Mercurial > dive4elements > river

annotate artifacts/src/main/java/org/dive4elements/river/artifacts/model/sq/Fitting.java @ 6780:b8f94e865875

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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.
author Sascha L. Teichmann <teichmann@intevation.de>
date Thu, 08 Aug 2013 12:17:03 +0200
parents 48f6780c372d
children 51eb6491c537
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.river.artifacts.math.fitting.Function;
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12
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13 import java.util.ArrayList;
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14 import java.util.List;
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15
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16 import org.apache.commons.math.MathException;
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17
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18 import org.apache.commons.math.optimization.fitting.CurveFitter;
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19
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20 import org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer;
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21 import org.apache.commons.math.stat.regression.SimpleRegression;
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22
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23 import org.apache.log4j.Logger;
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24
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25 public class Fitting
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26 implements Outlier.Callback
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27 {
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28 // XXX: Hack to force linear fitting!
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29 private static final boolean USE_NON_LINEAR_FITTING =
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30 Boolean.getBoolean("minfo.sq.fitting.nonlinear");
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31
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32 private static Logger log = Logger.getLogger(Fitting.class);
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33
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34 public interface Callback {
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35
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36 void afterIteration(
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37 double [] parameters,
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38 SQ [] measurements,
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39 SQ [] outliers,
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40 double standardDeviation,
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41 double chiSqr);
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42 } // interfacte
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43
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44 protected Function function;
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45
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46 protected double [] coeffs;
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47
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48 protected org.dive4elements.river.artifacts.math.Function instance;
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49
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50 protected double stdDevFactor;
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51 protected double chiSqr;
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52
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53 protected Callback callback;
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54
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55 protected SQ.View sqView;
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56
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57 public Fitting() {
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58 }
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59
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60 public Fitting(Function function, double stdDevFactor, SQ.View sqView) {
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61 this.function = function;
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62 this.stdDevFactor = stdDevFactor;
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63 this.sqView = sqView;
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64 }
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65
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66 public Function getFunction() {
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67 return function;
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68 }
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69
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70 public void setFunction(Function function) {
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71 this.function = function;
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72 }
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73
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74 public double getStdDevFactor() {
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75 return stdDevFactor;
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76 }
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77
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78 public void setStdDevFactor(double stdDevFactor) {
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79 this.stdDevFactor = stdDevFactor;
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80 }
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81
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82 @Override
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83 public void initialize(List<SQ> sqs) throws MathException {
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84
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85 if (USE_NON_LINEAR_FITTING
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86 || function.getInitialGuess().length != 2) {
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87 nonLinearFitting(sqs);
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88 }
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89 else {
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90 linearFitting(sqs);
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91 }
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92 }
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93
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94 protected void linearFitting(List<SQ> sqs) {
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95
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96 coeffs = linearRegression(sqs);
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97
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98 instance = function.instantiate(coeffs);
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99 }
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100
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101 protected double [] linearRegression(List<SQ> sqs) {
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102
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103 SimpleRegression reg = new SimpleRegression();
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104
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105 int invalidPoints = 0;
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106 for (SQ sq: sqs) {
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107 double s = sq.getS();
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108 double q = sq.getQ();
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109 if (s <= 0d || q <= 0d) {
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110 ++invalidPoints;
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111 continue;
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112 }
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113 reg.addData(Math.log(q), Math.log(s));
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114 }
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115
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116 if (sqs.size() - invalidPoints < 2) {
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117 log.debug("not enough points");
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118 return new double [] { 0, 0 };
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119 }
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120
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121 double a = Math.exp(reg.getIntercept());
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122 double b = reg.getSlope();
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123
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124 if (log.isDebugEnabled()) {
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125 log.debug("invalid points: " +
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126 invalidPoints + " (" + sqs.size() + ")");
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127 log.debug("a: " + a + " (" + Math.log(a) + ")");
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128 log.debug("b: " + b);
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129 }
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130
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131 return new double [] { a, b };
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132 }
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133
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134
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135 protected void nonLinearFitting(List<SQ> sqs) throws MathException {
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136
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137 LevenbergMarquardtOptimizer optimizer =
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138 new LevenbergMarquardtOptimizer();
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139
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140 CurveFitter cf = new CurveFitter(optimizer);
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141
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142 for (SQ sq: sqs) {
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143 cf.addObservedPoint(sq.getS(), sq.getQ());
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144 }
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145
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146 coeffs = cf.fit(
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147 function, function.getInitialGuess());
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148
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149 instance = function.instantiate(coeffs);
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150
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151 chiSqr = optimizer.getChiSquare();
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152 }
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153
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154 @Override
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155 public double eval(SQ sq) {
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156 double s = instance.value(sqView.getQ(sq));
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157 return sqView.getS(sq) - s;
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158 }
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159
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160 @Override
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161 public void iterationFinished(
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162 double standardDeviation,
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163 SQ outlier,
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164 List<SQ> remainings
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165 ) {
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166 if (log.isDebugEnabled()) {
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167 log.debug("iterationFinished ----");
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168 log.debug(" num remainings: " + remainings.size());
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169 log.debug(" has outlier: " + outlier != null);
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170 log.debug(" standardDeviation: " + standardDeviation);
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171 log.debug(" Chi^2: " + chiSqr);
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172 log.debug("---- iterationFinished");
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173 }
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174 callback.afterIteration(
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175 coeffs,
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176 remainings.toArray(new SQ[remainings.size()]),
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177 outlier != null ? new SQ [] { outlier} : new SQ [] {},
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178 standardDeviation,
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179 chiSqr);
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180 }
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181
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182 public boolean fit(List<SQ> sqs, String method, Callback callback) {
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183
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184 if (sqs.size() < 2) {
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185 log.warn("Too less points for fitting.");
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186 return false;
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187 }
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188
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189 sqs = new ArrayList<SQ>(sqs);
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190
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191 this.callback = callback;
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192
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193 try {
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194 Outlier.detectOutliers(this, sqs, stdDevFactor, method);
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195 }
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196 catch (MathException me) {
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197 log.warn(me);
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198 return false;
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199 }
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200
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201 return true;
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202 }
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203 }
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204 // vim:set ts=4 sw=4 si et sta sts=4 fenc=utf8 :
http://dive4elements.wald.intevation.org