[example][1ptracer] Update doc after changing the random distribution

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()))