apply diataxis framework to tutorials by CarinaFo · Pull Request #13584 · mne-tools/mne-python

CarinaFo · 2026-01-10T05:03:13Z

apply diataxis framework to tutorials/inverse/80_brainstorm_phantom_elekta.py

Bumps [davidslusser/actions_python_bandit](https://github.com/davidslusser/actions_python_bandit) from 1.0.0 to 1.0.1. - [Release notes](https://github.com/davidslusser/actions_python_bandit/releases) - [Commits](davidslusser/actions_python_bandit@v1.0.0...v1.0.1) --- updated-dependencies: - dependency-name: davidslusser/actions_python_bandit dependency-type: direct:production update-type: version-update:semver-patch ... Signed-off-by: dependabot[bot] <support@github.com>

…usser/actions_python_bandit-1.0.1 Bump davidslusser/actions_python_bandit from 1.0.0 to 1.0.1

CarinaFo · 2026-01-25T01:41:31Z

tutorials/inverse/80_brainstorm_phantom_elekta.py

 raw.plot(events=events)

+# We can see that the simulated dipoles produce sinusoidal bursts at 20 Hz
+#  (can we really see that in the plot?)


Here I wonder if we can get rid of one of the screenshots of the dipole events and maybe zoom into one event to show the 20Hz burst

Yes that sounds good, you should be able to see it clearly at least in the average, and depending on the dipole amplitude you can sometimes see it in the raw / epoched data

I plotted fewer channels, I think now it's a bit easier to see

CarinaFo · 2026-01-25T01:43:02Z

tutorials/inverse/80_brainstorm_phantom_elekta.py

 cov = mne.compute_covariance(epochs, tmax=bmax)
 mne.viz.plot_evoked_white(epochs["1"].average(), cov)

+# Not sure what we see here TBH


Here we should explain why we plot the whitened data and what the user is expected to see vs. what we actually see in this plot.

Or can we just link to the whitening / covariance tutorials? It is explained there I think

I would add one sentence on whitening plus link to the whitening tutorial for further referenc (this is in line with diataxis)

CarinaFo · 2026-01-25T01:44:00Z

tutorials/inverse/80_brainstorm_phantom_elekta.py

-# Now we can compare to the actual locations, taking the difference in mm:
-
+# Finally, we compare the estimated to the true dipole locations
+# To do this, we calculate the difference by .....


I think we should explain how we compute the difference and why, this seems to be crucial info for a tutorial on comparing estimated vs. true dipoles.

Makes sense to me

CarinaFo · 2026-01-25T01:45:43Z

tutorials/inverse/80_brainstorm_phantom_elekta.py

 ax3.set_ylabel("Amplitude error (nAm)")

+# We can see that the error magnitude depends on the position of the estimate dipole
+# however, the location error is never greater than 5 mm which is good?


again I am not sure if we can interpret the error magnitude (or should). I think it would be very useful for a user to get some guidance on what to do with those results but maybe this goes too far for the current tutorial.

I think we can, we can say something about the potential localization accuracy of MEG. Like if we can get ~2-5mm error localizing these dipoles we can say MEG can localize point sources with that accuracy (given proper coreg etc.), which helps justify claims of "sub-centimeter" accuracy

larsoner

Didn't read through all changes but wanted to give input on questions!

larsoner · 2026-01-26T14:05:08Z

tutorials/inverse/80_brainstorm_phantom_elekta.py

 raw.plot(events=events)

+# We can see that the simulated dipoles produce sinusoidal bursts at 20 Hz
+#  (can we really see that in the plot?)


Yes that sounds good, you should be able to see it clearly at least in the average, and depending on the dipole amplitude you can sometimes see it in the raw / epoched data

larsoner · 2026-01-26T14:05:45Z

tutorials/inverse/80_brainstorm_phantom_elekta.py

 cov = mne.compute_covariance(epochs, tmax=bmax)
 mne.viz.plot_evoked_white(epochs["1"].average(), cov)

+# Not sure what we see here TBH


Or can we just link to the whitening / covariance tutorials? It is explained there I think

larsoner · 2026-01-26T14:06:33Z

tutorials/inverse/80_brainstorm_phantom_elekta.py

-# Now we can compare to the actual locations, taking the difference in mm:
-
+# Finally, we compare the estimated to the true dipole locations
+# To do this, we calculate the difference by .....


Makes sense to me

larsoner · 2026-01-26T14:08:46Z

tutorials/inverse/80_brainstorm_phantom_elekta.py

 ax3.set_ylabel("Amplitude error (nAm)")

+# We can see that the error magnitude depends on the position of the estimate dipole
+# however, the location error is never greater than 5 mm which is good?


I think we can, we can say something about the potential localization accuracy of MEG. Like if we can get ~2-5mm error localizing these dipoles we can say MEG can localize point sources with that accuracy (given proper coreg etc.), which helps justify claims of "sub-centimeter" accuracy

CarinaFo · 2026-02-17T00:31:47Z

Building the docs is still failing due to sphinx formatting error. I tried various blank line options, not sure what the issue is.

dependabot bot and others added 11 commits March 11, 2024 03:30

Merge pull request #4 from CarinaFo/dependabot/github_actions/davidsl…

8aa3e7a

…usser/actions_python_bandit-1.0.1 Bump davidslusser/actions_python_bandit from 1.0.0 to 1.0.1

Merge branch 'mne-tools:main' into main

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Merge branch 'mne-tools:main' into main

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Merge branch 'mne-tools:main' into main

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diataxis

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first draft using diataxis framework

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added changelog

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changelog update

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wrong PR

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deleted changelog with wrong PR

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CarinaFo commented Jan 25, 2026

View reviewed changes

larsoner reviewed Jan 26, 2026

View reviewed changes

CarinaFo added 8 commits February 14, 2026 13:32

Merge branch 'main' into diataxis

efb2765

added explanations

ab6f3c5

formatting for docs

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more formatting

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final formatting

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add blank lines around directives

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add blank line at file end

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fix sphinx error log

e8299e2

CarinaFo marked this pull request as ready for review February 17, 2026 00:31

CarinaFo requested review from agramfort and drammock as code owners February 17, 2026 00:31

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CarinaFo commented Jan 10, 2026

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CarinaFo commented Feb 17, 2026

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