嵌套函数中的Quosure

我正在努力编写一个使用fun1的函数fun2。。。不断地出错。我在下面写了一个简化的例子。这是我第一次处理“整洁的评估”，不确定是否理解它的来龙去脉

数据帧示例：

d1 = data.frame(
  ID = c("A", "A", "A", "B", "B", "C", "C", "C", "C"),
  EXPR = c(2, 8, 3, 5, 7, 20, 1, 5, 4)
)

d2 = data.frame(
  ID = c("A", "B", "C"),
  NUM = c(22, 50, 31)
)

第一个功能

fun1 <- function(
  df1 = "df 1", 
  df2 = "df 2",
  t1 = "threshold 1",
  expr_col = "expr column", 
  id_col = "sample column - must be present in df1 and df2") {

  # dataframes
  df <- df1
  db <- df2

  # quosure
  enquo_id <- enquo(id_col)
  enquo_expr <- enquo(expr_col)

  # classify
  df <- df %>% 
    mutate(threshold = t1) %>% 
    mutate(class = ifelse(!!enquo_expr > t1, "positive", "negative")) %>% 
    mutate(class = factor(class, levels = c("positive", "negative")))

  # calculate sample data
  df.sum <- df %>% 
    group_by(!!enquo_id, class) %>% 
    summarise(count = n()) %>% 
    complete(class, fill = list(count = 0)) %>% 
    mutate(total = sum(count), freq = count/total)

  # merge dataframes
  df.sum <- left_join(df.sum, db, by = quo_name(enquo_id))

  # return
  return(df.sum)
}

我试过各种各样的东西。。。我被困在这里了。我想我没有正确使用enquo（）。我可以通过不使用varX并直接在fun1参数中输入每个元素的实际适当名称来实现它，但对我来说，这样做的全部目的是使它“通用化”因此，仅在fun2中指定参数，然后将这些参数传递给fun1

---

任何帮助都将不胜感激

非常感谢您的回答。我现在使用以下代码进行排序：

fun2 <- function(
  df1 = "df 1", 
  df2 = "df 2",
  expr_col = "expr column", 
  id_col = "sample column - must be present in df1 and df2",
  ti = "initial value",
  tf = "final value",
  res = "resolution") {

  # define variables for fun1
  var4 <- enquo(expr_col)
  var5 <- enquo(id_col)

  # get sequence of values
  seq <- seq(from = ti, to = tf, by = res)

  # open list
  t.list <- list()

  ### Loop --------------------------------------------------------------
  for (i in seq_along(seq)){
    t1 <- seq[i]
    t.list[[i]] <- fun1(df1 = df1,
                        df2 = df2,
                        t1 = t1,
                        expr_col = !!var4,
                        id_col = !!var5)
  }
  df.out <- plyr::ldply(t.list, rbind)

  ### Return ---
  return(df.out)
}

# TEST FUN2
test <- fun2(df1 = d1, df2 = d2, expr_col = EXPR, id_col = ID, ti = 1, tf = 10, res = 1)

---

fun2传递
EXPR
并期望它工作意味着
EXPR
可以在全局环境中找到（根据您提供的代码判断，它不是）。也许您想引用一个名为
EXPR
的数据帧列？或者您可能想
attach（）
dataframe？
EXPR
这是dataframe
d1
的列名。。。但事实上，我的代码似乎不起作用……当您将
EXPR
传递到
fun2（）
时，您将其作为对象
EXPR
传递，而不是数据帧列。是否您的意思是
d1$EXPR
？在
fun2（）
中没有使用参数名称。例如，您的参数名是
expr\u col
，但您使用
expr
。
id\u col
vs
id
也有同样的问题。我认为您需要，例如，
var4
fun2 <- function(
  df1 = "df 1", 
  df2 = "df 2",
  expr_col = "expr column", 
  id_col = "sample column - must be present in df1 and df2",
  ti = "initial value",
  tf = "final value",
  res = "resolution") {

  # define variables for fun1
  var1 <- enquo(d1)
  var2 <- enquo(d2)
  var3 <- enquo(t1)
  var4 <- enquo(EXPR)
  var5 <- enquo(ID)

  # get sequence of values
  seq <- seq(from = ti, to = tf, by = res)

  # open list
  t.list <- list()

  # Loop ----
  for (i in seq_along(seq)){
    t1 <- seq[i]
    t.list[[i]] <- fun1(df1 = var1,
                        df2 = var2,
                        t1 = var3,
                        expr_col = var4,
                        id_col = var5)
  }
  df.out <- plyr::ldply(t.list, rbind)

  ### Return ---
  return(df.out)
}

test <- fun2(df1 = d1, df2 = d2, expr_col = EXPR, id_col = ID, ti = 1, tf = 10, res = 1)

Error in (function (x)  : object 'EXPR' not found

fun2 <- function(
  df1 = "df 1", 
  df2 = "df 2",
  expr_col = "expr column", 
  id_col = "sample column - must be present in df1 and df2",
  ti = "initial value",
  tf = "final value",
  res = "resolution") {

  # define variables for fun1
  var4 <- enquo(expr_col)
  var5 <- enquo(id_col)

  # get sequence of values
  seq <- seq(from = ti, to = tf, by = res)

  # open list
  t.list <- list()

  ### Loop --------------------------------------------------------------
  for (i in seq_along(seq)){
    t1 <- seq[i]
    t.list[[i]] <- fun1(df1 = df1,
                        df2 = df2,
                        t1 = t1,
                        expr_col = !!var4,
                        id_col = !!var5)
  }
  df.out <- plyr::ldply(t.list, rbind)

  ### Return ---
  return(df.out)
}

# TEST FUN2
test <- fun2(df1 = d1, df2 = d2, expr_col = EXPR, id_col = ID, ti = 1, tf = 10, res = 1)