使用Rcpp

Question

目前我在这里测试数字相等性，如果x是数字且y是向量，则它可以正常工作。

almostEqual <- function(x, y, tolerance=1e-8) {
  diff <- abs(x - y)
  mag <- pmax( abs(x), abs(y) )
  ifelse( mag > tolerance, diff/mag <= tolerance, diff <= tolerance)
}

示例：

almostEqual(1,c(1,1.00000000000001,1.00002))
[1]  TRUE  TRUE FALSE

你能加快速度吗（只用基础R）？

修改：我建议我找到有用的

"%~=%" <- almostEqual;
"%~in%" <- function(x,y){ sapply(x,FUN=function(a,b){any(almostEqual(a,b))},y)};

Answer 1

开始ifelse开始可以节省57％......

almostEqual2 <- function(x, y, tolerance=1e-8) {
  diff <- abs(x - y)
  mag <- pmax( abs(x), abs(y) )
  out <- logical(length(y))
  out[ mag > tolerance ] <- (diff/mag <= tolerance)[ mag > tolerance]
  out[ ! mag > tolerance ] <- (diff <= tolerance)[! mag > tolerance]
  return( out )
}


require(microbenchmark)

set.seed(1)
x <- 1
y <- rnorm(1e6)

bm <- microbenchmark( almostEqual(x,y,tol=0.5) , almostEqual2(x,y,tol=0.5) , times = 25 )
print( bm , digits = 3 , unit = "relative" , order = "median" )
#Unit: relative
#                          expr  min   lq median   uq  max neval
# almostEqual2(x, y, tol = 0.5) 1.00 1.00   1.00 1.00 1.00    25
#  almostEqual(x, y, tol = 0.5) 2.09 1.76   1.73 1.86 1.82    25

使用Rcpp

我不明白为什么你不会在base以外的CRAN中使用最依赖的软件包，但如果你想要，你可以实现比我之前的努力快5倍（10倍）在OP）上它也优雅地处理NA ...

#include <Rcpp.h>

using namespace Rcpp;

//[[Rcpp::export]]


LogicalVector all_equalC( double x , NumericVector y , double tolerance ){
  NumericVector diff = abs( x - y );
  NumericVector mag = pmax( abs(x) , abs(y) );
  LogicalVector res = ifelse( mag > tolerance , diff/mag <= tolerance , diff <= tolerance );
  return( res );
}

使用Rcpp::sourceCpp('path/to/file.cpp')提供。结果...

bm <- microbenchmark( almostEqual(x,y,tol=0.5) , almostEqual2(x,y,tol=0.5) , all_equalC(x,y,tolerance=0.5) , times = 25 )
print( bm , digits = 3 , unit = "relative" , order = "median" )
#Unit: relative
#                              expr  min   lq median   uq   max neval
# all_equalC(x, y, tolerance = 0.5) 1.00 1.00   1.00 1.00  1.00    25
#     almostEqual2(x, y, tol = 0.5) 4.50 4.39   5.39 5.24  7.32    25
#      almostEqual(x, y, tol = 0.5) 8.69 9.34   9.24 9.96 10.91    25

如何加快测试R中数字之间的相等性的方法

1 个答案:

使用Rcpp