1 // This file is part of Eigen, a lightweight C++ template library 2 // for linear algebra. 3 // 4 // Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud (at) inria.fr> 5 // 6 // This Source Code Form is subject to the terms of the Mozilla 7 // Public License v. 2.0. If a copy of the MPL was not distributed 8 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. 9 10 #include "main.h" 11 12 template<typename MatrixType> void syrk(const MatrixType& m) 13 { 14 typedef typename MatrixType::Index Index; 15 typedef typename MatrixType::Scalar Scalar; 16 typedef typename NumTraits<Scalar>::Real RealScalar; 17 typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, Dynamic> Rhs1; 18 typedef Matrix<Scalar, Dynamic, MatrixType::RowsAtCompileTime> Rhs2; 19 typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, Dynamic,RowMajor> Rhs3; 20 21 Index rows = m.rows(); 22 Index cols = m.cols(); 23 24 MatrixType m1 = MatrixType::Random(rows, cols), 25 m2 = MatrixType::Random(rows, cols); 26 27 Rhs1 rhs1 = Rhs1::Random(internal::random<int>(1,320), cols); 28 Rhs2 rhs2 = Rhs2::Random(rows, internal::random<int>(1,320)); 29 Rhs3 rhs3 = Rhs3::Random(internal::random<int>(1,320), rows); 30 31 Scalar s1 = internal::random<Scalar>(); 32 33 Index c = internal::random<Index>(0,cols-1); 34 35 m2.setZero(); 36 VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(rhs2,s1)._expression()), 37 ((s1 * rhs2 * rhs2.adjoint()).eval().template triangularView<Lower>().toDenseMatrix())); 38 39 m2.setZero(); 40 VERIFY_IS_APPROX(m2.template selfadjointView<Upper>().rankUpdate(rhs2,s1)._expression(), 41 (s1 * rhs2 * rhs2.adjoint()).eval().template triangularView<Upper>().toDenseMatrix()); 42 43 m2.setZero(); 44 VERIFY_IS_APPROX(m2.template selfadjointView<Lower>().rankUpdate(rhs1.adjoint(),s1)._expression(), 45 (s1 * rhs1.adjoint() * rhs1).eval().template triangularView<Lower>().toDenseMatrix()); 46 47 m2.setZero(); 48 VERIFY_IS_APPROX(m2.template selfadjointView<Upper>().rankUpdate(rhs1.adjoint(),s1)._expression(), 49 (s1 * rhs1.adjoint() * rhs1).eval().template triangularView<Upper>().toDenseMatrix()); 50 51 m2.setZero(); 52 VERIFY_IS_APPROX(m2.template selfadjointView<Lower>().rankUpdate(rhs3.adjoint(),s1)._expression(), 53 (s1 * rhs3.adjoint() * rhs3).eval().template triangularView<Lower>().toDenseMatrix()); 54 55 m2.setZero(); 56 VERIFY_IS_APPROX(m2.template selfadjointView<Upper>().rankUpdate(rhs3.adjoint(),s1)._expression(), 57 (s1 * rhs3.adjoint() * rhs3).eval().template triangularView<Upper>().toDenseMatrix()); 58 59 m2.setZero(); 60 VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(m1.col(c),s1)._expression()), 61 ((s1 * m1.col(c) * m1.col(c).adjoint()).eval().template triangularView<Lower>().toDenseMatrix())); 62 63 m2.setZero(); 64 VERIFY_IS_APPROX((m2.template selfadjointView<Upper>().rankUpdate(m1.col(c),s1)._expression()), 65 ((s1 * m1.col(c) * m1.col(c).adjoint()).eval().template triangularView<Upper>().toDenseMatrix())); 66 67 m2.setZero(); 68 VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(m1.col(c).conjugate(),s1)._expression()), 69 ((s1 * m1.col(c).conjugate() * m1.col(c).conjugate().adjoint()).eval().template triangularView<Lower>().toDenseMatrix())); 70 71 m2.setZero(); 72 VERIFY_IS_APPROX((m2.template selfadjointView<Upper>().rankUpdate(m1.col(c).conjugate(),s1)._expression()), 73 ((s1 * m1.col(c).conjugate() * m1.col(c).conjugate().adjoint()).eval().template triangularView<Upper>().toDenseMatrix())); 74 75 m2.setZero(); 76 VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(m1.row(c),s1)._expression()), 77 ((s1 * m1.row(c).transpose() * m1.row(c).transpose().adjoint()).eval().template triangularView<Lower>().toDenseMatrix())); 78 79 m2.setZero(); 80 VERIFY_IS_APPROX((m2.template selfadjointView<Upper>().rankUpdate(m1.row(c).adjoint(),s1)._expression()), 81 ((s1 * m1.row(c).adjoint() * m1.row(c).adjoint().adjoint()).eval().template triangularView<Upper>().toDenseMatrix())); 82 } 83 84 void test_product_syrk() 85 { 86 for(int i = 0; i < g_repeat ; i++) 87 { 88 int s; 89 s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE); 90 CALL_SUBTEST_1( syrk(MatrixXf(s, s)) ); 91 s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE); 92 CALL_SUBTEST_2( syrk(MatrixXd(s, s)) ); 93 s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2); 94 CALL_SUBTEST_3( syrk(MatrixXcf(s, s)) ); 95 s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2); 96 CALL_SUBTEST_4( syrk(MatrixXcd(s, s)) ); 97 } 98 } 99
