"""
Utilities for defining, loading, and handling spectroscopic calibration data
"""
import warnings
from pathlib import Path
from typing import Sequence, Literal
from urllib.error import URLError
from astropy import units as u
from astropy.table import Table, vstack, QTable
from astropy.utils.data import download_file
from astropy.utils.exceptions import AstropyUserWarning
from astropy.coordinates import SpectralCoord
from specutils.utils.wcs_utils import vac_to_air
from specreduce.compat import Spectrum
__all__ = [
'get_available_line_catalogs',
'load_pypeit_calibration_lines',
'load_MAST_calspec',
'load_onedstds',
'AtmosphericExtinction',
'AtmosphericTransmission'
]
SUPPORTED_EXTINCTION_MODELS = [
"kpno",
"ctio",
"apo",
"lapalma",
"mko",
"mtham",
"paranal"
]
SPECPHOT_DATASETS = [
"bstdscal",
"ctiocal",
"ctionewcal",
"eso",
"gemini",
"iidscal",
"irscal",
"oke1990",
"redcal",
"snfactory",
"spec16cal",
"spec50cal",
"spechayescal"
]
PYPEIT_CALIBRATION_LINELISTS = [
'Ne_IR_MOSFIRE',
'ArII',
'CdI',
'OH_MOSFIRE_H',
'OH_triplespec',
'Ar_IR_MOSFIRE',
'OH_GNIRS',
'ThAr_XSHOOTER_VIS',
'ThAr_MagE',
'HgI',
'NeI',
'XeI',
'OH_MODS',
'ZnI',
'OH_GMOS',
'CuI',
'ThAr_XSHOOTER_VIS_air',
'ThAr_XSHOOTER_UVB',
'OH_NIRES',
'HeI',
'FeI',
'OH_MOSFIRE_J',
'KrI',
'Cd_DeVeny1200',
'Ar_IR_GNIRS',
'OH_MOSFIRE_Y',
'ThAr',
'FeII',
'OH_XSHOOTER',
'OH_FIRE_Echelle',
'OH_MOSFIRE_K',
'OH_R24000',
'Hg_DeVeny1200',
'ArI'
]
SPECREDUCE_DATA_URL = ("https://raw.githubusercontent.com/astropy/specreduce-data/"
"main/specreduce_data/reference_data/")
PYPEIT_DATA_URL = ("https://raw.githubusercontent.com/pypeit/"
"pypeit/release/pypeit/data/")
[docs]
def get_available_line_catalogs() -> dict:
"""
Returns a dictionary of available line catalogs. Currently only ``pypeit``
catalogs are fully supported.
"""
return {
'pypeit': PYPEIT_CALIBRATION_LINELISTS
}
[docs]
def load_pypeit_calibration_lines(
lamps: Sequence | None = None,
wave_air: bool = False,
cache: bool | Literal['update'] = True,
show_progress: bool = False
) -> QTable | None:
"""
Load reference calibration lines from ``pypeit`` linelists. The ``pypeit`` linelists are
well-curated and have been tested across a wide range of spectrographs. The available
linelists are defined by ``PYPEIT_CALIBRATION_LINELISTS``.
Parameters
----------
lamps : Lamp string, comma-separated list of lamps, or sequence of lamps to include in
output reference linelist. The parlance of "lamp" is retained here for consistency
with its use in ``pypeit`` and elsewhere. In several of the supported cases the
"lamp" is the sky itself (e.g. OH lines in the near-IR).
The available lamps are defined by ``PYPEIT_CALIBRATION_LINELISTS``.
wave_air : If True, convert the vacuum wavelengths used by ``pypeit`` to air wavelengths.
cache : Toggle caching of downloaded data
show_progress : Show download progress bar
Returns
-------
linelist:
Table containing the combined calibration line list. ``pypeit`` linelists have the
following columns:
* ``ion``: Ion or molecule generating the line.
* ``wavelength``: Vacuum wavelength of the line in Angstroms.
* ``NIST``: Flag denoting if NIST is the ultimate reference for the line's wavelength.
* ``Instr``: ``pypeit``-specific instrument flag.
* ``amplitude``: Amplitude of the line. Beware, not consistent between lists.
* ``Source``: Source of the line information.
"""
if lamps is None:
return None
if not isinstance(lamps, Sequence):
raise ValueError(f"Invalid calibration lamps specification: {lamps}")
if isinstance(lamps, str):
if ',' in lamps:
lamps = [lamp.strip() for lamp in lamps.split(',')]
else:
lamps = [lamps]
linelists = []
for lamp in lamps:
if lamp in PYPEIT_CALIBRATION_LINELISTS:
data_url = f"{PYPEIT_DATA_URL}/arc_lines/lists/{lamp}_lines.dat"
try:
data_path = download_file(data_url, cache=cache,
show_progress=show_progress,
pkgname='specreduce')
linelists.append(Table.read(data_path, format='ascii.fixed_width', comment='#'))
except URLError as e:
warnings.warn(f"Downloading of {data_url} failed: {e}", AstropyUserWarning)
else:
warnings.warn(
f"{lamp} not in the list of supported calibration "
f"line lists: {PYPEIT_CALIBRATION_LINELISTS}."
)
if len(linelists) == 0:
warnings.warn(f"No calibration lines loaded from {lamps}.")
linelist = None
else:
linelist = QTable(vstack(linelists))
linelist.rename_column('wave', 'wavelength')
# pypeit linelists use vacuum wavelengths in angstroms
linelist['wavelength'] *= u.Angstrom
if wave_air:
linelist['wavelength'] = vac_to_air(linelist['wavelength'])
return linelist
[docs]
def load_MAST_calspec(
filename: str | Path,
cache: bool | Literal['update'] = True,
show_progress: bool = False
) -> Spectrum | None:
"""
Load a standard star spectrum from the ``calspec`` database at MAST. These spectra are provided
in FITS format and are described in detail at:
https://www.stsci.edu/hst/instrumentation/reference-data-for-calibration-and-tools/astronomical-catalogs/calspec
If ``remote`` is True, the spectrum will be downloaded from MAST. Set ``remote`` to False to
load a local file.
.. note:: This function requires ``synphot`` to be installed separately.
Parameters
----------
filename : FITS filename of a standard star spectrum, e.g. g191b2b_005.fits.
If this is a local file, it will be loaded. If not, then a download from
MAST will be attempted.
cache : Toggle whether downloaded data is cached or not.
show_progress : Toggle whether download progress bar is shown.
Returns
-------
spectrum : If the spectrum can be loaded, return it as a `~specutils.Spectrum`.
Otherwise return None. The spectral_axis units are Å and the flux units are milli-Janskys.
"""
filename = Path(filename)
if filename.exists() and filename.is_file():
file_path = filename
else:
try:
data_url = f"https://archive.stsci.edu/hlsps/reference-atlases/cdbs/calspec/{filename}"
file_path = download_file(data_url, cache=cache,
show_progress=show_progress,
pkgname='specreduce')
except URLError as e:
warnings.warn(f"Downloading of {filename} failed: {e}", AstropyUserWarning)
file_path = None
if file_path is None:
return None
else:
import synphot
_, wave, flux = synphot.specio.read_fits_spec(file_path)
# DEV: pllim does not think this is necessary at all but whatever.
# the calspec data stores flux in synphot's FLAM units. convert to flux units
# supported directly by astropy.units. mJy is chosen since it's the JWST
# standard and can easily be converted to/from AB magnitudes.
flux_mjy = synphot.units.convert_flux(wave, flux, u.mJy)
spectrum = Spectrum(spectral_axis=wave, flux=flux_mjy)
return spectrum
[docs]
def load_onedstds(
dataset: str = "snfactory",
specfile: str = "EG131.dat",
cache: bool | Literal['update'] = True,
show_progress: bool = False
) -> Spectrum | None:
"""
This is a convenience function for loading a standard star spectrum from the 'onedstds'
dataset in the ``specreduce_data`` package. They will be downloaded from the
repository on GitHub and cached by default.
Parameters
----------
dataset : Standard star spectrum database. Valid options are described
in :ref:`specphot_standards`.
specfile : Filename of the standard star spectrum.
cache : Enable caching of downloaded data.
show_progress : Show download progress bar if data is downloaded.
Returns
-------
spectrum : If the spectrum can be loaded, return it as a `~specutils.Spectrum`.
Otherwise return None. The spectral_axis units are Å and the flux units are milli-Janskys.
"""
if dataset not in SPECPHOT_DATASETS:
msg = (f"Specfied dataset, {dataset}, not in list of supported datasets of "
f"spectrophotometric standard stars: f{SPECPHOT_DATASETS}")
warnings.warn(msg, AstropyUserWarning)
return None
try:
data_path = download_file(f"{SPECREDUCE_DATA_URL}/onedstds/{dataset}/{specfile}",
cache=cache, show_progress=show_progress, pkgname="specreduce")
t = Table.read(data_path, format="ascii", names=['wavelength', 'ABmag', 'binsize'])
except URLError as e:
msg = f"Can't load {specfile} from {dataset}: {e}."
warnings.warn(msg, AstropyUserWarning)
return None
# the specreduce_data standard star spectra all provide wavelengths in angstroms
spectral_axis = t['wavelength'].data * u.angstrom
# the specreduce_data standard star spectra all provide fluxes in AB mag
flux = t['ABmag'].data * u.ABmag
flux = flux.to(u.mJy) # convert to linear flux units
spectrum = Spectrum(spectral_axis=spectral_axis, flux=flux)
return spectrum
[docs]
class AtmosphericExtinction(Spectrum):
"""
Spectrum container for atmospheric extinction in magnitudes as a function of wavelength.
If extinction and spectral_axis are provided, this will use them to build a custom model.
If they are not, the 'model' parameter will be used to lookup and load a pre-defined
atmospheric extinction model from the ``specreduce_data`` package.
Parameters
----------
model : str
Name of atmospheric extinction model provided by ``specreduce_data``. Valid
options are:
* kpno - Kitt Peak National Observatory (default)
* ctio - Cerro Tololo International Observatory
* apo - Apache Point Observatory
* lapalma - Roque de los Muchachos Observatory, La Palma, Canary Islands
* mko - Mauna Kea Observatories
* mtham - Lick Observatory, Mt. Hamilton station
* paranal - European Southern Observatory, Cerro Paranal station
extinction : float, `~astropy.units.Quantity`, or `None`, optional
Provides extinction data for this spectrum. Used along with
spectral_axis to build custom atmospheric extinction model. If no units are provided,
assumed to be given in magnitudes.
spectral_axis : `~astropy.coordinates.SpectralCoord`, `~astropy.units.Quantity`, or `None`, optional
Dispersion information with the same shape as the last (or only)
dimension of flux, or one greater than the last dimension of flux
if specifying bin edges. Used along with flux to build custom atmospheric
extinction model.
Attributes
----------
extinction_mag : `~astropy.units.Quantity`
Extinction expressed in dimensionless magnitudes
transmission : `~astropy.units.Quantity`
Extinction expressed as fractional transmission
""" # noqa: E501
def __init__(
self,
model: str = "kpno",
extinction: Sequence[float] | u.Quantity | None = None,
spectral_axis: SpectralCoord | u.Quantity | None = None,
cache: bool | Literal['update'] = True,
show_progress: bool = False,
**kwargs: str
) -> None:
if extinction is not None:
if not isinstance(extinction, u.Quantity):
warnings.warn(
"Input extinction is not a Quanitity. Assuming it is given in magnitudes...",
AstropyUserWarning
)
extinction = u.Magnitude(
extinction,
u.MagUnit(u.dimensionless_unscaled)
).to(u.dimensionless_unscaled) # Spectrum wants this to be linear
elif isinstance(extinction, (u.LogUnit, u.Magnitude)) or extinction.unit == u.mag:
# if in log or magnitudes, recast into Magnitude with dimensionless physical units
extinction = u.Magnitude(
extinction.value,
u.MagUnit(u.dimensionless_unscaled)
).to(u.dimensionless_unscaled)
elif extinction.unit != u.dimensionless_unscaled:
# if we're given something linear that's not dimensionless_unscaled,
# it's an error
msg = "Input extinction must have unscaled dimensionless units."
raise ValueError(msg)
if extinction is None and spectral_axis is None:
if model not in SUPPORTED_EXTINCTION_MODELS:
msg = (
f"Requested extinction model, {model}, not in list "
f"of available models: {SUPPORTED_EXTINCTION_MODELS}"
)
raise ValueError(msg)
data_file = download_file(f"{SPECREDUCE_DATA_URL}/extinction/{model}extinct.dat",
cache=cache, show_progress=show_progress,
pkgname='specreduce')
t = Table.read(data_file, format="ascii", names=['wavelength', 'extinction'])
# the specreduce_data models all provide wavelengths in angstroms
spectral_axis = t['wavelength'].data * u.angstrom
# the specreduce_data models all provide extinction in magnitudes at an airmass of 1
extinction = u.Magnitude(
t['extinction'].data,
u.MagUnit(u.dimensionless_unscaled)
).to(u.dimensionless_unscaled)
if spectral_axis is None:
msg = "Missing spectral axis for input extinction data."
raise ValueError(msg)
super(AtmosphericExtinction, self).__init__(
flux=extinction,
spectral_axis=spectral_axis,
unit=u.dimensionless_unscaled,
**kwargs
)
@property
def extinction_mag(self) -> u.Quantity:
"""
This property returns the extinction in magnitudes
"""
return self.flux.to(u.mag(u.dimensionless_unscaled))
@property
def transmission(self) -> u.Quantity:
"""
This property returns the transmission as a fraction between 0 and 1
"""
return self.flux
[docs]
class AtmosphericTransmission(AtmosphericExtinction):
"""
Spectrum container for atmospheric transmission as a function of wavelength.
Parameters
----------
data_file : Name to file containing atmospheric transmission data. Data is assumed to have
two columns, wavelength and transmission (unscaled dimensionless). If
this isn't provided, a model is built from a pre-calculated table of values
from 0.9 to 5.6 microns. The values were generated by the ATRAN model,
https://ntrs.nasa.gov/citations/19930010877 (Lord, S. D., 1992, NASA
Technical Memorandum 103957). The extinction is given as a linear transmission
fraction at an airmass of 1 and 1 mm of precipitable water.
wave_unit : Units for spectral axis.
"""
def __init__(
self,
data_file: str | Path | None = None,
wave_unit: u.Unit = u.um,
**kwargs: str
) -> None:
if data_file is None:
data_file = download_file(f"{SPECREDUCE_DATA_URL}/extinction/atm_trans_am1.0.dat")
t = Table.read(data_file, format="ascii", names=['wavelength', 'extinction'])
# spectral axis is given in microns
spectral_axis = t['wavelength'].data * wave_unit
# extinction is given in a dimensionless transmission fraction
extinction = t['extinction'].data * u.dimensionless_unscaled
super(AtmosphericTransmission, self).__init__(
extinction=extinction,
spectral_axis=spectral_axis,
**kwargs
)
