Merge branch 'main' into interpolate-x-plot

JoshuaLampert · Nov 20, 2023 · c8f40f3 · c8f40f3
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diff --git a/.github/workflows/CI.yml b/.github/workflows/CI.yml
@@ -5,17 +5,25 @@ on:
       - main
     tags: ['*']
     paths-ignore:
+      - 'CITATION.bib'
       - 'LICENSE.md'
       - 'README.md'
+      - '.zenodo.json'
       - '.github/workflows/CompatHelper.yml'
+      - '.github/workflows/Documenter.yml'
+      - '.github/workflows/Format-check.yml'
       - '.github/workflows/TagBot.yml'
       - '.github/workflows/SpellCheck.yml'
       - 'docs/**'
   pull_request:
     paths-ignore:
+      - 'CITATION.bib'
       - 'LICENSE.md'
       - 'README.md'
+      - '.zenodo.json'
       - '.github/workflows/CompatHelper.yml'
+      - '.github/workflows/Documenter.yml'
+      - '.github/workflows/Format-check.yml'
       - '.github/workflows/TagBot.yml'
       - '.github/workflows/SpellCheck.yml'
       - 'docs/**'

diff --git a/.github/workflows/Documenter.yml b/.github/workflows/Documenter.yml
@@ -6,6 +6,7 @@ on:
       - 'main'
     tags: '*'
     paths-ignore:
+      - '.zenodo.json'
       - '.github/workflows/CI.yml'
       - '.github/workflows/CompatHelper.yml'
       - '.github/workflows/TagBot.yml'

diff --git a/.github/workflows/Format-check.yml b/.github/workflows/Format-check.yml
@@ -25,7 +25,7 @@ jobs:
       - name: Install JuliaFormatter and format
         run: |
           julia -e 'using Pkg; Pkg.add(PackageSpec(name = "JuliaFormatter"))'
-          julia -e 'using JuliaFormatter; format(["src", "test", "examples", "visualization"], verbose = true)'
+          julia -e 'using JuliaFormatter; format(["src", "test", "examples"], verbose = true)'
       - name: Format check
         run: |
           julia -e '

diff --git a/CITATION.bib b/CITATION.bib
@@ -0,0 +1,9 @@
+@misc{lampert2023dispersive,
+  title={{D}ispersive{S}hallow{W}ater.jl: {S}tructure-preserving numerical
+         methods for dispersive shallow water models},
+  author={Lampert, Joshua},
+  year={2023},
+  month={10},
+  howpublished={\url{https://github.com/JoshuaLampert/DispersiveShallowWater.jl}},
+  doi={10.5281/zenodo.10034636}
+}
diff --git a/Project.toml b/Project.toml
@@ -21,12 +21,15 @@ SummationByPartsOperators = "9f78cca6-572e-554e-b819-917d2f1cf240"
 [compat]
 DiffEqBase = "6.121"
 Interpolations = "0.14"
+LinearAlgebra = "1"
 PolynomialBases = "0.4.15"
+Printf = "1"
 RecipesBase = "1.1"
 Reexport = "1.0"
 Roots = "2.0.17"
 SciMLBase = "1.90, 2"
 SimpleUnPack = "1.1"
+SparseArrays = "1"
 StaticArrays = "1"
 SummationByPartsOperators = "0.5.41"
 julia = "1.8"
diff --git a/README.md b/README.md
@@ -56,9 +56,24 @@ for more details. Other examples can be found in the subdirectory [examples/](ht
 A list of all examples is returned by running `get_examples()`. You can pass the filename of one of the examples or your own simulation file to `include` in order to run it,
 e.g., `include(joinpath(examples_dir(), "svaerd_kalisch_1d", "svaerd_kalisch_1d_dingemans_relaxation.jl"))`.
 
+## Referencing
+
+You can directly refer to DispersiveShallowWater.jl as
+```bibtex
+@misc{lampert2023dispersive,
+  title={{D}ispersive{S}hallow{W}ater.jl: {S}tructure-preserving numerical
+         methods for dispersive shallow water models},
+  author={Lampert, Joshua},
+  year={2023},
+  month={10},
+  howpublished={\url{https://github.com/JoshuaLampert/DispersiveShallowWater.jl}},
+  doi={10.5281/zenodo.10034636}
+}
+```
+
 ## Authors
 
-The package is developed and maintained by Joshua Lampert and was initiated as part of the master thesis "Structure-Preserving Numerical Methods for Dispersive Shallow Water Models" (2023).
+The package is developed and maintained by Joshua Lampert (University of Hamburg).
 Some parts of this repository are based on parts of [Dispersive-wave-schemes-notebooks. A Broad Class of Conservative Numerical Methods for Dispersive Wave Equations](https://github.com/ranocha/Dispersive-wave-schemes-notebooks)
 by Hendrik Ranocha, Dimitrios Mitsotakis and David Ketcheson. The code structure is inspired by [Trixi.jl](https://github.com/trixi-framework/Trixi.jl/).
 

diff --git a/docs/make.jl b/docs/make.jl
@@ -18,7 +18,6 @@ makedocs(;
          pages = [
              "Home" => "index.md",
              "Overview" => "overview.md",
-             "Reproduce figures" => "reproduce.md",
              "Reference" => "ref.md",
              "License" => "license.md",
          ])

diff --git a/docs/src/index.md b/docs/src/index.md
@@ -18,7 +18,7 @@ The semidiscretizations are based on summation by parts (SBP) operators, which a
 In order to obtain fully discrete schemes, the time integration methods from [OrdinaryDiffEq.jl](https://github.com/SciML/OrdinaryDiffEq.jl) are used to solve the resulting ordinary differential equations.
 Fully discrete entropy-conservative methods can be obtained by using the [relaxation method](https://epubs.siam.org/doi/10.1137/19M1263662) provided by DispersiveShallowWater.jl.
 
-# Installation
+## Installation
 
 If you have not yet installed Julia, then you first need to [download Julia](https://julialang.org/downloads/). Please [follow the instructions for your operating system](https://julialang.org/downloads/platform/).
 DispersiveShallowWater.jl works with Julia v1.8 and newer. DispersiveShallowWater.jl is a registered Julia package. Therefore, you can install it by executing the following commands from the Julia REPL
@@ -34,7 +34,7 @@ which can be installed running
 julia> Pkg.add("SummationByPartsOperators")
 ```
 
-# Usage
+## Usage
 
 In the Julia REPL, first load the package DispersiveShallowWater.jl
 ```julia
@@ -55,12 +55,27 @@ for more details. Other examples can be found in the subdirectory [examples/](ht
 A list of all examples is returned by running [`get_examples()`](@ref). You can pass the filename of one of the examples or your own simulation file to `include` in order to run it,
 e.g., `include(joinpath(examples_dir(), "svaerd_kalisch_1d", "svaerd_kalisch_1d_dingemans_relaxation.jl"))`.
 
-# Authors
+## Referencing
 
-The package is developed and maintained by Joshua Lampert and was initiated as part of the master thesis "Structure-Preserving Numerical Methods for Dispersive Shallow Water Models" (2023).
+You can directly refer to DispersiveShallowWater.jl as
+```bibtex
+@misc{lampert2023dispersive,
+  title={{D}ispersive{S}hallow{W}ater.jl: {S}tructure-preserving numerical
+         methods for dispersive shallow water models},
+  author={Lampert, Joshua},
+  year={2023},
+  month={10},
+  howpublished={\url{https://github.com/JoshuaLampert/DispersiveShallowWater.jl}},
+  doi={10.5281/zenodo.10034636}
+}
+```
+
+## Authors
+
+The package is developed and maintained by Joshua Lampert (University of Hamburg).
 Some parts of this repository are based on parts of [Dispersive-wave-schemes-notebooks. A Broad Class of Conservative Numerical Methods for Dispersive Wave Equations](https://github.com/ranocha/Dispersive-wave-schemes-notebooks)
 by Hendrik Ranocha, Dimitrios Mitsotakis and David Ketcheson. The code structure is inspired by [Trixi.jl](https://github.com/trixi-framework/Trixi.jl/).
 
-# License and contributing
+## License and contributing
 
 DispersiveShallowWater.jl is published under the MIT license (see [License](https://github.com/JoshuaLampert/DispersiveShallowWater.jl/blob/main/LICENSE)). We are pleased to accept contributions from everyone, preferably in the form of a PR.
diff --git a/docs/src/overview.md b/docs/src/overview.md
@@ -117,7 +117,8 @@ end
 gif(anim, "shoaling_solution.gif", fps = 25)
 ```
 
-It is also possible to plot the solution variables at a fixed spatial point over time by calling `plot(semi => sol, x)` for some `x`-value, see [plot_examples.jl](https://github.com/JoshuaLampert/DispersiveShallowWater.jl/blob/main/visualization/plot_examples.jl) for some examples.
+It is also possible to plot the solution variables at a fixed spatial point over time by calling `plot(semi => sol, x)` for some `x`-value, see [plot_examples.jl](https://github.com/JoshuaLampert/2023-master-thesis/blob/main/code/plot_examples.jl) from
+the reproducibility repository of the master thesis of Joshua Lampert for some examples.
 
 Often, it is interesting to have a look at how the quantities that are recorded by the `AnalysisCallback` evolve in time. To this end, you can `plot` the `AnalysisCallback` by
 
@@ -224,7 +225,7 @@ For more details see also the [documentation of SummationByPartsOperators.jl](ht
 
 Some more examples sorted by the simulated equations can be found in the [examples/](https://github.com/JoshuaLampert/DispersiveShallowWater.jl/tree/main/examples) subdirectory. Especially, in [examples/svaerd\_kalisch\_1d/](https://github.com/JoshuaLampert/DispersiveShallowWater.jl/tree/main/examples/svaerd_kalisch_1d) you can find Julia scripts that solve the [`SvaerdKalischEquations1D`](@ref) that were not covered in this tutorial. The same steps as described above, however, apply in the same way to these equations. Attention must be paid for these equations because they do not conserve the classical total entropy ``\mathcal E``, but a modified entropy ``\hat{\mathcal E}``, available as [`entropy_modified`](@ref).
 
-More examples, especially focussing on plotting, can be found in the scripts [create_figures.jl](https://github.com/JoshuaLampert/DispersiveShallowWater.jl/blob/main/visualization/create_figures.jl) and [plot_examples.jl](https://github.com/JoshuaLampert/DispersiveShallowWater.jl/blob/main/visualization/plot_examples.jl).
+More examples, especially focussing on plotting, can be found in the scripts [create_figures.jl](https://github.com/JoshuaLampert/2023-master-thesis/blob/main/code/create_figures.jl) and [plot_examples.jl](https://github.com/JoshuaLampert/2023-master-thesis/blob/main/code/plot_examples.jl) from the reproducibility repository of the master thesis of Joshua Lampert.
 
 ## References
 

diff --git a/docs/src/reproduce.md b/docs/src/reproduce.md
diff --git a/visualization/bbm_bbm_1d_widestencil.jl → ...les/bbm_bbm_1d/bbm_bbm_1d_manufactured.jl b/visualization/bbm_bbm_1d_widestencil.jl → ...les/bbm_bbm_1d/bbm_bbm_1d_manufactured.jl
@@ -1,36 +1,33 @@
 using OrdinaryDiffEq
 using DispersiveShallowWater
-using SummationByPartsOperators: periodic_derivative_operator
-using SparseArrays: sparse
 
 ###############################################################################
 # Semidiscretization of the BBM-BBM equations
 
-equations = BBMBBMEquations1D(gravity_constant = 9.81, D = 2.0)
+equations = BBMBBMEquations1D(gravity_constant = 9.81, D = 4.0)
 
-# initial_condition_convergence_test needs periodic boundary conditions
-initial_condition = initial_condition_convergence_test
+initial_condition = initial_condition_manufactured
+source_terms = source_terms_manufactured
 boundary_conditions = boundary_condition_periodic
 
 # create homogeneous mesh
-coordinates_min = -35.0
-coordinates_max = 35.0
+coordinates_min = 0.0
+coordinates_max = 1.0
 N = 512
 mesh = Mesh1D(coordinates_min, coordinates_max, N)
 
 # create solver with periodic SBP operators of accuracy order 4
 accuracy_order = 4
-D1 = periodic_derivative_operator(1, accuracy_order, mesh.xmin, mesh.xmax, mesh.N)
-D2 = sparse(D1)^2
-solver = Solver(D1, D2)
+solver = Solver(mesh, accuracy_order)
 
 # semidiscretization holds all the necessary data structures for the spatial discretization
 semi = Semidiscretization(mesh, equations, initial_condition, solver,
-                          boundary_conditions = boundary_conditions)
+                          boundary_conditions = boundary_conditions,
+                          source_terms = source_terms)
 
 ###############################################################################
 # Create `ODEProblem` and run the simulation
-tspan = (0.0, 30.0)
+tspan = (0.0, 1.0)
 ode = semidiscretize(semi, tspan)
 analysis_callback = AnalysisCallback(semi; interval = 10,
                                      extra_analysis_errors = (:conservation_error,),

diff --git a/...bbm_variable_bathymetry_1d_widestencil.jl → ...bm_variable_bathymetry_1d_manufactured.jl b/...bbm_variable_bathymetry_1d_widestencil.jl → ...bm_variable_bathymetry_1d_manufactured.jl
@@ -1,36 +1,33 @@
 using OrdinaryDiffEq
 using DispersiveShallowWater
-using SummationByPartsOperators: periodic_derivative_operator
-using SparseArrays: sparse
 
 ###############################################################################
 # Semidiscretization of the BBM-BBM equations
 
 equations = BBMBBMVariableEquations1D(gravity_constant = 9.81)
 
-# initial_condition_convergence_test needs periodic boundary conditions
-initial_condition = initial_condition_convergence_test
+initial_condition = initial_condition_manufactured
+source_terms = source_terms_manufactured
 boundary_conditions = boundary_condition_periodic
 
 # create homogeneous mesh
-coordinates_min = -35.0
-coordinates_max = 35.0
+coordinates_min = 0.0
+coordinates_max = 1.0
 N = 512
 mesh = Mesh1D(coordinates_min, coordinates_max, N)
 
 # create solver with periodic SBP operators of accuracy order 4
 accuracy_order = 4
-D1 = periodic_derivative_operator(1, accuracy_order, mesh.xmin, mesh.xmax, mesh.N)
-D2 = sparse(D1)^2
-solver = Solver(D1, D2)
+solver = Solver(mesh, accuracy_order)
 
 # semidiscretization holds all the necessary data structures for the spatial discretization
 semi = Semidiscretization(mesh, equations, initial_condition, solver,
-                          boundary_conditions = boundary_conditions)
+                          boundary_conditions = boundary_conditions,
+                          source_terms = source_terms)
 
 ###############################################################################
 # Create `ODEProblem` and run the simulation
-tspan = (0.0, 30.0)
+tspan = (0.0, 1.0)
 ode = semidiscretize(semi, tspan)
 analysis_callback = AnalysisCallback(semi; interval = 10,
                                      extra_analysis_errors = (:conservation_error,),

diff --git a/.../bbm_bbm_variable_bathymetry_1d_upwind.jl → ...isch_1d/svaerd_kalisch_1d_manufactured.jl b/.../bbm_bbm_variable_bathymetry_1d_upwind.jl → ...isch_1d/svaerd_kalisch_1d_manufactured.jl
@@ -1,38 +1,36 @@
 using OrdinaryDiffEq
 using DispersiveShallowWater
-using SummationByPartsOperators: upwind_operators, periodic_derivative_operator
-using SparseArrays: sparse
 
 ###############################################################################
-# Semidiscretization of the BBM-BBM equations
+# Semidiscretization of the Svärd-Kalisch equations
 
-equations = BBMBBMVariableEquations1D(gravity_constant = 9.81)
+equations = SvaerdKalischEquations1D(gravity_constant = 1.0, eta0 = 0.0,
+                                     alpha = 0.0004040404040404049,
+                                     beta = 0.49292929292929294,
+                                     gamma = 0.15707070707070708)
 
-# initial_condition_convergence_test needs periodic boundary conditions
-initial_condition = initial_condition_convergence_test
+initial_condition = initial_condition_manufactured
+source_terms = source_terms_manufactured
 boundary_conditions = boundary_condition_periodic
 
 # create homogeneous mesh
-coordinates_min = -35.0
-coordinates_max = 35.0
-N = 512
+coordinates_min = 0.0
+coordinates_max = 1.0
+N = 128
 mesh = Mesh1D(coordinates_min, coordinates_max, N)
 
 # create solver with periodic SBP operators of accuracy order 4
 accuracy_order = 4
-D1 = upwind_operators(periodic_derivative_operator; derivative_order = 1,
-                      accuracy_order = accuracy_order, xmin = mesh.xmin, xmax = mesh.xmax,
-                      N = mesh.N)
-D2 = sparse(D1.plus) * sparse(D1.minus)
-solver = Solver(D1, D2)
+solver = Solver(mesh, accuracy_order)
 
 # semidiscretization holds all the necessary data structures for the spatial discretization
 semi = Semidiscretization(mesh, equations, initial_condition, solver,
-                          boundary_conditions = boundary_conditions)
+                          boundary_conditions = boundary_conditions,
+                          source_terms = source_terms)
 
 ###############################################################################
 # Create `ODEProblem` and run the simulation
-tspan = (0.0, 30.0)
+tspan = (0.0, 1.0)
 ode = semidiscretize(semi, tspan)
 analysis_callback = AnalysisCallback(semi; interval = 10,
                                      extra_analysis_errors = (:conservation_error,),

diff --git a/src/DispersiveShallowWater.jl b/src/DispersiveShallowWater.jl
@@ -24,8 +24,8 @@ import SummationByPartsOperators: grid, xmin, xmax
 
 include("boundary_conditions.jl")
 include("mesh.jl")
-include("solver.jl")
 include("equations/equations.jl")
+include("solver.jl")
 include("semidiscretization.jl")
 include("callbacks_step/callbacks_step.jl")
 include("visualization.jl")
@@ -48,7 +48,9 @@ export Semidiscretization, semidiscretize, grid
 
 export boundary_condition_periodic
 
-export initial_condition_convergence_test, initial_condition_dingemans
+export initial_condition_convergence_test,
+       initial_condition_manufactured, source_terms_manufactured,
+       initial_condition_dingemans
 
 export AnalysisCallback, RelaxationCallback
 export tstops, errors, integrals