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Laura++  v2r1p1
A maximum likelihood fitting package for performing Dalitz-plot analysis.

Class for defining a Cruijff PDF (with DP dependence). More...

#include <LauDPDepCruijffPdf.hh>

Inheritance diagram for LauDPDepCruijffPdf:
LauAbsPdf

Public Types

enum  DPAxis {
  M12, M13, M23, CentreDist,
  MMIN, MMAX
}
 Define possibilties for the DP axes. More...
 
- Public Types inherited from LauAbsPdf
enum  IntMethod { GaussLegendre, Trapezoid }
 The possible numerical intergration methods. More...
 
typedef std::vector< Double_t > LauAbscissas
 The type used for containing multiple abscissa values. More...
 

Public Member Functions

 LauDPDepCruijffPdf (const TString &theVarName, const std::vector< LauAbsRValue * > &params, 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. More...
 
virtual ~LauDPDepCruijffPdf ()
 Destructor. More...
 
 LauDPDepCruijffPdf (const LauDPDepCruijffPdf &other)
 Copy constructor. More...
 
virtual Bool_t isDPDependent () const
 Specifies whether or not the PDF is DP dependent. More...
 
virtual void calcLikelihoodInfo (const LauAbscissas &abscissas)
 Calculate the likelihood (and intermediate info) for a given abscissa. More...
 
virtual void calcNorm ()
 Calculate the normalisation. More...
 
virtual void calcPDFHeight (const LauKinematics *kinematics)
 Calculate the PDF height. More...
 
- Public Member Functions inherited from LauAbsPdf
 LauAbsPdf (const TString &theVarName, const std::vector< LauAbsRValue * > &params, Double_t minAbscissa, Double_t maxAbscissa)
 Constructor for a 1D PDF. More...
 
 LauAbsPdf (const std::vector< TString > &theVarNames, const std::vector< LauAbsRValue * > &params, const LauFitData &minAbscissas, const LauFitData &maxAbscissas)
 Constructor for a multidimensional PDF. More...
 
virtual ~LauAbsPdf ()
 Destructor. More...
 
virtual const TString & varName () const
 Retrieve the name of the abscissa. More...
 
virtual std::vector< TString > varNames () const
 Retrieve the names of the abscissas. More...
 
virtual UInt_t nParameters () const
 Retrieve the number of PDF parameters. More...
 
virtual UInt_t nFixedParameters () const
 Retrieve the number of fixed PDF parameters. More...
 
virtual UInt_t nInputVars () const
 Retrieve the number of abscissas. More...
 
virtual Double_t getMinAbscissa () const
 Retrieve the minimum value of the (primary) abscissa. More...
 
virtual Double_t getMaxAbscissa () const
 Retrieve the maximum value of the (primary) abscissa. More...
 
virtual Double_t getRange () const
 Retrieve the range of the (primary) abscissa. More...
 
virtual Double_t getMinAbscissa (const TString &theVarName) const
 Retrieve the minimum value of the specified abscissa. More...
 
virtual Double_t getMaxAbscissa (const TString &theVarName) const
 Retrieve the maximum value of the specified abscissa. More...
 
virtual Double_t getRange (const TString &theVarName) const
 Retrieve the range of the specified abscissa. More...
 
virtual LauFitData getMinAbscissas () const
 Retrieve the minimum values of all the abscissas. More...
 
virtual LauFitData getMaxAbscissas () const
 Retrieve the maximum values of all the abscissas. More...
 
virtual LauFitData getRanges () const
 Retrieve the ranges of all the abscissas. More...
 
virtual void updatePulls ()
 Update the pulls for all parameters. More...
 
virtual void cacheInfo (const LauFitDataTree &inputData)
 Cache information from data. More...
 
virtual void calcLikelihoodInfo (UInt_t iEvt)
 Retrieve the likelihood (and all associated information) given the event number. More...
 
virtual Double_t getUnNormLikelihood () const
 Retrieve the unnormalised likelihood value. More...
 
virtual Double_t getNorm () const
 Retrieve the normalisation factor. More...
 
virtual Double_t getLikelihood () const
 Retrieve the normalised likelihood value. More...
 
virtual Double_t getLikelihood (const TString &theVarName) const
 For multidimentional PDFs, retrieve the normalised likelihood value of a named variable. More...
 
virtual Double_t getMaxHeight () const
 Retrieve the maximum height. More...
 
virtual LauFitData generate (const LauKinematics *kinematics)
 Generate an event from the PDF. More...
 
virtual void setRandomFun (TRandom *randomFun)
 Set the random function used for toy MC generation. More...
 
virtual const std::vector
< LauAbsRValue * > & 
getParameters () const
 Retrieve the parameters of the PDF, e.g. so that they can be loaded into a fit. More...
 
virtual std::vector
< LauAbsRValue * > & 
getParameters ()
 Retrieve the parameters of the PDF, e.g. so that they can be loaded into a fit. More...
 
virtual Bool_t heightUpToDate () const
 Check if the maximum height of the PDF is up to date. More...
 
virtual Bool_t cachePDF () const
 Check if the PDF is to be cached. More...
 
virtual Int_t nNormPoints () const
 Retrieve the number of points to integrate over when normalising. More...
 
virtual void nNormPoints (Int_t nPoints)
 Set the number of points to integrate over when normalising. More...
 
virtual IntMethod integMethod () const
 Retrieve the integration method used to normalise the PDF. More...
 
virtual void integMethod (IntMethod method)
 Set the integration method used to normalise the PDF. More...
 

Protected Member Functions

void scalePars (Double_t dpPos)
 Scale parameters by their dependence on the DP position. More...
 
Double_t currentPDFValue (Double_t abscissa) const
 Current PDF value. More...
 
virtual Double_t integrGaussLegendre ()
 Integrate the PDF using the Gauss-Legendre method. More...
 
virtual Double_t integTrapezoid ()
 Integrate the PDF using the simple trapezoid method. More...
 
- Protected Member Functions inherited from LauAbsPdf
virtual void cachePDF (Bool_t doCachePDF)
 Set whether the PDF is to be cached. More...
 
virtual void heightUpToDate (Bool_t hutd)
 Set whether the height is up to date. More...
 
virtual void setNorm (Double_t norm)
 Set the normalisation factor. More...
 
virtual void setMaxHeight (Double_t maxHeight)
 Set the maximum height. More...
 
virtual void setMinAbscissa (const TString &theVarName, Double_t minAbscissa)
 Set the minimum value of the specified abscissa. More...
 
virtual void setMaxAbscissa (const TString &theVarName, Double_t maxAbscissa)
 Set the maximum value of the specified abscissa. More...
 
virtual void setRange (const TString &theVarName, Double_t minAbscissa, Double_t maxAbscissa)
 Set the range of the specified abscissa. More...
 
virtual Bool_t checkRange (const LauAbscissas &abscissas) const
 Check that all abscissas are within their allowed ranges. More...
 
virtual void setUnNormPDFVal (Double_t unNormPDFVal)
 Set the unnormalised likelihood. More...
 
virtual LauAbsRValuefindParameter (const TString &parName)
 Retrieve the specified parameter. More...
 
virtual const LauAbsRValuefindParameter (const TString &parName) const
 Retrieve the specified parameter. More...
 
virtual TRandom * getRandomFun () const
 Retrieve the random function used for MC generation. More...
 
virtual std::vector
< LauAbscissas > & 
getAbscissas ()
 Retrieve the abscissa(s) More...
 
virtual const std::vector
< LauAbscissas > & 
getAbscissas () const
 Retrieve the abscissa(s) More...
 
virtual std::vector< Double_t > & getUnNormPDFValues ()
 Retrieve the cached unnormalised likelihood values. More...
 
virtual const std::vector
< Double_t > & 
getUnNormPDFValues () const
 Retrieve the cached unnormalised likelihood values. More...
 
virtual void addParameters (std::vector< LauAbsRValue * > &params)
 Add parameters to the PDF. More...
 
virtual Bool_t withinNormCalc () const
 Check whether the calcNorm method is running. More...
 
virtual void withinNormCalc (Bool_t yorn)
 Set flag to track whether the calcNorm method is running. More...
 
virtual Bool_t withinGeneration () const
 Check whether the generate method is running. More...
 
virtual void withinGeneration (Bool_t yorn)
 Set flag to track whether the generate method is running. More...
 
virtual Bool_t normWeightsDone () const
 Check whether the normalisation weights have been calculated. More...
 
virtual void normWeightsDone (Bool_t yorn)
 Set whether the normalisation weights have been calculated. More...
 
virtual void getNormWeights ()
 Calculate the weights and abscissas used for normalisation. More...
 
virtual const std::vector
< LauAbscissas > & 
normAbscissas () const
 Retrieve the abscissa points used for normalisation. More...
 
virtual const std::vector
< Double_t > & 
normWeights () const
 Retrieve the weights used for normalisation. More...
 

Private Attributes

const LauKinematicskinematics_
 The current DP kinematics. More...
 
LauAbsRValuemean_
 Gaussian mean. More...
 
LauAbsRValuesigmaL_
 Sigma of left Gaussian. More...
 
LauAbsRValuesigmaR_
 Sigma of right Gaussian. More...
 
LauAbsRValuealphaL_
 Alpha of left Gaussian. More...
 
LauAbsRValuealphaR_
 Alpha of right Gaussian. More...
 
Double_t meanVal_
 Gaussian mean. More...
 
Double_t sigmaLVal_
 Sigma of left Gaussian. More...
 
Double_t sigmaRVal_
 Sigma of right Gaussian. More...
 
Double_t alphaLVal_
 Alpha of left Gaussian. More...
 
Double_t alphaRVal_
 Alpha of right Gaussian. More...
 
const std::vector< Double_t > meanCoeffs_
 Coefficients of Gaussian mean. More...
 
const std::vector< Double_t > sigmaLCoeffs_
 Coefficients of sigma for the left Gaussian. More...
 
const std::vector< Double_t > sigmaRCoeffs_
 Coefficients of sigma for the right Gaussian. More...
 
const std::vector< Double_t > alphaLCoeffs_
 Coefficients of alpha for the left Gaussian. More...
 
const std::vector< Double_t > alphaRCoeffs_
 Coefficients of alpha for the right Gaussian. More...
 
DPAxis dpAxis_
 The DP axis we depend on. More...
 

Detailed Description

Class for defining a Cruijff PDF (with DP dependence).

Class that allows the user to define a Cruijff PDF where one or more of the parameters have a polynomial dependence on the DP position.

Definition at line 35 of file LauDPDepCruijffPdf.hh.

Member Enumeration Documentation

Define possibilties for the DP axes.

Enumerator
M12 

dependence is on m^2_12

M13 

dependence is on m^2_13

M23 

dependence is on m^2_23

CentreDist 

dependence is on the distance from the DP centre

MMIN 

dependence is on the minimum of m^2_13 and m^2_23

MMAX 

dependence is on the maximum of m^2_13 and m^2_23

Definition at line 39 of file LauDPDepCruijffPdf.hh.

Constructor & Destructor Documentation

LauDPDepCruijffPdf::LauDPDepCruijffPdf ( const TString &  theVarName,
const std::vector< LauAbsRValue * > &  params,
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.

Parameters
[in]theVarNamethe name of the abscissa variable
[in]paramsthe PDF parameters - mean, sigmaR, sigmaL, alphaR and alphaL
[in]minAbscissathe minimum value of the abscissa
[in]maxAbscissathe maximum value of the abscissa
[in]daughtersthe daughter particles
[in]meanCoeffsthe coefficients of the DP dependence of the Gaussian mean
[in]sigmaLCoeffsthe coefficients of the DP dependence of the sigma for the left Gaussian
[in]sigmaRCoeffsthe coefficients of the DP dependence of the sigma for the right Gaussian
[in]alphaLCoeffsthe coefficients of the DP dependence of the alpha for the left Gaussian
[in]alphaRCoeffsthe coefficients of the DP dependence of the alpha for the right Gaussian
[in]dpAxisthe DP axis that defines the parameter dependence

Definition at line 32 of file LauDPDepCruijffPdf.cc.

LauDPDepCruijffPdf::~LauDPDepCruijffPdf ( )
virtual

Destructor.

Definition at line 87 of file LauDPDepCruijffPdf.cc.

LauDPDepCruijffPdf::LauDPDepCruijffPdf ( const LauDPDepCruijffPdf other)

Copy constructor.

Definition at line 92 of file LauDPDepCruijffPdf.cc.

Member Function Documentation

void LauDPDepCruijffPdf::calcLikelihoodInfo ( const LauAbscissas abscissas)
virtual

Calculate the likelihood (and intermediate info) for a given abscissa.

Parameters
[in]abscissasthe values of the abscissa(s)

Implements LauAbsPdf.

Definition at line 126 of file LauDPDepCruijffPdf.cc.

void LauDPDepCruijffPdf::calcNorm ( )
virtual

Calculate the normalisation.

Reimplemented from LauAbsPdf.

Definition at line 121 of file LauDPDepCruijffPdf.cc.

void LauDPDepCruijffPdf::calcPDFHeight ( const LauKinematics kinematics)
virtual

Calculate the PDF height.

Parameters
[in]kinematicsthe current DP kinematics

Implements LauAbsPdf.

Definition at line 291 of file LauDPDepCruijffPdf.cc.

Double_t LauDPDepCruijffPdf::currentPDFValue ( Double_t  abscissa) const
protected

Current PDF value.

Parameters
[in]abscissathe values of the abscissa(s)

Definition at line 180 of file LauDPDepCruijffPdf.cc.

Double_t LauDPDepCruijffPdf::integrGaussLegendre ( )
protectedvirtual

Integrate the PDF using the Gauss-Legendre method.

Returns
the integral of the PDF

Reimplemented from LauAbsPdf.

Definition at line 196 of file LauDPDepCruijffPdf.cc.

Double_t LauDPDepCruijffPdf::integTrapezoid ( )
protectedvirtual

Integrate the PDF using the simple trapezoid method.

Returns
the integral of the PDF

Reimplemented from LauAbsPdf.

Definition at line 216 of file LauDPDepCruijffPdf.cc.

virtual Bool_t LauDPDepCruijffPdf::isDPDependent ( ) const
inlinevirtual

Specifies whether or not the PDF is DP dependent.

Returns
true if the PDF is DP-dependent (the default)

Reimplemented from LauAbsPdf.

Definition at line 82 of file LauDPDepCruijffPdf.hh.

void LauDPDepCruijffPdf::scalePars ( Double_t  dpPos)
protected

Scale parameters by their dependence on the DP position.

Parameters
[in]dpPosthe DP position

Definition at line 253 of file LauDPDepCruijffPdf.cc.

Member Data Documentation

LauAbsRValue* LauDPDepCruijffPdf::alphaL_
private

Alpha of left Gaussian.

Definition at line 137 of file LauDPDepCruijffPdf.hh.

const std::vector<Double_t> LauDPDepCruijffPdf::alphaLCoeffs_
private

Coefficients of alpha for the left Gaussian.

Definition at line 159 of file LauDPDepCruijffPdf.hh.

Double_t LauDPDepCruijffPdf::alphaLVal_
private

Alpha of left Gaussian.

Definition at line 148 of file LauDPDepCruijffPdf.hh.

LauAbsRValue* LauDPDepCruijffPdf::alphaR_
private

Alpha of right Gaussian.

Definition at line 139 of file LauDPDepCruijffPdf.hh.

const std::vector<Double_t> LauDPDepCruijffPdf::alphaRCoeffs_
private

Coefficients of alpha for the right Gaussian.

Definition at line 161 of file LauDPDepCruijffPdf.hh.

Double_t LauDPDepCruijffPdf::alphaRVal_
private

Alpha of right Gaussian.

Definition at line 150 of file LauDPDepCruijffPdf.hh.

DPAxis LauDPDepCruijffPdf::dpAxis_
private

The DP axis we depend on.

Definition at line 164 of file LauDPDepCruijffPdf.hh.

const LauKinematics* LauDPDepCruijffPdf::kinematics_
private

The current DP kinematics.

Definition at line 128 of file LauDPDepCruijffPdf.hh.

LauAbsRValue* LauDPDepCruijffPdf::mean_
private

Gaussian mean.

Definition at line 131 of file LauDPDepCruijffPdf.hh.

const std::vector<Double_t> LauDPDepCruijffPdf::meanCoeffs_
private

Coefficients of Gaussian mean.

Definition at line 153 of file LauDPDepCruijffPdf.hh.

Double_t LauDPDepCruijffPdf::meanVal_
private

Gaussian mean.

Definition at line 142 of file LauDPDepCruijffPdf.hh.

LauAbsRValue* LauDPDepCruijffPdf::sigmaL_
private

Sigma of left Gaussian.

Definition at line 133 of file LauDPDepCruijffPdf.hh.

const std::vector<Double_t> LauDPDepCruijffPdf::sigmaLCoeffs_
private

Coefficients of sigma for the left Gaussian.

Definition at line 155 of file LauDPDepCruijffPdf.hh.

Double_t LauDPDepCruijffPdf::sigmaLVal_
private

Sigma of left Gaussian.

Definition at line 144 of file LauDPDepCruijffPdf.hh.

LauAbsRValue* LauDPDepCruijffPdf::sigmaR_
private

Sigma of right Gaussian.

Definition at line 135 of file LauDPDepCruijffPdf.hh.

const std::vector<Double_t> LauDPDepCruijffPdf::sigmaRCoeffs_
private

Coefficients of sigma for the right Gaussian.

Definition at line 157 of file LauDPDepCruijffPdf.hh.

Double_t LauDPDepCruijffPdf::sigmaRVal_
private

Sigma of right Gaussian.

Definition at line 146 of file LauDPDepCruijffPdf.hh.


The documentation for this class was generated from the following files: