matplotlib - How can I use MaxNLocator and specify a number which has to be in an axis?

Question

I do have a question with matplotlib in python. I create different figures, where every figure should have the same height to print them in a publication/poster next to each other.

If the y-axis has a label on the very top, this shrinks the height of the box with the plot. So I use MaxNLocator to remove the upper and lower y-tick. In some plots, I want to have the 1.0 as a number on the y-axis, because I have normalized data. So I need a solution, which expands in these cases the y-axis and ensures 1.0 is a y-Tick, but does not corrupt the size of the figure using tight_layout().

Here is a minimal example:

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import MaxNLocator

x = np.linspace(0,1,num=11)
y = np.linspace(1,.42,num=11)

fig,axs = plt.subplots(1,1)
axs.plot(x,y)

locator=MaxNLocator(prune='both',nbins=5)
axs.yaxis.set_major_locator(locator)

plt.tight_layout()

fig.show()

Here is a link to a example-pdf, which shows the problems with height of upper boxline.

I tried to work with adjust_subplots() but this is of no use for me, because I vary the size of the figures and want to have same the font size all the time, which changes the margins.

Question is:

How can I use MaxNLocator and specify a number which has to be in the y-axis?

Hopefully someone of you has some advice.

Greetings, Laenan

Answer 1

Assuming that you know in advance how many plots there will be in 1 row on a page one way to solve this would be to put all those plots into one figure - matplotlib will make sure they are aligned on axes:

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import MaxNLocator

x = np.linspace(0, 1, num=11)
y = np.linspace(1, .42, num=11)

fig, (ax1, ax2) = plt.subplots(1,2, figsize=(8,3), gridspec_kw={'wspace':.2})
ax1.plot(x,y)
ax2.plot(x,y)

locator=MaxNLocator(prune='both', nbins=5)
ax1.yaxis.set_major_locator(locator)

# You don't need to use tight_layout and using it might give an error
# plt.tight_layout()  

fig.show()