mne_denoise.viz.plot_component_cleaning_summary#

mne_denoise.viz.plot_component_cleaning_summary(scores=None, selected_count=0, patterns=None, info=None, channel_names=None, removed=None, sources=None, sfreq=None, freqs=None, psd_before=None, psd_after=None, line_freq=None, fmax=100.0, segment_info=None, summary_rows=None, title='Component Cleaning Summary', figsize=None, dpi=200, show=True, fname=None)[source]#

Plot a generic component-cleaning dashboard.

Parameters:

  • scores (array-like | None) – Component score vector.

  • selected_count (int) – Number of selected/removed components.

  • patterns (array-like | None) – Component patterns with shape (n_channels, n_components).

  • info (mne.Info | None) – Optional MNE info for topomap rendering.

  • channel_names (sequence of str | None) – Channel labels used by non-topomap fallback panels.

  • removed (array-like | None) – Removed signal with shape (n_channels, n_times) or (n_epochs, n_channels, n_times).

  • sources (array-like | None) – Component source traces with shape (n_components, n_times) or (n_epochs, n_components, n_times).

  • sfreq (float | None) – Sampling frequency for source/segment time axes.

  • freqs (array-like | None) – Frequency axis for PSD panel.

  • psd_before (array-like | None) – PSD values for before/after comparison.

  • psd_after (array-like | None) – PSD values for before/after comparison.

  • line_freq (float | None) – Optional line frequency marker in PSD panel.

  • fmax (float) – Upper frequency bound for PSD panel.

  • segment_info (list[dict] | None) – Optional segmented metadata. If provided, segmented panels replace score/removed/source panels.

  • summary_rows (list[tuple[str, object]] | None) – Optional explicit table rows.

  • title (str) – Figure title.

  • figsize (tuple[float, float] | None) – Figure size.

  • dpi (int) – Figure resolution.

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

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

Returns:

fig – Figure handle.

Return type:

matplotlib.figure.Figure

Raises:

ValueError – If panel inputs are incompatible with expected dimensions or metadata requirements (for example invalid source/pattern/segment shapes).

Notes

This function is a thin composer around internal panel painters in mne_denoise.viz._summary_panels. It does not run fitting or denoising; all inputs are expected to be precomputed by the caller.

Examples

>>> import numpy as np
>>> from mne_denoise.viz import plot_component_cleaning_summary
>>> rng = np.random.default_rng(0)
>>> freqs = np.linspace(0, 80, 161)
>>> fig = plot_component_cleaning_summary(
...     scores=np.array([2.0, 1.2, 0.7]),
...     selected_count=1,
...     patterns=rng.standard_normal((5, 3)),
...     removed=rng.standard_normal((5, 200)),
...     sources=rng.standard_normal((3, 200)),
...     sfreq=200.0,
...     freqs=freqs,
...     psd_before=rng.random((5, freqs.size)),
...     psd_after=rng.random((5, freqs.size)),
...     show=False,
... )