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simulation.py
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import numpy as np
import random
from scipy.integrate import odeint
import matplotlib.pyplot as plt
from math import *
import scipy.io as sio
from scipy import signal
import time
t_i = time.time()
# Total population, N.
N1 = 5000
N2 = 50000
# Initial number of infected and recovered individuals, I0 and R0.
I10=1000
R10=10
I20 =1000
# Everyone else, S0, is susceptible to infection initially.
S10 = N1 - I10 - R10
S20 = N2 - I20
# Contact rate, beta, and mean recovery rate, gamma, (in 1/days).
beta_hv=0.03
alpha=0.0011
gamma=0.01
mu_h = 0.02
beta_vh =0.1
mu_0 = 0.1
mu_v = 0.1
a=0.75
Tf=int(9*1e8)
#Tf0 = 1
#delta = 365*Tf0
t = 0.0
#t0 = np.linspace(0, delta-1, delta)
#R0 = np.zeros(np.int(delta))
#mu= np.zeros(np.int(delta))
#for i in range(np.int(delta)):
#R0[i] = (N2*np.exp (mu_0*(1+(signal.square(2*np.pi*t/365, duty=a)))- mu_v)*beta_hv*beta_vh)/(N1*(gamma+mu_h)*mu_0 * (1 + (signal.square(2*np.pi*t/365, duty=a))) )
# mu[i] = (mu_0/a)*(1+signal.square(2*np.pi*t0[i]/365, duty=a))
#t1=t0/365
#R0 = np.zeros(Tf)
T = np.zeros(Tf)
S1 = np.zeros(Tf)
I1 = np.zeros(Tf)
R1 = np.zeros(Tf)
S2 = np.zeros(Tf)
I2= np.zeros(Tf)
T[0] = t
S1[0] = S10
I1[0] = I10
R1[0] = R10
S2[0] = S20
I2[0] = I20
tS1, tI1, tR1, tS2, tI2 = S10, I10, R10, S20, I20
count = 0
while((tI1 > -0.01 ) and (tI2 > -0.01) and (count < Tf-1) and t < 3650.0 ): #t is number of days for which simulation will take place
#if(t%365 < )
#k1 = (mu_0/a)*(1+(signal.square(2*np.pi*t/365, duty=a)))*(tS2 +tI2)
k1 = (mu_0)*(1+a*np.cos(2*np.pi*t/365))*(tS2 +tI2)
k2 = mu_v* tS2
k3 = mu_v * tI2
k4 = gamma * tI1
k5 = mu_h * tI1
k6 = mu_h * tR1
k7 = alpha * tR1
k8 = beta_vh * tI1 * tS2 / (tS1+tI1+tR1)
k9 = mu_h * N1
k10 = mu_h * tS1
k11 = beta_hv * tI2 * tS1 / (tS1+tI1+tR1)
K = k1 + k2 + k3 + k4 + k5 +k6 + k7 + k8 + k9 +k10 + k11
#R0[count] = (mu_v)*(1+a*np.cos(2*np.pi*t/365))
delta = (1.0/K) * np.log(1.0/random.random())
t += delta
r = random.random() * K
if (r < k1) :
tS2 += 1
elif (r < k1+k2) :
tS2 -= 1
elif (r < k1+k2+k3) :
tI2 -= 1
elif (r < k1+k2+k3+k4) :
tI1 -= 1
tR1 += 1
elif (r < k1+k2+k3+k4+k5) :
tI1 -= 1
elif (r < k1+k2+k3+k4+k5+k6) :
tR1 -= 1
elif (r < k1+k2+k3+k4+k5+k6+k7) :
tR1 -= 1
tS1 += 1
elif (r < k1+k2+k3+k4+k5+k6+k7+k8) :
tS2 -= 1
tI2 += 1
elif (r < k1+k2+k3+k4+k5+k6+k7+k8+k9) :
tS1 += 1
elif (r < k1+k2+k3+k4+k5+k6+k7+k8+k9+k10) :
tS1 -= 1
elif (r < k1+k2+k3+k4+k5+k6+k7+k8+k9+k10+k11) :
tS1 -= 1
tI1 += 1
#print( round(k1,2), round(k2,2), round(k3,2),round(k4,2),round(k5,2),round(k6,2),round(k7,2),round(k8,2),round(k9,2),round(k10,2),round(k11,2), round(r,2), tS1,tI1,tR1,tS2,tI2 )
count += 1
if ((count%5)==0):
T[count] = t
S1[count] = tS1
I1[count] = tI1
R1[count] = tR1
S2[count] = tS2
I2[count] = tI2
print( round(tI1,2), round(tI2,2), count, T[count])
#R0 = R0[:count]
T = T[:count]
S1 = S1[:count]
I1 = I1[:count]
R1 = R1[:count]
S2 = S2[:count]
I2 = I2[:count]
np.savez_compressed('output_medium'.format(a) , a=T, b=I1, c=I2, d=R1, e=S2)
t_f = time.time() - t_i
print( t_f)