class TestPairwiseLearning(unittest.TestCase):
def setUp(self):
# initialize query
self.test_num_features = 6
test_query = """
4 qid:1 1:2.6 2:1 3:2.1 4:0 5:2 6:1.4 # highly relevant
1 qid:1 1:1.2 2:1 3:2.9 4:0 5:2 6:1.9 # bad
0 qid:1 1:0.5 2:1 3:2.3 4:0 5:2 6:5.6 # not relevant
0 qid:1 1:0.5 2:1 3:2.3 4:0 5:2 6:5.6 # not relevant
"""
self.query_fh = cStringIO.StringIO(test_query)
self.queries = query.Queries(self.query_fh, self.test_num_features)
self.query = self.queries['1']
# initialize pairwise learner
self.learner = PairwiseLearningSystem(
self.test_num_features,
"--init_weights 0,0,1,0,0,0 --epsilon 0.0 --eta 0.001 --ranker "
"ranker.DeterministicRankingFunction --ranker_tie first")
def testGetSolution(self):
self.assertEqual(list([0, 0, 1, 0, 0, 0]),
list(self.learner.get_solution()))
def testGetRankedList(self):
self.assertEqual(list([1, 2, 3, 0]),
list(self.learner.get_ranked_list(self.query)))
def testUpdateSolution(self):
self.learner.get_ranked_list(self.query)
new_weights = self.learner.update_solution(array([0, 1, 0, 0]))
# check values one by one - needed due to floating point prec. diffs
self.assertEqual(6, len(new_weights))
for x, y in zip([-0.0007, 0, 0.9994, 0, 0, 0.0037], new_weights):
self.assertEqual(round(x, 4), round(y, 4),
"mismatch between %.4f - %.4f" % (x, y))
class TestPairwiseLearning(unittest.TestCase):
def setUp(self):
# initialize query
self.test_num_features = 6
test_query = """
4 qid:1 1:2.6 2:1 3:2.1 4:0 5:2 6:1.4 # highly relevant
1 qid:1 1:1.2 2:1 3:2.9 4:0 5:2 6:1.9 # bad
0 qid:1 1:0.5 2:1 3:2.3 4:0 5:2 6:5.6 # not relevant
0 qid:1 1:0.5 2:1 3:2.3 4:0 5:2 6:5.6 # not relevant
"""
self.query_fh = cStringIO.StringIO(test_query)
self.queries = query.Queries(self.query_fh, self.test_num_features)
self.query = self.queries['1']
# initialize pairwise learner
self.learner = PairwiseLearningSystem(self.test_num_features,
"--init_weights 0,0,1,0,0,0 --epsilon 0.0 --eta 0.001 --ranker "
"ranker.DeterministicRankingFunction --ranker_tie first")
def testGetSolution(self):
self.assertEqual(list([0, 0, 1, 0, 0, 0]),
list(self.learner.get_solution()))
def testGetRankedList(self):
self.assertEqual(list([1, 2, 3, 0]),
list(self.learner.get_ranked_list(self.query)))
def testUpdateSolution(self):
self.learner.get_ranked_list(self.query)
new_weights = self.learner.update_solution(array([0, 1, 0, 0]))
# check values one by one - needed due to floating point prec. diffs
self.assertEqual(6, len(new_weights))
for x, y in zip([-0.0007, 0, 0.9994, 0, 0, 0.0037], new_weights):
self.assertEqual(round(x, 4), round(y, 4),
"mismatch between %.4f - %.4f" % (x, y))
def setUp(self):
# initialize query
self.test_num_features = 6
test_query = """
4 qid:1 1:2.6 2:1 3:2.1 4:0 5:2 6:1.4 # highly relevant
1 qid:1 1:1.2 2:1 3:2.9 4:0 5:2 6:1.9 # bad
0 qid:1 1:0.5 2:1 3:2.3 4:0 5:2 6:5.6 # not relevant
0 qid:1 1:0.5 2:1 3:2.3 4:0 5:2 6:5.6 # not relevant
"""
self.query_fh = cStringIO.StringIO(test_query)
self.queries = query.Queries(self.query_fh, self.test_num_features)
self.query = self.queries['1']
# initialize pairwise learner
self.learner = PairwiseLearningSystem(self.test_num_features,
"--init_weights 0,0,1,0,0,0 --epsilon 0.0 --eta 0.001 --ranker "
"ranker.DeterministicRankingFunction --ranker_tie first")
rankers = []
rankers = addRanker(rankers, 'features64/ranker-00.txt')
# print rankers[0]
rankers = addRanker(rankers, 'features64/ranker-01.txt')
rankers = addRanker(rankers, 'features64/ranker-02.txt')
rankers = addRanker(rankers, 'features64/ranker-03.txt')
rankers = addRanker(rankers, 'features64/ranker-04.txt')
# initialize pairwise learner
for i in range(0, 5):
for j in range(0, 5):
if i != j:
for iter in range(0, 100):
learner = PairwiseLearningSystem(
test_num_features,
"--init_weights zero --epsilon 0.0 --eta 0.001 --ranker "
"ranker.DeterministicRankingFunction --ranker_tie first --ranker_args"
+ rankers[i] + ' ' + rankers[j])
print learner.getSolution()
# def testGetSolution(self):
# self.assertEqual(list([0, 0, 1, 0, 0, 0]),
# list(self.learner.get_solution()))
# def testGetRankedList(self):
# self.assertEqual(list([1, 2, 3, 0]),
# list(self.learner.get_ranked_list(self.query)))
# def testUpdateSolution(self):
# self.learner.get_ranked_list(self.query)
# new_weights = self.learner.update_solution(array([0, 1, 0, 0]))
return rankers
rankers = []
rankers = addRanker(rankers, 'features64/ranker-00.txt');
# print rankers[0]
rankers = addRanker(rankers, 'features64/ranker-01.txt');
rankers = addRanker(rankers, 'features64/ranker-02.txt');
rankers = addRanker(rankers, 'features64/ranker-03.txt');
rankers = addRanker(rankers, 'features64/ranker-04.txt');
# initialize pairwise learner
for i in range(0,5):
for j in range (0,5):
if i!=j:
for iter in range(0,100):
learner = PairwiseLearningSystem(test_num_features,
"--init_weights zero --epsilon 0.0 --eta 0.001 --ranker "
"ranker.DeterministicRankingFunction --ranker_tie first --ranker_args" + rankers[i] + ' ' + rankers[j])
print learner.getSolution()
# def testGetSolution(self):
# self.assertEqual(list([0, 0, 1, 0, 0, 0]),
# list(self.learner.get_solution()))
# def testGetRankedList(self):
# self.assertEqual(list([1, 2, 3, 0]),
# list(self.learner.get_ranked_list(self.query)))
# def testUpdateSolution(self):
# self.learner.get_ranked_list(self.query)
# new_weights = self.learner.update_solution(array([0, 1, 0, 0]))
# check values one by one - needed due to floating point prec. diffs
