source: trunk/test/vector_distance_test.cc @ 898

// $Id: vector_distance_test.cc 898 2007-09-26 13:44:19Z markus $

#include "yat/classifier/DataLookupWeighted1D.h"
#include "yat/classifier/MatrixLookupWeighted.h"
#include "yat/statistics/euclidean_vector_distance.h"
#include "yat/statistics/pearson_vector_distance.h"
#include "yat/statistics/vector_distance_ptr.h"
#include "yat/utility/matrix.h"
#include "yat/utility/vector.h"

#include <cassert>
#include <fstream>
#include <iostream>


using namespace theplu::yat;


// Function to test pointers to distance specialized for DataLookup1D::iterator
double f(statistics::vector_distance_lookup_weighted_ptr distance) {
  utility::matrix m(2,3,1);
  m(0,1)=2;
  m(1,0)=0;
  m(1,1)=0;
  utility::matrix w(2,3,1);
  w(0,0)=0;
  classifier::MatrixLookupWeighted mw(m,w);
  classifier::DataLookupWeighted1D aw(mw,0,true);
  classifier::DataLookupWeighted1D bw(mw,1,true);
  
  double dist=(*distance)(aw.begin(),aw.end(),bw.begin());
  return dist;  
}

int main(const int argc,const char* argv[])

{  
  std::ostream* error;
  if (argc>1 && argv[1]==std::string("-v"))
    error = &std::cerr;
  else {
    error = new std::ofstream("/dev/null");
    if (argc>1)
      std::cout << "vector_distance_test -v : for printing extra information\n";
  }
  *error << "testing vector_distance" << std::endl;
  bool ok = true;

  utility::vector a(3,1);
  a(1) = 2;
  utility::vector b(3,0);
  b(2) = 1;

  double tolerance=1e-4;

  double dist=statistics::vector_distance(a.begin(),a.end(),b.begin(),
                                          statistics::euclidean_vector_distance_tag());
  if(fabs(dist-2.23607)>tolerance) {
    *error << "Error in unweighted Euclidean vector_distance: " << std::endl;
    ok=false;
  }

  dist=statistics::vector_distance(a.begin(),a.end(),b.begin(),
                                          statistics::pearson_vector_distance_tag()); 
  if(fabs(dist-1.5)>tolerance) {
    *error << "Error in unweighted Pearson vector_distance: " << std::endl;
    ok=false;
  }

  
  // Testing weighted versions
  utility::matrix m(2,3,1);
  m(0,1)=2;
  m(1,0)=0;
  m(1,1)=0;
  utility::matrix w(2,3,1);
  w(0,0)=0;
  classifier::MatrixLookupWeighted mw(m,w);
  classifier::DataLookupWeighted1D aw(mw,0,true);
  classifier::DataLookupWeighted1D bw(mw,1,true);
  
  dist=statistics::vector_distance(aw.begin(),aw.end(),bw.begin(),
                                   statistics::euclidean_vector_distance_tag());
  
  if(fabs(dist-2)>tolerance) {
    *error << "Error in weighted Euclidean vector_distance: " << std::endl;
    ok=false;
  }

  dist=statistics::vector_distance(aw.begin(),aw.end(),bw.begin(),
                                          statistics::pearson_vector_distance_tag());
  
  if(fabs(dist-2)>tolerance) {
    *error << "Error in weighted Pearson vector_distance: " << std::endl;
    ok=false;
  }


  // Test with std::vectors
  std::vector<double> sa(3,1);
  sa[1] = 2;
  std::vector<double> sb(3,0);
  sb[2] = 1;

  dist=statistics::vector_distance(sa.begin(),sa.end(),sb.begin(),
                                   statistics::euclidean_vector_distance_tag());  if(fabs(dist-2.23607)>tolerance) {
    *error << "Error in vector_distance for std::vector: " << std::endl;
    ok=false;
  }


  // Test with pointer to a vector_distance
  statistics::vector_distance_lookup_weighted_ptr test_ptr=
    statistics::vector_distance<statistics::euclidean_vector_distance_tag>;
  dist=(*test_ptr)(aw.begin(),aw.end(),bw.begin());
  if(fabs(dist-2)>tolerance) {
    *error << "Error when using pointer to vector_distance" << std::endl;
    ok=false;
  }

  if(!ok) {
    *error << "vector_distance_test failed" << std::endl;
  }
  if (error!=&std::cerr)
    delete error;
  if (ok=true)  
    return 0;
  return -1;
}