pyprep
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sappelhoff
A Python implementation of the Preprocessing Pipeline (PREP) for EEG data
So, for some context, I was doing an internship in Canada (CoCo lab Udem, Montreal), and in one of the slack channels someone asked for EEG packages to do automatic...
Issue #143 # Merge Checklist - [ ] Respect the `matlab_strict ` flag - [ ] Documentation - [ ] Clearly show how the new option is an improvement (use...
Apparently we need to introduce some fixes for Numpy 2.0 https://github.com/sappelhoff/pyprep/actions/runs/9541812770/job/26295569011#step:9:857
Currently, PREP assumes you have no prior information about which channels are bad. This isn't necessarily a bad design choice if it's philosophically important that all bad channel identification be...
Users can use RANSAC in the way that is described in this example: https://pyprep.readthedocs.io/en/latest/auto_examples/run_ransac.html#sphx-glr-auto-examples-run-ransac-py No need to private two routes to the same goal.
https://pyprep.readthedocs.io/en/latest/generated/pyprep.Reference.html# From my point of view, users should call `pyprep.PrepPipeline(...).fit()`, which then calls the `Reference` class and its methods in the correct order. Please respond here if you think this...
The matprep repository by @a-hurst has been super helpful, but it also (understandably) hasn't received a lot of updates in the past: https://github.com/a-hurst/matprep_artifacts I think for maintainability, we should: 1....
See for example: https://github.com/sappelhoff/pyprep/blob/82390acff4c15a8e8ca92ed92c46f7a50d72e049/pyprep/find_noisy_channels.py#L57 This raises: > NOTE: pick_types() is a legacy function. New code should use inst.pick(...).
We are still using numpy's old random API in many places. It would be good to migrate to the recommended `np.random.default_rng`. This might turn out to be difficult, given our...
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A Python implementation of the Preprocessing Pipeline (PREP) for EEG data