Comments (6)
It's definitely not suited for MEG data, ICLabel was trained on EEG data.
Could you still post the full traceback of this error, to check if it's due to the selection of EEG channels that yielded nothing or to something else?
Mathieu
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Thank you for your reply. Now I see why my code did not work.
Below is the traceback of this error.
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Perhaps we can have an error message if there are no eeg type channels selected?
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Yes, we should, I just wanted to make sure that the error raised was due to the lack of EEG channels, and it is!
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MRE:
from mne.datasets import sample
from mne.io import read_raw_fif
from mne.preprocessing import ICA
from mne_icalabel import label_components
directory = sample.data_path() / "MEG" / "sample"
raw = read_raw_fif(directory / "sample_audvis_raw.fif", preload=False)
raw.pick_types(meg=True)
raw.load_data()
raw.filter(1., 100.)
ica = ICA(n_components=5, method="picard")
ica.fit(raw)
labels = label_components(raw, ica, method="iclabel")
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Many thanks. I think rasing an error of no EEG channels selected is very helpful~
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Related Issues (20)
- [DOC] Clarify the types of data to be used HOT 2
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- DOC: tables in dark mode are unreadable HOT 1
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