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
|
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#define EIGEN_NO_STATIC_ASSERT // otherwise we fail at compile time on unused paths
#include "main.h"
template<typename MatrixType> void block(const MatrixType& m)
{
typedef typename MatrixType::Index Index;
typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::RealScalar RealScalar;
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
typedef Matrix<Scalar, 1, MatrixType::ColsAtCompileTime> RowVectorType;
typedef Matrix<Scalar, Dynamic, Dynamic> DynamicMatrixType;
typedef Matrix<Scalar, Dynamic, 1> DynamicVectorType;
Index rows = m.rows();
Index cols = m.cols();
MatrixType m1 = MatrixType::Random(rows, cols),
m1_copy = m1,
m2 = MatrixType::Random(rows, cols),
m3(rows, cols),
ones = MatrixType::Ones(rows, cols);
VectorType v1 = VectorType::Random(rows);
Scalar s1 = internal::random<Scalar>();
Index r1 = internal::random<Index>(0,rows-1);
Index r2 = internal::random<Index>(r1,rows-1);
Index c1 = internal::random<Index>(0,cols-1);
Index c2 = internal::random<Index>(c1,cols-1);
//check row() and col()
VERIFY_IS_EQUAL(m1.col(c1).transpose(), m1.transpose().row(c1));
//check operator(), both constant and non-constant, on row() and col()
m1 = m1_copy;
m1.row(r1) += s1 * m1_copy.row(r2);
VERIFY_IS_APPROX(m1.row(r1), m1_copy.row(r1) + s1 * m1_copy.row(r2));
// check nested block xpr on lhs
m1.row(r1).row(0) += s1 * m1_copy.row(r2);
VERIFY_IS_APPROX(m1.row(r1), m1_copy.row(r1) + Scalar(2) * s1 * m1_copy.row(r2));
m1 = m1_copy;
m1.col(c1) += s1 * m1_copy.col(c2);
VERIFY_IS_APPROX(m1.col(c1), m1_copy.col(c1) + s1 * m1_copy.col(c2));
m1.col(c1).col(0) += s1 * m1_copy.col(c2);
VERIFY_IS_APPROX(m1.col(c1), m1_copy.col(c1) + Scalar(2) * s1 * m1_copy.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_EQUAL(b1, m1.block(r1,c1,1,1));
VERIFY_IS_EQUAL(m1.row(r1), br1);
VERIFY_IS_EQUAL(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);
enum {
BlockRows = 2,
BlockCols = 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_EQUAL(b, m1.block(3,3,BlockRows,BlockCols));
}
if (rows>2)
{
// test sub vectors
VERIFY_IS_EQUAL(v1.template head<2>(), v1.block(0,0,2,1));
VERIFY_IS_EQUAL(v1.template head<2>(), v1.head(2));
VERIFY_IS_EQUAL(v1.template head<2>(), v1.segment(0,2));
VERIFY_IS_EQUAL(v1.template head<2>(), v1.template segment<2>(0));
Index i = rows-2;
VERIFY_IS_EQUAL(v1.template tail<2>(), v1.block(i,0,2,1));
VERIFY_IS_EQUAL(v1.template tail<2>(), v1.tail(2));
VERIFY_IS_EQUAL(v1.template tail<2>(), v1.segment(i,2));
VERIFY_IS_EQUAL(v1.template tail<2>(), v1.template segment<2>(i));
i = internal::random<Index>(0,rows-2);
VERIFY_IS_EQUAL(v1.segment(i,2), v1.template segment<2>(i));
}
// stress some basic stuffs with block matrices
VERIFY(internal::real(ones.col(c1).sum()) == RealScalar(rows));
VERIFY(internal::real(ones.row(r1).sum()) == RealScalar(cols));
VERIFY(internal::real(ones.col(c1).dot(ones.col(c2))) == RealScalar(rows));
VERIFY(internal::real(ones.row(r1).dot(ones.row(r2))) == RealScalar(cols));
// now test some block-inside-of-block.
// expressions with direct access
VERIFY_IS_EQUAL( (m1.block(r1,c1,rows-r1,cols-c1).block(r2-r1,c2-c1,rows-r2,cols-c2)) , (m1.block(r2,c2,rows-r2,cols-c2)) );
VERIFY_IS_EQUAL( (m1.block(r1,c1,r2-r1+1,c2-c1+1).row(0)) , (m1.row(r1).segment(c1,c2-c1+1)) );
VERIFY_IS_EQUAL( (m1.block(r1,c1,r2-r1+1,c2-c1+1).col(0)) , (m1.col(c1).segment(r1,r2-r1+1)) );
VERIFY_IS_EQUAL( (m1.block(r1,c1,r2-r1+1,c2-c1+1).transpose().col(0)) , (m1.row(r1).segment(c1,c2-c1+1)).transpose() );
VERIFY_IS_EQUAL( (m1.transpose().block(c1,r1,c2-c1+1,r2-r1+1).col(0)) , (m1.row(r1).segment(c1,c2-c1+1)).transpose() );
// expressions without direct access
VERIFY_IS_EQUAL( ((m1+m2).block(r1,c1,rows-r1,cols-c1).block(r2-r1,c2-c1,rows-r2,cols-c2)) , ((m1+m2).block(r2,c2,rows-r2,cols-c2)) );
VERIFY_IS_EQUAL( ((m1+m2).block(r1,c1,r2-r1+1,c2-c1+1).row(0)) , ((m1+m2).row(r1).segment(c1,c2-c1+1)) );
VERIFY_IS_EQUAL( ((m1+m2).block(r1,c1,r2-r1+1,c2-c1+1).col(0)) , ((m1+m2).col(c1).segment(r1,r2-r1+1)) );
VERIFY_IS_EQUAL( ((m1+m2).block(r1,c1,r2-r1+1,c2-c1+1).transpose().col(0)) , ((m1+m2).row(r1).segment(c1,c2-c1+1)).transpose() );
VERIFY_IS_EQUAL( ((m1+m2).transpose().block(c1,r1,c2-c1+1,r2-r1+1).col(0)) , ((m1+m2).row(r1).segment(c1,c2-c1+1)).transpose() );
// evaluation into plain matrices from expressions with direct access (stress MapBase)
DynamicMatrixType dm;
DynamicVectorType dv;
dm.setZero();
dm = m1.block(r1,c1,rows-r1,cols-c1).block(r2-r1,c2-c1,rows-r2,cols-c2);
VERIFY_IS_EQUAL(dm, (m1.block(r2,c2,rows-r2,cols-c2)));
dm.setZero();
dv.setZero();
dm = m1.block(r1,c1,r2-r1+1,c2-c1+1).row(0).transpose();
dv = m1.row(r1).segment(c1,c2-c1+1);
VERIFY_IS_EQUAL(dv, dm);
dm.setZero();
dv.setZero();
dm = m1.col(c1).segment(r1,r2-r1+1);
dv = m1.block(r1,c1,r2-r1+1,c2-c1+1).col(0);
VERIFY_IS_EQUAL(dv, dm);
dm.setZero();
dv.setZero();
dm = m1.block(r1,c1,r2-r1+1,c2-c1+1).transpose().col(0);
dv = m1.row(r1).segment(c1,c2-c1+1);
VERIFY_IS_EQUAL(dv, dm);
dm.setZero();
dv.setZero();
dm = m1.row(r1).segment(c1,c2-c1+1).transpose();
dv = m1.transpose().block(c1,r1,c2-c1+1,r2-r1+1).col(0);
VERIFY_IS_EQUAL(dv, dm);
}
template<typename MatrixType>
void compare_using_data_and_stride(const MatrixType& m)
{
typedef typename MatrixType::Index Index;
Index rows = m.rows();
Index cols = m.cols();
Index size = m.size();
Index innerStride = m.innerStride();
Index outerStride = m.outerStride();
Index rowStride = m.rowStride();
Index colStride = m.colStride();
const typename MatrixType::Scalar* data = m.data();
for(int j=0;j<cols;++j)
for(int i=0;i<rows;++i)
VERIFY(m.coeff(i,j) == data[i*rowStride + j*colStride]);
if(!MatrixType::IsVectorAtCompileTime)
{
for(int j=0;j<cols;++j)
for(int i=0;i<rows;++i)
VERIFY(m.coeff(i,j) == data[(MatrixType::Flags&RowMajorBit)
? i*outerStride + j*innerStride
: j*outerStride + i*innerStride]);
}
if(MatrixType::IsVectorAtCompileTime)
{
VERIFY(innerStride == int((&m.coeff(1))-(&m.coeff(0))));
for (int i=0;i<size;++i)
VERIFY(m.coeff(i) == data[i*innerStride]);
}
}
template<typename MatrixType>
void data_and_stride(const MatrixType& m)
{
typedef typename MatrixType::Index Index;
Index rows = m.rows();
Index cols = m.cols();
Index r1 = internal::random<Index>(0,rows-1);
Index r2 = internal::random<Index>(r1,rows-1);
Index c1 = internal::random<Index>(0,cols-1);
Index c2 = internal::random<Index>(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_block()
{
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_1( block(Matrix<float, 1, 1>()) );
CALL_SUBTEST_2( block(Matrix4d()) );
CALL_SUBTEST_3( block(MatrixXcf(3, 3)) );
CALL_SUBTEST_4( block(MatrixXi(8, 12)) );
CALL_SUBTEST_5( block(MatrixXcd(20, 20)) );
CALL_SUBTEST_6( block(MatrixXf(20, 20)) );
CALL_SUBTEST_8( block(Matrix<float,Dynamic,4>(3, 4)) );
#ifndef EIGEN_DEFAULT_TO_ROW_MAJOR
CALL_SUBTEST_6( data_and_stride(MatrixXf(internal::random(5,50), internal::random(5,50))) );
CALL_SUBTEST_7( data_and_stride(Matrix<int,Dynamic,Dynamic,RowMajor>(internal::random(5,50), internal::random(5,50))) );
#endif
}
}
|