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kd_fix_rad_search.cpp

//----------------------------------------------------------------------
// File:                kd_fix_rad_search.cpp
// Programmer:          Sunil Arya and David Mount
// Description:         Standard kd-tree fixed-radius kNN search
// Last modified: 05/03/05 (Version 1.1)
//----------------------------------------------------------------------
// Copyright (c) 1997-2005 University of Maryland and Sunil Arya and
// David Mount.  All Rights Reserved.
// 
// This software and related documentation is part of the Approximate
// Nearest Neighbor Library (ANN).  This software is provided under
// the provisions of the Lesser GNU Public License (LGPL).  See the
// file ../ReadMe.txt for further information.
// 
// The University of Maryland (U.M.) and the authors make no
// representations about the suitability or fitness of this software for
// any purpose.  It is provided "as is" without express or implied
// warranty.
//----------------------------------------------------------------------
// History:
//    Revision 1.1  05/03/05
//          Initial release
//----------------------------------------------------------------------

#include "kd_fix_rad_search.h"                  // kd fixed-radius search decls

//----------------------------------------------------------------------
//    Approximate fixed-radius k nearest neighbor search
//          The squared radius is provided, and this procedure finds the
//          k nearest neighbors within the radius, and returns the total
//          number of points lying within the radius.
//
//          The method used for searching the kd-tree is a variation of the
//          nearest neighbor search used in kd_search.cpp, except that the
//          radius of the search ball is known.  We refer the reader to that
//          file for the explanation of the recursive search procedure.
//----------------------------------------------------------------------

//----------------------------------------------------------------------
//          To keep argument lists short, a number of global variables
//          are maintained which are common to all the recursive calls.
//          These are given below.
//----------------------------------------------------------------------

int                     ANNkdFRDim;                   // dimension of space
ANNpoint          ANNkdFRQ;                     // query point
ANNdist                 ANNkdFRSqRad;                 // squared radius search bound
double                  ANNkdFRMaxErr;                // max tolerable squared error
ANNpointArray     ANNkdFRPts;                   // the points
ANNmin_k*         ANNkdFRPointMK;               // set of k closest points
int                     ANNkdFRPtsVisited;            // total points visited
int                     ANNkdFRPtsInRange;            // number of points in the range

//----------------------------------------------------------------------
//    annkFRSearch - fixed radius search for k nearest neighbors
//----------------------------------------------------------------------

int ANNkd_tree::annkFRSearch(
      ANNpoint                q,                      // the query point
      ANNdist                       sqRad,                  // squared radius search bound
      int                           k,                      // number of near neighbors to return
      ANNidxArray             nn_idx,                 // nearest neighbor indices (returned)
      ANNdistArray            dd,                     // the approximate nearest neighbor
      double                        eps)              // the error bound
{
      ANNkdFRDim = dim;                         // copy arguments to static equivs
      ANNkdFRQ = q;
      ANNkdFRSqRad = sqRad;
      ANNkdFRPts = pts;
      ANNkdFRPtsVisited = 0;                    // initialize count of points visited
      ANNkdFRPtsInRange = 0;                    // ...and points in the range

      ANNkdFRMaxErr = ANN_POW(1.0 + eps);
      ANN_FLOP(2)                                     // increment floating op count

      ANNkdFRPointMK = new ANNmin_k(k);   // create set for closest k points
                                                            // search starting at the root
      root->ann_FR_search(annBoxDistance(q, bnd_box_lo, bnd_box_hi, dim));

      for (int i = 0; i < k; i++) {       // extract the k-th closest points
            if (dd != NULL)
                  dd[i] = ANNkdFRPointMK->ith_smallest_key(i);
            if (nn_idx != NULL)
                  nn_idx[i] = ANNkdFRPointMK->ith_smallest_info(i);
      }

      delete ANNkdFRPointMK;                    // deallocate closest point set
      return ANNkdFRPtsInRange;                 // return final point count
}

//----------------------------------------------------------------------
//    kd_split::ann_FR_search - search a splitting node
//          Note: This routine is similar in structure to the standard kNN
//          search.  It visits the subtree that is closer to the query point
//          first.  For fixed-radius search, there is no benefit in visiting
//          one subtree before the other, but we maintain the same basic
//          code structure for the sake of uniformity.
//----------------------------------------------------------------------

void ANNkd_split::ann_FR_search(ANNdist box_dist)
{
                                                            // check dist calc term condition
      if (ANNmaxPtsVisited != 0 && ANNkdFRPtsVisited > ANNmaxPtsVisited) return;

                                                            // distance to cutting plane
      ANNcoord cut_diff = ANNkdFRQ[cut_dim] - cut_val;

      if (cut_diff < 0) {                             // left of cutting plane
            child[ANN_LO]->ann_FR_search(box_dist);// visit closer child first

            ANNcoord box_diff = cd_bnds[ANN_LO] - ANNkdFRQ[cut_dim];
            if (box_diff < 0)                   // within bounds - ignore
                  box_diff = 0;
                                                            // distance to further box
            box_dist = (ANNdist) ANN_SUM(box_dist,
                        ANN_DIFF(ANN_POW(box_diff), ANN_POW(cut_diff)));

                                                            // visit further child if in range
            if (box_dist * ANNkdFRMaxErr <= ANNkdFRSqRad)
                  child[ANN_HI]->ann_FR_search(box_dist);

      }
      else {                                                // right of cutting plane
            child[ANN_HI]->ann_FR_search(box_dist);// visit closer child first

            ANNcoord box_diff = ANNkdFRQ[cut_dim] - cd_bnds[ANN_HI];
            if (box_diff < 0)                   // within bounds - ignore
                  box_diff = 0;
                                                            // distance to further box
            box_dist = (ANNdist) ANN_SUM(box_dist,
                        ANN_DIFF(ANN_POW(box_diff), ANN_POW(cut_diff)));

                                                            // visit further child if close enough
            if (box_dist * ANNkdFRMaxErr <= ANNkdFRSqRad)
                  child[ANN_LO]->ann_FR_search(box_dist);

      }
      ANN_FLOP(13)                                    // increment floating ops
      ANN_SPL(1)                                      // one more splitting node visited
}

//----------------------------------------------------------------------
//    kd_leaf::ann_FR_search - search points in a leaf node
//          Note: The unreadability of this code is the result of
//          some fine tuning to replace indexing by pointer operations.
//----------------------------------------------------------------------

void ANNkd_leaf::ann_FR_search(ANNdist box_dist)
{
      register ANNdist dist;                    // distance to data point
      register ANNcoord* pp;                    // data coordinate pointer
      register ANNcoord* qq;                    // query coordinate pointer
      register ANNcoord t;
      register int d;

      for (int i = 0; i < n_pts; i++) {   // check points in bucket

            pp = ANNkdFRPts[bkt[i]];            // first coord of next data point
            qq = ANNkdFRQ;                            // first coord of query point
            dist = 0;

            for(d = 0; d < ANNkdFRDim; d++) {
                  ANN_COORD(1)                        // one more coordinate hit
                  ANN_FLOP(5)                         // increment floating ops

                  t = *(qq++) - *(pp++);        // compute length and adv coordinate
                                                            // exceeds dist to k-th smallest?
                  if( (dist = ANN_SUM(dist, ANN_POW(t))) > ANNkdFRSqRad) {
                        break;
                  }
            }

            if (d >= ANNkdFRDim &&                          // among the k best?
               (ANN_ALLOW_SELF_MATCH || dist!=0)) { // and no self-match problem
                                                                        // add it to the list
                  ANNkdFRPointMK->insert(dist, bkt[i]);
                  ANNkdFRPtsInRange++;                      // increment point count
            }
      }
      ANN_LEAF(1)                                     // one more leaf node visited
      ANN_PTS(n_pts)                                  // increment points visited
      ANNkdFRPtsVisited += n_pts;               // increment number of points visited
}

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