LauDPDepCruijffPdf.cc
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32 LauDPDepCruijffPdf::LauDPDepCruijffPdf(const TString& theVarName, const std::vector<LauParameter*>& params,
64 cerr<<"ERROR in LauDPDepCruijffPdf::LauDPDepCruijffPdf : Have not been provided with a valid DP kinematics object."<<endl;
78 if ((this->nParameters() != 5) || (mean_ == 0) || (sigmaR_ == 0) || (sigmaL_ == 0) || (alphaL_ == 0) || (alphaR_ == 0)) {
79 cerr<<"ERROR in LauDPDepCruijffPdf constructor: LauDPDepCruijffPdf requires 5 parameters: \"mean\", \"sigmaL\", \"sigmaR\", \"alphaR\" and \"alphaL\"."<<endl;
92 LauDPDepCruijffPdf::LauDPDepCruijffPdf(const LauDPDepCruijffPdf& other) : LauAbsPdf(other.varName(), other.getParameters(), other.getMinAbscissa(), other.getMaxAbscissa()),
173 Double_t normFac = (sumMethod == GaussLegendre) ? this->integrGaussLegendre() : this->integTrapezoid();
256 for (std::vector<Double_t>::const_iterator iter = meanCoeffs_.begin(); iter != meanCoeffs_.end(); ++iter) {
263 for (std::vector<Double_t>::const_iterator iter = sigmaLCoeffs_.begin(); iter != sigmaLCoeffs_.end(); ++iter) {
270 for (std::vector<Double_t>::const_iterator iter = sigmaRCoeffs_.begin(); iter != sigmaRCoeffs_.end(); ++iter) {
277 for (std::vector<Double_t>::const_iterator iter = alphaLCoeffs_.begin(); iter != alphaLCoeffs_.end(); ++iter) {
284 for (std::vector<Double_t>::const_iterator iter = alphaRCoeffs_.begin(); iter != alphaRCoeffs_.end(); ++iter) {
Definition: LauDPDepCruijffPdf.hh:40 virtual Double_t integTrapezoid() Integrate the PDF using the simple trapezoid method. Definition: LauDPDepCruijffPdf.cc:216 Definition: LauDPDepCruijffPdf.hh:42 Double_t calcThirdMassSq(Double_t firstMassSq, Double_t secondMassSq) const Calculate the third invariant mass square from the two provided (e.g. mjkSq from mijSq and mikSq) ... Definition: LauKinematics.cc:435 virtual void setUnNormPDFVal(Double_t unNormPDFVal) Set the unnormalised likelihood. Definition: LauAbsPdf.hh:454 virtual Double_t getMinAbscissa() const Retrieve the minimum value of the (primary) abscissa. Definition: LauAbsPdf.hh:158 Definition: LauDPDepCruijffPdf.hh:44 virtual Bool_t normWeightsDone() const Check whether the normalisation weights have been calculated. Definition: LauAbsPdf.hh:532 const std::vector< Double_t > alphaLCoeffs_ Coefficients of alpha for the left Gaussian. Definition: LauDPDepCruijffPdf.hh:162 Class for defining a Cruijff PDF (with DP dependence). Definition: LauDPDepCruijffPdf.hh:35 Class that defines the particular 3-body decay under study. Definition: LauDaughters.hh:33 virtual const std::vector< LauAbscissas > & normAbscissas() const Retrieve the abscissa points used for normalisation. Definition: LauAbsPdf.hh:547 Double_t currentPDFValue(Double_t abscissa) const Current PDF value. Definition: LauDPDepCruijffPdf.cc:180 virtual Double_t getUnNormLikelihood() const Retrieve the unnormalised likelihood value. Definition: LauAbsPdf.hh:278 File containing declaration of LauDaughters class. void scalePars(Double_t dpPos) Scale parameters by their dependence on the DP position. Definition: LauDPDepCruijffPdf.cc:253 virtual Bool_t checkRange(const LauAbscissas &abscissas) const Check that all abscissas are within their allowed ranges. Definition: LauAbsPdf.cc:213 virtual Int_t nNormPoints() const Retrieve the number of points to integrate over when normalising. Definition: LauAbsPdf.hh:361 Definition: LauDPDepCruijffPdf.hh:41 Double_t distanceFromDPCentre() const Calculate the distance from the currently set (m13Sq, m23Sq) point to the centre of the Dalitz plot (... Definition: LauKinematics.cc:441 File containing declaration of LauKinematics class. virtual TRandom * getRandomFun() const Retrieve the random function used for MC generation. Definition: LauAbsPdf.hh:472 const std::vector< Double_t > sigmaLCoeffs_ Coefficients of sigma for the left Gaussian. Definition: LauDPDepCruijffPdf.hh:158 Definition: LauAbsPdf.hh:48 Definition: LauDPDepCruijffPdf.hh:45 const std::vector< Double_t > alphaRCoeffs_ Coefficients of alpha for the right Gaussian. Definition: LauDPDepCruijffPdf.hh:164 File containing declaration of LauDPDepCruijffPdf class. virtual Double_t getMaxAbscissa() const Retrieve the maximum value of the (primary) abscissa. Definition: LauAbsPdf.hh:164 const std::vector< Double_t > meanCoeffs_ Coefficients of Gaussian mean. Definition: LauDPDepCruijffPdf.hh:156 virtual const std::vector< Double_t > & normWeights() const Retrieve the weights used for normalisation. Definition: LauAbsPdf.hh:553 virtual Double_t integrGaussLegendre() Integrate the PDF using the Gauss-Legendre method. Definition: LauDPDepCruijffPdf.cc:196 File containing LauConstants namespace. virtual void getNormWeights() Calculate the weights and abscissas used for normalisation. Definition: LauAbsPdf.cc:569 virtual LauParameter * findParameter(const TString &parName) Retrieve the specified parameter. Definition: LauAbsPdf.cc:381 virtual void calcPDFHeight(const LauKinematics *kinematics) Calculate the PDF height. Definition: LauDPDepCruijffPdf.cc:291 const std::vector< Double_t > sigmaRCoeffs_ Coefficients of sigma for the right Gaussian. Definition: LauDPDepCruijffPdf.hh:160 virtual IntMethod integMethod() const Retrieve the integration method used to normalise the PDF. Definition: LauAbsPdf.hh:373 virtual void calcLikelihoodInfo(const LauAbscissas &abscissas) Calculate the likelihood (and intermediate info) for a given abscissa. Definition: LauDPDepCruijffPdf.cc:126 virtual Double_t getRange() const Retrieve the range of the (primary) abscissa. Definition: LauAbsPdf.hh:170 virtual void setRandomFun(TRandom *randomFun) Set the random function used for toy MC generation. Definition: LauAbsPdf.hh:315 LauDPDepCruijffPdf(const TString &theVarName, const std::vector< LauParameter * > ¶ms, Double_t minAbscissa, Double_t maxAbscissa, const LauDaughters *daughters, const std::vector< Double_t > &meanCoeffs, const std::vector< Double_t > &sigmaLCoeffs, const std::vector< Double_t > &sigmaRCoeffs, const std::vector< Double_t > &alphaLCoeffs, const std::vector< Double_t > &alphaRCoeffs, DPAxis dpAxis) Constructor. Definition: LauDPDepCruijffPdf.cc:32 std::vector< Double_t > LauAbscissas The type used for containing multiple abscissa values. Definition: LauAbsPdf.hh:44 Generated by 1.8.5 |