我试图用RcppArmadillo
并行化一个double for循环,但是我对RMatrix
和RVector
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/