// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2009 Gael Guennebaud // // 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_SELFCWISEBINARYOP_H #define EIGEN_SELFCWISEBINARYOP_H /** \class SelfCwiseBinaryOp * * \internal * * \brief Internal helper class for optimizing operators like +=, -= */ template struct ei_traits > : ei_traits {}; template class SelfCwiseBinaryOp //: public MatrixBase > : public MatrixType::template MakeBase< SelfCwiseBinaryOp >::Type { public: typedef typename MatrixType::template MakeBase< SelfCwiseBinaryOp >::Type Base; _EIGEN_DENSE_PUBLIC_INTERFACE(SelfCwiseBinaryOp) // EIGEN_GENERIC_PUBLIC_INTERFACE(SelfCwiseBinaryOp) typedef typename ei_packet_traits::type Packet; using Base::operator=; inline SelfCwiseBinaryOp(MatrixType& xpr, const BinaryOp& func = BinaryOp()) : m_matrix(xpr), m_functor(func) {} inline int rows() const { return m_matrix.rows(); } inline int cols() const { return m_matrix.cols(); } inline int stride() const { return m_matrix.stride(); } // note that this function is needed by assign to correctly align loads/stores // TODO make Assign use .data() inline Scalar& coeffRef(int row, int col) { return m_matrix.const_cast_derived().coeffRef(row, col); } // note that this function is needed by assign to correctly align loads/stores // TODO make Assign use .data() inline Scalar& coeffRef(int index) { return m_matrix.const_cast_derived().coeffRef(index); } template void copyCoeff(int row, int col, const DenseBase& other) { OtherDerived& _other = other.const_cast_derived(); ei_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(int index, const DenseBase& other) { OtherDerived& _other = other.const_cast_derived(); ei_internal_assert(index >= 0 && index < m_matrix.size()); Scalar& tmp = m_matrix.coeffRef(index); tmp = m_functor(tmp, _other.coeff(index)); } template void copyPacket(int row, int col, const DenseBase& other) { OtherDerived& _other = other.const_cast_derived(); ei_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(int index, const DenseBase& other) { OtherDerived& _other = other.const_cast_derived(); ei_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)) ); } protected: MatrixType& m_matrix; const BinaryOp& m_functor; private: SelfCwiseBinaryOp& operator=(const SelfCwiseBinaryOp&); }; #endif // EIGEN_SELFCWISEBINARYOP_H