title: How to use sharex and sharey combined with aspect=equal and adjustable='box-forced' to create subplots with the same scale in matplotlib?
body: <p>I'm trying to create four subplots, whose axes represent different range of distances [km] in different directions, except for the x-axis of the lower right subplot that represents counts. All the axes of distance should have the same scale in all the subplots. Also, the two subplots on the top should share their y-axes and the two subplots on the left should share their x-axes. </p>
  
  <p>Following this <a href="https://github.com/matplotlib/matplotlib/issues/7621" rel="nofollow noreferrer">issue</a> (whose solution works well for equal limits in x and y axes), I have tried several combinations of the sharex, sharey, aspect, and adjustable, parameters without success.</p>
  
  <p>Is there a way to achieve this kind of plot, in particular without affecting any of the axis limits?</p>
  
  <p>Here is my MCVE:</p>
  
  <pre><code>import matplotlib.pyplot as plt
  lim1 = [0.,30.]
  lim2 = [0.,15.]
  lim3 = [0.,75.]
  lim4 = [0,5]
  xdat = [12.,25.]
  ydat = [6.,12.]
  zdat = [50.,25.]
  cdat = [1,1]
  fig = plt.figure()
  ax1 = plt.subplot(221,aspect='equal',adjustable='box-forced')
  ax1.plot(xdat,ydat,'o')
  ax1.set_xlim(lim1)
  ax1.set_ylim(lim2)
  ax2 = plt.subplot(222,aspect='equal',adjustable='box-forced',sharey=ax1)
  ax2.plot(zdat,ydat,'o') 
  ax2.set_xlim(lim3)
  ax3 = plt.subplot(223,aspect='equal',adjustable='box-forced',sharex=ax1)
  ax3.plot(xdat,zdat,'o')
  ax3.set_ylim(lim3)
  ax4 = plt.subplot(224)
  ax4.plot(cdat,zdat,'o')
  ax4.set_xlim(lim4)
  ax4.set_ylim(lim3)
  plt.show()
  </code></pre>
  
  <p>I would like to get something like the plot in the image below, that shows the axes shared as I mentioned above, keeping the original axis limits and the same scale on the different axes of distance.   </p>
  
  <p><img src="https://i.stack.imgur.com/TKqPh.png" alt="image"></p>
  
  <p>I'm currently using:<br>
  Platform: Linux Ubuntu 14.04.5 LTS<br>
  matplotlib: 1.5.1<br>
  python: 2.7.14</p>