| |
| /* |
| * Copyright 2012 Google Inc. |
| * |
| * Use of this source code is governed by a BSD-style license that can be |
| * found in the LICENSE file. |
| */ |
| |
| #ifndef SkRTree_DEFINED |
| #define SkRTree_DEFINED |
| |
| #include "SkRect.h" |
| #include "SkTDArray.h" |
| #include "SkChunkAlloc.h" |
| #include "SkBBoxHierarchy.h" |
| |
| /** |
| * An R-Tree implementation. In short, it is a balanced n-ary tree containing a hierarchy of |
| * bounding rectangles. |
| * |
| * Much like a B-Tree it maintains balance by enforcing minimum and maximum child counts, and |
| * splitting nodes when they become overfull. Unlike B-trees, however, we're using spatial data; so |
| * there isn't a canonical ordering to use when choosing insertion locations and splitting |
| * distributions. A variety of heuristics have been proposed for these problems; here, we're using |
| * something resembling an R*-tree, which attempts to minimize area and overlap during insertion, |
| * and aims to minimize a combination of margin, overlap, and area when splitting. |
| * |
| * One detail that is thus far unimplemented that may improve tree quality is attempting to remove |
| * and reinsert nodes when they become full, instead of immediately splitting (nodes that may have |
| * been placed well early on may hurt the tree later when more nodes have been added; removing |
| * and reinserting nodes generally helps reduce overlap and make a better tree). Deletion of nodes |
| * is also unimplemented. |
| * |
| * For more details see: |
| * |
| * Beckmann, N.; Kriegel, H. P.; Schneider, R.; Seeger, B. (1990). "The R*-tree: |
| * an efficient and robust access method for points and rectangles" |
| * |
| * It also supports bulk-loading from a batch of bounds and values; if you don't require the tree |
| * to be usable in its intermediate states while it is being constructed, this is significantly |
| * quicker than individual insertions and produces more consistent trees. |
| */ |
| class SkRTree : public SkBBoxHierarchy { |
| public: |
| SK_DECLARE_INST_COUNT(SkRTree) |
| |
| /** |
| * Create a new R-Tree with specified min/max child counts. |
| * The child counts are valid iff: |
| * - (max + 1) / 2 >= min (splitting an overfull node must be enough to populate 2 nodes) |
| * - min < max |
| * - min > 0 |
| * - max < SK_MaxU16 |
| * If you have some prior information about the distribution of bounds you're expecting, you |
| * can provide an optional aspect ratio parameter. This allows the bulk-load algorithm to create |
| * better proportioned tiles of rectangles. |
| */ |
| static SkRTree* Create(int minChildren, int maxChildren, SkScalar aspectRatio = 1); |
| virtual ~SkRTree(); |
| |
| /** |
| * Insert a node, consisting of bounds and a data value into the tree, if we don't immediately |
| * need to use the tree; we may allow the insert to be deferred (this can allow us to bulk-load |
| * a large batch of nodes at once, which tends to be faster and produce a better tree). |
| * @param data The data value |
| * @param bounds The corresponding bounding box |
| * @param defer Can this insert be deferred? (this may be ignored) |
| */ |
| virtual void insert(void* data, const SkIRect& bounds, bool defer = false); |
| |
| /** |
| * If any inserts have been deferred, this will add them into the tree |
| */ |
| virtual void flushDeferredInserts(); |
| |
| /** |
| * Given a query rectangle, populates the passed-in array with the elements it intersects |
| */ |
| virtual void search(const SkIRect& query, SkTDArray<void*>* results); |
| |
| virtual void clear(); |
| bool isEmpty() const { return 0 == fCount; } |
| int getDepth() const { return this->isEmpty() ? 0 : fRoot.fChild.subtree->fLevel + 1; } |
| |
| /** |
| * This gets the insertion count (rather than the node count) |
| */ |
| virtual int getCount() const { return fCount; } |
| |
| private: |
| |
| struct Node; |
| |
| /** |
| * A branch of the tree, this may contain a pointer to another interior node, or a data value |
| */ |
| struct Branch { |
| union { |
| Node* subtree; |
| void* data; |
| } fChild; |
| SkIRect fBounds; |
| }; |
| |
| /** |
| * A node in the tree, has between fMinChildren and fMaxChildren (the root is a special case) |
| */ |
| struct Node { |
| uint16_t fNumChildren; |
| uint16_t fLevel; |
| bool isLeaf() { return 0 == fLevel; } |
| // Since we want to be able to pick min/max child counts at runtime, we assume the creator |
| // has allocated sufficient space directly after us in memory, and index into that space |
| Branch* child(size_t index) { |
| return reinterpret_cast<Branch*>(this + 1) + index; |
| } |
| }; |
| |
| typedef int32_t SkIRect::*SortSide; |
| |
| // Helper for sorting our children arrays by sides of their rects |
| struct RectLessThan { |
| RectLessThan(SkRTree::SortSide side) : fSide(side) { } |
| bool operator()(const SkRTree::Branch lhs, const SkRTree::Branch rhs) const { |
| return lhs.fBounds.*fSide < rhs.fBounds.*fSide; |
| } |
| private: |
| const SkRTree::SortSide fSide; |
| }; |
| |
| struct RectLessX { |
| bool operator()(const SkRTree::Branch lhs, const SkRTree::Branch rhs) { |
| return ((lhs.fBounds.fRight - lhs.fBounds.fLeft) >> 1) < |
| ((rhs.fBounds.fRight - lhs.fBounds.fLeft) >> 1); |
| } |
| }; |
| |
| struct RectLessY { |
| bool operator()(const SkRTree::Branch lhs, const SkRTree::Branch rhs) { |
| return ((lhs.fBounds.fBottom - lhs.fBounds.fTop) >> 1) < |
| ((rhs.fBounds.fBottom - lhs.fBounds.fTop) >> 1); |
| } |
| }; |
| |
| SkRTree(int minChildren, int maxChildren, SkScalar aspectRatio); |
| |
| /** |
| * Recursively descend the tree to find an insertion position for 'branch', updates |
| * bounding boxes on the way up. |
| */ |
| Branch* insert(Node* root, Branch* branch, uint16_t level = 0); |
| |
| int chooseSubtree(Node* root, Branch* branch); |
| SkIRect computeBounds(Node* n); |
| int distributeChildren(Branch* children); |
| void search(Node* root, const SkIRect query, SkTDArray<void*>* results) const; |
| |
| /** |
| * This performs a bottom-up bulk load using the STR (sort-tile-recursive) algorithm, this |
| * seems to generally produce better, more consistent trees at significantly lower cost than |
| * repeated insertions. |
| * |
| * This consumes the input array. |
| * |
| * TODO: Experiment with other bulk-load algorithms (in particular the Hilbert pack variant, |
| * which groups rects by position on the Hilbert curve, is probably worth a look). There also |
| * exist top-down bulk load variants (VAMSplit, TopDownGreedy, etc). |
| */ |
| Branch bulkLoad(SkTDArray<Branch>* branches, int level = 0); |
| |
| void validate(); |
| int validateSubtree(Node* root, SkIRect bounds, bool isRoot = false); |
| |
| const int fMinChildren; |
| const int fMaxChildren; |
| const size_t fNodeSize; |
| |
| // This is the count of data elements (rather than total nodes in the tree) |
| size_t fCount; |
| |
| Branch fRoot; |
| SkChunkAlloc fNodes; |
| SkTDArray<Branch> fDeferredInserts; |
| SkScalar fAspectRatio; |
| |
| Node* allocateNode(uint16_t level); |
| |
| typedef SkBBoxHierarchy INHERITED; |
| }; |
| |
| #endif |