Auto-scaling of extent not working for subplots when using sharex and sharey

[michaelaye]

Using MPL 1.1.0 from the 32-bit EPD 7.3-2 on a Macbook Pro Retina.

This error only shows when using subplots. When creating your own sublots via add_subplot it does not seem to occur.

from matplotlib.pyplot import show, subplots
from numpy import arange, array

arr = arange(10000).reshape(100,100)
l = [arr,arr,arr,arr]
narr = array(l)

fig, axes = subplots(2,2,sharex=True,sharey=True)

for ax,im in zip(axes.flatten(),narr):
    ax.imshow(im)

show()

Expected vs Seen:

One can see that all the 4 axes show the image array with an extent of [-10,110, 0, 100] here instead of the expected intent of [0,100, 0, 100].

[dmcdougall]

Thanks for this @michaelaye. Apologies for the messy advice on the mailing list. Did you manage to get the workaround functional?

Hopefully this can get some visibility before the 1.2 release.

Thanks again.

[michaelaye]

Not really (see feedback on the mailing list.) Your example that way fails to set the extent as well. So I will add it here as another way to reproduce.

[michaelaye]

The following code with the setting of an extent at the end fails to work for me as well. As a side, it also does not share the x and y axis.

import matplotlib.pyplot as plt
from numpy import arange, array

arr = arange(10000).reshape(100,100)
l = [arr,arr,arr,arr]
narr = array(l)

axes = []
fig = plt.figure()
for i in range(4):
    if i == 0:
        axes.append(fig.add_subplot(2, 2, i))
    if i > 0:
        axes.append(fig.add_subplot(2, 2, i, sharex=axes[0], sharey=axes[0]))

for ax, im in zip(axes, narr):
    ax.imshow(im, extent=[0,100,0,100])

plt.show()

[dmcdougall]

The sharing is working for me, but the extent isn't set right in that example either. Actually, that example is diagnostically helpful. Cheers for posting it.

[leejjoon]

shared_axes and aspect=1 does not play along well . If both parameters are set, matplotlib changes the adjustable parameter to "datalim" (default is "box"). And when the aspect is applied during the drawing time, it changes the data-limits (not box size).

If you have both x- and -y axes are shared and all the shared axes have aspect=1, you can change the adjustable to "box-forced" which will work as expected.

for ax,im in zip(axes.flatten(),narr):
    ax.set_adjustable("box-forced")
    ax.imshow(im)

[pelson]

@michaelaye - did @leejjoon 's suggestion work for you?

[tacaswell]

Punting this to (at least) 1.4.x as this is an issue with too many constraints on the limits not playing nice with each other/having unclear precedence/hysteresis.

[michaelaye]

Sorry for not having answered above. @leejjoon 's workaround does work for me, even showing the sharing of the axes work. I don't remember why we had such a inflated example though. These days I would just do:

fig, axes = subplots(nrows=2, ncols=2, sharex=True, sharey=True)
arr = arange(10000).reshape(100,100)
for ax in axes.flatten():
    ax.set_adjustable('box-forced')
    ax.imshow(arr)
show()

Was there no subplots available in Oct 2012? Time flies...

Edit: Ah, my bad. it was the distinction between subplots and add_subplot that was the essence of this bug in the first place.

[tacaswell]

Closing as the set_adjustable fixes the problem and the default behavior looks like a feature not a bug.