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

#include <LauDPDepCruijffPdf.hh>

Inheritance diagram for LauDPDepCruijffPdf:

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 LauAbsRValue *	findParameter (const TString &parName)
	Retrieve the specified parameter. More...

virtual const LauAbsRValue *	findParameter (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 LauKinematics *	kinematics_
	The current DP kinematics. More...

LauAbsRValue *	mean_
	Gaussian mean. More...

LauAbsRValue *	sigmaL_
	Sigma of left Gaussian. More...

LauAbsRValue *	sigmaR_
	Sigma of right Gaussian. More...

LauAbsRValue *	alphaL_
	Alpha of left Gaussian. More...

LauAbsRValue *	alphaR_
	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

enum LauDPDepCruijffPdf::DPAxis

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]	theVarName	the name of the abscissa variable
[in]	params	the PDF parameters - mean, sigmaR, sigmaL, alphaR and alphaL
[in]	minAbscissa	the minimum value of the abscissa
[in]	maxAbscissa	the maximum value of the abscissa
[in]	daughters	the daughter particles
[in]	meanCoeffs	the coefficients of the DP dependence of the Gaussian mean
[in]	sigmaLCoeffs	the coefficients of the DP dependence of the sigma for the left Gaussian
[in]	sigmaRCoeffs	the coefficients of the DP dependence of the sigma for the right Gaussian
[in]	alphaLCoeffs	the coefficients of the DP dependence of the alpha for the left Gaussian
[in]	alphaRCoeffs	the coefficients of the DP dependence of the alpha for the right Gaussian
[in]	dpAxis	the 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] abscissas the 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] kinematics the 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] abscissa the 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] dpPos the 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:

inc/LauDPDepCruijffPdf.hh
src/LauDPDepCruijffPdf.cc

Public Types

Public Member Functions

Protected Member Functions

Private Attributes

Detailed Description

Member Enumeration Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation