astar 注释
This commit is contained in:
1
source/bin/framework.d.ts
vendored
1
source/bin/framework.d.ts
vendored
@@ -61,6 +61,7 @@ declare class PriorityQueue<T extends PriorityQueueNode> {
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constructor(maxNodes: number);
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clear(): void;
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readonly count: number;
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readonly maxSize: number;
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contains(node: T): boolean;
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enqueue(node: T, priority: number): void;
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dequeue(): T;
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@@ -418,7 +418,22 @@ var PriorityQueue = (function () {
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enumerable: true,
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configurable: true
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});
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Object.defineProperty(PriorityQueue.prototype, "maxSize", {
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get: function () {
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return this._nodes.length - 1;
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},
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enumerable: true,
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configurable: true
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});
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PriorityQueue.prototype.contains = function (node) {
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if (!node) {
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console.error("node cannot be null");
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return false;
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}
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if (node.queueIndex < 0 || node.queueIndex >= this._nodes.length) {
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console.error("node.QueueIndex has been corrupted. Did you change it manually? Or add this node to another queue?");
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return false;
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}
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return (this._nodes[node.queueIndex] == node);
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};
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PriorityQueue.prototype.enqueue = function (node, priority) {
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2
source/bin/framework.min.js
vendored
2
source/bin/framework.min.js
vendored
File diff suppressed because one or more lines are too long
@@ -3,6 +3,12 @@
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* 计算路径给定的IAstarGraph和开始/目标位置
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*/
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class AStarPathfinder {
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/**
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* 尽可能从开始到目标找到一条路径。如果没有找到路径,则返回null。
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* @param graph
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* @param start
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* @param goal
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*/
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public static search<T>(graph: IAstarGraph<T>, start: T, goal: T){
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let foundPath = false;
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let cameFrom = new Map<T, T>();
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@@ -60,6 +66,12 @@ class AStarPathfinder {
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return null;
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}
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/**
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* 从cameFrom字典重新构造路径
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* @param cameFrom
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* @param start
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* @param goal
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*/
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public static recontructPath<T>(cameFrom: Map<T, T>, start: T, goal: T): T[]{
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let path = [];
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let current = goal;
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@@ -33,13 +33,18 @@ class AstarGridGraph implements IAstarGraph<Vector2> {
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}
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/**
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* 检查节点是否可以通过。墙壁是不可逾越的。
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* 检查节点是否可以通过。walls是不可逾越的。
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* @param node
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*/
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public isNodePassable(node: Vector2): boolean {
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return !this.walls.firstOrDefault(wall => JSON.stringify(wall) == JSON.stringify(node));
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}
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/**
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* 调用AStarPathfinder.search的快捷方式
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* @param start
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* @param goal
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*/
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public search(start: Vector2, goal: Vector2){
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return AStarPathfinder.search(this, start, goal);
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}
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@@ -1,5 +1,22 @@
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/**
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* graph的接口,可以提供给AstarPathfinder.search方法
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*/
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interface IAstarGraph<T> {
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/**
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* getNeighbors方法应该返回从传入的节点可以到达的任何相邻节点
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* @param node
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*/
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getNeighbors(node: T): Array<T>;
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/**
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* 计算从从from到to的成本
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* @param from
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* @param to
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*/
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cost(from: T, to: T): number;
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/**
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* 计算从node到to的启发式。参见WeightedGridGraph了解常用的Manhatten方法。
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* @param node
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* @param goal
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*/
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heuristic(node: T, goal: T);
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}
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@@ -1,27 +1,74 @@
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/**
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* 使用堆实现最小优先级队列 O(1)复杂度
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* 这种查找速度比使用字典快5-10倍
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* 但是,由于IPriorityQueue.contains()是许多寻路算法中调用最多的方法,因此尽可能快地实现它对于我们的应用程序非常重要。
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*/
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class PriorityQueue<T extends PriorityQueueNode> {
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private _numNodes: number;
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private _nodes: T[];
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private _numNodesEverEnqueued;
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/**
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* 实例化一个新的优先级队列
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* @param maxNodes 允许加入队列的最大节点(执行此操作将导致undefined的行为)
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*/
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constructor(maxNodes: number) {
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this._numNodes = 0;
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this._nodes = new Array(maxNodes + 1);
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this._numNodesEverEnqueued = 0;
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}
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/**
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* 从队列中删除每个节点。
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* O(n)复杂度 所有尽可能少调用该方法
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*/
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public clear() {
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this._nodes.splice(1, this._numNodes);
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this._numNodes = 0;
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}
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/**
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* 返回队列中的节点数。
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* O(1)复杂度
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*/
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public get count() {
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return this._numNodes;
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}
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/**
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* 返回可同时进入此队列的最大项数。一旦你达到这个数字(即。一旦Count == MaxSize),尝试加入另一个项目将导致undefined的行为
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* O(1)复杂度
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*/
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public get maxSize() {
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return this._nodes.length - 1;
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}
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/**
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* 返回(在O(1)中)给定节点是否在队列中
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* O (1)复杂度
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* @param node
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*/
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public contains(node: T): boolean {
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if (!node){
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console.error("node cannot be null");
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return false;
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}
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if (node.queueIndex < 0 || node.queueIndex >= this._nodes.length){
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console.error("node.QueueIndex has been corrupted. Did you change it manually? Or add this node to another queue?");
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return false;
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}
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return (this._nodes[node.queueIndex] == node);
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}
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/**
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* 将节点放入优先队列 较低的值放在前面 先入先出
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* 如果队列已满,则结果undefined。如果节点已经加入队列,则结果undefined。
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* O(log n)
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* @param node
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* @param priority
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*/
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public enqueue(node: T, priority: number) {
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node.priority = priority;
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this._numNodes++;
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@@ -31,12 +78,21 @@ class PriorityQueue<T extends PriorityQueueNode> {
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this.cascadeUp(this._nodes[this._numNodes]);
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}
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/**
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* 删除队列头(具有最小优先级的节点;按插入顺序断开连接),并返回它。如果队列为空,结果undefined
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* O(log n)
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*/
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public dequeue(): T {
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let returnMe = this._nodes[1];
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this.remove(returnMe);
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return returnMe;
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}
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/**
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* 从队列中删除一个节点。节点不需要是队列的头。如果节点不在队列中,则结果未定义。如果不确定,首先检查Contains()
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* O(log n)
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* @param node
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*/
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public remove(node: T) {
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if (node.queueIndex == this._numNodes) {
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this._nodes[this._numNodes] = null;
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@@ -52,6 +108,9 @@ class PriorityQueue<T extends PriorityQueueNode> {
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this.onNodeUpdated(formerLastNode);
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}
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/**
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* 检查以确保队列仍然处于有效状态。用于测试/调试队列。
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*/
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public isValidQueue(): boolean {
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for (let i = 1; i < this._nodes.length; i++) {
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if (this._nodes[i]) {
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@@ -71,24 +130,29 @@ class PriorityQueue<T extends PriorityQueueNode> {
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}
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private onNodeUpdated(node: T) {
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// 将更新后的节点按适当的方式向上或向下冒泡
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let parentIndex = Math.floor(node.queueIndex / 2);
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let parentNode = this._nodes[parentIndex];
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if (parentIndex > 0 && this.hasHigherPriority(node, parentNode)) {
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this.cascadeUp(node);
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} else {
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// 注意,如果parentNode == node(即节点是根),则将调用CascadeDown。
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this.cascadeDown(node);
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}
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}
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private cascadeDown(node: T) {
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// 又名Heapify-down
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let newParent: T;
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let finalQueueIndex = node.queueIndex;
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while (true) {
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newParent = node;
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let childLeftIndex = 2 * finalQueueIndex;
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// 检查左子节点的优先级是否高于当前节点
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if (childLeftIndex > this._numNodes) {
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// 这可以放在循环之外,但是我们必须检查newParent != node两次
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node.queueIndex = finalQueueIndex;
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this._nodes[finalQueueIndex] = node;
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break;
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@@ -99,6 +163,7 @@ class PriorityQueue<T extends PriorityQueueNode> {
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newParent = childLeft;
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}
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// 检查右子节点的优先级是否高于当前节点或左子节点
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let childRightIndex = childLeftIndex + 1;
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if (childRightIndex <= this._numNodes) {
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let childRight = this._nodes[childRightIndex];
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@@ -107,13 +172,17 @@ class PriorityQueue<T extends PriorityQueueNode> {
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}
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}
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// 如果其中一个子节点具有更高(更小)的优先级,则交换并继续级联
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if (newParent != node) {
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// 将新的父节点移动到它的新索引
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// 节点将被移动一次,这样做比调用Swap()少一个赋值操作。
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this._nodes[finalQueueIndex] = newParent;
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let temp = newParent.queueIndex;
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newParent.queueIndex = finalQueueIndex;
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finalQueueIndex = temp;
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} else {
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// 参见上面的笔记
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node.queueIndex = finalQueueIndex;
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this._nodes[finalQueueIndex] = node;
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break;
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@@ -121,13 +190,20 @@ class PriorityQueue<T extends PriorityQueueNode> {
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}
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}
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/**
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* 当没有内联时,性能会稍微好一些
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* @param node
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*/
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private cascadeUp(node: T) {
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// 又名Heapify-up
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let parent = Math.floor(node.queueIndex / 2);
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while (parent >= 1) {
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let parentNode = this._nodes[parent];
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if (this.hasHigherPriority(parentNode, node))
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break;
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// 节点具有较低的优先级值,因此将其向上移动到堆中
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// 出于某种原因,使用Swap()比使用单独的操作更快,如CascadeDown()
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this.swap(node, parentNode);
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parent = Math.floor(node.queueIndex / 2);
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@@ -135,14 +211,22 @@ class PriorityQueue<T extends PriorityQueueNode> {
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}
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private swap(node1: T, node2: T) {
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// 交换节点
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this._nodes[node1.queueIndex] = node2;
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this._nodes[node2.queueIndex] = node1;
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// 交换他们的indicies
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let temp = node1.queueIndex;
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node1.queueIndex = node2.queueIndex;
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node2.queueIndex = temp;
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}
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/**
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* 如果higher的优先级高于lower,则返回true,否则返回false。
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* 注意,调用HasHigherPriority(节点,节点)(即。两个参数为同一个节点)将返回false
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* @param higher
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* @param lower
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*/
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private hasHigherPriority(higher: T, lower: T) {
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return (higher.priority < lower.priority ||
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(higher.priority == lower.priority && higher.insertionIndex < lower.insertionIndex));
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