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 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
Basic usage:
from tsne import bh_sne
X_2d = bh_sne(X)
See Barnes-Hut-SNE (2013), L.J.P. van der Maaten. It is available on arxiv.