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28dde19e40
- Updated unit tests to check above constructor. - In the compute() method of decompositions: Made temporary matrices/vectors class members to avoid heap allocations during compute() (when dynamic matrices are used, of course). These changes can speed up decomposition computation time when a solver instance is used to solve multiple same-sized problems. An added benefit is that the compute() method can now be invoked in contexts were heap allocations are forbidden, such as in real-time control loops. CAVEAT: Not all of the decompositions in the Eigenvalues module have a heap-allocation-free compute() method. A future patch may address this issue, but some required API changes need to be incorporated first.
70 lines
2.7 KiB
C++
70 lines
2.7 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) 2008-2009 Gael Guennebaud <g.gael@free.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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#include <Eigen/Eigenvalues>
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#include <Eigen/LU>
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template<typename MatrixType> void eigensolver(const MatrixType& m)
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{
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/* this test covers the following files:
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ComplexEigenSolver.h, and indirectly ComplexSchur.h
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*/
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int rows = m.rows();
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int cols = m.cols();
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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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typedef Matrix<RealScalar, MatrixType::RowsAtCompileTime, 1> RealVectorType;
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typedef typename std::complex<typename NumTraits<typename MatrixType::Scalar>::Real> Complex;
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MatrixType a = MatrixType::Random(rows,cols);
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MatrixType symmA = a.adjoint() * a;
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ComplexEigenSolver<MatrixType> ei0(symmA);
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VERIFY_IS_APPROX(symmA * ei0.eigenvectors(), ei0.eigenvectors() * ei0.eigenvalues().asDiagonal());
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ComplexEigenSolver<MatrixType> ei1(a);
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VERIFY_IS_APPROX(a * ei1.eigenvectors(), ei1.eigenvectors() * ei1.eigenvalues().asDiagonal());
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// Regression test for issue #66
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MatrixType z = MatrixType::Zero(rows,cols);
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ComplexEigenSolver<MatrixType> eiz(z);
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VERIFY((eiz.eigenvalues().cwiseEqual(0)).all());
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}
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void test_eigensolver_complex()
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{
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for(int i = 0; i < g_repeat; i++) {
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CALL_SUBTEST_1( eigensolver(Matrix4cf()) );
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CALL_SUBTEST_2( eigensolver(MatrixXcd(14,14)) );
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CALL_SUBTEST_3( eigensolver(Matrix<std::complex<float>, 1, 1>()) );
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CALL_SUBTEST_4( eigensolver(Matrix3f()) );
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}
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// Test problem size constructors
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CALL_SUBTEST_5(ComplexEigenSolver<MatrixXf>(10));
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}
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