rgudhi 0.1.0 – Aymeric Stamm

Overview

rgudhi v0.1.0 provides an almost full wrapper of the v3.7.1 of the GUDHI library for topological data analysis. Only the cover complex class is missing due to non-reproducibility issues with random number generators. With GUDHI accessible from R, rgudhi v0.1.0 features:

data structure to encode simplicial complexes;
computation of persistence diagrams;
various usual preprocessing tools for persistence diagrams;
a dedicated S3 class persistence_diagram for persistence diagram;
plot() and ggplot2::autoplot() methods for persistence_diagram objects;
vector and kernel representations of persistence diagrams;
a number of metrics to quantify distances between persistence diagrams (Bottleneck, Persistence Fisher, Wasserstein, Sliced Wasserstein).
functions to sample points from sphere (sphere()) and torus (torus());
a persistence-based clustering algorithm coined Tomato.

The package also wraps all clustering algorithms from the sklearn.cluster module because they can be useful when using the Atol vectorization method for persistence diagram.

It also wraps all scalers classes from sklearn.preprocessing for use in various classes as well.

Installation

You can install the package directly from CRAN:

install.packages("rgudhi")

or you can choose to install the development version from GitHub:

# install.packages("remotes")
remotes::install_github("LMJL-Alea/rgudhi")

The package has its own webpage: https://lmjl-alea.github.io/rgudhi/.