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(v1.7.1.9023) Removed filter_ functions, new set_ab_names(), ATC code update, ab selector update, fixes #46 and fixed #47

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dr. M.S. (Matthijs) Berends
2021-08-16 21:54:34 +02:00
parent 4e1efd902c
commit a2d249962f
248 changed files with 2377 additions and 12201 deletions
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88
R/ab.R
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@ -33,7 +33,7 @@
#' @param ... arguments passed on to internal functions
#' @rdname as.ab
#' @inheritSection WHOCC WHOCC
#' @details All entries in the [antibiotics] data set have three different identifiers: a human readable EARS-Net code (column `ab`, used by ECDC and WHONET), an ATC code (column `atc`, used by WHO), and a CID code (column `cid`, Compound ID, used by PubChem). The data set contains more than 5,000 official brand names from many different countries, as found in PubChem.
#' @details All entries in the [antibiotics] data set have three different identifiers: a human readable EARS-Net code (column `ab`, used by ECDC and WHONET), an ATC code (column `atc`, used by WHO), and a CID code (column `cid`, Compound ID, used by PubChem). The data set contains more than 5,000 official brand names from many different countries, as found in PubChem. Not that some drugs contain multiple ATC codes.
#'
#' All these properties will be searched for the user input. The [as.ab()] can correct for different forms of misspelling:
#'
@ -101,6 +101,11 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
if (is.ab(x)) {
return(x)
}
if (all(x %in% c(AB_lookup$ab, NA))) {
# all valid AB codes, but not yet right class
return(set_clean_class(x,
new_class = c("ab", "character")))
}
initial_search <- is.null(list(...)$initial_search)
already_regex <- isTRUE(list(...)$already_regex)
@ -110,24 +115,6 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
x <- toupper(x)
x_nonNA <- x[!is.na(x)]
if (all(x_nonNA %in% antibiotics$ab, na.rm = TRUE)) {
# all valid AB codes, but not yet right class
return(set_clean_class(x,
new_class = c("ab", "character")))
}
if (all(x_nonNA %in% toupper(antibiotics$name), na.rm = TRUE)) {
# all valid AB names
out <- antibiotics$ab[match(x, toupper(antibiotics$name))]
out[is.na(x)] <- NA_character_
return(out)
}
if (all(x_nonNA %in% antibiotics$atc, na.rm = TRUE)) {
# all valid ATC codes
out <- antibiotics$ab[match(x, antibiotics$atc)]
out[is.na(x)] <- NA_character_
return(out)
}
# remove diacritics
x <- iconv(x, from = "UTF-8", to = "ASCII//TRANSLIT")
x <- gsub('"', "", x, fixed = TRUE)
@ -155,13 +142,29 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
found[1L]
}
if (initial_search == TRUE) {
progress <- progress_ticker(n = length(x), n_min = 25, print = info) # start if n >= 25
# Fill in names, AB codes, CID codes and ATC codes directly (`x` is already clean and uppercase)
known_names <- x %in% AB_lookup$generalised_name
x_new[known_names] <- AB_lookup$ab[match(x[known_names], AB_lookup$generalised_name)]
known_codes_ab <- x %in% AB_lookup$ab
known_codes_atc <- vapply(FUN.VALUE = logical(1), x, function(x_) x_ %in% unlist(AB_lookup$atc), USE.NAMES = FALSE)
known_codes_cid <- x %in% AB_lookup$cid
x_new[known_codes_ab] <- AB_lookup$ab[match(x[known_codes_ab], AB_lookup$ab)]
x_new[known_codes_atc] <- AB_lookup$ab[vapply(FUN.VALUE = integer(1),
x[known_codes_atc],
function(x_) which(vapply(FUN.VALUE = logical(1),
AB_lookup$atc,
function(atc) x_ %in% atc)),
USE.NAMES = FALSE)]
x_new[known_codes_cid] <- AB_lookup$ab[match(x[known_codes_cid], AB_lookup$cid)]
already_known <- known_names | known_codes_ab | known_codes_atc | known_codes_cid
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 seq_len(length(x))) {
for (i in which(!already_known)) {
if (initial_search == TRUE) {
progress$tick()
}
@ -189,34 +192,6 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
next
}
# exact name
found <- antibiotics[which(AB_lookup$generalised_name == x[i]), ]$ab
if (length(found) > 0) {
x_new[i] <- found[1L]
next
}
# exact AB code
found <- antibiotics[which(antibiotics$ab == x[i]), ]$ab
if (length(found) > 0) {
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
next
}
# exact ATC code
found <- antibiotics[which(antibiotics$atc == x[i]), ]$ab
if (length(found) > 0) {
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
next
}
# exact CID code
found <- antibiotics[which(antibiotics$cid == x[i]), ]$ab
if (length(found) > 0) {
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
next
}
# exact LOINC code
loinc_found <- unlist(lapply(AB_lookup$generalised_loinc,
function(s) x[i] %in% s))
@ -296,7 +271,7 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
next
}
# INITIAL SEARCH - More uncertain results ----
if (initial_search == TRUE && fast_mode == FALSE) {
@ -461,7 +436,7 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
x_unknown <- c(x_unknown, x_bak[x[i] == x_bak_clean][1])
}
if (initial_search == TRUE) {
if (initial_search == TRUE & sum(already_known) < length(x)) {
close(progress)
}
@ -479,11 +454,8 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
vector_and(x_unknown), ".",
call = FALSE)
}
x_result <- data.frame(x = x_bak_clean, stringsAsFactors = FALSE) %pm>%
pm_left_join(data.frame(x = x, x_new = x_new, stringsAsFactors = FALSE), by = "x") %pm>%
pm_pull(x_new)
x_result <- x_new[match(x_bak_clean, x)]
if (length(x_result) == 0) {
x_result <- NA_character_
}