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@@ -474,30 +474,30 @@ class ClusterFeedbackService {
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final checkSizes = [kMinimumClusterSizeSearchResult, 20, 10, 5, 1];
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late Map<int, Vector> clusterAvgBigClusters;
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for (final minimumSize in checkSizes.toSet()) {
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- if (smallestPersonClusterSize >= minimumSize) {
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- clusterAvgBigClusters = await _getUpdateClusterAvg(
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- allClusterIdsToCountMap,
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- ignoredClusters,
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- minClusterSize: minimumSize,
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- );
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- w?.log(
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- 'Calculate avg for ${clusterAvgBigClusters.length} clusters of min size $minimumSize',
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- );
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- final List<(int, double)> suggestionsMeanBigClusters =
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- _calcSuggestionsMean(
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- clusterAvgBigClusters,
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- personClusters,
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- ignoredClusters,
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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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- );
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- if (suggestionsMeanBigClusters.isNotEmpty) {
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- return suggestionsMeanBigClusters
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- .map((e) => (e.$1, e.$2, true))
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- .toList(growable: false);
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- }
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+ // if (smallestPersonClusterSize >= minimumSize) {
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+ clusterAvgBigClusters = await _getUpdateClusterAvg(
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+ allClusterIdsToCountMap,
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+ ignoredClusters,
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+ minClusterSize: minimumSize,
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+ );
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+ w?.log(
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+ 'Calculate avg for ${clusterAvgBigClusters.length} clusters of min size $minimumSize',
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+ );
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+ final List<(int, double)> suggestionsMeanBigClusters =
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+ _calcSuggestionsMean(
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+ clusterAvgBigClusters,
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+ personClusters,
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+ ignoredClusters,
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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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+ );
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+ if (suggestionsMeanBigClusters.isNotEmpty) {
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+ return suggestionsMeanBigClusters
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+ .map((e) => (e.$1, e.$2, true))
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+ .toList(growable: false);
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+ // }
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}
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}
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w?.reset();
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