style: format code with isort and Yapf

This commit fixes the style issues introduced in bdd4f19 according to the output
from isort and Yapf.

Details: None

tests/test_hsf.py

@@ -59,14 +59,22 @@ def config(models_path):
                 "execution_providers": [
                     [
                         "CUDAExecutionProvider",
-                        {"device_id": 0, "gpu_mem_limit": 2147483648},
+                        {
+                            "device_id": 0,
+                            "gpu_mem_limit": 2147483648
+                        },
                     ],
                     "CPUExecutionProvider",
                 ],
-                "batch_size": 1,
+                "batch_size":
+                1,
             },
         },
-        "roiloc": {"roi": "hippocampus", "contrast": "t2", "margin": [2, 0, 2]},
+        "roiloc": {
+            "roi": "hippocampus",
+            "contrast": "t2",
+            "margin": [2, 0, 2]
+        },
         "augmentation": {
             "flip": {
                 "axes": ["LR"],
@@ -89,18 +97,24 @@ def config(models_path):
         "multispectrality": {
             "pattern": None,
             "same_space": True,
-            "registration": {"type_of_transform": "AffineFast"},
+            "registration": {
+                "type_of_transform": "AffineFast"
+            },
         },
         "segmentation": {
             "ca_mode": "1/2/3",
             "models_path": str(models_path),
             "models": {
                 "model.onnx": {
-                    "url": "https://zenodo.org/record/6457484/files/arunet_3.0.0_single.onnx?download=1",
+                    "url":
+                    "https://zenodo.org/record/6457484/files/arunet_3.0.0_single.onnx?download=1",
                     "xxh3_64": "71edec9011f7f304",
                 }
             },
-            "segmentation": {"test_time_augmentation": True, "test_time_num_aug": 5},
+            "segmentation": {
+                "test_time_augmentation": True,
+                "test_time_num_aug": 5
+            },
         },
     }
 
@@ -112,9 +126,9 @@ def deepsparse_inference_engines(models_path):
     """Tests that models can be loaded using DeepSparse"""
     settings = DictConfig({"num_cores": 0, "batch_size": 2})
 
-    engines = hsf.engines.get_inference_engines(
-        models_path, engine_name="deepsparse", engine_settings=settings
-    )
+    engines = hsf.engines.get_inference_engines(models_path,
+                                                engine_name="deepsparse",
+                                                engine_settings=settings)
 
     return list(engines)
 
@@ -157,13 +171,16 @@ def test_roiloc(models_path):
 
     mri, mask = hsf.roiloc_wrapper.get_mri(mris[0], mask_pattern="mask.nii.gz")
     assert isinstance(mask, ants.ANTsImage)
-    mri, mask = hsf.roiloc_wrapper.get_mri(mris[0], mask_pattern="no_mask.nii.gz")
+    mri, mask = hsf.roiloc_wrapper.get_mri(mris[0],
+                                           mask_pattern="no_mask.nii.gz")
     assert isinstance(mri, ants.ANTsImage)
     assert mask is None
 
-    _, right, left = hsf.roiloc_wrapper.get_hippocampi(
-        mri, {"contrast": "t2", "margin": [2, 0, 2], "roi": "hippocampus"}, mask
-    )
+    _, right, left = hsf.roiloc_wrapper.get_hippocampi(mri, {
+        "contrast": "t2",
+        "margin": [2, 0, 2],
+        "roi": "hippocampus"
+    }, mask)
 
     assert isinstance(right, ants.ANTsImage)
     assert isinstance(left, ants.ANTsImage)
@@ -195,33 +212,40 @@ def test_segment(models_path, config, deepsparse_inference_engines):
 
 def test_multispectrality(models_path):
     """Tests that we can co-locate hippocampi in another contrast."""
-    config = DictConfig(
-        {
-            "files": {"output_dir": str(models_path)},
-            "multispectrality": {
-                "pattern": "sub0_tse.nii.gz",
-                "same_space": False,
-                "registration": {"type_of_transform": "AffineFast"},
+    config = DictConfig({
+        "files": {
+            "output_dir": str(models_path)
+        },
+        "multispectrality": {
+            "pattern": "sub0_tse.nii.gz",
+            "same_space": False,
+            "registration": {
+                "type_of_transform": "AffineFast"
             },
-        }
-    )
+        },
+    })
 
-    mri = hsf.roiloc_wrapper.load_from_config(models_path, "sub0_tse.nii.gz")[0]
-    second_contrast = hsf.multispectrality.get_second_contrast(mri, "sub0_tse.nii.gz")
+    mri = hsf.roiloc_wrapper.load_from_config(models_path,
+                                              "sub0_tse.nii.gz")[0]
+    second_contrast = hsf.multispectrality.get_second_contrast(
+        mri, "sub0_tse.nii.gz")
 
     registered = hsf.multispectrality.register(
-        mri, second_contrast, DictConfig({"multispectrality": {"same_space": True}})
-    )
+        mri, second_contrast,
+        DictConfig({"multispectrality": {
+            "same_space": True
+        }}))
     registered = hsf.multispectrality.register(mri, second_contrast, config)
 
     img = ants.image_read(str(mri), reorient="LPI")
-    locator, _, _ = hsf.roiloc_wrapper.get_hippocampi(
-        img, {"contrast": "t2", "margin": [2, 0, 2], "roi": "hippocampus"}, None
-    )
+    locator, _, _ = hsf.roiloc_wrapper.get_hippocampi(img, {
+        "contrast": "t2",
+        "margin": [2, 0, 2],
+        "roi": "hippocampus"
+    }, None)
 
     _, _ = hsf.multispectrality.get_additional_hippocampi(
-        mri, registered, locator, config
-    )
+        mri, registered, locator, config)
 
 
 def test_uncertainty():