def test_simsearch(self):
db = PersistentDB(schema, 'pk', dbname='testdb', overwrite=True)
n_add = 50
mus = np.random.uniform(low=0.0, high=1.0, size=n_add)
sigs = np.random.uniform(low=0.05, high=0.4, size=n_add)
jits = np.random.uniform(low=0.05, high=0.2, size=n_add)
for i, m, s, j in zip(range(n_add), mus, sigs, jits):
db.insert_ts("ts-{}".format(i), tsmaker(m, s, j))
m = np.random.uniform(low=0.0, high=1.0)
s = np.random.uniform(low=0.05, high=0.4)
j = np.random.uniform(low=0.05, high=0.2)
query = tsmaker(m, s, j)
with self.assertRaises(ValueError): # No similarity search w/o vantage points
closest = db.simsearch(query)
for i in range(5):
db.add_vp()
closest = db.simsearch(query)
def test_simsearch(self):
db = PersistentDB(schema, 'pk', dbname='testdb', overwrite=True)
n_add = 50
mus = np.random.uniform(low=0.0, high=1.0, size=n_add)
sigs = np.random.uniform(low=0.05, high=0.4, size=n_add)
jits = np.random.uniform(low=0.05, high=0.2, size=n_add)
for i, m, s, j in zip(range(n_add), mus, sigs, jits):
db.insert_ts("ts-{}".format(i), tsmaker(m, s, j))
m = np.random.uniform(low=0.0, high=1.0)
s = np.random.uniform(low=0.05, high=0.4)
j = np.random.uniform(low=0.05, high=0.2)
query = tsmaker(m, s, j)
with self.assertRaises(
ValueError): # No similarity search w/o vantage points
closest = db.simsearch(query)
for i in range(5):
db.add_vp()
closest = db.simsearch(query)
