scipy.stats.mstats.tmax#

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

Compute the trimmed maximum

This function computes the maximum value of an array along a given axis, while ignoring values larger than a specified upper limit.

Parameters

aarray_like: array of values
upperlimitNone or float, optional: Values in the input array greater than the given limit will be ignored. When upperlimit 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 upper limit are included. The default value is True.

Returns

tmaxfloat, int or ndarray

Notes

For more details on tmax, see stats.tmax.

Examples

>>> from scipy.stats import mstats
>>> a = np.array([[6, 8, 3, 0],
...               [3, 9, 1, 2],
...               [8, 7, 8, 2],
...               [5, 6, 0, 2],
...               [4, 5, 5, 2]])
...
...
>>> mstats.tmax(a, 4)
masked_array(data=[4, --, 3, 2],
             mask=[False,  True, False, False],
       fill_value=999999)

scipy.stats.mstats.tmin

scipy.stats.mstats.tsem