def test_simple_iqr_scenario(self):
# Make some descriptors;
# Pick some from created set that are close to each other and use as
# positive query, picking some other random descriptors as negative
# examples.
# Rank index based on chosen pos/neg
# Check that positive choices are at the top of the ranking (closest to
# 0) and negative choices are closest to the bottom.
iqr_index = LibSvmHikRelevancyIndex()
iqr_index.build_index(self.index_descriptors)
rank = iqr_index.rank([self.q_pos], [self.q_neg])
rank_ordered = sorted(rank.items(), key=lambda e: e[1], reverse=True)
# Check expected ordering
# 0-5-1-2-6-3-4
# - 2 should end up coming before 6, because 6 has more intersection
# with the negative example.
ntools.assert_equal(rank_ordered[0][0], self.d0)
ntools.assert_equal(rank_ordered[1][0], self.d5)
ntools.assert_equal(rank_ordered[2][0], self.d1)
ntools.assert_equal(rank_ordered[3][0], self.d2)
ntools.assert_equal(rank_ordered[4][0], self.d6)
ntools.assert_equal(rank_ordered[5][0], self.d3)
ntools.assert_equal(rank_ordered[6][0], self.d4)
def test_simple_iqr_scenario(self):
# Make some descriptors;
# Pick some from created set that are close to each other and use as
# positive query, picking some other random descriptors as
# negative examples.
# Rank index based on chosen pos/neg
# Check that positive choices are at the top of the ranking (closest
# to 0) and negative choices are closest to the bottom.
iqr_index = LibSvmHikRelevancyIndex()
iqr_index.build_index(self.index_descriptors)
rank = iqr_index.rank([self.q_pos], [self.q_neg])
rank_ordered = sorted(rank.items(),
key=lambda e: e[1],
reverse=True)
print("rank_ordered:")
for i, r in enumerate(rank_ordered):
print("..{}: {}".format(i, r))
# Check expected ordering
# 0-5-1-2-6-3-4
# - 2 should end up coming before 6, because 6 has more intersection
# with the negative example.
assert rank_ordered[0][0] == self.d0
assert rank_ordered[1][0] == self.d5
assert rank_ordered[2][0] == self.d1
# Results show that d2 and d6 have the same rank, so their position
# in interchangeable.
assert rank_ordered[3][0] in (self.d2, self.d6)
assert rank_ordered[4][0] in (self.d2, self.d6)
assert rank_ordered[3][0] != rank_ordered[4][0]
# d3 and d4 evaluate to the same rank based on query (no
# intersection with positive, equal intersection with negative).
assert rank_ordered[5][0] in (self.d3, self.d4)
assert rank_ordered[6][0] in (self.d3, self.d4)
assert rank_ordered[5][0] != rank_ordered[6][0]
def test_count(self):
iqr_index = LibSvmHikRelevancyIndex()
ntools.assert_equal(iqr_index.count(), 0)
iqr_index.build_index(self.index_descriptors)
ntools.assert_equal(iqr_index.count(), 7)
def test_rank_no_input(self):
iqr_index = LibSvmHikRelevancyIndex()
iqr_index.build_index(self.index_descriptors)
ntools.assert_raises(ValueError, iqr_index.rank, [], [])
def test_rank_no_neg(self):
iqr_index = LibSvmHikRelevancyIndex()
iqr_index.build_index(self.index_descriptors)
# index should auto-select some negative examples, thus not raising an
# exception.
iqr_index.rank([self.q_pos], [])
def test_rank_no_pos(self):
iqr_index = LibSvmHikRelevancyIndex()
iqr_index.build_index(self.index_descriptors)
self.assertRaises(ValueError, iqr_index.rank, [], [self.q_neg])
