3dpcp/3rdparty/ann_1.1.1_modified/include/ANN/ANNperf.h

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2012-09-16 12:33:11 +00:00
//----------------------------------------------------------------------
// File: ANNperf.h
// Programmer: Sunil Arya and David Mount
// Last modified: 03/04/98 (Release 0.1)
// Description: Include file for ANN performance stats
//
// Some of the code for statistics gathering has been adapted
// from the SmplStat.h package in the g++ library.
//----------------------------------------------------------------------
// 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
// Revision 1.0 04/01/05
// Added ANN_ prefix to avoid name conflicts.
//----------------------------------------------------------------------
#ifndef ANNperf_H
#define ANNperf_H
#undef min
#undef max
//----------------------------------------------------------------------
// basic includes
//----------------------------------------------------------------------
#include <ANN/ANN.h> // basic ANN includes
//----------------------------------------------------------------------
// kd-tree stats object
// This object is used for collecting information about a kd-tree
// or bd-tree.
//----------------------------------------------------------------------
class ANNkdStats { // stats on kd-tree
public:
int dim; // dimension of space
int n_pts; // no. of points
int bkt_size; // bucket size
int n_lf; // no. of leaves (including trivial)
int n_tl; // no. of trivial leaves (no points)
int n_spl; // no. of splitting nodes
int n_shr; // no. of shrinking nodes (for bd-trees)
int depth; // depth of tree
float sum_ar; // sum of leaf aspect ratios
float avg_ar; // average leaf aspect ratio
//
// reset stats
void reset(int d=0, int n=0, int bs=0)
{
dim = d; n_pts = n; bkt_size = bs;
n_lf = n_tl = n_spl = n_shr = depth = 0;
sum_ar = avg_ar = 0.0;
}
ANNkdStats() // basic constructor
{ reset(); }
void merge(const ANNkdStats &st); // merge stats from child
};
//----------------------------------------------------------------------
// ANNsampStat
// A sample stat collects numeric (double) samples and returns some
// simple statistics. Its main functions are:
//
// reset() Reset to no samples.
// += x Include sample x.
// samples() Return number of samples.
// mean() Return mean of samples.
// stdDev() Return standard deviation
// min() Return minimum of samples.
// max() Return maximum of samples.
//----------------------------------------------------------------------
class DLL_API ANNsampStat {
int n; // number of samples
double sum; // sum
double sum2; // sum of squares
double minVal, maxVal; // min and max
public :
void reset() // reset everything
{
n = 0;
sum = sum2 = 0;
minVal = ANN_DBL_MAX;
maxVal = -ANN_DBL_MAX;
}
ANNsampStat() { reset(); } // constructor
void operator+=(double x) // add sample
{
n++; sum += x; sum2 += x*x;
if (x < minVal) minVal = x;
if (x > maxVal) maxVal = x;
}
int samples() { return n; } // number of samples
double mean() { return sum/n; } // mean
// standard deviation
double stdDev() { return sqrt((sum2 - (sum*sum)/n)/(n-1));}
double min() { return minVal; } // minimum
double max() { return maxVal; } // maximum
};
//----------------------------------------------------------------------
// Operation count updates
//----------------------------------------------------------------------
#ifdef ANN_PERF
#define ANN_FLOP(n) {ann_Nfloat_ops += (n);}
#define ANN_LEAF(n) {ann_Nvisit_lfs += (n);}
#define ANN_SPL(n) {ann_Nvisit_spl += (n);}
#define ANN_SHR(n) {ann_Nvisit_shr += (n);}
#define ANN_PTS(n) {ann_Nvisit_pts += (n);}
#define ANN_COORD(n) {ann_Ncoord_hts += (n);}
#else
#define ANN_FLOP(n)
#define ANN_LEAF(n)
#define ANN_SPL(n)
#define ANN_SHR(n)
#define ANN_PTS(n)
#define ANN_COORD(n)
#endif
//----------------------------------------------------------------------
// Performance statistics
// The following data and routines are used for computing performance
// statistics for nearest neighbor searching. Because these routines
// can slow the code down, they can be activated and deactiviated by
// defining the ANN_PERF variable, by compiling with the option:
// -DANN_PERF
//----------------------------------------------------------------------
//----------------------------------------------------------------------
// Global counters for performance measurement
//
// visit_lfs The number of leaf nodes visited in the
// tree.
//
// visit_spl The number of splitting nodes visited in the
// tree.
//
// visit_shr The number of shrinking nodes visited in the
// tree.
//
// visit_pts The number of points visited in all the
// leaf nodes visited. Equivalently, this
// is the number of points for which distance
// calculations are performed.
//
// coord_hts The number of times a coordinate of a
// data point is accessed. This is generally
// less than visit_pts*d if partial distance
// calculation is used. This count is low
// in the sense that if a coordinate is hit
// many times in the same routine we may
// count it only once.
//
// float_ops The number of floating point operations.
// This includes all operations in the heap
// as well as distance calculations to boxes.
//
// average_err The average error of each query (the
// error of the reported point to the true
// nearest neighbor). For k nearest neighbors
// the error is computed k times.
//
// rank_err The rank error of each query (the difference
// in the rank of the reported point and its
// true rank).
//
// data_pts The number of data points. This is not
// a counter, but used in stats computation.
//----------------------------------------------------------------------
extern int ann_Ndata_pts; // number of data points
extern int ann_Nvisit_lfs; // number of leaf nodes visited
extern int ann_Nvisit_spl; // number of splitting nodes visited
extern int ann_Nvisit_shr; // number of shrinking nodes visited
extern int ann_Nvisit_pts; // visited points for one query
extern int ann_Ncoord_hts; // coordinate hits for one query
extern int ann_Nfloat_ops; // floating ops for one query
extern ANNsampStat ann_visit_lfs; // stats on leaf nodes visits
extern ANNsampStat ann_visit_spl; // stats on splitting nodes visits
extern ANNsampStat ann_visit_shr; // stats on shrinking nodes visits
extern ANNsampStat ann_visit_nds; // stats on total nodes visits
extern ANNsampStat ann_visit_pts; // stats on points visited
extern ANNsampStat ann_coord_hts; // stats on coordinate hits
extern ANNsampStat ann_float_ops; // stats on floating ops
//----------------------------------------------------------------------
// The following need to be part of the public interface, because
// they are accessed outside the DLL in ann_test.cpp.
//----------------------------------------------------------------------
DLL_API extern ANNsampStat ann_average_err; // average error
DLL_API extern ANNsampStat ann_rank_err; // rank error
//----------------------------------------------------------------------
// Declaration of externally accessible routines for statistics
//----------------------------------------------------------------------
DLL_API void annResetStats(int data_size); // reset stats for a set of queries
DLL_API void annResetCounts(); // reset counts for one queries
DLL_API void annUpdateStats(); // update stats with current counts
DLL_API void annPrintStats(ANNbool validate); // print statistics for a run
#endif