def main():
gui = Gui()
generateGhost()
probs = getInitialDist()
while True:
gui.drawProb(probs)
pos = gui.getMouse()
if pos[1] > numRow-1:
if pos[0] >= numRow/2:
gui.setBlackColors()
moveGhost()
probs = calcForwardProb(probs)
else:
gui.drawEndBtn("blue")
pos = gui.getMouse()
result = isGhostThere(pos)
gui.drawResult(pos, result)
revealGhost()
break
else:
color = useSensor(pos)
gui.drawSensorReading(pos, color)
probs = getNewPosDist(pos, color, probs)
gui.getMouse()
def main():
gui = Gui()
rawData = readDataset(dataPath)
data = parseData(rawData)
gui.drawData(data)
training, heldout, test = divideData(data)
rawdata = unlableData(heldout)
for sample in heldout:
classification = classify(training, sample)
print(sample, classification)
gui.getMouse()
def main():
gui = Gui()
rawData = readDataset(dataPath)
data = parseData(rawData)
gui.drawData(data)
# training, heldout, test = divideData(data)
gui.getMouse()
weights = learn(data)
if numClass == 2:
gui.drawDivision(weights[0])
gui.getMouse()
def main():
gui = Gui()
generateGhost()
iniProbs = getInitialDist()
particles = distributeParticles(particleNum, iniProbs)
probs = getProbs(particles)
while True:
gui.drawProb(probs)
pos = gui.getMouse()
if pos[1] > numRow-1:
if pos[0] >= numRow/2:
gui.setBlackColors()
moveGhost()
particles = moveParticles(particles)
probs = getProbs(particles)
else:
gui.drawEndBtn("blue")
pos = gui.getMouse()
result = isGhostThere(pos)
gui.drawResult(pos, result)
revealGhost()
break
else:
color = useSensor(pos)
gui.drawSensorReading(pos, color)
condProbs = getNewPosDist(pos, color, probs)
weights = weightParticles(particles, condProbs)
normWeights = normalize(weights)
particles = redistributeParticles(particles, normWeights)
probs = getProbs(particles)
gui.getMouse()
