/usr/share/pyshared/nibabel/loadsave.py is in python-nibabel 1.3.0-2.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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#
# See COPYING file distributed along with the NiBabel package for the
# copyright and license terms.
#
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# module imports
from .py3k import asbytes
from .filename_parser import types_filenames, splitext_addext
from . import volumeutils as vu
from . import spm2analyze as spm2
from . import nifti1
from .freesurfer import MGHImage
from .fileholders import FileHolderError
from .spatialimages import ImageFileError
from .imageclasses import class_map, ext_map
def load(filename):
''' Load file given filename, guessing at file type
Parameters
----------
filename : string
specification of file to load
Returns
-------
img : ``SpatialImage``
Image of guessed type
'''
froot, ext, trailing = splitext_addext(filename, ('.gz', '.bz2'))
try:
img_type = ext_map[ext]
except KeyError:
raise ImageFileError('Cannot work out file type of "%s"' %
filename)
if ext in ('.nii', '.mnc', '.mgh', '.mgz'):
klass = class_map[img_type]['class']
else:
# might be nifti pair or analyze of some sort
files_types = (('image','.img'), ('header','.hdr'))
filenames = types_filenames(filename, files_types)
hdr = nifti1.Nifti1Header.from_fileobj(
vu.allopen(filenames['header']),
check=False)
if hdr['magic'] in (asbytes('ni1'), asbytes('n+1')):
# allow goofy nifti single magic for pair
klass = nifti1.Nifti1Pair
else:
klass = spm2.Spm2AnalyzeImage
return klass.from_filename(filename)
def save(img, filename):
''' Save an image to file adapting format to `filename`
Parameters
----------
img : ``SpatialImage``
image to save
filename : str
filename (often implying filenames) to which to save `img`.
Returns
-------
None
'''
try:
img.to_filename(filename)
except ImageFileError:
pass
else:
return
froot, ext, trailing = splitext_addext(filename, ('.gz', '.bz2'))
img_type = ext_map[ext]
klass = class_map[img_type]['class']
converted = klass.from_image(img)
converted.to_filename(filename)
def read_img_data(img, prefer='scaled'):
""" Read data from image associated with files
Parameters
----------
img : ``SpatialImage``
Image with valid image file in ``img.file_map``. Unlike the
``img.get_data()`` method, this function returns the data read
from the image file, as specified by the *current* image header
and *current* image files.
prefer : str, optional
Can be 'scaled' - in which case we return the data with the
scaling suggested by the format, or 'unscaled', in which case we
return, if we can, the raw data from the image file, without the
scaling applied.
Returns
-------
arr : ndarray
array as read from file, given parameters in header
Notes
-----
Summary: please use the ``get_data`` method of `img` instead of this
function unless you are sure what you are doing.
In general, you will probably prefer ``prefer='scaled'``, because
this gives the data as the image format expects to return it.
Use `prefer` == 'unscaled' with care; the modified Analyze-type
formats such as SPM formats, and nifti1, specify that the image data
array is given by the raw data on disk, multiplied by a scalefactor
and maybe with the addition of a constant. This function, with
``unscaled`` returns the data on the disk, without these
format-specific scalings applied. Please use this funciton only if
you absolutely need the unscaled data, and the magnitude of the
data, as given by the scalefactor, is not relevant to your
application. The Analyze-type formats have a single scalefactor +/-
offset per image on disk. If you do not care about the absolute
values, and will be removing the mean from the data, then the
unscaled values will have preserved intensity ratios compared to the
mean-centered scaled data. However, this is not necessarily true of
other formats with more complicated scaling - such as MINC.
"""
image_fileholder = img.file_map['image']
try:
fileobj = image_fileholder.get_prepare_fileobj()
except FileHolderError:
raise ImageFileError('No image file specified for this image')
if prefer not in ('scaled', 'unscaled'):
raise ValueError('Invalid string "%s" for "prefer"' % prefer)
hdr = img.get_header()
if prefer == 'unscaled':
try:
return hdr.raw_data_from_fileobj(fileobj)
except AttributeError:
pass
return hdr.data_from_fileobj(fileobj)
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