From 0cc35ad04f9c2997014d7cf62a12f697e79fb534 Mon Sep 17 00:00:00 2001 From: Arnur Nigmetov Date: Sat, 20 Jan 2018 19:11:29 +0100 Subject: Major rewrite, templatized version --- .../bottleneck/src/ann/kd_fix_rad_search.cpp | 185 --------------------- 1 file changed, 185 deletions(-) delete mode 100644 geom_bottleneck/bottleneck/src/ann/kd_fix_rad_search.cpp (limited to 'geom_bottleneck/bottleneck/src/ann/kd_fix_rad_search.cpp') diff --git a/geom_bottleneck/bottleneck/src/ann/kd_fix_rad_search.cpp b/geom_bottleneck/bottleneck/src/ann/kd_fix_rad_search.cpp deleted file mode 100644 index 1a4749e..0000000 --- a/geom_bottleneck/bottleneck/src/ann/kd_fix_rad_search.cpp +++ /dev/null @@ -1,185 +0,0 @@ -//---------------------------------------------------------------------- -// 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 - -namespace geom_bt { -//---------------------------------------------------------------------- -// 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 -} -} -- cgit v1.2.3