the
    entry 2 in the input is connected to 1,
    but 1 is not connected to 2.

    Examples
    --------
    Create an image with some features, then label it using the default
    (cross-shaped) structuring element:

    >>> from scipy.ndimage import label, generate_binary_structure
    >>> import numpy as np
    >>> a = np.array([[0,0,1,1,0,0],
    ...               [0,0,0,1,0,0],
    ...               [1,1,0,0,1,0],
    ...               [0,0,0,1,0,0]])
    >>> labeled_array, num_features = label(a)

    Each of the 4 features are labeled with a different integer:

    >>> num_features
    4
    >>> labeled_array
    array([[0, 0, 1, 1, 0, 0],
           [0, 0, 0, 1, 0, 0],
           [2, 2, 0, 0, 3, 0],
           [0, 0, 0, 4, 0, 0]])

    Generate a structuring element that will consider features connected even
    if they touch diagonally:

    >>> s = generate_binary_structure(2,2)

    or,

    >>> s = [[1,1,1],
    ...      [1,1,1],
    ...      [1,1,1]]

    Label the image using the new structuring element:

    >>> labeled_array, num_features = label(a, structure=s)

    Show the 2 labeled features (note that features 1, 3, and 4 from above are
    now considered a single feature):

    >>> num_features
    2
    >>> labeled_array
    array([[0, 0, 1, 1, 0, 0],
           [0, 0, 0, 1, 0, 0],
           [2, 2, 0, 0, 1, 0],
           [0, 0, 0, 1, 0, 0]])

    References
    ----------

    .. [1] James R. Weaver, "Centrosymmetric (cross-symmetric)
       matrices, their basic properties, eigenvalues, and
       eigenvectors." The American Mathematical Monthly 92.10
       (1985): 711-717.

    ú