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        "description": "pyfof\n=====\n\nFriends of Friends cluster finding in python.\n\nThis implements the friends-of-friends algorithm to find clusters of points,\naccelerated with an R*-tree.\n\n## Requirements\n * c++11 complient compiler\n * [Cython](http://cython.org/) (for the development version only)\n * [numpy](http://www.numpy.org/)\n * [boost](http://www.boost.org/)\n\n## Installation\n\nIf your boost installation is in a normal place you should just be able to install\nthe latest release of the package directly from PyPI\n\n```pip install pyfof```\n\nIf that fails then you will need to tell pip where to find your boost include\ndirectory. This can be done by creating a file in your home directory called\n```.pydistutils.cfg``` containing:\n\n```\n[build_ext]\ninclude_dirs=/path/to/boost/include/directory\n```\n\nand then running the above command.\n\n## Examples\n\n### Two Gaussian blobs\n\n```python\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport matplotlib.cm as cm\nimport pyfof\n\nnpts = 10000\ndata = np.vstack((np.random.normal(-1,0.2,(npts/2,2)),\\\n                  np.random.normal(1,0.2,(npts/2,2))))\n\ngroups = pyfof.friends_of_friends(data, 0.4)\n\ncolors = cm.rainbow(np.linspace(0, 1, len(groups)))\nfor g,c in zip(groups, colors):\n    plt.scatter(data[g,0], data[g,1], color=c, s=3)\n\nplt.show()\n```\n\n![gaussian_example](/../screenshots/img/gaussian_example.png)\n\n### A more complicated example\n\n![stream_example](/../screenshots/img/stream_example.png)\n\n\n",
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