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adding unit tests #2

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Nov 18, 2024
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adding unit tests #2

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49 changes: 47 additions & 2 deletions tests/test_medical_datasets.py
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Original file line number Diff line number Diff line change
Expand Up @@ -250,8 +250,29 @@ def _create_synthetic_dataset(self):
self.sample_paths.append(Path(img_path).expanduser().resolve())
self.sample_class.append(self.class_names.index(class_name))

def _generate_image_names(add_dots_in_title, n_dots: int = 3, extension: str = '.nii.gz'):
# see issue 1105
if add_dots_in_title:
img_name = str(uuid4())
_possible_idx = list(range(len(img_name)))
for i in range(n_dots):
rand_idx = random.choice(_possible_idx)
img_name = img_name[:rand_idx] + '.' + img_name[rand_idx + 1:]
_possible_idx.remove(rand_idx)

return f'{img_name}{extension}'
else:
return f'image_{uuid4()}{extension}'


def _create_synthetic_dataset(root: str, n_samples: int, tabular_file: str, index_col: str):
def _create_synthetic_dataset(
root: str,
n_samples: int,
tabular_file: str,
index_col: str,
add_dots_in_title: bool = False,
extension: str = '.nii.gz'
):
"""Creates synthetic dataset for test purposes

Args:
Expand Down Expand Up @@ -280,7 +301,10 @@ def _create_synthetic_dataset(root: str, n_samples: int, tabular_file: str, inde
for modality in modalities:
modality_folder = os.path.join(subject_folder, modality)
os.mkdir(modality_folder)
img_path = os.path.join(modality_folder, f'image_{uuid4()}.nii.gz')
img_path = os.path.join(
modality_folder,
_generate_image_names(add_dots_in_title, n_dots=6, extension=extension)
)
itk.imwrite(img, img_path)

# Add demographics information
Expand Down Expand Up @@ -793,6 +817,27 @@ def test_medical_folder_dataset_16_load_MedicalFolder(self):
medical_folder_controller.load_MedicalFolder()
mfd_patcher.stop()

def test_medical_folder_dataset_16_(self):
# test for bug #1105: failure when loading image which title contains dots
for extension in ('.nii', '.nii.gz'):
self.root2 = tempfile.mkdtemp()
self.tabular_file = os.path.join(self.root2, 'participants.csv')
self.index_col = 'FOLDER_NAME'

self.transform = {'T1': Lambda(lambda x: torch.flatten(x))}
self.target_transform = {'label': GaussianSmooth()}

self.n_samples = 10
self.batch_size = 3

print(f'Dataset folder located in: {self.root2}')
_create_synthetic_dataset(self.root2, self.n_samples, self.tabular_file, self.index_col, add_dots_in_title=True, extension=extension)
dataset = MedicalFolderDataset(self.root, tabular_file=self.tabular_file, index_col=self.index_col,)

for _subj in os.listdir(self.root2):
if os.path.isdir(_subj):
data = dataset.load_images(Path(self.root2).joinpath(_subj), ['T1', 'T2'])
self.assertListEqual(['T1', 'T2'], list(data.keys()))

class TestMedicalFolderBase(unittest.TestCase):

Expand Down