def SampleTopicRelWeights(state):
"""Computes P(zr|zt) for each zr, zt.
The return value is a matrix such that weights[i,j] = P(zr=j|zt=i)
"""
alpha = state.hypers['alpha']
counts = cCollect.TabulateTopicRelationCounts(state) + alpha
weights = cDists.SampleDirichletArray(counts)
return weights
def SampleTopicSubWeights(state):
"""Update the distribution over subjects for each table topic.
Computes P(zs|zt) for each zs, zt.
The return value is a matrix such that weights[i,j] = P(zs=j|zt=i)
"""
alpha = state.hypers['alpha_sub']
counts = cCollect.TabulateTopicSubjectCounts(state) + alpha
weights = cDists.SampleDirichletArray(counts)
return weights
def SampleTypeSubWeights(state):
obs_counts = cCollect.TabulateRangeSubjectCounts(state)
alpha = state.hypers['alpha']
weights = cDists.SampleDirichletArray(obs_counts + alpha)
return weights
def SampleRelTokenWeights(state):
alpha = state.hypers['alpha_token']
counts = cCollect.TabulateRelationTokenCounts(state) + alpha
weights = cDists.SampleDirichletArray(counts)
return weights