Scikit-TDA is an opinionated collection of libraries for Topological Data Analysis. The user interfaces across all included libraries are standardized and compatible with numpy and scikit-learn.
This is currently a WIP. Documentation and examples will be coming this summer.
Currently, we include
- Kepler Mapper for mapper and visualization.
- UMAP for dimensionality reduction.
- ripser for persistent homology.
- persim for persistence images.
To install all these libraries
pip install scikit-tda
The libraries will then be accessible from
import sktda.kmapper as km
It is not clear what the best way to do this is. Should all libraries exist at the top level, or should we reorganize the libraries so they make more sense as a group?