Re: [matplotlib-devel] Another colormap

[Tony Yu <ts...@gm...>]

On Thu, Sep 22, 2011 at 5:16 PM, Nathaniel Smith <nj...@po...> wrote:

> On Sep 21, 2011 5:29 PM, "Christoph Gohlke" <cg...@uc...> wrote:
> > On 9/13/2011 12:24 AM, Eric Firing wrote:
> > > On 07/18/2011 07:07 AM, Sameer Grover wrote:
> > >> I came across this website where different colormaps have been
> compared
> > >> and the author has come up with an optimal colormap for data
> > >> visualization called the "cool-warm colormap".
> > >>
> > >> http://www.cs.unm.edu/~kmorel/documents/ColorMaps/index.html
> > >>
> > >> It is somewhat similar to the cool colormap already included in
> > >> matplotlib, but I've added the new colormap to matplotlib in the patch
> > >> attached in case it is deemed fit to be included in the matplotlib
> source.
> > > We should include this, but I think the 257-entry version is overkill;
> > > it adds a big chunk to the _cm.py file, and I doubt it is visually
> > > distinguishable from the 33-entry version.  Would you mind providing a
> > > patch for the latter?  (Or better yet, the functions that generate the
> > > r,g,b values.)
> > Here's a pull request for the 33 entry map:
> > <https://github.com/matplotlib/matplotlib/pull/486>
>
> Let me open a can of worms here...
>
> I looked at the paper, and the goal was specifically to produce a good
> "default" colormap - not necessarily the best for any situation, but good
> overall and certainly better than the rainbow ('jet') colormap in most
> cases. (I agree with the author that jet is pretty terrible and tends to
> distort data.)
>
> Should we switch to this as the default matplotlib colormap? I think it
> would be a clear improvement.
>
I have absolutely no clout here, but I'd definitely be in favor of changing
the default colormap away from "jet".

Personally, I'd prefer a two-tone colormap as the default (two-distinct
tones at the limits with a gradient in-between---dubbed "sequential" in the
paper) instead of a three-tone colormap (three-distinct tones---dubbed
"diverging" in the paper). (I think this is a more common use case, and I
think using a "diverging" colormap effectively requires setting vmin/vmax.)
But really, (almost) anything is better than "jet".

Don't misunderstand: I know I can change the default colormap in my
matplotlibrc file (and this is what I do). But 90% of people don't bother to
change the defaults. If changing this default in matplotlib prevents just 1
person from publishing a paper with a "jet" colormap, I think we'll have
made the world a better place. ;)

-Tony