Sample implementation of a parametric function.

It can be used for example for the Fumili method when minimizing with Minuit. In the present case the function is a one-dimensional Gaussian, which is described by its mean, standard deviation and the constant term describing the amplitude. As it is used for function minimization, the role of the variables (or coordinates) and parameters is inversed! I.e. in the case of a one-dimensional Gaussian it is x that will be the Parameter and the mean, standard deviation etc will be the variables.

Author: Andras Zsenei and Lorenzo Moneta, Creation date: 26 Oct 2004

See also: Definition of the Normal/Gaussian distribution (note: this Gaussian is normalized).; ParametricFunction; FumiliFCNBase; FumiliMaximumLikelihoodFCN

Definition at line 62 of file GaussianModelFunction.h.

Public Member Functions
	GaussianModelFunction ()
	Constructor which initializes the normalized Gaussian with x = 0.0. More...

	GaussianModelFunction (const std::vector< double > &params)
	Constructor which initializes the ParametricFunction with the parameters given as input. More...

	~GaussianModelFunction ()

std::vector< double >	GetGradient (const std::vector< double > &x) const
	Member function returning the Gradient of the function with respect to its variables (but without including gradients with respect to its internal parameters). More...

double	operator() (const std::vector< double > &x) const
	Calculates the Gaussian as a function of the given input. More...

double	operator() (const std::vector< double > &x, const std::vector< double > &param) const
	Calculates the Gaussian as a function of the given input. More...

virtual double	Up () const
	THAT SHOULD BE REMOVED, IT IS ONLY HERE, BECAUSE AT PRESENT FOR GRADIENT CALCULATION ONE NEEDS TO INHERIT FROM FCNBASE WHICH NEEDS THIS METHOD. More...

Public Member Functions inherited from ROOT::Minuit2::ParametricFunction
	ParametricFunction (const std::vector< double > &params)
	Constructor which initializes the ParametricFunction with the parameters given as input. More...

	ParametricFunction (int nparams)
	Constructor which initializes the ParametricFunction by setting the number of parameters. More...

virtual	~ParametricFunction ()

virtual const std::vector< double > &	GetParameters () const
	Accessor for the state of the parameters. More...

virtual unsigned int	NumberOfParameters () const
	Accessor for the number of parameters. More...

virtual void	SetParameters (const std::vector< double > &params) const
	Sets the parameters of the ParametricFunction. More...

Public Member Functions inherited from ROOT::Minuit2::FCNBase
virtual	~FCNBase ()

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

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

Public Member Functions inherited from ROOT::Minuit2::GenericFunction
virtual	~GenericFunction ()

Additional Inherited Members
Protected Attributes inherited from ROOT::Minuit2::ParametricFunction
std::vector< double >	par
	The vector containing the parameters of the function It is mutable for "historical reasons" as in the hierarchy methods and classes are const and all the implications of changing them back to non-const are not clear. More...

#include </mnt/build/workspace/root-makedoc-v610/rootspi/rdoc/src/v6-10-00-patches/math/minuit2/test/MnSim/GaussianModelFunction.h>

Inheritance diagram for ROOT::Minuit2::GaussianModelFunction:

[legend]

Constructor & Destructor Documentation

◆ GaussianModelFunction() [1/2]

ROOT::Minuit2::GaussianModelFunction::GaussianModelFunction ( )

inline

Constructor which initializes the normalized Gaussian with x = 0.0.

Definition at line 73 of file GaussianModelFunction.h.

◆ GaussianModelFunction() [2/2]

ROOT::Minuit2::GaussianModelFunction::GaussianModelFunction ( const std::vector< double > & params )

inline

Constructor which initializes the ParametricFunction with the parameters given as input.

Parameters

params vector containing the initial Parameter Value.

Definition at line 92 of file GaussianModelFunction.h.

◆ ~GaussianModelFunction()

ROOT::Minuit2::GaussianModelFunction::~GaussianModelFunction ( )

inline

Definition at line 101 of file GaussianModelFunction.h.

Member Function Documentation

◆ GetGradient()

std::vector<double> ROOT::Minuit2::GaussianModelFunction::GetGradient ( const std::vector< double > & x ) const

inlinevirtual

Member function returning the Gradient of the function with respect to its variables (but without including gradients with respect to its internal parameters).

Parameters

x	vector containing the coordinates of the point where the Gradient is to be calculated.

Returns: the Gradient vector of the function at the given point.

Reimplemented from ROOT::Minuit2::ParametricFunction.

Definition at line 167 of file GaussianModelFunction.h.

◆ operator()() [1/2]

double ROOT::Minuit2::GaussianModelFunction::operator() ( const std::vector< double > & x ) const

inlinevirtual

Calculates the Gaussian as a function of the given input.

Parameters

x	vector containing the mean, standard deviation and amplitude.

Returns: the Value of the Gaussian for the given input.

See also: Definition of the Normal/Gaussian distribution (note: this Gaussian is normalized).

Implements ROOT::Minuit2::ParametricFunction.

Definition at line 118 of file GaussianModelFunction.h.

◆ operator()() [2/2]

double ROOT::Minuit2::GaussianModelFunction::operator()	(	const std::vector< double > &	x,
		const std::vector< double > &	param
	)		const

inlinevirtual

Calculates the Gaussian as a function of the given input.

Parameters

x	vector containing the mean, the standard deviation and the constant describing the Gaussian.
par	vector containing the x coordinate (which is the Parameter in the case of a minimization).