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(v2.1.1.9241) fix sir

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dr. M.S. (Matthijs) Berends
2025-04-18 13:25:59 +02:00
parent cf91e677c6
commit 579025f678
9 changed files with 143 additions and 89 deletions
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14
data-raw/gpt_training_text_v2.1.1.9240.txt → data-raw/gpt_training_text_v2.1.1.9241.txt
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@@ -1,6 +1,6 @@
This knowledge base contains all context you must know about the AMR package for R. You are a GPT trained to be an assistant for the AMR package in R. You are an incredible R specialist, especially trained in this package and in the tidyverse.
First and foremost, you are trained on version 2.1.1.9240. Remember this whenever someone asks which AMR package version you’re at.
First and foremost, you are trained on version 2.1.1.9241. Remember this whenever someone asks which AMR package version you’re at.
Below are the contents of the NAMESPACE file, the index.md file, and all the man/*.Rd files (documentation) in the package. Every file content is split using 100 hypens.
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@@ -1723,10 +1723,9 @@ retrieve_wisca_parameters(wisca_model, ...)
\arguments{
\item{x}{A \link{data.frame} containing at least a column with microorganisms and columns with antimicrobial results (class 'sir', see \code{\link[=as.sir]{as.sir()}}).}
\item{antimicrobials}{A vector specifying the antimicrobials to include in the antibiogram (see \emph{Examples}). Will be evaluated using \code{\link[=guess_ab_col]{guess_ab_col()}}. This can be:
\item{antimicrobials}{A vector specifying the antimicrobials containing SIR values to include in the antibiogram (see \emph{Examples}). Will be evaluated using \code{\link[=guess_ab_col]{guess_ab_col()}}. This can be:
\itemize{
\item Any antimicrobial name or code that matches to a column name in \code{x}
\item A column name in \code{x} that contains SIR values
\item Any antimicrobial name or code that could match (see \code{\link[=guess_ab_col]{guess_ab_col()}}) to any column in \code{x}
\item Any \link[=antimicrobial_selectors]{antimicrobial selector}, such as \code{\link[=aminoglycosides]{aminoglycosides()}} or \code{\link[=carbapenems]{carbapenems()}}
\item A combination of the above, using \code{c()}, e.g.:
\itemize{
@@ -3461,7 +3460,7 @@ sir_interpretation_history(clean = FALSE)
\item{ab}{A vector (or column name) with \link{character}s that can be coerced to a valid antimicrobial drug code with \code{\link[=as.ab]{as.ab()}}.}
\item{guideline}{Defaults to EUCAST 2024 (the latest implemented EUCAST guideline in the \link{clinical_breakpoints} data set), but can be set with the package option \code{\link[=AMR-options]{AMR_guideline}}. Currently supports EUCAST (2011-2024) and CLSI (2011-2024), see \emph{Details}.}
\item{guideline}{A guideline name (or column name) to use for SIR interpretation. Defaults to EUCAST 2024 (the latest implemented EUCAST guideline in the \link{clinical_breakpoints} data set), but can be set with the package option \code{\link[=AMR-options]{AMR_guideline}}. Currently supports EUCAST (2011-2024) and CLSI (2011-2024), see \emph{Details}. Using a column name for \code{\link[=as.sir]{as.sir()}} allows for easy interpretation on historical data which needs to be interpreted according to e.g., various years.}
\item{uti}{(Urinary Tract Infection) a vector (or column name) with \link{logical}s (\code{TRUE} or \code{FALSE}) to specify whether a UTI specific interpretation from the guideline should be chosen. For using \code{\link[=as.sir]{as.sir()}} on a \link{data.frame}, this can also be a column containing \link{logical}s or when left blank, the data set will be searched for a column 'specimen', and rows within this column containing 'urin' (such as 'urine', 'urina') will be regarded isolates from a UTI. See \emph{Examples}.}
@@ -3646,7 +3645,8 @@ df_long <- data.frame(
bacteria = rep("Escherichia coli", 4),
antibiotic = c("amoxicillin", "cipro", "tobra", "genta"),
mics = as.mic(c(0.01, 1, 4, 8)),
disks = as.disk(c(6, 10, 14, 18))
disks = as.disk(c(6, 10, 14, 18)),
guideline = c("EUCAST 2021", "EUCAST 2022", "EUCAST 2023", "EUCAST 2024")
)
\donttest{
@@ -3665,7 +3665,7 @@ if (require("dplyr")) {
mutate_if(is.mic, as.sir,
mo = "bacteria",
ab = "antibiotic",
guideline = "CLSI"
guideline = guideline
)
df_long \%>\%
mutate(across(