star_graph(n, create_using=None)

The star graph consists of one center node connected to n outer nodes.

Notes

The graph has n+1 nodes for integer n. So star_graph(3) is the same as star_graph(range(4)).

Parameters

n : int or iterable

If an integer, node labels are 0 to n with center 0. If an iterable of nodes, the center is the first.

create_using : NetworkX graph constructor, optional (default=nx.Graph)

Graph type to create. If graph instance, then cleared before populated.

Return the star graph

Examples

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

networkx.algorithms.assortativity.mixing.degree_mixing_matrix networkx.algorithms.similarity.panther_similarity networkx.algorithms.similarity.graph_edit_distance networkx.algorithms.centrality.second_order.second_order_centrality networkx.algorithms.bipartite.cluster.average_clustering networkx.algorithms.similarity.generate_random_paths networkx.generators.line.line_graph

Local connectivity graph

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

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GitHub : /networkx/generators/classic.py#600
type: <class 'function'>
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