Mercurial > dive4elements > river

annotate flys-artifacts/src/main/java/de/intevation/flys/artifacts/model/fixings/FixCalculation.java @ 3603:d2ae58f6730d

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FixA: Use the column cache to establish a consistent index scheme. flys-artifacts/trunk@5229 c6561f87-3c4e-4783-a992-168aeb5c3f6f
author Sascha L. Teichmann <sascha.teichmann@intevation.de>
date Wed, 22 Aug 2012 10:51:29 +0000
parents b5eec54bd4a2
children 2382b26079ac
rev   line source
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da7cf0e3ccaa FixA: Created a common base class for the fixing related calculations.
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parents:
diff changeset
1 package de.intevation.flys.artifacts.model.fixings;
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2
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3 import de.intevation.artifacts.common.utils.StringUtils;
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4
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5 import de.intevation.flys.artifacts.access.FixAccess;
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6
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parents: 3434
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7 import de.intevation.flys.artifacts.math.fitting.Function;
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8 import de.intevation.flys.artifacts.math.fitting.FunctionFactory;
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9
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10 import de.intevation.flys.artifacts.model.Calculation;
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11 import de.intevation.flys.artifacts.model.CalculationResult;
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12 import de.intevation.flys.artifacts.model.FixingsColumn;
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13 import de.intevation.flys.artifacts.model.FixingsColumnFactory;
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14
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15 import de.intevation.flys.artifacts.model.FixingsOverview.Fixing.Filter;
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16
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17 import de.intevation.flys.artifacts.model.FixingsOverview.Fixing;
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18 import de.intevation.flys.artifacts.model.FixingsOverview.IdsFilter;
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20 import de.intevation.flys.artifacts.model.FixingsOverview;
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21 import de.intevation.flys.artifacts.model.FixingsOverviewFactory;
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parents: 3434
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22 import de.intevation.flys.artifacts.model.Parameters;
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23
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24 import de.intevation.flys.utils.DoubleUtil;
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25 import de.intevation.flys.utils.KMIndex;
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26
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27 import java.util.ArrayList;
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28 import java.util.Date;
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29 import java.util.HashMap;
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30 import java.util.List;
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31 import java.util.Map;
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32
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33 import org.apache.log4j.Logger;
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34
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35 public abstract class FixCalculation
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36 extends Calculation
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37 {
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38 private static Logger log = Logger.getLogger(FixCalculation.class);
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parents:
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39
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40 public static final double EPSILON = 1e-4;
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41
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42 public static final String [] STANDARD_COLUMNS = {
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43 "km", "chi_sqr", "max_q", "std-dev"
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44 };
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45
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46 protected static class FitResult {
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47
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parents: 3434
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48 protected Parameters parameters;
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49 protected KMIndex<QWD []> referenced;
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50 protected KMIndex<QW []> outliers;
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51
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52 public FitResult() {
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parents: 3434
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53 }
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parents: 3434
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54
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parents: 3434
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55 public FitResult(
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56 Parameters parameters,
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57 KMIndex<QWD []> referenced,
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58 KMIndex<QW []> outliers
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59 ) {
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60 this.parameters = parameters;
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61 this.referenced = referenced;
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62 this.outliers = outliers;
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63 }
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64
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65 public Parameters getParameters() {
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66 return parameters;
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67 }
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68
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69 public KMIndex<QWD []> getReferenced() {
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70 return referenced;
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71 }
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72
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73 public KMIndex<QW []> getOutliers() {
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74 return outliers;
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75 }
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76 } // class FitResult
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77
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78 /** Helper class to bundle the meta information of a column
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79 * and the real data.
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80 */
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81 protected static class Column {
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82
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83 protected Fixing.Column meta;
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84 protected FixingsColumn data;
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85 protected int index;
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86
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87 public Column() {
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88 }
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89
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90 public Column(Fixing.Column meta, FixingsColumn data, int index) {
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91 this.meta = meta;
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92 this.data = data;
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93 this.index = index;
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94 }
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95
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96 public Date getDate() {
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97 return meta.getStartTime();
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98 }
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99
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100 public String getDescription() {
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101 return meta.getDescription();
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102 }
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103
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104 public int getIndex() {
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105 return index;
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106 }
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107
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108 public boolean getQW(
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109 double km,
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110 double [] qs,
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111 double [] ws,
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112 int index
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113 ) {
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114 qs[index] = data.getQ(km);
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115 return data.getW(km, ws, index);
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116 }
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117
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118 public boolean getQW(double km, double [] wq) {
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119 data.getW(km, wq, 0);
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120 if (Double.isNaN(wq[0])) return false;
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121 wq[1] = data.getQ(km);
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122 return !Double.isNaN(wq[1]);
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123 }
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124 } // class Column
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125
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126 /**
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127 * Helper class to find the data belonging to meta info more quickly.
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128 */
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129 protected static class ColumnCache {
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130
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131 protected Map<Integer, Column> columns;
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132
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133 public ColumnCache() {
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134 columns = new HashMap<Integer, Column>();
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135 }
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136
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137 public Column getColumn(Fixing.Column meta) {
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138 Integer key = meta.getId();
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139 Column column = columns.get(key);
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140 if (column == null) {
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141 FixingsColumn data = FixingsColumnFactory
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142 .getInstance()
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143 .getColumnData(meta);
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144 if (data != null) {
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145 column = new Column(meta, data, columns.size());
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146 columns.put(key, column);
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147 }
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148 }
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149 return column;
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150 }
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151 } // class ColumnCache
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152
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153
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154 protected String river;
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155 protected double from;
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156 protected double to;
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157 protected double step;
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158 protected boolean preprocessing;
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159 protected String function;
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160 protected int [] events;
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161 protected int qSectorStart;
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162 protected int qSectorEnd;
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163
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164 public FixCalculation() {
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165 }
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166
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167 public FixCalculation(FixAccess access) {
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168 String river = access.getRiver();
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169 Double from = access.getFrom();
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170 Double to = access.getTo();
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171 Double step = access.getStep();
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172 String function = access.getFunction();
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173 int [] events = access.getEvents();
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174 Integer qSectorStart = access.getQSectorStart();
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175 Integer qSectorEnd = access.getQSectorEnd();
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176 Boolean preprocessing = access.getPreprocessing();
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177
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178 if (river == null) {
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179 addProblem("fix.missing.river");
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180 }
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181
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182 if (from == null) {
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183 addProblem("fix.missing.from");
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184 }
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185
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186 if (to == null) {
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187 addProblem("fix.missing.to");
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188 }
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189
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190 if (step == null) {
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191 addProblem("fix.missing.step");
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192 }
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193
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194 if (function == null) {
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195 addProblem("fix.missing.function");
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196 }
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197
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198 if (events == null || events.length < 1) {
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199 addProblem("fix.missing.events");
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200 }
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201
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202 if (qSectorStart == null) {
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203 addProblem("fix.missing.qstart.sector");
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204 }
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205
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206 if (qSectorEnd == null) {
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207 addProblem("fix.missing.qend.sector");
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208 }
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209
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210 if (preprocessing == null) {
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211 addProblem("fix.missing.preprocessing");
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212 }
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213
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214 if (!hasProblems()) {
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215 this.river = river;
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216 this.from = from;
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217 this.to = to;
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218 this.step = step;
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219 this.function = function;
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220 this.events = events;
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221 this.qSectorStart = qSectorStart;
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222 this.qSectorEnd = qSectorEnd;
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223 this.preprocessing = preprocessing;
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224 }
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225 }
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226
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227 protected static String toString(
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228 String [] parameterNames,
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229 double [] values
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230 ) {
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231 StringBuilder sb = new StringBuilder();
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232 for (int i = 0; i < parameterNames.length; ++i) {
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233 if (i > 0) sb.append(", ");
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234 sb.append(parameterNames[i]).append(": ").append(values[i]);
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235 }
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236 return sb.toString();
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237 }
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238
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239 protected Filter createFilter() {
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240 return new IdsFilter(events);
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241 }
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242
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243 protected List<Column> getEventColumns(
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244 FixingsOverview overview,
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245 ColumnCache cc
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246 ) {
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247 FixingsColumnFactory fcf = FixingsColumnFactory.getInstance();
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248
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249 Filter filter = createFilter();
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250
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251 List<Fixing.Column> metas = overview.filter(null, filter);
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252
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253 List<Column> columns = new ArrayList<Column>(metas.size());
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254
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255 for (Fixing.Column meta: metas) {
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256
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257 Column data = cc.getColumn(meta);
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258 if (data == null) {
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259 addProblem("fix.cannot.load.data");
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260 }
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261 else {
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262 columns.add(data);
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263 }
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264 }
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265
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266 return columns;
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267 }
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268
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269 protected FitResult doFitting(
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270 FixingsOverview overview,
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271 ColumnCache cc,
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272 Function func
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273 ) {
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274 boolean debug = log.isDebugEnabled();
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275
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276 final List<Column> eventColumns = getEventColumns(overview, cc);
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277
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278 if (eventColumns.size() < 2) {
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279 addProblem("fix.too.less.data.columns");
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280 return null;
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281 }
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282
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283 final double [] qs = new double[eventColumns.size()];
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284 final double [] ws = new double[qs.length];
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285 final boolean [] interpolated = new boolean[ws.length];
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286
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287 Fitting.QWDFactory qwdFactory = new Fitting.QWDFactory() {
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288 @Override
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289 public QWD create(double q, double w) {
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290 // Check all the event columns for close match
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291 // and take the description and the date from meta.
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292 for (int i = 0; i < qs.length; ++i) {
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293 if (Math.abs(qs[i]-q) < EPSILON
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294 && Math.abs(ws[i]-w) < EPSILON) {
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295 Column column = eventColumns.get(i);
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296 return new QWD(
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297 qs[i], ws[i],
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298 column.getDescription(),
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299 column.getDate(),
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300 interpolated[i],
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301 0d);
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302 }
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303 }
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304 log.warn("cannot find column for (" + q + ", " + w + ")");
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305 return new QWD(q, w);
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306 }
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307 };
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308
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309 Fitting fitting = new Fitting(func, qwdFactory, preprocessing);
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310
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311 String [] parameterNames = func.getParameterNames();
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312
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313 Parameters results =
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314 new Parameters(
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315 StringUtils.join(STANDARD_COLUMNS, parameterNames));
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316
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317 boolean invalid = false;
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318
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319 double [] kms = DoubleUtil.explode(from, to, step / 1000.0);
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320
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321 if (debug) {
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322 log.debug("number of kms: " + kms.length);
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323 }
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324
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325 KMIndex<QW []> outliers = new KMIndex<QW []>();
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326 KMIndex<QWD []> referenced = new KMIndex<QWD []>(kms.length);
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327
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328 int kmIndex = results.columnIndex("km");
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329 int chiSqrIndex = results.columnIndex("chi_sqr");
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330 int maxQIndex = results.columnIndex("max_q");
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331 int stdDevIndex = results.columnIndex("std-dev");
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332 int [] parameterIndices = results.columnIndices(parameterNames);
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333
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334 int numFailed = 0;
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335
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336 for (int i = 0; i < kms.length; ++i) {
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337 double km = kms[i];
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338
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339 // Fill Qs and Ws from event columns.
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340 for (int j = 0; j < ws.length; ++j) {
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341 interpolated[j] = !eventColumns.get(j).getQW(km, qs, ws, j);
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342 }
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343
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344 fitting.reset();
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345
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346 if (!fitting.fit(qs, ws)) {
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347 ++numFailed;
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348 addProblem(km, "fix.fitting.failed");
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349 continue;
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350 }
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351
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352 referenced.add(km, fitting.referencedToArray());
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353
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354 if (fitting.hasOutliers()) {
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355 outliers.add(km, fitting.outliersToArray());
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356 }
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357
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358 int row = results.newRow();
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359 double [] values = fitting.getParameters();
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360
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361 results.set(row, kmIndex, km);
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362 results.set(row, chiSqrIndex, fitting.getChiSquare());
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363 results.set(row, stdDevIndex, fitting.getStandardDeviation());
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364 results.set(row, maxQIndex, fitting.getMaxQ());
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365 invalid |= results.set(row, parameterIndices, values);
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366
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367 if (debug) {
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368 log.debug("km: "+km+" " + toString(parameterNames, values));
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369 }
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370 }
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371
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372 if (debug) {
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373 log.debug("success: " + (kms.length - numFailed));
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374 log.debug("failed: " + numFailed);
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375 }
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376
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377 if (invalid) {
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378 addProblem("fix.invalid.values");
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379 results.removeNaNs();
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380 }
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381
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382 outliers.sort();
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383 referenced.sort();
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384
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385 return new FitResult(
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386 results,
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387 referenced,
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388 outliers);
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389 }
3437
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390
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391 public CalculationResult calculate() {
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392 FixingsOverview overview =
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393 FixingsOverviewFactory.getOverview(river);
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394
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395 if (overview == null) {
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396 addProblem("fix.no.overview.available");
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397 }
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398
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399 Function func = FunctionFactory.getInstance()
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400 .getFunction(function);
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401
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402 if (func == null) {
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403 addProblem("fix.invalid.function.name");
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404 }
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405
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406 if (hasProblems()) {
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407 return new CalculationResult(this);
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408 }
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409
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410 return innerCalculate(overview, func);
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411 }
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412
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413 protected abstract CalculationResult innerCalculate(
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414 FixingsOverview overview,
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415 Function function
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416 );
3419
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parents:
diff changeset
417 }
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parents:
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418 // vim:set ts=4 sw=4 si et sta sts=4 fenc=utf8 :
http://dive4elements.wald.intevation.org