Always use goodMeanDistance
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@@ -40,7 +40,8 @@ class ClusterFeedbackService {
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final _computer = Computer.shared();
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ClusterFeedbackService._privateConstructor();
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static final ClusterFeedbackService instance = ClusterFeedbackService._privateConstructor();
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static final ClusterFeedbackService instance =
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ClusterFeedbackService._privateConstructor();
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static int lastViewedClusterID = -1;
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static setLastViewedClusterID(int clusterID) {
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@@ -686,7 +687,7 @@ class ClusterFeedbackService {
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clusterAvgBigClusters,
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personClusters,
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ignoredClusters,
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(minimumSize == 100) ? goodMeanDistance + 0.15 : goodMeanDistance,
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goodMeanDistance,
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);
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w?.log(
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'Calculate suggestions using mean for ${clusterAvgBigClusters.length} clusters of min size $minimumSize',
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@@ -1165,7 +1166,9 @@ List<(int, double)> _calcSuggestionsMean(Map<String, dynamic> args) {
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}
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}
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if (nearestPersonCluster != null && minDistance != null) {
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suggestions.putIfAbsent(nearestPersonCluster, () => []).add((otherClusterID, minDistance));
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suggestions
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.putIfAbsent(nearestPersonCluster, () => [])
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.add((otherClusterID, minDistance));
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suggestionCount++;
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}
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if (suggestionCount >= suggestionMax) {
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@@ -1195,7 +1198,8 @@ List<(int, double)> _calcSuggestionsMean(Map<String, dynamic> args) {
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}
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}
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Future<(Map<int, Vector>, Set<int>, int, int, int)> checkAndSerializeCurrentClusterMeans(
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Future<(Map<int, Vector>, Set<int>, int, int, int)>
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checkAndSerializeCurrentClusterMeans(
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Map args,
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) async {
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final Map<int, int> allClusterIdsToCountMap = args['allClusterIdsToCountMap'];
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