def _snn_imp(ind, ref_set_):
    """Internal function for fast snn calculation

    Parameters
    ----------
    ind : int
        Indices return by kNN.

    ref_set_ : int, optional (default=10)
        specifies the number of shared nearest neighbors to create the
        reference set. Note that ref_set must be smaller than n_neighbors.

    """
    n = ind.shape[0]
    _count = np.zeros(shape=(n, ref_set_), dtype=np.uint32)
    for i in nb.prange(n):
        temp = np.empty(n, dtype=np.uint32)
        test_element_set = set(ind[i])
        for j in nb.prange(n):
            temp[j] = len(set(ind[j]).intersection(test_element_set))
        temp[i] = np.iinfo(np.uint32).max
        _count[i] = np.argsort(temp)[::-1][1:ref_set_ + 1]

    return _count
Internal function for fast snn calculation

    Parameters
    ----------
    ind : int
        Indices return by kNN.

    ref_set_ : int, optional (default=10)
        specifies the number of shared nearest neighbors to create the
        reference set. Note that ref_set must be smaller than n_neighbors.

    
pyod/models/sod.py