def testExploitativeProbabilisticInterleaveExploit(self):
r1 = ProbabilisticRankingFunction(1, self.weights_1)
r2 = ProbabilisticRankingFunction(1, self.weights_2)
# exploration rate = 0.1
epi = ExploitativeProbabilisticInterleave("--exploration_rate=0.1")
r1.init_ranking(self.query)
r2.init_ranking(self.query)
(docids, probs) = epi._get_document_distribution(r1, r2)
exp_docids = [1, 3, 2, 0]
exp_probs = [0.456, 0.232, 0.156, 0.156]
self._prob_doc_test_helper(docids, exp_docids, probs, exp_probs)
# exploration rate = 0.0
epi = ExploitativeProbabilisticInterleave("--exploration_rate=0.0")
r1.init_ranking(self.query)
r2.init_ranking(self.query)
(docids, probs) = epi._get_document_distribution(r1, r2)
exp_docids = [1, 3, 2, 0]
exp_probs = [0.48, 0.24, 0.16, 0.12]
self._prob_doc_test_helper(docids, exp_docids, probs, exp_probs)
def testExploitativeProbabilisticInterleave(self):
r1 = ProbabilisticRankingFunction(1, self.weights_1)
r2 = ProbabilisticRankingFunction(1, self.weights_2)
r1.init_ranking(self.query)
r2.init_ranking(self.query)
epi = ExploitativeProbabilisticInterleave("--exploration_rate=0.5")
(docids, probs) = epi._get_document_distribution(r1, r2)
exp_docids = [1, 0, 3, 2]
exp_probs = [0.36, 0.3, 0.2, 0.14]
self._prob_doc_test_helper(docids, exp_docids, probs, exp_probs)
def testExploitativeProbabilisticInterleaveExploit(self):
r1 = ProbabilisticRankingFunction(1, self.weights_1)
r2 = ProbabilisticRankingFunction(1, self.weights_2)
# exploration rate = 0.1
epi = ExploitativeProbabilisticInterleave("--exploration_rate=0.1")
r1.init_ranking(self.query)
r2.init_ranking(self.query)
(docids, probs) = epi._get_document_distribution(r1, r2)
exp_docids = [1, 3, 2, 0]
exp_probs = [0.456, 0.232, 0.156, 0.156]
self._prob_doc_test_helper(docids, exp_docids, probs, exp_probs)
# exploration rate = 0.0
epi = ExploitativeProbabilisticInterleave("--exploration_rate=0.0")
r1.init_ranking(self.query)
r2.init_ranking(self.query)
(docids, probs) = epi._get_document_distribution(r1, r2)
exp_docids = [1, 3, 2, 0]
exp_probs = [0.48, 0.24, 0.16, 0.12]
self._prob_doc_test_helper(docids, exp_docids, probs, exp_probs)
def testExploitativeProbabilisticInterleave(self):
r1 = ProbabilisticRankingFunction(1, self.weights_1)
r2 = ProbabilisticRankingFunction(1, self.weights_2)
r1.init_ranking(self.query)
r2.init_ranking(self.query)
epi = ExploitativeProbabilisticInterleave("--exploration_rate=0.5")
(docids, probs) = epi._get_document_distribution(r1, r2)
exp_docids = [1, 0, 3, 2]
exp_probs = [0.36, 0.3, 0.2, 0.14]
self._prob_doc_test_helper(docids, exp_docids, probs, exp_probs)
def testExploitativeProbabilisticInterleaveThreeDocs(self):
epi = ExploitativeProbabilisticInterleave("--exploration_rate=0.5")
# prepare rankers
r1 = ProbabilisticRankingFunction(1, self.weights_1)
r2 = ProbabilisticRankingFunction(1, self.weights_2)
r1.init_ranking(self.query)
r2.init_ranking(self.query)
r1.rm_document(0)
r2.rm_document(0)
# test after document 0 was removed
(docids, probs) = epi._get_document_distribution(r1, r2)
exp_docids = [1, 3, 2]
exp_probs = [0.5034965, 0.29020979, 0.20629371]
self._prob_doc_test_helper(docids, exp_docids, probs, exp_probs)
# prepare rankers
r1.init_ranking(self.query)
r2.init_ranking(self.query)
r1.rm_document(3)
r2.rm_document(3)
# test after document 3 was removed
(docids, probs) = epi._get_document_distribution(r1, r2)
exp_docids = [1, 0, 2]
exp_probs = [0.45864662, 0.36466165, 0.17669173]
self._prob_doc_test_helper(docids, exp_docids, probs, exp_probs)
def testExploitativeProbabilisticInterleaveThreeDocs(self):
epi = ExploitativeProbabilisticInterleave("--exploration_rate=0.5")
# prepare rankers
r1 = ProbabilisticRankingFunction(1, self.weights_1)
r2 = ProbabilisticRankingFunction(1, self.weights_2)
r1.init_ranking(self.query)
r2.init_ranking(self.query)
r1.rm_document(0)
r2.rm_document(0)
# test after document 0 was removed
(docids, probs) = epi._get_document_distribution(r1, r2)
exp_docids = [1, 3, 2]
exp_probs = [0.5034965, 0.29020979, 0.20629371]
self._prob_doc_test_helper(docids, exp_docids, probs, exp_probs)
# prepare rankers
r1.init_ranking(self.query)
r2.init_ranking(self.query)
r1.rm_document(3)
r2.rm_document(3)
# test after document 3 was removed
(docids, probs) = epi._get_document_distribution(r1, r2)
exp_docids = [1, 0, 2]
exp_probs = [0.45864662, 0.36466165, 0.17669173]
self._prob_doc_test_helper(docids, exp_docids, probs, exp_probs)
def testExploitativeProbabilisticInterleaveTwoDocs(self):
# prepare rankers
r1 = ProbabilisticRankingFunction(1, self.weights_1)
r2 = ProbabilisticRankingFunction(1, self.weights_2)
r1.init_ranking(self.query)
r2.init_ranking(self.query)
r1.rm_document(1)
r2.rm_document(1)
r1.rm_document(3)
r2.rm_document(3)
# test after 1 and 3 were removed
epi = ExploitativeProbabilisticInterleave("--exploration_rate=0.5")
(docids, probs) = epi._get_document_distribution(r1, r2)
exp_docids = [0, 2]
exp_probs = [0.61428571, 0.38571429]
self._prob_doc_test_helper(docids, exp_docids, probs, exp_probs)
def testExploitativeProbabilisticInterleaveTwoDocs(self):
# prepare rankers
r1 = ProbabilisticRankingFunction(1, self.weights_1)
r2 = ProbabilisticRankingFunction(1, self.weights_2)
r1.init_ranking(self.query)
r2.init_ranking(self.query)
r1.rm_document(1)
r2.rm_document(1)
r1.rm_document(3)
r2.rm_document(3)
# test after 1 and 3 were removed
epi = ExploitativeProbabilisticInterleave("--exploration_rate=0.5")
(docids, probs) = epi._get_document_distribution(r1, r2)
exp_docids = [0, 2]
exp_probs = [0.61428571, 0.38571429]
self._prob_doc_test_helper(docids, exp_docids, probs, exp_probs)
