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Efficient implmenetations of instantiations of the Trinity of Covariation.

Project description

ConAction

Instantiations of the Trinity of Covariation

Open Source Love Documentation Status PyPI version PyPI - Downloads License Code style: Black

Project Description

The ConAction library provides mathematical functions that are inspired from the metaphor of the Trinity of Covariation as part of the MSc thesis of Galen Seilis.

Supervisory Committee Members

The code in this repository is intended to support researchers analyzing multivariate data.

The thesis provides an extensive background reading for this package, and can be found at (link needed).

Installation

ConAction is available through PyPi, and can be installed via pip using

pip install conaction

or

pip3 install conaction

Example Usage

from conaction import estimators
import numpy as np

X = np.random.normal(size=1000).reshape((100,10)) # Get a 100 x 10 data table

estimators.pearson_correlation(X) # Compute the 10-linear Pearson correlation coefficient

Documentation

Build documentation locally:

cd /path/to/conaction/docs
make html

Tutorials

Coming soon.

Publications

Coming soon.

Citation


@mastersthesis{seilisthesis2022,
  author  = "Galen Seilis",
  title   = "ConAction: Efficient Implementations and Applications of Functions Inspired by the Trinity of Covariation",
  school  = "University of Northern British Columbia",
  year    = "Unpublished",
  address = "3333 University Way, Prince George, British Columbia, V2N 4Z9, Canada",
  month   = "TBA",
}

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