如何在其他子图中绘制Contourf Colorbar-Matplotlib

Question

This is a very similar question to "How to plot pcolor colorbar in a different subplot - matplotlib" . I am trying to plot a filled contour plot and a line plot with a shared axis and the colorbar in a separate subplot (ie so it doesn't take up space for the contourf axis and thus muck up the x-axis sharing). However, the x-axis in my code does not rescale nicely:

import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt

z = np.random.rand(20, 20)
x, y = np.arange(20), np.arange(20)
y2 = np.random.rand(20)
fig = plt.figure(figsize=(8, 8))
gs = mpl.gridspec.GridSpec(2, 2, height_ratios=[1, 2], width_ratios=[2, 1])
ax1 = fig.add_subplot(gs[1, 0])
ax2 = fig.add_subplot(gs[0, 0], sharex=ax1)
ax3 = fig.add_subplot(gs[1, 1])
cont = ax1.contourf(x, y, z, 20)
plt.tick_params(which='both', top=False, right=False)
ax2.plot(x, y2, color='g')
plt.tick_params(which='both', top=False, right=False)
cbar = plt.colorbar(cont, cax=ax3)
cbar.set_label('Intensity', rotation=270, labelpad=20)
plt.tight_layout()
plt.show()

which produces an x-axis scaled from 0 to 20 (inclusive) rather than 0 to 19, which means there is unsightly whitespace in the filled contour plot. Commenting out the sharex=ax1 in the above code means that the x-axis for the contour plot is scaled nicely, but not for the line plot above it and the plt.tick_params code has no effect on either axis.

Is there a way of solving this?

Answer 1

You could also turn off the autoscaling of x-axis for all subsequent call of plot on this axis so that it keeps the range set by contourf and sharex=True :

ax2.set_autoscalex_on(False)

This comes even before your call to ax2.plot() and I think it is better than calling ax2.set_xlim(0, 19) since you do not need to know what are the actual limit of your x-axis that may be needed.

---

import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1.inset_locator import inset_axes

z = np.random.rand(20, 20)
x, y = np.arange(20), np.arange(20)
y2 = np.random.rand(20)
fig = plt.figure(figsize=(8, 8))
gs = mpl.gridspec.GridSpec(2, 1, height_ratios=[1, 2], width_ratios=[2,
1])
ax1 = fig.add_subplot(gs[1, 0])
ax2 = fig.add_subplot(gs[0, 0], sharex=ax1)
cont = ax1.contourf(x, y, z, 20)
plt.tick_params(which='both', top=False, right=False)

ax2.set_autoscalex_on(False)
ax2.plot(x, y2, color='g')

axins = inset_axes(ax1,
           width="5%", # width = 10% of parent_bbox width
           height="100%", # height : 50%
           loc=6,
           bbox_to_anchor=(1.05, 0., 1, 1),
           bbox_transform=ax1.transAxes,
           borderpad=0,
       )

cbar = plt.colorbar(cont, cax=axins)
plt.show()

Answer 2

You can use inset_axes for this without added another axis.

import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1.inset_locator import inset_axes

z = np.random.rand(20, 20)
x, y = np.arange(20), np.arange(20)
y2 = np.random.rand(20)
fig = plt.figure(figsize=(8, 8))
gs = mpl.gridspec.GridSpec(2, 2, height_ratios=[1, 2], width_ratios=[2, 1])
ax1 = fig.add_subplot(gs[1, 0])
ax2 = fig.add_subplot(gs[0, 0], sharex=ax1)
cont = ax1.contourf(x, y, z, 20)
plt.tick_params(which='both', top=False, right=False)
ax2.plot(x, y2, color='g')
plt.tick_params(which='both', top=False, right=False)




axins = inset_axes(ax1,
               width="5%", # width = 10% of parent_bbox width
               height="100%", # height : 50%
               loc=6,
               bbox_to_anchor=(1.05, 0., 1, 1),
               bbox_transform=ax1.transAxes,
               borderpad=0,
           )

cbar = plt.colorbar(cont, cax=axins)
plt.savefig('figure.jpg',bbox_inches='tight',dpi=200)