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sciPy function stats.tmax () | python

scipy.stats.tmax (array, lowerlimit = None, axis = 0, inclusive = True) calculates the truncated maximum of array elements and also ignores values ​​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:

# Maximum clipped

 

from scipy import stats

import numpy as np 

 
# array elements in the range from 0 to 19

x = [ 1 , 3 , 27 , 56 , 2 , 4 , 13 , 3 , 6 ]

 

print ( "Trimmed Maximum:" , stats.tmax (x)) 

 

 

print ( " Trimmed Maximum by setting limit: "

  stats.tmax (x, ( 5 )) )

Exit:

 Trimmed Maximum : 56 Trimmed Maximum by setting limit: 4 

Code # 2: with multidimensional data

# Cropped 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 the axis

print ( "Trimmed Maximum by setting axis:"

  stats.tmax (x, axis = 1 ))

 

print ( " Trimmed Maximum by setting axis: "

stats.tmax (x, axis = 0 ))

 
# installed setting limit

print ( "Trimmed Maximum by setting limit: "

  stats.tmax (x, ( 5 ), axis = 1 ))

 

 

print ( "Trimmed Maximum by setting limit:"

  stats.tmax (x, ( 5 ), axis = 0 ))

Exit:

 Trimmed Maxi mum: [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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