// 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_VECTOR_H #define EIGEN_AUTODIFF_VECTOR_H namespace Eigen { /* \class AutoDiffScalar * \brief A scalar type replacement with automatic differentation capability * * \param DerType the vector type used to store/represent the derivatives (e.g. Vector3f) * * This class represents a scalar value while tracking its respective derivatives. * * It supports the following list of global math function: * - std::abs, std::sqrt, std::pow, std::exp, std::log, std::sin, std::cos, * - internal::abs, internal::sqrt, numext::pow, internal::exp, internal::log, internal::sin, internal::cos, * - internal::conj, internal::real, internal::imag, numext::abs2. * * AutoDiffScalar can be used as the scalar type of an Eigen::Matrix object. However, * in that case, the expression template mechanism only occurs at the top Matrix level, * while derivatives are computed right away. * */ template<typename ValueType, typename JacobianType> class AutoDiffVector { public: //typedef typename internal::traits<ValueType>::Scalar Scalar; typedef typename internal::traits<ValueType>::Scalar BaseScalar; typedef AutoDiffScalar<Matrix<BaseScalar,JacobianType::RowsAtCompileTime,1> > ActiveScalar; typedef ActiveScalar Scalar; typedef AutoDiffScalar<typename JacobianType::ColXpr> CoeffType; typedef typename JacobianType::Index Index; inline AutoDiffVector() {} inline AutoDiffVector(const ValueType& values) : m_values(values) { m_jacobian.setZero(); } CoeffType operator[] (Index i) { return CoeffType(m_values[i], m_jacobian.col(i)); } const CoeffType operator[] (Index i) const { return CoeffType(m_values[i], m_jacobian.col(i)); } CoeffType operator() (Index i) { return CoeffType(m_values[i], m_jacobian.col(i)); } const CoeffType operator() (Index i) const { return CoeffType(m_values[i], m_jacobian.col(i)); } CoeffType coeffRef(Index i) { return CoeffType(m_values[i], m_jacobian.col(i)); } const CoeffType coeffRef(Index i) const { return CoeffType(m_values[i], m_jacobian.col(i)); } Index size() const { return m_values.size(); } // FIXME here we could return an expression of the sum Scalar sum() const { /*std::cerr << "sum \n\n";*/ /*std::cerr << m_jacobian.rowwise().sum() << "\n\n";*/ return Scalar(m_values.sum(), m_jacobian.rowwise().sum()); } inline AutoDiffVector(const ValueType& values, const JacobianType& jac) : m_values(values), m_jacobian(jac) {} template<typename OtherValueType, typename OtherJacobianType> inline AutoDiffVector(const AutoDiffVector<OtherValueType, OtherJacobianType>& other) : m_values(other.values()), m_jacobian(other.jacobian()) {} inline AutoDiffVector(const AutoDiffVector& other) : m_values(other.values()), m_jacobian(other.jacobian()) {} template<typename OtherValueType, typename OtherJacobianType> inline AutoDiffVector& operator=(const AutoDiffVector<OtherValueType, OtherJacobianType>& other) { m_values = other.values(); m_jacobian = other.jacobian(); return *this; } inline AutoDiffVector& operator=(const AutoDiffVector& other) { m_values = other.values(); m_jacobian = other.jacobian(); return *this; } inline const ValueType& values() const { return m_values; } inline ValueType& values() { return m_values; } inline const JacobianType& jacobian() const { return m_jacobian; } inline JacobianType& jacobian() { return m_jacobian; } template<typename OtherValueType,typename OtherJacobianType> inline const AutoDiffVector< typename MakeCwiseBinaryOp<internal::scalar_sum_op<BaseScalar>,ValueType,OtherValueType>::Type, typename MakeCwiseBinaryOp<internal::scalar_sum_op<BaseScalar>,JacobianType,OtherJacobianType>::Type > operator+(const AutoDiffVector<OtherValueType,OtherJacobianType>& other) const { return AutoDiffVector< typename MakeCwiseBinaryOp<internal::scalar_sum_op<BaseScalar>,ValueType,OtherValueType>::Type, typename MakeCwiseBinaryOp<internal::scalar_sum_op<BaseScalar>,JacobianType,OtherJacobianType>::Type >( m_values + other.values(), m_jacobian + other.jacobian()); } template<typename OtherValueType, typename OtherJacobianType> inline AutoDiffVector& operator+=(const AutoDiffVector<OtherValueType,OtherJacobianType>& other) { m_values += other.values(); m_jacobian += other.jacobian(); return *this; } template<typename OtherValueType,typename OtherJacobianType> inline const AutoDiffVector< typename MakeCwiseBinaryOp<internal::scalar_difference_op<Scalar>,ValueType,OtherValueType>::Type, typename MakeCwiseBinaryOp<internal::scalar_difference_op<Scalar>,JacobianType,OtherJacobianType>::Type > operator-(const AutoDiffVector<OtherValueType,OtherJacobianType>& other) const { return AutoDiffVector< typename MakeCwiseBinaryOp<internal::scalar_difference_op<Scalar>,ValueType,OtherValueType>::Type, typename MakeCwiseBinaryOp<internal::scalar_difference_op<Scalar>,JacobianType,OtherJacobianType>::Type >( m_values - other.values(), m_jacobian - other.jacobian()); } template<typename OtherValueType, typename OtherJacobianType> inline AutoDiffVector& operator-=(const AutoDiffVector<OtherValueType,OtherJacobianType>& other) { m_values -= other.values(); m_jacobian -= other.jacobian(); return *this; } inline const AutoDiffVector< typename MakeCwiseUnaryOp<internal::scalar_opposite_op<Scalar>, ValueType>::Type, typename MakeCwiseUnaryOp<internal::scalar_opposite_op<Scalar>, JacobianType>::Type > operator-() const { return AutoDiffVector< typename MakeCwiseUnaryOp<internal::scalar_opposite_op<Scalar>, ValueType>::Type, typename MakeCwiseUnaryOp<internal::scalar_opposite_op<Scalar>, JacobianType>::Type >( -m_values, -m_jacobian); } inline const AutoDiffVector< typename MakeCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, ValueType>::Type, typename MakeCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, JacobianType>::Type> operator*(const BaseScalar& other) const { return AutoDiffVector< typename MakeCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, ValueType>::Type, typename MakeCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, JacobianType>::Type >( m_values * other, m_jacobian * other); } friend inline const AutoDiffVector< typename MakeCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, ValueType>::Type, typename MakeCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, JacobianType>::Type > operator*(const Scalar& other, const AutoDiffVector& v) { return AutoDiffVector< typename MakeCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, ValueType>::Type, typename MakeCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, JacobianType>::Type >( v.values() * other, v.jacobian() * other); } // template<typename OtherValueType,typename OtherJacobianType> // inline const AutoDiffVector< // CwiseBinaryOp<internal::scalar_multiple_op<Scalar>, ValueType, OtherValueType> // CwiseBinaryOp<internal::scalar_sum_op<Scalar>, // CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, JacobianType>, // CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, OtherJacobianType> > > // operator*(const AutoDiffVector<OtherValueType,OtherJacobianType>& other) const // { // return AutoDiffVector< // CwiseBinaryOp<internal::scalar_multiple_op<Scalar>, ValueType, OtherValueType> // CwiseBinaryOp<internal::scalar_sum_op<Scalar>, // CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, JacobianType>, // CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, OtherJacobianType> > >( // m_values.cwise() * other.values(), // (m_jacobian * other.values()) + (m_values * other.jacobian())); // } inline AutoDiffVector& operator*=(const Scalar& other) { m_values *= other; m_jacobian *= other; return *this; } template<typename OtherValueType,typename OtherJacobianType> inline AutoDiffVector& operator*=(const AutoDiffVector<OtherValueType,OtherJacobianType>& other) { *this = *this * other; return *this; } protected: ValueType m_values; JacobianType m_jacobian; }; } #endif // EIGEN_AUTODIFF_VECTOR_H