#ifndef MARS_MHGausEvents #define MARS_MHGausEvents #ifndef ROOT_TH1 #include #endif #ifndef MARS_MH #include "MH.h" #endif class TVirtualPad; class TGraph; class TArrayF; class TH1F; class TH1I; class TF1; class MHGausEvents : public MH { private: const static Float_t fgProbLimit; // Default probability limit for judgement if fit is OK const static Int_t fgNDFLimit; // Default NDF limit for judgement if fit is OK const static Int_t fgPowerProbabilityBins; // Default number of bins for the projected power spectrum const static Int_t fgBinsAfterStripping; // Default number of bins for the Gauss Histogram after stripping off the zeros at both end Int_t fPowerProbabilityBins; // number of bins for the projected power spectrum Int_t fBinsAfterStripping; // number of bins for the Gauss Histogram after stripping off the zeros at both end Float_t fEventFrequency; // The event frequency in Hertz (to be set) TH1I *fHPowerProbability; // Fourier transform of fEvents projected on y-axis TArrayF *fPowerSpectrum; // Fourier transform of fEvents TGraph *fGraphEvents; //! TGraph to display the event array (will not be cloned!!) TGraph *fGraphPowerSpectrum; //! TGraph to display the power spectrum array (will not be cloned!!) Double_t fMean; // Mean of the Gauss fit Double_t fSigma; // Sigma of the Gauss fit Double_t fMeanErr; // Error of the mean of the Gauss fit Double_t fSigmaErr; // Error of the sigma of the Gauss fit Double_t fProb; // Probability of the Gauss fit (derived from Chi-Square and NDF enum { kGausFitOK, kExpFitOK, kFourierSpectrumOK }; // Bits to hold information about fit results Byte_t fFlags; // Byte to hold the bits fit result bits Int_t fCurrentSize; // Current size of the array fEvents protected: TH1F fHGausHist; // Histogram which should hold the Gaussian distribution TArrayF fEvents; // Array which holds the entries of GausHist TF1 *fFGausFit; // Gauss fit for fHGausHist TF1 *fFExpFit; // Exponential fit for FHPowerProbability Float_t fProbLimit; // Probability limit for judgement if fit is OK Int_t fNDFLimit; // NDF limit for judgement if fit is OK // Setters void SetPowerProbabilityBins ( const Int_t nbins=fgPowerProbabilityBins ) { fPowerProbabilityBins = nbins; } void SetBinsAfterStripping ( const Int_t nbins=fgBinsAfterStripping ) { fBinsAfterStripping = nbins; } void DrawEvents(); // Draw a graph of the array fEvents void DrawPowerSpectrum(TVirtualPad &pad, Int_t i); // Draw a graph of the array fPowerSpectrum and the hist fHPowerProbability Float_t *CreateXaxis(Int_t n); // Create an x-axis for the TGraphs public: MHGausEvents(const char* name=NULL, const char* title=NULL); ~MHGausEvents(); virtual void Clear(Option_t *o=""); virtual void Reset(); // Setters void SetEventFrequency(const Float_t f=0) { fEventFrequency = f; } void SetMean ( const Double_t d ) { fMean = d; } void SetMeanErr ( const Double_t d ) { fMeanErr = d; } void SetSigma ( const Double_t d ) { fSigma = d; } void SetSigmaErr( const Double_t d ) { fSigmaErr = d; } void SetProb ( const Double_t d ) { fProb = d; } void SetProbLimit( const Float_t lim=fgProbLimit ) { fProbLimit = lim; } void SetNDFLimit( const Int_t lim=fgNDFLimit ) { fNDFLimit = lim; } // Setters ONLY for MC: void SetGausFitOK( const Bool_t b ); void SetExpFitOK( const Bool_t b ); void SetFourierSpectrumOK( const Bool_t b ); // Getters const Double_t GetMean() const { return fMean; } const Double_t GetMeanErr() const { return fMeanErr; } const Double_t GetSigma() const { return fSigma; } const Double_t GetSigmaErr() const { return fSigmaErr; } const Double_t GetChiSquare() const; const Double_t GetProb() const { return fProb; } const Int_t GetNdf() const; const Double_t GetSlope() const; const Double_t GetOffset() const; const Double_t GetExpChiSquare() const; const Double_t GetExpProb() const; const Int_t GetExpNdf() const; TH1F *GetHGausHist() { return &fHGausHist; } const TH1F *GetHGausHist() const { return &fHGausHist; } TArrayF *GetEvents() { return &fEvents; } const TArrayF *GetEvents() const { return &fEvents; } TArrayF *GetPowerSpectrum() { return fPowerSpectrum; } const TArrayF *GetPowerSpectrum() const { return fPowerSpectrum; } TF1 *GetFGausFit() { return fFGausFit; } const TF1 *GetFGausFit() const { return fFGausFit; } TH1I *GetHPowerProbability() { return fHPowerProbability; } const TH1I *GetHPowerProbability() const { return fHPowerProbability; } TF1 *GetFExpFit() { return fFExpFit; } const TF1 *GetFExpFit() const { return fFExpFit; } TGraph *GetGraphEvents() { return fGraphEvents; } const TGraph *GetGraphEvents() const { return fGraphEvents; } TGraph *GetGraphPowerSpectrum() { return fGraphPowerSpectrum; } const TGraph *GetGraphPowerSpectrum() const { return fGraphPowerSpectrum; } const Bool_t IsGausFitOK() const; const Bool_t IsExpFitOK() const; const Bool_t IsEmpty() const; const Bool_t IsFourierSpectrumOK() const; // Fill void FillArray(const Float_t f); // Fill only the array fEvents Bool_t FillHist(const Float_t f); // Fill only the histogram HGausHist Bool_t FillHistAndArray(const Float_t f); // Fill bothe the array fEvents and the histogram HGausHist // Fits Bool_t FitGaus(Option_t *option="RQ0", const Double_t xmin=0., const Double_t xmax=0.); // Fit the histogram HGausHist with a Gaussian // Draws virtual void Draw(Option_t *option=""); // Default Draw // Prints virtual void Print(const Option_t *o="") const; // Default Print // Miscelleaneous void CreateFourierSpectrum(); // Create the fourier spectrum out of fEvents void CreateGraphEvents(); // Create the TGraph fGraphEvents of fEvents void CreateGraphPowerSpectrum(); // Create the TGraph fGraphPowerSpectrum out of fPowerSpectrum ClassDef(MHGausEvents, 1) // Base class for events with Gaussian distributed values }; #endif