random_powerlaw_tree(n, gamma=3, seed=None, tries=100)
A trial power law degree sequence is chosen and then elements are swapped with new elements from a powerlaw distribution until the sequence makes a tree (by checking, for example, that the number of edges is one smaller than the number of nodes).
The number of nodes.
Exponent of the power law.
Indicator of random number generation state. See Randomness<randomness>
.
Number of attempts to adjust the sequence to make it a tree.
If no valid sequence is found within the maximum number of attempts.
Returns a tree with a power law degree distribution.
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