def test_from_file_apply_invalid_transformation(self):
with self.assertRaises(Exception):
next(
iter(
test.PickledDicomoDataSet(dicom_data_set, ["CT"],
transform=[],
constraints={})))
def test_len(self):
dataset = iter(
test.PickledDicomoDataSet(dicom_data_set, ["CT"], constraints={}))
self.assertEqual(len(dataset), 0)
next(dataset)
self.assertEqual(len(dataset), 1)
next(dataset)
next(dataset)
self.assertEqual(len(dataset), 3)
def test_from_file_apply_valid_transformation(self):
t1 = torchvision.transforms.Compose([
torchvision.transforms.ToPILImage(),
torchvision.transforms.Resize((244, 244)),
torchvision.transforms.ToTensor()
])
data = next(
iter(
test.PickledDicomoDataSet(dicom_data_set, ["CT"],
transform=t1,
constraints={})))
self.assertIsInstance(data, list)
def test_iter(self):
dataset = test.PickledDicomoDataSet(dicom_data_set, ["CT"],
constraints={})
dataset = iter(dataset)
self.assertIsInstance(dataset, test.PickledDicomoDataSet)
def test_next(self):
dataset = test.PickledDicomoDataSet(dicom_data_set, ["CT"],
constraints={})
data = next(iter(dataset))
self.assertIsInstance(data, list)
def test_classes_correct_usage(self):
data = test.PickledDicomoDataSet(dicom_data_set, ["CT"],
constraints={})
self.assertIsInstance(data.classes("Modality"), list)
def test_init_wrong_constraints_type(self):
with self.assertRaises(TypeError):
dataset = test.PickledDicomoDataSet(dicom_data_set, ["CT"],
constraints=[])
def test_init_wrong_label_counter_type(self):
with self.assertRaises(TypeError):
test.PickledDicomoDataSet(
dicom_data_set, ["CT"],
constraints={},
label_counter_type=TestPickledDicomoDataSet)
def test_init_invalid_file_path(self):
with self.assertRaises(FileNotFoundError):
test.PickledDicomoDataSet(wrong_dicom_file_path, ["CT"],
constraints={})
def test_summarize_wrong_summary_type(self):
data = test.PickledDicomoDataSet(dicom_data_set, ["CT"],
constraints={})
with self.assertRaises(TypeError):
data.summarize("Modality", print_summary=None)
def test_init_correct_usage(self):
dataset = test.PickledDicomoDataSet(dicom_data_set, ["CT"],
constraints={})
self.assertIsInstance(dataset, test.PickledDicomoDataSet)
def test_summarize_test_CT_constraint(self):
data = test.PickledDicomoDataSet(dicom_data_set, ["CT"],
constraints={})
summary_1 = data.summarize("Modality", print_summary=False)
summary_2 = data.summarize("BodyPartExamined", print_summary=False)
self.assertNotEqual(str(summary_1), str(summary_2))
def test_summarize_correct_usage(self):
data = test.PickledDicomoDataSet(dicom_data_set, ["CT"],
constraints={})
self.assertIsInstance(data.summarize("Modality", print_summary=False),
test.gem.LabelCounter)
def test_classes_wrong_label_type(self):
data = test.PickledDicomoDataSet(dicom_data_set, ["CT"],
constraints={})
with self.assertRaises(TypeError):
data.classes(["Modality"])
def test_subset_correct_usage(self):
data = test.PickledDicomoDataSet(dicom_data_set, ["CT"],
constraints={})
subset = data.subset({"Modality": "asd"})
with self.assertRaises(StopIteration):
next(iter(subset))
def test_init_file_has_wrong_type(self):
dataset = test.PickledDicomoDataSet(raw_dicom_file_path, ["CT"],
constraints={})
with self.assertRaises(test.gem.pickle.UnpicklingError):
next(iter(dataset))
def test_subset_wrong_constraint_type(self):
data = test.PickledDicomoDataSet(dicom_data_set, ["CT"],
constraints={})
with self.assertRaises(TypeError):
subset = data.subset(("Modality", 1))
def test_can_be_parallelized(self):
data = test.PickledDicomoDataSet(dicom_data_set, ["CT"],
constraints={})
self.assertEqual(data.can_be_parallelized(), False)