simulation_umap#

scdiffeq.plotting._simulation_umap.simulation_umap(adata_sim: AnnData, color: str = 't', use_key: str = 'X_umap', gene_key: str = 'X_gene_inv', gene_ids_key: str = 'gene_ids', ax: Axes | None = None, figsize: tuple = (4, 4), cmap: str | Colormap = 'viridis', categorical_cmap: Dict[str, str] | None = None, s: float = 1.0, alpha: float = 0.8, title: str | None = None, show_colorbar: bool = True, colorbar_label: str | None = None, show_legend: bool = True, legend_loc: str = 'best', save: bool = False, savename: str | None = None, save_format: str = 'svg', dpi: int = 300, **kwargs) → Axes[source]#

Plot UMAP embedding of simulated data, colored by obs attribute or gene expression.

Parameters:

  • adata_sim (AnnData) – Simulated data from sdq.tl.simulate(), with UMAP coordinates in obsm and optionally gene expression in obsm after calling sdq.tl.invert_scaled_gex().

  • color (str, default="t") – What to color points by. Can be: - Column name in adata_sim.obs (e.g., “t”, “fate”, “sim_i”) - Gene name (will look up in gene_ids_key and extract from gene_key)

  • use_key (str, default="X_umap") – Key in adata_sim.obsm containing UMAP coordinates.

  • gene_key (str, default="X_gene_inv") – Key in adata_sim.obsm containing gene expression matrix.

  • gene_ids_key (str, default="gene_ids") – Key in adata_sim.uns containing gene names.

  • ax (plt.Axes, optional) – Matplotlib axes to plot on. If None, creates new figure.

  • figsize (tuple, default=(4, 4)) – Figure size (width, height) in inches if creating new figure.

  • cmap (str or Colormap, default="viridis") – Colormap for continuous values.

  • categorical_cmap (Dict[str, str], optional) – Mapping from category names to colors for categorical data.

  • s (float, default=1.0) – Point size.

  • alpha (float, default=0.8) – Point transparency.

  • title (str, optional) – Plot title. If None, uses the color parameter.

  • show_colorbar (bool, default=True) – Whether to show colorbar for continuous values.

  • colorbar_label (str, optional) – Label for colorbar. If None, uses the color parameter.

  • show_legend (bool, default=True) – Whether to show legend for categorical values.

  • legend_loc (str, default="best") – Legend location.

  • save (bool, default=False) – Whether to save the figure.

  • savename (str, optional) – Filename for saving. If None, auto-generates from color parameter.

  • save_format (str, default="svg") – Format for saving figure.

  • dpi (int, default=300) – Resolution for saving figure.

  • **kwargs – Additional keyword arguments passed to ax.scatter() (e.g., zorder, edgecolors, linewidths).

Returns:

The matplotlib axes object.

Return type:

plt.Axes

Examples

>>> import scdiffeq as sdq
>>> # Color by time
>>> sdq.pl.simulation_umap(adata_sim, color="t")
>>> # Color by fate
>>> sdq.pl.simulation_umap(adata_sim, color="fate", categorical_cmap={"Mon.": "orange", "Neu.": "blue"})
>>> # Color by gene expression
>>> sdq.pl.simulation_umap(adata_sim, color="Myc")
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