Metadata-Version: 2.4
Name: nptsne
Version: 2.0.3
Summary: The nptsne package is designed to export a number of python classes that wrap tSNE and HSNE
Author: Nicola Pezzotti, Thomas Höllt, Julian Thijssen, Alexander Vieth
Author-email: Baldur van Lew <b.van_lew@lumc.nl>
License-Expression: Apache-2.0
Project-URL: Tracker, https://github.com/biovault/nptsne/issues
Project-URL: Documentation, https://bldrvnlw.readthedocs.io
Project-URL: Source, https://github.com/biovault/nptsne
Keywords: tSNE,HSNE,embedding,GPU
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Classifier: Programming Language :: C++
Classifier: Typing :: Typed
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: numpy>=1.11.0
Dynamic: license-file

### 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](https://nptsne.readthedocs.io/en/v2.0.3)

###### Demos

Demos, runnable  via uv, are at [nptsne demo release pages] https://github.com/biovault/nptsne/releases/tag/v2.0.3
