(v1.6.0.9031) tinytest unit tests

2025-11-07 13:24:35 +01:00 · 2021-05-15 21:36:22 +02:00
parent 9a381c8d18
commit d8c91d5876
71 changed files with 2671 additions and 2901 deletions
--- a/inst/tinytest/test-episode.R
+++ b/inst/tinytest/test-episode.R
@@ -0,0 +1,52 @@
+# ==================================================================== #
+# 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/   #
+# ==================================================================== #
+
+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$date, 365),
+             c(1, 1, 2, 2, 2, 3, 3, 4, 1, 2, 2, 2, 3))
+
+if (suppressWarnings(require("dplyr"))) {
+  expect_identical(test_df %>% group_by(patient_id) %>% mutate(f = is_new_episode(date, 365)) %>% pull(f),
+                   c(TRUE, FALSE, TRUE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, TRUE))
+  
+  suppressMessages(
+    x <- example_isolates %>%
+      mutate(out = first_isolate(., include_unknown = TRUE, method = "episode-based", info = FALSE))
+  )
+  y <- example_isolates %>%
+    group_by(patient_id, mo) %>%
+    mutate(out = is_new_episode(date, 365))
+  
+  expect_identical(which(x$out), which(y$out))
+}