some more documentation

1 files changed, 2 insertions, 19 deletions

diff --git a/unsupported/Eigen/src/NumericalDiff/NumericalDiff.h b/unsupported/Eigen/src/NumericalDiff/NumericalDiff.h
index 4a8480230..98872e0bc 100644
--- a/unsupported/Eigen/src/NumericalDiff/NumericalDiff.h
+++ b/unsupported/Eigen/src/NumericalDiff/NumericalDiff.h
@@ -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