topology-demos

A repository for generating the figures for Persistent Homology: A Non-Mathy Introduction with Examples on Towards Data Science on Medium. This repo covers some of the basic topology concepts used at Geometric Data Analytics.

NOTE: this code was mostly written in 2019 (./runners/signal_compression.py has been updated since the publishing of the Medium article though). This repository was never meant for public release, so the code / usability is not nearly as clean as it should be. Furthermore, the code, the conda environment, and the interaction of the two have not (and will not) be maintained.

Any figures / gifs from the Medium post are generated by scripts in ./runners for replicability at the time of development.

Code was written to run in the conda environment specified by topology_demos_env.yml. It can be installed by running:

cd <path/to/topology/demos>
bash install_env.sh

To uninstall the conda environment, run:

cd <path/to/topology/demos>
bash uninstall_env.sh

All runners are designed to run from the root of the repo, e.g.:

cd <path/to/topology/demos>
export PYTHONPATH=$pwd:$PYTHONPATH
python ./runners/<runner>.py

All code added to ./sandbox will be gitignored.

Alessiacosmos/topology-demos

topology-demos