def test():
# S0 = initial healthy population
# I0 = initial infected population
# R0 = initial resistant population
# v0 = initial vaccinated population
# T = duration (days)
#beta = probability of infection per SI pair
vaccine_problem = ProblemSIRV(beta=0.0005,
v=0.1,
S0=1500,
I0=1,
R0=0,
V0=0,
p=0.1,
T=60)
vaccine_sim = SolverSIRV(vaccine_problem, 0.5)
vaccine_sim.solve()
vaccine_sim.plot()
print 'The maximum no. people infected now with vaccination:', int(
vaccine_sim.calc_max())
old_problem = ProblemSIR(beta=0.0005, v=0.1, S0=1500, I0=1, R0=0, T=60)
simulation_old = SolverSIR(old_problem, 0.5)
simulation_old.solve()
print 'Compared to the old maximum no. of infected (beta=0.0005):', int(
simulation_old.calc_max())
import matplotlib.pyplot as plt
import numpy as np
from SIR_class import ProblemSIR, SolverSIR
problem = ProblemSIR(beta=5e-4, nu=.1, S0=1500, I0=1, R0=0, T=60)
solver = SolverSIR(problem, .5)
solver.solve()
plt.subplot(2, 1, 1)
plt.title('Constant beta')
solver.plot()
problem_ = ProblemSIR(beta=lambda t: 0.0005 if t <= 12 else 0.0001,
nu=0.1,
S0=1500,
I0=1,
R0=0,
T=60)
solver_ = SolverSIR(problem_, .5)
solver_.solve()
plt.subplot(2, 1, 2)
plt.title('Varying beta')
solver_.plot()
plt.legend()
plt.show()