• A星算法


    A星算法,egret中使用例子

    var list = [
                  [1,1,1,1,0,1,0,0,0,1,0,0,1,1,0],
                  [0,1,1,0,1,1,0,1,0,1,1,1,1,0,0],
                  [0,0,1,1,1,0,0,1,1,1,1,0,1,0,1],
                  [0,0,0,1,1,0,0,1,1,0,1,0,1,1,1],
                  [0,0,0,1,0,0,1,1,1,0,1,0,1,1,1],
                  [0,0,1,1,1,1,1,1,0,0,0,0,1,0,1],
                  [0,0,1,1,1,0,0,1,0,1,1,0,1,0,1],
                ];
    var graph = new AStar.Graph(list,{});
    var start = graph.grid[0][0];
    var end = graph.grid[3][14];
    var result = AStar.astar.search(graph, start, end,{closest:true, heuristic:AStar.astar.heuristics.diagonal});

    源代码

    module AStar {
        export class AStar {
            public constructor() {
            }
        }
    
        export function pathTo(node) {
            var curr = node;
            var path = [];
            while (curr.parent) {
                path.unshift(curr);
                curr = curr.parent;
            }
            return path;
        }
    
        export function getHeap() {
            return new BinaryHeap(function(node) {
                return node.f;
            });
        }
    
        export var astar = {
            /**
             * Perform an A* Search on a graph given a start and end node.
            * @param {Graph} graph
            * @param {GridNode} start
            * @param {GridNode} end
            * @param {Object} [options]
            * @param {bool} [options.closest] Specifies whether to return the
                        path to the closest node if the target is unreachable.
            * @param {Function} [options.heuristic] Heuristic function (see
            *          astar.heuristics).
            */
            search: function(graph, start, end, options) {
                graph.cleanDirty();
                options = options || {};
                var heuristic = options.heuristic || astar.heuristics.manhattan;
                var closest = options.closest || false;
    
                var openHeap = getHeap();
                var closestNode = start; // set the start node to be the closest if required
    
                start.h = heuristic(start, end);
                graph.markDirty(start);
    
                openHeap.push(start);
    
                while (openHeap.size() > 0) {
    
                // Grab the lowest f(x) to process next.  Heap keeps this sorted for us.
                var currentNode = openHeap.pop();
    
                // End case -- result has been found, return the traced path.
                if (currentNode === end) {
                    return pathTo(currentNode);
                }
    
                // Normal case -- move currentNode from open to closed, process each of its neighbors.
                currentNode.closed = true;
    
                // Find all neighbors for the current node.
                var neighbors = graph.neighbors(currentNode);
    
                for (var i = 0, il = neighbors.length; i < il; ++i) {
                    var neighbor = neighbors[i];
    
                    if (neighbor.closed || neighbor.isWall()) {
                    // Not a valid node to process, skip to next neighbor.
                    continue;
                    }
    
                    // The g score is the shortest distance from start to current node.
                    // We need to check if the path we have arrived at this neighbor is the shortest one we have seen yet.
                    var gScore = currentNode.g + neighbor.getCost(currentNode);
                    var beenVisited = neighbor.visited;
    
                    if (!beenVisited || gScore < neighbor.g) {
    
                    // Found an optimal (so far) path to this node.  Take score for node to see how good it is.
                    neighbor.visited = true;
                    neighbor.parent = currentNode;
                    neighbor.h = neighbor.h || heuristic(neighbor, end);
                    neighbor.g = gScore;
                    neighbor.f = neighbor.g + neighbor.h;
                    graph.markDirty(neighbor);
                    if (closest) {
                        // If the neighbour is closer than the current closestNode or if it's equally close but has
                        // a cheaper path than the current closest node then it becomes the closest node
                        if (neighbor.h < closestNode.h || (neighbor.h === closestNode.h && neighbor.g < closestNode.g)) {
                        closestNode = neighbor;
                        }
                    }
    
                    if (!beenVisited) {
                        // Pushing to heap will put it in proper place based on the 'f' value.
                        openHeap.push(neighbor);
                    } else {
                        // Already seen the node, but since it has been rescored we need to reorder it in the heap
                        openHeap.rescoreElement(neighbor);
                    }
                    }
                }
                }
    
            if (closest) {
            return pathTo(closestNode);
            }
    
            // No result was found - empty array signifies failure to find path.
            return [];
        },
        // See list of heuristics: http://theory.stanford.edu/~amitp/GameProgramming/Heuristics.html
        heuristics: {
            manhattan: function(pos0, pos1) {
            var d1 = Math.abs(pos1.x - pos0.x);
            var d2 = Math.abs(pos1.y - pos0.y);
            return d1 + d2;
            },
            diagonal: function(pos0, pos1) {
            var D = 1;
            var D2 = Math.sqrt(2);
            var d1 = Math.abs(pos1.x - pos0.x);
            var d2 = Math.abs(pos1.y - pos0.y);
            return (D * (d1 + d2)) + ((D2 - (2 * D)) * Math.min(d1, d2));
            }
        },
        cleanNode: function(node) {
            node.f = 0;
            node.g = 0;
            node.h = 0;
            node.visited = false;
            node.closed = false;
            node.parent = null;
        }
        };
    
        /**
         * A graph memory structure
         * @param {Array} gridIn 2D array of input weights
         * @param {Object} [options]
         * @param {bool} [options.diagonal] Specifies whether diagonal moves are allowed
         */
        export function Graph(gridIn, options) {
            options = options || {};
            this.nodes = [];
            this.diagonal = !!options.diagonal;
            this.grid = [];
            for (var x = 0; x < gridIn.length; x++) {
                this.grid[x] = [];
    
                for (var y = 0, row = gridIn[x]; y < row.length; y++) {
                var node = new GridNode(x, y, row[y]);
                this.grid[x][y] = node;
                this.nodes.push(node);
                }
            }
            this.init();
        }
    
        Graph.prototype.init = function() {
        this.dirtyNodes = [];
        for (var i = 0; i < this.nodes.length; i++) {
            astar.cleanNode(this.nodes[i]);
        }
        };
    
        Graph.prototype.cleanDirty = function() {
        for (var i = 0; i < this.dirtyNodes.length; i++) {
            astar.cleanNode(this.dirtyNodes[i]);
        }
        this.dirtyNodes = [];
        };
    
        Graph.prototype.markDirty = function(node) {
        this.dirtyNodes.push(node);
        };
    
        Graph.prototype.neighbors = function(node) {
        var ret = [];
        var x = node.x;
        var y = node.y;
        var grid = this.grid;
    
        // West
        if (grid[x - 1] && grid[x - 1][y]) {
            ret.push(grid[x - 1][y]);
        }
    
        // East
        if (grid[x + 1] && grid[x + 1][y]) {
            ret.push(grid[x + 1][y]);
        }
    
        // South
        if (grid[x] && grid[x][y - 1]) {
            ret.push(grid[x][y - 1]);
        }
    
        // North
        if (grid[x] && grid[x][y + 1]) {
            ret.push(grid[x][y + 1]);
        }
    
        if (this.diagonal) {
            // Southwest
            if (grid[x - 1] && grid[x - 1][y - 1]) {
            ret.push(grid[x - 1][y - 1]);
            }
    
            // Southeast
            if (grid[x + 1] && grid[x + 1][y - 1]) {
            ret.push(grid[x + 1][y - 1]);
            }
    
            // Northwest
            if (grid[x - 1] && grid[x - 1][y + 1]) {
            ret.push(grid[x - 1][y + 1]);
            }
    
            // Northeast
            if (grid[x + 1] && grid[x + 1][y + 1]) {
            ret.push(grid[x + 1][y + 1]);
            }
        }
    
        return ret;
        };
    
        Graph.prototype.toString = function() {
        var graphString = [];
        var nodes = this.grid;
        for (var x = 0; x < nodes.length; x++) {
            var rowDebug = [];
            var row = nodes[x];
            for (var y = 0; y < row.length; y++) {
            rowDebug.push(row[y].weight);
            }
            graphString.push(rowDebug.join(" "));
        }
        return graphString.join("
    ");
        };
    
        function GridNode(x, y, weight) {
        this.x = x;
        this.y = y;
        this.weight = weight;
        }
    
        GridNode.prototype.toString = function() {
        return "[" + this.x + " " + this.y + "]";
        };
    
        GridNode.prototype.getCost = function(fromNeighbor) {
        // Take diagonal weight into consideration.
        if (fromNeighbor && fromNeighbor.x != this.x && fromNeighbor.y != this.y) {
            return this.weight * 1.41421;
        }
        return this.weight;
        };
    
        GridNode.prototype.isWall = function() {
        return this.weight === 0;
        };
    
        function BinaryHeap(scoreFunction) {
        this.content = [];
        this.scoreFunction = scoreFunction;
        }
    
        BinaryHeap.prototype = {
        push: function(element) {
            // Add the new element to the end of the array.
            this.content.push(element);
    
            // Allow it to sink down.
            this.sinkDown(this.content.length - 1);
        },
        pop: function() {
            // Store the first element so we can return it later.
            var result = this.content[0];
            // Get the element at the end of the array.
            var end = this.content.pop();
            // If there are any elements left, put the end element at the
            // start, and let it bubble up.
            if (this.content.length > 0) {
            this.content[0] = end;
            this.bubbleUp(0);
            }
            return result;
        },
        remove: function(node) {
            var i = this.content.indexOf(node);
    
            // When it is found, the process seen in 'pop' is repeated
            // to fill up the hole.
            var end = this.content.pop();
    
            if (i !== this.content.length - 1) {
            this.content[i] = end;
    
            if (this.scoreFunction(end) < this.scoreFunction(node)) {
                this.sinkDown(i);
            } else {
                this.bubbleUp(i);
            }
            }
        },
        size: function() {
            return this.content.length;
        },
        rescoreElement: function(node) {
            this.sinkDown(this.content.indexOf(node));
        },
        sinkDown: function(n) {
            // Fetch the element that has to be sunk.
            var element = this.content[n];
    
            // When at 0, an element can not sink any further.
            while (n > 0) {
    
            // Compute the parent element's index, and fetch it.
            var parentN = ((n + 1) >> 1) - 1;
            var parent = this.content[parentN];
            // Swap the elements if the parent is greater.
            if (this.scoreFunction(element) < this.scoreFunction(parent)) {
                this.content[parentN] = element;
                this.content[n] = parent;
                // Update 'n' to continue at the new position.
                n = parentN;
            }
            // Found a parent that is less, no need to sink any further.
            else {
                break;
            }
            }
        },
        bubbleUp: function(n) {
            // Look up the target element and its score.
            var length = this.content.length;
            var element = this.content[n];
            var elemScore = this.scoreFunction(element);
    
            while (true) {
            // Compute the indices of the child elements.
            var child2N = (n + 1) << 1;
            var child1N = child2N - 1;
            // This is used to store the new position of the element, if any.
            var swap = null;
            var child1Score;
            // If the first child exists (is inside the array)...
            if (child1N < length) {
                // Look it up and compute its score.
                var child1 = this.content[child1N];
                child1Score = this.scoreFunction(child1);
    
                // If the score is less than our element's, we need to swap.
                if (child1Score < elemScore) {
                swap = child1N;
                }
            }
    
            // Do the same checks for the other child.
            if (child2N < length) {
                var child2 = this.content[child2N];
                var child2Score = this.scoreFunction(child2);
                if (child2Score < (swap === null ? elemScore : child1Score)) {
                swap = child2N;
                }
            }
    
            // If the element needs to be moved, swap it, and continue.
            if (swap !== null) {
                this.content[n] = this.content[swap];
                this.content[swap] = element;
                n = swap;
            }
            // Otherwise, we are done.
            else {
                break;
            }
            }
        }
        };
    }
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  • 原文地址:https://www.cnblogs.com/maxwell-xu/p/7766680.html
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