Matplotlib extensys style for making figures This repo has Matplotlib Extensys style to format your figure for scientific publications and presentation.

The easist way to install ExtensysPlots is to use pip:

# to install the latest release (from PyPI) 
pip install ExtensysPlots

# in Ubuntu/Debian
python3 -m pip install extensysplots

# to install latest commit (from GitHub)
pip install git+https://github.com/mcekwonu/ExtensysPlots.git

The pip installation will automatically move all of the Matplotlib style files *.mplstyle into the appropriate directory on your computer.

Please see the FAQ section for more information and troubleshooting.

"extensys" 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('extensys')

Available styles include:

extensys, extensys-pl, extensys-gd, extensys-nb, extensys-sc

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

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

The default format to save figure is .png with dpi=500. Other formats by obtained by passing it in the plt.savefig as well as the dpi. For example:

plt.savefig("figures/fig1" + ".pdf", dpi=1000)

The extensys style:

The extensys-ms style (with markers)

The extensys-gd style (with grid)

The extensys-nb style (with jupyter notebook)

The extensys + dark_background style

The extensys-sc style (with scatter)

The extensys-pl plain style

Plotting multiple left and right y-axis using extensys style

Please feel free to contribute to the ExtensysPlots repo! Before starting a new style or making any changes, please create an issue through the GitHub issue tracker.

If you need any help with ExtensysPlots, 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.

1. Installing ExtensysPlots manually

   • If you like, you can install the *.mplstyle files 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())

     In my case it returned /home/mce/.config/matplotlib on Ubuntu and C:\Users\User\.matplotlib on Windows. Please verify the location of matplotib configdir as the location may differ for different users depending on how the matplotlib package was installed.

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

   • For Ubuntu

     cp styles/*.mplstyle ~/.config/matplotlib/stylelib/

   • For Windows

     cp styles/*.mplstyle ~/.matplotlib/stylelib/

2. Using different fonts:

   • ExtensysPlots uses the default sans-serif font. If you would like to specify a different font, you can use:

     import matplotlib.pyplot as plt
     plt.style.use('extensys')
     plt.rcParams.update({
     "font.family": "serif",   # specify font family here
     "font.serif": ["Times"],  # specify font here
     "font.size":12})          # specify font size here

3. Adjusting the legend placement:

   • You can adjust the legend borderpad when you have more than four legend parameters, for proper placement. You will need to try different values manually and see that it is placed correctly.

     import matplotlib.pyplot as plt
     plt.style.use('extensys')
     plt.rcParams.update({"legend.borderaxespad": -4.0})

4. Installing ExtensysPlots within Google Colab, IPython, Jupyter Notebooks, etc.:

   • After installing ExtensysPlots within one of these environments, you may need to reload the Matplotlib style library. For example:

     !pip install ExtensysPlots
     import matplotlib.pyplot as plt
     plt.style.reload_library()
     plt.style.use('extensys')

The following papers used ExtensysPlots:

• M.T. Nasir, M.C. Ekwonu, J.A. Esfahani, K.C. Kim, "Performance assessment and multi-objective optimization of an organic Rankine cycles and vapor compression cycle based combined cooling, heating, and power system", Sustainable Energy Technologies and Assessments, Volume 47, 2021, 101457, ISSN 2213-1388. (open access).

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

You don't have to cite ExtensysPlots if you use it but it's nice if you do:

@article{ExtensysPlots,
    author    = {Michael Chukwuemeka Ekwonu},
    title     = {{mcekwonu/ExtensysPlots}},
    month     = {mar},
    year      = {2021},
    publisher = {},
    version   = {1.0.0},
    doi       = {10.5281/zenodo.4572436},
    url       = {https://doi.org/10.5281/zenodo.4572436}
}

MIT