def obyo(y, tag, nusd, nus, numatrix_CO, mdbCO, cdbH2H2):
# CO
SijM_CO = jit(vmap(SijT,
(0, None, None, None, 0)))(Tarr, mdbCO.logsij0,
mdbCO.dev_nu_lines,
mdbCO.elower, qt_CO)
gammaLMP_CO = jit(vmap(gamma_exomol,
(0, 0, None, None)))(Parr, Tarr, mdbCO.n_Texp,
mdbCO.alpha_ref)
gammaLMN_CO = gamma_natural(mdbCO.A)
gammaLM_CO = gammaLMP_CO + gammaLMN_CO[None, :]
sigmaDM_CO = jit(vmap(doppler_sigma,
(None, 0, None)))(mdbCO.dev_nu_lines, Tarr,
molmassCO)
xsm_CO = xsmatrix(numatrix_CO, sigmaDM_CO, gammaLM_CO, SijM_CO)
dtaumCO = dtauM(dParr, xsm_CO, MMR_CO * ONEARR, molmassCO, g)
# CIA
dtaucH2H2 = dtauCIA(nus, Tarr, Parr, dParr, vmrH2, vmrH2, mmw, g,
cdbH2H2.nucia, cdbH2H2.tcia, cdbH2H2.logac)
dtau = dtaumCO + dtaucH2H2
sourcef = planck.piBarr(Tarr, nus)
F0 = rtrun(dtau, sourcef) / norm
Frot = response.rigidrot(nus, F0, vsini, u1, u2)
mu = response.ipgauss_sampling(nusd, nus, Frot, beta, RV)
numpyro.sample(tag, dist.Normal(mu, sigmain), obs=y)
def obyo(y, tag, nusdx, nus, mdbCO, mdbH2O, cdbH2H2, cdbH2He):
#CO
SijM_CO, ngammaLM_CO, nsigmaDl_CO = exomol(mdbCO, Tarr, Parr, R_CO,
molmassCO)
xsm_CO = xsmatrix(cnu_CO, indexnu_CO, R_CO, pmarray_CO, nsigmaDl_CO,
ngammaLM_CO, SijM_CO, nus, dgm_ngammaL_CO)
dtaumCO = dtauM(dParr, jnp.abs(xsm_CO), MMR_CO * ONEARR, molmassCO, g)
#H2O
SijM_H2O, ngammaLM_H2O, nsigmaDl_H2O = exomol(mdbH2O, Tarr, Parr,
R_H2O, molmassH2O)
xsm_H2O = xsmatrix(cnu_H2O, indexnu_H2O, R_H2O, pmarray_H2O,
nsigmaDl_H2O, ngammaLM_H2O, SijM_H2O, nus,
dgm_ngammaL_H2O)
dtaumH2O = dtauM(dParr, jnp.abs(xsm_H2O), MMR_H2O * ONEARR, molmassH2O,
g)
#CIA
dtaucH2H2=dtauCIA(nus,Tarr,Parr,dParr,vmrH2,vmrH2,\
mmw,g,cdbH2H2.nucia,cdbH2H2.tcia,cdbH2H2.logac)
dtaucH2He=dtauCIA(nus,Tarr,Parr,dParr,vmrH2,vmrHe,\
mmw,g,cdbH2He.nucia,cdbH2He.tcia,cdbH2He.logac)
dtau = dtaumCO + dtaumH2O + dtaucH2H2 + dtaucH2He
sourcef = planck.piBarr(Tarr, nus)
Ftoa = Fref / Rp**2
F0 = rtrun(dtau, sourcef) / baseline / Ftoa
Frot = response.rigidrot(nus, F0, vsini, u1, u2)
mu = response.ipgauss_sampling(nusdx, nus, Frot, beta, RV)
errall = jnp.sqrt(e1**2 + sigma**2)
numpyro.sample(tag, dist.Normal(mu, errall), obs=y)
def model_c(nu1, y1, e1):
Rp = sample('Rp', dist.Uniform(0.5, 1.5))
Mp = sample('Mp', dist.Normal(33.5, 0.3))
RV = sample('RV', dist.Uniform(26.0, 30.0))
MMR_CO = sample('MMR_CO', dist.Uniform(0.0, maxMMR_CO))
MMR_H2O = sample('MMR_H2O', dist.Uniform(0.0, maxMMR_H2O))
T0 = sample('T0', dist.Uniform(1000.0, 1700.0))
alpha = sample('alpha', dist.Uniform(0.05, 0.15))
vsini = sample('vsini', dist.Uniform(10.0, 20.0))
# Kipping Limb Darkening Prior
q1 = sample('q1', dist.Uniform(0.0, 1.0))
q2 = sample('q2', dist.Uniform(0.0, 1.0))
u1, u2 = ld_kipping(q1, q2)
#GP
logtau = sample('logtau', dist.Uniform(-1.5, 0.5)) #tau=1 <=> 5A
tau = 10**(logtau)
loga = sample('loga', dist.Uniform(-4.0, -2.0))
a = 10**(loga)
#gravity
g = getjov_gravity(Rp, Mp)
#T-P model//
Tarr = T0 * (Parr / Pref)**alpha
#CO
SijM_CO, gammaLM_CO, sigmaDM_CO = exomol(mdbCO, Tarr, Parr, molmassCO)
xsm_CO = xsmatrix(numatrix_CO, sigmaDM_CO, gammaLM_CO, SijM_CO)
dtaumCO = dtauM(dParr, xsm_CO, MMR_CO * ONEARR, molmassCO, g)
#H2O
SijM_H2O, gammaLM_H2O, sigmaDM_H2O = exomol(mdbH2O, Tarr, Parr, molmassH2O)
xsm_H2O = xsmatrix(numatrix_H2O, sigmaDM_H2O, gammaLM_H2O, SijM_H2O)
dtaumH2O = dtauM(dParr, xsm_H2O, MMR_H2O * ONEARR, molmassH2O, g)
#CIA
dtaucH2H2=dtauCIA(nus,Tarr,Parr,dParr,vmrH2,vmrH2,\
mmw,g,cdbH2H2.nucia,cdbH2H2.tcia,cdbH2H2.logac)
dtaucH2He=dtauCIA(nus,Tarr,Parr,dParr,vmrH2,vmrHe,\
mmw,g,cdbH2He.nucia,cdbH2He.tcia,cdbH2He.logac)
dtau = dtaumCO + dtaumH2O + dtaucH2H2 + dtaucH2He
sourcef = planck.piBarr(Tarr, nus)
Ftoa = Fref / Rp**2
F0 = rtrun(dtau, sourcef) / baseline / Ftoa
Frot = response.rigidrot(nus, F0, vsini, u1, u2)
mu = response.ipgauss_sampling(nu1, nus, Frot, beta, RV)
cov = gpkernel_RBF(nu1, tau, a, e1)
sample("y1",
dist.MultivariateNormal(loc=mu, covariance_matrix=cov),
obs=y1)
def obyo(y, tag, nusd, nus, numatrix_CO, numatrix_H2O, mdbCO, mdbH2O,
cdbH2H2, cdbH2He):
#CO
SijM_CO=jit(vmap(SijT,(0,None,None,None,0)))\
(Tarr,mdbCO.logsij0,mdbCO.dev_nu_lines,mdbCO.elower,qt_CO)
gammaLMP_CO = jit(vmap(gamma_hitran,(0,0,0,None,None,None)))\
(Parr*0.99,Tarr,Parr*0.01,mdbCO.n_air,mdbCO.gamma_air,mdbCO.gamma_self)
gammaLMN_CO = gamma_natural(mdbCO.A)
gammaLM_CO = gammaLMP_CO + gammaLMN_CO[None, :]
sigmaDM_CO=jit(vmap(doppler_sigma,(None,0,None)))\
(mdbCO.dev_nu_lines,Tarr,molmassCO)
xsm_CO = xsmatrix(numatrix_CO, sigmaDM_CO, gammaLM_CO, SijM_CO)
dtaumCO = dtauM(dParr, xsm_CO, MMR_CO * ONEARR, molmassCO, g)
#H2O
SijM_H2O=jit(vmap(SijT,(0,None,None,None,0)))\
(Tarr,mdbH2O.logsij0,mdbH2O.dev_nu_lines,mdbH2O.elower,qt_H2O)
gammaLMP_H2O = jit(vmap(gamma_exomol,(0,0,None,None)))\
(Parr,Tarr,mdbH2O.n_Texp,mdbH2O.alpha_ref)
gammaLMN_H2O = gamma_natural(mdbH2O.A)
gammaLM_H2O = gammaLMP_H2O + gammaLMN_H2O[None, :]
sigmaDM_H2O=jit(vmap(doppler_sigma,(None,0,None)))\
(mdbH2O.dev_nu_lines,Tarr,molmassH2O)
xsm_H2O = xsmatrix(numatrix_H2O, sigmaDM_H2O, gammaLM_H2O, SijM_H2O)
dtaumH2O = dtauM(dParr, xsm_H2O, MMR_H2O * ONEARR, molmassH2O, g)
#CIA
dtaucH2H2=dtauCIA(nus,Tarr,Parr,dParr,vmrH2,vmrH2,\
mmw,g,cdbH2H2.nucia,cdbH2H2.tcia,cdbH2H2.logac)
dtaucH2He=dtauCIA(nus,Tarr,Parr,dParr,vmrH2,vmrHe,\
mmw,g,cdbH2He.nucia,cdbH2He.tcia,cdbH2He.logac)
dtau = dtaumCO + dtaumH2O + dtaucH2H2 + dtaucH2He
sourcef = planck.piBarr(Tarr, nus)
Ftoa = Fref / (Rp**2)
F0 = rtrun(dtau, sourcef) / baseline / Ftoa
Frot = response.rigidrot(nus, F0, vsini, u1, u2)
mu = response.ipgauss_sampling(nusd, nus, Frot, beta, RV)
#errall=jnp.sqrt(e1**2+sigma**2)
errall = e1
cov = modelcov(nusd, tau, a, errall)
#cov = modelcov(nusd,tau,a,e1)
#numpyro.sample(tag, dist.Normal(mu, e1), obs=y)
numpyro.sample(tag,
dist.MultivariateNormal(loc=mu, covariance_matrix=cov),
obs=y)
def __init__(self,
nus,
gravity,
mmw,
Tarr,
Parr,
dParr=None,
databasedir='.database',
xsmode='auto',
autogridconv=True):
"""
Args:
nus: wavenumber bin (cm-1)
gravity: gravity (cm/s2)
mmw: mean molecular weight of the atmosphere
Tarr: temperature layer (K)
Parr: pressure layer (bar)
dParr: delta pressure (bar) optional
databasedir: directory for saving database
xsmode: xsmode for opacity computation (auto/LPF/DIT/MODIT)
autogridconv: automatic wavenumber grid conversion (True/False). If you are quite sure the wavenumber grid you use, set False.
"""
self.nus = nus
self.gravity = gravity
self.mmw = mmw
self.nlayer = len(Tarr)
self.Tarr = Tarr
self.Parr = Parr
self.xsmode = xsmode
self.autogridconv = autogridconv
if check_scale_nugrid(nus, gridmode='ESLOG'):
print('nu grid is evenly spaced in log space (ESLOG).')
elif check_scale_nugrid(nus, gridmode='ESLIN'):
print('nu grid is evenly spaced in linear space (ESLIN).')
else:
print('nu grid is NOT evenly spaced in log nor linear space.')
if dParr is None:
from exojax.utils.chopstacks import buildwall
wParr = buildwall(Parr)
self.dParr = wParr[1:] - wParr[0:-1]
else:
self.dParr = dParr
self.databasedir = databasedir
self.sourcef = planck.piBarr(self.Tarr, self.nus)
self.dtau = np.zeros((self.nlayer, len(nus)))
print('xsmode=', self.xsmode)
def frun(Tarr, MMR_CH4, Mp, Rp, u1, u2, RV, vsini):
g = 2478.57730044555 * Mp / Rp**2
SijM_CH4, ngammaLM_CH4, nsigmaDl_CH4 = modit.exomol(
mdbCH4, Tarr, Parr, R, molmassCH4)
xsm_CH4 = modit.xsmatrix(cnu, indexnu, R, pmarray, nsigmaDl_CH4,
ngammaLM_CH4, SijM_CH4, nus, dgm_ngammaL)
# abs is used to remove negative values in xsv
dtaumCH4 = dtauM(dParr, jnp.abs(xsm_CH4), MMR_CH4 * ONEARR, molmassCH4, g)
# CIA
dtaucH2H2 = dtauCIA(nus, Tarr, Parr, dParr, vmrH2, vmrH2, mmw, g,
cdbH2H2.nucia, cdbH2H2.tcia, cdbH2H2.logac)
dtau = dtaumCH4 + dtaucH2H2
sourcef = planck.piBarr(Tarr, nus)
F0 = rtrun(dtau, sourcef) / norm
Frot = response.rigidrot(nus, F0, vsini, u1, u2)
mu = response.ipgauss_sampling(nusd, nus, Frot, beta_inst, RV)
return mu
def obyo(y, tag, nusd, nus, numatrix_CO, numatrix_H2O, mdbCO, mdbH2O,
cdbH2H2, cdbH2He):
#CO
SijM_CO=jit(vmap(SijT,(0,None,None,None,0)))\
(Tarr,mdbCO.logsij0,mdbCO.dev_nu_lines,mdbCO.elower,qt_CO)
gammaLMP_CO = jit(vmap(gamma_exomol,(0,0,None,None)))\
(Parr,Tarr,mdbCO.n_Texp,mdbCO.alpha_ref)
gammaLMN_CO = gamma_natural(mdbCO.A)
gammaLM_CO = gammaLMP_CO + gammaLMN_CO[None, :]
sigmaDM_CO=jit(vmap(doppler_sigma,(None,0,None)))\
(mdbCO.dev_nu_lines,Tarr,molmassCO)
xsm_CO = xsmatrix(numatrix_CO, sigmaDM_CO, gammaLM_CO, SijM_CO)
dtaumCO = dtauM(dParr, xsm_CO, MMR_CO * ONEARR, molmassCO, g)
#H2O
SijM_H2O=jit(vmap(SijT,(0,None,None,None,0)))\
(Tarr,mdbH2O.logsij0,mdbH2O.dev_nu_lines,mdbH2O.elower,qt_H2O)
gammaLMP_H2O = jit(vmap(gamma_exomol,(0,0,None,None)))\
(Parr,Tarr,mdbH2O.n_Texp,mdbH2O.alpha_ref)
gammaLMN_H2O = gamma_natural(mdbH2O.A)
gammaLM_H2O = gammaLMP_H2O + gammaLMN_H2O[None, :]
sigmaDM_H2O=jit(vmap(doppler_sigma,(None,0,None)))\
(mdbH2O.dev_nu_lines,Tarr,molmassH2O)
xsm_H2O = xsmatrix(numatrix_H2O, sigmaDM_H2O, gammaLM_H2O, SijM_H2O)
dtaumH2O = dtauM(dParr, xsm_H2O, MMR_H2O * ONEARR, molmassH2O, g)
#CIA
dtaucH2H2=dtauCIA(nus,Tarr,Parr,dParr,vmrH2,vmrH2,\
mmw,g,cdbH2H2.nucia,cdbH2H2.tcia,cdbH2H2.logac)
dtaucH2He=dtauCIA(nus,Tarr,Parr,dParr,vmrH2,vmrHe,\
mmw,g,cdbH2He.nucia,cdbH2He.tcia,cdbH2He.logac)
dtau = dtaumCO + dtaumH2O + dtaucH2H2 + dtaucH2He
sourcef = planck.piBarr(Tarr, nus)
Ftoa = Fref / Rp**2
F0 = rtrun(dtau, sourcef) / baseline / Ftoa
Frot = response.rigidrot(nus, F0, vsini, u1, u2)
mu = response.ipgauss_sampling(nusd, nus, Frot, beta, RV)
np.savez("dtau_lpf.npz", [nus, dtaumCO, dtaumH2O])
return mu
def obyo(y, tag, nusdx, nus, mdbCO, mdbH2O, cdbH2H2, cdbH2He):
#CO
SijM_CO, ngammaLM_CO, nsigmaDl_CO = exomol(mdbCO, Tarr, Parr, R_CO,
molmassCO)
xsm_CO = xsmatrix(cnu_CO, indexnu_CO, R_CO, pmarray_CO, nsigmaDl_CO,
ngammaLM_CO, SijM_CO, nus, dgm_ngammaL_CO)
dtaumCO = dtauM(dParr, jnp.abs(xsm_CO), MMR_CO * ONEARR, molmassCO, g)
#H2O
SijM_H2O, ngammaLM_H2O, nsigmaDl_H2O = exomol(mdbH2O, Tarr, Parr,
R_H2O, molmassH2O)
xsm_H2O = xsmatrix(cnu_H2O, indexnu_H2O, R_H2O, pmarray_H2O,
nsigmaDl_H2O, ngammaLM_H2O, SijM_H2O, nus,
dgm_ngammaL_H2O)
dtaumH2O = dtauM(dParr, jnp.abs(xsm_H2O), MMR_H2O * ONEARR, molmassH2O,
g)
#CIA
dtaucH2H2=dtauCIA(nus,Tarr,Parr,dParr,vmrH2,vmrH2,\
mmw,g,cdbH2H2.nucia,cdbH2H2.tcia,cdbH2H2.logac)
dtaucH2He=dtauCIA(nus,Tarr,Parr,dParr,vmrH2,vmrHe,\
mmw,g,cdbH2He.nucia,cdbH2He.tcia,cdbH2He.logac)
dtau = dtaumCO + dtaumH2O + dtaucH2H2 + dtaucH2He
sourcef = planck.piBarr(Tarr, nus)
Ftoa = Fref / Rp**2
F0 = rtrun(dtau, sourcef) / baseline / Ftoa
Frot = response.rigidrot(nus, F0, vsini, u1, u2)
mu = response.ipgauss_sampling(nusdx, nus, Frot, beta, RV)
if FP64 == True:
np.savez("dtau_modit" + str(N) + "_64.npz",
[nus, dtaumCO, dtaumH2O])
else:
np.savez("dtau_modit" + str(N) + ".npz", [nus, dtaumCO, dtaumH2O])
return mu
def frun(Tarr, MMR_H2O, MMR_CO, Mp, Rp, u1, u2, RV, vsini):
g = 2478.57730044555 * Mp / Rp**2
SijM_H2O, ngammaLM_H2O, nsigmaDl_H2O = modit.exomol(
mdbH2O, Tarr, Parr, R, molmassH2O)
xsm_H2O = modit.xsmatrix(cnu_H2O, indexnu_H2O, R_H2O, pmarray_H2O,
nsigmaDl_H2O, ngammaLM_H2O, SijM_H2O, nus,
dgm_ngammaL_H2O)
dtaumH2O = dtauM(dParr, jnp.abs(xsm_H2O), MMR_H2O * ONEARR, molmassH2O, g)
SijM_CO, ngammaLM_CO, nsigmaDl_CO = modit.exomol(mdbCO, Tarr, Parr, R,
molmassCO)
xsm_CO = modit.xsmatrix(cnu_CO, indexnu_CO, R_CO, pmarray_CO, nsigmaDl_CO,
ngammaLM_CO, SijM_CO, nus, dgm_ngammaL_CO)
dtaumCO = dtauM(dParr, jnp.abs(xsm_CO), MMR_CO * ONEARR, molmassCO, g)
# CIA
dtaucH2H2 = dtauCIA(nus, Tarr, Parr, dParr, vmrH2, vmrH2, mmw, g,
cdbH2H2.nucia, cdbH2H2.tcia, cdbH2H2.logac)
dtau = dtaumH2O + dtaumCO + dtaucH2H2
sourcef = planck.piBarr(Tarr, nus)
F0 = rtrun(dtau, sourcef) / norm
Frot = response.rigidrot(nus, F0, vsini, u1, u2)
mu = response.ipgauss_sampling(nusd, nus, Frot, beta_inst, RV)
return mu
q = mdbM.qr_interp(1500.0)
S = SijT(1500.0, mdbM.logsij0, mdbM.nu_lines, mdbM.elower, q)
mask = S > 1.e-25
mdbM.masking(mask)
Tarr = jnp.logspace(jnp.log10(800), jnp.log10(1600), 100)
qt = vmap(mdbM.qr_interp)(Tarr)
SijM = jit(vmap(SijT,
(0, None, None, None, 0)))(Tarr, mdbM.logsij0, mdbM.nu_lines,
mdbM.elower, qt)
imax = jnp.argmax(SijM, axis=0)
Tmax = Tarr[imax]
print(jnp.min(Tmax))
pl = planck.piBarr(jnp.array([1100.0, 1000.0]), nus)
print(pl[1] / pl[0])
pl = planck.piBarr(jnp.array([1400.0, 1200.0]), nus)
print(pl[1] / pl[0])
lsa = ['solid', 'dashed', 'dotted', 'dashdot']
lab = ['A', 'B', 'C']
fac = 1.e22
fig = plt.figure(figsize=(12, 6))
# for j,i in enumerate(range(len(mdbM.A))):
# for j,i in enumerate([56,72,141,147,173,236,259,211,290]):
for j, i in enumerate([259, 236, 56]):
print(1.e8 / mdbM.nu_lines[i])
w = lab[j] + ': ' + str(int(1.e8 / mdbM.nu_lines[i])) + '$\\AA$'
plt.plot(Tarr,
def test_VALD_MODIT():
#wavelength range
wls, wll = 10395, 10405
#Set a model atmospheric layers, wavenumber range for the model, an instrument
NP = 100
Parr, dParr, k = pressure_layer(NP=NP)
Pref = 1.0 #bar
ONEARR = np.ones_like(Parr)
Nx = 2000
nus, wav, res = nugrid(wls - 5.0, wll + 5.0, Nx, unit="AA", xsmode="modit")
Rinst = 100000. #instrumental spectral resolution
beta_inst = R2STD(
Rinst) #equivalent to beta=c/(2.0*np.sqrt(2.0*np.log(2.0))*R)
#atoms and ions from VALD
adbV = moldb.AdbVald(
path_ValdLineList, nus, crit=1e-100
) #The crit is defined just in case some weak lines may cause an error that results in a gamma of 0... (220219)
asdb = moldb.AdbSepVald(adbV)
#molecules from exomol
mdbH2O = moldb.MdbExomol('.database/H2O/1H2-16O/POKAZATEL',
nus,
crit=1e-50) #,crit = 1e-40)
mdbTiO = moldb.MdbExomol('.database/TiO/48Ti-16O/Toto', nus,
crit=1e-50) #,crit = 1e-50)
mdbOH = moldb.MdbExomol('.database/OH/16O-1H/MoLLIST', nus)
mdbFeH = moldb.MdbExomol('.database/FeH/56Fe-1H/MoLLIST', nus)
#CIA
cdbH2H2 = contdb.CdbCIA('.database/H2-H2_2011.cia', nus)
#molecular mass
molmassH2O = molinfo.molmass("H2O")
molmassTiO = molinfo.molmass("TiO")
molmassOH = molinfo.molmass("OH")
molmassFeH = molinfo.molmass("FeH")
molmassH = molinfo.molmass("H")
molmassH2 = molinfo.molmass("H2")
#Initialization of MODIT (for separate VALD species, and exomol molecules(e.g., FeH))
cnuS, indexnuS, R, pmarray = initspec.init_modit_vald(
asdb.nu_lines, nus, asdb.N_usp)
cnu_FeH, indexnu_FeH, R, pmarray = initspec.init_modit(
mdbFeH.nu_lines, nus)
cnu_H2O, indexnu_H2O, R, pmarray = initspec.init_modit(
mdbH2O.nu_lines, nus)
cnu_OH, indexnu_OH, R, pmarray = initspec.init_modit(mdbOH.nu_lines, nus)
cnu_TiO, indexnu_TiO, R, pmarray = initspec.init_modit(
mdbTiO.nu_lines, nus)
#sampling the max/min of temperature profiles
fT = lambda T0, alpha: T0[:, None] * (Parr[None, :] / Pref)**alpha[:, None]
T0_test = np.array([1500.0, 4000.0, 1500.0, 4000.0])
alpha_test = np.array([0.2, 0.2, 0.05, 0.05])
res = 0.2
#Assume typical atmosphere
H_He_HH_VMR_ref = [0.1, 0.15, 0.75]
PH_ref = Parr * H_He_HH_VMR_ref[0]
PHe_ref = Parr * H_He_HH_VMR_ref[1]
PHH_ref = Parr * H_He_HH_VMR_ref[2]
#Precomputing dgm_ngammaL
dgm_ngammaL_VALD = setdgm_vald_all(asdb, PH_ref, PHe_ref, PHH_ref, R, fT,
res, T0_test, alpha_test)
dgm_ngammaL_FeH = setdgm_exomol(mdbFeH, fT, Parr, R, molmassFeH, res,
T0_test, alpha_test)
dgm_ngammaL_H2O = setdgm_exomol(mdbH2O, fT, Parr, R, molmassH2O, res,
T0_test, alpha_test)
dgm_ngammaL_OH = setdgm_exomol(mdbOH, fT, Parr, R, molmassOH, res, T0_test,
alpha_test)
dgm_ngammaL_TiO = setdgm_exomol(mdbTiO, fT, Parr, R, molmassTiO, res,
T0_test, alpha_test)
T0 = 3000.
alpha = 0.07
Mp = 0.155 * 1.99e33 / 1.90e30
Rp = 0.186 * 6.96e10 / 6.99e9
u1 = 0.0
u2 = 0.0
RV = 0.00
vsini = 2.0
mmw = 2.33 * ONEARR #mean molecular weight
log_e_H = -4.2
VMR_H = 0.09
VMR_H2 = 0.77
VMR_FeH = 10**-8
VMR_H2O = 10**-4
VMR_OH = 10**-4
VMR_TiO = 10**-8
A_Fe = 1.5
A_Ti = 1.2
adjust_continuum = 0.99
ga = 2478.57730044555 * Mp / Rp**2
Tarr = T0 * (Parr / Pref)**alpha
PH = Parr * VMR_H
PHe = Parr * (1 - VMR_H - VMR_H2)
PHH = Parr * VMR_H2
VMR_e = VMR_H * 10**log_e_H
#VMR of atoms and ions (+Abundance modification)
mods_ID = jnp.array([[26, 1], [22, 1]])
mods = jnp.array([A_Fe, A_Ti])
VMR_uspecies = atomll.get_VMR_uspecies(asdb.uspecies, mods_ID, mods)
VMR_uspecies = VMR_uspecies[:, None] * ONEARR
#Compute delta tau
#Atom & ions (VALD)
SijMS, ngammaLMS, nsigmaDlS = vald_all(asdb, Tarr, PH, PHe, PHH, R)
xsmS = xsmatrix_vald(cnuS, indexnuS, R, pmarray, nsigmaDlS, ngammaLMS,
SijMS, nus, dgm_ngammaL_VALD)
dtauatom = dtauVALD(dParr, xsmS, VMR_uspecies, mmw, ga)
#FeH
SijM_FeH, ngammaLM_FeH, nsigmaDl_FeH = exomol(mdbFeH, Tarr, Parr, R,
molmassFeH)
xsm_FeH = xsmatrix(cnu_FeH, indexnu_FeH, R, pmarray, nsigmaDl_FeH,
ngammaLM_FeH, SijM_FeH, nus, dgm_ngammaL_FeH)
dtaum_FeH = dtauM_mmwl(dParr, jnp.abs(xsm_FeH), VMR_FeH * ONEARR, mmw, ga)
#H2O
SijM_H2O, ngammaLM_H2O, nsigmaDl_H2O = exomol(mdbH2O, Tarr, Parr, R,
molmassH2O)
xsm_H2O = xsmatrix(cnu_H2O, indexnu_H2O, R, pmarray, nsigmaDl_H2O,
ngammaLM_H2O, SijM_H2O, nus, dgm_ngammaL_H2O)
dtaum_H2O = dtauM_mmwl(dParr, jnp.abs(xsm_H2O), VMR_H2O * ONEARR, mmw, ga)
#OH
SijM_OH, ngammaLM_OH, nsigmaDl_OH = exomol(mdbOH, Tarr, Parr, R, molmassOH)
xsm_OH = xsmatrix(cnu_OH, indexnu_OH, R, pmarray, nsigmaDl_OH, ngammaLM_OH,
SijM_OH, nus, dgm_ngammaL_OH)
dtaum_OH = dtauM_mmwl(dParr, jnp.abs(xsm_OH), VMR_OH * ONEARR, mmw, ga)
#TiO
SijM_TiO, ngammaLM_TiO, nsigmaDl_TiO = exomol(mdbTiO, Tarr, Parr, R,
molmassTiO)
xsm_TiO = xsmatrix(cnu_TiO, indexnu_TiO, R, pmarray, nsigmaDl_TiO,
ngammaLM_TiO, SijM_TiO, nus, dgm_ngammaL_TiO)
dtaum_TiO = dtauM_mmwl(dParr, jnp.abs(xsm_TiO), VMR_TiO * ONEARR, mmw, ga)
#Hminus
dtau_Hm = dtauHminus_mmwl(nus, Tarr, Parr, dParr, VMR_e * ONEARR,
VMR_H * ONEARR, mmw, ga)
#CIA
dtauc_H2H2 = dtauCIA_mmwl(nus, Tarr, Parr, dParr, VMR_H2 * ONEARR,
VMR_H2 * ONEARR, mmw, ga, cdbH2H2.nucia,
cdbH2H2.tcia, cdbH2H2.logac)
#Summations
dtau = dtauatom + dtaum_FeH + dtaum_H2O + dtaum_OH + dtaum_TiO + dtau_Hm + dtauc_H2H2
sourcef = planck.piBarr(Tarr, nus)
F0 = rtrun(dtau, sourcef)
Frot = response.rigidrot(nus, F0, vsini, u1, u2)
wavd = jnp.linspace(wls, wll, 500)
nusd = jnp.array(1.e8 / wavd[::-1])
mu = response.ipgauss_sampling(nusd, nus, Frot, beta_inst, RV)
mu = mu / jnp.nanmax(mu) * adjust_continuum
assert (np.all(~np.isnan(mu)) * \
np.all(mu != 0) * \
np.all(abs(mu) != np.inf))
mmrH2 = 0.74
molmassH2 = molinfo.molmass('H2')
vmrH2 = (mmrH2 * mmw / molmassH2) # VMR
dtaucH2H2 = dtauCIA(nus, Tarr, Parr, dParr, vmrH2, vmrH2, mmw, g,
cdbH2H2.nucia, cdbH2H2.tcia, cdbH2H2.logac)
dtau = dtaum + dtaucH2H2
plotcf(nus, dtau, Tarr, Parr, dParr)
plt.show()
# radiative transfering...
# In[26]:
sourcef = planck.piBarr(Tarr, nus)
F0 = rtrun(dtau, sourcef)
wavd = jnp.linspace(15910, 16290, 1500) # observational wavelength grid
nusd = 1.e8 / wavd[::-1]
RV = 10.0 # RV km/s
vsini = 20.0 # Vsini km/s
u1 = 0.0 # limb darkening u1
u2 = 0.0 # limb darkening u2
Rinst = 100000.
beta = c / (2.0 * np.sqrt(2.0 * np.log(2.0)) * Rinst) # IP sigma need check
Frot = response.rigidrot(nus, F0, vsini, u1, u2)
F = response.ipgauss_sampling(nusd, nus, Frot, beta, RV)
