Comments (4)
I think you should be able to copy the eog channels to another object (in example copying the raw object and then dropping all but eog); then add them back to the raw object thats preprocessed with raw.add_channels().
Now there may be problems with the times (ie the array length)? Im not sure, I think there should not be problems. But thats one thing to try, never done it though.
The dropping inside pyprep is indeed done in the constructor of the PrepPipeline class. Incidentally maybe inside prep we should do that to not lose the eog channels when we return the preprocessed object.
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Hi @SebastianSpeer can you post that part of the code where you call pyprep?
Markdown tip:
If you want to format code over multiple lines, you need to use three backticks at the start, and at the end:
like this:
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for code on a single line, you can use single backticks, like you did: hello this is code
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@SebastianSpeer did you make another comment here? Because in my email notifications it seems like you commented something else but here is nowhere to be found.
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@yjmantilla I initially commented something, but then I figured it out myself. Your suggestion worked fine. Thanks!
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Related Issues (20)
- 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.
- How to include the prep output in my preprocessing pipeline? HOT 1
- New release? HOT 4
- Possible to add an argument in find_bad_by_nan_flat() to change FLAT_THRESHOLD ? HOT 2
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