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| author | ROUVREAU Vincent <vincent.rouvreau@inria.fr> | 2020-07-02 21:23:50 +0200 |
|---|---|---|
| committer | ROUVREAU Vincent <vincent.rouvreau@inria.fr> | 2020-07-02 21:23:50 +0200 |
| commit | e44b0a88e2241f81b51b9060f73ac86f53c9cfc1 (patch) | |
| tree | 5020b95c18d0206fe8e693a40d1e4aaf132d6a51 /.github | |
| parent | 0f364d372a6bce81d895d4ccd066174bad260e9e (diff) | |
[skip ci] modify release note
Diffstat (limited to '.github')
| -rw-r--r-- | .github/next_release.md | 10 |
1 files changed, 8 insertions, 2 deletions
diff --git a/.github/next_release.md b/.github/next_release.md index cc868db7..e73f7c96 100644 --- a/.github/next_release.md +++ b/.github/next_release.md @@ -1,8 +1,10 @@ We are pleased to announce the release 3.3.0 of the GUDHI library. -As a major new feature, the GUDHI library now offers a persistence-based clustering algorithm and weighted Rips complex using DTM. +As a major new feature, the GUDHI library now offers a persistence-based clustering algorithm, weighted Rips complex using DTM +and edge collapse. -We are now using GitHub to develop the GUDHI library, do not hesitate to [fork the GUDHI project on GitHub](https://github.com/GUDHI/gudhi-devel). From a user point of view, we recommend to download GUDHI user version (gudhi.3.3.0.tar.gz). +The GUDHI library is hosted on GitHub, do not hesitate to [fork the GUDHI project on GitHub](https://github.com/GUDHI/gudhi-devel). +From a user point of view, we recommend to download GUDHI user version (gudhi.3.3.0.tar.gz). Below is a list of changes made since GUDHI 3.2.0: @@ -21,6 +23,10 @@ Below is a list of changes made since GUDHI 3.2.0: - [Clustering](https://gudhi.inria.fr/python/latest/clustering.html) - Python implementation of [ToMATo](https://doi.org/10.1145/2535927), a persistence-based clustering algorithm +- [Edge Collapse](https://gudhi.inria.fr/doc/latest/group__edge__collapse.html) of a filtered flag complex + - This C++ implementation reduces a filtration of Vietoris-Rips complex from its graph to another smaller + flag filtration with the same persistence. + - [Bottleneck distance](https://gudhi.inria.fr/python/latest/bottleneck_distance_user.html) - Python interface to [hera](https://github.com/grey-narn/hera)'s bottleneck distance |