source: pacpussensors/trunk/Vislab/lib3dv-1.2.0/lib3dv/eigen/test/sparse_basic.cpp@ 136

Last change on this file since 136 was 136, checked in by ldecherf, 7 years ago

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1// This file is part of Eigen, a lightweight C++ template library
2// for linear algebra.
3//
4// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
5// Copyright (C) 2008 Daniel Gomez Ferro <dgomezferro@gmail.com>
6// Copyright (C) 2013 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
7//
8// This Source Code Form is subject to the terms of the Mozilla
9// Public License v. 2.0. If a copy of the MPL was not distributed
10// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
11
12#include "sparse.h"
13
14template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& ref)
15{
16 typedef typename SparseMatrixType::Index Index;
17 typedef Matrix<Index,2,1> Vector2;
18
19 const Index rows = ref.rows();
20 const Index cols = ref.cols();
21 typedef typename SparseMatrixType::Scalar Scalar;
22 enum { Flags = SparseMatrixType::Flags };
23
24 double density = (std::max)(8./(rows*cols), 0.01);
25 typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
26 typedef Matrix<Scalar,Dynamic,1> DenseVector;
27 typedef Matrix<Scalar,1,Dynamic> RowDenseVector;
28 Scalar eps = 1e-6;
29
30 Scalar s1 = internal::random<Scalar>();
31 {
32 SparseMatrixType m(rows, cols);
33 DenseMatrix refMat = DenseMatrix::Zero(rows, cols);
34 DenseVector vec1 = DenseVector::Random(rows);
35
36 std::vector<Vector2> zeroCoords;
37 std::vector<Vector2> nonzeroCoords;
38 initSparse<Scalar>(density, refMat, m, 0, &zeroCoords, &nonzeroCoords);
39
40 if (zeroCoords.size()==0 || nonzeroCoords.size()==0)
41 return;
42
43 // test coeff and coeffRef
44 for (int i=0; i<(int)zeroCoords.size(); ++i)
45 {
46 VERIFY_IS_MUCH_SMALLER_THAN( m.coeff(zeroCoords[i].x(),zeroCoords[i].y()), eps );
47 if(internal::is_same<SparseMatrixType,SparseMatrix<Scalar,Flags> >::value)
48 VERIFY_RAISES_ASSERT( m.coeffRef(zeroCoords[0].x(),zeroCoords[0].y()) = 5 );
49 }
50 VERIFY_IS_APPROX(m, refMat);
51
52 m.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
53 refMat.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
54
55 VERIFY_IS_APPROX(m, refMat);
56
57 // test InnerIterators and Block expressions
58 for (int t=0; t<10; ++t)
59 {
60 int j = internal::random<int>(0,cols-1);
61 int i = internal::random<int>(0,rows-1);
62 int w = internal::random<int>(1,cols-j-1);
63 int h = internal::random<int>(1,rows-i-1);
64
65 VERIFY_IS_APPROX(m.block(i,j,h,w), refMat.block(i,j,h,w));
66 for(int c=0; c<w; c++)
67 {
68 VERIFY_IS_APPROX(m.block(i,j,h,w).col(c), refMat.block(i,j,h,w).col(c));
69 for(int r=0; r<h; r++)
70 {
71 VERIFY_IS_APPROX(m.block(i,j,h,w).col(c).coeff(r), refMat.block(i,j,h,w).col(c).coeff(r));
72 VERIFY_IS_APPROX(m.block(i,j,h,w).coeff(r,c), refMat.block(i,j,h,w).coeff(r,c));
73 }
74 }
75 for(int r=0; r<h; r++)
76 {
77 VERIFY_IS_APPROX(m.block(i,j,h,w).row(r), refMat.block(i,j,h,w).row(r));
78 for(int c=0; c<w; c++)
79 {
80 VERIFY_IS_APPROX(m.block(i,j,h,w).row(r).coeff(c), refMat.block(i,j,h,w).row(r).coeff(c));
81 VERIFY_IS_APPROX(m.block(i,j,h,w).coeff(r,c), refMat.block(i,j,h,w).coeff(r,c));
82 }
83 }
84
85 VERIFY_IS_APPROX(m.middleCols(j,w), refMat.middleCols(j,w));
86 VERIFY_IS_APPROX(m.middleRows(i,h), refMat.middleRows(i,h));
87 for(int r=0; r<h; r++)
88 {
89 VERIFY_IS_APPROX(m.middleCols(j,w).row(r), refMat.middleCols(j,w).row(r));
90 VERIFY_IS_APPROX(m.middleRows(i,h).row(r), refMat.middleRows(i,h).row(r));
91 for(int c=0; c<w; c++)
92 {
93 VERIFY_IS_APPROX(m.col(c).coeff(r), refMat.col(c).coeff(r));
94 VERIFY_IS_APPROX(m.row(r).coeff(c), refMat.row(r).coeff(c));
95
96 VERIFY_IS_APPROX(m.middleCols(j,w).coeff(r,c), refMat.middleCols(j,w).coeff(r,c));
97 VERIFY_IS_APPROX(m.middleRows(i,h).coeff(r,c), refMat.middleRows(i,h).coeff(r,c));
98 if(m.middleCols(j,w).coeff(r,c) != Scalar(0))
99 {
100 VERIFY_IS_APPROX(m.middleCols(j,w).coeffRef(r,c), refMat.middleCols(j,w).coeff(r,c));
101 }
102 if(m.middleRows(i,h).coeff(r,c) != Scalar(0))
103 {
104 VERIFY_IS_APPROX(m.middleRows(i,h).coeff(r,c), refMat.middleRows(i,h).coeff(r,c));
105 }
106 }
107 }
108 for(int c=0; c<w; c++)
109 {
110 VERIFY_IS_APPROX(m.middleCols(j,w).col(c), refMat.middleCols(j,w).col(c));
111 VERIFY_IS_APPROX(m.middleRows(i,h).col(c), refMat.middleRows(i,h).col(c));
112 }
113 }
114
115 for(int c=0; c<cols; c++)
116 {
117 VERIFY_IS_APPROX(m.col(c) + m.col(c), (m + m).col(c));
118 VERIFY_IS_APPROX(m.col(c) + m.col(c), refMat.col(c) + refMat.col(c));
119 }
120
121 for(int r=0; r<rows; r++)
122 {
123 VERIFY_IS_APPROX(m.row(r) + m.row(r), (m + m).row(r));
124 VERIFY_IS_APPROX(m.row(r) + m.row(r), refMat.row(r) + refMat.row(r));
125 }
126
127
128 // test assertion
129 VERIFY_RAISES_ASSERT( m.coeffRef(-1,1) = 0 );
130 VERIFY_RAISES_ASSERT( m.coeffRef(0,m.cols()) = 0 );
131 }
132
133 // test insert (inner random)
134 {
135 DenseMatrix m1(rows,cols);
136 m1.setZero();
137 SparseMatrixType m2(rows,cols);
138 if(internal::random<int>()%2)
139 m2.reserve(VectorXi::Constant(m2.outerSize(), 2));
140 for (Index j=0; j<cols; ++j)
141 {
142 for (Index k=0; k<rows/2; ++k)
143 {
144 Index i = internal::random<Index>(0,rows-1);
145 if (m1.coeff(i,j)==Scalar(0))
146 m2.insert(i,j) = m1(i,j) = internal::random<Scalar>();
147 }
148 }
149 m2.finalize();
150 VERIFY_IS_APPROX(m2,m1);
151 }
152
153 // test insert (fully random)
154 {
155 DenseMatrix m1(rows,cols);
156 m1.setZero();
157 SparseMatrixType m2(rows,cols);
158 if(internal::random<int>()%2)
159 m2.reserve(VectorXi::Constant(m2.outerSize(), 2));
160 for (int k=0; k<rows*cols; ++k)
161 {
162 Index i = internal::random<Index>(0,rows-1);
163 Index j = internal::random<Index>(0,cols-1);
164 if ((m1.coeff(i,j)==Scalar(0)) && (internal::random<int>()%2))
165 m2.insert(i,j) = m1(i,j) = internal::random<Scalar>();
166 else
167 {
168 Scalar v = internal::random<Scalar>();
169 m2.coeffRef(i,j) += v;
170 m1(i,j) += v;
171 }
172 }
173 VERIFY_IS_APPROX(m2,m1);
174 }
175
176 // test insert (un-compressed)
177 for(int mode=0;mode<4;++mode)
178 {
179 DenseMatrix m1(rows,cols);
180 m1.setZero();
181 SparseMatrixType m2(rows,cols);
182 VectorXi r(VectorXi::Constant(m2.outerSize(), ((mode%2)==0) ? m2.innerSize() : std::max<int>(1,m2.innerSize()/8)));
183 m2.reserve(r);
184 for (int k=0; k<rows*cols; ++k)
185 {
186 Index i = internal::random<Index>(0,rows-1);
187 Index j = internal::random<Index>(0,cols-1);
188 if (m1.coeff(i,j)==Scalar(0))
189 m2.insert(i,j) = m1(i,j) = internal::random<Scalar>();
190 if(mode==3)
191 m2.reserve(r);
192 }
193 if(internal::random<int>()%2)
194 m2.makeCompressed();
195 VERIFY_IS_APPROX(m2,m1);
196 }
197
198 // test innerVector()
199 {
200 DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
201 SparseMatrixType m2(rows, rows);
202 initSparse<Scalar>(density, refMat2, m2);
203 Index j0 = internal::random<Index>(0,rows-1);
204 Index j1 = internal::random<Index>(0,rows-1);
205 if(SparseMatrixType::IsRowMajor)
206 VERIFY_IS_APPROX(m2.innerVector(j0), refMat2.row(j0));
207 else
208 VERIFY_IS_APPROX(m2.innerVector(j0), refMat2.col(j0));
209
210 if(SparseMatrixType::IsRowMajor)
211 VERIFY_IS_APPROX(m2.innerVector(j0)+m2.innerVector(j1), refMat2.row(j0)+refMat2.row(j1));
212 else
213 VERIFY_IS_APPROX(m2.innerVector(j0)+m2.innerVector(j1), refMat2.col(j0)+refMat2.col(j1));
214
215 SparseMatrixType m3(rows,rows);
216 m3.reserve(VectorXi::Constant(rows,rows/2));
217 for(Index j=0; j<rows; ++j)
218 for(Index k=0; k<j; ++k)
219 m3.insertByOuterInner(j,k) = k+1;
220 for(Index j=0; j<rows; ++j)
221 {
222 VERIFY(j==numext::real(m3.innerVector(j).nonZeros()));
223 if(j>0)
224 VERIFY(j==numext::real(m3.innerVector(j).lastCoeff()));
225 }
226 m3.makeCompressed();
227 for(Index j=0; j<rows; ++j)
228 {
229 VERIFY(j==numext::real(m3.innerVector(j).nonZeros()));
230 if(j>0)
231 VERIFY(j==numext::real(m3.innerVector(j).lastCoeff()));
232 }
233
234 //m2.innerVector(j0) = 2*m2.innerVector(j1);
235 //refMat2.col(j0) = 2*refMat2.col(j1);
236 //VERIFY_IS_APPROX(m2, refMat2);
237 }
238
239 // test innerVectors()
240 {
241 DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
242 SparseMatrixType m2(rows, rows);
243 initSparse<Scalar>(density, refMat2, m2);
244 if(internal::random<float>(0,1)>0.5) m2.makeCompressed();
245
246 Index j0 = internal::random<Index>(0,rows-2);
247 Index j1 = internal::random<Index>(0,rows-2);
248 Index n0 = internal::random<Index>(1,rows-(std::max)(j0,j1));
249 if(SparseMatrixType::IsRowMajor)
250 VERIFY_IS_APPROX(m2.innerVectors(j0,n0), refMat2.block(j0,0,n0,cols));
251 else
252 VERIFY_IS_APPROX(m2.innerVectors(j0,n0), refMat2.block(0,j0,rows,n0));
253 if(SparseMatrixType::IsRowMajor)
254 VERIFY_IS_APPROX(m2.innerVectors(j0,n0)+m2.innerVectors(j1,n0),
255 refMat2.middleRows(j0,n0)+refMat2.middleRows(j1,n0));
256 else
257 VERIFY_IS_APPROX(m2.innerVectors(j0,n0)+m2.innerVectors(j1,n0),
258 refMat2.block(0,j0,rows,n0)+refMat2.block(0,j1,rows,n0));
259
260 VERIFY_IS_APPROX(m2, refMat2);
261
262 m2.innerVectors(j0,n0) = m2.innerVectors(j0,n0) + m2.innerVectors(j1,n0);
263 if(SparseMatrixType::IsRowMajor)
264 refMat2.middleRows(j0,n0) = (refMat2.middleRows(j0,n0) + refMat2.middleRows(j1,n0)).eval();
265 else
266 refMat2.middleCols(j0,n0) = (refMat2.middleCols(j0,n0) + refMat2.middleCols(j1,n0)).eval();
267
268 VERIFY_IS_APPROX(m2, refMat2);
269
270 }
271
272 // test basic computations
273 {
274 DenseMatrix refM1 = DenseMatrix::Zero(rows, rows);
275 DenseMatrix refM2 = DenseMatrix::Zero(rows, rows);
276 DenseMatrix refM3 = DenseMatrix::Zero(rows, rows);
277 DenseMatrix refM4 = DenseMatrix::Zero(rows, rows);
278 SparseMatrixType m1(rows, rows);
279 SparseMatrixType m2(rows, rows);
280 SparseMatrixType m3(rows, rows);
281 SparseMatrixType m4(rows, rows);
282 initSparse<Scalar>(density, refM1, m1);
283 initSparse<Scalar>(density, refM2, m2);
284 initSparse<Scalar>(density, refM3, m3);
285 initSparse<Scalar>(density, refM4, m4);
286
287 VERIFY_IS_APPROX(m1+m2, refM1+refM2);
288 VERIFY_IS_APPROX(m1+m2+m3, refM1+refM2+refM3);
289 VERIFY_IS_APPROX(m3.cwiseProduct(m1+m2), refM3.cwiseProduct(refM1+refM2));
290 VERIFY_IS_APPROX(m1*s1-m2, refM1*s1-refM2);
291
292 VERIFY_IS_APPROX(m1*=s1, refM1*=s1);
293 VERIFY_IS_APPROX(m1/=s1, refM1/=s1);
294
295 VERIFY_IS_APPROX(m1+=m2, refM1+=refM2);
296 VERIFY_IS_APPROX(m1-=m2, refM1-=refM2);
297
298 if(SparseMatrixType::IsRowMajor)
299 VERIFY_IS_APPROX(m1.innerVector(0).dot(refM2.row(0)), refM1.row(0).dot(refM2.row(0)));
300 else
301 VERIFY_IS_APPROX(m1.innerVector(0).dot(refM2.row(0)), refM1.col(0).dot(refM2.row(0)));
302
303 VERIFY_IS_APPROX(m1.conjugate(), refM1.conjugate());
304 VERIFY_IS_APPROX(m1.real(), refM1.real());
305
306 refM4.setRandom();
307 // sparse cwise* dense
308 VERIFY_IS_APPROX(m3.cwiseProduct(refM4), refM3.cwiseProduct(refM4));
309 // dense cwise* sparse
310 VERIFY_IS_APPROX(refM4.cwiseProduct(m3), refM4.cwiseProduct(refM3));
311// VERIFY_IS_APPROX(m3.cwise()/refM4, refM3.cwise()/refM4);
312
313 // test aliasing
314 VERIFY_IS_APPROX((m1 = -m1), (refM1 = -refM1));
315 VERIFY_IS_APPROX((m1 = m1.transpose()), (refM1 = refM1.transpose().eval()));
316 VERIFY_IS_APPROX((m1 = -m1.transpose()), (refM1 = -refM1.transpose().eval()));
317 VERIFY_IS_APPROX((m1 += -m1), (refM1 += -refM1));
318 }
319
320 // test transpose
321 {
322 DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
323 SparseMatrixType m2(rows, rows);
324 initSparse<Scalar>(density, refMat2, m2);
325 VERIFY_IS_APPROX(m2.transpose().eval(), refMat2.transpose().eval());
326 VERIFY_IS_APPROX(m2.transpose(), refMat2.transpose());
327
328 VERIFY_IS_APPROX(SparseMatrixType(m2.adjoint()), refMat2.adjoint());
329 }
330
331
332
333 // test generic blocks
334 {
335 DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
336 SparseMatrixType m2(rows, rows);
337 initSparse<Scalar>(density, refMat2, m2);
338 Index j0 = internal::random<Index>(0,rows-2);
339 Index j1 = internal::random<Index>(0,rows-2);
340 Index n0 = internal::random<Index>(1,rows-(std::max)(j0,j1));
341 if(SparseMatrixType::IsRowMajor)
342 VERIFY_IS_APPROX(m2.block(j0,0,n0,cols), refMat2.block(j0,0,n0,cols));
343 else
344 VERIFY_IS_APPROX(m2.block(0,j0,rows,n0), refMat2.block(0,j0,rows,n0));
345
346 if(SparseMatrixType::IsRowMajor)
347 VERIFY_IS_APPROX(m2.block(j0,0,n0,cols)+m2.block(j1,0,n0,cols),
348 refMat2.block(j0,0,n0,cols)+refMat2.block(j1,0,n0,cols));
349 else
350 VERIFY_IS_APPROX(m2.block(0,j0,rows,n0)+m2.block(0,j1,rows,n0),
351 refMat2.block(0,j0,rows,n0)+refMat2.block(0,j1,rows,n0));
352
353 Index i = internal::random<Index>(0,m2.outerSize()-1);
354 if(SparseMatrixType::IsRowMajor) {
355 m2.innerVector(i) = m2.innerVector(i) * s1;
356 refMat2.row(i) = refMat2.row(i) * s1;
357 VERIFY_IS_APPROX(m2,refMat2);
358 } else {
359 m2.innerVector(i) = m2.innerVector(i) * s1;
360 refMat2.col(i) = refMat2.col(i) * s1;
361 VERIFY_IS_APPROX(m2,refMat2);
362 }
363
364 VERIFY_IS_APPROX(DenseVector(m2.col(j0)), refMat2.col(j0));
365 VERIFY_IS_APPROX(m2.col(j0), refMat2.col(j0));
366
367 VERIFY_IS_APPROX(RowDenseVector(m2.row(j0)), refMat2.row(j0));
368 VERIFY_IS_APPROX(m2.row(j0), refMat2.row(j0));
369
370 VERIFY_IS_APPROX(m2.block(j0,j1,n0,n0), refMat2.block(j0,j1,n0,n0));
371 VERIFY_IS_APPROX((2*m2).block(j0,j1,n0,n0), (2*refMat2).block(j0,j1,n0,n0));
372 }
373
374 // test prune
375 {
376 SparseMatrixType m2(rows, rows);
377 DenseMatrix refM2(rows, rows);
378 refM2.setZero();
379 int countFalseNonZero = 0;
380 int countTrueNonZero = 0;
381 for (Index j=0; j<m2.outerSize(); ++j)
382 {
383 m2.startVec(j);
384 for (Index i=0; i<m2.innerSize(); ++i)
385 {
386 float x = internal::random<float>(0,1);
387 if (x<0.1)
388 {
389 // do nothing
390 }
391 else if (x<0.5)
392 {
393 countFalseNonZero++;
394 m2.insertBackByOuterInner(j,i) = Scalar(0);
395 }
396 else
397 {
398 countTrueNonZero++;
399 m2.insertBackByOuterInner(j,i) = Scalar(1);
400 if(SparseMatrixType::IsRowMajor)
401 refM2(j,i) = Scalar(1);
402 else
403 refM2(i,j) = Scalar(1);
404 }
405 }
406 }
407 m2.finalize();
408 VERIFY(countFalseNonZero+countTrueNonZero == m2.nonZeros());
409 VERIFY_IS_APPROX(m2, refM2);
410 m2.prune(Scalar(1));
411 VERIFY(countTrueNonZero==m2.nonZeros());
412 VERIFY_IS_APPROX(m2, refM2);
413 }
414
415 // test setFromTriplets
416 {
417 typedef Triplet<Scalar,Index> TripletType;
418 std::vector<TripletType> triplets;
419 int ntriplets = rows*cols;
420 triplets.reserve(ntriplets);
421 DenseMatrix refMat(rows,cols);
422 refMat.setZero();
423 for(int i=0;i<ntriplets;++i)
424 {
425 Index r = internal::random<Index>(0,rows-1);
426 Index c = internal::random<Index>(0,cols-1);
427 Scalar v = internal::random<Scalar>();
428 triplets.push_back(TripletType(r,c,v));
429 refMat(r,c) += v;
430 }
431 SparseMatrixType m(rows,cols);
432 m.setFromTriplets(triplets.begin(), triplets.end());
433 VERIFY_IS_APPROX(m, refMat);
434 }
435
436 // test triangularView
437 {
438 DenseMatrix refMat2(rows, rows), refMat3(rows, rows);
439 SparseMatrixType m2(rows, rows), m3(rows, rows);
440 initSparse<Scalar>(density, refMat2, m2);
441 refMat3 = refMat2.template triangularView<Lower>();
442 m3 = m2.template triangularView<Lower>();
443 VERIFY_IS_APPROX(m3, refMat3);
444
445 refMat3 = refMat2.template triangularView<Upper>();
446 m3 = m2.template triangularView<Upper>();
447 VERIFY_IS_APPROX(m3, refMat3);
448
449 refMat3 = refMat2.template triangularView<UnitUpper>();
450 m3 = m2.template triangularView<UnitUpper>();
451 VERIFY_IS_APPROX(m3, refMat3);
452
453 refMat3 = refMat2.template triangularView<UnitLower>();
454 m3 = m2.template triangularView<UnitLower>();
455 VERIFY_IS_APPROX(m3, refMat3);
456
457 refMat3 = refMat2.template triangularView<StrictlyUpper>();
458 m3 = m2.template triangularView<StrictlyUpper>();
459 VERIFY_IS_APPROX(m3, refMat3);
460
461 refMat3 = refMat2.template triangularView<StrictlyLower>();
462 m3 = m2.template triangularView<StrictlyLower>();
463 VERIFY_IS_APPROX(m3, refMat3);
464 }
465
466 // test selfadjointView
467 if(!SparseMatrixType::IsRowMajor)
468 {
469 DenseMatrix refMat2(rows, rows), refMat3(rows, rows);
470 SparseMatrixType m2(rows, rows), m3(rows, rows);
471 initSparse<Scalar>(density, refMat2, m2);
472 refMat3 = refMat2.template selfadjointView<Lower>();
473 m3 = m2.template selfadjointView<Lower>();
474 VERIFY_IS_APPROX(m3, refMat3);
475 }
476
477 // test sparseView
478 {
479 DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
480 SparseMatrixType m2(rows, rows);
481 initSparse<Scalar>(density, refMat2, m2);
482 VERIFY_IS_APPROX(m2.eval(), refMat2.sparseView().eval());
483 }
484
485 // test diagonal
486 {
487 DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
488 SparseMatrixType m2(rows, rows);
489 initSparse<Scalar>(density, refMat2, m2);
490 VERIFY_IS_APPROX(m2.diagonal(), refMat2.diagonal().eval());
491 }
492
493 // test conservative resize
494 {
495 std::vector< std::pair<Index,Index> > inc;
496 inc.push_back(std::pair<Index,Index>(-3,-2));
497 inc.push_back(std::pair<Index,Index>(0,0));
498 inc.push_back(std::pair<Index,Index>(3,2));
499 inc.push_back(std::pair<Index,Index>(3,0));
500 inc.push_back(std::pair<Index,Index>(0,3));
501
502 for(size_t i = 0; i< inc.size(); i++) {
503 Index incRows = inc[i].first;
504 Index incCols = inc[i].second;
505 SparseMatrixType m1(rows, cols);
506 DenseMatrix refMat1 = DenseMatrix::Zero(rows, cols);
507 initSparse<Scalar>(density, refMat1, m1);
508
509 m1.conservativeResize(rows+incRows, cols+incCols);
510 refMat1.conservativeResize(rows+incRows, cols+incCols);
511 if (incRows > 0) refMat1.bottomRows(incRows).setZero();
512 if (incCols > 0) refMat1.rightCols(incCols).setZero();
513
514 VERIFY_IS_APPROX(m1, refMat1);
515
516 // Insert new values
517 if (incRows > 0)
518 m1.insert(m1.rows()-1, 0) = refMat1(refMat1.rows()-1, 0) = 1;
519 if (incCols > 0)
520 m1.insert(0, m1.cols()-1) = refMat1(0, refMat1.cols()-1) = 1;
521
522 VERIFY_IS_APPROX(m1, refMat1);
523
524
525 }
526 }
527
528 // test Identity matrix
529 {
530 DenseMatrix refMat1 = DenseMatrix::Identity(rows, rows);
531 SparseMatrixType m1(rows, rows);
532 m1.setIdentity();
533 VERIFY_IS_APPROX(m1, refMat1);
534 for(int k=0; k<rows*rows/4; ++k)
535 {
536 Index i = internal::random<Index>(0,rows-1);
537 Index j = internal::random<Index>(0,rows-1);
538 Scalar v = internal::random<Scalar>();
539 m1.coeffRef(i,j) = v;
540 refMat1.coeffRef(i,j) = v;
541 VERIFY_IS_APPROX(m1, refMat1);
542 if(internal::random<Index>(0,10)<2)
543 m1.makeCompressed();
544 }
545 m1.setIdentity();
546 refMat1.setIdentity();
547 VERIFY_IS_APPROX(m1, refMat1);
548 }
549}
550
551void test_sparse_basic()
552{
553 for(int i = 0; i < g_repeat; i++) {
554 int s = Eigen::internal::random<int>(1,50);
555 EIGEN_UNUSED_VARIABLE(s);
556 CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double>(8, 8)) ));
557 CALL_SUBTEST_2(( sparse_basic(SparseMatrix<std::complex<double>, ColMajor>(s, s)) ));
558 CALL_SUBTEST_2(( sparse_basic(SparseMatrix<std::complex<double>, RowMajor>(s, s)) ));
559 CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double>(s, s)) ));
560 CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,ColMajor,long int>(s, s)) ));
561 CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,RowMajor,long int>(s, s)) ));
562
563 CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,ColMajor,short int>(short(s), short(s))) ));
564 CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,RowMajor,short int>(short(s), short(s))) ));
565 }
566}
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