Plotting

plotting.commitment_score(adata[, lineage_key])	Compute and plot cell fate commitment scores based on fate probabilities.
plotting.cellfate_perturbation(adata, df[, ...])	Plot depletion likelihood or score for transcription factors across terminal states.
plotting.simulated_visit_diff(adata, ...[, ...])	Assign and visualize smoothed absolute differences in visit counts between control and perturbation simulations.
plotting.regulatory_network(motif[, figsize])	Visualize a gene regulatory network (GRN) from a DataFrame.
plotting.plot_visits_dist(df, palette_rel, ...)	Plot a boxplot of visit difference values per terminal state for a single TF.
plotting.plot_visits_dist_screen(adata, ...)	Plot a combined boxplot of visit differences across all knocked-out TFs, one panel per terminal state, filtered to a significance threshold.
plotting.plot_TF_success_rate(adata[, ...])	Rank TFs by how their knockout affects differentiation to the terminal states.
plotting.plot_grn_weight(adata, vae, TF, ...)	Plot cell-resolved regulatory weights for one TF against several targets.
plotting.plot_TF_regulon(adata, rgv_model, ...)	Plot a TF's regulon ranking, regulatory network, and cell-resolved weights.