squidpy.pl.ripley

squidpy.pl.ripley(adata, cluster_key, mode='F', plot_sims=True, palette=None, figsize=None, dpi=None, save=None, ax=None, legend_kwargs=mappingproxy({}), **kwargs)

Plot Ripley’s statistics for each cluster.

The estimate is computed by squidpy.gr.ripley().

Parameters:

• adata (AnnData) – Annotated data object.

• cluster_key (str) – Key in anndata.AnnData.obs where clustering is stored.

• mode (Literal['F', 'G', 'L']) – Ripley’s statistics to be plotted.

• plot_sims (bool) – Whether to overlay simulations in the plot.

• palette (str | ListedColormap | None) – Categorical colormap for the clusters. If None, use anndata.AnnData.uns ['{cluster_key}_colors'], if available.

• figsize (tuple[float, float] | None) – Size of the figure in inches.

• dpi (int | None) – Dots per inch.

• save (str | Path | None) – Whether to save the plot.

• scalebar_kwargs – Keyword arguments for matplotlib_scalebar.ScaleBar.

• edges_kwargs – Keyword arguments for networkx.drawing.nx_pylab.draw_networkx_edges().

• kwargs (Any) – Keyword arguments for matplotlib.pyplot.scatter() or matplotlib.pyplot.imshow().

• ax (Axes | None) – Axes, matplotlib.axes.Axes.

• legend_kwargs (Mapping[str, Any]) – Keyword arguments for matplotlib.pyplot.legend().

• kwargs – Keyword arguments for seaborn.lineplot().

Return type:

None

Returns:

Nothing, just plots the figure and optionally saves the plot.