RcppParallel:RMatrix 和 RVector 算术运算

我正在尝试使用 RcppArmadillo 并行化双精度 for 循环，但我在 RMatrix 和 RVector 可用的算术运算方面遇到了问题。我查看了 github 上可用的头文件，但我在那里没有看到任何东西，所以我想我找错了地方。这是我的工作线程，我评论了我尝试在两个RMatrix对象之间进行算术运算的地方。

#include <RcppParallel.h>
#include <iostream>
#include <algorithm>
#include <cmath>
#include <Rmath.h>
#include <RcppArmadillo.h>
using namespace RcppParallel;

struct ClosestMean : public Worker {
  // Input data and means matrix
  const RMatrix<double> input_data;
  const RMatrix<double> means;
  // Output labels
  RVector<int> predicted_labels;
  // constructor
  ClosestMean(const Rcpp::NumericMatrix input_data, const Rcpp::NumericMatrix means, Rcpp::IntegerVector predicted_labels)
    : input_data(input_data), means(means), predicted_labels(predicted_labels) {}
  // function call operator for the specified range (begin/end)
  void operator () (std::size_t begin, std::size_t end){
    for (unsigned int i = begin; i < end; i++){
      // Check for User Interrupts
      Rcpp::checkUserInterrupt();
      // Get the label corresponding to the cluster mean
      // for which the point is closest to
      RMatrix<double>::Row point = input_data.row(i);
      int label_min = -1;
      double dist;
      double min_dist = INFINITY;
      for (unsigned int j = 0; j < means.nrow(); j++){
        RMatrix<double>::Row mean = means.row(j);
        dist = sqrt(Rcpp::sum((mean - point)^2)); // This is where the operation is failing
        if (dist < min_dist){
          min_dist = dist;
          label_min = j;
        }
      }
      predicted_labels[i] = label_min;
    }
  }
};

感谢您的任何建议。