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            "License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)",
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        "description": "[![Build Status](https://travis-ci.org/aestrivex/bctpy.svg?branch=master)](https://travis-ci.org/aestrivex/bctpy)\n\n# Brain Connectivity Toolbox for Python version 0.5.1\n\nAuthor: Roan LaPlante <rlaplant@nmr.mgh.harvard.edu>\n\n## Copyright information\n\nThis program strictly observes the tenets of fundamentalist Theravada Mahasi\nstyle Buddhism.  Any use of this program in violation of these aforementioned\ntenets or in violation of the principles described in the Visuddhimagga Sutta\nis strictly prohibited and punishable by extensive Mahayana style practice.\nBy being or not being mindful of the immediate present moment sensations\ninvolved in the use of this program, you confer your acceptance of these terms\nand conditions.\n\nNote that the observation of the tenets of fundamentalist Theravada Mahasi\nstyle Buddhism and the Visuddhimagga Sutta is optional as long as the terms and\nconditions of the GNU GPLv3+ are upheld.\n\n## Packages used\n\nBCTPY is written in pure python and requires only `scipy` and `numpy`. `scipy` is required for a couple of functions for its statistical and linear algebra\npackages which have some features not available in `numpy` alone. If you don't\nhave `scipy`, most functions that do not need `scipy` functionality will still work.\n\nNote that graphs must be passed in as `numpy.array`s rather than `numpy.matrix`es. Other constraints/ edge cases of the adjacency matrices (e.g. self-loops, negative weights) behave similarly to the matlab functions.\n\nA small number of functions (notably including network-based statistics, a\nnonparametric test for differences in undirected weighted graphs from different\npopulations) currently require networkx, though this should be changed at some\npoint in the future.\n\nNosetests is used for the test suite. The test suite is not complete.\n\n## About `bctpy` and other authors\n\nBCT is a matlab toolbox with many graph theoretical measures off of which `bctpy`\nis based.  I did not write BCT (apart from small bugfixes I have submitted)\nand a quality of life improvements that I have taken liberties to add.\nWith few exceptions, `bctpy` is a direct translation of matlab code to python.\n\n`bctpy` should be considered beta software, with BCT being the gold standard by\ncomparison. I did my best to test all functionality in `bctpy`, but much of it is\narcane math that flies over the head of this humble programmer. There *are*\nbugs lurking in `bctpy`, the question is not whether but how many. If you locate\nbugs, please submit them to me at rlaplant@nmr.mgh.harvard.edu.\n\nMany thanks to Stefan Fuertinger for his assistance tracking down a number of\nbugs. Stefan Fuertinger has a similar software package dealing with brain\nnetwork functionality at http://research.mssm.edu/simonyanlab/analytical-tools/\n\nMany thanks to Chris Barnes for his assistance in documenting a number of issues and facilitating a number of test cases.\n\nCredit for writing BCT (the matlab version) goes to the following list of\nauthors, especially Olaf Sporns and Mika Rubinov.\n\n- Olaf Sporns\n- Mikail Rubinov\n- Yusuke Adachi\n- Andrea Avena\n- Danielle Bassett\n- Richard Betzel\n- Joaquin Goni\n- Alexandros Goulas\n- Patric Hagmann\n- Christopher Honey\n- Martijn van den Heuvel\n- Rolf Kotter\n- Jonathan Power\n- Murray Shanahan\n- Andrew Zalesky\n\nIn order to be a bit more compact I have removed the accreditations from the\ndocstrings each functions. This does not in any way mean that I wish to take\ncredit from the individual contributions. I have moved these accreditations\nto the credits file.\n\n\n",
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