def si_model(pop, init, length, alpha, beta):
"""Discrete SI (susceptible, infected) ILM. `init` are the amount of initial infections which are randomly generated
at time 0. `length` is the simulation length in days.
"""
edb = event_db(init, pop)
for i in range(1, (length+1)):
edb = infect(pop, alpha, beta, edb, i)
return edb
def sicr_model(pop, init, length, alpha, beta, gamma):
"""Discrete SIR (susceptible, infected, recovered) ILM. `init` are the amount of initial infections which are randomly generated
at time 0. `length` is the simulation length in days. Recovery period is a constant, `gamma`.
"""
edb = event_db(init, pop)
for i in range(1, (length+1)):
edb = infect(pop, alpha, beta, edb, i)
edb = constant_recover(pop, edb, i, gamma)
return edb
def sir_model(pop, init, length, alpha, beta, gamma):
"""Discrete SIR (susceptible, infected, recovered) ILM. `init` are the amount of initial infections which are randomly generated
at time 0. `length` is the simulation length in days. Mean recovery period `gamma` is equivalent to the mean of the geometric
distribution.
"""
edb = event_db(init, pop)
for i in range(1, (length+1)):
edb = infect(pop, alpha, beta, edb, i)
edb = geometric_recover(pop, edb, i, gamma)
return edb
