Merge pull request #364 from bcipolli/filebasedimage

RF: Move load/save logic out of SpatialImage into FileBasedImage

Prepares for XML-based images that do not store data as binary arrays.
Spatial{Image,Header} now subclass FileBased{Image,Header}
Header is a deprecated alias for SpatialHeader

Author: effigies

doc/source/old/examples.txt

@@ -32,7 +32,7 @@ and we have made a temporary directory for the files we are going to write:
 and we've got the path to the nifti example data:
 
   >>> from nibabel.testing import data_path as example_data_path
-  
+
 Loading and saving NIfTI files
 ==============================
 
@@ -77,7 +77,7 @@ The relevant header information is extracted from the NumPy array. If you
 query the header information about the dimensionality of the image, it returns
 the desired values:
 
-  >>> print nim.get_header()['dim']
+  >>> print nim.header['dim']
   [  4  32  32  16 100   1   1   1]
 
 First value shows the number of dimensions in the datset: 4 (good, that's what
@@ -110,8 +110,8 @@ preserving as much header information as possible
 
   >>> nim2 = nib.Nifti1Image(nim.get_data()[..., :10],
   ...                       nim.get_affine(),
-  ...                       nim.get_header())
-  >>> print nim2.get_header()['dim']
+  ...                       nim.header)
+  >>> print nim2.header['dim']
   [ 4 32 32 16 10  1  1  1]
   >>> # a filename in our temporary directory
   >>> fname = pjoin(tmpdir, 'part.hdr.gz')
@@ -136,7 +136,7 @@ will first create a NIfTI image with just a single voxel and 50 timepoints
   >>> nim = nib.Nifti1Image(
   ...           (np.linspace(0,100) + np.random.randn(50)).reshape(1,1,1,50),
   ...           np.eye(4))
-  >>> print nim.get_header()['dim']
+  >>> print nim.header['dim']
   [ 4  1  1  1 50  1  1  1]
 
 Depending on the datatype of the input image the detrending process might
@@ -154,4 +154,4 @@ source image.
 
   >>> nim_detrended = nib.Nifti1Image(data_detrended,
   ...                                nim.get_affine(),
-  ...                                nim.get_header())
+  ...                                nim.header)

doc/source/old/orientation.txt

@@ -6,7 +6,7 @@
 
 Every image in ``nibabel`` has an orientation.  The orientation is the
 relationship between the voxels in the image array, and millimeters in
-some space.  
+some space.
 
 Affines as orientation
 ----------------------
@@ -85,7 +85,7 @@ the affine after loading, as in::
     img = nibabel.load('some_image.img')
     aff = img.get_affine()
     x_flipper = np.diag([-1,1,1,1])
-    lr_img = nibabel.Nifti1Image(img.get_data, np.dot(x_flipper, aff), img.get_header())
+    lr_img = nibabel.Nifti1Image(img.get_data, np.dot(x_flipper, aff), img.header)
 
 Affines for Analyze, SPM analyze, and NIFTI
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

nibabel/ecat.py

@@ -929,7 +929,7 @@ def to_file_map(self, file_map=None):
         # It appears to be necessary to load the data before saving even if the
         # data itself is not used.
         self.get_data()
-        hdr = self.get_header()
+        hdr = self.header
         mlist = self._mlist
         subheaders = self.get_subheaders()
         dir_pos = 512
@@ -944,7 +944,7 @@ def to_file_map(self, file_map=None):
         hdr.write_to(hdrf)
 
         # Write every frames
-        for index in range(0, self.get_header()['num_frames']):
+        for index in range(0, self.header['num_frames']):
             # Move to subheader offset
             frame_offset = subheaders._get_frame_offset(index) - 512
             imgf.seek(frame_offset)