ENH: Use obliquity directly from nibabel

nitransforms/linear.py

@@ -13,9 +13,9 @@
 from pathlib import Path
 
 from nibabel.loadsave import load as loadimg
-from nibabel.affines import from_matvec, voxel_sizes
+from nibabel.affines import from_matvec, voxel_sizes, obliquity
 from .base import TransformBase
-from .patched import obliquity, shape_zoom_affine
+from .patched import shape_zoom_affine
 
 
 LPS = np.diag([-1, -1, 1, 1])

nitransforms/patched.py

@@ -1,29 +1,4 @@
 import numpy as np
-from nibabel.affines import voxel_sizes
-
-
-def obliquity(affine):
-    r"""
-    Estimate the *obliquity* an affine's axes represent.
-    The term *obliquity* is defined here as the rotation of those axes with
-    respect to the cardinal axes.
-    This implementation is inspired by `AFNI's implementation
-    <https://github.com/afni/afni/blob/b6a9f7a21c1f3231ff09efbd861f8975ad48e525/src/thd_coords.c#L660-L698>`_.
-    For further details about *obliquity*, check `AFNI's documentation
-    <https://sscc.nimh.nih.gov/sscc/dglen/Obliquity>_.
-    Parameters
-    ----------
-    affine : 2D array-like
-        Affine transformation array.  Usually shape (4, 4), but can be any 2D
-        array.
-    Returns
-    -------
-    angles : 1D array-like
-        The *obliquity* of each axis with respect to the cardinal axes, in radians.
-    """
-    vs = voxel_sizes(affine)
-    best_cosines = np.abs((affine[:-1, :-1] / vs).max(axis=1))
-    return np.arccos(best_cosines)
 
 
 def shape_zoom_affine(shape, zooms, x_flip=True, y_flip=False):

setup.cfg

@@ -7,7 +7,7 @@ python_requires = >= 3.5
 install_requires =
     numpy
     scipy
-    nibabel
+    nibabel @ git+https://github.com/nipy/nibabel@cd48bf05bc567387afe4504eda1da15324bb616f
     h5py
 test_requires =
     pytest