2018-12-16 22:45:12 +01:00
|
|
|
# ==================================================================== #
|
|
|
|
# TITLE #
|
2021-02-02 23:57:35 +01:00
|
|
|
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
2018-12-16 22:45:12 +01:00
|
|
|
# #
|
2019-01-02 23:24:07 +01:00
|
|
|
# SOURCE #
|
2020-07-08 14:48:06 +02:00
|
|
|
# https://github.com/msberends/AMR #
|
2018-12-16 22:45:12 +01:00
|
|
|
# #
|
|
|
|
# LICENCE #
|
2021-12-23 18:56:28 +01:00
|
|
|
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
2020-10-08 11:16:03 +02:00
|
|
|
# Developed at the University of Groningen, the Netherlands, in #
|
|
|
|
# collaboration with non-profit organisations Certe Medical #
|
|
|
|
# Diagnostics & Advice, and University Medical Center Groningen. #
|
2018-12-16 22:45:12 +01:00
|
|
|
# #
|
2019-01-02 23:24:07 +01:00
|
|
|
# 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. #
|
2020-01-05 17:22:09 +01:00
|
|
|
# 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. #
|
2020-10-08 11:16:03 +02:00
|
|
|
# #
|
|
|
|
# Visit our website for the full manual and a complete tutorial about #
|
2021-02-02 23:57:35 +01:00
|
|
|
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
2018-12-16 22:45:12 +01:00
|
|
|
# ==================================================================== #
|
|
|
|
|
2021-05-15 21:36:22 +02:00
|
|
|
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"
|
|
|
|
))
|
2018-07-08 22:14:55 +02:00
|
|
|
|
2021-05-15 21:36:22 +02:00
|
|
|
expect_equal(get_episode(test_df$date, 365),
|
|
|
|
c(1, 1, 2, 2, 2, 3, 3, 4, 1, 2, 2, 2, 3))
|
2021-11-29 11:55:18 +01:00
|
|
|
expect_equal(get_episode(test_df$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$patient_id == "B")], 365),
|
|
|
|
c(1, 2, 2, 2, 3))
|
2021-05-15 21:36:22 +02:00
|
|
|
|
2021-10-05 09:58:08 +02:00
|
|
|
if (AMR:::pkg_is_available("dplyr", min_version = "1.0.0")) {
|
2021-05-15 21:36:22 +02:00
|
|
|
expect_identical(test_df %>% group_by(patient_id) %>% mutate(f = is_new_episode(date, 365)) %>% pull(f),
|
|
|
|
c(TRUE, FALSE, TRUE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, TRUE))
|
2020-10-04 21:02:16 +02:00
|
|
|
|
2021-05-15 21:36:22 +02:00
|
|
|
suppressMessages(
|
|
|
|
x <- example_isolates %>%
|
|
|
|
mutate(out = first_isolate(., include_unknown = TRUE, method = "episode-based", info = FALSE))
|
|
|
|
)
|
|
|
|
y <- example_isolates %>%
|
|
|
|
group_by(patient_id, mo) %>%
|
|
|
|
mutate(out = is_new_episode(date, 365))
|
2020-10-04 21:02:16 +02:00
|
|
|
|
2021-05-15 21:36:22 +02:00
|
|
|
expect_identical(which(x$out), which(y$out))
|
|
|
|
}
|