r - 查找目标数字之间所有数字的最快方法

Question

给定向量中的数字(例如 1 5 10 12)，我正在寻找向量中落在我选择的数字范围之间的数字(例如 c(9, 11))。我希望在这个小例子中返回 vec = c(10) 。

下面是一个更大的 MWE，我使用 dplyr::between 对相关值进行子集化...但是，我正在寻找一种更快的方法来执行此操作(不使用并行化作为解决方案)。如果我可以更好地解释一些事情，请告诉我。

# Data
set.seed(1)
targets <- sort(sample(1:1e8, 1e7, replace=FALSE))
vec <- c(1345706, 1405938)

# Function
dplyr_between <- function(vec, targets) {
            require(dplyr)
            targets <- targets[dplyr::between(targets, vec[1], vec[2])]
            return(targets)
        }

test <- dplyr_between(vec, targets)
# 1345732 1345761 1345779 1345780 1345797

编辑使用 x < max & x > min 添加基于评论的功能(已删除)

# More Functions
base_compare <- function(vec, targets) {
            targets <- targets[targets < vec[2] & targets > vec[1]]
            return(targets)
        }

base_compare(vec, targets)
# 1345732 1345761 1345779 1345780 1345797

使用 @docendo 中的 data.table::inrange 进行编辑

# inrange function
dt_inrange <- function(vec, targets) {
            require(data.table)
            targets <- targets[inrange(targets, vec[1], vec[2])]
            return(targets)
        }

dt_inrange(vec, targets)
# 1345732 1345761 1345779 1345780 1345797

基准

library(microbenchmark)
microbenchmark(dplyr_between(vec, targets), base_compare(vec, targets), dt_inrange(vec, targets), times=10L)
# Unit: milliseconds
                       # expr      min       lq     mean   median       uq      max
# dplyr_between(vec, targets) 265.5192 283.5998 296.0947 296.7552 309.4403 323.3634
#  base_compare(vec, targets) 303.4629 317.8389 343.6311 343.3765 354.6891 427.1962
#    dt_inrange(vec, targets) 129.3800 131.1634 142.8658 144.4569 149.3728 164.5824
 # neval
    # 10
    # 10
    # 10

谢谢!

Answer 1

简单的 Rcpp 实现:

temp.cpp 中的 C++ 代码”

#include <Rcpp.h>
#include <vector>

using namespace Rcpp;
// [[Rcpp::plugins(cpp11)]]
// [[Rcpp::export]]
std::vector<int> betweenRcpp(IntegerVector vec, int lower, int upper) {
  std::vector<int> ret;
  for(int i=0; i<vec.size(); i++) {
    if((vec[i] > lower) & (vec[i] < upper)) {
      ret.push_back(vec[i]);
    } else if(vec[i] >= upper) {
      break;
    }
  }
  return ret;
}

R代码:

library(Rcpp)
library(microbenchmark)
setwd("~/Desktop")
# Data
set.seed(1)
targets <- sort(sample(1:1e8, 1e7, replace=FALSE))
vec <- c(1345706, 1405938)

# Function
dplyr_between <- function(vec, targets) {
  require(dplyr)
  targets <- targets[dplyr::between(targets, vec[1], vec[2])]
  return(targets)
}

sourceCpp("temp.cpp")

test <- dplyr_between(vec, targets)
test2 <- betweenRcpp(targets, vec[1], vec[2])

microbenchmark(dplyr_between(vec, targets), betweenRcpp(targets, vec[1], vec[2]), times=10)


Unit: microseconds
                                 expr       min        lq        mean      median        uq        max neval cld
          dplyr_between(vec, targets) 72066.027 77809.681 108023.3793 103723.4075 125280.89 173892.552    10   b
 betweenRcpp(targets, vec[1], vec[2])   439.124   464.475    502.7439    481.8025    543.12    594.578    10  a 

测试解决方案之间的相等性:

all(test == test2)