DOC - fix up getting started doctests

Author: matthew-brett

doc/source/gettingstarted.rst

@@ -23,81 +23,86 @@ familiarize oneself with the basic design of the API.
 
 When loading an image, NiBabel aims to figure out the image format from the
 filename. An image in a known format can easily be loaded by simply passing its
-name to the ``load`` function:
+name to the ``load`` function.  First let's get the nibabel example data
+directory:
 
-  >>> import nibabel as nb
-  >>> import os
-  >>> import numpy as np
-  >>> img = nb.load(os.path.join('nibabel', 'tests', 'data',
-  ...                            'example4d.nii.gz'))
+>>> import os
+>>> from nibabel.testing import data_path
 
-A NiBabel image knows about its shape
+Now we can load an image:
 
-  >>> img.get_shape()
-  (128, 96, 24, 2)
+>>> import nibabel as nib
+>>> img = nib.load(os.path.join(data_path, 'example4d.nii.gz'))
 
-its data type
+A NiBabel image knows about its shape:
 
-  >>> img.get_data_dtype()
-  dtype('int16')
+>>> img.get_shape()
+(128, 96, 24, 2)
+
+and its data type:
+
+>>> img.get_data_dtype()
+dtype('int16')
 
 and an affine transformation that determines the world-coordinates of the image
 elements.
 
-  >>> img.get_affine().shape
-  (4, 4)
+>>> img.get_affine().shape
+(4, 4)
 
 This information is available without the need to load anything of the main
 image data into the memory. Of course there is also access to the image data as
 a NumPy_ array
 
-  >>> data = img.get_data()
-  >>> data.shape
-  (128, 96, 24, 2)
-  >>> type(data)
-  <type 'numpy.ndarray'>
+>>> data = img.get_data()
+>>> data.shape
+(128, 96, 24, 2)
+>>> type(data)
+<type 'numpy.ndarray'>
 
 The complete information embedded in an image header is available via a
 format-specific header object.
 
-  >>> hdr = img.get_header()
+>>> hdr = img.get_header()
 
 In case of this NIfTI_ file it allows accessing all NIfTI-specific information,
 e.g.
 
-  >>> hdr.get_xyzt_units()
-  ('mm', 'sec')
+>>> hdr.get_xyzt_units()
+('mm', 'sec')
 
 Corresponding "setter" methods allow modifying a header, while ensuring its
 compliance with the file format specifications.
 
 In some situations even more flexibility is required and for ultimate experts
 NiBabel also offers access to the raw header information
 
-  >>> raw = hdr.structarr
-  >>> raw['xyzt_units']
-  array(10, dtype=uint8)
+>>> raw = hdr.structarr
+>>> raw['xyzt_units']
+array(10, dtype=uint8)
 
 This lowest level of the API is only for people that know what they are doing
-comes without any safety-net.
+and comes without any safety-net.
 
 Creating a new image in some file format is also easy. At a minimum it only
 needs some image data and an image coordinate transformation.
 
-  >>> data = np.ones((32, 32, 15, 100), dtype=np.int16)
-  >>> img = nb.Nifti1Image(data, np.eye(4))
-  >>> img.get_data_dtype()
-  dtype('int16')
-  >>> img.get_header().get_xyzt_units()
-  ('unknown', 'unknown')
+>>> import numpy as np
+>>> data = np.ones((32, 32, 15, 100), dtype=np.int16)
+>>> img = nib.Nifti1Image(data, np.eye(4))
+>>> img.get_data_dtype()
+dtype('int16')
+>>> img.get_header().get_xyzt_units()
+('unknown', 'unknown')
 
 In this case, identity is used as the affine transformation. The image header
 is initialized from the provided data array (i.e. shape, dtype) and all other
 values are set to resonable defaults.
 
-Saving this new image to a file is trivial
+Saving this new image to a file is trivial.  We won't do it here, but it looks
+like::
 
-  >>> img.to_filename(os.path.join('build','test4d.nii.gz'))
+    img.to_filename(os.path.join('build','test4d.nii.gz'))
 
 This short introduction only gave a quick overview of NiBabel's capabilities.
 Please have a look at the :ref:`api` for more details about supported file