1 // This file is part of Eigen, a lightweight C++ template library
2 // for linear algebra.
3 //
4 // Copyright (C) 2008-2009 Gael Guennebaud <[email protected]>
5 //
6 // This Source Code Form is subject to the terms of the Mozilla
7 // Public License v. 2.0. If a copy of the MPL was not distributed
8 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
9
10 #include "main.h"
11
array_for_matrix(const MatrixType & m)12 template<typename MatrixType> void array_for_matrix(const MatrixType& m)
13 {
14 typedef typename MatrixType::Scalar Scalar;
15 typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> ColVectorType;
16 typedef Matrix<Scalar, 1, MatrixType::ColsAtCompileTime> RowVectorType;
17
18 Index rows = m.rows();
19 Index cols = m.cols();
20
21 MatrixType m1 = MatrixType::Random(rows, cols),
22 m2 = MatrixType::Random(rows, cols),
23 m3(rows, cols);
24
25 ColVectorType cv1 = ColVectorType::Random(rows);
26 RowVectorType rv1 = RowVectorType::Random(cols);
27
28 Scalar s1 = internal::random<Scalar>(),
29 s2 = internal::random<Scalar>();
30
31 // scalar addition
32 VERIFY_IS_APPROX(m1.array() + s1, s1 + m1.array());
33 VERIFY_IS_APPROX((m1.array() + s1).matrix(), MatrixType::Constant(rows,cols,s1) + m1);
34 VERIFY_IS_APPROX(((m1*Scalar(2)).array() - s2).matrix(), (m1+m1) - MatrixType::Constant(rows,cols,s2) );
35 m3 = m1;
36 m3.array() += s2;
37 VERIFY_IS_APPROX(m3, (m1.array() + s2).matrix());
38 m3 = m1;
39 m3.array() -= s1;
40 VERIFY_IS_APPROX(m3, (m1.array() - s1).matrix());
41
42 // reductions
43 VERIFY_IS_MUCH_SMALLER_THAN(m1.colwise().sum().sum() - m1.sum(), m1.squaredNorm());
44 VERIFY_IS_MUCH_SMALLER_THAN(m1.rowwise().sum().sum() - m1.sum(), m1.squaredNorm());
45 VERIFY_IS_MUCH_SMALLER_THAN(m1.colwise().sum() + m2.colwise().sum() - (m1+m2).colwise().sum(), (m1+m2).squaredNorm());
46 VERIFY_IS_MUCH_SMALLER_THAN(m1.rowwise().sum() - m2.rowwise().sum() - (m1-m2).rowwise().sum(), (m1-m2).squaredNorm());
47 VERIFY_IS_APPROX(m1.colwise().sum(), m1.colwise().redux(internal::scalar_sum_op<Scalar,Scalar>()));
48
49 // vector-wise ops
50 m3 = m1;
51 VERIFY_IS_APPROX(m3.colwise() += cv1, m1.colwise() + cv1);
52 m3 = m1;
53 VERIFY_IS_APPROX(m3.colwise() -= cv1, m1.colwise() - cv1);
54 m3 = m1;
55 VERIFY_IS_APPROX(m3.rowwise() += rv1, m1.rowwise() + rv1);
56 m3 = m1;
57 VERIFY_IS_APPROX(m3.rowwise() -= rv1, m1.rowwise() - rv1);
58
59 // empty objects
60 VERIFY_IS_APPROX((m1.template block<0,Dynamic>(0,0,0,cols).colwise().sum()), RowVectorType::Zero(cols));
61 VERIFY_IS_APPROX((m1.template block<Dynamic,0>(0,0,rows,0).rowwise().sum()), ColVectorType::Zero(rows));
62 VERIFY_IS_APPROX((m1.template block<0,Dynamic>(0,0,0,cols).colwise().prod()), RowVectorType::Ones(cols));
63 VERIFY_IS_APPROX((m1.template block<Dynamic,0>(0,0,rows,0).rowwise().prod()), ColVectorType::Ones(rows));
64
65 VERIFY_IS_APPROX(m1.block(0,0,0,cols).colwise().sum(), RowVectorType::Zero(cols));
66 VERIFY_IS_APPROX(m1.block(0,0,rows,0).rowwise().sum(), ColVectorType::Zero(rows));
67 VERIFY_IS_APPROX(m1.block(0,0,0,cols).colwise().prod(), RowVectorType::Ones(cols));
68 VERIFY_IS_APPROX(m1.block(0,0,rows,0).rowwise().prod(), ColVectorType::Ones(rows));
69
70 // verify the const accessors exist
71 const Scalar& ref_m1 = m.matrix().array().coeffRef(0);
72 const Scalar& ref_m2 = m.matrix().array().coeffRef(0,0);
73 const Scalar& ref_a1 = m.array().matrix().coeffRef(0);
74 const Scalar& ref_a2 = m.array().matrix().coeffRef(0,0);
75 VERIFY(&ref_a1 == &ref_m1);
76 VERIFY(&ref_a2 == &ref_m2);
77
78 // Check write accessors:
79 m1.array().coeffRef(0,0) = 1;
80 VERIFY_IS_APPROX(m1(0,0),Scalar(1));
81 m1.array()(0,0) = 2;
82 VERIFY_IS_APPROX(m1(0,0),Scalar(2));
83 m1.array().matrix().coeffRef(0,0) = 3;
84 VERIFY_IS_APPROX(m1(0,0),Scalar(3));
85 m1.array().matrix()(0,0) = 4;
86 VERIFY_IS_APPROX(m1(0,0),Scalar(4));
87 }
88
comparisons(const MatrixType & m)89 template<typename MatrixType> void comparisons(const MatrixType& m)
90 {
91 using std::abs;
92 typedef typename MatrixType::Scalar Scalar;
93 typedef typename NumTraits<Scalar>::Real RealScalar;
94
95 Index rows = m.rows();
96 Index cols = m.cols();
97
98 Index r = internal::random<Index>(0, rows-1),
99 c = internal::random<Index>(0, cols-1);
100
101 MatrixType m1 = MatrixType::Random(rows, cols),
102 m2 = MatrixType::Random(rows, cols),
103 m3(rows, cols);
104
105 VERIFY(((m1.array() + Scalar(1)) > m1.array()).all());
106 VERIFY(((m1.array() - Scalar(1)) < m1.array()).all());
107 if (rows*cols>1)
108 {
109 m3 = m1;
110 m3(r,c) += 1;
111 VERIFY(! (m1.array() < m3.array()).all() );
112 VERIFY(! (m1.array() > m3.array()).all() );
113 }
114
115 // comparisons to scalar
116 VERIFY( (m1.array() != (m1(r,c)+1) ).any() );
117 VERIFY( (m1.array() > (m1(r,c)-1) ).any() );
118 VERIFY( (m1.array() < (m1(r,c)+1) ).any() );
119 VERIFY( (m1.array() == m1(r,c) ).any() );
120 VERIFY( m1.cwiseEqual(m1(r,c)).any() );
121
122 // test Select
123 VERIFY_IS_APPROX( (m1.array()<m2.array()).select(m1,m2), m1.cwiseMin(m2) );
124 VERIFY_IS_APPROX( (m1.array()>m2.array()).select(m1,m2), m1.cwiseMax(m2) );
125 Scalar mid = (m1.cwiseAbs().minCoeff() + m1.cwiseAbs().maxCoeff())/Scalar(2);
126 for (int j=0; j<cols; ++j)
127 for (int i=0; i<rows; ++i)
128 m3(i,j) = abs(m1(i,j))<mid ? 0 : m1(i,j);
129 VERIFY_IS_APPROX( (m1.array().abs()<MatrixType::Constant(rows,cols,mid).array())
130 .select(MatrixType::Zero(rows,cols),m1), m3);
131 // shorter versions:
132 VERIFY_IS_APPROX( (m1.array().abs()<MatrixType::Constant(rows,cols,mid).array())
133 .select(0,m1), m3);
134 VERIFY_IS_APPROX( (m1.array().abs()>=MatrixType::Constant(rows,cols,mid).array())
135 .select(m1,0), m3);
136 // even shorter version:
137 VERIFY_IS_APPROX( (m1.array().abs()<mid).select(0,m1), m3);
138
139 // count
140 VERIFY(((m1.array().abs()+1)>RealScalar(0.1)).count() == rows*cols);
141
142 // and/or
143 VERIFY( ((m1.array()<RealScalar(0)).matrix() && (m1.array()>RealScalar(0)).matrix()).count() == 0);
144 VERIFY( ((m1.array()<RealScalar(0)).matrix() || (m1.array()>=RealScalar(0)).matrix()).count() == rows*cols);
145 RealScalar a = m1.cwiseAbs().mean();
146 VERIFY( ((m1.array()<-a).matrix() || (m1.array()>a).matrix()).count() == (m1.cwiseAbs().array()>a).count());
147
148 typedef Matrix<Index, Dynamic, 1> VectorOfIndices;
149
150 // TODO allows colwise/rowwise for array
151 VERIFY_IS_APPROX(((m1.array().abs()+1)>RealScalar(0.1)).matrix().colwise().count(), VectorOfIndices::Constant(cols,rows).transpose());
152 VERIFY_IS_APPROX(((m1.array().abs()+1)>RealScalar(0.1)).matrix().rowwise().count(), VectorOfIndices::Constant(rows, cols));
153 }
154
lpNorm(const VectorType & v)155 template<typename VectorType> void lpNorm(const VectorType& v)
156 {
157 using std::sqrt;
158 typedef typename VectorType::RealScalar RealScalar;
159 VectorType u = VectorType::Random(v.size());
160
161 if(v.size()==0)
162 {
163 VERIFY_IS_APPROX(u.template lpNorm<Infinity>(), RealScalar(0));
164 VERIFY_IS_APPROX(u.template lpNorm<1>(), RealScalar(0));
165 VERIFY_IS_APPROX(u.template lpNorm<2>(), RealScalar(0));
166 VERIFY_IS_APPROX(u.template lpNorm<5>(), RealScalar(0));
167 }
168 else
169 {
170 VERIFY_IS_APPROX(u.template lpNorm<Infinity>(), u.cwiseAbs().maxCoeff());
171 }
172
173 VERIFY_IS_APPROX(u.template lpNorm<1>(), u.cwiseAbs().sum());
174 VERIFY_IS_APPROX(u.template lpNorm<2>(), sqrt(u.array().abs().square().sum()));
175 VERIFY_IS_APPROX(numext::pow(u.template lpNorm<5>(), typename VectorType::RealScalar(5)), u.array().abs().pow(5).sum());
176 }
177
cwise_min_max(const MatrixType & m)178 template<typename MatrixType> void cwise_min_max(const MatrixType& m)
179 {
180 typedef typename MatrixType::Scalar Scalar;
181
182 Index rows = m.rows();
183 Index cols = m.cols();
184
185 MatrixType m1 = MatrixType::Random(rows, cols);
186
187 // min/max with array
188 Scalar maxM1 = m1.maxCoeff();
189 Scalar minM1 = m1.minCoeff();
190
191 VERIFY_IS_APPROX(MatrixType::Constant(rows,cols, minM1), m1.cwiseMin(MatrixType::Constant(rows,cols, minM1)));
192 VERIFY_IS_APPROX(m1, m1.cwiseMin(MatrixType::Constant(rows,cols, maxM1)));
193
194 VERIFY_IS_APPROX(MatrixType::Constant(rows,cols, maxM1), m1.cwiseMax(MatrixType::Constant(rows,cols, maxM1)));
195 VERIFY_IS_APPROX(m1, m1.cwiseMax(MatrixType::Constant(rows,cols, minM1)));
196
197 // min/max with scalar input
198 VERIFY_IS_APPROX(MatrixType::Constant(rows,cols, minM1), m1.cwiseMin( minM1));
199 VERIFY_IS_APPROX(m1, m1.cwiseMin(maxM1));
200 VERIFY_IS_APPROX(-m1, (-m1).cwiseMin(-minM1));
201 VERIFY_IS_APPROX(-m1.array(), ((-m1).array().min)( -minM1));
202
203 VERIFY_IS_APPROX(MatrixType::Constant(rows,cols, maxM1), m1.cwiseMax( maxM1));
204 VERIFY_IS_APPROX(m1, m1.cwiseMax(minM1));
205 VERIFY_IS_APPROX(-m1, (-m1).cwiseMax(-maxM1));
206 VERIFY_IS_APPROX(-m1.array(), ((-m1).array().max)(-maxM1));
207
208 VERIFY_IS_APPROX(MatrixType::Constant(rows,cols, minM1).array(), (m1.array().min)( minM1));
209 VERIFY_IS_APPROX(m1.array(), (m1.array().min)( maxM1));
210
211 VERIFY_IS_APPROX(MatrixType::Constant(rows,cols, maxM1).array(), (m1.array().max)( maxM1));
212 VERIFY_IS_APPROX(m1.array(), (m1.array().max)( minM1));
213
214 }
215
resize(const MatrixTraits & t)216 template<typename MatrixTraits> void resize(const MatrixTraits& t)
217 {
218 typedef typename MatrixTraits::Scalar Scalar;
219 typedef Matrix<Scalar,Dynamic,Dynamic> MatrixType;
220 typedef Array<Scalar,Dynamic,Dynamic> Array2DType;
221 typedef Matrix<Scalar,Dynamic,1> VectorType;
222 typedef Array<Scalar,Dynamic,1> Array1DType;
223
224 Index rows = t.rows(), cols = t.cols();
225
226 MatrixType m(rows,cols);
227 VectorType v(rows);
228 Array2DType a2(rows,cols);
229 Array1DType a1(rows);
230
231 m.array().resize(rows+1,cols+1);
232 VERIFY(m.rows()==rows+1 && m.cols()==cols+1);
233 a2.matrix().resize(rows+1,cols+1);
234 VERIFY(a2.rows()==rows+1 && a2.cols()==cols+1);
235 v.array().resize(cols);
236 VERIFY(v.size()==cols);
237 a1.matrix().resize(cols);
238 VERIFY(a1.size()==cols);
239 }
240
241 template<int>
regression_bug_654()242 void regression_bug_654()
243 {
244 ArrayXf a = RowVectorXf(3);
245 VectorXf v = Array<float,1,Dynamic>(3);
246 }
247
248 // Check propagation of LvalueBit through Array/Matrix-Wrapper
249 template<int>
regrrssion_bug_1410()250 void regrrssion_bug_1410()
251 {
252 const Matrix4i M;
253 const Array4i A;
254 ArrayWrapper<const Matrix4i> MA = M.array();
255 MA.row(0);
256 MatrixWrapper<const Array4i> AM = A.matrix();
257 AM.row(0);
258
259 VERIFY((internal::traits<ArrayWrapper<const Matrix4i> >::Flags&LvalueBit)==0);
260 VERIFY((internal::traits<MatrixWrapper<const Array4i> >::Flags&LvalueBit)==0);
261
262 VERIFY((internal::traits<ArrayWrapper<Matrix4i> >::Flags&LvalueBit)==LvalueBit);
263 VERIFY((internal::traits<MatrixWrapper<Array4i> >::Flags&LvalueBit)==LvalueBit);
264 }
265
EIGEN_DECLARE_TEST(array_for_matrix)266 EIGEN_DECLARE_TEST(array_for_matrix)
267 {
268 for(int i = 0; i < g_repeat; i++) {
269 CALL_SUBTEST_1( array_for_matrix(Matrix<float, 1, 1>()) );
270 CALL_SUBTEST_2( array_for_matrix(Matrix2f()) );
271 CALL_SUBTEST_3( array_for_matrix(Matrix4d()) );
272 CALL_SUBTEST_4( array_for_matrix(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
273 CALL_SUBTEST_5( array_for_matrix(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
274 CALL_SUBTEST_6( array_for_matrix(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
275 }
276 for(int i = 0; i < g_repeat; i++) {
277 CALL_SUBTEST_1( comparisons(Matrix<float, 1, 1>()) );
278 CALL_SUBTEST_2( comparisons(Matrix2f()) );
279 CALL_SUBTEST_3( comparisons(Matrix4d()) );
280 CALL_SUBTEST_5( comparisons(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
281 CALL_SUBTEST_6( comparisons(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
282 }
283 for(int i = 0; i < g_repeat; i++) {
284 CALL_SUBTEST_1( cwise_min_max(Matrix<float, 1, 1>()) );
285 CALL_SUBTEST_2( cwise_min_max(Matrix2f()) );
286 CALL_SUBTEST_3( cwise_min_max(Matrix4d()) );
287 CALL_SUBTEST_5( cwise_min_max(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
288 CALL_SUBTEST_6( cwise_min_max(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
289 }
290 for(int i = 0; i < g_repeat; i++) {
291 CALL_SUBTEST_1( lpNorm(Matrix<float, 1, 1>()) );
292 CALL_SUBTEST_2( lpNorm(Vector2f()) );
293 CALL_SUBTEST_7( lpNorm(Vector3d()) );
294 CALL_SUBTEST_8( lpNorm(Vector4f()) );
295 CALL_SUBTEST_5( lpNorm(VectorXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
296 CALL_SUBTEST_4( lpNorm(VectorXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
297 }
298 CALL_SUBTEST_5( lpNorm(VectorXf(0)) );
299 CALL_SUBTEST_4( lpNorm(VectorXcf(0)) );
300 for(int i = 0; i < g_repeat; i++) {
301 CALL_SUBTEST_4( resize(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
302 CALL_SUBTEST_5( resize(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
303 CALL_SUBTEST_6( resize(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
304 }
305 CALL_SUBTEST_6( regression_bug_654<0>() );
306 CALL_SUBTEST_6( regrrssion_bug_1410<0>() );
307 }
308