# Colormap Resources
* [In Search of a Perfect Colormap](http://inversed.ru/Blog_2.htm) by Peter Karpov provides assessments and information about many common colormaps, including a simple way to download colormaps as CSV files. However, no license information is indicated on the page, and I suspect the source colormap licenses are not properly respected.
* [mpl colormaps](https://bids.github.io/colormap/) include `magma`, `inferno`, `plasma`, and `viridis` by Nathaniel J. Smith, Stefan van der Walt, Eric Firing. They are now included with matplotlib ([colormaps.py](https://github.com/BIDS/colormap/blob/master/colormaps.py)) under a permissive CC0 license (public domain) so they can be easily included in other projects.
* [Turbo, An Improved Rainbow Colormap for Visualization](https://ai.googleblog.com/2019/08/turbo-improved-rainbow-colormap-for.html) describes an excellent rainbow-like alternative to Jet which was created by Google. RGB vales can be sourced from [turbo_colormap.c](https://gist.github.com/mikhailov-work/6a308c20e494d9e0ccc29036b28faa7a) or [turbo_colormap.py](https://gist.github.com/mikhailov-work/ee72ba4191942acecc03fe6da94fc73f)
 It's released under the Apache 2.0 license which indicates "In every licensed file changed, a notification must be added stating that changes have been made to that file".
* [Beautiful colormaps for oceanography: cmocean](https://matplotlib.org/cmocean/) by Kristen Thyng ([matplotlib/cmocean on GitHub](https://github.com/matplotlib/cmocean)) is a fantastic collection of colormaps and information written by ascientist with extensive experience using colormaps to display oceanographic data
* [cpt-city: An archive of colour gradients](http://soliton.vm.bytemark.co.uk/pub/cpt-city/) is an impressively-large list of publicly-available colormaps collected together with their license files.