equence of ints, optional
        Labels for which to calculate centers-of-mass. If not specified,
        the combined center of mass of all labels greater than zero
        will be calculated. Only used with `labels`.

    Returns
    -------
    center_of_mass : tuple, or list of tuples
        Coordinates of centers-of-mass.

    Examples
    --------
    >>> import numpy as np
    >>> a = np.array(([0,0,0,0],
    ...               [0,1,1,0],
    ...               [0,1,1,0],
    ...               [0,1,1,0]))
    >>> from scipy import ndimage
    >>> ndimage.center_of_mass(a)
    (2.0, 1.5)

    Calculation of multiple objects in an image

    >>> b = np.array(([0,1,1,0],
    ...               [0,1,0,0],
    ...               [0,0,0,0],
    ...               [0,0,1,1],
    ...               [0,0,1,1]))
    >>> lbl = ndimage.label(b)[0]
    >>> ndimage.center_of_mass(b, lbl, [1,2])
    [(0.33333333333333331, 1.3333333333333333), (3.5, 2.5)]

    Negative masses are also accepted, which can occur for example when
    bias is removed from measured data due to random noise.

    >>> c = np.array(([-1,0,0,0],
    ...               [0,-1,-1,0],
    ...               [0,1,-1,0],
    ...               [0,1,1,0]))
    >>> ndimage.center_of_mass(c)
    (-4.0, 1.0)

    If there are division by zero issues, the function does not raise an
    error but rather issues a RuntimeWarning before returning inf and/or NaN.

    >>> d = np.array([-1, 1])
    >>> ndimage.center_of_mass(d)
    (inf,)
    c