def test_works_with_hdf5_fibsem(self):
train_dataset = get_train_dataset(h5py.File)
dataset = train_dataset[0]
origin = (105, 100, 100)
numpy_dataset, expected_dataset = self.get_datasets(dataset, origin)
for key in ['data', 'label', 'mask']:
self.assertEqual(numpy_dataset[key].shape, expected_dataset[key].shape)
np.testing.assert_almost_equal(
numpy_dataset[key],
expected_dataset[key],
err_msg=str((key, "result", numpy_dataset[key], "desired", expected_dataset[key])),
)
def test_works_with_dvid(self):
train_dataset = get_train_dataset(DVIDDataInstance)
dataset = train_dataset[0]
dataset['body_names_to_exclude'] = ['out']
origin = (3000, 3000, 3000)
numpy_dataset, expected_dataset = self.get_datasets(dataset, origin)
for key in ['data', 'label', 'mask']:
self.assertEqual(numpy_dataset[key].shape, expected_dataset[key].shape)
np.testing.assert_almost_equal(
numpy_dataset[key],
expected_dataset[key],
err_msg=str((key, "result", numpy_dataset[key], "desired", expected_dataset[key])),
)
def test_works_with_hdf5_fibsem(self):
train_dataset = get_train_dataset(h5py.File)
dataset = train_dataset[0]
origin = (105, 100, 100)
numpy_dataset, expected_dataset = self.get_datasets(dataset, origin)
for key in ['data', 'label', 'mask']:
self.assertEqual(numpy_dataset[key].shape,
expected_dataset[key].shape)
np.testing.assert_almost_equal(
numpy_dataset[key],
expected_dataset[key],
err_msg=str((key, "result", numpy_dataset[key], "desired",
expected_dataset[key])),
)
def test_works_with_dvid(self):
train_dataset = get_train_dataset(DVIDDataInstance)
dataset = train_dataset[0]
dataset['body_names_to_exclude'] = ['out']
origin = (3000, 3000, 3000)
numpy_dataset, expected_dataset = self.get_datasets(dataset, origin)
for key in ['data', 'label', 'mask']:
self.assertEqual(numpy_dataset[key].shape,
expected_dataset[key].shape)
np.testing.assert_almost_equal(
numpy_dataset[key],
expected_dataset[key],
err_msg=str((key, "result", numpy_dataset[key], "desired",
expected_dataset[key])),
)
