On Thursday, September 22, 2011, Tony Yu <tsy...@gmail.com> wrote:
> On Thu, Sep 22, 2011 at 5:16 PM, Nathaniel Smith <n...@pobox.com> wrote:
>>
>> On Sep 21, 2011 5:29 PM, "Christoph Gohlke" <cgoh...@uci.edu> 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 <
http://www.cs.unm.edu/%7Ekmorel/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. ;)
If it only prevents one person from publishing in "jet", then we really
stink in our jobs of promoting matplotlib...
Anyway, this is certainly is worthy of debate, but it certainly won't happen
for this release. We should be cutting RC tomorrow.
After the release, I encourage you guys to make your cases. Show us plots
that have been in "jet" and show them as better in another colormap.
As a bit of a challenge to you all, I am not color-blind, but I do wear
tinted glasses that make it difficult to tell the difference between darker
blues and black, and sometimes greens and blues are hard to distinguish.
Furthermore, as a radar meteorologist, I am very accustomed to the
colormaps commonly used for radar reflectivies (and is similar to "jet").
Of course, I am not the only one to convince (and others could certainly
overrule me)...
Ben Root
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