import logging
import os
import warnings
import numpy as np
from astropy import units as u
from astropy.io import fits
from astropy.time import Time
from astropy.wcs import WCS
from specutils import Spectrum1D
from jdaviz.core.registries import data_parser_registry
from jdaviz.utils import standardize_metadata, PRIHDR_KEY
__all__ = ['parse_data']
EXT_TYPES = dict(flux=['flux', 'sci', 'data'],
uncert=['ivar', 'err', 'var', 'uncert'],
mask=['mask', 'dq', 'quality'])
[docs]
@data_parser_registry("cubeviz-data-parser")
def parse_data(app, file_obj, data_type=None, data_label=None):
"""
Attempts to parse a data file and auto-populate available viewers in
cubeviz.
Parameters
----------
app : `~jdaviz.app.Application`
The application-level object used to reference the viewers.
file_obj : str
The path to a cube-like data file.
data_type : str, {'flux', 'mask', 'uncert'}
The data type used to explicitly differentiate parsed data.
data_label : str, optional
The label to be applied to the Glue data component.
"""
flux_viewer_reference_name = app._jdaviz_helper._default_flux_viewer_reference_name
uncert_viewer_reference_name = app._jdaviz_helper._default_uncert_viewer_reference_name
spectrum_viewer_reference_name = app._jdaviz_helper._default_spectrum_viewer_reference_name
if data_type is not None and data_type.lower() not in ('flux', 'mask', 'uncert'):
raise TypeError("Data type must be one of 'flux', 'mask', or 'uncert' "
f"but got '{data_type}'")
# If the file object is an hdulist or a string, use the generic parser for
# fits files.
# TODO: this currently only supports fits files. We will want to make this
# generic enough to work with other file types (e.g. ASDF). For now, this
# supports MaNGA and JWST data.
if isinstance(file_obj, fits.hdu.hdulist.HDUList):
_parse_hdulist(
app, file_obj, file_name=data_label,
flux_viewer_reference_name=flux_viewer_reference_name,
spectrum_viewer_reference_name=spectrum_viewer_reference_name,
uncert_viewer_reference_name=uncert_viewer_reference_name
)
app.get_tray_item_from_name("Spectral Extraction").disabled_msg = ""
elif isinstance(file_obj, str):
if file_obj.lower().endswith('.gif'): # pragma: no cover
_parse_gif(app, file_obj, data_label,
flux_viewer_reference_name=flux_viewer_reference_name,
spectrum_viewer_reference_name=spectrum_viewer_reference_name)
return
file_name = os.path.basename(file_obj)
with fits.open(file_obj) as hdulist:
prihdr = hdulist[0].header
telescop = prihdr.get('TELESCOP', '').lower()
exptype = prihdr.get('EXP_TYPE', '').lower()
# NOTE: Alerted to deprecation of FILETYPE keyword from pipeline on 2022-07-08
# Kept for posterity in for data processed prior to this date. Use EXP_TYPE instead
filetype = prihdr.get('FILETYPE', '').lower()
system = prihdr.get('SYSTEM', '').lower()
if telescop == 'jwst' and ('ifu' in exptype or
'mrs' in exptype or
filetype == '3d ifu cube'):
for ext, viewer_name in (('SCI', flux_viewer_reference_name),
('ERR', uncert_viewer_reference_name),
('DQ', None)):
data_label = app.return_data_label(file_name, ext)
_parse_jwst_s3d(
app, hdulist, data_label, ext=ext, viewer_name=viewer_name,
flux_viewer_reference_name=flux_viewer_reference_name,
spectrum_viewer_reference_name=spectrum_viewer_reference_name
)
elif telescop == 'jwst' and filetype == 'r3d' and system == 'esa-pipeline':
for ext, viewer_name in (('DATA', flux_viewer_reference_name),
('ERR', uncert_viewer_reference_name),
('QUALITY', None)):
data_label = app.return_data_label(file_name, ext)
_parse_esa_s3d(
app, hdulist, data_label, ext=ext, viewer_name=viewer_name,
flux_viewer_reference_name=flux_viewer_reference_name,
spectrum_viewer_reference_name=spectrum_viewer_reference_name
)
else:
_parse_hdulist(
app, hdulist, file_name=data_label or file_name,
flux_viewer_reference_name=flux_viewer_reference_name,
spectrum_viewer_reference_name=spectrum_viewer_reference_name,
uncert_viewer_reference_name=uncert_viewer_reference_name
)
app.get_tray_item_from_name("Spectral Extraction").disabled_msg = ""
# If the data types are custom data objects, use explicit parsers. Note
# that this relies on the glue-astronomy machinery to turn the data object
# into something glue can understand.
elif isinstance(file_obj, Spectrum1D) and file_obj.flux.ndim in (1, 3):
if file_obj.flux.ndim == 3:
_parse_spectrum1d_3d(
app, file_obj, data_label=data_label,
flux_viewer_reference_name=flux_viewer_reference_name,
spectrum_viewer_reference_name=spectrum_viewer_reference_name,
uncert_viewer_reference_name=uncert_viewer_reference_name
)
else:
_parse_spectrum1d(
app, file_obj, data_label=data_label,
spectrum_viewer_reference_name=spectrum_viewer_reference_name
)
app.get_tray_item_from_name("Spectral Extraction").disabled_msg = ""
elif isinstance(file_obj, np.ndarray) and file_obj.ndim == 3:
_parse_ndarray(app, file_obj, data_label=data_label, data_type=data_type,
flux_viewer_reference_name=flux_viewer_reference_name,
spectrum_viewer_reference_name=spectrum_viewer_reference_name,
uncert_viewer_reference_name=uncert_viewer_reference_name)
app.get_tray_item_from_name("Spectral Extraction").disabled_msg = ""
else:
raise NotImplementedError(f'Unsupported data format: {file_obj}')
def _get_celestial_wcs(wcs):
""" If `wcs` has a celestial component return that, otherwise return None """
return wcs.celestial if hasattr(wcs, 'celestial') else None
def _return_spectrum_with_correct_units(flux, wcs, metadata, data_type, target_wave_unit=None,
hdulist=None, uncertainty=None, mask=None):
"""Upstream issue of WCS not using the correct units for data must be fixed here.
Issue: https://github.com/astropy/astropy/issues/3658
"""
with warnings.catch_warnings():
warnings.filterwarnings(
'ignore', message='Input WCS indicates that the spectral axis is not last',
category=UserWarning)
sc = Spectrum1D(flux=flux, wcs=wcs, uncertainty=uncertainty, mask=mask)
if target_wave_unit is None and hdulist is not None:
found_target = False
for ext in ('SCI', 'FLUX', 'PRIMARY', 'DATA'): # In priority order
if found_target:
break
if ext not in hdulist:
continue
hdr = hdulist[ext].header
# The WCS could be swapped or unswapped.
for cunit_num in (3, 1):
cunit_key = f"CUNIT{cunit_num}"
ctype_key = f"CTYPE{cunit_num}"
if cunit_key in hdr and 'WAV' in hdr[ctype_key]:
target_wave_unit = u.Unit(hdr[cunit_key])
found_target = True
break
if (data_type == 'flux' and target_wave_unit is not None
and target_wave_unit != sc.spectral_axis.unit):
metadata['_orig_spec'] = sc
with warnings.catch_warnings():
warnings.filterwarnings(
'ignore', message='Input WCS indicates that the spectral axis is not last',
category=UserWarning)
new_sc = Spectrum1D(
flux=sc.flux,
spectral_axis=sc.spectral_axis.to(target_wave_unit, u.spectral()),
meta=metadata,
uncertainty=sc.uncertainty,
mask=sc.mask
)
else:
sc.meta = metadata
new_sc = sc
return new_sc
def _parse_hdulist(app, hdulist, file_name=None,
flux_viewer_reference_name=None,
spectrum_viewer_reference_name=None,
uncert_viewer_reference_name=None):
if file_name is None and hasattr(hdulist, 'file_name'):
file_name = hdulist.file_name
else:
file_name = file_name or "Unknown HDU object"
is_loaded = []
wcs_sci = None
# TODO: This needs refactoring to be more robust.
# Current logic fails if there are multiple EXTVER.
for hdu in hdulist:
if hdu.data is None or not hdu.is_image or hdu.data.ndim != 3:
continue
data_type = _get_data_type_by_hdu(hdu)
if not data_type:
continue
# Only load each type once.
if data_type in is_loaded:
continue
is_loaded.append(data_type)
data_label = app.return_data_label(file_name, hdu.name)
if data_type == 'flux':
wcs = WCS(hdu.header, hdulist)
wcs_sci = wcs
else:
wcs = wcs_sci
if 'BUNIT' in hdu.header:
try:
flux_unit = u.Unit(hdu.header['BUNIT'])
except Exception:
logging.warning("Invalid BUNIT, using count as data unit")
flux_unit = u.count
elif data_type == 'mask': # DQ flags have no unit
flux_unit = u.dimensionless_unscaled
else:
logging.warning("Invalid BUNIT, using count as data unit")
flux_unit = u.count
flux = hdu.data << flux_unit
metadata = standardize_metadata(hdu.header)
if hdu.name != 'PRIMARY' and 'PRIMARY' in hdulist:
metadata[PRIHDR_KEY] = standardize_metadata(hdulist['PRIMARY'].header)
sc = _return_spectrum_with_correct_units(flux, wcs, metadata, data_type, hdulist=hdulist)
# store original WCS in metadata. this is a hacky workaround for converting subsets
# to sky regions, where the parent data of the subset might have dropped spatial WCS info
metadata['_orig_spatial_wcs'] = _get_celestial_wcs(wcs)
app.add_data(sc, data_label)
if data_type == 'flux': # Forced wave unit conversion made it lose stuff, so re-add
app.data_collection[-1].get_component("flux").units = flux_unit
if data_type == 'mask':
# We no longer auto-populate the mask cube into a viewer
pass
elif data_type == 'uncert':
app.add_data_to_viewer(uncert_viewer_reference_name, data_label)
app._jdaviz_helper._loaded_uncert_cube = app.data_collection[data_label]
else: # flux
# Add flux to top left image viewer
app.add_data_to_viewer(flux_viewer_reference_name, data_label)
# Add flux to spectrum viewer
app.add_data_to_viewer(spectrum_viewer_reference_name, data_label)
app._jdaviz_helper._loaded_flux_cube = app.data_collection[data_label]
def _parse_jwst_s3d(app, hdulist, data_label, ext='SCI',
viewer_name=None, flux_viewer_reference_name=None,
spectrum_viewer_reference_name=None):
hdu = hdulist[ext]
data_type = _get_data_type_by_hdu(hdu)
# Manually inject MJD-OBS until we can support GWCS, see
# https://github.com/spacetelescope/jdaviz/issues/690 and
# https://github.com/glue-viz/glue-astronomy/issues/59
if ext == 'SCI' and 'MJD-OBS' not in hdu.header:
for key in ('MJD-BEG', 'DATE-OBS'): # Possible alternatives
if key in hdu.header:
if key.startswith('MJD'):
hdu.header['MJD-OBS'] = hdu.header[key]
break
else:
t = Time(hdu.header[key])
hdu.header['MJD-OBS'] = t.mjd
break
if ext == 'DQ': # DQ flags have no unit
flux = hdu.data << u.dimensionless_unscaled
else:
unit = u.Unit(hdu.header.get('BUNIT', 'count'))
flux = hdu.data << unit
wcs = WCS(hdulist['SCI'].header, hdulist) # Everything uses SCI WCS
metadata = standardize_metadata(hdu.header)
# store original WCS in metadata. this is a hacky workaround for converting subsets
# to sky regions, where the parent data of the subset might have dropped spatial WCS info
metadata['_orig_spatial_wcs'] = _get_celestial_wcs(wcs)
if hdu.name != 'PRIMARY' and 'PRIMARY' in hdulist:
metadata[PRIHDR_KEY] = standardize_metadata(hdulist['PRIMARY'].header)
data = _return_spectrum_with_correct_units(flux, wcs, metadata, data_type, hdulist=hdulist)
app.add_data(data, data_label)
if data_type == 'flux': # Forced wave unit conversion made it lose stuff, so re-add
app.data_collection[-1].get_component("flux").units = flux.unit
if viewer_name is not None:
app.add_data_to_viewer(viewer_name, data_label)
# Also add the collapsed flux to the spectrum viewer
if viewer_name == flux_viewer_reference_name:
app.add_data_to_viewer(spectrum_viewer_reference_name, data_label)
if data_type == 'flux':
app._jdaviz_helper._loaded_flux_cube = app.data_collection[data_label]
elif data_type == 'uncert':
app._jdaviz_helper._loaded_uncert_cube = app.data_collection[data_label]
def _parse_esa_s3d(app, hdulist, data_label, ext='DATA', flux_viewer_reference_name=None,
spectrum_viewer_reference_name=None):
hdu = hdulist[ext]
data_type = _get_data_type_by_hdu(hdu)
if ext == 'QUALITY': # QUALITY flags have no unit
flux = hdu.data << u.dimensionless_unscaled
else:
unit = u.Unit(hdu.header.get('BUNIT', 'count'))
flux = hdu.data << unit
hdr = hdulist[1].header
wcs_dict = {
'CTYPE1': 'WAVE ', 'CUNIT1': 'um', 'CDELT1': hdr['CDELT3'] * 1E6,
'CRPIX1': hdr['CRPIX3'],
'CRVAL1': hdr['CRVAL3'] * 1E6, 'NAXIS1': hdr['NAXIS3'],
'CTYPE2': 'DEC--TAN', 'CUNIT2': 'deg', 'CDELT2': hdr['CDELT1'], 'CRPIX2': hdr['CRPIX1'],
'CRVAL2': hdr['CRVAL1'], 'NAXIS2': hdr['NAXIS1'],
'CTYPE3': 'RA---TAN', 'CUNIT3': 'deg', 'CDELT3': hdr['CDELT2'], 'CRPIX3': hdr['CRPIX2'],
'CRVAL3': hdr['CRVAL2'], 'NAXIS3': hdr['NAXIS2']}
wcs = WCS(wcs_dict)
flux = np.moveaxis(flux, 0, -1)
flux = np.swapaxes(flux, 0, 1)
metadata = standardize_metadata(hdu.header)
metadata.update(wcs_dict) # To be internally consistent
if hdu.name != 'PRIMARY' and 'PRIMARY' in hdulist:
metadata[PRIHDR_KEY] = standardize_metadata(hdulist['PRIMARY'].header)
# store original WCS in metadata. this is a hacky workaround for converting subsets
# to sky regions, where the parent data of the subset might have dropped spatial WCS info
metadata['_orig_spatial_wcs'] = _get_celestial_wcs(wcs)
data = _return_spectrum_with_correct_units(flux, wcs, metadata, data_type, hdulist=hdulist)
app.add_data(data, data_label)
if data_type == 'flux': # Forced wave unit conversion made it lose stuff, so re-add
app.data_collection[-1].get_component("flux").units = flux.unit
app.add_data_to_viewer(flux_viewer_reference_name, data_label)
app.add_data_to_viewer(spectrum_viewer_reference_name, data_label)
if data_type == 'flux':
app._jdaviz_helper._loaded_flux_cube = app.data_collection[data_label]
if data_type == 'uncert':
app._jdaviz_helper._loaded_uncert_cube = app.data_collection[data_label]
def _parse_spectrum1d_3d(app, file_obj, data_label=None,
flux_viewer_reference_name=None, spectrum_viewer_reference_name=None,
uncert_viewer_reference_name=None):
"""Load spectrum1d as a cube."""
if data_label is None:
data_label = "Unknown spectrum object"
for attr in ("flux", "mask", "uncertainty"):
val = getattr(file_obj, attr)
if val is None:
continue
if attr == "mask":
flux = val << u.dimensionless_unscaled # DQ flags have no unit
elif attr == "uncertainty":
if hasattr(val, "array"):
flux = u.Quantity(val.array, file_obj.flux.unit)
else:
continue
else:
flux = val
flux = np.moveaxis(flux, 1, 0)
with warnings.catch_warnings():
warnings.filterwarnings(
'ignore', message='Input WCS indicates that the spectral axis is not last',
category=UserWarning)
meta = standardize_metadata(file_obj.meta)
# store original WCS in metadata. this is a hacky workaround for
# converting subsets to sky regions, where the parent data of the
# subset might have dropped spatial WCS info
meta['_orig_spatial_wcs'] = None
if hasattr(file_obj, 'wcs'):
meta['_orig_spatial_wcs'] = _get_celestial_wcs(file_obj.wcs)
s1d = Spectrum1D(flux=flux, wcs=file_obj.wcs, meta=meta)
cur_data_label = app.return_data_label(data_label, attr.upper())
app.add_data(s1d, cur_data_label)
if attr == 'flux':
app.add_data_to_viewer(flux_viewer_reference_name, cur_data_label)
app.add_data_to_viewer(spectrum_viewer_reference_name, cur_data_label)
app._jdaviz_helper._loaded_flux_cube = app.data_collection[cur_data_label]
elif attr == 'uncertainty':
app.add_data_to_viewer(uncert_viewer_reference_name, cur_data_label)
app._jdaviz_helper._loaded_uncert_cube = app.data_collection[cur_data_label]
# We no longer auto-populate the mask cube into a viewer
def _parse_spectrum1d(app, file_obj, data_label=None, spectrum_viewer_reference_name=None):
# Here 'file_obj' is a Spectrum1D
if data_label is None:
data_label = app.return_data_label(file_obj)
# store original WCS in metadata. this is a hacky workaround for converting subsets
# to sky regions, where the parent data of the subset might have dropped spatial WCS info
file_obj.meta['_orig_spatial_wcs'] = _get_celestial_wcs(file_obj.wcs) if hasattr(file_obj, 'wcs') else None # noqa: E501
# TODO: glue-astronomy translators only look at the flux property of
# specutils Spectrum1D objects. Fix to support uncertainties and masks.
app.add_data(file_obj, data_label)
app.add_data_to_viewer(spectrum_viewer_reference_name, data_label)
def _parse_ndarray(app, file_obj, data_label=None, data_type=None,
flux_viewer_reference_name=None, spectrum_viewer_reference_name=None,
uncert_viewer_reference_name=None):
if data_label is None:
data_label = app.return_data_label(file_obj)
if data_type is None:
data_type = 'flux'
# Cannot change axis to ensure roundtripping within Cubeviz.
# Axes must already be (x, y, z) at this point.
flux = file_obj
if not hasattr(flux, 'unit'):
flux = flux << u.count
meta = standardize_metadata({'_orig_spatial_wcs': None})
s3d = Spectrum1D(flux=flux, meta=meta)
app.add_data(s3d, data_label)
if data_type == 'flux':
app.add_data_to_viewer(flux_viewer_reference_name, data_label)
app.add_data_to_viewer(spectrum_viewer_reference_name, data_label)
app._jdaviz_helper._loaded_flux_cube = app.data_collection[data_label]
elif data_type == 'uncert':
app.add_data_to_viewer(uncert_viewer_reference_name, data_label)
app._jdaviz_helper._loaded_uncert_cube = app.data_collection[data_label]
def _parse_gif(app, file_obj, data_label=None, flux_viewer_reference_name=None,
spectrum_viewer_reference_name=None): # pragma: no cover
# NOTE: Parsing GIF needs imageio and Pillow, both are which undeclared
# in setup.cfg but might or might not be installed by declared ones.
import imageio
file_name = os.path.basename(file_obj)
if data_label is None:
data_label = app.return_data_label(file_obj)
flux = imageio.v3.imread(file_obj, mode='P') # All frames as gray scale
flux = np.rot90(np.moveaxis(flux, 0, 2), k=-1, axes=(0, 1))
meta = {'filename': file_name, '_orig_spatial_wcs': None}
s3d = Spectrum1D(flux=flux * u.count, meta=standardize_metadata(meta))
app.add_data(s3d, data_label)
app.add_data_to_viewer(flux_viewer_reference_name, data_label)
app.add_data_to_viewer(spectrum_viewer_reference_name, data_label)
def _get_data_type_by_hdu(hdu):
# If the data type is some kind of integer, assume it's the mask/dq
if (hdu.data.dtype in (int, np.uint, np.uint8, np.uint16, np.uint32) or
any(x in hdu.name.lower() for x in EXT_TYPES['mask'])):
data_type = 'mask'
elif ('errtype' in [x.lower() for x in hdu.header.keys()] or
any(x in hdu.name.lower() for x in EXT_TYPES['uncert'])):
data_type = 'uncert'
elif any(x in hdu.name.lower() for x in EXT_TYPES['flux']):
data_type = 'flux'
else:
data_type = ''
return data_type
