[MAINT] Update BrainStat Version

.github/workflows/test.yml

@@ -17,7 +17,7 @@ jobs:
       fail-fast: false
       matrix:
         os: [ubuntu-latest, macos-latest]
-        python-version: ['3.9', '3.10', '3.11', '3.12']
+        python-version: ['3.10', '3.11', '3.12', '3.13']
     steps:
       - uses: actions/checkout@v6
       - uses: snok/install-poetry@v1

.pre-commit-config.yaml

@@ -13,7 +13,6 @@ repos:
     rev: v2.3.0
     hooks:
       - id: codespell
-        args: ["--ignore-words-list=ALS"]
         additional_dependencies:
           - tomli
   - repo: https://github.com/python-poetry/poetry

clinica/pipelines/statistics_surface/_utils.py

@@ -158,12 +158,12 @@ def build_design_matrix(contrast: str, covariates: Optional[str] = None) -> str:
 
     Example
     -------
-    >>> from clinica.pipelines.statistics_surface.statistics_surface_utils import _build_design_matrix
-    >>> _build_design_matrix('group', 'age sex group')
+    >>> from clinica.pipelines.statistics_surface._utils import build_design_matrix
+    >>> build_design_matrix('group', 'age sex group')
     1 + group + age + sex
-    >>> _build_design_matrix('group', 'age')
+    >>> build_design_matrix('group', 'age')
     1 + group + age
-    >>> _build_design_matrix('group', None)
+    >>> build_design_matrix('group', None)
     1 + group
     """
     if covariates:

clinica/utils/image.py

@@ -16,7 +16,6 @@
     "compute_aggregated_volume",
     "get_new_image_like",
     "merge_nifti_images_in_time_dimension",
-    "remove_dummy_dimension_from_image",
     "crop_nifti",
     "clip_nifti",
     "crop_nifti_using_t1_mni_template",
@@ -220,31 +219,6 @@ def _check_volumes_from_images(images: Tuple[Path, ...]) -> Tuple[np.ndarray, ..
     return tuple(four_dimensional_volumes)
 
 
-def remove_dummy_dimension_from_image(image: str, output: str) -> str:
-    """Remove all dummy dimensions (i.e. equal to 1) from an image.
-
-    Parameters
-    ----------
-    image : str
-        Path to the input image.
-
-    output : str
-        Path to the desired output image.
-
-    Returns
-    -------
-    str :
-        The path to the output image.
-    """
-    import nibabel as nib
-    from nilearn.image import new_img_like
-
-    img = new_img_like(image, nib.load(image).get_fdata().squeeze())
-    nib.save(img, output)
-
-    return output
-
-
 @dataclass
 class Slice:
     """Interval composed of a starting point and ending point."""

ignore_words.txt

@@ -6,3 +6,4 @@ nd
 siz
 te
 vox
+ALS

pyproject.toml

@@ -14,7 +14,7 @@ maintainers = [
     { name = "Clinica developers", email = "clinica.run@gmail.com>" },
 ]
 readme = "README.md"
-requires-python = ">=3.9,<3.13"
+requires-python = ">=3.10,<3.14"
 keywords = [
     "bids",
     "image processing",
@@ -33,7 +33,7 @@ classifiers = [
 ]
 dependencies = [
     "nibabel (>=5)",
-    "nipype (>=1.8.6)",
+    "nipype (>=1.10.0)",
     "argcomplete (>=1.9.4,<2)",
     "pandas (>=2,<3)",
     "jinja2 (>=3,<4)",
@@ -43,7 +43,7 @@ dependencies = [
     "nilearn (>=0.10.3,<1.0)",
     "colorlog (>=5,<6)",
     "xgboost",
-    "scipy (>=1.12,<2)",
+    "scipy (>=1.14,<2)",
     "matplotlib",
     "scikit-image",
     "pydicom",
@@ -63,8 +63,9 @@ dependencies = [
     "pydra-freesurfer (>=0.0.9)",
     "pydra-petpvc (>=0.0.4)",
     "pydra-fsl (>=0.0.22)",
-    "antspyx (>=0.4.2)",
+    "antspyx (>=0.5.4)",
     "rich (>=13.8.0)",
+    "brainstat (>=0.5.2)",
 ]
 
 [project.urls]
@@ -90,9 +91,6 @@ mkdocs = "^1.1"
 mkdocs-material = ">=7.1.8"
 pymdown-extensions = "*"
 
-[tool.poetry.group.optional.dependencies]
-brainstat = "^0.4.2"
-
 [project.scripts]
 clinica = "clinica.cmdline:main"
 

test/unittests/utils/test_image.py

@@ -153,24 +153,6 @@ def test_merge_nifti_images_in_time_dimension_3d_and_4d(
     assert_array_equal(out_img.get_fdata(), expected_data)
 
 
-def test_remove_dummy_dimension_from_image(tmp_path):
-    from clinica.utils.image import remove_dummy_dimension_from_image
-
-    input_data = np.random.randint(low=0, high=10, size=(16, 10, 6, 3))
-    input_image = nib.Nifti1Image(input_data.astype(np.int32), affine=np.eye(4))
-    nib.save(input_image, tmp_path / "input_image.nii.gz")
-
-    result = remove_dummy_dimension_from_image(
-        str(tmp_path / "input_image.nii.gz"),
-        str(tmp_path / "output_image.nii.gz"),
-    )
-    result_image = nib.load(result)
-
-    assert result == str(tmp_path / "output_image.nii.gz")
-    assert_array_equal(result_image.affine, np.eye(4))
-    assert_array_equal(result_image.get_fdata(), input_data)
-
-
 def test_slice_error():
     from clinica.utils.image import Slice  # noqa