Mercurial > dive4elements > river
annotate flys-artifacts/src/main/java/de/intevation/flys/artifacts/model/WstValueTable.java @ 365:c13ca9d632d6
Introduced GNU Trove to store WQKms values in a more performant data structure.
flys-artifacts/trunk@1773 c6561f87-3c4e-4783-a992-168aeb5c3f6f
author | Ingo Weinzierl <ingo.weinzierl@intevation.de> |
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date | Fri, 29 Apr 2011 08:28:44 +0000 |
parents | 3571357c85a7 |
children | fc3cf0ef777e |
rev | line source |
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1 package de.intevation.flys.artifacts.model; |
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2 |
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3 import java.io.Serializable; |
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4 |
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5 import de.intevation.flys.model.River; |
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6 import de.intevation.flys.model.Wst; |
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7 import de.intevation.flys.model.WstColumn; |
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8 |
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9 import de.intevation.flys.backend.SessionHolder; |
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11 import java.util.Arrays; |
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12 import java.util.ArrayList; |
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13 import java.util.Comparator; |
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14 import java.util.List; |
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15 import java.util.Collections; |
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16 import java.util.Iterator; |
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17 |
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18 import org.apache.log4j.Logger; |
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19 |
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20 import org.apache.commons.math.analysis.interpolation.SplineInterpolator; |
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21 |
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22 import org.apache.commons.math.analysis.polynomials.PolynomialSplineFunction; |
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23 |
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24 import org.apache.commons.math.ArgumentOutsideDomainException; |
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25 |
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26 import org.hibernate.Session; |
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27 import org.hibernate.Query; |
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28 import org.hibernate.SQLQuery; |
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29 |
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30 import org.hibernate.type.StandardBasicTypes; |
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31 |
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32 public class WstValueTable |
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33 implements Serializable |
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34 { |
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35 private static Logger log = Logger.getLogger(WstValueTable.class); |
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36 |
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37 // TODO: put this into a property file |
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38 public static final String SQL_POS_WQ = |
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39 "SELECT position, w, q, column_pos" + |
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40 " FROM wst_value_table" + |
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41 " WHERE wst_id = :wst_id"; |
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42 |
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43 public static final double DEFAULT_STEP_WIDTH = 0.01; |
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44 |
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45 public static class Column |
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46 implements Serializable |
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47 { |
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48 protected String name; |
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49 |
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50 public Column() { |
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51 } |
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52 |
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53 public Column(String name) { |
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54 this.name = name; |
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55 } |
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56 |
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57 public String getName() { |
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58 return name; |
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59 } |
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60 |
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61 public void setName(String name) { |
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62 this.name = name; |
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63 } |
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64 } |
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65 // class Column |
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66 |
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67 public static class Row |
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68 implements Serializable, Comparable<Row> |
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69 { |
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70 double km; |
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71 double [] ws; |
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72 double [] qs; |
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73 boolean qSorted; |
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74 |
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75 public Row() { |
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76 } |
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77 |
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78 public Row(double km) { |
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79 this.km = km; |
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80 } |
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81 |
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82 public Row(double km, double [] ws, double [] qs) { |
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83 this(km); |
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84 this.ws = ws; |
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85 this.qs = qs; |
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86 } |
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87 |
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88 public static final double linear( |
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89 double x, |
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90 double x1, double x2, |
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91 double y1, double y2 |
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92 ) { |
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93 // y1 = m*x1 + b |
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94 // y2 = m*x2 + b |
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95 // y2 - y1 = m*(x2 - x1) |
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96 // m = (y2 - y1)/(x2 - x1) # x2 != x1 |
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97 // b = y1 - m*x1 |
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98 |
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99 if (x1 == x2) { |
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100 return 0.5*(y1 + y2); |
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101 } |
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102 double m = (y2 - y1)/(x2 - x1); |
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103 double b = y1 - m*x1; |
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104 return x*m + b; |
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105 } |
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106 |
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107 public static final double factor(double x, double p1, double p2) { |
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108 // 0 = m*p1 + b <=> b = -m*p1 |
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109 // 1 = m*p2 + b |
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110 // 1 = m*(p2 - p1) |
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111 // m = 1/(p2 - p1) # p1 != p2 |
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112 // f(x) = x/(p2-p1) - p1/(p2-p1) <=> (x-p1)/(p2-p1) |
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113 |
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114 return p1 == p2 ? 0.0 : (x-p1)/(p2-p1); |
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115 } |
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116 |
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117 public static final double weight(double factor, double a, double b) { |
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118 return (1.0-factor)*a + factor*b; |
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119 } |
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120 |
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121 public double getWForKM(Row other, int index, double km) { |
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122 double w1 = ws[index]; |
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123 double w2 = other.ws[index]; |
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124 double km1 = this.km; |
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125 double km2 = other.km; |
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126 return linear(km, km1, km2, w1, w2); |
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127 } |
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128 |
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129 public void interpolateW( |
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130 Row other, |
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131 double km, |
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132 double [] input, |
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133 double [] output |
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134 ) { |
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135 double factor = factor(km, this.km, other.km); |
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136 |
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137 for (int i = 0; i < input.length; ++i) { |
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138 double q = input[i]; |
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139 int idx1 = getQIndex(q); |
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140 int idx2 = other.getQIndex(q); |
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141 |
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142 double w1 = idx1 >= 0 |
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143 ? ws[idx1] |
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144 : interpolateW(-idx1-1, q); |
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145 |
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146 double w2 = idx2 >= 0 |
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147 ? other.ws[idx2] |
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148 : other.interpolateW(-idx2-1, q); |
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149 |
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150 output[i] = weight(factor, w1, w2); |
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151 } |
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152 } |
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153 |
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154 public double interpolateW(int idx, double q) { |
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155 return idx < 1 || idx >= qs.length |
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156 ? Double.NaN // do not extrapolate |
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157 : linear(q, qs[idx-1], qs[idx], ws[idx-1], ws[idx]); |
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158 } |
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159 |
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160 public double interpolateW(double q) { |
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161 if (Double.isNaN(q)) return Double.NaN; |
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162 int index = getQIndex(q); |
360
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163 return index >= 0 ? ws[index] : interpolateW(-index -1, q); |
335
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164 } |
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165 |
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166 public int getQIndex(double q) { |
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167 return qSorted ? binaryQIndex(q) : linearQIndex(q); |
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168 } |
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169 |
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170 public int binaryQIndex(double q) { |
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171 return Arrays.binarySearch(qs, q); |
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172 } |
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173 |
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174 public int linearQIndex(double q) { |
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175 switch (qs.length) { |
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176 case 0: break; |
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177 case 1: |
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178 if (qs[0] == q) return 0; |
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179 if (qs[0] < q) return -(1+1); |
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180 return -(0+1); |
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181 default: |
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182 for (int i = 1; i < qs.length; ++i) { |
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183 double qa = qs[i-1]; |
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184 double qb = qs[i]; |
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185 if (qa == q) return i-1; |
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186 if (qb == q) return i; |
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187 if (qa > qb) { double t = qa; qa = qb; qb = t; } |
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188 if (q > qa && q < qb) return -(i+1); |
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189 } |
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190 return -qs.length; |
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191 } |
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192 |
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193 return -1; |
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194 } |
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195 |
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196 public int compareTo(Row other) { |
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197 double d = km - other.km; |
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198 if (d < 0.0) return -1; |
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199 if (d > 0.0) return +1; |
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200 return 0; |
326
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Fetches w/q value tables from the backend.
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201 } |
339
4509ba8fae68
Implementation of "Abflusskurve/Abflusstafel" calculation.
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202 |
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203 public double [][] cloneWQs() { |
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204 return new double [][] { |
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205 (double [])ws.clone(), |
344
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206 (double [])qs.clone() }; |
339
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207 } |
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208 |
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209 public double [][] interpolateWQ(Row other, double km, double stepWidth) { |
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210 |
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211 int W1 = ascendingWs(); |
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212 int W2 = other.ascendingWs(); |
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213 |
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214 int W = Math.min(W1, W2); |
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215 |
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216 if (W < 1) { |
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217 return new double[2][0]; |
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218 } |
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219 |
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220 double factor = factor(km, this.km, other.km); |
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221 |
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222 double minW = weight(factor, ws[0], other.ws[0]); |
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223 double maxW = weight(factor, ws[W-1], other.ws[W-1]); |
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224 |
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225 if (minW > maxW) { |
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226 double t = minW; |
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227 minW = maxW; |
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228 maxW = t; |
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229 } |
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230 double [] x = new double[W]; |
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231 double [] y = new double[W]; |
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232 |
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233 for (int i = 0; i < W; ++i) { |
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234 x[i] = weight(factor, ws[i], other.ws[i]); |
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235 y[i] = weight(factor, qs[i], other.qs[i]); |
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236 } |
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237 |
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238 SplineInterpolator interpolator = new SplineInterpolator(); |
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239 PolynomialSplineFunction spline = interpolator.interpolate(x, y); |
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240 |
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241 double [] outWs = |
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242 new double[(int)Math.ceil((maxW - minW)/stepWidth)]; |
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243 double [] outQs = |
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244 new double[outWs.length]; |
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245 |
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246 try { |
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247 double w = minW; |
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248 for (int i = 0; i < outWs.length; ++i, w += stepWidth) { |
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249 outQs[i] = spline.value(outWs[i] = w); |
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250 } |
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251 } |
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252 catch (ArgumentOutsideDomainException aode) { |
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253 log.error("Spline interpolation failed.", aode); |
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254 } |
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255 |
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256 return new double [][] { outWs, outQs }; |
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257 |
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258 } |
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259 |
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260 public double [][] interpolateWQ(double stepWidth) { |
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261 int W = ascendingWs(); // ignore back jumps |
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262 |
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263 if (W < 1) { |
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264 return new double[2][0]; |
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265 } |
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266 |
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267 double [] x = new double[W]; |
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268 double [] y = new double[W]; |
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269 |
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270 for (int i = 0; i < W; ++i) { |
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271 x[i] = ws[i]; |
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272 y[i] = qs[i]; |
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273 } |
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274 |
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275 SplineInterpolator interpolator = new SplineInterpolator(); |
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276 |
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277 PolynomialSplineFunction spline = interpolator.interpolate(x, y); |
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278 |
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279 double minW = ws[0]; |
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280 double maxW = ws[W-1]; |
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281 |
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282 double [] outWs = |
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283 new double[(int)Math.ceil((maxW - minW)/stepWidth)]; |
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284 double [] outQs = |
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285 new double[outWs.length]; |
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286 |
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287 try { |
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288 double w = minW; |
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289 for (int i = 0; i < outWs.length; ++i, w += stepWidth) { |
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290 outQs[i] = spline.value(outWs[i] = w); |
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291 } |
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292 } |
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293 catch (ArgumentOutsideDomainException aode) { |
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294 log.error("Spline interpolation failed.", aode); |
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295 } |
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296 |
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297 return new double [][] { outWs, outQs }; |
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298 } |
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299 |
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300 public int ascendingWs() { |
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301 if (ws.length < 2) { |
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302 return ws.length; |
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303 } |
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304 |
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305 int idx = 1; |
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306 |
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307 for (; idx < ws.length; ++idx) { |
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308 if (Double.isNaN(ws[idx]) || ws[idx] < ws[idx-1]) { |
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309 return idx; |
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310 } |
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311 } |
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312 |
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313 return idx; |
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314 } |
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315 |
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316 public double [][] weightWQs(Row other, double km) { |
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317 int W = Math.min(ws.length, other.ws.length); |
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318 double factor = factor(km, this.km, other.km); |
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319 |
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320 double [] outWs = new double[W]; |
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321 double [] outQs = new double[W]; |
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322 |
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323 for (int i = 0; i < W; ++i) { |
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324 outWs[i] = weight(factor, ws[i], other.ws[i]); |
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325 outQs[i] = weight(factor, qs[i], other.qs[i]); |
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326 } |
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327 |
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328 return new double [][] { outWs, outQs }; |
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329 } |
326
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330 } |
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331 // class Row |
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332 |
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333 protected List<Row> rows; |
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334 |
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335 protected Column [] columns; |
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336 |
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337 public WstValueTable() { |
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338 rows = new ArrayList<Row>(); |
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339 } |
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340 |
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341 public WstValueTable(Column [] columns) { |
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342 this(); |
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343 this.columns = columns; |
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344 } |
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345 |
335
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346 |
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347 public double [] interpolateW(double km, double [] qs) { |
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348 |
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349 double [] ws = new double[qs.length]; |
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350 |
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351 int rowIndex = Collections.binarySearch(rows, new Row(km)); |
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352 |
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353 if (rowIndex >= 0) { // direct row match |
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354 Row row = rows.get(rowIndex); |
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355 for (int i = 0; i < qs.length; ++i) { |
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356 ws[i] = row.interpolateW(qs[i]); |
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357 } |
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358 } |
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359 else { // needs bilinear interpolation |
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360 rowIndex = -rowIndex -1; |
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361 |
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362 if (rowIndex < 1 || rowIndex >= rows.size()) { |
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363 // do not extrapolate |
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364 Arrays.fill(ws, Double.NaN); |
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365 } |
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366 else { |
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367 rows.get(rowIndex-1).interpolateW( |
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368 rows.get(rowIndex), |
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369 km, qs, ws); |
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370 } |
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371 } |
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372 |
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373 return ws; |
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374 } |
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375 |
339
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376 |
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377 public double [][] interpolateWQ(double km) { |
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378 return interpolateWQ(km, DEFAULT_STEP_WIDTH, true); |
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379 } |
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380 |
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381 public double [][] interpolateWQ( |
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382 double km, |
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383 double stepWidth, |
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384 boolean checkAscending |
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385 ) { |
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386 int rowIndex = Collections.binarySearch(rows, new Row(km)); |
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387 |
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388 if (rowIndex >= 0) { // direct row match |
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389 Row row = rows.get(rowIndex); |
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390 return checkAscending |
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391 ? row.interpolateWQ(stepWidth) |
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392 : row.cloneWQs(); |
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393 } |
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394 |
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395 rowIndex = -rowIndex -1; |
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396 |
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397 if (rowIndex < 1 || rowIndex >= rows.size()) { |
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398 // do not extrapolate |
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399 return new double[2][0]; |
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400 } |
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401 |
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402 Row r1 = rows.get(rowIndex-1); |
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403 Row r2 = rows.get(rowIndex); |
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404 |
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405 return checkAscending |
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406 ? r1.interpolateWQ(r2, km, stepWidth) |
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407 : r1.weightWQs(r2, km); |
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408 } |
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409 |
326
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410 public static WstValueTable getTable(River river) { |
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411 return getTable(river, 0); |
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412 } |
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413 |
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414 public static WstValueTable getTable(River river, int kind) { |
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415 |
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416 Session session = SessionHolder.HOLDER.get(); |
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417 |
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418 Query query = session.createQuery( |
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419 "from Wst where river=:river and kind=:kind"); |
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420 query.setParameter("river", river); |
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421 query.setInteger("kind", kind); |
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422 |
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423 List<Wst> wsts = query.list(); |
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424 |
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425 if (wsts.isEmpty()) { |
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426 return null; |
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427 } |
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428 |
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429 Wst wst = wsts.get(0); |
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430 |
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431 // TODO: Do this sorting at database level |
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432 List<WstColumn> wstColumns = new ArrayList(wst.getColumns()); |
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433 Collections.sort(wstColumns, new Comparator<WstColumn>() { |
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434 public int compare(WstColumn a, WstColumn b) { |
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435 int pa = a.getPosition(); |
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436 int pb = b.getPosition(); |
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437 if (pa < pb) return -1; |
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438 if (pa > pb) return +1; |
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439 return 0; |
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440 } |
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441 }); |
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442 |
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443 Column [] columns = new Column[wstColumns.size()]; |
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444 for (int i = 0; i < columns.length; ++i) { |
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445 columns[i] = new Column(wstColumns.get(i).getName()); |
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446 } |
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447 |
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448 // using native SQL here to avoid myriad of small objects. |
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449 SQLQuery sqlQuery = session.createSQLQuery(SQL_POS_WQ) |
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450 .addScalar("position", StandardBasicTypes.DOUBLE) |
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451 .addScalar("w", StandardBasicTypes.DOUBLE) |
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452 .addScalar("q", StandardBasicTypes.DOUBLE) |
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453 .addScalar("column_pos", StandardBasicTypes.INTEGER); |
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454 |
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455 sqlQuery.setInteger("wst_id", wst.getId()); |
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456 |
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457 WstValueTable valueTable = new WstValueTable(columns); |
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458 |
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459 int lastColumnNo = -1; |
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460 Row row = null; |
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461 |
335
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462 Double lastQ = -Double.MAX_VALUE; |
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463 boolean qSorted = true; |
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464 |
360
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Bugfix: Removed endless loop and a bug while iterating over Hibernate results.
Ingo Weinzierl <ingo.weinzierl@intevation.de>
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465 for (Object r: sqlQuery.list()) { |
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Bugfix: Removed endless loop and a bug while iterating over Hibernate results.
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466 Object[] result = (Object[]) r; |
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467 |
326
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468 double km = (Double) result[0]; |
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469 Double w = (Double) result[1]; |
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470 Double q = (Double) result[2]; |
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471 int columnNo = (Integer)result[3]; |
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|
472 |
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473 if (columnNo > lastColumnNo) { // new row |
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474 if (row != null) { |
335
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475 row.qSorted = qSorted; |
326
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476 valueTable.rows.add(row); |
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|
477 } |
335
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478 row = new Row( |
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479 km, |
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480 new double[columnNo+1], |
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481 new double[columnNo+1]); |
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482 lastQ = -Double.MAX_VALUE; |
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483 qSorted = true; |
326
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484 } |
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changeset
|
485 |
335
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486 row.ws[columnNo] = w != null ? w : Double.NaN; |
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487 row.qs[columnNo] = q != null ? q : Double.NaN; |
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|
488 |
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|
489 if (qSorted && (q == null || lastQ > q)) { |
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490 qSorted = false; |
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491 } |
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492 lastQ = q; |
326
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|
493 |
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494 lastColumnNo = columnNo; |
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|
495 } |
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|
496 |
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|
497 if (row != null) { |
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|
498 valueTable.rows.add(row); |
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|
499 } |
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|
500 |
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501 return valueTable; |
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|
502 } |
07eba6d3b4a5
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|
503 } |
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|
504 // vim:set ts=4 sw=4 si et sta sts=4 fenc=utf8 : |