This is a Java Program to implement 2D KD Tree and perform partial search(Searching a node with either of the coordinate). In computer science, a k-d tree (short for k-dimensional tree) is a space-partitioning data structure for organizing points in a k-dimensional space. k-d trees are a useful data structure for several applications, such as searches involving a multidimensional search key (e.g. range searches and nearest neighbor searches). k-d trees are a special case of binary space partitioning trees.
Here is the source code of the Java Program to Perform Partial Key Search in a K-D Tree. The Java program is successfully compiled and run on a Windows system. The program output is also shown below.
//This is a java program to perform partial search in 2D KD Tree
import java.io.IOException;
import java.util.Scanner;
class KD2DNode
{
int axis;
double[] x;
int id;
boolean checked;
boolean orientation;
KD2DNode Parent;
KD2DNode Left;
KD2DNode Right;
public KD2DNode(double[] x0, int axis0)
{
x = new double[2];
axis = axis0;
for (int k = 0; k < 2; k++)
x[k] = x0[k];
Left = Right = Parent = null;
checked = false;
id = 0;
}
public KD2DNode FindParent(double[] x0)
{
KD2DNode parent = null;
KD2DNode next = this;
int split;
while (next != null)
{
split = next.axis;
parent = next;
if (x0[split] > next.x[split])
next = next.Right;
else
next = next.Left;
}
return parent;
}
public KD2DNode Insert(double[] p)
{
x = new double[2];
KD2DNode parent = FindParent(p);
if (equal(p, parent.x, 2) == true)
return null;
KD2DNode newNode = new KD2DNode(p,
parent.axis + 1 < 2 ? parent.axis + 1 : 0);
newNode.Parent = parent;
if (p[parent.axis] > parent.x[parent.axis])
{
parent.Right = newNode;
newNode.orientation = true; //
} else
{
parent.Left = newNode;
newNode.orientation = false; //
}
return newNode;
}
boolean equal(double[] x1, double[] x2, int dim)
{
for (int k = 0; k < dim; k++)
{
if (x1[k] != x2[k])
return false;
}
return true;
}
double distance2(double[] x1, double[] x2, int dim)
{
double S = 0;
for (int k = 0; k < dim; k++)
S += (x1[k] - x2[k]) * (x1[k] - x2[k]);
return S;
}
}
class KD2DTree
{
KD2DNode Root;
int TimeStart, TimeFinish;
int CounterFreq;
double d_min;
KD2DNode nearest_neighbour;
int KD_id;
int nList;
KD2DNode CheckedNodes[];
int checked_nodes;
KD2DNode List[];
double x_min[], x_max[];
boolean max_boundary[], min_boundary[];
int n_boundary;
public KD2DTree(int i)
{
Root = null;
KD_id = 1;
nList = 0;
List = new KD2DNode[i];
CheckedNodes = new KD2DNode[i];
max_boundary = new boolean[2];
min_boundary = new boolean[2];
x_min = new double[2];
x_max = new double[2];
}
public boolean add(double[] x)
{
if (nList >= 2000000 - 1)
return false; // can't add more points
if (Root == null)
{
Root = new KD2DNode(x, 0);
Root.id = KD_id++;
List[nList++] = Root;
} else
{
KD2DNode pNode;
if ((pNode = Root.Insert(x)) != null)
{
pNode.id = KD_id++;
List[nList++] = pNode;
}
}
return true;
}
public KD2DNode find_nearest(double[] x)
{
if (Root == null)
return null;
checked_nodes = 0;
KD2DNode parent = Root.FindParent(x);
nearest_neighbour = parent;
d_min = Root.distance2(x, parent.x, 2);
;
if (parent.equal(x, parent.x, 2) == true)
return nearest_neighbour;
search_parent(parent, x);
uncheck();
return nearest_neighbour;
}
public void check_subtree(KD2DNode node, double[] x)
{
if ((node == null) || node.checked)
return;
CheckedNodes[checked_nodes++] = node;
node.checked = true;
set_bounding_cube(node, x);
int dim = node.axis;
double d = node.x[dim] - x[dim];
if (d * d > d_min)
{
if (node.x[dim] > x[dim])
check_subtree(node.Left, x);
else
check_subtree(node.Right, x);
} else
{
check_subtree(node.Left, x);
check_subtree(node.Right, x);
}
}
public void set_bounding_cube(KD2DNode node, double[] x)
{
if (node == null)
return;
int d = 0;
double dx;
for (int k = 0; k < 2; k++)
{
dx = node.x[k] - x[k];
if (dx > 0)
{
dx *= dx;
if (!max_boundary[k])
{
if (dx > x_max[k])
x_max[k] = dx;
if (x_max[k] > d_min)
{
max_boundary[k] = true;
n_boundary++;
}
}
} else
{
dx *= dx;
if (!min_boundary[k])
{
if (dx > x_min[k])
x_min[k] = dx;
if (x_min[k] > d_min)
{
min_boundary[k] = true;
n_boundary++;
}
}
}
d += dx;
if (d > d_min)
return;
}
if (d < d_min)
{
d_min = d;
nearest_neighbour = node;
}
}
public KD2DNode search_parent(KD2DNode parent, double[] x)
{
for (int k = 0; k < 2; k++)
{
x_min[k] = x_max[k] = 0;
max_boundary[k] = min_boundary[k] = false; //
}
n_boundary = 0;
KD2DNode search_root = parent;
while (parent != null && (n_boundary != 2 * 2))
{
check_subtree(parent, x);
search_root = parent;
parent = parent.Parent;
}
return search_root;
}
public void uncheck()
{
for (int n = 0; n < checked_nodes; n++)
CheckedNodes[n].checked = false;
}
public void inorder()
{
inorder(Root);
}
private void inorder(KD2DNode root)
{
if (root != null)
{
inorder(root.Left);
System.out.print("(" + root.x[0] + ", " + root.x[1] + ") ");
inorder(root.Right);
}
}
public void preorder()
{
preorder(Root);
}
private void preorder(KD2DNode root)
{
if (root != null)
{
System.out.print("(" + root.x[0] + ", " + root.x[1] + ") ");
inorder(root.Left);
inorder(root.Right);
}
}
public void postorder()
{
postorder(Root);
}
private void postorder(KD2DNode root)
{
if (root != null)
{
inorder(root.Left);
inorder(root.Right);
System.out.print("(" + root.x[0] + ", " + root.x[1] + ") ");
}
}
public void search(double p)
{
search(Root, p);
}
private void search(KD2DNode root, double p)
{
if (root != null)
{
search(root.Left, p);
if (p == root.x[0] || p == root.x[1])
System.out.print("True (" + root.x[0] + ", " + root.x[1]
+ ") ");
search(root.Right, p);
}
}
}
public class KD2D_Partial_Search
{
public static void main(String args[]) throws IOException
{
int numpoints = 5;
Scanner sc = new Scanner(System.in);
KD2DTree kdt = new KD2DTree(numpoints);
double x[] = new double[2];
x[0] = 0.0;
x[1] = 0.0;
kdt.add(x);
x[0] = 3.3;
x[1] = 1.5;
kdt.add(x);
x[0] = 4.7;
x[1] = 11.1;
kdt.add(x);
x[0] = 5.0;
x[1] = 12.3;
kdt.add(x);
x[0] = 5.1;
x[1] = 1.2;
kdt.add(x);
System.out.println("Enter the any one of the co-ordinates of the point: <x>/<y>");
double q = sc.nextDouble();
kdt.search(q);
System.out.println("\nInorder of 2D Kd tree: ");
kdt.inorder();
System.out.println("\nPreorder of 2D Kd tree: ");
kdt.preorder();
System.out.println("\npostorder of 2D Kd tree: ");
kdt.postorder();
sc.close();
}
}
Output:
$ javac KD2D_Partial_Search.java $ java KD2D_Partial_Search Partial Key Search Enter the any one of the co-ordinates of the point: <x>/<y> 5 True (5.0, 12.3) Inorder of 2D Kd tree: (0.0, 0.0) (5.1, 1.2) (3.3, 1.5) (4.7, 11.1) (5.0, 12.3) Preorder of 2D Kd tree: (0.0, 0.0) (5.1, 1.2) (3.3, 1.5) (4.7, 11.1) (5.0, 12.3) postorder of 2D Kd tree: (5.1, 1.2) (3.3, 1.5) (4.7, 11.1) (5.0, 12.3) (0.0, 0.0)
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