Fix custom reference_data support in as.sir() (#239) (PR #279)

* Fix custom reference_data support in as.sir() (#239)

- custom guideline names now correctly classify values as R: CLSI convention
  (>= breakpoint_R for MIC, <= for disk) applies only when guideline contains
  "CLSI"; all other guidelines including custom ones use the EUCAST convention
  (> breakpoint_R for MIC, < for disk)
- guideline argument is now optional when reference_data is manually set: if
  omitted or if its value does not match any row in the custom data, all rows
  in reference_data are used; if set to a value present in the data, only
  matching rows are filtered — useful for multi-guideline custom tables
- host = NA in custom reference_data now acts as a host-agnostic fallback
  when no host-specific breakpoint row exists for the current animal species
- updated reference_data argument documentation to explain these conventions

https://claude.ai/code/session_01Q8KtFFGG9qrjAgLJBbxG2U

* Refactor R-classification logic using custom_breakpoints_set flag

Introduce custom_breakpoints_set <- !identical(reference_data, AMR::clinical_breakpoints)
at the top of as_sir_method() and replace all identical() calls inside that
function with this variable.

In the case_when_AMR interpretation blocks (MIC and disk), the R-classification
now has three explicit arms:
- !custom_breakpoints_set & EUCAST guideline -> open interval (> / <)
- !custom_breakpoints_set & CLSI guideline  -> closed interval (>= / <=)
- custom_breakpoints_set                    -> open interval (> / <), always,
  regardless of the guideline name in the custom data (e.g. "CLSI_custom"
  must not accidentally trigger CLSI convention)

https://claude.ai/code/session_01Q8KtFFGG9qrjAgLJBbxG2U

* Fix unit tests for custom reference_data (#239)

- Do not override my_bp$mo / my_bp$ab in tests: assigning plain character
  strips the <mo>/<ab> class, which check_reference_data() rejects. Use the
  mo/ab values already present in the source row instead.
- Use NA_character_ instead of NA for my_bp$host so the host column keeps
  its character class.
- Pass breakpoint_type = "animal" explicitly in the host-fallback test since
  the custom reference_data only contains animal-type breakpoints.

https://claude.ai/code/session_01Q8KtFFGG9qrjAgLJBbxG2U

* Add coerce_reference_data_columns() for lenient reference_data validation

check_reference_data() now returns the (possibly coerced) reference_data and
the call site captures the result so downstream code sees the fixed columns.

A new coerce_reference_data_columns() helper is called before the strict class
check inside check_reference_data(). It coerces columns to the expected types:
- mo  -> as.mo() if not already <mo> class
- ab  -> as.ab() if not already <ab> class
- character columns -> as.character() (e.g. host = NA becomes NA_character_)
- numeric columns  -> as.double()
- logical columns  -> as.logical()

This allows users to build a custom reference_data from a plain data.frame
without having to pre-apply as.mo()/as.ab() or worry about NA column types.

Updated the reference_data roxygen argument to document the auto-coercion and
restored the tests to the simpler form that uses plain character assignments,
relying on the new coercion instead of workarounds.

https://claude.ai/code/session_01Q8KtFFGG9qrjAgLJBbxG2U

---------

Co-authored-by: Claude <noreply@anthropic.com>

tests/testthat/test-sir.R

@@ -529,3 +529,53 @@ test_that("test-sir.R", {
     expect_lte(n_mentions, 1L)
   }
 })
+
+# issue #239 — custom reference_data support
+test_that("custom reference_data: non-EUCAST/CLSI guideline produces R", {
+  # Build a minimal one-row custom breakpoint table from a plain data.frame.
+  # coerce_reference_data_columns() will coerce mo/ab to the right class.
+  my_bp <- clinical_breakpoints[clinical_breakpoints$method == "MIC" &
+    clinical_breakpoints$type == "human", ][1, ]
+  my_bp$guideline    <- "MyLab 2025"
+  my_bp$mo           <- "B_ACHRMB_XYLS"  # plain character — coerced to <mo>
+  my_bp$ab           <- "MEM"             # plain character — coerced to <ab>
+  my_bp$breakpoint_S <- 8
+  my_bp$breakpoint_R <- 32
+
+  # guideline omitted: all rows in reference_data are used; R via open interval (>)
+  expect_equal(as.character(suppressMessages(
+    as.sir(as.mic(64), mo = "B_ACHRMB_XYLS", ab = "MEM", reference_data = my_bp)
+  )), "R")
+  expect_equal(as.character(suppressMessages(
+    as.sir(as.mic(16), mo = "B_ACHRMB_XYLS", ab = "MEM", reference_data = my_bp)
+  )), "I")
+  # at R breakpoint value must be I (open interval: > not >=)
+  expect_equal(as.character(suppressMessages(
+    as.sir(as.mic(32), mo = "B_ACHRMB_XYLS", ab = "MEM", reference_data = my_bp)
+  )), "I")
+
+  # guideline explicitly set: same result when it matches the data
+  expect_equal(as.character(suppressMessages(
+    as.sir(as.mic(64), mo = "B_ACHRMB_XYLS", ab = "MEM",
+      guideline = "MyLab 2025", reference_data = my_bp)
+  )), "R")
+})
+
+test_that("custom reference_data: host = NA acts as host-agnostic fallback", {
+  my_bp <- clinical_breakpoints[clinical_breakpoints$method == "MIC" &
+    clinical_breakpoints$type == "human", ][1, ]
+  my_bp$guideline    <- "MyLab 2025"
+  my_bp$mo           <- "B_ACHRMB_XYLS"
+  my_bp$ab           <- "MEM"
+  my_bp$type         <- "animal"
+  my_bp$host         <- NA  # logical NA — coerced to character by coerce_reference_data_columns()
+  my_bp$breakpoint_S <- 8
+  my_bp$breakpoint_R <- 32
+
+  # NA host should match when no species-specific row exists
+  result <- suppressMessages(
+    as.sir(as.mic(64), mo = "B_ACHRMB_XYLS", ab = "MEM",
+      host = "dogs", breakpoint_type = "animal", reference_data = my_bp)
+  )
+  expect_equal(as.character(result), "R")
+})