Class for defining a Cruijff PDF. More...

#include <LauCruijffPdf.hh>

Inheritance diagram for LauCruijffPdf:

Public Member Functions
	LauCruijffPdf (const TString &theVarName, const vector< LauAbsRValue * > &params, Double_t minAbscissa, Double_t maxAbscissa)
	Constructor. More...

virtual	~LauCruijffPdf ()
	Destructor. More...

	LauCruijffPdf (const LauCruijffPdf &other)
	Copy constructor. More...

virtual void	calcLikelihoodInfo (const LauAbscissas &abscissas)
	Calculate the likelihood (and intermediate info) for a given abscissa. 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 Bool_t	isDPDependent () const
	Specifies whether or not the PDF is DP dependent. 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 void	calcNorm ()
	Calculate the normalisation factor of the PDF. 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...

Private Attributes
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...

Additional Inherited Members
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...

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 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...

Detailed Description

Class for defining a Cruijff PDF.

Class that allows the user to define a Cruijff PDF, a bifurcated Gaussian with asymmetric tails. The guts of the implementation have been copied from Wouter Hulsbergen's RooFit class.

Definition at line 50 of file LauCruijffPdf.hh.

Constructor & Destructor Documentation

LauCruijffPdf::LauCruijffPdf	(	const TString &	theVarName,
		const vector< LauAbsRValue * > &	params,
		Double_t	minAbscissa,
		Double_t	maxAbscissa
	)

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

Definition at line 46 of file LauCruijffPdf.cc.

LauCruijffPdf::~LauCruijffPdf ( )

virtual

Destructor.

Definition at line 76 of file LauCruijffPdf.cc.

LauCruijffPdf::LauCruijffPdf ( const LauCruijffPdf & other )

Copy constructor.

Definition at line 81 of file LauCruijffPdf.cc.

Member Function Documentation

void LauCruijffPdf::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 88 of file LauCruijffPdf.cc.

void LauCruijffPdf::calcPDFHeight ( const LauKinematics * kinematics )

virtual

Calculate the PDF height.

Parameters

[in] kinematics the current DP kinematics

Implements LauAbsPdf.

Definition at line 134 of file LauCruijffPdf.cc.

Member Data Documentation

LauAbsRValue* LauCruijffPdf::alphaL_

private

Alpha of left Gaussian.

Definition at line 92 of file LauCruijffPdf.hh.

LauAbsRValue* LauCruijffPdf::alphaR_

private

Alpha of right Gaussian.

Definition at line 94 of file LauCruijffPdf.hh.

LauAbsRValue* LauCruijffPdf::mean_

private

Gaussian mean.

Definition at line 86 of file LauCruijffPdf.hh.

LauAbsRValue* LauCruijffPdf::sigmaL_

private

Sigma of left Gaussian.

Definition at line 88 of file LauCruijffPdf.hh.

LauAbsRValue* LauCruijffPdf::sigmaR_

private

Sigma of right Gaussian.

Definition at line 90 of file LauCruijffPdf.hh.

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

inc/LauCruijffPdf.hh
src/LauCruijffPdf.cc

Public Member Functions

Private Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation