Change default example (#276)

Author: JoshuaLampert

NEWS.md

@@ -5,6 +5,12 @@ DispersiveShallowWater.jl follows the interpretation of
 used in the Julia ecosystem. Notable changes will be documented in this file
 for human readability.
 
+## Changes when updating to v0.9 from v0.8.x
+
+#### Changed
+
+- Changed the `default_example()` from a BBM-BBM setup to a physically more relevant Serre-Green-Naghdi setup ([#276]).
+
 ## Changes in the v0.8 lifecycle
 
 #### Added

Project.toml

@@ -1,7 +1,7 @@
 name = "DispersiveShallowWater"
 uuid = "4ab875f6-b79a-4e28-9745-4f0293954817"
 authors = ["Joshua Lampert <joshua.lampert@uni-hamburg.de>"]
-version = "0.8.9-DEV"
+version = "0.9.0-DEV"
 
 [deps]
 BandedMatrices = "aae01518-5342-5314-be14-df237901396f"

README.md

@@ -58,7 +58,7 @@ In the Julia REPL, first load the package DispersiveShallowWater.jl
 julia> using DispersiveShallowWater
 ```
 
-You can run a basic simulation that solves the BBM-BBM equations by executing
+You can run a basic simulation that solves the Serre-Green-Naghdi equations by executing
 
 ```julia
 julia> include(default_example());

docs/src/index.md

@@ -59,7 +59,7 @@ In the Julia REPL, first load the package [DispersiveShallowWater.jl](https://gi
 julia> using DispersiveShallowWater
 ```
 
-You can run a basic simulation that solves the BBM-BBM equations by executing
+You can run a basic simulation that solves the Serre-Green-Naghdi equations by executing
 
 ```julia
 julia> include(default_example());

src/util.jl

@@ -44,7 +44,7 @@ See also [`examples_dir`](@ref) and [`get_examples`](@ref).
 Copied from [Trixi.jl](https://github.com/trixi-framework/Trixi.jl).
 """
 function default_example()
-    joinpath(examples_dir(), "bbm_bbm_1d", "bbm_bbm_1d_basic.jl")
+    joinpath(examples_dir(), "serre_green_naghdi_1d", "serre_green_naghdi_soliton.jl")
 end
 
 """

test/test_unit.jl

@@ -540,15 +540,15 @@ end
 
     accuracy_orders = [2, 4, 6]
     for accuracy_order in accuracy_orders
-        eoc_mean_values, _ = convergence_test(@__MODULE__, default_example(), 2, N = 512,
+        eoc_mean_values, _ = convergence_test(@__MODULE__, default_example(), 2, N = 256,
                                               tspan = (0.0, 1.0),
                                               accuracy_order = accuracy_order)
         @test isapprox(eoc_mean_values[:l2][1], accuracy_order, atol = 0.5)
-        @test isapprox(eoc_mean_values[:linf][2], accuracy_order, atol = 0.5)
-        @test isapprox(eoc_mean_values[:l2][1], accuracy_order, atol = 0.5)
+        @test isapprox(eoc_mean_values[:linf][1], accuracy_order, atol = 0.5)
+        @test isapprox(eoc_mean_values[:l2][2], accuracy_order, atol = 0.5)
         @test isapprox(eoc_mean_values[:linf][2], accuracy_order, atol = 0.5)
 
-        eoc_mean_values2, _ = convergence_test(@__MODULE__, default_example(), [512, 1024],
+        eoc_mean_values2, _ = convergence_test(@__MODULE__, default_example(), [256, 512],
                                                tspan = (0.0, 1.0),
                                                accuracy_order = accuracy_order)
         for kind in (:l2, :linf), variable in (1, 2)