def test_refine_no_rel_index(self):
"""
Test that refinement cannot occur if there is no relevancy index
instance yet.
"""
iqrs = IqrSession()
with pytest.raises(RuntimeError, match="No relevancy index yet"):
iqrs.refine()
def test_refine_no_pos(self):
"""
Test that refinement cannot occur if there are no positive descriptor
external/adjudicated elements.
"""
iqrs = IqrSession()
# Mock relevancy index in order to check how its called and mock return
# value.
iqrs.rel_index = mock.MagicMock(spec=RelevancyIndex)
# Mock length to be non-zero to simulate it having contents
iqrs.rel_index.__len__.return_value = 1
with pytest.raises(RuntimeError,
match='Did not find at least one '
'positive adjudication'):
iqrs.refine()
def test_refine_with_prev_results(self):
"""
Test that the results of RelevancyIndex ranking are directly reflected
in an existing results dictionary of probability values.
"""
# IqrSession instance. No config for rel_index because we will mock
# that.
iqrs = IqrSession()
# Mock relevancy index in order to check how its called and mock return
# value.
iqrs.rel_index = mock.MagicMock(spec=RelevancyIndex)
# Mock length to be non-zero to simulate it having contents
iqrs.rel_index.__len__.return_value = 1
test_in_pos_elem = DescriptorMemoryElement('t', 0).set_vector([0])
test_in_neg_elem = DescriptorMemoryElement('t', 1).set_vector([1])
test_ex_pos_elem = DescriptorMemoryElement('t', 2).set_vector([2])
test_ex_neg_elem = DescriptorMemoryElement('t', 3).set_vector([3])
test_other_elem = DescriptorMemoryElement('t', 4).set_vector([4])
# Mock return dictionary, probabilities don't matter much other than
# they are not 1.0 or 0.0.
iqrs.rel_index.rank.return_value = \
{e: 0.5 for e in [test_in_pos_elem, test_in_neg_elem,
test_other_elem]}
# Create a "previous state" of the results dictionary containing
# results from our "working set" of descriptor elements.
iqrs.results = {
test_in_pos_elem: 0.2,
test_in_neg_elem: 0.2,
test_other_elem: 0.2,
# ``refine`` replaces the previous dict, so disjoint keys are
# NOT retained.
'something else': 0.3,
}
# Prepare IQR state for refinement
# - set dummy internal/external positive negatives.
iqrs.external_descriptors(positive=[test_ex_pos_elem],
negative=[test_ex_neg_elem])
iqrs.adjudicate(new_positives=[test_in_pos_elem],
new_negatives=[test_in_neg_elem])
# Test calling refine method
iqrs.refine()
# We test that:
# - ``rel_index.rank`` called with the combination of
# external/adjudicated descriptor elements.
# - ``results`` attribute now has an dict value
# - value of ``results`` attribute is what we expect.
iqrs.rel_index.rank.assert_called_once_with(
{test_in_pos_elem, test_ex_pos_elem},
{test_in_neg_elem, test_ex_neg_elem},
)
assert iqrs.results is not None
assert len(iqrs.results) == 3
assert test_other_elem in iqrs.results
assert test_in_pos_elem in iqrs.results
assert test_in_neg_elem in iqrs.results
assert 'something else' not in iqrs.results
assert iqrs.results[test_other_elem] == 0.5
assert iqrs.results[test_in_pos_elem] == 0.5
assert iqrs.results[test_in_neg_elem] == 0.5
def test_refine_no_prev_results(self):
"""
Test that the results of RelevancyIndex ranking are directly reflected
in a new results dictionary of probability values, even for elements
that were also used in adjudication.
This test is useful because a previous state of the IQR Session
structure would force return probabilities for some descriptor elements
to certain values if they were also present in the positive or negative
adjudicate (internal or external) sets.
"""
# IqrSession instance. No config for rel_index because we will mock
# that.
iqrs = IqrSession()
# Mock relevancy index in order to check how its called and mock return
# value.
iqrs.rel_index = mock.MagicMock(spec=RelevancyIndex)
# Mock length to be non-zero to simulate it having contents
iqrs.rel_index.__len__.return_value = 1
test_in_pos_elem = DescriptorMemoryElement('t', 0).set_vector([0])
test_in_neg_elem = DescriptorMemoryElement('t', 1).set_vector([1])
test_ex_pos_elem = DescriptorMemoryElement('t', 2).set_vector([2])
test_ex_neg_elem = DescriptorMemoryElement('t', 3).set_vector([3])
test_other_elem = DescriptorMemoryElement('t', 4).set_vector([4])
# Mock return dictionary, probabilities don't matter much other than
# they are not 1.0 or 0.0.
iqrs.rel_index.rank.return_value = \
{e: 0.5 for e in [test_in_pos_elem, test_in_neg_elem,
test_other_elem]}
# Asserting expected pre-condition where there are no results yet.
assert iqrs.results is None
# Prepare IQR state for refinement
# - set dummy internal/external positive negatives.
iqrs.external_descriptors(positive=[test_ex_pos_elem],
negative=[test_ex_neg_elem])
iqrs.adjudicate(new_positives=[test_in_pos_elem],
new_negatives=[test_in_neg_elem])
# Test calling refine method
iqrs.refine()
# We test that:
# - ``rel_index.rank`` called with the combination of
# external/adjudicated descriptor elements.
# - ``results`` attribute now has a dict value
# - value of ``results`` attribute is what we expect.
iqrs.rel_index.rank.assert_called_once_with(
{test_in_pos_elem, test_ex_pos_elem},
{test_in_neg_elem, test_ex_neg_elem},
)
assert iqrs.results is not None
assert len(iqrs.results) == 3
assert test_other_elem in iqrs.results
assert test_in_pos_elem in iqrs.results
assert test_in_neg_elem in iqrs.results
assert iqrs.results[test_other_elem] == 0.5
assert iqrs.results[test_in_pos_elem] == 0.5
assert iqrs.results[test_in_neg_elem] == 0.5