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) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
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5 | //
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6 | // This Source Code Form is subject to the terms of the Mozilla
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7 | // Public License v. 2.0. If a copy of the MPL was not distributed
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8 | // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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9 |
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10 | #ifndef EIGEN_SPARSEPRODUCT_H
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11 | #define EIGEN_SPARSEPRODUCT_H
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12 |
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13 | namespace Eigen {
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14 |
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15 | template<typename Lhs, typename Rhs>
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16 | struct SparseSparseProductReturnType
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17 | {
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18 | typedef typename internal::traits<Lhs>::Scalar Scalar;
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19 | typedef typename internal::traits<Lhs>::Index Index;
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20 | enum {
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21 | LhsRowMajor = internal::traits<Lhs>::Flags & RowMajorBit,
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22 | RhsRowMajor = internal::traits<Rhs>::Flags & RowMajorBit,
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23 | TransposeRhs = (!LhsRowMajor) && RhsRowMajor,
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24 | TransposeLhs = LhsRowMajor && (!RhsRowMajor)
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25 | };
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26 |
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27 | typedef typename internal::conditional<TransposeLhs,
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28 | SparseMatrix<Scalar,0,Index>,
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29 | typename internal::nested<Lhs,Rhs::RowsAtCompileTime>::type>::type LhsNested;
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30 |
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31 | typedef typename internal::conditional<TransposeRhs,
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32 | SparseMatrix<Scalar,0,Index>,
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33 | typename internal::nested<Rhs,Lhs::RowsAtCompileTime>::type>::type RhsNested;
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34 |
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35 | typedef SparseSparseProduct<LhsNested, RhsNested> Type;
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36 | };
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37 |
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38 | namespace internal {
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39 | template<typename LhsNested, typename RhsNested>
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40 | struct traits<SparseSparseProduct<LhsNested, RhsNested> >
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41 | {
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42 | typedef MatrixXpr XprKind;
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43 | // clean the nested types:
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44 | typedef typename remove_all<LhsNested>::type _LhsNested;
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45 | typedef typename remove_all<RhsNested>::type _RhsNested;
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46 | typedef typename _LhsNested::Scalar Scalar;
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47 | typedef typename promote_index_type<typename traits<_LhsNested>::Index,
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48 | typename traits<_RhsNested>::Index>::type Index;
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49 |
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50 | enum {
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51 | LhsCoeffReadCost = _LhsNested::CoeffReadCost,
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52 | RhsCoeffReadCost = _RhsNested::CoeffReadCost,
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53 | LhsFlags = _LhsNested::Flags,
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54 | RhsFlags = _RhsNested::Flags,
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55 |
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56 | RowsAtCompileTime = _LhsNested::RowsAtCompileTime,
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57 | ColsAtCompileTime = _RhsNested::ColsAtCompileTime,
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58 | MaxRowsAtCompileTime = _LhsNested::MaxRowsAtCompileTime,
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59 | MaxColsAtCompileTime = _RhsNested::MaxColsAtCompileTime,
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60 |
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61 | InnerSize = EIGEN_SIZE_MIN_PREFER_FIXED(_LhsNested::ColsAtCompileTime, _RhsNested::RowsAtCompileTime),
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62 |
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63 | EvalToRowMajor = (RhsFlags & LhsFlags & RowMajorBit),
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64 |
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65 | RemovedBits = ~(EvalToRowMajor ? 0 : RowMajorBit),
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66 |
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67 | Flags = (int(LhsFlags | RhsFlags) & HereditaryBits & RemovedBits)
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68 | | EvalBeforeAssigningBit
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69 | | EvalBeforeNestingBit,
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70 |
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71 | CoeffReadCost = Dynamic
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72 | };
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73 |
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74 | typedef Sparse StorageKind;
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75 | };
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76 |
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77 | } // end namespace internal
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78 |
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79 | template<typename LhsNested, typename RhsNested>
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80 | class SparseSparseProduct : internal::no_assignment_operator,
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81 | public SparseMatrixBase<SparseSparseProduct<LhsNested, RhsNested> >
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82 | {
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83 | public:
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84 |
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85 | typedef SparseMatrixBase<SparseSparseProduct> Base;
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86 | EIGEN_DENSE_PUBLIC_INTERFACE(SparseSparseProduct)
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87 |
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88 | private:
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89 |
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90 | typedef typename internal::traits<SparseSparseProduct>::_LhsNested _LhsNested;
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91 | typedef typename internal::traits<SparseSparseProduct>::_RhsNested _RhsNested;
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92 |
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93 | public:
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94 |
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95 | template<typename Lhs, typename Rhs>
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96 | EIGEN_STRONG_INLINE SparseSparseProduct(const Lhs& lhs, const Rhs& rhs)
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97 | : m_lhs(lhs), m_rhs(rhs), m_tolerance(0), m_conservative(true)
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98 | {
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99 | init();
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100 | }
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101 |
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102 | template<typename Lhs, typename Rhs>
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103 | EIGEN_STRONG_INLINE SparseSparseProduct(const Lhs& lhs, const Rhs& rhs, const RealScalar& tolerance)
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104 | : m_lhs(lhs), m_rhs(rhs), m_tolerance(tolerance), m_conservative(false)
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105 | {
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106 | init();
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107 | }
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108 |
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109 | SparseSparseProduct pruned(const Scalar& reference = 0, const RealScalar& epsilon = NumTraits<RealScalar>::dummy_precision()) const
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110 | {
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111 | using std::abs;
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112 | return SparseSparseProduct(m_lhs,m_rhs,abs(reference)*epsilon);
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113 | }
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114 |
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115 | template<typename Dest>
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116 | void evalTo(Dest& result) const
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117 | {
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118 | if(m_conservative)
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119 | internal::conservative_sparse_sparse_product_selector<_LhsNested, _RhsNested, Dest>::run(lhs(),rhs(),result);
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120 | else
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121 | internal::sparse_sparse_product_with_pruning_selector<_LhsNested, _RhsNested, Dest>::run(lhs(),rhs(),result,m_tolerance);
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122 | }
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123 |
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124 | EIGEN_STRONG_INLINE Index rows() const { return m_lhs.rows(); }
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125 | EIGEN_STRONG_INLINE Index cols() const { return m_rhs.cols(); }
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126 |
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127 | EIGEN_STRONG_INLINE const _LhsNested& lhs() const { return m_lhs; }
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128 | EIGEN_STRONG_INLINE const _RhsNested& rhs() const { return m_rhs; }
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129 |
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130 | protected:
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131 | void init()
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132 | {
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133 | eigen_assert(m_lhs.cols() == m_rhs.rows());
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134 |
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135 | enum {
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136 | ProductIsValid = _LhsNested::ColsAtCompileTime==Dynamic
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137 | || _RhsNested::RowsAtCompileTime==Dynamic
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138 | || int(_LhsNested::ColsAtCompileTime)==int(_RhsNested::RowsAtCompileTime),
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139 | AreVectors = _LhsNested::IsVectorAtCompileTime && _RhsNested::IsVectorAtCompileTime,
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140 | SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(_LhsNested,_RhsNested)
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141 | };
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142 | // note to the lost user:
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143 | // * for a dot product use: v1.dot(v2)
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144 | // * for a coeff-wise product use: v1.cwise()*v2
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145 | EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes),
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146 | INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS)
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147 | EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors),
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148 | INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
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149 | EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
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150 | }
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151 |
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152 | LhsNested m_lhs;
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153 | RhsNested m_rhs;
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154 | RealScalar m_tolerance;
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155 | bool m_conservative;
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156 | };
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157 |
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158 | // sparse = sparse * sparse
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159 | template<typename Derived>
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160 | template<typename Lhs, typename Rhs>
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161 | inline Derived& SparseMatrixBase<Derived>::operator=(const SparseSparseProduct<Lhs,Rhs>& product)
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162 | {
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163 | product.evalTo(derived());
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164 | return derived();
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165 | }
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166 |
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167 | /** \returns an expression of the product of two sparse matrices.
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168 | * By default a conservative product preserving the symbolic non zeros is performed.
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169 | * The automatic pruning of the small values can be achieved by calling the pruned() function
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170 | * in which case a totally different product algorithm is employed:
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171 | * \code
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172 | * C = (A*B).pruned(); // supress numerical zeros (exact)
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173 | * C = (A*B).pruned(ref);
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174 | * C = (A*B).pruned(ref,epsilon);
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175 | * \endcode
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176 | * where \c ref is a meaningful non zero reference value.
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177 | * */
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178 | template<typename Derived>
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179 | template<typename OtherDerived>
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180 | inline const typename SparseSparseProductReturnType<Derived,OtherDerived>::Type
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181 | SparseMatrixBase<Derived>::operator*(const SparseMatrixBase<OtherDerived> &other) const
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182 | {
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183 | return typename SparseSparseProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
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184 | }
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185 |
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186 | } // end namespace Eigen
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187 |
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188 | #endif // EIGEN_SPARSEPRODUCT_H
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