AMR/tests/testthat/test-ggplot_rsi.R

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# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
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# SOURCE #
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# https://github.com/msberends/AMR #
# #
# LICENCE #
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# (c) 2018-2021 Berends MS, Luz CF et al. #
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# Developed at the University of Groningen, the Netherlands, in #
# collaboration with non-profit organisations Certe Medical #
# Diagnostics & Advice, and University Medical Center Groningen. #
# #
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# 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. #
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# #
# Visit our website for the full manual and a complete tutorial about #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
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context("ggplot_rsi.R")
test_that("ggplot_rsi works", {
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skip_on_cran()
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skip_if_not_installed("ggplot2")
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skip_if_not_installed("dplyr")
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if (require("dplyr") & require("ggplot2")) {
pdf(NULL) # prevent Rplots.pdf being created
# data should be equal
expect_equal(
(example_isolates %>% select(AMC, CIP) %>% ggplot_rsi())$data %>% summarise_all(resistance) %>% as.double(),
example_isolates %>% select(AMC, CIP) %>% summarise_all(resistance) %>% as.double()
)
print(example_isolates %>% select(AMC, CIP) %>% ggplot_rsi(x = "interpretation", facet = "antibiotic"))
print(example_isolates %>% select(AMC, CIP) %>% ggplot_rsi(x = "antibiotic", facet = "interpretation"))
expect_equal(
(example_isolates %>% select(AMC, CIP) %>% ggplot_rsi(x = "interpretation", facet = "antibiotic"))$data %>% summarise_all(resistance) %>% as.double(),
example_isolates %>% select(AMC, CIP) %>% summarise_all(resistance) %>% as.double()
)
expect_equal(
(example_isolates %>% select(AMC, CIP) %>% ggplot_rsi(x = "antibiotic", facet = "interpretation"))$data %>% summarise_all(resistance) %>% as.double(),
example_isolates %>% select(AMC, CIP) %>% summarise_all(resistance) %>% as.double()
)
expect_equal(
(example_isolates %>% select(AMC, CIP) %>% ggplot_rsi(x = "antibiotic", facet = "interpretation"))$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_equal(class((data.frame(mo = as.mo(c("e. coli", "s aureus")),
n = c(40, 100)) %>%
ggplot(aes(x = mo, y = n)) +
geom_col())$data),
"data.frame")
expect_equal(class((data.frame(ab = as.ab(c("amx", "amc")),
n = c(40, 100)) %>%
ggplot(aes(x = ab, y = n)) +
geom_col())$data),
"data.frame")
expect_equal(class((data.frame(ab = as.ab(c("amx", "amc")),
n = c(40, 100)) %>%
ggplot(aes(x = ab, y = n)) +
geom_col())$data),
"data.frame")
# support for manual colours
expect_equal(class((ggplot(data.frame(x = c("Value1", "Value2", "Value3"),
y = c(1, 2, 3),
z = c("Value4", "Value5", "Value6"))) +
geom_col(aes(x = x, y = y, fill = z)) +
scale_rsi_colours(Value4 = "S", Value5 = "I", Value6 = "R"))$data),
"data.frame")
}
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})