1 | // This file is part of Eigen, a lightweight C++ template library
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2 | // for linear algebra.
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3 | //
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4 | // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
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5 | // Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
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6 | //
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7 | // This Source Code Form is subject to the terms of the Mozilla
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8 | // Public License v. 2.0. If a copy of the MPL was not distributed
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9 | // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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10 |
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11 | #ifndef EIGEN_GENERAL_PRODUCT_H
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12 | #define EIGEN_GENERAL_PRODUCT_H
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13 |
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14 | namespace Eigen {
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15 |
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16 | /** \class GeneralProduct
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17 | * \ingroup Core_Module
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18 | *
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19 | * \brief Expression of the product of two general matrices or vectors
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20 | *
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21 | * \param LhsNested the type used to store the left-hand side
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22 | * \param RhsNested the type used to store the right-hand side
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23 | * \param ProductMode the type of the product
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24 | *
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25 | * This class represents an expression of the product of two general matrices.
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26 | * We call a general matrix, a dense matrix with full storage. For instance,
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27 | * This excludes triangular, selfadjoint, and sparse matrices.
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28 | * It is the return type of the operator* between general matrices. Its template
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29 | * arguments are determined automatically by ProductReturnType. Therefore,
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30 | * GeneralProduct should never be used direclty. To determine the result type of a
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31 | * function which involves a matrix product, use ProductReturnType::Type.
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32 | *
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33 | * \sa ProductReturnType, MatrixBase::operator*(const MatrixBase<OtherDerived>&)
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34 | */
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35 | template<typename Lhs, typename Rhs, int ProductType = internal::product_type<Lhs,Rhs>::value>
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36 | class GeneralProduct;
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37 |
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38 | enum {
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39 | Large = 2,
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40 | Small = 3
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41 | };
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42 |
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43 | namespace internal {
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44 |
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45 | template<int Rows, int Cols, int Depth> struct product_type_selector;
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46 |
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47 | template<int Size, int MaxSize> struct product_size_category
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48 | {
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49 | enum { is_large = MaxSize == Dynamic ||
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50 | Size >= EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD,
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51 | value = is_large ? Large
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52 | : Size == 1 ? 1
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53 | : Small
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54 | };
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55 | };
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56 |
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57 | template<typename Lhs, typename Rhs> struct product_type
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58 | {
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59 | typedef typename remove_all<Lhs>::type _Lhs;
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60 | typedef typename remove_all<Rhs>::type _Rhs;
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61 | enum {
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62 | MaxRows = _Lhs::MaxRowsAtCompileTime,
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63 | Rows = _Lhs::RowsAtCompileTime,
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64 | MaxCols = _Rhs::MaxColsAtCompileTime,
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65 | Cols = _Rhs::ColsAtCompileTime,
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66 | MaxDepth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::MaxColsAtCompileTime,
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67 | _Rhs::MaxRowsAtCompileTime),
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68 | Depth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::ColsAtCompileTime,
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69 | _Rhs::RowsAtCompileTime),
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70 | LargeThreshold = EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
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71 | };
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72 |
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73 | // the splitting into different lines of code here, introducing the _select enums and the typedef below,
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74 | // is to work around an internal compiler error with gcc 4.1 and 4.2.
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75 | private:
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76 | enum {
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77 | rows_select = product_size_category<Rows,MaxRows>::value,
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78 | cols_select = product_size_category<Cols,MaxCols>::value,
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79 | depth_select = product_size_category<Depth,MaxDepth>::value
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80 | };
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81 | typedef product_type_selector<rows_select, cols_select, depth_select> selector;
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82 |
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83 | public:
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84 | enum {
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85 | value = selector::ret
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86 | };
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87 | #ifdef EIGEN_DEBUG_PRODUCT
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88 | static void debug()
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89 | {
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90 | EIGEN_DEBUG_VAR(Rows);
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91 | EIGEN_DEBUG_VAR(Cols);
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92 | EIGEN_DEBUG_VAR(Depth);
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93 | EIGEN_DEBUG_VAR(rows_select);
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94 | EIGEN_DEBUG_VAR(cols_select);
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95 | EIGEN_DEBUG_VAR(depth_select);
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96 | EIGEN_DEBUG_VAR(value);
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97 | }
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98 | #endif
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99 | };
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100 |
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101 |
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102 | /* The following allows to select the kind of product at compile time
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103 | * based on the three dimensions of the product.
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104 | * This is a compile time mapping from {1,Small,Large}^3 -> {product types} */
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105 | // FIXME I'm not sure the current mapping is the ideal one.
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106 | template<int M, int N> struct product_type_selector<M,N,1> { enum { ret = OuterProduct }; };
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107 | template<int Depth> struct product_type_selector<1, 1, Depth> { enum { ret = InnerProduct }; };
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108 | template<> struct product_type_selector<1, 1, 1> { enum { ret = InnerProduct }; };
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109 | template<> struct product_type_selector<Small,1, Small> { enum { ret = CoeffBasedProductMode }; };
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110 | template<> struct product_type_selector<1, Small,Small> { enum { ret = CoeffBasedProductMode }; };
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111 | template<> struct product_type_selector<Small,Small,Small> { enum { ret = CoeffBasedProductMode }; };
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112 | template<> struct product_type_selector<Small, Small, 1> { enum { ret = LazyCoeffBasedProductMode }; };
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113 | template<> struct product_type_selector<Small, Large, 1> { enum { ret = LazyCoeffBasedProductMode }; };
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114 | template<> struct product_type_selector<Large, Small, 1> { enum { ret = LazyCoeffBasedProductMode }; };
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115 | template<> struct product_type_selector<1, Large,Small> { enum { ret = CoeffBasedProductMode }; };
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116 | template<> struct product_type_selector<1, Large,Large> { enum { ret = GemvProduct }; };
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117 | template<> struct product_type_selector<1, Small,Large> { enum { ret = CoeffBasedProductMode }; };
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118 | template<> struct product_type_selector<Large,1, Small> { enum { ret = CoeffBasedProductMode }; };
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119 | template<> struct product_type_selector<Large,1, Large> { enum { ret = GemvProduct }; };
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120 | template<> struct product_type_selector<Small,1, Large> { enum { ret = CoeffBasedProductMode }; };
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121 | template<> struct product_type_selector<Small,Small,Large> { enum { ret = GemmProduct }; };
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122 | template<> struct product_type_selector<Large,Small,Large> { enum { ret = GemmProduct }; };
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123 | template<> struct product_type_selector<Small,Large,Large> { enum { ret = GemmProduct }; };
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124 | template<> struct product_type_selector<Large,Large,Large> { enum { ret = GemmProduct }; };
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125 | template<> struct product_type_selector<Large,Small,Small> { enum { ret = GemmProduct }; };
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126 | template<> struct product_type_selector<Small,Large,Small> { enum { ret = GemmProduct }; };
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127 | template<> struct product_type_selector<Large,Large,Small> { enum { ret = GemmProduct }; };
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128 |
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129 | } // end namespace internal
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130 |
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131 | /** \class ProductReturnType
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132 | * \ingroup Core_Module
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133 | *
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134 | * \brief Helper class to get the correct and optimized returned type of operator*
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135 | *
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136 | * \param Lhs the type of the left-hand side
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137 | * \param Rhs the type of the right-hand side
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138 | * \param ProductMode the type of the product (determined automatically by internal::product_mode)
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139 | *
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140 | * This class defines the typename Type representing the optimized product expression
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141 | * between two matrix expressions. In practice, using ProductReturnType<Lhs,Rhs>::Type
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142 | * is the recommended way to define the result type of a function returning an expression
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143 | * which involve a matrix product. The class Product should never be
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144 | * used directly.
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145 | *
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146 | * \sa class Product, MatrixBase::operator*(const MatrixBase<OtherDerived>&)
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147 | */
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148 | template<typename Lhs, typename Rhs, int ProductType>
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149 | struct ProductReturnType
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150 | {
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151 | // TODO use the nested type to reduce instanciations ????
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152 | // typedef typename internal::nested<Lhs,Rhs::ColsAtCompileTime>::type LhsNested;
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153 | // typedef typename internal::nested<Rhs,Lhs::RowsAtCompileTime>::type RhsNested;
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154 |
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155 | typedef GeneralProduct<Lhs/*Nested*/, Rhs/*Nested*/, ProductType> Type;
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156 | };
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157 |
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158 | template<typename Lhs, typename Rhs>
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159 | struct ProductReturnType<Lhs,Rhs,CoeffBasedProductMode>
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160 | {
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161 | typedef typename internal::nested<Lhs, Rhs::ColsAtCompileTime, typename internal::plain_matrix_type<Lhs>::type >::type LhsNested;
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162 | typedef typename internal::nested<Rhs, Lhs::RowsAtCompileTime, typename internal::plain_matrix_type<Rhs>::type >::type RhsNested;
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163 | typedef CoeffBasedProduct<LhsNested, RhsNested, EvalBeforeAssigningBit | EvalBeforeNestingBit> Type;
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164 | };
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165 |
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166 | template<typename Lhs, typename Rhs>
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167 | struct ProductReturnType<Lhs,Rhs,LazyCoeffBasedProductMode>
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168 | {
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169 | typedef typename internal::nested<Lhs, Rhs::ColsAtCompileTime, typename internal::plain_matrix_type<Lhs>::type >::type LhsNested;
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170 | typedef typename internal::nested<Rhs, Lhs::RowsAtCompileTime, typename internal::plain_matrix_type<Rhs>::type >::type RhsNested;
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171 | typedef CoeffBasedProduct<LhsNested, RhsNested, NestByRefBit> Type;
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172 | };
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173 |
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174 | // this is a workaround for sun CC
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175 | template<typename Lhs, typename Rhs>
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176 | struct LazyProductReturnType : public ProductReturnType<Lhs,Rhs,LazyCoeffBasedProductMode>
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177 | {};
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178 |
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179 | /***********************************************************************
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180 | * Implementation of Inner Vector Vector Product
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181 | ***********************************************************************/
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182 |
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183 | // FIXME : maybe the "inner product" could return a Scalar
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184 | // instead of a 1x1 matrix ??
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185 | // Pro: more natural for the user
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186 | // Cons: this could be a problem if in a meta unrolled algorithm a matrix-matrix
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187 | // product ends up to a row-vector times col-vector product... To tackle this use
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188 | // case, we could have a specialization for Block<MatrixType,1,1> with: operator=(Scalar x);
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189 |
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190 | namespace internal {
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191 |
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192 | template<typename Lhs, typename Rhs>
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193 | struct traits<GeneralProduct<Lhs,Rhs,InnerProduct> >
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194 | : traits<Matrix<typename scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1> >
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195 | {};
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196 |
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197 | }
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198 |
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199 | template<typename Lhs, typename Rhs>
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200 | class GeneralProduct<Lhs, Rhs, InnerProduct>
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201 | : internal::no_assignment_operator,
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202 | public Matrix<typename internal::scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1>
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203 | {
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204 | typedef Matrix<typename internal::scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1> Base;
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205 | public:
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206 | GeneralProduct(const Lhs& lhs, const Rhs& rhs)
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207 | {
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208 | Base::coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum();
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209 | }
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210 |
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211 | /** Convertion to scalar */
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212 | operator const typename Base::Scalar() const {
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213 | return Base::coeff(0,0);
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214 | }
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215 | };
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216 |
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217 | /***********************************************************************
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218 | * Implementation of Outer Vector Vector Product
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219 | ***********************************************************************/
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220 |
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221 | namespace internal {
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222 |
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223 | // Column major
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224 | template<typename ProductType, typename Dest, typename Func>
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225 | EIGEN_DONT_INLINE void outer_product_selector_run(const ProductType& prod, Dest& dest, const Func& func, const false_type&)
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226 | {
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227 | typedef typename Dest::Index Index;
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228 | // FIXME make sure lhs is sequentially stored
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229 | // FIXME not very good if rhs is real and lhs complex while alpha is real too
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230 | const Index cols = dest.cols();
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231 | for (Index j=0; j<cols; ++j)
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232 | func(dest.col(j), prod.rhs().coeff(0,j) * prod.lhs());
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233 | }
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234 |
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235 | // Row major
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236 | template<typename ProductType, typename Dest, typename Func>
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237 | EIGEN_DONT_INLINE void outer_product_selector_run(const ProductType& prod, Dest& dest, const Func& func, const true_type&) {
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238 | typedef typename Dest::Index Index;
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239 | // FIXME make sure rhs is sequentially stored
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240 | // FIXME not very good if lhs is real and rhs complex while alpha is real too
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241 | const Index rows = dest.rows();
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242 | for (Index i=0; i<rows; ++i)
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243 | func(dest.row(i), prod.lhs().coeff(i,0) * prod.rhs());
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244 | }
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245 |
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246 | template<typename Lhs, typename Rhs>
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247 | struct traits<GeneralProduct<Lhs,Rhs,OuterProduct> >
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248 | : traits<ProductBase<GeneralProduct<Lhs,Rhs,OuterProduct>, Lhs, Rhs> >
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249 | {};
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250 |
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251 | }
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252 |
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253 | template<typename Lhs, typename Rhs>
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254 | class GeneralProduct<Lhs, Rhs, OuterProduct>
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255 | : public ProductBase<GeneralProduct<Lhs,Rhs,OuterProduct>, Lhs, Rhs>
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256 | {
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257 | template<typename T> struct is_row_major : internal::conditional<(int(T::Flags)&RowMajorBit), internal::true_type, internal::false_type>::type {};
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258 |
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259 | public:
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260 | EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct)
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261 |
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262 | GeneralProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
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263 | {
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264 | }
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265 |
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266 | struct set { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() = src; } };
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267 | struct add { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() += src; } };
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268 | struct sub { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() -= src; } };
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269 | struct adds {
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270 | Scalar m_scale;
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271 | adds(const Scalar& s) : m_scale(s) {}
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272 | template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const {
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273 | dst.const_cast_derived() += m_scale * src;
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274 | }
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275 | };
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276 |
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277 | template<typename Dest>
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278 | inline void evalTo(Dest& dest) const {
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279 | internal::outer_product_selector_run(*this, dest, set(), is_row_major<Dest>());
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280 | }
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281 |
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282 | template<typename Dest>
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283 | inline void addTo(Dest& dest) const {
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284 | internal::outer_product_selector_run(*this, dest, add(), is_row_major<Dest>());
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285 | }
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286 |
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287 | template<typename Dest>
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288 | inline void subTo(Dest& dest) const {
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289 | internal::outer_product_selector_run(*this, dest, sub(), is_row_major<Dest>());
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290 | }
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291 |
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292 | template<typename Dest> void scaleAndAddTo(Dest& dest, const Scalar& alpha) const
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293 | {
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294 | internal::outer_product_selector_run(*this, dest, adds(alpha), is_row_major<Dest>());
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295 | }
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296 | };
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297 |
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298 | /***********************************************************************
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299 | * Implementation of General Matrix Vector Product
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300 | ***********************************************************************/
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301 |
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302 | /* According to the shape/flags of the matrix we have to distinghish 3 different cases:
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303 | * 1 - the matrix is col-major, BLAS compatible and M is large => call fast BLAS-like colmajor routine
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304 | * 2 - the matrix is row-major, BLAS compatible and N is large => call fast BLAS-like rowmajor routine
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305 | * 3 - all other cases are handled using a simple loop along the outer-storage direction.
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306 | * Therefore we need a lower level meta selector.
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307 | * Furthermore, if the matrix is the rhs, then the product has to be transposed.
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308 | */
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309 | namespace internal {
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310 |
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311 | template<typename Lhs, typename Rhs>
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312 | struct traits<GeneralProduct<Lhs,Rhs,GemvProduct> >
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313 | : traits<ProductBase<GeneralProduct<Lhs,Rhs,GemvProduct>, Lhs, Rhs> >
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314 | {};
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315 |
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316 | template<int Side, int StorageOrder, bool BlasCompatible>
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317 | struct gemv_selector;
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318 |
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319 | } // end namespace internal
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320 |
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321 | template<typename Lhs, typename Rhs>
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322 | class GeneralProduct<Lhs, Rhs, GemvProduct>
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323 | : public ProductBase<GeneralProduct<Lhs,Rhs,GemvProduct>, Lhs, Rhs>
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324 | {
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325 | public:
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326 | EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct)
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327 |
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328 | typedef typename Lhs::Scalar LhsScalar;
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329 | typedef typename Rhs::Scalar RhsScalar;
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330 |
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331 | GeneralProduct(const Lhs& a_lhs, const Rhs& a_rhs) : Base(a_lhs,a_rhs)
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332 | {
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333 | // EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::Scalar, typename Rhs::Scalar>::value),
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334 | // YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
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335 | }
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336 |
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337 | enum { Side = Lhs::IsVectorAtCompileTime ? OnTheLeft : OnTheRight };
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338 | typedef typename internal::conditional<int(Side)==OnTheRight,_LhsNested,_RhsNested>::type MatrixType;
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339 |
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340 | template<typename Dest> void scaleAndAddTo(Dest& dst, const Scalar& alpha) const
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341 | {
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342 | eigen_assert(m_lhs.rows() == dst.rows() && m_rhs.cols() == dst.cols());
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343 | internal::gemv_selector<Side,(int(MatrixType::Flags)&RowMajorBit) ? RowMajor : ColMajor,
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344 | bool(internal::blas_traits<MatrixType>::HasUsableDirectAccess)>::run(*this, dst, alpha);
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345 | }
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346 | };
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347 |
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348 | namespace internal {
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349 |
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350 | // The vector is on the left => transposition
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351 | template<int StorageOrder, bool BlasCompatible>
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352 | struct gemv_selector<OnTheLeft,StorageOrder,BlasCompatible>
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353 | {
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354 | template<typename ProductType, typename Dest>
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355 | static void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha)
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356 | {
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357 | Transpose<Dest> destT(dest);
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358 | enum { OtherStorageOrder = StorageOrder == RowMajor ? ColMajor : RowMajor };
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359 | gemv_selector<OnTheRight,OtherStorageOrder,BlasCompatible>
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360 | ::run(GeneralProduct<Transpose<const typename ProductType::_RhsNested>,Transpose<const typename ProductType::_LhsNested>, GemvProduct>
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361 | (prod.rhs().transpose(), prod.lhs().transpose()), destT, alpha);
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362 | }
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363 | };
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364 |
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365 | template<typename Scalar,int Size,int MaxSize,bool Cond> struct gemv_static_vector_if;
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366 |
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367 | template<typename Scalar,int Size,int MaxSize>
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368 | struct gemv_static_vector_if<Scalar,Size,MaxSize,false>
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369 | {
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370 | EIGEN_STRONG_INLINE Scalar* data() { eigen_internal_assert(false && "should never be called"); return 0; }
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371 | };
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372 |
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373 | template<typename Scalar,int Size>
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374 | struct gemv_static_vector_if<Scalar,Size,Dynamic,true>
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375 | {
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376 | EIGEN_STRONG_INLINE Scalar* data() { return 0; }
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377 | };
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378 |
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379 | template<typename Scalar,int Size,int MaxSize>
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380 | struct gemv_static_vector_if<Scalar,Size,MaxSize,true>
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381 | {
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382 | #if EIGEN_ALIGN_STATICALLY
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383 | internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize),0> m_data;
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384 | EIGEN_STRONG_INLINE Scalar* data() { return m_data.array; }
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385 | #else
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386 | // Some architectures cannot align on the stack,
|
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387 | // => let's manually enforce alignment by allocating more data and return the address of the first aligned element.
|
---|
388 | enum {
|
---|
389 | ForceAlignment = internal::packet_traits<Scalar>::Vectorizable,
|
---|
390 | PacketSize = internal::packet_traits<Scalar>::size
|
---|
391 | };
|
---|
392 | internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize)+(ForceAlignment?PacketSize:0),0> m_data;
|
---|
393 | EIGEN_STRONG_INLINE Scalar* data() {
|
---|
394 | return ForceAlignment
|
---|
395 | ? reinterpret_cast<Scalar*>((reinterpret_cast<size_t>(m_data.array) & ~(size_t(15))) + 16)
|
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396 | : m_data.array;
|
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397 | }
|
---|
398 | #endif
|
---|
399 | };
|
---|
400 |
|
---|
401 | template<> struct gemv_selector<OnTheRight,ColMajor,true>
|
---|
402 | {
|
---|
403 | template<typename ProductType, typename Dest>
|
---|
404 | static inline void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha)
|
---|
405 | {
|
---|
406 | typedef typename ProductType::Index Index;
|
---|
407 | typedef typename ProductType::LhsScalar LhsScalar;
|
---|
408 | typedef typename ProductType::RhsScalar RhsScalar;
|
---|
409 | typedef typename ProductType::Scalar ResScalar;
|
---|
410 | typedef typename ProductType::RealScalar RealScalar;
|
---|
411 | typedef typename ProductType::ActualLhsType ActualLhsType;
|
---|
412 | typedef typename ProductType::ActualRhsType ActualRhsType;
|
---|
413 | typedef typename ProductType::LhsBlasTraits LhsBlasTraits;
|
---|
414 | typedef typename ProductType::RhsBlasTraits RhsBlasTraits;
|
---|
415 | typedef Map<Matrix<ResScalar,Dynamic,1>, Aligned> MappedDest;
|
---|
416 |
|
---|
417 | ActualLhsType actualLhs = LhsBlasTraits::extract(prod.lhs());
|
---|
418 | ActualRhsType actualRhs = RhsBlasTraits::extract(prod.rhs());
|
---|
419 |
|
---|
420 | ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs())
|
---|
421 | * RhsBlasTraits::extractScalarFactor(prod.rhs());
|
---|
422 |
|
---|
423 | // make sure Dest is a compile-time vector type (bug 1166)
|
---|
424 | typedef typename conditional<Dest::IsVectorAtCompileTime, Dest, typename Dest::ColXpr>::type ActualDest;
|
---|
425 |
|
---|
426 | enum {
|
---|
427 | // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
|
---|
428 | // on, the other hand it is good for the cache to pack the vector anyways...
|
---|
429 | EvalToDestAtCompileTime = (ActualDest::InnerStrideAtCompileTime==1),
|
---|
430 | ComplexByReal = (NumTraits<LhsScalar>::IsComplex) && (!NumTraits<RhsScalar>::IsComplex),
|
---|
431 | MightCannotUseDest = (ActualDest::InnerStrideAtCompileTime!=1) || ComplexByReal
|
---|
432 | };
|
---|
433 |
|
---|
434 | gemv_static_vector_if<ResScalar,ActualDest::SizeAtCompileTime,ActualDest::MaxSizeAtCompileTime,MightCannotUseDest> static_dest;
|
---|
435 |
|
---|
436 | bool alphaIsCompatible = (!ComplexByReal) || (numext::imag(actualAlpha)==RealScalar(0));
|
---|
437 | bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible;
|
---|
438 |
|
---|
439 | RhsScalar compatibleAlpha = get_factor<ResScalar,RhsScalar>::run(actualAlpha);
|
---|
440 |
|
---|
441 | ei_declare_aligned_stack_constructed_variable(ResScalar,actualDestPtr,dest.size(),
|
---|
442 | evalToDest ? dest.data() : static_dest.data());
|
---|
443 |
|
---|
444 | if(!evalToDest)
|
---|
445 | {
|
---|
446 | #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
|
---|
447 | int size = dest.size();
|
---|
448 | EIGEN_DENSE_STORAGE_CTOR_PLUGIN
|
---|
449 | #endif
|
---|
450 | if(!alphaIsCompatible)
|
---|
451 | {
|
---|
452 | MappedDest(actualDestPtr, dest.size()).setZero();
|
---|
453 | compatibleAlpha = RhsScalar(1);
|
---|
454 | }
|
---|
455 | else
|
---|
456 | MappedDest(actualDestPtr, dest.size()) = dest;
|
---|
457 | }
|
---|
458 |
|
---|
459 | general_matrix_vector_product
|
---|
460 | <Index,LhsScalar,ColMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsBlasTraits::NeedToConjugate>::run(
|
---|
461 | actualLhs.rows(), actualLhs.cols(),
|
---|
462 | actualLhs.data(), actualLhs.outerStride(),
|
---|
463 | actualRhs.data(), actualRhs.innerStride(),
|
---|
464 | actualDestPtr, 1,
|
---|
465 | compatibleAlpha);
|
---|
466 |
|
---|
467 | if (!evalToDest)
|
---|
468 | {
|
---|
469 | if(!alphaIsCompatible)
|
---|
470 | dest += actualAlpha * MappedDest(actualDestPtr, dest.size());
|
---|
471 | else
|
---|
472 | dest = MappedDest(actualDestPtr, dest.size());
|
---|
473 | }
|
---|
474 | }
|
---|
475 | };
|
---|
476 |
|
---|
477 | template<> struct gemv_selector<OnTheRight,RowMajor,true>
|
---|
478 | {
|
---|
479 | template<typename ProductType, typename Dest>
|
---|
480 | static void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha)
|
---|
481 | {
|
---|
482 | typedef typename ProductType::LhsScalar LhsScalar;
|
---|
483 | typedef typename ProductType::RhsScalar RhsScalar;
|
---|
484 | typedef typename ProductType::Scalar ResScalar;
|
---|
485 | typedef typename ProductType::Index Index;
|
---|
486 | typedef typename ProductType::ActualLhsType ActualLhsType;
|
---|
487 | typedef typename ProductType::ActualRhsType ActualRhsType;
|
---|
488 | typedef typename ProductType::_ActualRhsType _ActualRhsType;
|
---|
489 | typedef typename ProductType::LhsBlasTraits LhsBlasTraits;
|
---|
490 | typedef typename ProductType::RhsBlasTraits RhsBlasTraits;
|
---|
491 |
|
---|
492 | typename add_const<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(prod.lhs());
|
---|
493 | typename add_const<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(prod.rhs());
|
---|
494 |
|
---|
495 | ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs())
|
---|
496 | * RhsBlasTraits::extractScalarFactor(prod.rhs());
|
---|
497 |
|
---|
498 | enum {
|
---|
499 | // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
|
---|
500 | // on, the other hand it is good for the cache to pack the vector anyways...
|
---|
501 | DirectlyUseRhs = _ActualRhsType::InnerStrideAtCompileTime==1
|
---|
502 | };
|
---|
503 |
|
---|
504 | gemv_static_vector_if<RhsScalar,_ActualRhsType::SizeAtCompileTime,_ActualRhsType::MaxSizeAtCompileTime,!DirectlyUseRhs> static_rhs;
|
---|
505 |
|
---|
506 | ei_declare_aligned_stack_constructed_variable(RhsScalar,actualRhsPtr,actualRhs.size(),
|
---|
507 | DirectlyUseRhs ? const_cast<RhsScalar*>(actualRhs.data()) : static_rhs.data());
|
---|
508 |
|
---|
509 | if(!DirectlyUseRhs)
|
---|
510 | {
|
---|
511 | #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
|
---|
512 | int size = actualRhs.size();
|
---|
513 | EIGEN_DENSE_STORAGE_CTOR_PLUGIN
|
---|
514 | #endif
|
---|
515 | Map<typename _ActualRhsType::PlainObject>(actualRhsPtr, actualRhs.size()) = actualRhs;
|
---|
516 | }
|
---|
517 |
|
---|
518 | general_matrix_vector_product
|
---|
519 | <Index,LhsScalar,RowMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsBlasTraits::NeedToConjugate>::run(
|
---|
520 | actualLhs.rows(), actualLhs.cols(),
|
---|
521 | actualLhs.data(), actualLhs.outerStride(),
|
---|
522 | actualRhsPtr, 1,
|
---|
523 | dest.data(), dest.col(0).innerStride(), //NOTE if dest is not a vector at compile-time, then dest.innerStride() might be wrong. (bug 1166)
|
---|
524 | actualAlpha);
|
---|
525 | }
|
---|
526 | };
|
---|
527 |
|
---|
528 | template<> struct gemv_selector<OnTheRight,ColMajor,false>
|
---|
529 | {
|
---|
530 | template<typename ProductType, typename Dest>
|
---|
531 | static void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha)
|
---|
532 | {
|
---|
533 | typedef typename Dest::Index Index;
|
---|
534 | // TODO makes sure dest is sequentially stored in memory, otherwise use a temp
|
---|
535 | const Index size = prod.rhs().rows();
|
---|
536 | for(Index k=0; k<size; ++k)
|
---|
537 | dest += (alpha*prod.rhs().coeff(k)) * prod.lhs().col(k);
|
---|
538 | }
|
---|
539 | };
|
---|
540 |
|
---|
541 | template<> struct gemv_selector<OnTheRight,RowMajor,false>
|
---|
542 | {
|
---|
543 | template<typename ProductType, typename Dest>
|
---|
544 | static void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha)
|
---|
545 | {
|
---|
546 | typedef typename Dest::Index Index;
|
---|
547 | // TODO makes sure rhs is sequentially stored in memory, otherwise use a temp
|
---|
548 | const Index rows = prod.rows();
|
---|
549 | for(Index i=0; i<rows; ++i)
|
---|
550 | dest.coeffRef(i) += alpha * (prod.lhs().row(i).cwiseProduct(prod.rhs().transpose())).sum();
|
---|
551 | }
|
---|
552 | };
|
---|
553 |
|
---|
554 | } // end namespace internal
|
---|
555 |
|
---|
556 | /***************************************************************************
|
---|
557 | * Implementation of matrix base methods
|
---|
558 | ***************************************************************************/
|
---|
559 |
|
---|
560 | /** \returns the matrix product of \c *this and \a other.
|
---|
561 | *
|
---|
562 | * \note If instead of the matrix product you want the coefficient-wise product, see Cwise::operator*().
|
---|
563 | *
|
---|
564 | * \sa lazyProduct(), operator*=(const MatrixBase&), Cwise::operator*()
|
---|
565 | */
|
---|
566 | template<typename Derived>
|
---|
567 | template<typename OtherDerived>
|
---|
568 | inline const typename ProductReturnType<Derived, OtherDerived>::Type
|
---|
569 | MatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) const
|
---|
570 | {
|
---|
571 | // A note regarding the function declaration: In MSVC, this function will sometimes
|
---|
572 | // not be inlined since DenseStorage is an unwindable object for dynamic
|
---|
573 | // matrices and product types are holding a member to store the result.
|
---|
574 | // Thus it does not help tagging this function with EIGEN_STRONG_INLINE.
|
---|
575 | enum {
|
---|
576 | ProductIsValid = Derived::ColsAtCompileTime==Dynamic
|
---|
577 | || OtherDerived::RowsAtCompileTime==Dynamic
|
---|
578 | || int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime),
|
---|
579 | AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime,
|
---|
580 | SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived)
|
---|
581 | };
|
---|
582 | // note to the lost user:
|
---|
583 | // * for a dot product use: v1.dot(v2)
|
---|
584 | // * for a coeff-wise product use: v1.cwiseProduct(v2)
|
---|
585 | EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes),
|
---|
586 | INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS)
|
---|
587 | EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors),
|
---|
588 | INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
|
---|
589 | EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
|
---|
590 | #ifdef EIGEN_DEBUG_PRODUCT
|
---|
591 | internal::product_type<Derived,OtherDerived>::debug();
|
---|
592 | #endif
|
---|
593 | return typename ProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
|
---|
594 | }
|
---|
595 |
|
---|
596 | /** \returns an expression of the matrix product of \c *this and \a other without implicit evaluation.
|
---|
597 | *
|
---|
598 | * The returned product will behave like any other expressions: the coefficients of the product will be
|
---|
599 | * computed once at a time as requested. This might be useful in some extremely rare cases when only
|
---|
600 | * a small and no coherent fraction of the result's coefficients have to be computed.
|
---|
601 | *
|
---|
602 | * \warning This version of the matrix product can be much much slower. So use it only if you know
|
---|
603 | * what you are doing and that you measured a true speed improvement.
|
---|
604 | *
|
---|
605 | * \sa operator*(const MatrixBase&)
|
---|
606 | */
|
---|
607 | template<typename Derived>
|
---|
608 | template<typename OtherDerived>
|
---|
609 | const typename LazyProductReturnType<Derived,OtherDerived>::Type
|
---|
610 | MatrixBase<Derived>::lazyProduct(const MatrixBase<OtherDerived> &other) const
|
---|
611 | {
|
---|
612 | enum {
|
---|
613 | ProductIsValid = Derived::ColsAtCompileTime==Dynamic
|
---|
614 | || OtherDerived::RowsAtCompileTime==Dynamic
|
---|
615 | || int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime),
|
---|
616 | AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime,
|
---|
617 | SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived)
|
---|
618 | };
|
---|
619 | // note to the lost user:
|
---|
620 | // * for a dot product use: v1.dot(v2)
|
---|
621 | // * for a coeff-wise product use: v1.cwiseProduct(v2)
|
---|
622 | EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes),
|
---|
623 | INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS)
|
---|
624 | EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors),
|
---|
625 | INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
|
---|
626 | EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
|
---|
627 |
|
---|
628 | return typename LazyProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
|
---|
629 | }
|
---|
630 |
|
---|
631 | } // end namespace Eigen
|
---|
632 |
|
---|
633 | #endif // EIGEN_PRODUCT_H
|
---|