#!/usr/bin/env python """ ===== Atlas ===== Atlas of all graphs of 6 nodes or less. """ # Author: Aric Hagberg (hagberg@lanl.gov) # Copyright (C) 2004-2019 by # Aric Hagberg # Dan Schult # Pieter Swart # All rights reserved. # BSD license. import random try: import pygraphviz from networkx.drawing.nx_agraph import graphviz_layout except ImportError: try: import pydot from networkx.drawing.nx_pydot import graphviz_layout except ImportError: raise ImportError("This example needs Graphviz and either " "PyGraphviz or pydot.") import matplotlib.pyplot as plt import networkx as nx from networkx.algorithms.isomorphism.isomorph import graph_could_be_isomorphic as isomorphic from networkx.generators.atlas import graph_atlas_g def atlas6(): """ Return the atlas of all connected graphs of 6 nodes or less. Attempt to check for isomorphisms and remove. """ Atlas = graph_atlas_g()[0:208] # 208 # remove isolated nodes, only connected graphs are left U = nx.Graph() # graph for union of all graphs in atlas for G in Atlas: zerodegree = [n for n in G if G.degree(n) == 0] for n in zerodegree: G.remove_node(n) U = nx.disjoint_union(U, G) # iterator of graphs of all connected components C = (U.subgraph(c) for c in nx.connected_components(U)) UU = nx.Graph() # do quick isomorphic-like check, not a true isomorphism checker nlist = [] # list of nonisomorphic graphs for G in C: # check against all nonisomorphic graphs so far if not iso(G, nlist): nlist.append(G) UU = nx.disjoint_union(UU, G) # union the nonisomorphic graphs return UU def iso(G1, glist): """Quick and dirty nonisomorphism checker used to check isomorphisms.""" for G2 in glist: if isomorphic(G1, G2): return True return False if __name__ == '__main__': G = atlas6() print("graph has %d nodes with %d edges" % (nx.number_of_nodes(G), nx.number_of_edges(G))) print(nx.number_connected_components(G), "connected components") plt.figure(1, figsize=(8, 8)) # layout graphs with positions using graphviz neato pos = graphviz_layout(G, prog="neato") # color nodes the same in each connected subgraph C = (G.subgraph(c) for c in nx.connected_components(G)) for g in C: c = [random.random()] * nx.number_of_nodes(g) # random color... nx.draw(g, pos, node_size=40, node_color=c, vmin=0.0, vmax=1.0, with_labels=False ) plt.show()