Read and write NetworkX graphs as edge lists.

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With the edgelist format simple edge data can be stored but node or graph data is not. ... Returns ----- G : graph A networkx Graph or other type specified with create_using Notes ----- Since nodes must be hashable, the function nodetype must return hashable types (e.g.

The default is networkx.Graph, an undirected graph. def read_graph(edgeList,weighted=False, directed=False): ''' Reads the input network in networkx. int, float, str, frozenset - or tuples of those, etc.) create_using ( NetworkX graph) – Use specified graph for result.

To find all isomorphic graph groups you can use the function connected_components() or find_cliques() with iso_graph:

Networkx allows us to create both directed and undirected Multigraphs. A Multigraph is a Graph where multiple parallel edges can connect the same nodes. There is no way of representing isolated nodes unless the node has a self-loop edge. But you can compare all possible graph combinations and build the graph iso_graph from combinations which are isomorphic.

>>> edgelist= [ (0,1)] # single edge (0,1) >>> G=nx.from_edgelist(edgelist) or >>> G=nx.Graph (edgelist) # use Graph constructor.

create_using (Graph container, optional,) – Use specified container to build graph. Otherwise a new graph is created. They have four different relations among them … Examples. The multi-line adjacency list format is useful for graphs with nodes that can be meaningfully represented as strings. edgelist ( list or iterator) – Edge tuples. To determine if two graphs are isomorphic you can use the function is_isomorphic().Unfortunately there is no function to compare more than 2 graphs.

For example, let us create a network of 10 people, A, B, C, D, E, F, G, H, I and J.