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        "author": "Daniel Rapp",
        "author_email": "rappdw@gmail.com",
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            "Development Status :: 5 - Production/Stable",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: Apache Software License",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Scientific/Engineering :: Visualization",
            "Topic :: Software Development :: Libraries :: Python Modules"
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        "description": "[![PyPI - Version](https://img.shields.io/pypi/v/tsne-mp.svg)](https://pypi.org/project/tsne-mp/) [![PyPI - Wheel](https://img.shields.io/pypi/wheel/tsne-mp.svg)](https://pypi.org/project/tsne-mp/) [![Python 3.6](https://img.shields.io/badge/python-3.7-blue.svg)](https://www.python.org/downloads/release/python-370/) [![Python 3.6](https://img.shields.io/badge/python-3.6-blue.svg)](https://www.python.org/downloads/release/python-360/) [![Python 3.6](https://img.shields.io/badge/python-3.5-blue.svg)](https://www.python.org/downloads/release/python-350/) \n\n# Python TSNE implementation utilizing openmp for performance\n\nThis is based on the [10XDev/tsne](https://github.com/10XDev/tsne.git) fork of L.J.P. van der Maaten BH-tSNE implementation.\n\nIt has fixes to allow this to run in Python 3 and performance has been significantly\nincreased with OpenMP parallelism. (see: [tsne-perf-test](https://github.com/rappdw/tsne-perf-test.git))\n\n**Note:** While [Scikit-learn v0.17](http://scikit-learn.org/stable/whats_new.html#version-0-17) has a tsne implementation, \nthis implementation performs significantly faster than scikit-learn's. If you need speed, use this.\n\n\n## Algorithms\n\n### Barnes-Hut-SNE\n\nA python ([cython](http://www.cython.org)) wrapper for [Barnes-Hut-SNE](http://homepage.tudelft.nl/19j49/t-SNE.html) aka fast-tsne.\n\nWe forked 10XDev's implementation and openmp enabled the code.\n\n## Installation\n\nThis library has been added to pypi as tsne-mp\n\n```\npip install tsne-mp\n```\n\nIt requires openmp support.\n* OSX - `brew install libomp`\n* linux - 'sudo apt-get install libgomp1'\n* Windows - Included with Visual Studio C++\n\n## Usage\n\nBasic usage:\n\n```\nfrom tsne import bh_sne\nX_2d = bh_sne(X)\n```\nOr, the wheels also contain an executable that can be used from the command-line as described\nin [the original project](https://github.com/lvdmaaten/bhtsne).\n\n### Examples\n\n* [Iris](http://nbviewer.ipython.org/urls/raw.github.com/danielfrg/py_tsne/master/examples/iris.ipynb)\n* [MNIST](http://nbviewer.ipython.org/urls/raw.github.com/danielfrg/py_tsne/master/examples/mnist.ipynb)\n* [word2vec on presidential speeches](https://github.com/prateekpg2455/U.S-Presidential-Speeches) via [@prateekpg2455](https://github.com/prateekpg2455)\n\n## More Information\n\nSee *Barnes-Hut-SNE* (2013), L.J.P. van der Maaten. It is available on [arxiv](http://arxiv.org/abs/1301.3342).\n\n\n\n",
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        "license": "Apache License Version 2.0, January 2004",
        "maintainer": "",
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        "name": "tsne-mp",
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