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https://github.com/lmcinnes/glasbey

Algorithmically create or extend categorical colour palettes
https://github.com/lmcinnes/glasbey

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Algorithmically create or extend categorical colour palettes

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README 

        
.. -*- mode: rst -*-



.. image:: doc/glasbey_logo.png

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  :alt: Glasbey logo

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=======================================

Glasbey Categorical Color Palette Tools

=======================================



The glasbey library allows for the algorithmic creation of colour palettes designed for use with categorical data

using techniques from the paper Colour Displays for Categorical Images by Glasbey, Heijden, Toh and Gray. You don't

need to worry about the technical details however -- the glasbey library is easy to use.



It is quite common to require a colour palette for some categorical data such that each category has a visually

distinctive colour. Usually one relies upon predefined colour palettes such as those from

`ColorBrewer `_, or provided by your plotting library of

choice. Unfortunately such palettes do not always meet your needs: perhaps they don't have enough distinct colours and

you don't want to re-use or cycle the palette; perhaps you have specific constraints you want to apply to get a

certain look to your palette. Fortunately we can use math and perceptual colour spaces to create new palettes that

maximize the perceptual visual distinctiveness of colours within constraints. It is also easy to extend an

existing palette, or seed a created palette with some initial colours (perhaps your company or institutions colours).

Lastly, glasbey makes it easy to generate block palettes, suitable for working with hierarchical categories.



Create categorical palettes



.. image:: doc/glasbey_basic_palette.png

  :width: 600

  :alt: Glasbey basic palette example

  :align: center



or constrain the palette options (e.g. to muted colours)



.. image:: doc/glasbey_muted_palette.png

  :width: 600

  :alt: Glasbey muted palette example

  :align: center



or extend existing palettes



.. image:: doc/glasbey_tab10_palette.png

  :width: 600

  :alt: Glasbey extending tab10 example

  :align: center



or create block categorical palettes



.. image:: doc/glasbey_block_palette.png

  :width: 600

  :alt: Glasbey block palette example

  :align: center



-----------

Basic Usage

-----------



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



.. code:: python3



    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.



.. code:: python3



    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:



.. code:: bash



    pip install glasbey



To manually install this package:



.. code:: bash



    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.



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References

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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



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License

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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.