import pylab as plt
import numpy as np
N=101
dx=2./(N-1)
dt=0.1
D=1./4(dx*2)/dt
class diffusion:
def init(self,step):
self.step=step
self.x=np.linspace(-1,1,N)
self.y=np.linspace(0,0,N)
self.old_y=np.linspace(0,0,N)
self.y[50]=1
def update(self):
for i in range(N):
self.old_y[i]=self.y[i]
for i in range(1,N-1):
self.y[i]=self.old_y[i]+Ddt/(dx2)(self.old_y[i+1]+self.old_y[i-1]-2*self.old_y[i])
def fire(self):
for i in range(self.step):
self.update()
i+=1
plt.plot(self.x,self.y,label="step="+str(self.step))
A=diffusion(1000)
A.fire()
A=diffusion(100)
A.fire()
A=diffusion(10)
A.fire()
A=diffusion(50)
A.fire()
A=diffusion(200)
A.fire()
A=diffusion(500)
A.fire()
plt.legend(loc="best")
plt.show()
