Whats the deal with oklch? My naive reaction was a that it sucks to define colors in a way you can’t easily reason about or need and external tool to make.
I encourage you to think about two random colors and imagining a gradient between them and then drawing said gradient in RGB and HSL color spaces. In both cases it will be wildly different from what you'd expect or could create with two blobs of oil paint on canvas.
Long answer - unfortunatelly it's quite hard to convey why we need a better color space in twitter-space but this video (while 40m long it's quite condensed) is an excellent explainer: https://www.youtube.com/watch?v=gnUYoQ1pwes
OKLCH is really easy to work with. Once you have your palette it's easy to get correct shades and hues by tweaking some values. This works great with CSS custom properties.
This page has more information: https://evilmartians.com/chronicles/oklch-in-css-why-quit-rg...
Our eyes are much more sensitive to Blue/Violet, and less sensitive to green. There's a bunch of maths behind the perceived responses of our eyes.
If you're interested you can calculate perceived differences in the LCh colorspace using something like CIEDE2000.(https://en.wikipedia.org/wiki/Color_difference#CIEDE2000)
A Rainbow with equal DE between colors would probably look better than this one with equal DL.
The main purpose of ΔE is specifying error tolerances for specified colors / measuring small differences between nearby colors, so that e.g. if you hire someone to paint a car or print a magazine you can check that their output matches expectation sufficiently. For colors that are significantly different ΔE isn't that helpful a practical tool.
Hm? It's the exact opposite. That's why the full-intensity RGB green looks much brighter than the full-intensity blue. To convert RGB to pure luminance (gray), you do something like 0.3 * R + 0.6 * G + 0.1 * B, meaning green contributes six times as much as blue.
There is an additive color mixing model, which is basically your standard RGB model, where you basically control how bright each of the red, green, and blue lamps shining at a point. There is a complementary subtractive color mixing model, which is controlling the amount of pigments you drop onto a substrate (CMYK is what you'll see used in computers these days). Then there's a third model, where you measure it according to brightness, colorfulness, and then the actual hue it is--there's a lot more variants in this model, basically any colorspace you don't recognize is this kind of model.
If you visualize colors existing in an RGB cube, you have 8 colors at the vertices: black and white are at opposite ends of a diagonal, and the other 6 are two sets of nonadjacent vertices: red, green, and blue in one set, and cyan, magenta, and yellow in the other set. Given such a cube, you should be able to easily see that RGB is using one of those sets as its basis set, whereas CMYK is using the other set as its basis set. The third set of models is built by tilting the cube such that the black-white diagonal is now the vertical line (one of the components), and then distance from this line becomes another component, and then the angle around the line is the final component--it's a cylindrical coordinate space in 3D space, not a Cartesian space.
Some models, like CIELAB or Oklab, use the third model but retain a Cartesian coordinate system, the last two values being called something generic like 'a' and 'b'. Oklch is the same as Oklab, but expressed as cylindrical coordinates, because chroma (colorfulness aka distance from the pure light line) and hue (aka the dominant color of the light) is more convenient for people to work with than a Cartesian system.
If you interpolate between RGB colors you will get very weird grayish shades inbetween and the new color may be preceptually darker or brighter, which may be a problem (e.g. if it is text on a background). With OKLCH you define one color and as you rotate around the color wheel it stays the same preceptual brightness, which is incredibly cool.
This means before a designer would have to touch 3 values (RGB or HSV) to match the colors preceptually using their eyeballs, now there is only one value and it matched nearly perfectly as it is.
Lightness dictates how white or black a color is, chroma dictates how saturated it is, and hue is which angle on the color wheel it occupies. Varying these one at a time lets you intuitively pick colors that are close to one another in the space of human perception. And CIE Lab colors are especially nice because they cover more than the sRGB gamut that we're all used to defining with HSL or RGB, so you can really make the most of your fancy wide color gamut monitor.
My programmer brain immediately jumped away in disgust.
I'm sure there's many good reasons for choosing those, but it seems to me it could have easily have been done with 3 percentages (0-100% for the 3 numbers). Way easier to work with programmatically.
Chroma cap is dependent on Lightness and Hue, so it has to be unsized to preserve "equal delta leads to equal color distinction" concept
In color spaces you just don't have any math that can be done without following its structure
You may check https://oklch.com/ on how the color space looks like
There's nothing magical about the number 360. You can do cycles in the 0-1 range. You can even make trigonometry with that (no radians). See:
Other than that, I agree that “chroma” is hard to reason about. But, at least it is easier to reason than the “a”/“b” parameters in “lab”.
But the RGB defaults can't be easily reasoned about either, so this is still an improvement, so it's not worse
The loss is no longer having any intuition about what a color is just by seeing the numbers.