如何在其中一个地块上绘制共享X轴和多个Y轴的堆积图？

Question

我想修改this example，所以还有第二个图表共享相同的X轴。不幸的是，现在还不清楚如何在这个结构中添加子图。我试图直接结合一个不同的例子，但它只是创建两个数字。

如何将另一个绘图与相同X轴的两个y轴绘图分开？

""" 
Parasite axis demo 

The following code is an example of a parasite axis. It aims to show a user how 
to plot multiple different values onto one single plot. Notice how in this 
example, par1 and par2 are both calling twinx meaning both are tied directly to 
the x-axis. From there, each of those two axis can behave separately from the 
each other, meaning they can take on separate values from themselves as well as 
the x-axis. 
""" 
from mpl_toolkits.axes_grid1 import host_subplot 
import mpl_toolkits.axisartist as AA 
import matplotlib.pyplot as plt 

host = host_subplot(111, axes_class=AA.Axes) 
plt.subplots_adjust(right=0.75) 

par1 = host.twinx() 
par2 = host.twinx() 

offset = 60 
new_fixed_axis = par2.get_grid_helper().new_fixed_axis 
par2.axis["right"] = new_fixed_axis(loc="right", 
            axes=par2, 
            offset=(offset, 0)) 

par2.axis["right"].toggle(all=True) 

host.set_xlim(0, 2) 
host.set_ylim(0, 2) 

host.set_xlabel("Distance") 
host.set_ylabel("Density") 
par1.set_ylabel("Temperature") 
par2.set_ylabel("Velocity") 

p1, = host.plot([0, 1, 2], [0, 1, 2], label="Density") 
p2, = par1.plot([0, 1, 2], [0, 3, 2], label="Temperature") 
p3, = par2.plot([0, 1, 2], [50, 30, 15], label="Velocity") 

par1.set_ylim(0, 4) 
par2.set_ylim(1, 65) 

host.legend() 

host.axis["left"].label.set_color(p1.get_color()) 
par1.axis["right"].label.set_color(p2.get_color()) 
par2.axis["right"].label.set_color(p3.get_color()) 

## Attempts to add stacked plot on top 
f, axarr = plt.subplots(2, sharex=True) 
axarr[1].plot([0,1,2], [5,6,7]) 
axarr[1].set_title('Sharing X axis') 

plt.draw() 
plt.show() 

Answer 1

您可以创建一个新的主机子图并共享x轴。

取代host = host_subplot(111, axes_class=AA.Axes) 与host = host_subplot(211, axes_class=AA.Axes)

与

host2 = host_subplot(212, axes_class=AA.Axes, sharex=host) 
host2.plot([0,1,2], [5,6,7]) 
host2.set_title('Sharing X axis') 
plt.tight_layout() 
plt.draw() 
plt.show() 

这导致更换您的行## Attempts to add stacked plot on top下面的线