(v1.6.0.9063) prepare new release

R/ab.R

@@ -82,7 +82,7 @@
 #' # they use as.ab() internally:
 #' ab_name("J01FA01")    # "Erythromycin"
 #' ab_name("eryt")       # "Erythromycin"
-#' 
+#' \donttest{
 #' if (require("dplyr")) {
 #' 
 #'   # you can quickly rename <rsi> columns using dplyr >= 1.0.0:
@@ -90,6 +90,7 @@
 #'     rename_with(as.ab, where(is.rsi))
 #'    
 #' }
+#' }
 as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
   meet_criteria(x, allow_class = c("character", "numeric", "integer", "factor"), allow_NA = TRUE)
   meet_criteria(flag_multiple_results, allow_class = "logical", has_length = 1)

R/ab_class_selectors.R

@@ -70,7 +70,7 @@
 #' 
 #' 
 #' # dplyr -------------------------------------------------------------------
-#' 
+#' \donttest{
 #' if (require("dplyr")) {
 #' 
 #'   # this will select columns 'IPM' (imipenem) and 'MEM' (meropenem):
@@ -119,6 +119,7 @@
 #'   example_isolates %>% filter(carbapenems() == "R")
 #'   example_isolates %>% filter(across(carbapenems(), ~.x == "R"))
 #' }
+#' }
 ab_class <- function(ab_class, 
                      only_rsi_columns = FALSE) {
   ab_selector(ab_class, function_name = "ab_class", only_rsi_columns = only_rsi_columns)

R/age.R

@@ -88,13 +88,13 @@ age <- function(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...) {
     # add decimal parts of year
     mod <- n_days_x_rest / n_days_reference_year
     # negative mods are cases where `x_in_reference_year` > `reference` - so 'add' a year
-    mod[mod < 0] <- mod[mod < 0] + 1
+    mod[!is.na(mod) & mod < 0] <- mod[!is.na(mod) & mod < 0] + 1
     # and finally add to ages
     ages <- ages + mod
   }
   
   if (any(ages < 0, na.rm = TRUE)) {
-    ages[ages < 0] <- NA
+    ages[!is.na(ages) & ages < 0] <- NA
     warning_("NAs introduced for ages below 0.", call = TRUE)
   }
   if (any(ages > 120, na.rm = TRUE)) {

R/atc_online.R

@@ -64,7 +64,7 @@
 #' @inheritSection AMR Read more on Our Website!
 #' @source <https://www.whocc.no/atc_ddd_alterations__cumulative/ddd_alterations/abbrevations/>
 #' @examples
-#' \donttest{
+#' \dontrun{
 #' # oral DDD (Defined Daily Dose) of amoxicillin
 #' atc_online_property("J01CA04", "DDD", "O")
 #' 

R/availability.R

@@ -35,13 +35,14 @@
 #' @export
 #' @examples
 #' availability(example_isolates)
-#'
+#' \donttest{
 #' if (require("dplyr")) {
 #'   example_isolates %>%
 #'     filter(mo == as.mo("E. coli")) %>%
 #'     select_if(is.rsi) %>%
 #'     availability()
 #' }
+#' }
 availability <- function(tbl, width = NULL) {
   meet_criteria(tbl, allow_class = "data.frame")
   meet_criteria(width, allow_class = c("numeric", "integer"), has_length = 1, allow_NULL = TRUE, is_positive = TRUE, is_finite = TRUE)

R/count.R

@@ -72,7 +72,7 @@
 #' count_susceptible(example_isolates$AMX)
 #' susceptibility(example_isolates$AMX) * n_rsi(example_isolates$AMX)
 #'
-#' 
+#' \donttest{
 #' if (require("dplyr")) {
 #'   example_isolates %>%
 #'     group_by(hospital_id) %>%
@@ -106,6 +106,7 @@
 #'     group_by(hospital_id) %>%
 #'     count_df(translate = FALSE)
 #' }
+#' }
 count_resistant <- function(..., only_all_tested = FALSE) {
   rsi_calc(...,
            ab_result = "R",

R/data.R

@@ -269,12 +269,14 @@
 #' @inheritSection AMR Reference Data Publicly Available
 #' @inheritSection AMR Read more on Our Website!
 #' @examples
+#' \donttest{
 #' if (require("dplyr")) {
 #'   intrinsic_resistant %>%
 #'     filter(antibiotic == "Vancomycin", microorganism %like% "Enterococcus") %>% 
 #'     pull(microorganism)
 #'   # [1] "Enterococcus casseliflavus" "Enterococcus gallinarum"
 #' }
+#' }
 "intrinsic_resistant"
 
 #' Data Set with Treatment Dosages as Defined by EUCAST

R/ggplot_pca.R

@@ -65,6 +65,7 @@
 #' # See ?example_isolates.
 #'
 #' # See ?pca for more info about Principal Component Analysis (PCA).
+#' \donttest{
 #' if (require("dplyr")) {
 #'   pca_model <- example_isolates %>% 
 #'     filter(mo_genus(mo) == "Staphylococcus") %>% 
@@ -84,6 +85,7 @@
 #'       labs(title = "Title here")
 #'   }
 #' }
+#' }
 ggplot_pca <- function(x,
                        choices = 1:2,
                        scale = 1,

R/ggplot_rsi.R

@@ -67,6 +67,7 @@
 #' @export
 #' @inheritSection AMR Read more on Our Website!
 #' @examples
+#' \donttest{
 #' if (require("ggplot2") & require("dplyr")) {
 #'  
 #'   # get antimicrobial results for drugs against a UTI:
@@ -116,7 +117,6 @@
 #'     scale_rsi_colours(Value4 = "S", Value5 = "I", Value6 = "R")
 #' }
 #'   
-#' \donttest{
 #' # resistance of ciprofloxacine per age group
 #' example_isolates %>%
 #'   mutate(first_isolate = first_isolate(.)) %>%

R/italicise_taxonomy.R

@@ -45,12 +45,13 @@
 #' 
 #' # since ggplot2 supports no markdown (yet), use
 #' # italicise_taxonomy() and the `ggtext` pkg for titles:
-#' 
+#' \donttest{
 #' if (require("ggplot2") && require("ggtext")) {
 #'   ggplot(example_isolates$AMC,
 #'          title = italicise_taxonomy("Amoxi/clav in E. coli")) +
 #'     theme(plot.title = ggtext::element_markdown())
 #' }
+#' }
 italicise_taxonomy <- function(string, type = c("markdown", "ansi")) {
   if (missing(type)) {
     type <- "markdown"

R/mo_property.R

@@ -152,6 +152,7 @@
 #' mo_is_yeast(c("Candida", "E. coli"))      # TRUE, FALSE
 #' 
 #' # gram stains and intrinsic resistance can also be used as a filter in dplyr verbs
+#' \donttest{
 #' if (require("dplyr")) {
 #'   example_isolates %>%
 #'     filter(mo_is_gram_positive())
@@ -167,6 +168,7 @@
 #' #   SNOMED codes, and URL to the online database
 #' mo_info("E. coli")
 #' }
+#' }
 mo_name <- function(x, language = get_locale(), ...) {
   if (missing(x)) {
     # this tries to find the data and an <mo> column

R/pca.R

@@ -42,7 +42,6 @@
 #' # See ?example_isolates.
 #'
 #' \donttest{
-#' 
 #' if (require("dplyr")) {
 #'   # calculate the resistance per group first 
 #'   resistance_data <- example_isolates %>% 

R/plot.R

@@ -61,11 +61,13 @@
 #' plot(some_mic_values, mo = "S. aureus", ab = "ampicillin")
 #' plot(some_disk_values, mo = "Escherichia coli", ab = "cipro")
 #' 
+#' \donttest{
 #' if (require("ggplot2")) {
 #'   ggplot(some_mic_values)
 #'   ggplot(some_disk_values, mo = "Escherichia coli", ab = "cipro")
 #'   ggplot(some_rsi_values)
 #' }
+#' }
 NULL
 
 #' @method plot mic

R/proportion.R

@@ -103,6 +103,7 @@
 #' proportion_IR(example_isolates$AMX)
 #' proportion_R(example_isolates$AMX)
 #'
+#' \donttest{
 #' if (require("dplyr")) {
 #'   example_isolates %>%
 #'     group_by(hospital_id) %>%
@@ -161,6 +162,7 @@
 #'     group_by(hospital_id) %>%
 #'     proportion_df(translate = FALSE)
 #' }
+#' }
 resistance <- function(...,
                        minimum = 30,
                        as_percent = FALSE,

R/resistance_predict.R

@@ -70,6 +70,7 @@
 #'                         year_min = 2010,
 #'                         model = "binomial")
 #' plot(x)
+#' \donttest{
 #' if (require("ggplot2")) {
 #'   ggplot_rsi_predict(x)
 #' }
@@ -114,6 +115,7 @@
 #'          x = "Year") +
 #'     theme_minimal(base_size = 13)
 #' }
+#' }
 resistance_predict <- function(x,
                                col_ab,
                                col_date = NULL,

R/rsi.R

@@ -101,12 +101,12 @@
 #' @inheritSection AMR Read more on Our Website!
 #' @examples
 #' summary(example_isolates) # see all R/SI results at a glance
-#' 
+#' \donttest{
 #' if (require("skimr")) {
 #'   # class <rsi> supported in skim() too:
 #'   skim(example_isolates)
 #' }
-#' 
+#' }
 #' # For INTERPRETING disk diffusion and MIC values -----------------------
 #'        
 #' # a whole data set, even with combined MIC values and disk zones