Extension of the FCNBase for the Fumili method.

Fumili applies only to minimization problems used for fitting. The method is based on a linearization of the model function negleting second derivatives. User needs to provide the model function. The figure-of-merit describing the difference between the model function and the actual measurements has to be implemented by the user in a subclass of FumiliFCNBase. For an example see the FumiliChi2FCN and FumiliStandardChi2FCN classes.

Author: Andras Zsenei and Lorenzo Moneta, Creation date: 23 Aug 2004

See also: MINUIT Tutorial on function minimization, section 5; FumiliChi2FCN; FumiliStandardChi2FCN

Definition at line 46 of file FumiliFCNBase.h.

Public Member Functions
	FumiliFCNBase ()
	Default Constructor.

	FumiliFCNBase (unsigned int npar)
	Constructor which initializes the class with the function provided by the user for modeling the data.

virtual unsigned int	Dimension ()
	return number of function variable (parameters) , i.e.

virtual double	ErrorDef () const
	Error definition of the function.

virtual void	EvaluateAll (std::vector< double > const &par)=0
	Evaluate function Value, Gradient and Hessian using Fumili approximation, for values of parameters p The result is cached inside and is return from the FumiliFCNBase::Value , FumiliFCNBase::Gradient and FumiliFCNBase::Hessian methods.

virtual std::vector< double >	G2 (std::vector< double > const &) const
	Return the diagonal elements of the Hessian (second derivatives).

virtual const std::vector< double > &	Gradient () const
	Return cached Value of function Gradient estimated previously using the FumiliFCNBase::EvaluateAll method.

std::vector< double >	Gradient (std::vector< double > const &) const override
	Return the gradient vector of the function at the given parameter point.

virtual std::vector< double >	GradientWithPrevResult (std::vector< double > const &parameters, double , double , double *) const

virtual GradientParameterSpace	gradParameterSpace () const

virtual bool	HasG2 () const

bool	HasGradient () const override

virtual bool	HasHessian () const

std::vector< double >	Hessian (std::vector< double > const &) const override
	Return Value of the i-th j-th element of the Hessian matrix estimated previously using the FumiliFCNBase::EvaluateAll method.

virtual double	Hessian (unsigned int row, unsigned int col) const

virtual double	operator() (std::vector< double > const &v) const =0
	The meaning of the vector of parameters is of course defined by the user, who uses the values of those parameters to calculate their function Value.

virtual void	SetErrorDef (double)
	add interface to set dynamically a new error definition Re-implement this function if needed.

virtual double	Up () const =0
	Error definition of the function.

virtual double	Value () const
	Return cached Value of objective function estimated previously using the FumiliFCNBase::EvaluateAll method.

Protected Member Functions
std::vector< double > &	Gradient ()

std::vector< double > &	Hessian ()

virtual void	InitAndReset (unsigned int npar)
	initialize and reset values of gradien and Hessian

void	SetFCNValue (double value)

Private Attributes
std::vector< double >	fGradient

std::vector< double >	fHessian

unsigned int	fNumberOfParameters

double	fValue

#include <Minuit2/FumiliFCNBase.h>

Inheritance diagram for ROOT::Minuit2::FumiliFCNBase:

Constructor & Destructor Documentation

◆ FumiliFCNBase() [1/2]

ROOT::Minuit2::FumiliFCNBase::FumiliFCNBase ( )

inline

Default Constructor.

Need in this case to create when implementing EvaluateAll the Gradient and Hessian vectors with the right size

Definition at line 54 of file FumiliFCNBase.h.

◆ FumiliFCNBase() [2/2]

ROOT::Minuit2::FumiliFCNBase::FumiliFCNBase ( unsigned int npar )

inline

Constructor which initializes the class with the function provided by the user for modeling the data.

Parameters

npar	the number of parameters

Definition at line 67 of file FumiliFCNBase.h.

Member Function Documentation

◆ Dimension()

virtual unsigned int ROOT::Minuit2::FumiliFCNBase::Dimension ( )

inlinevirtual

return number of function variable (parameters) , i.e.

function dimension

Definition at line 121 of file FumiliFCNBase.h.

◆ ErrorDef()

virtual double ROOT::Minuit2::FCNBase::ErrorDef ( ) const

inlinevirtualinherited

Error definition of the function.

MINUIT defines Parameter errors as the change in Parameter Value required to change the function Value by up. Normally, for chisquared fits it is 1, and for negative log likelihood, its Value is 0.5. If the user wants instead the 2-sigma errors for chisquared fits, it becomes 4, as Chi2(x+n*sigma) = Chi2(x) + n*n.

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Definition at line 70 of file FCNBase.h.

◆ EvaluateAll()

virtual void ROOT::Minuit2::FumiliFCNBase::EvaluateAll ( std::vector< double > const & par )

pure virtual

Evaluate function Value, Gradient and Hessian using Fumili approximation, for values of parameters p The result is cached inside and is return from the FumiliFCNBase::Value , FumiliFCNBase::Gradient and FumiliFCNBase::Hessian methods.

Parameters

par	vector of parameters

Implemented in ROOT::Minuit2::FumiliStandardChi2FCN, ROOT::Minuit2::FumiliStandardMaximumLikelihoodFCN, and ROOT::Minuit2::FumiliFCNAdapter< Function >.

◆ G2()

virtual std::vector< double > ROOT::Minuit2::FCNBase::G2 ( std::vector< double > const & ) const

inlinevirtualinherited

Return the diagonal elements of the Hessian (second derivatives).

By default, returns an empty vector. Override this method if analytic second derivatives (per-parameter curvature) are available.

Parameters

v	Parameter vector.

Returns: Vector of second derivatives with respect to each parameter.

Reimplemented in ROOT::Minuit2::FCNAdapter.

Definition at line 116 of file FCNBase.h.

◆ Gradient() [1/3]

std::vector< double > & ROOT::Minuit2::FumiliFCNBase::Gradient ( )

inlineprotected

Definition at line 138 of file FumiliFCNBase.h.

◆ Gradient() [2/3]

virtual const std::vector< double > & ROOT::Minuit2::FumiliFCNBase::Gradient ( ) const

inlinevirtual

Return cached Value of function Gradient estimated previously using the FumiliFCNBase::EvaluateAll method.

Definition at line 97 of file FumiliFCNBase.h.

◆ Gradient() [3/3]

std::vector< double > ROOT::Minuit2::FumiliFCNBase::Gradient ( std::vector< double > const & ) const

inlineoverridevirtual

Return the gradient vector of the function at the given parameter point.

By default, returns an empty vector (no analytic gradient provided). Override this method if an analytic gradient is available.

Parameters

v	Parameter vector.

Returns: Gradient vector with respect to the parameters.

Reimplemented from ROOT::Minuit2::FCNBase.

Definition at line 98 of file FumiliFCNBase.h.

◆ GradientWithPrevResult()

virtual std::vector< double > ROOT::Minuit2::FCNBase::GradientWithPrevResult	(	std::vector< double > const &	parameters,
		double *	,
		double *	,
		double *	) const

inlinevirtualinherited

Warning: Not meant to be overridden! This is a requirement for an internal optimization in RooFit that might go away with any refactoring.

Definition at line 99 of file FCNBase.h.

◆ gradParameterSpace()

virtual GradientParameterSpace ROOT::Minuit2::FCNBase::gradParameterSpace ( ) const

inlinevirtualinherited

Warning: Not meant to be overridden! This is a requirement for an internal optimization in RooFit that might go away with any refactoring.

Definition at line 107 of file FCNBase.h.

◆ HasG2()

virtual bool ROOT::Minuit2::FCNBase::HasG2 ( ) const

inlinevirtualinherited

Reimplemented in ROOT::Minuit2::FCNAdapter.

Definition at line 129 of file FCNBase.h.

◆ HasGradient()

bool ROOT::Minuit2::FumiliFCNBase::HasGradient ( ) const

inlineoverridevirtual

Reimplemented from ROOT::Minuit2::FCNBase.

Definition at line 56 of file FumiliFCNBase.h.

◆ HasHessian()

virtual bool ROOT::Minuit2::FCNBase::HasHessian ( ) const

inlinevirtualinherited

Reimplemented in ROOT::Minuit2::FCNAdapter.

Definition at line 127 of file FCNBase.h.

◆ Hessian() [1/3]

std::vector< double > & ROOT::Minuit2::FumiliFCNBase::Hessian ( )

inlineprotected

Definition at line 140 of file FumiliFCNBase.h.

◆ Hessian() [2/3]

std::vector< double > ROOT::Minuit2::FumiliFCNBase::Hessian ( std::vector< double > const & ) const

inlineoverridevirtual

Return Value of the i-th j-th element of the Hessian matrix estimated previously using the FumiliFCNBase::EvaluateAll method.

Parameters

row	row Index of the matrix
col	col Index of the matrix

Reimplemented from ROOT::Minuit2::FCNBase.

Definition at line 107 of file FumiliFCNBase.h.

◆ Hessian() [3/3]

virtual double ROOT::Minuit2::FumiliFCNBase::Hessian	(	unsigned int	row,
		unsigned int	col ) const

inlinevirtual

Definition at line 108 of file FumiliFCNBase.h.

◆ InitAndReset()

virtual void ROOT::Minuit2::FumiliFCNBase::InitAndReset ( unsigned int npar )

inlineprotectedvirtual

initialize and reset values of gradien and Hessian

Definition at line 128 of file FumiliFCNBase.h.

◆ operator()()

virtual double ROOT::Minuit2::FCNBase::operator() ( std::vector< double > const & v ) const

pure virtualinherited

The meaning of the vector of parameters is of course defined by the user, who uses the values of those parameters to calculate their function Value.

The order and the position of these parameters is strictly the one specified by the user when supplying the starting values for minimization. The starting values must be specified by the user, either via an std::vector<double> or the MnUserParameters supplied as input to the MINUIT minimizers such as VariableMetricMinimizer or MnMigrad. Later values are determined by MINUIT as it searches for the Minimum or performs whatever analysis is requested by the user.

Parameters

v	function parameters as defined by the user.

Returns: the Value of the function.

See also: MnUserParameters; VariableMetricMinimizer; MnMigrad

Implemented in ROOT::Minuit2::FumiliChi2FCN, ROOT::Minuit2::FumiliMaximumLikelihoodFCN, ROOT::Minuit2::FCNAdapter, ROOT::Minuit2::FumiliFCNAdapter< Function >, and ROOT::Minuit2::ParametricFunction.

◆ SetErrorDef()

virtual void ROOT::Minuit2::FCNBase::SetErrorDef ( double )

inlinevirtualinherited

add interface to set dynamically a new error definition Re-implement this function if needed.

Reimplemented in ROOT::Minuit2::FCNAdapter, and ROOT::Minuit2::FumiliFCNAdapter< Function >.

Definition at line 84 of file FCNBase.h.

◆ SetFCNValue()

void ROOT::Minuit2::FumiliFCNBase::SetFCNValue ( double value )

inlineprotected

Definition at line 136 of file FumiliFCNBase.h.

◆ Up()

virtual double ROOT::Minuit2::FCNBase::Up ( ) const

pure virtualinherited

Error definition of the function.

MINUIT defines Parameter errors as the change in Parameter Value required to change the function Value by up. Normally, for chisquared fits it is 1, and for negative log likelihood, its Value is 0.5. If the user wants instead the 2-sigma errors for chisquared fits, it becomes 4, as Chi2(x+n*sigma) = Chi2(x) + n*n.

Implemented in ROOT::Minuit2::FCNAdapter, ROOT::Minuit2::FumiliChi2FCN, ROOT::Minuit2::FumiliFCNAdapter< Function >, and ROOT::Minuit2::FumiliMaximumLikelihoodFCN.

◆ Value()

virtual double ROOT::Minuit2::FumiliFCNBase::Value ( ) const

inlinevirtual

Return cached Value of objective function estimated previously using the FumiliFCNBase::EvaluateAll method.

Definition at line 91 of file FumiliFCNBase.h.

Member Data Documentation

◆ fGradient

std::vector<double> ROOT::Minuit2::FumiliFCNBase::fGradient

private

Definition at line 145 of file FumiliFCNBase.h.

◆ fHessian

std::vector<double> ROOT::Minuit2::FumiliFCNBase::fHessian

private

Definition at line 146 of file FumiliFCNBase.h.

◆ fNumberOfParameters

unsigned int ROOT::Minuit2::FumiliFCNBase::fNumberOfParameters

private

Definition at line 143 of file FumiliFCNBase.h.

◆ fValue

double ROOT::Minuit2::FumiliFCNBase::fValue

private

Definition at line 144 of file FumiliFCNBase.h.

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

math/minuit2/inc/Minuit2/FumiliFCNBase.h

Public Member Functions

Protected Member Functions

Private Attributes

Constructor & Destructor Documentation

◆ FumiliFCNBase() [1/2]

◆ FumiliFCNBase() [2/2]

Member Function Documentation

◆ Dimension()

◆ ErrorDef()

◆ EvaluateAll()

◆ G2()

◆ Gradient() [1/3]

◆ Gradient() [2/3]

◆ Gradient() [3/3]

◆ GradientWithPrevResult()

◆ gradParameterSpace()

◆ HasG2()

◆ HasGradient()

◆ HasHessian()

◆ Hessian() [1/3]

◆ Hessian() [2/3]

◆ Hessian() [3/3]

◆ InitAndReset()

◆ operator()()

◆ SetErrorDef()

◆ SetFCNValue()

◆ Up()

◆ Value()

Member Data Documentation

◆ fGradient

◆ fHessian

◆ fNumberOfParameters

◆ fValue