问题
When I set up equal aspect ratio for 3d graph the z-axis does not change to 'equal'. So, this:
fig = pylab.figure()
mesFig = fig.gca(projection='3d', adjustable='box')
mesFig.axis('equal')
mesFig.plot(xC, yC, zC, 'r.')
mesFig.plot(xO, yO, zO, 'b.')
pyplot.show()
gives me the following:
where obviously the unit length of z-axis is not equal to x- and y-units.
How can I make the unit length of all three axes equal? All the solutions I could find did not work. Thank you.
回答1:
I believe matplotlib does not yet set correctly equal axis in 3D... But I found a trick some times ago (I don't remember where) that I've adapted using it. The concept is to create a fake cubic bounding box around your data. You can test it with the following code:
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
import matplotlib.pyplot as plt
import numpy as np
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.set_aspect('equal')
X = np.random.rand(100)*10+5
Y = np.random.rand(100)*5+2.5
Z = np.random.rand(100)*50+25
scat = ax.scatter(X, Y, Z)
# Create cubic bounding box to simulate equal aspect ratio
max_range = np.array([X.max()-X.min(), Y.max()-Y.min(), Z.max()-Z.min()]).max()
Xb = 0.5*max_range*np.mgrid[-1:2:2,-1:2:2,-1:2:2][0].flatten() + 0.5*(X.max()+X.min())
Yb = 0.5*max_range*np.mgrid[-1:2:2,-1:2:2,-1:2:2][1].flatten() + 0.5*(Y.max()+Y.min())
Zb = 0.5*max_range*np.mgrid[-1:2:2,-1:2:2,-1:2:2][2].flatten() + 0.5*(Z.max()+Z.min())
# Comment or uncomment following both lines to test the fake bounding box:
for xb, yb, zb in zip(Xb, Yb, Zb):
ax.plot([xb], [yb], [zb], 'w')
plt.grid()
plt.show()
z data are about an order of magnitude larger than x and y, but even with equal axis option, matplotlib autoscale z axis:
But if you add the bounding box, you obtain a correct scaling:
回答2:
I simplified Remy F's solution by using the set_x/y/zlim functions.
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
import matplotlib.pyplot as plt
import numpy as np
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.set_aspect('equal')
X = np.random.rand(100)*10+5
Y = np.random.rand(100)*5+2.5
Z = np.random.rand(100)*50+25
scat = ax.scatter(X, Y, Z)
max_range = np.array([X.max()-X.min(), Y.max()-Y.min(), Z.max()-Z.min()]).max() / 2.0
mid_x = (X.max()+X.min()) * 0.5
mid_y = (Y.max()+Y.min()) * 0.5
mid_z = (Z.max()+Z.min()) * 0.5
ax.set_xlim(mid_x - max_range, mid_x + max_range)
ax.set_ylim(mid_y - max_range, mid_y + max_range)
ax.set_zlim(mid_z - max_range, mid_z + max_range)
plt.show()
回答3:
I like the above solutions, but they do have the drawback that you need to keep track of the ranges and means over all your data. This could be cumbersome if you have multiple data sets that will be plotted together. To fix this, I made use of the ax.get_[xyz]lim3d() methods and put the whole thing into a standalone function that can be called just once before you call plt.show(). Here is the new version:
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
import matplotlib.pyplot as plt
import numpy as np
def set_axes_equal(ax):
'''Make axes of 3D plot have equal scale so that spheres appear as spheres,
cubes as cubes, etc.. This is one possible solution to Matplotlib's
ax.set_aspect('equal') and ax.axis('equal') not working for 3D.
Input
ax: a matplotlib axis, e.g., as output from plt.gca().
'''
x_limits = ax.get_xlim3d()
y_limits = ax.get_ylim3d()
z_limits = ax.get_zlim3d()
x_range = abs(x_limits[1] - x_limits[0])
x_middle = np.mean(x_limits)
y_range = abs(y_limits[1] - y_limits[0])
y_middle = np.mean(y_limits)
z_range = abs(z_limits[1] - z_limits[0])
z_middle = np.mean(z_limits)
# The plot bounding box is a sphere in the sense of the infinity
# norm, hence I call half the max range the plot radius.
plot_radius = 0.5*max([x_range, y_range, z_range])
ax.set_xlim3d([x_middle - plot_radius, x_middle + plot_radius])
ax.set_ylim3d([y_middle - plot_radius, y_middle + plot_radius])
ax.set_zlim3d([z_middle - plot_radius, z_middle + plot_radius])
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.set_aspect('equal')
X = np.random.rand(100)*10+5
Y = np.random.rand(100)*5+2.5
Z = np.random.rand(100)*50+25
scat = ax.scatter(X, Y, Z)
set_axes_equal(ax)
plt.show()
回答4:
Adapted from @karlo's answer to make things even cleaner:
def set_axes_radius(ax, origin, radius):
ax.set_xlim3d([origin[0] - radius, origin[0] + radius])
ax.set_ylim3d([origin[1] - radius, origin[1] + radius])
ax.set_zlim3d([origin[2] - radius, origin[2] + radius])
def set_axes_equal(ax):
'''Make axes of 3D plot have equal scale so that spheres appear as spheres,
cubes as cubes, etc.. This is one possible solution to Matplotlib's
ax.set_aspect('equal') and ax.axis('equal') not working for 3D.
Input
ax: a matplotlib axis, e.g., as output from plt.gca().
'''
limits = np.array([
ax.get_xlim3d(),
ax.get_ylim3d(),
ax.get_zlim3d(),
])
origin = np.mean(limits, axis=1)
radius = 0.5 * np.max(np.abs(limits[:, 1] - limits[:, 0]))
set_axes_radius(ax, origin, radius)
Usage:
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.set_aspect('equal') # important!
# ...draw here...
set_axes_equal(ax) # important!
plt.show()
回答5:
EDIT: user2525140's code should work perfectly fine, although this answer supposedly attempted to fix a non--existant error. The answer below is just a duplicate (alternative) implementation:
def set_aspect_equal_3d(ax):
"""Fix equal aspect bug for 3D plots."""
xlim = ax.get_xlim3d()
ylim = ax.get_ylim3d()
zlim = ax.get_zlim3d()
from numpy import mean
xmean = mean(xlim)
ymean = mean(ylim)
zmean = mean(zlim)
plot_radius = max([abs(lim - mean_)
for lims, mean_ in ((xlim, xmean),
(ylim, ymean),
(zlim, zmean))
for lim in lims])
ax.set_xlim3d([xmean - plot_radius, xmean + plot_radius])
ax.set_ylim3d([ymean - plot_radius, ymean + plot_radius])
ax.set_zlim3d([zmean - plot_radius, zmean + plot_radius])
来源：https://stackoverflow.com/questions/13685386/matplotlib-equal-unit-length-with-equal-aspect-ratio-z-axis-is-not-equal-to