Matplotlib

4.1 Proplot

Why proplot?

Matplotlib is an extremely versatile plotting package used by scientists and engineers far and wide. However, matplotlib can be cumbersome or repetitive for users who…

• Make highly complex figures with many subplots.

• Want to finely tune their annotations and aesthetics.

• Need to make new figures nearly every day.

Proplot’s core mission is to provide a smoother plotting experience for matplotlib’s most demanding users. We accomplish this by expanding upon matplotlib’s object-oriented interface. Proplot makes changes that would be hard to justify or difficult to incorporate into matplotlib itself, owing to differing design choices and backwards compatibility considerations.

This page enumerates these changes and explains how they address the limitations of matplotlib’s default interface. To start using these features, see the usage introduction and the user guide.

4.2 seaborn.objects

The next-generation seaborn interface attempts to achieve a pythonic equivalent to ggplot, at least somewhat:

as seaborn has become more powerful, one has to write increasing amounts of matpotlib code to recreate what it is doing.

So the goal is to expose seaborn’s core features — integration with pandas, automatic mapping between data and graphics, statistical transformations — within an interface that is more compositional, extensible, and comprehensive.

One will note that the result looks a bit (a lot?) like ggplot. That’s not unintentional, but the goal is also not to “port ggplot2 to Python”. (If that’s what you’re looking for, check out the very nice plotnine package). There is an immense amount of wisdom in the grammar of graphics and in its particular implementation as ggplot2. But I think that, as languages, R and Python are just too different for idioms from one to feel natural when translated literally into the other. So while I have taken much inspiration from ggplot, I’ve also made plenty of choices differently, for better or for worse.

UPDATE this has been released.

• The seaborn.objects interface tutorial
• Joshua Ebner, How to Make a Seaborn Lineplot
• Joshua Ebner, A Quick Introduction to the Seaborn Objects System

4.3 plotnine

Plotnine implements a best-effort clone of R’s ggplot2 library for matplotlib I believe plotnine supersedes the abandoned(?) ggplot.py by yhat (ggplot source, plotnine source).

5.1 Margins on saved graphics are too large

plt.savefig("image.png", dpi=300, bbox_inches='tight', pad_inches=0)

5.2 Axis labels

Suppressing?

ax = plt.gca()
ax.axes.xaxis.set_visible(False)
ax.axes.yaxis.set_visible(False)

8.1 Help matplotlib cannot find my font

Corrupt font cache? Some places we see this advice

import matplotlib.font_manager as fm
fm._rebuild()

That does not work for me as of matplotlib 3.6. What does is finding the path thusly:

import matplotlib
matplotlib.get_cachedir()

and then removing it with rm -rf. Still cannot find that fint? what if you are on the HPC?

Harriet Alexander advises setting up truetype fonts properly.

8.2 tikzplotlib

Agustinus Kristiadi, in The Last Mile of Creating Publication-Ready Plots introduces texworld/tikzplotlib,, which is a tikz plotting backend; why do we want this? For one, it can match fonts to the parent document.

8.3 Basic font stuff

Someone made the idiosyncratic choice that default font is sans serif, even for mathematical text. You can change this by setting serif fonts also for mathtext.

from matplotlib import rc
rc(
  'font',
  family='serif',
  serif=['Palatino']
)
rc(
  'mathtext',
  fontset='dejavuserif'
)

Supported math fonts are reputedly

• dejavusans (the horrible default)
• dejavuserif (beware of odd greek letters)
• cm (“Computer Modern”. Classic, dated.)
• stix (modern serif, looks OK)
• stixsans (sounds like sans serif to me)

I am not aware of any publications which use those fonts in their style guides, but the difference between, say Deja Vu Serif and Times New Roman is small enough that only font nerds notice.

Alternatively I can render graph labels with TeX which leads to some weird spacing but allows me to match fonts better. It is also fragile and character set issues are terrible. Are these problems eased if I use XeLaTeX/LuaLaTeX?

Further suggestion: Automate these selection problems away using TUEplots.

TUEplots is a light-weight matplotlib extension that adapts your figure sizes to formats more suitable for scientific publications. It produces configurations that are compatible with matplotlib’s rcParams, and provides fonts, figure sizes, font sizes, color schemes, and more, for a number of publication formats.

import matplotlib.pyplot as plt

from tueplots import bundles

bundles.icml2022()
{'text.usetex': True, 'font.family': 'serif', 'text.latex.preamble': '\\usepackage{times} ', 'figure.figsize': (3.25, 2.0086104634371584), 'figure.constrained_layout.use': True, 'figure.autolayout': False, 'savefig.bbox': 'tight', 'savefig.pad_inches': 0.015, 'font.size': 8, 'axes.labelsize': 8, 'legend.fontsize': 6, 'xtick.labelsize': 6, 'ytick.labelsize': 6, 'axes.titlesize': 8}

# Plug any of those into either the rcParams or into an rc_context:

with plt.rc_context(bundles.icml2022()):
    pass

I am indebted to my colleague Christian Walder for suggesting the following as a reliable initialisation procedure for matplotlib plotting with equations.

import matplotlib
import sys, os

# GTK GTKAgg GTKCairo MacOSX Qt4Agg TkAgg WX WXAgg CocoaAgg
# GTK3Cairo GTK3Agg WebAgg agg cairo emf gdk pdf pgf ps svg template

is_mac = sys.platform == 'darwin'
if is_mac:
    _matplotlib_backend = 'MacOSX'
else:
    _matplotlib_backend = 'pdf'

matplotlib.rcParams['svg.fonttype'] = 'none'
matplotlib.rcParams['backend'] = _matplotlib_backend
matplotlib.rcParams['mathtext.fontset'] = 'stix'
matplotlib.rcParams['font.family'] = 'Times New Roman'

matplotlib.use(_matplotlib_backend)
import matplotlib.pyplot as plt
import matplotlib as mpl

plt.switch_backend(_matplotlib_backend)
# print(matplotlib.pyplot.get_backend())
try:
    import cairocffi as cairo
except:
    pass
    # logging.warning('import cairocffi failed')

_latex_preamble = [
    r'\usepackage{amsmath,bm}',
    r'\newcommand\what{\hat{\bm{w}}}',
    r'\newcommand\tr{^\top}',
    r'\newcommand\dt[1]{\left|#1\right|}',]

_latex_path = '/Library/TeX/texbin/'


def use_latex_mpl(
        latex_path=_latex_path,
        latex_preamble=_latex_preamble):
    mpl.rcParams['text.usetex'] = True
    mpl.rcParams['text.latex.preamble'] = latex_preamble
    if latex_path is not None:
        os.environ['PATH'] = '%s:%s' % (os.environ['PATH'], latex_path)