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* Add short documentation for Array class * Put all classes explicitly in Core module (where applicable) * Section on Modules in Quick Reference Guide * Put Page 7 after Page 6 in Contents :)
71 lines
2.5 KiB
Plaintext
71 lines
2.5 KiB
Plaintext
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2009 Thomas Capricelli <orzel@freehackers.org>
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//
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// Eigen is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 3 of the License, or (at your option) any later version.
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//
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// Alternatively, you can redistribute it and/or
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// modify it under the terms of the GNU General Public License as
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// published by the Free Software Foundation; either version 2 of
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// the License, or (at your option) any later version.
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//
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// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License and a copy of the GNU General Public License along with
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// Eigen. If not, see <http://www.gnu.org/licenses/>.
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#ifndef EIGEN_NUMERICALDIFF_MODULE
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#define EIGEN_NUMERICALDIFF_MODULE
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#include <Eigen/Core>
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namespace Eigen {
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/** \ingroup Unsupported_modules
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* \defgroup NumericalDiff_Module Numerical differentiation module
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*
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* \code
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* #include <unsupported/Eigen/NumericalDiff>
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* \endcode
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*
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* See http://en.wikipedia.org/wiki/Numerical_differentiation
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*
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* Warning : this should NOT be confused with automatic differentiation, which
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* is a different method and has its own module in Eigen : \ref
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* AutoDiff_Module.
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*
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* Currently only "Forward" and "Central" schemes are implemented. Those
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* are basic methods, and there exist some more elaborated way of
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* computing such approximates. They are implemented using both
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* proprietary and free software, and usually requires linking to an
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* external library. It is very easy for you to write a functor
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* using such software, and the purpose is quite orthogonal to what we
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* want to achieve with Eigen.
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*
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* This is why we will not provide wrappers for every great numerical
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* differentiation software that exist, but should rather stick with those
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* basic ones, that still are useful for testing.
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*
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* Also, the \ref NonLinearOptimization_Module needs this in order to
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* provide full features compatibility with the original (c)minpack
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* package.
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*
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*/
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//@{
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#include "src/NumericalDiff/NumericalDiff.h"
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//@}
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}
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#endif // EIGEN_NUMERICALDIFF_MODULE
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