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Eigen-unsupported
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00001 // This file is part of Eigen, a lightweight C++ template library 00002 // for linear algebra. 00003 // 00004 // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr> 00005 // 00006 // This Source Code Form is subject to the terms of the Mozilla 00007 // Public License v. 2.0. If a copy of the MPL was not distributed 00008 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. 00009 00010 #ifndef EIGEN_AUTODIFF_JACOBIAN_H 00011 #define EIGEN_AUTODIFF_JACOBIAN_H 00012 00013 namespace Eigen 00014 { 00015 00016 template<typename Functor> class AutoDiffJacobian : public Functor 00017 { 00018 public: 00019 AutoDiffJacobian() : Functor() {} 00020 AutoDiffJacobian(const Functor& f) : Functor(f) {} 00021 00022 // forward constructors 00023 template<typename T0> 00024 AutoDiffJacobian(const T0& a0) : Functor(a0) {} 00025 template<typename T0, typename T1> 00026 AutoDiffJacobian(const T0& a0, const T1& a1) : Functor(a0, a1) {} 00027 template<typename T0, typename T1, typename T2> 00028 AutoDiffJacobian(const T0& a0, const T1& a1, const T2& a2) : Functor(a0, a1, a2) {} 00029 00030 enum { 00031 InputsAtCompileTime = Functor::InputsAtCompileTime, 00032 ValuesAtCompileTime = Functor::ValuesAtCompileTime 00033 }; 00034 00035 typedef typename Functor::InputType InputType; 00036 typedef typename Functor::ValueType ValueType; 00037 typedef typename Functor::JacobianType JacobianType; 00038 typedef typename JacobianType::Scalar Scalar; 00039 typedef typename JacobianType::Index Index; 00040 00041 typedef Matrix<Scalar,InputsAtCompileTime,1> DerivativeType; 00042 typedef AutoDiffScalar<DerivativeType> ActiveScalar; 00043 00044 00045 typedef Matrix<ActiveScalar, InputsAtCompileTime, 1> ActiveInput; 00046 typedef Matrix<ActiveScalar, ValuesAtCompileTime, 1> ActiveValue; 00047 00048 void operator() (const InputType& x, ValueType* v, JacobianType* _jac=0) const 00049 { 00050 eigen_assert(v!=0); 00051 if (!_jac) 00052 { 00053 Functor::operator()(x, v); 00054 return; 00055 } 00056 00057 JacobianType& jac = *_jac; 00058 00059 ActiveInput ax = x.template cast<ActiveScalar>(); 00060 ActiveValue av(jac.rows()); 00061 00062 if(InputsAtCompileTime==Dynamic) 00063 for (Index j=0; j<jac.rows(); j++) 00064 av[j].derivatives().resize(this->inputs()); 00065 00066 for (Index i=0; i<jac.cols(); i++) 00067 ax[i].derivatives() = DerivativeType::Unit(this->inputs(),i); 00068 00069 Functor::operator()(ax, &av); 00070 00071 for (Index i=0; i<jac.rows(); i++) 00072 { 00073 (*v)[i] = av[i].value(); 00074 jac.row(i) = av[i].derivatives(); 00075 } 00076 } 00077 protected: 00078 00079 }; 00080 00081 } 00082 00083 #endif // EIGEN_AUTODIFF_JACOBIAN_H