ENH: improve evoked.plot_image with channel layouts
See original GitHub issueEvoked images (heatmap, channels on y axis) are often plotted grouped by hemisphere, e.g.
This is IMO nicer to interpret than the current MNE function. I have homegrown routines, is anyone interested in me trying to integrate them in MNE eventually? API would probably be adding a grouping=
keyword to evoked.plot_image
.
Issue Analytics
- State:
- Created 8 years ago
- Comments:27 (27 by maintainers)
Top Results From Across the Web
mne.Evoked — MNE 1.2.2 documentation - MNE-Python
Set EEG/sEEG/ECoG/DBS/fNIRS channel positions and digitization points. shift_time (tshift[, relative]). Shift time scale in epoched or evoked ...
Read more >Histogram of Gradient Orientations of Signal Plots Applied to ...
It was verified that this method has an improved performance at letter identification than other methods that process the signals on a channel...
Read more >ENH: plot_topo layout creation · Issue #3987 - GitHub
is in any given channel layout, and instead ensure that our internal layouts are actually in head coordinates.
Read more >Image tutorial — Matplotlib 3.6.2 documentation
A short tutorial on plotting images with Matplotlib. Startup commands#. First, let's start IPython. It is a most excellent enhancement to the standard...
Read more >Specifying the channel layout for plotting - FieldTrip toolbox
Sometimes a schematic layout is more convenient, since it “flattens” the head and allows to see all channels better.
Read more >
Top Related Medium Post
No results found
Top Related StackOverflow Question
No results found
Troubleshoot Live Code
Lightrun enables developers to add logs, metrics and snapshots to live code - no restarts or redeploys required.
Start Free
Top Related Reddit Thread
No results found
Top Related Hackernoon Post
No results found
Top Related Tweet
No results found
Top Related Dev.to Post
No results found
Top Related Hashnode Post
No results found
@jona-sassenhagen Looks good!
I often like masking the insignificant (or otherwise uninteresting) values with transparency. I actually have lots of matlab code for this, one example:
The channels are grouped differently here (frontal, central, posterior and each group has channels from left (top) to right (bottom)) - and it would be nice if both ways were possible here (in mne). If you want to take a look at the matlab code it is here and here for example (but it’s messy). BTW masking transparently with colors not from the current colormap is a nightmare in matlab (or maybe just used to be) but a pleasure in matplotlib 😃
I am thinking about doing an example on this later. With the merging of #5010, probably don’t need main code support. Closing.