def test_matches_sort_by_document_interface_not_in_proto():
docs = [Document(embedding=np.array([1] * (10 - i))) for i in range(10)]
query = Document()
query.matches = docs
assert len(query.matches) == 10
assert query.matches[0].embedding.shape == (10,)
query.matches.sort(key=lambda m: m.embedding.shape[0])
assert query.matches[0].embedding.shape == (1,)
def test_matches_sort_by_document_interface_in_proto():
docs = [Document(weight=(10 - i)) for i in range(10)]
query = Document()
query.matches = docs
assert len(query.matches) == 10
assert query.matches[0].weight == 10
query.matches.sort(key=lambda m: m.weight)
assert query.matches[0].weight == 1
def test_query_match_array_sort_scores():
query = Document()
query.matches = [
Document(id=i, copy=True, scores={'euclid': 10 - i}) for i in range(10)
]
assert query.matches[0].id == '0'
assert query.matches[0].scores['euclid'].value == 10
query.matches.sort(
key=lambda m: m.scores['euclid'].value) # sort matches by their values
assert query.matches[0].id == '9'
assert query.matches[0].scores['euclid'].value == 1
def test_doc_match_score_assign():
d = Document(id='hello')
d1 = Document(d, copy=True, score=123)
d.matches = [d1]
assert d.matches[0].score.value == 123
