1 | //---------------------------------------------------------------------- |
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2 | // File: ann_sample.cpp |
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3 | // Programmer: Sunil Arya and David Mount |
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4 | // Last modified: 03/04/98 (Release 0.1) |
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5 | // Description: Sample program for ANN |
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6 | //---------------------------------------------------------------------- |
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7 | // Copyright (c) 1997-2005 University of Maryland and Sunil Arya and |
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8 | // David Mount. All Rights Reserved. |
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9 | // |
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10 | // This software and related documentation is part of the Approximate |
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11 | // Nearest Neighbor Library (ANN). This software is provided under |
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12 | // the provisions of the Lesser GNU Public License (LGPL). See the |
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13 | // file ../ReadMe.txt for further information. |
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14 | // |
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15 | // The University of Maryland (U.M.) and the authors make no |
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16 | // representations about the suitability or fitness of this software for |
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17 | // any purpose. It is provided "as is" without express or implied |
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18 | // warranty. |
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19 | //---------------------------------------------------------------------- |
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20 | |
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21 | #include <cstdlib> // C standard library |
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22 | #include <cstdio> // C I/O (for sscanf) |
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23 | #include <cstring> // string manipulation |
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24 | #include <fstream> // file I/O |
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25 | #include <ANN/ANN.h> // ANN declarations |
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26 | |
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27 | using namespace std; // make std:: accessible |
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28 | |
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29 | //---------------------------------------------------------------------- |
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30 | // ann_sample |
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31 | // |
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32 | // This is a simple sample program for the ANN library. After compiling, |
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33 | // it can be run as follows. |
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34 | // |
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35 | // ann_sample [-d dim] [-max mpts] [-nn k] [-e eps] [-df data] [-qf query] |
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36 | // |
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37 | // where |
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38 | // dim is the dimension of the space (default = 2) |
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39 | // mpts maximum number of data points (default = 1000) |
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40 | // k number of nearest neighbors per query (default 1) |
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41 | // eps is the error bound (default = 0.0) |
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42 | // data file containing data points |
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43 | // query file containing query points |
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44 | // |
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45 | // Results are sent to the standard output. |
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46 | //---------------------------------------------------------------------- |
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47 | |
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48 | //---------------------------------------------------------------------- |
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49 | // Parameters that are set in getArgs() |
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50 | //---------------------------------------------------------------------- |
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51 | void getArgs(int argc, char **argv); // get command-line arguments |
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52 | |
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53 | int k = 1; // number of nearest neighbors |
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54 | int dim = 2; // dimension |
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55 | double eps = 0; // error bound |
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56 | int maxPts = 1000; // maximum number of data points |
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57 | |
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58 | istream* dataIn = NULL; // input for data points |
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59 | istream* queryIn = NULL; // input for query points |
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60 | |
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61 | bool readPt(istream &in, ANNpoint p) // read point (false on EOF) |
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62 | { |
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63 | for (int i = 0; i < dim; i++) { |
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64 | if(!(in >> p[i])) return false; |
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65 | } |
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66 | return true; |
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67 | } |
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68 | |
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69 | void printPt(ostream &out, ANNpoint p) // print point |
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70 | { |
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71 | out << "(" << p[0]; |
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72 | for (int i = 1; i < dim; i++) { |
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73 | out << ", " << p[i]; |
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74 | } |
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75 | out << ")\n"; |
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76 | } |
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77 | |
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78 | int main(int argc, char **argv) |
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79 | { |
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80 | int nPts; // actual number of data points |
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81 | ANNpointArray dataPts; // data points |
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82 | ANNpoint queryPt; // query point |
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83 | ANNidxArray nnIdx; // near neighbor indices |
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84 | ANNdistArray dists; // near neighbor distances |
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85 | ANNkd_tree* kdTree; // search structure |
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86 | |
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87 | getArgs(argc, argv); // read command-line arguments |
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88 | |
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89 | queryPt = annAllocPt(dim); // allocate query point |
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90 | dataPts = annAllocPts(maxPts, dim); // allocate data points |
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91 | nnIdx = new ANNidx[k]; // allocate near neigh indices |
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92 | dists = new ANNdist[k]; // allocate near neighbor dists |
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93 | |
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94 | nPts = 0; // read data points |
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95 | |
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96 | cout << "Data Points:\n"; |
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97 | while (nPts < maxPts && readPt(*dataIn, dataPts[nPts])) { |
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98 | printPt(cout, dataPts[nPts]); |
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99 | nPts++; |
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100 | } |
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101 | |
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102 | kdTree = new ANNkd_tree( // build search structure |
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103 | dataPts, // the data points |
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104 | nPts, // number of points |
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105 | dim); // dimension of space |
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106 | |
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107 | while (readPt(*queryIn, queryPt)) { // read query points |
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108 | cout << "Query point: "; // echo query point |
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109 | printPt(cout, queryPt); |
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110 | |
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111 | kdTree->annkSearch( // search |
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112 | queryPt, // query point |
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113 | k, // number of near neighbors |
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114 | nnIdx, // nearest neighbors (returned) |
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115 | dists, // distance (returned) |
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116 | eps); // error bound |
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117 | |
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118 | cout << "\tNN:\tIndex\tDistance\n"; |
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119 | for (int i = 0; i < k; i++) { // print summary |
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120 | dists[i] = sqrt(dists[i]); // unsquare distance |
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121 | cout << "\t" << i << "\t" << nnIdx[i] << "\t" << dists[i] << "\n"; |
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122 | } |
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123 | } |
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124 | delete [] nnIdx; // clean things up |
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125 | delete [] dists; |
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126 | delete kdTree; |
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127 | annClose(); // done with ANN |
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128 | |
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129 | return EXIT_SUCCESS; |
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130 | } |
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131 | |
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132 | //---------------------------------------------------------------------- |
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133 | // getArgs - get command line arguments |
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134 | //---------------------------------------------------------------------- |
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135 | |
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136 | void getArgs(int argc, char **argv) |
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137 | { |
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138 | static ifstream dataStream; // data file stream |
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139 | static ifstream queryStream; // query file stream |
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140 | |
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141 | if (argc <= 1) { // no arguments |
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142 | cerr << "Usage:\n\n" |
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143 | << " ann_sample [-d dim] [-max m] [-nn k] [-e eps] [-df data]" |
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144 | " [-qf query]\n\n" |
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145 | << " where:\n" |
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146 | << " dim dimension of the space (default = 2)\n" |
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147 | << " m maximum number of data points (default = 1000)\n" |
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148 | << " k number of nearest neighbors per query (default 1)\n" |
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149 | << " eps the error bound (default = 0.0)\n" |
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150 | << " data name of file containing data points\n" |
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151 | << " query name of file containing query points\n\n" |
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152 | << " Results are sent to the standard output.\n" |
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153 | << "\n" |
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154 | << " To run this demo use:\n" |
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155 | << " ann_sample -df data.pts -qf query.pts\n"; |
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156 | exit(0); |
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157 | } |
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158 | int i = 1; |
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159 | while (i < argc) { // read arguments |
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160 | if (!strcmp(argv[i], "-d")) { // -d option |
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161 | dim = atoi(argv[++i]); // get dimension to dump |
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162 | } |
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163 | else if (!strcmp(argv[i], "-max")) { // -max option |
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164 | maxPts = atoi(argv[++i]); // get max number of points |
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165 | } |
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166 | else if (!strcmp(argv[i], "-nn")) { // -nn option |
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167 | k = atoi(argv[++i]); // get number of near neighbors |
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168 | } |
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169 | else if (!strcmp(argv[i], "-e")) { // -e option |
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170 | sscanf(argv[++i], "%lf", &eps); // get error bound |
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171 | } |
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172 | else if (!strcmp(argv[i], "-df")) { // -df option |
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173 | dataStream.open(argv[++i], ios::in);// open data file |
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174 | if (!dataStream) { |
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175 | cerr << "Cannot open data file\n"; |
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176 | exit(1); |
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177 | } |
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178 | dataIn = &dataStream; // make this the data stream |
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179 | } |
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180 | else if (!strcmp(argv[i], "-qf")) { // -qf option |
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181 | queryStream.open(argv[++i], ios::in);// open query file |
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182 | if (!queryStream) { |
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183 | cerr << "Cannot open query file\n"; |
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184 | exit(1); |
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185 | } |
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186 | queryIn = &queryStream; // make this query stream |
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187 | } |
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188 | else { // illegal syntax |
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189 | cerr << "Unrecognized option.\n"; |
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190 | exit(1); |
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191 | } |
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192 | i++; |
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193 | } |
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194 | if (dataIn == NULL || queryIn == NULL) { |
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195 | cerr << "-df and -qf options must be specified\n"; |
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196 | exit(1); |
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197 | } |
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198 | } |
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