Plotting

animate_atlas([hammerbundle_dict, ...])	param ax: axis to plot on
animate_streamplot(via_object, embedding[, ...])	Draw Animated vector plots.
get_gene_expression(via_object, gene_exp[, ...])	param via_object: via object
plot_atlas_view([hammerbundle_dict, ...])	Edges can be colored by time-series numeric labels, pseudotime, lineage pathway probabilities, or gene expression.
plot_differentiation_flow(via_object[, idx, ...])	#SANKEY PLOTS G is the igraph knn (low K) used for shortest path in high dim space.
plot_gene_trend_heatmaps(via_object, df_gene_exp)	Plot the gene trends on heatmap: a heatmap is generated for each lineage (identified by terminal cluster number).
plot_piechart_viagraph(via_object[, ...])	plot two subplots with a clustergraph level representation of the viagraph showing true-label composition (lhs) and pseudotime/gene expression (rhs) Returns matplotlib figure with two axes that plot the clustergraph using edge bundling left axis shows the clustergraph with each node colored by annotated ground truth membership.
plot_population_composition(via_object[, ...])	param via_object: optional. this is required unless both time_labels and cell_labels are provided as arguments to the function
plot_sc_lineage_probability(via_object[, ...])	G is the igraph knn (low K) used for shortest path in high dim space.
plot_scatter(embedding, labels[, cmap, s, ...])	General scatter plotting tool for numeric and categorical labels on the single-cell level
plot_trajectory_curves(via_object[, ...])	projects the graph based coarse trajectory onto a umap/tsne embedding
plot_viagraph(via_object[, type_data, ...])	cluster level expression of gene/feature intensity :param via_object: :param type_data: :param gene_exp: pd.Dataframe size n_cells x genes.
via_streamplot(via_object[, embedding, ...])	Construct vector streamplot on the embedding to show a fine-grained view of inferred directions in the trajectory