# ==================================================================== # # TITLE # # Antimicrobial Resistance (AMR) 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 analysis: https://msberends.github.io/AMR/ # # ==================================================================== # context("first_isolate.R") test_that("first isolates work", { skip_on_cran() # first isolates expect_equal( sum( first_isolate(x = example_isolates, col_date = "date", col_patient_id = "patient_id", col_mo = "mo", info = TRUE), na.rm = TRUE), 1300) # first weighted isolates ex_iso_with_keyab <- example_isolates ex_iso_with_keyab$keyab <- key_antibiotics(example_isolates, warnings = FALSE) expect_equal( suppressWarnings( sum( first_isolate(x = ex_iso_with_keyab, # let syntax determine arguments automatically type = "keyantibiotics", info = TRUE), na.rm = TRUE)), 1396) # when not ignoring I expect_equal( suppressWarnings( sum( first_isolate(x = ex_iso_with_keyab, col_date = "date", col_patient_id = "patient_id", col_mo = "mo", col_keyantibiotics = "keyab", ignore_I = FALSE, type = "keyantibiotics", info = TRUE), na.rm = TRUE)), 1419) # when using points expect_equal( suppressWarnings( sum( first_isolate(x = ex_iso_with_keyab, col_date = "date", col_patient_id = "patient_id", col_mo = "mo", col_keyantibiotics = "keyab", type = "points", info = TRUE), na.rm = TRUE)), 1399) # first non-ICU isolates expect_equal( sum( first_isolate(example_isolates, col_mo = "mo", col_date = "date", col_patient_id = "patient_id", col_icu = "ward_icu", info = TRUE, icu_exclude = TRUE), na.rm = TRUE), 881) # set 1500 random observations to be of specimen type 'Urine' random_rows <- sample(x = 1:2000, size = 1500, replace = FALSE) x <- example_isolates x$specimen <- "Other" x[random_rows, "specimen"] <- "Urine" expect_lt( sum( first_isolate(x = x, col_date = "date", col_patient_id = "patient_id", col_mo = "mo", col_specimen = "specimen", filter_specimen = "Urine", info = TRUE), na.rm = TRUE), 1501) # same, but now exclude ICU expect_lt( sum( first_isolate(x = x, col_date = "date", col_patient_id = "patient_id", col_mo = "mo", col_specimen = "specimen", filter_specimen = "Urine", col_icu = "ward_icu", icu_exclude = TRUE, info = TRUE), na.rm = TRUE), 1501) # "No isolates found" test_iso <- example_isolates test_iso$specimen <- "test" expect_message(first_isolate(test_iso, "date", "patient_id", col_mo = "mo", col_specimen = "specimen", filter_specimen = "something_unexisting", info = TRUE)) # printing of exclusion message expect_message(first_isolate(example_isolates, col_date = "date", col_mo = "mo", col_patient_id = "patient_id", col_testcode = "gender", testcodes_exclude = "M", info = TRUE)) # errors expect_error(first_isolate("date", "patient_id", col_mo = "mo")) expect_error(first_isolate(example_isolates, col_date = "non-existing col", col_mo = "mo")) require("dplyr") # if mo is not an mo class, result should be the same expect_identical(example_isolates %>% mutate(mo = as.character(mo)) %>% first_isolate(col_date = "date", col_mo = "mo", col_patient_id = "patient_id"), example_isolates %>% first_isolate(col_date = "date", col_mo = "mo", col_patient_id = "patient_id")) # support for WHONET expect_message(example_isolates %>% select(-patient_id) %>% mutate(`First name` = "test", `Last name` = "test", Sex = "Female") %>% first_isolate(info = TRUE)) # missing dates should be no problem df <- example_isolates df[1:100, "date"] <- NA expect_equal( sum( first_isolate(x = df, col_date = "date", col_patient_id = "patient_id", col_mo = "mo", info = TRUE), na.rm = TRUE), 1305) # unknown MOs test_unknown <- example_isolates test_unknown$mo <- ifelse(test_unknown$mo == "B_ESCHR_COLI", "UNKNOWN", test_unknown$mo) expect_equal(sum(first_isolate(test_unknown, include_unknown = FALSE)), 1045) expect_equal(sum(first_isolate(test_unknown, include_unknown = TRUE)), 1528) test_unknown$mo <- ifelse(test_unknown$mo == "UNKNOWN", NA, test_unknown$mo) expect_equal(sum(first_isolate(test_unknown)), 1045) # shortcuts expect_identical(filter_first_isolate(example_isolates), subset(example_isolates, first_isolate(example_isolates))) ex <- example_isolates ex$keyab <- key_antibiotics(ex) expect_identical(filter_first_weighted_isolate(example_isolates), subset(example_isolates, first_isolate(ex))) # notice that all mo's are distinct, so all are TRUE expect_true(all(example_isolates %pm>% pm_distinct(mo, .keep_all = TRUE) %pm>% first_isolate(info = TRUE) == TRUE)) # only one isolate, so return fast expect_true(first_isolate(data.frame(mo = "Escherichia coli", date = Sys.Date(), patient = "patient"), info = TRUE)) })