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comparison flys-artifacts/src/main/java/de/intevation/flys/artifacts/model/sq/Fitting.java @ 3188:1e46ced2bb57

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SQ: Added fitting shell for SQ curves. flys-artifacts/trunk@4803 c6561f87-3c4e-4783-a992-168aeb5c3f6f
author Sascha L. Teichmann <sascha.teichmann@intevation.de>
date Tue, 26 Jun 2012 17:05:11 +0000
parents
children 49fe2ed03c12
comparison
equal deleted inserted replaced
3187:1e2733f749b5 3188:1e46ced2bb57
1 package de.intevation.flys.artifacts.model.sq;
2
3 import de.intevation.flys.artifacts.math.fitting.Function;
4
5 import java.util.ArrayList;
6 import java.util.Iterator;
7 import java.util.List;
8
9 import org.apache.commons.math.MathException;
10
11 import org.apache.commons.math.optimization.fitting.CurveFitter;
12
13 import org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer;
14
15 import org.apache.log4j.Logger;
16
17 public class Fitting
18 {
19 private static Logger log = Logger.getLogger(Fitting.class);
20
21 protected Function function;
22
23 protected double [] parameters;
24
25 protected double stdDevFactor;
26
27 protected double standardDeviation;
28
29 protected double chiSqr;
30
31 protected List<SQ> remaining;
32
33 protected List<List<SQ>> outliers;
34
35 public Fitting() {
36 }
37
38 public Fitting(Function function, double stdDevFactor) {
39 this.function = function;
40 this.stdDevFactor = stdDevFactor;
41 }
42
43 public Function getFunction() {
44 return function;
45 }
46
47 public void setFunction(Function function) {
48 this.function = function;
49 }
50
51 public double [] getParameters() {
52 return parameters;
53 }
54
55 public void setParameters(double [] parameters) {
56 this.parameters = parameters;
57 }
58
59 public double getStdDevFactor() {
60 return stdDevFactor;
61 }
62
63 public void setStdDevFactor(double stdDevFactor) {
64 this.stdDevFactor = stdDevFactor;
65 }
66
67 public double getStandardDeviation() {
68 return standardDeviation;
69 }
70
71 public void setStandardDeviation(double standardDeviation) {
72 this.standardDeviation = standardDeviation;
73 }
74
75 public double getChiSqr() {
76 return chiSqr;
77 }
78
79 public void setChiSqr(double chiSqr) {
80 this.chiSqr = chiSqr;
81 }
82
83 public List<SQ> getRemaining() {
84 return remaining;
85 }
86
87 public void setRemaining(List<SQ> remaining) {
88 this.remaining = remaining;
89 }
90
91 public List<List<SQ>> getOutliers() {
92 return outliers;
93 }
94
95 public void setOutliers(List<List<SQ>> outliers) {
96 this.outliers = outliers;
97 }
98
99 public void reset() {
100 outliers = null;
101 remaining = null;
102 parameters = null;
103 standardDeviation = 0d;
104 standardDeviation = 0d;
105 chiSqr = 0d;
106 }
107
108 protected static final List<SQ> onlyValid(List<SQ> sqs) {
109
110 List<SQ> good = new ArrayList<SQ>(sqs.size());
111
112 for (SQ sq: sqs) {
113 if (sq.isValid()) {
114 good.add(sq);
115 }
116 }
117
118 return good;
119 }
120
121 public boolean fit(List<SQ> sqs) {
122
123 sqs = onlyValid(sqs);
124
125 if (sqs.size() < 2) {
126 log.warn("Too less points for fitting.");
127 return false;
128 }
129
130 final LevenbergMarquardtOptimizer lmo =
131 new LevenbergMarquardtOptimizer();
132
133 CurveFitter cf = new CurveFitter(lmo);
134
135 for (SQ sq: sqs) {
136 cf.addObservedPoint(sq.getQ(), sq.getS());
137 }
138
139 try {
140 parameters = cf.fit(function, function.getInitialGuess());
141 }
142 catch (MathException me) {
143 log.warn(me);
144 return false;
145 }
146
147 chiSqr = lmo.getChiSquare();
148
149 final de.intevation.flys.artifacts.math.Function [] instance = {
150 function.instantiate(parameters)
151 };
152
153 try {
154 remaining = Outlier.detectOutliers(
155 new Outlier.Callback() {
156
157 List<List<SQ>> outliers =
158 new ArrayList<List<SQ>>();
159
160 int currentIteration;
161
162 @Override
163 public double eval(SQ sq) {
164 double s = instance[0].value(sq.q);
165 return s - sq.s;
166 }
167
168 @Override
169 public void iteration(int i) {
170 currentIteration = i;
171 }
172
173 @Override
174 public void outlier(SQ sq) {
175 if (currentIteration > outliers.size()) {
176 outliers.add(new ArrayList<SQ>(2));
177 }
178 outliers.get(currentIteration-1).add(sq);
179 }
180
181 @Override
182 public void standardDeviation(double stdDev) {
183 setStandardDeviation(stdDev);
184 }
185
186 @Override
187 public void reinitialize(Iterator<SQ> good)
188 throws MathException
189 {
190 CurveFitter cf = new CurveFitter(lmo);
191 while (good.hasNext()) {
192 SQ sq = good.next();
193 cf.addObservedPoint(sq.getQ(), sq.getS());
194 }
195
196 parameters = cf.fit(
197 function, function.getInitialGuess());
198
199 instance[0] = function.instantiate(parameters);
200
201 chiSqr = lmo.getChiSquare();
202 }
203
204 @Override
205 public void finished() {
206 setOutliers(outliers);
207 }
208 },
209 sqs,
210 stdDevFactor);
211 }
212 catch (MathException me) {
213 log.warn(me);
214 return false;
215 }
216
217 return true;
218 }
219 }
220 // vim:set ts=4 sw=4 si et sta sts=4 fenc=utf8 :
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