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comparison liboctave/array/dSparse.cc @ 17682:93e272018df2

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Correct dimesion of return values form sparse min/max function with empty matrices (bug #40295) * dSparse.cc (SparseMatrix SparseMatrix::max (Array<octave_idx-type>&, int)) : Specialize return values if called with an empty matrix (SparseMatrix SparseMatrix::min (Array<octave_idx-type>&, int)) : ditto * CSparse.cc (SparseComplexMatrix SparseComplexMatrix::max ( Array<octave_idx-type>&, int)) : Specialize return values if called with an empty matrix (SparseComplexMatrix SparseComplexMatrix::min (Array<octave_idx-type>&, int)) : ditto
author David Bateman <dbateman@free.fr>
date Fri, 18 Oct 2013 01:36:31 +0200
parents c81debf315e0
children 8031fc73f291
comparison
equal deleted inserted replaced
17681:f6fded839513 17682:93e272018df2
277 SparseMatrix result; 277 SparseMatrix result;
278 dim_vector dv = dims (); 278 dim_vector dv = dims ();
279 octave_idx_type nr = dv(0); 279 octave_idx_type nr = dv(0);
280 octave_idx_type nc = dv(1); 280 octave_idx_type nc = dv(1);
281 281
282 if (nr == 0 || nc == 0 || dim >= dv.length ()) 282 if (dim >= dv.length ())
283 return result; 283 {
284 idx_arg.resize (dim_vector (nr, nc), 0);
285 return *this;
286 }
284 287
285 if (dim < 0) 288 if (dim < 0)
286 dim = dv.first_non_singleton (); 289 dim = dv.first_non_singleton ();
287 290
288 if (dim == 0) 291 if (dim == 0)
289 { 292 {
290 idx_arg.clear (1, nc); 293 idx_arg.resize (dim_vector (nr == 0 ? 0 : 1, nc), 0);
294
295 if (nr == 0 || nc == 0 || dim >= dv.length ())
296 return SparseMatrix (nr == 0 ? 0 : 1, nc);
297
291 octave_idx_type nel = 0; 298 octave_idx_type nel = 0;
292 for (octave_idx_type j = 0; j < nc; j++) 299 for (octave_idx_type j = 0; j < nc; j++)
293 { 300 {
294 double tmp_max = octave_NaN; 301 double tmp_max = octave_NaN;
295 octave_idx_type idx_j = 0; 302 octave_idx_type idx_j = 0;
339 346
340 } 347 }
341 } 348 }
342 else 349 else
343 { 350 {
344 idx_arg.resize (dim_vector (nr, 1), 0); 351 idx_arg.resize (dim_vector (nr, nc == 0 ? 0 : 1), 0);
352
353 if (nr == 0 || nc == 0 || dim >= dv.length ())
354 return SparseMatrix (nr, nc == 0 ? 0 : 1);
345 355
346 for (octave_idx_type i = cidx (0); i < cidx (1); i++) 356 for (octave_idx_type i = cidx (0); i < cidx (1); i++)
347 idx_arg.elem (ridx (i)) = -1; 357 idx_arg.elem (ridx (i)) = -1;
348 358
349 for (octave_idx_type j = 0; j < nc; j++) 359 for (octave_idx_type j = 0; j < nc; j++)
425 SparseMatrix result; 435 SparseMatrix result;
426 dim_vector dv = dims (); 436 dim_vector dv = dims ();
427 octave_idx_type nr = dv(0); 437 octave_idx_type nr = dv(0);
428 octave_idx_type nc = dv(1); 438 octave_idx_type nc = dv(1);
429 439
430 if (nr == 0 || nc == 0 || dim >= dv.length ()) 440 if (dim >= dv.length ())
431 return result; 441 {
442 idx_arg.resize (dim_vector (nr, nc), 0);
443 return *this;
444 }
432 445
433 if (dim < 0) 446 if (dim < 0)
434 dim = dv.first_non_singleton (); 447 dim = dv.first_non_singleton ();
435 448
436 if (dim == 0) 449 if (dim == 0)
437 { 450 {
438 idx_arg.clear (1, nc); 451 idx_arg.resize (dim_vector (nr == 0 ? 0 : 1, nc), 0);
452
453 if (nr == 0 || nc == 0 || dim >= dv.length ())
454 return SparseMatrix (nr == 0 ? 0 : 1, nc);
455
439 octave_idx_type nel = 0; 456 octave_idx_type nel = 0;
440 for (octave_idx_type j = 0; j < nc; j++) 457 for (octave_idx_type j = 0; j < nc; j++)
441 { 458 {
442 double tmp_min = octave_NaN; 459 double tmp_min = octave_NaN;
443 octave_idx_type idx_j = 0; 460 octave_idx_type idx_j = 0;
487 504
488 } 505 }
489 } 506 }
490 else 507 else
491 { 508 {
492 idx_arg.resize (dim_vector (nr, 1), 0); 509 idx_arg.resize (dim_vector (nr, nc == 0 ? 0 : 1), 0);
510
511 if (nr == 0 || nc == 0 || dim >= dv.length ())
512 return SparseMatrix (nr, nc == 0 ? 0 : 1);
493 513
494 for (octave_idx_type i = cidx (0); i < cidx (1); i++) 514 for (octave_idx_type i = cidx (0); i < cidx (1); i++)
495 idx_arg.elem (ridx (i)) = -1; 515 idx_arg.elem (ridx (i)) = -1;
496 516
497 for (octave_idx_type j = 0; j < nc; j++) 517 for (octave_idx_type j = 0; j < nc; j++)