mplcyberpunk 0.7.6

Add-on for Matplotlib to produce 'Cyberpunk' style plots

mplcyberpunk

A Python package on top of matplotlib to create 'cyberpunk' style plots with 3 additional lines of code.

Installation

pip install mplcyberpunk

Usage

After importing the package, the cyberpunk stylesheet (dark background etc.) is available via plt.style.use. The line glow and 'underglow' effects are added via calling add_glow_effects:

import matplotlib.pyplot as plt
import mplcyberpunk

plt.style.use("cyberpunk")

plt.plot([1, 3, 9, 5, 2, 1, 1], marker='o')
plt.plot([4, 5, 5, 7, 9, 8, 6], marker='o')

mplcyberpunk.add_glow_effects()

plt.show()

Result:

This effect is currently only implemented for lines.

The individual steps are described here in more detail.

Add effects individually

Instead of add_glow_effects, you can add the line glow and underglow effects separately:

mplcyberpunk.make_lines_glow()
mplcyberpunk.add_underglow()

You can also add the effect to a specific axis object explicitly:

fig, ax = plt.subplots()
...
mplcyberpunk.make_lines_glow(ax)

To activate the glow effect only for specific lines, pass a Line2D object or a list of Line2Ds to make_lines_glow.

Gradient glow

Gradient underglow effect can be added with

mplcyberpunk.add_glow_effects(gradient_fill=True)

or independently of line glow with

mplcyberpunk.add_gradient_fill(alpha_gradientglow=0.5)

add_gradient_fill takes a gradient_start argument for different gradient starting values:

Different glow configurations:

Scatter plots

Glow effect can be added to scatter plots via mplcyberpunk.make_scatter_glow():

Colormap

The default colormap is cool:

Others:

Bar charts

import matplotlib.pyplot as plt
import mplcyberpunk

plt.style.use('cyberpunk')

categories = ['A', 'B', 'C', 'D', 'E']
values = [25, 67, 19, 45, 10]
colors = ["C0", "C1", "C2", "C3", "C4"]

bars = plt.bar(categories, values, color=colors, zorder=2)

mplcyberpunk.add_bar_gradient(bars=bars)

plt.show()

Gallery

Some images can be bought as posters here.