python - Draw network and grouped vertices of the same community or partition -

i need view (drawn or plot) communities structure in networks

i have this:

import igraph random import randint  def _plot(g, membership=none):     layout = g.layout("kk")     visual_style = {}     visual_style["edge_color"] = "gray"     visual_style["vertex_size"] = 30     visual_style["layout"] = layout     visual_style["bbox"] = (1024, 768)     visual_style["margin"] = 40     vertex in g.vs():         vertex["label"] = vertex.index     if membership not none:         colors = []         in range(0, max(membership)+1):             colors.append('%06x' % randint(0, 0xffffff))         vertex in g.vs():             vertex["color"] = str('#') + colors[membership[vertex.index]]         visual_style["vertex_color"] = g.vs["color"]     igraph.plot(g, **visual_style)  if __name__ == "__main__":     karate = igraph.nexus.get("karate")     cl = karate.community_fastgreedy()     membership = cl.as_clustering().membership     _plot(karate, membership) 

but vertices spread. in networks result worse.

i want vertices grouped color in similar region.

e.g:

based on @gabor-csardi answer, made code:

import igraph random import randint  def _plot(g, membership=none):     if membership not none:         gcopy = g.copy()         edges = []         edges_colors = []         edge in g.es():             if membership[edge.tuple[0]] != membership[edge.tuple[1]]:                 edges.append(edge)                 edges_colors.append("gray")             else:                 edges_colors.append("black")         gcopy.delete_edges(edges)         layout = gcopy.layout("kk")         g.es["color"] = edges_colors     else:         layout = g.layout("kk")         g.es["color"] = "gray"     visual_style = {}     visual_style["vertex_label_dist"] = 0     visual_style["vertex_shape"] = "circle"     visual_style["edge_color"] = g.es["color"]     # visual_style["bbox"] = (4000, 2500)     visual_style["vertex_size"] = 30     visual_style["layout"] = layout     visual_style["bbox"] = (1024, 768)     visual_style["margin"] = 40     visual_style["edge_label"] = g.es["weight"]     vertex in g.vs():         vertex["label"] = vertex.index     if membership not none:         colors = []         in range(0, max(membership)+1):             colors.append('%06x' % randint(0, 0xffffff))         vertex in g.vs():             vertex["color"] = str('#') + colors[membership[vertex.index]]         visual_style["vertex_color"] = g.vs["color"]     igraph.plot(g, **visual_style)  if __name__ == "__main__":     g = igraph.nexus.get("karate")     cl = g.community_fastgreedy()     membership = cl.as_clustering().membership     _plot(g, membership) 

results: