使用C++ Boost库并行计算物种矩阵的相对丰度

{///'#include///' //n#include///' //n#include///' //n#include///' <boost/algorithm/string.hpp>//n#include///' <boost/range/algorithm.hpp>//n#include///' <boost/numeric/ublas/matrix.hpp>//n#include///' <boost/numeric/ublas/io.hpp>//n#include///' <boost/thread/thread.hpp>//n//nusing namespace boost::numeric::ublas;//n//n// Function to calculate the relative abundance of each species//nvoid calculateRelativeAbundance(matrix& data) {//n // Get the sum of each column (species)//n vector colSums(data.size2(), 0.0);//n for (std::size_t j = 0; j < data.size2(); ++j) {//n for (std::size_t i = 0; i < data.size1(); ++i) {//n colSums[j] += data(i, j);//n }//n }//n//n // Calculate the relative abundance for each cell//n for (std::size_t j = 0; j < data.size2(); ++j) {//n for (std::size_t i = 0; i < data.size1(); ++i) {//n data(i, j) /= colSums[j];//n }//n }//n}//n//nint main() {//n // Read the species matrix from a file//n std::ifstream file(///'species_matrix.txt///');//n std::string line;//n std::vectorstd::string rowNames;//n std::vectorstd::string colNames;//n std::vector<std::vector> values;//n while (std::getline(file, line)) {//n std::vectorstd::string tokens;//n boost::split(tokens, line, boost::is_any_of(///'//t///'));//n if (rowNames.empty()) {//n colNames = tokens;//n } else {//n rowNames.push_back(tokens[0]);//n tokens.erase(tokens.begin());//n std::vector rowValues;//n for (const auto& token : tokens) {//n rowValues.push_back(std::stod(token));//n }//n values.push_back(rowValues);//n }//n }//n file.close();//n//n // Create the species matrix//n matrix data(values.size(), colNames.size());//n for (std::size_t i = 0; i < values.size(); ++i) {//n for (std::size_t j = 0; j < values[i].size(); ++j) {//n data(i, j) = values[i][j];//n }//n }//n//n // Perform parallel computation of relative abundance//n boost::thread_group threads;//n for (std::size_t i = 0; i < boost::thread::hardware_concurrency(); ++i) {//n threads.create_thread(boost::bind(&calculateRelativeAbundance, boost::ref(data)));//n }//n threads.join_all();//n//n // Output the resulting matrix//n for (std::size_t i = 0; i < data.size1(); ++i) {//n std::cout << rowNames[i] << ///'//t///';//n for (std::size_t j = 0; j < data.size2(); ++j) {//n std::cout << data(i, j) << ///'//t///';//n }//n std::cout << std::endl;//n }//n//n return 0;//n}//n/