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) 2008-2011 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 | #include "sparse.h"
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11 |
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12 | template<typename SparseMatrixType, typename DenseMatrix, bool IsRowMajor=SparseMatrixType::IsRowMajor> struct test_outer;
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13 |
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14 | template<typename SparseMatrixType, typename DenseMatrix> struct test_outer<SparseMatrixType,DenseMatrix,false> {
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15 | static void run(SparseMatrixType& m2, SparseMatrixType& m4, DenseMatrix& refMat2, DenseMatrix& refMat4) {
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16 | typedef typename SparseMatrixType::Index Index;
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17 | Index c = internal::random<Index>(0,m2.cols()-1);
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18 | Index c1 = internal::random<Index>(0,m2.cols()-1);
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19 | VERIFY_IS_APPROX(m4=m2.col(c)*refMat2.col(c1).transpose(), refMat4=refMat2.col(c)*refMat2.col(c1).transpose());
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20 | VERIFY_IS_APPROX(m4=refMat2.col(c1)*m2.col(c).transpose(), refMat4=refMat2.col(c1)*refMat2.col(c).transpose());
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21 | }
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22 | };
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23 |
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24 | template<typename SparseMatrixType, typename DenseMatrix> struct test_outer<SparseMatrixType,DenseMatrix,true> {
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25 | static void run(SparseMatrixType& m2, SparseMatrixType& m4, DenseMatrix& refMat2, DenseMatrix& refMat4) {
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26 | typedef typename SparseMatrixType::Index Index;
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27 | Index r = internal::random<Index>(0,m2.rows()-1);
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28 | Index c1 = internal::random<Index>(0,m2.cols()-1);
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29 | VERIFY_IS_APPROX(m4=m2.row(r).transpose()*refMat2.col(c1).transpose(), refMat4=refMat2.row(r).transpose()*refMat2.col(c1).transpose());
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30 | VERIFY_IS_APPROX(m4=refMat2.col(c1)*m2.row(r), refMat4=refMat2.col(c1)*refMat2.row(r));
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31 | }
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32 | };
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33 |
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34 | // (m2,m4,refMat2,refMat4,dv1);
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35 | // VERIFY_IS_APPROX(m4=m2.innerVector(c)*dv1.transpose(), refMat4=refMat2.colVector(c)*dv1.transpose());
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36 | // VERIFY_IS_APPROX(m4=dv1*mcm.col(c).transpose(), refMat4=dv1*refMat2.col(c).transpose());
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37 |
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38 | template<typename SparseMatrixType> void sparse_product()
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39 | {
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40 | typedef typename SparseMatrixType::Index Index;
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41 | Index n = 100;
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42 | const Index rows = internal::random<Index>(1,n);
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43 | const Index cols = internal::random<Index>(1,n);
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44 | const Index depth = internal::random<Index>(1,n);
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45 | typedef typename SparseMatrixType::Scalar Scalar;
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46 | enum { Flags = SparseMatrixType::Flags };
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47 |
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48 | double density = (std::max)(8./(rows*cols), 0.1);
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49 | typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
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50 | typedef Matrix<Scalar,Dynamic,1> DenseVector;
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51 | typedef Matrix<Scalar,1,Dynamic> RowDenseVector;
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52 | typedef SparseVector<Scalar,0,Index> ColSpVector;
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53 | typedef SparseVector<Scalar,RowMajor,Index> RowSpVector;
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54 |
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55 | Scalar s1 = internal::random<Scalar>();
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56 | Scalar s2 = internal::random<Scalar>();
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57 |
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58 | // test matrix-matrix product
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59 | {
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60 | DenseMatrix refMat2 = DenseMatrix::Zero(rows, depth);
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61 | DenseMatrix refMat2t = DenseMatrix::Zero(depth, rows);
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62 | DenseMatrix refMat3 = DenseMatrix::Zero(depth, cols);
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63 | DenseMatrix refMat3t = DenseMatrix::Zero(cols, depth);
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64 | DenseMatrix refMat4 = DenseMatrix::Zero(rows, cols);
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65 | DenseMatrix refMat4t = DenseMatrix::Zero(cols, rows);
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66 | DenseMatrix refMat5 = DenseMatrix::Random(depth, cols);
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67 | DenseMatrix refMat6 = DenseMatrix::Random(rows, rows);
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68 | DenseMatrix dm4 = DenseMatrix::Zero(rows, rows);
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69 | // DenseVector dv1 = DenseVector::Random(rows);
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70 | SparseMatrixType m2 (rows, depth);
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71 | SparseMatrixType m2t(depth, rows);
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72 | SparseMatrixType m3 (depth, cols);
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73 | SparseMatrixType m3t(cols, depth);
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74 | SparseMatrixType m4 (rows, cols);
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75 | SparseMatrixType m4t(cols, rows);
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76 | SparseMatrixType m6(rows, rows);
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77 | initSparse(density, refMat2, m2);
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78 | initSparse(density, refMat2t, m2t);
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79 | initSparse(density, refMat3, m3);
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80 | initSparse(density, refMat3t, m3t);
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81 | initSparse(density, refMat4, m4);
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82 | initSparse(density, refMat4t, m4t);
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83 | initSparse(density, refMat6, m6);
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84 |
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85 | // int c = internal::random<int>(0,depth-1);
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86 |
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87 | // sparse * sparse
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88 | VERIFY_IS_APPROX(m4=m2*m3, refMat4=refMat2*refMat3);
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89 | VERIFY_IS_APPROX(m4=m2t.transpose()*m3, refMat4=refMat2t.transpose()*refMat3);
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90 | VERIFY_IS_APPROX(m4=m2t.transpose()*m3t.transpose(), refMat4=refMat2t.transpose()*refMat3t.transpose());
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91 | VERIFY_IS_APPROX(m4=m2*m3t.transpose(), refMat4=refMat2*refMat3t.transpose());
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92 |
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93 | VERIFY_IS_APPROX(m4 = m2*m3/s1, refMat4 = refMat2*refMat3/s1);
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94 | VERIFY_IS_APPROX(m4 = m2*m3*s1, refMat4 = refMat2*refMat3*s1);
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95 | VERIFY_IS_APPROX(m4 = s2*m2*m3*s1, refMat4 = s2*refMat2*refMat3*s1);
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96 |
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97 | VERIFY_IS_APPROX(m4=(m2*m3).pruned(0), refMat4=refMat2*refMat3);
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98 | VERIFY_IS_APPROX(m4=(m2t.transpose()*m3).pruned(0), refMat4=refMat2t.transpose()*refMat3);
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99 | VERIFY_IS_APPROX(m4=(m2t.transpose()*m3t.transpose()).pruned(0), refMat4=refMat2t.transpose()*refMat3t.transpose());
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100 | VERIFY_IS_APPROX(m4=(m2*m3t.transpose()).pruned(0), refMat4=refMat2*refMat3t.transpose());
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101 |
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102 | // test aliasing
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103 | m4 = m2; refMat4 = refMat2;
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104 | VERIFY_IS_APPROX(m4=m4*m3, refMat4=refMat4*refMat3);
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105 |
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106 | // sparse * dense
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107 | VERIFY_IS_APPROX(dm4=m2*refMat3, refMat4=refMat2*refMat3);
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108 | VERIFY_IS_APPROX(dm4=m2*refMat3t.transpose(), refMat4=refMat2*refMat3t.transpose());
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109 | VERIFY_IS_APPROX(dm4=m2t.transpose()*refMat3, refMat4=refMat2t.transpose()*refMat3);
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110 | VERIFY_IS_APPROX(dm4=m2t.transpose()*refMat3t.transpose(), refMat4=refMat2t.transpose()*refMat3t.transpose());
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111 |
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112 | VERIFY_IS_APPROX(dm4=m2*(refMat3+refMat3), refMat4=refMat2*(refMat3+refMat3));
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113 | VERIFY_IS_APPROX(dm4=m2t.transpose()*(refMat3+refMat5)*0.5, refMat4=refMat2t.transpose()*(refMat3+refMat5)*0.5);
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114 |
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115 | // dense * sparse
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116 | VERIFY_IS_APPROX(dm4=refMat2*m3, refMat4=refMat2*refMat3);
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117 | VERIFY_IS_APPROX(dm4=refMat2*m3t.transpose(), refMat4=refMat2*refMat3t.transpose());
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118 | VERIFY_IS_APPROX(dm4=refMat2t.transpose()*m3, refMat4=refMat2t.transpose()*refMat3);
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119 | VERIFY_IS_APPROX(dm4=refMat2t.transpose()*m3t.transpose(), refMat4=refMat2t.transpose()*refMat3t.transpose());
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120 |
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121 | // sparse * dense and dense * sparse outer product
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122 | test_outer<SparseMatrixType,DenseMatrix>::run(m2,m4,refMat2,refMat4);
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123 |
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124 | VERIFY_IS_APPROX(m6=m6*m6, refMat6=refMat6*refMat6);
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125 |
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126 | // sparse matrix * sparse vector
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127 | ColSpVector cv0(cols), cv1;
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128 | DenseVector dcv0(cols), dcv1;
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129 | initSparse(2*density,dcv0, cv0);
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130 |
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131 | RowSpVector rv0(depth), rv1;
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132 | RowDenseVector drv0(depth), drv1(rv1);
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133 | initSparse(2*density,drv0, rv0);
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134 |
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135 | VERIFY_IS_APPROX(cv1=rv0*m3, dcv1=drv0*refMat3);
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136 | VERIFY_IS_APPROX(rv1=rv0*m3, drv1=drv0*refMat3);
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137 | VERIFY_IS_APPROX(cv1=m3*cv0, dcv1=refMat3*dcv0);
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138 | VERIFY_IS_APPROX(cv1=m3t.adjoint()*cv0, dcv1=refMat3t.adjoint()*dcv0);
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139 | VERIFY_IS_APPROX(rv1=m3*cv0, drv1=refMat3*dcv0);
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140 | }
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141 |
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142 | // test matrix - diagonal product
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143 | {
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144 | DenseMatrix refM2 = DenseMatrix::Zero(rows, cols);
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145 | DenseMatrix refM3 = DenseMatrix::Zero(rows, cols);
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146 | DenseMatrix d3 = DenseMatrix::Zero(rows, cols);
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147 | DiagonalMatrix<Scalar,Dynamic> d1(DenseVector::Random(cols));
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148 | DiagonalMatrix<Scalar,Dynamic> d2(DenseVector::Random(rows));
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149 | SparseMatrixType m2(rows, cols);
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150 | SparseMatrixType m3(rows, cols);
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151 | initSparse<Scalar>(density, refM2, m2);
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152 | initSparse<Scalar>(density, refM3, m3);
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153 | VERIFY_IS_APPROX(m3=m2*d1, refM3=refM2*d1);
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154 | VERIFY_IS_APPROX(m3=m2.transpose()*d2, refM3=refM2.transpose()*d2);
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155 | VERIFY_IS_APPROX(m3=d2*m2, refM3=d2*refM2);
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156 | VERIFY_IS_APPROX(m3=d1*m2.transpose(), refM3=d1*refM2.transpose());
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157 |
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158 | // also check with a SparseWrapper:
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159 | DenseVector v1 = DenseVector::Random(cols);
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160 | DenseVector v2 = DenseVector::Random(rows);
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161 | VERIFY_IS_APPROX(m3=m2*v1.asDiagonal(), refM3=refM2*v1.asDiagonal());
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162 | VERIFY_IS_APPROX(m3=m2.transpose()*v2.asDiagonal(), refM3=refM2.transpose()*v2.asDiagonal());
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163 | VERIFY_IS_APPROX(m3=v2.asDiagonal()*m2, refM3=v2.asDiagonal()*refM2);
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164 | VERIFY_IS_APPROX(m3=v1.asDiagonal()*m2.transpose(), refM3=v1.asDiagonal()*refM2.transpose());
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165 |
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166 | VERIFY_IS_APPROX(m3=v2.asDiagonal()*m2*v1.asDiagonal(), refM3=v2.asDiagonal()*refM2*v1.asDiagonal());
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167 |
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168 | // evaluate to a dense matrix to check the .row() and .col() iterator functions
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169 | VERIFY_IS_APPROX(d3=m2*d1, refM3=refM2*d1);
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170 | VERIFY_IS_APPROX(d3=m2.transpose()*d2, refM3=refM2.transpose()*d2);
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171 | VERIFY_IS_APPROX(d3=d2*m2, refM3=d2*refM2);
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172 | VERIFY_IS_APPROX(d3=d1*m2.transpose(), refM3=d1*refM2.transpose());
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173 | }
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174 |
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175 | // test self adjoint products
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176 | {
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177 | DenseMatrix b = DenseMatrix::Random(rows, rows);
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178 | DenseMatrix x = DenseMatrix::Random(rows, rows);
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179 | DenseMatrix refX = DenseMatrix::Random(rows, rows);
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180 | DenseMatrix refUp = DenseMatrix::Zero(rows, rows);
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181 | DenseMatrix refLo = DenseMatrix::Zero(rows, rows);
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182 | DenseMatrix refS = DenseMatrix::Zero(rows, rows);
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183 | SparseMatrixType mUp(rows, rows);
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184 | SparseMatrixType mLo(rows, rows);
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185 | SparseMatrixType mS(rows, rows);
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186 | do {
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187 | initSparse<Scalar>(density, refUp, mUp, ForceRealDiag|/*ForceNonZeroDiag|*/MakeUpperTriangular);
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188 | } while (refUp.isZero());
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189 | refLo = refUp.adjoint();
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190 | mLo = mUp.adjoint();
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191 | refS = refUp + refLo;
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192 | refS.diagonal() *= 0.5;
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193 | mS = mUp + mLo;
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194 | // TODO be able to address the diagonal....
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195 | for (int k=0; k<mS.outerSize(); ++k)
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196 | for (typename SparseMatrixType::InnerIterator it(mS,k); it; ++it)
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197 | if (it.index() == k)
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198 | it.valueRef() *= 0.5;
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199 |
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200 | VERIFY_IS_APPROX(refS.adjoint(), refS);
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201 | VERIFY_IS_APPROX(mS.adjoint(), mS);
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202 | VERIFY_IS_APPROX(mS, refS);
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203 | VERIFY_IS_APPROX(x=mS*b, refX=refS*b);
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204 |
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205 | VERIFY_IS_APPROX(x=mUp.template selfadjointView<Upper>()*b, refX=refS*b);
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206 | VERIFY_IS_APPROX(x=mLo.template selfadjointView<Lower>()*b, refX=refS*b);
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207 | VERIFY_IS_APPROX(x=mS.template selfadjointView<Upper|Lower>()*b, refX=refS*b);
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208 |
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209 | // sparse selfadjointView * sparse
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210 | SparseMatrixType mSres(rows,rows);
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211 | VERIFY_IS_APPROX(mSres = mLo.template selfadjointView<Lower>()*mS,
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212 | refX = refLo.template selfadjointView<Lower>()*refS);
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213 | // sparse * sparse selfadjointview
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214 | VERIFY_IS_APPROX(mSres = mS * mLo.template selfadjointView<Lower>(),
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215 | refX = refS * refLo.template selfadjointView<Lower>());
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216 | }
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217 |
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218 | }
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219 |
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220 | // New test for Bug in SparseTimeDenseProduct
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221 | template<typename SparseMatrixType, typename DenseMatrixType> void sparse_product_regression_test()
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222 | {
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223 | // This code does not compile with afflicted versions of the bug
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224 | SparseMatrixType sm1(3,2);
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225 | DenseMatrixType m2(2,2);
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226 | sm1.setZero();
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227 | m2.setZero();
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228 |
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229 | DenseMatrixType m3 = sm1*m2;
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230 |
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231 |
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232 | // This code produces a segfault with afflicted versions of another SparseTimeDenseProduct
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233 | // bug
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234 |
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235 | SparseMatrixType sm2(20000,2);
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236 | sm2.setZero();
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237 | DenseMatrixType m4(sm2*m2);
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238 |
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239 | VERIFY_IS_APPROX( m4(0,0), 0.0 );
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240 | }
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241 |
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242 | void test_sparse_product()
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243 | {
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244 | for(int i = 0; i < g_repeat; i++) {
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245 | CALL_SUBTEST_1( (sparse_product<SparseMatrix<double,ColMajor> >()) );
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246 | CALL_SUBTEST_1( (sparse_product<SparseMatrix<double,RowMajor> >()) );
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247 | CALL_SUBTEST_2( (sparse_product<SparseMatrix<std::complex<double>, ColMajor > >()) );
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248 | CALL_SUBTEST_2( (sparse_product<SparseMatrix<std::complex<double>, RowMajor > >()) );
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249 | CALL_SUBTEST_3( (sparse_product<SparseMatrix<float,ColMajor,long int> >()) );
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250 | CALL_SUBTEST_4( (sparse_product_regression_test<SparseMatrix<double,RowMajor>, Matrix<double, Dynamic, Dynamic, RowMajor> >()) );
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251 | }
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252 | }
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