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This is the Modular EEg Toolkit (MEET) for Python 2.

************************************************************************
***Disclosure:                                                       ***
***-----------                                                       ***
***This software comes as it is - there might be errors at runtime   ***
***and results might be wrong although the code was tested and did   ***
***work as expected. Since resuluts might be wrong you must          ***
***absolutely not use this software for a medical purpuse - decisions***
***converning diagnosis, treatment or prophylaxis of any medical     ***
***condition mustn't rely on this software.                          ***
************************************************************************

Only Python 2 is supported at the moment, however modifications should
be easy to do.

Dependencies:
-------------
-Python 2
-Numpy
-Scipy
-Matplotlib

Installation:
-------------
Using the usual procedure:

python setup.py build
python setup.py install (be sure that the python executable is Python 2)

Uninstallation:
---------------
if you use pip you can uninstall doing:

pip uninstall meet

Version Compatibility:
----------------------
I try to avoid incompatibilities when updating functions,
this however cannot be totaly avoided from time to time. However
functions are thoroughly tested.

Citation:
---------
If you use this software for scientific publications please give proper
citations.

Please cite any (or all):
Waterstraat G, Burghoff M, Fedele T, Nikulin V, Scheer HJ, Curio G.
Non-invasive single-trial EEG detection of evoked human neocortical population spikes.
Neuroimage. 2015 Jan 15;105:13-20. doi: 10.1016/j.neuroimage.2014.10.024. Epub 2014 Oct 18.

Waterstraat G, Fedele T, Burghoff M, Scheer HJ, Curio G.
Recording human cortical population spikes non-invasively - An EEG tutorial.
J Neurosci Methods. 2015 Jul 30;250:74-84. doi: 10.1016/j.jneumeth.2014.08.013. Epub 2014 Aug 27.

Waterstraat G, Curio G, Nikulin VV.
On optimal spatial filtering for the detection of phase coupling in multivariate neural recordings.
Neuroimage. 2017 Jun 13;157:331-340. doi: 10.1016/j.neuroimage.2017.06.025.

https://github.com/neurophysics/meet. Retrieved on <date>

License:
--------
Copyright (c) 2017 Gunnar Waterstraat

Permission is hereby granted, free of charge, to any person obtaining a
copy of this software and associated documentation files (the
"Software"), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publish,
distribute, sublicense, and/or sell copies of the Software, and to
permit persons to whom the Software is furnished to do so, subject to
the following conditions:

The above copyright notice and this permission notice shall be included
in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Author & Contact
----------------
Written by Gunnar Waterstraat
email: gunnar[dot]waterstraat[at]charite.de

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