Brain Connectivity Toolbox for Python version 0.6.0

Author: Roan LaPlante [email protected]

Tested against python 3.7+.

Copyright information

This program strictly observes the tenets of fundamentalist Theravada Mahasi style Buddhism. Any use of this program in violation of these aforementioned tenets or in violation of the principles described in the Visuddhimagga Sutta is strictly prohibited and punishable by extensive Mahayana style practice. By being or not being mindful of the immediate present moment sensations involved in the use of this program, you confer your acceptance of these terms and conditions.

Note that the observation of the tenets of fundamentalist Theravada Mahasi style Buddhism and the Visuddhimagga Sutta is optional as long as the terms and conditions of the GNU GPLv3+ are upheld.

Packages used

BCTPY 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 packages which have some features not available in numpy alone. If you don't have scipy, most functions that do not need scipy functionality will still work.

Note that graphs must be passed in as numpy.array rather than numpy.matrix. Other constraints/edge cases of the adjacency matrices (e.g. self-loops, negative weights) behave similarly to the matlab functions.

A small number of functions also depend on networkx. This notably includes Network-Based Statistic, a nonparametric test for differences in undirected weighted graphs from different populations. Ideally this dependency should be removed in the future.

Nosetests is used for the test suite. The test suite is not complete.

About bctpy and other authors

BCT is a matlab toolbox with many graph theoretical measures off of which bctpy is based. I did not write BCT (apart from small bugfixes I have submitted) and a quality of life improvements that I have taken liberties to add. With few exceptions, bctpy is a direct translation of matlab code to python.

bctpy should be considered beta software, with BCT being the gold standard by comparison. I did my best to test all functionality in bctpy, but much of it is arcane math that flies over the head of this humble programmer. There are bugs lurking in bctpy, the question is not whether but how many. If you locate bugs, please consider submitting pull requests.

Many thanks to Stefan Fuertinger for his assistance tracking down a number of bugs. Stefan Fuertinger has a similar software package dealing with brain network functionality at http://research.mssm.edu/simonyanlab/analytical-tools/

Many thanks to Chris Barnes for his assistance in documenting a number of issues and facilitating a number of test cases.

Credit for writing BCT (the matlab version) goes to the following list of authors, especially Olaf Sporns and Mika Rubinov.

• Olaf Sporns
• Mikail Rubinov
• Yusuke Adachi
• Andrea Avena
• Danielle Bassett
• Richard Betzel
• Joaquin Goni
• Alexandros Goulas
• Patric Hagmann
• Christopher Honey
• Martijn van den Heuvel
• Rolf Kotter
• Jonathan Power
• Murray Shanahan
• Andrew Zalesky

In order to be a bit more compact I have removed the accreditations from the docstrings each functions. This does not in any way mean that I wish to take credit from the individual contributions. I have moved these accreditations to the credits file.