Code for stochastic area metric : binary search for speed

de Angelis, M. and Sunny, J. (2022) Code for stochastic area metric : binary search for speed. GitHub. (https://doi.org/10.5281/ZENODO.6366288)

Full text not available in this repository.Request a copy

Abstract

This repository contains Python scientific code for computing efficiently the area metric, a.k.a. 1-Wasserstein distance, between tabular samples. The code is optimized by running Numpy under the hood, thus is as vectorized as possible. A basic Matlab version is also present in this repository.

ORCID iDs

de Angelis, M. ORCID logoORCID: https://orcid.org/0000-0001-8851-023X and Sunny, J.;