nhdaly / colorschemesinvert.jl

[Deprecated] demo package for `invert(cscheme, c)`

ColorSchemesInvert

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This repo is deprecated and should not be used. It only ever existed as an example for a PR to JuliaGraphics/ColorSchemes.jl.

It has been fully merged into ColorSchemes.jl in JuliaGraphics/ColorSchemes.jl#11. You can read about how to use this feature, here:
https://juliagraphics.github.io/ColorSchemes.jl/v3/finding

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ColorSchemesInvert.jl provides a function, invert(cscheme, c), which is the inverse of get(cscheme, x) provided by JuliaGraphics/ColorSchemes.jl.

invert places a color within a colorscheme, by converting the color to a value representing its position on the colorscheme's axis.

using ColorSchemesInvert, ColorSchemes, Colors

ColorSchemes.darkrainbow

Examples

invert(ColorSchemes.darkrainbow, RGB(1,0,0))  # Red

0.9

invert(ColorSchemes.darkrainbow, RGB(0,1,0))  # Green

0.5484818351995914

invert(ColorSchemes.darkrainbow, RGB(0,0,1))  # Blue

0.04946640675057849

invert(ColorSchemes.darkrainbow, ColorSchemes.darkrainbow[2])  # darker blue

0.1

Motivating Example

One use-case for invert is to convert a heat-map image into an Array of continuous values, e.g. temperature.

In this example, we will convert a heat-map style image representing elevation in the United States into an Array of elevations.

using Images, FileIO
img = download("https://www.nasa.gov/images/content/719282main_2008_2012_printdata.1462.jpg") |> load
img = imresize(img, Tuple(Int(x) for x in size(img).*0.2));
display(img)

  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                 Dload  Upload   Total   Spent    Left  Speed
100 3011k  100 3011k    0     0  20.1M      0 --:--:-- --:--:-- --:--:-- 12.0M

ColorSchemes.temperaturemap

temps = [invert(ColorSchemes.temperaturemap, pixel) for pixel in img]

432×768 Array{Float64,2}:
 0.975615  0.975615  0.975615  0.975615  …  0.975615  0.975615  0.975615
 0.975484  0.975767  0.975615  0.975615     0.975615  0.975615  0.975767
 0.975615  0.975615  0.975615  0.975615     0.975615  0.975615  0.975615
 0.975615  0.975615  0.975615  0.975615     0.975615  0.975615  0.975615
 0.975615  0.975615  0.975615  0.975615     0.975615  0.975615  0.975615
 0.975615  0.975615  0.975615  0.975615  …  0.975615  0.975615  0.975615
 0.975615  0.975615  0.975615  0.975615     0.975615  0.975615  0.975615
 0.975615  0.975615  0.975615  0.975615     0.975615  0.975615  0.975615
 0.975615  0.975615  0.975615  0.975615     0.975615  0.975615  0.975615
 0.975615  0.975615  0.975615  0.975615     0.975615  0.975615  0.975615
 0.975615  0.975615  0.975615  0.975615  …  0.975615  0.975615  0.975615
 0.975615  0.975615  0.975615  0.975615     0.975899  0.975899  0.975615
 0.975615  0.975615  0.975615  0.975615     0.975739  0.975739  0.975899
 ⋮                                       ⋱  ⋮                           
 0.84482   0.844684  0.84482   0.821402  …  0.845689  0.846855  0.84482 
 0.823358  0.823887  0.823887  0.823536     0.822783  0.823358  0.823358
 0.822956  0.822359  0.821921  0.82257      0.823536  0.823536  0.823996
 0.821989  0.822677  0.821949  0.821949     0.823141  0.824371  0.822677
 0.820419  0.820084  0.819388  0.819388     0.819977  0.821949  0.81973 
 0.816596  0.816055  0.816055  0.816055  …  0.819388  0.819388  0.818957
 0.813865  0.813247  0.813247  0.813247     0.816055  0.815452  0.813865
 0.810015  0.809307  0.809307  0.809307     0.813247  0.812582  0.812582
 0.808566  0.805171  0.805171  0.805171     0.810015  0.810015  0.809307
 0.804418  0.801045  0.80182   0.801045     0.805171  0.805171  0.805171
 0.801045  0.802513  0.802513  0.800252  …  0.804418  0.804308  0.801045
 0.802037  0.798624  0.798624  0.798624     0.802401  0.800252  0.802848

Now we have converted the data from its original colorscheme to a continuous value, which makes it possible to process as data.

For example, we could find the coldest and warmest places on earth:

mintemp,maxtemp = ind2sub(temps, indmin(temps)), ind2sub(temps, indmax(temps))

((397, 127), (17, 314))

Finally, we can display the new, continous values as a grayscale, representing 0 to 1 as black to white:

Gray.(temps)

convertToScheme

The presence of invert makes it easy to convert an image from one colorscheme to another. This package also defines convertToScheme(cscheme, img) to do exactly that.

convertToScheme will return a new image, where each pixel from the provided image is mapped to its closest matching color in the provided scheme.

convertToScheme(vcat(ColorSchemes.coffee, RGB(0,0,0)), img)

NOTE: I think the "flattening" out of the colors into a few pallete colors is a bug, but I'm not entirely sure. More investigation to do there, I think... :)