<p><span style="padding: 3px 10px; border-radius: 5px; color: #ffffff; font-weight: bold; display: inline-block; background-color: #ff0000;"> External Email - Use Caution </span></p><p></p><div dir="ltr">The topomaps in the example don't show this problem, at least for plot_topomap:<div><br></div><div><a href="https://mne.tools/dev/auto_examples/preprocessing/plot_eeg_csd.html#sphx-glr-auto-examples-preprocessing-plot-eeg-csd-py">https://mne.tools/dev/auto_examples/preprocessing/plot_eeg_csd.html#sphx-glr-auto-examples-preprocessing-plot-eeg-csd-py</a><br></div><div><br></div><div><div>First, it's worth <a href="https://mne.tools/dev/install/advanced.html#using-the-development-version-of-mne-python-latest-master">trying latest</a> `master` branch rather than 0.20.x to see if we have fixed it already.</div><div><br></div><div></div></div><div>If that doesn't work, can you see if you can reproduce on the `sample` dataset by modifying the example above? If not, there might be something about your data in particular -- if you can turn this into some tiny script (probably <a href="https://gist.github.com/">gist</a>) to demonstrate the problem and share your data someone can take a look.</div><div><br></div><div>Eric</div><div><br></div></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Wed, Jun 24, 2020 at 9:35 AM Gabriel Weindel <<a href="mailto:gabriel.weindel@gmail.com">gabriel.weindel@gmail.com</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"> External Email - Use Caution <br>
<br>
Hello all,<br>
<br>
I am applying CSD to my epoched data and want to compare the <br>
distributions of the ERPs on the scalp before and after surface laplacian.<br>
<br>
epochs_csd = mne.preprocessing.compute_current_source_density(epochs)<br>
<br>
I use : mne.viz.plot_compare_evokeds([epochs.average()], picks='eeg', <br>
axes='topo')<br>
To plot before CSD, everything works fine but then I use :<br>
mne.viz.plot_compare_evokeds([epochs_csd.average()], picks='csd', <br>
axes='topo')<br>
And then the channel order is preserved but the cartoon head is shrinked <br>
to the lower left of the figure (see attached) making it impossible to read.<br>
<br>
I am assuming that the montage is lost in the csd transform as <br>
<a href="http://epoch.info" rel="noreferrer" target="_blank">epoch.info</a> prints me :<br>
<Info | 11 non-empty values<br>
bads: []<br>
ch_names: Fp1, AF7, AF3, F1, F3, F5, F7, FT7, FC5, FC3, FC1, C1, C3, <br>
C5, ...<br>
chs: 64 EEG<br>
custom_ref_applied: True<br>
dig: 712 items (3 Cardinal, 64 EEG, 645 Extra)<br>
file_id: 4 items (dict)<br>
highpass: 0.0 Hz<br>
lowpass: 40.0 Hz<br>
meas_date: 2019-06-06 11:46:59 UTC<br>
meas_id: 4 items (dict)<br>
nchan: 64<br>
projs: []<br>
sfreq: 1000.0 Hz<br>
><br>
<br>
and <a href="http://epochs_csd.info" rel="noreferrer" target="_blank">epochs_csd.info</a> :<br>
<br>
<Info | 11 non-empty values<br>
bads: []<br>
ch_names: Fp1, AF7, AF3, F1, F3, F5, F7, FT7, FC5, FC3, FC1, C1, C3, <br>
C5, ...<br>
chs: 64 CSD<br>
custom_ref_applied: True<br>
dig: 712 items (3 Cardinal, 64 EEG, 645 Extra)<br>
file_id: 4 items (dict)<br>
highpass: 0.0 Hz<br>
lowpass: 40.0 Hz<br>
meas_date: 2019-06-06 11:46:59 UTC<br>
meas_id: 4 items (dict)<br>
nchan: 64<br>
projs: []<br>
sfreq: 1000.0 Hz<br>
><br>
<br>
Is there a quick workaround ?<br>
<br>
Best,<br>
Gabriel<br>
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