Python library containing T-SNE algorithms.

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

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

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

• numpy > =1.7.1
• scipy >= 0.12.0
• cython >= 0.19.1
• cblas or openblas. Tested version is v0.2.5 and v0.2.6 (not necessary for OSX).

Anaconda is recommended.

You can install the package 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

Basic usage:

from tsne import bh_sne
X_2d = bh_sne(X)

• Iris
• MNIST
• word2vec on presidential speeches via @prateekpg2455

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