Mercurial > dive4elements > river
annotate flys-artifacts/src/main/java/de/intevation/flys/artifacts/model/Parameters.java @ 3175:4616436a84f4
Progressed LegendItemAggregation.
flys-artifacts/trunk@4789 c6561f87-3c4e-4783-a992-168aeb5c3f6f
author | Felix Wolfsteller <felix.wolfsteller@intevation.de> |
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date | Mon, 25 Jun 2012 18:12:19 +0000 |
parents | fe9be7ccc5e8 |
children | 79dd823733e2 |
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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 static final double EPSILON = 1e-4; |
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17 |
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18 protected String [] columnNames; |
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19 protected TDoubleArrayList [] columns; |
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20 |
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21 public Parameters() { |
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22 } |
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23 |
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24 public Parameters(String [] columnNames) { |
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25 if (columnNames == null || columnNames.length < 1) { |
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26 throw new IllegalArgumentException("columnNames too short."); |
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27 } |
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28 this.columnNames = columnNames; |
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29 columns = new TDoubleArrayList[columnNames.length]; |
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30 for (int i = 0; i < columns.length; ++i) { |
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31 columns[i] = new TDoubleArrayList(); |
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32 } |
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33 } |
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34 |
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35 public int columnIndex(String name) { |
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36 for (int i = 0; i < columnNames.length; ++i) { |
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37 if (columnNames[i].equals(name)) { |
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38 return i; |
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39 } |
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40 } |
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41 if (log.isDebugEnabled()) { |
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42 log.debug("columnIndex: " + name + " not found in columnNames"); |
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43 } |
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44 return -1; |
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45 } |
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46 |
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47 public int newRow() { |
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48 |
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49 int N = columns[0].size(); |
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50 |
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51 for (int i = 0; i < columns.length; ++i) { |
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52 columns[i].add(Double.NaN); |
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53 } |
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54 |
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55 return N; |
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56 } |
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57 |
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58 public double get(int row, int index) { |
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59 return columns[index].getQuick(row); |
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60 } |
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61 |
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62 public double get(int i, String columnName) { |
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63 int index = columnIndex(columnName); |
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64 return index >= 0 |
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65 ? columns[index].getQuick(i) |
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66 : Double.NaN; |
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67 } |
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68 |
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69 public void set(int row, int index, double value) { |
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70 columns[index].setQuick(row, value); |
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71 } |
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72 |
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73 public void set(int i, String columnName, double value) { |
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74 int idx = columnIndex(columnName); |
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75 if (idx >= 0) { |
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76 columns[idx].setQuick(i, value); |
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77 } |
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78 } |
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79 |
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80 public boolean set(int row, int [] indices, double [] values) { |
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81 boolean invalid = false; |
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82 for (int i = 0; i < indices.length; ++i) { |
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83 double v = values[i]; |
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84 if (Double.isNaN(v)) { |
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85 invalid = true; |
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86 } |
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87 else { |
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88 columns[indices[i]].setQuick(row, v); |
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89 } |
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90 } |
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91 return invalid; |
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92 } |
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93 |
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94 public int size() { |
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95 return columns[0].size(); |
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96 } |
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97 |
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98 public int getNumberColumns() { |
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99 return columnNames.length; |
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100 } |
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101 |
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102 public String [] getColumnNames() { |
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103 return columnNames; |
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104 } |
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105 |
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106 public void removeNaNs() { |
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107 W.removeNaNs(columns); |
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108 } |
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109 |
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110 public int [] columnIndices(String [] columns) { |
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111 int [] indices = new int[columns.length]; |
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112 for (int i = 0; i < columns.length; ++i) { |
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113 indices[i] = columnIndex(columns[i]); |
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114 } |
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115 return indices; |
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116 } |
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117 |
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118 public double [] get(int row, String [] columns) { |
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119 return get(row, columns, new double[columns.length]); |
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120 } |
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121 |
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122 public double [] get(int row, String [] columns, double [] values) { |
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123 for (int i = 0; i < columns.length; ++i) { |
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124 int idx = columnIndex(columns[i]); |
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125 values[i] = idx < 0 |
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126 ? Double.NaN |
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127 : this.columns[idx].getQuick(row); |
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128 } |
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129 |
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130 return values; |
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131 } |
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132 |
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133 public void get(int row, int [] columnIndices, double [] values) { |
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134 for (int i = 0; i < columnIndices.length; ++i) { |
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135 int index = columnIndices[i]; |
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136 values[i] = index >= 0 && index < columns.length |
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137 ? columns[index].getQuick(row) |
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138 : Double.NaN; |
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139 } |
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140 } |
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141 |
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142 public int binarySearch(String columnName, double value) { |
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143 return binarySearch(columnIndex(columnName), value); |
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144 } |
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145 |
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146 /** |
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147 * Performes a binary search in the column identified by its |
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148 * index. |
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149 * @return Index of found element or negative insertion point (shifted by one) |
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150 */ |
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151 public int binarySearch(int columnIndex, double value) { |
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152 TDoubleArrayList column = columns[columnIndex]; |
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153 return column.binarySearch(value); |
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154 } |
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155 |
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156 public int binarySearch(String columnName, double value, double epsilon) { |
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157 return binarySearch(columnIndex(columnName), value, epsilon); |
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158 } |
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159 |
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160 public int binarySearch(int columnIndex, double value, double epsilon) { |
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161 if (epsilon < 0d) epsilon = -epsilon; |
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162 double vl = value - epsilon; |
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163 double vh = value + epsilon; |
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164 |
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165 TDoubleArrayList column = columns[columnIndex]; |
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166 int lo = 0, hi = column.size()-1; |
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167 while (hi >= lo) { |
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168 int mid = (lo + hi) >> 1; |
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169 double v = column.getQuick(mid); |
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170 if (v < vl) lo = mid + 1; |
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171 else if (v > vh) hi = mid - 1; |
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172 else return mid; |
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173 } |
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174 |
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175 return -(lo + 1); |
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176 } |
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177 |
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178 public double [] interpolate(int columnIndex, double key) { |
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179 return interpolate(columnIndex, key, new double[columns.length]); |
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180 } |
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181 |
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182 public double [] interpolate(String columnName, double key) { |
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183 return interpolate( |
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184 columnIndex(columnName), key, new double[columns.length]); |
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185 } |
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186 |
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187 public double [] interpolate( |
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188 String columnName, |
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189 double key, |
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190 double [] values |
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191 ) { |
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192 return interpolate(columnIndex(columnName), key, values); |
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193 } |
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194 |
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195 public double [] interpolate( |
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196 int columnIndex, |
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197 double key, |
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198 double [] values |
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199 ) { |
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200 int row = binarySearch(columnIndex, key, EPSILON); |
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201 |
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202 if (row >= 0) { // direct hit |
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203 for (int i = 0; i < values.length; ++i) { |
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204 values[i] = columns[i].getQuick(row); |
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205 } |
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206 } |
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207 else { |
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208 row = -row - 1; |
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209 if (row < 1 || row >= size()) { |
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210 return null; |
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211 } |
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212 double v1 = columns[columnIndex].getQuick(row-1); |
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213 double v2 = columns[columnIndex].getQuick(row); |
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214 double factor = Linear.factor(key, v1, v2); |
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215 for (int i = 0; i < values.length; ++i) { |
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216 values[i] = Linear.weight( |
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217 factor, |
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218 columns[i].getQuick(row-1), |
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219 columns[i].getQuick(row)); |
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220 } |
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221 } |
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222 return values; |
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223 } |
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224 |
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225 |
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226 public double [] interpolate( |
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227 String keyName, |
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228 double key, |
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229 String [] columnNames |
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230 ) { |
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231 int keyIndex = columnIndex(keyName); |
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232 return keyIndex < 0 |
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233 ? null |
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234 : interpolate(keyIndex, key, columnNames); |
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235 } |
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236 |
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237 public double [] interpolate( |
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238 int keyIndex, |
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239 double key, |
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240 String [] columnNames |
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241 ) { |
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242 int row = binarySearch(keyIndex, key, EPSILON); |
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243 |
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244 if (row >= 0) { // direct match |
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245 double [] values = new double[columnNames.length]; |
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246 for (int i = 0; i < values.length; ++i) { |
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247 int ci = columnIndex(columnNames[i]); |
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248 values[i] = ci < 0 |
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249 ? Double.NaN |
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250 : columns[ci].getQuick(row); |
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251 } |
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252 return values; |
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253 } |
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254 |
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255 row = -row - 1; |
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256 if (row < 1 || row >= size()) { |
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257 log.debug("interpolate: row is out of bounds"); |
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258 return null; |
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259 } |
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260 |
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261 double v1 = columns[keyIndex].getQuick(row-1); |
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262 double v2 = columns[keyIndex].getQuick(row); |
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263 double factor = Linear.factor(key, v1, v2); |
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264 |
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265 double [] values = new double[columnNames.length]; |
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266 |
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267 for (int i = 0; i < values.length; ++i) { |
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268 int ci = columnIndex(columnNames[i]); |
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269 values[i] = ci < 0 |
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270 ? Double.NaN |
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271 : Linear.weight( |
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272 factor, |
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273 columns[ci].getQuick(row-1), |
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274 columns[ci].getQuick(row)); |
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275 } |
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276 |
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277 return values; |
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278 } |
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279 |
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280 public boolean isSorted(String columnName) { |
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281 return isSorted(columnIndex(columnName)); |
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282 } |
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283 |
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284 public boolean isSorted(int columnIndex) { |
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285 TDoubleArrayList column = columns[columnIndex]; |
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286 for (int i = 1, N = column.size(); i < N; ++i) { |
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287 if (column.getQuick(i-1) > column.getQuick(i)) { |
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288 return false; |
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289 } |
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290 } |
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291 return true; |
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292 } |
2695
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293 } |
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294 // vim:set ts=4 sw=4 si et sta sts=4 fenc=utf8 : |