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