Mercurial > dive4elements > river
annotate flys-artifacts/src/main/java/de/intevation/flys/artifacts/model/fixings/FixCalculation.java @ 4699:756aba0d2a7a
Removed unneeded imports.
author | Sascha L. Teichmann <teichmann@intevation.de> |
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date | Mon, 17 Dec 2012 17:57:32 +0100 |
parents | 3cda41b5eb23 |
children | 345f3bba6f15 |
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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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FixA: Created a common base class for the fixing related calculations.
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5 import de.intevation.flys.artifacts.access.FixAccess; |
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6 |
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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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19 |
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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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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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FixA: Made calculation base class abstract. Sub classes are called with fixings overview an function to fit.
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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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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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48 protected Parameters parameters; |
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49 protected KMIndex<QWD []> referenced; |
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50 protected KMIndex<QWI []> outliers; |
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51 |
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52 public FitResult() { |
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53 } |
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54 |
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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<QWI []> 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<QWI []> 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 column.getIndex()); |
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303 } |
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304 } |
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305 log.warn("cannot find column for (" + q + ", " + w + ")"); |
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306 return new QWD(q, w); |
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307 } |
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308 }; |
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309 |
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310 Fitting fitting = new Fitting(func, qwdFactory, preprocessing); |
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311 |
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312 String [] parameterNames = func.getParameterNames(); |
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313 |
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314 Parameters results = |
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315 new Parameters( |
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316 StringUtils.join(STANDARD_COLUMNS, parameterNames)); |
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317 |
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318 boolean invalid = false; |
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319 |
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320 double [] kms = DoubleUtil.explode(from, to, step / 1000.0); |
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321 |
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322 if (debug) { |
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323 log.debug("number of kms: " + kms.length); |
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324 } |
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325 |
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326 KMIndex<QWI []> outliers = new KMIndex<QWI []>(); |
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327 KMIndex<QWD []> referenced = new KMIndex<QWD []>(kms.length); |
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328 |
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329 int kmIndex = results.columnIndex("km"); |
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330 int chiSqrIndex = results.columnIndex("chi_sqr"); |
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331 int maxQIndex = results.columnIndex("max_q"); |
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332 int stdDevIndex = results.columnIndex("std-dev"); |
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333 int [] parameterIndices = results.columnIndices(parameterNames); |
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334 |
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335 int numFailed = 0; |
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336 |
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337 for (int i = 0; i < kms.length; ++i) { |
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338 double km = kms[i]; |
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339 |
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340 // Fill Qs and Ws from event columns. |
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341 for (int j = 0; j < ws.length; ++j) { |
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342 interpolated[j] = !eventColumns.get(j).getQW(km, qs, ws, j); |
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343 } |
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344 |
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345 fitting.reset(); |
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346 |
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347 if (!fitting.fit(qs, ws)) { |
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348 ++numFailed; |
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349 addProblem(km, "fix.fitting.failed"); |
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350 continue; |
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351 } |
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352 |
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353 referenced.add(km, fitting.referencedToArray()); |
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354 |
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355 if (fitting.hasOutliers()) { |
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356 outliers.add(km, fitting.outliersToArray()); |
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357 } |
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358 |
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359 int row = results.newRow(); |
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360 double [] values = fitting.getParameters(); |
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361 |
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362 results.set(row, kmIndex, km); |
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363 results.set(row, chiSqrIndex, fitting.getChiSquare()); |
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364 results.set(row, stdDevIndex, fitting.getStandardDeviation()); |
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365 results.set(row, maxQIndex, fitting.getMaxQ()); |
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366 invalid |= results.set(row, parameterIndices, values); |
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367 |
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368 if (debug) { |
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369 log.debug("km: "+km+" " + toString(parameterNames, values)); |
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370 } |
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371 } |
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372 |
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373 if (debug) { |
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374 log.debug("success: " + (kms.length - numFailed)); |
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375 log.debug("failed: " + numFailed); |
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376 } |
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377 |
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378 if (invalid) { |
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379 addProblem("fix.invalid.values"); |
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380 results.removeNaNs(); |
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381 } |
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382 |
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383 outliers.sort(); |
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384 referenced.sort(); |
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385 |
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386 return new FitResult( |
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387 results, |
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388 referenced, |
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389 outliers); |
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390 } |
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391 |
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392 public CalculationResult calculate() { |
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393 FixingsOverview overview = |
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394 FixingsOverviewFactory.getOverview(river); |
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395 |
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396 if (overview == null) { |
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397 addProblem("fix.no.overview.available"); |
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398 } |
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399 |
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400 Function func = FunctionFactory.getInstance() |
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401 .getFunction(function); |
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402 |
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403 if (func == null) { |
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404 addProblem("fix.invalid.function.name"); |
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405 } |
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406 |
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407 if (hasProblems()) { |
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408 return new CalculationResult(this); |
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409 } |
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410 |
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411 return innerCalculate(overview, func); |
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412 } |
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413 |
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414 protected abstract CalculationResult innerCalculate( |
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415 FixingsOverview overview, |
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416 Function function |
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417 ); |
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418 } |
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419 // vim:set ts=4 sw=4 si et sta sts=4 fenc=utf8 : |