Module models 

Information diffusion models

Provides four simulation models on an adjacency representation:

Model	Description
IndependentCascade	Each active node activates each inactive neighbour with probability p(u,v)
LinearThreshold	Node activates when total in-weight from active neighbours ≥ per-node threshold
SIRModel	Epidemic SIR: β infection probability per edge, γ recovery probability per step
SISModel	Epidemic SIS: β/γ as SIR but recovered nodes return to susceptible

Structs

IndependentCascade

Independent Cascade (IC) diffusion model configuration.

LinearThreshold

Linear Threshold (LT) diffusion model configuration.

SIRModel

SIR epidemic model (Susceptible–Infected–Recovered).

SISModel

SIS epidemic model (Susceptible–Infected–Susceptible).

SimulationResult

Outcome of a single diffusion simulation.

Enums

SirState

State of a node in the SIR / SIS epidemic model.

Functions

expected_spread

Estimate the expected spread of a seed set under the IC model using Monte-Carlo averaging over num_simulations independent runs.

simulate_ic

Simulate one run of the Independent Cascade model.

simulate_lt

Simulate one run of the Linear Threshold model.

simulate_sir

Simulate one run of the SIR epidemic model.

simulate_sis

Simulate one run of the SIS epidemic model.

Type Aliases

AdjList

Compact edge representation: (target_id, edge_weight).