def prioritizedRunningSum(self):
force = (0, 0)
remaining_reservoir = self.force_reservoir
for behaviorKeyword in self.keywords:
action = self.actions[behaviorKeyword]
if action is None:
continue
arguments = (self.agent,) + action
behaviorFunction = self.steeringFunctions[behaviorKeyword]
weight = self.weight[behaviorKeyword]
forceForBehavior = calculate.multiplyVectorAndScalar(behaviorFunction(*arguments),
weight)
forceForBehavior = vector.truncate(forceForBehavior,
remaining_reservoir)
magnitudeForBehaviorForce = vector.getMagnitude(forceForBehavior)
remaining_reservoir -= magnitudeForBehaviorForce
force = calculate.addVectors(force,
forceForBehavior)
if remaining_reservoir <= 0:
break
force = vector.truncate(force,
self.agent.getMaxForce())
return force
def update(self,
timeElapsed):
current_time = self.world.current_time
if self.timeOfNormalColor and current_time < self.timeOfNormalColor:
self.color = (random.random(), random.random(), random.random())
elif self.timeOfNormalColor:
self.timeOfNormalColor = None
self.color = self.normalColor
world = self.world
maxspeed = self.maxSpeed
throttlespeed = self.throttleSpeed
maxforce = self.maxForce
minDetectionLength = self.minDetectionLength
for stateMachine in self.stateMachines:
stateMachine.update()
for turret in self.turrets:
turret.update(timeElapsed)
self.launch()
force = self.steeringController.calculate()
force = vector.truncate(vectorTuple=force,
cap=maxforce)
acceleration = calculate.multiplyVectorAndScalar(vector=force,
scalar=timeElapsed / (self.mass * 1000.0))
velocity = calculate.addVectors(self.velocity,
acceleration)
velocity = vector.truncate(velocity,
throttlespeed)
self.velocity = velocity
speed = vector.getMagnitude(velocity)
(x, y) = calculate.addPointAndVector(self.position,
velocity)
self.position = (x, y)
self.obstacleDetectionDimensions[0] =\
minDetectionLength + (speed / maxspeed) * minDetectionLength
def weightedTruncatedSum(self):
force = (0, 0)
action_list = self.action_list
for behavior in self.keyword_list:
if self.on(behavior):
forceForBehavior = calculate.multiplyVectorAndScalar(action_list[behavior].getWeight(),
action_list[behavior].executeFunction())
force = calculate.addVectors(force,
forceForBehavior)
force = vector.truncate(force,
self.parent_agent.getMaxForce())
return force
def test_forceFiveMasOne_returnOne(self):
startVector = (0, 5)
newVector = vector.truncate(startVector,
1)
self.assertEquals((0, 1),
newVector)
