private void ExpandCluster(DbscanPoint newPoint, IEnumerable <DbscanPoint> neighborPts, int clusterId)
{
newPoint.ClusterId = clusterId;
var queue = new Queue <DbscanPoint>(neighborPts);
while (queue.Count > 0)
{
var point = queue.Dequeue();
if (point.ClusterId == UNCLASSIFIED)
{
point.ClusterId = clusterId;
}
if (point.IsVisited)
{
continue;
}
point.IsVisited = true;
var neighbors = neighbor(point.ClusterPoint);
if (neighbors.Count() >= MinPts)
{
foreach (var neighbor in neighbors.Where(neighbor => !neighbor.IsVisited))
{
queue.Enqueue(neighbor);
}
}
}
}
public ClusteringStarted(DbscanPoint <TF> point, DbscanPoint <TF>[] neighborPoints,
int clusterId, double epsilon, int minimumPoints)
{
Point = point;
NeighborPoints = neighborPoints;
ClusterId = clusterId;
Epsilon = epsilon;
MinimumPoints = minimumPoints;
}
/// <summary>
///
/// </summary>
/// <param name="allPoints">Dataset</param>
/// <param name="point">point to be in a cluster</param>
/// <param name="neighborPts">other points in same region with point parameter</param>
/// <param name="clusterId">given clusterId</param>
/// <param name="epsilon">Desired region ball range</param>
/// <param name="minPts">Minimum number of points to be in a region</param>
private void ExpandCluster(KDTree.KDTree <DbscanPoint <T> > tree, DbscanPoint <T> p, DbscanPoint <T>[] neighborPts, int clusterId, double epsilon, int minPts)
{
p.ClusterId = clusterId;
//for (int i = 0; i < neighborPts.Length; i++)
//{
// DbscanPoint<T> pn = neighborPts[i];
// if (!pn.IsVisited)
// {
// pn.IsVisited = true;
// DbscanPoint<T>[] neighborPts2 = RegionQuery(tree, pn.ClusterPoint, epsilon); ;
// if (neighborPts2.Length >= minPts)
// {
// neighborPts = neighborPts.Union(neighborPts2).ToArray();
// }
// }
// if (pn.ClusterId == (int)ClusterIds.Unclassified)
// pn.ClusterId = clusterId;
//}
var queue = new Queue <DbscanPoint <T> >(neighborPts);
while (queue.Count > 0)
{
var point = queue.Dequeue();
if (point.ClusterId == (int)ClusterIds.Unclassified)
{
point.ClusterId = clusterId;
}
if (point.IsVisited)
{
continue;
}
point.IsVisited = true;
var neighbors = RegionQuery(tree, point.ClusterPoint, epsilon);
if (neighbors.Length >= minPts)
{
foreach (var neighbor in neighbors.Where(neighbor => !neighbor.IsVisited))
{
queue.Enqueue(neighbor);
}
}
}
}
public void ComputeClusterDbscan(T[] allPoints, double epsilon, int minPts, out HashSet <T[]> clusters, ref List <int> clusterIds)
{
DbscanPoint <T>[] allPointsDbscan = allPoints.Where(x => x.posX != 0 || x.posY != 0 || x.posZ != 0)
.Select(x => new DbscanPoint <T>(x)).ToArray();
var tree = new KDTree.KDTree <DbscanPoint <T> >(3);
for (var i = 0; i < allPointsDbscan.Length; ++i)
{
Record temp = allPointsDbscan[i].ClusterPoint;
tree.AddPoint(new double[] { temp.posX, temp.posY, temp.posZ }, allPointsDbscan[i]);
}
int clusterId = 0;
for (int i = 0; i < allPointsDbscan.Length; i++)
{
DbscanPoint <T> p = allPointsDbscan[i];
if (p.IsVisited)
{
clusterIds.Add(p.ClusterId);
continue;
}
p.IsVisited = true;
var neighborPts = RegionQuery(tree, p.ClusterPoint, epsilon);
if (neighborPts.Length < minPts)
{
p.ClusterId = (int)ClusterIds.Noise;
}
else
{
clusterId++;
ExpandCluster(tree, p, neighborPts, clusterId, epsilon, minPts);
}
clusterIds.Add(p.ClusterId);
}
clusters = new HashSet <T[]>(
allPointsDbscan
.Where(x => x.ClusterId > 0)
.GroupBy(x => x.ClusterId)
.Select(x => x.Select(y => y.ClusterPoint).ToArray())
);
}
private void ExpandCluster(DbscanPoint[] allPoints, DbscanPoint p, DbscanPoint[] neighborPts, int c, double epsilon, int minPts)
{
p.ClusterId = c;
for (int i = 0; i < neighborPts.Length; i++)
{
var pn = neighborPts[i];
if (!pn.IsVisited)
{
pn.IsVisited = true;
DbscanPoint[] neighborPts2 = null;
RegionQuery(allPoints, pn.ClusterPoint, epsilon, out neighborPts2);
if (neighborPts2.Length >= minPts)
{
neighborPts = neighborPts.Union(neighborPts2).ToArray();
}
}
if (pn.ClusterId == (int)ClusterIds.UNCLASSIFIED)
{
pn.ClusterId = c;
}
}
}
public void Process(DbscanPoint <TF> point)
{
if (point.ClusterId.HasValue && !Result.Clusters.ContainsKey(point.ClusterId.Value))
{
Result.Clusters.Add(point.ClusterId.Value, new List <DbscanPoint <TF> >());
}
switch (point)
{
case DbscanPoint <TF> core when core.PointType == PointType.Core:
Result.Clusters[core.ClusterId.Value].Add(core);
break;
case DbscanPoint <TF> border when border.PointType == PointType.Border:
Result.Clusters[border.ClusterId.Value].Add(border);
break;
case DbscanPoint <TF> noise when noise.PointType == PointType.Noise:
Result.Noise.Add(noise);
break;
}
}
public bool CheckCenterEmpty(T[] clusterPoints, T centerPoint, double epsilon, int maxPts)
{
DbscanPoint <T>[] clusterPointsDbscan = clusterPoints.Select(x => new DbscanPoint <T>(x)).ToArray();
var tree = new KDTree.KDTree <DbscanPoint <T> >(3);
for (var i = 0; i < clusterPointsDbscan.Length; ++i)
{
Record temp = clusterPointsDbscan[i].ClusterPoint;
tree.AddPoint(new double[] { temp.posX, temp.posY, temp.posZ }, clusterPointsDbscan[i]);
}
Record tempCenter = new DbscanPoint <T>(centerPoint).ClusterPoint;
tree.AddPoint(new double[] { tempCenter.posX, tempCenter.posY, tempCenter.posZ }, new DbscanPoint <T>(centerPoint));
var neighborPts = RegionQuery(tree, centerPoint, epsilon);
if (neighborPts.Length > maxPts)
{
return(false);
}
else
{
return(true);
}
}
public PointProcessFinished(DbscanPoint <TF> point)
{
Point = point;
}
public PointProcessStarted(DbscanPoint <TF> point)
{
Point = point;
}
public PointAlreadyProcessed(DbscanPoint <TF> point)
{
Point = point;
}
public RegionQueryStarted(DbscanPoint <TF> point, double epsilon, int minimumPoints)
{
Point = point;
Epsilon = epsilon;
MinimumPoints = minimumPoints;
}
public RegionQueryFinished(DbscanPoint <TF> point, DbscanPoint <TF>[] neighborPoints)
{
Point = point;
NeighborPoints = neighborPoints;
}
public PointTypeAssigned(DbscanPoint <TF> point, PointType assignedType)
{
Point = point;
AssignedType = assignedType;
}
private void visit(DbscanPoint p)
{
p.IsVisited = true;
increceCounterAndNotify();
}
