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This is some awesome robot code
Dependencies: mbed-rtos mbed QEI
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tvmet/xpr/MtMProduct.h
- Committer:
- madcowswe
- Date:
- 2013-04-17
- Revision:
- 90:e4164bb8c60e
- Parent:
- 15:9c5aaeda36dc
File content as of revision 90:e4164bb8c60e:
/* * 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: MtMProduct.h,v 1.19 2007-06-23 15:59:00 opetzold Exp $ */ #ifndef TVMET_XPR_MTMPRODUCT_H #define TVMET_XPR_MTMPRODUCT_H #include <tvmet/meta/Gemtm.h> #include <tvmet/loop/Gemtm.h> namespace tvmet { /** * \class XprMtMProduct MtMProduct.h "tvmet/xpr/MtMProduct.h" * \brief Expression for product of transposed(matrix)-matrix product. * using formula * \f[ * M_1^{T}\,M_2 * \f] * \note The number of rows of rhs matrix have to be equal rows of rhs matrix, * since lhs matrix 1 is transposed. * The result is a (Cols1 x Cols2) matrix. */ template<class E1, std::size_t Rows1, std::size_t Cols1, class E2, std::size_t Cols2> class XprMtMProduct : public TvmetBase< XprMtMProduct<E1, Rows1, Cols1, E2, Cols2> > { private: XprMtMProduct(); XprMtMProduct& operator=(const XprMtMProduct&); 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, M = Rows1 * Cols1 * Cols2, N = (Rows1-1) * Cols1 * Cols2, ops_plus = M * NumericTraits<value_type>::ops_plus, ops_muls = N * NumericTraits<value_type>::ops_muls, ops = ops_plus + ops_muls, use_meta = Cols1*Cols2 < TVMET_COMPLEXITY_MM_TRIGGER ? true : false }; public: /** Constructor. */ explicit XprMtMProduct(const E1& lhs, const E2& rhs) : m_lhs(lhs), m_rhs(rhs) { } /** Copy Constructor. Not explicit! */ #if defined(TVMET_OPTIMIZE_XPR_MANUAL_CCTOR) XprMtMProduct(const XprMtMProduct& e) : m_lhs(e.m_lhs), m_rhs(e.m_rhs) { } #endif private: /** Wrapper for meta gemm. */ static inline value_type do_gemtm(dispatch<true>, const E1& lhs, const E2& rhs, std::size_t i, std::size_t j) { return meta::gemtm<Rows1, Cols1, Cols2, 0>::prod(lhs, rhs, i, j); } /** Wrapper for loop gemm. */ static inline value_type do_gemtm(dispatch<false>, const E1& lhs, const E2& rhs, std::size_t i, std::size_t j) { return loop::gemtm<Rows1, Cols1, Cols2>::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 < Cols1) && (j < Cols2), "XprMtMProduct Bounce Violation") return do_gemtm(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++) << "XprMtMProduct[" << (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" << IndentLevel(l) << "\n" << IndentLevel(--l) << ">," << std::endl; } private: const E1 m_lhs; const E2 m_rhs; }; } // namespace tvmet #endif // TVMET_XPR_MTMPRODUCT_H // Local Variables: // mode:C++ // tab-width:8 // End: