// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2009-2010 Gael Guennebaud // // 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_SELFCWISEBINARYOP_H #define EIGEN_SELFCWISEBINARYOP_H namespace Eigen { /** \class SelfCwiseBinaryOp * \ingroup Core_Module * * \internal * * \brief Internal helper class for optimizing operators like +=, -= * * This is a pseudo expression class re-implementing the copyCoeff/copyPacket * method to directly performs a +=/-= operations in an optimal way. In particular, * this allows to make sure that the input/output data are loaded only once using * aligned packet loads. * * \sa class SwapWrapper for a similar trick. */ namespace internal { template struct traits > : traits > { enum { // Note that it is still a good idea to preserve the DirectAccessBit // so that assign can correctly align the data. Flags = traits >::Flags | (Lhs::Flags&DirectAccessBit) | (Lhs::Flags&LvalueBit), OuterStrideAtCompileTime = Lhs::OuterStrideAtCompileTime, InnerStrideAtCompileTime = Lhs::InnerStrideAtCompileTime }; }; } template class SelfCwiseBinaryOp : public internal::dense_xpr_base< SelfCwiseBinaryOp >::type { public: typedef typename internal::dense_xpr_base::type Base; EIGEN_DENSE_PUBLIC_INTERFACE(SelfCwiseBinaryOp) typedef typename internal::packet_traits::type Packet; inline SelfCwiseBinaryOp(Lhs& xpr, const BinaryOp& func = BinaryOp()) : m_matrix(xpr), m_functor(func) {} inline Index rows() const { return m_matrix.rows(); } inline Index cols() const { return m_matrix.cols(); } inline Index outerStride() const { return m_matrix.outerStride(); } inline Index innerStride() const { return m_matrix.innerStride(); } inline const Scalar* data() const { return m_matrix.data(); } // note that this function is needed by assign to correctly align loads/stores // TODO make Assign use .data() inline Scalar& coeffRef(Index row, Index col) { EIGEN_STATIC_ASSERT_LVALUE(Lhs) return m_matrix.const_cast_derived().coeffRef(row, col); } inline const Scalar& coeffRef(Index row, Index col) const { return m_matrix.coeffRef(row, col); } // note that this function is needed by assign to correctly align loads/stores // TODO make Assign use .data() inline Scalar& coeffRef(Index index) { EIGEN_STATIC_ASSERT_LVALUE(Lhs) return m_matrix.const_cast_derived().coeffRef(index); } inline const Scalar& coeffRef(Index index) const { return m_matrix.const_cast_derived().coeffRef(index); } template void copyCoeff(Index row, Index col, const DenseBase& other) { OtherDerived& _other = other.const_cast_derived(); eigen_internal_assert(row >= 0 && row < rows() && col >= 0 && col < cols()); Scalar& tmp = m_matrix.coeffRef(row,col); tmp = m_functor(tmp, _other.coeff(row,col)); } template void copyCoeff(Index index, const DenseBase& other) { OtherDerived& _other = other.const_cast_derived(); eigen_internal_assert(index >= 0 && index < m_matrix.size()); Scalar& tmp = m_matrix.coeffRef(index); tmp = m_functor(tmp, _other.coeff(index)); } template void copyPacket(Index row, Index col, const DenseBase& other) { OtherDerived& _other = other.const_cast_derived(); eigen_internal_assert(row >= 0 && row < rows() && col >= 0 && col < cols()); m_matrix.template writePacket(row, col, m_functor.packetOp(m_matrix.template packet(row, col),_other.template packet(row, col)) ); } template void copyPacket(Index index, const DenseBase& other) { OtherDerived& _other = other.const_cast_derived(); eigen_internal_assert(index >= 0 && index < m_matrix.size()); m_matrix.template writePacket(index, m_functor.packetOp(m_matrix.template packet(index),_other.template packet(index)) ); } // reimplement lazyAssign to handle complex *= real // see CwiseBinaryOp ctor for details template EIGEN_STRONG_INLINE SelfCwiseBinaryOp& lazyAssign(const DenseBase& rhs) { EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Lhs,RhsDerived) EIGEN_CHECK_BINARY_COMPATIBILIY(BinaryOp,typename Lhs::Scalar,typename RhsDerived::Scalar); #ifdef EIGEN_DEBUG_ASSIGN internal::assign_traits::debug(); #endif eigen_assert(rows() == rhs.rows() && cols() == rhs.cols()); internal::assign_impl::run(*this,rhs.derived()); #ifndef EIGEN_NO_DEBUG this->checkTransposeAliasing(rhs.derived()); #endif return *this; } // overloaded to honor evaluation of special matrices // maybe another solution would be to not use SelfCwiseBinaryOp // at first... SelfCwiseBinaryOp& operator=(const Rhs& _rhs) { typename internal::nested::type rhs(_rhs); return Base::operator=(rhs); } Lhs& expression() const { return m_matrix; } const BinaryOp& functor() const { return m_functor; } protected: Lhs& m_matrix; const BinaryOp& m_functor; private: SelfCwiseBinaryOp& operator=(const SelfCwiseBinaryOp&); }; template inline Derived& DenseBase::operator*=(const Scalar& other) { typedef typename Derived::PlainObject PlainObject; SelfCwiseBinaryOp, Derived, typename PlainObject::ConstantReturnType> tmp(derived()); tmp = PlainObject::Constant(rows(),cols(),other); return derived(); } template inline Derived& DenseBase::operator/=(const Scalar& other) { typedef typename internal::conditional::IsInteger, internal::scalar_quotient_op, internal::scalar_product_op >::type BinOp; typedef typename Derived::PlainObject PlainObject; SelfCwiseBinaryOp tmp(derived()); Scalar actual_other; if(NumTraits::IsInteger) actual_other = other; else actual_other = Scalar(1)/other; tmp = PlainObject::Constant(rows(),cols(), actual_other); return derived(); } } // end namespace Eigen #endif // EIGEN_SELFCWISEBINARYOP_H