| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. Eigen itself is part of the KDE project. |
| // |
| // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr> |
| // |
| // Eigen is free software; you can redistribute it and/or |
| // modify it under the terms of the GNU Lesser General Public |
| // License as published by the Free Software Foundation; either |
| // version 3 of the License, or (at your option) any later version. |
| // |
| // Alternatively, you can redistribute it and/or |
| // modify it under the terms of the GNU General Public License as |
| // published by the Free Software Foundation; either version 2 of |
| // the License, or (at your option) any later version. |
| // |
| // Eigen is distributed in the hope that it will be useful, but WITHOUT ANY |
| // WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS |
| // FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the |
| // GNU General Public License for more details. |
| // |
| // You should have received a copy of the GNU Lesser General Public |
| // License and a copy of the GNU General Public License along with |
| // Eigen. If not, see <http://www.gnu.org/licenses/>. |
| |
| #include "main.h" |
| #include <Eigen/QR> |
| |
| template<typename MatrixType> void eigensolver(const MatrixType& m) |
| { |
| /* this test covers the following files: |
| EigenSolver.h, SelfAdjointEigenSolver.h (and indirectly: Tridiagonalization.h) |
| */ |
| int rows = m.rows(); |
| int cols = m.cols(); |
| |
| typedef typename std::complex<typename NumTraits<typename MatrixType::Scalar>::Real> Complex; |
| |
| MatrixType a = MatrixType::Random(rows,cols); |
| MatrixType symmA = a.adjoint() * a; |
| |
| SelfAdjointEigenSolver<MatrixType> eiSymm(symmA); |
| VERIFY_IS_APPROX(symmA * eiSymm.eigenvectors(), (eiSymm.eigenvectors() * eiSymm.eigenvalues().asDiagonal().eval())); |
| |
| // generalized eigen problem Ax = lBx |
| MatrixType b = MatrixType::Random(rows,cols); |
| MatrixType symmB = b.adjoint() * b; |
| eiSymm.compute(symmA,symmB); |
| VERIFY_IS_APPROX(symmA * eiSymm.eigenvectors(), symmB * (eiSymm.eigenvectors() * eiSymm.eigenvalues().asDiagonal().eval())); |
| |
| // EigenSolver<MatrixType> eiNotSymmButSymm(covMat); |
| // VERIFY_IS_APPROX((covMat.template cast<Complex>()) * (eiNotSymmButSymm.eigenvectors().template cast<Complex>()), |
| // (eiNotSymmButSymm.eigenvectors().template cast<Complex>()) * (eiNotSymmButSymm.eigenvalues().asDiagonal())); |
| |
| // EigenSolver<MatrixType> eiNotSymm(a); |
| // VERIFY_IS_APPROX(a.template cast<Complex>() * eiNotSymm.eigenvectors().template cast<Complex>(), |
| // eiNotSymm.eigenvectors().template cast<Complex>() * eiNotSymm.eigenvalues().asDiagonal()); |
| |
| } |
| |
| void test_eigensolver() |
| { |
| for(int i = 0; i < 1; i++) { |
| // very important to test a 3x3 matrix since we provide a special path for it |
| CALL_SUBTEST( eigensolver(Matrix3f()) ); |
| CALL_SUBTEST( eigensolver(Matrix4d()) ); |
| CALL_SUBTEST( eigensolver(MatrixXd(7,7)) ); |
| CALL_SUBTEST( eigensolver(MatrixXcd(6,6)) ); |
| CALL_SUBTEST( eigensolver(MatrixXcd(3,3)) ); |
| } |
| } |