Revisions of python-openTSNE

buildservice-autocommit accepted request 1160837 from Dirk Mueller's avatar Dirk Mueller (dirkmueller) (revision 12)
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Dirk Mueller's avatar Dirk Mueller (dirkmueller) committed (revision 10)
- 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)
  * Given the longtime stability of openTSNE, it is only fitting
buildservice-autocommit accepted request 1111748 from Dirk Mueller's avatar Dirk Mueller (dirkmueller) (revision 9)
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Dirk Mueller's avatar Dirk Mueller (dirkmueller) accepted request 1111345 from Markéta Machová's avatar Markéta Machová (mcalabkova) (revision 8)
- 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
buildservice-autocommit accepted request 963465 from Dirk Mueller's avatar Dirk Mueller (dirkmueller) (revision 7)
baserev update by copy to link target
Dirk Mueller's avatar Dirk Mueller (dirkmueller) accepted request 963336 from Benjamin Greiner's avatar Benjamin Greiner (bnavigator) (revision 6)
- 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
Dirk Mueller's avatar Dirk Mueller (dirkmueller) accepted request 951592 from Benjamin Greiner's avatar Benjamin Greiner (bnavigator) (revision 5)
- 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
buildservice-autocommit accepted request 882539 from Markéta Machová's avatar Markéta Machová (mcalabkova) (revision 4)
baserev update by copy to link target
Markéta Machová's avatar Markéta Machová (mcalabkova) accepted request 882511 from Bernhard Wiedemann's avatar Bernhard Wiedemann (bmwiedemann) (revision 3)
Add python-openTSNE-disable-CPU-autodetection.patch (boo#1100677)
Richard Brown's avatar Richard Brown (RBrownSUSE) accepted request 867964 from Benjamin Greiner's avatar Benjamin Greiner (bnavigator) (revision 2)
initialized devel package after accepting 867964
Dirk Mueller's avatar Dirk Mueller (dirkmueller) accepted request 867806 from Benjamin Greiner's avatar Benjamin Greiner (bnavigator) (revision 1)
The new name for python-fastTSNE
Displaying all 12 revisions
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