def argrelmin(data, axis=<NUM_LIT:0>, order=<NUM_LIT:1>, mode='<STR_LIT>'):
return argrelextrema(data, np.less, axis, order, mode)<EOL>
Calculate the relative minima of `data`.

Parameters
----------
data : ndarray
    Array in which to find the relative minima.
axis : int, optional
    Axis over which to select from `data`.  Default is 0.
order : int, optional
    How many points on each side to use for the comparison
    to consider ``comparator(n, n+x)`` to be True.
mode : str, optional
    How the edges of the vector are treated.
    Available options are 'wrap' (wrap around) or 'clip' (treat overflow
    as the same as the last (or first) element).
    Default 'clip'. See numpy.take

Returns
-------
extrema : tuple of ndarrays
    Indices of the minima in arrays of integers.  ``extrema[k]`` is
    the array of indices of axis `k` of `data`.  Note that the
    return value is a tuple even when `data` is one-dimensional.

See Also
--------
argrelextrema, argrelmax

Notes
-----
This function uses `argrelextrema` with np.less as comparator.

.. versionadded:: 0.11.0

Examples
--------
>>> x = np.array([2, 1, 2, 3, 2, 0, 1, 0])
>>> argrelmin(x)
(array([1, 5]),)
>>> y = np.array([[1, 2, 1, 2],
...               [2, 2, 0, 0],
...               [5, 3, 4, 4]])
...
>>> argrelmin(y, axis=1)
(array([0, 2]), array([2, 1]))