scipy.stats.mstats.tmin

scipy.stats.mstats.tmin(a, lowerlimit=None, axis=0, inclusive=True)

Compute the trimmed minimum

Parameters:

a : array_like

array of values

lowerlimit : None or float, optional

Values in the input array less than the given limit will be ignored. When lowerlimit is None, then all values are used. The default value is None.

axis : int or None, optional

Axis along which to operate. Default is 0. If None, compute over the whole array a.

inclusive : {True, False}, optional

This flag determines whether values exactly equal to the lower limit are included. The default value is True.

Returns:

tmin : float, int or ndarray

Notes

For more details on tmin, see stats.tmin.

Examples

>>> from scipy.stats import mstats
>>> a = np.array([[6, 8, 3, 0],
...               [3, 2, 1, 2],
...               [8, 1, 8, 2],
...               [5, 3, 0, 2],
...               [4, 7, 5, 2]])
...
>>> mstats.tmin(a, 5)
masked_array(data=[5, 7, 5, --],
             mask=[False, False, False,  True],
       fill_value=999999)