Fast python distance computations in a variety of metrics that uses Graphics Processing Units with PyCuda.

This is a framework that will allow general distance metrics to be incorporated into tree-based neighbors searches. The idea is that we need a fast way to compute the distance between two points under a given metric.

>>> from pycudadistances.distances import euclidean_distances
>>> X = [[0, 1], [1, 1]]

>>> euclidean_distances(X, X)
array([[ 0.,  1.],
       [ 1.,  0.]])

>>> # get distance to origin
>>> euclidean_distances(X, [[0, 0]])
array([[ 1.        ],
       [ 1.41421356]])

Please submit bugs you might encounter, as well Patches and Features Requests to the Issues Tracker located at GitHub.

If you want to submit a patch to this project, it is AWESOME. Follow this guide:

• Fork PycudaDistances
• Make your alterations and commit
• Create a topic branch - git checkout -b my_branch
• Push to your branch - git push origin my_branch
• Create a Pull Request from your branch.
• You just contributed to the PycudaDistances project!

The required dependencies to build the software are Python >= 2.6, setuptools, Numpy >= 1.3, PyCuda.

To install for all users on Unix/Linux::

sudo python setup.py install

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