mirror of https://github.com/msberends/AMR.git
67 lines
3.4 KiB
R
67 lines
3.4 KiB
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/random.R
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\name{random}
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\alias{random}
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\alias{random_mic}
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\alias{random_disk}
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\alias{random_rsi}
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\title{Random MIC Values/Disk Zones/RSI Generation}
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\usage{
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random_mic(size = NULL, mo = NULL, ab = NULL, ...)
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random_disk(size = NULL, mo = NULL, ab = NULL, ...)
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random_rsi(size = NULL, prob_RSI = c(0.33, 0.33, 0.33), ...)
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}
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\arguments{
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\item{size}{desired size of the returned vector. If used in a \link{data.frame} call or \code{dplyr} verb, will get the current (group) size if left blank.}
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\item{mo}{any \link{character} that can be coerced to a valid microorganism code with \code{\link[=as.mo]{as.mo()}}}
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\item{ab}{any \link{character} that can be coerced to a valid antimicrobial agent code with \code{\link[=as.ab]{as.ab()}}}
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\item{...}{ignored, only in place to allow future extensions}
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\item{prob_RSI}{a vector of length 3: the probabilities for "R" (1st value), "S" (2nd value) and "I" (3rd value)}
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}
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\value{
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class \verb{<mic>} for \code{\link[=random_mic]{random_mic()}} (see \code{\link[=as.mic]{as.mic()}}) and class \verb{<disk>} for \code{\link[=random_disk]{random_disk()}} (see \code{\link[=as.disk]{as.disk()}})
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}
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\description{
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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.
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}
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\details{
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The base \R function \code{\link[=sample]{sample()}} is used for generating values.
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Generated values are based on the EUCAST 2022 guideline as implemented in the \link{rsi_translation} data set. To create specific generated values per bug or drug, set the \code{mo} and/or \code{ab} argument.
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}
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\section{Stable Lifecycle}{
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\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
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The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
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If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
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}
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\section{Read more on Our Website!}{
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On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
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}
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\examples{
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random_mic(100)
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random_disk(100)
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random_rsi(100)
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\donttest{
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# make the random generation more realistic by setting a bug and/or drug:
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random_mic(100, "Klebsiella pneumoniae") # range 0.0625-64
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random_mic(100, "Klebsiella pneumoniae", "meropenem") # range 0.0625-16
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random_mic(100, "Streptococcus pneumoniae", "meropenem") # range 0.0625-4
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random_disk(100, "Klebsiella pneumoniae") # range 8-50
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random_disk(100, "Klebsiella pneumoniae", "ampicillin") # range 11-17
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random_disk(100, "Streptococcus pneumoniae", "ampicillin") # range 12-27
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}
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}
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