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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.
89 lines
3.2 KiB
C++
89 lines
3.2 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 verifyIsQuasiTriangular(const MatrixType& T)
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{
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const int size = T.cols();
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typedef typename MatrixType::Scalar Scalar;
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// Check T is lower Hessenberg
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for(int row = 2; row < size; ++row) {
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for(int col = 0; col < row - 1; ++col) {
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VERIFY(T(row,col) == Scalar(0));
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}
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}
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// Check that any non-zero on the subdiagonal is followed by a zero and is
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// part of a 2x2 diagonal block with imaginary eigenvalues.
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for(int row = 1; row < size; ++row) {
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if (T(row,row-1) != Scalar(0)) {
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VERIFY(row == size-1 || T(row+1,row) == 0);
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Scalar tr = T(row-1,row-1) + T(row,row);
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Scalar det = T(row-1,row-1) * T(row,row) - T(row-1,row) * T(row,row-1);
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VERIFY(4 * det > tr * tr);
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}
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}
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}
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template<typename MatrixType> void schur(int size = MatrixType::ColsAtCompileTime)
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{
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// Test basic functionality: T is quasi-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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RealSchur<MatrixType> schurOfA(A);
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MatrixType U = schurOfA.matrixU();
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MatrixType T = schurOfA.matrixT();
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std::cout << "T = \n" << T << "\n\n";
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verifyIsQuasiTriangular(T);
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VERIFY_IS_APPROX(A, U * T * U.transpose());
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}
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// Test asserts when not initialized
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RealSchur<MatrixType> rsUninitialized;
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VERIFY_RAISES_ASSERT(rsUninitialized.matrixT());
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VERIFY_RAISES_ASSERT(rsUninitialized.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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RealSchur<MatrixType> rs1;
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rs1.compute(A);
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RealSchur<MatrixType> rs2(A);
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VERIFY_IS_EQUAL(rs1.matrixT(), rs2.matrixT());
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VERIFY_IS_EQUAL(rs1.matrixU(), rs2.matrixU());
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}
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void test_schur_real()
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{
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CALL_SUBTEST_1(( schur<Matrix4f>() ));
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CALL_SUBTEST_2(( schur<MatrixXd>(ei_random<int>(1,50)) ));
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CALL_SUBTEST_3(( schur<Matrix<float, 1, 1> >() ));
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CALL_SUBTEST_4(( schur<Matrix<double, 3, 3, Eigen::RowMajor> >() ));
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// Test problem size constructors
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CALL_SUBTEST_5(RealSchur<MatrixXf>(10));
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}
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