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97 lines
5.1 KiB
97 lines
5.1 KiB
# ==================================================================== # |
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# TITLE # |
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# Antimicrobial Resistance (AMR) Data Analysis for R # |
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# # |
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# SOURCE # |
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# https://github.com/msberends/AMR # |
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# # |
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# 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 # |
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# collaboration with non-profit organisations Certe Medical # |
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# Diagnostics & Advice, and University Medical Center Groningen. # |
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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://msberends.github.io/AMR/ # |
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# ==================================================================== # |
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expect_equal(count_resistant(example_isolates$AMX), count_R(example_isolates$AMX)) |
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expect_equal(count_susceptible(example_isolates$AMX), count_SI(example_isolates$AMX)) |
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expect_equal(count_all(example_isolates$AMX), n_rsi(example_isolates$AMX)) |
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# AMX resistance in `example_isolates` |
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expect_equal(count_R(example_isolates$AMX), 804) |
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expect_equal(count_I(example_isolates$AMX), 3) |
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expect_equal(suppressWarnings(count_S(example_isolates$AMX)), 543) |
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expect_equal(count_R(example_isolates$AMX) + count_I(example_isolates$AMX), |
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suppressWarnings(count_IR(example_isolates$AMX))) |
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expect_equal(suppressWarnings(count_S(example_isolates$AMX)) + count_I(example_isolates$AMX), |
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count_SI(example_isolates$AMX)) |
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# warning for speed loss |
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expect_warning(count_resistant(as.character(example_isolates$AMC))) |
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expect_warning(count_resistant(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_resistant("test", minimum = "test")) |
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expect_error(count_resistant("test", as_percent = "test")) |
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expect_error(count_susceptible("test", minimum = "test")) |
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expect_error(count_susceptible("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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if (AMR:::pkg_is_available("dplyr", min_version = "1.0.0")) { |
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expect_equal(example_isolates %>% count_susceptible(AMC), 1433) |
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expect_equal(example_isolates %>% count_susceptible(AMC, GEN, only_all_tested = TRUE), 1687) |
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expect_equal(example_isolates %>% count_susceptible(AMC, GEN, only_all_tested = FALSE), 1764) |
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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_susceptible(AMC, GEN, only_all_tested = TRUE) + |
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example_isolates %>% count_resistant(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_susceptible(CIP), |
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genta = count_susceptible(GEN), |
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combination = count_susceptible(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$AMX %>% count_susceptible(), |
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example_isolates$AMX %>% count_resistant()) |
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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(suppressWarnings(example_isolates$AMX %>% count_S()), |
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suppressWarnings(example_isolates$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(suppressWarnings(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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# grouping in rsi_calc_df() (= backbone of rsi_df()) |
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expect_true("hospital_id" %in% (example_isolates %>% |
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group_by(hospital_id) %>% |
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select(hospital_id, AMX, CIP, gender) %>% |
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rsi_df() %>% |
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colnames())) |
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}
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