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Function is_mask

numpy/ma/core.py:1477–1542  ·  view source on GitHub ↗

Return True if m is a valid, standard mask. This function does not check the contents of the input, only that the type is MaskType. In particular, this function returns False if the mask has a flexible dtype. Parameters ---------- m : array_like Array to test.

(m)

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1475
1476
1477def is_mask(m):
1478 """
1479 Return True if m is a valid, standard mask.
1480
1481 This function does not check the contents of the input, only that the
1482 type is MaskType. In particular, this function returns False if the
1483 mask has a flexible dtype.
1484
1485 Parameters
1486 ----------
1487 m : array_like
1488 Array to test.
1489
1490 Returns
1491 -------
1492 result : bool
1493 True if `m.dtype.type` is MaskType, False otherwise.
1494
1495 See Also
1496 --------
1497 ma.isMaskedArray : Test whether input is an instance of MaskedArray.
1498
1499 Examples
1500 --------
1501 >>> import numpy.ma as ma
1502 >>> m = ma.masked_equal([0, 1, 0, 2, 3], 0)
1503 >>> m
1504 masked_array(data=[--, 1, --, 2, 3],
1505 mask=[ True, False, True, False, False],
1506 fill_value=0)
1507 >>> ma.is_mask(m)
1508 False
1509 >>> ma.is_mask(m.mask)
1510 True
1511
1512 Input must be an ndarray (or have similar attributes)
1513 for it to be considered a valid mask.
1514
1515 >>> m = [False, True, False]
1516 >>> ma.is_mask(m)
1517 False
1518 >>> m = np.array([False, True, False])
1519 >>> m
1520 array([False, True, False])
1521 >>> ma.is_mask(m)
1522 True
1523
1524 Arrays with complex dtypes don't return True.
1525
1526 >>> dtype = np.dtype({'names':['monty', 'pithon'],
1527 ... 'formats':[bool, bool]})
1528 >>> dtype
1529 dtype([('monty', '|b1'), ('pithon', '|b1')])
1530 >>> m = np.array([(True, False), (False, True), (True, False)],
1531 ... dtype=dtype)
1532 >>> m
1533 array([( True, False), (False, True), ( True, False)],
1534 dtype=[('monty', '?'), ('pithon', '?')])

Callers 1

mask_orFunction · 0.85

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