initial commit

Author: miguelmaso

deps/build.jl

@@ -40,6 +40,7 @@ for (i,(title,filename)) in enumerate(files)
   notebook = string(notebook_prefix,splitext(filename)[1])
   notebook_title = string("# # Tutorial ", i, ": ", title)
   function preprocess_notebook(content)
+    content = replace(content, "output_path" => notebook_prefix)
     return string(notebook_title, "\n\n", content)
   end
   Literate.notebook(joinpath(repo_src,filename), notebooks_dir; name=notebook, preprocess=preprocess_notebook, documenter=false, execute=false)

src/poisson.jl

@@ -54,7 +54,8 @@ model = DiscreteModelFromFile("../models/model.json")
 #
 # You can easily inspect the generated discrete model in [Paraview](https://www.paraview.org/) by writing it in `vtk` format.
 
-writevtk(model,"model")
+mkdir("output_path")
+writevtk(model,"output_path/model")
 
 # The previous line generates four different files `model_0.vtu`, `model_1.vtu`, `model_2.vtu`, and `model_3.vtu` containing the vertices, edges, faces, and cells present in the discrete model. Moreover, you can easily inspect which boundaries are defined within the model.
 #
@@ -137,7 +138,7 @@ uh = solve(solver,op)
 
 # The `solve` function returns the computed numerical solution `uh`. This object is an instance of `FEFunction`, the type used to represent a function in a FE space. We can inspect the result by writing it into a `vtk` file:
 
-writevtk(Ω,"results",cellfields=["uh"=>uh])
+writevtk(Ω,"output_path/results",cellfields=["uh"=>uh])
 
 #  which will generate a file named `results.vtu` having a nodal field named `"uh"` containing the solution of our problem (see next figure).
 #

src/transient_linear.jl

@@ -108,14 +108,12 @@ uh = solve(solver, op, t0, tF, uh0)
 
 # We highlight that `uh` is an iterable function and the result at each time step is only computed lazily when iterating over it. We can post-process the results and generate the corresponding `vtk` files using the `createpvd` and `createvtk` functions. The former will create a `.pvd` file with the collection of `.vtu` files saved at each time step by `createvtk`. The computation of the problem solutions will be triggered in the following loop:
 
-if !isdir("tmp")
-  mkdir("tmp")
-end
+mkpath("output_path/results")
 
-createpvd("results") do pvd
-  pvd[0] = createvtk(Ω, "tmp/results_0" * ".vtu", cellfields=["u" => uh0])
+createpvd("output_path/results") do pvd
+  pvd[0] = createvtk(Ω, "output_path/results/results_0" * ".vtu", cellfields=["u" => uh0])
   for (tn, uhn) in uh
-    pvd[tn] = createvtk(Ω, "tmp/results_$tn" * ".vtu", cellfields=["u" => uhn])
+    pvd[tn] = createvtk(Ω, "output_path/results/results_$tn" * ".vtu", cellfields=["u" => uhn])
   end
 end
 

src/validation.jl

@@ -66,7 +66,8 @@ model3d = CartesianDiscreteModel(domain3d,partition3d)
 
 # Let us return to the 2D `CartesianDiscreteModel` that we have already constructed. You can inspect it by writing it into vtk format. Note that you can also print a 3D model, but not a 4D one. In the future, it would be cool to generate a movie from a 4D model, but this functionality is not yet implemented.
 
-writevtk(model,"model")
+mkdir("output_path")
+writevtk(model,"output_path/model")
 
 
 # If you open the generated files, you will see that the boundary vertices and facets are identified with the name "boundary". This is just what we need to impose the Dirichlet boundary conditions in this example.
@@ -113,7 +114,7 @@ e = u - uh
 
 # Once the error is defined, you can, e.g., visualize it.
 
-writevtk(Ω,"error",cellfields=["e" => e])
+writevtk(Ω,"output_path/error",cellfields=["e" => e])
 
 # This generates a file called `error.vtu`. Open it with Paraview to check that the error is of the order of the machine precision.
 #