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- scipy.stats.tmax.- Examples - >>> import numpy as np >>> 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)