roboptim::finiteDifferenceGradientPolicies::FivePointsRule< T > Class Template Reference

Precise finite difference gradient computation. More...

#include <roboptim/core/fwd.hh>

Inheritance diagram for roboptim::finiteDifferenceGradientPolicies::FivePointsRule< T >:

Public Member Functions
	ROBOPTIM_DIFFERENTIABLE_FUNCTION_FWD_TYPEDEFS_ (GenericDifferentiableFunction< T >)
	FivePointsRule (const GenericFunction< T > &adaptee)
void	computeColumn (value_type epsilon, gradient_ref column, const_argument_ref argument, size_type colIdx, argument_ref xEps) const
void	computeGradient (value_type epsilon, gradient_ref gradient, const_argument_ref argument, size_type idFunction, argument_ref xEps) const
void	computeJacobian (value_type epsilon, jacobian_ref jacobian, const_argument_ref argument, argument_ref xEps) const
void	compute_deriv (typename GenericFunction< T >::size_type j, double h, double &result, double &round, double &trunc, typename GenericFunction< T >::const_argument_ref argument, typename GenericFunction< T >::size_type idFunction, typename GenericFunction< T >::argument_ref xEps) const
	Algorithm from the Gnu Scientific Library. More...
template<>
void	computeGradient (value_type epsilon, gradient_ref gradient, const_argument_ref argument, size_type idFunction, argument_ref xEps) const
template<>
void	computeJacobian (value_type epsilon, jacobian_ref jacobian, const_argument_ref argument, argument_ref xEps) const
template<>
void	computeColumn (value_type, gradient_ref, const_argument_ref, size_type, argument_ref) const
Public Member Functions inherited from roboptim::finiteDifferenceGradientPolicies::Policy< T >
	ROBOPTIM_DIFFERENTIABLE_FUNCTION_FWD_TYPEDEFS_ (GenericDifferentiableFunction< T >)
	Policy (const GenericFunction< T > &adaptee)
virtual	~Policy ()
	Virtual destructor. More...
value_type &	sparseEpsilon ()
	Get a reference to the epsilon used to converse dense to sparse matrices. More...

Additional Inherited Members
Protected Member Functions inherited from roboptim::finiteDifferenceGradientPolicies::Policy< T >
template<>
void	computeJacobian (value_type epsilon, jacobian_ref jacobian, const_argument_ref argument, argument_ref xEps) const
Protected Attributes inherited from roboptim::finiteDifferenceGradientPolicies::Policy< T >
const GenericFunction< T > &	adaptee_
	Wrapped function. More...
vector_t	column_
	Vector storing temporary Jacobian column. More...
gradient_t	gradient_
	Vector storing temporary Jacobian row. More...
value_type	sparseEps_
	Threshold used for the conversion from dense to sparse matrix. More...

Detailed Description

template<typename T>
class roboptim::finiteDifferenceGradientPolicies::FivePointsRule< T >

Precise finite difference gradient computation.

Finite difference is computed using five-points stencil (i.e. \(\{x-2h, x-h, x, x+h, x+2h\}\)).

Constructor & Destructor Documentation

template<typename T >

roboptim::finiteDifferenceGradientPolicies::FivePointsRule< T >::FivePointsRule ( const GenericFunction< T > &  adaptee )

inlineexplicit

Member Function Documentation

template<typename T >

void roboptim::finiteDifferenceGradientPolicies::FivePointsRule< T >::compute_deriv	(	typename GenericFunction< T >::size_type	j,
		double	h,
		double &	result,
		double &	round,
		double &	trunc,
		typename GenericFunction< T >::const_argument_ref	argument,
		typename GenericFunction< T >::size_type	idFunction,
		typename GenericFunction< T >::argument_ref	xEps
	)		const

Algorithm from the Gnu Scientific Library.

template<typename T >

void roboptim::finiteDifferenceGradientPolicies::FivePointsRule< T >::computeColumn ( value_type  epsilon, gradient_ref  column, const_argument_ref  argument, size_type  colIdx, argument_ref  xEps  ) const

virtual

Implements roboptim::finiteDifferenceGradientPolicies::Policy< T >.

template<>

void roboptim::finiteDifferenceGradientPolicies::FivePointsRule< EigenMatrixSparse >::computeColumn ( value_type  , gradient_ref  , const_argument_ref  , size_type  , argument_ref    ) const

inlinevirtual

Implements roboptim::finiteDifferenceGradientPolicies::Policy< T >.

template<typename T >

void roboptim::finiteDifferenceGradientPolicies::FivePointsRule< T >::computeGradient ( value_type  epsilon, gradient_ref  gradient, const_argument_ref  argument, size_type  idFunction, argument_ref  xEps  ) const

virtual

Implements roboptim::finiteDifferenceGradientPolicies::Policy< T >.

template<>

void roboptim::finiteDifferenceGradientPolicies::FivePointsRule< EigenMatrixSparse >::computeGradient ( value_type  epsilon, gradient_ref  gradient, const_argument_ref  argument, size_type  idFunction, argument_ref  xEps  ) const

inlinevirtual

Implements roboptim::finiteDifferenceGradientPolicies::Policy< T >.

template<typename T >

void roboptim::finiteDifferenceGradientPolicies::FivePointsRule< T >::computeJacobian ( value_type  epsilon, jacobian_ref  jacobian, const_argument_ref  argument, argument_ref  xEps  ) const

virtual

Reimplemented from roboptim::finiteDifferenceGradientPolicies::Policy< T >.

Referenced by roboptim::finiteDifferenceGradientPolicies::FivePointsRule< T >::computeJacobian().

template<>

void roboptim::finiteDifferenceGradientPolicies::FivePointsRule< EigenMatrixSparse >::computeJacobian ( value_type  epsilon, jacobian_ref  jacobian, const_argument_ref  argument, argument_ref  xEps  ) const

inlinevirtual

ROBOPTIM_DO_NOT_CHECK_ALLOCATION

ROBOPTIM_DO_NOT_CHECK_ALLOCATION

Reimplemented from roboptim::finiteDifferenceGradientPolicies::Policy< T >.

References roboptim::finiteDifferenceGradientPolicies::FivePointsRule< T >::computeJacobian(), roboptim::is_malloc_allowed(), and roboptim::set_is_malloc_allowed().

template<typename T >

roboptim::finiteDifferenceGradientPolicies::FivePointsRule< T >::ROBOPTIM_DIFFERENTIABLE_FUNCTION_FWD_TYPEDEFS_

(

GenericDifferentiableFunction< T >

)