Metadata-Version: 2.1
Name: ra-trivial
Version: 0.0.3
Summary: Diverence metric
Home-page: https://github.com/RachelAlcraft/MultiDimensionalAssociations
Author: Rachel Alcraft
Author-email: rachelalcraft@gmail.com
Project-URL: Bug Tracker, https://github.com/RachelAlcraft/MultiDimensionalAssociations/issues
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE

# Alcraft-Williams Trivial Divergence

There is a google colab to demonstrate this here: https://colab.research.google.com/drive/1NNfjDTaUO6IfAcVu5DDs9UvcEdGY_TDA?usp=sharing

### Alcraft-Williams Association
This implements the Alcraft-Williams Association for finding associations in non-linear multi-dimensional data.
It has a particular advantage in being able to identify associations in sinusoidal data.

### Install
It is installed on Test PyPi and can installed with

pip install -i https://test.pypi.org/simple/ nDimAssociations-pkg-RachelAlcraft

 
