def read_cube(filename, **kwargs):
cube_data = None
exclude_exts = []
data_collection = []
hdulist = fits.open(filename)
try:
cube_data = CubeData.read(hdulist)
except CubeDataIOError as e:
warnings.warn('No CubeData found in "{}": {}'.format(
filename,
e.message
))
if cube_data is not None:
data = Data()
try:
data.coords = coordinates_from_wcs(cube_data.wcs)
except AttributeError:
# There is no wcs. Not to worry now.
pass
data.add_component(Component(cube_data), label="cube")
data_collection.append(data)
exclude_exts = cube_data.meta.get('hdu_ids')
# Read in the rest of the FITS file.
data_collection += _load_fits_generic(hdulist,
exclude_exts=exclude_exts)
return data_collection
def _load_fits_generic(filename, **kwargs):
hdulist = fits.open(filename)
groups = dict()
label_base = basename(filename).rpartition('.')[0]
if not label_base:
label_base = basename(filename)
for extnum, hdu in enumerate(hdulist):
if hdu.data is not None:
hdu_name = hdu.name if hdu.name else str(extnum)
if is_image_hdu(hdu):
shape = hdu.data.shape
try:
data = groups[shape]
except KeyError:
label = '{}[{}]'.format(
label_base,
'x'.join(str(x) for x in shape)
)
data = Data(label=label)
data.coords = coordinates_from_header(hdu.header)
groups[shape] = data
data.add_component(component=hdu.data,
label=hdu_name)
elif is_table_hdu(hdu):
# Loop through columns and make component list
table = Table(hdu.data)
table_name = '{}[{}]'.format(
label_base,
hdu_name
)
for column_name in table.columns:
column = table[column_name]
shape = column.shape
data_label = '{}[{}]'.format(
table_name,
'x'.join(str(x) for x in shape)
)
try:
data = groups[data_label]
except KeyError:
data = Data(label=data_label)
groups[data_label] = data
component = Component.autotyped(column, units=column.unit)
data.add_component(component=component,
label=column_name)
return [data for data in groups.itervalues()]
def _load_fits_generic(filename, **kwargs):
hdulist = fits.open(filename)
groups = defaultdict(Data)
for extnum, hdu in enumerate(hdulist):
if not isinstance(hdu, fits.TableHDU) and\
hdu.data is not None:
shape = hdu.data.shape
if shape not in groups:
label = '{}[{}]'.format(
basename(filename).split('.', 1)[0],
'x'.join((str(x) for x in shape))
)
data = Data(label=label)
data.coords = coordinates_from_header(hdu.header)
groups[shape] = data
else:
data = groups[shape]
data.add_component(component=hdu.data,
label=hdu.header.get('EXTNAME', 'EXT[{}]'.format(str(extnum))))
return [data for data in groups.itervalues()]
def _load_fits_generic(source, exclude_exts=None, **kwargs):
"""Read in all extensions from a FITS file.
Parameters
----------
source: str or HDUList
The pathname to the FITS file.
If and HDUList is passed in, simply use that.
exclude_exts: [hdu, ] or [index, ]
List of HDU's to exclude from reading.
This can be a list of HDU's or a list
of HDU indexes.
"""
exclude_exts = exclude_exts or []
if not isinstance(source, fits.hdu.hdulist.HDUList):
hdulist = fits.open(source)
else:
hdulist = source
groups = dict()
label_base = basename(hdulist.filename()).rpartition('.')[0]
if not label_base:
label_base = basename(hdulist.filename())
for extnum, hdu in enumerate(hdulist):
hdu_name = hdu.name if hdu.name else str(extnum)
if hdu.data is not None and \
hdu_name not in exclude_exts and \
extnum not in exclude_exts:
if is_image_hdu(hdu):
shape = hdu.data.shape
try:
data = groups[shape]
except KeyError:
label = '{}[{}]'.format(
label_base,
'x'.join(str(x) for x in shape)
)
data = Data(label=label)
data.coords = coordinates_from_header(hdu.header)
groups[shape] = data
data.add_component(component=hdu.data,
label=hdu_name)
elif is_table_hdu(hdu):
# Loop through columns and make component list
table = Table(hdu.data)
table_name = '{}[{}]'.format(
label_base,
hdu_name
)
for column_name in table.columns:
column = table[column_name]
shape = column.shape
data_label = '{}[{}]'.format(
table_name,
'x'.join(str(x) for x in shape)
)
try:
data = groups[data_label]
except KeyError:
data = Data(label=data_label)
groups[data_label] = data
component = Component(column, units=column.unit)
data.add_component(component=component,
label=column_name)
return [data for data in six.itervalues(groups)]
