Class for defining a Bifurcated Gaussian PDF (DP dependent). More...

#include <LauDPDepBifurGaussPdf.hh>

Inheritance diagram for LauDPDepBifurGaussPdf:

Public Types
enum	DPAxis { M12, M13, M23, CentreDist, MMIN, MMAX }
	Define possibilties for the DP axes. More...

enum	ScaleMethod { poly, polyNegPower }
	Define possibilties for the scaling method. 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
	LauDPDepBifurGaussPdf (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, DPAxis dpAxis)
	Constructor. More...

virtual	~LauDPDepBifurGaussPdf ()
	Destructor. 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...

ScaleMethod	scaleMethod () const
	Retrieve scaling method information. More...

void	scaleMethod (ScaleMethod method)
	Set the scaling method. 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 void	heightUpToDate (Bool_t hutd)
	Set whether the height 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_poly (Double_t perEventDist)
	Scale the Gaussian parameters with polynomial method. More...

void	scalePars_polyNegPower (Double_t perEventDist)
	Scale the Gaussian parameters with negative power polynomial method. More...

Protected Member Functions inherited from LauAbsPdf
virtual void	cachePDF (Bool_t doCachePDF)
	Set whether the PDF is to be cached. 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...

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 Member Functions
	LauDPDepBifurGaussPdf (const LauDPDepBifurGaussPdf &other)
	Copy constructor (not implemented) More...

LauDPDepBifurGaussPdf &	operator= (const LauDPDepBifurGaussPdf &other)
	Copy assignment operator (not implemented) More...

Private Attributes
const LauKinematics *	kinematics_
	The current DP kinematics. More...

LauAbsRValue *	mean_
	Gaussian mean. More...

LauAbsRValue *	sigmaL_
	Left Gaussian sigma. More...

LauAbsRValue *	sigmaR_
	Right Gaussian sigma. More...

Double_t	meanVal_
	Gaussian mean. More...

Double_t	sigmaLVal_
	Left Gaussian sigma. More...

Double_t	sigmaRVal_
	Right Gaussian sigma. More...

const std::vector< Double_t >	meanCoeffs_
	Coefficients of Gaussian mean. More...

const std::vector< Double_t >	sigmaLCoeffs_
	Coefficients of left Gaussian sigma. More...

const std::vector< Double_t >	sigmaRCoeffs_
	Coefficients of right Gaussian sigma. More...

DPAxis	dpAxis_
	The DP axis we depend on. More...

ScaleMethod	scaleMethod_
	Scaling method information. More...

Detailed Description

Class for defining a Bifurcated Gaussian PDF (DP dependent).

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

Definition at line 31 of file LauDPDepBifurGaussPdf.hh.

Member Enumeration Documentation

enum LauDPDepBifurGaussPdf::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 35 of file LauDPDepBifurGaussPdf.hh.

enum LauDPDepBifurGaussPdf::ScaleMethod

Define possibilties for the scaling method.

Enumerator
poly	dependence is polynomial
polyNegPower	dependence is a Laurent polynomial with only negative powers

Definition at line 45 of file LauDPDepBifurGaussPdf.hh.

Constructor & Destructor Documentation

LauDPDepBifurGaussPdf::LauDPDepBifurGaussPdf	(	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,
		DPAxis	dpAxis
	)

Constructor.

Parameters

[in]	theVarName	the name of the abscissa variable
[in]	params	the PDF parameters - mean and sigma
[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]	dpAxis	the DP axis that defines the parameter dependence

LauDPDepBifurGaussPdf::~LauDPDepBifurGaussPdf ( )

virtual

Destructor.

Definition at line 86 of file LauDPDepBifurGaussPdf.cc.

LauDPDepBifurGaussPdf::LauDPDepBifurGaussPdf ( const LauDPDepBifurGaussPdf & other )

private

Copy constructor (not implemented)

Member Function Documentation

void LauDPDepBifurGaussPdf::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 91 of file LauDPDepBifurGaussPdf.cc.

void LauDPDepBifurGaussPdf::calcNorm ( )

virtual

Calculate the normalisation.

Reimplemented from LauAbsPdf.

Definition at line 227 of file LauDPDepBifurGaussPdf.cc.

void LauDPDepBifurGaussPdf::calcPDFHeight ( const LauKinematics * kinematics )

virtual

Calculate the PDF height.

Parameters

[in] kinematics the current DP kinematics

Implements LauAbsPdf.

Definition at line 232 of file LauDPDepBifurGaussPdf.cc.

virtual Bool_t LauDPDepBifurGaussPdf::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 77 of file LauDPDepBifurGaussPdf.hh.

LauDPDepBifurGaussPdf& LauDPDepBifurGaussPdf::operator= ( const LauDPDepBifurGaussPdf & other )

private

Copy assignment operator (not implemented)

ScaleMethod LauDPDepBifurGaussPdf::scaleMethod ( ) const

inline

Retrieve scaling method information.

Returns: scaling method

Definition at line 100 of file LauDPDepBifurGaussPdf.hh.

void LauDPDepBifurGaussPdf::scaleMethod ( ScaleMethod method )

inline

Set the scaling method.

Parameters

[in] method the scaling method

Definition at line 106 of file LauDPDepBifurGaussPdf.hh.

void LauDPDepBifurGaussPdf::scalePars_poly ( Double_t perEventDist )

protected

Scale the Gaussian parameters with polynomial method.

Parameters

[in] perEventDist the event distribution

Definition at line 179 of file LauDPDepBifurGaussPdf.cc.

void LauDPDepBifurGaussPdf::scalePars_polyNegPower ( Double_t perEventDist )

protected

Scale the Gaussian parameters with negative power polynomial method.

Parameters

[in] perEventDist the event distribution

Definition at line 203 of file LauDPDepBifurGaussPdf.cc.

Member Data Documentation

DPAxis LauDPDepBifurGaussPdf::dpAxis_

private

The DP axis we depend on.

Definition at line 153 of file LauDPDepBifurGaussPdf.hh.

const LauKinematics* LauDPDepBifurGaussPdf::kinematics_

private

The current DP kinematics.

Definition at line 129 of file LauDPDepBifurGaussPdf.hh.

LauAbsRValue* LauDPDepBifurGaussPdf::mean_

private

Gaussian mean.

Definition at line 132 of file LauDPDepBifurGaussPdf.hh.

const std::vector<Double_t> LauDPDepBifurGaussPdf::meanCoeffs_

private

Coefficients of Gaussian mean.

Definition at line 146 of file LauDPDepBifurGaussPdf.hh.

Double_t LauDPDepBifurGaussPdf::meanVal_

private

Gaussian mean.

Definition at line 139 of file LauDPDepBifurGaussPdf.hh.

ScaleMethod LauDPDepBifurGaussPdf::scaleMethod_

private

Scaling method information.

Definition at line 156 of file LauDPDepBifurGaussPdf.hh.

LauAbsRValue* LauDPDepBifurGaussPdf::sigmaL_

private

Left Gaussian sigma.

Definition at line 134 of file LauDPDepBifurGaussPdf.hh.

const std::vector<Double_t> LauDPDepBifurGaussPdf::sigmaLCoeffs_

private

Coefficients of left Gaussian sigma.

Definition at line 148 of file LauDPDepBifurGaussPdf.hh.

Double_t LauDPDepBifurGaussPdf::sigmaLVal_

private

Left Gaussian sigma.

Definition at line 141 of file LauDPDepBifurGaussPdf.hh.

LauAbsRValue* LauDPDepBifurGaussPdf::sigmaR_

private

Right Gaussian sigma.

Definition at line 136 of file LauDPDepBifurGaussPdf.hh.

const std::vector<Double_t> LauDPDepBifurGaussPdf::sigmaRCoeffs_

private

Coefficients of right Gaussian sigma.

Definition at line 150 of file LauDPDepBifurGaussPdf.hh.

Double_t LauDPDepBifurGaussPdf::sigmaRVal_

private

Right Gaussian sigma.

Definition at line 143 of file LauDPDepBifurGaussPdf.hh.

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

inc/LauDPDepBifurGaussPdf.hh
src/LauDPDepBifurGaussPdf.cc

Public Types

Public Member Functions

Protected Member Functions

Private Member Functions

Private Attributes

Detailed Description

Member Enumeration Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation