183 lines
5.5 KiB
Julia
183 lines
5.5 KiB
Julia
module ColourApproximations
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using Colors
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using GLMakie
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using Makie.GeometryBasics: Rect, HyperRectangle
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using Observables
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# Utilities
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const colours3bit = # xterm colours
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Colorant[colorant"rgb(0, 0, 0)",
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colorant"rgb(205, 0, 0)",
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colorant"rgb(0, 205, 0)",
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colorant"rgb(205, 205, 0)",
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colorant"rgb(0, 0, 238)",
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colorant"rgb(205, 0, 205)",
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colorant"rgb(0, 205, 205)",
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colorant"rgb(229, 229, 229)"]
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const colours4bit = # xterm again
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vcat(colours3bit,
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Colorant[colorant"rgb(127, 127, 127)",
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colorant"rgb(255, 0, 0)",
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colorant"rgb(0, 252, 0)",
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colorant"rgb(255, 255, 0)",
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colorant"rgb(0, 0, 252)",
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colorant"rgb(255, 0, 255)",
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colorant"rgb(0, 255, 255)",
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colorant"rgb(255, 255, 255)"])
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const colour6cube =
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Colorant[RGB(r, g, b)
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for r in range(0, 1, length=6)
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for g in range(0, 1, length=6)
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for b in range(0, 1, length=6)]
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const colour24greys = Colorant[RGB(w, w, w) for w in range(0, 1, length=24)]
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const colours8bit = vcat(colours4bit, colour6cube, colour24greys)
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const coloursets =
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[Symbol("3-bit") => colours3bit,
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Symbol("4-bit") => colours4bit,
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Symbol("8-bit") => colours8bit]
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nearestcolour(metric::Colors.DifferenceMetric, options::Vector{<:Colorant}, colour::Colorant) =
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options[argmin(o -> colordiff(options[o], colour; metric), axes(options, 1))]
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const nearcolourcache =
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Dict{Colors.DifferenceMetric, Dict{Symbol, Dict{Colorant, Colorant}}}()
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function nearestcolour(metric::Colors.DifferenceMetric, options::Symbol)
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if !haskey(nearcolourcache, metric)
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nearcolourcache[metric] = Dict{Symbol, Dict{Colorant, Colorant}}()
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end
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if !haskey(nearcolourcache[metric], options)
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nearcolourcache[metric][options] = Dict{Colorant, Colorant}()
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end
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relevantcache = nearcolourcache[metric][options]
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colourset = coloursets[findfirst(s -> first(s) == options, coloursets)] |> last
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function (c::Colorant)
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cached = get(relevantcache, c, nothing)
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if isnothing(cached)
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cached = relevantcache[c] = nearestcolour(metric, colourset, c)
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end
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cached
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end
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end
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# Extra colour differences
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struct DE_RGB <: Colors.EuclideanDifferenceMetric{RGB} end
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struct DE_HSL <: Colors.EuclideanDifferenceMetric{HSL} end
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colour_distance_metrics =
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["CIEΔE2000" => DE_2000(),
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"CIEΔE94" => DE_94(),
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"BFD" => DE_BFD(),
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"CMC" => DE_CMC(),
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"JPC79" => DE_JPC79(),
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"l2 LAB" => DE_AB(),
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"l2 DIN99" => DE_DIN99(),
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"l2 DIN99d" => DE_DIN99d(),
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"l2 DIN99o" => DE_DIN99o(),
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"l2 RGB" => DE_RGB(),
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"l2 HSL" => DE_HSL()]
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# The control observables
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saturation = Observable(1.0)
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x_granularity = Observable(256)
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y_granularity = Observable(128)
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diffmetric = Observable{Colors.DifferenceMetric}(last(first(colour_distance_metrics)))
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# Plot setup
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fig = Figure()
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controlrow1 = fig[1,1] = GridLayout()
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xgrad_slider = Slider(controlrow1[1,2], range=32:32:1024, startvalue=x_granularity[])
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Label(controlrow1[1,1], text="X divisions")
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ygrad_slider = Slider(controlrow1[1,4], range=16:16:512, startvalue=y_granularity[])
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Label(controlrow1[1,3], text="Y divisions")
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metric_slider = Slider(controlrow1[1,6], range=1:length(colour_distance_metrics))
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Label(controlrow1[1,5], text=@lift(colour_distance_metrics[$(metric_slider.value)] |> first))
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connect!(x_granularity, xgrad_slider.value)
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connect!(y_granularity, ygrad_slider.value)
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# colsize!(controlrow1, 1, Auto(true, 0.0))
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# colsize!(controlrow1, 2, Fixed(120))
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# colsize!(controlrow1, 3, Auto(true, 0.0))
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# colsize!(controlrow1, 4, Fixed(120))
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# colsize!(controlrow1, 5, Auto(true, 0.0))
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# colsize!(controlrow1, 6, Fixed(160))
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ax = Axis(fig[2,1])
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hidedecorations!(ax)
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hidespines!(ax)
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controlrow2 = fig[3,1] = GridLayout()
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saturation_slider = Slider(controlrow2[1,2], range = 0:0.01:1, startvalue=saturation[])
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Label(controlrow2[1,1], text="Saturation")
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colourset_slider = Slider(controlrow2[1,4], range=1:length(coloursets))
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Label(controlrow2[1,3], text=@lift(coloursets[$(colourset_slider.value)] |> first |> string))
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round_colours = Toggle(controlrow2[1,6])
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Label(controlrow2[1,5], text="Round")
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colsize!(controlrow2, 1, Auto(true, 0.0))
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colsize!(controlrow2, 2, Auto(false, 0.8))
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colsize!(controlrow2, 3, Auto(true, 0.0))
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colsize!(controlrow2, 4, Fixed(100))
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colsize!(controlrow2, 5, Auto(true, 0.0))
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colsize!(controlrow2, 6, Fixed(60))
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# Plotting
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connect!(saturation, saturation_slider.value)
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map!(diffmetric, metric_slider.value) do v
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colour_distance_metrics[v] |> last
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end
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roundfun = Observable{Function}(identity)
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map!(roundfun, diffmetric, colourset_slider.value) do metric, cset
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nearestcolour(metric, coloursets[cset] |> first)
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end
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rect_list = Observable(Vector{HyperRectangle}())
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rect_list = map(x_granularity, y_granularity) do x, y
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[Rect(i, j, 1, 1) for i in 1:x for j in 1:y]
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end
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colour_list_unprocessed = map(saturation) do s
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[HSL(h, s, l)
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for h in range(0, 360, length=x_granularity[])
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for l in range(0, 1, length=y_granularity[])]
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end
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colour_list = Observable(Vector{Colorant}())
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map!(colour_list, colour_list_unprocessed, roundfun, round_colours.active) do clist, cround, croundp
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if croundp cround.(clist) else clist end
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end
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# The main event
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p = poly!(ax, rect_list, color = colour_list)
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on(rect_list, priority=1) do
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delete!(ax, p)
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p = poly!(ax, rect_list, color = colour_list)
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end
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fig
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end
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