Skip to content
A set of useful perceptually uniform colormaps for plotting scientific data
Branch: master
Clone or download
jsignell Fixing wheel (#21)
Following comment in #16
Latest commit e3ba0aa Feb 15, 2019
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
assets Version 1.0.0 Sep 25, 2017
colorcet Updated to use pyct, pyctdev, nbsite (#19) Feb 13, 2019
doc Last fixes before release (#20) Feb 14, 2019
examples Last fixes before release (#20) Feb 14, 2019
.appveyor.yml
.gitattributes Updated to use pyct, pyctdev, nbsite (#19) Feb 13, 2019
.gitignore
.travis.yml
LICENSE.txt
MANIFEST.in
README.md
dodo.py
pyproject.toml
setup.cfg
setup.py
tox.ini Updated to use pyct, pyctdev, nbsite (#19) Feb 13, 2019

README.md



Colorcet: Collection of perceptually uniform colormaps

Build Status Linux/MacOS Build Status Windows Build status
Latest dev release Github tag
Latest release Github release PyPI version colorcet version conda-forge version defaults version
Docs gh-pages site

What is it?

Colorcet is a collection of perceptually uniform colormaps for use with Python plotting programs like bokeh, matplotlib, holoviews, and datashader based on the set of perceptually uniform colormaps created by Peter Kovesi at the Center for Exploration Targeting.

Installation

Colorcet supports Python 2.7, 3.5, 3.6 and 3.7 on Linux, Windows, or Mac and can be installed with conda:

    conda install colorcet

or with pip:

    pip install colorcet

For more information take a look at Getting Started.

Learning more

You can see all the details about the methods used to create these colormaps in Peter Kovesi's 2015 arXiv paper. Other useful background is available in a 1996 paper from IBM.

The matplotlib project also has a number of relevant resources, including an excellent 2015 SciPy talk, the viscm tool for creating maps like the four in mpl, the cmocean site collecting a set of maps created by viscm, and the discussion of how the mpl maps were created.

Samples

All the colorcet colormaps that have short, memorable names (which are probably the most useful ones) are visible here:

But the complete set of 50+ is shown in the User Guide.

About PyViz

Colorcet is part of the PyViz initiative for making Python-based visualization tools work well together. See pyviz.org for related packages that you can use with Colorcet and status.pyviz.org for the current status of each PyViz project.

You can’t perform that action at this time.