def test_process_observations_providing_list(self):
observations = [0, 1, 2, 3, 4, 5, 6, 7]
processed_obs, num_features, labels = \
_process_observations(observations, self.comm)
self.assertTrue(isinstance(processed_obs, Block))
self.assertEqual(num_features, 1)
self.assertTrue(isinstance(labels, Block))
def test_process_observations_providing_mpi_np_array(self):
#Default block distribution
mpi_np_observations = mpi_np.arange(8, dist='b')
processed_obs, num_features, labels = \
_process_observations(mpi_np_observations, self.comm)
self.assertTrue(isinstance(processed_obs, Block))
self.assertEqual(num_features, 1)
self.assertTrue(isinstance(labels, Block))
#Replicated distribution
mpi_np_observations = mpi_np.arange(8, dist='r')
processed_obs, num_features, labels = \
_process_observations(mpi_np_observations, self.comm)
self.assertTrue(isinstance(processed_obs, Block))
self.assertEqual(num_features, 1)
self.assertTrue(isinstance(labels, Block))
def test_process_observations_providing_numpy_array(self):
np_observations = np.arange(8)
processed_obs, num_features, labels = \
_process_observations(np_observations, self.comm)
self.assertTrue(isinstance(processed_obs, Block))
self.assertEqual(num_features, 1)
self.assertTrue(isinstance(labels, Block))
def test_kmeans_calls_process_observations(self):
obs = self.dist_obs_1_feature
k = self.k
processed_obs, num_features, labels = \
_process_observations(obs, self.comm)
with mock.patch('mpids.MPIscipy.cluster._kmeans._process_observations',
return_value=(processed_obs, num_features,
labels)) as mock_proc_obs:
mpi_scipy_cluster.kmeans(obs, k)
mock_proc_obs.assert_called_with(obs, self.comm)
def test_process_observations_providing_3D_observations_raises_ValueError(
self):
observations = np.arange(27).reshape(3, 3, 3)
with self.assertRaises(ValueError):
_process_observations(observations, self.comm)