Move mmcs functionality to include from examples

examples/mmcs_method/CMakeLists.txt

@@ -108,13 +108,11 @@ else ()
 
   find_package(OpenMP REQUIRED)
 
-  add_executable (skinny_cube_10_dim skinny_cube_10_dim.cpp)
-  add_executable (random_hpoly_50_dim random_hpoly_50_dim.cpp)
-  add_executable (random_hpoly_50_dim_parallel random_hpoly_50_dim_parallel.cpp)
-
-  TARGET_LINK_LIBRARIES(skinny_cube_10_dim ${LP_SOLVE})
-  TARGET_LINK_LIBRARIES(random_hpoly_50_dim ${LP_SOLVE})
-  TARGET_LINK_LIBRARIES(random_hpoly_50_dim_parallel ${LP_SOLVE} OpenMP::OpenMP_CXX)
+  add_executable (simple simple.cpp)
+  add_executable (parallel parallel.cpp)
 
+  TARGET_LINK_LIBRARIES(simple ${LP_SOLVE})
+  TARGET_LINK_LIBRARIES(parallel ${LP_SOLVE})
+  TARGET_LINK_LIBRARIES(parallel ${LP_SOLVE} OpenMP::OpenMP_CXX)
 
 endif()

examples/mmcs_method/simple.cpp

@@ -0,0 +1,63 @@
+// VolEsti (volume computation and sampling library)
+
+// Copyright (c) 2012-2021 Vissarion Fisikopoulos
+// Copyright (c) 2018-2021 Apostolos Chalkis
+
+#include "Eigen/Eigen"
+
+#include <chrono>
+#include <boost/random.hpp>
+#include <boost/random/uniform_int.hpp>
+#include <boost/random/normal_distribution.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "random_walks/random_walks.hpp"
+#include "volume/volume_sequence_of_balls.hpp"
+#include "volume/volume_cooling_gaussians.hpp"
+#include "sampling/mmcs.hpp"
+#include "generators/h_polytopes_generator.h"
+#include "generators/known_polytope_generators.h"
+#include "diagnostics/multivariate_psrf.hpp"
+#include "diagnostics/univariate_psrf.hpp"
+#include "diagnostics/ess_window_updater.hpp"
+
+
+template <typename NT>
+void run_main()
+{
+    typedef Cartesian<NT> Kernel;
+    typedef boost::mt19937 PolyRNGType;
+    typedef typename Kernel::Point Point;
+    typedef HPolytope <Point> Hpolytope;
+    typedef Eigen::Matrix<NT,Eigen::Dynamic,1> VT;
+    typedef Eigen::Matrix<NT,Eigen::Dynamic,Eigen::Dynamic> MT;
+
+    {
+        int n = 50;
+        Hpolytope P = random_hpoly<Hpolytope, PolyRNGType>(n, 4*n, 127); // we fix the example polytope, seed = 127
+
+        MT S;
+        int total_neff;
+        mmcs(P, 400, S, total_neff);
+
+        std::cerr << "sum of effective sample sizes: " << total_neff << std::endl;
+        std::cerr << "multivariate PSRF: " <<  multivariate_psrf<NT, VT>(S) << std::endl;
+        std::cerr << "maximum marginal PSRF: " <<  univariate_psrf<NT, VT>(S).maxCoeff() << std::endl;
+    }
+    {
+        int n = 10;
+        Hpolytope P = generate_skinny_cube<Hpolytope>(n, false);
+
+        MT S;
+        int total_neff;
+        mmcs(P, 1000, S, total_neff);
+
+        std::cerr << "sum of effective sample sizes: " << total_neff << std::endl;
+        std::cerr << "multivariate PSRF: " <<  multivariate_psrf<NT, VT>(S) << std::endl;
+        std::cerr << "maximum marginal PSRF: " <<  univariate_psrf<NT, VT>(S).maxCoeff() << std::endl;
+    }
+}
+
+int main() {
+  run_main<double>();
+  return 0;
+}