Mercurial > dive4elements > river

annotate flys-artifacts/src/main/java/de/intevation/flys/artifacts/model/sq/Fitting.java @ 3190:49fe2ed03c12

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SQ: Refactored fitting to better fit the data types of SQResult. flys-artifacts/trunk@4805 c6561f87-3c4e-4783-a992-168aeb5c3f6f
author Sascha L. Teichmann <sascha.teichmann@intevation.de>
date Tue, 26 Jun 2012 17:20:31 +0000
parents 1e46ced2bb57
children 1df6984628c3
rev   line source
3188
1e46ced2bb57 SQ: Added fitting shell for SQ curves.
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parents:
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1 package de.intevation.flys.artifacts.model.sq;
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2
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3 import de.intevation.flys.artifacts.math.fitting.Function;
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4
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5 import java.util.ArrayList;
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6 import java.util.Iterator;
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7 import java.util.List;
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8
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9 import org.apache.commons.math.MathException;
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10
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11 import org.apache.commons.math.optimization.fitting.CurveFitter;
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12
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13 import org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer;
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14
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15 import org.apache.log4j.Logger;
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16
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17 public class Fitting
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18 {
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19 private static Logger log = Logger.getLogger(Fitting.class);
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20
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21 protected Function function;
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22
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23 protected double [] parameters;
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24
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25 protected double stdDevFactor;
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26
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27 protected double standardDeviation;
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28
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29 protected double chiSqr;
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30
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31 protected SQ [] remaining;
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32
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33 protected List<SQ []> outliers;
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34
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35 public Fitting() {
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36 }
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37
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38 public Fitting(Function function, double stdDevFactor) {
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39 this.function = function;
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40 this.stdDevFactor = stdDevFactor;
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41 }
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42
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43 public Function getFunction() {
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44 return function;
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45 }
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46
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47 public void setFunction(Function function) {
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48 this.function = function;
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49 }
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50
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51 public double [] getParameters() {
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52 return parameters;
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53 }
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54
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55 public void setParameters(double [] parameters) {
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56 this.parameters = parameters;
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57 }
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58
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59 public double getStdDevFactor() {
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60 return stdDevFactor;
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61 }
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62
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63 public void setStdDevFactor(double stdDevFactor) {
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64 this.stdDevFactor = stdDevFactor;
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65 }
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66
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67 public double getStandardDeviation() {
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68 return standardDeviation;
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69 }
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70
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71 public void setStandardDeviation(double standardDeviation) {
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72 this.standardDeviation = standardDeviation;
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73 }
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74
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75 public double getChiSqr() {
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76 return chiSqr;
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77 }
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78
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79 public void setChiSqr(double chiSqr) {
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80 this.chiSqr = chiSqr;
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81 }
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82
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83 public SQ [] getRemaining() {
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84 return remaining;
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85 }
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86
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87 public void setRemaining(SQ [] remaining) {
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88 this.remaining = remaining;
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89 }
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90
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91 public List<SQ []> getOutliers() {
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92 return outliers;
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93 }
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94
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95 public void setOutliers(List<SQ []> outliers) {
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96 this.outliers = outliers;
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97 }
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98
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99 public void reset() {
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100 outliers = null;
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101 remaining = null;
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102 parameters = null;
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103 standardDeviation = 0d;
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104 standardDeviation = 0d;
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105 chiSqr = 0d;
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106 }
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107
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108 protected static final List<SQ> onlyValid(List<SQ> sqs) {
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109
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110 List<SQ> good = new ArrayList<SQ>(sqs.size());
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111
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112 for (SQ sq: sqs) {
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113 if (sq.isValid()) {
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114 good.add(sq);
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115 }
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116 }
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117
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118 return good;
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119 }
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120
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121 public boolean fit(List<SQ> sqs) {
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122
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123 sqs = onlyValid(sqs);
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124
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125 if (sqs.size() < 2) {
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126 log.warn("Too less points for fitting.");
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127 return false;
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128 }
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129
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130 final LevenbergMarquardtOptimizer lmo =
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131 new LevenbergMarquardtOptimizer();
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132
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133 CurveFitter cf = new CurveFitter(lmo);
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134
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135 for (SQ sq: sqs) {
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136 cf.addObservedPoint(sq.getQ(), sq.getS());
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137 }
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138
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139 try {
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140 parameters = cf.fit(function, function.getInitialGuess());
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141 }
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142 catch (MathException me) {
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143 log.warn(me);
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144 return false;
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145 }
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146
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147 chiSqr = lmo.getChiSquare();
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148
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149 final de.intevation.flys.artifacts.math.Function [] instance = {
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150 function.instantiate(parameters)
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151 };
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152
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153 try {
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154 remaining = Outlier.detectOutliers(
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155 new Outlier.Callback() {
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156
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157 List<List<SQ>> outliers =
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158 new ArrayList<List<SQ>>();
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159
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160 int currentIteration;
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161
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162 @Override
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163 public double eval(SQ sq) {
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164 double s = instance[0].value(sq.q);
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165 return s - sq.s;
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166 }
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167
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168 @Override
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169 public void iteration(int i) {
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170 currentIteration = i;
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171 }
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172
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173 @Override
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174 public void outlier(SQ sq) {
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175 if (currentIteration > outliers.size()) {
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176 outliers.add(new ArrayList<SQ>(2));
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177 }
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178 outliers.get(currentIteration-1).add(sq);
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179 }
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180
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181 @Override
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182 public void standardDeviation(double stdDev) {
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183 setStandardDeviation(stdDev);
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184 }
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185
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186 @Override
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187 public void reinitialize(Iterator<SQ> good)
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188 throws MathException
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189 {
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190 CurveFitter cf = new CurveFitter(lmo);
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191 while (good.hasNext()) {
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192 SQ sq = good.next();
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193 cf.addObservedPoint(sq.getQ(), sq.getS());
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194 }
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195
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196 parameters = cf.fit(
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197 function, function.getInitialGuess());
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198
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199 instance[0] = function.instantiate(parameters);
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200
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201 chiSqr = lmo.getChiSquare();
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202 }
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203
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204 @Override
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205 public void finished() {
3190
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206 List<SQ []> result =
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207 new ArrayList<SQ []>(outliers.size());
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208
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209 for (List<SQ> ols: outliers) {
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210 result.add(ols.toArray(new SQ[ols.size()]));
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211 }
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212
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213 setOutliers(result);
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214 }
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215 },
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216 sqs,
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217 stdDevFactor);
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218 }
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219 catch (MathException me) {
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220 log.warn(me);
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221 return false;
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222 }
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223
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224 return true;
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225 }
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226 }
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227 // vim:set ts=4 sw=4 si et sta sts=4 fenc=utf8 :
http://dive4elements.wald.intevation.org