SIR model¶

[17]:

from epistochmodels import SIR, SIR_Dem

[18]:

%pylab inline

Populating the interactive namespace from numpy and matplotlib

[19]:

pop = 1000
beta = 0.7
gamma = 0.2
model = SIR(pop,beta,gamma)

[20]:

model.initialize(990,10,0)

[21]:

%%time
res = model.run(0,1000)

CPU times: user 2.66 ms, sys: 0 ns, total: 2.66 ms
Wall time: 2.67 ms

[22]:

plot(res[0],res[1])
legend(['S','I','R']);
grid();

[23]:

pop2 = 1000
alpha = 0.05 # Mortality rate
model2 = SIR_Dem(pop2, alpha,beta,gamma)

[24]:

model2.initialize(990,10,0)

[25]:

%%time
res2 = model2.run(0,100)

CPU times: user 37.6 ms, sys: 7.04 ms, total: 44.6 ms
Wall time: 43 ms

[26]:

plot(res2[0],res2[1])
legend(['S','I','R']);
grid()

[ ]:

EpiStochModels