This is a Python implementation of Tsallis Regularized Optimal Transport (TROT) for ecological inference, following
Boris Muzellec, Richard Nock, Giorgio Patrini, Frank Nielsen. Tsallis Regularized Optimal Transport and Ecological Inference. arXiv:1609.04495
It contains both scripts implementing algorithms for solving TROT, and notebooks which reproduce the ecological inference pipeline from the article.
numpy, scipy, pickle
To run the Ecological Inference notebook, you will first want to download the Florida dataset (600 MB):
and put it in the root folder of the repo.
You can then run
Notebooks/Ecological/Inference.ipynb for a reproduction of the article's ecological inference pipeline, and
Notebooks/Tsallis/Plots.ipynb for a visualization of the impact of parameter $q$ and $\lambda$.
The code under
Trot/ contains the basics for building a TROT-based application.