mirror of https://github.com/msberends/AMR.git
91 lines
4.3 KiB
R
91 lines
4.3 KiB
R
# ==================================================================== #
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# TITLE #
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# Antimicrobial Resistance (AMR) Analysis #
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# #
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# SOURCE #
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# https://gitlab.com/msberends/AMR #
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# #
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# LICENCE #
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# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
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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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# #
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# This R package was created for academic research and was publicly #
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# released in the hope that it will be useful, but it comes WITHOUT #
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# ANY WARRANTY OR LIABILITY. #
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# Visit our website for more info: https://msberends.gitlab.io/AMR. #
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# ==================================================================== #
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context("count.R")
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test_that("counts work", {
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# AMX resistance in `example_isolates`
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expect_equal(count_R(example_isolates$AMX), 683)
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expect_equal(count_I(example_isolates$AMX), 3)
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expect_equal(count_S(example_isolates$AMX), 543)
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expect_equal(count_R(example_isolates$AMX) + count_I(example_isolates$AMX),
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count_IR(example_isolates$AMX))
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expect_equal(count_S(example_isolates$AMX) + count_I(example_isolates$AMX),
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count_SI(example_isolates$AMX))
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library(dplyr)
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expect_equal(example_isolates %>% count_S(AMC), 1342)
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expect_equal(example_isolates %>% count_S(AMC, GEN, only_all_tested = TRUE), 1660)
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expect_equal(example_isolates %>% count_S(AMC, GEN, only_all_tested = FALSE), 1728)
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expect_equal(example_isolates %>% count_all(AMC, GEN, only_all_tested = TRUE), 1798)
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expect_equal(example_isolates %>% count_all(AMC, GEN, only_all_tested = FALSE), 1936)
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expect_identical(example_isolates %>% count_all(AMC, GEN, only_all_tested = TRUE),
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example_isolates %>% count_S(AMC, GEN, only_all_tested = TRUE) +
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example_isolates %>% count_IR(AMC, GEN, only_all_tested = TRUE))
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# count of cases
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expect_equal(example_isolates %>%
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group_by(hospital_id) %>%
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summarise(cipro = count_SI(CIP),
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genta = count_SI(GEN),
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combination = count_SI(CIP, GEN)) %>%
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pull(combination),
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c(253, 465, 192, 558))
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# count_df
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expect_equal(
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example_isolates %>% select(AMX) %>% count_df() %>% pull(value),
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c(example_isolates$AMX %>% count_SI(),
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example_isolates$AMX %>% count_R())
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)
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expect_equal(
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example_isolates %>% select(AMX) %>% count_df(combine_IR = TRUE) %>% pull(value),
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c(example_isolates$AMX %>% count_S(),
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example_isolates$AMX %>% count_IR())
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)
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expect_equal(
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example_isolates %>% select(AMX) %>% count_df(combine_SI = FALSE) %>% pull(value),
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c(example_isolates$AMX %>% count_S(),
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example_isolates$AMX %>% count_I(),
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example_isolates$AMX %>% count_R())
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)
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# warning for speed loss
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expect_warning(count_R(as.character(example_isolates$AMC)))
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expect_warning(count_I(as.character(example_isolates$AMC)))
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expect_warning(count_S(as.character(example_isolates$AMC,
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example_isolates$GEN)))
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expect_warning(count_S(example_isolates$AMC,
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as.character(example_isolates$GEN)))
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# check for errors
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expect_error(count_IR("test", minimum = "test"))
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expect_error(count_IR("test", as_percent = "test"))
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expect_error(count_I("test", minimum = "test"))
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expect_error(count_I("test", as_percent = "test"))
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expect_error(count_S("test", minimum = "test"))
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expect_error(count_S("test", as_percent = "test"))
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expect_error(count_df(c("A", "B", "C")))
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expect_error(count_df(example_isolates[,"date"]))
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})
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