矢量化()与应用() [英] Vectorize() vs apply()

问题描述

R 中的 Vectorize() 和 apply() 函数通常可用于实现相同的目标.出于可读性原因，我通常更喜欢对函数进行向量化，因为主要调用函数与手头的任务相关，而 sapply 则不是.当我将在我的 R 代码中多次使用该矢量化函数时，它对 Vectorize() 也很有用.例如:

The Vectorize() and the apply() functions in R can often be used to accomplish the same goal. I usually prefer vectorizing a function for readability reasons, because the main calling function is related to the task at hand while sapply is not. It is also useful to Vectorize() when I am going to be using that vectorized function multiple times in my R code. For instance:

a <- 100
b <- 200
c <- 300
varnames <- c('a', 'b', 'c')

getv <- Vectorize(get)
getv(varnames)

对比

sapply(varnames, get)

但是，至少在 SO 上，我很少在解决方案中看到带有 Vectorize() 的示例，只有 apply()(或它的兄弟之一).Vectorize() 是否有任何效率问题或其他合理的问题使 apply() 成为更好的选择?

However, at least on SO I rarely see examples with Vectorize() in the solution, only apply() (or one of it's siblings). Are there any efficiency issues or other legitimate concerns with Vectorize() that make apply() a better option?

推荐答案

Vectorize 只是 mapply 的包装器.它只是为您提供的任何函数构建一个 mapply 循环.因此，通常有比 Vectorize() 更容易的事情，而且显式的 *apply 解决方案最终在计算上等效或可能更好.

Vectorize is just a wrapper for mapply. It just builds you an mapply loop for whatever function you feed it. Thus there are often easier things do to than Vectorize() it and the explicit *apply solutions end up being computationally equivalent or perhaps superior.

此外，对于您的具体示例，您听说过 mget，对吗?

Also, for your specific example, you've heard of mget, right?

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