def test_badness_real(): #networks = ['data/protein_interaction.adj'] networks = ['data/food_web.adj', 'data/protein_interaction.adj', 'data/pierre_auger.adj'] for filename in networks: G = Graph(readwrite.read_adjacency_list(filename)) G = G.largest_component() G.defragment_indices() G.embed_ncMCE() badness = G.greedy_routing_badness() max_badness = max(badness.values()) for vertex, attributes in G.vert.items(): attributes.update({'color':badness[vertex]/max_badness}) attributes.update({'size':badness[vertex]/max_badness}) G.draw(representation='hyperbolic_polar', vertex_scale=50) G.embed_ncMCE(angular_adjustment=embedding.circular_adjustment) badness = G.greedy_routing_badness() max_badness = max(badness.values()) for vertex, attributes in G.vert.items(): attributes.update({'color':badness[vertex]/max_badness}) attributes.update({'size':badness[vertex]/max_badness}) G.draw(representation='hyperbolic_polar', vertex_scale=50) return