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@ -1,13 +1,89 @@
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using System;
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using System.Collections;
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using System.Collections.Generic;
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using System.Linq;
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namespace ZeroLevel.HNSW.Services
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{
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public static class AutomaticGraphClusterer
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public class Cluster
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: IEnumerable<int>
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{
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private const int HALF_LONG_BITS = 32;
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private HashSet<int> _elements = new HashSet<int>();
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public int Count => _elements.Count;
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public bool Contains(int id) => _elements.Contains(id);
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public bool Add(int id) => _elements.Add(id);
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public IEnumerator<int> GetEnumerator()
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{
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return _elements.GetEnumerator();
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}
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IEnumerator IEnumerable.GetEnumerator()
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{
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return _elements.GetEnumerator();
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}
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public void Merge(Cluster cluster)
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{
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foreach (var e in cluster)
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{
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this._elements.Add(e);
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}
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}
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public float MaxDistance(Func<int, int, float> distance, Cluster other)
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{
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var max = float.MinValue;
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foreach (var e in this._elements)
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{
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foreach (var o in other)
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{
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var d = distance(e, o);
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if (d > max)
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{
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max = d;
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}
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}
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}
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return max;
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}
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public float MinDistance(Func<int, int, float> distance, Cluster other)
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{
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var min = float.MaxValue;
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foreach (var e in this._elements)
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{
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foreach (var o in other)
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{
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var d = distance(e, o);
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if (d < min)
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{
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min = d;
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}
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}
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}
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return min;
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}
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public float AvgDistance(Func<int, int, float> distance, Cluster other)
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{
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var dist = new List<float>();
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foreach (var e in this._elements)
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{
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foreach (var o in other)
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{
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dist.Add(distance(e, o));
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}
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}
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return dist.Average();
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}
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}
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public static class AutomaticGraphClusterer
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{
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private class Link
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{
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public int Id1;
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@ -15,13 +91,13 @@ namespace ZeroLevel.HNSW.Services
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public float Distance;
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}
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public static List<HashSet<int>> DetectClusters<T>(SmallWorld<T> world)
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public static List<Cluster> DetectClusters<T>(SmallWorld<T> world)
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{
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var distance = world.DistanceFunction;
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var links = world.GetLinks().SelectMany(pair => pair.Value.Select(id => new Link { Id1 = pair.Key, Id2 = id, Distance = distance(pair.Key, id) })).ToList();
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// 1. Find R - bound between intra-cluster distances and out-of-cluster distances
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var histogram = new Histogram(HistogramMode.SQRT, links.Select(l => l.Distance));
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var histogram = new Histogram(HistogramMode.LOG, links.Select(l => l.Distance));
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int threshold = histogram.CuttOff();
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var min = histogram.Bounds[threshold - 1];
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var max = histogram.Bounds[threshold];
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@ -39,7 +115,7 @@ namespace ZeroLevel.HNSW.Services
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}
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// 3. Extract clusters
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List<HashSet<int>> clusters = new List<HashSet<int>>();
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List<Cluster> clusters = new List<Cluster>();
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foreach (var l in resultLinks)
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{
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var id1 = l.Id1;
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@ -62,7 +138,7 @@ namespace ZeroLevel.HNSW.Services
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}
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if (found == false)
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{
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var c = new HashSet<int>();
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var c = new Cluster();
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c.Add(id1);
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c.Add(id2);
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clusters.Add(c);
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