(v2.1.1.9256) unit tests

tests/testthat/test-ab.R

@@ -41,10 +41,9 @@ test_that("test-ab.R", {
       "ERYT",
       "ERY",
       "erytromicine",
-      "Erythrocin",
-      "Romycin"
+      "Erythrocin"
     ))),
-    rep("ERY", 9)
+    rep("ERY", 8)
   )
 
   expect_identical(class(as.ab("amox")), c("ab", "character"))

tests/testthat/test-antibiogram.R

@@ -39,8 +39,7 @@ test_that("test-antibiogram.R", {
   ab2 <- antibiogram(example_isolates,
     antimicrobials = aminoglycosides(),
     ab_transform = "atc",
-    mo_transform = "gramstain",
-    add_total_n = TRUE
+    mo_transform = "gramstain"
   )
 
   ab3 <- antibiogram(example_isolates,

tests/testthat/test-resistance_predict.R

@@ -1,124 +0,0 @@
-# ==================================================================== #
-# TITLE:                                                               #
-# AMR: An R Package for Working with Antimicrobial Resistance Data     #
-#                                                                      #
-# SOURCE CODE:                                                         #
-# https://github.com/msberends/AMR                                     #
-#                                                                      #
-# PLEASE CITE THIS SOFTWARE AS:                                        #
-# Berends MS, Luz CF, Friedrich AW, et al. (2022).                     #
-# AMR: An R Package for Working with Antimicrobial Resistance Data.    #
-# Journal of Statistical Software, 104(3), 1-31.                       #
-# https://doi.org/10.18637/jss.v104.i03                                #
-#                                                                      #
-# Developed at the University of Groningen and the University Medical  #
-# Center Groningen in The Netherlands, in collaboration with many      #
-# colleagues from around the world, see our website.                   #
-#                                                                      #
-# 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://amr-for-r.org              #
-# ==================================================================== #
-
-test_that("test-resistance_predict.R", {
-  skip_on_cran()
-
-  if (AMR:::pkg_is_available("dplyr", min_version = "1.0.0", also_load = TRUE)) {
-    expect_output(AMX_R <- example_isolates %>%
-      filter(mo == "B_ESCHR_COLI") %>%
-      sir_predict(
-        col_ab = "AMX",
-        col_date = "date",
-        model = "binomial",
-        minimum = 10,
-        info = TRUE
-      ) %>%
-      pull("value"))
-    # AMX resistance will increase according to data set `example_isolates`
-    expect_true(AMX_R[3] < AMX_R[20])
-  }
-
-  expect_output(x <- suppressMessages(resistance_predict(example_isolates,
-    col_ab = "AMX",
-    year_min = 2010,
-    model = "binomial",
-    info = TRUE
-  )))
-  pdf(NULL) # prevent Rplots.pdf being created
-  expect_silent(plot(x))
-  if (AMR:::pkg_is_available("ggplot2")) {
-    expect_silent(ggplot_sir_predict(x))
-    expect_silent(ggplot2::autoplot(x))
-    expect_error(ggplot_sir_predict(example_isolates))
-  }
-  expect_output(sir_predict(
-    x = subset(example_isolates, mo == "B_ESCHR_COLI"),
-    model = "binomial",
-    col_ab = "AMX",
-    col_date = "date",
-    info = TRUE
-  ))
-  expect_output(sir_predict(
-    x = subset(example_isolates, mo == "B_ESCHR_COLI"),
-    model = "loglin",
-    col_ab = "AMX",
-    col_date = "date",
-    info = TRUE
-  ))
-  expect_output(sir_predict(
-    x = subset(example_isolates, mo == "B_ESCHR_COLI"),
-    model = "lin",
-    col_ab = "AMX",
-    col_date = "date",
-    info = TRUE
-  ))
-
-  expect_error(sir_predict(
-    x = subset(example_isolates, mo == "B_ESCHR_COLI"),
-    model = "INVALID MODEL",
-    col_ab = "AMX",
-    col_date = "date",
-    info = TRUE
-  ))
-  expect_error(sir_predict(
-    x = subset(example_isolates, mo == "B_ESCHR_COLI"),
-    model = "binomial",
-    col_ab = "NOT EXISTING COLUMN",
-    col_date = "date",
-    info = TRUE
-  ))
-  expect_error(sir_predict(
-    x = subset(example_isolates, mo == "B_ESCHR_COLI"),
-    model = "binomial",
-    col_ab = "AMX",
-    col_date = "NOT EXISTING COLUMN",
-    info = TRUE
-  ))
-  expect_error(sir_predict(
-    x = subset(example_isolates, mo == "B_ESCHR_COLI"),
-    col_ab = "AMX",
-    col_date = "NOT EXISTING COLUMN",
-    info = TRUE
-  ))
-  expect_error(sir_predict(
-    x = subset(example_isolates, mo == "B_ESCHR_COLI"),
-    col_ab = "AMX",
-    col_date = "date",
-    info = TRUE
-  ))
-  # almost all E. coli are MEM S in the Netherlands :)
-  expect_error(resistance_predict(
-    x = subset(example_isolates, mo == "B_ESCHR_COLI"),
-    model = "binomial",
-    col_ab = "MEM",
-    col_date = "date",
-    info = TRUE
-  ))
-})

tests/testthat/test-sir.R

@@ -325,12 +325,14 @@ test_that("test-sir.R", {
   expect_message(as.sir(data.frame(
     mo = "E. coli",
     NIT = c("<= 2", 32),
-    uti = TRUE
+    uti = TRUE,
+    info = TRUE
   )))
   expect_message(as.sir(data.frame(
     mo = "E. coli",
     NIT = c("<= 2", 32),
-    specimen = c("urine", "blood")
+    specimen = c("urine", "blood"),
+    info = TRUE
   )))
 
   # SDD vs I in CLSI 2024