Find the unique elements of an array, ignoring shape.
(ar, return_index=False, return_inverse=False,
return_counts=False, *, equal_nan=True)
| 321 | |
| 322 | |
| 323 | def _unique1d(ar, return_index=False, return_inverse=False, |
| 324 | return_counts=False, *, equal_nan=True): |
| 325 | """ |
| 326 | Find the unique elements of an array, ignoring shape. |
| 327 | """ |
| 328 | ar = np.asanyarray(ar).flatten() |
| 329 | |
| 330 | optional_indices = return_index or return_inverse |
| 331 | |
| 332 | if optional_indices: |
| 333 | perm = ar.argsort(kind='mergesort' if return_index else 'quicksort') |
| 334 | aux = ar[perm] |
| 335 | else: |
| 336 | ar.sort() |
| 337 | aux = ar |
| 338 | mask = np.empty(aux.shape, dtype=np.bool_) |
| 339 | mask[:1] = True |
| 340 | if (equal_nan and aux.shape[0] > 0 and aux.dtype.kind in "cfmM" and |
| 341 | np.isnan(aux[-1])): |
| 342 | if aux.dtype.kind == "c": # for complex all NaNs are considered equivalent |
| 343 | aux_firstnan = np.searchsorted(np.isnan(aux), True, side='left') |
| 344 | else: |
| 345 | aux_firstnan = np.searchsorted(aux, aux[-1], side='left') |
| 346 | if aux_firstnan > 0: |
| 347 | mask[1:aux_firstnan] = ( |
| 348 | aux[1:aux_firstnan] != aux[:aux_firstnan - 1]) |
| 349 | mask[aux_firstnan] = True |
| 350 | mask[aux_firstnan + 1:] = False |
| 351 | else: |
| 352 | mask[1:] = aux[1:] != aux[:-1] |
| 353 | |
| 354 | ret = (aux[mask],) |
| 355 | if return_index: |
| 356 | ret += (perm[mask],) |
| 357 | if return_inverse: |
| 358 | imask = np.cumsum(mask) - 1 |
| 359 | inv_idx = np.empty(mask.shape, dtype=np.intp) |
| 360 | inv_idx[perm] = imask |
| 361 | ret += (inv_idx,) |
| 362 | if return_counts: |
| 363 | idx = np.concatenate(np.nonzero(mask) + ([mask.size],)) |
| 364 | ret += (np.diff(idx),) |
| 365 | return ret |
| 366 | |
| 367 | |
| 368 | def _intersect1d_dispatcher( |