intersect1d(ar1, ar2, assume_unique=False)
Masked values are considered equal one to the other. The output is always a masked array.
See numpy.intersect1d
for more details.
Returns the unique elements common to both arrays.
numpy.intersect1d
Equivalent function for ndarrays.
>>> x = np.ma.array([1, 3, 3, 3], mask=[0, 0, 0, 1])See :
... y = np.ma.array([3, 1, 1, 1], mask=[0, 0, 0, 1])
... np.ma.intersect1d(x, y) masked_array(data=[1, 3, --], mask=[False, False, True], fill_value=999999)
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