Mercurial > hg > nsaunier > traffic-intelligence

comparison trafficintelligence/tests/moving.txt @ 1028:cc5cb04b04b0

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major update using the trafficintelligence package name and install through pip
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Fri, 15 Jun 2018 11:19:10 -0400
parents python/tests/moving.txt@5d2f6afae35b
children aafbc0bab925
comparison
equal deleted inserted replaced
1027:6129296848d3 1028:cc5cb04b04b0
1 >>> from moving import *
2 >>> import storage
3 >>> import numpy as np
4
5 >>> Interval().empty()
6 True
7 >>> Interval(0,1).empty()
8 False
9 >>> Interval(0,1)
10 [0, 1]
11 >>> Interval(0,1).length()
12 1.0
13 >>> Interval(23.2,24.9).length()
14 1.6999999999999993
15 >>> Interval(10,8).length()
16 0.0
17
18 >>> TimeInterval(0,1).length()
19 2.0
20 >>> TimeInterval(10,8).length()
21 0.0
22 >>> TimeInterval(10,8) == TimeInterval(10,8)
23 True
24 >>> TimeInterval(10,8) == TimeInterval(8,10)
25 True
26 >>> TimeInterval(11,8) == TimeInterval(10,8)
27 False
28
29 >>> [i for i in TimeInterval(9,13)]
30 [9, 10, 11, 12, 13]
31
32 >>> TimeInterval(2,5).equal(TimeInterval(2,5))
33 True
34 >>> TimeInterval(2,5).equal(TimeInterval(2,4))
35 False
36 >>> TimeInterval(2,5).equal(TimeInterval(5,2))
37 False
38
39 >>> TimeInterval(3,6).distance(TimeInterval(4,6))
40 0
41 >>> TimeInterval(3,6).distance(TimeInterval(6,10))
42 0
43 >>> TimeInterval(3,6).distance(TimeInterval(8,10))
44 2
45 >>> TimeInterval(20,30).distance(TimeInterval(3,15))
46 5
47 >>> TimeInterval.unionIntervals([TimeInterval(3,6), TimeInterval(8,10),TimeInterval(11,15)])
48 [3, 15]
49
50 >>> Point(0,3) == Point(0,3)
51 True
52 >>> Point(0,3) == Point(0,3.2)
53 False
54 >>> Point(3,4)-Point(1,7)
55 (2.000000,-3.000000)
56 >>> -Point(1,2)
57 (-1.000000,-2.000000)
58 >>> Point(1,2)*0.5
59 (0.500000,1.000000)
60
61 >>> Point(3,2).norm2Squared()
62 13
63
64 >>> Point.distanceNorm2(Point(3,4),Point(1,7))
65 3.605551275463989
66
67 >>> Point(3,2).inPolygon(np.array([[0,0],[1,0],[1,1],[0,1]]))
68 False
69 >>> Point(3,2).inPolygon(np.array([[0,0],[4,0],[4,3],[0,3]]))
70 True
71
72 >>> predictPositionNoLimit(10, Point(0,0), Point(1,1)) # doctest:+ELLIPSIS
73 ((1.0...,1.0...), (10.0...,10.0...))
74
75 >>> segmentIntersection(Point(0,0), Point(0,1), Point(1,1), Point(2,3))
76 >>> segmentIntersection(Point(0,1), Point(0,3), Point(1,0), Point(3,1))
77 >>> segmentIntersection(Point(0.,0.), Point(2.,2.), Point(0.,2.), Point(2.,0.))
78 (1.000000,1.000000)
79 >>> segmentIntersection(Point(0,0), Point(4,4), Point(0,4), Point(4,0))
80 (2.000000,2.000000)
81 >>> segmentIntersection(Point(0,1), Point(1,2), Point(2,0), Point(3,2))
82
83 >>> t1 = Trajectory.fromPointList([(92.2, 102.9), (56.7, 69.6)])
84 >>> t2 = Trajectory.fromPointList([(92.2, 102.9), (56.7, 69.6)])
85 >>> t1 == t2
86 True
87 >>> t3 = Trajectory.fromPointList([(92.24, 102.9), (56.7, 69.6)])
88 >>> t1 == t3
89 False
90 >>> t3 = Trajectory.fromPointList([(92.2, 102.9), (56.7, 69.6), (56.7, 69.6)])
91 >>> t1 == t3
92 False
93
94 >>> left = Trajectory.fromPointList([(92.291666666666686, 102.99239033124439), (56.774193548387103, 69.688898836168306)])
95 >>> middle = Trajectory.fromPointList([(87.211021505376351, 93.390778871978512), (59.032258064516128, 67.540286481647257)])
96 >>> right = Trajectory.fromPointList([(118.82392473118281, 115.68263205013426), (63.172043010752688, 66.600268576544309)])
97 >>> alignments = [left, middle, right]
98 >>> for a in alignments: a.computeCumulativeDistances()
99 >>> getSYfromXY(Point(73, 82), alignments)
100 [1, 0, (73.819977,81.106170), 18.172277808821125, 18.172277808821125, 1.2129694042343868]
101 >>> getSYfromXY(Point(78, 83), alignments, 0.5)
102 [1, 0, (77.033188,84.053889), 13.811799123113715, 13.811799123113715, -1.4301775140225983]
103
104 >>> Trajectory().length()
105 0
106 >>> t1 = Trajectory([[0.5,1.5,2.5],[0.5,3.5,6.5]])
107 >>> t1.length() == 3.
108 True
109 >>> t1[1]
110 (1.500000,3.500000)
111
112 >>> t1.differentiate()
113 (1.000000,3.000000) (1.000000,3.000000)
114 >>> t1.differentiate(True)
115 (1.000000,3.000000) (1.000000,3.000000) (1.000000,3.000000)
116 >>> t1 = Trajectory([[0.5,1.5,3.5],[0.5,2.5,7.5]])
117 >>> t1.differentiate()
118 (1.000000,2.000000) (2.000000,5.000000)
119
120 >>> t1.computeCumulativeDistances()
121 >>> t1.getDistance(0)
122 2.23606797749979
123 >>> t1.getDistance(1)
124 5.385164807134504
125 >>> t1.getDistance(2)
126 Index 2 beyond trajectory length 3-1
127 >>> t1.getCumulativeDistance(0)
128 0.0
129 >>> t1.getCumulativeDistance(1)
130 2.23606797749979
131 >>> t1.getCumulativeDistance(2)
132 7.6212327846342935
133 >>> t1.getCumulativeDistance(3)
134 Index 3 beyond trajectory length 3
135
136
137 >>> from utils import LCSS
138 >>> lcss = LCSS(lambda x,y: Point.distanceNorm2(x,y) <= 0.1)
139 >>> Trajectory.lcss(t1, t1, lcss)
140 3
141 >>> lcss = LCSS(lambda p1, p2: (p1-p2).normMax() <= 0.1)
142 >>> Trajectory.lcss(t1, t1, lcss)
143 3
144
145 >>> p1=Point(0,0)
146 >>> p2=Point(1,0)
147 >>> v1 = Point(0.1,0.1)
148 >>> v2 = Point(-0.1, 0.1)
149 >>> abs(Point.timeToCollision(p1, p2, v1, v2, 0.)-5.0) < 0.00001
150 True
151 >>> abs(Point.timeToCollision(p1, p2, v1, v2, 0.1)-4.5) < 0.00001
152 True
153 >>> p1=Point(0,1)
154 >>> p2=Point(1,0)
155 >>> v1 = Point(0,0.1)
156 >>> v2 = Point(0.1, 0)
157 >>> Point.timeToCollision(p1, p2, v1, v2, 0.) == None
158 True
159 >>> Point.timeToCollision(p2, p1, v2, v1, 0.) == None
160 True
161 >>> Point.midPoint(p1, p2)
162 (0.500000,0.500000)
163 >>> p1=Point(0.,0.)
164 >>> p2=Point(5.,0.)
165 >>> v1 = Point(2.,0.)
166 >>> v2 = Point(1.,0.)
167 >>> Point.timeToCollision(p1, p2, v1, v2, 0.)
168 5.0
169 >>> Point.timeToCollision(p1, p2, v1, v2, 1.)
170 4.0
171
172 >>> objects = storage.loadTrajectoriesFromSqlite('../samples/laurier.sqlite', 'object')
173 >>> len(objects)
174 5
175 >>> objects[0].hasFeatures()
176 False
177 >>> features = storage.loadTrajectoriesFromSqlite('../samples/laurier.sqlite', 'feature')
178 >>> for o in objects: o.setFeatures(features)
179 >>> objects[0].hasFeatures()
180 True
181
182 >>> o1 = MovingObject.generate(1, Point(-5.,0.), Point(1.,0.), TimeInterval(0,10))
183 >>> o2 = MovingObject.generate(2, Point(0.,-5.), Point(0.,1.), TimeInterval(0,10))
184 >>> MovingObject.computePET(o1, o2, 0.1)
185 (0.0, 5, 5)
186 >>> o2 = MovingObject.generate(2, Point(0.,-5.), Point(0.,1.), TimeInterval(5,15))
187 >>> MovingObject.computePET(o1, o2, 0.1)
188 (5.0, 5, 10)
189 >>> o2 = MovingObject.generate(2, Point(0.,-5.), Point(0.,1.), TimeInterval(15,30))
190 >>> MovingObject.computePET(o1, o2, 0.1)
191 (15.0, 5, 20)
192
193 >>> t = CurvilinearTrajectory(S = [1., 2., 3., 5.], Y = [0.5, 0.5, 0.6, 0.7], lanes = ['1']*4)
194 >>> t.differentiate() # doctest:+ELLIPSIS
195 [1.0, 0.0, '1'] [1.0, 0.099..., '1'] [2.0, 0.099..., '1']
196 >>> t.differentiate(True) # doctest:+ELLIPSIS
197 [1.0, 0.0, '1'] [1.0, 0.099..., '1'] [2.0, 0.099..., '1'] [2.0, 0.099..., '1']
198 >>> t = CurvilinearTrajectory(S = [1.], Y = [0.5], lanes = ['1'])
199 >>> t.differentiate().empty()
200 True
201
202 >>> o1 = MovingObject.generate(1, Point(1., 2.), Point(1., 1.), TimeInterval(0,10))
203 >>> o1.features = [o1]
204 >>> o2 = MovingObject.generate(2, Point(14., 14.), Point(1., 0.), TimeInterval(14,20))
205 >>> o2.features = [o2]
206 >>> o3 = MovingObject.generate(3, Point(2., 2.), Point(1., 1.), TimeInterval(2,12))
207 >>> o3.features = [o3]
208 >>> o13 = MovingObject.concatenate(o1, o3, 4)
209 >>> o13.getNum()
210 4
211 >>> o13.getTimeInterval() == TimeInterval(0,12)
212 True
213 >>> t=5
214 >>> o13.getPositionAtInstant(t) == (o1.getPositionAtInstant(t)+o3.getPositionAtInstant(t)).divide(2)
215 True
216 >>> len(o13.getFeatures())
217 2
218 >>> o12 = MovingObject.concatenate(o1, o2, 5)
219 >>> o12.getTimeInterval() == TimeInterval(o1.getFirstInstant(), o2.getLastInstant())
220 True
221 >>> v = o12.getVelocityAtInstant(12)
222 >>> v == Point(3./4, 2./4)
223 True
224 >>> o12.getPositionAtInstant(11) == o1.getPositionAtInstant(10)+v
225 True
226 >>> len(o12.getFeatures())
227 3
228
229 >>> o1 = MovingObject.generate(1, Point(0., 2.), Point(0., 1.), TimeInterval(0,2))
230 >>> o1.classifyUserTypeSpeedMotorized(0.5, np.median)
231 >>> userTypeNames[o1.getUserType()]
232 'car'
233 >>> o1.classifyUserTypeSpeedMotorized(1.5, np.median)
234 >>> userTypeNames[o1.getUserType()]
235 'pedestrian'
236
237 >>> o1 = MovingObject.generate(1, Point(0.,0.), Point(1.,0.), TimeInterval(0,10))
238 >>> gt1 = BBMovingObject(1, TimeInterval(0,10), MovingObject.generate(1, Point(0.2,0.6), Point(1.,0.), TimeInterval(0,10)), MovingObject.generate(2, Point(-0.2,-0.4), Point(1.,0.), TimeInterval(0,10)))
239 >>> gt1.computeCentroidTrajectory()
240 >>> computeClearMOT([gt1], [], 0.2, 0, 10)
241 (None, 0.0, 11, 0, 0, 11, None, None)
242 >>> computeClearMOT([], [o1], 0.2, 0, 10)
243 (None, None, 0, 0, 11, 0, None, None)
244 >>> computeClearMOT([gt1], [o1], 0.2, 0, 10) # doctest:+ELLIPSIS
245 (0.0999..., 1.0, 0, 0, 0, 11, None, None)
246 >>> computeClearMOT([gt1], [o1], 0.05, 0, 10)
247 (None, -1.0, 11, 0, 11, 11, None, None)
248
249 >>> o1 = MovingObject(1, TimeInterval(0,3), positions = Trajectory([list(range(4)), [0.1, 0.1, 1.1, 1.1]]))
250 >>> o2 = MovingObject(2, TimeInterval(0,3), positions = Trajectory([list(range(4)), [0.9, 0.9, -0.1, -0.1]]))
251 >>> gt1 = BBMovingObject(1, TimeInterval(0,3), MovingObject(positions = Trajectory([list(range(4)), [0.]*4])), MovingObject(positions = Trajectory([list(range(4)), [0.]*4])))
252 >>> gt1.computeCentroidTrajectory()
253 >>> gt2 = BBMovingObject(2, TimeInterval(0,3), MovingObject(positions = Trajectory([list(range(4)), [1.]*4])), MovingObject(positions = Trajectory([list(range(4)), [1.]*4])))
254 >>> gt2.computeCentroidTrajectory()
255 >>> computeClearMOT([gt1, gt2], [o1, o2], 0.2, 0, 3) # doctest:+ELLIPSIS
256 (0.1..., 0.75, 0, 2, 0, 8, None, None)
257 >>> computeClearMOT([gt2, gt1], [o2, o1], 0.2, 0, 3) # doctest:+ELLIPSIS
258 (0.1..., 0.75, 0, 2, 0, 8, None, None)
259 >>> computeClearMOT([gt1], [o1, o2], 0.2, 0, 3)
260 (0.1, -0.25, 0, 1, 4, 4, None, None)
261 >>> computeClearMOT([gt1], [o2, o1], 0.2, 0, 3) # symmetry
262 (0.1, -0.25, 0, 1, 4, 4, None, None)
263 >>> computeClearMOT([gt1, gt2], [o1], 0.2, 0, 3) # doctest:+ELLIPSIS
264 (0.100..., 0.375, 4, 1, 0, 8, None, None)
265 >>> computeClearMOT([gt2, gt1], [o1], 0.2, 0, 3) # doctest:+ELLIPSIS
266 (0.100..., 0.375, 4, 1, 0, 8, None, None)
267 >>> computeClearMOT([gt1, gt2], [o1, o2], 0.08, 0, 3)
268 (None, -1.0, 8, 0, 8, 8, None, None)