Problem

Figures used in publications often consist of multiple panels. Matplotlib provides (amazing, ever-growing) functionality for creating and arranging multiple axes within a figure. When preparing a multi-panel figure for publication, you often need to label each panel so you can reference the individual subplots. It is common to use letters near the upper-left corner of each subplot.

(For an example five-panel figure and caption, see the last figure onhttps://www.internationalscienceediting.com/how-to-write-a-figure-caption/)

While Matplotlib provides much functionality for arranging axes, calling, e.g.,plt.annotate to manually place every panel label is tedious. The Transformations Tutorial showsan example of manually labeling panels. I am not aware of an existing automatic solution.

While not all Matplotlib users are making figures for publication, many are. Given how common it is to label panels for publication figures, I believe it is worth making panel labeling more convenient.

Proposed Solution

I propose adding a convenience functionletter_subplots to Matplotlib that takes a list of axes and adds letters automatically. Automatic lettering supports common journal formats (uppercase bold letters, lowercase letters in parentheses, etc.) or a list of arbitrary letters can be used.

Here is a gist of myletter_subplots:https://gist.github.com/bagrow/e3fd0bcfb7e107c0471d657b98ffc19d

A user can also change the position of labels, even setting a different position for each. Additional keyword arguments are passed toannotate.

I have used this function myself for several years and find it extremely helpful.

Here are some example uses (from the docstring):

Defaults:

>>>fig,axes=plt.subplots(1,3)>>>letter_subplots()# boldfaced A, B, C

Common labeling schemes inferred from the first letter:

>>>fig,axes=plt.subplots(1,4)>>>letter_subplots(letters='(a)')# panels labeled (a), (b), (c), (d)

Fully custom lettering:

>>>fig,axes=plt.subplots(2,1)>>>letter_subplots(axes,letters=['(a.1)','(b.2)'],fontweight='normal')

Per-axis offsets:

>>>fig,axes=plt.subplots(1,2)>>>letter_subplots(axes,xoffset=[-0.1,-0.15])

I understand that choosing the right defaults is critical. I like using uppercase bold letters, but the default should probably be whatever is most common across publications or otherwise determined through the same process as any of Matplotlib's style defaults.