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							81 lines
						
					
					
						
							2.7 KiB
						
					
					
				| // This file is part of Eigen, a lightweight C++ template library | |
| // for linear algebra. | |
| // | |
| // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr> | |
| // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com> | |
| // | |
| // This Source Code Form is subject to the terms of the Mozilla | |
| // Public License v. 2.0. If a copy of the MPL was not distributed | |
| // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. | |
|  | |
| #include "main.h" | |
| #include <Eigen/SVD> | |
|  | |
| template<typename MatrixType, typename JacobiScalar> | |
| void jacobi(const MatrixType& m = MatrixType()) | |
| { | |
|   typedef typename MatrixType::Index Index; | |
|   Index rows = m.rows(); | |
|   Index cols = m.cols(); | |
| 
 | |
|   enum { | |
|     RowsAtCompileTime = MatrixType::RowsAtCompileTime, | |
|     ColsAtCompileTime = MatrixType::ColsAtCompileTime | |
|   }; | |
| 
 | |
|   typedef Matrix<JacobiScalar, 2, 1> JacobiVector; | |
| 
 | |
|   const MatrixType a(MatrixType::Random(rows, cols)); | |
| 
 | |
|   JacobiVector v = JacobiVector::Random().normalized(); | |
|   JacobiScalar c = v.x(), s = v.y(); | |
|   JacobiRotation<JacobiScalar> rot(c, s); | |
| 
 | |
|   { | |
|     Index p = internal::random<Index>(0, rows-1); | |
|     Index q; | |
|     do { | |
|       q = internal::random<Index>(0, rows-1); | |
|     } while (q == p); | |
| 
 | |
|     MatrixType b = a; | |
|     b.applyOnTheLeft(p, q, rot); | |
|     VERIFY_IS_APPROX(b.row(p), c * a.row(p) + numext::conj(s) * a.row(q)); | |
|     VERIFY_IS_APPROX(b.row(q), -s * a.row(p) + numext::conj(c) * a.row(q)); | |
|   } | |
| 
 | |
|   { | |
|     Index p = internal::random<Index>(0, cols-1); | |
|     Index q; | |
|     do { | |
|       q = internal::random<Index>(0, cols-1); | |
|     } while (q == p); | |
| 
 | |
|     MatrixType b = a; | |
|     b.applyOnTheRight(p, q, rot); | |
|     VERIFY_IS_APPROX(b.col(p), c * a.col(p) - s * a.col(q)); | |
|     VERIFY_IS_APPROX(b.col(q), numext::conj(s) * a.col(p) + numext::conj(c) * a.col(q)); | |
|   } | |
| } | |
| 
 | |
| void test_jacobi() | |
| { | |
|   for(int i = 0; i < g_repeat; i++) { | |
|     CALL_SUBTEST_1(( jacobi<Matrix3f, float>() )); | |
|     CALL_SUBTEST_2(( jacobi<Matrix4d, double>() )); | |
|     CALL_SUBTEST_3(( jacobi<Matrix4cf, float>() )); | |
|     CALL_SUBTEST_3(( jacobi<Matrix4cf, std::complex<float> >() )); | |
| 
 | |
|     int r = internal::random<int>(2, internal::random<int>(1,EIGEN_TEST_MAX_SIZE)/2), | |
|         c = internal::random<int>(2, internal::random<int>(1,EIGEN_TEST_MAX_SIZE)/2); | |
|     CALL_SUBTEST_4(( jacobi<MatrixXf, float>(MatrixXf(r,c)) )); | |
|     CALL_SUBTEST_5(( jacobi<MatrixXcd, double>(MatrixXcd(r,c)) )); | |
|     CALL_SUBTEST_5(( jacobi<MatrixXcd, std::complex<double> >(MatrixXcd(r,c)) )); | |
|     // complex<float> is really important to test as it is the only way to cover conjugation issues in certain unaligned paths | |
|     CALL_SUBTEST_6(( jacobi<MatrixXcf, float>(MatrixXcf(r,c)) )); | |
|     CALL_SUBTEST_6(( jacobi<MatrixXcf, std::complex<float> >(MatrixXcf(r,c)) )); | |
|      | |
|     TEST_SET_BUT_UNUSED_VARIABLE(r); | |
|     TEST_SET_BUT_UNUSED_VARIABLE(c); | |
|   } | |
| }
 |