How to adjust padding with cutoff or overlapping labels

Updated MRE with subplots

  • I'm not sure of the usefulness of the original question and MRE. The margin padding seems to be properly adjusted for large x and y labels.
  • The issue is reproducible with subplots.
  • Using matplotlib 3.4.2
fig, axes = plt.subplots(ncols=2, nrows=2, figsize=(8, 6))
axes = axes.flatten()

for ax in axes:
    ax.set_ylabel(r'$\ln\left(\frac{x_a-x_b}{x_a-x_c}\right)$')
    ax.set_xlabel(r'$\ln\left(\frac{x_a-x_d}{x_a-x_e}\right)$')

plt.show()

enter image description here

Original

I am plotting a dataset using matplotlib where I have an xlabel that is quite "tall" (it's a formula rendered in TeX that contains a fraction and is therefore has the height equivalent of a couple of lines of text).

In any case, the bottom of the formula is always cut off when I draw the figures. Changing figure size doesn't seem to help this, and I haven't been able to figure out how to shift the x-axis "up" to make room for the xlabel. Something like that would be a reasonable temporary solution, but what would be nice would be to have a way to make matplotlib recognize automatically that the label is cut off and resize accordingly.

Here's an example of what I mean:

import matplotlib.pyplot as plt

plt.figure()
plt.ylabel(r'$\ln\left(\frac{x_a-x_b}{x_a-x_c}\right)$')
plt.xlabel(r'$\ln\left(\frac{x_a-x_d}{x_a-x_e}\right)$', fontsize=50)
plt.title('Example with matplotlib 3.4.2\nMRE no longer an issue')
plt.show()

enter image description here

The entire ylabel is visible, however, the xlabel is cut off at the bottom.

In the case this is a machine-specific problem, I am running this on OSX 10.6.8 with matplotlib 1.0.0


Solution 1:

Use:

import matplotlib.pyplot as plt

plt.gcf().subplots_adjust(bottom=0.15)

# alternate option without .gcf
plt.subplots_adjust(bottom=0.15)

to make room for the label, where plt.gcf() means get the current figure. plt.gca(), which gets the current Axes, can also be used.

Edit:

Since I gave the answer, matplotlib has added the plt.tight_layout() function.

See matplotlib Tutorials: Tight Layout Guide

So I suggest using it:

fig, axes = plt.subplots(ncols=2, nrows=2, figsize=(8, 6))
axes = axes.flatten()

for ax in axes:
    ax.set_ylabel(r'$\ln\left(\frac{x_a-x_b}{x_a-x_c}\right)$')
    ax.set_xlabel(r'$\ln\left(\frac{x_a-x_d}{x_a-x_e}\right)$')

plt.tight_layout()
plt.show()

enter image description here

Solution 2:

In case you want to store it to a file, you solve it using bbox_inches="tight" argument:

plt.savefig('myfile.png', bbox_inches="tight")

Solution 3:

An easy option is to configure matplotlib to automatically adjust the plot size. It works perfectly for me and I'm not sure why it's not activated by default.

Method 1

Set this in your matplotlibrc file

figure.autolayout : True

See here for more information on customizing the matplotlibrc file: http://matplotlib.org/users/customizing.html

Method 2

Update the rcParams during runtime like this

from matplotlib import rcParams
rcParams.update({'figure.autolayout': True})

The advantage of using this approach is that your code will produce the same graphs on differently-configured machines.

Solution 4:

plt.autoscale() worked for me.