| // 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))); |
| CALL_SUBTEST_5(syrk(Matrix<bfloat16, Dynamic, Dynamic>(s, s))); |
| TEST_SET_BUT_UNUSED_VARIABLE(s) |
| } |
| } |