1 | // UPGMATree.java |
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2 | // |
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3 | // (c) 1999-2001 PAL Development Core Team |
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4 | // |
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5 | // This package may be distributed under the |
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6 | // terms of the Lesser GNU General Public License (LGPL) |
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7 | |
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8 | // Known bugs and limitations: |
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9 | // - computational complexity O(numSeqs^3) |
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10 | // (this could be brought down to O(numSeqs^2) |
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11 | // but this needs more clever programming ...) |
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12 | |
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13 | |
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14 | package de.ugoe.cs.autoquest.tasktrees.alignment.pal.tree; |
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15 | |
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16 | import java.util.ArrayList; |
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17 | |
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18 | import de.ugoe.cs.autoquest.tasktrees.alignment.algorithms.NumberSequence; |
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19 | import de.ugoe.cs.autoquest.tasktrees.alignment.matrix.UPGMAMatrix; |
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20 | import de.ugoe.cs.autoquest.tasktrees.alignment.pal.misc.Identifier; |
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21 | |
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22 | |
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23 | /** |
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24 | * constructs a UPGMA tree from pairwise distances |
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25 | * |
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26 | * @version $Id: UPGMATree.java,v 1.9 2001/07/13 14:39:13 korbinian Exp $ |
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27 | * |
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28 | * @author Korbinian Strimmer |
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29 | * @author Alexei Drummond |
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30 | */ |
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31 | public class UPGMAAligningTree extends SimpleTree |
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32 | { |
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33 | // |
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34 | // Public stuff |
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35 | // |
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36 | |
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37 | /** |
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38 | * constructor UPGMA tree |
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39 | * @param numberseqs |
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40 | * |
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41 | * @param m distance matrix |
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42 | */ |
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43 | public UPGMAAligningTree(ArrayList<NumberSequence> numberseqs, UPGMAMatrix m) |
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44 | { |
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45 | if (m.size() < 2) |
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46 | { |
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47 | new IllegalArgumentException("LESS THAN 2 TAXA IN DISTANCE MATRIX"); |
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48 | } |
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49 | |
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50 | this.numberseqs = numberseqs; |
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51 | init(m); |
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52 | |
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53 | while (true) |
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54 | { |
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55 | findNextPair(); |
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56 | newBranchLengths(); |
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57 | |
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58 | if (numClusters == 2) |
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59 | { |
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60 | break; |
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61 | } |
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62 | |
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63 | newCluster(); |
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64 | } |
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65 | |
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66 | finish(); |
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67 | createNodeList(); |
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68 | } |
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69 | |
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70 | |
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71 | // |
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72 | // Private stuff |
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73 | // |
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74 | private ArrayList<NumberSequence> numberseqs; |
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75 | private int numClusters; |
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76 | private int besti, abi; |
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77 | private int bestj, abj; |
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78 | private int[] alias; |
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79 | private double[][] distance; |
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80 | |
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81 | private double[] height; |
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82 | private int[] oc; |
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83 | |
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84 | private double getDist(int a, int b) |
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85 | { |
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86 | return distance[alias[a]][alias[b]]; |
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87 | } |
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88 | |
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89 | private void init(UPGMAMatrix m) |
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90 | { |
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91 | numClusters = m.size(); |
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92 | |
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93 | distance = new double[numClusters][numClusters]; |
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94 | for (int i = 0; i < numClusters; i++) |
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95 | { |
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96 | for (int j = 0; j < numClusters; j++) |
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97 | { |
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98 | distance[i][j] = m.get(i,j); |
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99 | } |
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100 | } |
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101 | |
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102 | for (int i = 0; i < numClusters; i++) |
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103 | { |
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104 | Node tmp = NodeFactory.createNode(); |
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105 | tmp.setIdentifier(new Identifier(Integer.toString(i))); |
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106 | tmp.addSequence(numberseqs.get(i)); |
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107 | getRoot().addChild(tmp); |
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108 | } |
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109 | |
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110 | alias = new int[numClusters]; |
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111 | for (int i = 0; i < numClusters; i++) |
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112 | { |
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113 | alias[i] = i; |
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114 | } |
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115 | |
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116 | height = new double[numClusters]; |
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117 | oc = new int[numClusters]; |
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118 | for (int i = 0; i < numClusters; i++) |
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119 | { |
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120 | height[i] = 0.0; |
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121 | oc[i] = 1; |
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122 | } |
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123 | } |
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124 | |
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125 | private void finish() |
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126 | { |
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127 | distance = null; |
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128 | } |
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129 | |
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130 | private void findNextPair() |
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131 | { |
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132 | besti = 0; |
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133 | bestj = 1; |
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134 | double dmin = getDist(0, 1); |
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135 | for (int i = 0; i < numClusters-1; i++) |
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136 | { |
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137 | for (int j = i+1; j < numClusters; j++) |
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138 | { |
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139 | if (getDist(i, j) < dmin) |
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140 | { |
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141 | dmin = getDist(i, j); |
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142 | besti = i; |
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143 | bestj = j; |
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144 | } |
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145 | } |
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146 | } |
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147 | abi = alias[besti]; |
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148 | abj = alias[bestj]; |
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149 | //System.out.println("Found best pair: " + abi + "/" +abj + " - "+ besti+ "/"+bestj +" with distance " + dmin); |
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150 | |
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151 | } |
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152 | |
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153 | private void newBranchLengths() |
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154 | { |
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155 | double dij = getDist(besti, bestj); |
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156 | |
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157 | getRoot().getChild(besti).setBranchLength(dij/2.0-height[abi]); |
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158 | getRoot().getChild(bestj).setBranchLength(dij/2.0-height[abj]); |
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159 | } |
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160 | |
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161 | private void newCluster() |
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162 | { |
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163 | // Update distances |
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164 | for (int k = 0; k < numClusters; k++) |
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165 | { |
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166 | if (k != besti && k != bestj) |
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167 | { |
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168 | int ak = alias[k]; |
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169 | double updated = updatedDistance(besti,bestj,k); |
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170 | distance[ak][abi] = distance[abi][ak] = updated; |
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171 | } |
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172 | } |
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173 | distance[abi][abi] = 0.0; |
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174 | |
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175 | // Update UPGMA variables |
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176 | height[abi] = getDist(besti, bestj)/2.0; |
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177 | oc[abi] += oc[abj]; |
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178 | |
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179 | // Index besti now represent the new cluster |
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180 | getRoot().joinChildren(besti, bestj); |
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181 | |
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182 | // Update alias |
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183 | for (int i = bestj; i < numClusters-1; i++) |
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184 | { |
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185 | alias[i] = alias[i+1]; |
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186 | } |
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187 | |
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188 | numClusters--; |
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189 | } |
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190 | |
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191 | |
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192 | /** |
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193 | * compute updated distance between the new cluster (i,j) |
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194 | * to any other cluster k |
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195 | */ |
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196 | private double updatedDistance(int i, int j, int k) |
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197 | { |
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198 | int ai = alias[i]; |
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199 | int aj = alias[j]; |
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200 | |
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201 | double ocsum = (double) (oc[ai]+oc[aj]); |
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202 | double idist = getDist(k,i); |
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203 | double jdist = getDist(k,j); |
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204 | //TODO: Dirty hack to deal with infinity, insert proper solution here |
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205 | if(Double.isInfinite(idist)) { |
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206 | idist = 100; |
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207 | } |
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208 | if(Double.isInfinite(jdist)) { |
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209 | jdist = 100; |
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210 | } |
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211 | |
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212 | return (oc[ai]/ocsum)*idist+ |
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213 | (oc[aj]/ocsum)*jdist; |
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214 | } |
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215 | } |
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