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
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
|
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra. Eigen itself is part of the KDE project.
//
// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
// 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"
#include <functional>
#include <Eigen/Array>
using namespace std;
template<typename Scalar> struct AddIfNull {
const Scalar operator() (const Scalar a, const Scalar b) const {return a<=1e-3 ? b : a;}
enum { Cost = NumTraits<Scalar>::AddCost };
};
template<typename MatrixType> void cwiseops(const MatrixType& m)
{
typedef typename MatrixType::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
int rows = m.rows();
int cols = m.cols();
MatrixType m1 = test_random_matrix<MatrixType>(rows, cols),
m2 = test_random_matrix<MatrixType>(rows, cols),
m3(rows, cols),
mzero = MatrixType::Zero(rows, cols),
mones = MatrixType::Ones(rows, cols),
identity = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
::Identity(rows, rows),
square = test_random_matrix<Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> >(rows, rows);
VectorType v1 = test_random_matrix<VectorType>(rows),
v2 = test_random_matrix<VectorType>(rows),
vzero = VectorType::Zero(rows);
int r = ei_random<int>(0, rows-1),
c = ei_random<int>(0, cols-1);
m2 = m2.template binaryExpr<AddIfNull<Scalar> >(mones);
VERIFY_IS_APPROX(m1.cwise().pow(2), m1.cwise().abs2());
VERIFY_IS_APPROX(m1.cwise().pow(2), m1.cwise().square());
VERIFY_IS_APPROX(m1.cwise().pow(3), m1.cwise().cube());
VERIFY_IS_APPROX(m1 + mones, m1.cwise()+Scalar(1));
VERIFY_IS_APPROX(m1 - mones, m1.cwise()-Scalar(1));
m3 = m1; m3.cwise() += 1;
VERIFY_IS_APPROX(m1 + mones, m3);
m3 = m1; m3.cwise() -= 1;
VERIFY_IS_APPROX(m1 - mones, m3);
VERIFY_IS_APPROX(m2, m2.cwise() * mones);
VERIFY_IS_APPROX(m1.cwise() * m2, m2.cwise() * m1);
VERIFY_IS_APPROX(mones, m2.cwise()/m2);
if(NumTraits<Scalar>::HasFloatingPoint)
{
VERIFY_IS_APPROX(m1.cwise() / m2, m1.cwise() * (m2.cwise().inverse()));
m3 = m1.cwise().abs().cwise().sqrt();
VERIFY_IS_APPROX(m3.cwise().square(), m1.cwise().abs());
VERIFY_IS_APPROX(m1.cwise().square().cwise().sqrt(), m1.cwise().abs());
VERIFY_IS_APPROX(m1.cwise().abs().cwise().log().cwise().exp() , m1.cwise().abs());
// VERIFY_IS_APPROX(m1.cwise().pow(-1), m1.cwise().inverse());
// VERIFY_IS_APPROX(m1.cwise().pow(0.5), m1.cwise().sqrt());
// VERIFY_IS_APPROX(m1.cwise().tan(), m1.cwise().sin().cwise() / m1.cwise().cos());
VERIFY_IS_APPROX(mones, m1.cwise().sin().cwise().square() + m1.cwise().cos().cwise().square());
}
// check min
VERIFY_IS_APPROX( m1.cwise().min(m2), m2.cwise().min(m1) );
VERIFY_IS_APPROX( m1.cwise().min(m1+mones), m1 );
VERIFY_IS_APPROX( m1.cwise().min(m1-mones), m1-mones );
// check max
VERIFY_IS_APPROX( m1.cwise().max(m2), m2.cwise().max(m1) );
VERIFY_IS_APPROX( m1.cwise().max(m1-mones), m1 );
VERIFY_IS_APPROX( m1.cwise().max(m1+mones), m1+mones );
VERIFY( (m1.cwise() == m1).all() );
VERIFY( (m1.cwise() != m2).any() );
VERIFY(!(m1.cwise() == (m1+mones)).any() );
if (rows*cols>1)
{
m3 = m1;
m3(r,c) += 1;
VERIFY( (m1.cwise() == m3).any() );
VERIFY( !(m1.cwise() == m3).all() );
}
VERIFY( (m1.cwise().min(m2).cwise() <= m2).all() );
VERIFY( (m1.cwise().max(m2).cwise() >= m2).all() );
VERIFY( (m1.cwise().min(m2).cwise() < (m1+mones)).all() );
VERIFY( (m1.cwise().max(m2).cwise() > (m1-mones)).all() );
VERIFY( (m1.cwise()<m1.unaryExpr(bind2nd(plus<Scalar>(), Scalar(1)))).all() );
VERIFY( !(m1.cwise()<m1.unaryExpr(bind2nd(minus<Scalar>(), Scalar(1)))).all() );
VERIFY( !(m1.cwise()>m1.unaryExpr(bind2nd(plus<Scalar>(), Scalar(1)))).any() );
}
void test_cwiseop()
{
for(int i = 0; i < g_repeat ; i++) {
CALL_SUBTEST( cwiseops(Matrix<float, 1, 1>()) );
CALL_SUBTEST( cwiseops(Matrix4d()) );
CALL_SUBTEST( cwiseops(MatrixXf(3, 3)) );
CALL_SUBTEST( cwiseops(MatrixXf(22, 22)) );
CALL_SUBTEST( cwiseops(MatrixXi(8, 12)) );
CALL_SUBTEST( cwiseops(MatrixXd(20, 20)) );
}
}
|
