6b4e215710
I hope to implement the real case soon, but it's a bit more complicated due to the 2-by-2 blocks in the real Schur decomposition.
47 lines
1.6 KiB
C++
47 lines
1.6 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) 2011 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 <unsupported/Eigen/MatrixFunctions>
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template<typename MatrixType>
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void testMatrixSqrt(const MatrixType& m)
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{
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typedef typename MatrixType::Index Index;
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const Index size = m.rows();
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MatrixType A = MatrixType::Random(size, size);
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MatrixSquareRoot<MatrixType> msr(A);
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MatrixType S;
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msr.compute(S);
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VERIFY_IS_APPROX(S*S, A);
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}
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void test_matrix_square_root()
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{
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for (int i = 0; i < g_repeat; i++) {
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CALL_SUBTEST_1(testMatrixSqrt(Matrix3cf()));
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CALL_SUBTEST_2(testMatrixSqrt(MatrixXcd(12,12)));
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}
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}
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