Means
Means, Aggregation functions...
Example 1:
# example data
data = [0.2, 0.6, 0.7]
# configure function parameters
func1 = A_amn(p=0.5)
# use aggregation funciton
print(func1(data))
# Combine two aggregations - arithmetic mean and minimum
func2 = Combine2Aggregations(A_ar(), min)
# use combination of aggregation funciton
print(func2(data))
Example2:
To get information about aggregation function you can use __str__()
or 'repr()' methods.
func1 = A_amn(p=0.5)
print(func1)
>>>A_amn(0.5)
func2 = Combine2Aggregations(A_ar(), A_md())
print(func2)
>>>A_armd
func3 = Combine2Aggregations(A_ar(), A_pw(r=3))
print(func3.__repr__()) # function parameters are printed in order: func1, func2
>>>A_arpw(r=3)
exponential(y, r=1)
is given by equation
A_ar - Arithmetic mean
A_qd - Quadratic mean
A_gm - Geometric mean
A_hm - Harmonic mean
A_pw - Power mean
A_ex, A_ex2, A_ex3 - Exponential mean
A_lm - Lehmer mean
A_amn - Arithmetic minimum mean
A_amx - Arithmetic maximum mean
A_md - Median - ordered weighted aggregation
A_ol - Olimpic aggregation
A_oln - Olimpic aggregation
We can specify how many greatest and smallest records remove
Combine2Aggregations - Combine aggregation functions
Amn, Amx, Aar , Aex , Amd, Aow1, Aow1