Merge branch 'feature/example-tracer-cleanup' into 'master'

Feature/example tracer cleanup

See merge request !2513

examples/1ptracer/CMakeLists.txt

@@ -3,7 +3,6 @@ dune_symlink_to_source_files(FILES "params.input")
 dumux_add_test(NAME example_1ptracer
                LABELS porousmediumflow tracer example
                SOURCES main.cc
-               CMAKE_GUARD HAVE_UMFPACK
                COMMAND ${CMAKE_SOURCE_DIR}/bin/testing/runtest.py
                CMD_ARGS --script fuzzy
                         --files ${CMAKE_SOURCE_DIR}/test/references/test_1ptracer_transport-reference.vtu

examples/1ptracer/doc/1p.md

@@ -314,9 +314,15 @@ over the computational grid
 In this example, we use a randomly generated and element-wise distributed
 permeability field. For this, we use the random number generation facilities
 provided by the C++ standard library.
+Dumux additionally implements some simpler but
+standard-library-implementation-independent random distributions
+that are accurate enough for our purposes
+but allow to generate reproducible and portable random fields (when using a constant seed)
+for testing purposes.
 
 ```cpp
 #include <random>
+#include <dumux/common/random.hh>
 ```
 
 We include the spatial parameters class for single-phase models discretized
@@ -380,15 +386,19 @@ of 10% here and compute permeabily values for all elements of the computational
 
         // Furthermore, the position of the lens, which is defined by the position of the lower left and the upper right corners, are obtained from the input file.
         lensLowerLeft_ = getParam<GlobalPosition>("SpatialParams.LensLowerLeft");
-        lensUpperRight_ =getParam<GlobalPosition>("SpatialParams.LensUpperRight");
+        lensUpperRight_ = getParam<GlobalPosition>("SpatialParams.LensUpperRight");
 
         // We generate random fields for the permeability using lognormal distributions,
         // with `permeability_` as mean value and 10 % of it as standard deviation.
         // A separate distribution is used for the lens using `permeabilityLens_`.
         // A permeability value is created for each element of the grid and is stored in the vector `K_`.
+        // For a "truly" random field (different every time we execute) the seed `0` for the
+        // Mersenne-Twister pseudo-random-number generator should be replaced
+        // by `std::random_device{}()`. For unbiased high-quality distributions (usually not needed)
+        // replace `Dumux::SimpleLogNormalDistribution` by `std::lognormal_distribution`.
         std::mt19937 rand(0);
-        std::lognormal_distribution<Scalar> K(std::log(permeability_), std::log(permeability_)*0.1);
-        std::lognormal_distribution<Scalar> KLens(std::log(permeabilityLens_), std::log(permeabilityLens_)*0.1);
+        Dumux::SimpleLogNormalDistribution<Scalar> K(std::log(permeability_), std::log(permeability_)*0.1);
+        Dumux::SimpleLogNormalDistribution<Scalar> KLens(std::log(permeabilityLens_), std::log(permeabilityLens_)*0.1);
 
         // loop over all elements and compute a permeability value
         for (const auto& element : elements(gridGeometry->gridView()))

examples/1ptracer/doc/main.md

@@ -31,8 +31,6 @@ These are DUNE helper classes related to parallel computations, time measurement
 ```cpp
 #include <dune/common/parallel/mpihelper.hh>
 #include <dune/common/timer.hh>
-#include <dune/grid/io/file/dgfparser/dgfexception.hh>
-#include <dune/grid/io/file/vtk.hh>
 ```
 
 The following headers include functionality related to property definition or retrieval, as well as
@@ -161,7 +159,8 @@ The grid variables are used store variables (primary and secondary variables) on
 ```
 
 We now instantiate the assembler class, assemble the linear system and solve it with the linear
-solver UMFPack. Besides that, the time needed for assembly and solve is measured and printed.
+solver ILUnBiCGSTABBackend (a bi-conjugate gradient solver preconditioned by an incomplete LU-factorization preconditioner).
+Besides that, the time needed for assembly and solve is measured and printed.
 
 ```cpp
     using OnePAssembler = FVAssembler<OnePTypeTag, DiffMethod::analytic>;
@@ -175,7 +174,7 @@ solver UMFPack. Besides that, the time needed for assembly and solve is measured
 
     (*r) *= -1.0; // We want to solve `Ax = -r`.
 
-    using LinearSolver = UMFPackBackend;
+    using LinearSolver = ILUnBiCGSTABBackend;
     Dune::Timer solverTimer; std::cout << "Solving linear system ..." << std::flush;
     auto linearSolver = std::make_shared<LinearSolver>();
     linearSolver->solve(*A, p, *r);

examples/1ptracer/main.cc

@@ -31,8 +31,6 @@
 // These are DUNE helper classes related to parallel computations, time measurements and file I/O
 #include <dune/common/parallel/mpihelper.hh>
 #include <dune/common/timer.hh>
-#include <dune/grid/io/file/dgfparser/dgfexception.hh>
-#include <dune/grid/io/file/vtk.hh>
 
 // The following headers include functionality related to property definition or retrieval, as well as
 // the retrieval of input parameters specified in the input file or via the command line.
@@ -127,7 +125,8 @@ int main(int argc, char** argv) try
     onePGridVariables->init(p);
 
     // We now instantiate the assembler class, assemble the linear system and solve it with the linear
-    // solver UMFPack. Besides that, the time needed for assembly and solve is measured and printed.
+    // solver ILUnBiCGSTABBackend (a bi-conjugate gradient solver preconditioned by an incomplete LU-factorization preconditioner).
+    // Besides that, the time needed for assembly and solve is measured and printed.
     using OnePAssembler = FVAssembler<OnePTypeTag, DiffMethod::analytic>;
     auto assemblerOneP = std::make_shared<OnePAssembler>(problemOneP, gridGeometry, onePGridVariables);
     assemblerOneP->setLinearSystem(A, r); // tell assembler to use our previously defined system
@@ -139,7 +138,7 @@ int main(int argc, char** argv) try
 
     (*r) *= -1.0; // We want to solve `Ax = -r`.
 
-    using LinearSolver = UMFPackBackend;
+    using LinearSolver = ILUnBiCGSTABBackend;
     Dune::Timer solverTimer; std::cout << "Solving linear system ..." << std::flush;
     auto linearSolver = std::make_shared<LinearSolver>();
     linearSolver->solve(*A, p, *r);