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) 2008-2009 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_SPARSEVECTOR_H |
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11 | #define EIGEN_SPARSEVECTOR_H |
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12 | |
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13 | namespace Eigen { |
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14 | |
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15 | /** \ingroup SparseCore_Module |
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16 | * \class SparseVector |
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17 | * |
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18 | * \brief a sparse vector class |
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19 | * |
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20 | * \tparam _Scalar the scalar type, i.e. the type of the coefficients |
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21 | * |
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22 | * See http://www.netlib.org/linalg/html_templates/node91.html for details on the storage scheme. |
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23 | * |
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24 | * This class can be extended with the help of the plugin mechanism described on the page |
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25 | * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_SPARSEVECTOR_PLUGIN. |
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26 | */ |
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27 | |
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28 | namespace internal { |
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29 | template<typename _Scalar, int _Options, typename _Index> |
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30 | struct traits<SparseVector<_Scalar, _Options, _Index> > |
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31 | { |
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32 | typedef _Scalar Scalar; |
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33 | typedef _Index Index; |
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34 | typedef Sparse StorageKind; |
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35 | typedef MatrixXpr XprKind; |
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36 | enum { |
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37 | IsColVector = (_Options & RowMajorBit) ? 0 : 1, |
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38 | |
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39 | RowsAtCompileTime = IsColVector ? Dynamic : 1, |
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40 | ColsAtCompileTime = IsColVector ? 1 : Dynamic, |
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41 | MaxRowsAtCompileTime = RowsAtCompileTime, |
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42 | MaxColsAtCompileTime = ColsAtCompileTime, |
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43 | Flags = _Options | NestByRefBit | LvalueBit | (IsColVector ? 0 : RowMajorBit), |
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44 | CoeffReadCost = NumTraits<Scalar>::ReadCost, |
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45 | SupportedAccessPatterns = InnerRandomAccessPattern |
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46 | }; |
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47 | }; |
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48 | |
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49 | // Sparse-Vector-Assignment kinds: |
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50 | enum { |
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51 | SVA_RuntimeSwitch, |
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52 | SVA_Inner, |
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53 | SVA_Outer |
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54 | }; |
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55 | |
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56 | template< typename Dest, typename Src, |
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57 | int AssignmentKind = !bool(Src::IsVectorAtCompileTime) ? SVA_RuntimeSwitch |
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58 | : Src::InnerSizeAtCompileTime==1 ? SVA_Outer |
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59 | : SVA_Inner> |
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60 | struct sparse_vector_assign_selector; |
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61 | |
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62 | } |
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63 | |
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64 | template<typename _Scalar, int _Options, typename _Index> |
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65 | class SparseVector |
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66 | : public SparseMatrixBase<SparseVector<_Scalar, _Options, _Index> > |
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67 | { |
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68 | typedef SparseMatrixBase<SparseVector> SparseBase; |
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69 | |
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70 | public: |
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71 | EIGEN_SPARSE_PUBLIC_INTERFACE(SparseVector) |
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72 | EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, +=) |
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73 | EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, -=) |
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74 | |
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75 | typedef internal::CompressedStorage<Scalar,Index> Storage; |
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76 | enum { IsColVector = internal::traits<SparseVector>::IsColVector }; |
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77 | |
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78 | enum { |
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79 | Options = _Options |
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80 | }; |
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81 | |
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82 | EIGEN_STRONG_INLINE Index rows() const { return IsColVector ? m_size : 1; } |
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83 | EIGEN_STRONG_INLINE Index cols() const { return IsColVector ? 1 : m_size; } |
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84 | EIGEN_STRONG_INLINE Index innerSize() const { return m_size; } |
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85 | EIGEN_STRONG_INLINE Index outerSize() const { return 1; } |
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86 | |
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87 | EIGEN_STRONG_INLINE const Scalar* valuePtr() const { return &m_data.value(0); } |
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88 | EIGEN_STRONG_INLINE Scalar* valuePtr() { return &m_data.value(0); } |
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89 | |
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90 | EIGEN_STRONG_INLINE const Index* innerIndexPtr() const { return &m_data.index(0); } |
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91 | EIGEN_STRONG_INLINE Index* innerIndexPtr() { return &m_data.index(0); } |
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92 | |
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93 | /** \internal */ |
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94 | inline Storage& data() { return m_data; } |
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95 | /** \internal */ |
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96 | inline const Storage& data() const { return m_data; } |
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97 | |
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98 | inline Scalar coeff(Index row, Index col) const |
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99 | { |
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100 | eigen_assert(IsColVector ? (col==0 && row>=0 && row<m_size) : (row==0 && col>=0 && col<m_size)); |
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101 | return coeff(IsColVector ? row : col); |
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102 | } |
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103 | inline Scalar coeff(Index i) const |
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104 | { |
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105 | eigen_assert(i>=0 && i<m_size); |
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106 | return m_data.at(i); |
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107 | } |
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108 | |
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109 | inline Scalar& coeffRef(Index row, Index col) |
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110 | { |
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111 | eigen_assert(IsColVector ? (col==0 && row>=0 && row<m_size) : (row==0 && col>=0 && col<m_size)); |
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112 | return coeff(IsColVector ? row : col); |
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113 | } |
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114 | |
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115 | /** \returns a reference to the coefficient value at given index \a i |
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116 | * This operation involes a log(rho*size) binary search. If the coefficient does not |
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117 | * exist yet, then a sorted insertion into a sequential buffer is performed. |
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118 | * |
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119 | * This insertion might be very costly if the number of nonzeros above \a i is large. |
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120 | */ |
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121 | inline Scalar& coeffRef(Index i) |
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122 | { |
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123 | eigen_assert(i>=0 && i<m_size); |
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124 | return m_data.atWithInsertion(i); |
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125 | } |
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126 | |
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127 | public: |
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128 | |
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129 | class InnerIterator; |
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130 | class ReverseInnerIterator; |
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131 | |
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132 | inline void setZero() { m_data.clear(); } |
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133 | |
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134 | /** \returns the number of non zero coefficients */ |
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135 | inline Index nonZeros() const { return static_cast<Index>(m_data.size()); } |
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136 | |
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137 | inline void startVec(Index outer) |
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138 | { |
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139 | EIGEN_UNUSED_VARIABLE(outer); |
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140 | eigen_assert(outer==0); |
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141 | } |
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142 | |
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143 | inline Scalar& insertBackByOuterInner(Index outer, Index inner) |
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144 | { |
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145 | EIGEN_UNUSED_VARIABLE(outer); |
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146 | eigen_assert(outer==0); |
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147 | return insertBack(inner); |
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148 | } |
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149 | inline Scalar& insertBack(Index i) |
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150 | { |
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151 | m_data.append(0, i); |
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152 | return m_data.value(m_data.size()-1); |
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153 | } |
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154 | |
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155 | inline Scalar& insert(Index row, Index col) |
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156 | { |
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157 | eigen_assert(IsColVector ? (col==0 && row>=0 && row<m_size) : (row==0 && col>=0 && col<m_size)); |
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158 | |
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159 | Index inner = IsColVector ? row : col; |
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160 | Index outer = IsColVector ? col : row; |
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161 | eigen_assert(outer==0); |
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162 | return insert(inner); |
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163 | } |
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164 | Scalar& insert(Index i) |
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165 | { |
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166 | eigen_assert(i>=0 && i<m_size); |
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167 | |
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168 | Index startId = 0; |
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169 | Index p = Index(m_data.size()) - 1; |
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170 | // TODO smart realloc |
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171 | m_data.resize(p+2,1); |
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172 | |
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173 | while ( (p >= startId) && (m_data.index(p) > i) ) |
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174 | { |
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175 | m_data.index(p+1) = m_data.index(p); |
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176 | m_data.value(p+1) = m_data.value(p); |
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177 | --p; |
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178 | } |
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179 | m_data.index(p+1) = i; |
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180 | m_data.value(p+1) = 0; |
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181 | return m_data.value(p+1); |
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182 | } |
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183 | |
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184 | /** |
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185 | */ |
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186 | inline void reserve(Index reserveSize) { m_data.reserve(reserveSize); } |
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187 | |
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188 | |
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189 | inline void finalize() {} |
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190 | |
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191 | void prune(const Scalar& reference, const RealScalar& epsilon = NumTraits<RealScalar>::dummy_precision()) |
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192 | { |
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193 | m_data.prune(reference,epsilon); |
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194 | } |
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195 | |
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196 | void resize(Index rows, Index cols) |
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197 | { |
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198 | eigen_assert(rows==1 || cols==1); |
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199 | resize(IsColVector ? rows : cols); |
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200 | } |
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201 | |
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202 | void resize(Index newSize) |
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203 | { |
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204 | m_size = newSize; |
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205 | m_data.clear(); |
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206 | } |
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207 | |
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208 | void resizeNonZeros(Index size) { m_data.resize(size); } |
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209 | |
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210 | inline SparseVector() : m_size(0) { check_template_parameters(); resize(0); } |
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211 | |
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212 | inline SparseVector(Index size) : m_size(0) { check_template_parameters(); resize(size); } |
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213 | |
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214 | inline SparseVector(Index rows, Index cols) : m_size(0) { check_template_parameters(); resize(rows,cols); } |
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215 | |
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216 | template<typename OtherDerived> |
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217 | inline SparseVector(const SparseMatrixBase<OtherDerived>& other) |
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218 | : m_size(0) |
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219 | { |
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220 | check_template_parameters(); |
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221 | *this = other.derived(); |
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222 | } |
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223 | |
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224 | inline SparseVector(const SparseVector& other) |
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225 | : SparseBase(other), m_size(0) |
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226 | { |
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227 | check_template_parameters(); |
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228 | *this = other.derived(); |
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229 | } |
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230 | |
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231 | /** Swaps the values of \c *this and \a other. |
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232 | * Overloaded for performance: this version performs a \em shallow swap by swaping pointers and attributes only. |
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233 | * \sa SparseMatrixBase::swap() |
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234 | */ |
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235 | inline void swap(SparseVector& other) |
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236 | { |
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237 | std::swap(m_size, other.m_size); |
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238 | m_data.swap(other.m_data); |
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239 | } |
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240 | |
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241 | inline SparseVector& operator=(const SparseVector& other) |
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242 | { |
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243 | if (other.isRValue()) |
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244 | { |
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245 | swap(other.const_cast_derived()); |
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246 | } |
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247 | else |
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248 | { |
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249 | resize(other.size()); |
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250 | m_data = other.m_data; |
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251 | } |
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252 | return *this; |
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253 | } |
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254 | |
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255 | template<typename OtherDerived> |
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256 | inline SparseVector& operator=(const SparseMatrixBase<OtherDerived>& other) |
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257 | { |
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258 | SparseVector tmp(other.size()); |
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259 | internal::sparse_vector_assign_selector<SparseVector,OtherDerived>::run(tmp,other.derived()); |
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260 | this->swap(tmp); |
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261 | return *this; |
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262 | } |
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263 | |
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264 | #ifndef EIGEN_PARSED_BY_DOXYGEN |
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265 | template<typename Lhs, typename Rhs> |
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266 | inline SparseVector& operator=(const SparseSparseProduct<Lhs,Rhs>& product) |
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267 | { |
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268 | return Base::operator=(product); |
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269 | } |
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270 | #endif |
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271 | |
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272 | friend std::ostream & operator << (std::ostream & s, const SparseVector& m) |
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273 | { |
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274 | for (Index i=0; i<m.nonZeros(); ++i) |
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275 | s << "(" << m.m_data.value(i) << "," << m.m_data.index(i) << ") "; |
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276 | s << std::endl; |
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277 | return s; |
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278 | } |
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279 | |
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280 | /** Destructor */ |
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281 | inline ~SparseVector() {} |
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282 | |
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283 | /** Overloaded for performance */ |
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284 | Scalar sum() const; |
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285 | |
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286 | public: |
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287 | |
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288 | /** \internal \deprecated use setZero() and reserve() */ |
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289 | EIGEN_DEPRECATED void startFill(Index reserve) |
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290 | { |
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291 | setZero(); |
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292 | m_data.reserve(reserve); |
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293 | } |
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294 | |
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295 | /** \internal \deprecated use insertBack(Index,Index) */ |
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296 | EIGEN_DEPRECATED Scalar& fill(Index r, Index c) |
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297 | { |
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298 | eigen_assert(r==0 || c==0); |
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299 | return fill(IsColVector ? r : c); |
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300 | } |
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301 | |
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302 | /** \internal \deprecated use insertBack(Index) */ |
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303 | EIGEN_DEPRECATED Scalar& fill(Index i) |
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304 | { |
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305 | m_data.append(0, i); |
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306 | return m_data.value(m_data.size()-1); |
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307 | } |
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308 | |
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309 | /** \internal \deprecated use insert(Index,Index) */ |
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310 | EIGEN_DEPRECATED Scalar& fillrand(Index r, Index c) |
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311 | { |
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312 | eigen_assert(r==0 || c==0); |
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313 | return fillrand(IsColVector ? r : c); |
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314 | } |
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315 | |
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316 | /** \internal \deprecated use insert(Index) */ |
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317 | EIGEN_DEPRECATED Scalar& fillrand(Index i) |
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318 | { |
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319 | return insert(i); |
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320 | } |
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321 | |
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322 | /** \internal \deprecated use finalize() */ |
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323 | EIGEN_DEPRECATED void endFill() {} |
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324 | |
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325 | // These two functions were here in the 3.1 release, so let's keep them in case some code rely on them. |
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326 | /** \internal \deprecated use data() */ |
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327 | EIGEN_DEPRECATED Storage& _data() { return m_data; } |
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328 | /** \internal \deprecated use data() */ |
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329 | EIGEN_DEPRECATED const Storage& _data() const { return m_data; } |
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330 | |
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331 | # ifdef EIGEN_SPARSEVECTOR_PLUGIN |
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332 | # include EIGEN_SPARSEVECTOR_PLUGIN |
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333 | # endif |
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334 | |
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335 | protected: |
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336 | |
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337 | static void check_template_parameters() |
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338 | { |
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339 | EIGEN_STATIC_ASSERT(NumTraits<Index>::IsSigned,THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE); |
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340 | EIGEN_STATIC_ASSERT((_Options&(ColMajor|RowMajor))==Options,INVALID_MATRIX_TEMPLATE_PARAMETERS); |
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341 | } |
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342 | |
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343 | Storage m_data; |
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344 | Index m_size; |
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345 | }; |
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346 | |
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347 | template<typename Scalar, int _Options, typename _Index> |
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348 | class SparseVector<Scalar,_Options,_Index>::InnerIterator |
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349 | { |
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350 | public: |
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351 | InnerIterator(const SparseVector& vec, Index outer=0) |
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352 | : m_data(vec.m_data), m_id(0), m_end(static_cast<Index>(m_data.size())) |
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353 | { |
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354 | EIGEN_UNUSED_VARIABLE(outer); |
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355 | eigen_assert(outer==0); |
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356 | } |
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357 | |
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358 | InnerIterator(const internal::CompressedStorage<Scalar,Index>& data) |
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359 | : m_data(data), m_id(0), m_end(static_cast<Index>(m_data.size())) |
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360 | {} |
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361 | |
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362 | inline InnerIterator& operator++() { m_id++; return *this; } |
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363 | |
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364 | inline Scalar value() const { return m_data.value(m_id); } |
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365 | inline Scalar& valueRef() { return const_cast<Scalar&>(m_data.value(m_id)); } |
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366 | |
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367 | inline Index index() const { return m_data.index(m_id); } |
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368 | inline Index row() const { return IsColVector ? index() : 0; } |
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369 | inline Index col() const { return IsColVector ? 0 : index(); } |
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370 | |
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371 | inline operator bool() const { return (m_id < m_end); } |
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372 | |
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373 | protected: |
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374 | const internal::CompressedStorage<Scalar,Index>& m_data; |
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375 | Index m_id; |
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376 | const Index m_end; |
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377 | }; |
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378 | |
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379 | template<typename Scalar, int _Options, typename _Index> |
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380 | class SparseVector<Scalar,_Options,_Index>::ReverseInnerIterator |
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381 | { |
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382 | public: |
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383 | ReverseInnerIterator(const SparseVector& vec, Index outer=0) |
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384 | : m_data(vec.m_data), m_id(static_cast<Index>(m_data.size())), m_start(0) |
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385 | { |
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386 | EIGEN_UNUSED_VARIABLE(outer); |
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387 | eigen_assert(outer==0); |
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388 | } |
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389 | |
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390 | ReverseInnerIterator(const internal::CompressedStorage<Scalar,Index>& data) |
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391 | : m_data(data), m_id(static_cast<Index>(m_data.size())), m_start(0) |
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392 | {} |
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393 | |
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394 | inline ReverseInnerIterator& operator--() { m_id--; return *this; } |
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395 | |
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396 | inline Scalar value() const { return m_data.value(m_id-1); } |
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397 | inline Scalar& valueRef() { return const_cast<Scalar&>(m_data.value(m_id-1)); } |
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398 | |
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399 | inline Index index() const { return m_data.index(m_id-1); } |
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400 | inline Index row() const { return IsColVector ? index() : 0; } |
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401 | inline Index col() const { return IsColVector ? 0 : index(); } |
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402 | |
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403 | inline operator bool() const { return (m_id > m_start); } |
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404 | |
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405 | protected: |
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406 | const internal::CompressedStorage<Scalar,Index>& m_data; |
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407 | Index m_id; |
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408 | const Index m_start; |
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409 | }; |
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410 | |
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411 | namespace internal { |
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412 | |
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413 | template< typename Dest, typename Src> |
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414 | struct sparse_vector_assign_selector<Dest,Src,SVA_Inner> { |
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415 | static void run(Dest& dst, const Src& src) { |
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416 | eigen_internal_assert(src.innerSize()==src.size()); |
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417 | for(typename Src::InnerIterator it(src, 0); it; ++it) |
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418 | dst.insert(it.index()) = it.value(); |
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419 | } |
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420 | }; |
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421 | |
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422 | template< typename Dest, typename Src> |
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423 | struct sparse_vector_assign_selector<Dest,Src,SVA_Outer> { |
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424 | static void run(Dest& dst, const Src& src) { |
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425 | eigen_internal_assert(src.outerSize()==src.size()); |
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426 | for(typename Dest::Index i=0; i<src.size(); ++i) |
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427 | { |
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428 | typename Src::InnerIterator it(src, i); |
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429 | if(it) |
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430 | dst.insert(i) = it.value(); |
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431 | } |
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432 | } |
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433 | }; |
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434 | |
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435 | template< typename Dest, typename Src> |
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436 | struct sparse_vector_assign_selector<Dest,Src,SVA_RuntimeSwitch> { |
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437 | static void run(Dest& dst, const Src& src) { |
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438 | if(src.outerSize()==1) sparse_vector_assign_selector<Dest,Src,SVA_Inner>::run(dst, src); |
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439 | else sparse_vector_assign_selector<Dest,Src,SVA_Outer>::run(dst, src); |
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440 | } |
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441 | }; |
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442 | |
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443 | } |
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444 | |
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445 | } // end namespace Eigen |
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446 | |
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447 | #endif // EIGEN_SPARSEVECTOR_H |
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