有两种方法可以做到这一点

Two ways you could do this would be

• 结合使用 set_offsets()和 set_3d_properties
• 清除figure 和/或axes 对象并在每次迭代中绘制一个新的scatter

• Use a combination of set_offsets() and set_3d_properties
• Clear the figure and/or axes object(s) and plot a new scatter every iteration

使用 set_offsets() 和 set_3d_properties 的示例:

Example using set_offsets() and set_3d_properties:

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np

x = np.linspace(0, np.pi*2, 25)
y = np.sin(x)
z = np.cos(x)

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

def plot(ax):
    return ax.scatter(x, y, z)

def update(s):
    s.set_offsets(np.stack([x, y], 1))
    s.set_3d_properties(z, 'z')

s = plot(ax)
plt.savefig("./before.png")
y = np.cos(x)
z = np.sin(x)
update(s)
plt.savefig("./after.png")

示例清除和重绘:

def plot(fig, ax):
    ax.scatter(x, y, z)

plot(fig, ax)
plt.savefig("./before.png")
y = np.cos(x)
z = np.sin(x)
plt.cla()
plot(fig, ax)
plt.savefig("./after.png")

或者，如果您想在同一个散点图中累积每次迭代的数据，您可以将新数据点附加到 x、y 和 z 对象并使用上述方法之一.

Or, if you want to accumulate the data from every iteration in the same scatter plot, you can just append the new data points to the x, y, and z objects and use one of the above methods.

累积示例:

def plot(ax):
    return ax.scatter(x, y, z)

def update(s):
    s.set_offsets(np.stack([x, y], 1))
    s.set_3d_properties(z, 'z')

s = plot(ax)
plt.savefig("./before.png")
x = np.vstack([x,x])
y = np.vstack([y, np.cos(x)])
z = np.vstack([z, np.sin(x)])
update(s)
plt.savefig("./after.png")

我推荐 set_offsets() 和 set_3d_properties() 的组合.请参见此答案有关确定 figure 和 axes 对象的范围的更多信息.

I would recommend the combination of set_offsets() and set_3d_properties(). See this answer for more about scoping the figure and axes objects.