1 | // $Id: vector_distance_test.cc 900 2007-09-27 07:10:33Z markus $ |
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2 | |
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3 | #include "yat/classifier/DataLookupWeighted1D.h" |
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4 | #include "yat/classifier/MatrixLookupWeighted.h" |
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5 | #include "yat/statistics/euclidean_vector_distance.h" |
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6 | #include "yat/statistics/pearson_vector_distance.h" |
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7 | #include "yat/statistics/vector_distance_ptr.h" |
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8 | #include "yat/utility/matrix.h" |
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9 | #include "yat/utility/vector.h" |
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10 | |
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11 | #include <cassert> |
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12 | #include <fstream> |
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13 | #include <iostream> |
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14 | #include <list> |
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15 | #include <string> |
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16 | #include <vector> |
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17 | |
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18 | |
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19 | using namespace theplu::yat; |
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20 | |
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21 | |
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22 | // Function to test pointers to distance specialized for DataLookup1D::iterator |
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23 | double f(statistics::vector_distance_lookup_weighted_ptr distance) { |
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24 | utility::matrix m(2,3,1); |
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25 | m(0,1)=2; |
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26 | m(1,0)=0; |
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27 | m(1,1)=0; |
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28 | utility::matrix w(2,3,1); |
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29 | w(0,0)=0; |
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30 | classifier::MatrixLookupWeighted mw(m,w); |
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31 | classifier::DataLookupWeighted1D aw(mw,0,true); |
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32 | classifier::DataLookupWeighted1D bw(mw,1,true); |
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33 | |
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34 | double dist=(*distance)(aw.begin(),aw.end(),bw.begin()); |
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35 | return dist; |
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36 | } |
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37 | |
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38 | int main(const int argc,const char* argv[]) |
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39 | |
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40 | { |
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41 | std::ostream* error; |
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42 | if (argc>1 && argv[1]==std::string("-v")) |
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43 | error = &std::cerr; |
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44 | else { |
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45 | error = new std::ofstream("/dev/null"); |
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46 | if (argc>1) |
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47 | std::cout << "vector_distance_test -v : for printing extra information\n"; |
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48 | } |
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49 | *error << "testing vector_distance" << std::endl; |
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50 | bool ok = true; |
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51 | |
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52 | utility::vector a(3,1); |
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53 | a(1) = 2; |
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54 | utility::vector b(3,0); |
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55 | b(2) = 1; |
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56 | |
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57 | double tolerance=1e-4; |
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58 | |
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59 | double dist=statistics::vector_distance(a.begin(),a.end(),b.begin(), |
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60 | statistics::euclidean_vector_distance_tag()); |
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61 | if(fabs(dist-2.23607)>tolerance) { |
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62 | *error << "Error in unweighted Euclidean vector_distance " << std::endl; |
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63 | ok=false; |
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64 | } |
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65 | |
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66 | dist=statistics::vector_distance(a.begin(),a.end(),b.begin(), |
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67 | statistics::pearson_vector_distance_tag()); |
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68 | if(fabs(dist-1.5)>tolerance) { |
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69 | *error << "Error in unweighted Pearson vector_distance " << std::endl; |
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70 | ok=false; |
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71 | } |
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72 | |
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73 | |
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74 | // Testing weighted versions |
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75 | utility::matrix m(2,3,1); |
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76 | m(0,1)=2; |
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77 | m(1,0)=0; |
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78 | m(1,1)=0; |
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79 | utility::matrix w(2,3,1); |
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80 | w(0,0)=0; |
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81 | classifier::MatrixLookupWeighted mw(m,w); |
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82 | classifier::DataLookupWeighted1D aw(mw,0,true); |
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83 | classifier::DataLookupWeighted1D bw(mw,1,true); |
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84 | |
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85 | dist=statistics::vector_distance(aw.begin(),aw.end(),bw.begin(), |
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86 | statistics::euclidean_vector_distance_tag()); |
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87 | |
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88 | if(fabs(dist-2)>tolerance) { |
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89 | *error << "Error in weighted Euclidean vector_distance " << std::endl; |
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90 | ok=false; |
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91 | } |
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92 | |
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93 | dist=statistics::vector_distance(aw.begin(),aw.end(),bw.begin(), |
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94 | statistics::pearson_vector_distance_tag()); |
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95 | |
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96 | if(fabs(dist-2)>tolerance) { |
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97 | *error << "Error in weighted Pearson vector_distance " << std::endl; |
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98 | ok=false; |
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99 | } |
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100 | |
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101 | |
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102 | // Test with pointer to a vector_distance |
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103 | statistics::vector_distance_lookup_weighted_ptr test_ptr= |
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104 | statistics::vector_distance<statistics::euclidean_vector_distance_tag>; |
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105 | dist=(*test_ptr)(aw.begin(),aw.end(),bw.begin()); |
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106 | if(fabs(dist-2)>tolerance) { |
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107 | *error << "Error when using pointer to vector_distance" << std::endl; |
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108 | ok=false; |
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109 | } |
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110 | |
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111 | // Test with std::vectors |
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112 | std::vector<double> sa(3,1); |
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113 | sa[1] = 2; |
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114 | std::vector<double> sb(3,0); |
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115 | sb[2] = 1; |
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116 | |
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117 | dist=statistics::vector_distance(sa.begin(),sa.end(),sb.begin(), |
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118 | statistics::euclidean_vector_distance_tag()); |
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119 | if(fabs(dist-2.23607)>tolerance) { |
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120 | *error << "Error in vector_distance for std::vector " << std::endl; |
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121 | ok=false; |
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122 | } |
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123 | |
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124 | // Test for a std::list and a std::vector |
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125 | std::list<double> la; |
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126 | std::copy(sa.begin(),sa.end(),std::back_inserter<std::list<double> >(la)); |
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127 | dist=statistics::vector_distance(la.begin(),la.end(),sb.begin(), |
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128 | statistics::euclidean_vector_distance_tag()); |
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129 | if(fabs(dist-2.23607)>tolerance) { |
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130 | *error << "Error in vector_distance for std::list " << std::endl; |
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131 | ok=false; |
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132 | } |
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133 | |
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134 | if(!ok) { |
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135 | *error << "vector_distance_test failed" << std::endl; |
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136 | } |
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137 | if (error!=&std::cerr) |
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138 | delete error; |
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139 | if (ok=true) |
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140 | return 0; |
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141 | return -1; |
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142 | } |
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143 | |
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144 | |
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