实际上，以下来自用户ImportanceOfBeingErnest的注释并使用axes_grid1，我可以使它工作。

主要区别：对于每一行，我定义一个ImageGrid对象：

axrows = [[] for r in range(nrows)]

i = 0

for r in range(nrows):

axcols = [None for c in range(ncols)]

axcols = ImageGrid(fig, (nrows, 1, r+1),

nrows_ncols=(1, ncols),

axes_pad = 0.0,

share_all = True,

label_mode = 'L',

cbar_mode = 'edge',

cbar_location = 'right',

cbar_size = "7%",

cbar_pad = "2%")

axrows[r] = axcols

然后，在代码中的正确位置，我添加了颜色条

axcols.cbar_axes[0].colorbar(im)

这是完整的代码：

#!/usr/bin/env python3

import numpy as np

import matplotlib.pyplot as plt

import matplotlib.colors

from mpl_toolkits.axes_grid1 import make_axes_locatable, axes_size

from mpl_toolkits.axes_grid1 import ImageGrid

# border limits for plots

lowlim = 0.43

uplim = 0.52

nx = 10

kernels = ['cubic_spline', 'quintic_spline',

'wendland_C2', 'wendland_C4', 'wendland_C6']

#========================

def main():

#========================

eta_facts = [ 0, 1, 2, 3, 4, 5 ]

nrows = len(eta_facts)

ncols = len(kernels)

Ay_list = [[None for c in range(ncols)] for r in range(nrows)]

#--------------------------------

# Loop and compute As

#--------------------------------

dx = (uplim - lowlim)/nx

for row, eta in enumerate(eta_facts):

for col, kernel in enumerate(kernels):

A = np.zeros((nx, nx), dtype=np.float)

for i in range(nx):

for j in range(nx):

A[j,i] = row + np.random.random()/10 # not a typo: need A[j,i] for imshow

Ay_list[row][col] = A

#------------------------------------

# Now plot it

#------------------------------------

fig = plt.figure(figsize=(3.5*ncols+1, 3.5*nrows))

axrows = [[] for r in range(nrows)]

i = 0

for r in range(nrows):

axcols = [None for c in range(ncols)]

axcols = ImageGrid(fig, (nrows, 1, r+1),

nrows_ncols=(1, ncols),

axes_pad = 0.0,

share_all = True,

label_mode = 'L',

cbar_mode = 'edge',

cbar_location = 'right',

cbar_size = "7%",

cbar_pad = "2%")

axrows[r] = axcols

cmap = 'YlGnBu_r'

lw = 2

for row in range(nrows):

axcols = axrows[row]

minval = min([np.min(Ay_list[row][c]) for c in range(ncols)])

maxval = max([np.max(Ay_list[row][c]) for c in range(ncols)])

for col, ax in enumerate(axcols):

im = ax.imshow(Ay_list[row][col], origin='lower',

vmin=minval, vmax=maxval, cmap=cmap,

extent=(lowlim, uplim, lowlim, uplim),

# norm=matplotlib.colors.SymLogNorm(1e-3),

zorder=1)

ax.set_xlim((lowlim,uplim))

ax.set_ylim((lowlim,uplim))

# cosmetics

if col > 0:

left = False

else:

left = True

if row == len(eta_facts)-1 :

bottom = True

else:

bottom = False

ax.tick_params(

axis='both', # changes apply to the x-axis

which='both', # both major and minor ticks are affected

bottom=bottom, # ticks along the bottom edge are off

top=False, # ticks along the top edge are off

left=left, # ticks along the left edge are off

right=False, # ticks along the rigt edge are off

labelbottom=bottom, # labels along the bottom edge are off

labeltop=False, # labels along the top edge are off

labelleft=left, # labels along the left edge are off

labelright=False) # labels along the right edge are off

if row==0:

ax.set_title(kernels[col] + ' kernel', fontsize=14)

if col==0:

ax.set_ylabel(r"$\eta = $ "+str(eta_facts[row])+r"$\eta_0$")

axcols.cbar_axes[0].colorbar(im)

fig.suptitle(r"Some title", fontsize=18)

plt.tight_layout(rect=(0, 0, 1, 0.97))

plt.subplots_adjust(wspace=0.0, hspace=0.0)

plt.savefig('for_stackexchange.png', dpi=150)

plt.close()

print('finished.')

return

if __name__ == '__main__':

main()

哪个产生这个图像：