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some more documentation

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This commit is contained in:
Thomas Capricelli
2009-11-09 04:21:45 +01:00
parent ac8f7d8c9c
commit de195e0e78
4 changed files with 59 additions and 20 deletions
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10
unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h
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@@ -28,6 +28,16 @@
#ifndef EIGEN_HYBRIDNONLINEARSOLVER_H
#define EIGEN_HYBRIDNONLINEARSOLVER_H
/**
* \brief Finds a zero of a system of n
* nonlinear functions in n variables by a modification of the Powell
* hybrid method ("dogleg").
*
* The user must provide a subroutine which calculates the
* functions. The Jacobian is either provided by the user, or approximated
* using a forward-difference method.
*
*/
template<typename FunctorType, typename Scalar=double>
class HybridNonLinearSolver
{

21
unsupported/Eigen/src/NumericalDiff/NumericalDiff.h
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@@ -35,32 +35,15 @@ enum NumericalDiffMode {
/**
* \brief asdf
*
* 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() using it.
* 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. Those
* are basic methods, and there exist some more elaborated way of
* computing such approximates. They are implemented using both
* proprietary and free software, and usually requires linking to an
* external library. It is very easy for you to write a functor
* using such software, and the purpose is quite orthogonal to what we
* want to achieve with Eigen.
*
* This is why we will not provide wrappers for every great numerical
* differenciation software that exist, but should rather stick with those
* basic ones, that still are useful for testing.
*
* Also, the module "Non linear optimization" needs this in order to
* provide full features compatibility with the original (c)minpack
* package.
*
* Currently only "Forward" and "Central" scheme are implemented.
*/
template<typename Functor, NumericalDiffMode mode=Forward>
class NumericalDiff : public Functor