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 argument`x`

into`object`

. - Rectify an invalid URL pointing to the paper for BIRCH clustering.

- Incoherence of

**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, 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.