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