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View Code? Open in Web Editor NEWTools for analysis of brain imaging-derived networks, based on NetworkX
License: BSD 3-Clause "New" or "Revised" License
brainx's Introduction
================================================ Brainx: network analysis for neuroimaging data ================================================ Brainx provides a set of tools, based on the NetworkX graph theory package, for the analysis of graph properties of neuroimaging data. Installation ============ For a normal installation, simply type:: python setup.py install [other options here] To install using setuptools support, use:: python setup_egg.py install [other options here] For example, to install using a development-mode setup in your personal user directory, use:: python setup_egg.py develop --prefix=$HOME/.local Testing ======= To run the test suite, once you have installed it as per the above instructions, simply use:: nosetests brainx or for more informative details:: nosetests -vvs brainx For further information, type ``nosetests -h``. License information =================== Brainx is licensed under the terms of the new BSD license. See the file "LICENSE" for information on the history of this software, terms & conditions for usage, and a DISCLAIMER OF ALL WARRANTIES.
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cindeem jarrodmillman whitergh rsblume kbegany cgallen stefanv cgratton imclab jennychang3 jrcohen02 jbpoline espool daniellafurman adamrybinski kaihwang olliepeng adameich nagyistge locuscaeruleus ericpalakovichcarr shitou333111 satra jhlegarreta daniel-ge spaccedementia dragon-dane hao199509brainx's Issues
Is this error due to the use of a newer networkx version ?
Hi Guys,
Installed Brainx on my UCI setup. We are running canopy. I have networkx 1.8.1-2 installed in my session. I get the error below. I think this is networkx version issue.
mod.simulated_annealing(pfc_graph). Is this correct? What version should I be using? Currently trying to get nx 1.6 installed
ValueError Traceback (most recent call last)
in ()
----> 1 mod.simulated_annealing(pfc_graph)
/home/rblumenf/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/brainx-0.1.dev-py2.7.egg/brainx/modularity.pyc in simulated_annealing(g, p0, temperature, temp_scaling, tmin, bad_accept_mod_ratio_max, bad_accept_nod_ratio_max, accept_mod_ratio_min, accept_nod_ratio_min, extra_info, debug)
1063 # make a graph partition object
1064 if p0 is None:
-> 1065 graph_partition = GraphPartition(g,part)
1066 else:
1067 graph_partition = p0
/home/rblumenf/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/brainx-0.1.dev-py2.7.egg/brainx/modularity.pyc in init(self, graph, index)
79
80 # Now, build the edge information used in modularity computations
---> 81 self.mod_e, self.mod_a = self._edge_info()
82
83
/home/rblumenf/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/brainx-0.1.dev-py2.7.egg/brainx/modularity.pyc in _edge_info(self, mod_e, mod_a, index)
113 #looks like a set when we read it in ipython
114 mat_within = mat[modnodes,:][:,modnodes]
--> 115 mat_between = mat[modnodes,:][:,btwnnodes]
116 perc_within = mat_within.sum() * norm_factor
117 perc_btwn = mat_between.sum() * norm_factor
/home/rblumenf/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/numpy/matrixlib/defmatrix.pyc in getitem(self, index)
314
315 try:
--> 316 out = N.ndarray.getitem(self, index)
317 finally:
318 self._getitem = False
ValueError: invalid literal for long() with base 10: '24d
simulated annealing directed graph?
Hi team,
I accidentally passed a digraph to mod.simulated_annealing(). The algo is currently churning away without throwing up an warning or error. Is this desirable?
Fix adjust_partition
Adjust partition is to be used with Newman Spectral partitioning, It is currently broken and has invalid tests. Update to allow for optomizing spectral partition, and look into new method (First principles mutiway spectral partitioning of graphs" that we plan to review. http://arxiv.org/abs/1209.5969) for same purpose
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