Mercurial Hosting > traffic-intelligence
comparison python/tests/moving.txt @ 576:0eff0471f9cb
added functions to use trajectories as alignments
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
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date | Thu, 28 Aug 2014 16:42:13 -0400 |
parents | cae4e5f3fe9f |
children | d0abd2ee17b9 |
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575:13df64a9ff9d | 576:0eff0471f9cb |
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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) |