def post_pred_map(self, groups, entity_pos, threadpool=None):
"""
Combines likelihood and the CRP
"""
# can't post-pred an assigned row
assert self.assignments[entity_pos] == NOT_ASSIGNED
assigned_entity_N = self._assigned_entity_count()
scores = np.zeros(len(groups))
rel_group_ids = np.zeros((len(self.relations), len(groups)),
dtype=np.int)
sizes = np.zeros(len(groups))
for gi, g in enumerate(groups):
rel_group_ids[:, gi] = self.gid_mapping[g]
gc = self.group_size(g)
if not self.fixed_k:
prior_score = util.crp_post_pred(gc, assigned_entity_N + 1,
self.alpha)
else:
prior_score = util.dm_post_pred(gc, assigned_entity_N + 1,
self.alpha, self.group_count())
scores[gi] += prior_score / self.temp
for ri, (t, r) in enumerate(self.relations):
scores += r.post_pred_map(t, rel_group_ids[ri].tolist(),
entity_pos, threadpool)
return scores
def post_pred_map(self, groups, entity_pos, threadpool = None):
"""
Combines likelihood and the CRP
"""
# can't post-pred an assigned row
assert self.assignments[entity_pos] == NOT_ASSIGNED
assigned_entity_N = self._assigned_entity_count()
scores = np.zeros(len(groups))
rel_group_ids = np.zeros((len(self.relations), len(groups)),
dtype=np.int)
sizes = np.zeros(len(groups))
for gi, g in enumerate(groups):
rel_group_ids[:, gi] = self.gid_mapping[g]
gc = self.group_size(g)
if not self.fixed_k:
prior_score = util.crp_post_pred(gc, assigned_entity_N+1, self.alpha)
else:
prior_score = util.dm_post_pred(gc, assigned_entity_N+1, self.alpha,
self.group_count())
scores[gi] += prior_score / self.temp
for ri, (t, r) in enumerate(self.relations):
scores += r.post_pred_map(t, rel_group_ids[ri].tolist(),
entity_pos, threadpool)
return scores
def post_pred(self, group_id, entity_pos):
"""
Combines likelihood and the CRP
"""
# can't post-pred an assigned row
assert self.assignments[entity_pos] == NOT_ASSIGNED
rel_groupid = self.gid_mapping[group_id]
scores = [r.post_pred(t, g, entity_pos) for g, (t, r) in zip(rel_groupid,
self.relations)]
gc = self.group_size(group_id)
assigned_entity_N = self._assigned_entity_count()
if not self.fixed_k:
prior_score = util.crp_post_pred(gc, assigned_entity_N+1, self.alpha)
else:
prior_score = util.dm_post_pred(gc, assigned_entity_N+1, self.alpha,
self.group_count())
return np.sum(scores) + prior_score/self.temp
def post_pred(self, group_id, entity_pos):
"""
Combines likelihood and the CRP
"""
# can't post-pred an assigned row
assert self.assignments[entity_pos] == NOT_ASSIGNED
rel_groupid = self.gid_mapping[group_id]
scores = [
r.post_pred(t, g, entity_pos)
for g, (t, r) in zip(rel_groupid, self.relations)
]
gc = self.group_size(group_id)
assigned_entity_N = self._assigned_entity_count()
if not self.fixed_k:
prior_score = util.crp_post_pred(gc, assigned_entity_N + 1,
self.alpha)
else:
prior_score = util.dm_post_pred(gc, assigned_entity_N + 1,
self.alpha, self.group_count())
return np.sum(scores) + prior_score / self.temp