pythonmatplotlibcolorbar
matplotlib adjacent subplots: adding colorbar changes size of a subplot
I am trying to plot a figure consisting of 5 x 6 subplots, all of which I want to be adjacent, i.e. share their x and y axes.
I also want to add a colorbar to the rightmost plot in each row, which is normalized for all the subplots in that row.
I add the colorbar using:
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.15)
fig.colorbar(im, cax=cax)
However, adding the colorbar changes the size of the subplot, and it's not sticking to the other subplots any more. Here is a sample output:
How can I get it to not change dimensions when I'm adding a colorbar?
Here is the example for the code that generates the image above:
#!/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
# 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, 3.5*nrows))
axrows = []
i = 1
for r in range(nrows):
axcols = []
for c in range(ncols):
if r > 0:
if c > 0:
axcols.append(fig.add_subplot(nrows, ncols, i,
aspect='equal', sharex=axrows[r-1][c], sharey=axcols[c-1]))
else:
axcols.append(fig.add_subplot(nrows, ncols, i,
aspect='equal', sharex=axrows[r-1][c]))
else:
if c > 0:
axcols.append(fig.add_subplot(nrows, ncols, i,
aspect='equal', sharey=axcols[c-1]))
else:
axcols.append(fig.add_subplot(nrows, ncols, i, aspect='equal'))
i+=1
axrows.append(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)
# only plot colorbar for last column
if col==len(kernels)-1:
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.15)
fig.colorbar(im, cax=cax)
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"$\eta_0$")
fig.suptitle(r"Some title", fontsize=18)
plt.tight_layout(rect=(0, 0, 1, 0.97))
plt.subplots_adjust(wspace=0, hspace=0)
plt.savefig('for_stackexchange.png', dpi=150)
plt.close()
print('finished.')
return
if __name__ == '__main__':
main()
Solution
Indeed, the following the comments from user ImportanceOfBeingErnest and using axes_grid1, I could make it work.
The main difference: For each row, I define a ImageGrid object:
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
And then, at the right place in the code, I add the colorbar with
axcols.cbar_axes[0].colorbar(im)
Here is the full code:
#!/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()
Which produces this image:
