numpy.ma.masked_object(x, value, copy=True, shrink=True)
[source]
Mask the array x
where the data are exactly equal to value.
This function is similar to masked_values
, but only suitable for object arrays: for floating point, use masked_values
instead.
Parameters: |
x : array_like Array to mask value : object Comparison value copy : {True, False}, optional Whether to return a copy of shrink : {True, False}, optional Whether to collapse a mask full of False to nomask |
---|---|
Returns: |
result : MaskedArray The result of masking |
See also
masked_where
masked_equal
masked_values
>>> import numpy.ma as ma >>> food = np.array(['green_eggs', 'ham'], dtype=object) >>> # don't eat spoiled food >>> eat = ma.masked_object(food, 'green_eggs') >>> print(eat) [-- ham] >>> # plain ol` ham is boring >>> fresh_food = np.array(['cheese', 'ham', 'pineapple'], dtype=object) >>> eat = ma.masked_object(fresh_food, 'green_eggs') >>> print(eat) [cheese ham pineapple]
Note that mask
is set to nomask
if possible.
>>> eat masked_array(data = [cheese ham pineapple], mask = False, fill_value=?)
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Licensed under the NumPy License.
https://docs.scipy.org/doc/numpy-1.12.0/reference/generated/numpy.ma.masked_object.html