我终于找到了一个解决方案。你可以通过使用这个脚本来简单地完成它。我试图保持简单：

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation

# Helps me to get the data from the file I want to plot
N = 0

# Load particle positioins
with open('//home//user//data.dat', 'r') as fp:
    particles = []
    for line in fp:
        line = line.split() 
        particles.append(line)

# Create new Figure and an Axes which fills it.
fig = plt.figure(figsize=(7, 7))
ax = fig.add_axes([0, 0, 1, 1], frameon=True)
border = 100
ax.set_xlim(-border, border), ax.set_xticks([])
ax.set_ylim(-border, border), ax.set_yticks([])

# particle data
p = 18 # number of particles
myPa = np.zeros(p, dtype=[('position', float, 2)])

# Construct the scatter which we will update during animation
scat = ax.scatter(myPa['position'][:, 0], myPa['position'][:, 1])

def update(frame_number):
    # New positions
    myPa['position'][:] = particles[N*p:N*p+p]

    # Update the scatter collection, with the new colors, sizes and positions.
    scat.set_offsets(myPa['position'])
    increment()

def increment():
    global N
    N = N+1

# Construct the animation, using the update function as the animation director.
animation = FuncAnimation(fig, update, interval=20)

plt.show()

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制作动画最简单、最干净的方法是使用matplotlib.animation模块，如下面的Matplotlib Animation Tutorial所示。
因为散点图返回matplotlib.collections.PathCollection，所以更新它的方法是调用它的set_offsets方法。您可以向它传递一个shape（N，2）数组或N个二元组的列表-每个二元组是(x,y)坐标。
比如说，

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation

T = 100
numbParticles = 2
particles = np.random.random((T,numbParticles)).tolist()
x, y = np.array([]), np.array([])

def init():
    pathcol.set_offsets([[], []])
    return [pathcol]

def update(i, pathcol, particles):
    pathcol.set_offsets(particles[i])
    return [pathcol]

fig = plt.figure()
xs, ys = zip(*particles)
xmin, xmax = min(xs), max(xs)
ymin, ymax = min(ys), max(ys)
ax = plt.axes(xlim=(xmin, xmax), ylim=(ymin, ymax))
pathcol = plt.scatter([], [], s=100)

anim = FuncAnimation(fig, update, init_func=init, fargs=(pathcol, particles),
                     interval=1000, frames=T, blit=True, repeat=True)
plt.show()

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循环在FuncAnimation()内部，所以你看不到它。如果你愿意，你可以看看source code（实际上那里没有循环，而是一个迭代器），但你也可以接受从外部看到的FuncAnimation(fig, update, interval=1000, frames=100)每1000 ms调用一次函数update，并将i递增1，直到frames给出的数字。