Configuration

This file contains an example of how to configure the beautiplot library according to your needs. The configuration allows you to set various parameters such as output paths, font sizes, and other settings that will be applied to all plots created with beautiplot. All configuration options are documented with examples in the config class. Here, we will summarize the most important options and how to use them.

Global Configuration

We start by importing the necessary instance.

import beautiplot.plot as bp
from beautiplot import config

The config object is an instance of the _Config class, which allows you to set global configuration options.

Warning

You should never import and instantiate the _Config class directly, but always use the config object provided by the beautiplot module.

The output_path option specifies the directory where the plots will be saved. You can set it to any valid path on your system. We will save the plots in a directory called example_plots in the current working directory. If the directory does not exist, it will be created automatically.

config.output_path = 'docs/example_plots'

You should definitely set the width of the plots to the width of your document. This ensures that the text inside the plots has the same size as the text in your document. The width is specified in points (pt) and you can get the width of your document in LaTeX by including

\the\textwidth

in your document and compiling it. We will assume that the width of our document is 400pt and set the width option accordingly.

config.width = 400

The default color map used by beautiplot is inferno. You can change it to any other color map supported by Matplotlib or a custom one by using the set_cmapmethod. We will set the color map toviridis`.

config.set_cmap('viridis')

Plot Specific Configuration

You can also set plot-specific configuration options. Most of the functions in the plot module have arguments that, if specified, will override the global configuration or take additional keyword arguments that can be used to customize the plot and override the global configuration.

Some examples of plot-specific configuration options are using a different color map, figure width or aspect ratio.

fig, axes = bp.newfig(width=0.5, aspect=1.5)
bp.imshow(axes, [[1, 2], [3, 4]], extent=(0, 1, 0, 1), cmap='plasma')

The width argument sets the width of the figure to 50% of the global configuration width, and the aspect argument sets the aspect ratio of the figure to 1.5. The cmap argument overrides the global color map setting and uses plasma for this specific plot.