You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.

125 lines
6.3 KiB

# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
# #
# LICENCE #
# (c) 2018-2021 Berends MS, Luz CF et al. #
# Developed at the University of Groningen, the Netherlands, in #
# collaboration with non-profit organisations Certe Medical #
# Diagnostics & Advice, and University Medical Center Groningen. #
# #
# 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://msberends.github.io/AMR/ #
# ==================================================================== #
expect_equal(proportion_R(example_isolates$AMX), resistance(example_isolates$AMX))
expect_equal(proportion_SI(example_isolates$AMX), susceptibility(example_isolates$AMX))
# AMX resistance in `example_isolates`
expect_equal(proportion_R(example_isolates$AMX), 0.5955556, tolerance = 0.0001)
expect_equal(proportion_I(example_isolates$AMX), 0.002222222, tolerance = 0.0001)
expect_equal(1 - proportion_R(example_isolates$AMX) - proportion_I(example_isolates$AMX),
proportion_S(example_isolates$AMX))
expect_equal(proportion_R(example_isolates$AMX) + proportion_I(example_isolates$AMX),
proportion_IR(example_isolates$AMX))
expect_equal(proportion_S(example_isolates$AMX) + proportion_I(example_isolates$AMX),
proportion_SI(example_isolates$AMX))
if (AMR:::pkg_is_available("dplyr", min_version = "1.0.0")) {
expect_equal(example_isolates %>% proportion_SI(AMC),
0.7626397,
tolerance = 0.0001)
expect_equal(example_isolates %>% proportion_SI(AMC, GEN),
0.9408,
tolerance = 0.0001)
expect_equal(example_isolates %>% proportion_SI(AMC, GEN, only_all_tested = TRUE),
0.9382647,
tolerance = 0.0001)
# percentages
expect_equal(example_isolates %>%
group_by(hospital_id) %>%
summarise(R = proportion_R(CIP, as_percent = TRUE),
I = proportion_I(CIP, as_percent = TRUE),
S = proportion_S(CIP, as_percent = TRUE),
n = n_rsi(CIP),
total = n()) %>%
pull(n) %>%
sum(),
1409)
# count of cases
expect_equal(example_isolates %>%
group_by(hospital_id) %>%
summarise(cipro_p = proportion_SI(CIP, as_percent = TRUE),
cipro_n = n_rsi(CIP),
genta_p = proportion_SI(GEN, as_percent = TRUE),
genta_n = n_rsi(GEN),
combination_p = proportion_SI(CIP, GEN, as_percent = TRUE),
combination_n = n_rsi(CIP, GEN)) %>%
pull(combination_n),
c(305, 617, 241, 711))
# proportion_df
expect_equal(
example_isolates %>% select(AMX) %>% proportion_df() %>% pull(value),
c(example_isolates$AMX %>% proportion_SI(),
example_isolates$AMX %>% proportion_R())
)
expect_equal(
example_isolates %>% select(AMX) %>% proportion_df(combine_IR = TRUE) %>% pull(value),
c(example_isolates$AMX %>% proportion_S(),
example_isolates$AMX %>% proportion_IR())
)
expect_equal(
example_isolates %>% select(AMX) %>% proportion_df(combine_SI = FALSE) %>% pull(value),
c(example_isolates$AMX %>% proportion_S(),
example_isolates$AMX %>% proportion_I(),
example_isolates$AMX %>% proportion_R())
)
}
expect_warning(proportion_R(as.character(example_isolates$AMC)))
expect_warning(proportion_S(as.character(example_isolates$AMC)))
expect_warning(proportion_S(as.character(example_isolates$AMC,
example_isolates$GEN)))
expect_warning(n_rsi(as.character(example_isolates$AMC,
example_isolates$GEN)))
expect_equal(suppressWarnings(n_rsi(as.character(example_isolates$AMC,
example_isolates$GEN))),
1879)
# check for errors
expect_error(proportion_IR("test", minimum = "test"))
expect_error(proportion_IR("test", as_percent = "test"))
expect_error(proportion_I("test", minimum = "test"))
expect_error(proportion_I("test", as_percent = "test"))
expect_error(proportion_S("test", minimum = "test"))
expect_error(proportion_S("test", as_percent = "test"))
expect_error(proportion_S("test", also_single_tested = TRUE))
# check too low amount of isolates
expect_identical(suppressWarnings(proportion_R(example_isolates$AMX, minimum = nrow(example_isolates) + 1)),
NA_real_)
expect_identical(suppressWarnings(proportion_I(example_isolates$AMX, minimum = nrow(example_isolates) + 1)),
NA_real_)
expect_identical(suppressWarnings(proportion_S(example_isolates$AMX, minimum = nrow(example_isolates) + 1)),
NA_real_)
# warning for speed loss
expect_warning(proportion_R(as.character(example_isolates$GEN)))
expect_warning(proportion_I(as.character(example_isolates$GEN)))
expect_warning(proportion_S(example_isolates$AMC, as.character(example_isolates$GEN)))
expect_error(proportion_df(c("A", "B", "C")))
expect_error(proportion_df(example_isolates[, "date"]))