|
@@ 796-823 (lines=28) @@
|
| 793 |
|
logging.getLogger().info(result) |
| 794 |
|
assert len(result[0]) == 0 |
| 795 |
|
|
| 796 |
|
def test_search_distance_superstructure_flat_index_B(self, connect, superstructure_collection): |
| 797 |
|
''' |
| 798 |
|
target: search ip_collection, and check the result: distance |
| 799 |
|
method: compare the return distance value with value computed with SUPER |
| 800 |
|
expected: the return distance equals to the computed value |
| 801 |
|
''' |
| 802 |
|
# from scipy.spatial import distance |
| 803 |
|
top_k = 3 |
| 804 |
|
nprobe = 512 |
| 805 |
|
int_vectors, vectors, ids = self.init_binary_data(connect, superstructure_collection, nb=2) |
| 806 |
|
index_type = IndexType.FLAT |
| 807 |
|
index_param = { |
| 808 |
|
"nlist": 16384 |
| 809 |
|
} |
| 810 |
|
connect.create_index(superstructure_collection, index_type, index_param) |
| 811 |
|
logging.getLogger().info(connect.get_collection_info(superstructure_collection)) |
| 812 |
|
logging.getLogger().info(connect.get_index_info(superstructure_collection)) |
| 813 |
|
query_int_vectors, query_vecs = gen_binary_super_vectors(int_vectors, 2) |
| 814 |
|
search_param = get_search_param(index_type) |
| 815 |
|
status, result = connect.search(superstructure_collection, top_k, query_vecs, params=search_param) |
| 816 |
|
logging.getLogger().info(status) |
| 817 |
|
logging.getLogger().info(result) |
| 818 |
|
assert len(result[0]) == 2 |
| 819 |
|
assert len(result[1]) == 2 |
| 820 |
|
assert result[0][0].id in ids |
| 821 |
|
assert result[0][0].distance <= epsilon |
| 822 |
|
assert result[1][0].id in ids |
| 823 |
|
assert result[1][0].distance <= epsilon |
| 824 |
|
|
| 825 |
|
def test_search_distance_tanimoto_flat_index(self, connect, tanimoto_collection): |
| 826 |
|
''' |
|
@@ 741-768 (lines=28) @@
|
| 738 |
|
logging.getLogger().info(result) |
| 739 |
|
assert len(result[0]) == 0 |
| 740 |
|
|
| 741 |
|
def test_search_distance_substructure_flat_index_B(self, connect, substructure_collection): |
| 742 |
|
''' |
| 743 |
|
target: search ip_collection, and check the result: distance |
| 744 |
|
method: compare the return distance value with value computed with SUB |
| 745 |
|
expected: the return distance equals to the computed value |
| 746 |
|
''' |
| 747 |
|
# from scipy.spatial import distance |
| 748 |
|
top_k = 3 |
| 749 |
|
nprobe = 512 |
| 750 |
|
int_vectors, vectors, ids = self.init_binary_data(connect, substructure_collection, nb=2) |
| 751 |
|
index_type = IndexType.FLAT |
| 752 |
|
index_param = { |
| 753 |
|
"nlist": 16384 |
| 754 |
|
} |
| 755 |
|
connect.create_index(substructure_collection, index_type, index_param) |
| 756 |
|
logging.getLogger().info(connect.get_collection_info(substructure_collection)) |
| 757 |
|
logging.getLogger().info(connect.get_index_info(substructure_collection)) |
| 758 |
|
query_int_vectors, query_vecs = gen_binary_sub_vectors(int_vectors, 2) |
| 759 |
|
search_param = get_search_param(index_type) |
| 760 |
|
status, result = connect.search(substructure_collection, top_k, query_vecs, params=search_param) |
| 761 |
|
logging.getLogger().info(status) |
| 762 |
|
logging.getLogger().info(result) |
| 763 |
|
assert len(result[0]) == 1 |
| 764 |
|
assert len(result[1]) == 1 |
| 765 |
|
assert result[0][0].distance <= epsilon |
| 766 |
|
assert result[0][0].id == ids[0] |
| 767 |
|
assert result[1][0].distance <= epsilon |
| 768 |
|
assert result[1][0].id == ids[1] |
| 769 |
|
|
| 770 |
|
def test_search_distance_superstructure_flat_index(self, connect, superstructure_collection): |
| 771 |
|
''' |