numpy.ma.masked_object — NumPy v1.11 Manual (original) (raw)
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. |
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=?)