Python implementation of Arithmetic, quasi arithmetic and other aggregating functions
Project description
Means
Means, Aggregation functions...
Example 1:
Mix numpy and pure python example:
import numpy as np
t1 = [0.0, 0.0, 0.0, 0.0, 0.1]
t2 = [1 - x for x in t1]
mean1 = np.mean(t1)
mean2 = np.mean(t2)
print(t1, mean1)
print(t2, mean2)
In output we can see that returned value does not sum to 1. It have impact on comparasion
>>> [0.0, 0.0, 0.0, 0.0, 0.1] 0.02
>>> [1.0, 1.0, 1.0, 1.0, 0.9] 0.9800000000000001
Using 1:
from aggregationslib.aggregation import arithmetic
t1 = [0.0, 0.0, 0.0, 0.0, 0.1]
t2 = [1 - x for x in t1]
mean1 = arithmetic_(t1)
mean2 = arithmetic_(t2)
print(t1, mean1)
print(t2, mean2)
In implementation we obtain exact number:
>>> [0.0, 0.0, 0.0, 0.0, 0.1] 0.02
>>> [1.0, 1.0, 1.0, 1.0, 0.9] 0.98
exponential(y, r=1)
is given by equation $A_6^{(r)}(x_1,...,x_n)= \frac{1}{r}\ln
\Big(\frac{1}{n} \sum \limits_{k=1}^{n} e^{rx_k}\Big)$, where
$r \in \mathbb{R}$, $r \neq 0$
1
arithmetic(y)
2
quadratic(y)
3
geometric(y)
4
harmonic(y)
5
power(y, r=1)
6
exponential(y, r=1)
7
lehmer(y, r=0)
8
arithmetic_min(y, p=0)
9
arithmetic_max(y, p=0)
10
median(y)
11
olimpic(y)
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