numpy.ma.masked_object¶
- 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 x.
shrink : {True, False}, optional
Whether to collapse a mask full of False to nomask
Returns: result : MaskedArray
The result of masking x where equal to value.
See also
- masked_where
- Mask where a condition is met.
- masked_equal
- Mask where equal to a given value (integers).
- masked_values
- Mask using floating point equality.
Examples
>>> 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=?)