knnshow.cpp
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1 /*
2 
3 Copyright (c) 2010--2011, Stephane Magnenat, ASL, ETHZ, Switzerland
4 You can contact the author at <stephane at magnenat dot net>
5 
6 All rights reserved.
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9 modification, are permitted provided that the following conditions are met:
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17  derived from this software without specific prior written permission.
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19 THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
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21 WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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28 SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
29 
30 */
31 
32 #include "nabo/nabo.h"
33 #include <iostream>
34 #include <fstream>
35 #include <stdexcept>
36 
37 using namespace std;
38 using namespace Nabo;
39 
40 template<typename T>
41 typename NearestNeighbourSearch<T>::Matrix load(const char *fileName)
42 {
43  typedef typename NearestNeighbourSearch<T>::Matrix Matrix;
44 
45  ifstream ifs(fileName);
46  if (!ifs.good())
47  throw runtime_error(string("Cannot open file ") + fileName);
48 
49  vector<T> data;
50  int dim(0);
51  bool firstLine(true);
52 
53  while (!ifs.eof())
54  {
55  char line[1024];
56  ifs.getline(line, sizeof(line));
57  line[sizeof(line)-1] = 0;
58 
59  char *token = strtok(line, " \t,;");
60  while (token)
61  {
62  if (firstLine)
63  ++dim;
64  data.push_back(atof(token));
65  //cout << atof(token) << " ";
66  token = strtok(NULL, " \t,;"); // FIXME: non reentrant, use strtok_r
67  }
68  firstLine = false;
69  }
70 
71  return Matrix::Map(&data[0], dim, data.size() / dim);
72 }
73 
74 template<typename T>
75 void dumpCoordinateForSVG(const typename NearestNeighbourSearch<T>::Vector coord, const float zoom = 1, const float ptSize = 1, const char* style = "stroke=\"black\" fill=\"red\"")
76 {
77  if (coord.size() == 2)
78  cout
79  << "<circle cx=\"" << zoom*coord(0)
80  << "\" cy=\"" << zoom*coord(1)
81  << "\" r=\"" << ptSize
82  << "\" stroke-width=\"" << 0.2 * ptSize
83  << "\" " << style << "/>" << endl;
84  else
85  assert(false);
86 }
87 
88 int main(int argc, char* argv[])
89 {
95  typedef Nabo::KDTree<float> KDTF;
96 
97  if (argc != 2)
98  {
99  cerr << "Usage " << argv[0] << " DATA" << endl;
100  return 1;
101  }
102 
103  Matrix d(load<float>(argv[1]));
104  BFSF bfs(d);
105  KDTF kdt(d);
106  const Index K(10);
107 
108  // uncomment to compare KDTree with brute force search
109  if (K >= d.size())
110  return 2;
111  const int itCount(100);
112  for (int i = 0; i < itCount; ++i)
113  {
114  //Vector q(bfs.minBound.size());
115  //for (int i = 0; i < q.size(); ++i)
116  // q(i) = bfs.minBound(i) + float(rand()) * (bfs.maxBound(i) - bfs.minBound(i)) / float(RAND_MAX);
117  Vector q(d.col(rand() % d.cols()));
118  q.cwise() += 0.01;
119  //cerr << "bfs:\n";
120  Indexes indexes_bf(bfs.knn(q, K, false));
121  //cerr << "kdt:\n";
122  Indexes indexes_kdtree(kdt.knn(q, K, false));
123  //cout << indexes_bf.size() << " " << indexes_kdtree.size() << " " << K << endl;
124  if (ndexes_bf.size() != indexes_kdtree.size())
125  return 2;
126  assert(indexes_bf.size() == indexes_kdtree.size());
127  assert(indexes_bf.size() == K);
128  //cerr << "\nquery:\n" << q << "\n\n";
129  for (size_t j = 0; j < K; ++j)
130  {
131  Vector pbf(d.col(indexes_bf[j]));
132  Vector pkdtree(d.col(indexes_kdtree[j]));
133  //cerr << "index " << j << ": " << indexes_bf[j] << ", " << indexes_kdtree[j] << "\n";
134  //cerr << "point " << j << ": " << "\nbf:\n" << pbf << "\nkdtree:\n" << pkdtree << "\n\n";
135  assert(indexes_bf[j] == indexes_kdtree[j]);
136  assert(dist2(pbf, pkdtree) < numeric_limits<float>::epsilon());
137  }
138  }
139  cerr << "stats kdtree: "
140  << kdt.getStatistics().totalVisitCount << " on "
141  << itCount * d.cols() << " ("
142  << double(100 * kdt.getStatistics().totalVisitCount) / double(itCount * d.cols()) << " %"
143  << ")" << endl;
144 
145  /*
146  // uncomment to randomly get a point and find its minimum
147  cout << "<?xml version=\"1.0\" standalone=\"no\"?>" << endl;
148  cout << "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\" \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">" << endl;
149  cout << "<svg width=\"100%\" height=\"100%\" version=\"1.1\" xmlns=\"http://www.w3.org/2000/svg\">" << endl;
150  srand(time(0));
151  for (int i = 0; i < d.cols(); ++i)
152  dumpCoordinateForSVG<float>(d.col(i), 100, 1);
153  Vector q(bfs.minBound.size());
154  for (int i = 0; i < q.size(); ++i)
155  q(i) = bfs.minBound(i) + float(rand()) * (bfs.maxBound(i) - bfs.minBound(i)) / float(RAND_MAX);
156  Indexes indexes_bf(bfs.knn(q, K, false));
157  for (size_t i = 0; i < K; ++i)
158  dumpCoordinateForSVG<float>(d.col(indexes_bf[i]), 100, 1, "stroke=\"black\" fill=\"green\"");
159  dumpCoordinateForSVG<float>(q, 100, 1, "stroke=\"black\" fill=\"blue\"");
160  cout << "</svg>" << endl;
161  */
162 
163  //cout << "Average KDTree visit count: " << double(totKDTreeVisitCount) * 100. / double(itCount * d.cols()) << " %" << endl;
164 
165 
166  return 0;
167 }
Nabo
Namespace for Nabo.
Definition: experimental/kdtree_cpu.cpp:40
Nabo::BruteForceSearch::knn
virtual unsigned long knn(const Matrix &query, IndexMatrix &indices, Matrix &dists2, const Index k, const T epsilon, const unsigned optionFlags, const T maxRadius) const
Definition: brute_force_cpu.cpp:64
dumpCoordinateForSVG
void dumpCoordinateForSVG(const typename NearestNeighbourSearch< T >::Vector coord, const float zoom=1, const float ptSize=1, const char *style="stroke=\"black\" fill=\"red\"")
Definition: knnshow.cpp:75
nabo.h
public interface
Nabo::runtime_error
Definition: nabo/nabo.cpp:50
Index
NNSNabo::Index Index
Definition: python/nabo.cpp:11
main
int main(int argc, char *argv[])
Definition: knnshow.cpp:88
load
NearestNeighbourSearch< T >::Matrix load(const char *fileName)
Definition: knnshow.cpp:41
Nabo::NearestNeighbourSearch::Matrix
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > Matrix
a column-major Eigen matrix in which each column is a point; this matrix has dim rows
Definition: nabo.h:263
BFSF
Nabo::BruteForceSearch< float > BFSF
Definition: knnbench.cpp:60
Nabo::NearestNeighbourSearch
Nearest neighbour search interface, templatized on scalar type.
Definition: nabo.h:258
Nabo::dist2
T dist2(const A &v0, const B &v1)
Euclidean distance.
Definition: nabo_private.h:65
Nabo::NearestNeighbourSearch::Vector
Eigen::Matrix< T, Eigen::Dynamic, 1 > Vector
an Eigen vector of type T, to hold the coordinates of a point
Definition: nabo.h:261
std
Definition: any.hpp:450
Nabo::NearestNeighbourSearch::Index
int Index
an index to a Vector or a Matrix, for refering to data points
Definition: nabo.h:267
test.q
q
Definition: test.py:8
Nabo::BruteForceSearch
Brute-force nearest neighbour.
Definition: nabo_private.h:72


libnabo
Author(s): Stéphane Magnenat
autogenerated on Fri Aug 2 2024 08:39:11