aesthetic 0.7

a e s t h e t i c

a e s t h e t i c

Luke's matplotlib style sheets. See also John Garrett's SciencePlots.

Preferences include:

• Avoid constantly repeating matplotlib calls to prettify plots.
• Avoid DejaVu Sans as a default matplotlib font.
• Avoid drawing right and top axis spines unless they provide function.
• White on black reduces eye strain; make generating white on black figures easier using *_wob style sheets.

install

...via pip: pip install aesthetic

...via local clone: git clone [e-mail]:lgbouma/aesthetic.git; cd aesthetic; pip install -e .

usage examples

for plot styles, see the test driver. the general syntax follows:

from aesthetic import set_style
set_style("clean")

set_style("clean_wob")

set_style("science")

set_style("science_wob")

So if you wanted to make four different versions of the same plot with responsive colors:

from aesthetic import set_style

import numpy as np, matplotlib.pyplot as plt, matplotlib as mpl
import matplotlib.colors as mcolors
from cycler import cycler

def set_colors(style):
    base = plt.rcParams['axes.prop_cycle'].by_key()['color']
    if '_wob' in style:
        inverse = [tuple(1 - v for v in mcolors.to_rgb(c)) for c in base]
        plt.rcParams['axes.prop_cycle'] = cycler('color', inverse)
    else:
        pass

def make_plot(style):
    x = np.linspace(0,10,1000)
    y = (x/100)**3 + 5*np.sin(x)
    _x, _y = np.arange(2, 8, 0.5), np.arange(2, 8, 0.5)

    set_colors(style)
    fig, ax = plt.subplots(figsize=(3,2.5))
    ax.plot(x, y, label=f'style: {style}')
    ax.plot(x, y+3)
    ax.plot(x, y+6)
    _yerr = np.abs(np.random.normal(2, 1, _x.size))
    c = 'k' if '_wob' not in style else 'w'
    ax.errorbar(_x, _y, yerr=_yerr, marker='o', elinewidth=0.5, lw=0, c=c, markersize=2)
    ax.update({
        'xlabel': r'x [units]',
        'ylabel': r'y [units]',
    })
    ax.legend(fontsize='small')
    return fig

if __name__ == '__main__':
    styles = ['clean', 'science', 'clean_wob', 'science_wob']
    for style in styles:
        set_style(style)
        fig = make_plot(style)
        fig.savefig(f'plot_{style}.png', bbox_inches='tight', dpi=400)
        mpl.rc_file_defaults()