In the previous part of this blog series, an introduction to the bib2gls and glossaries-extra packages for automatically generating glossaries was given. In this last part of the blog series, a neat workflow for creating and integrating vector graphics (e.g., svg graphics) in the thesis document will be presented. This will be done in two steps:

  1. Creating vector graphics in matplotlib.
  2. Integrating the vector graphics in LaTeX with the help of Inkscape

A zipped version of the project can be downloaded here. Compiling the project gives you the following pdf:

Prerequisites

  1. python, matplotlib and numpy must be installed. By installing anaconda, all that is done at once.
  2. Inkscape must be installed and added to the system’s PATH variables (make sure to chose this option during installation).
  3. The following user defined tool must be added in Texstudio: txs:///pdflatex/[--shell-escape] (Preferences > Build > add the command in the lower part of the window and give it a name, such as “svg2tex”)

Creating scientific plots with matplotlib

First, we will add a new folder to the LaTeX project, which contains the Jupyter notebook file that creates the vector graphics. Furthermore, we add a mplstyle file, which contains necessary matplotlib style settings, in the source folder. The final project structure looks as follows:

thesis
│   main.tex
│   refs.bib     
│
└───source
│   │   introduction.tex
│   │   results.tex
│   │   conclusions.tex
│   │   appendix.tex
│   │   acronyms.bib 
│   │   notations.bib
│   │   symbols.bib 
│   │   svg.mplstyle % new: mplstyle file with the necessary matplotlib style settings
│   
└───figures
│   │   jamesWebb.png
│
└───notebooks % new: folder for jupyter notebooks
│   │   plot.ipynb % new: python notebook creating a vector graphic and storing it in the figures folder

First, the vector graphic, that will be integrated in the LaTeX document, has to be generated. This is done in the notebook plot.ipynb, which loads the necessary python packages numpy and matplotlib:

import numpy as np
import matplotlib.pyplot as plt

Futhermore, the pre-defined matplotlib style svg.mplstyle is loaded and used for all plots:

plt.style.use(['file:../source/svg.mplstyle'])

The file svg.mplstyle contains only a few matplotlib settings, that we will need for integrating the vector graphic in the LaTeX document:

# set svg fonttype
svg.fonttype : none

# do not use unicode minus
axes.unicode_minus : False

That’s it. Now, we can create vector graphics and save them in the figures folder:

x = np.linspace(-1, 1, 100) # create vector of inputs
y = x**2 + np.random.normal(0, 0.01, size=len(x)) # create vector of outputs

fig, ax = plt.subplots(figsize=(3,2)) # create figure
ax.plot(x, y) # plot data
ax.set(xlabel='\$x\longrightarrow\$', ylabel='\$f(x)\longrightarrow\$', title='\$f(x) = x^2 + \epsilon, \quad \epsilon \sim N(0, 0.01)\$') # set labels and title
ax.grid() # display a grid

plt.savefig('../figures/plot.svg', format='svg') # save the figure
plt.show() # show the figure

This creates and saves a vector graphic called plot.svg in the figures folder.

In the next step, this svg figure will be further processed by Inkscape to a pdf_tex file and a pdf file, which finally can be integrated in the LaTeX document. How to do this automatically is described in the next section.

Integrating vector graphics in LaTeX

First, the svg package is loaded in the preamble of the main.tex file and a few options are set:

\usepackage{svg}
\svgpath{{figures/}} % tell the svg package where to find the svg files

One very handy feature of integrating vector graphics this way is, that the font can be globally defined for all vector graphics in the entire document. This can be done with the floatrow package. Say we want the fontsize of all vector graphics in the document to be smaller (e.g., footnotesize), than this can be set globally in the preamble:

\usepackage{floatrow} % for global setting of fontsize in floats (tables and figures)
\floatsetup[figure]{font={footnotesize}}

What’s still missing is the actual integration of the vector graphic in the introduction.tex file. This can be done as follows:

\begin{figure}
	\centering
	\includesvg{plot}
	\caption{A sample vector graphic}
	\label{fig:plot}
\end{figure}

That is it! Feel free to try to integrate a second figure and change the fontsize to large and see what happens.

Note, that in order to successfully compile the entire document including the svg file and the nomenclature in TeXstudio, you have to compile in the following order: “svg2tex” user tool > “bib2gls” user tool > F5.

Summary

In this last part of the bolg series, an automated workflow for integrating vector graphics into a LaTeX document was presented. The main takeaways should be:

  1. matplotlib is a free and efficient way of creating svg files that can easily be integrated into a LaTeX document
  2. With the help of the svg and floatrow packages, the fonts of vector graphics can be globally set. This leads to a uniform appearance of all plots and can be handy for late changes.

With this last part of the blog series, I hope I could convince you that writing a thesis in LaTeX is worth the effort and I hope that I could help you to write a beautiful thesis in LaTeX with less pain but more fun!