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
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
|
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
//
// 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"
// check minor separately in order to avoid the possible creation of a zero-sized
// array. Comes from a compilation error with gcc-3.4 or gcc-4 with -ansi -pedantic.
// Another solution would be to declare the array like this: T m_data[Size==0?1:Size]; in ei_matrix_storage
// but this is probably not bad to raise such an error at compile time...
template<typename Scalar, int _Rows, int _Cols> struct CheckMinor
{
typedef Matrix<Scalar, _Rows, _Cols> MatrixType;
CheckMinor(MatrixType& m1, int r1, int c1)
{
int rows = m1.rows();
int cols = m1.cols();
Matrix<Scalar, Dynamic, Dynamic> mi = m1.minor(0,0).eval();
VERIFY_IS_APPROX(mi, m1.block(1,1,rows-1,cols-1));
mi = m1.minor(r1,c1);
VERIFY_IS_APPROX(mi.transpose(), m1.transpose().minor(c1,r1));
//check operator(), both constant and non-constant, on minor()
m1.minor(r1,c1)(0,0) = m1.minor(0,0)(0,0);
}
};
template<typename Scalar> struct CheckMinor<Scalar,1,1>
{
typedef Matrix<Scalar, 1, 1> MatrixType;
CheckMinor(MatrixType&, int, int) {}
};
template<typename MatrixType> void submatrices(const MatrixType& m)
{
/* this test covers the following files:
Row.h Column.h Block.h Minor.h DiagonalCoeffs.h
*/
typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::RealScalar RealScalar;
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
typedef Matrix<Scalar, 1, MatrixType::ColsAtCompileTime> RowVectorType;
int rows = m.rows();
int cols = m.cols();
MatrixType m1 = MatrixType::Random(rows, cols),
m2 = MatrixType::Random(rows, cols),
m3(rows, cols),
mzero = MatrixType::Zero(rows, cols),
ones = MatrixType::Ones(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),
v3 = VectorType::Random(rows),
vzero = VectorType::Zero(rows);
Scalar s1 = ei_random<Scalar>();
int r1 = ei_random<int>(0,rows-1);
int r2 = ei_random<int>(r1,rows-1);
int c1 = ei_random<int>(0,cols-1);
int c2 = ei_random<int>(c1,cols-1);
//check row() and col()
VERIFY_IS_APPROX(m1.col(c1).transpose(), m1.transpose().row(c1));
// FIXME perhaps we should re-enable that without the .eval()
VERIFY_IS_APPROX(m1.col(c1).dot(square.row(r1)), (square * m1.conjugate()).eval()(r1,c1));
//check operator(), both constant and non-constant, on row() and col()
m1.row(r1) += s1 * m1.row(r2);
m1.col(c1) += s1 * m1.col(c2);
//check block()
Matrix<Scalar,Dynamic,Dynamic> b1(1,1); b1(0,0) = m1(r1,c1);
RowVectorType br1(m1.block(r1,0,1,cols));
VectorType bc1(m1.block(0,c1,rows,1));
VERIFY_IS_APPROX(b1, m1.block(r1,c1,1,1));
VERIFY_IS_APPROX(m1.row(r1), br1);
VERIFY_IS_APPROX(m1.col(c1), bc1);
//check operator(), both constant and non-constant, on block()
m1.block(r1,c1,r2-r1+1,c2-c1+1) = s1 * m2.block(0, 0, r2-r1+1,c2-c1+1);
m1.block(r1,c1,r2-r1+1,c2-c1+1)(r2-r1,c2-c1) = m2.block(0, 0, r2-r1+1,c2-c1+1)(0,0);
//check minor()
CheckMinor<Scalar, MatrixType::RowsAtCompileTime, MatrixType::ColsAtCompileTime> checkminor(m1,r1,c1);
//check diagonal()
VERIFY_IS_APPROX(m1.diagonal(), m1.transpose().diagonal());
m2.diagonal() = 2 * m1.diagonal();
m2.diagonal()[0] *= 3;
const int BlockRows = EIGEN_ENUM_MIN(MatrixType::RowsAtCompileTime,2);
const int BlockCols = EIGEN_ENUM_MIN(MatrixType::ColsAtCompileTime,5);
if (rows>=5 && cols>=8)
{
// test fixed block() as lvalue
m1.template block<BlockRows,BlockCols>(1,1) *= s1;
// test operator() on fixed block() both as constant and non-constant
m1.template block<BlockRows,BlockCols>(1,1)(0, 3) = m1.template block<2,5>(1,1)(1,2);
// check that fixed block() and block() agree
Matrix<Scalar,Dynamic,Dynamic> b = m1.template block<BlockRows,BlockCols>(3,3);
VERIFY_IS_APPROX(b, m1.block(3,3,BlockRows,BlockCols));
}
if (rows>2)
{
// test sub vectors
VERIFY_IS_APPROX(v1.template start<2>(), v1.block(0,0,2,1));
VERIFY_IS_APPROX(v1.template start<2>(), v1.start(2));
VERIFY_IS_APPROX(v1.template start<2>(), v1.segment(0,2));
VERIFY_IS_APPROX(v1.template start<2>(), v1.template segment<2>(0));
int i = rows-2;
VERIFY_IS_APPROX(v1.template end<2>(), v1.block(i,0,2,1));
VERIFY_IS_APPROX(v1.template end<2>(), v1.end(2));
VERIFY_IS_APPROX(v1.template end<2>(), v1.segment(i,2));
VERIFY_IS_APPROX(v1.template end<2>(), v1.template segment<2>(i));
i = ei_random(0,rows-2);
VERIFY_IS_APPROX(v1.segment(i,2), v1.template segment<2>(i));
enum {
N1 = MatrixType::RowsAtCompileTime>1 ? 1 : 0,
N2 = MatrixType::RowsAtCompileTime>2 ? -2 : 0
};
// check sub/super diagonal
m2.template diagonal<N1>() = 2 * m1.template diagonal<N1>();
m2.template diagonal<N1>()[0] *= 3;
VERIFY_IS_APPROX(m2.template diagonal<N1>()[0], static_cast<Scalar>(6) * m1.template diagonal<N1>()[0]);
m2.template diagonal<N2>() = 2 * m1.template diagonal<N2>();
m2.template diagonal<N2>()[0] *= 3;
VERIFY_IS_APPROX(m2.template diagonal<N2>()[0], static_cast<Scalar>(6) * m1.template diagonal<N2>()[0]);
m2.diagonal(N1) = 2 * m1.diagonal(N1);
m2.diagonal(N1)[0] *= 3;
VERIFY_IS_APPROX(m2.diagonal(N1)[0], static_cast<Scalar>(6) * m1.diagonal(N1)[0]);
m2.diagonal(N2) = 2 * m1.diagonal(N2);
m2.diagonal(N2)[0] *= 3;
VERIFY_IS_APPROX(m2.diagonal(N2)[0], static_cast<Scalar>(6) * m1.diagonal(N2)[0]);
}
// stress some basic stuffs with block matrices
VERIFY(ei_real(ones.col(c1).sum()) == RealScalar(rows));
VERIFY(ei_real(ones.row(r1).sum()) == RealScalar(cols));
VERIFY(ei_real(ones.col(c1).dot(ones.col(c2))) == RealScalar(rows));
VERIFY(ei_real(ones.row(r1).dot(ones.row(r2))) == RealScalar(cols));
}
template<typename MatrixType>
void compare_using_data_and_stride(const MatrixType& m)
{
int rows = m.rows();
int cols = m.cols();
int size = m.size();
int stride = m.stride();
const typename MatrixType::Scalar* data = m.data();
for(int j=0;j<cols;++j)
for(int i=0;i<rows;++i)
VERIFY_IS_APPROX(m.coeff(i,j), data[(MatrixType::Flags&RowMajorBit) ? i*stride+j : j*stride + i]);
if(MatrixType::IsVectorAtCompileTime)
{
VERIFY_IS_APPROX(stride, int((&m.coeff(1))-(&m.coeff(0))));
for (int i=0;i<size;++i)
VERIFY_IS_APPROX(m.coeff(i), data[i*stride]);
}
}
template<typename MatrixType>
void data_and_stride(const MatrixType& m)
{
int rows = m.rows();
int cols = m.cols();
int r1 = ei_random<int>(0,rows-1);
int r2 = ei_random<int>(r1,rows-1);
int c1 = ei_random<int>(0,cols-1);
int c2 = ei_random<int>(c1,cols-1);
MatrixType m1 = MatrixType::Random(rows, cols);
compare_using_data_and_stride(m1.block(r1, c1, r2-r1+1, c2-c1+1));
compare_using_data_and_stride(m1.transpose().block(c1, r1, c2-c1+1, r2-r1+1));
compare_using_data_and_stride(m1.row(r1));
compare_using_data_and_stride(m1.col(c1));
compare_using_data_and_stride(m1.row(r1).transpose());
compare_using_data_and_stride(m1.col(c1).transpose());
}
void test_submatrices()
{
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST( submatrices(Matrix<float, 1, 1>()) );
CALL_SUBTEST( submatrices(Matrix4d()) );
CALL_SUBTEST( submatrices(MatrixXcf(3, 3)) );
CALL_SUBTEST( submatrices(MatrixXi(8, 12)) );
CALL_SUBTEST( submatrices(MatrixXcd(20, 20)) );
CALL_SUBTEST( submatrices(MatrixXf(20, 20)) );
CALL_SUBTEST( data_and_stride(MatrixXf(ei_random(5,50), ei_random(5,50))) );
CALL_SUBTEST( data_and_stride(Matrix<int,Dynamic,Dynamic,RowMajor>(ei_random(5,50), ei_random(5,50))) );
}
}
|
