Some of the images in this writeup are part of Ana Swanson's Wonk Blot post How a dog sees a rainbow, and 12 other images that explain how we see color at the Washington Post.
In an audience of 8 men and 8 women, chances are 50% that at least one has some degree of color blindness1,2. When encoding information or designing content, use colors that is color-blind safe.
1About 8% of males and 0.5% of females are affected with some kind of color blindness in populations of European descent (wikipedia, Worldwide prevalence of red-green color deficiency, JOSAA). The rate for other races is lower Asians and Africans is lower (Caucasian Boys Show Highest Prevalence of Color Blindness Among Preschoolers, AAO).
2The probability that among `N=8` men and `N=8` women at least one person is affected by color blindness is `P(men,women) = P(8,8) = 1 - (1-0.08)^8 * (1-0.005)^8 = 0.51`. For `N=34` (i.e., 68 people in total), this probability is `P(34,34)=0.95`. Because the rate of color blindness in women is so low, for most groups of mixed gender we can approximate the probability by only counting the men. For example, in a group of 17 women the probability that at least one of them is color blind is `P(0,17) = 0.082`, which is the same probability as for 1 man, `P(1,0)`.
Color Oracle is a good and free color blindness simulator for Windows, Mac and Linux.
You can download the RGB transformation table for deuteranopia, protanopia and tritanopia. It is available for all (r,g,b) colors in steps of 5 in each of the channels. The mapping for all other RGB colors can be interpolated.
The normal human eye is a 3-channel color detector3. There are three types of photoreceptors, each sensitive to a different part of the spectrum. Their combined response to a given wavelength produces a unique response that is the basis of the perception of color.
3Compared to hearing, the color vision is a primitive detector. While we can hear thousands of distinct frequencies and process them simultaneously, we have only three independent color inputs. While the ear can distinguish pure tones from complex sounds that have multiple frequencies the eye is relatively unsophisticated in separating a color sensation into its three constituent primary stimuli.
People with color blindness have one of the photo receptor groups either reduced in number or entirely missing. With only two groups of photoreceptors, the perception of hue is drastically altered.
For example, in deuteranopia, the most common type of color blindness, the medium (M) wavelength photoreceptors are reduced in number or missing. This results in the loss of perceived difference between reds and greens because only one group of photoreceptors (L) are sensitive to the wavelengths of these colors. The spectrum appears to be split into two hues along the blue-green boundary (see figure below).
Visible light is in the range of 390-700 nm. The exact definition of the upper limit varies, with some sources giving as high as 760 nm. Shorter wavelengths are absorbed by the cornea (<295nm) and lens (315-390nm). Some near infrared light also reaches the retina (760-1400nm).
The opposite condition to color blindness exists too—tetrachromacy. In this case, an individual has an extra type of color receptor which improves discrimination in the red part of the spectrum. While the anatomy of their retina can be described, how true tetrachromats subjectively perceive color is unknown. And, perhaps, even unknowable.
Tetrachromacy is common in other animals, such as fish (e.g. goldfish, zebrafish) and birds (e.g. finch, starling). The dimensionality of the perceived color space isn't necessarily proportional to the number of different receptors. If the signal from 3 color receptors are combined by the brain and each processor has a weighted response to a broad range of wavelengths, then a color can be modeled by a point in 3-dimensional space, in which the receptors are the axes. This system can perceive a large number of colors.
In the extreme case where the receptors respond to a very narrow range, of which none overlap with the other, a color is one of three points in a 1-dimensional space. This sytem can perceive only 3 colors.
If you use Color Oracle to transform your screen colors to simulate color blindness, you can see that none of the equivalent swatches in one kind of color blindness are equivalent in another. This is particularly interesting when applied to a duotone image which is drawn using equivalent colors. In the figure below4, a row of Mr. Spocks disappears (or is difficult to see) to people with color blindness.
4In tribute to Leonard Nimoy, 1931–2015
To people with color blindness, some colors appear the same. This equivalence can be used to identify distinct colors which are unique to those with normal and color blind vision.
The seven colors (and black) in the figure below are perceived as reasonably distinct by both normal and color blind individuals. The table on the left is reproduced from Nature Method's Points of View: Color blindness by Bang Wong.
For more tips about designing with color blindness in mind, see Color Universal Design (CUD) — How to make figures and presentations that are friendly to Colorblind people.
The figure below shows the mapping of different colors to six different grades of each of the two hues seen by deuteranopes. It offers more distinct options than the 7-color palette above.
Even more color choices for color blindess, including colors that map onto greys.
If you're looking to encode quantitative information, I suggest using the subset of Brewer palettes that are safe for color blindess (e.g. pink-yellow-green, brown-blue-green).
Another collection of typographical posters. These ones really ask you to look.
The charts show a variety of interesting symbols and operators found in science and math. The design is in the style of a Snellen chart and typset with the Rockwell font.
In collaboration with the Phil Poronnik and Kim Bell-Anderson at the University of Sydney, I'm delighted to share with you our 8-part video series project about thinking about drawing data and communicating science.
We've created 8 videos, each focusing on a different essential idea in data visualization: encoding, shapes, color, uncertainty, design, drawing missing or unobserved data, labels and process.
The videos were designed as teaching materials. Each video comes with a slide deck and exercises.
This month is our first of a two-part article about P values. Here we look at 'P value hacking' and 'data dredging', which are questionable practices that invalidate the correct interpretation of P values.
We also illustrate how P values can lead us astray by asking "What is the smallest P value we can expect if the null hypothesis is true but we have done many tests, either explicitly or implicitly?"
Incidentally, this is our first column in which the standfirst is a haiku.
Altman, N. & Krzywinski, M. (2017) Points of Significance: P values and the search for significance. Nature Methods 14:3–4.
Krzywinski, M. & Altman, N. (2013) Points of significance: Significance, P values and t–tests. Nature Methods 10:1041–1042.
Appeal to intuition when designing with value judgments in mind.
Figure clarity and concision are improved when the selection of shapes and colors is grounded in the Gestalt principles, which describe how we visually perceive and organize information.
The Gestalt principles are value free. For example, they tell us how we group objects but do not speak to any meaning that we might intuitively infer from visual characteristics.
This month, we discuss how appealing to such intuitions—related to shapes, colors and spatial orientation— can help us add information to a figure as well as anticipate and encourage useful interpretations.
Krzywinski, M. (2016) Points of View: Intuitive Design. Nature Methods 13:895.