swiftascmaps:泰勒·斯威夫特(Taylor Swift)启发的色彩图

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  • 2022-04-06 07:55
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泰勒·斯威夫特(Taylor Swift)彩色地图收藏。 包括基于以下相册的颜色图: 红色(红色,red_r) 1989年(nineteen_eighty_nine,nineteen_eighty_nine_r) 声誉(信誉,声誉_r) 情人(情人,lover_r) 民俗(民俗,民俗_r) Evermore(evermore,evermore_r,evermore_shifted,evermore_shifted_r) 无所畏惧:泰勒的版本(fearless_tv,fearless_tv_r) 许可证:LGPLv3作者:Josh Borrow( ) 用法 要使用它们,您可以导入它们,并将其与matplotlib一起使用,就像与其他任何颜色图一样。 from swiftascmaps import red from matplotlib . pyplot import
swiftascmaps-master.zip
  • swiftascmaps-master
  • images
  • folklore.png
    965.4KB
  • lover.png
    866.6KB
  • evermore.png
    1.4MB
  • 1989.png
    753.3KB
  • fearless_tv.png
    725.9KB
  • lightness_cmaps_re_recordings.png
    27.3KB
  • lightness_swift_as_cmaps.png
    60.9KB
  • evermore_shifted.png
    1.3MB
  • reputation.png
    315.8KB
  • red.png
    1005.8KB
  • swiftascmaps
  • colors.py
    928B
  • __init__.py
    1.5KB
  • make_cmap.py
    1.2KB
  • __version__.py
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  • LICENSE.txt
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  • requirements.txt
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  • setup.py
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  • README.md
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内容介绍
Taylor Swift color map collection. 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) License: LGPLv3 Author: Josh Borrow (josh@joshborrow.com) Usage ----- To use these, you can import them and use them with matplotlib as you would with any other color map. ```python from swiftascmaps import red from matplotlib.pyplot import imshow from numpy import random imshow(random.rand(128, 128), cmap=red) ``` Examples -------- ### Red ![](images/red.png) ### 1989 ![](images/1989.png) ### Reputation ![](images/reputation.png) ### Lover ![](images/lover.png) ### Folklore ![](images/folklore.png) ### Evermore ![](images/evermore.png) ### Evermore shifted ![](images/evermore_shifted.png) ### Fearless: Taylor's Version ![](images/fearless_tv.png) 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. ![](images/lightness_swift_as_cmaps.png) ![](images/lightness_cmaps_re_recordings.png) For quantitative comparisons, please ensure that you use a perceptually uniform colour map (see e.g. those available directly through [matplotlib](https://matplotlib.org/3.1.0/tutorials/colors/colormaps.html)).
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