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 | #include "main.h"
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11 |
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12 | template<typename MatrixType> void syrk(const MatrixType& m)
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13 | {
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14 | typedef typename MatrixType::Index Index;
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15 | typedef typename MatrixType::Scalar Scalar;
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16 | typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::ColsAtCompileTime, RowMajor> RMatrixType;
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17 | typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, Dynamic> Rhs1;
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18 | typedef Matrix<Scalar, Dynamic, MatrixType::RowsAtCompileTime> Rhs2;
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19 | typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, Dynamic,RowMajor> Rhs3;
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20 |
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21 | Index rows = m.rows();
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22 | Index cols = m.cols();
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23 |
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24 | MatrixType m1 = MatrixType::Random(rows, cols),
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25 | m2 = MatrixType::Random(rows, cols),
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26 | m3 = MatrixType::Random(rows, cols);
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27 | RMatrixType rm2 = MatrixType::Random(rows, cols);
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28 |
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29 | Rhs1 rhs1 = Rhs1::Random(internal::random<int>(1,320), cols); Rhs1 rhs11 = Rhs1::Random(rhs1.rows(), cols);
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30 | Rhs2 rhs2 = Rhs2::Random(rows, internal::random<int>(1,320)); Rhs2 rhs22 = Rhs2::Random(rows, rhs2.cols());
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31 | Rhs3 rhs3 = Rhs3::Random(internal::random<int>(1,320), rows);
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32 |
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33 | Scalar s1 = internal::random<Scalar>();
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34 |
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35 | Index c = internal::random<Index>(0,cols-1);
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36 |
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37 | m2.setZero();
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38 | VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(rhs2,s1)._expression()),
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39 | ((s1 * rhs2 * rhs2.adjoint()).eval().template triangularView<Lower>().toDenseMatrix()));
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40 | m2.setZero();
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41 | VERIFY_IS_APPROX(((m2.template triangularView<Lower>() += s1 * rhs2 * rhs22.adjoint()).nestedExpression()),
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42 | ((s1 * rhs2 * rhs22.adjoint()).eval().template triangularView<Lower>().toDenseMatrix()));
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43 |
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44 |
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45 | m2.setZero();
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46 | VERIFY_IS_APPROX(m2.template selfadjointView<Upper>().rankUpdate(rhs2,s1)._expression(),
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47 | (s1 * rhs2 * rhs2.adjoint()).eval().template triangularView<Upper>().toDenseMatrix());
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48 | m2.setZero();
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49 | VERIFY_IS_APPROX((m2.template triangularView<Upper>() += s1 * rhs22 * rhs2.adjoint()).nestedExpression(),
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50 | (s1 * rhs22 * rhs2.adjoint()).eval().template triangularView<Upper>().toDenseMatrix());
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51 |
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52 |
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53 | m2.setZero();
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54 | VERIFY_IS_APPROX(m2.template selfadjointView<Lower>().rankUpdate(rhs1.adjoint(),s1)._expression(),
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55 | (s1 * rhs1.adjoint() * rhs1).eval().template triangularView<Lower>().toDenseMatrix());
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56 | m2.setZero();
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57 | VERIFY_IS_APPROX((m2.template triangularView<Lower>() += s1 * rhs11.adjoint() * rhs1).nestedExpression(),
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58 | (s1 * rhs11.adjoint() * rhs1).eval().template triangularView<Lower>().toDenseMatrix());
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59 |
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60 |
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61 | m2.setZero();
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62 | VERIFY_IS_APPROX(m2.template selfadjointView<Upper>().rankUpdate(rhs1.adjoint(),s1)._expression(),
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63 | (s1 * rhs1.adjoint() * rhs1).eval().template triangularView<Upper>().toDenseMatrix());
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64 | VERIFY_IS_APPROX((m2.template triangularView<Upper>() = s1 * rhs1.adjoint() * rhs11).nestedExpression(),
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65 | (s1 * rhs1.adjoint() * rhs11).eval().template triangularView<Upper>().toDenseMatrix());
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66 |
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67 |
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68 | m2.setZero();
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69 | VERIFY_IS_APPROX(m2.template selfadjointView<Lower>().rankUpdate(rhs3.adjoint(),s1)._expression(),
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70 | (s1 * rhs3.adjoint() * rhs3).eval().template triangularView<Lower>().toDenseMatrix());
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71 |
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72 | m2.setZero();
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73 | VERIFY_IS_APPROX(m2.template selfadjointView<Upper>().rankUpdate(rhs3.adjoint(),s1)._expression(),
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74 | (s1 * rhs3.adjoint() * rhs3).eval().template triangularView<Upper>().toDenseMatrix());
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75 |
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76 | m2.setZero();
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77 | VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(m1.col(c),s1)._expression()),
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78 | ((s1 * m1.col(c) * m1.col(c).adjoint()).eval().template triangularView<Lower>().toDenseMatrix()));
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79 |
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80 | m2.setZero();
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81 | VERIFY_IS_APPROX((m2.template selfadjointView<Upper>().rankUpdate(m1.col(c),s1)._expression()),
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82 | ((s1 * m1.col(c) * m1.col(c).adjoint()).eval().template triangularView<Upper>().toDenseMatrix()));
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83 | rm2.setZero();
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84 | VERIFY_IS_APPROX((rm2.template selfadjointView<Upper>().rankUpdate(m1.col(c),s1)._expression()),
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85 | ((s1 * m1.col(c) * m1.col(c).adjoint()).eval().template triangularView<Upper>().toDenseMatrix()));
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86 | m2.setZero();
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87 | VERIFY_IS_APPROX((m2.template triangularView<Upper>() += s1 * m3.col(c) * m1.col(c).adjoint()).nestedExpression(),
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88 | ((s1 * m3.col(c) * m1.col(c).adjoint()).eval().template triangularView<Upper>().toDenseMatrix()));
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89 | rm2.setZero();
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90 | VERIFY_IS_APPROX((rm2.template triangularView<Upper>() += s1 * m1.col(c) * m3.col(c).adjoint()).nestedExpression(),
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91 | ((s1 * m1.col(c) * m3.col(c).adjoint()).eval().template triangularView<Upper>().toDenseMatrix()));
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92 |
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93 | m2.setZero();
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94 | VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(m1.col(c).conjugate(),s1)._expression()),
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95 | ((s1 * m1.col(c).conjugate() * m1.col(c).conjugate().adjoint()).eval().template triangularView<Lower>().toDenseMatrix()));
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96 |
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97 | m2.setZero();
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98 | VERIFY_IS_APPROX((m2.template selfadjointView<Upper>().rankUpdate(m1.col(c).conjugate(),s1)._expression()),
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99 | ((s1 * m1.col(c).conjugate() * m1.col(c).conjugate().adjoint()).eval().template triangularView<Upper>().toDenseMatrix()));
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100 |
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101 |
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102 | m2.setZero();
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103 | VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(m1.row(c),s1)._expression()),
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104 | ((s1 * m1.row(c).transpose() * m1.row(c).transpose().adjoint()).eval().template triangularView<Lower>().toDenseMatrix()));
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105 | rm2.setZero();
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106 | VERIFY_IS_APPROX((rm2.template selfadjointView<Lower>().rankUpdate(m1.row(c),s1)._expression()),
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107 | ((s1 * m1.row(c).transpose() * m1.row(c).transpose().adjoint()).eval().template triangularView<Lower>().toDenseMatrix()));
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108 | m2.setZero();
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109 | VERIFY_IS_APPROX((m2.template triangularView<Lower>() += s1 * m3.row(c).transpose() * m1.row(c).transpose().adjoint()).nestedExpression(),
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110 | ((s1 * m3.row(c).transpose() * m1.row(c).transpose().adjoint()).eval().template triangularView<Lower>().toDenseMatrix()));
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111 | rm2.setZero();
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112 | VERIFY_IS_APPROX((rm2.template triangularView<Lower>() += s1 * m3.row(c).transpose() * m1.row(c).transpose().adjoint()).nestedExpression(),
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113 | ((s1 * m3.row(c).transpose() * m1.row(c).transpose().adjoint()).eval().template triangularView<Lower>().toDenseMatrix()));
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114 |
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115 |
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116 | m2.setZero();
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117 | VERIFY_IS_APPROX((m2.template selfadjointView<Upper>().rankUpdate(m1.row(c).adjoint(),s1)._expression()),
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118 | ((s1 * m1.row(c).adjoint() * m1.row(c).adjoint().adjoint()).eval().template triangularView<Upper>().toDenseMatrix()));
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119 | }
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120 |
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121 | void test_product_syrk()
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122 | {
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123 | for(int i = 0; i < g_repeat ; i++)
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124 | {
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125 | int s;
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126 | s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE);
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127 | CALL_SUBTEST_1( syrk(MatrixXf(s, s)) );
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128 | s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE);
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129 | CALL_SUBTEST_2( syrk(MatrixXd(s, s)) );
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130 | s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2);
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131 | CALL_SUBTEST_3( syrk(MatrixXcf(s, s)) );
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132 | s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2);
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133 | CALL_SUBTEST_4( syrk(MatrixXcd(s, s)) );
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134 | }
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135 | }
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