165 lines
8.2 KiB
C++
165 lines
8.2 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#include "main.h"
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template <typename MatrixType>
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void syrk(const MatrixType& m) {
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typedef typename MatrixType::Scalar Scalar;
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typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::ColsAtCompileTime, RowMajor> RMatrixType;
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typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, Dynamic> Rhs1;
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typedef Matrix<Scalar, Dynamic, MatrixType::RowsAtCompileTime> Rhs2;
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typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, Dynamic, RowMajor> Rhs3;
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Index rows = m.rows();
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Index cols = m.cols();
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MatrixType m1 = MatrixType::Random(rows, cols), m2 = MatrixType::Random(rows, cols),
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m3 = MatrixType::Random(rows, cols);
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RMatrixType rm2 = MatrixType::Random(rows, cols);
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Rhs1 rhs1 = Rhs1::Random(internal::random<int>(1, 320), cols);
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Rhs1 rhs11 = Rhs1::Random(rhs1.rows(), cols);
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Rhs2 rhs2 = Rhs2::Random(rows, internal::random<int>(1, 320));
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Rhs2 rhs22 = Rhs2::Random(rows, rhs2.cols());
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Rhs3 rhs3 = Rhs3::Random(internal::random<int>(1, 320), rows);
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Scalar s1 = internal::random<Scalar>();
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Index c = internal::random<Index>(0, cols - 1);
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m2.setZero();
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VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(rhs2, s1)._expression()),
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((s1 * rhs2 * rhs2.adjoint()).eval().template triangularView<Lower>().toDenseMatrix()));
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m2.setZero();
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VERIFY_IS_APPROX(((m2.template triangularView<Lower>() += s1 * rhs2 * rhs22.adjoint()).nestedExpression()),
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((s1 * rhs2 * rhs22.adjoint()).eval().template triangularView<Lower>().toDenseMatrix()));
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m2.setZero();
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VERIFY_IS_APPROX(m2.template selfadjointView<Upper>().rankUpdate(rhs2, s1)._expression(),
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(s1 * rhs2 * rhs2.adjoint()).eval().template triangularView<Upper>().toDenseMatrix());
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m2.setZero();
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VERIFY_IS_APPROX((m2.template triangularView<Upper>() += s1 * rhs22 * rhs2.adjoint()).nestedExpression(),
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(s1 * rhs22 * rhs2.adjoint()).eval().template triangularView<Upper>().toDenseMatrix());
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m2.setZero();
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VERIFY_IS_APPROX(m2.template selfadjointView<Lower>().rankUpdate(rhs1.adjoint(), s1)._expression(),
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(s1 * rhs1.adjoint() * rhs1).eval().template triangularView<Lower>().toDenseMatrix());
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m2.setZero();
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VERIFY_IS_APPROX((m2.template triangularView<Lower>() += s1 * rhs11.adjoint() * rhs1).nestedExpression(),
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(s1 * rhs11.adjoint() * rhs1).eval().template triangularView<Lower>().toDenseMatrix());
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m2.setZero();
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VERIFY_IS_APPROX(m2.template selfadjointView<Upper>().rankUpdate(rhs1.adjoint(), s1)._expression(),
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(s1 * rhs1.adjoint() * rhs1).eval().template triangularView<Upper>().toDenseMatrix());
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VERIFY_IS_APPROX((m2.template triangularView<Upper>() = s1 * rhs1.adjoint() * rhs11).nestedExpression(),
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(s1 * rhs1.adjoint() * rhs11).eval().template triangularView<Upper>().toDenseMatrix());
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m2.setZero();
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VERIFY_IS_APPROX(m2.template selfadjointView<Lower>().rankUpdate(rhs3.adjoint(), s1)._expression(),
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(s1 * rhs3.adjoint() * rhs3).eval().template triangularView<Lower>().toDenseMatrix());
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m2.setZero();
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VERIFY_IS_APPROX(m2.template selfadjointView<Upper>().rankUpdate(rhs3.adjoint(), s1)._expression(),
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(s1 * rhs3.adjoint() * rhs3).eval().template triangularView<Upper>().toDenseMatrix());
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m2.setZero();
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VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(m1.col(c), s1)._expression()),
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((s1 * m1.col(c) * m1.col(c).adjoint()).eval().template triangularView<Lower>().toDenseMatrix()));
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m2.setZero();
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VERIFY_IS_APPROX((m2.template selfadjointView<Upper>().rankUpdate(m1.col(c), s1)._expression()),
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((s1 * m1.col(c) * m1.col(c).adjoint()).eval().template triangularView<Upper>().toDenseMatrix()));
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rm2.setZero();
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VERIFY_IS_APPROX((rm2.template selfadjointView<Upper>().rankUpdate(m1.col(c), s1)._expression()),
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((s1 * m1.col(c) * m1.col(c).adjoint()).eval().template triangularView<Upper>().toDenseMatrix()));
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m2.setZero();
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VERIFY_IS_APPROX((m2.template triangularView<Upper>() += s1 * m3.col(c) * m1.col(c).adjoint()).nestedExpression(),
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((s1 * m3.col(c) * m1.col(c).adjoint()).eval().template triangularView<Upper>().toDenseMatrix()));
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rm2.setZero();
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VERIFY_IS_APPROX((rm2.template triangularView<Upper>() += s1 * m1.col(c) * m3.col(c).adjoint()).nestedExpression(),
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((s1 * m1.col(c) * m3.col(c).adjoint()).eval().template triangularView<Upper>().toDenseMatrix()));
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m2.setZero();
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VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(m1.col(c).conjugate(), s1)._expression()),
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((s1 * m1.col(c).conjugate() * m1.col(c).conjugate().adjoint())
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.eval()
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.template triangularView<Lower>()
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.toDenseMatrix()));
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m2.setZero();
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VERIFY_IS_APPROX((m2.template selfadjointView<Upper>().rankUpdate(m1.col(c).conjugate(), s1)._expression()),
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((s1 * m1.col(c).conjugate() * m1.col(c).conjugate().adjoint())
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.eval()
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.template triangularView<Upper>()
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.toDenseMatrix()));
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m2.setZero();
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VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(m1.row(c), s1)._expression()),
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((s1 * m1.row(c).transpose() * m1.row(c).transpose().adjoint())
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.eval()
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.template triangularView<Lower>()
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.toDenseMatrix()));
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rm2.setZero();
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VERIFY_IS_APPROX((rm2.template selfadjointView<Lower>().rankUpdate(m1.row(c), s1)._expression()),
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((s1 * m1.row(c).transpose() * m1.row(c).transpose().adjoint())
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.eval()
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.template triangularView<Lower>()
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.toDenseMatrix()));
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m2.setZero();
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VERIFY_IS_APPROX((m2.template triangularView<Lower>() += s1 * m3.row(c).transpose() * m1.row(c).transpose().adjoint())
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.nestedExpression(),
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((s1 * m3.row(c).transpose() * m1.row(c).transpose().adjoint())
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.eval()
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.template triangularView<Lower>()
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.toDenseMatrix()));
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rm2.setZero();
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VERIFY_IS_APPROX(
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(rm2.template triangularView<Lower>() += s1 * m3.row(c).transpose() * m1.row(c).transpose().adjoint())
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.nestedExpression(),
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((s1 * m3.row(c).transpose() * m1.row(c).transpose().adjoint())
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.eval()
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.template triangularView<Lower>()
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.toDenseMatrix()));
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m2.setZero();
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VERIFY_IS_APPROX((m2.template selfadjointView<Upper>().rankUpdate(m1.row(c).adjoint(), s1)._expression()),
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((s1 * m1.row(c).adjoint() * m1.row(c).adjoint().adjoint())
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.eval()
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.template triangularView<Upper>()
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.toDenseMatrix()));
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// destination with a non-default inner-stride
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// see bug 1741
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{
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typedef Matrix<Scalar, Dynamic, Dynamic> MatrixX;
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MatrixX buffer(2 * rows, 2 * cols);
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Map<MatrixType, 0, Stride<Dynamic, 2> > map1(buffer.data(), rows, cols, Stride<Dynamic, 2>(2 * rows, 2));
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buffer.setZero();
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VERIFY_IS_APPROX((map1.template selfadjointView<Lower>().rankUpdate(rhs2, s1)._expression()),
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((s1 * rhs2 * rhs2.adjoint()).eval().template triangularView<Lower>().toDenseMatrix()));
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}
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}
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EIGEN_DECLARE_TEST(product_syrk) {
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for (int i = 0; i < g_repeat; i++) {
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int s;
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s = internal::random<int>(1, EIGEN_TEST_MAX_SIZE);
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CALL_SUBTEST_1(syrk(MatrixXf(s, s)));
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CALL_SUBTEST_2(syrk(MatrixXd(s, s)));
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TEST_SET_BUT_UNUSED_VARIABLE(s)
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s = internal::random<int>(1, EIGEN_TEST_MAX_SIZE / 2);
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CALL_SUBTEST_3(syrk(MatrixXcf(s, s)));
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CALL_SUBTEST_4(syrk(MatrixXcd(s, s)));
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CALL_SUBTEST_5(syrk(Matrix<bfloat16, Dynamic, Dynamic>(s, s)));
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TEST_SET_BUT_UNUSED_VARIABLE(s)
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}
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}
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