EoN.SIR_homogeneous_meanfield¶
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EoN.SIR_homogeneous_meanfield(S0, I0, R0, n, tau, gamma, tmin=0, tmax=100, tcount=1001)[source]¶ Encodes System (4.9) of Kiss, Miller, & Simon. Please cite the book if using this algorithm.
In the text this is often referred to as the “mean-field model closed at the level of pairs”
These are often referred to as the “Kermack-McKendrick equations”
[dot{S}] = - tau n[S][I]/N [dot{I}] = au n[S][I]/N - gamma [I] [dot{R}] = gamma [I]
Arguments: - S0 number
- initial number susceptible
- I0 number
- initial number infected
- R0 number
- initial number recovered
- n number
- (average) degree of each node
- tau positive float
- transmission rate
- gamma number
- recovery rate
- tmin number (default 0)
- minimum report time
- tmax number (default 100)
- maximum report time
- tcount integer (default 1001)
- number of reports
Returns: times, S, I, R all numpy arrays
SAMPLE USE: import networkx as nx import EoN S0 = 999 I0 = 1 n = 4 #degree tau = 1 gamma = 2 t, S, I, R = EoN.SIR_homogeneous_meanfield(S0, I0, 0, n, tau, gamma)