Python – Creating square subplots (of equal height and width) in matplotlib

matplotlib, python

When I run this code

from pylab import *figure()ax1 = subplot(121)plot([1, 2, 3], [1, 2, 3])subplot(122, sharex=ax1, sharey=ax1)plot([1, 2, 3], [1, 2, 3])draw()show()

I get two subplots which are "squished" in the X-dimension. How do I get these subplots such that the height of the Y-axis equals the width of the X-axis, for both subplots?

I am using matplotlib v.0.99.1.2 on Ubuntu 10.04.

Update 2010-07-08: Let's look at some things that don't work.

After Googling around all day, I thought that it might be related to auto-scaling. So I tried fiddling with that.

from pylab import *figure()ax1 = subplot(121, autoscale_on=False)plot([1, 2, 3], [1, 2, 3])subplot(122, sharex=ax1, sharey=ax1)plot([1, 2, 3], [1, 2, 3])draw()show()

matplotlib insists on auto-scaling.

from pylab import *figure()ax1 = subplot(121, autoscale_on=False)plot([1, 2, 3], [1, 2, 3])subplot(122, sharex=ax1, sharey=ax1, autoscale_on=False)plot([1, 2, 3], [1, 2, 3])draw()show()

In this one, the data completely disappears. WTF, matplotlib? Just WTF?

Okay, well maybe if we fix the aspect ratio?

from pylab import *figure()ax1 = subplot(121, autoscale_on=False)plot([1, 2, 3], [1, 2, 3])axes().set_aspect('equal')subplot(122, sharex=ax1, sharey=ax1)plot([1, 2, 3], [1, 2, 3])draw()show()

This one causes the first subplot to disappear entirely. That's hilarious! Who came up with that one?

In all seriousness, now… should this really be such a hard thing to accomplish?

Best Solution

Your problem in setting the aspect of the plots is coming in when you're using sharex and sharey.

One workaround is to just not used shared axes. For example, you could do this:

from pylab import *figure()subplot(121, aspect='equal')plot([1, 2, 3], [1, 2, 3])subplot(122, aspect='equal')plot([1, 2, 3], [1, 2, 3])show()

However, a better workaround is to change the "adjustable" keywarg... You want adjustable='box', but when you're using shared axes, it has to be adjustable='datalim' (and setting it back to 'box' gives an error).

However, there's a third option for adjustable to handle exactly this case: adjustable="box-forced".

For example:

from pylab import *figure()ax1 = subplot(121, aspect='equal', adjustable='box-forced')plot([1, 2, 3], [1, 2, 3])subplot(122, aspect='equal', adjustable='box-forced', sharex=ax1, sharey=ax1)plot([1, 2, 3], [1, 2, 3])show()

Or in more modern style (note: this part of the answer wouldn't have worked in 2010):

import matplotlib.pyplot as pltfig, axes = plt.subplots(ncols=2, sharex=True, sharey=True)for ax in axes:    ax.plot([1, 2, 3], [1, 2, 3])    ax.set(adjustable='box-forced', aspect='equal')plt.show()

Either way, you'll get something similar to:

enter image description here