user3750097 - 8 months ago 49

Java Question

I'm currently implementing a KD Tree and nearest neighbour search, following the algorithm described here: http://ldots.org/kdtree/

I have come across a couple of different ways to implement a KD Tree, one in which points are stored in internal nodes, and one in which they are only stored in leaf nodes. As I have a very simple use case (all I need to do is construct the tree once, it does not need to be modified), I went for the leaf-only approach is it seemed to be simpler to implement. I have successfully implemented everything, the tree is always constructed successfully and in most cases the nearest neighbour search returns the correct value. However, I have some issues that with some data sets and search points, the algorithm returns an incorrect value. Consider the points:

`[[6, 1], [5, 5], [9, 6], [3, 81], [4, 9], [4, 0], [7, 9], [2, 9], [6, 74]]`

Which constructs a tree looking something like this (excuse my bad diagramming):

Where the square leaf nodes are those that contain the points, and the circular nodes contain the median value for splitting the list at that depth. When calling my nearest neighbour search on this data set, and looking for the nearest neighbour to

`[6, 74]`

`[7, 9]`

`[6, 74]`

`[3, 81]`

`[7, 9]`

Here are the points plotted, for visualization, the red point being the one I am attempting to find the nearest neighbour for:

If it helps, my search method is as follows:

`private LeafNode search(int depth, Point point, KDNode node) {`

if(node instanceof LeafNode)

return (LeafNode)node;

else {

MedianNode medianNode = (MedianNode) node;

double meanValue = medianNode.getValue();

double comparisonValue = 0;

if(valueEven(depth)) {

comparisonValue = point.getX();

}

else {

comparisonValue = point.getY();

}

KDNode nextNode;

if(comparisonValue < meanValue) {

if (node.getLeft() != null)

nextNode = node.getLeft();

else

nextNode = node.getRight();

}

else {

if (node.getRight() != null)

nextNode = node.getRight();

else

nextNode = node.getLeft();

}

return search(depth + 1, point, nextNode);

}

}

So my questions are:

- Is this what to expect from nearest neighbour search in a KD Tree, or should I be getting the closest point to the point I am searching for (as this is my only reason for using the tree)?
- Is this an issue only with this form of KD Tree, should I change it to store points in inner nodes to solve this?

Answer

A correct implementation of a KD-tree always finds the closest point(it doesn't matter if points are stored in leaves only or not). Your search method is not correct, though. Here is how it should look like:

```
bestDistance = INF
def getClosest(node, point)
if node is null
return
// I will assume that this node splits points
// by their x coordinate for the sake of brevity.
if node is a leaf
// updateAnswer updates bestDistance value
// and keeps track of the closest point to the given one.
updateAnswer(node.point, point)
else
middleX = node.median
if point.x < middleX
getClosest(node.left, point)
if node.right.minX - point.x < bestDistance
getClosest(node.right, point)
else
getClosest(node.right, point)
if point.x - node.left.maxX < bestDistance
getClosest(node.left, point)
```