EoN.EBCM_discrete_from_graph¶
-
EoN.
EBCM_discrete_from_graph
(G, p, initial_infecteds=None, initial_recovereds=None, rho=None, tmin=0, tmax=100, return_full_data=False)[source]¶ Takes a given graph, finds the degree distribution (from which it gets psi), assumes a constant proportion of the population is infected at time 0, and then uses the discrete EBCM model.
Arguments: - G Networkx Graph
- the contact network
- p number
- per edge transmission probability
- initial infecteds node or iterable of nodes (default
None
) - if a single node, then this node is initially infected if an iterable, then whole set is initially infected if None, then choose randomly based on rho. If rho is also None, a random single node is chosen. If both initial_infecteds and rho are assigned, then there is an error.
- initial_recovereds iterable of nodes (default
None
) - this whole collection is made recovered. Currently there is no test for consistency with initial_infecteds. Understood that everyone who isn’t infected or recovered initially is initially susceptible.
- rho float between 0 and 1 (default
None
) - the fraction to be randomly infected at time 0 If None, then rho=1/N is used where N = G.order()
- tmax number
- maximum time
- return_full_data boolean
- if False,
- return t, S, I, R and if True return t, S, I, R, and theta
Returns: - if return_full_data == False:
- returns t, S, I, R, all numpy arrays
- if …== True
- returns t, S, I, R and theta, all numpy arrays