Run ruff with unsafe-fixes.

Author: tsalo

src/modelarrayio/__init__.py

@@ -70,7 +70,7 @@
 EXTRA_REQUIRES['docs'] = EXTRA_REQUIRES['doc']
 
 # Enable a handle to install all extra dependencies at once
-EXTRA_REQUIRES['all'] = list(set([v for deps in EXTRA_REQUIRES.values() for v in deps]))
+EXTRA_REQUIRES['all'] = list({v for deps in EXTRA_REQUIRES.values() for v in deps})
 
 CLASSIFIERS = [
     'Development Status :: 3 - Alpha',

src/modelarrayio/cifti.py

@@ -301,7 +301,7 @@ def write_storage(
             return 0
 
         # Establish a reference brain axis once to ensure consistent ordering across workers.
-        first_scalar, first_sources = next(iter(scalar_sources.items()))
+        _first_scalar, first_sources = next(iter(scalar_sources.items()))
         first_path = op.join(relative_root, first_sources[0])
         _, reference_brain_names = extract_cifti_scalar_data(first_path)
 

src/modelarrayio/fixels.py

@@ -89,7 +89,7 @@ def gather_fixels(index_file, directions_file):
         path to a Nifti2 directions file
     """
 
-    index_img, index_data = mif_to_nifti2(index_file)
+    _index_img, index_data = mif_to_nifti2(index_file)
     count_vol = index_data[..., 0].astype(
         np.uint32
     )  # number of fixels in each voxel; by index.mif definition
@@ -123,23 +123,23 @@ def gather_fixels(index_file, directions_file):
     sorted_coords = voxel_coords[id_sort]
 
     voxel_table = pd.DataFrame(
-        dict(
-            voxel_id=np.arange(voxel_coords.shape[0]),
-            i=sorted_coords[:, 0],
-            j=sorted_coords[:, 1],
-            k=sorted_coords[:, 2],
-        )
+        {
+            'voxel_id': np.arange(voxel_coords.shape[0]),
+            'i': sorted_coords[:, 0],
+            'j': sorted_coords[:, 1],
+            'k': sorted_coords[:, 2],
+        }
     )
 
-    directions_img, directions_data = mif_to_nifti2(directions_file)
+    _directions_img, directions_data = mif_to_nifti2(directions_file)
     fixel_table = pd.DataFrame(
-        dict(
-            fixel_id=fixel_ids,
-            voxel_id=fixel_voxel_ids,
-            x=directions_data[:, 0],
-            y=directions_data[:, 1],
-            z=directions_data[:, 2],
-        )
+        {
+            'fixel_id': fixel_ids,
+            'voxel_id': fixel_voxel_ids,
+            'x': directions_data[:, 0],
+            'y': directions_data[:, 1],
+            'z': directions_data[:, 2],
+        }
     )
 
     return fixel_table, voxel_table
@@ -192,11 +192,11 @@ def write_storage(
     scalars = defaultdict(list)
     sources_lists = defaultdict(list)
     print('Extracting .mif data...')
-    for ix, row in tqdm(
+    for _ix, row in tqdm(
         cohort_df.iterrows(), total=cohort_df.shape[0]
     ):  # ix: index of row (start from 0); row: one row of data
         scalar_file = op.join(relative_root, row['source_file'])
-        scalar_img, scalar_data = mif_to_nifti2(scalar_file)
+        _scalar_img, scalar_data = mif_to_nifti2(scalar_file)
         scalars[row['scalar_name']].append(scalar_data)  # append to specific scalar_name
         sources_lists[row['scalar_name']].append(
             row['source_file']

src/modelarrayio/voxels.py

@@ -294,12 +294,12 @@ def write_storage(
 
     # voxel_table: records the coordinations of the nonzero voxels; coord starts from 0 (because using python)
     voxel_table = pd.DataFrame(
-        dict(
-            voxel_id=np.arange(voxel_coords.shape[0]),
-            i=voxel_coords[:, 0],
-            j=voxel_coords[:, 1],
-            k=voxel_coords[:, 2],
-        )
+        {
+            'voxel_id': np.arange(voxel_coords.shape[0]),
+            'i': voxel_coords[:, 0],
+            'j': voxel_coords[:, 1],
+            'k': voxel_coords[:, 2],
+        }
     )
 
     # upload each cohort's data

test/test_cifti_cli.py

@@ -103,12 +103,7 @@ def test_concifti_cli_creates_expected_hdf5(tmp_path):
         # Column names exist and match subjects count
         grp = h5['scalars/THICK']
         assert 'column_names' in grp
-        colnames = list(
-            map(
-                lambda x: x.decode('utf-8') if isinstance(x, bytes) else str(x),
-                grp['column_names'][...],
-            )
-        )
+        colnames = [x.decode('utf-8') if isinstance(x, bytes) else str(x) for x in grp['column_names'][...]]
         assert len(colnames) == 2
 
         # Spot-check a couple values

test/test_voxels_cli.py

@@ -122,12 +122,7 @@ def test_convoxel_cli_creates_expected_hdf5(tmp_path):
         # Column names exist and match subjects count
         grp = h5['scalars/FA']
         assert 'column_names' in grp
-        colnames = list(
-            map(
-                lambda x: x.decode('utf-8') if isinstance(x, bytes) else str(x),
-                grp['column_names'][...],
-            )
-        )
+        colnames = [x.decode('utf-8') if isinstance(x, bytes) else str(x) for x in grp['column_names'][...]]
         assert len(colnames) == 2
 
         # Spot-check a voxel mapping (pick the third voxel)