scipy.stats.tmin(array, lowerlimit=None, axis=0, inclusive=True)
function calculates the trimmed minimum 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 minimum.
axis: [Default is zero] Input array or object having the elements to calculate the minimum.
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 : Geometric mean of the array elements based on the set parameters.
Code #1:
# Trimmed Minimum 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 Minimum :" , stats.tmin(x)) print ( "\nTrimmed Minimum by setting limit : " , stats.tmin(x, ( 5 ))) |
Trimmed Minimum : 1 Trimmed Minimum by setting limit : 6
Code #2: Checking different parameters
# Trimmed Minimum 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 Minimum :" , stats.tmin(x)) # setting axis print ( "\nTrimmed Minimum by setting axis : " , stats.tmin(x, axis = 1 )) print ( "\nTrimmed Minimum by setting axis : " , stats.tmin(x, axis = 0 )) # setting limit print ( "\nTrimmed Minimum by setting limit : " , stats.tmin(x, ( 5 ), axis = 1 )) print ( "\nTrimmed Minimum by setting limit : " , stats.tmin(x, ( 5 ), axis = 0 )) |
Trimmed Minimum : [1 3 3] Trimmed Minimum by setting axis : [1 3 3 3] Trimmed Minimum by setting axis : [1 3 3] Trimmed Minimum by setting limit : [27 7 6 6] Trimmed Minimum by setting limit : [7 6 7]