newman_watts_strogatz_graph(n, k, p, seed=None)
First create a ring over $n$ nodes . Then each node in the ring is connected with its $k$ nearest neighbors (or $k - 1$ neighbors if $k$ is odd). Then shortcuts are created by adding new edges as follows: for each edge $(u, v)$ in the underlying "$n$-ring with $k$ nearest neighbors" with probability $p$ add a new edge $(u, w)$ with randomly-chosen existing node $w$. In contrast with watts_strogatz_graph
, no edges are removed.
The number of nodes.
Each node is joined with its k nearest neighbors in a ring topology.
The probability of adding a new edge for each edge.
Indicator of random number generation state. See Randomness<randomness>
.
Returns a Newman–Watts–Strogatz small-world graph.
The following pages refer to to this document either explicitly or contain code examples using this.
networkx.generators.random_graphs.connected_watts_strogatz_graph
networkx.generators.random_graphs.watts_strogatz_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