def asDict(self):
"""Returns the header data of the `NiftiImage` in a dictionary.
:Returns:
dict
The dictionary contains all NIfTI header information. Additionally,
it might also contain a special 'meta' item that contains the
meta data currently assigned to this instance.
.. note::
Modifications done to the returned dictionary do not cause any
modifications in the NIfTI image itself. Please use
:meth:`~nifti.format.NiftiFormat.updateFromDict` to apply
changes to the image.
.. seealso::
:meth:`~nifti.format.NiftiFormat.updateFromDict`,
:attr:`~nifti.format.NiftiFormat.header`
"""
# Convert nifti_image struct into nifti1 header struct.
# This get us all data that will actually make it into a
# NIfTI file.
nhdr = ncl.nifti_convert_nim2nhdr(self.raw_nimg)
# pass extensions as well
ret = nhdr2dict(nhdr, extensions=self.extensions)
if len(self.meta.keys()):
ret['meta'] = self.meta
return ret
def __newFromArray(self, data, hdr=None):
"""Create a `nifti_image` struct from a ndarray.
:Parameters:
data: ndarray
Source ndarray.
hdr: dict
Optional dictionary with NIfTI header data.
.. warning::
This is an internal method. Neither its availability nor its API is
guarenteed.
"""
if hdr == None:
hdr = {}
# check array
if len(data.shape) > 7:
raise ValueError, \
"NIfTI does not support data with more than 7 dimensions."
# create template nifti header struct
niptr = ncl.nifti_simple_init_nim()
nhdr = ncl.nifti_convert_nim2nhdr(niptr)
# intermediate cleanup
ncl.nifti_image_free(niptr)
# convert virgin nifti header to dict to merge properties
# with supplied information and array properties
hdic = nhdr2dict(nhdr)
# copy data from supplied header dict
for k, v in hdr.iteritems():
hdic[k] = v
# finally set header data that is determined by the data array
# convert NumPy to nifti datatype
hdic['datatype'] = Ndtype2niftidtype(data)
# make sure there are no zeros in the dim vector
# especially not in #4 as FSLView doesn't like that
hdic['dim'] = [ 1 for i in hdic['dim'] ]
# set number of dims
hdic['dim'][0] = len(data.shape)
# set size of each dim (and reverse the order to match nifti format
# requirements)
for i, s in enumerate(data.shape):
hdic['dim'][len(data.shape)-i] = s
# set magic field to mark as nifti file
hdic['magic'] = 'n+1'
self._rebuildNimgFromHdrAndDict(nhdr, hdic)
def updateFromDict(self, hdrdict):
"""Update NIfTI header information.
Updated header data is read from the supplied dictionary. One cannot
modify dimensionality and datatype of the image data. If such
information is present in the header dictionary it is removed before
the update. If resizing or datatype casting are required one has to
convert the image data into a separate array and perform resize and
data manipulations on this array. When finished, the array can be
converted into a nifti file by calling the NiftiImage constructor with
the modified array as 'source' and the nifti header of the original
NiftiImage object as 'header'.
.. note::
If the provided dictionary contains a 'meta' item its content is
used to overwrite any potentially existing meta data.
dictionary.
The same behavior will be used for 'extensions'. If extensions
are defined in the provided dictionary all currently existing
extensions will be overwritten.
.. seealso::
:meth:`~nifti.format.NiftiFormat.asDict`,
:attr:`~nifti.format.NiftiFormat.header`
"""
# rebuild nifti header from current image struct
nhdr = ncl.nifti_convert_nim2nhdr(self.__nimg)
# remove settings from the hdrdict that are determined by
# the data set and must not be modified to preserve data integrity
if hdrdict.has_key('datatype'):
del hdrdict['datatype']
if hdrdict.has_key('dim'):
del hdrdict['dim']
self._rebuildNimgFromHdrAndDict(nhdr, hdrdict)
