[136] | 1 | // This file is part of Eigen, a lightweight C++ template library
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| 2 | // for linear algebra.
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| 3 | //
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| 4 | // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
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| 5 | // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
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| 6 | //
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| 7 | // This Source Code Form is subject to the terms of the Mozilla
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| 8 | // Public License v. 2.0. If a copy of the MPL was not distributed
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| 9 | // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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| 10 |
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| 11 | #include "main.h"
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| 12 | #include <Eigen/SVD>
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| 13 |
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| 14 | template<typename MatrixType, typename JacobiScalar>
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| 15 | void jacobi(const MatrixType& m = MatrixType())
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| 16 | {
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| 17 | typedef typename MatrixType::Index Index;
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| 18 | Index rows = m.rows();
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| 19 | Index cols = m.cols();
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| 20 |
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| 21 | enum {
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| 22 | RowsAtCompileTime = MatrixType::RowsAtCompileTime,
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| 23 | ColsAtCompileTime = MatrixType::ColsAtCompileTime
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| 24 | };
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| 25 |
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| 26 | typedef Matrix<JacobiScalar, 2, 1> JacobiVector;
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| 27 |
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| 28 | const MatrixType a(MatrixType::Random(rows, cols));
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| 29 |
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| 30 | JacobiVector v = JacobiVector::Random().normalized();
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| 31 | JacobiScalar c = v.x(), s = v.y();
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| 32 | JacobiRotation<JacobiScalar> rot(c, s);
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| 33 |
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| 34 | {
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| 35 | Index p = internal::random<Index>(0, rows-1);
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| 36 | Index q;
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| 37 | do {
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| 38 | q = internal::random<Index>(0, rows-1);
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| 39 | } while (q == p);
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| 40 |
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| 41 | MatrixType b = a;
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| 42 | b.applyOnTheLeft(p, q, rot);
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| 43 | VERIFY_IS_APPROX(b.row(p), c * a.row(p) + numext::conj(s) * a.row(q));
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| 44 | VERIFY_IS_APPROX(b.row(q), -s * a.row(p) + numext::conj(c) * a.row(q));
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| 45 | }
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| 46 |
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| 47 | {
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| 48 | Index p = internal::random<Index>(0, cols-1);
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| 49 | Index q;
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| 50 | do {
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| 51 | q = internal::random<Index>(0, cols-1);
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| 52 | } while (q == p);
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| 53 |
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| 54 | MatrixType b = a;
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| 55 | b.applyOnTheRight(p, q, rot);
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| 56 | VERIFY_IS_APPROX(b.col(p), c * a.col(p) - s * a.col(q));
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| 57 | VERIFY_IS_APPROX(b.col(q), numext::conj(s) * a.col(p) + numext::conj(c) * a.col(q));
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| 58 | }
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| 59 | }
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| 60 |
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| 61 | void test_jacobi()
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| 62 | {
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| 63 | for(int i = 0; i < g_repeat; i++) {
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| 64 | CALL_SUBTEST_1(( jacobi<Matrix3f, float>() ));
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| 65 | CALL_SUBTEST_2(( jacobi<Matrix4d, double>() ));
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| 66 | CALL_SUBTEST_3(( jacobi<Matrix4cf, float>() ));
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| 67 | CALL_SUBTEST_3(( jacobi<Matrix4cf, std::complex<float> >() ));
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| 68 |
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| 69 | int r = internal::random<int>(2, internal::random<int>(1,EIGEN_TEST_MAX_SIZE)/2),
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| 70 | c = internal::random<int>(2, internal::random<int>(1,EIGEN_TEST_MAX_SIZE)/2);
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| 71 | CALL_SUBTEST_4(( jacobi<MatrixXf, float>(MatrixXf(r,c)) ));
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| 72 | CALL_SUBTEST_5(( jacobi<MatrixXcd, double>(MatrixXcd(r,c)) ));
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| 73 | CALL_SUBTEST_5(( jacobi<MatrixXcd, std::complex<double> >(MatrixXcd(r,c)) ));
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| 74 | // complex<float> is really important to test as it is the only way to cover conjugation issues in certain unaligned paths
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| 75 | CALL_SUBTEST_6(( jacobi<MatrixXcf, float>(MatrixXcf(r,c)) ));
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| 76 | CALL_SUBTEST_6(( jacobi<MatrixXcf, std::complex<float> >(MatrixXcf(r,c)) ));
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| 77 |
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| 78 | TEST_SET_BUT_UNUSED_VARIABLE(r);
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| 79 | TEST_SET_BUT_UNUSED_VARIABLE(c);
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| 80 | }
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| 81 | }
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