create some more figures

some improvements related to plotting
JoshuaLampert · Sep 25, 2023 · c370f28 · c370f28
1 parent 55275a3
commit c370f28
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Showing 18 changed files with 165 additions and 100 deletions.
diff --git a/create_figures.jl b/create_figures.jl
@@ -56,7 +56,7 @@ function fig_2()
     plot(k, c_euler.(k) ./ c0, label = "Euler", ylim = ylim, xguide = L"k",
          yguide = L"c/c_0", linewidth = linewidth, markershape = :circle,
          markersize = markersize)
-    plot!(k_zoom, c_euler.(k_zoom) ./ c0, ylims = (0.54, 1.0),
+    plot!(k_zoom, c_euler.(k_zoom) ./ c0, ylim = (0.54, 1.0),
           inset = bbox(0.35, 0.1, 0.35, 0.3), subplot = 2, legend = nothing,
           linewidth = linewidth, markershape = :circle, markersize = markersize)
 
@@ -112,18 +112,72 @@ function fig_2()
     savefig(joinpath(OUT, "dispersion_relations.pdf"))
 end
 
+const OUT_SOLITON = joinpath(OUT, "soliton")
+ispath(OUT_SOLITON) || mkpath(OUT_SOLITON)
+
+# Plot errors, change of invariants, and solution at final time for baseline and relaxation
+function fig_3_4_5()
+    linewidth = 2
+
+    g = 9.81
+    D = 2.0
+    c = 5 / 2 * sqrt(g * D)
+    x_min = -35.0
+    x_max = 35.0
+    tspan = (0.0, 50 * (x_max - x_min) / c)
+    N = 512
+    accuracy_order = 8
+
+    # baseline
+    trixi_include(joinpath(examples_dir(), EXAMPLES_DIR_BBMBBM, "bbm_bbm_1d_basic.jl"),
+                  gravity_constant = g, D = D, coordinates_min = x_min,
+                  coordinates_max = x_max, tspan = tspan, N = N,
+                  accuracy_order = accuracy_order)
+    p1 = plot(analysis_callback, title = "", label_extension = "baseline", style = :auto,
+              linewidth = linewidth, layout = 2, subplot = 1)
+    p2 = plot(analysis_callback, title = "", what = (:errors,),
+              label_extension = "baseline", linestyle = :dash, linewidth = linewidth,
+              ylabel = L"\Vert\eta - \eta_{ana}\Vert_2 + \Vert v - v_{ana}\Vert_2",
+              exclude = [:conservation_error])
+    p3 = plot(semi => sol, label = "baseline", plot_initial = true, linestyle = :dash,
+              linewidth = linewidth, plot_title = "", title = "")
+
+    # relaxation
+    trixi_include(joinpath(examples_dir(), EXAMPLES_DIR_BBMBBM, "bbm_bbm_1d_relaxation.jl"),
+                  gravity_constant = g, D = D, coordinates_min = x_min,
+                  coordinates_max = x_max, tspan = tspan, N = N,
+                  accuracy_order = accuracy_order)
+    plot!(p1, analysis_callback, title = "", label_extension = "relaxation", style = :auto,
+          linewidth = linewidth, subplot = 2)
+    plot!(p2, analysis_callback, title = "", what = (:errors,),
+          label_extension = "relaxation", linestyle = :dot, linewidth = linewidth,
+          ylabel = L"\Vert\eta - \eta_{ana}\Vert_2 + \Vert v - v_{ana}\Vert_2",
+          exclude = [:conservation_error])
+    plot!(p3, semi => sol, plot_bathymetry = false, label = "relaxation", linestyle = :dot,
+          linewidth = linewidth, plot_title = "", title = "", color = :green)
+
+    savefig(p1, joinpath(OUT_SOLITON, "invariants.pdf"))
+    savefig(p2, joinpath(OUT_SOLITON, "errors.pdf"))
+    savefig(p3, joinpath(OUT_SOLITON, "solution.pdf"))
+end
+
 # Plot convergence orders for baseline and relaxation
-function fig_3()
+function fig_6()
     tspan = (0.0, 10.0)
     accuracy_orders = [2, 4, 6, 8]
-    styles = [:dash, :dot, :dashdot, :dashdotdot]
     iters = [4, 4, 4, 3]
     initial_Ns = [128, 128, 128, 128]
 
     all_Ns = minimum(initial_Ns) * 2 .^ (0:(maximum(iters) - 1))
 
-    plot([], label = :none, xscale = :log2, yscale = :log10, xticks = all_Ns, xlabel = "N",
-         ylabel = L"||\eta - \eta_{ana}||_2 + ||v - v_{ana}||_2")
+    linewidth = 2
+    markersize = 5
+    markershapes = [:circle, :star5, :star8, :rtriangle]
+    plot(label = :none, xscale = :log2, yscale = :log10, xlabel = "N", ylim = (1e-5, 1e2),
+         ylabel = L"\Vert\eta - \eta_{ana}\Vert_2 + \Vert v - v_{ana}\Vert_2",
+         legend = :bottomleft, layout = 2)
+
+    # left subplot: baseline
     for i in 1:length(accuracy_orders)
         Ns = initial_Ns[i] * 2 .^ (0:(iters[i] - 1))
         _, errormatrix = convergence_test("examples/bbm_bbm_1d/bbm_bbm_1d_basic.jl",
@@ -133,12 +187,13 @@ function fig_3()
         l2_err = sum(errormatrix[:l2], dims = 2)
         eocs = log.(l2_err[2:end] ./ l2_err[1:(end - 1)]) ./ log(0.5)
         eoc_mean = round(sum(eocs) / length(eocs), digits = 2)
-        plot!(Ns, l2_err, style = styles[i], label = "p = $accuracy_order, EOC: $eoc_mean")
+        plot!(Ns, l2_err, label = "p = $accuracy_order, EOC: $eoc_mean",
+              markershape = markershapes[i], linewidth = linewidth, markersize = markersize,
+              subplot = 1)
     end
-    savefig(joinpath(OUT, "orders.pdf"))
+    xticks!(all_Ns, string.(all_Ns), subplot = 1)
 
-    plot([], label = :none, xscale = :log2, yscale = :log10, xticks = all_Ns, xlabel = "N",
-         ylabel = L"||\eta - \eta_{ana}||_2 + ||v - v_{ana}||_2")
+    # right subplot: relaxation
     for i in 1:length(accuracy_orders)
         Ns = initial_Ns[i] * 2 .^ (0:(iters[i] - 1))
         _, errormatrix = convergence_test("examples/bbm_bbm_1d/bbm_bbm_1d_relaxation.jl",
@@ -148,11 +203,15 @@ function fig_3()
         l2_err = sum(errormatrix[:l2], dims = 2)
         eocs = log.(l2_err[2:end] ./ l2_err[1:(end - 1)]) ./ log(0.5)
         eoc_mean = round(sum(eocs) / length(eocs), digits = 2)
-        plot!(Ns, l2_err, style = styles[i], label = "p = $accuracy_order, EOC: $eoc_mean")
+        plot!(Ns, l2_err, label = "p = $accuracy_order, EOC: $eoc_mean",
+              markershape = markershapes[i], linewidth = linewidth, markersize = markersize,
+              subplot = 2)
     end
-    savefig(joinpath(OUT, "orders_relaxation.pdf"))
+    xticks!(all_Ns, string.(all_Ns), subplot = 2)
+    savefig(joinpath(OUT_SOLITON, "orders.pdf"))
 end
 
 fig_1()
 fig_2()
-fig_3()
+fig_3_4_5()
+fig_6()
diff --git a/docs/src/overview.md b/docs/src/overview.md
@@ -105,16 +105,13 @@ savefig("shoaling_solution.png")
 
 ![](shoaling_solution.png)
 
-By default, this will plot the bathymetry, but not the initial (analytical) solution. You can adjust this by passing the boolean values `plot_bathymetry` (if `true` always plot to first subplot) and `plot_initial`. You can also provide a `conversion` function that converts the solution. A conversion function should take the values of the primitive variables `q` at one node, and the `equations` as input and should return an `SVector` of any length as output. For a user defined conversion function, there should also exist a function `varnames(conversion, equations)` that returns a `Tuple` of the variable names used for labelling. The conversion function can, e.g., be [`prim2cons`](@ref) or [`waterheight_total`](@ref) if one only wants to plot the total waterheight. The resulting plot will have one subplot for each of the returned variables of the conversion variable. By default, the conversion function is just [`prim2prim`](@ref), i.e. the identity. The limits of the y-axis can be set by the keyword argument `yli`, which should be given as a vector of `Tuple`s with the same length as there are subplots.
-
-!!! note "Setting y limits"
-    `ylim` and similar arguments are already occupied by Plots.jl and do not work with different y limits for multiple subplots.
+By default, this will plot the bathymetry, but not the initial (analytical) solution. You can adjust this by passing the boolean values `plot_bathymetry` (if `true` always plot to first subplot) and `plot_initial`. You can also provide a `conversion` function that converts the solution. A conversion function should take the values of the primitive variables `q` at one node, and the `equations` as input and should return an `SVector` of any length as output. For a user defined conversion function, there should also exist a function `varnames(conversion, equations)` that returns a `Tuple` of the variable names used for labelling. The conversion function can, e.g., be [`prim2cons`](@ref) or [`waterheight_total`](@ref) if one only wants to plot the total waterheight. The resulting plot will have one subplot for each of the returned variables of the conversion variable. By default, the conversion function is just [`prim2prim`](@ref), i.e. the identity.
 
 Plotting an animation over time can, e.g., be done by the following command, which uses `step` to plot the solution at a specific time step.
 
 ```@example overview
 anim = @animate for step in 1:length(sol.u)
-    plot(semi => sol, plot_initial = true, conversion = waterheight_total, step = step, xlim = (-50, 20), yli = [(-0.8, 0.1)])
+    plot(semi => sol, plot_initial = true, conversion = waterheight_total, step = step, xlim = (-50, 20), ylims = [(-0.8, 0.1)])
 end
 gif(anim, "shoaling_solution.gif", fps = 25)
 ```
@@ -213,7 +210,7 @@ callbacks = CallbackSet(relaxation_callback, analysis_callback)
 sol = solve(ode, Tsit5(), abstol = 1e-7, reltol = 1e-7,
             save_everystep = false, callback = callbacks, saveat = saveat)
 anim = @animate for step in 1:length(sol.u)
-    plot(semi => sol, plot_initial = true, conversion = waterheight_total, step = step, xlim = (-50, 20), yli = [(-0.8, 0.1)])
+    plot(semi => sol, plot_initial = true, conversion = waterheight_total, step = step, xlim = (-50, 20), ylims = [(-0.8, 0.1)])
 end
 gif(anim, "shoaling_solution_dg.gif", fps = 25)
 ```

diff --git a/examples/bbm_bbm_1d/bbm_bbm_1d_basic.jl b/examples/bbm_bbm_1d/bbm_bbm_1d_basic.jl
@@ -14,7 +14,7 @@ boundary_conditions = boundary_condition_periodic
 coordinates_min = -35.0
 coordinates_max = 35.0
 N = 512
-mesh = Mesh1D(coordinates_min, coordinates_max, N + 1)
+mesh = Mesh1D(coordinates_min, coordinates_max, N)
 
 # create solver with periodic SBP operators of accuracy order 4
 accuracy_order = 4

diff --git a/examples/bbm_bbm_1d/bbm_bbm_1d_relaxation.jl b/examples/bbm_bbm_1d/bbm_bbm_1d_relaxation.jl
@@ -14,7 +14,7 @@ boundary_conditions = boundary_condition_periodic
 coordinates_min = -35.0
 coordinates_max = 35.0
 N = 512
-mesh = Mesh1D(coordinates_min, coordinates_max, N + 1)
+mesh = Mesh1D(coordinates_min, coordinates_max, N)
 
 # create solver with periodic SBP operators of accuracy order 4
 accuracy_order = 4

diff --git a/examples/bbm_bbm_variable_bathymetry_1d/bbm_bbm_variable_bathymetry_1d_basic.jl b/examples/bbm_bbm_variable_bathymetry_1d/bbm_bbm_variable_bathymetry_1d_basic.jl
@@ -14,7 +14,7 @@ boundary_conditions = boundary_condition_periodic
 coordinates_min = -35.0
 coordinates_max = 35.0
 N = 512
-mesh = Mesh1D(coordinates_min, coordinates_max, N + 1)
+mesh = Mesh1D(coordinates_min, coordinates_max, N)
 
 # create solver with periodic SBP operators of accuracy order 4
 solver = Solver(mesh, 4)

diff --git a/examples/bbm_bbm_variable_bathymetry_1d/bbm_bbm_variable_bathymetry_1d_dingemans.jl b/examples/bbm_bbm_variable_bathymetry_1d/bbm_bbm_variable_bathymetry_1d_dingemans.jl
@@ -13,7 +13,7 @@ boundary_conditions = boundary_condition_periodic
 coordinates_min = -138.0
 coordinates_max = 46.0
 N = 512
-mesh = Mesh1D(coordinates_min, coordinates_max, N + 1)
+mesh = Mesh1D(coordinates_min, coordinates_max, N)
 
 # create solver with periodic SBP operators of accuracy order 4
 solver = Solver(mesh, 4)

diff --git a/examples/bbm_bbm_variable_bathymetry_1d/bbm_bbm_variable_bathymetry_1d_relaxation.jl b/examples/bbm_bbm_variable_bathymetry_1d/bbm_bbm_variable_bathymetry_1d_relaxation.jl
@@ -16,7 +16,7 @@ boundary_conditions = boundary_condition_periodic
 coordinates_min = -1.0
 coordinates_max = 1.0
 N = 512
-mesh = Mesh1D(coordinates_min, coordinates_max, N + 1)
+mesh = Mesh1D(coordinates_min, coordinates_max, N)
 
 # create solver with periodic SBP operators
 D1 = periodic_derivative_operator(1, 4, mesh.xmin, mesh.xmax, mesh.N)

diff --git a/examples/bbm_bbm_variable_bathymetry_1d/bbm_bbm_variable_bathymetry_1d_well_balanced.jl b/examples/bbm_bbm_variable_bathymetry_1d/bbm_bbm_variable_bathymetry_1d_well_balanced.jl
@@ -35,7 +35,7 @@ boundary_conditions = boundary_condition_periodic
 coordinates_min = -1.0
 coordinates_max = 1.0
 N = 512
-mesh = Mesh1D(coordinates_min, coordinates_max, N + 1)
+mesh = Mesh1D(coordinates_min, coordinates_max, N)
 
 # create solver with periodic SBP operators
 D1 = periodic_derivative_operator(1, 4, mesh.xmin, mesh.xmax, mesh.N)

diff --git a/examples/svaerd_kalisch_1d/svaerd_kalisch_1d_dingemans.jl b/examples/svaerd_kalisch_1d/svaerd_kalisch_1d_dingemans.jl
@@ -14,7 +14,7 @@ boundary_conditions = boundary_condition_periodic
 coordinates_min = -138.0
 coordinates_max = 46.0
 N = 512
-mesh = Mesh1D(coordinates_min, coordinates_max, N + 1)
+mesh = Mesh1D(coordinates_min, coordinates_max, N)
 
 # create solver with periodic SBP operators of accuracy order 4
 solver = Solver(mesh, 4)

diff --git a/examples/svaerd_kalisch_1d/svaerd_kalisch_1d_dingemans_relaxation.jl b/examples/svaerd_kalisch_1d/svaerd_kalisch_1d_dingemans_relaxation.jl
@@ -14,7 +14,7 @@ boundary_conditions = boundary_condition_periodic
 coordinates_min = -138.0
 coordinates_max = 46.0
 N = 512
-mesh = Mesh1D(coordinates_min, coordinates_max, N + 1)
+mesh = Mesh1D(coordinates_min, coordinates_max, N)
 
 # create solver with periodic SBP operators of accuracy order 4
 solver = Solver(mesh, 4)

diff --git a/examples/svaerd_kalisch_1d/svaerd_kalisch_1d_dingemans_upwind.jl b/examples/svaerd_kalisch_1d/svaerd_kalisch_1d_dingemans_upwind.jl
@@ -15,7 +15,7 @@ boundary_conditions = boundary_condition_periodic
 coordinates_min = -138.0
 coordinates_max = 46.0
 N = 512
-mesh = Mesh1D(coordinates_min, coordinates_max, N + 1)
+mesh = Mesh1D(coordinates_min, coordinates_max, N)
 
 # create solver with periodic SBP operators of accuracy order 4
 accuracy_order = 4

diff --git a/examples/svaerd_kalisch_1d/svaerd_kalisch_1d_well_balanced.jl b/examples/svaerd_kalisch_1d/svaerd_kalisch_1d_well_balanced.jl
@@ -36,7 +36,7 @@ boundary_conditions = boundary_condition_periodic
 coordinates_min = -1.0
 coordinates_max = 1.0
 N = 200
-mesh = Mesh1D(coordinates_min, coordinates_max, N + 1)
+mesh = Mesh1D(coordinates_min, coordinates_max, N)
 
 # create solver with periodic SBP operators of accuracy order 4
 solver = Solver(mesh, 4)

diff --git a/plot_examples.jl b/plot_examples.jl
@@ -28,7 +28,7 @@ macro plot_example(filename, args...)
 
         # Plot solution
         anim = @animate for step in 1:length(sol.u)
-            plot(semi => sol, plot_initial = true, step = step, yli = $ylims_gif)
+            plot(semi => sol, plot_initial = true, step = step, ylims = $ylims_gif)
         end
         gif(anim, joinpath(outdir, "solution.gif"), fps = 25)
 
@@ -39,7 +39,7 @@ macro plot_example(filename, args...)
         # Plot at different x values over time
         @assert size($x_values) == size($tlims)
         for (i, x) in enumerate($x_values)
-            plot(semi => sol, x, xlim = $tlims[i], yli = $ylims_x)
+            plot(semi => sol, x, xlim = $tlims[i], ylims = $ylims_x)
             savefig(joinpath(outdir, "solution_at_x_" * string(x) * ".pdf"))
         end
     end
@@ -66,19 +66,19 @@ const EXAMPLES_DIR_SVAERD_KALISCH = "svaerd_kalisch_1d"
 # Travelling wave solution for one-dimensional BBM-BBM equations with periodic boundary conditions
 # using periodic SBP operators
 @plot_example(joinpath(EXAMPLES_DIR_BBMBBM, "bbm_bbm_1d_basic.jl"),
-              ylims_gif=[(-8, 4), :auto], tspan=(0.0, 50.0))
+              ylims_gif=[(-8, 4) :auto], tspan=(0.0, 50.0))
 
 ###############################################################################
 # Travelling wave solution for one-dimensional BBM-BBM equations with periodic boundary conditions
 # using discontinuously coupled Legendre SBP operators
 @plot_example(joinpath(EXAMPLES_DIR_BBMBBM, "bbm_bbm_1d_dg.jl"),
-              ylims_gif=[(-4, 2), :auto])
+              ylims_gif=[(-4, 2) :auto])
 
 ###############################################################################
 # Travelling wave solution for one-dimensional BBM-BBM equations with periodic boundary conditions
 # using periodic SBP operators and relaxation, is energy-conservative
 @plot_example(joinpath(EXAMPLES_DIR_BBMBBM, "bbm_bbm_1d_relaxation.jl"),
-              ylims_gif=[(-8, 4), (-10, 30)],
+              ylims_gif=[(-8, 4) (-10, 30)],
               tspan=(0.0, 30.0))
 
 ###############################################################################
@@ -87,7 +87,7 @@ const EXAMPLES_DIR_SVAERD_KALISCH = "svaerd_kalisch_1d"
 # as a constant. Should give the same result as "bbm_bbm_1d_basic.jl"
 @plot_example(joinpath(EXAMPLES_DIR_BBMBBM_VARIABLE,
                        "bbm_bbm_variable_bathymetry_1d_basic.jl"),
-              ylims_gif=[(-8, 4), :auto],
+              ylims_gif=[(-8, 4) :auto],
               tspan=(0.0, 50.0))
 
 ###############################################################################
@@ -96,7 +96,7 @@ const EXAMPLES_DIR_SVAERD_KALISCH = "svaerd_kalisch_1d"
 # is energy-conservative. Uses periodic finite difference SBP operators.
 @plot_example(joinpath(EXAMPLES_DIR_BBMBBM_VARIABLE,
                        "bbm_bbm_variable_bathymetry_1d_relaxation.jl"),
-              ylims_gif=[(-1.5, 6.0), (-10.0, 10.0)],
+              ylims_gif=[(-1.5, 6.0) (-10.0, 10.0)],
               tspan=(0.0, 10.0))
 
 ###############################################################################
@@ -105,7 +105,7 @@ const EXAMPLES_DIR_SVAERD_KALISCH = "svaerd_kalisch_1d"
 # is energy-conservative. Uses upwind discontinuously coupled SBP operators.
 @plot_elixir(joinpath(EXAMPLES_DIR_BBMBBM_VARIABLE,
                       "bbm_bbm_variable_bathymetry_1d_dg_upwind_relaxation.jl"),
-             ylims_gif=[(-1.5, 6.0), (-10.0, 10.0)],
+             ylims_gif=[(-1.5, 6.0) (-10.0, 10.0)],
              tspan=(0.0, 10.0))
 
 ###############################################################################
@@ -114,7 +114,7 @@ const EXAMPLES_DIR_SVAERD_KALISCH = "svaerd_kalisch_1d"
 # is energy-conservative. Uses periodic finite difference discontinuously coupled SBP operators.
 @plot_example(joinpath(EXAMPLES_DIR_BBMBBM_VARIABLE,
                        "bbm_bbm_variable_bathymetry_1d_upwind_relaxation.jl"),
-              ylims_gif=[(-1.5, 6.0), (-10.0, 10.0)],
+              ylims_gif=[(-1.5, 6.0) (-10.0, 10.0)],
               tspan=(0.0, 10.0))
 
 ###############################################################################
@@ -124,16 +124,16 @@ const EXAMPLES_DIR_SVAERD_KALISCH = "svaerd_kalisch_1d"
 # (exactly) constant in time.
 @plot_example(joinpath(EXAMPLES_DIR_BBMBBM_VARIABLE,
                        "bbm_bbm_variable_bathymetry_1d_well_balanced.jl"),
-              ylims_gif=[(2.0 - 1e-3, 2.0 + 1e-3), (-1e-3, 1e-3)],
+              ylims_gif=[(2.0 - 1e-3, 2.0 + 1e-3) (-1e-3, 1e-3)],
               tspan=(0.0, 10.0))
 
 ###############################################################################
 # One-dimensional BBM-BBM equations with initial condition that models
 # a wave make. This setup comes from experiments by W. M. Dingemans.
 @plot_example(joinpath(EXAMPLES_DIR_BBMBBM_VARIABLE,
                        "bbm_bbm_variable_bathymetry_1d_dingemans.jl"),
-              ylims_gif=[(-0.1, 0.9), (-0.3, 0.3)],
-              ylims_x=[:auto, :auto],
+              ylims_gif=[(-0.1, 0.9) (-0.3, 0.3)],
+              ylims_x=[:auto :auto],
               x_values=[3.04, 9.44, 20.04, 26.04, 30.44, 37.04],
               tlims=[
                   (15.0, 45.0),
@@ -150,8 +150,8 @@ const EXAMPLES_DIR_SVAERD_KALISCH = "svaerd_kalisch_1d"
 # a wave make. This setup comes from experiments by W. M. Dingemans.
 @plot_example(joinpath(EXAMPLES_DIR_SVAERD_KALISCH,
                        "svaerd_kalisch_1d_dingemans.jl"),
-              ylims_gif=[(-0.1, 0.9), (-0.3, 0.3)],
-              ylims_x=[:auto, :auto],
+              ylims_gif=[(-0.1, 0.9) (-0.3, 0.3)],
+              ylims_x=[:auto :auto],
               x_values=[3.04, 9.44, 20.04, 26.04, 30.44, 37.04],
               tlims=[
                   (15.0, 45.0),
@@ -168,8 +168,8 @@ const EXAMPLES_DIR_SVAERD_KALISCH = "svaerd_kalisch_1d"
 # a wave make. This setup comes from experiments by W. M. Dingemans.
 @plot_example(joinpath(EXAMPLES_DIR_SVAERD_KALISCH,
                        "svaerd_kalisch_1d_dingemans_upwind.jl"),
-              ylims_gif=[(-0.1, 0.9), (-0.3, 0.3)],
-              ylims_x=[:auto, :auto],
+              ylims_gif=[(-0.1, 0.9) (-0.3, 0.3)],
+              ylims_x=[:auto :auto],
               x_values=[3.04, 9.44, 20.04, 26.04, 30.44, 37.04],
               tlims=[
                   (15.0, 45.0),
@@ -187,8 +187,8 @@ const EXAMPLES_DIR_SVAERD_KALISCH = "svaerd_kalisch_1d"
 # to preserve the modified entropy.
 @plot_example(joinpath(EXAMPLES_DIR_SVAERD_KALISCH,
                        "svaerd_kalisch_1d_dingemans_relaxation.jl"),
-              ylims_gif=[(-0.1, 0.9), (-0.3, 0.3)],
-              ylims_x=[:auto, :auto],
+              ylims_gif=[(-0.1, 0.9) (-0.3, 0.3)],
+              ylims_x=[:auto :auto],
               x_values=[3.04, 9.44, 20.04, 26.04, 30.44, 37.04],
               tlims=[
                   (15.0, 45.0),
@@ -207,5 +207,5 @@ const EXAMPLES_DIR_SVAERD_KALISCH = "svaerd_kalisch_1d"
 # (exactly) constant in time.
 @plot_example(joinpath(EXAMPLES_DIR_SVAERD_KALISCH,
                        "svaerd_kalisch_1d_well_balanced.jl"),
-              ylims=[(2.0 - 1e-3, 2.0 + 1e-3), (-1e-3, 1e-3)],
+              ylims=[(2.0 - 1e-3, 2.0 + 1e-3) (-1e-3, 1e-3)],
               tspan=(0.0, 10.0))