tensor_product

tensor_product(G, H)

Return the tensor product of G and H.

The tensor product P of the graphs G and H has a node set that is the Cartesian product of the node sets, $V(P)=V(G) times V(H)$. P has an edge ((u,v),(x,y)) if and only if (u,v) is an edge in G and (x,y) is an edge in H.

Sometimes referred to as the categorical product.

Parameters :

G, H: graphs :

Networkx graphs.

Returns :

P: NetworkX graph :

The tensor product of G and H. P will be a multi-graph if either G or H is a multi-graph. Will be a directed if G and H are directed, and undirected if G and H are undirected.

Raises :

NetworkXError :

If G and H are not both directed or both undirected.

Notes

Node attributes in P are two-tuple of the G and H node attributes. Missing attributes are assigned None.

For example >>> G = nx.Graph() >>> H = nx.Graph() >>> G.add_node(0,a1=True) >>> H.add_node(‘a’,a2=’Spam’) >>> P = nx.tensor_product(G,H) >>> P.nodes(data=True) [((0, ‘a’), {‘a1’: (True, None), ‘a2’: (None, ‘Spam’)})]

Edge attributes and edge keys (for multigraphs) are also copied to the new product graph