source: trunk/MagicSoft/Mars/mcalib/MHGausEvents.h@ 3243

Last change on this file since 3243 was 3192, checked in by gaug, 21 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
12class TVirtualPad;
13class TGraph;
14class TArrayF;
15class TH1F;
16class TH1I;
17class TF1;
18class MHGausEvents : public MH
19{
20private:
21
22 const static Float_t fgProbLimit; // Default probability limit for judgement if fit is OK
23 const static Int_t fgNDFLimit; // Default NDF limit for judgement if fit is OK
24 const static Int_t fgPowerProbabilityBins; // Default number of bins for the projected power spectrum
25 const static Int_t fgBinsAfterStripping; // Default number of bins for the Gauss Histogram after stripping off the zeros at both end
26
27 Float_t fProbLimit; // Probability limit for judgement if fit is OK
28 Int_t fNDFLimit; // NDF limit for judgement if fit is OK
29 Int_t fPowerProbabilityBins; // number of bins for the projected power spectrum
30 Int_t fBinsAfterStripping; // number of bins for the Gauss Histogram after stripping off the zeros at both end
31 Float_t fEventFrequency; // The event frequency in Hertz (to be set)
32
33 TF1 *fFGausFit; //-> Gauss fit for fHGausHist
34 TF1 *fFExpFit; //-> Exponential fit for FHPowerProbability
35
36 TH1I *fHPowerProbability; //-> Fourier transform of fEvents projected on y-axis
37
38 TArrayF *fPowerSpectrum; //-> Fourier transform of fEvents
39
40 TGraph *fGraphEvents; //! TGraph to display the event array (will not be cloned!!)
41 TGraph *fGraphPowerSpectrum; //! TGraph to display the power spectrum array (will not be cloned!!)
42
43 Float_t *CreateXaxis(Int_t n); // Create an x-axis for the TGraphs
44
45 Double_t fMean; // Mean of the Gauss fit
46 Double_t fSigma; // Sigma of the Gauss fit
47 Double_t fMeanErr; // Error of the mean of the Gauss fit
48 Double_t fSigmaErr; // Error of the sigma of the Gauss fit
49 Double_t fProb; // Probability of the Gauss fit (derived from Chi-Square and NDF
50
51 enum { kGausFitOK, kExpFitOK, kFourierSpectrumOK }; // Bits to hold information about fit results
52
53 Byte_t fFlags; // Byte to hold the bits fit result bits
54
55 UInt_t fCurrentSize; // Current size of the array fEvents
56
57protected:
58
59 TH1F fHGausHist; // Histogram which should hold the Gaussian distribution
60 TArrayF fEvents; // Array which holds the entries of GausHist
61
62 // Setters
63 void SetPowerProbabilityBins(const Int_t nbins=fgPowerProbabilityBins) { fPowerProbabilityBins = nbins; }
64 void SetBinsAfterStripping(const Int_t nbins=fgBinsAfterStripping) { fBinsAfterStripping = nbins; }
65
66 void DrawEvents(); // Draw a graph of the array fEvents
67 void DrawPowerSpectrum(TVirtualPad &pad, Int_t i); // Draw a graph of the array fPowerSpectrum and the hist fHPowerProbability
68
69public:
70
71 MHGausEvents(const char* name=NULL, const char* title=NULL);
72 ~MHGausEvents();
73
74 virtual void Clear(Option_t *o="");
75 virtual void Reset();
76
77 // Setters
78 void SetEventFrequency(const Float_t f=0) { fEventFrequency = f; }
79
80 void SetMean( const Double_t d ) { fMean = d; }
81 void SetMeanErr( const Double_t d ) { fMeanErr = d; }
82 void SetSigma( const Double_t d ) { fSigma = d; }
83 void SetSigmaErr( const Double_t d ) { fSigmaErr = d; }
84
85 void SetProbLimit( const Float_t lim=fgProbLimit ) { fProbLimit = lim; }
86 void SetNDFLimit( const Int_t lim=fgNDFLimit ) { fNDFLimit = lim; }
87
88 // Setters ONLY for MC:
89 void SetGausFitOK( const Bool_t b );
90 void SetExpFitOK( const Bool_t b );
91 void SetFourierSpectrumOK( const Bool_t b );
92
93 // Getters
94 const Double_t GetMean() const { return fMean; }
95 const Double_t GetMeanErr() const { return fMeanErr; }
96 const Double_t GetSigma() const { return fSigma; }
97 const Double_t GetSigmaErr() const { return fSigmaErr; }
98 const Double_t GetChiSquare() const;
99 const Double_t GetProb() const { return fProb; }
100 const Int_t GetNdf() const;
101
102 const Double_t GetSlope() const;
103 const Double_t GetOffset() const;
104 const Double_t GetExpChiSquare() const;
105 const Double_t GetExpProb() const;
106 const Int_t GetExpNdf() const;
107
108 TH1F *GetHGausHist() { return &fHGausHist; }
109 const TH1F *GetHGausHist() const { return &fHGausHist; }
110
111 TArrayF *GetEvents() { return &fEvents; }
112 const TArrayF *GetEvents() const { return &fEvents; }
113
114 TArrayF *GetPowerSpectrum() { return fPowerSpectrum; }
115 const TArrayF *GetPowerSpectrum() const { return fPowerSpectrum; }
116
117 TF1 *GetFGausFit() { return fFGausFit; }
118 const TF1 *GetFGausFit() const { return fFGausFit; }
119
120 TH1I *GetHPowerProbability() { return fHPowerProbability; }
121 const TH1I *GetHPowerProbability() const { return fHPowerProbability; }
122
123 TF1 *GetFExpFit() { return fFExpFit; }
124 const TF1 *GetFExpFit() const { return fFExpFit; }
125
126 TGraph *GetGraphEvents() { return fGraphEvents; }
127 const TGraph *GetGraphEvents() const { return fGraphEvents; }
128
129 TGraph *GetGraphPowerSpectrum() { return fGraphPowerSpectrum; }
130 const TGraph *GetGraphPowerSpectrum() const { return fGraphPowerSpectrum; }
131
132 const Bool_t IsGausFitOK() const;
133 const Bool_t IsExpFitOK() const;
134 const Bool_t IsEmpty() const;
135 const Bool_t IsFourierSpectrumOK() const;
136
137 // Fill
138 void FillArray(const Float_t f); // Fill only the array fEvents
139 Bool_t FillHist(const Float_t f); // Fill only the histogram HGausHist
140 Bool_t FillHistAndArray(const Float_t f); // Fill bothe the array fEvents and the histogram HGausHist
141
142 // Fits
143 Bool_t FitGaus(Option_t *option="RQ0"); // Fit the histogram HGausHist with a Gaussian
144
145 // Draws
146 virtual void Draw(Option_t *option=""); // Default Draw
147
148 // Prints
149 virtual void Print(const Option_t *o="") const; // Default Print
150
151 // Miscelleaneous
152 void CreateFourierSpectrum(); // Create the fourier spectrum out of fEvents
153 void CreateGraphEvents(); // Create the TGraph fGraphEvents of fEvents
154 void CreateGraphPowerSpectrum(); // Create the TGraph fGraphPowerSpectrum out of fPowerSpectrum
155
156 ClassDef(MHGausEvents, 1) // Base class for events with Gaussian distributed values
157};
158
159#endif
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