/// <summary> /// Construct a new nearest neighbour iterator. /// </summary> /// <param name="pRoot">The root of the tree to begin searching from.</param> /// <param name="tSearchPoint">The point in n-dimensional space to search.</param> /// <param name="kDistance">The distance function used to evaluate the points.</param> /// <param name="iMaxPoints">The max number of points which can be returned by this iterator. Capped to max in tree.</param> /// <param name="fThreshold">Threshold to apply to the search space. Negative numbers indicate that no threshold is applied.</param> public NearestNeighbour(KDNode pRoot, Vector3d tSearchPoint, DistanceFunctions kDistance, int iMaxPoints, double fThreshold) { // Store the search point. this.tSearchPoint = new Vector3d(tSearchPoint); // Store the point count, distance function and tree root. this.iPointsRemaining = Math.Min(iMaxPoints, pRoot.Size); this.fThreshold = fThreshold; this.kDistanceFunction = kDistance; this.pRoot = pRoot; this.iMaxPointsReturned = iMaxPoints; _CurrentDistance = -1; // Create an interval heap for the points we check. this.pEvaluated = new IntervalHeap(); // Create a min heap for the things we need to check. this.pPending = new MinHeap(); this.pPending.Insert(0, pRoot); }
/// <summary> /// Reset the iterator. /// </summary> public void Reset() { // Store the point count and the distance function. this.iPointsRemaining = Math.Min(iMaxPointsReturned, pRoot.Size); _CurrentDistance = -1; // Create an interval heap for the points we check. this.pEvaluated = new IntervalHeap(); // Create a min heap for the things we need to check. this.pPending = new MinHeap(); this.pPending.Insert(0, pRoot); }