ReddeningLaw¶
-
class
synphot.reddening.
ReddeningLaw
(modelclass, clean_meta=False, **kwargs)[source]¶ Bases:
synphot.spectrum.BaseUnitlessSpectrum
Class to handle reddening law.
Parameters: - modelclass, kwargs
See
BaseSpectrum
.
Methods Summary
extinction_curve
(ebv[, wavelengths])Generate extinction curve. from_extinction_model
(modelname, **kwargs)Load pre-defined extinction model. from_file
(filename, **kwargs)Create a reddening law from file. to_fits
(filename[, wavelengths])Write the reddening law to a FITS file. Methods Documentation
-
extinction_curve
(ebv, wavelengths=None)[source]¶ Generate extinction curve.
\[ \begin{align}\begin{aligned}A(V) = R(V) \; \times \; E(B-V)\\THRU = 10^{-0.4 \; A(V)}\end{aligned}\end{align} \]Parameters: Returns: - extcurve :
ExtinctionCurve
Empirical extinction curve.
Raises: - synphot.exceptions.SynphotError
Invalid input.
- extcurve :
-
classmethod
from_extinction_model
(modelname, **kwargs)[source]¶ Load pre-defined extinction model.
Parameters: - modelname : str
Extinction model name. Choose from ‘lmc30dor’, ‘lmcavg’, ‘mwavg’, ‘mwdense’, ‘mwrv21’, ‘mwrv40’, ‘smcbar’, or ‘xgalsb’.
- kwargs : dict
Keywords acceptable by
read_remote_spec()
.
Returns: - redlaw :
ReddeningLaw
Empirical reddening law.
Raises: - synphot.exceptions.SynphotError
Invalid extinction model name.
-
classmethod
from_file
(filename, **kwargs)[source]¶ Create a reddening law from file.
If filename has ‘fits’ or ‘fit’ suffix, it is read as FITS. Otherwise, it is read as ASCII.
Parameters: - filename : str
Reddening law filename.
- kwargs : dict
Keywords acceptable by
read_fits_spec()
(if FITS) orread_ascii_spec()
(if ASCII).
Returns: - redlaw :
ReddeningLaw
Empirical reddening law.
-
to_fits
(filename, wavelengths=None, **kwargs)[source]¶ Write the reddening law to a FITS file.
\(R(V)\) column is automatically named ‘Av/E(B-V)’.
Parameters: - filename : str
Output filename.
- wavelengths : array-like,
Quantity
, orNone
Wavelength values for sampling. If not a Quantity, assumed to be in Angstrom. If
None
,self.waveset
is used.- kwargs : dict
Keywords accepted by
write_fits_spec()
.