3 ms·

For example, if you want to show the spatial extent of some Gibbs (ringing) phenomenon at the edge of a structure that itself takes on a wide range of values (t

For example, if you want to show the spatial extent of some Gibbs (ringing) phenomenon at the edge of a structure that itself takes on a wide range of values (this is descriptive of visualizations I've had to make). The basic shape of the structure, and its low-frequency value patterns are already known (part of the problem definition), so increasing discriminability will make the colormap more useful.

CorrectHorseBat 5y ago
You're increasing the discriminability at the cost of high _local_ distortion, I don't see how that is a good tradeoff. As a comparison, what would you rather have: a non-distorted plot or a plot that is on average about three times as big, but it's heavily distorted. At some places it's smaller than the original and on other places it's 5 times bigger. Would you really choose the bigger figure? That is what jet is. Look at this plot https://youtu.be/xAoljeRJ3lU?t=791 https://youtu.be/xAoljeRJ3lU?t=791 (watch the whole video if you have the time), ideally you want the derivatives (the 2 plots on the left top) to be constant so not to distort your data. Jet is all over the place while viridis is basically constant (not shown in the slides, but the derivative stays all the way around 120).
- an1sotropy 5y ago
  We're not really disagreeing. I also like properties of Viridis, but it doesn't make it better for all tasks. It is a shorter path through color space, so it is not as good for some tasks. "Distortion" is not really a well-defined term, absent a particular visual analysis task. People can say "use viridis" with as much self-assured confidence as others say "use python", but they're still missing the point that different needs call for different tools.
  - CorrectHorseBat 5y ago
    I'm disagreeing with you, and I say "never use jet" (I'm more a fan of Magma) with a lot more confidence than I would say "use python". Different needs call for different tools but there is no need that calls for making distorted plots of your data. Jet adds information that is not there, you never want that.
    - an1sotropy 5y ago
      Every data visualization is necessarily a contrivance because it is creating visual features for things that weren't already visual. Data visualization research has not been able to formalize a rigorous notion of visual "information" in a form that usefully predicts performance across the enormous variety of visualization tasks and settings for which colormaps might be applied. "Distortion" is also a common but somewhat meaningless term. You're referring to perceptual effects (related to color appearance) that are side-effects of using "jet", but again, for some tasks they may be an acceptable side-effect, given the benefits of increased discriminability. Our different levels of certainty and conviction may arise from my being a data vis academic, rather than a tool user or tool builder.

CorrectHorseBat 5y ago

You're increasing the discriminability at the cost of high _local_ distortion, I don't see how that is a good tradeoff. As a comparison, what would you rather have: a non-distorted plot or a plot that is on average about three times as big, but it's heavily distorted. At some places it's smaller than the original and on other places it's 5 times bigger. Would you really choose the bigger figure? That is what jet is. Look at this plot https://youtu.be/xAoljeRJ3lU?t=791 https://youtu.be/xAoljeRJ3lU?t=791 (watch the whole video if you have the time), ideally you want the derivatives (the 2 plots on the left top) to be constant so not to distort your data. Jet is all over the place while viridis is basically constant (not shown in the slides, but the derivative stays all the way around 120).

an1sotropy 5y ago
We're not really disagreeing. I also like properties of Viridis, but it doesn't make it better for all tasks. It is a shorter path through color space, so it is not as good for some tasks. "Distortion" is not really a well-defined term, absent a particular visual analysis task. People can say "use viridis" with as much self-assured confidence as others say "use python", but they're still missing the point that different needs call for different tools.
- CorrectHorseBat 5y ago
  I'm disagreeing with you, and I say "never use jet" (I'm more a fan of Magma) with a lot more confidence than I would say "use python". Different needs call for different tools but there is no need that calls for making distorted plots of your data. Jet adds information that is not there, you never want that.
  - an1sotropy 5y ago
    Every data visualization is necessarily a contrivance because it is creating visual features for things that weren't already visual. Data visualization research has not been able to formalize a rigorous notion of visual "information" in a form that usefully predicts performance across the enormous variety of visualization tasks and settings for which colormaps might be applied. "Distortion" is also a common but somewhat meaningless term. You're referring to perceptual effects (related to color appearance) that are side-effects of using "jet", but again, for some tasks they may be an acceptable side-effect, given the benefits of increased discriminability. Our different levels of certainty and conviction may arise from my being a data vis academic, rather than a tool user or tool builder.