def __init__(self):
self.scale = ReadScale()
scores = ReadRanks()
score_pmf = thinkbayes.MakePmfFromDict(dict(scores))
self.raw = self.ReverseScale(score_pmf)
self.max_score = max(self.raw.Values())
self.prior = DivideValues(self.raw, denom=self.max_score)
def makeOneCauseMI(p=0.5, q=0.5):
px=prob.MakePmfFromDict({"H":p, "L":1.0-p})
joint = prob.Joint()
for v1, p1 in px.Items():
if v1 =="H":
joint.Set((v1, "H"), p1*q)
joint.Set((v1, "L"), p1*q)
else:
joint.Set((v1, "H"), 0.0)
joint.Set((v1, "L"), p1*1.0)
py=joint.Marginal(1)
return px, py, joint
def __init__(self):
self.scale = ReadScale()
scores = ReadRanks()
score_pmf = thinkbayes.MakePmfFromDict(dict(scores))
self.raw = self.ReverseScale(score_pmf)
self.max_score = max(self.raw.Values())
self.prior = DivideValues(self.raw, denom=self.max_score)
center = -0.05
width = 1.8
self.difficulties = MakeDifficulties(center, width, self.max_score)