The Tor Browser / file revision

 /*

  * 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,

             bool orderWhenBulkLoading = true);

     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) SK_OVERRIDE;

     /**

      * If any inserts have been deferred, this will add them into the tree

      */

     virtual void flushDeferredInserts() SK_OVERRIDE;

     /**

      * Given a query rectangle, populates the passed-in array with the elements it intersects

      */

     virtual void search(const SkIRect& query, SkTDArray<void*>* results) SK_OVERRIDE;

     virtual void clear() SK_OVERRIDE;

     bool isEmpty() const { return 0 == fCount; }

     /**

      * Gets the depth of the tree structure

      */

     virtual int getDepth() const SK_OVERRIDE {

         return this->isEmpty() ? 0 : fRoot.fChild.subtree->fLevel + 1;

     }

     /**

      * This gets the insertion count (rather than the node count)

      */

     virtual int getCount() const SK_OVERRIDE { return fCount; }

     virtual void rewindInserts() SK_OVERRIDE;

 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, bool orderWhenBulkLoading);

     /**

      * 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)

     int fCount;

     Branch fRoot;

     SkChunkAlloc fNodes;

     SkTDArray<Branch> fDeferredInserts;

     SkScalar fAspectRatio;

     bool fSortWhenBulkLoading;

     Node* allocateNode(uint16_t level);

     typedef SkBBoxHierarchy INHERITED;

 };

 #endif