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IBM did research back in the 90s on perceptually-based colormaps and how to best represent various types of data within the color dimensions of luminescence, sa

IBM did research back in the 90s on perceptually-based colormaps and how to best represent various types of data within the color dimensions of luminescence, saturation and hue [1]. For exmpale, they found that, (1) Hue was not a good dimension for encoding magnitude information, i.e. rainbow color maps are bad. (2) The mechanisms in human vision responsible for high spatial frequency information processing are luminance channels. If the data to be represented have high spatial frequency, use a colormap which has a strong luminance variation across the data range. (3) For interval and ratio data, both luminance- and saturation-varying colormaps should produce the effect of having equal steps in data value correspond to equal perceptual steps, but the first will be most effective for high spatial frequency data variations and the second will be most effective for low spatial frequency variations. === [1] https://www.research.ibm.com/people/l/lloydt/color/color.HTM https://www.research.ibm.com/people/l/lloydt/color/color.HTM or as pdf: https://github.com/frankMilde/interesting-reads/blob/master/ibm-research__why-should-engineers-and-scientists-be-worried-about-color.pdf https://github.com/frankMilde/interesting-reads/blob/master/...

jordache 8y ago
Neither links work.
- splittingTimes 8y ago
  Indeed the original IBM link was taken down: https://web.archive.org/web/20180225102505/https://www.research.ibm.com/people/l/lloydt/color/color.HTM https://web.archive.org/web/20180225102505/https://www.resea... GitHub displays the PDF just fine on desktop but fails on mobile.
nerdponx 8y ago
As a result, we have the colormap Viridis [0] [1], which is universally one of the best options available. Odd to see a data viz article about color choice in 2018 that doesn't mention Viridis. [0]: https://www.youtube.com/watch?v=xAoljeRJ3lU https://www.youtube.com/watch?v=xAoljeRJ3lU [1]: https://www.youtube.com/watch?v=TojFwkglCKs https://www.youtube.com/watch?v=TojFwkglCKs
- aflam 8y ago
  Odd indeed, especially since it has all the other useful tools one could use to create palettes. Maybe the target audience is creative people, not us just reusing ad nauseum the same effective palette.
- vanderZwan 8y ago
  And yesterday a paper explaining the process of creating Cividis, an even more CVD friendly iteration, was published on plos.org[0]. It's already in Matplotlib, and available for R[1]. (I submitted it yesterday but it didn't get much traction[2], which makes sense given how specific it is) [0] http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0199239 http://journals.plos.org/plosone/article?id=10.1371%2Fjourna... [1] https://github.com/marcosci/cividis https://github.com/marcosci/cividis [2] https://news.ycombinator.com/item?id=17667572 https://news.ycombinator.com/item?id=17667572
  - nemetroid 8y ago
    I looked at the paper, and wouldn't really call cividis an iteration of viridis. It's more of a conversion of viridis to "CVD colorspace" (can you say that?), with a few tweaks applied.
    - vanderZwan 8y ago
      Well, from my CVD point of view it looks like one ;). It's largely the same except with better color contrast and ability to distinguish detail. But I understand it actually is missing a significant chunk of green hues for the non-colorblind.
yiyus 8y ago
> rainbow color maps are bad This is true. But, unfortunately, it is the current standard for many applications. For example: although a luminance-varying colormap is theoretically better, if my doctor has been analyzing MRI scans using the jet palette for 30 years, I want him to use that color palette when he analyzes mine, instead of using a new one. I have similar problems in my work, when representing crystallographic textures. The standard way of representing them has multiple problems (not only color choices, but also the use of Euler angles to represent orientations is a huge headache). However, if I publish a paper using a different (objectively better) method, nobody will understand my figures. I have tried including both, but I think almost everybody just ignores the new ones.
- bastijn 8y ago
  We have been fighting that fight for a while in viz. Spreading the word already in 2012 in "Rainbow colormaps - What are they good for? Absolutely nothing!" [0] That article/post reached some audience and was referenced quite well at the time. Keep spreading the word I guess. [0] http://medvis.org/2012/08/21/rainbow-colormaps-what-are-they-good-for-absolutely-nothing/ http://medvis.org/2012/08/21/rainbow-colormaps-what-are-they...
weinzierl 8y ago
I agree with all of this. I encountered one problem when using luminance (either alone or in combination with color) to encode categorical data though: Luminance inevitably conveys a certain ordering. A dark black line will be automatically identified as more as important than a light grey line. This can be desired (and abused), but often I want to present my categories as neutral as possible. I experimented with balancing lightness with other features (like line width) but not with much success.

jordache 8y ago

Neither links work.

splittingTimes 8y ago
Indeed the original IBM link was taken down: https://web.archive.org/web/20180225102505/https://www.research.ibm.com/people/l/lloydt/color/color.HTM https://web.archive.org/web/20180225102505/https://www.resea... GitHub displays the PDF just fine on desktop but fails on mobile.

nerdponx 8y ago

As a result, we have the colormap Viridis [0] [1], which is universally one of the best options available. Odd to see a data viz article about color choice in 2018 that doesn't mention Viridis. [0]: https://www.youtube.com/watch?v=xAoljeRJ3lU https://www.youtube.com/watch?v=xAoljeRJ3lU [1]: https://www.youtube.com/watch?v=TojFwkglCKs https://www.youtube.com/watch?v=TojFwkglCKs

aflam 8y ago
Odd indeed, especially since it has all the other useful tools one could use to create palettes. Maybe the target audience is creative people, not us just reusing ad nauseum the same effective palette.
vanderZwan 8y ago
And yesterday a paper explaining the process of creating Cividis, an even more CVD friendly iteration, was published on plos.org[0]. It's already in Matplotlib, and available for R[1]. (I submitted it yesterday but it didn't get much traction[2], which makes sense given how specific it is) [0] http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0199239 http://journals.plos.org/plosone/article?id=10.1371%2Fjourna... [1] https://github.com/marcosci/cividis https://github.com/marcosci/cividis [2] https://news.ycombinator.com/item?id=17667572 https://news.ycombinator.com/item?id=17667572
- nemetroid 8y ago
  I looked at the paper, and wouldn't really call cividis an iteration of viridis. It's more of a conversion of viridis to "CVD colorspace" (can you say that?), with a few tweaks applied.
  - vanderZwan 8y ago
    Well, from my CVD point of view it looks like one ;). It's largely the same except with better color contrast and ability to distinguish detail. But I understand it actually is missing a significant chunk of green hues for the non-colorblind.

yiyus 8y ago

> rainbow color maps are bad This is true. But, unfortunately, it is the current standard for many applications. For example: although a luminance-varying colormap is theoretically better, if my doctor has been analyzing MRI scans using the jet palette for 30 years, I want him to use that color palette when he analyzes mine, instead of using a new one. I have similar problems in my work, when representing crystallographic textures. The standard way of representing them has multiple problems (not only color choices, but also the use of Euler angles to represent orientations is a huge headache). However, if I publish a paper using a different (objectively better) method, nobody will understand my figures. I have tried including both, but I think almost everybody just ignores the new ones.

bastijn 8y ago
We have been fighting that fight for a while in viz. Spreading the word already in 2012 in "Rainbow colormaps - What are they good for? Absolutely nothing!" [0] That article/post reached some audience and was referenced quite well at the time. Keep spreading the word I guess. [0] http://medvis.org/2012/08/21/rainbow-colormaps-what-are-they-good-for-absolutely-nothing/ http://medvis.org/2012/08/21/rainbow-colormaps-what-are-they...

weinzierl 8y ago

I agree with all of this. I encountered one problem when using luminance (either alone or in combination with color) to encode categorical data though: Luminance inevitably conveys a certain ordering. A dark black line will be automatically identified as more as important than a light grey line. This can be desired (and abused), but often I want to present my categories as neutral as possible. I experimented with balancing lightness with other features (like line width) but not with much success.