1// This file is part of Eigen, a lightweight C++ template library
2// for linear algebra.
3//
4// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
5// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
6//
7// This Source Code Form is subject to the terms of the Mozilla
8// Public License v. 2.0. If a copy of the MPL was not distributed
9// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
10
11#include "svd_common.h"
12
13template<typename MatrixType, int QRPreconditioner>
14void jacobisvd_check_full(const MatrixType& m, const JacobiSVD<MatrixType, QRPreconditioner>& svd)
15{
16  svd_check_full<MatrixType, JacobiSVD<MatrixType, QRPreconditioner > >(m, svd);
17}
18
19template<typename MatrixType, int QRPreconditioner>
20void jacobisvd_compare_to_full(const MatrixType& m,
21                               unsigned int computationOptions,
22                               const JacobiSVD<MatrixType, QRPreconditioner>& referenceSvd)
23{
24  svd_compare_to_full<MatrixType, JacobiSVD<MatrixType, QRPreconditioner> >(m, computationOptions, referenceSvd);
25}
26
27
28template<typename MatrixType, int QRPreconditioner>
29void jacobisvd_solve(const MatrixType& m, unsigned int computationOptions)
30{
31  svd_solve< MatrixType, JacobiSVD< MatrixType, QRPreconditioner > >(m, computationOptions);
32}
33
34
35
36template<typename MatrixType, int QRPreconditioner>
37void jacobisvd_test_all_computation_options(const MatrixType& m)
38{
39
40  if (QRPreconditioner == NoQRPreconditioner && m.rows() != m.cols())
41    return;
42
43  JacobiSVD< MatrixType, QRPreconditioner > fullSvd(m, ComputeFullU|ComputeFullV);
44  svd_test_computation_options_1< MatrixType, JacobiSVD< MatrixType, QRPreconditioner > >(m, fullSvd);
45
46  if(QRPreconditioner == FullPivHouseholderQRPreconditioner)
47    return;
48  svd_test_computation_options_2< MatrixType, JacobiSVD< MatrixType, QRPreconditioner > >(m, fullSvd);
49
50}
51
52template<typename MatrixType>
53void jacobisvd(const MatrixType& a = MatrixType(), bool pickrandom = true)
54{
55  MatrixType m = pickrandom ? MatrixType::Random(a.rows(), a.cols()) : a;
56
57  jacobisvd_test_all_computation_options<MatrixType, FullPivHouseholderQRPreconditioner>(m);
58  jacobisvd_test_all_computation_options<MatrixType, ColPivHouseholderQRPreconditioner>(m);
59  jacobisvd_test_all_computation_options<MatrixType, HouseholderQRPreconditioner>(m);
60  jacobisvd_test_all_computation_options<MatrixType, NoQRPreconditioner>(m);
61}
62
63
64template<typename MatrixType>
65void jacobisvd_verify_assert(const MatrixType& m)
66{
67
68  svd_verify_assert<MatrixType, JacobiSVD< MatrixType > >(m);
69
70  typedef typename MatrixType::Index Index;
71  Index rows = m.rows();
72  Index cols = m.cols();
73
74  enum {
75    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
76    ColsAtCompileTime = MatrixType::ColsAtCompileTime
77  };
78
79  MatrixType a = MatrixType::Zero(rows, cols);
80  a.setZero();
81
82  if (ColsAtCompileTime == Dynamic)
83  {
84    JacobiSVD<MatrixType, FullPivHouseholderQRPreconditioner> svd_fullqr;
85    VERIFY_RAISES_ASSERT(svd_fullqr.compute(a, ComputeFullU|ComputeThinV))
86    VERIFY_RAISES_ASSERT(svd_fullqr.compute(a, ComputeThinU|ComputeThinV))
87    VERIFY_RAISES_ASSERT(svd_fullqr.compute(a, ComputeThinU|ComputeFullV))
88  }
89}
90
91template<typename MatrixType>
92void jacobisvd_method()
93{
94  enum { Size = MatrixType::RowsAtCompileTime };
95  typedef typename MatrixType::RealScalar RealScalar;
96  typedef Matrix<RealScalar, Size, 1> RealVecType;
97  MatrixType m = MatrixType::Identity();
98  VERIFY_IS_APPROX(m.jacobiSvd().singularValues(), RealVecType::Ones());
99  VERIFY_RAISES_ASSERT(m.jacobiSvd().matrixU());
100  VERIFY_RAISES_ASSERT(m.jacobiSvd().matrixV());
101  VERIFY_IS_APPROX(m.jacobiSvd(ComputeFullU|ComputeFullV).solve(m), m);
102}
103
104
105
106template<typename MatrixType>
107void jacobisvd_inf_nan()
108{
109  svd_inf_nan<MatrixType, JacobiSVD< MatrixType > >();
110}
111
112
113// Regression test for bug 286: JacobiSVD loops indefinitely with some
114// matrices containing denormal numbers.
115void jacobisvd_bug286()
116{
117#if defined __INTEL_COMPILER
118// shut up warning #239: floating point underflow
119#pragma warning push
120#pragma warning disable 239
121#endif
122  Matrix2d M;
123  M << -7.90884e-313, -4.94e-324,
124                 0, 5.60844e-313;
125#if defined __INTEL_COMPILER
126#pragma warning pop
127#endif
128  JacobiSVD<Matrix2d> svd;
129  svd.compute(M); // just check we don't loop indefinitely
130}
131
132
133void jacobisvd_preallocate()
134{
135  svd_preallocate< JacobiSVD <MatrixXf> >();
136}
137
138void test_jacobisvd()
139{
140  CALL_SUBTEST_11(( jacobisvd<Matrix<double,Dynamic,Dynamic> >
141		    (Matrix<double,Dynamic,Dynamic>(16, 6)) ));
142
143  CALL_SUBTEST_3(( jacobisvd_verify_assert(Matrix3f()) ));
144  CALL_SUBTEST_4(( jacobisvd_verify_assert(Matrix4d()) ));
145  CALL_SUBTEST_7(( jacobisvd_verify_assert(MatrixXf(10,12)) ));
146  CALL_SUBTEST_8(( jacobisvd_verify_assert(MatrixXcd(7,5)) ));
147
148  for(int i = 0; i < g_repeat; i++) {
149    Matrix2cd m;
150    m << 0, 1,
151         0, 1;
152    CALL_SUBTEST_1(( jacobisvd(m, false) ));
153    m << 1, 0,
154         1, 0;
155    CALL_SUBTEST_1(( jacobisvd(m, false) ));
156
157    Matrix2d n;
158    n << 0, 0,
159         0, 0;
160    CALL_SUBTEST_2(( jacobisvd(n, false) ));
161    n << 0, 0,
162         0, 1;
163    CALL_SUBTEST_2(( jacobisvd(n, false) ));
164
165    CALL_SUBTEST_3(( jacobisvd<Matrix3f>() ));
166    CALL_SUBTEST_4(( jacobisvd<Matrix4d>() ));
167    CALL_SUBTEST_5(( jacobisvd<Matrix<float,3,5> >() ));
168    CALL_SUBTEST_6(( jacobisvd<Matrix<double,Dynamic,2> >(Matrix<double,Dynamic,2>(10,2)) ));
169
170    int r = internal::random<int>(1, 30),
171        c = internal::random<int>(1, 30);
172    CALL_SUBTEST_7(( jacobisvd<MatrixXf>(MatrixXf(r,c)) ));
173    CALL_SUBTEST_8(( jacobisvd<MatrixXcd>(MatrixXcd(r,c)) ));
174    (void) r;
175    (void) c;
176
177    // Test on inf/nan matrix
178    CALL_SUBTEST_7( jacobisvd_inf_nan<MatrixXf>() );
179  }
180
181  CALL_SUBTEST_7(( jacobisvd<MatrixXf>(MatrixXf(internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/2), internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/2))) ));
182  CALL_SUBTEST_8(( jacobisvd<MatrixXcd>(MatrixXcd(internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/3), internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/3))) ));
183
184
185  // test matrixbase method
186  CALL_SUBTEST_1(( jacobisvd_method<Matrix2cd>() ));
187  CALL_SUBTEST_3(( jacobisvd_method<Matrix3f>() ));
188
189
190  // Test problem size constructors
191  CALL_SUBTEST_7( JacobiSVD<MatrixXf>(10,10) );
192
193  // Check that preallocation avoids subsequent mallocs
194  CALL_SUBTEST_9( jacobisvd_preallocate() );
195
196  // Regression check for bug 286
197  CALL_SUBTEST_2( jacobisvd_bug286() );
198}
199