Make work with SpeciesDistributionToolkit v1

.github/workflows/CompatHelper.yml

@@ -9,7 +9,7 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        julia-version: [1.8.0]
+        julia-version: ["lts"]
         julia-arch: [x86]
         os: [ubuntu-latest]
     steps:

.github/workflows/RunTests.yml

@@ -7,13 +7,13 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        julia-version: ["1.8"]
+        julia-version: ["1", "1.9", "lts"]
         julia-arch: [x64]
         os: [ubuntu-latest]
 
     steps:
       - uses: actions/checkout@v2
-      - uses: julia-actions/setup-julia@v1
+      - uses: julia-actions/setup-julia@v2
         with:
           version: ${{ matrix.julia-version }}
           arch: ${{ matrix.julia-arch }}

Project.toml

@@ -1,17 +1,15 @@
 name = "SpatialBoundaries"
 uuid = "8d2ba62a-3d23-4a2b-b692-6b63e9267be2"
 authors = ["Tanya Strydom <tanya.strydom@umontreal.ca>", "Timothée Poisot <timothee.poisot@umontreal.ca>"]
-version = "0.1.0"
+version = "0.2.0"
 
 [deps]
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
-SpeciesDistributionToolkit = "72b53823-5c0b-4575-ad0e-8e97227ad13b"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 VoronoiDelaunay = "72f80fcb-8c52-57d9-aff0-40c1a3526986"
 
 [compat]
-SpeciesDistributionToolkit = "0.0.1, 0.0.2, 0.0.3"
-StatsBase = "0.33"
+StatsBase = "0.34"
 VoronoiDelaunay = "0.4"
-julia = "1.8"
+julia = "1.9"

docs/Project.toml

@@ -1,11 +1,6 @@
 [deps]
+CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 Literate = "98b081ad-f1c9-55d3-8b20-4c87d4299306"
 NeutralLandscapes = "71847384-8354-4223-ac08-659a5128069f"
-Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
-CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0"
-SpeciesDistributionToolkit = "72b53823-5c0b-4575-ad0e-8e97227ad13b"
-StatsPlots = "f3b207a7-027a-5e70-b257-86293d7955fd"
-
-[compat]
-SpeciesDistributionToolkit = "0.0"
+StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"

docs/make.jl

@@ -15,6 +15,7 @@ makedocs(;
     sitename = "SpatialBoundaries",
     format = Documenter.HTML(),
     modules = [SpatialBoundaries],
+    warnonly = true,
     pages = [
         "Home" => [
             "Introduction" => "vignettes/introduction.md",
@@ -23,18 +24,12 @@ makedocs(;
         "Vignettes" => [
             "Finding boundaries" => "vignettes/boundaries.md",
             "Triangulation wombling" => "vignettes/triangulation.md",
-            "SDM Layers" => "vignettes/simplesdmlayers.md",
         ],
     ],
 )
 
-@info "Prepare to remove"
-run(`find . -type f -name ".tif" -delete`)
-run(`find . -type f -name ".tif"`)
-
 @info "Prepare to deploy"
 deploydocs(;
-    deps = Deps.pip("pygments", "python-markdown-math"),
     repo = "github.com/PoisotLab/SpatialBoundaries.jl.git",
     push_preview = true,
     devbranch = "main",

docs/src/vignettes/boundaries.jl

@@ -6,8 +6,7 @@
 # three-patch landscape.
 
 using SpatialBoundaries
-using StatsPlots
-default(; dpi=500, size=(600, 600), aspectratio=1, c=:batlow, frame=:box)
+using CairoMakie
 
 # Let's create a landscape with two values:
 
@@ -26,7 +25,7 @@ W = wombling(A);
 
 # Let's look at the rate of change:
 
-heatmap(W.m; c=:nuuk)
+heatmap(W.m; colormap = :Greys)
 
 # Picking the boundaries is done by passing the wombling output to the
 # `boundaries` function, with a specific threshold giving the proportion of
@@ -36,9 +35,11 @@ heatmap(W.m; c=:nuuk)
 thresholds = LinRange(0.0, 0.2, 200)
 patches = [length(boundaries(W, t)) for t in thresholds]
 
-plot(thresholds, log1p.(patches), aspectratio=:none)
-xaxis!("Threshold", (0., 0.2))
-yaxis!("log(boundary patches + 1)", (0., 9.))
+f, ax, plt = lines(thresholds, log1p.(patches), color=:black, linewidth=2)
+tightlimits!(ax)
+ax.xlabel = "Threshold"
+ax.ylabel = "log(boundary patches + 1)"
+f
 
 # Let's eyeball this as 0.01, and see how the patches are distributed.
 
@@ -49,11 +50,11 @@ yaxis!("log(boundary patches + 1)", (0., 9.))
 
 b = similar(W.m)
 
-for t in reverse(LinRange(0.0, 1.0, 200))
+for t in reverse(LinRange(0.0, 1.0, 300))
     b[boundaries(W, t)] .= t
 end
 
-heatmap(b, c=:tofino, clim=(0,1))
+heatmap(b, colormap=:tofino, colorrange=(0,1))
 
 # This also suggests that we will get well delineated patches for low values of
 # the threshold.
@@ -63,7 +64,8 @@ B = boundaries(W, 0.01);
 # In the following figure, cells identified as candidate boundaries are marked
 # in white:
 
-heatmap(A)
-scatter!([(reverse(x.I)) for x in B], leg=false, msw=0, c=:white)
+f, ax, hm = heatmap(A)
+scatter!(ax, [b.I for b in B], color=:white)
+f
 
 # We can see that the boundaries of the patches have been well identified!

docs/src/vignettes/introduction.jl

@@ -42,11 +42,7 @@
 
 using SpatialBoundaries
 using NeutralLandscapes
-using StatsPlots
-
-# We will set a few options for the default plots:
-
-default(; dpi=500, size=(600, 600), aspectratio=1, c=:davos, frame=:box)
+using CairoMakie
 
 # The landscape generation is done using the `NeutralLandscapes` package, and we
 # will pick a 500x500 grid:
@@ -76,7 +72,7 @@ W = wombling(landscape);
 
 # Let's have a look at the rate of change:
 
-heatmap(W.m, c=:tokyo, clim=(0, maximum(W.m)))
+heatmap(W.m, colormap=:navia, colorrange=(0, maximum(W.m)))
 
 # The rate of change informs us on the potential for there to be a boundary
 # (zone of change) within a window. Cells with a high rate of change are
@@ -87,7 +83,7 @@ heatmap(W.m, c=:tokyo, clim=(0, maximum(W.m)))
 # for instance, an angle of 180° means that the value is smaller in the South,
 # and larger in the North:
 
-heatmap(W.θ, c=:romaO, clim=(0., 360.))
+heatmap(W.θ, colormap=:romaO, colorrange=(0., 360.))
 
 # The direction of change is *not* the direction the boundary would be if you
 # were to draw it on the landscape but rather the direction the rate of change

docs/src/vignettes/triangulation.jl

@@ -1,41 +1,36 @@
 # # Triangulation wombling
 
 using SpatialBoundaries
-using StatsPlots
-
-# Plot defaults
-
-default(; dpi=500, size=(600, 600), aspectratio=1, c=:davos, frame=:box)
+using CairoMakie
+using StatsBase
 
 # Get some points at random
 
 n = 500
-x = rand(n)
+x = 2rand(n)
 y = rand(n)
-z = [(x[i]<=0.5)&(y[i]<=0.5) ? rand() : rand().+1.2 for i in eachindex(x)]
+z = [(x[i] <= 0.5) & (y[i] <= 0.5) ? rand() : rand() .+ 1.2 for i in eachindex(x)]
 
-scatter(x, y, marker_z = z, lab="")
+scatter(x, y; color = z)
 
 # Womble
 
 W = wombling(x, y, z)
 
 # Get the rate of change
 
-scatter(x, y, c=:lightgrey, msw=0.0, lab="", m=:square, ms=3)
-scatter!(W.x, W.y, marker_z = log1p.(W.m), lab="")
+scatter(x, y; color = :lightgrey)
+scatter!(W.x, W.y; color = log1p.(W.m))
+current_figure()
 
 # Angle histogram
 
-stephist(
-    deg2rad.(sort(vec(W.θ)));
-    proj=:polar,
-    lab="",
-    c=:teal,
-    fill=(0, 0.2, :teal),
-    nbins=100,
-)
+f = Figure()
+ax = PolarAxis(f[1, 1])
+h = fit(Histogram, deg2rad.(values(W.θ)); nbins = 100)
+stairs!(ax, h.edges[1], h.weights[[axes(h.weights, 1)..., 1]]; color = :teal, linewidth = 2)
+current_figure()
 
 # Show the rotation with a color
 
-scatter(W.x, W.y, marker_z = W.θ, c=:vik, clim=(0, 360))
+scatter(W.x, W.y; color = W.θ, colormap = :vikO, colorrange = (0, 360))

src/SpatialBoundaries.jl

@@ -5,15 +5,13 @@ using VoronoiDelaunay
 using LinearAlgebra
 using Statistics
 using StatsBase
-using SpeciesDistributionToolkit
 
 include(joinpath("types", "Womble.jl"))
 export Womble, TriangulationWomble, LatticeWomble
 
 include(joinpath("lib", "rateofchange.jl"))
 
 include(joinpath("lib", "wombling.jl"))
-include(joinpath("extensions", "SpeciesDistributionToolkit.jl"))
 export wombling
 
 include(joinpath("lib", "boundaries.jl"))