mne_denoise.viz.plot_signal_overlay#

mne_denoise.viz.plot_signal_overlay(inst_before, inst_after, times, pick=None, start=None, stop=None, scale_after=True, before_label='Before', after_label='After', x_label='Time', y_label='Amplitude', title=None, show=True, fname=None)[source]#

Overlay one before/after trace to inspect reconstruction quality.

Parameters:

  • inst_before (MNE object | ndarray) – Inputs to compare. Accepted array signal shapes are (n_times,), (n_channels, n_times), and (n_epochs, n_channels, n_times).

  • inst_after (MNE object | ndarray) – Inputs to compare. Accepted array signal shapes are (n_times,), (n_channels, n_times), and (n_epochs, n_channels, n_times).

  • times (array-like of shape (n_times,)) – Explicit time axis for both traces after length alignment.

  • pick (int | str | None) – Channel to display. Required when input has more than one channel. String picks require MNE channel names.

  • start (float | None) – Optional lower/upper bounds applied on the time axis.

  • stop (float | None) – Optional lower/upper bounds applied on the time axis.

  • scale_after (bool) – If True, scale the after-trace to the before-trace standard deviation.

  • before_label (str) – Legend label for the first input.

  • after_label (str) – Legend label for the second input.

  • x_label (str) – X-axis label.

  • y_label (str) – Y-axis label.

  • title (str | None) – Optional custom title.

  • show (bool) – If True, display 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 input shapes are invalid, multi-channel data is used without pick, or times length is inconsistent.

Notes

If traces have different lengths, both are trimmed to the common prefix before any time-window filtering.

Examples

>>> from mne_denoise.viz import plot_signal_overlay
>>> fig = plot_signal_overlay(
...     before_array,
...     after_array,
...     pick=0,
...     times=np.arange(1000) / 250.0,
...     show=False,
... )