BillingeGroup mpl-stylesheets

• matplotlib can accept a manually defined stylesheet file that is located remotely or locally.

• To use the BillingeGroup stylesheet, please install this package first

  1. You can install from source code in this repo by python setup.py install.

  2. Or you can conda install the package from conda-forge.

• By default the package uses LaTeX fonts for mathematical symbols. This feature requires a Latex package on your computer. It is not required for the use of the styel-sheet but gives better results for things like angstrom symbols.

  • For Ubuntu users, you can try this suggestion:

  apt-get install dvipng texlive-latex-base texlive-latex-extra texlive-latex-recommended texlive-fonts-recommended cm-super
  

• Then simply place the following commands at the begining of you python session whenever you plot.

  import matplotlib.pyplot as plt
  from bg_mpl_stylesheet.bg_mpl_stylesheet import bg_mpl_style
  plt.style.use(bg_mpl_style)
  

• If you wish to use BillingeGroup stylesheet as the default style of your plots, please follow these steps.

  1. Use following commands to figure out which matplotlib config directory on your system:

     import matplotlib
     config_dir = matplotlib.get_configdir()
     

  2. Copy and paste bg_mpl_stylesheet file to the config_dir found at previous step.

  • NOTE: If you installed bg-mpl-stylesheets via conda, or do not have the bg_mpl_stylesheet file for any other reason, you can (re)download it here.

• You could also configure any matplotlib rcParameter dynamically in your python session by

  plt.rcParams['figure.dpi'] = 180
  plt.rcParams['font.size'] = 18
  (... and so on)
  

• Now you can start writing the plot codes as normal, such as

  import matplotlib.pyplot as plt
  plt.plot([1, 2, 3, 4])
  plt.ylabel('some numbers')
  plt.show()
  

• You can also go to the example folder and run plot.py for testing. The example plot would be like this:

• The full group color cycle is shown in the following along with the color codes:

• For full reference, please see matplotlib doc: https://matplotlib.org/users/dflt_style_changes.html