swiftascmaps

Taylor Swift inspired Matplotlib colormaps.


Licenses
LGPL-3.0/GPL-3.0+
Install
pip install swiftascmaps==1.5.0

Documentation

Taylor Swift color map collection.

DOI

Quick start: pip install swiftascmaps

Includes color maps based on the following albums:

  • Red (red, red_r)
  • 1989 (nineteen_eighty_nine, nineteen_eighty_nine_r)
  • Reputation (reputation, reputation_r)
  • Lover (lover, lover_r)
  • Folklore (folklore, folklore_r)
  • Evermore (evermore, evermore_r, evermore_shifted, evermore_shifted_r)
  • Fearless: Taylor's Version (fearless_tv, fearless_tv_r)
  • Red: Taylor's Version (red_tv, red_tv_r)
  • Midnights (midnights, midnights_r)
  • Speak Now: Taylor's Version (speak_now_tv, speak_now_tv_r)
  • 1989: Taylor's Version (nineteen_eighty_nine_tv, nineteen_eighty_nine_tv_r)

License: LGPLv3 Author: Josh Borrow (josh@joshborrow.com)

If you prefer to use R, there is an alternative package maintained as taloRswift.

Usage

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

from swiftascmaps import red
from matplotlib.pyplot import imshow
from numpy import random

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

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

import swiftascmaps

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

Examples

Note

Of course, these aren't necessarily designed to be colorblind friendly, or perceptually uniform, so use them with caution. They are quite pretty 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).