| // This file is part of Eigen, a lightweight C++ template library | 
 | // for linear algebra. | 
 | // | 
 | // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr> | 
 | // | 
 | // 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_AUTODIFF_JACOBIAN_H | 
 | #define EIGEN_AUTODIFF_JACOBIAN_H | 
 |  | 
 | namespace Eigen | 
 | { | 
 |  | 
 | template<typename Functor> class AutoDiffJacobian : public Functor | 
 | { | 
 | public: | 
 |   AutoDiffJacobian() : Functor() {} | 
 |   AutoDiffJacobian(const Functor& f) : Functor(f) {} | 
 |  | 
 |   // forward constructors | 
 |   template<typename T0> | 
 |   AutoDiffJacobian(const T0& a0) : Functor(a0) {} | 
 |   template<typename T0, typename T1> | 
 |   AutoDiffJacobian(const T0& a0, const T1& a1) : Functor(a0, a1) {} | 
 |   template<typename T0, typename T1, typename T2> | 
 |   AutoDiffJacobian(const T0& a0, const T1& a1, const T1& a2) : Functor(a0, a1, a2) {} | 
 |  | 
 |   enum { | 
 |     InputsAtCompileTime = Functor::InputsAtCompileTime, | 
 |     ValuesAtCompileTime = Functor::ValuesAtCompileTime | 
 |   }; | 
 |  | 
 |   typedef typename Functor::InputType InputType; | 
 |   typedef typename Functor::ValueType ValueType; | 
 |   typedef typename Functor::JacobianType JacobianType; | 
 |   typedef typename JacobianType::Scalar Scalar; | 
 |   typedef typename JacobianType::Index Index; | 
 |  | 
 |   typedef Matrix<Scalar,InputsAtCompileTime,1> DerivativeType; | 
 |   typedef AutoDiffScalar<DerivativeType> ActiveScalar; | 
 |  | 
 |  | 
 |   typedef Matrix<ActiveScalar, InputsAtCompileTime, 1> ActiveInput; | 
 |   typedef Matrix<ActiveScalar, ValuesAtCompileTime, 1> ActiveValue; | 
 |  | 
 |   void operator() (const InputType& x, ValueType* v, JacobianType* _jac=0) const | 
 |   { | 
 |     eigen_assert(v!=0); | 
 |     if (!_jac) | 
 |     { | 
 |       Functor::operator()(x, v); | 
 |       return; | 
 |     } | 
 |  | 
 |     JacobianType& jac = *_jac; | 
 |  | 
 |     ActiveInput ax = x.template cast<ActiveScalar>(); | 
 |     ActiveValue av(jac.rows()); | 
 |  | 
 |     if(InputsAtCompileTime==Dynamic) | 
 |       for (Index j=0; j<jac.rows(); j++) | 
 |         av[j].derivatives().resize(this->inputs()); | 
 |  | 
 |     for (Index i=0; i<jac.cols(); i++) | 
 |       ax[i].derivatives() = DerivativeType::Unit(this->inputs(),i); | 
 |  | 
 |     Functor::operator()(ax, &av); | 
 |  | 
 |     for (Index i=0; i<jac.rows(); i++) | 
 |     { | 
 |       (*v)[i] = av[i].value(); | 
 |       jac.row(i) = av[i].derivatives(); | 
 |     } | 
 |   } | 
 | protected: | 
 |  | 
 | }; | 
 |  | 
 | } | 
 |  | 
 | #endif // EIGEN_AUTODIFF_JACOBIAN_H |