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(v2.1.1.9118) move ggplot2 plotting functions to general 'plotting' man page
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201
R/plotting.R
201
R/plotting.R
@ -27,7 +27,7 @@
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# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
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# ==================================================================== #
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#' Plotting for Classes `sir`, `mic` and `disk`
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#' Plotting Helpers for AMR Data Analysis
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#'
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#' @description
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#' Functions to plot classes `sir`, `mic` and `disk`, with support for base \R and `ggplot2`.
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@ -49,6 +49,16 @@
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#' 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)`.
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#'
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#' Simply using `"CLSI"` or `"EUCAST"` as input will automatically select the latest version of that guideline.
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#'
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#' ### Additional `ggplot2` Functions
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#'
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#' This package contains several functions that extend the `ggplot2` package, to help in visualising AMR data results. All these functions are internally used by [ggplot_sir()] too.
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#'
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#' * [facet_sir()] creates 2d plots (at default based on S/I/R) using [ggplot2::facet_wrap()].
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#' * [scale_y_percent()] transforms the y axis to a 0 to 100% range using [ggplot2::scale_y_continuous()].
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#' * [scale_sir_colours()] sets colours to the bars (green for S, yellow for I, and red for R). Has multilingual support. The default colours are colour-blind friendly, while maintaining the convention that e.g. 'susceptible' should be green and 'resistant' should be red.
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#' * [theme_sir()] is a [ggplot2 theme][[ggplot2::theme()] with minimal distraction.
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#' * [labels_sir_count()] print datalabels on the bars with percentage and number of isolates, using [ggplot2::geom_text()].
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#' @name plot
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#' @rdname plot
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#' @return The `autoplot()` functions return a [`ggplot`][ggplot2::ggplot()] model that is extendible with any `ggplot2` function.
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@ -915,3 +925,192 @@ plot_colours_subtitle_guideline <- function(x, mo, ab, guideline, colours_SIR, f
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list(cols = cols, count = as.double(x), sub = sub, guideline = guideline)
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}
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#' @rdname plot
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#' @export
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facet_sir <- function(facet = c("interpretation", "antibiotic"), nrow = NULL) {
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facet <- facet[1]
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stop_ifnot_installed("ggplot2")
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meet_criteria(facet, allow_class = "character", has_length = 1)
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meet_criteria(nrow, allow_class = c("numeric", "integer"), has_length = 1, allow_NULL = TRUE, is_positive = TRUE, is_finite = TRUE)
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# we work with aes_string later on
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facet_deparse <- deparse(substitute(facet))
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if (facet_deparse != "facet") {
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facet <- facet_deparse
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}
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if (facet %like% '".*"') {
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facet <- substr(facet, 2, nchar(facet) - 1)
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}
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if (tolower(facet) %in% tolower(c("SIR", "sir", "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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}
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#' @rdname plot
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#' @export
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scale_y_percent <- function(breaks = function(x) seq(0, max(x, na.rm = TRUE), 0.1), limits = NULL) {
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stop_ifnot_installed("ggplot2")
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meet_criteria(breaks, allow_class = c("numeric", "integer", "function"))
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meet_criteria(limits, allow_class = c("numeric", "integer"), has_length = 2, allow_NULL = TRUE, allow_NA = TRUE)
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if (!is.function(breaks) && all(breaks[breaks != 0] > 1)) {
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breaks <- breaks / 100
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}
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ggplot2::scale_y_continuous(
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breaks = breaks,
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labels = if (is.function(breaks)) function(x) percentage(breaks(x)) else percentage(breaks),
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limits = limits
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)
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}
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#' @rdname plot
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#' @export
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scale_sir_colours <- function(...,
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aesthetics = "fill",
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colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B")) {
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stop_ifnot_installed("ggplot2")
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meet_criteria(aesthetics, allow_class = "character", is_in = c("alpha", "colour", "color", "fill", "linetype", "shape", "size"))
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meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
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if (length(colours_SIR) == 1) {
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colours_SIR <- rep(colours_SIR, 3)
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}
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# behaviour until AMR pkg v1.5.0 and also when coming from ggplot_sir()
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if ("colours" %in% names(list(...))) {
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original_cols <- c(
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S = colours_SIR[1],
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SI = colours_SIR[1],
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I = colours_SIR[2],
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IR = colours_SIR[3],
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R = colours_SIR[3]
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)
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colours <- replace(original_cols, names(list(...)$colours), list(...)$colours)
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# limits = force is needed in ggplot2 3.3.4 and 3.3.5, see here;
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# https://github.com/tidyverse/ggplot2/issues/4511#issuecomment-866185530
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return(ggplot2::scale_fill_manual(values = colours, limits = force))
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}
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if (identical(unlist(list(...)), FALSE)) {
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return(invisible())
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}
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names_susceptible <- c(
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"S", "SI", "IS", "S+I", "I+S", "susceptible", "Susceptible",
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unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Susceptible"),
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"replacement",
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drop = TRUE
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])
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)
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names_incr_exposure <- c(
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"I", "intermediate", "increased exposure", "incr. exposure",
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"Increased exposure", "Incr. exposure", "Susceptible, incr. exp.",
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unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Intermediate"),
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"replacement",
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drop = TRUE
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]),
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unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Susceptible, incr. exp."),
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"replacement",
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drop = TRUE
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])
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)
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names_resistant <- c(
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"R", "IR", "RI", "R+I", "I+R", "resistant", "Resistant",
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unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Resistant"),
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"replacement",
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drop = TRUE
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])
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)
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susceptible <- rep(colours_SIR[1], length(names_susceptible))
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names(susceptible) <- names_susceptible
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incr_exposure <- rep(colours_SIR[2], length(names_incr_exposure))
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names(incr_exposure) <- names_incr_exposure
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resistant <- rep(colours_SIR[3], length(names_resistant))
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names(resistant) <- names_resistant
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original_cols <- c(susceptible, incr_exposure, resistant)
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dots <- c(...)
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# replace S, I, R as colours: scale_sir_colours(mydatavalue = "S")
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dots[dots == "S"] <- colours_SIR[1]
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dots[dots == "I"] <- colours_SIR[2]
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dots[dots == "R"] <- colours_SIR[3]
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cols <- replace(original_cols, names(dots), dots)
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# limits = force is needed in ggplot2 3.3.4 and 3.3.5, see here;
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# https://github.com/tidyverse/ggplot2/issues/4511#issuecomment-866185530
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ggplot2::scale_discrete_manual(aesthetics = aesthetics, values = cols, limits = force)
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}
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#' @rdname plot
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#' @export
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theme_sir <- 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(
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panel.grid.major.x = ggplot2::element_blank(),
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panel.grid.minor = ggplot2::element_blank(),
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panel.grid.major.y = ggplot2::element_line(colour = "grey75"),
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# center title and subtitle
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plot.title = ggplot2::element_text(hjust = 0.5),
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plot.subtitle = ggplot2::element_text(hjust = 0.5)
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)
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}
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#' @rdname plot
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#' @export
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labels_sir_count <- function(position = NULL,
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x = "antibiotic",
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translate_ab = "name",
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minimum = 30,
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language = get_AMR_locale(),
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combine_SI = TRUE,
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datalabels.size = 3,
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datalabels.colour = "grey15") {
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stop_ifnot_installed("ggplot2")
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meet_criteria(position, allow_class = "character", has_length = 1, is_in = c("fill", "stack", "dodge"), allow_NULL = TRUE)
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meet_criteria(x, allow_class = "character", has_length = 1)
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meet_criteria(translate_ab, allow_class = c("character", "logical"), has_length = 1, allow_NA = TRUE)
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meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_positive_or_zero = TRUE, is_finite = TRUE)
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language <- validate_language(language)
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meet_criteria(combine_SI, allow_class = "logical", has_length = 1)
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meet_criteria(datalabels.size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
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meet_criteria(datalabels.colour, allow_class = "character", has_length = 1)
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if (is.null(position)) {
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position <- "fill"
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}
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if (identical(position, "fill")) {
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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(
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mapping = ggplot2::aes_string(
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label = "lbl",
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x = x,
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y = "value"
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),
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position = position,
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inherit.aes = FALSE,
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size = datalabels.size,
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colour = datalabels.colour,
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lineheight = 0.75,
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data = function(x) {
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transformed <- sir_df(
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data = x,
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translate_ab = translate_ab,
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combine_SI = combine_SI,
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minimum = minimum,
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language = language
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)
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transformed$gr <- transformed[, x_name, drop = TRUE]
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transformed %pm>%
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pm_group_by(gr) %pm>%
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pm_mutate(lbl = paste0("n=", isolates)) %pm>%
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pm_ungroup() %pm>%
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pm_select(-gr)
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}
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)
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}
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