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)