scipy.stats.tmax(array, lowerlimit=None, axis=0, inclusive=True) function calculates the trimmed maximum of the array elements along with ignoring the values lying outside the specified limits, along the specified axis.
Parameters :
array: Input array or object having the elements to calculate the trimmed maximum.
axis: Axis along which the statistics is to be computed. By default axis = 0
limits: Lower and upper bound of the array to consider, values less than the lower limit or greater than the upper limit will be ignored. If limits is None [default], then all values are used.
inclusive: Decide whether to include the values equal to lower or upper bound, or to exclude them while calculation.Returns : Trimmed maximum of the array elements based on the set parameters.
Code #1:
# Trimmed Maximum from scipy import stats import numpy as np # array elements ranging from 0 to 19 x = [1, 3, 27, 56, 2, 4, 13, 3, 6] print("Trimmed Maximum :", stats.tmax(x)) print("\nTrimmed Maximum by setting limit : ", stats.tmax(x, (5))) |
Trimmed Maximum : 56 Trimmed Maximum by setting limit : 4
Code #2: With multi-dimensional data
# Trimmed Maximum from scipy import stats import numpy as np # array elements ranging from 0 to 19 x = [[1, 3, 27], [3, 4, 7], [7, 6, 3], [3, 6, 8]] print("Trimmed Maximum :", stats.tmax(x)) # setting axis print("\nTrimmed Maximum by setting axis : ", stats.tmax(x, axis = 1)) print("\nTrimmed Maximum by setting axis : ", stats.tmax(x, axis = 0)) # setting limit print("\nTrimmed Maximum by setting limit : ", stats.tmax(x, (5), axis = 1)) print("\nTrimmed Maximum by setting limit : ", stats.tmax(x, (5), axis = 0)) |
Trimmed Maximum : [ 7 6 27] Trimmed Maximum by setting axis : [27 7 7 8] Trimmed Maximum by setting axis : [ 7 6 27] Trimmed Maximum by setting limit : [3 4 3 3] Trimmed Maximum by setting limit : [3 4 3]
