EoN.EBCM_uniform_introduction¶
- 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.
- Arguments:
- 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
- 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