Quelle AutoDiffVector.h Sprache: C

// 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

quality100%

¤ Dauer der Verarbeitung: 0.1 Sekunden (vorverarbeitet) ¤

Wurzel

Suchen

Beweissystem der NASA

Beweissystem Isabelle

NIST Cobol Testsuite

Cephes Mathematical Library

Wiener Entwicklungsmethode

Haftungshinweis

Die Informationen auf dieser Webseite wurden nach bestem Wissen sorgfältig zusammengestellt. Es wird jedoch weder Vollständigkeit, noch Richtigkeit, noch Qualität der bereit gestellten Informationen zugesichert.

Bemerkung:

Die farbliche Syntaxdarstellung ist noch experimentell.