reftbl in plots, speedup for as.sir() and mo_validate

DESCRIPTION

@@ -1,5 +1,5 @@
 Package: AMR
-Version: 2.0.0.9029
+Version: 2.0.0.9030
 Date: 2023-07-10
 Title: Antimicrobial Resistance Data Analysis
 Description: Functions to simplify and standardise antimicrobial resistance (AMR)

NEWS.md

@@ -1,4 +1,4 @@
-# AMR 2.0.0.9029
+# AMR 2.0.0.9030
 
 ## New
 * Clinical breakpoints and intrinsic resistance of EUCAST 2023 and CLSI 2023 have been added for `as.sir()`. EUCAST 2023 (v13.0) is now the new default guideline for all MIC and disks diffusion interpretations
@@ -15,6 +15,10 @@
 ## Changed
 * Updated algorithm of `as.mo()` by giving more weight to fungi
 * `mo_rank()` now returns `NA` for 'unknown' microorganisms (`B_ANAER`, `B_ANAER-NEG`, `B_ANAER-POS`, `B_GRAMN`, `B_GRAMP`, `F_FUNGUS`, `F_YEAST`, and `UNKNOWN`)
+* When printing MO codes in a tibble, a mouse-hover now shows the full name of the microorganism
+* Plots for MIC and disk diffusion values:
+  * Now have settable arguments for breakpoint type and PK/PD, like `as.sir()`
+  * Will now contain the name of the guideline table in the subtitle of the plot
 * Fixed formatting for `sir_interpretation_history()`
 * Fixed some WHONET codes for microorganisms and consequently a couple of entries in `clinical_breakpoints`
 * Fixed a bug for `as.mo()` that led to coercion of `NA` values when using custom microorganism codes
@@ -26,6 +30,7 @@
 * Updated the code table in `microorganisms.codes`
 * Fixed an endless loop if using `reference_df` in `as.mo()`
 * Fixed bug for indicating UTIs in `as.sir()`
+* Greatly improved speed of `as.sir()`
 
 
 # AMR 2.0.0

R/aa_globals.R

@@ -60,19 +60,19 @@ EUCAST_VERSION_EXPERT_RULES <- list(
     version_txt = "v3.3",
     year = 2021,
     title = "'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes'",
-    url = "https://www.eucast.org/expert_rules_and_expected_phenotypes/"
+    url = "https://www.eucast.org/expert_rules_and_expected_phenotypes"
   ),
   "3.2" = list(
     version_txt = "v3.2",
     year = 2020,
     title = "'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes'",
-    url = "https://www.eucast.org/expert_rules_and_expected_phenotypes/"
+    url = "https://www.eucast.org/expert_rules_and_expected_phenotypes"
   ),
   "3.1" = list(
     version_txt = "v3.1",
     year = 2016,
     title = "'EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes'",
-    url = "https://www.eucast.org/expert_rules_and_expected_phenotypes/"
+    url = "https://www.eucast.org/expert_rules_and_expected_phenotypes"
   )
 )
 # EUCAST_VERSION_RESISTANTPHENOTYPES <- list(
@@ -80,7 +80,7 @@ EUCAST_VERSION_EXPERT_RULES <- list(
 #     version_txt = "v1.2",
 #     year = 2023,
 #     title = "'Expected Resistant Phenotypes'",
-#     url = "https://www.eucast.org/expert_rules_and_expected_phenotypes/"
+#     url = "https://www.eucast.org/expert_rules_and_expected_phenotypes"
 #   )
 # )
 

R/aa_helper_functions.R

@@ -1237,7 +1237,7 @@ font_grey_bg <- function(..., collapse = " ") {
 }
 font_red_bg <- function(..., collapse = " ") {
   # this is #ed553b (picked to be colourblind-safe with other SIR colours)
-  try_colour(font_black(..., collapse = collapse), before = "\033[48;5;203m", after = "\033[49m", collapse = collapse)
+  try_colour(font_black(..., collapse = collapse, adapt = FALSE), before = "\033[48;5;203m", after = "\033[49m", collapse = collapse)
 }
 font_orange_bg <- function(..., collapse = " ") {
   # this is #f6d55c (picked to be colourblind-safe with other SIR colours)
@@ -1533,19 +1533,17 @@ readRDS_AMR <- function(file, refhook = NULL) {
 # Faster data.table implementations ----
 
 match <- function(x, table, ...) {
-  chmatch <- import_fn("chmatch", "data.table", error_on_fail = FALSE)
+  if (!is.null(AMR_env$chmatch) && inherits(x, "character") && inherits(table, "character")) {
-  if (!is.null(chmatch) && is.character(x) && is.character(table)) {
     # data.table::chmatch() is much faster than base::match() for character
-    chmatch(x, table, ...)
+    AMR_env$chmatch(x, table, ...)
   } else {
     base::match(x, table, ...)
   }
 }
 `%in%` <- function(x, table) {
-  chin <- import_fn("%chin%", "data.table", error_on_fail = FALSE)
+  if (!is.null(AMR_env$chin) && inherits(x, "character") && inherits(table, "character")) {
-  if (!is.null(chin) && is.character(x) && is.character(table)) {
     # data.table::`%chin%`() is much faster than base::`%in%`() for character
-    chin(x, table)
+    AMR_env$chin(x, table)
   } else {
     base::`%in%`(x, table)
   }

R/mo.R

@@ -628,6 +628,12 @@ pillar_shaft.mo <- function(x, ...) {
     )
   }
   
+  # add the names to the bugs as mouse-over!
+  if (tryCatch(isTRUE(getExportedValue("ansi_has_hyperlink_support", ns = asNamespace("cli"))()), error = function(e) FALSE)) {
+    out[!x %in% c("UNKNOWN", NA)] <- font_url(url = mo_name(x[!x %in% c("UNKNOWN", NA)], language = NULL, keep_synonyms = TRUE),
+                                              txt = out[!x %in% c("UNKNOWN", NA)])
+  }
+  
   # make it always fit exactly
   max_char <- max(nchar(x))
   if (is.na(max_char)) {

R/mo_property.R

@@ -914,6 +914,15 @@ mo_validate <- function(x, property, language, keep_synonyms = keep_synonyms, ..
   }
   has_Becker_or_Lancefield <- Becker %in% c(TRUE, "all") || Lancefield %in% c(TRUE, "all")
   
+  if (isFALSE(has_Becker_or_Lancefield) && isTRUE(keep_synonyms) && all(x %in% c(AMR_env$MO_lookup$mo, NA))) {
+    # fastest way to get properties
+    if (property == "snomed") {
+      x <- lapply(x, function(y) unlist(AMR_env$MO_lookup$snomed[match(y, AMR_env$MO_lookup$mo)]))
+    } else {
+      x <- AMR_env$MO_lookup[[property]][match(x, AMR_env$MO_lookup$mo)]
+    }
+    
+  } else {
     # get microorganisms data set, but remove synonyms if keep_synonyms is FALSE
     mo_data_check <- AMR_env$MO_lookup[which(AMR_env$MO_lookup$status %in% if (isTRUE(keep_synonyms)) c("synonym", "accepted") else "accepted"), , drop = FALSE]
     
@@ -934,6 +943,7 @@ mo_validate <- function(x, property, language, keep_synonyms = keep_synonyms, ..
     } else {
       x <- AMR_env$MO_lookup[[property]][match(x, AMR_env$MO_lookup$mo)]
     }
+  }
 
   if (property == "mo") {
     return(set_clean_class(x, new_class = c("mo", "character")))

R/plot.R

@@ -40,6 +40,7 @@
 #' @param colours_SIR colours to use for filling in the bars, must be a vector of three values (in the order S, I and R). The default colours are colour-blind friendly.
 #' @param language language to be used to translate 'Susceptible', 'Increased exposure'/'Intermediate' and 'Resistant' - the default is system language (see [get_AMR_locale()]) and can be overwritten by setting the [package option][AMR-options] [`AMR_locale`][AMR-options], e.g. `options(AMR_locale = "de")`, see [translate]. Use `language = NULL` or `language = ""` to prevent translation.
 #' @param expand a [logical] to indicate whether the range on the x axis should be expanded between the lowest and highest value. For MIC values, intermediate values will be factors of 2 starting from the highest MIC value. For disk diameters, the whole diameter range will be filled.
+#' @inheritParams as.sir
 #' @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.
 #'
@@ -93,6 +94,8 @@ plot.mic <- function(x,
                      colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
                      language = get_AMR_locale(),
                      expand = TRUE,
+                     include_PKPD = getOption("AMR_include_PKPD", TRUE),
+                     breakpoint_type = getOption("AMR_breakpoint_type", "human"),
                      ...) {
   meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE)
   meet_criteria(ab, allow_class = c("ab", "character"), allow_NULL = TRUE)
@@ -123,7 +126,9 @@ plot.mic <- function(x,
     colours_SIR = colours_SIR,
     fn = as.mic,
     language = language,
-    type = "MIC",
+    method = "MIC",
+    include_PKPD = include_PKPD,
+    breakpoint_type = breakpoint_type,
     ...
   )
   barplot(x,
@@ -224,6 +229,8 @@ autoplot.mic <- function(object,
                          colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
                          language = get_AMR_locale(),
                          expand = TRUE,
+                         include_PKPD = getOption("AMR_include_PKPD", TRUE),
+                         breakpoint_type = getOption("AMR_breakpoint_type", "human"),
                          ...) {
   stop_ifnot_installed("ggplot2")
   meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE)
@@ -256,7 +263,9 @@ autoplot.mic <- function(object,
     colours_SIR = colours_SIR,
     fn = as.mic,
     language = language,
-    type = "MIC",
+    method = "MIC",
+    include_PKPD = include_PKPD,
+    breakpoint_type = breakpoint_type,
     ...
   )
   df <- as.data.frame(x, stringsAsFactors = TRUE)
@@ -327,6 +336,8 @@ plot.disk <- function(x,
                       colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
                       language = get_AMR_locale(),
                       expand = TRUE,
+                      include_PKPD = getOption("AMR_include_PKPD", TRUE),
+                      breakpoint_type = getOption("AMR_breakpoint_type", "human"),
                       ...) {
   meet_criteria(main, allow_class = "character", has_length = 1, allow_NULL = TRUE)
   meet_criteria(ylab, allow_class = "character", has_length = 1)
@@ -357,7 +368,9 @@ plot.disk <- function(x,
     colours_SIR = colours_SIR,
     fn = as.disk,
     language = language,
-    type = "disk",
+    method = "disk",
+    include_PKPD = include_PKPD,
+    breakpoint_type = breakpoint_type,
     ...
   )
 
@@ -458,6 +471,8 @@ autoplot.disk <- function(object,
                           colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
                           language = get_AMR_locale(),
                           expand = TRUE,
+                          include_PKPD = getOption("AMR_include_PKPD", TRUE),
+                          breakpoint_type = getOption("AMR_breakpoint_type", "human"),
                           ...) {
   stop_ifnot_installed("ggplot2")
   meet_criteria(title, allow_class = "character", allow_NULL = TRUE)
@@ -490,7 +505,9 @@ autoplot.disk <- function(object,
     colours_SIR = colours_SIR,
     fn = as.disk,
     language = language,
-    type = "disk",
+    method = "disk",
+    include_PKPD = include_PKPD,
+    breakpoint_type = breakpoint_type,
     ...
   )
   df <- as.data.frame(x, stringsAsFactors = TRUE)
@@ -744,7 +761,7 @@ plot_name_of_I <- function(guideline) {
   }
 }
 
-plot_colours_subtitle_guideline <- function(x, mo, ab, guideline, colours_SIR, fn, language, type, ...) {
+plot_colours_subtitle_guideline <- function(x, mo, ab, guideline, colours_SIR, fn, language, method, breakpoint_type, include_PKPD, ...) {
   guideline <- get_guideline(guideline, AMR::clinical_breakpoints)
   if (!is.null(mo) && !is.null(ab)) {
     # interpret and give colour based on MIC values
@@ -753,29 +770,35 @@ plot_colours_subtitle_guideline <- function(x, mo, ab, guideline, colours_SIR, f
     ab <- as.ab(ab)
     abname <- ab_name(ab, language = language)
     
-    sir <- suppressWarnings(suppressMessages(as.sir(fn(names(x)), mo = mo, ab = ab, guideline = guideline, include_screening = FALSE, include_PKPD = TRUE, ...)))
+    # store previous interpretations to backup
+    sir_history <- AMR_env$sir_interpretation_history
+    # and clear previous interpretations
+    AMR_env$sir_interpretation_history <- AMR_env$sir_interpretation_history[0, , drop = FALSE]
+
+    sir <- suppressWarnings(suppressMessages(as.sir(fn(names(x)), mo = mo, ab = ab, guideline = guideline, include_screening = FALSE, include_PKPD = include_PKPD, breakpoint_type = breakpoint_type, ...)))
     guideline_txt <- guideline
     if (all(is.na(sir))) {
-      sir_screening <- suppressWarnings(suppressMessages(as.sir(fn(names(x)), mo = mo, ab = ab, guideline = guideline, include_screening = TRUE, include_PKPD = TRUE, ...)))
+      sir_screening <- suppressWarnings(suppressMessages(as.sir(fn(names(x)), mo = mo, ab = ab, guideline = guideline, include_screening = TRUE, include_PKPD = include_PKPD, breakpoint_type = breakpoint_type, ...)))
       if (!all(is.na(sir_screening))) {
         message_(
-          "Only ", guideline, " ", type, " interpretations found for ",
+          "Only ", guideline, " ", method, " interpretations found for ",
           ab_name(ab, language = NULL, tolower = TRUE), " in ", italicise(moname), " for screening"
         )
         sir <- sir_screening
         guideline_txt <- paste0("(Screen, ", guideline_txt, ")")
       } else {
         message_(
-          "No ", guideline, " ", type, " interpretations found for ",
+          "No ", guideline, " ", method, " interpretations found for ",
           ab_name(ab, language = NULL, tolower = TRUE), " in ", italicise(moname)
         )
-        guideline_txt <- ""
+        guideline_txt <- paste0("(", guideline_txt, ")")
       }
     } else {
       if (isTRUE(list(...)$uti)) {
         guideline_txt <- paste("UTIs,", guideline_txt)
       }
-      guideline_txt <- paste0("(", guideline_txt, ")")
+      ref_tbl <- paste0('"', unique(AMR_env$sir_interpretation_history$ref_table), '"', collapse = "/")
+      guideline_txt <- paste0("(", guideline_txt, ": ", ref_tbl, ")")
     }
     cols <- character(length = length(sir))
     cols[is.na(sir)] <- "#BEBEBE"
@@ -787,5 +810,9 @@ plot_colours_subtitle_guideline <- function(x, mo, ab, guideline, colours_SIR, f
     cols <- "#BEBEBE"
     sub <- NULL
   }
+  
+  # restore previous interpretations to backup
+  AMR_env$sir_interpretation_history <- sir_history
+  
   list(cols = cols, count = as.double(x), sub = sub, guideline = guideline)
 }

R/sir.R

@@ -793,7 +793,7 @@ as_sir_method <- function(method_short,
     mo.bak <- mo
   }
   # be sure to take current taxonomy, as the 'clinical_breakpoints' data set only contains current taxonomy
-  mo <- suppressWarnings(suppressMessages(as.mo(mo, keep_synonyms = FALSE, inf0 = FALSE)))
+  mo <- suppressWarnings(suppressMessages(as.mo(mo, keep_synonyms = FALSE, info = FALSE)))
   guideline_coerced <- get_guideline(guideline, reference_data)
   if (is.na(ab)) {
     message_("Returning NAs for unknown antibiotic: '", font_bold(ab.bak),
@@ -846,6 +846,7 @@ as_sir_method <- function(method_short,
   message_(intro_txt, appendLF = FALSE, as_note = FALSE)
   
   msg_note <- function(messages) {
+    messages <- unique(messages)
     for (i in seq_len(length(messages))) {
       messages[i] <- word_wrap(extra_indent = 5, messages[i])
     }
@@ -879,7 +880,6 @@ as_sir_method <- function(method_short,
   rise_note <- FALSE
   method_coerced <- toupper(method)
   ab_coerced <- ab
-  mo_coerced <- mo
   
   if (identical(reference_data, AMR::clinical_breakpoints)) {
     breakpoints <- reference_data %pm>%
@@ -943,21 +943,23 @@ as_sir_method <- function(method_short,
     values <- df[rows, "values", drop = TRUE]
     new_sir <- rep(NA_sir_, length(rows))
 
-    # find different mo properties
+    # find different mo properties, as fast as possible
-    mo_current_genus <- as.mo(mo_genus(mo_current, language = NULL))
+    mo_current_genus <- AMR_env$MO_lookup$mo[match(AMR_env$MO_lookup$genus[match(mo_current, AMR_env$MO_lookup$mo)], AMR_env$MO_lookup$genus)]
-    mo_current_family <- as.mo(mo_family(mo_current, language = NULL))
+    mo_current_family <- AMR_env$MO_lookup$mo[match(AMR_env$MO_lookup$family[match(mo_current, AMR_env$MO_lookup$mo)], AMR_env$MO_lookup$family)]
-    mo_current_order <- as.mo(mo_order(mo_current, language = NULL))
+    mo_current_order <- AMR_env$MO_lookup$mo[match(AMR_env$MO_lookup$order[match(mo_current, AMR_env$MO_lookup$mo)], AMR_env$MO_lookup$order)]
-    mo_current_class <- as.mo(mo_class(mo_current, language = NULL))
+    mo_current_class <- AMR_env$MO_lookup$mo[match(AMR_env$MO_lookup$class[match(mo_current, AMR_env$MO_lookup$mo)], AMR_env$MO_lookup$class)]
+    mo_current_rank <- AMR_env$MO_lookup$rank[match(mo_current, AMR_env$MO_lookup$mo)]
+    mo_current_name <- AMR_env$MO_lookup$fullname[match(mo_current, AMR_env$MO_lookup$mo)]
     if (mo_current %in% AMR::microorganisms.groups$mo) {
       # get the species group
       mo_current_species_group <- AMR::microorganisms.groups$mo_group[match(mo_current, AMR::microorganisms.groups$mo)]
     } else {
       mo_current_species_group <- mo_current
     }
-    mo_current_other <- as.mo("UNKNOWN")
+    mo_current_other <- structure("UNKNOWN", class = c("mo", "character"))
     # formatted for notes
-    mo_formatted <- suppressMessages(suppressWarnings(mo_fullname(mo_current, language = NULL, keep_synonyms = FALSE)))
+    mo_formatted <- mo_current_name
-    if (!mo_rank(mo_current) %in% c("kingdom", "phylum", "class", "order")) {
+    if (!mo_current_rank %in% c("kingdom", "phylum", "class", "order")) {
       mo_formatted <- font_italic(mo_formatted)
     }
     ab_formatted <- paste0(
@@ -1106,8 +1108,7 @@ as_sir_method <- function(method_short,
 sir_interpretation_history <- function(clean = FALSE) {
   meet_criteria(clean, allow_class = "logical", has_length = 1)
 
-  out.bak <- AMR_env$sir_interpretation_history
+  out <- AMR_env$sir_interpretation_history
-  out <- out.bak
   if (NROW(out) == 0) {
     message_("No results to return. Run `as.sir()` on MIC values or disk diffusion zones first to see a 'logbook' data set here.")
     return(invisible(NULL))
@@ -1118,8 +1119,6 @@ sir_interpretation_history <- function(clean = FALSE) {
   # keep stored for next use
   if (isTRUE(clean)) {
     AMR_env$sir_interpretation_history <- AMR_env$sir_interpretation_history[0, , drop = FALSE]
-  } else {
-    AMR_env$sir_interpretation_history <- out.bak
   }
   
   # sort descending on time
@@ -1141,7 +1140,11 @@ pillar_shaft.sir <- function(x, ...) {
     out[is.na(x)] <- font_grey("  NA")
     out[x == "S"] <- font_green_bg("  S  ")
     out[x == "I"] <- font_orange_bg("  I  ")
+    if (is_dark()) {
       out[x == "R"] <- font_red_bg("  R  ")
+    } else {
+      out[x == "R"] <- font_rose_bg("  R  ")
+    }
   }
   create_pillar_column(out, align = "left", width = 5)
 }

R/zzz.R

@@ -73,6 +73,8 @@ AMR_env$sir_interpretation_history <- data.frame(
 AMR_env$custom_ab_codes <- character(0)
 AMR_env$custom_mo_codes <- character(0)
 AMR_env$is_dark_theme <- NULL
+AMR_env$chmatch <- import_fn("chmatch", "data.table", error_on_fail = FALSE)
+AMR_env$chin <- import_fn("%chin%", "data.table", error_on_fail = FALSE)
 
 # determine info icon for messages
 if (pkg_is_available("cli")) {

man/antibiotic_class_selectors.Rd

@@ -133,7 +133,7 @@ The \code{\link[=ab_selector]{ab_selector()}} function can be used to internally
 
 The \code{\link[=administrable_per_os]{administrable_per_os()}} and \code{\link[=administrable_iv]{administrable_iv()}} functions also rely on the \link{antibiotics} data set - antibiotic columns will be matched where a DDD (defined daily dose) for resp. oral and IV treatment is available in the \link{antibiotics} data set.
 
-The \code{\link[=not_intrinsic_resistant]{not_intrinsic_resistant()}} function can be used to only select antibiotic columns that pose no intrinsic resistance for the microorganisms in the data set. For example, if a data set contains only microorganism codes or names of \emph{E. coli} and \emph{K. pneumoniae} and contains a column "vancomycin", this column will be removed (or rather, unselected) using this function. It currently applies \href{https://www.eucast.org/expert_rules_and_expected_phenotypes/}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3} (2021) to determine intrinsic resistance, using the \code{\link[=eucast_rules]{eucast_rules()}} function internally. Because of this determination, this function is quite slow in terms of performance.
+The \code{\link[=not_intrinsic_resistant]{not_intrinsic_resistant()}} function can be used to only select antibiotic columns that pose no intrinsic resistance for the microorganisms in the data set. For example, if a data set contains only microorganism codes or names of \emph{E. coli} and \emph{K. pneumoniae} and contains a column "vancomycin", this column will be removed (or rather, unselected) using this function. It currently applies \href{https://www.eucast.org/expert_rules_and_expected_phenotypes}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3} (2021) to determine intrinsic resistance, using the \code{\link[=eucast_rules]{eucast_rules()}} function internally. Because of this determination, this function is quite slow in terms of performance.
 }
 \section{Full list of supported (antibiotic) classes}{
 

man/as.sir.Rd

@@ -94,7 +94,7 @@ sir_interpretation_history(clean = FALSE)
 
 \item{conserve_capped_values}{a \link{logical} to indicate that MIC values starting with \code{">"} (but not \code{">="}) must always return "R" , and that MIC values starting with \code{"<"} (but not \code{"<="}) must always return "S"}
 
-\item{add_intrinsic_resistance}{\emph{(only useful when using a EUCAST guideline)} a \link{logical} to indicate whether intrinsic antibiotic resistance must also be considered for applicable bug-drug combinations, meaning that e.g. ampicillin will always return "R" in \emph{Klebsiella} species. Determination is based on the \link{intrinsic_resistant} data set, that itself is based on \href{https://www.eucast.org/expert_rules_and_expected_phenotypes/}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3} (2021).}
+\item{add_intrinsic_resistance}{\emph{(only useful when using a EUCAST guideline)} a \link{logical} to indicate whether intrinsic antibiotic resistance must also be considered for applicable bug-drug combinations, meaning that e.g. ampicillin will always return "R" in \emph{Klebsiella} species. Determination is based on the \link{intrinsic_resistant} data set, that itself is based on \href{https://www.eucast.org/expert_rules_and_expected_phenotypes}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3} (2021).}
 
 \item{reference_data}{a \link{data.frame} to be used for interpretation, which defaults to the \link{clinical_breakpoints} data set. Changing this argument allows for using own interpretation guidelines. This argument must contain a data set that is equal in structure to the \link{clinical_breakpoints} data set (same column names and column types). Please note that the \code{guideline} argument will be ignored when \code{reference_data} is manually set.}
 

man/intrinsic_resistant.Rd

@@ -18,7 +18,7 @@ intrinsic_resistant
 Data set containing defined intrinsic resistance by EUCAST of all bug-drug combinations.
 }
 \details{
-This data set is based on \href{https://www.eucast.org/expert_rules_and_expected_phenotypes/}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3} (2021).
+This data set is based on \href{https://www.eucast.org/expert_rules_and_expected_phenotypes}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3} (2021).
 \subsection{Direct download}{
 
 Like all data sets in this package, this data set is publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit \href{https://msberends.github.io/AMR/articles/datasets.html}{our website for the download links}. The actual files are of course available on \href{https://github.com/msberends/AMR/tree/main/data-raw}{our GitHub repository}.

man/mo_property.Rd

@@ -327,7 +327,7 @@ Determination of the Gram stain (\code{\link[=mo_gramstain]{mo_gramstain()}}) wi
 
 Determination of yeasts (\code{\link[=mo_is_yeast]{mo_is_yeast()}}) will be based on the taxonomic kingdom and class. \emph{Budding yeasts} are fungi of the phylum Ascomycota, class Saccharomycetes (also called Hemiascomycetes). \emph{True yeasts} are aggregated into the underlying order Saccharomycetales. Thus, for all microorganisms that are member of the taxonomic class Saccharomycetes, the function will return \code{TRUE}. It returns \code{FALSE} otherwise (or \code{NA} when the input is \code{NA} or the MO code is \code{UNKNOWN}).
 
-Determination of intrinsic resistance (\code{\link[=mo_is_intrinsic_resistant]{mo_is_intrinsic_resistant()}}) will be based on the \link{intrinsic_resistant} data set, which is based on \href{https://www.eucast.org/expert_rules_and_expected_phenotypes/}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3} (2021). The \code{\link[=mo_is_intrinsic_resistant]{mo_is_intrinsic_resistant()}} function can be vectorised over both argument \code{x} (input for microorganisms) and \code{ab} (input for antibiotics).
+Determination of intrinsic resistance (\code{\link[=mo_is_intrinsic_resistant]{mo_is_intrinsic_resistant()}}) will be based on the \link{intrinsic_resistant} data set, which is based on \href{https://www.eucast.org/expert_rules_and_expected_phenotypes}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3} (2021). The \code{\link[=mo_is_intrinsic_resistant]{mo_is_intrinsic_resistant()}} function can be vectorised over both argument \code{x} (input for microorganisms) and \code{ab} (input for antibiotics).
 
 Determination of bacterial oxygen tolerance (\code{\link[=mo_oxygen_tolerance]{mo_oxygen_tolerance()}}) will be based on BacDive, see \emph{Source}. The function \code{\link[=mo_is_anaerobic]{mo_is_anaerobic()}} only returns \code{TRUE} if the oxygen tolerance is \code{"anaerobe"}, indicting an obligate anaerobic species or genus. It always returns \code{FALSE} for species outside the taxonomic kingdom of Bacteria.
 

man/plot.Rd

@@ -24,6 +24,8 @@
   colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
   language = get_AMR_locale(),
   expand = TRUE,
+  include_PKPD = getOption("AMR_include_PKPD", TRUE),
+  breakpoint_type = getOption("AMR_breakpoint_type", "human"),
   ...
 )
 
@@ -38,6 +40,8 @@
   colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
   language = get_AMR_locale(),
   expand = TRUE,
+  include_PKPD = getOption("AMR_include_PKPD", TRUE),
+  breakpoint_type = getOption("AMR_breakpoint_type", "human"),
   ...
 )
 
@@ -54,6 +58,8 @@
   colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
   language = get_AMR_locale(),
   expand = TRUE,
+  include_PKPD = getOption("AMR_include_PKPD", TRUE),
+  breakpoint_type = getOption("AMR_breakpoint_type", "human"),
   ...
 )
 
@@ -68,6 +74,8 @@
   colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
   language = get_AMR_locale(),
   expand = TRUE,
+  include_PKPD = getOption("AMR_include_PKPD", TRUE),
+  breakpoint_type = getOption("AMR_breakpoint_type", "human"),
   ...
 )
 
@@ -113,6 +121,10 @@
 
 \item{expand}{a \link{logical} to indicate whether the range on the x axis should be expanded between the lowest and highest value. For MIC values, intermediate values will be factors of 2 starting from the highest MIC value. For disk diameters, the whole diameter range will be filled.}
 
+\item{include_PKPD}{a \link{logical} to indicate that PK/PD clinical breakpoints must be applied as a last resort - the default is \code{TRUE}. Can also be set with the \link[=AMR-options]{package option} \code{\link[=AMR-options]{AMR_include_PKPD}}.}
+
+\item{breakpoint_type}{the type of breakpoints to use, either "ECOFF", "animal", or "human". ECOFF stands for Epidemiological Cut-Off values. The default is \code{"human"}, which can also be set with the \link[=AMR-options]{package option} \code{\link[=AMR-options]{AMR_breakpoint_type}}.}
+
 \item{...}{arguments passed on to methods}
 }
 \value{