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]