#ifndef MARS_MHCalibrationBlindPixel #define MARS_MHCalibrationBlindPixel #ifndef MARS_MH #include "MH.h" #endif #ifndef MARS_MHCalibrationConfig #include "MHCalibrationConfig.h" #endif #ifndef ROOT_TH1 #include "TH1.h" #endif #ifndef ROOT_TH1F #include "TH1F.h" #endif #ifndef ROOT_TF1 #include "TF1.h" #endif #ifndef ROOT_TPaveText #include "TPaveText.h" #endif const Double_t NoWay = 10000000000.0; class TMath; class MParList; class MHCalibrationBlindPixel : public MH { private: TH1F* fHBlindPixelCharge; //-> Histogram with the single Phe spectrum TH1I* fHBlindPixelTime; //-> Variance of summed FADC slices TH1I* fHBlindPixelChargevsN; //-> Summed Charge vs. Event Nr. TF1 *fSinglePheFit; TF1 *fTimeGausFit; TF1 *fSinglePhePedFit; Axis_t fBlindPixelChargefirst; Axis_t fBlindPixelChargelast; Int_t fBlindPixelChargenbins; void ResetBin(Int_t i); void DrawLegend(); TPaveText *fFitLegend; Bool_t fFitOK; Double_t fLambda; Double_t fMu0; Double_t fMu1; Double_t fSigma0; Double_t fSigma1; Double_t fLambdaErr; Double_t fMu0Err; Double_t fMu1Err; Double_t fSigma0Err; Double_t fSigma1Err; Double_t fChisquare; Double_t fProb; Int_t fNdf; Double_t fMeanTime; Double_t fMeanTimeErr; Double_t fSigmaTime; Double_t fSigmaTimeErr; Double_t fLambdaCheck; Double_t fLambdaCheckErr; public: MHCalibrationBlindPixel(const char *name=NULL, const char *title=NULL); ~MHCalibrationBlindPixel(); typedef Double_t (*BlindPixelFitFunc)(Double_t *, Double_t *); Bool_t FillBlindPixelCharge(Float_t q) { return fHBlindPixelCharge->Fill(q) > -1; } Bool_t FillBlindPixelTime(Int_t t) { return fHBlindPixelTime->Fill(t) > -1; } Bool_t FillBlindPixelChargevsN(Stat_t rq, Int_t t) { return fHBlindPixelChargevsN->Fill(t,rq) > -1; } const Double_t GetLambda() const { return fLambda; } const Double_t GetLambdaCheck() const { return fLambdaCheck; } const Double_t GetMu0() const { return fMu0; } const Double_t GetMu1() const { return fMu1; } const Double_t GetSigma0() const { return fSigma0; } const Double_t GetSigma1() const { return fSigma1; } const Double_t GetLambdaErr() const { return fLambdaErr; } const Double_t GetLambdaCheckErr() const { return fLambdaCheckErr; } const Double_t GetMu0Err() const { return fMu0Err; } const Double_t GetMu1Err() const { return fMu1Err; } const Double_t GetSigma0Err() const { return fSigma0Err; } const Double_t GetSigma1Err() const { return fSigma1Err; } const Double_t GetChiSquare() const { return fChisquare; } const Double_t GetProb() const { return fProb; } const Int_t GetNdf() const { return fNdf; } const Double_t GetMeanTime() const { return fMeanTime; } const Double_t GetMeanTimeErr() const { return fMeanTimeErr; } const Double_t GetSigmaTime() const { return fSigmaTime; } const Double_t GetSigmaTimeErr() const { return fSigmaTimeErr; } Bool_t SimulateSinglePhe(Double_t lambda, Double_t mu0, Double_t mu1, Double_t sigma0, Double_t sigma1); Bool_t FitSinglePhe(Axis_t rmin=0, Axis_t rmax=0, Option_t *opt="RL0+Q"); Bool_t FitTime(Axis_t rmin=0., Axis_t rmax=0.,Option_t *opt="R0+Q"); void ChangeFitFunc(BlindPixelFitFunc fitfunc, Int_t par=6); void CutAllEdges(); TObject *DrawClone(Option_t *option="") const; void Draw(Option_t *option=""); Bool_t IsFitOK() { return fFitOK; } private: BlindPixelFitFunc fgSinglePheFitFunc; //! In the beginning, Int_t fgSinglePheFitNPar; //! we want to be flexible using different functions inline static Double_t gfKto4(Double_t *x, Double_t *par) { Double_t lambda = par[0]; Double_t sum = 0.; Double_t arg = 0.; Double_t mu0 = par[1]; Double_t mu1 = par[2]; if (mu1 < mu0) return NoWay; Double_t sigma0 = par[3]; Double_t sigma1 = par[4]; if (sigma1 < sigma0) return NoWay; Double_t mu2 = (2.*mu1)-mu0; Double_t mu3 = (3.*mu1)-(2.*mu0); Double_t mu4 = (4.*mu1)-(3.*mu0); Double_t sigma2 = TMath::Sqrt((2.*sigma1*sigma1) - (sigma0*sigma0)); Double_t sigma3 = TMath::Sqrt((3.*sigma1*sigma1) - (2.*sigma0*sigma0)); Double_t sigma4 = TMath::Sqrt((4.*sigma1*sigma1) - (3.*sigma0*sigma0)); Double_t lambda2 = lambda*lambda; Double_t lambda3 = lambda2*lambda; Double_t lambda4 = lambda3*lambda; // k=0: arg = (x[0] - mu0)/sigma0; sum = TMath::Exp(-0.5*arg*arg)/sigma0; // k=1: arg = (x[0] - mu1)/sigma1; sum += lambda*TMath::Exp(-0.5*arg*arg)/sigma1; // k=2: arg = (x[0] - mu2)/sigma2; sum += 0.5*lambda2*TMath::Exp(-0.5*arg*arg)/sigma2; // k=3: arg = (x[0] - mu3)/sigma3; sum += 0.1666666667*lambda3*TMath::Exp(-0.5*arg*arg)/sigma3; // k=4: arg = (x[0] - mu4)/sigma4; sum += 0.041666666666667*lambda4*TMath::Exp(-0.5*arg*arg)/sigma4; return TMath::Exp(-1.*lambda)*par[5]*sum; } //-> inline static Double_t gfKto5(Double_t *x, Double_t *par) { Double_t lambda = par[0]; Double_t sum = 0.; Double_t arg = 0.; Double_t mu0 = par[1]; Double_t mu1 = par[2]; if (mu1 < mu0) return NoWay; Double_t sigma0 = par[3]; Double_t sigma1 = par[4]; if (sigma1 < sigma0) return NoWay; Double_t mu2 = (2.*mu1)-mu0; Double_t mu3 = (3.*mu1)-(2.*mu0); Double_t mu4 = (4.*mu1)-(3.*mu0); Double_t mu5 = (5.*mu1)-(4.*mu0); Double_t sigma2 = TMath::Sqrt((2.*sigma1*sigma1) - (sigma0*sigma0)); Double_t sigma3 = TMath::Sqrt((3.*sigma1*sigma1) - (2.*sigma0*sigma0)); Double_t sigma4 = TMath::Sqrt((4.*sigma1*sigma1) - (3.*sigma0*sigma0)); Double_t sigma5 = TMath::Sqrt((5.*sigma1*sigma1) - (4.*sigma0*sigma0)); Double_t lambda2 = lambda*lambda; Double_t lambda3 = lambda2*lambda; Double_t lambda4 = lambda3*lambda; Double_t lambda5 = lambda4*lambda; // k=0: arg = (x[0] - mu0)/sigma0; sum = TMath::Exp(-0.5*arg*arg)/sigma0; // k=1: arg = (x[0] - mu1)/sigma1; sum += lambda*TMath::Exp(-0.5*arg*arg)/sigma1; // k=2: arg = (x[0] - mu2)/sigma2; sum += 0.5*lambda2*TMath::Exp(-0.5*arg*arg)/sigma2; // k=3: arg = (x[0] - mu3)/sigma3; sum += 0.1666666667*lambda3*TMath::Exp(-0.5*arg*arg)/sigma3; // k=4: arg = (x[0] - mu4)/sigma4; sum += 0.041666666666667*lambda4*TMath::Exp(-0.5*arg*arg)/sigma4; // k=5: arg = (x[0] - mu5)/sigma5; sum += 0.008333333333333*lambda5*TMath::Exp(-0.5*arg*arg)/sigma5; return TMath::Exp(-1.*lambda)*par[5]*sum; } inline static Double_t gfKto6(Double_t *x, Double_t *par) { Double_t lambda = par[0]; Double_t sum = 0.; Double_t arg = 0.; Double_t mu0 = par[1]; Double_t mu1 = par[2]; if (mu1 < mu0) return NoWay; Double_t sigma0 = par[3]; Double_t sigma1 = par[4]; if (sigma1 < sigma0) return NoWay; Double_t mu2 = (2.*mu1)-mu0; Double_t mu3 = (3.*mu1)-(2.*mu0); Double_t mu4 = (4.*mu1)-(3.*mu0); Double_t mu5 = (5.*mu1)-(4.*mu0); Double_t mu6 = (6.*mu1)-(5.*mu0); Double_t sigma2 = TMath::Sqrt((2.*sigma1*sigma1) - (sigma0*sigma0)); Double_t sigma3 = TMath::Sqrt((3.*sigma1*sigma1) - (2.*sigma0*sigma0)); Double_t sigma4 = TMath::Sqrt((4.*sigma1*sigma1) - (3.*sigma0*sigma0)); Double_t sigma5 = TMath::Sqrt((5.*sigma1*sigma1) - (4.*sigma0*sigma0)); Double_t sigma6 = TMath::Sqrt((6.*sigma1*sigma1) - (5.*sigma0*sigma0)); Double_t lambda2 = lambda*lambda; Double_t lambda3 = lambda2*lambda; Double_t lambda4 = lambda3*lambda; Double_t lambda5 = lambda4*lambda; Double_t lambda6 = lambda5*lambda; // k=0: arg = (x[0] - mu0)/sigma0; sum = TMath::Exp(-0.5*arg*arg)/sigma0; // k=1: arg = (x[0] - mu1)/sigma1; sum += lambda*TMath::Exp(-0.5*arg*arg)/sigma1; // k=2: arg = (x[0] - mu2)/sigma2; sum += 0.5*lambda2*TMath::Exp(-0.5*arg*arg)/sigma2; // k=3: arg = (x[0] - mu3)/sigma3; sum += 0.1666666667*lambda3*TMath::Exp(-0.5*arg*arg)/sigma3; // k=4: arg = (x[0] - mu4)/sigma4; sum += 0.041666666666667*lambda4*TMath::Exp(-0.5*arg*arg)/sigma4; // k=5: arg = (x[0] - mu5)/sigma5; sum += 0.008333333333333*lambda5*TMath::Exp(-0.5*arg*arg)/sigma5; // k=6: arg = (x[0] - mu6)/sigma6; sum += 0.001388888888889*lambda6*TMath::Exp(-0.5*arg*arg)/sigma6; return TMath::Exp(-1.*lambda)*par[5]*sum; } ClassDef(MHCalibrationBlindPixel, 1) }; #endif /* MARS_MHCalibrationBlindPixel */