Visualization#

Note

Visualization helpers require the optional viz dependency: pip install "mne-denoise[viz]".

All names below are available from the public mne_denoise.viz facade.

ASR diagnostics#

`plot_asr_repair_timeline`	Plot the per-window count of reconstructed components over time.
`plot_asr_calibration_fraction`	Bar chart of the clean calibration fraction for one or more estimators.
`plot_asr_component_reconstruction`	Heatmap of per-window component variance relative to rejection thresholds.
`plot_guided_asr_weights`	Plot experimental GuidedASR soft weights by window and component.

`plot_component_summary`	Plot a compact per-component summary dashboard.
`plot_component_patterns`	Plot spatial component patterns.
`plot_component_score_curve`	Plot a 1D component score curve for a fitted estimator.
`plot_component_epochs_image`	Plot component activity as an epoch-by-time image.
`plot_component_time_series`	Plot stacked component time series with fixed vertical offsets.
`plot_component_spectrogram`	Plot a time-frequency power view for one component.
`plot_window_score_traces`	Plot per-window score traces from a 2D score matrix.

`plot_channel_time_course_comparison`	Plot before/after channel time courses for explicit channel picks.
`plot_evoked_gfp_comparison`	Plot GFP comparison for before/after signals.
`plot_power_ratio_map`	Plot a topomap of preserved power ratio after denoising.
`plot_signal_overlay`	Overlay one before/after trace to inspect reconstruction quality.
`plot_grand_average_evokeds`	Plot group-mean evoked responses with optional SEM bands.

`plot_narrowband_score_scan`	Plot score/eigenvalue profiles from a narrowband scan.
`plot_time_frequency_mask`	Visualize a time-frequency mask matrix.
`plot_psd_gallery`	Plot full-spectrum and zoomed PSD panels across multiple series.
`plot_psd_comparison`	Plot PSD comparison for original and denoised data.
`plot_psd_overlay`	Plot full-spectrum and focused PSD overlays across multiple series.
`plot_psd_zoom_comparison`	Plot a PSD comparison plus zoomed panels around selected frequencies.
`plot_spectrogram_comparison`	Compare before/after spectrograms averaged across selected channels.
`plot_component_psd_comparison`	Plot input PSD next to PSDs of selected components.

`plot_metric_bars`	Plot grouped bar charts for one or more scalar metrics.
`plot_tradeoff_scatter`	Plot a grouped x/y trade-off scatter with optional group means.
`plot_metric_comparison`	Plot one metric as grouped bars or paired subject trajectories.
`plot_harmonic_attenuation`	Plot grouped per-harmonic attenuation bars for line-noise studies.
`plot_metric_slopes`	Plot subject-level paired trajectories for one or more metrics.
`plot_metric_violins`	Plot violin + strip distributions with optional paired subject lines.
`plot_null_distribution`	Plot a null-distribution histogram with observed statistic and CI.
`plot_forest`	Plot per-subject point estimates with confidence intervals.
`plot_window_count_series`	Plot a per-window count or metric series.

`plot_denoising_summary`	Plot a generic denoising diagnostics dashboard.
`plot_component_cleaning_summary`	Plot a generic component-cleaning dashboard.
`plot_signal_diagnostics_summary`	Plot grouped time-domain signal diagnostics.
`plot_condition_interaction_summary`	Plot condition-by-group interaction traces.
`plot_group_condition_interaction_summary`	Plot group-wise condition interaction traces.
`plot_endpoint_metrics_summary`	Plot a generic endpoint-metric storyboard.
`plot_metric_tradeoff_summary`	Plot a two-panel metric trade-off summary.

Selection controller returned by plot_component_selector().

Plot an interactive component selector for DSS or standard ZapLine.

`get_color`	Return a color from the shared viz palettes by key.
`get_series_color`	Return a color from the shared spectral series palette.
`style_axes`	Apply per-axes theme overrides.
`themed_figure`	Create a figure + axes with the package plotting defaults.
`themed_legend`	Add a clean, minimal legend.
`get_theme_rc`	Return the theme rcParams, optionally merged with overrides.
`use_theme`	Context manager that temporarily applies the mne-denoise theme.
`set_theme`	Apply the mne-denoise plotting theme to matplotlib rcParams.