blocks|key|374885|text|听起来你想调整情节的规模。我不认为有办法将线性比例扩展到用户规范，但您可以使用set_yscale()、set_xscale()、set_zscale()来相互修改比例。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|374886|直观地说，set_yscale(log)，set_xscale(log)，set_zscale(linear)可以解决你的问题。|374887|一个可能更好的选项:指定一个扩展，将它们全部设置为具有相同日志基的符号日志，然后根据您的规范指定Z轴的linscalex/linscaley+kwargs的符号标度。|374888|这里有更多内容：|374889|toolkits/mplot3d/api.html|374890|entityMap|0|LINK|mutability|MUTABLE|url|http://matplotlib.org/mpl_toolkits/mplot3d/api.html^0|13|C|1G|C|1T|C|0|5|F|L|F|11|I|0|1F|J|0|0|0|P|0|0^^$0|@$1|2|3|4|5|6|7|V|8|@$9|W|A|X|B|C]|$9|Y|A|Z|B|C]|$9|10|A|11|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|12|8|@$9|13|A|14|B|C]|$9|15|A|16|B|C]|$9|17|A|18|B|C]]|D|@]|E|$]]|$1|H|3|I|5|6|7|19|8|@$9|1A|A|1B|B|C]]|D|@]|E|$]]|$1|J|3|K|5|6|7|1C|8|@]|D|@]|E|$]]|$1|L|3|M|5|6|7|1D|8|@]|D|@$9|1E|A|1F|1|1G]]|E|$]]|$1|N|3|-4|5|6|7|1H|8|@]|D|@]|E|$]]]|O|$P|$5|Q|R|S|E|$T|U]]]]

Sounds like you're trying to adjust the scale of the plot. I don't think there's a way to stretch a linear scale to user specifications, but you can use <code>set_yscale()</code>, <code>set_xscale()</code>, <code>set_zscale()</code> to alter the scales with respect to each other.

Intuitively, <code>set_yscale(log)</code>, <code>set_xscale(log)</code>, <code>set_zscale(linear)</code> might solve your problems. 

A likely better option: specify a stretch, set them all to symlog with the same log base and then specify the Z-axis's symlog scale with the <code>linscalex/linscaley</code> kwargs to your specifications.

More here:

<a href="http://matplotlib.org/mpl_toolkits/mplot3d/api.html" rel="nofollow">http://matplotlib.org/mpl_toolkits/mplot3d/api.html</a>

blocks|key|374958|text|在默认情况下，mplot3d会在非常高的地块的顶部和底部留下相当大的空间。但是，您可以使用fig.subplots_adjust来欺骗它以填充空间，并将顶部和底部扩展到正常绘图区域之外(即top+>+1和bottom+<+0)。这里可能需要对您的特定情节进行一些尝试和错误。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|374959|我为x、y和z创建了一些具有类似于您的图的限制的随机数组，并发现下面的参数(bottom=-0.15、top+=+1.2)似乎工作正常。|374960|您还可能希望更改ax.view_init以设置一个很好的视角。|374961|import+matplotlib.pyplot+as+plt
from+mpl_toolkits.mplot3d+import+axes3d
from+numpy+import+random

#+Make+some+random+data+with+similar+limits+to+the+OP's+example
x,y,z=random.rand(3,100)
z*=250
y*=800
y%2B=900
x*=350
x%2B=1200

fig=plt.figure(figsize=(4,35))

#+Set+the+bottom+and+top+outside+the+actual+figure+limits,+
#+to+stretch+the+3D+axis
fig.subplots_adjust(bottom=-0.15,top=1.2)

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

#+Change+the+viewing+angle+to+an+agreeable+one
ax.view_init(2,None)

ax.scatter(x,+y,+z,+zdir='z',+c=+'red')
plt.savefig("plot.png")|code-block|syntax|javascript|374962|​|374963|📷|atomic|374964|374965|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://developer.qcloudimg.com/http-save/yehe-900000/c04cf5c34f4031083b9b363841bdc5ea.png|imageAlt^0|19|J|2M|7|2U|A|0|12|C|1F|9|0|8|C|0|0|0|0|1|0|0|0^^$0|@$1|2|3|4|5|6|7|13|8|@$9|14|A|15|B|C]|$9|16|A|17|B|C]|$9|18|A|19|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|1A|8|@$9|1B|A|1C|B|C]|$9|1D|A|1E|B|C]]|D|@]|E|$]]|$1|H|3|I|5|6|7|1F|8|@$9|1G|A|1H|B|C]]|D|@]|E|$]]|$1|J|3|K|5|L|7|1I|8|@]|D|@]|E|$M|N]]|$1|O|3|P|5|6|7|1J|8|@]|D|@]|E|$]]|$1|Q|3|R|5|S|7|1K|8|@]|D|@$9|1L|A|1M|1|1N]]|E|$]]|$1|T|3|P|5|6|7|1O|8|@]|D|@]|E|$]]|$1|U|3|-4|5|6|7|1P|8|@]|D|@]|E|$]]]|V|$W|$5|X|Y|Z|E|$10|11|12|-4]]]]

I looks like by default, mplot3d will leave quite a bit of room at the top and bottom of a very tall plot. But, you can trick it into filling that space using <code>fig.subplots_adjust</code>, and extending the top and bottom out of the normal plotting area (i.e. <code>top &gt; 1</code> and <code>bottom &lt; 0</code>). Some trial and error here is probably needed for your particular plot. 

I've created some random arrays for x, y, and z with limits similar to your plot, and have found the parameters below (<code>bottom=-0.15</code>, <code>top = 1.2</code>) seem to work ok.

You might also want to change <code>ax.view_init</code> to set a nice viewing angle.

<pre><code>import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import axes3d
from numpy import random

# Make some random data with similar limits to the OP's example
x,y,z=random.rand(3,100)
z*=250
y*=800
y+=900
x*=350
x+=1200

fig=plt.figure(figsize=(4,35))

# Set the bottom and top outside the actual figure limits, 
# to stretch the 3D axis
fig.subplots_adjust(bottom=-0.15,top=1.2)

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

# Change the viewing angle to an agreeable one
ax.view_init(2,None)

ax.scatter(x, y, z, zdir='z', c= 'red')
plt.savefig("plot.png")
</code></pre>

<img src="https://i.stack.imgur.com/NNq3D.png" width="200">

blocks|key|1140378|text|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。下面是基于matplot：toolkits/mplot3d/tutorial.html#line-plots提供的示例的一个示例|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1140379|(答案末尾有一个较短的版本)|1140380|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]+%2B+np.cos(razim)+*+np.cos(relev)+*+self.dist
++++yp+=+R[1]+%2B+np.sin(razim)+*+np.cos(relev)+*+self.dist
++++zp+=+R[2]+%2B+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+%2B+1
x+=+r+*+np.sin(theta)
y+=+r+*+np.cos(theta)
ax.plot(x,+y,+z,+label='parametric+curve')
ax.legend()

plt.show()|code-block|syntax|javascript|1140381|标准产出：|1140382|​|1140383|📷|atomic|1140384|1140385|按(1、2、3)缩放：|1140386|1140387|1140388|1140389|按(1、1、3)缩放：|1140390|1140391|1140392|1140393|我特别喜欢这种方法的原因是，交换z和x，按(3，1，1)进行缩放：|1140394|1140395|1140396|1140397|下面是代码的较短版本。|1140398|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+%2B+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()|1140399|entityMap|0|LINK|mutability|MUTABLE|url|http://matplotlib.org/1.4.0/mpl_toolkits/mplot3d/tutorial.html#line-plots|1|IMAGE|IMMUTABLE|imageUrl|https://developer.qcloudimg.com/http-save/yehe-900000/3a0f80a06d3fa1af1aa92cd038f5700f.jpg|imageAlt|2|https://developer.qcloudimg.com/http-save/yehe-900000/7ecc48db8f77097595253fdb35282d10.jpg|3|https://developer.qcloudimg.com/http-save/yehe-900000/50f4761de33f9cbad5e1c18858cf28d4.jpg|4|https://developer.qcloudimg.com/http-save/yehe-900000/7b6b0c12cd0f3bebdb1e1038a99036eb.png^0|21|15|0|0|0|0|0|0|0|1|1|0|0|0|0|0|1|2|0|0|0|0|0|1|3|0|0|0|0|0|1|4|0|0|0|0^^$0|@$1|2|3|4|5|6|7|1V|8|@]|9|@$A|1W|B|1X|1|1Y]]|C|$]]|$1|D|3|E|5|6|7|1Z|8|@]|9|@]|C|$]]|$1|F|3|G|5|H|7|20|8|@]|9|@]|C|$I|J]]|$1|K|3|L|5|6|7|21|8|@]|9|@]|C|$]]|$1|M|3|N|5|6|7|22|8|@]|9|@]|C|$]]|$1|O|3|P|5|Q|7|23|8|@]|9|@$A|24|B|25|1|26]]|C|$]]|$1|R|3|N|5|6|7|27|8|@]|9|@]|C|$]]|$1|S|3|T|5|6|7|28|8|@]|9|@]|C|$]]|$1|U|3|N|5|6|7|29|8|@]|9|@]|C|$]]|$1|V|3|P|5|Q|7|2A|8|@]|9|@$A|2B|B|2C|1|2D]]|C|$]]|$1|W|3|N|5|6|7|2E|8|@]|9|@]|C|$]]|$1|X|3|Y|5|6|7|2F|8|@]|9|@]|C|$]]|$1|Z|3|N|5|6|7|2G|8|@]|9|@]|C|$]]|$1|10|3|P|5|Q|7|2H|8|@]|9|@$A|2I|B|2J|1|2K]]|C|$]]|$1|11|3|N|5|6|7|2L|8|@]|9|@]|C|$]]|$1|12|3|13|5|6|7|2M|8|@]|9|@]|C|$]]|$1|14|3|N|5|6|7|2N|8|@]|9|@]|C|$]]|$1|15|3|P|5|Q|7|2O|8|@]|9|@$A|2P|B|2Q|1|2R]]|C|$]]|$1|16|3|N|5|6|7|2S|8|@]|9|@]|C|$]]|$1|17|3|18|5|6|7|2T|8|@]|9|@]|C|$]]|$1|19|3|1A|5|H|7|2U|8|@]|9|@]|C|$I|J]]|$1|1B|3|-4|5|6|7|2V|8|@]|9|@]|C|$]]]|1C|$1D|$5|1E|1F|1G|C|$1H|1I]]|1J|$5|1K|1F|1L|C|$1M|1N|1O|-4]]|1P|$5|1K|1F|1L|C|$1M|1Q|1O|-4]]|1R|$5|1K|1F|1L|C|$1M|1S|1O|-4]]|1T|$5|1K|1F|1L|C|$1M|1U|1O|-4]]]]

The code example below provides a way to scale each axis relative to the others. However, to do so you need to modify the Axes3D.get_proj function. Below is an example based on the example provided by matplot lib: <a href="http://matplotlib.org/1.4.0/mpl_toolkits/mplot3d/tutorial.html#line-plots" rel="noreferrer">http://matplotlib.org/1.4.0/mpl_toolkits/mplot3d/tutorial.html#line-plots</a>

(There is a shorter version at the end of this answer)

<pre><code>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) &gt; 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()
</code></pre>

Standard output:

<img src="https://i.stack.imgur.com/F26Fcm.png" alt="Normal Scale">

Scaled by (1, 2, 3):

<img src="https://i.stack.imgur.com/cmvwqm.png" alt="Scale_x=1, Scale_y=2, Scale_z=3 ">

Scaled by (1, 1, 3):

<img src="https://i.stack.imgur.com/OGsTVm.png" alt="Scale_x=1, Scale_y=1, Scale_z=3">

The reason I particularly like this method,
Swap z and x, scale by (3, 1, 1):

<img src="https://i.stack.imgur.com/qXoc4.png" alt="Swap z and x, scale_x=4">

Below is a shorter version of the code.

<pre><code>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()
</code></pre>

blocks|key|375066|text|把你的z值乘以9，|type|unstyled|depth|inlineStyleRanges|entityRanges|data|375067|ax.scatter(x,+y,+9*z,+zdir='z',+c=+'red')|code-block|syntax|javascript|375068|然后给出z轴自定义绘图标签和间距。|375069|ax.ZTick+=+[0,-9*50,+-9*100,+-9*150,+-9*200];
ax.ZTickLabel+=+{'0','-50','-100','-150','-200'};|375070|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|N|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|O|8|@]|9|@]|A|$]]|$1|I|3|J|5|D|7|P|8|@]|9|@]|A|$E|F]]|$1|K|3|-4|5|6|7|Q|8|@]|9|@]|A|$]]]|L|$]]

Multiply all your z values by 9,

<pre><code>ax.scatter(x, y, 9*z, zdir='z', c= 'red')
</code></pre>

And then give the z-axis custom plot labels and spacing.

<pre><code>ax.ZTick = [0,-9*50, -9*100, -9*150, -9*200];
ax.ZTickLabel = {'0','-50','-100','-150','-200'};
</code></pre>

blocks|key|317807|text|请注意，下面的答案简化了补丁程序，但使用了与@ChristianSarofeen.的答案相同的基本原则。|type|unstyled|depth|inlineStyleRanges|offset|length|style|BOLD|entityRanges|data|317808|解决方案|317809|正如在其他答案中已经指出的，它不是目前在matplotlib中实现的特性。但是，由于您所要求的只是一个3D转换，它可以应用于matplotlib所使用的现有投影矩阵，而且由于的出色特性，这个问题可以通过一个简单的oneliner来解决。|317810|ax.get_proj+=+lambda:+np.dot(Axes3D.get_proj(ax),+np.diag([scale_x,+scale_y,+scale_z,+1]))|code-block|syntax|javascript|317811|其中，scale_x、scale_y和scale_z是从0到1的值，它们将相应地沿着每个轴重新缩放您的地块。ax就是ax+=+fig.gca(projection='3d')可以得到的三维轴。|CODE|317812|解释|317813|为了解释，函数get_proj+of+Axes3D从当前观看位置生成投影矩阵。将其乘以一个缩放矩阵：|317814|scale_x,+0,+++++++0
0,+++++++scale_y,+0
0,+++++++0,+++++++scale_z
0,+++++++0,+++++++1|317815|包括缩放到渲染器使用的投影。所以，我们在这里做的是用一个表达式替换原始的get_proj函数，这个表达式接受原始get_proj的结果，然后乘以缩放矩阵。|317816|示例|317817|为了用标准参数函数示例说明结果：|317818|from+mpl_toolkits.mplot3d+import+Axes3D
import+numpy+as+np
import+matplotlib.pyplot+as+plt

fig+=+plt.figure()
ax+=+fig.gca(projection='3d')
theta+=+np.linspace(-4+*+np.pi,+4+*+np.pi,+100)
z+=+np.linspace(-2,+2,+100)
r+=+z+**+2+%2B+1
x+=+r+*+np.sin(theta)
y+=+r+*+np.cos(theta)

#+OUR+ONE+LINER+ADDED+HERE:
ax.get_proj+=+lambda:+np.dot(Axes3D.get_proj(ax),+np.diag([0.5,+0.5,+1,+1]))

ax.plot(x,+y,+z)
plt.show()|317819|对于值0.5,+0.5,+1，我们得到：|317820|​|317821|📷|atomic|317822|317823|而对于值0.2,+1.0,+0.2，我们得到：|317824|317825|317826|317827|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://developer.qcloudimg.com/http-save/yehe-900000/908dcc63c4d7440ea497e44120ee7cda.png|imageAlt|1|https://developer.qcloudimg.com/http-save/yehe-900000/b772e454893d87ca1577d976b21809f2.png^0|0|15|0|0|1F|4|2F|V|0|0|0|2O|3|7|B|7|J|7|1I|2|1M|T|0|0|2|0|0|1E|7|8|J|6|0|0|0|25|10|8|1K|8|0|0|2|0|0|G|0|0|0|K|3|B|0|0|1|0|0|1|0|1|0|0|0|1|0|0|N|4|D|0|0|1|0|0|1|0|1|1|0|0|1|0^^$0|@$1|2|3|4|5|6|7|1T|8|@$9|1U|A|1V|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|1W|8|@]|D|@]|E|$]]|$1|H|3|I|5|6|7|1X|8|@$9|1Y|A|1Z|B|C]|$9|20|A|21|B|C]]|D|@]|E|$]]|$1|J|3|K|5|L|7|22|8|@]|D|@]|E|$M|N]]|$1|O|3|P|5|6|7|23|8|@$9|24|A|25|B|C]|$9|26|A|27|B|Q]|$9|28|A|29|B|Q]|$9|2A|A|2B|B|Q]|$9|2C|A|2D|B|Q]|$9|2E|A|2F|B|Q]]|D|@]|E|$]]|$1|R|3|S|5|6|7|2G|8|@$9|2H|A|2I|B|C]]|D|@]|E|$]]|$1|T|3|U|5|6|7|2J|8|@$9|2K|A|2L|B|C]|$9|2M|A|2N|B|Q]|$9|2O|A|2P|B|Q]]|D|@]|E|$]]|$1|V|3|W|5|L|7|2Q|8|@]|D|@]|E|$M|N]]|$1|X|3|Y|5|6|7|2R|8|@$9|2S|A|2T|B|C]|$9|2U|A|2V|B|Q]|$9|2W|A|2X|B|Q]]|D|@]|E|$]]|$1|Z|3|10|5|6|7|2Y|8|@$9|2Z|A|30|B|C]]|D|@]|E|$]]|$1|11|3|12|5|6|7|31|8|@$9|32|A|33|B|C]]|D|@]|E|$]]|$1|13|3|14|5|L|7|34|8|@]|D|@]|E|$M|N]]|$1|15|3|16|5|6|7|35|8|@$9|36|A|37|B|C]|$9|38|A|39|B|Q]]|D|@]|E|$]]|$1|17|3|18|5|6|7|3A|8|@$9|3B|A|3C|B|C]]|D|@]|E|$]]|$1|19|3|1A|5|1B|7|3D|8|@$9|3E|A|3F|B|C]]|D|@$9|3G|A|3H|1|3I]]|E|$]]|$1|1C|3|18|5|6|7|3J|8|@$9|3K|A|3L|B|C]]|D|@]|E|$]]|$1|1D|3|1E|5|6|7|3M|8|@$9|3N|A|3O|B|C]|$9|3P|A|3Q|B|Q]]|D|@]|E|$]]|$1|1F|3|18|5|6|7|3R|8|@$9|3S|A|3T|B|C]]|D|@]|E|$]]|$1|1G|3|1A|5|1B|7|3U|8|@$9|3V|A|3W|B|C]]|D|@$9|3X|A|3Y|1|3Z]]|E|$]]|$1|1H|3|18|5|6|7|40|8|@$9|41|A|42|B|C]]|D|@]|E|$]]|$1|1I|3|-4|5|6|7|43|8|@]|D|@]|E|$]]]|1J|$1K|$5|1L|1M|1N|E|$1O|1P|1Q|-4]]|1R|$5|1L|1M|1N|E|$1O|1S|1Q|-4]]]]

Please note that the answer below simplifies the patch, but uses the same underlying principle as the answer by @ChristianSarofeen.

<h3>Solution</h3>

As already indicated in other answers, it is not a feature that is currently implemented in matplotlib. However, since what you are requesting is simply a 3D transformation that can be applied to the existing projection matrix used by matplotlib, and thanks to the wonderful features of Python, this problem can be solved with a simple oneliner:

<pre><code>ax.get_proj = lambda: np.dot(Axes3D.get_proj(ax), np.diag([scale_x, scale_y, scale_z, 1]))
</code></pre>

where <code>scale_x</code>, <code>scale_y</code> and <code>scale_z</code> are values from 0 to 1 that will re-scale your plot along each of the axes accordingly. <code>ax</code> is simply the 3D axes which can be obtained with <code>ax = fig.gca(projection='3d')</code>

<h3>Explanation</h3>

To explain, the function <code>get_proj</code> of <code>Axes3D</code> generates the projection matrix from the current viewing position. Multiplying it by a scaling matrix:

<pre><code>scale_x, 0, 0
0, scale_y, 0
0, 0, scale_z
0, 0, 1
</code></pre>

includes the scaling into the projection used by the renderer. So, what we are doing here is substituting the original <code>get_proj</code> function with an expression taking the result of the original <code>get_proj</code> and multiplying it by the scaling matrix. 

<h3>Example</h3>

To illustrate the result with the standard parametric function example:

<pre><code>from mpl_toolkits.mplot3d import Axes3D
import numpy as np
import matplotlib.pyplot as plt

fig = plt.figure()
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)

# OUR ONE LINER ADDED HERE:
ax.get_proj = lambda: np.dot(Axes3D.get_proj(ax), np.diag([0.5, 0.5, 1, 1]))

ax.plot(x, y, z)
plt.show()
</code></pre>

for values <code>0.5, 0.5, 1</code>, we get:

<img src="https://i.stack.imgur.com/pFqDp.png" alt="enter image description here">

while for values <code>0.2, 1.0, 0.2</code>, we get:

<img src="https://i.stack.imgur.com/kEReL.png" alt="enter image description here">

blocks|key|317925|text|我在搜索类似的问题时发现了这个。在做了一些实验之后，也许我可以分享一下我的一些前期发现--+here..matplotlib库是巨大的！(我是新来的)请注意，非常类似于这个问题，我想要的是‘视觉’拉伸图表，而不扭曲它。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|317926|背景故事(只显示关键代码片段，以避免对那些熟悉库的人来说不必要的混乱，如果您想要一个可运行的代码，请删除一个注释)：我有三个一维ndarray分别表示X、Y和Z数据点。显然，我不能使用plot_surface+(因为每个暗点都需要2d的ndarray)，所以我选择了非常有用的plot_trisurf：|317927|fig+=+plt.figure()
ax+=+Axes3D(fig)
3d_surf_obj+=+ax.plot_trisurf(X,+Y,+Z_defl,+cmap=cm.jet,linewidth=0,antialiased=True)|code-block|syntax|javascript|317928|​|317929|📷|atomic|offset|length|317930|317931|你可以把这个情节想象成一个浮动的驳船在waves...As中变形，你可以看到，轴的拉伸使得它在视觉上很有欺骗性(注意x在x6上的时间应该比y和>>>>>+z长一倍)。虽然情节点是正确的，但我希望至少在视觉上“伸展”一些东西。我想找个快速解决办法，如果可以的话。长话短说，我发现了一些成功的.‘图形大小’的一般设置(见下面的片段)。|317932|++++matplotlib.rcParams.update({'font.serif':+'Times+New+Roman',
++++++++++++++++++++++++++++++++'font.size':+10.0,
++++++++++++++++++++++++++++++++'axes.labelsize':+'Medium',
++++++++++++++++++++++++++++++++'axes.labelweight':+'normal',
++++++++++++++++++++++++++++++++'axes.linewidth':+0.8,
+++++++++++++++++++++++++++++++++###########################################
+++++++++++++++++++++++++++++++++#+THIS+IS+THE+IMPORTANT+ONE+FOR+STRETCHING
+++++++++++++++++++++++++++++++++#+default+is+[6,4]+but...i+changed+it+to
++++++++++++++++++++++++++++++++'figure.figsize':[15,5]+++#+THIS+ONE+#
++++++++++++++++++++++++++++++})|317933|15,5我得到了类似的..。|317934|317935|317936|317937|很干净！！|317938|所以我开始推动..。在决定在那里定居之前达到了20,6人。|317939|317940|317941|317942|如果你想在视觉上拉伸垂直轴，试着用如下的比例.7,10，在这个案子里.|317943|317944|317945|317946|不太寒酸！|317947|应该是为了视觉能力。|317948|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://developer.qcloudimg.com/http-save/yehe-900000/fb6a86369dea61545600921b6e057e03.png|imageAlt|1|https://developer.qcloudimg.com/http-save/yehe-900000/e5b07c5036e679c4c2cff0fb376bb3fa.png|2|https://developer.qcloudimg.com/http-save/yehe-900000/1da0e768831dcd395f29d6ed117adb2d.png|3|https://developer.qcloudimg.com/http-save/yehe-900000/cc742464cbe411002b2a2a2f801fd38c.png^0|0|0|0|0|0|1|0|0|0|0|0|0|0|0|1|1|0|0|0|0|0|0|1|2|0|0|0|0|0|1|3|0|0|0|0^^$0|@$1|2|3|4|5|6|7|1U|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|1V|8|@]|9|@]|A|$]]|$1|D|3|E|5|F|7|1W|8|@]|9|@]|A|$G|H]]|$1|I|3|J|5|6|7|1X|8|@]|9|@]|A|$]]|$1|K|3|L|5|M|7|1Y|8|@]|9|@$N|1Z|O|20|1|21]]|A|$]]|$1|P|3|J|5|6|7|22|8|@]|9|@]|A|$]]|$1|Q|3|R|5|6|7|23|8|@]|9|@]|A|$]]|$1|S|3|T|5|F|7|24|8|@]|9|@]|A|$G|H]]|$1|U|3|V|5|6|7|25|8|@]|9|@]|A|$]]|$1|W|3|J|5|6|7|26|8|@]|9|@]|A|$]]|$1|X|3|L|5|M|7|27|8|@]|9|@$N|28|O|29|1|2A]]|A|$]]|$1|Y|3|J|5|6|7|2B|8|@]|9|@]|A|$]]|$1|Z|3|10|5|6|7|2C|8|@]|9|@]|A|$]]|$1|11|3|12|5|6|7|2D|8|@]|9|@]|A|$]]|$1|13|3|J|5|6|7|2E|8|@]|9|@]|A|$]]|$1|14|3|L|5|M|7|2F|8|@]|9|@$N|2G|O|2H|1|2I]]|A|$]]|$1|15|3|J|5|6|7|2J|8|@]|9|@]|A|$]]|$1|16|3|17|5|6|7|2K|8|@]|9|@]|A|$]]|$1|18|3|J|5|6|7|2L|8|@]|9|@]|A|$]]|$1|19|3|L|5|M|7|2M|8|@]|9|@$N|2N|O|2O|1|2P]]|A|$]]|$1|1A|3|J|5|6|7|2Q|8|@]|9|@]|A|$]]|$1|1B|3|1C|5|6|7|2R|8|@]|9|@]|A|$]]|$1|1D|3|1E|5|6|7|2S|8|@]|9|@]|A|$]]|$1|1F|3|-4|5|6|7|2T|8|@]|9|@]|A|$]]]|1G|$1H|$5|1I|1J|1K|A|$1L|1M|1N|-4]]|1O|$5|1I|1J|1K|A|$1L|1P|1N|-4]]|1Q|$5|1I|1J|1K|A|$1L|1R|1N|-4]]|1S|$5|1I|1J|1K|A|$1L|1T|1N|-4]]]]

I found this while searching on a similar problem. After experimenting a bit, perhaps I can share some of my prelim findings here..matplotlib library is VAST!! (am a newcomer). Note that quite akin to this question, all i wanted was to 'visually' stretch the chart without distorting it.

Background story (only key code snippets are shown to avoid unnecessary clutter for those who know the library, and if you want a run-able code please drop a comment):
I have three 1-d ndarrays representing the X,Y and Z data points respectively. Clearly I can't use plot_surface (as it requires 2d ndarrays for each dim) so I went for the extremely useful plot_trisurf:

<pre><code>fig = plt.figure()
ax = Axes3D(fig)
3d_surf_obj = ax.plot_trisurf(X, Y, Z_defl, cmap=cm.jet,linewidth=0,antialiased=True)
</code></pre>

<a href="https://i.stack.imgur.com/rjqid.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/rjqid.png" alt="enter image description here"></a>

You can think of the plot like a floating barge deforming in waves...As you can see, the axes stretch make it pretty deceiving visually (note that x is supposed to be at x6 times longer than y and >>>>> z). While the plot points are correct, I wanted something more visually 'stretched' at the very least. Was looking for A QUICK FIX, if I may. Long story cut short, I found a bit of success with...'figure.figsize' general setting (see snippet below). 

<pre><code> matplotlib.rcParams.update({'font.serif': 'Times New Roman',
 'font.size': 10.0,
 'axes.labelsize': 'Medium',
 'axes.labelweight': 'normal',
 'axes.linewidth': 0.8,
 ###########################################
 # THIS IS THE IMPORTANT ONE FOR STRETCHING
 # default is [6,4] but...i changed it to
 'figure.figsize':[15,5] # THIS ONE #
 })
</code></pre>

For [15,5] I got something like...

<a href="https://i.stack.imgur.com/LrAJM.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/LrAJM.png" alt="enter image description here"></a>

Pretty neat!! 

So I started to push it.... and got up to [20,6] before deciding to settle there..

<a href="https://i.stack.imgur.com/IKn4k.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/IKn4k.png" alt="enter image description here"></a>

If you want to try for visually stretching the vertical axis, try with ratios like... [7,10], which in this case gives me ... 

<a href="https://i.stack.imgur.com/qihEf.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/qihEf.png" alt="enter image description here"></a>

Not too shabby ! 

Should do it for visual prowess.

blocks|key|1140571|text|在我的例子中，我想要拉伸z轴2次，以获得更好的点能见度。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1140572|from+mpl_toolkits+import+mplot3d
from+mpl_toolkits.mplot3d+import+Axes3D

import+matplotlib.pyplot+as+plt
#+plt.rcParams["figure.figsize"]+=+(10,200)
#+plt.rcParams["figure.autolayout"]+=+True
ax+=+plt.axes(projection='3d')
ax.set_box_aspect(aspect+=+(1,1,2))

ax.plot(dataX,dataY,dataZ)|code-block|syntax|javascript|1140573|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

In my case I wanted to stretch z-axis 2 times for better point visibility
<pre class="lang-py prettyprint-override"><code>from mpl_toolkits import mplot3d
from mpl_toolkits.mplot3d import Axes3D

import matplotlib.pyplot as plt
# plt.rcParams[&quot;figure.figsize&quot;] = (10,200)
# plt.rcParams[&quot;figure.autolayout&quot;] = True
ax = plt.axes(projection='3d')
ax.set_box_aspect(aspect = (1,1,2))

ax.plot(dataX,dataY,dataZ)
</code></pre>

I have this so far:

<pre><code>x,y,z = data.nonzero() 
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.scatter(x, y, z, zdir='z', c= 'red')
plt.savefig("plot.png")
</code></pre>

Which creates:
<img src="https://i.stack.imgur.com/HKQVl.png" alt="enter image description here">

What I'd like to do is stretch this out to make the Z axis 9 times taller and keep X and Y the same. I'd like to keep the same coordinates though.

So far I tried this guy:

<pre><code>fig = plt.figure(figsize=(4.,35.))
</code></pre>

But that just stretches out the plot.png image.

matplotlib (mplot3d) - how to increase the size of an axis (stretch) in a 3D Plot?

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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到目前为止，我有这样的看法：x,y,z = data.nonzero()    fig = plt.figure()ax = fig.add_subplot(111, projection='3d')ax.scatter(x, y, z, zdir='z', c= 'red')plt.savefig("plot.png...

问matplotlib (mplot3d) --如何在三维图形中增加轴(拉伸)的大小？
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问matplotlib (mplot3d) --如何在三维图形中增加轴(拉伸)的大小？EN