如何为子图中的人物设置动画？

Question

我写了一个代码来解释波浪的叠加。我在下面粘贴我的代码和输出。但是问题是我只创建了静态图。...如果我可以对波浪进行动画处理（在我的代码：subplot(211)中，并且在{{1}中产生相应的结果，则事情将变得更加有趣。 }。但是到目前为止，我只能在没有子图的情况下进行动画处理……而当我在互联网上研究“使用subplot(212)进行子图动画化”时，结果对我来说不是那么容易理解，并且与本例中的代码也不相同。

有人可以在这方面帮助我吗？如果动画基于我的以下代码结构会更好（当然，可以理解子图动画的必要更改）。谢谢大家。

我的代码

matplotlib

输出

在这里，我想为#Composition of Waves import matplotlib as mpl mpl.rc('text', usetex = True) mpl.rc('font', family = 'serif') import matplotlib.pyplot as plt import numpy as np plt.gca().set_aspect('equal', adjustable='box') plt.style.use(['ggplot','dark_background']) title = 'Composition of Waves' #Parameters: #a=Amplitude; w=Angular Frequency; phi = Phase Angle. #Definition of the function: def f(t,a,w,phi): y = a*np.sin(w*t + phi) return y t = np.arange(0,4*np.pi,0.001) def create_plot(ptype): y1 = f(t,1,1,1) y2 = f(t,2,2,2) y = y1 + y2 if ptype == 'waves': plt.plot(t, y1, label='$y=f_1(t)$') plt.plot(t, y2, label='$y=f_2(t)$') elif ptype == 'composition': plt.plot(t, y, label='$Composition$', color= 'm') plt.figure(1) plt.subplot(211) create_plot('waves') plt.legend() plt.legend(loc='center left', bbox_to_anchor=(1, 0.5)) #plt.xlabel('$x$') plt.ylabel('$y$') plt.title(title) plt.subplot(212) create_plot('composition') plt.legend() plt.legend(loc='center left', bbox_to_anchor=(1, 0.5)) plt.xlabel('$t$') plt.ylabel('$y$') # Tweak spacing between subplots to prevent labels from overlapping plt.subplots_adjust(hspace=0.5) plt.savefig('composition_Waves.eps', format='eps', dpi=1000,bbox_inches='tight') plt.show() 和w不同的波浪设置动画。

Answer 1

无论是否具有子图，创建动画都没有什么不同。唯一重要的是保留对Artist对象的引用（在这种情况下，由Line2D返回的plt.plot()对象可以在动画函数中修改其属性（数据）

import matplotlib as mpl
mpl.rc('text', usetex = False)
mpl.rc('font', family = 'serif')
import matplotlib.pyplot as plt
import numpy as np

plt.gca().set_aspect('equal', adjustable='box')
plt.style.use(['ggplot','dark_background'])

title = 'Composition of Waves'
#Parameters:
#a=Amplitude; w=Angular Frequency; phi = Phase Angle.

#Definition of the function:
def f(t,a,w,phi): 
    y = a*np.sin(w*t + phi)
    return y

t = np.arange(0,4*np.pi,0.001)

def create_plot(ptype):
    y1 = f(t,1,1,1)
    y2 = f(t,2,2,2)
    y = y1 + y2
    arts = []
    if ptype == 'waves':
        l1, = plt.plot(t, y1, label='$y=f_1(t)$')
        l2, = plt.plot(t, y2, label='$y=f_2(t)$')
        arts = [l1, l2]
    elif ptype == 'composition':
        l3, = plt.plot(t, y, label='$Composition$', color= 'm')
        arts = [l3]
    return arts ## return the artists created by `plt.plot()`



my_lines = [] ## array to keep track of the Line2D artists
fig = plt.figure(1)
plt.subplot(211)                                  
l = create_plot('waves') 
my_lines += l ## add artists to array
plt.legend()
plt.legend(loc='center left', bbox_to_anchor=(1, 0.5))
#plt.xlabel('$x$')
plt.ylabel('$y$')
plt.title(title)

plt.subplot(212)
l = create_plot('composition')
my_lines += l
plt.legend()
plt.legend(loc='center left', bbox_to_anchor=(1, 0.5))
plt.xlabel('$t$')
plt.ylabel('$y$')

# Tweak spacing between subplots to prevent labels from overlapping
plt.subplots_adjust(hspace=0.5)

print(my_lines)

def animate(i):
    ## in this examples, i takes values 0-10 by steps of 0.01 (the frames in the animation call)
    ## and will represent the frequency of the 2nd wave in the top subplot
    y1 = f(t,1,1,1)
    y2 = f(t,2,i,2)
    y = y1 + y2

    # update the content of the Line2D objects
    my_lines[1].set_ydata(y2)
    my_lines[2].set_ydata(y)
    return my_lines ## return updated artists

ani = animation.FuncAnimation(fig, animate, frames=np.linspace(0,10,100))

plt.show()