triangles(G, nodes=None)
Finds the number of triangles that include a node as one vertex.
When computing triangles for the entire graph each triangle is counted three times, once at each node. Self loops are ignored.
A networkx graph
Compute triangles for nodes in this container.
Number of triangles keyed by node label.
Compute the number of triangles.
>>> G = nx.complete_graph(5)
... print(nx.triangles(G, 0)) 6
>>> print(nx.triangles(G)) {0: 6, 1: 6, 2: 6, 3: 6, 4: 6}
>>> print(list(nx.triangles(G, (0, 1)).values())) [6, 6]See :
The following pages refer to to this document either explicitly or contain code examples using this.
networkx.algorithms.cluster.generalized_degree
networkx.algorithms.cluster.triangles
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