| // This file is part of Eigen, a lightweight C++ template library | |
| // for linear algebra. | |
| // | |
| // Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr> | |
| // | |
| // This Source Code Form is subject to the terms of the Mozilla | |
| // Public License v. 2.0. If a copy of the MPL was not distributed | |
| // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. | |
| #include "main.h" | |
| template<typename MatrixType> void syrk(const MatrixType& m) | |
| { | |
| typedef typename MatrixType::Scalar Scalar; | |
| typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::ColsAtCompileTime, RowMajor> RMatrixType; | |
| typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, Dynamic> Rhs1; | |
| typedef Matrix<Scalar, Dynamic, MatrixType::RowsAtCompileTime> Rhs2; | |
| typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, Dynamic,RowMajor> Rhs3; | |
| Index rows = m.rows(); | |
| Index cols = m.cols(); | |
| MatrixType m1 = MatrixType::Random(rows, cols), | |
| m2 = MatrixType::Random(rows, cols), | |
| m3 = MatrixType::Random(rows, cols); | |
| RMatrixType rm2 = MatrixType::Random(rows, cols); | |
| Rhs1 rhs1 = Rhs1::Random(internal::random<int>(1,320), cols); Rhs1 rhs11 = Rhs1::Random(rhs1.rows(), cols); | |
| Rhs2 rhs2 = Rhs2::Random(rows, internal::random<int>(1,320)); Rhs2 rhs22 = Rhs2::Random(rows, rhs2.cols()); | |
| Rhs3 rhs3 = Rhs3::Random(internal::random<int>(1,320), rows); | |
| Scalar s1 = internal::random<Scalar>(); | |
| Index c = internal::random<Index>(0,cols-1); | |
| m2.setZero(); | |
| VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(rhs2,s1)._expression()), | |
| ((s1 * rhs2 * rhs2.adjoint()).eval().template triangularView<Lower>().toDenseMatrix())); | |
| m2.setZero(); | |
| VERIFY_IS_APPROX(((m2.template triangularView<Lower>() += s1 * rhs2 * rhs22.adjoint()).nestedExpression()), | |
| ((s1 * rhs2 * rhs22.adjoint()).eval().template triangularView<Lower>().toDenseMatrix())); | |
| m2.setZero(); | |
| VERIFY_IS_APPROX(m2.template selfadjointView<Upper>().rankUpdate(rhs2,s1)._expression(), | |
| (s1 * rhs2 * rhs2.adjoint()).eval().template triangularView<Upper>().toDenseMatrix()); | |
| m2.setZero(); | |
| VERIFY_IS_APPROX((m2.template triangularView<Upper>() += s1 * rhs22 * rhs2.adjoint()).nestedExpression(), | |
| (s1 * rhs22 * rhs2.adjoint()).eval().template triangularView<Upper>().toDenseMatrix()); | |
| m2.setZero(); | |
| VERIFY_IS_APPROX(m2.template selfadjointView<Lower>().rankUpdate(rhs1.adjoint(),s1)._expression(), | |
| (s1 * rhs1.adjoint() * rhs1).eval().template triangularView<Lower>().toDenseMatrix()); | |
| m2.setZero(); | |
| VERIFY_IS_APPROX((m2.template triangularView<Lower>() += s1 * rhs11.adjoint() * rhs1).nestedExpression(), | |
| (s1 * rhs11.adjoint() * rhs1).eval().template triangularView<Lower>().toDenseMatrix()); | |
| m2.setZero(); | |
| VERIFY_IS_APPROX(m2.template selfadjointView<Upper>().rankUpdate(rhs1.adjoint(),s1)._expression(), | |
| (s1 * rhs1.adjoint() * rhs1).eval().template triangularView<Upper>().toDenseMatrix()); | |
| VERIFY_IS_APPROX((m2.template triangularView<Upper>() = s1 * rhs1.adjoint() * rhs11).nestedExpression(), | |
| (s1 * rhs1.adjoint() * rhs11).eval().template triangularView<Upper>().toDenseMatrix()); | |
| m2.setZero(); | |
| VERIFY_IS_APPROX(m2.template selfadjointView<Lower>().rankUpdate(rhs3.adjoint(),s1)._expression(), | |
| (s1 * rhs3.adjoint() * rhs3).eval().template triangularView<Lower>().toDenseMatrix()); | |
| m2.setZero(); | |
| VERIFY_IS_APPROX(m2.template selfadjointView<Upper>().rankUpdate(rhs3.adjoint(),s1)._expression(), | |
| (s1 * rhs3.adjoint() * rhs3).eval().template triangularView<Upper>().toDenseMatrix()); | |
| m2.setZero(); | |
| VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(m1.col(c),s1)._expression()), | |
| ((s1 * m1.col(c) * m1.col(c).adjoint()).eval().template triangularView<Lower>().toDenseMatrix())); | |
| m2.setZero(); | |
| VERIFY_IS_APPROX((m2.template selfadjointView<Upper>().rankUpdate(m1.col(c),s1)._expression()), | |
| ((s1 * m1.col(c) * m1.col(c).adjoint()).eval().template triangularView<Upper>().toDenseMatrix())); | |
| rm2.setZero(); | |
| VERIFY_IS_APPROX((rm2.template selfadjointView<Upper>().rankUpdate(m1.col(c),s1)._expression()), | |
| ((s1 * m1.col(c) * m1.col(c).adjoint()).eval().template triangularView<Upper>().toDenseMatrix())); | |
| m2.setZero(); | |
| VERIFY_IS_APPROX((m2.template triangularView<Upper>() += s1 * m3.col(c) * m1.col(c).adjoint()).nestedExpression(), | |
| ((s1 * m3.col(c) * m1.col(c).adjoint()).eval().template triangularView<Upper>().toDenseMatrix())); | |
| rm2.setZero(); | |
| VERIFY_IS_APPROX((rm2.template triangularView<Upper>() += s1 * m1.col(c) * m3.col(c).adjoint()).nestedExpression(), | |
| ((s1 * m1.col(c) * m3.col(c).adjoint()).eval().template triangularView<Upper>().toDenseMatrix())); | |
| m2.setZero(); | |
| VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(m1.col(c).conjugate(),s1)._expression()), | |
| ((s1 * m1.col(c).conjugate() * m1.col(c).conjugate().adjoint()).eval().template triangularView<Lower>().toDenseMatrix())); | |
| m2.setZero(); | |
| VERIFY_IS_APPROX((m2.template selfadjointView<Upper>().rankUpdate(m1.col(c).conjugate(),s1)._expression()), | |
| ((s1 * m1.col(c).conjugate() * m1.col(c).conjugate().adjoint()).eval().template triangularView<Upper>().toDenseMatrix())); | |
| m2.setZero(); | |
| VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(m1.row(c),s1)._expression()), | |
| ((s1 * m1.row(c).transpose() * m1.row(c).transpose().adjoint()).eval().template triangularView<Lower>().toDenseMatrix())); | |
| rm2.setZero(); | |
| VERIFY_IS_APPROX((rm2.template selfadjointView<Lower>().rankUpdate(m1.row(c),s1)._expression()), | |
| ((s1 * m1.row(c).transpose() * m1.row(c).transpose().adjoint()).eval().template triangularView<Lower>().toDenseMatrix())); | |
| m2.setZero(); | |
| VERIFY_IS_APPROX((m2.template triangularView<Lower>() += s1 * m3.row(c).transpose() * m1.row(c).transpose().adjoint()).nestedExpression(), | |
| ((s1 * m3.row(c).transpose() * m1.row(c).transpose().adjoint()).eval().template triangularView<Lower>().toDenseMatrix())); | |
| rm2.setZero(); | |
| VERIFY_IS_APPROX((rm2.template triangularView<Lower>() += s1 * m3.row(c).transpose() * m1.row(c).transpose().adjoint()).nestedExpression(), | |
| ((s1 * m3.row(c).transpose() * m1.row(c).transpose().adjoint()).eval().template triangularView<Lower>().toDenseMatrix())); | |
| m2.setZero(); | |
| VERIFY_IS_APPROX((m2.template selfadjointView<Upper>().rankUpdate(m1.row(c).adjoint(),s1)._expression()), | |
| ((s1 * m1.row(c).adjoint() * m1.row(c).adjoint().adjoint()).eval().template triangularView<Upper>().toDenseMatrix())); | |
| // destination with a non-default inner-stride | |
| // see bug 1741 | |
| { | |
| typedef Matrix<Scalar,Dynamic,Dynamic> MatrixX; | |
| MatrixX buffer(2*rows,2*cols); | |
| Map<MatrixType,0,Stride<Dynamic,2> > map1(buffer.data(),rows,cols,Stride<Dynamic,2>(2*rows,2)); | |
| buffer.setZero(); | |
| VERIFY_IS_APPROX((map1.template selfadjointView<Lower>().rankUpdate(rhs2,s1)._expression()), | |
| ((s1 * rhs2 * rhs2.adjoint()).eval().template triangularView<Lower>().toDenseMatrix())); | |
| } | |
| } | |
| EIGEN_DECLARE_TEST(product_syrk) | |
| { | |
| for(int i = 0; i < g_repeat ; i++) | |
| { | |
| int s; | |
| s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE); | |
| CALL_SUBTEST_1( syrk(MatrixXf(s, s)) ); | |
| CALL_SUBTEST_2( syrk(MatrixXd(s, s)) ); | |
| TEST_SET_BUT_UNUSED_VARIABLE(s) | |
| s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2); | |
| CALL_SUBTEST_3( syrk(MatrixXcf(s, s)) ); | |
| CALL_SUBTEST_4( syrk(MatrixXcd(s, s)) ); | |
| TEST_SET_BUT_UNUSED_VARIABLE(s) | |
| } | |
| } |