>>> from moving import *
>>> 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
>>> 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).inPolygonNoShapely(np.array([[0,0],[1,0],[1,1],[0,1]]))
False
>>> Point(3,2).inPolygonNoShapely(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(0,1), 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.getTrajectoryInPolygonNoShapely(np.array([[0,0],[4,0],[4,3],[0,3]]))
(0.500000,0.500000)
>>> t1.getTrajectoryInPolygonNoShapely(np.array([[10,10],[14,10],[14,13],[10,13]])).length()
0

>>> 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

>>> 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(positions = Trajectory([[0]*3,[2]*3]), velocities = Trajectory([[0]*3,[1]*3]))
>>> o1.classifyUserTypeSpeedMotorized(0.5, np.median)
>>> userTypeNames[o1.getUserType()]
'car'
>>> o1.classifyUserTypeSpeedMotorized(0.5, np.mean)
>>> userTypeNames[o1.getUserType()]
'car'
>>> o1.classifyUserTypeSpeedMotorized(1.5, np.median)
>>> userTypeNames[o1.getUserType()]
'pedestrian'