在Matplotlib

Question

同時動畫在同一個情節兩條曲線

我試圖動畫兩個高斯曲線，使他們能夠以相同的速度同時進步，確切的解決方案將保持原有特性，而計算的解決方案將隨時間擴散。

我做所有的計算，但我不能動畫兩條曲線，使他們能夠在同一地塊共同進步。

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

沒有理由在這裏使用兩個不同的FuncAnimation S，只要你想一個單一的動畫，動畫兩個或多個對象。

由於unpf和uexact似乎具有相同數量的項目，因此執行此操作非常簡單。

... # 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()