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236 lines
9.3 KiB
C++
236 lines
9.3 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2009 Gael Guennebaud <g.gael@free.fr>
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//
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// Eigen is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 3 of the License, or (at your option) any later version.
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//
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// Alternatively, you can redistribute it and/or
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// modify it under the terms of the GNU General Public License as
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// published by the Free Software Foundation; either version 2 of
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// the License, or (at your option) any later version.
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//
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// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License and a copy of the GNU General Public License along with
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// Eigen. If not, see <http://www.gnu.org/licenses/>.
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#ifndef EIGEN_AUTODIFF_VECTOR_H
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#define EIGEN_AUTODIFF_VECTOR_H
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namespace Eigen {
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/* \class AutoDiffScalar
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* \brief A scalar type replacement with automatic differentation capability
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*
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* \param DerType the vector type used to store/represent the derivatives (e.g. Vector3f)
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*
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* This class represents a scalar value while tracking its respective derivatives.
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*
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* It supports the following list of global math function:
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* - std::abs, std::sqrt, std::pow, std::exp, std::log, std::sin, std::cos,
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* - ei_abs, ei_sqrt, ei_pow, ei_exp, ei_log, ei_sin, ei_cos,
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* - ei_conj, ei_real, ei_imag, ei_abs2.
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*
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* AutoDiffScalar can be used as the scalar type of an Eigen::Matrix object. However,
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* in that case, the expression template mechanism only occurs at the top Matrix level,
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* while derivatives are computed right away.
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*
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*/
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template<typename ValueType, typename JacobianType>
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class AutoDiffVector
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{
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public:
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//typedef typename ei_traits<ValueType>::Scalar Scalar;
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typedef typename ei_traits<ValueType>::Scalar BaseScalar;
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typedef AutoDiffScalar<Matrix<BaseScalar,JacobianType::RowsAtCompileTime,1> > ActiveScalar;
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typedef ActiveScalar Scalar;
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typedef AutoDiffScalar<typename JacobianType::ColXpr> CoeffType;
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typedef typename JacobianType::Index Index;
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inline AutoDiffVector() {}
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inline AutoDiffVector(const ValueType& values)
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: m_values(values)
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{
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m_jacobian.setZero();
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}
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CoeffType operator[] (Index i) { return CoeffType(m_values[i], m_jacobian.col(i)); }
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const CoeffType operator[] (Index i) const { return CoeffType(m_values[i], m_jacobian.col(i)); }
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CoeffType operator() (Index i) { return CoeffType(m_values[i], m_jacobian.col(i)); }
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const CoeffType operator() (Index i) const { return CoeffType(m_values[i], m_jacobian.col(i)); }
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CoeffType coeffRef(Index i) { return CoeffType(m_values[i], m_jacobian.col(i)); }
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const CoeffType coeffRef(Index i) const { return CoeffType(m_values[i], m_jacobian.col(i)); }
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Index size() const { return m_values.size(); }
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// FIXME here we could return an expression of the sum
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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()); }
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inline AutoDiffVector(const ValueType& values, const JacobianType& jac)
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: m_values(values), m_jacobian(jac)
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{}
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template<typename OtherValueType, typename OtherJacobianType>
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inline AutoDiffVector(const AutoDiffVector<OtherValueType, OtherJacobianType>& other)
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: m_values(other.values()), m_jacobian(other.jacobian())
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{}
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inline AutoDiffVector(const AutoDiffVector& other)
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: m_values(other.values()), m_jacobian(other.jacobian())
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{}
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template<typename OtherValueType, typename OtherJacobianType>
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inline AutoDiffVector& operator=(const AutoDiffVector<OtherValueType, OtherJacobianType>& other)
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{
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m_values = other.values();
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m_jacobian = other.jacobian();
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return *this;
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}
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inline AutoDiffVector& operator=(const AutoDiffVector& other)
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{
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m_values = other.values();
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m_jacobian = other.jacobian();
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return *this;
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}
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inline const ValueType& values() const { return m_values; }
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inline ValueType& values() { return m_values; }
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inline const JacobianType& jacobian() const { return m_jacobian; }
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inline JacobianType& jacobian() { return m_jacobian; }
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template<typename OtherValueType,typename OtherJacobianType>
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inline const AutoDiffVector<
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typename MakeCwiseBinaryOp<ei_scalar_sum_op<BaseScalar>,ValueType,OtherValueType>::Type,
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typename MakeCwiseBinaryOp<ei_scalar_sum_op<BaseScalar>,JacobianType,OtherJacobianType>::Type >
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operator+(const AutoDiffVector<OtherValueType,OtherJacobianType>& other) const
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{
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return AutoDiffVector<
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typename MakeCwiseBinaryOp<ei_scalar_sum_op<BaseScalar>,ValueType,OtherValueType>::Type,
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typename MakeCwiseBinaryOp<ei_scalar_sum_op<BaseScalar>,JacobianType,OtherJacobianType>::Type >(
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m_values + other.values(),
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m_jacobian + other.jacobian());
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}
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template<typename OtherValueType, typename OtherJacobianType>
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inline AutoDiffVector&
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operator+=(const AutoDiffVector<OtherValueType,OtherJacobianType>& other)
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{
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m_values += other.values();
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m_jacobian += other.jacobian();
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return *this;
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}
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template<typename OtherValueType,typename OtherJacobianType>
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inline const AutoDiffVector<
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typename MakeCwiseBinaryOp<ei_scalar_difference_op<Scalar>,ValueType,OtherValueType>::Type,
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typename MakeCwiseBinaryOp<ei_scalar_difference_op<Scalar>,JacobianType,OtherJacobianType>::Type >
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operator-(const AutoDiffVector<OtherValueType,OtherJacobianType>& other) const
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{
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return AutoDiffVector<
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typename MakeCwiseBinaryOp<ei_scalar_difference_op<Scalar>,ValueType,OtherValueType>::Type,
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typename MakeCwiseBinaryOp<ei_scalar_difference_op<Scalar>,JacobianType,OtherJacobianType>::Type >(
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m_values - other.values(),
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m_jacobian - other.jacobian());
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}
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template<typename OtherValueType, typename OtherJacobianType>
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inline AutoDiffVector&
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operator-=(const AutoDiffVector<OtherValueType,OtherJacobianType>& other)
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{
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m_values -= other.values();
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m_jacobian -= other.jacobian();
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return *this;
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}
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inline const AutoDiffVector<
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typename MakeCwiseUnaryOp<ei_scalar_opposite_op<Scalar>, ValueType>::Type,
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typename MakeCwiseUnaryOp<ei_scalar_opposite_op<Scalar>, JacobianType>::Type >
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operator-() const
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{
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return AutoDiffVector<
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typename MakeCwiseUnaryOp<ei_scalar_opposite_op<Scalar>, ValueType>::Type,
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typename MakeCwiseUnaryOp<ei_scalar_opposite_op<Scalar>, JacobianType>::Type >(
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-m_values,
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-m_jacobian);
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}
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inline const AutoDiffVector<
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typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, ValueType>::Type,
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typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, JacobianType>::Type>
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operator*(const BaseScalar& other) const
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{
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return AutoDiffVector<
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typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, ValueType>::Type,
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typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, JacobianType>::Type >(
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m_values * other,
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m_jacobian * other);
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}
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friend inline const AutoDiffVector<
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typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, ValueType>::Type,
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typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, JacobianType>::Type >
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operator*(const Scalar& other, const AutoDiffVector& v)
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{
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return AutoDiffVector<
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typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, ValueType>::Type,
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typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, JacobianType>::Type >(
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v.values() * other,
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v.jacobian() * other);
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}
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// template<typename OtherValueType,typename OtherJacobianType>
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// inline const AutoDiffVector<
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// CwiseBinaryOp<ei_scalar_multiple_op<Scalar>, ValueType, OtherValueType>
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// CwiseBinaryOp<ei_scalar_sum_op<Scalar>,
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// CwiseUnaryOp<ei_scalar_multiple_op<Scalar>, JacobianType>,
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// CwiseUnaryOp<ei_scalar_multiple_op<Scalar>, OtherJacobianType> > >
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// operator*(const AutoDiffVector<OtherValueType,OtherJacobianType>& other) const
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// {
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// return AutoDiffVector<
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// CwiseBinaryOp<ei_scalar_multiple_op<Scalar>, ValueType, OtherValueType>
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// CwiseBinaryOp<ei_scalar_sum_op<Scalar>,
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// CwiseUnaryOp<ei_scalar_multiple_op<Scalar>, JacobianType>,
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// CwiseUnaryOp<ei_scalar_multiple_op<Scalar>, OtherJacobianType> > >(
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// m_values.cwise() * other.values(),
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// (m_jacobian * other.values()) + (m_values * other.jacobian()));
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// }
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inline AutoDiffVector& operator*=(const Scalar& other)
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{
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m_values *= other;
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m_jacobian *= other;
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return *this;
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}
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template<typename OtherValueType,typename OtherJacobianType>
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inline AutoDiffVector& operator*=(const AutoDiffVector<OtherValueType,OtherJacobianType>& other)
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{
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*this = *this * other;
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return *this;
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}
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protected:
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ValueType m_values;
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JacobianType m_jacobian;
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};
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}
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#endif // EIGEN_AUTODIFF_VECTOR_H
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