There's another app from a Japanese lab but can't remember the name.
Forgive me for sharing again my writeup on this syndrome from my own experience, if you don't yourself have any such deficiencies you might find it interesting!
Rainbow color schemes are ridiculously bad. One study showed that medical professionals who look at rainbow-themed plots every day, immediately made fewer errors if presented with a simple grayscale plot instead, despite not having any experience with the grayscale color scheme.
Add to that that human perception is much better at seeing high-frequency lightness contrast than color contrast. Color contrasts are better-suited for categorical data.
Closer to 1 in 7, because the reviewer might be female (who are rarely color blind).
“Color Advice for Maps”
Brewer has been on this for a while! Mike Bostock approved. Check “colorblind safe”
Rinse and repeat.
The article seems to say "this scale is better" whilst also describing how other scales can be better. The evidence they present says to me "choose scales according to the data, the desired use, and the observer", of you ship the data used to cover a visualisation along with that visualisation then people can use their own scale altered to the purposes (and disabilities) they have.
They built a tool for any colormap. And then used it on Viridis. The result is this Cividis.
> We identified one colormap in particular to be optimal for viewing by those with or without CVD, which
we name cividis (Figs 4 and 5), generated by optimizing the viridis colormap and selecting the J'
linearization that maximizes the range of J'. We chose this map due to its wide range of colors, resulting
from a wide range of J0 values while still changing b0 significantly, and overall sharpness when overlaid
onto complex images.
So pretty closely related :)
To my eyes, cividis (which is the new scale) is good by the numbers, and there's a strong argument it's more robust for colorblind users, but viridis looks better.
Also related: seaborn (a helper library on top of matplotlib) has a special case dedicated to rejecting requests for using jet
> The jet colormap is associated with an astrophysical fluid jet simulation from the National Center for Supercomputer Applications. See the "Examples" section
Apart from the comment on line 1, that file contains 256 lines with a colour. I suppose to get a finer scale, you can interpolate with any reasonable function you like since the differences are so small.
multiply each number by 255 to get RGB val, and call Math.round() on each or let the browser round it.
With LEDs being able to project (nearly) any color the old-guard are facing some challenges.
Their proposed scale, cividis, does not have a brightness in the middle of the scale. It's the second image in the article: https://static.scientificamerican.com/sciam/assets/Image/jou...
https://www.comsol.com/blogs/a-simulation-color-table-for-en... - midway down the page.
I always hated rainbow scales because I always see artificial boundaries where the colors change between 2 contrasting ones.
+ve = positive
-ve = negative
I gave up and closed the tab.