1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
|
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra. Eigen itself is part of the KDE project.
//
// Copyright (C) 2006-2008 Benoit Jacob <jacob@math.jussieu.fr>
//
// 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"
namespace Eigen {
template<typename MatrixType> void linearStructure(const MatrixType& m)
{
/* this test covers the following files:
Sum.h Difference.h Opposite.h ScalarMultiple.h
*/
typedef typename MatrixType::Scalar Scalar;
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
int rows = m.rows();
int cols = m.cols();
// this test relies a lot on Random.h, and there's not much more that we can do
// to test it, hence I consider that we will have tested Random.h
MatrixType m1 = MatrixType::random(rows, cols),
m2 = MatrixType::random(rows, cols),
m3(rows, cols),
mzero = MatrixType::zero(rows, cols),
identity = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
::identity(rows, rows),
square = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
::random(rows, rows);
VectorType v1 = VectorType::random(rows),
v2 = VectorType::random(rows),
vzero = VectorType::zero(rows);
Scalar s1 = ei_random<Scalar>(),
s2 = ei_random<Scalar>();
int r = ei_random<int>(0, rows-1),
c = ei_random<int>(0, cols-1);
VERIFY_IS_APPROX(-(-m1), m1);
VERIFY_IS_APPROX(m1+m1, 2*m1);
VERIFY_IS_APPROX(m1+m2-m1, m2);
VERIFY_IS_APPROX(-m2+m1+m2, m1);
VERIFY_IS_APPROX(m1*s1, s1*m1);
VERIFY_IS_APPROX((m1+m2)*s1, s1*m1+s1*m2);
VERIFY_IS_APPROX((s1+s2)*m1, m1*s1+m1*s2);
VERIFY_IS_APPROX((m1-m2)*s1, s1*m1-s1*m2);
VERIFY_IS_APPROX((s1-s2)*m1, m1*s1-m1*s2);
VERIFY_IS_APPROX((-m1+m2)*s1, -s1*m1+s1*m2);
VERIFY_IS_APPROX((-s1+s2)*m1, -m1*s1+m1*s2);
m3 = m2; m3 += m1;
VERIFY_IS_APPROX(m3, m1+m2);
m3 = m2; m3 -= m1;
VERIFY_IS_APPROX(m3, m2-m1);
m3 = m2; m3 *= s1;
VERIFY_IS_APPROX(m3, s1*m2);
if(NumTraits<Scalar>::HasFloatingPoint)
{
m3 = m2; m3 /= s1;
VERIFY_IS_APPROX(m3, m2/s1);
}
// again, test operator() to check const-qualification
VERIFY_IS_APPROX((-m1)(r,c), -(m1(r,c)));
VERIFY_IS_APPROX((m1-m2)(r,c), (m1(r,c))-(m2(r,c)));
VERIFY_IS_APPROX((m1+m2)(r,c), (m1(r,c))+(m2(r,c)));
VERIFY_IS_APPROX((s1*m1)(r,c), s1*(m1(r,c)));
VERIFY_IS_APPROX((m1*s1)(r,c), (m1(r,c))*s1);
if(NumTraits<Scalar>::HasFloatingPoint)
VERIFY_IS_APPROX((m1/s1)(r,c), (m1(r,c))/s1);
}
void EigenTest::testLinearStructure()
{
for(int i = 0; i < m_repeat; i++) {
linearStructure(Matrix<float, 1, 1>());
linearStructure(Matrix4d());
linearStructure(MatrixXcf(3, 3));
linearStructure(MatrixXi(8, 12));
linearStructure(MatrixXcd(20, 20));
}
}
} // namespace Eigen
|
