STY: Run ruff at the source root

nitransforms/__init__.py

@@ -16,6 +16,7 @@
 
    transform
 """
+
 from . import linear, manip, nonlinear, surface
 from .linear import Affine, LinearTransformsMapping
 from .nonlinear import DenseFieldTransform

nitransforms/cli.py

@@ -32,8 +32,8 @@ def cli_apply(pargs):
 
     xfm = (
         nlinload(pargs.transform, fmt=fmt)
-        if pargs.nonlinear else
-        linload(pargs.transform, fmt=fmt)
+        if pargs.nonlinear
+        else linload(pargs.transform, fmt=fmt)
     )
 
     # ensure a reference is set

nitransforms/conftest.py

@@ -1,4 +1,5 @@
 """py.test configuration."""
+
 import os
 from pathlib import Path
 import numpy as np
@@ -64,7 +65,9 @@ def _reorient(path):
     newaff = imgaff.copy()
     newaff[0, 0] *= -1.0
     newaff[0, 3] = imgaff.dot(np.hstack((np.array(img.shape[:3]) - 1, 1.0)))[0]
-    _data["LAS"] = nb.Nifti1Image(np.flip(np.asanyarray(img.dataobj), 0), newaff, img.header)
+    _data["LAS"] = nb.Nifti1Image(
+        np.flip(np.asanyarray(img.dataobj), 0), newaff, img.header
+    )
     _data["LAS"].set_data_dtype(img.get_data_dtype())
     newaff = imgaff.copy()
     newaff[0, 0] *= -1.0

nitransforms/io/afni.py

@@ -1,4 +1,5 @@
 """Read/write AFNI's transforms."""
+
 from math import pi
 import numpy as np
 from nibabel.affines import (
@@ -132,15 +133,16 @@ def to_ras(self, moving=None, reference=None):
         """Return a nitransforms' internal RAS matrix."""
 
         pre_rotation = post_rotation = np.eye(4)
-        if reference is not None and _is_oblique(ref_aff := _ensure_image(reference).affine):
+        if reference is not None and _is_oblique(
+            ref_aff := _ensure_image(reference).affine
+        ):
             pre_rotation = _cardinal_rotation(ref_aff, True)
         if moving is not None and _is_oblique(mov_aff := _ensure_image(moving).affine):
             post_rotation = _cardinal_rotation(mov_aff, False)
 
-        return np.stack([
-            post_rotation @ (xfm.to_ras() @ pre_rotation)
-            for xfm in self.xforms
-        ])
+        return np.stack(
+            [post_rotation @ (xfm.to_ras() @ pre_rotation) for xfm in self.xforms]
+        )
 
     def to_string(self):
         """Convert to a string directly writeable to file."""
@@ -161,7 +163,9 @@ def from_ras(cls, ras, moving=None, reference=None):
 
         pre_rotation = post_rotation = np.eye(4)
 
-        if reference is not None and _is_oblique(ref_aff := _ensure_image(reference).affine):
+        if reference is not None and _is_oblique(
+            ref_aff := _ensure_image(reference).affine
+        ):
             pre_rotation = _cardinal_rotation(ref_aff, False)
         if moving is not None and _is_oblique(mov_aff := _ensure_image(moving).affine):
             post_rotation = _cardinal_rotation(mov_aff, True)
@@ -198,7 +202,7 @@ def from_image(cls, imgobj):
         hdr = imgobj.header.copy()
         shape = hdr.get_data_shape()
 
-        if len(shape) != 5 or shape[-2] != 1 or not shape[-1] in (2, 3):
+        if len(shape) != 5 or shape[-2] != 1 or shape[-1] not in (2, 3):
             raise TransformFileError(
                 'Displacements field "%s" does not come from AFNI.'
                 % imgobj.file_map["image"].filename

nitransforms/io/base.py

@@ -1,4 +1,5 @@
 """Read/write linear transforms."""
+
 from pathlib import Path
 import numpy as np
 from nibabel import load as loadimg

nitransforms/io/fsl.py

@@ -1,4 +1,5 @@
 """Read/write FSL's transforms."""
+
 import os
 import warnings
 import numpy as np
@@ -41,7 +42,9 @@ def from_ras(cls, ras, moving=None, reference=None):
             moving = reference
 
         if reference is None:
-            raise TransformIOError("Cannot build FSL linear transform without a reference")
+            raise TransformIOError(
+                "Cannot build FSL linear transform without a reference"
+            )
 
         reference = _ensure_image(reference)
         moving = _ensure_image(moving)
@@ -78,7 +81,9 @@ def from_string(cls, string):
     def to_ras(self, moving=None, reference=None):
         """Return a nitransforms internal RAS+ matrix."""
         if reference is None:
-            raise TransformIOError("Cannot build FSL linear transform without a reference")
+            raise TransformIOError(
+                "Cannot build FSL linear transform without a reference"
+            )
 
         if moving is None:
             warnings.warn(
@@ -180,10 +185,11 @@ def from_image(cls, imgobj):
         hdr = imgobj.header.copy()
         shape = hdr.get_data_shape()
 
-        if len(shape) != 4 or not shape[-1] in (2, 3):
+        if len(shape) != 4 or shape[-1] not in (2, 3):
             raise TransformFileError(
-                'Displacements field "%s" does not come from FSL.' %
-                imgobj.file_map['image'].filename)
+                'Displacements field "%s" does not come from FSL.'
+                % imgobj.file_map["image"].filename
+            )
 
         field = np.squeeze(np.asanyarray(imgobj.dataobj))
         field[..., 0] *= -1.0

nitransforms/io/itk.py

@@ -1,4 +1,5 @@
 """Read/write ITK transforms."""
+
 import warnings
 import numpy as np
 from scipy.io import loadmat as _read_mat, savemat as _save_mat
@@ -138,8 +139,7 @@ def from_matlab_dict(cls, mdict, index=0):
         sa = tf.structarr
 
         affine = mdict.get(
-            "AffineTransform_double_3_3",
-            mdict.get("AffineTransform_float_3_3")
+            "AffineTransform_double_3_3", mdict.get("AffineTransform_float_3_3")
         )
 
         if affine is None:
@@ -337,7 +337,7 @@ def from_image(cls, imgobj):
         hdr = imgobj.header.copy()
         shape = hdr.get_data_shape()
 
-        if len(shape) != 5 or shape[-2] != 1 or not shape[-1] in (2, 3):
+        if len(shape) != 5 or shape[-2] != 1 or shape[-1] not in (2, 3):
             raise TransformFileError(
                 'Displacements field "%s" does not come from ITK.'
                 % imgobj.file_map["image"].filename
@@ -412,7 +412,9 @@ def from_h5obj(cls, fileobj, check=True, only_linear=False):
                 # ITK uses Fortran ordering, like NIfTI, but with the vector dimension first
                 field = np.moveaxis(
                     np.reshape(
-                        xfm[f"{typo_fallback}Parameters"], (3, *shape.astype(int)), order='F'
+                        xfm[f"{typo_fallback}Parameters"],
+                        (3, *shape.astype(int)),
+                        order="F",
                     ),
                     0,
                     -1,
@@ -422,9 +424,7 @@ def from_h5obj(cls, fileobj, check=True, only_linear=False):
                 hdr.set_intent("vector")
                 hdr.set_data_dtype("float")
 
-                xfm_list.append(
-                    Nifti1Image(field.astype("float"), LPS @ affine, hdr)
-                )
+                xfm_list.append(Nifti1Image(field.astype("float"), LPS @ affine, hdr))
                 continue
 
             raise TransformIOError(