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
LICENCE (GNU GPL)
Copyright (c) 2013
All rights reserved.