Mercurial > dive4elements > river
annotate artifacts/src/main/java/org/dive4elements/river/artifacts/model/sq/Fitting.java @ 6796:978ab716a15e
flys/issue1347: Added missing calcutions. TODO: Bring them into the generated outs.
author | Sascha L. Teichmann <teichmann@intevation.de> |
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date | Fri, 09 Aug 2013 18:24:55 +0200 |
parents | 51eb6491c537 |
children | 0a5239a1e46e |
rev | line source |
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1 /* Copyright (C) 2011, 2012, 2013 by Bundesanstalt für Gewässerkunde |
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2 * Software engineering by Intevation GmbH |
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3 * |
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4 * This file is Free Software under the GNU AGPL (>=v3) |
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5 * and comes with ABSOLUTELY NO WARRANTY! Check out the |
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6 * documentation coming with Dive4Elements River for details. |
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7 */ |
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8 |
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9 package org.dive4elements.river.artifacts.model.sq; |
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10 |
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11 import org.dive4elements.artifacts.common.utils.StringUtils; |
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12 import org.dive4elements.river.artifacts.math.fitting.Function; |
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13 |
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14 import java.util.ArrayList; |
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15 import java.util.List; |
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16 |
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17 import org.apache.commons.math.MathException; |
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18 |
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19 import org.apache.commons.math.optimization.fitting.CurveFitter; |
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20 |
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21 import org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer; |
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22 import org.apache.commons.math.stat.regression.SimpleRegression; |
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23 |
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24 import org.apache.log4j.Logger; |
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25 |
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26 public class Fitting |
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27 implements Outlier.Callback |
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28 { |
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29 // XXX: Hack to force linear fitting! |
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30 private static final boolean USE_NON_LINEAR_FITTING = |
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31 Boolean.getBoolean("minfo.sq.fitting.nonlinear"); |
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32 |
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33 private static Logger log = Logger.getLogger(Fitting.class); |
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34 |
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35 public interface Callback { |
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36 |
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37 void afterIteration( |
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38 double [] parameters, |
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39 SQ [] measurements, |
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40 SQ [] outliers, |
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41 double standardDeviation, |
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42 double chiSqr); |
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43 } // interfacte |
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44 |
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45 protected Function function; |
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46 |
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47 protected double [] coeffs; |
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48 |
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49 protected org.dive4elements.river.artifacts.math.Function instance; |
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50 |
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51 protected double stdDevFactor; |
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52 protected double chiSqr; |
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53 |
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54 protected Callback callback; |
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55 |
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56 protected SQ.View sqView; |
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57 |
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58 public Fitting() { |
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59 } |
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60 |
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61 public Fitting(Function function, double stdDevFactor, SQ.View sqView) { |
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62 this.function = function; |
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63 this.stdDevFactor = stdDevFactor; |
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64 this.sqView = sqView; |
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65 } |
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66 |
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67 public Function getFunction() { |
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68 return function; |
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69 } |
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70 |
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71 public void setFunction(Function function) { |
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72 this.function = function; |
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73 } |
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74 |
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75 public double getStdDevFactor() { |
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76 return stdDevFactor; |
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77 } |
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78 |
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79 public void setStdDevFactor(double stdDevFactor) { |
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80 this.stdDevFactor = stdDevFactor; |
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81 } |
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82 |
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83 @Override |
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84 public void initialize(List<SQ> sqs) throws MathException { |
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85 |
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86 if (USE_NON_LINEAR_FITTING |
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87 || function.getParameterNames().length != 2) { |
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88 nonLinearFitting(sqs); |
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89 } |
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90 else { |
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91 linearFitting(sqs); |
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92 } |
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93 } |
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94 |
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95 protected void linearFitting(List<SQ> sqs) { |
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96 coeffs = linearRegression(sqs); |
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97 instance = function.instantiate(coeffs); |
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98 } |
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99 |
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100 protected double [] linearRegression(List<SQ> sqs) { |
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101 |
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102 String [] pns = function.getParameterNames(); |
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103 double [] result = new double[pns.length]; |
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104 |
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105 if (sqs.size() < 2) { |
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106 log.debug("not enough points"); |
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107 return result; |
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108 } |
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109 |
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110 SimpleRegression reg = new SimpleRegression(); |
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111 |
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112 for (SQ sq: sqs) { |
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113 double s = sqView.getS(sq); |
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114 double q = sqView.getQ(sq); |
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115 reg.addData(q, s); |
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116 } |
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117 |
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118 double m = reg.getIntercept(); |
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119 double b = reg.getSlope(); |
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120 |
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121 if (log.isDebugEnabled()) { |
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122 log.debug("m: " + m); |
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123 log.debug("b: " + b); |
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124 } |
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125 |
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126 int mIdx = StringUtils.indexOf("m", pns); |
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127 int bIdx = StringUtils.indexOf("b", pns); |
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128 |
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129 if (mIdx == -1 || bIdx == -1) { |
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130 log.error("index not found: " + mIdx + " " + bIdx); |
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131 return result; |
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132 } |
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133 |
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134 result[bIdx] = m; |
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135 result[mIdx] = b; |
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136 |
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137 return result; |
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138 } |
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139 |
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140 |
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141 protected void nonLinearFitting(List<SQ> sqs) throws MathException { |
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142 |
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143 LevenbergMarquardtOptimizer optimizer = |
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144 new LevenbergMarquardtOptimizer(); |
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145 |
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146 CurveFitter cf = new CurveFitter(optimizer); |
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147 |
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148 for (SQ sq: sqs) { |
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149 cf.addObservedPoint(sqView.getQ(sq), sqView.getS(sq)); |
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150 } |
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151 |
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152 coeffs = cf.fit( |
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153 function, function.getInitialGuess()); |
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154 |
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155 instance = function.instantiate(coeffs); |
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156 |
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157 chiSqr = optimizer.getChiSquare(); |
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158 } |
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159 |
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160 @Override |
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161 public double eval(SQ sq) { |
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162 double s = instance.value(sqView.getQ(sq)); |
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163 return sqView.getS(sq) - s; |
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164 } |
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165 |
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166 @Override |
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167 public void iterationFinished( |
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168 double standardDeviation, |
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169 SQ outlier, |
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170 List<SQ> remainings |
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171 ) { |
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172 if (log.isDebugEnabled()) { |
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173 log.debug("iterationFinished ----"); |
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174 log.debug(" num remainings: " + remainings.size()); |
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175 log.debug(" has outlier: " + outlier != null); |
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176 log.debug(" standardDeviation: " + standardDeviation); |
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177 log.debug(" Chi^2: " + chiSqr); |
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178 log.debug("---- iterationFinished"); |
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179 } |
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180 callback.afterIteration( |
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181 coeffs, |
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182 remainings.toArray(new SQ[remainings.size()]), |
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183 outlier != null ? new SQ [] { outlier} : new SQ [] {}, |
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184 standardDeviation, |
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185 chiSqr); |
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186 } |
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187 |
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188 public boolean fit(List<SQ> sqs, String method, Callback callback) { |
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189 |
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190 if (sqs.size() < 2) { |
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191 log.warn("Too less points for fitting."); |
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192 return false; |
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193 } |
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194 |
6780
b8f94e865875
S/Q relation: Part I of 'faking' fitting linear data. S/Qs can now be subclassed and processed through views. TODO: Add knob to setup a linear data path.
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195 sqs = new ArrayList<SQ>(sqs); |
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S/Q relation: Part I of 'faking' fitting linear data. S/Qs can now be subclassed and processed through views. TODO: Add knob to setup a linear data path.
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196 |
3552
1df6984628c3
S/Q: Extented the result data model of the S/Q calculation to
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197 this.callback = callback; |
3188
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198 |
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199 try { |
5396
aaf810d4ec82
Use new state 'outlier mehtod selection' in SQ-relation.
Raimund Renkert <rrenkert@intevation.de>
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200 Outlier.detectOutliers(this, sqs, stdDevFactor, method); |
3188
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201 } |
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202 catch (MathException me) { |
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203 log.warn(me); |
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204 return false; |
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205 } |
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206 |
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207 return true; |
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208 } |
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parents:
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209 } |
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parents:
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210 // vim:set ts=4 sw=4 si et sta sts=4 fenc=utf8 : |