumOK,
43 kExcluded }; // Bits for information about fit results
44
45 MArrayF fEvents; // Array which holds the entries of GausHist
46 TF1 *fFGausFit; // Gauss fit for fHGausHist
47 TF1 *fFExpFit; // Exponential fit for FHPowerProbability
48 Axis_t fFirst; // Lower histogram edge for fHGausHist (used by InitBins())
49 TGraph *fGraphEvents; //! TGraph to display the event array (will not be cloned!!)
50 TGraph *fGraphPowerSpectrum; //! TGraph to display the power spectrum array (will not be cloned!!)
51 TH1F fHGausHist; // Histogram to hold the Gaussian distribution
52 Axis_t fLast; // Upper histogram edge for fHGausHist (used by InitBins())
53 Double_t fMean; // Mean of the Gauss fit
54 Double_t fMeanErr; // Error of the mean of the Gauss fit
55 Int_t fNbins; // Number histogram bins for fHGausHist (used by InitBins())
56 Int_t fNDFLimit; // NDF limit for judgement if fit is OK
57 Double_t fSigma; // Sigma of the Gauss fit
58 Double_t fSigmaErr; // Error of the sigma of the Gauss fit
59 Double_t fProb; // Probability of the Gauss fit
60 Float_t fProbLimit; // Probability limit for judgement if fit is OK
61
62 virtual Float_t *CreateEventXaxis(Int_t n); // Create an x-axis for the Event TGraphs
63 virtual Float_t *CreatePSDXaxis(Int_t n); // Create an x-axis for the PSD TGraphs
64
65 void DrawPowerSpectrum(TVirtualPad &pad, Int_t i); // Draw graph of fPowerSpectrum and fHPowerProbability
66
67 // Setters
68 void SetBinsAfterStripping ( const Int_t nbins=0 ) { fBinsAfterStripping =nbins; }
69 void SetPowerProbabilityBins ( const Int_t nbins=fgPowerProbabilityBins ) { fPowerProbabilityBins=nbins; }
70
71public:
72
73 MHGausEvents(const char* name=NULL, const char* title=NULL);
74 ~MHGausEvents();
75
76 TObject *Clone(const char* name="") const;
77
78 void Clear(Option_t *o="");
79 void Reset();
80
81 // Draws
82 void Draw(Option_t *option=""); // Default Draw
83 void DrawEvents(Option_t *option=""); // Draw graph of fEvents
84
85 // Inits
86 virtual void InitBins();
87
88 // Getters
89 const Double_t GetChiSquare() const;
90 const Double_t GetExpChiSquare() const;
91 const Int_t GetExpNdf() const;
92 const Double_t GetExpProb() const;
93 MArrayF *GetEvents() { return &fEvents; }
94 const MArrayF *GetEvents() const { return &fEvents; }
95 TF1 *GetFExpFit() { return fFExpFit; }
96 const TF1 *GetFExpFit() const { return fFExpFit; }
97 TF1 *GetFGausFit() { return fFGausFit; }
98 const TF1 *GetFGausFit() const { return fFGausFit; }
99 TGraph *GetGraphEvents() { return fGraphEvents; }
100 const Double_t GetFirst() const { return fFirst; }
101 const Double_t GetLast () const { return fLast ; }
102 const TGraph *GetGraphEvents() const { return fGraphEvents; }
103 TGraph *GetGraphPowerSpectrum() { return fGraphPowerSpectrum; }
104 const TGraph *GetGraphPowerSpectrum() const { return fGraphPowerSpectrum; }
105 TH1F *GetHGausHist() { return &fHGausHist; }
106 const TH1F *GetHGausHist() const { return &fHGausHist; }
107 TH1I *GetHPowerProbability() { return fHPowerProbability; }
108 const TH1I *GetHPowerProbability() const { return fHPowerProbability; }
109 const Double_t GetMean() const { return fMean; }
110 const Double_t GetMeanErr() const { return fMeanErr; }
111 const Int_t GetNdf() const;
112 const Int_t GetNbins() const { return fNbins; }
113 const Double_t GetOffset() const;
114 MArrayF *GetPowerSpectrum() { return fPowerSpectrum; }
115 const MArrayF *GetPowerSpectrum() const { return fPowerSpectrum; }
116 const Double_t GetProb() const { return fProb; }
117 const Double_t GetSigma() const { return fSigma; }
118 const Double_t GetSigmaErr() const { return fSigmaErr; }
119 const Double_t GetSlope() const;
120
121 const Bool_t IsExcluded() const;
122 const Bool_t IsExpFitOK() const;
123 const Bool_t IsEmpty() const;
124 const Bool_t IsFourierSpectrumOK() const;
125 const Bool_t IsGausFitOK() const;
126 const Bool_t IsOnlyOverflow() const;
127 const Bool_t IsOnlyUnderflow() const;
128
129 // Fill
130 void FillArray ( const Float_t f ); // Fill only the array fEvents
131 Bool_t FillHist ( const Float_t f ); // Fill only the histogram HGausHist
132 Bool_t FillHistAndArray( const Float_t f ); // Fill bothe the array fEvents and the histogram HGausHist
133
134 // Fits
135 Bool_t FitGaus( Option_t *option="RQ0",
136 const Double_t xmin=0.,
137 const Double_t xmax=0.); // Fit the histogram HGausHist with a Gaussian
138
139 // Prints
140 virtual void Print(const Option_t *o="") const; // Default Print
141
142 // Setters
143 void SetExcluded ( const Bool_t b=kTRUE );
144 void SetExpFitOK ( const Bool_t b=kTRUE );
145 void SetFourierSpectrumOK( const Bool_t b=kTRUE );
146 void SetGausFitOK ( const Bool_t b=kTRUE );
147 void SetLast ( const Double_t d ) { fLast = d; }
148 void SetFirst ( const Double_t d ) { fFirst = d; }
149 void SetMean ( const Double_t d ) { fMean = d; }
150 void SetMeanErr ( const Double_t d ) { fMeanErr = d; }
151 void SetNbins ( const Int_t i ) { fNbins = i; }
152 void SetNDFLimit ( const Int_t lim=fgNDFLimit ) { fNDFLimit = lim; }
153 void SetProb ( const Double_t d ) { fProb = d; }
154 void SetProbLimit ( const Float_t lim=fgProbLimit ) { fProbLimit = lim; }
155 void SetSigma ( const Double_t d ) { fSigma = d; }
156 void SetSigmaErr ( const Double_t d ) { fSigmaErr = d; }
157
158 void CreateFourierSpectrum(); // Create the fourier spectrum out of fEvents
159 virtual void CreateGraphEvents(); // Create the TGraph fGraphEvents of fEvents
160 virtual void CreateGraphPowerSpectrum(); // Create the TGraph fGraphPowerSpectrum out of fPowerSpectrum
161
162 ClassDef(MHGausEvents, 1) // Base class for events with Gaussian distributed values
163};
164
165#endif
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