277 lines
8.7 KiB
C++
277 lines
8.7 KiB
C++
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#ifndef STAR_A_STAR_HPP
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#define STAR_A_STAR_HPP
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#include <queue>
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#include "StarList.hpp"
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#include "StarMap.hpp"
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#include "StarSet.hpp"
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#include "StarLexicalCast.hpp"
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#include "StarMathCommon.hpp"
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#include "StarBlockAllocator.hpp"
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namespace Star {
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namespace AStar {
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struct Score {
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Score();
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double gScore;
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double hScore;
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double fScore;
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};
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// 'Edge' should be implemented as a class with public fields compatible with
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// these:
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// double cost;
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// Node source;
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// Node target;
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template <class Edge>
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using Path = List<Edge>;
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template <class Edge, class Node>
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class Search {
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public:
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typedef function<double(Node, Node)> HeuristicFunction;
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typedef function<void(Node, List<Edge>& neighbors)> NeighborFunction;
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typedef function<bool(Node)> GoalFunction;
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typedef function<bool(Node, Node)> CompareFunction;
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typedef function<bool(Edge)> ValidateEndFunction;
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Search(HeuristicFunction heuristicCost,
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NeighborFunction getAdjacent,
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GoalFunction goalReached,
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bool returnBestIfFailed = false,
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// In returnBestIfFailed mode, validateEnd checks the end of the path
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// is valid, e.g. not floating in the air.
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Maybe<ValidateEndFunction> validateEnd = {},
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Maybe<double> maxFScore = {},
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Maybe<unsigned> maxNodesToSearch = {});
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// Start a new exploration, resets result if it was found before.
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void start(Node startNode, Node goalNode);
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// Explore the given number of nodes in the search space. If
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// maxNodesToSearch is reached, or the search space is exhausted, will
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// return
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// false to signal failure. On success, will return true. If the given
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// maxExploreNodes is exhausted before success or failure, will return
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// nothing.
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Maybe<bool> explore(Maybe<unsigned> maxExploreNodes = {});
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// Returns the result if it was found.
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Maybe<Path<Edge>> const& result() const;
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// Convenience, equivalent to calling start, then explore({}) and returns
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// result()
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Maybe<Path<Edge>> const& findPath(Node startNode, Node goalNode);
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private:
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struct ScoredNode {
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bool operator<(ScoredNode const& other) const {
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return score.fScore > other.score.fScore;
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}
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Score score;
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Node node;
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};
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struct NodeMeta {
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Score score;
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Maybe<Edge> cameFrom;
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};
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Path<Edge> reconstructPath(Node currentNode);
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HeuristicFunction m_heuristicCost;
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NeighborFunction m_getAdjacent;
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GoalFunction m_goalReached;
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bool m_returnBestIfFailed;
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Maybe<ValidateEndFunction> m_validateEnd;
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Maybe<double> m_maxFScore;
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Maybe<unsigned> m_maxNodesToSearch;
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Node m_goal;
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Map<Node, NodeMeta, std::less<Node>, BlockAllocator<pair<Node const, NodeMeta>, 1024>> m_nodeMeta;
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std::priority_queue<ScoredNode> m_openQueue;
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Set<Node, std::less<Node>, BlockAllocator<Node, 1024>> m_openSet;
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Set<Node, std::less<Node>, BlockAllocator<Node, 1024>> m_closedSet;
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Maybe<ScoredNode> m_earlyExploration;
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bool m_finished;
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Maybe<Path<Edge>> m_result;
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};
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inline Score::Score() : gScore(highest<double>()), hScore(0), fScore(highest<double>()) {}
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template <class Edge, class Node>
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Search<Edge, Node>::Search(HeuristicFunction heuristicCost,
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NeighborFunction getAdjacent,
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GoalFunction goalReached,
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bool returnBestIfFailed,
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Maybe<ValidateEndFunction> validateEnd,
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Maybe<double> maxFScore,
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Maybe<unsigned> maxNodesToSearch)
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: m_heuristicCost(heuristicCost),
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m_getAdjacent(getAdjacent),
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m_goalReached(goalReached),
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m_returnBestIfFailed(returnBestIfFailed),
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m_validateEnd(validateEnd),
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m_maxFScore(maxFScore),
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m_maxNodesToSearch(maxNodesToSearch) {}
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template <class Edge, class Node>
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void Search<Edge, Node>::start(Node startNode, Node goalNode) {
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m_goal = move(goalNode);
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m_nodeMeta.clear();
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m_openQueue = std::priority_queue<ScoredNode>();
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m_openSet.clear();
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m_closedSet.clear();
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m_earlyExploration = {};
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m_finished = false;
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m_result.reset();
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Score startScore;
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startScore.gScore = 0;
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startScore.hScore = m_heuristicCost(startNode, m_goal);
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startScore.fScore = startScore.hScore;
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m_nodeMeta[startNode].score = startScore;
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m_openSet.insert(startNode);
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m_openQueue.push(ScoredNode{startScore, move(startNode)});
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}
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template <class Edge, class Node>
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Maybe<bool> Search<Edge, Node>::explore(Maybe<unsigned> maxExploreNodes) {
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if (m_finished)
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return m_result.isValid();
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List<Edge> neighbors;
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while (true) {
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if ((m_maxNodesToSearch && m_closedSet.size() > *m_maxNodesToSearch)
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|| (m_openQueue.empty() && !m_earlyExploration)) {
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m_finished = true;
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// Search failed. Either return the path to the closest node to the
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// target,
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// or return nothing.
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if (m_returnBestIfFailed) {
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double bestScore = highest<double>();
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Maybe<Node> bestNode;
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for (Node node : m_closedSet) {
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NodeMeta const& nodeMeta = m_nodeMeta[node];
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if (m_validateEnd && nodeMeta.cameFrom && !(*m_validateEnd)(*nodeMeta.cameFrom))
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continue;
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if (nodeMeta.score.hScore < bestScore) {
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bestScore = nodeMeta.score.hScore;
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bestNode = node;
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}
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}
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if (bestNode)
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m_result = reconstructPath(*bestNode);
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}
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return false;
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}
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if (maxExploreNodes) {
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if (*maxExploreNodes == 0)
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return {};
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--*maxExploreNodes;
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}
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ScoredNode currentScoredNode;
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if (m_earlyExploration) {
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currentScoredNode = m_earlyExploration.take();
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} else {
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currentScoredNode = m_openQueue.top();
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m_openQueue.pop();
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if (!m_openSet.remove(currentScoredNode.node))
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// Duplicate entry in the queue due to this node's score being
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// updated.
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// Just ignore this node; we've already searched it.
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continue;
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}
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Node const& current = currentScoredNode.node;
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Score const& currentScore = currentScoredNode.score;
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if (m_goalReached(current)) {
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m_finished = true;
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m_result = reconstructPath(current);
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return true;
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}
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m_closedSet.insert(current);
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neighbors.clear();
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m_getAdjacent(current, neighbors);
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for (Edge const& edge : neighbors) {
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if (m_closedSet.find(edge.target) != m_closedSet.end())
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// We've already visited this node.
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continue;
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double newGScore = currentScore.gScore + edge.cost;
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NodeMeta& targetMeta = m_nodeMeta[edge.target];
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Score& targetScore = targetMeta.score;
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if (m_openSet.find(edge.target) == m_openSet.end() || newGScore < targetScore.gScore) {
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targetMeta.cameFrom = edge;
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targetScore.gScore = newGScore;
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targetScore.hScore = m_heuristicCost(edge.target, m_goal);
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targetScore.fScore = targetScore.gScore + targetScore.hScore;
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if (m_maxFScore && targetScore.fScore > *m_maxFScore)
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continue;
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// Early exploration optimization - no need to add things to the
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// openQueue/openSet
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// if they're at least as good as the current node.
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if (targetScore.fScore <= currentScore.fScore) {
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if (m_earlyExploration.isNothing()) {
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m_earlyExploration = ScoredNode{targetScore, edge.target};
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continue;
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} else if (m_earlyExploration->score.fScore > targetScore.fScore) {
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m_openSet.insert(m_earlyExploration->node);
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m_openQueue.push(*m_earlyExploration);
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m_earlyExploration = ScoredNode{targetScore, edge.target};
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continue;
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}
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}
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m_openSet.insert(edge.target);
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m_openQueue.push(ScoredNode{targetScore, edge.target});
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}
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}
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}
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}
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template <class Edge, class Node>
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Maybe<Path<Edge>> const& Search<Edge, Node>::result() const {
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return m_result;
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}
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template <class Edge, class Node>
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Maybe<Path<Edge>> const& Search<Edge, Node>::findPath(Node startNode, Node goalNode) {
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start(move(startNode), move(goalNode));
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explore();
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return result();
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}
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template <class Edge, class Node>
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Path<Edge> Search<Edge, Node>::reconstructPath(Node currentNode) {
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Path<Edge> res; // this will be backwards, we reverse it before returning it.
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while (m_nodeMeta.find(currentNode) != m_nodeMeta.end()) {
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Maybe<Edge> currentEdge = m_nodeMeta[currentNode].cameFrom;
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if (currentEdge.isNothing())
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break;
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res.append(*currentEdge);
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currentNode = currentEdge->source;
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}
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std::reverse(res.begin(), res.end());
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return res;
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}
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}
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}
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#endif
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