dual_barabasi_albert_graph(n, m1, m2, p, seed=None, initial_graph=None)
A graph of $n$ nodes is grown by attaching new nodes each with either $m_1$ edges (with probability $p$) or $m_2$ edges (with probability $1-p$) that are preferentially attached to existing nodes with high degree.
Number of nodes
Number of edges to link each new node to existing nodes with probability $p$
Number of edges to link each new node to existing nodes with probability $1-p$
The probability of attaching $m_1$ edges (as opposed to $m_2$ edges)
Indicator of random number generation state. See Randomness<randomness>
.
Initial network for Barabási–Albert algorithm. A copy of :None:None:`initial_graph` is used. It should be connected for most use cases. If None, starts from an star graph on max(m1, m2) + 1 nodes.
If :None:None:`m1` and :None:None:`m2` do not satisfy 1 <= m1,m2 < n
, or p does not satisfy 0 <= p <= 1
, or the initial graph number of nodes m0 does not satisfy m1, m2 <= m0 <= n.
Returns a random graph using dual Barabási–Albert preferential attachment
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