Eigen::NumericalDiff< _Functor, mode > Class Template Reference

This class allows you to add a method df() to your functor, which will use numerical differentiation to compute an approximate of the derivative for the functor. More...

#include <NumericalDiff.h>

Inheritance diagram for Eigen::NumericalDiff< _Functor, mode >:

Public Types
enum	{ InputsAtCompileTime = Functor::InputsAtCompileTime, ValuesAtCompileTime = Functor::ValuesAtCompileTime }
typedef _Functor	Functor
typedef Functor::Scalar	Scalar
typedef Functor::InputType	InputType
typedef Functor::ValueType	ValueType
typedef Functor::JacobianType	JacobianType

Public Member Functions
	NumericalDiff (Scalar _epsfcn=0.)
	NumericalDiff (const Functor &f, Scalar _epsfcn=0.)
template<typename T0 >
	NumericalDiff (const T0 &a0)
template<typename T0 , typename T1 >
	NumericalDiff (const T0 &a0, const T1 &a1)
template<typename T0 , typename T1 , typename T2 >
	NumericalDiff (const T0 &a0, const T1 &a1, const T2 &a2)
int	df (const InputType &_x, JacobianType &jac) const
	return the number of evaluation of functor

Detailed Description

template<typename _Functor, NumericalDiffMode mode = Forward>
class Eigen::NumericalDiff< _Functor, mode >

This class allows you to add a method df() to your functor, which will use numerical differentiation to compute an approximate of the derivative for the functor.

Of course, if you have an analytical form for the derivative, you should rather implement df() by yourself.

More information on http://en.wikipedia.org/wiki/Numerical_differentiation

Currently only "Forward" and "Central" scheme are implemented.

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The documentation for this class was generated from the following file:

• third-party-libs/eigen3/unsupported/Eigen/src/NumericalDiff/NumericalDiff.h