(v1.7.1.9005) ab class selectors for R-3.0 and R-3.1

.github/workflows/check.yaml

@@ -107,9 +107,9 @@ jobs:
           sudo apt install -y libssl-dev pandoc pandoc-citeproc libxml2-dev libicu-dev libcurl4-openssl-dev libpng-dev
 
       - name: Query dependencies
-        # this will change once a week, so it will cache dependency updates
+        # this will change every day (i.e. at scheduled night run of GitHub Action), so it will cache dependency updates
         run: |
-          writeLines(paste(format(Sys.Date(), "week %V %Y"), sprintf("R-%i.%i", getRversion()$major, getRversion()$minor)), ".github/week-R-version")
+          writeLines(paste0(format(Sys.Date(), "%Y%m%d"), sprintf("-R-%i.%i", getRversion()$major, getRversion()$minor)), ".github/daily-R-bundle")
         shell: Rscript {0}
         
       - name: Restore cached R packages
@@ -117,7 +117,7 @@ jobs:
         uses: actions/cache@v2
         with:
           path: ${{ env.R_LIBS_USER }}
-          key: ${{ matrix.config.os }}-${{ hashFiles('.github/week-R-version') }}-v4
+          key: ${{ matrix.config.os }}-${{ hashFiles('.github/daily-R-bundle') }}-v4
 
       - name: Unpack AMR and install R dependencies
         if: always()

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: AMR
-Version: 1.7.1.9004
+Version: 1.7.1.9005
-Date: 2021-06-15
+Date: 2021-06-22
 Title: Antimicrobial Resistance Data Analysis
 Authors@R: c(
     person(role = c("aut", "cre"), 

NEWS.md

@@ -1,12 +1,17 @@
-# `AMR` 1.7.1.9004
+# `AMR` 1.7.1.9005
-## <small>Last updated: 15 June 2021</small>
+## <small>Last updated: 22 June 2021</small>
 
 ### Changed
-* Added more antibiotic class selectors: `aminopenicillins()`, `lincosamides()`, `lipoglycopeptides()`, `polymyxins()`, `quinolones()`, `streptogramins()` and `ureidopenicillins()`
+* Antibiotic class selectors (see `ab_class()`)
+  * They now finally also work in R-3.0 and R-3.1, supporting every version of R since 2013
+  * Added more selectors: `aminopenicillins()`, `lincosamides()`, `lipoglycopeptides()`, `polymyxins()`, `quinolones()`, `streptogramins()` and `ureidopenicillins()`
+  * Fix for using selectors multiple times in one call (e.g., using them in `dplyr::filter()` and immediately after in `dplyr::select()`)
 * Added `ggplot2::autoplot()` generic for classes `<mic>`, `<disk>`, `<rsi>` and `<resistance_predict>`
 * Fix to prevent introducing `NA`s for old MO codes when running `as.mo()` on them
 * Added more informative error messages when any of the `proportion_*()` and `count_*()` functions fail
-* Fix for using antibiotic selectors multiple times in one call (e.g., using in `dplyr::filter()` and immediately after in `dplyr::select()`)
+* When printing a tibble with any old MO code, a warning will be thrown that old codes should be updated using `as.mo()`
+* Improved automatic column selector when `col_*` arguments are left blank, e.g. in `first_isolate()`
+* The right input types for `random_mic()`, `random_disk()` and `random_rsi()` are now enforced
 
 
 # `AMR` 1.7.1

R/aa_helper_functions.R

@@ -170,65 +170,73 @@ search_type_in_df <- function(x, type, info = TRUE) {
 
   # remove attributes from other packages
   x <- as.data.frame(x, stringsAsFactors = FALSE)
-  colnames(x) <- trimws(colnames(x))
+  colnames_formatted <- tolower(generalise_antibiotic_name(colnames(x)))
 
   # -- mo
   if (type == "mo") {
     if (any(vapply(FUN.VALUE = logical(1), x, is.mo))) {
-      found <- sort(colnames(x)[vapply(FUN.VALUE = logical(1), x, is.mo)])[1]
+      # take first <mo> column
-    } else if ("mo" %in% colnames(x) &
+      found <- colnames(x)[vapply(FUN.VALUE = logical(1), x, is.mo)]
-               suppressWarnings(
+    } else if ("mo" %in% colnames_formatted &
-                 all(x$mo %in% c(NA, microorganisms$mo)))) {
+               suppressWarnings(all(x$mo %in% c(NA, microorganisms$mo)))) {
       found <- "mo"
-    } else if (any(colnames(x) %like% "^(mo|microorganism|organism|bacteria|ba[ck]terie)s?$")) {
+    } else if (any(colnames_formatted %like_case% "^(mo|microorganism|organism|bacteria|ba[ck]terie)s?$")) {
-      found <- sort(colnames(x)[colnames(x) %like% "^(mo|microorganism|organism|bacteria|ba[ck]terie)s?$"])[1]
+      found <- sort(colnames(x)[colnames_formatted %like_case% "^(mo|microorganism|organism|bacteria|ba[ck]terie)s?$"])
-    } else if (any(colnames(x) %like% "^(microorganism|organism|bacteria|ba[ck]terie)")) {
+    } else if (any(colnames_formatted %like_case% "^(microorganism|organism|bacteria|ba[ck]terie)")) {
-      found <- sort(colnames(x)[colnames(x) %like% "^(microorganism|organism|bacteria|ba[ck]terie)"])[1]
+      found <- sort(colnames(x)[colnames_formatted %like_case% "^(microorganism|organism|bacteria|ba[ck]terie)"])
-    } else if (any(colnames(x) %like% "species")) {
+    } else if (any(colnames_formatted %like_case% "species")) {
-      found <- sort(colnames(x)[colnames(x) %like% "species"])[1]
+      found <- sort(colnames(x)[colnames_formatted %like_case% "species"])
     }
 
   }
   # -- key antibiotics
   if (type %in% c("keyantibiotics", "keyantimicrobials")) {
-    if (any(colnames(x) %like% "^key.*(ab|antibiotics|antimicrobials)")) {
+    if (any(colnames_formatted %like_case% "^key.*(ab|antibiotics|antimicrobials)")) {
-      found <- sort(colnames(x)[colnames(x) %like% "^key.*(ab|antibiotics|antimicrobials)"])[1]
+      found <- sort(colnames(x)[colnames_formatted %like_case% "^key.*(ab|antibiotics|antimicrobials)"])
     }
   }
   # -- date
   if (type == "date") {
-    if (any(colnames(x) %like% "^(specimen date|specimen_date|spec_date)")) {
+    if (any(colnames_formatted %like_case% "^(specimen date|specimen_date|spec_date)")) {
       # WHONET support
-      found <- sort(colnames(x)[colnames(x) %like% "^(specimen date|specimen_date|spec_date)"])[1]
+      found <- sort(colnames(x)[colnames_formatted %like_case% "^(specimen date|specimen_date|spec_date)"])
       if (!any(class(pm_pull(x, found)) %in% c("Date", "POSIXct"))) {
         stop(font_red(paste0("Found column '", font_bold(found), "' to be used as input for `col_", type,
                              "`, but this column contains no valid dates. Transform its values to valid dates first.")),
              call. = FALSE)
       }
+      
     } else if (any(vapply(FUN.VALUE = logical(1), x, function(x) inherits(x, c("Date", "POSIXct"))))) {
-      found <- sort(colnames(x)[vapply(FUN.VALUE = logical(1), x, function(x) inherits(x, c("Date", "POSIXct")))])[1]
+      # take first <Date> column
+      found <- colnames(x)[vapply(FUN.VALUE = logical(1), x, function(x) inherits(x, c("Date", "POSIXct")))]
     }
   }
   # -- patient id
   if (type == "patient_id") {
-    if (any(colnames(x) %like% "^(identification |patient|patid)")) {
+    crit1 <- colnames_formatted %like_case% "^(patient|patid)"
-      found <- sort(colnames(x)[colnames(x) %like% "^(identification |patient|patid)"])[1]
+    if (any(crit1)) {
+      found <- colnames(x)[crit1]
+    } else {
+      crit2 <- colnames_formatted %like_case% "(identification |patient|pat.*id)"
+      if (any(crit2)) {
+        found <- colnames(x)[crit2]
+      }
     }
   }
   # -- specimen
   if (type == "specimen") {
-    if (any(colnames(x) %like% "(specimen type|spec_type)")) {
+    if (any(colnames_formatted %like_case% "(specimen type|spec_type)")) {
-      found <- sort(colnames(x)[colnames(x) %like% "(specimen type|spec_type)"])[1]
+      found <- sort(colnames(x)[colnames_formatted %like_case% "(specimen type|spec_type)"])
-    } else if (any(colnames(x) %like% "^(specimen)")) {
+    } else if (any(colnames_formatted %like_case% "^(specimen)")) {
-      found <- sort(colnames(x)[colnames(x) %like% "^(specimen)"])[1]
+      found <- sort(colnames(x)[colnames_formatted %like_case% "^(specimen)"])
     }
   }
   # -- UTI (urinary tract infection)
   if (type == "uti") {
-    if (any(colnames(x) == "uti")) {
+    if (any(colnames_formatted == "uti")) {
-      found <- colnames(x)[colnames(x) == "uti"][1]
+      found <- colnames(x)[colnames_formatted == "uti"]
-    } else if (any(colnames(x) %like% "(urine|urinary)")) {
+    } else if (any(colnames_formatted %like_case% "(urine|urinary)")) {
-      found <- sort(colnames(x)[colnames(x) %like% "(urine|urinary)"])[1]
+      found <- sort(colnames(x)[colnames_formatted %like_case% "(urine|urinary)"])
     }
     if (!is.null(found)) {
       # this column should contain logicals
@@ -241,10 +249,12 @@ search_type_in_df <- function(x, type, info = TRUE) {
     }
   }
   
+  found <- found[1]
+  
   if (!is.null(found) & info == TRUE) {
     if (message_not_thrown_before(fn = paste0("search_", type))) {
       msg <- paste0("Using column '", font_bold(found), "' as input for `col_", type, "`.")
-      if (type %in% c("keyantibiotics", "specimen")) {
+      if (type %in% c("keyantibiotics", "keyantimicrobials", "specimen")) {
         msg <- paste(msg, "Use", font_bold(paste0("col_", type), "= FALSE"), "to prevent this.")
       }
       message_(msg)
@@ -696,7 +706,7 @@ meet_criteria <- function(object,
             ifelse(!is.null(has_length) && length(has_length) == 1 && has_length == 1,
                    "be a finite number",
                    "all be finite numbers"),
-            " (i.e., not be infinite)",
+            " (i.e. not be infinite)",
             call = call_depth)
   }
   if (!is.null(contains_column_class)) {
@@ -713,13 +723,7 @@ meet_criteria <- function(object,
   return(invisible())
 }
 
-get_current_data <- function(arg_name, call, reuse_from_1st_call = TRUE) {
+get_current_data <- function(arg_name, call) {
-  # check if retrieved before, then get it from package environment to improve speed
-  if (reuse_from_1st_call == TRUE &&
-      identical(unique_call_id(entire_session = FALSE), pkg_env$get_current_data.call)) {
-    return(pkg_env$get_current_data.out)
-  }
-  
   # try dplyr::cur_data_all() first to support dplyr groups
   # only useful for e.g. dplyr::filter(), dplyr::mutate() and dplyr::summarise()
   # not useful (throws error) with e.g. dplyr::select() - but that will be caught later in this function
@@ -727,73 +731,32 @@ get_current_data <- function(arg_name, call, reuse_from_1st_call = TRUE) {
   if (!is.null(cur_data_all)) {
     out <- tryCatch(cur_data_all(), error = function(e) NULL)
     if (is.data.frame(out)) {
-      out <- structure(out, type = "dplyr_cur_data_all")
+      return(structure(out, type = "dplyr_cur_data_all"))
-      pkg_env$get_current_data.call <- unique_call_id(entire_session = FALSE)
-      pkg_env$get_current_data.out <- out
-      return(out)
-    }
-  }
-
-  if (getRversion() < "3.2") {
-    # R-3.0 and R-3.1 do not have an `x` element in the call stack, rendering this function useless
-    # R-3.2 was released in April 2015
-    if (is.na(arg_name)) {
-      # such as for carbapenems() etc.
-      warning_("this function requires R version 3.2 or later - you have ", R.version.string, 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)
     }
   }
   
-  # try a (base R) method, by going over the complete system call stack with sys.frames()
+  # try a manual (base R) method, by going over all underlying environments with sys.frames()
-  not_set <- TRUE
+  for (el in sys.frames()) {
-  source <- "base_R"
+    if (!is.null(el$`.Generic`)) {
-  frms <- lapply(sys.frames(), function(el) {
+      # don't check `".Generic" %in% names(el)`, because in R < 3.2, `names(el)` is always NULL
-    if (not_set == TRUE && ".Generic" %in% names(el)) {
+      
-      if (tryCatch(".data" %in% names(el) && is.data.frame(el$`.data`), error = function(e) FALSE)) {
+      if (!is.null(el$`.data`) && is.data.frame(el$`.data`)) {
-        # - - - -
+        # an element `.data` will be in the environment when using `dplyr::select()`
-        # dplyr
+        # (but not when using `dplyr::filter()`, `dplyr::mutate()` or `dplyr::summarise()`)
-        # - - - -
+        return(structure(el$`.data`, type = "dplyr_selector"))
-        # an element `.data` will be in the system call stack when using dplyr::select()
+        
-        # [but not when using dplyr::filter(), dplyr::mutate() or dplyr::summarise()]
+      } else if (!is.null(el$xx) && is.data.frame(el$xx)) {
-        not_set <<- FALSE
+        # an element `xx` will be in the environment for rows + cols, e.g. `example_isolates[c(1:3), carbapenems()]`
-        source <<- "dplyr_selector"
+        return(structure(el$xx, type = "base_R"))
-        el$`.data`
+        
-      } else if (tryCatch(any(c("x", "xx") %in% names(el)), error = function(e) FALSE)) {
+      } else if (!is.null(el$x) && is.data.frame(el$x)) {
-        # - - - -
+        # an element `x` will be in the environment for only cols, e.g. `example_isolates[, carbapenems()]`
-        # base R
+        return(structure(el$x, type = "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$xx), error = function(e) FALSE)) {
-          not_set <<- FALSE
-          el$xx
-        } else if (tryCatch(is.data.frame(el$x))) {
-          not_set <<- FALSE
-          el$x
-        } else {
-          NULL
-        }
-      } else {
-        NULL
       }
-    } else {
-      NULL
     }
-  })
-  
-  # 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)) {
-    out <- structure(vars_df, type = source)
-    pkg_env$get_current_data.call <- unique_call_id(entire_session = FALSE)
-    pkg_env$get_current_data.out <- out
-    return(out)
   }
   
-  # nothing worked, so:
+  # no data.frame found, so an error  must be returned:
   if (is.na(arg_name)) {
     if (isTRUE(is.numeric(call))) {
       fn <- as.character(sys.call(call + 1)[1])
@@ -982,8 +945,8 @@ font_grey_bg <- function(..., collapse = " ") {
     # similar to HTML #444444
     try_colour(..., before = "\033[48;5;238m", after = "\033[49m", collapse = collapse)  
   } else {
-    # similar to HTML #eeeeee
+    # similar to HTML #f0f0f0
-    try_colour(..., before = "\033[48;5;254m", after = "\033[49m", collapse = collapse)
+    try_colour(..., before = "\033[48;5;255m", after = "\033[49m", collapse = collapse)
   }
 }
 font_green_bg <- function(..., collapse = " ") {

R/ab_class_selectors.R

@@ -25,13 +25,12 @@
 
 #' Antibiotic Class Selectors
 #' 
-#' These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations. \strong{\Sexpr{ifelse(getRversion() < "3.2", paste0("NOTE: THESE FUNCTIONS DO NOT WORK ON YOUR CURRENT R VERSION. These functions require R version 3.2 or later - you have ", R.version.string, "."), "")}}
+#' These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations.
 #' @inheritSection lifecycle Stable Lifecycle
 #' @param ab_class an antimicrobial class, such as `"carbapenems"`. The columns `group`, `atc_group1` and `atc_group2` of the [antibiotics] data set will be searched (case-insensitive) for this value.
 #' @param only_rsi_columns a [logical] to indicate whether only columns of class `<rsi>` must be selected (defaults to `FALSE`), see [as.rsi()]
-#' @details \strong{\Sexpr{ifelse(getRversion() < "3.2", paste0("NOTE: THESE FUNCTIONS DO NOT WORK ON YOUR CURRENT R VERSION. These functions require R version 3.2 or later - you have ", R.version.string, "."), "")}}
+#' @details
-#' 
+#' These functions can be used in data set calls for selecting columns and filtering rows. They are heavily inspired by the [Tidyverse selection helpers](https://tidyselect.r-lib.org/reference/language.html), but also work in base \R and not only in `dplyr` verbs. Nonetheless, they are very convenient to use with `dplyr` functions such as [`select()`][dplyr::select()], [`filter()`][dplyr::filter()] and [`summarise()`][dplyr::summarise()], see *Examples*.
-#' These functions can be used in data set calls for selecting columns and filtering rows, see *Examples*. They support base R, but work more convenient in dplyr functions such as [`select()`][dplyr::select()], [`filter()`][dplyr::filter()] and [`summarise()`][dplyr::summarise()].
 #' 
 #' All columns in the data in which these functions are called will be searched for known antibiotic names, abbreviations, brand names, and codes (ATC, EARS-Net, WHO, etc.) in the [antibiotics] data set. This means that a selector such as [aminoglycosides()] will pick up column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc. Use the [ab_class()] function to filter/select on a manually defined antibiotic class.
 #' 
@@ -267,18 +266,9 @@ ab_selector <- function(function_name,
   meet_criteria(function_name, allow_class = "character", has_length = 1, allow_NULL = TRUE, .call_depth = 1)
   meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1, .call_depth = 1)
   meet_criteria(ab_class, allow_class = "character", has_length = 1, allow_NULL = TRUE, .call_depth = 1)
-  
+
-  if (getRversion() < "3.2") {
-    # get_current_data() does not work on R 3.0 and R 3.1.
-    # R 3.2 was released in April 2015.
-    warning_("antibiotic class selectors such as ", function_name, 
-             "() require R version 3.2 or later - you have ", R.version.string,
-             call = FALSE)
-    return(NULL)
-  }
-  
   # get_current_data() has to run each time, for cases where e.g., filter() and select() are used in same call
-  vars_df <- get_current_data(arg_name = NA, call = -3, reuse_from_1st_call = FALSE)
+  vars_df <- get_current_data(arg_name = NA, call = -3)
   # to improve speed, get_column_abx() will only run once when e.g. in a select or group call
   ab_in_data <- get_column_abx(vars_df, info = FALSE, only_rsi_columns = only_rsi_columns, sort = FALSE)
   
@@ -315,12 +305,15 @@ ab_selector <- function(function_name,
     } else {
       agents_formatted <- paste0("'", font_bold(agents, collapse = NULL), "'")
       agents_names <- ab_name(names(agents), tolower = TRUE, language = NULL)
-      need_name <- tolower(gsub("[^a-zA-Z]", "", agents)) != tolower(gsub("[^a-zA-Z]", "", agents_names))
+      need_name <- generalise_antibiotic_name(agents) != generalise_antibiotic_name(agents_names)
-      agents_formatted[need_name] <- paste0(agents_formatted[need_name],
+      agents_formatted[need_name] <- paste0(agents_formatted[need_name], " (", agents_names[need_name], ")")
-                                            " (", agents_names[need_name], ")")
+      message_("For `", function_name, "(",
-      message_("For `", function_name, "(", ifelse(function_name == "ab_class", paste0("\"", ab_class, "\""), ""), ")` using ",
+               ifelse(function_name == "ab_class", 
+                      paste0("\"", ab_class, "\""),
+                      ""),
+               ")` using ",
                ifelse(length(agents) == 1, "column: ", "columns: "),
-               vector_and(agents_formatted, quotes = FALSE))
+               vector_and(agents_formatted, quotes = FALSE, sort = FALSE))
     }
     remember_thrown_message(function_name)
   }

R/deprecated.R

@@ -62,7 +62,7 @@ filter_first_weighted_isolate <- function(x = NULL,
   if (is_null_or_grouped_tbl(x)) {
     # when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
     # is also fix for using a grouped df as input (a dot as first argument)
-    x <- tryCatch(get_current_data(arg_name = "x", call = -2, reuse_from_1st_call = FALSE), error = function(e) x)
+    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_date, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
@@ -104,7 +104,7 @@ key_antibiotics <- function(x = NULL,
   if (is_null_or_grouped_tbl(x)) {
     # when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
     # is also fix for using a grouped df as input (a dot as first argument)
-    x <- tryCatch(get_current_data(arg_name = "x", call = -2, reuse_from_1st_call = FALSE), error = function(e) x)
+    x <- tryCatch(get_current_data(arg_name = "x", call = -2), error = function(e) x)
   }
 
   key_antimicrobials(x = x, 
@@ -170,7 +170,7 @@ filter_ab_class <- function(x,
   if (missing(x) || is_null_or_grouped_tbl(x)) {
     # when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
     # is also fix for using a grouped df as input (a dot as first argument)
-    x <- get_current_data(arg_name = "x", call = -2 - .call_depth, reuse_from_1st_call = FALSE)
+    x <- get_current_data(arg_name = "x", call = -2 - .call_depth)
     .x_name <- "your_data"
   }
   meet_criteria(x, allow_class = "data.frame", .call_depth = .call_depth)

R/first_isolate.R

@@ -131,11 +131,8 @@
 #' # `example_isolates` is a data set available in the AMR package.
 #' # See ?example_isolates.
 #' 
-#' example_isolates[first_isolate(example_isolates), ]
-#' \donttest{
-#' # faster way, only works in R 3.2 and later:
 #' example_isolates[first_isolate(), ]
-#' 
+#' \donttest{
 #' # get all first Gram-negatives
 #' example_isolates[which(first_isolate() & mo_is_gram_negative()), ]
 #'
@@ -207,7 +204,7 @@ first_isolate <- function(x = NULL,
   if (is_null_or_grouped_tbl(x)) {
     # when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
     # is also fix for using a grouped df as input (a dot as first argument)
-    x <- tryCatch(get_current_data(arg_name = "x", call = -2, reuse_from_1st_call = FALSE), error = function(e) x)
+    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_date, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
@@ -618,7 +615,7 @@ filter_first_isolate <- function(x = NULL,
   if (is_null_or_grouped_tbl(x)) {
     # when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
     # is also fix for using a grouped df as input (a dot as first argument)
-    x <- tryCatch(get_current_data(arg_name = "x", call = -2, reuse_from_1st_call = FALSE), error = function(e) x)
+    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_date, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))

R/join_microorganisms.R

@@ -36,7 +36,7 @@
 #' @param ... ignored, only in place to allow future extensions
 #' @details **Note:** As opposed to the `join()` functions of `dplyr`, [character] vectors are supported and at default existing columns will get a suffix `"2"` and the newly joined columns will not get a suffix. 
 #' 
-#' If the `dplyr` package is installed, their join functions will be used. Otherwise, the much slower [merge()] and [interaction()] functions from base R will be used.
+#' If the `dplyr` package is installed, their join functions will be used. Otherwise, the much slower [merge()] and [interaction()] functions from base \R will be used.
 #' @inheritSection AMR Read more on Our Website!
 #' @return a [data.frame]
 #' @export

R/key_antimicrobials.R

@@ -130,7 +130,7 @@ key_antimicrobials <- function(x = NULL,
   if (is_null_or_grouped_tbl(x)) {
     # when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
     # is also fix for using a grouped df as input (a dot as first argument)
-    x <- tryCatch(get_current_data(arg_name = "x", call = -2, reuse_from_1st_call = FALSE), error = function(e) x)
+    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, is_in = colnames(x))
@@ -232,7 +232,7 @@ all_antimicrobials <- function(x = NULL,
   if (is_null_or_grouped_tbl(x)) {
     # when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
     # is also fix for using a grouped df as input (a dot as first argument)
-    x <- tryCatch(get_current_data(arg_name = "x", call = -2, reuse_from_1st_call = FALSE), error = function(e) x)
+    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(only_rsi_columns, allow_class = "logical", has_length = 1)

R/mdro.R

@@ -170,7 +170,7 @@ mdro <- function(x = NULL,
   if (is_null_or_grouped_tbl(x)) {
     # when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
     # is also fix for using a grouped df as input (a dot as first argument)
-    x <- tryCatch(get_current_data(arg_name = "x", call = -2, reuse_from_1st_call = FALSE), error = function(e) x)
+    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(guideline, allow_class = c("list", "character"), allow_NULL = TRUE)

R/mo.R

@@ -1664,9 +1664,7 @@ pillar_shaft.mo <- function(x, ...) {
   out[is.na(x)] <- font_na("  NA")
   out[x == "UNKNOWN"] <- font_na("  UNKNOWN")
   
-  df <- tryCatch(get_current_data(arg_name = "x",
+  df <- tryCatch(get_current_data(arg_name = "x", call = 0),
-                                  call = 0,
-                                  reuse_from_1st_call = FALSE),
                  error = function(e) NULL)
   if (!is.null(df)) {
     mo_cols <- vapply(FUN.VALUE = logical(1), df, is.mo)

R/mo_property.R

@@ -747,16 +747,14 @@ mo_validate <- function(x, property, language, ...) {
 find_mo_col <- function(fn) {
   # this function tries to find an mo column in the data the function was called in,
   # which is useful when functions are used within dplyr verbs
-  df <- get_current_data(arg_name = "x", 
+  df <- get_current_data(arg_name = "x", call = -3) # will return an error if not found
-                         call = -3,
-                         reuse_from_1st_call = FALSE) # will return an error if not found
   mo <- NULL
   try({
     mo <- suppressMessages(search_type_in_df(df, "mo"))
   }, silent = TRUE)
   if (!is.null(df) && !is.null(mo) && is.data.frame(df)) {
     if (message_not_thrown_before(fn = fn)) {
-      message_("Using column '", font_bold(mo), "' as input for ", fn, "()")
+      message_("Using column '", font_bold(mo), "' as input for `", fn, "()`")
       remember_thrown_message(fn = fn)
     }
     return(df[, mo, drop = TRUE])

R/plot.R

@@ -25,7 +25,7 @@
 
 #' Plotting for Classes `rsi`, `mic` and `disk`
 #' 
-#' Functions to plot classes `rsi`, `mic` and `disk`, with support for base R and `ggplot2`.
+#' Functions to plot classes `rsi`, `mic` and `disk`, with support for base \R and `ggplot2`.
 #' @inheritSection lifecycle Stable Lifecycle
 #' @inheritSection AMR Read more on Our Website!
 #' @param x,data MIC values created with [as.mic()] or disk diffusion values created with [as.disk()]

R/random.R

@@ -32,7 +32,7 @@
 #' @param ab any [character] that can be coerced to a valid antimicrobial agent code with [as.ab()]
 #' @param prob_RSI a vector of length 3: the probabilities for R (1st value), S (2nd value) and I (3rd value)
 #' @param ... ignored, only in place to allow future extensions
-#' @details The base R function [sample()] is used for generating values.
+#' @details The base \R function [sample()] is used for generating values.
 #' 
 #' Generated values are based on the latest EUCAST guideline implemented in the [rsi_translation] data set. To create specific generated values per bug or drug, set the `mo` and/or `ab` argument.
 #' @return class `<mic>` for [random_mic()] (see [as.mic()]) and class `<disk>` for [random_disk()] (see [as.disk()])
@@ -56,18 +56,26 @@
 #' random_disk(100, "Streptococcus pneumoniae", "ampicillin") # range 12-27
 #' }
 random_mic <- function(size, mo = NULL, ab = NULL, ...) {
+  meet_criteria(size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
+  meet_criteria(mo, allow_class = "character", has_length = 1, allow_NULL = TRUE)
+  meet_criteria(ab, allow_class = "character", has_length = 1, allow_NULL = TRUE)
   random_exec("MIC", size = size, mo = mo, ab = ab)
 }
 
 #' @rdname random
 #' @export
 random_disk <- function(size, mo = NULL, ab = NULL, ...) {
+  meet_criteria(size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
+  meet_criteria(mo, allow_class = "character", has_length = 1, allow_NULL = TRUE)
+  meet_criteria(ab, allow_class = "character", has_length = 1, allow_NULL = TRUE)
   random_exec("DISK", size = size, mo = mo, ab = ab)
 }
 
 #' @rdname random
 #' @export
 random_rsi <- function(size, prob_RSI = c(0.33, 0.33, 0.33), ...) {
+  meet_criteria(size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
+  meet_criteria(prob_RSI, allow_class = c("numeric", "integer"), has_length = 3)
   sample(as.rsi(c("R", "S", "I")), size = size, replace = TRUE, prob = prob_RSI)
 }
 

R/rsi.R

@@ -349,7 +349,7 @@ as.rsi.mic <- function(x,
   
   # for dplyr's across()
   cur_column_dplyr <- import_fn("cur_column", "dplyr", error_on_fail = FALSE)
-  if (!is.null(cur_column_dplyr) && tryCatch(is.data.frame(get_current_data("ab", call = 0, reuse_from_1st_call = FALSE)), error = function(e) FALSE)) {
+  if (!is.null(cur_column_dplyr) && tryCatch(is.data.frame(get_current_data("ab", call = 0)), error = function(e) FALSE)) {
     # try to get current column, which will only be available when in across()
     ab <- tryCatch(cur_column_dplyr(),
                    error = function(e) ab)
@@ -438,7 +438,7 @@ as.rsi.disk <- function(x,
   
   # for dplyr's across()
   cur_column_dplyr <- import_fn("cur_column", "dplyr", error_on_fail = FALSE)
-  if (!is.null(cur_column_dplyr) && tryCatch(is.data.frame(get_current_data("ab", call = 0, reuse_from_1st_call = FALSE)), error = function(e) FALSE)) {
+  if (!is.null(cur_column_dplyr) && tryCatch(is.data.frame(get_current_data("ab", call = 0)), error = function(e) FALSE)) {
     # try to get current column, which will only be available when in across()
     ab <- tryCatch(cur_column_dplyr(),
                    error = function(e) ab)
@@ -448,7 +448,7 @@ as.rsi.disk <- function(x,
   mo_var_found <- ""
   if (is.null(mo)) {
     tryCatch({
-      df <- get_current_data(arg_name = "mo", call = -3, reuse_from_1st_call = FALSE) # will return an error if not found
+      df <- get_current_data(arg_name = "mo", call = -3) # will return an error if not found
       mo <- NULL
       try({
         mo <- suppressMessages(search_type_in_df(df, "mo"))

data-raw/_install_deps.R

@@ -24,8 +24,8 @@
 # ==================================================================== #
 
 # some old R instances have trouble installing tinytest, so we ship it too
-install.packages("data-raw/tinytest_1.2.4.10.tar.gz")
+install.packages("data-raw/tinytest_1.2.4.10.tar.gz", repos = "https://cran.rstudio.com/", type = "source")
-install.packages("data-raw/AMR_latest.tar.gz", dependencies = FALSE)
+install.packages("data-raw/AMR_latest.tar.gz", repos = "https://cran.rstudio.com/", type = "source", dependencies = FALSE)
 
 pkg_suggests <- gsub("[^a-zA-Z0-9]+", "", unlist(strsplit(packageDescription("AMR", fields = "Suggests"), ", ?")))
 cat("Packages listed in Suggests:", paste(pkg_suggests, collapse = ", "), "\n")

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">1.7.1.9004</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</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">1.7.1.9004</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
       </span>
     </div>
 

docs/articles/datasets.html

@@ -39,7 +39,7 @@
       </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">1.7.1.9004</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
       </span>
     </div>
 
@@ -192,7 +192,7 @@
     <div class="page-header toc-ignore">
       <h1 data-toc-skip>Data sets for download / own use</h1>
             
-            <h4 class="date">15 June 2021</h4>
+            <h4 class="date">22 June 2021</h4>
       
       <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/datasets.Rmd"><code>vignettes/datasets.Rmd</code></a></small>
       <div class="hidden name"><code>datasets.Rmd</code></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">1.7.1.9004</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</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">1.7.1.9004</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
       </span>
     </div>
 

docs/index.html

@@ -42,7 +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">1.7.1.9004</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
       </span>
     </div>
 
@@ -217,16 +217,12 @@
 <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>
-  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span><span class="op">(</span>bacteria <span class="op">=</span> <span class="fu"><a href="reference/mo_property.html">mo_fullname</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span><span class="op">)</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>bacteria <span class="op">=</span> <span class="fu"><a href="reference/mo_property.html">mo_fullname</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</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_gram_negative</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span>ab <span class="op">=</span> <span class="st">"cefotax"</span><span class="op">)</span><span class="op">)</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_gram_negative</a></span><span class="op">(</span><span class="op">)</span>,
-  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span><span class="op">(</span><span class="va">bacteria</span>, <span class="fu"><a href="reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span>
+         <span class="fu"><a href="reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span>ab <span class="op">=</span> <span class="st">"cefotax"</span><span class="op">)</span><span class="op">)</span> <span class="op">%&gt;%</span>
-<span class="co">#&gt; ℹ Using column 'mo' as input for `mo_is_gram_negative()`</span>
+  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span><span class="op">(</span><span class="va">bacteria</span>,
-<span class="co">#&gt; ℹ Using column 'mo' as input for `mo_is_intrinsic_resistant()`</span>
+         <span class="fu"><a href="reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>,
-<span class="co">#&gt; ℹ Determining intrinsic resistance based on 'EUCAST Expert Rules' and 'EUCAST Intrinsic</span>
+         <span class="fu"><a href="reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span></code></pre></div>
-<span class="co">#&gt;    Resistance and Unusual Phenotypes' v3.2 (2020)</span>
-<span class="co">#&gt; ℹ For `aminoglycosides()` using columns: 'AMK' (amikacin), 'GEN' (gentamicin), 'KAN'</span>
-<span class="co">#&gt;    (kanamycin) and 'TOB' (tobramycin)</span>
-<span class="co">#&gt; ℹ For `carbapenems()` using columns: 'IPM' (imipenem) and 'MEM' (meropenem)</span></code></pre></div>
 <p>With only having defined a row filter on Gram-negative bacteria with intrinsic resistance to cefotaxime (<code><a href="reference/mo_property.html">mo_is_gram_negative()</a></code> and <code><a href="reference/mo_property.html">mo_is_intrinsic_resistant()</a></code>) and a column selection on two antibiotic groups (<code><a href="reference/antibiotic_class_selectors.html">aminoglycosides()</a></code> and <code><a href="reference/antibiotic_class_selectors.html">carbapenems()</a></code>), the reference data about <a href="./reference/microorganisms.html">all microorganisms</a> and <a href="./reference/antibiotics.html">all antibiotics</a> in the <code>AMR</code> package make sure you get what you meant:</p>
 <table class="table">
 <thead><tr class="header">
@@ -386,7 +382,7 @@
 <div id="latest-development-version" class="section level4">
 <h4 class="hasAnchor">
 <a href="#latest-development-version" class="anchor"></a>Latest development version</h4>
-<p><img src="https://github.com/msberends/AMR/workflows/R-code-check/badge.svg?branch=master" alt="R-code-check"><img src="https://www.codefactor.io/repository/github/msberends/amr" alt="CodeFactor"><img src="https://codecov.io/gh/msberends/AMR?branch=master" alt="Codecov"></p>
+<p>[R-code-check][<a href="https://github.com/msberends/AMR/workflows/R-code-check/badge.svg?branch=master" class="uri">https://github.com/msberends/AMR/workflows/R-code-check/badge.svg?branch=master</a>](<a href="https://github.com/msberends/AMR/actions" class="uri">https://github.com/msberends/AMR/actions</a>) [CodeFactor][<a href="https://www.codefactor.io/repository/github/msberends/amr/badge" class="uri">https://www.codefactor.io/repository/github/msberends/amr/badge</a>](<a href="https://www.codefactor.io/repository/github/msberends/amr" class="uri">https://www.codefactor.io/repository/github/msberends/amr</a>) [Codecov][<a href="https://codecov.io/gh/msberends/AMR/branch/master/graph/badge.svg" class="uri">https://codecov.io/gh/msberends/AMR/branch/master/graph/badge.svg</a>](<a href="https://codecov.io/gh/msberends/AMR?branch=master" class="uri">https://codecov.io/gh/msberends/AMR?branch=master</a>)</p>
 <p>The latest and unpublished development version can be installed from GitHub in two ways:</p>
 <ol>
 <li>

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">1.7.1.9004</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
       </span>
     </div>
 
@@ -236,24 +236,34 @@
       <small>Source: <a href='https://github.com/msberends/AMR/blob/master/NEWS.md'><code>NEWS.md</code></a></small>
     </div>
 
-    <div id="amr-1719004" class="section level1">
+    <div id="amr-1719005" class="section level1">
-<h1 class="page-header" data-toc-text="1.7.1.9004">
+<h1 class="page-header" data-toc-text="1.7.1.9005">
-<a href="#amr-1719004" class="anchor"></a><small> Unreleased </small><code>AMR</code> 1.7.1.9004</h1>
+<a href="#amr-1719005" class="anchor"></a><small> Unreleased </small><code>AMR</code> 1.7.1.9005</h1>
-<div id="last-updated-15-june-2021" class="section level2">
+<div id="last-updated-22-june-2021" class="section level2">
 <h2 class="hasAnchor">
-<a href="#last-updated-15-june-2021" class="anchor"></a><small>Last updated: 15 June 2021</small>
+<a href="#last-updated-22-june-2021" class="anchor"></a><small>Last updated: 22 June 2021</small>
 </h2>
 <div id="changed" class="section level3">
 <h3 class="hasAnchor">
 <a href="#changed" class="anchor"></a>Changed</h3>
 <ul>
-<li>Added more antibiotic class selectors: <code><a href="../reference/antibiotic_class_selectors.html">aminopenicillins()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">lincosamides()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">lipoglycopeptides()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">polymyxins()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">quinolones()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">streptogramins()</a></code> and <code><a href="../reference/antibiotic_class_selectors.html">ureidopenicillins()</a></code>
+<li>Antibiotic class selectors (see <code><a href="../reference/antibiotic_class_selectors.html">ab_class()</a></code>)
+<ul>
+<li>They now finally also work in R-3.0 and R-3.1, supporting every version of R since 2013</li>
+<li>Added more selectors: <code><a href="../reference/antibiotic_class_selectors.html">aminopenicillins()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">lincosamides()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">lipoglycopeptides()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">polymyxins()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">quinolones()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">streptogramins()</a></code> and <code><a href="../reference/antibiotic_class_selectors.html">ureidopenicillins()</a></code>
+</li>
+<li>Fix for using selectors multiple times in one call (e.g., using them in <code><a href="https://dplyr.tidyverse.org/reference/filter.html">dplyr::filter()</a></code> and immediately after in <code><a href="https://dplyr.tidyverse.org/reference/select.html">dplyr::select()</a></code>)</li>
+</ul>
 </li>
 <li>Added <code><a href="https://ggplot2.tidyverse.org/reference/autoplot.html">ggplot2::autoplot()</a></code> generic for classes <code>&lt;mic&gt;</code>, <code>&lt;disk&gt;</code>, <code>&lt;rsi&gt;</code> and <code>&lt;resistance_predict&gt;</code>
 </li>
 <li>Fix to prevent introducing <code>NA</code>s for old MO codes when running <code><a href="../reference/as.mo.html">as.mo()</a></code> on them</li>
 <li>Added more informative error messages when any of the <code>proportion_*()</code> and <code>count_*()</code> functions fail</li>
-<li>Fix for using antibiotic selectors multiple times in one call (e.g., using in <code><a href="https://dplyr.tidyverse.org/reference/filter.html">dplyr::filter()</a></code> and immediately after in <code><a href="https://dplyr.tidyverse.org/reference/select.html">dplyr::select()</a></code>)</li>
+<li>When printing a tibble with any old MO code, a warning will be thrown that old codes should be updated using <code><a href="../reference/as.mo.html">as.mo()</a></code>
+</li>
+<li>Improved automatic column selector when <code>col_*</code> arguments are left blank, e.g. in <code><a href="../reference/first_isolate.html">first_isolate()</a></code>
+</li>
+<li>The right input types for <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> are now enforced</li>
 </ul>
 </div>
 </div>
@@ -307,7 +317,7 @@
 </ul>
 </li>
 <li>Function <code><a href="../reference/antibiotic_class_selectors.html">betalactams()</a></code> as additional antbiotic column selector and function <code><a href="../reference/AMR-deprecated.html">filter_betalactams()</a></code> as additional antbiotic column filter. The group of betalactams consists of all carbapenems, cephalosporins and penicillins.</li>
-<li>A <code>ggplot()</code> method for <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code>
+<li>A <code><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot()</a></code> method for <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code>
 </li>
 </ul>
 </div>
@@ -408,7 +418,7 @@
 <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>ggplot()</code> generics for classes <code>&lt;mic&gt;</code> and <code>&lt;disk&gt;</code></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>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="cb4"><pre class="downlit sourceCode r">
@@ -465,7 +475,7 @@
 <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>ggplot()</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><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot()</a></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>

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: 2021-06-15T08:50Z
+last_built: 2021-06-22T10:02Z
 urls:
   reference: https://msberends.github.io/AMR//reference
   article: https://msberends.github.io/AMR//articles

docs/reference/antibiotic_class_selectors.html

@@ -49,8 +49,7 @@
   <script src="../extra.js"></script>
 
 <meta property="og:title" content="Antibiotic Class Selectors — antibiotic_class_selectors" />
-<meta property="og:description" content="These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations. 
+<meta property="og:description" content="These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations." />
-" />
 <meta property="og:image" content="https://msberends.github.io/AMR/logo.png" />
 
 
@@ -83,7 +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">1.7.1.9001</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
       </span>
     </div>
 
@@ -240,8 +239,7 @@
     </div>
 
     <div class="ref-description">
-    <p>These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations. <strong>
+    <p>These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations.</p>
-</strong></p>
     </div>
 
     <pre class="usage"><span class='fu'>ab_class</span><span class='op'>(</span><span class='va'>ab_class</span>, only_rsi_columns <span class='op'>=</span> <span class='cn'>FALSE</span><span class='op'>)</span>
@@ -305,9 +303,7 @@
 
     <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
 
-    <p><strong>
+    <p>These functions can be used in data set calls for selecting columns and filtering rows. They are heavily inspired by the <a href='https://tidyselect.r-lib.org/reference/language.html'>Tidyverse selection helpers</a>, but also work in base <span style="R">R</span> and not only in <code>dplyr</code> verbs. Nonetheless, they are very convenient to use with <code>dplyr</code> functions such as <code><a href='https://dplyr.tidyverse.org/reference/select.html'>select()</a></code>, <code><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter()</a></code> and <code><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarise()</a></code>, see <em>Examples</em>.</p>
-</strong></p>
-<p>These functions can be used in data set calls for selecting columns and filtering rows, see <em>Examples</em>. They support base R, but work more convenient in dplyr functions such as <code><a href='https://dplyr.tidyverse.org/reference/select.html'>select()</a></code>, <code><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter()</a></code> and <code><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarise()</a></code>.</p>
 <p>All columns in the data in which these functions are called will be searched for known antibiotic names, abbreviations, brand names, and codes (ATC, EARS-Net, WHO, etc.) in the <a href='antibiotics.html'>antibiotics</a> data set. This means that a selector such as <code>aminoglycosides()</code> will pick up column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc. Use the <code>ab_class()</code> function to filter/select on a manually defined antibiotic class.</p>
     <h2 class="hasAnchor" id="full-list-of-supported-agents"><a class="anchor" href="#full-list-of-supported-agents"></a>Full list of supported agents</h2>
 

docs/reference/count.html

@@ -83,7 +83,7 @@ count_resistant() should be used to count resistant isolates, count_susceptible(
       </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">1.7.1.9002</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
       </span>
     </div>
 

docs/reference/first_isolate.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">1.7.1</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
       </span>
     </div>
 
@@ -457,11 +457,8 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
     <pre class="examples"><span class='co'># `example_isolates` is a data set available in the AMR package.</span>
 <span class='co'># See ?example_isolates.</span>
 
-<span class='va'>example_isolates</span><span class='op'>[</span><span class='fu'>first_isolate</span><span class='op'>(</span><span class='va'>example_isolates</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'>first_isolate</span><span class='op'>(</span><span class='op'>)</span>, <span class='op'>]</span>
-
+<span class='co'># \donttest{</span>
 <span class='co'># get all first Gram-negatives</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'>first_isolate</span><span class='op'>(</span><span class='op'>)</span> <span class='op'>&amp;</span> <span class='fu'><a href='mo_property.html'>mo_is_gram_negative</a></span><span class='op'>(</span><span class='op'>)</span><span class='op'>)</span>, <span class='op'>]</span>
 

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">1.7.1.9004</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
       </span>
     </div>
 

docs/reference/join.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">1.7.1</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
       </span>
     </div>
 
@@ -281,7 +281,7 @@
     <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
 
     <p><strong>Note:</strong> As opposed to the <code>join()</code> functions of <code>dplyr</code>, <a href='https://rdrr.io/r/base/character.html'>character</a> vectors are supported and at default existing columns will get a suffix <code>"2"</code> and the newly joined columns will not get a suffix.</p>
-<p>If the <code>dplyr</code> package is installed, their join functions will be used. Otherwise, the much slower <code><a href='https://rdrr.io/r/base/merge.html'>merge()</a></code> and <code><a href='https://rdrr.io/r/base/interaction.html'>interaction()</a></code> functions from base R will be used.</p>
+<p>If the <code>dplyr</code> package is installed, their join functions will be used. Otherwise, the much slower <code><a href='https://rdrr.io/r/base/merge.html'>merge()</a></code> and <code><a href='https://rdrr.io/r/base/interaction.html'>interaction()</a></code> functions from base <span style="R">R</span> will be used.</p>
     <h2 class="hasAnchor" id="stable-lifecycle"><a class="anchor" href="#stable-lifecycle"></a>Stable Lifecycle</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">1.7.1.9002</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
       </span>
     </div>
 
@@ -239,7 +239,7 @@
     </div>
 
     <div class="ref-description">
-    <p>Functions to plot classes <code>rsi</code>, <code>mic</code> and <code>disk</code>, with support for base R and <code>ggplot2</code>.</p>
+    <p>Functions to plot classes <code>rsi</code>, <code>mic</code> and <code>disk</code>, with support for base <span style="R">R</span> and <code>ggplot2</code>.</p>
     </div>
 
     <pre class="usage"><span class='co'># S3 method for mic</span>

docs/reference/random.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">1.7.1</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
       </span>
     </div>
 
@@ -278,7 +278,7 @@
     <p>class <code>&lt;mic&gt;</code> for <code>random_mic()</code> (see <code><a href='as.mic.html'>as.mic()</a></code>) and class <code>&lt;disk&gt;</code> for <code>random_disk()</code> (see <code><a href='as.disk.html'>as.disk()</a></code>)</p>
     <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
 
-    <p>The base R function <code><a href='https://rdrr.io/r/base/sample.html'>sample()</a></code> is used for generating values.</p>
+    <p>The base <span style="R">R</span> function <code><a href='https://rdrr.io/r/base/sample.html'>sample()</a></code> is used for generating values.</p>
 <p>Generated values are based on the latest EUCAST guideline implemented in the <a href='rsi_translation.html'>rsi_translation</a> data set. To create specific generated values per bug or drug, set the <code>mo</code> and/or <code>ab</code> argument.</p>
     <h2 class="hasAnchor" id="stable-lifecycle"><a class="anchor" href="#stable-lifecycle"></a>Stable Lifecycle</h2>
 

docs/reference/resistance_predict.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">1.7.1.9002</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
       </span>
     </div>
 

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">1.7.1.9004</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
       </span>
     </div>
 

index.md

@@ -25,16 +25,12 @@ library(AMR)
 library(dplyr)
 
 example_isolates %>%
-  mutate(bacteria = mo_fullname(mo)) %>%
+  mutate(bacteria = mo_fullname()) %>%
-  filter(mo_is_gram_negative(), mo_is_intrinsic_resistant(ab = "cefotax")) %>%
+  filter(mo_is_gram_negative(),
-  select(bacteria, aminoglycosides(), carbapenems())
+         mo_is_intrinsic_resistant(ab = "cefotax")) %>%
-#> ℹ Using column 'mo' as input for `mo_is_gram_negative()`
+  select(bacteria,
-#> ℹ Using column 'mo' as input for `mo_is_intrinsic_resistant()`
+         aminoglycosides(),
-#> ℹ Determining intrinsic resistance based on 'EUCAST Expert Rules' and 'EUCAST Intrinsic
+         carbapenems())
-#>    Resistance and Unusual Phenotypes' v3.2 (2020)
-#> ℹ For `aminoglycosides()` using columns: 'AMK' (amikacin), 'GEN' (gentamicin), 'KAN'
-#>    (kanamycin) and 'TOB' (tobramycin)
-#> ℹ For `carbapenems()` using columns: 'IPM' (imipenem) and 'MEM' (meropenem)
 ```
 
 With only having defined a row filter on Gram-negative bacteria with intrinsic resistance to cefotaxime (`mo_is_gram_negative()` and `mo_is_intrinsic_resistant()`) and a column selection on two antibiotic groups (`aminoglycosides()` and `carbapenems()`), the reference data about [all microorganisms](./reference/microorganisms.html) and [all antibiotics](./reference/antibiotics.html) in the `AMR` package make sure you get what you meant:
@@ -114,9 +110,9 @@ It will be downloaded and installed automatically. For RStudio, click on the men
 
 #### Latest development version
 
-![R-code-check](https://github.com/msberends/AMR/workflows/R-code-check/badge.svg?branch=master)
+![R-code-check][https://github.com/msberends/AMR/workflows/R-code-check/badge.svg?branch=master](https://github.com/msberends/AMR/actions)
-![[CodeFactor](https://www.codefactor.io/repository/github/msberends/amr/badge)](https://www.codefactor.io/repository/github/msberends/amr)
+![CodeFactor][https://www.codefactor.io/repository/github/msberends/amr/badge](https://www.codefactor.io/repository/github/msberends/amr)
-![[Codecov](https://codecov.io/gh/msberends/AMR/branch/master/graph/badge.svg)](https://codecov.io/gh/msberends/AMR?branch=master)
+![Codecov][https://codecov.io/gh/msberends/AMR/branch/master/graph/badge.svg](https://codecov.io/gh/msberends/AMR?branch=master)
 
 The latest and unpublished development version can be installed from GitHub in two ways:
 

inst/tinytest/test-ab_class_selectors.R

@@ -23,52 +23,48 @@
 # how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
 # ==================================================================== #
 
-if (getRversion() < "3.2") {
+# antibiotic class selectors
-  expect_warning(example_isolates[, aminoglycosides(), drop = FALSE])
+expect_true(ncol(example_isolates[, ab_class("antimyco"), drop = FALSE]) < ncol(example_isolates))
-}
+expect_true(ncol(example_isolates[, aminoglycosides(), drop = FALSE]) < ncol(example_isolates))
-if (getRversion() >= "3.2") {
+expect_true(ncol(example_isolates[, aminopenicillins(), drop = FALSE]) < ncol(example_isolates))
-  # antibiotic class selectors require at least R-3.2
+expect_true(ncol(example_isolates[, betalactams(), drop = FALSE]) < ncol(example_isolates))
-  expect_true(ncol(example_isolates[, ab_class("antimyco"), drop = FALSE]) < ncol(example_isolates))
+expect_true(ncol(example_isolates[, carbapenems(), drop = FALSE]) < ncol(example_isolates))
-  expect_true(ncol(example_isolates[, aminoglycosides(), drop = FALSE]) < ncol(example_isolates))
+expect_true(ncol(example_isolates[, cephalosporins(), drop = FALSE]) < ncol(example_isolates))
-  expect_true(ncol(example_isolates[, aminopenicillins(), drop = FALSE]) < ncol(example_isolates))
+expect_true(ncol(example_isolates[, cephalosporins_1st(), drop = FALSE]) < ncol(example_isolates))
-  expect_true(ncol(example_isolates[, betalactams(), drop = FALSE]) < ncol(example_isolates))
+expect_true(ncol(example_isolates[, cephalosporins_2nd(), drop = FALSE]) < ncol(example_isolates))
-  expect_true(ncol(example_isolates[, carbapenems(), drop = FALSE]) < ncol(example_isolates))
+expect_true(ncol(example_isolates[, cephalosporins_3rd(), drop = FALSE]) < ncol(example_isolates))
-  expect_true(ncol(example_isolates[, cephalosporins(), drop = FALSE]) < ncol(example_isolates))
+expect_true(ncol(example_isolates[, cephalosporins_4th(), drop = FALSE]) < ncol(example_isolates))
-  expect_true(ncol(example_isolates[, cephalosporins_1st(), drop = FALSE]) < ncol(example_isolates))
+expect_true(ncol(example_isolates[, cephalosporins_5th(), drop = FALSE]) < ncol(example_isolates))
-  expect_true(ncol(example_isolates[, cephalosporins_2nd(), drop = FALSE]) < ncol(example_isolates))
+expect_true(ncol(example_isolates[, fluoroquinolones(), drop = FALSE]) < ncol(example_isolates))
-  expect_true(ncol(example_isolates[, cephalosporins_3rd(), drop = FALSE]) < ncol(example_isolates))
+expect_true(ncol(example_isolates[, glycopeptides(), drop = FALSE]) < ncol(example_isolates))
-  expect_true(ncol(example_isolates[, cephalosporins_4th(), drop = FALSE]) < ncol(example_isolates))
+expect_true(ncol(example_isolates[, lincosamides(), drop = FALSE]) < ncol(example_isolates))
-  expect_true(ncol(example_isolates[, cephalosporins_5th(), drop = FALSE]) < ncol(example_isolates))
+expect_true(ncol(example_isolates[, lipoglycopeptides(), drop = FALSE]) < ncol(example_isolates))
-  expect_true(ncol(example_isolates[, fluoroquinolones(), drop = FALSE]) < ncol(example_isolates))
+expect_true(ncol(example_isolates[, macrolides(), drop = FALSE]) < ncol(example_isolates))
-  expect_true(ncol(example_isolates[, glycopeptides(), drop = FALSE]) < ncol(example_isolates))
+expect_true(ncol(example_isolates[, oxazolidinones(), drop = FALSE]) < ncol(example_isolates))
-  expect_true(ncol(example_isolates[, lincosamides(), drop = FALSE]) < ncol(example_isolates))
+expect_true(ncol(example_isolates[, penicillins(), drop = FALSE]) < ncol(example_isolates))
-  expect_true(ncol(example_isolates[, lipoglycopeptides(), drop = FALSE]) < ncol(example_isolates))
+expect_true(ncol(example_isolates[, polymyxins(), drop = FALSE]) < ncol(example_isolates))
-  expect_true(ncol(example_isolates[, macrolides(), drop = FALSE]) < ncol(example_isolates))
+expect_true(ncol(example_isolates[, streptogramins(), drop = FALSE]) < ncol(example_isolates))
-  expect_true(ncol(example_isolates[, oxazolidinones(), drop = FALSE]) < ncol(example_isolates))
+expect_true(ncol(example_isolates[, quinolones(), drop = FALSE]) < ncol(example_isolates))
-  expect_true(ncol(example_isolates[, penicillins(), drop = FALSE]) < ncol(example_isolates))
+expect_true(ncol(example_isolates[, tetracyclines(), drop = FALSE]) < ncol(example_isolates))
-  expect_true(ncol(example_isolates[, polymyxins(), drop = FALSE]) < ncol(example_isolates))
+expect_true(ncol(example_isolates[, ureidopenicillins(), drop = FALSE]) < ncol(example_isolates))
-  expect_true(ncol(example_isolates[, streptogramins(), drop = FALSE]) < ncol(example_isolates))
+
-  expect_true(ncol(example_isolates[, quinolones(), drop = FALSE]) < ncol(example_isolates))
+# Examples:
-  expect_true(ncol(example_isolates[, tetracyclines(), drop = FALSE]) < ncol(example_isolates))
+
-  expect_true(ncol(example_isolates[, ureidopenicillins(), drop = FALSE]) < ncol(example_isolates))
+# select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB'
-  
+expect_equal(ncol(example_isolates[, c("mo", aminoglycosides())]), 5, tolerance = 0.5)
-  # Examples:
+
-  
+# filter using any() or all()
-  # select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB'
+expect_equal(nrow(example_isolates[any(carbapenems() == "R"), ]), 55, tolerance = 0.5)
-  expect_equal(ncol(example_isolates[, c("mo", aminoglycosides())]), 5, tolerance = 0.5)
+expect_equal(nrow(subset(example_isolates, any(carbapenems() == "R"))), 55, tolerance = 0.5)
-  
+
-  # filter using any() or all()
+# filter on any or all results in the carbapenem columns (i.e., IPM, MEM):
-  expect_equal(nrow(example_isolates[any(carbapenems() == "R"), ]), 55, tolerance = 0.5)
+expect_equal(nrow(example_isolates[any(carbapenems()), ]), 962, tolerance = 0.5)
-  expect_equal(nrow(subset(example_isolates, any(carbapenems() == "R"))), 55, tolerance = 0.5)
+expect_equal(nrow(example_isolates[all(carbapenems()), ]), 756, tolerance = 0.5)
-  
+
-  # filter on any or all results in the carbapenem columns (i.e., IPM, MEM):
+# filter with multiple antibiotic selectors using c()
-  expect_equal(nrow(example_isolates[any(carbapenems()), ]), 962, tolerance = 0.5)
+expect_equal(nrow(example_isolates[all(c(carbapenems(), aminoglycosides()) == "R"), ]), 26, tolerance = 0.5)
-  expect_equal(nrow(example_isolates[all(carbapenems()), ]), 756, tolerance = 0.5)
+
-  
+# filter + select in one go: get penicillins in carbapenems-resistant strains
-  # filter with multiple antibiotic selectors using c()
+expect_equal(nrow(example_isolates[any(carbapenems() == "R"), penicillins()]), 55, tolerance = 0.5)
-  expect_equal(nrow(example_isolates[all(c(carbapenems(), aminoglycosides()) == "R"), ]), 26, tolerance = 0.5)
+expect_equal(ncol(example_isolates[any(carbapenems() == "R"), penicillins()]), 7, tolerance = 0.5)
-  
+
-  # filter + select in one go: get penicillins in carbapenems-resistant strains
-  expect_equal(nrow(example_isolates[any(carbapenems() == "R"), penicillins()]), 55, tolerance = 0.5)
-  expect_equal(ncol(example_isolates[any(carbapenems() == "R"), penicillins()]), 7, tolerance = 0.5)
-}

man/antibiotic_class_selectors.Rd

@@ -79,12 +79,10 @@ ureidopenicillins(only_rsi_columns = FALSE)
 \item{only_rsi_columns}{a \link{logical} to indicate whether only columns of class \verb{<rsi>} must be selected (defaults to \code{FALSE}), see \code{\link[=as.rsi]{as.rsi()}}}
 }
 \description{
-These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations. \strong{\Sexpr{ifelse(getRversion() < "3.2", paste0("NOTE: THESE FUNCTIONS DO NOT WORK ON YOUR CURRENT R VERSION. These functions require R version 3.2 or later - you have ", R.version.string, "."), "")}}
+These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations.
 }
 \details{
-\strong{\Sexpr{ifelse(getRversion() < "3.2", paste0("NOTE: THESE FUNCTIONS DO NOT WORK ON YOUR CURRENT R VERSION. These functions require R version 3.2 or later - you have ", R.version.string, "."), "")}}
+These functions can be used in data set calls for selecting columns and filtering rows. They are heavily inspired by the \href{https://tidyselect.r-lib.org/reference/language.html}{Tidyverse selection helpers}, but also work in base \R and not only in \code{dplyr} verbs. Nonetheless, they are very convenient to use with \code{dplyr} functions such as \code{\link[dplyr:select]{select()}}, \code{\link[dplyr:filter]{filter()}} and \code{\link[dplyr:summarise]{summarise()}}, see \emph{Examples}.
-
-These functions can be used in data set calls for selecting columns and filtering rows, see \emph{Examples}. They support base R, but work more convenient in dplyr functions such as \code{\link[dplyr:select]{select()}}, \code{\link[dplyr:filter]{filter()}} and \code{\link[dplyr:summarise]{summarise()}}.
 
 All columns in the data in which these functions are called will be searched for known antibiotic names, abbreviations, brand names, and codes (ATC, EARS-Net, WHO, etc.) in the \link{antibiotics} data set. This means that a selector such as \code{\link[=aminoglycosides]{aminoglycosides()}} will pick up column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc. Use the \code{\link[=ab_class]{ab_class()}} function to filter/select on a manually defined antibiotic class.
 }

man/first_isolate.Rd

@@ -181,11 +181,8 @@ On our website \url{https://msberends.github.io/AMR/} you can find \href{https:/
 # `example_isolates` is a data set available in the AMR package.
 # See ?example_isolates.
 
-example_isolates[first_isolate(example_isolates), ]
-\donttest{
-# faster way, only works in R 3.2 and later:
 example_isolates[first_isolate(), ]
-
+\donttest{
 # get all first Gram-negatives
 example_isolates[which(first_isolate() & mo_is_gram_negative()), ]
 

man/join.Rd

@@ -41,7 +41,7 @@ Join the data set \link{microorganisms} easily to an existing data set or to a \
 \details{
 \strong{Note:} As opposed to the \code{join()} functions of \code{dplyr}, \link{character} vectors are supported and at default existing columns will get a suffix \code{"2"} and the newly joined columns will not get a suffix.
 
-If the \code{dplyr} package is installed, their join functions will be used. Otherwise, the much slower \code{\link[=merge]{merge()}} and \code{\link[=interaction]{interaction()}} functions from base R will be used.
+If the \code{dplyr} package is installed, their join functions will be used. Otherwise, the much slower \code{\link[=merge]{merge()}} and \code{\link[=interaction]{interaction()}} functions from base \R will be used.
 }
 \section{Stable Lifecycle}{
 

man/plot.Rd

@@ -158,7 +158,7 @@
 The \code{ggplot} functions return a \code{\link[ggplot2:ggplot]{ggplot}} model that is extendible with any \code{ggplot2} function.
 }
 \description{
-Functions to plot classes \code{rsi}, \code{mic} and \code{disk}, with support for base R and \code{ggplot2}.
+Functions to plot classes \code{rsi}, \code{mic} and \code{disk}, with support for base \R and \code{ggplot2}.
 }
 \details{
 The interpretation of "I" will be named "Increased exposure" for all EUCAST guidelines since 2019, and will be named "Intermediate" in all other cases.

man/random.Rd

@@ -31,7 +31,7 @@ class \verb{<mic>} for \code{\link[=random_mic]{random_mic()}} (see \code{\link[
 These functions can be used for generating random MIC values and disk diffusion diameters, for AMR data analysis practice. By providing a microorganism and antimicrobial agent, the generated results will reflect reality as much as possible.
 }
 \details{
-The base R function \code{\link[=sample]{sample()}} is used for generating values.
+The base \R function \code{\link[=sample]{sample()}} is used for generating values.
 
 Generated values are based on the latest EUCAST guideline implemented in the \link{rsi_translation} data set. To create specific generated values per bug or drug, set the \code{mo} and/or \code{ab} argument.
 }