Merge pull request #147 from jhlegarreta/FormatCodebase

STYLE: Format the code base style

.github/workflows/contrib.yml

@@ -21,3 +21,5 @@ jobs:
           python-version: 3
       - name: Lint EddyMotion
         run: pipx run ruff check --diff
+      - name: Format EddyMotion
+        run: pipx run ruff format --diff

.maint/paper_author_list.py

@@ -1,5 +1,6 @@
 #!/usr/bin/env python3
 """Generate an author list for a new paper or abstract."""
+
 import json
 import sys
 from pathlib import Path
@@ -63,7 +64,5 @@ def _aslist(inlist):
 
     print(
         "\n\nAffiliations:\n%s"
-        % "\n".join(
-            ["{0: >2}. {1}".format(i + 1, a) for i, a in enumerate(affiliations)]
-        )
+        % "\n".join(["{0: >2}. {1}".format(i + 1, a) for i, a in enumerate(affiliations)])
     )

.maint/update_zenodo.py

@@ -1,5 +1,6 @@
 #!/usr/bin/env python3
 """Update and sort the creators list of the zenodo record."""
+
 import json
 import sys
 from pathlib import Path
@@ -16,20 +17,14 @@ def sort_contributors(entries, git_lines, exclude=None, last=None):
     last = last or []
     sorted_authors = sorted(entries, key=lambda i: i["name"])
 
-    first_last = [
-        " ".join(val["name"].split(",")[::-1]).strip() for val in sorted_authors
-    ]
-    first_last_excl = [
-        " ".join(val["name"].split(",")[::-1]).strip() for val in exclude or []
-    ]
+    first_last = [" ".join(val["name"].split(",")[::-1]).strip() for val in sorted_authors]
+    first_last_excl = [" ".join(val["name"].split(",")[::-1]).strip() for val in exclude or []]
 
     unmatched = []
     author_matches = []
     position = 1
     for ele in git_lines:
-        matches = process.extract(
-            ele, first_last, scorer=fuzz.token_sort_ratio, limit=2
-        )
+        matches = process.extract(ele, first_last, scorer=fuzz.token_sort_ratio, limit=2)
         # matches is a list [('First match', % Match), ('Second match', % Match)]
         if matches[0][1] > 80:
             val = sorted_authors[first_last.index(matches[0][0])]

src/eddymotion/__init__.py

@@ -21,6 +21,7 @@
 #     https://www.nipreps.org/community/licensing/
 #
 """Top-level package for eddymotion."""
+
 from eddymotion._version import __version__
 
 __packagename__ = "eddymotion"

src/eddymotion/data/dmri.py

@@ -21,6 +21,7 @@
 #     https://www.nipreps.org/community/licensing/
 #
 """Representing data in hard-disk and memory."""
+
 from collections import namedtuple
 from pathlib import Path
 from tempfile import mkdtemp
@@ -255,7 +256,7 @@ def load(
             warn(
                 "Gradients table file and b-vec/val files are defined; "
                 "dismissing b-vec/val files.",
-                stacklevel=2
+                stacklevel=2,
             )
     elif bvec_file and bval_file:
         grad = np.vstack(

src/eddymotion/data/pet.py

@@ -21,6 +21,7 @@
 #     https://www.nipreps.org/community/licensing/
 #
 """PET data representation."""
+
 from collections import namedtuple
 from pathlib import Path
 from tempfile import mkdtemp

src/eddymotion/estimator.py

@@ -21,6 +21,7 @@
 #     https://www.nipreps.org/community/licensing/
 #
 """A model-based algorithm for the realignment of dMRI data."""
+
 from collections import namedtuple
 from pathlib import Path
 from tempfile import TemporaryDirectory, mkstemp

src/eddymotion/model/__init__.py

@@ -21,6 +21,7 @@
 #     https://www.nipreps.org/community/licensing/
 #
 """Data models."""
+
 from eddymotion.model.base import (
     AverageDWModel,
     DKIModel,

src/eddymotion/model/base.py

@@ -21,6 +21,7 @@
 #     https://www.nipreps.org/community/licensing/
 #
 """A factory class that adapts DIPY's dMRI models."""
+
 import warnings
 
 import numpy as np

src/eddymotion/viz.py

@@ -21,6 +21,7 @@
 #     https://www.nipreps.org/community/licensing/
 #
 """Visualization utilities."""
+
 import nibabel as nb
 import numpy as np
 from nireports.reportlets.nuisance import plot_carpet as nw_plot_carpet

test/conftest.py

@@ -21,6 +21,7 @@
 #     https://www.nipreps.org/community/licensing/
 #
 """py.test configuration."""
+
 import os
 from pathlib import Path
 

test/test_estimator.py

@@ -21,6 +21,7 @@
 #     https://www.nipreps.org/community/licensing/
 #
 """Unit tests exercising the estimator."""
+
 import nibabel as nb
 import nitransforms as nt
 import numpy as np
@@ -69,9 +70,7 @@ def test_ANTs_config_b0(datadir, tmp_path, r_x, r_y, r_z, t_x, t_y, t_z):
 
     result = registration.run(cwd=str(tmp_path)).outputs
     xform = nt.linear.Affine(
-        nt.io.itk.ITKLinearTransform.from_filename(
-            result.forward_transforms[0]
-        ).to_ras(),
+        nt.io.itk.ITKLinearTransform.from_filename(result.forward_transforms[0]).to_ras(),
         reference=b0nii,
     )
 

test/test_integration.py

@@ -39,27 +39,13 @@ def test_proximity_estimator_trivial_model(datadir, tmp_path):
     # Generate a list of large-yet-plausible bulk-head motion.
     xfms = nt.linear.LinearTransformsMapping(
         [
-            nb.affines.from_matvec(
-                nb.eulerangles.euler2mat(x=0.03, z=0.005), (0.8, 0.2, 0.2)
-            ),
-            nb.affines.from_matvec(
-                nb.eulerangles.euler2mat(x=0.02, z=0.005), (0.8, 0.2, 0.2)
-            ),
-            nb.affines.from_matvec(
-                nb.eulerangles.euler2mat(x=0.02, z=0.02), (0.4, 0.2, 0.2)
-            ),
-            nb.affines.from_matvec(
-                nb.eulerangles.euler2mat(x=-0.02, z=0.02), (0.4, 0.2, 0.2)
-            ),
-            nb.affines.from_matvec(
-                nb.eulerangles.euler2mat(x=-0.02, z=0.002), (0.0, 0.2, 0.2)
-            ),
-            nb.affines.from_matvec(
-                nb.eulerangles.euler2mat(y=-0.02, z=0.002), (0.0, 0.2, 0.2)
-            ),
-            nb.affines.from_matvec(
-                nb.eulerangles.euler2mat(y=-0.01, z=0.002), (0.0, 0.4, 0.2)
-            ),
+            nb.affines.from_matvec(nb.eulerangles.euler2mat(x=0.03, z=0.005), (0.8, 0.2, 0.2)),
+            nb.affines.from_matvec(nb.eulerangles.euler2mat(x=0.02, z=0.005), (0.8, 0.2, 0.2)),
+            nb.affines.from_matvec(nb.eulerangles.euler2mat(x=0.02, z=0.02), (0.4, 0.2, 0.2)),
+            nb.affines.from_matvec(nb.eulerangles.euler2mat(x=-0.02, z=0.02), (0.4, 0.2, 0.2)),
+            nb.affines.from_matvec(nb.eulerangles.euler2mat(x=-0.02, z=0.002), (0.0, 0.2, 0.2)),
+            nb.affines.from_matvec(nb.eulerangles.euler2mat(y=-0.02, z=0.002), (0.0, 0.2, 0.2)),
+            nb.affines.from_matvec(nb.eulerangles.euler2mat(y=-0.01, z=0.002), (0.0, 0.4, 0.2)),
         ],
         reference=b0nii,
     )
@@ -81,9 +67,7 @@ def test_proximity_estimator_trivial_model(datadir, tmp_path):
     )
 
     estimator = EddyMotionEstimator()
-    em_affines = estimator.fit(
-        dwdata=dwi_motion, models=("b0",), align_kwargs=None, seed=None
-    )
+    em_affines = estimator.fit(dwdata=dwi_motion, models=("b0",), align_kwargs=None, seed=None)
 
     # Uncomment to see the realigned dataset
     # nt.linear.LinearTransformsMapping(

test/test_model.py

@@ -21,6 +21,7 @@
 #     https://www.nipreps.org/community/licensing/
 #
 """Unit tests exercising models."""
+
 import numpy as np
 import pytest
 
@@ -64,11 +65,13 @@ def test_average_model():
 
     tmodel_mean = model.AverageDWModel(gtab=gtab, bias=False, stat="mean")
     tmodel_median = model.AverageDWModel(gtab=gtab, bias=False, stat="median")
-    tmodel_1000 = model.AverageDWModel(
-        gtab=gtab, bias=False, th_high=1000, th_low=900
-    )
+    tmodel_1000 = model.AverageDWModel(gtab=gtab, bias=False, th_high=1000, th_low=900)
     tmodel_2000 = model.AverageDWModel(
-        gtab=gtab, bias=False, th_high=2000, th_low=900, stat="mean",
+        gtab=gtab,
+        bias=False,
+        th_high=2000,
+        th_low=900,
+        stat="mean",
     )
 
     # Verify that fit function returns nothing

test/test_version.py

@@ -21,6 +21,7 @@
 #     https://www.nipreps.org/community/licensing/
 #
 """Test _version.py."""
+
 import sys
 from importlib import reload