Hi all,
I'm having trouble following the tutorial for Artifact Correction with ICA.
http://martinos.org/mne/stable/auto_tutorials/plot_artifacts_correction_ica.html?highlight=ica%20fit
I have epoched data where my artifact is timed to the event; I'm not
investigating EOG artifact. I am able to use ica.plot_properties and
ica.plot_sources fine. But when I try to do ica.plot_overlay, it looks
like it's not excluding my bad component. Since artifact is timed to
event, average is just the averaged epochs.
Attached: images from ica.plot_properties, ica.plot_sources, and
ica.plot_overlay. I'm not exactly clear on what picks and exclude expects
(list, array, int?).
Commands used are below.
Thanks very much for any help!
Megan
random_state = 23
n_components =50 # if float, select n_components by explained variance of PCA
method = 'fastica' # for comparison with EEGLAB try "extended-infomax" here
decim = 3 # we need sufficient statistics, not all time points -> saves time
reject=None # artifact is rather large, so don't want to reject it...
ica = ICA(n_components=n_components, method=method, random_state=random_state)
ica.fit(epochs, picks=picks_meg, decim=decim, reject=reject)
ica.plot_sources(epochs)
epoch_avg= epochs.average()
ica.plot_sources(epoch_avg, exclude=['35'])
ica.plot_properties(epochs, picks=35, psd_args={'fmax': 35.},
image_args={'sigma': 1.})
# Following lines included with input and output:
In [72]: ica.plot_overlay(epoch_avg, exclude=['35'], show=False)
Transforming to ICA space (50 components)
/export/research/analysis/human/jstephen/shared/programs/python/anaconda3/lib/python3.5/site-packages/numpy/lib/arraysetops.py:375:
FutureWarning: elementwise comparison failed; returning scalar
instead, but in the future will perform elementwise comparison
mask &= (ar1 != a)
Zeroing out 0 ICA components
Out[72]: <matplotlib.figure.Figure at 0x7f8c469d55c0>
In [74]: mne.__version__
Out[74]: '0.14.dev0'
MEG Technician
The Mind Research Network
1101 Yale Blvd. NE
Albuquerque, New Mexico 87106
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