Question

我正在尝试设置两个高斯配置文件的动画，以便它们可以以相同的速度同时进行，精确的解决方案将保持其原始配置文件，而计算的解决方案将随时间扩散。

我进行了所有计算，但我无法为两条曲线设置动画，以便它们可以在同一块图上一起进行。

import numpy as np 
import pandas as pd
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
import matplotlib.animation as animation
%matplotlib notebook

xmin = 0        # minimum value of x 
xmax = 2        # maximum value of x
N = 200         # Number of nodes  
dt = 0.005      # time step
tmax = 2      # solution time
v = 0.5           # velocity
t0 = 0

# Discritize the domain 
dx = (xmax - xmin)/N
x = np.arange(xmin-dx,xmax+dx,dx)
# set initial condition 
u0 = np.exp(-200*np.square(x-0.25))

u = u0.copy()
unp1 = u0.copy()
unpf = []
uexact = []
t = np.arange(t0, tmax, dt)
#Newman boundary condition no gradient across the boundary 
u[0]= u[2]
u[-1]= u[N-1]
#Loop through time
nsteps = int(tmax/dt)
for n in range (0,nsteps):    
    #Calculate the FOU scheme
    for i in range (1, N+1):
        unp1[i] = u[i] - v*(dt/dx)*(u[i]-u[i-1])
    unpf.append(unp1.copy())
    uexact.append(np.exp(-200*np.square(x-0.25-v*t[n])))
    u = unp1

fig, ax = plt.subplots()

plt.xlabel('x')
plt.ylabel('u')
plt.title('Initial condition')
line, = ax.plot(x, u0)
def animate(i):
    line.set_ydata(uexact[i])  # update the data
    return line,
ani = animation.FuncAnimation(fig, animate, np.arange(1, len(uexact)), interval=100)

line, = ax.plot(x, u0)
ax.set_xlim(xmin, xmax)
ax.set_xlabel('X nodes - Axis')
ax.set_ylabel('Y nodes - Axis')
def animate(i):
    line.set_ydata(unpf[i])  # update the data
    return line,
ani = animation.FuncAnimation(fig, animate, np.arange(1, len(unpf)), interval=100)
plt.show()

Answer 1

没有理由在这里使用两个不同的FuncAnimation，因为您需要一个动画，动画两个或更多个对象。

由于unpf和uexact似乎具有相同数量的项目，因此可以直接实现此目标。

... # all other code

line, = ax.plot(x, u0)
line2, = ax.plot(x, u0)
def animate(i):
    line.set_ydata(uexact[i])  # update the data
    line2.set_ydata(unpf[i])  # update the data
    return line, line2,

ani = animation.FuncAnimation(fig, animate, np.arange(1, len(unpf)), interval=100)
plt.show()

在Matplotlib

1 个答案: