Description

This package provides an Python implementation of the ElPiGraph algorithm. A self-contained description of the algorithm is available here or on this arXiv paper

A R implementation of this algorithm is also available, coded by Luca Albergante

A native MATLAB implementation of the algorithm (coded by Andrei Zinovyev and Evgeny Mirkes) is also available

Citation

When using this package, please cite our preprint:

Albergante, L. et al . Robust and Scalable Learning of Data Manifold with Complex Topologies via ElPiGraph. arXiv: 1804.07580 (2018)

Requirements

This code was tested with Python 3.6, the following packages are needed:

• numpy
• matplotlib
• scipy
• pip

Installation & Usage

To install that package, clone this git, open a terminal on the root of the git folder and type:

pip install .

Or, without cloning, simply run the following command

pip install git+https://github.com/LouisFaure/ElPiGraph.P.git

Here is a notebook showing cases of basic usage