mne.viz.plot_ica_overlay¶
- mne.viz.plot_ica_overlay(ica, inst, exclude=None, picks=None, start=None, stop=None, title=None, show=True, n_pca_components=None)[source]¶
Overlay of raw and cleaned signals given the unmixing matrix.
This method helps visualizing signal quality and artifact rejection.
- Parameters
- icainstance of
mne.preprocessing.ICA
The ICA object.
- instinstance of
mne.io.Raw
ormne.Evoked
The signals to be compared given the ICA solution. If Raw input, The raw data are displayed before and after cleaning. In a second panel the cross channel average will be displayed. Since dipolar sources will be canceled out this display is sensitive to artifacts. If evoked input, butterfly plots for clean and raw signals will be superimposed.
- excludearray_like of
int
|None
(default) The components marked for exclusion. If None (default), ICA.exclude will be used.
- picks
str
|list
|slice
|None
Channels 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.- start
int
|None
X-axis start index. If None (default) from the beginning.
- stop
int
|None
X-axis stop index. If None (default) to 3.0s.
- title
str
The figure title.
- showbool
Show figure if True.
- n_pca_components
int
|float
|None
The 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.
- icainstance of
- Returns
- figinstance of
Figure
The figure.
- figinstance of