Fix serial-path reproducibility for L'Ecuyer-CMRG (list) seeds

NEWS.md

@@ -2,6 +2,13 @@
 
 ## Changes in SimDesign 2.25
 
+- Fixed a bug where list-based (L'Ecuyer-CMRG) seeds were not applied on the
+  serial (non-parallel) execution path, causing `runArraySimulation(..., iseed)`
+  and `runSimulation(seed = <genSeeds() list>)` to be non-reproducible when
+  `parallel = FALSE`. The internal `set_seed()` helper was assigning
+  `.Random.seed` to its local frame rather than `.GlobalEnv`, so the RNG state
+  was silently discarded. The parallel path was unaffected
+
 - `SimErrors()` and `SimWarnings()`  functions added to better track and 
   extract error/warning information. Makes it easier to track down specific 
   seed states to replicate any of the recorded messages

R/util.R

@@ -678,7 +678,7 @@ pickReps <- function(replications, iter){
 }
 
 set_seed <- function(seed){
-    if(is.list(seed)) .Random.seed <- seed[[1L]]
+    if(is.list(seed)) .GlobalEnv$.Random.seed <- seed[[1L]]
     else set.seed(seed)
     invisible(NULL)
 }

tests/tests/test-03-array.R

@@ -70,6 +70,22 @@ test_that('array', {
 
     SimClean('mysim-1.rds')
 
+    # serial iseed must be byte-for-byte reproducible (L'Ecuyer-CMRG seed
+    # applied via set_seed(); see GitHub bug re: .GlobalEnv assignment)
+    res_s1 <- runArraySimulation(design=Design, replications=20,
+                                 generate=Generate, analyse=Analyse,
+                                 summarise=Summarise, arrayID=1L,
+                                 iseed=iseed, filename='serialseed',
+                                 parallel=FALSE, verbose=FALSE)
+    res_s2 <- runArraySimulation(design=Design, replications=20,
+                                 generate=Generate, analyse=Analyse,
+                                 summarise=Summarise, arrayID=1L,
+                                 iseed=iseed, filename='serialseed',
+                                 parallel=FALSE, verbose=FALSE)
+    expect_identical(SimExtract(res_s1, what='results'),
+                     SimExtract(res_s2, what='results'))
+    SimClean('serialseed-1.rds')
+
     ########################
     # Same submission job as above, however split the replications over multiple
     # evaluations and combine when complete