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Comment by aborsy | Hacker News Reader

Nice book. But frankly Tikz and pgfplots are better for scientific visualization, unless your plot is too complex (in which case you have to settle for a lower quality plot).

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TikZ has a steep learning curve and felt so convoluted when I tried to use it.

Great use case for llms?

I would actually be very surprised if that is true. tikz is one of those examples (like e.g. M4 macros or assembly code or OpenSCAD) where producing working code requires significant mental arithmetic. Most skilled humans need to write down intermediate calculations on a piece of paper.

If you don't believe me, look at the "tikz unicorn" of GPT4 demo fame. Then try to replicate that with the currently available "degraded because of safety" GPT4 versions. Then ask yourself how on Earth you could use that to produce publication quality graphics.

I tried the "Draw a unicorn in TiKZ" in chatGPT now, and it actually looks even better than in that paper, and the code is very clean too. Not surprising as the quality of outputs from chatbots have steadily improved in the ~17 months since.

TikZ does have a steep learning curve and can get pretty convoluted, but once you get a hang of it, you have a tremendous amount of control over what you are doing. I sometimes feel like TikZ is more like TeX instead of LaTeX given how primitive it can be, but it can be quite powerful if you give it enough time.

How do you use those outside of Latex? Lots of figures are coming from Matlab or Python, where Latex is a non-starter. Is there a cookbook to pollinate?

You export figure in PDF or some other format.

You can use matplotlib's pgf backend for direct use in latex. That said, not sure I agree that's better for scientific viz. Perhaps in the past. Also tikz/pgf is much more fiddly and has it's limitations too (imho).

Matplotlib is very easy to customize via “style sheets”, so you can make it match any style you want. Note that you can even turn on the “usetex” option and provide a preamble to compile all text/equations via TeX.

No doubt it’s very customizable. But the display quality seems to me not as good as even matlab. At least with defaults, which is a bit barebones. You have to work on it .

The syntax of python is also a bit verbose. Like, why do we need plt.show(), when I plot a figure obviously I want to plot it! Now I know, the point is, see matlab, gnuplot etc.

Compare with the default plot of gnuplot.

The limitation of latex is you can’t do much calculation with data, and memory usage.

Don’t get me wrong, I still sometimes go to python for plotting. But it’s general purpose programming language, and for specific applications there are custom tools.

Don’t get me wrong either – I personally prefer Gnuplot by quite a margin, Matplotlib is indeed too verbose. These days I use Matplotlib more mainly because I use Python more.

I’m just saying that it doesn’t take too much configuration to make publication-quality plots in Matplotlib either, by e.g. enabling the TeX integration and setting up a reusable stylesheet file. The style sheet format is actually very reasonable, and several examples ship with Matplotlib. There’s also the Seaborn package if you want some nicer default stylesheets.

(Side note, the same goes for Gnuplot… As shown by e.g. gnuplotting.org you can definitely create publication-quality plots there as well.)

gnuplot + tikz terminal. I have yet to see better looking figures.

And technically, it's one of the rare if not the only one solution that can give you bibtex resolved citations in figure labels.... (Don't do it, the journals hate it)

> The syntax of python is also a bit verbose. Like, why do we need plt.show(), when I plot a figure obviously I want to plot it!

That is kind of annoying. Fortunately, it's easy to turn that off by activating "interactive mode", in which figures automatically appear when you use a plotting command. You can do this via "plt.ion()", or have it set automatically with

   interactive : True

in your .matplotlibrc file.

Just keep in mind that when you do this, most plots will by default reuse the existing frame without clearing it. So you need to manually call plt.figure() more often (which in my opinion is more logical than plt.show).

There’s also a change in semantics regarding whether the script “hangs” until the user closes the plot window, if I recall correctly.

Or you can call plt.clf() to clear the frame.

I often use Matplotlib within a GUI. It's convenient to be able to defer the display of a plot until it's fully built, for instance if the plot is displaying data in a live update mode.

That's the whole point. It's not at all obvious that you want to show the plot.

It's just as valid to save the plot and use the file in an external document.

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