Haven't really dug into it much yet, but I've verified that adaptive line noise removal (a.k.a. CleanLine) differs somehow between PyPREP and Matlab PREP.
This is sort of a weird one, where the MNE notch filter that PyPREP uses seems to be very aggressive and distorts the waveband, whereas the MatPREP version doesn't seem to do much of anything (there's a very subtle difference around the 50Hz and 100Hz bands if you a/b the images). I should probably try different test files though, since average-referencing seems to handle 99% of the line noise distortions in the PSD for this data (is this a feature of CMS/DRL I didn't know about?)
Pre-cleanline data:
Post-CleanLine data (MatPREP):
Post-CleanLine data (PyPREP):
Anyway, I think this the final component I hadn't formally tested yet for #58!
Haven't really dug into it much yet, but I've verified that adaptive line noise removal (a.k.a. CleanLine) differs somehow between PyPREP and Matlab PREP.
This is sort of a weird one, where the MNE notch filter that PyPREP uses seems to be very aggressive and distorts the waveband, whereas the MatPREP version doesn't seem to do much of anything (there's a very subtle difference around the 50Hz and 100Hz bands if you a/b the images). I should probably try different test files though, since average-referencing seems to handle 99% of the line noise distortions in the PSD for this data (is this a feature of CMS/DRL I didn't know about?)
Pre-cleanline data:
Post-CleanLine data (MatPREP):
Post-CleanLine data (PyPREP):
Anyway, I think this the final component I hadn't formally tested yet for #58!