Comments (4)
Also thinking on usability (specifically #16) : when we do the refactor a bit of renaming should be helpful (ie prepPipeline.raw should be renamed so it is associated with the actual processed eeg , not solely 'raw')
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I released 0.3.0
today and did several commits for maintenance, fixing tests, improving docs, etc.
there is a little more automation in place now which will make future maintenance of this package easier
I also added a big disclaimer that this software is in ALPHA phase (use at your own risk) and that we are searching for contributors.
@yjmantilla you should also have a new look at https://github.com/sappelhoff/pyprep#installation and update your development environment --> I configured pre-commit hooks for this project, which will hopefully make the integration with "black" a bit more smooth in the future.
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Ah sorry to hear that it's been a stressfull time for you ... no worries -> I just wanted to keep you up to date.
Now, apart from the the good old rebase, is there anything needed to do new contributions?
nope, just doing pip install -r requirements-dev.txt
again and then pre-commit install
from the project root.
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Awesome! @sappelhoff
Sorry I haven't contributed much from the start of covid. Paradoxically college classes and work have been more stressful so I have not been able to find the time. I already finished 2 courses this week but still got left the hardest ones. I expect to have much more free time in about a month, when I have already got out of the main evaluations. Until then I may contribute a bit but can't really promise anything.
I checked https://github.com/sappelhoff/pyprep#installation and it is really nice to have the automated black commits. Now, apart from the the good old rebase, is there anything needed to do new contributions?
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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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