Fix #7354, Implementing NSE in cube

R/data.table.R

@@ -521,6 +521,50 @@ replace_dot_alias = function(e) {
   list(GForce=GForce, jsub=jsub, jvnames=jvnames)
 }
 
+# Helper function to process SDcols
+.processSDcols = function(SDcols_sub, SDcols_missing, x, jsub, by, enclos = parent.frame()) {
+ names_x = names(x)
+ bysub = substitute(by)
+ allbyvars = intersect(all.vars(bysub), names_x)
+ usesSD = ".SD" %chin% all.vars(jsub)
+ if (!usesSD) {
+   return(NULL)
+ }
+ if (SDcols_missing) {
+   ansvars = sdvars = setdiff(unique(names_x), union(by, allbyvars))
+   ansvals = match(ansvars, names_x)
+   return(list(ansvars = ansvars, sdvars = sdvars, ansvals = ansvals))
+ }
+ sub.result = SDcols_sub
+ if (sub.result %iscall% "patterns") {
+   .SDcols = eval_with_cols(sub.result, names_x)
+ } else {
+   .SDcols = eval(sub.result, enclos)
+ }
+ if (anyNA(.SDcols))
+   stopf(".SDcols missing at the following indices: %s", brackify(which(is.na(.SDcols))))
+ if (is.character(.SDcols)) {
+   idx = .SDcols %chin% names_x
+   if (!all(idx))
+     stopf("Some items of .SDcols are not column names: %s", toString(.SDcols[!idx]))
+   ansvars = sdvars = .SDcols
+   ansvals = match(ansvars, names_x)
+ } else if (is.numeric(.SDcols)) {
+     ansvals = as.integer(.SDcols)
+   if (any(ansvals < 1L | ansvals > length(names_x)))
+     stopf(".SDcols contains indices out of bounds")
+   ansvars = sdvars = names_x[ansvals]
+ } else if (is.logical(.SDcols)) {
+   if (length(.SDcols) != length(names_x))
+     stopf(".SDcols is a logical vector of length %d but there are %d columns", length(.SDcols), length(names_x))
+   ansvals = which(.SDcols)
+   ansvars = sdvars = names_x[ansvals]
+ } else {
+   stopf(".SDcols must be character, numeric, or logical")
+ }
+ list(ansvars = ansvars, sdvars = sdvars, ansvals = ansvals)
+}
+
 "[.data.table" = function(x, i, j, by, keyby, with=TRUE, nomatch=NA, mult="all", roll=FALSE, rollends=if (roll=="nearest") c(TRUE,TRUE) else if (roll>=0.0) c(FALSE,TRUE) else c(TRUE,FALSE), which=FALSE, .SDcols, verbose=getOption("datatable.verbose"), allow.cartesian=getOption("datatable.allow.cartesian"), drop=NULL, on=NULL, env=NULL, showProgress=getOption("datatable.showProgress", interactive()))
 {
   # ..selfcount <<- ..selfcount+1  # in dev, we check no self calls, each of which doubles overhead, or could

R/groupingsets.R

@@ -29,6 +29,17 @@ cube.data.table = function(x, j, by, .SDcols, id = FALSE, label = NULL, ...) {
     stopf("Argument 'id' must be a logical scalar.")
   if (missing(j))
     stopf("Argument 'j' is required")
+  # Implementing NSE in cube using the helper, .processSDcols
+  jj = substitute(j)
+ sdcols_result = .processSDcols(SDcols_sub = substitute(.SDcols), SDcols_missing = missing(.SDcols), x = x, jsub = jj, by = by, enclos = parent.frame())
+ if (is.null(sdcols_result)) {
+   .SDcols = NULL
+ } else {
+   ansvars = sdcols_result$ansvars
+   sdvars = sdcols_result$sdvars
+   ansvals = sdcols_result$ansvals
+   .SDcols = sdvars
+ }
   # generate grouping sets for cube - power set: http://stackoverflow.com/a/32187892/2490497
   n = length(by)
   keepBool = sapply(2L^(seq_len(n)-1L), function(k) rep(c(FALSE, TRUE), times=k, each=((2L^n)/(2L*k))))

inst/tests/tests.Rraw

@@ -11102,6 +11102,43 @@ test(1750.34,
                            character(0)),
                id = TRUE)
 )
+test(1750.35,
+  cube(dt, j = lapply(.SD, sum), by = c("color","year","status"), id=TRUE, .SDcols=patterns("value")),
+  groupingsets(dt, j = lapply(.SD, sum), by = c("color","year","status"), .SDcols = "value", 
+                sets = list(c("color","year","status"),
+                            c("color","year"),
+                            c("color","status"),
+                            "color",
+                            c("year","status"),
+                            "year",
+                            "status",
+                            character(0)),
+                id = TRUE)
+)
+test(1750.36,
+  cube(dt, j = lapply(.SD, sum), by = "year", .SDcols = c("value", "BADCOL")),
+  error = "Some items of \\.SDcols are not column names"
+)
+
+test(1750.37,
+  cube(dt, j = lapply(.SD, sum), by = "year", .SDcols = c(TRUE, FALSE)),
+  error = "\\.SDcols is a logical vector of length"
+)
+
+test(1750.38,
+cube(dt, j = lapply(.SD, mean), by = "color", .SDcols = c(FALSE, FALSE, FALSE, TRUE, FALSE), id=TRUE),
+  groupingsets(dt, j = lapply(.SD, mean), by = "color", .SDcols = "amount",
+                sets = list("color", character(0)),
+                id = TRUE)
+)
+test(1750.39,
+  cube(dt, j = lapply(.SD, sum), by = "color", .SDcols = list("amount")),
+  error = ".SDcols must be character, numeric, or logical"
+)
+test(1750.40,
+  cube(dt, j = lapply(.SD, sum), by = "color", .SDcols = c(1, 99)),
+  error = "out of bounds"
+)
 # grouping sets with integer64
 if (test_bit64) {
   set.seed(26)
@@ -11147,6 +11184,16 @@ if (test_bit64) {
 }
 # end Grouping Sets
 
+# extra cube tests
+test(1750.49,
+  cube(dt, j = lapply(.SD, sum), by = "year", .SDcols = c(NA_character_, "amount")),
+  error = "\\.SDcols missing at the following indices: \\[1\\]"
+)
+test(1750.50,
+  cube(dt, j = lapply(.SD, sum), by = "year", .SDcols = c(4L, 5L)),
+  cube(dt, j = lapply(.SD, sum), by = "year", .SDcols = c("amount", "value"))
+)
+
 # for completeness, added test for NA problem to close #1837.
 DT = data.table(x=NA)
 test(1751.1, capture.output(fwrite(DT, verbose=FALSE)), c("x",""))