[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

src/torchio/data/image.py

@@ -923,14 +923,12 @@ def count_labels(self) -> Dict[int, int]:
 
 
 class LazyImage(Image):
-
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
 
     def load(self):
-
         if self._is_multipath():
-            message = (f'No multiple paths for LazyImage')
+            message = f'No multiple paths for LazyImage'
             RuntimeError(message)
 
         tensor, affine = self.read_and_check(self.path)
@@ -943,7 +941,6 @@ def _parse_tensor(
         tensor: Optional[TypeData],
         none_ok: bool = True,
     ) -> Optional[torch.Tensor]:
-
         if tensor is None:
             if none_ok:
                 return None
@@ -986,11 +983,10 @@ def __repr__(self):
 
 
 class LazyScalarImage(LazyImage, ScalarImage):
-
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
 
-class LazyLabelMap(LazyImage, LabelMap):
 
+class LazyLabelMap(LazyImage, LabelMap):
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)

src/torchio/transforms/preprocessing/spatial/crop.py

@@ -49,7 +49,7 @@ def apply_transform(self, sample) -> Subject:
             new_affine[:3, 3] = new_origin
             i0, j0, k0 = index_ini
             i1, j1, k1 = index_fin
-            if isinstance(image.data,torch.Tensor):
+            if isinstance(image.data, torch.Tensor):
                 image.set_data(image.data[:, i0:i1, j0:j1, k0:k1].clone())
             else:
                 image.set_data(torch.as_tensor(image.data[:, i0:i1, j0:j1, k0:k1]))