Topology · scale_free
Scale-Free Directed
NetworkX scale_free_graph — directed scale-free graph with configurable alpha/beta/gamma.
Evaluation
Linear · T ∘ E–iterations (left / right recursion)
Doubling · T ∘ T–iterations (double recursion)
iteration 1new pairs per iteration
Point at a node (or tab to the drawing and use the arrow keys) to see every node it reaches, wave by wave. Those pairs are its rows of the closure.
Nodes · edges22 · 29
Closure |TC|55
Closure / edges1.9×
A small instance from the generator the benchmark runs with n from 100 upwards.
Definition
Symbol
SF_n
Edges
\text{Directed scale-free graph.}
Generator
engine.data_generator.DataGenerator.generate_scale_free_graphgenerate_db.py
def generate_scale_free_graph(self, n: int) -> Generator[tuple[int, int], None, None]:
"""Generate a scale-free directed graph."""
import networkx as nx
logging.info(f'Generating scale-free graph for n={n}')
graph = nx.scale_free_graph(n, seed=42)
# a MultiDiGraph: parallel edges are yielded once per edge (see save_for_clingo_xsb)
for u, v in graph.edges():
yield (u + 1, v + 1)