styled, unit test fix

R/random.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -25,14 +25,14 @@
 
 #' Random MIC Values/Disk Zones/RSI Generation
 #'
-#' 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. 
+#' 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.
 #' @param size desired size of the returned vector. If used in a [data.frame] call or `dplyr` verb, will get the current (group) size if left blank.
 #' @param mo any [character] that can be coerced to a valid microorganism code with [as.mo()]
 #' @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.
-#' 
+#'
 #' Generated values are based on the EUCAST `r max(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "EUCAST")$guideline)))` guideline as 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()])
 #' @name random
@@ -42,15 +42,15 @@
 #' random_mic(25)
 #' random_disk(25)
 #' random_rsi(25)
-#' 
+#'
 #' \donttest{
 #' # make the random generation more realistic by setting a bug and/or drug:
-#' random_mic(25, "Klebsiella pneumoniae")                 # range 0.0625-64
-#' random_mic(25, "Klebsiella pneumoniae", "meropenem")    # range 0.0625-16
+#' random_mic(25, "Klebsiella pneumoniae") # range 0.0625-64
+#' random_mic(25, "Klebsiella pneumoniae", "meropenem") # range 0.0625-16
 #' random_mic(25, "Streptococcus pneumoniae", "meropenem") # range 0.0625-4
-#' 
-#' random_disk(25, "Klebsiella pneumoniae")                  # range 8-50
-#' random_disk(25, "Klebsiella pneumoniae", "ampicillin")    # range 11-17
+#'
+#' random_disk(25, "Klebsiella pneumoniae") # range 8-50
+#' random_disk(25, "Klebsiella pneumoniae", "ampicillin") # range 11-17
 #' random_disk(25, "Streptococcus pneumoniae", "ampicillin") # range 12-27
 #' }
 random_mic <- function(size = NULL, mo = NULL, ab = NULL, ...) {
@@ -92,14 +92,16 @@ random_exec <- function(type, size, mo = NULL, ab = NULL) {
     pm_filter(guideline %like% "EUCAST") %pm>%
     pm_arrange(pm_desc(guideline)) %pm>%
     subset(guideline == max(guideline) &
-              method == type)
-  
+      method == type)
+
   if (!is.null(mo)) {
     mo_coerced <- as.mo(mo)
-    mo_include <- c(mo_coerced,
-                    as.mo(mo_genus(mo_coerced)),
-                    as.mo(mo_family(mo_coerced)),
-                    as.mo(mo_order(mo_coerced)))
+    mo_include <- c(
+      mo_coerced,
+      as.mo(mo_genus(mo_coerced)),
+      as.mo(mo_family(mo_coerced)),
+      as.mo(mo_order(mo_coerced))
+    )
     df_new <- df %pm>%
       subset(mo %in% mo_include)
     if (nrow(df_new) > 0) {
@@ -108,7 +110,7 @@ random_exec <- function(type, size, mo = NULL, ab = NULL) {
       warning_("in `random_", tolower(type), "()`: no rows found that match mo '", mo, "', ignoring argument `mo`")
     }
   }
-  
+
   if (!is.null(ab)) {
     ab_coerced <- as.ab(ab)
     df_new <- df %pm>%
@@ -119,16 +121,20 @@ random_exec <- function(type, size, mo = NULL, ab = NULL) {
       warning_("in `random_", tolower(type), "()`: no rows found that match ab '", ab, "', ignoring argument `ab`")
     }
   }
- 
+
   if (type == "MIC") {
     # set range
     mic_range <- c(0.001, 0.002, 0.005, 0.010, 0.025, 0.0625, 0.125, 0.250, 0.5, 1, 2, 4, 8, 16, 32, 64, 128, 256)
 
     # get highest/lowest +/- random 1 to 3 higher factors of two
-    max_range <- mic_range[min(length(mic_range),
-                               which(mic_range == max(df$breakpoint_R)) + sample(c(1:3), 1))]
-    min_range <- mic_range[max(1,
-                               which(mic_range == min(df$breakpoint_S)) - sample(c(1:3), 1))]
+    max_range <- mic_range[min(
+      length(mic_range),
+      which(mic_range == max(df$breakpoint_R)) + sample(c(1:3), 1)
+    )]
+    min_range <- mic_range[max(
+      1,
+      which(mic_range == min(df$breakpoint_S)) - sample(c(1:3), 1)
+    )]
 
     mic_range_new <- mic_range[mic_range <= max_range & mic_range >= min_range]
     if (length(mic_range_new) == 0) {
@@ -144,9 +150,11 @@ random_exec <- function(type, size, mo = NULL, ab = NULL) {
     }
     return(out)
   } else if (type == "DISK") {
-    set_range <- seq(from = as.integer(min(df$breakpoint_R) / 1.25),
-                     to = as.integer(max(df$breakpoint_S) * 1.25),
-                     by = 1)
+    set_range <- seq(
+      from = as.integer(min(df$breakpoint_R) / 1.25),
+      to = as.integer(max(df$breakpoint_S) * 1.25),
+      by = 1
+    )
     out <- sample(set_range, size = size, replace = TRUE)
     out[out < 6] <- sample(c(6:10), length(out[out < 6]), replace = TRUE)
     out[out > 50] <- sample(c(40:50), length(out[out > 50]), replace = TRUE)