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Laura++  v3r2
A maximum likelihood fitting package for performing Dalitz-plot analysis.

Class for defining a Parametric Step Function PDF. More...

#include <LauParametricStepFuncPdf.hh>

Inheritance diagram for LauParametricStepFuncPdf:
LauAbsPdf

Public Types

enum  NormBin { First, Last }
 Define the allowed options for the normalisation bin. 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

 LauParametricStepFuncPdf (const TString &theVarName, const std::vector< LauAbsRValue * > &params, const std::vector< Double_t > &limits, NormBin normalisationBin=Last)
 Constructor. More...
 
virtual ~LauParametricStepFuncPdf ()
 Destructor. 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 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 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

UInt_t nBins () const
 Number of bins. More...
 
NormBin normBin () const
 Normalisation bin. 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 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 Member Functions

 LauParametricStepFuncPdf (const LauParametricStepFuncPdf &rhs)
 Copy constructor (not implemented) More...
 
LauParametricStepFuncPdfoperator= (const LauParametricStepFuncPdf &rhs)
 Copy assignment operator (not implemented) More...
 

Private Attributes

NormBin normBin_
 normalisation bin More...
 
std::vector< Double_t > limits_
 limits of the bins More...
 

Detailed Description

Class for defining a Parametric Step Function PDF.

Class that allows the user to define a Parametric Step Function PDF. Code mostly copied from RooFit/RooParametricStepFunction.

Definition at line 51 of file LauParametricStepFuncPdf.hh.

Member Enumeration Documentation

Define the allowed options for the normalisation bin.

Enumerator
First 

The height of the first bin is determined from the rest to satisfy the normalisation

Last 

The height of the last bin is determined from the rest to satisfy the normalisation

Definition at line 55 of file LauParametricStepFuncPdf.hh.

Constructor & Destructor Documentation

LauParametricStepFuncPdf::LauParametricStepFuncPdf ( const TString &  theVarName,
const std::vector< LauAbsRValue * > &  params,
const std::vector< Double_t > &  limits,
NormBin  normalisationBin = Last 
)

Constructor.

Parameters
[in]theVarNamethe name of the abscissa variable
[in]paramsthe bin contents of all the but the normalisation bin, so (N_bins - 1 entries)
[in]limitsthe limits of the bins (lower limit of all bins and upper limit of the last), so (N_bins + 1) entries
[in]normalisationBinthe normalisation bin
LauParametricStepFuncPdf::~LauParametricStepFuncPdf ( )
virtual

Destructor.

Definition at line 69 of file LauParametricStepFuncPdf.cc.

LauParametricStepFuncPdf::LauParametricStepFuncPdf ( const LauParametricStepFuncPdf rhs)
private

Copy constructor (not implemented)

Member Function Documentation

void LauParametricStepFuncPdf::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 74 of file LauParametricStepFuncPdf.cc.

void LauParametricStepFuncPdf::calcNorm ( )
virtual

Calculate the normalisation.

Reimplemented from LauAbsPdf.

Definition at line 148 of file LauParametricStepFuncPdf.cc.

void LauParametricStepFuncPdf::calcPDFHeight ( const LauKinematics kinematics)
virtual

Calculate the PDF height.

Parameters
[in]kinematicsthe current DP kinematics

Implements LauAbsPdf.

Definition at line 153 of file LauParametricStepFuncPdf.cc.

UInt_t LauParametricStepFuncPdf::nBins ( ) const
inlineprotected

Number of bins.

Returns
the number of bins

Definition at line 94 of file LauParametricStepFuncPdf.hh.

NormBin LauParametricStepFuncPdf::normBin ( ) const
inlineprotected

Normalisation bin.

Returns
the normalisation bin

Definition at line 100 of file LauParametricStepFuncPdf.hh.

LauParametricStepFuncPdf& LauParametricStepFuncPdf::operator= ( const LauParametricStepFuncPdf rhs)
private

Copy assignment operator (not implemented)

Member Data Documentation

std::vector<Double_t> LauParametricStepFuncPdf::limits_
private

limits of the bins

Definition at line 112 of file LauParametricStepFuncPdf.hh.

NormBin LauParametricStepFuncPdf::normBin_
private

normalisation bin

Definition at line 110 of file LauParametricStepFuncPdf.hh.


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