Calculate weighted OWA functions and extending bivariate means
Project description
combineArrays
This package calculates weighted OWA functions and extending bivariate means" Functions are:
- owa: callback function if sorting is needed in general
- weightedf: symmetric base aggregator
Documentation
Installation
To install type:
$ pip install wowa
Usage of owa( x, w)
from wowa import owa
Callback function if sorting is needed in general
Parameters
Input parameters:
Input parameters: x[]: NumPy array of size n, float w[]: NumPy array of size n, float
Output parameters:
double y: sum of x[i] * w[i]
Usage of weightedf( x, p, w, cb, L)
from wowa import weightedf
Symmetric base aggregator. The weights must add to one and be non-negative.
Parameters
Input parameters:
x[]: NumPy array of inputs, size n, float p[]: NumPy array of weights of inputs x[], size n, float w[]: NumPy array of weights for OWA, size n, float cb: callback function L: number of binary tree levels. Run time = O[(n-1)L]
Output parameters:
y = weightedf
Test
To unit test type:
$ test/test.py
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