template<class DerivFunType, class ModelFunType = ROOT::Math::IParamMultiFunction>
class ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >

LogLikelihoodFCN class for likelihood fits.

it is template to distinguish gradient and non-gradient case

Definition at line 40 of file LogLikelihoodFCN.h.

Public Types
typedef BasicFCN< DerivFunType, ModelFunType, UnBinData >	BaseFCN

typedef BaseObjFunction::BaseFunction	BaseFunction

typedef ::ROOT::Math::BasicFitMethodFunction< DerivFunType >	BaseObjFunction

typedef ::ROOT::Math::IParamMultiFunctionTempl< T >	IModelFunction

typedef ModelFunType::BackendType	T

typedef BaseObjFunction::Type_t	Type_t

Public Types inherited from ROOT::Math::BasicFitMethodFunction< DerivFunType >
typedef FunctionType::BaseFunc	BaseFunction

enum	Type_t
	enumeration specifying the possible fit method types More...

Public Member Functions
	LogLikelihoodFCN (const LogLikelihoodFCN &f)
	Copy constructor.

	LogLikelihoodFCN (const std::shared_ptr< UnBinData > &data, const std::shared_ptr< IModelFunction > &func, int weight=0, bool extended=false, const ::ROOT::EExecutionPolicy &executionPolicy=::ROOT::EExecutionPolicy::kSequential)
	Constructor from unbin data set and model function (pdf)

	LogLikelihoodFCN (const UnBinData &data, const IModelFunction &func, int weight=0, bool extended=false, const ::ROOT::EExecutionPolicy &executionPolicy=::ROOT::EExecutionPolicy::kSequential)
	Constructor from unbin data set and model function (pdf) for object managed by users.

virtual	~LogLikelihoodFCN ()
	Destructor (no operations)

virtual BaseFunction *	Clone () const
	clone the function (need to return Base for Windows)

virtual double	DataElement (const double x, unsigned int i, double g, double *h=nullptr, bool fullHessian=false) const
	i-th likelihood contribution and its gradient

virtual void	Gradient (const double x, double g) const

virtual unsigned int	NFitPoints () const

LogLikelihoodFCN &	operator= (const LogLikelihoodFCN &rhs)
	Assignment operator.

virtual BaseObjFunction::Type_t	Type () const
	get type of fit method function

void	UseSumOfWeightSquare (bool on=true)

Public Member Functions inherited from ROOT::Fit::BasicFCN< DerivFunType, ModelFunType, DataType >
virtual const DataType &	Data () const
	access to const reference to the data

std::shared_ptr< DataType >	DataPtr () const
	access to data pointer

virtual bool	HasHessian () const
	flag to indicate if can compute Hessian

virtual const IModelFunction &	ModelFunction () const
	access to const reference to the model function

std::shared_ptr< IModelFunction >	ModelFunctionPtr () const
	access to function pointer

Public Member Functions inherited from ROOT::Math::BasicFitMethodFunction< DerivFunType >
	BasicFitMethodFunction (int dim, int npoint)

	~BasicFitMethodFunction () override
	Virtual Destructor (no operations)

virtual bool	G2 (const double , double ) const
	Computes the Second derivatives.

virtual bool	Hessian (const double x, double hess) const
	Computes the full Hessian.

bool	IsAGradFCN ()

virtual unsigned int	NCalls () const
	return the total number of function calls (override if needed)

unsigned int	NDim () const override
	Number of dimension (parameters) .

virtual unsigned int	NPoints () const
	return the number of data points used in evaluating the function

virtual void	ResetNCalls ()
	reset number of function calls

virtual void	UpdateNCalls () const
	update number of calls

Private Member Functions
virtual double	DoDerivative (const double *x, unsigned int icoord) const

virtual double	DoEval (const double *x) const
	Evaluation of the function (required by interface)

Private Attributes
::ROOT::EExecutionPolicy	fExecutionPolicy
	Execution policy.

std::vector< double >	fGrad
	for derivatives

bool	fIsExtended
	flag for indicating if likelihood is extended

unsigned int	fNEffPoints
	number of effective points used in the fit

int	fWeight
	flag to indicate if needs to evaluate using weight or weight squared (default weight = 0)

Additional Inherited Members
Static Public Member Functions inherited from ROOT::Math::BasicFitMethodFunction< DerivFunType >
static bool	IsAGradFCN ()
	Static function to indicate if a function is supporting gradient.

Protected Types inherited from ROOT::Fit::BasicFCN< DerivFunType, ModelFunType, DataType >
typedef BaseObjFunction::BaseFunction	BaseFunction

typedef ::ROOT::Math::BasicFitMethodFunction< DerivFunType >	BaseObjFunction

typedef ::ROOT::Math::IParametricGradFunctionMultiDimTempl< T >	IGradModelFunction

typedef ::ROOT::Math::IParamMultiFunctionTempl< T >	IModelFunction

typedef ModelFunType::BackendType	T

Protected Member Functions inherited from ROOT::Fit::BasicFCN< DerivFunType, ModelFunType, DataType >
	BasicFCN (const std::shared_ptr< DataType > &data, const std::shared_ptr< IModelFunction > &func)
	Constructor from data set and model function.

virtual	~BasicFCN ()
	Destructor (no operations)

void	SetData (const std::shared_ptr< DataType > &data)
	Set the data pointer.

void	SetModelFunction (const std::shared_ptr< IModelFunction > &func)
	Set the function pointer.

Protected Attributes inherited from ROOT::Fit::BasicFCN< DerivFunType, ModelFunType, DataType >
std::shared_ptr< DataType >	fData

std::shared_ptr< IModelFunction >	fFunc

#include <Fit/LogLikelihoodFCN.h>

Inheritance diagram for ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >:

[legend]

Member Typedef Documentation

◆ BaseFCN

template<class DerivFunType , class ModelFunType = ROOT::Math::IParamMultiFunction>

typedef BasicFCN<DerivFunType,ModelFunType,UnBinData> ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >::BaseFCN

Definition at line 45 of file LogLikelihoodFCN.h.

◆ BaseFunction

template<class DerivFunType , class ModelFunType = ROOT::Math::IParamMultiFunction>

typedef BaseObjFunction::BaseFunction ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >::BaseFunction

Definition at line 48 of file LogLikelihoodFCN.h.

◆ BaseObjFunction

template<class DerivFunType , class ModelFunType = ROOT::Math::IParamMultiFunction>

typedef ::ROOT::Math::BasicFitMethodFunction<DerivFunType> ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >::BaseObjFunction

Definition at line 47 of file LogLikelihoodFCN.h.

◆ IModelFunction

template<class DerivFunType , class ModelFunType = ROOT::Math::IParamMultiFunction>

typedef ::ROOT::Math::IParamMultiFunctionTempl<T> ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >::IModelFunction

Definition at line 50 of file LogLikelihoodFCN.h.

◆ T

template<class DerivFunType , class ModelFunType = ROOT::Math::IParamMultiFunction>

typedef ModelFunType::BackendType ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >::T

Definition at line 44 of file LogLikelihoodFCN.h.

◆ Type_t

template<class DerivFunType , class ModelFunType = ROOT::Math::IParamMultiFunction>

typedef BaseObjFunction::Type_t ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >::Type_t

Definition at line 51 of file LogLikelihoodFCN.h.

Constructor & Destructor Documentation

◆ LogLikelihoodFCN() [1/3]

template<class DerivFunType , class ModelFunType = ROOT::Math::IParamMultiFunction>

ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >::LogLikelihoodFCN	(	const std::shared_ptr< UnBinData > &	data,
		const std::shared_ptr< IModelFunction > &	func,
		int	weight = `0`,
		bool	extended = `false`,
		const ::ROOT::EExecutionPolicy &	executionPolicy = `::ROOT::EExecutionPolicy::kSequential`
	)

inline

Constructor from unbin data set and model function (pdf)

Definition at line 57 of file LogLikelihoodFCN.h.

◆ LogLikelihoodFCN() [2/3]

template<class DerivFunType , class ModelFunType = ROOT::Math::IParamMultiFunction>

ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >::LogLikelihoodFCN	(	const UnBinData &	data,
		const IModelFunction &	func,
		int	weight = `0`,
		bool	extended = `false`,
		const ::ROOT::EExecutionPolicy &	executionPolicy = `::ROOT::EExecutionPolicy::kSequential`
	)

inline

Constructor from unbin data set and model function (pdf) for object managed by users.

Definition at line 69 of file LogLikelihoodFCN.h.

◆ ~LogLikelihoodFCN()

template<class DerivFunType , class ModelFunType = ROOT::Math::IParamMultiFunction>

virtual ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >::~LogLikelihoodFCN ( )

inlinevirtual

Destructor (no operations)

Definition at line 81 of file LogLikelihoodFCN.h.

◆ LogLikelihoodFCN() [3/3]

template<class DerivFunType , class ModelFunType = ROOT::Math::IParamMultiFunction>

ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >::LogLikelihoodFCN ( const LogLikelihoodFCN< DerivFunType, ModelFunType > & f )

inline

Copy constructor.

Definition at line 86 of file LogLikelihoodFCN.h.

Member Function Documentation

◆ Clone()

template<class DerivFunType , class ModelFunType = ROOT::Math::IParamMultiFunction>

virtual BaseFunction * ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >::Clone ( ) const

inlinevirtual

clone the function (need to return Base for Windows)

Definition at line 112 of file LogLikelihoodFCN.h.

◆ DataElement()

template<class DerivFunType , class ModelFunType = ROOT::Math::IParamMultiFunction>

virtual double ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >::DataElement	(	const double *	x,
		unsigned int	i,
		double *	g,
		double *	h = `nullptr`,
		bool	fullHessian = `false`
	)		const

inlinevirtual

i-th likelihood contribution and its gradient

Implements ROOT::Math::BasicFitMethodFunction< DerivFunType >.

Definition at line 121 of file LogLikelihoodFCN.h.

◆ DoDerivative()

template<class DerivFunType , class ModelFunType = ROOT::Math::IParamMultiFunction>

virtual double ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >::DoDerivative	(	const double *	x,
		unsigned int	icoord
	)		const

inlineprivatevirtual

Definition at line 161 of file LogLikelihoodFCN.h.

◆ DoEval()

template<class DerivFunType , class ModelFunType = ROOT::Math::IParamMultiFunction>

virtual double ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >::DoEval ( const double * x ) const

inlineprivatevirtual

Evaluation of the function (required by interface)

Definition at line 155 of file LogLikelihoodFCN.h.

◆ Gradient()

template<class DerivFunType , class ModelFunType = ROOT::Math::IParamMultiFunction>

virtual void ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >::Gradient	(	const double *	x,
		double *	g
	)		const

inlinevirtual

Definition at line 127 of file LogLikelihoodFCN.h.

◆ NFitPoints()

template<class DerivFunType , class ModelFunType = ROOT::Math::IParamMultiFunction>

virtual unsigned int ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >::NFitPoints ( ) const

inlinevirtual

Definition at line 118 of file LogLikelihoodFCN.h.

◆ operator=()

template<class DerivFunType , class ModelFunType = ROOT::Math::IParamMultiFunction>

LogLikelihoodFCN & ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >::operator= ( const LogLikelihoodFCN< DerivFunType, ModelFunType > & rhs )

inline

Assignment operator.

Definition at line 99 of file LogLikelihoodFCN.h.

◆ Type()

template<class DerivFunType , class ModelFunType = ROOT::Math::IParamMultiFunction>

virtual BaseObjFunction::Type_t ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >::Type ( ) const

inlinevirtual

get type of fit method function

Reimplemented from ROOT::Math::BasicFitMethodFunction< DerivFunType >.

Definition at line 134 of file LogLikelihoodFCN.h.

◆ UseSumOfWeightSquare()

template<class DerivFunType , class ModelFunType = ROOT::Math::IParamMultiFunction>

void ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >::UseSumOfWeightSquare ( bool on = true )

inline

Definition at line 139 of file LogLikelihoodFCN.h.

Member Data Documentation

◆ fExecutionPolicy

template<class DerivFunType , class ModelFunType = ROOT::Math::IParamMultiFunction>

::ROOT::EExecutionPolicy ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >::fExecutionPolicy

private

Execution policy.

Definition at line 176 of file LogLikelihoodFCN.h.

◆ fGrad

template<class DerivFunType , class ModelFunType = ROOT::Math::IParamMultiFunction>

std::vector<double> ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >::fGrad

mutableprivate

for derivatives

Definition at line 174 of file LogLikelihoodFCN.h.

◆ fIsExtended

template<class DerivFunType , class ModelFunType = ROOT::Math::IParamMultiFunction>

bool ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >::fIsExtended

private

flag for indicating if likelihood is extended

Definition at line 168 of file LogLikelihoodFCN.h.

◆ fNEffPoints

template<class DerivFunType , class ModelFunType = ROOT::Math::IParamMultiFunction>

unsigned int ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >::fNEffPoints

mutableprivate

number of effective points used in the fit

Definition at line 172 of file LogLikelihoodFCN.h.

◆ fWeight

template<class DerivFunType , class ModelFunType = ROOT::Math::IParamMultiFunction>

int ROOT::Fit::LogLikelihoodFCN< DerivFunType, ModelFunType >::fWeight

private

flag to indicate if needs to evaluate using weight or weight squared (default weight = 0)

Definition at line 169 of file LogLikelihoodFCN.h.

math/mathcore/inc/Fit/LogLikelihoodFCN.h

Public Types

Public Member Functions

Private Member Functions

Private Attributes

Additional Inherited Members

Member Typedef Documentation

◆ BaseFCN

◆ BaseFunction

◆ BaseObjFunction

◆ IModelFunction

◆ T

◆ Type_t

Constructor & Destructor Documentation

◆ LogLikelihoodFCN() [1/3]

◆ LogLikelihoodFCN() [2/3]

◆ ~LogLikelihoodFCN()

◆ LogLikelihoodFCN() [3/3]

Member Function Documentation

◆ Clone()

◆ DataElement()

◆ DoDerivative()

◆ DoEval()

◆ Gradient()

◆ NFitPoints()

◆ operator=()

◆ Type()

◆ UseSumOfWeightSquare()

Member Data Documentation

◆ fExecutionPolicy

◆ fGrad

◆ fIsExtended

◆ fNEffPoints

◆ fWeight