By providing a comparer that could change over time (as estimated costs on the graph were updated), this meant the priority queue could have its heap property invalidated and thus not maintain a correct ordering. Instead we store elements into the queue with their estimations at the time. This preserves the heap property and thus ensures the queue returns properly ordered results, although it may contain out of date estimations. This also improves performance. The fixed comparer need not perform expensive lookups into the graph, but can instead use the readily available value. This speeds up adds and removes on the queue significantly.
152 lines
4.5 KiB
C#
152 lines
4.5 KiB
C#
#region Copyright & License Information
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/*
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* Copyright 2007-2015 The OpenRA Developers (see AUTHORS)
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* This file is part of OpenRA, which is free software. It is made
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* available to you under the terms of the GNU General Public License
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* as published by the Free Software Foundation. For more information,
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* see COPYING.
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*/
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#endregion
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using System;
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using System.Collections.Generic;
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using System.Linq;
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using OpenRA.Mods.Common.Traits;
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using OpenRA.Primitives;
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namespace OpenRA.Mods.Common.Pathfinder
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{
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public sealed class PathSearch : BasePathSearch
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{
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public override IEnumerable<Pair<CPos, int>> Considered
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{
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get { return considered; }
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}
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LinkedList<Pair<CPos, int>> considered;
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#region Constructors
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private PathSearch(IGraph<CellInfo> graph)
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: base(graph)
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{
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considered = new LinkedList<Pair<CPos, int>>();
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}
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public static IPathSearch Search(World world, MobileInfo mi, Actor self, bool checkForBlocked, Func<CPos, bool> goalCondition)
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{
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var graph = new PathGraph(CellInfoLayerManager.Instance.NewLayer(world.Map), mi, self, world, checkForBlocked);
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var search = new PathSearch(graph);
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search.isGoal = goalCondition;
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search.heuristic = loc => 0;
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return search;
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}
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public static IPathSearch FromPoint(World world, MobileInfo mi, Actor self, CPos from, CPos target, bool checkForBlocked)
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{
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var graph = new PathGraph(CellInfoLayerManager.Instance.NewLayer(world.Map), mi, self, world, checkForBlocked);
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var search = new PathSearch(graph)
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{
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heuristic = DefaultEstimator(target)
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};
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search.isGoal = loc =>
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{
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var locInfo = search.Graph[loc];
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return locInfo.EstimatedTotal - locInfo.CostSoFar == 0;
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};
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if (world.Map.Contains(from))
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search.AddInitialCell(from);
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return search;
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}
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public static IPathSearch FromPoints(World world, MobileInfo mi, Actor self, IEnumerable<CPos> froms, CPos target, bool checkForBlocked)
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{
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var graph = new PathGraph(CellInfoLayerManager.Instance.NewLayer(world.Map), mi, self, world, checkForBlocked);
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var search = new PathSearch(graph)
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{
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heuristic = DefaultEstimator(target)
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};
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search.isGoal = loc =>
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{
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var locInfo = search.Graph[loc];
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return locInfo.EstimatedTotal - locInfo.CostSoFar == 0;
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};
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foreach (var sl in froms.Where(sl => world.Map.Contains(sl)))
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search.AddInitialCell(sl);
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return search;
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}
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protected override void AddInitialCell(CPos location)
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{
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var cost = heuristic(location);
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Graph[location] = new CellInfo(0, cost, location, CellStatus.Open);
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var connection = new GraphConnection(location, cost);
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OpenQueue.Add(connection);
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StartPoints.Add(connection);
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considered.AddLast(new Pair<CPos, int>(location, 0));
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}
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#endregion
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/// <summary>
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/// This function analyzes the neighbors of the most promising node in the Pathfinding graph
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/// using the A* algorithm (A-star) and returns that node
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/// </summary>
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/// <returns>The most promising node of the iteration</returns>
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public override CPos Expand()
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{
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var currentMinNode = OpenQueue.Pop().Destination;
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var currentCell = Graph[currentMinNode];
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Graph[currentMinNode] = new CellInfo(currentCell.CostSoFar, currentCell.EstimatedTotal, currentCell.PreviousPos, CellStatus.Closed);
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if (Graph.CustomCost != null && Graph.CustomCost(currentMinNode) == Constants.InvalidNode)
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return currentMinNode;
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foreach (var connection in Graph.GetConnections(currentMinNode))
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{
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// Calculate the cost up to that point
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var gCost = currentCell.CostSoFar + connection.Cost;
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var neighborCPos = connection.Destination;
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var neighborCell = Graph[neighborCPos];
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// Cost is even higher; next direction:
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if (neighborCell.Status == CellStatus.Closed || gCost >= neighborCell.CostSoFar)
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continue;
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// Now we may seriously consider this direction using heuristics. If the cell has
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// already been processed, we can reuse the result (just the difference between the
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// estimated total and the cost so far
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int hCost;
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if (neighborCell.Status == CellStatus.Open)
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hCost = neighborCell.EstimatedTotal - neighborCell.CostSoFar;
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else
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hCost = heuristic(neighborCPos);
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var estimatedCost = gCost + hCost;
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Graph[neighborCPos] = new CellInfo(gCost, estimatedCost, currentMinNode, CellStatus.Open);
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if (neighborCell.Status != CellStatus.Open)
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OpenQueue.Add(new GraphConnection(neighborCPos, estimatedCost));
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if (Debug)
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{
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if (gCost > MaxCost)
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MaxCost = gCost;
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considered.AddLast(new Pair<CPos, int>(neighborCPos, gCost));
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}
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}
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return currentMinNode;
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}
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}
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}
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