t numpy as np
    >>> a = np.array([[10, 20, 30],
    ...               [40, 80, 100],
    ...               [1, 100, 200]])
    >>> b = np.array([[1, 2, 0, 1],
    ...               [5, 3, 0, 4],
    ...               [0, 0, 0, 7],
    ...               [9, 3, 0, 0]])

    >>> from scipy import ndimage

    >>> ndimage.minimum_position(a)
    (2, 0)
    >>> ndimage.minimum_position(b)
    (0, 2)

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

    >>> label, pos = ndimage.label(a)
    >>> ndimage.minimum_position(a, label, index=np.arange(1, pos+1))
    [(2, 0)]

    >>> label, pos = ndimage.label(b)
    >>> ndimage.minimum_position(b, label, index=np.arange(1, pos+1))
    [(0, 0), (0, 3), (3, 1)]

    r