| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. |
| // |
| // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr> |
| // |
| // This Source Code Form is subject to the terms of the Mozilla |
| // Public License v. 2.0. If a copy of the MPL was not distributed |
| // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. |
| |
| #ifndef EIGEN_AUTODIFF_JACOBIAN_H |
| #define EIGEN_AUTODIFF_JACOBIAN_H |
| |
| // IWYU pragma: private |
| #include "./InternalHeaderCheck.h" |
| |
| namespace Eigen { |
| |
| template <typename Functor> |
| class AutoDiffJacobian : public Functor { |
| public: |
| AutoDiffJacobian() : Functor() {} |
| AutoDiffJacobian(const Functor& f) : Functor(f) {} |
| |
| // forward constructors |
| template <typename... T> |
| AutoDiffJacobian(const T&... Values) : Functor(Values...) {} |
| |
| typedef typename Functor::InputType InputType; |
| typedef typename Functor::ValueType ValueType; |
| typedef typename ValueType::Scalar Scalar; |
| |
| enum { InputsAtCompileTime = InputType::RowsAtCompileTime, ValuesAtCompileTime = ValueType::RowsAtCompileTime }; |
| |
| typedef Matrix<Scalar, ValuesAtCompileTime, InputsAtCompileTime> JacobianType; |
| 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; |
| |
| // Some compilers don't accept variadic parameters after a default parameter, |
| // i.e., we can't just write _jac=0 but we need to overload operator(): |
| EIGEN_STRONG_INLINE void operator()(const InputType& x, ValueType* v) const { this->operator()(x, v, 0); } |
| template <typename... ParamsType> |
| void operator()(const InputType& x, ValueType* v, JacobianType* _jac, const ParamsType&... Params) const { |
| eigen_assert(v != 0); |
| |
| if (!_jac) { |
| Functor::operator()(x, v, Params...); |
| 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(x.rows()); |
| |
| for (Index i = 0; i < jac.cols(); i++) ax[i].derivatives() = DerivativeType::Unit(x.rows(), i); |
| |
| Functor::operator()(ax, &av, Params...); |
| |
| for (Index i = 0; i < jac.rows(); i++) { |
| (*v)[i] = av[i].value(); |
| jac.row(i) = av[i].derivatives(); |
| } |
| } |
| }; |
| |
| } // namespace Eigen |
| |
| #endif // EIGEN_AUTODIFF_JACOBIAN_H |