2014 Eurobot fork
Dependencies: mbed-rtos mbed QEI
tvmet/xpr/MMtProduct.h
- Committer:
- rsavitski
- Date:
- 2013-10-15
- Revision:
- 92:4a1225fbb146
- Parent:
- 15:9c5aaeda36dc
File content as of revision 92:4a1225fbb146:
/* * Tiny Vector Matrix Library * Dense Vector Matrix Libary of Tiny size using Expression Templates * * Copyright (C) 2001 - 2007 Olaf Petzold <opetzold@users.sourceforge.net> * * This library 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 2.1 of the License, or (at your option) any later version. * * This library 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 for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this library; if not, write to the Free Software * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * * $Id: MMtProduct.h,v 1.20 2007-06-23 15:58:59 opetzold Exp $ */ #ifndef TVMET_XPR_MMTPRODUCT_H #define TVMET_XPR_MMTPRODUCT_H #include <tvmet/meta/Gemmt.h> #include <tvmet/loop/Gemmt.h> namespace tvmet { /** * \class XprMMtProduct MMtProduct.h "tvmet/xpr/MMtProduct.h" * \brief Expression for matrix-matrix product. * Using formula: * \f[ * M_1\,M_2^T * \f] * \note The number of cols of rhs matrix have to be equal to cols of rhs matrix. * The result is a (Rows1 x Rows2) matrix. */ template<class E1, std::size_t Rows1, std::size_t Cols1, class E2, std::size_t Cols2> class XprMMtProduct : public TvmetBase< XprMMtProduct<E1, Rows1, Cols1, E2, Cols2> > { private: XprMMtProduct(); XprMMtProduct& operator=(const XprMMtProduct&); public: typedef typename PromoteTraits< typename E1::value_type, typename E2::value_type >::value_type value_type; public: /** Complexity counter. */ enum { ops_lhs = E1::ops, ops_rhs = E2::ops, Rows2 = Cols1, M = Rows1 * Cols1 * Rows1, N = Rows1 * (Cols1 - 1) * Rows2, ops_plus = M * NumericTraits<value_type>::ops_plus, ops_muls = N * NumericTraits<value_type>::ops_muls, ops = ops_plus + ops_muls, use_meta = Rows1*Rows2 < TVMET_COMPLEXITY_MM_TRIGGER ? true : false }; public: /** Constructor. */ explicit XprMMtProduct(const E1& lhs, const E2& rhs) : m_lhs(lhs), m_rhs(rhs) { } /** Copy Constructor. Not explicit! */ #if defined(TVMET_OPTIMIZE_XPR_MANUAL_CCTOR) XprMMtProduct(const XprMMtProduct& e) : m_lhs(e.m_lhs), m_rhs(e.m_rhs) { } #endif private: /** Wrapper for meta gemm. */ static inline value_type do_gemmt(dispatch<true>, const E1& lhs, const E2& rhs, std::size_t i, std::size_t j) { return meta::gemmt<Rows1, Cols1, Cols2, 0>::prod(lhs, rhs, i, j); } /** Wrapper for loop gemm. */ static inline value_type do_gemmt(dispatch<false>, const E1& lhs, const E2& rhs, std::size_t i, std::size_t j) { return loop::gemmt<Rows1, Cols1, Cols1>::prod(lhs, rhs, i, j); } public: /** index operator for arrays/matrices */ value_type operator()(std::size_t i, std::size_t j) const { TVMET_RT_CONDITION((i < Rows1) && (j < Rows2), "XprMMtProduct Bounce Violation") return do_gemmt(dispatch<use_meta>(), m_lhs, m_rhs, i, j); } public: // debugging Xpr parse tree void print_xpr(std::ostream& os, std::size_t l=0) const { os << IndentLevel(l++) << "XprMMtProduct[" << (use_meta ? "M" : "L") << ", O=" << ops << ", (O1=" << ops_lhs << ", O2=" << ops_rhs << ")]<" << std::endl; m_lhs.print_xpr(os, l); os << IndentLevel(l) << "R1=" << Rows1 << ", C1=" << Cols1 << ",\n"; m_rhs.print_xpr(os, l); os << IndentLevel(l) << "C2=" << Cols2 << ",\n" << "\n" << IndentLevel(--l) << ">," << std::endl; } private: const E1 m_lhs; const E2 m_rhs; }; } // namespace tvmet #endif // TVMET_XPR_MMTPRODUCT_H // Local Variables: // mode:C++ // tab-width:8 // End: