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

Committer:
madcowswe
Date:
Wed Mar 28 15:53:45 2012 +0000
Revision:
0:feb4117d16d8

        

Who changed what in which revision?

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madcowswe 0:feb4117d16d8 1 /*
madcowswe 0:feb4117d16d8 2 * Tiny Vector Matrix Library
madcowswe 0:feb4117d16d8 3 * Dense Vector Matrix Libary of Tiny size using Expression Templates
madcowswe 0:feb4117d16d8 4 *
madcowswe 0:feb4117d16d8 5 * Copyright (C) 2001 - 2007 Olaf Petzold <opetzold@users.sourceforge.net>
madcowswe 0:feb4117d16d8 6 *
madcowswe 0:feb4117d16d8 7 * This library is free software; you can redistribute it and/or
madcowswe 0:feb4117d16d8 8 * modify it under the terms of the GNU Lesser General Public
madcowswe 0:feb4117d16d8 9 * License as published by the Free Software Foundation; either
madcowswe 0:feb4117d16d8 10 * version 2.1 of the License, or (at your option) any later version.
madcowswe 0:feb4117d16d8 11 *
madcowswe 0:feb4117d16d8 12 * This library is distributed in the hope that it will be useful,
madcowswe 0:feb4117d16d8 13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
madcowswe 0:feb4117d16d8 14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
madcowswe 0:feb4117d16d8 15 * Lesser General Public License for more details.
madcowswe 0:feb4117d16d8 16 *
madcowswe 0:feb4117d16d8 17 * You should have received a copy of the GNU Lesser General Public
madcowswe 0:feb4117d16d8 18 * License along with this library; if not, write to the Free Software
madcowswe 0:feb4117d16d8 19 * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
madcowswe 0:feb4117d16d8 20 *
madcowswe 0:feb4117d16d8 21 * $Id: MMtProduct.h,v 1.20 2007-06-23 15:58:59 opetzold Exp $
madcowswe 0:feb4117d16d8 22 */
madcowswe 0:feb4117d16d8 23
madcowswe 0:feb4117d16d8 24 #ifndef TVMET_XPR_MMTPRODUCT_H
madcowswe 0:feb4117d16d8 25 #define TVMET_XPR_MMTPRODUCT_H
madcowswe 0:feb4117d16d8 26
madcowswe 0:feb4117d16d8 27 #include <tvmet/meta/Gemmt.h>
madcowswe 0:feb4117d16d8 28 #include <tvmet/loop/Gemmt.h>
madcowswe 0:feb4117d16d8 29
madcowswe 0:feb4117d16d8 30 namespace tvmet {
madcowswe 0:feb4117d16d8 31
madcowswe 0:feb4117d16d8 32
madcowswe 0:feb4117d16d8 33 /**
madcowswe 0:feb4117d16d8 34 * \class XprMMtProduct MMtProduct.h "tvmet/xpr/MMtProduct.h"
madcowswe 0:feb4117d16d8 35 * \brief Expression for matrix-matrix product.
madcowswe 0:feb4117d16d8 36 * Using formula:
madcowswe 0:feb4117d16d8 37 * \f[
madcowswe 0:feb4117d16d8 38 * M_1\,M_2^T
madcowswe 0:feb4117d16d8 39 * \f]
madcowswe 0:feb4117d16d8 40 * \note The number of cols of rhs matrix have to be equal to cols of rhs matrix.
madcowswe 0:feb4117d16d8 41 * The result is a (Rows1 x Rows2) matrix.
madcowswe 0:feb4117d16d8 42 */
madcowswe 0:feb4117d16d8 43 template<class E1, std::size_t Rows1, std::size_t Cols1,
madcowswe 0:feb4117d16d8 44 class E2, std::size_t Cols2>
madcowswe 0:feb4117d16d8 45 class XprMMtProduct
madcowswe 0:feb4117d16d8 46 : public TvmetBase< XprMMtProduct<E1, Rows1, Cols1, E2, Cols2> >
madcowswe 0:feb4117d16d8 47 {
madcowswe 0:feb4117d16d8 48 private:
madcowswe 0:feb4117d16d8 49 XprMMtProduct();
madcowswe 0:feb4117d16d8 50 XprMMtProduct& operator=(const XprMMtProduct&);
madcowswe 0:feb4117d16d8 51
madcowswe 0:feb4117d16d8 52 public:
madcowswe 0:feb4117d16d8 53 typedef typename PromoteTraits<
madcowswe 0:feb4117d16d8 54 typename E1::value_type,
madcowswe 0:feb4117d16d8 55 typename E2::value_type
madcowswe 0:feb4117d16d8 56 >::value_type value_type;
madcowswe 0:feb4117d16d8 57
madcowswe 0:feb4117d16d8 58 public:
madcowswe 0:feb4117d16d8 59 /** Complexity counter. */
madcowswe 0:feb4117d16d8 60 enum {
madcowswe 0:feb4117d16d8 61 ops_lhs = E1::ops,
madcowswe 0:feb4117d16d8 62 ops_rhs = E2::ops,
madcowswe 0:feb4117d16d8 63 Rows2 = Cols1,
madcowswe 0:feb4117d16d8 64 M = Rows1 * Cols1 * Rows1,
madcowswe 0:feb4117d16d8 65 N = Rows1 * (Cols1 - 1) * Rows2,
madcowswe 0:feb4117d16d8 66 ops_plus = M * NumericTraits<value_type>::ops_plus,
madcowswe 0:feb4117d16d8 67 ops_muls = N * NumericTraits<value_type>::ops_muls,
madcowswe 0:feb4117d16d8 68 ops = ops_plus + ops_muls,
madcowswe 0:feb4117d16d8 69 use_meta = Rows1*Rows2 < TVMET_COMPLEXITY_MM_TRIGGER ? true : false
madcowswe 0:feb4117d16d8 70 };
madcowswe 0:feb4117d16d8 71
madcowswe 0:feb4117d16d8 72 public:
madcowswe 0:feb4117d16d8 73 /** Constructor. */
madcowswe 0:feb4117d16d8 74 explicit XprMMtProduct(const E1& lhs, const E2& rhs)
madcowswe 0:feb4117d16d8 75 : m_lhs(lhs), m_rhs(rhs)
madcowswe 0:feb4117d16d8 76 { }
madcowswe 0:feb4117d16d8 77
madcowswe 0:feb4117d16d8 78 /** Copy Constructor. Not explicit! */
madcowswe 0:feb4117d16d8 79 #if defined(TVMET_OPTIMIZE_XPR_MANUAL_CCTOR)
madcowswe 0:feb4117d16d8 80 XprMMtProduct(const XprMMtProduct& e)
madcowswe 0:feb4117d16d8 81 : m_lhs(e.m_lhs), m_rhs(e.m_rhs)
madcowswe 0:feb4117d16d8 82 { }
madcowswe 0:feb4117d16d8 83 #endif
madcowswe 0:feb4117d16d8 84
madcowswe 0:feb4117d16d8 85 private:
madcowswe 0:feb4117d16d8 86 /** Wrapper for meta gemm. */
madcowswe 0:feb4117d16d8 87 static inline
madcowswe 0:feb4117d16d8 88 value_type do_gemmt(dispatch<true>, const E1& lhs, const E2& rhs, std::size_t i, std::size_t j) {
madcowswe 0:feb4117d16d8 89 return meta::gemmt<Rows1, Cols1,
madcowswe 0:feb4117d16d8 90 Cols2,
madcowswe 0:feb4117d16d8 91 0>::prod(lhs, rhs, i, j);
madcowswe 0:feb4117d16d8 92 }
madcowswe 0:feb4117d16d8 93
madcowswe 0:feb4117d16d8 94 /** Wrapper for loop gemm. */
madcowswe 0:feb4117d16d8 95 static inline
madcowswe 0:feb4117d16d8 96 value_type do_gemmt(dispatch<false>, const E1& lhs, const E2& rhs, std::size_t i, std::size_t j) {
madcowswe 0:feb4117d16d8 97 return loop::gemmt<Rows1, Cols1, Cols1>::prod(lhs, rhs, i, j);
madcowswe 0:feb4117d16d8 98 }
madcowswe 0:feb4117d16d8 99
madcowswe 0:feb4117d16d8 100 public:
madcowswe 0:feb4117d16d8 101 /** index operator for arrays/matrices */
madcowswe 0:feb4117d16d8 102 value_type operator()(std::size_t i, std::size_t j) const {
madcowswe 0:feb4117d16d8 103 TVMET_RT_CONDITION((i < Rows1) && (j < Rows2), "XprMMtProduct Bounce Violation")
madcowswe 0:feb4117d16d8 104 return do_gemmt(dispatch<use_meta>(), m_lhs, m_rhs, i, j);
madcowswe 0:feb4117d16d8 105 }
madcowswe 0:feb4117d16d8 106
madcowswe 0:feb4117d16d8 107 public: // debugging Xpr parse tree
madcowswe 0:feb4117d16d8 108 void print_xpr(std::ostream& os, std::size_t l=0) const {
madcowswe 0:feb4117d16d8 109 os << IndentLevel(l++)
madcowswe 0:feb4117d16d8 110 << "XprMMtProduct["
madcowswe 0:feb4117d16d8 111 << (use_meta ? "M" : "L") << ", O=" << ops
madcowswe 0:feb4117d16d8 112 << ", (O1=" << ops_lhs << ", O2=" << ops_rhs << ")]<"
madcowswe 0:feb4117d16d8 113 << std::endl;
madcowswe 0:feb4117d16d8 114 m_lhs.print_xpr(os, l);
madcowswe 0:feb4117d16d8 115 os << IndentLevel(l)
madcowswe 0:feb4117d16d8 116 << "R1=" << Rows1 << ", C1=" << Cols1 << ",\n";
madcowswe 0:feb4117d16d8 117 m_rhs.print_xpr(os, l);
madcowswe 0:feb4117d16d8 118 os << IndentLevel(l)
madcowswe 0:feb4117d16d8 119 << "C2=" << Cols2 << ",\n"
madcowswe 0:feb4117d16d8 120 << "\n"
madcowswe 0:feb4117d16d8 121 << IndentLevel(--l)
madcowswe 0:feb4117d16d8 122 << ">," << std::endl;
madcowswe 0:feb4117d16d8 123 }
madcowswe 0:feb4117d16d8 124
madcowswe 0:feb4117d16d8 125 private:
madcowswe 0:feb4117d16d8 126 const E1 m_lhs;
madcowswe 0:feb4117d16d8 127 const E2 m_rhs;
madcowswe 0:feb4117d16d8 128 };
madcowswe 0:feb4117d16d8 129
madcowswe 0:feb4117d16d8 130
madcowswe 0:feb4117d16d8 131 } // namespace tvmet
madcowswe 0:feb4117d16d8 132
madcowswe 0:feb4117d16d8 133 #endif // TVMET_XPR_MMTPRODUCT_H
madcowswe 0:feb4117d16d8 134
madcowswe 0:feb4117d16d8 135 // Local Variables:
madcowswe 0:feb4117d16d8 136 // mode:C++
madcowswe 0:feb4117d16d8 137 // tab-width:8
madcowswe 0:feb4117d16d8 138 // End: