From 8701d9dba60bf4042457c38a0816079cada535c5 Mon Sep 17 00:00:00 2001
From: kenomersmannPC <advieser@gmail.com>
Date: Sat, 2 Nov 2024 20:59:39 +0100
Subject: [PATCH] fix + restructure comments

---
 R/utils.R | 27 +++++++++++----------------
 1 file changed, 11 insertions(+), 16 deletions(-)

diff --git a/R/utils.R b/R/utils.R
index 5231898d4..582de7d63 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -42,23 +42,19 @@ task_filter_ex = function(task, row_ids) {
   # Rbind duplicated rows to task
   if (length(dup_ids)) {
 
+    # First, get a data.table with all duplicated rows.
     new_data = task$data(rows = dup_ids, cols = cols)
 
-    # For column with role "group", create new groups for duplicates by adding a suffix.
+    # Second, if task has a column with role "group", create new groups for duplicate rows by adding a suffix to the group entry.
     if (!is.null(task$groups)) {
       group = NULL  # for binding
       row_id = NULL  # for binding
 
-      # We create a data.table with the corresponding group to each duplicated ID.
-      # We then change the group entry based on how often the ID occurs.
-      # Note that we make no assumptions on whether the whole group is sampled here.
-      # That has to be checked in the functions calling this.
-      #
-      # We assume that the rbinded rows are in the same positions as the original ids in dup_ids.
-      # This should generally be the case as long as the task does not have a col role group
-      # and task$data(..., ordered = FALSE) in task$rbind() above (default).
-
-      grps = unique(task$groups)
+      # We create a data.table "new_groups" with the corresponding group to each duplicated ID.
+      # We then change the group entry based on how often the ID occurs. E.g. row_id = 1 occurs
+      # two times has the group entry "g". Then we rename the group entries to "g_1" and "g_2".
+      # If a group with a suffix (e.g. "_1") already exists, we add another suffix to it (i.e. "_1_1").
+      grps = unique(task$groups$group)
       new_groups = task$groups[J(dup_ids), on = "row_id"][, group := {
         groups = character(0)
         i = 1
@@ -70,17 +66,18 @@ task_filter_ex = function(task, row_ids) {
         groups
       }, by = row_id]
 
-      # Generate data.table with rows for all newly added rows and updated group names
+      # Use "new_groups" to update the group entries.
       new_data[, (task$col_roles$group) := new_groups$group]
     }
 
+    # Lastly, new data is rbinded to the original task.
     task$rbind(new_data)
-
   }
 
-  # Row ids can be anything, we just take what mlr3 happens to assign to filter the task.
+  # row_ids can be anything, we just take what mlr3 happens to assign to filter the task.
   row_ids[duplicated(row_ids)] = task$row_ids[newrows]
 
+  # Update row_ids, effectively filtering the task
   task$row_roles$use = row_ids
   task
 }
@@ -107,7 +104,6 @@ curry = function(fn, ..., varname = "x") {
   }
 }
 
-
 # 'and' operator for checkmate check_*-functions
 # example:
 # check_numeric(x) %check&&% check_true(all(x < 0))
@@ -121,7 +117,6 @@ curry = function(fn, ..., varname = "x") {
   TRUE
 }
 
-
 # perform gsub on names of list
 # `...` are given to `gsub()`
 rename_list = function(x, ...) {