diff --git a/src/pcms/point_search.h b/src/pcms/point_search.h index ab7a5554..f43c4241 100644 --- a/src/pcms/point_search.h +++ b/src/pcms/point_search.h @@ -16,6 +16,135 @@ namespace pcms // this function is in the public header for testing, but should not be directly // used namespace detail { + +/** + * Check if a point is within a radial cutoff distance of an axis-aligned bounding box (AABB). + * + * Used to quickly reject boxes that are too far from the point during neighbor search. + */ +template +KOKKOS_INLINE_FUNCTION +bool radial_intersects_bbox(const double pt[dim], const AABBox& bbox, double cutoff_squared) +{ + double d_min = 0.0; // Accumulates squared distance from point to box (only in directions where point is outside the box) + for (unsigned d = 0; d < dim; ++d) { + double dist = fabs(pt[d] - bbox.center[d]); // Distance from point to box center along axis d + double excess = dist - bbox.half_width[d]; // How far point lies outside the box in this axis + if (excess > 0.0) { + d_min += excess * excess; // Add squared excess if point is outside box in this axis + if (d_min > cutoff_squared) return false; + } + } + return true; +} + +template +struct GridRadialNeighborFunctor { + Kokkos::View target_points; + Kokkos::View source_points; + Kokkos::View[1]> grid; + Kokkos::View cell_ptrs; + Kokkos::View cell_indices; + Kokkos::View cell_size; + double cutoff; + double cutoff_squared; + LO num_cells; + + KOKKOS_FUNCTION + GridRadialNeighborFunctor( + Kokkos::View tgt_pts, + Kokkos::View src_pts, + Kokkos::View[1]> grid_in, + Kokkos::View cell_ptrs_in, + Kokkos::View cell_indices_in, + double cutoff_in, + LO num_cells_in, + Kokkos::View cell_size_in) + : target_points(tgt_pts), + source_points(src_pts), + grid(grid_in), + cell_ptrs(cell_ptrs_in), + cell_indices(cell_indices_in), + cell_size(cell_size_in), + cutoff(cutoff_in), + cutoff_squared(cutoff_in * cutoff_in), + num_cells(num_cells_in) {} + + KOKKOS_INLINE_FUNCTION + LO operator()(LO target_idx, LO* fill) const { + double pt[dim]; + for (int d = 0; d < dim; ++d) + pt[d] = target_points(target_idx, d); + + LO count = 0; + const auto& grid_obj = grid(0); + + // Compute min/max grid indices around the cutoff + int min_idx[dim], max_idx[dim]; + for (int d = 0; d < dim; ++d) { + const double min_coord = pt[d] - cutoff; + const double max_coord = pt[d] + cutoff; + + min_idx[d] = static_cast((min_coord - grid_obj.bot_left[d]) / cell_size(d)); + min_idx[d] = (min_idx[d] < 0) ? 0 : (min_idx[d] >= grid_obj.divisions[d]) ? grid_obj.divisions[d] - 1 : min_idx[d]; + + max_idx[d] = static_cast((max_coord - grid_obj.bot_left[d]) / cell_size(d)); + max_idx[d] = (max_idx[d] < 0) ? 0 : (max_idx[d] >= grid_obj.divisions[d]) ? grid_obj.divisions[d] - 1 : max_idx[d]; + } + + // Iterate over intersecting grid cells + if constexpr (dim == 3) { + for (int z = min_idx[2]; z <= max_idx[2]; ++z) + for (int y = min_idx[1]; y <= max_idx[1]; ++y) + for (int x = min_idx[0]; x <= max_idx[0]; ++x) + process_cell(x, y, z, pt, count, fill); + } else if constexpr (dim == 2) { + for (int y = min_idx[1]; y <= max_idx[1]; ++y) + for (int x = min_idx[0]; x <= max_idx[0]; ++x) + process_cell(x, y, 0, pt, count, fill); + } else { + for (int x = min_idx[0]; x <= max_idx[0]; ++x) + process_cell(x, 0, 0, pt, count, fill); + } + + return count; + } + +private: + KOKKOS_INLINE_FUNCTION + void process_cell(int x, int y, int z, const double pt[dim], LO& count, LO* fill) const { + const auto& grid_obj = grid(0); + LO cell_id; + + if constexpr (dim == 3) { + cell_id = z * (grid_obj.divisions[0] * grid_obj.divisions[1]) + y * grid_obj.divisions[0] + x; + } else if constexpr (dim == 2) { + cell_id = y * grid_obj.divisions[0] + x; + } else { + cell_id = x; + } + + if (cell_id >= num_cells || cell_ptrs[cell_id] == cell_ptrs[cell_id + 1]) return; + + const auto bbox = grid_obj.GetCellBBOX(cell_id); + if (!radial_intersects_bbox(pt, bbox, cutoff_squared)) return; + + for (LO i = cell_ptrs[cell_id]; i < cell_ptrs[cell_id + 1]; ++i) { + const LO src_idx = cell_indices[i]; + double r2 = 0.0; + for (int d = 0; d < dim; ++d) { + double diff = pt[d] - source_points(src_idx, d); + r2 += diff * diff; + if (r2 > cutoff_squared) break; + } + if (r2 <= cutoff_squared) { + if (fill) fill[count] = src_idx; + ++count; + } + } + } +}; + Kokkos::Crs construct_intersection_map(Omega_h::Mesh& mesh, Kokkos::View grid, int num_grid_cells); } diff --git a/test/CMakeLists.txt b/test/CMakeLists.txt index 27b0a3c0..81404843 100644 --- a/test/CMakeLists.txt +++ b/test/CMakeLists.txt @@ -104,14 +104,15 @@ if(Catch2_FOUND) add_executable(field_transfer_example field_transfer_example.cpp) target_link_libraries(field_transfer_example PUBLIC pcms::core pcms_interpolator) list(APPEND PCMS_UNIT_TEST_SOURCES - test_field_transfer.cpp - test_uniform_grid.cpp - test_omega_h_copy.cpp - test_point_search.cpp - test_mls_basis.cpp - test_rbf_interp.cpp - test_normalisation.cpp - test_svd_serial.cpp) + test_field_transfer.cpp + test_uniform_grid.cpp + test_omega_h_copy.cpp + test_point_search.cpp + test_mls_basis.cpp + test_rbf_interp.cpp + test_normalisation.cpp + test_svd_serial.cpp + point_to_mesh_mls.cpp) endif () add_executable(unit_tests ${PCMS_UNIT_TEST_SOURCES}) target_link_libraries(unit_tests PUBLIC Catch2::Catch2 pcms::core pcms_interpolator) diff --git a/test/data/BOUT.dmp.bp/data.0 b/test/data/BOUT.dmp.bp/data.0 new file mode 100644 index 00000000..74089f48 Binary files /dev/null and b/test/data/BOUT.dmp.bp/data.0 differ diff --git a/test/data/BOUT.dmp.bp/md.0 b/test/data/BOUT.dmp.bp/md.0 new file mode 100644 index 00000000..c9581f70 Binary files /dev/null and b/test/data/BOUT.dmp.bp/md.0 differ diff --git a/test/data/BOUT.dmp.bp/md.idx b/test/data/BOUT.dmp.bp/md.idx new file mode 100644 index 00000000..5ec30343 Binary files /dev/null and b/test/data/BOUT.dmp.bp/md.idx differ diff --git a/test/data/BOUT.dmp.bp/mmd.0 b/test/data/BOUT.dmp.bp/mmd.0 new file mode 100644 index 00000000..5f454f71 Binary files /dev/null and b/test/data/BOUT.dmp.bp/mmd.0 differ diff --git a/test/data/BOUT.dmp.bp/profiling.json b/test/data/BOUT.dmp.bp/profiling.json new file mode 100644 index 00000000..d05b6a63 --- /dev/null +++ b/test/data/BOUT.dmp.bp/profiling.json @@ -0,0 +1,3 @@ +[ +{ "rank":0, "start":"Tue_Jan_14_16:14:23_2025", "ES":{"mus":5021, "nCalls":3}, "ES_meta1":{"mus":115, "nCalls":3}, "ES_meta2":{"mus":448, "nCalls":3}, "ES_close":{"mus":2295, "nCalls":3}, "ES_AWD":{"mus":2151, "nCalls":3}, "transport_0":{"type":"File_POSIX", "wbytes":3040000, "close":{"mus":19698, "nCalls":1}, "open":{"mus":109, "nCalls":1}, "write":{"mus":1631, "nCalls":3}}, "transport_1":{"type":"File_POSIX", "wbytes":56144, "close":{"mus":88, "nCalls":1}, "open":{"mus":106, "nCalls":1}, "write":{"mus":166, "nCalls":13}} } +] diff --git a/test/data/source_points.txt b/test/data/source_points.txt new file mode 100644 index 00000000..9338e586 --- /dev/null +++ b/test/data/source_points.txt 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0.289071 +2.04286 0.185714 0.42 0.340379 +2.04286 0.185714 0.48 0.462405 +2.04286 0.185714 0.6 0.753012 +2.04286 0.185714 0.54 0.613051 +2.22857 0.185714 0.6 0.582668 +2.22857 0.185714 0.54 0.403028 +2.22857 0 0.54 0.559112 +2.22857 0 0.6 0.67282 +2.04286 0 0.6 0.74744 +2.04286 0 0.54 0.694015 +2.04286 0 0.42 0.352869 +2.04286 0 0.48 0.549725 +2.04286 0 0.36 0.197103 +2.22857 0 0.42 0.072499 +2.22857 0 0.48 0.30962 +2.22857 0 0.36 -0.0345593 +2.22857 0 0.3 0.0473764 +2.22857 0 0.18 0.767278 +2.22857 0 0.24 0.362403 +2.04286 0 0.3 0.221168 +2.04286 0 0.24 0.471999 +2.04286 0 0.18 0.807039 +2.04286 0.185714 0.3 0.365909 +2.04286 0.185714 0.18 0.777653 +2.04286 0.185714 0.24 0.558662 +2.22857 0.185714 0.3 0.173638 +2.22857 0.185714 0.24 0.442464 +2.22857 0.185714 0.18 0.732431 +2.22857 0.185714 0.12 0.902903 +2.22857 0.185714 0 1.00665 +2.22857 0.185714 0.06 0.960557 +2.04286 0.185714 0.12 0.921208 +2.04286 0.185714 0 1.0061 +2.04286 0.185714 0.06 0.978401 +2.04286 0 0.12 1.01623 +2.04286 0 0 0.990435 +2.04286 0 0.06 1.04426 +2.22857 0 0.12 1.00987 +2.22857 0 0 0.990349 +2.22857 0 0.06 1.03603 +2.41429 0 0.06 0.892596 +2.41429 0 0 0.969631 +2.41429 0 0.12 0.88033 +2.41429 0 0.3 0.0429019 +2.41429 0 0.24 0.349251 +2.41429 0 0.18 0.705801 +2.41429 0.185714 0.3 0.11011 +2.41429 0.185714 0.24 0.350221 +2.41429 0.185714 0.18 0.616576 +2.41429 0.185714 0.12 0.757627 +2.41429 0.185714 0.06 0.8159 +2.41429 0.185714 0 0.981899 +2.6 0 0.3 0.0525006 +2.6 0 0.24 0.362959 +2.6 0 0.18 0.718168 +2.6 0 0.12 0.886341 +2.6 0 0.06 0.899591 +2.6 0 0 1.0078 diff --git a/test/point_to_mesh_mls.cpp b/test/point_to_mesh_mls.cpp new file mode 100644 index 00000000..3f2bd250 --- /dev/null +++ b/test/point_to_mesh_mls.cpp @@ -0,0 +1,1092 @@ +#include +#include +#include +#include +#include +#include +#include "KokkosBatched_SVD_Decl.hpp" +#include "KokkosBatched_SVD_Serial_Impl.hpp" +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +using namespace Omega_h; +using namespace pcms; + +namespace fs = std::filesystem; + +// __FILE__ is ".../pcms/test/point_to_mesh_mls.cpp" +static const fs::path src_file = __FILE__; +static const fs::path test_dir = src_file.parent_path(); // .../pcms/test +static const fs::path data_dir = test_dir / "data"; // .../pcms/test/data + +std::vector readTeData(const std::string& filePath, MPI_Comm comm = MPI_COMM_WORLD) { + int rank, size; + MPI_Comm_rank(comm, &rank); + MPI_Comm_size(comm, &size); + + std::vector Te_data; + + // Ensure MPI is initialized + int mpi_initialized; + MPI_Initialized(&mpi_initialized); + if (!mpi_initialized) { + MPI_Init(nullptr, nullptr); + } + + // Initialize ADIOS2 + adios2::ADIOS adios(comm); + adios2::IO io = adios.DeclareIO("BoutIO"); + + // Ensure the engine is set to BP format + if (!io.InConfigFile()) { + io.SetEngine("BP"); + } + + // Open the file in STREAMING mode + adios2::Engine reader = io.Open(filePath, adios2::Mode::Read, comm); + if (!reader) { + std::cerr << "Error: Failed to open file " << filePath << std::endl; + return Te_data; + } + + // BeginStep (needed for streaming mode) + adios2::StepStatus status = reader.BeginStep(); + if (status != adios2::StepStatus::OK) { + std::cerr << "Error: Failed to start step in ADIOS2 reader.\n"; + reader.Close(); + return Te_data; + } + + // Inquire the variable "Te" + auto var_Te = io.InquireVariable("Te"); + if (!var_Te) { + std::cerr << "Error: Could not find variable 'Te' in the BOUT file.\n"; + reader.EndStep(); + reader.Close(); + return Te_data; + } + + // Get the shape of the dataset + auto shape = var_Te.Shape(); + + // Debugging: Print detected shape + if (rank == 0) { // Only print from one rank to avoid excessive output + std::cout << "Detected shape of 'Te': "; + for (auto s : shape) { + std::cout << s << " "; + } + std::cout << std::endl; + } + + // Ensure shape is valid (must be 3D) + if (shape.size() != 3) { + std::cerr << "Error: Unexpected shape for 'Te'. Expected 3D array (Nx, Ny, Nz).\n"; + reader.EndStep(); + reader.Close(); + return Te_data; + } + + size_t Nx = shape[0]; // 20 (number of x grid points) + size_t Ny = shape[1]; // 10 (number of y grid points) + size_t Nz = shape[2]; // 20 (number of z grid points) + + // Distribute workload across MPI ranks + size_t N_per_rank = Nx / size; + size_t start_x = rank * N_per_rank; + size_t count_x = (rank == size - 1) ? Nx - rank * N_per_rank : N_per_rank; + + // Resize output vector to hold (count_x * Ny * Nz) values for this rank + Te_data.resize(count_x * Ny * Nz); + + // Set selection for distributed x-range + var_Te.SetSelection({{start_x, 0, 0}, {count_x, Ny, Nz}}); + + // Read data into the vector + reader.Get(var_Te, Te_data.data(), adios2::Mode::Sync); + + // EndStep must be called before closing + reader.EndStep(); + reader.Close(); + + // // Print first 10 values for debugging (only from rank 0) + // if (rank == 0) { + // std::cout << "Te values (first 10 entries):\n"; + // for (size_t i = 0; i < std::min(size_t(10), Te_data.size()); ++i) { + // std::cout << "Te[" << i << "] = " << Te_data[i] << "\n"; + // } + // } + + return Te_data; +} + +std::vector, double>> generateSourcePointsWithTe(const std::vector& Te_data) { + const int radial = 20; // R direction points (Nx) + const int poloidal = 20; // Z direction points (Nz) + const int toroidal = 10; // θ direction points (Ny) + + double R_min = 1.4, R_max = 2.6; + // double Z_min = -0.6, Z_max = 0.6; + double Z_min = 0.0, Z_max = 1.2; + double dy = 0.18; + double dR = (R_max - R_min) / (radial - 1); + double dZ = (Z_max - Z_min) / (poloidal - 1); + + std::vector, double>> source_points_with_Te; + + for (int i = 0; i < radial; ++i) { + double R = R_min + i * dR; + for (int j = 0; j < poloidal; ++j) { + double Z = Z_min + j * dZ; + for (int k = 0; k < toroidal; ++k) { + double theta = k * dy; + + // Convert to Cartesian coordinates + double x = R * cos(theta); + double y = R * sin(theta); + double z = Z; + + // Compute correct Te index (column-major: k + Ny * (j + Nz * i)) + size_t index = k + toroidal * (j + poloidal * i); + + // Bounds check to prevent errors + if (index >= Te_data.size()) { + std::cerr << "Index out of bounds: " << index << " for Te_data size " << Te_data.size() << std::endl; + continue; + } + + double Te_value = Te_data[index]; + + // Store (x, y, z) with corresponding Te + source_points_with_Te.push_back({{x, y, z}, Te_value}); + } + } + } + return source_points_with_Te; +} + +// n² search to find neighbors (Brute force search) +inline SupportResults findNeighbors( + const std::vector>& host_source_points, + const std::vector>& host_target_points, + double cutoffDistance) { + + SupportResults results; + int numTargets = host_target_points.size(); + int numSources = host_source_points.size(); + double cutoffDistanceSq = cutoffDistance * cutoffDistance; + + if (numSources == 0 || numTargets == 0) { + std::cerr << "Warning: No source or target points provided!\n"; + return results; + } + + // Allocate storage + Write nSupports(numTargets, 0, "number of supports for each target"); + Write radii2(numTargets, cutoffDistanceSq, "squared radii of supports"); + + // Create Kokkos Views for device storage + Kokkos::View source_points("source_points", numSources, 3); + Kokkos::View target_points("target_points", numTargets, 3); + + // Create host mirrors + auto host_source_view = Kokkos::create_mirror_view(source_points); + auto host_target_view = Kokkos::create_mirror_view(target_points); + + // Copy data from std::vector to host mirror views + for (int i = 0; i < numSources; ++i) { + for (int d = 0; d < 3; ++d) { // 3D coordinates + host_source_view(i, d) = host_source_points[i][d]; + } + } + + for (int i = 0; i < numTargets; ++i) { + for (int d = 0; d < 3; ++d) { + host_target_view(i, d) = host_target_points[i][d]; + } + } + + // Copy from host mirror to device views + Kokkos::deep_copy(source_points, host_source_view); + Kokkos::deep_copy(target_points, host_target_view); + + // Count neighbors + Kokkos::parallel_for("count neighbors", numTargets, KOKKOS_LAMBDA(int i) { + int count = 0; + for (int j = 0; j < numSources; ++j) { + double dx = target_points(i, 0) - source_points(j, 0); + double dy = target_points(i, 1) - source_points(j, 1); + double dz = target_points(i, 2) - source_points(j, 2); + double dist_sq = dx * dx + dy * dy + dz * dz; + + if (dist_sq <= cutoffDistanceSq) { + count++; + } + } + nSupports[i] = count; + }); + + // Compute prefix sum (scan index) + Write supports_ptr(numTargets + 1, 0, "scan index"); + LO total_supports = 0; + Kokkos::parallel_scan( + "compute scan index", numTargets, + KOKKOS_LAMBDA(int j, int& update, bool final) { + update += nSupports[j]; + if (final) { + supports_ptr[j + 1] = update; + } + }, + total_supports); + + // Allocate storage for actual neighbor indices and distances + Write supports_idx(total_supports, 0, "neighbor indices"); + Write radii_vals(total_supports, 0, "neighbor squared distances"); + + // Fill neighbor indices + Kokkos::parallel_for("fill neighbor indices", numTargets, KOKKOS_LAMBDA(int i) { + int offset = supports_ptr[i]; + int count = 0; + for (int j = 0; j < numSources; ++j) { + double dx = target_points(i, 0) - source_points(j, 0); + double dy = target_points(i, 1) - source_points(j, 1); + double dz = target_points(i, 2) - source_points(j, 2); + double dist_sq = dx * dx + dy * dy + dz * dz; + + if (dist_sq <= cutoffDistanceSq) { + supports_idx[offset + count] = j; + radii_vals[offset + count] = dist_sq; + count++; + } + } + }); + + // Assign results + results.supports_ptr = supports_ptr; + results.supports_idx = supports_idx; + results.radii2 = radii_vals; + + return results; +} + +SupportResults findNeighborsUniformGrid( + const std::vector>& host_source_points, + const std::vector>& host_target_points, + double cutoffDistance) +{ + static_assert(std::is_trivially_copyable>::value, + "UniformGrid<3> must be trivially copyable to store in Kokkos::View."); + + using ExecSpace = Kokkos::DefaultExecutionSpace; + using MemorySpace = ExecSpace::memory_space; + + SupportResults results; + const LO numSources = host_source_points.size(); + const LO numTargets = host_target_points.size(); + if (numSources == 0 || numTargets == 0) return results; + + // Copy source and target points to Kokkos Views + Kokkos::View source("source", numSources, 3); + Kokkos::View target("target", numTargets, 3); + auto hsrc = Kokkos::create_mirror_view(source); + auto htar = Kokkos::create_mirror_view(target); + for (LO i = 0; i < numSources; ++i) + for (int d = 0; d < 3; ++d) + hsrc(i, d) = host_source_points[i][d]; + for (LO i = 0; i < numTargets; ++i) + for (int d = 0; d < 3; ++d) + htar(i, d) = host_target_points[i][d]; + Kokkos::deep_copy(source, hsrc); + Kokkos::deep_copy(target, htar); + + // Compute bounding box of the source points + std::array min_coord, max_coord; + for (int d = 0; d < 3; ++d) min_coord[d] = max_coord[d] = hsrc(0, d); + for (LO i = 1; i < numSources; ++i) + for (int d = 0; d < 3; ++d) { + min_coord[d] = std::min(min_coord[d], hsrc(i, d)); + max_coord[d] = std::max(max_coord[d], hsrc(i, d)); + } + + // Build a uniform grid that bounds the source points + pcms::UniformGrid<3> grid; + for (int d = 0; d < 3; ++d) { + grid.edge_length[d] = max_coord[d] - min_coord[d]; + grid.bot_left[d] = min_coord[d]; + grid.divisions[d] = std::max(static_cast(grid.edge_length[d] / cutoffDistance), LO(1)); + } + + // Copy the grid to device memory + LO numCells = grid.GetNumCells(); + Kokkos::View*> grid_view("grid_view", 1); + auto hgrid = Kokkos::create_mirror_view(grid_view); + hgrid(0) = grid; + Kokkos::deep_copy(grid_view, hgrid); + + // Precompute cell_size on host + std::array cell_size_host; + for (int d = 0; d < 3; ++d) + cell_size_host[d] = grid.edge_length[d] / grid.divisions[d]; + + // Copy cell_size to device + Kokkos::View cell_size_view("cell_size_view"); + auto h_cell_size_view = Kokkos::create_mirror_view(cell_size_view); + for (int d = 0; d < 3; ++d) + h_cell_size_view(d) = cell_size_host[d]; + Kokkos::deep_copy(cell_size_view, h_cell_size_view); + + // Count how many source points fall into each grid cell + Kokkos::View cell_counts("cell_counts", numCells); + Kokkos::parallel_for("Count sources per cell", numSources, KOKKOS_LAMBDA(LO i) { + auto grid = grid_view(0); + Omega_h::Vector<3> p; + for (int d = 0; d < 3; ++d) + p[d] = source(i, d); + + LO cell_id = grid.ClosestCellID(p); + Kokkos::atomic_increment(&cell_counts(cell_id)); + }); + + // Compute cell_ptrs using prefix scan + Kokkos::View cell_ptrs("cell_ptrs", numCells + 1); + Kokkos::parallel_scan("Scan cell counts", numCells + 1, KOKKOS_LAMBDA(LO i, LO& acc, const bool final) { + if (final) cell_ptrs(i) = acc; + if (i < numCells) acc += cell_counts(i); + }); + + // Get total number of binned sources + LO total_sources = 0; + Kokkos::deep_copy(total_sources, Kokkos::subview(cell_ptrs, numCells)); + + Kokkos::View cell_indices("cell_indices", total_sources); + Kokkos::View cell_offsets("cell_offsets", numCells); + Kokkos::deep_copy(cell_offsets, 0); + + Kokkos::parallel_for("Fill cell bins", numSources, KOKKOS_LAMBDA(LO i) { + auto grid = grid_view(0); + + Omega_h::Vector<3> p; + for (int d = 0; d < 3; ++d) + p[d] = source(i, d); + + LO cid = grid.ClosestCellID(p); + LO offset = Kokkos::atomic_fetch_add(&cell_offsets(cid), 1); + cell_indices(cell_ptrs(cid) + offset) = i; + }); + + // Count number of neighbors per target + Kokkos::View supports_ptr("supports_ptr", numTargets + 1); + Kokkos::View support_counts("support_counts", numTargets); + pcms::detail::GridRadialNeighborFunctor<3> functor{ + target, source, grid_view, cell_ptrs, cell_indices, cutoffDistance, numCells, cell_size_view + }; + + Kokkos::parallel_for("Count neighbors", numTargets, KOKKOS_LAMBDA(LO i) { + support_counts(i) = functor(i, nullptr); + }); + + Kokkos::parallel_scan("Scan support counts", numTargets + 1, KOKKOS_LAMBDA(LO i, LO& acc, const bool final) { + if (final) supports_ptr(i) = acc; + if (i < numTargets) acc += support_counts(i); + }); + + LO total_neighbors = 0; + Kokkos::deep_copy(total_neighbors, Kokkos::subview(supports_ptr, numTargets)); + Kokkos::View supports_idx("supports_idx", total_neighbors); + Kokkos::View radii2("radii2", total_neighbors); + + // Fill the neighbors and compute squared distances + Kokkos::parallel_for("Fill neighbors", numTargets, KOKKOS_LAMBDA(LO i) { + LO offset = supports_ptr(i); + LO* ptr = &supports_idx(offset); + LO actual_count = functor(i, ptr); + double pt[3]; + for (int d = 0; d < 3; ++d) pt[d] = target(i, d); + for (LO j = 0; j < actual_count; ++j) { + double q[3]; + for (int d = 0; d < 3; ++d) q[d] = source(ptr[j], d); + Real r2 = 0.0; + for (int d = 0; d < 3; ++d) + r2 += (pt[d] - q[d]) * (pt[d] - q[d]); + radii2(offset + j) = r2; + } + }); + + // Allocate Omega_h::Write arrays directly on device + Omega_h::Write ptr_w(supports_ptr.extent(0)); + Omega_h::Write idx_w(supports_idx.extent(0)); + Omega_h::Write rad_w(radii2.extent(0)); + + // Fill Omega_h::Write using Kokkos parallel_for (device-safe) + Kokkos::parallel_for("copy ptr_w", ptr_w.size(), KOKKOS_LAMBDA(LO i) { + ptr_w[i] = supports_ptr(i); + }); + Kokkos::parallel_for("copy idx_w", idx_w.size(), KOKKOS_LAMBDA(LO i) { + idx_w[i] = supports_idx(i); + }); + Kokkos::parallel_for("copy rad_w", rad_w.size(), KOKKOS_LAMBDA(LO i) { + rad_w[i] = radii2(i); + }); + + // Omega_h::Write ptr_w(supports_ptr.size()); + // Omega_h::Write idx_w(supports_idx.size()); + // Omega_h::Write rad_w(radii2.size()); + + // auto k_ptr_w = Kokkos::View(ptr_w.data(), ptr_w.size()); + // auto k_idx_w = Kokkos::View(idx_w.data(), idx_w.size()); + // auto k_rad_w = Kokkos::View(rad_w.data(), rad_w.size()); + + // Kokkos::deep_copy(k_ptr_w, supports_ptr); + // Kokkos::deep_copy(k_idx_w, supports_idx); + // Kokkos::deep_copy(k_rad_w, radii2); + + // Store in output struct + results.supports_ptr = ptr_w; + results.supports_idx = idx_w; + results.radii2 = rad_w; + + return results; +} + +inline void test_interpolation_point_to_mesh( + Mesh& mesh, double cutoffDistance, + Reals source_values, Write& target_values, + Reals source_coordinates, Reals target_coordinates, + const SupportResults& support) +{ + using ExecSpace = Kokkos::DefaultExecutionSpace; + using TeamPolicy = Kokkos::TeamPolicy; + using MemberType = TeamPolicy::member_type; + using ScratchSpace = typename MemberType::scratch_memory_space; + + using MatView = Kokkos::View>; + using VecView = Kokkos::View>; + + const int dim = mesh.dim(); + const size_t num_targets = target_values.size(); + constexpr int basis_size = 10; // Quadratic: [1, x, y, z, x², y², z², xy, xz, yz] + + auto d_supports_ptr = support.supports_ptr; + auto d_supports_idx = support.supports_idx; + auto d_radii2 = support.radii2; + + Write temp_values(num_targets, "svd interpolated values"); + + // Find max support + LO max_support = 0; + auto host_ptr = HostRead(d_supports_ptr); + for (size_t i = 0; i < num_targets; ++i) + max_support = std::max(max_support, host_ptr[i + 1] - host_ptr[i]); + + const int bytes_per_double = sizeof(double); + const int scratch_bytes = bytes_per_double * ( + max_support * basis_size + // A + max_support + // b + basis_size + // x + max_support + // weights + basis_size + // sigma + basis_size * basis_size + // Vt + max_support * max_support + // U + max_support + // work + basis_size // Ut_b + ); + + TeamPolicy policy(num_targets, Kokkos::AUTO); + policy = policy.set_scratch_size(1, Kokkos::PerTeam(scratch_bytes)); + + Kokkos::parallel_for("MLS-SVD Interpolation", policy, KOKKOS_LAMBDA(const MemberType& team) { + const int i = team.league_rank(); + const LO start = d_supports_ptr[i]; + const LO end = d_supports_ptr[i + 1]; + const int nsupports = end - start; + + if (nsupports < basis_size) return; + + MatView A(team.team_scratch(1), nsupports, basis_size); + VecView b(team.team_scratch(1), nsupports); + VecView x(team.team_scratch(1), basis_size); + VecView weights(team.team_scratch(1), nsupports); + MatView U(team.team_scratch(1), nsupports, nsupports); + MatView Vt(team.team_scratch(1), basis_size, basis_size); + VecView sigma(team.team_scratch(1), basis_size); + VecView work(team.team_scratch(1), nsupports); + VecView Ut_b(team.team_scratch(1), basis_size); + + const double h = 0.5 * cutoffDistance; + + for (int j = 0; j < nsupports; ++j) { + const int idx = d_supports_idx[start + j]; + double x_s = source_coordinates[idx * dim + 0]; + double y_s = source_coordinates[idx * dim + 1]; + double z_s = source_coordinates[idx * dim + 2]; + double r2 = d_radii2[start + j]; + double w = exp(-r2 / (h * h)); + weights(j) = w; + + A(j, 0) = w * 1.0; + A(j, 1) = w * x_s; + A(j, 2) = w * y_s; + A(j, 3) = w * z_s; + A(j, 4) = w * x_s * x_s; + A(j, 5) = w * y_s * y_s; + A(j, 6) = w * z_s * z_s; + A(j, 7) = w * x_s * y_s; + A(j, 8) = w * x_s * z_s; + A(j, 9) = w * y_s * z_s; + + b(j) = w * source_values[idx]; + } + + // SVD solve + if (team.team_rank() == 0) { + KokkosBatched::SerialSVD::invoke( + KokkosBatched::SVD_USV_Tag(), A, U, sigma, Vt, work); + } + team.team_barrier(); + + for (int k = 0; k < basis_size; ++k) { + Ut_b(k) = 0.0; + for (int j = 0; j < nsupports; ++j) + Ut_b(k) += U(j, k) * b(j); + } + + for (int irow = 0; irow < basis_size; ++irow) { + double val = 0.0; + for (int j = 0; j < basis_size; ++j) + if (sigma(j) > 1e-10) + val += Vt(j, irow) * (Ut_b(j) / sigma(j)); + x(irow) = val; + } + + double xt = target_coordinates[i * dim + 0]; + double yt = target_coordinates[i * dim + 1]; + double zt = target_coordinates[i * dim + 2]; + + Real interpolated = + x(0) + x(1)*xt + x(2)*yt + x(3)*zt + + x(4)*xt*xt + x(5)*yt*yt + x(6)*zt*zt + + x(7)*xt*yt + x(8)*xt*zt + x(9)*yt*zt; + + temp_values[i] = interpolated; + }); + + target_values = temp_values; +} + + TEST_CASE("point to mesh mls svd") { + + const std::string filePath = (data_dir / "BOUT.dmp.bp").string(); + // Read the first time step (index 0) + std::vector Te_data = readTeData(filePath); + + auto lib = Library{}; + auto world = lib.world(); + + auto mesh = build_box(world, OMEGA_H_SIMPLEX, 2.6, 2.6, 1.2, 14, 14, 20, false); + + // // Debug + // auto host_coords = HostRead(mesh.coords()); + + // double min_zz = std::numeric_limits::max(); + // double max_zz = std::numeric_limits::lowest(); + + // for (int i = 0; i < mesh.nverts(); ++i) { + // double z = host_coords[i * 3 + 2]; + // min_zz = std::min(min_zz, z); + // max_zz = std::max(max_zz, z); + // } + // std::cout << "Z range after shifting: [" << min_zz << ", " << max_zz << "]\n"; + + Real cutoffDistance = 0.35; + // cutoffDistance = cutoffDistance * cutoffDistance; + + const int dim = mesh.dim(); + const auto& target_coordinates = mesh.coords(); + const auto ntargets = mesh.nverts(); + + auto source_data = generateSourcePointsWithTe(Te_data); + size_t numSources = source_data.size(); + + // // Debugging Print first few entries for debugging + // std::cout << "First few source points (x, y, z, Te):" << std::endl; + // for (size_t i = 0; i < std::min(numSources, size_t(10)); ++i) { + // std::cout << "Point " << i << ": (" + // << source_data[i].first[0] << ", " + // << source_data[i].first[1] << ", " + // << source_data[i].first[2] << ") " + // << " Te = " << source_data[i].second << std::endl; + // } + + // Convert mesh coordinates to host format + std::vector> host_target_data; + auto host_target_coords = HostRead(target_coordinates); + + // Filtering target points + for (size_t i = 0; i < ntargets; ++i) { + double x = host_target_coords[i * 3]; + double y = host_target_coords[i * 3 + 1]; + double z = host_target_coords[i * 3 + 2]; + + double r = std::sqrt(x * x + y * y); + double theta = std::atan2(y, x); + + // Normalize theta to [0, 2π] if needed + if (theta < 0) theta += 2 * M_PI; + + if (r >= 1.4 && r <= 2.6 && + z >= 0.0 && z <= 1.2 && + theta >= 0.0 && theta <= 1.62) { + host_target_data.push_back({x, y, z}); + } + } + + // Update `ntargets` to reflect the filtered number of points + const auto ntargets_filtered = host_target_data.size(); + + // Define new variable for filtered target coordinates + Write target_coordinates_filtered(ntargets_filtered * 3, 0.0, "target coordinates filtered"); + + // Create a Kokkos View for host_target_data + Kokkos::View host_target_data_view("host_target_data_view", ntargets_filtered, 3); + + // Copy host_target_data into the Kokkos View + auto host_mirror = Kokkos::create_mirror_view(host_target_data_view); + for (size_t i = 0; i < ntargets_filtered; ++i) { + for (int d = 0; d < 3; ++d) { + host_mirror(i, d) = host_target_data[i][d]; + } + } + Kokkos::deep_copy(host_target_data_view, host_mirror); + + // Fill target_coordinates_filtered using Kokkos parallel_for + Kokkos::parallel_for("fill target_coordinates_filtered", ntargets_filtered, KOKKOS_LAMBDA(int i) { + target_coordinates_filtered[i * 3] = host_target_data_view(i, 0); + target_coordinates_filtered[i * 3 + 1] = host_target_data_view(i, 1); + target_coordinates_filtered[i * 3 + 2] = host_target_data_view(i, 2); + }); + + // // Debugging + // auto host_target_coords_filtered = HostRead(target_coordinates_filtered); + + // std::cout << "Filtered target coordinates (first 10):" << std::endl; + // for (size_t i = 0; i < std::min(ntargets_filtered, size_t(10)); ++i) { + // std::cout << "Target " << i << ": (" + // << host_target_coords_filtered[i * 3] << ", " + // << host_target_coords_filtered[i * 3 + 1] << ", " + // << host_target_coords_filtered[i * 3 + 2] << ")" << std::endl; + // } + // // Debugging: Check min/max of r, theta, z + // double min_r = std::numeric_limits::max(); + // double max_r = std::numeric_limits::lowest(); + // double min_theta = std::numeric_limits::max(); + // double max_theta = std::numeric_limits::lowest(); + // double min_z = std::numeric_limits::max(); + // double max_z = std::numeric_limits::lowest(); + // auto host_target_coords_filtered = HostRead(target_coordinates_filtered); + // for (size_t i = 0; i < ntargets_filtered; ++i) { + // double x = host_target_coords_filtered[i * 3]; + // double y = host_target_coords_filtered[i * 3 + 1]; + // double z = host_target_coords_filtered[i * 3 + 2]; + // double r = std::sqrt(x * x + y * y); + // double theta = std::atan2(y, x); + // if (theta < 0) theta += 2 * M_PI; + // min_r = std::min(min_r, r); + // max_r = std::max(max_r, r); + // min_theta = std::min(min_theta, theta); + // max_theta = std::max(max_theta, theta); + // min_z = std::min(min_z, z); + // max_z = std::max(max_z, z); + // } + // std::cout << "Filtered Target Range:\n"; + // std::cout << " r ∈ [" << min_r << ", " << max_r << "]\n"; + // std::cout << " θ ∈ [" << min_theta << ", " << max_theta << "] (rad)\n"; + // std::cout << " z ∈ [" << min_z << ", " << max_z << "]\n"; + + // Extract {x, y, z} from source_data before calling findNeighbors + std::vector> source_coordinates; + for (const auto& p : source_data) { + source_coordinates.push_back({p.first[0], p.first[1], p.first[2]}); + } + + SupportResults support = findNeighborsUniformGrid(source_coordinates, host_target_data, cutoffDistance); + + auto host_supports_ptr = HostRead(support.supports_ptr); + auto host_supports_idx = HostRead(support.supports_idx); + auto host_radii2 = HostRead(support.radii2); + + // // Debugging + // std::cout << "First 10 targets' neighbor counts:" << std::endl; + // for (size_t i = 0; i < std::min(ntargets_filtered, size_t(100)); ++i) { + // int num_neighbors = host_supports_ptr[i + 1] - host_supports_ptr[i]; + // std::cout << "Target " << i << " has " << num_neighbors << " neighbors." << std::endl; + // } + + // Ensure at least one neighbor is found + CHECK(host_supports_ptr[ntargets_filtered] > 0); + + // Ensure supports_ptr size is correct + CHECK(support.supports_ptr.size() == ntargets_filtered + 1); + + // Ensure supports_ptr is non-decreasing + for (size_t i = 0; i < ntargets_filtered; ++i) { + CHECK(host_supports_ptr[i] <= host_supports_ptr[i + 1]); + } + + // Ensure first and last values are correct + CHECK(host_supports_ptr[0] == 0); + CHECK(host_supports_ptr[ntargets_filtered] == support.supports_idx.size()); + + // Check that each target has at least one neighbor + for (size_t i = 0; i < ntargets_filtered; ++i) { + int num_neighbors = host_supports_ptr[i + 1] - host_supports_ptr[i]; + CHECK(num_neighbors >= 0); + } + + // Check that found neighbors are actually within the cutoff distance + const auto host_source_data = source_data; + + for (size_t i = 0; i < ntargets_filtered; ++i) { + int start_idx = host_supports_ptr[i]; + int end_idx = host_supports_ptr[i + 1]; + + for (int j = start_idx; j < end_idx; ++j) { + int neighbor_index = host_supports_idx[j]; + + // Extract only x, y, z from source data + double dx = host_target_data[i][0] - host_source_data[neighbor_index].first[0]; + double dy = host_target_data[i][1] - host_source_data[neighbor_index].first[1]; + double dz = host_target_data[i][2] - host_source_data[neighbor_index].first[2]; + + double dist_sq = dx * dx + dy * dy + dz * dz; + CHECK(dist_sq <= cutoffDistance* cutoffDistance); + } + } + + // Check that every neighbor is counted only once per target + for (size_t i = 0; i < ntargets_filtered; ++i) { + int start_idx = host_supports_ptr[i]; + int end_idx = host_supports_ptr[i + 1]; + + std::unordered_set unique_neighbors; + + for (int j = start_idx; j < end_idx; ++j) { + int neighbor_index = host_supports_idx[j]; + CHECK(unique_neighbors.find(neighbor_index) == unique_neighbors.end()); + unique_neighbors.insert(neighbor_index); + } + } + + // Convert source points to a GPU-compatible Kokkos View + Kokkos::View source_view("source_view", numSources, 4); + auto host_source_view = Kokkos::create_mirror_view(source_view); + + for (size_t i = 0; i < numSources; ++i) { + for (int d = 0; d < 3; ++d) { + host_source_view(i, d) = source_data[i].first[d]; // Extract {x, y, z} + } + host_source_view(i, 3) = source_data[i].second; // Store Te value as the 4th column + } + + // Copy data from host to device + Kokkos::deep_copy(source_view, host_source_view); + + // Define a new variable for flattened source coordinates + Te + Write source_data_flat(4 * numSources, 0.0, "source data flat"); + + // Convert source points to flat `Reals` array for MLS + Kokkos::parallel_for("convert source_data", numSources, KOKKOS_LAMBDA(const size_t i) { + source_data_flat[i * 4] = source_view(i, 0); // x + source_data_flat[i * 4 + 1] = source_view(i, 1); // y + source_data_flat[i * 4 + 2] = source_view(i, 2); // z + source_data_flat[i * 4 + 3] = source_view(i, 3); // Te + }); + + + // Convert target points to a Kokkos View + Kokkos::View target_view("target_view", ntargets_filtered, 3); + auto host_target_view = Kokkos::create_mirror_view(target_view); + + for (size_t i = 0; i < ntargets_filtered; ++i) { + for (int d = 0; d < dim; ++d) { + host_target_view(i, d) = host_target_data[i][d]; + } + } + + // Copy from host to device + Kokkos::deep_copy(target_view, host_target_view); + + // SECTION("Linear MLS interpolation Te source to target") { + // int degree = 1; + // LO min_num_supports = 10; + + // Write source_values(numSources, 0.0, "source Te values"); + // Write target_values(ntargets_filtered, 0.0, "exact Te values"); + + // // Assign Te values from source points + // Kokkos::parallel_for("assign source Te values", numSources, KOKKOS_LAMBDA(const size_t i) { + // source_values[i] = source_view(i, 3); // Te is stored in column 3 + // }); + + // // Initialize target_values to 0 (they will be interpolated) + // Kokkos::parallel_for("initialize target Te values", ntargets_filtered, KOKKOS_LAMBDA(int i) { + // target_values[i] = 0.0; // Placeholder, will be interpolated + // }); + + // // Flatten source coordinates + // Write source_coordinates_flat(numSources * 3, 0.0, "source coordinates"); + // Kokkos::parallel_for("flatten source coordinates", numSources, KOKKOS_LAMBDA(const size_t i) { + // source_coordinates_flat[i * 3] = source_view(i, 0); // x + // source_coordinates_flat[i * 3 + 1] = source_view(i, 1); // y + // source_coordinates_flat[i * 3 + 2] = source_view(i, 2); // z + // }); + + // // Flatten target coordinates + // Write target_coordinates_flat(ntargets_filtered * 3, 0.0, "target coordinates filtered"); + // Kokkos::parallel_for("flatten target coordinates", ntargets_filtered, KOKKOS_LAMBDA(const size_t i) { + // target_coordinates_flat[i * 3] = target_view(i, 0); + // target_coordinates_flat[i * 3 + 1] = target_view(i, 1); + // target_coordinates_flat[i * 3 + 2] = target_view(i, 2); + // }); + + // test_interpolation_point_to_mesh( + // mesh, cutoffDistance, degree, min_num_supports, + // Reals(source_values), target_values, + // Reals(source_coordinates_flat), Reals(target_coordinates_flat) + // ); + + // // // Debug: Print first 10 target values + // // auto host_target_values_debug = HostRead(target_values); + // // std::cout << "\nTarget Te values after interpolation (first 10 targets)11111:\n"; + // // for (size_t i = 0; i < std::min(ntargets_filtered, size_t(10)); ++i) { + // // std::cout << "Target " << i << " | Te = " << host_target_values_debug[i] << "\n"; + // // } + // } + + SECTION("Two-way MLS interpolation: Source → Target → Source") { + + // First Interpolation: Source → Target + Write source_values(numSources, 0.0, "source Te values"); + Write target_values(ntargets_filtered, 0.0, "interpolated Te at targets"); + + // Assign `Te` values from source points + Kokkos::parallel_for("assign source Te values", numSources, KOKKOS_LAMBDA(const size_t i) { + source_values[i] = source_view(i, 3); // Te is in column 3 + }); + + // Flatten source and target coordinates + Write source_coordinates_flat(numSources * 3, 0.0, "source coordinates"); + Write target_coordinates_flat(ntargets_filtered * 3, 0.0, "target coordinates filtered"); + + Kokkos::parallel_for("flatten source coordinates", numSources, KOKKOS_LAMBDA(const size_t i) { + source_coordinates_flat[i * 3] = source_view(i, 0); + source_coordinates_flat[i * 3 + 1] = source_view(i, 1); + source_coordinates_flat[i * 3 + 2] = source_view(i, 2); + }); + + Kokkos::parallel_for("flatten target coordinates", ntargets_filtered, KOKKOS_LAMBDA(const size_t i) { + target_coordinates_flat[i * 3] = target_view(i, 0); + target_coordinates_flat[i * 3 + 1] = target_view(i, 1); + target_coordinates_flat[i * 3 + 2] = target_view(i, 2); + }); + + // Debug + auto host_source_values_debug = HostRead(source_values); + std::cout << "\nSource Te values before first interpolation (first 10 sources):\n"; + for (size_t i = 0; i < std::min(numSources, size_t(10)); ++i) { + std::cout << "Source " << i << " | Te = " << host_source_values_debug[i] << "\n"; + } + // Debug + std::cout << "\nChecking neighbors per target (first 10 targets):\n"; + for (size_t i = 0; i < std::min(ntargets_filtered, size_t(10)); ++i) { + int num_neighbors = host_supports_ptr[i + 1] - host_supports_ptr[i]; + std::cout << "Target " << i << " has " << num_neighbors << " neighbors.\n"; + } + + // Perform first MLS interpolation: `source → target` + test_interpolation_point_to_mesh( + mesh, cutoffDistance, Reals(source_values), target_values, + Reals(source_coordinates_flat), Reals(target_coordinates_flat), + support + ); + + // Debug: Print first 10 target values after first interpolation + auto host_target_values_debug = HostRead(target_values); + std::cout << "\nTarget Te values after first interpolation (first 10 targets):\n"; + for (size_t i = 0; i < std::min(ntargets_filtered, size_t(10)); ++i) { + std::cout << "Target " << i << " | Te = " << host_target_values_debug[i] << "\n"; + } + + // Define new source points (previous target points) and their Te values + Write new_source_values(ntargets_filtered, 0.0, "new source Te values"); + + // Use Reals as an intermediate buffer before copying + Reals temp_target_values = Reals(target_values); + Kokkos::parallel_for("copy target_values -> new_source_values", ntargets_filtered, KOKKOS_LAMBDA(int i) { + new_source_values[i] = temp_target_values[i]; + }); + + // Define new source coordinates + Write new_source_coordinates(ntargets_filtered * 3, 0.0, "new source coordinates"); + Reals temp_target_coordinates = Reals(target_coordinates_flat); + Kokkos::parallel_for("copy target_coordinates -> new_source_coordinates", ntargets_filtered, KOKKOS_LAMBDA(int i) { + new_source_coordinates[i * 3] = temp_target_coordinates[i * 3]; + new_source_coordinates[i * 3 + 1] = temp_target_coordinates[i * 3 + 1]; + new_source_coordinates[i * 3 + 2] = temp_target_coordinates[i * 3 + 2]; + }); + + // Define new target points (previous source points), initialize Te to zero + Write recovered_source_values(numSources, 0.0, "recovered Te at sources"); + Write new_target_coordinates(numSources * 3, 0.0, "new target coordinates"); + + Reals temp_source_coordinates = Reals(source_coordinates_flat); + Kokkos::parallel_for("copy source_coordinates -> new_target_coordinates", numSources, KOKKOS_LAMBDA(int i) { + new_target_coordinates[i * 3] = temp_source_coordinates[i * 3]; + new_target_coordinates[i * 3 + 1] = temp_source_coordinates[i * 3 + 1]; + new_target_coordinates[i * 3 + 2] = temp_source_coordinates[i * 3 + 2]; + }); + + // Convert `Reals` to host `std::vector>` format + std::vector> host_new_source_data; + std::vector> host_new_target_data; + + auto host_new_source_coords = HostRead(new_source_coordinates); + auto host_new_target_coords = HostRead(new_target_coordinates); + + // Fill new source data + for (size_t i = 0; i < ntargets_filtered; ++i) { + host_new_source_data.push_back({ + host_new_source_coords[i * 3], + host_new_source_coords[i * 3 + 1], + host_new_source_coords[i * 3 + 2] + }); + } + + // Fill new target data + for (size_t i = 0; i < numSources; ++i) { + host_new_target_data.push_back({ + host_new_target_coords[i * 3], + host_new_target_coords[i * 3 + 1], + host_new_target_coords[i * 3 + 2] + }); + } + + // // Debug: Print Te values before second interpolation + // std::cout << "\nTarget Te values before second interpolation (first 10 targets):\n"; + // for (size_t i = 0; i < std::min(ntargets_filtered, size_t(10)); ++i) { + // std::cout << "Target " << i << " | Te = " << host_target_values_debug[i] << "\n"; + // } + + Real second_cutoffDistance = cutoffDistance * 1.5; + + // Find new neighbors (target → source) + SupportResults support_target_to_source = findNeighborsUniformGrid( + host_new_source_data, + host_new_target_data, + second_cutoffDistance + ); + + // Ensure neighbors are found + CHECK(support_target_to_source.supports_idx.size() > 0); + + // Debug: Check neighbors per new target (original sources) + auto host_supports_ptr_new = HostRead(support_target_to_source.supports_ptr); + std::cout << "\nChecking neighbors per source (first 10 sources):\n"; + for (size_t i = 0; i < std::min(numSources, size_t(10)); ++i) { + int num_neighbors = host_supports_ptr_new[i + 1] - host_supports_ptr_new[i]; + std::cout << "Source " << i << " has " << num_neighbors << " neighbors.\n"; + } + + // Perform second MLS interpolation: `target → source` + test_interpolation_point_to_mesh( + mesh, cutoffDistance, Reals(new_source_values), recovered_source_values, + Reals(new_source_coordinates), Reals(new_target_coordinates), + support_target_to_source + ); + + // Compare original vs recovered values + auto host_original_source_values = HostRead(source_values); + auto host_recovered_source_values = HostRead(recovered_source_values); + std::cout << "\nComparing Original vs. Recovered Te values (first 10 sources):\n"; + for (size_t i = 0; i < std::min(numSources, size_t(10)); ++i) { + std::cout << "Source " << i + << " | Original Te = " << host_original_source_values[i] + << " | Recovered Te = " << host_recovered_source_values[i] << "\n"; + } + + // Read source data from host memory + auto host_source_coords = HostRead(source_coordinates_flat); + auto host_original_Te = HostRead(source_values); + auto host_recovered_Te = HostRead(recovered_source_values); + + // Read target data from host memory + auto host_target_coords = HostRead(target_coordinates_flat); + auto host_target_Te = HostRead(target_values); // Target values after first interpolation + + // Save source data to source_points.txt + std::ofstream sourceFile { (data_dir / "source_points.txt").string() }; + sourceFile << "X_source Y_source Z_source Te_Original Te_Recovered\n"; + for (size_t i = 0; i < numSources; ++i) { + double x = host_source_coords[i * 3]; + double y = host_source_coords[i * 3 + 1]; + double z = host_source_coords[i * 3 + 2]; + double te_orig = host_original_Te[i]; + double te_recovered = host_recovered_Te[i]; + sourceFile << x << " " << y << " " << z << " " << te_orig << " " << te_recovered << "\n"; + } + sourceFile.close(); + + // Save target data to target_points.txt + std::ofstream targetFile { (data_dir / "target_points.txt").string() }; + targetFile << "X_target Y_target Z_target Te_Target_Interpolated\n"; + for (size_t i = 0; i < ntargets_filtered; ++i) { + double x = host_target_coords[i * 3]; + double y = host_target_coords[i * 3 + 1]; + double z = host_target_coords[i * 3 + 2]; + double te = host_target_Te[i]; + targetFile << x << " " << y << " " << z << " " << te << "\n"; + } + targetFile.close(); + + //Debug + double min_orig = std::numeric_limits::max(); + double max_orig = std::numeric_limits::lowest(); + double min_recv = std::numeric_limits::max(); + double max_recv = std::numeric_limits::lowest(); + for (size_t i = 0; i < numSources; ++i) { + double te_orig = host_original_Te[i]; + double te_recv = host_recovered_Te[i]; + if (te_orig < min_orig) min_orig = te_orig; + if (te_orig > max_orig) max_orig = te_orig; + if (te_recv < min_recv) min_recv = te_recv; + if (te_recv > max_recv) max_recv = te_recv; + } + double min_target = std::numeric_limits::max(); + double max_target = std::numeric_limits::lowest(); + for (size_t i = 0; i < ntargets_filtered; ++i) { + double te = host_target_Te[i]; + if (te < min_target) min_target = te; + if (te > max_target) max_target = te; + } + std::cout << "==== Temperature Range Summary ====\n"; + std::cout << "Te_Original : min = " << min_orig << ", max = " << max_orig << "\n"; + std::cout << "Te_Recovered : min = " << min_recv << ", max = " << max_recv << "\n"; + std::cout << "Te_Target : min = " << min_target << ", max = " << max_target << "\n"; + + std::cout << "Saved source data to source_points.txt\n"; + std::cout << "Saved target data to target_points.txt\n"; + } +} \ No newline at end of file diff --git a/test/test_n2_search_mls.cpp b/test/test_n2_search_mls.cpp new file mode 100644 index 00000000..60b66084 --- /dev/null +++ b/test/test_n2_search_mls.cpp @@ -0,0 +1,598 @@ +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +using namespace Omega_h; +using namespace pcms; + +// Convert cylindrical coordinates (R, Z, θ) to Cartesian (x, y, z) +std::vector> generateSourcePoints() { + const int radial = 20, toroidal = 10, poloidal = 20; + double R_min = 1.4, R_max = 2.6, Z_min = -0.6, Z_max = 0.6; + double dy = 0.18; + double dR = (R_max - R_min) / (radial - 1); + double dZ = (Z_max - Z_min) / (poloidal - 1); + + std::vector> source_points; + for (int i = 0; i < radial; ++i) { + double R = R_min + i * dR; + for (int j = 0; j < poloidal; ++j) { + double Z_val = Z_min + j * dZ; + for (int k = 0; k < toroidal; ++k) { + double theta = k * dy; + source_points.push_back({R * cos(theta), R * sin(theta), Z_val}); + } + } + } + return source_points; +} + +KOKKOS_INLINE_FUNCTION +double evaluatePolynomial(const Coord& p, int degree) { + auto x = p.x; + auto y = p.y; + auto z = p.z; + + if (degree == 0) { + return 3.0; + } else if (degree == 1) { + return x + y + z; + } else if (degree == 2) { + return (x * x) + (y * y) + (z * z); + } else if (degree == 3) { + return (x * x * x) + (y * y * y) + (z * z * z); + } else { + printf("No polynomials with degree = %d\n", degree); + return 0.0; + } +} + +// n² search to find neighbors (Brute force search) +inline SupportResults findNeighbors( + const std::vector>& host_source_points, + const std::vector>& host_target_points, + double cutoffDistance) { + + SupportResults results; + int numTargets = host_target_points.size(); + int numSources = host_source_points.size(); + double cutoffDistanceSq = cutoffDistance * cutoffDistance; + + if (numSources == 0 || numTargets == 0) { + std::cerr << "Warning: No source or target points provided!\n"; + return results; + } + + // Allocate storage + Write nSupports(numTargets, 0, "number of supports for each target"); + Write radii2(numTargets, cutoffDistanceSq, "squared radii of supports"); + + // Create Kokkos Views for device storage + Kokkos::View source_points("source_points", numSources, 3); + Kokkos::View target_points("target_points", numTargets, 3); + + // Create host mirrors + auto host_source_view = Kokkos::create_mirror_view(source_points); + auto host_target_view = Kokkos::create_mirror_view(target_points); + + // Copy data from std::vector to host mirror views + for (int i = 0; i < numSources; ++i) { + for (int d = 0; d < 3; ++d) { // 3D coordinates + host_source_view(i, d) = host_source_points[i][d]; + } + } + + for (int i = 0; i < numTargets; ++i) { + for (int d = 0; d < 3; ++d) { + host_target_view(i, d) = host_target_points[i][d]; + } + } + + // Copy from host mirror to device views + Kokkos::deep_copy(source_points, host_source_view); + Kokkos::deep_copy(target_points, host_target_view); + + // Count neighbors + Kokkos::parallel_for("count neighbors", numTargets, KOKKOS_LAMBDA(int i) { + int count = 0; + for (int j = 0; j < numSources; ++j) { + double dx = target_points(i, 0) - source_points(j, 0); + double dy = target_points(i, 1) - source_points(j, 1); + double dz = target_points(i, 2) - source_points(j, 2); + double dist_sq = dx * dx + dy * dy + dz * dz; + + if (dist_sq <= cutoffDistanceSq) { + count++; + } + } + nSupports[i] = count; + }); + + // Compute prefix sum (scan index) + Write supports_ptr(numTargets + 1, 0, "scan index"); + LO total_supports = 0; + Kokkos::parallel_scan( + "compute scan index", numTargets, + KOKKOS_LAMBDA(int j, int& update, bool final) { + update += nSupports[j]; + if (final) { + supports_ptr[j + 1] = update; + } + }, + total_supports); + + // Allocate storage for actual neighbor indices and distances + Write supports_idx(total_supports, 0, "neighbor indices"); + Write radii_vals(total_supports, 0, "neighbor squared distances"); + + // Fill neighbor indices + Kokkos::parallel_for("fill neighbor indices", numTargets, KOKKOS_LAMBDA(int i) { + int offset = supports_ptr[i]; + int count = 0; + for (int j = 0; j < numSources; ++j) { + double dx = target_points(i, 0) - source_points(j, 0); + double dy = target_points(i, 1) - source_points(j, 1); + double dz = target_points(i, 2) - source_points(j, 2); + double dist_sq = dx * dx + dy * dy + dz * dz; + + if (dist_sq <= cutoffDistanceSq) { + supports_idx[offset + count] = j; + radii_vals[offset + count] = dist_sq; + count++; + } + } + }); + + // Assign results + results.supports_ptr = supports_ptr; + results.supports_idx = supports_idx; + results.radii2 = radii_vals; + + return results; +} + +inline void test_interpolation_point_to_mesh(Mesh& mesh, Real cutoffDistance, int degree, LO min_num_supports, + Reals source_values, Reals exact_target_values, + Reals source_coordinates, Reals target_coordinates) +{ + int dim = mesh.dim(); + assert(dim==3); + Real tolerance = 0.05; + + std::vector rbf_types = { + RadialBasisFunction::RBF_GAUSSIAN, RadialBasisFunction::RBF_C4, + RadialBasisFunction::RBF_CONST + }; + + // Ensure `source_coordinates` and `target_coordinates` are valid + REQUIRE(source_coordinates.size() % dim == 0); + REQUIRE(target_coordinates.size() % dim == 0); + + size_t num_sources = source_coordinates.size() / dim; + size_t num_targets = target_coordinates.size() / dim; + + // Convert `Reals` to host std::vector> format + std::vector> host_source_data(num_sources, std::vector(dim)); + std::vector> host_target_data(num_targets, std::vector(dim)); + + // Read `Reals` into `HostRead` once to avoid redundant memory copies + auto host_source_coords = HostRead(source_coordinates); + auto host_target_coords = HostRead(target_coordinates); + + for (size_t i = 0; i < num_sources; ++i) { + for (int d = 0; d < dim; ++d) { + host_source_data[i][d] = host_source_coords[i * dim + d]; + } + } + for (size_t i = 0; i < num_targets; ++i) { + for (int d = 0; d < dim; ++d) { + host_target_data[i][d] = host_target_coords[i * dim + d]; + } + } + + // Perform neighbor search + SupportResults support = findNeighbors(host_source_data, host_target_data, cutoffDistance); + + // Ensure neighbor search results are valid + CHECK(support.supports_ptr.size() == num_targets + 1); + CHECK(support.supports_idx.size() > 0); // Ensure we found at least one neighbor + + for (const auto& rbf : rbf_types) { + auto approx_target_values = + mls_interpolation(source_values, source_coordinates, target_coordinates, + support, dim, degree, support.radii2, rbf); + + // Read exact and interpolated values from device memory + auto host_approx_target_values = HostRead(approx_target_values); + auto host_exact_target_values = HostRead(exact_target_values); + + int m = exact_target_values.size(); + int n = approx_target_values.size(); + + REQUIRE(m == n); + + // // Debugging + // for (size_t i = 0; i < 10; ++i) { // Check first 10 values + // std::cout << "Target " << i << " exact: " << host_exact_target_values[i] + // << ", approx: " << host_approx_target_values[i] << "\n"; + // } + + // double min_x = std::numeric_limits::max(); + // double max_x = std::numeric_limits::lowest(); + // double min_y = min_x, min_z = min_x; + // double max_y = max_x, max_z = max_x; + + // for (size_t i = 0; i < num_targets; ++i) { + // min_x = std::min(min_x, host_target_data[i][0]); + // min_y = std::min(min_y, host_target_data[i][1]); + // min_z = std::min(min_z, host_target_data[i][2]); + // max_x = std::max(max_x, host_target_data[i][0]); + // max_y = std::max(max_y, host_target_data[i][1]); + // max_z = std::max(max_z, host_target_data[i][2]); + // } + + // std::cout << "Filtered target bounding box: " + // << "[" << min_x << ", " << max_x << "] x " + // << "[" << min_y << ", " << max_y << "] x " + // << "[" << min_z << ", " << max_z << "]\n"; + + auto host_supports_ptr = HostRead(support.supports_ptr); + + for (size_t i = 0; i < m; ++i) { + int num_neighbors = host_supports_ptr[i + 1] - host_supports_ptr[i]; + if (num_neighbors >= min_num_supports) { + CHECK_THAT( + host_exact_target_values[i], + Catch::Matchers::WithinAbs(host_approx_target_values[i], tolerance)); + } + } + } +} + +TEST_CASE("point to mesh mls interp brute force search") { + auto lib = Library{}; + auto world = lib.world(); + + auto mesh = build_box(world, OMEGA_H_SIMPLEX, 5.2, 5.2, 1.2, 28, 28, 14, false); + + Real cutoffDistance = 0.2; + cutoffDistance = cutoffDistance * cutoffDistance; // Squared for efficiency + + const int dim = mesh.dim(); + const auto& target_coordinates = mesh.coords(); + const auto ntargets = mesh.nverts(); + + // Generate source points + auto source_data = generateSourcePoints(); + size_t numSources = source_data.size(); + + // // Convert mesh coordinates to host format + // std::vector> host_target_data(ntargets, std::vector(dim)); + // auto host_target_coords = HostRead(target_coordinates); + + // for (size_t i = 0; i < ntargets; ++i) { + // for (int d = 0; d < dim; ++d) { + // host_target_data[i][d] = host_target_coords[i * dim + d]; + // } + // } + + // Convert mesh coordinates to host format + std::vector> host_target_data; + auto host_target_coords = HostRead(target_coordinates); + + // Compute bounding box of source points + double min_x = std::numeric_limits::max(); + double min_y = std::numeric_limits::max(); + double min_z = std::numeric_limits::max(); + double max_x = std::numeric_limits::lowest(); + double max_y = std::numeric_limits::lowest(); + double max_z = std::numeric_limits::lowest(); + + for (const auto& point : source_data) { + min_x = std::min(min_x, point[0]); + min_y = std::min(min_y, point[1]); + min_z = std::min(min_z, point[2]); + max_x = std::max(max_x, point[0]); + max_y = std::max(max_y, point[1]); + max_z = std::max(max_z, point[2]); + } + + // Now filter target points using this bounding box + for (size_t i = 0; i < ntargets; ++i) { + double x = host_target_coords[i * 3]; + double y = host_target_coords[i * 3 + 1]; + double z = host_target_coords[i * 3 + 2]; + + double r = sqrt(x * x + y * y); // Compute radial distance + + if (x >= min_x && x <= max_x && + y >= min_y && y <= max_y && + z >= min_z && z <= max_z && + r >= 1.4 && r <= 2.6) { + host_target_data.push_back({x, y, z}); + } + } + + // Update `ntargets` to reflect the filtered number of points + const auto ntargets_filtered = host_target_data.size(); + + // Define new variable for filtered target coordinates + Write target_coordinates_filtered(ntargets_filtered * 3, 0.0, "target coordinates filtered"); + + // Create a Kokkos View for host_target_data + Kokkos::View host_target_data_view("host_target_data_view", ntargets_filtered, 3); + + // Copy host_target_data into the Kokkos View + auto host_mirror = Kokkos::create_mirror_view(host_target_data_view); + for (size_t i = 0; i < ntargets_filtered; ++i) { + for (int d = 0; d < 3; ++d) { + host_mirror(i, d) = host_target_data[i][d]; + } + } + Kokkos::deep_copy(host_target_data_view, host_mirror); + + // Fill target_coordinates_filtered using Kokkos parallel_for + Kokkos::parallel_for("fill target_coordinates_filtered", ntargets_filtered, KOKKOS_LAMBDA(int i) { + target_coordinates_filtered[i * 3] = host_target_data_view(i, 0); + target_coordinates_filtered[i * 3 + 1] = host_target_data_view(i, 1); + target_coordinates_filtered[i * 3 + 2] = host_target_data_view(i, 2); + }); + + // Run the neighbor search function + SupportResults support = findNeighbors(source_data, host_target_data, cutoffDistance); + + auto host_supports_ptr = HostRead(support.supports_ptr); + auto host_supports_idx = HostRead(support.supports_idx); + auto host_radii2 = HostRead(support.radii2); + + // Ensure at least one neighbor is found + CHECK(host_supports_ptr[ntargets_filtered] > 0); + + // Ensure supports_ptr size is correct + CHECK(support.supports_ptr.size() == ntargets_filtered + 1); + + // Ensure supports_ptr is non-decreasing + for (size_t i = 0; i < ntargets_filtered; ++i) { + CHECK(host_supports_ptr[i] <= host_supports_ptr[i + 1]); + } + + // Ensure first and last values are correct + CHECK(host_supports_ptr[0] == 0); + CHECK(host_supports_ptr[ntargets_filtered] == support.supports_idx.size()); + + // Check that each target has at least one neighbor + for (size_t i = 0; i < ntargets_filtered; ++i) { + int num_neighbors = host_supports_ptr[i + 1] - host_supports_ptr[i]; + CHECK(num_neighbors >= 0); + } + + // Check that found neighbors are actually within the cutoff distance + const auto host_source_data = source_data; + + for (size_t i = 0; i < ntargets_filtered; ++i) { + int start_idx = host_supports_ptr[i]; + int end_idx = host_supports_ptr[i + 1]; + + for (int j = start_idx; j < end_idx; ++j) { + int neighbor_index = host_supports_idx[j]; + + double dx = host_target_data[i][0] - host_source_data[neighbor_index][0]; + double dy = host_target_data[i][1] - host_source_data[neighbor_index][1]; + double dz = host_target_data[i][2] - host_source_data[neighbor_index][2]; + + double dist_sq = dx * dx + dy * dy + dz * dz; + CHECK(dist_sq <= cutoffDistance); + } + } + + // Check that every neighbor is counted only once per target + for (size_t i = 0; i < ntargets_filtered; ++i) { + int start_idx = host_supports_ptr[i]; + int end_idx = host_supports_ptr[i + 1]; + + std::unordered_set unique_neighbors; + + for (int j = start_idx; j < end_idx; ++j) { + int neighbor_index = host_supports_idx[j]; + CHECK(unique_neighbors.find(neighbor_index) == unique_neighbors.end()); + unique_neighbors.insert(neighbor_index); + } + } + + // Convert source points to a GPU-compatible Kokkos View + Kokkos::View source_view("source_view", numSources, 3); + auto host_source_view = Kokkos::create_mirror_view(source_view); + + for (size_t i = 0; i < numSources; ++i) { + for (int d = 0; d < 3; ++d) { + host_source_view(i, d) = source_data[i][d]; + } + } + + // Copy data from host to device + Kokkos::deep_copy(source_view, host_source_view); + + // Convert source points to flat `Reals` array for MLS + Write source_coordinates(dim * numSources, 0.0, "source coordinates"); + + Kokkos::parallel_for("convert source_data", numSources, KOKKOS_LAMBDA(const size_t i) { + source_coordinates[i * dim] = source_view(i, 0); + source_coordinates[i * dim + 1] = source_view(i, 1); + source_coordinates[i * dim + 2] = source_view(i, 2); + }); + + // Convert target points to a Kokkos View + Kokkos::View target_view("target_view", ntargets_filtered, 3); + auto host_target_view = Kokkos::create_mirror_view(target_view); + + for (size_t i = 0; i < ntargets_filtered; ++i) { + for (int d = 0; d < dim; ++d) { + // host_target_view(i, d) = host_target_coords[i * dim + d]; + host_target_view(i, d) = host_target_data[i][d]; + } + } + + // Copy from host to device + Kokkos::deep_copy(target_view, host_target_view); + + SECTION("MLS interpolation with isolated target") { + // auto host_source_data = generateSourcePoints(gridData); + auto host_source_data = generateSourcePoints(); + std::vector> isolated_target_data = { {100, 100, 100} }; // Far from all sources + + SupportResults support = findNeighbors(host_source_data, isolated_target_data, cutoffDistance); + + CHECK(support.supports_idx.size() == 0); // No neighbors + CHECK(support.supports_ptr.size() == 2); // Should still be valid + } + + SECTION("MLS degree 1, poly 0") { + int degree = 1; + LO min_num_supports = 10; + + Write source_values(numSources, 0.0, "source values"); + Write exact_target_values(ntargets_filtered, 0.0, "exact target values"); + + Kokkos::parallel_for("assign source values", numSources, KOKKOS_LAMBDA(const size_t i) { + Coord p; + p.x = source_view(i, 0); + p.y = source_view(i, 1); + p.z = source_view(i, 2); + source_values[i] = evaluatePolynomial(p, degree - 1); + }); + + Kokkos::parallel_for("compute exact target values", ntargets_filtered, KOKKOS_LAMBDA(int i) { + Coord p; + p.x = target_view(i, 0); + p.y = target_view(i, 1); + p.z = target_view(i, 2); + exact_target_values[i] = evaluatePolynomial(p, degree - 1); + }); + + test_interpolation_point_to_mesh(mesh, cutoffDistance, degree, min_num_supports, + Reals(source_values), Reals(exact_target_values), + Reals(source_coordinates), Reals(target_coordinates_filtered)); + } + + SECTION("MLS degree 1, poly 1") { + int degree = 1; + LO min_num_supports = 10; + + Write source_values(numSources, 0.0, "source values"); + Write exact_target_values(ntargets_filtered, 0.0, "exact target values"); + + Kokkos::parallel_for("assign source values", numSources, KOKKOS_LAMBDA(const size_t i) { + Coord p; + p.x = source_view(i, 0); + p.y = source_view(i, 1); + p.z = source_view(i, 2); + source_values[i] = evaluatePolynomial(p, degree); + }); + + Kokkos::parallel_for("compute exact target values", ntargets_filtered, KOKKOS_LAMBDA(int i) { + Coord p; + p.x = target_view(i, 0); + p.y = target_view(i, 1); + p.z = target_view(i, 2); + exact_target_values[i] = evaluatePolynomial(p, degree); + }); + + test_interpolation_point_to_mesh(mesh, cutoffDistance, degree, min_num_supports, + Reals(source_values), Reals(exact_target_values), + Reals(source_coordinates), Reals(target_coordinates_filtered)); + } + + SECTION("MLS degree 2, poly 0") { + int degree = 2; + LO min_num_supports = 16; + + Write source_values(numSources, 0.0, "source values"); + Write exact_target_values(ntargets_filtered, 0.0, "exact target values"); + + Kokkos::parallel_for("assign source values", numSources, KOKKOS_LAMBDA(const size_t i) { + Coord p; + p.x = source_view(i, 0); + p.y = source_view(i, 1); + p.z = source_view(i, 2); + source_values[i] = evaluatePolynomial(p, degree - 2); // Polynomial degree 0 + }); + + Kokkos::parallel_for("compute exact target values", ntargets_filtered, KOKKOS_LAMBDA(int i) { + Coord p; + p.x = target_view(i, 0); + p.y = target_view(i, 1); + p.z = target_view(i, 2); + exact_target_values[i] = evaluatePolynomial(p, degree - 2); // Polynomial degree 0 + }); + + test_interpolation_point_to_mesh(mesh, cutoffDistance, degree, min_num_supports, + Reals(source_values), Reals(exact_target_values), + Reals(source_coordinates), Reals(target_coordinates_filtered)); + } + + SECTION("MLS degree 2, poly 1") { + int degree = 2; + LO min_num_supports = 16; + + Write source_values(numSources, 0.0, "source values"); + Write exact_target_values(ntargets_filtered, 0.0, "exact target values"); + + Kokkos::parallel_for("assign source values", numSources, KOKKOS_LAMBDA(const size_t i) { + Coord p; + p.x = source_view(i, 0); + p.y = source_view(i, 1); + p.z = source_view(i, 2); + source_values[i] = evaluatePolynomial(p, degree - 1); // Polynomial degree 1 + }); + + Kokkos::parallel_for("compute exact target values", ntargets_filtered, KOKKOS_LAMBDA(int i) { + Coord p; + p.x = target_view(i, 0); + p.y = target_view(i, 1); + p.z = target_view(i, 2); + exact_target_values[i] = evaluatePolynomial(p, degree - 1); // Polynomial degree 1 + }); + + test_interpolation_point_to_mesh(mesh, cutoffDistance, degree, min_num_supports, + Reals(source_values), Reals(exact_target_values), + Reals(source_coordinates), Reals(target_coordinates_filtered)); + } + + SECTION("MLS degree 2, poly 2") { + int degree = 2; + LO min_num_supports = 16; + + Write source_values(numSources, 0.0, "source values"); + Write exact_target_values(ntargets_filtered, 0.0, "exact target values"); + + Kokkos::parallel_for("assign source values", numSources, KOKKOS_LAMBDA(const size_t i) { + Coord p; + p.x = source_view(i, 0); + p.y = source_view(i, 1); + p.z = source_view(i, 2); + source_values[i] = evaluatePolynomial(p, degree); // Polynomial degree 2 + }); + + Kokkos::parallel_for("compute exact target values", ntargets_filtered, KOKKOS_LAMBDA(int i) { + Coord p; + p.x = target_view(i, 0); + p.y = target_view(i, 1); + p.z = target_view(i, 2); + exact_target_values[i] = evaluatePolynomial(p, degree); // Polynomial degree 2 + }); + + test_interpolation_point_to_mesh(mesh, cutoffDistance, degree, min_num_supports, + Reals(source_values), Reals(exact_target_values), + Reals(source_coordinates), Reals(target_coordinates_filtered)); + } +} \ No newline at end of file diff --git a/test/test_point_search.cpp b/test/test_point_search.cpp index c14a8599..d01548a2 100644 --- a/test/test_point_search.cpp +++ b/test/test_point_search.cpp @@ -228,3 +228,152 @@ TEST_CASE("uniform grid search") { REQUIRE(-1 * out_of_bounds.tri_id == bot_left.tri_id); } } + +TEST_CASE("radial_intersects_bbox 2D") { + using pcms::detail::radial_intersects_bbox; + using pcms::AABBox; + + AABBox<2> box{.center = {0.0, 0.0}, .half_width = {0.5, 0.5}}; + double cutoff_squared = 0.25; + + SECTION("Point outside cutoff") { + double pt[2] = {1.5, 0.0}; + REQUIRE_FALSE(radial_intersects_bbox<2>(pt, box, cutoff_squared)); + } + + SECTION("Point on edge of cutoff") { + double pt[2] = {1.0, 0.0}; + REQUIRE(radial_intersects_bbox<2>(pt, box, 1.0)); + } + + SECTION("Point inside AABB") { + double pt[2] = {0.0, 0.0}; + REQUIRE(radial_intersects_bbox<2>(pt, box, cutoff_squared)); + } + + SECTION("Point close to corner") { + double pt[2] = {0.8, 0.8}; + REQUIRE_FALSE(radial_intersects_bbox<2>(pt, box, 0.1)); + REQUIRE(radial_intersects_bbox<2>(pt, box, 0.64)); + } + + SECTION("Radial region partially overlaps box") { + double pt[2] = {1.0, 0.0}; + REQUIRE(radial_intersects_bbox<2>(pt, box, 0.3)); // cutoff_squared=0.3 (~0.55 radius) + } + + SECTION("Point on AABB edge") { + double pt[2] = {0.5, 0.0}; // Exactly on the box edge + REQUIRE(radial_intersects_bbox<2>(pt, box, 0.25)); + } + + SECTION("Negative coordinate check") { + double pt[2] = {-1.5, 0.0}; + REQUIRE_FALSE(radial_intersects_bbox<2>(pt, box, 0.25)); + } + + SECTION("Excess in one axis only") { + double pt[2] = {1.0, 0.0}; // Excess in x-axis but within y-axis + REQUIRE(radial_intersects_bbox<2>(pt, box, 1.0)); + } +} + +TEST_CASE("GridRadialNeighborFunctor 2D") { + using namespace pcms; + using detail::GridRadialNeighborFunctor; + + const int dim = 2; + const int num_sources = 4; + const int num_targets = 2; + double cutoff = 1.0; + + // Allocate Views in the default memory space (device if enabled) + Kokkos::View sources("sources", num_sources, dim); + Kokkos::View targets("targets", num_targets, dim); + + // Initialize via host mirrors + auto hsources = Kokkos::create_mirror_view(sources); + auto htargets = Kokkos::create_mirror_view(targets); + + // Source points (2x2 grid) + hsources(0,0) = 0.0; hsources(0,1) = 0.0; + hsources(1,0) = 1.0; hsources(1,1) = 0.0; + hsources(2,0) = 0.0; hsources(2,1) = 1.0; + hsources(3,0) = 1.0; hsources(3,1) = 1.0; + + // Target points + htargets(0,0) = 0.5; htargets(0,1) = 0.5; // Center + htargets(1,0) = 2.0; htargets(1,1) = 2.0; // Outside + + Kokkos::deep_copy(sources, hsources); + Kokkos::deep_copy(targets, htargets); + + // Grid setup matching production code + UniformGrid<2> grid; + grid.bot_left = {-0.5, -0.5}; + grid.edge_length = {2.0, 2.0}; + grid.divisions = {2, 2}; + + Kokkos::View*> grid_view("grid", 1); + auto hgrid = Kokkos::create_mirror_view(grid_view); + hgrid(0) = grid; + Kokkos::deep_copy(grid_view, hgrid); + + // Compute cell_size and copy to device + std::array cell_size_host; + for (int d = 0; d < 2; ++d) + cell_size_host[d] = grid.edge_length[d] / grid.divisions[d]; + + Kokkos::View cell_size_view("cell_size_view"); + auto h_cell_size_view = Kokkos::create_mirror_view(cell_size_view); + for (int d = 0; d < 2; ++d) + h_cell_size_view(d) = cell_size_host[d]; + Kokkos::deep_copy(cell_size_view, h_cell_size_view); + + // Cell data initialization (all sources in cell 0) + Kokkos::View cell_ptrs("cell_ptrs", 5); + Kokkos::View cell_indices("cell_indices", 4); + + auto hptrs = Kokkos::create_mirror_view(cell_ptrs); + auto hidx = Kokkos::create_mirror_view(cell_indices); + hptrs(0) = 0; hptrs(1) = 4; hptrs(2) = 4; hptrs(3) = 4; hptrs(4) = 4; + for (int i=0; i<4; ++i) hidx(i) = i; + + Kokkos::deep_copy(cell_ptrs, hptrs); + Kokkos::deep_copy(cell_indices, hidx); + + // Updated functor with cell_size_view + GridRadialNeighborFunctor<2> functor( + targets, sources, grid_view, cell_ptrs, cell_indices, cutoff, 4, cell_size_view + ); + + SECTION("Target inside should find 4 neighbors") { + Kokkos::View d_neighbors("neighbors", 4); + Kokkos::View d_count("count"); + + Kokkos::parallel_for("test_inside", 1, KOKKOS_LAMBDA(const int) { + d_count() = functor(0, d_neighbors.data()); + }); + + auto h_count = Kokkos::create_mirror_view(d_count); + auto h_neighbors = Kokkos::create_mirror_view(d_neighbors); + Kokkos::deep_copy(h_count, d_count); + Kokkos::deep_copy(h_neighbors, d_neighbors); + + REQUIRE(h_count() == 4); + } + + SECTION("Target outside should find no neighbors") { + Kokkos::View d_neighbors("neighbors", 4); + Kokkos::View d_count("count"); + + Kokkos::parallel_for("test_outside", 1, KOKKOS_LAMBDA(const int) { + d_count() = functor(1, d_neighbors.data()); + }); + + auto h_count = Kokkos::create_mirror_view(d_count); + Kokkos::deep_copy(h_count, d_count); + + REQUIRE(h_count() == 0); + } +} \ No newline at end of file