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random_regular_graph(d, n, seed=None)

The resulting graph has no self-loops or parallel edges.

Notes

The nodes are numbered from $0$ to $n - 1$.

Kim and Vu's paper shows that this algorithm samples in an asymptotically uniform way from the space of random graphs when $d = O(n^{1 / 3 - \epsilon})$.

Parameters

d : int

The degree of each node.

n : integer

The number of nodes. The value of $n \times d$ must be even.

seed : integer, random_state, or None (default)

Indicator of random number generation state. See Randomness<randomness> .

Raises

NetworkXError

If $n \times d$ is odd or $d$ is greater than or equal to $n$.

Returns a random $d$-regular graph on $n$ nodes.

Examples

See :

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


GitHub : /networkx/generators/random_graphs.py#486
type: <class 'function'>
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