| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. |
| // |
| // Copyright (C) 2011 Jitse Niesen <jitse@maths.leeds.ac.uk> |
| // |
| // 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 <unsupported/Eigen/MatrixFunctions> |
| |
| template <typename MatrixType, int IsComplex = NumTraits<typename internal::traits<MatrixType>::Scalar>::IsComplex> |
| struct generateTestMatrix; |
| |
| // for real matrices, make sure none of the eigenvalues are negative |
| template <typename MatrixType> |
| struct generateTestMatrix<MatrixType,0> |
| { |
| static void run(MatrixType& result, typename MatrixType::Index size) |
| { |
| MatrixType mat = MatrixType::Random(size, size); |
| EigenSolver<MatrixType> es(mat); |
| typename EigenSolver<MatrixType>::EigenvalueType eivals = es.eigenvalues(); |
| for (typename MatrixType::Index i = 0; i < size; ++i) { |
| if (eivals(i).imag() == 0 && eivals(i).real() < 0) |
| eivals(i) = -eivals(i); |
| } |
| result = (es.eigenvectors() * eivals.asDiagonal() * es.eigenvectors().inverse()).real(); |
| } |
| }; |
| |
| // for complex matrices, any matrix is fine |
| template <typename MatrixType> |
| struct generateTestMatrix<MatrixType,1> |
| { |
| static void run(MatrixType& result, typename MatrixType::Index size) |
| { |
| result = MatrixType::Random(size, size); |
| } |
| }; |
| |
| template<typename MatrixType> |
| void testMatrixSqrt(const MatrixType& m) |
| { |
| MatrixType A; |
| generateTestMatrix<MatrixType>::run(A, m.rows()); |
| MatrixType sqrtA = A.sqrt(); |
| VERIFY_IS_APPROX(sqrtA * sqrtA, A); |
| } |
| |
| void test_matrix_square_root() |
| { |
| for (int i = 0; i < g_repeat; i++) { |
| CALL_SUBTEST_1(testMatrixSqrt(Matrix3cf())); |
| CALL_SUBTEST_2(testMatrixSqrt(MatrixXcd(12,12))); |
| CALL_SUBTEST_3(testMatrixSqrt(Matrix4f())); |
| CALL_SUBTEST_4(testMatrixSqrt(Matrix<double,Dynamic,Dynamic,RowMajor>(9, 9))); |
| CALL_SUBTEST_5(testMatrixSqrt(Matrix<float,1,1>())); |
| CALL_SUBTEST_5(testMatrixSqrt(Matrix<std::complex<float>,1,1>())); |
| } |
| } |