本文整理匯總了Python中nearpy.Engine.clean_all_buckets方法的典型用法代碼示例。如果您正苦於以下問題：Python Engine.clean_all_buckets方法的具體用法？Python Engine.clean_all_buckets怎麽用？Python Engine.clean_all_buckets使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類nearpy.Engine的用法示例。
在下文中一共展示了Engine.clean_all_buckets方法的3個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: TestEngine
# 需要導入模塊: from nearpy import Engine [as 別名]
# 或者: from nearpy.Engine import clean_all_buckets [as 別名]
class TestEngine(unittest.TestCase):
def setUp(self):
self.engine = Engine(1000)
def test_retrieval(self):
for k in range(100):
self.engine.clean_all_buckets()
x = numpy.random.randn(1000)
x_data = 'data'
self.engine.store_vector(x, x_data)
n = self.engine.neighbours(x)
y = n[0][0]
y_data = n[0][1]
y_distance = n[0][2]
self.assertTrue((y == x).all())
self.assertEqual(y_data, x_data)
self.assertEqual(y_distance, 0.0)
def test_retrieval_sparse(self):
for k in range(100):
self.engine.clean_all_buckets()
x = scipy.sparse.rand(1000, 1, density=0.05)
x_data = 'data'
self.engine.store_vector(x, x_data)
n = self.engine.neighbours(x)
y = n[0][0]
y_data = n[0][1]
y_distance = n[0][2]
self.assertTrue((y - x).sum() == 0.0)
self.assertEqual(y_data, x_data)
self.assertEqual(y_distance, 0.0)示例2: TestEngine
# 需要導入模塊: from nearpy import Engine [as 別名]
# 或者: from nearpy.Engine import clean_all_buckets [as 別名]
class TestEngine(unittest.TestCase):
def setUp(self):
self.engine = Engine(1000)
def test_storage_issue(self):
engine1 = Engine(100)
engine2 = Engine(100)
for k in range(1000):
x = numpy.random.randn(100)
x_data = 'data'
engine1.store_vector(x, x_data)
# Each engine should have its own default storage
self.assertTrue(len(engine2.storage.buckets)==0)
def test_retrieval(self):
for k in range(100):
self.engine.clean_all_buckets()
x = numpy.random.randn(1000)
x_data = 'data'
self.engine.store_vector(x, x_data)
n = self.engine.neighbours(x)
y = n[0][0]
y_data = n[0][1]
y_distance = n[0][2]
self.assertTrue((y == x).all())
self.assertEqual(y_data, x_data)
self.assertEqual(y_distance, 0.0)
def test_retrieval_sparse(self):
for k in range(100):
self.engine.clean_all_buckets()
x = scipy.sparse.rand(1000, 1, density=0.05)
x_data = 'data'
self.engine.store_vector(x, x_data)
n = self.engine.neighbours(x)
y = n[0][0]
y_data = n[0][1]
y_distance = n[0][2]
self.assertTrue((y - x).sum() == 0.0)
self.assertEqual(y_data, x_data)
self.assertEqual(y_distance, 0.0)示例3: TestEngine
# 需要導入模塊: from nearpy import Engine [as 別名]
# 或者: from nearpy.Engine import clean_all_buckets [as 別名]
class TestEngine(unittest.TestCase):
def setUp(self):
self.engine = Engine(1000)
def test_storage_issue(self):
engine1 = Engine(100)
engine2 = Engine(100)
for k in range(1000):
x = numpy.random.randn(100)
x_data = 'data'
engine1.store_vector(x, x_data)
# Each engine should have its own default storage
self.assertTrue(len(engine2.storage.buckets)==0)
def test_retrieval(self):
for k in range(100):
self.engine.clean_all_buckets()
x = numpy.random.randn(1000)
x_data = 'data'
self.engine.store_vector(x, x_data)
n = self.engine.neighbours(x)
y, y_data, y_distance = n[0]
normalized_x = unitvec(x)
delta = 0.000000001
self.assertAlmostEqual(numpy.abs((normalized_x - y)).max(), 0, delta=delta)
self.assertEqual(y_data, x_data)
self.assertAlmostEqual(y_distance, 0.0, delta=delta)
def test_retrieval_sparse(self):
for k in range(100):
self.engine.clean_all_buckets()
x = scipy.sparse.rand(1000, 1, density=0.05)
x_data = 'data'
self.engine.store_vector(x, x_data)
n = self.engine.neighbours(x)
y, y_data, y_distance = n[0]
normalized_x = unitvec(x)
delta = 0.000000001
self.assertAlmostEqual(numpy.abs((normalized_x - y)).max(), 0, delta=delta)
self.assertEqual(y_data, x_data)
self.assertAlmostEqual(y_distance, 0.0, delta=delta)