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pythonnumerical-methodsrunge-kuttalorenz-system

Runge Kutta constants diverging for Lorenz system?


I'm trying to solve the Lorenz system using the 4th order Runge Kutta method, where

dx/dt=a*(y-x)
dy/dt=x(b-z)-y
dx/dt=x*y-c*z

Since this system doesn't depend explicity on time, it's possibly to ignore that part in the iteration, so I just have dX=F(x,y,z)

def func(x0):
    a=10
    b=38.63
    c=8/3
    fx=a*(x0[1]-x0[0])
    fy=x0[0]*(b-x0[2])-x0[1]
    fz=x0[0]*x0[1]-c*x0[2]
    return np.array([fx,fy,fz])

def kcontants(f,h,x0):
    k0=h*f(x0)
    k1=h*f(f(x0)+k0/2)
    k2=h*f(f(x0)+k1/2)
    k3=h*f(f(x0)+k2)
    #note returned K is a matrix
    return np.array([k0,k1,k2,k3])

x0=np.array([-8,8,27])
h=0.001

t=np.arange(0,50,h)
result=np.zeros([len(t),3])

for time in range(len(t)):
    if time==0:
        k=kcontants(func,h,x0)
        result[time]=func(x0)+(1/6)*(k[0]+2*k[1]+2*k[2]+k[3])
    else:
        k=kcontants(func,h,result[time-1])
        result[time]=result[time-1]+(1/6)*(k[0]+2*k[1]+2*k[2]+k[3])

The result should be the Lorenz atractors, however my code diverges around the fifth iteration, and it's because the contants I create in kconstants do, however I checked and I'm pretty sure the runge kutta impletmentation is not to fault... (at least i think)

edit:

Found a similar post ,yet can't figure what I'm doing wrong


Solution

  • You have an extra call of f(x0) in the calculation of k1, k2 and k3. Change the function kcontants to

    def kcontants(f,h,x0):
        k0=h*f(x0)
        k1=h*f(x0 + k0/2)
        k2=h*f(x0 + k1/2)
        k3=h*f(x0 + k2)
        #note returned K is a matrix
        return np.array([k0,k1,k2,k3])