AutoDiffVector.h
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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_VECTOR_H
00011 #define EIGEN_AUTODIFF_VECTOR_H
00012 
00013 namespace Eigen {
00014 
00015 /* \class AutoDiffScalar
00016   * \brief A scalar type replacement with automatic differentation capability
00017   *
00018   * \param DerType the vector type used to store/represent the derivatives (e.g. Vector3f)
00019   *
00020   * This class represents a scalar value while tracking its respective derivatives.
00021   *
00022   * It supports the following list of global math function:
00023   *  - std::abs, std::sqrt, std::pow, std::exp, std::log, std::sin, std::cos,
00024   *  - internal::abs, internal::sqrt, internal::pow, internal::exp, internal::log, internal::sin, internal::cos,
00025   *  - internal::conj, internal::real, internal::imag, internal::abs2.
00026   *
00027   * AutoDiffScalar can be used as the scalar type of an Eigen::Matrix object. However,
00028   * in that case, the expression template mechanism only occurs at the top Matrix level,
00029   * while derivatives are computed right away.
00030   *
00031   */
00032 template<typename ValueType, typename JacobianType>
00033 class AutoDiffVector
00034 {
00035   public:
00036     //typedef typename internal::traits<ValueType>::Scalar Scalar;
00037     typedef typename internal::traits<ValueType>::Scalar BaseScalar;
00038     typedef AutoDiffScalar<Matrix<BaseScalar,JacobianType::RowsAtCompileTime,1> > ActiveScalar;
00039     typedef ActiveScalar Scalar;
00040     typedef AutoDiffScalar<typename JacobianType::ColXpr> CoeffType;
00041     typedef typename JacobianType::Index Index;
00042 
00043     inline AutoDiffVector() {}
00044 
00045     inline AutoDiffVector(const ValueType& values)
00046       : m_values(values)
00047     {
00048       m_jacobian.setZero();
00049     }
00050 
00051 
00052     CoeffType operator[] (Index i) { return CoeffType(m_values[i], m_jacobian.col(i)); }
00053     const CoeffType operator[] (Index i) const { return CoeffType(m_values[i], m_jacobian.col(i)); }
00054 
00055     CoeffType operator() (Index i) { return CoeffType(m_values[i], m_jacobian.col(i)); }
00056     const CoeffType operator() (Index i) const { return CoeffType(m_values[i], m_jacobian.col(i)); }
00057 
00058     CoeffType coeffRef(Index i) { return CoeffType(m_values[i], m_jacobian.col(i)); }
00059     const CoeffType coeffRef(Index i) const { return CoeffType(m_values[i], m_jacobian.col(i)); }
00060 
00061     Index size() const { return m_values.size(); }
00062 
00063     // FIXME here we could return an expression of the sum
00064     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()); }
00065 
00066 
00067     inline AutoDiffVector(const ValueType& values, const JacobianType& jac)
00068       : m_values(values), m_jacobian(jac)
00069     {}
00070 
00071     template<typename OtherValueType, typename OtherJacobianType>
00072     inline AutoDiffVector(const AutoDiffVector<OtherValueType, OtherJacobianType>& other)
00073       : m_values(other.values()), m_jacobian(other.jacobian())
00074     {}
00075 
00076     inline AutoDiffVector(const AutoDiffVector& other)
00077       : m_values(other.values()), m_jacobian(other.jacobian())
00078     {}
00079 
00080     template<typename OtherValueType, typename OtherJacobianType>
00081     inline AutoDiffVector& operator=(const AutoDiffVector<OtherValueType, OtherJacobianType>& other)
00082     {
00083       m_values = other.values();
00084       m_jacobian = other.jacobian();
00085       return *this;
00086     }
00087 
00088     inline AutoDiffVector& operator=(const AutoDiffVector& other)
00089     {
00090       m_values = other.values();
00091       m_jacobian = other.jacobian();
00092       return *this;
00093     }
00094 
00095     inline const ValueType& values() const { return m_values; }
00096     inline ValueType& values() { return m_values; }
00097 
00098     inline const JacobianType& jacobian() const { return m_jacobian; }
00099     inline JacobianType& jacobian() { return m_jacobian; }
00100 
00101     template<typename OtherValueType,typename OtherJacobianType>
00102     inline const AutoDiffVector<
00103       typename MakeCwiseBinaryOp<internal::scalar_sum_op<BaseScalar>,ValueType,OtherValueType>::Type,
00104       typename MakeCwiseBinaryOp<internal::scalar_sum_op<BaseScalar>,JacobianType,OtherJacobianType>::Type >
00105     operator+(const AutoDiffVector<OtherValueType,OtherJacobianType>& other) const
00106     {
00107       return AutoDiffVector<
00108       typename MakeCwiseBinaryOp<internal::scalar_sum_op<BaseScalar>,ValueType,OtherValueType>::Type,
00109       typename MakeCwiseBinaryOp<internal::scalar_sum_op<BaseScalar>,JacobianType,OtherJacobianType>::Type >(
00110         m_values + other.values(),
00111         m_jacobian + other.jacobian());
00112     }
00113 
00114     template<typename OtherValueType, typename OtherJacobianType>
00115     inline AutoDiffVector&
00116     operator+=(const AutoDiffVector<OtherValueType,OtherJacobianType>& other)
00117     {
00118       m_values += other.values();
00119       m_jacobian += other.jacobian();
00120       return *this;
00121     }
00122 
00123     template<typename OtherValueType,typename OtherJacobianType>
00124     inline const AutoDiffVector<
00125       typename MakeCwiseBinaryOp<internal::scalar_difference_op<Scalar>,ValueType,OtherValueType>::Type,
00126       typename MakeCwiseBinaryOp<internal::scalar_difference_op<Scalar>,JacobianType,OtherJacobianType>::Type >
00127     operator-(const AutoDiffVector<OtherValueType,OtherJacobianType>& other) const
00128     {
00129       return AutoDiffVector<
00130         typename MakeCwiseBinaryOp<internal::scalar_difference_op<Scalar>,ValueType,OtherValueType>::Type,
00131         typename MakeCwiseBinaryOp<internal::scalar_difference_op<Scalar>,JacobianType,OtherJacobianType>::Type >(
00132           m_values - other.values(),
00133           m_jacobian - other.jacobian());
00134     }
00135 
00136     template<typename OtherValueType, typename OtherJacobianType>
00137     inline AutoDiffVector&
00138     operator-=(const AutoDiffVector<OtherValueType,OtherJacobianType>& other)
00139     {
00140       m_values -= other.values();
00141       m_jacobian -= other.jacobian();
00142       return *this;
00143     }
00144 
00145     inline const AutoDiffVector<
00146       typename MakeCwiseUnaryOp<internal::scalar_opposite_op<Scalar>, ValueType>::Type,
00147       typename MakeCwiseUnaryOp<internal::scalar_opposite_op<Scalar>, JacobianType>::Type >
00148     operator-() const
00149     {
00150       return AutoDiffVector<
00151         typename MakeCwiseUnaryOp<internal::scalar_opposite_op<Scalar>, ValueType>::Type,
00152         typename MakeCwiseUnaryOp<internal::scalar_opposite_op<Scalar>, JacobianType>::Type >(
00153           -m_values,
00154           -m_jacobian);
00155     }
00156 
00157     inline const AutoDiffVector<
00158       typename MakeCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, ValueType>::Type,
00159       typename MakeCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, JacobianType>::Type>
00160     operator*(const BaseScalar& other) const
00161     {
00162       return AutoDiffVector<
00163         typename MakeCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, ValueType>::Type,
00164         typename MakeCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, JacobianType>::Type >(
00165           m_values * other,
00166           m_jacobian * other);
00167     }
00168 
00169     friend inline const AutoDiffVector<
00170       typename MakeCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, ValueType>::Type,
00171       typename MakeCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, JacobianType>::Type >
00172     operator*(const Scalar& other, const AutoDiffVector& v)
00173     {
00174       return AutoDiffVector<
00175         typename MakeCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, ValueType>::Type,
00176         typename MakeCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, JacobianType>::Type >(
00177           v.values() * other,
00178           v.jacobian() * other);
00179     }
00180 
00181 //     template<typename OtherValueType,typename OtherJacobianType>
00182 //     inline const AutoDiffVector<
00183 //       CwiseBinaryOp<internal::scalar_multiple_op<Scalar>, ValueType, OtherValueType>
00184 //       CwiseBinaryOp<internal::scalar_sum_op<Scalar>,
00185 //         CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, JacobianType>,
00186 //         CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, OtherJacobianType> > >
00187 //     operator*(const AutoDiffVector<OtherValueType,OtherJacobianType>& other) const
00188 //     {
00189 //       return AutoDiffVector<
00190 //         CwiseBinaryOp<internal::scalar_multiple_op<Scalar>, ValueType, OtherValueType>
00191 //         CwiseBinaryOp<internal::scalar_sum_op<Scalar>,
00192 //           CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, JacobianType>,
00193 //           CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, OtherJacobianType> > >(
00194 //             m_values.cwise() * other.values(),
00195 //             (m_jacobian * other.values()) + (m_values * other.jacobian()));
00196 //     }
00197 
00198     inline AutoDiffVector& operator*=(const Scalar& other)
00199     {
00200       m_values *= other;
00201       m_jacobian *= other;
00202       return *this;
00203     }
00204 
00205     template<typename OtherValueType,typename OtherJacobianType>
00206     inline AutoDiffVector& operator*=(const AutoDiffVector<OtherValueType,OtherJacobianType>& other)
00207     {
00208       *this = *this * other;
00209       return *this;
00210     }
00211 
00212   protected:
00213     ValueType m_values;
00214     JacobianType m_jacobian;
00215 
00216 };
00217 
00218 }
00219 
00220 #endif // EIGEN_AUTODIFF_VECTOR_H


win_eigen
Author(s): Daniel Stonier
autogenerated on Wed Sep 16 2015 07:10:18