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using Unity.Mathematics;
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using Unity.Burst;
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using Pathfinding.Util;
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using Pathfinding.Graphs.Util;
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using Pathfinding.Collections;
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namespace Pathfinding {
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/// <summary>
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/// Calculates an estimated cost from the specified point to the target.
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///
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/// See: https://en.wikipedia.org/wiki/A*_search_algorithm
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/// </summary>
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[BurstCompile]
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public readonly struct HeuristicObjective {
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readonly int3 mn;
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readonly int3 mx;
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readonly Heuristic heuristic;
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readonly float heuristicScale;
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readonly UnsafeSpan<uint> euclideanEmbeddingCosts;
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readonly uint euclideanEmbeddingPivots;
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readonly uint targetNodeIndex;
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public HeuristicObjective (int3 point, Heuristic heuristic, float heuristicScale) {
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this.mn = this.mx = point;
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this.heuristic = heuristic;
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this.heuristicScale = heuristicScale;
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this.euclideanEmbeddingCosts = default;
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this.euclideanEmbeddingPivots = 0;
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this.targetNodeIndex = 0;
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}
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public HeuristicObjective (int3 point, Heuristic heuristic, float heuristicScale, uint targetNodeIndex, EuclideanEmbedding euclideanEmbedding) {
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this.mn = this.mx = point;
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this.heuristic = heuristic;
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this.heuristicScale = heuristicScale;
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// The euclidean embedding costs are guaranteed to be valid for the duration of the pathfinding request.
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// We cannot perform checks here, because we may be running in another thread, and Unity does not like that.
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this.euclideanEmbeddingCosts = euclideanEmbedding != null? euclideanEmbedding.costs.AsUnsafeSpanNoChecks() : default;
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this.euclideanEmbeddingPivots = euclideanEmbedding != null ? (uint)euclideanEmbedding.pivotCount : 0;
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this.targetNodeIndex = targetNodeIndex;
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}
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public HeuristicObjective (int3 mn, int3 mx, Heuristic heuristic, float heuristicScale, uint targetNodeIndex, EuclideanEmbedding euclideanEmbedding) {
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this.mn = mn;
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this.mx = mx;
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this.heuristic = heuristic;
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this.heuristicScale = heuristicScale;
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// The euclidean embedding costs are guaranteed to be valid for the duration of the pathfinding request.
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// We cannot perform checks here, because we may be running in another thread, and Unity does not like that.
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this.euclideanEmbeddingCosts = euclideanEmbedding != null? euclideanEmbedding.costs.AsUnsafeSpanNoChecks() : default;
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this.euclideanEmbeddingPivots = euclideanEmbedding != null ? (uint)euclideanEmbedding.pivotCount : 0;
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this.targetNodeIndex = targetNodeIndex;
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}
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public int Calculate (int3 point, uint nodeIndex) {
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return Calculate(in this, ref point, nodeIndex);
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}
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[BurstCompile]
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public static int Calculate (in HeuristicObjective objective, ref int3 point, uint nodeIndex) {
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var closest = math.clamp(point, objective.mn, objective.mx);
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var diff = point - closest;
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int h;
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switch (objective.heuristic) {
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case Heuristic.Euclidean:
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h = (int)(math.length((float3)diff) * objective.heuristicScale);
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break;
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case Heuristic.Manhattan:
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h = (int)(math.csum(math.abs(diff)) * objective.heuristicScale);
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break;
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case Heuristic.DiagonalManhattan:
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// Octile distance extended to 3D
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diff = math.abs(diff);
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var a = diff.x;
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var b = diff.y;
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var c = diff.z;
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// Sort the values so that a <= b <= c
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if (a > b) Memory.Swap(ref a, ref b);
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if (b > c) Memory.Swap(ref b, ref c);
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if (a > b) Memory.Swap(ref a, ref b);
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// This is the same as the Manhattan distance, but with a different weight for the diagonal moves.
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const float SQRT_3 = 1.7321f;
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const float SQRT_2 = 1.4142f;
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h = (int)(objective.heuristicScale * (SQRT_3 * a + SQRT_2 * (b-a) + (c-b-a)));
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break;
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case Heuristic.None:
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default:
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h = 0;
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break;
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}
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if (objective.euclideanEmbeddingPivots > 0) {
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h = math.max(h, (int)EuclideanEmbedding.GetHeuristic(objective.euclideanEmbeddingCosts, objective.euclideanEmbeddingPivots, nodeIndex, objective.targetNodeIndex));
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}
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return h;
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}
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}
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}
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