scipy.stats.tmax#

scipy.stats.tmax(a, upperlimit=None, axis=0, inclusive=True, nan_policy='propagate')[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.

nan_policy{‘propagate’, ‘raise’, ‘omit’}, optional

Defines how to handle when input contains nan. The following options are available (default is ‘propagate’):

  • ‘propagate’: returns nan

  • ‘raise’: throws an error

  • ‘omit’: performs the calculations ignoring nan values

Returns:
tmaxfloat, int or ndarray

Trimmed maximum.

Examples

>>> import numpy as np
>>> from scipy import stats
>>> x = np.arange(20)
>>> stats.tmax(x)
19
>>> stats.tmax(x, 13)
13
>>> stats.tmax(x, 13, inclusive=False)
12