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| Name: python311-openTSNE | Distribution: openSUSE Tumbleweed |
| Version: 1.0.2 | Vendor: openSUSE |
| Release: 2.1 | Build date: Fri May 9 07:12:25 2025 |
| Group: Unspecified | Build host: reproducible |
| Size: 1670954 | Source RPM: python-openTSNE-1.0.2-2.1.src.rpm |
| Packager: http://bugs.opensuse.org | |
| Url: https://github.com/pavlin-policar/openTSNE | |
| Summary: Extensible, parallel implementations of t-SNE | |
Extensible, parallel implementations of t-SNE
BSD-3-Clause
* Fri May 09 2025 Steve Kowalik <steven.kowalik@suse.com>
- Switch to pyproject macros.
* Thu Nov 14 2024 Dirk Müller <dmueller@suse.com>
- update to 1.0.2:
* build wheels for Python 3.12 (#255)
* update minimum Python version to 3.9
* add numpy 2.x support
* Tue Sep 03 2024 Andreas Schwab <schwab@suse.de>
- TestTSNECorrectnessUsingPrecomputedDistanceMatrix fails almost everywhere
* Fri Mar 22 2024 Dirk Müller <dmueller@suse.com>
- update to 1.0.1:
* setup.py maintenance
* drop Python 3.6 support
* correctly implement dof parameter in exact BH implementation
- drop get-numpy-include.patch (upstream)
* Thu Sep 14 2023 Markéta Machová <mmachova@suse.com>
- Update to 1.0.0
* Given the longtime stability of openTSNE, it is only fitting
that we release a v1.0.0.
* Various documentation fixes
* Include Python 3.11 in the test and build matrix
* Uniform affinity kernel now supports mean and max mode
- add get-numpy-include.patch
* Sun Mar 20 2022 Ben Greiner <code@bnavigator.de>
- Update to 0.6.2
* By default, we now use the MultiscaleMixture affinity model,
enabling us to pass in a list of perplexities instead of a
single perplexity value. This is fully backwards compatible.
* Previously, perplexity values would be changed according to the
dataset. E.g. we pass in perplexity=100 with N=150. Then
TSNE.perplexity would be equal to 50. Instead, keep this value
as is and add an effective_perplexity_ attribute (following the
convention from scikit-learn, which puts in the corrected
perplexity values.
* Fix bug where interpolation grid was being prepared even when
using BH optimization during transform.
* Enable calling .transform with precomputed distances. In this
case, the data matrix will be assumed to be a distance matrix.
* Fix potential problem with clang-13, which actually does
optimization with infinities using the -ffast-math flag
- Enable python310 build
- Skip a test in 32bit failing due to rounding errors
* Fri Feb 04 2022 Ben Greiner <code@bnavigator.de>
- Update to 0.6.1
* Remove affinites from TSNE construction, allow custom
affinities and initialization in .fit method. This improves the
API when dealing with non-tabular data. This is not backwards
compatible.
* Add metric="precomputed". This includes the addition of
openTSNE.nearest_neighbors.PrecomputedDistanceMatrix and
openTSNE.nearest_neighbors.PrecomputedNeighbors.
* Add knn_index parameter to openTSNE.affinity classes.
* Add (less-than-ideal) workaround for pickling Annoy objects.
* Extend the range of recommended FFTW boxes up to 1000.
* Remove deprecated openTSNE.nearest_neighbors.BallTree.
* Remove deprecated openTSNE.callbacks.ErrorLogger.
* Remove deprecated TSNE.neighbors_method property.
* Add and set as default negative_gradient_method="auto".
- Skip building on python310: gh#pavlin-policar/openTSNE#205
* Thu Apr 01 2021 Bernhard Wiedemann <bwiedemann@suse.com>
- Add python-openTSNE-disable-CPU-autodetection.patch (boo#1100677)
* Fri Jan 29 2021 Ben Greiner <code@bnavigator.de>
- initial specfile for version 0.5.1
- replaces python-fastTSNE
- The pytest_arch macro needs the "Cepl-Strangelove-Parameter"
(= specify --import-mode)
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