sciPy stats.tmax() function | Python

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:

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# 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)))

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Output:



Trimmed Maximum : 56

Trimmed Maximum by setting limit :  4

Code #2: With multi-dimensional data

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# 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))

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Output:

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]

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