Run CI on Julia v1.10

.buildkite/pipeline.yml

@@ -6,18 +6,18 @@ steps:
   - label: "🦓 Julia 1.6"
     plugins:
       - JuliaCI/julia#v1:
-          version: 1.6
+          version: '1.6'
       - JuliaCI/julia-test#v1: ~
     agents:
       queue: "juliagpu"
       cuda: "*"
     if: build.message !~ /\[skip tests\]/
     timeout_in_minutes: 60
 
-  - label: "🐫 Julia 1.9"
+  - label: "🐫 Julia 1.10"
     plugins:
       - JuliaCI/julia#v1:
-          version: 1.9
+          version: '1.10'
       - JuliaCI/julia-test#v1: ~
       - JuliaCI/julia-coverage#v1:
           codecov: true

.github/workflows/Documenter.yml

@@ -11,10 +11,10 @@ jobs:
   build:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
       - uses: julia-actions/setup-julia@latest
         with:
-          version: 1.9
+          version: '1.10'
       - name: Install dependencies
         run: julia --project=docs/ -e 'using Pkg; Pkg.develop(PackageSpec(path=pwd())); Pkg.instantiate()'
       - name: Build and deploy

appveyor.yml

@@ -1,7 +1,7 @@
 environment:
   matrix:
   - julia_version: 1.6
-  - julia_version: 1.9
+  - julia_version: 1.10
   - julia_version: nightly
 
 platform:

docs/Project.toml

@@ -8,7 +8,7 @@ Literate = "98b081ad-f1c9-55d3-8b20-4c87d4299306"
 Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
 
 [compat]
-CairoMakie = "0.10"
+CairoMakie = "0.11"
 Documenter = "1"
 DocumenterCitations = "1.1"
 Literate = "≥2.9.0"

docs/src/output.md

@@ -36,7 +36,6 @@ DocTestSetup = quote
     E = Diagnostic(energy, prob, freq=2, nsteps=200)
     filepath = "."
     filename = joinpath(filepath, "simplestpde.jld2")
-    get_uh(prob) = prob.sol
 end
 ```
 

docs/src/problem.md

@@ -135,7 +135,7 @@ prob.clock
 ```
 
 Let's initiate our problem with, e.g., ``u(x, 0) = \cos(\pi x)``, integrate up 
-to ``t = 4`` and compare our numerical solution with the analytic solution 
+to ``t = 4`` and compare our numerical solution with the analytical solution 
 ``u(x, t) = e^{-\alpha t} \cos(\pi x)``.
 
 ```@example 2
@@ -165,7 +165,7 @@ ldiv!(prob.vars.u, grid.rfftplan, prob.sol)
 nothing # hide
 ```
 
-and finally, let's plot our solution and compare with the analytic solution:
+and finally, let's plot our solution and compare with the analytical solution:
 
 ```@example 2
 using CairoMakie, Printf

examples/OneDShallowWaterGeostrophicAdjustment.jl

@@ -265,7 +265,7 @@ gaussian_width = 6e3
 gaussian_amplitude = 3.0
 gaussian_bump = @. gaussian_amplitude * exp( - grid.x^2 / (2*gaussian_width^2) )
 
-fig = Figure(resolution = (600, 260))
+fig = Figure(size = (600, 260))
 ax =  Axis(fig[1, 1];
            xlabel = "x [km]",
            ylabel = "η [m]",
@@ -287,7 +287,7 @@ noise_amplitude = 0.1 # the amplitude of the noise for η(x, t=0) (m)
 η_noise = noise_amplitude * Random.randn(size(grid.x))
 @. η_noise *= mask    # mask the noise
 
-fig = Figure(resolution = (600, 520))
+fig = Figure(size = (600, 520))
 
 kwargs = (xlabel = "x [km]", limits = ((-Lx/2e3, Lx/2e3), nothing))
 
@@ -315,7 +315,7 @@ v0 = zeros(grid.nx)
 
 set_uvη!(prob, u0, v0, η0)
 
-fig = Figure(resolution = (600, 260))
+fig = Figure(size = (600, 260))
 
 ax =  Axis(fig[1, 1];
            xlabel = "x [km]",
@@ -376,7 +376,7 @@ v = @lift irfft(file[string("snapshots/sol/", iterations[$n])][:, 2], nx)
 
 toptitle = @lift "t = " * @sprintf("%.1f", file[string("snapshots/t/", iterations[$n])]/60) * " min"
 
-fig = Figure(resolution = (600, 800))
+fig = Figure(size = (600, 800))
 
 kwargs_η = (xlabel = "x [km]", limits = ((-Lx/2e3, Lx/2e3), nothing))
 kwargs_uv = (xlabel = "x [km]", limits = ((-Lx/2e3, Lx/2e3), (-0.3, 0.3)))
@@ -430,7 +430,7 @@ nothing # hide
 # The geostrophic solution should capture well the the behavior of the flow in the center
 # of the domain, after small-scale disturbances propagate away. Let's plot and see!
 
-fig = Figure(resolution = (600, 600))
+fig = Figure(size = (600, 600))
 
 kwargs = (xlabel = "x [km]", limits = ((-Lx/2e3, Lx/2e3), (-0.3, 0.3)))