isleward/src/client/js/misc/pathfinder.js

// javascript-astar 0.4.1
// http://github.com/bgrins/javascript-astar
// Freely distributable under the MIT License.
// Implements the astar search algorithm in javascript using a Binary Heap.
// Includes Binary Heap (with modifications) from Marijn Haverbeke.
// http://eloquentjavascript.net/appendix2.html
(function (definition) {
	/* global module, define */
	if (typeof module === 'object' && typeof module.exports === 'object') 
		module.exports = definition();
	 else if (typeof define === 'function' && define.amd) 
		define([], definition);
	 else {
		let exports = definition();
		window.astar = exports.astar;
		window.Graph = exports.Graph;
	}
})(function () {
	function pathTo (node) {
		let curr = node;
		let path = [];
		while (curr.parent) {
			path.unshift(curr);
			curr = curr.parent;
		}
		return path;
	}

	function getHeap () {
		return new BinaryHeap(function (node) {
			return node.f;
		});
	}

	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) {
			start = graph.grid[start.x][start.y] || start;
			end = graph.grid[end.x][end.y] || end;

			graph.cleanDirty();
			options = options || {};
			let heuristic = options.heuristic || astar.heuristics.manhattan;
			let closest = options.closest || false;
			let distance = options.distance;

			if (distance)
				heuristic = astar.heuristics.manhattanDistance;

			let openHeap = getHeap();
			let closestNode = start; // set the start node to be the closest if required

			start.h = heuristic(start, end, distance);
			graph.markDirty(start);

			openHeap.push(start);

			while (openHeap.size() > 0) {
				// Grab the lowest f(x) to process next.  Heap keeps this sorted for us.
				let currentNode = openHeap.pop();

				let onWall = !currentNode.isWall || currentNode.isWall();

				if (!onWall) {
					if (distance) {
						if (currentNode.h == distance)
							return pathTo(currentNode);
					} else {
						// 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.
				let neighbors = graph.neighbors(currentNode);

				for (let i = 0, il = neighbors.length; i < il; ++i) {
					let 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.
					let gScore = currentNode.g + neighbor.getCost(currentNode);
					let 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, distance);
						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) {
				let d1 = Math.abs(pos1.x - pos0.x);
				let d2 = Math.abs(pos1.y - pos0.y);
				return Math.max(d1, d2);
			},
			manhattanDistance: function (pos0, pos1, distance) {
				let d1 = Math.abs(pos1.x - pos0.x);
				let d2 = Math.abs(pos1.y - pos0.y);
				return Math.abs(distance - Math.max(d1, d2)) + 1;
			},
			diagonal: function (pos0, pos1) {
				let D = 1;
				let D2 = Math.sqrt(2);
				let d1 = Math.abs(pos1.x - pos0.x);
				let d2 = Math.abs(pos1.y - pos0.y);
				return (D * (d1 + d2)) + ((D2 - (2 * D)) * Math.min(d1, d2));
			}
		},
		cleanNode: function (node) {
			if (!node)
				return;
			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
	 */
	function Graph (gridIn, options) {
		options = options || {};
		this.nodes = [];
		this.diagonal = !!options.diagonal;
		this.grid = [];

		for (let x = 0; x < gridIn.length; x++) {
			this.grid[x] = [];

			for (let y = 0, row = gridIn[x]; y < row.length; y++) {
				if (!row[y]) {
					node = new GridNode(x, y, row[y] ? 0 : 1);
					this.grid[x][y] = node;
					this.nodes.push(node);
				}
			}
		}
		this.init();
	}

	Graph.prototype.init = function () {
		this.dirtyNodes = [];
		for (let i = 0; i < this.nodes.length; i++) 
			astar.cleanNode(this.nodes[i]);
	};

	Graph.prototype.cleanDirty = function () {
		for (let 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) {
		let ret = [];
		let x = node.x;
		let y = node.y;
		let 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 () {
		let graphString = [];
		let nodes = this.grid;
		for (let x = 0; x < nodes.length; x++) {
			let rowDebug = [];
			let row = nodes[x];
			for (let y = 0; y < row.length; y++) 
				rowDebug.push(row[y].weight);
			
			graphString.push(rowDebug.join(' '));
		}
		return graphString.join('\n');
	};

	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.
			let result = this.content[0];
			// Get the element at the end of the array.
			let 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) {
			let i = this.content.indexOf(node);

			// When it is found, the process seen in 'pop' is repeated
			// to fill up the hole.
			let 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.
			let 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.
				let parentN = ((n + 1) >> 1) - 1;
				let 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.
			let length = this.content.length;
			let element = this.content[n];
			let elemScore = this.scoreFunction(element);

			while (true) {
				// Compute the indices of the child elements.
				let child2N = (n + 1) << 1;
				let child1N = child2N - 1;
				// This is used to store the new position of the element, if any.
				let swap = null;
				var child1Score;
				// If the first child exists (is inside the array)...
				if (child1N < length) {
					// Look it up and compute its score.
					let 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) {
					let child2 = this.content[child2N];
					let 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;
			}
		}
	};

	return {
		astar: astar,
		Graph: Graph,
		gridNode: GridNode
	};
});