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() 

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() 

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

8 Answers

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() 

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") 

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:

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.

plt.autoscale() worked for me.

You can also set custom padding as defaults in your $HOME/.matplotlib/matplotlib_rc as follows. In the example below I have modified both the bottom and left out-of-the-box padding:

# The figure subplot parameters. All dimensions are a fraction of the # figure width or height figure.subplot.left : 0.1 #left side of the subplots of the figure #figure.subplot.right : 0.9 figure.subplot.bottom : 0.15 ... 

There is also a way to do this using the OOP interface, applying tight_layout directly to a figure:

fig, ax = plt.subplots() fig.set_tight_layout(True) 

for some reason sharex was set to True so I turned it back to False and it worked fine.

df.plot(........,sharex=False) 

You need to use sizzors to modify the axis-range:

import sizzors as sizzors_module sizzors_module.reshape_the_axis(plt).save("literlymylief.tiff")