Plotting

Publication plots under cf.pl. Tissue coordinates use embedding(..., basis="spatial"); there is no separate spatial plotting module.

Marsilea-based dotplot / grid_dotplot need pip install cellfish[plot].

Style and fonts

plot.setup_style(*[, font, dpi, font_dir, ...])	Load fonts if present and set publication rcParams (PDF fonttype 42).
plot.savefig(fig, path, *[, dpi, also_png])	Save fig; if path is PDF/SVG, also write a PNG sidecar unless disabled.
plot.font_signature(ttf_path)	Return (family, subfamily, weight, is_italic) for a TTF file.
plot.validate_and_load_fonts(font_list[, ...])	Validate and load custom fonts from font_dir.
plot.export_mplstyle([filename])	Write current matplotlib rcParams that differ from defaults.

Palettes

Project-specific colors stay in the analysis repo. Pass them with palette= or group_color_dict=.

plot.get_palette(name)	Get a predefined color palette by name.
plot.create_palette_from_types(cell_types[, ...])	Create a color mapping for a list of cell types.
plot.order_labels([observed, order])	Return order first, then any extra observed labels.
plot.reorder_and_set_palettes(adata, group)	Reorder a group column in adata.obs and set its corresponding palette.
plot.show_color(color_input[, title, n_colors])	Intelligently visualizes a color input.
plot.show_palette(palette[, title, labels])	Display a palette with optional labels.
plot.list_available_palettes()	List all available predefined palettes dynamically.

Embedding

plot.embedding(adata, basis, *[, color, ...])	Scatter plot for user specified embedding basis (e.g. umap, pca, etc).
plot.embedding_numbered(adata, basis, *[, ...])	A derived version of embedding() that: - writes numeric indices (1..N) on the embedding (at per-group centroids), - and shows a right-side legend with "<idx>  <group>" labels.
plot.umap(adata, **kwargs)	Plot UMAP embedding.
plot.tsne(adata, **kwargs)	Plot t-SNE embedding.
plot.pca(adata, **kwargs)	Plot PCA embedding.
plot.mde(adata, **kwargs)	Plot MDE embedding.
plot.embedding_celltype(adata[, figsize, ...])	Plot embedding with celltype color by omicverse.
plot.embedding_adjust(adata, groupby[, ...])	Get locations of cluster median and adjust text labels accordingly.
plot.embedding_density(adata, basis, ...)
plot.ConvexHull(adata, basis, cluster_key, ...)	Plot the ConvexHull for a cluster in embedding.
plot.add_arrow(ax, adata, basis[, fontsize, ...])	Add arrow and label to the axis :type ax: matplotlib.axes.Axes :param ax: The axis to add the arrow and label to.

Composition

plot.get_cluster_proportions(adata[, ...])	Return percent composition (0–100) with samples as index and clusters as columns.
plot.plot_cluster_proportions(cluster_props)	Stacked bar chart of get_cluster_proportions output.
plot.cellproportion(adata, ...[, ...])	Plot cell proportion of each cell type in each visual cluster.
plot.cellstackarea(adata, celltype_clusters, ...)	Plot the cell type percentage in each groupby category
plot.cell_alluvial(adata, celltype_clusters, ...)	Temporal / grouped composition plot with smooth alluvial ribbons.

Categorical / statistical plots

plot.bardotplot(adata, groupby, color[, ...])
plot.single_group_boxplot(adata[, groupby, ...])	adata (AnnData object): The data object containing the information for plotting.
plot.plot_boxplots(data, feature_name[, ...])	Grouped boxplot visualization.
plot.violin_box(adata, keys, groupby[, ax, ...])
plot.violin_old(adata[, keys, groupby, ax, ...])
plot.dotplot_doublegroup(adata, gene, ...[, ...])
plot.ridgeplot(adata, metric[, groupby, ...])	Ridge / overlapping KDE of adata.obs[metric] grouped by groupby.

Contours and obs scatter

plot.add_contour(ax, adata, groupby, clusters)	Add density contour to plot.
plot.contour(ax, adata, groupby, clusters[, ...])	Add density contour to plot.
plot.plot_scatter(adata, x, y, hue, cmap[, ...])	Scatter plot from AnnData.obs with optional cluster highlighting.
plot.obs_scatter(adata, x, y, hue, cmap[, ...])	Scatter plot from AnnData.obs with optional cluster highlighting.

plot1cell

plot.plot1cell(adata, clusters[, basis, ...])	Circular UMAP with metadata tracks.
plot.plot1cell_atlas_meta_rings(adata, *[, ...])	Draw an atlas-style plot1cell figure with original plot1cell-like inner metadata rings.
plot.simulate_atlas_anndata([n_cells, ...])	Generate a simulated atlas-like AnnData object for testing the plotting function.

Dotplots (marsilea)

These attributes are loaded lazily. Install cellfish[plot] first.

plot.dotplot(adata, var_names, groupby, *[, ...])	Make a dot plot of the expression values of var_names.
plot.grid_dotplot(adata, var_names, groupby, *)	Grouped dotplot with Marsilea, supporting 2D category splits and colored labels.
plot.CircleLabels(labels[, split_groups, ...])	Draw colored dots with text labels beside them (Marsilea RenderPlan).
plot.rank_genes_groups_dotplot(adata[, ...])	Create a dot plot from rank_genes_groups results.