Metadata-Version: 2.1
Name: matplotlib2tikz
Version: 0.6.18
Summary: convert matplotlib figures into TikZ/PGFPlots
Home-page: https://github.com/nschloe/matplotlib2tikz
Author: Nico Schlömer
Author-email: nico.schloemer@gmail.com
License: License :: OSI Approved :: MIT License
Download-URL: https://pypi.python.org/pypi/matplotlib2tikz
Description: # matplotlib2tikz
        
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        This is matplotlib2tikz, a Python tool for converting matplotlib figures into
        [PGFPlots](https://www.ctan.org/pkg/pgfplots)
        ([TikZ](https://www.ctan.org/pkg/pgf)) figures like
        
        ![](https://nschloe.github.io/matplotlib2tikz/example.png)
        
        for native inclusion into LaTeX documents.
        
        matplotlib2tikz works with both Python 2 and Python 3.
        
        The output of matplotlib2tikz is in
        [PGFPlots](http://pgfplots.sourceforge.net/pgfplots.pdf), 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](https://matplotlib.org/users/whats_new.html#pgf-tikz-backend).
        For example, the matplotlib figure
        ```python,test
        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)
        
        from matplotlib2tikz import save as tikz_save
        
        tikz_save("test.tex")
        ```
        (see above) gives
        ```latex
        % This file was created by matplotlib2tikz vx.y.z.
        \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=-0.095, xmax=1.995,
        ymin=-1.1, ymax=1.1,
        tick align=outside,
        tick pos=left,
        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={solid}]
        table {%
        0 0
        0.1 0.587785252292473
        % [...]
        1.9 -0.587785252292473
        };
        \addplot [line width=1.64pt, color1, mark=*, mark size=3, mark options={solid}]
        table {%
        0 1
        0.1 0.809016994374947
        % [...]
        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 LaTeX
        work flow.
        [The fantastic PGFPlots manual](http://pgfplots.sourceforge.net/pgfplots.pdf)
        contains great examples of how to make your plot look even better.
        
        ### Installation
        
        matplotlib2tikz is [available from the Python Package
        Index](https://pypi.org/project/matplotlib2tikz/), so
        simply type
        ```
        pip install -U matplotlib2tikz
        ```
        to install/update.
        
        
        ### Usage
        
        1. Generate your matplotlib plot as usual.
        
        2. Instead of `pyplot.show()`, invoke matplotlib2tikz by
            ```python
            tikz_save('mytikz.tex')
            ```
           to store the TikZ file as `mytikz.tex`. Load the library with:
            ```python
            from matplotlib2tikz import save as tikz_save
            ```
           _Optional:_
           The scripts accepts several options, for example `height`, `width`,
           `encoding`, and some others. Invoke by
            ```python
            tikz_save('mytikz.tex', figureheight='4cm', figurewidth='6cm')
            ```
           Note that height and width must be set large enough; setting it too low may
           result in a LaTeX compilation failure along the lines of `Dimension Too Large` or `Arithmetic Overflow`;
           see information about these errors in [the PGFPlots manual](http://pgfplots.sourceforge.net/pgfplots.pdf).
           To specify the dimension of the plot from within the LaTeX document, try
            ```python
            tikz_save(
                'mytikz.tex',
                figureheight='\\figureheight',
                figurewidth='\\figurewidth'
                )
            ```
            and in the LaTeX source
            ```latex
            \newlength\figureheight
            \newlength\figurewidth
            \setlength\figureheight{4cm}
            \setlength\figurewidth{6cm}
            \input{mytikz.tex}
            ```
        
        3. Add the contents of `mytikz.tex` into your LaTeX source code; a convenient
           way of doing so is via `\input{/path/to/mytikz.tex}`. Also make sure that
           in the header of your document the packages for PGFPlots and proper Unicode
           support and are included:
            ```latex
            \usepackage[utf8]{inputenc}
            \usepackage{pgfplots}
            ```
           Additionally, with LuaLaTeX
            ```latex
            \usepackage{fontspec}
            ```
           is needed to typeset Unicode characters.
           Optionally, to use the latest PGFPlots features, insert
            ```latex
            \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
        
         * run through matplotlib2tikz,
         * the resulting LaTeX file is compiled into a PDF (`pdflatex`),
         * the PDF is converted into a PNG (`pdftoppm`),
         * 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
        ```
        pytest
        ```
        
        The final pHash may depend on any of the tools used during the process. For
        example, if your version of [Pillow](https://pypi.org/project/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 pHash, and
          * a function that creates the image in matplotlib.
        
        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 create a new release
        
        1. bump the `__version__` number,
        
        2. publish to PyPi and GitHub:
            ```
            $ make publish
            ```
        
        ### License
        
        matplotlib2tikz is published under the [MIT license](https://en.wikipedia.org/wiki/MIT_License).
        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Multimedia :: Graphics :: Graphics Conversion
Classifier: Topic :: Scientific/Engineering :: Visualization
Description-Content-Type: text/markdown
Provides-Extra: all
Provides-Extra: update
