Mercurial > dive4elements > river
annotate flys-artifacts/src/main/java/de/intevation/flys/artifacts/model/Parameters.java @ 4989:f4d61ac84b76 dami
If we bother to check if the file is readable we might also
bother to check if it's a file at all.
Thanks to teichmann for noticing
author | Andre Heinecke <aheinecke@intevation.de> |
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date | Thu, 14 Feb 2013 10:54:02 +0100 |
parents | bcf25d8c183e |
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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 de.intevation.flys.utils.DoubleUtil; |
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6 |
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7 import gnu.trove.TDoubleArrayList; |
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8 |
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9 import java.io.Serializable; |
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10 |
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11 import org.apache.log4j.Logger; |
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12 |
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13 public class Parameters |
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14 implements Serializable |
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15 { |
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16 private static Logger log = Logger.getLogger(Parameters.class); |
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17 |
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18 public interface Visitor { |
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19 |
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20 void visit(double [] row); |
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21 |
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22 } // interface Visitor |
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23 |
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24 public static final double EPSILON = 1e-4; |
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25 |
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26 protected String [] columnNames; |
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27 protected TDoubleArrayList [] columns; |
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28 |
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29 public Parameters() { |
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30 } |
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31 |
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32 public Parameters(String [] columnNames) { |
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33 if (columnNames == null || columnNames.length < 1) { |
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34 throw new IllegalArgumentException("columnNames too short."); |
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35 } |
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36 this.columnNames = columnNames; |
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37 columns = new TDoubleArrayList[columnNames.length]; |
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38 for (int i = 0; i < columns.length; ++i) { |
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39 columns[i] = new TDoubleArrayList(); |
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40 } |
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41 } |
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42 |
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43 public int columnIndex(String name) { |
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44 for (int i = 0; i < columnNames.length; ++i) { |
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45 if (columnNames[i].equals(name)) { |
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46 return i; |
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47 } |
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48 } |
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49 if (log.isDebugEnabled()) { |
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50 log.debug("columnIndex: " + name + " not found in columnNames"); |
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51 } |
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52 return -1; |
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53 } |
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54 |
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55 public int newRow() { |
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56 |
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57 int N = columns[0].size(); |
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58 |
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59 for (int i = 0; i < columns.length; ++i) { |
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60 columns[i].add(Double.NaN); |
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61 } |
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62 |
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63 return N; |
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64 } |
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65 |
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66 public double get(int row, int index) { |
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67 return columns[index].getQuick(row); |
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68 } |
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69 |
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70 public double get(int i, String columnName) { |
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71 int index = columnIndex(columnName); |
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72 return index >= 0 |
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73 ? columns[index].getQuick(i) |
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74 : Double.NaN; |
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75 } |
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76 |
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77 public void set(int row, int index, double value) { |
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78 columns[index].setQuick(row, value); |
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79 } |
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80 |
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81 public void set(int i, String columnName, double value) { |
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82 int idx = columnIndex(columnName); |
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83 if (idx >= 0) { |
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84 columns[idx].setQuick(i, value); |
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85 } |
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86 } |
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87 |
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88 public boolean set(int row, int [] indices, double [] values) { |
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89 boolean invalid = false; |
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90 for (int i = 0; i < indices.length; ++i) { |
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91 double v = values[i]; |
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92 if (Double.isNaN(v)) { |
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93 invalid = true; |
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94 } |
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95 else { |
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96 columns[indices[i]].setQuick(row, v); |
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97 } |
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98 } |
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99 return invalid; |
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100 } |
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101 |
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102 public boolean set(int row, String [] names, double [] values) { |
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103 boolean success = true; |
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104 for (int i = 0; i < names.length; ++i) { |
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105 int idx = columnIndex(names[i]); |
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106 if (idx >= 0) { |
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107 columns[idx].setQuick(row, values[i]); |
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108 } |
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109 else { |
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110 success = false; |
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111 } |
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112 } |
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113 return success; |
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114 } |
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115 |
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116 public int size() { |
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117 return columns[0].size(); |
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118 } |
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119 |
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120 public int getNumberColumns() { |
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121 return columnNames.length; |
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122 } |
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123 |
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124 public String [] getColumnNames() { |
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125 return columnNames; |
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126 } |
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127 |
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128 public void removeNaNs() { |
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129 DoubleUtil.removeNaNs(columns); |
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130 } |
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131 |
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132 public int [] columnIndices(String [] columns) { |
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133 int [] indices = new int[columns.length]; |
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134 for (int i = 0; i < columns.length; ++i) { |
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135 indices[i] = columnIndex(columns[i]); |
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136 } |
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137 return indices; |
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138 } |
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139 |
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140 public double getValue(int row, String column) { |
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141 int idx = columnIndex(column); |
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142 return idx >= 0 |
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143 ? columns[idx].getQuick(row) |
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144 : Double.NaN; |
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145 } |
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146 |
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147 public double [] get(int row, String [] columns) { |
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148 return get(row, columns, new double[columns.length]); |
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149 } |
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150 |
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151 public double [] get(int row, String [] columns, double [] values) { |
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152 for (int i = 0; i < columns.length; ++i) { |
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153 int idx = columnIndex(columns[i]); |
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154 values[i] = idx < 0 |
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155 ? Double.NaN |
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156 : this.columns[idx].getQuick(row); |
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157 } |
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158 |
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159 return values; |
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160 } |
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161 |
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162 public void get(int row, int [] columnIndices, double [] values) { |
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163 for (int i = 0; i < columnIndices.length; ++i) { |
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164 int index = columnIndices[i]; |
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165 values[i] = index >= 0 && index < columns.length |
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166 ? columns[index].getQuick(row) |
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167 : Double.NaN; |
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168 } |
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169 } |
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170 |
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171 public int binarySearch(String columnName, double value) { |
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172 return binarySearch(columnIndex(columnName), value); |
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173 } |
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174 |
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175 /** |
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176 * Performes a binary search in the column identified by its |
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177 * index. |
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178 * @return Index of found element or negative insertion point (shifted by one) |
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179 */ |
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180 public int binarySearch(int columnIndex, double value) { |
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181 TDoubleArrayList column = columns[columnIndex]; |
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182 return column.binarySearch(value); |
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183 } |
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184 |
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185 public int binarySearch(String columnName, double value, double epsilon) { |
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186 return binarySearch(columnIndex(columnName), value, epsilon); |
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187 } |
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188 |
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189 public int binarySearch(int columnIndex, double value, double epsilon) { |
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190 if (epsilon < 0d) epsilon = -epsilon; |
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191 double vl = value - epsilon; |
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192 double vh = value + epsilon; |
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193 |
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194 TDoubleArrayList column = columns[columnIndex]; |
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195 int lo = 0, hi = column.size()-1; |
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196 while (hi >= lo) { |
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197 int mid = (lo + hi) >> 1; |
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198 double v = column.getQuick(mid); |
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199 if (v < vl) lo = mid + 1; |
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200 else if (v > vh) hi = mid - 1; |
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201 else return mid; |
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202 } |
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203 |
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204 return -(lo + 1); |
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205 } |
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206 |
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207 public double [] interpolate(int columnIndex, double key) { |
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208 return interpolate(columnIndex, key, new double[columns.length]); |
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209 } |
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210 |
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211 public double [] interpolate(String columnName, double key) { |
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212 return interpolate( |
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213 columnIndex(columnName), key, new double[columns.length]); |
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214 } |
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215 |
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216 public double [] interpolate( |
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217 String columnName, |
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218 double key, |
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219 double [] values |
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220 ) { |
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221 return interpolate(columnIndex(columnName), key, values); |
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222 } |
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223 |
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224 public double [] interpolate( |
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225 int columnIndex, |
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226 double key, |
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227 double [] values |
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228 ) { |
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229 int row = binarySearch(columnIndex, key, EPSILON); |
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230 |
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231 if (row >= 0) { // direct hit |
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232 for (int i = 0; i < values.length; ++i) { |
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233 values[i] = columns[i].getQuick(row); |
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234 } |
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235 } |
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236 else { |
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237 row = -row - 1; |
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238 if (row < 1 || row >= size()) { |
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239 return null; |
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240 } |
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241 double v1 = columns[columnIndex].getQuick(row-1); |
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242 double v2 = columns[columnIndex].getQuick(row); |
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243 double factor = Linear.factor(key, v1, v2); |
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244 for (int i = 0; i < values.length; ++i) { |
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245 values[i] = Linear.weight( |
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246 factor, |
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247 columns[i].getQuick(row-1), |
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248 columns[i].getQuick(row)); |
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249 } |
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250 } |
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251 return values; |
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252 } |
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253 |
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254 |
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255 public double [] interpolate( |
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256 String keyName, |
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257 double key, |
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258 String [] columnNames |
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259 ) { |
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260 int keyIndex = columnIndex(keyName); |
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261 return keyIndex < 0 |
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262 ? null |
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263 : interpolate(keyIndex, key, columnNames); |
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264 } |
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265 |
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266 public double [] interpolate( |
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267 int keyIndex, |
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268 double key, |
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269 String [] columnNames |
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270 ) { |
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271 int row = binarySearch(keyIndex, key, EPSILON); |
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272 |
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273 if (row >= 0) { // direct match |
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274 double [] values = new double[columnNames.length]; |
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275 for (int i = 0; i < values.length; ++i) { |
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276 int ci = columnIndex(columnNames[i]); |
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277 values[i] = ci < 0 |
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278 ? Double.NaN |
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279 : columns[ci].getQuick(row); |
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280 } |
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281 return values; |
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282 } |
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283 |
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284 row = -row - 1; |
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|
285 if (row < 1 || row >= size()) { |
3082
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FixA: Lowered log level in parameter interpolation.
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|
286 log.debug("interpolate: row is out of bounds"); |
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287 return null; |
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288 } |
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289 |
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290 double v1 = columns[keyIndex].getQuick(row-1); |
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291 double v2 = columns[keyIndex].getQuick(row); |
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292 double factor = Linear.factor(key, v1, v2); |
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293 |
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294 double [] values = new double[columnNames.length]; |
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295 |
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296 for (int i = 0; i < values.length; ++i) { |
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297 int ci = columnIndex(columnNames[i]); |
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298 values[i] = ci < 0 |
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299 ? Double.NaN |
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300 : Linear.weight( |
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301 factor, |
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302 columns[ci].getQuick(row-1), |
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303 columns[ci].getQuick(row)); |
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304 } |
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305 |
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306 return values; |
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307 } |
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308 |
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309 public boolean isSorted(String columnName) { |
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310 return isSorted(columnIndex(columnName)); |
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311 } |
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312 |
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313 public boolean isSorted(int columnIndex) { |
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|
314 TDoubleArrayList column = columns[columnIndex]; |
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315 for (int i = 1, N = column.size(); i < N; ++i) { |
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316 if (column.getQuick(i-1) > column.getQuick(i)) { |
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317 return false; |
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318 } |
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319 } |
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320 return true; |
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321 } |
3217
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322 |
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323 public void visit(Visitor visitor) { |
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324 visit(visitor, new double[columns.length]); |
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325 } |
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326 |
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|
327 public void visit(Visitor visitor, double [] data) { |
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328 for (int i = 0, R = size(); i < R; ++i) { |
79dd823733e2
FixA: Added parameter exporter.
Sascha L. Teichmann <sascha.teichmann@intevation.de>
parents:
3126
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changeset
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329 for (int j = 0; j < data.length; ++j) { |
79dd823733e2
FixA: Added parameter exporter.
Sascha L. Teichmann <sascha.teichmann@intevation.de>
parents:
3126
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changeset
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330 data[j] = columns[j].getQuick(i); |
79dd823733e2
FixA: Added parameter exporter.
Sascha L. Teichmann <sascha.teichmann@intevation.de>
parents:
3126
diff
changeset
|
331 } |
79dd823733e2
FixA: Added parameter exporter.
Sascha L. Teichmann <sascha.teichmann@intevation.de>
parents:
3126
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332 visitor.visit(data); |
79dd823733e2
FixA: Added parameter exporter.
Sascha L. Teichmann <sascha.teichmann@intevation.de>
parents:
3126
diff
changeset
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333 } |
79dd823733e2
FixA: Added parameter exporter.
Sascha L. Teichmann <sascha.teichmann@intevation.de>
parents:
3126
diff
changeset
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334 } |
2695
ae0742f92cd5
Added model to store fitting results into cache.
Sascha L. Teichmann <sascha.teichmann@intevation.de>
parents:
diff
changeset
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335 } |
ae0742f92cd5
Added model to store fitting results into cache.
Sascha L. Teichmann <sascha.teichmann@intevation.de>
parents:
diff
changeset
|
336 // vim:set ts=4 sw=4 si et sta sts=4 fenc=utf8 : |