def testHaversineDistancesExecution(self):
raw_x = np.random.rand(30, 2)
raw_y = np.random.rand(21, 2)
# one chunk
x1 = mt.tensor(raw_x, chunk_size=30)
y1 = mt.tensor(raw_y, chunk_size=30)
# multiple chunks
x2 = mt.tensor(raw_x, chunk_size=(11, 1))
y2 = mt.tensor(raw_y, chunk_size=(17, 1))
for x, y in [(x1, y1), (x2, y2)]:
for use_sklearn in [True, False]:
distance = haversine_distances(x, y)
distance.op._use_sklearn = use_sklearn
result = self.executor.execute_tensor(distance, concat=True)[0]
expected = sk_haversine_distances(raw_x, raw_y)
np.testing.assert_array_equal(result, expected)
# test x is y
distance = haversine_distances(x)
distance.op._use_sklearn = use_sklearn
result = self.executor.execute_tensor(distance, concat=True)[0]
expected = sk_haversine_distances(raw_x, raw_x)
np.testing.assert_array_equal(result, expected)
def test_haversine_distances_execution(setup, x, y, use_sklearn):
distance = haversine_distances(x, y)
distance.op._use_sklearn = use_sklearn
result = distance.execute().fetch()
expected = sk_haversine_distances(raw_x, raw_y)
np.testing.assert_array_equal(result, expected)
# test x is y
distance = haversine_distances(x)
distance.op._use_sklearn = use_sklearn
result = distance.execute().fetch()
expected = sk_haversine_distances(raw_x, raw_x)
np.testing.assert_array_equal(result, expected)
def test_haversine_distances_op():
# shape[1] != 2
with pytest.raises(ValueError):
haversine_distances(mt.random.rand(10, 3))
# shape[1] != 2
with pytest.raises(ValueError):
haversine_distances(mt.random.rand(10, 2), mt.random.rand(11, 3))
# cannot support sparse
with pytest.raises(TypeError):
haversine_distances(mt.random.randint(10, size=(10, 2), density=0.5))
def testHaversineDistancesOp(self):
# shape[1] != 2
with self.assertRaises(ValueError):
haversine_distances(mt.random.rand(10, 3))
# shape[1] != 2
with self.assertRaises(ValueError):
haversine_distances(mt.random.rand(10, 2), mt.random.rand(11, 3))
# cannot support sparse
with self.assertRaises(TypeError):
haversine_distances(
mt.random.randint(10, size=(10, 2), density=0.5))