// This file is part of Eigen, a lightweight C++ template library // for linear algebra. Eigen itself is part of the KDE project. // // Copyright (C) 2006-2008 Benoit Jacob // Copyright (C) 2008 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_PRODUCT_H #define EIGEN_PRODUCT_H template struct ei_product_unroller { static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res) { ei_product_unroller::run(row, col, lhs, rhs, res); res += lhs.coeff(row, Index) * rhs.coeff(Index, col); } }; template struct ei_product_unroller<0, Size, Lhs, Rhs> { static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res) { res = lhs.coeff(row, 0) * rhs.coeff(0, col); } }; template struct ei_product_unroller { static void run(int, int, const Lhs&, const Rhs&, typename Lhs::Scalar&) {} }; // prevent buggy user code from causing an infinite recursion template struct ei_product_unroller { static void run(int, int, const Lhs&, const Rhs&, typename Lhs::Scalar&) {} }; /** \class Product * * \brief Expression of the product of two matrices * * \param Lhs the type of the left-hand side * \param Rhs the type of the right-hand side * \param EvalMode internal use only * * This class represents an expression of the product of two matrices. * It is the return type of the operator* between matrices, and most of the time * this is the only way it is used. * * \sa class Sum, class Difference */ template struct ei_product_eval_mode { enum{ value = Lhs::MaxRowsAtCompileTime >= 8 && Rhs::MaxColsAtCompileTime >= 8 ? CacheOptimal : UnrolledDotProduct }; }; template struct ei_traits > { typedef typename Lhs::Scalar Scalar; typedef typename ei_xpr_copy::type LhsXprCopy; typedef typename ei_xpr_copy::type RhsXprCopy; typedef typename ei_unref::type ActualLhs; typedef typename ei_unref::type ActualRhs; enum { LhsCoeffReadCost = ActualLhs::CoeffReadCost, RhsCoeffReadCost = ActualRhs::CoeffReadCost, LhsFlags = ActualLhs::Flags, RhsFlags = ActualRhs::Flags, RowsAtCompileTime = Lhs::RowsAtCompileTime, ColsAtCompileTime = Rhs::ColsAtCompileTime, MaxRowsAtCompileTime = Lhs::MaxRowsAtCompileTime, MaxColsAtCompileTime = Rhs::MaxColsAtCompileTime, Flags = ( (RowsAtCompileTime == Dynamic || ColsAtCompileTime == Dynamic) ? (unsigned int)(LhsFlags | RhsFlags) : (unsigned int)(LhsFlags | RhsFlags) & ~LargeBit ) | EvalBeforeAssigningBit | (ei_product_eval_mode::value == (int)CacheOptimal ? EvalBeforeNestingBit : 0), CoeffReadCost = Lhs::ColsAtCompileTime == Dynamic ? Dynamic : Lhs::ColsAtCompileTime * (NumTraits::MulCost + LhsCoeffReadCost + RhsCoeffReadCost) + (Lhs::ColsAtCompileTime - 1) * NumTraits::AddCost }; }; template class Product : ei_no_assignment_operator, public MatrixBase > { public: EIGEN_GENERIC_PUBLIC_INTERFACE(Product) typedef typename ei_traits::LhsXprCopy LhsXprCopy; typedef typename ei_traits::RhsXprCopy RhsXprCopy; Product(const Lhs& lhs, const Rhs& rhs) : m_lhs(lhs), m_rhs(rhs) { ei_assert(lhs.cols() == rhs.rows()); } /** \internal */ template void _cacheOptimalEval(DestDerived& res) const; private: int _rows() const { return m_lhs.rows(); } int _cols() const { return m_rhs.cols(); } const Scalar _coeff(int row, int col) const { Scalar res; const bool unroll = CoeffReadCost <= EIGEN_UNROLLING_LIMIT; if(unroll) { ei_product_unroller::type, typename ei_unref::type> ::run(row, col, m_lhs, m_rhs, res); } else { res = m_lhs.coeff(row, 0) * m_rhs.coeff(0, col); for(int i = 1; i < m_lhs.cols(); i++) res += m_lhs.coeff(row, i) * m_rhs.coeff(i, col); } return res; } protected: const LhsXprCopy m_lhs; const RhsXprCopy m_rhs; }; /** \returns the matrix product of \c *this and \a other. * * \note This function causes an immediate evaluation. If you want to perform a matrix product * without immediate evaluation, call .lazy() on one of the matrices before taking the product. * * \sa lazy(), operator*=(const MatrixBase&) */ template template const Product MatrixBase::operator*(const MatrixBase &other) const { return Product(derived(), other.derived()); } /** replaces \c *this by \c *this * \a other. * * \returns a reference to \c *this */ template template Derived & MatrixBase::operator*=(const MatrixBase &other) { return *this = *this * other; } template template Derived& MatrixBase::lazyAssign(const Product& product) { product._cacheOptimalEval(*this); return derived(); } template template void Product::_cacheOptimalEval(DestDerived& res) const { res.setZero(); const int cols4 = m_lhs.cols()&0xfffffffC; for (int k=0; k