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# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis #
# #
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# SOURCE #
# https://gitlab.com/msberends/AMR #
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# #
# LICENCE #
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# (c) 2018-2020 Berends MS, Luz CF et al. #
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# #
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# This R package is free software; you can freely use and distribute #
# it for both personal and commercial purposes under the terms of the #
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
# the Free Software Foundation. #
# #
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# We created this package for both routine data analysis and academic #
# research and it was publicly released in the hope that it will be #
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
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# Visit our website for more info: https://msberends.gitlab.io/AMR. #
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# ==================================================================== #
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#' AMR plots with `ggplot2`
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#'
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#' Use these functions to create bar plots for antimicrobial resistance analysis. All functions rely on internal [ggplot2][ggplot2::ggplot()] functions.
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#' @inheritSection lifecycle Maturing lifecycle
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#' @param data a [`data.frame`] with column(s) of class [`rsi`] (see [as.rsi()])
#' @param position position adjustment of bars, either `"fill"`, `"stack"` or `"dodge"`
#' @param x variable to show on x axis, either `"antibiotic"` (default) or `"interpretation"` or a grouping variable
#' @param fill variable to categorise using the plots legend, either `"antibiotic"` (default) or `"interpretation"` or a grouping variable
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#' @param breaks numeric vector of positions
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#' @param limits numeric vector of length two providing limits of the scale, use `NA` to refer to the existing minimum or maximum
#' @param facet variable to split plots by, either `"interpretation"` (default) or `"antibiotic"` or a grouping variable
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#' @inheritParams proportion
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#' @param nrow (when using `facet`) number of rows
#' @param colours a named vector with colours for the bars. The names must be one or more of: S, SI, I, IR, R or be `FALSE` to use default [ggplot2][[ggplot2::ggplot()] colours.
#' @param datalabels show datalabels using [labels_rsi_count()]
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#' @param datalabels.size size of the datalabels
#' @param datalabels.colour colour of the datalabels
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#' @param title text to show as title of the plot
#' @param subtitle text to show as subtitle of the plot
#' @param caption text to show as caption of the plot
#' @param x.title text to show as x axis description
#' @param y.title text to show as y axis description
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#' @param ... other parameters passed on to [geom_rsi()]
#' @details At default, the names of antibiotics will be shown on the plots using [ab_name()]. This can be set with the `translate_ab` parameter. See [count_df()].
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#'
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#' ## The functions
#' [geom_rsi()] will take any variable from the data that has an [`rsi`] class (created with [as.rsi()]) using [rsi_df()] and will plot bars with the percentage R, I and S. The default behaviour is to have the bars stacked and to have the different antibiotics on the x axis.
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#'
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#' [facet_rsi()] creates 2d plots (at default based on S/I/R) using [ggplot2::facet_wrap()].
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#'
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#' [scale_y_percent()] transforms the y axis to a 0 to 100% range using [ggplot2::scale_continuous()].
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#'
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#' [scale_rsi_colours()] sets colours to the bars: pastel blue for S, pastel turquoise for I and pastel red for R, using [ggplot2::scale_brewer()].
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#'
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#' [theme_rsi()] is a [ggplot2 theme][[ggplot2::theme()] with minimal distraction.
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#'
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#' [labels_rsi_count()] print datalabels on the bars with percentage and amount of isolates using [ggplot2::geom_text()]
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#'
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#' [ggplot_rsi()] is a wrapper around all above functions that uses data as first input. This makes it possible to use this function after a pipe (`%>%`). See Examples.
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#' @rdname ggplot_rsi
#' @export
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#' @inheritSection AMR Read more on our website!
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#' @examples
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#' if (require("ggplot2") & require("dplyr")) {
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#'
#' # get antimicrobial results for drugs against a UTI:
#' ggplot(example_isolates %>% select(AMX, NIT, FOS, TMP, CIP)) +
#' geom_rsi()
#'
#' # prettify the plot using some additional functions:
#' df <- example_isolates %>% select(AMX, NIT, FOS, TMP, CIP)
#' ggplot(df) +
#' geom_rsi() +
#' scale_y_percent() +
#' scale_rsi_colours() +
#' labels_rsi_count() +
#' theme_rsi()
#'
#' # or better yet, simplify this using the wrapper function - a single command:
#' example_isolates %>%
#' select(AMX, NIT, FOS, TMP, CIP) %>%
#' ggplot_rsi()
#'
#' # get only proportions and no counts:
#' example_isolates %>%
#' select(AMX, NIT, FOS, TMP, CIP) %>%
#' ggplot_rsi(datalabels = FALSE)
#'
#' # add other ggplot2 parameters as you like:
#' example_isolates %>%
#' select(AMX, NIT, FOS, TMP, CIP) %>%
#' ggplot_rsi(width = 0.5,
#' colour = "black",
#' size = 1,
#' linetype = 2,
#' alpha = 0.25)
#'
#' example_isolates %>%
#' select(AMX) %>%
#' ggplot_rsi(colours = c(SI = "yellow"))
#'
#' }
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#'
#' \dontrun{
#'
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#' # resistance of ciprofloxacine per age group
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#' example_isolates %>%
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#' mutate(first_isolate = first_isolate(.)) %>%
#' filter(first_isolate == TRUE,
#' mo == as.mo("E. coli")) %>%
#' # `age_group` is also a function of this package:
#' group_by(age_group = age_groups(age)) %>%
#' select(age_group,
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#' CIP) %>%
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#' ggplot_rsi(x = "age_group")
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#'
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#' # for colourblind mode, use divergent colours from the viridis package:
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#' example_isolates %>%
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#' select(AMX, NIT, FOS, TMP, CIP) %>%
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#' ggplot_rsi() + scale_fill_viridis_d()
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#' # a shorter version which also adjusts data label colours:
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#' example_isolates %>%
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#' select(AMX, NIT, FOS, TMP, CIP) %>%
#' ggplot_rsi(colours = FALSE)
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#'
#'
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#' # it also supports groups (don't forget to use the group var on `x` or `facet`):
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#' example_isolates %>%
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#' select(hospital_id, AMX, NIT, FOS, TMP, CIP) %>%
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#' group_by(hospital_id) %>%
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#' ggplot_rsi(x = "hospital_id",
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#' facet = "antibiotic",
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#' nrow = 1,
#' title = "AMR of Anti-UTI Drugs Per Hospital",
#' x.title = "Hospital",
#' datalabels = FALSE)
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#' }
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ggplot_rsi <- function ( data ,
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position = NULL ,
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x = " antibiotic" ,
fill = " interpretation" ,
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# params = list(),
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facet = NULL ,
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breaks = seq ( 0 , 1 , 0.1 ) ,
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limits = NULL ,
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translate_ab = " name" ,
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combine_SI = TRUE ,
combine_IR = FALSE ,
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language = get_locale ( ) ,
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nrow = NULL ,
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colours = c ( S = " #61a8ff" ,
SI = " #61a8ff" ,
I = " #61f7ff" ,
IR = " #ff6961" ,
R = " #ff6961" ) ,
datalabels = TRUE ,
datalabels.size = 2.5 ,
datalabels.colour = " gray15" ,
title = NULL ,
subtitle = NULL ,
caption = NULL ,
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x.title = " Antimicrobial" ,
y.title = " Proportion" ,
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... ) {
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stop_ifnot_installed ( " ggplot2" )
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x <- x [1 ]
facet <- facet [1 ]
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# we work with aes_string later on
x_deparse <- deparse ( substitute ( x ) )
if ( x_deparse != " x" ) {
x <- x_deparse
}
if ( x %like% ' ".*"' ) {
x <- substr ( x , 2 , nchar ( x ) - 1 )
}
facet_deparse <- deparse ( substitute ( facet ) )
if ( facet_deparse != " facet" ) {
facet <- facet_deparse
}
if ( facet %like% ' ".*"' ) {
facet <- substr ( facet , 2 , nchar ( facet ) - 1 )
}
if ( facet %in% c ( " NULL" , " " ) ) {
facet <- NULL
}
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if ( is.null ( position ) ) {
position <- " fill"
}
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p <- ggplot2 :: ggplot ( data = data ) +
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geom_rsi ( position = position , x = x , fill = fill , translate_ab = translate_ab ,
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combine_SI = combine_SI , combine_IR = combine_IR , ... ) +
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theme_rsi ( )
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if ( fill == " interpretation" ) {
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# set RSI colours
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if ( isFALSE ( colours ) & missing ( datalabels.colour ) ) {
# set datalabel colour to middle gray
datalabels.colour <- " gray50"
}
p <- p + scale_rsi_colours ( colours = colours )
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}
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if ( identical ( position , " fill" ) ) {
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# proportions, so use y scale with percentage
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p <- p + scale_y_percent ( breaks = breaks , limits = limits )
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}
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if ( datalabels == TRUE ) {
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p <- p + labels_rsi_count ( position = position ,
x = x ,
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translate_ab = translate_ab ,
combine_SI = combine_SI ,
combine_IR = combine_IR ,
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datalabels.size = datalabels.size ,
datalabels.colour = datalabels.colour )
}
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if ( ! is.null ( facet ) ) {
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p <- p + facet_rsi ( facet = facet , nrow = nrow )
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}
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p <- p + ggplot2 :: labs ( title = title ,
subtitle = subtitle ,
caption = caption ,
x = x.title ,
y = y.title )
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p
}
#' @rdname ggplot_rsi
#' @export
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geom_rsi <- function ( position = NULL ,
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x = c ( " antibiotic" , " interpretation" ) ,
fill = " interpretation" ,
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translate_ab = " name" ,
language = get_locale ( ) ,
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combine_SI = TRUE ,
combine_IR = FALSE ,
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... ) {
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stop_ifnot_installed ( " ggplot2" )
stop_if ( is.data.frame ( position ) , " `position` is invalid. Did you accidentally use '%>%' instead of '+'?" )
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y <- " value"
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if ( missing ( position ) | is.null ( position ) ) {
position <- " fill"
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}
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if ( identical ( position , " fill" ) ) {
position <- ggplot2 :: position_fill ( vjust = 0.5 , reverse = TRUE )
}
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x <- x [1 ]
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# we work with aes_string later on
x_deparse <- deparse ( substitute ( x ) )
if ( x_deparse != " x" ) {
x <- x_deparse
}
if ( x %like% ' ".*"' ) {
x <- substr ( x , 2 , nchar ( x ) - 1 )
}
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if ( tolower ( x ) %in% tolower ( c ( " ab" , " abx" , " antibiotics" ) ) ) {
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x <- " antibiotic"
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} else if ( tolower ( x ) %in% tolower ( c ( " SIR" , " RSI" , " interpretations" , " result" ) ) ) {
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x <- " interpretation"
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}
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ggplot2 :: layer ( geom = " bar" , stat = " identity" , position = position ,
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mapping = ggplot2 :: aes_string ( x = x , y = y , fill = fill ) ,
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params = list ( ... ) , data = function ( x ) {
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rsi_df ( data = x ,
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translate_ab = translate_ab ,
language = language ,
combine_SI = combine_SI ,
combine_IR = combine_IR )
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} )
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}
#' @rdname ggplot_rsi
#' @export
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facet_rsi <- function ( facet = c ( " interpretation" , " antibiotic" ) , nrow = NULL ) {
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stop_ifnot_installed ( " ggplot2" )
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facet <- facet [1 ]
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# we work with aes_string later on
facet_deparse <- deparse ( substitute ( facet ) )
if ( facet_deparse != " facet" ) {
facet <- facet_deparse
}
if ( facet %like% ' ".*"' ) {
facet <- substr ( facet , 2 , nchar ( facet ) - 1 )
}
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if ( tolower ( facet ) %in% tolower ( c ( " SIR" , " RSI" , " interpretations" , " result" ) ) ) {
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facet <- " interpretation"
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} else if ( tolower ( facet ) %in% tolower ( c ( " ab" , " abx" , " antibiotics" ) ) ) {
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facet <- " antibiotic"
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}
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ggplot2 :: facet_wrap ( facets = facet , scales = " free_x" , nrow = nrow )
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}
#' @rdname ggplot_rsi
#' @export
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scale_y_percent <- function ( breaks = seq ( 0 , 1 , 0.1 ) , limits = NULL ) {
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stop_ifnot_installed ( " ggplot2" )
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if ( all ( breaks [breaks != 0 ] > 1 ) ) {
breaks <- breaks / 100
}
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ggplot2 :: scale_y_continuous ( breaks = breaks ,
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labels = percentage ( breaks ) ,
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limits = limits )
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}
#' @rdname ggplot_rsi
#' @export
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scale_rsi_colours <- function ( colours = c ( S = " #61a8ff" ,
SI = " #61a8ff" ,
I = " #61f7ff" ,
IR = " #ff6961" ,
R = " #ff6961" ) ) {
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stop_ifnot_installed ( " ggplot2" )
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# previous colour: palette = "RdYlGn"
# previous colours: values = c("#b22222", "#ae9c20", "#7cfc00")
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if ( ! identical ( colours , FALSE ) ) {
original_cols <- c ( S = " #61a8ff" ,
SI = " #61a8ff" ,
I = " #61f7ff" ,
IR = " #ff6961" ,
R = " #ff6961" )
colours <- replace ( original_cols , names ( colours ) , colours )
ggplot2 :: scale_fill_manual ( values = colours )
}
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}
#' @rdname ggplot_rsi
#' @export
theme_rsi <- function ( ) {
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stop_ifnot_installed ( " ggplot2" )
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ggplot2 :: theme_minimal ( base_size = 10 ) +
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ggplot2 :: theme ( panel.grid.major.x = ggplot2 :: element_blank ( ) ,
panel.grid.minor = ggplot2 :: element_blank ( ) ,
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panel.grid.major.y = ggplot2 :: element_line ( colour = " grey75" ) ,
# center title and subtitle
plot.title = ggplot2 :: element_text ( hjust = 0.5 ) ,
plot.subtitle = ggplot2 :: element_text ( hjust = 0.5 ) )
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}
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#' @rdname ggplot_rsi
#' @export
labels_rsi_count <- function ( position = NULL ,
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x = " antibiotic" ,
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translate_ab = " name" ,
combine_SI = TRUE ,
combine_IR = FALSE ,
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datalabels.size = 3 ,
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datalabels.colour = " gray15" ) {
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stop_ifnot_installed ( " ggplot2" )
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if ( is.null ( position ) ) {
position <- " fill"
}
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if ( identical ( position , " fill" ) ) {
position <- ggplot2 :: position_fill ( vjust = 0.5 , reverse = TRUE )
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}
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x_name <- x
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ggplot2 :: geom_text ( mapping = ggplot2 :: aes_string ( label = " lbl" ,
x = x ,
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y = " value" ) ,
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position = position ,
inherit.aes = FALSE ,
size = datalabels.size ,
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colour = datalabels.colour ,
lineheight = 0.75 ,
data = function ( x ) {
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transformed <- rsi_df ( data = x ,
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translate_ab = translate_ab ,
combine_SI = combine_SI ,
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combine_IR = combine_IR )
transformed $ gr <- transformed [ , x_name , drop = TRUE ]
transformed %>%
group_by ( gr ) %>%
mutate ( lbl = paste0 ( " n=" , isolates ) ) %>%
ungroup ( ) %>%
select ( - gr )
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} )
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}