mne_denoise.viz.plot_denoising_summary#

mne_denoise.viz.plot_denoising_summary(inst_before, inst_after, *, info, times, title='Denoising Summary', show=True, fname=None)[source]#

Plot a generic denoising diagnostics dashboard.

Parameters:

  • inst_before (MNE object | ndarray) – Signals before and after denoising. Supported array shapes are (n_channels, n_times) and (n_epochs, n_channels, n_times). MNE Raw/Epochs/Evoked inputs are also accepted.

  • inst_after (MNE object | ndarray) – Signals before and after denoising. Supported array shapes are (n_channels, n_times) and (n_epochs, n_channels, n_times). MNE Raw/Epochs/Evoked inputs are also accepted.

  • info (mne.Info) – Channel info used for the power-ratio map panel.

  • times (array-like of shape (n_times,)) – Explicit time axis for GFP traces.

  • title (str) – Figure title.

  • show (bool) – Whether to display the figure.

  • fname (path-like | None) – Optional output path.

Returns:

fig – Figure handle.

Return type:

matplotlib.figure.Figure

Raises:

ValueError – If times is not 1D or does not match the GFP length.

Notes

The figure is composed of three panels: 1. Per-channel power ratio map (before/after). 2. PSD comparison (before/after). 3. GFP overlay with difference shading.

Examples

>>> from mne_denoise.viz import plot_denoising_summary
>>> fig = plot_denoising_summary(
...     before,
...     after,
...     info=info,
...     times=times,
...     show=False,
... )