kd_pr_search.h

c++实现的KNN库:建立高维度的K-d tree,实现K邻域搜索

//----------------------------------------------------------------------
// File:			kd_pr_search.h
// Programmer:		Sunil Arya and David Mount
// Description:		Priority kd-tree search
// Last modified:	01/04/05 (Version 1.0)
//----------------------------------------------------------------------
// 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 0.1  03/04/98
//		Initial release
//----------------------------------------------------------------------

#ifndef ANN_kd_pr_search_H
#define ANN_kd_pr_search_H

#include "kd_tree.h"					// kd-tree declarations
#include "kd_util.h"					// kd-tree utilities
#include "pr_queue.h"					// priority queue declarations
#include "pr_queue_k.h"					// k-element priority queue

#include <ANN/ANNperf.h>				// performance evaluation

//----------------------------------------------------------------------
//	Global variables
//		Active for the life of each call to Appx_Near_Neigh() or
//		Appx_k_Near_Neigh().
//----------------------------------------------------------------------

extern double			ANNprEps;		// the error bound
extern int				ANNprDim;		// dimension of space
extern ANNpoint			ANNprQ;			// query point
extern double			ANNprMaxErr;	// max tolerable squared error
extern ANNpointArray	ANNprPts;		// the points
extern ANNpr_queue		*ANNprBoxPQ;	// priority queue for boxes
extern ANNmin_k			*ANNprPointMK;	// set of k closest points

#endif