Overlay of raw and cleaned signals given the unmixing matrix.
This method helps visualizing signal quality and artifact rejection.
mne.preprocessing.ICAThe ICA object.
mne.io.Raw or mne.EvokedThe signal to plot. If Raw, the raw data is displayed before
and after cleaning. In a second panel, the cross-channel average will
be displayed. Since dipolar sources will be canceled out, this
representation is sensitive to artifacts. If Evoked, butterfly
traces for signals before and after cleaning will be superimposed.
int | None (default)The components marked for exclusion. If None (default), ICA.exclude
will be used.
str | list | slice | NoneChannels to include. Slices and lists of integers will be interpreted as
channel indices. In lists, channel type strings (e.g., ['meg',
'eeg']) will pick channels of those types, channel name strings (e.g.,
['MEG0111', 'MEG2623'] will pick the given channels. Can also be the
string values “all” to pick all channels, or “data” to pick data
channels. None (default) will pick all channels that were included during fitting.
float | NoneThe first and last time point (in seconds) of the data to plot. If
inst is a Raw object, start=None and stop=None
will be translated into start=0. and stop=3., respectively. For
Evoked, None refers to the beginning and end of the evoked
signal.
str | NoneThe title of the generated figure. If None (default), no title is
displayed.
Show the figure if True.
int | float | NoneThe number of PCA components to be kept, either absolute (int)
or fraction of the explained variance (float). If None (default),
the ica.n_pca_components from initialization will be used in 0.22;
in 0.23 all components will be used.
New in version 0.22.
FigureThe figure.