def average_quantile(s, p):
negatives, positives = neg_gen(PathQuery(s, p, ''),
't',
return_positives=True)
pos_query = PathQuery(s, p, positives)
neg_query = PathQuery(s, p, negatives)
return util.average_quantile(scores(pos_query), scores(neg_query))
def performance(query):
s, r, t = query.s, query.r, query.t
negatives = neg_gen(query, 't')
pos_query = PathQuery(s, r, t)
neg_query = PathQuery(s, r, negatives)
# don't score queries with no negatives
if len(negatives) == 0:
query.quantile = np.nan
else:
query.quantile = util.average_quantile(scores(pos_query), scores(neg_query))
query.num_candidates = len(negatives) + 1
attributes = query.s, ','.join(query.r), query.t, str(query.quantile), str(query.num_candidates)
return '\t'.join(attributes)
def performance(query):
s, r, t = query.s, query.r, query.t
negatives = neg_gen(query, 't')
pos_query = PathQuery(s, r, t)
neg_query = PathQuery(s, r, negatives)
# don't score queries with no negatives
if len(negatives) == 0:
query.quantile = np.nan
else:
query.quantile = util.average_quantile(scores(pos_query),
scores(neg_query))
query.num_candidates = len(negatives) + 1
attributes = query.s, ','.join(query.r), query.t, str(
query.quantile), str(query.num_candidates)
return '\t'.join(attributes)
def average_quantile(s, p):
negatives, positives = neg_gen(PathQuery(s, p, ''), 't', return_positives=True)
pos_query = PathQuery(s, p, positives)
neg_query = PathQuery(s, p, negatives)
return util.average_quantile(scores(pos_query), scores(neg_query))
