当函数使用 enquo 列时，如何将多个函数传递给 purr::map（exec 或 invoke_map）？

Question

当我尝试将参数传递给使用 enquo() 的函数时，出现以下错误。

“错误：只能在 quasiquotation 上下文中不引用引文。”

在下面的例子中，

Wrap1 函数使用 map 为单个函数运行多个参数集。使用 !!enquo() 传递变量有效。

Wrap 2 尝试传递多个函数和参数，但我无法获得正确的语法。

1. 我的传递方式是否存在问题（exec 或 invoke_map 函数中的顺序，或者列如何通过 !!enquo(cols) 传递？

2. 有没有办法将额外的变量传递给 invoke_map 或参数列表之外的所有变量（类似于在下面的 wrap1 代码中使用 partial）？

library(dplyr)  
library(lubridate)  
library(purrr)   
library(rlang)   
library(rkt)

dataset <- tibble(Date= lubridate::decimal_date(seq(as.Date("2000/1/1"), by = "month", length.out = 120)),
                  Value = rnorm(120), 
                  season = lubridate::month(seq(as.Date("2000/1/1"), by = "month", length.out = 120)))
  
#inner function
run1_fun <- function(df, yCOL, datesCOL, seasCOL=NULL,  ind.obs=TRUE){
  
  y <- df %>% pull(!!enquo(yCOL))
  dates <- df %>% pull(!!enquo(datesCOL))
   
  mk <- rlang::quo_is_null(enquo(seasCOL))

  if (mk){
    seas <- rep(1, length(y))  #just so can get nseas=1 later
    smk <- rkt::rkt(date=dates, y=y)
  } else {
    seas <- df %>% pull(!!enquo(seasCOL))
    smk <- rkt::rkt(date=dates, y=y, block=seas, correct = !ind.obs)
  }

  out <- tibble(tau = smk$tau, 
                slope = smk$B, 
                type = ifelse(mk, "MK", "SK"))
  out
}

#inner function with by option
run1_fun_by <- function(df, by=NULL, yCOL, datesCOL, seasCOL=NULL,  ind.obs=TRUE){
  
    if(is.null(by)) {
      df <- run1_fun(df, !!enquo(yCOL), !!enquo(datesCOL), !!enquo(seasCOL),ind.obs)
  } else {
    df <- plyr::ddply(df, .variables = by, 
                     .fun = run1_fun, !!enquo(yCOL), !!enquo(datesCOL), !!enquo(seasCOL),ind.obs)
  }
  df
}

#to run:
run1_fun_by(dataset, by="season", Value, Date, ind.obs=TRUE)

#WRAP 1: WORKS
# example of wrap function that passing multiple arguments sets to the above inner function that uses enquo variables. 
wrap1 <- function(df, yCOL, datesCOL, seasCOL=NULL,  ind.obs=TRUE, 
                  ttype=c("MK", "SK")){

  fun_args <- partial(run1_fun, df=df, yCOL = !!enquo(yCOL), datesCOL =  !!enquo(datesCOL), ind.obs=ind.obs)
             
  #fun_args - order in "SK", "MK"  
  keep <- which(c("SK", "MK") %in% ttype)
  args <- list(seasCOL = dplyr::vars(!!enquo(seasCOL), NULL)[keep])   # didnt work with alist..
  #args <-tibble(seasCOL = dplyr::vars(!!enquo(seasCOL), NULL)[keep])  #works too
  res <- purrr::pmap_dfr(args, fun_args)
  
  res
}
#to run: 
wrap1(dataset, Value, Date, season, ind.obs=TRUE, ttype=c("MK", "SK"))

#WRAP 2: DOESN'T WORK
#attempt to iterate through multiple functions and argument sets (where functions requires enquo arguments)
using either invoke_map or exec?

wrap2 <- function(df, yCOL, datesCOL, seasCOL=NULL,  ind.obs=TRUE, 
                  ttype=c("MK", "SK", "MKSeas")){
  
  t <- c("SK", "MK", "MKSeas")
  
   #HOW CAN I PASS (which are enq in next function)
    sim <- tribble(
   ~f,               ~params,
  "run1_fun",        list(seasCOL = dplyr::vars(!!enquo(seasCOL)), ind.obs=ind.obs),   #SK
  "run1_fun",        list(seasCOL = dplyr::vars(NULL)),                                      #MK
  "run1_fun_by",     list(by="season"))                                                #MKSeas
  
  #with invoke_map - but looks like this is retired 
  res  <- invoke_map_dfc(sim$f, sim$params, df=df, yCOL=!!enquo(yCOL), datesCOL=!!enquo(datesCOL)) 
  
  #with exec - new
  #res <-  map2_dfc(sim$f, sim$params, function(fn, args) exec(fn, !!!args))

  res  
}

#to run
wrap2(dataset, Value, Date, season, ind.obs=TRUE, ttype=c("MK", "SK", "MKSeas"))

错误：Quosures 只能在 quasiquotation 上下文中不被引用。

不好：

列表(!!myquosure)

好：

dplyr::mutate(数据, !!myquosure) 致电rlang::last_error() 查看回溯 调用自：abort(paste_line("Quosures 只能在 quasiquotation 上下文中不被引用。", "", "# Bad:", "list(!!myquosure)", "", " # Good:", " dplyr::mutate(data, !!myquosure)")

Answer 1

使用rlang::call2 组合所需的函数调用，然后评估它们。

另外，因为您使用的是列名，所以正确的 NSE 动词是 ensym()，而不是 enquo()。前者捕获符号名称并使用字符串。后者捕获一个表达式及其上下文。在这种情况下，上下文是数据帧，它已经被直接传递给函数，而enquo() 正在捕获全局环境（这是不正确的）。

wrap2 <- function(df, yCOL, datesCOL, seasCOL=NULL,  ind.obs=TRUE,
                  ttype=c("MK", "SK", "MKSeas")){

  sim <- tribble(
          ~f,             ~params,
          "run1_fun",     list(seasCOL = ensym(seasCOL), ind.obs=ind.obs),  #SK
          "run1_fun",     list(seasCOL = NULL),                             #MK
          "run1_fun_by",  list(by="season"))                                #MKSeas

  # Concatenate common arguments to each list of parameters
  myArgs <- map( sim$params, c, yCOL=ensym(yCOL), datesCOL=ensym(datesCOL) )

  # Compose the function calls
  calls <- map2( sim$f, myArgs, ~rlang::call2(.x, !!!.y, df=df) )

  # Evaluate the function calls and aggregate the results
  map_dfr( calls, eval )
}

wrap2(dataset, Value, Date, season, ind.obs=TRUE, ttype=c("MK", "SK", "MKSeas"))
# # A tibble: 14 x 4
#        tau   slope type  season
#      <dbl>   <dbl> <chr>  <dbl>
#  1 -0.0259 -0.0180 SK        NA
#  2 -0.0255 -0.0151 MK        NA
#  3  0.2     0.0743 MK         1
#  4 -0.378  -0.162  MK         2
#  5 -0.0222 -0.0505 MK         3
# ...