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(v2.1.1.9159) new approach as.ab()

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dr. M.S. (Matthijs) Berends 2025-02-26 19:23:54 +01:00
parent 122bca0f95
commit 0c3ea4b538
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18 changed files with 130 additions and 284 deletions
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2
.github/workflows/check-old-tinytest.yaml vendored
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@ -61,7 +61,7 @@ jobs:
R_REMOTES_NO_ERRORS_FROM_WARNINGS: true
steps:
- uses: actions/checkout@v3
- uses: actions/checkout@v4
- uses: r-lib/actions/setup-r@v2
with:

2
.github/workflows/codecovr.yaml vendored
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@ -42,7 +42,7 @@ jobs:
GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
CODECOV_TOKEN: ${{secrets.CODECOV_TOKEN}}
steps:
- uses: actions/checkout@v3
- uses: actions/checkout@v4
- uses: r-lib/actions/setup-pandoc@v2

12
.github/workflows/lintr.yaml vendored
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@ -41,7 +41,7 @@ jobs:
env:
GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
steps:
- uses: actions/checkout@v3
- uses: actions/checkout@v4
- uses: r-lib/actions/setup-pandoc@v2
@ -59,13 +59,15 @@ jobs:
run: |
# old: lintr::lint_package(linters = lintr::with_defaults(line_length_linter = NULL, trailing_whitespace_linter = NULL, object_name_linter = NULL, cyclocomp_linter = NULL, object_length_linter = lintr::object_length_linter(length = 50L)), exclusions = list("R/aa_helper_pm_functions.R"))
# now get ALL linters, not just default ones
linters <- ls(envir = asNamespace("lintr"), pattern = "_linter$")
linters <- getNamespaceExports(asNamespace("lintr"))
linters <- sort(linters[grepl("_linter$", linters)])
# lose deprecated
linters <- linters[!grepl("^(closed_curly|open_curly|paren_brace|semicolon_terminator)_linter$", linters)]
linters <- linters[!grepl("^(closed_curly|open_curly|paren_brace|semicolon_terminator|consecutive_stopifnot|no_tab|single_quotes|unnecessary_nested_if|unneeded_concatenation)_linter$", linters)]
# and the ones we find unnnecessary
linters <- linters[!grepl("^(extraction_operator|implicit_integer|line_length|object_name|nonportable_path|is)_linter$", linters)]
# put the functions in a list
linters <- lapply(linters, function(l) eval(parse(text = paste0("lintr::", l, "()")), envir = asNamespace("lintr")))
linters_list <- lapply(linters, function(l) eval(parse(text = paste0("lintr::", l, "()")), envir = asNamespace("lintr")))
names(linters_list) <- linters
# run them all!
lintr::lint_package(linters = linters, exclusions = list("R/aa_helper_pm_functions.R"))
lintr::lint_package(linters = linters_list, exclusions = list("R/aa_helper_pm_functions.R"))
shell: Rscript {0}

2
.github/workflows/publish-to-pypi.yml vendored
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@ -40,7 +40,7 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v3
uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v4

2
.github/workflows/website.yaml vendored
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@ -43,7 +43,7 @@ jobs:
continue-on-error: true
steps:
- uses: actions/checkout@v3
- uses: actions/checkout@v4
with:
# this is to keep timestamps, the default fetch-depth: 1 gets the timestamps of the moment of cloning
# we need this for the download page on our website - dates must be of the files, not of the latest git push

2
DESCRIPTION
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@ -1,5 +1,5 @@
Package: AMR
Version: 2.1.1.9158
Version: 2.1.1.9159
Date: 2025-02-26
Title: Antimicrobial Resistance Data Analysis
Description: Functions to simplify and standardise antimicrobial resistance (AMR)

2
NEWS.md
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@ -1,4 +1,4 @@
# AMR 2.1.1.9158
# AMR 2.1.1.9159
*(this beta version will eventually become v3.0. We're happy to reach a new major milestone soon, which will be all about the new One Health support! Install this beta using [the instructions here](https://msberends.github.io/AMR/#latest-development-version).)*

2
PythonPackage/AMR/AMR.egg-info/PKG-INFO
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@ -1,6 +1,6 @@
Metadata-Version: 2.2
Name: AMR
Version: 2.1.1.9158
Version: 2.1.1.9159
Summary: A Python wrapper for the AMR R package
Home-page: https://github.com/msberends/AMR
Author: Matthijs Berends

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PythonPackage/AMR/dist/amr-2.1.1.9158.tar.gz vendored
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PythonPackage/AMR/dist/amr-2.1.1.9158-py3-none-any.whl → PythonPackage/AMR/dist/amr-2.1.1.9159-py3-none-any.whl vendored
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PythonPackage/AMR/dist/amr-2.1.1.9159.tar.gz vendored Normal file
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2
PythonPackage/AMR/setup.py
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@ -2,7 +2,7 @@ from setuptools import setup, find_packages
setup(
name='AMR',
version='2.1.1.9158',
version='2.1.1.9159',
packages=find_packages(),
install_requires=[
'rpy2',

262
R/ab.R
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@ -32,6 +32,7 @@
#' Use this function to determine the antibiotic drug code of one or more antibiotics. The data set [antibiotics] will be searched for abbreviations, official names and synonyms (brand names).
#' @param x a [character] vector to determine to antibiotic ID
#' @param flag_multiple_results a [logical] to indicate whether a note should be printed to the console that probably more than one antibiotic drug code or name can be retrieved from a single input value.
#' @param language language to coerce input values from any of the `r length(LANGUAGES_SUPPORTED)` supported languages - default to the system language if supported (see [get_AMR_locale()])
#' @param info a [logical] to indicate whether a progress bar should be printed - the default is `TRUE` only in interactive mode
#' @param ... arguments passed on to internal functions
#' @rdname as.ab
@ -67,7 +68,6 @@
#' as.ab("J 01 FA 01")
#' as.ab("Erythromycin")
#' as.ab("eryt")
#' as.ab(" eryt 123")
#' as.ab("ERYT")
#' as.ab("ERY")
#' as.ab("eritromicine") # spelled wrong, yet works
@ -92,9 +92,10 @@
#' set_ab_names(where(is.sir), property = "atc")
#' }
#' }
as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
as.ab <- function(x, flag_multiple_results = TRUE, language = get_AMR_locale(), info = interactive(), ...) {
meet_criteria(x, allow_class = c("character", "numeric", "integer", "factor"), allow_NA = TRUE)
meet_criteria(flag_multiple_results, allow_class = "logical", has_length = 1)
language <- validate_language(language)
meet_criteria(info, allow_class = "logical", has_length = 1)
if (is.ab(x) || all(x %in% c(AMR_env$AB_lookup$ab, NA))) {
@ -157,12 +158,12 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
known_names <- x %in% AMR_env$AB_lookup$generalised_name
x_new[known_names] <- AMR_env$AB_lookup$ab[match(x[known_names], AMR_env$AB_lookup$generalised_name)]
known_codes_ab <- x %in% AMR_env$AB_lookup$ab
known_codes_atc <- vapply(FUN.VALUE = logical(1), x, function(x_) x_ %in% unlist(AMR_env$AB_lookup$atc), USE.NAMES = FALSE)
known_codes_atc <- vapply(FUN.VALUE = logical(1), gsub(" ", "", x), function(x_) x_ %in% unlist(AMR_env$AB_lookup$atc), USE.NAMES = FALSE)
known_codes_cid <- x %in% AMR_env$AB_lookup$cid
x_new[known_codes_ab] <- AMR_env$AB_lookup$ab[match(x[known_codes_ab], AMR_env$AB_lookup$ab)]
x_new[known_codes_atc] <- AMR_env$AB_lookup$ab[vapply(
FUN.VALUE = integer(1),
x[known_codes_atc],
gsub(" ", "", x[known_codes_atc]),
function(x_) {
which(vapply(
FUN.VALUE = logical(1),
@ -310,6 +311,8 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
next
}
# try if name ends with it
found <- AMR_env$AB_lookup[which(AMR_env$AB_lookup$generalised_name %like% paste0(x_spelling, "$")), "ab", drop = TRUE]
if (nchar(x[i]) >= 4 && length(found) > 0) {
@ -329,235 +332,62 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
}
# INITIAL SEARCH - More uncertain results ----
if (loop_time <= 2 && fast_mode == FALSE) {
if (loop_time == 1 && fast_mode == FALSE) {
# only run on first and second try
# base on the Levensthein distance function if length >= 6
if (nchar(x[i]) >= 6) {
l_dist <- as.double(utils::adist(x[i], AMR_env$AB_lookup$generalised_name,
ab_df <- AMR_env$AB_lookup
ab_df$length_name <- nchar(ab_df$generalised_name)
# now retrieve Levensthein distance for name, synonyms, and translated names
ab_df$lev_name <- as.double(utils::adist(x[i], ab_df$generalised_name,
ignore.case = FALSE,
fixed = TRUE,
costs = c(insertions = 1, deletions = 2, substitutions = 2),
costs = c(insertions = 1, deletions = 1, substitutions = 2),
counts = FALSE))
ab_df$lev_syn <- vapply(FUN.VALUE = double(1),
ab_df$generalised_synonyms,
function(y) ifelse(length(y[nchar(y) >= 5]) == 0,
999,
min(as.double(utils::adist(x[i], y[nchar(y) >= 5], ignore.case = FALSE,
fixed = TRUE,
costs = c(insertions = 1, deletions = 1, substitutions = 2),
counts = FALSE)), na.rm = TRUE)),
USE.NAMES = FALSE)
if (!is.null(language) && language != "en") {
ab_df$trans <- generalise_antibiotic_name(translate_AMR(ab_df$name, language = language))
ab_df$lev_trans <- as.double(utils::adist(x[i], ab_df$trans,
ignore.case = FALSE,
fixed = TRUE,
costs = c(insertions = 1, deletions = 1, substitutions = 2),
counts = FALSE))
x_new[i] <- AMR_env$AB_lookup$ab[order(l_dist)][1]
x_uncertain <- c(x_uncertain, x_bak[x[i] == x_bak_clean][1])
next
}
# try by removing all spaces
if (x[i] %like% " ") {
found <- suppressWarnings(as.ab(gsub(" +", "", x[i], perl = TRUE), loop_time = loop_time + 2))
if (length(found) > 0 && !is.na(found)) {
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
x_uncertain <- c(x_uncertain, x_bak[x[i] == x_bak_clean][1])
next
}
}
# try by removing all spaces and numbers
if (x[i] %like% " " || x[i] %like% "[0-9]") {
found <- suppressWarnings(as.ab(gsub("[ 0-9]", "", x[i], perl = TRUE), loop_time = loop_time + 2))
if (length(found) > 0 && !is.na(found)) {
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
x_uncertain <- c(x_uncertain, x_bak[x[i] == x_bak_clean][1])
next
}
}
# reverse a combination, e.g. clavulanic acid/amoxicillin
if (x[i] %like% " ") {
split <- strsplit(x[i], " ")[[1]]
permute <- function(x) {
if (length(x) == 1) return(list(x))
result <- vector("list", factorial(length(x)))
index <- 1
for (i in seq_along(x)) {
sub_perms <- permute(x[-i]) # Recursively get permutations of remaining elements
for (sub in sub_perms) {
result[[index]] <- c(x[i], sub)
index <- index + 1
}
}
return(result)
}
permutations <- permute(split)
found_perms <- character(length(permutations))
for (s in seq_len(length(permutations))) {
concat <- paste0(permutations[[s]], collapse = " ")
if (concat %in% AMR_env$AB_lookup$generalised_name) {
found_perms[s] <- AMR_env$AB_lookup[which(AMR_env$AB_lookup$generalised_name == concat), "ab", drop = TRUE]
} else {
found_perms[s] <- suppressWarnings(as.ab(concat, loop_time = loop_time + 2))
}
}
found_perms <- found_perms[!is.na(found_perms)]
if (length(found_perms) > 0) {
found <- found_perms[order(nchar(found_perms), decreasing = TRUE)][1]
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
x_uncertain <- c(x_uncertain, x_bak[x[i] == x_bak_clean][1])
next
}
ab_df$lev_trans <- ab_df$lev_name
}
# transform back from other languages and try again
x_translated <- paste(
lapply(
strsplit(x[i], "[^A-Z0-9]"),
function(y) {
for (i in seq_len(length(y))) {
for (lang in LANGUAGES_SUPPORTED[LANGUAGES_SUPPORTED != "en"]) {
y[i] <- ifelse(tolower(y[i]) %in% tolower(TRANSLATIONS[, lang, drop = TRUE]),
TRANSLATIONS[which(tolower(TRANSLATIONS[, lang, drop = TRUE]) == tolower(y[i]) &
!isFALSE(TRANSLATIONS$fixed)), "pattern"],
y[i]
)
}
}
generalise_antibiotic_name(y)
}
)[[1]],
collapse = "/"
)
x_translated_guess <- suppressWarnings(as.ab(x_translated, loop_time = loop_time + 2))
if (!is.na(x_translated_guess)) {
x_new[i] <- x_translated_guess
if (any(ab_df$lev_name < 5, na.rm = TRUE)) {
x_new[i] <- ab_df$ab[order(ab_df$lev_name)][1]
x_uncertain <- c(x_uncertain, x_bak[x[i] == x_bak_clean][1])
next
}
# now also try to coerce brandname combinations like "Amoxy/clavulanic acid"
x_translated <- paste(
lapply(
strsplit(x_translated, "[^A-Z0-9 ]"),
function(y) {
for (i in seq_len(length(y))) {
y_name <- suppressWarnings(ab_name(y[i], language = NULL, loop_time = loop_time + 2))
y[i] <- ifelse(!is.na(y_name),
y_name,
y[i]
)
}
generalise_antibiotic_name(y)
}
)[[1]],
collapse = "/"
)
x_translated_guess <- suppressWarnings(as.ab(x_translated, loop_time = loop_time + 2))
if (!is.na(x_translated_guess)) {
x_new[i] <- x_translated_guess
} else if (any(ab_df$lev_trans < 5, na.rm = TRUE)) {
x_new[i] <- ab_df$ab[order(ab_df$lev_trans)][1]
x_uncertain <- c(x_uncertain, x_bak[x[i] == x_bak_clean][1])
next
}
# try by removing all trailing capitals
if (x[i] %like_case% "[a-z]+[A-Z]+$") {
found <- suppressWarnings(as.ab(gsub("[A-Z]+$", "", x[i], perl = TRUE), loop_time = loop_time + 2))
if (!is.na(found)) {
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
} else if (any(ab_df$lev_syn < 5, na.rm = TRUE)) {
x_new[i] <- ab_df$ab[order(ab_df$lev_syn)][1]
x_uncertain <- c(x_uncertain, x_bak[x[i] == x_bak_clean][1])
next
}
}
# keep only letters
found <- suppressWarnings(as.ab(gsub("[^A-Z]", "", x[i], perl = TRUE), loop_time = loop_time + 2))
if (!is.na(found)) {
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
x_uncertain <- c(x_uncertain, x_bak[x[i] == x_bak_clean][1])
next
}
# try from a bigger text, like from a health care record, see ?ab_from_text
# already calculated above if flag_multiple_results = TRUE
if (flag_multiple_results == TRUE) {
found <- from_text[1L]
} else {
found <- tryCatch(suppressWarnings(ab_from_text(x[i], loop_time = loop_time + 2, translate_ab = FALSE)[[1]][1L]),
error = function(e) NA_character_
)
}
if (!is.na(found)) {
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
# then just take name if Levensthein is max 100% of length of name
ab_df$lev_len_ratio <- ab_df$lev_name / ab_df$length_name
if (any(ab_df$lev_len_ratio < 1)) {
ab_df <- ab_df[ab_df$lev_len_ratio < 1, , drop = FALSE]
x_new[i] <- ab_df$ab[order(ab_df$lev_name)][1]
x_uncertain <- c(x_uncertain, x_bak[x[i] == x_bak_clean][1])
next
}
# first 5 except for cephalosporins, then first 7 (those cephalosporins all start quite the same!)
found <- suppressWarnings(as.ab(substr(x[i], 1, 5), loop_time = loop_time + 2))
if (!is.na(found) && ab_group(found, loop_time = loop_time + 1) %unlike% "cephalosporins") {
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
next
}
found <- suppressWarnings(as.ab(substr(x[i], 1, 7), loop_time = loop_time + 2))
if (!is.na(found)) {
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
x_uncertain <- c(x_uncertain, x_bak[x[i] == x_bak_clean][1])
next
}
# make all consonants facultative
search_str <- gsub("([BCDFGHJKLMNPQRSTVWXZ])", "\\1*", x[i], perl = TRUE)
found <- suppressWarnings(as.ab(search_str, loop_time = loop_time + 2, already_regex = TRUE))
# keep at least 4 normal characters
if (nchar(gsub(".\\*", "", search_str, perl = TRUE)) < 4) {
found <- NA
}
if (!is.na(found)) {
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
x_uncertain <- c(x_uncertain, x_bak[x[i] == x_bak_clean][1])
next
}
# make all vowels facultative
search_str <- gsub("([AEIOUY])", "\\1*", x[i], perl = TRUE)
found <- suppressWarnings(as.ab(search_str, loop_time = loop_time + 2, already_regex = TRUE))
# keep at least 5 normal characters
if (nchar(gsub(".\\*", "", search_str, perl = TRUE)) < 5) {
found <- NA
}
if (!is.na(found)) {
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
x_uncertain <- c(x_uncertain, x_bak[x[i] == x_bak_clean][1])
next
}
# allow misspelling of vowels
x_spelling <- gsub("A+", "[AEIOU]+", x_spelling, fixed = TRUE)
x_spelling <- gsub("E+", "[AEIOU]+", x_spelling, fixed = TRUE)
x_spelling <- gsub("I+", "[AEIOU]+", x_spelling, fixed = TRUE)
x_spelling <- gsub("O+", "[AEIOU]+", x_spelling, fixed = TRUE)
x_spelling <- gsub("U+", "[AEIOU]+", x_spelling, fixed = TRUE)
found <- suppressWarnings(as.ab(x_spelling, loop_time = loop_time + 2, already_regex = TRUE))
if (!is.na(found)) {
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
x_uncertain <- c(x_uncertain, x_bak[x[i] == x_bak_clean][1])
next
}
# try with switched character, like "mreopenem"
for (j in seq_len(nchar(x[i]))) {
x_switched <- paste0(
# beginning part:
substr(x[i], 1, j - 1),
# here is the switching of 2 characters:
substr(x[i], j + 1, j + 1),
substr(x[i], j, j),
# ending part:
substr(x[i], j + 2, nchar(x[i]))
)
found <- suppressWarnings(as.ab(x_switched, loop_time = loop_time + 1))
if (!is.na(found)) {
break
}
}
if (!is.na(found)) {
x_new[i] <- found[1L]
x_uncertain <- c(x_uncertain, x_bak[x[i] == x_bak_clean][1])
next
}
} # end of loop_time <= 2
# not found
# nothing found
x_unknown <- c(x_unknown, x_bak[x[i] == x_bak_clean][1])
}
@ -767,16 +597,20 @@ generalise_antibiotic_name <- function(x) {
x <- gsub("[^A-Z0-9 -)(]", "/", x, perl = TRUE)
# correct for 'high level' antibiotics
x <- trimws(gsub("([^A-Z0-9/ -]+)?(HIGH(.?LE?VE?L)?|[^A-Z0-9/]H[^A-Z0-9]?L)([^A-Z0-9 -]+)?", "-HIGH", x, perl = TRUE))
x <- trimws(gsub("^(-HIGH)(.*)", "\\2\\1", x))
x <- trimws(gsub("^(-HIGH)(.*)", "\\2\\1", x, perl = TRUE))
# remove part between brackets if that's followed by another string
x <- gsub("(.*)+ [(].*[)]", "\\1", x)
# spaces around non-characters must be removed: amox + clav -> amox/clav
# spaces around non-characters must be removed: amox + clav -> amox clav
x <- gsub("(.*[A-Z0-9]) ([^A-Z0-9].*)", "\\1\\2", x, perl = TRUE)
x <- gsub("(.*[^A-Z0-9]) ([A-Z0-9].*)", "\\1\\2", x, perl = TRUE)
# remove hyphen after a starting "co"
x <- gsub("^CO-", "CO", x, perl = TRUE)
# replace operators with a space
x <- gsub("(/| AND | WITH | W/|[+]|[-])+", " ", x, perl = TRUE)
# replace more than 1 space
x <- trimws(gsub(" +", " ", x, perl = TRUE))
# move HIGH to end
x <- trimws(gsub("(.*) HIGH(.*)", "\\1\\2 HIGH", x, perl = TRUE))
x
}

8
data-raw/gpt_training_text_v2.1.1.9158.txt → data-raw/gpt_training_text_v2.1.1.9159.txt
View File

@ -1,6 +1,6 @@
This knowledge base contains all context you must know about the AMR package for R. You are a GPT trained to be an assistant for the AMR package in R. You are an incredible R specialist, especially trained in this package and in the tidyverse.
First and foremost, you are trained on version 2.1.1.9158. Remember this whenever someone asks which AMR package version you’re at.
First and foremost, you are trained on version 2.1.1.9159. Remember this whenever someone asks which AMR package version you’re at.
Below are the contents of the file, the file, and all the files (documentation) in the package. Every file content is split using 100 hypens.
----------------------------------------------------------------------------------------------------
@ -2577,7 +2577,8 @@ THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/as.ab.Rd':
\alias{ab_reset_session}
\title{Transform Input to an Antibiotic ID}
\usage{
as.ab(x, flag_multiple_results = TRUE, info = interactive(), ...)
as.ab(x, flag_multiple_results = TRUE, language = get_AMR_locale(),
info = interactive(), ...)
is.ab(x)
@ -2588,6 +2589,8 @@ ab_reset_session()
\item{flag_multiple_results}{a \link{logical} to indicate whether a note should be printed to the console that probably more than one antibiotic drug code or name can be retrieved from a single input value.}
\item{language}{language to coerce input values from any of the 20 supported languages - default to the system language if supported (see \code{\link[=get_AMR_locale]{get_AMR_locale()}})}
\item{info}{a \link{logical} to indicate whether a progress bar should be printed - the default is \code{TRUE} only in interactive mode}
\item{...}{arguments passed on to internal functions}
@ -2644,7 +2647,6 @@ as.ab("J01FA01")
as.ab("J 01 FA 01")
as.ab("Erythromycin")
as.ab("eryt")
as.ab(" eryt 123")
as.ab("ERYT")
as.ab("ERY")
as.ab("eritromicine") # spelled wrong, yet works

6
man/as.ab.Rd
View File

@ -7,7 +7,8 @@
\alias{ab_reset_session}
\title{Transform Input to an Antibiotic ID}
\usage{
as.ab(x, flag_multiple_results = TRUE, info = interactive(), ...)
as.ab(x, flag_multiple_results = TRUE, language = get_AMR_locale(),
info = interactive(), ...)
is.ab(x)
@ -18,6 +19,8 @@ ab_reset_session()
\item{flag_multiple_results}{a \link{logical} to indicate whether a note should be printed to the console that probably more than one antibiotic drug code or name can be retrieved from a single input value.}
\item{language}{language to coerce input values from any of the 20 supported languages - default to the system language if supported (see \code{\link[=get_AMR_locale]{get_AMR_locale()}})}
\item{info}{a \link{logical} to indicate whether a progress bar should be printed - the default is \code{TRUE} only in interactive mode}
\item{...}{arguments passed on to internal functions}
@ -74,7 +77,6 @@ as.ab("J01FA01")
as.ab("J 01 FA 01")
as.ab("Erythromycin")
as.ab("eryt")
as.ab(" eryt 123")
as.ab("ERYT")
as.ab("ERY")
as.ab("eritromicine") # spelled wrong, yet works

7
tests/testthat/test-ab.R
View File

@ -27,20 +27,21 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
ab_reset_session()
expect_equal(
as.character(as.ab(c(
"J01FA01",
"J 01 FA 01",
"Erythromycin",
"eryt",
" eryt 123",
"ERYT",
"ERY",
"erytromicine",
"Erythrocin",
"Romycin"
))),
rep("ERY", 10)
rep("ERY", 9)
)
expect_identical(class(as.ab("amox")), c("ab", "character"))
@ -49,7 +50,7 @@ expect_true(is.ab(as.ab("amox")))
expect_stdout(print(as.ab("amox")))
expect_stdout(print(data.frame(a = as.ab("amox"))))
# expect_warning(as.ab("J00AA00")) # ATC not yet available in data set
expect_warning(as.ab("J00AA00")) # ATC not yet available in data set
# expect_warning(as.ab("UNKNOWN"))
expect_stdout(print(as.ab("amox")))

14
tests/testthat/test-ab_from_text.R
View File

@ -27,20 +27,22 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
ab_reset_session()
expect_identical(
ab_from_text("28/03/2020 regular amoxicilliin 500mg po tds")[[1]],
ab_from_text("28/03/2020 amoxicilliin 500mg po tds")[[1]],
as.ab("Amoxicillin")
)
expect_identical(
ab_from_text("28/03/2020 regular amoxicilliin 500mg po tds", thorough_search = TRUE)[[1]],
ab_from_text("28/03/2020 amoxicilliin 500mg po tds", thorough_search = TRUE)[[1]],
as.ab("Amoxicillin")
)
expect_identical(
ab_from_text("28/03/2020 regular amoxicilliin 500mg po tds", thorough_search = FALSE)[[1]],
ab_from_text("28/03/2020 amoxicilliin 500mg po tds", thorough_search = FALSE)[[1]],
as.ab("Amoxicillin")
)
expect_identical(
ab_from_text("28/03/2020 regular amoxicilliin 500mg po tds", translate_ab = TRUE)[[1]],
ab_from_text("28/03/2020 amoxicilliin 500mg po tds", translate_ab = TRUE)[[1]],
"Amoxicillin"
)
expect_identical(
@ -49,10 +51,10 @@ expect_identical(
)
expect_identical(
ab_from_text("28/03/2020 regular amoxicilliin 500mg po tds", type = "dose")[[1]],
ab_from_text("28/03/2020 amoxicilliin 500mg po tds", type = "dose")[[1]],
500
)
expect_identical(
ab_from_text("28/03/2020 regular amoxicilliin 500mg po tds", type = "admin")[[1]],
ab_from_text("28/03/2020 amoxicilliin 500mg po tds", type = "admin")[[1]],
"oral"
)

3
tests/testthat/test-ab_property.R
View File

@ -27,6 +27,8 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
ab_reset_session()
expect_identical(ab_name("AMX", language = NULL), "Amoxicillin")
expect_identical(ab_atc("AMX"), "J01CA04")
expect_identical(ab_cid("AMX"), as.integer(33613))
@ -94,3 +96,4 @@ if (AMR:::pkg_is_available("dplyr", min_version = "1.0.0", also_load = TRUE)) {
set_ab_names(NIT:VAN) %>%
colnames())))
}