File:Lorenz 96.svg
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![File:Lorenz 96.svg](https://upload.wikimedia.org/wikipedia/commons/thumb/6/6f/Lorenz_96.svg/405px-Lorenz_96.svg.png?20171103005451)
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[edit]DescriptionLorenz 96.svg |
English: Plot of 3 variables in a Lorenz 96 model simulation with 36 variables and |
Date | |
Source | Generated using code from Lorenz 96 model, added by anonymous user with IP 163.1.81.7 |
Author | AnonymousUnknown author |
SVG development InfoField | ![]() This plot was created with Matplotlib. |
Source code InfoField | Python codefrom scipy.integrate import odeint
import matplotlib.pyplot as plt
import numpy as np
# these are our constants
N = 36 # number of variables
F = 8 # forcing
def Lorenz96(x,t):
# compute state derivatives
d = np.zeros(N)
# first the 3 edge cases: i=1,2,N
d[0] = (x[1] - x[N-2]) * x[N-1] - x[0]
d[1] = (x[2] - x[N-1]) * x[0]- x[1]
d[N-1] = (x[0] - x[N-3]) * x[N-2] - x[N-1]
# then the general case
for i in range(2, N-1):
d[i] = (x[i+1] - x[i-2]) * x[i-1] - x[i]
# add the forcing term
d = d + F
# return the state derivatives
return d
x0 = F*np.ones(N) # initial state (equilibrium)
x0[19] += 0.01 # add small perturbation to 20th variable
t = np.arange(0.0, 30.0, 0.01)
x = odeint(Lorenz96, x0, t)
# plot first three variables
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.plot(x[:,0],x[:,1],x[:,2])
ax.set_xlabel('$x_1$')
ax.set_ylabel('$x_2$')
ax.set_zlabel('$x_3$')
plt.show()
|
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Date/Time | Thumbnail | Dimensions | User | Comment | |
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current | 00:54, 3 November 2017 | ![]() | 405 × 314 (76 KB) | InverseHypercube (talk | contribs) | Cropped |
00:47, 3 November 2017 | ![]() | 575 × 431 (56 KB) | InverseHypercube (talk | contribs) | User created page with UploadWizard |
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