EoN.SIS_homogeneous_pairwise_from_graph¶
-
EoN.
SIS_homogeneous_pairwise_from_graph
(G, tau, gamma, initial_infecteds=None, rho=None, tmin=0, tmax=100, tcount=1001, return_full_data=False)[source]¶ Calls SIS_homogeneous_pairwise after calculating S0, I0, SI0, SS0, n based on the graph G and initial fraction infected rho.
Arguments: - G networkx Graph
- the contact network
- tau positive float
- transmission rate
- gamma number
- recovery rate
- 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.
- 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()
- tmin number (default 0)
- minimum report time
- tmax number (default 100)
- maximum report time
- tcount integer (default 1001)
- number of reports
- return_full_data boolean (default False)
- tells whether to just return times, S, I, or all calculated data. if True, then returns times, S, I, SI, SS
Returns: - if return_full_data is True:
- t, S, I, SI, SS, II
- if return_full_data is False:
- t, S, I
SAMPLE USE: import networkx as nx import EoN G = nx.fast_gnp_random_graph(10000,0.0005) tau = 1 gamma = 3 rho = 0.02 t, S, I = EoN.SIS_homogeneous_pairwise_from_graph(G, tau, gamma, rho, tmax = 20)