dynamicalab.dynamics.SISDynamics¶

class dynamicalab.dynamics.SISDynamics(p, q, self_activation=0)[source]¶

Markovian discrete time Suceptible-infected-suceptible process on networks.

__init__(p, q, self_activation=0)[source]¶

Parameters

p : Float: Probability of infection
q : Float: Probability of recovery
self_activation : Float : (default=0): Probability of spontaneous activation

Note that the __call__(G, T) method is independent of T[i]-T[i+1]. Only len(T) is taken into account for the number of steps.

Methods

`__init__`(p, q[, self_activation])	Parameters
`best_x0`(G)	Convenient method to get a good initial state given as a random infection.

DynamicaLab