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88 lines
3.6 KiB
C++
88 lines
3.6 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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// Eigen is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 3 of the License, or (at your option) any later version.
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//
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// Alternatively, you can redistribute it and/or
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// modify it under the terms of the GNU General Public License as
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// published by the Free Software Foundation; either version 2 of
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// the License, or (at your option) any later version.
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//
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// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License and a copy of the GNU General Public License along with
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// Eigen. If not, see <http://www.gnu.org/licenses/>.
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#include "main.h"
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template<typename MatrixType> void syrk(const MatrixType& m)
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{
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typedef typename MatrixType::Index Index;
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typedef typename MatrixType::Scalar Scalar;
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typedef typename NumTraits<Scalar>::Real RealScalar;
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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),
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m2 = MatrixType::Random(rows, cols);
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Rhs1 rhs1 = Rhs1::Random(ei_random<int>(1,320), cols);
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Rhs2 rhs2 = Rhs2::Random(rows, ei_random<int>(1,320));
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Rhs3 rhs3 = Rhs3::Random(ei_random<int>(1,320), rows);
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Scalar s1 = ei_random<Scalar>();
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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 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 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 selfadjointView<Upper>().rankUpdate(rhs1.adjoint(),s1)._expression(),
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(s1 * rhs1.adjoint() * rhs1).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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}
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void test_product_syrk()
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{
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for(int i = 0; i < g_repeat ; i++)
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{
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int s;
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s = ei_random<int>(1,320);
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CALL_SUBTEST_1( syrk(MatrixXf(s, s)) );
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s = ei_random<int>(1,320);
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CALL_SUBTEST_2( syrk(MatrixXd(s, s)) );
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s = ei_random<int>(1,200);
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CALL_SUBTEST_3( syrk(MatrixXcf(s, s)) );
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s = ei_random<int>(1,200);
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CALL_SUBTEST_4( syrk(MatrixXcd(s, s)) );
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}
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}
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