de014efdaf
* add an efficient selfadjoint * vector implementation (= blas symv) perf are inbetween MKL and GOTO => the interface is still missing (have to be rethougth)
71 lines
2.8 KiB
C++
71 lines
2.8 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra. Eigen itself is part of the KDE project.
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//
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// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@gmail.com>
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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 product_selfadjoint(const MatrixType& m)
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{
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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::RowsAtCompileTime, 1> VectorType;
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int rows = m.rows();
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int 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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VectorType v1 = VectorType::Random(rows),
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v2 = VectorType::Random(rows);
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m1 = m1.adjoint()*m1;
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// col-lower
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m2.setZero();
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m2.template part<LowerTriangular>() = m1;
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ei_product_selfadjoint_vector<Scalar,MatrixType::Flags&RowMajorBit,LowerTriangularBit>
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(cols,m2.data(),cols, v1.data(), v2.data());
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VERIFY_IS_APPROX(v2, m1 * v1);
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// col-upper
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m2.setZero();
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m2.template part<UpperTriangular>() = m1;
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ei_product_selfadjoint_vector<Scalar,MatrixType::Flags&RowMajorBit,UpperTriangularBit>(cols,m2.data(),cols, v1.data(), v2.data());
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VERIFY_IS_APPROX(v2, m1 * v1);
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}
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void test_product_selfadjoint()
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{
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for(int i = 0; i < g_repeat ; i++) {
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CALL_SUBTEST( product_selfadjoint(Matrix<float, 1, 1>()) );
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CALL_SUBTEST( product_selfadjoint(Matrix<float, 2, 2>()) );
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CALL_SUBTEST( product_selfadjoint(Matrix3d()) );
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CALL_SUBTEST( product_selfadjoint(MatrixXcf(4, 4)) );
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CALL_SUBTEST( product_selfadjoint(MatrixXcd(21,21)) );
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CALL_SUBTEST( product_selfadjoint(MatrixXd(17,17)) );
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CALL_SUBTEST( product_selfadjoint(Matrix<float,Dynamic,Dynamic,RowMajor>(18,18)) );
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CALL_SUBTEST( product_selfadjoint(Matrix<std::complex<double>,Dynamic,Dynamic,RowMajor>(19, 19)) );
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}
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}
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