How to have one colorbar for all subplots

Question

I've spent entirely too long researching how to get two subplots to share the same y-axis with a single colorbar shared between the two in Matplotlib.

What was happening was that when I called the colorbar() function in either subplot1 or subplot2, it would autoscale the plot such that the colorbar plus the plot would fit inside the 'subplot' bounding box, causing the two side-by-side plots to be two very different sizes.

To get around this, I tried to create a third subplot which I then hacked to render no plot with just a colorbar present. The only problem is, now the heights and widths of the two plots are uneven, and I can't figure out how to make it look okay.

Here is my code:

from __future__ import division import matplotlib.pyplot as plt import numpy as np from matplotlib import patches from matplotlib.ticker import NullFormatter  # SIS Functions TE = 1 # Einstein radius g1 = lambda x,y: (TE/2) * (y**2-x**2)/((x**2+y**2)**(3/2))  g2 = lambda x,y: -1*TE*x*y / ((x**2+y**2)**(3/2)) kappa = lambda x,y: TE / (2*np.sqrt(x**2+y**2))  coords = np.linspace(-2,2,400) X,Y = np.meshgrid(coords,coords) g1out = g1(X,Y) g2out = g2(X,Y) kappaout = kappa(X,Y) for i in range(len(coords)):     for j in range(len(coords)):         if np.sqrt(coords[i]**2+coords[j]**2) <= TE:             g1out[i][j]=0             g2out[i][j]=0  fig = plt.figure() fig.subplots_adjust(wspace=0,hspace=0)  # subplot number 1 ax1 = fig.add_subplot(1,2,1,aspect='equal',xlim=[-2,2],ylim=[-2,2]) plt.title(r"$\gamma_{1}$",fontsize="18") plt.xlabel(r"x ($\theta_{E}$)",fontsize="15") plt.ylabel(r"y ($\theta_{E}$)",rotation='horizontal',fontsize="15") plt.xticks([-2.0,-1.5,-1.0,-0.5,0,0.5,1.0,1.5]) plt.xticks([-2.0,-1.5,-1.0,-0.5,0,0.5,1.0,1.5]) plt.imshow(g1out,extent=(-2,2,-2,2)) plt.axhline(y=0,linewidth=2,color='k',linestyle="--") plt.axvline(x=0,linewidth=2,color='k',linestyle="--") e1 = patches.Ellipse((0,0),2,2,color='white') ax1.add_patch(e1)  # subplot number 2 ax2 = fig.add_subplot(1,2,2,sharey=ax1,xlim=[-2,2],ylim=[-2,2]) plt.title(r"$\gamma_{2}$",fontsize="18") plt.xlabel(r"x ($\theta_{E}$)",fontsize="15") ax2.yaxis.set_major_formatter( NullFormatter() ) plt.axhline(y=0,linewidth=2,color='k',linestyle="--") plt.axvline(x=0,linewidth=2,color='k',linestyle="--") plt.imshow(g2out,extent=(-2,2,-2,2)) e2 = patches.Ellipse((0,0),2,2,color='white') ax2.add_patch(e2)  # subplot for colorbar ax3 = fig.add_subplot(1,1,1) ax3.axis('off') cbar = plt.colorbar(ax=ax2)  plt.show() 

Answer 1

Just place the colorbar in its own axis and use subplots_adjust to make room for it.

As a quick example:

import numpy as np import matplotlib.pyplot as plt  fig, axes = plt.subplots(nrows=2, ncols=2) for ax in axes.flat:     im = ax.imshow(np.random.random((10,10)), vmin=0, vmax=1)  fig.subplots_adjust(right=0.8) cbar_ax = fig.add_axes([0.85, 0.15, 0.05, 0.7]) fig.colorbar(im, cax=cbar_ax)  plt.show() 

Note that the color range will be set by the last image plotted (that gave rise to im) even if the range of values is set by vmin and vmax. If another plot has, for example, a higher max value, points with higher values than the max of im will show in uniform color.