glasbey 0.1.0

Basic Usage

Creating new categorical colour palettes is as easy as single function call.

import glasbey

# Create a categorical palette with 15 colours
glasbey.create_palette(palette_size=15)
# Create a muted palette with 12 colours
glasbey.create_palette(palette_size=12, lightness_bounds=(20, 40), chroma_bounds=(40, 50))

It is also easy to extend an existing palette, or create a new palette from some seed colours.

import glasbey

# Add an extra 5 colours to matplotlib's tab10 palette
glasbey.extend_palette("tab10", palette_size=15)
# Seed a palette with some initial colours
glasbey.extend_palette(["#2a3e63", "#7088b8", "#fcaf3e", "#b87088"], palette_size=8)

Installation

Glasbey requires:

• numba

• numpy

• colorspacious

• matplotlib

Glasbey can be installed via pip:

pip install glasbey

To manually install this package:

wget https://github.com/lmcinnes/glasbey/archive/main.zip
unzip main.zip
rm main.zip
cd glasbey-main
python setup.py install

Acknowledgements

This library is heavily indebted to the original glasbey library by Sergey Alexandrov.

References

1. Glasbey, C., van der Heijden, G., Toh, V. F. K. and Gray, A. (2007), Colour Displays for Categorical Images. Color Research and Application, 32: 304-309

2. Luo, M. R., Cui, G. and Li, C. (2006), Uniform Colour Spaces Based on CIECAM02 Colour Appearance Model. Color Research and Application, 31: 320–330

License

Glasbey is MIT licensed. See the LICENSE file for details.

Contributing

Contributions are more than welcome! If you have ideas for features of projects please get in touch. Everything from code to notebooks to examples and documentation are all equally valuable so please don’t feel you can’t contribute. To contribute please fork the project make your changes and submit a pull request. We will do our best to work through any issues with you and get your code merged in.