matplotlib2tikz 0.2.1

convert matplotlib figures into TikZ/PGFPlots

This is matplotlib2tikz, a Python tool for converting matplotlib figures into PGFPlots (TikZ) figures like

for native inclusion into LaTeX.

The output of matplotlib2tikz is in PGFPlots, a LaTeX library that sits on top of TikZ and describes graphs in terms of axes, data etc. Consequently, the output of matplotlib2tikz retains more information, can be more easily understood, and is more easily editable than raw TikZ output. For example, the matplotlib figure

from matplotlib import pyplot as pp
from matplotlib import style
import numpy as np
fig = pp.figure()
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)
pp.plot(t, s, 'o-', lw=4.1)
pp.plot(t, s2, 'o-', lw=4.1)
pp.xlabel('time(s)')
pp.ylabel('Voltage (mV)')
pp.title('Simple plot $\\frac{\\alpha}{2}$')
pp.grid(True)

(see above) gives

% This file was created by matplotlib2tikz.
\begin{tikzpicture}

\definecolor{color1}{rgb}{0.203921568627451,0.541176470588235,0.741176470588235}
\definecolor{color0}{rgb}{0.886274509803922,0.290196078431373,0.2}

\begin{axis}[
title={Simple plot $\frac{\alpha}{2}$},
xlabel={time(s)},
ylabel={Voltage (mV)},
xmin=0, xmax=2,
ymin=-1, ymax=1,
width=7.5cm,
xmajorgrids,
x grid style={white},
ymajorgrids,
y grid style={white},
axis line style={white},
axis background/.style={fill=white!89.803921568627459!black}
]
\addplot [line width=1.64pt, color0, mark=*, mark size=3, mark options={draw=black}]
coordinates {
(0,0)
(0.1,0.587785252292473)
% [...]
(1.9,-0.587785252292473)
};
\addplot [line width=1.64pt, color1, mark=*, mark size=3, mark options={draw=black}]
coordinates {
(0,1)
(0.1,0.809016994374947)
% [...]
(1.9,0.809016994374947)
};
\path [draw=white, fill opacity=0] (axis cs:13,0)--(axis cs:13,0);

\path [draw=white, fill opacity=0] (axis cs:1,13)--(axis cs:1,13);

\path [draw=white, fill opacity=0] (axis cs:0,13)--(axis cs:0,13);

\path [draw=white, fill opacity=0] (axis cs:13,1)--(axis cs:13,1);

\end{axis}

\end{tikzpicture}

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

Installation

Python Package Index

matplotlib2tikz is available from the Python Package Index, so simply type

pip install matplotlib2tikz

Manual installation

Download matplotlibtikz from https://github.com/nschloe/matplotlib2tikz. Place the matplotlib2tikz script in a directory where Python can find it (e.g., $PYTHONPATH). You can install it systemwide with

python setup.py install

or place the script matplotlib2tikz.py into the directory where you intend to use it.

Dependencies

matplotlib2tikz needs matplotlib and NumPy to work. matplotlib2tikz works both with Python 2 and Python 3.

To use the resulting TikZ/PGFPlots figures, your LaTeX installation needs

• TikZ (aka PGF, >=2.00), and

• PGFPlots (>=1.3).

Usage

1. Generate your matplotlib plot as usual.

2. Instead of pyplot.show(), invoke matplotlib2tikz by

   tikz_save('myfile.tikz');

   to store the TikZ file as myfile.tikz. Load the libary with:

   from matplotlib2tikz import save as tikz_save

   Optional: The scripts accepts several options, for example height, width, encoding, and some others. Invoke by

   tikz_save('myfile.tikz', figureheight='4cm', figurewidth='6cm')

IMPORTANT: Height and width must be set large enough; setting it too low it may result in a LaTeX compilation failure such as - Dimension Too Large, or - Arithmetic Overflow (see information about these errors in the manual of PGFPlots).

To specify the dimension of the plot from within the LaTeX document, try python tikz_save( 'myfile.tikz', figureheight = '\\figureheight', figurewidth = '\\figurewidth' ) and in the LaTeX source latex \newlength\figureheight \newlength\figurewidth \setlength\figureheight{4cm} \setlength\figurewidth{6cm} \input{myfile.tikz}

3. Add the contents of myfile.tikz into your LaTeX source code; a convenient way of doing so is to use \input{/path/to/myfile.tikz}. Also make sure that at the header of your document the packages TikZ and PGFPlots are included:

   \usepackage{tikz}
   \usepackage{pgfplots}

   Optionally, to use features of the latest PGFPlots package (as of PGFPlots 1.3), insert

   \pgfplotsset{compat=newest}

Contributing

If you experience bugs, would like to contribute, have nice examples of what matplotlib2tikz can do, or if you are just looking for more information, then please visit [matplotlib2tikz’s GitHub page] (https://github.com/nschloe/matplotlib2tikz).

Testing

matplotlib2tikz has automatic unit testing to make sure that the software doesn’t accidentally get worse over time. In test/testfunctions/, a number of test cases are specified. Those are

• run through matplotlib2tikz,

• the resulting LaTeX file is compiled into a PDF (pdflatex),

• the PDF is converted into a PNG (`pdftoppm <http://poppler.freedesktop.org/>`__),

• a perceptual hash is computed from the PNG and compared to a previously stored version.

To run the tests, just check out this repository and type

nosetests

or

nose2 -s test

The final pHash may depend on any of the tools used during the process. For example, if your version of Pillow is too old, the pHash function might operate slightly differently and produce a slightly different pHash, resulting in a failing test. If tests are failing on your local machine, you should first make sure to have an up-to-date Pillow, .

If you would like to contribute a test, just take a look at the examples in test/testfunctions/. Essentially a test consists of three things: * a description, * a function that creates the image in matplotlib, and * a pHash. Just add your file, add it to test/testfunction/__init__.py, and run the tests. A failing test will always print out the pHash, so you can leave it empty in the first run and fill it in later to make the test pass.

Distribution

To publish a new version of matplotlib2tikz on PyPi, make sure to have updated the version numbers consistently. Then run

python setup.py sdist upload

Warnings about a missing README can be ignored.

License

matplotlib2tikz is published under the MIT license.