Question

我正在尝试编写一个生成字符串向量的函数，每个函数都被评估为全局环境中的表达式。问题是eval（parse（text = x））仅在函数环境中进行求值。

作为一个假设的例子，假设我想用NA替换几个变量的值，但前提是它们低于某个截止值。

set.seed(200)
df <- as.data.frame(matrix(runif(25), nrow=5, ncol=5))
df
         V1         V2        V3        V4         V5
1 0.5337724 0.83929374 0.4543649 0.3072981 0.46036069
2 0.5837650 0.71160009 0.6492529 0.5667674 0.09874701
3 0.5895783 0.09650122 0.1537271 0.1317879 0.20659381
4 0.6910399 0.52382473 0.6492887 0.9221776 0.92233983
5 0.6673315 0.23535054 0.3832137 0.6463296 0.31942681

cutoff.V1 <- 0.9
cutoff.V2 <- 0.5
cutoff.V3 <- 0.1
cutoff.V4 <- 0.7
cutoff.V5 <- 0.4

不是一遍又一遍地复制和粘贴相同的行，而是更改每行中的相同文本...

df$V1[df$V1 < cutoff.V1] <- NA
df$V2[df$V2 < cutoff.V2] <- NA
df$V3[df$V3 < cutoff.V3] <- NA
df$V4[df$V4 < cutoff.V4] <- NA
df$V5[df$V5 < cutoff.V5] <- NA
# ad infinitum...

......我正在努力让R为我做这件事：

vars <- c("V1", "V2", "V3", "V4", "V5")

variable.queue <- function(vec, placeholder, command) {
  x <- vector()
  for(i in 1:length(vec)) { 
    x[i] <- gsub(placeholder, vec[i], command) 
  }
  return(x)
}

commands <- variable.queue(vars, "foo", "df$foo[df$foo < cutoff.foo] <- NA")
for(i in 1:length(commands)) {eval(parse(text=commands[i]))}

df

  V1        V2        V3        V4        V5
1 NA 0.8392937 0.4543649        NA 0.4603607
2 NA 0.7116001 0.6492529        NA        NA
3 NA        NA 0.1537271        NA        NA
4 NA 0.5238247 0.6492887 0.9221776 0.9223398
5 NA        NA 0.3832137        NA        NA


# FYI the object "commands" is the vector of strings that I want evaluated

commands
[1] "df$V1[df$V1 < cutoff.V1] <- NA" "df$V2[df$V2 < cutoff.V2] <- NA" "df$V3[df$V3 < cutoff.V3] <- NA"
[4] "df$V4[df$V4 < cutoff.V4] <- NA" "df$V5[df$V5 < cutoff.V5] <- NA"

此解决方案有效，但我想将最后一个for循环INSIDE放在函数中。有任何想法吗？

编辑：谢谢，凯文。这是“功能”版本（bwahaha，我有时候无法帮助自己）：

variable.queue <- function(vec, placeholder, command) {
  x <- vector()
  for(i in 1:length(vec)) { 
    x[i] <- gsub(placeholder, vec[i], command) 
  }
  for(i in 1:length(x)) {
    eval(parse(text=x[i]), envir= .GlobalEnv)
  }
}

variable.queue(vars, "foo", "df$foo[df$foo < cutoff.foo] <- NA")

Answer 1

必须有更好的解决方案。例如，对于您的示例，这有效：

set.seed(200)
df <- as.data.frame(matrix(runif(25), nrow=5, ncol=5))
cutoff <- c(0.9,0.5,0.1,0.7,0.4)

df[mapply("<", df,cutoff)] <- NA

#or
df[sweep(df,2,cutoff,"<")] <- NA

#or even
df[df < rep(cutoff,each=nrow(df))] <- NA

所有人都给出了：

> df
  V1        V2        V3        V4        V5
1 NA 0.8392937 0.4543649        NA 0.4603607
2 NA 0.7116001 0.6492529        NA        NA
3 NA        NA 0.1537271        NA        NA
4 NA 0.5238247 0.6492887 0.9221776 0.9223398
5 NA        NA 0.3832137        NA        NA

Answer 2

eval有一个参数envir，允许您指定要在其中评估表达式的环境。所以，

eval(parse(text=command[i]), envir=.GlobalEnv)

应该有希望工作。

eval（解析（text = x））函数内部，如何在全局环境中进行求值？

2 个答案: