fix: ruff errors

.github/workflows/main.yml

@@ -22,7 +22,8 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest, macos-latest, windows-latest]
-        python-version: ["3.12", "3.11", "3.10"]
+        python-version: 3.11
+        # python-version: ["3.12", "3.11", "3.10"]
 
     steps:
       - uses: actions/checkout@v3

examples/radcure_simple.py

@@ -114,7 +114,7 @@ def process_one_subject(self, subject_id):
 
         image = self.image_input(subject_id).image
 
-        structure_set = self.structure_set_input(subject_id)
+        structure_set = self.structure_set_input(subject_id)  # noqa: F841
         dose_set = self.rtdose_input(subject_id)
         pet_set = self.petscan_input(subject_id)
 

src/imgtools/autopipeline.py

@@ -474,7 +474,7 @@ def process_one_subject(self, subject_id):
                         if conn_to == "CT" or conn_to == "MR":
                             img = image
                         elif conn_to == "PT":
-                            img = pet
+                            img = pet  # noqa: F821
 
                         mask = self.make_binary_mask(structure_set, img, 
                                                      self.existing_roi_indices, 

src/imgtools/image.py

@@ -124,9 +124,6 @@ def geometry(self):
                              direction=self.direction,
                              spacing=self.spacing)
 
-    @property
-    def size(self):
-        return self._image.GetSize()[::-1]
 
     @property
     def ndim(self):

src/imgtools/io/dataset.py

@@ -174,7 +174,7 @@ def process_one_subject(
                 if conn_to == "CT":
                     mask = make_binary_mask(structure_set, image)
                 elif conn_to == "PT":
-                    mask = make_binary_mask(structure_set, pet)
+                    mask = make_binary_mask(structure_set, pet)  # noqa: F821
                 else:
                     raise ValueError("You need to pass a reference CT or PT/PET image to map contours to.")
                 temp[f"mod_{colname}"] = tio.LabelMap.from_sitk(mask)

src/imgtools/io/writers.py

@@ -119,7 +119,7 @@ def put(self, subject_id, mask, **kwargs):
 
         origin = mask.GetOrigin()
         spacing = mask.GetSpacing()
-        direction = mask.GetDirection()
+        direction = mask.GetDirection()  # noqa: F841
 
         space = "left-posterior-superior"  # everything is ITK read/write 
 

src/imgtools/modules/datagraph.py

@@ -267,7 +267,7 @@ def parser(self, query_string: str) -> pd.DataFrame:
         '''
         # Basic processing of just one modality
         supp_mods   = ["RTDOSE", "RTSTRUCT", "CT", "PT", 'MR', 'SEG']
-        edge_def    = {"RTSTRUCT,RTDOSE" : 0, "CT,RTDOSE" : 1, "CT,RTSTRUCT" : 2, "PET,RTSTRUCT" : 3, "CT,PT" : 4, 'MR,RTSTRUCT': 2, "RTPLAN,RTSTRUCT": 6, "RTPLAN,RTDOSE": 5, "CT,SEG": 7, "MR,SEG": 7, "MR,RTSTRUCT": 2}
+        edge_def    = {"RTSTRUCT,RTDOSE" : 0, "CT,RTDOSE" : 1, "CT,RTSTRUCT" : 2, "PET,RTSTRUCT" : 3, "CT,PT" : 4, 'MR,RTSTRUCT': 2, "RTPLAN,RTSTRUCT": 6, "RTPLAN,RTDOSE": 5, "CT,SEG": 7, "MR,SEG": 7}
         self.mods   = query_string.split(",")
         self.mods_n = len(self.mods)
 

src/imgtools/ops/ops.py

@@ -100,7 +100,7 @@ def __init__(self,
 
         import json
         with open(tree_crawl_path, 'r') as f:
-            tree_db = json.load(f)  # currently unused, TO BE implemented in the future
+            tree_db = json.load(f)  # currently unused, TO BE implemented in the future  # noqa: F841
 
         # GRAPH
         # -----
@@ -1636,7 +1636,7 @@ def get_mask(self, reference_image, seg, mask, label, idx, continuous):
             mask[:,:,:,idx] += seg[:,:,:,idx_seg]
         else:                                       # if 2D segmentations on 3D images
             frame        = seg.frame_groups[idx_seg]
-            ref_uid      = frame.DerivationImageSequence[0].SourceImageSequence[0].ReferencedSOPInstanceUID  # unused but references InstanceUID of slice
+            ref_uid      = frame.DerivationImageSequence[0].SourceImageSequence[0].ReferencedSOPInstanceUID  # unused but references InstanceUID of slice  # noqa: F841
             frame_coords = np.array(frame.PlanePositionSequence[0].ImagePositionPatient)
             img_coords   = physical_points_to_idxs(reference_image, np.expand_dims(frame_coords, (0, 1)))[0][0]
             z            = img_coords[0]

src/imgtools/utils/nnunet.py

@@ -41,7 +41,7 @@ def subfiles(folder: str, join: bool = True, prefix: str = None, suffix: str = N
     if join:
         path_fn = os.path.join
     else:
-        path_fn = lambda x, y: y
+        path_fn = lambda x, y: y  # noqa: E731
     res = [path_fn(folder, i) for i in os.listdir(folder) if os.path.isfile(os.path.join(folder, i))
            and (prefix is None or i.startswith(prefix))
            and (suffix is None or i.endswith(suffix))]

tests/dataset_check.py

@@ -37,7 +37,7 @@ def dataset_path():
 
     #Defining paths for autopipeline and dataset component
     crawl_path = pathlib.Path(imgtools_path, f"imgtools_{dataset_name}.csv").as_posix()
-    json_path =  pathlib.Path(imgtools_path, f"imgtools_{dataset_name}.json").as_posix()
+    json_path =  pathlib.Path(imgtools_path, f"imgtools_{dataset_name}.json").as_posix()  # noqa: F841
     edge_path = pathlib.Path(imgtools_path, f"imgtools_{dataset_name}_edges.csv").as_posix()
     yield quebec_path, output_path, crawl_path, edge_path
 

tests/test_components.py

@@ -35,7 +35,7 @@ def dataset_path():
 
     #Defining paths for autopipeline and dataset component
     crawl_path = pathlib.Path(imgtools_path, f"imgtools_{dataset_name}.csv").as_posix()
-    json_path =  pathlib.Path(imgtools_path, f"imgtools_{dataset_name}.json").as_posix()
+    json_path =  pathlib.Path(imgtools_path, f"imgtools_{dataset_name}.json").as_posix()  # noqa: F841
     edge_path = pathlib.Path(imgtools_path, f"imgtools_{dataset_name}_edges.csv").as_posix()
     yield quebec_path, output_path, crawl_path, edge_path