matplotlib动画打印所有点，而不仅仅是最新的迭代

Question

我正在尝试使用matplotlib设置一组在2D空间中移动的点的动画。它目前的工作方式是，它的代码确实产生了一个动画点，但这不是我认为它将如何工作。它不是在每一个时间点绘制点，而是在所有时间点绘制它们。

例如，如果代码运行时有20个点，我希望它在一个帧显示20个点，然后在下一个帧显示相同的点，依此类推。相反，它保留了之前的帧点，而不只是显示新的帧点。

有人能告诉我我哪里出错了吗？

当我的研究发现一个真正的动画问题时，我也会把它作为一个真正的问题来追溯，但我也会把它作为一个真正的问题来解决：

文件“C:\Users\Anaconda3\lib\site packages\matplotlib\动画.py“，第1568行，在绘图框中 a、 设置动画（self.\u blit）

属性错误：'努比·恩达雷'对象没有属性'set\u animated'

我也不知道为什么会这样，网上搜索也没有帮助。

代码如下：

import matplotlib.pyplot as plt #Import plotting library
from matplotlib import animation
import numpy as np #Import numpy library

dim = 2             #Defines the dimensionality of the system
n = 25               #Number of BOIDS
tmax = 80             #Length of sim
dmax = 5            #Distance boids can "see", determines what other boids interact with them
o = np.zeros(dim) #Origin as vector
r = np.random.rand(n,dim) #Places BOIDs randomly with co-ordinates (x,y,z) from 0 to 1. Has dimensions n and dim
v = 2*np.random.rand(n,dim)-1#Sets initial velocity of each BOID from -1 to 1 in each cardinal direction
rt = np.zeros((tmax,n,dim)) #This array contains the whole system's positions at each point in time
x = np.empty(n)
y = np.empty(n)
d = np.zeros(n)
vk = np.zeros((n,2))
vksum = np.zeros((n,2))
pltx = np.zeros((tmax,n))
plty = np.zeros((tmax,n))
"""rt[a][b][0] is the x co-ordinate of boid n=b at t=a
   rt[a][b][1] is the y co-ordiante of boid n=b at t=a
   np.linalg.norm gives the modulus of an array, check documentation for arguments"""

fig, ax = plt.subplots(figsize=(14,9))
ax.grid(True,linestyle='-',color='0.75') #Sets up a grid on subplot
ax.set_xlim(-50,50)
ax.set_ylim(-50,50) #Set limits for x and y axes 

for t in range (0,tmax):
    for i in range (0,n):
        for k in range (0,n):
            if abs(k-n)>0:
                d[k] = ((r[i][0]-r[k][0])**2+(r[i][1]-r[k][1])**2)**(1/2) #Checks distance from ith boid to each other boid
            if (d[k]-dmax)<0:   #If they are within range of the ith boid
                vk[k] = (v[i] +v[k])/((np.linalg.norm(v[i]))*np.linalg.norm(v[k]))#Aligns the velocity of ith boid toward the velocity of the kth boid
        for l in range (0,n):
            vksum[i] = vksum[i] + vk[l] #Sums the boid's velocity contributions together
        v[i] = (3/4)*v[i] + (vksum[i]/np.linalg.norm(vksum[i])) #Sets the boid's new velocity 
        r[i] = r[i] + v[i]  #Sets the boid's new position
        rt[t][i] = r[i] #Logs the position of the boid in the time array
        pltx[t][i] = r[i][0]
        plty[t][i] = r[i][1]


def init():
    for i in range (0,n):
        x[i] = rt[0][i][0]
        y[i] = rt[0][i][1]
    return x,y,  

def update(j):
    for i in range (0,n):
        x[i] = rt[j][i][0]
        y[i] = rt[j][i][1]
    points = ax.scatter(x[:],y[:],c='r')
    return x,y

anim = animation.FuncAnimation(fig, update, frames=tmax, interval=50,blit=True)

Answer 1

使用ax.clear()删除以前的点（当您使用blit=False时）

def update(j):

    ax.clear()

    for i in range (0,n):
        x[i] = rt[j][i][0]
        y[i] = rt[j][i][1]
    points = ax.scatter(x[:], y[:], c='r')

    return x,y