sapply 与复合函数的速度比较

问题描述

> system.time(sapply(rnorm(1000000,0,1), function (x) round(x,2)))
   user  system elapsed 
   2.78    0.11    2.89 
> system.time(round(rnorm(1000000,0,1),2))
   user  system elapsed 
   0.29    0.00    0.30 

我在阅读了 R 提示问题的答案后尝试了这一点.我没想到 sapply 比上述情况下的等效复合函数慢几个数量级.有谁知道为什么会这样?如果我理解正确 sapply 将矢量化并接近最佳速度.

I was trying this out after reading the answers to the R tips question. I did not expect sapply to be order of magnitude slower than the equivalent composite function in the above case. Does anyone know why this is the case? If i understand correctly sapply will vectorize and be near optimally fast.

推荐答案

这里没有什么可应用的 - 你只给它一个向量 - 不是向量列表，并且 sapply 将结果转换为(单列)矩阵.

There's nothing here to sapply to - you only give it a single vector - not a list of vectors, and sapply converts the result to a (single column) matrix.

sapply 正在为您简化结果，但这样做必须生成一个数组.

sapply is simplifying the result for you, but in doing so has to generate an array.

比较一下，如果给它一个列表:

Compare if you give it a list:

system.time(sapply(list(rnorm(1000000,0,1)), function (x) round(x,2))) 
user  system elapsed 
 0.22    0.00    0.22 

system.time(sapply(rnorm(1000000,0,1), function (x) round(x,2))) 
user  system elapsed 
4.21    0.00    4.21 

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