count_all and some fixes

R/count.R

@@ -21,15 +21,15 @@
 #' @description These functions can be used to count resistant/susceptible microbial isolates. All functions support quasiquotation with pipes, can be used in \code{dplyr}s \code{\link[dplyr]{summarise}} and support grouped variables, see \emph{Examples}.
 #'
 #' \code{count_R} and \code{count_IR} can be used to count resistant isolates, \code{count_S} and \code{count_SI} can be used to count susceptible isolates.\cr
+#' @param ... one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with \code{\link{as.rsi}} if needed.
 #' @inheritParams portion
-#' @details \strong{Remember that you should filter your table to let it contain only first isolates!} Use \code{\link{first_isolate}} to determine them in your data set.
+#' @details These functions are meant to count isolates. Use the \code{\link{portion}_*} functions to calculate microbial resistance.
 #'
-#' These functions are meant to count isolates. Use the \code{\link{portion}_*} functions to calculate microbial resistance.
+#' \code{n_rsi} is an alias of \code{count_all}. They can be used to count all available isolates, i.e. where all input antibiotics have an available result (S, I or R). Their use is equal to \code{\link{n_distinct}}. Their function is equal to \code{count_S(...) + count_IR(...)}.
 #'
 #' \code{count_df} takes any variable from \code{data} that has an \code{"rsi"} class (created with \code{\link{as.rsi}}) and counts the amounts of R, I and S. The resulting \emph{tidy data} (see Source) \code{data.frame} will have three rows (S/I/R) and a column for each variable with class \code{"rsi"}.
 #' @source Wickham H. \strong{Tidy Data.} The Journal of Statistical Software, vol. 59, 2014. \url{http://vita.had.co.nz/papers/tidy-data.html}
-#' @seealso \code{\link{portion}_*} to calculate microbial resistance and susceptibility.\cr
-#' \code{\link{n_rsi}} to count all cases where antimicrobial results are available.
+#' @seealso \code{\link{portion}_*} to calculate microbial resistance and susceptibility.
 #' @keywords resistance susceptibility rsi antibiotics isolate isolates
 #' @return Integer
 #' @rdname count
@@ -47,6 +47,10 @@
 #' count_S(septic_patients$amox)
 #' count_SI(septic_patients$amox)
 #'
+#' # Count all available isolates
+#' count_all(septic_patients$amox)
+#' n_rsi(septic_patients$amox)
+#'
 #' # Since n_rsi counts available isolates, you can
 #' # calculate back to count e.g. non-susceptible isolates.
 #' # This results in the same:
@@ -56,24 +60,25 @@
 #' library(dplyr)
 #' septic_patients %>%
 #'   group_by(hospital_id) %>%
-#'   summarise(R = count_R(cipr),
-#'             I = count_I(cipr),
-#'             S = count_S(cipr),
-#'             n = n_rsi(cipr), # the actual total; sum of all three
-#'             total = n())     # NOT the amount of tested isolates!
+#'   summarise(R  = count_R(cipr),
+#'             I  = count_I(cipr),
+#'             S  = count_S(cipr),
+#'             n1 = count_all(cipr), # the actual total; sum of all three
+#'             n2 = n_rsi(cipr),     # same - analogous to n_distinct
+#'             total = n())          # NOT the amount of tested isolates!
 #'
 #' # Count co-resistance between amoxicillin/clav acid and gentamicin,
 #' # so we can see that combination therapy does a lot more than mono therapy.
 #' # Please mind that `portion_S` calculates percentages right away instead.
-#' count_S(septic_patients$amcl)   # S = 1056 (67.3%)
-#' n_rsi(septic_patients$amcl)     # n = 1570
+#' count_S(septic_patients$amcl)   # S = 1057 (67.1%)
+#' count_all(septic_patients$amcl) # n = 1576
 #'
-#' count_S(septic_patients$gent)   # S = 1363 (74.0%)
-#' n_rsi(septic_patients$gent)     # n = 1842
+#' count_S(septic_patients$gent)   # S = 1372 (74.0%)
+#' count_all(septic_patients$gent) # n = 1855
 #'
 #' with(septic_patients,
-#'      count_S(amcl, gent))       # S = 1385 (92.1%)
-#' with(septic_patients,           # n = 1504
+#'      count_S(amcl, gent))       # S = 1396 (92.0%)
+#' with(septic_patients,           # n = 1517
 #'      n_rsi(amcl, gent))
 #'
 #' # Get portions S/I/R immediately of all rsi columns
@@ -140,6 +145,20 @@ count_S <- function(...) {
            only_count = TRUE)
 }
 
+#' @rdname count
+#' @export
+count_all <- function(...) {
+  # only print warnings once, if needed
+  count_S(...) + suppressWarnings(count_IR(...))
+}
+
+#' @rdname count
+#' @export
+n_rsi <- function(...) {
+  # only print warnings once, if needed
+  count_S(...) + suppressWarnings(count_IR(...))
+}
+
 #' @rdname count
 #' @importFrom dplyr %>% select_if bind_rows summarise_if mutate group_vars select everything
 #' @export