Metadata-Version: 1.2
Name: bctpy
Version: 0.5.2
Summary: Brain Connectivity Toolbox for Python
Home-page: https://github.com/aestrivex/bctpy
Maintainer: Roan LaPlante
Maintainer-email: rlaplant@nmr.mgh.harvard.edu
License: Visuddhimagga Sutta; GPLv3+
Description: # Brain Connectivity Toolbox for Python version 0.5.2
        
        Author: Roan LaPlante <rlaplant@nmr.mgh.harvard.edu>
        
        Tested against python 2.7 and 3.5+.
        
        ## 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.
        
Platform: any
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: X11 Applications
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering :: Information Analysis
