scipy.stats.mstats.tmin#

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

Compute the trimmed minimum

Parameters

aarray_like: array of values
lowerlimitNone 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.
axisint 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

tminfloat, 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)

scipy.stats.mstats.tvar

scipy.stats.mstats.tmax