Skip to content

Tools for information theoretic measures estimation.

License

Notifications You must be signed in to change notification settings

statbiophys/catede

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

catede

The python software catede is a collection of different estimation methods for the entropy and divergence in the context of categorical distribution with finite number of categories. Provided a data sample in the shape of a list or other comprehensive supported formats, the software provides methods to estimate the Shannon entropy, the Simpson index, the Kullback-Leibler divergence and the Hellinger distance. In particular it provides the code for the Dirichlet prior mixture estimators for the divergence, published in Camaglia et al. (2024), Phys. Rev. E.

Installation

The package catede can be installed from github by running from terminal the following command line :

pip install git+https://github.com/statbiophys/catede.git.

References

Cite this as:

Francesco Camaglia, Ilya Nemenman, Thierry Mora, Aleksandra Walczak (2024). Bayesian estimation of the Kullback-Leibler divergence for categorical sytems using mixtures of Dirichlet priors. Phys. Rev. E

Tutorial

A brief tutorial can be found here.

Contact

Any issues or questions should be addressed to us.

License

Free use of catede is granted under the terms of the GNU General Public License version 3 (GPLv3).

About

Tools for information theoretic measures estimation.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 88.8%
  • Jupyter Notebook 11.2%