1
0
mirror of https://github.com/msberends/AMR.git synced 2025-07-10 04:21:59 +02:00

(v2.1.1.9154) documentation fix

This commit is contained in:
2025-02-22 22:07:56 +01:00
parent abb5602532
commit 226d10f546
10 changed files with 34 additions and 368 deletions

View File

@ -81,20 +81,24 @@
#' some_sir_values <- random_sir(50, prob_SIR = c(0.55, 0.05, 0.30))
#'
#'
#' # Plotting using base R's plot() ---------------------------------------
#'
#' plot(some_mic_values)
#' plot(some_disk_values)
#' plot(some_sir_values)
#'
#' # when providing the microorganism and antibiotic, colours will show interpretations:
#' plot(some_mic_values, mo = "S. aureus", ab = "ampicillin")
#' plot(some_disk_values, mo = "Escherichia coli", ab = "cipro")
#' plot(some_disk_values, mo = "Escherichia coli", ab = "cipro", language = "nl")
#' \donttest{
#' # Plotting using ggplot2's autoplot() for MIC, disk, and SIR -----------
#' if (require("ggplot2")) {
#' autoplot(some_mic_values)
#' }
#' if (require("ggplot2")) {
#' # when providing the microorganism and antibiotic, colours will show interpretations:
#' autoplot(some_mic_values, mo = "Escherichia coli", ab = "cipro")
#' }
#' if (require("ggplot2")) {
#' # support for 20 languages, various guidelines, and many options
#' autoplot(some_disk_values, mo = "Escherichia coli", ab = "cipro",
#' guideline = "CLSI 2024", language = "no",
#' title = "Disk diffusion from the North")
#' }
#'
#'
#' # Plotting using scale_x_mic() -----------------------------------------
#' \donttest{
#' if (require("ggplot2")) {
#' mic_plot <- ggplot(data.frame(mics = as.mic(c(0.25, "<=4", 4, 8, 32, ">=32")),
#' counts = c(1, 1, 2, 2, 3, 3)),
@ -142,22 +146,10 @@
#' aes(group, mic)) +
#' geom_boxplot() +
#' geom_violin(linetype = 2, colour = "grey", fill = NA) +
#' scale_y_mic(mic_range = c(NA, 2))
#' scale_y_mic(mic_range = c(NA, 0.25))
#' }
#'
#'
#' # Plotting using scale_fill_mic() -----------------------------------------
#' some_counts <- as.integer(runif(20, 5, 50))
#'
#' if (require("ggplot2")) {
#' ggplot(data.frame(mic = some_mic_values,
#' group = some_groups,
#' counts = some_counts),
#' aes(group, counts, fill = mic)) +
#' geom_col() +
#' scale_fill_mic(mic_range = c(0.5, 16))
#' }
#'
#' # Plotting using scale_x_sir() -----------------------------------------
#' if (require("ggplot2")) {
#' ggplot(data.frame(x = c("I", "R", "S"),
@ -191,42 +183,22 @@
#' if (require("ggplot2")) {
#' plain +
#' scale_y_mic(mic_range = c(0.005, 32), name = "Our MICs!") +
#' scale_colour_sir(language = "nl", eucast_I = FALSE,
#' name = "In Dutch!")
#' scale_colour_sir(language = "pt",
#' name = "Support in 20 languages")
#' }
#'
#'
#' # Plotting using ggplot2's autoplot() ----------------------------------
#' if (require("ggplot2")) {
#' autoplot(some_mic_values)
#' }
#' if (require("ggplot2")) {
#' autoplot(some_disk_values, mo = "Escherichia coli", ab = "cipro")
#' }
#' if (require("ggplot2")) {
#' autoplot(some_sir_values)
#' }
#' # Plotting using base R's plot() ---------------------------------------
#'
#' plot(some_mic_values)
#' # when providing the microorganism and antibiotic, colours will show interpretations:
#' plot(some_mic_values, mo = "S. aureus", ab = "ampicillin")
#'
#' plot(some_disk_values)
#' plot(some_disk_values, mo = "Escherichia coli", ab = "cipro")
#' plot(some_disk_values, mo = "Escherichia coli", ab = "cipro", language = "nl")
#'
#' # Plotting using scale_y_percent() -------------------------------------
#' if (require("ggplot2")) {
#' p <- ggplot(data.frame(mics = as.mic(c(0.25, "<=4", 4, 8, 32, ">=32")),
#' counts = c(1, 1, 2, 2, 3, 3)),
#' aes(mics, counts / sum(counts))) +
#' geom_col()
#' print(p)
#'
#' p2 <- p +
#' scale_y_percent() +
#' theme_sir()
#' print(p2)
#'
#' p +
#' scale_y_percent(breaks = seq(from = 0, to = 1, by = 0.1),
#' limits = c(0, 1)) +
#' theme_sir()
#' }
#' }
#' plot(some_sir_values)
NULL
create_scale_mic <- function(aest, keep_operators, mic_range = NULL, ...) {
@ -243,12 +215,12 @@ create_scale_mic <- function(aest, keep_operators, mic_range = NULL, ...) {
scale$mic_limits_set <- limits_set
scale$transform <- function(x) {
as.double(rescale_mic(x = as.double(x), keep_operators = keep_operators, mic_range = mic_range, as.mic = TRUE))
as.double(rescale_mic(x = as.double(as.mic(x)), keep_operators = keep_operators, mic_range = mic_range, as.mic = TRUE))
}
scale$transform_df <- function(self, df) {
stop_if(all(is.na(df[[aest]])),
"`scale_", aest, "_mic()`: All MIC values are `NA`. Check your input data.", call = FALSE)
self$mic_values_rescaled <- rescale_mic(x = as.double(df[[aest]]), keep_operators = keep_operators, mic_range = mic_range, as.mic = TRUE)
self$mic_values_rescaled <- rescale_mic(x = as.double(as.mic(df[[aest]])), keep_operators = keep_operators, mic_range = mic_range, as.mic = TRUE)
# create new breaks and labels here
lims <- range(self$mic_values_rescaled, na.rm = TRUE)
# support inner and outer mic_range settings (e.g., data ranges 0.5-8 and mic_range is set to 0.025-64)