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Minimum image regression relies on distinction between "accepted" and "ignored" components #1085

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tsalo opened this issue Apr 21, 2024 · 1 comment · May be fixed by #1086
Open

Minimum image regression relies on distinction between "accepted" and "ignored" components #1085

tsalo opened this issue Apr 21, 2024 · 1 comment · May be fixed by #1086
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tsalo commented Apr 21, 2024 •
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Summary

I'm working on refactoring the global signal regression functions in order to better understand them (particularly for #1071), and I noticed that gscontrol.minimum_image_regression specifically uses "accepted" components and not "ignored" components. Since we eliminated the "ignored" classification in #756, MIR likely doesn't work the way it was intended anymore.

We could probably leverage the classification tags, but those vary by decision tree and are essentially up to the user.
@tsalo tsalo added bug issues describing a bug or error found in the project discussion issues that still need to be discussed labels Apr 21, 2024
@tsalo tsalo linked a pull request Apr 21, 2024 that will close this issue
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tsalo commented Apr 29, 2024

Ah, I see that "low variance" and "accept borderline" only exist as classification tags in the meica and tedana_orig trees.

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Refactor gscontrol module tsalo/tedana
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