Mercurial > hg > nsaunier > traffic-intelligence

comparison python/poly_utils.py @ 598:11f96bd08552

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refine to be more generic
author Mohamed Gomaa
date Thu, 18 Apr 2013 15:29:33 -0400
parents 484cc1d6cfd1
children
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597:484cc1d6cfd1 598:11f96bd08552
4 import utils 4 import utils
5 from moving import TimeInterval 5 from moving import TimeInterval
6 import numpy as np 6 import numpy as np
7 7
8 __metaclass__ = type 8 __metaclass__ = type
9 from indicators import SeverityIndicator
9 10
10 # inputs variables
11 #dirname= 'G:/0-phdstart/Code/trial/indicatorsNew/'
12 #extension= '-indicatorsNew.csv'
13 #indicatorsNames= {1:'Distance',2:'Cosine',3:'collision Course Angle',4:'Velocity Cosine',5:'Velocity Angle',6:'Speed Differential',7:'Collision Probability',8:'Severity Index',9:'TTC'}
14 ''' min Distance case'''
15 dirname= 'G:/0-phdstart/Code/trial/minDistanceIndicator/'
16 extension= '-minDistanceInd.csv'
17 indicatorsNames= {1:'minDistance'}
18 11
19 def loadNewInteractions(videoFilename,interactionType, roaduserNum1,roaduserNum2, selectedIndicators=[]): 12 def loadNewInteractions(videoFilename,interactionType,dirname, extension, indicatorsNames, roaduserNum1,roaduserNum2, selectedIndicators=[]):
20 '''Loads interactions from the POLY traffic event format''' 13 '''Loads interactions from the POLY traffic event format'''
21 from events import Interaction 14 from events import Interaction
22 from indicators import SeverityIndicator 15 filename= dirname + videoFilename + extension
23 #filename= dirname + videoFilename + extension 16 #filename= dirname + interactionType+ '-' + videoFilename + extension # case of min distance todo: change the saving format to be matched with all outputs
24 filename= dirname + interactionType+ '-' + videoFilename + extension # case of min distance todo: change the saving format to be matched with all outputs
25 file = utils.openCheck(filename) 17 file = utils.openCheck(filename)
26 if (not file): 18 if (not file):
27 return [] 19 return []
28 interactions = [] 20 #interactions = []
29 interactionNum = 0 21 interactionNum = 0
30 data= np.loadtxt(filename) 22 data= np.loadtxt(filename)
31 indicatorFrameNums= data[:,0] 23 indicatorFrameNums= data[:,0]
32 inter = Interaction(interactionNum, TimeInterval(indicatorFrameNums[0],indicatorFrameNums[-1]), roaduserNum1, roaduserNum2) 24 inter = Interaction(interactionNum, TimeInterval(indicatorFrameNums[0],indicatorFrameNums[-1]), roaduserNum1, roaduserNum2)
33 inter.addVideoFilename(videoFilename) 25 inter.addVideoFilename(videoFilename)
41 values= {} 33 values= {}
42 for i,t in enumerate(indicatorFrameNums): 34 for i,t in enumerate(indicatorFrameNums):
43 values[t] = [data[i,index] for index in selectedIndicators] 35 values[t] = [data[i,index] for index in selectedIndicators]
44 inter.addIndicator(SeverityIndicator('selectedIndicators', values)) 36 inter.addIndicator(SeverityIndicator('selectedIndicators', values))
45 37
46 interactions.append(inter) 38 #interactions.append(inter)
47 file.close() 39 file.close()
48 return interactions 40 #return interactions
41 return inter
49 42
43 # Plotting results
44
45 frameRate = 15.
46
47 # To run in directory that contains the directories that contain the results (Miss-xx and Incident-xx)
48 #dirname = '/home/nicolas/Research/Data/kentucky-db/'
49
50 interactingRoadUsers = {'Miss/0404052336': [(0,3)] # 0,2 and 1 vs 3
51 #,
52 #'Incident/0306022035': [(1,3)]
53 #,
54 #'Miss/0208030956': [(4,5),(5,7)]
55 }
56
57
58 def getIndicatorName(filename, withUnit = False):
59 if withUnit:
60 unit = ' (s)'
61 else:
62 unit = ''
63 if 'collision-point' in filename:
64 return 'TTC'+unit
65 elif 'crossing' in filename:
66 return 'pPET'+unit
67 elif 'probability' in filename:
68 return 'P(UEA)'
69
70 def getMethodName(fileprefix):
71 if fileprefix == 'constant-velocity':
72 return 'Con. Vel.'
73 elif fileprefix == 'normal-adaptation':
74 return 'Norm. Ad.'
75 elif fileprefix == 'point-set':
76 return 'Pos. Set'
77 elif fileprefix == 'evasive-action':
78 return 'Ev. Act.'
79 elif fileprefix == 'point-set-evasive-action':
80 return 'Pos. Set'
81
82 indicator2TimeIdx = {'TTC':2,'pPET':2, 'P(UEA)':3}
83
84 def getDataAtInstant(data, i):
85 return data[data[:,2] == i]
86
87 def getPointsAtInstant(data, i):
88 return getDataAtInstant(i)[3:5]
89
90 def getIndicator(data, roadUserNumbers, indicatorName):
91 if data.ndim ==1:
92 data.shape = (1,data.shape[0])
93
94 # find the order for the roadUserNumbers
95 uniqueObj1 = np.unique(data[:,0])
96 uniqueObj2 = np.unique(data[:,1])
97 found = False
98 if roadUserNumbers[0] in uniqueObj1 and roadUserNumbers[1] in uniqueObj2:
99 objNum1 = roadUserNumbers[0]
100 objNum2 = roadUserNumbers[1]
101 found = True
102 if roadUserNumbers[1] in uniqueObj1 and roadUserNumbers[0] in uniqueObj2:
103 objNum1 = roadUserNumbers[1]
104 objNum2 = roadUserNumbers[0]
105 found = True
106
107 # get subset of data for road user numbers
108 if found:
109 roadUserData = data[np.logical_and(data[:,0] == objNum1, data[:,1] == objNum2),:]
110 if roadUserData.size > 0:
111 time = np.unique(roadUserData[:,indicator2TimeIdx[indicatorName]])
112 values = {}
113 if indicatorName == 'P(UEA)':
114 tmp = roadUserData[:,4]
115 for k,v in zip(time, tmp):
116 values[k]=v
117 return SeverityIndicator(indicatorName, values, mostSevereIsMax = False, maxValue = 1.), roadUserData
118 else:
119 for i in xrange(time[0],time[-1]+1):
120 try:
121 tmp = getDataAtInstant(roadUserData, i)
122 values[i] = np.sum(tmp[:,5]*tmp[:,6])/np.sum(tmp[:,5])/frameRate
123 except IOError:
124 values[i] = np.inf
125 return SeverityIndicator(indicatorName, values, mostSevereIsMax = False), roadUserData
126 return None, None