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The nptsne package is designed to export a number of python classes that wrap tSNE and HSNE

Project description

nptsne - A numpy compatible python extension for GPGPU linear complexity tSNE

The nptsne package is designed to export a number of python classes that wrap GPGPU linear complexity tSNE or the hierarchical SNE (hSNE) method.

When using nptsne please include the following citations when using t-SNE and or using HSNE:

using t-SNE

*Pezzotti, N., Thijssen, J., Mordvintsev, A., Höllt, T., Van Lew, B., Lelieveldt, B.P.F., Eisemann, E., Vilanova, A., (2020), "GPGPU Linear Complexity t-SNE Optimization" in IEEE Transactions on Visualization and Computer Graphics.
doi: 10.1109/TVCG.2019.2934307
keywords: {Minimization;Linear programming;Computational modeling;Approximation algorithms;Complexity theory;Optimization;Data visualization;High Dimensional Data;Dimensionality Reduction;Progressive Visual Analytics;Approximate Computation;GPGPU},
URL: https://doi.org/10.1109/TVCG.2019.2934307 *

using HNSE

*Pezzotti, N., Höllt, T., Lelieveldt, B., Eisemann, E., Vilanova, A., (2016), "Hierarchical Stochastic Neighbor Embedding" in Computer Graphics Forum, 35: 21-30.
doi:10.1111/cgf.12878
keywords: {Categories and Subject Descriptors (according to ACM CCS), I.3.0 Computer Graphics: General},
URL: https://doi.org/10.1111/cgf.12878 *

Attributions

The t-SNE and HSNE implementations are the original work of the authors named in the literature.

Full documentation

Full documentation is available at the nptsne doc pages

Download files

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Source Distributions

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nptsne-1.2.0-cp39-cp39-win_amd64.whl (417.2 kB view hashes)

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nptsne-1.2.0-cp39-cp39-macosx_10_9_x86_64.whl (958.2 kB view hashes)

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nptsne-1.2.0-cp38-cp38-win_amd64.whl (422.0 kB view hashes)

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nptsne-1.2.0-cp38-cp38-macosx_10_9_x86_64.whl (958.1 kB view hashes)

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nptsne-1.2.0-cp37-cp37m-win_amd64.whl (421.3 kB view hashes)

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nptsne-1.2.0-cp36-cp36m-win_amd64.whl (421.3 kB view hashes)

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