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annotate python/indicators.py @ 247:8f0ed138d373

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moved the tests for indicators
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Wed, 18 Jul 2012 02:54:02 -0400
parents 5027c174ab90
children 7a3bf04cf016
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rev   line source
244
5027c174ab90 moved indicators to new file, added ExtrapolatedTrajectory class to extrapolation file
Nicolas Saunier <nicolas.saunier@polymtl.ca>
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1 #! /usr/bin/env python
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2 '''Class for indicators, temporal indicators, and safety indicators'''
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3
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4 __metaclass__ = type
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5
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6 # need for a class representing the indicators, their units, how to print them in graphs...
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7 class TemporalIndicator:
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8 '''Class for temporal indicators
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9 i.e. indicators that take a value at specific instants
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10
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11 values should be
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12 * a dict, for the values at specific time instants
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13 * or a list with a time interval object if continuous measurements
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14
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15 it should have more information like name, unit'''
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16
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17 def __init__(self, name, values, timeInterval=None):
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18 self.name = name
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19 self.isCosine = name.find('Cosine')
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20 self.values = values
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21 self.timeInterval = timeInterval
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22 if timeInterval:
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23 assert len(values) == timeInterval.length()
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24
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25 def empty(self):
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26 return len(self.values) == 0
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27
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28 def __getitem__(self, i):
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29 if self.timeInterval:
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30 if self.timeInterval.contains(i):
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31 return self.values[i-self.timeInterval.first]
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32 else:
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33 if i in self.values.keys():
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34 return self.values[i]
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35 return None # default
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36
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37 def __iter__(self):
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38 self.iterInstantNum = 0 # index in the interval or keys of the dict
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39 return self
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40
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41 def next(self):
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42 if self.iterInstantNum >= len(self.values):#(self.timeInterval and self.iterInstantNum>=self.timeInterval.length())\
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43 # or (self.iterInstantNum >= self.values)
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44 raise StopIteration
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45 else:
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46 self.iterInstantNum += 1
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47 if self.timeInterval:
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48 return self.values[self.iterInstantNum-1]
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49 else:
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50 return self.values.values()[self.iterInstantNum-1]
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51
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52 def getTimeInterval(self):
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53 if not self.timeInterval and type(self.values)==dict:
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54 instants = self.values.keys()
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55 if instants:
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56 self.timeInterval = TimeInterval(instants[0], instants[-1])
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57 else:
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58 self.timeInterval = TimeInterval()
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59 return self.timeInterval
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60
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61 def getValues(self):
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62 if self.timeInterval:
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63 return self.values
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64 else:
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65 return self.values.values()
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66
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67 def getAngleValues(self):
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68 '''if the indicator is a function of an angle,
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69 transform it to an angle (eg cos)
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70 (no transformation otherwise)'''
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71 from numpy import arccos
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72 values = self.getValues()
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73 if self.isCosine >= 0:
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74 return [arccos(c) for c in values]
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75 else:
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76 return values
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77
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78 class SeverityIndicator(TemporalIndicator):
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79 '''Class for severity indicators
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80 field mostSevereIsMax is True
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81 if the most severe value taken by the indicator is the maximum'''
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82
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83 def __init__(self, name, values, timeInterval=None, mostSevereIsMax=True, ignoredValue = None):
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84 TemporalIndicator.__init__(self, name, values, timeInterval)
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85 self.mostSevereIsMax = mostSevereIsMax
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86 self.ignoredValue = ignoredValue
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87
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88 def getMostSevereValue(self, minNInstants=1):
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89 from matplotlib.mlab import find
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90 from numpy.core.multiarray import array
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91 from numpy.core.fromnumeric import mean
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92 values = array(self.values.values())
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93 if self.ignoredValue:
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94 indices = find(values != self.ignoredValue)
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95 else:
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96 indices = range(len(values))
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97 if len(indices) >= minNInstants:
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98 values = sorted(values[indices], reverse = self.mostSevereIsMax) # inverted if most severe is max -> take the first values
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99 return mean(values[:minNInstants])
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100 else:
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101 return None
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102
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103 # functions to aggregate discretized maps of indicators
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104 # TODO add values in the cells between the positions (similar to discretizing vector graphics to bitmap)
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105
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106 def indicatorMap(indicatorValues, trajectory, squareSize):
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107 '''Returns a dictionary
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108 with keys for the indices of the cells (squares)
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109 in which the trajectory positions are located
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110 at which the indicator values are attached
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111
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112 ex: speeds and trajectory'''
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113
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114 from numpy import floor, mean
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115 assert len(indicatorValues) == trajectory.length()
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116 indicatorMap = {}
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117 for k in xrange(trajectory.length()):
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118 p = trajectory[k]
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119 i = floor(p.x/squareSize)
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120 j = floor(p.y/squareSize)
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121 if indicatorMap.has_key((i,j)):
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122 indicatorMap[(i,j)].append(indicatorValues[k])
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123 else:
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124 indicatorMap[(i,j)] = [indicatorValues[k]]
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125 for k in indicatorMap.keys():
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126 indicatorMap[k] = mean(indicatorMap[k])
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127 return indicatorMap
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128
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129 def indicatorMapFromPolygon(value, polygon, squareSize):
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130 '''Fills an indicator map with the value within the polygon
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131 (array of Nx2 coordinates of the polygon vertices)'''
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132 import matplotlib.nxutils as nx
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133 from numpy.core.multiarray import array, arange
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134 from numpy import floor
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135
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136 points = []
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137 for x in arange(min(polygon[:,0])+squareSize/2, max(polygon[:,0]), squareSize):
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138 for y in arange(min(polygon[:,1])+squareSize/2, max(polygon[:,1]), squareSize):
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139 points.append([x,y])
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140 inside = nx.points_inside_poly(array(points), polygon)
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141 indicatorMap = {}
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142 for i in xrange(len(inside)):
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143 if inside[i]:
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144 indicatorMap[(floor(points[i][0]/squareSize), floor(points[i][1]/squareSize))] = 0
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145 return indicatorMap
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146
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147 def indicatorMapFromAxis(value, limits, squareSize):
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148 '''axis = [xmin, xmax, ymin, ymax] '''
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149 from numpy.core.multiarray import arange
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150 from numpy import floor
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151 indicatorMap = {}
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152 for x in arange(limits[0], limits[1], squareSize):
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153 for y in arange(limits[2], limits[3], squareSize):
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154 indicatorMap[(floor(x/squareSize), floor(y/squareSize))] = value
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155 return indicatorMap
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156
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157 def combineIndicatorMaps(maps, squareSize, combinationFunction):
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158 '''Puts many indicator maps together
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159 (averaging the values in each cell
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160 if more than one maps has a value)'''
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161 #from numpy import mean
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162 indicatorMap = {}
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163 for m in maps:
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164 for k,v in m.iteritems():
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165 if indicatorMap.has_key(k):
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166 indicatorMap[k].append(v)
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167 else:
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168 indicatorMap[k] = [v]
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169 for k in indicatorMap.keys():
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170 indicatorMap[k] = combinationFunction(indicatorMap[k])
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171 return indicatorMap
247
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172
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173 if __name__ == "__main__":
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174 import doctest
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175 import unittest
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176 suite = doctest.DocFileSuite('tests/indicators.txt')
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177 unittest.TextTestRunner().run(suite)
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178 # #doctest.testmod()
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179 # #doctest.testfile("example.txt")