meeg_utils.steps.DropChannels

class meeg_utils.steps.DropChannels(ch_names, *, on_missing='raise')

Remove channels, e.g. mastoid electrodes before re-referencing.

Parameters:

• ch_names (list of str) – Channels to remove.

• on_missing ({"raise", "ignore"}) – What to do if a channel is not in the data.

qc_

dropped and missing channels.

Type:

dict

__init__(ch_names, *, on_missing='raise')

Methods

__init__(ch_names, *[, on_missing])
fit(inst[, y, system])	Learn the step's state from the data.
fit_transform(inst[, y, system, copy])	Fit the step on the data and transform the same data.
get_metadata_routing()	Get metadata routing of this object.
get_params([deep])	Get parameters for this estimator.
plot([kind, inst])	Draw quality-control figures.
set_fit_request(*[, inst, system])	Configure whether metadata should be requested to be passed to the fit method.
set_params(**params)	Set the parameters of this estimator.
set_transform_request(*[, copy, inst])	Configure whether metadata should be requested to be passed to the transform method.
transform(inst, *[, copy])	Apply the fitted step to the data.

Attributes

accepts	Data types the step accepts.
adds_annotations	Whether the step may add BAD_ annotations (existing ones are kept).
changes_channels	Whether the step may add, drop or reorder channels.
changes_times	Whether the step may change the time axis (e.g. resampling, cropping).
drops_epochs	Whether the step may drop epochs (e.g. artifact rejection).
plot_kinds	kind -> whether it needs data (inst).
returns	Data type the step returns; None means the same type as its input.
systems	Acquisition systems the step applies to; None means all systems.

accepts: ClassVar[tuple[type, ...]] = (<class 'mne.io.base.BaseRaw'>, <class 'mne.epochs.BaseEpochs'>, <class 'mne.evoked.Evoked'>)

Data types the step accepts.

changes_channels: ClassVar[bool] = True

Whether the step may add, drop or reorder channels.