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209 lines
9.5 KiB
R
209 lines
9.5 KiB
R
# ==================================================================== #
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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 CODE: #
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# https://github.com/msberends/AMR #
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# #
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# PLEASE CITE THIS SOFTWARE AS: #
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# Berends MS, Luz CF, Friedrich AW, et al. (2022). #
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# AMR: An R Package for Working with Antimicrobial Resistance Data. #
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# Journal of Statistical Software, 104(3), 1-31. #
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# https://doi.org/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://amr-for-r.org #
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# ==================================================================== #
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test_that("test-plotting.R", {
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skip_on_cran()
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if (AMR:::pkg_is_available("ggplot2", also_load = TRUE)) {
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pdf(NULL) # prevent Rplots.pdf being created
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# scale_*_mic
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aesthetics <- c("x", "y", "colour", "fill")
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expected_methods <- c("transform", "transform_df", "breaks", "labels", "limits")
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for (aest in aesthetics) {
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scale_fn_name <- paste0("scale_", aest, "_continuous")
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scale_obj <- getExportedValue("ggplot2", scale_fn_name)()
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for (method in expected_methods) {
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expect_true(is.function(scale_obj[[method]]) || method %in% names(scale_obj),
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info = paste0("Method '", method, "' is missing in ggplot2::", scale_fn_name)
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)
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}
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}
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# scale_*_sir
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aesthetics <- c("colour", "fill")
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expected_methods <- c("transform", "transform_df", "labels", "limits")
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for (aest in aesthetics) {
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scale_fn_name <- "scale_discrete_manual"
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scale_obj <- getExportedValue("ggplot2", scale_fn_name)(aesthetics = aest)
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for (method in expected_methods) {
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expect_true(is.function(scale_obj[[method]]) || method %in% names(scale_obj),
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info = paste0("Method '", method, "' is missing in ggplot2::", scale_fn_name)
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)
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}
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}
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for (method in expected_methods) {
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expect_true(is.function(ggplot2::scale_x_discrete()[[method]]) || method %in% names(ggplot2::scale_x_discrete()),
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info = paste0("Method '", method, "' is missing in ggplot2::", "scale_x_discrete")
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)
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}
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expect_inherits(
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ggplot(
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data.frame(
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count = c(1, 2, 3, 4),
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sir = c("S", "I", "R", "SDD")
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),
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aes(x = sir, y = count, fill = sir)
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) +
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geom_col() +
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scale_x_sir(eucast_I = F, language = "el") +
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scale_fill_sir(eucast_I = T, language = "nl"),
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"gg"
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)
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expect_inherits(
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ggplot(
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data.frame(
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mic = as.mic(c(2, 4, 8, 16)),
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sir = as.sir(c("S", "I", "R", "SDD"))
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),
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aes(x = sir, y = mic)
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) +
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geom_point() +
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scale_y_mic(),
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"gg"
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)
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expect_inherits(
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ggplot(
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data.frame(
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mic = as.mic(c(2, 4, 8, 16)),
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sir = as.sir(c("S", "I", "R", "SDD"))
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),
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aes(x = sir, y = mic)
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) +
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geom_col() +
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scale_y_mic(),
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"gg"
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)
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expect_inherits(
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ggplot(
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data.frame(
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mic = as.mic(c(2, 4, 8, 16)),
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sir = as.sir(c("S", "I", "R", "SDD"))
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),
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aes(x = sir, y = mic)
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) +
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geom_col() +
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scale_y_mic(mic_range = c(4, 16)) +
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scale_x_sir(),
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"gg"
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)
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# named colours are matched by name, and SDD, S/I and I/R follow S and R
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expect_identical(AMR:::expand_SIR_colours(c(R = "r", I = "i", SDD = "d", S = "s")), c("s", "d", "i", "r", "s", "r"))
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expect_identical(AMR:::expand_SIR_colours(c(S = "s", I = "i", R = "r")), c("s", "s", "i", "r", "s", "r"))
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expect_identical(AMR:::expand_SIR_colours(c("s", "i", "r")), c("s", "s", "i", "r", "s", "r"))
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expect_error(AMR:::expand_SIR_colours(c(S = "s", I = "i", X = "r")))
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# missing names S, I and R get the default colours, as in the example of ggplot_sir()
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expect_identical(AMR:::expand_SIR_colours(c(SI = "y")), c("#3CAEA3", "#3CAEA3", "#F6D55C", "#ED553B", "y", "#ED553B"))
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# colours of SIR bar plots follow the SIR values
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sir_values <- as.sir(c("S", "S", "R", "NI", "NS"))
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keep <- AMR:::plot_sir_levels_to_keep(sir_values, table(sir_values))
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expect_identical(names(table(sir_values))[keep], c("S", "R", "NI", "NS"))
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p <- autoplot(sir_values)
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expect_identical(as.character(p$data$x), c("S", "R", "NI", "NS"))
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expect_identical(unique(ggplot_build(p)$data[[1]]$fill), c("#3CAEA3", "#ED553B", "grey30"))
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# SDD in disk diffusion plots
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p <- autoplot(as.disk(15:30), mo = "Escherichia coli", ab = "cefepime", guideline = "CLSI 2025", language = "en")
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expect_true("(SDD) Susceptible dose-dependent" %in% as.character(p$data$cols))
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expect_false(anyNA(p$data$cols))
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# colours and labels are named by, and cover, all SIR levels
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expect_identical(names(AMR:::plot_sir_colour_values(AMR:::expand_SIR_colours("red"))), AMR:::VALID_SIR_LEVELS)
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expect_identical(names(AMR:::plot_sir_label_values("EUCAST")), AMR:::VALID_SIR_LEVELS)
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# arguments are passed on
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expect_identical(scale_x_sir(name = "Interpretation")$name, "Interpretation")
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expect_identical(scale_fill_sir(values = c(S = "black"))$palette(1)[["S"]], "black")
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expect_identical(scale_fill_sir(values = c(S = "black"))$palette(1)[["R"]], "#ED553B")
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expect_error(scale_fill_sir(values = c("black", "white", "grey")))
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expect_warning(scale_x_sir(values = c(S = "black")))
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expect_identical(AMR:::plot_count_ticks(3), c(0, 1, 2, 3))
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expect_identical(AMR:::plot_name_of_I("EUCAST"), "Susceptible, incr. exp.")
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expect_identical(AMR:::plot_name_of_I("EUCAST 2018"), "Intermediate")
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# unquoted column names in facet_sir() are not evaluated, also not if an object with that name exists
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antibiotic <- "some other column"
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expect_identical(facet_sir(antibiotic)$params$facets, facet_sir("antibiotic")$params$facets)
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# the default of eucast_I follows the guideline option
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old_option <- options(AMR_guideline = "EUCAST")
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expect_identical(scale_fill_sir(language = "en")$labels("I"), "(I) Susceptible, incr. exp.")
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options(AMR_guideline = "EUCAST 2018")
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expect_identical(scale_fill_sir(language = "en")$labels("I"), "(I) Intermediate")
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options(AMR_guideline = "CLSI")
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expect_identical(scale_fill_sir(language = "en")$labels("I"), "(I) Intermediate")
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options(old_option)
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# keep_operators = TRUE/FALSE equals "all"/"none"
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mic_labels <- function(keep_operators) {
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p <- ggplot(data.frame(m = as.mic(c(">=8", "2", "<=0.5"))), aes(m, 1)) +
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geom_point() +
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scale_x_mic(keep_operators = keep_operators)
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ggplot_build(p)$layout$panel_params[[1]]$x$get_labels()
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}
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expect_identical(mic_labels(TRUE), mic_labels("all"))
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expect_identical(mic_labels(FALSE), mic_labels("none"))
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expect_false(identical(mic_labels(TRUE), mic_labels(FALSE)))
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}
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# base R plots: texts in the legend (drawn with text()) and bar names (drawn with axis())
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recorded_strings <- function(expr, fn) {
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pdf(NULL)
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dev.control("enable")
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on.exit(dev.off())
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force(expr)
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unlist(lapply(recordPlot()[[1]], function(call) {
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if (identical(call[[2]][[1]]$name, fn)) {
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as.character(call[[2]][[if (fn == "C_text") 3 else 4]])
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}
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}))
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}
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mic_values <- as.mic(c(0.25, 0.25, 4, 32))
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# the legend is based on the interpretation, so SDD is not shown when it has the colour of S
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expect_identical(
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recorded_strings(plot(mic_values, mo = "Escherichia coli", ab = "AMC", language = "en", colours_SIR = c("green", "yellow", "red")), "C_text"),
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c("(S) Susceptible", "(R) Resistant")
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)
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# zone diameters run from resistant to susceptible, and so does the legend
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expect_identical(
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recorded_strings(plot(as.disk(15:30), mo = "Escherichia coli", ab = "cefepime", guideline = "CLSI 2025", language = "en"), "C_text"),
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c("(R) Resistant", "(SDD) Susceptible dose-dependent", "(S) Susceptible")
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)
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# barplot() for MIC values passes on language and expand
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expect_identical(
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recorded_strings(barplot(mic_values, mo = "Escherichia coli", ab = "AMC", language = "nl"), "C_text"),
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c("(S) Gevoelig", "(R) Resistent")
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)
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expect_true(length(recorded_strings(barplot(mic_values, expand = TRUE), "C_axis")) > length(recorded_strings(barplot(mic_values, expand = FALSE), "C_axis")))
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})
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