Comments (3)
sappelhoff
commented on May 23, 2024
We should be able to see the result of each criteria in the prepPipeline object
I absolutely agree 👍 PREP should be transparent at every step.
Your proposed implementation seems like a quick fix, however I think that we can get the code a bit cleaner by doing a more full refactoring, like @adam2392 said he might have some time for in one or two weeks.
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yjmantilla
commented on May 23, 2024
@sappelhoff Although this is a quick fix, could we implement this to make the pyprep validation against matlab easier (at least comparing the bad channels detected).
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sappelhoff
commented on May 23, 2024
agreed @yjmantilla if it helps debugging/inspecting pyprep we should implement that now ... and refactor later, once the critical issues are solved. PR is welcome!
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Related Issues (20)
- Strange PyPrep/Ransac outputs HOT 1
- Release 0.4 HOT 4
- Adding flake8 to pre-commit-config
- Use the MNE logger to set the verbosity HOT 6
- Make pyprep load MNE raw data for object, if not already loaded HOT 3
- filt vs filtfilt (MATLAB implementation)
- Add a "reject_by_annotation" parameter for finding bad channels HOT 1
- pyprep.utils._filter_design throws error for large sampling rates HOT 4
- Passing a custom montage to the PrepPipeline(raw, montage=?)? HOT 5
- Saving prep.raw give error " ValueError: Measurement infos are inconsistent for dig" HOT 4
- List of channel names causes TypeError in find_bad_by_ransac HOT 2
- migrate from `.zenodo.json` to `CITATION.cff` HOT 1
- update issue/pr templates HOT 1
- Computation of window size based on cutoff frequency in local detrend method HOT 1
- Question: using pyprep.NoisyChannels on numpy arrays HOT 1
- Issue with RawBrainVision HOT 2
- find_all_bads throws inf/nan error after filtering/detrending? HOT 12
- Documentation for Noisy Channels Algorithms' stand-alone use HOT 1
- [Feature suggestion] Allow for relevant annotation selection during processing.
- Real-world benchmarking for (Py)PREP
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