Calculates `element in test_elements`, broadcasting over `element` only. The output is always a masked array of the same shape as `element`. See `numpy.isin` for more details. See Also -------- in1d : Flattened version of this function. numpy.isin : Equivalen
(element, test_elements, assume_unique=False, invert=False)
| 1432 | |
| 1433 | |
| 1434 | def isin(element, test_elements, assume_unique=False, invert=False): |
| 1435 | """ |
| 1436 | Calculates `element in test_elements`, broadcasting over |
| 1437 | `element` only. |
| 1438 | |
| 1439 | The output is always a masked array of the same shape as `element`. |
| 1440 | See `numpy.isin` for more details. |
| 1441 | |
| 1442 | See Also |
| 1443 | -------- |
| 1444 | in1d : Flattened version of this function. |
| 1445 | numpy.isin : Equivalent function for ndarrays. |
| 1446 | |
| 1447 | Examples |
| 1448 | -------- |
| 1449 | >>> import numpy as np |
| 1450 | >>> element = np.ma.array([1, 2, 3, 4, 5, 6]) |
| 1451 | >>> test_elements = [0, 2] |
| 1452 | >>> np.ma.isin(element, test_elements) |
| 1453 | masked_array(data=[False, True, False, False, False, False], |
| 1454 | mask=False, |
| 1455 | fill_value=True) |
| 1456 | |
| 1457 | """ |
| 1458 | element = ma.asarray(element) |
| 1459 | return in1d(element, test_elements, assume_unique=assume_unique, |
| 1460 | invert=invert).reshape(element.shape) |
| 1461 | |
| 1462 | |
| 1463 | def union1d(ar1, ar2): |