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(v3.0.0.9007) allow any tidyselect language in as.sir()

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dr. M.S. (Matthijs) Berends
2025-07-17 14:29:35 +02:00
parent 0138e33ce9
commit 8dab0a3730
16 changed files with 123 additions and 113 deletions
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27
R/sir.R
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@ -69,7 +69,9 @@
#' @param reference_data A [data.frame] to be used for interpretation, which defaults to the [clinical_breakpoints] data set. Changing this argument allows for using own interpretation guidelines. This argument must contain a data set that is equal in structure to the [clinical_breakpoints] data set (same column names and column types). Please note that the `guideline` argument will be ignored when `reference_data` is manually set.
#' @param threshold Maximum fraction of invalid antimicrobial interpretations of `x`, see *Examples*.
#' @param conserve_capped_values Deprecated, use `capped_mic_handling` instead.
#' @param ... For using on a [data.frame]: names of columns to apply [as.sir()] on (supports tidy selection such as `column1:column4`). Otherwise: arguments passed on to methods.
#' @param ... For using on a [data.frame]: selection of columns to apply `as.sir()` to. Supports [tidyselect language][tidyselect::starts_with()] such as `where(is.mic)`, `starts_with(...)`, or `column1:column4`, and can thus also be [antimicrobial selectors][amr_selector()] such as `as.sir(df, penicillins())`.
#'
#' Otherwise: arguments passed on to methods.
#' @details
#' *Note: The clinical breakpoints in this package were validated through, and imported from, [WHONET](https://whonet.org). The public use of this `AMR` package has been endorsed by both CLSI and EUCAST. See [clinical_breakpoints] for more information.*
#'
@ -225,9 +227,12 @@
#' df_wide %>% mutate_if(is.mic, as.sir)
#' df_wide %>% mutate_if(function(x) is.mic(x) | is.disk(x), as.sir)
#' df_wide %>% mutate(across(where(is.mic), as.sir))
#'
#' df_wide %>% mutate_at(vars(amoxicillin:tobra), as.sir)
#' df_wide %>% mutate(across(amoxicillin:tobra, as.sir))
#'
#' df_wide %>% mutate(across(aminopenicillins(), as.sir))
#'
#' # approaches that all work with additional arguments:
#' df_long %>%
#' # given a certain data type, e.g. MIC values
@ -722,8 +727,17 @@ as.sir.data.frame <- function(x,
meet_criteria(info, allow_class = "logical", has_length = 1)
meet_criteria(parallel, allow_class = "logical", has_length = 1)
meet_criteria(max_cores, allow_class = c("numeric", "integer"), has_length = 1)
x.bak <- x
if (tryCatch(length(list(...)) > 0, error = function(e) TRUE)) {
sel <- colnames(pm_select(x, ...))
} else {
sel <- colnames(x)
}
if (!is.null(col_mo)) {
sel <- sel[sel != col_mo]
}
for (i in seq_len(ncol(x))) {
# don't keep factors, overwriting them is hard
if (is.factor(x[, i, drop = TRUE])) {
@ -803,15 +817,6 @@ as.sir.data.frame <- function(x,
}
i <- 0
if (tryCatch(length(list(...)) > 0, error = function(e) TRUE)) {
sel <- colnames(pm_select(x, ...))
} else {
sel <- colnames(x)
}
if (!is.null(col_mo)) {
sel <- sel[sel != col_mo]
}
ab_cols <- colnames(x)[vapply(FUN.VALUE = logical(1), x, function(y) {
i <<- i + 1
check <- is.mic(y) | is.disk(y)