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doxygen classify/kdtree.cpp
This commit is contained in:
Jim O'Regan
parent
5668a52670
commit
84788d49a0
@ -48,7 +48,7 @@ static int NextLevel(KDTREE *tree, int level) {
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}
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//-----------------------------------------------------------------------------
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// Store the k smallest-keyed key-value pairs.
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/** Store the k smallest-keyed key-value pairs. */
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template<typename Key, typename Value>
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class MinK {
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public:
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@ -70,11 +70,11 @@ class MinK {
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const Element* elements() { return elements_; }
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private:
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const Key max_key_; // the maximum possible Key
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Element* elements_; // unsorted array of elements
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int elements_count_; // the number of results collected so far
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int k_; // the number of results we want from the search
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int max_index_; // the index of the result with the largest key
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const Key max_key_; //< the maximum possible Key
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Element* elements_; //< unsorted array of elements
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int elements_count_; //< the number of results collected so far
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int k_; //< the number of results we want from the search
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int max_index_; //< the index of the result with the largest key
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};
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template<typename Key, typename Value>
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@ -117,13 +117,13 @@ bool MinK<Key, Value>::insert(Key key, Value value) {
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//-----------------------------------------------------------------------------
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// Helper class for searching for the k closest points to query_point in tree.
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/** Helper class for searching for the k closest points to query_point in tree. */
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class KDTreeSearch {
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public:
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KDTreeSearch(KDTREE* tree, FLOAT32 *query_point, int k_closest);
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~KDTreeSearch();
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// Return the k nearest points' data.
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/** Return the k nearest points' data. */
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void Search(int *result_count, FLOAT32 *distances, void **results);
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private:
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@ -133,8 +133,8 @@ class KDTreeSearch {
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KDTREE *tree_;
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FLOAT32 *query_point_;
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MinK<FLOAT32, void *>* results_;
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FLOAT32 *sb_min_; // search box minimum
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FLOAT32 *sb_max_; // search box maximum
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FLOAT32 *sb_min_; //< search box minimum
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FLOAT32 *sb_max_; //< search box maximum
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};
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KDTreeSearch::KDTreeSearch(KDTREE* tree, FLOAT32 *query_point, int k_closest) :
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@ -151,8 +151,8 @@ KDTreeSearch::~KDTreeSearch() {
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delete[] sb_max_;
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}
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// Locate the k_closest points to query_point_, and return their distances and
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// data into the given buffers.
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/// Locate the k_closest points to query_point_, and return their distances and
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/// data into the given buffers.
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void KDTreeSearch::Search(int *result_count,
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FLOAT32 *distances,
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void **results) {
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@ -176,11 +176,9 @@ void KDTreeSearch::Search(int *result_count,
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/*-----------------------------------------------------------------------------
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Public Code
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-----------------------------------------------------------------------------*/
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/*---------------------------------------------------------------------------*/
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/// Return a new KDTREE based on the specified parameters.
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/// Parameters:
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/// KeySize # of dimensions in the K-D tree
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/// KeyDesc array of params to describe key dimensions
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/// @return a new KDTREE based on the specified parameters.
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/// @param KeySize # of dimensions in the K-D tree
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/// @param KeyDesc array of params to describe key dimensions
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KDTREE *MakeKDTree(inT16 KeySize, const PARAM_DESC KeyDesc[]) {
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KDTREE *KDTree = (KDTREE *) Emalloc(
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sizeof(KDTREE) + (KeySize - 1) * sizeof(PARAM_DESC));
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@ -205,8 +203,6 @@ KDTREE *MakeKDTree(inT16 KeySize, const PARAM_DESC KeyDesc[]) {
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}
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/*---------------------------------------------------------------------------*/
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void KDStore(KDTREE *Tree, FLOAT32 *Key, void *Data) {
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/**
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* This routine stores Data in the K-D tree specified by Tree
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* using Key as an access key.
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@ -219,6 +215,7 @@ void KDStore(KDTREE *Tree, FLOAT32 *Key, void *Data) {
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* @note History: 3/10/89, DSJ, Created.
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* 7/13/89, DSJ, Changed return to void.
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*/
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void KDStore(KDTREE *Tree, FLOAT32 *Key, void *Data) {
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int Level;
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KDNODE *Node;
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KDNODE **PtrToNode;
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@ -245,7 +242,6 @@ void KDStore(KDTREE *Tree, FLOAT32 *Key, void *Data) {
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} /* KDStore */
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/*---------------------------------------------------------------------------*/
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/**
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* This routine deletes a node from Tree. The node to be
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* deleted is specified by the Key for the node and the Data
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@ -303,39 +299,36 @@ KDDelete (KDTREE * Tree, FLOAT32 Key[], void *Data) {
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} /* KDDelete */
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/*---------------------------------------------------------------------------*/
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/**
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* This routine searches the K-D tree specified by Tree and
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* finds the QuerySize nearest neighbors of Query. All neighbors
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* must be within MaxDistance of Query. The data contents of
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* the nearest neighbors
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* are placed in NBuffer and their distances from Query are
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* placed in DBuffer.
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* @param Tree ptr to K-D tree to be searched
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* @param Query ptr to query key (point in D-space)
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* @param QuerySize number of nearest neighbors to be found
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* @param MaxDistance all neighbors must be within this distance
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* @param NBuffer ptr to QuerySize buffer to hold nearest neighbors
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* @param DBuffer ptr to QuerySize buffer to hold distances
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* from nearest neighbor to query point
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* @return Number of nearest neighbors actually found
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* @note Exceptions: none
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* @note History:
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* - 3/10/89, DSJ, Created.
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* - 7/13/89, DSJ, Return contents of node instead of node itself.
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*/
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void KDNearestNeighborSearch(
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KDTREE *Tree, FLOAT32 Query[], int QuerySize, FLOAT32 MaxDistance,
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int *NumberOfResults, void **NBuffer, FLOAT32 DBuffer[]) {
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/*
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** Parameters:
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** Tree ptr to K-D tree to be searched
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** Query ptr to query key (point in D-space)
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** QuerySize number of nearest neighbors to be found
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** MaxDistance all neighbors must be within this distance
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** NBuffer ptr to QuerySize buffer to hold nearest neighbors
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** DBuffer ptr to QuerySize buffer to hold distances
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** from nearest neighbor to query point
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** Operation:
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** This routine searches the K-D tree specified by Tree and
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** finds the QuerySize nearest neighbors of Query. All neighbors
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** must be within MaxDistance of Query. The data contents of
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** the nearest neighbors
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** are placed in NBuffer and their distances from Query are
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** placed in DBuffer.
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** Return: Number of nearest neighbors actually found
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** Exceptions: none
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** History:
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** 3/10/89, DSJ, Created.
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** 7/13/89, DSJ, Return contents of node instead of node itself.
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*/
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KDTreeSearch search(Tree, Query, QuerySize);
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search.Search(NumberOfResults, DBuffer, NBuffer);
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}
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/*---------------------------------------------------------------------------*/
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// Walk a given Tree with action.
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/** Walk a given Tree with action. */
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void KDWalk(KDTREE *Tree, void_proc action, void *context) {
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if (Tree->Root.Left != NULL)
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Walk(Tree, action, context, Tree->Root.Left, NextLevel(Tree, -1));
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@ -343,22 +336,19 @@ void KDWalk(KDTREE *Tree, void_proc action, void *context) {
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/*---------------------------------------------------------------------------*/
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void FreeKDTree(KDTREE *Tree) {
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/*
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** Parameters:
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** Tree tree data structure to be released
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** Operation:
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** This routine frees all memory which is allocated to the
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** specified KD-tree. This includes the data structure for
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** the kd-tree itself plus the data structures for each node
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** in the tree. It does not include the Key and Data items
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** which are pointed to by the nodes. This memory is left
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** untouched.
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** Return: none
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** Exceptions: none
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** History:
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** 5/26/89, DSJ, Created.
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/**
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* This routine frees all memory which is allocated to the
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* specified KD-tree. This includes the data structure for
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* the kd-tree itself plus the data structures for each node
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* in the tree. It does not include the Key and Data items
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* which are pointed to by the nodes. This memory is left
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* untouched.
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* @param Tree tree data structure to be released
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* @return none
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* @note Exceptions: none
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* @note History: 5/26/89, DSJ, Created.
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*/
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void FreeKDTree(KDTREE *Tree) {
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FreeSubTree(Tree->Root.Left);
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memfree(Tree);
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} /* FreeKDTree */
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@ -368,25 +358,20 @@ void FreeKDTree(KDTREE *Tree) {
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Private Code
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-----------------------------------------------------------------------------*/
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/*---------------------------------------------------------------------------*/
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KDNODE *MakeKDNode(KDTREE *tree, FLOAT32 Key[], void *Data, int Index) {
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/*
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** Parameters:
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** tree The tree to create the node for
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** Key Access key for new node in KD tree
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** Data ptr to data to be stored in new node
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** Index index of Key to branch on
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** Operation:
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** This routine allocates memory for a new K-D tree node
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** and places the specified Key and Data into it. The
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** left and right subtree pointers for the node are
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** initialized to empty subtrees.
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** Return:
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** pointer to new K-D tree node
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** Exceptions:
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** None
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** History:
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** 3/11/89, DSJ, Created.
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/**
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* This routine allocates memory for a new K-D tree node
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* and places the specified Key and Data into it. The
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* left and right subtree pointers for the node are
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* initialized to empty subtrees.
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* @param tree The tree to create the node for
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* @param Key Access key for new node in KD tree
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* @param Data ptr to data to be stored in new node
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* @param Index index of Key to branch on
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* @return pointer to new K-D tree node
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* @note Exceptions: None
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* @note History: 3/11/89, DSJ, Created.
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*/
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KDNODE *MakeKDNode(KDTREE *tree, FLOAT32 Key[], void *Data, int Index) {
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KDNODE *NewNode;
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NewNode = (KDNODE *) Emalloc (sizeof (KDNODE));
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@ -410,10 +395,11 @@ void FreeKDNode(KDNODE *Node) {
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/*---------------------------------------------------------------------------*/
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// Recursively accumulate the k_closest points to query_point_ into results_.
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// Parameters:
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// Level level in tree of sub-tree to be searched
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// SubTree sub-tree to be searched
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/**
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* Recursively accumulate the k_closest points to query_point_ into results_.
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* @param Level level in tree of sub-tree to be searched
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* @param SubTree sub-tree to be searched
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*/
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void KDTreeSearch::SearchRec(int level, KDNODE *sub_tree) {
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if (level >= tree_->KeySize)
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level = 0;
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@ -456,12 +442,13 @@ void KDTreeSearch::SearchRec(int level, KDNODE *sub_tree) {
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/*---------------------------------------------------------------------------*/
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// Returns the Euclidean distance squared between p1 and p2 for all essential
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// dimensions.
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// Parameters:
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// k keys are in k-space
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// dim dimension descriptions (essential, circular, etc)
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// p1,p2 two different points in K-D space
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/**
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*Returns the Euclidean distance squared between p1 and p2 for all essential
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* dimensions.
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* @param k keys are in k-space
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* @param dim dimension descriptions (essential, circular, etc)
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* @param p1,p2 two different points in K-D space
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*/
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FLOAT32 DistanceSquared(int k, PARAM_DESC *dim, FLOAT32 p1[], FLOAT32 p2[]) {
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FLOAT32 total_distance = 0;
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@ -488,10 +475,10 @@ FLOAT32 ComputeDistance(int k, PARAM_DESC *dim, FLOAT32 p1[], FLOAT32 p2[]) {
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}
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/*---------------------------------------------------------------------------*/
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// Return whether the query region (the smallest known circle about
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// query_point_ containing results->k_ points) intersects the box specified
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// between lower and upper. For circular dimensions, we also check the point
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// one wrap distance away from the query.
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/// Return whether the query region (the smallest known circle about
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/// query_point_ containing results->k_ points) intersects the box specified
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/// between lower and upper. For circular dimensions, we also check the point
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/// one wrap distance away from the query.
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bool KDTreeSearch::BoxIntersectsSearch(FLOAT32 *lower, FLOAT32 *upper) {
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FLOAT32 *query = query_point_;
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FLOAT64 total_distance = 0.0;
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@ -530,20 +517,21 @@ bool KDTreeSearch::BoxIntersectsSearch(FLOAT32 *lower, FLOAT32 *upper) {
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/*---------------------------------------------------------------------------*/
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// Walk a tree, calling action once on each node.
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//
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// Parameters:
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// tree root of the tree being walked.
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// action action to be performed at every node
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// context action's context
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// sub_tree ptr to root of subtree to be walked
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// level current level in the tree for this node
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// Operation:
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// This routine walks thru the specified sub_tree and invokes action
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// action at each node as follows:
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// action(context, data, level)
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// data the data contents of the node being visited,
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// level is the level of the node in the tree with the root being level 0.
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/**
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* Walk a tree, calling action once on each node.
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*
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* Operation:
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* This routine walks thru the specified sub_tree and invokes action
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* action at each node as follows:
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* action(context, data, level)
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* data the data contents of the node being visited,
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* level is the level of the node in the tree with the root being level 0.
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* @param tree root of the tree being walked.
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* @param action action to be performed at every node
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* @param context action's context
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* @param sub_tree ptr to root of subtree to be walked
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* @param level current level in the tree for this node
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*/
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void Walk(KDTREE *tree, void_proc action, void *context,
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KDNODE *sub_tree, inT32 level) {
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(*action)(context, sub_tree->Data, level);
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@ -554,7 +542,7 @@ void Walk(KDTREE *tree, void_proc action, void *context,
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}
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// Given a subtree nodes, insert all of its elements into tree.
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/** Given a subtree nodes, insert all of its elements into tree. */
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void InsertNodes(KDTREE *tree, KDNODE *nodes) {
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if (nodes == NULL)
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return;
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@ -564,11 +552,11 @@ void InsertNodes(KDTREE *tree, KDNODE *nodes) {
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InsertNodes(tree, nodes->Right);
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}
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// Free all of the nodes of a sub tree.
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/** Free all of the nodes of a sub tree. */
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void FreeSubTree(KDNODE *sub_tree) {
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if (sub_tree != NULL) {
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FreeSubTree(sub_tree->Left);
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FreeSubTree(sub_tree->Right);
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memfree(sub_tree);
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}
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} /* FreeSubTree */
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}
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