Fix black formatting with --skip-magic-trailing-comma

Signed-off-by: Emanuilo Jovanovic <emanuilo.jovanovic@hotmail.com>

Author: emanuilo

tests/transforms/test_spatial_cropd.py

@@ -79,34 +79,23 @@ class TestSpatialCropdStringKeys(unittest.TestCase):
     def test_string_roi_start_end(self):
         """String keys for roi_start and roi_end should resolve from data dict."""
         img = MetaTensor(torch.rand(3, 10, 10, 10))
-        data = {
-            "img": img,
-            "roi_start_key": [0, 0, 0],
-            "roi_end_key": [5, 5, 5],
-        }
+        data = {"img": img, "roi_start_key": [0, 0, 0], "roi_end_key": [5, 5, 5]}
         cropper = SpatialCropd(keys="img", roi_start="roi_start_key", roi_end="roi_end_key")
         result = cropper(data)
         self.assertEqual(result["img"].shape, (3, 5, 5, 5))
 
     def test_string_roi_center_size(self):
         """String keys for roi_center and roi_size should resolve from data dict."""
         img = MetaTensor(torch.rand(1, 20, 20, 20))
-        data = {
-            "img": img,
-            "center_key": [10, 10, 10],
-            "size_key": [6, 6, 6],
-        }
+        data = {"img": img, "center_key": [10, 10, 10], "size_key": [6, 6, 6]}
         cropper = SpatialCropd(keys="img", roi_center="center_key", roi_size="size_key")
         result = cropper(data)
         self.assertEqual(result["img"].shape, (1, 6, 6, 6))
 
     def test_mixed_string_and_direct(self):
         """Mix of string key and direct value for ROI params."""
         img = MetaTensor(torch.rand(1, 20, 20, 20))
-        data = {
-            "img": img,
-            "center_key": [10, 10, 10],
-        }
+        data = {"img": img, "center_key": [10, 10, 10]}
         cropper = SpatialCropd(keys="img", roi_center="center_key", roi_size=[4, 4, 4])
         result = cropper(data)
         self.assertEqual(result["img"].shape, (1, 4, 4, 4))
@@ -175,11 +164,7 @@ def test_string_key_same_as_direct(self):
     def test_inverse_with_string_keys(self):
         """Inverse should work correctly when string keys are used."""
         img = MetaTensor(torch.rand(1, 10, 10, 10))
-        data = {
-            "img": img,
-            "start": [2, 2, 2],
-            "end": [6, 6, 6],
-        }
+        data = {"img": img, "start": [2, 2, 2], "end": [6, 6, 6]}
         cropper = SpatialCropd(keys="img", roi_start="start", roi_end="end")
         result = cropper(data)
         self.assertEqual(result["img"].shape, (1, 4, 4, 4))

tests/transforms/utility/test_transform_points_image_to_worldd.py

@@ -40,11 +40,7 @@ class TestTransformPointsImageToWorldd(unittest.TestCase):
     @parameterized.expand(TEST_CASES)
     def test_transform(self, image, points, expected_output):
         data = {"image": image, "point": points}
-        transform = TransformPointsImageToWorldd(
-            keys="point",
-            refer_keys="image",
-            dtype=torch.int64,
-        )
+        transform = TransformPointsImageToWorldd(keys="point", refer_keys="image", dtype=torch.int64)
         output = transform(data)
         self.assertTrue(torch.allclose(output["point"], expected_output))
 

tests/transforms/utility/test_transform_points_world_to_imaged.py

@@ -47,10 +47,7 @@ class TestTransformPointsWorldToImaged(unittest.TestCase):
     def test_transform(self, image, points, affine_lps_to_ras, expected_output):
         data = {"image": image, "point": points}
         transform = TransformPointsWorldToImaged(
-            keys="point",
-            refer_keys="image",
-            dtype=torch.int64,
-            affine_lps_to_ras=affine_lps_to_ras,
+            keys="point", refer_keys="image", dtype=torch.int64, affine_lps_to_ras=affine_lps_to_ras
         )
         output = transform(data)
         self.assertTrue(torch.allclose(output["point"], expected_output))