pandoc-plot

A Pandoc filter to generate figures from code blocks in documents

pandoc-plot turns code blocks present in your documents (Markdown, LaTeX, etc.) into embedded figures, using your plotting toolkit of choice, including Matplotlib, ggplot2, MATLAB, Mathematica, and more.

• Overview
• Supported toolkits
• Features
  • Captions
  • Link to source code
  • Preamble scripts
  • Performance
  • Compatibility with pandoc-crossref
• Detailed usage
  • As a filter
  • Parameters and options
  • Configuration
  • Other commands
• Installation
  • Binaries and Installers
  • conda
  • From Hackage/Stackage
  • From source
• Warning

Overview

This program is a Pandoc filter. It can therefore be used in the middle of conversion from input format to output format, replacing code blocks with figures.

The filter recognizes code blocks with classes that match plotting toolkits. For example, using the matplotlib toolkit:

# My document

This is a paragraph.

```{.matplotlib}
import matplotlib.pyplot as plt

plt.figure()
plt.plot([0,1,2,3,4], [1,2,3,4,5])
plt.title('This is an example figure')
```

Putting the above in input.md, we can then generate the plot and embed it in an HTML page:

pandoc --filter pandoc-plot input.md --output output.html

Note that pandoc-plot only works with pandoc >= 2.8 because of some breaking changes in pandoc’s API.

Supported toolkits

pandoc-plot currently supports the following plotting toolkits (installed separately):

• matplotlib: plots using the matplotlib Python library;
• plotly_python : plots using the plotly Python library;
• plotly_r: plots using the plotly R library
• matlabplot: plots using MATLAB;
• mathplot : plots using Mathematica;
• octaveplot: plots using GNU Octave;
• ggplot2: plots using ggplot2;
• gnuplot: plots using gnuplot;
• graphviz: graphs using the Graphviz

To know which toolkits are useable on your machine (and which ones are not available), you can check with the toolkits command:

pandoc-plot toolkits

The toolkits command is described in its own section below.

Wish your plotting toolkit of choice was available? Please raise an issue!

Features

Captions

You can also specify a caption for your image. This is done using the optional caption parameter.

Markdown:

```{.matlabplot caption="This is a simple figure with a **Markdown** caption"}
x  = 0: .1 : 2*pi;
y1 = cos(x);
y2 = sin(x);

figure
plot(x, y1, 'b', x, y2, 'r-.', 'LineWidth', 2)
```

LaTex:

\begin{minted}[caption=This is a simple figure with a caption]{matlabplot}
x  = 0: .1 : 2*pi;
y1 = cos(x);
y2 = sin(x);

figure
plot(x, y1, 'b', x, y2, 'r-.', 'LineWidth', 2)
\end{minted}

Caption formatting unfortunately cannot be determined automatically. To specify a caption format (e.g. “markdown”, “LaTeX”, etc.), see Configuration.

Link to source code

In case of an output format that supports links (e.g. HTML), the embedded image generated by pandoc-plot can show a link to the source code which was used to generate the file. Therefore, other people can see what code was used to create your figures.

You can turn this on via the source=true key:

Markdown:

```{.mathplot source=true}
...
```

LaTex:

\begin{minted}[source=true]{mathplot}
...
\end{minted}

or via a configuration file.

Preamble scripts

If you find yourself always repeating some steps, inclusion of scripts is possible using the preamble parameter. For example, if you want all Matplotlib plots to have the ggplot style, you can write a very short preamble style.py like so:

import matplotlib.pyplot as plt
plt.style.use('ggplot')

and include it in your document as follows:

```{.matplotlib preamble=style.py}
plt.figure()
plt.plot([0,1,2,3,4], [1,2,3,4,5])
plt.title('This is an example figure')
```

Which is equivalent to writing the following markdown:

```{.matplotlib}
import matplotlib.pyplot as plt
plt.style.use('ggplot')

plt.figure()
plt.plot([0,1,2,3,4], [1,2,3,4,5])
plt.title('This is an example figure')
```

The equivalent LaTeX usage is as follows:

\begin{minted}[include=style.py]{matplotlib}

\end{minted}

This preamble parameter is perfect for longer documents with many plots. Simply define the style you want in a separate script! You can also import packages this way, or define functions you often use.

Performance

pandoc-plot minimizes work, only generating figures if it absolutely must, i.e. if the content has changed. pandoc-plot will save the hash of the source code used to generate a figure in its filename. Before generating a figure, pandoc-plot will check it this figure already exists based on the hash of its source! This also means that there is no way to directly name figures.

Moreover, starting with version 0.5.0.0, pandoc-plot takes advantage of multicore CPUs, rendering figures in parallel.

Therefore, you can confidently run the filter on very large documents containing hundreds of figures, like a book or a thesis.

Compatibility with pandoc-crossref

pandoc-crossref is a pandoc filter that makes it effortless to cross-reference objects in Markdown documents.

You can use pandoc-crossref in conjunction with pandoc-plot for the ultimate figure-making pipeline. You can combine both in a figure like so:

```{#fig:myexample .plotly_python caption="This is a caption"}
# Insert figure script here
```

As you can see in @fig:myexample, ...

If the above source is located in file myfile.md, you can render the figure and references by applying pandoc-plot first, and then pandoc-crossref. For example:

pandoc --filter pandoc-plot --filter pandoc-crossref -i myfile.md -o myfile.html

Detailed usage

pandoc-plot is a command line executable with a few functions. You can take a look at the help using the -h/--help flag:

pandoc-plot - generate figures directly in documents using your plotting toolkit
of choice.

Usage: pandoc-plot.exe [(-v|--version) | --full-version | (-m|--manual)] 
                       [COMMAND] [AST]
  This pandoc filter generates plots from code blocks using a multitude of
  possible renderers. This allows to keep documentation and figures in perfect
  synchronicity.

Available options:
  -v,--version             Show version number and exit.
  --full-version           Show full version information and exit.
  -m,--manual              Open the manual page in the default web browser and
                           exit.
  -h,--help                Show this help text

Available commands:
  toolkits                 Show information on toolkits and exit.
  clean                    Clean output directories where figures from FILE
                           might be stored. WARNING: All files in those
                           directories will be deleted.
  write-example-config     Write example configuration to a file and exit.

More information can be found via the manual (pandoc-plot --manual) or the repository README, located at
    https://github.com/LaurentRDC/pandoc-plot

As a filter

The most common use for pandoc-plot is as a pandoc filter, in which case it should be called without arguments. For example:

pandoc --filter pandoc-plot -i input.md -o output.html

If pandoc-plot fails to render a code block into a figure, the filtering will not stop. Your code blocks will stay unchanged.

You can chain other filters with it (e.g., pandoc-crossref) like so:

pandoc --filter pandoc-plot --filter pandoc-crossref -i input.md -o output.html

Parameters and options

pandoc-plot looks for code blocks with a specific class, depending on the toolkit you want to use. pandoc-plot will run the code and capture the figure output. There can only be one figure per code block.

There are parameters that affect the figure that will be included in your document. Here are all the possible general parameters:

  ```{.cls directory=(path) caption=(text) format=(PNG|PDF|SVG|JPG|EPS|GIF|TIF|WEBP) source=(true|false) preamble=(path) dpi=(integer) executable=(path) caption_format=(text)}
  # script content
  ```

• cls must be one of the following: matplotlib, matlabplot, plotly_python, plotly_r, mathplot, octaveplot, ggplot2, gnuplot

All following parameters are optional, with their default values controlled by the configuration

• directory is a path to the directory where the figure and source code will be saved. You cannot control the file name. This path is either absolute, or relative from the working directory where you call pandoc-plot.
• caption is the caption text. The format of the caption is specified in the caption_format parameter, described below.
• format is the desired filetype for the resulting figure. Possible values for format are [PNG, PDF, SVG, JPG, EPS, GIF, TIF, WEBP]. Not all toolkits support all formats. See pandoc-plot toolkits for toolkit-specific information regarding save formats.
• source is a boolean toggle that determines whether the source code should be linked in the caption or not. Possible values are [true, True, false, False].
• preamble is a path to a script that will be included as a preamble to the content of the code block. This path is either absolute, or relative from the working directory where you call pandoc-plot.
• dpi is the pixel density of the figure in dots-per-inch. Possible values are positive integers. Not all toolkits respect this.
• executable is a path to the executable to use (e.g. C:\\python3.exe) or the name of the executable (e.g. python3).
• caption_format is the text format of the caption. Possible values are exactly the same as pandoc’s format specification, usually FORMAT+EXTENSION-EXTENSION. For example, captions in Markdown with raw LaTeX would be parsed correctly provided that caption_format=markdown+raw_tex. See Pandoc’s guide on Specifying formats.

Code highlighting

If your editor supports code highlighting in code blocks, you can also include the programming language. In Markdown:

  ```{.language .cls (options)}
  # script content
  ```

For example, for Matplotlib plots:

  ```{.python .matplotlib}
  # script content
  ```

or for GGPlot2 figures:

  ```{.r .ggplot2}
  # script content
  ```

This way, you benefit from code highlighting and pandoc-plot.

Configuration

To avoid repetition, pandoc-plot can be configured using simple YAML files. Here are all the possible parameters:

# This is an example configuration. Everything in this file is optional.
# Please refer to the documentation to know about the parameters herein.
#
# The `executable` parameter for all toolkits can be either the
# executable name (if it is present on the PATH), or
# the full path to the executable.
# E.g.:
#  executable: python3
#  executable: "C:\Python37\Scripts\python.exe"
#
# Note that this file should be re-named to ".pandoc-plot.yml" before pandoc-plot 
# notices it.

# The following parameters affect all toolkits
# Directory where to save the plots. The path can be relative to this file, or absolute.
directory: plots/

# Whether or not to include a link to the source script in the caption. 
# Particularly useful for HTML output.
source: false

# Default density of figures in dots per inches (DPI). 
# This can be changed in the document specifically as well.
dpi: 80

# Default format in which to save the figures. This can be specified individually as well.
format: PNG

# Text format for the captions. Unfortunately, there is no way to detect this automatically.
# You can use the same notation as Pandoc's --from parameter, specified here:
# https://pandoc.org/MANUAL.html#option--from
# Example: markdown, rst+raw_tex
caption_format: markdown+tex_math_dollars

# The possible parameters for the Matplotlib toolkit
matplotlib:
  # preamble: matplotlib.py
  tight_bbox: false
  transparent: false
  executable: python

# The possible parameters for the MATLAB toolkit
matlabplot:
  # preamble: matlab.m
  executable: matlab

# The possible parameters for the Plotly/Python toolkit
plotly_python:
  # preamble: plotly-python.py
  executable: python

# The possible parameters for the Plotly/R toolkit
plotly_r:
  # preamble: plotly-r.r
  executable: Rscript

# The possible parameters for the Mathematica toolkit
mathplot:
  # preamble: mathematica.m
  executable: math

# The possible parameters for the GNU Octave toolkit
octaveplot:
  # preamble: octave.m
  executable: octave

# The possible parameters for the ggplot2 toolkit
ggplot2:
  # preamble: ggplot2.r
  executable: Rscript

# The possible parameters for the gnuplot toolkit
gnuplot:
  # preamble: gnuplot.gp
  executable: gnuplot

# The possible parameters for the graphviz toolkit
graphviz:
  # preamble: graphviz.dot
  executable: dot

A file like the above sets the default values; you can still override them in documents directly.

The easiest way to specify configuration for pandoc-plot is to place a .pandoc-plot.yml file in the current working directory. You can also specify a configuration file in document metadata, under the plot-configuration key. For example, in Markdown:

---
title: My document
author: John Doe
plot-configuration: /path/to/file.yml
---

or on the command line, using pandoc’s -M/--metadata flag:

pandoc --filter pandoc-plot -M plot-configuration=/path/to/file.yml ...

The hierarchy of configuration files is as follows:

1. A configuration file specified in the metadata under the plot-configuration key;
2. Otherwise, a file in the current working directory named .pandoc-plot.yml;
3. Finally, the default configuration is used.

Executables

The executable parameter for all toolkits can be either the executable name (if it is present on the PATH), or the full path to the executable.

Examples:

matplotlib:
  executable: python3

matlabplot:
  executable: "C:\Program Files\Matlab\R2019b\bin\matlab.exe"

Toolkit-specific options

Matplotlib

• tight_bbox is a boolean that determines whether to use bbox_inches="tight" or not when saving Matplotlib figures. For example, tight_bbox: true. See here for details.
• transparent is a boolean that determines whether to make Matplotlib figure background transparent or not. This is useful, for example, for displaying a plot on top of a colored background on a web page. High-resolution figures are not affected. For example, transparent: true.

Other commands

Finding installed toolkits

You can determine which toolkits are available on your current machine using the pandoc-plot toolkits command. Here is the full help text:

Usage: pandoc-plot.exe toolkits [--config PATH]
  Show information on toolkits and exit.

Available options:
  --config PATH            Path to optional configuration file.
  -h,--help                Show this help text

Cleaning output

Figures produced by pandoc-plot can be placed in a few different locations. You can set a default location in the Configuration, but you can also re-direct specific figures in other directories if you use the directory=... argument in code blocks. These figures will build up over time. You can use the clean command to scan documents and delete the associated pandoc-plot output files. For example, to delete the figures generated from the input.md file:

pandoc-plot clean input.md

This sill remove all directories where a figure could have been placed. WARNING: all files will be removed.

Here is the full help text for the clean command:

Usage: pandoc-plot.exe clean [--config PATH] FILE
  Clean output directories where figures from FILE might be stored. WARNING: All
  files in those directories will be deleted.

Available options:
  --config PATH            Path to optional configuration file.
  -h,--help                Show this help text

Configuration template

Because pandoc-plot supports a few toolkits, there are a lot of configuration options. Don’t start from scratch! The write-example-config command will create a file for you, which you can then modify:

pandoc-plot write-example-config

You will need to re-name the file to .pandoc-ploy.yml to be able to use it, so don’t worry about overwriting your own configuration.

Here is the full help text for the write-example-config command:

Usage: pandoc-plot.exe write-example-config [--path FILE]
  Write example configuration to a file and exit.

Available options:
  --path FILE              Target location of the configuration file. Default is
                           ".example-pandoc-plot.yml"
  -h,--help                Show this help text

Installation

Binaries and Installers

Windows, Linux, and Mac OS binaries are available on the GitHub release page. There are also Windows installers.

conda

Like pandoc, pandoc-plot is available as a package installable with conda. Click here to see the package page.

To install in the current environment:

conda install -c conda-forge pandoc-plot

From Hackage/Stackage

pandoc-plot is available on Hackage and Stackage. Using the cabal-install tool:

cabal update
cabal install pandoc-plot

or

stack update
stack install pandoc-plot

From source

Building from source can be done using stack or cabal:

git clone https://github.com/LaurentRDC/pandoc-plot
cd pandoc-plot
stack install # Alternatively, `cabal install`

Warning

Do not run this filter on unknown documents. There is nothing in pandoc-plot that can stop a script from performing evil actions.