(v3.0.0.9019) Fixes #229, #230, #227, #225

.github/prehooks/pre-commit

@@ -68,49 +68,56 @@ echo ""
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 echo "Updating semantic versioning and date..."
 
-# Get tags from remote and remove tags not on remote
-git fetch origin --prune --prune-tags --quiet
-currenttagfull=$(git describe --tags --abbrev=0)
-currenttag=$(git describe --tags --abbrev=0 | sed 's/v//')
-
-# Assume main branch to be 'main' or 'master'
-defaultbranch=$(git branch | cut -c 3- | grep -E '^master$|^main$')
-if [ "$currenttag" = "" ]; then
-  currenttag="0.0.1"
-  currentcommit=$(git rev-list --count ${defaultbranch})
-  echo "- No git tags found, creating one in format 'v(x).(y).(z)' - currently ${currentcommit} previous commits in '${defaultbranch}'"
+current_branch=$(git rev-parse --abbrev-ref HEAD)
+if [ "$current_branch" != "main" ]; then
+  echo "- Current branch is '$current_branch'; skipping version/date update (only runs on 'main')"
 else
-  currentcommit=$(git rev-list --count ${currenttagfull}..${defaultbranch})
-  echo "- Latest tag is '${currenttagfull}', with ${currentcommit} previous commits in '${defaultbranch}'"
-fi
+  # Version update logic begins here
   
-# Combine tag and commit number
-currentversion="$currenttag.$((currentcommit + 9001))"
-echo "- ${currentpkg} pkg version set to ${currentversion}"
+  # Get tags from remote and remove tags not on remote
+  git fetch origin --prune --prune-tags --quiet
+  currenttagfull=$(git describe --tags --abbrev=0)
+  currenttag=$(git describe --tags --abbrev=0 | sed 's/v//')
   
-# Update version number and date in DESCRIPTION
-sed -i -- "s/^Version: .*/Version: ${currentversion}/" DESCRIPTION
-sed -i -- "s/^Date: .*/Date: $(date '+%Y-%m-%d')/" DESCRIPTION
-echo "- Updated version number and date in ./DESCRIPTION"
-rm -f DESCRIPTION--
-git add DESCRIPTION
-
-# Update version number in NEWS.md
-if [ -e "NEWS.md" ]; then
-  if [ "$currentpkg" = "your" ]; then
-    currentpkg=""
+  # Assume main branch to be 'main' or 'master'
+  defaultbranch=$(git branch | cut -c 3- | grep -E '^master$|^main$')
+  if [ "$currenttag" = "" ]; then
+    currenttag="0.0.1"
+    currentcommit=$(git rev-list --count ${defaultbranch})
+    echo "- No git tags found, creating one in format 'v(x).(y).(z)' - currently ${currentcommit} previous commits in '${defaultbranch}'"
+  else
+    currentcommit=$(git rev-list --count ${currenttagfull}..${defaultbranch})
+    echo "- Latest tag is '${currenttagfull}', with ${currentcommit} previous commits in '${defaultbranch}'"
   fi
-  sed -i -- "1s/.*/# ${currentpkg} ${currentversion}/" NEWS.md
-  echo "- Updated version number in ./NEWS.md"
-  rm -f NEWS.md--
-  git add NEWS.md
-else
-  echo "- No NEWS.md found!"
-fi
-echo ""
   
-# Save the version number for use in the commit-msg hook
-echo "${currentversion}" > .git/commit_version.tmp
+  # Combine tag and commit number
+  currentversion="$currenttag.$((currentcommit + 9001))"
+  echo "- ${currentpkg} pkg version set to ${currentversion}"
+  
+  # Update version number and date in DESCRIPTION
+  sed -i -- "s/^Version: .*/Version: ${currentversion}/" DESCRIPTION
+  sed -i -- "s/^Date: .*/Date: $(date '+%Y-%m-%d')/" DESCRIPTION
+  echo "- Updated version number and date in ./DESCRIPTION"
+  rm -f DESCRIPTION--
+  git add DESCRIPTION
+  
+  # Update version number in NEWS.md
+  if [ -e "NEWS.md" ]; then
+    if [ "$currentpkg" = "your" ]; then
+      currentpkg=""
+    fi
+    sed -i -- "1s/.*/# ${currentpkg} ${currentversion}/" NEWS.md
+    echo "- Updated version number in ./NEWS.md"
+    rm -f NEWS.md--
+    git add NEWS.md
+  else
+    echo "- No NEWS.md found!"
+  fi
+  echo ""
+  
+  # Save the version number for use in the commit-msg hook
+  echo "${currentversion}" > .git/commit_version.tmp
+fi
 
 git add data-raw/*
 git add data/*

.github/workflows/check-old-tinytest.yaml

@@ -59,8 +59,15 @@ jobs:
 
     env:
       R_REMOTES_NO_ERRORS_FROM_WARNINGS: true
+      LANG: en_US.UTF-8
+      LC_ALL: en_US.UTF-8
 
     steps:
+      - name: Set up locales
+        run: |
+          sudo locale-gen en_US.UTF-8
+          sudo update-locale LANG=en_US.UTF-8
+
       - uses: actions/checkout@v4
 
       - uses: r-lib/actions/setup-r@v2

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: AMR
-Version: 3.0.0.9004
-Date: 2025-06-13
+Version: 3.0.0.9019
+Date: 2025-09-01
 Title: Antimicrobial Resistance Data Analysis
 Description: Functions to simplify and standardise antimicrobial resistance (AMR)
   data analysis and to work with microbial and antimicrobial properties by

NEWS.md

@@ -1,16 +1,30 @@
-# AMR 3.0.0.9004
+# AMR 3.0.0.9019
+
+This is primarily a bugfix release, though we added one nice feature too.
 
 ### New
 * Integration with the **tidymodels** framework to allow seamless use of MIC and SIR data in modelling pipelines via `recipes`
   - `step_mic_log2()` to transform `<mic>` columns with log2, and `step_sir_numeric()` to convert `<sir>` columns to numeric
-  - `tidyselect` helpers: `all_mic()`, `all_mic_predictors()`, `all_sir()`, `all_sir_predictors()`
-  - Enables seamless use of MIC and SIR data in modelling pipelines via `recipes`
+  - New `tidyselect` helpers: `all_mic()`, `all_mic_predictors()`, `all_sir()`, `all_sir_predictors()`
 
 ### Changed
 * Fixed a bug in `antibiogram()` for when no antimicrobials are set
+* Fixed a bug in `antibiogram()` to allow column names containing the `+` character (#222)
 * Fixed a bug in `as.ab()` for antimicrobial codes with a number in it if they are preceded by a space
 * Fixed a bug in `eucast_rules()` for using specific custom rules
+* Fixed a bug in `as.sir()` to allow any tidyselect language (#220)
+* Fixed a bug in `as.sir()` to pick right breakpoint when `uti = FALSE` (#216)
+* Fixed a bug in `ggplot_sir()` when using `combine_SI = FALSE` (#213)
+* Fixed a bug the `antimicrobials` data set to remove statins (#229)
+* Fixed a bug in `mdro()` to make sure all genes specified in arguments are acknowledges
+* Fixed ATC J01CR05 to map to piperacillin/tazobactam rather than piperacillin/sulbactam (#230)
+* Fixed all plotting to contain a separate colour for SDD (susceptible dose-dependent) (#223)
 * Fixed some specific Dutch translations for antimicrobials
+* Added all reasons in verbose output of `mdro()` (#227)
+* Added `names` to `age_groups()` so that custom names can be given (#215)
+* Added note to `as.sir()` to make it explicit when higher-level taxonomic breakpoints are used (#218)
+* Added antibiotic codes from the Comprehensive Antibiotic Resistance Database (CARD) to the `antimicrobials` data set (#225)
+* Updated Fosfomycin to be of antibiotic class 'Phosphonics' (#225)
 * Updated `random_mic()` and `random_disk()` to set skewedness of the distribution and allow multiple microorganisms
 
 

R/aa_helper_functions.R

@@ -63,31 +63,6 @@ pm_left_join <- function(x, y, by = NULL, suffix = c(".x", ".y")) {
   merged
 }
 
-# support where() like tidyverse (this function will also be used when running `antibiogram()`):
-where <- function(fn) {
-  # based on https://github.com/nathaneastwood/poorman/blob/52eb6947e0b4430cd588976ed8820013eddf955f/R/where.R#L17-L32
-  if (!is.function(fn)) {
-    stop_("`", deparse(substitute(fn)), "()` is not a valid predicate function.")
-  }
-  df <- pm_select_env$.data
-  cols <- pm_select_env$get_colnames()
-  if (is.null(df)) {
-    df <- get_current_data("where", call = FALSE)
-    cols <- colnames(df)
-  }
-  preds <- unlist(lapply(
-    df,
-    function(x, fn) {
-      do.call("fn", list(x))
-    },
-    fn
-  ))
-  if (!is.logical(preds)) stop_("`where()` must be used with functions that return `TRUE` or `FALSE`.")
-  data_cols <- cols
-  cols <- data_cols[preds]
-  which(data_cols %in% cols)
-}
-
 # copied and slightly rewritten from {poorman} under permissive license (2021-10-15)
 # https://github.com/nathaneastwood/poorman, MIT licensed, Nathan Eastwood, 2020
 case_when_AMR <- function(...) {
@@ -544,7 +519,7 @@ word_wrap <- function(...,
     )
     msg <- paste0(parts, collapse = "`")
   }
-  msg <- gsub("`(.+?)`", font_grey_bg("\\1"), msg)
+  msg <- gsub("`(.+?)`", font_grey_bg("`\\1`"), msg)
 
   # clean introduced whitespace in between fullstops
   msg <- gsub("[.] +[.]", "..", msg)
@@ -814,7 +789,7 @@ meet_criteria <- function(object, # can be literally `list(...)` for `allow_argu
 
   # if object is missing, or another error:
   tryCatch(invisible(object),
-    error = function(e) AMR_env$meet_criteria_error_txt <- e$message
+    error = function(e) AMR_env$meet_criteria_error_txt <- conditionMessage(e)
   )
   if (!is.null(AMR_env$meet_criteria_error_txt)) {
     error_txt <- AMR_env$meet_criteria_error_txt
@@ -1319,6 +1294,10 @@ font_green_bg <- function(..., collapse = " ") {
   # this is #3caea3 (picked to be colourblind-safe with other SIR colours)
   try_colour(font_black(..., collapse = collapse, adapt = FALSE), before = "\033[48;5;79m", after = "\033[49m", collapse = collapse)
 }
+font_green_lighter_bg <- function(..., collapse = " ") {
+  # this is #8FD6C4 (picked to be colourblind-safe with other SIR colours)
+  try_colour(font_black(..., collapse = collapse, adapt = FALSE), before = "\033[48;5;158m", after = "\033[49m", collapse = collapse)
+}
 font_purple_bg <- function(..., collapse = " ") {
   try_colour(font_black(..., collapse = collapse, adapt = FALSE), before = "\033[48;5;89m", after = "\033[49m", collapse = collapse)
 }
@@ -1636,6 +1615,36 @@ get_n_cores <- function(max_cores = Inf) {
   n_cores
 }
 
+# Support `where()` if tidyselect not installed ----
+if (!is.null(import_fn("where", "tidyselect", error_on_fail = FALSE))) {
+  # tidyselect::where() exists, load the namespace to make `where()`s work across the package in default arguments
+  loadNamespace("tidyselect")
+} else {
+  where <- function(fn) {
+    # based on https://github.com/nathaneastwood/poorman/blob/52eb6947e0b4430cd588976ed8820013eddf955f/R/where.R#L17-L32
+    if (!is.function(fn)) {
+      stop_("`", deparse(substitute(fn)), "()` is not a valid predicate function.")
+    }
+    df <- pm_select_env$.data
+    cols <- pm_select_env$get_colnames()
+    if (is.null(df)) {
+      df <- get_current_data("where", call = FALSE)
+      cols <- colnames(df)
+    }
+    preds <- unlist(lapply(
+      df,
+      function(x, fn) {
+        do.call("fn", list(x))
+      },
+      fn
+    ))
+    if (!is.logical(preds)) stop_("`where()` must be used with functions that return `TRUE` or `FALSE`.")
+    data_cols <- cols
+    cols <- data_cols[preds]
+    which(data_cols %in% cols)
+  }
+}
+
 # Faster data.table implementations ----
 
 match <- function(x, table, ...) {
@@ -1655,52 +1664,6 @@ match <- function(x, table, ...) {
   }
 }
 
-# nolint start
-
-# Register S3 methods ----
-# copied from vctrs::s3_register by their permission:
-# https://github.com/r-lib/vctrs/blob/05968ce8e669f73213e3e894b5f4424af4f46316/R/register-s3.R
-s3_register <- function(generic, class, method = NULL) {
-  stopifnot(is.character(generic), length(generic) == 1)
-  stopifnot(is.character(class), length(class) == 1)
-  pieces <- strsplit(generic, "::")[[1]]
-  stopifnot(length(pieces) == 2)
-  package <- pieces[[1]]
-  generic <- pieces[[2]]
-  caller <- parent.frame()
-  get_method_env <- function() {
-    top <- topenv(caller)
-    if (isNamespace(top)) {
-      asNamespace(environmentName(top))
-    } else {
-      caller
-    }
-  }
-  get_method <- function(method, env) {
-    if (is.null(method)) {
-      get(paste0(generic, ".", class), envir = get_method_env())
-    } else {
-      method
-    }
-  }
-  method_fn <- get_method(method)
-  stopifnot(is.function(method_fn))
-  setHook(packageEvent(package, "onLoad"), function(...) {
-    ns <- asNamespace(package)
-    method_fn <- get_method(method)
-    registerS3method(generic, class, method_fn, envir = ns)
-  })
-  if (!isNamespaceLoaded(package)) {
-    return(invisible())
-  }
-  envir <- asNamespace(package)
-  if (exists(generic, envir)) {
-    registerS3method(generic, class, method_fn, envir = envir)
-  }
-  invisible()
-}
-
-
 # Support old R versions ----
 # these functions were not available in previous versions of R
 # see here for the full list: https://github.com/r-lib/backports

R/aa_helper_pm_functions.R

@@ -952,7 +952,19 @@ pm_select_env$get_nrow <- function() nrow(pm_select_env$.data)
 pm_select_env$get_ncol <- function() ncol(pm_select_env$.data)
 
 pm_select <- function(.data, ...) {
-  col_pos <- pm_select_positions(.data, ..., .group_pos = TRUE)
+  # col_pos <- pm_select_positions(.data, ..., .group_pos = TRUE),
+  col_pos <- tryCatch(pm_select_positions(.data, ..., .group_pos = TRUE), error = function(e) NULL)
+  if (is.null(col_pos)) {
+    # try with tidyverse
+    select_dplyr <- import_fn("select", "dplyr", error_on_fail = FALSE)
+    if (!is.null(select_dplyr)) {
+      col_pos <- which(colnames(.data) %in% colnames(select_dplyr(.data, ...)))
+    } else {
+      # this will throw an error as it did, but dplyr is not available, so no other option
+      col_pos <- pm_select_positions(.data, ..., .group_pos = TRUE)
+    }
+  }
+
   map_names <- names(col_pos)
   map_names_length <- nchar(map_names)
   if (any(map_names_length == 0L)) {

R/ab.R

@@ -184,7 +184,8 @@ as.ab <- function(x, flag_multiple_results = TRUE, language = get_AMR_locale(),
   x_new[known_codes_cid] <- AMR_env$AB_lookup$ab[match(x[known_codes_cid], AMR_env$AB_lookup$cid)]
   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)]
-  if (any(previously_coerced) && isTRUE(info) && message_not_thrown_before("as.ab", entire_session = TRUE)) {
+  previously_coerced_mention <- x %in% AMR_env$ab_previously_coerced$x & !x %in% AMR_env$AB_lookup$ab & !x %in% AMR_env$AB_lookup$generalised_name
+  if (any(previously_coerced_mention) && isTRUE(info) && message_not_thrown_before("as.ab", entire_session = TRUE)) {
     message_(
       "Returning previously coerced ",
       ifelse(length(unique(which(x[which(previously_coerced)] %in% x_bak_clean))) > 1, "value for an antimicrobial", "values for various antimicrobials"),

R/ab_property.R

@@ -445,7 +445,7 @@ ab_validate <- function(x, property, ...) {
     # try to catch an error when inputting an invalid argument
     # so the 'call.' can be set to FALSE
     tryCatch(x[1L] %in% AMR_env$AB_lookup[1, property, drop = TRUE],
-      error = function(e) stop(e$message, call. = FALSE)
+      error = function(e) stop(conditionMessage(e), call. = FALSE)
     )
 
     if (!all(x %in% AMR_env$AB_lookup[, property, drop = TRUE])) {

R/age.R

@@ -128,9 +128,10 @@ age <- function(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...) {
 
 #' Split Ages into Age Groups
 #'
-#' Split ages into age groups defined by the `split` argument. This allows for easier demographic (antimicrobial resistance) analysis.
+#' Split ages into age groups defined by the `split` argument. This allows for easier demographic (antimicrobial resistance) analysis. The function returns an ordered [factor].
 #' @param x Age, e.g. calculated with [age()].
 #' @param split_at Values to split `x` at - the default is age groups 0-11, 12-24, 25-54, 55-74 and 75+. See *Details*.
+#' @param names Optional names to be given to the various age groups.
 #' @param na.rm A [logical] to indicate whether missing values should be removed.
 #' @details To split ages, the input for the `split_at` argument can be:
 #'
@@ -152,6 +153,7 @@ age <- function(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...) {
 #'
 #' # split into 0-19, 20-49 and 50+
 #' age_groups(ages, c(20, 50))
+#' age_groups(ages, c(20, 50), names = c("Under 20 years", "20 to 50 years", "Over 50 years"))
 #'
 #' # split into groups of ten years
 #' age_groups(ages, 1:10 * 10)
@@ -181,9 +183,10 @@ age <- function(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...) {
 #'     )
 #' }
 #' }
-age_groups <- function(x, split_at = c(12, 25, 55, 75), na.rm = FALSE) {
+age_groups <- function(x, split_at = c(0, 12, 25, 55, 75), names = NULL, na.rm = FALSE) {
   meet_criteria(x, allow_class = c("numeric", "integer"), is_positive_or_zero = TRUE, is_finite = TRUE)
   meet_criteria(split_at, allow_class = c("numeric", "integer", "character"), is_positive_or_zero = TRUE, is_finite = TRUE)
+  meet_criteria(names, allow_class = "character", allow_NULL = TRUE)
   meet_criteria(na.rm, allow_class = "logical", has_length = 1)
 
   if (any(x < 0, na.rm = TRUE)) {
@@ -224,6 +227,11 @@ age_groups <- function(x, split_at = c(12, 25, 55, 75), na.rm = FALSE) {
 
   agegroups <- factor(lbls[y], levels = lbls, ordered = TRUE)
 
+  if (!is.null(names)) {
+    stop_ifnot(length(names) == length(levels(agegroups)), "`names` must have the same length as the number of age groups (", length(levels(agegroups)), ").")
+    levels(agegroups) <- names
+  }
+
   if (isTRUE(na.rm)) {
     agegroups <- agegroups[!is.na(agegroups)]
   }

R/amr_selectors.R

@@ -527,7 +527,7 @@ amr_selector <- function(filter,
   )
   call <- substitute(filter)
   agents <- tryCatch(AMR_env$AB_lookup[which(eval(call, envir = AMR_env$AB_lookup)), "ab", drop = TRUE],
-    error = function(e) stop_(e$message, call = -5)
+    error = function(e) stop_(conditionMessage(e), call = -5)
   )
   agents <- ab_in_data[ab_in_data %in% agents]
   message_agent_names(
@@ -640,7 +640,7 @@ not_intrinsic_resistant <- function(only_sir_columns = FALSE, col_mo = NULL, ver
         )
       }
     ),
-    error = function(e) stop_("in not_intrinsic_resistant(): ", e$message, call = FALSE)
+    error = function(e) stop_("in not_intrinsic_resistant(): ", conditionMessage(e), call = FALSE)
   )
 
   agents <- ab_in_data[ab_in_data %in% names(vars_df_R[which(vars_df_R)])]

R/antibiogram.R

@@ -576,6 +576,15 @@ antibiogram.default <- function(x,
     }
     antimicrobials <- unlist(antimicrobials)
   } else {
+    existing_ab_combined_cols <- ab_trycatch[ab_trycatch %like% "[+]" & ab_trycatch %in% colnames(x)]
+    if (length(existing_ab_combined_cols) > 0 && !is.null(ab_transform)) {
+      ab_transform <- NULL
+      warning_(
+        "Detected column name(s) containing the '+' character, which conflicts with the expected syntax in `antibiogram()`: the '+' is used to combine separate antimicrobial agent columns (e.g., \"AMP+GEN\").\n\n",
+        "To avoid incorrectly guessing which antimicrobials this represents, `ab_transform` was automatically set to `NULL`.\n\n",
+        "If this is unintended, please rename the column(s) to avoid using '+' in the name, or set `ab_transform = NULL` explicitly to suppress this message."
+      )
+    }
     antimicrobials <- ab_trycatch
   }
 

R/av_property.R

@@ -264,7 +264,7 @@ av_validate <- function(x, property, ...) {
     # try to catch an error when inputting an invalid argument
     # so the 'call.' can be set to FALSE
     tryCatch(x[1L] %in% AMR_env$AV_lookup[1, property, drop = TRUE],
-      error = function(e) stop(e$message, call. = FALSE)
+      error = function(e) stop(conditionMessage(e), call. = FALSE)
     )
 
     if (!all(x %in% AMR_env$AV_lookup[, property, drop = TRUE])) {

R/count.R

@@ -126,7 +126,7 @@ count_resistant <- function(..., only_all_tested = FALSE) {
       only_all_tested = only_all_tested,
       only_count = TRUE
     ),
-    error = function(e) stop_(gsub("in sir_calc(): ", "", e$message, fixed = TRUE), call = -5)
+    error = function(e) stop_(gsub("in sir_calc(): ", "", conditionMessage(e), fixed = TRUE), call = -5)
   )
 }
 
@@ -139,7 +139,7 @@ count_susceptible <- function(..., only_all_tested = FALSE) {
       only_all_tested = only_all_tested,
       only_count = TRUE
     ),
-    error = function(e) stop_(gsub("in sir_calc(): ", "", e$message, fixed = TRUE), call = -5)
+    error = function(e) stop_(gsub("in sir_calc(): ", "", conditionMessage(e), fixed = TRUE), call = -5)
   )
 }
 
@@ -152,7 +152,7 @@ count_S <- function(..., only_all_tested = FALSE) {
       only_all_tested = only_all_tested,
       only_count = TRUE
     ),
-    error = function(e) stop_(gsub("in sir_calc(): ", "", e$message, fixed = TRUE), call = -5)
+    error = function(e) stop_(gsub("in sir_calc(): ", "", conditionMessage(e), fixed = TRUE), call = -5)
   )
 }
 
@@ -165,7 +165,7 @@ count_SI <- function(..., only_all_tested = FALSE) {
       only_all_tested = only_all_tested,
       only_count = TRUE
     ),
-    error = function(e) stop_(gsub("in sir_calc(): ", "", e$message, fixed = TRUE), call = -5)
+    error = function(e) stop_(gsub("in sir_calc(): ", "", conditionMessage(e), fixed = TRUE), call = -5)
   )
 }
 
@@ -178,7 +178,7 @@ count_I <- function(..., only_all_tested = FALSE) {
       only_all_tested = only_all_tested,
       only_count = TRUE
     ),
-    error = function(e) stop_(gsub("in sir_calc(): ", "", e$message, fixed = TRUE), call = -5)
+    error = function(e) stop_(gsub("in sir_calc(): ", "", conditionMessage(e), fixed = TRUE), call = -5)
   )
 }
 
@@ -191,7 +191,7 @@ count_IR <- function(..., only_all_tested = FALSE) {
       only_all_tested = only_all_tested,
       only_count = TRUE
     ),
-    error = function(e) stop_(gsub("in sir_calc(): ", "", e$message, fixed = TRUE), call = -5)
+    error = function(e) stop_(gsub("in sir_calc(): ", "", conditionMessage(e), fixed = TRUE), call = -5)
   )
 }
 
@@ -204,7 +204,7 @@ count_R <- function(..., only_all_tested = FALSE) {
       only_all_tested = only_all_tested,
       only_count = TRUE
     ),
-    error = function(e) stop_(gsub("in sir_calc(): ", "", e$message, fixed = TRUE), call = -5)
+    error = function(e) stop_(gsub("in sir_calc(): ", "", conditionMessage(e), fixed = TRUE), call = -5)
   )
 }
 
@@ -217,7 +217,7 @@ count_all <- function(..., only_all_tested = FALSE) {
       only_all_tested = only_all_tested,
       only_count = TRUE
     ),
-    error = function(e) stop_(gsub("in sir_calc(): ", "", e$message, fixed = TRUE), call = -5)
+    error = function(e) stop_(gsub("in sir_calc(): ", "", conditionMessage(e), fixed = TRUE), call = -5)
   )
 }
 
@@ -240,6 +240,6 @@ count_df <- function(data,
       combine_SI = combine_SI,
       confidence_level = 0.95 # doesn't matter, will be removed
     ),
-    error = function(e) stop_(gsub("in sir_calc_df(): ", "", e$message, fixed = TRUE), call = -5)
+    error = function(e) stop_(gsub("in sir_calc_df(): ", "", conditionMessage(e), fixed = TRUE), call = -5)
   )
 }

R/custom_mdro_guideline.R

@@ -175,7 +175,7 @@ custom_mdro_guideline <- function(..., as_factor = TRUE) {
 
     # Value
     val <- tryCatch(eval(dots[[i]][[3]]), error = function(e) NULL)
-    stop_if(is.null(val), "rule ", i, " must return a valid value, it now returns an error: ", tryCatch(eval(dots[[i]][[3]]), error = function(e) e$message))
+    stop_if(is.null(val), "rule ", i, " must return a valid value, it now returns an error: ", tryCatch(eval(dots[[i]][[3]]), error = function(e) conditionMessage(e)))
     stop_if(length(val) > 1, "rule ", i, " must return a value of length 1, not ", length(val))
     out[[i]]$value <- as.character(val)
   }
@@ -254,7 +254,7 @@ run_custom_mdro_guideline <- function(df, guideline, info) {
   for (i in seq_len(n_dots)) {
     qry <- tryCatch(eval(parse(text = guideline[[i]]$query), envir = df, enclos = parent.frame()),
       error = function(e) {
-        AMR_env$err_msg <- e$message
+        AMR_env$err_msg <- conditionMessage(e)
         return("error")
       }
     )

R/eucast_rules.R

@@ -1178,7 +1178,7 @@ edit_sir <- function(x,
             ifelse(length(rows) > 10, "...", ""),
             " while writing value '", to,
             "' to column(s) `", paste(cols, collapse = "`, `"),
-            "`:\n", e$message
+            "`:\n", conditionMessage(e)
           ),
           call. = FALSE
         )

R/ggplot_sir.R

@@ -177,6 +177,7 @@ ggplot_sir <- function(data,
                        nrow = NULL,
                        colours = c(
                          S = "#3CAEA3",
+                         SDD = "#8FD6C4",
                          SI = "#3CAEA3",
                          I = "#F6D55C",
                          IR = "#ED553B",
@@ -205,7 +206,7 @@ ggplot_sir <- function(data,
   meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_positive_or_zero = TRUE, is_finite = TRUE)
   language <- validate_language(language)
   meet_criteria(nrow, allow_class = c("numeric", "integer"), has_length = 1, allow_NULL = TRUE, is_positive = TRUE, is_finite = TRUE)
-  meet_criteria(colours, allow_class = c("character", "logical"))
+  meet_criteria(colours, allow_class = c("character", "logical"), allow_NULL = TRUE)
   meet_criteria(datalabels, allow_class = "logical", has_length = 1)
   meet_criteria(datalabels.size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
   meet_criteria(datalabels.colour, allow_class = "character", has_length = 1)
@@ -245,7 +246,7 @@ ggplot_sir <- function(data,
     ) +
     theme_sir()
 
-  if (fill == "interpretation") {
+  if (fill == "interpretation" && !is.null(colours) && !isFALSE(colours)) {
     p <- suppressWarnings(p + scale_sir_colours(aesthetics = "fill", colours = colours))
   }
 

R/mdro.R

@@ -41,7 +41,7 @@
 #' @inheritParams eucast_rules
 #' @param pct_required_classes Minimal required percentage of antimicrobial classes that must be available per isolate, rounded down. For example, with the default guideline, 17 antimicrobial classes must be available for *S. aureus*. Setting this `pct_required_classes` argument to `0.5` (default) means that for every *S. aureus* isolate at least 8 different classes must be available. Any lower number of available classes will return `NA` for that isolate.
 #' @param combine_SI A [logical] to indicate whether all values of S and I must be merged into one, so resistance is only considered when isolates are R, not I. As this is the default behaviour of the [mdro()] function, it follows the redefinition by EUCAST about the interpretation of I (increased exposure) in 2019, see section 'Interpretation of S, I and R' below. When using `combine_SI = FALSE`, resistance is considered when isolates are R or I.
-#' @param verbose A [logical] to turn Verbose mode on and off (default is off). In Verbose mode, the function does not return the MDRO results, but instead returns a data set in logbook form with extensive info about which isolates would be MDRO-positive, or why they are not.
+#' @param verbose A [logical] to turn Verbose mode on and off (default is off). In Verbose mode, the function returns a data set with the MDRO results in logbook form with extensive info about which isolates would be MDRO-positive, or why they are not.
 #' @details
 #' These functions are context-aware. This means that the `x` argument can be left blank if used inside a [data.frame] call, see *Examples*.
 #'
@@ -174,48 +174,23 @@ mdro <- function(x = NULL,
   }
 
   # get gene values as TRUE/FALSE
-  if (is.character(esbl)) {
-    meet_criteria(esbl, is_in = colnames(x), allow_NA = FALSE, has_length = 1)
-    esbl <- x[[esbl]]
-    meet_criteria(esbl, allow_class = "logical", allow_NA = TRUE)
-  } else if (length(esbl) == 1) {
-    esbl <- rep(esbl, NROW(x))
-  }
-  if (is.character(carbapenemase)) {
-    meet_criteria(carbapenemase, is_in = colnames(x), allow_NA = FALSE, has_length = 1)
-    carbapenemase <- x[[carbapenemase]]
-    meet_criteria(carbapenemase, allow_class = "logical", allow_NA = TRUE)
-  } else if (length(carbapenemase) == 1) {
-    carbapenemase <- rep(carbapenemase, NROW(x))
-  }
-  if (is.character(mecA)) {
-    meet_criteria(mecA, is_in = colnames(x), allow_NA = FALSE, has_length = 1)
-    mecA <- x[[mecA]]
-    meet_criteria(mecA, allow_class = "logical", allow_NA = TRUE)
-  } else if (length(mecA) == 1) {
-    mecA <- rep(mecA, NROW(x))
-  }
-  if (is.character(mecC)) {
-    meet_criteria(mecC, is_in = colnames(x), allow_NA = FALSE, has_length = 1)
-    mecC <- x[[mecC]]
-    meet_criteria(mecC, allow_class = "logical", allow_NA = TRUE)
-  } else if (length(mecC) == 1) {
-    mecC <- rep(mecC, NROW(x))
-  }
-  if (is.character(vanA)) {
-    meet_criteria(vanA, is_in = colnames(x), allow_NA = FALSE, has_length = 1)
-    vanA <- x[[vanA]]
-    meet_criteria(vanA, allow_class = "logical", allow_NA = TRUE)
-  } else if (length(vanA) == 1) {
-    vanA <- rep(vanA, NROW(x))
-  }
-  if (is.character(vanB)) {
-    meet_criteria(vanB, is_in = colnames(x), allow_NA = FALSE, has_length = 1)
-    vanB <- x[[vanB]]
-    meet_criteria(vanB, allow_class = "logical", allow_NA = TRUE)
-  } else if (length(vanB) == 1) {
-    vanB <- rep(vanB, NROW(x))
+  resolve_gene_var <- function(x, gene, varname) {
+    if (is.character(gene)) {
+      meet_criteria(gene, is_in = colnames(x), allow_NA = FALSE, has_length = 1)
+      gene <- x[[gene]]
+      meet_criteria(gene, allow_class = "logical", allow_NA = TRUE)
+    } else if (length(gene) == 1) {
+      gene <- rep(gene, NROW(x))
+    }
+    x[[varname]] <- gene
+    x
   }
+  x <- resolve_gene_var(x, esbl, "esbl")
+  x <- resolve_gene_var(x, carbapenemase, "carbapenemase")
+  x <- resolve_gene_var(x, mecA, "mecA")
+  x <- resolve_gene_var(x, mecC, "mecC")
+  x <- resolve_gene_var(x, vanA, "vanA")
+  x <- resolve_gene_var(x, vanB, "vanB")
 
   info.bak <- info
   # don't throw info's more than once per call
@@ -772,7 +747,7 @@ mdro <- function(x = NULL,
         )
       }
       x[rows_to_change, "MDRO"] <<- to
-      x[rows_to_change, "reason"] <<- reason
+      x[rows_to_change, "reason"] <<- paste0(x[rows_to_change, "reason", drop = TRUE], "; ", reason)
       x[rows_not_to_change, "reason"] <<- "guideline criteria not met"
     }
   }
@@ -854,7 +829,7 @@ mdro <- function(x = NULL,
   x <- left_join_microorganisms(x, by = col_mo)
   x$MDRO <- ifelse(!is.na(x$genus), 1, NA_integer_)
   x$row_number <- seq_len(nrow(x))
-  x$reason <- NA_character_
+  x$reason <- ""
   x$all_nonsusceptible_columns <- ""
 
   if (guideline$code == "cmi2012") {
@@ -1498,7 +1473,7 @@ mdro <- function(x = NULL,
     }
     trans_tbl(
       3, # positive
-      rows = which(x$order == "Enterobacterales" & esbl == TRUE),
+      rows = which(x$order == "Enterobacterales" & x$esbl == TRUE),
       cols = "any",
       any_all = "any",
       reason = "Enterobacterales: ESBL"
@@ -1519,7 +1494,7 @@ mdro <- function(x = NULL,
     )
     trans_tbl(
       3,
-      rows = which(x$order == "Enterobacterales" & carbapenemase == TRUE),
+      rows = which(x$order == "Enterobacterales" & x$carbapenemase == TRUE),
       cols = "any",
       any_all = "any",
       reason = "Enterobacterales: carbapenemase"
@@ -1557,14 +1532,14 @@ mdro <- function(x = NULL,
     )
     trans_tbl(
       2, # unconfirmed
-      rows = which(x[[col_mo]] %in% AMR::microorganisms.groups$mo[AMR::microorganisms.groups$mo_group_name == "Acinetobacter baumannii complex"] & is.na(carbapenemase)),
+      rows = which(x[[col_mo]] %in% AMR::microorganisms.groups$mo[AMR::microorganisms.groups$mo_group_name == "Acinetobacter baumannii complex"] & is.na(x$carbapenemase)),
       cols = carbapenems,
       any_all = "any",
       reason = "A. baumannii-calcoaceticus complex: potential carbapenemase"
     )
     trans_tbl(
       3,
-      rows = which(x[[col_mo]] %in% AMR::microorganisms.groups$mo[AMR::microorganisms.groups$mo_group_name == "Acinetobacter baumannii complex"] & carbapenemase == TRUE),
+      rows = which(x[[col_mo]] %in% AMR::microorganisms.groups$mo[AMR::microorganisms.groups$mo_group_name == "Acinetobacter baumannii complex"] & x$carbapenemase == TRUE),
       cols = carbapenems,
       any_all = "any",
       reason = "A. baumannii-calcoaceticus complex: carbapenemase"
@@ -1574,6 +1549,7 @@ mdro <- function(x = NULL,
     x$psae <- 0
     x$psae <- x$psae + ifelse(NA_as_FALSE(col_values(x, TOB) == "R") | NA_as_FALSE(col_values(x, AMK) == "R"), 1, 0)
     x$psae <- x$psae + ifelse(NA_as_FALSE(col_values(x, IPM) == "R") | NA_as_FALSE(col_values(x, MEM) == "R"), 1, 0)
+    x$psae <- x$psae + ifelse(NA_as_FALSE(x$carbapenemase), 1, 0)
     x$psae <- x$psae + ifelse(NA_as_FALSE(col_values(x, PIP) == "R") | NA_as_FALSE(col_values(x, TZP) == "R"), 1, 0)
     x$psae <- x$psae + ifelse(NA_as_FALSE(col_values(x, CAZ) == "R") | NA_as_FALSE(col_values(x, CZA) == "R"), 1, 0)
     x$psae <- x$psae + ifelse(NA_as_FALSE(col_values(x, CIP) == "R") | NA_as_FALSE(col_values(x, NOR) == "R") | NA_as_FALSE(col_values(x, LVX) == "R"), 1, 0)
@@ -1602,7 +1578,7 @@ mdro <- function(x = NULL,
     )
     trans_tbl(
       3,
-      rows = which(x$genus == "Enterococcus" & x$species == "faecium" & (vanA == TRUE | vanB == TRUE)),
+      rows = which(x$genus == "Enterococcus" & x$species == "faecium" & (x$vanA == TRUE | x$vanB == TRUE)),
       cols = c(PEN, AMX, AMP, VAN),
       any_all = "any",
       reason = "E. faecium: vanA/vanB gene + penicillin group"
@@ -1611,14 +1587,14 @@ mdro <- function(x = NULL,
     # Staphylococcus aureus complex (= aureus, argenteus or schweitzeri)
     trans_tbl(
       2,
-      rows = which(x$genus == "Staphylococcus" & x$species %in% c("aureus", "argenteus", "schweitzeri") & (is.na(mecA) | is.na(mecC))),
+      rows = which(x$genus == "Staphylococcus" & x$species %in% c("aureus", "argenteus", "schweitzeri") & (is.na(x$mecA) | is.na(x$mecC))),
       cols = c(AMC, TZP, FLC, OXA, FOX, FOX1),
       any_all = "any",
       reason = "S. aureus complex: potential MRSA"
     )
     trans_tbl(
       3,
-      rows = which(x$genus == "Staphylococcus" & x$species %in% c("aureus", "argenteus", "schweitzeri") & (mecA == TRUE | mecC == TRUE)),
+      rows = which(x$genus == "Staphylococcus" & x$species %in% c("aureus", "argenteus", "schweitzeri") & (x$mecA == TRUE | x$mecC == TRUE)),
       cols = "any",
       any_all = "any",
       reason = "S. aureus complex: mecA/mecC gene"
@@ -1899,6 +1875,10 @@ mdro <- function(x = NULL,
     # fill in empty reasons
     x$reason[is.na(x$reason)] <- "not covered by guideline"
     x[rows_empty, "reason"] <- paste(x[rows_empty, "reason"], "(note: no available test results)")
+    # starting semicolons must be removed
+    x$reason <- trimws(gsub("^;", "", x$reason))
+    # if criteria were not met initially, but later they were, then they have a following semicolon; remove the initial lack of meeting criteria
+    x$reason <- trimws(gsub("guideline criteria not met;", "", x$reason, fixed = TRUE))
     # format data set
     colnames(x)[colnames(x) == col_mo] <- "microorganism"
     x$microorganism <- mo_name(x$microorganism, language = NULL)

R/mean_amr_distance.R

@@ -31,7 +31,7 @@
 #'
 #' Calculates a normalised mean for antimicrobial resistance between multiple observations, to help to identify similar isolates without comparing antibiograms by hand.
 #' @param x A vector of class [sir][as.sir()], [mic][as.mic()] or [disk][as.disk()], or a [data.frame] containing columns of any of these classes.
-#' @param ... Variables to select. Supports [tidyselect language][tidyselect::language] (such as `column1:column4` and `where(is.mic)`), and can thus also be [antimicrobial selectors][amr_selector()].
+#' @param ... Variables to select. 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()].
 #' @param combine_SI A [logical] to indicate whether all values of S, SDD, and I must be merged into one, so the input only consists of S+I vs. R (susceptible vs. resistant) - the default is `TRUE`.
 #' @details The mean AMR distance is effectively [the Z-score](https://en.wikipedia.org/wiki/Standard_score); a normalised numeric value to compare AMR test results which can help to identify similar isolates, without comparing antibiograms by hand.
 #'

R/mo.R

@@ -1186,7 +1186,7 @@ parse_and_convert <- function(x) {
         parsed <- gsub('"', "", parsed, fixed = TRUE)
         parsed
       },
-      error = function(e) stop(e$message, call. = FALSE)
+      error = function(e) stop(conditionMessage(e), call. = FALSE)
     ) # this will also be thrown when running `as.mo(no_existing_object)`
   }
   out <- trimws2(out)

R/mo_property.R

@@ -974,7 +974,7 @@ mo_validate <- function(x, property, language, keep_synonyms = keep_synonyms, ..
   # try to catch an error when inputting an invalid argument
   # so the 'call.' can be set to FALSE
   tryCatch(x[1L] %in% unlist(AMR_env$MO_lookup[1, property, drop = TRUE]),
-    error = function(e) stop(e$message, call. = FALSE)
+    error = function(e) stop(conditionMessage(e), call. = FALSE)
   )
 
   dots <- list(...)

R/pca.R

@@ -99,7 +99,7 @@ pca <- function(x,
     new_list <- list(0)
     for (i in seq_len(length(dots) - 1)) {
       new_list[[i]] <- tryCatch(eval(dots[[i + 1]], envir = x),
-        error = function(e) stop(e$message, call. = FALSE)
+        error = function(e) stop(conditionMessage(e), call. = FALSE)
       )
       if (length(new_list[[i]]) == 1) {
         if (is.character(new_list[[i]]) && new_list[[i]] %in% colnames(x)) {

R/plotting.R

@@ -90,6 +90,10 @@
 #'   autoplot(some_mic_values, mo = "Escherichia coli", ab = "cipro")
 #' }
 #' if (require("ggplot2")) {
+#'   autoplot(some_mic_values, mo = "Staph aureus", ab = "Ceftaroline", guideline = "CLSI")
+#' }
+#'
+#' if (require("ggplot2")) {
 #'   # support for 27 languages, various guidelines, and many options
 #'   autoplot(some_disk_values,
 #'     mo = "Escherichia coli", ab = "cipro",
@@ -146,7 +150,7 @@
 #'     aes(group, mic)
 #'   ) +
 #'     geom_boxplot() +
-#'     geom_violin(linetype = 2, colour = "grey", fill = NA) +
+#'     geom_violin(linetype = 2, colour = "grey30", fill = NA) +
 #'     scale_y_mic()
 #' }
 #' if (require("ggplot2")) {
@@ -158,7 +162,7 @@
 #'     aes(group, mic)
 #'   ) +
 #'     geom_boxplot() +
-#'     geom_violin(linetype = 2, colour = "grey", fill = NA) +
+#'     geom_violin(linetype = 2, colour = "grey30", fill = NA) +
 #'     scale_y_mic(mic_range = c(NA, 0.25))
 #' }
 #'
@@ -191,7 +195,7 @@
 #'     aes(x = group, y = mic, colour = sir)
 #'   ) +
 #'     theme_minimal() +
-#'     geom_boxplot(fill = NA, colour = "grey") +
+#'     geom_boxplot(fill = NA, colour = "grey30") +
 #'     geom_jitter(width = 0.25)
 #'
 #'   plain
@@ -377,6 +381,8 @@ create_scale_sir <- function(aesthetics, colours_SIR, language, eucast_I, ...) {
   args <- list(...)
   args[c("value", "labels", "limits")] <- NULL
 
+  colours_SIR <- expand_SIR_colours(colours_SIR, unname = FALSE)
+
   if (identical(aesthetics, "x")) {
     ggplot_fn <- ggplot2::scale_x_discrete
   } else {
@@ -385,24 +391,19 @@ create_scale_sir <- function(aesthetics, colours_SIR, language, eucast_I, ...) {
       args,
       list(
         aesthetics = aesthetics,
-        values = c(
-          S = colours_SIR[1],
-          SDD = colours_SIR[2],
-          I = colours_SIR[2],
-          R = colours_SIR[3],
-          NI = "grey30"
-        )
+        values = c(colours_SIR, NI = "grey30")
       )
     )
   }
   scale <- do.call(ggplot_fn, args)
 
   scale$labels <- function(x) {
-    stop_ifnot(all(x %in% c(levels(NA_sir_), NA)),
+    stop_ifnot(all(x %in% c(levels(NA_sir_), "SI", "IR", NA)),
       "Apply `scale_", aesthetics[1], "_sir()` to a variable of class 'sir', see `?as.sir`.",
       call = FALSE
     )
-    x <- as.character(as.sir(x))
+    x <- as.character(x)
+    x[!x %in% c("SI", "IR")] <- as.character(as.sir(x[!x %in% c("SI", "IR")]))
     if (!is.null(language)) {
       x[x == "S"] <- "(S) Susceptible"
       x[x == "SDD"] <- "(SDD) Susceptible dose-dependent"
@@ -412,6 +413,8 @@ create_scale_sir <- function(aesthetics, colours_SIR, language, eucast_I, ...) {
         x[x == "I"] <- "(I) Intermediate"
       }
       x[x == "R"] <- "(R) Resistant"
+      x[x == "SI"] <- "(S/I) Susceptible"
+      x[x == "IR"] <- "(I/R) Non-susceptible"
       x[x == "NI"] <- "(NI) Non-interpretable"
       x <- translate_AMR(x, language = language)
     }
@@ -419,7 +422,7 @@ create_scale_sir <- function(aesthetics, colours_SIR, language, eucast_I, ...) {
   }
   scale$limits <- function(x, ...) {
     # force SIR in the right order
-    as.character(sort(factor(x, levels = levels(NA_sir_))))
+    as.character(sort(factor(x, levels = c(levels(NA_sir_), "SI", "IR"))))
   }
 
   scale
@@ -427,11 +430,16 @@ create_scale_sir <- function(aesthetics, colours_SIR, language, eucast_I, ...) {
 
 #' @rdname plot
 #' @export
-scale_x_sir <- function(colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
+scale_x_sir <- function(colours_SIR = c(
+                          S = "#3CAEA3",
+                          SDD = "#8FD6C4",
+                          I = "#F6D55C",
+                          R = "#ED553B"
+                        ),
                         language = get_AMR_locale(),
                         eucast_I = getOption("AMR_guideline", "EUCAST") == "EUCAST",
                         ...) {
-  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
+  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3, 4))
   language <- validate_language(language)
   meet_criteria(eucast_I, allow_class = "logical", has_length = 1)
   create_scale_sir(aesthetics = "x", colours_SIR = colours_SIR, language = language, eucast_I = eucast_I)
@@ -439,11 +447,16 @@ scale_x_sir <- function(colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
 
 #' @rdname plot
 #' @export
-scale_colour_sir <- function(colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
+scale_colour_sir <- function(colours_SIR = c(
+                               S = "#3CAEA3",
+                               SDD = "#8FD6C4",
+                               I = "#F6D55C",
+                               R = "#ED553B"
+                             ),
                              language = get_AMR_locale(),
                              eucast_I = getOption("AMR_guideline", "EUCAST") == "EUCAST",
                              ...) {
-  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
+  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3, 4))
   language <- validate_language(language)
   meet_criteria(eucast_I, allow_class = "logical", has_length = 1)
   args <- list(...)
@@ -463,11 +476,16 @@ scale_color_sir <- scale_colour_sir
 
 #' @rdname plot
 #' @export
-scale_fill_sir <- function(colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
+scale_fill_sir <- function(colours_SIR = c(
+                             S = "#3CAEA3",
+                             SDD = "#8FD6C4",
+                             I = "#F6D55C",
+                             R = "#ED553B"
+                           ),
                            language = get_AMR_locale(),
                            eucast_I = getOption("AMR_guideline", "EUCAST") == "EUCAST",
                            ...) {
-  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
+  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3, 4))
   language <- validate_language(language)
   meet_criteria(eucast_I, allow_class = "logical", has_length = 1)
   args <- list(...)
@@ -491,7 +509,12 @@ plot.mic <- function(x,
                      main = deparse(substitute(x)),
                      ylab = translate_AMR("Frequency", language = language),
                      xlab = translate_AMR("Minimum Inhibitory Concentration (mg/L)", language = language),
-                     colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
+                     colours_SIR = c(
+                       S = "#3CAEA3",
+                       SDD = "#8FD6C4",
+                       I = "#F6D55C",
+                       R = "#ED553B"
+                     ),
                      language = get_AMR_locale(),
                      expand = TRUE,
                      include_PKPD = getOption("AMR_include_PKPD", TRUE),
@@ -503,16 +526,13 @@ plot.mic <- function(x,
   meet_criteria(main, allow_class = "character", has_length = 1, allow_NULL = TRUE)
   meet_criteria(ylab, allow_class = "character", has_length = 1)
   meet_criteria(xlab, allow_class = "character", has_length = 1)
-  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
+  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3, 4))
   language <- validate_language(language)
   meet_criteria(expand, allow_class = "logical", has_length = 1)
 
   x <- as.mic(x) # make sure that currently implemented MIC levels are used
-
-  if (length(colours_SIR) == 1) {
-    colours_SIR <- rep(colours_SIR, 3)
-  }
   main <- gsub(" +", " ", paste0(main, collapse = " "))
+  colours_SIR <- expand_SIR_colours(colours_SIR)
 
   x <- plotrange_as_table(x, expand = expand)
   cols_sub <- plot_colours_subtitle_guideline(
@@ -549,13 +569,17 @@ plot.mic <- function(x,
       legend_col <- colours_SIR[1]
     }
     if (any(cols_sub$cols == colours_SIR[2] & cols_sub$count > 0)) {
-      legend_txt <- c(legend_txt, paste("(I)", plot_name_of_I(cols_sub$guideline)))
+      legend_txt <- c(legend_txt, "(SDD) Susceptible dose-dependent")
       legend_col <- c(legend_col, colours_SIR[2])
     }
     if (any(cols_sub$cols == colours_SIR[3] & cols_sub$count > 0)) {
-      legend_txt <- c(legend_txt, "(R) Resistant")
+      legend_txt <- c(legend_txt, paste("(I)", plot_name_of_I(cols_sub$guideline)))
       legend_col <- c(legend_col, colours_SIR[3])
     }
+    if (any(cols_sub$cols == colours_SIR[4] & cols_sub$count > 0)) {
+      legend_txt <- c(legend_txt, "(R) Resistant")
+      legend_col <- c(legend_col, colours_SIR[4])
+    }
 
     legend("top",
       x.intersp = 0.5,
@@ -580,7 +604,12 @@ barplot.mic <- function(height,
                         main = deparse(substitute(height)),
                         ylab = translate_AMR("Frequency", language = language),
                         xlab = translate_AMR("Minimum Inhibitory Concentration (mg/L)", language = language),
-                        colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
+                        colours_SIR = c(
+                          S = "#3CAEA3",
+                          SDD = "#8FD6C4",
+                          I = "#F6D55C",
+                          R = "#ED553B"
+                        ),
                         language = get_AMR_locale(),
                         expand = TRUE,
                         ...) {
@@ -590,7 +619,7 @@ barplot.mic <- function(height,
   meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE)
   meet_criteria(ab, allow_class = c("ab", "character"), allow_NULL = TRUE)
   meet_criteria(guideline, allow_class = "character", has_length = 1)
-  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
+  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3, 4))
   language <- validate_language(language)
   meet_criteria(expand, allow_class = "logical", has_length = 1)
 
@@ -622,7 +651,12 @@ autoplot.mic <- function(object,
                          title = deparse(substitute(object)),
                          ylab = translate_AMR("Frequency", language = language),
                          xlab = translate_AMR("Minimum Inhibitory Concentration (mg/L)", language = language),
-                         colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
+                         colours_SIR = c(
+                           S = "#3CAEA3",
+                           SDD = "#8FD6C4",
+                           I = "#F6D55C",
+                           R = "#ED553B"
+                         ),
                          language = get_AMR_locale(),
                          expand = TRUE,
                          include_PKPD = getOption("AMR_include_PKPD", TRUE),
@@ -635,7 +669,7 @@ autoplot.mic <- function(object,
   meet_criteria(title, allow_class = "character", allow_NULL = TRUE)
   meet_criteria(ylab, allow_class = "character", has_length = 1)
   meet_criteria(xlab, allow_class = "character", has_length = 1)
-  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
+  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3, 4))
   language <- validate_language(language)
   meet_criteria(expand, allow_class = "logical", has_length = 1)
 
@@ -646,6 +680,8 @@ autoplot.mic <- function(object,
     title <- gsub(" +", " ", paste0(title, collapse = " "))
   }
 
+  colours_SIR <- expand_SIR_colours(colours_SIR)
+
   object <- as.mic(object) # make sure that currently implemented MIC levels are used
   x <- plotrange_as_table(object, expand = expand)
   cols_sub <- plot_colours_subtitle_guideline(
@@ -665,12 +701,14 @@ autoplot.mic <- function(object,
   colnames(df) <- c("mic", "count")
   df$cols <- cols_sub$cols
   df$cols[df$cols == colours_SIR[1]] <- "(S) Susceptible"
-  df$cols[df$cols == colours_SIR[2]] <- paste("(I)", plot_name_of_I(cols_sub$guideline))
-  df$cols[df$cols == colours_SIR[3]] <- "(R) Resistant"
+  df$cols[df$cols == colours_SIR[2]] <- "(SDD) Susceptible dose-dependent"
+  df$cols[df$cols == colours_SIR[3]] <- paste("(I)", plot_name_of_I(cols_sub$guideline))
+  df$cols[df$cols == colours_SIR[4]] <- "(R) Resistant"
   df$cols <- factor(translate_into_language(df$cols, language = language),
     levels = translate_into_language(
       c(
         "(S) Susceptible",
+        "(SDD) Susceptible dose-dependent",
         paste("(I)", plot_name_of_I(cols_sub$guideline)),
         "(R) Resistant"
       ),
@@ -684,10 +722,10 @@ autoplot.mic <- function(object,
     vals <- c(
       "(S) Susceptible" = colours_SIR[1],
       "(SDD) Susceptible dose-dependent" = colours_SIR[2],
-      "(I) Susceptible, incr. exp." = colours_SIR[2],
-      "(I) Intermediate" = colours_SIR[2],
-      "(R) Resistant" = colours_SIR[3],
-      "(NI) Non-interpretable" = "grey"
+      "(I) Susceptible, incr. exp." = colours_SIR[3],
+      "(I) Intermediate" = colours_SIR[3],
+      "(R) Resistant" = colours_SIR[4],
+      "(NI) Non-interpretable" = "grey30"
     )
     names(vals) <- translate_into_language(names(vals), language = language)
     p <- p +
@@ -731,7 +769,12 @@ plot.disk <- function(x,
                       mo = NULL,
                       ab = NULL,
                       guideline = getOption("AMR_guideline", "EUCAST"),
-                      colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
+                      colours_SIR = c(
+                        S = "#3CAEA3",
+                        SDD = "#8FD6C4",
+                        I = "#F6D55C",
+                        R = "#ED553B"
+                      ),
                       language = get_AMR_locale(),
                       expand = TRUE,
                       include_PKPD = getOption("AMR_include_PKPD", TRUE),
@@ -743,14 +786,12 @@ plot.disk <- function(x,
   meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE)
   meet_criteria(ab, allow_class = c("ab", "character"), allow_NULL = TRUE)
   meet_criteria(guideline, allow_class = "character", has_length = 1)
-  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
+  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3, 4))
   language <- validate_language(language)
   meet_criteria(expand, allow_class = "logical", has_length = 1)
 
-  if (length(colours_SIR) == 1) {
-    colours_SIR <- rep(colours_SIR, 3)
-  }
   main <- gsub(" +", " ", paste0(main, collapse = " "))
+  colours_SIR <- expand_SIR_colours(colours_SIR)
 
   x <- plotrange_as_table(x, expand = expand)
   cols_sub <- plot_colours_subtitle_guideline(
@@ -783,12 +824,16 @@ plot.disk <- function(x,
   if (any(colours_SIR %in% cols_sub$cols)) {
     legend_txt <- character(0)
     legend_col <- character(0)
-    if (any(cols_sub$cols == colours_SIR[3] & cols_sub$count > 0)) {
+    if (any(cols_sub$cols == colours_SIR[4] & cols_sub$count > 0)) {
       legend_txt <- "(R) Resistant"
-      legend_col <- colours_SIR[3]
+      legend_col <- colours_SIR[4]
+    }
+    if (any(cols_sub$cols == colours_SIR[3] & cols_sub$count > 0)) {
+      legend_txt <- c(legend_txt, paste("(I)", plot_name_of_I(cols_sub$guideline)))
+      legend_col <- c(legend_col, colours_SIR[3])
     }
     if (any(cols_sub$cols == colours_SIR[2] & cols_sub$count > 0)) {
-      legend_txt <- c(legend_txt, paste("(I)", plot_name_of_I(cols_sub$guideline)))
+      legend_txt <- c(legend_txt, "(SDD) Susceptible dose-dependent")
       legend_col <- c(legend_col, colours_SIR[2])
     }
     if (any(cols_sub$cols == colours_SIR[1] & cols_sub$count > 0)) {
@@ -818,7 +863,12 @@ barplot.disk <- function(height,
                          mo = NULL,
                          ab = NULL,
                          guideline = getOption("AMR_guideline", "EUCAST"),
-                         colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
+                         colours_SIR = c(
+                           S = "#3CAEA3",
+                           SDD = "#8FD6C4",
+                           I = "#F6D55C",
+                           R = "#ED553B"
+                         ),
                          language = get_AMR_locale(),
                          expand = TRUE,
                          ...) {
@@ -828,7 +878,7 @@ barplot.disk <- function(height,
   meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE)
   meet_criteria(ab, allow_class = c("ab", "character"), allow_NULL = TRUE)
   meet_criteria(guideline, allow_class = "character", has_length = 1)
-  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
+  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3, 4))
   language <- validate_language(language)
   meet_criteria(expand, allow_class = "logical", has_length = 1)
 
@@ -858,7 +908,12 @@ autoplot.disk <- function(object,
                           ylab = translate_AMR("Frequency", language = language),
                           xlab = translate_AMR("Disk diffusion diameter (mm)", language = language),
                           guideline = getOption("AMR_guideline", "EUCAST"),
-                          colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
+                          colours_SIR = c(
+                            S = "#3CAEA3",
+                            SDD = "#8FD6C4",
+                            I = "#F6D55C",
+                            R = "#ED553B"
+                          ),
                           language = get_AMR_locale(),
                           expand = TRUE,
                           include_PKPD = getOption("AMR_include_PKPD", TRUE),
@@ -871,7 +926,7 @@ autoplot.disk <- function(object,
   meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE)
   meet_criteria(ab, allow_class = c("ab", "character"), allow_NULL = TRUE)
   meet_criteria(guideline, allow_class = "character", has_length = 1)
-  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
+  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3, 4))
   language <- validate_language(language)
   meet_criteria(expand, allow_class = "logical", has_length = 1)
 
@@ -882,6 +937,8 @@ autoplot.disk <- function(object,
     title <- gsub(" +", " ", paste0(title, collapse = " "))
   }
 
+  colours_SIR <- expand_SIR_colours(colours_SIR)
+
   x <- plotrange_as_table(object, expand = expand)
   cols_sub <- plot_colours_subtitle_guideline(
     x = x,
@@ -899,10 +956,10 @@ autoplot.disk <- function(object,
   df <- as.data.frame(x, stringsAsFactors = TRUE)
   colnames(df) <- c("disk", "count")
   df$cols <- cols_sub$cols
-
   df$cols[df$cols == colours_SIR[1]] <- "(S) Susceptible"
-  df$cols[df$cols == colours_SIR[2]] <- paste("(I)", plot_name_of_I(cols_sub$guideline))
-  df$cols[df$cols == colours_SIR[3]] <- "(R) Resistant"
+  df$cols[df$cols == colours_SIR[2]] <- "(SDD) Susceptible dose-dependent"
+  df$cols[df$cols == colours_SIR[3]] <- paste("(I)", plot_name_of_I(cols_sub$guideline))
+  df$cols[df$cols == colours_SIR[4]] <- "(R) Resistant"
   df$cols <- factor(translate_into_language(df$cols, language = language),
     levels = translate_into_language(
       c(
@@ -920,10 +977,10 @@ autoplot.disk <- function(object,
     vals <- c(
       "(S) Susceptible" = colours_SIR[1],
       "(SDD) Susceptible dose-dependent" = colours_SIR[2],
-      "(I) Susceptible, incr. exp." = colours_SIR[2],
-      "(I) Intermediate" = colours_SIR[2],
-      "(R) Resistant" = colours_SIR[3],
-      "(NI) Non-interpretable" = "grey"
+      "(I) Susceptible, incr. exp." = colours_SIR[3],
+      "(I) Intermediate" = colours_SIR[3],
+      "(R) Resistant" = colours_SIR[4],
+      "(NI) Non-interpretable" = "grey30"
     )
     names(vals) <- translate_into_language(names(vals), language = language)
     p <- p +
@@ -1024,22 +1081,26 @@ barplot.sir <- function(height,
                         main = deparse(substitute(height)),
                         xlab = translate_AMR("Antimicrobial Interpretation", language = language),
                         ylab = translate_AMR("Frequency", language = language),
-                        colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
+                        colours_SIR = c(
+                          S = "#3CAEA3",
+                          SDD = "#8FD6C4",
+                          I = "#F6D55C",
+                          R = "#ED553B"
+                        ),
                         language = get_AMR_locale(),
                         expand = TRUE,
                         ...) {
   meet_criteria(xlab, allow_class = "character", has_length = 1)
   meet_criteria(main, allow_class = "character", has_length = 1, allow_NULL = TRUE)
   meet_criteria(ylab, allow_class = "character", has_length = 1)
-  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
+  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3, 4))
   language <- validate_language(language)
   meet_criteria(expand, allow_class = "logical", has_length = 1)
 
-  if (length(colours_SIR) == 1) {
-    colours_SIR <- rep(colours_SIR, 3)
-  }
+  colours_SIR <- expand_SIR_colours(colours_SIR)
+
   # add SDD and N to colours
-  colours_SIR <- c(colours_SIR[1:2], colours_SIR[2], colours_SIR[3], "#888888")
+  colours_SIR <- c(colours_SIR, "grey30")
   main <- gsub(" +", " ", paste0(main, collapse = " "))
 
   x <- table(height)
@@ -1065,14 +1126,19 @@ autoplot.sir <- function(object,
                          title = deparse(substitute(object)),
                          xlab = translate_AMR("Antimicrobial Interpretation", language = language),
                          ylab = translate_AMR("Frequency", language = language),
-                         colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
+                         colours_SIR = c(
+                           S = "#3CAEA3",
+                           SDD = "#8FD6C4",
+                           I = "#F6D55C",
+                           R = "#ED553B"
+                         ),
                          language = get_AMR_locale(),
                          ...) {
   stop_ifnot_installed("ggplot2")
   meet_criteria(title, allow_class = "character", allow_NULL = TRUE)
   meet_criteria(ylab, allow_class = "character", has_length = 1)
   meet_criteria(xlab, allow_class = "character", has_length = 1)
-  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
+  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3, 4))
 
   if ("main" %in% names(list(...))) {
     title <- list(...)$main
@@ -1081,9 +1147,7 @@ autoplot.sir <- function(object,
     title <- gsub(" +", " ", paste0(title, collapse = " "))
   }
 
-  if (length(colours_SIR) == 1) {
-    colours_SIR <- rep(colours_SIR, 3)
-  }
+  colours_SIR <- expand_SIR_colours(colours_SIR)
 
   df <- as.data.frame(table(object), stringsAsFactors = TRUE)
   colnames(df) <- c("x", "n")
@@ -1095,9 +1159,9 @@ autoplot.sir <- function(object,
       values = c(
         "S" = colours_SIR[1],
         "SDD" = colours_SIR[2],
-        "I" = colours_SIR[2],
-        "R" = colours_SIR[3],
-        "NI" = "#888888"
+        "I" = colours_SIR[3],
+        "R" = colours_SIR[4],
+        "NI" = "grey30"
       ),
       limits = force
     ) +
@@ -1223,9 +1287,9 @@ plot_colours_subtitle_guideline <- function(x, mo, ab, guideline, colours_SIR, f
     cols[is.na(sir)] <- "#BEBEBE"
     cols[sir == "S"] <- colours_SIR[1]
     cols[sir == "SDD"] <- colours_SIR[2]
-    cols[sir == "I"] <- colours_SIR[2]
-    cols[sir == "R"] <- colours_SIR[3]
-    cols[sir == "NI"] <- "#888888"
+    cols[sir == "I"] <- colours_SIR[3]
+    cols[sir == "R"] <- colours_SIR[4]
+    cols[sir == "NI"] <- "grey30"
     sub <- bquote(.(abname) ~ "-" ~ italic(.(moname)) ~ .(guideline_txt))
   } else {
     cols <- "#BEBEBE"
@@ -1284,10 +1348,15 @@ scale_y_percent <- function(breaks = function(x) seq(0, max(x, na.rm = TRUE), 0.
 #' @export
 scale_sir_colours <- function(...,
                               aesthetics,
-                              colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B")) {
+                              colours_SIR = c(
+                                S = "#3CAEA3",
+                                SDD = "#8FD6C4",
+                                I = "#F6D55C",
+                                R = "#ED553B"
+                              )) {
   stop_ifnot_installed("ggplot2")
   meet_criteria(aesthetics, allow_class = "character", is_in = c("alpha", "colour", "color", "fill", "linetype", "shape", "size"))
-  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
+  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3, 4))
 
   if ("fill" %in% aesthetics && message_not_thrown_before("scale_sir_colours", "fill", entire_session = TRUE)) {
     warning_("Using `scale_sir_colours()` for the `fill` aesthetic has been superseded by `scale_fill_sir()`, please use that instead. This warning will be shown once per session.")
@@ -1296,67 +1365,48 @@ scale_sir_colours <- function(...,
     warning_("Using `scale_sir_colours()` for the `colour` aesthetic has been superseded by `scale_colour_sir()`, please use that instead. This warning will be shown once per session.")
   }
 
-  if (length(colours_SIR) == 1) {
-    colours_SIR <- rep(colours_SIR, 3)
-  }
-  # behaviour until AMR pkg v1.5.0 and also when coming from ggplot_sir()
   if ("colours" %in% names(list(...))) {
-    original_cols <- c(
-      S = colours_SIR[1],
-      SI = colours_SIR[1],
-      I = colours_SIR[2],
-      IR = colours_SIR[3],
-      R = colours_SIR[3]
-    )
-    colours <- replace(original_cols, names(list(...)$colours), list(...)$colours)
+    colours_SIR <- list(...)$colours
+  }
+
+  colours_SIR <- expand_SIR_colours(colours_SIR, unname = FALSE)
+
+  # behaviour when coming from ggplot_sir()
+  if ("colours" %in% names(list(...))) {
     # limits = force is needed in ggplot2 3.3.4 and 3.3.5, see here;
     # https://github.com/tidyverse/ggplot2/issues/4511#issuecomment-866185530
-    return(ggplot2::scale_fill_manual(values = colours, limits = force, aesthetics = aesthetics))
+    return(ggplot2::scale_fill_manual(values = colours_SIR, limits = force, aesthetics = aesthetics))
   }
   if (identical(unlist(list(...)), FALSE)) {
     return(invisible())
   }
 
-  names_susceptible <- c(
-    "S", "SI", "IS", "S+I", "I+S", "susceptible", "Susceptible",
-    unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Susceptible"),
-      "replacement",
-      drop = TRUE
-    ])
-  )
+  colours_SIR <- unname(colours_SIR)
+
+  names_susceptible <- c("S", "SI", "IS", "S+I", "I+S", "susceptible", "Susceptible")
+  names_susceptible_dose_dep <- c("SDD", "susceptible dose-dependent", "Susceptible dose-dependent")
   names_incr_exposure <- c(
     "I", "intermediate", "increased exposure", "incr. exposure",
-    "Increased exposure", "Incr. exposure", "Susceptible, incr. exp.",
-    unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Intermediate"),
-      "replacement",
-      drop = TRUE
-    ]),
-    unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Susceptible, incr. exp."),
-      "replacement",
-      drop = TRUE
-    ])
-  )
-  names_resistant <- c(
-    "R", "IR", "RI", "R+I", "I+R", "resistant", "Resistant",
-    unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Resistant"),
-      "replacement",
-      drop = TRUE
-    ])
+    "Increased exposure", "Incr. exposure", "Susceptible, incr. exp."
   )
+  names_resistant <- c("R", "IR", "RI", "R+I", "I+R", "resistant", "Resistant")
 
   susceptible <- rep(colours_SIR[1], length(names_susceptible))
   names(susceptible) <- names_susceptible
-  incr_exposure <- rep(colours_SIR[2], length(names_incr_exposure))
+  susceptible_dose_dep <- rep(colours_SIR[2], length(names_susceptible_dose_dep))
+  names(susceptible_dose_dep) <- names_susceptible_dose_dep
+  incr_exposure <- rep(colours_SIR[3], length(names_incr_exposure))
   names(incr_exposure) <- names_incr_exposure
-  resistant <- rep(colours_SIR[3], length(names_resistant))
+  resistant <- rep(colours_SIR[4], length(names_resistant))
   names(resistant) <- names_resistant
 
-  original_cols <- c(susceptible, incr_exposure, resistant)
+  original_cols <- c(susceptible, susceptible_dose_dep, incr_exposure, resistant)
   dots <- c(...)
-  # replace S, I, R as colours: scale_sir_colours(mydatavalue = "S")
+  # replace S, SDD, I, R as colours: scale_sir_colours(mydatavalue = "S")
   dots[dots == "S"] <- colours_SIR[1]
-  dots[dots == "I"] <- colours_SIR[2]
-  dots[dots == "R"] <- colours_SIR[3]
+  dots[dots == "SDD"] <- colours_SIR[2]
+  dots[dots == "I"] <- colours_SIR[3]
+  dots[dots == "R"] <- colours_SIR[4]
   cols <- replace(original_cols, names(dots), dots)
   # limits = force is needed in ggplot2 3.3.4 and 3.3.5, see here;
   # https://github.com/tidyverse/ggplot2/issues/4511#issuecomment-866185530
@@ -1435,3 +1485,39 @@ labels_sir_count <- function(position = NULL,
     }
   )
 }
+
+expand_SIR_colours <- function(colours_SIR, unname = TRUE) {
+  sir_order <- c("S", "SDD", "I", "R", "SI", "IR")
+
+  if (is.null(names(colours_SIR))) {
+    if (length(colours_SIR) == 1) {
+      colours_SIR <- rep(colours_SIR, 4)
+    } else if (length(colours_SIR) == 3) {
+      # old method for AMR < 3.0.1 which allowed for 3 colours
+      # fill in green for SDD as extra colour
+      colours_SIR <- c(colours_SIR[1], colours_SIR[1], colours_SIR[2], colours_SIR[3])
+    }
+    if (length(colours_SIR) == 4) {
+      # add colours for SI (same as S) and IR (same as R)
+      colours_SIR <- c(colours_SIR[1:4], colours_SIR[1], colours_SIR[4])
+    }
+    names(colours_SIR) <- sir_order
+  } else {
+    # named input: match and reorder
+    stop_ifnot(
+      all(names(colours_SIR) %in% sir_order),
+      "Unknown names in `colours_SIR`. Expected any of: ", vector_or(levels(NA_sir_), quotes = FALSE, sort = FALSE), "."
+    )
+    if (length(colours_SIR) == 4) {
+      # add colours for SI (same as S) and IR (same as R)
+      colours_SIR <- c(colours_SIR[1:4], SI = unname(colours_SIR[1]), IR = unname(colours_SIR[4]))
+    }
+    colours_SIR <- colours_SIR[sir_order]
+  }
+
+  if (unname) {
+    colours_SIR <- unname(colours_SIR)
+  }
+
+  return(colours_SIR)
+}

R/proportion.R

@@ -237,7 +237,7 @@ resistance <- function(...,
       only_all_tested = only_all_tested,
       only_count = FALSE
     ),
-    error = function(e) stop_(gsub("in sir_calc(): ", "", e$message, fixed = TRUE), call = -5)
+    error = function(e) stop_(gsub("in sir_calc(): ", "", conditionMessage(e), fixed = TRUE), call = -5)
   )
 }
 
@@ -255,7 +255,7 @@ susceptibility <- function(...,
       only_all_tested = only_all_tested,
       only_count = FALSE
     ),
-    error = function(e) stop_(gsub("in sir_calc(): ", "", e$message, fixed = TRUE), call = -5)
+    error = function(e) stop_(gsub("in sir_calc(): ", "", conditionMessage(e), fixed = TRUE), call = -5)
   )
 }
 
@@ -283,7 +283,7 @@ sir_confidence_interval <- function(...,
       only_all_tested = only_all_tested,
       only_count = TRUE
     ),
-    error = function(e) stop_(gsub("in sir_calc(): ", "", e$message, fixed = TRUE), call = -5)
+    error = function(e) stop_(gsub("in sir_calc(): ", "", conditionMessage(e), fixed = TRUE), call = -5)
   )
   n <- tryCatch(
     sir_calc(...,
@@ -291,7 +291,7 @@ sir_confidence_interval <- function(...,
       only_all_tested = only_all_tested,
       only_count = TRUE
     ),
-    error = function(e) stop_(gsub("in sir_calc(): ", "", e$message, fixed = TRUE), call = -5)
+    error = function(e) stop_(gsub("in sir_calc(): ", "", conditionMessage(e), fixed = TRUE), call = -5)
   )
 
   if (x == 0) {
@@ -347,7 +347,7 @@ proportion_R <- function(...,
       only_all_tested = only_all_tested,
       only_count = FALSE
     ),
-    error = function(e) stop_(gsub("in sir_calc(): ", "", e$message, fixed = TRUE), call = -5)
+    error = function(e) stop_(gsub("in sir_calc(): ", "", conditionMessage(e), fixed = TRUE), call = -5)
   )
 }
 
@@ -365,7 +365,7 @@ proportion_IR <- function(...,
       only_all_tested = only_all_tested,
       only_count = FALSE
     ),
-    error = function(e) stop_(gsub("in sir_calc(): ", "", e$message, fixed = TRUE), call = -5)
+    error = function(e) stop_(gsub("in sir_calc(): ", "", conditionMessage(e), fixed = TRUE), call = -5)
   )
 }
 
@@ -383,7 +383,7 @@ proportion_I <- function(...,
       only_all_tested = only_all_tested,
       only_count = FALSE
     ),
-    error = function(e) stop_(gsub("in sir_calc(): ", "", e$message, fixed = TRUE), call = -5)
+    error = function(e) stop_(gsub("in sir_calc(): ", "", conditionMessage(e), fixed = TRUE), call = -5)
   )
 }
 
@@ -401,7 +401,7 @@ proportion_SI <- function(...,
       only_all_tested = only_all_tested,
       only_count = FALSE
     ),
-    error = function(e) stop_(gsub("in sir_calc(): ", "", e$message, fixed = TRUE), call = -5)
+    error = function(e) stop_(gsub("in sir_calc(): ", "", conditionMessage(e), fixed = TRUE), call = -5)
   )
 }
 
@@ -419,7 +419,7 @@ proportion_S <- function(...,
       only_all_tested = only_all_tested,
       only_count = FALSE
     ),
-    error = function(e) stop_(gsub("in sir_calc(): ", "", e$message, fixed = TRUE), call = -5)
+    error = function(e) stop_(gsub("in sir_calc(): ", "", conditionMessage(e), fixed = TRUE), call = -5)
   )
 }
 
@@ -443,6 +443,6 @@ proportion_df <- function(data,
       combine_SI = combine_SI,
       confidence_level = confidence_level
     ),
-    error = function(e) stop_(gsub("in sir_calc_df(): ", "", e$message, fixed = TRUE), call = -5)
+    error = function(e) stop_(gsub("in sir_calc_df(): ", "", conditionMessage(e), fixed = TRUE), call = -5)
   )
 }

R/sir.R

@@ -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)
@@ -863,7 +868,7 @@ as.sir.data.frame <- function(x,
     cl <- tryCatch(parallel::makeCluster(n_cores, type = "PSOCK"),
       error = function(e) {
         if (isTRUE(info)) {
-          message_("Could not create parallel cluster, using single-core computation. Error message: ", e$message, add_fn = font_red)
+          message_("Could not create parallel cluster, using single-core computation. Error message: ", conditionMessage(e), add_fn = font_red)
         }
         return(NULL)
       }
@@ -1135,7 +1140,6 @@ as_sir_method <- function(method_short,
   current_sir_interpretation_history <- NROW(AMR_env$sir_interpretation_history)
 
   if (isTRUE(info) && message_not_thrown_before("as.sir", "sir_interpretation_history")) {
-    message()
     message_("Run `sir_interpretation_history()` afterwards to retrieve a logbook with all details of the breakpoint interpretations.\n\n", add_fn = font_green)
   }
 
@@ -1553,7 +1557,7 @@ as_sir_method <- function(method_short,
       ))
 
     if (breakpoint_type == "animal") {
-      # 2025-03-13 for now, only strictly follow guideline for current host, no extrapolation
+      # 2025-03-13/ for now, only strictly follow guideline for current host, no extrapolation
       breakpoints_current <- breakpoints_current[which(breakpoints_current$host == host_current), , drop = FALSE]
     }
 
@@ -1651,26 +1655,23 @@ as_sir_method <- function(method_short,
       next
     }
 
-    # sort on host and taxonomic rank
-    # (this will e.g. prefer 'species' breakpoints over 'order' breakpoints)
-    if (is.na(uti_current)) {
-      breakpoints_current <- breakpoints_current %pm>%
-        #  `uti` is a column in the data set
-        # this will put UTI = FALSE first, then UTI = NA, then UTI = TRUE
-        pm_mutate(uti_index = ifelse(!is.na(uti) & uti == FALSE, 1,
-          ifelse(is.na(uti), 2,
-            3
-          )
-        )) %pm>%
-        # be as specific as possible (i.e. prefer species over genus):
-        pm_arrange(rank_index, uti_index)
-    } else if (uti_current == TRUE) {
-      breakpoints_current <- breakpoints_current %pm>%
-        subset(uti == TRUE) %pm>%
-        # be as specific as possible (i.e. prefer species over genus):
-        pm_arrange(rank_index)
+    # if the user explicitly set uti, keep only those rows
+    if (!is.na(uti_current)) {
+      breakpoints_current <- breakpoints_current[breakpoints_current$uti == uti_current, , drop = FALSE]
     }
 
+    # build a helper factor so FALSE < NA < TRUE
+    uti_index <- factor(
+      ifelse(is.na(breakpoints_current$uti), "NA",
+        as.character(breakpoints_current$uti)
+      ),
+      levels = c("FALSE", "NA", "TRUE")
+    )
+
+    # sort on host and taxonomic rank first, then by UTI
+    # (this will e.g. prefer 'species' breakpoints over 'order' breakpoints)
+    breakpoints_current <- breakpoints_current[order(breakpoints_current$rank_index, uti_index), , drop = FALSE]
+
     # throw messages for different body sites
     site <- breakpoints_current[1L, "site", drop = FALSE] # this is the one we'll take
     if (is.na(site)) {
@@ -1682,7 +1683,7 @@ as_sir_method <- function(method_short,
       # only UTI breakpoints available
       notes_current <- paste0(
         notes_current, "\n",
-        paste0("Breakpoints for ", font_bold(ab_formatted), " in ", mo_formatted, " are only available for (uncomplicated) urinary tract infections (UTI); assuming `uti = TRUE`.")
+        paste0("Breakpoints for ", font_bold(ab_formatted), " in ", mo_formatted, " are only available for (uncomplicated) urinary tract infections (UTI) - assuming `uti = TRUE`.")
       )
     } else if (nrow(breakpoints_current) > 1 && length(unique(breakpoints_current$site)) > 1 && any(is.na(uti_current)) && all(c(TRUE, FALSE) %in% breakpoints_current$uti, na.rm = TRUE) && message_not_thrown_before("as.sir", "siteUTI", mo_current, ab_current)) {
       # both UTI and Non-UTI breakpoints available
@@ -1705,7 +1706,7 @@ as_sir_method <- function(method_short,
       new_sir <- rep(as.sir("R"), length(rows))
       notes_current <- paste0(
         notes_current, "\n",
-        paste0("Intrinsic resistance applied for ", ab_formatted, " in ", mo_formatted, "")
+        paste0("Intrinsic resistance applied for ", ab_formatted, " in ", mo_formatted, ".")
       )
     } else if (nrow(breakpoints_current) == 0) {
       # no rules available
@@ -1713,41 +1714,48 @@ as_sir_method <- function(method_short,
     } else {
       # then run the rules
       breakpoints_current <- breakpoints_current[1L, , drop = FALSE]
+      if (breakpoints_current$rank_index > 3) {
+        # we resort to a high-level taxonomic record since there are no breakpoint on genus (rank_index = 3) or lower, so note this
+        notes_current <- paste0(
+          "No genus- or species-level breakpoint available - applying higher taxonomic level instead.\n",
+          notes_current
+        )
+      }
 
       notes_current <- paste0(
         notes_current, "\n",
         ifelse(breakpoints_current$mo == "UNKNOWN" | breakpoints_current$ref_tbl %like% "PK.*PD",
-          "Some PK/PD breakpoints were applied - use `include_PKPD = FALSE` to prevent this",
+          "Some PK/PD breakpoints were applied - use `include_PKPD = FALSE` to prevent this.",
           ""
         ),
         "\n",
         ifelse(breakpoints_current$site %like% "screen" | breakpoints_current$ref_tbl %like% "screen",
-          "Some screening breakpoints were applied - use `include_screening = FALSE` to prevent this",
+          "Some screening breakpoints were applied - use `include_screening = FALSE` to prevent this.",
           ""
         ),
         "\n",
         ifelse(method == "mic" & capped_mic_handling %in% c("conservative", "inverse") & as.character(values_bak) %like% "^[<][0-9]",
-          paste0("MIC values with the operator '<' are all considered 'S' since capped_mic_handling = \"", capped_mic_handling, "\""),
+          paste0("MIC values with the operator '<' are all considered 'S' since capped_mic_handling = \"", capped_mic_handling, "\"."),
           ""
         ),
         "\n",
         ifelse(method == "mic" & capped_mic_handling %in% c("conservative", "inverse") & as.character(values_bak) %like% "^[>][0-9]",
-          paste0("MIC values with the operator '>' are all considered 'R' since capped_mic_handling = \"", capped_mic_handling, "\""),
+          paste0("MIC values with the operator '>' are all considered 'R' since capped_mic_handling = \"", capped_mic_handling, "\"."),
           ""
         ),
         "\n",
         ifelse(method == "mic" & capped_mic_handling %in% c("conservative", "standard") & as.character(values_bak) %like% "^[><]=[0-9]" & as.double(values) > breakpoints_current$breakpoint_S & as.double(values) < breakpoints_current$breakpoint_R,
-          paste0("MIC values within the breakpoint guideline range with the operator '<=' or '>=' are considered 'NI' (non-interpretable) since capped_mic_handling = \"", capped_mic_handling, "\""),
+          paste0("MIC values within the breakpoint guideline range with the operator '<=' or '>=' are considered 'NI' (non-interpretable) since capped_mic_handling = \"", capped_mic_handling, "\"."),
           ""
         ),
         "\n",
         ifelse(method == "mic" & capped_mic_handling %in% c("conservative", "standard") & as.character(values_bak) %like% "^<=[0-9]" & as.double(values) == breakpoints_current$breakpoint_R,
-          paste0("MIC values at the R breakpoint with the operator '<=' are considered 'NI' (non-interpretable) since capped_mic_handling = \"", capped_mic_handling, "\""),
+          paste0("MIC values at the R breakpoint with the operator '<=' are considered 'NI' (non-interpretable) since capped_mic_handling = \"", capped_mic_handling, "\"."),
           ""
         ),
         "\n",
         ifelse(method == "mic" & capped_mic_handling %in% c("conservative", "standard") & as.character(values_bak) %like% "^>=[0-9]" & as.double(values) == breakpoints_current$breakpoint_S,
-          paste0("MIC values at the S breakpoint with the operator '>=' are considered 'NI' (non-interpretable) since capped_mic_handling = \"", capped_mic_handling, "\""),
+          paste0("MIC values at the S breakpoint with the operator '>=' are considered 'NI' (non-interpretable) since capped_mic_handling = \"", capped_mic_handling, "\"."),
           ""
         )
       )
@@ -1757,7 +1765,7 @@ as_sir_method <- function(method_short,
         notes_current <- paste0(
           notes_current, "\n",
           ifelse(!is.na(breakpoints_current$breakpoint_S) & is.na(breakpoints_current$breakpoint_R),
-            "NAs because of missing R breakpoints were substituted with R since substitute_missing_r_breakpoint = TRUE",
+            "NAs because of missing R breakpoints were substituted with R since substitute_missing_r_breakpoint = TRUE.",
             ""
           )
         )
@@ -1796,7 +1804,7 @@ as_sir_method <- function(method_short,
       }
 
       # write to verbose output
-      notes_current <- trimws2(notes_current)
+      notes_current <- gsub("\n\n", "\n", trimws2(notes_current), fixed = TRUE)
       notes_current[notes_current == ""] <- NA_character_
       out <- data.frame(
         # recycling 1 to 2 rows does not always seem to work, which is why vectorise_log_entry() was added
@@ -1904,11 +1912,11 @@ pillar_shaft.sir <- function(x, ...) {
     # colours will anyway not work when has_colour() == FALSE,
     # but then the indentation should also not be applied
     out[is.na(x)] <- font_grey("  NA")
-    out[x == "NI"] <- font_grey_bg(font_black("  NI "))
     out[x == "S"] <- font_green_bg("  S  ")
+    out[x == "SDD"] <- font_green_lighter_bg(" SDD ")
     out[x == "I"] <- font_orange_bg("  I  ")
-    out[x == "SDD"] <- font_orange_bg(" SDD ")
     out[x == "R"] <- font_rose_bg("  R  ")
+    out[x == "NI"] <- font_grey_bg(font_black("  NI "))
   }
   create_pillar_column(out, align = "left", width = 5)
 }

R/sir_calc.R

@@ -244,7 +244,7 @@ sir_calc_df <- function(type, # "proportion", "count" or "both"
   translate_ab <- get_translate_ab(translate_ab)
 
   data.bak <- data
-  # select only groups and antimicrobials
+  # select only groups and antibiotics
   if (is_null_or_grouped_tbl(data)) {
     data_has_groups <- TRUE
     groups <- get_group_names(data)
@@ -255,10 +255,12 @@ sir_calc_df <- function(type, # "proportion", "count" or "both"
   }
 
   data <- as.data.frame(data, stringsAsFactors = FALSE)
-  if (isTRUE(combine_SI)) {
-    for (i in seq_len(ncol(data))) {
-      if (is.sir(data[, i, drop = TRUE])) {
-        data[, i] <- as.character(data[, i, drop = TRUE])
+
+  for (i in seq_len(ncol(data))) {
+    # transform SIR columns
+    if (is.sir(data[, i, drop = TRUE])) {
+      data[, i] <- as.character(data[, i, drop = TRUE])
+      if (isTRUE(combine_SI)) {
         if ("SDD" %in% data[, i, drop = TRUE] && message_not_thrown_before("sir_calc_df", combine_SI, entire_session = TRUE)) {
           message_("Note that `sir_calc_df()` will also count dose-dependent susceptibility, 'SDD', as 'SI' when `combine_SI = TRUE`. This note will be shown once for this session.", as_note = FALSE)
         }
@@ -364,7 +366,7 @@ sir_calc_df <- function(type, # "proportion", "count" or "both"
   } else {
     # don't use as.sir() here, as it would add the class 'sir' and we would like
     # the same data structure as output, regardless of input
-    if (out$value[out$interpretation == "SDD"] > 0) {
+    if (any(out$value[out$interpretation == "SDD"] > 0, na.rm = TRUE)) {
       out$interpretation <- factor(out$interpretation, levels = c("S", "SDD", "I", "R"), ordered = TRUE)
     } else {
       out$interpretation <- factor(out$interpretation, levels = c("S", "I", "R"), ordered = TRUE)

R/sir_df.R

@@ -47,6 +47,6 @@ sir_df <- function(data,
       combine_SI = combine_SI,
       confidence_level = confidence_level
     ),
-    error = function(e) stop_(gsub("in sir_calc_df(): ", "", e$message, fixed = TRUE), call = -5)
+    error = function(e) stop_(gsub("in sir_calc_df(): ", "", conditionMessage(e), fixed = TRUE), call = -5)
   )
 }

R/tidymodels.R

@@ -19,56 +19,59 @@
 #' @keywords internal
 #' @export
 #' @examples
-#' library(tidymodels)
+#' if (require("tidymodels")) {
 #'
-#' # The below approach formed the basis for this paper: DOI 10.3389/fmicb.2025.1582703
-#' # Presence of ESBL genes was predicted based on raw MIC values.
+#'   # The below approach formed the basis for this paper: DOI 10.3389/fmicb.2025.1582703
+#'   # Presence of ESBL genes was predicted based on raw MIC values.
 #'
 #'
-#' # example data set in the AMR package
-#' esbl_isolates
+#'   # example data set in the AMR package
+#'   esbl_isolates
 #'
-#' # Prepare a binary outcome and convert to ordered factor
-#' data <- esbl_isolates %>%
-#'   mutate(esbl = factor(esbl, levels = c(FALSE, TRUE), ordered = TRUE))
+#'   # Prepare a binary outcome and convert to ordered factor
+#'   data <- esbl_isolates %>%
+#'     mutate(esbl = factor(esbl, levels = c(FALSE, TRUE), ordered = TRUE))
 #'
-#' # Split into training and testing sets
-#' split <- initial_split(data)
-#' training_data <- training(split)
-#' testing_data <- testing(split)
+#'   # Split into training and testing sets
+#'   split <- initial_split(data)
+#'   training_data <- training(split)
+#'   testing_data <- testing(split)
 #'
-#' # Create and prep a recipe with MIC log2 transformation
-#' mic_recipe <- recipe(esbl ~ ., data = training_data) %>%
-#'   # Optionally remove non-predictive variables
-#'   remove_role(genus, old_role = "predictor") %>%
-#'   # Apply the log2 transformation to all MIC predictors
-#'   step_mic_log2(all_mic_predictors()) %>%
-#'   prep()
+#'   # Create and prep a recipe with MIC log2 transformation
+#'   mic_recipe <- recipe(esbl ~ ., data = training_data) %>%
 #'
-#' # View prepped recipe
-#' mic_recipe
+#'     # Optionally remove non-predictive variables
+#'     remove_role(genus, old_role = "predictor") %>%
 #'
-#' # Apply the recipe to training and testing data
-#' out_training <- bake(mic_recipe, new_data = NULL)
-#' out_testing <- bake(mic_recipe, new_data = testing_data)
+#'     # Apply the log2 transformation to all MIC predictors
+#'     step_mic_log2(all_mic_predictors()) %>%
 #'
-#' # Fit a logistic regression model
-#' fitted <- logistic_reg(mode = "classification") %>%
-#'   set_engine("glm") %>%
-#'   fit(esbl ~ ., data = out_training)
+#'     # And apply the preparation steps
+#'     prep()
 #'
-#' # Generate predictions on the test set
-#' predictions <- predict(fitted, out_testing) %>%
-#'   bind_cols(out_testing)
+#'   # View prepped recipe
+#'   mic_recipe
 #'
-#' # Evaluate predictions using standard classification metrics
-#' our_metrics <- metric_set(accuracy, kap, ppv, npv)
-#' metrics <- our_metrics(predictions, truth = esbl, estimate = .pred_class)
+#'   # Apply the recipe to training and testing data
+#'   out_training <- bake(mic_recipe, new_data = NULL)
+#'   out_testing <- bake(mic_recipe, new_data = testing_data)
 #'
-#' # Show performance:
-#' # - negative predictive value (NPV) of ~98%
-#' # - positive predictive value (PPV) of ~94%
-#' metrics
+#'   # Fit a logistic regression model
+#'   fitted <- logistic_reg(mode = "classification") %>%
+#'     set_engine("glm") %>%
+#'     fit(esbl ~ ., data = out_training)
+#'
+#'   # Generate predictions on the test set
+#'   predictions <- predict(fitted, out_testing) %>%
+#'     bind_cols(out_testing)
+#'
+#'   # Evaluate predictions using standard classification metrics
+#'   our_metrics <- metric_set(accuracy, kap, ppv, npv)
+#'   metrics <- our_metrics(predictions, truth = esbl, estimate = .pred_class)
+#'
+#'   # Show performance
+#'   metrics
+#' }
 all_mic <- function() {
   x <- tidymodels_amr_select(levels(NA_mic_))
   names(x)

R/vctrs.R

@@ -30,7 +30,6 @@
 # These are all S3 implementations for the vctrs package,
 # that is used internally by tidyverse packages such as dplyr.
 # They are to convert AMR-specific classes to bare characters and integers.
-# All of them will be exported using s3_register() in R/zzz.R when loading the package.
 
 # see https://github.com/tidyverse/dplyr/issues/5955 why this is required
 

R/zzz.R

@@ -127,7 +127,7 @@ AMR_env$cross_icon <- if (isTRUE(base::l10n_info()$`UTF-8`)) "\u00d7" else "x"
           suppressWarnings(suppressMessages(add_custom_antimicrobials(x)))
           packageStartupMessage("OK.")
         },
-        error = function(e) packageStartupMessage("Failed: ", e$message)
+        error = function(e) packageStartupMessage("Failed: ", conditionMessage(e))
       )
     }
   }
@@ -143,7 +143,7 @@ AMR_env$cross_icon <- if (isTRUE(base::l10n_info()$`UTF-8`)) "\u00d7" else "x"
           suppressWarnings(suppressMessages(add_custom_microorganisms(x)))
           packageStartupMessage("OK.")
         },
-        error = function(e) packageStartupMessage("Failed: ", e$message)
+        error = function(e) packageStartupMessage("Failed: ", conditionMessage(e))
       )
     }
   }

data-raw/_generate_python_wrapper.sh

@@ -56,7 +56,8 @@ os.makedirs(r_lib_path, exist_ok=True)
 os.environ['R_LIBS_SITE'] = r_lib_path
 
 from rpy2 import robjects
-from rpy2.robjects import pandas2ri
+from rpy2.robjects.conversion import localconverter
+from rpy2.robjects import default_converter, numpy2ri, pandas2ri
 from rpy2.robjects.packages import importr, isinstalled
 
 # Import base and utils
@@ -94,27 +95,26 @@ if r_amr_version != python_amr_version:
 print(f"AMR: Setting up R environment and AMR datasets...", flush=True)
 
 # Activate the automatic conversion between R and pandas DataFrames
-pandas2ri.activate()
+with localconverter(default_converter + numpy2ri.converter + pandas2ri.converter):
+    # example_isolates
+    example_isolates = robjects.r('''
+    df <- AMR::example_isolates
+    df[] <- lapply(df, function(x) {
+        if (inherits(x, c("Date", "POSIXt", "factor"))) {
+            as.character(x)
+        } else {
+            x
+        }
+    })
+    df <- df[, !sapply(df, is.list)]
+    df
+    ''')
+    example_isolates['date'] = pd.to_datetime(example_isolates['date'])
 
-# example_isolates
-example_isolates = pandas2ri.rpy2py(robjects.r('''
-df <- AMR::example_isolates
-df[] <- lapply(df, function(x) {
-    if (inherits(x, c("Date", "POSIXt", "factor"))) {
-        as.character(x)
-    } else {
-        x
-    }
-})
-df <- df[, !sapply(df, is.list)]
-df
-'''))
-example_isolates['date'] = pd.to_datetime(example_isolates['date'])
-
-# microorganisms
-microorganisms = pandas2ri.rpy2py(robjects.r('AMR::microorganisms[, !sapply(AMR::microorganisms, is.list)]'))
-antimicrobials = pandas2ri.rpy2py(robjects.r('AMR::antimicrobials[, !sapply(AMR::antimicrobials, is.list)]'))
-clinical_breakpoints = pandas2ri.rpy2py(robjects.r('AMR::clinical_breakpoints[, !sapply(AMR::clinical_breakpoints, is.list)]'))
+    # microorganisms
+    microorganisms = robjects.r('AMR::microorganisms[, !sapply(AMR::microorganisms, is.list)]')
+    antimicrobials = robjects.r('AMR::antimicrobials[, !sapply(AMR::antimicrobials, is.list)]')
+    clinical_breakpoints = robjects.r('AMR::clinical_breakpoints[, !sapply(AMR::clinical_breakpoints, is.list)]')
 
 base.options(warn = 0)
 
@@ -129,16 +129,15 @@ echo "from .datasets import clinical_breakpoints" >> $init_file
 
 # Write header to the functions Python file, including the convert_to_python function
 cat <<EOL > "$functions_file"
+import functools
 import rpy2.robjects as robjects
 from rpy2.robjects.packages import importr
 from rpy2.robjects.vectors import StrVector, FactorVector, IntVector, FloatVector, DataFrame
-from rpy2.robjects import pandas2ri
+from rpy2.robjects.conversion import localconverter
+from rpy2.robjects import default_converter, numpy2ri, pandas2ri
 import pandas as pd
 import numpy as np
 
-# Activate automatic conversion between R data frames and pandas data frames
-pandas2ri.activate()
-
 # Import the AMR R package
 amr_r = importr('AMR')
 
@@ -156,10 +155,8 @@ def convert_to_python(r_output):
         return list(r_output)  # Convert to a Python list of integers or floats
     
     # Check if it's a pandas-compatible R data frame
-    elif isinstance(r_output, pd.DataFrame):
+    elif isinstance(r_output, (pd.DataFrame, DataFrame)):
         return r_output  # Return as pandas DataFrame (already converted by pandas2ri)
-    elif isinstance(r_output, DataFrame):
-        return pandas2ri.rpy2py(r_output) # Return as pandas DataFrame
 
     # Check if the input is a NumPy array and has a string data type
     if isinstance(r_output, np.ndarray) and np.issubdtype(r_output.dtype, np.str_):
@@ -167,6 +164,15 @@ def convert_to_python(r_output):
     
     # Fall-back
     return r_output
+
+def r_to_python(r_func):
+    """Decorator that runs an rpy2 function under a localconverter
+    and then applies convert_to_python to its output."""
+    @functools.wraps(r_func)
+    def wrapper(*args, **kwargs):
+        with localconverter(default_converter + numpy2ri.converter + pandas2ri.converter):
+            return convert_to_python(r_func(*args, **kwargs))
+    return wrapper
 EOL
 
 # Directory where the .Rd files are stored (update path as needed)
@@ -246,10 +252,11 @@ for rd_file in "$rd_dir"/*.Rd; do
         gsub("FALSE", "False", func_args)
         gsub("NULL", "None", func_args)
 
-        # Write the Python function definition to the output file
+        # Write the Python function definition to the output file, using decorator
+        print "@r_to_python" >> "'"$functions_file"'"  
         print "def " func_name_py "(" func_args "):" >> "'"$functions_file"'"  
         print "    \"\"\"Please see our website of the R package for the full manual: https://amr-for-r.org\"\"\"" >> "'"$functions_file"'"  
-        print "    return convert_to_python(amr_r." func_name_py "(" func_args "))" >> "'"$functions_file"'"
+        print "    return amr_r." func_name_py "(" func_args ")" >> "'"$functions_file"'"  
 
         print "from .functions import " func_name_py >> "'"$init_file"'"
     }

data-raw/_reproduction_scripts/reproduction_of_microorganisms.R

@@ -288,7 +288,7 @@ for (page in LETTERS) {
   url <- paste0("https://lpsn.dsmz.de/genus?page=", page)
   x <- tryCatch(read_html(url),
                 error = function(e) {
-                  message("Waiting 10 seconds because of error: ", e$message)
+                  message("Waiting 10 seconds because of error: ", conditionMessage(e))
                   Sys.sleep(10)
                   read_html(url)
                 })

data-raw/_reproduction_scripts/reproduction_of_poorman.R

@@ -108,3 +108,18 @@ writeLines(contents, "R/aa_helper_pm_functions.R")
 
 # note: pm_left_join() will be overwritten by aaa_helper_functions.R, which contains a faster implementation
 # replace `res <- as.data.frame(res)` with  `res <- as.data.frame(res, stringsAsFactors = FALSE)`
+
+# after running, pm_select must be altered. The line:
+# col_pos <- pm_select_positions(.data, ..., .group_pos = TRUE)
+# ... must be replaced with this to support tidyselect functionality such as `starts_with()`:
+# col_pos <- tryCatch(pm_select_positions(.data, ..., .group_pos = TRUE), error = function(e) NULL)
+# if (is.null(col_pos)) {
+#   # try with tidyverse
+#   select_dplyr <- import_fn("select", "dplyr", error_on_fail = FALSE)
+#   if (!is.null(select_dplyr)) {
+#     col_pos <- which(colnames(.data) %in% colnames(select_dplyr(.data, ...)))
+#   } else {
+#     # this will throw an error as it did, but dplyr is not available, so no other option
+#     col_pos <- pm_select_positions(.data, ..., .group_pos = TRUE)
+#   }
+# }

data-raw/ab.md5

@@ -1 +1 @@
-228840b3941753c4adee2b781d901590
+d12f1c78feaecbb4d1631f9c735ad49b

data-raw/datasets/antimicrobials.txt

@@ -116,7 +116,7 @@
 "CSU"	68718	"Cefsumide"	"Cephalosporins (unclassified gen.)"	"NA"			"NA"	"cefsulmid,cefsumido,cefsumidum"					"NA"
 "CPT"	56841980	"Ceftaroline"	"Cephalosporins (5th gen.)"	"J01DI02,QJ01DI02"			"ceftar,cfro"	"ceftaroine,teflaro,zinforo"					"73604-1,73605-8,73626-4,73627-2,73649-6,73650-4,74170-2"
 "CPA"		"Ceftaroline/avibactam"	"Cephalosporins (5th gen.)"	"NA"			"NA"	"NA"					"73604-1,73626-4,73649-6"
-"CAZ"	5481173	"Ceftazidime"	"Cephalosporins (3rd gen.)"	"J01DD02,QJ01DD02"	"Other beta-lactam antibacterials"	"Third-generation cephalosporins"	"caz,cefta,ceftaz,cfta,cftz,taz,tz,xtz"	"ceftazimide,ceptaz,fortam,fortaz,fortum,glazidim,kefazim,modacin,pentacef,tazicef,tizime"			4	"g"	"101481-0,101482-8,101483-6,132-1,133-9,134-7,135-4,18893-8,21151-6,3449-6,35774-9,35775-6,35776-4,42352-5,55648-0,55649-8,55650-6,55651-4,58705-5,6995-5,73603-3,73625-6,73648-8,80960-8,87734-0,90850-9"
+"CAZ"	5481173	"Ceftazidime"	"Cephalosporins (3rd gen.)"	"J01DD02,QJ01DD02"	"Other beta-lactam antibacterials"	"Third-generation cephalosporins"	"caz,cef,cefta,ceftaz,cfta,cftz,taz,tz,xtz"	"ceftazimide,ceptaz,fortam,fortaz,fortum,glazidim,kefazim,modacin,pentacef,tazicef,tizime"			4	"g"	"101481-0,101482-8,101483-6,132-1,133-9,134-7,135-4,18893-8,21151-6,3449-6,35774-9,35775-6,35776-4,42352-5,55648-0,55649-8,55650-6,55651-4,58705-5,6995-5,73603-3,73625-6,73648-8,80960-8,87734-0,90850-9"
 "CZA"	90643431	"Ceftazidime/avibactam"	"Cephalosporins (3rd gen.)"	"J01DD52,QJ01DD52"			"cfav"	"avycaz,zavicefta"			6	"g"	"101483-6,73603-3,73625-6,73648-8,87734-0"
 "CCV"	9575352	"Ceftazidime/clavulanic acid"	"Cephalosporins (3rd gen.)"	"J01DD52,QJ01DD52"	"Other beta-lactam antibacterials"	"Third-generation cephalosporins"	"czcl,tazcla,xtzl"	"NA"			6	"g"	"NA"
 "CEM"	6537431	"Cefteram"	"Cephalosporins (3rd gen.)"	"J01DD18,QJ01DD18"			"cefter"	"cefterame,cefteramum,ceftetrame"	0.4	"g"			"100047-0,76144-5"
@@ -162,7 +162,7 @@
 "CYC"	6234	"Cycloserine"	"Oxazolidinones"	"J04AB01,QJ04AB01"	"Drugs for treatment of tuberculosis"	"Antibiotics"	"cycl,cyclos"	"cicloserina,closina,cyclorin,cycloserin,cycloserinum,farmiserina,levcicloserina,levcycloserine,levcycloserinum,micoserina,miroserina,miroseryn,novoserin,oxamicina,oxamycin,seromycin,tebemicina,wasserina"	0.75	"g"			"16702-3,18914-2,212-1,213-9,214-7,215-4,23608-3,25207-2,25208-0,25209-8,25251-0,3519-6,55667-0"
 "DAL"	23724878	"Dalbavancin"	"Glycopeptides"	"J01XA04,QJ01XA04"	"Other antibacterials"	"Glycopeptide antibacterials"	"dalb,dalbav"	"dalbavancina,dalvance,xydalba,zeven"			1.5	"g"	"41688-3,41689-1,41690-9,41734-5"
 "DAN"	71335	"Danofloxacin"	"Fluoroquinolones"	"QJ01MA92"			"danofl"	"advocin,danofloxacine,danofloxacino,danofloxacinum"					"73601-7,73623-1,73646-2"
-"DPS"	2955	"Dapsone"	"Other antibacterials"	"D10AX05,J04BA02,QD10AX05,QJ04BA02"	"Drugs for treatment of lepra"	"Drugs for treatment of lepra"	"NA"	"aczone,atrisone,avlosulfon,avlosulfone,avlosulphone,benzenamide,benzenamine,bissulfone,bissulphone,croysulfone,croysulphone,dapson,dapsona,dapsonum,daspone,diaphenylsulfon,diaphenylsulfone,diaphenylsulphon,diaphenylsulphone,diphenasone,diphone,disulfone,disulone,disulphone,dubronax,dumitone,eporal,medapsol,novophone,servidapson,sulfadione,sulfona,sulfonyldianiline,sulphadione,sulphonyldianiline,tarimyl,udolac,undolac"	50	"mg"			"51698-9,9747-7"
+"DPS"	2955	"Dapsone"	"Other antibacterials"	"D10AX05,J04BA02,QD10AX05,QJ04BA02"	"Drugs for treatment of lepra"	"Drugs for treatment of lepra"	"dao"	"aczone,atrisone,avlosulfon,avlosulfone,avlosulphone,benzenamide,benzenamine,bissulfone,bissulphone,croysulfone,croysulphone,dapson,dapsona,dapsonum,daspone,diaphenylsulfon,diaphenylsulfone,diaphenylsulphon,diaphenylsulphone,diphenasone,diphone,disulfone,disulone,disulphone,dubronax,dumitone,eporal,medapsol,novophone,servidapson,sulfadione,sulfona,sulfonyldianiline,sulphadione,sulphonyldianiline,tarimyl,udolac,undolac"	50	"mg"			"51698-9,9747-7"
 "DAP"	16134395	"Daptomycin"	"Other antibacterials"	"J01XX09,QJ01XX09"	"Other antibacterials"	"Other antibacterials"	"dap,dapt,dapt25,dapt50,daptom"	"cidecin,cubicin,dapcin,daptomicina,daptomycine,daptomycinum,deptomycin"			0.28	"g"	"35787-1,35788-9,35789-7,41691-7"
 "DFX"	487101	"Delafloxacin"	"Fluoroquinolones"	"J01MA23,QJ01MA23"			"NA"	"baxdela,delafloxacinum,quofenix"	0.9	"g"	0.6	"g"	"88885-9,90447-4,93790-4"
 "DLM"	6480466	"Delamanid"	"Antimycobacterials"	"J04AK06,QJ04AK06"	"Drugs for treatment of tuberculosis"	"Other drugs for treatment of tuberculosis"	"dela"	"deltyba"	0.2	"g"			"93851-4,96109-4"
@@ -184,7 +184,7 @@
 "ERV"	54726192	"Eravacycline"	"Tetracyclines"	"J01AA13,QJ01AA13"	"Tetracyclines"	"Tetracyclines"	"erav"	"xerava"			0.14	"g"	"100049-6,85423-2,93767-2"
 "ETP"	150610	"Ertapenem"	"Carbapenems"	"J01DH03,QJ01DH03"	"Other beta-lactam antibacterials"	"Carbapenems"	"erta,ertape,etp"	"ertapenemsalt,invanz"			1	"g"	"101486-9,35799-6,35800-2,35801-0,35802-8"
 "ERY"	12560	"Erythromycin"	"Macrolides/lincosamides"	"D10AF02,J01FA01,QD10AF02,QJ01FA01,QJ51FA01,QS01AA17,S01AA17"	"Macrolides, lincosamides and streptogramins"	"Macrolides"	"e,em,ery,ery32,eryt,eryth"	"abboticin,abomacetin,acneryne,acnesol,aknemycin,aknin,benzamycin,derimer,deripil,dotycin,dumotrycin,emgel,emuvin,emycin,endoeritrin,erecin,erisone,eritomicina,eritrocina,eritromicina,ermycin,eryacne,eryacnen,erycen,erycette,erycinum,eryderm,erydermer,erygel,eryhexal,erymax,erymed,erysafe,erytab,erythro,erythroderm,erythrogran,erythroguent,erythromast,erythromid,erythromycine,erythromycinum,erytop,erytrociclin,ilocaps,ilosone,iloticina,ilotycin,inderm,latotryd,lederpax,mephamycin,mercina,oftamolets,pantoderm,pantodrin,pantomicina,pharyngocin,primacine,propiocine,proterytrin,retcin,robimycin,sansac,spotex,staticin,stiemicyn,stiemycin,tiprocin,torlamicina,wemid"	2	"g"	1	"g"	"100050-4,11576-6,12298-6,16829-4,16830-2,18919-1,18920-9,20380-2,232-9,233-7,234-5,235-2,236-0,23633-1,237-8,238-6,239-4,25224-7,25275-9,3597-2,7009-4"
-"ETH"	14052	"Ethambutol"	"Antimycobacterials"	"J04AK02,QJ04AK02"	"Drugs for treatment of tuberculosis"	"Other drugs for treatment of tuberculosis"	"etha,ethamb"	"aethambutolum,dadibutol,diambutol,etambutol,etambutolo,ethambutolum,myambutol,purderal,servambutol,tibutol"	1.2	"g"	1.2	"g"	"100051-2,16841-9,18921-7,20381-0,23625-7,240-2,241-0,242-8,243-6,25187-6,25194-2,25195-9,25230-4,25404-5,3607-9,42645-2,42646-0,55154-9,55674-6,56025-0,7010-2,89491-5"
+"ETH"	14052	"Ethambutol"	"Antimycobacterials"	"J04AK02,QJ04AK02"	"Drugs for treatment of tuberculosis"	"Other drugs for treatment of tuberculosis"	"emb,etha,ethamb"	"aethambutolum,dadibutol,diambutol,etambutol,etambutolo,ethambutolum,myambutol,purderal,servambutol,tibutol"	1.2	"g"	1.2	"g"	"100051-2,16841-9,18921-7,20381-0,23625-7,240-2,241-0,242-8,243-6,25187-6,25194-2,25195-9,25230-4,25404-5,3607-9,42645-2,42646-0,55154-9,55674-6,56025-0,7010-2,89491-5"
 "ETI"	456476	"Ethambutol/isoniazid"	"Antimycobacterials"	"J04AM03,QJ04AM03"	"Drugs for treatment of tuberculosis"	"Combinations of drugs for treatment of tuberculosis"	"NA"	"NA"					"NA"
 "ETI1"	2761171	"Ethionamide"	"Antimycobacterials"	"J04AD03,QJ04AD03"	"Drugs for treatment of tuberculosis"	"Thiocarbamide derivatives"	"ethi,ethion"	"aethionamidum,aetina,aetiva,amidazin,amidazine,atina,ethimide,ethina,ethinamide,ethionamidum,ethioniamide,ethylisothiamide,ethyonomide,etimid,etiocidan,etionamid,etionamida,etionamide,etioniamid,etionid,etionizin,etionizina,etionizine,fatoliamid,iridocin,iridozin,isothin,isotiamida,itiocide,nicotion,nisotin,nizotin,rigenicid,sertinon,teberus,thianid,thianide,thioamide,thiodine,thiomid,thioniden,tianid,tiomid,trecator,trekator,trescatyl,trescazide,tubenamide,tubermin,tuberoid,tuberoson"	0.75	"g"			"16099-4,16845-0,18922-5,20382-8,23617-4,25183-5,25196-7,25198-3,25231-2,41693-3,42647-8,42648-6,7011-0,96110-2"
 "ETO"	6034	"Ethopabate"	"Other antibacterials"	"QP51AX17"			"NA"	"ethopabat"					"NA"
@@ -202,7 +202,7 @@
 "FLM"	3374	"Flumequine"	"Quinolones"	"J01MB07,QJ01MB07"	"Quinolone antibacterials"	"Other quinolones"	"flumeq"	"apurone,fantacin,flumequina,flumequino,flumequinum,flumigal,flumiquil,flumisol,flumix,imequyl"	1.2	"g"			"55675-3,55676-1,55677-9,55678-7"
 "FLR1"	71260	"Flurithromycin"	"Macrolides/lincosamides"	"J01FA14,QJ01FA14"	"Macrolides, lincosamides and streptogramins"	"Macrolides"	"NA"	"abbot,beritromicina,berythromycin,berythromycine,berythromycinum,flurithromycine,flurithromycinum,fluritromicina,fluritromycinum,flurizic,mizar"	0.75	"g"			"NA"
 "FFL"	214356	"Fosfluconazole"	"Antifungals/antimycotics"	"NA"			"NA"	"fosfluconazol,procif,prodif"					"NA"
-"FOS"	446987	"Fosfomycin"	"Other antibacterials"	"J01XX01,QJ01XX01,QS02AA17,S02AA17"	"Other antibacterials"	"Other antibacterials"	"ff,fm,fo,fof,fos,fosf,fosfom,fosmyc"	"fosfocina,fosfomicin,fosfomicina,fosfomycine,fosfomycinum,fosfonomycin,infectophos,phosphonemycin,phosphonomycin,veramina"	3	"g"	8	"g"	"25596-8,25653-7,35809-3,35810-1"
+"FOS"	446987	"Fosfomycin"	"Phosphonics"	"J01XX01,QJ01XX01,QS02AA17,S02AA17"	"Other antibacterials"	"Other antibacterials"	"ff,fm,fo,fof,fos,fosf,fosfom,fosmyc"	"fosfocina,fosfomicin,fosfomicina,fosfomycine,fosfomycinum,fosfonomycin,infectophos,phosphonemycin,phosphonomycin,veramina"	3	"g"	8	"g"	"25596-8,25653-7,35809-3,35810-1"
 "FMD"	572	"Fosmidomycin"	"Other antibacterials"	"NA"			"NA"	"fosmidomicina,fosmidomycina,fosmidomycine,fosmidomycinsalt,fosmidomycinum"					"NA"
 "FRM"	8378	"Framycetin"	"Aminoglycosides"	"D09AA01,QD09AA01,QJ01GB91,QR01AX08,QS01AA07,R01AX08,S01AA07"			"fram,framyc"	"actilin,actiline,antibiotique,bycomycin,enterfram,fradiomycin,fradiomycinum,framicetina,framidal,framycetine,framycetinum,framycin,framygen,francetin,jernadex,myacyne,mycerin,mycifradin,neobrettin,neolate,neomas,neomcin,neomicina,neomin,neomycine,neomycinum,nivemycin,soframycin,soframycine"					"18926-6,257-6,258-4,259-2,260-0,55679-5"
 "FUR"	6870646	"Furazidin"	"Other antibacterials"	"J01XE03,QJ01XE03"	"Other antibacterials"	"Nitrofuran derivatives"	"NA"	"akritoin,furagin,furaginum,furamag,furazidine,hydantoin"	0.3	"g"			"NA"
@@ -268,7 +268,7 @@
 "MET"	6087	"Meticillin"	"Beta-lactams/penicillins"	"J01CF03,QJ01CF03,QJ51CF03"	"Beta-lactam antibacterials, penicillins"	"Beta-lactamase resistant penicillins"	"methic,meti"	"belfacillin,celbenin,celpilline,cinopenil,dimocillin,estafcilina,flabelline,lucopenin,metacillin,methcillin,methicillin,methicillinanhydrous,methicillinhydrate,methicillinsalt,methicillinum,methycillin,meticilina,meticillina,meticilline,meticillinsalt,meticillinum,penaureus,penysol,staficyn,staphcillin,synticillin"			4	"g"	"NA"
 "MTP"	68590	"Metioprim"	"Other antibacterials"	"NA"			"NA"	"methioprim,metioprima,metioprime,metioprimum"					"NA"
 "MXT"	3047729	"Metioxate"	"Fluoroquinolones"	"NA"			"NA"	"metioxato,metioxatum"					"NA"
-"MTR"	4173	"Metronidazole"	"Other antibacterials"	"A01AB17,D06BX01,G01AF01,J01XD01,P01AB01,QA01AB17,QD06BX01,QG01AF01,QJ01XD01,QP51CA01"	"Other antibacterials"	"Imidazole derivatives"	"metr,metron,mnz"	"acromona,anagiardil,arilin,atrivyl,bexon,clont,danizol,deflamon,donnan,efloran,elyzol,entizol,eumin,flagemona,flagesol,flagil,flagyl,flazol,flegyl,florazole,fossyol,giatricol,gineflavir,givagil,hydroxydimetridazole,hydroxymetronidazole,izoklion,klion,klont,mepagyl,meronidal,metric,metrolag,metrolyl,metromidol,metronidazolo,metronidazolum,metroplex,metrotop,mexibol,monagyl,monasin,nalox,nidagyl,noritate,novonidazol,nuvessa,orvagil,polibiotic,protostat,rathimed,rosaced,rosased,sanatrichom,satric,takimetol,trichazol,trichex,trichobrol,trichocide,trichomol,trichopal,trichopol,tricocet,tricom,trikacide,trikamon,trikhopol,trikojol,trikozol,trimeks,trivazol,vagilen,vagimid,vandazole,vertisal,wagitran,zadstat,zidoval"	2	"g"	1.5	"g"	"10991-8,18946-4,326-9,327-7,328-5,329-3,7031-8"
+"MTR"	4173	"Metronidazole"	"Other antibacterials"	"A01AB17,D06BX01,G01AF01,J01XD01,P01AB01,QA01AB17,QD06BX01,QG01AF01,QJ01XD01,QP51CA01"	"Other antibacterials"	"Imidazole derivatives"	"metr,metron,mnz,mtz"	"acromona,anagiardil,arilin,atrivyl,bexon,clont,danizol,deflamon,donnan,efloran,elyzol,entizol,eumin,flagemona,flagesol,flagil,flagyl,flazol,flegyl,florazole,fossyol,giatricol,gineflavir,givagil,hydroxydimetridazole,hydroxymetronidazole,izoklion,klion,klont,mepagyl,meronidal,metric,metrolag,metrolyl,metromidol,metronidazolo,metronidazolum,metroplex,metrotop,mexibol,monagyl,monasin,nalox,nidagyl,noritate,novonidazol,nuvessa,orvagil,polibiotic,protostat,rathimed,rosaced,rosased,sanatrichom,satric,takimetol,trichazol,trichex,trichobrol,trichocide,trichomol,trichopal,trichopol,tricocet,tricom,trikacide,trikamon,trikhopol,trikojol,trikozol,trimeks,trivazol,vagilen,vagimid,vandazole,vertisal,wagitran,zadstat,zidoval"	2	"g"	1.5	"g"	"10991-8,18946-4,326-9,327-7,328-5,329-3,7031-8"
 "MEZ"	656511	"Mezlocillin"	"Beta-lactams/penicillins"	"J01CA10,QJ01CA10"	"Beta-lactam antibacterials, penicillins"	"Penicillins with extended spectrum"	"mez,mezl,mezlo,mz"	"baycipen,baypen,mezlin,mezlocilina,mezlocilline,mezlocillinsalt,mezlocillinum,multocillin"			6	"g"	"18947-2,330-1,331-9,332-7,333-5,3820-8,41702-2,54194-6,54195-3,54196-1"
 "MSU"		"Mezlocillin/sulbactam"	"Beta-lactams/penicillins"	"NA"			"mezsul"	"NA"					"54194-6,54195-3,54196-1"
 "MIF"	477468	"Micafungin"	"Antifungals/antimycotics"	"J02AX05,QJ02AX05"	"Antimycotics for systemic use"	"Other antimycotics for systemic use"	"mica,micafu"	"fungard,funguard,micafungina,micafunginsalt,mycamine"			0.1	"g"	"53812-4,58418-5,65340-2,85048-7"
@@ -339,7 +339,7 @@
 "PMR"	5284447	"Pimaricin"	"Antifungals/antimycotics"	"NA"			"natamycin"	"delvocid,delvolan,delvopos,mycophyt,myprozine,natacyn,natafucin,natajen,natamatrix,natamax,natamicina,natamycin,natamycine,natamycinum,pimafucin,pimaracin,pimaricine,pimarizin,synogil,tennecetin"					"NA"
 "PPA"	4831	"Pipemidic acid"	"Quinolones"	"J01MB04,QJ01MB04"	"Quinolone antibacterials"	"Other quinolones"	"pipaci,pipz,pizu"	"deblaston,dolcol,filtrax,karunomazin,memento,nuril,palin,pipedac,pipemid,pipemidate,pipemidic,pipemidicacid,pipram,pipurin,tractur,uromidin,urosten,uroval"	0.8	"g"			"NA"
 "PIP"	43672	"Piperacillin"	"Beta-lactams/penicillins"	"J01CA12,QJ01CA12"	"Beta-lactam antibacterials, penicillins"	"Penicillins with extended spectrum"	"pi,pip,pipc,pipe,pipera,pp"	"penmalin,pentcillin,peperacillin,peracin,piperacilina,piperacillina,piperacilline,piperacillinhydrate,piperacillinum,pipercillin,pipracil,tazocin"			14	"g"	"101490-1,101491-9,18969-6,18970-4,25268-4,3972-7,407-7,408-5,409-3,410-1,411-9,412-7,413-5,414-3,54197-9,54198-7,54199-5,55704-1,7043-3,7044-1"
-"PIS"		"Piperacillin/sulbactam"	"Beta-lactams/penicillins"	"J01CR05,QJ01CR05"			"NA"	"NA"			14	"g"	"54197-9,54198-7,54199-5,55704-1"
+"PIS"		"Piperacillin/sulbactam"	"Beta-lactams/penicillins"	"NA"			"NA"	"NA"			14	"g"	"54197-9,54198-7,54199-5,55704-1"
 "TZP"	461573	"Piperacillin/tazobactam"	"Beta-lactams/penicillins"	"J01CR05,QJ01CR05"	"Beta-lactam antibacterials, penicillins"	"Combinations of penicillins, incl. beta-lactamase inhibitors"	"p/t,piptaz,piptazo,pit,pita,pt,ptc,ptz,tzp"	"piptazobactam,tazonam,zobactin,zosyn"			14	"g"	"101491-9,18970-4,411-9,412-7,413-5,414-3,7044-1"
 "PRC"	71978	"Piridicillin"	"Beta-lactams/penicillins"	"NA"			"NA"	"NA"					"NA"
 "PRL"	157385	"Pirlimycin"	"Macrolides/lincosamides"	"QJ51FF90"			"pirlim"	"pirlimycina,pirlimycine,pirlimycinum,pirsue"					"35829-1,35830-9,35831-7"
@@ -370,7 +370,7 @@
 "RBC"	44631912	"Ribociclib"	"Antifungals/antimycotics"	"L01EF02,QL01EF02"	"Antimycotics for systemic use"	"Triazole derivatives"	"ribo"	"kisqali"	0.45	"g"			"NA"
 "RST"	33042	"Ribostamycin"	"Aminoglycosides"	"J01GB10,QJ01GB10"	"Aminoglycoside antibacterials"	"Other aminoglycosides"	"NA"	"exaluren,hetangmycin,ribastamin,ribostamicina,ribostamycine,ribostamycinum,vistamycin,xylostatin"			1	"g"	"NA"
 "RID1"	16659285	"Ridinilazole"	"Other antibacterials"	"NA"			"NA"	"ridinilazol"					"NA"
-"RIB"	135398743	"Rifabutin"	"Antimycobacterials"	"J04AB04,QJ04AB04"	"Drugs for treatment of tuberculosis"	"Antibiotics"	"ansamy,rifb"	"alfacid,ansamicin,ansamycins,ansatipin,ansatipine,assatipin,mycobutin,rifabutinum"	0.15	"g"			"100699-8,16100-0,16386-5,16387-3,19149-4,20386-9,23630-7,24032-5,25199-1,25200-7,25201-5,42655-1,42656-9,54183-9,96113-6"
+"RIB"	135398743	"Rifabutin"	"Antimycobacterials"	"J04AB04,QJ04AB04"	"Drugs for treatment of tuberculosis"	"Antibiotics"	"ansamy,rfb,rifb"	"alfacid,ansamicin,ansamycins,ansatipin,ansatipine,assatipin,mycobutin,rifabutinum"	0.15	"g"			"100699-8,16100-0,16386-5,16387-3,19149-4,20386-9,23630-7,24032-5,25199-1,25200-7,25201-5,42655-1,42656-9,54183-9,96113-6"
 "RIF"	135398735	"Rifampicin"	"Antimycobacterials"	"J04AB02,QJ04AB02,QJ54AB02"	"Drugs for treatment of tuberculosis"	"Antibiotics"	"rifa,rifamp"	"abrifam,archidyn,arficin,arzide,benemicin,doloresum,eremfat,famcin,fenampicin,rifadin,rifadine,rifagen,rifaldazin,rifaldazine,rifaldin,rifam,rifamor,rifampicina,rifampicine,rifampicinum,rifampin,rifamsolin,rifapiam,rifaprodin,rifcin,rifinah,rifobac,rifoldin,rifoldine,riforal,rimactan,rimactane,rimactazid,rimactizid,rimazid,sinerdol,tubocin"	0.6	"g"	0.6	"g"	"NA"
 "REI"	135483893	"Rifampicin/ethambutol/isoniazid"	"Antimycobacterials"	"J04AM07,QJ04AM07"	"Drugs for treatment of tuberculosis"	"Combinations of drugs for treatment of tuberculosis"	"NA"	"isonarif,rifamate,rifamazid"					"NA"
 "RFI"		"Rifampicin/isoniazid"	"Antimycobacterials"	"J04AM02,QJ04AM02"	"Drugs for treatment of tuberculosis"	"Combinations of drugs for treatment of tuberculosis"	"NA"	"NA"					"NA"
@@ -391,7 +391,6 @@
 "SRC"	54681908	"Sarecycline"	"Tetracyclines"	"J01AA14,QJ01AA14"	"Tetracyclines"	"Tetracyclines"	"NA"	"sareciclina,seysara"	0.1	"g"			"NA"
 "SRX"	9933415	"Sarmoxicillin"	"Beta-lactams/penicillins"	"NA"			"NA"	"sarmoxillina,sarmoxilline,sarmoxillinum"					"NA"
 "SEC"	71815	"Secnidazole"	"Other antibacterials"	"P01AB07"			"NA"	"flagentyl,secnidal,secnidazolum,secnil,sindose,solosec"	2	"g"			"NA"
-"SMF"		"Simvastatin/fenofibrate"	"Antimycobacterials"	"C10BA04,QC10BA04"	"Drugs for treatment of tuberculosis"	"Other drugs for treatment of tuberculosis"	"simv"	"NA"					"NA"
 "SIS"	36119	"Sisomicin"	"Aminoglycosides"	"J01GB08,QJ01GB08"	"Aminoglycoside antibacterials"	"Other aminoglycosides"	"siso,sisomy"	"rickamicin,salvamina,sisomicina,sisomicine,sisomicinum,sisomin,sisomycin,sissomicin,sizomycin"			0.24	"g"	"18979-5,447-3,448-1,449-9,450-7,55714-0"
 "SIT"	461399	"Sitafloxacin"	"Fluoroquinolones"	"J01MA21,QJ01MA21"			"sitafl"	"gracevit"	0.1	"g"			"NA"
 "SDA"	2724368	"Sodium aminosalicylate"	"Antimycobacterials"	"J04AA02,QJ04AA02"	"Drugs for treatment of tuberculosis"	"Aminosalicylic acid and derivatives"	"NA"	"bactylan,lepasen,monopas,tubersan"	14	"g"	14	"g"	"NA"
@@ -495,4 +494,4 @@
 "VOR"	71616	"Voriconazole"	"Antifungals/antimycotics"	"J02AC03,QJ02AC03"	"Antimycotics for systemic use"	"Triazole derivatives"	"vori,vorico,vrc"	"vfend,voriconazol,voriconazolum,voriconzole,vorikonazole"	0.4	"g"	0.4	"g"	"32379-0,35862-2,35863-0,38370-3,41199-1,41200-7,53902-3,73676-9,80553-1,80651-3"
 "XBR"	72144	"Xibornol"	"Other antibacterials"	"J01XX02,QJ01XX02"	"Other antibacterials"	"Other antibacterials"	"NA"	"bactacine,bracen,nanbacine,xibornolo,xibornolum"					"NA"
 "ZID"	77846445	"Zidebactam"	"Other antibacterials"	"NA"			"NA"	"zidebactamsalt"					"NA"
-"ZFD"		"Zoliflodacin"		"NA"			"NA"	"NA"					"NA"
+"ZFD"		"Zoliflodacin"		"NA"			"zol"	"NA"					"NA"

data-raw/read_EUCAST.R

@@ -283,7 +283,7 @@ for (i in 2:length(sheets_to_analyse)) {
         guideline_name = guideline_name
       )
     ),
-    error = function(e) message(e$message)
+    error = function(e) message(conditionMessage(e))
   )
 }
 

index.Rmd

@@ -133,7 +133,7 @@ ggplot(data.frame(mic = some_mic_values,
                   sir = interpretation),
        aes(x = group, y = mic, colour = sir)) +
   theme_minimal() +
-  geom_boxplot(fill = NA, colour = "grey") +
+  geom_boxplot(fill = NA, colour = "grey30") +
   geom_jitter(width = 0.25) +
   
   # NEW scale function: plot MIC values to x, y, colour or fill

index.md

@@ -27,12 +27,12 @@
 
 <p style="text-align:left; width: 50%;">
 
-<small><a href="https://amr-for-r.org/">https://amr-for-r.org</a></small>
+<small><a href="https://amr-for-r.org/">amr-for-r.org</a></small>
 </p>
 
 <p style="text-align:right; width: 50%;">
 
-<small><a href="https://doi.org/10.18637/jss.v104.i03" target="_blank">https://doi.org/10.18637/jss.v104.i03</a></small>
+<small><a href="https://doi.org/10.18637/jss.v104.i03" target="_blank">doi.org/10.18637/jss.v104.i03</a></small>
 </p>
 
 </div>
@@ -171,14 +171,14 @@ example_isolates %>%
   select(bacteria,
          aminoglycosides(),
          carbapenems())
-#> ℹ Using column 'mo' as input for mo_fullname()
-#> ℹ Using column 'mo' as input for mo_is_gram_negative()
-#> ℹ Using column 'mo' as input for mo_is_intrinsic_resistant()
+#> ℹ Using column 'mo' as input for `mo_fullname()`
+#> ℹ Using column 'mo' as input for `mo_is_gram_negative()`
+#> ℹ Using column 'mo' as input for `mo_is_intrinsic_resistant()`
 #> ℹ Determining intrinsic resistance based on 'EUCAST Expected Resistant
 #>   Phenotypes' v1.2 (2023). This note will be shown once per session.
-#> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB'
+#> ℹ For `aminoglycosides()` using columns 'GEN' (gentamicin), 'TOB'
 #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin)
-#> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem)
+#> ℹ For `carbapenems()` using columns 'IPM' (imipenem) and 'MEM' (meropenem)
 #> # A tibble: 35 × 7
 #>    bacteria                     GEN   TOB   AMK   KAN   IPM   MEM  
 #>    <chr>                        <sir> <sir> <sir> <sir> <sir> <sir>
@@ -215,9 +215,9 @@ output format automatically (such as markdown, LaTeX, HTML, etc.).
 ``` r
 antibiogram(example_isolates,
             antimicrobials = c(aminoglycosides(), carbapenems()))
-#> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB'
+#> ℹ For `aminoglycosides()` using columns 'GEN' (gentamicin), 'TOB'
 #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin)
-#> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem)
+#> ℹ For `carbapenems()` using columns 'IPM' (imipenem) and 'MEM' (meropenem)
 ```
 
 | Pathogen | Amikacin | Gentamicin | Imipenem | Kanamycin | Meropenem | Tobramycin |
@@ -289,7 +289,7 @@ ggplot(data.frame(mic = some_mic_values,
                   sir = interpretation),
        aes(x = group, y = mic, colour = sir)) +
   theme_minimal() +
-  geom_boxplot(fill = NA, colour = "grey") +
+  geom_boxplot(fill = NA, colour = "grey30") +
   geom_jitter(width = 0.25) +
   
   # NEW scale function: plot MIC values to x, y, colour or fill
@@ -321,9 +321,9 @@ example_isolates %>%
 #> # A tibble: 3 × 5
 #>   ward       GEN_total_R GEN_conf_int TOB_total_R TOB_conf_int
 #>   <chr>            <dbl> <chr>              <dbl> <chr>       
-#> 1 Clinical     0.2289362 0.205-0.254    0.3147503 0.284-0.347 
-#> 2 ICU          0.2902655 0.253-0.33     0.4004739 0.353-0.449 
-#> 3 Outpatient   0.2       0.131-0.285    0.3676471 0.254-0.493
+#> 1 Clinical         0.229 0.205-0.254        0.315 0.284-0.347 
+#> 2 ICU              0.290 0.253-0.33         0.400 0.353-0.449 
+#> 3 Outpatient       0.2   0.131-0.285        0.368 0.254-0.493
 ```
 
 Or use [antimicrobial
@@ -340,44 +340,44 @@ out <- example_isolates %>%
   # calculate AMR using resistance(), over all aminoglycosides and polymyxins:
   summarise(across(c(aminoglycosides(), polymyxins()),
             resistance))
-#> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB'
+#> ℹ For `aminoglycosides()` using columns 'GEN' (gentamicin), 'TOB'
 #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin)
-#> ℹ For polymyxins() using column 'COL' (colistin)
+#> ℹ For `polymyxins()` using column 'COL' (colistin)
 #> Warning: There was 1 warning in `summarise()`.
 #> ℹ In argument: `across(c(aminoglycosides(), polymyxins()), resistance)`.
 #> ℹ In group 3: `ward = "Outpatient"`.
 #> Caused by warning:
 #> ! Introducing NA: only 23 results available for KAN in group: ward =
-#> "Outpatient" (minimum = 30).
+#> "Outpatient" (`minimum` = 30).
 out
 #> # A tibble: 3 × 6
-#>   ward             GEN       TOB       AMK   KAN       COL
-#>   <chr>          <dbl>     <dbl>     <dbl> <dbl>     <dbl>
-#> 1 Clinical   0.2289362 0.3147503 0.6258993     1 0.7802956
-#> 2 ICU        0.2902655 0.4004739 0.6624473     1 0.8574144
-#> 3 Outpatient 0.2       0.3676471 0.6052632    NA 0.8888889
+#>   ward         GEN   TOB   AMK   KAN   COL
+#>   <chr>      <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1 Clinical   0.229 0.315 0.626     1 0.780
+#> 2 ICU        0.290 0.400 0.662     1 0.857
+#> 3 Outpatient 0.2   0.368 0.605    NA 0.889
 ```
 
 ``` r
 # transform the antibiotic columns to names:
 out %>% set_ab_names()
 #> # A tibble: 3 × 6
-#>   ward       gentamicin tobramycin  amikacin kanamycin  colistin
-#>   <chr>           <dbl>      <dbl>     <dbl>     <dbl>     <dbl>
-#> 1 Clinical    0.2289362  0.3147503 0.6258993         1 0.7802956
-#> 2 ICU         0.2902655  0.4004739 0.6624473         1 0.8574144
-#> 3 Outpatient  0.2        0.3676471 0.6052632        NA 0.8888889
+#>   ward       gentamicin tobramycin amikacin kanamycin colistin
+#>   <chr>           <dbl>      <dbl>    <dbl>     <dbl>    <dbl>
+#> 1 Clinical        0.229      0.315    0.626         1    0.780
+#> 2 ICU             0.290      0.400    0.662         1    0.857
+#> 3 Outpatient      0.2        0.368    0.605        NA    0.889
 ```
 
 ``` r
 # transform the antibiotic column to ATC codes:
 out %>% set_ab_names(property = "atc")
 #> # A tibble: 3 × 6
-#>   ward         J01GB03   J01GB01   J01GB06 J01GB04   J01XB01
-#>   <chr>          <dbl>     <dbl>     <dbl>   <dbl>     <dbl>
-#> 1 Clinical   0.2289362 0.3147503 0.6258993       1 0.7802956
-#> 2 ICU        0.2902655 0.4004739 0.6624473       1 0.8574144
-#> 3 Outpatient 0.2       0.3676471 0.6052632      NA 0.8888889
+#>   ward       J01GB03 J01GB01 J01GB06 J01GB04 J01XB01
+#>   <chr>        <dbl>   <dbl>   <dbl>   <dbl>   <dbl>
+#> 1 Clinical     0.229   0.315   0.626       1   0.780
+#> 2 ICU          0.290   0.400   0.662       1   0.857
+#> 3 Outpatient   0.2     0.368   0.605      NA   0.889
 ```
 
 ## What else can you do with this package?

man/age_groups.Rd

@@ -4,20 +4,23 @@
 \alias{age_groups}
 \title{Split Ages into Age Groups}
 \usage{
-age_groups(x, split_at = c(12, 25, 55, 75), na.rm = FALSE)
+age_groups(x, split_at = c(0, 12, 25, 55, 75), names = NULL,
+  na.rm = FALSE)
 }
 \arguments{
 \item{x}{Age, e.g. calculated with \code{\link[=age]{age()}}.}
 
 \item{split_at}{Values to split \code{x} at - the default is age groups 0-11, 12-24, 25-54, 55-74 and 75+. See \emph{Details}.}
 
+\item{names}{Optional names to be given to the various age groups.}
+
 \item{na.rm}{A \link{logical} to indicate whether missing values should be removed.}
 }
 \value{
 Ordered \link{factor}
 }
 \description{
-Split ages into age groups defined by the \code{split} argument. This allows for easier demographic (antimicrobial resistance) analysis.
+Split ages into age groups defined by the \code{split} argument. This allows for easier demographic (antimicrobial resistance) analysis. The function returns an ordered \link{factor}.
 }
 \details{
 To split ages, the input for the \code{split_at} argument can be:
@@ -41,6 +44,7 @@ age_groups(ages, 50)
 
 # split into 0-19, 20-49 and 50+
 age_groups(ages, c(20, 50))
+age_groups(ages, c(20, 50), names = c("Under 20 years", "20 to 50 years", "Over 50 years"))
 
 # split into groups of ten years
 age_groups(ages, 1:10 * 10)

man/amr-tidymodels.Rd

@@ -65,56 +65,59 @@ Pre-processing pipeline steps include:
 These steps integrate with \code{recipes::recipe()} and work like standard preprocessing steps. They are useful for preparing data for modelling, especially with classification models.
 }
 \examples{
-library(tidymodels)
+if (require("tidymodels")) {
 
-# The below approach formed the basis for this paper: DOI 10.3389/fmicb.2025.1582703
-# Presence of ESBL genes was predicted based on raw MIC values.
+  # The below approach formed the basis for this paper: DOI 10.3389/fmicb.2025.1582703
+  # Presence of ESBL genes was predicted based on raw MIC values.
 
 
-# example data set in the AMR package
-esbl_isolates
+  # example data set in the AMR package
+  esbl_isolates
 
-# Prepare a binary outcome and convert to ordered factor
-data <- esbl_isolates \%>\%
-  mutate(esbl = factor(esbl, levels = c(FALSE, TRUE), ordered = TRUE))
+  # Prepare a binary outcome and convert to ordered factor
+  data <- esbl_isolates \%>\%
+    mutate(esbl = factor(esbl, levels = c(FALSE, TRUE), ordered = TRUE))
 
-# Split into training and testing sets
-split <- initial_split(data)
-training_data <- training(split)
-testing_data <- testing(split)
+  # Split into training and testing sets
+  split <- initial_split(data)
+  training_data <- training(split)
+  testing_data <- testing(split)
 
-# Create and prep a recipe with MIC log2 transformation
-mic_recipe <- recipe(esbl ~ ., data = training_data) \%>\%
-  # Optionally remove non-predictive variables
-  remove_role(genus, old_role = "predictor") \%>\%
-  # Apply the log2 transformation to all MIC predictors
-  step_mic_log2(all_mic_predictors()) \%>\%
-  prep()
+  # Create and prep a recipe with MIC log2 transformation
+  mic_recipe <- recipe(esbl ~ ., data = training_data) \%>\%
 
-# View prepped recipe
-mic_recipe
+    # Optionally remove non-predictive variables
+    remove_role(genus, old_role = "predictor") \%>\%
 
-# Apply the recipe to training and testing data
-out_training <- bake(mic_recipe, new_data = NULL)
-out_testing <- bake(mic_recipe, new_data = testing_data)
+    # Apply the log2 transformation to all MIC predictors
+    step_mic_log2(all_mic_predictors()) \%>\%
 
-# Fit a logistic regression model
-fitted <- logistic_reg(mode = "classification") \%>\%
-  set_engine("glm") \%>\%
-  fit(esbl ~ ., data = out_training)
+    # And apply the preparation steps
+    prep()
 
-# Generate predictions on the test set
-predictions <- predict(fitted, out_testing) \%>\%
-  bind_cols(out_testing)
+  # View prepped recipe
+  mic_recipe
 
-# Evaluate predictions using standard classification metrics
-our_metrics <- metric_set(accuracy, kap, ppv, npv)
-metrics <- our_metrics(predictions, truth = esbl, estimate = .pred_class)
+  # Apply the recipe to training and testing data
+  out_training <- bake(mic_recipe, new_data = NULL)
+  out_testing <- bake(mic_recipe, new_data = testing_data)
 
-# Show performance:
-# - negative predictive value (NPV) of ~98\%
-# - positive predictive value (PPV) of ~94\%
-metrics
+  # Fit a logistic regression model
+  fitted <- logistic_reg(mode = "classification") \%>\%
+    set_engine("glm") \%>\%
+    fit(esbl ~ ., data = out_training)
+
+  # Generate predictions on the test set
+  predictions <- predict(fitted, out_testing) \%>\%
+    bind_cols(out_testing)
+
+  # Evaluate predictions using standard classification metrics
+  our_metrics <- metric_set(accuracy, kap, ppv, npv)
+  metrics <- our_metrics(predictions, truth = esbl, estimate = .pred_class)
+
+  # Show performance
+  metrics
+}
 }
 \seealso{
 \code{\link[recipes:recipe]{recipes::recipe()}}, \code{\link[=as.mic]{as.mic()}}, \code{\link[=as.sir]{as.sir()}}

man/antimicrobial_selectors.Rd

@@ -181,7 +181,7 @@ The \code{\link[=not_intrinsic_resistant]{not_intrinsic_resistant()}} function c
 \item \code{\link[=aminoglycosides]{aminoglycosides()}} can select: \cr amikacin (AMK), amikacin/fosfomycin (AKF), apramycin (APR), arbekacin (ARB), astromicin (AST), bekanamycin (BEK), dibekacin (DKB), framycetin (FRM), gentamicin (GEN), gentamicin-high (GEH), habekacin (HAB), hygromycin (HYG), isepamicin (ISE), kanamycin (KAN), kanamycin-high (KAH), kanamycin/cephalexin (KAC), micronomicin (MCR), neomycin (NEO), netilmicin (NET), pentisomicin (PIM), plazomicin (PLZ), propikacin (PKA), ribostamycin (RST), sisomicin (SIS), streptoduocin (STR), streptomycin (STR1), streptomycin-high (STH), tobramycin (TOB), and tobramycin-high (TOH)
 \item \code{\link[=aminopenicillins]{aminopenicillins()}} can select: \cr amoxicillin (AMX) and ampicillin (AMP)
 \item \code{\link[=antifungals]{antifungals()}} can select: \cr amorolfine (AMO), amphotericin B (AMB), amphotericin B-high (AMH), anidulafungin (ANI), butoconazole (BUT), caspofungin (CAS), ciclopirox (CIX), clotrimazole (CTR), econazole (ECO), fluconazole (FLU), flucytosine (FCT), fosfluconazole (FFL), griseofulvin (GRI), hachimycin (HCH), ibrexafungerp (IBX), isavuconazole (ISV), isoconazole (ISO), itraconazole (ITR), ketoconazole (KET), manogepix (MGX), micafungin (MIF), miconazole (MCZ), nystatin (NYS), oteseconazole (OTE), pimaricin (PMR), posaconazole (POS), rezafungin (RZF), ribociclib (RBC), sulconazole (SUC), terbinafine (TRB), terconazole (TRC), and voriconazole (VOR)
-\item \code{\link[=antimycobacterials]{antimycobacterials()}} can select: \cr 4-aminosalicylic acid (AMA), calcium aminosalicylate (CLA), capreomycin (CAP), clofazimine (CLF), delamanid (DLM), enviomycin (ENV), ethambutol (ETH), ethambutol/isoniazid (ETI), ethionamide (ETI1), isoniazid (INH), isoniazid/sulfamethoxazole/trimethoprim/pyridoxine (IST), morinamide (MRN), p-aminosalicylic acid (PAS), pretomanid (PMD), protionamide (PTH), pyrazinamide (PZA), rifabutin (RIB), rifampicin (RIF), rifampicin/ethambutol/isoniazid (REI), rifampicin/isoniazid (RFI), rifampicin/pyrazinamide/ethambutol/isoniazid (RPEI), rifampicin/pyrazinamide/isoniazid (RPI), rifamycin (RFM), rifapentine (RFP), simvastatin/fenofibrate (SMF), sodium aminosalicylate (SDA), streptomycin/isoniazid (STI), terizidone (TRZ), thioacetazone (TAT), thioacetazone/isoniazid (THI1), tiocarlide (TCR), and viomycin (VIO)
+\item \code{\link[=antimycobacterials]{antimycobacterials()}} can select: \cr 4-aminosalicylic acid (AMA), calcium aminosalicylate (CLA), capreomycin (CAP), clofazimine (CLF), delamanid (DLM), enviomycin (ENV), ethambutol (ETH), ethambutol/isoniazid (ETI), ethionamide (ETI1), isoniazid (INH), isoniazid/sulfamethoxazole/trimethoprim/pyridoxine (IST), morinamide (MRN), p-aminosalicylic acid (PAS), pretomanid (PMD), protionamide (PTH), pyrazinamide (PZA), rifabutin (RIB), rifampicin (RIF), rifampicin/ethambutol/isoniazid (REI), rifampicin/isoniazid (RFI), rifampicin/pyrazinamide/ethambutol/isoniazid (RPEI), rifampicin/pyrazinamide/isoniazid (RPI), rifamycin (RFM), rifapentine (RFP), sodium aminosalicylate (SDA), streptomycin/isoniazid (STI), terizidone (TRZ), thioacetazone (TAT), thioacetazone/isoniazid (THI1), tiocarlide (TCR), and viomycin (VIO)
 \item \code{\link[=betalactams]{betalactams()}} can select: \cr amoxicillin (AMX), amoxicillin/clavulanic acid (AMC), amoxicillin/sulbactam (AXS), ampicillin (AMP), ampicillin/sulbactam (SAM), apalcillin (APL), aspoxicillin (APX), azidocillin (AZD), azlocillin (AZL), aztreonam (ATM), aztreonam/avibactam (AZA), aztreonam/nacubactam (ANC), bacampicillin (BAM), benzathine benzylpenicillin (BNB), benzathine phenoxymethylpenicillin (BNP), benzylpenicillin (PEN), benzylpenicillin screening test (PEN-S), biapenem (BIA), carbenicillin (CRB), carindacillin (CRN), carumonam (CAR), cefacetrile (CAC), cefaclor (CEC), cefadroxil (CFR), cefalexin (LEX), cefaloridine (RID), cefalotin (CEP), cefamandole (MAN), cefapirin (HAP), cefatrizine (CTZ), cefazedone (CZD), cefazolin (CZO), cefcapene (CCP), cefcapene pivoxil (CCX), cefdinir (CDR), cefditoren (DIT), cefditoren pivoxil (DIX), cefepime (FEP), cefepime/amikacin (CFA), cefepime/clavulanic acid (CPC), cefepime/enmetazobactam (FPE), cefepime/nacubactam (FNC), cefepime/tazobactam (FPT), cefepime/zidebactam (FPZ), cefetamet (CAT), cefetamet pivoxil (CPI), cefetecol (CCL), cefetrizole (CZL), cefiderocol (FDC), cefixime (CFM), cefmenoxime (CMX), cefmetazole (CMZ), cefodizime (DIZ), cefonicid (CID), cefoperazone (CFP), cefoperazone/sulbactam (CSL), ceforanide (CND), cefoselis (CSE), cefotaxime (CTX), cefotaxime screening test (CTX-S), cefotaxime/clavulanic acid (CTC), cefotaxime/sulbactam (CTS), cefotetan (CTT), cefotiam (CTF), cefotiam hexetil (CHE), cefovecin (FOV), cefoxitin (FOX), cefoxitin screening test (FOX-S), cefozopran (ZOP), cefpimizole (CFZ), cefpiramide (CPM), cefpirome (CPO), cefpodoxime (CPD), cefpodoxime proxetil (CPX), cefpodoxime/clavulanic acid (CDC), cefprozil (CPR), cefquinome (CEQ), cefroxadine (CRD), cefsulodin (CFS), cefsumide (CSU), ceftaroline (CPT), ceftaroline/avibactam (CPA), ceftazidime (CAZ), ceftazidime/avibactam (CZA), ceftazidime/clavulanic acid (CCV), cefteram (CEM), cefteram pivoxil (CPL), ceftezole (CTL), ceftibuten (CTB), ceftiofur (TIO), ceftizoxime (CZX), ceftizoxime alapivoxil (CZP), ceftobiprole (BPR), ceftobiprole medocaril (CFM1), ceftolozane/tazobactam (CZT), ceftriaxone (CRO), ceftriaxone/beta-lactamase inhibitor (CEB), cefuroxime (CXM), cefuroxime axetil (CXA), cephradine (CED), ciclacillin (CIC), clometocillin (CLM), cloxacillin (CLO), dicloxacillin (DIC), doripenem (DOR), epicillin (EPC), ertapenem (ETP), flucloxacillin (FLC), hetacillin (HET), imipenem (IPM), imipenem/EDTA (IPE), imipenem/relebactam (IMR), latamoxef (LTM), lenampicillin (LEN), loracarbef (LOR), mecillinam (MEC), meropenem (MEM), meropenem/nacubactam (MNC), meropenem/vaborbactam (MEV), metampicillin (MTM), meticillin (MET), mezlocillin (MEZ), mezlocillin/sulbactam (MSU), nafcillin (NAF), oxacillin (OXA), oxacillin screening test (OXA-S), panipenem (PAN), penamecillin (PNM), penicillin/novobiocin (PNO), penicillin/sulbactam (PSU), pheneticillin (PHE), phenoxymethylpenicillin (PHN), piperacillin (PIP), piperacillin/sulbactam (PIS), piperacillin/tazobactam (TZP), piridicillin (PRC), pivampicillin (PVM), pivmecillinam (PME), procaine benzylpenicillin (PRB), propicillin (PRP), razupenem (RZM), ritipenem (RIT), ritipenem acoxil (RIA), sarmoxicillin (SRX), sulbenicillin (SBC), sultamicillin (SLT6), talampicillin (TAL), tebipenem (TBP), temocillin (TEM), ticarcillin (TIC), ticarcillin/clavulanic acid (TCC), and tigemonam (TMN)
 \item \code{\link[=betalactams_with_inhibitor]{betalactams_with_inhibitor()}} can select: \cr amoxicillin/clavulanic acid (AMC), amoxicillin/sulbactam (AXS), ampicillin/sulbactam (SAM), aztreonam/avibactam (AZA), aztreonam/nacubactam (ANC), cefepime/amikacin (CFA), cefepime/clavulanic acid (CPC), cefepime/enmetazobactam (FPE), cefepime/nacubactam (FNC), cefepime/tazobactam (FPT), cefepime/zidebactam (FPZ), cefoperazone/sulbactam (CSL), cefotaxime/clavulanic acid (CTC), cefotaxime/sulbactam (CTS), cefpodoxime/clavulanic acid (CDC), ceftaroline/avibactam (CPA), ceftazidime/avibactam (CZA), ceftazidime/clavulanic acid (CCV), ceftolozane/tazobactam (CZT), ceftriaxone/beta-lactamase inhibitor (CEB), imipenem/relebactam (IMR), meropenem/nacubactam (MNC), meropenem/vaborbactam (MEV), mezlocillin/sulbactam (MSU), penicillin/novobiocin (PNO), penicillin/sulbactam (PSU), piperacillin/sulbactam (PIS), piperacillin/tazobactam (TZP), and ticarcillin/clavulanic acid (TCC)
 \item \code{\link[=carbapenems]{carbapenems()}} can select: \cr biapenem (BIA), doripenem (DOR), ertapenem (ETP), imipenem (IPM), imipenem/EDTA (IPE), imipenem/relebactam (IMR), meropenem (MEM), meropenem/nacubactam (MNC), meropenem/vaborbactam (MEV), panipenem (PAN), razupenem (RZM), ritipenem (RIT), ritipenem acoxil (RIA), and tebipenem (TBP)

man/antimicrobials.Rd

@@ -5,9 +5,9 @@
 \alias{antimicrobials}
 \alias{antibiotics}
 \alias{antivirals}
-\title{Data Sets with 617 Antimicrobial Drugs}
+\title{Data Sets with 616 Antimicrobial Drugs}
 \format{
-\subsection{For the \link{antimicrobials} data set: a \link[tibble:tibble]{tibble} with 497 observations and 14 variables:}{
+\subsection{For the \link{antimicrobials} data set: a \link[tibble:tibble]{tibble} with 496 observations and 14 variables:}{
 \itemize{
 \item \code{ab}\cr antimicrobial ID as used in this package (such as \code{AMC}), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available. \emph{\strong{This is a unique identifier.}}
 \item \code{cid}\cr Compound ID as found in PubChem. \emph{\strong{This is a unique identifier.}}
@@ -50,7 +50,7 @@ LOINC:
 }
 }
 
-An object of class \code{deprecated_amr_dataset} (inherits from \code{tbl_df}, \code{tbl}, \code{data.frame}) with 497 rows and 14 columns.
+An object of class \code{deprecated_amr_dataset} (inherits from \code{tbl_df}, \code{tbl}, \code{data.frame}) with 496 rows and 14 columns.
 
 An object of class \code{tbl_df} (inherits from \code{tbl}, \code{data.frame}) with 120 rows and 11 columns.
 }

man/as.sir.Rd

@@ -75,7 +75,9 @@ sir_interpretation_history(clean = FALSE)
 \arguments{
 \item{x}{Vector of values (for class \code{\link{mic}}: MIC values in mg/L, for class \code{\link{disk}}: a disk diffusion radius in millimetres).}
 
-\item{...}{For using on a \link{data.frame}: names of columns to apply \code{\link[=as.sir]{as.sir()}} on (supports tidy selection such as \code{column1:column4}). Otherwise: arguments passed on to methods.}
+\item{...}{For using on a \link{data.frame}: selection of columns to apply \code{as.sir()} to. Supports \link[tidyselect:starts_with]{tidyselect language} such as \code{where(is.mic)}, \code{starts_with(...)}, or \code{column1:column4}, and can thus also be \link[=amr_selector]{antimicrobial selectors} such as \code{as.sir(df, penicillins())}.
+
+Otherwise: arguments passed on to methods.}
 
 \item{threshold}{Maximum fraction of invalid antimicrobial interpretations of \code{x}, see \emph{Examples}.}
 
@@ -314,9 +316,12 @@ if (require("dplyr")) {
   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

man/custom_eucast_rules.Rd

@@ -103,7 +103,7 @@ These 35 antimicrobial groups are allowed in the rules (case-insensitive) and ca
 \item aminoglycosides\cr(amikacin, amikacin/fosfomycin, apramycin, arbekacin, astromicin, bekanamycin, dibekacin, framycetin, gentamicin, gentamicin-high, habekacin, hygromycin, isepamicin, kanamycin, kanamycin-high, kanamycin/cephalexin, micronomicin, neomycin, netilmicin, pentisomicin, plazomicin, propikacin, ribostamycin, sisomicin, streptoduocin, streptomycin, streptomycin-high, tobramycin, and tobramycin-high)
 \item aminopenicillins\cr(amoxicillin and ampicillin)
 \item antifungals\cr(amorolfine, amphotericin B, amphotericin B-high, anidulafungin, butoconazole, caspofungin, ciclopirox, clotrimazole, econazole, fluconazole, flucytosine, fosfluconazole, griseofulvin, hachimycin, ibrexafungerp, isavuconazole, isoconazole, itraconazole, ketoconazole, manogepix, micafungin, miconazole, nystatin, oteseconazole, pimaricin, posaconazole, rezafungin, ribociclib, sulconazole, terbinafine, terconazole, and voriconazole)
-\item antimycobacterials\cr(4-aminosalicylic acid, calcium aminosalicylate, capreomycin, clofazimine, delamanid, enviomycin, ethambutol, ethambutol/isoniazid, ethionamide, isoniazid, isoniazid/sulfamethoxazole/trimethoprim/pyridoxine, morinamide, p-aminosalicylic acid, pretomanid, protionamide, pyrazinamide, rifabutin, rifampicin, rifampicin/ethambutol/isoniazid, rifampicin/isoniazid, rifampicin/pyrazinamide/ethambutol/isoniazid, rifampicin/pyrazinamide/isoniazid, rifamycin, rifapentine, simvastatin/fenofibrate, sodium aminosalicylate, streptomycin/isoniazid, terizidone, thioacetazone, thioacetazone/isoniazid, tiocarlide, and viomycin)
+\item antimycobacterials\cr(4-aminosalicylic acid, calcium aminosalicylate, capreomycin, clofazimine, delamanid, enviomycin, ethambutol, ethambutol/isoniazid, ethionamide, isoniazid, isoniazid/sulfamethoxazole/trimethoprim/pyridoxine, morinamide, p-aminosalicylic acid, pretomanid, protionamide, pyrazinamide, rifabutin, rifampicin, rifampicin/ethambutol/isoniazid, rifampicin/isoniazid, rifampicin/pyrazinamide/ethambutol/isoniazid, rifampicin/pyrazinamide/isoniazid, rifamycin, rifapentine, sodium aminosalicylate, streptomycin/isoniazid, terizidone, thioacetazone, thioacetazone/isoniazid, tiocarlide, and viomycin)
 \item betalactams\cr(amoxicillin, amoxicillin/clavulanic acid, amoxicillin/sulbactam, ampicillin, ampicillin/sulbactam, apalcillin, aspoxicillin, azidocillin, azlocillin, aztreonam, aztreonam/avibactam, aztreonam/nacubactam, bacampicillin, benzathine benzylpenicillin, benzathine phenoxymethylpenicillin, benzylpenicillin, benzylpenicillin screening test, biapenem, carbenicillin, carindacillin, carumonam, cefacetrile, cefaclor, cefadroxil, cefalexin, cefaloridine, cefalotin, cefamandole, cefapirin, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/amikacin, cefepime/clavulanic acid, cefepime/enmetazobactam, cefepime/nacubactam, cefepime/tazobactam, cefepime/zidebactam, cefetamet, cefetamet pivoxil, cefetecol, cefetrizole, cefiderocol, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime screening test, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening test, cefozopran, cefpimizole, cefpiramide, cefpirome, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefprozil, cefquinome, cefroxadine, cefsulodin, cefsumide, ceftaroline, ceftaroline/avibactam, ceftazidime, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftezole, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftobiprole, ceftobiprole medocaril, ceftolozane/tazobactam, ceftriaxone, ceftriaxone/beta-lactamase inhibitor, cefuroxime, cefuroxime axetil, cephradine, ciclacillin, clometocillin, cloxacillin, dicloxacillin, doripenem, epicillin, ertapenem, flucloxacillin, hetacillin, imipenem, imipenem/EDTA, imipenem/relebactam, latamoxef, lenampicillin, loracarbef, mecillinam, meropenem, meropenem/nacubactam, meropenem/vaborbactam, metampicillin, meticillin, mezlocillin, mezlocillin/sulbactam, nafcillin, oxacillin, oxacillin screening test, panipenem, penamecillin, penicillin/novobiocin, penicillin/sulbactam, pheneticillin, phenoxymethylpenicillin, piperacillin, piperacillin/sulbactam, piperacillin/tazobactam, piridicillin, pivampicillin, pivmecillinam, procaine benzylpenicillin, propicillin, razupenem, ritipenem, ritipenem acoxil, sarmoxicillin, sulbenicillin, sultamicillin, talampicillin, tebipenem, temocillin, ticarcillin, ticarcillin/clavulanic acid, and tigemonam)
 \item betalactams_with_inhibitor\cr(amoxicillin/clavulanic acid, amoxicillin/sulbactam, ampicillin/sulbactam, aztreonam/avibactam, aztreonam/nacubactam, cefepime/amikacin, cefepime/clavulanic acid, cefepime/enmetazobactam, cefepime/nacubactam, cefepime/tazobactam, cefepime/zidebactam, cefoperazone/sulbactam, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefpodoxime/clavulanic acid, ceftaroline/avibactam, ceftazidime/avibactam, ceftazidime/clavulanic acid, ceftolozane/tazobactam, ceftriaxone/beta-lactamase inhibitor, imipenem/relebactam, meropenem/nacubactam, meropenem/vaborbactam, mezlocillin/sulbactam, penicillin/novobiocin, penicillin/sulbactam, piperacillin/sulbactam, piperacillin/tazobactam, and ticarcillin/clavulanic acid)
 \item carbapenems\cr(biapenem, doripenem, ertapenem, imipenem, imipenem/EDTA, imipenem/relebactam, meropenem, meropenem/nacubactam, meropenem/vaborbactam, panipenem, razupenem, ritipenem, ritipenem acoxil, and tebipenem)

man/custom_mdro_guideline.Rd

@@ -99,7 +99,7 @@ All 35 antimicrobial selectors are supported for use in the rules:
 \item \code{\link[=aminoglycosides]{aminoglycosides()}} can select: \cr amikacin, amikacin/fosfomycin, apramycin, arbekacin, astromicin, bekanamycin, dibekacin, framycetin, gentamicin, gentamicin-high, habekacin, hygromycin, isepamicin, kanamycin, kanamycin-high, kanamycin/cephalexin, micronomicin, neomycin, netilmicin, pentisomicin, plazomicin, propikacin, ribostamycin, sisomicin, streptoduocin, streptomycin, streptomycin-high, tobramycin, and tobramycin-high
 \item \code{\link[=aminopenicillins]{aminopenicillins()}} can select: \cr amoxicillin and ampicillin
 \item \code{\link[=antifungals]{antifungals()}} can select: \cr amorolfine, amphotericin B, amphotericin B-high, anidulafungin, butoconazole, caspofungin, ciclopirox, clotrimazole, econazole, fluconazole, flucytosine, fosfluconazole, griseofulvin, hachimycin, ibrexafungerp, isavuconazole, isoconazole, itraconazole, ketoconazole, manogepix, micafungin, miconazole, nystatin, oteseconazole, pimaricin, posaconazole, rezafungin, ribociclib, sulconazole, terbinafine, terconazole, and voriconazole
-\item \code{\link[=antimycobacterials]{antimycobacterials()}} can select: \cr 4-aminosalicylic acid, calcium aminosalicylate, capreomycin, clofazimine, delamanid, enviomycin, ethambutol, ethambutol/isoniazid, ethionamide, isoniazid, isoniazid/sulfamethoxazole/trimethoprim/pyridoxine, morinamide, p-aminosalicylic acid, pretomanid, protionamide, pyrazinamide, rifabutin, rifampicin, rifampicin/ethambutol/isoniazid, rifampicin/isoniazid, rifampicin/pyrazinamide/ethambutol/isoniazid, rifampicin/pyrazinamide/isoniazid, rifamycin, rifapentine, simvastatin/fenofibrate, sodium aminosalicylate, streptomycin/isoniazid, terizidone, thioacetazone, thioacetazone/isoniazid, tiocarlide, and viomycin
+\item \code{\link[=antimycobacterials]{antimycobacterials()}} can select: \cr 4-aminosalicylic acid, calcium aminosalicylate, capreomycin, clofazimine, delamanid, enviomycin, ethambutol, ethambutol/isoniazid, ethionamide, isoniazid, isoniazid/sulfamethoxazole/trimethoprim/pyridoxine, morinamide, p-aminosalicylic acid, pretomanid, protionamide, pyrazinamide, rifabutin, rifampicin, rifampicin/ethambutol/isoniazid, rifampicin/isoniazid, rifampicin/pyrazinamide/ethambutol/isoniazid, rifampicin/pyrazinamide/isoniazid, rifamycin, rifapentine, sodium aminosalicylate, streptomycin/isoniazid, terizidone, thioacetazone, thioacetazone/isoniazid, tiocarlide, and viomycin
 \item \code{\link[=betalactams]{betalactams()}} can select: \cr amoxicillin, amoxicillin/clavulanic acid, amoxicillin/sulbactam, ampicillin, ampicillin/sulbactam, apalcillin, aspoxicillin, azidocillin, azlocillin, aztreonam, aztreonam/avibactam, aztreonam/nacubactam, bacampicillin, benzathine benzylpenicillin, benzathine phenoxymethylpenicillin, benzylpenicillin, benzylpenicillin screening test, biapenem, carbenicillin, carindacillin, carumonam, cefacetrile, cefaclor, cefadroxil, cefalexin, cefaloridine, cefalotin, cefamandole, cefapirin, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/amikacin, cefepime/clavulanic acid, cefepime/enmetazobactam, cefepime/nacubactam, cefepime/tazobactam, cefepime/zidebactam, cefetamet, cefetamet pivoxil, cefetecol, cefetrizole, cefiderocol, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime screening test, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening test, cefozopran, cefpimizole, cefpiramide, cefpirome, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefprozil, cefquinome, cefroxadine, cefsulodin, cefsumide, ceftaroline, ceftaroline/avibactam, ceftazidime, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftezole, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftobiprole, ceftobiprole medocaril, ceftolozane/tazobactam, ceftriaxone, ceftriaxone/beta-lactamase inhibitor, cefuroxime, cefuroxime axetil, cephradine, ciclacillin, clometocillin, cloxacillin, dicloxacillin, doripenem, epicillin, ertapenem, flucloxacillin, hetacillin, imipenem, imipenem/EDTA, imipenem/relebactam, latamoxef, lenampicillin, loracarbef, mecillinam, meropenem, meropenem/nacubactam, meropenem/vaborbactam, metampicillin, meticillin, mezlocillin, mezlocillin/sulbactam, nafcillin, oxacillin, oxacillin screening test, panipenem, penamecillin, penicillin/novobiocin, penicillin/sulbactam, pheneticillin, phenoxymethylpenicillin, piperacillin, piperacillin/sulbactam, piperacillin/tazobactam, piridicillin, pivampicillin, pivmecillinam, procaine benzylpenicillin, propicillin, razupenem, ritipenem, ritipenem acoxil, sarmoxicillin, sulbenicillin, sultamicillin, talampicillin, tebipenem, temocillin, ticarcillin, ticarcillin/clavulanic acid, and tigemonam
 \item \code{\link[=betalactams_with_inhibitor]{betalactams_with_inhibitor()}} can select: \cr amoxicillin/clavulanic acid, amoxicillin/sulbactam, ampicillin/sulbactam, aztreonam/avibactam, aztreonam/nacubactam, cefepime/amikacin, cefepime/clavulanic acid, cefepime/enmetazobactam, cefepime/nacubactam, cefepime/tazobactam, cefepime/zidebactam, cefoperazone/sulbactam, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefpodoxime/clavulanic acid, ceftaroline/avibactam, ceftazidime/avibactam, ceftazidime/clavulanic acid, ceftolozane/tazobactam, ceftriaxone/beta-lactamase inhibitor, imipenem/relebactam, meropenem/nacubactam, meropenem/vaborbactam, mezlocillin/sulbactam, penicillin/novobiocin, penicillin/sulbactam, piperacillin/sulbactam, piperacillin/tazobactam, and ticarcillin/clavulanic acid
 \item \code{\link[=carbapenems]{carbapenems()}} can select: \cr biapenem, doripenem, ertapenem, imipenem, imipenem/EDTA, imipenem/relebactam, meropenem, meropenem/nacubactam, meropenem/vaborbactam, panipenem, razupenem, ritipenem, ritipenem acoxil, and tebipenem

man/ggplot_sir.Rd

@@ -9,10 +9,10 @@ ggplot_sir(data, position = NULL, x = "antibiotic",
   fill = "interpretation", facet = NULL, breaks = seq(0, 1, 0.1),
   limits = NULL, translate_ab = "name", combine_SI = TRUE,
   minimum = 30, language = get_AMR_locale(), nrow = NULL, colours = c(S
-  = "#3CAEA3", SI = "#3CAEA3", I = "#F6D55C", IR = "#ED553B", R = "#ED553B"),
-  datalabels = TRUE, datalabels.size = 2.5, datalabels.colour = "grey15",
-  title = NULL, subtitle = NULL, caption = NULL,
-  x.title = "Antimicrobial", y.title = "Proportion", ...)
+  = "#3CAEA3", SDD = "#8FD6C4", SI = "#3CAEA3", I = "#F6D55C", IR = "#ED553B",
+  R = "#ED553B"), datalabels = TRUE, datalabels.size = 2.5,
+  datalabels.colour = "grey15", title = NULL, subtitle = NULL,
+  caption = NULL, x.title = "Antimicrobial", y.title = "Proportion", ...)
 
 geom_sir(position = NULL, x = c("antibiotic", "interpretation"),
   fill = "interpretation", translate_ab = "name", minimum = 30,

man/mdro.Rd

@@ -57,7 +57,7 @@ eucast_exceptional_phenotypes(x = NULL, only_sir_columns = any(is.sir(x)),
 
 \item{combine_SI}{A \link{logical} to indicate whether all values of S and I must be merged into one, so resistance is only considered when isolates are R, not I. As this is the default behaviour of the \code{\link[=mdro]{mdro()}} function, it follows the redefinition by EUCAST about the interpretation of I (increased exposure) in 2019, see section 'Interpretation of S, I and R' below. When using \code{combine_SI = FALSE}, resistance is considered when isolates are R or I.}
 
-\item{verbose}{A \link{logical} to turn Verbose mode on and off (default is off). In Verbose mode, the function does not return the MDRO results, but instead returns a data set in logbook form with extensive info about which isolates would be MDRO-positive, or why they are not.}
+\item{verbose}{A \link{logical} to turn Verbose mode on and off (default is off). In Verbose mode, the function returns a data set with the MDRO results in logbook form with extensive info about which isolates would be MDRO-positive, or why they are not.}
 
 \item{only_sir_columns}{A \link{logical} to indicate whether only antimicrobial columns must be included that were transformed to class \link[=as.sir]{sir} on beforehand. Defaults to \code{FALSE} if no columns of \code{x} have a class \link[=as.sir]{sir}.}
 

man/mean_amr_distance.Rd

@@ -18,7 +18,7 @@ amr_distance_from_row(amr_distance, row)
 \arguments{
 \item{x}{A vector of class \link[=as.sir]{sir}, \link[=as.mic]{mic} or \link[=as.disk]{disk}, or a \link{data.frame} containing columns of any of these classes.}
 
-\item{...}{Variables to select. Supports \link[tidyselect:language]{tidyselect language} (such as \code{column1:column4} and \code{where(is.mic)}), and can thus also be \link[=amr_selector]{antimicrobial selectors}.}
+\item{...}{Variables to select. Supports \link[tidyselect:starts_with]{tidyselect language} such as \code{where(is.mic)}, \code{starts_with(...)}, or \code{column1:column4}, and can thus also be \link[=amr_selector]{antimicrobial selectors}.}
 
 \item{combine_SI}{A \link{logical} to indicate whether all values of S, SDD, and I must be merged into one, so the input only consists of S+I vs. R (susceptible vs. resistant) - the default is \code{TRUE}.}
 

man/plot.Rd

@@ -33,25 +33,25 @@ scale_colour_mic(keep_operators = "edges", mic_range = NULL, ...)
 
 scale_fill_mic(keep_operators = "edges", mic_range = NULL, ...)
 
-scale_x_sir(colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
-  language = get_AMR_locale(), eucast_I = getOption("AMR_guideline",
-  "EUCAST") == "EUCAST", ...)
+scale_x_sir(colours_SIR = c(S = "#3CAEA3", SDD = "#8FD6C4", I = "#F6D55C", R
+  = "#ED553B"), language = get_AMR_locale(),
+  eucast_I = getOption("AMR_guideline", "EUCAST") == "EUCAST", ...)
 
-scale_colour_sir(colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
-  language = get_AMR_locale(), eucast_I = getOption("AMR_guideline",
-  "EUCAST") == "EUCAST", ...)
+scale_colour_sir(colours_SIR = c(S = "#3CAEA3", SDD = "#8FD6C4", I =
+  "#F6D55C", R = "#ED553B"), language = get_AMR_locale(),
+  eucast_I = getOption("AMR_guideline", "EUCAST") == "EUCAST", ...)
 
-scale_fill_sir(colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
-  language = get_AMR_locale(), eucast_I = getOption("AMR_guideline",
-  "EUCAST") == "EUCAST", ...)
+scale_fill_sir(colours_SIR = c(S = "#3CAEA3", SDD = "#8FD6C4", I = "#F6D55C",
+  R = "#ED553B"), language = get_AMR_locale(),
+  eucast_I = getOption("AMR_guideline", "EUCAST") == "EUCAST", ...)
 
 \method{plot}{mic}(x, mo = NULL, ab = NULL,
   guideline = getOption("AMR_guideline", "EUCAST"),
   main = deparse(substitute(x)), ylab = translate_AMR("Frequency", language
   = language),
   xlab = translate_AMR("Minimum Inhibitory Concentration (mg/L)", language =
-  language), colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
-  language = get_AMR_locale(), expand = TRUE,
+  language), colours_SIR = c(S = "#3CAEA3", SDD = "#8FD6C4", I = "#F6D55C", R
+  = "#ED553B"), language = get_AMR_locale(), expand = TRUE,
   include_PKPD = getOption("AMR_include_PKPD", TRUE),
   breakpoint_type = getOption("AMR_breakpoint_type", "human"), ...)
 
@@ -60,8 +60,8 @@ scale_fill_sir(colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
   title = deparse(substitute(object)), ylab = translate_AMR("Frequency",
   language = language),
   xlab = translate_AMR("Minimum Inhibitory Concentration (mg/L)", language =
-  language), colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
-  language = get_AMR_locale(), expand = TRUE,
+  language), colours_SIR = c(S = "#3CAEA3", SDD = "#8FD6C4", I = "#F6D55C", R
+  = "#ED553B"), language = get_AMR_locale(), expand = TRUE,
   include_PKPD = getOption("AMR_include_PKPD", TRUE),
   breakpoint_type = getOption("AMR_breakpoint_type", "human"), ...)
 
@@ -69,8 +69,8 @@ scale_fill_sir(colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
   ylab = translate_AMR("Frequency", language = language),
   xlab = translate_AMR("Disk diffusion diameter (mm)", language = language),
   mo = NULL, ab = NULL, guideline = getOption("AMR_guideline", "EUCAST"),
-  colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
-  language = get_AMR_locale(), expand = TRUE,
+  colours_SIR = c(S = "#3CAEA3", SDD = "#8FD6C4", I = "#F6D55C", R =
+  "#ED553B"), language = get_AMR_locale(), expand = TRUE,
   include_PKPD = getOption("AMR_include_PKPD", TRUE),
   breakpoint_type = getOption("AMR_breakpoint_type", "human"), ...)
 
@@ -78,8 +78,8 @@ scale_fill_sir(colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
   title = deparse(substitute(object)), ylab = translate_AMR("Frequency",
   language = language), xlab = translate_AMR("Disk diffusion diameter (mm)",
   language = language), guideline = getOption("AMR_guideline", "EUCAST"),
-  colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
-  language = get_AMR_locale(), expand = TRUE,
+  colours_SIR = c(S = "#3CAEA3", SDD = "#8FD6C4", I = "#F6D55C", R =
+  "#ED553B"), language = get_AMR_locale(), expand = TRUE,
   include_PKPD = getOption("AMR_include_PKPD", TRUE),
   breakpoint_type = getOption("AMR_breakpoint_type", "human"), ...)
 
@@ -90,8 +90,8 @@ scale_fill_sir(colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
 
 \method{autoplot}{sir}(object, title = deparse(substitute(object)),
   xlab = translate_AMR("Antimicrobial Interpretation", language = language),
-  ylab = translate_AMR("Frequency", language = language),
-  colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
+  ylab = translate_AMR("Frequency", language = language), colours_SIR = c(S
+  = "#3CAEA3", SDD = "#8FD6C4", I = "#F6D55C", R = "#ED553B"),
   language = get_AMR_locale(), ...)
 
 facet_sir(facet = c("interpretation", "antibiotic"), nrow = NULL)
@@ -99,8 +99,8 @@ facet_sir(facet = c("interpretation", "antibiotic"), nrow = NULL)
 scale_y_percent(breaks = function(x) seq(0, max(x, na.rm = TRUE), 0.1),
   limits = c(0, NA))
 
-scale_sir_colours(..., aesthetics, colours_SIR = c("#3CAEA3", "#F6D55C",
-  "#ED553B"))
+scale_sir_colours(..., aesthetics, colours_SIR = c(S = "#3CAEA3", SDD =
+  "#8FD6C4", I = "#F6D55C", R = "#ED553B"))
 
 theme_sir()
 
@@ -210,6 +210,10 @@ if (require("ggplot2")) {
   # when providing the microorganism and antibiotic, colours will show interpretations:
   autoplot(some_mic_values, mo = "Escherichia coli", ab = "cipro")
 }
+if (require("ggplot2")) {
+  autoplot(some_mic_values, mo = "Staph aureus", ab = "Ceftaroline", guideline = "CLSI")
+}
+
 if (require("ggplot2")) {
   # support for 27 languages, various guidelines, and many options
   autoplot(some_disk_values,
@@ -267,7 +271,7 @@ if (require("ggplot2")) {
     aes(group, mic)
   ) +
     geom_boxplot() +
-    geom_violin(linetype = 2, colour = "grey", fill = NA) +
+    geom_violin(linetype = 2, colour = "grey30", fill = NA) +
     scale_y_mic()
 }
 if (require("ggplot2")) {
@@ -279,7 +283,7 @@ if (require("ggplot2")) {
     aes(group, mic)
   ) +
     geom_boxplot() +
-    geom_violin(linetype = 2, colour = "grey", fill = NA) +
+    geom_violin(linetype = 2, colour = "grey30", fill = NA) +
     scale_y_mic(mic_range = c(NA, 0.25))
 }
 
@@ -312,7 +316,7 @@ if (require("ggplot2")) {
     aes(x = group, y = mic, colour = sir)
   ) +
     theme_minimal() +
-    geom_boxplot(fill = NA, colour = "grey") +
+    geom_boxplot(fill = NA, colour = "grey30") +
     geom_jitter(width = 0.25)
 
   plain

pkgdown/extra.css

@@ -190,6 +190,15 @@ this shows on top of every sidebar to the right
   }
 }
 
+.template-reference-topic h3,
+.template-reference-topic h3 code {
+  color: var(--amr-green-dark) !important;
+}
+.template-reference-topic h3 {
+  font-weight: normal;
+  margin-top: 2rem;
+}
+
 /* replace 'Developers' with 'Maintainers' */
 .developers h2 {
   display: none;

tests/testthat/test-zzz.R

@@ -63,10 +63,12 @@ test_that("test-zzz.R", {
     "progress_bar" = "progress",
     "read_html" = "xml2",
     "right_join" = "dplyr",
+    "select" = "dplyr",
     "semi_join" = "dplyr",
     "showQuestion" = "rstudioapi",
     "symbol" = "cli",
     "tibble" = "tibble",
+    "where" = "tidyselect",
     "write.xlsx" = "openxlsx"
   )