1 2 /* 3 * Copyright 2012 Google Inc. 4 * 5 * Use of this source code is governed by a BSD-style license that can be 6 * found in the LICENSE file. 7 */ 8 9 #ifndef SkRTree_DEFINED 10 #define SkRTree_DEFINED 11 12 #include "SkRect.h" 13 #include "SkTDArray.h" 14 #include "SkChunkAlloc.h" 15 #include "SkBBoxHierarchy.h" 16 17 /** 18 * An R-Tree implementation. In short, it is a balanced n-ary tree containing a hierarchy of 19 * bounding rectangles. 20 * 21 * Much like a B-Tree it maintains balance by enforcing minimum and maximum child counts, and 22 * splitting nodes when they become overfull. Unlike B-trees, however, we're using spatial data; so 23 * there isn't a canonical ordering to use when choosing insertion locations and splitting 24 * distributions. A variety of heuristics have been proposed for these problems; here, we're using 25 * something resembling an R*-tree, which attempts to minimize area and overlap during insertion, 26 * and aims to minimize a combination of margin, overlap, and area when splitting. 27 * 28 * One detail that is thus far unimplemented that may improve tree quality is attempting to remove 29 * and reinsert nodes when they become full, instead of immediately splitting (nodes that may have 30 * been placed well early on may hurt the tree later when more nodes have been added; removing 31 * and reinserting nodes generally helps reduce overlap and make a better tree). Deletion of nodes 32 * is also unimplemented. 33 * 34 * For more details see: 35 * 36 * Beckmann, N.; Kriegel, H. P.; Schneider, R.; Seeger, B. (1990). "The R*-tree: 37 * an efficient and robust access method for points and rectangles" 38 * 39 * It also supports bulk-loading from a batch of bounds and values; if you don't require the tree 40 * to be usable in its intermediate states while it is being constructed, this is significantly 41 * quicker than individual insertions and produces more consistent trees. 42 */ 43 class SkRTree : public SkBBoxHierarchy { 44 public: 45 SK_DECLARE_INST_COUNT(SkRTree) 46 47 /** 48 * Create a new R-Tree with specified min/max child counts. 49 * The child counts are valid iff: 50 * - (max + 1) / 2 >= min (splitting an overfull node must be enough to populate 2 nodes) 51 * - min < max 52 * - min > 0 53 * - max < SK_MaxU16 54 * If you have some prior information about the distribution of bounds you're expecting, you 55 * can provide an optional aspect ratio parameter. This allows the bulk-load algorithm to create 56 * better proportioned tiles of rectangles. 57 */ 58 static SkRTree* Create(int minChildren, int maxChildren, SkScalar aspectRatio = 1); 59 virtual ~SkRTree(); 60 61 /** 62 * Insert a node, consisting of bounds and a data value into the tree, if we don't immediately 63 * need to use the tree; we may allow the insert to be deferred (this can allow us to bulk-load 64 * a large batch of nodes at once, which tends to be faster and produce a better tree). 65 * @param data The data value 66 * @param bounds The corresponding bounding box 67 * @param defer Can this insert be deferred? (this may be ignored) 68 */ 69 virtual void insert(void* data, const SkIRect& bounds, bool defer = false); 70 71 /** 72 * If any inserts have been deferred, this will add them into the tree 73 */ 74 virtual void flushDeferredInserts(); 75 76 /** 77 * Given a query rectangle, populates the passed-in array with the elements it intersects 78 */ 79 virtual void search(const SkIRect& query, SkTDArray<void*>* results); 80 81 virtual void clear(); 82 bool isEmpty() const { return 0 == fCount; } 83 int getDepth() const { return this->isEmpty() ? 0 : fRoot.fChild.subtree->fLevel + 1; } 84 85 /** 86 * This gets the insertion count (rather than the node count) 87 */ 88 virtual int getCount() const { return fCount; } 89 90 virtual void rewindInserts() SK_OVERRIDE; 91 92 private: 93 94 struct Node; 95 96 /** 97 * A branch of the tree, this may contain a pointer to another interior node, or a data value 98 */ 99 struct Branch { 100 union { 101 Node* subtree; 102 void* data; 103 } fChild; 104 SkIRect fBounds; 105 }; 106 107 /** 108 * A node in the tree, has between fMinChildren and fMaxChildren (the root is a special case) 109 */ 110 struct Node { 111 uint16_t fNumChildren; 112 uint16_t fLevel; 113 bool isLeaf() { return 0 == fLevel; } 114 // Since we want to be able to pick min/max child counts at runtime, we assume the creator 115 // has allocated sufficient space directly after us in memory, and index into that space 116 Branch* child(size_t index) { 117 return reinterpret_cast<Branch*>(this + 1) + index; 118 } 119 }; 120 121 typedef int32_t SkIRect::*SortSide; 122 123 // Helper for sorting our children arrays by sides of their rects 124 struct RectLessThan { 125 RectLessThan(SkRTree::SortSide side) : fSide(side) { } 126 bool operator()(const SkRTree::Branch lhs, const SkRTree::Branch rhs) const { 127 return lhs.fBounds.*fSide < rhs.fBounds.*fSide; 128 } 129 private: 130 const SkRTree::SortSide fSide; 131 }; 132 133 struct RectLessX { 134 bool operator()(const SkRTree::Branch lhs, const SkRTree::Branch rhs) { 135 return ((lhs.fBounds.fRight - lhs.fBounds.fLeft) >> 1) < 136 ((rhs.fBounds.fRight - lhs.fBounds.fLeft) >> 1); 137 } 138 }; 139 140 struct RectLessY { 141 bool operator()(const SkRTree::Branch lhs, const SkRTree::Branch rhs) { 142 return ((lhs.fBounds.fBottom - lhs.fBounds.fTop) >> 1) < 143 ((rhs.fBounds.fBottom - lhs.fBounds.fTop) >> 1); 144 } 145 }; 146 147 SkRTree(int minChildren, int maxChildren, SkScalar aspectRatio); 148 149 /** 150 * Recursively descend the tree to find an insertion position for 'branch', updates 151 * bounding boxes on the way up. 152 */ 153 Branch* insert(Node* root, Branch* branch, uint16_t level = 0); 154 155 int chooseSubtree(Node* root, Branch* branch); 156 SkIRect computeBounds(Node* n); 157 int distributeChildren(Branch* children); 158 void search(Node* root, const SkIRect query, SkTDArray<void*>* results) const; 159 160 /** 161 * This performs a bottom-up bulk load using the STR (sort-tile-recursive) algorithm, this 162 * seems to generally produce better, more consistent trees at significantly lower cost than 163 * repeated insertions. 164 * 165 * This consumes the input array. 166 * 167 * TODO: Experiment with other bulk-load algorithms (in particular the Hilbert pack variant, 168 * which groups rects by position on the Hilbert curve, is probably worth a look). There also 169 * exist top-down bulk load variants (VAMSplit, TopDownGreedy, etc). 170 */ 171 Branch bulkLoad(SkTDArray<Branch>* branches, int level = 0); 172 173 void validate(); 174 int validateSubtree(Node* root, SkIRect bounds, bool isRoot = false); 175 176 const int fMinChildren; 177 const int fMaxChildren; 178 const size_t fNodeSize; 179 180 // This is the count of data elements (rather than total nodes in the tree) 181 size_t fCount; 182 183 Branch fRoot; 184 SkChunkAlloc fNodes; 185 SkTDArray<Branch> fDeferredInserts; 186 SkScalar fAspectRatio; 187 188 Node* allocateNode(uint16_t level); 189 190 typedef SkBBoxHierarchy INHERITED; 191 }; 192 193 #endif 194
