def read_spec(ispec, second_file=None):
'''Parse spectrum out of the input
Parameters:
-----------
ispec: Spectrum1D, str, or tuple
Returns:
-----------
spec: XSpectrum1D
spec_file: str
'''
from specutils import Spectrum1D
from linetools.spectra.utils import XSpectrum1D
#
if isinstance(ispec,basestring):
spec_fil = ispec
spec = lsi.readspec(spec_fil)
# Second file?
if not second_file is None:
spec2 = lsi.readspec(second_file)
if spec2.sig is None:
spec2.sig = np.zeros(spec.flux.size)
# Scale for convenience of plotting
xper1 = xstats.basic.perc(spec.flux, per=0.9)
xper2 = xstats.basic.perc(spec2.flux, per=0.9)
scl = xper1[1]/xper2[1]
# Stitch together
wave3 = np.append(spec.dispersion, spec2.dispersion)
flux3 = np.append(spec.flux, spec2.flux*scl)
sig3 = np.append(spec.sig, spec2.sig*scl)
spec3 = Spectrum1D.from_array(wave3, flux3, uncertainty=StdDevUncertainty(sig3))
# Overwrite
spec = spec3
spec.filename = spec_fil
elif isinstance(ispec,Spectrum1D):
spec = ispec # Assuming Spectrum1D
spec_fil = spec.filename # Grab from Spectrum1D
elif isinstance(ispec,tuple):
# Units
try:
wv_unit = ispec[0].unit
except AttributeError:
wv_unit = u.AA
uwave = u.Quantity(ispec[0], unit=wv_unit)
# Generate
if len(ispec) == 2: # wave, flux
spec = XSpectrum1D.from_array(uwave, u.Quantity(ispec[1]))
else:
spec = XSpectrum1D.from_array(uwave, u.Quantity(ispec[1]),
uncertainty=StdDevUncertainty(ispec[2]))
#
spec_fil = 'none'
spec.filename = spec_fil
else:
raise ValueError('Bad input to read_spec')
# Return
return spec, spec_fil
def voigt_model(spec, line, Npix=None, flg_ret=1):
"""Generates a Voigt model from a line or list of lines
Parameters:
------------
spec: wave array or Spectrum
line: Abs_Line, List of Abs_line, or array of parameters
flg_ret : int (1) Byte-wise Flag for return
1: vmodel
2: tau
ToDo:
1. May need to more finely sample the wavelength array
JXP 01 Nov 2014
"""
# Imports
import copy
from linetools.spectra.utils import XSpectrum1D
from astropy.nddata import StdDevUncertainty
from xastropy.spec.lines_utils import AbsLine
# Spectrum input
if isinstance(spec,np.ndarray): # Standard wavelength array
vmodel = XSpectrum1D.from_array(spec, np.ones(len(spec)),
uncertainty=StdDevUncertainty(np.zeros(len(spec))))
elif isinstance(spec,Spectrum1D):
vmodel = copy.deepcopy(spec)
else:
raise ValueError('voigt_model: Unknown input')
#xdb.set_trace()
# Line input
if isinstance(line,AbsLine): # Single line as a Abs_Line Class
par = [0*i for i in range(6)] # Dummy list
par[0] = line.attrib['N']
par[1] = line.z
par[2] = line.attrib['b']
par[3] = line.wrest
par[4] = line.atomic['fval']
par[5] = line.atomic['gamma']
elif isinstance(line,list):
if isinstance(line[0],AbsLine): # List of Abs_Line
tau = np.zeros(len(vmodel.flux))
for iline in line:
tau += voigt_model(vmodel.dispersion, iline, Npix=None, flg_ret=2)
else:
par = line # Single line as a vector
else:
raise ValueError('voigt: Unknown type for voigt line')
# tau
if 'tau' not in locals():
#xdb.set_trace()
cold = 10.0**par[0] / u.cm / u.cm
zp1=par[1]+1.0
wv=par[3].to(u.cm) #*1.0e-8
nujk = (const.c / wv).to(u.Hz)
dnu = ((par[2]*u.km/u.s) / wv).to('Hz')
avoigt = ((par[5]/u.s)/( 4 * np.pi * dnu)).to(u.dimensionless_unscaled)
uvoigt = ( ((const.c / (vmodel.dispersion/zp1)) - nujk) / dnu).to(u.dimensionless_unscaled)
'''
wv=par[3].to(u.cm) #*1.0e-8
bl=((par[2]*u.km/u.s)*wv/const.c).to(u.cm) # 2.99792458E5
a= ((par[5]/u.s)*wv*wv/( 4 * np.pi * const.c.to('cm/s') * bl)).to(u.dimensionless_unscaled)
cns=wv*wv*par[4]/(bl*2.002134602291006E12) * u.cm
# Converting to Voigt units
cne=cold*cns
ww=(vmodel.dispersion.to('cm'))/zp1
v=wv*ww*((1.0/ww)-(1.0/wv))/bl
'''
# Voigt
cne = 0.01497 * cold * par[4] * u.cm * u.cm * u.Hz
tau = cne * voigtking(uvoigt,avoigt) / (np.sqrt(np.pi) * dnu)
# Flux
if vmodel.unit is None:
try:
vmodel.flux = (np.exp(-1.0*tau)).value
except AttributeError:
vmodel.flux = np.exp(-1.0*tau)
else:
vmodel.flux = np.exp(-1.0*tau).to(vmodel.unit)
# Convolve
if Npix is not None:
vmodel.gauss_smooth(npix=Npix)
# Return
ret_val = []
if flg_ret % 2 == 1: ret_val.append(vmodel)
if flg_ret % 4 >= 2: ret_val.append(tau)
#xdb.set_trace()
if len(ret_val) == 1: ret_val = ret_val[0]
return ret_val