/// <summary>
/// Nearest neighbor search method to find the single nearest neighbor at a given point.
/// Translated from https://github.com/gvd/kdtree/blob/master/kdtree.h
/// </summary>
/// <param name="query">The nearest neighbor search query point.</param>
/// <returns>The closest node to the parameter query is returned.</returns>
//public KDNode NNSearch(Point query)
//{
// MinPriorityQueue<Tuple<double, KDNode>> pq = new MinPriorityQueue<Tuple<double, KDNode>>();
// //Tuple<double, KDNode> best = new Tuple<double, KDNode>(1.79769e+308, root);
// pq.Enqueue(new Tuple<double, KDNode>(0.0, root));
// do
// {
// var current = pq.Dequeue();
// //if (current.Item1 >= best.Item1)
// //{
// // if (EuclideanDistance(query, current.Item2.Data) > EuclideanDistance(query, best.Item2.Data))
// // return best.Item2;
// // else
// // return current.Item2;
// //}
// List<KDNode> a = new List<KDNode>
// {
// };
// var currentNode = current.Item2;
// //double d = EuclideanDistance(query, currentNode.Data);
// //double dx = Subtract(query, currentNode.Data, currentNode.Depth);
// if ()
// {
// best = new Tuple<double, KDNode>(d, currentNode);
// }
// KDNode near, far;
// near = currentNode.Left;
// else
// near = currentNode.Right;
// far = currentNode.Right;
// else
// far = currentNode.Left;
// if (near != null)
// pq.Enqueue(new Tuple<double, KDNode>(0, near));
// if (far != null)
// pq.Enqueue(new Tuple<double, KDNode>(0, far));
// } while (pq.Count() != 0);
// return best.Item2;
//}
public List <KDNode> LocSearch(Point query)
{
MinPriorityQueue <Tuple <double, KDNode> > pq = new MinPriorityQueue <Tuple <double, KDNode> >();
Point p = new Point(0, 0);
List <KDNode> a = new List <KDNode>
{
};
pq.Enqueue(new Tuple <double, KDNode>(0.0, root));
do
{
var current = pq.Dequeue();
// current.Item2.Data;
var currentNode = current.Item2;
if (query.x < currentNode.Data.x && currentNode.Data.x < query.x && query.y < currentNode.Data.y)
{
a.Add(currentNode);
}
double d = EuclideanDistance(query, currentNode.Data);
double dx = Subtract(query, currentNode.Data, currentNode.Depth);
KDNode near;
if (dx <= 0)
{
near = currentNode.Left;
}
else
{
near = currentNode.Right;
}
//if (dx <= 0)
// far = currentNode.Right;
//else
// far = currentNode.Left;
if (near != null)
{
pq.Enqueue(new Tuple <double, KDNode>(0, near));
}
} while (pq.Count() != 0);
return(a);
}
public List <String> LocSearch(Point query1, Point query2)
{
MinPriorityQueue <Tuple <double, KDNode> > pq = new MinPriorityQueue <Tuple <double, KDNode> >();
List <String> a = new List <String>();
pq.Enqueue(new Tuple <double, KDNode>(0.0, root));
do
{
var current = pq.Dequeue();
var currentNode = current.Item2;
if (query1.x > query2.x && query1.y > query2.y)
{
if (query1.x >= currentNode.Data.x && query2.x <= currentNode.Data.x && query1.y >= currentNode.Data.y && query2.y <= currentNode.Data.y)
{
a.Add(currentNode.Data.x.ToString());
a.Add(currentNode.Data.y.ToString());
}
}
else if (query1.x < query2.x && query1.y < query2.y)
{
if (query1.x <= currentNode.Data.x && query2.x >= currentNode.Data.x && query1.y <= currentNode.Data.y && query2.y >= currentNode.Data.y)
{
a.Add(currentNode.Data.x.ToString());
a.Add(currentNode.Data.y.ToString());
}
}
else if (query1.x < query2.x && query1.y > query2.y)
{
if (query1.x <= currentNode.Data.x && query2.x >= currentNode.Data.x && query1.y >= currentNode.Data.y && query2.y <= currentNode.Data.y)
{
a.Add(currentNode.Data.x.ToString());
a.Add(currentNode.Data.y.ToString());
}
}
else if (query1.x > query2.x && query1.y < query2.y)
{
if (query1.x >= currentNode.Data.x && query2.x <= currentNode.Data.x && query1.y <= currentNode.Data.y && query2.y >= currentNode.Data.y)
{
a.Add(currentNode.Data.x.ToString());
a.Add(currentNode.Data.y.ToString());
}
}
KDNode near, far;
near = currentNode.Right;
far = currentNode.Left;
if (near != null)
{
pq.Enqueue(new Tuple <double, KDNode>(0, near));
}
if (far != null)
{
pq.Enqueue(new Tuple <double, KDNode>(0, far));
}
} while (pq.Count() != 0);
return(a);
}