polsys/ennemi: 1.2.0

ennemi: easy nearest neighbor estimation of mutual information. Mutual information (MI) can be used to find non-linear correlations between variables, and this Python 3 package is designed to fit into your data analysis workflow.

This is a minor release that contains only small but significant "quality-of-life" changes. It also drops support for older NumPy and SciPy versions. There is no difference in the algorithms compared to 1.1.0.

The documentation for this release is available at https://polsys.github.io/ennemi. This release requires at least

• Python 3.7
• NumPy 1.19
• SciPy 1.5
• (Optional: pandas 1.0.0)

Changes since 1.1.1

Added estimate_corr and pairwise_corr methods. These methods are aliases to estimate_mi and pairwise_mi with parameter normalize=True.

Python 3.7 is still supported in this version, contrary to 1.1.1 release notes. However, the minimum NumPy and SciPy versions have increased.

Installation

This package is available on PyPI. To install/update it, execute

pip install --upgrade ennemi

on your Python installation.

Contributing

Your feedback is very valuable! If you encounter any problems, please file an issue. Code contributions are welcomed as well.