R/internal_utils.R

In TidyMultiqc: Converts 'MultiQC' Reports into Tidy Data Frames

#' Maps over the keys and values of a vector, but expects the function to return
#' a named vector with "key" and "value" entries. These will become the names
#' and values of the final vector. Think of this as like a Python dictionary
#' comprehension: it takes an iterable and produces a dictionary.
#'
#' @param l a vector to map over
#' @param func the function to apply over that vector, which must return a `list(key=?, value=?)`
#' @param map_keys logical. If TRUE, then use `imap` which provides the keys as the second element to the function
#' @keywords internal
#' @noRd
#' @examples
#' library(magrittr)
#' c(1, 2, 3) %>% kv_map(~ list(key = letters[[.]], value = .))
#' c(1, 2, 3) %>% kv_map(function(x) {
#'   list(key = letters[[x]], value = x)
#' })
#' c(a = 1, b = 2, c = 3) %>% kv_map(~ list(key = stringr::str_c(.y, "²"), value = .x), map_keys = TRUE)
kv_map <- function(l, func, map_keys = FALSE) {
  mapper <- ifelse(map_keys, purrr::imap, purrr::map)
  mapped <- mapper(l, func) %>% purrr::set_names(nm = NULL)
  keys <- mapped %>% purrr::map_chr("key")
  vals <- mapped %>% purrr::map("value")
  vals %>% purrr::set_names(keys)
}

#' Converts a MultiQC string into a standardised identifier for the final
#' data frame
#' @keywords internal
#' @noRd
sanitise_column_name <- function(name) {
  name %>%
    stringr::str_replace_all(pattern = "[- ]", replacement = "_") %>% # Any dividing characters become underscores
    stringr::str_remove_all(pattern = "[^\\w%_]") %>% # Any special characters bar underscore and % get deleted
    stringr::str_to_lower()
}

ROW_IDENTIFIER <- "metadata.sample_id"