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
#from barak import spec as bs
from barak import convolve as bc
import copy
from specutils.spectrum1d import Spectrum1D
# Spectrum input
if isinstance(spec,np.ndarray): # Standard wavelength array
vmodel = Spectrum1D.from_array(spec, np.zeros(len(spec)))
elif isinstance(spec,Spectrum1D):
vmodel = copy.deepcopy(spec)
else:
raise ValueError('voigt_model: Unknown input')
# Line input
if isinstance(line,abs_line.Abs_Line): # 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],abs_line.Abs_Line): # 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)
#xdb.set_trace()
else:
par = line # Single line as a vector
else:
raise ValueError('voigt: Unknown type for voigt line')
# tau
if 'tau' not in locals():
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
# Test ions
if (flg_test % 2**1) >= 2**0:
print('-------------------------')
tmp1.get_ions()
print('C IV: ')
print(tmp1.ions[(6,4)])
print(tmp1.ions.trans[5]) # CIV 1550
# Plot the LLS
if (flg_test % 2**2) >= 2**1:
print('-------------------------')
tmp1.fill_lls_lines()
from specutils.spectrum1d import Spectrum1D
wa=np.linspace(3400.0,5000.0,10000)
spec = Spectrum1D.from_array(wa,np.ones(len(wa)))
model = tmp1.flux_model(spec, smooth=4)
model.qck_plot()
#xdb.set_trace()
# Test zpeak
if (flg_test % 2**3) >= 2**2:
print('-------------------------')
tmp1.fill_ions()
ion,vpeak = tmp1.get_zpeak()
print('zpeak = {:g}'.format(tmp1.zpeak))
# Write .dat
if (flg_test % 2**4) >= 2**3:
tmp1.write_dat_file()
doppler = 3.0
fval = 1.669
gamma = 2.5E9
wrest = 1206.5*u.AA # SiIII
line = [coldens,zabs,doppler,wrest,fval,gamma]
plt.clf()
if flg_test % 16 >= 8:
vmodel = voigt_model(wave, line, Npix=None) # No smoothing
xdb.xplot(vmodel.dispersion, vmodel.flux, drawstyle='steps-mid')
vmodel2 = voigt_model(wave, line, Npix=4.) # Smoothing
print('voigt: Smooth test')
xdb.xplot(vmodel.dispersion, vmodel.flux)
# Test pass back
if flg_test % 32 >= 16:
vmodel,tau = voigt_model(wave, line, Npix=None, flg_ret=3) # No smoothing
vmodel.qck_plot()
print('voigt: Passing test. Tau plot')
xdb.xplot(wave,tau)
# Test spec input
if flg_test % 64 >= 32:
from specutils.spectrum1d import Spectrum1D
spec = Spectrum1D.from_array(wave, np.zeros(len(wave)))
vmodel = voigt_model(spec, line, Npix=None, flg_ret=1) # No smoothing
print('voigt: Spec input test')
vmodel.qck_plot()
print('voigt: All done testing..')
def test_from_spec1d():
spec = Spectrum1D.from_array(np.array([1,2,3]), np.array([1,1,1]))
xspec = XSpectrum1D.from_spec1d(spec)
