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)
• Life of a Showgirl (life_of_a_showgirl, life_of_a_showgirl_r)

Please note that The Tortured Poets Department is not included in this collection due to its unispring album cover. Taylor, if you want me to make colour maps for you, stop making black and white covers!

License: LGPLv3 Author: Josh Borrow ([email protected])

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

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")

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).