scipy.stats.mstats.tmax

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

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:

a : array_like

array of values

upperlimit : None 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.

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 upper limit are included. The default value is True.

Returns:

tmax : float, 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)