numpy.ma.setdiff1d#

ma.setdiff1d(ar1, ar2, assume_unique=False)[source]#

Set difference of 1D arrays with unique elements.

The output is always a masked array. See numpy.setdiff1d for more details.

See also

numpy.setdiff1d

Equivalent function for ndarrays.

Examples

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>>> import numpy as np
>>> x = np.ma.array([1, 2, 3, 4], mask=[0, 1, 0, 1])
>>> np.ma.setdiff1d(x, [1, 2])
masked_array(data=[3, --],
             mask=[False,  True],
       fill_value=999999)

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