下面的代码示例提供了一种相对于其他轴缩放每个轴的方法。但是，要做到这一点，您需要修改Axes3D.get_proj函数。下面是一个基于matplot lib：

http://matplotlib.org/1.4.0/mpl_toolkits/mplot3d/tutorial.html#line-plots提供的例子

(这个答案的结尾有一个较短的版本)

from mpl_toolkits.mplot3d.axes3d import Axes3D

from mpl_toolkits.mplot3d import proj3d

import matplotlib as mpl

import numpy as np

import matplotlib.pyplot as plt

#Make sure these are floating point values:

scale_x = 1.0

scale_y = 2.0

scale_z = 3.0

#Axes are scaled down to fit in scene

max_scale=max(scale_x, scale_y, scale_z)

scale_x=scale_x/max_scale

scale_y=scale_y/max_scale

scale_z=scale_z/max_scale

#Create scaling matrix

scale = np.array([[scale_x,0,0,0],

[0,scale_y,0,0],

[0,0,scale_z,0],

[0,0,0,1]])

print scale

def get_proj_scale(self):

"""

Create the projection matrix from the current viewing position.

elev stores the elevation angle in the z plane

azim stores the azimuth angle in the x,y plane

dist is the distance of the eye viewing point from the object

point.

"""

relev, razim = np.pi * self.elev/180, np.pi * self.azim/180

xmin, xmax = self.get_xlim3d()

ymin, ymax = self.get_ylim3d()

zmin, zmax = self.get_zlim3d()

# transform to uniform world coordinates 0-1.0,0-1.0,0-1.0

worldM = proj3d.world_transformation(

xmin, xmax,

ymin, ymax,

zmin, zmax)

# look into the middle of the new coordinates

R = np.array([0.5, 0.5, 0.5])

xp = R[0] + np.cos(razim) * np.cos(relev) * self.dist

yp = R[1] + np.sin(razim) * np.cos(relev) * self.dist

zp = R[2] + np.sin(relev) * self.dist

E = np.array((xp, yp, zp))

self.eye = E

self.vvec = R - E

self.vvec = self.vvec / proj3d.mod(self.vvec)

if abs(relev) > np.pi/2:

# upside down

V = np.array((0, 0, -1))

else:

V = np.array((0, 0, 1))

zfront, zback = -self.dist, self.dist

viewM = proj3d.view_transformation(E, R, V)

perspM = proj3d.persp_transformation(zfront, zback)

M0 = np.dot(viewM, worldM)

M = np.dot(perspM, M0)

return np.dot(M, scale);

Axes3D.get_proj=get_proj_scale

"""

You need to include all the code above.

From here on you should be able to plot as usual.

"""

mpl.rcParams['legend.fontsize'] = 10

fig = plt.figure(figsize=(5,5))

ax = fig.gca(projection='3d')

theta = np.linspace(-4 * np.pi, 4 * np.pi, 100)

z = np.linspace(-2, 2, 100)

r = z**2 + 1

x = r * np.sin(theta)

y = r * np.cos(theta)

ax.plot(x, y, z, label='parametric curve')

ax.legend()

plt.show()

标准输出：

(1，2，3)：

缩放(1，1，3)：

我特别喜欢这种方法的原因，

交换z和x，缩放(3,1,1)：

以下是较短版本的代码。

from mpl_toolkits.mplot3d.axes3d import Axes3D

from mpl_toolkits.mplot3d import proj3d

import matplotlib as mpl

import numpy as np

import matplotlib.pyplot as plt

mpl.rcParams['legend.fontsize'] = 10

fig = plt.figure(figsize=(5,5))

ax = fig.gca(projection='3d')

theta = np.linspace(-4 * np.pi, 4 * np.pi, 100)

z = np.linspace(-2, 2, 100)

r = z**2 + 1

x = r * np.sin(theta)

y = r * np.cos(theta)

"""

Scaling is done from here...

"""

x_scale=1

y_scale=1

z_scale=2

scale=np.diag([x_scale, y_scale, z_scale, 1.0])

scale=scale*(1.0/scale.max())

scale[3,3]=1.0

def short_proj():

return np.dot(Axes3D.get_proj(ax), scale)

ax.get_proj=short_proj

"""

to here

"""

ax.plot(z, y, x, label='parametric curve')

ax.legend()

plt.show()