(v3.0.1.9090) unit test

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: AMR
-Version: 3.0.1.9089
-Date: 2026-09-03
+Version: 3.0.1.9090
+Date: 2026-09-04
 Title: Antimicrobial Resistance Data Analysis
 Description: Functions to simplify and standardise antimicrobial resistance (AMR)
   data analysis and to work with microbial and antimicrobial properties by

NEWS.md

@@ -1,4 +1,4 @@
-# AMR 3.0.1.9089
+# AMR 3.0.1.9090
 
 Planned as v3.1.0, end of September 2026.
 

R/aa_helper_functions.R

@@ -972,10 +972,14 @@ meet_criteria <- function(object, # can be literally `list(...)` for `allow_argu
     if ("logical" %in% allow_class) {
       or_values <- paste0(or_values, ", or TRUE or FALSE")
     }
-    stop_ifnot(all(object %in% is_in.bak, na.rm = TRUE), "argument {.arg ", obj_name, "} ",
-      ifelse(!is.null(has_length) && length(has_length) == 1 && has_length == 1,
-        "must be either ",
-        "must only contain values "
+    stop_ifnot(all(object %in% is_in.bak, na.rm = TRUE),
+      "argument {.arg ", obj_name, "} ",
+      ifelse(!is.null(has_length) && length(has_length) == 1 && has_length == 1 && length(is_in.bak) == 1,
+        "must be ",
+        ifelse(!is.null(has_length) && length(has_length) == 1 && has_length == 1,
+          "must be either ",
+          "must only contain values "
+        )
       ),
       or_values,
       ifelse(allow_NA == TRUE, ", or NA", ""),

tests/testthat/test-interpretive_rules.R

@@ -108,17 +108,17 @@ test_that("test-interpretive_rules.R", {
   )
   expect_equal(suppressWarnings(interpretive_rules(a, "mo", info = FALSE)), b)
 
-  # piperacillin must be R in Enterobacteriaceae when tica is R
+  # piperacillin must be R in E. coli when ampi is R
   if (AMR:::pkg_is_available("dplyr", min_version = "1.0.0", also_load = TRUE)) {
     expect_equal(
       suppressWarnings(
         example_isolates %>%
-          filter(mo_family(mo) == "Enterobacteriaceae") %>%
+          filter(mo_name(mo) == "Escherichia coli") %>%
           mutate(
-            TIC = as.sir("R"),
-            PIP = as.sir("S")
+            AMP = as.sir("R"),
+            PIP = as.sir(NA)
           ) %>%
-          interpretive_rules(col_mo = "mo", version_expertrules = 3.1, rules = "expert", info = FALSE, overwrite = TRUE) %>%
+          interpretive_rules(col_mo = "mo", version_expertrules = 3.3, rules = "expert", info = FALSE, overwrite = TRUE) %>%
           pull(PIP) %>%
           unique() %>%
           as.character()