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[FIX] Fix tests failing due to deprecations in pre-release dependencies #3746

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merged 6 commits into from
Jun 9, 2023
Merged

[FIX] Fix tests failing due to deprecations in pre-release dependencies #3746

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727df13
Fix test in test_html_report
Jun 6, 2023
d6912e6
Fix other test in test_html_report
Jun 7, 2023
0116b12
Remove raise warning since already tested
Jun 7, 2023
5de4cf2
Fix clipping
Jun 7, 2023
4c6e35a
Clarify if statement
Jun 8, 2023
1e57ca4
Improve if statement
Jun 8, 2023
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4 changes: 2 additions & 2 deletions nilearn/image/resampling.py
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Expand Up @@ -686,8 +686,8 @@ def resample_img(
# preventing ringing artefact
# We need to add zero as a value considered for clipping, as it
# appears in padding images.
vmin = min(data.min(), 0)
vmax = max(data.max(), 0)
vmin = min(np.nanmin(data), 0)
vmax = max(np.nanmax(data), 0)
resampled_data.clip(vmin, vmax, out=resampled_data)

return new_img_like(img, resampled_data, target_affine)
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3 changes: 1 addition & 2 deletions nilearn/image/tests/test_resampling.py
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Expand Up @@ -586,8 +586,7 @@ def test_resampling_nan(affine, core_shape):

# check 3x3 transformation matrix
target_affine = np.eye(3)[axis_permutation]
with pytest.warns(Warning, match=r"(\bnan\b|invalid value)"):
resampled_img = resample_img(source_img, target_affine=target_affine)
resampled_img = resample_img(source_img, target_affine=target_affine)

resampled_data = get_data(resampled_img)
if full_data.ndim == 4:
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6 changes: 5 additions & 1 deletion nilearn/maskers/nifti_maps_masker.py
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Expand Up @@ -229,7 +229,11 @@ def generate_report(self, displayed_maps=10):
from nilearn.reporting.html_report import generate_report

if (
displayed_maps != "all"
(isinstance(displayed_maps, str) and displayed_maps != "all")
or (
not isinstance(displayed_maps, str)
and np.all(displayed_maps != "all")
)
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The logic here is abit complex. Cna you give plain word explanation of the intended behevior

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I did it with the code. Is it clear enough like this?

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Definitely clearer. To me at least.

and not isinstance(displayed_maps, (list, np.ndarray, int))
):
raise TypeError(
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