matplot2tikz

The artist formerly known as tikzplotlib.

This is matplot2tikz, a Python tool for converting matplotlib figures into PGFPlots (PGF/TikZ) figures like

for native inclusion into LaTeX or ConTeXt documents.

The output of matplot2tikz is in PGFPlots, a TeX library that sits on top of PGF/TikZ and describes graphs in terms of axes, data etc. Consequently, the output of matplot2tikz

• retains more information,
• can be more easily understood, and
• is more easily editable

than raw TikZ output. For example, the matplotlib figure

import matplotlib.pyplot as plt
import numpy as np

plt.style.use("ggplot")

t = np.arange(0.0, 2.0, 0.1)
s = np.sin(2 * np.pi * t)
s2 = np.cos(2 * np.pi * t)
plt.plot(t, s, "o-", lw=4.1)
plt.plot(t, s2, "o-", lw=4.1)
plt.xlabel("time (s)")
plt.ylabel("Voltage (mV)")
plt.title("Simple plot $\\frac{\\alpha}{2}$")
plt.grid(True)

import matplot2tikz

matplot2tikz.save("test.tex")

--> (see above) gives

\begin{tikzpicture}

\definecolor{chocolate2267451}{RGB}{226,74,51}
\definecolor{dimgray85}{RGB}{85,85,85}
\definecolor{gainsboro229}{RGB}{229,229,229}
\definecolor{steelblue52138189}{RGB}{52,138,189}
\begin{axis}[
axis background/.style={fill=gainsboro229},
axis line style={white},
tick align=outside,
tick pos=left,
title={Simple plot \(\displaystyle \frac{\alpha}{2}\)},
x grid style={white},
xlabel=\textcolor{dimgray85}{time (s)},
xmajorgrids,
xmin=-0.095, xmax=1.995,
xtick style={color=dimgray85},
y grid style={white},
ylabel=\textcolor{dimgray85}{Voltage (mV)},
ymajorgrids,
ymin=-1.1, ymax=1.1,
ytick style={color=dimgray85}
]
\addplot [line width=1.64pt, chocolate2267451, mark=*, mark size=3, mark options={solid}]
table {%
0 0
% [...]
1.9 -0.587785252292473
};
\addplot [line width=1.64pt, steelblue52138189, mark=*, mark size=3, mark options={solid}]
table {%
0 1
% [...]
1.9 0.809016994374947
};
\end{axis}

\end{tikzpicture}

(Use get_tikz_code() instead of save() if you want the code as a string.)

Tweaking the plot is straightforward and can be done as part of your TeX work flow. The fantastic PGFPlots manual contains great examples of how to make your plot look even better.

Of course, not all figures produced by matplotlib can be converted without error. Notably, 3D plots don't work.

Installation

matplot2tikz is available from the Python Package Index, so simply do

pip install matplot2tikz

to install.

Usage

1. Generate your matplotlib plot as usual.

2. Instead of pyplot.show(), invoke matplot2tikz by

   import matplot2tikz
   
   matplot2tikz.save("mytikz.tex")
   # or
   matplot2tikz.save("mytikz.tex", flavor="context")

   to store the TikZ file as mytikz.tex.

3. Add the contents of mytikz.tex into your TeX source code. A convenient way of doing so is via

   \input{/path/to/mytikz}

   Also make sure that the packages for PGFPlots and proper Unicode support and are included in the header of your document:

   \usepackage[utf8]{inputenc}
   \usepackage{pgfplots}
   \DeclareUnicodeCharacter{2212}{−}
   \usepgfplotslibrary{groupplots,dateplot}
   \usetikzlibrary{patterns,shapes.arrows}
   \pgfplotsset{compat=newest}

   or:

   \setupcolors[state=start]
   \usemodule[tikz]
   \usemodule[pgfplots]
   \usepgfplotslibrary[groupplots,dateplot]
   \usetikzlibrary[patterns,shapes.arrows]
   \pgfplotsset{compat=newest}
   \unexpanded\def\startgroupplot{\groupplot}
   \unexpanded\def\stopgroupplot{\endgroupplot}

   You can also get the code via:

   import matplot2tikz
   
   matplot2tikz.Flavors.latex.preamble()
   # or
   matplot2tikz.Flavors.context.preamble()

4. [Optional] Clean up the figure before exporting to tikz using the clean_figure command.

   import matplotlib.pyplot as plt
   import numpy as np
   
   # ... do your plotting
   
   import matplot2tikz
   
   matplot2tikz.clean_figure()
   matplot2tikz.save("test.tex")

   The command will remove points that are outside the axes limits, simplify curves and reduce point density for the specified target resolution.

   The feature originated from the tikzplotlib project.

Contributing

If you experience bugs, would like to contribute, have nice examples of what matplot2tikz can do, or if you are just looking for more information, then please visit matplot2tikz's GitHub page.

For contributing, follow these steps:

1. Download the git repository, e.g., using git clone git@github.com:ErwindeGelder/matplot2tikz.git.

2. Create a virtual environment, e.g., using python -m venv venv.

3. Activate the virtual environment (e.g., on Windows, venv\Scripts\activate.bat).

4. Install the necessary libraries using pip install -e .[dev].

5. The main branch is protected, meaning that you cannot directly push changes to this branch. Therefore, if you want to make changes, do so in a seperate branch. For example, you can create a new branch using git checkout -b feature/my_awesome_new_feature.

6. Before pushing changes, ensure that the code adheres to the linting rules and that the tests are successful. To run the linting and testing, tox first needs to know where it can find the different Python versions that are supported. One way to do so is by making use of pyenv or pyenv-win. Note that you only need to do this once for a single machine.

7. Run tox. This does a linting check and runs all test scripts. To manually perform these steps, use the following commands (note that to ensure the same output is generated, Python 3.8 is used in step 2 above):

   1. Run tox run -e lint. If issues arise, fix them. You can do the linting commands manually using:
      1. ruff format . --check (remove the --check flag to let ruff do the formatting)
      2. ruff check .
      3. mypy .
   2. Run tox run -f test.

8. Check if the tests covered everything using the coverage report in /reports/coverage_html/index.html.

   NOTE: Currently, now all code is covered. Ideally, all code is covered, but for now, ensure that all new code is covered by the testing.

9. Push changes to GitHub. If everything is OK and you want to merge your changes to the main branch, create a pull request. Ideally, there is at least one reviewer who reviews the pull request before the merge.

Note that currently only "Code owners" can merge pull requests onto the main branch. This is to ensure that not everyone can break the main code (even unintentially). If you want to be a "Code owner", let us know!

License

matplot2tikz is published under the MIT license.