improve examples

Author: PierreMarchand20

examples/compression_comparison.sh

@@ -11,13 +11,13 @@ make Compression_comparison
 mkdir -p ../output/examples/compression_comparison
 
 # Arguments
-outputpath=../output/examples/compression_comparison/
+outputfolder=../output/examples/compression_comparison/
 distances=(1 2 3)
 
 # Run
 for distance in "${distances[@]}"
 do
-    ./examples/compression_comparison ${distance} compression_comparison_${distance}.csv ${outputpath}
+    ./examples/compression_comparison ${distance} compression_comparison_${distance}.csv ${outputfolder}
 done
 
 

examples/use_clustering.cpp

@@ -9,15 +9,15 @@ using namespace htool;
 int main(int argc, char *argv[]) {
 
     // Check the number of parameters
-    if (argc != 2) {
+    if (argc > 2) {
         // Tell the user how to run the program
-        cerr << "Usage: " << argv[0] << "  outputname" << endl;
+        cerr << "Usage: " << argv[0] << "  output_folder" << endl;
         /* "Usage messages" are a conventional way of telling the user
          * how to run a program if they enter the command incorrectly.
          */
         return 1;
     }
-    std::string outputname = argv[1];
+    std::string output_folder = argc == 2 ? argv[1] : "./";
 
     // Geometry
     const int number_points        = 10000;
@@ -30,13 +30,13 @@ int main(int argc, char *argv[]) {
     // Cluster tree builder with customization
     ClusterTreeBuilder<double> recursive_build_strategy;
     recursive_build_strategy.set_maximal_leaf_size(10);
-    recursive_build_strategy.set_partitioning_strategy(std::make_shared<Partitioning<double, ComputeLargestExtent<double>, RegularSplitting<double>>>()); // this is actually the default choice
+    recursive_build_strategy.set_partitioning_strategy(std::make_shared<Partitioning_N<double, ComputeLargestExtent<double>, RegularSplitting<double>>>());
 
     // Clustering
     Cluster<double> cluster = recursive_build_strategy.create_cluster_tree(number_points, spatial_dimension, coordinates.data(), number_of_children, number_of_partitions);
 
     // Output
-    save_clustered_geometry(cluster, spatial_dimension, coordinates.data(), outputname + "/clustering_output", {1, 2, 3});
+    save_clustered_geometry(cluster, spatial_dimension, coordinates.data(), output_folder + "/clustering_output", {1, 2, 3});
 
     return 0;
 }

examples/use_clustering.sh

@@ -11,10 +11,10 @@ make Use_clustering
 mkdir -p ../output/examples/use_clustering
 
 # Arguments
-outputpath=../output/examples/use_clustering/
+outputfolder=../output/examples/use_clustering/
 
 # Run
-./examples/Use_clustering ${outputpath}
+./examples/Use_clustering ${outputfolder}
 
 # Display output
 python3 ../tools/plot_cluster.py --inputfile ../output/examples/use_clustering/clustering_output.csv --depth 2

examples/use_ddm_solver.sh

@@ -10,8 +10,5 @@ cmake ../
 make Use_ddm_solver
 mkdir -p ../output/examples/use_ddm_solver
 
-# Arguments
-outputpath=../output/examples/use_ddm_solver/
-
 # Run
-mpirun -np 4 ./examples/Use_ddm_solver ${outputpath}
+mpirun -np 4 ./examples/Use_ddm_solver

examples/use_distributed_operator.cpp

@@ -64,28 +64,29 @@ int main(int argc, char *argv[]) {
     MPI_Comm_size(MPI_COMM_WORLD, &sizeWorld);
 
     // Check the number of parameters
-    if (argc != 2) {
+    if (argc > 2) {
         // Tell the user how to run the program
-        cerr << "Usage: " << argv[0] << " outputpath" << endl;
+        cerr << "Usage: " << argv[0] << " output_folder" << endl;
         /* "Usage messages" are a conventional way of telling the user
          * how to run a program if they enter the command incorrectly.
          */
         return 1;
     }
 
-    std::string outputpath = argv[1];
+    std::string output_folder = argc == 2 ? argv[1] : "./";
 
     // Geometry
     const int number_points        = 10000;
     const int spatial_dimension    = 3;
     const int number_of_partitions = sizeWorld;
     const int number_of_children   = 8;
     vector<double> coordinates(spatial_dimension * number_points);
-    create_sphere(number_points, coordinates.data());
+    create_rotated_ellipse(3, 4., 1., 0., 0., number_points, coordinates.data()); // 2d ellipse in 3d
 
     // Clustering
     ClusterTreeBuilder<double> recursive_build_strategy;
     recursive_build_strategy.set_maximal_leaf_size(100);
+    recursive_build_strategy.set_partitioning_strategy(std::make_shared<Partitioning_N<double, ComputeLargestExtent<double>, RegularSplitting<double>>>()); // this is actually the default choice
     Cluster<double> cluster = recursive_build_strategy.create_cluster_tree(number_points, spatial_dimension, coordinates.data(), number_of_children, number_of_partitions);
 
     // HMatrix parameters
@@ -122,7 +123,7 @@ int main(int argc, char *argv[]) {
         std::cout << "Information about hmatrices accross all processors\n";
     }
     print_distributed_hmatrix_information(local_hmatrix, std::cout, MPI_COMM_WORLD);
-    save_leaves_with_rank(local_hmatrix, outputpath + "/local_hmatrix_" + std::to_string(rankWorld));
+    save_leaves_with_rank(local_hmatrix, output_folder + "/local_hmatrix_" + std::to_string(rankWorld));
 
     // Finalize the MPI environment.
     MPI_Finalize();

examples/use_distributed_operator.sh

@@ -11,10 +11,10 @@ make Use_distributed_operator
 mkdir -p ../output/examples/use_distributed_operator
 
 # Arguments
-outputpath=../output/examples/use_distributed_operator/
+outputfolder=../output/examples/use_distributed_operator/
 
 # Run
-mpirun -np 4 ./examples/Use_distributed_operator ${outputpath}
+mpirun -np 4 ./examples/Use_distributed_operator ${outputfolder}
 
 # Display output
 python3 ../tools/plot_hmatrix.py --inputfile ../output/examples/use_distributed_operator/local_hmatrix_0.csv

examples/use_hmatrix.cpp

@@ -59,16 +59,16 @@ class UserOperator : public VirtualGenerator<double> {
 int main(int argc, char *argv[]) {
 
     // Check the number of parameters
-    if (argc != 2) {
+    if (argc > 2) {
         // Tell the user how to run the program
-        cerr << "Usage: " << argv[0] << " outputpath" << endl;
+        cerr << "Usage: " << argv[0] << " output_folder" << endl;
         /* "Usage messages" are a conventional way of telling the user
          * how to run a program if they enter the command incorrectly.
          */
         return 1;
     }
 
-    std::string outputpath = argv[1];
+    std::string output_folder = argc == 2 ? argv[1] : "./";
 
     // Execution policy
     auto &policy = exec_compat::par;
@@ -77,15 +77,16 @@ int main(int argc, char *argv[]) {
     const int number_points     = 10000;
     const int spatial_dimension = 3;
     vector<double> coordinates(spatial_dimension * number_points);
-    create_sphere(number_points, coordinates.data());
+    create_rotated_ellipse(3, 4., 1., 0., 0., number_points, coordinates.data()); // 2d ellipse in 3d
 
     // Cluster tree builder
     ClusterTreeBuilder<double> recursive_build_strategy;
     recursive_build_strategy.set_maximal_leaf_size(500);
+    recursive_build_strategy.set_partitioning_strategy(std::make_shared<Partitioning_N<double, ComputeLargestExtent<double>, RegularSplitting<double>>>());
 
     // HMatrix parameters
     const double epsilon = 0.01;
-    const double eta     = 10;
+    const double eta     = 200;
     char symmetry        = 'S';
     char UPLO            = 'L';
 
@@ -97,18 +98,18 @@ int main(int argc, char *argv[]) {
     HMatrix<double> hmatrix = hmatrix_builder.build(policy, A, htool::HMatrixTreeBuilder<double>(epsilon, eta, symmetry, UPLO));
 
     // Output
-    // save_leaves_with_rank(hmatrix, outputpath + "hmatrix");
+    save_leaves_with_rank(hmatrix, output_folder + "/hmatrix");
     print_tree_parameters(hmatrix, std::cout);
     print_hmatrix_information(hmatrix, std::cout);
 
-    // sequential y= A*x
+    // y= A*x
     std::vector<double> x(number_points, 1), y(number_points, 0), ref(number_points, 0);
     add_hmatrix_vector_product(policy, 'N', double(1), hmatrix, x.data(), double(0), y.data());
     ref = A * x;
     std::cout << "relative error on matrix vector product : ";
     std::cout << norm2(ref - y) / norm2(ref) << "\n";
 
-    // sequential z = A^-1 y
+    // z = A^-1 y
     std::vector<double> z(number_points, 0);
     z = y;
     MatrixView<double> z_view(number_points, 1, z.data());

examples/use_hmatrix.sh

@@ -11,10 +11,10 @@ make Use_hmatrix
 mkdir -p ../output/examples/use_hmatrix
 
 # Arguments
-outputpath=../output/examples/use_hmatrix/
+outputfolder=../output/examples/use_hmatrix/
 
 # Run
-./examples/Use_hmatrix ${outputpath}
+./examples/Use_hmatrix ${outputfolder}
 
 # Display output
 python3 ../tools/plot_hmatrix.py --inputfile ../output/examples/use_hmatrix/hmatrix.csv