color update

slides.qmd

@@ -63,9 +63,9 @@ See also @higino2021 for more quality 🦝 content
 include(joinpath("code", "pkg.jl")); # Dependencies
 include(joinpath("code", "nbc.jl")); # Naive Bayes Classifier
 include(joinpath("code", "bioclim.jl")); # BioClim model
+include(joinpath("code", "confusion.jl")); # Confusion matrix utilities
 include(joinpath("code", "splitters.jl")); # Cross-validation
 include(joinpath("code", "crossvalidate.jl")); # Cross-validation
-include(joinpath("code", "confusion.jl")); # Confusion matrix utilities
 include(joinpath("code", "variableselection.jl")); # Variable selection
 include(joinpath("code", "shapley.jl")); # Shapley values
 include(joinpath("code", "palettes.jl")); # Color palettes
@@ -636,7 +636,7 @@ end
 
 fig = Figure(; resolution=(900, 500))
 ax = Axis(fig[1,1]; xlabel="Longitude", ylabel="Latitude", aspect=DataAspect())
-hm = heatmap!(ax, entropy.(prediction), colormap=Reverse(:linear_gow_65_90_c35_n256), colorrange=(0., 1.))
+hm = heatmap!(ax, entropy.(prediction), colormap=cgrad(iridescent), colorrange=(0., 1.))
 heatmap!(ax, presence_layer; colormap=[:black,:black])
 Colorbar(fig[1,2], hm; tellheight=false)
 current_figure()
@@ -677,7 +677,7 @@ shapval = [similar(first(predictors)) for i in eachindex(available_variables)]
 Threads.@threads for k in keys(shapval[1])
     x = [p[k] for p in predictors[available_variables]]
     for i in axes(shapval, 1)
-        shapval[i][k] = shapleyvalues(finalmodel, tX, x, i; M=50)
+        shapval[i][k] = shapleyvalues(finalmodel, tX[:,available_variables], x, i; M=50)
         if isnan(shapval[i][k])
             shapval[i][k] = 0.0
         end
@@ -715,19 +715,19 @@ fpos = 1
 for i in sortperm(varimp; rev=true)[1:3]
     ax_mp = Axis(gl[fpos,1]) # Absolute contribution
     scl = maximum(abs.(extrema(shapval[i]))).*(-1,1)
-    heatmap!(ax_mp, shapval[i], colorrange=scl, colormap=Reverse(:diverging_bwr_20_95_c54_n256), aspect=DataAspect())
-    hidexdecorations!(ax_mp)
+    heatmap!(ax_mp, shapval[i], colorrange=scl, colormap=cgrad(sunset), aspect=DataAspect())
+    hidexdecorations!(ax_mp)nightfall
     hideydecorations!(ax_mp)
 
     ax_pp = Axis(gl[fpos,2]) # Relative contribution
     relcon = abs(shapval[i])/totalvar
-    heatmap!(ax_pp, relcon, colorrange=extrema(relcon), colormap=Reverse(:linear_gow_65_90_c35_n256), aspect=DataAspect())
+    heatmap!(ax_pp, relcon, colorrange=extrema(relcon), colormap=cgrad(iridescent), aspect=DataAspect())
     hidexdecorations!(ax_pp)
     hideydecorations!(ax_pp)
 
     ax_pr = Axis(gl[fpos,3], title=variables[available_variables[i]][2]) # Partial response
     ylims!(ax_pr, scl)
-    hexbin!(ax_pr, predictors[available_variables[i]], shapval[i], bins=200, colormap=:linear_bgy_10_95_c74_n256)
+    hexbin!(ax_pr, predictors[available_variables[i]], shapval[i], bins=200, colormap=cgrad(incandescent))
     fpos += 1
 end