Comments (6)
We're a group of graduate students from Johns Hopkins University. We're working on implementation of the entire PREP pipeline in python. We'd like to add new functionalities to this repo and make PRs here. @adam2392
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I think your first suggestion works well. That way you can work independently of any GitHub rights you may need to move forward.
It'd be great to tag me occasionally when there is new stuff you integrate, ... that way I won't be too overwhelmed once you make a PR from your fork to this repo :-)
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Hi @Nick3151 - that sounds great to me. Who is "we"? How do you want to work on this?
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And maybe we could get pyprep merged into MNE in the future.
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sounds very good, let's continue the discussion in mne-tools/mne-python#7049
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@sappelhoff How do you feel that these folks, @Nick3151 and two others work on a PR into the forked version of this in https://github.com/NeuroDataDesign/pyprep and then we submit a PR here?
Or should we directly try to address the fixes mentioned here and in the discussion in mne-tools/mne-python#7049 with a direct PR in the main repo?
Let us know your thoughts.
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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
- Add to NoisyChannel a bad_by_psd method to tackle low-frequency artefacts HOT 8
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