Network relabelling

PopPUNK/__init__.py

@@ -3,7 +3,7 @@
 
 '''PopPUNK (POPulation Partitioning Using Nucleotide Kmers)'''
 
-__version__ = '2.7.1'
+__version__ = '2.7.2'
 
 # Minimum sketchlib version
 SKETCHLIB_MAJOR = 2

PopPUNK/plot.py

@@ -559,15 +559,26 @@ def outputsForCytoscape(G, G_mst, isolate_names, clustering, outPrefix, epiCsv,
         save_network(G, prefix = outPrefix, suffix = suffix, use_graphml = True)
 
     # Save each component too (useful for very large graphs)
+    example_cluster_title = list(clustering.keys())[0]
     component_assignments, component_hist = gt.label_components(G)
     for component_idx in range(len(component_hist)):
-        remove_list = []
-        for vidx, v_component in enumerate(component_assignments.a):
-            if v_component != component_idx:
-                remove_list.append(vidx)
-        G.remove_vertex(remove_list)
-        G.purge_vertices()
-        save_network(G, prefix = outPrefix, suffix = "_component_" + str(component_idx + 1), use_graphml = True)
+      # Naming must reflect the full graph size
+      component_name = component_idx + 1
+      get_component_name = (use_partial_query_graph is not None)
+      # Filter the graph for the current component
+      comp_filter = G.new_vertex_property("bool")
+      for v in G.vertices():
+        comp_filter[v] = (component_assignments[v] == component_idx)
+        # If using partial query graph find the component name from the clustering
+        if get_component_name and comp_filter[v]:
+          example_isolate_name = seqLabels[int(v)]
+          component_name = clustering[example_cluster_title][example_isolate_name]
+          get_component_name = False
+      G_component = gt.GraphView(G, vfilt=comp_filter)
+      # Purge the component to remove unreferenced vertices (optional but recommended)
+      G_component.purge_vertices()
+      # Save the component network
+      save_network(G_component, prefix = outPrefix, suffix = "_component_" + str(component_name), use_graphml = True)
 
     if G_mst != None:
         isolate_labels = isolateNameToLabel(G_mst.vp.id)

PopPUNK/visualise.py

@@ -699,21 +699,17 @@ def generate_visualisations(query_db,
             if gpu_graph:
                 genomeNetwork = cugraph_to_graph_tool(genomeNetwork, isolateNameToLabel(all_seq))
             # Hard delete from network to remove samples (mask doesn't work neatly)
-            if include_files is not None and not use_partial_query_graph:
+            if include_files is not None:
                 genomeNetwork = remove_nodes_from_graph(genomeNetwork, all_seq, viz_subset, use_gpu = gpu_graph)
         elif rank_fit is not None:
             genomeNetwork = sparse_mat_to_network(sparse_mat, combined_seq, use_gpu = gpu_graph)
         else:
             sys.stderr.write('Cytoscape output requires a network file or lineage rank fit to be provided\n')
             sys.exit(1)
-        # If network has been pruned then only use the appropriate subset of names - otherwise use all names
-        # for full network
-        node_labels = viz_subset if (use_partial_query_graph is not None or include_files is not None) \
-                                      else combined_seq
         sys.stderr.write('Preparing outputs for cytoscape\n')
         outputsForCytoscape(genomeNetwork,
                             mst_graph,
-                            node_labels,
+                            combined_seq,
                             isolateClustering,
                             output,
                             info_csv,