Developer Reference

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Examples

The following example demonstrates how to construct the linear spline and perform the interpolation.
#include <cstdint> #include <iostream> #include <vector> #include <CL/sycl.hpp> #include <oneapi/mkl/experimental/data_fitting.hpp> constexpr std::int64_t nx = 10'000; constexpr std::int64_t nsites = 150'000; int main (int argc, char ** argv) { sycl::queue q; sycl::usm_allocator<double, sycl::usm::alloc::shared> alloc(q); // Allocate memory for spline parameters std::vector<double, decltype(alloc)> partitions(nx, alloc); std::vector<double, decltype(alloc)> functions(nx, alloc); std::vector<double, decltype(alloc)> coeffs(2 * (nx - 1), alloc); std::vector<double, decltype(alloc)> sites(nsites, alloc); std::vector<double, decltype(alloc)> results(nsites, alloc); // Fill parameters with valid data for (std::int64_t i = 0; i < nx; ++i) { partitions[i] = 0.1 * i; functions[i] = i * i; } for (std::int64_t i = 0; i < nsites; ++i) { sites[i] = (0.1 * nx * i) / nsites); } namespace df = oneapi::mkl::experimental::data_fitting; // Set parameters to spline df::spline<double, df::linear_spline::default_type> spl(q); spl.set_partitions(partitions.data(), nx) .set_coefficients(coeffs.data()) .set_function_values(functions.data()); // Construct spline auto event = spl.construct(); event = df::interpolate(spl, sites.data(), nsites, results.data(), { event }); event.wait(); std::cout << "done" << std::endl; return 0; }

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