def testProbabilisticDocs(self):
rf = ProbabilisticRankingFunction(3, self.weights)
rf.init_ranking(self.query)
for _ in range(self.query.get_document_count()):
docids = list(rf.docids)
docid = rf.next()
self.assertIn(docid, docids)
self.assertNotIn(docid, rf.docids)
def testProbabilisticDocs(self):
rf = ProbabilisticRankingFunction(3, self.weights)
rf.init_ranking(self.query)
for _ in range(self.query.get_document_count()):
docids = list(rf.docids)
docid = rf.next()
self.assertIn(docid, docids)
self.assertNotIn(docid, rf.docids)
def testProbabilisticSum(self):
rf = ProbabilisticRankingFunction(3, self.weights)
rf.init_ranking(self.query)
self.assertAlmostEqual(
1,
sum([
rf.get_document_probability(i)
for i in range(self.query.get_document_count())
]))
def testProbabilisticSum(self):
rf = ProbabilisticRankingFunction(3, self.weights)
rf.init_ranking(self.query)
self.assertAlmostEqual(1, sum([rf.get_document_probability(i) for i in
range(self.query.get_document_count())]))
def testProbabilisticDeterministic(self):
rf = ProbabilisticRankingFunction(3, self.weights)
rf.init_ranking(self.query)
self.assertIn([rf.next_det() for _ in
range(self.query.get_document_count())], [[1, 2, 3, 0],
[1, 3, 2, 0]])
def testProbabilisticProbabilities(self):
rf = ProbabilisticRankingFunction(3, self.weights)
rf.init_ranking(self.query)
self.assertAlmostEqual(0.0132678, rf.get_document_probability(0))
self.assertAlmostEqual(0.8491400, rf.get_document_probability(1))
def testProbabilisticDeterministic(self):
rf = ProbabilisticRankingFunction(3, self.weights)
rf.init_ranking(self.query)
self.assertIn(
[rf.next_det() for _ in range(self.query.get_document_count())],
[[1, 2, 3, 0], [1, 3, 2, 0]])
def testProbabilisticProbabilities(self):
rf = ProbabilisticRankingFunction(3, self.weights)
rf.init_ranking(self.query)
self.assertAlmostEqual(0.0132678, rf.get_document_probability(0))
self.assertAlmostEqual(0.8491400, rf.get_document_probability(1))