How to share x axes of two subplots after they have been created?
The usual way to share axes is to create the shared properties at creation. Either
fig=plt.figure()
ax1 = plt.subplot(211)
ax2 = plt.subplot(212, sharex = ax1)
or
fig, (ax1, ax2) = plt.subplots(nrows=2, sharex=True)
Sharing the axes after they have been created should therefore not be necessary.
However if for any reason, you need to share axes after they have been created (actually, using a different library which creates some subplots, like here might be a reason), there would still be a solution:
Using
ax1.get_shared_x_axes().join(ax1, ax2)
creates a link between the two axes, ax1
and ax2
. In contrast to the sharing at creation time, you will have to set the xticklabels off manually for one of the axes (in case that is wanted).
A complete example:
import numpy as np
import matplotlib.pyplot as plt
t= np.arange(1000)/100.
x = np.sin(2*np.pi*10*t)
y = np.cos(2*np.pi*10*t)
fig=plt.figure()
ax1 = plt.subplot(211)
ax2 = plt.subplot(212)
ax1.plot(t,x)
ax2.plot(t,y)
ax1.get_shared_x_axes().join(ax1, ax2)
ax1.set_xticklabels([])
# ax2.autoscale() ## call autoscale if needed
plt.show()
The other answer has code for dealing with a list of axes:
axes[0].get_shared_x_axes().join(axes[0], *axes[1:])
Just to add to ImportanceOfBeingErnest's answer above:
If you have an entire list
of axes objects, you can pass them all at once and have their axes shared by unpacking the list like so:
ax_list = [ax1, ax2, ... axn] #< your axes objects
ax_list[0].get_shared_x_axes().join(ax_list[0], *ax_list)
The above will link all of them together. Of course, you can get creative and sub-set your list
to link only some of them.
Note:
In order to have all axes
linked together, you do have to include the first element of the axes_list
in the call, despite the fact that you are invoking .get_shared_x_axes()
on the first element to start with!
So doing this, which would certainly appear logical:
ax_list[0].get_shared_x_axes().join(ax_list[0], *ax_list[1:])
... will result in linking all axes
objects together except the first one, which will remain entirely independent from the others.
As of Matplotlib v3.3 there now exist Axes.sharex
, Axes.sharey
methods:
ax1.sharex(ax2)
ax1.sharey(ax3)