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added rbo measure #15

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added rbo measure #15

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22 changes: 22 additions & 0 deletions diffir/measure/unsupervised.py
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Original file line number Diff line number Diff line change
Expand Up @@ -108,6 +108,26 @@ def kl_div(self, x, y):
y = y / y.sum()
return -(stats.entropy(x, y) + stats.entropy(y, x)) / 2

def rbo(self, x, y, p=0.95, depth=1000):
# adapted from <https://github.com/terrierteam/ir_measures/blob/main/ir_measures/providers/compat_provider.py>
from collections import Counter
x_set = set()
y_set = set()
score = 0.0
normalizer = 0.0
weight = 1.0
x = [d for d, s in Counter(x).most_common()]
y = [d for d, s in Counter(y).most_common()]
for i in range(depth):
if i < len(x):
x_set.add(x[i])
if i < len(y):
y_set.add(y[i])
score += weight*len(x_set.intersection(y_set))/(i + 1)
normalizer += weight
weight *= p
return score/normalizer

def _query_differences(self, run1, run2, *args, **kwargs):
"""
:param run1: TREC run. Has the format {qid: {docid: score}, ...}
Expand Down Expand Up @@ -146,6 +166,8 @@ def _query_differences(self, run1, run2, *args, **kwargs):
tau = (self.pearson_rank(union_score1, union_score2) + self.pearson_rank(union_score2, union_score1)) / 2
elif metric == "kldiv":
tau = self.kl_div(union_score1, union_score2)
elif metric == "rbo":
tau = self.rbo(run1[qid], run2[qid])
else:
raise ValueError("Metric {} not supported for the measure {}".format(self.metric, "metric"))
id2measure[qid] = tau
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2 changes: 1 addition & 1 deletion diffir/run.py
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Original file line number Diff line number Diff line change
Expand Up @@ -74,7 +74,7 @@ def __init__(self, dataset="none", queries="none", measure="topk", metric="weigh
self.queries = queries
if measure == "qrel":
self.measure = QrelMeasure(metric, topk)
elif measure in ["tauap", "weightedtau", "spearmanr", "pearsonrank", "kldiv"]:
elif measure in ["tauap", "weightedtau", "spearmanr", "pearsonrank", "kldiv", "rbo"]:
self.measure = TopkMeasure(measure, topk)
else:
raise ValueError("Measure {} is not supported".format(measure))
Expand Down