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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.
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) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
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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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template<typename MatrixType> void schur(int size = MatrixType::ColsAtCompileTime)
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{
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typedef typename ComplexSchur<MatrixType>::ComplexScalar ComplexScalar;
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typedef typename ComplexSchur<MatrixType>::ComplexMatrixType ComplexMatrixType;
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// Test basic functionality: T is triangular and A = U T U*
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for(int counter = 0; counter < g_repeat; ++counter) {
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MatrixType A = MatrixType::Random(size, size);
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ComplexSchur<MatrixType> schurOfA(A);
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ComplexMatrixType U = schurOfA.matrixU();
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ComplexMatrixType T = schurOfA.matrixT();
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for(int row = 1; row < size; ++row) {
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for(int col = 0; col < row; ++col) {
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VERIFY(T(row,col) == (typename MatrixType::Scalar)0);
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}
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}
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VERIFY_IS_APPROX(A.template cast<ComplexScalar>(), U * T * U.adjoint());
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}
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// Test asserts when not initialized
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ComplexSchur<MatrixType> csUninitialized;
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VERIFY_RAISES_ASSERT(csUninitialized.matrixT());
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VERIFY_RAISES_ASSERT(csUninitialized.matrixU());
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// Test whether compute() and constructor returns same result
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MatrixType A = MatrixType::Random(size, size);
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ComplexSchur<MatrixType> cs1;
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cs1.compute(A);
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ComplexSchur<MatrixType> cs2(A);
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VERIFY_IS_EQUAL(cs1.matrixT(), cs2.matrixT());
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VERIFY_IS_EQUAL(cs1.matrixU(), cs2.matrixU());
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}
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void test_schur_complex()
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{
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CALL_SUBTEST_1(( schur<Matrix4cd>() ));
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CALL_SUBTEST_2(( schur<MatrixXcf>(ei_random<int>(1,50)) ));
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CALL_SUBTEST_3(( schur<Matrix<std::complex<float>, 1, 1> >() ));
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CALL_SUBTEST_4(( schur<Matrix<float, 3, 3, Eigen::RowMajor> >() ));
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// Test problem size constructors
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CALL_SUBTEST_5(ComplexSchur<MatrixXf>(10));
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}
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