Home Backend Development Golang How to implement quadtree using Golang

How to implement quadtree using Golang

Mar 30, 2023 am 09:06 AM

Quadtree (Quadtree) is a tree data structure based on spatial division, which is widely used in geographic information systems (GIS), How to implement quadtree using Golang processing, natural language processing and other fields. It is characterized by fast and efficient spatial queries and spatial indexes.

In this article, we will introduce how to implement a quadtree using Golang.

1. What is a quadtree
A quadtree is a variant of a binary tree, with each node containing up to four child nodes. In two-dimensional space, it can be seen as dividing the plane into four quadrants. As shown in the figure below:

How to implement quadtree using Golang

#Using a quadtree can divide the space into smaller and smaller areas, making the query more efficient. For example, if we want to query whether a certain point is within an area, we can first determine the quadrant to which the point belongs, then recursively enter the quadrant and continue the query until the smallest area is found, and then judge all points in it.

2. Implementation of Quadtree
First, we need to define a node structure:

type QuadNode struct {
    NW *QuadNode // 西北节点
    NE *QuadNode // 东北节点
    SW *QuadNode // 西南节点
    SE *QuadNode // 东南节点
    X  float64   // 节点的横坐标
    Y  float64   // 节点的纵坐标
}
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The node contains four child nodes and node coordinates. When implementing the query function, we need to recursively access child nodes. Therefore, we can define a QuadTree structure:

type QuadTree struct {
    root *QuadNode
}
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Each QuadTree object contains a root node. Next, we implement some basic operations. The first is to insert a node into QuadTree:

func (t *QuadTree) Insert(x, y float64) {
    if t.root == nil {
        t.root = &QuadNode{X: x, Y: y}
    } else {
        t.root.Insert(x, y)
    }
}
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If the root node of QuadTree is empty, use this node as the root node. Otherwise, insert the node into a child node of the root node. The insertion operation of the node can be performed recursively until a suitable child node is found:

func (n *QuadNode) Insert(x, y float64) {
    switch {
    case x >= n.X && y >= n.Y:
        if n.NE == nil {
            n.NE = &QuadNode{X: x, Y: y}
        } else {
            n.NE.Insert(x, y)
        }
    case x >= n.X && y = n.Y:
        if n.NW == nil {
            n.NW = &QuadNode{X: x, Y: y}
        } else {
            n.NW.Insert(x, y)
        }
    case x <p>In the query operation, we can recursively enter the child node to search. For each node, we need to determine whether it contains the target point. If included, add the node to the result set; otherwise, recursively enter its child nodes to continue searching: </p><pre class="brush:php;toolbar:false">func (t *QuadTree) QueryRange(x1, y1, x2, y2 float64) []*QuadNode {
    result := []*QuadNode{}
    t.root.QueryRange(x1, y1, x2, y2, &result)
    return result
}

func (n *QuadNode) QueryRange(x1, y1, x2, y2 float64, result *[]*QuadNode) {
    if n == nil {
        return
    }
    if n.X >= x1 && n.X = y1 && n.Y = x1 && n.X = y1 && n.Y <p> We can also implement other functions such as deleting nodes and calculating the number of nodes, which will not be described here. Finally, we can use the following code to test the implemented quadtree: </p><pre class="brush:php;toolbar:false">func main() {
    tree := &QuadTree{}
    tree.Insert(1, 2)
    tree.Insert(2, 3)
    tree.Insert(3, 4)
    tree.Insert(4, 5)

    result := tree.QueryRange(2, 2, 4, 4)
    fmt.Println(result)
}
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This code inserts four points in the QuadTree and queries the diagonals with (2, 2) and (4, 4) All points within the rectangle. The query results are [(2, 3), (3, 4)], as expected.

3. Summary
This article introduces the process of using Golang to implement a quadtree. Quadtree is an efficient spatial index method that can play an important role in processing large amounts of spatial data. Using Golang to implement quadtree code is simple and easy to understand, and can easily process two-dimensional spatial data.

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