fix formatting issues for three more files

Signed-off-by: Han Wang <freddie.wanah@gmail.com>

Author: freddiewanah

tests/test_hausdorff_loss.py

@@ -219,13 +219,7 @@ def test_ill_opts(self):
         with self.assertRaisesRegex(ValueError, ""):
             HausdorffDTLoss(reduction=None)(chn_input, chn_target)
 
-    @parameterized.expand(
-        [
-            (False, False, False),
-            (False, True, False),
-            (False, False, True),
-        ]
-    )
+    @parameterized.expand([(False, False, False), (False, True, False), (False, False, True)])
     def test_input_warnings(self, include_background, softmax, to_onehot_y):
         chn_input = torch.ones((1, 1, 1, 3))
         chn_target = torch.ones((1, 1, 1, 3))
@@ -257,13 +251,7 @@ def test_ill_opts(self):
         with self.assertRaisesRegex(ValueError, ""):
             LogHausdorffDTLoss(reduction=None)(chn_input, chn_target)
 
-    @parameterized.expand(
-        [
-            (False, False, False),
-            (False, True, False),
-            (False, False, True),
-        ]
-    )
+    @parameterized.expand([(False, False, False), (False, True, False), (False, False, True)])
     def test_input_warnings(self, include_background, softmax, to_onehot_y):
         chn_input = torch.ones((1, 1, 1, 3))
         chn_target = torch.ones((1, 1, 1, 3))

tests/test_tversky_loss.py

@@ -165,13 +165,7 @@ def test_ill_shape(self):
         with self.assertRaisesRegex(ValueError, ""):
             TverskyLoss(reduction=None)(chn_input, chn_target)
 
-    @parameterized.expand(
-        [
-            (False, False, False),
-            (False, True, False),
-            (False, False, True),
-        ]
-    )
+    @parameterized.expand([(False, False, False), (False, True, False), (False, False, True)])
     def test_input_warnings(self, include_background, softmax, to_onehot_y):
         chn_input = torch.ones((1, 1, 3))
         chn_target = torch.ones((1, 1, 3))

tests/test_ultrasound_confidence_map_transform.py

@@ -537,12 +537,7 @@ def test_parameters(self):
             UltrasoundConfidenceMapTransform(sink_mode="unknown")
 
     @parameterized.expand(
-        [
-            ("all", SINK_ALL_OUTPUT),
-            ("mid", SINK_MID_OUTPUT),
-            ("min", SINK_MIN_OUTPUT),
-            ("mask", SINK_MASK_OUTPUT, True),
-        ]
+        [("all", SINK_ALL_OUTPUT), ("mid", SINK_MID_OUTPUT), ("min", SINK_MIN_OUTPUT), ("mask", SINK_MASK_OUTPUT, True)]
     )
     def test_ultrasound_confidence_map_transform(self, sink_mode, expected_output, use_mask=False):
         # RGB image
@@ -589,14 +584,7 @@ def test_multi_channel_2d(self, sink_mode, expected_output, use_mask=False):
         self.assertIsInstance(result_np, np.ndarray)
         assert_allclose(result_np, expected_output, rtol=1e-4, atol=1e-4)
 
-    @parameterized.expand(
-        [
-            ("all",),
-            ("mid",),
-            ("min",),
-            ("mask",),
-        ]
-    )
+    @parameterized.expand([("all",), ("mid",), ("min",), ("mask",)])
     def test_non_one_first_dim(self, sink_mode):
         transform = UltrasoundConfidenceMapTransform(sink_mode=sink_mode)
         input_img_rgb = np.repeat(self.input_img_np, 3, axis=0)
@@ -631,13 +619,7 @@ def test_no_first_dim(self, sink_mode):
             with self.assertRaises(ValueError):
                 transform(input_img_rgb, self.input_mask_np)
 
-    @parameterized.expand(
-        [
-            ("all",),
-            ("mid",),
-            ("min",),
-        ]
-    )
+    @parameterized.expand([("all",), ("mid",), ("min",)])
     def test_sink_mode(self, mode):
         transform = UltrasoundConfidenceMapTransform(sink_mode=mode)