Apply ruff/refurb preview rule FURB148

DimitriPapadopoulos · DimitriPapadopoulos · commit 888317e9391e · 2024-10-05T18:21:24.000+02:00
FURB148 `enumerate` index is unused, use `for x in y` instead
diff --git a/nipy/algorithms/utils/pca.py b/nipy/algorithms/utils/pca.py
@@ -216,7 +216,7 @@ def _get_covariance(data, UX, rmse_scales_func, mask):
         # If we have more then 2D, then we iterate over slices in the second
         # dimension, in order to save memory
         slices = [slice(i,i+1) for i in range(data.shape[1])]
-    for i, s_slice in enumerate(slices):
+    for s_slice in slices:
         Y = data[:,s_slice].reshape((n_pts, -1))
         # project data into required space
         YX = np.dot(UX, Y)
diff --git a/nipy/labs/mask.py b/nipy/labs/mask.py
@@ -293,7 +293,7 @@ def compute_mask_sessions(session_images, m=0.2, M=0.9, cc=1, threshold=0.5,
         The mean image
     """
     mask, mean = None, None
-    for index, session in enumerate(session_images):
+    for session in session_images:
         if hasattr(session, 'get_fdata'):
             mean = session.get_fdata()
             if mean.ndim > 3:
diff --git a/nipy/modalities/fmri/tests/test_glm.py b/nipy/modalities/fmri/tests/test_glm.py
@@ -37,7 +37,7 @@ def write_fake_fmri_data(shapes, rk=3, affine=np.eye(4)):
 def generate_fake_fmri_data(shapes, rk=3, affine=np.eye(4)):
     fmri_data = []
     design_matrices = []
-    for i, shape in enumerate(shapes):
+    for shape in shapes:
         data = 100 + np.random.randn(*shape)
         data[0] -= 10
         fmri_data.append(Nifti1Image(data, affine))
