199 lines
6.6 KiB
C++
199 lines
6.6 KiB
C++
|
//----------------------------------------------------------------------
|
||
|
// File: ann_sample.cpp
|
||
|
// Programmer: Sunil Arya and David Mount
|
||
|
// Last modified: 03/04/98 (Release 0.1)
|
||
|
// Description: Sample program for ANN
|
||
|
//----------------------------------------------------------------------
|
||
|
// 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.
|
||
|
//----------------------------------------------------------------------
|
||
|
|
||
|
#include <cstdlib> // C standard library
|
||
|
#include <cstdio> // C I/O (for sscanf)
|
||
|
#include <cstring> // string manipulation
|
||
|
#include <fstream> // file I/O
|
||
|
#include <ANN/ANN.h> // ANN declarations
|
||
|
|
||
|
using namespace std; // make std:: accessible
|
||
|
|
||
|
//----------------------------------------------------------------------
|
||
|
// ann_sample
|
||
|
//
|
||
|
// This is a simple sample program for the ANN library. After compiling,
|
||
|
// it can be run as follows.
|
||
|
//
|
||
|
// ann_sample [-d dim] [-max mpts] [-nn k] [-e eps] [-df data] [-qf query]
|
||
|
//
|
||
|
// where
|
||
|
// dim is the dimension of the space (default = 2)
|
||
|
// mpts maximum number of data points (default = 1000)
|
||
|
// k number of nearest neighbors per query (default 1)
|
||
|
// eps is the error bound (default = 0.0)
|
||
|
// data file containing data points
|
||
|
// query file containing query points
|
||
|
//
|
||
|
// Results are sent to the standard output.
|
||
|
//----------------------------------------------------------------------
|
||
|
|
||
|
//----------------------------------------------------------------------
|
||
|
// Parameters that are set in getArgs()
|
||
|
//----------------------------------------------------------------------
|
||
|
void getArgs(int argc, char **argv); // get command-line arguments
|
||
|
|
||
|
int k = 1; // number of nearest neighbors
|
||
|
int dim = 2; // dimension
|
||
|
double eps = 0; // error bound
|
||
|
int maxPts = 1000; // maximum number of data points
|
||
|
|
||
|
istream* dataIn = NULL; // input for data points
|
||
|
istream* queryIn = NULL; // input for query points
|
||
|
|
||
|
bool readPt(istream &in, ANNpoint p) // read point (false on EOF)
|
||
|
{
|
||
|
for (int i = 0; i < dim; i++) {
|
||
|
if(!(in >> p[i])) return false;
|
||
|
}
|
||
|
return true;
|
||
|
}
|
||
|
|
||
|
void printPt(ostream &out, ANNpoint p) // print point
|
||
|
{
|
||
|
out << "(" << p[0];
|
||
|
for (int i = 1; i < dim; i++) {
|
||
|
out << ", " << p[i];
|
||
|
}
|
||
|
out << ")\n";
|
||
|
}
|
||
|
|
||
|
int main(int argc, char **argv)
|
||
|
{
|
||
|
int nPts; // actual number of data points
|
||
|
ANNpointArray dataPts; // data points
|
||
|
ANNpoint queryPt; // query point
|
||
|
ANNidxArray nnIdx; // near neighbor indices
|
||
|
ANNdistArray dists; // near neighbor distances
|
||
|
ANNkd_tree* kdTree; // search structure
|
||
|
|
||
|
getArgs(argc, argv); // read command-line arguments
|
||
|
|
||
|
queryPt = annAllocPt(dim); // allocate query point
|
||
|
dataPts = annAllocPts(maxPts, dim); // allocate data points
|
||
|
nnIdx = new ANNidx[k]; // allocate near neigh indices
|
||
|
dists = new ANNdist[k]; // allocate near neighbor dists
|
||
|
|
||
|
nPts = 0; // read data points
|
||
|
|
||
|
cout << "Data Points:\n";
|
||
|
while (nPts < maxPts && readPt(*dataIn, dataPts[nPts])) {
|
||
|
printPt(cout, dataPts[nPts]);
|
||
|
nPts++;
|
||
|
}
|
||
|
|
||
|
kdTree = new ANNkd_tree( // build search structure
|
||
|
dataPts, // the data points
|
||
|
nPts, // number of points
|
||
|
dim); // dimension of space
|
||
|
|
||
|
while (readPt(*queryIn, queryPt)) { // read query points
|
||
|
cout << "Query point: "; // echo query point
|
||
|
printPt(cout, queryPt);
|
||
|
|
||
|
kdTree->annkSearch( // search
|
||
|
queryPt, // query point
|
||
|
k, // number of near neighbors
|
||
|
nnIdx, // nearest neighbors (returned)
|
||
|
dists, // distance (returned)
|
||
|
eps); // error bound
|
||
|
|
||
|
cout << "\tNN:\tIndex\tDistance\n";
|
||
|
for (int i = 0; i < k; i++) { // print summary
|
||
|
dists[i] = sqrt(dists[i]); // unsquare distance
|
||
|
cout << "\t" << i << "\t" << nnIdx[i] << "\t" << dists[i] << "\n";
|
||
|
}
|
||
|
}
|
||
|
delete [] nnIdx; // clean things up
|
||
|
delete [] dists;
|
||
|
delete kdTree;
|
||
|
annClose(); // done with ANN
|
||
|
|
||
|
return EXIT_SUCCESS;
|
||
|
}
|
||
|
|
||
|
//----------------------------------------------------------------------
|
||
|
// getArgs - get command line arguments
|
||
|
//----------------------------------------------------------------------
|
||
|
|
||
|
void getArgs(int argc, char **argv)
|
||
|
{
|
||
|
static ifstream dataStream; // data file stream
|
||
|
static ifstream queryStream; // query file stream
|
||
|
|
||
|
if (argc <= 1) { // no arguments
|
||
|
cerr << "Usage:\n\n"
|
||
|
<< " ann_sample [-d dim] [-max m] [-nn k] [-e eps] [-df data]"
|
||
|
" [-qf query]\n\n"
|
||
|
<< " where:\n"
|
||
|
<< " dim dimension of the space (default = 2)\n"
|
||
|
<< " m maximum number of data points (default = 1000)\n"
|
||
|
<< " k number of nearest neighbors per query (default 1)\n"
|
||
|
<< " eps the error bound (default = 0.0)\n"
|
||
|
<< " data name of file containing data points\n"
|
||
|
<< " query name of file containing query points\n\n"
|
||
|
<< " Results are sent to the standard output.\n"
|
||
|
<< "\n"
|
||
|
<< " To run this demo use:\n"
|
||
|
<< " ann_sample -df data.pts -qf query.pts\n";
|
||
|
exit(0);
|
||
|
}
|
||
|
int i = 1;
|
||
|
while (i < argc) { // read arguments
|
||
|
if (!strcmp(argv[i], "-d")) { // -d option
|
||
|
dim = atoi(argv[++i]); // get dimension to dump
|
||
|
}
|
||
|
else if (!strcmp(argv[i], "-max")) { // -max option
|
||
|
maxPts = atoi(argv[++i]); // get max number of points
|
||
|
}
|
||
|
else if (!strcmp(argv[i], "-nn")) { // -nn option
|
||
|
k = atoi(argv[++i]); // get number of near neighbors
|
||
|
}
|
||
|
else if (!strcmp(argv[i], "-e")) { // -e option
|
||
|
sscanf(argv[++i], "%lf", &eps); // get error bound
|
||
|
}
|
||
|
else if (!strcmp(argv[i], "-df")) { // -df option
|
||
|
dataStream.open(argv[++i], ios::in);// open data file
|
||
|
if (!dataStream) {
|
||
|
cerr << "Cannot open data file\n";
|
||
|
exit(1);
|
||
|
}
|
||
|
dataIn = &dataStream; // make this the data stream
|
||
|
}
|
||
|
else if (!strcmp(argv[i], "-qf")) { // -qf option
|
||
|
queryStream.open(argv[++i], ios::in);// open query file
|
||
|
if (!queryStream) {
|
||
|
cerr << "Cannot open query file\n";
|
||
|
exit(1);
|
||
|
}
|
||
|
queryIn = &queryStream; // make this query stream
|
||
|
}
|
||
|
else { // illegal syntax
|
||
|
cerr << "Unrecognized option.\n";
|
||
|
exit(1);
|
||
|
}
|
||
|
i++;
|
||
|
}
|
||
|
if (dataIn == NULL || queryIn == NULL) {
|
||
|
cerr << "-df and -qf options must be specified\n";
|
||
|
exit(1);
|
||
|
}
|
||
|
}
|