],
    ...               [0, 0, 0, 7],
    ...               [9, 3, 0, 0]])
    >>> from scipy import ndimage
    >>> ndimage.variance(a)
    7.609375

    Features to process can be specified using `labels` and `index`:

    >>> lbl, nlbl = ndimage.label(a)
    >>> ndimage.variance(a, lbl, index=np.arange(1, nlbl+1))
    array([ 2.1875,  2.25  ,  9.    ])

    If no index is given, all non-zero `labels` are processed:

    >>> ndimage.variance(a, lbl)
    6.1875

    T)