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%matplotlib inline
In this example, MEG data are remapped from one channel type to another. This is useful to:
- visualize combined magnetometers and gradiometers as magnetometers
or gradiometers.
- run statistics from both magnetometers and gradiometers while
working with a single type of channels.
In [ ]:
# Author: Mainak Jas <mainak.jas@telecom-paristech.fr>
# License: BSD (3-clause)
import mne
from mne.datasets import sample
print(__doc__)
# read the evoked
data_path = sample.data_path()
fname = data_path + '/MEG/sample/sample_audvis-ave.fif'
evoked = mne.read_evokeds(fname, condition='Left Auditory', baseline=(None, 0))
# go from grad + mag to mag
virt_evoked = evoked.as_type('mag')
evoked.plot_topomap(ch_type='mag', title='mag (original)', time_unit='s')
virt_evoked.plot_topomap(ch_type='mag', time_unit='s',
title='mag (interpolated from mag + grad)')
# go from grad + mag to grad
virt_evoked = evoked.as_type('grad')
evoked.plot_topomap(ch_type='grad', title='grad (original)', time_unit='s')
virt_evoked.plot_topomap(ch_type='grad', time_unit='s',
title='grad (interpolated from mag + grad)')