Feat/interpolate channels #480
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fix event list in tests
moabb/datasets/preprocessing.py
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| # Trick: mark these channels as bad | ||
| raw.info["bads"].extend(missing_channels) | ||
| # ...and use mne bad channel interpolation to generate the value of the missing channels | ||
| raw.interpolate_bads(origin=(0, 0, 0.04)) |
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Hi @gcattan , I really like your idea about channel interpolation to match electrodes of two datasets.
Is there a reason why in interpolate_bads you have selected origin (0, 0, 0.04) ? Option "auto" will fit a sphere to headshape based on the existing electrodes and determine its radius and origin.
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Hi! I am not sure it will work if the montage is disabled. But let me try.
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@Sara04 I added a try-catch, so we first try with the 'auto' parameter, and default to (0, 0, 0.04) in case of ValueError. This happens, for example, when there is no montage information. The braindecode pipeline fails, but I don't think the issue originates from this PR.
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Thanks @gcattan ! Yes, it doesn't seem that it fails due to this PR.
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Sure. Is it ok to merge this PR then?
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For me it is OK. @sylvchev , @bruAristimunha do you have some other comments?
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@bruAristimunha @Sara04 |
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Done :) |
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This PR modifies the
match_allmethod inside base paradigm, which set-up the paradigm to be compatible with a list of datasets.It is now possible to select the intersection of the channels in all datasets, or their union.
For example, if you pass two datasets:
d1 -> Cz, Fz
d2 -> Cz, C4,
then the
channelsattribute inside the paradigm can contain either: Cz or {Cz, Fz, C4}.In the case you selected the union of all channels, then missing channels in dataset d1 or d2 will be interpolated using mne.
This interpolation is done directly in the
RawToEpochstransformer.@bruAristimunha FYI