MAINT: Add ruff for linting

.codespellrc

@@ -0,0 +1,3 @@
+[codespell]
+skip = [setup.cfg] 
+ignore-words-list = Reson, DNE, ACI, FPT, sagital, saggital

.github/workflows/test.yml

@@ -36,7 +36,7 @@ jobs:
         python -m pip check
     - name: Lint
       run: |
-        flake8 --ignore N802,N806,W503 --select W504 `find . -name \*.py | grep -v setup.py | grep -v version.py | grep -v __init__.py | grep -v /docs/`
+        ruff check .
     - name: Test
       run: |
         cd && mkdir for_test && cd for_test && pytest --pyargs AFQ --cov-report term-missing --cov=AFQ -m "not nightly and not nightly_basic and not nightly_custom and not nightly_anisotropic and not nightly_slr and not nightly_reco and not nightly_reco80" --durations=0

.maintenance/update_zenodo.py

@@ -7,81 +7,80 @@
 https://github.com/nipreps/dmriprep/blob/master/LICENSE
 
 """
-import sys
+
+import json
 import shutil
+import subprocess as sp
+import sys
 from pathlib import Path
-import json
+
 from rapidfuzz import fuzz, process
-import subprocess as sp
 
 # These ORCIDs should go last
-CREATORS_LAST = ['Yeatman, Jason', 'Rokem, Ariel']
+CREATORS_LAST = ["Yeatman, Jason", "Rokem, Ariel"]
 # for entries not found in line-contributions
-MISSING_ENTRIES = [
-]
+MISSING_ENTRIES = []
 
-if __name__ == '__main__':
-    contrib_file = Path('line-contributors.txt')
+if __name__ == "__main__":
+    contrib_file = Path("line-contributors.txt")
     lines = []
     if contrib_file.exists():
-        print('WARNING: Reusing existing line-contributors.txt file.',
-              file=sys.stderr)
+        print("WARNING: Reusing existing line-contributors.txt file.", file=sys.stderr)
         lines = contrib_file.read_text().splitlines()
 
-    git_line_summary_path = shutil.which('git-summary')
+    git_line_summary_path = shutil.which("git-summary")
     if not lines and git_line_summary_path:
         print("Running git-line-summary on the repo")
         lines = sp.check_output([git_line_summary_path]).decode().splitlines()
-        contrib_file.write_text('\n'.join(lines))
+        contrib_file.write_text("\n".join(lines))
 
     if not lines:
         raise RuntimeError(
             """Could not find line-contributors from git repository.%s"""
             % """git-line-summary not found, please install git-extras. """
-            * (git_line_summary_path is None))
+            * (git_line_summary_path is None)
+        )
 
-    data = [' '.join(line.strip().split()[1:-1]) for line in lines if '%'
-            in line]
+    data = [" ".join(line.strip().split()[1:-1]) for line in lines if "%" in line]
 
     # load zenodo from master
-    zenodo_file = Path('.zenodo.json')
+    zenodo_file = Path(".zenodo.json")
     zenodo = json.loads(zenodo_file.read_text())
-    zen_names = [' '.join(val['name'].split(',')[::-1]).strip()
-                 for val in zenodo['creators']]
+    zen_names = [
+        " ".join(val["name"].split(",")[::-1]).strip() for val in zenodo["creators"]
+    ]
     total_names = len(zen_names) + len(MISSING_ENTRIES)
 
     name_matches = []
     position = 1
     for ele in data:
-        match = process.extractOne(ele, zen_names,
-                                   scorer=fuzz.token_sort_ratio,
-                                   score_cutoff=80)
+        match = process.extractOne(
+            ele, zen_names, scorer=fuzz.token_sort_ratio, score_cutoff=80
+        )
 
         if match:
-            val = zenodo['creators'][zen_names.index(match[0])]
+            val = zenodo["creators"][zen_names.index(match[0])]
         else:
             # skip unmatched names
             print("No entry to sort:", ele)
             continue
 
         if val not in name_matches:
-            if val['name'] not in CREATORS_LAST:
-                val['position'] = position
+            if val["name"] not in CREATORS_LAST:
+                val["position"] = position
                 position += 1
             else:
-                val['position'] = total_names + \
-                    CREATORS_LAST.index(val['name'])
+                val["position"] = total_names + CREATORS_LAST.index(val["name"])
             name_matches.append(val)
 
     for missing in MISSING_ENTRIES:
-        missing['position'] = position
+        missing["position"] = position
         position += 1
         name_matches.append(missing)
 
-    zenodo['creators'] = sorted(name_matches, key=lambda k: k['position'])
+    zenodo["creators"] = sorted(name_matches, key=lambda k: k["position"])
     # Remove position
-    for creator in zenodo['creators']:
-        del creator['position']
+    for creator in zenodo["creators"]:
+        del creator["position"]
 
-    zenodo_file.write_text('%s\n' % json.dumps(zenodo, indent=2,
-                           sort_keys=True))
+    zenodo_file.write_text("%s\n" % json.dumps(zenodo, indent=2, sort_keys=True))

.pre-commit-config.yaml

@@ -0,0 +1,18 @@
+default_language_version:
+  python: python3
+
+repos:
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: v0.14.10
+    hooks:
+      # Run the linter
+      - id: ruff
+        args: [ --fix, --config, pyproject.toml ]
+      # Run the formatter
+      - id: ruff-format
+  - repo: https://github.com/codespell-project/codespell
+    rev: v2.3.0
+    hooks:
+      - id: codespell
+        additional_dependencies:
+          - tomli

AFQ/_fixes.py

@@ -1,31 +1,25 @@
-import numpy as np
 import logging
-
-from scipy.special import lpmv, gammaln
-from scipy.linalg import pinvh
-
-from tqdm import tqdm
-
 import math
 
-from dipy.reconst.gqi import squared_radial_component
+import numpy as np
 from dipy.data import default_sphere
+from dipy.reconst.gqi import squared_radial_component
 from dipy.tracking.streamline import set_number_of_points
-from scipy.linalg import blas
-
+from scipy.linalg import blas, pinvh
+from scipy.special import gammaln, lpmv
+from tqdm import tqdm
 
-logger = logging.getLogger('AFQ')
+logger = logging.getLogger("AFQ")
 
 
 def gwi_odf(gqmodel, data):
     gqi_vector = np.real(
-        squared_radial_component(np.dot(
-            gqmodel.b_vector, default_sphere.vertices.T)
-            * gqmodel.Lambda))
+        squared_radial_component(
+            np.dot(gqmodel.b_vector, default_sphere.vertices.T) * gqmodel.Lambda
+        )
+    )
     odf = blas.dgemm(
-        alpha=1.,
-        a=data.reshape(-1, gqi_vector.shape[0]),
-        b=gqi_vector
+        alpha=1.0, a=data.reshape(-1, gqi_vector.shape[0]), b=gqi_vector
     ).reshape((*data.shape[:-1], gqi_vector.shape[1]))
     return odf
 
@@ -44,7 +38,7 @@ def spherical_harmonics(m, n, theta, phi):
 
 
 def in_place_norm(vec, axis=-1, keepdims=False, delvec=True):
-    """ Return Vectors with Euclidean (L2) norm
+    """Return Vectors with Euclidean (L2) norm
 
     See :term:`unit vector` and :term:`Euclidean norm`
 
@@ -131,9 +125,7 @@ def tensor_odf(evals, evecs, sphere, num_batches=100):
     batch_size = math.ceil(num_vertices / num_batches)
     batches = range(num_batches)
 
-    mask = np.where((evals[..., 0] > 0)
-                    & (evals[..., 1] > 0)
-                    & (evals[..., 2] > 0))
+    mask = np.where((evals[..., 0] > 0) & (evals[..., 1] > 0) & (evals[..., 2] > 0))
     evecs = evecs[mask]
 
     proj_norm = np.zeros((num_vertices, evecs.shape[0]))
@@ -157,8 +149,7 @@ def tensor_odf(evals, evecs, sphere, num_batches=100):
     return odf
 
 
-def gaussian_weights(bundle, n_points=100, return_mahalnobis=False,
-                     stat=np.mean):
+def gaussian_weights(bundle, n_points=100, return_mahalnobis=False, stat=np.mean):
     """
     Calculate weights for each streamline/node in a bundle, based on a
     Mahalanobis distance from the core the bundle, at that node (mean, per
@@ -203,9 +194,12 @@ def gaussian_weights(bundle, n_points=100, return_mahalnobis=False,
 
     if n_sls < 15:  # Cov^-1 unstable under this amount
         weights = np.ones((n_sls, n_nodes))
-        logger.warning((
-            "Not enough streamlines for weight calculation, "
-            "weighting everything evenly"))
+        logger.warning(
+            (
+                "Not enough streamlines for weight calculation, "
+                "weighting everything evenly"
+            )
+        )
         if return_mahalnobis:
             return np.full((n_sls, n_nodes), np.nan)
         else:
@@ -225,11 +219,9 @@ def gaussian_weights(bundle, n_points=100, return_mahalnobis=False,
 
         # calculate Mahalanobis for node in every fiber
         if np.any(cov > 0):
-            weights[:, i] = np.sqrt(np.einsum(
-                'ij,jk,ik->i',
-                diff[:, i, :],
-                pinvh(cov),
-                diff[:, i, :]))
+            weights[:, i] = np.sqrt(
+                np.einsum("ij,jk,ik->i", diff[:, i, :], pinvh(cov), diff[:, i, :])
+            )
 
         # In the special case where all the streamlines have the exact same
         # coordinate in this node, the covariance matrix is all zeros, so