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

#include <ForwardDifferenceGradientEstimate.hpp>

Inheritance diagram for ipo_function::detail::ForwardDifferenceGradientEstimate:

Collaboration diagram for ipo_function::detail::ForwardDifferenceGradientEstimate:

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

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

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...

Protected Attributes
Function &	function
	The function. More...

double const	h
	The qotient size. 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...

Detailed Description

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

The function must be supplied as an ipo::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.

See also: DerivativesEstimates

Definition at line 47 of file ForwardDifferenceGradientEstimate.hpp.

Constructor & Destructor Documentation

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