#pragma once #include "nlohmann/json.hpp" #include <set> #include <filesystem> #include <fstream> #include "teqp/exceptions.hpp" namespace teqp{ /// Load a JSON file from a specified file inline nlohmann::json load_a_JSON_file(const std::string& path) { if (!std::filesystem::is_regular_file(path)) { throw std::invalid_argument("Path to be loaded does not exist: " + path); } auto stream = std::ifstream(path); if (!stream) { throw std::invalid_argument("File stream cannot be opened from: " + path); } try { return nlohmann::json::parse(stream); } catch (...) { throw std::invalid_argument("File at " + path + " is not valid JSON"); } } inline auto all_same_length(const nlohmann::json& j, const std::vector<std::string>& ks) { std::set<decltype(j[0].size())> lengths; for (auto k : ks) { lengths.insert(j.at(k).size()); } return lengths.size() == 1; } auto build_square_matrix = [](const nlohmann::json& j){ if (j.is_null() || (j.is_array() && j.size() == 0)){ return Eigen::ArrayXXd(0, 0); } try{ const std::valarray<std::valarray<double>> m = j; // First assume that the matrix is square, resize Eigen::ArrayXXd mat(m.size(), m.size()); if (m.size() == 0){ return mat; } // Then copy elements over for (auto i = 0; i < m.size(); ++i){ auto row = m[i]; if (row.size() != mat.rows()){ throw std::invalid_argument("provided matrix is not square"); } for (auto j = 0; j < row.size(); ++j){ mat(i, j) = row[j]; } } return mat; } catch(const nlohmann::json::exception&){ throw teqp::InvalidArgument("Unable to convert this kmat to a 2x2 matrix of doubles:" + j.dump(2)); } }; }