Function in1d

numpy/ma/extras.py:1387–1431

Test whether each element of an array is also present in a second array. The output is always a masked array. We recommend using :func:`isin` instead of `in1d` for new code. See Also -------- isin : Version of this function that preserves the shape of ar1.

(ar1, ar2, assume_unique=False, invert=False)

def in1d(ar1, ar2, assume_unique=False, invert=False):
    """
    Test whether each element of an array is also present in a second
    array.

    The output is always a masked array.

    We recommend using :func:`isin` instead of `in1d` for new code.

    See Also
    --------
    isin       : Version of this function that preserves the shape of ar1.

    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)

    """
    if not assume_unique:
        ar1, rev_idx = unique(ar1, return_inverse=True)
        ar2 = unique(ar2)

    ar = ma.concatenate((ar1, ar2))
    # We need this to be a stable sort, so always use 'mergesort'
    # here. The values from the first array should always come before
    # the values from the second array.
    order = ar.argsort(kind='mergesort')
    sar = ar[order]
    if invert:
        bool_ar = (sar[1:] != sar[:-1])
    else:
        bool_ar = (sar[1:] == sar[:-1])
    flag = ma.concatenate((bool_ar, [invert]))
    indx = order.argsort(kind='mergesort')[:len(ar1)]

    if assume_unique:
        return flag[indx]
    else:
        return flag[indx][rev_idx]


def isin(element, test_elements, assume_unique=False, invert=False):