Efficient implmenetations of instantiations of the Trinity of Covariation.
Project description
ConAction
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
- Supervisor: Dr. Edward Dobrowolski (Department of Mathematics and Statistics, UNBC)
- Committee Member: Dr. Brent Murray (Department of Biology, UNBC)
- Committee Member: Dr. Mohammad El Smaily (Department of Mathematics and Statistics, UNBC)
- External Examiner: Dr. Anne Condon (Department of Computer Science)
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year = "Unpublished",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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