I have a list of RGB triplets, and I'd like to plot them in such a way that they form something like a spectrum.
I've converted them to HSV, which people seem to recommend.
from PIL import Image, ImageDraw
import colorsys
def make_rainbow_rgb(colors, width, height):
"""colors is an array of RGB tuples, with values between 0 and 255"""
img = Image.new("RGBA", (width, height))
canvas = ImageDraw.Draw(img)
def hsl(x):
to_float = lambda x : x / 255.0
(r, g, b) = map(to_float, x)
h, s, l = colorsys.rgb_to_hsv(r,g,b)
h = h if 0 < h else 1 # 0 -> 1
return h, s, l
rainbow = sorted(colors, key=hsl)
dx = width / float(len(colors))
x = 0
y = height / 2.0
for rgb in rainbow:
canvas.line((x, y, x + dx, y), width=height, fill=rgb)
x += dx
img.show()
However, the result doesn't look very much like a nice rainbow-y spectrum. I suspect I need to either convert to a different color space or handle the HSL triplet differently.
Does anyone know what I need to do to make this data look roughly like a rainbow?
Update:
I was playing around with Hilbert curves and revisited this problem. Sorting the RGB values (same colors in both images) by their position along a Hilbert curve yields an interesting (if still not entirely satisfying) result:
You're trying to convert a three-dimensional space into a one-dimensional space. There's no guarantee that you can make a pleasing rainbow out of it, as Oli says.
What you can do is "bucket" the colors into a few different categories based on saturation and value/lightness, and then sort within the categories, to get several independent gradients. For example, high-saturation colors first for the classic rainbow, then mid-saturation high-value colors (pastels), then low-saturation (grays).
Alternately, if all you care about is the rainbow, convert to hsl, then slam saturation to 1.0 and value to 0.5, convert back to rgb and render that instead of the original color.