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completely updated antibiotics

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dr. M.S. (Matthijs) Berends
2022-10-30 14:31:45 +01:00
parent 3d9faf89cf
commit d40e0ef20b
60 changed files with 102028 additions and 95116 deletions
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24
R/ab.R
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@ -48,7 +48,7 @@
#' Use the [`ab_*`][ab_property()] functions to get properties based on the returned antibiotic ID, see *Examples*.
#'
#' Note: the [as.ab()] and [`ab_*`][ab_property()] functions may use very long regular expression to match brand names of antimicrobial agents. This may fail on some systems.
#'
#'
#' You can add your own manual codes to be considered by [as.ab()] and all [`ab_*`][ab_property()] functions, see [add_custom_antimicrobials()].
#' @section Source:
#' World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology: \url{https://www.whocc.no/atc_ddd_index/}
@ -84,7 +84,7 @@
#' # they use as.ab() internally:
#' ab_name("J01FA01") # "Erythromycin"
#' ab_name("eryt") # "Erythromycin"
#'
#'
#' \donttest{
#' if (require("dplyr")) {
#'
@ -170,16 +170,16 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
previously_coerced <- x %in% AMR_env$ab_previously_coerced$x
x_new[previously_coerced & is.na(x_new)] <- AMR_env$ab_previously_coerced$ab[match(x[is.na(x_new) & x %in% AMR_env$ab_previously_coerced$x], AMR_env$ab_previously_coerced$x)]
already_known <- known_names | known_codes_ab | known_codes_atc | known_codes_cid | previously_coerced
# fix for NAs
x_new[is.na(x)] <- NA
already_known[is.na(x)] <- FALSE
if (initial_search == TRUE && sum(already_known) < length(x)) {
progress <- progress_ticker(n = sum(!already_known), n_min = 25, print = info) # start if n >= 25
on.exit(close(progress))
}
for (i in which(!already_known)) {
if (initial_search == TRUE) {
progress$tick()
@ -490,15 +490,15 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
if (initial_search == TRUE && sum(already_known) < length(x)) {
close(progress)
}
# save to package env to save time for next time
AMR_env$ab_previously_coerced <- unique(rbind(AMR_env$ab_previously_coerced,
data.frame(
x = x,
ab = x_new,
stringsAsFactors = FALSE
),
stringsAsFactors = FALSE
data.frame(
x = x,
ab = x_new,
stringsAsFactors = FALSE
),
stringsAsFactors = FALSE
))
# take failed ATC codes apart from rest