Re: [matplotlib-devel] Matplotlib's new default colormap

[Phil E. <pel...@gm...>]

P.S. I just found
http://davidjohnstone.net/pages/lch-lab-colour-gradient-picker

On 22 December 2014 at 11:21, Phil Elson <pel...@gm...> wrote:

> Thanks for all the contributions so far. Looks like matplotlib is blessed
> with people who are far more knowledgeable than I on the subject, and I'd
> say we were pretty much at a consensus on requirements.
>
> Given these requirements, what we need is some proposed colormaps - Max's
> approach of generating an optimal solution in LAB space sounds interesting,
> as do the other approaches of minimising some parameters of existing
> colormaps.
>
> To facilitate this discussion, do we need a repository of proposed
> colormaps so that we can compare like with like? I notice that Mike Bostock
> has an interesting post to show various color spaces in d3.js which may be
> of interest http://bl.ocks.org/mbostock/3014589.
>
>
>
> On 4 December 2014 at 14:38, Maximilian Albert <
> max...@gm...> wrote:
>
>> Hi all,
>>
>> I had a discussion with Phil Elson about this last weekend during the
>> Bloomberg Open Source Day. I don't consider myself an expert on colormaps
>> by any means, but I started digging into them a while ago when I was
>> looking for a way of generating a perceptually linear *cyclic* colormap in
>> order to represent phase angle values. (I've been meaning to discuss this
>> issue on this list for a while but will do so in a different thread once I
>> get around to tidying up my results so far.) Phil encouraged me to reply to
>> this thread because he said that even non-expert views would be very
>> welcome, so here you go.
>>
>> Basically, I agree with most of what Nathaniel Smith suggested in his
>> email from November 21. I'm going to comment on some of his points inline
>> below and will finally suggest a way of designing a new colormap at the end.
>>
>>
>> Nathaniel Smith wrote:
>>
>> > it should be a sequential colormap [...]
>>
>> Agreed.
>>
>> > it should be perceptually uniform
>>
>> Agreed.
>>
>> > There's lots of research on how to measure perceptual distance --
>> > a colleague and I happen to have recently implemented a
>> > state-of-the-art model of this for another project, in case anyone
>> > wants to play with it [3].
>>
>> I haven't had time to check this out in detail yet, but it looks pretty
>> interesting and will certainly be very useful to assess the quality of any
>> suggestions. However, can this help to actually *design* a new colormap?
>> The answer might be hidden in the referenced paper [Luo2006], but I haven't
>> read it yet.
>>
>> > or just using good-old-L*a*b* is a reasonable quick-and-dirty
>> approximation.
>>
>> Can you elaborate how "dirty" you think using L*a*b* would be? (See my
>> suggestion for finding a new colormap below.)
>>
>> >- it should have a perceptually uniform luminance ramp, i.e. if you
>> > convert to greyscale it should still be uniform.
>>
>> Agreed. What's unclear to me is how large this luminance ramp should be.
>> We certainly can't go all the way to full luminance because this won't be
>> visible on a white background. This probably needs experimenting (again see
>> below).
>>
>> > - it should also have some kind of variation in hue, because
>> > hue variation is a really helpful additional cue to perception,
>> > having two cues is better than one, and there's no reason
>> > not to do it.
>>
>> Agreed.
>>
>> > - the hue variation should be chosen to produce reasonable results
>> > even for viewers with the more common types of colorblindness.
>> > (Which rules out things like red-to-green.)
>>
>> Agreed. Are you aware of any simple ways of avoiding the most common
>> issues? Are there any blog posts or papers on designing colormaps that are
>> suitable for colorblind people?
>>
>> > And, for bonus points, it would be nice to choose a hue ramp that
>> > still works if you throw away the luminance variation, because then we
>> > could use the version with varying luminance for 2d plots, and the
>> > version with just hue variation for 3d plots. (In 3d plots you really
>> > want to reserve the luminance channel for lighting/shading, because
>> > your brain is *really* good at extracting 3d shape from luminance
>> > variation. If the 3d surface itself has massively varying luminance
>> > then this screws up the ability to see shape.)
>>
>> Just out of interest, is there currently an easy way in matplotlib of
>> producing a 3d plot where luminance is used for lighting/shading as you
>> suggest?
>>
>>
>> Now the question is: how do we actually *design* a colormap with these
>> requirements? Leon Krischer's notebook [1] looks totally awesome, but if I
>> understand correctly the optimisation he uses "only" takes care of
>> linearising the luminance value, but this does not necessarily guarantee
>> that the hue values are also linear, right? It also feels somewhat clumsy
>> to me to start out with a colormap that's "wrong" (w.r.t. our requirements
>> above) and then "fix" it. However, the notebook looks like a great guidance
>> for finding suitable candidates and assessing their quality.
>>
>> It appears to me that a simple yet effective way of coming up with a good
>> colormap would be to pick two points in the L*a*b* color space that can be
>> represented by RGB values, connect them by a line and use the interpolated
>> values for the resulting colormap. Since L*a*b* space is (close to)
>> perceptually linear, this would pretty much guarantee all the requirements
>> above.
>>
>> What's missing is an easy way of doing this. I'm envisaging a simply GUI
>> which allows the user to easily pick two points in L*a*b* space, generates
>> a colormap from them as described above and also generates a few sample
>> plots to evaluate the quality of the colormap (along the lines of [1] or
>> the numerous blog posts linked to in the discussion). I am close to having
>> a prototype for such a GUI which should allow to do this relatively
>> painlessly. I'll try to finish it up over the weekend and will post here
>> once it's ready. Btw, if anyone has suggestions for sample datasets that
>> can help in assessing the quality of colormaps they would be much
>> appreciated.
>>
>> Any comments or clarifications of points that I misunderstood are very
>> welcome.
>>
>> Best wishes,
>> Max
>>
>> [1] http://nbviewer.ipython.org/gist/krischer/d35096a9d3b6da5846a5
>>
>>
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