|  | // 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) | 
|  | } | 
|  | } |