1 | //---------------------------------------------------------------------- |
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2 | // File: rand.h |
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3 | // Programmer: Sunil Arya and David Mount |
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4 | // Description: Basic include file for random point generators |
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5 | // Last modified: 08/04/06 (Version 1.1.1) |
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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 | // History: |
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21 | // Revision 0.1 03/04/98 |
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22 | // Initial release |
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23 | // Revision 1.0 04/01/05 |
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24 | // Added annClusOrthFlats distribution |
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25 | // Changed procedure names to avoid namespace conflicts |
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26 | // Added annClusFlats distribution |
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27 | // Revision 1.1.1 08/04/06 |
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28 | // Added planted distribution |
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29 | //---------------------------------------------------------------------- |
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30 | |
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31 | #ifndef rand_H |
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32 | #define rand_H |
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33 | |
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34 | //---------------------------------------------------------------------- |
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35 | // Basic includes |
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36 | //---------------------------------------------------------------------- |
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37 | #include <cstdlib> // standard includes (rand/random) |
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38 | #include <cmath> // math routines |
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39 | #include <ANN/ANN.h> // basic ANN includes |
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40 | |
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41 | //---------------------------------------------------------------------- |
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42 | // Although random/srandom is a more reliable random number generator, |
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43 | // many systems do not have it. If it is not available, set the |
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44 | // preprocessor symbol ANN_NO_RANDOM, and this will substitute the use |
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45 | // of rand/srand for them. |
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46 | //---------------------------------------------------------------------- |
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47 | #ifdef ANN_NO_RANDOM // for systems not having random() |
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48 | #define ANN_RAND rand |
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49 | #define ANN_SRAND srand |
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50 | #define ANN_RAND_MAX RAND_MAX |
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51 | #else // otherwise use rand() |
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52 | #define ANN_RAND random |
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53 | #define ANN_SRAND srandom |
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54 | #define ANN_RAND_MAX 2147483647UL // 2**{31} - 1 |
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55 | // #define ANN_RAND_MAX 1073741824UL // 2**{30} |
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56 | #endif |
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57 | |
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58 | //---------------------------------------------------------------------- |
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59 | // Globals |
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60 | //---------------------------------------------------------------------- |
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61 | extern int annIdum; // random number seed |
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62 | |
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63 | //---------------------------------------------------------------------- |
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64 | // External entry points |
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65 | //---------------------------------------------------------------------- |
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66 | |
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67 | void annUniformPts( // uniform distribution |
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68 | ANNpointArray pa, // point array (modified) |
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69 | int n, // number of points |
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70 | int dim); // dimension |
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71 | |
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72 | void annGaussPts( // Gaussian distribution |
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73 | ANNpointArray pa, // point array (modified) |
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74 | int n, // number of points |
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75 | int dim, // dimension |
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76 | double std_dev); // standard deviation |
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77 | |
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78 | void annCoGaussPts( // correlated-Gaussian distribution |
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79 | ANNpointArray pa, // point array (modified) |
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80 | int n, // number of points |
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81 | int dim, // dimension |
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82 | double correlation); // correlation |
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83 | |
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84 | void annLaplacePts( // Laplacian distribution |
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85 | ANNpointArray pa, // point array (modified) |
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86 | int n, // number of points |
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87 | int dim); // dimension |
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88 | |
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89 | void annCoLaplacePts( // correlated-Laplacian distribution |
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90 | ANNpointArray pa, // point array (modified) |
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91 | int n, // number of points |
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92 | int dim, // dimension |
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93 | double correlation); // correlation |
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94 | |
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95 | void annClusGaussPts( // clustered-Gaussian distribution |
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96 | ANNpointArray pa, // point array (modified) |
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97 | int n, // number of points |
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98 | int dim, // dimension |
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99 | int n_clus, // number of colors (clusters) |
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100 | ANNbool new_clust, // generate new cluster centers |
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101 | double std_dev); // standard deviation within clusters |
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102 | |
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103 | void annClusOrthFlats( // clustered along orthogonal flats |
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104 | ANNpointArray pa, // point array (modified) |
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105 | int n, // number of points |
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106 | int dim, // dimension |
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107 | int n_clus, // number of colors |
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108 | ANNbool new_clust, // generate new clusters. |
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109 | double std_dev, // standard deviation within clusters |
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110 | int max_dim); // maximum dimension of the flats |
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111 | |
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112 | void annClusEllipsoids( // clustered around ellipsoids |
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113 | ANNpointArray pa, // point array (modified) |
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114 | int n, // number of points |
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115 | int dim, // dimension |
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116 | int n_clus, // number of colors |
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117 | ANNbool new_clust, // generate new clusters. |
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118 | double std_dev_small, // small standard deviation |
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119 | double std_dev_lo, // low standard deviation for ellipses |
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120 | double std_dev_hi, // high standard deviation for ellipses |
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121 | int max_dim); // maximum dimension of the flats |
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122 | |
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123 | void annPlanted( // planted nearest neighbors |
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124 | ANNpointArray pa, // point array (modified) |
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125 | int n, // number of points |
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126 | int dim, // dimension |
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127 | ANNpointArray src, // source point array |
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128 | int n_src, // source size |
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129 | double std_dev); // standard deviation about source |
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130 | |
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131 | #endif |
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