braindecode.datautil.filterbank

braindecode.datautil.filterbank(raw, frequency_bands, drop_original_signals=True, **mne_filter_kwargs)

Applies multiple bandpass filters to the signals in raw. The raw will be modified in-place and number of channels in raw will be updated to len(frequency_bands) * len(raw.ch_names) (-len(raw.ch_names) if drop_original_signals).

Parameters
raw: Instance of mne.io.Raw

The raw signals to be filtered

frequency_bands: list(tuple)

The frequency bands to be filtered for (e.g. [(4, 8), (8, 13)])

drop_original_signals: bool

Whether to drop the original unfiltered signals

mne_filter_kwargs: dict

Keyworkd arguments for filtering supported by mne.io.Raw.filter(). Please refer to mne for a detailed explanation.