- scale_free_graph(n, alpha=0.41, beta=0.54, gamma=0.05, delta_in=0.2, delta_out=0, seed=None, initial_graph=None)#
Returns a scale-free directed graph.
Number of nodes in graph
Probability for adding a new node connected to an existing node chosen randomly according to the in-degree distribution.
Probability for adding an edge between two existing nodes. One existing node is chosen randomly according the in-degree distribution and the other chosen randomly according to the out-degree distribution.
Probability for adding a new node connected to an existing node chosen randomly according to the out-degree distribution.
Bias for choosing nodes from in-degree distribution.
Bias for choosing nodes from out-degree distribution.
- seedinteger, random_state, or None (default)
Indicator of random number generation state. See Randomness.
- initial_graphMultiDiGraph instance, optional
Build the scale-free graph starting from this initial MultiDiGraph, if provided.
The sum of
gammamust be 1.
B. Bollobás, C. Borgs, J. Chayes, and O. Riordan, Directed scale-free graphs, Proceedings of the fourteenth annual ACM-SIAM Symposium on Discrete Algorithms, 132–139, 2003.
Create a scale-free graph on one hundred nodes:
>>> G = nx.scale_free_graph(100)