pyVIA.plotting_via.plot_trajectory_curves

pyVIA.plotting_via.plot_trajectory_curves(via_object, embedding=None, idx=None, title_str='Pseudotime', draw_all_curves=True, arrow_width_scale_factor=15.0, scatter_size=50, scatter_alpha=0.5, linewidth=1.5, marker_edgewidth=1, cmap_pseudotime='viridis_r', dpi=150, highlight_terminal_states=True, use_maxout_edgelist=False)[source]

projects the graph based coarse trajectory onto a umap/tsne embedding

Parameters:

  • via_object – via object

  • embedding (ndarray) – 2d array [n_samples x 2] with x and y coordinates of all n_samples. Umap, tsne, pca OR use the via computed embedding via_object.embedding

  • idx (Optional[list]) – default: None. Or List. if you had previously computed a umap/tsne (embedding) only on a subset of the total n_samples (subsampled as per idx), then the via objects and results will be indexed according to idx too

  • title_str (str) – title of figure

  • draw_all_curves (bool) – if the clustergraph has too many edges to project in a visually interpretable way, set this to False to get a simplified view of the graph pathways

  • arrow_width_scale_factor (float) –

  • scatter_size (float) –

  • scatter_alpha (float) –

  • linewidth (float) –

  • marker_edgewidth (float) –

  • cmap_pseudotime (str) –

  • dpi (int) – int default = 150. Use 300 for paper figures

  • highlight_terminal_states (bool) – whether or not to highlight/distinguish the clusters which are detected as the terminal states by via

Returns:

f, ax1, ax2