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setdiff1d(ar1, ar2, assume_unique=False)

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

Set difference of 1D arrays with unique elements.

See Also

numpy.setdiff1d

Equivalent function for ndarrays.

Examples

>>> 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)
See :

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GitHub : /numpy/ma/extras.py#1226
type: <class 'function'>
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