我正在尝试实现 runge-kutta 方法来解决 Lotka-Volterra 系统,但代码(波纹管)无法正常工作。我遵循了我在 StackOverflow 的其他主题中找到的建议,但结果与内置的 Runge-Kutta 方法不收敛,例如 Pylab 中可用的 rk4 方法。有人可以帮助我吗?
import matplotlib.pyplot as plt
import numpy as np
from pylab import *
def meurk4( f, x0, t ):
n = len( t )
x = np.array( [ x0 ] * n )
for i in range( n - 1 ):
h = t[i+1] - t[i]
k1 = h * f( x[i], t[i] )
k2 = h * f( x[i] + 0.5 * h * k1, t[i] + 0.5 * h )
k3 = h * f( x[i] + 0.5 * h * k2, t[i] + 0.5 * h )
k4 = h * f( x[i] + h * k3, t[i] + h)
x[i+1] = x[i] + ( k1 + 2 * ( k2 + k3 ) + k4 ) * 6**-1
return x
def model(state,t):
x,y = state
a = 0.8
b = 0.02
c = 0.2
d = 0.004
k = 600
return np.array([ x*(a*(1-x*k**-1)-b*y) , -y*(c - d*x) ]) # corresponds to [dx/dt, dy/dt]
# initial conditions for the system
x0 = 500
y0 = 200
# vector of time
t = np.linspace( 0, 50, 100 )
result = meurk4( model, [x0,y0], t )
print result
plt.plot(t,result)
plt.xlabel('Time')
plt.ylabel('Population Size')
plt.legend(('x (prey)','y (predator)'))
plt.title('Lotka-Volterra Model')
plt.show()
我刚刚在评论之后更新了代码。所以,功能meurk4
:
def meurk4( f, x0, t ):
n = len( t )
x = np.array( [ x0 ] * n )
for i in range( n - 1 ):
h = t[i+1] - t[i]
k1 = h * f( x[i], t[i] )
k2 = h * f( x[i] + 0.5 * h * k1, t[i] + 0.5 * h )
k3 = h * f( x[i] + 0.5 * h * k2, t[i] + 0.5 * h )
k4 = h * f( x[i] + h * k3, t[i] + h)
x[i+1] = x[i] + ( k1 + 2 * ( k2 + k3 ) + k4 ) * 6**-1
return x
现在变成(更正):
def meurk4( f, x0, t ):
n = len( t )
x = np.array( [ x0 ] * n )
for i in range( n - 1 ):
h = t[i+1] - t[i]
k1 = f( x[i], t[i] )
k2 = f( x[i] + 0.5 * h * k1, t[i] + 0.5 * h )
k3 = f( x[i] + 0.5 * h * k2, t[i] + 0.5 * h )
k4 = f( x[i] + h * k3, t[i] + h)
x[i+1] = x[i] + ( k1 + 2 * ( k2 + k3 ) + k4 ) * (h/6)
return x
然而,结果如下:
而buitin方法rk4(来自Pylab)的结果如下:
所以,当然我的代码仍然不正确,因为它的结果与内置的 rk4 方法不同。拜托,有人可以帮助我吗?