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COLORMAP documentation

Please see : http://colormap.readthedocs.io/ for an up-to-date documentation.

https://github.com/cokelaer/colormap/actions/workflows/ci.yml/badge.svg?branch=main https://coveralls.io/repos/cokelaer/colormap/badge.png?branch=main
version:Python 3.8, 3.9, 3.10, 3.11, 3.12
contributions:Please join https://github.com/cokelaer/colormap
issues:Please use https://github.com/cokelaer/colormap/issues
notebook:Please see https://github.com/cokelaer/colormap/tree/main/notebooks

What is it ?

colormap package provides simple utilities to convert colors between RGB, HEX, HLS, HUV and a class to easily build colormaps for matplotlib. All matplotlib colormaps and some R colormaps are available altogether. The plot_colormap method (see below) is handy to quickly pick up a colormaps and the test_colormap is useful to see test a new colormap.

Installation

pip install colormap

Example

  • Create your own colormap from red to green colors with intermediate color as whitish (diverging map from red to green):

    c = Colormap()
    mycmap = c.cmap( {'red':[1,1,0], 'green':[0,1,.39], 'blue':[0,1,0]})
    cmap = c.test_colormap(mycmap)
    
  • Even simpler if the colormap is linear:

    c = Colormap()
    mycmap = c.cmap_linear('red', 'white', 'green(w3c)')
    cmap = c.test_colormap(mycmap)
    

https://colormap.readthedocs.io/en/latest/_images/quickstart-6.png

  • check out the available colormaps:

    c = Colormap()
    c.plot_colormap('diverging')
    

https://colormap.readthedocs.io/en/latest/_images/quickstart-4.png

See online documentation for details: http://colormap.readthedocs.io/

changelog

Version Description
1.1.0
  • switch to pyproject. remove easydev dependency. compat for python 3.11 and 3.12
1.0.6
  • Fix a matplotlib deprecation
  • Fix RTD documentation
1.0.5
  • remove Python3.6 and added Python3.10 to CI action
  • Fix issue in setup reported in cokelaer#14
  • add requirements in MANIFEST
  • applied black on all files

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Utilities to visualise and create matplotlib colormaps and various color codecs

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  • Jupyter Notebook 80.2%
  • Python 19.8%
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