mne_denoise.viz.plot_component_epochs_image#

mne_denoise.viz.plot_component_epochs_image(estimator, data=None, n_components=None, show=True, fname=None)[source]#

Plot component activity as an epoch-by-time image.

Parameters:

  • estimator (object) – Fitted estimator exposing component sources via cache or transform.

  • data (mne.io.BaseRaw | mne.BaseEpochs | ndarray | None) – Input data used to compute sources when they are not cached.

  • n_components (int | sequence of int | None) – Components to plot. If None, plot up to five components.

  • show (bool, default=True) – If True, show the figure.

  • fname (path-like | None) – Optional output path used to save the figure.

Returns:

fig – Figure handle.

Return type:

matplotlib.figure.Figure

Raises:

ValueError – If sources are not 2D/3D, or if no components are selected.

Notes

Input source shapes are interpreted as:

  • (n_components, n_times) for a single average/time series.

  • (n_components, n_times, n_epochs) for epoched sources.

Examples

>>> from mne_denoise.viz import plot_component_epochs_image
>>> fig = plot_component_epochs_image(
...     estimator, data=epochs, n_components=[0, 1], show=False
... )