numpy.ma.isin#

ma.isin(element, test_elements, assume_unique=False, invert=False)[source]#

Calculates element in test_elements, broadcasting over element only.

The output is always a masked array of the same shape as element. See numpy.isin for more details.

See also

in1d: Flattened version of this function.
numpy.isin: Equivalent function for ndarrays.

Examples

>>> import numpy as np
>>> element = np.ma.array([1, 2, 3, 4, 5, 6])
>>> test_elements = [0, 2]
>>> np.ma.isin(element, test_elements)
masked_array(data=[False,  True, False, False, False, False],
             mask=False,
       fill_value=True)