eegdash.viz.identity module#

EEGDash data-visualization identity helpers.

The visual identity centres on the Data Rail — a thin EEGDash-blue horizontal line near the top of every figure, with a short EEGDash-orange pulse segment at its left edge. Tutorials call use_eegdash_style() once at the top, then style_figure() per figure to get the rail, title/subtitle/source band, and consistent spines/grids/ticks across every axes.

eegdash.viz.identity.chance_line(ax, level: float, *, label: str = 'chance')[source]

Add a horizontal dashed reference line at level.

eegdash.viz.identity.get_eegdash_palette(n: int) → list[str][source]

Return n colors from the EEGDash data-viz palette.

eegdash.viz.identity.style_figure(fig, *, title: str, subtitle: str = '', source: str = '', data_rail: bool = True, grid_axis: str = 'y') → None[source]

Apply the EEGDash identity to every axes in fig.

Parameters:

  • fig (matplotlib.figure.Figure) – Target figure.

  • title (str) – Short, 1-line figure title (top-left).

  • subtitle (str) – Dataset/task/split context line.

  • source (str) – Provenance footer (italic, bottom-left).

  • data_rail (bool, default True) – Attach the Data Rail.

  • grid_axis ({"y", "x", "both", "none"}) – Grid orientation.

eegdash.viz.identity.use_eegdash_style() → None[source]

Configure matplotlib (and seaborn if installed) for EEGDash plots.