A*(A-star) 算法给出了错误的路径和崩溃
A*(A-star) algorithm gives wrong path and crashes
我正在 react.js 中实现 A*(A-star) 算法，但只要 startNode(green) 或 destinationNode(blue) 有多个邻居，或者如果有循环，我的程序就会崩溃图形。添加和删除邻居 from/to openList 或更新 getPath() 函数中的 parentId 时出现问题。我什至看不到控制台，因为网站出现故障。
每个节点都有：id,name,x,y,connectedToIdsList:[],gcost:Infinity,fcost:0,heuristic:0,parentId:null。
我正在将路径发送到打印出路径的另一个组件“TodoList”。我的程序不应该 return 路径，而是在我向列表添加节点和边时不断更新路径。请帮忙，我已经被困了几个小时了：/
我的代码：
export default class TurnByTurnComponent extends React.PureComponent {
constructor(props) {
super(props);
this.state = { shortestPath: [] }
}
render() {
const {
destinationLocationId,
locations,
originLocationId
} = this.props;
let path = []
if (destinationLocationId != null && originLocationId != null) {
if (originLocationId == destinationLocationId) { //check if the startNode node is the end node
return originLocationId;
}
var openList = [];
let startNode = getNodeById(originLocationId);
let destinationNode = getNodeById(destinationLocationId)
if (startNode.connectedToIds.length > 0 && destinationNode.connectedToIds.length > 0) { //check if start and destination nodes are connected first
startNode.gcost = 0
startNode.heuristic = manhattanDistance(startNode, destinationNode)
startNode.fcost = startNode.gcost + startNode.heuristic;
//perform A*
openList.push(startNode); //starting with the startNode
while (openList.length > 0) {
console.log("inside while")
var currentNode = getNodeOfMinFscore(openList); //get the node of the minimum f cost of all nodes in the openList
if (currentIsEqualDistanation(currentNode)) {
path = getPath(currentNode);
}
deleteCurrentFromOpenList(currentNode, openList);
for (let neighbourId of currentNode.connectedToIds) {
var neighbourNode = getNodeById(neighbourId);
currentNode.gcost = currentNode.gcost + manhattanDistance(currentNode, neighbourNode);
if (currentNode.gcost < neighbourNode.gcost) {
neighbourNode.parentId = currentNode.id; // keep track of the path
// total cost saved in neighbour.g
neighbourNode.gcost = currentNode.gcost;
neighbourNode.heuristic = manhattanDistance(neighbourNode, destinationNode);
neighbourNode.fcost = neighbourNode.gcost + neighbourNode.heuristic; //calculate f cost of the neighbourNode
addNeighbourNodeToOpenList(neighbourNode, openList);
}
}
}
path = path.reverse().join("->");
}
}
function addNeighbourNodeToOpenList(neighbourNode, openList) {
//add neighbourNode to the open list to be discovered later
if (!openList.includes(neighbourNode)) {
openList.push(neighbourNode);
}
}
function deleteCurrentFromOpenList(currNode, openList) {
const currIndex = openList.indexOf(currNode);
openList.splice(currIndex, 1); //deleting currentNode from openList
}
function currentIsEqualDistanation(currNode) {
//check if we reached out the distanation node
return (currNode.id == destinationLocationId)
}
function getNodeById(nid) {
var node;
for (let i = 0; i < locations.length; i++) {
if (locations[i].id == nid) {
node = locations[i]
}
}
return node
}
function getPath(destNode) {
console.log("inside getpath")
var parentPath = []
var parent;
while (destNode.parentId != null) {
parentPath.push(destNode.name)
parent = destNode.parentId;
destNode = getNodeById(parent);
}
//adding startNode to the path
parentPath.push(getNodeById(originLocationId).name)
return parentPath;
}
function getNodeOfMinFscore(openList) {
var minFscore = openList[0].fcost; //initValue
var nodeOfminFscore;
for (let i = 0; i < openList.length; i++) {
if (openList[i].fcost <= minFscore) {
minFscore = openList[i].fcost //minFvalue
nodeOfminFscore = openList[i]
}
}
return nodeOfminFscore
}
//manhattan distance is for heuristic and gScore. Here I use Manhattan instead of Euclidean
//because in this example we dont have diagnosal path.
function manhattanDistance(stNode, dstNode) {
var x = Math.abs(dstNode.x - stNode.x);
var y = Math.abs(dstNode.y - stNode.y);
var dist = x + y;
return dist;
}
return (
<div className="turn-by-turn-component">
<TodoList
list={"Shortest path: ", [path]}
/>
<TodoList
list={[]}
/>
</div>
);
}
}
TurnByTurnComponent.propTypes = {
destinationLocationId: PropTypes.number,
locations: PropTypes.arrayOf(PropTypes.shape({
id: PropTypes.number.isRequired,
name: PropTypes.string.isRequired,
x: PropTypes.number.isRequired,
y: PropTypes.number.isRequired,
connectedToIds: PropTypes.arrayOf(PropTypes.number.isRequired).isRequired
})),
originLocationId: PropTypes.number
};
更新新问题
链接新节点前后的图片。当我更新图形并添加新节点时，路径消失了。如果我仍然向图中添加新节点和边，有时会回来等等。正如我所说，每个节点都有：id、name、x、y、connectedToIdsList:[]、gcost:Infinity、fcost:0、heuristic:0、parentId:null。
我现在的新密码是：
export default class TurnByTurnComponent extends React.PureComponent {
constructor(props) {
super(props);
this.state = { shortestPath: [] }
}
render() {
const {
destinationLocationId,
locations,
originLocationId
} = this.props;
let path = []
if (destinationLocationId != null && originLocationId != null) {
console.log(JSON.stringify(locations))
path = [getNodeById(originLocationId).namne];
if (originLocationId != destinationLocationId) {
var openList = [];
let startNode = getNodeById(originLocationId);
let destinationNode = getNodeById(destinationLocationId)
if (startNode.connectedToIds.length > 0 && destinationNode.connectedToIds.length > 0) {
startNode.gcost = 0
startNode.heuristic = manhattanDistance(startNode, destinationNode)
startNode.fcost = startNode.gcost + startNode.heuristic;
openList.push(startNode); //starting with the startNode
while (openList.length > 0) {
var currentNode = getNodeOfMinFscore(openList); //get the node of the minimum f cost of all nodes in the openList
if (currentIsEqualDistanation(currentNode)) {
path = getPath(currentNode);
break;
}
deleteCurrentFromOpenList(currentNode, openList);
for (let neighbourId of currentNode.connectedToIds) {
var neighbourNode = getNodeById(neighbourId);
let gcost = currentNode.gcost + manhattanDistance(currentNode, neighbourNode);
if (gcost < (neighbourNode.gcost ?? Infinity)) {
neighbourNode.parentId = currentNode.id;
// keep track of the path
// total cost saved in neighbour.g
neighbourNode.gcost = gcost;
neighbourNode.heuristic = manhattanDistance(neighbourNode, destinationNode);
neighbourNode.fcost = neighbourNode.gcost + neighbourNode.heuristic; //calculate f cost of the neighbourNode
addNeighbourNodeToOpenList(neighbourNode, openList);
}
}
}
}
}
}
path = path.reverse().join("->");
function addNeighbourNodeToOpenList(neighbourNode, openList) {
//add neighbourNode to the open list to be discovered later
if (!openList.includes(neighbourNode)) {
openList.push(neighbourNode);
}
}
function deleteCurrentFromOpenList(currentNode, openList) {
const currIndex = openList.indexOf(currentNode);
openList.splice(currIndex, 1); //deleting currentNode from openList
}
function currentIsEqualDistanation(currentNode) {
//check if we reached out the distanation node
return (currentNode.id == destinationLocationId)
}
function getNodeById(id) {
var node;
for (let i = 0; i < locations.length; i++) {
if (locations[i].id == id) {
node = locations[i]
}
}
return node
}
function getPath(destinationNode) {
console.log("inside getpath")
var parentPath = []
var parent;
while (destinationNode.parentId != null) {
parentPath.push(destinationNode.name)
parent = destinationNode.parentId;
destinationNode = getNodeById(parent);
}
//adding startNode to the path
parentPath.push(getNodeById(originLocationId).name)
return parentPath;
}
function getNodeOfMinFscore(openList) {
var minFscore = openList[0].fcost; //initValue
var nodeOfminFscore;
for (let i = 0; i < openList.length; i++) {
if (openList[i].fcost <= minFscore) {
minFscore = openList[i].fcost //minFvalue
nodeOfminFscore = openList[i]
}
}
return nodeOfminFscore
}
//manhattan distance is for heuristic and gScore. Here I use Manhattan instead of Euclidean
//because in this example we dont have diagnosal path.
function manhattanDistance(startNode, destinationNode) {
var x = Math.abs(destinationNode.x - startNode.x);
var y = Math.abs(destinationNode.y - startNode.y);
var dist = x + y;
return dist;
}
return (
<div className="turn-by-turn-component">
<TodoList
title="Mandatory work"
list={[path]}
/>
<TodoList
title="Optional work"
list={[]}
/>
</div>
);
}
}
TurnByTurnComponent.propTypes = {
destinationLocationId: PropTypes.number,
locations: PropTypes.arrayOf(PropTypes.shape({
id: PropTypes.number.isRequired,
name: PropTypes.string.isRequired,
x: PropTypes.number.isRequired,
y: PropTypes.number.isRequired,
connectedToIds: PropTypes.arrayOf(PropTypes.number.isRequired).isRequired
})),
originLocationId: PropTypes.number
};
您的代码中存在一些问题：
return originLocationId; 不应该发生。当source等于target的时候，再设置路径，确保这个函数最后的return被执行，因为你要return div元素。
当在循环中找到目标时，不仅要构建path，还要退出循环。所以加一个break
currentNode.gcost = currentNode.gcost + manhattanDistance(currentNode, neighbourNode); 是不对的：你不想修改 currentNode.gcost：它的值不应该依赖于那个邻居的出边。而是将此总和存储在临时变量中（如 gcost）
当该节点还没有 gcost 成员时，与 neighbourNode.gcost 的比较将不起作用。我在你的代码中没有看到它有一个默认值来确保这个条件为真，所以你应该在这里使用一个默认值，比如 (neighbourNode.gcost ?? Infinity)
path = path.reverse().join("->"); 最好执行 always，当没有解决方案时（所以 path 是一个字符串）或当源和目标是同一个节点。
这是一个更正后的版本，稍微适应了 运行 这里作为 运行 可用的片段：
function render() {
const {
destinationLocationId,
locations,
originLocationId
} = this.props;
let path = [];
if (destinationLocationId != null && originLocationId != null) {
path = [originLocationId]; // The value for when the next if condition is not true
if (originLocationId != destinationLocationId) {
var openList = [];
let startNode = getNodeById(originLocationId);
let destinationNode = getNodeById(destinationLocationId)
if (startNode.connectedToIds.length > 0 && destinationNode.connectedToIds.length > 0) {
startNode.gcost = 0
startNode.heuristic = manhattanDistance(startNode, destinationNode)
startNode.fcost = startNode.gcost + startNode.heuristic;
openList.push(startNode);
while (openList.length > 0) {
var currentNode = getNodeOfMinFscore(openList);
if (currentIsEqualDistanation(currentNode)) {
path = getPath(currentNode);
break; // Should end the search here!
}
deleteCurrentFromOpenList(currentNode, openList);
for (let neighbourId of currentNode.connectedToIds) {
var neighbourNode = getNodeById(neighbourId);
// Should not modify the current node's gcost. Use a variable instead:
let gcost = currentNode.gcost + manhattanDistance(currentNode, neighbourNode);
// Condition should also work when neighbour has no gcost yet:
if (gcost < (neighbourNode.gcost ?? Infinity)) {
neighbourNode.parentId = currentNode.id;
neighbourNode.gcost = gcost; // Use the variable
neighbourNode.heuristic = manhattanDistance(neighbourNode, destinationNode);
neighbourNode.fcost = neighbourNode.gcost + neighbourNode.heuristic;
addNeighbourNodeToOpenList(neighbourNode, openList);
}
}
}
}
}
}
// Convert the path to string in ALL cases:
path = path.reverse().join("->");
function addNeighbourNodeToOpenList(neighbourNode, openList) {
if (!openList.includes(neighbourNode)) {
openList.push(neighbourNode);
}
}
function deleteCurrentFromOpenList(currNode, openList) {
const currIndex = openList.indexOf(currNode);
openList.splice(currIndex, 1);
}
function currentIsEqualDistanation(currNode) {
return (currNode.id == destinationLocationId)
}
function getNodeById(nid) {
var node;
for (let i = 0; i < locations.length; i++) {
if (locations[i].id == nid) {
node = locations[i]
}
}
return node
}
function getPath(destNode) {
var parentPath = []
var parentId;
while (destNode.parentId != null) {
parentPath.push(destNode.name)
parentId = destNode.parentId;
destNode = getNodeById(parentId);
}
parentPath.push(getNodeById(originLocationId).name)
return parentPath;
}
function getNodeOfMinFscore(openList) {
var minFscore = openList[0].fcost;
var nodeOfminFscore;
for (let i = 0; i < openList.length; i++) {
if (openList[i].fcost <= minFscore) {
minFscore = openList[i].fcost
nodeOfminFscore = openList[i]
}
}
return nodeOfminFscore
}
function manhattanDistance(stNode, dstNode) {
var x = Math.abs(dstNode.x - stNode.x);
var y = Math.abs(dstNode.y - stNode.y);
var dist = x + y;
return dist;
}
return "Shortest path: " + path;
}
// Demo
let props = {
locations: [
{ id: 1, x: 312, y: 152, connectedToIds: [4,2], name: "Thetaham" },
{ id: 2, x: 590, y: 388, connectedToIds: [1,3], name: "Deltabury" },
{ id: 3, x: 428, y: 737, connectedToIds: [2], name: "Gammation" },
{ id: 4, x: 222, y: 430, connectedToIds: [1], name: "Theta City" },
],
originLocationId: 1,
destinationLocationId: 3,
};
console.log(render.call({props}));
我正在 react.js 中实现 A*(A-star) 算法，但只要 startNode(green) 或 destinationNode(blue) 有多个邻居，或者如果有循环，我的程序就会崩溃图形。添加和删除邻居 from/to openList 或更新 getPath() 函数中的 parentId 时出现问题。我什至看不到控制台，因为网站出现故障。 每个节点都有：id,name,x,y,connectedToIdsList:[],gcost:Infinity,fcost:0,heuristic:0,parentId:null。 我正在将路径发送到打印出路径的另一个组件“TodoList”。我的程序不应该 return 路径，而是在我向列表添加节点和边时不断更新路径。请帮忙，我已经被困了几个小时了：/
我的代码：
export default class TurnByTurnComponent extends React.PureComponent {
constructor(props) {
super(props);
this.state = { shortestPath: [] }
}
render() {
const {
destinationLocationId,
locations,
originLocationId
} = this.props;
let path = []
if (destinationLocationId != null && originLocationId != null) {
if (originLocationId == destinationLocationId) { //check if the startNode node is the end node
return originLocationId;
}
var openList = [];
let startNode = getNodeById(originLocationId);
let destinationNode = getNodeById(destinationLocationId)
if (startNode.connectedToIds.length > 0 && destinationNode.connectedToIds.length > 0) { //check if start and destination nodes are connected first
startNode.gcost = 0
startNode.heuristic = manhattanDistance(startNode, destinationNode)
startNode.fcost = startNode.gcost + startNode.heuristic;
//perform A*
openList.push(startNode); //starting with the startNode
while (openList.length > 0) {
console.log("inside while")
var currentNode = getNodeOfMinFscore(openList); //get the node of the minimum f cost of all nodes in the openList
if (currentIsEqualDistanation(currentNode)) {
path = getPath(currentNode);
}
deleteCurrentFromOpenList(currentNode, openList);
for (let neighbourId of currentNode.connectedToIds) {
var neighbourNode = getNodeById(neighbourId);
currentNode.gcost = currentNode.gcost + manhattanDistance(currentNode, neighbourNode);
if (currentNode.gcost < neighbourNode.gcost) {
neighbourNode.parentId = currentNode.id; // keep track of the path
// total cost saved in neighbour.g
neighbourNode.gcost = currentNode.gcost;
neighbourNode.heuristic = manhattanDistance(neighbourNode, destinationNode);
neighbourNode.fcost = neighbourNode.gcost + neighbourNode.heuristic; //calculate f cost of the neighbourNode
addNeighbourNodeToOpenList(neighbourNode, openList);
}
}
}
path = path.reverse().join("->");
}
}
function addNeighbourNodeToOpenList(neighbourNode, openList) {
//add neighbourNode to the open list to be discovered later
if (!openList.includes(neighbourNode)) {
openList.push(neighbourNode);
}
}
function deleteCurrentFromOpenList(currNode, openList) {
const currIndex = openList.indexOf(currNode);
openList.splice(currIndex, 1); //deleting currentNode from openList
}
function currentIsEqualDistanation(currNode) {
//check if we reached out the distanation node
return (currNode.id == destinationLocationId)
}
function getNodeById(nid) {
var node;
for (let i = 0; i < locations.length; i++) {
if (locations[i].id == nid) {
node = locations[i]
}
}
return node
}
function getPath(destNode) {
console.log("inside getpath")
var parentPath = []
var parent;
while (destNode.parentId != null) {
parentPath.push(destNode.name)
parent = destNode.parentId;
destNode = getNodeById(parent);
}
//adding startNode to the path
parentPath.push(getNodeById(originLocationId).name)
return parentPath;
}
function getNodeOfMinFscore(openList) {
var minFscore = openList[0].fcost; //initValue
var nodeOfminFscore;
for (let i = 0; i < openList.length; i++) {
if (openList[i].fcost <= minFscore) {
minFscore = openList[i].fcost //minFvalue
nodeOfminFscore = openList[i]
}
}
return nodeOfminFscore
}
//manhattan distance is for heuristic and gScore. Here I use Manhattan instead of Euclidean
//because in this example we dont have diagnosal path.
function manhattanDistance(stNode, dstNode) {
var x = Math.abs(dstNode.x - stNode.x);
var y = Math.abs(dstNode.y - stNode.y);
var dist = x + y;
return dist;
}
return (
<div className="turn-by-turn-component">
<TodoList
list={"Shortest path: ", [path]}
/>
<TodoList
list={[]}
/>
</div>
);
}
}
TurnByTurnComponent.propTypes = {
destinationLocationId: PropTypes.number,
locations: PropTypes.arrayOf(PropTypes.shape({
id: PropTypes.number.isRequired,
name: PropTypes.string.isRequired,
x: PropTypes.number.isRequired,
y: PropTypes.number.isRequired,
connectedToIds: PropTypes.arrayOf(PropTypes.number.isRequired).isRequired
})),
originLocationId: PropTypes.number
};
更新新问题 链接新节点前后的图片。当我更新图形并添加新节点时，路径消失了。如果我仍然向图中添加新节点和边，有时会回来等等。正如我所说，每个节点都有：id、name、x、y、connectedToIdsList:[]、gcost:Infinity、fcost:0、heuristic:0、parentId:null。 我现在的新密码是：
export default class TurnByTurnComponent extends React.PureComponent {
constructor(props) {
super(props);
this.state = { shortestPath: [] }
}
render() {
const {
destinationLocationId,
locations,
originLocationId
} = this.props;
let path = []
if (destinationLocationId != null && originLocationId != null) {
console.log(JSON.stringify(locations))
path = [getNodeById(originLocationId).namne];
if (originLocationId != destinationLocationId) {
var openList = [];
let startNode = getNodeById(originLocationId);
let destinationNode = getNodeById(destinationLocationId)
if (startNode.connectedToIds.length > 0 && destinationNode.connectedToIds.length > 0) {
startNode.gcost = 0
startNode.heuristic = manhattanDistance(startNode, destinationNode)
startNode.fcost = startNode.gcost + startNode.heuristic;
openList.push(startNode); //starting with the startNode
while (openList.length > 0) {
var currentNode = getNodeOfMinFscore(openList); //get the node of the minimum f cost of all nodes in the openList
if (currentIsEqualDistanation(currentNode)) {
path = getPath(currentNode);
break;
}
deleteCurrentFromOpenList(currentNode, openList);
for (let neighbourId of currentNode.connectedToIds) {
var neighbourNode = getNodeById(neighbourId);
let gcost = currentNode.gcost + manhattanDistance(currentNode, neighbourNode);
if (gcost < (neighbourNode.gcost ?? Infinity)) {
neighbourNode.parentId = currentNode.id;
// keep track of the path
// total cost saved in neighbour.g
neighbourNode.gcost = gcost;
neighbourNode.heuristic = manhattanDistance(neighbourNode, destinationNode);
neighbourNode.fcost = neighbourNode.gcost + neighbourNode.heuristic; //calculate f cost of the neighbourNode
addNeighbourNodeToOpenList(neighbourNode, openList);
}
}
}
}
}
}
path = path.reverse().join("->");
function addNeighbourNodeToOpenList(neighbourNode, openList) {
//add neighbourNode to the open list to be discovered later
if (!openList.includes(neighbourNode)) {
openList.push(neighbourNode);
}
}
function deleteCurrentFromOpenList(currentNode, openList) {
const currIndex = openList.indexOf(currentNode);
openList.splice(currIndex, 1); //deleting currentNode from openList
}
function currentIsEqualDistanation(currentNode) {
//check if we reached out the distanation node
return (currentNode.id == destinationLocationId)
}
function getNodeById(id) {
var node;
for (let i = 0; i < locations.length; i++) {
if (locations[i].id == id) {
node = locations[i]
}
}
return node
}
function getPath(destinationNode) {
console.log("inside getpath")
var parentPath = []
var parent;
while (destinationNode.parentId != null) {
parentPath.push(destinationNode.name)
parent = destinationNode.parentId;
destinationNode = getNodeById(parent);
}
//adding startNode to the path
parentPath.push(getNodeById(originLocationId).name)
return parentPath;
}
function getNodeOfMinFscore(openList) {
var minFscore = openList[0].fcost; //initValue
var nodeOfminFscore;
for (let i = 0; i < openList.length; i++) {
if (openList[i].fcost <= minFscore) {
minFscore = openList[i].fcost //minFvalue
nodeOfminFscore = openList[i]
}
}
return nodeOfminFscore
}
//manhattan distance is for heuristic and gScore. Here I use Manhattan instead of Euclidean
//because in this example we dont have diagnosal path.
function manhattanDistance(startNode, destinationNode) {
var x = Math.abs(destinationNode.x - startNode.x);
var y = Math.abs(destinationNode.y - startNode.y);
var dist = x + y;
return dist;
}
return (
<div className="turn-by-turn-component">
<TodoList
title="Mandatory work"
list={[path]}
/>
<TodoList
title="Optional work"
list={[]}
/>
</div>
);
}
}
TurnByTurnComponent.propTypes = {
destinationLocationId: PropTypes.number,
locations: PropTypes.arrayOf(PropTypes.shape({
id: PropTypes.number.isRequired,
name: PropTypes.string.isRequired,
x: PropTypes.number.isRequired,
y: PropTypes.number.isRequired,
connectedToIds: PropTypes.arrayOf(PropTypes.number.isRequired).isRequired
})),
originLocationId: PropTypes.number
};
您的代码中存在一些问题：
return originLocationId;不应该发生。当source等于target的时候，再设置路径，确保这个函数最后的return被执行，因为你要returndiv元素。当在循环中找到目标时，不仅要构建
path，还要退出循环。所以加一个breakcurrentNode.gcost = currentNode.gcost + manhattanDistance(currentNode, neighbourNode);是不对的：你不想修改currentNode.gcost：它的值不应该依赖于那个邻居的出边。而是将此总和存储在临时变量中（如gcost）当该节点还没有
gcost成员时，与neighbourNode.gcost的比较将不起作用。我在你的代码中没有看到它有一个默认值来确保这个条件为真，所以你应该在这里使用一个默认值，比如(neighbourNode.gcost ?? Infinity)path = path.reverse().join("->");最好执行 always，当没有解决方案时（所以path是一个字符串）或当源和目标是同一个节点。
这是一个更正后的版本，稍微适应了 运行 这里作为 运行 可用的片段：
function render() {
const {
destinationLocationId,
locations,
originLocationId
} = this.props;
let path = [];
if (destinationLocationId != null && originLocationId != null) {
path = [originLocationId]; // The value for when the next if condition is not true
if (originLocationId != destinationLocationId) {
var openList = [];
let startNode = getNodeById(originLocationId);
let destinationNode = getNodeById(destinationLocationId)
if (startNode.connectedToIds.length > 0 && destinationNode.connectedToIds.length > 0) {
startNode.gcost = 0
startNode.heuristic = manhattanDistance(startNode, destinationNode)
startNode.fcost = startNode.gcost + startNode.heuristic;
openList.push(startNode);
while (openList.length > 0) {
var currentNode = getNodeOfMinFscore(openList);
if (currentIsEqualDistanation(currentNode)) {
path = getPath(currentNode);
break; // Should end the search here!
}
deleteCurrentFromOpenList(currentNode, openList);
for (let neighbourId of currentNode.connectedToIds) {
var neighbourNode = getNodeById(neighbourId);
// Should not modify the current node's gcost. Use a variable instead:
let gcost = currentNode.gcost + manhattanDistance(currentNode, neighbourNode);
// Condition should also work when neighbour has no gcost yet:
if (gcost < (neighbourNode.gcost ?? Infinity)) {
neighbourNode.parentId = currentNode.id;
neighbourNode.gcost = gcost; // Use the variable
neighbourNode.heuristic = manhattanDistance(neighbourNode, destinationNode);
neighbourNode.fcost = neighbourNode.gcost + neighbourNode.heuristic;
addNeighbourNodeToOpenList(neighbourNode, openList);
}
}
}
}
}
}
// Convert the path to string in ALL cases:
path = path.reverse().join("->");
function addNeighbourNodeToOpenList(neighbourNode, openList) {
if (!openList.includes(neighbourNode)) {
openList.push(neighbourNode);
}
}
function deleteCurrentFromOpenList(currNode, openList) {
const currIndex = openList.indexOf(currNode);
openList.splice(currIndex, 1);
}
function currentIsEqualDistanation(currNode) {
return (currNode.id == destinationLocationId)
}
function getNodeById(nid) {
var node;
for (let i = 0; i < locations.length; i++) {
if (locations[i].id == nid) {
node = locations[i]
}
}
return node
}
function getPath(destNode) {
var parentPath = []
var parentId;
while (destNode.parentId != null) {
parentPath.push(destNode.name)
parentId = destNode.parentId;
destNode = getNodeById(parentId);
}
parentPath.push(getNodeById(originLocationId).name)
return parentPath;
}
function getNodeOfMinFscore(openList) {
var minFscore = openList[0].fcost;
var nodeOfminFscore;
for (let i = 0; i < openList.length; i++) {
if (openList[i].fcost <= minFscore) {
minFscore = openList[i].fcost
nodeOfminFscore = openList[i]
}
}
return nodeOfminFscore
}
function manhattanDistance(stNode, dstNode) {
var x = Math.abs(dstNode.x - stNode.x);
var y = Math.abs(dstNode.y - stNode.y);
var dist = x + y;
return dist;
}
return "Shortest path: " + path;
}
// Demo
let props = {
locations: [
{ id: 1, x: 312, y: 152, connectedToIds: [4,2], name: "Thetaham" },
{ id: 2, x: 590, y: 388, connectedToIds: [1,3], name: "Deltabury" },
{ id: 3, x: 428, y: 737, connectedToIds: [2], name: "Gammation" },
{ id: 4, x: 222, y: 430, connectedToIds: [1], name: "Theta City" },
],
originLocationId: 1,
destinationLocationId: 3,
};
console.log(render.call({props}));