tests/testthat/test-ggplot_sir.R

In AMR: Antimicrobial Resistance Data Analysis

# ==================================================================== #
# 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://amr-for-r.org              #
# ==================================================================== #

test_that("test-ggplot_sir.R", {
  skip_on_cran()

  if (AMR:::pkg_is_available("dplyr", min_version = "1.0.0", also_load = TRUE) &&
    AMR:::pkg_is_available("ggplot2", also_load = TRUE)) {
    pdf(NULL) # prevent Rplots.pdf being created

    # data should be equal
    expect_equal(
      (example_isolates %>%
        select(AMC, CIP) %>%
        ggplot_sir())$data %>%
        summarise_all(resistance) %>%
        as.double(),
      example_isolates %>%
        select(AMC, CIP) %>%
        summarise_all(resistance) %>%
        as.double()
    )

    expect_inherits(
      example_isolates %>%
        select(AMC, CIP) %>%
        ggplot_sir(x = "interpretation", facet = "antibiotic"),
      "gg"
    )
    expect_inherits(
      example_isolates %>%
        select(AMC, CIP) %>%
        ggplot_sir(x = "antibiotic", facet = "interpretation"),
      "gg"
    )

    expect_equal(
      (example_isolates %>%
        select(AMC, CIP) %>%
        ggplot_sir(x = "interpretation", facet = "antibiotic"))$data %>%
        summarise_all(resistance) %>%
        as.double(),
      example_isolates %>%
        select(AMC, CIP) %>%
        summarise_all(resistance) %>%
        as.double()
    )

    expect_equal(
      (example_isolates %>%
        select(AMC, CIP) %>%
        ggplot_sir(x = "antibiotic", facet = "interpretation"))$data %>%
        summarise_all(resistance) %>%
        as.double(),
      example_isolates %>%
        select(AMC, CIP) %>%
        summarise_all(resistance) %>%
        as.double()
    )

    expect_equal(
      (example_isolates %>%
        select(AMC, CIP) %>%
        ggplot_sir(x = "antibiotic", facet = "interpretation"))$data %>%
        summarise_all(count_resistant) %>%
        as.double(),
      example_isolates %>%
        select(AMC, CIP) %>%
        summarise_all(count_resistant) %>%
        as.double()
    )

    # support for scale_type ab and mo
    expect_inherits(
      (data.frame(
        mo = as.mo(c("e. coli", "s aureus")),
        n = c(40, 100)
      ) %>%
        ggplot(aes(x = mo, y = n)) +
        geom_col())$data,
      "data.frame"
    )
    expect_inherits(
      (data.frame(
        ab = as.ab(c("amx", "amc")),
        n = c(40, 100)
      ) %>%
        ggplot(aes(x = ab, y = n)) +
        geom_col())$data,
      "data.frame"
    )

    expect_inherits(
      (data.frame(
        ab = as.ab(c("amx", "amc")),
        n = c(40, 100)
      ) %>%
        ggplot(aes(x = ab, y = n)) +
        geom_col())$data,
      "data.frame"
    )

    # support for manual colours
    expect_inherits(
      suppressWarnings((ggplot(data.frame(
        x = c("Value1", "Value2", "Value3"),
        y = c(1, 2, 3),
        z = c("Value4", "Value5", "Value6")
      )) +
        geom_col(aes(x = x, y = y, fill = z)) +
        scale_sir_colours(aesthetics = "fill", Value4 = "S", Value5 = "I", Value6 = "R"))$data),
      "data.frame"
    )
  }
})