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

Class for defining a Cruijff PDF. More...

#include <LauCruijffPdf.hh>

Inheritance diagram for LauCruijffPdf:
LauAbsPdf

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

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...
 

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 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...
 

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]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

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]abscissasthe 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]kinematicsthe 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: