isleward/src/server/misc/pathfinder.js

/* eslint-disable */

// 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 {
		var exports = definition();
		window.astar = exports.astar;
		window.Graph = exports.Graph;
	}
})(function() {

	function pathTo(node) {
		var curr = node;
		var 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 || {};
			var heuristic = options.heuristic || astar.heuristics.manhattan;
			var closest = options.closest || false;
			var distance = options.distance;

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

			var openHeap = getHeap();
			var 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.
				var currentNode = openHeap.pop();

				var 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.
				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, 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) {
				var d1 = Math.abs(pos1.x - pos0.x);
				var d2 = Math.abs(pos1.y - pos0.y);
				return Math.max(d1, d2);
			},
			manhattanDistance: function(pos0, pos1, distance) {
				var d1 = Math.abs(pos1.x - pos0.x);
				var d2 = Math.abs(pos1.y - pos0.y);
				return Math.abs(distance - Math.max(d1, d2)) + 1;
			},
			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) {
			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 (var x = 0; x < gridIn.length; x++) {
			this.grid[x] = [];

			for (var 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 (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("\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.
			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;
				}
			}
		}
	};

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

});