The Virtual Brain Project

Source code for tvb.datatypes.sensors_bst_to_tvb

# -*- coding: utf-8 -*-
#
#  TheVirtualBrain-Scientific Package. This package holds all simulators, and
# analysers necessary to run brain-simulations. You can use it stand alone or
# in conjunction with TheVirtualBrain-Framework Package. See content of the
# documentation-folder for more details. See also http://www.thevirtualbrain.org
#
# (c) 2012-2017, Baycrest Centre for Geriatric Care ("Baycrest") and others
#
# This program is free software: you can redistribute it and/or modify it under the
# terms of the GNU General Public License as published by the Free Software Foundation,
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# program.  If not, see <http://www.gnu.org/licenses/>.
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#
#   CITATION:
# When using The Virtual Brain for scientific publications, please cite it as follows:
#
#   Paula Sanz Leon, Stuart A. Knock, M. Marmaduke Woodman, Lia Domide,
#   Jochen Mersmann, Anthony R. McIntosh, Viktor Jirsa (2013)
#       The Virtual Brain: a simulator of primate brain network dynamics.
#   Frontiers in Neuroinformatics (7:10. doi: 10.3389/fninf.2013.00010)
#
#

"""
Small script for converting Brainstorm sensor files for our default dataset
to the simple ASCII format used by TVB (and other software).

NB: Brainstorm uses meters, TVB uses millimeters.

.. moduleauthor:: Marmaduke Woodman <marmaduke.woodman@univ-amu.fr>

"""

import numpy
import scipy.io


[docs]def get_field_array(mat_group, n=3, dtype=numpy.float64): return numpy.array([ l.flat[:n] if l.size else numpy.zeros((n, ), dtype) for l in mat_group[0] ], dtype=dtype)
[docs]def convert_brainstorm_to_tvb(tvb_data_path, chan_paths): """ Convert given set of channels from Brainstorm to TVB formats. """ bst_path = tvb_data_path + 'brainstorm/data/TVB-Subject/' for sens_type, sens_path in chan_paths.iteritems(): # only MEG channels require orientation information use_ori = sens_type in ('meg', ) # read from MAT file necessary fields mat = scipy.io.loadmat(bst_path + sens_path) name = [l[0] for l in mat['Channel']['Name'][0]] loc = get_field_array(mat['Channel']['Loc']) if use_ori: ori = get_field_array(mat['Channel']['Orient']) # bst uses m, we use mm loc *= 1e3 # write out to text format out_fname = '%s/sensors/%s-brainstorm-%d.txt' out_fname %= tvb_data_path, sens_type, len(name) with open(out_fname, 'w') as fd: if use_ori: # MEG for n, (x, y, z), (ox, oy, oz) in zip(name, loc, ori): line = '\t'.join(['%s']+['%f']*6) + '\n' line %= n, x, y, z, ox, oy, oz fd.write(line) else: # sEEG, EEG for n, (x, y, z) in zip(name, loc): line = '\t'.join(['%s']+['%f']*3) + '\n' line %= n, x, y, z fd.write(line)
if __name__ == '__main__': import tvb_data convert_brainstorm_to_tvb(tvb_data.__path__, chan_paths={ 'eeg': 'EEG_channels/channel.mat', 'meg': 'MEGchannels/channel_4d_acc1.mat', 'seeg': 'seeg_channels/channel.mat', })