I have opened a PR to document this discussion. It is meant to provide a
permanent record of the thought process leading up to color map and to
serve as a tool in making the finial decision.
https://github.com/matplotlib/matplotlib/pull/4238
On Mon, Mar 2, 2015 at 6:32 AM jni <jni.s...@gmail.com> wrote:
> Hi Pierre,
>
> Could you please elaborate a bit on this
>> usecase. I was thinking, naively, that when plotting a grayscale image,
>> one would simply used a gray colormap.
>>
>
> Using a colormap with hue and saturation gives you better contrast than
> pure grayscale. For natural images, that is, photographs of human-scale
> objects, indeed grayscale is a good choice, because that is how we are used
> to looking at those images. But for looking at physical quantities, for
> example, using a colormap with hue and saturation as well as lightness is
> useful. Here are some examples:
> http://www.gnuplotting.org/color-maps-from-colorbrewer/
> https://www.mrao.cam.ac.uk/~dag/CUBEHELIX/
>
> See also a "boundary probability map" for a natural image here (panel B,
> top right):
>
> http://www.frontiersin.org/files/Articles/74212/fninf-08-00034-r2/image_m/fninf-08-00034-g001.jpg
> Having the colormap makes it easier to place the intermediate levels of
> the probability map.
>
> Again, restricting the lightness range for these maps would be
> problematic, to say the least.
>
> Juan.
>
> ------------------------------
> View this message in context: Re: release strategy and the color
> revolution
> <http://matplotlib.1069221.n5.nabble.com/release-strategy-and-the-color-revolution-tp44929p45030.html>
> Sent from the matplotlib - devel mailing list archive
> <http://matplotlib.1069221.n5.nabble.com/matplotlib-devel-f28077.html> at
> Nabble.com.
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