cfpq_data.graphs.generators.labeled_scale_free_graph#
- labeled_scale_free_graph(n: int, *, alpha: float = 0.41, beta: float = 0.54, gamma: float = 0.05, delta_in: float = 0.2, delta_out: float = 0, labels: ~typing.Iterable[str] = 'abcd', choice: ~typing.Callable[[~typing.Iterable[str]], str] = <bound method Random.choice of <random.Random object>>, seed: int | None = None) MultiDiGraph [source]#
Returns a scale-free directed graph. With labeled edges.
- Parameters:
n (integer) -- Number of nodes in graph.
alpha (float) -- Probability for adding a new node connected to an existing node chosen randomly according to the in-degree distribution.
beta (float) -- 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.
gamma (float) -- Probability for adding a new node connected to an existing node chosen randomly according to the out-degree distribution.
delta_in (float) -- Bias for choosing nodes from in-degree distribution.
delta_out (float) -- Bias for choosing nodes from out-degree distribution.
labels (Iterable[str]) -- Labels that will be used to mark the edges of the graph.
choice (Callable[[Iterable[str]], str]) -- Function for marking edges.
seed (integer, random_state, or None (default)) -- Indicator of random number generation state.
Examples
>>> from cfpq_data import * >>> g = labeled_scale_free_graph(42, seed=42) >>> g.number_of_nodes() 42 >>> g.number_of_edges() 81
- Returns:
g -- A scale-free directed graph.
- Return type:
MultiDiGraph
Notes
The sum of
alpha
,beta
, andgamma
must be 1.References
[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.