// // Copyright 2016 Ettus Research // // SPDX-License-Identifier: GPL-3.0 // #ifndef INCLUDED_UHD_INTERPOLATION_IPP #define INCLUDED_UHD_INTERPOLATION_IPP #include "interpolation.hpp" #include // This is a bugfix for Boost 1.64, maybe future Boosts won't need this #if BOOST_VERSION >= 106400 # include #endif // end of bugfix #include #include #include using namespace boost::numeric; namespace uhd { namespace cal { #define CAL_INTERP_METHOD(return_type, method, args, ...) \ template \ return_type interp::\ method(args, __VA_ARGS__) #define ARGS_T typename interp::args_t #define CONTAINER_T typename interp::container_t CAL_INTERP_METHOD(in_type, calc_dist, const ARGS_T &a, const ARGS_T &b) { in_type dist = 0; for (size_t i = 0; i < std::min(a.size(), b.size()); i++) { dist += std::abs(a[i] - b[i]); } return dist; } CAL_INTERP_METHOD(const out_type, nn_interp, CONTAINER_T &data, const ARGS_T &args) { // Check the cache for the output if (data.find(args) != data.end()) { return data[args]; } out_type output = 0; in_type min_dist = 0; typename container_t::const_iterator citer; for (citer = data.begin(); citer != data.end(); citer++) { in_type dist = calc_dist(citer->first, args); if (citer == data.begin() || dist < min_dist) { min_dist = dist; output = data[citer->first]; } } return output; } CAL_INTERP_METHOD(const out_type, bl_interp, CONTAINER_T &data, const ARGS_T &args) { if (args.size() != 2) { throw uhd::assertion_error(str(boost::format( "Bilinear interpolation expects 2D values. Received %d.") % args.size() )); } if (data.size() < 4) { throw uhd::assertion_error(str(boost::format( "Bilinear interpolation requires at least 4 input points. Found %d.") % data.size() )); } // Locate the nearest 4 points typedef std::pair::args_t, out_type> cal_pair_t; typename std::vector nearest; // Initialize the resulting pair to something cal_pair_t pair = *data.begin(); for (size_t i = 0; i < 4; i++) { bool init = true; in_type min_dist = 0; typename container_t::const_iterator citer; for (citer = data.begin(); citer != data.end(); citer++) { cal_pair_t temp = *citer; if (std::find(nearest.begin(), nearest.end(), temp) == nearest.end()) { in_type dist = calc_dist(citer->first, args); if (dist < min_dist || init) { min_dist = dist; pair = temp; init = false; } } } // Push back the nearest pair nearest.push_back(pair); } // // Since these points are not grid aligned, // we perform irregular bilinear interpolation. // This math involves finding our interpolation // function using lagrange multipliers: // // f(x, y) = ax^2 + bxy + cy^2 + dx + ey + f // // The solution is to solve the following system: // // A x b // | E X' | | s | - | 0 | // | X 0 | | l | - | z | // // where s is a vector of the above coefficients. // typename ublas::matrix A(10, 10, 0.0); // E A(0, 0) = 1.0; A(1, 1) = 1.0; A(2, 2) = 1.0; in_type x1, x2, x3, x4; in_type y1, y2, y3, y4; x1 = nearest[0].first[0]; y1 = nearest[0].first[1]; x2 = nearest[1].first[0]; y2 = nearest[1].first[1]; x3 = nearest[2].first[0]; y3 = nearest[2].first[1]; x4 = nearest[3].first[0]; y4 = nearest[3].first[1]; // X A(0, 6) = x1*x1; A(1, 6) = x1*y1; A(2, 6) = y1*y1; A(3, 6) = x1; A(4, 6) = y1; A(5, 6) = 1.0; A(0, 7) = x2*x2; A(1, 7) = x2*y2; A(2, 7) = y2*y2; A(3, 7) = x2; A(4, 7) = y2; A(5, 7) = 1.0; A(0, 8) = x3*x3; A(1, 8) = x3*y3; A(2, 8) = y3*y3; A(3, 8) = x3; A(4, 8) = y3; A(5, 8) = 1.0; A(0, 9) = x4*x4; A(1, 9) = x4*y4; A(2, 9) = y4*y4; A(3, 9) = x4; A(4, 9) = y4; A(5, 9) = 1.0; // X' A(6, 0) = x1*x1; A(6, 1) = x1*y1; A(6, 2) = y1*y1; A(6, 3) = x1; A(6, 4) = y1; A(6, 5) = 1.0; A(7, 0) = x2*x2; A(7, 1) = x2*y2; A(7, 2) = y2*y2; A(7, 3) = x2; A(7, 4) = y2; A(7, 5) = 1.0; A(8, 0) = x3*x3; A(8, 1) = x3*y3; A(8, 2) = y3*y3; A(8, 3) = x3; A(8, 4) = y3; A(8, 5) = 1.0; A(9, 0) = x4*x4; A(9, 1) = x4*y4; A(9, 2) = y4*y4; A(9, 3) = x4; A(9, 4) = y4; A(9, 5) = 1.0; // z typename ublas::vector b(10, 0.0); b(6) = nearest[0].second; b(7) = nearest[1].second; b(8) = nearest[2].second; b(9) = nearest[3].second; typename ublas::matrix A_t = A; typename ublas::vector s = b; typename ublas::permutation_matrix P(A_t.size1()); // Use LUP factorization to solve for the coefficients // We're solving the problem in the form of Ax = b bool is_singular = ublas::lu_factorize(A_t, P); out_type output = 0; // Fall back to 1D interpolation if the matrix is singular if (is_singular) { // Warn the user that the A matrix is singular UHD_LOGGER_WARNING("CAL") << "Bilinear interpolation: singular matrix detected. " << "Performing 1D linear interpolation against the nearest measurements. " << "Provide calibration data with more measurements"; output = (b[7] - b[6]) / 2.0; output += b[6]; return output; } ublas::lu_substitute(A_t, P, s); in_type x = args[0]; in_type y = args[1]; // Utilize the solution to calculate the interpolation function output = s[0]*x*x + s[1]*x*y + s[2]*y*y + s[3]*x + s[4]*y + s[5]; return output; } } // namespace cal } // namespace uhd #endif /* INCLUDED_UHD_INTERPOLATION_IPP */