将子图与颜色栏对齐

Question

I am trying to share the x-axis of a imshow that have to be square and a classique plot:

1. the imshow has to be square
2. with a colorbar
3. the plot bellow should share the same axis (or at least look like align with the imshow)

I spent two days on it, and now I am crazy. Did someone know how to align them ?

The code used to produce the image is bellow.

def myplot( Nbin=20 ):

X = np.random.rand(1000)
Y = np.random.rand(1000)
h2, yh2, xh2 = np.histogram2d( Y, X, bins=[Nbin,Nbin] )
h1, xh1 = np.histogram( X, bins=Nbin )
######################################
######################################
fig = plt.figure(  )
gs = gridspec.GridSpec( 3, 2 )
######################################
######################################
ax1 = plt.subplot( gs[:-1,:] )
im = plt.imshow( h2, interpolation='nearest', origin='lower',
                 extent=[xh2[0],xh2[-1],yh2[0],yh2[-1]] )
cb = plt.colorbar( im, ax=ax1 )
plt.xlim( xh1[0], xh1[-1] )
plt.ylim( xh1[0], xh1[-1] )
ax1.tick_params( axis='x', which='both', bottom='on', top='on', labelbottom='off' )
######################################
######################################
ax2 = plt.subplot( gs[-1,:] )
plt.plot( xh1[:-1] + np.diff(xh1)/2., h1 )
plt.xlim( xh1[0], xh1[-1] )
cm = plt.cm.Blues
cb2 = plt.colorbar( ax=ax2 )
ax2.tick_params( axis='x', which='both', bottom='on', top='on', labelbottom='on' )
######################################
######################################
fig.tight_layout()
fig.subplots_adjust(hspace=0.05)
cb2.ax.set_visible(False)

Answer 1

I could imagine that the easiest way to have the second axes directly below the image is to use mpl_toolkits.axes_grid1.make_axes_locatable . This allows to shrink the image at the expense of the newly created subplot and can equally be used to position the colorbar.

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable

Nbin=20

X = np.random.rand(1000)
Y = np.random.rand(1000)
h2, yh2, xh2 = np.histogram2d( Y, X, bins=[Nbin,Nbin] )
h1, xh1 = np.histogram( X, bins=Nbin )

fig = plt.figure(  )


ax1 = plt.subplot(111)
im = ax1.imshow( h2, interpolation='nearest', origin='lower',
                 extent=[xh2[0],xh2[-1],yh2[0],yh2[-1]] )

plt.xlim( xh1[0], xh1[-1] )
plt.ylim( xh1[0], xh1[-1] )
ax1.tick_params( axis='x', which='both', bottom='on', top='on', labelbottom='off' )


divider = make_axes_locatable(ax1)
ax2 = divider.append_axes("bottom", size="50%", pad=0.08)
cax = divider.append_axes("right", size="5%", pad=0.08)
cb = plt.colorbar( im, ax=ax1, cax=cax )

#ax2 = plt.subplot( gs[-1,:] )  # , sharex=ax1
ax2.plot( xh1[:-1] + np.diff(xh1)/2., h1 )
ax2.set_xlim( xh1[0], xh1[-1] )
cm = plt.cm.Blues

ax2.tick_params( axis='x', which='both', bottom='on', top='on', labelbottom='on' )

plt.show()