This class estimates a function value, gradient and Hessian at a given vector. More...

#include <ForwardDifferenceDerivativesEstimates.hpp>

Inheritance diagram for ipo_function::detail::ForwardDifferenceDerivativesEstimates:

Collaboration diagram for ipo_function::detail::ForwardDifferenceDerivativesEstimates:

Public Member Functions
	ForwardDifferenceDerivativesEstimates (Function &function, double const h=std::sqrt(std::numeric_limits< double >::epsilon()), double const h2=std::sqrt(std::sqrt(std::numeric_limits< double >::epsilon())))
	Find forward difference quotient estimates. More...

	~ForwardDifferenceDerivativesEstimates ()=default
	Default destructor. More...

	ForwardDifferenceDerivativesEstimates (ForwardDifferenceDerivativesEstimates const &)=delete
	No copy constructor. More...

ForwardDifferenceDerivativesEstimates &	operator= (ForwardDifferenceDerivativesEstimates const &)=delete
	No copy operator. More...

	ForwardDifferenceDerivativesEstimates (ForwardDifferenceDerivativesEstimates &&de)
	Move constructor. More...

ForwardDifferenceDerivativesEstimates &	operator= (ForwardDifferenceDerivativesEstimates &&de)
	Move operator. More...

virtual void	setVector (gsl::vector const &vector)
	Set the vector to a new value. More...

Public Member Functions inherited from ipo_function::DerivativesEstimates
	DerivativesEstimates (size_t const size=0)
	Constructor. More...

virtual gsl::matrix	hessian () const

Public Member Functions inherited from ipo_function::GradientEstimate
	GradientEstimate (size_t const size=0)
	Constructor. More...

virtual double	value () const

virtual gsl::vector	gradient () const

Public Member Functions inherited from ipo_function::detail::FunctionBase
	FunctionBase (size_t const size=0)
	Constructor. More...

virtual	~FunctionBase ()=0
	Make the class abstract. More...

size_t	getSize () const
	Get size of vector for function arguments or zero for arbitrary size. More...

Public Member Functions inherited from ipo_function::detail::ForwardDifferenceGradientEstimate
	ForwardDifferenceGradientEstimate (Function &function, double const h=std::sqrt(std::numeric_limits< double >::epsilon()))
	Find forward difference quotient estimates. More...

Protected Attributes
double const	h2
	The quotient size for hessian estimates: default is fourth root of machine epsilon. More...

Protected Attributes inherited from ipo_function::DerivativesEstimates
gsl::matrix	functionHessian
	The Hessian value. More...

Protected Attributes inherited from ipo_function::GradientEstimate
double	functionValue
	The function value. More...

gsl::vector	functionGradient
	The gradient value. More...

Protected Attributes inherited from ipo_function::detail::FunctionBase
size_t const	size
	Size of vector arguments to supply to subclass functions. More...

Protected Attributes inherited from ipo_function::detail::ForwardDifferenceGradientEstimate
Function &	function
	The function. More...

double const	h
	The qotient size. More...

Detailed Description

This class estimates a function value, gradient and Hessian at a given vector.

The function must be supplied as a Function. The vector must be supplied as a gsl::vector::vector. The gradient and Hessian are estimated using forward difference quotients. A forward difference quotient requires a value h and if no value is supplied, then the class uses the square root of the machine epsilon. This is a reasonably standard value and ensures that the function is evaluated with changes in approximately the lower half of the significant digits of the vector.

The values returned by gradient() and hessian() can be modified but should not be used once the object creating them no longer exists.

Definition at line 46 of file ForwardDifferenceDerivativesEstimates.hpp.

Constructor & Destructor Documentation

ForwardDifferenceDerivativesEstimates::ForwardDifferenceDerivativesEstimates	(	Function &	function,
		double const	h = `std::sqrt( std::numeric_limits<double>:: epsilon() )`,
		double const	h2 = `std:: sqrt( std::sqrt( std::numeric_limits<double>:: epsilon() ) )`
	)

Find forward difference quotient estimates.

Parameters

function	This is the function whose derivatives we estimate
h	The quotient size: default is square root of machine epsilon
h2	The quotient size for hessian estimates: default is fourth root of machine epsilon

Definition at line 29 of file ForwardDifferenceDerivativesEstimates.cc.

ipo_function::detail::ForwardDifferenceDerivativesEstimates::~ForwardDifferenceDerivativesEstimates ( )

default

Default destructor.

ipo_function::detail::ForwardDifferenceDerivativesEstimates::ForwardDifferenceDerivativesEstimates ( ForwardDifferenceDerivativesEstimates const & )

delete

No copy constructor.

ipo_function::detail::ForwardDifferenceDerivativesEstimates::ForwardDifferenceDerivativesEstimates ( ForwardDifferenceDerivativesEstimates && de )

Move constructor.

Parameters

de	Another DerivativesEstimate

Member Function Documentation

ForwardDifferenceDerivativesEstimates& ipo_function::detail::ForwardDifferenceDerivativesEstimates::operator= ( ForwardDifferenceDerivativesEstimates const & )

delete

No copy operator.

ForwardDifferenceDerivativesEstimates& ipo_function::detail::ForwardDifferenceDerivativesEstimates::operator= ( ForwardDifferenceDerivativesEstimates && de )

Move operator.

Parameters