1
0
mirror of https://github.com/msberends/AMR.git synced 2024-12-27 22:46:11 +01:00
AMR/tests/testthat/test-is_new_episode.R

56 lines
2.6 KiB
R
Raw Normal View History

2020-11-23 21:50:27 +01:00
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
# #
# LICENCE #
# (c) 2018-2020 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 analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
context("is_new_episode.R")
test_that("new episodes work", {
skip_on_cran()
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"
))
library(dplyr)
expect_identical(test_df %>% group_by(patient_id) %>% mutate(f = is_new_episode(date)) %>% 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, info = FALSE))
)
y <- example_isolates %>%
group_by(patient_id, mo) %>%
mutate(out = is_new_episode(date))
expect_identical(which(x$out), which(y$out))
})