mirror of https://github.com/msberends/AMR.git
244 lines
7.7 KiB
R
Executable File
244 lines
7.7 KiB
R
Executable File
# ==================================================================== #
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# TITLE #
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# Antimicrobial Resistance (AMR) Analysis #
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# #
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# SOURCE #
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# https://gitlab.com/msberends/AMR #
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# #
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# LICENCE #
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# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
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# #
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# This R package is free software; you can freely use and distribute #
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# it for both personal and commercial purposes under the terms of the #
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# GNU General Public License version 2.0 (GNU GPL-2), as published by #
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# the Free Software Foundation. #
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# #
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# This R package was created for academic research and was publicly #
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# released in the hope that it will be useful, but it comes WITHOUT #
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# ANY WARRANTY OR LIABILITY. #
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# Visit our website for more info: https://msberends.gitab.io/AMR. #
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# ==================================================================== #
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#' Class 'rsi'
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#'
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#' This transforms a vector to a new class \code{rsi}, which is an ordered factor with levels \code{S < I < R}. Invalid antimicrobial interpretations will be translated as \code{NA} with a warning.
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#' @rdname as.rsi
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#' @param x vector
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#' @param threshold maximum fraction of \code{x} that is allowed to fail transformation, see Examples
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#' @details The function \code{is.rsi.eligible} returns \code{TRUE} when a columns contains only valid antimicrobial interpretations (S and/or I and/or R), and \code{FALSE} otherwise.
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#' @return Ordered factor with new class \code{rsi}
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#' @keywords rsi
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#' @export
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#' @importFrom dplyr %>%
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#' @seealso \code{\link{as.mic}}
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#' @inheritSection AMR Read more on our website!
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#' @examples
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#' rsi_data <- as.rsi(c(rep("S", 474), rep("I", 36), rep("R", 370)))
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#' rsi_data <- as.rsi(c(rep("S", 474), rep("I", 36), rep("R", 370), "A", "B", "C"))
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#' is.rsi(rsi_data)
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#'
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#' # this can also coerce combined MIC/RSI values:
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#' as.rsi("<= 0.002; S") # will return S
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#'
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#' plot(rsi_data) # for percentages
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#' barplot(rsi_data) # for frequencies
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#' freq(rsi_data) # frequency table with informative header
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#'
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#' # using dplyr's mutate
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#' library(dplyr)
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#' septic_patients %>%
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#' mutate_at(vars(peni:rifa), as.rsi)
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#'
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#'
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#' # fastest way to transform all columns with already valid AB results to class `rsi`:
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#' septic_patients %>%
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#' mutate_if(is.rsi.eligible,
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#' as.rsi)
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#'
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#' # default threshold of `is.rsi.eligible` is 5%.
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#' is.rsi.eligible(WHONET$`First name`) # fails, >80% is invalid
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#' is.rsi.eligible(WHONET$`First name`, threhold = 0.9) # succeeds
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as.rsi <- function(x) {
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if (is.rsi(x)) {
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x
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} else if (identical(levels(x), c("S", "I", "R"))) {
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structure(x, class = c('rsi', 'ordered', 'factor'))
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} else {
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x <- x %>% unlist()
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x.bak <- x
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na_before <- x[is.na(x) | x == ''] %>% length()
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# remove all spaces
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x <- gsub(' +', '', x)
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# remove all MIC-like values: numbers, operators and periods
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x <- gsub('[0-9.,;:<=>]+', '', x)
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# disallow more than 3 characters
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x[nchar(x) > 3] <- NA
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# set to capitals
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x <- toupper(x)
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# remove all invalid characters
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x <- gsub('[^RSI]+', '', x)
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# in cases of "S;S" keep S, but in case of "S;I" make it NA
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x <- gsub('^S+$', 'S', x)
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x <- gsub('^I+$', 'I', x)
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x <- gsub('^R+$', 'R', x)
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x[!x %in% c('S', 'I', 'R')] <- NA
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na_after <- x[is.na(x) | x == ''] %>% length()
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if (na_before != na_after) {
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list_missing <- x.bak[is.na(x) & !is.na(x.bak) & x.bak != ''] %>%
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unique() %>%
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sort()
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list_missing <- paste0('"', list_missing , '"', collapse = ", ")
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warning(na_after - na_before, ' results truncated (',
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round(((na_after - na_before) / length(x)) * 100),
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'%) that were invalid antimicrobial interpretations: ',
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list_missing, call. = FALSE)
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}
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x <- factor(x, levels = c("S", "I", "R"), ordered = TRUE)
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class(x) <- c('rsi', 'ordered', 'factor')
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x
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}
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}
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#' @rdname as.rsi
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#' @export
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is.rsi <- function(x) {
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identical(class(x),
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c('rsi', 'ordered', 'factor'))
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}
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#' @rdname as.rsi
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#' @export
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is.rsi.eligible <- function(x, threshold = 0.05) {
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if (NCOL(x) > 1) {
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stop('`x` must be a one-dimensional vector.')
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}
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if (any(c("logical",
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"numeric",
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"integer",
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"mo",
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"Date",
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"POSIXct",
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"rsi",
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"raw",
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"hms")
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%in% class(x))) {
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# no transformation needed
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FALSE
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} else {
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x <- x[!is.na(x) & !is.null(x) & !identical(x, "")]
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if (length(x) == 0) {
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return(FALSE)
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}
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checked <- suppressWarnings(as.rsi(x))
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outcome <- sum(is.na(checked)) / length(x)
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outcome <= threshold
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}
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}
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#' @exportMethod print.rsi
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#' @export
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#' @importFrom dplyr %>%
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#' @noRd
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print.rsi <- function(x, ...) {
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cat("Class 'rsi'\n")
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print(as.character(x), quote = FALSE)
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}
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#' @exportMethod droplevels.rsi
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#' @export
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#' @noRd
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droplevels.rsi <- function(x, exclude = if(anyNA(levels(x))) NULL else NA, ...) {
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x <- droplevels.factor(x, exclude = exclude, ...)
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class(x) <- c('rsi', 'ordered', 'factor')
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x
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}
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#' @exportMethod summary.rsi
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#' @export
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#' @noRd
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summary.rsi <- function(object, ...) {
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x <- object
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c(
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"Class" = 'rsi',
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"<NA>" = sum(is.na(x)),
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"Sum S" = sum(x == "S", na.rm = TRUE),
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"Sum IR" = sum(x %in% c("I", "R"), na.rm = TRUE),
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"-Sum R" = sum(x == "R", na.rm = TRUE),
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"-Sum I" = sum(x == "I", na.rm = TRUE)
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)
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}
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#' @exportMethod plot.rsi
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#' @export
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#' @importFrom dplyr %>% group_by summarise filter mutate if_else n_distinct
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#' @importFrom graphics plot text
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#' @noRd
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plot.rsi <- function(x, ...) {
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x_name <- deparse(substitute(x))
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suppressWarnings(
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data <- data.frame(x = x,
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y = 1,
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stringsAsFactors = TRUE) %>%
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group_by(x) %>%
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summarise(n = sum(y)) %>%
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filter(!is.na(x)) %>%
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mutate(s = round((n / sum(n)) * 100, 1))
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)
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data$x <- factor(data$x, levels = c('S', 'I', 'R'), ordered = TRUE)
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ymax <- if_else(max(data$s) > 95, 105, 100)
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plot(x = data$x,
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y = data$s,
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lwd = 2,
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col = c('green', 'orange', 'red'),
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ylim = c(0, ymax),
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ylab = 'Percentage',
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xlab = 'Antimicrobial Interpretation',
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main = paste('Susceptibility Analysis of', x_name),
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axes = FALSE,
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...)
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# x axis
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axis(side = 1, at = 1:n_distinct(data$x), labels = levels(data$x), lwd = 0)
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# y axis, 0-100%
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axis(side = 2, at = seq(0, 100, 5))
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text(x = data$x,
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y = data$s + 4,
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labels = paste0(data$s, '% (n = ', data$n, ')'))
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}
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#' @exportMethod barplot.rsi
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#' @export
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#' @importFrom dplyr %>% group_by summarise filter mutate if_else n_distinct
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#' @importFrom graphics barplot axis
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#' @noRd
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barplot.rsi <- function(height, ...) {
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x <- height
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x_name <- deparse(substitute(height))
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suppressWarnings(
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data <- data.frame(rsi = x, cnt = 1) %>%
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group_by(rsi) %>%
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summarise(cnt = sum(cnt)) %>%
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droplevels()
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)
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barplot(table(x),
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col = c('green3', 'orange2', 'red3'),
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xlab = 'Antimicrobial Interpretation',
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main = paste('Susceptibility Analysis of', x_name),
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ylab = 'Frequency',
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axes = FALSE,
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...)
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# y axis, 0-100%
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axis(side = 2, at = seq(0, max(data$cnt) + max(data$cnt) * 1.1, by = 25))
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}
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