karate_club_graph()
Each node in the returned graph has a node attribute 'club' that indicates the name of the club to which the member represented by that node belongs, either 'Mr. Hi' or 'Officer'. Each edge has a weight based on the number of contexts in which that edge's incident node members interacted.
Returns Zachary's Karate Club graph.
See :>>> G = nx.karate_club_graph() >>> G.nodes[5]["club"] 'Mr. Hi' >>> G.nodes[9]["club"] 'Officer'
The following pages refer to to this document either explicitly or contain code examples using this.
networkx.algorithms.non_randomness.non_randomness
networkx.generators.spectral_graph_forge.spectral_graph_forge
networkx.algorithms.traversal.beamsearch.bfs_beam_edges
networkx.algorithms.flow.gomory_hu.gomory_hu_tree
networkx.algorithms.community.modularity_max.greedy_modularity_communities
networkx.algorithms.community.modularity_max.naive_greedy_modularity_communities
Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.
Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)
SVG is more flexible but power hungry; and does not scale well to 50 + nodes.
All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them