(v1.6.0.9009) key_antibiotics update

.Rbuildignore

@@ -1,3 +1,4 @@
+^.*\.RData$
 ^.*\.Rproj$
 ^\.Renviron$
 ^\.Rprofile$

.github/workflows/check.yaml

@@ -65,10 +65,10 @@ jobs:
           - {os: ubuntu-20.04,   r: '3.6',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
           - {os: ubuntu-20.04,   r: '3.5',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
           - {os: ubuntu-20.04,   r: '3.4',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
-          - {os: ubuntu-20.04,   r: '3.3',     allowfail: true,  rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
+          - {os: ubuntu-20.04,   r: '3.3',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
           # - {os: ubuntu-20.04,   r: '3.2',     allowfail: true,  rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
           # - {os: ubuntu-20.04,   r: '3.1',     allowfail: true,  rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
-          - {os: ubuntu-20.04,   r: '3.0',     allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
+          - {os: ubuntu-20.04,   r: '3.0',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
           
           - {os: ubuntu-16.04,   r: 'devel',   allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
           - {os: ubuntu-16.04,   r: 'release', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
@@ -77,10 +77,10 @@ jobs:
           - {os: ubuntu-16.04,   r: '3.6',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
           - {os: ubuntu-16.04,   r: '3.5',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
           - {os: ubuntu-16.04,   r: '3.4',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
-          - {os: ubuntu-16.04,   r: '3.3',     allowfail: true,  rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
+          - {os: ubuntu-16.04,   r: '3.3',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
           # - {os: ubuntu-16.04,   r: '3.2',     allowfail: true,  rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
           # - {os: ubuntu-16.04,   r: '3.1',     allowfail: true,  rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
-          - {os: ubuntu-16.04,   r: '3.0',     allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
+          - {os: ubuntu-16.04,   r: '3.0',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
           
     env:
       R_REMOTES_NO_ERRORS_FROM_WARNINGS: true
@@ -151,6 +151,8 @@ jobs:
         if: matrix.config.r != '3.0' && matrix.config.r != '3.1' && matrix.config.r != '3.2'
         env:
           _R_CHECK_CRAN_INCOMING_: false
+          _R_CHECK_LENGTH_1_CONDITION_: verbose
+          _R_CHECK_LENGTH_1_LOGIC2_: verbose
         run: rcmdcheck::rcmdcheck(args = c("--no-manual", "--as-cran"), error_on = "warning", check_dir = "check")
         shell: Rscript {0}
         
@@ -159,10 +161,12 @@ jobs:
         env:
           _R_CHECK_CRAN_INCOMING_: false
           _R_CHECK_FORCE_SUGGESTS_: false
+          _R_CHECK_DEPENDS_ONLY_: true
           _R_CHECK_LENGTH_1_CONDITION_: verbose
           _R_CHECK_LENGTH_1_LOGIC2_: verbose
         run: |
-          R CMD check data-raw/AMR_latest.tar.gz --no-manual --no-build-vignettes
+          tar -xvf data-raw/AMR_latest.tar.gz
+          R CMD check AMR --no-manual --no-build-vignettes
 
       - name: Show testthat output
         if: always()

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: AMR
-Version: 1.6.0
-Date: 2021-03-14
+Version: 1.6.0.9009
+Date: 2021-04-23
 Title: Antimicrobial Resistance Data Analysis
 Authors@R: c(
     person(role = c("aut", "cre"), 
@@ -35,11 +35,10 @@ Authors@R: c(
            family = "Souverein", given = "Dennis", email = "d.souvereing@streeklabhaarlem.nl"),
     person(role = "ctb",
            family = "Underwood", given = "Anthony", email = "au3@sanger.ac.uk"))
-Description: Functions to simplify the analysis and prediction of Antimicrobial 
-    Resistance (AMR) and to work with microbial and antimicrobial properties by
-    using evidence-based methods, like those defined by Leclercq et al. (2013) 
-    <doi:10.1111/j.1469-0691.2011.03703.x> and containing reference data such as 
-    LPSN <doi:10.1099/ijsem.0.004332>.
+Description: Functions to simplify and standardise antimicrobial resistance (AMR)
+    data analysis and to work with microbial and antimicrobial properties by
+    using evidence-based methods and reliable reference data such as LPSN
+    <doi:10.1099/ijsem.0.004332>.
 Depends:
     R (>= 3.0.0)
 Suggests:

NAMESPACE

@@ -43,6 +43,8 @@ S3method(as.data.frame,ab)
 S3method(as.data.frame,mo)
 S3method(as.double,mic)
 S3method(as.integer,mic)
+S3method(as.list,custom_eucast_rules)
+S3method(as.list,custom_mdro_guideline)
 S3method(as.matrix,mic)
 S3method(as.numeric,mic)
 S3method(as.rsi,data.frame)
@@ -57,6 +59,8 @@ S3method(barplot,disk)
 S3method(barplot,mic)
 S3method(barplot,rsi)
 S3method(c,ab)
+S3method(c,custom_eucast_rules)
+S3method(c,custom_mdro_guideline)
 S3method(c,disk)
 S3method(c,mic)
 S3method(c,mo)
@@ -97,6 +101,7 @@ S3method(plot,rsi)
 S3method(print,ab)
 S3method(print,bug_drug_combinations)
 S3method(print,catalogue_of_life_version)
+S3method(print,custom_eucast_rules)
 S3method(print,custom_mdro_guideline)
 S3method(print,disk)
 S3method(print,mic)
@@ -137,6 +142,8 @@ S3method(unique,mo)
 S3method(unique,rsi)
 export("%like%")
 export("%like_case%")
+export("%unlike%")
+export("%unlike_case%")
 export(ab_atc)
 export(ab_atc_group1)
 export(ab_atc_group2)
@@ -184,6 +191,7 @@ export(count_all)
 export(count_df)
 export(count_resistant)
 export(count_susceptible)
+export(custom_eucast_rules)
 export(custom_mdro_guideline)
 export(eucast_dosage)
 export(eucast_exceptional_phenotypes)

NEWS.md

@@ -1,5 +1,36 @@
-# AMR 1.6.0
+# AMR 1.6.0.9009
+## <small>Last updated: 23 April 2021</small>
 
+### New
+* Function `custom_eucast_rules()` that brings support for custom AMR rules in `eucast_rules()`
+
+### Changed
+* Custom MDRO guidelines (`mdro()`, `custom_mdro_guideline()`):
+  * Custom MDRO guidelines can now be combined with other custom MDRO guidelines using `c()`
+  * Fix for applying the rules; in previous versions, rows were interpreted according to the last matched rule. Now, rows are interpreted according to the first matched rule
+* Fix for `age_groups()` for persons aged zero
+* The `example_isolates` data set now contains some (fictitious) zero-year old patients
+* Fix for minor translation errors
+* Printing of microbial codes in a `data.frame` or `tibble` now gives a warning if the data contains old microbial codes (from a previous AMR package version)
+* `first_isolate()` can now take a vector of values for `col_keyantibiotics` and can have an episode length of `Inf`
+* Extended the `like()` functions:
+  * Now checks if `pattern` is a *valid* regular expression
+  * Added `%unlike%` and `%unlike_case%` (as negations of the existing `%like%` and `%like_case%`). This greatly improves readability:
+    ```r
+    if (!grepl("EUCAST", guideline)) ...
+    # same:
+    if (guideline %unlike% "EUCAST") ...
+    ```
+  * Altered the RStudio addin, so it now iterates over `%like%` -> `%unlike%` -> `%like_case%` -> `%unlike_case%` if you keep pressing your keyboard shortcut
+* Fixed an installation error on R-3.0
+* Added `info` argument to `as.mo()` to turn on/off the progress bar
+* Fixed a bug that `col_mo` for some functions (esp. `eucast_rules()` and `mdro()`) could not be column names of the `microorganisms` data set as it would throw an error
+* Using `first_isolate()` with key antibiotics:
+  * Fixed a bug in the algorithm when using `type == "points"`, that now leads to inclusion of slightly more isolates
+  * Big speed improvement for `key_antibiotics_equal()` when using `type == "points"`
+
+
+# AMR 1.6.0
 
 ### New
 * Support for EUCAST Clinical Breakpoints v11.0 (2021), effective in the `eucast_rules()` function and in `as.rsi()` to interpret MIC and disk diffusion values. This is now the default guideline in this package.
@@ -59,7 +90,7 @@
   ```
 
 ### Changed
-* Updated the bacterial taxonomy to 3 March 2021 (using [LSPN](https://lpsn.dsmz.de))
+* Updated the bacterial taxonomy to 3 March 2021 (using [LPSN](https://lpsn.dsmz.de))
   * Added 3,372 new species and 1,523 existing species became synomyms
   * The URL of a bacterial species (`mo_url()`) will now lead to https://lpsn.dsmz.de
 * Big update for plotting classes `rsi`, `<mic>`, and `<disk>`:

R/aa_helper_functions.R

@@ -71,7 +71,49 @@ addin_insert_in <- function() {
 
 # No export, no Rd
 addin_insert_like <- function() {
-  import_fn("insertText", "rstudioapi")(" %like% ")
+  # we want Shift + Ctrl/Cmd + L to iterate over %like%, %unlike%, %like_case%, and %unlike_case%
+  
+  getActiveDocumentContext <- import_fn("getActiveDocumentContext", "rstudioapi")
+  insertText <- import_fn("insertText", "rstudioapi")
+  modifyRange <- import_fn("modifyRange", "rstudioapi")
+  document_range <- import_fn("document_range", "rstudioapi")
+  document_position <- import_fn("document_position", "rstudioapi")
+  
+  context <- getActiveDocumentContext()
+  current_row <- context$selection[[1]]$range$end[1]
+  current_col <- context$selection[[1]]$range$end[2]
+  current_row_txt <- context$contents[current_row]
+  if (is.null(current_row) || current_row_txt %unlike% "%(un)?like") {
+    insertText(" %like% ")
+    return(invisible())
+  }
+  
+  pos_preceded_by <- function(txt) {
+    if (tryCatch(substr(current_row_txt, current_col - nchar(trimws(txt, which = "right")), current_col) == trimws(txt, which = "right"),
+                 error = function(e) FALSE)) {
+      return(TRUE)
+    }
+    tryCatch(substr(current_row_txt, current_col - nchar(txt), current_col) %like% paste0("^", txt),
+             error = function(e) FALSE)
+  }
+  replace_pos <- function(old, with) {
+    modifyRange(document_range(document_position(current_row, current_col - nchar(old)),
+                               document_position(current_row, current_col)),
+                text = with,
+                id = context$id)
+  }
+  
+  if (pos_preceded_by(" %like% ")) {
+    replace_pos(" %like% ", with = " %unlike% ")
+  } else if (pos_preceded_by(" %unlike% ")) {
+    replace_pos(" %unlike% ", with = " %like_case% ")
+  } else if (pos_preceded_by(" %like_case% ")) {
+    replace_pos(" %like_case% ", with = " %unlike_case% ")
+  } else if (pos_preceded_by(" %unlike_case% ")) {
+    replace_pos(" %unlike_case% ", with = " %like% ")
+  } else {
+    insertText(" %like% ")
+  }
 }
 
 check_dataset_integrity <- function() {
@@ -211,10 +253,21 @@ search_type_in_df <- function(x, type, info = TRUE) {
   found
 }
 
-is_possibly_regex <- function(x) {
-  tryCatch(vapply(FUN.VALUE = character(1), strsplit(x, ""),
-                  function(y) any(y %in% c("$", "(", ")", "*", "+", "-", ".", "?", "[", "]", "^", "{", "|", "}", "\\"), na.rm = TRUE)),
-           error = function(e) rep(TRUE, length(x)))
+is_valid_regex <- function(x) {
+  regex_at_all <- tryCatch(vapply(FUN.VALUE = logical(1),
+                                  X = strsplit(x, ""),
+                                  FUN = function(y) any(y %in% c("$", "(", ")", "*", "+", "-",
+                                                                 ".", "?", "[", "]", "^", "{", 
+                                                                 "|", "}", "\\"),
+                                                        na.rm = TRUE),
+                                  USE.NAMES = FALSE),
+                           error = function(e) rep(TRUE, length(x)))
+  regex_valid <- vapply(FUN.VALUE = logical(1),
+                        X = x,
+                        FUN = function(y) !"try-error" %in% class(try(grepl(y, "", perl = TRUE),
+                                                                      silent = TRUE)),
+                        USE.NAMES = FALSE)
+  regex_at_all & regex_valid
 }
 
 stop_ifnot_installed <- function(package) {
@@ -223,8 +276,8 @@ stop_ifnot_installed <- function(package) {
   vapply(FUN.VALUE = character(1), package, function(pkg)
     tryCatch(get(".packageName", envir = asNamespace(pkg)),
              error = function(e) {
-               if (package == "rstudioapi") {
-                 stop("This function only works in RStudio.", call. = FALSE)
+               if (pkg == "rstudioapi") {
+                 stop("This function only works in RStudio when using R >= 3.2.", call. = FALSE)
                } else if (pkg != "base") {
                  stop("This requires the '", pkg, "' package.",
                       "\nTry to install it with: install.packages(\"", pkg, "\")",
@@ -504,8 +557,8 @@ format_class <- function(class, plural) {
   if ("matrix" %in% class) {
     class <- "a matrix"
   }
-  if ("isolate_identifier" %in% class) {
-    class <- "created with isolate_identifier()"
+  if ("custom_eucast_rules" %in% class) {
+    class <- "input created with `custom_eucast_rules()`"
   }
   if (any(c("mo", "ab", "rsi") %in% class)) {
     class <- paste0("of class <", class[1L], ">")
@@ -522,6 +575,7 @@ meet_criteria <- function(object,
                           looks_like = NULL,
                           is_in = NULL,
                           is_positive = NULL,
+                          is_positive_or_zero = NULL,
                           is_finite = NULL,
                           contains_column_class = NULL,
                           allow_NULL = FALSE,
@@ -590,16 +644,23 @@ meet_criteria <- function(object,
                ifelse(allow_NA == TRUE, ", or NA", ""),
                call = call_depth)
   }
-  if (!is.null(is_positive)) {
+  if (isTRUE(is_positive)) {
     stop_if(is.numeric(object) && !all(object > 0, na.rm = TRUE), "argument `", obj_name,
             "` must ",
             ifelse(!is.null(has_length) && length(has_length) == 1 && has_length == 1,
-                   "be a positive number",
-                   "all be positive numbers"),
-            " (higher than zero)",
+                   "be a number higher than zero",
+                   "all be numbers higher than zero"),
             call = call_depth)
   }
-  if (!is.null(is_finite)) {
+  if (isTRUE(is_positive_or_zero)) {
+    stop_if(is.numeric(object) && !all(object >= 0, na.rm = TRUE), "argument `", obj_name,
+            "` must ",
+            ifelse(!is.null(has_length) && length(has_length) == 1 && has_length == 1,
+                   "be zero or a positive number",
+                   "all be zero or numbers higher than zero"),
+            call = call_depth)
+  }
+  if (isTRUE(is_finite)) {
     stop_if(is.numeric(object) && !all(is.finite(object[!is.na(object)]), na.rm = TRUE), "argument `", obj_name,
             "` must ",
             ifelse(!is.null(has_length) && length(has_length) == 1 && has_length == 1,
@@ -633,7 +694,7 @@ get_current_data <- function(arg_name, call) {
       return(out)
     }
   }
-  
+
   if (as.double(R.Version()$major) + (as.double(R.Version()$minor) / 10) < 3.2) {
     # R-3.0 and R-3.1 do not have an `x` element in the call stack, rendering this function useless
     if (is.na(arg_name)) {
@@ -641,6 +702,7 @@ get_current_data <- function(arg_name, call) {
       warning_("this function can only be used in R >= 3.2", call = call)
       return(data.frame())
     } else {
+      # mimic a default R error, e.g. for example_isolates[which(mo_name() %like% "^ent"), ] 
       stop_("argument `", arg_name, "` is missing with no default", call = call)
     }
   }
@@ -650,12 +712,17 @@ get_current_data <- function(arg_name, call) {
   frms <- lapply(sys.frames(), function(el) {
     if (not_set == TRUE && ".Generic" %in% names(el)) {
       if (tryCatch(".data" %in% names(el) && is.data.frame(el$`.data`), error = function(e) FALSE)) {
-        # dplyr? - an element `.data` will be in the system call stack
-        # will be used in dplyr::select() (but not in dplyr::filter(), dplyr::mutate() or dplyr::summarise())
+        # - - - -
+        # dplyr
+        # - - - -
+        # an element `.data` will be in the system call stack when using dplyr::select()
+        # [but not when using dplyr::filter(), dplyr::mutate() or dplyr::summarise()]
         not_set <<- FALSE
         el$`.data`
       } else if (tryCatch(any(c("x", "xx") %in% names(el)), error = function(e) FALSE)) {
-        # otherwise try base R:
+        # - - - -
+        # base R
+        # - - - -
         # an element `x` will be in this environment for only cols, e.g. `example_isolates[, carbapenems()]`
         # an element `xx` will be in this environment for rows + cols, e.g. `example_isolates[c(1:3), carbapenems()]`
         if (tryCatch(is.data.frame(el$xx), error = function(e) FALSE)) {
@@ -675,6 +742,7 @@ get_current_data <- function(arg_name, call) {
     }
   })
   
+  # lookup the matched frame and return its value: a data.frame
   vars_df <- tryCatch(frms[[which(!vapply(FUN.VALUE = logical(1), frms, is.null))]], error = function(e) NULL)
   if (is.data.frame(vars_df)) {
     return(vars_df)
@@ -913,8 +981,8 @@ font_stripstyle <- function(x) {
   gsub("(?:(?:\\x{001b}\\[)|\\x{009b})(?:(?:[0-9]{1,3})?(?:(?:;[0-9]{0,3})*)?[A-M|f-m])|\\x{001b}[A-M]", "", x, perl = TRUE)
 }
 
-progress_ticker <- function(n = 1, n_min = 0, ...) {
-  if (!interactive() || n < n_min) {
+progress_ticker <- function(n = 1, n_min = 0, print = TRUE, ...) {
+  if (print == FALSE || n < n_min) {
     pb <- list()
     pb$tick <- function() {
       invisible()
@@ -1087,8 +1155,8 @@ time_track <- function(name = NULL) {
   paste("(until now:", trimws(round(as.numeric(Sys.time()) * 1000) - pkg_env$time_start), "ms)")
 }
 
-# prevent dependency on package 'backports'
-# these functions were not available in previous versions of R (last checked: R 4.0.3)
+# prevent dependency on package 'backports' ----
+# these functions were not available in previous versions of R (last checked: R 4.0.5)
 # see here for the full list: https://github.com/r-lib/backports
 strrep <- function(x, times) {
   x <- as.character(x)
@@ -1135,3 +1203,11 @@ isNamespaceLoaded <- function(pkg) {
 lengths <- function(x, use.names = TRUE) {
   vapply(x, length, FUN.VALUE = NA_integer_, USE.NAMES = use.names)
 }
+
+if (as.double(R.Version()$major) + (as.double(R.Version()$minor) / 10) < 3.1) {
+  # R-3.0 does not contain these functions, set them here to prevent installation failure
+  # (required for extension of the <mic> class)
+  cospi <- function(...) 1
+  sinpi <- function(...) 1
+  tanpi <- function(...) 1
+}

R/ab.R

@@ -29,7 +29,7 @@
 #' @inheritSection lifecycle Stable Lifecycle
 #' @param x character vector to determine to antibiotic ID
 #' @param flag_multiple_results logical to indicate whether a note should be printed to the console that probably more than one antibiotic code or name can be retrieved from a single input value.
-#' @param info logical to indicate whether a progress bar should be printed
+#' @param info a [logical] to indicate whether a progress bar should be printed, defaults to `TRUE` only in interactive mode
 #' @param ... arguments passed on to internal functions
 #' @rdname as.ab
 #' @inheritSection WHOCC WHOCC
@@ -90,7 +90,7 @@
 #'     rename_with(as.ab, where(is.rsi))
 #'    
 #' }
-as.ab <- function(x, flag_multiple_results = TRUE, info = TRUE, ...) {
+as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
   meet_criteria(x, allow_class = c("character", "numeric", "integer", "factor"), allow_NA = TRUE)
   meet_criteria(flag_multiple_results, allow_class = "logical", has_length = 1)
   meet_criteria(info, allow_class = "logical", has_length = 1)
@@ -155,7 +155,7 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = TRUE, ...) {
   }
   
   if (initial_search == TRUE) {
-    progress <- progress_ticker(n = length(x), n_min = ifelse(isTRUE(info), 25, length(x) + 1)) # start if n >= 25
+    progress <- progress_ticker(n = length(x), n_min = 25, print = info) # start if n >= 25
     on.exit(close(progress))
   }
   
@@ -389,7 +389,7 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = TRUE, ...) {
       
       # first 5 except for cephalosporins, then first 7 (those cephalosporins all start quite the same!)
       found <- suppressWarnings(as.ab(substr(x[i], 1, 5), initial_search = FALSE))
-      if (!is.na(found) && !ab_group(found, initial_search = FALSE) %like% "cephalosporins") {
+      if (!is.na(found) && ab_group(found, initial_search = FALSE) %unlike% "cephalosporins") {
         x_new[i] <- note_if_more_than_one_found(found, i, from_text)
         next
       }

R/ab_from_text.R

@@ -32,6 +32,7 @@
 #' @param collapse character to pass on to `paste(, collapse = ...)` to only return one character per element of `text`, see *Examples*
 #' @param translate_ab if `type = "drug"`: a column name of the [antibiotics] data set to translate the antibiotic abbreviations to, using [ab_property()]. Defaults to `FALSE`. Using `TRUE` is equal to using "name".
 #' @param thorough_search logical to indicate whether the input must be extensively searched for misspelling and other faulty input values. Setting this to `TRUE` will take considerably more time than when using `FALSE`. At default, it will turn `TRUE` when all input elements contain a maximum of three words.
+#' @param info logical to indicate whether a progress bar should be printed, defaults to `TRUE` only in interactive mode
 #' @param ... arguments passed on to [as.ab()]
 #' @details This function is also internally used by [as.ab()], although it then only searches for the first drug name and will throw a note if more drug names could have been returned. Note: the [as.ab()] function may use very long regular expression to match brand names of antimicrobial agents. This may fail on some systems.
 #' 
@@ -92,6 +93,7 @@ ab_from_text <- function(text,
                          collapse = NULL,
                          translate_ab = FALSE,
                          thorough_search = NULL,
+                         info = interactive(),
                          ...) {
   if (missing(type)) {
     type <- type[1L]
@@ -102,12 +104,13 @@ ab_from_text <- function(text,
   meet_criteria(collapse, has_length = 1, allow_NULL = TRUE)
   meet_criteria(translate_ab, allow_NULL = FALSE) # get_translate_ab() will be more informative about what's allowed
   meet_criteria(thorough_search, allow_class = "logical", has_length = 1, allow_NULL = TRUE)
+  meet_criteria(info, allow_class = "logical", has_length = 1)
 
   type <- tolower(trimws(type))
   
   text <- tolower(as.character(text))
   text_split_all <- strsplit(text, "[ ;.,:\\|]")
-  progress <- progress_ticker(n = length(text_split_all), n_min = 5)
+  progress <- progress_ticker(n = length(text_split_all), n_min = 5, print = info)
   on.exit(close(progress))
   
   if (type %like% "(drug|ab|anti)") {

R/age.R

@@ -149,8 +149,8 @@ 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) {
-  meet_criteria(x, allow_class = c("numeric", "integer"), is_positive = TRUE, is_finite = TRUE)
-  meet_criteria(split_at, allow_class = c("numeric", "integer", "character"), is_positive = TRUE, is_finite = TRUE)
+  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(na.rm, allow_class = "logical", has_length = 1) 
   
   if (any(x < 0, na.rm = TRUE)) {

R/custom_eucast_rules.R

@@ -0,0 +1,306 @@
+# ==================================================================== #
+# TITLE                                                                #
+# Antimicrobial Resistance (AMR) Data Analysis for R                   #
+#                                                                      #
+# SOURCE                                                               #
+# https://github.com/msberends/AMR                                     #
+#                                                                      #
+# LICENCE                                                              #
+# (c) 2018-2021 Berends MS, Luz CF et al.                              #
+# Developed at the University of Groningen, the Netherlands, in        #
+# collaboration with non-profit organisations Certe Medical            #
+# Diagnostics & Advice, and University Medical Center Groningen.       #
+#                                                                      #
+# This R package is free software; you can freely use and distribute   #
+# it for both personal and commercial purposes under the terms of the  #
+# GNU General Public License version 2.0 (GNU GPL-2), as published by  #
+# the Free Software Foundation.                                        #
+# We created this package for both routine data analysis and academic  #
+# research and it was publicly released in the hope that it will be    #
+# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY.              #
+#                                                                      #
+# Visit our website for the full manual and a complete tutorial about  #
+# how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
+# ==================================================================== #
+
+#' Define Custom EUCAST Rules
+#' 
+#' Define custom EUCAST rules for your organisation or specific analysis and use the output of this function in [eucast_rules()].
+#' @inheritSection lifecycle Maturing Lifecycle
+#' @param ... rules in formula notation, see *Examples*
+#' @details
+#' Some organisations have their own adoption of EUCAST rules. This function can be used to define custom EUCAST rules to be used in the [eucast_rules()] function.
+#' 
+#' @section How it works:
+#' 
+#' ### Basics
+#' 
+#' If you are familiar with the [`case_when()`][dplyr::case_when()] function of the `dplyr` package, you will recognise the input method to set your own rules. Rules must be set using what \R considers to be the 'formula notation'. The rule itself is written *before* the tilde (`~`) and the consequence of the rule is written *after* the tilde:
+#' 
+#' ```
+#' x <- custom_eucast_rules(TZP == "S" ~ aminopenicillins == "S",
+#'                          TZP == "R" ~ aminopenicillins == "R")
+#' ```
+#' 
+#' These are two custom EUCAST rules: if TZP (piperacillin/tazobactam) is "S", all aminopenicillins (ampicillin and amoxicillin) must be made "S", and if TZP is "R", aminopenicillins must be made "R". These rules can also be printed to the console, so it is immediately clear how they work:
+#' 
+#' ```
+#' x
+#' #> A set of custom EUCAST rules:
+#' #> 
+#' #>   1. If TZP is S then set to S:
+#' #>      amoxicillin (AMX), ampicillin (AMP)
+#' #> 
+#' #>   2. If TZP is R then set to R:
+#' #>      amoxicillin (AMX), ampicillin (AMP)
+#' ```
+#' 
+#' The rules (the part *before* the tilde, in above example `TZP == "S"` and `TZP == "R"`) must be evaluable in your data set: it should be able to run as a filter in your data set without errors. This means for the above example that the column `TZP` must exist. We will create a sample data set and test the rules set:
+#' 
+#' ```
+#' df <- data.frame(mo = c("E. coli", "K. pneumoniae"),
+#'                  TZP = "R",
+#'                  amox = "",
+#'                  AMP = "")
+#' df
+#' #>              mo TZP amox AMP
+#' #> 1       E. coli   R         
+#' #> 2 K. pneumoniae   R         
+#'                  
+#' eucast_rules(df, rules = "custom", custom_rules = x)
+#' #>              mo TZP amox AMP
+#' #> 1       E. coli   R    R   R     
+#' #> 2 K. pneumoniae   R    R   R  
+#' ```
+#' 
+#' ### Using taxonomic properties in rules
+#' 
+#' There is one exception in variables used for the rules: all column names of the [microorganisms] data set can also be used, but do not have to exist in the data set. These column names are: `r vector_and(colnames(microorganisms), quote = "``", sort = FALSE)`. Thus, this next example will work as well, despite the fact that the `df` data set does not contain a column `genus`:
+#' 
+#' ```
+#' y <- custom_eucast_rules(TZP == "S" & genus == "Klebsiella" ~ aminopenicillins == "S",
+#'                          TZP == "R" & genus == "Klebsiella" ~ aminopenicillins == "R")
+#'
+#' eucast_rules(df, rules = "custom", custom_rules = y)
+#' #>              mo TZP amox AMP
+#' #> 1       E. coli   R         
+#' #> 2 K. pneumoniae   R    R   R
+#' ```
+#' 
+#' ### Usage of antibiotic group names
+#' 
+#' It is possible to define antibiotic groups instead of single antibiotics for the rule consequence, the part *after* the tilde. In above examples, the antibiotic group `aminopenicillins` is used to include ampicillin and amoxicillin. The following groups are allowed (case-insensitive). Within parentheses are the antibiotic agents that will be matched when running the rule.
+#' 
+#' `r paste0("  * ", sapply(DEFINED_AB_GROUPS, function(x) paste0("``", tolower(x), "``\\cr(", paste0(sort(ab_name(eval(parse(text = x), envir = asNamespace("AMR")), language = NULL, tolower = TRUE)), collapse = ", "), ")"), USE.NAMES = FALSE), "\n", collapse = "")`
+#' @returns A [list] containing the custom rules
+#' @export
+#' @examples
+#' x <- custom_eucast_rules(AMC == "R" & genus == "Klebsiella" ~ aminopenicillins == "R",
+#'                          AMC == "I" & genus == "Klebsiella" ~ aminopenicillins == "I")
+#' eucast_rules(example_isolates,
+#'              rules = "custom",
+#'              custom_rules = x,
+#'              info = FALSE)
+#'              
+#' # combine rule sets
+#' x2 <- c(x,
+#'         custom_eucast_rules(TZP == "R" ~ carbapenems == "R"))
+#' x2
+custom_eucast_rules <- function(...) {
+
+  dots <- tryCatch(list(...),
+                   error = function(e) "error")
+  stop_if(identical(dots, "error"),
+          "rules must be a valid formula inputs (e.g., using '~'), see `?custom_eucast_rules`")
+  n_dots <- length(dots)
+  stop_if(n_dots == 0, "no custom rules were set. Please read the documentation using `?custom_eucast_rules`.")
+  out <- vector("list", n_dots)
+  for (i in seq_len(n_dots)) {
+    stop_ifnot(inherits(dots[[i]], "formula"), 
+               "rule ", i, " must be a valid formula input (e.g., using '~'), see `?custom_eucast_rules`")
+    
+    # Query
+    qry <- dots[[i]][[2]]
+    if (inherits(qry, "call")) {
+      qry <- as.expression(qry)
+    }
+    qry <- as.character(qry)
+    # these will prevent vectorisation, so replace them:
+    qry <- gsub("&&", "&", qry, fixed = TRUE)
+    qry <- gsub("||", "|", qry, fixed = TRUE)
+    # format nicely, setting spaces around operators
+    qry <- gsub(" *([&|+-/*^><==]+) *", " \\1 ", qry)
+    qry <- gsub(" ?, ?", ", ", qry)
+    qry <- gsub("'", "\"", qry, fixed = TRUE)
+    out[[i]]$query <- as.expression(qry)
+    
+    # Resulting rule
+    result <- dots[[i]][[3]]
+    stop_ifnot(deparse(result) %like% "==", 
+               "the result of rule ", i, " (the part after the `~`) must contain `==`, such as in `... ~ ampicillin == \"R\"`, see `?custom_eucast_rules`")
+    result_group <- as.character(result)[[2]]
+    if (paste0(toupper(result_group), "S") %in% DEFINED_AB_GROUPS) {
+      # support for e.g. 'aminopenicillin' if user meant 'aminopenicillins'
+      result_group <- paste0(result_group, "s")
+    }
+    if (toupper(result_group) %in% DEFINED_AB_GROUPS) {
+      result_group <- eval(parse(text = toupper(result_group)), envir = asNamespace("AMR"))
+    } else {
+      result_group <- tryCatch(
+        suppressWarnings(as.ab(result_group,
+                               fast_mode = TRUE,
+                               info = FALSE, 
+                               flag_multiple_results = FALSE)),
+        error = function(e) NA_character_)
+    }
+    
+    stop_if(any(is.na(result_group)),
+            "this result of rule ", i, " could not be translated to a single antimicrobial agent/group: \"", 
+            as.character(result)[[2]], "\".\n\nThe input can be a name or code of an antimicrobial agent, or be one of: ", 
+            vector_or(tolower(DEFINED_AB_GROUPS), quotes = FALSE), ".")
+    result_value <- as.character(result)[[3]]
+    result_value[result_value == "NA"] <- NA
+    stop_ifnot(result_value %in% c("R", "S", "I", NA),
+               "the resulting value of rule ", i, " must be either \"R\", \"S\", \"I\" or NA")
+    result_value <- as.rsi(result_value)
+    
+    out[[i]]$result_group <- result_group
+    out[[i]]$result_value <- result_value
+  }
+  
+  names(out) <- paste0("rule", seq_len(n_dots))
+  set_clean_class(out, new_class = c("custom_eucast_rules", "list"))
+}
+
+#' @method c custom_eucast_rules
+#' @noRd
+#' @export
+c.custom_eucast_rules <- function(x, ...) {
+  if (length(list(...)) == 0) {
+    return(x)
+  }
+  out <- unclass(x)
+  for (e in list(...)) {
+    out <- c(out, unclass(e))
+  }
+  names(out) <- paste0("rule", seq_len(length(out)))
+  set_clean_class(out, new_class = c("custom_eucast_rules", "list"))
+}
+
+#' @method as.list custom_eucast_rules
+#' @noRd
+#' @export
+as.list.custom_eucast_rules <- function(x, ...) {
+  c(x, ...)
+}
+
+#' @method print custom_eucast_rules
+#' @export
+#' @noRd
+print.custom_eucast_rules <- function(x, ...) {
+  cat("A set of custom EUCAST rules:\n")
+  for (i in seq_len(length(x))) {
+    rule <- x[[i]]
+    rule$query <- format_custom_query_rule(rule$query)
+    if (rule$result_value == "R") {
+      val <- font_rsi_R_bg(font_black(" R "))
+    } else if (rule$result_value == "S") {
+      val <- font_rsi_S_bg(font_black(" S "))
+    } else {
+      val <- font_rsi_I_bg(font_black(" I "))
+    }
+    agents <- paste0(font_blue(ab_name(rule$result_group, language = NULL, tolower = TRUE),
+                               collapse = NULL),
+                     " (", rule$result_group, ")")
+    agents <- sort(agents)
+    rule_if <- word_wrap(paste0(i, ". ", font_bold("If "), font_blue(rule$query), font_bold(" then "),
+                            "set to {result}:"),
+                     extra_indent = 5)
+    rule_if <- gsub("{result}", val, rule_if, fixed = TRUE)
+    rule_then <- paste0("     ", word_wrap(paste0(agents, collapse = ", "), extra_indent = 5))
+    cat("\n  ", rule_if, "\n", rule_then, "\n", sep = "")
+  }
+}
+
+run_custom_eucast_rules <- function(df, rule, info) {
+  n_dots <- length(rule)
+  stop_if(n_dots == 0, "no custom rules set", call = -2)
+  out <- character(length = NROW(df))
+  reasons <- character(length = NROW(df))
+  for (i in seq_len(n_dots)) {
+    qry <- tryCatch(eval(parse(text = rule[[i]]$query), envir = df, enclos = parent.frame()),
+                    error = function(e) { 
+                      pkg_env$err_msg <- e$message
+                      return("error")
+                    })
+    if (identical(qry, "error")) {
+      warning_("in custom_eucast_rules(): rule ", i, 
+               " (`", as.character(rule[[i]]$query), "`) was ignored because of this error message: ",
+               pkg_env$err_msg,
+               call = FALSE, 
+               add_fn = font_red)
+      next
+    }
+    stop_ifnot(is.logical(qry), "in custom_eucast_rules(): rule ", i, " (`", rule[[i]]$query, 
+               "`) must return `TRUE` or `FALSE`, not ", 
+               format_class(class(qry), plural = FALSE), call = FALSE)
+    
+    new_eucasts <- which(qry == TRUE & out == "")
+    
+    if (info == TRUE) {
+      cat(word_wrap("- Custom EUCAST rule ", i, ": `", as.character(rule[[i]]$query),
+                    "` (", length(new_eucasts),  " rows matched)"), "\n", sep = "")
+    }
+    val <- rule[[i]]$value
+    out[new_eucasts] <- val
+    reasons[new_eucasts] <- paste0("matched rule ", gsub("rule", "", names(rule)[i]), ": ", as.character(rule[[i]]$query))
+  }
+  out[out == ""] <- "Negative"
+  reasons[out == "Negative"] <- "no rules matched"
+  
+  if (isTRUE(attributes(rule)$as_factor)) {
+    out <- factor(out, levels = attributes(rule)$values, ordered = TRUE)
+  }
+  
+  columns_nonsusceptible <- as.data.frame(t(df[, is.rsi(df)] == "R"))
+  columns_nonsusceptible <- vapply(FUN.VALUE = character(1), 
+                                   columns_nonsusceptible, 
+                                   function(x) paste0(rownames(columns_nonsusceptible)[which(x)], collapse = " "))
+  columns_nonsusceptible[is.na(out)] <- NA_character_
+  
+  data.frame(row_number = seq_len(NROW(df)),
+             EUCAST = out,
+             reason = reasons,
+             columns_nonsusceptible = columns_nonsusceptible,
+             stringsAsFactors = FALSE)
+}
+
+format_custom_query_rule <- function(query, colours = has_colour()) {
+  query <- gsub(" & ", font_black(font_bold(" and ")), query, fixed = TRUE)
+  query <- gsub(" | ", font_black(" or "), query, fixed = TRUE)
+  query <- gsub(" + ", font_black(" plus "), query, fixed = TRUE)
+  query <- gsub(" - ", font_black(" minus "), query, fixed = TRUE)
+  query <- gsub(" / ", font_black(" divided by "), query, fixed = TRUE)
+  query <- gsub(" * ", font_black(" times "), query, fixed = TRUE)
+  query <- gsub(" == ", font_black(" is "), query, fixed = TRUE)
+  query <- gsub(" > ", font_black(" is higher than "), query, fixed = TRUE)
+  query <- gsub(" < ", font_black(" is lower than "), query, fixed = TRUE)
+  query <- gsub(" >= ", font_black(" is higher than or equal to "), query, fixed = TRUE)
+  query <- gsub(" <= ", font_black(" is lower than or equal to "), query, fixed = TRUE)
+  query <- gsub(" ^ ", font_black(" to the power of "), query, fixed = TRUE)
+  query <- gsub(" %in% ", font_black(" is one of "), query, fixed = TRUE)
+  query <- gsub(" %like% ", font_black(" resembles "), query, fixed = TRUE)
+  if (colours == TRUE) {
+    query <- gsub('"R"', font_rsi_R_bg(font_black(" R ")), query, fixed = TRUE)
+    query <- gsub('"S"', font_rsi_S_bg(font_black(" S ")), query, fixed = TRUE)
+    query <- gsub('"I"', font_rsi_I_bg(font_black(" I ")), query, fixed = TRUE)
+  }
+  # replace the black colour 'stops' with blue colour 'starts'
+  query <- gsub("\033[39m", "\033[34m", as.character(query), fixed = TRUE)
+  # start with blue
+  query <- paste0("\033[34m", query)
+  if (colours == FALSE) {
+    query <- font_stripstyle(query)
+  }
+  query
+}

R/data.R

@@ -98,7 +98,7 @@
 #' @details 
 #' Please note that entries are only based on the Catalogue of Life and the LPSN (see below). Since these sources incorporate entries based on (recent) publications in the International Journal of Systematic and Evolutionary Microbiology (IJSEM), it can happen that the year of publication is sometimes later than one might expect.
 #' 
-#' For example, *Staphylococcus pettenkoferi* was described for the first time in Diagnostic Microbiology and Infectious Disease in 2002 (\doi{10.1016/s0732-8893(02)00399-1}), but it was not before 2007 that a publication in IJSEM followed (\doi{10.1099/ijs.0.64381-0}). Consequently, the AMR package returns 2007 for `mo_year("S. pettenkoferi")`.
+#' For example, *Staphylococcus pettenkoferi* was described for the first time in Diagnostic Microbiology and Infectious Disease in 2002 (\doi{10.1016/s0732-8893(02)00399-1}), but it was not before 2007 that a publication in IJSEM followed (\doi{10.1099/ijs.0.64381-0}). Consequently, the `AMR` package returns 2007 for `mo_year("S. pettenkoferi")`.
 #' 
 #' ## Manual additions
 #' For convenience, some entries were added manually:

R/episode.R

@@ -28,7 +28,7 @@
 #' These functions determine which items in a vector can be considered (the start of) a new episode, based on the argument `episode_days`. This can be used to determine clinical episodes for any epidemiological analysis. The [get_episode()] function returns the index number of the episode per group, while the [is_new_episode()] function returns values `TRUE`/`FALSE` to indicate whether an item in a vector is the start of a new episode.
 #' @inheritSection lifecycle Stable Lifecycle
 #' @param x vector of dates (class `Date` or `POSIXt`)
-#' @param episode_days required episode length in days, can also be less than a day, see *Details*
+#' @param episode_days required episode length in days, can also be less than a day or `Inf`, see *Details*
 #' @param ... currently not used
 #' @details 
 #' Dates are first sorted from old to new. The oldest date will mark the start of the first episode. After this date, the next date will be marked that is at least `episode_days` days later than the start of the first episode. From that second marked date on, the next date will be marked that is at least `episode_days` days later than the start of the second episode which will be the start of the third episode, and so on. Before the vector is being returned, the original order will be restored.
@@ -88,7 +88,7 @@
 #'   # grouping on patients and microorganisms leads to the same results
 #'   # as first_isolate():
 #'   x <- example_isolates %>%
-#'     filter(first_isolate(., include_unknown = TRUE))
+#'     filter_first_isolate(include_unknown = TRUE)
 #'     
 #'   y <- example_isolates %>%
 #'     group_by(patient_id, mo) %>%
@@ -105,7 +105,7 @@
 #' }
 get_episode <- function(x, episode_days, ...) {
   meet_criteria(x, allow_class = c("Date", "POSIXt"))
-  meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
+  meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = FALSE)
   
   exec_episode(type = "sequential",
                x = x, 
@@ -117,7 +117,7 @@ get_episode <- function(x, episode_days, ...) {
 #' @export
 is_new_episode <- function(x, episode_days, ...) {
   meet_criteria(x, allow_class = c("Date", "POSIXt"))
-  meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
+  meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = FALSE)
   
   exec_episode(type = "logical",
                x = x, 

R/eucast_rules.R

@@ -51,7 +51,7 @@ format_eucast_version_nr <- function(version, markdown = TRUE) {
 #' @inheritSection lifecycle Stable Lifecycle
 #' @param x data with antibiotic columns, such as `amox`, `AMX` and `AMC`
 #' @param info a logical to indicate whether progress should be printed to the console, defaults to only print while in interactive sessions
-#' @param rules a character vector that specifies which rules should be applied. Must be one or more of `"breakpoints"`, `"expert"`, `"other"`, `"all"`, and defaults to `c("breakpoints", "expert")`. The default value can be set to another value, e.g. using `options(AMR_eucastrules = "all")`.
+#' @param rules a character vector that specifies which rules should be applied. Must be one or more of `"breakpoints"`, `"expert"`, `"other"`, `"custom"`, `"all"`, and defaults to `c("breakpoints", "expert")`. The default value can be set to another value, e.g. using `options(AMR_eucastrules = "all")`. If using `"custom"`, be sure to fill in argument `custom_rules` too. Custom rules can be created with [custom_eucast_rules()].
 #' @param verbose a [logical] to turn Verbose mode on and off (default is off). In Verbose mode, the function does not apply rules to the data, but instead returns a data set in logbook form with extensive info about which rows and columns would be effected and in which way. Using Verbose mode takes a lot more time.
 #' @param version_breakpoints the version number to use for the EUCAST Clinical Breakpoints guideline. Can be either `r vector_or(names(EUCAST_VERSION_BREAKPOINTS), reverse = TRUE)`.
 #' @param version_expertrules the version number to use for the EUCAST Expert Rules and Intrinsic Resistance guideline. Can be either `r vector_or(names(EUCAST_VERSION_EXPERT_RULES), reverse = TRUE)`.
@@ -60,12 +60,26 @@ format_eucast_version_nr <- function(version, markdown = TRUE) {
 #' @param ab any (vector of) text that can be coerced to a valid antibiotic code with [as.ab()]
 #' @param administration route of administration, either `r vector_or(dosage$administration)`
 #' @param only_rsi_columns a logical to indicate whether only antibiotic columns must be detected that were transformed to class `<rsi>` (see [as.rsi()]) on beforehand (defaults to `FALSE`)
+#' @param custom_rules custom rules to apply, created with [custom_eucast_rules()]
 #' @inheritParams first_isolate
 #' @details
 #' **Note:** This function does not translate MIC values to RSI values. Use [as.rsi()] for that. \cr
-#' **Note:** When ampicillin (AMP, J01CA01) is not available but amoxicillin (AMX, J01CA04) is, the latter will be used for all rules where there is a dependency on ampicillin. These drugs are interchangeable when it comes to expression of antimicrobial resistance.
+#' **Note:** When ampicillin (AMP, J01CA01) is not available but amoxicillin (AMX, J01CA04) is, the latter will be used for all rules where there is a dependency on ampicillin. These drugs are interchangeable when it comes to expression of antimicrobial resistance. \cr
+
 #'
-#' The file containing all EUCAST rules is located here: <https://github.com/msberends/AMR/blob/master/data-raw/eucast_rules.tsv>.
+#' The file containing all EUCAST rules is located here: <https://github.com/msberends/AMR/blob/master/data-raw/eucast_rules.tsv>.  **Note:** Old taxonomic names are replaced with the current taxonomy where applicable. For example, *Ochrobactrum anthropi* was renamed to *Brucella anthropi* in 2020; the original EUCAST rules v3.1 and v3.2 did not yet contain this new taxonomic name. The file used as input for this `AMR` package contains the taxonomy updated until [`r CATALOGUE_OF_LIFE$yearmonth_LPSN`][catalogue_of_life()].
+#' 
+#' ## Custom Rules
+#' 
+#' Custom rules can be created using [custom_eucast_rules()], e.g.:
+#' 
+#' ```
+#' x <- custom_eucast_rules(AMC == "R" & genus == "Klebsiella" ~ aminopenicillins == "R",
+#'                          AMC == "I" & genus == "Klebsiella" ~ aminopenicillins == "I")
+#'
+#' eucast_rules(example_isolates, rules = "custom", custom_rules = x)
+#' ```
+#' 
 #' 
 #' ## 'Other' Rules
 #' 
@@ -149,19 +163,34 @@ eucast_rules <- function(x,
                          version_expertrules = 3.2,
                          ampc_cephalosporin_resistance = NA,
                          only_rsi_columns = FALSE,
+                         custom_rules = NULL,
                          ...) {
   meet_criteria(x, allow_class = "data.frame")
   meet_criteria(col_mo, allow_class = "character", has_length = 1, is_in = colnames(x), allow_NULL = TRUE)
   meet_criteria(info, allow_class = "logical", has_length = 1)
-  meet_criteria(rules, allow_class = "character", has_length = c(1, 2, 3, 4), is_in = c("breakpoints", "expert", "other", "all"))
+  meet_criteria(rules, allow_class = "character", has_length = c(1, 2, 3, 4, 5), is_in = c("breakpoints", "expert", "other", "all", "custom"))
   meet_criteria(verbose, allow_class = "logical", has_length = 1)
   meet_criteria(version_breakpoints, allow_class = c("numeric", "integer"), has_length = 1, is_in = as.double(names(EUCAST_VERSION_BREAKPOINTS)))
   meet_criteria(version_expertrules, allow_class = c("numeric", "integer"), has_length = 1, is_in = as.double(names(EUCAST_VERSION_EXPERT_RULES)))
   meet_criteria(ampc_cephalosporin_resistance, allow_class = c("logical", "character", "rsi"), has_length = 1, allow_NA = TRUE, allow_NULL = TRUE)
   meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
+  meet_criteria(custom_rules, allow_class = "custom_eucast_rules", allow_NULL = TRUE)
+  
+  if ("custom" %in% rules & is.null(custom_rules)) {
+    warning_("No custom rules were set with the `custom_rules` argument",
+             call = FALSE,
+             immediate = TRUE)
+    rules <- rules[rules != "custom"]
+    if (length(rules) == 0) {
+      if (info == TRUE) {
+        message_("No other rules were set, returning original data", add_fn = font_red, as_note = FALSE)
+      }
+      return(x)
+    }
+  }
   
   x_deparsed <- deparse(substitute(x))
-  if (length(x_deparsed) > 1 || !all(x_deparsed %like% "[a-z]+")) {
+  if (length(x_deparsed) > 1 || any(x_deparsed %unlike% "[a-z]+")) {
     x_deparsed <- "your_data"
   }
   
@@ -196,8 +225,6 @@ eucast_rules <- function(x,
   if (is.null(col_mo)) {
     col_mo <- search_type_in_df(x = x, type = "mo", info = info)
     stop_if(is.null(col_mo), "`col_mo` must be set")
-  } else {
-    stop_ifnot(col_mo %in% colnames(x), "column '", col_mo, "' (`col_mo`) not found")
   }
   
   decimal.mark <- getOption("OutDec")
@@ -263,238 +290,13 @@ eucast_rules <- function(x,
                             info = info,
                             only_rsi_columns = only_rsi_columns,
                             ...)
-
-  AMC <- cols_ab["AMC"]
-  AMK <- cols_ab["AMK"]
-  AMP <- cols_ab["AMP"]
-  AMX <- cols_ab["AMX"]
-  APL <- cols_ab["APL"]
-  APX <- cols_ab["APX"]
-  ATM <- cols_ab["ATM"]
-  AVB <- cols_ab["AVB"]
-  AVO <- cols_ab["AVO"]
-  AZD <- cols_ab["AZD"]
-  AZL <- cols_ab["AZL"]
-  AZM <- cols_ab["AZM"]
-  BAM <- cols_ab["BAM"]
-  BPR <- cols_ab["BPR"]
-  CAC <- cols_ab["CAC"]
-  CAT <- cols_ab["CAT"]
-  CAZ <- cols_ab["CAZ"]
-  CCP <- cols_ab["CCP"]
-  CCV <- cols_ab["CCV"]
-  CCX <- cols_ab["CCX"]
-  CDC <- cols_ab["CDC"]
-  CDR <- cols_ab["CDR"]
-  CDZ <- cols_ab["CDZ"]
-  CEC <- cols_ab["CEC"]
-  CED <- cols_ab["CED"]
-  CEI <- cols_ab["CEI"]
-  CEM <- cols_ab["CEM"]
-  CEP <- cols_ab["CEP"]
-  CFM <- cols_ab["CFM"]
-  CFM1 <- cols_ab["CFM1"]
-  CFP <- cols_ab["CFP"]
-  CFR <- cols_ab["CFR"]
-  CFS <- cols_ab["CFS"]
-  CFZ <- cols_ab["CFZ"]
-  CHE <- cols_ab["CHE"]
-  CHL <- cols_ab["CHL"]
-  CIC <- cols_ab["CIC"]
-  CID <- cols_ab["CID"]
-  CIP <- cols_ab["CIP"]
-  CLI <- cols_ab["CLI"]
-  CLM <- cols_ab["CLM"]
-  CLO <- cols_ab["CLO"]
-  CLR <- cols_ab["CLR"]
-  CMX <- cols_ab["CMX"]
-  CMZ <- cols_ab["CMZ"]
-  CND <- cols_ab["CND"]
-  COL <- cols_ab["COL"]
-  CPD <- cols_ab["CPD"]
-  CPI <- cols_ab["CPI"]
-  CPL <- cols_ab["CPL"]
-  CPM <- cols_ab["CPM"]
-  CPO <- cols_ab["CPO"]
-  CPR <- cols_ab["CPR"]
-  CPT <- cols_ab["CPT"]
-  CPX <- cols_ab["CPX"]
-  CRB <- cols_ab["CRB"]
-  CRD <- cols_ab["CRD"]
-  CRN <- cols_ab["CRN"]
-  CRO <- cols_ab["CRO"]
-  CSL <- cols_ab["CSL"]
-  CTB <- cols_ab["CTB"]
-  CTC <- cols_ab["CTC"]
-  CTF <- cols_ab["CTF"]
-  CTL <- cols_ab["CTL"]
-  CTS <- cols_ab["CTS"]
-  CTT <- cols_ab["CTT"]
-  CTX <- cols_ab["CTX"]
-  CTZ <- cols_ab["CTZ"]
-  CXM <- cols_ab["CXM"]
-  CYC <- cols_ab["CYC"]
-  CZA <- cols_ab["CZA"]
-  CZD <- cols_ab["CZD"]
-  CZO <- cols_ab["CZO"]
-  CZP <- cols_ab["CZP"]
-  CZX <- cols_ab["CZX"]
-  DAL <- cols_ab["DAL"]
-  DAP <- cols_ab["DAP"]
-  DIC <- cols_ab["DIC"]
-  DIR <- cols_ab["DIR"]
-  DIT <- cols_ab["DIT"]
-  DIX <- cols_ab["DIX"]
-  DIZ <- cols_ab["DIZ"]
-  DKB <- cols_ab["DKB"]
-  DOR <- cols_ab["DOR"]
-  DOX <- cols_ab["DOX"]
-  ENX <- cols_ab["ENX"]
-  EPC <- cols_ab["EPC"]
-  ERY <- cols_ab["ERY"]
-  ETP <- cols_ab["ETP"]
-  FEP <- cols_ab["FEP"]
-  FLC <- cols_ab["FLC"]
-  FLE <- cols_ab["FLE"]
-  FLR1 <- cols_ab["FLR1"]
-  FOS <- cols_ab["FOS"]
-  FOV <- cols_ab["FOV"]
-  FOX <- cols_ab["FOX"]
-  FOX1 <- cols_ab["FOX1"]
-  FUS <- cols_ab["FUS"]
-  GAT <- cols_ab["GAT"]
-  GEM <- cols_ab["GEM"]
-  GEN <- cols_ab["GEN"]
-  GRX <- cols_ab["GRX"]
-  HAP <- cols_ab["HAP"]
-  HET <- cols_ab["HET"]
-  IPM <- cols_ab["IPM"]
-  ISE <- cols_ab["ISE"]
-  JOS <- cols_ab["JOS"]
-  KAN <- cols_ab["KAN"]
-  LEN <- cols_ab["LEN"]
-  LEX <- cols_ab["LEX"]
-  LIN <- cols_ab["LIN"]
-  LNZ <- cols_ab["LNZ"]
-  LOM <- cols_ab["LOM"]
-  LOR <- cols_ab["LOR"]
-  LTM <- cols_ab["LTM"]
-  LVX <- cols_ab["LVX"]
-  MAN <- cols_ab["MAN"]
-  MCM <- cols_ab["MCM"]
-  MEC <- cols_ab["MEC"]
-  MEM <- cols_ab["MEM"]
-  MET <- cols_ab["MET"]
-  MEV <- cols_ab["MEV"]
-  MEZ <- cols_ab["MEZ"]
-  MFX <- cols_ab["MFX"]
-  MID <- cols_ab["MID"]
-  MNO <- cols_ab["MNO"]
-  MTM <- cols_ab["MTM"]
-  NAC <- cols_ab["NAC"]
-  NAF <- cols_ab["NAF"]
-  NAL <- cols_ab["NAL"]
-  NEO <- cols_ab["NEO"]
-  NET <- cols_ab["NET"]
-  NIT <- cols_ab["NIT"]
-  NOR <- cols_ab["NOR"]
-  NOV <- cols_ab["NOV"]
-  NVA <- cols_ab["NVA"]
-  OFX <- cols_ab["OFX"]
-  OLE <- cols_ab["OLE"]
-  ORI <- cols_ab["ORI"]
-  OXA <- cols_ab["OXA"]
-  PAZ <- cols_ab["PAZ"]
-  PEF <- cols_ab["PEF"]
-  PEN <- cols_ab["PEN"]
-  PHE <- cols_ab["PHE"]
-  PHN <- cols_ab["PHN"]
-  PIP <- cols_ab["PIP"]
-  PLB <- cols_ab["PLB"]
-  PME <- cols_ab["PME"]
-  PNM <- cols_ab["PNM"]
-  PRC <- cols_ab["PRC"]
-  PRI <- cols_ab["PRI"]
-  PRL <- cols_ab["PRL"]
-  PRP <- cols_ab["PRP"]
-  PRU <- cols_ab["PRU"]
-  PVM <- cols_ab["PVM"]
-  QDA <- cols_ab["QDA"]
-  RAM <- cols_ab["RAM"]
-  RFL <- cols_ab["RFL"]
-  RID <- cols_ab["RID"]
-  RIF <- cols_ab["RIF"]
-  ROK <- cols_ab["ROK"]
-  RST <- cols_ab["RST"]
-  RXT <- cols_ab["RXT"]
-  SAM <- cols_ab["SAM"]
-  SBC <- cols_ab["SBC"]
-  SDI <- cols_ab["SDI"]
-  SDM <- cols_ab["SDM"]
-  SIS <- cols_ab["SIS"]
-  SLF <- cols_ab["SLF"]
-  SLF1 <- cols_ab["SLF1"]
-  SLF10 <- cols_ab["SLF10"]
-  SLF11 <- cols_ab["SLF11"]
-  SLF12 <- cols_ab["SLF12"]
-  SLF13 <- cols_ab["SLF13"]
-  SLF2 <- cols_ab["SLF2"]
-  SLF3 <- cols_ab["SLF3"]
-  SLF4 <- cols_ab["SLF4"]
-  SLF5 <- cols_ab["SLF5"]
-  SLF6 <- cols_ab["SLF6"]
-  SLF7 <- cols_ab["SLF7"]
-  SLF8 <- cols_ab["SLF8"]
-  SLF9 <- cols_ab["SLF9"]
-  SLT1 <- cols_ab["SLT1"]
-  SLT2 <- cols_ab["SLT2"]
-  SLT3 <- cols_ab["SLT3"]
-  SLT4 <- cols_ab["SLT4"]
-  SLT5 <- cols_ab["SLT5"]
-  SLT6 <- cols_ab["SLT6"]
-  SMX <- cols_ab["SMX"]
-  SPI <- cols_ab["SPI"]
-  SPX <- cols_ab["SPX"]
-  SRX <- cols_ab["SRX"]
-  STR <- cols_ab["STR"]
-  STR1 <- cols_ab["STR1"]
-  SUD <- cols_ab["SUD"]
-  SUL <- cols_ab["SUL"]
-  SUT <- cols_ab["SUT"]
-  SXT <- cols_ab["SXT"]
-  SZO <- cols_ab["SZO"]
-  TAL <- cols_ab["TAL"]
-  TAZ <- cols_ab["TAZ"]
-  TCC <- cols_ab["TCC"]
-  TCM <- cols_ab["TCM"]
-  TCY <- cols_ab["TCY"]
-  TEC <- cols_ab["TEC"]
-  TEM <- cols_ab["TEM"]
-  TGC <- cols_ab["TGC"]
-  THA <- cols_ab["THA"]
-  TIC <- cols_ab["TIC"]
-  TIO <- cols_ab["TIO"]
-  TLT <- cols_ab["TLT"]
-  TLV <- cols_ab["TLV"]
-  TMP <- cols_ab["TMP"]
-  TMX <- cols_ab["TMX"]
-  TOB <- cols_ab["TOB"]
-  TRL <- cols_ab["TRL"]
-  TVA <- cols_ab["TVA"]
-  TZD <- cols_ab["TZD"]
-  TZP <- cols_ab["TZP"]
-  VAN <- cols_ab["VAN"]
   
-  ab_missing <- function(ab) {
-    all(ab %in% c(NULL, NA))
-  }
-  
-  if (ab_missing(AMP) & !ab_missing(AMX)) {
+  if (!"AMP" %in% names(cols_ab) & "AMX" %in% names(cols_ab)) {
     # ampicillin column is missing, but amoxicillin is available
     if (info == TRUE) {
-      message_("Using column '", font_bold(AMX), "' as input for ampicillin since many EUCAST rules depend on it.")
+      message_("Using column '", cols_ab[names(cols_ab) == "AMX"], "' as input for ampicillin since many EUCAST rules depend on it.")
     }
-    AMP <- AMX
+    cols_ab <- c(cols_ab, c(AMP = unname(cols_ab[names(cols_ab) == "AMX"])))
   }
   
   # data preparation ----
@@ -502,40 +304,23 @@ eucast_rules <- function(x,
     message_("Preparing data...", appendLF = FALSE, as_note = FALSE)
   }
   
-  # nolint start
-  # antibiotic classes ----
-  aminoglycosides <- c(AMK, DKB, GEN, ISE, KAN, NEO, NET, RST, SIS, STR, STR1, TOB)
-  aminopenicillins <- c(AMP, AMX)
-  carbapenems <- c(DOR, ETP, IPM, MEM, MEV)
-  cephalosporins <- c(CDZ, CCP, CAC, CEC, CFR, RID, MAN, CTZ, CZD, CZO, CDR, DIT, FEP, CAT, CFM, CMX, CMZ, DIZ, CID, CFP, CSL, CND, CTX, CTT, CTF, FOX, CPM, CPO, CPD, CPR, CRD, CFS, CPT, CAZ, CCV, CTL, CTB, CZX, BPR, CFM1, CEI, CRO, CXM, LEX, CEP, HAP, CED, LTM, LOR)
-  cephalosporins_1st <- c(CAC, CFR, RID, CTZ, CZD, CZO, CRD, CTL, LEX, CEP, HAP, CED)
-  cephalosporins_2nd <- c(CEC, MAN, CMZ, CID, CND, CTT, CTF, FOX, CPR, CXM, LOR)
-  cephalosporins_3rd <- c(CDZ, CCP, CCX, CDR, DIT, DIX, CAT, CPI, CFM, CMX, DIZ, CFP, CSL, CTX, CTC, CTS, CHE, FOV, CFZ, CPM, CPD, CPX, CDC, CFS, CAZ, CZA, CCV, CEM, CPL, CTB, TIO, CZX, CZP, CRO, LTM)
-  cephalosporins_except_CAZ <- cephalosporins[cephalosporins != ifelse(is.null(CAZ), "", CAZ)]
-  fluoroquinolones <- c(CIP, ENX, FLE, GAT, GEM, GRX, LVX, LOM, MFX, NOR, OFX, PAZ, PEF, PRU, RFL, SPX, TMX, TVA)
-  glycopeptides <- c(AVO, NVA, RAM, TEC, TCM, VAN) # dalba/orita/tela are in lipoglycopeptides
-  lincosamides <- c(CLI, LIN, PRL)
-  lipoglycopeptides <- c(DAL, ORI, TLV)
-  macrolides <- c(AZM, CLR, DIR, ERY, FLR1, JOS, MID, MCM, OLE, ROK, RXT, SPI, TLT, TRL)
-  oxazolidinones <- c(CYC, LNZ, THA, TZD)
-  polymyxins <- c(PLB, COL)
-  streptogramins <- c(QDA, PRI)
-  tetracyclines <- c(DOX, MNO, TCY) # since EUCAST v3.1 tigecycline (TGC) is set apart
-  ureidopenicillins <- c(PIP, TZP, AZL, MEZ)
-  all_betalactams <- c(aminopenicillins, cephalosporins, carbapenems, ureidopenicillins, AMC, OXA, FLC, PEN)
-  # nolint end
-  
   # Some helper functions ---------------------------------------------------
-  get_antibiotic_columns <- function(x, df) {
-    x <- trimws(unlist(strsplit(x, ",", fixed = TRUE)))
-    y <- character(0)
-    for (i in seq_len(length(x))) {
-      if (is.function(get(x[i]))) {
-        stop("Column ", x[i], " is also a function. Please create an issue on github.com/msberends/AMR/issues.")
+  get_antibiotic_columns <- function(x, cols_ab) {
+    x <- strsplit(x, ", *")[[1]]
+    x_new <- character()
+    for (val in x) {
+      if (toupper(val) %in% ls(envir = asNamespace("AMR"))) {
+        # antibiotic group names, as defined in data-raw/_internals.R, such as `CARBAPENEMS`
+        val <- eval(parse(text = toupper(val)), envir = asNamespace("AMR"))
+      } else if (toupper(val) %in% AB_lookup$ab) {
+        # separate drugs, such as `AMX`
+        val <- as.ab(val)
+      } else {
+        stop_("antimicrobial agent (group) not found in EUCAST rules file: ", val, call = FALSE)
       }
-      y <- c(y, tryCatch(get(x[i]), error = function(e) ""))
+      x_new <- c(x_new, val)
     }
-    y[y != "" & y %in% colnames(df)]
+    cols_ab[match(x_new, names(cols_ab))]
   }
   markup_italics_where_needed <- function(x) {
     # returns names found in family, genus or species as italics
@@ -553,7 +338,7 @@ eucast_rules <- function(x,
       strsplit(",") %pm>%
       unlist() %pm>%
       trimws() %pm>%
-      vapply(FUN.VALUE = character(1), function(x) if (x %in% antibiotics$ab) ab_name(x, language = NULL, tolower = TRUE) else x) %pm>%
+      vapply(FUN.VALUE = character(1), function(x) if (x %in% antibiotics$ab) ab_name(x, language = NULL, tolower = TRUE, fast_mode = TRUE) else x) %pm>%
       sort() %pm>%
       paste(collapse = ", ")
     x <- gsub("_", " ", x, fixed = TRUE)
@@ -633,8 +418,11 @@ eucast_rules <- function(x,
     pm_distinct(`.rowid`, .keep_all = TRUE) %pm>% 
     as.data.frame(stringsAsFactors = FALSE)
   x[, col_mo] <- as.mo(as.character(x[, col_mo, drop = TRUE]))
-  x <- x %pm>%
-    left_join_microorganisms(by = col_mo, suffix = c("_oldcols", ""))
+  # rename col_mo to prevent interference with joined columns
+  colnames(x)[colnames(x) == col_mo] <- ".col_mo"
+  col_mo <- ".col_mo"
+  # join to microorganisms data set
+  x <- left_join_microorganisms(x, by = col_mo, suffix = c("_oldcols", ""))
   x$gramstain <- mo_gramstain(x[, col_mo, drop = TRUE], language = NULL)
   x$genus_species <- paste(x$genus, x$species)
   if (info == TRUE & NROW(x) > 10000) {
@@ -662,33 +450,47 @@ eucast_rules <- function(x,
                          font_red(paste0("v", utils::packageDescription("AMR")$Version, ", ", 
                                          format(as.Date(utils::packageDescription("AMR")$Date), format = "%Y"))), "), see ?eucast_rules\n"))))
     }
-    
     ab_enzyme <- subset(antibiotics, name %like% "/")[, c("ab", "name")]
-    ab_enzyme$base_name <- gsub("^([a-zA-Z0-9]+).*", "\\1", ab_enzyme$name)
-    ab_enzyme$base_ab <- as.ab(ab_enzyme$base_name)
+    colnames(ab_enzyme) <- c("enzyme_ab", "enzyme_name")
+    ab_enzyme$base_name <- gsub("^([a-zA-Z0-9]+).*", "\\1", ab_enzyme$enzyme_name)
+    ab_enzyme$base_ab <- antibiotics[match(ab_enzyme$base_name, antibiotics$name), "ab", drop = TRUE]
+    ab_enzyme <- subset(ab_enzyme, !is.na(base_ab))
+    # make ampicillin and amoxicillin interchangable
+    ampi <- subset(ab_enzyme, base_ab == "AMX")
+    ampi$base_ab <- "AMP"
+    ampi$base_name <- ab_name("AMP", language = NULL)
+    amox <- subset(ab_enzyme, base_ab == "AMP")
+    amox$base_ab <- "AMX"
+    amox$base_name <- ab_name("AMX", language = NULL)
+    # merge and sort
+    ab_enzyme <- rbind(ab_enzyme, ampi, amox)
+    ab_enzyme <- ab_enzyme[order(ab_enzyme$enzyme_name), ]
+    
     for (i in seq_len(nrow(ab_enzyme))) {
-      if (all(c(ab_enzyme[i, ]$ab, ab_enzyme[i, ]$base_ab) %in% names(cols_ab), na.rm = TRUE)) {
-        ab_name_base <- ab_name(cols_ab[ab_enzyme[i, ]$base_ab], language = NULL, tolower = TRUE)
-        ab_name_enzyme <- ab_name(cols_ab[ab_enzyme[i, ]$ab], language = NULL, tolower = TRUE)
+      # check if both base and base + enzyme inhibitor are part of the data set
+      if (all(c(ab_enzyme$base_ab[i], ab_enzyme$enzyme_ab[i]) %in% names(cols_ab), na.rm = TRUE)) {
+        col_base <- unname(cols_ab[ab_enzyme$base_ab[i]])
+        col_enzyme <- unname(cols_ab[ab_enzyme$enzyme_ab[i]])
         
         # Set base to R where base + enzyme inhibitor is R ----
-        rule_current <- paste0("Set ", ab_name_base, " (", cols_ab[ab_enzyme[i, ]$base_ab], ") = R where ",
-                               ab_name_enzyme, " (", cols_ab[ab_enzyme[i, ]$ab], ") = R")
+        rule_current <- paste0(ab_enzyme$base_name[i], " ('", font_bold(col_base), "') = R if ",
+                               tolower(ab_enzyme$enzyme_name[i]), " ('", font_bold(col_enzyme), "') = R")
         if (info == TRUE) {
-          cat(word_wrap(rule_current))
-          cat("\n")
+          cat(word_wrap(rule_current, 
+                        width = getOption("width") - 30,
+                        extra_indent = 6))
         }
         run_changes <- edit_rsi(x = x,
-                                col_mo = col_mo,
                                 to = "R",
                                 rule = c(rule_current, "Other rules", "",
                                          paste0("Non-EUCAST: AMR package v", utils::packageDescription("AMR")$Version)),
-                                rows = which(as.rsi_no_warning(x[, cols_ab[ab_enzyme[i, ]$ab]]) == "R"),
-                                cols = cols_ab[ab_enzyme[i, ]$base_ab],
+                                rows = which(as.rsi_no_warning(x[, col_enzyme, drop = TRUE]) == "R"),
+                                cols = col_base,
                                 last_verbose_info = verbose_info,
                                 original_data = x.bak,
                                 warned = warned,
-                                info = info)
+                                info = info,
+                                verbose = verbose)
         n_added <- n_added + run_changes$added
         n_changed <- n_changed + run_changes$changed
         verbose_info <- run_changes$verbose_info
@@ -704,23 +506,25 @@ eucast_rules <- function(x,
         }
         
         # Set base + enzyme inhibitor to S where base is S ----
-        rule_current <- paste0("Set ", ab_name_enzyme, " (", cols_ab[ab_enzyme[i, ]$ab], ") = S where ",
-                               ab_name_base, " (", cols_ab[ab_enzyme[i, ]$base_ab], ") = S")
+        rule_current <- paste0(ab_enzyme$enzyme_name[i], " ('", font_bold(col_enzyme), "') = S if ",
+                               tolower(ab_enzyme$base_name[i]), " ('", font_bold(col_base), "') = S")
+
         if (info == TRUE) {
-          cat(word_wrap(rule_current))
-          cat("\n")
+          cat(word_wrap(rule_current, 
+                        width = getOption("width") - 30,
+                        extra_indent = 6))
         }
         run_changes <- edit_rsi(x = x,
-                                col_mo = col_mo,
                                 to = "S",
                                 rule = c(rule_current, "Other rules", "", 
                                          paste0("Non-EUCAST: AMR package v", utils::packageDescription("AMR")$Version)),
-                                rows = which(as.rsi_no_warning(x[, cols_ab[ab_enzyme[i, ]$base_ab]]) == "S"),
-                                cols = cols_ab[ab_enzyme[i, ]$ab],
+                                rows = which(as.rsi_no_warning(x[, col_base, drop = TRUE]) == "S"),
+                                cols = col_enzyme,
                                 last_verbose_info = verbose_info,
                                 original_data = x.bak,
                                 warned = warned,
-                                info = info)
+                                info = info,
+                                verbose = verbose)
         n_added <- n_added + run_changes$added
         n_changed <- n_changed + run_changes$changed
         verbose_info <- run_changes$verbose_info
@@ -740,10 +544,17 @@ eucast_rules <- function(x,
   } else {
     if (info == TRUE) {
       cat("\n")
-      message_("Skipping inheritance rules defined by this package, such as setting trimethoprim (TMP) = R where trimethoprim/sulfamethoxazole (SXT) = R. Use `eucast_rules(..., rules = \"all\")` to also apply those rules.")
+      message_("Skipping inheritance rules defined by this AMR package, such as setting trimethoprim (TMP) = R where trimethoprim/sulfamethoxazole (SXT) = R. Add \"other\" or \"all\" to the `rules` argument to apply those rules.")
     }
   }
   
+  if (!any(c("all", "custom") %in% rules) & !is.null(custom_rules)) {
+    if (info == TRUE) {
+      message_("Skipping custom EUCAST rules, since the `rules` argument does not contain \"custom\".")
+    }
+    custom_rules <- NULL
+  }
+  
   # Official EUCAST rules ---------------------------------------------------
   eucast_notification_shown <- FALSE
   if (!is.null(list(...)$eucast_rules_df)) {
@@ -757,19 +568,19 @@ eucast_rules <- function(x,
   # filter on user-set guideline versions ----
   if (any(c("all", "breakpoints") %in% rules)) {
     eucast_rules_df <- subset(eucast_rules_df,
-                              !reference.rule_group %like% "breakpoint" |
+                              reference.rule_group %unlike% "breakpoint" |
                                 (reference.rule_group %like% "breakpoint" & reference.version == version_breakpoints))
   }
   if (any(c("all", "expert") %in% rules)) {
     eucast_rules_df <- subset(eucast_rules_df,
-                              !reference.rule_group %like% "expert" |
+                              reference.rule_group %unlike% "expert" |
                                 (reference.rule_group %like% "expert" & reference.version == version_expertrules))
   }
   # filter out AmpC de-repressed cephalosporin-resistant mutants ----
   # cefotaxime, ceftriaxone, ceftazidime
   if (is.null(ampc_cephalosporin_resistance) || isFALSE(ampc_cephalosporin_resistance)) {
     eucast_rules_df <- subset(eucast_rules_df,
-                              !reference.rule %like% "ampc")
+                              reference.rule %unlike% "ampc")
   } else {
     if (isTRUE(ampc_cephalosporin_resistance)) {
       ampc_cephalosporin_resistance <- "R"
@@ -777,6 +588,7 @@ eucast_rules <- function(x,
     eucast_rules_df[which(eucast_rules_df$reference.rule %like% "ampc"), "to_value"] <- as.character(ampc_cephalosporin_resistance)
   }
   
+  # Go over all rules and apply them ----
   for (i in seq_len(nrow(eucast_rules_df))) {
     
     rule_previous <- eucast_rules_df[max(1, i - 1), "reference.rule", drop = TRUE]
@@ -784,6 +596,14 @@ eucast_rules <- function(x,
     rule_next <- eucast_rules_df[min(nrow(eucast_rules_df), i + 1), "reference.rule", drop = TRUE]
     rule_group_previous <- eucast_rules_df[max(1, i - 1), "reference.rule_group", drop = TRUE]
     rule_group_current <- eucast_rules_df[i, "reference.rule_group", drop = TRUE]
+    # don't apply rules if user doesn't want to apply them
+    if (rule_group_current %like% "breakpoint" & !any(c("all", "breakpoints") %in% rules)) {
+      next
+    }
+    if (rule_group_current %like% "expert" & !any(c("all", "expert") %in% rules)) {
+      next
+    }
+    
     if (isFALSE(info) | isFALSE(verbose)) {
       rule_text <- ""
     } else {
@@ -804,17 +624,9 @@ eucast_rules <- function(x,
       rule_next <- ""
     }
     
-    # don't apply rules if user doesn't want to apply them
-    if (rule_group_current %like% "breakpoint" & !any(c("all", "breakpoints") %in% rules)) {
-      next
-    }
-    if (rule_group_current %like% "expert" & !any(c("all", "expert") %in% rules)) {
-      next
-    }
-    
     if (info == TRUE) {
       # Print EUCAST intro ------------------------------------------------------
-      if (!rule_group_current %like% "other" & eucast_notification_shown == FALSE) {
+      if (rule_group_current %unlike% "other" & eucast_notification_shown == FALSE) {
         cat(
           paste0("\n", font_grey(strrep("-", 0.95 * options()$width)), "\n",
                  word_wrap("Rules by the ", font_bold("European Committee on Antimicrobial Susceptibility Testing (EUCAST)")), "\n", 
@@ -899,26 +711,26 @@ eucast_rules <- function(x,
     source_value <- trimws(unlist(strsplit(eucast_rules_df[i, "have_these_values", drop = TRUE], ",", fixed = TRUE)))
     target_antibiotics <- eucast_rules_df[i, "then_change_these_antibiotics", drop = TRUE]
     target_value <- eucast_rules_df[i, "to_value", drop = TRUE]
-    
+
     if (is.na(source_antibiotics)) {
       rows <- tryCatch(which(x[, if_mo_property, drop = TRUE] %like% mo_value),
                        error = function(e) integer(0))
     } else {
-      source_antibiotics <- get_antibiotic_columns(source_antibiotics, x)
+      source_antibiotics <- get_antibiotic_columns(source_antibiotics, cols_ab)
       if (length(source_value) == 1 & length(source_antibiotics) > 1) {
         source_value <- rep(source_value, length(source_antibiotics))
       }
       if (length(source_antibiotics) == 0) {
         rows <- integer(0)
       } else if (length(source_antibiotics) == 1) {
-        rows <-  tryCatch(which(x[, if_mo_property, drop = TRUE] %like% mo_value
-                                & as.rsi_no_warning(x[, source_antibiotics[1L]]) == source_value[1L]),
-                          error = function(e) integer(0))
+        rows <- tryCatch(which(x[, if_mo_property, drop = TRUE] %like% mo_value
+                               & as.rsi_no_warning(x[, source_antibiotics[1L]]) == source_value[1L]),
+                         error = function(e) integer(0))
       } else if (length(source_antibiotics) == 2) {
-        rows <-  tryCatch(which(x[, if_mo_property, drop = TRUE] %like% mo_value
-                                & as.rsi_no_warning(x[, source_antibiotics[1L]]) == source_value[1L]
-                                & as.rsi_no_warning(x[, source_antibiotics[2L]]) == source_value[2L]),
-                          error = function(e) integer(0))
+        rows <- tryCatch(which(x[, if_mo_property, drop = TRUE] %like% mo_value
+                               & as.rsi_no_warning(x[, source_antibiotics[1L]]) == source_value[1L]
+                               & as.rsi_no_warning(x[, source_antibiotics[2L]]) == source_value[2L]),
+                         error = function(e) integer(0))
         # nolint start
       # } else if (length(source_antibiotics) == 3) {
       #   rows <-  tryCatch(which(x[, if_mo_property, drop = TRUE] %like% mo_value
@@ -932,12 +744,11 @@ eucast_rules <- function(x,
       }
     }
     
-    cols <- get_antibiotic_columns(target_antibiotics, x)
+    cols <- get_antibiotic_columns(target_antibiotics, cols_ab)
     
     # Apply rule on data ------------------------------------------------------
     # this will return the unique number of changes
     run_changes <- edit_rsi(x = x,
-                            col_mo = col_mo,
                             to = target_value,
                             rule = c(rule_text, rule_group_current, rule_current, 
                                      ifelse(rule_group_current %like% "breakpoint",
@@ -948,7 +759,8 @@ eucast_rules <- function(x,
                             last_verbose_info = verbose_info,
                             original_data = x.bak,
                             warned = warned,
-                            info = info)
+                            info = info,
+                            verbose = verbose)
     n_added <- n_added + run_changes$added
     n_changed <- n_changed + run_changes$changed
     verbose_info <- run_changes$verbose_info
@@ -962,6 +774,60 @@ eucast_rules <- function(x,
       n_added <- 0
       n_changed <- 0
     }
+  } # end of going over all rules
+
+  # Apply custom rules ----
+  if (!is.null(custom_rules)) {
+    if (info == TRUE) {
+      cat("\n")
+      cat(font_bold("Custom EUCAST rules, set by user"), "\n")
+    }
+    for (i in seq_len(length(custom_rules))) {
+      rule <- custom_rules[[i]]
+      rows <- which(eval(parse(text = rule$query), envir = x))
+      cols <- as.character(rule$result_group)
+      cols <- c(cols[cols %in% colnames(x)],               # direct column names
+                unname(cols_ab[names(cols_ab) %in% cols])) # based on previous cols_ab finding
+      cols <- unique(cols)
+      target_value <- as.character(rule$result_value)
+      rule_text <- paste0("report as '", target_value, "' when ",
+                          format_custom_query_rule(rule$query, colours = FALSE), ": ",
+                          get_antibiotic_names(cols))
+      if (info == TRUE) {
+        # print rule
+        cat(markup_italics_where_needed(word_wrap(format_custom_query_rule(rule$query, colours = FALSE), 
+                                                  width = getOption("width") - 30,
+                                                  extra_indent = 6)))
+        warned <- FALSE
+      }
+      run_changes <- edit_rsi(x = x,
+                              to = target_value,
+                              rule = c(rule_text, 
+                                       "Custom EUCAST rules",
+                                       paste0("Custom EUCAST rule ", i),
+                                       paste0("Object '", deparse(substitute(custom_rules)), 
+                                              "' consisting of ", length(custom_rules), " custom rules")),
+                              rows = rows,
+                              cols = cols,
+                              last_verbose_info = verbose_info,
+                              original_data = x.bak,
+                              warned = warned,
+                              info = info,
+                              verbose = verbose)
+      n_added <- n_added + run_changes$added
+      n_changed <- n_changed + run_changes$changed
+      verbose_info <- run_changes$verbose_info
+      x <- run_changes$output
+      warn_lacking_rsi_class <- c(warn_lacking_rsi_class, run_changes$rsi_warn)
+      # Print number of new changes ---------------------------------------------
+      if (info == TRUE & rule_next != rule_current) {
+        # print only on last one of rules in this group
+        txt_ok(n_added = n_added, n_changed = n_changed, warned = warned)
+        # and reset counters
+        n_added <- 0
+        n_changed <- 0
+      }
+    }
   }
   
   # Print overview ----------------------------------------------------------
@@ -1080,16 +946,16 @@ eucast_rules <- function(x,
 }
 
 # helper function for editing the table ----
-edit_rsi <- function(x, 
-                     col_mo,
-                     to, 
-                     rule, 
+edit_rsi <- function(x,
+                     to,
+                     rule,
                      rows,
                      cols,
-                     last_verbose_info, 
+                     last_verbose_info,
                      original_data,
                      warned,
-                     info) {
+                     info,
+                     verbose) {
   cols <- unique(cols[!is.na(cols) & !is.null(cols)])
   
   # for Verbose Mode, keep track of all changes and return them
@@ -1146,7 +1012,7 @@ edit_rsi <- function(x,
     )
     
     track_changes$output <- new_edits
-    if (isTRUE(info) && !isTRUE(all.equal(x, track_changes$output))) {
+    if ((info == TRUE | verbose == TRUE) && !isTRUE(all.equal(x, track_changes$output))) {
       get_original_rows <- function(rowids) {
         as.integer(rownames(original_data[which(original_data$.rowid %in% rowids), , drop = FALSE]))
       }

R/filter_ab_class.R

@@ -425,7 +425,7 @@ find_ab_group <- function(ab_class) {
 
 find_ab_names <- function(ab_group, n = 3) {
   ab_group <- gsub("[^a-zA-Z0-9]", ".*", ab_group)
-  drugs <- antibiotics[which(antibiotics$group %like% ab_group & !antibiotics$ab %like% "[0-9]$"), ]$name
+  drugs <- antibiotics[which(antibiotics$group %like% ab_group & antibiotics$ab %unlike% "[0-9]$"), ]$name
   paste0(sort(ab_name(sample(drugs, size = min(n, length(drugs)), replace = FALSE),
                       tolower = TRUE, language = NULL)), 
          collapse = ", ")

R/first_isolate.R

@@ -34,7 +34,7 @@
 #' @param col_testcode column name of the test codes. Use `col_testcode = NULL` to **not** exclude certain test codes (such as test codes for screening). In that case `testcodes_exclude` will be ignored.
 #' @param col_specimen column name of the specimen type or group
 #' @param col_icu column name of the logicals (`TRUE`/`FALSE`) whether a ward or department is an Intensive Care Unit (ICU)
-#' @param col_keyantibiotics column name of the key antibiotics to determine first (weighted) isolates, see [key_antibiotics()]. Defaults to the first column that starts with 'key' followed by 'ab' or 'antibiotics' (case insensitive). Use `col_keyantibiotics = FALSE` to prevent this.
+#' @param col_keyantibiotics column name of the key antibiotics to determine first (weighted) isolates, see [key_antibiotics()]. Defaults to the first column that starts with 'key' followed by 'ab' or 'antibiotics' (case insensitive). Use `col_keyantibiotics = FALSE` to prevent this. Can also be the output of [key_antibiotics()].
 #' @param episode_days episode in days after which a genus/species combination will be determined as 'first isolate' again. The default of 365 days is based on the guideline by CLSI, see *Source*. 
 #' @param testcodes_exclude character vector with test codes that should be excluded (case-insensitive)
 #' @param icu_exclude logical to indicate whether ICU isolates should be excluded (rows with value `TRUE` in the column set with `col_icu`)
@@ -42,7 +42,7 @@
 #' @param type type to determine weighed isolates; can be `"keyantibiotics"` or `"points"`, see *Details*
 #' @param ignore_I logical to indicate whether antibiotic interpretations with `"I"` will be ignored when `type = "keyantibiotics"`, see *Details*
 #' @param points_threshold points until the comparison of key antibiotics will lead to inclusion of an isolate when `type = "points"`, see *Details*
-#' @param info print progress
+#' @param info a [logical] to indicate info should be printed, defaults to `TRUE` only in interactive mode
 #' @param include_unknown logical to indicate whether 'unknown' microorganisms should be included too, i.e. microbial code `"UNKNOWN"`, which defaults to `FALSE`. For WHONET users, this means that all records with organism code `"con"` (*contamination*) will be excluded at default. Isolates with a microbial ID of `NA` will always be excluded as first isolate.
 #' @param include_untested_rsi logical to indicate whether also rows without antibiotic results are still eligible for becoming a first isolate. Use `include_untested_rsi = FALSE` to always return `FALSE` for such rows. This checks the data set for columns of class `<rsi>` and consequently requires transforming columns with antibiotic results using [as.rsi()] first.
 #' @param ... arguments passed on to [first_isolate()] when using [filter_first_isolate()], or arguments passed on to [key_antibiotics()] when using [filter_first_weighted_isolate()]
@@ -177,11 +177,17 @@ first_isolate <- function(x = NULL,
   }
   meet_criteria(col_specimen, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
   meet_criteria(col_icu, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
-  if (isFALSE(col_keyantibiotics)) {
-    col_keyantibiotics <- NULL
+  if (length(col_keyantibiotics) > 1) {
+    meet_criteria(col_keyantibiotics, allow_class = "character", has_length = nrow(x))
+    x$keyabcol <- col_keyantibiotics
+    col_keyantibiotics <- "keyabcol"
+  } else {
+    if (isFALSE(col_keyantibiotics)) {
+      col_keyantibiotics <- NULL
+    }
+    meet_criteria(col_keyantibiotics, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
   }
-  meet_criteria(col_keyantibiotics, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
-  meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
+  meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = FALSE)
   meet_criteria(testcodes_exclude, allow_class = "character", allow_NULL = TRUE)
   meet_criteria(icu_exclude, allow_class = "logical", has_length = 1)
   meet_criteria(specimen_group, allow_class = "character", has_length = 1, allow_NULL = TRUE)
@@ -396,7 +402,7 @@ first_isolate <- function(x = NULL,
                                              type = type_param,
                                              ignore_I = ignore_I,
                                              points_threshold = points_threshold,
-                                             info = info)
+                                             na.rm = TRUE)
     # with key antibiotics
     x$newvar_first_isolate <- pm_if_else(x$newvar_row_index_sorted >= row.start &
                                            x$newvar_row_index_sorted <= row.end &
@@ -491,10 +497,10 @@ first_isolate <- function(x = NULL,
     n_found <- sum(x$newvar_first_isolate, na.rm = TRUE)
     p_found_total <- percentage(n_found / nrow(x[which(!is.na(x$newvar_mo)), , drop = FALSE]), digits = 1)
     p_found_scope <- percentage(n_found / scope.size, digits = 1)
-    if (!p_found_total %like% "[.]") {
+    if (p_found_total %unlike% "[.]") {
       p_found_total <- gsub("%", ".0%", p_found_total, fixed = TRUE)
     }
-    if (!p_found_scope %like% "[.]") {
+    if (p_found_scope %unlike% "[.]") {
       p_found_scope <- gsub("%", ".0%", p_found_scope, fixed = TRUE)
     }
     # mark up number of found

R/globals.R

@@ -66,6 +66,7 @@ globalVariables(c(".rowid",
                   "antibiotics",
                   "atc_group1",
                   "atc_group2",
+                  "base_ab",
                   "code",
                   "cols",
                   "count",

R/join_microorganisms.R

@@ -279,7 +279,7 @@ check_groups_before_join <- function(x, fn) {
   if (is.data.frame(x) && !is.null(attributes(x)$groups)) {
     x <- pm_ungroup(x)
     attr(x, "groups") <- NULL
-    class(x) <- class(x)[!class(x) %like% "group"]
+    class(x) <- class(x)[class(x) %unlike% "group"]
     warning_("Groups are dropped, since the ", fn, "() function relies on merge() from base R.", call = FALSE)
   }
   x

R/key_antibiotics.R

@@ -136,7 +136,7 @@ key_antibiotics <- function(x = NULL,
     x <- tryCatch(get_current_data(arg_name = "x", call = -2), error = function(e) x)
   }
   meet_criteria(x, allow_class = "data.frame") # also checks dimensions to be >0
-  meet_criteria(col_mo, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
+  meet_criteria(col_mo, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE, is_in = colnames(x))
   meet_criteria(universal_1, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
   meet_criteria(universal_2, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
   meet_criteria(universal_3, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
@@ -173,10 +173,14 @@ key_antibiotics <- function(x = NULL,
   # -- mo
   if (is.null(col_mo)) {
     col_mo <- search_type_in_df(x = x, type = "mo")
-    stop_if(is.null(col_mo), "`col_mo` must be set")
-  } else {
-    stop_ifnot(col_mo %in% colnames(x), "column '", col_mo, "' (`col_mo`) not found")
   }
+  if (is.null(col_mo)) {
+    warning_("No column found for `col_mo`, ignoring antimicrobial agents set for Gram-negative and Gram-positive bacteria", call = FALSE)
+    x$gramstain <- NA_character_
+  } else {
+    x$gramstain <- mo_gramstain(as.mo(x[, col_mo, drop = TRUE]), language = NULL)
+  }
+  x$key_ab <- NA_character_
   
   # check columns
   col.list <- c(universal_1, universal_2, universal_3, universal_4, universal_5, universal_6,
@@ -239,7 +243,7 @@ key_antibiotics <- function(x = NULL,
                      GramPos_4, GramPos_5, GramPos_6)
   gram_positive <- gram_positive[!is.null(gram_positive)]
   gram_positive <- gram_positive[!is.na(gram_positive)]
-  if (length(gram_positive) < 12 & message_not_thrown_before("key_antibiotics.grampos")) {
+  if (length(gram_positive) < 12 & !all(is.na(x$gramstain)) & message_not_thrown_before("key_antibiotics.grampos")) {
     warning_("Only using ", length(gram_positive), " different antibiotics as key antibiotics for Gram-positives. See ?key_antibiotics.", call = FALSE)
     remember_thrown_message("key_antibiotics.grampos")
   }
@@ -249,33 +253,29 @@ key_antibiotics <- function(x = NULL,
                      GramNeg_4, GramNeg_5, GramNeg_6)
   gram_negative <- gram_negative[!is.null(gram_negative)]
   gram_negative <- gram_negative[!is.na(gram_negative)]
-  if (length(gram_negative) < 12 & message_not_thrown_before("key_antibiotics.gramneg")) {
+  if (length(gram_negative) < 12 & !all(is.na(x$gramstain)) & message_not_thrown_before("key_antibiotics.gramneg")) {
     warning_("Only using ", length(gram_negative), " different antibiotics as key antibiotics for Gram-negatives. See ?key_antibiotics.", call = FALSE)
     remember_thrown_message("key_antibiotics.gramneg")
   }
   
-  x[, col_mo] <- as.mo(x[, col_mo, drop = TRUE])
-  x$gramstain <- mo_gramstain(x[, col_mo, drop = TRUE], language = NULL)
-  x$key_ab <- NA_character_
-  
   # Gram +
   x$key_ab <- pm_if_else(x$gramstain == "Gram-positive",
-                      tryCatch(apply(X = x[, gram_positive],
-                                     MARGIN = 1,
-                                     FUN = function(x) paste(x, collapse = "")),
-                               error = function(e) paste0(rep(".", 12), collapse = "")),
-                      x$key_ab)
+                         tryCatch(apply(X = x[, gram_positive],
+                                        MARGIN = 1,
+                                        FUN = function(x) paste(x, collapse = "")),
+                                  error = function(e) paste0(rep(".", 12), collapse = "")),
+                         as.character(x$key_ab))
   
   # Gram -
   x$key_ab <- pm_if_else(x$gramstain == "Gram-negative",
-                      tryCatch(apply(X = x[, gram_negative],
-                                     MARGIN = 1,
-                                     FUN = function(x) paste(x, collapse = "")),
-                               error = function(e) paste0(rep(".", 12), collapse = "")),
-                      x$key_ab)
+                         tryCatch(apply(X = x[, gram_negative],
+                                        MARGIN = 1,
+                                        FUN = function(x) paste(x, collapse = "")),
+                                  error = function(e) paste0(rep(".", 12), collapse = "")),
+                         as.character(x$key_ab))
   
   # format
-  key_abs <- toupper(gsub("[^SIR]", ".", gsub("(NA|NULL)", ".", x$key_ab)))
+  key_abs <- toupper(gsub("(NA|NULL|[^RSIrsi])", ".", x$key_ab))
   
   if (pm_n_distinct(key_abs) == 1) {
     warning_("No distinct key antibiotics determined.", call = FALSE)
@@ -286,95 +286,75 @@ key_antibiotics <- function(x = NULL,
 }
 
 #' @rdname key_antibiotics
+#' @param info unused - previously used to indicate whether a progress bar should print
+#' @param na.rm a [logical] to indicate whether comparison with `NA` should return `FALSE` (defaults to `TRUE` for backwards compatibility)
 #' @export
 key_antibiotics_equal <- function(y,
                                   z,
                                   type = c("keyantibiotics", "points"),
                                   ignore_I = TRUE,
                                   points_threshold = 2,
-                                  info = FALSE) {
+                                  info = FALSE,
+                                  na.rm = TRUE,
+                                  ...) {
   meet_criteria(y, allow_class = "character")
   meet_criteria(z, allow_class = "character")
-  meet_criteria(type, allow_class = "character", has_length = c(1, 2))
+  if (length(type) == 2) {
+    type <- type[1L]
+  }
+  meet_criteria(type, allow_class = "character", has_length = 1, is_in = c("keyantibiotics", "points"))
   meet_criteria(ignore_I, allow_class = "logical", has_length = 1)
   meet_criteria(points_threshold, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
   meet_criteria(info, allow_class = "logical", has_length = 1)
-  
+  meet_criteria(na.rm, allow_class = "logical", has_length = 1)
   stop_ifnot(length(y) == length(z), "length of `y` and `z` must be equal")
-  # y is active row, z is lag
-  x <- y
-  y <- z
-  
-  type <- type[1]
-  
-  # only show progress bar on points or when at least 5000 isolates
-  info_needed <- info == TRUE & (type == "points" | length(x) > 5000)
-  
-  result <- logical(length(x))
-  
-  if (info_needed == TRUE) {
-    p <- progress_ticker(length(x))
-    on.exit(close(p))
+
+  key2rsi <- function(val) {
+    as.double(as.rsi(gsub(".", NA_character_, unlist(strsplit(val, "")), fixed = TRUE)))
   }
+  y <- lapply(y, key2rsi)
+  z <- lapply(z, key2rsi)
   
-  for (i in seq_len(length(x))) {
-    
-    if (info_needed == TRUE) {
-      p$tick()
+  determine_equality <- function(a, b, type, points_threshold, ignore_I) {
+    if (length(a) != length(b)) {
+      # incomparable, so not equal
+      return(FALSE)
     }
+    # ignore NAs on both sides
+    NA_ind <- which(is.na(a) | is.na(b))
+    a[NA_ind] <- NA_real_
+    b[NA_ind] <- NA_real_
     
-    if (is.na(x[i])) {
-      x[i] <- ""
-    }
-    if (is.na(y[i])) {
-      y[i] <- ""
-    }
-    
-    if (x[i] == y[i]) {
-      
-      result[i] <- TRUE
-      
-    } else if (nchar(x[i]) != nchar(y[i])) {
-      
-      result[i] <- FALSE
-      
+    if (type == "points") {
+      # count points for every single character:
+      # - no change is 0 points
+      # - I <-> S|R is 0.5 point
+      # - S|R <-> R|S is 1 point
+      # use the levels of as.rsi (S = 1, I = 2, R = 3)
+      (sum(abs(a - b), na.rm = TRUE) / 2) < points_threshold
     } else {
-      
-      x_split <- strsplit(x[i], "")[[1]]
-      y_split <- strsplit(y[i], "")[[1]]
-      
-      if (type == "keyantibiotics") {
-        
-        if (ignore_I == TRUE) {
-          x_split[x_split == "I"] <- "."
-          y_split[y_split == "I"] <- "."
-        }
-        
-        y_split[x_split == "."] <- "."
-        x_split[y_split == "."] <- "."
-        
-        result[i] <- all(x_split == y_split)
-        
-      } else if (type == "points") {
-        # count points for every single character:
-        # - no change is 0 points
-        # - I <-> S|R is 0.5 point
-        # - S|R <-> R|S is 1 point
-        # use the levels of as.rsi (S = 1, I = 2, R = 3)
-        
-        suppressWarnings(x_split <- x_split %pm>% as.rsi() %pm>% as.double())
-        suppressWarnings(y_split <- y_split %pm>% as.rsi() %pm>% as.double())
-        
-        points <- (x_split - y_split) %pm>% abs() %pm>% sum(na.rm = TRUE) / 2
-        result[i] <- points >= points_threshold
-        
-      } else {
-        stop("`", type, '` is not a valid value for type, must be "points" or "keyantibiotics". See ?key_antibiotics')
+      if (ignore_I == TRUE) {
+        ind <- which(a == 2 | b == 2) # since as.double(as.rsi("I")) == 2
+        a[ind] <- NA_real_
+        b[ind] <- NA_real_
       }
+      all(a == b, na.rm = TRUE)
     }
   }
-  if (info_needed == TRUE) {
-    close(p)
+  out <- unlist(mapply(FUN = determine_equality,
+                       y,
+                       z,
+                       MoreArgs = list(type = type,
+                                       points_threshold = points_threshold,
+                                       ignore_I = ignore_I),
+                       SIMPLIFY = FALSE,
+                       USE.NAMES = FALSE))
+  if (na.rm == FALSE) {
+    out[is.na(y) | is.na(z)] <- NA
+  } else  {
+    # NA means not equal if `na.rm == TRUE`, as per the manual
+    out[is.na(y) | is.na(z)] <- FALSE
   }
-  result
+  
+  out
 }

R/like.R

@@ -23,30 +23,29 @@
 # how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
 # ==================================================================== #
 
-#' Pattern Matching with Keyboard Shortcut
+#' Vectorised Pattern Matching with Keyboard Shortcut
 #'
 #' Convenient wrapper around [grepl()] to match a pattern: `x %like% pattern`. It always returns a [`logical`] vector and is always case-insensitive (use `x %like_case% pattern` for case-sensitive matching). Also, `pattern` can be as long as `x` to compare items of each index in both vectors, or they both can have the same length to iterate over all cases.
 #' @inheritSection lifecycle Stable Lifecycle
 #' @param x a character vector where matches are sought, or an object which can be coerced by [as.character()] to a character vector.
-#' @param pattern a character string containing a regular expression (or [character] string for `fixed = TRUE`) to be matched in the given character vector. Coerced by [as.character()] to a character string if possible.  If a [character] vector of length 2 or more is supplied, the first element is used with a warning.
+#' @param pattern a character vector containing regular expressions (or a [character] string for `fixed = TRUE`) to be matched in the given character vector. Coerced by [as.character()] to a character string if possible.
 #' @param ignore.case if `FALSE`, the pattern matching is *case sensitive* and if `TRUE`, case is ignored during matching.
-#' @return A [`logical`] vector
+#' @return A [logical] vector
 #' @name like
 #' @rdname like
 #' @export
 #' @details
-#' The `%like%` function:
-#' * Is case-insensitive (use `%like_case%` for case-sensitive matching)
-#' * Supports multiple patterns
-#' * Checks if `pattern` is a regular expression and sets `fixed = TRUE` if not, to greatly improve speed
-#' * Always uses compatibility with Perl
+#' These [like()] and `%like%`/`%unlike%` functions:
+#' * Are case-insensitive (use `%like_case%`/`%unlike_case%` for case-sensitive matching)
+#' * Support multiple patterns
+#' * Check if `pattern` is a valid regular expression and sets `fixed = TRUE` if not, to greatly improve speed (vectorised over `pattern`)
+#' * Always use compatibility with Perl unless `fixed = TRUE`, to greatly improve speed
 #' 
-#' Using RStudio? The text `%like%` can also be directly inserted in your code from the Addins menu and can have its own Keyboard Shortcut like `Ctrl+Shift+L` or `Cmd+Shift+L` (see `Tools` > `Modify Keyboard Shortcuts...`).
-#' @source Idea from the [`like` function from the `data.table` package](https://github.com/Rdatatable/data.table/blob/master/R/like.R)
+#' Using RStudio? The `%like%`/`%unlike%` functions can also be directly inserted in your code from the Addins menu and can have its own keyboard shortcut like `Shift+Ctrl+L` or `Shift+Cmd+L` (see menu `Tools` > `Modify Keyboard Shortcuts...`). If you keep pressing your shortcut, the inserted text will be iterated over `%like%` -> `%unlike%` -> `%like_case%` -> `%unlike_case%`.
+#' @source Idea from the [`like` function from the `data.table` package](https://github.com/Rdatatable/data.table/blob/ec1259af1bf13fc0c96a1d3f9e84d55d8106a9a4/R/like.R), although altered as explained in *Details*.
 #' @seealso [grepl()]
 #' @inheritSection AMR Read more on Our Website!
 #' @examples
-#' # simple test
 #' a <- "This is a test"
 #' b <- "TEST"
 #' a %like% b
@@ -59,16 +58,23 @@
 #' b <- c(     "case",           "diff",      "yet")
 #' a %like% b
 #' #> TRUE TRUE TRUE
+#' a %unlike% b
+#' #> FALSE FALSE FALSE
+#' 
 #' a[1] %like% b
 #' #> TRUE FALSE FALSE
 #' a %like% b[1]
 #' #> TRUE FALSE FALSE
 #' 
 #' # get isolates whose name start with 'Ent' or 'ent'
+#' example_isolates[which(mo_name(example_isolates$mo) %like% "^ent"), ]
 #' \donttest{
+#' # faster way, only works in R 3.2 and later:
+#' example_isolates[which(mo_name() %like% "^ent"), ]
+#' 
 #' if (require("dplyr")) {
 #'   example_isolates %>%
-#'     filter(mo_name(mo) %like% "^ent")
+#'     filter(mo_name() %like% "^ent")
 #' }
 #' }
 like <- function(x, pattern, ignore.case = TRUE) {
@@ -79,9 +85,10 @@ like <- function(x, pattern, ignore.case = TRUE) {
   if (all(is.na(x))) {
     return(rep(FALSE, length(x)))
   }
-  
-  # set to fixed if no regex found
-  fixed <- !any(is_possibly_regex(pattern))
+
+  # set to fixed if no valid regex (vectorised)
+  fixed <- !is_valid_regex(pattern)
+
   if (ignore.case == TRUE) {
     # set here, otherwise if fixed = TRUE, this warning will be thrown: argument `ignore.case = TRUE` will be ignored
     x <- tolower(x)
@@ -91,21 +98,26 @@ like <- function(x, pattern, ignore.case = TRUE) {
   if (is.factor(x)) {
     x <- as.character(x)
   }
-  
+
   if (length(pattern) == 1) {
     grepl(pattern, x, ignore.case = FALSE, fixed = fixed, perl = !fixed)
   } else {
     if (length(x) == 1) {
       x <- rep(x, length(pattern))
     } else if (length(pattern) != length(x)) {
-      stop_("arguments `x` and `pattern` must be of same length, or either one must be 1")
+      stop_("arguments `x` and `pattern` must be of same length, or either one must be 1 ",
+            "(`x` has length ", length(x), " and `pattern` has length ", length(pattern), ")")
     }
     unlist(
-      Map(f = grepl,
-          pattern,
-          x,
-          MoreArgs = list(ignore.case = FALSE, fixed = fixed, perl = !fixed)),
-      use.names = FALSE)
+      mapply(FUN = grepl,
+             x = x,
+             pattern = pattern,
+             fixed = fixed,
+             perl = !fixed,
+             MoreArgs = list(ignore.case = FALSE),
+             SIMPLIFY = FALSE,
+             USE.NAMES = FALSE)
+    )
   }
 }
 
@@ -117,6 +129,14 @@ like <- function(x, pattern, ignore.case = TRUE) {
   like(x, pattern, ignore.case = TRUE)
 }
 
+#' @rdname like
+#' @export
+"%unlike%" <- function(x, pattern) {
+  meet_criteria(x, allow_NA = TRUE)
+  meet_criteria(pattern, allow_NA = FALSE)
+  !like(x, pattern, ignore.case = TRUE)
+}
+
 #' @rdname like
 #' @export
 "%like_case%" <- function(x, pattern) {
@@ -124,3 +144,11 @@ like <- function(x, pattern, ignore.case = TRUE) {
   meet_criteria(pattern, allow_NA = FALSE)
   like(x, pattern, ignore.case = FALSE)
 }
+
+#' @rdname like
+#' @export
+"%unlike_case%" <- function(x, pattern) {
+  meet_criteria(x, allow_NA = TRUE)
+  meet_criteria(pattern, allow_NA = FALSE)
+  !like(x, pattern, ignore.case = FALSE)
+}

R/mdro.R

@@ -78,7 +78,7 @@
 #' 
 #' Custom guidelines can be set with the [custom_mdro_guideline()] function. This is of great importance if you have custom rules to determine MDROs in your hospital, e.g., rules that are dependent on ward, state of contact isolation or other variables in your data.
 #' 
-#' If you are familiar with `case_when()` of the `dplyr` package, you will recognise the input method to set your own rules. Rules must be set using what \R considers to be the 'formula notation':
+#' If you are familiar with the [`case_when()`][dplyr::case_when()] function of the `dplyr` package, you will recognise the input method to set your own rules. Rules must be set using what \R considers to be the 'formula notation'. The rule is written *before* the tilde (`~`) and the consequence of the rule is written *after* the tilde:
 #' 
 #' ```
 #' custom <- custom_mdro_guideline(CIP == "R" & age > 60 ~ "Elderly Type A",
@@ -102,10 +102,22 @@
 #' The outcome of the function can be used for the `guideline` argument in the [mdro()] function:
 #' 
 #' ```
-#' x <- mdro(example_isolates, guideline = custom)
+#' x <- mdro(example_isolates,
+#'           guideline = custom)
 #' table(x)
-#' #> Elderly Type A Elderly Type B       Negative 
-#' #>             43            891           1066 
+#' #>       Negative Elderly Type A Elderly Type B
+#' #>           1070            198            732
+#' ```
+#' 
+#' Rules can also be combined with other custom rules by using [c()]:
+#' 
+#' ```
+#' x <- mdro(example_isolates,
+#'           guideline = c(custom, 
+#'                         custom_mdro_guideline(ERY == "R" & age > 50 ~ "Elderly Type C")))
+#' table(x)
+#' #>       Negative Elderly Type A Elderly Type B Elderly Type C 
+#' #>            961            198            732            109
 #' ```
 #' 
 #' The rules set (the `custom` object in this case) could be exported to a shared file location using [saveRDS()] if you collaborate with multiple users. The custom rules set could then be imported using [readRDS()].
@@ -246,7 +258,7 @@ mdro <- function(x = NULL,
       txt <- word_wrap(txt)
       cat(txt, "\n", sep = "")
     }
-    x <- run_custom_mdro_guideline(x, guideline)
+    x <- run_custom_mdro_guideline(df = x, guideline = guideline, info = info)
     if (info.bak == TRUE) {
       cat(group_msg)
       if (sum(!is.na(x$MDRO)) == 0) {
@@ -299,7 +311,6 @@ mdro <- function(x = NULL,
     col_mo <- "mo"
   }
   stop_if(is.null(col_mo), "`col_mo` must be set")
-  stop_ifnot(col_mo %in% colnames(x), "column '", col_mo, "' (`col_mo`) not found")
   
   if (guideline$code == "cmi2012") {
     guideline$name <- "Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance."
@@ -749,7 +760,11 @@ mdro <- function(x = NULL,
       row_filter <- x[which(row_filter), "row_number", drop = TRUE]
       rows <- rows[rows %in% row_filter]
       x[rows, "MDRO"] <<- to
-      x[rows, "reason"] <<- paste0(any_all, " of the required antibiotics ", ifelse(any_all == "any", "is", "are"), " R")
+      x[rows, "reason"] <<- paste0(any_all, 
+                                   " of the required antibiotics ",
+                                   ifelse(any_all == "any", "is", "are"),
+                                   " R",
+                                   ifelse(!isTRUE(combine_SI), " or I", ""))
     }
   }
   trans_tbl2 <- function(txt, rows, lst) {
@@ -802,6 +817,9 @@ mdro <- function(x = NULL,
   }
   
   x[, col_mo] <- as.mo(as.character(x[, col_mo, drop = TRUE]))
+  # rename col_mo to prevent interference with joined columns
+  colnames(x)[colnames(x) == col_mo] <- ".col_mo"
+  col_mo <- ".col_mo"
   # join to microorganisms data set
   x <- left_join_microorganisms(x, by = col_mo)
   x$MDRO <- ifelse(!is.na(x$genus), 1, NA_integer_)
@@ -1015,7 +1033,10 @@ mdro <- function(x = NULL,
     # PDR (=4): all agents are R 
     x[which(x$classes_affected == 999 & x$classes_in_guideline == x$classes_available), "MDRO"] <- 4
     if (verbose == TRUE) {
-      x[which(x$MDRO == 4), "reason"] <- paste("all antibiotics in all", x$classes_in_guideline[which(x$MDRO == 4)], "classes were tested R or I")
+      x[which(x$MDRO == 4), "reason"] <- paste("all antibiotics in all",
+                                               x$classes_in_guideline[which(x$MDRO == 4)], 
+                                               "classes were tested R",
+                                               ifelse(!isTRUE(combine_SI), " or I", ""))
     }
     
     # not enough classes available
@@ -1378,7 +1399,12 @@ mdro <- function(x = NULL,
   # some more info on negative results
   if (verbose == TRUE) {
     if (guideline$code == "cmi2012") {
-      x[which(x$MDRO == 1 & !is.na(x$classes_affected)), "reason"] <- paste0(x$classes_affected[which(x$MDRO == 1 & !is.na(x$classes_affected))], " of ", x$classes_available[which(x$MDRO == 1 & !is.na(x$classes_affected))], " available classes contain R or I (3 required for MDR)")
+      x[which(x$MDRO == 1 & !is.na(x$classes_affected)), "reason"] <- paste0(x$classes_affected[which(x$MDRO == 1 & !is.na(x$classes_affected))],
+                                                                             " of ",
+                                                                             x$classes_available[which(x$MDRO == 1 & !is.na(x$classes_affected))],
+                                                                             " available classes contain R",
+                                                                             ifelse(!isTRUE(combine_SI), " or I", ""),
+                                                                             " (3 required for MDR)")
     } else {
       x[which(x$MDRO == 1), "reason"] <- "too few antibiotics are R"
     }
@@ -1419,8 +1445,10 @@ mdro <- function(x = NULL,
   }
   
   if (verbose == TRUE) {
+    colnames(x)[colnames(x) == col_mo] <- "microorganism"
+    x$microorganism <- mo_name(x$microorganism, language = NULL)
     x[, c("row_number",
-          col_mo,
+          "microorganism",
           "MDRO",
           "reason",
           "columns_nonsusceptible"), 
@@ -1434,6 +1462,8 @@ mdro <- function(x = NULL,
 #' @rdname mdro
 #' @export
 custom_mdro_guideline <- function(..., as_factor = TRUE) {
+  meet_criteria(as_factor, allow_class = "logical", has_length = 1)
+  
   dots <- tryCatch(list(...),
                    error = function(e) "error")
   stop_if(identical(dots, "error"),
@@ -1470,11 +1500,49 @@ custom_mdro_guideline <- function(..., as_factor = TRUE) {
   
   names(out) <- paste0("rule", seq_len(n_dots))
   out <- set_clean_class(out, new_class = c("custom_mdro_guideline", "list"))
-  attr(out, "values") <- c("Negative", vapply(FUN.VALUE = character(1), out, function(x) x$value))
+  attr(out, "values") <- unname(c("Negative", vapply(FUN.VALUE = character(1), unclass(out), function(x) x$value)))
   attr(out, "as_factor") <- as_factor
   out
 }
 
+#' @method c custom_mdro_guideline
+#' @noRd
+#' @export
+c.custom_mdro_guideline <- function(x, ..., as_factor = NULL) {
+  if (length(list(...)) == 0) {
+    return(x)
+  }
+  if (!is.null(as_factor)) {
+    meet_criteria(as_factor, allow_class = "logical", has_length = 1)
+  } else {
+    as_factor <- attributes(x)$as_factor
+  }
+  for (g in list(...)) {
+    stop_ifnot(inherits(g, "custom_mdro_guideline"),
+               "for combining custom MDRO guidelines, all rules must be created with `custom_mdro_guideline()`",
+               call = FALSE)
+    vals <- attributes(x)$values
+    if (!all(attributes(g)$values %in% vals)) {
+      vals <- unname(unique(c(vals, attributes(g)$values)))
+    }
+    attributes(g) <- NULL
+    x <- c(unclass(x), unclass(g))
+    attr(x, "values") <- vals
+  }
+  names(x) <- paste0("rule", seq_len(length(x)))
+  x <- set_clean_class(x, new_class = c("custom_mdro_guideline", "list"))
+  attr(x, "values") <- vals
+  attr(x, "as_factor") <- as_factor
+  x
+}
+
+#' @method as.list custom_mdro_guideline
+#' @noRd
+#' @export
+as.list.custom_mdro_guideline <- function(x, ...) {
+  c(x, ...)
+}
+
 #' @method print custom_mdro_guideline
 #' @export
 #' @noRd
@@ -1482,23 +1550,10 @@ print.custom_mdro_guideline <- function(x, ...) {
   cat("A set of custom MDRO rules:\n")
   for (i in seq_len(length(x))) {
     rule <- x[[i]]
-    rule$query <- gsub(" & ", font_black(font_italic(" and ")), rule$query, fixed = TRUE)
-    rule$query <- gsub(" | ", font_black(" or "), rule$query, fixed = TRUE)
-    rule$query <- gsub(" + ", font_black(" plus "), rule$query, fixed = TRUE)
-    rule$query <- gsub(" - ", font_black(" minus "), rule$query, fixed = TRUE)
-    rule$query <- gsub(" / ", font_black(" divided by "), rule$query, fixed = TRUE)
-    rule$query <- gsub(" * ", font_black(" times "), rule$query, fixed = TRUE)
-    rule$query <- gsub(" == ", font_black(" is "), rule$query, fixed = TRUE)
-    rule$query <- gsub(" > ", font_black(" is higher than "), rule$query, fixed = TRUE)
-    rule$query <- gsub(" < ", font_black(" is lower than "), rule$query, fixed = TRUE)
-    rule$query <- gsub(" >= ", font_black(" is higher than or equal to "), rule$query, fixed = TRUE)
-    rule$query <- gsub(" <= ", font_black(" is lower than or equal to "), rule$query, fixed = TRUE)
-    rule$query <- gsub(" ^ ", font_black(" to the power of "), rule$query, fixed = TRUE)
-    # replace the black colour 'stops' with blue colour 'starts'
-    rule$query <- gsub("\033[39m", "\033[34m", as.character(rule$query), fixed = TRUE)
-    cat("  ", i, ". ", font_blue(rule$query), font_bold(" -> "), font_red(rule$value), "\n", sep = "")
+    rule$query <- format_custom_query_rule(rule$query)
+    cat("  ", i, ". ", font_bold("If "), font_blue(rule$query), font_bold(" then: "), font_red(rule$value), "\n", sep = "")
   }
-  cat("  ", i + 1, ". Otherwise", font_bold(" -> "), font_red(paste0("Negative")), "\n", sep = "")
+  cat("  ", i + 1, ". ", font_bold("Otherwise: "), font_red(paste0("Negative")), "\n", sep = "")
   cat("\nUnmatched rows will return ", font_red("NA"), ".\n", sep = "")
   if (isTRUE(attributes(x)$as_factor)) {
     cat("Results will be of class <factor>, with ordered levels: ", paste0(attributes(x)$values, collapse = " < "), "\n", sep = "")
@@ -1507,7 +1562,7 @@ print.custom_mdro_guideline <- function(x, ...) {
   }
 }
 
-run_custom_mdro_guideline <- function(df, guideline) {
+run_custom_mdro_guideline <- function(df, guideline, info) {
   n_dots <- length(guideline)
   stop_if(n_dots == 0, "no custom guidelines set", call = -2)
   out <- character(length = NROW(df))
@@ -1520,7 +1575,7 @@ run_custom_mdro_guideline <- function(df, guideline) {
                     })
     if (identical(qry, "error")) {
       warning_("in custom_mdro_guideline(): rule ", i, 
-               " (`", guideline[[i]]$query, "`) was ignored because of this error message: ",
+               " (`", as.character(guideline[[i]]$query), "`) was ignored because of this error message: ",
                pkg_env$err_msg,
                call = FALSE, 
                add_fn = font_red)
@@ -1529,9 +1584,16 @@ run_custom_mdro_guideline <- function(df, guideline) {
     stop_ifnot(is.logical(qry), "in custom_mdro_guideline(): rule ", i, " (`", guideline[[i]]$query, 
                "`) must return `TRUE` or `FALSE`, not ", 
                format_class(class(qry), plural = FALSE), call = FALSE)
+    
+    new_mdros <- which(qry == TRUE & out == "")
+    
+    if (info == TRUE) {
+      cat(word_wrap("- Custom MDRO rule ", i, ": `", as.character(guideline[[i]]$query),
+                    "` (", length(new_mdros),  " rows matched)"), "\n", sep = "")
+    }
     val <- guideline[[i]]$value
-    out[which(qry)] <- val
-    reasons[which(qry)] <- paste0("matched rule ", gsub("rule", "", names(guideline)[i]), ": ", as.character(guideline[[i]]$query))
+    out[new_mdros] <- val
+    reasons[new_mdros] <- paste0("matched rule ", gsub("rule", "", names(guideline)[i]), ": ", as.character(guideline[[i]]$query))
   }
   out[out == ""] <- "Negative"
   reasons[out == "Negative"] <- "no rules matched"
@@ -1540,8 +1602,7 @@ run_custom_mdro_guideline <- function(df, guideline) {
     out <- factor(out, levels = attributes(guideline)$values, ordered = TRUE)
   }
   
-  rsi_cols <- vapply(FUN.VALUE = logical(1), df, function(x) is.rsi(x))
-  columns_nonsusceptible <- as.data.frame(t(df[, rsi_cols] == "R"))
+  columns_nonsusceptible <- as.data.frame(t(df[, is.rsi(df)] == "R"))
   columns_nonsusceptible <- vapply(FUN.VALUE = character(1), 
                                    columns_nonsusceptible, 
                                    function(x) paste0(rownames(columns_nonsusceptible)[which(x)], collapse = " "))

R/mic.R

@@ -133,7 +133,7 @@ as.mic <- function(x, na.rm = FALSE) {
     # keep only one zero before dot
     x <- gsub("0+[.]", "0.", x, perl = TRUE)
     # starting 00 is probably 0.0 if there's no dot yet
-    x[!x %like% "[.]"] <- gsub("^00", "0.0", x[!x %like% "[.]"])
+    x[x %unlike% "[.]"] <- gsub("^00", "0.0", x[!x %like% "[.]"])
     # remove last zeroes
     x <- gsub("([.].?)0+$", "\\1", x, perl = TRUE)
     x <- gsub("(.*[.])0+$", "\\10", x, perl = TRUE)

R/mo.R

@@ -38,6 +38,7 @@
 #' @param reference_df a [data.frame] to be used for extra reference when translating `x` to a valid [`mo`]. See [set_mo_source()] and [get_mo_source()] to automate the usage of your own codes (e.g. used in your analysis or organisation).
 #' @param ignore_pattern a regular expression (case-insensitive) of which all matches in `x` must return `NA`. This can be convenient to exclude known non-relevant input and can also be set with the option `AMR_ignore_pattern`, e.g. `options(AMR_ignore_pattern = "(not reported|contaminated flora)")`.
 #' @param language language to translate text like "no growth", which defaults to the system language (see [get_locale()])
+#' @param info a [logical] to indicate if a progress bar should be printed if more than 25 items are to be coerced, defaults to `TRUE` only in interactive mode
 #' @param ... other arguments passed on to functions
 #' @rdname as.mo
 #' @aliases mo
@@ -161,6 +162,7 @@ as.mo <- function(x,
                   reference_df = get_mo_source(),
                   ignore_pattern = getOption("AMR_ignore_pattern"),
                   language = get_locale(),
+                  info = interactive(),
                   ...) {
   meet_criteria(x, allow_class = c("mo", "data.frame", "list", "character", "numeric", "integer", "factor"), allow_NA = TRUE)
   meet_criteria(Becker, allow_class = c("logical", "character"), has_length = 1)
@@ -169,7 +171,8 @@ as.mo <- function(x,
   meet_criteria(reference_df, allow_class = "data.frame", allow_NULL = TRUE)
   meet_criteria(ignore_pattern, allow_class = "character", has_length = 1, allow_NULL = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-
+  meet_criteria(info, allow_class = "logical", has_length = 1)
+  
   check_dataset_integrity()
 
   if (tryCatch(all(x[!is.na(x)] %in% MO_lookup$mo)
@@ -227,6 +230,7 @@ as.mo <- function(x,
                      reference_df = reference_df,
                      ignore_pattern = ignore_pattern,
                      language = language,
+                     info = info,
                      ...)
   }
 
@@ -253,6 +257,7 @@ exec_as.mo <- function(x,
                        Lancefield = FALSE,
                        allow_uncertain = TRUE,
                        reference_df = get_mo_source(),
+                       info = interactive(),
                        property = "mo",
                        initial_search = TRUE,
                        dyslexia_mode = FALSE,
@@ -600,7 +605,7 @@ exec_as.mo <- function(x,
       }
       
       if (initial_search == TRUE) {
-        progress <- progress_ticker(n = length(x[!already_known]), n_min = 25) # start if n >= 25
+        progress <- progress_ticker(n = length(x[!already_known]), n_min = 25, print = info) # start if n >= 25
         on.exit(close(progress))
       }
       
@@ -703,7 +708,7 @@ exec_as.mo <- function(x,
         
         # check for very small input, but ignore the O antigens of E. coli
         if (nchar(gsub("[^a-zA-Z]", "", x_trimmed[i])) < 3
-            & !toupper(x_backup_without_spp[i]) %like_case% "O?(26|103|104|104|111|121|145|157)") {
+            & toupper(x_backup_without_spp[i]) %unlike_case% "O?(26|103|104|104|111|121|145|157)") {
           # fewer than 3 chars and not looked for species, add as failure
           x[i] <- lookup(mo == "UNKNOWN")
           if (initial_search == TRUE) {
@@ -855,7 +860,7 @@ exec_as.mo <- function(x,
             x[i] <- lookup(genus == "Salmonella", uncertainty = -1)
             next
           } else if (x_backup[i] %like_case% "[sS]almonella [A-Z][a-z]+ ?.*" &
-                     !x_backup[i] %like% "t[iy](ph|f)[iy]") {
+                     x_backup[i] %unlike% "t[iy](ph|f)[iy]") {
             # Salmonella with capital letter species like "Salmonella Goettingen" - they're all S. enterica
             # except for S. typhi, S. paratyphi, S. typhimurium
             x[i] <- lookup(fullname == "Salmonella enterica", uncertainty = -1)
@@ -911,7 +916,7 @@ exec_as.mo <- function(x,
           # FIRST TRY FULLNAMES AND CODES ----
           # if only genus is available, return only genus
           
-          if (all(!c(x[i], b.x_trimmed) %like_case% " ")) {
+          if (all(c(x[i], b.x_trimmed) %unlike_case% " ")) {
             found <- lookup(fullname_lower %in% c(h.x_species, i.x_trimmed_species),
                             haystack = data_to_check)
             if (!is.na(found)) {
@@ -1118,8 +1123,8 @@ exec_as.mo <- function(x,
               if (isTRUE(debug)) {
                 cat(font_bold("\n[ UNCERTAINTY LEVEL", now_checks_for_uncertainty_level, "] (3) look for genus only, part of name\n"))
               }
-              if (nchar(g.x_backup_without_spp) > 4 & !b.x_trimmed %like_case% " ") {
-                if (!b.x_trimmed %like_case% "^[A-Z][a-z]+") {
+              if (nchar(g.x_backup_without_spp) > 4 & b.x_trimmed %unlike_case% " ") {
+                if (b.x_trimmed %unlike_case% "^[A-Z][a-z]+") {
                   if (isTRUE(debug)) {
                     message("Running '", paste(b.x_trimmed, "species"), "'")
                   }
@@ -1263,7 +1268,7 @@ exec_as.mo <- function(x,
                                         stringsAsFactors = FALSE)
                 return(found)
               }
-              if (b.x_trimmed %like_case% "(fungus|fungi)" & !b.x_trimmed %like_case% "fungiphrya") {
+              if (b.x_trimmed %like_case% "(fungus|fungi)" & b.x_trimmed %unlike_case% "fungiphrya") {
                 found <- "F_FUNGUS"
                 found_result <- found
                 found <- lookup(mo == found)
@@ -1654,10 +1659,28 @@ pillar_shaft.mo <- function(x, ...) {
   out[!is.na(x)] <- gsub("^([A-Z]+_)(.*)", paste0(font_subtle("\\1"), "\\2"), out[!is.na(x)], perl = TRUE)
   # and grey out every _
   out[!is.na(x)] <- gsub("_", font_subtle("_"), out[!is.na(x)])
-
+  
   # markup NA and UNKNOWN
   out[is.na(x)] <- font_na("  NA")
   out[x == "UNKNOWN"] <- font_na("  UNKNOWN")
+  
+  if (!all(x[!is.na(x)] %in% MO_lookup$mo)) {
+    # markup old mo codes
+    out[!x %in% MO_lookup$mo] <- font_italic(font_na(x[!x %in% MO_lookup$mo], 
+                                                     collapse = NULL),
+                                             collapse = NULL)
+    # throw a warning with the affected column name
+    mo <- tryCatch(search_type_in_df(get_current_data(arg_name = "x", call = 0), type = "mo", info = FALSE),
+                   error = function(e) NULL)
+    if (!is.null(mo)) {
+      col <- paste0("Column '", mo, "'")
+    } else {
+      col <- "The data"
+    }
+    warning_(col, " contains old microbial codes (from a previous AMR package version). ",
+             "Please update your MO codes with `as.mo()`.",
+             call = FALSE)
+  }
 
   # make it always fit exactly
   max_char <- max(nchar(x))
@@ -1753,11 +1776,16 @@ summary.mo <- function(object, ...) {
 #' @export
 #' @noRd
 as.data.frame.mo <- function(x, ...) {
+  if (!all(x[!is.na(x)] %in% MO_lookup$mo)) {
+    warning_("The data contains old microbial codes (from a previous AMR package version). ",
+             "Please update your MO codes with `as.mo()`.",
+             call = FALSE)
+  }
   nm <- deparse1(substitute(x))
   if (!"nm" %in% names(list(...))) {
-    as.data.frame.vector(as.mo(x), ..., nm = nm)
+    as.data.frame.vector(x, ..., nm = nm)
   } else {
-    as.data.frame.vector(as.mo(x), ...)
+    as.data.frame.vector(x, ...)
   }
 }
 
@@ -1875,6 +1903,7 @@ print.mo_uncertainties <- function(x, ...) {
                            collapse = "")
       # after strwrap, make taxonomic names italic
       candidates <- gsub("([A-Za-z]+)", font_italic("\\1"), candidates, perl = TRUE)
+      candidates <- gsub(font_italic("and"), "and", candidates, fixed = TRUE)
       candidates <- gsub(paste(font_italic(c("Also", "matched"), collapse = NULL), collapse = " "),
                          "Also matched",
                          candidates, fixed = TRUE)
@@ -2028,13 +2057,15 @@ replace_old_mo_codes <- function(x, property) {
     x[which(!is.na(matched))] <- mo_new[which(!is.na(matched))]
     n_matched <- length(matched[!is.na(matched)])
     if (property != "mo") {
-      message_(font_blue("The input contained old microbial codes (from previous package versions). Please update your MO codes with `as.mo()`."))
+      message_(font_blue(paste0("The input contained ", n_matched,
+                                " old microbial code", ifelse(n_matched == 1, "", "s"),
+                                " (from a previous AMR package version). Please update your MO codes with `as.mo()`.")))
     } else {
-      if (n_matched == 1) {
-        message_(font_blue("1 old microbial code (from previous package versions) was updated to a current used MO code."))
-      } else {
-        message_(font_blue(n_matched, "old microbial codes (from previous package versions) were updated to current used MO codes.")) 
-      }
+      message_(font_blue(paste0(n_matched, " old microbial code", ifelse(n_matched == 1, "", "s"), 
+                                " (from a previous AMR package version) ", 
+                                ifelse(n_matched == 1, "was", "were"), 
+                                " updated to ", ifelse(n_matched == 1, "a ", ""), 
+                                "currently used MO code", ifelse(n_matched == 1, "", "s"), ".")))
     }
   }
   x

R/mo_matching_score.R

@@ -44,7 +44,7 @@
 #' * \ifelse{html}{\out{<i>p<sub>n</sub></i> is the human pathogenic prevalence group of <i>n</i>, as described below;}}{p_n is the human pathogenic prevalence group of \eqn{n}, as described below;}
 #' * \ifelse{html}{\out{<i>k<sub>n</sub></i> is the taxonomic kingdom of <i>n</i>, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}}{l_n is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}
 #' 
-#' The grouping into human pathogenic prevalence (\eqn{p}) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. **Group 1** (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is *Enterococcus*, *Staphylococcus* or *Streptococcus*. This group consequently contains all common Gram-negative bacteria, such as *Pseudomonas* and *Legionella* and all species within the order Enterobacterales. **Group 2** consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is *Absidia*, *Acremonium*, *Actinotignum*, *Alternaria*, *Anaerosalibacter*, *Apophysomyces*, *Arachnia*, *Aspergillus*, *Aureobacterium*, *Aureobasidium*, *Bacteroides*, *Basidiobolus*, *Beauveria*, *Blastocystis*, *Branhamella*, *Calymmatobacterium*, *Candida*, *Capnocytophaga*, *Catabacter*, *Chaetomium*, *Chryseobacterium*, *Chryseomonas*, *Chrysonilia*, *Cladophialophora*, *Cladosporium*, *Conidiobolus*, *Cryptococcus*, *Curvularia*, *Exophiala*, *Exserohilum*, *Flavobacterium*, *Fonsecaea*, *Fusarium*, *Fusobacterium*, *Hendersonula*, *Hypomyces*, *Koserella*, *Lelliottia*, *Leptosphaeria*, *Leptotrichia*, *Malassezia*, *Malbranchea*, *Mortierella*, *Mucor*, *Mycocentrospora*, *Mycoplasma*, *Nectria*, *Ochroconis*, *Oidiodendron*, *Phoma*, *Piedraia*, *Pithomyces*, *Pityrosporum*, *Prevotella*, *Pseudallescheria*, *Rhizomucor*, *Rhizopus*, *Rhodotorula*, *Scolecobasidium*, *Scopulariopsis*, *Scytalidium*,*Sporobolomyces*, *Stachybotrys*, *Stomatococcus*, *Treponema*, *Trichoderma*, *Trichophyton*, *Trichosporon*, *Tritirachium* or *Ureaplasma*. **Group 3** consists of all other microorganisms.
+#' The grouping into human pathogenic prevalence (\eqn{p}) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. **Group 1** (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is *Enterococcus*, *Staphylococcus* or *Streptococcus*. This group consequently contains all common Gram-negative bacteria, such as *Pseudomonas* and *Legionella* and all species within the order Enterobacterales. **Group 2** consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is *Absidia*, *Acremonium*, *Actinotignum*, *Alternaria*, *Anaerosalibacter*, *Apophysomyces*, *Arachnia*, *Aspergillus*, *Aureobacterium*, *Aureobasidium*, *Bacteroides*, *Basidiobolus*, *Beauveria*, *Blastocystis*, *Branhamella*, *Calymmatobacterium*, *Candida*, *Capnocytophaga*, *Catabacter*, *Chaetomium*, *Chryseobacterium*, *Chryseomonas*, *Chrysonilia*, *Cladophialophora*, *Cladosporium*, *Conidiobolus*, *Cryptococcus*, *Curvularia*, *Exophiala*, *Exserohilum*, *Flavobacterium*, *Fonsecaea*, *Fusarium*, *Fusobacterium*, *Hendersonula*, *Hypomyces*, *Koserella*, *Lelliottia*, *Leptosphaeria*, *Leptotrichia*, *Malassezia*, *Malbranchea*, *Mortierella*, *Mucor*, *Mycocentrospora*, *Mycoplasma*, *Nectria*, *Ochroconis*, *Oidiodendron*, *Phoma*, *Piedraia*, *Pithomyces*, *Pityrosporum*, *Prevotella*, *Pseudallescheria*, *Rhizomucor*, *Rhizopus*, *Rhodotorula*, *Scolecobasidium*, *Scopulariopsis*, *Scytalidium*, *Sporobolomyces*, *Stachybotrys*, *Stomatococcus*, *Treponema*, *Trichoderma*, *Trichophyton*, *Trichosporon*, *Tritirachium* or *Ureaplasma*. **Group 3** consists of all other microorganisms.
 #' 
 #' All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., `"E. coli"` will return the microbial ID of *Escherichia coli* (\eqn{m = `r round(mo_matching_score("E. coli", "Escherichia coli"), 3)`}, a highly prevalent microorganism found in humans) and not *Entamoeba coli* (\eqn{m = `r round(mo_matching_score("E. coli", "Entamoeba coli"), 3)`}, a less prevalent microorganism in humans), although the latter would alphabetically come first. 
 #' @export

R/mo_property.R

@@ -723,20 +723,13 @@ mo_validate <- function(x, property, language, ...) {
     # special case for mo_* functions where class is already <mo>
     return(MO_lookup[match(x, MO_lookup$mo), property, drop = TRUE])
   }
-
+  
   # try to catch an error when inputting an invalid argument
   # so the 'call.' can be set to FALSE
   tryCatch(x[1L] %in% MO_lookup[1, property, drop = TRUE],
            error = function(e) stop(e$message, call. = FALSE))
-  
-  if (is.mo(x)
-      & !Becker %in% c(TRUE, "all")
-      & !Lancefield %in% c(TRUE, "all")) {
-    # this will not reset mo_uncertainties and mo_failures
-    # because it's already a valid MO
-    x <- exec_as.mo(x, property = property, initial_search = FALSE, language = language, ...)
-  } else if (!all(x %in% MO_lookup[, property, drop = TRUE])
-             | has_Becker_or_Lancefield) {
+
+  if (!all(x[!is.na(x)] %in% MO_lookup[, property, drop = TRUE]) | has_Becker_or_Lancefield) {
     x <- exec_as.mo(x, property = property, language = language, ...)
   }
   

R/plot.R

@@ -93,6 +93,14 @@ plot.mic <- function(x,
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
   meet_criteria(expand, allow_class = "logical", has_length = 1)
   
+  # translate if not specifically set
+  if (missing(ylab)) {
+    ylab <- translate_AMR(ylab, language = language)
+  }
+  if (missing(xlab)) {
+    xlab <- translate_AMR(xlab, language = language)
+  }
+  
   if (length(colours_RSI) == 1) {
     colours_RSI <- rep(colours_RSI, 3)
   }
@@ -135,13 +143,14 @@ plot.mic <- function(x,
       legend_txt <- c(legend_txt, "Resistant")
       legend_col <- c(legend_col, colours_RSI[1])
     }
-    legend("top", 
+    legend("top",
            x.intersp = 0.5,
            legend = translate_AMR(legend_txt, language = language),
            fill = legend_col,
            horiz = TRUE,
-           cex = 0.75, 
-           box.lwd = 0, 
+           cex = 0.75,
+           box.lwd = 0,
+           box.col = "#FFFFFF55",
            bg = "#FFFFFF55")
   }
 }
@@ -170,6 +179,14 @@ barplot.mic <- function(height,
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
   meet_criteria(expand, allow_class = "logical", has_length = 1)
   
+  # translate if not specifically set
+  if (missing(ylab)) {
+    ylab <- translate_AMR(ylab, language = language)
+  }
+  if (missing(xlab)) {
+    xlab <- translate_AMR(xlab, language = language)
+  }
+  
   main <- gsub(" +", " ", paste0(main, collapse = " "))
   
   plot(x = height,
@@ -209,6 +226,14 @@ ggplot.mic <- function(data,
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
   meet_criteria(expand, allow_class = "logical", has_length = 1)
   
+  # translate if not specifically set
+  if (missing(ylab)) {
+    ylab <- translate_AMR(ylab, language = language)
+  }
+  if (missing(xlab)) {
+    xlab <- translate_AMR(xlab, language = language)
+  }
+  
   if ("main" %in% names(list(...))) {
     title <- list(...)$main
   }
@@ -285,6 +310,14 @@ plot.disk <- function(x,
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
   meet_criteria(expand, allow_class = "logical", has_length = 1)
   
+  # translate if not specifically set
+  if (missing(ylab)) {
+    ylab <- translate_AMR(ylab, language = language)
+  }
+  if (missing(xlab)) {
+    xlab <- translate_AMR(xlab, language = language)
+  }
+  
   if (length(colours_RSI) == 1) {
     colours_RSI <- rep(colours_RSI, 3)
   }
@@ -333,8 +366,9 @@ plot.disk <- function(x,
            legend = translate_AMR(legend_txt, language = language),
            fill = legend_col,
            horiz = TRUE,
-           cex = 0.75, 
-           box.lwd = 0, 
+           cex = 0.75,
+           box.lwd = 0,
+           box.col = "#FFFFFF55",
            bg = "#FFFFFF55")
   }
 }
@@ -363,6 +397,14 @@ barplot.disk <- function(height,
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
   meet_criteria(expand, allow_class = "logical", has_length = 1)
   
+  # translate if not specifically set
+  if (missing(ylab)) {
+    ylab <- translate_AMR(ylab, language = language)
+  }
+  if (missing(xlab)) {
+    xlab <- translate_AMR(xlab, language = language)
+  }
+  
   main <- gsub(" +", " ", paste0(main, collapse = " "))
   
   plot(x = height,
@@ -402,6 +444,14 @@ ggplot.disk <- function(data,
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
   meet_criteria(expand, allow_class = "logical", has_length = 1)
   
+  # translate if not specifically set
+  if (missing(ylab)) {
+    ylab <- translate_AMR(ylab, language = language)
+  }
+  if (missing(xlab)) {
+    xlab <- translate_AMR(xlab, language = language)
+  }
+  
   if ("main" %in% names(list(...))) {
     title <- list(...)$main
   }
@@ -454,79 +504,6 @@ ggplot.disk <- function(data,
     ggplot2::labs(title = title, x = xlab, y = ylab, subtitle = cols_sub$sub)
 }
 
-plot_prepare_table <- function(x, expand) {
-  if (is.mic(x)) {
-    if (expand == TRUE) {
-      # expand range for MIC by adding factors of 2 from lowest to highest so all MICs in between also print
-      extra_range <- max(x) / 2
-      while (min(extra_range) / 2 > min(x)) {
-        extra_range <- c(min(extra_range) / 2, extra_range)
-      }
-      nms <- extra_range
-      extra_range <- rep(0, length(extra_range))
-      names(extra_range) <- nms
-      x <- table(droplevels(x, as.mic = FALSE))
-      extra_range <- extra_range[!names(extra_range) %in% names(x)]
-      x <- as.table(c(x, extra_range))
-    } else {
-      x <- table(droplevels(x, as.mic = FALSE))
-    }
-    x <- x[order(as.double(as.mic(names(x))))]
-  } else if (is.disk(x)) {
-    if (expand == TRUE) {
-      # expand range for disks from lowest to highest so all mm's in between also print
-      extra_range <- rep(0, max(x) - min(x) - 1)
-      names(extra_range) <- seq(min(x) + 1, max(x) - 1)
-      x <- table(x)
-      extra_range <- extra_range[!names(extra_range) %in% names(x)]
-      x <- as.table(c(x, extra_range))
-    } else {
-      x <- table(x)
-    }
-    x <- x[order(as.double(names(x)))]
-  }
-  as.table(x)
-}
-
-plot_name_of_I <- function(guideline) {
-  if (!guideline %like% "CLSI" && as.double(gsub("[^0-9]+", "", guideline)) >= 2019) {
-    # interpretation since 2019
-    "Incr. exposure"
-  } else {
-    # interpretation until 2019
-    "Intermediate"
-  }
-}
-
-plot_colours_subtitle_guideline <- function(x, mo, ab, guideline, colours_RSI, fn, language, ...) {
-  guideline <- get_guideline(guideline, AMR::rsi_translation)
-  if (!is.null(mo) && !is.null(ab)) {
-    # interpret and give colour based on MIC values
-    mo <- as.mo(mo)
-    ab <- as.ab(ab)
-    rsi <- suppressWarnings(suppressMessages(as.rsi(fn(names(x)), mo = mo, ab = ab, guideline = guideline, ...)))
-    cols <- character(length = length(rsi))
-    cols[is.na(rsi)] <- "#BEBEBE"
-    cols[rsi == "R"] <- colours_RSI[1]
-    cols[rsi == "S"] <- colours_RSI[2]
-    cols[rsi == "I"] <- colours_RSI[3]
-    moname <- mo_name(mo, language = language)
-    abname <- ab_name(ab, language = language)
-    if (all(cols == "#BEBEBE")) {
-      message_("No ", guideline, " interpretations found for ", 
-               ab_name(ab, language = NULL, tolower = TRUE), " in ", moname)
-      guideline_txt <- ""
-    } else {
-      guideline_txt <- paste0("(", guideline, ")")
-    }
-    sub <- bquote(.(abname)~"in"~italic(.(moname))~.(guideline_txt))
-  } else {
-    cols <- "#BEBEBE"
-    sub <- NULL
-  }
-  list(cols = cols, count = as.double(x), sub = sub, guideline = guideline)
-}
-
 #' @method plot rsi
 #' @export
 #' @importFrom graphics plot text axis
@@ -599,6 +576,14 @@ barplot.rsi <- function(height,
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
   meet_criteria(expand, allow_class = "logical", has_length = 1)
   
+  # translate if not specifically set
+  if (missing(ylab)) {
+    ylab <- translate_AMR(ylab, language = language)
+  }
+  if (missing(xlab)) {
+    xlab <- translate_AMR(xlab, language = language)
+  }
+  
   if (length(colours_RSI) == 1) {
     colours_RSI <- rep(colours_RSI, 3)
   }
@@ -624,6 +609,7 @@ ggplot.rsi <- function(data,
                        xlab = "Antimicrobial Interpretation",
                        ylab = "Frequency",
                        colours_RSI = c("#ED553B", "#3CAEA3", "#F6D55C"),
+                       language = get_locale(),
                        ...) {
   stop_ifnot_installed("ggplot2")
   meet_criteria(title, allow_class = "character", allow_NULL = TRUE)
@@ -631,6 +617,14 @@ ggplot.rsi <- function(data,
   meet_criteria(xlab, allow_class = "character", has_length = 1)
   meet_criteria(colours_RSI, allow_class = "character", has_length = c(1, 3))
   
+  # translate if not specifically set
+  if (missing(ylab)) {
+    ylab <- translate_AMR(ylab, language = language)
+  }
+  if (missing(xlab)) {
+    xlab <- translate_AMR(xlab, language = language)
+  }
+  
   if ("main" %in% names(list(...))) {
     title <- list(...)$main
   }
@@ -658,3 +652,76 @@ ggplot.rsi <- function(data,
     ggplot2::labs(title = title, x = xlab, y = ylab) +
     ggplot2::theme(legend.position = "none")
 }
+
+plot_prepare_table <- function(x, expand) {
+  if (is.mic(x)) {
+    if (expand == TRUE) {
+      # expand range for MIC by adding factors of 2 from lowest to highest so all MICs in between also print
+      extra_range <- max(x) / 2
+      while (min(extra_range) / 2 > min(x)) {
+        extra_range <- c(min(extra_range) / 2, extra_range)
+      }
+      nms <- extra_range
+      extra_range <- rep(0, length(extra_range))
+      names(extra_range) <- nms
+      x <- table(droplevels(x, as.mic = FALSE))
+      extra_range <- extra_range[!names(extra_range) %in% names(x)]
+      x <- as.table(c(x, extra_range))
+    } else {
+      x <- table(droplevels(x, as.mic = FALSE))
+    }
+    x <- x[order(as.double(as.mic(names(x))))]
+  } else if (is.disk(x)) {
+    if (expand == TRUE) {
+      # expand range for disks from lowest to highest so all mm's in between also print
+      extra_range <- rep(0, max(x) - min(x) - 1)
+      names(extra_range) <- seq(min(x) + 1, max(x) - 1)
+      x <- table(x)
+      extra_range <- extra_range[!names(extra_range) %in% names(x)]
+      x <- as.table(c(x, extra_range))
+    } else {
+      x <- table(x)
+    }
+    x <- x[order(as.double(names(x)))]
+  }
+  as.table(x)
+}
+
+plot_name_of_I <- function(guideline) {
+  if (guideline %unlike% "CLSI" && as.double(gsub("[^0-9]+", "", guideline)) >= 2019) {
+    # interpretation since 2019
+    "Incr. exposure"
+  } else {
+    # interpretation until 2019
+    "Intermediate"
+  }
+}
+
+plot_colours_subtitle_guideline <- function(x, mo, ab, guideline, colours_RSI, fn, language, ...) {
+  guideline <- get_guideline(guideline, AMR::rsi_translation)
+  if (!is.null(mo) && !is.null(ab)) {
+    # interpret and give colour based on MIC values
+    mo <- as.mo(mo)
+    ab <- as.ab(ab)
+    rsi <- suppressWarnings(suppressMessages(as.rsi(fn(names(x)), mo = mo, ab = ab, guideline = guideline, ...)))
+    cols <- character(length = length(rsi))
+    cols[is.na(rsi)] <- "#BEBEBE"
+    cols[rsi == "R"] <- colours_RSI[1]
+    cols[rsi == "S"] <- colours_RSI[2]
+    cols[rsi == "I"] <- colours_RSI[3]
+    moname <- mo_name(mo, language = language)
+    abname <- ab_name(ab, language = language)
+    if (all(cols == "#BEBEBE")) {
+      message_("No ", guideline, " interpretations found for ", 
+               ab_name(ab, language = NULL, tolower = TRUE), " in ", moname)
+      guideline_txt <- ""
+    } else {
+      guideline_txt <- paste0("(", guideline, ")")
+    }
+    sub <- bquote(.(abname)~"-"~italic(.(moname))~.(guideline_txt))
+  } else {
+    cols <- "#BEBEBE"
+    sub <- NULL
+  }
+  list(cols = cols, count = as.double(x), sub = sub, guideline = guideline)
+}

R/rsi.R

@@ -263,9 +263,9 @@ as.rsi.default <- function(x, ...) {
     x[x == 2] <- "I"
     x[x == 3] <- "R"
     
-  } else if (!all(is.na(x)) && !identical(levels(x), c("S", "I", "R"))) {
-    
-    if (!any(x %like% "(R|S|I)", na.rm = TRUE)) {
+  } else if (!all(is.na(x)) && !identical(levels(x), c("S", "I", "R")) && !all(x %in% c("R", "S", "I", NA))) {
+
+    if (all(x %unlike% "(R|S|I)", na.rm = TRUE)) {
       # check if they are actually MICs or disks
       if (all_valid_mics(x)) {
         warning_("The input seems to be MIC values. Transform them with `as.mic()` before running `as.rsi()` to interpret them.")
@@ -683,7 +683,7 @@ get_guideline <- function(guideline, reference_data) {
   if (guideline_param %in% c("CLSI", "EUCAST")) {
     guideline_param <- rev(sort(subset(reference_data, guideline %like% guideline_param)$guideline))[1L]
   }
-  if (!guideline_param %like% " ") {
+  if (guideline_param %unlike% " ") {
     # like 'EUCAST2020', should be 'EUCAST 2020'
     guideline_param <- gsub("([a-z]+)([0-9]+)", "\\1 \\2", guideline_param, ignore.case = TRUE)
   }
@@ -776,7 +776,7 @@ exec_as.rsi <- function(method,
     any_is_intrinsic_resistant <- any_is_intrinsic_resistant | is_intrinsic_r
     
     if (isTRUE(add_intrinsic_resistance) & is_intrinsic_r) {
-      if (!guideline_coerced %like% "EUCAST") {
+      if (guideline_coerced %unlike% "EUCAST") {
         if (message_not_thrown_before("as.rsi2")) {
           warning_("Using 'add_intrinsic_resistance' is only useful when using EUCAST guidelines, since the rules for intrinsic resistance are based on EUCAST.", call = FALSE)
           remember_thrown_message("as.rsi2")

R/translate.R

@@ -157,11 +157,13 @@ translate_AMR <- function(from, language = get_locale(), only_unknown = FALSE, a
   df_trans$regular_expr[is.na(df_trans$regular_expr)] <- FALSE
   
   # check if text to look for is in one of the patterns
-  any_form_in_patterns <- tryCatch(any(from_unique %like% paste0("(", paste(df_trans$pattern, collapse = "|"), ")")),
-                                   error = function(e) {
-                                     warning_("Translation not possible. Please open an issue on GitHub (https://github.com/msberends/AMR/issues).", call = FALSE)
-                                     return(FALSE)
-                                   })
+  any_form_in_patterns <- tryCatch(
+    any(from_unique %like% paste0("(", paste(gsub(" +\\(.*", "", df_trans$pattern), collapse = "|"), ")")),
+    error = function(e) {
+      warning_("Translation not possible. Please open an issue on GitHub (https://github.com/msberends/AMR/issues).", call = FALSE)
+      return(FALSE)
+    })
+  
   if (NROW(df_trans) == 0 | !any_form_in_patterns) {
     return(from)
   }
@@ -170,7 +172,7 @@ translate_AMR <- function(from, language = get_locale(), only_unknown = FALSE, a
          function(i) from_unique_translated <<- gsub(pattern = df_trans$pattern[i],
                                                      replacement = df_trans[i, language, drop = TRUE],
                                                      x = from_unique_translated,
-                                                     ignore.case = !df_trans$case_sensitive[i], 
+                                                     ignore.case = !df_trans$case_sensitive[i] & df_trans$regular_expr[i], 
                                                      fixed = !df_trans$regular_expr[i],
                                                      perl = df_trans$regular_expr[i]))
   

R/zzz.R

@@ -61,20 +61,3 @@ pkg_env$mo_failed <- character(0)
     }
   }, silent = TRUE)
 }
-
-.onAttach <- function(...) {
-  # show notice in 10% of cases in interactive session
-  if (!interactive() || stats::runif(1) > 0.1 || isTRUE(as.logical(getOption("AMR_silentstart", FALSE)))) {
-    return()
-  }
-  packageStartupMessage(word_wrap("Thank you for using the AMR package! ",
-                                  "If you have a minute, please anonymously fill in this short questionnaire to improve the package and its functionalities: ",
-                                  font_blue("https://msberends.github.io/AMR/survey.html\n"),
-                                  "[prevent his notice with ",
-                                  font_bold("suppressPackageStartupMessages(library(AMR))"),
-                                  " or use ",
-                                  font_bold("options(AMR_silentstart = TRUE)"), "]"))
-}
-
-
-

_pkgdown.yml

@@ -143,6 +143,7 @@ reference:
     - "`as.mic`"
     - "`as.disk`"
     - "`eucast_rules`"
+    - "`custom_eucast_rules`"
     
   - title: "Analysing data: antimicrobial resistance"
     desc: >

data-raw/_internals.R

@@ -134,7 +134,7 @@ create_intr_resistance <- function() {
 
 
 
-# Save internal data sets to R/sysdata.rda --------------------------------
+# Save internal data to R/sysdata.rda -------------------------------------
 
 # See 'data-raw/eucast_rules.tsv' for the EUCAST reference file
 eucast_rules_file <- utils::read.delim(file = "data-raw/eucast_rules.tsv",
@@ -188,6 +188,35 @@ AB_lookup <- create_AB_lookup()
 MO_lookup <- create_MO_lookup()
 MO.old_lookup <- create_MO.old_lookup()
 
+# antibiotic groups
+# (these will also be used for eucast_rules() and understanding data-raw/eucast_rules.tsv)
+globalenv_before_ab <- c(ls(envir = globalenv()), "globalenv_before_ab")
+AMINOGLYCOSIDES <- antibiotics %>% filter(group %like% "aminoglycoside") %>% pull(ab)
+AMINOPENICILLINS <- as.ab(c("AMP", "AMX"))
+CARBAPENEMS <- antibiotics %>% filter(group %like% "carbapenem") %>% pull(ab)
+CEPHALOSPORINS <- antibiotics %>% filter(group %like% "cephalosporin") %>% pull(ab)
+CEPHALOSPORINS_1ST <- antibiotics %>% filter(group %like% "cephalosporin.*1") %>% pull(ab)
+CEPHALOSPORINS_2ND <- antibiotics %>% filter(group %like% "cephalosporin.*2") %>% pull(ab)
+CEPHALOSPORINS_3RD <- antibiotics %>% filter(group %like% "cephalosporin.*3") %>% pull(ab)
+CEPHALOSPORINS_EXCEPT_CAZ <- CEPHALOSPORINS[CEPHALOSPORINS != "CAZ"]
+FLUOROQUINOLONES <- antibiotics %>% filter(atc_group2 %like% "fluoroquinolone") %>% pull(ab)
+LIPOGLYCOPEPTIDES <- as.ab(c("DAL", "ORI", "TLV")) # dalba/orita/tela
+GLYCOPEPTIDES <- antibiotics %>% filter(group %like% "glycopeptide") %>% pull(ab)
+GLYCOPEPTIDES_EXCEPT_LIPO <- GLYCOPEPTIDES[!GLYCOPEPTIDES %in% LIPOGLYCOPEPTIDES]
+LINCOSAMIDES <- antibiotics %>% filter(atc_group2 %like% "lincosamide") %>% pull(ab) %>% c("PRL")
+MACROLIDES <- antibiotics %>% filter(atc_group2 %like% "macrolide") %>% pull(ab)
+OXAZOLIDINONES <- antibiotics %>% filter(group %like% "oxazolidinone") %>% pull(ab)
+PENICILLINS <- antibiotics %>% filter(group %like% "penicillin") %>% pull(ab)
+POLYMYXINS <- antibiotics %>% filter(group %like% "polymyxin") %>% pull(ab)
+STREPTOGRAMINS <- antibiotics %>% filter(atc_group2 %like% "streptogramin") %>% pull(ab)
+TETRACYCLINES <- antibiotics %>% filter(atc_group2 %like% "tetracycline") %>% pull(ab)
+TETRACYCLINES_EXCEPT_TGC <- TETRACYCLINES[TETRACYCLINES != "TGC"]
+UREIDOPENICILLINS <- as.ab(c("PIP", "TZP", "AZL", "MEZ"))
+BETALACTAMS <- c(PENICILLINS, CEPHALOSPORINS, CARBAPENEMS)
+
+DEFINED_AB_GROUPS <- ls(envir = globalenv())
+DEFINED_AB_GROUPS <- DEFINED_AB_GROUPS[!DEFINED_AB_GROUPS %in% globalenv_before_ab]
+
 # Export to package as internal data ----
 usethis::use_data(eucast_rules_file, 
                   translations_file,
@@ -199,6 +228,29 @@ usethis::use_data(eucast_rules_file,
                   AB_lookup,
                   MO_lookup,
                   MO.old_lookup,
+                  AMINOGLYCOSIDES,
+                  AMINOPENICILLINS,
+                  CARBAPENEMS,
+                  CEPHALOSPORINS,
+                  CEPHALOSPORINS_1ST,
+                  CEPHALOSPORINS_2ND,
+                  CEPHALOSPORINS_3RD,
+                  CEPHALOSPORINS_EXCEPT_CAZ,
+                  FLUOROQUINOLONES,
+                  LIPOGLYCOPEPTIDES,
+                  GLYCOPEPTIDES,
+                  GLYCOPEPTIDES_EXCEPT_LIPO,
+                  LINCOSAMIDES,
+                  MACROLIDES,
+                  OXAZOLIDINONES,
+                  PENICILLINS,
+                  POLYMYXINS,
+                  STREPTOGRAMINS,
+                  TETRACYCLINES,
+                  TETRACYCLINES_EXCEPT_TGC,
+                  UREIDOPENICILLINS,
+                  BETALACTAMS,
+                  DEFINED_AB_GROUPS,
                   internal = TRUE,
                   overwrite = TRUE,
                   version = 2,

data-raw/eucast_rules.tsv

@@ -1,7 +1,7 @@
 # -------------------------------------------------------------------------------------------------------------------------------
 # For editing this EUCAST reference file, these values can all be used for targeting antibiotics:
-# 'all_betalactams', 'aminoglycosides', 'aminopenicillins', 'carbapenems', 'cephalosporins', 'cephalosporins_1st', 'cephalosporins_2nd', 'cephalosporins_3rd', 'cephalosporins_except_CAZ',
-# 'fluoroquinolones', 'glycopeptides', 'lincosamides', 'lipoglycopeptides', 'macrolides', 'oxazolidinones', 'polymyxins', 'streptogramins', 'tetracyclines', 'ureidopenicillins',
+# 'betalactams', 'aminoglycosides', 'aminopenicillins', 'carbapenems', 'cephalosporins', 'cephalosporins_1st', 'cephalosporins_2nd', 'cephalosporins_3rd', 'cephalosporins_except_CAZ',
+# 'fluoroquinolones', 'glycopeptides', 'glycopeptides_except_lipo', 'lincosamides', 'lipoglycopeptides', 'macrolides', 'oxazolidinones', 'polymyxins', 'streptogramins', 'tetracyclines', 'tetracyclines_except_TGC', 'ureidopenicillins',
 # and all separate EARS-Net letter codes like 'AMC'. They can be separated by comma: 'AMC, fluoroquinolones'.
 # The 'if_mo_property' column can be any column name from the AMR::microorganisms data set, or "genus_species" or "gramstain".
 # The like.is.one_of column must be 'like' or 'is' or 'one_of' ('like' will read the 'this_value' column as regular expression)
@@ -14,7 +14,7 @@ order	is	Enterobacterales	AMP	I	AMX	I	Enterobacterales (Order)	Breakpoints	10
 order	is	Enterobacterales	AMP	R	AMX	R	Enterobacterales (Order)	Breakpoints	10	
 genus	is	Staphylococcus	PEN, FOX	S	AMP, AMX, PIP, TIC	S	Staphylococcus	Breakpoints	10	
 genus	is	Staphylococcus	PEN, FOX	R, S	OXA, FLC	S	Staphylococcus	Breakpoints	10	
-genus	is	Staphylococcus	FOX	R	all_betalactams	R	Staphylococcus	Breakpoints	10	
+genus	is	Staphylococcus	FOX	R	betalactams	R	Staphylococcus	Breakpoints	10	
 genus_species	is	Staphylococcus saprophyticus	AMP	S	AMX, AMC, PIP, TZP	S	Staphylococcus	Breakpoints	10	
 genus	is	Staphylococcus	FOX	S	carbapenems, cephalosporins_except_CAZ	S	Staphylococcus	Breakpoints	10	
 genus	is	Staphylococcus	FOX	I	carbapenems, cephalosporins_except_CAZ	I	Staphylococcus	Breakpoints	10	
@@ -120,7 +120,7 @@ order	is	Enterobacterales	AMP	I	AMX	I	Enterobacterales (Order)	Breakpoints	11
 order	is	Enterobacterales	AMP	R	AMX	R	Enterobacterales (Order)	Breakpoints	11	
 genus	is	Staphylococcus	PEN, FOX	S	AMP, AMX, PIP, TIC	S	Staphylococcus	Breakpoints	11	
 genus	is	Staphylococcus	PEN, FOX	R, S	OXA, FLC	S	Staphylococcus	Breakpoints	11	
-genus	is	Staphylococcus	FOX	R	all_betalactams	R	Staphylococcus	Breakpoints	11	
+genus	is	Staphylococcus	FOX	R	betalactams	R	Staphylococcus	Breakpoints	11	
 genus_species	is	Staphylococcus saprophyticus	AMP	S	AMX, AMC, PIP, TZP	S	Staphylococcus	Breakpoints	11	
 genus	is	Staphylococcus	FOX	S	carbapenems, cephalosporins_except_CAZ	S	Staphylococcus	Breakpoints	11	
 genus	is	Staphylococcus	FOX	I	carbapenems, cephalosporins_except_CAZ	I	Staphylococcus	Breakpoints	11	
@@ -224,7 +224,7 @@ genus_species	is	Burkholderia pseudomallei	TCY	R	DOX	R	Burkholderia pseudomallei
 genus	is	Bacillus	NOR	S	fluoroquinolones	S	Bacillus	Breakpoints	11	added in 11
 genus	is	Bacillus	NOR	I	fluoroquinolones	I	Bacillus	Breakpoints	11	added in 11
 genus	is	Bacillus	NOR	R	fluoroquinolones	R	Bacillus	Breakpoints	11	added in 11
-order	is	Enterobacterales			PEN, glycopeptides, FUS, macrolides, LIN, streptogramins, RIF, DAP, LNZ	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
+order	is	Enterobacterales			PEN, glycopeptides_except_lipo, FUS, macrolides, LIN, streptogramins, RIF, DAP, LNZ	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
 fullname	like	^Citrobacter (koseri|amalonaticus|sedlakii|farmeri|rodentium)			aminopenicillins, TIC	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
 fullname	like	^Citrobacter (freundii|braakii|murliniae|werkmanii|youngae)			aminopenicillins, AMC, CZO, FOX	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
 genus_species	is	Enterobacter cloacae			aminopenicillins, AMC, CZO, FOX	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
@@ -232,17 +232,17 @@ genus_species	is	Klebsiella aerogenes			aminopenicillins, AMC, CZO, FOX	R	Table
 genus_species	is	Escherichia hermannii			aminopenicillins, TIC	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
 genus_species	is	Hafnia alvei			aminopenicillins, AMC, CZO, FOX	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
 genus	is	Klebsiella			aminopenicillins, TIC	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
-genus_species	is	Morganella morganii			aminopenicillins, AMC, CZO, tetracyclines, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
-genus_species	is	Proteus mirabilis			tetracyclines, TGC, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
-genus_species	is	Proteus penneri			aminopenicillins, CZO, CXM, tetracyclines, TGC, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
-genus_species	is	Proteus vulgaris			aminopenicillins, CZO, CXM, tetracyclines, TGC, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
-genus_species	is	Providencia rettgeri			aminopenicillins, AMC, CZO, CXM, tetracyclines, TGC, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
-genus_species	is	Providencia stuartii			aminopenicillins, AMC, CZO, CXM, tetracyclines, TGC, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
+genus_species	is	Morganella morganii			aminopenicillins, AMC, CZO, DOX, MNO, TCY, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
+genus_species	is	Proteus mirabilis			DOX, MNO, TCY, TGC, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
+genus_species	is	Proteus penneri			aminopenicillins, CZO, CXM, DOX, MNO, TCY, TGC, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
+genus_species	is	Proteus vulgaris			aminopenicillins, CZO, CXM, DOX, MNO, TCY, TGC, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
+genus_species	is	Providencia rettgeri			aminopenicillins, AMC, CZO, CXM, DOX, MNO, TCY, TGC, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
+genus_species	is	Providencia stuartii			aminopenicillins, AMC, CZO, CXM, DOX, MNO, TCY, TGC, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
 genus	is	Raoultella			aminopenicillins, TIC	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
 genus_species	is	Serratia marcescens			aminopenicillins, AMC, CZO, FOX, CXM, DOX, TCY, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
 genus_species	is	Yersinia enterocolitica			aminopenicillins, AMC, TIC, CZO, FOX	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
 genus_species	is	Yersinia pseudotuberculosis			PLB, COL	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
-genus	one_of	Achromobacter, Acinetobacter, Alcaligenes, Bordetella, Burkholderia, Elizabethkingia, Flavobacterium, Ochrobactrum, Pseudomonas, Stenotrophomonas			PEN, FOX, CXM, glycopeptides, FUS, macrolides, LIN, streptogramins, RIF, DAP, LNZ	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
+genus	one_of	Achromobacter, Acinetobacter, Alcaligenes, Bordetella, Burkholderia, Elizabethkingia, Flavobacterium, Ochrobactrum, Pseudomonas, Stenotrophomonas			PEN, FOX, CXM, glycopeptides_except_lipo, FUS, macrolides, LIN, streptogramins, RIF, DAP, LNZ	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
 genus_species	is	Acinetobacter baumannii			aminopenicillins, AMC, CZO, CTX, CRO, ATM, ETP, TMP, FOS, DOX, TCY	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
 genus_species	is	Acinetobacter pittii			aminopenicillins, AMC, CZO, CTX, CRO, ATM, ETP, TMP, FOS, DOX, TCY	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
 genus_species	is	Acinetobacter nosocomialis			aminopenicillins, AMC, CZO, CTX, CRO, ATM, ETP, TMP, FOS, DOX, TCY	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
@@ -250,10 +250,10 @@ genus_species	is	Acinetobacter calcoaceticus			aminopenicillins, AMC, CZO, CTX,
 genus_species	is	Achromobacter xylosoxidans			aminopenicillins, CZO, CTX, CRO, ETP	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
 fullname	like	^Burkholderia (ambifaria|anthina|arboris|cepacia|cenocepacia|contaminans|diffusa|dolosa|lata|latens|metallica|multivorans|paludis|pseudomultivorans|pyrrocinia|pseudomultivorans|seminalis|stabilis|stagnalis|territorii|ubonensis|vietnamiensis)			aminopenicillins, AMC, TIC, PIP, TZP, CZO, CTX, CRO, ATM, ETP, CIP, CHL, aminoglycosides, TMP, FOS, polymyxins	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
 genus_species	is	Elizabethkingia meningoseptica			aminopenicillins, AMC, TIC, CZO, CTX, CRO, CAZ, FEP, ATM, ETP, IPM, MEM, polymyxins	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
-genus_species	is	Ochrobactrum anthropi			aminopenicillins, AMC, TIC, PIP, TZP, CZO, CTX, CRO, CAZ, FEP, ATM, ETP	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
-genus_species	is	Pseudomonas aeruginosa			aminopenicillins, AMC, CZO, CTX, CRO, ETP, CHL, KAN, NEO, TMP, SXT, tetracyclines, TGC	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
+genus_species	is	Brucella anthropi			aminopenicillins, AMC, TIC, PIP, TZP, CZO, CTX, CRO, CAZ, FEP, ATM, ETP	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
+genus_species	is	Pseudomonas aeruginosa			aminopenicillins, AMC, CZO, CTX, CRO, ETP, CHL, KAN, NEO, TMP, SXT, DOX, MNO, TCY, TGC	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
 genus_species	is	Stenotrophomonas maltophilia			aminopenicillins, AMC, TIC, PIP, TZP, CZO, CTX, CRO, ATM, ETP, IPM, MEM, aminoglycosides, TMP, FOS, TCY	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
-genus	one_of	Haemophilus, Moraxella, Neisseria, Campylobacter			glycopeptides, LIN, DAP, LNZ	R	Table 03: Intrinsic resistance in other Gram-negative bacteria	Expert Rules	3.1	
+genus	one_of	Haemophilus, Moraxella, Neisseria, Campylobacter			glycopeptides_except_lipo, LIN, DAP, LNZ	R	Table 03: Intrinsic resistance in other Gram-negative bacteria	Expert Rules	3.1	
 genus_species	is	Haemophilus influenzae			FUS, streptogramins	R	Table 03: Intrinsic resistance in other Gram-negative bacteria	Expert Rules	3.1	
 genus_species	is	Moraxella catarrhalis			TMP	R	Table 03: Intrinsic resistance in other Gram-negative bacteria	Expert Rules	3.1	
 genus	is	Neisseria			TMP	R	Table 03: Intrinsic resistance in other Gram-negative bacteria	Expert Rules	3.1	
@@ -279,8 +279,8 @@ genus_species	is	Enterococcus casseliflavus			FUS, CAZ, cephalosporins_except_CA
 genus_species	is	Enterococcus faecium			FUS, CAZ, cephalosporins_except_CAZ, aminoglycosides, macrolides, TMP, SXT	R	Table 04: Intrinsic resistance in Gram-positive bacteria	Expert Rules	3.1	
 genus	is	Corynebacterium			FOS	R	Table 04: Intrinsic resistance in Gram-positive bacteria	Expert Rules	3.1	
 genus_species	is	Listeria monocytogenes			cephalosporins	R	Table 04: Intrinsic resistance in Gram-positive bacteria	Expert Rules	3.1	
-genus	one_of	Leuconostoc, Pediococcus			glycopeptides	R	Table 04: Intrinsic resistance in Gram-positive bacteria	Expert Rules	3.1	
-genus	is	Lactobacillus			glycopeptides	R	Table 04: Intrinsic resistance in Gram-positive bacteria	Expert Rules	3.1	
+genus	one_of	Leuconostoc, Pediococcus			glycopeptides_except_lipo	R	Table 04: Intrinsic resistance in Gram-positive bacteria	Expert Rules	3.1	
+genus	is	Lactobacillus			glycopeptides_except_lipo	R	Table 04: Intrinsic resistance in Gram-positive bacteria	Expert Rules	3.1	
 genus_species	is	Clostridium ramosum			VAN	R	Table 04: Intrinsic resistance in Gram-positive bacteria	Expert Rules	3.1	
 genus_species	is	Clostridium innocuum			VAN	R	Table 04: Intrinsic resistance in Gram-positive bacteria	Expert Rules	3.1	
 genus_species	one_of	Streptococcus group A, Streptococcus group B, Streptococcus group C, Streptococcus group G	PEN	S	aminopenicillins, cephalosporins_except_CAZ, carbapenems	S	Table 08: Interpretive rules for B-lactam agents and Gram-positive cocci	Expert Rules	3.1	
@@ -298,7 +298,7 @@ genus	is	Staphylococcus	MFX	R	fluoroquinolones	R	Table 13: Interpretive rules fo
 genus_species	is	Streptococcus pneumoniae	MFX	R	fluoroquinolones	R	Table 13: Interpretive rules for quinolones	Expert Rules	3.1	
 order	is	Enterobacterales	CIP	R	fluoroquinolones	R	Table 13: Interpretive rules for quinolones	Expert Rules	3.1	
 genus_species	is	Neisseria gonorrhoeae	CIP	R	fluoroquinolones	R	Table 13: Interpretive rules for quinolones	Expert Rules	3.1	
-order	is	Enterobacterales			PEN, glycopeptides, lipoglycopeptides, FUS, macrolides, lincosamides, streptogramins, RIF, oxazolidinones	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
+order	is	Enterobacterales			PEN, glycopeptides_except_lipo, lipoglycopeptides, FUS, macrolides, lincosamides, streptogramins, RIF, oxazolidinones	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
 fullname	like	^Citrobacter (koseri|amalonaticus|sedlakii|farmeri|rodentium)			aminopenicillins, TIC	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
 fullname	like	^Citrobacter (freundii|braakii|murliniae|werkmanii|youngae)			aminopenicillins, AMC, SAM, CZO, CEP, LEX, CFR, FOX	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
 genus_species	is	Enterobacter cloacae			aminopenicillins, AMC, SAM, CZO, CEP, LEX, CFR, FOX	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
@@ -308,13 +308,13 @@ genus_species	is	Klebsiella aerogenes			aminopenicillins, AMC, SAM, CZO, CEP, LE
 genus_species	is	Klebsiella oxytoca			aminopenicillins, TIC	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
 fullname	like	^Klebsiella( pneumoniae| quasipneumoniae| variicola)?			aminopenicillins, TIC	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
 genus_species	is	Leclercia adecarboxylata			FOS	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
-genus_species	is	Morganella morganii			aminopenicillins, AMC, SAM, CZO, CEP, LEX, CFR, tetracyclines, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
+genus_species	is	Morganella morganii			aminopenicillins, AMC, SAM, CZO, CEP, LEX, CFR, DOX, MNO, TCY, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
 genus_species	is	Plesiomonas shigelloides			aminopenicillins, AMC, SAM	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
-genus_species	is	Proteus mirabilis			tetracyclines, TGC, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
-genus_species	is	Proteus penneri			aminopenicillins, CZO, CEP, LEX, CFR, CXM, tetracyclines, TGC, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
-genus_species	is	Proteus vulgaris			aminopenicillins, CZO, CEP, LEX, CFR, CXM, tetracyclines, TGC, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
-genus_species	is	Providencia rettgeri			aminopenicillins, AMC, SAM, CZO, CEP, LEX, CFR, tetracyclines, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
-genus_species	is	Providencia stuartii			aminopenicillins, AMC, SAM, CZO, CEP, LEX, CFR, tetracyclines, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
+genus_species	is	Proteus mirabilis			DOX, MNO, TCY, TGC, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
+genus_species	is	Proteus penneri			aminopenicillins, CZO, CEP, LEX, CFR, CXM, DOX, MNO, TCY, TGC, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
+genus_species	is	Proteus vulgaris			aminopenicillins, CZO, CEP, LEX, CFR, CXM, DOX, MNO, TCY, TGC, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
+genus_species	is	Providencia rettgeri			aminopenicillins, AMC, SAM, CZO, CEP, LEX, CFR, DOX, MNO, TCY, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
+genus_species	is	Providencia stuartii			aminopenicillins, AMC, SAM, CZO, CEP, LEX, CFR, DOX, MNO, TCY, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
 genus	is	Raoultella			aminopenicillins, TIC	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
 genus_species	is	Serratia marcescens			aminopenicillins, AMC, SAM, CZO, CEP, LEX, CFR, FOX, CXM, DOX, TCY, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
 genus_species	is	Yersinia enterocolitica			aminopenicillins, AMC, SAM, TIC, CZO, CEP, LEX, CFR, FOX	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
@@ -324,20 +324,20 @@ genus_species	is	Aeromonas veronii			aminopenicillins, AMC, SAM, FOX	R	Table 1:
 genus_species	is	Aeromonas dhakensis			aminopenicillins, AMC, SAM, FOX	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
 genus_species	is	Aeromonas caviae			aminopenicillins, AMC, SAM, FOX	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
 genus_species	is	Aeromonas jandaei			aminopenicillins, AMC, SAM, TIC,  CZO, CEP, LEX, CFR, FOX	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
-genus	one_of	Achromobacter, Acinetobacter, Alcaligenes, Bordetella, Burkholderia, Elizabethkingia, Flavobacterium, Ochrobactrum, Pseudomonas, Stenotrophomonas			PEN, cephalosporins_1st, cephalosporins_2nd, glycopeptides, lipoglycopeptides, FUS, macrolides, lincosamides, streptogramins, RIF, oxazolidinones	R	Table 2: Intrinsic resistance in non-fermentative gram-negative bacteria	Expert Rules	3.2	
+genus	one_of	Achromobacter, Acinetobacter, Alcaligenes, Bordetella, Burkholderia, Elizabethkingia, Flavobacterium, Ochrobactrum, Pseudomonas, Stenotrophomonas			PEN, cephalosporins_1st, cephalosporins_2nd, glycopeptides_except_lipo, lipoglycopeptides, FUS, macrolides, lincosamides, streptogramins, RIF, oxazolidinones	R	Table 2: Intrinsic resistance in non-fermentative gram-negative bacteria	Expert Rules	3.2	
 fullname	like	^Acinetobacter (baumannii|pittii|nosocomialis)			aminopenicillins, AMC, CRO, CTX, ATM, ETP, TMP, FOS, DOX, TCY	R	Table 2: Intrinsic resistance in non-fermentative gram-negative bacteria	Expert Rules	3.2	Additional rules from header added in separate rule (genus is one of…)
 genus	is	Acinetobacter			DOX, TCY	R	Table 2: Intrinsic resistance in non-fermentative gram-negative bacteria	Expert Rules	3.2	Additional rules from header added in separate rule (genus is one of…)
 genus_species	is	Achromobacter xylosoxidans 			aminopenicillins, CRO, CTX, ETP	R	Table 2: Intrinsic resistance in non-fermentative gram-negative bacteria	Expert Rules	3.2	Additional rules from header added in separate rule (genus is one of…)
 fullname	like	^Burkholderia (ambifaria|anthina|arboris|cepacia|cenocepacia|contaminans|diffusa|dolosa|lata|latens|metallica|multivorans|paludis|pseudomultivorans|pyrrocinia|pseudomultivorans|seminalis|stabilis|stagnalis|territorii|ubonensis|vietnamiensis)			aminopenicillins, AMC, SAM, TIC, TCC, PIP, TZP, CRO, CTX, ATM, ETP, CIP, CHL, aminoglycosides, TMP, FOS, polymyxins	R	Table 2: Intrinsic resistance in non-fermentative gram-negative bacteria	Expert Rules	3.2	Additional rules from header added in separate rule (genus is one of…)
 genus_species	is	Elizabethkingia meningoseptica			aminopenicillins, AMC, SAM, TIC, TCC, PIP, CZO, CTX, CRO, CAZ, FEP, ATM, ETP, IPM, MEM, polymyxins	R	Table 2: Intrinsic resistance in non-fermentative gram-negative bacteria	Expert Rules	3.2	Additional rules from header added in separate rule (genus is one of…)
-genus_species	is	Ochrobactrum anthropi			aminopenicillins, AMC, SAM, TIC, TCC, PIP, TZP, CZO, CTX, CRO, CAZ, FEP, ATM, ETP	R	Table 2: Intrinsic resistance in non-fermentative gram-negative bacteria	Expert Rules	3.2	Additional rules from header added in separate rule (genus is one of…)
-genus_species	is	Pseudomonas aeruginosa			aminopenicillins, AMC, SAM, CTX, CRO, ETP, CHL, KAN, NEO, TMP, tetracyclines, TGC	R	Table 2: Intrinsic resistance in non-fermentative gram-negative bacteria	Expert Rules	3.2	Additional rules from header added in separate rule (genus is one of…)
+genus_species	is	Brucella anthropi			aminopenicillins, AMC, SAM, TIC, TCC, PIP, TZP, CZO, CTX, CRO, CAZ, FEP, ATM, ETP	R	Table 2: Intrinsic resistance in non-fermentative gram-negative bacteria	Expert Rules	3.2	Additional rules from header added in separate rule (genus is one of…)
+genus_species	is	Pseudomonas aeruginosa			aminopenicillins, AMC, SAM, CTX, CRO, ETP, CHL, KAN, NEO, TMP, DOX, MNO, TCY, TGC	R	Table 2: Intrinsic resistance in non-fermentative gram-negative bacteria	Expert Rules	3.2	Additional rules from header added in separate rule (genus is one of…)
 genus_species	is	Stenotrophomonas maltophilia			aminopenicillins, AMC, SAM, TIC, PIP, TZP, CRO, CTX, ATM, ETP, IPM, MEM, aminoglycosides, TMP, FOS, TCY	R	Table 2: Intrinsic resistance in non-fermentative gram-negative bacteria	Expert Rules	3.2	Additional rules from header added in separate rule (genus is one of…)
-genus_species	is	Haemophilus influenzae			FUS, streptogramins, glycopeptides, lipoglycopeptides, lincosamides, oxazolidinones	R	Table 3: Intrinsic resistance in other gram-negative bacteria	Expert Rules	3.2	
-genus_species	is	Moraxella catarrhalis			TMP, glycopeptides, lipoglycopeptides, lincosamides, oxazolidinones	R	Table 3: Intrinsic resistance in other gram-negative bacteria	Expert Rules	3.2	
-genus	is	Neisseria			TMP, glycopeptides, lipoglycopeptides, lincosamides, oxazolidinones	R	Table 3: Intrinsic resistance in other gram-negative bacteria	Expert Rules	3.2	
-genus_species	is	Campylobacter fetus			FUS, streptogramins, TMP, NAL, glycopeptides, lipoglycopeptides, lincosamides, oxazolidinones	R	Table 3: Intrinsic resistance in other gram-negative bacteria	Expert Rules	3.2	
-fullname	like	^Campylobacter (jejuni|coli)			FUS, streptogramins, TMP, glycopeptides, lipoglycopeptides, lincosamides, oxazolidinones	R	Table 3: Intrinsic resistance in other gram-negative bacteria	Expert Rules	3.2	
+genus_species	is	Haemophilus influenzae			FUS, streptogramins, glycopeptides_except_lipo, lipoglycopeptides, lincosamides, oxazolidinones	R	Table 3: Intrinsic resistance in other gram-negative bacteria	Expert Rules	3.2	
+genus_species	is	Moraxella catarrhalis			TMP, glycopeptides_except_lipo, lipoglycopeptides, lincosamides, oxazolidinones	R	Table 3: Intrinsic resistance in other gram-negative bacteria	Expert Rules	3.2	
+genus	is	Neisseria			TMP, glycopeptides_except_lipo, lipoglycopeptides, lincosamides, oxazolidinones	R	Table 3: Intrinsic resistance in other gram-negative bacteria	Expert Rules	3.2	
+genus_species	is	Campylobacter fetus			FUS, streptogramins, TMP, NAL, glycopeptides_except_lipo, lipoglycopeptides, lincosamides, oxazolidinones	R	Table 3: Intrinsic resistance in other gram-negative bacteria	Expert Rules	3.2	
+fullname	like	^Campylobacter (jejuni|coli)			FUS, streptogramins, TMP, glycopeptides_except_lipo, lipoglycopeptides, lincosamides, oxazolidinones	R	Table 3: Intrinsic resistance in other gram-negative bacteria	Expert Rules	3.2	
 gramstain	is	Gram-positive			ATM, TEM, polymyxins, NAL	R	Table 4: Intrinsic resistance in gram-positive bacteria	Expert Rules	3.2	
 genus_species	is	Staphylococcus saprophyticus			FUS, CAZ, FOS, NOV	R	Table 4: Intrinsic resistance in gram-positive bacteria	Expert Rules	3.2	
 genus_species	is	Staphylococcus cohnii			CAZ, NOV	R	Table 4: Intrinsic resistance in gram-positive bacteria	Expert Rules	3.2	
@@ -372,8 +372,8 @@ fullname	like	^(Serratia|Providencia|Morganella morganii)			TGC	R	Expert Rules o
 genus	is	Salmonella			cephalosporins_2nd	R	Expert Rules on Salmonella	Expert Rules	3.2	
 genus	is	Salmonella			aminoglycosides	R	Expert Rules on Salmonella	Expert Rules	3.2	
 genus	is	Salmonella	PEF	R	CIP	R	Expert Rules on Salmonella	Expert Rules	3.2	
-genus_species	is	Staphylococcus aureus	FOX1	R	all_betalactams	R	Expert Rules on Staphylococcus	Expert Rules	3.2	
-genus_species	is	Staphylococcus aureus	FOX1	S	all_betalactams	S	Expert Rules on Staphylococcus	Expert Rules	3.2	
+genus_species	is	Staphylococcus aureus	FOX1	R	betalactams	R	Expert Rules on Staphylococcus	Expert Rules	3.2	
+genus_species	is	Staphylococcus aureus	FOX1	S	betalactams	S	Expert Rules on Staphylococcus	Expert Rules	3.2	
 genus_species	one_of	Staphylococcus aureus, Staphylococcus lugdunensis	PEN	R	AMP, AMX, AZL, BAM, CRB, CRN, EPC, HET, MEC, MEZ, MTM, PIP, PME, PVM, SBC, TAL, TEM, TIC	R	Expert Rules on Staphylococcus	Expert Rules	3.2	all penicillins without beta-lactamse inhibitor
 genus	is	Staphylococcus	ERY, CLI	S	macrolides, lincosamides	S	Expert Rules on Staphylococcus	Expert Rules	3.2	
 genus	is	Staphylococcus	NOR	S	CIP, LVX, MFX, OFX	S	Expert Rules on Staphylococcus	Expert Rules	3.2	
@@ -400,7 +400,7 @@ genus_species	is	Streptococcus pneumoniae	TCY	S	DOX, MNO	S	Expert Rules on Strep
 genus_species	is	Streptococcus pneumoniae	TCY	R	DOX, MNO	R	Expert Rules on Streptococcus pneumoniae	Expert Rules	3.2	
 genus_species	is	Streptococcus pneumoniae	VAN	S	lipoglycopeptides	S	Expert Rules on Streptococcus pneumoniae	Expert Rules	3.2	
 fullname	like	^Streptococcus (anginosus|australis|bovis|constellatus|cristatus|equinus|gallolyticus|gordonii|infantarius|infantis|intermedius|mitis|mutans|oligofermentans|oralis|parasanguinis|peroris|pseudopneumoniae|salivarius|sanguinis|sinensis|sobrinus|thermophilus|vestibularis|viridans)$	PEN	S	aminopenicillins, CTX, CRO	S	Expert Rules on Viridans Group Streptococci	Expert Rules	3.2	
-genus_species	is	Haemophilus influenzae 	PEN	S	all_betalactams	S	Expert Rules on Haemophilus influenzae	Expert Rules	3.2	
+genus_species	is	Haemophilus influenzae 	PEN	S	betalactams	S	Expert Rules on Haemophilus influenzae	Expert Rules	3.2	
 genus_species	is	Haemophilus influenzae 	NAL	S	fluoroquinolones	S	Expert Rules on Haemophilus influenzae	Expert Rules	3.2	
 genus_species	is	Haemophilus influenzae 	NAL	R	CIP, LVX, MFX	R	Expert Rules on Haemophilus influenzae	Expert Rules	3.2	
 genus_species	is	Haemophilus influenzae 	TCY	S	DOX, MNO	S	Expert Rules on Haemophilus influenzae	Expert Rules	3.2	

data-raw/read_EUCAST.R

@@ -136,8 +136,8 @@ read_EUCAST <- function(sheet, file, guideline_name) {
               disk_R = ifelse(has_zone_diameters, G, NA_character_)) %>% 
     filter(!is.na(drug),
            !(is.na(MIC_S) & is.na(MIC_R) & is.na(disk_S) & is.na(disk_R)),
-           !MIC_S %like% "(MIC|S ≤|note)",
-           !MIC_S %like% "^[-]",
+           MIC_S %unlike% "(MIC|S ≤|note)",
+           MIC_S %unlike% "^[-]",
            drug != MIC_S,) %>% 
     mutate(administration = case_when(drug %like% "[( ]oral" ~ "oral",
                                       drug %like% "[( ]iv"   ~ "iv",

data-raw/reproduction_of_antibiotics.R

@@ -114,8 +114,8 @@ abx_atc2 <- ab_old %>%
   filter(!atc %in% abx_atc1$atc,
          is.na(ears_net),
          !is.na(atc_group1),
-         !atc_group1 %like% ("virus|vaccin|viral|immun"),
-         !official %like% "(combinations| with )") %>%
+         atc_group1 %unlike% ("virus|vaccin|viral|immun"),
+         official %unlike% "(combinations| with )") %>%
   mutate(ab = NA_character_) %>%
   as.data.frame(stringsAsFactors = FALSE) %>%
   select(ab, atc, name = official)

data-raw/reproduction_of_microorganisms.R

@@ -382,7 +382,7 @@ MOs <- MOs %>%
 
 # what characters are in the fullnames?
 table(sort(unlist(strsplit(x = paste(MOs$fullname, collapse = ""), split = ""))))
-MOs %>% filter(!fullname %like% "^[a-z ]+$") %>% arrange(fullname) %>% View()
+MOs %>% filter(fullname %unlike% "^[a-z ]+$") %>% arrange(fullname) %>% View()
 
 table(MOs$kingdom, MOs$rank)
 table(AMR::microorganisms$kingdom, AMR::microorganisms$rank)

data-raw/reproduction_of_microorganisms_update.R

@@ -160,7 +160,7 @@ updated_microorganisms <- taxonomy %>%
                              TRUE ~ "subsp."),
             ref = get_author_year(authors),
             species_id = as.character(record_no),
-            source = "LSPN",
+            source = "LPSN",
             prevalence = 0,
             snomed = NA)
 

data-raw/reproduction_of_poorman.R

@@ -9,9 +9,9 @@ files <- xml2::read_html(paste0("https://github.com/nathaneastwood/poorman/tree/
 # get full URLs of all raw R files
 files <- sort(paste0("https://raw.githubusercontent.com", gsub("blob/", "", files[files %like% "/R/.*.R$"])))
 # remove files with only pkg specific code
-files <- files[!files %like% "(zzz|init)[.]R$"]
+files <- files[files %unlike% "(zzz|init)[.]R$"]
 # also, there's a lot of functions we don't use
-files <- files[!files %like% "(slice|glimpse|recode|replace_na|coalesce)[.]R$"]
+files <- files[files %unlike% "(slice|glimpse|recode|replace_na|coalesce)[.]R$"]
 
 # add our prepend file, containing info about the source of the data
 intro <- readLines("data-raw/poorman_prepend.R")

data-raw/translations.tsv

@@ -39,6 +39,10 @@ antibiotic	TRUE	TRUE	FALSE	Antibiotikum	antibioticum	antibiótico
 Antibiotic	TRUE	TRUE	FALSE	Antibiotikum	Antibioticum	Antibiótico			
 Drug	TRUE	TRUE	FALSE	Medikament	Middel	Fármaco			
 drug	TRUE	TRUE	FALSE	Medikament	middel	fármaco			
+Frequency	FALSE	TRUE	FALSE	Zahl	Aantal				
+Minimum Inhibitory Concentration (mg/L)	FALSE	FALSE	FALSE	Minimale Hemm-Konzentration (mg/L)	Minimale inhiberende concentratie (mg/L)				
+Disk diffusion diameter (mm)	FALSE	FALSE	FALSE	Durchmesser der Scheibenzone (mm)	Diameter diskzone (mm)				
+Antimicrobial Interpretation	FALSE	FALSE	FALSE	Antimikrobielle Auswertung	Antimicrobiële interpretatie				
 4-aminosalicylic acid	FALSE	TRUE	FALSE	4-Aminosalicylsäure	4-aminosalicylzuur	Ácido 4-aminosalicílico			
 Adefovir dipivoxil	FALSE	TRUE	FALSE	Adefovir Dipivoxil	Adefovir	Adefovir dipivoxil			
 Aldesulfone sodium	FALSE	TRUE	FALSE	Aldesulfon-Natrium	Aldesulfon	Aldesulfona sódica			

docs/404.html

@@ -81,7 +81,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="https://msberends.github.io/AMR//index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9009</span>
       </span>
     </div>
 

docs/LICENSE-text.html

@@ -81,7 +81,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9009</span>
       </span>
     </div>
 

docs/articles/index.html

@@ -81,7 +81,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9009</span>
       </span>
     </div>
 

docs/authors.html

@@ -81,7 +81,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9009</span>
       </span>
     </div>
 
@@ -236,13 +236,13 @@
       <small class="dont-index">Source: <a href='https://github.com/msberends/AMR/blob/master/inst/CITATION'><code>inst/CITATION</code></a></small>
     </div>
 
-    <p>Berends MS, Luz CF et al. (2019). AMR - An R Package for Working with Antimicrobial Resistance Data. bioRxiv, https://doi.org/10.1101/810622</p>
+    <p>Berends MS, Luz CF et al. (2021). AMR - An R Package for Working with Antimicrobial Resistance Data. bioRxiv, https://doi.org/10.1101/810622</p>
     <pre>@Article{,
   title = {AMR - An R Package for Working with Antimicrobial Resistance Data},
   author = {M S Berends and C F Luz and A W Friedrich and B N M Sinha and C J Albers and C Glasner},
   journal = {bioRxiv},
   publisher = {Cold Spring Harbor Laboratory},
-  year = {2019},
+  year = {2021},
   url = {https://doi.org/10.1101/810622},
 }</pre>
 

docs/index.html

@@ -19,11 +19,10 @@
 <!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="pkgdown.css" rel="stylesheet">
 <script src="pkgdown.js"></script><link href="extra.css" rel="stylesheet">
 <script src="extra.js"></script><meta property="og:title" content="Antimicrobial Resistance Data Analysis">
-<meta property="og:description" content="Functions to simplify the analysis and prediction of Antimicrobial 
-    Resistance (AMR) and to work with microbial and antimicrobial properties by
-    using evidence-based methods, like those defined by Leclercq et al. (2013) 
-    &lt;doi:10.1111/j.1469-0691.2011.03703.x&gt; and containing reference data such as 
-    LPSN &lt;doi:10.1099/ijsem.0.004332&gt;.">
+<meta property="og:description" content="Functions to simplify and standardise antimicrobial resistance (AMR)
+    data analysis and to work with microbial and antimicrobial properties by
+    using evidence-based methods and reliable reference data such as LPSN
+    &lt;doi:10.1099/ijsem.0.004332&gt;.">
 <meta property="og:image" content="https://msberends.github.io/AMR/logo.png">
 <!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
@@ -43,7 +42,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9009</span>
       </span>
     </div>
 
@@ -197,16 +196,12 @@
 <div class="page-header"><h1 class="hasAnchor">
 <a href="#amr-for-r-" class="anchor"></a><code>AMR</code> (for R) <img src="./logo.png" align="right" height="120px">
 </h1></div>
-<p><em>Note: the rules of ‘EUCAST Clinical Breakpoints v11.0 (2021)’ are now implemented</em></p>
-<blockquote>
-<p><span class="fa fa-clipboard-list" style="color: #128f76; font-size: 20pt; margin-right: 5px;"></span> <strong>PLEASE TAKE PART IN OUR SURVEY!</strong><br>
-Since you are one of our users, we would like to know how you use the package and what it brought you or your organisation. <strong>If you have a minute, please <a href="./survey.html">anonymously fill in this short questionnaire</a></strong>. Your valuable input will help to improve the package and its functionalities. You can answer the open questions in either English, Spanish, French, Dutch, or German. Thank you very much in advance! <br><a class="btn btn-info btn-amr" href="./survey.html">Take me to the 5-min survey!</a></p>
-</blockquote>
+<p><em>Note: the rules of ‘EUCAST Clinical Breakpoints v11.0 (2021)’ are now implemented.</em></p>
 <div id="what-is-amr-for-r" class="section level3">
 <h3 class="hasAnchor">
 <a href="#what-is-amr-for-r" class="anchor"></a>What is <code>AMR</code> (for R)?</h3>
 <p><em>(To find out how to conduct AMR data analysis, please <a href="./articles/AMR.html">continue reading here to get started</a>.)</em></p>
-<p><code>AMR</code> is a free, open-source and independent <a href="https://www.r-project.org">R package</a> to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. <strong>Our aim is to provide a standard</strong> for clean and reproducible antimicrobial resistance data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.</p>
+<p><code>AMR</code> is a free, open-source and independent <a href="https://www.r-project.org">R package</a> to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. <strong>Our aim is to provide a standard</strong> for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.</p>
 <p>After installing this package, R knows <a href="./reference/microorganisms.html"><strong>~70,000 distinct microbial species</strong></a> and all <a href="./reference/antibiotics.html"><strong>~550 antibiotic, antimycotic and antiviral drugs</strong></a> by name and code (including ATC, EARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data.</p>
 <p>This package is <a href="https://en.wikipedia.org/wiki/Dependency_hell">fully independent of any other R package</a> and works on Windows, macOS and Linux with all versions of R since R-3.0.0 (April 2013). <strong>It was designed to work in any setting, including those with very limited resources</strong>. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the <a href="https://www.rug.nl">University of Groningen</a>, in collaboration with non-profit organisations <a href="https://www.certe.nl">Certe Medical Diagnostics and Advice Foundation</a> and <a href="https://www.umcg.nl">University Medical Center Groningen</a>. This R package is <a href="./news">actively maintained</a> and is free software (see <a href="#copyright">Copyright</a>).</p>
 <div class="main-content" style="display: inline-block;">

docs/news/index.html

@@ -81,7 +81,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9009</span>
       </span>
     </div>
 
@@ -236,14 +236,76 @@
       <small>Source: <a href='https://github.com/msberends/AMR/blob/master/NEWS.md'><code>NEWS.md</code></a></small>
     </div>
 
-    <div id="amr-160" class="section level1">
-<h1 class="page-header" data-toc-text="1.6.0">
-<a href="#amr-160" class="anchor"></a>AMR 1.6.0<small> Unreleased </small>
+    <div id="amr-1609009" class="section level1">
+<h1 class="page-header" data-toc-text="1.6.0.9009">
+<a href="#amr-1609009" class="anchor"></a>AMR 1.6.0.9009<small> Unreleased </small>
 </h1>
+<div id="last-updated-23-april-2021" class="section level2">
+<h2 class="hasAnchor">
+<a href="#last-updated-23-april-2021" class="anchor"></a><small>Last updated: 23 April 2021</small>
+</h2>
 <div id="new" class="section level3">
 <h3 class="hasAnchor">
 <a href="#new" class="anchor"></a>New</h3>
 <ul>
+<li>Function <code><a href="../reference/custom_eucast_rules.html">custom_eucast_rules()</a></code> that brings support for custom AMR rules in <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>
+</li>
+</ul>
+</div>
+<div id="changed" class="section level3">
+<h3 class="hasAnchor">
+<a href="#changed" class="anchor"></a>Changed</h3>
+<ul>
+<li>Custom MDRO guidelines (<code><a href="../reference/mdro.html">mdro()</a></code>, <code><a href="../reference/mdro.html">custom_mdro_guideline()</a></code>):
+<ul>
+<li>Custom MDRO guidelines can now be combined with other custom MDRO guidelines using <code><a href="https://rdrr.io/r/base/c.html">c()</a></code>
+</li>
+<li>Fix for applying the rules; in previous versions, rows were interpreted according to the last matched rule. Now, rows are interpreted according to the first matched rule</li>
+</ul>
+</li>
+<li>Fix for <code><a href="../reference/age_groups.html">age_groups()</a></code> for persons aged zero</li>
+<li>The <code>example_isolates</code> data set now contains some (fictitious) zero-year old patients</li>
+<li>Fix for minor translation errors</li>
+<li>Printing of microbial codes in a <code>data.frame</code> or <code>tibble</code> now gives a warning if the data contains old microbial codes (from a previous AMR package version)</li>
+<li>
+<code><a href="../reference/first_isolate.html">first_isolate()</a></code> can now take a vector of values for <code>col_keyantibiotics</code> and can have an episode length of <code>Inf</code>
+</li>
+<li>Extended the <code><a href="../reference/like.html">like()</a></code> functions:
+<ul>
+<li><p>Now checks if <code>pattern</code> is a <em>valid</em> regular expression</p></li>
+<li>
+<p>Added <code><a href="../reference/like.html">%unlike%</a></code> and <code><a href="../reference/like.html">%unlike_case%</a></code> (as negations of the existing <code><a href="../reference/like.html">%like%</a></code> and <code><a href="../reference/like.html">%like_case%</a></code>). This greatly improves readability:</p>
+<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
+<code class="sourceCode R">
+<span class="kw">if</span> <span class="op">(</span><span class="op">!</span><span class="fu"><a href="https://rdrr.io/r/base/grep.html">grepl</a></span><span class="op">(</span><span class="st">"EUCAST"</span>, <span class="va">guideline</span><span class="op">)</span><span class="op">)</span> <span class="va">...</span>
+<span class="co"># same:</span>
+<span class="kw">if</span> <span class="op">(</span><span class="va">guideline</span> <span class="op">%unlike%</span> <span class="st">"EUCAST"</span><span class="op">)</span> <span class="va">...</span></code></pre></div>
+</li>
+<li><p>Altered the RStudio addin, so it now iterates over <code><a href="../reference/like.html">%like%</a></code> -&gt; <code><a href="../reference/like.html">%unlike%</a></code> -&gt; <code><a href="../reference/like.html">%like_case%</a></code> -&gt; <code><a href="../reference/like.html">%unlike_case%</a></code> if you keep pressing your keyboard shortcut</p></li>
+</ul>
+</li>
+<li>Fixed an installation error on R-3.0</li>
+<li>Added <code>info</code> argument to <code><a href="../reference/as.mo.html">as.mo()</a></code> to turn on/off the progress bar</li>
+<li>Fixed a bug that <code>col_mo</code> for some functions (esp. <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> and <code><a href="../reference/mdro.html">mdro()</a></code>) could not be column names of the <code>microorganisms</code> data set as it would throw an error</li>
+<li>Using <code><a href="../reference/first_isolate.html">first_isolate()</a></code> with key antibiotics:
+<ul>
+<li>Fixed a bug in the algorithm when using <code>type == "points"</code>, that now leads to inclusion of slightly more isolates</li>
+<li>Big speed improvement for <code><a href="../reference/key_antibiotics.html">key_antibiotics_equal()</a></code> when using <code>type == "points"</code>
+</li>
+</ul>
+</li>
+</ul>
+</div>
+</div>
+</div>
+    <div id="amr-160" class="section level1">
+<h1 class="page-header" data-toc-text="1.6.0">
+<a href="#amr-160" class="anchor"></a>AMR 1.6.0<small> 2021-03-14 </small>
+</h1>
+<div id="new-1" class="section level3">
+<h3 class="hasAnchor">
+<a href="#new-1" class="anchor"></a>New</h3>
+<ul>
 <li>
 <p>Support for EUCAST Clinical Breakpoints v11.0 (2021), effective in the <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function and in <code><a href="../reference/as.rsi.html">as.rsi()</a></code> to interpret MIC and disk diffusion values. This is now the default guideline in this package.</p>
 <ul>
@@ -265,7 +327,7 @@
 </li>
 <li>
 <p>Functions <code><a href="../reference/antibiotic_class_selectors.html">oxazolidinones()</a></code> (an antibiotic selector function) and <code><a href="../reference/filter_ab_class.html">filter_oxazolidinones()</a></code> (an antibiotic filter function) to select/filter on e.g. linezolid and tedizolid</p>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>
 <span class="va">x</span> <span class="op">&lt;-</span> <span class="va">example_isolates</span> <span class="op">%&gt;%</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span><span class="op">(</span><span class="va">date</span>, <span class="va">hospital_id</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">oxazolidinones</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span>
@@ -275,10 +337,10 @@
 <span class="co">#&gt; Filtering on oxazolidinones: value in column `LNZ` (linezolid) is either "R", "S" or "I"</span></code></pre></div>
 </li>
 <li><p>Support for custom MDRO guidelines, using the new <code><a href="../reference/mdro.html">custom_mdro_guideline()</a></code> function, please see <code><a href="../reference/mdro.html">mdro()</a></code> for additional info</p></li>
-<li><p><code><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot()</a></code> generics for classes <code>&lt;mic&gt;</code> and <code>&lt;disk&gt;</code></p></li>
+<li><p><code>ggplot()</code> generics for classes <code>&lt;mic&gt;</code> and <code>&lt;disk&gt;</code></p></li>
 <li>
 <p>Function <code><a href="../reference/mo_property.html">mo_is_yeast()</a></code>, which determines whether a microorganism is a member of the taxonomic class Saccharomycetes or the taxonomic order Saccharomycetales:</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="fu"><a href="../reference/mo_property.html">mo_kingdom</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"Aspergillus"</span>, <span class="st">"Candida"</span><span class="op">)</span><span class="op">)</span>
 <span class="co">#&gt; [1] "Fungi" "Fungi"</span>
@@ -290,7 +352,7 @@
 <span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/which.html">which</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_is_yeast</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span>, <span class="op">]</span>   <span class="co"># base R</span>
 <span class="va">example_isolates</span> <span class="op">%&gt;%</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_is_yeast</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="co"># dplyr</span></code></pre></div>
 <p>The <code><a href="../reference/mo_property.html">mo_type()</a></code> function has also been updated to reflect this change:</p>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="fu"><a href="../reference/mo_property.html">mo_type</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"Aspergillus"</span>, <span class="st">"Candida"</span><span class="op">)</span><span class="op">)</span>
 <span class="co"># [1] "Fungi"  "Yeasts"</span>
@@ -300,7 +362,7 @@
 <li><p>Added Pretomanid (PMD, J04AK08) to the <code>antibiotics</code> data set</p></li>
 <li>
 <p>MIC values (see <code><a href="../reference/as.mic.html">as.mic()</a></code>) can now be used in any mathematical processing, such as usage inside functions <code><a href="https://rdrr.io/r/base/Extremes.html">min()</a></code>, <code><a href="https://rdrr.io/r/base/Extremes.html">max()</a></code>, <code><a href="https://rdrr.io/r/base/range.html">range()</a></code>, and with binary operators (<code><a href="https://rdrr.io/r/base/Arithmetic.html">+</a></code>, <code><a href="https://rdrr.io/r/base/Arithmetic.html">-</a></code>, etc.). This allows for easy distribution analysis and fast filtering on MIC values:</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="va">x</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/random.html">random_mic</a></span><span class="op">(</span><span class="fl">10</span><span class="op">)</span>
 <span class="va">x</span>
@@ -316,11 +378,11 @@
 </li>
 </ul>
 </div>
-<div id="changed" class="section level3">
+<div id="changed-1" class="section level3">
 <h3 class="hasAnchor">
-<a href="#changed" class="anchor"></a>Changed</h3>
+<a href="#changed-1" class="anchor"></a>Changed</h3>
 <ul>
-<li>Updated the bacterial taxonomy to 3 March 2021 (using <a href="https://lpsn.dsmz.de">LSPN</a>)
+<li>Updated the bacterial taxonomy to 3 March 2021 (using <a href="https://lpsn.dsmz.de">LPSN</a>)
 <ul>
 <li>Added 3,372 new species and 1,523 existing species became synomyms</li>
 <li>The URL of a bacterial species (<code><a href="../reference/mo_property.html">mo_url()</a></code>) will now lead to <a href="https://lpsn.dsmz.de" class="uri">https://lpsn.dsmz.de</a>
@@ -332,7 +394,7 @@
 <li>Plotting of MIC and disk diffusion values now support interpretation colouring if you supply the microorganism and antimicrobial agent</li>
 <li>All colours were updated to colour-blind friendly versions for values R, S and I for all plot methods (also applies to tibble printing)</li>
 <li>Interpretation of MIC and disk diffusion values to R/SI will now be translated if the system language is German, Dutch or Spanish (see <code>translate</code>)</li>
-<li>Plotting is now possible with base R using <code><a href="../reference/plot.html">plot()</a></code> and with ggplot2 using <code><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot()</a></code> on any vector of MIC and disk diffusion values</li>
+<li>Plotting is now possible with base R using <code><a href="../reference/plot.html">plot()</a></code> and with ggplot2 using <code>ggplot()</code> on any vector of MIC and disk diffusion values</li>
 </ul>
 </li>
 <li>Updated SNOMED codes to US Edition of SNOMED CT from 1 September 2020 and added the source to the help page of the <code>microorganisms</code> data set</li>
@@ -378,13 +440,13 @@
 <h1 class="page-header" data-toc-text="1.5.0">
 <a href="#amr-150" class="anchor"></a>AMR 1.5.0<small> 2021-01-06 </small>
 </h1>
-<div id="new-1" class="section level3">
+<div id="new-2" class="section level3">
 <h3 class="hasAnchor">
-<a href="#new-1" class="anchor"></a>New</h3>
+<a href="#new-2" class="anchor"></a>New</h3>
 <ul>
 <li>
 <p>Functions <code><a href="../reference/get_episode.html">get_episode()</a></code> and <code><a href="../reference/get_episode.html">is_new_episode()</a></code> to determine (patient) episodes which are not necessarily based on microorganisms. The <code><a href="../reference/get_episode.html">get_episode()</a></code> function returns the index number of the episode per group, while the <code><a href="../reference/get_episode.html">is_new_episode()</a></code> function returns values <code>TRUE</code>/<code>FALSE</code> to indicate whether an item in a vector is the start of a new episode. They also support <code>dplyr</code>s grouping (i.e. using <code><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by()</a></code>):</p>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>
 <span class="va">example_isolates</span> <span class="op">%&gt;%</span>
@@ -396,9 +458,9 @@
 <li><p>Functions <code><a href="../reference/random.html">random_mic()</a></code>, <code><a href="../reference/random.html">random_disk()</a></code> and <code><a href="../reference/random.html">random_rsi()</a></code> for random value generation. The functions <code><a href="../reference/random.html">random_mic()</a></code> and <code><a href="../reference/random.html">random_disk()</a></code> take microorganism names and antibiotic names as input to make generation more realistic.</p></li>
 </ul>
 </div>
-<div id="changed-1" class="section level3">
+<div id="changed-2" class="section level3">
 <h3 class="hasAnchor">
-<a href="#changed-1" class="anchor"></a>Changed</h3>
+<a href="#changed-2" class="anchor"></a>Changed</h3>
 <ul>
 <li><p>New argument <code>ampc_cephalosporin_resistance</code> in <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> to correct for AmpC de-repressed cephalosporin-resistant mutants</p></li>
 <li>
@@ -438,7 +500,7 @@
 <code><a href="../reference/mdro.html">mdr_cmi2012()</a></code>,</li>
 <li><code><a href="../reference/mdro.html">eucast_exceptional_phenotypes()</a></code></li>
 </ul>
-<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="co"># to select first isolates that are Gram-negative </span>
 <span class="co"># and view results of cephalosporins and aminoglycosides:</span>
@@ -450,7 +512,7 @@
 </li>
 <li>
 <p>For antibiotic selection functions (such as <code><a href="../reference/antibiotic_class_selectors.html">cephalosporins()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">aminoglycosides()</a></code>) to select columns based on a certain antibiotic group, the dependency on the <code>tidyselect</code> package was removed, meaning that they can now also be used without the need to have this package installed and now also work in base R function calls (they rely on R 3.2 or later):</p>
-<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="co"># above example in base R:</span>
 <span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/which.html">which</a></span><span class="op">(</span><span class="fu"><a href="../reference/first_isolate.html">first_isolate</a></span><span class="op">(</span><span class="op">)</span> <span class="op">&amp;</span> <span class="fu"><a href="../reference/mo_property.html">mo_is_gram_negative</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span>,
@@ -492,16 +554,16 @@
 <h1 class="page-header" data-toc-text="1.4.0">
 <a href="#amr-140" class="anchor"></a>AMR 1.4.0<small> 2020-10-08 </small>
 </h1>
-<div id="new-2" class="section level3">
+<div id="new-3" class="section level3">
 <h3 class="hasAnchor">
-<a href="#new-2" class="anchor"></a>New</h3>
+<a href="#new-3" class="anchor"></a>New</h3>
 <ul>
 <li><p>Support for ‘EUCAST Expert Rules’ / ‘EUCAST Intrinsic Resistance and Unusual Phenotypes’ version 3.2 of May 2020. With this addition to the previously implemented version 3.1 of 2016, the <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function can now correct for more than 180 different antibiotics and the <code><a href="../reference/mdro.html">mdro()</a></code> function can determine multidrug resistance based on more than 150 different antibiotics. All previously implemented versions of the EUCAST rules are now maintained and kept available in this package. The <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function consequently gained the arguments <code>version_breakpoints</code> (at the moment defaults to v10.0, 2020) and <code>version_expertrules</code> (at the moment defaults to v3.2, 2020). The <code>example_isolates</code> data set now also reflects the change from v3.1 to v3.2. The <code><a href="../reference/mdro.html">mdro()</a></code> function now accepts <code>guideline == "EUCAST3.1"</code> and <code>guideline == "EUCAST3.2"</code>.</p></li>
 <li><p>A new vignette and website page with info about all our public and freely available data sets, that can be downloaded as flat files or in formats for use in R, SPSS, SAS, Stata and Excel: <a href="https://msberends.github.io/AMR/articles/datasets.html" class="uri">https://msberends.github.io/AMR/articles/datasets.html</a></p></li>
 <li>
 <p>Data set <code>intrinsic_resistant</code>. This data set contains all bug-drug combinations where the ‘bug’ is intrinsic resistant to the ‘drug’ according to the latest EUCAST insights. It contains just two columns: <code>microorganism</code> and <code>antibiotic</code>.</p>
 <p>Curious about which enterococci are actually intrinsic resistant to vancomycin?</p>
-<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span>
 <span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>
@@ -514,9 +576,9 @@
 <li><p>Support for skimming classes <code>&lt;rsi&gt;</code>, <code>&lt;mic&gt;</code>, <code>&lt;disk&gt;</code> and <code>&lt;mo&gt;</code> with the <code>skimr</code> package</p></li>
 </ul>
 </div>
-<div id="changed-2" class="section level3">
+<div id="changed-3" class="section level3">
 <h3 class="hasAnchor">
-<a href="#changed-2" class="anchor"></a>Changed</h3>
+<a href="#changed-3" class="anchor"></a>Changed</h3>
 <ul>
 <li><p>Although advertised that this package should work under R 3.0.0, we still had a dependency on R 3.6.0. This is fixed, meaning that our package should now work under R 3.0.0.</p></li>
 <li>
@@ -524,7 +586,7 @@
 <ul>
 <li>
 <p>Support for using <code>dplyr</code>’s <code><a href="https://dplyr.tidyverse.org/reference/across.html">across()</a></code> to interpret MIC values or disk zone diameters, which also automatically determines the column with microorganism names or codes.</p>
-<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="co"># until dplyr 1.0.0</span>
 <span class="va">your_data</span> <span class="op">%&gt;%</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html">mutate_if</a></span><span class="op">(</span><span class="va">is.mic</span>, <span class="va">as.rsi</span><span class="op">)</span>
@@ -542,7 +604,7 @@
 </li>
 <li>
 <p>Added intelligent data cleaning to <code><a href="../reference/as.disk.html">as.disk()</a></code>, so numbers can also be extracted from text and decimal numbers will always be rounded up:</p>
-<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="fu"><a href="../reference/as.disk.html">as.disk</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"disk zone: 23.4 mm"</span>, <span class="fl">23.4</span><span class="op">)</span><span class="op">)</span>
 <span class="co">#&gt; Class &lt;disk&gt;</span>
@@ -596,14 +658,14 @@
 <h1 class="page-header" data-toc-text="1.3.0">
 <a href="#amr-130" class="anchor"></a>AMR 1.3.0<small> 2020-07-31 </small>
 </h1>
-<div id="new-3" class="section level3">
+<div id="new-4" class="section level3">
 <h3 class="hasAnchor">
-<a href="#new-3" class="anchor"></a>New</h3>
+<a href="#new-4" class="anchor"></a>New</h3>
 <ul>
 <li><p>Function <code><a href="../reference/ab_from_text.html">ab_from_text()</a></code> to retrieve antimicrobial drug names, doses and forms of administration from clinical texts in e.g. health care records, which also corrects for misspelling since it uses <code><a href="../reference/as.ab.html">as.ab()</a></code> internally</p></li>
 <li>
 <p><a href="https://tidyselect.r-lib.org/reference/language.html">Tidyverse selection helpers</a> for antibiotic classes, that help to select the columns of antibiotics that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations. They can be used in any function that allows selection helpers, like <code><a href="https://dplyr.tidyverse.org/reference/select.html">dplyr::select()</a></code> and <code><a href="https://tidyr.tidyverse.org/reference/pivot_longer.html">tidyr::pivot_longer()</a></code>:</p>
-<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>
 
@@ -620,9 +682,9 @@
 <li><p>Added argument <code>conserve_capped_values</code> to <code><a href="../reference/as.rsi.html">as.rsi()</a></code> for interpreting MIC values - it makes sure that values starting with “&lt;” (but not “&lt;=”) will always return “S” and values starting with “&gt;” (but not “&gt;=”) will always return “R”. The default behaviour of <code><a href="../reference/as.rsi.html">as.rsi()</a></code> has not changed, so you need to specifically do <code><a href="../reference/as.rsi.html">as.rsi(..., conserve_capped_values = TRUE)</a></code>.</p></li>
 </ul>
 </div>
-<div id="changed-3" class="section level3">
+<div id="changed-4" class="section level3">
 <h3 class="hasAnchor">
-<a href="#changed-3" class="anchor"></a>Changed</h3>
+<a href="#changed-4" class="anchor"></a>Changed</h3>
 <ul>
 <li>
 <p>Big speed improvement for using any function on microorganism codes from earlier package versions (prior to <code>AMR</code> v1.2.0), such as <code><a href="../reference/as.mo.html">as.mo()</a></code>, <code><a href="../reference/mo_property.html">mo_name()</a></code>, <code><a href="../reference/first_isolate.html">first_isolate()</a></code>, <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>, <code><a href="../reference/mdro.html">mdro()</a></code>, etc.</p>
@@ -696,9 +758,9 @@
 </li>
 </ul>
 </div>
-<div id="changed-4" class="section level3">
+<div id="changed-5" class="section level3">
 <h3 class="hasAnchor">
-<a href="#changed-4" class="anchor"></a>Changed</h3>
+<a href="#changed-5" class="anchor"></a>Changed</h3>
 <ul>
 <li>Taxonomy:
 <ul>
@@ -743,17 +805,17 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <h1 class="page-header" data-toc-text="1.1.0">
 <a href="#amr-110" class="anchor"></a>AMR 1.1.0<small> 2020-04-15 </small>
 </h1>
-<div id="new-4" class="section level3">
+<div id="new-5" class="section level3">
 <h3 class="hasAnchor">
-<a href="#new-4" class="anchor"></a>New</h3>
+<a href="#new-5" class="anchor"></a>New</h3>
 <ul>
 <li>Support for easy principal component analysis for AMR, using the new <code><a href="../reference/pca.html">pca()</a></code> function</li>
 <li>Plotting biplots for principal component analysis using the new <code><a href="../reference/ggplot_pca.html">ggplot_pca()</a></code> function</li>
 </ul>
 </div>
-<div id="changed-5" class="section level3">
+<div id="changed-6" class="section level3">
 <h3 class="hasAnchor">
-<a href="#changed-5" class="anchor"></a>Changed</h3>
+<a href="#changed-6" class="anchor"></a>Changed</h3>
 <ul>
 <li>Improvements for the algorithm used by <code><a href="../reference/as.mo.html">as.mo()</a></code> (and consequently all <code>mo_*</code> functions, that use <code><a href="../reference/as.mo.html">as.mo()</a></code> internally):
 <ul>
@@ -785,14 +847,14 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <h1 class="page-header" data-toc-text="1.0.1">
 <a href="#amr-101" class="anchor"></a>AMR 1.0.1<small> 2020-02-23 </small>
 </h1>
-<div id="changed-6" class="section level3">
+<div id="changed-7" class="section level3">
 <h3 class="hasAnchor">
-<a href="#changed-6" class="anchor"></a>Changed</h3>
+<a href="#changed-7" class="anchor"></a>Changed</h3>
 <ul>
 <li><p>Fixed important floating point error for some MIC comparisons in EUCAST 2020 guideline</p></li>
 <li>
 <p>Interpretation from MIC values (and disk zones) to R/SI can now be used with <code><a href="https://dplyr.tidyverse.org/reference/mutate_all.html">mutate_at()</a></code> of the <code>dplyr</code> package:</p>
-<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="va">yourdata</span> <span class="op">%&gt;%</span> 
   <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html">mutate_at</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span><span class="op">(</span><span class="va">antibiotic1</span><span class="op">:</span><span class="va">antibiotic25</span><span class="op">)</span>, <span class="va">as.rsi</span>, mo <span class="op">=</span> <span class="st">"E. coli"</span><span class="op">)</span>
@@ -811,9 +873,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <a href="#amr-100" class="anchor"></a>AMR 1.0.0<small> 2020-02-17 </small>
 </h1>
 <p>This software is now out of beta and considered stable. Nonetheless, this package will be developed continually.</p>
-<div id="new-5" class="section level3">
+<div id="new-6" class="section level3">
 <h3 class="hasAnchor">
-<a href="#new-5" class="anchor"></a>New</h3>
+<a href="#new-6" class="anchor"></a>New</h3>
 <ul>
 <li>Support for the newest <a href="https://www.eucast.org/clinical_breakpoints/">EUCAST Clinical Breakpoint Tables v.10.0</a>, valid from 1 January 2020. This affects translation of MIC and disk zones using <code><a href="../reference/as.rsi.html">as.rsi()</a></code> and inferred resistance and susceptibility using <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>.</li>
 <li>The repository of this package now contains a clean version of the EUCAST and CLSI guidelines from 2011-2020 to translate MIC and disk diffusion values to R/SI: <a href="https://github.com/msberends/AMR/blob/master/data-raw/rsi_translation.txt" class="uri">https://github.com/msberends/AMR/blob/master/data-raw/rsi_translation.txt</a>. This <strong>allows for machine reading these guidelines</strong>, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. This file used to process the EUCAST Clinical Breakpoints Excel file <a href="https://github.com/msberends/AMR/blob/master/data-raw/read_EUCAST.R">can be found here</a>.</li>
@@ -821,7 +883,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <ul>
 <li>
 <p>Support for LOINC codes in the <code>antibiotics</code> data set. Use <code><a href="../reference/ab_property.html">ab_loinc()</a></code> to retrieve LOINC codes, or use a LOINC code for input in any <code>ab_*</code> function:</p>
-<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="fu"><a href="../reference/ab_property.html">ab_loinc</a></span><span class="op">(</span><span class="st">"ampicillin"</span><span class="op">)</span>
 <span class="co">#&gt; [1] "21066-6" "3355-5"  "33562-0" "33919-2" "43883-8" "43884-6" "87604-5"</span>
@@ -832,7 +894,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 </li>
 <li>
 <p>Support for SNOMED CT codes in the <code>microorganisms</code> data set. Use <code><a href="../reference/mo_property.html">mo_snomed()</a></code> to retrieve SNOMED codes, or use a SNOMED code for input in any <code>mo_*</code> function:</p>
-<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="fu"><a href="../reference/mo_property.html">mo_snomed</a></span><span class="op">(</span><span class="st">"S. aureus"</span><span class="op">)</span>
 <span class="co">#&gt; [1] 115329001   3092008 113961008</span>
@@ -897,11 +959,11 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <ul>
 <li>
 <p>If you were dependent on the old Enterobacteriaceae family e.g. by using in your code:</p>
-<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="kw">if</span> <span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_family</a></span><span class="op">(</span><span class="va">somebugs</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Enterobacteriaceae"</span><span class="op">)</span> <span class="va">...</span></code></pre></div>
 <p>then please adjust this to:</p>
-<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="kw">if</span> <span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_order</a></span><span class="op">(</span><span class="va">somebugs</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Enterobacterales"</span><span class="op">)</span> <span class="va">...</span></code></pre></div>
 </li>
@@ -909,13 +971,13 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 </li>
 </ul>
 </div>
-<div id="new-6" class="section level3">
+<div id="new-7" class="section level3">
 <h3 class="hasAnchor">
-<a href="#new-6" class="anchor"></a>New</h3>
+<a href="#new-7" class="anchor"></a>New</h3>
 <ul>
 <li>
 <p>Functions <code><a href="../reference/proportion.html">susceptibility()</a></code> and <code><a href="../reference/proportion.html">resistance()</a></code> as aliases of <code><a href="../reference/proportion.html">proportion_SI()</a></code> and <code><a href="../reference/proportion.html">proportion_R()</a></code>, respectively. These functions were added to make it more clear that “I” should be considered susceptible and not resistant.</p>
-<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb18"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>
 <span class="va">example_isolates</span> <span class="op">%&gt;%</span>
@@ -944,7 +1006,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li><p>More intelligent way of coping with some consonants like “l” and “r”</p></li>
 <li>
 <p>Added a score (a certainty percentage) to <code><a href="../reference/as.mo.html">mo_uncertainties()</a></code>, that is calculated using the <a href="https://en.wikipedia.org/wiki/Levenshtein_distance">Levenshtein distance</a>:</p>
-<div class="sourceCode" id="cb18"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb19"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"Stafylococcus aureus"</span>,
         <span class="st">"staphylokok aureuz"</span><span class="op">)</span><span class="op">)</span>
@@ -1003,14 +1065,14 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <ul>
 <li>
 <p>Determination of first isolates now <strong>excludes</strong> all ‘unknown’ microorganisms at default, i.e. microbial code <code>"UNKNOWN"</code>. They can be included with the new argument <code>include_unknown</code>:</p>
-<div class="sourceCode" id="cb19"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb20"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="fu"><a href="../reference/first_isolate.html">first_isolate</a></span><span class="op">(</span><span class="va">...</span>, include_unknown <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></code></pre></div>
 <p>For WHONET users, this means that all records/isolates with organism code <code>"con"</code> (<em>contamination</em>) will be excluded at default, since <code>as.mo("con") = "UNKNOWN"</code>. The function always shows a note with the number of ‘unknown’ microorganisms that were included or excluded.</p>
 </li>
 <li>
 <p>For code consistency, classes <code>ab</code> and <code>mo</code> will now be preserved in any subsetting or assignment. For the sake of data integrity, this means that invalid assignments will now result in <code>NA</code>:</p>
-<div class="sourceCode" id="cb20"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb21"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="co"># how it works in base R:</span>
 <span class="va">x</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/factor.html">factor</a></span><span class="op">(</span><span class="st">"A"</span><span class="op">)</span>
@@ -1029,13 +1091,13 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li><p>Renamed data set <code>septic_patients</code> to <code>example_isolates</code></p></li>
 </ul>
 </div>
-<div id="new-7" class="section level3">
+<div id="new-8" class="section level3">
 <h3 class="hasAnchor">
-<a href="#new-7" class="anchor"></a>New</h3>
+<a href="#new-8" class="anchor"></a>New</h3>
 <ul>
 <li>
 <p>Function <code><a href="../reference/bug_drug_combinations.html">bug_drug_combinations()</a></code> to quickly get a <code>data.frame</code> with the results of all bug-drug combinations in a data set. The column containing microorganism codes is guessed automatically and its input is transformed with <code><a href="../reference/mo_property.html">mo_shortname()</a></code> at default:</p>
-<div class="sourceCode" id="cb21"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb22"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="va">x</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/bug_drug_combinations.html">bug_drug_combinations</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">)</span>
 <span class="co">#&gt; NOTE: Using column `mo` as input for `col_mo`.</span>
@@ -1058,13 +1120,13 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <span class="co">#&gt; 4 Gram-negative AMX 227  0 405   632</span>
 <span class="co">#&gt; NOTE: Use 'format()' on this result to get a publicable/printable format.</span></code></pre></div>
 <p>You can format this to a printable format, ready for reporting or exporting to e.g. Excel with the base R <code><a href="https://rdrr.io/r/base/format.html">format()</a></code> function:</p>
-<div class="sourceCode" id="cb22"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb23"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="fu"><a href="https://rdrr.io/r/base/format.html">format</a></span><span class="op">(</span><span class="va">x</span>, combine_IR <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></code></pre></div>
 </li>
 <li>
 <p>Additional way to calculate co-resistance, i.e. when using multiple antimicrobials as input for <code>portion_*</code> functions or <code>count_*</code> functions. This can be used to determine the empiric susceptibility of a combination therapy. A new argument <code>only_all_tested</code> (<strong>which defaults to <code>FALSE</code></strong>) replaces the old <code>also_single_tested</code> and can be used to select one of the two methods to count isolates and calculate portions. The difference can be seen in this example table (which is also on the <code>portion</code> and <code>count</code> help pages), where the %SI is being determined:</p>
-<div class="sourceCode" id="cb23"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb24"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="co"># --------------------------------------------------------------------</span>
 <span class="co">#                     only_all_tested = FALSE  only_all_tested = TRUE</span>
@@ -1086,7 +1148,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 </li>
 <li>
 <p><code>tibble</code> printing support for classes <code>rsi</code>, <code>mic</code>, <code>disk</code>, <code>ab</code> <code>mo</code>. When using <code>tibble</code>s containing antimicrobial columns, values <code>S</code> will print in green, values <code>I</code> will print in yellow and values <code>R</code> will print in red. Microbial IDs (class <code>mo</code>) will emphasise on the genus and species, not on the kingdom.</p>
-<div class="sourceCode" id="cb24"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb25"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="co"># (run this on your own console, as this page does not support colour printing)</span>
 <span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>
@@ -1096,9 +1158,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 </li>
 </ul>
 </div>
-<div id="changed-7" class="section level3">
+<div id="changed-8" class="section level3">
 <h3 class="hasAnchor">
-<a href="#changed-7" class="anchor"></a>Changed</h3>
+<a href="#changed-8" class="anchor"></a>Changed</h3>
 <ul>
 <li>Many algorithm improvements for <code><a href="../reference/as.mo.html">as.mo()</a></code> (of which some led to additions to the <code>microorganisms</code> data set). Many thanks to all contributors that helped improving the algorithms.
 <ul>
@@ -1163,13 +1225,13 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <h1 class="page-header" data-toc-text="0.7.1">
 <a href="#amr-071" class="anchor"></a>AMR 0.7.1<small> 2019-06-23 </small>
 </h1>
-<div id="new-8" class="section level4">
+<div id="new-9" class="section level4">
 <h4 class="hasAnchor">
-<a href="#new-8" class="anchor"></a>New</h4>
+<a href="#new-9" class="anchor"></a>New</h4>
 <ul>
 <li>
 <p>Function <code><a href="../reference/proportion.html">rsi_df()</a></code> to transform a <code>data.frame</code> to a data set containing only the microbial interpretation (S, I, R), the antibiotic, the percentage of S/I/R and the number of available isolates. This is a convenient combination of the existing functions <code><a href="../reference/count.html">count_df()</a></code> and <code>portion_df()</code> to immediately show resistance percentages and number of available isolates:</p>
-<div class="sourceCode" id="cb25"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb26"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="va">septic_patients</span> <span class="op">%&gt;%</span>
   <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span><span class="op">(</span><span class="va">AMX</span>, <span class="va">CIP</span><span class="op">)</span> <span class="op">%&gt;%</span>
@@ -1196,7 +1258,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li>UPEC (Uropathogenic <em>E. coli</em>)</li>
 </ul>
 <p>All these lead to the microbial ID of <em>E. coli</em>:</p>
-<div class="sourceCode" id="cb26"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb27"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"UPEC"</span><span class="op">)</span>
 <span class="co"># B_ESCHR_COL</span>
@@ -1209,9 +1271,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li><p>Function <code><a href="../reference/mo_property.html">mo_synonyms()</a></code> to get all previously accepted taxonomic names of a microorganism</p></li>
 </ul>
 </div>
-<div id="changed-8" class="section level4">
+<div id="changed-9" class="section level4">
 <h4 class="hasAnchor">
-<a href="#changed-8" class="anchor"></a>Changed</h4>
+<a href="#changed-9" class="anchor"></a>Changed</h4>
 <ul>
 <li>Column names of output <code><a href="../reference/count.html">count_df()</a></code> and <code>portion_df()</code> are now lowercase</li>
 <li>Fixed bug in translation of microorganism names</li>
@@ -1248,9 +1310,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <h1 class="page-header" data-toc-text="0.7.0">
 <a href="#amr-070" class="anchor"></a>AMR 0.7.0<small> 2019-06-03 </small>
 </h1>
-<div id="new-9" class="section level4">
+<div id="new-10" class="section level4">
 <h4 class="hasAnchor">
-<a href="#new-9" class="anchor"></a>New</h4>
+<a href="#new-10" class="anchor"></a>New</h4>
 <ul>
 <li>Support for translation of disk diffusion and MIC values to RSI values (i.e. antimicrobial interpretations). Supported guidelines are EUCAST (2011 to 2019) and CLSI (2011 to 2019). Use <code><a href="../reference/as.rsi.html">as.rsi()</a></code> on an MIC value (created with <code><a href="../reference/as.mic.html">as.mic()</a></code>), a disk diffusion value (created with the new <code><a href="../reference/as.disk.html">as.disk()</a></code>) or on a complete date set containing columns with MIC or disk diffusion values.</li>
 <li>Function <code><a href="../reference/mo_property.html">mo_name()</a></code> as alias of <code><a href="../reference/mo_property.html">mo_fullname()</a></code>
@@ -1258,9 +1320,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li>Added guidelines of the WHO to determine multi-drug resistance (MDR) for TB (<code><a href="../reference/mdro.html">mdr_tb()</a></code>) and added a new vignette about MDR. Read this tutorial <a href="https://msberends.gitlab.io/AMR/articles/MDR.html">here on our website</a>.</li>
 </ul>
 </div>
-<div id="changed-9" class="section level4">
+<div id="changed-10" class="section level4">
 <h4 class="hasAnchor">
-<a href="#changed-9" class="anchor"></a>Changed</h4>
+<a href="#changed-10" class="anchor"></a>Changed</h4>
 <ul>
 <li>Fixed a critical bug in <code><a href="../reference/first_isolate.html">first_isolate()</a></code> where missing species would lead to incorrect FALSEs. This bug was not present in AMR v0.5.0, but was in v0.6.0 and v0.6.1.</li>
 <li>Fixed a bug in <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> where antibiotics from WHONET software would not be recognised</li>
@@ -1301,7 +1363,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li><p>when all values are unique it now shows a message instead of a warning</p></li>
 <li>
 <p>support for boxplots:</p>
-<div class="sourceCode" id="cb27"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb28"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="va">septic_patients</span> <span class="op">%&gt;%</span> 
   <span class="fu">freq</span><span class="op">(</span><span class="va">age</span><span class="op">)</span> <span class="op">%&gt;%</span> 
@@ -1345,9 +1407,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <h1 class="page-header" data-toc-text="0.6.1">
 <a href="#amr-061" class="anchor"></a>AMR 0.6.1<small> 2019-03-29 </small>
 </h1>
-<div id="changed-10" class="section level4">
+<div id="changed-11" class="section level4">
 <h4 class="hasAnchor">
-<a href="#changed-10" class="anchor"></a>Changed</h4>
+<a href="#changed-11" class="anchor"></a>Changed</h4>
 <ul>
 <li>Fixed a critical bug when using <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> with <code>verbose = TRUE</code>
 </li>
@@ -1365,9 +1427,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li>Contains the complete manual of this package and all of its functions with an explanation of their arguments</li>
 <li>Contains a comprehensive tutorial about how to conduct AMR data analysis, import data from WHONET or SPSS and many more.</li>
 </ul>
-<div id="new-10" class="section level4">
+<div id="new-11" class="section level4">
 <h4 class="hasAnchor">
-<a href="#new-10" class="anchor"></a>New</h4>
+<a href="#new-11" class="anchor"></a>New</h4>
 <ul>
 <li><p><strong>BREAKING</strong>: removed deprecated functions, arguments and references to ‘bactid’. Use <code><a href="../reference/as.mo.html">as.mo()</a></code> to identify an MO code.</p></li>
 <li>
@@ -1396,7 +1458,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 </li>
 <li>
 <p>New filters for antimicrobial classes. Use these functions to filter isolates on results in one of more antibiotics from a specific class:</p>
-<div class="sourceCode" id="cb28"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb29"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="fu"><a href="../reference/filter_ab_class.html">filter_aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>
 <span class="fu"><a href="../reference/filter_ab_class.html">filter_carbapenems</a></span><span class="op">(</span><span class="op">)</span>
@@ -1410,7 +1472,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <span class="fu"><a href="../reference/filter_ab_class.html">filter_macrolides</a></span><span class="op">(</span><span class="op">)</span>
 <span class="fu"><a href="../reference/filter_ab_class.html">filter_tetracyclines</a></span><span class="op">(</span><span class="op">)</span></code></pre></div>
 <p>The <code>antibiotics</code> data set will be searched, after which the input data will be checked for column names with a value in any abbreviations, codes or official names found in the <code>antibiotics</code> data set. For example:</p>
-<div class="sourceCode" id="cb29"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb30"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="va">septic_patients</span> <span class="op">%&gt;%</span> <span class="fu"><a href="../reference/filter_ab_class.html">filter_glycopeptides</a></span><span class="op">(</span>result <span class="op">=</span> <span class="st">"R"</span><span class="op">)</span>
 <span class="co"># Filtering on glycopeptide antibacterials: any of `vanc` or `teic` is R</span>
@@ -1419,7 +1481,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 </li>
 <li>
 <p>All <code>ab_*</code> functions are deprecated and replaced by <code>atc_*</code> functions:</p>
-<div class="sourceCode" id="cb30"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb31"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="va">ab_property</span> <span class="op">-&gt;</span> <span class="fu">atc_property</span><span class="op">(</span><span class="op">)</span>
 <span class="va">ab_name</span> <span class="op">-&gt;</span> <span class="fu">atc_name</span><span class="op">(</span><span class="op">)</span>
@@ -1440,7 +1502,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li><p>New function <code><a href="../reference/age_groups.html">age_groups()</a></code> to split ages into custom or predefined groups (like children or elderly). This allows for easier demographic AMR data analysis per age group.</p></li>
 <li>
 <p>New function <code><a href="../reference/resistance_predict.html">ggplot_rsi_predict()</a></code> as well as the base R <code><a href="../reference/plot.html">plot()</a></code> function can now be used for resistance prediction calculated with <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code>:</p>
-<div class="sourceCode" id="cb31"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb32"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="va">x</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/resistance_predict.html">resistance_predict</a></span><span class="op">(</span><span class="va">septic_patients</span>, col_ab <span class="op">=</span> <span class="st">"amox"</span><span class="op">)</span>
 <span class="fu"><a href="../reference/plot.html">plot</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
@@ -1448,13 +1510,13 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 </li>
 <li>
 <p>Functions <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code> and <code><a href="../reference/first_isolate.html">filter_first_weighted_isolate()</a></code> to shorten and fasten filtering on data sets with antimicrobial results, e.g.:</p>
-<div class="sourceCode" id="cb32"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb33"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="va">septic_patients</span> <span class="op">%&gt;%</span> <span class="fu"><a href="../reference/first_isolate.html">filter_first_isolate</a></span><span class="op">(</span><span class="va">...</span><span class="op">)</span>
 <span class="co"># or</span>
 <span class="fu"><a href="../reference/first_isolate.html">filter_first_isolate</a></span><span class="op">(</span><span class="va">septic_patients</span>, <span class="va">...</span><span class="op">)</span></code></pre></div>
 <p>is equal to:</p>
-<div class="sourceCode" id="cb33"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb34"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="va">septic_patients</span> <span class="op">%&gt;%</span>
   <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span><span class="op">(</span>only_firsts <span class="op">=</span> <span class="fu"><a href="../reference/first_isolate.html">first_isolate</a></span><span class="op">(</span><span class="va">septic_patients</span>, <span class="va">...</span><span class="op">)</span><span class="op">)</span> <span class="op">%&gt;%</span>
@@ -1465,9 +1527,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li><p>New vignettes about how to conduct AMR analysis, predict antimicrobial resistance, use the <em>G</em>-test and more. These are also available (and even easier readable) on our website: <a href="https://msberends.gitlab.io/AMR" class="uri">https://msberends.gitlab.io/AMR</a>.</p></li>
 </ul>
 </div>
-<div id="changed-11" class="section level4">
+<div id="changed-12" class="section level4">
 <h4 class="hasAnchor">
-<a href="#changed-11" class="anchor"></a>Changed</h4>
+<a href="#changed-12" class="anchor"></a>Changed</h4>
 <ul>
 <li>Function <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>:
 <ul>
@@ -1487,7 +1549,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <ul>
 <li>
 <p>Now handles incorrect spelling, like <code>i</code> instead of <code>y</code> and <code>f</code> instead of <code>ph</code>:</p>
-<div class="sourceCode" id="cb34"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb35"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="co"># mo_fullname() uses as.mo() internally</span>
 
@@ -1499,7 +1561,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 </li>
 <li>
 <p>Uncertainty of the algorithm is now divided into four levels, 0 to 3, where the default <code>allow_uncertain = TRUE</code> is equal to uncertainty level 2. Run <code><a href="../reference/as.mo.html">?as.mo</a></code> for more info about these levels.</p>
-<div class="sourceCode" id="cb35"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb36"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="co"># equal:</span>
 <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="va">...</span>, allow_uncertain <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>
@@ -1514,7 +1576,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li><p>All microbial IDs that found are now saved to a local file <code>~/.Rhistory_mo</code>. Use the new function <code>clean_mo_history()</code> to delete this file, which resets the algorithms.</p></li>
 <li>
 <p>Incoercible results will now be considered ‘unknown’, MO code <code>UNKNOWN</code>. On foreign systems, properties of these will be translated to all languages already previously supported: German, Dutch, French, Italian, Spanish and Portuguese:</p>
-<div class="sourceCode" id="cb36"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb37"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="st">"qwerty"</span>, language <span class="op">=</span> <span class="st">"es"</span><span class="op">)</span>
 <span class="co"># Warning: </span>
@@ -1564,7 +1626,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <ul>
 <li>
 <p>Support for tidyverse quasiquotation! Now you can create frequency tables of function outcomes:</p>
-<div class="sourceCode" id="cb37"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb38"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="co"># Determine genus of microorganisms (mo) in `septic_patients` data set:</span>
 <span class="co"># OLD WAY</span>
@@ -1611,9 +1673,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <h1 class="page-header" data-toc-text="0.5.0">
 <a href="#amr-050" class="anchor"></a>AMR 0.5.0<small> 2018-11-30 </small>
 </h1>
-<div id="new-11" class="section level4">
+<div id="new-12" class="section level4">
 <h4 class="hasAnchor">
-<a href="#new-11" class="anchor"></a>New</h4>
+<a href="#new-12" class="anchor"></a>New</h4>
 <ul>
 <li>Repository moved to GitLab</li>
 <li>Function <code>count_all</code> to get all available isolates (that like all <code>portion_*</code> and <code>count_*</code> functions also supports <code>summarise</code> and <code>group_by</code>), the old <code>n_rsi</code> is now an alias of <code>count_all</code>
@@ -1624,9 +1686,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li>Functions <code>mo_authors</code> and <code>mo_year</code> to get specific values about the scientific reference of a taxonomic entry</li>
 </ul>
 </div>
-<div id="changed-12" class="section level4">
+<div id="changed-13" class="section level4">
 <h4 class="hasAnchor">
-<a href="#changed-12" class="anchor"></a>Changed</h4>
+<a href="#changed-13" class="anchor"></a>Changed</h4>
 <ul>
 <li><p>Functions <code>MDRO</code>, <code>BRMO</code>, <code>MRGN</code> and <code>EUCAST_exceptional_phenotypes</code> were renamed to <code>mdro</code>, <code>brmo</code>, <code>mrgn</code> and <code>eucast_exceptional_phenotypes</code></p></li>
 <li><p><code>EUCAST_rules</code> was renamed to <code>eucast_rules</code>, the old function still exists as a deprecated function</p></li>
@@ -1648,7 +1710,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li><p>Fewer than 3 characters as input for <code>as.mo</code> will return NA</p></li>
 <li>
 <p>Function <code>as.mo</code> (and all <code>mo_*</code> wrappers) now supports genus abbreviations with “species” attached</p>
-<div class="sourceCode" id="cb38"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb39"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"E. species"</span><span class="op">)</span>        <span class="co"># B_ESCHR</span>
 <span class="fu"><a href="../reference/mo_property.html">mo_fullname</a></span><span class="op">(</span><span class="st">"E. spp."</span><span class="op">)</span>     <span class="co"># "Escherichia species"</span>
@@ -1665,7 +1727,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <ul>
 <li>
 <p>Support for grouping variables, test with:</p>
-<div class="sourceCode" id="cb39"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb40"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="va">septic_patients</span> <span class="op">%&gt;%</span> 
   <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op">%&gt;%</span> 
@@ -1673,7 +1735,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 </li>
 <li>
 <p>Support for (un)selecting columns:</p>
-<div class="sourceCode" id="cb40"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb41"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="va">septic_patients</span> <span class="op">%&gt;%</span> 
   <span class="fu">freq</span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op">%&gt;%</span> 
@@ -1735,9 +1797,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <h1 class="page-header" data-toc-text="0.4.0">
 <a href="#amr-040" class="anchor"></a>AMR 0.4.0<small> 2018-10-01 </small>
 </h1>
-<div id="new-12" class="section level4">
+<div id="new-13" class="section level4">
 <h4 class="hasAnchor">
-<a href="#new-12" class="anchor"></a>New</h4>
+<a href="#new-13" class="anchor"></a>New</h4>
 <ul>
 <li><p>The data set <code>microorganisms</code> now contains <strong>all microbial taxonomic data from ITIS</strong> (kingdoms Bacteria, Fungi and Protozoa), the Integrated Taxonomy Information System, available via <a href="https://itis.gov" class="uri">https://itis.gov</a>. The data set now contains more than 18,000 microorganisms with all known bacteria, fungi and protozoa according ITIS with genus, species, subspecies, family, order, class, phylum and subkingdom. The new data set <code>microorganisms.old</code> contains all previously known taxonomic names from those kingdoms.</p></li>
 <li>
@@ -1753,7 +1815,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 </li>
 </ul>
 <p>They also come with support for German, Dutch, French, Italian, Spanish and Portuguese:</p>
-<div class="sourceCode" id="cb41"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb42"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span>
 <span class="co"># [1] "Gram negative"</span>
@@ -1764,7 +1826,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <span class="fu"><a href="../reference/mo_property.html">mo_fullname</a></span><span class="op">(</span><span class="st">"S. group A"</span>, language <span class="op">=</span> <span class="st">"pt"</span><span class="op">)</span> <span class="co"># Portuguese</span>
 <span class="co"># [1] "Streptococcus grupo A"</span></code></pre></div>
 <p>Furthermore, former taxonomic names will give a note about the current taxonomic name:</p>
-<div class="sourceCode" id="cb42"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb43"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="st">"Esc blattae"</span><span class="op">)</span>
 <span class="co"># Note: 'Escherichia blattae' (Burgess et al., 1973) was renamed 'Shimwellia blattae' (Priest and Barker, 2010)</span>
@@ -1779,7 +1841,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li><p>Function <code>is.rsi.eligible</code> to check for columns that have valid antimicrobial results, but do not have the <code>rsi</code> class yet. Transform the columns of your raw data with: <code>data %&gt;% mutate_if(is.rsi.eligible, as.rsi)</code></p></li>
 <li>
 <p>Functions <code>as.mo</code> and <code>is.mo</code> as replacements for <code>as.bactid</code> and <code>is.bactid</code> (since the <code>microoganisms</code> data set not only contains bacteria). These last two functions are deprecated and will be removed in a future release. The <code>as.mo</code> function determines microbial IDs using intelligent rules:</p>
-<div class="sourceCode" id="cb43"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb44"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span>
 <span class="co"># [1] B_ESCHR_COL</span>
@@ -1788,7 +1850,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"S group A"</span><span class="op">)</span>
 <span class="co"># [1] B_STRPTC_GRA</span></code></pre></div>
 <p>And with great speed too - on a quite regular Linux server from 2007 it takes us less than 0.02 seconds to transform 25,000 items:</p>
-<div class="sourceCode" id="cb44"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb45"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="va">thousands_of_E_colis</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/rep.html">rep</a></span><span class="op">(</span><span class="st">"E. coli"</span>, <span class="fl">25000</span><span class="op">)</span>
 <span class="fu">microbenchmark</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span><span class="op">(</span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="va">thousands_of_E_colis</span><span class="op">)</span>, unit <span class="op">=</span> <span class="st">"s"</span><span class="op">)</span>
@@ -1815,14 +1877,14 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li><p>Renamed <code>septic_patients$sex</code> to <code>septic_patients$gender</code></p></li>
 </ul>
 </div>
-<div id="changed-13" class="section level4">
+<div id="changed-14" class="section level4">
 <h4 class="hasAnchor">
-<a href="#changed-13" class="anchor"></a>Changed</h4>
+<a href="#changed-14" class="anchor"></a>Changed</h4>
 <ul>
 <li><p>Added three antimicrobial agents to the <code>antibiotics</code> data set: Terbinafine (D01BA02), Rifaximin (A07AA11) and Isoconazole (D01AC05)</p></li>
 <li>
 <p>Added 163 trade names to the <code>antibiotics</code> data set, it now contains 298 different trade names in total, e.g.:</p>
-<div class="sourceCode" id="cb45"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb46"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="fu">ab_official</span><span class="op">(</span><span class="st">"Bactroban"</span><span class="op">)</span>
 <span class="co"># [1] "Mupirocin"</span>
@@ -1839,7 +1901,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li><p>Added arguments <code>minimum</code> and <code>as_percent</code> to <code>portion_df</code></p></li>
 <li>
 <p>Support for quasiquotation in the functions series <code>count_*</code> and <code>portions_*</code>, and <code>n_rsi</code>. This allows to check for more than 2 vectors or columns.</p>
-<div class="sourceCode" id="cb46"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb47"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="va">septic_patients</span> <span class="op">%&gt;%</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span><span class="op">(</span><span class="va">amox</span>, <span class="va">cipr</span><span class="op">)</span> <span class="op">%&gt;%</span> <span class="fu"><a href="../reference/count.html">count_IR</a></span><span class="op">(</span><span class="op">)</span>
 <span class="co"># which is the same as:</span>
@@ -1859,12 +1921,12 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li><p>Added longest en shortest character length in the frequency table (<code>freq</code>) header of class <code>character</code></p></li>
 <li>
 <p>Support for types (classes) list and matrix for <code>freq</code></p>
-<div class="sourceCode" id="cb47"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb48"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="va">my_matrix</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/with.html">with</a></span><span class="op">(</span><span class="va">septic_patients</span>, <span class="fu"><a href="https://rdrr.io/r/base/matrix.html">matrix</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="va">age</span>, <span class="va">gender</span><span class="op">)</span>, ncol <span class="op">=</span> <span class="fl">2</span><span class="op">)</span><span class="op">)</span>
 <span class="fu">freq</span><span class="op">(</span><span class="va">my_matrix</span><span class="op">)</span></code></pre></div>
 <p>For lists, subsetting is possible:</p>
-<div class="sourceCode" id="cb48"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb49"><pre class="downlit sourceCode r">
 <code class="sourceCode R">
 <span class="va">my_list</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span>age <span class="op">=</span> <span class="va">septic_patients</span><span class="op">$</span><span class="va">age</span>, gender <span class="op">=</span> <span class="va">septic_patients</span><span class="op">$</span><span class="va">gender</span><span class="op">)</span>
 <span class="va">my_list</span> <span class="op">%&gt;%</span> <span class="fu">freq</span><span class="op">(</span><span class="va">age</span><span class="op">)</span>
@@ -1884,9 +1946,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <h1 class="page-header" data-toc-text="0.3.0">
 <a href="#amr-030" class="anchor"></a>AMR 0.3.0<small> 2018-08-14 </small>
 </h1>
-<div id="new-13" class="section level4">
+<div id="new-14" class="section level4">
 <h4 class="hasAnchor">
-<a href="#new-13" class="anchor"></a>New</h4>
+<a href="#new-14" class="anchor"></a>New</h4>
 <ul>
 <li>
 <strong>BREAKING</strong>: <code>rsi_df</code> was removed in favour of new functions <code>portion_R</code>, <code>portion_IR</code>, <code>portion_I</code>, <code>portion_SI</code> and <code>portion_S</code> to selectively calculate resistance or susceptibility. These functions are 20 to 30 times faster than the old <code>rsi</code> function. The old function still works, but is deprecated.
@@ -1957,9 +2019,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 </li>
 </ul>
 </div>
-<div id="changed-14" class="section level4">
+<div id="changed-15" class="section level4">
 <h4 class="hasAnchor">
-<a href="#changed-14" class="anchor"></a>Changed</h4>
+<a href="#changed-15" class="anchor"></a>Changed</h4>
 <ul>
 <li>Improvements for forecasting with <code>resistance_predict</code> and added more examples</li>
 <li>More antibiotics added as arguments for EUCAST rules</li>
@@ -2021,9 +2083,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <h1 class="page-header" data-toc-text="0.2.0">
 <a href="#amr-020" class="anchor"></a>AMR 0.2.0<small> 2018-05-03 </small>
 </h1>
-<div id="new-14" class="section level4">
+<div id="new-15" class="section level4">
 <h4 class="hasAnchor">
-<a href="#new-14" class="anchor"></a>New</h4>
+<a href="#new-15" class="anchor"></a>New</h4>
 <ul>
 <li>Full support for Windows, Linux and macOS</li>
 <li>Full support for old R versions, only R-3.0.0 (April 2013) or later is needed (needed packages may have other dependencies)</li>
@@ -2043,9 +2105,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li>New print format for <code>tibble</code>s and <code>data.table</code>s</li>
 </ul>
 </div>
-<div id="changed-15" class="section level4">
+<div id="changed-16" class="section level4">
 <h4 class="hasAnchor">
-<a href="#changed-15" class="anchor"></a>Changed</h4>
+<a href="#changed-16" class="anchor"></a>Changed</h4>
 <ul>
 <li>Fixed <code>rsi</code> class for vectors that contain only invalid antimicrobial interpretations</li>
 <li>Renamed dataset <code>ablist</code> to <code>antibiotics</code>

docs/pkgdown.yml

@@ -12,7 +12,7 @@ articles:
   datasets: datasets.html
   resistance_predict: resistance_predict.html
   welcome_to_AMR: welcome_to_AMR.html
-last_built: 2021-03-14T08:55Z
+last_built: 2021-04-23T14:13Z
 urls:
   reference: https://msberends.github.io/AMR//reference
   article: https://msberends.github.io/AMR//articles

docs/reference/ab_from_text.html

@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.5.0.9040</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9007</span>
       </span>
     </div>
 
@@ -248,6 +248,7 @@
   collapse <span class='op'>=</span> <span class='cn'>NULL</span>,
   translate_ab <span class='op'>=</span> <span class='cn'>FALSE</span>,
   thorough_search <span class='op'>=</span> <span class='cn'>NULL</span>,
+  info <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/interactive.html'>interactive</a></span><span class='op'>(</span><span class='op'>)</span>,
   <span class='va'>...</span>
 <span class='op'>)</span></pre>
 
@@ -274,6 +275,10 @@
       <th>thorough_search</th>
       <td><p>logical to indicate whether the input must be extensively searched for misspelling and other faulty input values. Setting this to <code>TRUE</code> will take considerably more time than when using <code>FALSE</code>. At default, it will turn <code>TRUE</code> when all input elements contain a maximum of three words.</p></td>
     </tr>
+    <tr>
+      <th>info</th>
+      <td><p>logical to indicate whether a progress bar should be printed, defaults to <code>TRUE</code> only in interactive mode</p></td>
+    </tr>
     <tr>
       <th>...</th>
       <td><p>arguments passed on to <code><a href='as.ab.html'>as.ab()</a></code></p></td>

docs/reference/antibiotic_class_selectors.html

@@ -83,7 +83,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9000</span>
       </span>
     </div>
 

docs/reference/as.ab.html

@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.5.0.9016</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9007</span>
       </span>
     </div>
 
@@ -242,7 +242,7 @@
     <p>Use this function to determine the antibiotic code of one or more antibiotics. The data set <a href='antibiotics.html'>antibiotics</a> will be searched for abbreviations, official names and synonyms (brand names).</p>
     </div>
 
-    <pre class="usage"><span class='fu'>as.ab</span><span class='op'>(</span><span class='va'>x</span>, flag_multiple_results <span class='op'>=</span> <span class='cn'>TRUE</span>, info <span class='op'>=</span> <span class='cn'>TRUE</span>, <span class='va'>...</span><span class='op'>)</span>
+    <pre class="usage"><span class='fu'>as.ab</span><span class='op'>(</span><span class='va'>x</span>, flag_multiple_results <span class='op'>=</span> <span class='cn'>TRUE</span>, info <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/interactive.html'>interactive</a></span><span class='op'>(</span><span class='op'>)</span>, <span class='va'>...</span><span class='op'>)</span>
 
 <span class='fu'>is.ab</span><span class='op'>(</span><span class='va'>x</span><span class='op'>)</span></pre>
 
@@ -259,7 +259,7 @@
     </tr>
     <tr>
       <th>info</th>
-      <td><p>logical to indicate whether a progress bar should be printed</p></td>
+      <td><p>a <a href='https://rdrr.io/r/base/logical.html'>logical</a> to indicate whether a progress bar should be printed, defaults to <code>TRUE</code> only in interactive mode</p></td>
     </tr>
     <tr>
       <th>...</th>

docs/reference/as.mo.html

@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9007</span>
       </span>
     </div>
 
@@ -250,6 +250,7 @@
   reference_df <span class='op'>=</span> <span class='fu'><a href='mo_source.html'>get_mo_source</a></span><span class='op'>(</span><span class='op'>)</span>,
   ignore_pattern <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/options.html'>getOption</a></span><span class='op'>(</span><span class='st'>"AMR_ignore_pattern"</span><span class='op'>)</span>,
   language <span class='op'>=</span> <span class='fu'><a href='translate.html'>get_locale</a></span><span class='op'>(</span><span class='op'>)</span>,
+  info <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/interactive.html'>interactive</a></span><span class='op'>(</span><span class='op'>)</span>,
   <span class='va'>...</span>
 <span class='op'>)</span>
 
@@ -294,6 +295,10 @@
       <th>language</th>
       <td><p>language to translate text like "no growth", which defaults to the system language (see <code><a href='translate.html'>get_locale()</a></code>)</p></td>
     </tr>
+    <tr>
+      <th>info</th>
+      <td><p>a <a href='https://rdrr.io/r/base/logical.html'>logical</a> to indicate if a progress bar should be printed if more than 25 items are to be coerced, defaults to <code>TRUE</code> only in interactive mode</p></td>
+    </tr>
     <tr>
       <th>...</th>
       <td><p>other arguments passed on to functions</p></td>
@@ -399,7 +404,7 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
 <li><p><i>k<sub>n</sub></i> is the taxonomic kingdom of <i>n</i>, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.</p></li>
 </ul>
 
-<p>The grouping into human pathogenic prevalence (\(p\)) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. <strong>Group 1</strong> (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is <em>Enterococcus</em>, <em>Staphylococcus</em> or <em>Streptococcus</em>. This group consequently contains all common Gram-negative bacteria, such as <em>Pseudomonas</em> and <em>Legionella</em> and all species within the order Enterobacterales. <strong>Group 2</strong> consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is <em>Absidia</em>, <em>Acremonium</em>, <em>Actinotignum</em>, <em>Alternaria</em>, <em>Anaerosalibacter</em>, <em>Apophysomyces</em>, <em>Arachnia</em>, <em>Aspergillus</em>, <em>Aureobacterium</em>, <em>Aureobasidium</em>, <em>Bacteroides</em>, <em>Basidiobolus</em>, <em>Beauveria</em>, <em>Blastocystis</em>, <em>Branhamella</em>, <em>Calymmatobacterium</em>, <em>Candida</em>, <em>Capnocytophaga</em>, <em>Catabacter</em>, <em>Chaetomium</em>, <em>Chryseobacterium</em>, <em>Chryseomonas</em>, <em>Chrysonilia</em>, <em>Cladophialophora</em>, <em>Cladosporium</em>, <em>Conidiobolus</em>, <em>Cryptococcus</em>, <em>Curvularia</em>, <em>Exophiala</em>, <em>Exserohilum</em>, <em>Flavobacterium</em>, <em>Fonsecaea</em>, <em>Fusarium</em>, <em>Fusobacterium</em>, <em>Hendersonula</em>, <em>Hypomyces</em>, <em>Koserella</em>, <em>Lelliottia</em>, <em>Leptosphaeria</em>, <em>Leptotrichia</em>, <em>Malassezia</em>, <em>Malbranchea</em>, <em>Mortierella</em>, <em>Mucor</em>, <em>Mycocentrospora</em>, <em>Mycoplasma</em>, <em>Nectria</em>, <em>Ochroconis</em>, <em>Oidiodendron</em>, <em>Phoma</em>, <em>Piedraia</em>, <em>Pithomyces</em>, <em>Pityrosporum</em>, <em>Prevotella</em>, <em>Pseudallescheria</em>, <em>Rhizomucor</em>, <em>Rhizopus</em>, <em>Rhodotorula</em>, <em>Scolecobasidium</em>, <em>Scopulariopsis</em>, <em>Scytalidium</em>,<em>Sporobolomyces</em>, <em>Stachybotrys</em>, <em>Stomatococcus</em>, <em>Treponema</em>, <em>Trichoderma</em>, <em>Trichophyton</em>, <em>Trichosporon</em>, <em>Tritirachium</em> or <em>Ureaplasma</em>. <strong>Group 3</strong> consists of all other microorganisms.</p>
+<p>The grouping into human pathogenic prevalence (\(p\)) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. <strong>Group 1</strong> (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is <em>Enterococcus</em>, <em>Staphylococcus</em> or <em>Streptococcus</em>. This group consequently contains all common Gram-negative bacteria, such as <em>Pseudomonas</em> and <em>Legionella</em> and all species within the order Enterobacterales. <strong>Group 2</strong> consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is <em>Absidia</em>, <em>Acremonium</em>, <em>Actinotignum</em>, <em>Alternaria</em>, <em>Anaerosalibacter</em>, <em>Apophysomyces</em>, <em>Arachnia</em>, <em>Aspergillus</em>, <em>Aureobacterium</em>, <em>Aureobasidium</em>, <em>Bacteroides</em>, <em>Basidiobolus</em>, <em>Beauveria</em>, <em>Blastocystis</em>, <em>Branhamella</em>, <em>Calymmatobacterium</em>, <em>Candida</em>, <em>Capnocytophaga</em>, <em>Catabacter</em>, <em>Chaetomium</em>, <em>Chryseobacterium</em>, <em>Chryseomonas</em>, <em>Chrysonilia</em>, <em>Cladophialophora</em>, <em>Cladosporium</em>, <em>Conidiobolus</em>, <em>Cryptococcus</em>, <em>Curvularia</em>, <em>Exophiala</em>, <em>Exserohilum</em>, <em>Flavobacterium</em>, <em>Fonsecaea</em>, <em>Fusarium</em>, <em>Fusobacterium</em>, <em>Hendersonula</em>, <em>Hypomyces</em>, <em>Koserella</em>, <em>Lelliottia</em>, <em>Leptosphaeria</em>, <em>Leptotrichia</em>, <em>Malassezia</em>, <em>Malbranchea</em>, <em>Mortierella</em>, <em>Mucor</em>, <em>Mycocentrospora</em>, <em>Mycoplasma</em>, <em>Nectria</em>, <em>Ochroconis</em>, <em>Oidiodendron</em>, <em>Phoma</em>, <em>Piedraia</em>, <em>Pithomyces</em>, <em>Pityrosporum</em>, <em>Prevotella</em>, <em>Pseudallescheria</em>, <em>Rhizomucor</em>, <em>Rhizopus</em>, <em>Rhodotorula</em>, <em>Scolecobasidium</em>, <em>Scopulariopsis</em>, <em>Scytalidium</em>, <em>Sporobolomyces</em>, <em>Stachybotrys</em>, <em>Stomatococcus</em>, <em>Treponema</em>, <em>Trichoderma</em>, <em>Trichophyton</em>, <em>Trichosporon</em>, <em>Tritirachium</em> or <em>Ureaplasma</em>. <strong>Group 3</strong> consists of all other microorganisms.</p>
 <p>All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., <code>"E. coli"</code> will return the microbial ID of <em>Escherichia coli</em> (\(m = 0.688\), a highly prevalent microorganism found in humans) and not <em>Entamoeba coli</em> (\(m = 0.079\), a less prevalent microorganism in humans), although the latter would alphabetically come first.</p>
     <h2 class="hasAnchor" id="catalogue-of-life"><a class="anchor" href="#catalogue-of-life"></a>Catalogue of Life</h2>
 

docs/reference/custom_eucast_rules.html

@@ -0,0 +1,388 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Define Custom EUCAST Rules — custom_eucast_rules • AMR (for R)</title>
+
+<!-- favicons -->
+<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
+<link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
+<link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png" />
+
+<!-- jquery -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script>
+<!-- Bootstrap -->
+<link href="https://cdnjs.cloudflare.com/ajax/libs/bootswatch/3.4.0/flatly/bootstrap.min.css" rel="stylesheet" crossorigin="anonymous" />
+
+
+<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script>
+
+<!-- bootstrap-toc -->
+<link rel="stylesheet" href="../bootstrap-toc.css">
+<script src="../bootstrap-toc.js"></script>
+
+<!-- Font Awesome icons -->
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous" />
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
+
+<!-- clipboard.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
+
+<!-- headroom.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script>
+
+<!-- pkgdown -->
+<link href="../pkgdown.css" rel="stylesheet">
+<script src="../pkgdown.js"></script>
+
+
+
+  <link href="../extra.css" rel="stylesheet">
+  <script src="../extra.js"></script>
+
+<meta property="og:title" content="Define Custom EUCAST Rules — custom_eucast_rules" />
+<meta property="og:description" content="Define custom EUCAST rules for your organisation or specific analysis and use the output of this function in eucast_rules()." />
+<meta property="og:image" content="https://msberends.github.io/AMR/logo.png" />
+
+
+
+
+<!-- mathjax -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
+
+<!--[if lt IE 9]>
+<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
+<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
+<![endif]-->
+
+
+
+  </head>
+
+  <body data-spy="scroll" data-target="#toc">
+    <div class="container template-reference-topic">
+      <header>
+      <div class="navbar navbar-default navbar-fixed-top" role="navigation">
+  <div class="container">
+    <div class="navbar-header">
+      <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false">
+        <span class="sr-only">Toggle navigation</span>
+        <span class="icon-bar"></span>
+        <span class="icon-bar"></span>
+        <span class="icon-bar"></span>
+      </button>
+      <span class="navbar-brand">
+        <a class="navbar-link" href="../index.html">AMR (for R)</a>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9007</span>
+      </span>
+    </div>
+
+    <div id="navbar" class="navbar-collapse collapse">
+      <ul class="nav navbar-nav">
+        <li>
+  <a href="../index.html">
+    <span class="fas fa-home"></span>
+     
+    Home
+  </a>
+</li>
+<li class="dropdown">
+  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
+    <span class="fas fa-question-circle"></span>
+     
+    How to
+     
+    <span class="caret"></span>
+  </a>
+  <ul class="dropdown-menu" role="menu">
+    <li>
+      <a href="../articles/AMR.html">
+        <span class="fas fa-directions"></span>
+         
+        Conduct AMR analysis
+      </a>
+    </li>
+    <li>
+      <a href="../articles/resistance_predict.html">
+        <span class="fas fa-dice"></span>
+         
+        Predict antimicrobial resistance
+      </a>
+    </li>
+    <li>
+      <a href="../articles/datasets.html">
+        <span class="fas fa-database"></span>
+         
+        Data sets for download / own use
+      </a>
+    </li>
+    <li>
+      <a href="../articles/PCA.html">
+        <span class="fas fa-compress"></span>
+         
+        Conduct principal component analysis for AMR
+      </a>
+    </li>
+    <li>
+      <a href="../articles/MDR.html">
+        <span class="fas fa-skull-crossbones"></span>
+         
+        Determine multi-drug resistance (MDR)
+      </a>
+    </li>
+    <li>
+      <a href="../articles/WHONET.html">
+        <span class="fas fa-globe-americas"></span>
+         
+        Work with WHONET data
+      </a>
+    </li>
+    <li>
+      <a href="../articles/SPSS.html">
+        <span class="fas fa-file-upload"></span>
+         
+        Import data from SPSS/SAS/Stata
+      </a>
+    </li>
+    <li>
+      <a href="../articles/EUCAST.html">
+        <span class="fas fa-exchange-alt"></span>
+         
+        Apply EUCAST rules
+      </a>
+    </li>
+    <li>
+      <a href="../reference/mo_property.html">
+        <span class="fas fa-bug"></span>
+         
+        Get properties of a microorganism
+      </a>
+    </li>
+    <li>
+      <a href="../reference/ab_property.html">
+        <span class="fas fa-capsules"></span>
+         
+        Get properties of an antibiotic
+      </a>
+    </li>
+    <li>
+      <a href="../articles/benchmarks.html">
+        <span class="fas fa-shipping-fast"></span>
+         
+        Other: benchmarks
+      </a>
+    </li>
+  </ul>
+</li>
+<li>
+  <a href="../reference/index.html">
+    <span class="fas fa-book-open"></span>
+     
+    Manual
+  </a>
+</li>
+<li>
+  <a href="../authors.html">
+    <span class="fas fa-users"></span>
+     
+    Authors
+  </a>
+</li>
+<li>
+  <a href="../news/index.html">
+    <span class="far fa-newspaper"></span>
+     
+    Changelog
+  </a>
+</li>
+      </ul>
+      <ul class="nav navbar-nav navbar-right">
+        <li>
+  <a href="https://github.com/msberends/AMR">
+    <span class="fab fa-github"></span>
+     
+    Source Code
+  </a>
+</li>
+<li>
+  <a href="../survey.html">
+    <span class="fas fa-clipboard-list"></span>
+     
+    Survey
+  </a>
+</li>
+      </ul>
+      
+    </div><!--/.nav-collapse -->
+  </div><!--/.container -->
+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Define Custom EUCAST Rules</h1>
+    <small class="dont-index">Source: <a href='https://github.com/msberends/AMR/blob/master/R/custom_eucast_rules.R'><code>R/custom_eucast_rules.R</code></a></small>
+    <div class="hidden name"><code>custom_eucast_rules.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Define custom EUCAST rules for your organisation or specific analysis and use the output of this function in <code><a href='eucast_rules.html'>eucast_rules()</a></code>.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>custom_eucast_rules</span><span class='op'>(</span><span class='va'>...</span><span class='op'>)</span></pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>...</th>
+      <td><p>rules in formula notation, see <em>Examples</em></p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A <a href='https://rdrr.io/r/base/list.html'>list</a> containing the custom rules</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>Some organisations have their own adoption of EUCAST rules. This function can be used to define custom EUCAST rules to be used in the <code><a href='eucast_rules.html'>eucast_rules()</a></code> function.</p>
+    <h2 class="hasAnchor" id="how-it-works"><a class="anchor" href="#how-it-works"></a>How it works</h2>
+
+    
+
+<h3 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>Basics</h3>
+
+
+<p>If you are familiar with the <code><a href='https://dplyr.tidyverse.org/reference/case_when.html'>case_when()</a></code> function of the <code>dplyr</code> package, you will recognise the input method to set your own rules. Rules must be set using what <span style="R">R</span> considers to be the 'formula notation'. The rule itself is written <em>before</em> the tilde (<code><a href='https://rdrr.io/r/base/tilde.html'>~</a></code>) and the consequence of the rule is written <em>after</em> the tilde:</p><pre><span class='va'>x</span> <span class='op'>&lt;-</span> <span class='fu'>custom_eucast_rules</span><span class='op'>(</span><span class='va'>TZP</span> <span class='op'>==</span> <span class='st'>"S"</span> <span class='op'>~</span> <span class='va'>aminopenicillins</span> <span class='op'>==</span> <span class='st'>"S"</span>,
+                         <span class='va'>TZP</span> <span class='op'>==</span> <span class='st'>"R"</span> <span class='op'>~</span> <span class='va'>aminopenicillins</span> <span class='op'>==</span> <span class='st'>"R"</span><span class='op'>)</span>
+</pre>
+
+<p>These are two custom EUCAST rules: if TZP (piperacillin/tazobactam) is "S", all aminopenicillins (ampicillin and amoxicillin) must be made "S", and if TZP is "R", aminopenicillins must be made "R". These rules can also be printed to the console, so it is immediately clear how they work:</p><pre><span class='va'>x</span>
+<span class='co'>#&gt; A set of custom EUCAST rules:</span>
+<span class='co'>#&gt; </span>
+<span class='co'>#&gt;   1. If TZP is S then set to S:</span>
+<span class='co'>#&gt;      amoxicillin (AMX), ampicillin (AMP)</span>
+<span class='co'>#&gt; </span>
+<span class='co'>#&gt;   2. If TZP is R then set to R:</span>
+<span class='co'>#&gt;      amoxicillin (AMX), ampicillin (AMP)</span>
+</pre>
+
+<p>The rules (the part <em>before</em> the tilde, in above example <code>TZP == "S"</code> and <code>TZP == "R"</code>) must be evaluable in your data set: it should be able to run as a filter in your data set without errors. This means for the above example that the column <code>TZP</code> must exist. We will create a sample data set and test the rules set:</p><pre><span class='va'>df</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a></span><span class='op'>(</span>mo <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"E. coli"</span>, <span class='st'>"K. pneumoniae"</span><span class='op'>)</span>,
+                 TZP <span class='op'>=</span> <span class='st'>"R"</span>,
+                 amox <span class='op'>=</span> <span class='st'>""</span>,
+                 AMP <span class='op'>=</span> <span class='st'>""</span><span class='op'>)</span>
+<span class='va'>df</span>
+<span class='co'>#&gt;              mo TZP amox AMP</span>
+<span class='co'>#&gt; 1       E. coli   R         </span>
+<span class='co'>#&gt; 2 K. pneumoniae   R         </span>
+                 
+<span class='fu'><a href='eucast_rules.html'>eucast_rules</a></span><span class='op'>(</span><span class='va'>df</span>, rules <span class='op'>=</span> <span class='st'>"custom"</span>, custom_rules <span class='op'>=</span> <span class='va'>x</span><span class='op'>)</span>
+<span class='co'>#&gt;              mo TZP amox AMP</span>
+<span class='co'>#&gt; 1       E. coli   R    R   R     </span>
+<span class='co'>#&gt; 2 K. pneumoniae   R    R   R  </span>
+</pre>
+
+
+<h3 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>Using taxonomic properties in rules</h3>
+
+
+<p>There is one exception in variables used for the rules: all column names of the <a href='microorganisms.html'>microorganisms</a> data set can also be used, but do not have to exist in the data set. These column names are: <code>mo</code>, <code>fullname</code>, <code>kingdom</code>, <code>phylum</code>, <code>class</code>, <code>order</code>, <code>family</code>, <code>genus</code>, <code>species</code>, <code>subspecies</code>, <code>rank</code>, <code>ref</code>, <code>species_id</code>, <code>source</code>, <code>prevalence</code> and <code>snomed</code>. Thus, this next example will work as well, despite the fact that the <code>df</code> data set does not contain a column <code>genus</code>:</p><pre><span class='va'>y</span> <span class='op'>&lt;-</span> <span class='fu'>custom_eucast_rules</span><span class='op'>(</span><span class='va'>TZP</span> <span class='op'>==</span> <span class='st'>"S"</span> <span class='op'>&amp;</span> <span class='va'>genus</span> <span class='op'>==</span> <span class='st'>"Klebsiella"</span> <span class='op'>~</span> <span class='va'>aminopenicillins</span> <span class='op'>==</span> <span class='st'>"S"</span>,
+                         <span class='va'>TZP</span> <span class='op'>==</span> <span class='st'>"R"</span> <span class='op'>&amp;</span> <span class='va'>genus</span> <span class='op'>==</span> <span class='st'>"Klebsiella"</span> <span class='op'>~</span> <span class='va'>aminopenicillins</span> <span class='op'>==</span> <span class='st'>"R"</span><span class='op'>)</span>
+
+<span class='fu'><a href='eucast_rules.html'>eucast_rules</a></span><span class='op'>(</span><span class='va'>df</span>, rules <span class='op'>=</span> <span class='st'>"custom"</span>, custom_rules <span class='op'>=</span> <span class='va'>y</span><span class='op'>)</span>
+<span class='co'>#&gt;              mo TZP amox AMP</span>
+<span class='co'>#&gt; 1       E. coli   R         </span>
+<span class='co'>#&gt; 2 K. pneumoniae   R    R   R</span>
+</pre>
+
+
+<h3 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>Usage of antibiotic group names</h3>
+
+
+<p>It is possible to define antibiotic groups instead of single antibiotics for the rule consequence, the part <em>after</em> the tilde. In above examples, the antibiotic group <code>aminopenicillins</code> is used to include ampicillin and amoxicillin. The following groups are allowed (case-insensitive). Within parentheses are the antibiotic agents that will be matched when running the rule.</p><ul>
+<li><p><code>aminoglycosides</code><br />(amikacin, amikacin/fosfomycin, amphotericin B-high, 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, tobramycin-high)</p></li>
+<li><p><code>aminopenicillins</code><br />(amoxicillin, ampicillin)</p></li>
+<li><p><code>betalactams</code><br />(amoxicillin, amoxicillin/clavulanic acid, amoxicillin/sulbactam, ampicillin, ampicillin/sulbactam, apalcillin, aspoxicillin, avibactam, azidocillin, azlocillin, aztreonam, aztreonam/avibactam, bacampicillin, benzathine benzylpenicillin, benzathine phenoxymethylpenicillin, benzylpenicillin, biapenem, cadazolid, carbenicillin, carindacillin, cefacetrile, cefaclor, cefadroxil, cefaloridine, cefamandole, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol (Cefcatacol), cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, 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/enzyme inhibitor, ceftolozane/tazobactam, ceftriaxone, cefuroxime, cefuroxime axetil, cephalexin, cephalothin, cephapirin, cephradine, ciclacillin, clometocillin, cloxacillin, dicloxacillin, doripenem, epicillin, ertapenem, flucloxacillin, hetacillin, imipenem, imipenem/EDTA, imipenem/relebactam, latamoxef, lenampicillin, loracarbef, mecillinam (Amdinocillin), meropenem, meropenem/nacubactam, meropenem/vaborbactam, metampicillin, methicillin, mezlocillin, mezlocillin/sulbactam, nacubactam, nafcillin, oxacillin, panipenem, penamecillin, penicillin/novobiocin, penicillin/sulbactam, phenethicillin, phenoxymethylpenicillin, piperacillin, piperacillin/sulbactam, piperacillin/tazobactam, piridicillin, pivampicillin, pivmecillinam, procaine benzylpenicillin, propicillin, razupenem, ritipenem, ritipenem acoxil, sarmoxicillin, sulbactam, sulbenicillin, sultamicillin, talampicillin, tazobactam, tebipenem, temocillin, ticarcillin, ticarcillin/clavulanic acid)</p></li>
+<li><p><code>carbapenems</code><br />(biapenem, doripenem, ertapenem, imipenem, imipenem/EDTA, imipenem/relebactam, meropenem, meropenem/nacubactam, meropenem/vaborbactam, panipenem, razupenem, ritipenem, ritipenem acoxil, tebipenem)</p></li>
+<li><p><code>cephalosporins</code><br />(cadazolid, cefacetrile, cefaclor, cefadroxil, cefaloridine, cefamandole, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol (Cefcatacol), cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, 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/enzyme inhibitor, ceftolozane/tazobactam, ceftriaxone, cefuroxime, cefuroxime axetil, cephalexin, cephalothin, cephapirin, cephradine, latamoxef, loracarbef)</p></li>
+<li><p><code>cephalosporins_1st</code><br />(cefacetrile, cefadroxil, cefaloridine, cefatrizine, cefazedone, cefazolin, cefroxadine, ceftezole, cephalexin, cephalothin, cephapirin, cephradine)</p></li>
+<li><p><code>cephalosporins_2nd</code><br />(cefaclor, cefamandole, cefmetazole, cefonicid, ceforanide, cefotetan, cefotiam, cefoxitin, cefoxitin screening, cefprozil, cefuroxime, cefuroxime axetil, loracarbef)</p></li>
+<li><p><code>cephalosporins_3rd</code><br />(cadazolid, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefetamet, cefetamet pivoxil, cefixime, cefmenoxime, cefodizime, cefoperazone, cefoperazone/sulbactam, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotiam hexetil, cefovecin, cefpimizole, cefpiramide, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefsulodin, ceftazidime, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftriaxone, latamoxef)</p></li>
+<li><p><code>cephalosporins_except_caz</code><br />(cadazolid, cefacetrile, cefaclor, cefadroxil, cefaloridine, cefamandole, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol (Cefcatacol), cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, cefozopran, cefpimizole, cefpiramide, cefpirome, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefprozil, cefquinome, cefroxadine, cefsulodin, cefsumide, ceftaroline, ceftaroline/avibactam, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftezole, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftobiprole, ceftobiprole medocaril, ceftolozane/enzyme inhibitor, ceftolozane/tazobactam, ceftriaxone, cefuroxime, cefuroxime axetil, cephalexin, cephalothin, cephapirin, cephradine, latamoxef, loracarbef)</p></li>
+<li><p><code>fluoroquinolones</code><br />(ciprofloxacin, enoxacin, fleroxacin, gatifloxacin, gemifloxacin, grepafloxacin, levofloxacin, lomefloxacin, moxifloxacin, norfloxacin, ofloxacin, pazufloxacin, pefloxacin, prulifloxacin, rufloxacin, sparfloxacin, temafloxacin, trovafloxacin)</p></li>
+<li><p><code>glycopeptides</code><br />(avoparcin, dalbavancin, norvancomycin, oritavancin, ramoplanin, teicoplanin, teicoplanin-macromethod, telavancin, vancomycin, vancomycin-macromethod)</p></li>
+<li><p><code>glycopeptides_except_lipo</code><br />(avoparcin, norvancomycin, ramoplanin, teicoplanin, teicoplanin-macromethod, vancomycin, vancomycin-macromethod)</p></li>
+<li><p><code>lincosamides</code><br />(clindamycin, lincomycin, pirlimycin)</p></li>
+<li><p><code>lipoglycopeptides</code><br />(dalbavancin, oritavancin, telavancin)</p></li>
+<li><p><code>macrolides</code><br />(azithromycin, clarithromycin, dirithromycin, erythromycin, flurithromycin, josamycin, midecamycin, miocamycin, oleandomycin, rokitamycin, roxithromycin, spiramycin, telithromycin, troleandomycin)</p></li>
+<li><p><code>oxazolidinones</code><br />(cycloserine, linezolid, tedizolid, thiacetazone)</p></li>
+<li><p><code>penicillins</code><br />(amoxicillin, amoxicillin/clavulanic acid, amoxicillin/sulbactam, ampicillin, ampicillin/sulbactam, apalcillin, aspoxicillin, avibactam, azidocillin, azlocillin, aztreonam, aztreonam/avibactam, bacampicillin, benzathine benzylpenicillin, benzathine phenoxymethylpenicillin, benzylpenicillin, carbenicillin, carindacillin, ciclacillin, clometocillin, cloxacillin, dicloxacillin, epicillin, flucloxacillin, hetacillin, lenampicillin, mecillinam (Amdinocillin), metampicillin, methicillin, mezlocillin, mezlocillin/sulbactam, nacubactam, nafcillin, oxacillin, penamecillin, penicillin/novobiocin, penicillin/sulbactam, phenethicillin, phenoxymethylpenicillin, piperacillin, piperacillin/sulbactam, piperacillin/tazobactam, piridicillin, pivampicillin, pivmecillinam, procaine benzylpenicillin, propicillin, sarmoxicillin, sulbactam, sulbenicillin, sultamicillin, talampicillin, tazobactam, temocillin, ticarcillin, ticarcillin/clavulanic acid)</p></li>
+<li><p><code>polymyxins</code><br />(colistin, polymyxin B, polymyxin B/polysorbate 80)</p></li>
+<li><p><code>streptogramins</code><br />(pristinamycin, quinupristin/dalfopristin)</p></li>
+<li><p><code>tetracyclines</code><br />(chlortetracycline, clomocycline, demeclocycline, doxycycline, eravacycline, lymecycline, metacycline, minocycline, oxytetracycline, penimepicycline, rolitetracycline, tetracycline, tigecycline)</p></li>
+<li><p><code>tetracyclines_except_tgc</code><br />(chlortetracycline, clomocycline, demeclocycline, doxycycline, eravacycline, lymecycline, metacycline, minocycline, oxytetracycline, penimepicycline, rolitetracycline, tetracycline)</p></li>
+<li><p><code>ureidopenicillins</code><br />(azlocillin, mezlocillin, piperacillin, piperacillin/tazobactam)</p></li>
+</ul>
+
+
+    <h2 class="hasAnchor" id="maturing-lifecycle"><a class="anchor" href="#maturing-lifecycle"></a>Maturing Lifecycle</h2>
+
+    
+
+<p><img src='figures/lifecycle_maturing.svg' style=margin-bottom:5px /> <br />
+The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>maturing</strong>. The unlying code of a maturing function has been roughed out, but finer details might still change. Since this function needs wider usage and more extensive testing, you are very welcome <a href='https://github.com/msberends/AMR/issues'>to suggest changes at our repository</a> or <a href='AMR.html'>write us an email (see section 'Contact Us')</a>.</p>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><span class='va'>x</span> <span class='op'>&lt;-</span> <span class='fu'>custom_eucast_rules</span><span class='op'>(</span><span class='va'>AMC</span> <span class='op'>==</span> <span class='st'>"R"</span> <span class='op'>&amp;</span> <span class='va'>genus</span> <span class='op'>==</span> <span class='st'>"Klebsiella"</span> <span class='op'>~</span> <span class='va'>aminopenicillins</span> <span class='op'>==</span> <span class='st'>"R"</span>,
+                         <span class='va'>AMC</span> <span class='op'>==</span> <span class='st'>"I"</span> <span class='op'>&amp;</span> <span class='va'>genus</span> <span class='op'>==</span> <span class='st'>"Klebsiella"</span> <span class='op'>~</span> <span class='va'>aminopenicillins</span> <span class='op'>==</span> <span class='st'>"I"</span><span class='op'>)</span>
+<span class='fu'><a href='eucast_rules.html'>eucast_rules</a></span><span class='op'>(</span><span class='va'>example_isolates</span>,
+             rules <span class='op'>=</span> <span class='st'>"custom"</span>,
+             custom_rules <span class='op'>=</span> <span class='va'>x</span>,
+             info <span class='op'>=</span> <span class='cn'>FALSE</span><span class='op'>)</span>
+             
+<span class='co'># combine rule sets</span>
+<span class='va'>x2</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='va'>x</span>,
+        <span class='fu'>custom_eucast_rules</span><span class='op'>(</span><span class='va'>TZP</span> <span class='op'>==</span> <span class='st'>"R"</span> <span class='op'>~</span> <span class='va'>carbapenems</span> <span class='op'>==</span> <span class='st'>"R"</span><span class='op'>)</span><span class='op'>)</span>
+<span class='va'>x2</span>
+</pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+</div>
+
+
+      <footer>
+      <div class="copyright">
+  <p>Developed by <a href='https://www.rug.nl/staff/m.s.berends/'>Matthijs S. Berends</a>, <a href='https://www.rug.nl/staff/c.f.luz/'>Christian F. Luz</a>, <a href='https://www.rug.nl/staff/a.w.friedrich/'>Alexander W. Friedrich</a>, <a href='https://www.rug.nl/staff/b.sinha/'>Bhanu N. M. Sinha</a>, <a href='https://www.rug.nl/staff/c.j.albers/'>Casper J. Albers</a>, <a href='https://www.rug.nl/staff/c.glasner/'>Corinna Glasner</a>.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
+</div>
+
+      </footer>
+   </div>
+
+  
+
+
+  </body>
+</html>
+
+

docs/reference/eucast_rules.html

@@ -83,7 +83,7 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9007</span>
       </span>
     </div>
 
@@ -254,6 +254,7 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied
   version_expertrules <span class='op'>=</span> <span class='fl'>3.2</span>,
   ampc_cephalosporin_resistance <span class='op'>=</span> <span class='cn'>NA</span>,
   only_rsi_columns <span class='op'>=</span> <span class='cn'>FALSE</span>,
+  custom_rules <span class='op'>=</span> <span class='cn'>NULL</span>,
   <span class='va'>...</span>
 <span class='op'>)</span>
 
@@ -276,7 +277,7 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied
     </tr>
     <tr>
       <th>rules</th>
-      <td><p>a character vector that specifies which rules should be applied. Must be one or more of <code>"breakpoints"</code>, <code>"expert"</code>, <code>"other"</code>, <code>"all"</code>, and defaults to <code><a href='https://rdrr.io/r/base/c.html'>c("breakpoints", "expert")</a></code>. The default value can be set to another value, e.g. using <code><a href='https://rdrr.io/r/base/options.html'>options(AMR_eucastrules = "all")</a></code>.</p></td>
+      <td><p>a character vector that specifies which rules should be applied. Must be one or more of <code>"breakpoints"</code>, <code>"expert"</code>, <code>"other"</code>, <code>"custom"</code>, <code>"all"</code>, and defaults to <code><a href='https://rdrr.io/r/base/c.html'>c("breakpoints", "expert")</a></code>. The default value can be set to another value, e.g. using <code><a href='https://rdrr.io/r/base/options.html'>options(AMR_eucastrules = "all")</a></code>. If using <code>"custom"</code>, be sure to fill in argument <code>custom_rules</code> too. Custom rules can be created with <code><a href='custom_eucast_rules.html'>custom_eucast_rules()</a></code>.</p></td>
     </tr>
     <tr>
       <th>verbose</th>
@@ -298,6 +299,10 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied
       <th>only_rsi_columns</th>
       <td><p>a logical to indicate whether only antibiotic columns must be detected that were transformed to class <code>&lt;rsi&gt;</code> (see <code><a href='as.rsi.html'>as.rsi()</a></code>) on beforehand (defaults to <code>FALSE</code>)</p></td>
     </tr>
+    <tr>
+      <th>custom_rules</th>
+      <td><p>custom rules to apply, created with <code><a href='custom_eucast_rules.html'>custom_eucast_rules()</a></code></p></td>
+    </tr>
     <tr>
       <th>...</th>
       <td><p>column name of an antibiotic, see section <em>Antibiotics</em> below</p></td>
@@ -331,8 +336,18 @@ Leclercq et al. <strong>EUCAST expert rules in antimicrobial susceptibility test
     <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
 
     <p><strong>Note:</strong> This function does not translate MIC values to RSI values. Use <code><a href='as.rsi.html'>as.rsi()</a></code> for that. <br />
-<strong>Note:</strong> When ampicillin (AMP, J01CA01) is not available but amoxicillin (AMX, J01CA04) is, the latter will be used for all rules where there is a dependency on ampicillin. These drugs are interchangeable when it comes to expression of antimicrobial resistance.</p>
-<p>The file containing all EUCAST rules is located here: <a href='https://github.com/msberends/AMR/blob/master/data-raw/eucast_rules.tsv'>https://github.com/msberends/AMR/blob/master/data-raw/eucast_rules.tsv</a>.</p><h3 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>'Other' Rules</h3>
+<strong>Note:</strong> When ampicillin (AMP, J01CA01) is not available but amoxicillin (AMX, J01CA04) is, the latter will be used for all rules where there is a dependency on ampicillin. These drugs are interchangeable when it comes to expression of antimicrobial resistance. <br /></p>
+<p>The file containing all EUCAST rules is located here: <a href='https://github.com/msberends/AMR/blob/master/data-raw/eucast_rules.tsv'>https://github.com/msberends/AMR/blob/master/data-raw/eucast_rules.tsv</a>.  <strong>Note:</strong> Old taxonomic names are replaced with the current taxonomy where applicable. For example, <em>Ochrobactrum anthropi</em> was renamed to <em>Brucella anthropi</em> in 2020; the original EUCAST rules v3.1 and v3.2 did not yet contain this new taxonomic name. The file used as input for this <code>AMR</code> package contains the taxonomy updated until <a href='catalogue_of_life.html'>March 2021</a>.</p><h3 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>Custom Rules</h3>
+
+
+<p>Custom rules can be created using <code><a href='custom_eucast_rules.html'>custom_eucast_rules()</a></code>, e.g.:</p><pre><span class='va'>x</span> <span class='op'>&lt;-</span> <span class='fu'><a href='custom_eucast_rules.html'>custom_eucast_rules</a></span><span class='op'>(</span><span class='va'>AMC</span> <span class='op'>==</span> <span class='st'>"R"</span> <span class='op'>&amp;</span> <span class='va'>genus</span> <span class='op'>==</span> <span class='st'>"Klebsiella"</span> <span class='op'>~</span> <span class='va'>aminopenicillins</span> <span class='op'>==</span> <span class='st'>"R"</span>,
+                         <span class='va'>AMC</span> <span class='op'>==</span> <span class='st'>"I"</span> <span class='op'>&amp;</span> <span class='va'>genus</span> <span class='op'>==</span> <span class='st'>"Klebsiella"</span> <span class='op'>~</span> <span class='va'>aminopenicillins</span> <span class='op'>==</span> <span class='st'>"I"</span><span class='op'>)</span>
+
+<span class='fu'>eucast_rules</span><span class='op'>(</span><span class='va'>example_isolates</span>, rules <span class='op'>=</span> <span class='st'>"custom"</span>, custom_rules <span class='op'>=</span> <span class='va'>x</span><span class='op'>)</span>
+</pre>
+
+
+<h3 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>'Other' Rules</h3>
 
 
 <p>Before further processing, two non-EUCAST rules about drug combinations can be applied to improve the efficacy of the EUCAST rules, and the reliability of your data (analysis). These rules are:</p><ol>

docs/reference/first_isolate.html

@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.5.0.9040</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9009</span>
       </span>
     </div>
 
@@ -314,7 +314,7 @@
     </tr>
     <tr>
       <th>col_keyantibiotics</th>
-      <td><p>column name of the key antibiotics to determine first (weighted) isolates, see <code><a href='key_antibiotics.html'>key_antibiotics()</a></code>. Defaults to the first column that starts with 'key' followed by 'ab' or 'antibiotics' (case insensitive). Use <code>col_keyantibiotics = FALSE</code> to prevent this.</p></td>
+      <td><p>column name of the key antibiotics to determine first (weighted) isolates, see <code><a href='key_antibiotics.html'>key_antibiotics()</a></code>. Defaults to the first column that starts with 'key' followed by 'ab' or 'antibiotics' (case insensitive). Use <code>col_keyantibiotics = FALSE</code> to prevent this. Can also be the output of <code><a href='key_antibiotics.html'>key_antibiotics()</a></code>.</p></td>
     </tr>
     <tr>
       <th>episode_days</th>
@@ -346,7 +346,7 @@
     </tr>
     <tr>
       <th>info</th>
-      <td><p>print progress</p></td>
+      <td><p>a <a href='https://rdrr.io/r/base/logical.html'>logical</a> to indicate info should be printed, defaults to <code>TRUE</code> only in interactive mode</p></td>
     </tr>
     <tr>
       <th>include_unknown</th>

docs/reference/get_episode.html

@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.5.0.9016</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9003</span>
       </span>
     </div>
 
@@ -255,7 +255,7 @@
     </tr>
     <tr>
       <th>episode_days</th>
-      <td><p>required episode length in days, can also be less than a day, see <em>Details</em></p></td>
+      <td><p>required episode length in days, can also be less than a day or <code>Inf</code>, see <em>Details</em></p></td>
     </tr>
     <tr>
       <th>...</th>
@@ -337,7 +337,7 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
   <span class='co'># grouping on patients and microorganisms leads to the same results</span>
   <span class='co'># as first_isolate():</span>
   <span class='va'>x</span> <span class='op'>&lt;-</span> <span class='va'>example_isolates</span> <span class='op'>%&gt;%</span>
-    <span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span><span class='op'>(</span><span class='fu'><a href='first_isolate.html'>first_isolate</a></span><span class='op'>(</span><span class='va'>.</span>, include_unknown <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span><span class='op'>)</span>
+    <span class='fu'><a href='first_isolate.html'>filter_first_isolate</a></span><span class='op'>(</span>include_unknown <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
     
   <span class='va'>y</span> <span class='op'>&lt;-</span> <span class='va'>example_isolates</span> <span class='op'>%&gt;%</span>
     <span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span><span class='op'>(</span><span class='va'>patient_id</span>, <span class='va'>mo</span><span class='op'>)</span> <span class='op'>%&gt;%</span>

docs/reference/ggplot_pca.html

@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9000</span>
       </span>
     </div>
 

docs/reference/index.html

@@ -81,7 +81,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9009</span>
       </span>
     </div>
 
@@ -450,6 +450,12 @@
           <p><code><a href="eucast_rules.html">eucast_rules()</a></code> <code><a href="eucast_rules.html">eucast_dosage()</a></code> </p>
         </td>
         <td><p>Apply EUCAST Rules</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="custom_eucast_rules.html">custom_eucast_rules()</a></code> </p>
+        </td>
+        <td><p>Define Custom EUCAST Rules</p></td>
       </tr>
     </tbody><tbody>
       <tr>
@@ -593,9 +599,9 @@
       </tr><tr>
         
         <td>
-          <p><code><a href="like.html">like()</a></code> <code><a href="like.html">`%like%`</a></code> <code><a href="like.html">`%like_case%`</a></code> </p>
+          <p><code><a href="like.html">like()</a></code> <code><a href="like.html">`%like%`</a></code> <code><a href="like.html">`%unlike%`</a></code> <code><a href="like.html">`%like_case%`</a></code> <code><a href="like.html">`%unlike_case%`</a></code> </p>
         </td>
-        <td><p>Pattern Matching with Keyboard Shortcut</p></td>
+        <td><p>Vectorised Pattern Matching with Keyboard Shortcut</p></td>
       </tr><tr>
         
         <td>

docs/reference/key_antibiotics.html

@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.5.0.9040</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9009</span>
       </span>
     </div>
 
@@ -273,7 +273,9 @@
   type <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"keyantibiotics"</span>, <span class='st'>"points"</span><span class='op'>)</span>,
   ignore_I <span class='op'>=</span> <span class='cn'>TRUE</span>,
   points_threshold <span class='op'>=</span> <span class='fl'>2</span>,
-  info <span class='op'>=</span> <span class='cn'>FALSE</span>
+  info <span class='op'>=</span> <span class='cn'>FALSE</span>,
+  na.rm <span class='op'>=</span> <span class='cn'>TRUE</span>,
+  <span class='va'>...</span>
 <span class='op'>)</span></pre>
 
     <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
@@ -325,7 +327,11 @@
     </tr>
     <tr>
       <th>info</th>
-      <td><p>print progress</p></td>
+      <td><p>unused - previously used to indicate whether a progress bar should print</p></td>
+    </tr>
+    <tr>
+      <th>na.rm</th>
+      <td><p>a <a href='https://rdrr.io/r/base/logical.html'>logical</a> to indicate whether comparison with <code>NA</code> should return <code>FALSE</code> (defaults to <code>TRUE</code> for backwards compatibility)</p></td>
     </tr>
     </table>
 

docs/reference/like.html

@@ -6,7 +6,7 @@
 <meta http-equiv="X-UA-Compatible" content="IE=edge">
 <meta name="viewport" content="width=device-width, initial-scale=1.0">
 
-<title>Pattern Matching with Keyboard Shortcut — like • AMR (for R)</title>
+<title>Vectorised Pattern Matching with Keyboard Shortcut — like • AMR (for R)</title>
 
 <!-- favicons -->
 <link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
@@ -48,7 +48,7 @@
   <link href="../extra.css" rel="stylesheet">
   <script src="../extra.js"></script>
 
-<meta property="og:title" content="Pattern Matching with Keyboard Shortcut — like" />
+<meta property="og:title" content="Vectorised Pattern Matching with Keyboard Shortcut — like" />
 <meta property="og:description" content="Convenient wrapper around grepl() to match a pattern: x %like% pattern. It always returns a logical vector and is always case-insensitive (use x %like_case% pattern for case-sensitive matching). Also, pattern can be as long as x to compare items of each index in both vectors, or they both can have the same length to iterate over all cases." />
 <meta property="og:image" content="https://msberends.github.io/AMR/logo.png" />
 
@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.5.0.9027</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9008</span>
       </span>
     </div>
 
@@ -233,7 +233,7 @@
 <div class="row">
   <div class="col-md-9 contents">
     <div class="page-header">
-    <h1>Pattern Matching with Keyboard Shortcut</h1>
+    <h1>Vectorised Pattern Matching with Keyboard Shortcut</h1>
     <small class="dont-index">Source: <a href='https://github.com/msberends/AMR/blob/master/R/like.R'><code>R/like.R</code></a></small>
     <div class="hidden name"><code>like.Rd</code></div>
     </div>
@@ -246,7 +246,11 @@
 
 <span class='va'>x</span> <span class='op'>%like%</span> <span class='va'>pattern</span>
 
-<span class='va'>x</span> <span class='op'>%like_case%</span> <span class='va'>pattern</span></pre>
+<span class='va'>x</span> <span class='op'>%unlike%</span> <span class='va'>pattern</span>
+
+<span class='va'>x</span> <span class='op'>%like_case%</span> <span class='va'>pattern</span>
+
+<span class='va'>x</span> <span class='op'>%unlike_case%</span> <span class='va'>pattern</span></pre>
 
     <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
     <table class="ref-arguments">
@@ -257,7 +261,7 @@
     </tr>
     <tr>
       <th>pattern</th>
-      <td><p>a character string containing a regular expression (or <a href='https://rdrr.io/r/base/character.html'>character</a> string for <code>fixed = TRUE</code>) to be matched in the given character vector. Coerced by <code><a href='https://rdrr.io/r/base/character.html'>as.character()</a></code> to a character string if possible.  If a <a href='https://rdrr.io/r/base/character.html'>character</a> vector of length 2 or more is supplied, the first element is used with a warning.</p></td>
+      <td><p>a character vector containing regular expressions (or a <a href='https://rdrr.io/r/base/character.html'>character</a> string for <code>fixed = TRUE</code>) to be matched in the given character vector. Coerced by <code><a href='https://rdrr.io/r/base/character.html'>as.character()</a></code> to a character string if possible.</p></td>
     </tr>
     <tr>
       <th>ignore.case</th>
@@ -267,20 +271,20 @@
 
     <h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
 
-    <p>Idea from the <a href='https://github.com/Rdatatable/data.table/blob/master/R/like.R'><code>like</code> function from the <code>data.table</code> package</a></p>
+    <p>Idea from the <a href='https://github.com/Rdatatable/data.table/blob/ec1259af1bf13fc0c96a1d3f9e84d55d8106a9a4/R/like.R'><code>like</code> function from the <code>data.table</code> package</a>, although altered as explained in <em>Details</em>.</p>
     <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
 
-    <p>A <code><a href='https://rdrr.io/r/base/logical.html'>logical</a></code> vector</p>
+    <p>A <a href='https://rdrr.io/r/base/logical.html'>logical</a> vector</p>
     <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
 
-    <p>The <code>%like%</code> function:</p><ul>
-<li><p>Is case-insensitive (use <code>%like_case%</code> for case-sensitive matching)</p></li>
-<li><p>Supports multiple patterns</p></li>
-<li><p>Checks if <code>pattern</code> is a regular expression and sets <code>fixed = TRUE</code> if not, to greatly improve speed</p></li>
-<li><p>Always uses compatibility with Perl</p></li>
+    <p>These <code>like()</code> and <code>%like%</code>/<code>%unlike%</code> functions:</p><ul>
+<li><p>Are case-insensitive (use <code>%like_case%</code>/<code>%unlike_case%</code> for case-sensitive matching)</p></li>
+<li><p>Support multiple patterns</p></li>
+<li><p>Check if <code>pattern</code> is a valid regular expression and sets <code>fixed = TRUE</code> if not, to greatly improve speed (vectorised over <code>pattern</code>)</p></li>
+<li><p>Always use compatibility with Perl unless <code>fixed = TRUE</code>, to greatly improve speed</p></li>
 </ul>
 
-<p>Using RStudio? The text <code>%like%</code> can also be directly inserted in your code from the Addins menu and can have its own Keyboard Shortcut like <code>Ctrl+Shift+L</code> or <code>Cmd+Shift+L</code> (see <code>Tools</code> &gt; <code>Modify Keyboard Shortcuts...</code>).</p>
+<p>Using RStudio? The <code>%like%</code>/<code>%unlike%</code> functions can also be directly inserted in your code from the Addins menu and can have its own keyboard shortcut like <code>Shift+Ctrl+L</code> or <code>Shift+Cmd+L</code> (see menu <code>Tools</code> &gt; <code>Modify Keyboard Shortcuts...</code>). If you keep pressing your shortcut, the inserted text will be iterated over <code>%like%</code> -&gt; <code>%unlike%</code> -&gt; <code>%like_case%</code> -&gt; <code>%unlike_case%</code>.</p>
     <h2 class="hasAnchor" id="stable-lifecycle"><a class="anchor" href="#stable-lifecycle"></a>Stable Lifecycle</h2>
 
     
@@ -298,8 +302,7 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
     <div class='dont-index'><p><code><a href='https://rdrr.io/r/base/grep.html'>grepl()</a></code></p></div>
 
     <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><span class='co'># simple test</span>
-<span class='va'>a</span> <span class='op'>&lt;-</span> <span class='st'>"This is a test"</span>
+    <pre class="examples"><span class='va'>a</span> <span class='op'>&lt;-</span> <span class='st'>"This is a test"</span>
 <span class='va'>b</span> <span class='op'>&lt;-</span> <span class='st'>"TEST"</span>
 <span class='va'>a</span> <span class='op'>%like%</span> <span class='va'>b</span>
 <span class='co'>#&gt; TRUE</span>
@@ -311,16 +314,23 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
 <span class='va'>b</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span>     <span class='st'>"case"</span>,           <span class='st'>"diff"</span>,      <span class='st'>"yet"</span><span class='op'>)</span>
 <span class='va'>a</span> <span class='op'>%like%</span> <span class='va'>b</span>
 <span class='co'>#&gt; TRUE TRUE TRUE</span>
+<span class='va'>a</span> <span class='op'>%unlike%</span> <span class='va'>b</span>
+<span class='co'>#&gt; FALSE FALSE FALSE</span>
+
 <span class='va'>a</span><span class='op'>[</span><span class='fl'>1</span><span class='op'>]</span> <span class='op'>%like%</span> <span class='va'>b</span>
 <span class='co'>#&gt; TRUE FALSE FALSE</span>
 <span class='va'>a</span> <span class='op'>%like%</span> <span class='va'>b</span><span class='op'>[</span><span class='fl'>1</span><span class='op'>]</span>
 <span class='co'>#&gt; TRUE FALSE FALSE</span>
 
 <span class='co'># get isolates whose name start with 'Ent' or 'ent'</span>
+<span class='va'>example_isolates</span><span class='op'>[</span><span class='fu'><a href='https://rdrr.io/r/base/which.html'>which</a></span><span class='op'>(</span><span class='fu'><a href='mo_property.html'>mo_name</a></span><span class='op'>(</span><span class='va'>example_isolates</span><span class='op'>$</span><span class='va'>mo</span><span class='op'>)</span> <span class='op'>%like%</span> <span class='st'>"^ent"</span><span class='op'>)</span>, <span class='op'>]</span>
 <span class='co'># \donttest{</span>
+<span class='co'># faster way, only works in R 3.2 and later:</span>
+<span class='va'>example_isolates</span><span class='op'>[</span><span class='fu'><a href='https://rdrr.io/r/base/which.html'>which</a></span><span class='op'>(</span><span class='fu'><a href='mo_property.html'>mo_name</a></span><span class='op'>(</span><span class='op'>)</span> <span class='op'>%like%</span> <span class='st'>"^ent"</span><span class='op'>)</span>, <span class='op'>]</span>
+
 <span class='kw'>if</span> <span class='op'>(</span><span class='kw'><a href='https://rdrr.io/r/base/library.html'>require</a></span><span class='op'>(</span><span class='st'><a href='https://dplyr.tidyverse.org'>"dplyr"</a></span><span class='op'>)</span><span class='op'>)</span> <span class='op'>{</span>
   <span class='va'>example_isolates</span> <span class='op'>%&gt;%</span>
-    <span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span><span class='op'>(</span><span class='fu'><a href='mo_property.html'>mo_name</a></span><span class='op'>(</span><span class='va'>mo</span><span class='op'>)</span> <span class='op'>%like%</span> <span class='st'>"^ent"</span><span class='op'>)</span>
+    <span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span><span class='op'>(</span><span class='fu'><a href='mo_property.html'>mo_name</a></span><span class='op'>(</span><span class='op'>)</span> <span class='op'>%like%</span> <span class='st'>"^ent"</span><span class='op'>)</span>
 <span class='op'>}</span>
 <span class='co'># }</span>
 </pre>

docs/reference/mdro.html

@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9007</span>
       </span>
     </div>
 
@@ -360,7 +360,7 @@ Ordered <a href='https://rdrr.io/r/base/factor.html'>factor</a> with levels <cod
 
 
 <p>Custom guidelines can be set with the <code>custom_mdro_guideline()</code> function. This is of great importance if you have custom rules to determine MDROs in your hospital, e.g., rules that are dependent on ward, state of contact isolation or other variables in your data.</p>
-<p>If you are familiar with <code><a href='https://dplyr.tidyverse.org/reference/case_when.html'>case_when()</a></code> of the <code>dplyr</code> package, you will recognise the input method to set your own rules. Rules must be set using what <span style="R">R</span> considers to be the 'formula notation':</p><pre><span class='va'>custom</span> <span class='op'>&lt;-</span> <span class='fu'>custom_mdro_guideline</span><span class='op'>(</span><span class='va'>CIP</span> <span class='op'>==</span> <span class='st'>"R"</span> <span class='op'>&amp;</span> <span class='va'>age</span> <span class='op'>&gt;</span> <span class='fl'>60</span> <span class='op'>~</span> <span class='st'>"Elderly Type A"</span>,
+<p>If you are familiar with the <code><a href='https://dplyr.tidyverse.org/reference/case_when.html'>case_when()</a></code> function of the <code>dplyr</code> package, you will recognise the input method to set your own rules. Rules must be set using what <span style="R">R</span> considers to be the 'formula notation'. The rule is written <em>before</em> the tilde (<code><a href='https://rdrr.io/r/base/tilde.html'>~</a></code>) and the consequence of the rule is written <em>after</em> the tilde:</p><pre><span class='va'>custom</span> <span class='op'>&lt;-</span> <span class='fu'>custom_mdro_guideline</span><span class='op'>(</span><span class='va'>CIP</span> <span class='op'>==</span> <span class='st'>"R"</span> <span class='op'>&amp;</span> <span class='va'>age</span> <span class='op'>&gt;</span> <span class='fl'>60</span> <span class='op'>~</span> <span class='st'>"Elderly Type A"</span>,
                                 <span class='va'>ERY</span> <span class='op'>==</span> <span class='st'>"R"</span> <span class='op'>&amp;</span> <span class='va'>age</span> <span class='op'>&gt;</span> <span class='fl'>60</span> <span class='op'>~</span> <span class='st'>"Elderly Type B"</span><span class='op'>)</span>
 </pre>
 
@@ -374,10 +374,19 @@ Ordered <a href='https://rdrr.io/r/base/factor.html'>factor</a> with levels <cod
 <span class='co'>#&gt; Unmatched rows will return NA.</span>
 </pre>
 
-<p>The outcome of the function can be used for the <code>guideline</code> argument in the <code>mdro()</code> function:</p><pre><span class='va'>x</span> <span class='op'>&lt;-</span> <span class='fu'>mdro</span><span class='op'>(</span><span class='va'>example_isolates</span>, guideline <span class='op'>=</span> <span class='va'>custom</span><span class='op'>)</span>
+<p>The outcome of the function can be used for the <code>guideline</code> argument in the <code>mdro()</code> function:</p><pre><span class='va'>x</span> <span class='op'>&lt;-</span> <span class='fu'>mdro</span><span class='op'>(</span><span class='va'>example_isolates</span>,
+          guideline <span class='op'>=</span> <span class='va'>custom</span><span class='op'>)</span>
 <span class='fu'><a href='https://rdrr.io/r/base/table.html'>table</a></span><span class='op'>(</span><span class='va'>x</span><span class='op'>)</span>
-<span class='co'>#&gt; Elderly Type A Elderly Type B       Negative </span>
-<span class='co'>#&gt;             43            891           1066 </span>
+<span class='co'>#&gt;       Negative Elderly Type A Elderly Type B</span>
+<span class='co'>#&gt;           1070            198            732</span>
+</pre>
+
+<p>Rules can also be combined with other custom rules by using <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code>:</p><pre><span class='va'>x</span> <span class='op'>&lt;-</span> <span class='fu'>mdro</span><span class='op'>(</span><span class='va'>example_isolates</span>,
+          guideline <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='va'>custom</span>, 
+                        <span class='fu'>custom_mdro_guideline</span><span class='op'>(</span><span class='va'>ERY</span> <span class='op'>==</span> <span class='st'>"R"</span> <span class='op'>&amp;</span> <span class='va'>age</span> <span class='op'>&gt;</span> <span class='fl'>50</span> <span class='op'>~</span> <span class='st'>"Elderly Type C"</span><span class='op'>)</span><span class='op'>)</span><span class='op'>)</span>
+<span class='fu'><a href='https://rdrr.io/r/base/table.html'>table</a></span><span class='op'>(</span><span class='va'>x</span><span class='op'>)</span>
+<span class='co'>#&gt;       Negative Elderly Type A Elderly Type B Elderly Type C </span>
+<span class='co'>#&gt;            961            198            732            109</span>
 </pre>
 
 <p>The rules set (the <code>custom</code> object in this case) could be exported to a shared file location using <code><a href='https://rdrr.io/r/base/readRDS.html'>saveRDS()</a></code> if you collaborate with multiple users. The custom rules set could then be imported using <code><a href='https://rdrr.io/r/base/readRDS.html'>readRDS()</a></code>.</p>

docs/reference/microorganisms.html

@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9007</span>
       </span>
     </div>
 
@@ -281,7 +281,7 @@
     <p>Please note that entries are only based on the Catalogue of Life and the LPSN (see below). Since these sources incorporate entries based on (recent) publications in the International Journal of Systematic and Evolutionary Microbiology (IJSEM), it can happen that the year of publication is sometimes later than one might expect.</p>
 <p>For example, <em>Staphylococcus pettenkoferi</em> was described for the first time in Diagnostic Microbiology and Infectious Disease in 2002 (doi: <a href='https://doi.org/10.1016/s0732-8893(02)00399-1'>10.1016/s0732-8893(02)00399-1</a>
 ), but it was not before 2007 that a publication in IJSEM followed (doi: <a href='https://doi.org/10.1099/ijs.0.64381-0'>10.1099/ijs.0.64381-0</a>
-). Consequently, the AMR package returns 2007 for <code><a href='mo_property.html'>mo_year("S. pettenkoferi")</a></code>.</p><h3 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>Manual additions</h3>
+). Consequently, the <code>AMR</code> package returns 2007 for <code><a href='mo_property.html'>mo_year("S. pettenkoferi")</a></code>.</p><h3 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>Manual additions</h3>
 
 
 <p>For convenience, some entries were added manually:</p><ul>

docs/reference/mo_matching_score.html

@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9007</span>
       </span>
     </div>
 
@@ -272,7 +272,7 @@
 <li><p><i>k<sub>n</sub></i> is the taxonomic kingdom of <i>n</i>, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.</p></li>
 </ul>
 
-<p>The grouping into human pathogenic prevalence (\(p\)) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. <strong>Group 1</strong> (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is <em>Enterococcus</em>, <em>Staphylococcus</em> or <em>Streptococcus</em>. This group consequently contains all common Gram-negative bacteria, such as <em>Pseudomonas</em> and <em>Legionella</em> and all species within the order Enterobacterales. <strong>Group 2</strong> consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is <em>Absidia</em>, <em>Acremonium</em>, <em>Actinotignum</em>, <em>Alternaria</em>, <em>Anaerosalibacter</em>, <em>Apophysomyces</em>, <em>Arachnia</em>, <em>Aspergillus</em>, <em>Aureobacterium</em>, <em>Aureobasidium</em>, <em>Bacteroides</em>, <em>Basidiobolus</em>, <em>Beauveria</em>, <em>Blastocystis</em>, <em>Branhamella</em>, <em>Calymmatobacterium</em>, <em>Candida</em>, <em>Capnocytophaga</em>, <em>Catabacter</em>, <em>Chaetomium</em>, <em>Chryseobacterium</em>, <em>Chryseomonas</em>, <em>Chrysonilia</em>, <em>Cladophialophora</em>, <em>Cladosporium</em>, <em>Conidiobolus</em>, <em>Cryptococcus</em>, <em>Curvularia</em>, <em>Exophiala</em>, <em>Exserohilum</em>, <em>Flavobacterium</em>, <em>Fonsecaea</em>, <em>Fusarium</em>, <em>Fusobacterium</em>, <em>Hendersonula</em>, <em>Hypomyces</em>, <em>Koserella</em>, <em>Lelliottia</em>, <em>Leptosphaeria</em>, <em>Leptotrichia</em>, <em>Malassezia</em>, <em>Malbranchea</em>, <em>Mortierella</em>, <em>Mucor</em>, <em>Mycocentrospora</em>, <em>Mycoplasma</em>, <em>Nectria</em>, <em>Ochroconis</em>, <em>Oidiodendron</em>, <em>Phoma</em>, <em>Piedraia</em>, <em>Pithomyces</em>, <em>Pityrosporum</em>, <em>Prevotella</em>, <em>Pseudallescheria</em>, <em>Rhizomucor</em>, <em>Rhizopus</em>, <em>Rhodotorula</em>, <em>Scolecobasidium</em>, <em>Scopulariopsis</em>, <em>Scytalidium</em>,<em>Sporobolomyces</em>, <em>Stachybotrys</em>, <em>Stomatococcus</em>, <em>Treponema</em>, <em>Trichoderma</em>, <em>Trichophyton</em>, <em>Trichosporon</em>, <em>Tritirachium</em> or <em>Ureaplasma</em>. <strong>Group 3</strong> consists of all other microorganisms.</p>
+<p>The grouping into human pathogenic prevalence (\(p\)) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. <strong>Group 1</strong> (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is <em>Enterococcus</em>, <em>Staphylococcus</em> or <em>Streptococcus</em>. This group consequently contains all common Gram-negative bacteria, such as <em>Pseudomonas</em> and <em>Legionella</em> and all species within the order Enterobacterales. <strong>Group 2</strong> consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is <em>Absidia</em>, <em>Acremonium</em>, <em>Actinotignum</em>, <em>Alternaria</em>, <em>Anaerosalibacter</em>, <em>Apophysomyces</em>, <em>Arachnia</em>, <em>Aspergillus</em>, <em>Aureobacterium</em>, <em>Aureobasidium</em>, <em>Bacteroides</em>, <em>Basidiobolus</em>, <em>Beauveria</em>, <em>Blastocystis</em>, <em>Branhamella</em>, <em>Calymmatobacterium</em>, <em>Candida</em>, <em>Capnocytophaga</em>, <em>Catabacter</em>, <em>Chaetomium</em>, <em>Chryseobacterium</em>, <em>Chryseomonas</em>, <em>Chrysonilia</em>, <em>Cladophialophora</em>, <em>Cladosporium</em>, <em>Conidiobolus</em>, <em>Cryptococcus</em>, <em>Curvularia</em>, <em>Exophiala</em>, <em>Exserohilum</em>, <em>Flavobacterium</em>, <em>Fonsecaea</em>, <em>Fusarium</em>, <em>Fusobacterium</em>, <em>Hendersonula</em>, <em>Hypomyces</em>, <em>Koserella</em>, <em>Lelliottia</em>, <em>Leptosphaeria</em>, <em>Leptotrichia</em>, <em>Malassezia</em>, <em>Malbranchea</em>, <em>Mortierella</em>, <em>Mucor</em>, <em>Mycocentrospora</em>, <em>Mycoplasma</em>, <em>Nectria</em>, <em>Ochroconis</em>, <em>Oidiodendron</em>, <em>Phoma</em>, <em>Piedraia</em>, <em>Pithomyces</em>, <em>Pityrosporum</em>, <em>Prevotella</em>, <em>Pseudallescheria</em>, <em>Rhizomucor</em>, <em>Rhizopus</em>, <em>Rhodotorula</em>, <em>Scolecobasidium</em>, <em>Scopulariopsis</em>, <em>Scytalidium</em>, <em>Sporobolomyces</em>, <em>Stachybotrys</em>, <em>Stomatococcus</em>, <em>Treponema</em>, <em>Trichoderma</em>, <em>Trichophyton</em>, <em>Trichosporon</em>, <em>Tritirachium</em> or <em>Ureaplasma</em>. <strong>Group 3</strong> consists of all other microorganisms.</p>
 <p>All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., <code>"E. coli"</code> will return the microbial ID of <em>Escherichia coli</em> (\(m = 0.688\), a highly prevalent microorganism found in humans) and not <em>Entamoeba coli</em> (\(m = 0.079\), a less prevalent microorganism in humans), although the latter would alphabetically come first.</p>
     <h2 class="hasAnchor" id="stable-lifecycle"><a class="anchor" href="#stable-lifecycle"></a>Stable Lifecycle</h2>
 

docs/reference/mo_property.html

@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9007</span>
       </span>
     </div>
 
@@ -376,7 +376,7 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
 <li><p><i>k<sub>n</sub></i> is the taxonomic kingdom of <i>n</i>, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.</p></li>
 </ul>
 
-<p>The grouping into human pathogenic prevalence (\(p\)) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. <strong>Group 1</strong> (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is <em>Enterococcus</em>, <em>Staphylococcus</em> or <em>Streptococcus</em>. This group consequently contains all common Gram-negative bacteria, such as <em>Pseudomonas</em> and <em>Legionella</em> and all species within the order Enterobacterales. <strong>Group 2</strong> consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is <em>Absidia</em>, <em>Acremonium</em>, <em>Actinotignum</em>, <em>Alternaria</em>, <em>Anaerosalibacter</em>, <em>Apophysomyces</em>, <em>Arachnia</em>, <em>Aspergillus</em>, <em>Aureobacterium</em>, <em>Aureobasidium</em>, <em>Bacteroides</em>, <em>Basidiobolus</em>, <em>Beauveria</em>, <em>Blastocystis</em>, <em>Branhamella</em>, <em>Calymmatobacterium</em>, <em>Candida</em>, <em>Capnocytophaga</em>, <em>Catabacter</em>, <em>Chaetomium</em>, <em>Chryseobacterium</em>, <em>Chryseomonas</em>, <em>Chrysonilia</em>, <em>Cladophialophora</em>, <em>Cladosporium</em>, <em>Conidiobolus</em>, <em>Cryptococcus</em>, <em>Curvularia</em>, <em>Exophiala</em>, <em>Exserohilum</em>, <em>Flavobacterium</em>, <em>Fonsecaea</em>, <em>Fusarium</em>, <em>Fusobacterium</em>, <em>Hendersonula</em>, <em>Hypomyces</em>, <em>Koserella</em>, <em>Lelliottia</em>, <em>Leptosphaeria</em>, <em>Leptotrichia</em>, <em>Malassezia</em>, <em>Malbranchea</em>, <em>Mortierella</em>, <em>Mucor</em>, <em>Mycocentrospora</em>, <em>Mycoplasma</em>, <em>Nectria</em>, <em>Ochroconis</em>, <em>Oidiodendron</em>, <em>Phoma</em>, <em>Piedraia</em>, <em>Pithomyces</em>, <em>Pityrosporum</em>, <em>Prevotella</em>, <em>Pseudallescheria</em>, <em>Rhizomucor</em>, <em>Rhizopus</em>, <em>Rhodotorula</em>, <em>Scolecobasidium</em>, <em>Scopulariopsis</em>, <em>Scytalidium</em>,<em>Sporobolomyces</em>, <em>Stachybotrys</em>, <em>Stomatococcus</em>, <em>Treponema</em>, <em>Trichoderma</em>, <em>Trichophyton</em>, <em>Trichosporon</em>, <em>Tritirachium</em> or <em>Ureaplasma</em>. <strong>Group 3</strong> consists of all other microorganisms.</p>
+<p>The grouping into human pathogenic prevalence (\(p\)) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. <strong>Group 1</strong> (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is <em>Enterococcus</em>, <em>Staphylococcus</em> or <em>Streptococcus</em>. This group consequently contains all common Gram-negative bacteria, such as <em>Pseudomonas</em> and <em>Legionella</em> and all species within the order Enterobacterales. <strong>Group 2</strong> consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is <em>Absidia</em>, <em>Acremonium</em>, <em>Actinotignum</em>, <em>Alternaria</em>, <em>Anaerosalibacter</em>, <em>Apophysomyces</em>, <em>Arachnia</em>, <em>Aspergillus</em>, <em>Aureobacterium</em>, <em>Aureobasidium</em>, <em>Bacteroides</em>, <em>Basidiobolus</em>, <em>Beauveria</em>, <em>Blastocystis</em>, <em>Branhamella</em>, <em>Calymmatobacterium</em>, <em>Candida</em>, <em>Capnocytophaga</em>, <em>Catabacter</em>, <em>Chaetomium</em>, <em>Chryseobacterium</em>, <em>Chryseomonas</em>, <em>Chrysonilia</em>, <em>Cladophialophora</em>, <em>Cladosporium</em>, <em>Conidiobolus</em>, <em>Cryptococcus</em>, <em>Curvularia</em>, <em>Exophiala</em>, <em>Exserohilum</em>, <em>Flavobacterium</em>, <em>Fonsecaea</em>, <em>Fusarium</em>, <em>Fusobacterium</em>, <em>Hendersonula</em>, <em>Hypomyces</em>, <em>Koserella</em>, <em>Lelliottia</em>, <em>Leptosphaeria</em>, <em>Leptotrichia</em>, <em>Malassezia</em>, <em>Malbranchea</em>, <em>Mortierella</em>, <em>Mucor</em>, <em>Mycocentrospora</em>, <em>Mycoplasma</em>, <em>Nectria</em>, <em>Ochroconis</em>, <em>Oidiodendron</em>, <em>Phoma</em>, <em>Piedraia</em>, <em>Pithomyces</em>, <em>Pityrosporum</em>, <em>Prevotella</em>, <em>Pseudallescheria</em>, <em>Rhizomucor</em>, <em>Rhizopus</em>, <em>Rhodotorula</em>, <em>Scolecobasidium</em>, <em>Scopulariopsis</em>, <em>Scytalidium</em>, <em>Sporobolomyces</em>, <em>Stachybotrys</em>, <em>Stomatococcus</em>, <em>Treponema</em>, <em>Trichoderma</em>, <em>Trichophyton</em>, <em>Trichosporon</em>, <em>Tritirachium</em> or <em>Ureaplasma</em>. <strong>Group 3</strong> consists of all other microorganisms.</p>
 <p>All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., <code>"E. coli"</code> will return the microbial ID of <em>Escherichia coli</em> (\(m = 0.688\), a highly prevalent microorganism found in humans) and not <em>Entamoeba coli</em> (\(m = 0.079\), a less prevalent microorganism in humans), although the latter would alphabetically come first.</p>
     <h2 class="hasAnchor" id="catalogue-of-life"><a class="anchor" href="#catalogue-of-life"></a>Catalogue of Life</h2>
 

docs/reference/plot.html

@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.5.0.9031</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9001</span>
       </span>
     </div>
 
@@ -258,7 +258,7 @@
 <span class='op'>)</span>
 
 <span class='co'># S3 method for mic</span>
-<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/ggplot.html'>ggplot</a></span><span class='op'>(</span>
+<span class='fu'>ggplot</span><span class='op'>(</span>
   <span class='va'>data</span>,
   mapping <span class='op'>=</span> <span class='cn'>NULL</span>,
   title <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste</a></span><span class='op'>(</span><span class='st'>"MIC values of"</span>, <span class='fu'><a href='https://rdrr.io/r/base/deparse.html'>deparse</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/substitute.html'>substitute</a></span><span class='op'>(</span><span class='va'>data</span><span class='op'>)</span><span class='op'>)</span><span class='op'>)</span>,
@@ -289,7 +289,7 @@
 <span class='op'>)</span>
 
 <span class='co'># S3 method for disk</span>
-<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/ggplot.html'>ggplot</a></span><span class='op'>(</span>
+<span class='fu'>ggplot</span><span class='op'>(</span>
   <span class='va'>data</span>,
   mapping <span class='op'>=</span> <span class='cn'>NULL</span>,
   title <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste</a></span><span class='op'>(</span><span class='st'>"Disk zones of"</span>, <span class='fu'><a href='https://rdrr.io/r/base/deparse.html'>deparse</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/substitute.html'>substitute</a></span><span class='op'>(</span><span class='va'>data</span><span class='op'>)</span><span class='op'>)</span><span class='op'>)</span>,
@@ -314,13 +314,14 @@
 <span class='op'>)</span>
 
 <span class='co'># S3 method for rsi</span>
-<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/ggplot.html'>ggplot</a></span><span class='op'>(</span>
+<span class='fu'>ggplot</span><span class='op'>(</span>
   <span class='va'>data</span>,
   mapping <span class='op'>=</span> <span class='cn'>NULL</span>,
   title <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste</a></span><span class='op'>(</span><span class='st'>"Resistance Overview of"</span>, <span class='fu'><a href='https://rdrr.io/r/base/deparse.html'>deparse</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/substitute.html'>substitute</a></span><span class='op'>(</span><span class='va'>data</span><span class='op'>)</span><span class='op'>)</span><span class='op'>)</span>,
   xlab <span class='op'>=</span> <span class='st'>"Antimicrobial Interpretation"</span>,
   ylab <span class='op'>=</span> <span class='st'>"Frequency"</span>,
   colours_RSI <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"#ED553B"</span>, <span class='st'>"#3CAEA3"</span>, <span class='st'>"#F6D55C"</span><span class='op'>)</span>,
+  language <span class='op'>=</span> <span class='fu'><a href='translate.html'>get_locale</a></span><span class='op'>(</span><span class='op'>)</span>,
   <span class='va'>...</span>
 <span class='op'>)</span></pre>
 
@@ -407,7 +408,7 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
 <span class='fu'>plot</span><span class='op'>(</span><span class='va'>some_mic_values</span>, mo <span class='op'>=</span> <span class='st'>"S. aureus"</span>, ab <span class='op'>=</span> <span class='st'>"ampicillin"</span><span class='op'>)</span>
 <span class='fu'>plot</span><span class='op'>(</span><span class='va'>some_disk_values</span>, mo <span class='op'>=</span> <span class='st'>"Escherichia coli"</span>, ab <span class='op'>=</span> <span class='st'>"cipro"</span><span class='op'>)</span>
 
-<span class='kw'>if</span> <span class='op'>(</span><span class='kw'><a href='https://rdrr.io/r/base/library.html'>require</a></span><span class='op'>(</span><span class='st'><a href='http://ggplot2.tidyverse.org'>"ggplot2"</a></span><span class='op'>)</span><span class='op'>)</span> <span class='op'>{</span>
+<span class='kw'>if</span> <span class='op'>(</span><span class='kw'><a href='https://rdrr.io/r/base/library.html'>require</a></span><span class='op'>(</span><span class='st'><a href='https://ggplot2.tidyverse.org'>"ggplot2"</a></span><span class='op'>)</span><span class='op'>)</span> <span class='op'>{</span>
   <span class='fu'><a href='https://ggplot2.tidyverse.org/reference/ggplot.html'>ggplot</a></span><span class='op'>(</span><span class='va'>some_mic_values</span><span class='op'>)</span>
   <span class='fu'><a href='https://ggplot2.tidyverse.org/reference/ggplot.html'>ggplot</a></span><span class='op'>(</span><span class='va'>some_disk_values</span>, mo <span class='op'>=</span> <span class='st'>"Escherichia coli"</span>, ab <span class='op'>=</span> <span class='st'>"cipro"</span><span class='op'>)</span>
   <span class='fu'><a href='https://ggplot2.tidyverse.org/reference/ggplot.html'>ggplot</a></span><span class='op'>(</span><span class='va'>some_rsi_values</span><span class='op'>)</span>

docs/sitemap.xml

@@ -66,6 +66,9 @@
   <url>
     <loc>https://msberends.github.io/AMR//reference/count.html</loc>
   </url>
+  <url>
+    <loc>https://msberends.github.io/AMR//reference/custom_eucast_rules.html</loc>
+  </url>
   <url>
     <loc>https://msberends.github.io/AMR//reference/dosage.html</loc>
   </url>

docs/survey.html

@@ -81,7 +81,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9009</span>
       </span>
     </div>
 

git_premaster.sh

@@ -125,6 +125,7 @@ echo "• Building package •"
 echo "••••••••••••••••••••"
 echo "• Building 'data-raw/AMR_latest.tar.gz'..."
 Rscript -e "x <- devtools::build(path = 'data-raw', vignettes = FALSE, manual = FALSE, binary = FALSE, quiet = TRUE)"
+rm data-raw/AMR_latest.tar.gz
 mv data-raw/AMR_*.tar.gz data-raw/AMR_latest.tar.gz
 echo "• Installing..."
 Rscript -e "devtools::install(quiet = TRUE, dependencies = FALSE)"

index.md

@@ -1,17 +1,12 @@
 # `AMR` (for R) <img src="./logo.png" align="right" height="120px" />
 
-*Note: the rules of 'EUCAST Clinical Breakpoints v11.0 (2021)' are now implemented*
-
-> <span class="fa fa-clipboard-list" style="color: #128f76; font-size: 20pt; margin-right: 5px;"></span> **PLEASE TAKE PART IN OUR SURVEY!**  
-> Since you are one of our users, we would like to know how you use the package and what it brought you or your organisation. **If you have a minute, please [anonymously fill in this short questionnaire](./survey.html)**. Your valuable input will help to improve the package and its functionalities. You can answer the open questions in either English, Spanish, French, Dutch, or German. Thank you very much in advance!
-> <br>
-> <a class="btn btn-info btn-amr" href="./survey.html">Take me to the 5-min survey!</a>
+*Note: the rules of 'EUCAST Clinical Breakpoints v11.0 (2021)' are now implemented.*
 
 ### What is `AMR` (for R)?
 
 *(To find out how to conduct AMR data analysis, please [continue reading here to get started](./articles/AMR.html).)*
 
-`AMR` is a free, open-source and independent [R package](https://www.r-project.org) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. **Our aim is to provide a standard** for clean and reproducible antimicrobial resistance data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.
+`AMR` is a free, open-source and independent [R package](https://www.r-project.org) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. **Our aim is to provide a standard** for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.
 
 After installing this package, R knows [**~70,000 distinct microbial species**](./reference/microorganisms.html) and all [**~550 antibiotic, antimycotic and antiviral drugs**](./reference/antibiotics.html) by name and code (including ATC, EARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data.
 

inst/CITATION

@@ -6,9 +6,9 @@ citEntry(
   author       = "M S Berends and C F Luz and A W Friedrich and B N M Sinha and C J Albers and C Glasner",
   journal      = "bioRxiv",
   publisher    = "Cold Spring Harbor Laboratory",
-  year         = 2019,
+  year         = 2021,
   url          = "https://doi.org/10.1101/810622",
-  textVersion  = "Berends MS, Luz CF et al. (2019). AMR - An R Package for Working with Antimicrobial Resistance Data. bioRxiv, https://doi.org/10.1101/810622"
+  textVersion  = "Berends MS, Luz CF et al. (2021). AMR - An R Package for Working with Antimicrobial Resistance Data. bioRxiv, https://doi.org/10.1101/810622"
 )
 
-citFooter("The mentioned article is a preprinted version of a manuscript we sent to a journal. Many thanks for using our open-source method to work with microbial and antimicrobial data!")
+citFooter("This preprint was accepted for publication in the Journal of Statistical Software, but we are awaiting the actual publication. Many thanks for using our open-source method to work with microbial and antimicrobial data!")

inst/rstudio/addins.dcf

@@ -2,6 +2,6 @@ Name: Insert %in%
 Binding: addin_insert_in
 Interactive: false
 
-Name: Insert %like%
+Name: Insert %like% or %unlike% 
 Binding: addin_insert_like
 Interactive: false

man/ab_from_text.Rd

@@ -10,6 +10,7 @@ ab_from_text(
   collapse = NULL,
   translate_ab = FALSE,
   thorough_search = NULL,
+  info = interactive(),
   ...
 )
 }
@@ -24,6 +25,8 @@ ab_from_text(
 
 \item{thorough_search}{logical to indicate whether the input must be extensively searched for misspelling and other faulty input values. Setting this to \code{TRUE} will take considerably more time than when using \code{FALSE}. At default, it will turn \code{TRUE} when all input elements contain a maximum of three words.}
 
+\item{info}{logical to indicate whether a progress bar should be printed, defaults to \code{TRUE} only in interactive mode}
+
 \item{...}{arguments passed on to \code{\link[=as.ab]{as.ab()}}}
 }
 \value{

man/as.ab.Rd

@@ -6,7 +6,7 @@
 \alias{is.ab}
 \title{Transform Input to an Antibiotic ID}
 \usage{
-as.ab(x, flag_multiple_results = TRUE, info = TRUE, ...)
+as.ab(x, flag_multiple_results = TRUE, info = interactive(), ...)
 
 is.ab(x)
 }
@@ -15,7 +15,7 @@ is.ab(x)
 
 \item{flag_multiple_results}{logical to indicate whether a note should be printed to the console that probably more than one antibiotic code or name can be retrieved from a single input value.}
 
-\item{info}{logical to indicate whether a progress bar should be printed}
+\item{info}{a \link{logical} to indicate whether a progress bar should be printed, defaults to \code{TRUE} only in interactive mode}
 
 \item{...}{arguments passed on to internal functions}
 }

man/as.mo.Rd

@@ -17,6 +17,7 @@ as.mo(
   reference_df = get_mo_source(),
   ignore_pattern = getOption("AMR_ignore_pattern"),
   language = get_locale(),
+  info = interactive(),
   ...
 )
 
@@ -47,6 +48,8 @@ This excludes \emph{Enterococci} at default (who are in group D), use \code{Lanc
 
 \item{language}{language to translate text like "no growth", which defaults to the system language (see \code{\link[=get_locale]{get_locale()}})}
 
+\item{info}{a \link{logical} to indicate if a progress bar should be printed if more than 25 items are to be coerced, defaults to \code{TRUE} only in interactive mode}
+
 \item{...}{other arguments passed on to functions}
 }
 \value{
@@ -157,7 +160,7 @@ where:
 \item \ifelse{html}{\out{<i>k<sub>n</sub></i> is the taxonomic kingdom of <i>n</i>, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}}{l_n is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}
 }
 
-The grouping into human pathogenic prevalence (\eqn{p}) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. \strong{Group 1} (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is \emph{Enterococcus}, \emph{Staphylococcus} or \emph{Streptococcus}. This group consequently contains all common Gram-negative bacteria, such as \emph{Pseudomonas} and \emph{Legionella} and all species within the order Enterobacterales. \strong{Group 2} consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is \emph{Absidia}, \emph{Acremonium}, \emph{Actinotignum}, \emph{Alternaria}, \emph{Anaerosalibacter}, \emph{Apophysomyces}, \emph{Arachnia}, \emph{Aspergillus}, \emph{Aureobacterium}, \emph{Aureobasidium}, \emph{Bacteroides}, \emph{Basidiobolus}, \emph{Beauveria}, \emph{Blastocystis}, \emph{Branhamella}, \emph{Calymmatobacterium}, \emph{Candida}, \emph{Capnocytophaga}, \emph{Catabacter}, \emph{Chaetomium}, \emph{Chryseobacterium}, \emph{Chryseomonas}, \emph{Chrysonilia}, \emph{Cladophialophora}, \emph{Cladosporium}, \emph{Conidiobolus}, \emph{Cryptococcus}, \emph{Curvularia}, \emph{Exophiala}, \emph{Exserohilum}, \emph{Flavobacterium}, \emph{Fonsecaea}, \emph{Fusarium}, \emph{Fusobacterium}, \emph{Hendersonula}, \emph{Hypomyces}, \emph{Koserella}, \emph{Lelliottia}, \emph{Leptosphaeria}, \emph{Leptotrichia}, \emph{Malassezia}, \emph{Malbranchea}, \emph{Mortierella}, \emph{Mucor}, \emph{Mycocentrospora}, \emph{Mycoplasma}, \emph{Nectria}, \emph{Ochroconis}, \emph{Oidiodendron}, \emph{Phoma}, \emph{Piedraia}, \emph{Pithomyces}, \emph{Pityrosporum}, \emph{Prevotella}, \emph{Pseudallescheria}, \emph{Rhizomucor}, \emph{Rhizopus}, \emph{Rhodotorula}, \emph{Scolecobasidium}, \emph{Scopulariopsis}, \emph{Scytalidium},\emph{Sporobolomyces}, \emph{Stachybotrys}, \emph{Stomatococcus}, \emph{Treponema}, \emph{Trichoderma}, \emph{Trichophyton}, \emph{Trichosporon}, \emph{Tritirachium} or \emph{Ureaplasma}. \strong{Group 3} consists of all other microorganisms.
+The grouping into human pathogenic prevalence (\eqn{p}) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. \strong{Group 1} (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is \emph{Enterococcus}, \emph{Staphylococcus} or \emph{Streptococcus}. This group consequently contains all common Gram-negative bacteria, such as \emph{Pseudomonas} and \emph{Legionella} and all species within the order Enterobacterales. \strong{Group 2} consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is \emph{Absidia}, \emph{Acremonium}, \emph{Actinotignum}, \emph{Alternaria}, \emph{Anaerosalibacter}, \emph{Apophysomyces}, \emph{Arachnia}, \emph{Aspergillus}, \emph{Aureobacterium}, \emph{Aureobasidium}, \emph{Bacteroides}, \emph{Basidiobolus}, \emph{Beauveria}, \emph{Blastocystis}, \emph{Branhamella}, \emph{Calymmatobacterium}, \emph{Candida}, \emph{Capnocytophaga}, \emph{Catabacter}, \emph{Chaetomium}, \emph{Chryseobacterium}, \emph{Chryseomonas}, \emph{Chrysonilia}, \emph{Cladophialophora}, \emph{Cladosporium}, \emph{Conidiobolus}, \emph{Cryptococcus}, \emph{Curvularia}, \emph{Exophiala}, \emph{Exserohilum}, \emph{Flavobacterium}, \emph{Fonsecaea}, \emph{Fusarium}, \emph{Fusobacterium}, \emph{Hendersonula}, \emph{Hypomyces}, \emph{Koserella}, \emph{Lelliottia}, \emph{Leptosphaeria}, \emph{Leptotrichia}, \emph{Malassezia}, \emph{Malbranchea}, \emph{Mortierella}, \emph{Mucor}, \emph{Mycocentrospora}, \emph{Mycoplasma}, \emph{Nectria}, \emph{Ochroconis}, \emph{Oidiodendron}, \emph{Phoma}, \emph{Piedraia}, \emph{Pithomyces}, \emph{Pityrosporum}, \emph{Prevotella}, \emph{Pseudallescheria}, \emph{Rhizomucor}, \emph{Rhizopus}, \emph{Rhodotorula}, \emph{Scolecobasidium}, \emph{Scopulariopsis}, \emph{Scytalidium}, \emph{Sporobolomyces}, \emph{Stachybotrys}, \emph{Stomatococcus}, \emph{Treponema}, \emph{Trichoderma}, \emph{Trichophyton}, \emph{Trichosporon}, \emph{Tritirachium} or \emph{Ureaplasma}. \strong{Group 3} consists of all other microorganisms.
 
 All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., \code{"E. coli"} will return the microbial ID of \emph{Escherichia coli} (\eqn{m = 0.688}, a highly prevalent microorganism found in humans) and not \emph{Entamoeba coli} (\eqn{m = 0.079}, a less prevalent microorganism in humans), although the latter would alphabetically come first.
 }

man/custom_eucast_rules.Rd

@@ -0,0 +1,115 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/custom_eucast_rules.R
+\name{custom_eucast_rules}
+\alias{custom_eucast_rules}
+\title{Define Custom EUCAST Rules}
+\usage{
+custom_eucast_rules(...)
+}
+\arguments{
+\item{...}{rules in formula notation, see \emph{Examples}}
+}
+\value{
+A \link{list} containing the custom rules
+}
+\description{
+Define custom EUCAST rules for your organisation or specific analysis and use the output of this function in \code{\link[=eucast_rules]{eucast_rules()}}.
+}
+\details{
+Some organisations have their own adoption of EUCAST rules. This function can be used to define custom EUCAST rules to be used in the \code{\link[=eucast_rules]{eucast_rules()}} function.
+}
+\section{How it works}{
+
+\subsection{Basics}{
+
+If you are familiar with the \code{\link[dplyr:case_when]{case_when()}} function of the \code{dplyr} package, you will recognise the input method to set your own rules. Rules must be set using what \R considers to be the 'formula notation'. The rule itself is written \emph{before} the tilde (\code{~}) and the consequence of the rule is written \emph{after} the tilde:\preformatted{x <- custom_eucast_rules(TZP == "S" ~ aminopenicillins == "S",
+                         TZP == "R" ~ aminopenicillins == "R")
+}
+
+These are two custom EUCAST rules: if TZP (piperacillin/tazobactam) is "S", all aminopenicillins (ampicillin and amoxicillin) must be made "S", and if TZP is "R", aminopenicillins must be made "R". These rules can also be printed to the console, so it is immediately clear how they work:\preformatted{x
+#> A set of custom EUCAST rules:
+#> 
+#>   1. If TZP is S then set to S:
+#>      amoxicillin (AMX), ampicillin (AMP)
+#> 
+#>   2. If TZP is R then set to R:
+#>      amoxicillin (AMX), ampicillin (AMP)
+}
+
+The rules (the part \emph{before} the tilde, in above example \code{TZP == "S"} and \code{TZP == "R"}) must be evaluable in your data set: it should be able to run as a filter in your data set without errors. This means for the above example that the column \code{TZP} must exist. We will create a sample data set and test the rules set:\preformatted{df <- data.frame(mo = c("E. coli", "K. pneumoniae"),
+                 TZP = "R",
+                 amox = "",
+                 AMP = "")
+df
+#>              mo TZP amox AMP
+#> 1       E. coli   R         
+#> 2 K. pneumoniae   R         
+                 
+eucast_rules(df, rules = "custom", custom_rules = x)
+#>              mo TZP amox AMP
+#> 1       E. coli   R    R   R     
+#> 2 K. pneumoniae   R    R   R  
+}
+}
+
+\subsection{Using taxonomic properties in rules}{
+
+There is one exception in variables used for the rules: all column names of the \link{microorganisms} data set can also be used, but do not have to exist in the data set. These column names are: \code{mo}, \code{fullname}, \code{kingdom}, \code{phylum}, \code{class}, \code{order}, \code{family}, \code{genus}, \code{species}, \code{subspecies}, \code{rank}, \code{ref}, \code{species_id}, \code{source}, \code{prevalence} and \code{snomed}. Thus, this next example will work as well, despite the fact that the \code{df} data set does not contain a column \code{genus}:\preformatted{y <- custom_eucast_rules(TZP == "S" & genus == "Klebsiella" ~ aminopenicillins == "S",
+                         TZP == "R" & genus == "Klebsiella" ~ aminopenicillins == "R")
+
+eucast_rules(df, rules = "custom", custom_rules = y)
+#>              mo TZP amox AMP
+#> 1       E. coli   R         
+#> 2 K. pneumoniae   R    R   R
+}
+}
+
+\subsection{Usage of antibiotic group names}{
+
+It is possible to define antibiotic groups instead of single antibiotics for the rule consequence, the part \emph{after} the tilde. In above examples, the antibiotic group \code{aminopenicillins} is used to include ampicillin and amoxicillin. The following groups are allowed (case-insensitive). Within parentheses are the antibiotic agents that will be matched when running the rule.
+\itemize{
+\item \code{aminoglycosides}\cr(amikacin, amikacin/fosfomycin, amphotericin B-high, 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, tobramycin-high)
+\item \code{aminopenicillins}\cr(amoxicillin, ampicillin)
+\item \code{betalactams}\cr(amoxicillin, amoxicillin/clavulanic acid, amoxicillin/sulbactam, ampicillin, ampicillin/sulbactam, apalcillin, aspoxicillin, avibactam, azidocillin, azlocillin, aztreonam, aztreonam/avibactam, bacampicillin, benzathine benzylpenicillin, benzathine phenoxymethylpenicillin, benzylpenicillin, biapenem, cadazolid, carbenicillin, carindacillin, cefacetrile, cefaclor, cefadroxil, cefaloridine, cefamandole, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol (Cefcatacol), cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, 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/enzyme inhibitor, ceftolozane/tazobactam, ceftriaxone, cefuroxime, cefuroxime axetil, cephalexin, cephalothin, cephapirin, cephradine, ciclacillin, clometocillin, cloxacillin, dicloxacillin, doripenem, epicillin, ertapenem, flucloxacillin, hetacillin, imipenem, imipenem/EDTA, imipenem/relebactam, latamoxef, lenampicillin, loracarbef, mecillinam (Amdinocillin), meropenem, meropenem/nacubactam, meropenem/vaborbactam, metampicillin, methicillin, mezlocillin, mezlocillin/sulbactam, nacubactam, nafcillin, oxacillin, panipenem, penamecillin, penicillin/novobiocin, penicillin/sulbactam, phenethicillin, phenoxymethylpenicillin, piperacillin, piperacillin/sulbactam, piperacillin/tazobactam, piridicillin, pivampicillin, pivmecillinam, procaine benzylpenicillin, propicillin, razupenem, ritipenem, ritipenem acoxil, sarmoxicillin, sulbactam, sulbenicillin, sultamicillin, talampicillin, tazobactam, tebipenem, temocillin, ticarcillin, ticarcillin/clavulanic acid)
+\item \code{carbapenems}\cr(biapenem, doripenem, ertapenem, imipenem, imipenem/EDTA, imipenem/relebactam, meropenem, meropenem/nacubactam, meropenem/vaborbactam, panipenem, razupenem, ritipenem, ritipenem acoxil, tebipenem)
+\item \code{cephalosporins}\cr(cadazolid, cefacetrile, cefaclor, cefadroxil, cefaloridine, cefamandole, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol (Cefcatacol), cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, 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/enzyme inhibitor, ceftolozane/tazobactam, ceftriaxone, cefuroxime, cefuroxime axetil, cephalexin, cephalothin, cephapirin, cephradine, latamoxef, loracarbef)
+\item \code{cephalosporins_1st}\cr(cefacetrile, cefadroxil, cefaloridine, cefatrizine, cefazedone, cefazolin, cefroxadine, ceftezole, cephalexin, cephalothin, cephapirin, cephradine)
+\item \code{cephalosporins_2nd}\cr(cefaclor, cefamandole, cefmetazole, cefonicid, ceforanide, cefotetan, cefotiam, cefoxitin, cefoxitin screening, cefprozil, cefuroxime, cefuroxime axetil, loracarbef)
+\item \code{cephalosporins_3rd}\cr(cadazolid, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefetamet, cefetamet pivoxil, cefixime, cefmenoxime, cefodizime, cefoperazone, cefoperazone/sulbactam, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotiam hexetil, cefovecin, cefpimizole, cefpiramide, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefsulodin, ceftazidime, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftriaxone, latamoxef)
+\item \code{cephalosporins_except_caz}\cr(cadazolid, cefacetrile, cefaclor, cefadroxil, cefaloridine, cefamandole, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol (Cefcatacol), cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, cefozopran, cefpimizole, cefpiramide, cefpirome, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefprozil, cefquinome, cefroxadine, cefsulodin, cefsumide, ceftaroline, ceftaroline/avibactam, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftezole, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftobiprole, ceftobiprole medocaril, ceftolozane/enzyme inhibitor, ceftolozane/tazobactam, ceftriaxone, cefuroxime, cefuroxime axetil, cephalexin, cephalothin, cephapirin, cephradine, latamoxef, loracarbef)
+\item \code{fluoroquinolones}\cr(ciprofloxacin, enoxacin, fleroxacin, gatifloxacin, gemifloxacin, grepafloxacin, levofloxacin, lomefloxacin, moxifloxacin, norfloxacin, ofloxacin, pazufloxacin, pefloxacin, prulifloxacin, rufloxacin, sparfloxacin, temafloxacin, trovafloxacin)
+\item \code{glycopeptides}\cr(avoparcin, dalbavancin, norvancomycin, oritavancin, ramoplanin, teicoplanin, teicoplanin-macromethod, telavancin, vancomycin, vancomycin-macromethod)
+\item \code{glycopeptides_except_lipo}\cr(avoparcin, norvancomycin, ramoplanin, teicoplanin, teicoplanin-macromethod, vancomycin, vancomycin-macromethod)
+\item \code{lincosamides}\cr(clindamycin, lincomycin, pirlimycin)
+\item \code{lipoglycopeptides}\cr(dalbavancin, oritavancin, telavancin)
+\item \code{macrolides}\cr(azithromycin, clarithromycin, dirithromycin, erythromycin, flurithromycin, josamycin, midecamycin, miocamycin, oleandomycin, rokitamycin, roxithromycin, spiramycin, telithromycin, troleandomycin)
+\item \code{oxazolidinones}\cr(cycloserine, linezolid, tedizolid, thiacetazone)
+\item \code{penicillins}\cr(amoxicillin, amoxicillin/clavulanic acid, amoxicillin/sulbactam, ampicillin, ampicillin/sulbactam, apalcillin, aspoxicillin, avibactam, azidocillin, azlocillin, aztreonam, aztreonam/avibactam, bacampicillin, benzathine benzylpenicillin, benzathine phenoxymethylpenicillin, benzylpenicillin, carbenicillin, carindacillin, ciclacillin, clometocillin, cloxacillin, dicloxacillin, epicillin, flucloxacillin, hetacillin, lenampicillin, mecillinam (Amdinocillin), metampicillin, methicillin, mezlocillin, mezlocillin/sulbactam, nacubactam, nafcillin, oxacillin, penamecillin, penicillin/novobiocin, penicillin/sulbactam, phenethicillin, phenoxymethylpenicillin, piperacillin, piperacillin/sulbactam, piperacillin/tazobactam, piridicillin, pivampicillin, pivmecillinam, procaine benzylpenicillin, propicillin, sarmoxicillin, sulbactam, sulbenicillin, sultamicillin, talampicillin, tazobactam, temocillin, ticarcillin, ticarcillin/clavulanic acid)
+\item \code{polymyxins}\cr(colistin, polymyxin B, polymyxin B/polysorbate 80)
+\item \code{streptogramins}\cr(pristinamycin, quinupristin/dalfopristin)
+\item \code{tetracyclines}\cr(chlortetracycline, clomocycline, demeclocycline, doxycycline, eravacycline, lymecycline, metacycline, minocycline, oxytetracycline, penimepicycline, rolitetracycline, tetracycline, tigecycline)
+\item \code{tetracyclines_except_tgc}\cr(chlortetracycline, clomocycline, demeclocycline, doxycycline, eravacycline, lymecycline, metacycline, minocycline, oxytetracycline, penimepicycline, rolitetracycline, tetracycline)
+\item \code{ureidopenicillins}\cr(azlocillin, mezlocillin, piperacillin, piperacillin/tazobactam)
+}
+}
+}
+
+\section{Maturing Lifecycle}{
+
+\if{html}{\figure{lifecycle_maturing.svg}{options: style=margin-bottom:5px} \cr}
+The \link[=lifecycle]{lifecycle} of this function is \strong{maturing}. The unlying code of a maturing function has been roughed out, but finer details might still change. Since this function needs wider usage and more extensive testing, you are very welcome \href{https://github.com/msberends/AMR/issues}{to suggest changes at our repository} or \link[=AMR]{write us an email (see section 'Contact Us')}.
+}
+
+\examples{
+x <- custom_eucast_rules(AMC == "R" & genus == "Klebsiella" ~ aminopenicillins == "R",
+                         AMC == "I" & genus == "Klebsiella" ~ aminopenicillins == "I")
+eucast_rules(example_isolates,
+             rules = "custom",
+             custom_rules = x,
+             info = FALSE)
+             
+# combine rule sets
+x2 <- c(x,
+        custom_eucast_rules(TZP == "R" ~ carbapenems == "R"))
+x2
+}

man/eucast_rules.Rd

@@ -27,6 +27,7 @@ eucast_rules(
   version_expertrules = 3.2,
   ampc_cephalosporin_resistance = NA,
   only_rsi_columns = FALSE,
+  custom_rules = NULL,
   ...
 )
 
@@ -39,7 +40,7 @@ eucast_dosage(ab, administration = "iv", version_breakpoints = 11)
 
 \item{info}{a logical to indicate whether progress should be printed to the console, defaults to only print while in interactive sessions}
 
-\item{rules}{a character vector that specifies which rules should be applied. Must be one or more of \code{"breakpoints"}, \code{"expert"}, \code{"other"}, \code{"all"}, and defaults to \code{c("breakpoints", "expert")}. The default value can be set to another value, e.g. using \code{options(AMR_eucastrules = "all")}.}
+\item{rules}{a character vector that specifies which rules should be applied. Must be one or more of \code{"breakpoints"}, \code{"expert"}, \code{"other"}, \code{"custom"}, \code{"all"}, and defaults to \code{c("breakpoints", "expert")}. The default value can be set to another value, e.g. using \code{options(AMR_eucastrules = "all")}. If using \code{"custom"}, be sure to fill in argument \code{custom_rules} too. Custom rules can be created with \code{\link[=custom_eucast_rules]{custom_eucast_rules()}}.}
 
 \item{verbose}{a \link{logical} to turn Verbose mode on and off (default is off). In Verbose mode, the function does not apply rules to the data, but instead returns a data set in logbook form with extensive info about which rows and columns would be effected and in which way. Using Verbose mode takes a lot more time.}
 
@@ -51,6 +52,8 @@ eucast_dosage(ab, administration = "iv", version_breakpoints = 11)
 
 \item{only_rsi_columns}{a logical to indicate whether only antibiotic columns must be detected that were transformed to class \verb{<rsi>} (see \code{\link[=as.rsi]{as.rsi()}}) on beforehand (defaults to \code{FALSE})}
 
+\item{custom_rules}{custom rules to apply, created with \code{\link[=custom_eucast_rules]{custom_eucast_rules()}}}
+
 \item{...}{column name of an antibiotic, see section \emph{Antibiotics} below}
 
 \item{ab}{any (vector of) text that can be coerced to a valid antibiotic code with \code{\link[=as.ab]{as.ab()}}}
@@ -67,9 +70,18 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied
 }
 \details{
 \strong{Note:} This function does not translate MIC values to RSI values. Use \code{\link[=as.rsi]{as.rsi()}} for that. \cr
-\strong{Note:} When ampicillin (AMP, J01CA01) is not available but amoxicillin (AMX, J01CA04) is, the latter will be used for all rules where there is a dependency on ampicillin. These drugs are interchangeable when it comes to expression of antimicrobial resistance.
+\strong{Note:} When ampicillin (AMP, J01CA01) is not available but amoxicillin (AMX, J01CA04) is, the latter will be used for all rules where there is a dependency on ampicillin. These drugs are interchangeable when it comes to expression of antimicrobial resistance. \cr
+
+The file containing all EUCAST rules is located here: \url{https://github.com/msberends/AMR/blob/master/data-raw/eucast_rules.tsv}.  \strong{Note:} Old taxonomic names are replaced with the current taxonomy where applicable. For example, \emph{Ochrobactrum anthropi} was renamed to \emph{Brucella anthropi} in 2020; the original EUCAST rules v3.1 and v3.2 did not yet contain this new taxonomic name. The file used as input for this \code{AMR} package contains the taxonomy updated until \link[=catalogue_of_life]{March 2021}.
+\subsection{Custom Rules}{
+
+Custom rules can be created using \code{\link[=custom_eucast_rules]{custom_eucast_rules()}}, e.g.:\preformatted{x <- custom_eucast_rules(AMC == "R" & genus == "Klebsiella" ~ aminopenicillins == "R",
+                         AMC == "I" & genus == "Klebsiella" ~ aminopenicillins == "I")
+
+eucast_rules(example_isolates, rules = "custom", custom_rules = x)
+}
+}
 
-The file containing all EUCAST rules is located here: \url{https://github.com/msberends/AMR/blob/master/data-raw/eucast_rules.tsv}.
 \subsection{'Other' Rules}{
 
 Before further processing, two non-EUCAST rules about drug combinations can be applied to improve the efficacy of the EUCAST rules, and the reliability of your data (analysis). These rules are:

man/first_isolate.Rd

@@ -65,7 +65,7 @@ filter_first_weighted_isolate(
 
 \item{col_icu}{column name of the logicals (\code{TRUE}/\code{FALSE}) whether a ward or department is an Intensive Care Unit (ICU)}
 
-\item{col_keyantibiotics}{column name of the key antibiotics to determine first (weighted) isolates, see \code{\link[=key_antibiotics]{key_antibiotics()}}. Defaults to the first column that starts with 'key' followed by 'ab' or 'antibiotics' (case insensitive). Use \code{col_keyantibiotics = FALSE} to prevent this.}
+\item{col_keyantibiotics}{column name of the key antibiotics to determine first (weighted) isolates, see \code{\link[=key_antibiotics]{key_antibiotics()}}. Defaults to the first column that starts with 'key' followed by 'ab' or 'antibiotics' (case insensitive). Use \code{col_keyantibiotics = FALSE} to prevent this. Can also be the output of \code{\link[=key_antibiotics]{key_antibiotics()}}.}
 
 \item{episode_days}{episode in days after which a genus/species combination will be determined as 'first isolate' again. The default of 365 days is based on the guideline by CLSI, see \emph{Source}.}
 
@@ -81,7 +81,7 @@ filter_first_weighted_isolate(
 
 \item{points_threshold}{points until the comparison of key antibiotics will lead to inclusion of an isolate when \code{type = "points"}, see \emph{Details}}
 
-\item{info}{print progress}
+\item{info}{a \link{logical} to indicate info should be printed, defaults to \code{TRUE} only in interactive mode}
 
 \item{include_unknown}{logical to indicate whether 'unknown' microorganisms should be included too, i.e. microbial code \code{"UNKNOWN"}, which defaults to \code{FALSE}. For WHONET users, this means that all records with organism code \code{"con"} (\emph{contamination}) will be excluded at default. Isolates with a microbial ID of \code{NA} will always be excluded as first isolate.}
 

man/get_episode.Rd

@@ -12,7 +12,7 @@ is_new_episode(x, episode_days, ...)
 \arguments{
 \item{x}{vector of dates (class \code{Date} or \code{POSIXt})}
 
-\item{episode_days}{required episode length in days, can also be less than a day, see \emph{Details}}
+\item{episode_days}{required episode length in days, can also be less than a day or \code{Inf}, see \emph{Details}}
 
 \item{...}{currently not used}
 }
@@ -90,7 +90,7 @@ if (require("dplyr")) {
   # grouping on patients and microorganisms leads to the same results
   # as first_isolate():
   x <- example_isolates \%>\%
-    filter(first_isolate(., include_unknown = TRUE))
+    filter_first_isolate(include_unknown = TRUE)
     
   y <- example_isolates \%>\%
     group_by(patient_id, mo) \%>\%

man/key_antibiotics.Rd

@@ -36,7 +36,9 @@ key_antibiotics_equal(
   type = c("keyantibiotics", "points"),
   ignore_I = TRUE,
   points_threshold = 2,
-  info = FALSE
+  info = FALSE,
+  na.rm = TRUE,
+  ...
 )
 }
 \arguments{
@@ -62,7 +64,9 @@ key_antibiotics_equal(
 
 \item{points_threshold}{points until the comparison of key antibiotics will lead to inclusion of an isolate when \code{type = "points"}, see \emph{Details}}
 
-\item{info}{print progress}
+\item{info}{unused - previously used to indicate whether a progress bar should print}
+
+\item{na.rm}{a \link{logical} to indicate whether comparison with \code{NA} should return \code{FALSE} (defaults to \code{TRUE} for backwards compatibility)}
 }
 \description{
 These function can be used to determine first isolates (see \code{\link[=first_isolate]{first_isolate()}}). Using key antibiotics to determine first isolates is more reliable than without key antibiotics. These selected isolates can then be called first 'weighted' isolates.

man/like.Rd

@@ -3,41 +3,47 @@
 \name{like}
 \alias{like}
 \alias{\%like\%}
+\alias{\%unlike\%}
 \alias{\%like_case\%}
-\title{Pattern Matching with Keyboard Shortcut}
+\alias{\%unlike_case\%}
+\title{Vectorised Pattern Matching with Keyboard Shortcut}
 \source{
-Idea from the \href{https://github.com/Rdatatable/data.table/blob/master/R/like.R}{\code{like} function from the \code{data.table} package}
+Idea from the \href{https://github.com/Rdatatable/data.table/blob/ec1259af1bf13fc0c96a1d3f9e84d55d8106a9a4/R/like.R}{\code{like} function from the \code{data.table} package}, although altered as explained in \emph{Details}.
 }
 \usage{
 like(x, pattern, ignore.case = TRUE)
 
 x \%like\% pattern
 
+x \%unlike\% pattern
+
 x \%like_case\% pattern
+
+x \%unlike_case\% pattern
 }
 \arguments{
 \item{x}{a character vector where matches are sought, or an object which can be coerced by \code{\link[=as.character]{as.character()}} to a character vector.}
 
-\item{pattern}{a character string containing a regular expression (or \link{character} string for \code{fixed = TRUE}) to be matched in the given character vector. Coerced by \code{\link[=as.character]{as.character()}} to a character string if possible.  If a \link{character} vector of length 2 or more is supplied, the first element is used with a warning.}
+\item{pattern}{a character vector containing regular expressions (or a \link{character} string for \code{fixed = TRUE}) to be matched in the given character vector. Coerced by \code{\link[=as.character]{as.character()}} to a character string if possible.}
 
 \item{ignore.case}{if \code{FALSE}, the pattern matching is \emph{case sensitive} and if \code{TRUE}, case is ignored during matching.}
 }
 \value{
-A \code{\link{logical}} vector
+A \link{logical} vector
 }
 \description{
 Convenient wrapper around \code{\link[=grepl]{grepl()}} to match a pattern: \code{x \%like\% pattern}. It always returns a \code{\link{logical}} vector and is always case-insensitive (use \code{x \%like_case\% pattern} for case-sensitive matching). Also, \code{pattern} can be as long as \code{x} to compare items of each index in both vectors, or they both can have the same length to iterate over all cases.
 }
 \details{
-The \verb{\%like\%} function:
+These \code{\link[=like]{like()}} and \verb{\%like\%}/\verb{\%unlike\%} functions:
 \itemize{
-\item Is case-insensitive (use \verb{\%like_case\%} for case-sensitive matching)
-\item Supports multiple patterns
-\item Checks if \code{pattern} is a regular expression and sets \code{fixed = TRUE} if not, to greatly improve speed
-\item Always uses compatibility with Perl
+\item Are case-insensitive (use \verb{\%like_case\%}/\verb{\%unlike_case\%} for case-sensitive matching)
+\item Support multiple patterns
+\item Check if \code{pattern} is a valid regular expression and sets \code{fixed = TRUE} if not, to greatly improve speed (vectorised over \code{pattern})
+\item Always use compatibility with Perl unless \code{fixed = TRUE}, to greatly improve speed
 }
 
-Using RStudio? The text \verb{\%like\%} can also be directly inserted in your code from the Addins menu and can have its own Keyboard Shortcut like \code{Ctrl+Shift+L} or \code{Cmd+Shift+L} (see \code{Tools} > \verb{Modify Keyboard Shortcuts...}).
+Using RStudio? The \verb{\%like\%}/\verb{\%unlike\%} functions can also be directly inserted in your code from the Addins menu and can have its own keyboard shortcut like \code{Shift+Ctrl+L} or \code{Shift+Cmd+L} (see menu \code{Tools} > \verb{Modify Keyboard Shortcuts...}). If you keep pressing your shortcut, the inserted text will be iterated over \verb{\%like\%} -> \verb{\%unlike\%} -> \verb{\%like_case\%} -> \verb{\%unlike_case\%}.
 }
 \section{Stable Lifecycle}{
 
@@ -53,7 +59,6 @@ On our website \url{https://msberends.github.io/AMR/} you can find \href{https:/
 }
 
 \examples{
-# simple test
 a <- "This is a test"
 b <- "TEST"
 a \%like\% b
@@ -66,16 +71,23 @@ a <- c("Test case", "Something different", "Yet another thing")
 b <- c(     "case",           "diff",      "yet")
 a \%like\% b
 #> TRUE TRUE TRUE
+a \%unlike\% b
+#> FALSE FALSE FALSE
+
 a[1] \%like\% b
 #> TRUE FALSE FALSE
 a \%like\% b[1]
 #> TRUE FALSE FALSE
 
 # get isolates whose name start with 'Ent' or 'ent'
+example_isolates[which(mo_name(example_isolates$mo) \%like\% "^ent"), ]
 \donttest{
+# faster way, only works in R 3.2 and later:
+example_isolates[which(mo_name() \%like\% "^ent"), ]
+
 if (require("dplyr")) {
   example_isolates \%>\%
-    filter(mo_name(mo) \%like\% "^ent")
+    filter(mo_name() \%like\% "^ent")
 }
 }
 }

man/mdro.Rd

@@ -119,7 +119,7 @@ Please suggest your own (country-specific) guidelines by letting us know: \url{h
 
 Custom guidelines can be set with the \code{\link[=custom_mdro_guideline]{custom_mdro_guideline()}} function. This is of great importance if you have custom rules to determine MDROs in your hospital, e.g., rules that are dependent on ward, state of contact isolation or other variables in your data.
 
-If you are familiar with \code{case_when()} of the \code{dplyr} package, you will recognise the input method to set your own rules. Rules must be set using what \R considers to be the 'formula notation':\preformatted{custom <- custom_mdro_guideline(CIP == "R" & age > 60 ~ "Elderly Type A",
+If you are familiar with the \code{\link[dplyr:case_when]{case_when()}} function of the \code{dplyr} package, you will recognise the input method to set your own rules. Rules must be set using what \R considers to be the 'formula notation'. The rule is written \emph{before} the tilde (\code{~}) and the consequence of the rule is written \emph{after} the tilde:\preformatted{custom <- custom_mdro_guideline(CIP == "R" & age > 60 ~ "Elderly Type A",
                                 ERY == "R" & age > 60 ~ "Elderly Type B")
 }
 
@@ -134,10 +134,19 @@ You can print the rules set in the console for an overview. Colours will help re
 #> Unmatched rows will return NA.
 }
 
-The outcome of the function can be used for the \code{guideline} argument in the \code{\link[=mdro]{mdro()}} function:\preformatted{x <- mdro(example_isolates, guideline = custom)
+The outcome of the function can be used for the \code{guideline} argument in the \code{\link[=mdro]{mdro()}} function:\preformatted{x <- mdro(example_isolates,
+          guideline = custom)
 table(x)
-#> Elderly Type A Elderly Type B       Negative 
-#>             43            891           1066 
+#>       Negative Elderly Type A Elderly Type B
+#>           1070            198            732
+}
+
+Rules can also be combined with other custom rules by using \code{\link[=c]{c()}}:\preformatted{x <- mdro(example_isolates,
+          guideline = c(custom, 
+                        custom_mdro_guideline(ERY == "R" & age > 50 ~ "Elderly Type C")))
+table(x)
+#>       Negative Elderly Type A Elderly Type B Elderly Type C 
+#>            961            198            732            109
 }
 
 The rules set (the \code{custom} object in this case) could be exported to a shared file location using \code{\link[=saveRDS]{saveRDS()}} if you collaborate with multiple users. The custom rules set could then be imported using \code{\link[=readRDS]{readRDS()}}.

man/microorganisms.Rd

@@ -46,7 +46,7 @@ A data set containing the microbial taxonomy, last updated in March 2021, of six
 \details{
 Please note that entries are only based on the Catalogue of Life and the LPSN (see below). Since these sources incorporate entries based on (recent) publications in the International Journal of Systematic and Evolutionary Microbiology (IJSEM), it can happen that the year of publication is sometimes later than one might expect.
 
-For example, \emph{Staphylococcus pettenkoferi} was described for the first time in Diagnostic Microbiology and Infectious Disease in 2002 (\doi{10.1016/s0732-8893(02)00399-1}), but it was not before 2007 that a publication in IJSEM followed (\doi{10.1099/ijs.0.64381-0}). Consequently, the AMR package returns 2007 for \code{mo_year("S. pettenkoferi")}.
+For example, \emph{Staphylococcus pettenkoferi} was described for the first time in Diagnostic Microbiology and Infectious Disease in 2002 (\doi{10.1016/s0732-8893(02)00399-1}), but it was not before 2007 that a publication in IJSEM followed (\doi{10.1099/ijs.0.64381-0}). Consequently, the \code{AMR} package returns 2007 for \code{mo_year("S. pettenkoferi")}.
 \subsection{Manual additions}{
 
 For convenience, some entries were added manually:

man/mo_matching_score.Rd

@@ -30,7 +30,7 @@ where:
 \item \ifelse{html}{\out{<i>k<sub>n</sub></i> is the taxonomic kingdom of <i>n</i>, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}}{l_n is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}
 }
 
-The grouping into human pathogenic prevalence (\eqn{p}) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. \strong{Group 1} (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is \emph{Enterococcus}, \emph{Staphylococcus} or \emph{Streptococcus}. This group consequently contains all common Gram-negative bacteria, such as \emph{Pseudomonas} and \emph{Legionella} and all species within the order Enterobacterales. \strong{Group 2} consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is \emph{Absidia}, \emph{Acremonium}, \emph{Actinotignum}, \emph{Alternaria}, \emph{Anaerosalibacter}, \emph{Apophysomyces}, \emph{Arachnia}, \emph{Aspergillus}, \emph{Aureobacterium}, \emph{Aureobasidium}, \emph{Bacteroides}, \emph{Basidiobolus}, \emph{Beauveria}, \emph{Blastocystis}, \emph{Branhamella}, \emph{Calymmatobacterium}, \emph{Candida}, \emph{Capnocytophaga}, \emph{Catabacter}, \emph{Chaetomium}, \emph{Chryseobacterium}, \emph{Chryseomonas}, \emph{Chrysonilia}, \emph{Cladophialophora}, \emph{Cladosporium}, \emph{Conidiobolus}, \emph{Cryptococcus}, \emph{Curvularia}, \emph{Exophiala}, \emph{Exserohilum}, \emph{Flavobacterium}, \emph{Fonsecaea}, \emph{Fusarium}, \emph{Fusobacterium}, \emph{Hendersonula}, \emph{Hypomyces}, \emph{Koserella}, \emph{Lelliottia}, \emph{Leptosphaeria}, \emph{Leptotrichia}, \emph{Malassezia}, \emph{Malbranchea}, \emph{Mortierella}, \emph{Mucor}, \emph{Mycocentrospora}, \emph{Mycoplasma}, \emph{Nectria}, \emph{Ochroconis}, \emph{Oidiodendron}, \emph{Phoma}, \emph{Piedraia}, \emph{Pithomyces}, \emph{Pityrosporum}, \emph{Prevotella}, \emph{Pseudallescheria}, \emph{Rhizomucor}, \emph{Rhizopus}, \emph{Rhodotorula}, \emph{Scolecobasidium}, \emph{Scopulariopsis}, \emph{Scytalidium},\emph{Sporobolomyces}, \emph{Stachybotrys}, \emph{Stomatococcus}, \emph{Treponema}, \emph{Trichoderma}, \emph{Trichophyton}, \emph{Trichosporon}, \emph{Tritirachium} or \emph{Ureaplasma}. \strong{Group 3} consists of all other microorganisms.
+The grouping into human pathogenic prevalence (\eqn{p}) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. \strong{Group 1} (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is \emph{Enterococcus}, \emph{Staphylococcus} or \emph{Streptococcus}. This group consequently contains all common Gram-negative bacteria, such as \emph{Pseudomonas} and \emph{Legionella} and all species within the order Enterobacterales. \strong{Group 2} consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is \emph{Absidia}, \emph{Acremonium}, \emph{Actinotignum}, \emph{Alternaria}, \emph{Anaerosalibacter}, \emph{Apophysomyces}, \emph{Arachnia}, \emph{Aspergillus}, \emph{Aureobacterium}, \emph{Aureobasidium}, \emph{Bacteroides}, \emph{Basidiobolus}, \emph{Beauveria}, \emph{Blastocystis}, \emph{Branhamella}, \emph{Calymmatobacterium}, \emph{Candida}, \emph{Capnocytophaga}, \emph{Catabacter}, \emph{Chaetomium}, \emph{Chryseobacterium}, \emph{Chryseomonas}, \emph{Chrysonilia}, \emph{Cladophialophora}, \emph{Cladosporium}, \emph{Conidiobolus}, \emph{Cryptococcus}, \emph{Curvularia}, \emph{Exophiala}, \emph{Exserohilum}, \emph{Flavobacterium}, \emph{Fonsecaea}, \emph{Fusarium}, \emph{Fusobacterium}, \emph{Hendersonula}, \emph{Hypomyces}, \emph{Koserella}, \emph{Lelliottia}, \emph{Leptosphaeria}, \emph{Leptotrichia}, \emph{Malassezia}, \emph{Malbranchea}, \emph{Mortierella}, \emph{Mucor}, \emph{Mycocentrospora}, \emph{Mycoplasma}, \emph{Nectria}, \emph{Ochroconis}, \emph{Oidiodendron}, \emph{Phoma}, \emph{Piedraia}, \emph{Pithomyces}, \emph{Pityrosporum}, \emph{Prevotella}, \emph{Pseudallescheria}, \emph{Rhizomucor}, \emph{Rhizopus}, \emph{Rhodotorula}, \emph{Scolecobasidium}, \emph{Scopulariopsis}, \emph{Scytalidium}, \emph{Sporobolomyces}, \emph{Stachybotrys}, \emph{Stomatococcus}, \emph{Treponema}, \emph{Trichoderma}, \emph{Trichophyton}, \emph{Trichosporon}, \emph{Tritirachium} or \emph{Ureaplasma}. \strong{Group 3} consists of all other microorganisms.
 
 All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., \code{"E. coli"} will return the microbial ID of \emph{Escherichia coli} (\eqn{m = 0.688}, a highly prevalent microorganism found in humans) and not \emph{Entamoeba coli} (\eqn{m = 0.079}, a less prevalent microorganism in humans), although the latter would alphabetically come first.
 }

man/mo_property.Rd

@@ -160,7 +160,7 @@ where:
 \item \ifelse{html}{\out{<i>k<sub>n</sub></i> is the taxonomic kingdom of <i>n</i>, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}}{l_n is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}
 }
 
-The grouping into human pathogenic prevalence (\eqn{p}) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. \strong{Group 1} (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is \emph{Enterococcus}, \emph{Staphylococcus} or \emph{Streptococcus}. This group consequently contains all common Gram-negative bacteria, such as \emph{Pseudomonas} and \emph{Legionella} and all species within the order Enterobacterales. \strong{Group 2} consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is \emph{Absidia}, \emph{Acremonium}, \emph{Actinotignum}, \emph{Alternaria}, \emph{Anaerosalibacter}, \emph{Apophysomyces}, \emph{Arachnia}, \emph{Aspergillus}, \emph{Aureobacterium}, \emph{Aureobasidium}, \emph{Bacteroides}, \emph{Basidiobolus}, \emph{Beauveria}, \emph{Blastocystis}, \emph{Branhamella}, \emph{Calymmatobacterium}, \emph{Candida}, \emph{Capnocytophaga}, \emph{Catabacter}, \emph{Chaetomium}, \emph{Chryseobacterium}, \emph{Chryseomonas}, \emph{Chrysonilia}, \emph{Cladophialophora}, \emph{Cladosporium}, \emph{Conidiobolus}, \emph{Cryptococcus}, \emph{Curvularia}, \emph{Exophiala}, \emph{Exserohilum}, \emph{Flavobacterium}, \emph{Fonsecaea}, \emph{Fusarium}, \emph{Fusobacterium}, \emph{Hendersonula}, \emph{Hypomyces}, \emph{Koserella}, \emph{Lelliottia}, \emph{Leptosphaeria}, \emph{Leptotrichia}, \emph{Malassezia}, \emph{Malbranchea}, \emph{Mortierella}, \emph{Mucor}, \emph{Mycocentrospora}, \emph{Mycoplasma}, \emph{Nectria}, \emph{Ochroconis}, \emph{Oidiodendron}, \emph{Phoma}, \emph{Piedraia}, \emph{Pithomyces}, \emph{Pityrosporum}, \emph{Prevotella}, \emph{Pseudallescheria}, \emph{Rhizomucor}, \emph{Rhizopus}, \emph{Rhodotorula}, \emph{Scolecobasidium}, \emph{Scopulariopsis}, \emph{Scytalidium},\emph{Sporobolomyces}, \emph{Stachybotrys}, \emph{Stomatococcus}, \emph{Treponema}, \emph{Trichoderma}, \emph{Trichophyton}, \emph{Trichosporon}, \emph{Tritirachium} or \emph{Ureaplasma}. \strong{Group 3} consists of all other microorganisms.
+The grouping into human pathogenic prevalence (\eqn{p}) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. \strong{Group 1} (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is \emph{Enterococcus}, \emph{Staphylococcus} or \emph{Streptococcus}. This group consequently contains all common Gram-negative bacteria, such as \emph{Pseudomonas} and \emph{Legionella} and all species within the order Enterobacterales. \strong{Group 2} consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is \emph{Absidia}, \emph{Acremonium}, \emph{Actinotignum}, \emph{Alternaria}, \emph{Anaerosalibacter}, \emph{Apophysomyces}, \emph{Arachnia}, \emph{Aspergillus}, \emph{Aureobacterium}, \emph{Aureobasidium}, \emph{Bacteroides}, \emph{Basidiobolus}, \emph{Beauveria}, \emph{Blastocystis}, \emph{Branhamella}, \emph{Calymmatobacterium}, \emph{Candida}, \emph{Capnocytophaga}, \emph{Catabacter}, \emph{Chaetomium}, \emph{Chryseobacterium}, \emph{Chryseomonas}, \emph{Chrysonilia}, \emph{Cladophialophora}, \emph{Cladosporium}, \emph{Conidiobolus}, \emph{Cryptococcus}, \emph{Curvularia}, \emph{Exophiala}, \emph{Exserohilum}, \emph{Flavobacterium}, \emph{Fonsecaea}, \emph{Fusarium}, \emph{Fusobacterium}, \emph{Hendersonula}, \emph{Hypomyces}, \emph{Koserella}, \emph{Lelliottia}, \emph{Leptosphaeria}, \emph{Leptotrichia}, \emph{Malassezia}, \emph{Malbranchea}, \emph{Mortierella}, \emph{Mucor}, \emph{Mycocentrospora}, \emph{Mycoplasma}, \emph{Nectria}, \emph{Ochroconis}, \emph{Oidiodendron}, \emph{Phoma}, \emph{Piedraia}, \emph{Pithomyces}, \emph{Pityrosporum}, \emph{Prevotella}, \emph{Pseudallescheria}, \emph{Rhizomucor}, \emph{Rhizopus}, \emph{Rhodotorula}, \emph{Scolecobasidium}, \emph{Scopulariopsis}, \emph{Scytalidium}, \emph{Sporobolomyces}, \emph{Stachybotrys}, \emph{Stomatococcus}, \emph{Treponema}, \emph{Trichoderma}, \emph{Trichophyton}, \emph{Trichosporon}, \emph{Tritirachium} or \emph{Ureaplasma}. \strong{Group 3} consists of all other microorganisms.
 
 All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., \code{"E. coli"} will return the microbial ID of \emph{Escherichia coli} (\eqn{m = 0.688}, a highly prevalent microorganism found in humans) and not \emph{Entamoeba coli} (\eqn{m = 0.079}, a less prevalent microorganism in humans), although the latter would alphabetically come first.
 }

man/plot.Rd

@@ -83,6 +83,7 @@
   xlab = "Antimicrobial Interpretation",
   ylab = "Frequency",
   colours_RSI = c("#ED553B", "#3CAEA3", "#F6D55C"),
+  language = get_locale(),
   ...
 )
 }

tests/testthat/test-eucast_rules.R

@@ -38,7 +38,7 @@ test_that("EUCAST rules work", {
                  "reference.version",
                  "note"))
   MOs_mentioned <- unique(eucast_rules_file$this_value)
-  MOs_mentioned <- sort(trimws(unlist(strsplit(MOs_mentioned[!is_possibly_regex(MOs_mentioned)], ",", fixed = TRUE))))
+  MOs_mentioned <- sort(trimws(unlist(strsplit(MOs_mentioned[!is_valid_regex(MOs_mentioned)], ",", fixed = TRUE))))
   MOs_test <- suppressWarnings(suppressMessages(mo_name(MOs_mentioned)))
   expect_length(MOs_mentioned[MOs_test != MOs_mentioned], 0)
   
@@ -80,11 +80,10 @@ test_that("EUCAST rules work", {
   library(dplyr, warn.conflicts = FALSE)
   expect_equal(suppressWarnings(
     example_isolates %>%
+      filter(mo_family(mo) == "Enterobacteriaceae") %>%
       mutate(TIC = as.rsi("R"),
              PIP = as.rsi("S")) %>%
       eucast_rules(col_mo = "mo", version_expertrules = 3.1, info = FALSE) %>%
-      left_join_microorganisms(by = "mo") %>%
-      filter(family == "Enterobacteriaceae") %>%
       pull(PIP) %>%
       unique() %>%
       as.character()),
@@ -145,3 +144,21 @@ test_that("EUCAST rules work", {
   expect_s3_class(eucast_dosage(c("tobra", "genta", "cipro")), "data.frame")
   
 })
+
+test_that("Custom EUCAST rules work", {
+  
+  skip_on_cran()
+  x <- custom_eucast_rules(AMC == "R" & genus == "Klebsiella" ~ aminopenicillins == "R",
+                           AMC == "I" & genus == "Klebsiella" ~ aminopenicillins == "I")
+  expect_output(print(x))
+  expect_output(print(c(x, x)))
+  expect_output(print(as.list(x, x)))
+  
+  # this custom rules makes 8 changes
+  expect_equal(nrow(eucast_rules(example_isolates,
+                                 rules = "custom",
+                                 custom_rules = x,
+                                 info = FALSE,
+                                 verbose = TRUE)),
+               8)
+})

tests/testthat/test-first_isolate.R

@@ -50,7 +50,7 @@ test_that("first isolates work", {
                       type = "keyantibiotics",
                       info = TRUE),
         na.rm = TRUE)),
-    1395)
+    1398)
 
   # when not ignoring I
   expect_equal(
@@ -65,7 +65,7 @@ test_that("first isolates work", {
                       type = "keyantibiotics",
                       info = TRUE),
         na.rm = TRUE)),
-    1418)
+    1421)
   # when using points
   expect_equal(
     suppressWarnings(
@@ -78,7 +78,7 @@ test_that("first isolates work", {
                       type = "points",
                       info = TRUE),
         na.rm = TRUE)),
-    1398)
+    1348)
 
   # first non-ICU isolates
   expect_equal(

tests/testthat/test-kurtosis.R

@@ -28,20 +28,20 @@ context("kurtosis.R")
 test_that("kurtosis works", {
   skip_on_cran()
   expect_equal(kurtosis(example_isolates$age),
-               3.549319,
+               5.227999,
                tolerance = 0.00001)
   
   expect_equal(unname(kurtosis(data.frame(example_isolates$age))),
-               3.549319,
+               5.227999,
                tolerance = 0.00001)
   expect_equal(unname(kurtosis(data.frame(example_isolates$age), excess = TRUE)),
-               0.549319,
+               2.227999,
                tolerance = 0.00001)
   
   expect_equal(kurtosis(matrix(example_isolates$age)),
-               3.549319,
+               5.227999,
                tolerance = 0.00001)
   expect_equal(kurtosis(matrix(example_isolates$age), excess = TRUE),
-               0.549319,
+               2.227999,
                tolerance = 0.00001)
 })

tests/testthat/test-mdro.R

@@ -228,8 +228,11 @@ test_that("mdro works", {
                                   "ERY == 'R' & age > 60" ~ "Elderly Type B",
                                   as_factor = TRUE)
   expect_output(print(custom))
+  expect_output(print(c(custom, custom)))
+  expect_output(print(as.list(custom, custom)))
+  
   expect_output(x <- mdro(example_isolates, guideline = custom, info = TRUE))
-  expect_equal(as.double(table(x)), c(1066, 43, 891))
+  expect_equal(as.double(table(x)), c(1070, 198, 732))
   
   expect_output(print(custom_mdro_guideline(AMX == "R" ~ "test", as_factor = FALSE)))
   expect_error(custom_mdro_guideline())

tests/testthat/test-skewness.R

@@ -28,12 +28,12 @@ context("skewness.R")
 test_that("skewness works", {
   skip_on_cran()
   expect_equal(skewness(example_isolates$age),
-               -0.8958019,
+               -1.212888,
                tolerance = 0.00001)
   expect_equal(unname(skewness(data.frame(example_isolates$age))),
-               -0.8958019,
+               -1.212888,
                tolerance = 0.00001)
   expect_equal(skewness(matrix(example_isolates$age)),
-               -0.8958019,
+               -1.212888,
                tolerance = 0.00001)
 })