new unit tests for ggplot, small fixes

R/classes.R

@@ -102,9 +102,14 @@ print.rsi <- function(x, ...) {
 #' @noRd
 summary.rsi <- function(object, ...) {
   x <- object
-  lst <- c('rsi', sum(is.na(x)), sum(x == "S"), sum(x %in% c("I", "R")), sum(x == "R"), sum(x == "I"))
-  names(lst) <- c("Mode", "<NA>", "Sum S", "Sum IR", "-Sum R", "-Sum I")
-  lst
+  c(
+    "Mode" = 'rsi',
+    "<NA>" = sum(is.na(x)),
+    "Sum S" = sum(x == "S", na.rm = TRUE),
+    "Sum IR" = sum(x %in% c("I", "R"), na.rm = TRUE),
+    "-Sum R" = sum(x == "R", na.rm = TRUE),
+    "-Sum I" = sum(x == "I", na.rm = TRUE)
+  )
 }
 
 #' @exportMethod plot.rsi

R/ggplot_rsi.R

@@ -18,7 +18,7 @@
 
 #' AMR bar plots with \code{ggplot}
 #'
-#' Use these functions to create bar plots for antimicrobial resistance analysis. All functions rely on internal \code{\link{ggplot}} functions.
+#' Use these functions to create bar plots for antimicrobial resistance analysis. All functions rely on internal \code{\link[ggplot2]{ggplot}} functions.
 #' @param data a \code{data.frame} with column(s) of class \code{"rsi"} (see \code{\link{as.rsi}})
 #' @param position position adjustment of bars, either \code{"stack"} (default) or \code{"dodge"}
 #' @param x parameter to show on x axis, either \code{"Antibiotic"} (default) or \code{"Interpretation"}
@@ -28,13 +28,13 @@
 #' \strong{The functions}\cr
 #' \code{geom_rsi} will take any variable from the data that has an \code{rsi} class (created with \code{\link{as.rsi}}) using \code{\link{portion_df}} and will plot bars with the percentage R, I and S. The default behaviour is to have the bars stacked and to have the different antibiotics on the x axis.
 #'
-#' \code{facet_rsi} creates 2d plots (at default based on S/I/R) using \code{\link{facet_wrap}}.
+#' \code{facet_rsi} creates 2d plots (at default based on S/I/R) using \code{\link[ggplot2]{facet_wrap}}.
 #'
 #' \code{scale_y_percent} transforms the y axis to a 0 to 100% range.
 #'
 #' \code{scale_rsi_colours} sets colours to the bars: green for S, yellow for I and red for R.
 #'
-#' \code{theme_rsi} is a \code{\link{theme}} with minimal distraction.
+#' \code{theme_rsi} is a \code{\link[ggplot2]{theme}} with minimal distraction.
 #'
 #' \code{ggplot_rsi} is a wrapper around all above functions that uses data as first input. This makes it possible to use this function after a pipe (\code{\%>\%}). See Examples.
 #' @rdname ggplot_rsi
@@ -67,6 +67,11 @@
 ggplot_rsi <- function(data,
                        x = "Antibiotic",
                        facet = NULL) {
+
+  if (!"ggplot2" %in% rownames(installed.packages())) {
+    stop('this function requires the ggplot2 package.', call. = FALSE)
+  }
+
   p <- ggplot2::ggplot(data = data) +
     geom_rsi(x = x) +
     scale_y_percent() +

R/n_rsi.R

@@ -35,7 +35,7 @@
 #'             combination_n = n_rsi(cipr, gent))
 n_rsi <- function(ab1, ab2 = NULL) {
   if (NCOL(ab1) > 1) {
-    stop('`ab` must be a vector of antimicrobial interpretations', call. = FALSE)
+    stop('`ab1` must be a vector of antimicrobial interpretations', call. = FALSE)
   }
   if (!is.rsi(ab1)) {
     ab1 <- as.rsi(ab1)

R/portion.R

@@ -176,6 +176,32 @@ portion_S <- function(ab1,
            as_percent = as_percent)
 }
 
+#' @rdname portion
+#' @importFrom dplyr bind_cols summarise_if mutate
+#' @export
+portion_df <- function(data, translate = getOption("get_antibiotic_names", TRUE)) {
+  resS <- bind_cols(data.frame(Interpretation = "S", stringsAsFactors = FALSE),
+                    summarise_if(.tbl = data,
+                                 .predicate = is.rsi,
+                                 .funs = portion_S))
+  resI <- bind_cols(data.frame(Interpretation = "I", stringsAsFactors = FALSE),
+                    summarise_if(.tbl = data,
+                                 .predicate = is.rsi,
+                                 .funs = portion_I))
+  resR <- bind_cols(data.frame(Interpretation = "R", stringsAsFactors = FALSE),
+                    summarise_if(.tbl = data,
+                                 .predicate = is.rsi,
+                                 .funs = portion_R))
+
+  res <- bind_rows(resS, resI, resR) %>%
+    mutate(Interpretation = factor(Interpretation, levels = c("R", "I", "S"), ordered = TRUE)) %>%
+    tidyr::gather(Antibiotic, Percentage, -Interpretation)
+  if (translate == TRUE) {
+    res <- res %>% mutate(Antibiotic = abname(Antibiotic, from = "guess", to = "official"))
+  }
+  res
+}
+
 rsi_calc <- function(type,
                      ab1,
                      ab2,
@@ -244,29 +270,3 @@ rsi_calc <- function(type,
     found / total
   }
 }
-
-#' @rdname portion
-#' @importFrom dplyr bind_cols summarise_if mutate
-#' @export
-portion_df <- function(data, translate = getOption("get_antibiotic_names", TRUE)) {
-  resS <- bind_cols(data.frame(Interpretation = "S", stringsAsFactors = FALSE),
-                    summarise_if(.tbl = data,
-                                 .predicate = is.rsi,
-                                 .funs = portion_S))
-  resI <- bind_cols(data.frame(Interpretation = "I", stringsAsFactors = FALSE),
-                    summarise_if(.tbl = data,
-                                 .predicate = is.rsi,
-                                 .funs = portion_I))
-  resR <- bind_cols(data.frame(Interpretation = "R", stringsAsFactors = FALSE),
-                    summarise_if(.tbl = data,
-                                 .predicate = is.rsi,
-                                 .funs = portion_R))
-
-  res <- bind_rows(resS, resI, resR) %>%
-    mutate(Interpretation = factor(Interpretation, levels = c("R", "I", "S"), ordered = TRUE)) %>%
-    tidyr::gather(Antibiotic, Percentage, -Interpretation)
-  if (translate == TRUE) {
-    res <- res %>% mutate(Antibiotic = abname(Antibiotic, from = "guess", to = "official"))
-  }
-  res
-}