Distances and representations of persistence diagrams


Keywords
persistent, homology, persistence, images, diagrams, topological, data, analysis, algebraic, topology, unsupervised, learning, supervised, machine, sliced, wasserstein, distance, bottleneck, bottleneck-distance, persistence-diagrams, persistence-image, persistence-images, python, sliced-wasserstein-distance, tda
License
MIT
Install
pip install persim==0.3.5

Documentation

PyPI version PyPI - Downloads Conda Version Conda Downloads codecov License: MIT

Persim is a Python package for many tools used in analyzing Persistence Diagrams. It currently houses implementations of

  • Persistence Images
  • Persistence Landscapes
  • Bottleneck distance
  • Modified Gromov–Hausdorff distance
  • Sliced Wasserstein Kernel
  • Heat Kernel
  • Diagram plotting

Setup

The latest version of persim can be found on Pypi and installed with pip:

pip install persim

Documentation and Usage

Documentation about the library, it's API, and examples of how to use it can be found at persim.scikit-tda.org.

Contributions

We welcome contributions of all shapes and sizes. There are lots of opportunities for potential projects, so please get in touch if you would like to help out. Everything from an implementation of your favorite distance, notebooks, examples, and documentation are all equally valuable so please don't feel you can't contribute.

To contribute please fork the project make your changes and submit a pull request. We will do our best to work through any issues with you and get your code merged into the main branch.