MPTools

class MPTools : public TObject

    public:

                        MPTools()
                        MPTools(const MPTools&)
                        ~MPTools()
        static Double_t binomialDistribution(double* x, double* par)
        static Double_t binomialDistribution(Double_t x, Double_t singleProbability, Double_t N, Double_t logAmplitude = 0.)
        static Double_t calcCMEnergyOfPairDecay(Double_t minv, Double_t m1, Double_t m2)
        static Double_t calcCMMomentumOfPairDecay(Double_t minv, Double_t m1, Double_t m2, Double_t minvErr, Double_t m1Err, Double_t m2Err, Double_t& err)
        static Double_t calcCMMomentumOfPairDecay(Double_t minv, Double_t m1, Double_t m2)
            static TH1* calculateLikeSignCombinatorialBackground(TH1* pp, TH1* mm, TString name = background)
            static TH1* calculateLikeSignCombinatorialBackground(TH1* pp, TH1* mm, TH1* correction, TString name = background)
        static Double_t chiSquareDistribution(double* x, double* par)
        static Double_t chiSquareDistribution(Double_t x, Double_t ndf, Double_t logAmplitude = 0.)
         static TClass* Class()
        static Double_t getDistancePointToStraight(HGeomVector& point, HGeomVector& base, HGeomVector& direction)
        static Double_t integralGauss(Double_t* x, Double_t* par)
        virtual TClass* IsA() const
               MPTools& operator=(const MPTools&)
        static Double_t poissonDistribution(double* x, double* par)
        static Double_t poissonDistribution(Double_t x, Double_t mean, Double_t logAmplitude = 0.)
        static Double_t poissonDistributionShifted(double* x, double* par)
        static Double_t poissonDistributionShifted(Double_t x, Double_t mean, Double_t logAmplitude = 0., Double_t shift = 0)
           static TH1D* projectPtYDownToMt(TH2* hist, Int_t ymin, Int_t ymax, Double_t mass)
           static TH1D* projectPtYDownToMtInBoltzmannRepresentation(TH2* hist, Int_t ymin, Int_t ymax, Double_t mass)
           static TH1D* projectPtYDownToMtInInvariantRepresentation(TH2* hist, Int_t ymin, Int_t ymax, Double_t mass)
           static TH1D* projectPtYDownToMtM0(TH2* hist, Int_t ymin, Int_t ymax, Double_t mass)
           static TH1D* projectPtYDownToMtM0InInvariantRepresentation(TH2* hist, Int_t ymin, Int_t ymax, Double_t mass)
           static TH1D* projectPtYDownToPt(TH2* hist, Int_t ymin, Int_t ymax)
      static TObjArray* projectPtYDownToPt(TH2* hist, Int_t stepSize = 1)
           static TH1D* projectPtYDownToPtInBoltzmannRepresentation(TH2* hist, Int_t ymin, Int_t ymax, Double_t mass)
           static TH1D* projectPtYDownToPtInInvariantRepresentation(TH2* hist, Int_t ymin, Int_t ymax)
      static TObjArray* projectPtYDownToPtScaled(TH2* hist, Double_t scaleFactor = 1., Int_t stepSize = 1)
           static TH1D* projectPtYDownToY(TH2* hist, Int_t ptmin, Int_t ptmax)
      static TObjArray* projectPtYDownToY(TH2* hist, Int_t stepSize = 1)
      static TObjArray* projectPtYDownToYScaled(TH2* hist, Double_t scaleFactor = 1., Int_t stepSize = 1)
           virtual void ShowMembers(TMemberInspector& insp, char* parent)
           virtual void Streamer(TBuffer& b)
                   void StreamerNVirtual(TBuffer& b)

Data Members

Class Description

 Peter's Math Tools

            Author: Peter W. Zumbruch
           Contact: P.Zumbruch@gsi.de
           Created: March 18, 2004

 File: $RCSfile: mptools.cc,v $
 Version: $Revision: 1.18 $
 Modified by $Author: halo $ on $Date: 2006/08/12 13:05:25 $

 calculates binwise the likesign combinatorial background of two given histograms
 using the formula

              /---------
 back = 2 *  V pp * mm


 and returns the pointer to the background histogramm
 with the name assigned assigned by name [default: "background"]

 if pp or mm are null pointers NULL is returned
 if pp and mm are not compatible NULL is returned

 calculates binwise the likesign combinatorial background of two given histograms
 using the formula

                          /---------
 back = 2 * correction * V pp * mm


 and returns the pointer to the background histogramm
 with the name assigned assigned by name [default: "background"]

 correction is also a histogram containing bin-wise correction factors (like acceptance correction)

 if correction, pp or mm are null pointers NULL is returned
 if correction, pp and mm are not compatible NULL is returned

 discrete poisson distribution as continuous function
 poisson is the limiting form of the binomial distribution
 for p->0 and N->infinity

             r  -mean
         mean  e
 P(r) = -------------
             r!

 translates to

                          r  -mean
          amplitude   mean  e
 P(x) = 10           ---------------
                        Gamma(r+1)

 if x<0 P(0) is returned

 par[0] : amplitude
 par[1] : mean

 discrete poisson distribution as continuous function
 poisson is the limiting form of the binomial distribution
 for p->0 and N->infinity

             r  -mean
         mean  e
 P(r) = -------------
             r!

 translates to

                          r  -mean
          amplitude   mean  e
 P(x) = 10           ---------------
                        Gamma(r+1)

 if x<0 P(0) is returned

 discrete poisson distribution as continuous function
 poisson is the limiting form of the binomial distribution
 for p->0 and N->infinity

             r  -mean
         mean  e
 P(r) = -------------
             r!

 translates to

                          x+shift  -mean
          amplitude   mean  e
 P(x) = 10           ---------------
                        Gamma(x+1+shift)

 if x<0 -1 is returned

 par[0] : amplitude
 par[1] : mean

 discrete poisson distribution as continuous function
 poisson is the limiting form of the binomial distribution
 for p->0 and N->infinity

             r  -mean
         mean  e
 P(r) = -------------
             r!

 translates to

                          x+shift  -mean
          amplitude   mean  e
 P(x) = 10           ---------------
                        Gamma(x+1+shifta)

 if x<0 -1 is returned

 discrete binomial distribution as continuous function

              N!       r       N-r
 P(r) = ------------- p (1 - p)
         r! (N - r) !

 translates to

          Amplitude           Gamma(N+1)           r       N-r
 P(x) = 10           ---------------------------- p (1 - p)
                     Gamma(r+1) Gamma (N - r + 1)

 P(x) the probability of r successes in N tries
 p is the single probability

 par[0]: Amplitude, chosen for Normalization purposes
 par[1]: number of tries (N)
 par[2]: single probability (p)

 if x<0 -1 is returned

 if x>N -1 is returned

 discrete binomial distribution as continuous function

              N!       r       N-r
 P(r) = ------------- p (1 - p)
         r! (N - r) !

 translates to

          Amplitude           Gamma(N+1)           r       N-r
 P(x) = 10           ---------------------------- p (1 - p)
                     Gamma(r+1) Gamma (N - r + 1)

 P(x) the probability of r successes in N tries
 p is the single probability

 par[0]: Amplitude, chosen for Normalization purposes
 par[1]: number of tries (N)
 par[2]: single probability (p)
 if x<0 -1 is returned

 if x>N -1 is returned

 chi square distriubtion

                       (0.5 * NDF) -1     (- 0.5 * chi2)
           (0.5 * chi2)               * e
 P(chi2) = ----------------------------------------------
                         2 * Gamma (0.5 * NDF)

 adding a normalization amplitude

                                    (0.5 * NDF) -1     (- 0.5 * x[0])
             amplitude   (0.5 * x[0])               * e
 P(x[0]) = 10         *  ------------------------------------------------
                                       2 * Gamma (0.5 * NDF)


 par[1]: NDF are number of degrees of freedom
 par[0]: amplitude

 if ndf <=0 -1 is returned

 chi square distriubtion

                       (0.5 * NDF) -1     (- 0.5 * chi2)
           (0.5 * chi2)               * e
 P(chi2) = ----------------------------------------------
                         2 * Gamma (0.5 * NDF)

 adding a normalization amplitude

                                 (0.5 * NDF) -1     (- 0.5 * x)
          amplitude   (0.5 * x)               * e
 P(x) = 10         *  ------------------------------------------------
                                    2 * Gamma (0.5 * NDF)


 NDF are number of degrees of freedom
 amplitude

 if ndf <=0 -1 is returned

 calculates in a 2-body decay the center of momentum momentum of the decay particles
 where
    minv is the invariant mass of the parent
    m1 is the mass of the particle 1
    m2 is the mass of the particle 2
    minvErr is the absolute error parents invariant mass
    m1Err is absolute error of the mass of the particle 1
    m2Err is absolute error of the mass of the particle 2

    the error is returned via err
    in case of errors -1. is returned

 !!!! in case of m1!=m2 I am not quite sure if the result is ok. !!!

 calculates in a 2-body decay the center of momentum momentum of the decay particles
 where
    minv is the invariant mass of the parent
    m1 is the mass of the particle 1
    m2 is the mass of the particle 2

    the error is returned via err
    in case of errors -1. is returned

 calculates in a 2-body decay the center of momentum energy of the decay particles
 of particle with mass m1
 where
    minv is the invariant mass of the parent
    m1 is the mass of the particle 1
    m2 is the mass of the particle 2

    in case of errors -1. is returned

 Parametric 1-dimensional function with 3 parameters
 par[0] = Integral of Gaus-Funktion in range +- infinity
 par[1] = mean of gauss
 par[2] = sigma

 returns 0 if par[2] = 0

 else returns

 par[0]/(sqrt(TMath::Pi()*2)*par[2])*TMath::Gaus(x[0],par[1],par[2])

 if hist is NULL ... NULL is returned
 otherwise
 a histogram is returned
 that is the projection of hist in a bin range ymin to ymax on the x-Axis

 if hist is NULL ... NULL is returned
 otherwise
 a histogram is returned
 that is the invariant cross section weighted (1/pt) projection of hist in a bin range ymin to ymax on the x-Axis
 if pt = 0 the weight is also set to 0

 if hist is NULL ... NULL is returned
 otherwise
 a histogram is returned
 that is the boltzmann weighted (1/ptE = 1/(pt*sqrt(pt^2+mass^2)) projection of hist in a bin range ymin to ymax on the x-Axis
 if pt = 0 the weight is also set to 0

 if hist is NULL ... NULL is returned
 otherwise
 a histogram is returned
 that is the boltzmann weighted (1/ptE = 1/(pt*sqrt(pt^2+mass^2)) projection of hist in a bin range ymin to ymax on the x-Axis
 if pt = 0 the weight is also set to 0

 if hist is NULL ... NULL is returned
 otherwise
 a histogram is returned
 that is the boltzmann weighted (1/ptE = 1/(pt*sqrt(pt^2+mass^2)) projection of hist in a bin range ymin to ymax on the x-Axis
 if pt = 0 the weight is also set to 0

 if hist is NULL ... NULL is returned
 otherwise
 a histogram is returned
 that is the boltzmann weighted (1/ptE = 1/(pt*sqrt(pt^2+mass^2)) projection of hist in a bin range ymin to ymax on the x-Axis
 if pt = 0 the weight is also set to 0

 if hist is NULL ... NULL is returned
 otherwise
 a histogram is returned
 that is the boltzmann weighted (1/ptE = 1/(pt*sqrt(pt^2+mass^2)) projection of hist in a bin range ymin to ymax on the x-Axis
 if pt = 0 the weight is also set to 0

 if hist is NULL ... NULL is returned
 otherwise
 a histogram is returned
 that is the boltzmann weighted (1/ptE = 1/(pt*sqrt(pt^2+mass^2)) projection of hist in a bin range ymin to ymax on the x-Axis
 if pt = 0 the weight is also set to 0

 if hist is NULL ... NULL is returned
 otherwise
 a histogram is returned
 that is the projection of hist in a bin range ptmin to ptmax on the x-Axis

 if hist is NULL ... NULL is returned
 otherwise
 a TObjArray of histograms is returned
 where each histogram is the projection of hist from first bin for "stepSize" bins together,
 default: stepsize = 1, i.e for each bin allone
 beginning from the second histogram, all histograms are scaled by scaleFactor with respect to the previous histogram
   i.e. the (n+1th) histogramm is scaled by scaleFactor to the nth power
   if scale factor is negativ than the scaling order is reversed, i.e the first histogramm is scaled most

 if hist is NULL ... NULL is returned
 otherwise
 a TObjArray of histograms is returned
 where each histogram is the projection of hist from first bin for "stepSize" bins together,
 default: stepSize = 1, i.e for each bin allone
 beginning from the second histogram, all histograms are scaled by scaleFactor with respect to the previous histogram
   i.e. the (n+1th) histogramm is scaled by scaleFactor to the nth power
   if scale factor is negativ than the scaling order is reversed, i.e the first histogramm is scaled most

 if hist is NULL ... NULL is returned
 otherwise
 a TObjArray of histograms is returned
 where each histogram is the projection of hist from first bin for "stepSize" bins together,
 default: stepsize = 1, i.e for each bin allone
 beginning from the second histogram, all histograms are scaled by scaleFactor with respect to the previous histogram
   i.e. the (n+1th) histogramm is scaled by scaleFactor to the nth power
   if scale factor is negativ than the scaling order is reversed, i.e the first histogramm is scaled most

 if hist is NULL ... NULL is returned
 otherwise
 a TObjArray of histograms is returned
 where each histogram is the projection of hist from first bin for "stepSize" bins together,
 default: stepSize = 1, i.e for each bin allone
 beginning from the second histogram, all histograms are scaled by scaleFactor with respect to the previous histogram
   i.e. the (n+1th) histogramm is scaled by scaleFactor to the nth power
   if scale factor is negativ than the scaling order is reversed, i.e the first histogramm is scaled most

Inline Functions

               void ~MPTools()
            TClass* Class()
            TClass* IsA() const
               void ShowMembers(TMemberInspector& insp, char* parent)
               void Streamer(TBuffer& b)
               void StreamerNVirtual(TBuffer& b)
            MPTools MPTools()
            MPTools MPTools(const MPTools&)
           MPTools& operator=(const MPTools&)