예제 #1
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 public KDNode(int index, KDNode parent = null, KDNode left = null, KDNode right = null)
 {
     this.ElementIndex = index;
     this.Left         = left;
     this.Right        = right;
     this.Parent       = parent;
 }
예제 #2
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 public KDTreeNavigator(KDTree <TNode> tree, KDNode node)
 {
     this.tree = tree;
     this.node = node;
 }
예제 #3
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        /// <summary>
        /// A top-down recursive method to find the nearest neighbors of a given point.
        /// </summary>
        /// <param name="node">The index of the node for the current recursion branch.</param>
        /// <param name="target">The point whose neighbors we are trying to find.</param>
        /// <param name="rect">The <see cref="HyperRect{T}"/> containing the possible nearest neighbors.</param>
        /// <param name="dimension">The current splitting dimension for this recursion branch.</param>
        /// <param name="nearestNeighbors">The <see cref="BoundedPriorityList{TElement,TPriority}"/> containing the nearest neighbors already discovered.</param>
        /// <param name="maxSearchRadius">The radius of the current largest distance to search from the <paramref name="target"/></param>
        private void SearchForNearestNeighbors(
            KDNode node,
            double[] target,
            HyperRect <double> rect,
            int dimension,
            BoundablePriorityList <int, double> nearestNeighbors,
            double maxSearchRadius)
        {
            if (node == null)
            {
                return;
            }

            // Work out the current dimension
            var dim = dimension % this.Dimensions;

            // Get the coordinate of the current node.
            var coordinate = this.PointSelector(this.InternalList[node.ElementIndex]);

            // Split our hyper-rectangle into 2 sub rectangles along the current
            // node's point on the current dimension
            var leftRect = rect.Clone();

            leftRect.MaxPoint[dim] = coordinate[dim];

            var rightRect = rect.Clone();

            rightRect.MinPoint[dim] = coordinate[dim];

            // Determine which side the target resides in
            var comparison = target[dim] <= coordinate[dim];

            var nearerRect  = comparison ? leftRect : rightRect;
            var furtherRect = comparison ? rightRect : leftRect;

            var nearerNode  = comparison ? node.Left : node.Right;
            var furtherNode = comparison ? node.Right : node.Left;

            // Move down into the nearer branch
            this.SearchForNearestNeighbors(
                nearerNode,
                target,
                nearerRect,
                dimension + 1,
                nearestNeighbors,
                maxSearchRadius);

            // Walk down into the further branch but only if our capacity hasn't been reached
            // OR if there's a region in the further rectangle that's closer to the target than our
            // current furtherest nearest neighbor
            var closestPointInFurtherRect = furtherRect.GetClosestPoint(target);
            var distanceToTarget          = this.Metric(closestPointInFurtherRect, target);

            if (distanceToTarget.CompareTo(maxSearchRadius) <= 0)
            {
                if (nearestNeighbors.IsFull)
                {
                    if (distanceToTarget.CompareTo(nearestNeighbors.MaxPriority) < 0)
                    {
                        this.SearchForNearestNeighbors(
                            furtherNode,
                            target,
                            furtherRect,
                            dimension + 1,
                            nearestNeighbors,
                            maxSearchRadius);
                    }
                }
                else
                {
                    this.SearchForNearestNeighbors(
                        furtherNode,
                        target,
                        furtherRect,
                        dimension + 1,
                        nearestNeighbors,
                        maxSearchRadius);
                }
            }

            // Try to add the current node to our nearest neighbors list
            distanceToTarget = this.Metric(coordinate, target);
            if (distanceToTarget.CompareTo(maxSearchRadius) <= 0)
            {
                nearestNeighbors.Add(node.ElementIndex, distanceToTarget);
            }
        }
예제 #4
0
        /// <summary>
        /// Grows a KD tree recursively via median splitting. We find the median by doing a full sort.
        /// </summary>
        /// <param name="currentNode">The array index for the current node.</param>
        /// <param name="dim">The current splitting dimension.</param>
        /// <param name="points">The set of points remaining to be added to the KDTree.</param>
        /// <param name="nodes">The set of nodes RE</param>
        private void GenerateTree(
            ref KDNode currentNode,
            KDNode previousNode,
            int dim,
            IReadOnlyCollection <CoordinateWithIndex> points)
        {
            // See wikipedia for a good explanation KDTree construction.
            // https://en.wikipedia.org/wiki/K-d_tree

            // sort the points along the current dimension
            var sortedPoints = points.OrderBy(z => z.Coordinate[dim]).ToArray();

            // get the point which has the median value of the current dimension.
            var medianPoint    = sortedPoints[points.Count / 2];
            var medianPointIdx = sortedPoints.Length / 2;

            // The point with the median value all the current dimension now becomes the value of the current tree node
            // The previous node becomes the parents of the current node.
            currentNode  = new KDNode(medianPoint.Index, previousNode);
            previousNode = currentNode;

            // We now split the sorted points into 2 groups
            // 1st group: points before the median
            var leftPoints = new CoordinateWithIndex[medianPointIdx];

            Array.Copy(sortedPoints, leftPoints, leftPoints.Length);

            // 2nd group: Points after the median
            var rightPoints = new CoordinateWithIndex[sortedPoints.Length - (medianPointIdx + 1)];

            Array.Copy(
                sortedPoints,
                medianPointIdx + 1,
                rightPoints,
                0,
                rightPoints.Length);

            // We new recurse, passing the left and right arrays for arguments.
            // The current node's left and right values become the "roots" for
            // each recursion call. We also forward cycle to the next dimension.
            var nextDim = (dim + 1) % this.Dimensions; // select next dimension

            // We only need to recurse if the point array contains more than one point
            // If the array has no points then the node stay a null value
            if (leftPoints.Length <= 1)
            {
                if (leftPoints.Length == 1)
                {
                    currentNode.Left = new KDNode(leftPoints[0].Index, previousNode);
                }
            }
            else
            {
                this.GenerateTree(ref currentNode.Left, currentNode, nextDim, leftPoints);
            }

            // Do the same for the right points
            if (rightPoints.Length <= 1)
            {
                if (rightPoints.Length == 1)
                {
                    currentNode.Right = new KDNode(rightPoints[0].Index, previousNode);
                }
            }
            else
            {
                this.GenerateTree(ref currentNode.Right, currentNode, nextDim, rightPoints);
            }
        }