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| author | Vincent Rouvreau <10407034+VincentRouvreau@users.noreply.github.com> | 2020-12-14 16:29:12 +0100 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2020-12-14 16:29:12 +0100 |
| commit | 988277821dbcc204a8568a740293f2bf86b51f72 (patch) | |
| tree | 4384c230a25b4d259395de97d5a31f511c000011 /.github/next_release.md | |
| parent | 1a6f1aa1b3119d5b211eda8fb0908a845c920fa5 (diff) | |
| parent | 34e95e0853daa3dd897f08824cebc8ca77d5cef9 (diff) | |
Merge pull request #439 from VincentRouvreau/release_note_gudhi_3_4_0
Release note 3.4.0
Diffstat (limited to '.github/next_release.md')
| -rw-r--r-- | .github/next_release.md | 7 |
1 files changed, 4 insertions, 3 deletions
diff --git a/.github/next_release.md b/.github/next_release.md index 7e7fe03b..d8f53f0f 100644 --- a/.github/next_release.md +++ b/.github/next_release.md @@ -1,6 +1,6 @@ We are pleased to announce the release 3.4.0 of the GUDHI library. -As a major new feature, the GUDHI library now offers dD weighted alpha complex, ... +As a major new feature, the GUDHI library now offers dD weighted alpha complex, pip and conda packages for Python 3.9. 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). @@ -9,8 +9,9 @@ Below is a list of changes made since GUDHI 3.3.0: - [Alpha complex](https://gudhi.inria.fr/doc/latest/group__alpha__complex.html) - the C++ weighted version for alpha complex is now available in dimension D. -- [Module](link) - - ... +- 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 - [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. |