Releases: LMJL-Alea/rgudhi
Releases · LMJL-Alea/rgudhi
rgudhi 0.2.0
In this minor release, I:
-
Added the
persistence_diagram_sample
class; -
Implemented the Lagragian formulation to compute the Wasserstein barycenters
of a sample of persistence diagrams; -
Fixed CRAN warnings:
- Incoherence of
autoplot
method implementation following renaming of main
argumentx
intoobject
. - Rectify an invalid URL pointing to the paper for BIRCH clustering.
- Incoherence of
rgudhi 0.1.0
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
classpersistence_diagram
for persistence diagram; plot()
andggplot2::autoplot()
methods forpersistence_diagram
objects;- vector and kernel representations of persistence diagrams;
- a number of metrics to quantify distances between persistence diagrams
(Bottleneck, Persistence Fisher, Wasserstein, Slice-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.