Merge remote-tracking branch 'upstream/master'

Author: Raniga, Parnesh (H&B, Herston - RBWH)

nibabel/benchmarks/bench_streamlines.py

@@ -91,5 +91,6 @@ def bench_load_trk():
         for s1, s2 in zip(scalars_new, scalars_old):
             assert_array_equal(s1, s2)
 
+
 if __name__ == '__main__':
     bench_load_trk()

nibabel/casting.py

@@ -165,6 +165,7 @@ def shared_range(flt_type, int_type):
     _SHARED_RANGES[key] = (mn, mx)
     return mn, mx
 
+
 # ----------------------------------------------------------------------------
 # Routines to work out the next lowest representable integer in floating point
 # types.

nibabel/imageclasses.py

@@ -40,6 +40,7 @@ class ClassMapDict(dict):
     def __getitem__(self, *args, **kwargs):
         return super(ClassMapDict, self).__getitem__(*args, **kwargs)
 
+
 class_map = ClassMapDict(
     analyze={'class': AnalyzeImage,  # Image class
              'ext': '.img',  # characteristic image extension
@@ -95,6 +96,7 @@ class ExtMapRecoder(Recoder):
     def __getitem__(self, *args, **kwargs):
         return super(ExtMapRecoder, self).__getitem__(*args, **kwargs)
 
+
 # mapping of extensions to default image class names
 ext_map = ExtMapRecoder((
     ('nifti_single', '.nii'),

nibabel/orientations.py

@@ -63,7 +63,7 @@ def io_orientation(affine, tol=None):
     RS = RZS / zooms
     # Transform below is polar decomposition, returning the closest
     # shearless matrix R to RS
-    P, S, Qs = npl.svd(RS)
+    P, S, Qs = npl.svd(RS, full_matrices=False)
     # Threshold the singular values to determine the rank.
     if tol is None:
         tol = S.max() * max(RS.shape) * np.finfo(S.dtype).eps

nibabel/spm2analyze.py

@@ -130,5 +130,6 @@ class Spm2AnalyzeImage(spm99.Spm99AnalyzeImage):
     """
     header_class = Spm2AnalyzeHeader
 
+
 load = Spm2AnalyzeImage.load
 save = Spm2AnalyzeImage.instance_to_filename