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# ==================================================================== #
# TITLE: #
# AMR: An R Package for Working with Antimicrobial Resistance Data #
# #
# SOURCE CODE: #
# https://github.com/msberends/AMR #
# #
# PLEASE CITE THIS SOFTWARE AS: #
# Berends MS, Luz CF, Friedrich AW, et al. (2022). #
# AMR: An R Package for Working with Antimicrobial Resistance Data. #
# Journal of Statistical Software, 104(3), 1-31. #
# https://doi.org/10.18637/jss.v104.i03 #
# #
# Developed at the University of Groningen and the University Medical #
# Center Groningen in The Netherlands, in collaboration with many #
# colleagues from around the world, see our website. #
# #
# 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. #
# 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. #
# #
# Visit our website for the full manual and a complete tutorial about #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Plotting for Classes `sir`, `mic` and `disk`
#'
#' @description
#' Functions to plot classes `sir`, `mic` and `disk`, with support for base \R and `ggplot2`.
#'
#' Especially the `scale_*_mic()` functions are relevant wrappers to plot MIC values for `ggplot2`. They allows custom MIC ranges and to plot intermediate log2 levels for missing MIC values.
#' @param x,object values created with [as.mic()], [as.disk()] or [as.sir()] (or their `random_*` variants, such as [random_mic()])
#' @param mo any (vector of) text that can be coerced to a valid microorganism code with [as.mo()]
#' @param ab any (vector of) text that can be coerced to a valid antimicrobial drug code with [as.ab()]
#' @param guideline interpretation guideline to use - the default is the latest included EUCAST guideline, see *Details*
#' @param main,title title of the plot
#' @param xlab,ylab axis title
#' @param colours_SIR colours to use for filling in the bars, must be a vector of three values (in the order S, I and R). The default colours are colour-blind friendly.
#' @param language language to be used to translate 'Susceptible', 'Increased exposure'/'Intermediate' and 'Resistant' - the default is system language (see [get_AMR_locale()]) and can be overwritten by setting the package option [`AMR_locale`][AMR-options], e.g. `options(AMR_locale = "de")`, see [translate]. Use `language = NULL` or `language = ""` to prevent translation.
#' @param expand a [logical] to indicate whether the range on the x axis should be expanded between the lowest and highest value. For MIC values, intermediate values will be factors of 2 starting from the highest MIC value. For disk diameters, the whole diameter range will be filled.
#' @inheritParams as.sir
#' @details
#' The interpretation of "I" will be named "Increased exposure" for all EUCAST guidelines since 2019, and will be named "Intermediate" in all other cases.
#'
#' For interpreting MIC values as well as disk diffusion diameters, supported guidelines to be used as input for the `guideline` argument are: `r vector_and(AMR::clinical_breakpoints$guideline, quotes = TRUE, reverse = TRUE)`.
#'
#' Simply using `"CLSI"` or `"EUCAST"` as input will automatically select the latest version of that guideline.
#' @name plot
#' @rdname plot
#' @return The `autoplot()` functions return a [`ggplot`][ggplot2::ggplot()] model that is extendible with any `ggplot2` function.
#'
#' The `fortify()` functions return a [data.frame] as an extension for usage in the [ggplot2::ggplot()] function.
#' @param ... arguments passed on to methods
#' @examples
#' some_mic_values <- random_mic(size = 100)
#' some_disk_values <- random_disk(size = 100, mo = "Escherichia coli", ab = "cipro")
#' some_sir_values <- random_sir(50, prob_SIR = c(0.55, 0.05, 0.30))
#'
#' plot(some_mic_values)
#' plot(some_disk_values)
#' plot(some_sir_values)
#'
#' # when providing the microorganism and antibiotic, colours will show interpretations:
#' plot(some_mic_values, mo = "S. aureus", ab = "ampicillin")
#' plot(some_disk_values, mo = "Escherichia coli", ab = "cipro")
#' plot(some_disk_values, mo = "Escherichia coli", ab = "cipro", language = "nl")
#'
#'
#' # Plotting using scale_x_mic()
#' \donttest{
#' if (require("ggplot2")) {
#' mic_plot <- ggplot(data.frame(mics = as.mic(c(0.25, "<=4", 4, 8, 32, ">=32")),
#' counts = c(1, 1, 2, 2, 3, 3)),
#' aes(mics, counts)) +
#' geom_col()
#' mic_plot +
#' labs(title = "without scale_x_mic()")
#' }
#' if (require("ggplot2")) {
#' mic_plot +
#' scale_x_mic() +
#' labs(title = "with scale_x_mic()")
#' }
#' if (require("ggplot2")) {
#' mic_plot +
#' scale_x_mic(keep_operators = "all") +
#' labs(title = "with scale_x_mic() keeping all operators")
#' }
#' if (require("ggplot2")) {
#' mic_plot +
#' scale_x_mic(mic_range = c(1, 16)) +
#' labs(title = "with scale_x_mic() using a manual 'within' range")
#' }
#' if (require("ggplot2")) {
#' mic_plot +
#' scale_x_mic(mic_range = c(0.032, 256)) +
#' labs(title = "with scale_x_mic() using a manual 'outside' range")
#' }
#'
#' if (require("ggplot2")) {
#' autoplot(some_mic_values)
#' }
#' if (require("ggplot2")) {
#' autoplot(some_disk_values, mo = "Escherichia coli", ab = "cipro")
#' }
#' if (require("ggplot2")) {
#' autoplot(some_sir_values)
#' }
#' }
NULL
#' @export
#' @inheritParams as.mic
#' @param drop a [logical] to remove intermediate MIC values, defaults to `FALSE`
#' @rdname plot
scale_x_mic <- function(keep_operators = "edges", mic_range = NULL, drop = FALSE, ...) {
stop_ifnot_installed("ggplot2")
meet_criteria(drop, allow_class = "logical", has_length = 1)
scale <- ggplot2::scale_x_discrete(drop = drop, ...)
scale$transform <- function(x, keep_ops = keep_operators, mic_rng = mic_range) {
rescale_mic(x = x, keep_operators = keep_ops, mic_range = mic_rng, as.mic = FALSE)
}
scale
}
#' @export
#' @inheritParams as.mic
#' @rdname plot
scale_y_mic <- function(keep_operators = "edges", mic_range = NULL, drop = FALSE, ...) {
stop_ifnot_installed("ggplot2")
meet_criteria(drop, allow_class = "logical", has_length = 1)
scale <- ggplot2::scale_y_discrete(drop = drop, ...)
scale$transform <- function(x, keep_ops = keep_operators, mic_rng = mic_range) {
rescale_mic(x = x, keep_operators = keep_ops, mic_range = mic_rng, as.mic = FALSE)
}
scale
}
#' @export
#' @inheritParams as.mic
#' @rdname plot
scale_colour_mic <- function(keep_operators = "edges", mic_range = NULL, drop = FALSE, ...) {
stop_ifnot_installed("ggplot2")
meet_criteria(drop, allow_class = "logical", has_length = 1)
scale <- ggplot2::scale_colour_discrete(drop = drop, ...)
scale$transform <- function(x, keep_ops = keep_operators, mic_rng = mic_range) {
rescale_mic(x = x, keep_operators = keep_ops, mic_range = mic_rng, as.mic = FALSE)
}
scale
}
#' @export
#' @inheritParams as.mic
#' @rdname plot
scale_fill_mic <- function(keep_operators = "edges", mic_range = NULL, drop = FALSE, ...) {
stop_ifnot_installed("ggplot2")
meet_criteria(drop, allow_class = "logical", has_length = 1)
scale <- ggplot2::scale_fill_discrete(drop = drop, ...)
scale$transform <- function(x, keep_ops = keep_operators, mic_rng = mic_range) {
rescale_mic(x = x, keep_operators = keep_ops, mic_range = mic_rng, as.mic = FALSE)
}
scale
}
#' @method plot mic
#' @importFrom graphics barplot axis mtext legend
#' @export
#' @rdname plot
plot.mic <- function(x,
mo = NULL,
ab = NULL,
guideline = "EUCAST",
main = deparse(substitute(x)),
ylab = translate_AMR("Frequency", language = language),
xlab = translate_AMR("Minimum Inhibitory Concentration (mg/L)", language = language),
colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
language = get_AMR_locale(),
expand = TRUE,
include_PKPD = getOption("AMR_include_PKPD", TRUE),
breakpoint_type = getOption("AMR_breakpoint_type", "human"),
...) {
meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE)
meet_criteria(ab, allow_class = c("ab", "character"), allow_NULL = TRUE)
meet_criteria(guideline, allow_class = "character", has_length = 1)
meet_criteria(main, allow_class = "character", has_length = 1, allow_NULL = TRUE)
meet_criteria(ylab, allow_class = "character", has_length = 1)
meet_criteria(xlab, allow_class = "character", has_length = 1)
meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
language <- validate_language(language)
meet_criteria(expand, allow_class = "logical", has_length = 1)
x <- as.mic(x) # make sure that currently implemented MIC levels are used
if (length(colours_SIR) == 1) {
colours_SIR <- rep(colours_SIR, 3)
}
main <- gsub(" +", " ", paste0(main, collapse = " "))
x <- plotrange_as_table(x, expand = expand)
cols_sub <- plot_colours_subtitle_guideline(
x = x,
mo = mo,
ab = ab,
guideline = guideline,
colours_SIR = colours_SIR,
fn = as.mic,
language = language,
method = "MIC",
include_PKPD = include_PKPD,
breakpoint_type = breakpoint_type,
...
)
barplot(x,
col = cols_sub$cols,
main = main,
ylim = c(0, max(x) * ifelse(any(colours_SIR %in% cols_sub$cols), 1.1, 1)),
ylab = ylab,
xlab = xlab,
axes = FALSE
)
axis(2, seq(0, max(x)))
if (!is.null(cols_sub$sub)) {
mtext(side = 3, line = 0.5, adj = 0.5, cex = 0.75, cols_sub$sub)
}
if (any(colours_SIR %in% cols_sub$cols)) {
legend_txt <- character(0)
legend_col <- character(0)
if (any(cols_sub$cols == colours_SIR[1] & cols_sub$count > 0)) {
legend_txt <- c(legend_txt, "(S) Susceptible")
legend_col <- colours_SIR[1]
}
if (any(cols_sub$cols == colours_SIR[2] & cols_sub$count > 0)) {
legend_txt <- c(legend_txt, paste("(I)", plot_name_of_I(cols_sub$guideline)))
legend_col <- c(legend_col, colours_SIR[2])
}
if (any(cols_sub$cols == colours_SIR[3] & cols_sub$count > 0)) {
legend_txt <- c(legend_txt, "(R) Resistant")
legend_col <- c(legend_col, colours_SIR[3])
}
legend("top",
x.intersp = 0.5,
legend = translate_into_language(legend_txt, language = language),
fill = legend_col,
horiz = TRUE,
cex = 0.75,
box.lwd = 0,
box.col = "#FFFFFF55",
bg = "#FFFFFF55"
)
}
}
#' @method barplot mic
#' @export
#' @noRd
barplot.mic <- function(height,
mo = NULL,
ab = NULL,
guideline = "EUCAST",
main = deparse(substitute(height)),
ylab = translate_AMR("Frequency", language = language),
xlab = translate_AMR("Minimum Inhibitory Concentration (mg/L)", language = language),
colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
language = get_AMR_locale(),
expand = TRUE,
...) {
meet_criteria(main, allow_class = "character", has_length = 1, allow_NULL = TRUE)
meet_criteria(ylab, allow_class = "character", has_length = 1)
meet_criteria(xlab, allow_class = "character", has_length = 1)
meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE)
meet_criteria(ab, allow_class = c("ab", "character"), allow_NULL = TRUE)
meet_criteria(guideline, allow_class = "character", has_length = 1)
meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
language <- validate_language(language)
meet_criteria(expand, allow_class = "logical", has_length = 1)
main <- gsub(" +", " ", paste0(main, collapse = " "))
height <- as.mic(height) # make sure that currently implemented MIC levels are used
plot(
x = height,
main = main,
ylab = ylab,
xlab = xlab,
mo = mo,
ab = ab,
guideline = guideline,
colours_SIR = colours_SIR,
...
)
}
#' @method autoplot mic
#' @rdname plot
# will be exported using s3_register() in R/zzz.R
autoplot.mic <- function(object,
mo = NULL,
ab = NULL,
guideline = "EUCAST",
title = deparse(substitute(object)),
ylab = translate_AMR("Frequency", language = language),
xlab = translate_AMR("Minimum Inhibitory Concentration (mg/L)", language = language),
colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
language = get_AMR_locale(),
expand = TRUE,
include_PKPD = getOption("AMR_include_PKPD", TRUE),
breakpoint_type = getOption("AMR_breakpoint_type", "human"),
...) {
stop_ifnot_installed("ggplot2")
meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE)
meet_criteria(ab, allow_class = c("ab", "character"), allow_NULL = TRUE)
meet_criteria(guideline, allow_class = "character", has_length = 1)
meet_criteria(title, allow_class = "character", allow_NULL = TRUE)
meet_criteria(ylab, allow_class = "character", has_length = 1)
meet_criteria(xlab, allow_class = "character", has_length = 1)
meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
language <- validate_language(language)
meet_criteria(expand, allow_class = "logical", has_length = 1)
if ("main" %in% names(list(...))) {
title <- list(...)$main
}
if (!is.null(title)) {
title <- gsub(" +", " ", paste0(title, collapse = " "))
}
object <- as.mic(object) # make sure that currently implemented MIC levels are used
x <- plotrange_as_table(object, expand = expand)
cols_sub <- plot_colours_subtitle_guideline(
x = x,
mo = mo,
ab = ab,
guideline = guideline,
colours_SIR = colours_SIR,
fn = as.mic,
language = language,
method = "MIC",
include_PKPD = include_PKPD,
breakpoint_type = breakpoint_type,
...
)
df <- as.data.frame(x, stringsAsFactors = TRUE)
colnames(df) <- c("mic", "count")
df$cols <- cols_sub$cols
df$cols[df$cols == colours_SIR[1]] <- "(S) Susceptible"
df$cols[df$cols == colours_SIR[2]] <- paste("(I)", plot_name_of_I(cols_sub$guideline))
df$cols[df$cols == colours_SIR[3]] <- "(R) Resistant"
df$cols <- factor(translate_into_language(df$cols, language = language),
levels = translate_into_language(
c(
"(S) Susceptible",
paste("(I)", plot_name_of_I(cols_sub$guideline)),
"(R) Resistant"
),
language = language
),
ordered = TRUE
)
p <- ggplot2::ggplot(df)
if (any(colours_SIR %in% cols_sub$cols)) {
vals <- c(
"(S) Susceptible" = colours_SIR[1],
"(SDD) Susceptible dose-dependent" = colours_SIR[2],
"(I) Susceptible, incr. exp." = colours_SIR[2],
"(I) Intermediate" = colours_SIR[2],
"(R) Resistant" = colours_SIR[3]
)
names(vals) <- translate_into_language(names(vals), language = language)
p <- p +
ggplot2::geom_col(ggplot2::aes(x = mic, y = count, fill = cols)) +
# limits = force is needed because of a ggplot2 >= 3.3.4 bug (#4511)
ggplot2::scale_fill_manual(
values = vals,
name = NULL,
limits = force
)
} else {
p <- p +
ggplot2::geom_col(ggplot2::aes(x = mic, y = count))
}
p +
ggplot2::labs(title = title, x = xlab, y = ylab, subtitle = cols_sub$sub)
}
#' @method fortify mic
#' @rdname plot
# will be exported using s3_register() in R/zzz.R
fortify.mic <- function(object, ...) {
object <- as.mic(object) # make sure that currently implemented MIC levels are used
stats::setNames(
as.data.frame(plotrange_as_table(object, expand = FALSE)),
c("x", "y")
)
}
#' @method plot disk
#' @export
#' @importFrom graphics barplot axis mtext legend
#' @rdname plot
plot.disk <- function(x,
main = deparse(substitute(x)),
ylab = translate_AMR("Frequency", language = language),
xlab = translate_AMR("Disk diffusion diameter (mm)", language = language),
mo = NULL,
ab = NULL,
guideline = "EUCAST",
colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
language = get_AMR_locale(),
expand = TRUE,
include_PKPD = getOption("AMR_include_PKPD", TRUE),
breakpoint_type = getOption("AMR_breakpoint_type", "human"),
...) {
meet_criteria(main, allow_class = "character", has_length = 1, allow_NULL = TRUE)
meet_criteria(ylab, allow_class = "character", has_length = 1)
meet_criteria(xlab, allow_class = "character", has_length = 1)
meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE)
meet_criteria(ab, allow_class = c("ab", "character"), allow_NULL = TRUE)
meet_criteria(guideline, allow_class = "character", has_length = 1)
meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
language <- validate_language(language)
meet_criteria(expand, allow_class = "logical", has_length = 1)
if (length(colours_SIR) == 1) {
colours_SIR <- rep(colours_SIR, 3)
}
main <- gsub(" +", " ", paste0(main, collapse = " "))
x <- plotrange_as_table(x, expand = expand)
cols_sub <- plot_colours_subtitle_guideline(
x = x,
mo = mo,
ab = ab,
guideline = guideline,
colours_SIR = colours_SIR,
fn = as.disk,
language = language,
method = "disk",
include_PKPD = include_PKPD,
breakpoint_type = breakpoint_type,
...
)
barplot(x,
col = cols_sub$cols,
main = main,
ylim = c(0, max(x) * ifelse(any(colours_SIR %in% cols_sub$cols), 1.1, 1)),
ylab = ylab,
xlab = xlab,
axes = FALSE
)
axis(2, seq(0, max(x)))
if (!is.null(cols_sub$sub)) {
mtext(side = 3, line = 0.5, adj = 0.5, cex = 0.75, cols_sub$sub)
}
if (any(colours_SIR %in% cols_sub$cols)) {
legend_txt <- character(0)
legend_col <- character(0)
if (any(cols_sub$cols == colours_SIR[3] & cols_sub$count > 0)) {
legend_txt <- "(R) Resistant"
legend_col <- colours_SIR[3]
}
if (any(cols_sub$cols == colours_SIR[2] & cols_sub$count > 0)) {
legend_txt <- c(legend_txt, paste("(I)", plot_name_of_I(cols_sub$guideline)))
legend_col <- c(legend_col, colours_SIR[2])
}
if (any(cols_sub$cols == colours_SIR[1] & cols_sub$count > 0)) {
legend_txt <- c(legend_txt, "(S) Susceptible")
legend_col <- c(legend_col, colours_SIR[1])
}
legend("top",
x.intersp = 0.5,
legend = translate_into_language(legend_txt, language = language),
fill = legend_col,
horiz = TRUE,
cex = 0.75,
box.lwd = 0,
box.col = "#FFFFFF55",
bg = "#FFFFFF55"
)
}
}
#' @method barplot disk
#' @export
#' @noRd
barplot.disk <- function(height,
main = deparse(substitute(height)),
ylab = translate_AMR("Frequency", language = language),
xlab = translate_AMR("Disk diffusion diameter (mm)", language = language),
mo = NULL,
ab = NULL,
guideline = "EUCAST",
colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
language = get_AMR_locale(),
expand = TRUE,
...) {
meet_criteria(main, allow_class = "character", has_length = 1, allow_NULL = TRUE)
meet_criteria(ylab, allow_class = "character", has_length = 1)
meet_criteria(xlab, allow_class = "character", has_length = 1)
meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE)
meet_criteria(ab, allow_class = c("ab", "character"), allow_NULL = TRUE)
meet_criteria(guideline, allow_class = "character", has_length = 1)
meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
language <- validate_language(language)
meet_criteria(expand, allow_class = "logical", has_length = 1)
main <- gsub(" +", " ", paste0(main, collapse = " "))
plot(
x = height,
main = main,
ylab = ylab,
xlab = xlab,
mo = mo,
ab = ab,
guideline = guideline,
colours_SIR = colours_SIR,
...
)
}
#' @method autoplot disk
#' @rdname plot
# will be exported using s3_register() in R/zzz.R
autoplot.disk <- function(object,
mo = NULL,
ab = NULL,
title = deparse(substitute(object)),
ylab = translate_AMR("Frequency", language = language),
xlab = translate_AMR("Disk diffusion diameter (mm)", language = language),
guideline = "EUCAST",
colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
language = get_AMR_locale(),
expand = TRUE,
include_PKPD = getOption("AMR_include_PKPD", TRUE),
breakpoint_type = getOption("AMR_breakpoint_type", "human"),
...) {
stop_ifnot_installed("ggplot2")
meet_criteria(title, allow_class = "character", allow_NULL = TRUE)
meet_criteria(ylab, allow_class = "character", has_length = 1)
meet_criteria(xlab, allow_class = "character", has_length = 1)
meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE)
meet_criteria(ab, allow_class = c("ab", "character"), allow_NULL = TRUE)
meet_criteria(guideline, allow_class = "character", has_length = 1)
meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
language <- validate_language(language)
meet_criteria(expand, allow_class = "logical", has_length = 1)
if ("main" %in% names(list(...))) {
title <- list(...)$main
}
if (!is.null(title)) {
title <- gsub(" +", " ", paste0(title, collapse = " "))
}
x <- plotrange_as_table(object, expand = expand)
cols_sub <- plot_colours_subtitle_guideline(
x = x,
mo = mo,
ab = ab,
guideline = guideline,
colours_SIR = colours_SIR,
fn = as.disk,
language = language,
method = "disk",
include_PKPD = include_PKPD,
breakpoint_type = breakpoint_type,
...
)
df <- as.data.frame(x, stringsAsFactors = TRUE)
colnames(df) <- c("disk", "count")
df$cols <- cols_sub$cols
df$cols[df$cols == colours_SIR[1]] <- "(S) Susceptible"
df$cols[df$cols == colours_SIR[2]] <- paste("(I)", plot_name_of_I(cols_sub$guideline))
df$cols[df$cols == colours_SIR[3]] <- "(R) Resistant"
df$cols <- factor(translate_into_language(df$cols, language = language),
levels = translate_into_language(
c(
"(S) Susceptible",
paste("(I)", plot_name_of_I(cols_sub$guideline)),
"(R) Resistant"
),
language = language
),
ordered = TRUE
)
p <- ggplot2::ggplot(df)
if (any(colours_SIR %in% cols_sub$cols)) {
vals <- c(
"(S) Susceptible" = colours_SIR[1],
"(SDD) Susceptible dose-dependent" = colours_SIR[2],
"(I) Susceptible, incr. exp." = colours_SIR[2],
"(I) Intermediate" = colours_SIR[2],
"(R) Resistant" = colours_SIR[3]
)
names(vals) <- translate_into_language(names(vals), language = language)
p <- p +
ggplot2::geom_col(ggplot2::aes(x = disk, y = count, fill = cols)) +
# limits = force is needed because of a ggplot2 >= 3.3.4 bug (#4511)
ggplot2::scale_fill_manual(
values = vals,
name = NULL,
limits = force
)
} else {
p <- p +
ggplot2::geom_col(ggplot2::aes(x = disk, y = count))
}
p +
ggplot2::labs(title = title, x = xlab, y = ylab, subtitle = cols_sub$sub)
}
#' @method fortify disk
#' @rdname plot
# will be exported using s3_register() in R/zzz.R
fortify.disk <- function(object, ...) {
stats::setNames(
as.data.frame(plotrange_as_table(object, expand = FALSE)),
c("x", "y")
)
}
#' @method plot sir
#' @export
#' @importFrom graphics plot text axis
#' @rdname plot
plot.sir <- function(x,
ylab = translate_AMR("Percentage", language = language),
xlab = translate_AMR("Antimicrobial Interpretation", language = language),
main = deparse(substitute(x)),
language = get_AMR_locale(),
...) {
meet_criteria(ylab, allow_class = "character", has_length = 1)
meet_criteria(xlab, allow_class = "character", has_length = 1)
meet_criteria(main, allow_class = "character", has_length = 1, allow_NULL = TRUE)
data <- as.data.frame(table(x), stringsAsFactors = FALSE)
colnames(data) <- c("x", "n")
data$s <- round((data$n / sum(data$n)) * 100, 1)
if (!"S" %in% data$x) {
data <- rbind_AMR(data, data.frame(x = "S", n = 0, s = 0, stringsAsFactors = FALSE))
}
if (!"SDD" %in% data$x) {
data <- rbind_AMR(data, data.frame(x = "SDD", n = 0, s = 0, stringsAsFactors = FALSE))
}
if (!"I" %in% data$x) {
data <- rbind_AMR(data, data.frame(x = "I", n = 0, s = 0, stringsAsFactors = FALSE))
}
if (!"R" %in% data$x) {
data <- rbind_AMR(data, data.frame(x = "R", n = 0, s = 0, stringsAsFactors = FALSE))
}
if (!"NI" %in% data$x) {
data <- rbind_AMR(data, data.frame(x = "NI", n = 0, s = 0, stringsAsFactors = FALSE))
}
data <- data[!(data$n == 0 & data$x %in% c("SDD", "I", "NI")), , drop = FALSE]
data$x <- factor(data$x, levels = intersect(unique(data$x), c("S", "SDD", "I", "R", "NI")), ordered = TRUE)
ymax <- pm_if_else(max(data$s) > 95, 105, 100)
plot(
x = data$x,
y = data$s,
lwd = 2,
ylim = c(0, ymax),
ylab = ylab,
xlab = xlab,
main = main,
axes = FALSE
)
# x axis
axis(side = 1, at = 1:pm_n_distinct(data$x), labels = levels(data$x), lwd = 0)
# y axis, 0-100%
axis(side = 2, at = seq(0, 100, 5))
text(
x = data$x,
y = data$s + 4,
labels = paste0(data$s, "% (n = ", data$n, ")")
)
}
#' @method barplot sir
#' @importFrom graphics barplot axis
#' @export
#' @noRd
barplot.sir <- function(height,
main = deparse(substitute(height)),
xlab = translate_AMR("Antimicrobial Interpretation", language = language),
ylab = translate_AMR("Frequency", language = language),
colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
language = get_AMR_locale(),
expand = TRUE,
...) {
meet_criteria(xlab, allow_class = "character", has_length = 1)
meet_criteria(main, allow_class = "character", has_length = 1, allow_NULL = TRUE)
meet_criteria(ylab, allow_class = "character", has_length = 1)
meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
language <- validate_language(language)
meet_criteria(expand, allow_class = "logical", has_length = 1)
if (length(colours_SIR) == 1) {
colours_SIR <- rep(colours_SIR, 3)
}
# add SDD and N to colours
colours_SIR <- c(colours_SIR[1:2], colours_SIR[2], colours_SIR[3], "#888888")
main <- gsub(" +", " ", paste0(main, collapse = " "))
x <- table(height)
# remove missing I, SDD, and N
colours_SIR <- colours_SIR[!(names(x) %in% c("SDD", "I", "NI") & x == 0)]
x <- x[!(names(x) %in% c("SDD", "I", "NI") & x == 0)]
# plot it
barplot(x,
col = colours_SIR,
xlab = xlab,
main = main,
ylab = ylab,
axes = FALSE
)
axis(2, seq(0, max(x)))
}
#' @method autoplot sir
#' @rdname plot
# will be exported using s3_register() in R/zzz.R
autoplot.sir <- function(object,
title = deparse(substitute(object)),
xlab = translate_AMR("Antimicrobial Interpretation", language = language),
ylab = translate_AMR("Frequency", language = language),
colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
language = get_AMR_locale(),
...) {
stop_ifnot_installed("ggplot2")
meet_criteria(title, allow_class = "character", allow_NULL = TRUE)
meet_criteria(ylab, allow_class = "character", has_length = 1)
meet_criteria(xlab, allow_class = "character", has_length = 1)
meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
if ("main" %in% names(list(...))) {
title <- list(...)$main
}
if (!is.null(title)) {
title <- gsub(" +", " ", paste0(title, collapse = " "))
}
if (length(colours_SIR) == 1) {
colours_SIR <- rep(colours_SIR, 3)
}
df <- as.data.frame(table(object), stringsAsFactors = TRUE)
colnames(df) <- c("x", "n")
df <- df[!(df$n == 0 & df$x %in% c("SDD", "I", "NI")), , drop = FALSE]
ggplot2::ggplot(df) +
ggplot2::geom_col(ggplot2::aes(x = x, y = n, fill = x)) +
# limits = force is needed because of a ggplot2 >= 3.3.4 bug (#4511)
ggplot2::scale_fill_manual(
values = c(
"S" = colours_SIR[1],
"SDD" = colours_SIR[2],
"I" = colours_SIR[2],
"R" = colours_SIR[3],
"NI" = "#888888"
),
limits = force
) +
ggplot2::labs(title = title, x = xlab, y = ylab) +
ggplot2::theme(legend.position = "none")
}
#' @method fortify sir
#' @rdname plot
# will be exported using s3_register() in R/zzz.R
fortify.sir <- function(object, ...) {
stats::setNames(
as.data.frame(table(object)),
c("x", "y")
)
}
plotrange_as_table <- function(x, expand, keep_operators = "all", mic_range = NULL) {
x <- x[!is.na(x)]
if (is.mic(x)) {
x <- as.mic(x, keep_operators = keep_operators)
if (expand == TRUE) {
# expand range for MIC by adding common intermediate factors levels
if (!is.null(mic_range) && !all(is.na(mic_range))) {
# base on mic_range
`%na_or%` <- function(x, y) if (is.na(x)) y else x
extra_range <- COMMON_MIC_VALUES[COMMON_MIC_VALUES >= (mic_range[1] %na_or% min(x, na.rm = TRUE)) & COMMON_MIC_VALUES <= (mic_range[2] %na_or% max(x, na.rm = TRUE))]
} else {
# base on x
extra_range <- COMMON_MIC_VALUES[COMMON_MIC_VALUES > min(x, na.rm = TRUE) & COMMON_MIC_VALUES < max(x, na.rm = TRUE)]
}
# remove the ones that are in 25% range of user values
extra_range <- extra_range[!vapply(FUN.VALUE = logical(1), extra_range, function(r) any(abs(r - x) / x < 0.25, na.rm = TRUE))]
nms <- extra_range
extra_range <- rep(0, length(extra_range))
names(extra_range) <- nms
x <- table(droplevels(x, as.mic = FALSE))
extra_range <- extra_range[!names(extra_range) %in% names(x) & names(extra_range) %in% VALID_MIC_LEVELS]
x <- as.table(c(x, extra_range))
} else {
x <- table(droplevels(x, as.mic = FALSE))
}
x <- x[order(as.double(as.mic(names(x))))]
} else if (is.disk(x)) {
if (expand == TRUE) {
# expand range for disks from lowest to highest so all mm's in between also print
extra_range <- rep(0, max(x) - min(x) - 1)
names(extra_range) <- seq(min(x) + 1, max(x) - 1)
x <- table(x)
extra_range <- extra_range[!names(extra_range) %in% names(x)]
x <- as.table(c(x, extra_range))
} else {
x <- table(x)
}
x <- x[order(as.double(names(x)))]
}
as.table(x)
}
ggplot2_get_from_dots <- function(arg, default, ...) {
dots <- list(...)
if (!arg %in% names(dots)) {
default
} else {
dots[[arg]]
}
}
plot_name_of_I <- function(guideline) {
if (guideline %unlike% "CLSI" && as.double(gsub("[^0-9]+", "", guideline)) >= 2019) {
# interpretation since 2019
"Susceptible, incr. exp."
} else {
# interpretation until 2019
"Intermediate"
}
}
plot_colours_subtitle_guideline <- function(x, mo, ab, guideline, colours_SIR, fn, language, method, breakpoint_type, include_PKPD, ...) {
stop_if(length(x) == 0, "no observations to plot", call = FALSE)
guideline <- get_guideline(guideline, AMR::clinical_breakpoints)
# store previous interpretations to backup
sir_history <- AMR_env$sir_interpretation_history
# and clear previous interpretations
AMR_env$sir_interpretation_history <- AMR_env$sir_interpretation_history[0, , drop = FALSE]
if (!is.null(mo) && !is.null(ab)) {
# interpret and give colour based on MIC values
mo <- as.mo(mo)
moname <- mo_name(mo, language = language)
ab <- as.ab(ab)
abname <- ab_name(ab, language = language)
sir <- suppressWarnings(suppressMessages(as.sir(fn(names(x)), mo = mo, ab = ab, guideline = guideline, include_screening = FALSE, include_PKPD = include_PKPD, breakpoint_type = breakpoint_type, ...)))
guideline_txt <- guideline
if (all(is.na(sir))) {
sir_screening <- suppressWarnings(suppressMessages(as.sir(fn(names(x)), mo = mo, ab = ab, guideline = guideline, include_screening = TRUE, include_PKPD = include_PKPD, breakpoint_type = breakpoint_type, ...)))
if (!all(is.na(sir_screening))) {
message_(
"Only ", guideline, " ", method, " interpretations found for ",
ab_name(ab, language = NULL, tolower = TRUE), " in ", italicise(moname), " for screening"
)
sir <- sir_screening
guideline_txt <- paste0("(Screen, ", guideline_txt, ")")
} else {
message_(
"No ", guideline, " ", method, " interpretations found for ",
ab_name(ab, language = NULL, tolower = TRUE), " in ", italicise(moname)
)
guideline_txt <- paste0("(", guideline_txt, ")")
}
} else {
if (isTRUE(list(...)$uti)) {
guideline_txt <- paste("UTIs,", guideline_txt)
}
ref_tbl <- paste0('"', unique(AMR_env$sir_interpretation_history$ref_table), '"', collapse = "/")
guideline_txt <- paste0("(", guideline_txt, ": ", ref_tbl, ")")
}
cols <- character(length = length(sir))
cols[is.na(sir)] <- "#BEBEBE"
cols[sir == "S"] <- colours_SIR[1]
cols[sir == "SDD"] <- colours_SIR[2]
cols[sir == "I"] <- colours_SIR[2]
cols[sir == "R"] <- colours_SIR[3]
cols[sir == "NI"] <- "#888888"
sub <- bquote(.(abname) ~ "-" ~ italic(.(moname)) ~ .(guideline_txt))
} else {
cols <- "#BEBEBE"
sub <- NULL
}
# restore previous interpretations to backup
AMR_env$sir_interpretation_history <- sir_history
list(cols = cols, count = as.double(x), sub = sub, guideline = guideline)
}
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