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Replace RSI with SIR

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This commit is contained in:
Dr. Matthijs Berends
2023-01-21 23:47:20 +01:00
committed by GitHub
parent 24b12024ce
commit 98e62c9af2
127 changed files with 1746 additions and 1648 deletions
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16
R/random.R
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@ -27,17 +27,17 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Random MIC Values/Disk Zones/RSI Generation
#' Random MIC Values/Disk Zones/SIR 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 drug, 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 drug 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 prob_SIR a vector of length 3: the probabilities for "S" (1st value), "I" (2nd value) and "R" (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")$guideline)))` guideline as implemented in the [rsi_translation] data set. To create specific generated values per bug or drug, set the `mo` and/or `ab` argument.
#' Generated values are based on the EUCAST `r max(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "EUCAST")$guideline)))` guideline as implemented in the [clinical_breakpoints] 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
#' @rdname random
@ -45,7 +45,7 @@
#' @examples
#' random_mic(25)
#' random_disk(25)
#' random_rsi(25)
#' random_sir(25)
#'
#' \donttest{
#' # make the random generation more realistic by setting a bug and/or drug:
@ -81,17 +81,17 @@ random_disk <- function(size = NULL, mo = NULL, ab = NULL, ...) {
#' @rdname random
#' @export
random_rsi <- function(size = NULL, prob_RSI = c(0.33, 0.33, 0.33), ...) {
random_sir <- function(size = NULL, prob_SIR = c(0.33, 0.33, 0.33), ...) {
meet_criteria(size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE, allow_NULL = TRUE)
meet_criteria(prob_RSI, allow_class = c("numeric", "integer"), has_length = 3)
meet_criteria(prob_SIR, allow_class = c("numeric", "integer"), has_length = 3)
if (is.null(size)) {
size <- NROW(get_current_data(arg_name = "size", call = -3))
}
sample(as.rsi(c("R", "S", "I")), size = size, replace = TRUE, prob = prob_RSI)
sample(as.sir(c("S", "I", "R")), size = size, replace = TRUE, prob = prob_SIR)
}
random_exec <- function(type, size, mo = NULL, ab = NULL) {
df <- rsi_translation %pm>%
df <- clinical_breakpoints %pm>%
pm_filter(guideline %like% "EUCAST") %pm>%
pm_arrange(pm_desc(guideline)) %pm>%
subset(guideline == max(guideline) &