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A python wrapper for Barnes-Hut tsne
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README.md

Python-TSNE

travis-ci

Python library containing T-SNE algorithms.

Note: Scikit-learn v0.17 includes TSNE algorithms and you should probably be using them instead of this.

Algorithms

Barnes-Hut-SNE

A python (cython) wrapper for Barnes-Hut-SNE aka fast-tsne.

I basically took osdf's code and made it pip compliant.

Requirements

Anaconda is recommended.

Installation

You can install the package from Conda:

conda install -c maxibor tsne

Or from PyPI:

pip install tsne

Or directly from the Github repository:

pip install git+https://github.com/danielfrg/tsne.git

Or using docker (could be useful for testing):

$ docker build -t tsne .
$ docker run -it -v /Users/drodriguez/workspace/tsne/:/tsne tsn

# Inside Docker:
$ python setup.py install

Usage

Basic usage:

from tsne import bh_sne
X_2d = bh_sne(X)

Examples

More Information

See Barnes-Hut-SNE (2013), L.J.P. van der Maaten. It is available on arxiv.

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