jacobisvd.cpp
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1 // This file is part of Eigen, a lightweight C++ template library
2 // for linear algebra.
3 //
4 // Copyright (C) 2008-2014 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 // discard stack allocation as that too bypasses malloc
12 #define EIGEN_STACK_ALLOCATION_LIMIT 0
13 #define EIGEN_RUNTIME_NO_MALLOC
14 #include "main.h"
15 #include <Eigen/SVD>
16 
17 #define SVD_DEFAULT(M) JacobiSVD<M>
18 #define SVD_FOR_MIN_NORM(M) JacobiSVD<M,ColPivHouseholderQRPreconditioner>
19 #include "svd_common.h"
20 
21 // Check all variants of JacobiSVD
22 template<typename MatrixType>
23 void jacobisvd(const MatrixType& a = MatrixType(), bool pickrandom = true)
24 {
25  MatrixType m = a;
26  if(pickrandom)
27  svd_fill_random(m);
28 
32  if(m.rows()==m.cols())
34 }
35 
36 template<typename MatrixType> void jacobisvd_verify_assert(const MatrixType& m)
37 {
38  svd_verify_assert<JacobiSVD<MatrixType> >(m);
39  Index rows = m.rows();
40  Index cols = m.cols();
41 
42  enum {
43  ColsAtCompileTime = MatrixType::ColsAtCompileTime
44  };
45 
46 
47  MatrixType a = MatrixType::Zero(rows, cols);
48  a.setZero();
49 
50  if (ColsAtCompileTime == Dynamic)
51  {
56  }
57 }
58 
59 template<typename MatrixType>
61 {
62  enum { Size = MatrixType::RowsAtCompileTime };
63  typedef typename MatrixType::RealScalar RealScalar;
64  typedef Matrix<RealScalar, Size, 1> RealVecType;
65  MatrixType m = MatrixType::Identity();
66  VERIFY_IS_APPROX(m.jacobiSvd().singularValues(), RealVecType::Ones());
67  VERIFY_RAISES_ASSERT(m.jacobiSvd().matrixU());
68  VERIFY_RAISES_ASSERT(m.jacobiSvd().matrixV());
69  VERIFY_IS_APPROX(m.jacobiSvd(ComputeFullU|ComputeFullV).solve(m), m);
70 }
71 
72 namespace Foo {
73 // older compiler require a default constructor for Bar
74 // cf: https://stackoverflow.com/questions/7411515/
75 class Bar {public: Bar() {}};
76 bool operator<(const Bar&, const Bar&) { return true; }
77 }
78 // regression test for a very strange MSVC issue for which simply
79 // including SVDBase.h messes up with std::max and custom scalar type
81 {
82  const Foo::Bar a;
83  const Foo::Bar b;
85 }
86 
88 {
89  CALL_SUBTEST_3(( jacobisvd_verify_assert(Matrix3f()) ));
90  CALL_SUBTEST_4(( jacobisvd_verify_assert(Matrix4d()) ));
91  CALL_SUBTEST_7(( jacobisvd_verify_assert(MatrixXf(10,12)) ));
92  CALL_SUBTEST_8(( jacobisvd_verify_assert(MatrixXcd(7,5)) ));
93 
94  CALL_SUBTEST_11(svd_all_trivial_2x2(jacobisvd<Matrix2cd>));
95  CALL_SUBTEST_12(svd_all_trivial_2x2(jacobisvd<Matrix2d>));
96 
97  for(int i = 0; i < g_repeat; i++) {
98  CALL_SUBTEST_3(( jacobisvd<Matrix3f>() ));
99  CALL_SUBTEST_4(( jacobisvd<Matrix4d>() ));
100  CALL_SUBTEST_5(( jacobisvd<Matrix<float,3,5> >() ));
101  CALL_SUBTEST_6(( jacobisvd<Matrix<double,Dynamic,2> >(Matrix<double,Dynamic,2>(10,2)) ));
102 
103  int r = internal::random<int>(1, 30),
104  c = internal::random<int>(1, 30);
105 
108 
109  CALL_SUBTEST_10(( jacobisvd<MatrixXd>(MatrixXd(r,c)) ));
110  CALL_SUBTEST_7(( jacobisvd<MatrixXf>(MatrixXf(r,c)) ));
111  CALL_SUBTEST_8(( jacobisvd<MatrixXcd>(MatrixXcd(r,c)) ));
112  (void) r;
113  (void) c;
114 
115  // Test on inf/nan matrix
116  CALL_SUBTEST_7( (svd_inf_nan<JacobiSVD<MatrixXf>, MatrixXf>()) );
117  CALL_SUBTEST_10( (svd_inf_nan<JacobiSVD<MatrixXd>, MatrixXd>()) );
118 
119  // bug1395 test compile-time vectors as input
120  CALL_SUBTEST_13(( jacobisvd_verify_assert(Matrix<double,6,1>()) ));
121  CALL_SUBTEST_13(( jacobisvd_verify_assert(Matrix<double,1,6>()) ));
122  CALL_SUBTEST_13(( jacobisvd_verify_assert(Matrix<double,Dynamic,1>(r)) ));
123  CALL_SUBTEST_13(( jacobisvd_verify_assert(Matrix<double,1,Dynamic>(c)) ));
124  }
125 
126  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))) ));
127  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))) ));
128 
129  // test matrixbase method
130  CALL_SUBTEST_1(( jacobisvd_method<Matrix2cd>() ));
131  CALL_SUBTEST_3(( jacobisvd_method<Matrix3f>() ));
132 
133  // Test problem size constructors
134  CALL_SUBTEST_7( JacobiSVD<MatrixXf>(10,10) );
135 
136  // Check that preallocation avoids subsequent mallocs
137  CALL_SUBTEST_9( svd_preallocate<void>() );
138 
139  CALL_SUBTEST_2( svd_underoverflow<void>() );
140 
141  msvc_workaround();
142 }
Matrix3f m
void svd_test_all_computation_options(const MatrixType &m, bool full_only)
Definition: svd_common.h:224
void svd_fill_random(MatrixType &m, int Option=0)
Definition: svd_fill.h:21
#define VERIFY_RAISES_ASSERT(a)
Definition: main.h:285
#define max(a, b)
Definition: datatypes.h:20
#define EIGEN_NOT_A_MACRO
Definition: Macros.h:327
bool operator<(const Bar &, const Bar &)
Definition: jacobisvd.cpp:76
Scalar * b
Definition: benchVecAdd.cpp:17
Scalar Scalar * c
Definition: benchVecAdd.cpp:17
MatrixXf MatrixType
void jacobisvd_verify_assert(const MatrixType &m)
Definition: jacobisvd.cpp:36
void msvc_workaround()
Definition: jacobisvd.cpp:80
Array33i a
#define VERIFY_IS_APPROX(a, b)
void jacobisvd_method()
Definition: jacobisvd.cpp:60
static int g_repeat
Definition: main.h:144
EIGEN_DEFAULT_DENSE_INDEX_TYPE Index
The Index type as used for the API.
Definition: Meta.h:33
NumTraits< Scalar >::Real RealScalar
Definition: bench_gemm.cpp:34
void test_jacobisvd()
Definition: jacobisvd.cpp:87
#define TEST_SET_BUT_UNUSED_VARIABLE(X)
Definition: main.h:91
void jacobisvd(const MatrixType &a=MatrixType(), bool pickrandom=true)
Definition: jacobisvd.cpp:23
#define CALL_SUBTEST(FUNC)
Definition: main.h:342
#define EIGEN_TEST_MAX_SIZE
Two-sided Jacobi SVD decomposition of a rectangular matrix.
JacobiSVD & compute(const MatrixType &matrix, unsigned int computationOptions)
Method performing the decomposition of given matrix using custom options.
Definition: JacobiSVD.h:663
void svd_all_trivial_2x2(void(*cb)(const MatrixType &, bool))
Definition: svd_common.h:369
const int Dynamic
Definition: Constants.h:21
The matrix class, also used for vectors and row-vectors.
void svd_inf_nan()
Definition: svd_common.h:278


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autogenerated on Sat May 8 2021 02:42:23