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Sparse and structured methods for supervised and unsupervised learning on large neuroimaging data

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Neuroparser

Setup.py Installation

The usual

python setup.py install

should do the trick if you have the dependencies installed.

SCONS Installation

If you have scons installed, simply type

scons

in the top directory (neuroparser).

Warning!

This code is currently in an early state of development for public use, and will undergo many changes in the coming months. Use it at your own risk! It will likely be good to download the latest code with some frequency and rebuild by for example using

scons -c 

to clear away old files, and then

scons

to rebuild them.

Usage

Some basic examples of how the code can be called are in:

/neuroparser/examples/graphnet_example.py

and some more use cases can be found in:

/neuroparser/optimization/cwpath/tests/profile.py /neuroparser/optimization/cwpath/tests/test_graphnet.py

Please report bugs or feature requests to [email protected] or better using GitHub.

Logan Grosenick
Kiefer Katovich
Brad Klingenberg
Jonathan Taylor

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Sparse and structured methods for supervised and unsupervised learning on large neuroimaging data

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