enh: apply some early comments from @effigies.

.gitignore

@@ -84,4 +84,3 @@ Thumbs.db
 doc/source/reference
 venv/
 .buildbot.patch
-nibabel/maths/bspline.c

nibabel/transform/__init__.py

@@ -6,7 +6,8 @@
 #   copyright and license terms.
 #
 ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
-"""Geometric transforms
+"""
+Geometric transforms.
 
 .. currentmodule:: nibabel.transform
 
@@ -15,7 +16,6 @@
 
    transform
 """
-from __future__ import absolute_import
 from .linear import Affine
 from .nonlinear import DeformationFieldTransform
 

nibabel/transform/base.py

@@ -6,16 +6,16 @@
 #   copyright and license terms.
 #
 ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
-''' Common interface for transforms '''
-from __future__ import division, print_function, absolute_import
+"""Common interface for transforms."""
 import numpy as np
 import h5py
 
 from scipy import ndimage as ndi
 
 
 class ImageSpace(object):
-    '''Class to represent spaces of gridded data (images)'''
+    """Class to represent spaces of gridded data (images)."""
+
     __slots__ = ['_affine', '_shape', '_ndim', '_ndindex', '_coords', '_nvox',
                  '_inverse']
 
@@ -92,9 +92,8 @@ def __eq__(self, other):
 
 
 class TransformBase(object):
-    '''
-    Abstract image class to represent transforms
-    '''
+    """Abstract image class to represent transforms."""
+
     __slots__ = ['_reference']
 
     def __init__(self):
@@ -117,11 +116,11 @@ def ndim(self):
 
     def resample(self, moving, order=3, mode='constant', cval=0.0, prefilter=True,
                  output_dtype=None):
-        '''Resample the moving image in reference space
+        """
+        Resample the moving image in reference space.
 
         Parameters
         ----------
-
         moving : `spatialimage`
             The image object containing the data to be resampled in reference
             space
@@ -144,16 +143,14 @@ def resample(self, moving, order=3, mode='constant', cval=0.0, prefilter=True,
 
         Returns
         -------
-
         moved_image : `spatialimage`
             The moving imaged after resampling to reference space.
 
-        '''
-
+        """
+        moving_data = np.asanyarray(moving.dataobj)
         if output_dtype is None:
-            output_dtype = moving.header.get_data_dtype()
+            output_dtype = moving_data.dtype
 
-        moving_data = moving.get_data()
         moved = ndi.geometric_transform(
             moving_data,
             mapping=self.map_voxel,
@@ -171,22 +168,19 @@ def resample(self, moving, order=3, mode='constant', cval=0.0, prefilter=True,
         return moved_image
 
     def map_point(self, coords):
-        '''Find the coordinates in moving space corresponding to the
-        input reference coordinates'''
+        """Apply y = f(x), where x is the argument `coords`."""
         raise NotImplementedError
 
     def map_voxel(self, index, moving=None):
-        '''Find the voxel indices in the moving image corresponding to the
-        input reference voxel'''
+        """Apply ijk' = f_ijk((i, j, k)), equivalent to the above with indexes."""
         raise NotImplementedError
 
     def _to_hdf5(self, x5_root):
-        '''Serialize this object into the x5 file format'''
+        """Serialize this object into the x5 file format."""
         raise NotImplementedError
 
     def to_filename(self, filename, fmt='X5'):
-        '''Store the transform in BIDS-Transforms HDF5 file format (.x5).
-        '''
+        """Store the transform in BIDS-Transforms HDF5 file format (.x5)."""
         with h5py.File(filename, 'w') as out_file:
             out_file.attrs['Format'] = 'X5'
             out_file.attrs['Version'] = np.uint16(1)

nibabel/transform/linear.py

@@ -6,8 +6,7 @@
 #   copyright and license terms.
 #
 ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
-''' Linear transforms '''
-from __future__ import division, print_function, absolute_import
+"""Linear transforms."""
 import sys
 import numpy as np
 from scipy import ndimage as ndi
@@ -21,15 +20,16 @@
 
 
 class Affine(TransformBase):
-    '''Represents linear transforms on image data'''
+    """Represents linear transforms on image data."""
+
     __slots__ = ['_matrix']
 
     def __init__(self, matrix=None, reference=None):
-        '''Initialize a transform
+        """
+        Initialize a linear transform.
 
         Parameters
         ----------
-
         matrix : ndarray
             The inverse coordinate transformation matrix **in physical
             coordinates**, mapping coordinates from *reference* space
@@ -38,15 +38,15 @@ def __init__(self, matrix=None, reference=None):
 
         Examples
         --------
-
         >>> xfm = Affine([[1, 0, 0, 4], [0, 1, 0, 0], [0, 0, 1, 0], [0, 0, 0, 1]])
         >>> xfm.matrix  # doctest: +NORMALIZE_WHITESPACE
         array([[1, 0, 0, 4],
                [0, 1, 0, 0],
                [0, 0, 1, 0],
                [0, 0, 0, 1]])
 
-        '''
+        """
+        super(Affine, self).__init__()
         if matrix is None:
             matrix = [np.eye(4)]
 
@@ -56,7 +56,6 @@ def __init__(self, matrix=None, reference=None):
         self._matrix = np.array(matrix)
         assert self._matrix.ndim == 3, 'affine matrix should be 3D'
         assert self._matrix.shape[-2] == self._matrix.shape[-1], 'affine matrix is not square'
-        super(Affine, self).__init__()
 
         if reference:
             if isinstance(reference, str):
@@ -69,11 +68,11 @@ def matrix(self):
 
     def resample(self, moving, order=3, mode='constant', cval=0.0, prefilter=True,
                  output_dtype=None):
-        '''Resample the moving image in reference space
+        """
+        Resample the moving image in reference space.
 
         Parameters
         ----------
-
         moving : `spatialimage`
             The image object containing the data to be resampled in reference
             space
@@ -96,21 +95,19 @@ def resample(self, moving, order=3, mode='constant', cval=0.0, prefilter=True,
 
         Returns
         -------
-
         moved_image : `spatialimage`
             The moving imaged after resampling to reference space.
 
 
         Examples
         --------
-
         >>> import nibabel as nib
         >>> xfm = Affine([[1, 0, 0, 4], [0, 1, 0, 0], [0, 0, 1, 0], [0, 0, 0, 1]])
         >>> ref = nib.load('image.nii.gz')
         >>> xfm.reference = ref
         >>> xfm.resample(ref, order=0)
 
-        '''
+        """
         if output_dtype is None:
             output_dtype = moving.header.get_data_dtype()
 
@@ -163,13 +160,15 @@ def resample(self, moving, order=3, mode='constant', cval=0.0, prefilter=True,
         return moved_image
 
     def map_point(self, coords, index=0, forward=True):
+        """Apply y = f(x), where x is the argument `coords`."""
         coords = np.array(coords)
         if coords.shape[0] == self._matrix[index].shape[0] - 1:
             coords = np.append(coords, [1])
         affine = self._matrix[index] if forward else np.linalg.inv(self._matrix[index])
         return affine.dot(coords)[:-1]
 
     def map_voxel(self, index, nindex=0, moving=None):
+        """Apply ijk' = f_ijk((i, j, k)), equivalent to the above with indexes."""
         try:
             reference = self.reference
         except ValueError:
@@ -191,6 +190,7 @@ def map_voxel(self, index, nindex=0, moving=None):
         return tuple(matrix.dot(index)[:-1])
 
     def _to_hdf5(self, x5_root):
+        """Serialize this object into the x5 file format."""
         xform = x5_root.create_dataset('Transform', data=self._matrix)
         xform.attrs['Type'] = 'affine'
         x5_root.create_dataset('Inverse', data=np.linalg.inv(self._matrix))
@@ -199,9 +199,7 @@ def _to_hdf5(self, x5_root):
             self.reference._to_hdf5(x5_root.create_group('Reference'))
 
     def to_filename(self, filename, fmt='X5', moving=None):
-        '''Store the transform in BIDS-Transforms HDF5 file format (.x5).
-        '''
-
+        """Store the transform in BIDS-Transforms HDF5 file format (.x5)."""
         if fmt.lower() in ['itk', 'ants', 'elastix', 'nifty']:
             with open(filename, 'w') as f:
                 f.write('#Insight Transform File V1.0\n')
@@ -257,8 +255,7 @@ def to_filename(self, filename, fmt='X5', moving=None):
 
 
 def load(filename, fmt='X5', reference=None):
-    ''' Load a linear transform '''
-
+    """Load a linear transform."""
     if fmt.lower() in ['itk', 'ants', 'elastix', 'nifty']:
         with open(filename) as itkfile:
             itkxfm = itkfile.read().splitlines()
@@ -293,7 +290,10 @@ def load(filename, fmt='X5', reference=None):
 
 
 def _fsl_aff_adapt(space):
-    """Calculates a matrix to convert from the original RAS image
+    """
+    Adapt FSL affines.
+
+    Calculates a matrix to convert from the original RAS image
     coordinates to FSL's internal coordinate system of transforms
     """
     aff = space.affine

nibabel/transform/nonlinear.py

@@ -6,8 +6,7 @@
 #   copyright and license terms.
 #
 ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
-''' Common interface for transforms '''
-from __future__ import division, print_function, absolute_import
+"""Nonlinear transforms."""
 import numpy as np
 from scipy import ndimage as ndi
 # from gridbspline.maths import cubic
@@ -19,14 +18,13 @@
 
 
 class DeformationFieldTransform(TransformBase):
-    '''Represents a dense field of displacements (one vector per voxel)'''
+    """Represents a dense field of displacements (one vector per voxel)."""
+
     __slots__ = ['_field', '_moving', '_moving_space']
     __s = (slice(None), )
 
     def __init__(self, field, reference=None):
-        '''
-        Create a dense deformation field transform
-        '''
+        """Create a dense deformation field transform."""
         super(DeformationFieldTransform, self).__init__()
         self._field = field.get_data()
 
@@ -103,11 +101,11 @@ def _cache_moving(self, moving):
 
     def resample(self, moving, order=3, mode='constant', cval=0.0, prefilter=True,
                  output_dtype=None):
-        '''
+        """
+        Resample the `moving` image applying the deformation field.
 
         Examples
         --------
-
         >>> import numpy as np
         >>> import nibabel as nb
         >>> ref = nb.load('t1_weighted.nii.gz')
@@ -118,16 +116,18 @@ def resample(self, moving, order=3, mode='constant', cval=0.0, prefilter=True,
         >>> new = xfm.resample(ref)
         >>> new.to_filename('deffield.nii.gz')
 
-        '''
+        """
         self._cache_moving(moving)
         return super(DeformationFieldTransform, self).resample(
             moving, order=order, mode=mode, cval=cval, prefilter=prefilter)
 
     def map_voxel(self, index, moving=None):
+        """Apply ijk' = f_ijk((i, j, k)), equivalent to the above with indexes."""
         return tuple(self._moving[index + self.__s])
 
     def map_coordinates(self, coordinates, order=3, mode='mirror', cval=0.0,
                         prefilter=True):
+        """Apply y = f(x), where x is the argument `coords`."""
         coordinates = np.array(coordinates)
         # Extract shapes and dimensions, then flatten
         ndim = coordinates.shape[-1]
@@ -154,11 +154,13 @@ def map_coordinates(self, coordinates, order=3, mode='mirror', cval=0.0,
 
 
 class BSplineFieldTransform(TransformBase):
+    """Represent a nonlinear transform parameterized by BSpline basis."""
+
     __slots__ = ['_coeffs', '_knots', '_refknots', '_order', '_moving']
     __s = (slice(None), )
 
     def __init__(self, reference, coefficients, order=3):
-        '''Create a smooth deformation field using B-Spline basis'''
+        """Create a smooth deformation field using B-Spline basis."""
         super(BSplineFieldTransform, self).__init__()
         self._order = order
         self.reference = reference
@@ -216,16 +218,16 @@ def _interp_transform(self, coords):
         return self.reference.inverse.dot(np.hstack((coords, 1)))[:3]
 
     def map_voxel(self, index, moving=None):
-        '''Find the corresponding coordinates for a voxel in reference space'''
+        """Apply ijk' = f_ijk((i, j, k)), equivalent to the above with indexes."""
         return tuple(self._moving[index + self.__s])
 
     def resample(self, moving, order=3, mode='constant', cval=0.0, prefilter=True,
                  output_dtype=None):
-        '''
+        """
+        Resample the `moving` image applying the deformation field.
 
         Examples
         --------
-
         >>> import numpy as np
         >>> import nibabel as nb
         >>> ref = nb.load('t1_weighted.nii.gz')
@@ -238,7 +240,7 @@ def resample(self, moving, order=3, mode='constant', cval=0.0, prefilter=True,
         >>> new = xfm.resample(ref)
         >>> new.to_filename('deffield.nii.gz')
 
-        '''
+        """
         self._cache_moving()
         return super(BSplineFieldTransform, self).resample(
             moving, order=order, mode=mode, cval=cval, prefilter=prefilter)