// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2008-2009 Gael Guennebaud // Copyright (C) 2006-2008 Benoit Jacob // // Eigen is free software; you can redistribute it and/or // modify it under the terms of the GNU Lesser General Public // License as published by the Free Software Foundation; either // version 3 of the License, or (at your option) any later version. // // Alternatively, you can redistribute it and/or // modify it under the terms of the GNU General Public License as // published by the Free Software Foundation; either version 2 of // the License, or (at your option) any later version. // // Eigen is distributed in the hope that it will be useful, but WITHOUT ANY // WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS // FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the // GNU General Public License for more details. // // You should have received a copy of the GNU Lesser General Public // License and a copy of the GNU General Public License along with // Eigen. If not, see . #ifndef EIGEN_CWISE_BINARY_OP_H #define EIGEN_CWISE_BINARY_OP_H /** \class CwiseBinaryOp * * \brief Generic expression of a coefficient-wise operator between two matrices or vectors * * \param BinaryOp template functor implementing the operator * \param Lhs the type of the left-hand side * \param Rhs the type of the right-hand side * * This class represents an expression of a generic binary operator of two matrices or vectors. * It is the return type of the operator+, operator-, and the Cwise methods, and most * of the time this is the only way it is used. * * However, if you want to write a function returning such an expression, you * will need to use this class. * * \sa MatrixBase::binaryExpr(const MatrixBase &,const CustomBinaryOp &) const, class CwiseUnaryOp, class CwiseNullaryOp */ template struct ei_traits > : ei_traits { // even though we require Lhs and Rhs to have the same scalar type (see CwiseBinaryOp constructor), // we still want to handle the case when the result type is different. typedef typename ei_result_of< BinaryOp( typename Lhs::Scalar, typename Rhs::Scalar ) >::type Scalar; typedef typename ei_promote_storage_type::StorageType, typename ei_traits::StorageType>::ret StorageType; typedef typename Lhs::Nested LhsNested; typedef typename Rhs::Nested RhsNested; typedef typename ei_unref::type _LhsNested; typedef typename ei_unref::type _RhsNested; enum { LhsCoeffReadCost = _LhsNested::CoeffReadCost, RhsCoeffReadCost = _RhsNested::CoeffReadCost, LhsFlags = _LhsNested::Flags, RhsFlags = _RhsNested::Flags, StorageOrdersAgree = (int(Lhs::Flags)&RowMajorBit)==(int(Rhs::Flags)&RowMajorBit), Flags = (int(LhsFlags) | int(RhsFlags)) & ( HereditaryBits | (int(LhsFlags) & int(RhsFlags) & ( AlignedBit | (StorageOrdersAgree ? LinearAccessBit : 0) | (ei_functor_traits::PacketAccess && StorageOrdersAgree ? PacketAccessBit : 0) ) ) ), CoeffReadCost = LhsCoeffReadCost + RhsCoeffReadCost + ei_functor_traits::Cost }; }; template class CwiseBinaryOpImpl; template class CwiseBinaryOp : ei_no_assignment_operator, public CwiseBinaryOpImpl< BinaryOp, Lhs, Rhs, typename ei_promote_storage_type::StorageType, typename ei_traits::StorageType>::ret> { public: typedef typename CwiseBinaryOpImpl< BinaryOp, Lhs, Rhs, typename ei_promote_storage_type::StorageType, typename ei_traits::StorageType>::ret>::Base Base; EIGEN_GENERIC_PUBLIC_INTERFACE_NEW(CwiseBinaryOp) typedef typename ei_nested::type LhsNested; typedef typename ei_nested::type RhsNested; typedef typename ei_unref::type _LhsNested; typedef typename ei_unref::type _RhsNested; EIGEN_STRONG_INLINE CwiseBinaryOp(const Lhs& lhs, const Rhs& rhs, const BinaryOp& func = BinaryOp()) : m_lhs(lhs), m_rhs(rhs), m_functor(func) { // we require Lhs and Rhs to have the same scalar type. Currently there is no example of a binary functor // that would take two operands of different types. If there were such an example, then this check should be // moved to the BinaryOp functors, on a per-case basis. This would however require a change in the BinaryOp functors, as // currently they take only one typename Scalar template parameter. // It is tempting to always allow mixing different types but remember that this is often impossible in the vectorized paths. // So allowing mixing different types gives very unexpected errors when enabling vectorization, when the user tries to // add together a float matrix and a double matrix. EIGEN_STATIC_ASSERT((ei_functor_allows_mixing_real_and_complex::ret ? int(ei_is_same_type::ret) : int(ei_is_same_type::ret)), YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) // require the sizes to match EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Lhs, Rhs) ei_assert(lhs.rows() == rhs.rows() && lhs.cols() == rhs.cols()); } EIGEN_STRONG_INLINE int rows() const { return m_lhs.rows(); } EIGEN_STRONG_INLINE int cols() const { return m_lhs.cols(); } /** \returns the left hand side nested expression */ const _LhsNested& lhs() const { return m_lhs; } /** \returns the right hand side nested expression */ const _RhsNested& rhs() const { return m_rhs; } /** \returns the functor representing the binary operation */ const BinaryOp& functor() const { return m_functor; } protected: const LhsNested m_lhs; const RhsNested m_rhs; const BinaryOp m_functor; }; template class CwiseBinaryOpImpl : public Lhs::template MakeBase< CwiseBinaryOp >::Type { typedef CwiseBinaryOp Derived; public: typedef typename Lhs::template MakeBase< CwiseBinaryOp >::Type Base; EIGEN_DENSE_PUBLIC_INTERFACE( Derived ) EIGEN_STRONG_INLINE const Scalar coeff(int row, int col) const { return derived().functor()(derived().lhs().coeff(row, col), derived().rhs().coeff(row, col)); } template EIGEN_STRONG_INLINE PacketScalar packet(int row, int col) const { return derived().functor().packetOp(derived().lhs().template packet(row, col), derived().rhs().template packet(row, col)); } EIGEN_STRONG_INLINE const Scalar coeff(int index) const { return derived().functor()(derived().lhs().coeff(index), derived().rhs().coeff(index)); } template EIGEN_STRONG_INLINE PacketScalar packet(int index) const { return derived().functor().packetOp(derived().lhs().template packet(index), derived().rhs().template packet(index)); } }; /** replaces \c *this by \c *this - \a other. * * \returns a reference to \c *this */ template template EIGEN_STRONG_INLINE Derived & MatrixBase::operator-=(const MatrixBase &other) { SelfCwiseBinaryOp, Derived> tmp(derived()); tmp = other; return derived(); } /** replaces \c *this by \c *this + \a other. * * \returns a reference to \c *this */ template template EIGEN_STRONG_INLINE Derived & MatrixBase::operator+=(const MatrixBase& other) { SelfCwiseBinaryOp, Derived> tmp(derived()); tmp = other.derived(); return derived(); } #endif // EIGEN_CWISE_BINARY_OP_H