Docs for mpl_bsic - Version 1.3#

mpl_bsic helps you style matplotlib plots in BSIC style.

Setting up the Fonts (Optional)#

BSIC uses Gill Sans MT for Headings, and Garamond for text. This library will temporarily install the fonts on your matplotlib instance if you don’t have them on your computer, but if you want to install them, here’s a quick explanation.

As of now, the process has only been tested on MacOS. If it doesn’t work on Windows, shoot me a message.

  1. Download and install the fonts

    1. Download the fonts from the fonts folder in the main repository.

    2. Install the fonts (double click on the font files and click on “Install Font”).

  2. Clear your matplotlib cache.

    1. Go on your pc > users > [your-user] > .matplotlib

    2. If you cannot see the .matplotlib folder,

      press cmd + shift + . to show hidden files.

    3. Delete the fontlist-vXXX.json file.

[IMPORTANT] Plotting for BSIC Articles#

This section will explain how to correctly create plots for BSIC articles.

Choosing the figsize

Word documents have a maximum width of 7.32 inches. Any image larger than that will be resized to fit the page. If you end up resizing your image after exporting (or if Word does it for you), the font size of the Title of the plot won’t match the font size of the subsection titles in the article. Also, you won’t have consistent font sizes if you include more than 1 plot in the document.

To avoid this, you should always set the width of the figure to at most 7.32 inches before exporting. To get correct figsizes to use, and check that you set them correctly, you can use check_figsize().

Plotting the data correctly

In your python file, you will call apply_bsic_style() (and apply_bsic_logo()) on the plot you want to style.

Be sure to read the docs for apply_bsic_style() and apply_bsic_logo() thoroughly to see how to use them correctly.

from mpl_bsic import apply_bsic_style

fig, ax = plt.subplots(1,1)
apply_bsic_style(fig, ax)
ax.set_title('your title')

... # plot your data and apply the style
# fig.tight_layout() # DO NOT call this before exporting

# notice the arguments specified
fig.savefig("your_filename.svg", dpi=1200, bbox_inches="tight")

Exporting the plot

When exporting, we need to make sure that the figure is not resized automatically by matplotlib and that the font sizes stay consistent. To do that, you must not call fig.tight_layout() before exporting. Additionally, you must export the figure with bbox_inches='tight' to make sure that no parts of the plot are cropped out.

My recommendation is to export in svg format, so that the quality of the image stays constant even when resizing (which, by the way, you should ideally not do).

To export the figure, use the provided function mpl_bsic.export_figure, which takes care of applying the styles and the correct parameters to the .savefig() function provided in vanilla Matplotlib.

from mpl_bsic import export_figure

fig, ax = plt.subplots(1,1)

... # plot your data and apply the style
# DO NOT call fig.tight_layout() this before exporting

export_figure(fig, 'export_path') # specify the export path without the extension

Specific Use Cases#

Plotting Yield Curves

When plotting yield curves, to make the x ticks the same distance, regardless of time:

data.index = data.index.astype(str)

Functions#

mpl_bsic.apply_bsic_style(fig, ax[, sources])

Apply the BSIC Style to an existing matplotlib plot.

mpl_bsic.apply_bsic_logo(fig, ax[, scale, ...])

Apply the BSIC Logo to the Plot.

mpl_bsic.plot_trade(underlying, pnl, ...[, ...])

Plot a trade performance vs the underlying.

mpl_bsic.export_figure(fig, filename)

Export a figure according to BSIC Standards.

mpl_bsic.check_figsize([width, height, ...])

Check the validity of the figsize.

mpl_bsic.format_timeseries_axis(ax, ...[, fmt])

Format the x-axis of a timeseries plot.

mpl_bsic.preprocess_dataframe(df)

Handle and preprocess the DataFrame before plotting.

mpl_bsic.df_to_excel(df, path_to_excel[, ...])

Export a Pandas DataFrame as a formatted Excel table.

mpl_bsic.style_excel_file(path_to_excel, ...)

Format an already existing Excel file.

Indices and tables#