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changeset 466:e891a41c6c75

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name change in prediction.py
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Wed, 05 Mar 2014 17:47:26 -0500
parents 16fe64136506
children 08b67c9baca2 5304299e53a5
files python/prediction.py python/tests/prediction.txt
diffstat 2 files changed, 19 insertions(+), 8 deletions(-) [+]
line wrap: on
line diff
--- a/python/prediction.py	Thu Feb 27 03:30:28 2014 -0500
+++ b/python/prediction.py	Wed Mar 05 17:47:26 2014 -0500
@@ -47,8 +47,19 @@
     def getControl(self):
         return self.control
 
-class PredictedTrajectoryNormalAdaptation(PredictedTrajectory):
-    '''Random small adaptation of vehicle control '''
+class PredictedTrajectoryPrototype(PredictedTrajectory):
+    '''Predicted trajectory that follows a prototype trajectory
+    The prototype is in the format of a moving.Trajectory: it could be
+    1. an observed trajectory (extracted from video)
+    2. a generic polyline (eg the road centerline) that a vehicle is supposed to follow
+
+    Prediction can be done
+    1. at constant speed (the instant speed of the user'''
+
+    def __init__(self)
+
+class PredictedTrajectoryRandomControl(PredictedTrajectory):
+    '''Random vehicle control: suitable for normal adaptation'''
     def __init__(self, initialPosition, initialVelocity, accelerationDistribution, steeringDistribution, probability = 1., maxSpeed = None):
         '''Constructor
         accelerationDistribution and steeringDistribution are distributions 
@@ -245,11 +256,11 @@
             velocities = [obj.getVelocityAtInstant(instant)]
         for i in xrange(self.nPredictedTrajectories):
             for initialPosition,initialVelocity in zip(positions, velocities):
-                predictedTrajectories.append(PredictedTrajectoryNormalAdaptation(initialPosition, 
-                                                                                 initialVelocity, 
-                                                                                 self.accelerationDistribution, 
-                                                                                 self.steeringDistribution, 
-                                                                                 maxSpeed = self.maxSpeed))
+                predictedTrajectories.append(PredictedTrajectoryRandomControl(initialPosition, 
+                                                                              initialVelocity, 
+                                                                              self.accelerationDistribution, 
+                                                                              self.steeringDistribution, 
+                                                                              maxSpeed = self.maxSpeed))
         return predictedTrajectories
 
 class PointSetPredictionParameters(PredictionParameters):
--- a/python/tests/prediction.txt	Thu Feb 27 03:30:28 2014 -0500
+++ b/python/tests/prediction.txt	Wed Mar 05 17:47:26 2014 -0500
@@ -18,7 +18,7 @@
 >>> 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)
+>>> et = prediction.PredictedTrajectoryRandomControl(moving.Point(0,0),moving.Point(1,1), acceleration, steering, maxSpeed = 2)
 >>> p = et.predictPosition(500)
 >>> from numpy import max
 >>> max(et.getPredictedSpeeds()) <= 2.