From a0c52a56fcc5d160142359b93f6dc8c3cdf7bfdf Mon Sep 17 00:00:00 2001
From: Christian Wolf <github@christianwolf.email>
Date: Mon, 20 Nov 2023 10:22:07 +0100
Subject: [PATCH] Started to work towards new group management

---
 src/solo_turnier/worker.py | 115 ++++++++++++++++++++++++++++++++++++-
 1 file changed, 114 insertions(+), 1 deletion(-)

diff --git a/src/solo_turnier/worker.py b/src/solo_turnier/worker.py
index bee9d46..fc94abe 100644
--- a/src/solo_turnier/worker.py
+++ b/src/solo_turnier/worker.py
@@ -382,6 +382,7 @@ class Worker:
             "Slowfox",
             "Quickstep",
         ]
+        self._groupParser = solo_turnier.group.GroupParser()
 
     def collectAllData(self, htmlResultsFileNames: list[str]) -> types.State3:
         resultExtractor = ResultExtractor()
@@ -393,9 +394,18 @@ class Worker:
 
     def combineData(self, importedData: types.State3):
         self.l.info("Starting to build data sets.")
-        groups = self._extractGroups(importedData)
+
+        self.l.debug("Getting per participant groups")
+        groupMapping = self._getGroupMapping(importedData)
+        self.l.log(5, "ID-to-group mapping of the parsed data: %s", str(groupMapping))
+
+        # groups = self._extractGroups(importedData)
+        groups = self._extractGroupsFromGroupMapping(groupMapping)
         self.l.debug("Found groups in the dataset: %s", groups)
 
+        invertedGroupMapping = self._invertGroupMapping(groupMapping, groups)
+        self.l.log(5, "Inverted group maping: %s", invertedGroupMapping)
+
         totalResult = {}
 
         for group in groups:
@@ -451,6 +461,109 @@ class Worker:
         groups = groupParser.getGroupsAsSortedList(groupSet)
         return groups
 
+    def _getGroupMapping(
+        self, importedData: types.State3
+    ) -> dict[int, solo_turnier.group.Group | None]:
+        groupParser = solo_turnier.group.GroupParser()
+
+        def _getBestGroupGuess(groups, id):
+            counts = {}
+            grNones = 0
+            for gr in set(groups):
+                length = len(list(filter(lambda x: x == gr, groups)))
+                if isinstance(gr, tuple) or gr is None:
+                    grNones = grNones + length
+                else:
+                    counts[gr] = length
+            counts[None] = grNones
+            candidates = list(counts.keys())
+
+            def ccomp(i1):
+                return counts[i1]
+
+            candidates.sort(key=ccomp, reverse=True)
+
+            if len(candidates) == 1:
+                self.l.warning("Unrequired group guessing started.")
+                return candidates[0]
+            if len(candidates) == 0:
+                self.l.error("Problem during the group guessing triggered.")
+                return None
+
+            if counts[candidates[0]] > counts[candidates[1]]:
+                if candidates[0] is None:
+                    self.l.error(
+                        "Majority of guessed groups is ambigous. Guessing failed for id %d. Falling back to second best guess.",
+                        id,
+                    )
+                    return candidates[1]
+
+                self.l.info("Using best fit %s for guessed group.", candidates[0])
+                return candidates[0]
+
+            self.l.warning("Group guessing failed.")
+            return None
+
+        groupsPerId = {}
+        for tup in importedData.htmlResults.results:
+            competitionGroup = groupParser.parseClass(tup[0])
+            fixture = importedData.htmlResults.tabges.get(tup, (None, None, None))
+            id = int(tup[3])
+            if fixture[2] is not None:
+                group = groupParser.parseClass(fixture[2])
+            else:
+                containedGroups = competitionGroup.getContainedGroups()
+                if len(containedGroups) > 1:
+                    self.l.error(
+                        "The group for participant %d is ambiguous in (%s %s %s).",
+                        id,
+                        tup[0],
+                        tup[1],
+                        tup[2],
+                    )
+                    group = containedGroups
+                else:
+                    group = competitionGroup
+
+            knownGroups = groupsPerId.get(id, [])
+            if group is not None:
+                knownGroups.append(group)
+            groupsPerId[id] = knownGroups
+
+        ret = {}
+        for id in groupsPerId.keys():
+            groupCandidates = groupsPerId[id]
+            groupSet = set(groupCandidates)
+
+            if len(groupSet) == 1:
+                ret[id] = groupSet.pop()
+            elif len(groupSet) > 1:
+                self.l.warning(
+                    "Multiple groups for id %d found: %s", id, groupsPerId[id]
+                )
+                ret[id] = _getBestGroupGuess(groupCandidates, id)
+            else:
+                self.l.warning("No group for id %d could be found.", id)
+                ret[id] = None
+        return ret
+
+    def _extractGroupsFromGroupMapping(self, mapping):
+        foundGroups = set()
+        for id in mapping:
+            foundGroups.add(mapping[id])
+        sortedGroup = self._groupParser.getGroupsAsSortedList(foundGroups)
+        missingGroups = foundGroups.difference(sortedGroup)
+        sortedGroup = sortedGroup + list(missingGroups)
+        return sortedGroup
+
+    def _invertGroupMapping(self, mapping, groups):
+        ret = {}
+        for group in groups:
+            ret[group] = []
+        for id in mapping:
+            ret[mapping[id]].append(id)
+        return ret
+
     def _extractDancesPerGroup(
         self, data: types.State3, group: solo_turnier.group.Group
     ):