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Name: python312-openTSNE | Distribution: openSUSE Tumbleweed |
Version: 1.0.2 | Vendor: openSUSE |
Release: 1.2 | Build date: Thu Nov 14 10:02:21 2024 |
Group: Unspecified | Build host: reproducible |
Size: 1610286 | Source RPM: python-openTSNE-1.0.2-1.2.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
* 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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