Dirk Mueller
9fba3dde0b
- 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
OBS-URL: https://build.opensuse.org/request/show/963336
OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-openTSNE?expand=0&rev=6
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-------------------------------------------------------------------
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Sun Mar 20 19:38:50 UTC 2022 - Ben Greiner <code@bnavigator.de>
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- Update to 0.6.2
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* By default, we now use the MultiscaleMixture affinity model,
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enabling us to pass in a list of perplexities instead of a
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single perplexity value. This is fully backwards compatible.
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* Previously, perplexity values would be changed according to the
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dataset. E.g. we pass in perplexity=100 with N=150. Then
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TSNE.perplexity would be equal to 50. Instead, keep this value
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as is and add an effective_perplexity_ attribute (following the
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convention from scikit-learn, which puts in the corrected
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perplexity values.
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* Fix bug where interpolation grid was being prepared even when
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using BH optimization during transform.
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* Enable calling .transform with precomputed distances. In this
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case, the data matrix will be assumed to be a distance matrix.
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* Fix potential problem with clang-13, which actually does
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optimization with infinities using the -ffast-math flag
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- Enable python310 build
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- Skip a test in 32bit failing due to rounding errors
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-------------------------------------------------------------------
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Fri Feb 4 16:10:13 UTC 2022 - Ben Greiner <code@bnavigator.de>
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- Update to 0.6.1
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* Remove affinites from TSNE construction, allow custom
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affinities and initialization in .fit method. This improves the
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API when dealing with non-tabular data. This is not backwards
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compatible.
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* Add metric="precomputed". This includes the addition of
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openTSNE.nearest_neighbors.PrecomputedDistanceMatrix and
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openTSNE.nearest_neighbors.PrecomputedNeighbors.
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* Add knn_index parameter to openTSNE.affinity classes.
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* Add (less-than-ideal) workaround for pickling Annoy objects.
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* Extend the range of recommended FFTW boxes up to 1000.
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* Remove deprecated openTSNE.nearest_neighbors.BallTree.
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* Remove deprecated openTSNE.callbacks.ErrorLogger.
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* Remove deprecated TSNE.neighbors_method property.
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* Add and set as default negative_gradient_method="auto".
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- Skip building on python310: gh#pavlin-policar/openTSNE#205
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-------------------------------------------------------------------
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Thu Apr 1 07:36:31 UTC 2021 - Bernhard Wiedemann <bwiedemann@suse.com>
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- Add python-openTSNE-disable-CPU-autodetection.patch (boo#1100677)
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-------------------------------------------------------------------
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Fri Jan 29 19:18:18 UTC 2021 - Ben Greiner <code@bnavigator.de>
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- initial specfile for version 0.5.1
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- replaces python-fastTSNE
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- The pytest_arch macro needs the "Cepl-Strangelove-Parameter"
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(= specify --import-mode)
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