EoN.EBCM_uniform_introduction(N, psi, psiPrime, tau, gamma, rho, tmin=0, tmax=100, tcount=1001, return_full_data=False)[source]

Handles the case that the disease is introduced uniformly as opposed to depending on degree.

N positive integer
size of population
psi function
psihat(x) = sum_k S(k,0) x^k
psiPrime function
psihatPrime(x) = d psihat(x)/dx = sum_k k S(k,0) x^{k-1}
tau positive float
per edge transmission rate
gamma number
per node recovery rate
rho number
initial proportion infected
tmin number
start time
tmax number
stop time
tcount integer
number of distinct times to calculate
return_full_data boolean
if False,
return t, S, I, R
if True
return t, S, I, R, and theta
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