KMeans/KMeansBase/KMeans.cs

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, maxX) = (points.Min(p => p.X), points.Max(p => p.X));
        var (minY, maxY) = (points.Min(p => p.Y), 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);
            yield return point;
        }
    }
}