metalmaps 0.3.3

Metal and rock inspired Matplotlib colormaps.

Metalmaps - Heavy Metal and Classic Rock Album Art Inspired Matplotlib Colormaps

Ever wanted to make your python plots more metal? Fear not, now you can! metalmaps delivers heavy metal and classic rock album art inspired matplotlib colormaps!

All of this was inspired by (and shamelessly copied from) Josh Borrow's swiftascmaps.

License: LGPLv3

Authors: Mladen Ivkovic, Josh Borrow

Installation

Install this package via pip:

pip install metalmaps

Alternatively, grab the source from github.

Usage

To use these, you can import them and use them with matplotlib as you would with any other color map.

from metalmaps import black_sabbath
from matplotlib.pyplot import imshow
from numpy import random

imshow(random.rand(128, 128), cmap=black_sabbath)

The color maps can also be accessed in matplotlib using strings by prefixing metalmaps, e.g.

import metalmaps

imshow(random.rand(128, 128), cmap="metalmaps.red")

Examples

This package currently includes over 20 examples, and counting:

• The Apostasy (Behemoth)
• Black Sabbath (Black Sabbath)
• The Blues Brothers (The Blues Brothers)
• Blues Pills (Blues Pills)
• Cosmo's Factory (Creedence Clearwater Revival)
• Deep Purple in Rock (Deep Purple)
• The Dethalbum (Dethklok)
• From Mars to Sirius (Gojira)
• L.A. Woman (The Doors)
• London Calling (The Clash)
• Master of Puppets (Metallica)
• Made in Japan (Deep Purple)
• Meteora (Linkin Park)
• obZen (Meshuggah)
• Paranoid (Black Sabbath)
• Ride the Lightning (Metallica)
• The Rise and Fall of Ziggy Stardust and the Spiders From Mars (David Bowie)

:exclamation: For a full gallery, visit https://mladenivkovic.github.io/metalmaps/metalmaps.html

Here are some examples:

Black Sabbath (Black Sabbath)

Deep Purple in Rock (Deep Purple)

From Mars To Sirius (Gojira)

Master of Puppets (Metallica)

obZen (Meshuggah)

Paranoid (Black Sabbath)

Note

Of course, these aren't necessarily designed to be colorblind friendly, or perceptually uniform, so use them with caution. They are fun though. To underline how much you should not use these in a real scientific publication (apart from perhaps qualitative imaging), the lightness values are shown below.

For quantitative comparisons, please ensure that you use a perceptually uniform colour map (see e.g. those available directly through matplotlib).

Contributing

Yes please! It would be grand to collect even more album art colormaps.

Intstructions:

• generate your color palette any way you please, and add it to colors.py
• instantiate the matplotlib colormap in __init__.py
• submit your merge request
• ???
• profit!

Image Credits

• The "Kelvin-Helmholtz" data used in the plots below were generated using mesh-hydro.
• The "EAGLE" data used in the plots below were obtained from the swiftsim repository.
• The "NGC" data used in the plots below were originally obtained from flickr, credits to Judy Schmidt. I modified the image later to normalize the pixel values to be able to demonstrate the colormaps as above.