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// 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, internal::pow, internal::exp, internal::log, internal::sin, internal::cos,
* - internal::conj, internal::real, internal::imag, internal::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
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