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@@ -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/).
-