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 minor release adds support for NumPy 2.0, pandas 2.0, and Python 3.12. There are no user-visible changes or differences in the algorithms compared to 1.3.0. (However, results may be slightly different due to changes in e.g. SciPy random number generation.)
The documentation for this release is available at https://polsys.github.io/ennemi. This release requires at least
- Python 3.10
- NumPy 1.23 (NumPy 2.0 is supported)
- SciPy 1.9
- (Optional: pandas 1.5+ or 2.x)
Changes since 1.3.0
- Support for NumPy 2.0 and pandas 2.0
- Minimum required versions of dependencies have been increased
This release fixes several warnings/crashes in ennemi caused by changes in NumPy and pandas. If you upgrade to NumPy 2.x and/or pandas 2.x, you need to update ennemi as well.
There are no new features or algorithm changes. If you cannot upgrade your Python version, ennemi 1.3 should produce (near-)identical results.
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.