Fix 0.5.0 release blockers from the release review

.gitignore

@@ -16,8 +16,7 @@ CLAUDE.md
 # macOS
 .DS_Store
 
-# Generated documentation
-man/*.Rd
+# Generated documentation (man/*.Rd is committed so GitHub installs have help pages)
 docs/
 
 # Quarto/HTML output

NEWS.md

@@ -38,6 +38,11 @@
   `variable_details = NULL`, detail-level-only `databaseStart`, or another
   unsupported variable) on metadata that sets `anchor`, `create_mock_data()`
   stops and names the survival variables rather than dropping them.
+- The same applies to formula variables. If the legacy generator is
+  selected for metadata that sets `mockFormula` on an enabled variable,
+  `create_mock_data()` stops and names the formula variables. Previously the
+  legacy generator ignored the formula and returned unrelated random values,
+  or dropped a `DerivedVar::` variable, without saying so.
 
 ## New features
 
@@ -109,10 +114,11 @@
   an integer range now fails with a message naming the variable. (#58)
 - The packaged minimal example corrects two metadata errors: BMI's low
   garbage range had a stray parenthesis (`[-10;15])`), and height's
-  low-garbage proportion was 1.00 (every row) instead of 0.01. With these
-  and #58, every variable in the example except its survival dates now
-  generates through the v0.4 pipeline. Seeded output for the example
-  changes.
+  low-garbage proportion was 1.00 (every row) instead of 0.01; height's
+  high-garbage range had an infinite upper bound, `(2.1;inf]`, which
+  produced `NaN` values, and is now `(2.1;2.5]` (#60). With these, #58 and
+  the survival dates (#40), every variable in the example generates through
+  the v0.4 pipeline. Seeded output for the example changes.
 
 ## Deprecations
 

R/create_mock_data.R

@@ -48,6 +48,30 @@
   names(spec$variables)[unsupported]
 }
 
+#' @noRd
+.legacy_route_reasons <- function() {
+  paste0(
+    "It is used when validate = FALSE, when variable_details is NULL, when ",
+    "only variable_details has a databaseStart column, or when another ",
+    "variable uses a feature the v0.4 pipeline does not support. Run with ",
+    "verbose = TRUE to see which."
+  )
+}
+
+#' @noRd
+.legacy_formula_variables <- function(enabled_vars, variable_details, databaseStart) {
+  # Enabled variables with a non-blank mockFormula for the requested
+  # database, using the same lookup as the v0.4 adapter's carve-out.
+  if (is.null(variable_details) || !"mockFormula" %in% names(variable_details)) {
+    return(character(0))
+  }
+  database <- if ("databaseStart" %in% names(variable_details)) databaseStart else NULL
+  Filter(function(variable) {
+    details <- .filter_recodeflow_details(variable_details, variable, database)
+    !.is_blank(suppressWarnings(.details_mock_formula(details)))
+  }, as.character(enabled_vars$variable))
+}
+
 #' @noRd
 .has_survival_metadata <- function(variables) {
   # A row sets anchor, or carries survival parameters (followup_min,
@@ -371,6 +395,20 @@ create_mock_data <- function(databaseStart,
     enabled_vars <- variables
   }
 
+  # Formula variables are computed only by the v0.4 pipeline; the legacy
+  # dispatcher ignores mockFormula and would return unrelated random values,
+  # or drop a DerivedVar:: variable, without saying so. Checked before the
+  # derived exclusion below, which would otherwise hide DerivedVar:: rows.
+  formula_vars <- .legacy_formula_variables(enabled_vars, variable_details, databaseStart)
+  if (length(formula_vars) > 0) {
+    stop(
+      "Formula variable(s) ", paste(formula_vars, collapse = ", "),
+      " (mockFormula set) are computed only by the v0.4 pipeline, but the ",
+      "legacy generator was selected. ", .legacy_route_reasons(),
+      call. = FALSE
+    )
+  }
+
   # Exclude derived variables (identified by DerivedVar:: and Func:: patterns)
   if (!is.null(variable_details)) {
     derived_vars <- identify_derived_vars(enabled_vars, variable_details)
@@ -398,10 +436,7 @@ create_mock_data <- function(databaseStart,
       stop(
         "Survival date variable(s) ", paste(anchored, collapse = ", "),
         " (anchor set) are generated only by the v0.4 pipeline, but the ",
-        "legacy generator was selected. It is used when validate = FALSE, ",
-        "when variable_details is NULL, when only variable_details has a ",
-        "databaseStart column, or when another variable uses a feature the ",
-        "v0.4 pipeline does not support. Run with verbose = TRUE to see which.",
+        "legacy generator was selected. ", .legacy_route_reasons(),
         call. = FALSE
       )
     }

README.md

@@ -193,16 +193,18 @@ mock_data <- create_mock_data(
   seed = 123
 )
 
-head(mock_data)
-#>  age smoking interview_date
-#> 1  42       2     2001-08-05
-#> 2  47       2     2002-11-27
-#> 3  73       3     2002-11-14
-#> 4  51       1     2005-01-14
-#> 5  52       1     2001-02-25
-#> 6  76       3     2004-07-25
+head(mock_data[, c("age", "smoking", "BMI", "interview_date", "death_date")])
+#>   age smoking       BMI interview_date death_date
+#> 1  35       3 996.00000     2004-10-20       <NA>
+#> 2 999       1  31.52719     2004-01-11       <NA>
+#> 3  72       1  21.02576     2002-01-21       <NA>
+#> 4 997       2  28.36755     2004-06-25       <NA>
+#> 5  55       1  29.52888     2001-02-22       <NA>
+#> 6 998       3  25.80269     2004-01-12 2005-01-11
 ```
 
+The minimal example generates all of its variables; this shows five of them. Values such as 996 and 999 are missing codes declared by the metadata's `NA::` rows.
+
 **What's in those CSV files?** See [inst/extdata/minimal-example/](inst/extdata/minimal-example/README.md) - just variable names, types, ranges, and optional mock-data parameters.
 
 **When should you use metadata files?**

inst/extdata/minimal-example/variables.csv

@@ -2,7 +2,7 @@
 "cchsflow_v0001","age","Age in years","Continuous","integer","enabled,predictor,table1",10,10,,"[;]",,"[;]","normal",50,15,,,,,,"","","","1.0.0","2025-11-09","Normal distribution (mean=50, sd=15)"
 "cchsflow_v0002","smoking","Smoking status","Categorical","factor","enabled,predictor,table1",20,20,,"",,"","",,,,,,,,"","","","1.0.0","2025-11-09","Categorical variable with proportions"
 "cchsflow_v0003","BMI","Body mass index","Continuous","double","enabled,outcome,table1",30,30,0.02,"[-10;15]",0.01,"[60;150]","normal",27.5,5.2,,,,,,"","","","1.0.0","2025-11-09","Normal distribution with two-sided contamination"
-"cchsflow_v0004","height","Height in meters","Continuous","double","enabled,predictor",40,40,0.01,"[0;1.4)",0.01,"(2.1;inf]","normal",1.7,0.1,,,,,,"","","","1.0.0","2025-11-13","Height for BMI calculation"
+"cchsflow_v0004","height","Height in meters","Continuous","double","enabled,predictor",40,40,0.01,"[0;1.4)",0.01,"(2.1;2.5]","normal",1.7,0.1,,,,,,"","","","1.0.0","2025-11-13","Height for BMI calculation"
 "cchsflow_v0005","weight","Weight in kilograms","Continuous","double","enabled,predictor",50,50,,"[;]",,"[;]","normal",75,15,,,,,,"","","","1.0.0","2025-11-13","Weight for BMI calculation"
 "cchsflow_v0006","BMI_derived","BMI calculated from height and weight","Continuous","double","enabled,outcome,table1",60,60,,"[;]",,"[;]","",,,,,,,,"","","","1.0.0","2025-11-13","Derived variable: BMI = weight / (height^2)"
 "ices_v01","interview_date","Interview date (cohort entry)","Continuous","date","enabled,outcome",70,70,0,"[;]",0,"[;]","uniform",,,,,,,,"","","analysis","1.0.0","2025-11-09","Uniform date range (cohort entry)"