On Sun, Apr 5, 2015 at 12:46 AM, Eric Firing <efir...@hawaii.edu> wrote: > On 2015/04/04 9:20 PM, Nathaniel Smith wrote: > >> While it's taking longer than hoped, just to reassure you that this >> isn't total vaporware, here's a screenshot from the colormap designer >> that Stéfan van der Walt and I have been working on... still needs >> fine-tuning (which at this point probably won't happen until after I >> get back from PyCon), but we like what we're seeing so far :-) >> >> The colormap shown has, by construction, perfect lightness linearity >> and perfect perceptual uniformity, according to the better-than-CIELAB >> model used by the viscm tool I linked upthread. >> > > Thanks for the update, and the progress. The example colormap looks > promising as a viable alternative. It appears to have good contrast. How > well does this type of map work with the colorblindness filters?
Blue/yellow contrast is preserved with the common types of colorblindness, so it should become a smooth ramp of blue -> (reddish/greyish, depending on details/severity of color deficiency) -> yellow. And the luminance remains linear. So it's definitely not a disaster. Beyond that I'm not entirely sure how to numerically quantify perceptual uniformity for colorblind users -- we could use the sRGB->sRGB formulas for simulating colorblindness for non-colorblind viewers and then use the regular non-colorblind uniformity estimates, but I have no idea how accurate that would be... my guess though is that the way that colormaps is designed ATM it will have somewhat faster hue shifts in the lower (blue) region than the upper (yellow) region, and fastest in the middle, though this effect shouldn't be huge (and to some extent is inevitable with any map that's both colorful and perceptually uniform for non-colorblind users). Thinking through these details is one of the things I had in mind when I mentioned "fine tuning" above though :-). We'd welcome any feedback from readers with non-simulated color deficiency! -n -- Nathaniel J. Smith -- http://vorpus.org ------------------------------------------------------------------------------ Dive into the World of Parallel Programming The Go Parallel Website, sponsored by Intel and developed in partnership with Slashdot Media, is your hub for all things parallel software development, from weekly thought leadership blogs to news, videos, case studies, tutorials and more. Take a look and join the conversation now. http://goparallel.sourceforge.net/ _______________________________________________ Matplotlib-devel mailing list Matplotlib-devel@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-devel
