Your message dated Fri, 24 Oct 2025 19:53:58 +0000
with message-id <[email protected]>
and subject line Bug#1109953: fixed in nibabel 5.3.2-3
has caused the Debian Bug report #1109953,
regarding nibabel: tests failing with scipy 1.16
to be marked as done.

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-- 
1109953: https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=1109953
Debian Bug Tracking System
Contact [email protected] with problems
--- Begin Message ---
Source: nibabel
Version: 5.3.2-2
Severity: normal

scipy 1.16 has been uploaded to experimental.
nibabel tests are failing with it, possibly due to a change in API.

176s =========================== short test summary info 
============================
176s FAILED nibabel/tests/test_processing.py::test_resample_from_to - Failed: 
DID ...
176s FAILED nibabel/tests/test_processing.py::test_resample_to_output - Failed: 
DI...
176s = 2 failed, 5362 passed, 108 skipped, 11 xfailed, 1 xpassed, 26950 
warnings in 137.68s (0:02:17) =

nibabel is expecting a UserWarning which is not emitted, so test_resample* 
fails:

176s ___________________________ test_resample_to_output 
____________________________
176s 
176s caplog = <_pytest.logging.LogCaptureFixture object at 0x7fb89afd3110>
176s 
176s     @needs_scipy
176s     def test_resample_to_output(caplog):
176s         # Test routine to sample images to output space
176s         # Image aligned to output axes - no-op
176s         data = np.arange(24, dtype='int32').reshape((2, 3, 4))
176s         img = Nifti1Image(data, np.eye(4))
176s         # Check default resampling
176s         img2 = resample_to_output(img)
176s         assert_array_equal(img2.shape, (2, 3, 4))
176s         assert_array_equal(img2.affine, np.eye(4))
176s         assert_array_equal(img2.dataobj, data)
176s         # Check resampling with different voxel size specifications
176s         for vox_sizes in (None, 1, [1, 1, 1]):
176s             img2 = resample_to_output(img, vox_sizes)
176s             assert_array_equal(img2.shape, (2, 3, 4))
176s             assert_array_equal(img2.affine, np.eye(4))
176s             assert_array_equal(img2.dataobj, data)
176s         img2 = resample_to_output(img, vox_sizes)
176s         # Check 2D works
176s         img_2d = Nifti1Image(data[0], np.eye(4))
176s         for vox_sizes in (None, 1, (1, 1), (1, 1, 1)):
176s             img3 = resample_to_output(img_2d, vox_sizes)
176s             assert_array_equal(img3.shape, (3, 4, 1))
176s             assert_array_equal(img3.affine, np.eye(4))
176s             assert_array_equal(img3.dataobj, data[0][..., None])
176s         # Even 1D
176s         img_1d = Nifti1Image(data[0, 0], np.eye(4))
176s         img3 = resample_to_output(img_1d)
176s         assert_array_equal(img3.shape, (4, 1, 1))
176s         assert_array_equal(img3.affine, np.eye(4))
176s         assert_array_equal(img3.dataobj, data[0, 0][..., None, None])
176s         # But 4D does not
176s         img_4d = Nifti1Image(data.reshape(2, 3, 2, 2), np.eye(4))
176s         with pytest.raises(ValueError):
176s             resample_to_output(img_4d)
176s         # Run vox2vox_out tests, checking output shape, coordinate 
transform
176s         for in_shape, in_aff, vox, out_shape, out_aff in 
get_outspace_params():
176s             # Allow for expansion of image shape from < 3D
176s             in_n_dim = len(in_shape)
176s             if in_n_dim < 3:
176s                 in_shape = in_shape + (1,) * (3 - in_n_dim)
176s                 if not vox is None:
176s                     vox = vox + (1,) * (3 - in_n_dim)
176s                 assert len(out_shape) == in_n_dim
176s                 out_shape = out_shape + (1,) * (3 - in_n_dim)
176s             img = Nifti1Image(np.ones(in_shape), in_aff)
176s             out_img = resample_to_output(img, vox)
176s             assert_all_in(in_shape, in_aff, out_img.shape, out_img.affine)
176s             assert out_img.shape == out_shape
176s             assert_almost_equal(out_img.affine, out_aff)
176s         # Check data is as expected with some transforms
176s         # Flip first axis
176s         out_img = resample_to_output(Nifti1Image(data, np.diag([-1, 1, 1, 
1])))
176s         assert_array_equal(out_img.dataobj, np.flipud(data))
176s         # Subsample voxels
176s         out_img = resample_to_output(Nifti1Image(data, np.diag([4, 5, 6, 
1])))
176s >       with pytest.warns(UserWarning):  # Suppress scipy warning
176s E       Failed: DID NOT WARN. No warnings of type (<class 'UserWarning'>,) 
were emitted.
176s E        Emitted warnings: [].
176s 
176s nibabel/tests/test_processing.py:278: Failed


This bug will become RC serious later, after scipy 1.16 is uploaded to
unstable.


-- System Information:
Debian Release: 13.0
  APT prefers unstable-debug
  APT policy: (500, 'unstable-debug'), (500, 'unstable'), (1, 'experimental')
Architecture: amd64 (x86_64)
Foreign Architectures: i386

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Init: systemd (via /run/systemd/system)
LSM: AppArmor: enabled

--- End Message ---
--- Begin Message ---
Source: nibabel
Source-Version: 5.3.2-3
Done: Étienne Mollier <[email protected]>

We believe that the bug you reported is fixed in the latest version of
nibabel, which is due to be installed in the Debian FTP archive.

A summary of the changes between this version and the previous one is
attached.

Thank you for reporting the bug, which will now be closed.  If you
have further comments please address them to [email protected],
and the maintainer will reopen the bug report if appropriate.

Debian distribution maintenance software
pp.
Étienne Mollier <[email protected]> (supplier of updated nibabel package)

(This message was generated automatically at their request; if you
believe that there is a problem with it please contact the archive
administrators by mailing [email protected])


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Hash: SHA512

Format: 1.8
Date: Fri, 24 Oct 2025 21:23:58 +0200
Source: nibabel
Architecture: source
Version: 5.3.2-3
Distribution: unstable
Urgency: medium
Maintainer: Debian Med Packaging Team 
<[email protected]>
Changed-By: Étienne Mollier <[email protected]>
Closes: 1109953
Changes:
 nibabel (5.3.2-3) unstable; urgency=medium
 .
   * scipy-1.16.patch: new: fix tests with scipy 1.16. (Closes: #1109953)
   * d/patches/*: normalize Last-Update timestamp.
   * d/watch: convert to v5 Github template.
   * d/control: drop redundant Rules-Requires-Root: no.
   * d/control: declare compliance to standards version 4.7.2.
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--- End Message ---

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