move tests

Author: ben-schwen

R/test.data.table.R

@@ -361,7 +361,37 @@ gc_mem = function() {
   # nocov end
 }
 
-test = function(num,x,y=TRUE,error=NULL,warning=NULL,message=NULL,output=NULL,notOutput=NULL,ignore.warning=NULL,options=NULL,env=NULL) {
+test = function(num,x,y=TRUE,error=NULL,warning=NULL,message=NULL,output=NULL,notOutput=NULL,ignore.warning=NULL,options=NULL,env=NULL,levels=NULL) {
+  # if levels is provided, test across multiple optimization levels
+  if (!is.null(levels)) {
+    cl = match.call()
+    cl$levels = NULL  # Remove levels from the recursive call
+
+    vector_params = c("error", "warning", "message", "output", "notOutput", "ignore.warning")
+    # Check if y was explicitly provided (not just the default)
+    y_provided = !missing(y)
+    compare = !y_provided && length(levels)>1L && !any(vapply_1b(vector_params, function(p) length(get(p, envir=environment())) > 0L))
+
+    for (i in seq_along(levels)) {
+      cl$num = num + (i - 1L) * 1e-6
+      opt_level = list(datatable.optimize = levels[i])
+      cl$options = if (!is.null(options)) c(as.list(options), opt_level) else opt_level
+      for (p in vector_params) {
+        val = get(p, envir=environment())
+        if (length(val) > 0L) {
+          cl[[p]] = val[((i - 1L) %% length(val)) + 1L] # ccycle through values if fewer than levels
+        } else if (p %in% names(cl)) {
+          cl[[p]] = NULL
+        }
+      }
+
+      if (compare && i == 1L) cl$y = eval(cl$x, parent.frame())
+      eval(cl, parent.frame())
+    }
+    return(invisible())
+  }
+
+  # print(match.call())
   if (!is.null(env)) {
     old = Sys.getenv(names(env), names=TRUE, unset=NA)
     to_unset = !lengths(env)

inst/tests/benchmark.Rraw

@@ -190,24 +190,13 @@ DT = data.table(A=1:10,B=rnorm(10),C=paste("a",1:100010,sep=""))
 test(301.1, nrow(DT[,sum(B),by=C])==100010)
 
 # Test := by key, and that := to the key by key unsets the key. Make it non-trivial in size too.
-local({
-  old = options(datatable.optimize=0L); on.exit(options(old))
-  set.seed(1)
-  DT = data.table(a=sample(1:100, 1e6, replace=TRUE), b=sample(1:1000, 1e6, replace=TRUE), key="a")
-  test(637.1, DT[, m:=sum(b), by=a][1:3], data.table(a=1L, b=c(156L, 808L, 848L), m=DT[J(1), sum(b)], key="a"))
-  test(637.2, key(DT[J(43L), a:=99L]), NULL)
-  setkey(DT, a)
-  test(637.3, key(DT[, a:=99L, by=a]), NULL)
-})
-local({
-  options(datatable.optimize=2L); on.exit(options(old))
-  set.seed(1)
-  DT = data.table(a=sample(1:100, 1e6, replace=TRUE), b=sample(1:1000, 1e6, replace=TRUE), key="a")
-  test(638.1, DT[, m:=sum(b), by=a][1:3], data.table(a=1L, b=c(156L, 808L, 848L), m=DT[J(1), sum(b)], key="a"))
-  test(638.2, key(DT[J(43L), a:=99L]), NULL)
-  setkey(DT,a)
-  test(638.3, key(DT[, a:=99L, by=a]), NULL)
-})
+set.seed(1)
+DT = data.table(a=sample(1:100, 1e6, replace=TRUE), b=sample(1:1000, 1e6, replace=TRUE), key="a")
+opt = c(0L,2L)
+test(637.1, levels=opt, copy(DT)[, m:=sum(b), by=a][1:3], data.table(a=1L, b=c(156L, 808L, 848L), m=DT[J(1), sum(b)], key="a"))
+test(637.2, levels=opt, key(copy(DT)[J(43L), a:=99L]), NULL)
+setkey(DT, a)
+test(637.3, levels=opt, key(copy(DT)[, a:=99L, by=a]), NULL)
 
 # Test X[Y] slowdown, #2216
 # Many minutes in 1.8.2!  Now well under 1s, but 10s for very wide tolerance for CRAN. We'd like CRAN to tell us if any changes