def elapseTime(self):
transProb = util.loadTransProb()
#transProb = util.loadTransProb()
belief = util.Belief(self.belief.getNumRows(), self.belief.getNumCols(), 0.0)
#belief = self.getBelief()
for row in xrange(self.belief.getNumRows()):
for col in xrange(self.belief.getNumCols()):
if row in transProb and col in transProb[row]:
for newRow in transProb[row][col]:
for newCol, prob in transProb[row][col][newRow].iteritems():
belief.addProb(newRow, newCol, prob*self.belief.getProb(row, col))
else:
belief.setProb(row, col, self.getBelief().getProb(row, col))
#print belief.getSum()
#belief.normalize()
self.belief = belief
def elapseTime(self):
''' your code here'''
numRows = self.belief.getNumRows()
numCols = self.belief.getNumCols()
transProb = util.loadTransProb()
tempProb = []
for row in range(0, numRows):
temp = []
for col in range(0, numCols):
temp.append(self.belief.getProb(row, col))
self.belief.setProb(row, col, 0)
tempProb.append(temp)
for row in range(0, numRows):
for col in range(0, numCols):
# p: sum of transitionProbability * p(xt|evidence1:t)
if (row, col) in transProb:
for newPos, transitionP in transProb[(row, col)].iteritems():
self.belief.addProb(newPos[0], newPos[1], transitionP * tempProb[row][col])
def __init__(self, numRows, numCols):
self.belief = util.Belief(numRows, numCols)
# Load the transition probabilities and store them in an integer-valued defaultdict.
# Use self.transProbDict[oldTile][newTile] to get the probability of transitioning from oldTile to newTile.
self.transProb = util.loadTransProb()
self.transProbDict = dict()
for (oldTile, newTile) in self.transProb:
if not oldTile in self.transProbDict:
self.transProbDict[oldTile] = collections.defaultdict(int)
self.transProbDict[oldTile][newTile] = self.transProb[(oldTile, newTile)]
# Initialize the particles randomly.
self.particles = collections.defaultdict(int)
potentialParticles = self.transProbDict.keys()
for i in range(self.NUM_PARTICLES):
particleIndex = int(random.random() * len(potentialParticles))
self.particles[potentialParticles[particleIndex]] += 1
self.updateBelief()
def __init__(self, numRows, numCols):
self.belief = util.Belief(numRows, numCols)
# Load the transition probabilities and store them in a dict of Counters
# self.transProbDict[oldTile][newTile] = probability of transitioning from oldTile to newTile
self.transProb = util.loadTransProb()
self.transProbDict = dict()
for (oldTile, newTile) in self.transProb:
if not oldTile in self.transProbDict:
self.transProbDict[oldTile] = collections.Counter()
self.transProbDict[oldTile][newTile] = self.transProb[(oldTile, newTile)]
# Initialize the particles randomly
self.particles = collections.Counter()
potentialParticles = self.transProbDict.keys()
for i in range(self.NUM_PARTICLES):
particleIndex = int(random.random() * len(potentialParticles))
self.particles[potentialParticles[particleIndex]] += 1
self.updateBelief()
def __init__(self, numRows, numCols):
''' initialize any variables you will need later '''
self.belief = util.Belief(numRows, numCols)
self.transprob = util.loadTransProb()
self.probdic = {}
self.realtemp = {}
for key in self.transprob:
if not key[0] in self.probdic:
self.probdic[key[0]] = {}
self.realtemp[key[0]] = key[1]
self.probdic[key[0]][key[1]] = self.transprob[(key[0], key[1])]
else:
self.probdic[key[0]][key[1]] = self.transprob[(key[0], key[1])]
# move form transprob -> prodic
# make a random particle
keys = self.probdic.keys()
self.randomPart = {} # key = tile = (row, col)
for i in range(self.NUM_PARTICLES):
randomIndex = random.choice(keys)
if not randomIndex in self.randomPart:
self.randomPart[randomIndex] = 1
else:
self.randomPart[randomIndex] += 1
# update belief
NumRow = self.belief.getNumRows()
NumCol = self.belief.getNumCols()
new = util.Belief(NumRow, NumCol,
0) # its 0 make linear times O(numtile)
for key in self.randomPart:
new.setProb(key[0], key[1], self.randomPart[key])
new.normalize()
self.belief = new
def __init__(self, numRows, numCols):
self.belief = util.Belief(numRows, numCols)
# Load the transition probabilities and store them in an integer-valued defaultdict.
# Use self.transProbDict[oldTile][newTile] to get the probability of transitioning from oldTile to newTile.
self.transProb = util.loadTransProb()
self.transProbDict = dict()
for (oldTile, newTile) in self.transProb: # 遍历转移概率的keys
if not oldTile in self.transProbDict: # 同样,默认是指 键key 的集合.
self.transProbDict[oldTile] = collections.defaultdict(int)
self.transProbDict[oldTile][newTile] = self.transProb[(oldTile,
newTile)]
# 在构造 transProbDict - 它是一个字典的字典.（字典的嵌套）
# Initialize the particles randomly.
self.particles = collections.defaultdict(
int) # 索引是一个tile的位置(row,col), 对应的值是该位置上的粒子个数.
potentialParticles = list(
self.transProbDict.keys()) # 这时候存的是各个可能存在粒子的位置.
for i in range(self.NUM_PARTICLES):
particleIndex = int(random.random() * len(potentialParticles))
self.particles[potentialParticles[particleIndex]] += 1
self.updateBelief()
def __init__(self, numRows, numCols):
self.skipElapse = False ### ONLY USED BY GRADER.PY in case problem 3 has not been completed
# util.Belief is a class (constructor) that represents the belief for a single
# inference state of a single car (see util.py).
self.belief = util.Belief(numRows, numCols)
self.transProb = util.loadTransProb()
def __init__(self, numRows, numCols):
self.skipElapse = False ### ONLY USED BY GRADER.PY in case problem 3 has not been completed
self.belief = util.Belief(numRows, numCols)
self.transProb = util.loadTransProb()
def __init__(self, numRows, numCols):
self.skipElapse = False ### ONLY USED BY GRADER.PY in case problem 3 has not been completed
# util.Belief is a class (constructor) that represents the belief for a single
# inference state of a single car (see util.py).
self.belief = util.Belief(numRows, numCols)
self.transProb = util.loadTransProb()
def __init__(self, numRows, numCols):
self.skipElapse = False ### ONLY USED BY GRADER.PY in case problem 2 has not been completed
self.belief = util.Belief(numRows, numCols)
self.transProb = util.loadTransProb()
def __init__(self, numRows, numCols):
self.belief = util.Belief(numRows, numCols)
''' initialize any variables you will need later '''
self.transprob = util.loadTransProb()