def isTrajHasAvoidPoints(trajectory, aimAction, initPlayerGrid, target1, target2, decisionSteps, conditionName):
trajectory = list(map(tuple, trajectory))
if conditionName == 'expCondition':
avoidPoint = calAvoidPoints(initPlayerGrid, decisionSteps)
hasMidPoint = 1 if avoidPoint in trajectory else 0
if conditionName == 'lineCondition':
avoidPoint = calMidPoints(initPlayerGrid, target1, target2)
hasMidPoint = 1 if avoidPoint in trajectory else 0
# hasMidPoint = 1 if aimAction[decisionSteps] == aimAction[decisionSteps - 1] else 0
return hasMidPoint
def calDisToMidPointTrajLen(trajectory, target1, target2):
trajectory = list(map(tuple, trajectory))
playerGrid = trajectory[0]
midPoint = calMidPoints(playerGrid, target1, target2)
disToMidPointTraj = [
calculateGridDis(grid, midPoint) for grid in trajectory
]
meanDis = np.mean(disToMidPointTraj)
return meanDis
def calDisToMidPointTraj(trajectory, target1, target2):
trajectory = list(map(tuple, trajectory))
playerGrid = trajectory[0]
midPoint = calMidPoints(playerGrid, target1, target2)
disToMidPointTraj = [
calculateGridDis(grid, midPoint) for grid in trajectory
]
x = np.divide(np.arange(len(disToMidPointTraj)),
len(disToMidPointTraj) - 1)
y = np.array(disToMidPointTraj)
f = interp1d(x, y, kind='nearest')
xnew = np.linspace(0., 1., 30)
posterior = f(xnew)
return posterior
def __call__(self, selfGrid, target1, target2, trajectory):
initGrid = trajectory[0]
goal = trajectory[-1]
midpoint = calMidPoints(selfGrid, target1, target2)
zone = calculateAvoidCommitmnetZoneAll(initGrid, target1, target2)
if midpoint:
disToMidPoint = calculateGridDis(selfGrid, midpoint)
disToTargets = [calculateGridDis(selfGrid, target) for target in[target1, target2]]
isInDeliberationArea = 1 if disToMidPoint < min(disToTargets) else 0
if isInDeliberationArea:
actionDis = self.goalPolicy(selfGrid, midpoint)
else:
actionDis = self.goalPolicy(selfGrid, goal)
else:
actionDis = self.goalPolicy(selfGrid, goal)
return actionDis
def isTrajHasAvoidPoints(trajectory, aimAction, initPlayerGrid, target1, target2, decisionSteps, conditionName, obstacles):
trajectory = list(map(tuple, trajectory))
if conditionName == 'expCondition':
avoidPoint = calAvoidPoints(initPlayerGrid, decisionSteps)
hasMidPoint = 1 if avoidPoint in trajectory else 0
if decisionSteps == 0:
nextStep = trajectory[1]
nextStepInLineWithObstacles = [isGridsALine(nextStep, targetGrid) for targetGrid in obstacles]
hasMidPoint = 1 if sum(nextStepInLineWithObstacles) > 2 else 0
if decisionSteps == 1:
avoidPoint = calAvoidPoints(initPlayerGrid, decisionSteps - 1)
hasMidPoint = 1 if avoidPoint in trajectory else 0
if conditionName == 'lineCondition':
avoidPoint = calMidPoints(initPlayerGrid, target1, target2)
hasMidPoint = 1 if avoidPoint in trajectory else 0
# hasMidPoint = 1 if aimAction[decisionSteps] == aimAction[decisionSteps - 1] else 0
return hasMidPoint
def isTrajHasMidPoints(trajectory, target1, target2):
trajectory = list(map(tuple, trajectory))
initPlayerGrid = trajectory[0]
midPoint = calMidPoints(initPlayerGrid, target1, target2)
hasMidPoint = 1 if midPoint in trajectory else 0
return hasMidPoint
