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annotate python/events.py @ 317:d280b881e860

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added indicator min distance
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Fri, 12 Apr 2013 18:03:04 -0400
parents f7ca78a11ea6
children 419f30491a4b 4b5fe2de1e8d
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rev   line source
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61fe73df2d36 created new package, moved Interaction class and created Crossing class
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1 #! /usr/bin/env python
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2 '''Libraries for events
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3 Interactions, pedestrian crossing...'''
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4
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5 import numpy as np
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6 from numpy import arccos
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7
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8 import multiprocessing
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9 import itertools
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10
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f955e83da499 developed indicators in interactions
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11 import moving
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12 import prediction
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13 import indicators
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14
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15 __metaclass__ = type
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16
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17 class Interaction(moving.STObject):
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18 '''Class for an interaction between two road users
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19 or a road user and an obstacle
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20
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21 link to the moving objects
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22 contains the indicators in a dictionary with the names as keys
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23 '''
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24
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25 categories = {'headon': 0,
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26 'rearend': 1,
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27 'side': 2,
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28 'parallel': 3}
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29
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30 def __init__(self, num = None, timeInterval = None, roaduserNum1 = None, roaduserNum2 = None, movingObject1 = None, movingObject2 = None, categoryNum = None):
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31 moving.STObject.__init__(self, num, timeInterval)
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32 self.roaduserNumbers = set([roaduserNum1, roaduserNum2])
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33 self.movingObject1 = movingObject1
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34 self.movingObject2 = movingObject2
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35 self.categoryNum = categoryNum
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36 self.indicators = {}
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37
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38 def getIndicator(self, indicatorName):
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39 return self.indicators[indicatorName]
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40
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41 def addIndicator(self, indicator):
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42 self.indicators[indicator.name] = indicator
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43
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44 def computeIndicators(self):
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45 '''Computes the collision course cosine only if the cosine is positive'''
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46 collisionCourseDotProducts = {}#[0]*int(self.timeInterval.length())
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47 collisionCourseCosines = {}
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48 distances = {}#[0]*int(self.timeInterval.length())
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49 speedDifferentials = {}
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50 for instant in self.timeInterval:
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51 deltap = self.movingObject1.getPositionAtInstant(instant)-self.movingObject2.getPositionAtInstant(instant)
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52 deltav = self.movingObject2.getVelocityAtInstant(instant)-self.movingObject1.getVelocityAtInstant(instant)
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53 collisionCourseDotProducts[instant] = moving.Point.dot(deltap, deltav)
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54 distances[instant] = deltap.norm2()
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55 speedDifferentials[instant] = deltav.norm2()
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56 if collisionCourseDotProducts[instant] > 0:
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57 collisionCourseAngles[instant] = arccos(collisionCourseDotProducts[instant]/(distances[instant]*speedDifferentials[instant]))
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58
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59 # todo shorten the time intervals based on the interaction definition
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60 self.addIndicator(indicators.SeverityIndicator('Collision Course Dot Product', collisionCourseDotProducts))
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61 self.addIndicator(indicators.SeverityIndicator('Distance', distances))
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62 self.addIndicator(indicators.SeverityIndicator('Speed Differential', speedDifferentials))
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63 self.addIndicator(indicators.SeverityIndicator('Collision Course Angle', collisionCourseAngles))
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64
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65 # todo test for interaction instants and interval, compute indicators
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66
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67 # if we have features, compute other indicators
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68 if self.movingObject1.features and self.movingObject2.features:
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69 from scipy.spatial.distance import cdist
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70 minDistance={}
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71 for instant in self.timeInterval:
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72 positions1 = [f.getPositionAtInstant(instant).astuple() for f in self.movingObject1.features if f.existsAtInstant(instant)]
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73 positions2 = [f.getPositionAtInstant(instant).astuple() for f in self.movingObject2.features if f.existsAtInstant(instant)]
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74 distance = cdist(positions1, positions2, metric = 'euclidean')
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75 minDistance[instant] = distance.min()
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76 self.addIndicator(indicators.SeverityIndicator('Minimum Distance', minDistance))
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77
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78 def computeCollisionPoints(self, predictionParameters, collisionDistanceThreshold, timeHorizon):
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79 if self.movingObject1.features and self.movingObject2.features:
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80 collisionPoints = prediction.computeCollisions(self.movingObject1, self.movingObject2, predictionParameters, collisionDistanceThreshold, timeHorizon)
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81 self.addIndicator(indicators.SeverityIndicator('collisionPoints', collisionPoints))
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82 else:
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83 print('Features not associated with objects')
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84
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85 def addVideoFilename(self,videoFilename):
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86 self.videoFilename= videoFilename
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87
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88 def addInteractionType(self,interactionType):
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89 ''' interaction types: conflict or collision if they are known'''
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90 self.interactionType= interactionType
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91
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92 def createInteractions(objects):
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93 '''Create all interactions of two co-existing road users
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94
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95 todo add test to compute categories?'''
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96 interactions = []
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97 num = 0
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98 for i in xrange(len(objects)):
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99 for j in xrange(i):
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100 commonTimeInterval = objects[i].commonTimeInterval(objects[j])
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101 if not commonTimeInterval.empty():
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102 interactions.append(Interaction(num, commonTimeInterval, objects[i].num, objects[j].num, objects[i], objects[j]))
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103 num += 1
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104 return interactions
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105
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106
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107 # TODO:
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108 #http://stackoverflow.com/questions/3288595/multiprocessing-using-pool-map-on-a-function-defined-in-a-class
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109 #http://www.rueckstiess.net/research/snippets/show/ca1d7d90
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110 def calculateIndicatorPipe(pairs, predParam, timeHorizon=75,collisionDistanceThreshold=1.8):
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111 collisionPoints, crossingZones = prediction.computeCrossingsCollisions(pairs.movingObject1, pairs.movingObject2, predParam, collisionDistanceThreshold, timeHorizon)
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112 #print pairs.num
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113 # Ignore empty collision points
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114 empty = 1
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115 for i in collisionPoints:
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116 if(collisionPoints[i] != []):
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117 empty = 0
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118 if(empty == 1):
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119 pairs.hasCP = 0
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120 else:
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121 pairs.hasCP = 1
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122 pairs.CP = collisionPoints
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123
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124 # Ignore empty crossing zones
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125 empty = 1
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126 for i in crossingZones:
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127 if(crossingZones[i] != []):
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128 empty = 0
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129 if(empty == 1):
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130 pairs.hasCZ = 0
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131 else:
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132 pairs.hasCZ = 1
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133 pairs.CZ = crossingZones
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134 return pairs
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135
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136 def calculateIndicatorPipe_star(a_b):
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137 """Convert `f([1,2])` to `f(1,2)` call."""
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138 return calculateIndicatorPipe(*a_b)
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139
291
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140 class VehPairs():
293
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141 '''Create a veh-pairs object from objects list'''
291
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142 def __init__(self,objects):
293
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143 self.pairs = createInteractions(objects)
292
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144 self.interactionCount = 0
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145 self.CPcount = 0
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146 self.CZcount = 0
291
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147
292
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148 # Process indicator calculation with support for multi-threading
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149 def calculateIndicators(self,predParam,threads=1,timeHorizon=75,collisionDistanceThreshold=1.8):
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150 if(threads > 1):
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151 pool = multiprocessing.Pool(threads)
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152 self.pairs = pool.map(calculateIndicatorPipe_star, itertools.izip(self.pairs, itertools.repeat(predParam)))
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153 pool.close()
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154 else:
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155 #prog = Tools.ProgressBar(0, len(self.pairs), 77) #Removed in traffic-intelligenc port
291
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156 for j in xrange(len(self.pairs)):
292
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157 #prog.updateAmount(j) #Removed in traffic-intelligenc port
291
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158 collisionPoints, crossingZones = prediction.computeCrossingsCollisions(self.pairs[j].movingObject1, self.pairs[j].movingObject2, predParam, collisionDistanceThreshold, timeHorizon)
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159
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160 # Ignore empty collision points
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161 empty = 1
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162 for i in collisionPoints:
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163 if(collisionPoints[i] != []):
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164 empty = 0
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165 if(empty == 1):
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166 self.pairs[j].hasCP = 0
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167 else:
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168 self.pairs[j].hasCP = 1
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169 self.pairs[j].CP = collisionPoints
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170
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171 # Ignore empty crossing zones
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172 empty = 1
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173 for i in crossingZones:
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174 if(crossingZones[i] != []):
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175 empty = 0
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176 if(empty == 1):
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177 self.pairs[j].hasCZ = 0
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178 else:
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179 self.pairs[j].hasCZ = 1
292
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180 self.pairs[j].CZ = crossingZones
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181
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182 for j in self.pairs:
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183 self.interactionCount = self.interactionCount + len(j.CP)
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184 self.CPcount = len(self.getCPlist())
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185 self.Czcount = len(self.getCZlist())
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186
292
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187
291
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188 def getPairsWCP(self):
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189 lists = []
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190 for j in self.pairs:
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191 if(j.hasCP):
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192 lists.append(j.num)
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193 return lists
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194
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195 def getPairsWCZ(self):
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196 lists = []
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197 for j in self.pairs:
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198 if(j.hasCZ):
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199 lists.append(j.num)
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200 return lists
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201
292
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202 def getCPlist(self,indicatorThreshold=99999):
291
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203 lists = []
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204 for j in self.pairs:
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205 if(j.hasCP):
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206 for k in j.CP:
292
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207 if(j.CP[k] != [] and j.CP[k][0].indicator < indicatorThreshold):
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208 lists.append([k,j.CP[k][0]])
291
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209 return lists
292
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210
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211 def getCZlist(self,indicatorThreshold=99999):
291
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212 lists = []
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213 for j in self.pairs:
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214 if(j.hasCZ):
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215 for k in j.CZ:
292
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216 if(j.CZ[k] != [] and j.CZ[k][0].indicator < indicatorThreshold):
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217 lists.append([k,j.CZ[k][0]])
291
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218 return lists
292
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219
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220 def genIndicatorHistogram(self, CPlist=False, bins=range(0,100,1)):
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221 if(not CPlist):
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222 CPlist = self.getCPlist()
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223 if(not CPlist):
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224 return False
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225 TTC_list = []
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226 for i in CPlist:
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227 TTC_list.append(i[1].indicator)
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228 histo = np.histogram(TTC_list,bins=bins)
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229 histo += (histo[0].astype(float)/np.sum(histo[0]),)
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230 return histo
291
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231
59
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232 class Crossing(moving.STObject):
56
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233 '''Class for the event of a street crossing
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234
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235 TODO: detecter passage sur la chaussee
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236 identifier origines et destination (ou uniquement chaussee dans FOV)
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237 carac traversee
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238 detecter proximite veh (retirer si trop similaire simultanement
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239 carac interaction'''
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240
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241 def __init__(self, roaduserNum = None, num = None, timeInterval = None):
59
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diff changeset
242 moving.STObject.__init__(self, num, timeInterval)
56
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243 self.roaduserNum = roaduserNum
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244
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245
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246
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247 if __name__ == "__main__":
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248 import doctest
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249 import unittest
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250 #suite = doctest.DocFileSuite('tests/moving.txt')
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251 suite = doctest.DocTestSuite()
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252 unittest.TextTestRunner().run(suite)
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253