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R/ggplot_sir.R
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R/ggplot_sir.R
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# ==================================================================== #
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# TITLE #
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# AMR: An R Package for Working with Antimicrobial Resistance Data #
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# #
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# SOURCE #
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# https://github.com/msberends/AMR #
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# #
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# CITE AS #
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# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
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# (2022). AMR: An R Package for Working with Antimicrobial Resistance #
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# Data. Journal of Statistical Software, 104(3), 1-31. #
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# doi:10.18637/jss.v104.i03 #
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# #
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# Developed at the University of Groningen and the University Medical #
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# Center Groningen in The Netherlands, in collaboration with many #
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# colleagues from around the world, see our website. #
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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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# We created this package for both routine data analysis and academic #
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# research and it was publicly released in the hope that it will be #
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# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
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# #
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# Visit our website for the full manual and a complete tutorial about #
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# how to conduct AMR data analysis: https://msberends.github.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 AMR data analysis. All functions rely on [ggplot2][ggplot2::ggplot()] functions.
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#' @param data a [data.frame] with column(s) of class [`sir`] (see [as.sir()])
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#' @param position position adjustment of bars, either `"fill"`, `"stack"` or `"dodge"`
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#' @param x variable to show on x axis, either `"antibiotic"` (default) or `"interpretation"` or a grouping variable
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#' @param fill variable to categorise using the plots legend, either `"antibiotic"` (default) or `"interpretation"` or a grouping variable
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#' @param breaks a [numeric] vector of positions
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#' @param limits a [numeric] vector of length two providing limits of the scale, use `NA` to refer to the existing minimum or maximum
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#' @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
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#' @param colours a named vactor with colour to be used for filling. The default colours are colour-blind friendly.
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#' @param aesthetics aesthetics to apply the colours to, defaults to "fill" but can also be (a combination of) "alpha", "colour", "fill", "linetype", "shape" or "size"
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#' @param datalabels show datalabels using [labels_sir_count()]
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#' @param datalabels.size size of the datalabels
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#' @param datalabels.colour colour of the datalabels
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#' @param title text to show as title of the plot
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#' @param subtitle text to show as subtitle of the plot
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#' @param caption text to show as caption of the plot
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#' @param x.title text to show as x axis description
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#' @param y.title text to show as y axis description
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#' @param ... other arguments passed on to [geom_sir()] or, in case of [scale_sir_colours()], named values to set colours. The default colours are colour-blind friendly, while maintaining the convention that e.g. 'susceptible' should be green and 'resistant' should be red. See *Examples*.
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#' @details At default, the names of antibiotics will be shown on the plots using [ab_name()]. This can be set with the `translate_ab` argument. See [count_df()].
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#'
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#' ### The Functions
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#' [geom_sir()] will take any variable from the data that has an [`sir`] class (created with [as.sir()]) using [sir_df()] and will plot bars with the percentage S, I, and R. 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_sir()] 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_y_continuous()].
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#'
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#' [scale_sir_colours()] sets colours to the bars (green for S, yellow for I, and red for R). with 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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#'
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#' [theme_sir()] is a [ggplot2 theme][[ggplot2::theme()] with minimal distraction.
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#'
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#' [labels_sir_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_sir()] 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_sir
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#' @export
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#' @examples
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#' \donttest{
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#' if (require("ggplot2") && require("dplyr")) {
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#'
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#' # get antimicrobial results for drugs against a UTI:
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#' ggplot(example_isolates %>% select(AMX, NIT, FOS, TMP, CIP)) +
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#' geom_sir()
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#' }
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#' if (require("ggplot2") && require("dplyr")) {
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#'
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#' # prettify the plot using some additional functions:
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#' df <- example_isolates %>% select(AMX, NIT, FOS, TMP, CIP)
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#' ggplot(df) +
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#' geom_sir() +
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#' scale_y_percent() +
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#' scale_sir_colours() +
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#' labels_sir_count() +
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#' theme_sir()
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#' }
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#' if (require("ggplot2") && require("dplyr")) {
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#'
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#' # or better yet, simplify this using the wrapper function - a single command:
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#' example_isolates %>%
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#' select(AMX, NIT, FOS, TMP, CIP) %>%
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#' ggplot_sir()
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#' }
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#' if (require("ggplot2") && require("dplyr")) {
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#'
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#' # get only proportions and no counts:
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#' example_isolates %>%
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#' select(AMX, NIT, FOS, TMP, CIP) %>%
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#' ggplot_sir(datalabels = FALSE)
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#' }
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#' if (require("ggplot2") && require("dplyr")) {
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#'
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#' # add other ggplot2 arguments as you like:
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#' example_isolates %>%
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#' select(AMX, NIT, FOS, TMP, CIP) %>%
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#' ggplot_sir(
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#' width = 0.5,
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#' colour = "black",
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#' size = 1,
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#' linetype = 2,
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#' alpha = 0.25
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#' )
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#' }
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#' if (require("ggplot2") && require("dplyr")) {
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#'
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#' # you can alter the colours with colour names:
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#' example_isolates %>%
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#' select(AMX) %>%
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#' ggplot_sir(colours = c(SI = "yellow"))
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#' }
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#' if (require("ggplot2") && require("dplyr")) {
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#'
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#' # but you can also use the built-in colour-blind friendly colours for
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#' # your plots, where "S" is green, "I" is yellow and "R" is red:
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#' data.frame(
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#' x = c("Value1", "Value2", "Value3"),
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#' y = c(1, 2, 3),
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#' z = c("Value4", "Value5", "Value6")
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#' ) %>%
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#' ggplot() +
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#' geom_col(aes(x = x, y = y, fill = z)) +
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#' scale_sir_colours(Value4 = "S", Value5 = "I", Value6 = "R")
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#' }
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#' if (require("ggplot2") && require("dplyr")) {
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#'
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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()) %>%
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#' filter(
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#' first_isolate == TRUE,
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#' mo == as.mo("Escherichia coli")
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#' ) %>%
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#' # age_groups() is also a function in this AMR package:
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#' group_by(age_group = age_groups(age)) %>%
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#' select(age_group, CIP) %>%
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#' ggplot_sir(x = "age_group")
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#' }
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#' if (require("ggplot2") && require("dplyr")) {
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#'
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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) %>%
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#' ggplot_sir(colours = FALSE)
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#' }
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#' if (require("ggplot2") && require("dplyr")) {
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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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#' filter(mo_is_gram_negative(), ward != "Outpatient") %>%
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#' # select only UTI-specific drugs
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#' select(ward, AMX, NIT, FOS, TMP, CIP) %>%
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#' group_by(ward) %>%
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#' ggplot_sir(
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#' x = "ward",
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#' facet = "antibiotic",
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#' nrow = 1,
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#' title = "AMR of Anti-UTI Drugs Per Ward",
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#' x.title = "Ward",
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#' datalabels = FALSE
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#' )
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#' }
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#' }
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ggplot_sir <- function(data,
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position = NULL,
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x = "antibiotic",
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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,
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minimum = 30,
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language = get_AMR_locale(),
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nrow = NULL,
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colours = c(
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S = "#3CAEA3",
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SI = "#3CAEA3",
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I = "#F6D55C",
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IR = "#ED553B",
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R = "#ED553B"
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),
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datalabels = TRUE,
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datalabels.size = 2.5,
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datalabels.colour = "grey15",
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title = NULL,
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subtitle = NULL,
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caption = NULL,
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x.title = "Antimicrobial",
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y.title = "Proportion",
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...) {
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stop_ifnot_installed("ggplot2")
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meet_criteria(data, allow_class = "data.frame", contains_column_class = "sir")
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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(fill, allow_class = "character", has_length = 1)
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meet_criteria(facet, allow_class = "character", has_length = 1, allow_NULL = TRUE)
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meet_criteria(breaks, allow_class = c("numeric", "integer"))
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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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meet_criteria(translate_ab, allow_class = c("character", "logical"), has_length = 1, allow_NA = TRUE)
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meet_criteria(combine_SI, allow_class = "logical", has_length = 1)
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meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_finite = TRUE)
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language <- validate_language(language)
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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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meet_criteria(colours, allow_class = c("character", "logical"))
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meet_criteria(datalabels, 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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meet_criteria(title, allow_class = "character", has_length = 1, allow_NULL = TRUE)
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meet_criteria(subtitle, allow_class = "character", has_length = 1, allow_NULL = TRUE)
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meet_criteria(caption, allow_class = "character", has_length = 1, allow_NULL = TRUE)
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meet_criteria(x.title, allow_class = "character", has_length = 1, allow_NULL = TRUE)
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meet_criteria(y.title, allow_class = "character", has_length = 1, allow_NULL = TRUE)
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# we work with aes_string later on
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x_deparse <- deparse(substitute(x))
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if (x_deparse != "x") {
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x <- x_deparse
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}
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if (x %like% '".*"') {
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x <- substr(x, 2, nchar(x) - 1)
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}
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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 (facet %in% c("NULL", "")) {
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facet <- NULL
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}
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if (is.null(position)) {
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position <- "fill"
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}
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p <- ggplot2::ggplot(data = data) +
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geom_sir(
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position = position, x = x, fill = fill, translate_ab = translate_ab,
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minimum = minimum, language = language,
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combine_SI = combine_SI, ...
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) +
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theme_sir()
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if (fill == "interpretation") {
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p <- p + scale_sir_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_sir_count(
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position = position,
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x = x,
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translate_ab = translate_ab,
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minimum = minimum,
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language = language,
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combine_SI = combine_SI,
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datalabels.size = datalabels.size,
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datalabels.colour = datalabels.colour
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)
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}
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if (!is.null(facet)) {
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p <- p + facet_sir(facet = facet, nrow = nrow)
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}
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p <- p + ggplot2::labs(
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title = title,
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subtitle = subtitle,
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caption = caption,
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x = x.title,
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y = y.title
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)
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p
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}
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#' @rdname ggplot_sir
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#' @export
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geom_sir <- function(position = NULL,
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x = c("antibiotic", "interpretation"),
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fill = "interpretation",
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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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...) {
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x <- x[1]
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stop_ifnot_installed("ggplot2")
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stop_if(is.data.frame(position), "`position` is invalid. Did you accidentally use '%>%' instead of '+'?")
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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(fill, 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_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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y <- "value"
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if (missing(position) || 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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# we work with aes_string later on
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x_deparse <- deparse(substitute(x))
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if (x_deparse != "x") {
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x <- x_deparse
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}
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if (x %like% '".*"') {
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x <- substr(x, 2, nchar(x) - 1)
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}
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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", "sir", "interpretations", "result"))) {
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x <- "interpretation"
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}
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ggplot2::geom_col(
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data = function(x) {
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sir_df(
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data = x,
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translate_ab = translate_ab,
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language = language,
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minimum = minimum,
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combine_SI = combine_SI
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)
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},
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mapping = ggplot2::aes_string(x = x, y = y, fill = fill),
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position = position,
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...
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)
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}
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#' @rdname ggplot_sir
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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 ggplot_sir
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#' @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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meet_criteria(breaks, allow_class = c("numeric", "integer"))
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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 (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 = percentage(breaks),
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limits = limits
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)
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}
|
||||
|
||||
#' @rdname ggplot_sir
|
||||
#' @export
|
||||
scale_sir_colours <- function(...,
|
||||
aesthetics = "fill") {
|
||||
stop_ifnot_installed("ggplot2")
|
||||
meet_criteria(aesthetics, allow_class = "character", is_in = c("alpha", "colour", "color", "fill", "linetype", "shape", "size"))
|
||||
# behaviour until AMR pkg v1.5.0 and also when coming from ggplot_sir()
|
||||
if ("colours" %in% names(list(...))) {
|
||||
original_cols <- c(
|
||||
S = "#3CAEA3",
|
||||
SI = "#3CAEA3",
|
||||
I = "#F6D55C",
|
||||
IR = "#ED553B",
|
||||
R = "#ED553B"
|
||||
)
|
||||
colours <- replace(original_cols, names(list(...)$colours), list(...)$colours)
|
||||
# limits = force is needed in ggplot2 3.3.4 and 3.3.5, see here;
|
||||
# https://github.com/tidyverse/ggplot2/issues/4511#issuecomment-866185530
|
||||
return(ggplot2::scale_fill_manual(values = colours, limits = force))
|
||||
}
|
||||
if (identical(unlist(list(...)), FALSE)) {
|
||||
return(invisible())
|
||||
}
|
||||
|
||||
names_susceptible <- c(
|
||||
"S", "SI", "IS", "S+I", "I+S", "susceptible", "Susceptible",
|
||||
unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Susceptible"),
|
||||
"replacement",
|
||||
drop = TRUE
|
||||
])
|
||||
)
|
||||
names_incr_exposure <- c(
|
||||
"I", "intermediate", "increased exposure", "incr. exposure",
|
||||
"Increased exposure", "Incr. exposure", "Susceptible, incr. exp.",
|
||||
unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Intermediate"),
|
||||
"replacement",
|
||||
drop = TRUE
|
||||
]),
|
||||
unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Susceptible, incr. exp."),
|
||||
"replacement",
|
||||
drop = TRUE
|
||||
])
|
||||
)
|
||||
names_resistant <- c(
|
||||
"R", "IR", "RI", "R+I", "I+R", "resistant", "Resistant",
|
||||
unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Resistant"),
|
||||
"replacement",
|
||||
drop = TRUE
|
||||
])
|
||||
)
|
||||
|
||||
susceptible <- rep("#3CAEA3", length(names_susceptible))
|
||||
names(susceptible) <- names_susceptible
|
||||
incr_exposure <- rep("#F6D55C", length(names_incr_exposure))
|
||||
names(incr_exposure) <- names_incr_exposure
|
||||
resistant <- rep("#ED553B", length(names_resistant))
|
||||
names(resistant) <- names_resistant
|
||||
|
||||
original_cols <- c(susceptible, incr_exposure, resistant)
|
||||
dots <- c(...)
|
||||
# replace S, I, R as colours: scale_sir_colours(mydatavalue = "S")
|
||||
dots[dots == "S"] <- "#3CAEA3"
|
||||
dots[dots == "I"] <- "#F6D55C"
|
||||
dots[dots == "R"] <- "#ED553B"
|
||||
cols <- replace(original_cols, names(dots), dots)
|
||||
# limits = force is needed in ggplot2 3.3.4 and 3.3.5, see here;
|
||||
# https://github.com/tidyverse/ggplot2/issues/4511#issuecomment-866185530
|
||||
ggplot2::scale_discrete_manual(aesthetics = aesthetics, values = cols, limits = force)
|
||||
}
|
||||
|
||||
#' @rdname ggplot_sir
|
||||
#' @export
|
||||
theme_sir <- function() {
|
||||
stop_ifnot_installed("ggplot2")
|
||||
ggplot2::theme_minimal(base_size = 10) +
|
||||
ggplot2::theme(
|
||||
panel.grid.major.x = ggplot2::element_blank(),
|
||||
panel.grid.minor = ggplot2::element_blank(),
|
||||
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)
|
||||
)
|
||||
}
|
||||
|
||||
#' @rdname ggplot_sir
|
||||
#' @export
|
||||
labels_sir_count <- function(position = NULL,
|
||||
x = "antibiotic",
|
||||
translate_ab = "name",
|
||||
minimum = 30,
|
||||
language = get_AMR_locale(),
|
||||
combine_SI = TRUE,
|
||||
datalabels.size = 3,
|
||||
datalabels.colour = "grey15") {
|
||||
stop_ifnot_installed("ggplot2")
|
||||
meet_criteria(position, allow_class = "character", has_length = 1, is_in = c("fill", "stack", "dodge"), allow_NULL = TRUE)
|
||||
meet_criteria(x, allow_class = "character", has_length = 1)
|
||||
meet_criteria(translate_ab, allow_class = c("character", "logical"), has_length = 1, allow_NA = TRUE)
|
||||
meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_finite = TRUE)
|
||||
language <- validate_language(language)
|
||||
meet_criteria(combine_SI, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(datalabels.size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
|
||||
meet_criteria(datalabels.colour, allow_class = "character", has_length = 1)
|
||||
|
||||
if (is.null(position)) {
|
||||
position <- "fill"
|
||||
}
|
||||
if (identical(position, "fill")) {
|
||||
position <- ggplot2::position_fill(vjust = 0.5, reverse = TRUE)
|
||||
}
|
||||
x_name <- x
|
||||
ggplot2::geom_text(
|
||||
mapping = ggplot2::aes_string(
|
||||
label = "lbl",
|
||||
x = x,
|
||||
y = "value"
|
||||
),
|
||||
position = position,
|
||||
inherit.aes = FALSE,
|
||||
size = datalabels.size,
|
||||
colour = datalabels.colour,
|
||||
lineheight = 0.75,
|
||||
data = function(x) {
|
||||
transformed <- sir_df(
|
||||
data = x,
|
||||
translate_ab = translate_ab,
|
||||
combine_SI = combine_SI,
|
||||
minimum = minimum,
|
||||
language = language
|
||||
)
|
||||
transformed$gr <- transformed[, x_name, drop = TRUE]
|
||||
transformed %pm>%
|
||||
pm_group_by(gr) %pm>%
|
||||
pm_mutate(lbl = paste0("n=", isolates)) %pm>%
|
||||
pm_ungroup() %pm>%
|
||||
pm_select(-gr)
|
||||
}
|
||||
)
|
||||
}
|
Reference in New Issue
Block a user