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
, seescipy.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)