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4af7089ab8
(as new members to SelfAdjointEigenSolver) The QR module now depends on Cholesky. * Fix Transpose to correctly preserve the *TriangularBit.
71 lines
2.9 KiB
C++
71 lines
2.9 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 <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/QR>
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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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EigenSolver.h, SelfAdjointEigenSolver.h (and indirectly: Tridiagonalization.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 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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SelfAdjointEigenSolver<MatrixType> eiSymm(symmA);
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VERIFY_IS_APPROX(symmA * eiSymm.eigenvectors(), (eiSymm.eigenvectors() * eiSymm.eigenvalues().asDiagonal().eval()));
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// generalized eigen problem Ax = lBx
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MatrixType b = MatrixType::random(rows,cols);
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MatrixType symmB = b.adjoint() * b;
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eiSymm.compute(symmA,symmB);
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VERIFY_IS_APPROX(symmA * eiSymm.eigenvectors(), symmB * (eiSymm.eigenvectors() * eiSymm.eigenvalues().asDiagonal().eval()));
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// EigenSolver<MatrixType> eiNotSymmButSymm(covMat);
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// VERIFY_IS_APPROX((covMat.template cast<Complex>()) * (eiNotSymmButSymm.eigenvectors().template cast<Complex>()),
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// (eiNotSymmButSymm.eigenvectors().template cast<Complex>()) * (eiNotSymmButSymm.eigenvalues().asDiagonal()));
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// EigenSolver<MatrixType> eiNotSymm(a);
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// VERIFY_IS_APPROX(a.template cast<Complex>() * eiNotSymm.eigenvectors().template cast<Complex>(),
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// eiNotSymm.eigenvectors().template cast<Complex>() * eiNotSymm.eigenvalues().asDiagonal());
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}
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void test_eigensolver()
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{
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for(int i = 0; i < 1; i++) {
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// very important to test a 3x3 matrix since we provide a special path for it
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CALL_SUBTEST( eigensolver(Matrix3f()) );
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CALL_SUBTEST( eigensolver(Matrix4d()) );
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CALL_SUBTEST( eigensolver(MatrixXd(7,7)) );
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CALL_SUBTEST( eigensolver(MatrixXcd(6,6)) );
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CALL_SUBTEST( eigensolver(MatrixXcd(3,3)) );
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}
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}
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