spreadlab/internal/engine
Justin Visser c40e483ee6 engine: education strategies (random vs most-connected)
Two ways to spend the same education budget: a uniform random sample
(spray and pray) vs the highest-degree hubs, ties broken stably towards
lower node numbers so the pick is deterministic. The origin is never
educated; they post the fake. rng.Shuffle does a seeded Fisher-Yates,
so the random pick is reproducible too. min() is a builtin since
Go 1.21.
2026-06-10 12:08:39 +02:00
..
cascade.go engine: edge thresholds and the independent cascade 2026-06-10 12:08:12 +02:00
cascade_test.go engine: edge thresholds and the independent cascade 2026-06-10 12:08:12 +02:00
educate.go engine: education strategies (random vs most-connected) 2026-06-10 12:08:39 +02:00
educate_test.go engine: education strategies (random vs most-connected) 2026-06-10 12:08:39 +02:00
graph.go engine: undirected simple graph with deterministic neighbour order 2026-06-10 11:58:45 +02:00
graph_test.go engine: undirected simple graph with deterministic neighbour order 2026-06-10 11:58:45 +02:00
holmekim.go engine: Holme-Kim network generator (powerlaw_cluster_graph port) 2026-06-10 12:05:43 +02:00
holmekim_test.go engine: Holme-Kim network generator (powerlaw_cluster_graph port) 2026-06-10 12:05:43 +02:00
rng.go engine: seeded RNG helper, first tests 2026-06-10 11:57:39 +02:00
rng_test.go engine: undirected simple graph with deterministic neighbour order 2026-06-10 11:58:45 +02:00