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LaTeX vs. Unicode

I'm using matplotlib to create figures for my publications. For axes labels, legends, and everything else requiring text and symbols in a figure, I've so far used the excellent LaTeX support of matplotlib, and the results are (obviously) highly satisfactory:


../images/plot_tex.svg

There's a disadvantage, though: there are not too many fonts to chose from. Naively, I thought that this limitation would be lifted if I wouldn't use LaTeX, but Unicode instead:


../images/plot_uc.svg

And wouldn't XeLaTeX even combine the advantages of both?


../images/plot_xetex.svg

As you can see, matplotlib allows you to use any of these options, but what you don't see is that the desired results can be achieved only with a very limited set of fonts. For example, there are only a few fonts that include the unicode character for a 'superscript minus' (for an overview, see here). Sadly, most of these are part of the ClearType Font Collection, which was introduced by Microsoft with Windows Vista. Free fonts with a 'superscript minus' include Dejavu Sans, Free Sans, and Free Serif. If the 'superscript minus' is included instead as a command by employing the internal LaTeX support of matplotlib, many more fonts become accessible. Examples are shown in the table below. But even then one can't make any assumptions: while Source Sans Pro works fine, Source Serif Pro doesn't. I have no idea why.

You see from my last statement that this post in not in the least authoritative. I'm just toddling around, and if you find a better way, I'd appreciate corrections and additions. That's particularly true for the case of XeLaTeX, the use of which seems to require OTF-only fonts with math table support. I wasn't even able to find a single Sans Serif font with this profile :( . Others have similar problems.

Renderer Serif Sans Serif
LaTeX Palatino, Fourier Kurier, CM Bright
Unicode Noto, Gentium Plus Open Sans, Source Sans Pro
XeLaTeX Libertinus, XITS ?

Finally, here's an archive containing the three scripts I've used to create the figures above. In each case, I let matplotlib render a pdf, convert that into an svg by pdftocairo, and compress this svg files by gzip:

./plot_uc.py
pdftocairo -svg plot_uc.pdf plot_uc.svg
gzip -S z plot_uc.svg

The results are compressed scalable vector graphics that are fully compatible with inkscape if a post-processing should be necessary. That's how I got the unicode logo in, by the way. ;)

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