Updates

TestHNSW/HNSWDemo/Program.cs

@@ -1,5 +1,6 @@
 using HNSWDemo.Tests;
 using System;
+using ZeroLevel.Services.Web;
 
 namespace HNSWDemo
 {
@@ -7,6 +8,8 @@ namespace HNSWDemo
     {
         static void Main(string[] args)
         {
+            var uri = new Uri("https://hack33d.ru/bpla/upload.php?path=128111&get=0J/QuNC70LjQv9C10L3QutC+INCS0LvQsNC00LjQvNC40YAg0JzQuNGF0LDQudC70L7QstC40Yc7MDQuMDkuMTk1NCAoNjYg0LvQtdGCKTvQnNC+0YHQutC+0LLRgdC60LDRjzsxMjgxMTE7TEFfUkVaVVM7RkxZXzAy");
+            var parts = UrlUtility.ParseQueryString(uri.Query);
             new AutoClusteringMNISTTest().Run();
             //new HistogramTest().Run();
             Console.WriteLine("Completed");

TestHNSW/HNSWDemo/Tests/AutoClusteringMNISTTest.cs

@@ -81,13 +81,30 @@ namespace HNSWDemo.Tests
             var links = world.GetLinks().SelectMany(pair => pair.Value.Select(p=> distance(pair.Key, p))).ToList();
             var exists = links.Where(n => n > 0).ToArray();
             
-            var histogram = new Histogram(HistogramMode.SQRT, links);
+            var histogram = new Histogram(HistogramMode.LOG, links);
             DrawHistogram(histogram, @"D:\Mnist\histogram.jpg");
 
             var clusters = AutomaticGraphClusterer.DetectClusters(world);
             Console.WriteLine($"Found {clusters.Count} clusters");
-            
-            
+
+            while (clusters.Count > 10)
+            {
+                var last = clusters[clusters.Count - 1];
+                var testDistance = clusters[0].MinDistance(distance, last);
+                var index = 0;
+                for (int i = 1; i < clusters.Count - 1; i++)
+                { 
+                    var d = clusters[i].MinDistance(distance, last);
+                    if (d < testDistance)
+                    {
+                        testDistance = d;
+                        index = i;
+                    }
+                }
+                clusters[index].Merge(last);
+                clusters.RemoveAt(clusters.Count - 1);
+            }
+
             for (int i = 0; i < clusters.Count; i++)
             {
                 var ouput = Path.Combine(folder, i.ToString("D3"));

ZeroLevel.HNSW/Services/AutomaticGraphClusterer.cs

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

ZeroLevel.HNSW/ZeroLevel.HNSW.csproj

@@ -7,7 +7,10 @@
 
   <ItemGroup>
     <PackageReference Include="System.Numerics.Vectors" Version="4.5.0" />
-    <PackageReference Include="ZeroLevel" Version="3.3.5.6" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\ZeroLevel\ZeroLevel.csproj" />
   </ItemGroup>
 
 </Project>