Add Avalonia gui

KMeansBase/KMeans.cs

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+namespace KMeansBase;
+
+public static class KMeans
+{
+    private const int MaxLoops = 30;
+
+    public static void KMeansCalculation(IReadOnlyCollection<Point> points, int k, out IReadOnlyCollection<Point> centroids)
+    {
+        centroids = InitializeRandomCentroids(points, k).ToArray();
+
+        for (var i = 0; i < MaxLoops; i++)
+        {
+            AssignPointsToCentroids(points, centroids);
+            if (!UpdateCentroids(points, centroids)) break;
+        }
+    }
+
+    private static bool UpdateCentroids(IReadOnlyCollection<Point> points, IEnumerable<Point> centroids)
+    {
+        // calculate mean of all points of one cluster.
+        var updated = false;
+        foreach (var centroid in centroids)
+        {
+            updated |= UpdateClusterCentroid(centroid, points);
+        }
+
+        return updated;
+    }
+
+    private static bool UpdateClusterCentroid(Point centroid, IEnumerable<Point> points)
+    {
+        var pointsOfCluster = points.Where(p => p.ClusterId == centroid.ClusterId).ToArray();
+        var sumX = pointsOfCluster.Sum(p => p.X);
+        var meanX = sumX / pointsOfCluster.Length;
+        var sumY = pointsOfCluster.Sum(p => p.Y);
+        var meanY = sumY / pointsOfCluster.Length;
+
+        return centroid.SetCoordinates(meanX, meanY);
+    }
+
+    private static void AssignPointsToCentroids(IEnumerable<Point> points, IReadOnlyCollection<Point> centroids)
+    {
+        foreach (var point in points)
+        {
+            var id = 0;
+            var distance = double.MaxValue;
+            foreach (var centroid in centroids)
+            {
+                // calculate euclid distance and assign id.
+                var currentDistance = Distance(centroid, point);
+                if (currentDistance > distance) continue;
+                distance = currentDistance;
+                id = centroid.ClusterId;
+            }
+
+            point.ClusterId = id;
+        }
+    }
+
+    private static double Distance(Point centroid, Point point)
+    {
+        return Math.Sqrt(Math.Pow(centroid.X - point.X, 2) + Math.Pow(centroid.Y - point.Y, 2));
+    }
+
+    private static IEnumerable<Point> InitializeRandomCentroids(IReadOnlyCollection<Point> points, int k)
+    {
+        var minX = points.Min(p => p.X);
+        var maxX = points.Max(p => p.X);
+        var minY = points.Min(p => p.Y);
+        var maxY = points.Max(p => p.Y);
+        var rnd = new Random();
+
+        for (var i = 0; i < k; i++)
+        {
+            var x = (minX + maxX) * rnd.NextDouble();
+            var y = (minY + maxY) * rnd.NextDouble();
+            var point = new Point(x, y, i);
+            Console.WriteLine(point);
+            yield return point;
+        }
+    }
+}

KMeansBase/KMeansBase.csproj

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+<Project Sdk="Microsoft.NET.Sdk">
+
+    <PropertyGroup>
+        <TargetFramework>net6.0</TargetFramework>
+        <ImplicitUsings>enable</ImplicitUsings>
+        <Nullable>enable</Nullable>
+    </PropertyGroup>
+
+</Project>

KMeansBase/Point.cs

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+namespace KMeansBase;
+
+public record Point(double X, double Y, int ClusterId)
+{
+    public int ClusterId { get; set; } = ClusterId;
+    public double X { get; private set; } = X;
+    public double Y { get; private set; } = Y;
+
+    public bool SetCoordinates(double x, double y)
+    {
+        if (!(Math.Abs(X - x) > 1e-5) || !(Math.Abs(Y - y) > 1e-5)) return false;
+        X = x;
+        Y = y;
+        return true;
+    }
+}