/SciencePlots

Matplotlib styles for scientific plotting

Primary LanguagePythonMIT LicenseMIT

Science Plots

Matplotlib styles for scientific plotting

This repo has Matplotlib styles to format your plots for scientific papers, presentations and theses.

Installation

The easiest way to install SciencePlots is using pip:

# for latest commit
pip install git+https://github.com/garrettj403/SciencePlots.git

# for lastest release
pip install SciencePlots

The pip installation will automatically move all of the *.mplstyle files into the appropriate directory. If you like, you can also do this manually. First, clone the repository and then copy all of the *.mplstyle files into your Matplotlib style directory. If you're not sure where this is, in an interactive python console type:

import matplotlib
print(matplotlib.get_configdir())

You should get back something like /home/garrett/.matplotlib. You would then put the *.mplstyle files in /home/garrett/.matplotlib/stylelib/ (you may need to create the stylelib directory).

Using the Styles

science.mplstyle is the main style from this repo. Whenever you want to use it, simply add the following to the top of your python script:

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

You can also combine multiple styles together by:

plt.style.use(['science','ieee'])

In this case, the ieee style will override some of the parameters from the science style in order to configure the plot for IEEE papers (column width, fontsizes, etc.).

To use any of the styles temporarily, you can use:

with plt.style.context(['science', 'ieee']):
    plt.figure()
    plt.plot(x, y)
    plt.show()

Examples

The science style:

The science + grid styles:

The science + ieee styles for IEEE papers:

  • IEEE requires figures to be readable when printed in black and white. The ieee style also sets the figure width to fit within one column of an IEEE paper.

The science + scatter styles for scatter plots:

The science + notebook styles for Jupyter notebooks:

You can also combine these styles with the other styles that come with Matplotlib. For example, the dark_background + science + high-vis styles:

Note: See the examples/ directory for more!

Color Cycles

The high-vis color cycle:

The bright color cycle:

The vibrant color cycle:

The muted color cycle:

The retro color cycle:

Note: The bright, vibrant and muted color cycles are from Paul Tol's website. They are color-blind safe!

Help and Contributing

Please feel free to contribute to the SciencePlots repo! For example, it would be good to add new styles for different journals and add new color cycles. Before starting a new style or making any changes, please create an issue through the GitHub issue tracker. That way we can discuss if the changes are necessary and the best approach.

If you need any help with SciencePlots, please first check the FAQ and search through the previous GitHub issues. If you can't find an answer, create a new issue through the GitHub issue tracker.

You can checkout Matplotlib's documentation for more information on plotting settings.

FAQ

  1. Errors related to Latex:

    • If you get an error saying RuntimeError: Failed to process string with tex because latex could not be found, this means that you do not have Latex installed on your computer (or at least that Python/Matplotlib can't find it). You have two options: (1) install Latex, or (2) disable Latex using the no-latex option:

      plt.style.use(['science','no-latex'])

    • For Windows users, you may need to manually add Latex to your environment path (see issue).

SciencePlots in Academic Papers

The following papers use SciencePlots:

If you use SciencePlots in your paper/thesis, feel free to add it to the list!