1 | /*********************************************************************** |
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2 | * Software License Agreement (BSD License) |
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3 | * |
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4 | * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. |
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5 | * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. |
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6 | * |
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7 | * THE BSD LICENSE |
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8 | * |
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9 | * Redistribution and use in source and binary forms, with or without |
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10 | * modification, are permitted provided that the following conditions |
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11 | * are met: |
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12 | * |
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13 | * 1. Redistributions of source code must retain the above copyright |
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14 | * notice, this list of conditions and the following disclaimer. |
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15 | * 2. Redistributions in binary form must reproduce the above copyright |
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16 | * notice, this list of conditions and the following disclaimer in the |
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17 | * documentation and/or other materials provided with the distribution. |
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18 | * |
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19 | * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR |
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20 | * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES |
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21 | * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. |
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22 | * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, |
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23 | * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT |
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24 | * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, |
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25 | * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY |
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26 | * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT |
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27 | * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF |
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28 | * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
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29 | *************************************************************************/ |
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30 | |
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31 | #ifndef FLANN_SIMPLEX_DOWNHILL_H_ |
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32 | #define FLANN_SIMPLEX_DOWNHILL_H_ |
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33 | |
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34 | namespace flann |
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35 | { |
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36 | |
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37 | /** |
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38 | Adds val to array vals (and point to array points) and keeping the arrays sorted by vals. |
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39 | */ |
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40 | template <typename T> |
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41 | void addValue(int pos, float val, float* vals, T* point, T* points, int n) |
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42 | { |
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43 | vals[pos] = val; |
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44 | for (int i=0; i<n; ++i) { |
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45 | points[pos*n+i] = point[i]; |
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46 | } |
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47 | |
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48 | // bubble down |
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49 | int j=pos; |
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50 | while (j>0 && vals[j]<vals[j-1]) { |
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51 | swap(vals[j],vals[j-1]); |
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52 | for (int i=0; i<n; ++i) { |
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53 | swap(points[j*n+i],points[(j-1)*n+i]); |
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54 | } |
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55 | --j; |
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56 | } |
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57 | } |
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58 | |
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59 | |
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60 | /** |
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61 | Simplex downhill optimization function. |
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62 | Preconditions: points is a 2D mattrix of size (n+1) x n |
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63 | func is the cost function taking n an array of n params and returning float |
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64 | vals is the cost function in the n+1 simplex points, if NULL it will be computed |
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65 | |
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66 | Postcondition: returns optimum value and points[0..n] are the optimum parameters |
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67 | */ |
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68 | template <typename T, typename F> |
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69 | float optimizeSimplexDownhill(T* points, int n, F func, float* vals = NULL ) |
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70 | { |
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71 | const int MAX_ITERATIONS = 10; |
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72 | |
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73 | assert(n>0); |
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74 | |
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75 | T* p_o = new T[n]; |
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76 | T* p_r = new T[n]; |
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77 | T* p_e = new T[n]; |
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78 | |
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79 | int alpha = 1; |
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80 | |
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81 | int iterations = 0; |
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82 | |
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83 | bool ownVals = false; |
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84 | if (vals == NULL) { |
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85 | ownVals = true; |
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86 | vals = new float[n+1]; |
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87 | for (int i=0; i<n+1; ++i) { |
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88 | float val = func(points+i*n); |
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89 | addValue(i, val, vals, points+i*n, points, n); |
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90 | } |
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91 | } |
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92 | int nn = n*n; |
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93 | |
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94 | while (true) { |
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95 | |
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96 | if (iterations++ > MAX_ITERATIONS) break; |
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97 | |
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98 | // compute average of simplex points (except the highest point) |
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99 | for (int j=0; j<n; ++j) { |
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100 | p_o[j] = 0; |
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101 | for (int i=0; i<n; ++i) { |
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102 | p_o[i] += points[j*n+i]; |
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103 | } |
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104 | } |
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105 | for (int i=0; i<n; ++i) { |
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106 | p_o[i] /= n; |
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107 | } |
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108 | |
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109 | bool converged = true; |
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110 | for (int i=0; i<n; ++i) { |
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111 | if (p_o[i] != points[nn+i]) { |
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112 | converged = false; |
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113 | } |
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114 | } |
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115 | if (converged) break; |
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116 | |
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117 | // trying a reflection |
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118 | for (int i=0; i<n; ++i) { |
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119 | p_r[i] = p_o[i] + alpha*(p_o[i]-points[nn+i]); |
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120 | } |
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121 | float val_r = func(p_r); |
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122 | |
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123 | if ((val_r>=vals[0])&&(val_r<vals[n])) { |
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124 | // reflection between second highest and lowest |
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125 | // add it to the simplex |
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126 | Logger::info("Choosing reflection\n"); |
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127 | addValue(n, val_r,vals, p_r, points, n); |
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128 | continue; |
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129 | } |
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130 | |
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131 | if (val_r<vals[0]) { |
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132 | // value is smaller than smalest in simplex |
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133 | |
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134 | // expand some more to see if it drops further |
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135 | for (int i=0; i<n; ++i) { |
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136 | p_e[i] = 2*p_r[i]-p_o[i]; |
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137 | } |
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138 | float val_e = func(p_e); |
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139 | |
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140 | if (val_e<val_r) { |
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141 | Logger::info("Choosing reflection and expansion\n"); |
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142 | addValue(n, val_e,vals,p_e,points,n); |
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143 | } |
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144 | else { |
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145 | Logger::info("Choosing reflection\n"); |
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146 | addValue(n, val_r,vals,p_r,points,n); |
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147 | } |
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148 | continue; |
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149 | } |
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150 | if (val_r>=vals[n]) { |
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151 | for (int i=0; i<n; ++i) { |
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152 | p_e[i] = (p_o[i]+points[nn+i])/2; |
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153 | } |
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154 | float val_e = func(p_e); |
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155 | |
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156 | if (val_e<vals[n]) { |
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157 | Logger::info("Choosing contraction\n"); |
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158 | addValue(n,val_e,vals,p_e,points,n); |
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159 | continue; |
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160 | } |
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161 | } |
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162 | { |
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163 | Logger::info("Full contraction\n"); |
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164 | for (int j=1; j<=n; ++j) { |
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165 | for (int i=0; i<n; ++i) { |
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166 | points[j*n+i] = (points[j*n+i]+points[i])/2; |
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167 | } |
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168 | float val = func(points+j*n); |
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169 | addValue(j,val,vals,points+j*n,points,n); |
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170 | } |
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171 | } |
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172 | } |
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173 | |
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174 | float bestVal = vals[0]; |
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175 | |
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176 | delete[] p_r; |
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177 | delete[] p_o; |
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178 | delete[] p_e; |
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179 | if (ownVals) delete[] vals; |
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180 | |
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181 | return bestVal; |
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182 | } |
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183 | |
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184 | } |
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185 | |
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186 | #endif //FLANN_SIMPLEX_DOWNHILL_H_ |
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