Code

Teaspoon

Teaspoon logo

Teaspoon was named for Topological Signal Processing (TSP). It is focused on the use of persistent homology and its variations for signal processing applications, but also includes code to generate a vast array of dynamical systems as well as methods for feeding persistence diagrams to machine learning models. If you found it useful, we'd love to hear about it! Also, as with all research code, there is a high chance of bugs, please report them via github.

Persistent homology of complex networks for dynamic state detection

photo showing a cartoon of the pipeline for persistent homology of complex networks

This repo contains the companion code for the paper: "Persistent homology of complex networks for dynamic state detection," Audun Myers, Elizabeth Munch, and Firas A. Khasawneh, 2019, DOI: 10.1103/PhysRevE.100.022314.

Fuzzy Means Code

photo showing a cartoon of sampling persistence diagrams

This zip file contains the companion code for the paper: "Probabilistic Fréchet means for time varying persistence diagrams," 2015, DOI: 10.1214/15-EJS1030.