This is the Tiny Vector Matrix Expression Templates library found at http://tvmet.sourceforge.net. It is the fastest and most compact matrix lib out there (for < 10x10 matricies). I have done some minor tweaks to make it compile for mbed. For examples and hints on how to use, see: http://tvmet.sourceforge.net/usage.html
Dependents: Eurobot_2012_Secondary
Gemtv.h
00001 /* 00002 * Tiny Vector Matrix Library 00003 * Dense Vector Matrix Libary of Tiny size using Expression Templates 00004 * 00005 * Copyright (C) 2001 - 2007 Olaf Petzold <opetzold@users.sourceforge.net> 00006 * 00007 * This library is free software; you can redistribute it and/or 00008 * modify it under the terms of the GNU Lesser General Public 00009 * License as published by the Free Software Foundation; either 00010 * version 2.1 of the License, or (at your option) any later version. 00011 * 00012 * This library is distributed in the hope that it will be useful, 00013 * but WITHOUT ANY WARRANTY; without even the implied warranty of 00014 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU 00015 * Lesser General Public License for more details. 00016 * 00017 * You should have received a copy of the GNU Lesser General Public 00018 * License along with this library; if not, write to the Free Software 00019 * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA 00020 * 00021 * $Id: Gemtv.h,v 1.7 2007-06-23 15:58:59 opetzold Exp $ 00022 */ 00023 00024 #ifndef TVMET_LOOP_GEMTV_H 00025 #define TVMET_LOOP_GEMTV_H 00026 00027 namespace tvmet { 00028 00029 namespace loop { 00030 00031 00032 /** 00033 * \class gemtv Gemtv.h "tvmet/loop/Gemtv.h" 00034 * \brief class for transposed(matrix)-vector product using loop unrolling. 00035 * using formula 00036 * \f[ 00037 * M^T\,v 00038 * \f] 00039 * \par Example: 00040 * \code 00041 * template<class T, std::size_t Rows, std::size_t Cols> 00042 * inline 00043 * void 00044 * prod(const Matrix<T, Rows, Cols>& lhs, const Vector<T, Rows>& rhs, 00045 * Vector<T, Cols>& dest) 00046 * { 00047 * for (std::size_t i = 0; i != Cols; ++i) { 00048 * dest(i) = tvmet::loop::gemtv<Rows, Cols>().prod(lhs, rhs, i); 00049 * } 00050 * } 00051 * \endcode 00052 */ 00053 template<std::size_t Rows, std::size_t Cols> 00054 class gemtv 00055 { 00056 gemtv(const gemtv&); 00057 gemtv& operator=(const gemtv&); 00058 00059 private: 00060 enum { 00061 count = Rows, 00062 N = (count+7)/8 00063 }; 00064 00065 public: 00066 gemtv() { } 00067 00068 public: 00069 template<class E1, class E2> 00070 static inline 00071 typename PromoteTraits< 00072 typename E1::value_type, 00073 typename E2::value_type 00074 >::value_type 00075 prod(const E1& lhs, const E2& rhs, std::size_t i) { 00076 typename PromoteTraits< 00077 typename E1::value_type, 00078 typename E2::value_type 00079 >::value_type sum(0); 00080 std::size_t j(0); 00081 std::size_t n(N); 00082 00083 // Duff's device 00084 switch(count % 8) { 00085 case 0: do { sum += lhs(j, i) * rhs(j); ++j; 00086 case 7: sum += lhs(j, i) * rhs(j); ++j; 00087 case 6: sum += lhs(j, i) * rhs(j); ++j; 00088 case 5: sum += lhs(j, i) * rhs(j); ++j; 00089 case 4: sum += lhs(j, i) * rhs(j); ++j; 00090 case 3: sum += lhs(j, i) * rhs(j); ++j; 00091 case 2: sum += lhs(j, i) * rhs(j); ++j; 00092 case 1: sum += lhs(j, i) * rhs(j); ++j; 00093 } while(--n != 0); 00094 } 00095 00096 return sum; 00097 } 00098 }; 00099 00100 00101 } // namespace loop 00102 00103 } // namespace tvmet 00104 00105 #endif /* TVMET_LOOP_GEMTV_H */ 00106 00107 // Local Variables: 00108 // mode:C++ 00109 // tab-width:8 00110 // End:
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