AMR/inst/tinytest/test-episode.R

70 lines
3.2 KiB
R

# ==================================================================== #
# TITLE #
# AMR: An R Package for Working with Antimicrobial Resistance Data #
# #
# SOURCE #
# https://github.com/msberends/AMR #
# #
# CITE AS #
# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
# (2022). AMR: An R Package for Working with Antimicrobial Resistance #
# Data. Journal of Statistical Software, 104(3), 1-31. #
# doi:10.18637/jss.v104.i03 #
# #
# 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/ #
# ==================================================================== #
test_df <- rbind(
data.frame(
date = as.Date(c("2015-01-01", "2015-10-01", "2016-02-04", "2016-12-31", "2017-01-01", "2017-02-01", "2017-02-05", "2020-01-01")),
patient_id = "A"
),
data.frame(
date = as.Date(c("2015-01-01", "2016-02-01", "2016-12-31", "2017-01-01", "2017-02-03")),
patient_id = "B"
)
)
expect_equal(
get_episode(test_df$date, 365),
c(1, 1, 2, 2, 2, 3, 3, 4, 1, 2, 2, 2, 3)
)
expect_equal(
get_episode(test_df$date[which(test_df$patient_id == "A")], 365),
c(1, 1, 2, 2, 2, 2, 3, 4)
)
expect_equal(
get_episode(test_df$date[which(test_df$patient_id == "B")], 365),
c(1, 2, 2, 2, 3)
)
if (AMR:::pkg_is_available("dplyr", min_version = "1.0.0")) {
expect_identical(
test_df %>% group_by(patient_id) %>% mutate(f = is_new_episode(date, 365)) %>% pull(f),
c(TRUE, FALSE, TRUE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, TRUE)
)
suppressMessages(
x <- example_isolates %>%
mutate(out = first_isolate(., include_unknown = TRUE, method = "episode-based", info = FALSE))
)
y <- example_isolates %>%
group_by(patient, mo) %>%
mutate(out = is_new_episode(date, 365))
expect_identical(which(x$out), which(y$out))
}