kdTree.h

   1 #ifndef KDTREE_HEADER_
   2 #define KDTREE_HEADER_
   3
   4 #include "util.h"
   5
   6 namespace NOSPACE {
   7         using namespace std;
   8 }
   9
  10 /** Routines for computing with T[length] number fields */
  11 namespace FieldMath {
  12         /** Calls transformer(x,y) for every x from [i1..iEnd1) and corresponding y from [i2..) */
  13         template<class I1,class I2,class Transf>
  14         Transf transform2( I1 i1, I1 iEnd1, I2 i2, Transf transformer ) {
  15                 for (; i1!=iEnd1; ++i1,++i2)
  16                         transformer(*i1,*i2);
  17                 return transformer;
  18         }
  19         /** Analogous to ::transform2 */
  20         template<class I1,class I2,class I3,class Transf>
  21         Transf transform3( I1 i1, I1 iEnd1, I2 i2, I3 i3, Transf transformer ) {
  22                 for (; i1!=iEnd1; ++i1,++i2,++i3)
  23                         transformer(*i1,*i2,*i3);
  24                 return transformer;
  25         }
  26         /** Analogous to ::transform2 */
  27         template<class I1,class I2,class I3,class I4,class Transf>
  28         Transf transform4( I1 i1, I1 iEnd1, I2 i2, I3 i3, I4 i4, Transf transformer ) {
  29                 for (; i1!=iEnd1; ++i1,++i2,++i3,++i4)
  30                         transformer(*i1,*i2,*i3,*i4);
  31                 return transformer;
  32         }
  33
  34         /** Means b[i]=a[i]; */
  35         template<class T> T* assign(const T *a,int length,T *b) {
  36                 //copy(a,a+length,b);
  37
  38                 memcpy(b,a,length*sizeof(T));
  39
  40                 return b;
  41         }
  42
  43         namespace NOSPACE {
  44                 template<class T,bool CheckNaNs> struct MoveToBounds {
  45                         T sqrError;
  46
  47                         MoveToBounds()
  48                         : sqrError(0) {}
  49
  50                         void operator()(const T &point,const T bounds[2],T &result) {
  51                                 if ( CheckNaNs && isNaN(point) )
  52                                         return;
  53                                 if ( point < bounds[0] ) {
  54                                         sqrError+= sqr(bounds[0]-point);
  55                                         result= bounds[0];
  56                                 } else
  57                                 if ( point > bounds[1] ) {
  58                                         sqrError+= sqr(point-bounds[1]);
  59                                         result= bounds[1];
  60                                 } else
  61                                         result= point;
  62                         }
  63                 };
  64         }
  65         /** Copy_moves a vector (\p point) to the nearest point (\p result)
  66          *      within bounds (\p bounds) and returns SE (distance^2) */
  67         template<class T,bool CheckNaNs>
  68         T moveToBounds_copy(const T *point,const T (*bounds)[2],int length,T *result) {
  69                 return transform3( point, point+length, bounds, result
  70                         , MoveToBounds<T,CheckNaNs>() ) .sqrError;
  71         }
  72 //      namespace NOSPACE {
  73 //              template<class T> struct Min {
  74 //                      const T& operator()(const T &a,const T &b) const
  75 //                              { return min(a,b); }
  76 //              };
  77 //              template<class T> struct Max {
  78 //                      const T& operator()(const T &a,const T &b) const
  79 //                              { return max(a,b); }
  80 //              };
  81 //      }
  82 //      /** Means b[i]=min(a[i],b[i]) */
  83 //      template<class T> T* min(const T *a,int length,T *b) {
  84 //              transform( a, a+length, b, b, Min<T>() );
  85 //              return b;
  86 //      }
  87 //      /** Means b[i]=max(a[i],b[i]) */
  88 //      template<class T> T* max(const T *a,int length,T *b) {
  89 //              transform( a, a+length, b, b, Max<T>() );
  90 //              return b;
  91 //      }
  92
  93 //      /** Returns whether a[i]<=b[i] */
  94 //      template<class T> bool isOrdered(const T *a,const T *b,int length) {
  95 //              const T *aEnd=a+length;
  96 //              do {
  97 //                      if ( *a++ > *b++ )
  98 //                              return false;
  99 //              } while (a!=aEnd);
 100 //              return true;
 101 //      }
 102         /*
 103         namespace NOSPACE {
 104                 template<class T> struct Adder {
 105                         void operator()(const T &a,const T &b,T &c)
 106                                 { c=a+b; }
 107                 };
 108                 template<class T> struct Subtractor {
 109                         void operator()(const T &a,const T &b,T &c)
 110                                 { c=a-b; }
 111                 };
 112         }
 113         template<class T> T* add(const T *a,const T *b,int length,T *c) {
 114                 transform3( a, a+length, b, c, Adder<T>() );
 115         }
 116         template<class T> T* subtract(const T *a,const T *b,int length,T *c) {
 117                 transform3( a, a+length, b, c, Subtractor<T>() );
 118         }
 119         */
 120 }
 121
 122 template<class T> class KDBuilder;
 123 /** A generic KD-tree */
 124 template<class T> class KDTree {
 125 public:
 126         friend class KDBuilder<T>;
 127         typedef KDBuilder<T> Builder;
 128 protected:
 129         /** Represents one node of the KD-tree */
 130         struct Node {
 131                 int coord;      ///< The coordinate along which the tree splits in this node
 132                 T threshold;///< The threshold of the split (left[#coord] <= #threshold <= right[#coord])
 133         };
 134         typedef T (*Bounds)[2];
 135
 136 public:
 137         const int depth                 ///  The depth of the tree = ::log2ceil(#count)
 138         , length                                ///      The length of the vectors
 139         , count;                                ///< The number of the vectors
 140 protected:
 141         Node *nodes;    ///< The array of the tree-nodes
 142         int *dataIDs;   ///< Data IDs for children of "leaf" nodes
 143         Bounds bounds;  ///< The bounding box for all the data
 144
 145         /** Builds a new KD-tree from \p count_ vectors of \p length_ elements stored in \data */
 146         KDTree(int length_,int count_)
 147         : depth( log2ceil(count_) ), length(length_), count(count_)
 148         , nodes( new Node[count_] ), dataIDs( new int[count_] ), bounds( new T[length_][2] ) {
 149         }
 150
 151         /** Copy constructor with swapping (or rather moving) semantics */
 152         KDTree(KDTree &other)
 153         : depth(other.depth), length(other.length), count(other.count)
 154         , nodes(other.nodes), dataIDs(other.dataIDs), bounds(other.bounds) {
 155                 other.nodes= 0;
 156                 other.dataIDs= 0;
 157                 other.bounds= 0;
 158         }
 159
 160 public:
 161         /** Only frees the memory */
 162         ~KDTree() {
 163         //      clean up
 164                 delete[] nodes;
 165                 delete[] dataIDs;
 166                 delete[] bounds;
 167         }
 168         /** Takes an index of "leaf" (nonexistent) node and returns the appropriate data ID */
 169         int leafID2dataID(int leafID) const {
 170                 ASSERT( count<=leafID && leafID<2*count );
 171                 int index= leafID-powers[depth];
 172                 if (index<0)
 173                         index+= count;
 174                 ASSERT( 0<=index && index<count );
 175                 return dataIDs[index];
 176         }
 177
 178         /** Manages a heap from nodes of a KDTree.
 179          *      It returns vectors (their indices) in the order according to distance (SE)
 180          *      from a given fixed point. It can return a lower bound of the SEs of the remaining
 181          *      vectors at any time. */
 182         class PointHeap {
 183                 /** One element of the heap representing a node in the KDTree */
 184                 struct HeapNode {
 185                         int nodeIndex;  ///< Index of the node in #kd
 186                         T *data;                ///< Stores the SE and the coordinates of the nearest point
 187
 188                         /** No-init constructor */
 189                         HeapNode() {}
 190                         /** Initializes the members from the parameters */
 191                         HeapNode(int nodeIndex_,T *data_): nodeIndex(nodeIndex_), data(data_) {}
 192
 193                         /** Returns reference to the SE of the nearest point to this node's bounding box */
 194                         T& getSE()                      { return *data; }
 195                         /** Returns the SE of the nearest point to this node's bounding box */
 196                         T getSE() const         { return *data; }
 197                         /** Returns pointer to the nearest point to this node's bounding box */
 198                         T* getNearest()         { return data+1; }
 199                 };
 200                 /** Defines the order of #heap - ascending according to #getSE */
 201                 struct HeapOrder {
 202                         bool operator()(const HeapNode &a,const HeapNode &b)
 203                                 { return a.getSE() > b.getSE(); }
 204                 };
 205
 206                 const KDTree &kd;                       ///< Reference to the KDTree we operate on
 207                 const T* const point;           ///< Pointer to the point we are trying to approach
 208                 vector<HeapNode> heap;          ///< The current heap of the tree nodes
 209                 BulkAllocator<T> allocator;     ///< The allocator for HeapNode::data
 210         public:
 211                 /** Build the heap from the KDTree \p tree and vector \p point_
 212                  *      (they've got to remain valid until destruction) */
 213                 PointHeap(const KDTree &tree,const T *point_,bool checkNaNs)
 214                 : kd(tree), point(point_) {
 215                         ASSERT(point);
 216                 //      create the root heap-node
 217                         HeapNode rootNode( 1, allocator.makeField(kd.length+1) );
 218                 //      compute the nearest point within the global bounds and corresponding SE
 219                         using namespace FieldMath;
 220                         rootNode.getSE()= checkNaNs
 221                                 ? moveToBounds_copy<T,true> ( point, kd.bounds, kd.length, rootNode.getNearest() )
 222                                 : moveToBounds_copy<T,false>( point, kd.bounds, kd.length, rootNode.getNearest() );
 223                 //      push it onto the heap (and reserve more to speed up the first leaf-gettings)
 224                         heap.reserve(kd.depth*2);
 225                         heap.push_back(rootNode);
 226                 }
 227
 228                 /** Returns whether the heap is empty ( !isEmpty() is needed for all other methods) */
 229                 bool isEmpty()
 230                         { return heap.empty(); }
 231
 232                 /** Returns the SE of the top node (always equals the SE of the next leaf) */
 233                 T getTopSE() {
 234                         ASSERT( !isEmpty() );
 235                         return heap[0].getSE();
 236                 }
 237
 238                 /** Removes a leaf, returns the matching vector's index */
 239                 template<bool CheckNaNs> int popLeaf() {
 240                 //      ensure a leaf is on the top of the heap and get its ID
 241                         makeTopLeaf<CheckNaNs>();
 242                         int result= kd.leafID2dataID( heap.front().nodeIndex );
 243                 //      remove the top from the heap (no need to free the memory - #allocator)
 244                         pop_heap( heap.begin(), heap.end(), HeapOrder() );
 245                         heap.pop_back();
 246                         return result;
 247                 }
 248         protected:
 249                 /** Divides the top nodes until there's a leaf on the top */
 250                 template<bool CheckNaNs> void makeTopLeaf();
 251
 252         }; // PointHeap class
 253 }; // KDTree class
 254
 255
 256 template<class T> template<bool CheckNaNs>
 257 void KDTree<T>::PointHeap::makeTopLeaf() {
 258         ASSERT( !isEmpty() );
 259 //      exit if there's a leaf on the top already
 260         if ( !(heap[0].nodeIndex<kd.count) )
 261                 return;
 262         PtrInt oldHeapSize= heap.size();
 263         HeapNode heapRoot= heap[0]; // making a local working copy of the top of the heap
 264
 265         do { // while heapRoot isn't leaf ... while ( heapRoot.nodeIndex<kd.count )
 266                 const Node &node= kd.nodes[heapRoot.nodeIndex];
 267         //      now replace the node with its two children:
 268         //              one of them will have the same SE (replaces its parent on the top),
 269         //              the other one can have higher SE (push_back-ed on the heap)
 270
 271         //      create a new heap-node and allocate it's data
 272                 HeapNode newHNode;
 273                 newHNode.data= allocator.makeField(kd.length+1);
 274         //      assign index of the left child for both the heap-nodes (for now)
 275                 newHNode.nodeIndex= (heapRoot.nodeIndex*= 2);
 276         //      the nearest point of the new heap-node only differs in one coordinate
 277                 FieldMath::assign( heapRoot.getNearest(), kd.length, newHNode.getNearest() );
 278
 279                 if ( !CheckNaNs || !isNaN(point[node.coord]) ) { // valid coordinate -> normal processing
 280                         newHNode.getNearest()[node.coord]= node.threshold;
 281
 282                 //      the SE of the child heap-nodes can be computed from the parent heap-node
 283                         Real oldDistance= Real(point[node.coord]) - heapRoot.getNearest()[node.coord];
 284                         Real newDistance= Real(point[node.coord]) - node.threshold;
 285                         newHNode.getSE()= heapRoot.getSE() - sqr(oldDistance) + sqr(newDistance);
 286                         ASSERT( newHNode.getSE() >= heapRoot.getSE() );
 287                 /*      another way to do this, according to: A^2-B^2 = (A-B)*(A+B)
 288                         Real nearestInCoord= heapRoot.getNearest()[node.coord];
 289                         newHNode.getSE()= heapRoot.getSE() + (nearestInCoord-node.threshold)
 290                                 * ( ldexp((Real)point[node.coord],1) - nearestInCoord - node.threshold );
 291                 */
 292                 //      correct the nodeIndex of the new children
 293                         if ( newDistance <= 0 )
 294                         //      the point is in the left part -> the left child will be on the top
 295                                 ++newHNode.nodeIndex;
 296                         else
 297                         //      the point is in the right part -> the right child will be on the top
 298                                 ++heapRoot.nodeIndex;
 299
 300                 } else  { // the coordinate doesn't have any effect
 301                         newHNode.getSE()= heapRoot.getSE();
 302                         ++newHNode.nodeIndex;
 303                 }
 304
 305         //      add the new node to the back, restore the heap-property later
 306                 heap.push_back(newHNode);
 307         } while ( heapRoot.nodeIndex<kd.count );
 308
 309         heap[0]= heapRoot; // restoring the working copy of the heap's top node
 310 //      restore the heap-property on the added nodes
 311         typename vector<HeapNode>::iterator it= heap.begin()+oldHeapSize;
 312         do
 313                 push_heap( heap.begin(), it, HeapOrder() );
 314         while ( it++ != heap.end() );
 315 } // KDTree<T>::PointHeap::makeTopLeaf<CheckNaNs>() method
 316
 317
 318 template<class T> class KDBuilder: public KDTree<T> {
 319 public:
 320         typedef KDTree<T> Tree;
 321         typedef T BoundsPair[2];
 322         typedef typename Tree::Bounds Bounds;
 323         typedef int (KDBuilder::*CoordChooser)
 324                 (int nodeIndex,int *beginIDs,int *endIDs,int depthLeft) const;
 325 protected:
 326         using Tree::depth;      using Tree::length;             using Tree::count;
 327         using Tree::nodes;      using Tree::dataIDs;    using Tree::bounds;
 328
 329         const T *data;
 330         const CoordChooser chooser;
 331         mutable Bounds chooserTmp;
 332
 333         KDBuilder(const T *data_,int length,int count,CoordChooser chooser_)
 334         : Tree(length,count), data(data_), chooser(chooser_), chooserTmp(0) {
 335                 ASSERT( length>0 && count>0 && chooser && data );
 336         //      create the index-vector, coumpute the bounding box, build the tree
 337                 for (int i=0; i<count; ++i)
 338                         dataIDs[i]= i;
 339                 getBounds(bounds);
 340                 if (count>1)
 341                         buildNode(1,dataIDs,dataIDs+count,depth);
 342                 delete[] chooserTmp;
 343                 DEBUG_ONLY( chooserTmp= 0; )
 344         }
 345
 346         /** Creates bounds containing one value */
 347         struct NewBounds {
 348                 void operator()(const T &val,BoundsPair &bounds) const
 349                         { bounds[0]= bounds[1]= val; }
 350         };
 351         /** Expands a valid bounding box to contain a point (one coordinate at once) */
 352         struct BoundsExpander {
 353                 void operator()(const T &val,BoundsPair &bounds) const {
 354                         if ( val < bounds[0] ) // lower bound
 355                                 bounds[0]= val; else
 356                         if ( val > bounds[1] ) // upper bound
 357                                 bounds[1]= val;
 358                 }
 359         };
 360         /** Computes the bounding box of #count vectors with length #length stored in #data.
 361          *      The vectors in #data are stored linearly, /p boundsRes should be preallocated */
 362         void getBounds(Bounds boundsRes) const {
 363                 using namespace FieldMath;
 364                 ASSERT(length>0);
 365         //      make the initial bounds only contain the first point
 366                 transform2(data,data+length,boundsRes,NewBounds());
 367                 int count= Tree::count;
 368                 const T *nowData= data;
 369         //      expand the bounds by every point (except for the first one)
 370                 while (--count) {
 371                         nowData+= length;
 372                         transform2( nowData, nowData+length, boundsRes, BoundsExpander() );
 373                 }
 374         }
 375         /** Like #getBounds, but it only works on vectors with indices from [\p beginIDs..\p endIDs)
 376          *      instead of [0..#count), \p boundsRes should be preallocated to store the result */
 377         void getBounds(const int *beginIDs,const int *endIDs,Bounds boundsRes) const {
 378                 using namespace FieldMath;
 379                 ASSERT(endIDs>beginIDs);
 380         //      make the initial bounds only contain the first point
 381                 const T *begin= data + *beginIDs*length;
 382                 transform2(begin,begin+length,boundsRes,NewBounds());
 383         //      expand the bounds by every point (except for the first one)
 384                 while ( ++beginIDs != endIDs ) {
 385                         begin= data + *beginIDs*length;
 386                         transform2( begin, begin+length, boundsRes, BoundsExpander() );
 387                 }
 388         }
 389
 390         /** Recursively builds node \p nodeIndex and its subtree of depth \p depthLeft
 391         *       (including leaves), operates on data \p data in the range [\p beginIDs,\p endIDs) */
 392         void buildNode(int nodeIndex,int *beginIDs,int *endIDs,int depthLeft);
 393
 394 public:
 395         /** CoordChooser choosing the longest coordinate of the bounding box of the current interval */
 396         int choosePrecise(int nodeIndex,int *beginIDs,int *endIDs,int /*depthLeft*/) const;
 397         /** CoordChooser choosing the coordinate only according to the depth */
 398         int chooseFast(int /*nodeIndex*/,int* /*beginIDs*/,int* /*endIDs*/,int depthLeft) const
 399                 { return depthLeft%length; }
 400         /** CoordChooser choosing a random coordinate */
 401         int chooseRand(int /*nodeIndex*/,int* /*beginIDs*/,int* /*endIDs*/,int /*depthLeft*/) const
 402                 { return rand()%length; }
 403         int chooseApprox(int nodeIndex,int* /*beginIDs*/,int* /*endIDs*/,int depthLeft) const;
 404
 405         static Tree* makeTree(const T *data,int length,int count,CoordChooser chooser) {
 406                 KDBuilder builder(data,length,count,chooser);
 407                 return new Tree(builder);
 408         }
 409 }; // KDBuilder class
 410
 411
 412
 413 namespace NOSPACE {
 414         /** Finds the longest coordinate of a bounding box */
 415         template<class T> struct MaxDiffCoord {
 416                 typedef typename KDBuilder<T>::BoundsPair BoundsPair;
 417
 418                 T maxDiff;
 419                 int bestIndex, nextIndex;
 420
 421                 MaxDiffCoord(const BoundsPair& bounds0)
 422                 : maxDiff(bounds0[1]-bounds0[0]), bestIndex(0), nextIndex(1) {}
 423
 424                 void operator()(const BoundsPair& bounds_i) {
 425                         T diff= bounds_i[1]-bounds_i[0];
 426                         if (diff>maxDiff) {
 427                                 bestIndex= nextIndex;
 428                                 maxDiff= diff;
 429                         }
 430                         ++nextIndex;
 431                 }
 432         };
 433 }
 434 template<class T> int KDBuilder<T>
 435 ::choosePrecise(int nodeIndex,int *beginIDs,int *endIDs,int) const {
 436         ASSERT( nodeIndex>0 && beginIDs && endIDs && beginIDs<endIDs );
 437 //      temporary storage for computed bounding box
 438         BoundsPair boundsStorage[length];
 439         const BoundsPair *localBounds;
 440
 441         if ( nodeIndex>1 ) { // compute the bounding box
 442                 localBounds= boundsStorage;
 443                 getBounds( beginIDs, endIDs, boundsStorage );
 444         } else // we are in the root -> we can use already computed bounds
 445                 localBounds= bounds;
 446 //      find and return the longest coordinate
 447         MaxDiffCoord<T> mdc= for_each
 448                 ( localBounds+1, localBounds+length, MaxDiffCoord<T>(localBounds[0]) );
 449         ASSERT( mdc.nextIndex == length );
 450         return mdc.bestIndex;
 451 }
 452 template<class T> int KDBuilder<T>::chooseApprox(int nodeIndex,int*,int*,int) const {
 453         using namespace FieldMath;
 454         ASSERT(nodeIndex>0);
 455
 456         int myDepth= log2ceil(nodeIndex+1)-1;
 457         if (!myDepth) { // I'm in the root - copy the bounds
 458                 ASSERT(nodeIndex==1);
 459                 chooserTmp= new BoundsPair[length*(depth+1)]; // allocate my temporary bound-array
 460                 assign( bounds, length, chooserTmp );
 461         }
 462
 463         Bounds myBounds= chooserTmp+length*myDepth;
 464         if (myDepth) { // I'm not the root - copy parent's bounds and modify them
 465                 const typename Tree::Node &parent= nodes[nodeIndex/2];
 466                 Bounds parentBounds= myBounds-length;
 467                 if (nodeIndex%2) {      // I'm the right son -> bounds on this level not initialized
 468                         assign( parentBounds, length, myBounds );
 469                         myBounds[parent.coord][0]= parent.threshold; // adjusting the lower bound
 470                 } else // I'm the left son
 471                         if ( nodeIndex+1 < count ) { // almost the same as brother -> only adjust the coordinate
 472                                 myBounds[parent.coord][0]= parentBounds[parent.coord][0];
 473                                 myBounds[parent.coord][1]= parent.threshold;
 474                         } else { // I've got no brother
 475                                 ASSERT( nodeIndex+1 == count );
 476                                 assign( parentBounds, length, myBounds );
 477                                 myBounds[parent.coord][1]= parent.threshold;
 478                         }
 479         }
 480 //      find out the widest dimension
 481         MaxDiffCoord<T> mdc= for_each( myBounds+1, myBounds+length, MaxDiffCoord<T>(myBounds[0]) );
 482         ASSERT( mdc.nextIndex == length );
 483         return mdc.bestIndex;
 484 }
 485
 486 namespace NOSPACE {
 487         /** Compares vectors (given by their indices) according to a given coordinate */
 488         template<class T> class IndexComparator {
 489                 const T *data;
 490                 int length;
 491         public:
 492                 IndexComparator(const T *data_,int length_,int index_)
 493                 : data(data_+index_), length(length_) {}
 494                 bool operator()(int a,int b) const
 495                         { return data[a*length] < data[b*length]; }
 496         };
 497 }
 498 template<class T> void KDBuilder<T>
 499 ::buildNode(int nodeIndex,int *beginIDs,int *endIDs,int depthLeft) {
 500         int count= endIDs-beginIDs; // owershadowing Tree::count
 501 //      check we've got at least one vector and the depth&count are adequate to each other
 502         ASSERT( count>=2 && powers[depthLeft-1]<count && count<=powers[depthLeft] );
 503         --depthLeft;
 504         bool shallowRight= ( count <= powers[depthLeft]+powers[depthLeft-1] );
 505         int *middle= shallowRight
 506                 ? endIDs-powers[depthLeft-1]
 507                 : beginIDs+powers[depthLeft];
 508 //      find out the dividing coordinate and find the median in this coordinate
 509         int coord= (this->*chooser)(nodeIndex,beginIDs,endIDs,depthLeft);
 510         nth_element( beginIDs, middle , endIDs, IndexComparator<T>(data,length,coord) );
 511 //      fill the node's data (dividing coordinate and its threshold)
 512         nodes[nodeIndex].coord= coord;
 513         nodes[nodeIndex].threshold= data[*middle*length+coord];
 514 //      recurse on both halves (if needed; fall-through switch)
 515         switch (count) {
 516         default: //     we've got enough nodes - build both subtrees (fall through)
 517         //      build the right subtree
 518                 buildNode( 2*nodeIndex+1, middle, endIDs, depthLeft-shallowRight );
 519         case 3: // only a pair in the first half
 520         //      build the left subtree
 521                 buildNode( 2*nodeIndex, beginIDs, middle, depthLeft );
 522         case 2: // nothing needs to be sorted
 523                 ;
 524         }
 525 }
 526
 527 #endif // KDTREE_HEADER_