def test__in_mem_knn__refresh__underlying_data_model_and_similarity_is_refreshed(
):
fake_model = AbstractRecordDataModel()
fake_model.get_records = mock.Mock(return_value=[])
fake_model.refresh = mock.Mock()
fake_sim = AbstractRecordSimilarity()
fake_sim.get_similarity = mock.Mock(return_value=1.0)
fake_sim.refresh = mock.Mock()
fake_nhood = AbstractRecordNeighbourhood()
fake_nhood.get_neighbours = mock.Mock(return_value=[])
sut = InMemoryRecordNeighbourhood(
fake_model,
fake_sim,
50,
nhood_factory=lambda dm, sim, num_nh: fake_nhood)
sut = InMemoryRecordNeighbourhood(fake_model, fake_sim, 50)
refreshed_components = set()
sut.refresh(refreshed_components)
assert fake_model in refreshed_components
assert fake_sim in refreshed_components
assert sut in refreshed_components
assert fake_model.refresh.call_count == 1
assert fake_sim.refresh.call_count == 1
def test__record_similarity__get_similarity():
expected_sim = 1.0
record_1 = 'caesar'
record_2 = 'brutus'
preferences = {
record_1: {
1: Preference(1.0, None),
2: Preference(2.0, None),
3: Preference(2.0, None),
4: Preference(1.0, None),
},
record_2: {
1: Preference(1.0, None),
4: Preference(2.0, None),
5: Preference(2.0, None),
},
}
fake_model = AbstractRecordDataModel()
fake_model.get_preferences_for_record = mock.Mock(
side_effect=lambda r: preferences[r])
fake_sim = AbstractPreferenceSimilarity()
fake_sim.get_similarity = mock.Mock(
return_value=expected_sim)
sut = RecordSimilarity(fake_model, fake_sim)
sim = sut.get_similarity(record_1, record_2)
assert sim == expected_sim
fake_sim.get_similarity.assert_called_with(
preferences[record_1],
preferences[record_2])
def test__record_similarity__get_similarity():
expected_sim = 1.0
record_1 = 'caesar'
record_2 = 'brutus'
preferences = {
record_1: {
1: Preference(1.0, None),
2: Preference(2.0, None),
3: Preference(2.0, None),
4: Preference(1.0, None),
},
record_2: {
1: Preference(1.0, None),
4: Preference(2.0, None),
5: Preference(2.0, None),
},
}
fake_model = AbstractRecordDataModel()
fake_model.get_preferences_for_record = mock.Mock(
side_effect=lambda r: preferences[r])
fake_sim = AbstractPreferenceSimilarity()
fake_sim.get_similarity = mock.Mock(return_value=expected_sim)
sut = RecordSimilarity(fake_model, fake_sim)
sim = sut.get_similarity(record_1, record_2)
assert sim == expected_sim
fake_sim.get_similarity.assert_called_with(preferences[record_1],
preferences[record_2])
def create_k_nearest_neighbourhood(k, doc_sims, docs):
fake_model = AbstractRecordDataModel()
fake_model.get_records = mock.Mock(return_value=docs)
record_sim = AbstractRecordSimilarity()
record_sim.get_similarity = mock.Mock(
side_effect=lambda from_id, to_id: doc_sims[to_id])
return KNearestRecordNeighbourhood(k=k,
data_model=fake_model,
record_sim=record_sim)
def create_k_nearest_neighbourhood(k, doc_sims, docs):
fake_model = AbstractRecordDataModel()
fake_model.get_records = mock.Mock(
return_value=docs)
record_sim = AbstractRecordSimilarity()
record_sim.get_similarity = mock.Mock(
side_effect=lambda from_id, to_id: doc_sims[to_id])
return KNearestRecordNeighbourhood(
k=k, data_model=fake_model, record_sim=record_sim)
def test__in_mem_knn__get_nbours():
record_caesar = 'caesar'
record_brutus = 'brutus'
record_napoleon = 'napoleon'
nbours = {
record_caesar: [
record_brutus
],
record_brutus: [
record_caesar
],
record_napoleon: []
}
sims = {
record_caesar: {
record_brutus: 0.9
},
record_brutus: {
record_caesar: 0.8
},
record_napoleon: {}
}
fake_model = AbstractRecordDataModel()
fake_model.get_records = mock.Mock(return_value=nbours.keys())
fake_sim = AbstractRecordSimilarity()
fake_sim.get_similarity = mock.Mock(
side_effect=lambda from_r, to_r: sims[from_r][to_r])
fake_nhood = AbstractRecordNeighbourhood()
fake_nhood.get_neighbours = mock.Mock(
side_effect=lambda r: nbours[r])
sut = InMemoryRecordNeighbourhood(
fake_model, fake_sim, 50,
nhood_factory=lambda dm, sim, num_nh: fake_nhood)
assert sut.get_neighbours(record_caesar) == nbours[record_caesar]
assert sut.get_neighbours(record_brutus) == nbours[record_brutus]
assert sut.get_neighbours(record_napoleon) == nbours[record_napoleon]
assert sut.get_neighbours('unknown') == []
assert sut.get_similarity(record_caesar, record_brutus) ==\
sims[record_caesar][record_brutus]
assert sut.get_similarity(record_brutus, record_caesar) ==\
sims[record_brutus][record_caesar]
assert math.isnan(sut.get_similarity(record_caesar, record_napoleon))
assert math.isnan(sut.get_similarity(record_napoleon, record_caesar))
assert math.isnan(sut.get_similarity('unknown', record_napoleon))
assert math.isnan(sut.get_similarity(record_caesar, 'unknown'))
def test__record_similarity__refresh__underlying_data_model_is_refreshed():
fake_model = AbstractRecordDataModel()
fake_model.refresh = mock.Mock()
fake_sim = AbstractPreferenceSimilarity()
sut = RecordSimilarity(fake_model, fake_sim)
refreshed_components = set()
sut.refresh(refreshed_components)
assert fake_model in refreshed_components
assert sut in refreshed_components
assert fake_model.refresh.call_count == 1
def test__record_similarity__refresh__underlying_data_model_is_refreshed():
fake_model = AbstractRecordDataModel()
fake_model.refresh = mock.Mock()
fake_sim = AbstractPreferenceSimilarity()
sut = RecordSimilarity(fake_model, fake_sim)
refreshed_components = set()
sut.refresh(refreshed_components)
assert fake_model in refreshed_components
assert sut in refreshed_components
assert fake_model.refresh.call_count == 1
def create_recommender(preferences=default_prefs, doc_sims=doc_sims):
data_model = AbstractRecordDataModel()
data_model.get_preferences_of_session = mock.Mock(
side_effect=lambda s_id: preferences)
record_sim = AbstractRecordSimilarity()
record_sim.get_similarity = mock.Mock(
side_effect=lambda from_id, to_id: doc_sims[from_id][to_id])
record_nhood = AbstractRecordNeighbourhood()
record_nhood.get_neighbours = mock.Mock(
side_effect=lambda doc_id: doc_sims[doc_id].keys())
return RecordBasedRecommender(
data_model, record_nhood, record_sim)
def test__in_mem_knn__get_nbours():
record_caesar = 'caesar'
record_brutus = 'brutus'
record_napoleon = 'napoleon'
nbours = {
record_caesar: [record_brutus],
record_brutus: [record_caesar],
record_napoleon: []
}
sims = {
record_caesar: {
record_brutus: 0.9
},
record_brutus: {
record_caesar: 0.8
},
record_napoleon: {}
}
fake_model = AbstractRecordDataModel()
fake_model.get_records = mock.Mock(return_value=nbours.keys())
fake_sim = AbstractRecordSimilarity()
fake_sim.get_similarity = mock.Mock(
side_effect=lambda from_r, to_r: sims[from_r][to_r])
fake_nhood = AbstractRecordNeighbourhood()
fake_nhood.get_neighbours = mock.Mock(side_effect=lambda r: nbours[r])
sut = InMemoryRecordNeighbourhood(
fake_model,
fake_sim,
50,
nhood_factory=lambda dm, sim, num_nh: fake_nhood)
assert sut.get_neighbours(record_caesar) == nbours[record_caesar]
assert sut.get_neighbours(record_brutus) == nbours[record_brutus]
assert sut.get_neighbours(record_napoleon) == nbours[record_napoleon]
assert sut.get_neighbours('unknown') == []
assert sut.get_similarity(record_caesar, record_brutus) ==\
sims[record_caesar][record_brutus]
assert sut.get_similarity(record_brutus, record_caesar) ==\
sims[record_brutus][record_caesar]
assert math.isnan(sut.get_similarity(record_caesar, record_napoleon))
assert math.isnan(sut.get_similarity(record_napoleon, record_caesar))
assert math.isnan(sut.get_similarity('unknown', record_napoleon))
assert math.isnan(sut.get_similarity(record_caesar, 'unknown'))
def test__knn__refresh__underlying_data_model_and_similarity_is_refreshed():
fake_model = AbstractRecordDataModel()
fake_model.refresh = mock.Mock()
fake_sim = AbstractRecordSimilarity()
fake_sim.refresh = mock.Mock()
sut = KNearestRecordNeighbourhood(5, fake_model, fake_sim)
refreshed_components = set()
sut.refresh(refreshed_components)
assert fake_model in refreshed_components
assert fake_sim in refreshed_components
assert sut in refreshed_components
assert fake_model.refresh.call_count == 1
assert fake_sim.refresh.call_count == 1
def test__knn__refresh__underlying_data_model_and_similarity_is_refreshed():
fake_model = AbstractRecordDataModel()
fake_model.refresh = mock.Mock()
fake_sim = AbstractRecordSimilarity()
fake_sim.refresh = mock.Mock()
sut = KNearestRecordNeighbourhood(5, fake_model, fake_sim)
refreshed_components = set()
sut.refresh(refreshed_components)
assert fake_model in refreshed_components
assert fake_sim in refreshed_components
assert sut in refreshed_components
assert fake_model.refresh.call_count == 1
assert fake_sim.refresh.call_count == 1
def test__in_mem_dm__refresh__underlying_data_model_is_refreshed():
preferences = {}
fake_model = AbstractRecordDataModel()
fake_model.get_preferences_for_records = mock.Mock(
return_value=preferences.iteritems())
fake_model.refresh = mock.Mock()
sut = InMemoryRecordDataModel(fake_model)
sut = InMemoryRecordDataModel(fake_model)
refreshed_components = set()
sut.refresh(refreshed_components)
fake_model.refresh.assert_called_once_with(refreshed_components)
assert fake_model in refreshed_components
assert sut in refreshed_components
def test__in_mem_dm__get_preferences_of_session__session_not_present():
preferences = {
record_caesar: {
session_alice: Preference(1.0, datetime(1999, 1, 1)),
session_bob: Preference(2.0, datetime(1999, 1, 1)),
},
record_brutus: {
session_alice: Preference(1.0, datetime(1999, 1, 1)),
}
}
fake_model = AbstractRecordDataModel()
fake_model.get_preferences_for_records = mock.Mock(
return_value=preferences.iteritems())
sut = InMemoryRecordDataModel(fake_model)
assert sut.get_preferences_of_session('dogma') == {}
def test__in_mem_dm__get_preferences_of_session():
preferences = {
record_caesar: {
session_alice: Preference(1.0, datetime(1999, 1, 1)),
session_bob: Preference(2.0, datetime(1999, 1, 1)),
},
record_brutus: {
session_alice: Preference(1.0, datetime(1999, 1, 1)),
}
}
fake_model = AbstractRecordDataModel()
fake_model.get_preferences_for_records = mock.Mock(
return_value=preferences.iteritems())
sut = InMemoryRecordDataModel(fake_model)
sess_prefs = sut.get_preferences_of_session(session_alice)
for record_id, pref in sess_prefs.iteritems():
assert preferences[record_id][session_alice] == pref
def test__in_mem_dm__refresh__data_is_reloaded():
preferences = {}
fake_model = AbstractRecordDataModel()
fake_model.get_preferences_for_records = mock.Mock(
return_value=preferences.iteritems())
fake_model.refresh = mock.Mock()
sut = InMemoryRecordDataModel(fake_model)
assert {k: v for k, v in sut.get_preferences_for_records()} == {}
preferences[record_caesar] = {
session_alice: Preference(1.0, datetime(1999, 1, 1)),
}
sut.refresh(set())
for record_id, rec_prefs in sut.get_preferences_for_records():
for session_id, pref in rec_prefs.iteritems():
assert preferences[record_id][session_id] == pref
def test__in_mem_knn__refresh__data_is_reloaded():
record_caesar = 'caesar'
record_brutus = 'brutus'
nbours = {
}
sims = {
}
fake_model = AbstractRecordDataModel()
fake_model.get_records = mock.Mock(
side_effect=lambda: nbours.keys())
fake_model.refresh = mock.Mock()
fake_sim = AbstractRecordSimilarity()
fake_sim.get_similarity = mock.Mock(
side_effect=lambda from_r, to_r: sims[from_r][to_r])
fake_sim.refresh = mock.Mock()
fake_nhood = AbstractRecordNeighbourhood()
fake_nhood.get_neighbours = mock.Mock(
side_effect=lambda r: nbours[r])
sut = InMemoryRecordNeighbourhood(
fake_model, fake_sim, 50,
nhood_factory=lambda dm, sim, num_nh: fake_nhood)
assert sut.get_neighbours(record_caesar) == []
assert math.isnan(sut.get_similarity(record_caesar, record_brutus))
nbours[record_caesar] = [record_brutus]
nbours[record_brutus] = [record_caesar]
sims[record_caesar] = {record_brutus: 0.9}
sims[record_brutus] = {record_caesar: 0.8}
sut.refresh(set())
assert sut.get_neighbours(record_caesar) == nbours[record_caesar]
assert sut.get_similarity(record_caesar, record_brutus) ==\
sims[record_caesar][record_brutus]
def test__refresh__underlying_components_are_refreshed():
fake_model = AbstractRecordDataModel()
fake_model.refresh = mock.Mock()
fake_sim = AbstractRecordSimilarity()
fake_sim.refresh = mock.Mock()
fake_nhood = AbstractRecordNeighbourhood()
fake_nhood.refresh = mock.Mock()
sut = RecordBasedRecommender(
data_model=fake_model,
record_sim=fake_sim,
record_nhood=fake_nhood)
refreshed_components = set()
sut.refresh(refreshed_components)
assert fake_model in refreshed_components
assert fake_sim in refreshed_components
assert fake_nhood in refreshed_components
assert sut in refreshed_components
assert fake_model.refresh.call_count == 1
assert fake_sim.refresh.call_count == 1
assert fake_nhood.refresh.call_count == 1
def test__in_mem_knn__refresh__data_is_reloaded():
record_caesar = 'caesar'
record_brutus = 'brutus'
nbours = {}
sims = {}
fake_model = AbstractRecordDataModel()
fake_model.get_records = mock.Mock(side_effect=lambda: nbours.keys())
fake_model.refresh = mock.Mock()
fake_sim = AbstractRecordSimilarity()
fake_sim.get_similarity = mock.Mock(
side_effect=lambda from_r, to_r: sims[from_r][to_r])
fake_sim.refresh = mock.Mock()
fake_nhood = AbstractRecordNeighbourhood()
fake_nhood.get_neighbours = mock.Mock(side_effect=lambda r: nbours[r])
sut = InMemoryRecordNeighbourhood(
fake_model,
fake_sim,
50,
nhood_factory=lambda dm, sim, num_nh: fake_nhood)
assert sut.get_neighbours(record_caesar) == []
assert math.isnan(sut.get_similarity(record_caesar, record_brutus))
nbours[record_caesar] = [record_brutus]
nbours[record_brutus] = [record_caesar]
sims[record_caesar] = {record_brutus: 0.9}
sims[record_brutus] = {record_caesar: 0.8}
sut.refresh(set())
assert sut.get_neighbours(record_caesar) == nbours[record_caesar]
assert sut.get_similarity(record_caesar, record_brutus) ==\
sims[record_caesar][record_brutus]
def test__in_mem_knn__refresh__underlying_data_model_and_similarity_is_refreshed():
fake_model = AbstractRecordDataModel()
fake_model.get_records = mock.Mock(return_value=[])
fake_model.refresh = mock.Mock()
fake_sim = AbstractRecordSimilarity()
fake_sim.get_similarity = mock.Mock(return_value=1.0)
fake_sim.refresh = mock.Mock()
fake_nhood = AbstractRecordNeighbourhood()
fake_nhood.get_neighbours = mock.Mock(return_value=[])
sut = InMemoryRecordNeighbourhood(
fake_model, fake_sim, 50,
nhood_factory=lambda dm, sim, num_nh: fake_nhood)
sut = InMemoryRecordNeighbourhood(fake_model, fake_sim, 50)
refreshed_components = set()
sut.refresh(refreshed_components)
assert fake_model in refreshed_components
assert fake_sim in refreshed_components
assert sut in refreshed_components
assert fake_model.refresh.call_count == 1
assert fake_sim.refresh.call_count == 1