mne.viz.plot_ica_scores(ica, scores, exclude=None, labels=None, axhline=None, title='ICA component scores', figsize=(12, 6), show=True)

Plot scores related to detected components.

Use this function to asses how well your score describes outlier sources and how well you were detecting them.


ica : instance of mne.preprocessing.ICA

The ICA object.

scores : array_like of float, shape (n ica components) | list of arrays

Scores based on arbitrary metric to characterize ICA components.

exclude : array_like of int

The components marked for exclusion. If None (default), ICA.exclude will be used.

labels : str | list | ‘ecg’ | ‘eog’ | None

The labels to consider for the axes tests. Defaults to None. If list, should match the outer shape of scores. If ‘ecg’ or ‘eog’, the labels_ attributes will be looked up. Note that ‘/’ is used internally for sublabels specifying ECG and EOG channels.

axhline : float

Draw horizontal line to e.g. visualize rejection threshold.

title : str

The figure title.

figsize : tuple of int

The figure size. Defaults to (12, 6).

show : bool

Show figure if True.


fig : instance of matplotlib.pyplot.Figure

The figure object