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(v2.1.1.9256) unit tests

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dr. M.S. (Matthijs) Berends
2025-04-26 21:29:50 +02:00
parent d166aa2c1d
commit f340e257fa
10 changed files with 17 additions and 142 deletions
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1
R/ab.R
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@ -72,7 +72,6 @@
#' as.ab("ERY")
#' as.ab("eritromicine") # spelled wrong, yet works
#' as.ab("Erythrocin") # trade name
#' as.ab("Romycin") # trade name
#'
#' # spelling from different languages and dyslexia are no problem
#' ab_atc("ceftriaxon")

11
R/sir.R
View File

@ -680,8 +680,8 @@ as.sir.disk <- function(x,
}
#' @rdname as.sir
#' @param parallel A [logical] to indicate if parallel computing must be used, defaults to `FALSE`.
#' @param max_cores Maximum number of cores to use if `parallel = TRUE`. Use a negative value to subtract that number from the available number of cores, e.g. a value of `-2` on an 8-core machine means that 6 cores will be used. Defaults to `-1`. The available number of cores are detected using [parallelly::availableCores()] if that package is installed, and base \R's [parallel::detectCores()] otherwise.
#' @param parallel A [logical] to indicate if parallel computing must be used, defaults to `FALSE`. This requires no additional packages, as the used `parallel` package is part of base \R.
#' @param max_cores Maximum number of cores to use if `parallel = TRUE`. Use a negative value to subtract that number from the available number of cores, e.g. a value of `-2` on an 8-core machine means that at most 6 cores will be used. Defaults to `-1`. There will never be used more cores than variables to analyse. The available number of cores are detected using [parallelly::availableCores()] if that package is installed, and base \R's [parallel::detectCores()] otherwise.
#' @export
as.sir.data.frame <- function(x,
...,
@ -853,6 +853,7 @@ as.sir.data.frame <- function(x,
# set up parallel computing
n_cores <- get_n_cores(max_cores = max_cores)
n_cores <- min(n_cores, length(ab_cols)) # never more cores than variables required
run_as_sir_column <- function(i) {
ab_col <- ab_cols[i]
@ -952,7 +953,7 @@ as.sir.data.frame <- function(x,
if (isTRUE(parallel) && n_cores > 1 && length(ab_cols) > 1) {
if (isTRUE(info)) {
message()
message_("Running SIR interpretation in parallel mode on ", nr2char(length(ab_cols)), " columns, using ", n_cores, " out of ", get_n_cores(Inf), " cores...", as_note = FALSE, appendLF = FALSE, add_fn = font_red)
message_("Running in parallel mode using ", n_cores, " out of ", get_n_cores(Inf), " cores, on columns ", vector_and(font_bold(ab_cols, collapse = NULL), quotes = "'", sort = FALSE), "...", as_note = FALSE, appendLF = FALSE, add_fn = font_red)
}
if (.Platform$OS.type == "windows") {
cl <- parallel::makeCluster(n_cores, type = "PSOCK")
@ -976,10 +977,10 @@ as.sir.data.frame <- function(x,
}
} else {
# sequential mode (non-parallel)
if (n_cores > 1 && isTRUE(info) && (NROW(x) > 2500 || length(ab_cols) >= 5)) {
if (isTRUE(info) && n_cores > 1 && NROW(x) * NCOL(x) > 10000) {
# give a note that parallel mode might be better
message()
message_("Running SIR interpretation in sequential mode. Consider setting `parallel = TRUE` to speed up processing on multiple cores.\n", add_fn = font_red)
message_("Running in sequential mode. Consider setting `parallel = TRUE` to speed up processing on multiple cores.\n", add_fn = font_red)
}
# this will contain a progress bar already
result_list <- lapply(seq_along(ab_cols), run_as_sir_column)