mirror of
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119 lines
4.6 KiB
R
119 lines
4.6 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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}
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})
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