mne.viz.plot_ica_scores#

mne.viz.plot_ica_scores(ica, scores, exclude=None, labels=None, axhline=None, title='ICA component scores', figsize=None, n_cols=None, show=True)[source]#

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.

Parameters:

icainstance of mne.preprocessing.ICA

The ICA object.

scoresarray-like of float, shape (n_ica_components,) | list of array

Scores based on arbitrary metric to characterize ICA components.

excludearray-like of int

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

labelsstr | 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.

axhlinefloat

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

titlestr

The figure title.

figsizetuple of int | None

The figure size. If None it gets set automatically.

n_colsint | None

Scores are plotted in a grid. This parameter controls how many to plot side by side before starting a new row. By default, a number will be chosen to make the grid as square as possible.

showbool

Show figure if True.

Returns:

figinstance of Figure

The figure object.