我试图用RcppArmadillo并行化一个double for循环,但是我对RMatrixRVector可用的算术运算有麻烦。我查看了github上可用的 header file,但那里什么都没有看到,所以我想我在错误的位置查找。这是我的工作人员,我评论了我试图在两个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。

最佳答案

基本上,您不能像使用常规Rcpp vector 那样减去两个Row对象(即,利用所谓的Rcpp sugar)-只是RcppParallel包装器未实现。您必须自己编写迭代。

关于c++ - RcppParallel:RMatrix和RVector算术运算,我们在Stack Overflow上找到一个类似的问题:https://stackoverflow.com/questions/34862702/

10-11 14:38