numpy.ma.in1d#

ma.in1d(ar1, ar2, assume_unique=False, invert=False)[source]#

Test whether each element of an array is also present in a second array.

The output is always a masked array. See numpy.in1d for more details.

We recommend using isin instead of in1d for new code.

See also

isin: Version of this function that preserves the shape of ar1.
numpy.in1d: Equivalent function for ndarrays.

Examples

>>> 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)