internal void FindClusterCandidate_(int xyindex, com.epl.geometry.Clusterer.ClusterCandidate candidate)
{
com.epl.geometry.Point2D pointOfInterest = new com.epl.geometry.Point2D();
m_shape.GetXY(xyindex, pointOfInterest);
double x_0 = pointOfInterest.x - m_origin.x;
double x = x_0 * m_inv_cell_size;
double y0 = pointOfInterest.y - m_origin.y;
double y = y0 * m_inv_cell_size;
int xi = (int)x;
int yi = (int)y;
// find the nearest neighbour in the 4 neigbouring cells.
candidate.vertex = -1;
candidate.distance = com.epl.geometry.NumberUtils.DoubleMax();
com.epl.geometry.Clusterer.ClusterCandidate c = new com.epl.geometry.Clusterer.ClusterCandidate();
for (int dx = 0; dx <= 1; dx += 1)
{
for (int dy = 0; dy <= 1; dy += 1)
{
int bucket_ptr = m_hash_table.GetFirstInBucket(HashFunction_(xi + dx, yi + dy));
if (bucket_ptr != com.epl.geometry.IndexHashTable.NullNode())
{
GetNearestNeighbourCandidate_(xyindex, pointOfInterest, bucket_ptr, c);
if (c.vertex != com.epl.geometry.IndexHashTable.NullNode() && c.distance < candidate.distance)
{
candidate = c;
}
}
}
}
}
internal void GetNearestNeighbourCandidate_(int xyindex, com.epl.geometry.Point2D pointOfInterest, int bucket_ptr, com.epl.geometry.Clusterer.ClusterCandidate candidate)
{
candidate.vertex = -1;
candidate.distance = com.epl.geometry.NumberUtils.DoubleMax();
com.epl.geometry.Point2D pt = new com.epl.geometry.Point2D();
for (int node = bucket_ptr; node != -1; node = m_hash_table.GetNextInBucket(node))
{
int xyind = m_hash_table.GetElement(node);
if (xyindex == xyind)
{
continue;
}
m_shape.GetXY(xyind, pt);
if (IsClusterCandidate_(pointOfInterest.x, pointOfInterest.y, pt.x, pt.y, m_sqr_tolerance))
{
pt.Sub(pointOfInterest);
double l = pt.Length();
if (l < candidate.distance)
{
candidate.distance = l;
candidate.vertex = xyind;
}
}
}
}
