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Merged
merged 2 commits into from
Oct 6, 2024
Merged

Apply ruff/refurb preview rules (FURB) #581

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c3c3452
Apply ruff/refurb preview rule FURB145
DimitriPapadopoulos Oct 4, 2024
888317e
Apply ruff/refurb preview rule FURB148
DimitriPapadopoulos Oct 4, 2024
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2 changes: 1 addition & 1 deletion nipy/algorithms/utils/pca.py
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Expand Up @@ -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)
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4 changes: 2 additions & 2 deletions nipy/algorithms/utils/tests/test_pca_image.py
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Expand Up @@ -302,7 +302,7 @@ def test_other_axes(data_dict):
assert_almost_equal(pos_dp['basis_vectors'], pos_p[bv_key])
assert_almost_equal(pos_dp['basis_projections'], img_bps.get_fdata())
# And we've replaced the expected axis
exp_coords = in_coords[:]
exp_coords = in_coords.copy()
exp_coords[exp_coords.index(axis_name)] = 'PCA components'
assert img_bps.axes.coord_names == tuple(exp_coords)
# If the affine is not diagonal, we'll get an error
Expand All @@ -323,6 +323,6 @@ def test_other_axes(data_dict):
pytest.raises(AxisError, pca_image, nd_img, axis_name)
for axis_name in 'kt':
p = pca_image(img, axis_name, ncomp=ncomp)
exp_coords = in_coords[:]
exp_coords = in_coords.copy()
exp_coords[exp_coords.index(axis_name)] = 'PCA components'
assert p['basis_projections'].axes.coord_names == tuple(exp_coords)
2 changes: 1 addition & 1 deletion nipy/core/utils/generators.py
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Expand Up @@ -182,7 +182,7 @@ def slice_generator(data, axis=0):
slice_template = [slice(0, s) for s in data.shape]

for n in range(nmax):
slices = slice_template[:]
slices = slice_template.copy()
for (a, div, mod) in zip(axis, divs, mods):
x = int(n / div % mod)
slices[a] = x
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2 changes: 1 addition & 1 deletion nipy/labs/mask.py
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Expand Up @@ -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:
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2 changes: 1 addition & 1 deletion nipy/modalities/fmri/tests/test_glm.py
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Expand Up @@ -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))
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