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    "info": {
        "author": "Bernd G\u00e4rtner, Konstantin Weddige",
        "author_email": "",
        "bugtrack_url": null,
        "classifiers": [
            "License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
            "Programming Language :: Python",
            "Topic :: Scientific/Engineering",
            "Topic :: Scientific/Engineering :: Mathematics",
            "Topic :: Software Development :: Libraries",
            "Topic :: Utilities"
        ],
        "description": "miniball\n========\n\nThese are python bindings to Bernd G\u00e4rtners `miniball software`__.\n\nSetup\n-----\n\nTo install *miniball* clone the repository and run the setup script:\n\n.. code-block:: bash\n   \n   python setup.py install\n\nThere is also a package for Arch Linux: https://aur.archlinux.org/packages/python-miniball/\n\nExample\n-------\n\n.. code-block:: python\n\n   import math\n   import random\n   import miniball\n\n   P = [(random.uniform(0, 100), random.uniform(0, 100)) for i in range(10000)]\n   mb = miniball.Miniball(P)\n   print('Center', mb.center())\n   print('Radius', math.sqrt(mb.squared_radius()))\n\nNotes\n-----\nThis algorithm has some numerical challenges worth mentioning. The result may deviate from the optimal result by\n10 times the machine epsilon and sometimes even more:\n\n.. code-block:: python\n\n   P = [(642123.5528970208, 5424489.146461355),\n        (651592.349934072, 5424969.380667617),\n        (642591.1068130962, 5425775.320365907),\n        (646380.0282527813, 5418648.987550308),\n        (648098.891235107, 5426586.3920675),\n        (650011.5835629451, 5426132.820254512),\n        (650297.6960375579, 5419125.777007122),\n        (645249.2122321032, 5421055.739722816),\n        (645333.9125837489, 5426228.852409409)]\n\n   mb = miniball.Miniball(P)\n   if not mb.is_valid():\n       print('Possibly invalid!')\n   print('Relative error', mb.relative_error())\n\nIf this is a problem for you, shifting the input towards (0,0) may help:\n\n.. code-block:: python\n\n   minx = min(P, key=lambda p: p[0])[0]\n   miny = min(P, key=lambda p: p[1])[1]\n\n   P = [(p[0] - minx, p[1] - miny) for p in P]\n\n   mb = miniball.Miniball(P)\n   if not mb.is_valid():\n       print('Possibly invalid!')\n   print('Relative error', mb.relative_error())\n\n__ http://www.inf.ethz.ch/personal/gaertner/miniball.html",
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        "keywords": "",
        "license": "",
        "maintainer": "",
        "maintainer_email": "",
        "name": "MiniballCpp",
        "package_url": "https://pypi.org/project/MiniballCpp/",
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        "summary": "Smallest Enclosing Balls of Points",
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