def driftMood(self, dt = None, curMood = None):
now = globalClock.getFrameTime()
if not hasattr(self, 'lastDriftTime'):
self.lastDriftTime = now
if dt is None:
dt = now - self.lastDriftTime
self.lastDriftTime = now
if dt <= 0.0:
return
if curMood is None:
curMood = self
def doDrift(curValue, timeToMedian, dt = float(dt)):
newValue = curValue + dt / (timeToMedian * 7200)
return min(max(newValue, 0.0), 1.0)
self.boredom = doDrift(curMood.boredom, self.tBoredom)
self.loneliness = doDrift(curMood.loneliness, self.tLoneliness)
self.sadness = doDrift(curMood.sadness, self.tSadness)
self.fatigue = doDrift(curMood.fatigue, self.tFatigue)
self.hunger = doDrift(curMood.hunger, self.tHunger)
self.confusion = doDrift(curMood.confusion, self.tConfusion)
self.excitement = doDrift(curMood.excitement, self.tExcitement)
self.surprise = doDrift(curMood.surprise, self.tSurprise)
self.affection = doDrift(curMood.affection, self.tAffection)
abuse = average(curMood.hunger, curMood.hunger, curMood.hunger, curMood.boredom, curMood.loneliness)
tipPoint = 0.6
if abuse < tipPoint:
tAnger = lerp(self.tAngerDec, -PetMood.LONGTIME, abuse / tipPoint)
else:
tAnger = lerp(PetMood.LONGTIME, self.tAngerInc, (abuse - tipPoint) / (1.0 - tipPoint))
self.anger = doDrift(curMood.anger, tAnger)
self.announceChange()
return
def driftMood(self, dt=None, curMood=None):
# Pass in a dt to simulate mood over a specific amount of time.
# If dt not passed in, simulates based on time elapsed since last call.
# Typical call pattern:
# driftMood(timeSinceLastSeen)
# driftMood()
# driftMood()
# ...
#
# If you want to calculate mood drift using another PetMood as the
# starting point, pass it in as curMood. This is the recommended
# method for simulating mood on the client, where the results are
# not being stored in the database:
# driftMood(timeSinceLastSeen(), lastMood)
# ...
# driftMood(timeSinceLastSeen(), lastMood)
# ...
# driftMood(timeSinceLastSeen(), lastMood)
#
# The resulting mood will match the mood calculated by the AI
# (using the first method, above) when the pet comes into existence
# TODO: add variation to this. Over long dt's, add in a sine wave,
# some random noise, etc.
#print "dt is %s" % dt
now = globalClock.getFrameTime()
if not hasattr(self, 'lastDriftTime'):
self.lastDriftTime = now
if dt is None:
dt = now - self.lastDriftTime
self.lastDriftTime = now
if dt <= 0.:
return
if __debug__:
try:
dt *= simbase.petMoodTimescale
except:
pass
if curMood is None:
curMood = self
# linear motion, for now
def doDrift(curValue, timeToMedian, dt=float(dt)):
# mood = mood + secs/((hrs/2*(mood/2))*(secs/hr))
""" use this to make sure that the numbers are even moving
print curValue - (curValue + dt/(timeToMedian*7200))
"""
newValue = curValue + dt / (timeToMedian * 7200) #3600)#60*60)
return clampScalar(newValue, 0., 1.)
self.boredom = doDrift(curMood.boredom, self.tBoredom)
# these are currently never used
#self.restlessness = doDrift(curMood.restlessness, self.tRestlessness)
#self.playfulness = doDrift(curMood.playfulness, self.tPlayfulness)
self.loneliness = doDrift(curMood.loneliness, self.tLoneliness)
self.sadness = doDrift(curMood.sadness, self.tSadness)
self.fatigue = doDrift(curMood.fatigue, self.tFatigue)
self.hunger = doDrift(curMood.hunger, self.tHunger)
self.confusion = doDrift(curMood.confusion, self.tConfusion)
self.excitement = doDrift(curMood.excitement, self.tExcitement)
self.surprise = doDrift(curMood.surprise, self.tSurprise)
self.affection = doDrift(curMood.affection, self.tAffection)
# for the sake of long-haul calculations, do the feedback calcs
# after the simple independent calcs
abuse = average(curMood.hunger, curMood.hunger, curMood.hunger,
curMood.boredom, curMood.loneliness)
tipPoint = .6
if abuse < tipPoint:
tAnger = lerp(self.tAngerDec, -PetMood.LONGTIME, abuse / tipPoint)
else:
tAnger = lerp(PetMood.LONGTIME, self.tAngerInc,
(abuse - tipPoint) / (1. - tipPoint))
self.anger = doDrift(curMood.anger, tAnger)
self.announceChange()
