Mercurial Hosting > traffic-intelligence
view python/tests/moving.txt @ 748:d99866b0528a
merged latest change
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
---|---|
date | Fri, 02 Oct 2015 11:30:15 -0400 |
parents | ad31520e81b5 |
children | f8e0a8ea8402 |
line wrap: on
line source
>>> from moving import * >>> import storage >>> import numpy as np >>> Interval().empty() True >>> Interval(0,1).empty() False >>> Interval(0,1) [0, 1] >>> Interval(0,1).length() 1.0 >>> Interval(23.2,24.9).length() 1.6999999999999993 >>> Interval(10,8).length() 0.0 >>> TimeInterval(0,1).length() 2.0 >>> TimeInterval(10,8).length() 0.0 >>> [i for i in TimeInterval(9,13)] [9, 10, 11, 12, 13] >>> TimeInterval(2,5).equal(TimeInterval(2,5)) True >>> TimeInterval(2,5).equal(TimeInterval(2,4)) False >>> TimeInterval(2,5).equal(TimeInterval(5,2)) False >>> TimeInterval(3,6).distance(TimeInterval(4,6)) 0 >>> TimeInterval(3,6).distance(TimeInterval(6,10)) 0 >>> TimeInterval(3,6).distance(TimeInterval(8,10)) 2 >>> TimeInterval(20,30).distance(TimeInterval(3,15)) 5 >>> TimeInterval.unionIntervals([TimeInterval(3,6), TimeInterval(8,10),TimeInterval(11,15)]) [3, 15] >>> Point(3,4)-Point(1,7) (2.000000,-3.000000) >>> -Point(1,2) (-1.000000,-2.000000) >>> Point(1,2).multiply(0.5) (0.500000,1.000000) >>> Point(3,2).norm2Squared() 13 >>> Point.distanceNorm2(Point(3,4),Point(1,7)) 3.605551275463989 >>> Point(3,2).inPolygon(np.array([[0,0],[1,0],[1,1],[0,1]])) False >>> Point(3,2).inPolygon(np.array([[0,0],[4,0],[4,3],[0,3]])) True >>> predictPositionNoLimit(10, Point(0,0), Point(1,1)) # doctest:+ELLIPSIS ((1.0...,1.0...), (10.0...,10.0...)) >>> segmentIntersection(Point(0,0), Point(0,1), Point(1,1), Point(2,3)) >>> segmentIntersection(Point(0,1), Point(0,3), Point(1,0), Point(3,1)) >>> segmentIntersection(Point(0.,0.), Point(2.,2.), Point(0.,2.), Point(2.,0.)) (1.000000,1.000000) >>> segmentIntersection(Point(0,0), Point(4,4), Point(0,4), Point(4,0)) (2.000000,2.000000) >>> segmentIntersection(Point(0,1), Point(1,2), Point(2,0), Point(3,2)) >>> left = Trajectory.fromPointList([(92.291666666666686, 102.99239033124439), (56.774193548387103, 69.688898836168306)]) >>> middle = Trajectory.fromPointList([(87.211021505376351, 93.390778871978512), (59.032258064516128, 67.540286481647257)]) >>> right = Trajectory.fromPointList([(118.82392473118281, 115.68263205013426), (63.172043010752688, 66.600268576544309)]) >>> alignments = [left, middle, right] >>> for a in alignments: a.computeCumulativeDistances() >>> getSYfromXY(Point(73, 82), alignments) [1, 0, (73.819977,81.106170), 18.172277808821125, 18.172277808821125, 1.2129694042343868] >>> getSYfromXY(Point(78, 83), alignments, 0.5) [1, 0, (77.033188,84.053889), 13.811799123113715, 13.811799123113715, -1.4301775140225983] >>> Trajectory().length() 0 >>> t1 = Trajectory([[0.5,1.5,2.5],[0.5,3.5,6.5]]) >>> t1.length() == 3. True >>> t1[1] (1.500000,3.500000) >>> t1.differentiate() (1.000000,3.000000) (1.000000,3.000000) >>> t1.differentiate(True) (1.000000,3.000000) (1.000000,3.000000) (1.000000,3.000000) >>> t1 = Trajectory([[0.5,1.5,3.5],[0.5,2.5,7.5]]) >>> t1.differentiate() (1.000000,2.000000) (2.000000,5.000000) >>> t1.computeCumulativeDistances() >>> t1.getDistance(0) 2.23606797749979 >>> t1.getDistance(1) 5.385164807134504 >>> t1.getDistance(2) Index 2 beyond trajectory length 3-1 >>> t1.getCumulativeDistance(0) 0.0 >>> t1.getCumulativeDistance(1) 2.23606797749979 >>> t1.getCumulativeDistance(2) 7.6212327846342935 >>> t1.getCumulativeDistance(3) Index 3 beyond trajectory length 3 >>> from utils import LCSS >>> lcss = LCSS(lambda x,y: Point.distanceNorm2(x,y) <= 0.1) >>> Trajectory.lcss(t1, t1, lcss) 3 >>> lcss = LCSS(lambda p1, p2: (p1-p2).normMax() <= 0.1) >>> Trajectory.lcss(t1, t1, lcss) 3 >>> p1=Point(0,0) >>> p2=Point(1,0) >>> v1 = Point(0.1,0.1) >>> v2 = Point(-0.1, 0.1) >>> abs(Point.timeToCollision(p1, p2, v1, v2, 0.)-5.0) < 0.00001 True >>> abs(Point.timeToCollision(p1, p2, v1, v2, 0.1)-4.5) < 0.00001 True >>> p1=Point(0,1) >>> p2=Point(1,0) >>> v1 = Point(0,0.1) >>> v2 = Point(0.1, 0) >>> Point.timeToCollision(p1, p2, v1, v2, 0.) == None True >>> Point.timeToCollision(p2, p1, v2, v1, 0.) == None True >>> Point.midPoint(p1, p2) (0.500000,0.500000) >>> objects = storage.loadTrajectoriesFromSqlite('../samples/laurier.sqlite', 'object') >>> len(objects) 5 >>> objects[0].hasFeatures() False >>> features = storage.loadTrajectoriesFromSqlite('../samples/laurier.sqlite', 'feature') >>> for o in objects: o.setFeatures(features) >>> objects[0].hasFeatures() True >>> o1 = MovingObject.generate(Point(-5.,0.), Point(1.,0.), TimeInterval(0,10)) >>> o2 = MovingObject.generate(Point(0.,-5.), Point(0.,1.), TimeInterval(0,10)) >>> MovingObject.computePET(o1, o2, 0.1) 0.0 >>> o2 = MovingObject.generate(Point(0.,-5.), Point(0.,1.), TimeInterval(5,15)) >>> MovingObject.computePET(o1, o2, 0.1) 5.0 >>> t = CurvilinearTrajectory(S = [1., 2., 3., 5.], Y = [0.5, 0.5, 0.6, 0.7], lanes = ['1']*4) >>> t.differentiate() # doctest:+ELLIPSIS [1.0, 0.0, '1'] [1.0, 0.099..., '1'] [2.0, 0.099..., '1'] >>> t.differentiate(True) # doctest:+ELLIPSIS [1.0, 0.0, '1'] [1.0, 0.099..., '1'] [2.0, 0.099..., '1'] [2.0, 0.099..., '1'] >>> t = CurvilinearTrajectory(S = [1.], Y = [0.5], lanes = ['1']) >>> t.differentiate().empty() True >>> o1 = MovingObject.generate(Point(0., 2.), Point(0., 1.), TimeInterval(0,2)) >>> o1.classifyUserTypeSpeedMotorized(0.5, np.median) >>> userTypeNames[o1.getUserType()] 'car' >>> o1.classifyUserTypeSpeedMotorized(1.5, np.median) >>> userTypeNames[o1.getUserType()] 'pedestrian' >>> o1 = MovingObject.generate(Point(0.,0.), Point(1.,0.), TimeInterval(0,10)) >>> gt1 = BBAnnotation(1, TimeInterval(0,10), MovingObject.generate(Point(0.2,0.6), Point(1.,0.), TimeInterval(0,10)), MovingObject.generate(Point(-0.2,-0.4), Point(1.,0.), TimeInterval(0,10))) >>> gt1.computeCentroidTrajectory() >>> computeClearMOT([gt1], [], 0.2, 0, 10) (None, 0.0, 11, 0, 0, 11) >>> computeClearMOT([], [o1], 0.2, 0, 10) (None, None, 0, 0, 11, 0) >>> computeClearMOT([gt1], [o1], 0.2, 0, 10) # doctest:+ELLIPSIS (0.0999..., 1.0, 0, 0, 0, 11) >>> computeClearMOT([gt1], [o1], 0.05, 0, 10) (None, -1.0, 11, 0, 11, 11) >>> o1 = MovingObject(1, TimeInterval(0,3), positions = Trajectory([range(4), [0.1, 0.1, 1.1, 1.1]])) >>> o2 = MovingObject(2, TimeInterval(0,3), positions = Trajectory([range(4), [0.9, 0.9, -0.1, -0.1]])) >>> gt1 = BBAnnotation(1, TimeInterval(0,3), MovingObject(positions = Trajectory([range(4), [0.]*4])), MovingObject(positions = Trajectory([range(4), [0.]*4]))) >>> gt1.computeCentroidTrajectory() >>> gt2 = BBAnnotation(2, TimeInterval(0,3), MovingObject(positions = Trajectory([range(4), [1.]*4])), MovingObject(positions = Trajectory([range(4), [1.]*4]))) >>> gt2.computeCentroidTrajectory() >>> computeClearMOT([gt1, gt2], [o1, o2], 0.2, 0, 3) # doctest:+ELLIPSIS (0.1..., 0.75, 0, 2, 0, 8) >>> computeClearMOT([gt2, gt1], [o2, o1], 0.2, 0, 3) # doctest:+ELLIPSIS (0.1..., 0.75, 0, 2, 0, 8) >>> computeClearMOT([gt1], [o1, o2], 0.2, 0, 3) (0.1, -0.25, 0, 1, 4, 4) >>> computeClearMOT([gt1], [o2, o1], 0.2, 0, 3) # symmetry (0.1, -0.25, 0, 1, 4, 4) >>> computeClearMOT([gt1, gt2], [o1], 0.2, 0, 3) # doctest:+ELLIPSIS (0.100..., 0.375, 4, 1, 0, 8) >>> computeClearMOT([gt2, gt1], [o1], 0.2, 0, 3) # doctest:+ELLIPSIS (0.100..., 0.375, 4, 1, 0, 8) >>> computeClearMOT([gt1, gt2], [o1, o2], 0.08, 0, 3) (None, -1.0, 8, 0, 8, 8)