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ColourApproximationComparison/pairsurrounding.jl

126 lines
4.5 KiB
Julia

using Colors
using StatsBase
using FixedPointNumbers: N0f8, Normed
using Memoize
StatsBase.pairwise(metric::Colors.DifferenceMetric, colours::Vector{<:Colorant}) =
pairwise((x, y) -> colordiff(x, y; metric), colours)
function colourdistances(metric::Colors.DifferenceMetric, colours::Vector{<:Colorant})
distmat = pairwise(metric, colours)
Dict(c => sort([distmat[i, j] => colours[j]
for j in setdiff(axes(distmat, 1), i)],
by=first)
for (i, c) in enumerate(colours))
end
function deconstruct(colour::C) where {C <: Colorant}
fnames = fieldnames(C)
getfield.(colour, fnames)
end
deconstruct(colour::RGB{N0f8}) =
Float64.(getfield.(colour, (:r, :g, :b)))
function construct(C::Type{<:Colorant}, fields::Tuple)
eval(Expr(:new, C, fields...))
end
construct(::Type{RGB{N0f8}}, fields::NTuple{3, Float64}) =
RGB{N0f8}(fields...)
@memoize nearestcolour(metric::Colors.DifferenceMetric, options::Vector{<:Colorant}, colour::Colorant) =
options[argmin(o -> colordiff(options[o], colour; metric), axes(options, 1))]
"""
Examine various mixings of colours `a` and `b` in an attempt to confirm whether
there are no other colours from `options` that lie directly between `a` and `b`
according to `metric`.
This is done by bisecting the mix factor and checking if any other colours are
reported as nearest within `tol` of the crossover point.
"""
function bisectadjacency(metric::Colors.DifferenceMetric, a::C, b::C, options::Vector{<:Colorant}; tol=1e-6) where {C <: Colorant}
af, bf, = deconstruct.((a, b))
lastmixfactor, mixfactor, mixstep = 1.0, 0.5, 0.25
while abs(lastmixfactor - mixfactor) > tol
abf = @. mixfactor * af + (1 - mixfactor) * bf
ab = construct(C, abf)
near_ab = nearestcolour(metric, options, ab)
if near_ab == a
lastmixfactor, mixfactor = mixfactor, mixfactor + mixstep
elseif near_ab == b
lastmixfactor, mixfactor = mixfactor, mixfactor - mixstep
else
return false
end
mixstep /= 2
end
return true
end
function adjacentcolours(metric::Colors.DifferenceMetric, colours::Vector{C}) where {C <: Colorant}
distlist = colourdistances(metric, colours) |> collect
adjacencylist = Dict{C, Vector{Pair{Float64, C}}}()
for (c, others) in distlist
adjacencylist[c] =
filter(oth -> let o = last(oth)
if haskey(adjacencylist, o)
c last.(adjacencylist[o])
else
bisectadjacency(metric, c, o, colours)
end
end, others)
end
adjacencylist
end
@memoize function growcolours(metric::Colors.DifferenceMetric, colours::Vector{<:Colorant},
refmat::Matrix{<:Colorant})
cmat = Matrix{Union{Colorant, Missing}}(fill(missing, size(refmat)))
cadj = adjacentcolours(metric, colours)
for i in CartesianIndices(cmat)
if ismissing(cmat[i])
# @info "@ $(i.I)"
cnearest = nearestcolour(metric, colours, refmat[i])
cmat[i] = cnearest
if length(cadj[cnearest]) > 0
safethreshold = minimum(first.(cadj[cnearest]))/2
growcolour!(cmat, metric, refmat, cnearest, safethreshold, i)
end
end
end
Matrix{Colorant}(cmat)
end
function growcolour!(cmat::Matrix{Union{Colorant, Missing}}, metric::Colors.DifferenceMetric,
refmat::Matrix{<:Colorant}, cnearest::Colorant, safethreshold::Float64,
initalpos::CartesianIndex{2})
seeds = [initalpos]
while !isempty(seeds)
pos = pop!(seeds)
surrounding = Ref(pos) .+ CartesianIndex{2}.([(0, 1), (0, -1), (1, 0), (-1, 0)])
filter!(s -> all((1,1) .<= s.I .<= size(refmat)), surrounding)
for spos in surrounding
if ismissing(cmat[spos]) &&
colordiff(cnearest, refmat[spos]; metric) < safethreshold
cmat[spos] = cnearest
push!(seeds, spos)
end
end
end
end
function colour_grid_hsl(xs, ys, saturation=1)
[HSL(h, saturation, l)
for h in range(0, 360, length=xs),
l in range(0, 1, length=ys)]
end
# function growcolours!(cmat::Matrix, metric::Colors.DifferenceMetric,
# adjc::Dict{Colorant, Vector{Pair{Float64, Colorant}}}, refmat::Matrix,
# pos::CartesianIndex{2},
# lrwrap::Bool=false, udwrap::Bool=false)
# end