Mercurial > dive4elements > river
annotate flys-artifacts/src/main/java/de/intevation/flys/artifacts/model/Parameters.java @ 4205:0dd8963cec9c
Set also the width of the GaugeTree when resizing the GaugePanel
GWT is no longer able to calculate and set the correct width of the GaugeTree since
the GaugeTree is added via a Canvas wrapper. Therefore set the width manually
when resizing the GaugeTree.
author | Björn Ricks <bjoern.ricks@intevation.de> |
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date | Mon, 22 Oct 2012 15:33:16 +0200 |
parents | 1df6984628c3 |
children | bcf25d8c183e |
rev | line source |
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1 package de.intevation.flys.artifacts.model; |
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2 |
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Parameters: Linear interpolation of parameters.
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3 import de.intevation.flys.artifacts.math.Linear; |
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4 |
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5 import gnu.trove.TDoubleArrayList; |
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6 |
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7 import java.io.Serializable; |
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8 |
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9 import org.apache.log4j.Logger; |
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10 |
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11 public class Parameters |
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12 implements Serializable |
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13 { |
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14 private static Logger log = Logger.getLogger(Parameters.class); |
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15 |
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16 public interface Visitor { |
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17 |
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18 void visit(double [] row); |
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19 |
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20 } // interface Visitor |
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21 |
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22 public static final double EPSILON = 1e-4; |
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23 |
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24 protected String [] columnNames; |
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25 protected TDoubleArrayList [] columns; |
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26 |
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27 public Parameters() { |
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28 } |
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29 |
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30 public Parameters(String [] columnNames) { |
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31 if (columnNames == null || columnNames.length < 1) { |
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32 throw new IllegalArgumentException("columnNames too short."); |
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33 } |
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34 this.columnNames = columnNames; |
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35 columns = new TDoubleArrayList[columnNames.length]; |
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36 for (int i = 0; i < columns.length; ++i) { |
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37 columns[i] = new TDoubleArrayList(); |
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38 } |
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39 } |
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40 |
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41 public int columnIndex(String name) { |
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42 for (int i = 0; i < columnNames.length; ++i) { |
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43 if (columnNames[i].equals(name)) { |
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44 return i; |
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45 } |
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46 } |
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47 if (log.isDebugEnabled()) { |
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48 log.debug("columnIndex: " + name + " not found in columnNames"); |
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49 } |
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50 return -1; |
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51 } |
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52 |
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53 public int newRow() { |
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54 |
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55 int N = columns[0].size(); |
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56 |
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57 for (int i = 0; i < columns.length; ++i) { |
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58 columns[i].add(Double.NaN); |
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59 } |
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60 |
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61 return N; |
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62 } |
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63 |
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64 public double get(int row, int index) { |
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65 return columns[index].getQuick(row); |
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66 } |
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67 |
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68 public double get(int i, String columnName) { |
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69 int index = columnIndex(columnName); |
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70 return index >= 0 |
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71 ? columns[index].getQuick(i) |
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72 : Double.NaN; |
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73 } |
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74 |
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75 public void set(int row, int index, double value) { |
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76 columns[index].setQuick(row, value); |
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77 } |
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78 |
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79 public void set(int i, String columnName, double value) { |
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80 int idx = columnIndex(columnName); |
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81 if (idx >= 0) { |
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82 columns[idx].setQuick(i, value); |
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83 } |
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84 } |
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85 |
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86 public boolean set(int row, int [] indices, double [] values) { |
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87 boolean invalid = false; |
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88 for (int i = 0; i < indices.length; ++i) { |
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89 double v = values[i]; |
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90 if (Double.isNaN(v)) { |
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91 invalid = true; |
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92 } |
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93 else { |
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94 columns[indices[i]].setQuick(row, v); |
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95 } |
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96 } |
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97 return invalid; |
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98 } |
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99 |
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100 public boolean set(int row, String [] names, double [] values) { |
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101 boolean success = true; |
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102 for (int i = 0; i < names.length; ++i) { |
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103 int idx = columnIndex(names[i]); |
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104 if (idx >= 0) { |
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105 columns[idx].setQuick(row, values[i]); |
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106 } |
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107 else { |
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108 success = false; |
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109 } |
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110 } |
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111 return success; |
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112 } |
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113 |
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114 public int size() { |
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115 return columns[0].size(); |
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116 } |
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117 |
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118 public int getNumberColumns() { |
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119 return columnNames.length; |
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120 } |
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121 |
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122 public String [] getColumnNames() { |
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123 return columnNames; |
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124 } |
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125 |
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126 public void removeNaNs() { |
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127 W.removeNaNs(columns); |
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128 } |
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129 |
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130 public int [] columnIndices(String [] columns) { |
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131 int [] indices = new int[columns.length]; |
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132 for (int i = 0; i < columns.length; ++i) { |
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133 indices[i] = columnIndex(columns[i]); |
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134 } |
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135 return indices; |
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136 } |
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137 |
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138 public double getValue(int row, String column) { |
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139 int idx = columnIndex(column); |
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140 return idx >= 0 |
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141 ? columns[idx].getQuick(row) |
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142 : Double.NaN; |
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143 } |
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144 |
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145 public double [] get(int row, String [] columns) { |
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146 return get(row, columns, new double[columns.length]); |
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147 } |
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148 |
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149 public double [] get(int row, String [] columns, double [] values) { |
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150 for (int i = 0; i < columns.length; ++i) { |
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151 int idx = columnIndex(columns[i]); |
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152 values[i] = idx < 0 |
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153 ? Double.NaN |
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154 : this.columns[idx].getQuick(row); |
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155 } |
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156 |
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157 return values; |
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158 } |
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159 |
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160 public void get(int row, int [] columnIndices, double [] values) { |
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161 for (int i = 0; i < columnIndices.length; ++i) { |
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162 int index = columnIndices[i]; |
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163 values[i] = index >= 0 && index < columns.length |
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164 ? columns[index].getQuick(row) |
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165 : Double.NaN; |
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166 } |
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167 } |
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168 |
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169 public int binarySearch(String columnName, double value) { |
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170 return binarySearch(columnIndex(columnName), value); |
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171 } |
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172 |
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173 /** |
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174 * Performes a binary search in the column identified by its |
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175 * index. |
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176 * @return Index of found element or negative insertion point (shifted by one) |
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177 */ |
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178 public int binarySearch(int columnIndex, double value) { |
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179 TDoubleArrayList column = columns[columnIndex]; |
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180 return column.binarySearch(value); |
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181 } |
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182 |
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183 public int binarySearch(String columnName, double value, double epsilon) { |
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184 return binarySearch(columnIndex(columnName), value, epsilon); |
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185 } |
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186 |
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187 public int binarySearch(int columnIndex, double value, double epsilon) { |
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188 if (epsilon < 0d) epsilon = -epsilon; |
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189 double vl = value - epsilon; |
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190 double vh = value + epsilon; |
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191 |
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192 TDoubleArrayList column = columns[columnIndex]; |
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193 int lo = 0, hi = column.size()-1; |
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194 while (hi >= lo) { |
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195 int mid = (lo + hi) >> 1; |
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196 double v = column.getQuick(mid); |
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197 if (v < vl) lo = mid + 1; |
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198 else if (v > vh) hi = mid - 1; |
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199 else return mid; |
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200 } |
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201 |
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202 return -(lo + 1); |
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203 } |
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204 |
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205 public double [] interpolate(int columnIndex, double key) { |
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206 return interpolate(columnIndex, key, new double[columns.length]); |
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207 } |
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208 |
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209 public double [] interpolate(String columnName, double key) { |
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210 return interpolate( |
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211 columnIndex(columnName), key, new double[columns.length]); |
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212 } |
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213 |
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214 public double [] interpolate( |
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215 String columnName, |
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216 double key, |
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217 double [] values |
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218 ) { |
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219 return interpolate(columnIndex(columnName), key, values); |
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220 } |
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221 |
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222 public double [] interpolate( |
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223 int columnIndex, |
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224 double key, |
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225 double [] values |
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226 ) { |
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227 int row = binarySearch(columnIndex, key, EPSILON); |
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228 |
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229 if (row >= 0) { // direct hit |
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230 for (int i = 0; i < values.length; ++i) { |
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231 values[i] = columns[i].getQuick(row); |
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232 } |
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233 } |
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234 else { |
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235 row = -row - 1; |
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236 if (row < 1 || row >= size()) { |
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237 return null; |
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238 } |
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239 double v1 = columns[columnIndex].getQuick(row-1); |
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240 double v2 = columns[columnIndex].getQuick(row); |
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241 double factor = Linear.factor(key, v1, v2); |
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242 for (int i = 0; i < values.length; ++i) { |
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243 values[i] = Linear.weight( |
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244 factor, |
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245 columns[i].getQuick(row-1), |
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246 columns[i].getQuick(row)); |
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247 } |
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248 } |
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249 return values; |
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250 } |
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251 |
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252 |
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253 public double [] interpolate( |
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254 String keyName, |
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255 double key, |
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256 String [] columnNames |
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257 ) { |
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258 int keyIndex = columnIndex(keyName); |
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259 return keyIndex < 0 |
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260 ? null |
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261 : interpolate(keyIndex, key, columnNames); |
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262 } |
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263 |
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264 public double [] interpolate( |
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265 int keyIndex, |
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266 double key, |
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267 String [] columnNames |
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268 ) { |
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269 int row = binarySearch(keyIndex, key, EPSILON); |
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270 |
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271 if (row >= 0) { // direct match |
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272 double [] values = new double[columnNames.length]; |
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273 for (int i = 0; i < values.length; ++i) { |
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274 int ci = columnIndex(columnNames[i]); |
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275 values[i] = ci < 0 |
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276 ? Double.NaN |
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277 : columns[ci].getQuick(row); |
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278 } |
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279 return values; |
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280 } |
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281 |
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282 row = -row - 1; |
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|
283 if (row < 1 || row >= size()) { |
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FixA: Lowered log level in parameter interpolation.
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|
284 log.debug("interpolate: row is out of bounds"); |
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285 return null; |
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286 } |
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287 |
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288 double v1 = columns[keyIndex].getQuick(row-1); |
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289 double v2 = columns[keyIndex].getQuick(row); |
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290 double factor = Linear.factor(key, v1, v2); |
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291 |
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292 double [] values = new double[columnNames.length]; |
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293 |
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294 for (int i = 0; i < values.length; ++i) { |
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295 int ci = columnIndex(columnNames[i]); |
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296 values[i] = ci < 0 |
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297 ? Double.NaN |
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298 : Linear.weight( |
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299 factor, |
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300 columns[ci].getQuick(row-1), |
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301 columns[ci].getQuick(row)); |
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302 } |
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303 |
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304 return values; |
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305 } |
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306 |
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307 public boolean isSorted(String columnName) { |
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308 return isSorted(columnIndex(columnName)); |
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309 } |
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310 |
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311 public boolean isSorted(int columnIndex) { |
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312 TDoubleArrayList column = columns[columnIndex]; |
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313 for (int i = 1, N = column.size(); i < N; ++i) { |
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314 if (column.getQuick(i-1) > column.getQuick(i)) { |
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|
315 return false; |
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316 } |
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317 } |
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318 return true; |
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319 } |
3217
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320 |
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321 public void visit(Visitor visitor) { |
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322 visit(visitor, new double[columns.length]); |
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323 } |
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324 |
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325 public void visit(Visitor visitor, double [] data) { |
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326 for (int i = 0, R = size(); i < R; ++i) { |
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327 for (int j = 0; j < data.length; ++j) { |
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328 data[j] = columns[j].getQuick(i); |
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329 } |
79dd823733e2
FixA: Added parameter exporter.
Sascha L. Teichmann <sascha.teichmann@intevation.de>
parents:
3126
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330 visitor.visit(data); |
79dd823733e2
FixA: Added parameter exporter.
Sascha L. Teichmann <sascha.teichmann@intevation.de>
parents:
3126
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changeset
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331 } |
79dd823733e2
FixA: Added parameter exporter.
Sascha L. Teichmann <sascha.teichmann@intevation.de>
parents:
3126
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332 } |
2695
ae0742f92cd5
Added model to store fitting results into cache.
Sascha L. Teichmann <sascha.teichmann@intevation.de>
parents:
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333 } |
ae0742f92cd5
Added model to store fitting results into cache.
Sascha L. Teichmann <sascha.teichmann@intevation.de>
parents:
diff
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334 // vim:set ts=4 sw=4 si et sta sts=4 fenc=utf8 : |