mirror of https://mirror.osredm.com/root/redis.git
36 lines
1.6 KiB
Python
36 lines
1.6 KiB
Python
from test import TestCase
|
|
|
|
class BasicSimilarity(TestCase):
|
|
def getname(self):
|
|
return "VSIM reported distance makes sense with 4D vectors"
|
|
|
|
def test(self):
|
|
# Add two very similar vectors, one different
|
|
vec1 = [1, 0, 0, 0]
|
|
vec2 = [0.99, 0.01, 0, 0]
|
|
vec3 = [0.1, 1, -1, 0.5]
|
|
|
|
# Add vectors using VALUES format
|
|
self.redis.execute_command('VADD', self.test_key, 'VALUES', 4,
|
|
*[str(x) for x in vec1], f'{self.test_key}:item:1')
|
|
self.redis.execute_command('VADD', self.test_key, 'VALUES', 4,
|
|
*[str(x) for x in vec2], f'{self.test_key}:item:2')
|
|
self.redis.execute_command('VADD', self.test_key, 'VALUES', 4,
|
|
*[str(x) for x in vec3], f'{self.test_key}:item:3')
|
|
|
|
# Query similarity with vec1
|
|
result = self.redis.execute_command('VSIM', self.test_key, 'VALUES', 4,
|
|
*[str(x) for x in vec1], 'WITHSCORES')
|
|
|
|
# Convert results to dictionary
|
|
results_dict = {}
|
|
for i in range(0, len(result), 2):
|
|
key = result[i].decode()
|
|
score = float(result[i+1])
|
|
results_dict[key] = score
|
|
|
|
# Verify results
|
|
assert results_dict[f'{self.test_key}:item:1'] > 0.99, "Self-similarity should be very high"
|
|
assert results_dict[f'{self.test_key}:item:2'] > 0.99, "Similar vector should have high similarity"
|
|
assert results_dict[f'{self.test_key}:item:3'] < 0.8, "Not very similar vector should have low similarity"
|