roboptim::FiniteDifferenceGradient< FdgPolicy > Class Template Reference
[Mathematical functions]

Compute automatically a gradient with finite differences. More...

#include <roboptim/core/finite-difference-gradient.hh>

Inheritance diagram for roboptim::FiniteDifferenceGradient< FdgPolicy >:

List of all members.

Public Member Functions
	FiniteDifferenceGradient (const Function &f, value_type e=finiteDifferenceEpsilon) throw ()
	Instantiate a finite differences gradient.
	~FiniteDifferenceGradient () throw ()
Protected Member Functions
void	impl_compute (result_t &, const argument_t &) const throw ()
	Function evaluation.
void	impl_gradient (gradient_t &, const argument_t &argument, size_type=0) const throw ()
	Gradient evaluation.
Protected Attributes
const Function &	adaptee_
	Reference to the wrapped function.
const value_type	epsilon_

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Detailed Description

template<typename FdgPolicy>
class roboptim::FiniteDifferenceGradient< FdgPolicy >

Compute automatically a gradient with finite differences.

Finite difference gradient is a method to approximate a function's gradient. It is particularly useful in RobOptim to avoid the need to compute the analytical gradient manually.

This class takes a Function as its input and wraps it into a derivable function.

The one dimensional formula is:

where is a constant given when calling the class constructor.

Examples:

finite-difference-gradient.cc.

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Constructor & Destructor Documentation

template<typename FdgPolicy >

roboptim::FiniteDifferenceGradient< FdgPolicy >::FiniteDifferenceGradient	(	const Function &	f,
		value_type	e = finiteDifferenceEpsilon
	)			throw () [inline]

Instantiate a finite differences gradient.

Instantiate a derivable function that will wraps a non derivable function and compute automatically its gradient using finite differences.

Parameters:

	f	function that will e wrapped
	e	epsilon used in finite difference computation

template<typename FdgPolicy >

roboptim::FiniteDifferenceGradient< FdgPolicy >::~FiniteDifferenceGradient

(

)

throw () [inline]

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Member Function Documentation

template<typename FdgPolicy >

void roboptim::FiniteDifferenceGradient< FdgPolicy >::impl_compute	(	result_t &	result,
		const argument_t &	argument
	)			const throw () [inline, protected, virtual]

Function evaluation.

Evaluate the function, has to be implemented in concrete classes.

Warning:

Do not call this function directly, call operator()(result_t&, const argument_t&) const throw () instead.

Parameters:

	result	result will be stored in this vector
	argument	point at which the function will be evaluated

Implements roboptim::Function.

template<typename FdgPolicy >

void roboptim::FiniteDifferenceGradient< FdgPolicy >::impl_gradient	(	gradient_t &	gradient,
		const argument_t &	argument,
		size_type	functionId = 0
	)			const throw () [inline, protected, virtual]

Gradient evaluation.

Compute the gradient, has to be implemented in concrete classes. The gradient is computed for a specific sub-function which id is passed through the functionId argument.

Warning:

Do not call this function directly, call gradient instead.

Parameters:

	gradient	gradient will be store in this argument
	argument	point where the gradient will be computed
	functionId	evaluated function id in the split representation

Implements roboptim::DerivableFunction.

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Member Data Documentation

template<typename FdgPolicy>

const Function& roboptim::FiniteDifferenceGradient< FdgPolicy >::adaptee_ [protected]

Reference to the wrapped function.

template<typename FdgPolicy>

const value_type roboptim::FiniteDifferenceGradient< FdgPolicy >::epsilon_ [protected]