63 lines
2.7 KiB
Text
63 lines
2.7 KiB
Text
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//----------------------------------------------------------------------
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// File: bd_pr_search.cpp
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// Programmer: David Mount
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// Description: Priority search for bd-trees
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// Last modified: 01/04/05 (Version 1.0)
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//----------------------------------------------------------------------
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// Copyright (c) 1997-2005 University of Maryland and Sunil Arya and
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// David Mount. All Rights Reserved.
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//
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// This software and related documentation is part of the Approximate
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// Nearest Neighbor Library (ANN). This software is provided under
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// the provisions of the Lesser GNU Public License (LGPL). See the
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// file ../ReadMe.txt for further information.
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//
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// The University of Maryland (U.M.) and the authors make no
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// representations about the suitability or fitness of this software for
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// any purpose. It is provided "as is" without express or implied
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// warranty.
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//----------------------------------------------------------------------
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//History:
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// Revision 0.1 03/04/98
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// Initial release
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//----------------------------------------------------------------------
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#include "bd_tree.h" // bd-tree declarations
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#include "kd_pr_search.h" // kd priority search declarations
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//----------------------------------------------------------------------
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// Approximate priority searching for bd-trees.
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// See the file kd_pr_search.cc for general information on the
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// approximate nearest neighbor priority search algorithm. Here
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// we include the extensions for shrinking nodes.
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//----------------------------------------------------------------------
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//----------------------------------------------------------------------
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// bd_shrink::ann_search - search a shrinking node
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//----------------------------------------------------------------------
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void ANNbd_shrink::ann_pri_search(ANNdist box_dist)
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{
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ANNdist inner_dist = 0; // distance to inner box
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for (int i = 0; i < n_bnds; i++) { // is query point in the box?
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if (bnds[i].out(ANNprQ)) { // outside this bounding side?
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// add to inner distance
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inner_dist = (ANNdist) ANN_SUM(inner_dist, bnds[i].dist(ANNprQ));
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}
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}
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if (inner_dist <= box_dist) { // if inner box is closer
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if (child[ANN_OUT] != KD_TRIVIAL) // enqueue outer if not trivial
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ANNprBoxPQ->insert(box_dist,child[ANN_OUT]);
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// continue with inner child
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child[ANN_IN]->ann_pri_search(inner_dist);
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}
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else { // if outer box is closer
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if (child[ANN_IN] != KD_TRIVIAL) // enqueue inner if not trivial
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ANNprBoxPQ->insert(inner_dist,child[ANN_IN]);
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// continue with outer child
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child[ANN_OUT]->ann_pri_search(box_dist);
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}
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ANN_FLOP(3*n_bnds) // increment floating ops
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ANN_SHR(1) // one more shrinking node
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}
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