Skip to main content

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

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for nptsne, version 1.1.0
Filename, size File type Python version Upload date Hashes
Filename, size nptsne-1.1.0-cp36-cp36m-macosx_10_13_x86_64.whl (899.8 kB) File type Wheel Python version cp36 Upload date Hashes View
Filename, size nptsne-1.1.0-cp36-cp36m-manylinux2010_x86_64.whl (724.3 kB) File type Wheel Python version cp36 Upload date Hashes View
Filename, size nptsne-1.1.0-cp36-cp36m-win_amd64.whl (377.5 kB) File type Wheel Python version cp36 Upload date Hashes View
Filename, size nptsne-1.1.0-cp37-cp37m-macosx_10_13_x86_64.whl (899.8 kB) File type Wheel Python version cp37 Upload date Hashes View
Filename, size nptsne-1.1.0-cp37-cp37m-manylinux2010_x86_64.whl (724.3 kB) File type Wheel Python version cp37 Upload date Hashes View
Filename, size nptsne-1.1.0-cp37-cp37m-win_amd64.whl (377.4 kB) File type Wheel Python version cp37 Upload date Hashes View
Filename, size nptsne-1.1.0-cp38-cp38-macosx_10_13_x86_64.whl (905.9 kB) File type Wheel Python version cp38 Upload date Hashes View
Filename, size nptsne-1.1.0-cp38-cp38-manylinux2010_x86_64.whl (720.9 kB) File type Wheel Python version cp38 Upload date Hashes View
Filename, size nptsne-1.1.0-cp38-cp38-win_amd64.whl (375.3 kB) File type Wheel Python version cp38 Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page