The UNITE Toolbox is a Python library for incorporating Information Theory
into data analysis and modeling workflows.
The toolbox collects different methods of estimating information-theoretic quantities
in one easy-to-use Python package.
Currently, UNITE includes functions to calculate entropy
- Kernel density-based estimation (KDE)
- Binning using histograms
- k-nearest neighbor-based estimation (k-NN)
Although the code is still highly experimental and in very active development,
a release version is available on PyPI and can be installed using pip
.
pip install unite_toolbox
Alternatively, the latest updates can be installed directly from this repository
pip install git+https://github.com/manuel-alvarez-chaves/unite_toolbox
Check the pyproject.toml
for requirements.
In the documentation please find tutorials on the general usage of the toolbox and some applications.