Topological Data Analysis for humans
There is a growing need for an ecosystem of TDA libraries that is approachable to non-researchers. This project aims to provide a curated library for Python tools that are widely usable and easily approachable. Each is easy to install through traditional Python mechanisms, portable to all platforms, requires no dependencies outside of what is available on Pypi, has comprehensive documentation , is open source, provides an issue tracker and is responsive to questions, and exposes an intuitive API for developers familiar with the Python scientific computing ecosystem.
Each project can stand alone, or be used as part of the scikit-tda bundle. This project curates the group of packages and houses extensive documentation and examples on how each package can be used together.
Scikit-TDA is a home for compatible TDA libraries intended for non-researchers. We provide detailed documentation and unified APIs so that using TDA can be used in the wild. The TDA ecosystem is rapidly growing. Below is the list of current projects, either built or in development, to be included in scikit-tda.
- Ripser - Data to diagrams in one line
- Persim - Easy Persistence Images
- UMAP - Mathematically justified dimensionality reduction
- Kepler Mapper - Mapper framework integrated into sklearn
The following packages are currently in development:
- Cechmate - Custom filtrations builder
- Diagrams - Comparison & Visualization of diagrams
- TaDAsets - Data sets designed for TDA
To install all these libraries
pip install scikit-tda
This project is entirely a work in progress and still in the coneptual phase. We hope to assemble an ecosystem of TDA libraries, complete with documentation and examples, that is approachable to people outside the field of Algebraic Topology. If you would like to contribute and have ideas for how to do so, please reach out!
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size & hash SHA256 hash help||File type||Python version||Upload date|
|scikit_tda-0.0.3-py3-none-any.whl (2.6 kB) Copy SHA256 hash SHA256||Wheel||py3||Aug 12, 2018|
|scikit-tda-0.0.3.tar.gz (2.7 kB) Copy SHA256 hash SHA256||Source||None||Aug 12, 2018|