>>> import prediction
>>> import moving

>>> et = prediction.PredictedTrajectoryConstant(moving.Point(0,0), moving.Point(1,0))
>>> et.predictPosition(4) # doctest:+ELLIPSIS
(4.0...,0.0...)
>>> et.predictPosition(1) # doctest:+ELLIPSIS
(1.0...,0.0...)

>>> et = prediction.PredictedTrajectoryConstant(moving.Point(0,0), moving.Point(1,0), moving.NormAngle(0.1,0), maxSpeed = 2)
>>> et.predictPosition(10) # doctest:+ELLIPSIS
(15.5...,0.0...)
>>> et.predictPosition(11) # doctest:+ELLIPSIS
(17.5...,0.0...)
>>> et.predictPosition(12) # doctest:+ELLIPSIS
(19.5...,0.0...)

>>> import random
>>> acceleration = lambda: random.uniform(-0.5,0.5)
>>> steering = lambda: random.uniform(-0.1,0.1)
>>> et = prediction.PredictedTrajectoryNormalAdaptation(moving.Point(0,0),moving.Point(1,1), acceleration, steering, maxSpeed = 2)
>>> p = et.predictPosition(500)
>>> from numpy import max
>>> max(et.getPredictedSpeeds()) <= 2.
True