在 matplotlib 中缩放轴 3d

Question

I'm facing issues in scaling axes 3d in matplotlib. I have found another questions but somehow the answer it does not seems to work. Here is a sample code:

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

data=np.array([[0,0,0],[10,1,1],[2,2,2]])

fig=plt.figure()
ax=Axes3D(fig)
ax.set_xlim3d(0,15)
ax.set_ylim3d(0,15)
ax.set_zlim3d(0,15)
ax.scatter(data[:,0],data[:,1],data[:,2])
plt.show()

It seems it just ignore the ax.set commands...

Answer 1

In my experience, you have to set your axis limits after plotting the data, otherwise it will look at your data and adjust whatever axes settings you entered before to fit it all in-frame out to the next convenient increment along the axes in question. If, for instance, you set your x-axis limits to +/-400 but your data go out to about +/-1700 and matplotlib decides to label the x-axis in increments of 500, it's going to display the data relative to an x-axis that goes out to +/-2000.

So in your case, you just want to rearrange that last block of text as:

fig=plt.figure()
ax=Axes3D(fig)
ax.scatter(data[:,0],data[:,1],data[:,2])
ax.set_xlim3d(0,15)
ax.set_ylim3d(0,15)
ax.set_zlim3d(0,15)
plt.show()

Answer 2

The way of ColorOutOfSpace is good. But if you want to automate the scaling you have to search for the maximum and minimum number in the data and scale with those values.

min = np.amin(data)  # lowest number in the array
max = np.amax(data)  # highest number in the array

ax.set_xlim3d(min, max)
ax.set_ylim3d(min, max)
ax.set_zlim3d(min, max)