Fix imports

doc/conf.py

@@ -12,7 +12,6 @@
 import sys
 from pathlib import Path
 
-
 import fmralign
 
 # If extensions (or modules to document with autodoc) are in another

fmralign/tests/test_sparse_pairwise_alignment.py

@@ -1,4 +1,6 @@
 import numpy as np
+import pytest
+import torch
 from nibabel.nifti1 import Nifti1Image
 from nilearn.surface import SurfaceImage
 
@@ -7,8 +9,6 @@
     random_niimg,
     surf_img,
 )
-import torch
-import pytest
 
 devices = [torch.device("cpu")]
 if torch.cuda.is_available():

fmralign/tests/test_sparse_template_alignment.py

@@ -1,16 +1,18 @@
-import torch
+from itertools import product
+
 import numpy as np
 import pytest
+import torch
+from nibabel.nifti1 import Nifti1Image
+
+from fmralign.alignment_methods import SparseUOT
 from fmralign.sparse_template_alignment import (
-    _rescaled_euclidean_mean_torch,
+    SparseTemplateAlignment,
     _align_images_to_template,
     _fit_sparse_template,
+    _rescaled_euclidean_mean_torch,
 )
-from nibabel.nifti1 import Nifti1Image
-from fmralign.tests.utils import sample_subjects_data, random_niimg
-from itertools import product
-from fmralign.alignment_methods import SparseUOT
-from fmralign.sparse_template_alignment import SparseTemplateAlignment
+from fmralign.tests.utils import random_niimg, sample_subjects_data
 
 devices = [torch.device("cpu")]
 if torch.cuda.is_available():

fmralign/tests/test_utils.py

@@ -2,9 +2,10 @@
 import nibabel as nib
 import numpy as np
 import pytest
+import torch
 from nilearn.maskers import NiftiMasker
 from numpy.testing import assert_array_almost_equal, assert_array_equal
-import torch
+
 from fmralign._utils import (
     ParceledData,
     _make_parcellation,