Test whether each element of an array is also present in a second array.
The output is always a masked array.
We recommend using isin instead of in1d for new code.
See also
isinVersion of this function that preserves the shape of ar1.
>>> import numpy as np
>>> ar1 = np.ma.array([0, 1, 2, 5, 0])
>>> ar2 = [0, 2]
>>> np.ma.in1d(ar1, ar2)
masked_array(data=[ True, False, True, False, True],
mask=False,
fill_value=True)
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https://numpy.org/doc/2.4/reference/generated/numpy.ma.in1d.html