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diff --git a/.github/next_release.md b/.github/next_release.md index 72c55999..54115196 100644 --- a/.github/next_release.md +++ b/.github/next_release.md @@ -1,59 +1,18 @@ -We are pleased to announce the release 3.6.0 of the GUDHI library. +We are pleased to announce the release 3.7.1 of the GUDHI library. -As a major new feature, the GUDHI library now offers automatic differentiation for the computation of -persistence diagrams, Cubical complex persistence scikit-learn like interface, datasets fetch methods, -and weighted version for alpha complex in any dimension D. +This minor post-release is a bug fix version for [python representation module](https://gudhi.inria.fr/python/latest/representations.html). -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.X.X.tar.gz). -For further information, please visit the [GUDHI web site](https://gudhi.inria.fr/). +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.X.X.tar.gz). -# GUDHI 3.6.0 Release Notes -Below is a list of changes made since GUDHI 3.5.0: +The [list of bugs that were solved since GUDHI-3.7.0](https://github.com/GUDHI/gudhi-devel/issues?q=label%3A3.7.1+is%3Aclosed) is available on GitHub. -- TensorFlow 2 models that can handle automatic differentiation for the computation of persistence diagrams: - - [Cubical complex](https://gudhi.inria.fr/python/latest/cubical_complex_tflow_itf_ref.html) - - [lower-star persistence on simplex trees](https://gudhi.inria.fr/python/latest/ls_simplex_tree_tflow_itf_ref.html) - - [Rips complex](https://gudhi.inria.fr/python/latest/rips_complex_tflow_itf_ref.html) +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. -- [Cubical complex](https://gudhi.inria.fr/python/latest/cubical_complex_sklearn_itf_ref.html) - - Cubical complex persistence scikit-learn like interface +We kindly ask users to cite the GUDHI library as appropriately as possible in their papers, and to mention the use of the GUDHI library on the web pages of their projects using GUDHI and provide us with links to these web pages. -- [Datasets](https://gudhi.inria.fr/python/latest/datasets.html) - - `datasets.remote.fetch_bunny` and `datasets.remote.fetch_spiral_2d` allows to fetch datasets from [GUDHI-data](https://github.com/GUDHI/gudhi-data) +We provide [bibtex entries](https://gudhi.inria.fr/doc/latest/_citation.html) for the modules of the User and Reference Manual, as well as for publications directly related to the GUDHI library. -- [Alpha complex](https://gudhi.inria.fr/python/latest/alpha_complex_user.html) - - python weighted version for alpha complex is now available in any dimension D. - - `alpha_complex = gudhi.AlphaComplex(off_file='/data/points/tore3D_300.off')` is deprecated, please use [read_points_from_off_file](https://gudhi.inria.fr/python/latest/point_cloud.html#gudhi.read_points_from_off_file) instead. +Feel free to [contact us](https://gudhi.inria.fr/contact/) in case you have any questions or remarks. -- [Edge collapse](https://gudhi.inria.fr/doc/latest/group__edge__collapse.html) - - rewriting of the module to improve performance - -- [Čech complex](https://gudhi.inria.fr/doc/latest/group__cech__complex.html) - - rewriting of the module to improve performance - -- [Representations](https://gudhi.inria.fr/python/latest/representations.html#gudhi.representations.vector_methods.BettiCurve) - - A more flexible Betti curve class capable of computing exact curves - -- [C++ documentation](https://gudhi.inria.fr/doc/latest/) - - upgrade and improve performance with new doxygen features - -- [Simplex tree](https://gudhi.inria.fr/python/latest/simplex_tree_ref.html) - - `__deepcopy__`, `copy` and copy constructors for python module - - `expansion_with_blockers` python interface - -- Installation - - Boost ≥ 1.66.0 is now required (was ≥ 1.56.0). - - Python >= 3.5 and cython >= 0.27 are now required. - -- Miscellaneous - - The [list of bugs that were solved since GUDHI-3.5.0](https://github.com/GUDHI/gudhi-devel/issues?q=label%3A3.6.0+is%3Aclosed) is available on GitHub. - -## Contributors - -- @albert-github -- @gspr -- @Hind-M -- @MathieuCarriere -- @mglisse -- @Soriano-Trigueros -- @VincentRouvreau +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/). |