R dplyr:: A function with name injection (LHS of :=) later referenced on RHS of :=

I am writing a function using dplyr package and other related packages, such as tidyr and tidyselect. After reading Programming with dplyr and many trials and errors, I was able to write a function that incorporates both data masking/tidy select and name injection to achieve partial goal.

compute_ratio <- function(numerator = dcdata,
                          denominator = pgdata,
                          bygroup = c('STUDY', 'SITE'),
                          nbydp = n_dc_bydp_ym,
                          numsuffix = dc_byss,
                          denosuffix = pg_byss){
  numerator %>% 
    dplyr::group_by(dplyr::pick({{ bygroup }})) %>%
    dplyr::summarise("n_{{numsuffix}}" := sum({{ nbydp }}, na.rm = TRUE)) %>%
    dplyr::ungroup() %>%
    # Merge denominator data with numerator data
    dplyr::full_join(denominator, by = {{ bygroup }}) %>% 
    dplyr::mutate("cum_n_{{denosuffix}}" := cumsum("n_{{numsuffix}}"),
                  "ratio_{{numsuffix}}" := dplyr::if_else("cum_n_{{denosuffix}}" == 0, NA,
                                                        round("n_{{numsuffix}}" / "cum_n_{{denosuffix}}", 3)))
}

The current issue is in the last mutate(). I cannot figure out how to refer to the names which is a name injection in previous lines of the same function. For example, "n_{{numsuffix}}" is a data variable derived from summarise(). When I need to refer to this data variable later in the last mutate(), it now is not on LHS of :=, but the RHS of :=.

Any advice or guidance is appreciated. How to refer to the previous name injection as a data variable later in the same user-defined function?

I have tried .data[[]], embracing {{ }}, !!enquo. All end with errors.

Sample numerator data - dcdata

structure(list(STUDY = c("A", "B", "A", "A", "A", "A", "A", "B", 
"B", "A", "A", "A", "B", "A", "B", "A", "A", "B", "A", "B"), 
    SITE = c("0187", "086108", "4603", "4304", "8617", "3205", 
    "0713", "086124", "086048", "6140", "0186", "4407", "086344", 
    "4413", "061027", "4115", "3403", "086009", "8618", "086020"
    ), n_dc_bydp_ym = c(0, 0, 0, 0, 0, 0, 1, 0, 0, 2, 0, 1, 1, 
    0, 0, 0, 0, 0, 1, 2)), row.names = c(NA, -20L), class = c("tbl_df", 
"tbl", "data.frame"))

Sample denominator data -- pgdata

structure(list(STUDY = c("A", "A", "A", "A", "A", "A", "A", "A", 
"A", "A", "A", "A", "A", "B", "B", "B", "B", "B", "B", "B"), 
    SITE = c("0186", "0187", "0713", "3205", "3403", "4115", 
    "4304", "4407", "4413", "4603", "6140", "8617", "8618", "061027", 
    "086009", "086020", "086048", "086108", "086124", "086344"
    ), n_pg_byss = c(2705L, 371L, 1495L, 404L, 1357L, 2089L, 
    456L, 886L, 830L, 5034L, 912L, 1739L, 1991L, 60L, 18L, 858L, 
    666L, 759L, 28L, 171L)), row.names = c(NA, -20L), class = c("tbl_df", 
"tbl", "data.frame"))

Test

test_ratiofun <- compute_ratio(numerator = dcdata,
                               denominator = pgdata,
                               bygroup = c('STUDY', 'SITE'),
                               nbydp = n_dc_bydp_ym,
                               numsuffix = dc_byss,
                               denosuffix = pg_byss)

Solution

Maybe theres a less convoluted way, but seems to work for what you want

library(tidyverse)
library(rlang)
library(glue)
myfunc <- function(x,numsuffix,denosuffix){
  
  n_text <- as.character(glue("n_{as_name(enquo(numsuffix))}"))
  
  group_by(x,
           Species) |>
    summarise("{n_text}":= sum(Petal.Length, na.rm = TRUE)) %>%
    dplyr::ungroup() |> 
    mutate(
   "cum_n_{{denosuffix}}" := cumsum(!!sym(n_text)))
}

myfunc(iris,whatever,also)

# A tibble: 3 × 3
  Species    n_whatever cum_n_also
  <fct>           <dbl>      <dbl>
1 setosa           73.1       73.1
2 versicolor      213        286. 
3 virginica       278.       564.