Start your shift as a server.

Congratulations on your first first-author publication in a conference. The topic seems very interesting and I have yet to give the paper a good read-through, but I already like how well-presented it is.

Did you use TikZ for the diagrams and matplotlib for the graphs?

Why aren't their feet covered? Do people really sleep like that?

Awesome, thanks. How are you?

Ooooooooooo

Espresso with tabasco.

Preacher series does not come close to the quality of the source material. The comics are far better than the series, in my opinion.

btop, since I can use vi bindings to move around in it.

I'm already thinking about how to replicate that blue arrow in Fig. 2. It looks very clean. And the patterns in the plots do have a pgfplots vibe to it, so that makes sense.

In case you're not aware, it is also possible to have pgf outputs that preserve scaling with matplotlib with similar serif fonts for the labels that you can specify in matplotlibrc of the project. Hopefully you'd find that useful if you ever decide to use matplotlib beyond some quick plots.

They definitely are, I'm glad you got to get some workout done. Your reply also reminded me to get off my own ass and give some love to my core, so, thank you for that.

3 generous dashes for a shot of double espresso.

Always striving for minimal bloat. Be that on my machines, or my tummy.

Quite a big update. However, some plugins are incompatible with this version (e.g. Zotfile). So if your workflow relies on such plugins, it'd be a good idea to search for equivalent compatible alternatives before updating Zotero.

That colourblind palette is golden, thank you for sharing it. And I was just talking about me wanting have a crack at creating that arrow myself, but thank you for offering to share. I'll be sure to reach out if I find myself being unable to replicate it.

I wasn't even talking about tikzplotlib. It's just that pgf backend is now supported by matplotlib and you can produce pgf files with:

import matplotlib.pyplot as plt
import matplotlib

matplotlib.use('pgf')

fig, ax = plt.subplots()
# Code related to plotting here

fig.savefig("outputfile.pgf")

with relevant rcParams options in matplotlibrc, then import the pgf with:

\begin{figure}[h]
    \centering
      \resizebox{\linewidth}{!}{
        \input{outputfile.pgf}
      }
    \caption{Caption here.}
\end{figure}

But Python -> CSV -> LaTeX/pgf pipeline is quite smooth, for sure. I understand why you'd decide to opt for it without involving too many third-party dependencies.

What's wrong with Surfshark?

BlazBlue: Chronophantasma Extend

Constantine.

DS2 so good you played it twice!

Admittedly I'm quite late with the response, but I've sent you a mail with my own code for Fig. 2. I'm curious to see if this is the approach you had taken while creating yours.

That is a very interesting take. I can't relate to most of the advantages of imperial you mentioned since I've grown up with primarily metric. Exposure to a specific system for a certain period of time lets the mind just acclimate to that system (calculations inclusive), and conversion to imperial just feels like a chore to me. That being said, I can definitely see where you're coming from.

Thank you for this detailed answer.