def load(self, path, image_field="image", meta_field="metadata"):
""" A method that load the data and associated metadata.
Parameters
----------
path: str
the path to the data to be loaded.
image_field: str, default 'image'
the name of the data field that contains the image array.
image_field: str, default 'metadata'
the name of the data field that contains the image metadata.
Return
------
image: Image
the loaded image.
"""
data = loadmat(path)
_array = data[image_field]
_meta = {"path": path}
if meta_field in data:
_meta.update(data[meta_field])
return Image(data_type="scalar",
metadata=_meta,
data=_array)
def load(self, path):
""" A method that load the image data and associated metadata.
Parameters
----------
path: str
the path to the image to be loaded.
Returns
-------
image: Image
the loaded image.
"""
cube = np.load(path)
return Image(data_type="scalar", data=cube)
def load(self, path):
""" A method that load the image data and associated metadata.
Parameters
----------
path: str
the path to the image to be loaded.
Return
------
image: Image
the loaded image.
"""
_image = nibabel.load(path)
return Image(spacing=_image.header.get_zooms(),
data_type="scalar",
metadata={"path": path},
data=_image.get_data())
def load(self, path):
""" A method that load the image data and associated metadata.
Parameters
----------
path: str
the path to the image to be loaded.
Return
------
image: Image
the loaded image.
"""
hdulist = pyfits.open(path)
if len(hdulist) != 1:
raise Exception("Only one HDU object supported yet. Can't "
"read '{0}'.".format(path))
cube = hdulist[0].data
header = dict(hdulist[0].header.items())
header["path"] = path
hdulist.close()
return Image(data_type="scalar", metadata=header, data=cube)