Modeling a Zombie Apocalypse
This example demonstrates how to solve a system of first order ODEs using SciPy. Note that a Nth order equation can also be solved using SciPy by transforming it into a system of first order equations. In a this lighthearted example, a system of ODEs can be used to model a “zombie invasion”, using the equations specified in Munz et al. 2009.
The system is given as:
dS/dt = P - B_S_Z - d_S dZ/dt = B_S_Z + G_R - A_S_Z dR/dt = d_S + A_S_Z - G_R
with the following notations:
- S: the number of susceptible victims
- Z: the number of zombies
- R: the number of people “killed”
- P: the population birth rate
- d: the chance of a natural death
- B: the chance the “zombie disease” is transmitted (an alive person becomes a zombie)
- G: the chance a dead person is resurrected into a zombie
- A: the chance a zombie is totally destroyed
This involves solving a system of first order ODEs given by: dy/dt = f(y, t)
Where y = [S, Z, R].
The code used to solve this system is below:
# zombie apocalypse modeling
import numpy as np
import matplotlib.pyplot as plt
from scipy.integrate import odeint
plt.ion()
plt.rcParams['figure.figsize'] = 10, 8
P = 0 # birth rate
d = 0.0001 # natural death percent (per day)
B = 0.0095 # transmission percent (per day)
G = 0.0001 # resurect percent (per day)
A = 0.0001 # destroy percent (per day)
# solve the system dy/dt = f(y, t)
def f(y, t):
Si = y[0]
Zi = y[1]
Ri = y[2]
# the model equations (see Munz et al. 2009)
f0 = P - B*Si*Zi - d*Si
f1 = B*Si*Zi + G*Ri - A*Si*Zi
f2 = d*Si + A*Si*Zi - G*Ri
return [f0, f1, f2]
# initial conditions
S0 = 500. # initial population
Z0 = 0 # initial zombie population
R0 = 0 # initial death population
y0 = [S0, Z0, R0] # initial condition vector
t = np.linspace(0, 5., 1000) # time grid
# solve the DEs
soln = odeint(f, y0, t)
S = soln[:, 0]
Z = soln[:, 1]
R = soln[:, 2]
# plot results
plt.figure()
plt.plot(t, S, label='Living')
plt.plot(t, Z, label='Zombies')
plt.xlabel('Days from outbreak')
plt.ylabel('Population')
plt.title('Zombie Apocalypse - No Init. Dead Pop.; No New Births.')
plt.legend(loc=0)
# change the initial conditions
R0 = 0.01*S0 # 1% of initial pop is dead
y0 = [S0, Z0, R0]
# solve the DEs
soln = odeint(f, y0, t)
S = soln[:, 0]
Z = soln[:, 1]
R = soln[:, 2]
plt.figure()
plt.plot(t, S, label='Living')
plt.plot(t, Z, label='Zombies')
plt.xlabel('Days from outbreak')
plt.ylabel('Population')
plt.title('Zombie Apocalypse - 1% Init. Pop. is Dead; No New Births.')
plt.legend(loc=0)
# change the initial conditions
R0 = 0.01*S0 # 1% of initial pop is dead
P = 10 # 10 new births daily
y0 = [S0, Z0, R0]
# solve the DEs
soln = odeint(f, y0, t)
S = soln[:, 0]
Z = soln[:, 1]
R = soln[:, 2]
plt.figure()
plt.plot(t, S, label='Living')
plt.plot(t, Z, label='Zombies')
plt.xlabel('Days from outbreak')
plt.ylabel('Population')
plt.title('Zombie Apocalypse - 1% Init. Pop. is Dead; 10 Daily Births')
plt.legend(loc=0)
<matplotlib.legend.Legend at 0x392ac90>