metachat.pl.plot_communication_flow
- metachat.pl.plot_communication_flow(adata, database_name, metabolite_name=None, metapathway_name=None, customerlist_name=None, ms_pair_name=None, summary='receiver', plot_method='grid', background='image', library_id=None, group_name=None, group_cmap=None, background_legend=False, cmap='coolwarm', pos_idx=array([0, 1]), normalize_summary_quantile=0.995, ndsize=3, vmin=None, vmax=None, grid_density=1.0, grid_knn=None, grid_scale=1.0, grid_thresh=1.0, arrow_color='#000000', arrow_width=0.005, largest_arrow=0.05, normalize_v=False, normalize_v_quantile=0.95, title=None, plot_savepath=None, ax=None)[source]
Visualize inferred metabolic communication vector fields on tissue images or annotated backgrounds.
This function overlays communication flow vectors computed from MetaChat analysis results on tissue images, categorical annotations, or summary backgrounds. It supports spot-wise, grid-interpolated, or streamline rendering.
Parameters
- adataanndata.AnnData
Annotated data matrix containing spatial coordinates in
adata.obsm["spatial"].- database_namestr
Name of the metabolite–sensor interaction database used for communication inference.
- metabolite_namestr, optional
Name of a specific metabolite to visualize. Mutually exclusive with
metapathway_name,customerlist_name, andms_pair_name.- metapathway_namestr, optional
Name of a specific metabolic pathway to visualize.
- customerlist_namestr, optional
Name of a custom metabolite–sensor list to visualize.
- ms_pair_namestr, optional
Name of a metabolite–sensor pair to visualize.
- summary{“sender”, “receiver”}, default=”receiver”
Type of summary statistic used for background coloring.
- plot_method{“cell”, “grid”, “stream”}, default=”grid”
Rendering mode for vector visualization.
- background{“summary”, “image”, “group”}, default=”image”
Type of background to draw behind the vectors.
- library_idstr, optional
Visium library identifier used when
background="image".- group_namestr, optional
Column in
adata.obsused for categorical coloring whenbackground="group".- group_cmapdict, optional
Mapping from category names to colors.
- background_legendbool, default=False
Whether to display legend for the background.
- cmapstr, default=”coolwarm”
Colormap name for summary or numeric backgrounds.
- pos_idxnp.ndarray, default=np.array([0,1])
Indices of spatial coordinates used for plotting.
- normalize_summary_quantilefloat, default=0.995
Quantile for clipping background values.
- ndsizefloat, default=3
Spot marker size.
- vmin, vmaxfloat, optional
Color scale limits for background values.
- grid_densityfloat, default=1.0
Density of interpolation grid when
plot_method="grid".- grid_knnint, optional
Number of neighbors used for vector interpolation.
- grid_scalefloat, default=1.0
Kernel scale factor for interpolation.
- grid_threshfloat, default=1.0
Minimum interpolation weight threshold.
- arrow_colorstr, default=”#000000”
Color of flow arrows.
- arrow_widthfloat, default=0.005
Width of quiver arrows.
- largest_arrowfloat, default=0.05
Maximum arrow length after normalization.
- normalize_vbool, default=False
Whether to normalize vector magnitudes for visualization.
- normalize_v_quantilefloat, default=0.95
Quantile for magnitude clipping before normalization.
- titlestr, optional
Title of the plot.
- plot_savepathstr, optional
File path to save the plot; no saving if
None.- axmatplotlib.axes.Axes, optional
Axis to draw the plot on; creates new one if
None.
Returns
- axmatplotlib.axes.Axes
Matplotlib axis containing the resulting plot.
- coords_plotnp.ndarray
Coordinates used for plotting (after interpolation).
- V_plotnp.ndarray
Vector field used for plotting (after interpolation).