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diff --git a/.github/next_release.md b/.github/next_release.md index 14546066..5a74966d 100644 --- a/.github/next_release.md +++ b/.github/next_release.md @@ -1,47 +1,23 @@ -We are pleased to announce the release 3.3.0 of the GUDHI library. +We are pleased to announce the release 3.4.0 of the GUDHI library. -As a major new feature, the GUDHI library now offers a persistence-based clustering algorithm, weighted Rips complex using DTM -and edge collapse. +As a major new feature, the GUDHI library now offers dD weighted alpha complex, pip and conda packages for Python 3.9. -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). +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.3.4.0.tar.gz). -Below is a list of changes made since GUDHI 3.2.0: +Below is a list of changes made since GUDHI 3.3.0: -- [DTM density estimator](https://gudhi.inria.fr/python/latest/point_cloud.html#module-gudhi.point_cloud.dtm) - - Python implementation of a density estimator based on the distance to the empirical measure defined by a point set. +- [Alpha complex](https://gudhi.inria.fr/doc/latest/group__alpha__complex.html) + - the C++ weighted version for alpha complex is now available in any dimension D. -- [DTM Rips complex](https://gudhi.inria.fr/python/latest/rips_complex_user.html#dtm-rips-complex) - - This Python implementation constructs a weighted Rips complex giving larger weights to outliers, - which reduces their impact on the persistence diagram +- Simplex tree [C++](https://gudhi.inria.fr/doc/latest/class_gudhi_1_1_simplex__tree.html) [Python](http://gudhi.gforge.inria.fr/python/latest/simplex_tree_ref.html) + - A new method to reset the filtrations + - A new method to get the boundaries of a simplex -- [Alpha complex](https://gudhi.inria.fr/python/latest/alpha_complex_user.html) - Python interface improvements - - 'fast' and 'exact' computations - - Delaunay complex construction by not setting filtration values - - Use the specific 3d alpha complex automatically to make the computations faster - -- [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 - -- Persistence representations - - [Atol](https://gudhi.inria.fr/python/latest/representations.html#gudhi.representations.vector_methods.Atol) - is integrated in finite vectorisation methods. This - [article](https://www.fujitsu.com/global/about/resources/news/press-releases/2020/0316-01.html) talks about - applications using Atol. This module was originally available at - [https://github.com/martinroyer/atol](https://github.com/martinroyer/atol) - - Python interface change: [Wasserstein metrics](https://gudhi.inria.fr/python/latest/representations.html#gudhi.representations.metrics.WassersteinDistance) - is now [hera](https://github.com/grey-narn/hera) by default +- [Subsampling](https://gudhi.inria.fr/doc/latest/group__subsampling.html) + - The C++ function `choose_n_farthest_points()` now takes a distance function instead of a kernel as first argument, users can replace `k` with `k.squared_distance_d_object()` in each call in their code. - Miscellaneous - - The [list of bugs that were solved since GUDHI-3.2.0](https://github.com/GUDHI/gudhi-devel/issues?q=label%3A3.3.0+is%3Aclosed) - is available on GitHub. + - The [list of bugs that were solved since GUDHI-3.3.0](https://github.com/GUDHI/gudhi-devel/issues?q=label%3A3.4.0+is%3Aclosed) is available on GitHub. All modules are distributed under the terms of the MIT license. However, there are still GPL dependencies for many modules. We invite you to check our [license dedicated web page](https://gudhi.inria.fr/licensing/) for further details. @@ -53,4 +29,3 @@ We provide [bibtex entries](https://gudhi.inria.fr/doc/latest/_citation.html) fo Feel free to [contact us](https://gudhi.inria.fr/contact/) in case you have any questions or remarks. For further information about downloading and installing the library ([C++](https://gudhi.inria.fr/doc/latest/installation.html) or [Python](https://gudhi.inria.fr/python/latest/installation.html)), please visit the [GUDHI web site](https://gudhi.inria.fr/). - |