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New interface for sampling. Function is parameterized by walk and dis…
…tribution. Added support for basic uniform samplers.
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| project( VolEsti-cpp-example ) | ||
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| CMAKE_MINIMUM_REQUIRED(VERSION 3.11) | ||
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| add_definitions(-DDISABLE_NLP_ORACLES) | ||
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| include("../../external/cmake-files/Eigen.cmake") | ||
| GetEigen() | ||
| if (${CMAKE_VERSION} VERSION_LESS "3.12.0") | ||
| add_compile_options(-D "EIGEN_NO_DEBUG") | ||
| else () | ||
| add_compile_definitions("EIGEN_NO_DEBUG") | ||
| endif () | ||
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| include("../../external/cmake-files/Boost.cmake") | ||
| GetBoost() | ||
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| include("../../external/cmake-files/LPSolve.cmake") | ||
| GetLPSolve() | ||
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| set(CMAKE_EXPORT_COMPILE_COMMANDS "ON") | ||
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| add_definitions(${CMAKE_CXX_FLAGS} "-g") | ||
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| include_directories (BEFORE ../../external) | ||
| include_directories (BEFORE ../../include) | ||
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| add_executable (example simple_example.cpp) | ||
| target_link_libraries(example PUBLIC lp_solve) |
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| #include "Eigen/Eigen" | ||
| #include "cartesian_geom/cartesian_kernel.h" | ||
| #include "convex_bodies/hpolytope.h" | ||
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| #include "diagnostics/diagnostics.hpp" | ||
| //todo make headers automomous | ||
| //#include "diagnostics/effective_sample_size.hpp" | ||
| //#include "diagnostics/print_diagnostics.hpp" | ||
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| #include "generators/known_polytope_generators.h" | ||
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| #include "random_walks/random_walks.hpp" | ||
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| #include "sampling/sample_points.hpp" | ||
| #include "sampling/sampling.hpp" | ||
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| #include "volume/volume_cooling_balls.hpp" | ||
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| typedef Cartesian<double> Kernel; | ||
| typedef typename Kernel::Point Point; | ||
| typedef BoostRandomNumberGenerator<boost::mt19937, double> RNGType; | ||
| typedef HPolytope<Point> HPolytopeType; | ||
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| template <typename Walk, typename Distribution> | ||
| void sample_points_eigen_matrix(HPolytopeType const& HP, Point const& q, Walk const& walk, | ||
| Distribution const& distr, RNGType rng, int walk_len, int rnum, | ||
| int nburns) | ||
| { | ||
| using NT = double; | ||
| using MT = Eigen::Matrix<NT,Eigen::Dynamic,Eigen::Dynamic>; | ||
| using VT = Eigen::Matrix<NT,Eigen::Dynamic,1>; | ||
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| MT samples(HP.dimension(), rnum); | ||
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| sample_points(HP, q, walk, distr, rng, walk_len, rnum, nburns, samples); | ||
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| // sample stats | ||
| unsigned int min_ess; | ||
| auto score = effective_sample_size<NT, VT, MT>(samples, min_ess); | ||
| std::cout << "ess=" << min_ess << std::endl; | ||
| //print_diagnostics<NT, VT, MT>(samples, min_ess, std::cerr); | ||
| } | ||
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| int main() { | ||
| // Generating a 3-dimensional cube centered at origin | ||
| HPolytopeType HP = generate_cube<HPolytopeType>(10, false); | ||
| std::cout<<"Polytope: \n"; | ||
| HP.ComputeInnerBall(); | ||
| //HP.print(); | ||
| //std::cout<<"\n"; | ||
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| // Setup parameters for sampling | ||
| Point q(HP.dimension()); | ||
| RNGType rng(HP.dimension()); | ||
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| // NEW INTERFACE Sampling | ||
| AcceleratedBilliardWalk abill_walk; | ||
| AcceleratedBilliardWalk abill_walk_custom(10); //user defined walk parameters | ||
| BallWalk ball_walk; | ||
| BilliardWalk bill_walk; | ||
| CDHRWalk cdhr_walk; | ||
| DikinWalk dikin_walk; | ||
| JohnWalk john_walk; | ||
| RDHRWalk rdhr_walk; | ||
| VaidyaWalk vaidya_walk; | ||
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| GaussianBallWalk gball_walk; | ||
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| UniformDistribution udistr{}; | ||
| GaussianDistribution gdistr{}; | ||
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| using NT = double; | ||
| using MT = Eigen::Matrix<NT,Eigen::Dynamic,Eigen::Dynamic>; | ||
| using VT = Eigen::Matrix<NT,Eigen::Dynamic,1>; | ||
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| int rnum = 100; | ||
| int nburns = 50; | ||
| int walk_len = 10; | ||
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| MT samples(HP.dimension(), rnum); | ||
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| // 1. the eigen matrix interface | ||
| sample_points_eigen_matrix(HP, q, abill_walk, udistr, rng, walk_len, rnum, nburns); | ||
| sample_points_eigen_matrix(HP, q, abill_walk_custom, udistr, rng, walk_len, rnum, nburns); | ||
| sample_points_eigen_matrix(HP, q, ball_walk, udistr, rng, walk_len, rnum, nburns); | ||
| sample_points_eigen_matrix(HP, q, cdhr_walk, udistr, rng, walk_len, rnum, nburns); | ||
| sample_points_eigen_matrix(HP, q, dikin_walk, udistr, rng, walk_len, rnum, nburns); | ||
| sample_points_eigen_matrix(HP, q, john_walk, udistr, rng, walk_len, rnum, nburns); | ||
| sample_points_eigen_matrix(HP, q, rdhr_walk, udistr, rng, walk_len, rnum, nburns); | ||
| sample_points_eigen_matrix(HP, q, vaidya_walk, udistr, rng, walk_len, rnum, nburns); | ||
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| // TODO: fix | ||
| // Does not converge because of the starting point | ||
| // Also ess returns rnum instead of 0 | ||
| sample_points_eigen_matrix(HP, q, bill_walk, udistr, rng, walk_len, rnum, nburns); | ||
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| // Does not compile because of walk-distribution combination | ||
| //sample_points_eigen_matrix(HP, q, abill_walk, gdistr, rng, walk_len, rnum, nburns); | ||
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| // 2. the std::vector interface | ||
| std::vector<Point> points; | ||
| sample_points(HP, q, cdhr_walk, udistr, rng, walk_len, rnum, nburns, points); | ||
| for (auto& point : points) | ||
| { | ||
| // std::cout << point.getCoefficients().transpose() << "\n"; | ||
| } | ||
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| // 3. the old interface | ||
| // different billiard walks | ||
| typedef BilliardWalk::template Walk<HPolytopeType, RNGType> BilliardWalkType; | ||
| typedef AcceleratedBilliardWalk::template Walk<HPolytopeType, RNGType> AcceleratedBilliardWalkType; | ||
| typedef RandomPointGenerator<AcceleratedBilliardWalkType> Generator; | ||
| std::vector<Point> randPoints; | ||
| PushBackWalkPolicy push_back_policy; | ||
| Generator::apply(HP, q, rnum, walk_len, randPoints, push_back_policy, rng); | ||
| for (auto& point : randPoints) | ||
| { | ||
| // std::cout << point.getCoefficients().transpose() << "\n"; | ||
| } | ||
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| /* | ||
| unsigned int walkL = 10, numpoints = 10000, nburns = 0, d = HP.dimension(); | ||
| Point StartingPoint(d); | ||
| std::list<Point> randPoints; | ||
| // gaussian_sampling<AcceleratedBilliardWalk>(points, HP, rng, walkL, numpoints, 1.0, | ||
| // StartingPoint, nburns); | ||
| double variance = 1.0; | ||
| Point c(HP.dimension()); | ||
| HP.set_InnerBall(std::pair<Point,double>(Point(HP.dimension()), 1.0)); | ||
| c = GetDirection<Point>::apply(HP.dimension(), rng, false); | ||
| //ExponentialHamiltonianMonteCarloExactWalk | ||
| exponential_sampling<NutsHamiltonianMonteCarloWalk>(points, HP, rng, walkL, numpoints, c, variance, | ||
| StartingPoint, nburns); | ||
| */ | ||
| return 0; | ||
| } |
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