def test_remove_hdu(tmpdir):
hdulist = fits.HDUList()
image = fits.ImageHDU(np.random.random((25, 25)))
hdulist.append(image)
tree = {
'some_words': 'These are some words',
'nested': {
'a': 100,
'b': 42
},
'list': [x for x in range(10)],
'image': image.data
}
asdf_in_fits = str(tmpdir.join('asdf.fits'))
with AsdfInFits(hdulist, tree) as aif:
aif.write_to(asdf_in_fits)
with fits.open(asdf_in_fits) as hdul:
assert 'ASDF' in hdul
new_fits = str(tmpdir.join('remove.fits'))
remove_hdu(asdf_in_fits, new_fits)
assert os.path.exists(new_fits)
with fits.open(new_fits) as hdul:
assert 'ASDF' not in hdul
def test_extract(tmpdir):
hdulist = HDUList()
image = ImageHDU(np.random.random((25, 25)))
hdulist.append(image)
tree = {
'some_words': 'These are some words',
'nested': {
'a': 100,
'b': 42
},
'list': [x for x in range(10)],
'image': image.data
}
asdf_in_fits = str(tmpdir.join('asdf.fits'))
with AsdfInFits(hdulist, tree) as aif:
aif.write_to(asdf_in_fits)
pure_asdf = str(tmpdir.join('extract.asdf'))
extract.extract_file(asdf_in_fits, pure_asdf)
assert os.path.exists(pure_asdf)
with asdf.open(pure_asdf) as af:
assert not isinstance(af, AsdfInFits)
assert_tree_match(tree, af.tree)
def load_hdu(self, hdu, dstobj=None, **kwargs):
if isinstance(hdu, (
pyfits.ImageHDU,
pyfits.CompImageHDU,
pyfits.PrimaryHDU,
)):
# <-- data is an image
if dstobj is None:
# get model class for this type of object
obj_class = self.factory_dict.get('image', None)
if obj_class is None:
raise FITSError(
"I don't know how to load objects of kind 'image'")
dstobj = obj_class(logger=self.logger)
# For now, call back into the object to load it from pyfits-style
# HDU in future migrate to storage-neutral format
dstobj.load_hdu(hdu, **kwargs)
elif isinstance(hdu, (pyfits.TableHDU, pyfits.BinTableHDU)):
# <-- data is a table
# Handle ASDF embedded in FITS.
# TODO: Populate EXTNAME, EXTVER, NAXISn in ASDF meta from HDU?
# TODO: How to read from all the different ASDF layouts?
# TODO: Cache the ASDF object?
from ginga.util import io_asdf
if io_asdf.have_asdf and hdu.name == 'ASDF':
from asdf.fits_embed import AsdfInFits
from ginga import AstroImage
self.logger.debug('Attempting to load {} extension from '
'FITS'.format(hdu.name))
dstobj = AstroImage.AstroImage()
with AsdfInFits.open(self.fits_f) as asdf_f:
dstobj.load_asdf(asdf_f)
return dstobj
if dstobj is None:
self.logger.debug('Attempting to load table from FITS')
# get model class for this type of object
obj_class = self.factory_dict.get('table', None)
if obj_class is None:
raise FITSError(
"I don't know how to load objects of kind 'table'")
dstobj = obj_class(logger=self.logger)
# For now, call back into the object to load it from pyfits-style
# HDU in future migrate to storage-neutral format
dstobj.load_hdu(hdu, **kwargs)
else:
raise FITSError("I don't know how to read this HDU")
return dstobj
def load_hdu(self, hdu, dstobj=None, **kwargs):
typ = self.get_hdu_type(hdu)
if typ == 'image':
if dstobj is None:
# get model class for this type of object
obj_class = self.factory_dict.get('image', None)
if obj_class is None:
raise FITSError(
"I don't know how to load objects of kind 'image'")
dstobj = obj_class(logger=self.logger)
# For now, call back into the object to load it from pyfits-style
# HDU in future migrate to storage-neutral format
dstobj.load_hdu(hdu, **kwargs)
elif typ == 'table':
# <-- data may be a table
# Handle ASDF embedded in FITS.
# TODO: Populate EXTNAME, EXTVER, NAXISn in ASDF meta from HDU?
# TODO: How to read from all the different ASDF layouts?
# TODO: Cache the ASDF object?
from ginga.util import io_asdf
if io_asdf.have_asdf and hdu.name == 'ASDF':
from asdf.fits_embed import AsdfInFits
from ginga import AstroImage
self.logger.debug('Attempting to load {} extension from '
'FITS'.format(hdu.name))
dstobj = AstroImage.AstroImage()
with AsdfInFits.open(self.fits_f) as asdf_f:
dstobj.load_asdf(asdf_f)
return dstobj
if dstobj is None:
self.logger.debug('Attempting to load table from FITS')
# get model class for this type of object
obj_class = self.factory_dict.get('table', None)
if obj_class is None:
raise FITSError(
"I don't know how to load objects of kind 'table'")
dstobj = obj_class(logger=self.logger)
# For now, call back into the object to load it from pyfits-style
# HDU in future migrate to storage-neutral format
dstobj.load_hdu(hdu, **kwargs)
else:
raise FITSError("I don't know how to read this HDU")
return dstobj
def load_asdf_hdu_in_fits(self, fits_f, hdu, **kwargs):
"""*** This is a special method that should only be called from
WITHIN io_fits.py to open up ASDF-embedded-in-FITS ***
"""
# Handle ASDF embedded in FITS (see load_hdu() in io_fits.py)
# TODO: Populate EXTNAME, EXTVER, NAXISn in ASDF meta
# from HDU?
# TODO: How to read from all the different ASDF layouts?
# TODO: Cache the ASDF object?
# TODO: hdu is ignored for now, but presumably this loader might
# eventually want to check it
with AsdfInFits.open(fits_f) as asdf_f:
data_obj = self.load_asdf(asdf_f, logger=self.logger, **kwargs)
# metadata will be hopefully be set back in io_fits
return data_obj
def _jwst2data(file_obj, ext, data_label):
comp_label = ext.upper()
new_data_label = f'{data_label}[{comp_label}]'
data = Data(label=new_data_label)
unit_attr = f'bunit_{ext}'
try:
# This is very specific to JWST pipeline image output.
with AsdfInFits.open(file_obj) as af:
dm = af.tree
dm_meta = af.tree["meta"]
if (unit_attr in dm_meta and
_validate_bunit(dm_meta[unit_attr], raise_error=False)):
bunit = dm_meta[unit_attr]
else:
bunit = ''
# This is instance of gwcs.WCS, not astropy.wcs.WCS
if 'wcs' in dm_meta:
data.coords = dm_meta['wcs']
imdata = dm[ext]
component = Component.autotyped(imdata, units=bunit)
# Might have bad GWCS. If so, we exclude it.
try:
data.add_component(component=component, label=comp_label)
except Exception: # pragma: no cover
data.coords = None
data.add_component(component=component, label=comp_label)
# TODO: Do not need this when jwst.datamodels finally its own package.
# This might happen for grism image; fall back to FITS loader without WCS.
except Exception:
if ext == 'data':
ext = 'sci'
hdu = file_obj[ext]
return _hdu2data(hdu, data_label, file_obj, include_wcs=False)
return data, new_data_label