API Reference¶

Distances¶

 persim.wasserstein Perform the Wasserstein distance matching between persistence diagrams. persim.bottleneck Perform the Bottleneck distance matching between persistence diagrams. persim.sliced_wasserstein Implementation of Sliced Wasserstein distance as described in Sliced Wasserstein Kernel for Persistence Diagrams by Mathieu Carriere, Marco Cuturi, Steve Oudot (https://arxiv.org/abs/1706.03358) persim.heat Return the pseudo-metric between two diagrams based on the continuous heat kernel as described in “A Stable Multi-Scale Kernel for Topological Machine Learning” by Jan Reininghaus, Stefan Huber, Ulrich Bauer, and Roland Kwitt (CVPR 2015) persim.gromov_hausdorff Estimate the mGH distance between simple unweighted graphs, represented as compact metric spaces based on their shortest path lengths.

Persistence Images¶

 persim.PersistenceImager Transformer which converts persistence diagrams into persistence images. persim.PersImage Initialize a persistence image generator.

Diagram Visualization¶

 persim.plot_diagrams A helper function to plot persistence diagrams. persim.bottleneck_matching Visualize bottleneck matching between two diagrams persim.wasserstein_matching Visualize bottleneck matching between two diagrams

Persistence barcode measure¶

 persim.persistent_entropy The persistent entropy has been defined in [1].