fix up stff, docs broken

Author: behinger

Project.toml

@@ -9,7 +9,7 @@ Distances = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 Interpolations = "a98d9a8b-a2ab-59e6-89dd-64a1c18fca59"
 KernelAbstractions = "63c18a36-062a-441e-b654-da1e3ab1ce7c"
-MakieCore = "20f20a25-4f0e-4fdf-b5d1-57303727442b"
+Makie = "ee78f7c6-11fb-53f2-987a-cfe4a2b5a57a"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 
 [compat]
@@ -18,6 +18,6 @@ Distances = "0.10.12"
 Distributions = "0.25.117"
 Interpolations = "0.15.1"
 KernelAbstractions = "0.9.33"
-MakieCore = "0.9.0"
+Makie = "0.22.1"
 Random = "1.11.0"
 julia = "1.10"

docs/Project.toml

@@ -1,8 +1,12 @@
 [deps]
 CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
 CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0"
+ColorSchemeTools = "d3e213a1-5e82-5c18-bb32-2a58a99f8c46"
+Colors = "5ae59095-9a9b-59fe-a467-6f913c188581"
 DiscreteVoronoi = "01fd5c3e-b3b7-45fb-9d19-e82518019796"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+ImageTransformations = "02fcd773-0e25-5acc-982a-7f6622650795"
+Images = "916415d5-f1e6-5110-898d-aaa5f9f070e0"
 LiveServer = "16fef848-5104-11e9-1b77-fb7a48bbb589"
 MakieStippling = "a2bd6b23-9ae5-5b43-94df-c047a0516ae5"
 MeshGrid = "ebf956a0-ef5e-43be-9fb1-27952996e635"

docs/src/01-stippling.md

@@ -5,28 +5,21 @@ using CUDA
 using Random
 
 using CairoMakie
-using MeshGrid
+using WGLMakie
+#using MeshGrid
 ```
 
-create random data
+create an arbitrary density function
 
 ```julia
-n_sites = 5000
-n_conditions = 2
-sites_grouping = rand(1:n_conditions,n_sites)
-
-
-grid = Int.(zeros(500,500))
-grid_combined = CuArray(grid)
-sites = CartesianIndices(size(grid))[rand(1:length(grid),n_sites)]
-nothing #hide
+include("../simulate_densities.jl")
+grid_densities = simulate_densities(timepoints = 10,grid_sz = (500,500),n_conditions=2)
 ```
 
-create an arbitrary density function
-
 ```julia
-include("../simulate_densities.jl")
-grid_densities = simulate_densities(timepoints = 5,grid_sz = size(grid_combined),n_conditions=2)
+trig = Observable(0)
+ stipplemap(grid_densities,axis=(;aspect=1,limits=((0,500),(0,500)));one_more_iteration=trig)
+# [trig[] = k for k in 1:10] # funny way to run 10 iterations
 ```
 
 ```julia

docs/src/03_stippling_interactive.md

@@ -17,24 +17,86 @@ n_conditions = 2
 sites_grouping = rand(1:n_conditions,n_sites)
 
 
-grid = Int.(zeros(500,500))
-grid_combined = CuArray(grid)
-sites = CartesianIndices(size(grid))[rand(1:length(grid),n_sites)]
+
+grid_combined, grid_singles, sites =
+        setup(grid_densities, 100)
+
 ```
 
 ```julia
 include("../simulate_densities.jl")
-n_conditions = 2
-grid_densities = simulate_densities(;timepoints = 10,grid_sz = size(grid_combined),n_conditions)
+n_conditions = 3
+grid_densities = CuArray.(simulate_densities(;timepoints = 10,grid_sz = (500,500),n_conditions))
+colors = [:red,:green,:blue]
+#---
+#using TestImages
+grid_densities = [CuArray(Float32.(1 .-rotr90(testimage("cameraman")))),CuArray(Float32.(rotr90(testimage("cameraman"))))]
+colors = [:black,:white]
+
+#---
+_X = testimage("toucan")
+using ImageTransformations
+percentage_scale = 5
+new_size = trunc.(Int, size(_X) .* percentage_scale)
+X = rotr90(imresize(_X, new_size))
+
+# exract a colorscheme
+n = tempname()*".jpg";save(n,X)
+colors = extract(n,5,25,0.1)
+using Colors
+function extract_color(X,color)
+out = Colors.colordiff.(color,RGB.(X))
+
+#out = out ./ maximum(out)
+return Float32.(out)
+end
+colordiffs = extract_color.(Ref(X),colors)
+m = maximum(maximum.(colordiffs))
+X_cd = map(x->1 .-x./m,colordiffs)
+X_cd = map(x-> (alpha.(X)).*x,X_cd)
+grid_densities = CuArray.(X_cd)
+
+
+#grid_densities = [CuArray(Float32.(rotr90(getproperty.(X,:r)))),
+#                  CuArray(Float32.(rotr90(getproperty.(X,:g)))),
+#                  CuArray(Float32.(rotr90(getproperty.(X,:b))))]
+```
 
-#grid_densities = [testimage("cameraman")]
+```julia
+trig = Observable(20)
+stipplemap(grid_densities;
+    colors=colors[end:-1:1],
+    density_factor=0.2,
+    hysteresis=0.95,
+    markersize=5,
+
+    axis=(;aspect=1,limits=((0,size(grid_densities[1],1)),(0,size(grid_densities[1],2)))),
+    one_more_iteration=trig)
 ```
 
 run setup without iterations
 
 ```julia
-grid_singles,sites_sets = MakieStippling.run_iterations!(grid_combined,sites,sites_grouping,grid_densities;
-        n_iter=0)
+
+grid_combined, grid_singles, sites =
+        MakieStippling.setup(grid_densities, 100)
+MakieStippling.jfa_voronoi_gpu!(grid_combined, collect(reduce(union, to_value.(sites))))
+n_groups = length(grid_densities)
+[MakieStippling.jfa_voronoi_gpu!(grid_singles[k], collect(to_value(sites[k]))) for k = 1:n_groups]
+
+
+_sites = Set.(MakieStippling.linearized_sites.(collect.(to_value.(sites)), Ref(size(grid_combined))))
+
+@run MakieStippling.one_iteration!(
+            grid_combined,
+            grid_singles,
+            _sites,
+            to_value(grid_densities);
+            markersize = 5,
+            hysteresis_a = 0.8
+        )
+
+
 ```
 
 setup `Observables.jl` to quickly update the plot

src/MakieStippling.jl

@@ -9,11 +9,13 @@ using KernelAbstractions
 
 using Atomix
 
-using MakieCore
+using Makie
 
 include("jfa_voronoi.jl")
 include("grid_features.jl")
 include("density.jl")
 include("stippling.jl")
+include("stipplemap.jl")
 
+export stipplemap, stipplemap!
 end

src/grid_features.jl

@@ -83,7 +83,7 @@ function grid_features(A::AbstractMatrix{<:Integer}, sites_set)
     )
     KernelAbstractions.synchronize(device)
 
-    return Vector(hist_counts), #./ *(size(A)...), # uncomment to normalize
+    return (hist_counts), #./ *(size(A)...), # uncomment to normalize
     vec2tuple.(Vector(centroids_x), Vector(centroids_y))
 end
 vec2tuple(x, y) = (x, y)

src/stipplemap.jl

@@ -1,10 +1,95 @@
 @recipe(StippleMap, densities) do scene
-    Attributes(markersize = 10, hysteresis = 0.6)
+    Attributes(
+        markersize = 10.0,
+        hysteresis = 0.6,
+        density_factor = 0.5,
+        n_initial_sites = 1000,
+        n_iter = 10,
+        one_more_iteration = 0,
+        colors = nothing,
+    )
 end
 
-function MakieCore.plot!(sm::StippleMap)
+function setup(grid_densities, initial_sites)
+    n_groups = length(grid_densities)
+    grid_combined = similar(grid_densities[1], Int)
+    grid_singles = [similar(grid_combined) for _ = 1:n_groups]
+
+    sites = [
+        Observable(
+            Set(
+                CartesianIndices(size(grid_combined))[rand(
+                    1:length(grid_combined),
+                    initial_sites,
+                )],
+            ),
+        ) for _ = 1:n_groups
+    ]
+
+    return grid_combined, grid_singles, sites
+end
+
+function Makie.plot!(sm::StippleMap; kwargs...)
+
     grid_densities = sm.densities
+    n_groups = length(to_value(grid_densities))
+
+    grid_combined, grid_singles, sites =
+        setup(to_value(grid_densities), to_value(sm.n_initial_sites))
+
+    # init the grids
+    jfa_voronoi_gpu!(grid_combined, collect(reduce(union, to_value.(sites))))
+    [jfa_voronoi_gpu!(grid_singles[k], collect(to_value(sites[k]))) for k = 1:n_groups]
+
 
-    scatter!.(sm, sites, markerspace = :data, markersize = sm.markersize)
+    on(sm.one_more_iteration; update = true) do trg
+        _sites =
+            Set.(linearized_sites.(collect.(to_value.(sites)), Ref(size(grid_combined))))
+        @show trg
+        for t = 1:trg
+            one_iteration!(
+                grid_combined,
+                grid_singles,
+                _sites,
+                to_value(grid_densities);
+                markersize = to_value(sm.markersize),
+                hysteresis_a = to_value(sm.hysteresis),
+                density_factor = to_value(sm.density_factor),
+            )
+        end
+        for k = 1:n_groups
+            sites[k][] =
+                Set(linearized_sites.(collect(_sites[k]), Ref(size(grid_combined))))
+        end
+        #notify.(sites)
+
+    end
+
+
+
+
+    for k = 1:n_groups
+        order = @lift(.-Matrix($(grid_densities)[k])[collect($(sites[k]))])
+        site_obs = @lift(convert.(Point3, (collect($(sites[k]))), $order))
+        #@debug typeof(site_obs) typeof(to_value(site_obs[1]))
+        c = sm.colors
+        kw = try
+            (; color = @lift($c[k]))
+        catch
+            (;)
+        end
+        scatter!(
+            sm,
+            site_obs;
+            markerspace = :data,
+            markersize = sm.markersize,
+            fxaa = true,
+            kw...,
+        )
+
+    end
     return sm
 end
+
+Base.convert(Point2, x::CartesianIndex) = Point2(x[1], x[2])
+Base.convert(Point3, x::CartesianIndex, y) = Point3(x[1], x[2], y)