chore: Drop Python 3.9 support

.github/workflows/tox.yml

@@ -94,17 +94,17 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ["3.9", "3.10", "3.11", "3.12", "3.13"]
+        python-version: ["3.10", "3.11", "3.12", "3.13"]
         dependencies: [latest, pre]
         include:
-          - python-version: "3.9"
+          - python-version: "3.10"
             dependencies: min
         exclude:
           # Do not test pre-releases for versions out of SPEC0
-          - python-version: "3.9"
-            dependencies: pre
           - python-version: "3.10"
             dependencies: pre
+          - python-version: "3.11"
+            dependencies: pre
 
     env:
       DEPENDS: ${{ matrix.dependencies }}

niworkflows/func/tests/test_util.py

@@ -74,7 +74,7 @@
 
     bold_datasets = [[str((datapath / p).absolute()) for p in ds] for ds in bold_datasets]
 
-    parameters = zip(bold_datasets, exp_masks)
+    parameters = zip(bold_datasets, exp_masks, strict=False)
 
     if not bold_datasets:
         raise RuntimeError(

niworkflows/interfaces/bids.py

@@ -25,7 +25,6 @@
 import os
 import re
 import shutil
-import sys
 from collections import defaultdict
 from contextlib import suppress
 from json import dumps, loads
@@ -66,15 +65,6 @@
 LOGGER = logging.getLogger('nipype.interface')
 
 
-if sys.version_info < (3, 10):  # PY39
-    builtin_zip = zip
-
-    def zip(*args, strict=False):  # noqa: A001
-        if strict and any(len(args[0]) != len(arg) for arg in args):
-            raise ValueError('strict_zip() requires all arguments to have the same length')
-        return builtin_zip(*args)
-
-
 def _none():
     return None
 
@@ -629,7 +619,7 @@ def _run_interface(self, runtime):
         self._results['out_path'] = dest_files
         self._results['out_meta'] = metadata
 
-        for i, (orig_file, dest_file) in enumerate(zip(in_file, dest_files)):
+        for i, (orig_file, dest_file) in enumerate(zip(in_file, dest_files, strict=False)):
             # Set data and header iff changes need to be made. If these are
             # still None when it's time to write, just copy.
             new_data, new_header = None, None
@@ -1132,7 +1122,7 @@ def _run_interface(self, runtime):
                 f'by interpolated patterns ({len(dest_files)}).'
             )
 
-        for i, (orig_file, dest_file) in enumerate(zip(in_file, dest_files)):
+        for i, (orig_file, dest_file) in enumerate(zip(in_file, dest_files, strict=False)):
             out_file = out_path / dest_file
             out_file.parent.mkdir(exist_ok=True, parents=True)
             self._results['out_file'].append(str(out_file))

niworkflows/interfaces/confounds.py

@@ -303,7 +303,7 @@ def spike_regressors(
         post_final = data.shape[0] + 1
         epoch_length = np.diff(sorted(mask | {-1, post_final})) - 1
         epoch_end = sorted(mask | {post_final})
-        for end, length in zip(epoch_end, epoch_length):
+        for end, length in zip(epoch_end, epoch_length, strict=False):
             if length < minimum_contiguous:
                 mask = mask | set(range(end - length, end))
         mask = mask.intersection(indices)

niworkflows/interfaces/images.py

@@ -284,7 +284,9 @@ def _run_interface(self, runtime):
         self._results['out_file'] = fname(suffix='_average')
         self._results['out_volumes'] = fname(suffix='_sliced')
 
-        sliced = nb.concat_images(i for i, t in zip(nb.four_to_three(img), t_mask) if t)
+        sliced = nb.concat_images(
+            i for i, t in zip(nb.four_to_three(img), t_mask, strict=False) if t
+        )
 
         data = sliced.get_fdata(dtype='float32')
         # Data can come with outliers showing very high numbers - preemptively prune

niworkflows/interfaces/itk.py

@@ -141,7 +141,7 @@ def _run_interface(self, runtime):
         if num_threads == 1:
             out_files = [
                 _applytfms((in_file, in_xfm, ifargs, i, runtime.cwd))
-                for i, (in_file, in_xfm) in enumerate(zip(in_files, xfms_list))
+                for i, (in_file, in_xfm) in enumerate(zip(in_files, xfms_list, strict=False))
             ]
         else:
             from concurrent.futures import ThreadPoolExecutor
@@ -152,7 +152,9 @@ def _run_interface(self, runtime):
                         _applytfms,
                         [
                             (in_file, in_xfm, ifargs, i, runtime.cwd)
-                            for i, (in_file, in_xfm) in enumerate(zip(in_files, xfms_list))
+                            for i, (in_file, in_xfm) in enumerate(
+                                zip(in_files, xfms_list, strict=False)
+                            )
                         ],
                     )
                 )
@@ -264,4 +266,4 @@ def _arrange_xfms(transforms, num_files, tmp_folder):
         xfms_T.append(split_xfms)
 
     # Transpose back (only Python 3)
-    return list(map(list, zip(*xfms_T)))
+    return list(map(list, zip(*xfms_T, strict=False)))

niworkflows/interfaces/surf.py

@@ -743,6 +743,7 @@ def ply2gii(in_file, metadata, out_file=None):
         zip(
             ('SurfaceCenterX', 'SurfaceCenterY', 'SurfaceCenterZ'),
             [f'{c:.4f}' for c in surf.centroid],
+            strict=False,
         )
     )
 

niworkflows/interfaces/tests/test_bids.py

@@ -361,10 +361,10 @@ def test_DerivativesDataSink_build_path(
             ]
 
     base = (out_path_base or 'niworkflows') if interface == bintfs.DerivativesDataSink else ''
-    for out, exp in zip(output, expectation):
+    for out, exp in zip(output, expectation, strict=False):
         assert Path(out).relative_to(base_directory) == Path(base) / exp
 
-    for out, exp in zip(output, expectation):
+    for out, exp in zip(output, expectation, strict=False):
         assert Path(out).relative_to(base_directory) == Path(base) / exp
         # Regression - some images were given nan scale factors
         if out.endswith(('.nii', '.nii.gz')):
@@ -374,7 +374,7 @@ def test_DerivativesDataSink_build_path(
                     hdr = img.header.from_fileobj(fobj)
                 assert not np.isnan(hdr['scl_slope'])
                 assert not np.isnan(hdr['scl_inter'])
-    for out, chksum in zip(output, checksum):
+    for out, chksum in zip(output, checksum, strict=False):
         if chksum == '335f1394ce90b58bbf27026b6eeec4d2124c11da':
             if Version(nb.__version__) < Version('5.3'):
                 # Nibabel 5.3 avoids unnecessary roundtrips for Cifti2Headers

niworkflows/interfaces/tests/test_images.py

@@ -195,7 +195,7 @@ def test_TemplateDimensions(tmp_path):
         (0.9, 0.9, 0.9),
     ]
 
-    for i, (shape, zoom) in enumerate(zip(shapes, zooms)):
+    for i, (shape, zoom) in enumerate(zip(shapes, zooms, strict=False)):
         img = nb.Nifti1Image(np.ones(shape, dtype='float32'), np.eye(4))
         img.header.set_zooms(zoom)
         img.to_filename(tmp_path / f'test{i}.nii')

niworkflows/interfaces/utility.py

@@ -371,7 +371,7 @@ def _run_interface(self, runtime):
             raise ValueError('Number of columns in datasets do not match')
 
         merged = []
-        for d, j in zip(data, join):
+        for d, j in zip(data, join, strict=False):
             line = '%s\t%s' % ((j, d) if self.inputs.side == 'left' else (d, j))
             merged.append(line)
 

niworkflows/reports/core.py

@@ -534,7 +534,9 @@ def generate_reports(
 
         logger = logging.getLogger('cli')
         error_list = ', '.join(
-            f'{subid} ({err})' for subid, err in zip(subject_list, report_errors) if err
+            f'{subid} ({err})'
+            for subid, err in zip(subject_list, report_errors, strict=False)
+            if err
         )
         logger.error(
             'Preprocessing did not finish successfully. Errors occurred while processing '

niworkflows/tests/test_viz.py

@@ -72,7 +72,7 @@ def test_carpetplot(tr, sorting):
     rng.shuffle(indexes)
     segments = {}
     start = 0
-    for group, size in zip(labels, sizes):
+    for group, size in zip(labels, sizes, strict=False):
         segments[group] = indexes[start : start + size]
         data[indexes[start : start + size]] = rng.normal(
             rng.standard_normal(1) * 100, rng.normal(20, 5, size=1), size=(size, 300)
@@ -100,7 +100,7 @@ def test_carpetplot(tr, sorting):
     rng.shuffle(indexes)
     segments = {}
     start = 0
-    for i, (group, size) in enumerate(zip(labels, sizes)):
+    for i, (group, size) in enumerate(zip(labels, sizes, strict=False)):
         segments[group] = indexes[start : start + size]
         data[indexes[start : start + size]] = i
         start += size

niworkflows/utils/spaces.py

@@ -805,4 +805,4 @@ def _expand_entities(entities):
     """
     keys = list(entities.keys())
     values = list(product(*[entities[k] for k in keys]))
-    return [dict(zip(keys, combs)) for combs in values]
+    return [dict(zip(keys, combs, strict=False)) for combs in values]

niworkflows/utils/tests/test_spaces.py

@@ -95,7 +95,7 @@ def test_space_action(parser, spaces, expected):
         'Every element must be a `Reference`'
     )
     assert len(parsed_spaces.references) == len(expected)
-    for ref, expected_ref in zip(parsed_spaces.references, expected):
+    for ref, expected_ref in zip(parsed_spaces.references, expected, strict=False):
         assert str(ref) == expected_ref
 
 

niworkflows/viz/plots.py

@@ -758,7 +758,7 @@ def compcor_variance_plot(
             metadata_sources = ['CompCor']
         else:
             metadata_sources = [f'Decomposition {i:d}' for i in range(len(metadata_files))]
-    for file, source in zip(metadata_files, metadata_sources):
+    for file, source in zip(metadata_files, metadata_sources, strict=False):
         metadata[source] = pd.read_csv(str(file), sep=r'\s+')
         metadata[source]['source'] = source
     metadata = pd.concat(list(metadata.values()))

niworkflows/viz/utils.py

@@ -185,7 +185,7 @@ def cuts_from_bbox(mask_nii, cuts=3):
 
     vox_coords = np.zeros((4, cuts), dtype=np.float32)
     vox_coords[-1, :] = 1.0
-    for ax, (c, th) in enumerate(zip(ijk_counts, ijk_th)):
+    for ax, (c, th) in enumerate(zip(ijk_counts, ijk_th, strict=False)):
         # Start with full plane if mask is seemingly empty
         smin, smax = (0, mask_data.shape[ax] - 1)
 
@@ -198,7 +198,7 @@ def cuts_from_bbox(mask_nii, cuts=3):
         vox_coords[ax, :] = np.linspace(smin, smax, num=cuts + 2)[1:-1]
 
     ras_coords = mask_nii.affine.dot(vox_coords)[:3, ...]
-    return {k: list(v) for k, v in zip(['x', 'y', 'z'], np.around(ras_coords, 3))}
+    return {k: list(v) for k, v in zip(['x', 'y', 'z'], np.around(ras_coords, 3), strict=False)}
 
 
 def _3d_in_file(in_file):

pyproject.toml

@@ -9,38 +9,37 @@ description = "NeuroImaging Workflows provides processing tools for magnetic res
 readme = "README.rst"
 license = "Apache-2.0"
 license-files = ["LICENSE"]
-requires-python = ">= 3.9"
+requires-python = ">= 3.10"
 authors = [
     { name = "The NiPreps Developers", email = "[email protected]" },
 ]
 classifiers = [
     "Development Status :: 4 - Beta",
     "Intended Audience :: Science/Research",
-    "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
     "Programming Language :: Python :: 3.13",
     "Topic :: Scientific/Engineering :: Image Recognition",
 ]
 dependencies = [
-    "acres",
-    "attrs >=20.1",
+    "acres >=0.5",
+    "attrs >=23.1",
     "jinja2 >=3",
-    "looseversion",
-    "matplotlib >= 3.5",
-    "nibabel >= 3.0",
-    "nilearn >= 0.8",
-    "nipype >= 1.8.5",
-    "nitransforms >= 22.0.0",
-    "numpy >= 1.20",
+    "looseversion >=1.3",
+    "matplotlib >= 3.7",
+    "nibabel >= 5.0",
+    "nilearn >= 0.10",
+    "nipype >= 1.9.1",
+    "nitransforms >= 23.0.0",
+    "numpy >= 1.24",
     "packaging",
-    "pandas >= 1.2",
-    "pybids >= 0.15.1",
-    "PyYAML >= 5.4",
-    "scikit-image >= 0.18",
-    "scipy >= 1.8",
-    "seaborn >= 0.11",
+    "pandas >= 2.0",
+    "pybids >= 0.16",
+    "pyyaml >= 6.0",
+    "scikit-image >= 0.20",
+    "scipy >= 1.10",
+    "seaborn >= 0.13",
     "svgutils >= 0.3.4",
     "templateflow >= 23.1",
     "transforms3d >= 0.4",
@@ -62,11 +61,11 @@ style = [
     "flake8 >= 3.7.0",
 ]
 tests = [
-    "coverage[toml] >=5.2.1",
-    "pytest >= 6",
-    "pytest-cov >= 2.11",
+    "coverage[toml] >=7",
+    "pytest >= 8",
+    "pytest-cov >= 7",
     "pytest-env",
-    "pytest-xdist >= 2.5",
+    "pytest-xdist >= 3.8",
     "pytest-xvfb >= 2",
 ]
 # Aliases
@@ -226,3 +225,45 @@ source = [
 [tool.codespell]
 skip = "*/data/*,*/docs/_build/*,./examples/viz-report.*"
 ignore-words-list = "objekt,nd"
+
+[tool.pixi.workspace]
+channels = ["https://fsl.fmrib.ox.ac.uk/fsldownloads/fslconda/public", "conda-forge"]
+platforms = ["linux-64"]
+
+[tool.pixi.feature.niworkflows.activation.env]
+FSLDIR = "$CONDA_PREFIX"
+
+[tool.pixi.pypi-dependencies]
+niworkflows = { path = ".", editable = true }
+
+[tool.pixi.environments]
+default = { features = ["editable"], solve-group = "default" }
+test = { features = ["editable", "tests"], solve-group = "default" }
+niworkflows = { features = ["production"], solve-group = "production" }
+
+[tool.pixi.feature.editable.pypi-dependencies]
+niworkflows = { path = ".", editable = true }
+[tool.pixi.feature.production.pypi-dependencies]
+niworkflows = { path = ".", editable = false }
+
+[tool.pixi.tasks]
+
+[tool.pixi.dependencies]
+python = "3.12.*"
+mkl = "2024.2.2.*"
+mkl-service = "2.4.2.*"
+numpy = "1.26.*"
+scipy = "1.15.*"
+matplotlib = "3.9.*"
+pandas = "2.2.*"
+h5py = "3.13.*"
+scikit-image = "0.25.*"
+scikit-learn = "1.6.*"
+graphviz = "11.0.*"
+ants = "2.5.*"
+libitk = "5.4.0.*"
+fsl-bet2 = "2111.8.*"
+fsl-flirt = "2111.2.*"
+fsl-fast4 = "2111.3.*"
+fsl-mcflirt = "2111.0.*"
+fsl-miscmaths = "2203.2.*"

tox.ini

@@ -2,19 +2,18 @@
 requires =
   tox>=4
 envlist =
-  py3{9,10,11,12,13}-latest
-  py39-min
-  py3{10,11,12,13}-pre
+  py3{10,11,12,13,14}-{latest,pre}
+  py310-min
 skip_missing_interpreters = true
 
 # Configuration that allows us to split tests across GitHub runners effectively
 [gh-actions]
 python =
-  3.9: py39
   3.10: py310
   3.11: py311
   3.12: py312
   3.13: py313
+  3.14: py314
 
 [gh-actions:env]
 DEPENDS =
@@ -54,8 +53,6 @@ pass_env =
   CLICOLOR
   CLICOLOR_FORCE
   PYTHON_GIL
-deps =
-  py313: traits @ git+https://github.com/enthought/traits.git@10954eb
 extras = tests
 setenv =
   pre: PIP_EXTRA_INDEX_URL=https://pypi.anaconda.org/scientific-python-nightly-wheels/simple