// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2009 Thomas Capricelli <orzel@freehackers.org>
//
// Eigen is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.

#ifndef EIGEN_NUMERICALDIFF_MODULE
#define EIGEN_NUMERICALDIFF_MODULE

#include <Eigen/Core>

namespace Eigen {

/** \ingroup Unsupported_modules
  * \defgroup NumericalDiff_Module Numerical differenciation module
  *
  * \code
  * #include <unsupported/Eigen/NumericalDiff>
  * \endcode
  *
  * See http://en.wikipedia.org/wiki/Numerical_differentiation
  *
  * Warning : this should NOT be confused with automatic differentiation, which
  * is a different method and has its own module in Eigen : \ref
  * AutoDiff_Module.
  *
  * Currently only "Forward" and "Central" schemes 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.
  *
  */
//@{

#include "src/NumericalDiff/NumericalDiff.h"

//@}
}


#endif // EIGEN_NUMERICALDIFF_MODULE