Mercurial > hg > nsaunier > traffic-intelligence

comparison python/tests/moving.txt @ 576:0eff0471f9cb

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added functions to use trajectories as alignments
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Thu, 28 Aug 2014 16:42:13 -0400
parents cae4e5f3fe9f
children d0abd2ee17b9
comparison
equal deleted inserted replaced
575:13df64a9ff9d 576:0eff0471f9cb
94 (1.000000,3.000000) (1.000000,3.000000) (1.000000,3.000000) 94 (1.000000,3.000000) (1.000000,3.000000) (1.000000,3.000000)
95 >>> t1 = Trajectory([[0.5,1.5,3.5],[0.5,2.5,7.5]]) 95 >>> t1 = Trajectory([[0.5,1.5,3.5],[0.5,2.5,7.5]])
96 >>> t1.differentiate() 96 >>> t1.differentiate()
97 (1.000000,2.000000) (2.000000,5.000000) 97 (1.000000,2.000000) (2.000000,5.000000)
98 98
99 >>> t1.computeCumulativeDistances()
100 >>> t1.getDistance(0)
101 2.23606797749979
102 >>> t1.getDistance(1)
103 5.385164807134504
104 >>> t1.getCumulativeDistance(1)
105 7.6212327846342935
106 >>> t1.getCumulativeDistance(2)
107 Index 2 beyond trajectory length 3-1
108
109
99 >>> from utils import LCSS 110 >>> from utils import LCSS
100 >>> lcss = LCSS(lambda x,y: Point.distanceNorm2(x,y) <= 0.1) 111 >>> lcss = LCSS(lambda x,y: Point.distanceNorm2(x,y) <= 0.1)
101 >>> Trajectory.lcss(t1, t1, lcss) 112 >>> Trajectory.lcss(t1, t1, lcss)
102 3 113 3
103 >>> lcss = LCSS(lambda p1, p2: (p1-p2).normMax() <= 0.1) 114 >>> lcss = LCSS(lambda p1, p2: (p1-p2).normMax() <= 0.1)