partipy.plot_bootstrap_3D

partipy.plot_bootstrap_3D#

partipy.plot_bootstrap_3D(adata, dimensions=None, show_contours=True, contours_confidence_level=0.95, contours_alpha=0.3, size=6, alpha=0.5, result_filters=None)#

Interactive 3D visualization of archetypes from bootstrap samples to assess their variability.

Parameters:

  • adata (anndata.AnnData) – Annotated data object containing the archetype bootstrap data in adata.uns["AA_bootstrap"].

  • dimensions (list[int] | None, default None) – Three dimension indices to plot. If None, uses the first three dimensions specified in the AA configuration.

  • show_contours (bool, default True) – Whether to show confidence ellipsoids for each archetype.

  • contours_confidence_level (float, default 0.95) – Confidence level for the ellipsoids (0.0 to 1.0).

  • size (float, default 6) – Size of the points in the scatter plot.

  • alpha (float, default 0.5) – Opacity of the points in the scatter plot (0.0 to 1.0).

  • result_filters (Mapping[str, Any] | None, default None) – Filters applied to ArchetypeConfig entries to select the optimization configuration whose bootstrap runs are visualized. If unspecified, there must be only one configuration stored.

  • contours_alpha (float)

Return type:

Figure

Returns:

go.Figure A 3D scatter plot visualizing the bootstrap results for the archetypes.

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